jablonkagroup/chempile-code · Datasets at Hugging Face

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# -- coding: utf-8 -- """ Module gifted Provides functionality for reading and writing animated GIF images. Use write_gif to write a series of numpy arrays or PIL images as an animated GIF. Use read_gif to read an animated gif as a series of numpy arrays. Note that since July 2004, all patents on the LZW compression patent have expired. Therefore the GIF format may now be used freely. Acknowledgements ---------------- Many thanks to Ant1 for: * noting the use of "palette=PIL.Image.ADAPTIVE", which significantly improves the results. * the modifications to save each image with its own palette, or optionally the global palette (if its the same). Many thanks to Marius van Voorden for porting the NeuQuant quantization algorithm of Anthony Dekker to Python (See the NeuQuant class for its license). Many thanks to Alex Robinson for implementing the concept of subrectangles, which (depening on image content) can give a very significant reduction in file size. This code is based on gifmaker (in the scripts folder of the source distribution of PIL) Usefull links ------------- * http://tronche.com/computer-graphics/gif/ * http://en.wikipedia.org/wiki/Graphics_Interchange_Format * http://www.w3.org/Graphics/GIF/spec-gif89a.txt """ import os from fnmatch import fnmatch try: import PIL from PIL import Image from PIL.GifImagePlugin import getheader, getdata except ImportError: PIL = None try: import numpy as np except ImportError: np = None def get_cKDTree(): try: from scipy.spatial import cKDTree except ImportError: cKDTree = None return cKDTree # getheader gives a 87a header and a color palette (two elements in a list). # getdata()[0] gives the Image Descriptor up to (including) "LZW min code size". # getdatas()[1:] is the image data itself in chuncks of 256 bytes (well # technically the first byte says how many bytes follow, after which that # amount (max 255) follows). def check_images(images): """ check_images(images) Check numpy images and correct intensity range etc. The same for all movie formats. """ # Init results images2 = [] for img in images: if PIL and isinstance(img, PIL.Image.Image): # We assume PIL images are allright images2.append(img) elif np and isinstance(img, np.ndarray): # Check and convert dtype if img.dtype == np.uint8: images2.append(img) # Ok elif img.dtype in [np.float32, np.float64]: img = img.copy() img[img < 0] = 0 img[img > 1] = 1 img = 255 images2.append(img.astype(np.uint8)) else: img = img.astype(np.uint8) images2.append(img) # Check size if img.ndim == 2: pass # ok elif img.ndim == 3: if img.shape[2] not in [3, 4]: raise ValueError('This array can not represent an image.') else: raise ValueError('This array can not represent an image.') else: raise ValueError('Invalid image type: ' + str(type(img))) # Done return images2 def int_to_bin(i): """ Integer to two bytes """ # make string (little endian) return i.to_bytes(2, byteorder='little') class GifWriter(object): """ GifWriter() Class that contains methods for helping write the animated GIF file. """ def __init__(self): self.transparency = None @staticmethod def get_header_anim(img): """ get_header_anim(img) Get animation header. To replace PILs getheader()[0] """ header = b'GIF89a' header += int_to_bin(img.size[0]) header += int_to_bin(img.size[1]) header += b'\x87\x00\x00' return header @staticmethod def get_image_descriptor(img, coords=None): """ get_image_descriptor(img, coords=None) Used for the local color table properties per image. Otherwise global color table applies to all frames irrespective of whether additional colors comes in play that require a redefined palette. Still a maximum of 256 color per frame, obviously. Written by Ant1 on 2010-08-22 Modified by Alex Robinson in Janurari 2011 to implement subrectangles. """ # Defaule use full image and place at upper left if coords is None: coords = (0, 0) # Image separator descriptor = b'\x2C' # Image position and size descriptor += int_to_bin(coords[0]) # Left position descriptor += int_to_bin(coords[1]) # Top position descriptor += int_to_bin(img.size[0]) # image width descriptor += int_to_bin(img.size[1]) # image height # packed field: local color table flag1, interlace0, sorted table0, # reserved00, lct size111=7=2^(7+1)=256. descriptor += b'\x87' # LZW minimum size code now comes later, begining of [image data] blocks return descriptor @staticmethod def get_app_ext(loops=float('inf')): """ get_app_ext(loops=float('inf')) Application extention. This part specifies the amount of loops. If loops is 0 or inf, it goes on infinitely. """ if loops == 0 or loops == float('inf'): loops = 216-1 # bb = "" # application extension should not be used # # (the extension interprets zero loops # # to mean an infinite number of loops) # # Mmm, does not seem to work ext = b"\x21\xFF\x0B" # application extension ext += b"NETSCAPE2.0" ext += b"\x03\x01" ext += int_to_bin(loops) ext += b'\x00' # end return ext @staticmethod def get_graphics_control_ext( duration=0.1, dispose=2, transparent_flag=0, transparency_index=0): """ get_graphics_control_ext(duration=0.1, dispose=2) Graphics Control Extension. A sort of header at the start of each image. Specifies duration and transparancy. Dispose ------- 0 - No disposal specified. * 1 - Do not dispose. The graphic is to be left in place. * 2 - Restore to background color. The area used by the graphic must be restored to the background color. * 3 - Restore to previous. The decoder is required to restore the area overwritten by the graphic with what was there prior to rendering the graphic. * 4-7 -To be defined. """ ext = b'\x21\xF9\x04' ext += bytes([((dispose & 3) << 2) \| (transparent_flag & 1)]) # low bit 1 == transparency, # 2nd bit 1 == user input , next 3 bits, the low two of which are used, # are dispose. ext += int_to_bin(int(duration * 100)) # in 100th of seconds ext += bytes([transparency_index]) ext += b'\x00' # end return ext def handle_sub_rectangles(self, images, sub_rectangles): """ handle_sub_rectangles(images) Handle the sub-rectangle stuff. If the rectangles are given by the user, the values are checked. Otherwise the subrectangles are calculated automatically. """ if isinstance(sub_rectangles, (tuple, list)): # xy given directly # Check xy sub_recs = sub_rectangles if sub_recs is None: sub_recs = (0, 0) if hasattr(sub_recs, '__len__'): if len(sub_recs) == len(images): sub_recs = [xxyy for xxyy in sub_recs] else: raise ValueError("len(sub_recs) doesn't match amount of images.") else: sub_recs = [sub_recs for image in images] sub_recs[0] = (0, 0) else: # Calculate xy using some basic image processing # Check Numpy if np is None: raise RuntimeError("Need Numpy to use auto-sub_rectangles.") # First make numpy arrays if required for i in range(len(images)): image = images[i] if isinstance(image, Image.Image): tmp = image.convert() # Make without palette array_ = np.asarray(tmp) if len(array_.shape) == 0: raise MemoryError("Too little memory to convert PIL image to array") images[i] = array_ # Determine the sub rectangles images, sub_rec = self.get_sub_rectangles(images) # Done return images, sub_rec @staticmethod def get_sub_rectangles(images): """ get_sub_rectangles(images) Calculate the minimal rectangles that need updating each frame. Returns a two-element tuple containing the cropped images and a list of x-y positions. Calculating the subrectangles takes extra time, obviously. However, if the image sizes were reduced, the actual writing of the GIF goes faster. In some cases applying this method produces a GIF faster. """ # Check image count if len(images) < 2: return images, [(0, 0) for i in images] # We need numpy if np is None: raise RuntimeError("Need Numpy to calculate sub-rectangles. ") # Prepare ims2 = [images[0]] coords = [(0, 0)] # Iterate over images prev = images[0] for image in images[1:]: # Get difference, sum over colors diff = np.abs(image - prev) if diff.ndim == 3: diff = diff.sum(2) # Get begin and end for both dimensions X = np.argwhere(diff.sum(0)) Y = np.argwhere(diff.sum(1)) # Get rect coordinates if X.size and Y.size: x0, x1 = int(X[0][0]), int(X[-1][0]+1) y0, y1 = int(Y[0][0]), int(Y[-1][0]+1) else: # No change ... make it minimal x0, x1 = 0, 2 y0, y1 = 0, 2 # Cut out and store im2 = image[y0:y1, x0:x1] prev = image ims2.append(im2) coords.append((x0, y0)) return ims2, coords def convert_images_to_PIL(self, images, dither, nq=0): """ convert_images_to_PIL(images, nq=0) Convert images to Paletted PIL images, which can then be written to a single animaged GIF. """ # Convert to PIL images images2 = [] for image in images: if isinstance(image, Image.Image): images2.append(image) elif np and isinstance(image, np.ndarray): if image.ndim == 3 and image.shape[2] == 3: image = Image.fromarray(image, 'RGB') elif image.ndim == 3 and image.shape[2] == 4: # image = Image.fromarray(image[:,:,:3],'RGB') self.transparency = True image = Image.fromarray(image[:, :, :4], 'RGBA') elif image.ndim == 2: image = Image.fromarray(image, 'L') images2.append(image) # Convert to paletted PIL images images, images2 = images2, [] if nq >= 1: # NeuQuant algorithm for image in images: image = image.convert("RGBA") # NQ assumes RGBA # Learn colors from image nq_instance = NeuQuant(image, int(nq)) if dither: image = image.convert("RGB").quantize( palette=nq_instance.paletteImage(), colors=255) else: # Use to quantize the image itself image = nq_instance.quantize(image, colors=255) # since NQ assumes transparency self.transparency = True if self.transparency: alpha = image.split()[3] mask = Image.eval(alpha, lambda a: 255 if a <= 128 else 0) image.paste(255, mask=mask) images2.append(image) else: # for index,image in enumerate(images): for i in range(len(images)): image = images[i].convert('RGB').convert( 'P', palette=Image.ADAPTIVE, # Adaptive PIL algorithm dither=dither, colors=255 ) if self.transparency: alpha = images[i].split()[3] mask = Image.eval(alpha, lambda a: 255 if a <= 128 else 0) image.paste(255, mask=mask) images2.append(image) # Done return images2 def write_gif_to_file(self, file_, images, durations, loops, xys, disposes): """ write_gif_to_file(file_, images, durations, loops, xys, disposes) Given a set of images writes the bytes to the specified stream. """ # Obtain palette for all images and count each occurance palettes, occur = [], [] for image in images: palettes.append(getheader(image)[0][3]) for palette in palettes: occur.append(palettes.count(palette)) # Select most-used palette as the global one (or first in case no max) global_palette = palettes[occur.index(max(occur))] # Init frames = 0 first_frame = True for image, palette in zip(images, palettes): if first_frame: # Write header # Gather info header = self.get_header_anim(image) appext = self.get_app_ext(loops) # Write file_.write(header) file_.write(global_palette) file_.write(appext) # Next frame is not the first first_frame = False if True: # Write palette and image data # Gather info data = getdata(image) imdes, data = data[0], data[1:] transparent_flag = 1 if self.transparency else 0 graphext = self.get_graphics_control_ext( durations[frames], disposes[frames], transparent_flag=transparent_flag, transparency_index=255 ) # Make image descriptor suitable for using 256 local color palette lid = self.get_image_descriptor(image, xys[frames]) # Write local header if (palette != global_palette) or (disposes[frames] != 2): # Use local color palette file_.write(graphext) file_.write(lid) # write suitable image descriptor file_.write(palette) # write local color table file_.write(b'\x08') # LZW minimum size code else: # Use global color palette file_.write(graphext) file_.write(imdes) # write suitable image descriptor # Write image data for datum in data: file_.write(datum) # Prepare for next round frames = frames + 1 file_.write(b';') # end gif return frames # Exposed functions def write_gif(filename, images, duration=0.1, repeat=True, dither=False, nq=0, sub_rectangles=True, dispose=None): """ write_gif(filename, images, duration=0.1, repeat=True, dither=False, nq=0, sub_rectangles=True, dispose=None) Write an animated gif from the specified images. Parameters ---------- filename : string The name of the file to write the image to. images : list Should be a list consisting of PIL images or numpy arrays. The latter should be between 0 and 255 for integer types, and between 0 and 1 for float types. duration : scalar or list of scalars The duration for all frames, or (if a list) for each frame. repeat : bool or integer The amount of loops. If True, loops infinitetely. dither : bool Whether to apply dithering nq : integer If nonzero, applies the NeuQuant quantization algorithm to create the color palette. This algorithm is superior, but slower than the standard PIL algorithm. The value of nq is the quality parameter. 1 represents the best quality. 10 is in general a good tradeoff between quality and speed. When using this option, better results are usually obtained when sub_rectangles is False. sub_rectangles : False, True, or a list of 2-element tuples Whether to use sub-rectangles. If True, the minimal rectangle that is required to update each frame is automatically detected. This can give significant reductions in file size, particularly if only a part of the image changes. One can also give a list of x-y coordinates if you want to do the cropping yourself. The default is True. dispose : int How to dispose each frame. 1 means that each frame is to be left in place. 2 means the background color should be restored after each frame. 3 means the decoder should restore the previous frame. If sub_rectangles==False, the default is 2, otherwise it is 1. """ # Check PIL if PIL is None: raise RuntimeError("Need PIL to write animated gif files.") # Check images images = check_images(images) # Instantiate writer object gif_writer = GifWriter() gif_writer.transparency = False # init transparency flag used in GifWriter functions # Check loops if repeat is False: loops = 1 elif repeat is True: loops = 0 # zero means infinite else: loops = int(repeat) # Check duration if hasattr(duration, '__len__'): if len(duration) == len(images): duration = [d for d in duration] else: raise ValueError("len(duration) doesn't match amount of images.") else: duration = [duration for im in images] # Check subrectangles if sub_rectangles: images, xy = gif_writer.handle_sub_rectangles(images, sub_rectangles) default_dispose = 1 # Leave image in place else: # Normal mode xy = [(0, 0) for im in images] default_dispose = 2 # Restore to background color. # Check dispose if dispose is None: dispose = default_dispose if hasattr(dispose, '__len__'): if len(dispose) != len(images): raise ValueError("len(xy) doesn't match amount of images.") else: dispose = [dispose for im in images] # Make images in a format that we can write easy images = gif_writer.convert_images_to_PIL(images, dither, nq) # Write with open(filename, 'wb') as file_: gif_writer.write_gif_to_file(file_, images, duration, loops, xy, dispose) def read_gif(filename, as_numpy=True): """ read_gif(filename, as_numpy=True) Read images from an animated GIF file. Returns a list of numpy arrays, or, if as_numpy is false, a list if PIL images. """ # Check PIL if PIL is None: raise RuntimeError("Need PIL to read animated gif files.") # Check Numpy if np is None: raise RuntimeError("Need Numpy to read animated gif files.") # Check whether it exists if not os.path.isfile(filename): raise IOError('File not found: '+str(filename)) # Load file using PIL pil_image = PIL.Image.open(filename) pil_image.seek(0) # Read all images inside images = [] try: while True: # Get image as numpy array tmp = pil_image.convert() # Make without palette array_ = np.asarray(tmp) if len(array_.shape) == 0: raise MemoryError("Too little memory to convert PIL image to array") # Store, and next images.append(array_) pil_image.seek(pil_image.tell()+1) except EOFError: pass # Convert to normal PIL images if needed if not as_numpy: images2 = images images = [] for image in images2: tmp = PIL.Image.fromarray(image) images.append(tmp) # Done return images class NeuQuant: """ NeuQuant(image, samplefac=10, colors=256) samplefac should be an integer number of 1 or higher, 1 being the highest quality, but the slowest performance. With avalue of 10, one tenth of all pixels are used during training. This value seems a nice tradeof between speed and quality. colors is the amount of colors to reduce the image to. This should best be a power of two. See also: http://members.ozemail.com.au/~dekker/NEUQUANT.HTML License of the NeuQuant Neural-Net Quantization Algorithm --------------------------------------------------------- Copyright (c) 1994 Anthony Dekker Ported to python by Marius van Voorden in 2010 NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994. See "Kohonen neural networks for optimal colour quantization" in "network: Computation in Neural Systems" Vol. 5 (1994) pp 351-367. for a discussion of the algorithm. See also http://members.ozemail.com.au/~dekker/NEUQUANT.HTML Any party obtaining a copy of these files from the author, directly or indirectly, is granted, free of charge, a full and unrestricted irrevocable, world-wide, paid up, royalty-free, nonexclusive right and license to deal in this software and documentation files (the "Software"), including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons who receive copies from any such party to do so, with the only requirement being that this copyright notice remain intact. """ NCYCLES = None # Number of learning cycles NETSIZE = None # Number of colours used SPECIALS = None # Number of reserved colours used BGCOLOR = None # Reserved background colour CUTNETSIZE = None MAXNETPOS = None INITRAD = None # For 256 colours, radius starts at 32 RADIUSBIASSHIFT = None RADIUSBIAS = None INITBIASRADIUS = None RADIUSDEC = None # Factor of 1/30 each cycle ALPHABIASSHIFT = None INITALPHA = None # biased by 10 bits GAMMA = None BETA = None BETAGAMMA = None network = None # The network itself colormap = None # The network itself netindex = None # For network lookup - really 256 bias = None # Bias and freq arrays for learning freq = None pimage = None # Four primes near 500 - assume no image has a length so large # that it is divisible by all four primes PRIME1 = 499 PRIME2 = 491 PRIME3 = 487 PRIME4 = 503 MAXPRIME = PRIME4 pixels = None samplefac = None a_s = None def __init__(self, image, samplefac=10, colors=256): # Check Numpy if np is None: raise RuntimeError("Need Numpy for the NeuQuant algorithm.") # Check image if image.size[0] * image.size[1] < NeuQuant.MAXPRIME: raise IOError("Image is too small") if image.mode != "RGBA": raise IOError("Image mode should be RGBA.") # Initialize self.setconstants(samplefac, colors) self.pixels = np.fromstring(image.tostring(), np.uint32) self.set_up_arrays() self.learn() self.fix() self.inxbuild() def setconstants(self, samplefac, colors): """ Sets class constants """ self.NCYCLES = 100 # Number of learning cycles self.NETSIZE = colors # Number of colours used self.SPECIALS = 3 # Number of reserved colours used self.BGCOLOR = self.SPECIALS-1 # Reserved background colour self.CUTNETSIZE = self.NETSIZE - self.SPECIALS self.MAXNETPOS = self.NETSIZE - 1 self.INITRAD = self.NETSIZE/8 # For 256 colours, radius starts at 32 self.RADIUSBIASSHIFT = 6 self.RADIUSBIAS = 1 << self.RADIUSBIASSHIFT self.INITBIASRADIUS = self.INITRAD * self.RADIUSBIAS self.RADIUSDEC = 30 # Factor of 1/30 each cycle self.ALPHABIASSHIFT = 10 # Alpha starts at 1 self.INITALPHA = 1 << self.ALPHABIASSHIFT # biased by 10 bits self.GAMMA = 1024.0 self.BETA = 1.0/1024.0 self.BETAGAMMA = self.BETA * self.GAMMA self.network = np.empty((self.NETSIZE, 3), dtype='float64') # The network itself self.colormap = np.empty((self.NETSIZE, 4), dtype='int32') # The network itself self.netindex = np.empty(256, dtype='int32') # For network lookup - really 256 self.bias = np.empty(self.NETSIZE, dtype='float64') # Bias and freq arrays for learning self.freq = np.empty(self.NETSIZE, dtype='float64') self.pixels = None self.samplefac = samplefac self.a_s = dict() def write_colour_map(self, rgb, outstream): """ """ for i in range(self.NETSIZE): blue = self.colormap[i, 0] green = self.colormap[i, 1] red = self.colormap[i, 2] outstream.write(red if rgb else blue) outstream.write(green) outstream.write(blue if rgb else red) return self.NETSIZE def set_up_arrays(self): """ """ self.network[0, 0] = 0.0 # Black self.network[0, 1] = 0.0 self.network[0, 2] = 0.0 self.network[1, 0] = 255.0 # White self.network[1, 1] = 255.0 self.network[1, 2] = 255.0 # RESERVED self.BGCOLOR # Background for i in range(self.SPECIALS): self.freq[i] = 1.0 / self.NETSIZE self.bias[i] = 0.0 for i in range(self.SPECIALS, self.NETSIZE): p = self.network[i] p[:] = (255.0 * (i-self.SPECIALS)) / self.CUTNETSIZE self.freq[i] = 1.0 / self.NETSIZE self.bias[i] = 0.0 # Omitted: setPixels def altersingle(self, alpha, i, b, g, r): """Move neuron i towards biased (b,g,r) by factor alpha""" n = self.network[i] # Alter hit neuron n[0] -= (alpha(n[0] - b)) n[1] -= (alpha(n[1] - g)) n[2] -= (alpha(n[2] - r)) def geta(self, alpha, rad): try: return self.a_s[(alpha, rad)] except KeyError: length = rad2-1 mid = length/2 q = np.array(list(range(mid-1, -1, -1))+list(range(-1, mid))) a = alpha(radrad - qq)/(radrad) a[mid] = 0 self.a_s[(alpha, rad)] = a return a def alterneigh(self, alpha, rad, i, b, g, r): if i-rad >= self.SPECIALS-1: lo = i-rad start = 0 else: lo = self.SPECIALS-1 start = (self.SPECIALS-1 - (i-rad)) if i+rad <= self.NETSIZE: hi = i+rad end = rad2-1 else: hi = self.NETSIZE end = (self.NETSIZE - (i+rad)) a = self.geta(alpha, rad)[start:end] p = self.network[lo+1:hi] p -= np.transpose(np.transpose(p - np.array([b, g, r])) a) def contest(self, b, g, r): """ Search for biased BGR values Finds closest neuron (min dist) and updates self.freq finds best neuron (min dist-self.bias) and returns position for frequently chosen neurons, self.freq[i] is high and self.bias[i] is negative self.bias[i] = self.GAMMA((1/self.NETSIZE)-self.freq[i])""" i, j = self.SPECIALS, self.NETSIZE dists = abs(self.network[i:j] - np.array([b, g, r])).sum(1) bestpos = i + np.argmin(dists) biasdists = dists - self.bias[i:j] bestbiaspos = i + np.argmin(biasdists) self.freq[i:j] = (1-self.BETA) self.bias[i:j] += self.BETAGAMMA * self.freq[i:j] self.freq[bestpos] += self.BETA self.bias[bestpos] -= self.BETAGAMMA return bestbiaspos def special_find(self, b, g, r): for i in range(self.SPECIALS): n = self.network[i] if n[0] == b and n[1] == g and n[2] == r: return i return -1 def learn(self): biasRadius = self.INITBIASRADIUS alphadec = 30 + ((self.samplefac-1)/3) lengthcount = self.pixels.size samplepixels = lengthcount / self.samplefac delta = samplepixels / self.NCYCLES alpha = self.INITALPHA i = 0 rad = biasRadius >> self.RADIUSBIASSHIFT if rad <= 1: rad = 0 print("Beginning 1D learning: samplepixels = %1.2f rad = %i" % (samplepixels, rad)) step = 0 pos = 0 if lengthcount % NeuQuant.PRIME1 != 0: step = NeuQuant.PRIME1 elif lengthcount % NeuQuant.PRIME2 != 0: step = NeuQuant.PRIME2 elif lengthcount % NeuQuant.PRIME3 != 0: step = NeuQuant.PRIME3 else: step = NeuQuant.PRIME4 i = 0 printed_string = '' while i < samplepixels: if i % 100 == 99: tmp = '\b'len(printed_string) printed_string = str((i+1)100/samplepixels)+"%\n" print(tmp + printed_string) p = self.pixels[pos] r = (p >> 16) & 0xff g = (p >> 8) & 0xff b = (p) & 0xff if i == 0: # Remember background colour self.network[self.BGCOLOR] = [b, g, r] j = self.special_find(b, g, r) if j < 0: j = self.contest(b, g, r) if j >= self.SPECIALS: # Don't learn for specials a = (1.0 * alpha) / self.INITALPHA self.altersingle(a, j, b, g, r) if rad > 0: self.alterneigh(a, rad, j, b, g, r) pos = (pos+step) % lengthcount i += 1 if i % delta == 0: alpha -= alpha / alphadec biasRadius -= biasRadius / self.RADIUSDEC rad = biasRadius >> self.RADIUSBIASSHIFT if rad <= 1: rad = 0 finalAlpha = (1.0alpha)/self.INITALPHA print("Finished 1D learning: final alpha = %1.2f!" % finalAlpha) def fix(self): for i in range(self.NETSIZE): for j in range(3): x = int(0.5 + self.network[i, j]) x = max(0, x) x = min(255, x) self.colormap[i, j] = x self.colormap[i, 3] = i def inxbuild(self): previouscol = 0 startpos = 0 for i in range(self.NETSIZE): p = self.colormap[i] q = None smallpos = i smallval = p[1] # Index on g # Find smallest in i..self.NETSIZE-1 for j in range(i+1, self.NETSIZE): q = self.colormap[j] if q[1] < smallval: # Index on g smallpos = j smallval = q[1] # Index on g q = self.colormap[smallpos] # Swap p (i) and q (smallpos) entries if i != smallpos: p[:], q[:] = q, p.copy() # smallval entry is now in position i if smallval != previouscol: self.netindex[previouscol] = (startpos+i) >> 1 for j in range(previouscol+1, smallval): self.netindex[j] = i previouscol = smallval startpos = i self.netindex[previouscol] = (startpos+self.MAXNETPOS) >> 1 for j in range(previouscol+1, 256): # Really 256 self.netindex[j] = self.MAXNETPOS def paletteImage(self): """ PIL weird interface for making a paletted image: create an image which already has the palette, and use that in Image.quantize. This function returns this palette image. """ if self.pimage is None: palette = [] for i in range(self.NETSIZE): palette.extend(self.colormap[i][:3]) palette.extend([0](256-self.NETSIZE)3) # a palette image to use for quant self.pimage = Image.new("P", (1, 1), 0) self.pimage.putpalette(palette) return self.pimage def quantize(self, image): """ Use a kdtree to quickly find the closest palette colors for the pixels """ if get_cKDTree(): return self.quantize_with_scipy(image) else: print('Scipy not available, falling back to slower version.') return self.quantize_without_scipy(image) def quantize_with_scipy(self, image): w, h = image.size px = np.asarray(image).copy() px2 = px[:, :, :3].reshape((wh, 3)) cKDTree = get_cKDTree() kdtree = cKDTree(self.colormap[:, :3], leafsize=10) result = kdtree.query(px2) colorindex = result[1] print("Distance: %1.2f" % (result[0].sum()/(wh))) px2[:] = self.colormap[colorindex, :3] return Image.fromarray(px).convert("RGB").quantize(palette=self.paletteImage()) def quantize_without_scipy(self, image): """" This function can be used if no scipy is availabe. It's 7 times slower though. """ w, h = image.size px = np.asarray(image).copy() memo = {} for j in range(w): for i in range(h): key = (px[i, j, 0], px[i, j, 1], px[i, j, 2]) try: val = memo[key] except KeyError: val = self.convert(key) memo[key] = val px[i, j, 0], px[i, j, 1], px[i, j, 2] = val return Image.fromarray(px).convert("RGB").quantize(palette=self.paletteImage()) def convert(self, color): i = self.inxsearch(color) return self.colormap[i, :3] def inxsearch(self, r, g, b): """Search for BGR values 0..255 and return colour index""" dists = (self.colormap[:, :3] - np.array([r, g, b])) a = np.argmin((distsdists).sum(1)) return a def load_images(image_directory, extension, prefix=None): """ Locates image files in image_directory with the specified extension and/or prefix, and loads them into memory as PIL/Pillow objects :param image_directory: string :param extension: string :param prefix: string :returns: List of PIL Image objects """ exl = extension.lower() exu = extension.upper() # List everything in dir: all_files = os.listdir(image_directory) # Prune out unwanted extension types images = [i for i in all_files if fnmatch(i, "." + exl) or fnmatch(i, "." + exu)] # Prune out unwanted prefix types if prefix: images = [i for i in images if fnmatch(i, prefix + "")] # Sort to maintain order during GIF creation images.sort() return [Image.open(os.path.join(image_directory, i)) for i in images]	levi-rs/gifted	gifted/gifted.py	Python	bsd-3-clause	35,791	[ "NEURON" ]	d4cff7f9a898e05a253a5ee978ea665cb18629fd3b6178484bc7a01ed9dd3027
# Orca # # Copyright 2004-2009 Sun Microsystems Inc. # Copyright 2010-2011 The Orca Team # Copyright 2012 Igalia, S.L. # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the # Free Software Foundation, Inc., Franklin Street, Fifth Floor, # Boston MA 02110-1301 USA. """The main module for the Orca screen reader.""" __id__ = "$Id$" __version__ = "$Revision$" __date__ = "$Date$" __copyright__ = "Copyright (c) 2004-2009 Sun Microsystems Inc." \ "Copyright (c) 2010-2011 The Orca Team" \ "Copyright (c) 2012 Igalia, S.L." __license__ = "LGPL" import faulthandler import gi import importlib import os import pyatspi import re import signal import subprocess import sys try: from gi.repository.Gio import Settings a11yAppSettings = Settings(schema_id='org.gnome.desktop.a11y.applications') except: a11yAppSettings = None try: # This can fail due to gtk not being available. We want to # be able to recover from that if possible. The main driver # for this is to allow "orca --text-setup" to work even if # the desktop is not running. # gi.require_version("Gtk", "3.0") from gi.repository import Gtk gi.require_version("Gdk", "3.0") from gi.repository import Gdk # Note: This last import is here due to bgo #673396. # See bgo#673397 for the rest of the story. gi.require_version("GdkX11", "3.0") from gi.repository.GdkX11 import X11Screen except: pass from . import braille from . import debug from . import event_manager from . import keybindings from . import logger from . import messages from . import mouse_review from . import notification_messages from . import orca_state from . import orca_platform from . import script_manager from . import settings from . import settings_manager from . import speech from . import sound from .input_event import BrailleEvent _eventManager = event_manager.getManager() _scriptManager = script_manager.getManager() _settingsManager = settings_manager.getManager() _logger = logger.getLogger() def onEnabledChanged(gsetting, key): try: enabled = gsetting.get_boolean(key) except: return if key == 'screen-reader-enabled' and not enabled: shutdown() def getSettingsManager(): return _settingsManager def getLogger(): return _logger EXIT_CODE_HANG = 50 # The user-settings module (see loadUserSettings). # _userSettings = None # A subset of the original Xmodmap info prior to our stomping on it. # Right now, this is just for the user's chosen Orca modifier(s). # _originalXmodmap = "" _orcaModifiers = settings.DESKTOP_MODIFIER_KEYS + settings.LAPTOP_MODIFIER_KEYS _capsLockCleared = False _restoreOrcaKeys = False ######################################################################## # # # METHODS TO HANDLE APPLICATION LIST AND FOCUSED OBJECTS # # # ######################################################################## CARET_TRACKING = "caret-tracking" FOCUS_TRACKING = "focus-tracking" FLAT_REVIEW = "flat-review" MOUSE_REVIEW = "mouse-review" SAY_ALL = "say-all" def emitRegionChanged(obj, startOffset=None, endOffset=None, mode=None): """Notifies interested clients that the current region of interest has changed.""" if startOffset is None: startOffset = 0 if endOffset is None: endOffset = startOffset if mode is None: mode = FOCUS_TRACKING try: obj.emit("mode-changed::" + mode, 1, "") except: msg = "ORCA: Exception emitting mode-changed notification" debug.println(debug.LEVEL_INFO, msg, True) if mode != orca_state.activeMode: msg = "ORCA: Switching active mode from %s to %s" % (orca_state.activeMode, mode) debug.println(debug.LEVEL_INFO, msg, True) orca_state.activeMode = mode try: msg = "ORCA: Region of interest: %s (%i, %i)" % (obj, startOffset, endOffset) debug.println(debug.LEVEL_INFO, msg, True) obj.emit("region-changed", startOffset, endOffset) except: msg = "ORCA: Exception emitting region-changed notification" debug.println(debug.LEVEL_INFO, msg, True) def setLocusOfFocus(event, obj, notifyScript=True, force=False): """Sets the locus of focus (i.e., the object with visual focus) and notifies the script of the change should the script wish to present the change to the user. Arguments: - event: if not None, the Event that caused this to happen - obj: the Accessible with the new locus of focus. - notifyScript: if True, propagate this event - force: if True, don't worry if this is the same object as the current locusOfFocus """ if not force and obj == orca_state.locusOfFocus: msg = "ORCA: Setting locusOfFocus to existing locusOfFocus" debug.println(debug.LEVEL_INFO, msg, True) return if event and (orca_state.activeScript and not orca_state.activeScript.app): script = _scriptManager.getScript(event.host_application, event.source) _scriptManager.setActiveScript(script, "Setting locusOfFocus") oldFocus = orca_state.locusOfFocus try: oldFocus.getRole() except: msg = "ORCA: Old locusOfFocus is null or defunct" debug.println(debug.LEVEL_INFO, msg, True) oldFocus = None if not obj: msg = "ORCA: New locusOfFocus is null (being cleared)" debug.println(debug.LEVEL_INFO, msg, True) orca_state.locusOfFocus = None return if orca_state.activeScript: msg = "ORCA: Active script is: %s" % orca_state.activeScript debug.println(debug.LEVEL_INFO, msg, True) if orca_state.activeScript.utilities.isZombie(obj): msg = "ERROR: New locusOfFocus (%s) is zombie. Not updating." % obj debug.println(debug.LEVEL_INFO, msg, True) return if orca_state.activeScript.utilities.isDead(obj): msg = "ERROR: New locusOfFocus (%s) is dead. Not updating." % obj debug.println(debug.LEVEL_INFO, msg, True) return msg = "ORCA: Changing locusOfFocus from %s to %s" % (oldFocus, obj) debug.println(debug.LEVEL_INFO, msg, True) orca_state.locusOfFocus = obj if not notifyScript: return if not orca_state.activeScript: msg = "ORCA: Cannot notify active script because there isn't one" debug.println(debug.LEVEL_INFO, msg, True) return orca_state.activeScript.locusOfFocusChanged(event, oldFocus, orca_state.locusOfFocus) ######################################################################## # # # METHODS FOR PRE-PROCESSING AND MASSAGING BRAILLE EVENTS. # # # ######################################################################## def _processBrailleEvent(event): """Called whenever a key is pressed on the Braille display. Arguments: - command: the BrlAPI event for the key that was pressed. Returns True if the event was consumed; otherwise False """ consumed = False # Braille key presses always interrupt speech. # event = BrailleEvent(event) if event.event['command'] not in braille.dontInteruptSpeechKeys: speech.stop() orca_state.lastInputEvent = event try: consumed = _eventManager.processBrailleEvent(event) except: debug.printException(debug.LEVEL_SEVERE) if (not consumed) and orca_state.learnModeEnabled: consumed = True return consumed ######################################################################## # # # METHODS FOR HANDLING INITIALIZATION, SHUTDOWN, AND USE. # # # ######################################################################## def deviceChangeHandler(deviceManager, device): """New keyboards being plugged in stomp on our changes to the keymappings, so we have to re-apply""" source = device.get_source() if source == Gdk.InputSource.KEYBOARD: msg = "ORCA: Keyboard change detected, re-creating the xmodmap" debug.println(debug.LEVEL_INFO, msg, True) _createOrcaXmodmap() def updateKeyMap(keyboardEvent): """Unsupported convenience method to call sad hacks which should go away.""" global _restoreOrcaKeys if keyboardEvent.isPressedKey(): return if keyboardEvent.event_string in settings.orcaModifierKeys \ and orca_state.bypassNextCommand: _restoreXmodmap() _restoreOrcaKeys = True return if _restoreOrcaKeys and not orca_state.bypassNextCommand: _createOrcaXmodmap() _restoreOrcaKeys = False def _setXmodmap(xkbmap): """Set the keyboard map using xkbcomp.""" p = subprocess.Popen(['xkbcomp', '-w0', '-', os.environ['DISPLAY']], stdin=subprocess.PIPE, stdout=None, stderr=None) p.communicate(xkbmap) def _setCapsLockAsOrcaModifier(enable): """Enable or disable use of the caps lock key as an Orca modifier key.""" interpretCapsLineProg = re.compile( r'^\sinterpret\s+Caps[_+]Lock[_+]AnyOfOrNone\s\(all\)\s{\s$', re.I) normalCapsLineProg = re.compile( r'^\saction\s=\sLockMods\s\(\smodifiers\s=\sLock\s\)\s;\s$', re.I) interpretShiftLineProg = re.compile( r'^\sinterpret\s+Shift[_+]Lock[_+]AnyOf\s\(\sShift\s\+\sLock\s\)\s{\s$', re.I) normalShiftLineProg = re.compile( r'^\saction\s=\sLockMods\s\(\smodifiers\s=\sShift\s\)\s;\s$', re.I) disabledModLineProg = re.compile( r'^\saction\s=\sNoAction\s\(\s\)\s;\s*$', re.I) normalCapsLine = ' action= LockMods(modifiers=Lock);' normalShiftLine = ' action= LockMods(modifiers=Shift);' disabledModLine = ' action= NoAction();' lines = _originalXmodmap.decode('UTF-8').split('\n') foundCapsInterpretSection = False foundShiftInterpretSection = False modified = False for i, line in enumerate(lines): if not foundCapsInterpretSection and not foundShiftInterpretSection: if interpretCapsLineProg.match(line): foundCapsInterpretSection = True elif interpretShiftLineProg.match(line): foundShiftInterpretSection = True elif foundCapsInterpretSection: if enable: if normalCapsLineProg.match(line): lines[i] = disabledModLine modified = True else: if disabledModLineProg.match(line): lines[i] = normalCapsLine modified = True if line.find('}'): foundCapsInterpretSection = False else: # foundShiftInterpretSection if enable: if normalShiftLineProg.match(line): lines[i] = disabledModLine modified = True else: if disabledModLineProg.match(line): lines[i] = normalShiftLine modified = True if line.find('}'): foundShiftInterpretSection = False if modified: _setXmodmap(bytes('\n'.join(lines), 'UTF-8')) def _createOrcaXmodmap(): """Makes an Orca-specific Xmodmap so that the keys behave as we need them to do. This is especially the case for the Orca modifier. """ global _capsLockCleared cmd = [] if "Caps_Lock" in settings.orcaModifierKeys \ or "Shift_Lock" in settings.orcaModifierKeys: _setCapsLockAsOrcaModifier(True) _capsLockCleared = True elif _capsLockCleared: _setCapsLockAsOrcaModifier(False) _capsLockCleared = False def _storeXmodmap(keyList): """Save the original xmodmap for the keys in keyList before we alter it. Arguments: - keyList: A list of named keys to look for. """ global _originalXmodmap _originalXmodmap = subprocess.check_output(['xkbcomp', os.environ['DISPLAY'], '-']) def _restoreXmodmap(keyList=[]): """Restore the original xmodmap values for the keys in keyList. Arguments: - keyList: A list of named keys to look for. An empty list means to restore the entire saved xmodmap. """ global _capsLockCleared _capsLockCleared = False p = subprocess.Popen(['xkbcomp', '-w0', '-', os.environ['DISPLAY']], stdin=subprocess.PIPE, stdout=None, stderr=None) p.communicate(_originalXmodmap) def setKeyHandling(new): """Toggle use of the new vs. legacy key handling mode. """ _eventManager.setKeyHandling(new) def loadUserSettings(script=None, inputEvent=None, skipReloadMessage=False): """Loads (and reloads) the user settings module, reinitializing things such as speech if necessary. Returns True to indicate the input event has been consumed. """ debug.println(debug.LEVEL_INFO, 'ORCA: Loading User Settings', True) global _userSettings # Shutdown the output drivers and give them a chance to die. player = sound.getPlayer() player.shutdown() speech.shutdown() braille.shutdown() _scriptManager.deactivate() reloaded = False if _userSettings: _profile = _settingsManager.getSetting('activeProfile')[1] try: _userSettings = _settingsManager.getGeneralSettings(_profile) _settingsManager.setProfile(_profile) reloaded = True except ImportError: debug.printException(debug.LEVEL_INFO) except: debug.printException(debug.LEVEL_SEVERE) else: _profile = _settingsManager.profile try: _userSettings = _settingsManager.getGeneralSettings(_profile) except ImportError: debug.printException(debug.LEVEL_INFO) except: debug.printException(debug.LEVEL_SEVERE) if not script: script = _scriptManager.getDefaultScript() _settingsManager.loadAppSettings(script) if _settingsManager.getSetting('enableSpeech'): msg = 'ORCA: About to enable speech' debug.println(debug.LEVEL_INFO, msg, True) try: speech.init() if reloaded and not skipReloadMessage: script.speakMessage(messages.SETTINGS_RELOADED) except: debug.printException(debug.LEVEL_SEVERE) else: msg = 'ORCA: Speech is not enabled in settings' debug.println(debug.LEVEL_INFO, msg, True) if _settingsManager.getSetting('enableBraille'): msg = 'ORCA: About to enable braille' debug.println(debug.LEVEL_INFO, msg, True) try: braille.init(_processBrailleEvent) except: debug.printException(debug.LEVEL_WARNING) msg = 'ORCA: Could not initialize connection to braille.' debug.println(debug.LEVEL_WARNING, msg, True) else: msg = 'ORCA: Braille is not enabled in settings' debug.println(debug.LEVEL_INFO, msg, True) if _settingsManager.getSetting('enableMouseReview'): mouse_review.reviewer.activate() else: mouse_review.reviewer.deactivate() if _settingsManager.getSetting('enableSound'): player.init() global _orcaModifiers custom = [k for k in settings.orcaModifierKeys if k not in _orcaModifiers] _orcaModifiers += custom # Handle the case where a change was made in the Orca Preferences dialog. # if _originalXmodmap: _restoreXmodmap(_orcaModifiers) _storeXmodmap(_orcaModifiers) _createOrcaXmodmap() _scriptManager.activate() _eventManager.activate() debug.println(debug.LEVEL_INFO, 'ORCA: User Settings Loaded', True) return True def _showPreferencesUI(script, prefs): if orca_state.orcaOS: orca_state.orcaOS.showGUI() return try: module = importlib.import_module('.orca_gui_prefs', 'orca') except: debug.printException(debug.LEVEL_SEVERE) return uiFile = os.path.join(orca_platform.datadir, orca_platform.package, "ui", "orca-setup.ui") orca_state.orcaOS = module.OrcaSetupGUI(uiFile, "orcaSetupWindow", prefs) orca_state.orcaOS.init(script) orca_state.orcaOS.showGUI() def showAppPreferencesGUI(script=None, inputEvent=None): """Displays the user interface to configure the settings for a specific applications within Orca and set up those app-specific user preferences using a GUI. Returns True to indicate the input event has been consumed. """ prefs = {} for key in settings.userCustomizableSettings: prefs[key] = _settingsManager.getSetting(key) script = script or orca_state.activeScript _showPreferencesUI(script, prefs) return True def showPreferencesGUI(script=None, inputEvent=None): """Displays the user interface to configure Orca and set up user preferences using a GUI. Returns True to indicate the input event has been consumed. """ prefs = _settingsManager.getGeneralSettings(_settingsManager.profile) script = _scriptManager.getDefaultScript() _showPreferencesUI(script, prefs) return True def helpForOrca(script=None, inputEvent=None, page=""): """Show Orca Help window (part of the GNOME Access Guide). Returns True to indicate the input event has been consumed. """ orca_state.learnModeEnabled = False uri = "help:orca" if page: uri += "?%s" % page Gtk.show_uri(Gdk.Screen.get_default(), uri, Gtk.get_current_event_time()) return True def addKeyGrab(binding): """ Add a key grab for the given key binding. """ ret = [] for kd in binding.keyDefs(): ret.append(orca_state.device.add_key_grab(kd, None)) return ret def removeKeyGrab(id): """ Remove the key grab for the given key binding. """ orca_state.device.remove_key_grab(id) def mapModifier(keycode): return orca_state.device.map_modifier(keycode) def quitOrca(script=None, inputEvent=None): """Quit Orca. Check if the user wants to confirm this action. If so, show the confirmation GUI otherwise just shutdown. Returns True to indicate the input event has been consumed. """ shutdown() return True def showFindGUI(script=None, inputEvent=None): """Displays the user interface to perform an Orca Find. Returns True to indicate the input event has been consumed. """ try: module = importlib.import_module('.orca_gui_find', 'orca') module.showFindUI() except: debug.printException(debug.LEVEL_SEVERE) # If True, this module has been initialized. # _initialized = False def init(registry): """Initialize the orca module, which initializes the speech and braille modules. Also builds up the application list, registers for AT-SPI events, and creates scripts for all known applications. Returns True if the initialization procedure has run, or False if this module has already been initialized. """ debug.println(debug.LEVEL_INFO, 'ORCA: Initializing', True) global _initialized if _initialized and _settingsManager.isScreenReaderServiceEnabled(): debug.println(debug.LEVEL_INFO, 'ORCA: Already initialized', True) return False # Do not hang on initialization if we can help it. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) loadUserSettings() if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) _initialized = True # In theory, we can do this through dbus. In practice, it fails to # work sometimes. Until we know why, we need to leave this as-is # so that we respond when gnome-control-center is used to stop Orca. if a11yAppSettings: a11yAppSettings.connect('changed', onEnabledChanged) debug.println(debug.LEVEL_INFO, 'ORCA: Initialized', True) return True def start(registry, cacheValues): """Starts Orca.""" debug.println(debug.LEVEL_INFO, 'ORCA: Starting', True) if not _initialized: init(registry) # Do not hang on startup if we can help it. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) if cacheValues: pyatspi.setCacheLevel(pyatspi.CACHE_PROPERTIES) # Event handlers for input devices being plugged in/unplugged. # Used to re-create the Xmodmap when a new keyboard is plugged in. # Necessary, because plugging in a new keyboard resets the Xmodmap # and stomps our changes display = Gdk.Display.get_default() devmanager=display.get_device_manager() devmanager.connect("device-added", deviceChangeHandler) devmanager.connect("device-removed", deviceChangeHandler) Gdk.notify_startup_complete() msg = 'ORCA: Startup complete notification made' debug.println(debug.LEVEL_INFO, msg, True) debug.println(debug.LEVEL_INFO, 'ORCA: Starting registry', True) registry.start(gil=False) def die(exitCode=1): pid = os.getpid() if exitCode == EXIT_CODE_HANG: # Someting is hung and we wish to abort. os.kill(pid, signal.SIGKILL) return shutdown() sys.exit(exitCode) if exitCode > 1: os.kill(pid, signal.SIGTERM) def timeout(signum=None, frame=None): msg = 'TIMEOUT: something has hung. Aborting.' debug.println(debug.LEVEL_SEVERE, msg, True) debug.printStack(debug.LEVEL_SEVERE) debug.examineProcesses(force=True) die(EXIT_CODE_HANG) def shutdown(script=None, inputEvent=None): """Exits Orca. Unregisters any event listeners and cleans up. Returns True if the shutdown procedure ran or False if this module was never initialized. """ debug.println(debug.LEVEL_INFO, 'ORCA: Shutting down', True) global _initialized if not _initialized: return False # Try to say goodbye, but be defensive if something has hung. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) orca_state.activeScript.presentMessage(messages.STOP_ORCA, resetStyles=False) _scriptManager.deactivate() _eventManager.deactivate() # Shutdown all the other support. # if settings.enableSpeech: speech.shutdown() if settings.enableBraille: braille.shutdown() if settings.enableSound: player = sound.getPlayer() player.shutdown() if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) _initialized = False _restoreXmodmap(_orcaModifiers) debug.println(debug.LEVEL_INFO, 'ORCA: Stopping registry', True) pyatspi.Registry.stop() debug.println(debug.LEVEL_INFO, 'ORCA: Shutdown complete', True) return True exitCount = 0 def shutdownOnSignal(signum, frame): global exitCount try: # Requires python 3.8 signalString = '(%s)' % signal.strsignal(signum) except: signalString = '' msg = 'ORCA: Shutting down and exiting due to signal=%d %s' % \ (signum, signalString) debug.println(debug.LEVEL_INFO, msg, True) # Well...we'll try to exit nicely, but if we keep getting called, # something bad is happening, so just quit. # if exitCount: die(signum) else: exitCount += 1 # Try to do a graceful shutdown if we can. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) try: if _initialized: shutdown() else: # We always want to try to shutdown speech since the # speech servers are very persistent about living. # speech.shutdown() shutdown() cleanExit = True except: cleanExit = False if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) if not cleanExit: die(EXIT_CODE_HANG) def crashOnSignal(signum, frame): signal.signal(signum, signal.SIG_DFL) _restoreXmodmap(_orcaModifiers) os.kill(os.getpid(), signum) def main(cacheValues=True): """The main entry point for Orca. The exit codes for Orca will loosely be based on signals, where the exit code will be the signal used to terminate Orca (if a signal was used). Otherwise, an exit code of 0 means normal completion and an exit code of 50 means Orca exited because of a hang.""" msg = "ORCA: Launching version %s" % orca_platform.version if orca_platform.revision: msg += " (rev %s)" % orca_platform.revision debug.println(debug.LEVEL_INFO, msg, True) if debug.debugFile and os.path.exists(debug.debugFile.name): faulthandler.enable(file=debug.debugFile, all_threads=True) else: faulthandler.enable(all_threads=False) # Method to call when we think something might be hung. # settings.timeoutCallback = timeout # Various signal handlers we want to listen for. # signal.signal(signal.SIGHUP, shutdownOnSignal) signal.signal(signal.SIGINT, shutdownOnSignal) signal.signal(signal.SIGTERM, shutdownOnSignal) signal.signal(signal.SIGQUIT, shutdownOnSignal) signal.signal(signal.SIGSEGV, crashOnSignal) debug.println(debug.LEVEL_INFO, "ORCA: Enabling accessibility (if needed).", True) if not _settingsManager.isAccessibilityEnabled(): _settingsManager.setAccessibility(True) debug.println(debug.LEVEL_INFO, "ORCA: Initializing ATSPI registry.", True) init(pyatspi.Registry) debug.println(debug.LEVEL_INFO, "ORCA: ATSPI registry initialized.", True) try: message = messages.START_ORCA script = _scriptManager.getDefaultScript() script.presentMessage(message) except: debug.printException(debug.LEVEL_SEVERE) script = orca_state.activeScript if script: window = script.utilities.activeWindow() if window and not orca_state.locusOfFocus: try: app = window.getApplication() except: msg = "ORCA: Exception getting app for %s" % window debug.println(debug.LEVEL_INFO, msg, True) else: script = _scriptManager.getScript(app, window) _scriptManager.setActiveScript(script, "Launching.") setLocusOfFocus(None, window) focusedObject = script.utilities.focusedObject(window) if focusedObject: setLocusOfFocus(None, focusedObject) script = _scriptManager.getScript(focusedObject.getApplication(), focusedObject) _scriptManager.setActiveScript(script, "Found focused object.") try: debug.println(debug.LEVEL_INFO, "ORCA: Starting ATSPI registry.", True) start(pyatspi.Registry, cacheValues) # waits until we stop the registry except: debug.println(debug.LEVEL_SEVERE, "ORCA: Exception starting ATSPI registry.", True) die(EXIT_CODE_HANG) return 0 if __name__ == "__main__": sys.exit(main())	GNOME/orca	src/orca/orca.py	Python	lgpl-2.1	28,530	[ "ORCA" ]	be57ace019f253f6ab90683e8b93150aa12254b13ba006ccdf7c4cc334484296
# CLEANUP NOTES (for ISHAN): # - add documentation for each method # - add comments inline explaining each piece # - add a unit test for each method (at least) # future from __future__ import annotations # stdlib from typing import Any from typing import List as TypeList from typing import Optional # third party from nacl.signing import VerifyKey # the most generic class class Scalar: """ A Scalar is the most generic class, which keeps track of the current value, and a data-independent min-val and max-val. """ def publish( self, acc: Any, user_key: VerifyKey, sigma: float = 1.5 ) -> TypeList[Any]: """Adversarial accountant adds Gaussian noise and publishes the scalar's value""" # relative from ...publish import publish return publish([self], acc=acc, sigma=sigma, user_key=user_key) @property def max_val(self) -> Optional[float]: raise NotImplementedError @property def min_val(self) -> Optional[float]: raise NotImplementedError @property def value(self) -> Optional[float]: raise NotImplementedError def __str__(self) -> str: return ( "<" + str(type(self).__name__) + ": (" + str(self.min_val) + " < " + str(self.value) + " < " + str(self.max_val) + ")>" ) def __repr__(self) -> str: return str(self)	OpenMined/PySyft	packages/syft/src/syft/core/adp/scalar/abstract/scalar.py	Python	apache-2.0	1,478	[ "Gaussian" ]	051f3bb25a3a1228174127d25559591a4c7e84a22877463c805b14b9f5283f4b
"""Forest of trees-based ensemble methods Those methods include random forests and extremely randomized trees. The module structure is the following: - The ``BaseForest`` base class implements a common ``fit`` method for all the estimators in the module. The ``fit`` method of the base ``Forest`` class calls the ``fit`` method of each sub-estimator on random samples (with replacement, a.k.a. bootstrap) of the training set. The init of the sub-estimator is further delegated to the ``BaseEnsemble`` constructor. - The ``ForestClassifier`` and ``ForestRegressor`` base classes further implement the prediction logic by computing an average of the predicted outcomes of the sub-estimators. - The ``RandomForestClassifier`` and ``RandomForestRegressor`` derived classes provide the user with concrete implementations of the forest ensemble method using classical, deterministic ``DecisionTreeClassifier`` and ``DecisionTreeRegressor`` as sub-estimator implementations. - The ``ExtraTreesClassifier`` and ``ExtraTreesRegressor`` derived classes provide the user with concrete implementations of the forest ensemble method using the extremly randomized trees ``ExtraTreeClassifier`` and ``ExtraTreeRegressor`` as sub-estimator implementations. Single and multi-output problems are both handled. """ # Authors: Gilles Louppe, Brian Holt # License: BSD 3 import itertools import numpy as np from warnings import warn from abc import ABCMeta, abstractmethod from ..base import ClassifierMixin, RegressorMixin from ..externals.joblib import Parallel, delayed, cpu_count from ..feature_selection.selector_mixin import SelectorMixin from ..tree import DecisionTreeClassifier, DecisionTreeRegressor, \ ExtraTreeClassifier, ExtraTreeRegressor from ..tree._tree import DTYPE, DOUBLE from ..utils import array2d, check_random_state, check_arrays from ..metrics import r2_score from .base import BaseEnsemble __all__ = ["RandomForestClassifier", "RandomForestRegressor", "ExtraTreesClassifier", "ExtraTreesRegressor"] MAX_INT = np.iinfo(np.int32).max def _parallel_build_trees(n_trees, forest, X, y, sample_mask, X_argsorted, seed, verbose): """Private function used to build a batch of trees within a job.""" random_state = check_random_state(seed) trees = [] for i in xrange(n_trees): if verbose > 1: print("building tree %d of %d" % (i + 1, n_trees)) seed = random_state.randint(MAX_INT) tree = forest._make_estimator(append=False) tree.set_params(compute_importances=forest.compute_importances) tree.set_params(random_state=check_random_state(seed)) if forest.bootstrap: n_samples = X.shape[0] indices = random_state.randint(0, n_samples, n_samples) tree.fit(X[indices], y[indices], sample_mask=sample_mask, X_argsorted=X_argsorted) tree.indices_ = indices else: tree.fit(X, y, sample_mask=sample_mask, X_argsorted=X_argsorted) trees.append(tree) return trees def _parallel_predict_proba(trees, X, n_classes, n_outputs): """Private function used to compute a batch of predictions within a job.""" n_samples = X.shape[0] p = [] for k in xrange(n_outputs): p.append(np.zeros((n_samples, n_classes[k]))) for tree in trees: p_tree = tree.predict_proba(X) if n_outputs == 1: p_tree = [p_tree] for k in xrange(n_outputs): if n_classes[k] == tree.n_classes_[k]: p[k] += p_tree[k] else: for j, c in enumerate(tree.classes_[k]): p[k][:, c] += p_tree[k][:, j] return p def _parallel_predict_regression(trees, X): """Private function used to compute a batch of predictions within a job.""" return sum(tree.predict(X) for tree in trees) def _partition_trees(forest): """Private function used to partition trees between jobs.""" # Compute the number of jobs if forest.n_jobs == -1: n_jobs = min(cpu_count(), forest.n_estimators) else: n_jobs = min(forest.n_jobs, forest.n_estimators) # Partition trees between jobs n_trees = [int(forest.n_estimators / n_jobs)] * n_jobs for i in xrange(forest.n_estimators % n_jobs): n_trees[i] += 1 starts = [0] * (n_jobs + 1) for i in xrange(1, n_jobs + 1): starts[i] = starts[i - 1] + n_trees[i - 1] return n_jobs, n_trees, starts def _parallel_X_argsort(X): """Private function used to sort the features of X.""" return np.asarray(np.argsort(X.T, axis=1).T, dtype=np.int32, order="F") def _partition_features(forest, n_total_features): """Private function used to partition features between jobs.""" # Compute the number of jobs if forest.n_jobs == -1: n_jobs = min(cpu_count(), n_total_features) else: n_jobs = min(forest.n_jobs, n_total_features) # Partition features between jobs n_features = [n_total_features / n_jobs] * n_jobs for i in xrange(n_total_features % n_jobs): n_features[i] += 1 starts = [0] * (n_jobs + 1) for i in xrange(1, n_jobs + 1): starts[i] = starts[i - 1] + n_features[i - 1] return n_jobs, n_features, starts class BaseForest(BaseEnsemble, SelectorMixin): """Base class for forests of trees. Warning: This class should not be used directly. Use derived classes instead. """ __metaclass__ = ABCMeta @abstractmethod def __init__(self, base_estimator, n_estimators=10, estimator_params=[], bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(BaseForest, self).__init__( base_estimator=base_estimator, n_estimators=n_estimators, estimator_params=estimator_params) self.bootstrap = bootstrap self.compute_importances = compute_importances self.oob_score = oob_score self.n_jobs = n_jobs self.random_state = random_state self.n_features_ = None self.n_outputs_ = None self.classes_ = None self.n_classes_ = None self.feature_importances_ = None self.verbose = verbose def fit(self, X, y): """Build a forest of trees from the training set (X, y). Parameters ---------- X : array-like of shape = [n_samples, n_features] The training input samples. y : array-like, shape = [n_samples] or [n_samples, n_outputs] The target values (integers that correspond to classes in classification, real numbers in regression). Returns ------- self : object Returns self. """ self.random_state = check_random_state(self.random_state) # Precompute some data X, y = check_arrays(X, y, sparse_format="dense") if getattr(X, "dtype", None) != DTYPE or \ X.ndim != 2 or not X.flags.fortran: X = array2d(X, dtype=DTYPE, order="F") n_samples, self.n_features_ = X.shape if self.bootstrap: sample_mask = None X_argsorted = None else: if self.oob_score: raise ValueError("Out of bag estimation only available" " if bootstrap=True") sample_mask = np.ones((n_samples,), dtype=np.bool) n_jobs, _, starts = _partition_features(self, self.n_features_) all_X_argsorted = Parallel(n_jobs=n_jobs)( delayed(_parallel_X_argsort)( X[:, starts[i]:starts[i + 1]]) for i in xrange(n_jobs)) X_argsorted = np.asfortranarray(np.hstack(all_X_argsorted)) y = np.atleast_1d(y) if y.ndim == 1: y = y[:, np.newaxis] self.classes_ = [] self.n_classes_ = [] self.n_outputs_ = y.shape[1] if isinstance(self.base_estimator, ClassifierMixin): y = np.copy(y) for k in xrange(self.n_outputs_): unique = np.unique(y[:, k]) self.classes_.append(unique) self.n_classes_.append(unique.shape[0]) y[:, k] = np.searchsorted(unique, y[:, k]) if getattr(y, "dtype", None) != DTYPE or not y.flags.contiguous: y = np.ascontiguousarray(y, dtype=DOUBLE) # Assign chunk of trees to jobs n_jobs, n_trees, _ = _partition_trees(self) # Parallel loop all_trees = Parallel(n_jobs=n_jobs, verbose=self.verbose)( delayed(_parallel_build_trees)( n_trees[i], self, X, y, sample_mask, X_argsorted, self.random_state.randint(MAX_INT), verbose=self.verbose) for i in xrange(n_jobs)) # Reduce self.estimators_ = [tree for tree in itertools.chain(*all_trees)] # Calculate out of bag predictions and score if self.oob_score: if isinstance(self, ClassifierMixin): self.oob_decision_function_ = [] self.oob_score_ = 0.0 predictions = [] for k in xrange(self.n_outputs_): predictions.append(np.zeros((n_samples, self.n_classes_[k]))) for estimator in self.estimators_: mask = np.ones(n_samples, dtype=np.bool) mask[estimator.indices_] = False p_estimator = estimator.predict_proba(X[mask, :]) if self.n_outputs_ == 1: p_estimator = [p_estimator] for k in xrange(self.n_outputs_): predictions[k][mask, :] += p_estimator[k] for k in xrange(self.n_outputs_): if (predictions[k].sum(axis=1) == 0).any(): warn("Some inputs do not have OOB scores. " "This probably means too few trees were used " "to compute any reliable oob estimates.") decision = predictions[k] \ / predictions[k].sum(axis=1)[:, np.newaxis] self.oob_decision_function_.append(decision) self.oob_score_ += np.mean(y[:, k] \ == np.argmax(predictions[k], axis=1)) if self.n_outputs_ == 1: self.oob_decision_function_ = \ self.oob_decision_function_[0] self.oob_score_ /= self.n_outputs_ else: # Regression: predictions = np.zeros((n_samples, self.n_outputs_)) n_predictions = np.zeros((n_samples, self.n_outputs_)) for estimator in self.estimators_: mask = np.ones(n_samples, dtype=np.bool) mask[estimator.indices_] = False p_estimator = estimator.predict(X[mask, :]) if self.n_outputs_ == 1: p_estimator = p_estimator[:, np.newaxis] predictions[mask, :] += p_estimator n_predictions[mask, :] += 1 if (n_predictions == 0).any(): warn("Some inputs do not have OOB scores. " "This probably means too few trees were used " "to compute any reliable oob estimates.") n_predictions[n_predictions == 0] = 1 predictions /= n_predictions self.oob_prediction_ = predictions if self.n_outputs_ == 1: self.oob_prediction_ = \ self.oob_prediction_.reshape((n_samples, )) self.oob_score_ = 0.0 for k in xrange(self.n_outputs_): self.oob_score_ += r2_score(y[:, k], predictions[:, k]) self.oob_score_ /= self.n_outputs_ # Sum the importances if self.compute_importances: self.feature_importances_ = \ sum(tree.feature_importances_ for tree in self.estimators_) \ / self.n_estimators return self class ForestClassifier(BaseForest, ClassifierMixin): """Base class for forest of trees-based classifiers. Warning: This class should not be used directly. Use derived classes instead. """ __metaclass__ = ABCMeta @abstractmethod def __init__(self, base_estimator, n_estimators=10, estimator_params=[], bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ForestClassifier, self).__init__( base_estimator, n_estimators=n_estimators, estimator_params=estimator_params, bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) def predict(self, X): """Predict class for X. The predicted class of an input sample is computed as the majority prediction of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- y : array of shape = [n_samples] or [n_samples, n_outputs] The predicted classes. """ n_samples = len(X) P = self.predict_proba(X) if self.n_outputs_ == 1: P = [P] predictions = np.zeros((n_samples, self.n_outputs_)) for k in xrange(self.n_outputs_): predictions[:, k] = self.classes_[k].take(np.argmax(P[k], axis=1), axis=0) if self.n_outputs_ == 1: predictions = predictions.reshape((n_samples, )) return predictions def predict_proba(self, X): """Predict class probabilities for X. The predicted class probabilities of an input sample is computed as the mean predicted class probabilities of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- p : array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1. The class probabilities of the input samples. Classes are ordered by arithmetical order. """ # Check data if getattr(X, "dtype", None) != DTYPE or X.ndim != 2: X = array2d(X, dtype=DTYPE) # Assign chunk of trees to jobs n_jobs, n_trees, starts = _partition_trees(self) # Parallel loop all_p = Parallel(n_jobs=n_jobs)( delayed(_parallel_predict_proba)( self.estimators_[starts[i]:starts[i + 1]], X, self.n_classes_, self.n_outputs_) for i in xrange(n_jobs)) # Reduce p = all_p[0] for j in xrange(1, len(all_p)): for k in xrange(self.n_outputs_): p[k] += all_p[j][k] for k in xrange(self.n_outputs_): p[k] /= self.n_estimators if self.n_outputs_ == 1: return p[0] else: return p def predict_log_proba(self, X): """Predict class log-probabilities for X. The predicted class log-probabilities of an input sample is computed as the mean predicted class log-probabilities of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- p : array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1. The class log-probabilities of the input samples. Classes are ordered by arithmetical order. """ proba = self.predict_proba(X) if self.n_outputs_ == 1: return np.log(proba) else: for k in xrange(self.n_outputs_): proba[k] = np.log(proba[k]) return proba class ForestRegressor(BaseForest, RegressorMixin): """Base class for forest of trees-based regressors. Warning: This class should not be used directly. Use derived classes instead. """ __metaclass__ = ABCMeta @abstractmethod def __init__(self, base_estimator, n_estimators=10, estimator_params=[], bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ForestRegressor, self).__init__( base_estimator, n_estimators=n_estimators, estimator_params=estimator_params, bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) def predict(self, X): """Predict regression target for X. The predicted regression target of an input sample is computed as the mean predicted regression targets of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- y: array of shape = [n_samples] or [n_samples, n_outputs] The predicted values. """ # Check data if getattr(X, "dtype", None) != DTYPE or X.ndim != 2: X = array2d(X, dtype=DTYPE) # Assign chunk of trees to jobs n_jobs, n_trees, starts = _partition_trees(self) # Parallel loop all_y_hat = Parallel(n_jobs=n_jobs)( delayed(_parallel_predict_regression)( self.estimators_[starts[i]:starts[i + 1]], X) for i in xrange(n_jobs)) # Reduce y_hat = sum(all_y_hat) / self.n_estimators return y_hat class RandomForestClassifier(ForestClassifier): """A random forest classifier. A random forest is a meta estimator that fits a number of classifical decision trees on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="gini") The function to measure the quality of a split. Supported criteria are "gini" for the Gini impurity and "entropy" for the information gain. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split: - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=True) Whether bootstrap samples are used when building trees. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool Whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeClassifier The collection of fitted sub-estimators. `feature_importances_` : array, shape = [n_features] The feature importances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_decision_function_` : array, shape = [n_samples, n_classes] Decision function computed with out-of-bag estimate on the training set. References ---------- .. [1] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32, 2001. See also -------- DecisionTreeClassifier, ExtraTreesClassifier """ def __init__(self, n_estimators=10, criterion="gini", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=True, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(RandomForestClassifier, self).__init__( base_estimator=DecisionTreeClassifier(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features class RandomForestRegressor(ForestRegressor): """A random forest regressor. A random forest is a meta estimator that fits a number of classifical decision trees on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="mse") The function to measure the quality of a split. The only supported criterion is "mse" for the mean squared error. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split: - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=True) Whether bootstrap samples are used when building trees. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeRegressor The collection of fitted sub-estimators. `feature_importances_` : array of shape = [n_features] The feature mportances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_prediction_` : array, shape = [n_samples] Prediction computed with out-of-bag estimate on the training set. References ---------- .. [1] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32, 2001. See also -------- DecisionTreeRegressor, ExtraTreesRegressor """ def __init__(self, n_estimators=10, criterion="mse", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=True, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(RandomForestRegressor, self).__init__( base_estimator=DecisionTreeRegressor(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features class ExtraTreesClassifier(ForestClassifier): """An extra-trees classifier. This class implements a meta estimator that fits a number of randomized decision trees (a.k.a. extra-trees) on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="gini") The function to measure the quality of a split. Supported criteria are "gini" for the Gini impurity and "entropy" for the information gain. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split. - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=False) Whether bootstrap samples are used when building trees. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool Whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeClassifier The collection of fitted sub-estimators. `feature_importances_` : array of shape = [n_features] The feature mportances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_decision_function_` : array, shape = [n_samples, n_classes] Decision function computed with out-of-bag estimate on the training set. References ---------- .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", Machine Learning, 63(1), 3-42, 2006. See also -------- sklearn.tree.ExtraTreeClassifier : Base classifier for this ensemble. RandomForestClassifier : Ensemble Classifier based on trees with optimal splits. """ def __init__(self, n_estimators=10, criterion="gini", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ExtraTreesClassifier, self).__init__( base_estimator=ExtraTreeClassifier(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features class ExtraTreesRegressor(ForestRegressor): """An extra-trees regressor. This class implements a meta estimator that fits a number of randomized decision trees (a.k.a. extra-trees) on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="mse") The function to measure the quality of a split. The only supported criterion is "mse" for the mean squared error. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split: - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=False) Whether bootstrap samples are used when building trees. Note: this parameter is tree-specific. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool Whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeRegressor The collection of fitted sub-estimators. `feature_importances_` : array of shape = [n_features] The feature mportances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_prediction_` : array, shape = [n_samples] Prediction computed with out-of-bag estimate on the training set. References ---------- .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", Machine Learning, 63(1), 3-42, 2006. See also -------- sklearn.tree.ExtraTreeRegressor: Base estimator for this ensemble. RandomForestRegressor: Ensemble regressor using trees with optimal splits. """ def __init__(self, n_estimators=10, criterion="mse", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ExtraTreesRegressor, self).__init__( base_estimator=ExtraTreeRegressor(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features	GbalsaC/bitnamiP	venv/lib/python2.7/site-packages/sklearn/ensemble/forest.py	Python	agpl-3.0	41,898	[ "Brian" ]	70332f50177c22d4fc5fbc0263d3b9fe04fe68ac988453836d627fac9f9cc463
# Copyright 2003-2009 by Bartek Wilczynski. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. """Tools for sequence motif analysis (DEPRECATED, see Bio.motifs instead). This module (Bio.Motif) has been deprecated and will be removed in a future release of release of Biopython. Please use the new module Bio.motifs instead. This contains the core Motif class containing various I/O methods as well as methods for motif comparisons and motif searching in sequences. It also inlcudes functionality for parsing AlignACE and MEME programs. """ from __future__ import print_function import warnings from Bio import BiopythonDeprecationWarning warnings.warn("The module Bio.Motif has been deprecated and will be " "removed in a future release of Biopython. Instead " "please use the new module Bio.motifs instead. Please " "be aware that though the functionality of Bio.Motif " "is retained (and extended) in Bio.motifs, usage may " "be different.", BiopythonDeprecationWarning) from Bio.Motif._Motif import Motif from Bio.Motif.Parsers.AlignAce import read as _AlignAce_read from Bio.Motif.Parsers.MEME import read as _MEME_read from Bio.Motif.Thresholds import ScoreDistribution __docformat__ = "restructuredtext en" _parsers = {"AlignAce": _AlignAce_read, "MEME": _MEME_read, } def _from_pfm(handle): return Motif()._from_jaspar_pfm(handle) def _from_sites(handle): return Motif()._from_jaspar_sites(handle) _readers = {"jaspar-pfm": _from_pfm, "jaspar-sites": _from_sites } def parse(handle, format): """Parses an output file of motif finding programs. Currently supported formats: - AlignAce - MEME You can also use single-motif formats, although the Bio.Motif.read() function is simpler to use in this situation. - jaspar-pfm - jaspar-sites For example: >>> from Bio import Motif >>> with open("Motif/alignace.out") as handle: ... for motif in Motif.parse(handle, "AlignAce"): ... print(motif.consensus()) ... TCTACGATTGAG CTGCACCTAGCTACGAGTGAG GTGCCCTAAGCATACTAGGCG GCCACTAGCAGAGCAGGGGGC CGACTCAGAGGTT CCACGCTAAGAGAAGTGCCGGAG GCACGTCCCTGAGCA GTCCATCGCAAAGCGTGGGGC GAGATCAGAGGGCCG TGGACGCGGGG GACCAGAGCCTCGCATGGGGG AGCGCGCGTG GCCGGTTGCTGTTCATTAGG ACCGACGGCAGCTAAAAGGG GACGCCGGGGAT CGACTCGCGCTTACAAGG """ try: parser = _parsers[format] except KeyError: try: # not a true parser, try reader formats reader = _readers[format] except: raise ValueError("Wrong parser format") else: # we have a proper reader yield reader(handle) else: # we have a proper reader for m in parser(handle).motifs: yield m def read(handle, format): """Reads a motif from a handle using a specified file-format. This supports the same formats as Bio.Motif.parse(), but only for files containing exactly one record. For example, reading a pfm file: >>> from Bio import Motif >>> with open("Motif/SRF.pfm") as handle: ... motif = Motif.read(handle, "jaspar-pfm") ... >>> motif.consensus() Seq('GCCCATATATGG', IUPACUnambiguousDNA()) Or a single-motif MEME file, >>> from Bio import Motif >>> with open("Motif/meme.out") as handle: ... motif = Motif.read(handle, "MEME") ... >>> motif.consensus() Seq('CTCAATCGTA', IUPACUnambiguousDNA()) If the handle contains no records, or more than one record, an exception is raised: >>> from Bio import Motif >>> with open("Motif/alignace.out") as handle: ... motif = Motif.read(handle, "AlignAce") ... Traceback (most recent call last): ... ValueError: More than one motif found in handle If however you want the first record from a file containing multiple records this function would raise an exception (as shown in the example above). Instead use: >>> from Bio import Motif >>> with open("Motif/alignace.out") as handle: ... motif = next(Motif.parse(handle, "AlignAce")) ... >>> motif.consensus() Seq('TCTACGATTGAG', IUPACUnambiguousDNA()) Use the Bio.Motif.parse(handle, format) function if you want to read multiple records from the handle. """ iterator = parse(handle, format) try: first = next(iterator) except StopIteration: first = None if first is None: raise ValueError("No motifs found in handle") try: second = next(iterator) except StopIteration: second = None if second is not None: raise ValueError("More than one motif found in handle") return first if __name__ == "__main__": from Bio._utils import run_doctest run_doctest(verbose=0)	poojavade/Genomics_Docker	Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/Bio/Motif/__init__.py	Python	apache-2.0	5,092	[ "Biopython" ]	50f49464dde1ec92bb843b0d8ab985b5bf3bb24937d76bd3da88f8c18c7a305e
import sys sys.path.insert(1, "../../../") import h2o def link_incompatible_error(ip,port): print("Reading in original prostate data.") prostate = h2o.import_file(path=h2o.locate("smalldata/prostate/prostate.csv.zip")) print("Throw error when trying to create model with incompatible logit link.") try: h2o.model = h2o.glm(x=prostate[1:8], y=prostate[8], family="gaussian", link="logit") assert False, "expected an error" except EnvironmentError: assert True try: h2o.model = h2o.glm(x=prostate[1:8], y=prostate[8], family="tweedie", link="log") assert False, "expected an error" except EnvironmentError: assert True try: h2o.model = h2o.glm(x=prostate[2:9], y=prostate[1], family="binomial", link="inverse") assert False, "expected an error" except EnvironmentError: assert True if __name__ == "__main__": h2o.run_test(sys.argv, link_incompatible_error)	weaver-viii/h2o-3	h2o-py/tests/testdir_algos/glm/pyunit_link_incompatible_errorGLM.py	Python	apache-2.0	985	[ "Gaussian" ]	3a9fc598563419cb040746c614494c41bccc4ecf70c4859e4b17b2a3bb6fe05d
from setuptools import setup, find_packages import imp version = imp.load_source('crema.version', 'crema/version.py') setup( name='crema', version=version.version, description="Convolutional-recurrent estimators for music analysis", author='Brian McFee', url='http://github.com/bmcfee/crema', download_url='http://github.com/bmcfee/crema/releases', packages=find_packages(), package_data={'': ['models//.pkl', 'models//.h5', 'models//.json', 'models//.txt']}, long_description="Convolutional-recurrent estimators for music analysis", classifiers=[ "License :: OSI Approved :: ISC License (ISCL)", "Programming Language :: Python", "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Topic :: Software Development", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", ], keywords='audio music learning', license='ISC', install_requires=['six', 'librosa>=0.6', 'jams>=0.3', 'scikit-learn>=0.18', 'keras>=2.0', 'tensorflow>=1.0', 'mir_eval>=0.5', 'pumpp>=0.4', 'h5py>=2.7'], extras_require={ 'docs': ['numpydoc', 'sphinx'], 'tests': ['pytest', 'pytest-cov'], 'training': ['pescador>=2.0.1', 'muda'] } )	bmcfee/crema	setup.py	Python	bsd-2-clause	1,596	[ "Brian" ]	a4f22d0c98b76281108b318ac7ce0442d560c9c0f21ae153547a89aaa9087b6c
""" Django settings for Exchange project. For more information on this file, see https://docs.djangoproject.com/en/1.7/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.7/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os import uuid BASE_DIR = os.path.dirname(os.path.dirname(__file__)) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.7/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = '%p*m%z8z)jxkgvt1b0m)ha=e$uexa$i5o5-tifc=-t#9%7p+gg' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True MEDIA_URL = '/api/1.0/files/' MEDIA_ROOT = os.path.join(BASE_DIR, 'assets') TEMPLATE_DEBUG = True ALLOWED_HOSTS = [] SENDER = '84e847f929d34f66a94bf376cf30d12c' LOGIN_URL = 'login' LOGIN_REDIRECT_URL = 'dashboard' # Application definition INSTALLED_APPS = ( 'sslserver', 'flat', 'activelink', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'incidents', 'sending', 'corsheaders', 'oauth2_provider', 'rest_framework', 'widget_tweaks', 'datetimewidget', 'bootstrap_pagination', 'a_ppl_e', ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'corsheaders.middleware.CorsMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.middleware.locale.LocaleMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ) TEMPLATE_DIRS = [os.path.join(BASE_DIR, 'Exchange', 'templates')] TEMPLATE_CONTEXT_PROCESSORS = ( 'django.core.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.core.context_processors.media', 'django.core.context_processors.request', ) ROOT_URLCONF = 'Exchange.urls' WSGI_APPLICATION = 'Exchange.wsgi.application' # Database # https://docs.djangoproject.com/en/1.7/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Internationalization # https://docs.djangoproject.com/en/1.7/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.7/howto/static-files/ STATIC_URL = '/static/' # Additional locations of static files STATICFILES_DIRS = ( os.path.join(BASE_DIR, 'assets'), ) # RestFramework REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': ( 'oauth2_provider.ext.rest_framework.OAuth2Authentication', 'rest_framework.authentication.SessionAuthentication', ), # 'DEFAULT_PERMISSION_CLASSES': ( # 'rest_framework.permissions.IsAuthenticated', # ), 'PAGINATE_BY': 10, 'DEFAULT_PARSER_CLASSES': ( 'rest_framework.parsers.JSONParser', 'rest_framework.renderers.BrowsableAPIRenderer', ) } OAUTH2_PROVIDER = { # this is the list of available scopes 'SCOPES': {'subscriber': 'Subscriber', 'provider': 'Provider'} } CORS_ORIGIN_WHITELIST = ( 'localhost:8000', 'localhost:8800', ) OAUTH2_PROVIDER_APPLICATION_MODEL = 'oauth2_provider.Application' # TLP TLP_SCHEME = 'enisa' # US-CERT or ENISA TLP_DEFAULT_VALUE = 'green' # red, amber, green or white	SINTEF-Infosec/Incident-Information-Sharing-Tool	Exchange/settings.py	Python	apache-2.0	3,811	[ "Amber" ]	95a55d281d2c94d3d57a8c79eaceeff3567a526787b4272e1d7c3a5c4c5eef4b
# This file is part of PyEMMA. # # Copyright (c) 2015, 2014 Computational Molecular Biology Group, Freie Universitaet Berlin (GER) # # PyEMMA is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. from __future__ import absolute_import import warnings from pyemma._base.logging import Loggable from pyemma.util.types import is_string import mdtraj import six from pyemma.coordinates.data.featurization.util import (_parse_pairwise_input, _parse_groupwise_input) from .misc import CustomFeature import numpy as np __author__ = 'Frank Noe, Martin Scherer' __all__ = ['MDFeaturizer'] class MDFeaturizer(Loggable): r"""Extracts features from MD trajectories.""" def __init__(self, topfile): """extracts features from MD trajectories. Parameters ---------- topfile : str or mdtraj.Topology a path to a topology file (pdb etc.) or an mdtraj Topology() object """ self.topologyfile = None if isinstance(topfile, six.string_types): self.topology = (mdtraj.load(topfile)).topology self.topologyfile = topfile elif isinstance(topfile, mdtraj.Topology): self.topology = topfile else: raise ValueError("no valid topfile arg: type was %s, " "but only string or mdtraj.Topology allowed." % type(topfile)) self.active_features = [] self._dim = 0 self._showed_warning_empty_feature_list = False def __add_feature(self, f): # perform sanity checks if f.dimension == 0: self._logger.error("given an empty feature (eg. due to an empty/" "ineffective selection). Skipping it." " Feature desc: %s" % f.describe()) return if f not in self.active_features: self.active_features.append(f) else: self._logger.warning("tried to re-add the same feature %s" % f.__class__.__name__) def describe(self): """ Returns a list of strings, one for each feature selected, with human-readable descriptions of the features. Returns ------- labels : list of str An ordered list of strings, one for each feature selected, with human-readable descriptions of the features. """ all_labels = [] for f in self.active_features: all_labels += f.describe() return all_labels def select(self, selstring): """ Returns the indexes of atoms matching the given selection Parameters ---------- selstring : str Selection string. See mdtraj documentation for details: http://mdtraj.org/latest/atom_selection.html Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select(selstring) def select_Ca(self): """ Returns the indexes of all Ca-atoms Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select("name CA") def select_Backbone(self): """ Returns the indexes of backbone C, CA and N atoms Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select("backbone and (name C or name CA or name N)") def select_Heavy(self): """ Returns the indexes of all heavy atoms (Mass >= 2) Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select("mass >= 2") @staticmethod def pairs(sel, excluded_neighbors=0): """ Creates all pairs between indexes. Will exclude closest neighbors up to :py:obj:`excluded_neighbors` The self-pair (i,i) is always excluded Parameters ---------- sel : ndarray((n), dtype=int) array with selected atom indexes excluded_neighbors: int, default = 0 number of neighbors that will be excluded when creating the pairs Returns ------- sel : ndarray((m,2), dtype=int) m x 2 array with all pair indexes between different atoms that are at least :obj:`excluded_neighbors` indexes apart, i.e. if i is the index of an atom, the pairs [i,i-2], [i,i-1], [i,i], [i,i+1], [i,i+2], will not be in :py:obj:`sel` (n=excluded_neighbors) if :py:obj:`excluded_neighbors` = 2. Moreover, the list is non-redundant,i.e. if [i,j] is in sel, then [j,i] is not. """ assert isinstance(excluded_neighbors,int) p = [] for i in range(len(sel)): for j in range(i + 1, len(sel)): # get ordered pair I = sel[i] J = sel[j] if (I > J): I = sel[j] J = sel[i] # exclude 1 and 2 neighbors if (J > I + excluded_neighbors): p.append([I, J]) return np.array(p) def _check_indices(self, pair_inds, pair_n=2): """ensure pairs are valid (shapes, all atom indices available?, etc.) """ pair_inds = np.array(pair_inds).astype(dtype=np.int, casting='safe') if pair_inds.ndim != 2: raise ValueError("pair indices has to be a matrix.") if pair_inds.shape[1] != pair_n: raise ValueError("pair indices shape has to be (x, %i)." % pair_n) if pair_inds.max() > self.topology.n_atoms: raise ValueError("index out of bounds: %i." " Maximum atom index available: %i" % (pair_inds.max(), self.topology.n_atoms)) return pair_inds def add_all(self): """ Adds all atom coordinates to the feature list. The coordinates are flattened as follows: [x1, y1, z1, x2, y2, z2, ...] """ # TODO: add possibility to align to a reference structure self.add_selection(list(range(self.topology.n_atoms))) def add_selection(self, indexes): """ Adds the coordinates of the selected atom indexes to the feature list. The coordinates of the selection [1, 2, ...] are flattened as follows: [x1, y1, z1, x2, y2, z2, ...] Parameters ---------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ # TODO: add possibility to align to a reference structure from .misc import SelectionFeature f = SelectionFeature(self.topology, indexes) self.__add_feature(f) def add_distances(self, indices, periodic=True, indices2=None): r""" Adds the distances between atoms to the feature list. Parameters ---------- indices : can be of two types: ndarray((n, 2), dtype=int): n x 2 array with the pairs of atoms between which the distances shall be computed iterable of integers (either list or ndarray(n, dtype=int)): indices (not pairs of indices) of the atoms between which the distances shall be computed. periodic : optional, boolean, default is True If periodic is True and the trajectory contains unitcell information, distances will be computed under the minimum image convention. indices2: iterable of integers (either list or ndarray(n, dtype=int)), optional: Only has effect if :py:obj:`indices` is an iterable of integers. Instead of the above behaviour, only the distances between the atoms in :py:obj:`indices` and :py:obj:`indices2` will be computed. .. note:: When using the iterable of integers input, :py:obj:`indices` and :py:obj:`indices2` will be sorted numerically and made unique before converting them to a pairlist. Please look carefully at the output of :py:func:`describe()` to see what features exactly have been added. """ from .distances import DistanceFeature atom_pairs = _parse_pairwise_input( indices, indices2, self._logger, fname='add_distances()') atom_pairs = self._check_indices(atom_pairs) f = DistanceFeature(self.topology, atom_pairs, periodic=periodic) self.__add_feature(f) def add_distances_ca(self, periodic=True, excluded_neighbors=2): """ Adds the distances between all Ca's to the feature list. Parameters ---------- periodic : boolean, default is True Use the minimum image convetion when computing distances excluded_neighbors : int, default is 2 Number of exclusions when compiling the list of pairs. Two CA-atoms are considered neighbors if they belong to adjacent residues. """ # Atom indices for CAs at_idxs_ca = self.select_Ca() # Residue indices for residues contatinig CAs res_idxs_ca = [self.topology.atom(ca).residue.index for ca in at_idxs_ca] # Pairs of those residues, with possibility to exclude neighbors res_idxs_ca_pairs = self.pairs(res_idxs_ca, excluded_neighbors=excluded_neighbors) # Mapping back pairs of residue indices to pairs of CA indices distance_indexes = [] for ri, rj in res_idxs_ca_pairs: distance_indexes.append([self.topology.residue(ri).atom('CA').index, self.topology.residue(rj).atom('CA').index ]) distance_indexes = np.array(distance_indexes) self.add_distances(distance_indexes, periodic=periodic) def add_inverse_distances(self, indices, periodic=True, indices2=None): """ Adds the inverse distances between atoms to the feature list. Parameters ---------- indices : can be of two types: ndarray((n, 2), dtype=int): n x 2 array with the pairs of atoms between which the inverse distances shall be computed iterable of integers (either list or ndarray(n, dtype=int)): indices (not pairs of indices) of the atoms between which the inverse distances shall be computed. periodic : optional, boolean, default is True If periodic is True and the trajectory contains unitcell information, distances will be computed under the minimum image convention. indices2: iterable of integers (either list or ndarray(n, dtype=int)), optional: Only has effect if :py:obj:`indices` is an iterable of integers. Instead of the above behaviour, only the inverse distances between the atoms in :py:obj:`indices` and :py:obj:`indices2` will be computed. .. note:: When using the iterable of integers input, :py:obj:`indices` and :py:obj:`indices2` will be sorted numerically and made unique before converting them to a pairlist. Please look carefully at the output of :py:func:`describe()` to see what features exactly have been added. """ from .distances import InverseDistanceFeature atom_pairs = _parse_pairwise_input( indices, indices2, self._logger, fname='add_inverse_distances()') atom_pairs = self._check_indices(atom_pairs) f = InverseDistanceFeature(self.topology, atom_pairs, periodic=periodic) self.__add_feature(f) def add_contacts(self, indices, indices2=None, threshold=0.3, periodic=True, count_contacts=False): r""" Adds the contacts to the feature list. Parameters ---------- indices : can be of two types: ndarray((n, 2), dtype=int): n x 2 array with the pairs of atoms between which the contacts shall be computed iterable of integers (either list or ndarray(n, dtype=int)): indices (not pairs of indices) of the atoms between which the contacts shall be computed. indices2: iterable of integers (either list or ndarray(n, dtype=int)), optional: Only has effect if :py:obj:`indices` is an iterable of integers. Instead of the above behaviour, only the contacts between the atoms in :py:obj:`indices` and :py:obj:`indices2` will be computed. threshold : float, optional, default = .3 distances below this threshold (in nm) will result in a feature 1.0, distances above will result in 0.0. The default is set to .3 nm (3 Angstrom) periodic : boolean, default True use the minimum image convention if unitcell information is available count_contacts : boolean, default False If set to true, this feature will return the number of formed contacts (and not feature values with either 1.0 or 0) The ouput of this feature will be of shape (Nt,1), and not (Nt, nr_of_contacts) .. note:: When using the iterable of integers input, :py:obj:`indices` and :py:obj:`indices2` will be sorted numerically and made unique before converting them to a pairlist. Please look carefully at the output of :py:func:`describe()` to see what features exactly have been added. """ from .distances import ContactFeature atom_pairs = _parse_pairwise_input( indices, indices2, self._logger, fname='add_contacts()') atom_pairs = self._check_indices(atom_pairs) f = ContactFeature(self.topology, atom_pairs, threshold, periodic, count_contacts) self.__add_feature(f) def add_residue_mindist(self, residue_pairs='all', scheme='closest-heavy', ignore_nonprotein=True, threshold=None, periodic=True): r""" Adds the minimum distance between residues to the feature list. See below how the minimum distance can be defined. If the topology generated out of :py:obj:`topfile` contains information on periodic boundary conditions, the minimum image convention will be used when computing distances. Parameters ---------- residue_pairs : can be of two types: 'all' Computes distances between all pairs of residues excluding first and second neighbors ndarray((n, 2), dtype=int): n x 2 array with the pairs residues for which distances will be computed scheme : 'ca', 'closest', 'closest-heavy', default is closest-heavy Within a residue, determines the sub-group atoms that will be considered when computing distances ignore_nonprotein : boolean, default True Ignore residues that are not of protein type (e.g. water molecules, post-traslational modifications etc) threshold : float, optional, default is None distances below this threshold (in nm) will result in a feature 1.0, distances above will result in 0.0. If left to None, the numerical value will be returned periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. .. note:: Using :py:obj:`scheme` = 'closest' or 'closest-heavy' with :py:obj:`residue pairs` = 'all' will compute nearly all interatomic distances, for every frame, before extracting the closest pairs. This can be very time consuming. Those schemes are intended to be used with a subset of residues chosen via :py:obj:`residue_pairs`. """ from .distances import ResidueMinDistanceFeature if scheme != 'ca' and is_string(residue_pairs): if residue_pairs == 'all': self._logger.warning("Using all residue pairs with schemes like closest or closest-heavy is " "very time consuming. Consider reducing the residue pairs") f = ResidueMinDistanceFeature(self.topology, residue_pairs, scheme, ignore_nonprotein, threshold, periodic) self.__add_feature(f) def add_group_mindist(self, group_definitions, group_pairs='all', threshold=None, periodic=True, ): r""" Adds the minimum distance between groups of atoms to the feature list. If the groups of atoms are identical to residues, use :py:obj:`add_residue_mindist <pyemma.coordinates.data.featurizer.MDFeaturizer.add_residue_mindist>`. Parameters ---------- group_definition : list of 1D-arrays/iterables containing the group definitions via atom indices. If there is only one group_definition, it is assumed the minimum distance within this group (excluding the self-distance) is wanted. In this case, :py:obj:`group_pairs` is ignored. group_pairs : Can be of two types: 'all' Computes minimum distances between all pairs of groups contained in the group definitions ndarray((n, 2), dtype=int): n x 2 array with the pairs of groups for which the minimum distances will be computed. threshold : float, optional, default is None distances below this threshold (in nm) will result in a feature 1.0, distances above will result in 0.0. If left to None, the numerical value will be returned periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .distances import GroupMinDistanceFeature # Some thorough input checking and reformatting group_definitions, group_pairs, distance_list, group_identifiers = \ _parse_groupwise_input(group_definitions, group_pairs, self._logger, 'add_group_mindist') distance_list = self._check_indices(distance_list) f = GroupMinDistanceFeature(self.topology, group_definitions, group_pairs, distance_list, group_identifiers, threshold, periodic) self.__add_feature(f) def add_angles(self, indexes, deg=False, cossin=False, periodic=True): """ Adds the list of angles to the feature list Parameters ---------- indexes : np.ndarray, shape=(num_pairs, 3), dtype=int an array with triplets of atom indices deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import AngleFeature indexes = self._check_indices(indexes, pair_n=3) f = AngleFeature(self.topology, indexes, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_dihedrals(self, indexes, deg=False, cossin=False, periodic=True): """ Adds the list of dihedrals to the feature list Parameters ---------- indexes : np.ndarray, shape=(num_pairs, 4), dtype=int an array with quadruplets of atom indices deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import DihedralFeature indexes = self._check_indices(indexes, pair_n=4) f = DihedralFeature(self.topology, indexes, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_backbone_torsions(self, selstr=None, deg=False, cossin=False, periodic=True): """ Adds all backbone phi/psi angles or the ones specified in :obj:`selstr` to the feature list. Parameters ---------- selstr : str, optional, default = "" selection string specifying the atom selection used to specify a specific set of backbone angles If "" (default), all phi/psi angles found in the topology will be computed deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import BackboneTorsionFeature f = BackboneTorsionFeature( self.topology, selstr=selstr, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_chi1_torsions(self, selstr="", deg=False, cossin=False, periodic=True): """ Adds all chi1 angles or the ones specified in :obj:`selstr` to the feature list. Parameters ---------- selstr : str, optional, default = "" selection string specifying the atom selection used to specify a specific set of backbone angles If "" (default), all chi1 angles found in the topology will be computed deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import Chi1TorsionFeature f = Chi1TorsionFeature( self.topology, selstr=selstr, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_custom_feature(self, feature): """ Adds a custom feature to the feature list. Parameters ---------- feature : object an object with interface like CustomFeature (map, describe methods) """ if feature.dimension <= 0: raise ValueError("Dimension has to be positive. " "Please override dimension attribute in feature!") if not hasattr(feature, 'map'): raise ValueError("no map method in given feature") else: if not callable(getattr(feature, 'map')): raise ValueError("map exists but is not a method") self.__add_feature(feature) def add_minrmsd_to_ref(self, ref, ref_frame=0, atom_indices=None, precentered=False): r""" Adds the minimum root-mean-square-deviation (minrmsd) with respect to a reference structure to the feature list. Parameters ---------- ref: Reference structure for computing the minrmsd. Can be of two types: 1. :py:obj:`mdtraj.Trajectory` object 2. filename for mdtraj to load. In this case, only the :py:obj:`ref_frame` of that file will be used. ref_frame: integer, default=0 Reference frame of the filename specified in :py:obj:`ref`. This parameter has no effect if :py:obj:`ref` is not a filename. atom_indices: array_like, default=None Atoms that will be used for: 1. aligning the target and reference geometries. 2. computing rmsd after the alignment. If left to None, all atoms of :py:obj:`ref` will be used. precentered: bool, default=False Use this boolean at your own risk to let mdtraj know that the target conformations are already centered at the origin, i.e., their (uniformly weighted) center of mass lies at the origin. This will speed up the computation of the rmsd. """ from .misc import MinRmsdFeature f = MinRmsdFeature(ref, ref_frame=ref_frame, atom_indices=atom_indices, topology=self.topology, precentered=precentered) self.__add_feature(f) def add_custom_func(self, func, dim, args, kwargs): """ adds a user defined function to extract features Parameters ---------- func : function a user-defined function, which accepts mdtraj.Trajectory object as first parameter and as many optional and named arguments as desired. Has to return a numpy.ndarray dim : int output dimension of :py:obj:`function` args : any number of positional arguments these have to be in the same order as :py:obj:`func` is expecting them kwargs : dictionary named arguments passed to func """ f = CustomFeature(func, dim=dim, args, *kwargs) self.add_custom_feature(f) def dimension(self): """ current dimension due to selected features Returns ------- dim : int total dimension due to all selection features """ dim = sum(f.dimension for f in self.active_features) return dim def transform(self, traj): """ Maps an mdtraj Trajectory object to the selected output features Parameters ---------- traj : mdtraj Trajectory Trajectory object used as an input Returns ------- out : ndarray((T, n), dtype=float32) Output features: For each of T time steps in the given trajectory, a vector with all n output features selected. """ # if there are no features selected, return given trajectory if len(self.active_features) == 0: if not self._showed_warning_empty_feature_list: warnings.warn("You have no features selected." " Returning plain coordinates.") self._showed_warning_empty_feature_list = True s = traj.xyz.shape new_shape = (s[0], s[1] s[2]) return traj.xyz.reshape(new_shape) # handle empty chunks (which might occur due to time lagged access if traj.xyz.shape[0] == 0: return np.empty((0, self.dimension())) # otherwise build feature vector. feature_vec = [] # TODO: consider parallel evaluation computation here, this effort is # only worth it, if computation time dominates memory transfers for f in self.active_features: # perform sanity checks for custom feature input if isinstance(f, CustomFeature): # NOTE: casting=safe raises in numpy>=1.9 vec = f.transform(traj).astype(np.float32, casting='safe') if vec.shape[0] == 0: vec = np.empty((0, f.dimension)) if not isinstance(vec, np.ndarray): raise ValueError('Your custom feature %s did not return' ' a numpy.ndarray!' % str(f.describe())) if not vec.ndim == 2: raise ValueError('Your custom feature %s did not return' ' a 2d array. Shape was %s' % (str(f.describe()), str(vec.shape))) if not vec.shape[0] == traj.xyz.shape[0]: raise ValueError('Your custom feature %s did not return' ' as many frames as it received!' 'Input was %i, output was %i' % (str(f.describe()), traj.xyz.shape[0], vec.shape[0])) else: vec = f.transform(traj).astype(np.float32) feature_vec.append(vec) if len(feature_vec) > 1: res = np.hstack(feature_vec) else: res = feature_vec[0] return res	gph82/PyEMMA	pyemma/coordinates/data/featurization/featurizer.py	Python	lgpl-3.0	30,879	[ "MDTraj" ]	49dc7204a2fb3d28b1d66bed6ea44ace927f8d09f42d9f001d7bcfc79ad3a925
from galaxy.managers import base as manager_base class LDDAManager( manager_base.ModelManager ): """ A fairly sparse manager for LDDAs. """ def __init__( self ): """ Set up and initialize other managers needed by lddas. """ pass def get( self, trans, id, check_accessible=True ): return manager_base.get_object( trans, id, 'LibraryDatasetDatasetAssociation', check_ownership=False, check_accessible=check_accessible )	mikel-egana-aranguren/SADI-Galaxy-Docker	galaxy-dist/lib/galaxy/managers/lddas.py	Python	gpl-3.0	518	[ "Galaxy" ]	4b54a33fb41741bb6224aa150894db633364138649df440007428d39e30e0dd4
# Orca # # Copyright 2006-2008 Sun Microsystems Inc. # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the # Free Software Foundation, Inc., Franklin Street, Fifth Floor, # Boston MA 02110-1301 USA. """Provides an HTTP server for Orca. This currently serves mainly as something that self-voicing applications can use as their speech service.""" __id__ = "$Id$" __version__ = "$Revision$" __date__ = "$Date$" __copyright__ = "Copyright (c) 2006-2008 Sun Microsystems Inc." __license__ = "LGPL" import threading import BaseHTTPServer import debug import orca_platform import settings import speech _httpRequestThread = None # Handlers for logging speech and braille output. # loggingFileHandlers = {} loggingStreamHandlers = {} class _HTTPRequestHandler(BaseHTTPServer.BaseHTTPRequestHandler): """Provides support for communicating with Orca via HTTP. This is mainly to support self-voicing applications that want to use Orca as a speech service. The protocol is simple: POST content is 'stop', 'speak:<text>', or 'isSpeaking'. To test this, run: wget --post-data='speak:hello world' localhost:20433 """ def log_request(self, code=None, size=None): """Override to avoid getting a log message on stdout for each GET, POST, etc. request""" pass def do_GET(self): self.send_response(200) self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write("<html><body><p>Orca %s</p></body></html>" \ % orca_platform.version) def do_POST(self): contentLength = self.headers.getheader('content-length') if contentLength: contentLength = int(contentLength) inputBody = self.rfile.read(contentLength) debug.println(debug.LEVEL_FINEST, "httpserver._HTTPRequestHandler received %s" \ % inputBody) if inputBody.startswith("speak:"): speech.speak(inputBody[6:]) self.send_response(200, 'OK') elif inputBody == "stop": speech.stop() self.send_response(200, 'OK') elif inputBody == "isSpeaking": self.send_response(200, 'OK') self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write("%s" % speech.isSpeaking()) else: debug.println(debug.LEVEL_FINEST, "httpserver._HTTPRequestHandler received no data") class _HTTPRequestThread(threading.Thread): """Runs a _HTTPRequestHandler in a separate thread.""" def run(self): """Try to start an HTTP server on settings.httpServerPort. If this fails, retry settings.maxHttpServerRetries times, each time incrementing the server port number by 1. If we are still unable to start a server, just fail gracefully. """ portNo = settings.httpServerPort connected = False while not connected and \ (portNo < settings.httpServerPort + settings.maxHttpServerRetries): try: httpd = BaseHTTPServer.HTTPServer(('', portNo), _HTTPRequestHandler) connected = True except: if portNo == settings.httpServerPort: debug.printException(debug.LEVEL_WARNING) debug.println(debug.LEVEL_WARNING, "httpserver._HTTPRequestThread unable to start server " \ "on port %d" % portNo) portNo += 1 if not connected: debug.println(debug.LEVEL_WARNING, "httpserver._HTTPRequestThread server startup failed.") else: httpd.serve_forever() def init(): """Creates an HTTP server that listens for speak commands from a separate port defined by settings.httpServerPort. We run this as a daemon so it will die automatically when orca dies.""" global _httpRequestThread if settings.httpServerPort and (not _httpRequestThread): try: _httpRequestThread = _HTTPRequestThread() _httpRequestThread.setDaemon(True) _httpRequestThread.start() except: debug.printException(debug.LEVEL_WARNING) def shutdown(): """Stops the HTTP server. [[[WDW - not implemented yet.]]]""" pass	Alberto-Beralix/Beralix	i386-squashfs-root/usr/share/pyshared/orca/httpserver.py	Python	gpl-3.0	5,107	[ "ORCA" ]	356d67d915e45a058b3e20f617101c38246fab42fb4dcc54af998eca3affba62
import re from pygments.lexers.theorem import IsabelleLexer from pygments.lexer import RegexLexer, inherit, bygroups, words from pygments.token import * from . import encoding __all__ = ['IsarLexer'] class IsarLexer(IsabelleLexer): name = 'Isabelle/Isar' keyword_cartouche_text = ('text', 'txt', 'text_raw', 'chapter', 'section', 'subsection', 'subsubsection', 'paragraph', 'subparagraph', ) tokens = { 'root': [ (words(keyword_cartouche_text, prefix=r'\b', suffix=r'(%\w+)?(\s\\<open>)'), bygroups(Keyword, Comment.Preproc, Comment), 'cartouche-text'), (r'\\<comment>.$', Comment), (r'%\w+', Comment.Preproc), (r'\\<open>', String.Other, 'fact'), inherit, ], 'cartouche-text': [ (r'[^\\@]', Comment), (r'(@\{)(\w+)', bygroups(String.Other, Keyword), 'antiquotation'), (r'\\<open>', Text, '#push'), (r'\\<close>', Comment, '#pop'), (r'\\<[\^\w]+>', Comment.Symbol), (r'\\', Comment), ], 'antiquotation': [ (r'[^\{\}\\]', Text), (r'\{', String.Other, '#push'), (r'\}', String.Other, '#pop'), (r'\\<[\^\w]+>', String.Symbol), (r'\\', Text), ], 'fact': [ (r'\\<close>', String.Other, '#pop'), inherit, ], } def get_tokens_unprocessed(self, text): for index, token, value in RegexLexer.get_tokens_unprocessed(self, text): value = isar_decode(value) yield index, token, value def isar_decode(raw): global symbol_table if symbol_table is None: symbol_table = {} for line in symbols_raw.splitlines(): if line: if re.match(r"^#", line): continue m = re.match(r"^(\\<.>)\s+code:\s+0x([0-9a-f]+).$", line) assert m, "Failed to parse " + line n = int(m.group(2), 16) if n < 0x10000: symbol_table[m.group(1)] = chr(n) if isinstance(raw, str): raw = encoding.get_unicode(raw) def repl(m): if m.group(0) in symbol_table: return symbol_table[m.group(0)] else: return m.group(0) return re.sub(r"\\<[\^a-zA-Z]+>", repl, raw) # ~~/etc/symbols from Isabelle2016 symbol_table = None symbols_raw = """ \<zero> code: 0x01d7ec group: digit \<one> code: 0x01d7ed group: digit \<two> code: 0x01d7ee group: digit \<three> code: 0x01d7ef group: digit \<four> code: 0x01d7f0 group: digit \<five> code: 0x01d7f1 group: digit \<six> code: 0x01d7f2 group: digit \<seven> code: 0x01d7f3 group: digit \<eight> code: 0x01d7f4 group: digit \<nine> code: 0x01d7f5 group: digit \<A> code: 0x01d49c group: letter \<B> code: 0x00212c group: letter \<C> code: 0x01d49e group: letter \<D> code: 0x01d49f group: letter \<E> code: 0x002130 group: letter \<F> code: 0x002131 group: letter \<G> code: 0x01d4a2 group: letter \<H> code: 0x00210b group: letter \<I> code: 0x002110 group: letter \<J> code: 0x01d4a5 group: letter \<K> code: 0x01d4a6 group: letter \<L> code: 0x002112 group: letter \<M> code: 0x002133 group: letter \<N> code: 0x01d4a9 group: letter \<O> code: 0x01d4aa group: letter \<P> code: 0x01d4ab group: letter \<Q> code: 0x01d4ac group: letter \<R> code: 0x00211b group: letter \<S> code: 0x01d4ae group: letter \<T> code: 0x01d4af group: letter \<U> code: 0x01d4b0 group: letter \<V> code: 0x01d4b1 group: letter \<W> code: 0x01d4b2 group: letter \<X> code: 0x01d4b3 group: letter \<Y> code: 0x01d4b4 group: letter \<Z> code: 0x01d4b5 group: letter \<a> code: 0x01d5ba group: letter \<b> code: 0x01d5bb group: letter \<c> code: 0x01d5bc group: letter \<d> code: 0x01d5bd group: letter \<e> code: 0x01d5be group: letter \<f> code: 0x01d5bf group: letter \<g> code: 0x01d5c0 group: letter \<h> code: 0x01d5c1 group: letter \<i> code: 0x01d5c2 group: letter \<j> code: 0x01d5c3 group: letter \<k> code: 0x01d5c4 group: letter \<l> code: 0x01d5c5 group: letter \<m> code: 0x01d5c6 group: letter \<n> code: 0x01d5c7 group: letter \<o> code: 0x01d5c8 group: letter \<p> code: 0x01d5c9 group: letter \<q> code: 0x01d5ca group: letter \<r> code: 0x01d5cb group: letter \<s> code: 0x01d5cc group: letter \<t> code: 0x01d5cd group: letter \<u> code: 0x01d5ce group: letter \<v> code: 0x01d5cf group: letter \<w> code: 0x01d5d0 group: letter \<x> code: 0x01d5d1 group: letter \<y> code: 0x01d5d2 group: letter \<z> code: 0x01d5d3 group: letter \<AA> code: 0x01d504 group: letter \<BB> code: 0x01d505 group: letter \<CC> code: 0x00212d group: letter \<DD> code: 0x01d507 group: letter \<EE> code: 0x01d508 group: letter \<FF> code: 0x01d509 group: letter \<GG> code: 0x01d50a group: letter \<HH> code: 0x00210c group: letter \<II> code: 0x002111 group: letter \<JJ> code: 0x01d50d group: letter \<KK> code: 0x01d50e group: letter \<LL> code: 0x01d50f group: letter \<MM> code: 0x01d510 group: letter \<NN> code: 0x01d511 group: letter \<OO> code: 0x01d512 group: letter \<PP> code: 0x01d513 group: letter \<QQ> code: 0x01d514 group: letter \<RR> code: 0x00211c group: letter \<SS> code: 0x01d516 group: letter \<TT> code: 0x01d517 group: letter \<UU> code: 0x01d518 group: letter \<VV> code: 0x01d519 group: letter \<WW> code: 0x01d51a group: letter \<XX> code: 0x01d51b group: letter \<YY> code: 0x01d51c group: letter \<ZZ> code: 0x002128 group: letter \<aa> code: 0x01d51e group: letter \<bb> code: 0x01d51f group: letter \<cc> code: 0x01d520 group: letter \<dd> code: 0x01d521 group: letter \<ee> code: 0x01d522 group: letter \<ff> code: 0x01d523 group: letter \<gg> code: 0x01d524 group: letter \<hh> code: 0x01d525 group: letter \<ii> code: 0x01d526 group: letter \<jj> code: 0x01d527 group: letter \<kk> code: 0x01d528 group: letter \<ll> code: 0x01d529 group: letter \<mm> code: 0x01d52a group: letter \<nn> code: 0x01d52b group: letter \<oo> code: 0x01d52c group: letter \<pp> code: 0x01d52d group: letter \<qq> code: 0x01d52e group: letter \<rr> code: 0x01d52f group: letter \<ss> code: 0x01d530 group: letter \<tt> code: 0x01d531 group: letter \<uu> code: 0x01d532 group: letter \<vv> code: 0x01d533 group: letter \<ww> code: 0x01d534 group: letter \<xx> code: 0x01d535 group: letter \<yy> code: 0x01d536 group: letter \<zz> code: 0x01d537 group: letter \<alpha> code: 0x0003b1 group: greek \<beta> code: 0x0003b2 group: greek \<gamma> code: 0x0003b3 group: greek \<delta> code: 0x0003b4 group: greek \<epsilon> code: 0x0003b5 group: greek \<zeta> code: 0x0003b6 group: greek \<eta> code: 0x0003b7 group: greek \<theta> code: 0x0003b8 group: greek \<iota> code: 0x0003b9 group: greek \<kappa> code: 0x0003ba group: greek \<lambda> code: 0x0003bb group: greek abbrev: % \<mu> code: 0x0003bc group: greek \<nu> code: 0x0003bd group: greek \<xi> code: 0x0003be group: greek \<pi> code: 0x0003c0 group: greek \<rho> code: 0x0003c1 group: greek \<sigma> code: 0x0003c3 group: greek \<tau> code: 0x0003c4 group: greek \<upsilon> code: 0x0003c5 group: greek \<phi> code: 0x0003c6 group: greek \<chi> code: 0x0003c7 group: greek \<psi> code: 0x0003c8 group: greek \<omega> code: 0x0003c9 group: greek \<Gamma> code: 0x000393 group: greek \<Delta> code: 0x000394 group: greek \<Theta> code: 0x000398 group: greek \<Lambda> code: 0x00039b group: greek \<Xi> code: 0x00039e group: greek \<Pi> code: 0x0003a0 group: greek \<Sigma> code: 0x0003a3 group: greek \<Upsilon> code: 0x0003a5 group: greek \<Phi> code: 0x0003a6 group: greek \<Psi> code: 0x0003a8 group: greek \<Omega> code: 0x0003a9 group: greek \<bool> code: 0x01d539 group: letter \<complex> code: 0x002102 group: letter \<nat> code: 0x002115 group: letter \<rat> code: 0x00211a group: letter \<real> code: 0x00211d group: letter \<int> code: 0x002124 group: letter \<leftarrow> code: 0x002190 group: arrow abbrev: <. \<longleftarrow> code: 0x0027f5 group: arrow abbrev: <. \<longlongleftarrow> code: 0x00290e group: arrow abbrev: <. \<longlonglongleftarrow> code: 0x0021e0 group: arrow abbrev: <. \<rightarrow> code: 0x002192 group: arrow abbrev: .> abbrev: -> \<longrightarrow> code: 0x0027f6 group: arrow abbrev: .> abbrev: --> \<longlongrightarrow> code: 0x00290f group: arrow abbrev: .> abbrev: ---> \<longlonglongrightarrow> code: 0x0021e2 group: arrow abbrev: .> abbrev: ---> \<Leftarrow> code: 0x0021d0 group: arrow abbrev: <. \<Longleftarrow> code: 0x0027f8 group: arrow abbrev: <. \<Lleftarrow> code: 0x0021da group: arrow abbrev: <. \<Rightarrow> code: 0x0021d2 group: arrow abbrev: .> abbrev: => \<Longrightarrow> code: 0x0027f9 group: arrow abbrev: .> abbrev: ==> \<Rrightarrow> code: 0x0021db group: arrow abbrev: .> \<leftrightarrow> code: 0x002194 group: arrow abbrev: <> abbrev: <-> \<longleftrightarrow> code: 0x0027f7 group: arrow abbrev: <> abbrev: <-> abbrev: <--> \<Leftrightarrow> code: 0x0021d4 group: arrow abbrev: <> \<Longleftrightarrow> code: 0x0027fa group: arrow abbrev: <> \<mapsto> code: 0x0021a6 group: arrow abbrev: .> abbrev: \|-> \<longmapsto> code: 0x0027fc group: arrow abbrev: .> abbrev: \|--> \<midarrow> code: 0x002500 group: arrow abbrev: <> \<Midarrow> code: 0x002550 group: arrow abbrev: <> \<hookleftarrow> code: 0x0021a9 group: arrow abbrev: <. \<hookrightarrow> code: 0x0021aa group: arrow abbrev: .> \<leftharpoondown> code: 0x0021bd group: arrow abbrev: <. \<rightharpoondown> code: 0x0021c1 group: arrow abbrev: .> \<leftharpoonup> code: 0x0021bc group: arrow abbrev: <. \<rightharpoonup> code: 0x0021c0 group: arrow abbrev: .> \<rightleftharpoons> code: 0x0021cc group: arrow abbrev: <> abbrev: == \<leadsto> code: 0x00219d group: arrow abbrev: .> abbrev: ~> \<downharpoonleft> code: 0x0021c3 group: arrow \<downharpoonright> code: 0x0021c2 group: arrow \<upharpoonleft> code: 0x0021bf group: arrow #\<upharpoonright> code: 0x0021be group: arrow \<restriction> code: 0x0021be group: punctuation \<Colon> code: 0x002237 group: punctuation \<up> code: 0x002191 group: arrow \<Up> code: 0x0021d1 group: arrow \<down> code: 0x002193 group: arrow \<Down> code: 0x0021d3 group: arrow \<updown> code: 0x002195 group: arrow \<Updown> code: 0x0021d5 group: arrow \<langle> code: 0x0027e8 group: punctuation abbrev: << \<rangle> code: 0x0027e9 group: punctuation abbrev: >> \<lceil> code: 0x002308 group: punctuation abbrev: [. \<rceil> code: 0x002309 group: punctuation abbrev: .] \<lfloor> code: 0x00230a group: punctuation abbrev: [. \<rfloor> code: 0x00230b group: punctuation abbrev: .] \<lparr> code: 0x002987 group: punctuation abbrev: (\| \<rparr> code: 0x002988 group: punctuation abbrev: \|) \<lbrakk> code: 0x0027e6 group: punctuation abbrev: [\| \<rbrakk> code: 0x0027e7 group: punctuation abbrev: \|] \<lbrace> code: 0x002983 group: punctuation abbrev: {\| \<rbrace> code: 0x002984 group: punctuation abbrev: \|} \<guillemotleft> code: 0x0000ab group: punctuation abbrev: << \<guillemotright> code: 0x0000bb group: punctuation abbrev: >> \<bottom> code: 0x0022a5 group: logic \<top> code: 0x0022a4 group: logic \<and> code: 0x002227 group: logic abbrev: /\ abbrev: & \<And> code: 0x0022c0 group: logic abbrev: !! \<or> code: 0x002228 group: logic abbrev: \/ abbrev: \| \<Or> code: 0x0022c1 group: logic abbrev: ?? \<forall> code: 0x002200 group: logic abbrev: ! abbrev: ALL \<exists> code: 0x002203 group: logic abbrev: ? abbrev: EX \<nexists> code: 0x002204 group: logic abbrev: ~? \<not> code: 0x0000ac group: logic abbrev: ~ \<box> code: 0x0025a1 group: logic \<diamond> code: 0x0025c7 group: logic \<diamondop> code: 0x0022c4 group: operator \<turnstile> code: 0x0022a2 group: relation abbrev: \|- \<Turnstile> code: 0x0022a8 group: relation abbrev: \|= \<tturnstile> code: 0x0022a9 group: relation abbrev: \|- \<TTurnstile> code: 0x0022ab group: relation abbrev: \|= \<stileturn> code: 0x0022a3 group: relation abbrev: -\| \<surd> code: 0x00221a group: relation \<le> code: 0x002264 group: relation abbrev: <= \<ge> code: 0x002265 group: relation abbrev: >= \<lless> code: 0x00226a group: relation abbrev: << \<ggreater> code: 0x00226b group: relation abbrev: >> \<lesssim> code: 0x002272 group: relation \<greatersim> code: 0x002273 group: relation \<lessapprox> code: 0x002a85 group: relation \<greaterapprox> code: 0x002a86 group: relation \<in> code: 0x002208 group: relation abbrev: : \<notin> code: 0x002209 group: relation abbrev: ~: \<subset> code: 0x002282 group: relation \<supset> code: 0x002283 group: relation \<subseteq> code: 0x002286 group: relation abbrev: (= \<supseteq> code: 0x002287 group: relation abbrev: )= \<sqsubset> code: 0x00228f group: relation \<sqsupset> code: 0x002290 group: relation \<sqsubseteq> code: 0x002291 group: relation abbrev: [= \<sqsupseteq> code: 0x002292 group: relation abbrev: ]= \<inter> code: 0x002229 group: operator abbrev: Int \<Inter> code: 0x0022c2 group: operator abbrev: Inter abbrev: INT \<union> code: 0x00222a group: operator abbrev: Un \<Union> code: 0x0022c3 group: operator abbrev: Union abbrev: UN \<squnion> code: 0x002294 group: operator \<Squnion> code: 0x002a06 group: operator abbrev: SUP \<sqinter> code: 0x002293 group: operator \<Sqinter> code: 0x002a05 group: operator abbrev: INF \<setminus> code: 0x002216 group: operator \<propto> code: 0x00221d group: operator \<uplus> code: 0x00228e group: operator \<Uplus> code: 0x002a04 group: operator \<noteq> code: 0x002260 group: relation abbrev: ~= \<sim> code: 0x00223c group: relation \<doteq> code: 0x002250 group: relation abbrev: .= \<simeq> code: 0x002243 group: relation \<approx> code: 0x002248 group: relation \<asymp> code: 0x00224d group: relation \<cong> code: 0x002245 group: relation \<smile> code: 0x002323 group: relation \<equiv> code: 0x002261 group: relation abbrev: == \<frown> code: 0x002322 group: relation \<Join> code: 0x0022c8 \<bowtie> code: 0x002a1d \<prec> code: 0x00227a group: relation \<succ> code: 0x00227b group: relation \<preceq> code: 0x00227c group: relation \<succeq> code: 0x00227d group: relation \<parallel> code: 0x002225 group: punctuation abbrev: \|\| \<bar> code: 0x0000a6 group: punctuation abbrev: \|\| \<plusminus> code: 0x0000b1 group: operator \<minusplus> code: 0x002213 group: operator \<times> code: 0x0000d7 group: operator abbrev: <*> \<div> code: 0x0000f7 group: operator \<cdot> code: 0x0022c5 group: operator \<star> code: 0x0022c6 group: operator \<bullet> code: 0x002219 group: operator \<circ> code: 0x002218 group: operator \<dagger> code: 0x002020 \<ddagger> code: 0x002021 \<lhd> code: 0x0022b2 group: relation \<rhd> code: 0x0022b3 group: relation \<unlhd> code: 0x0022b4 group: relation \<unrhd> code: 0x0022b5 group: relation \<triangleleft> code: 0x0025c3 group: relation \<triangleright> code: 0x0025b9 group: relation \<triangle> code: 0x0025b3 group: relation \<triangleq> code: 0x00225c group: relation \<oplus> code: 0x002295 group: operator \<Oplus> code: 0x002a01 group: operator \<otimes> code: 0x002297 group: operator \<Otimes> code: 0x002a02 group: operator \<odot> code: 0x002299 group: operator \<Odot> code: 0x002a00 group: operator \<ominus> code: 0x002296 group: operator \<oslash> code: 0x002298 group: operator \<dots> code: 0x002026 group: punctuation abbrev: ... \<cdots> code: 0x0022ef group: punctuation \<Sum> code: 0x002211 group: operator abbrev: SUM \<Prod> code: 0x00220f group: operator abbrev: PROD \<Coprod> code: 0x002210 group: operator \<infinity> code: 0x00221e \<integral> code: 0x00222b group: operator \<ointegral> code: 0x00222e group: operator \<clubsuit> code: 0x002663 \<diamondsuit> code: 0x002662 \<heartsuit> code: 0x002661 \<spadesuit> code: 0x002660 \<aleph> code: 0x002135 \<emptyset> code: 0x002205 \<nabla> code: 0x002207 \<partial> code: 0x002202 \<flat> code: 0x00266d \<natural> code: 0x00266e \<sharp> code: 0x00266f \<angle> code: 0x002220 \<copyright> code: 0x0000a9 \<registered> code: 0x0000ae \<hyphen> code: 0x0000ad group: punctuation \<inverse> code: 0x0000af group: punctuation \<onequarter> code: 0x0000bc group: digit \<onehalf> code: 0x0000bd group: digit \<threequarters> code: 0x0000be group: digit \<ordfeminine> code: 0x0000aa \<ordmasculine> code: 0x0000ba \<section> code: 0x0000a7 \<paragraph> code: 0x0000b6 \<exclamdown> code: 0x0000a1 \<questiondown> code: 0x0000bf \<euro> code: 0x0020ac \<pounds> code: 0x0000a3 \<yen> code: 0x0000a5 \<cent> code: 0x0000a2 \<currency> code: 0x0000a4 \<degree> code: 0x0000b0 \<amalg> code: 0x002a3f group: operator \<mho> code: 0x002127 group: operator \<lozenge> code: 0x0025ca \<wp> code: 0x002118 \<wrong> code: 0x002240 group: relation \<acute> code: 0x0000b4 \<index> code: 0x000131 \<dieresis> code: 0x0000a8 \<cedilla> code: 0x0000b8 \<hungarumlaut> code: 0x0002dd \<bind> code: 0x00291c abbrev: >>= \<then> code: 0x002aa2 abbrev: >> \<some> code: 0x0003f5 \<hole> code: 0x002311 \<newline> code: 0x0023ce \<comment> code: 0x002015 group: document font: IsabelleText \<open> code: 0x002039 group: punctuation font: IsabelleText abbrev: << \<close> code: 0x00203a group: punctuation font: IsabelleText abbrev: >> \<here> code: 0x002302 font: IsabelleText \<^undefined> code: 0x002756 font: IsabelleText \<^noindent> code: 0x0021e4 group: document font: IsabelleText \<^smallskip> code: 0x002508 group: document font: IsabelleText \<^medskip> code: 0x002509 group: document font: IsabelleText \<^bigskip> code: 0x002501 group: document font: IsabelleText \<^item> code: 0x0025aa group: document font: IsabelleText \<^enum> code: 0x0025b8 group: document font: IsabelleText \<^descr> code: 0x0027a7 group: document font: IsabelleText \<^footnote> code: 0x00204b group: document font: IsabelleText \<^verbatim> code: 0x0025a9 group: document font: IsabelleText \<^theory_text> code: 0x002b1a group: document font: IsabelleText \<^emph> code: 0x002217 group: document font: IsabelleText \<^bold> code: 0x002759 group: control group: document font: IsabelleText \<^sub> code: 0x0021e9 group: control font: IsabelleText \<^sup> code: 0x0021e7 group: control font: IsabelleText \<^bsub> code: 0x0021d8 group: control_block font: IsabelleText abbrev: =_( \<^esub> code: 0x0021d9 group: control_block font: IsabelleText abbrev: =_) \<^bsup> code: 0x0021d7 group: control_block font: IsabelleText abbrev: =^( \<^esup> code: 0x0021d6 group: control_block font: IsabelleText abbrev: =^) """	KITPraktomatTeam/Praktomat	src/utilities/isar_lexer.py	Python	gpl-2.0	24,376	[ "Bowtie" ]	61c5a9afbe1245838a7e7f294fb623705327ad256a0d1dac8550c029e047e0c9
import os from os.path import join as pjoin import numpy as np import h5py from gps_viewer import read_gps_fields from WGS84toENU import WGS84toECEF, WGS84toENU from pipeline_config import EXPORT_STEP, EXPORT_START, MAPPING_PATH, ICP_ITERS, ICP_MAX_DIST, NUM_CPUS from graphslam_config import MATCH_JSON_DATA, CHUNK_SIZE, GRAPHSLAM_CHUNK_DIR, GRAPHSLAM_ALIGN_DIR, REALIGN_EVERY from pipeline_utils import print_and_call, dset_dir_from_rss from joblib import Parallel, delayed ''' For every alignment, we need to create two small chunks of the full maps that we want to align. These chunks are selected by looking at the best NN matches. We compute a new alignment every REALIGN_EVERY steps Since the chunks are stored relative to IMU 0, we need to first transform them by the global position of IMU 0 ''' def get_ecef0(gps_file): llh = read_gps_fields(gps_file, ['lat', 'long', 'height']) llh = np.array(llh, dtype=np.float64).T ecef = WGS84toECEF(llh) return ecef[:, 0] def get_enu0(gps_file, gps_ref_file): llh = read_gps_fields(gps_file, ['lat', 'long', 'height']) llh = np.array(llh, dtype=np.float64).T llh_ref = read_gps_fields(gps_ref_file, ['lat', 'long', 'height']) llh_ref = np.array(llh_ref, dtype=np.float64).T return WGS84toENU(llh_ref[0, :], llh)[:, 0] def vtk_filename(pcd_file): return os.path.splitext(pcd_file)[0] + '.vtk' # Helper function for chunk_and_align all def chunk_and_align(start1, start2, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num, debug=False): chunk1_files = list() chunk2_files = list() for k in range(0, CHUNK_SIZE): ind1 = start1 + k chunk1_files.append('%s/%d.pcd' % (pcd_dir1, ind1)) assert os.path.exists(chunk1_files[-1]) ind2 = start2 + k chunk2_files.append('%s/%d.pcd' % (pcd_dir2, ind2)) assert os.path.exists(chunk2_files[-1]) merged_chunks1 = '%s/%s' % (GRAPHSLAM_CHUNK_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '%d_1.pcd' % chunk_num) merged_chunks2 = '%s/%s' % (GRAPHSLAM_CHUNK_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '%d_2.pcd' % chunk_num) # Concatenate cmd = 'concatenate_points_pcd %s %s' % (' '.join(chunk1_files), merged_chunks1) print_and_call(cmd) cmd = 'concatenate_points_pcd %s %s' % (' '.join(chunk2_files), merged_chunks2) print_and_call(cmd) # Translate cmd = 'transform_point_cloud %s %s -trans %f,%f,%f' % (merged_chunks1, merged_chunks1, enu1[0]-enu2[0], enu1[1]-enu2[1], enu1[2]-enu2[2]) print_and_call(cmd) #cmd = 'transform_point_cloud %s %s -trans %f,%f,%f' % (merged_chunks2, merged_chunks2, -1enu2[0], -1enu2[1], -1enu2[2]) #print_and_call(cmd) # Generate VTK files so we can easily visualize to debug if debug: cmd = 'pcl_pcd2vtk %s %s' % (merged_chunks1, vtk_filename(merged_chunks1)) print_and_call(cmd) cmd = 'pcl_pcd2vtk %s %s' % (merged_chunks2, vtk_filename(merged_chunks2)) print_and_call(cmd) # Finally perform alignment reg = '%s/bin/align_clouds' % MAPPING_PATH h5f = '%s/%s' % (GRAPHSLAM_ALIGN_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '--%d' % chunk_num + '.h5') cmd = '{reg} --pcd_tgt {tgt} --pcd_src {src} --h5_file {h5f} --icp_iters {iters} --max_dist {dist}'.format( reg=reg, tgt=merged_chunks1, src=merged_chunks2, h5f=h5f, iters=ICP_ITERS, dist=ICP_MAX_DIST) print_and_call(cmd) def get_closest_key_value(k, d, max_shift=5): shift = -1 while k not in d: k = k + shift shift = -1 (abs(shift) + 1) * cmp(shift, 0) assert abs(shift) < max_shift, 'Index %d shift %d' % (k, shift) return d[k] def chunk_and_align_all(d): print d['match_file'] rss1 = d['rss1'] rss2 = d['rss2'] pcd_dir1 = pjoin(dset_dir_from_rss(rss1), 'pcd_downsampled_normals') pcd_dir2 = pjoin(dset_dir_from_rss(rss2), 'pcd_downsampled_normals') # Read and save initial transform files enu1 = get_enu0(d['gps_file1'], d['gps_file1']) enu2 = get_enu0(d['gps_file2'], d['gps_file1']) h5f = h5py.File(d['match_file'], 'r') nn_matches = h5f['matches'][...] nn_dict = dict(zip(nn_matches[:, 1], nn_matches[:, 0])) h5f.close() assert EXPORT_START == 0 start1 = nn_matches[0, 1] / EXPORT_STEP args_all = list() chunk_num = 0 for k in range(start1, nn_matches[-1, 1] / EXPORT_STEP - CHUNK_SIZE, REALIGN_EVERY): #def chunk_and_align(start1, start2, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num): try: k2 = get_closest_key_value(k * EXPORT_STEP, nn_dict, max_shift=10) except: # TODO Think this sometimes occurs near end of alignments break args_all.append((k, k2 / EXPORT_STEP, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num)) chunk_num += 1 Parallel(n_jobs=NUM_CPUS)(delayed(chunk_and_align)(args) for args in args_all) # For debugging ''' for args in args_all: _, _, _, _, rss1, rss2, _, _, chunk_num = args h5f = '%s/%s' % (GRAPHSLAM_ALIGN_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '--%d' % chunk_num + '.h5') if os.path.exists(h5f): continue chunk_and_align(args) ''' if __name__ == '__main__': for d in MATCH_JSON_DATA: chunk_and_align_all(d)	sameeptandon/sail-car-log	mapping/sandbox/graphslam/chunk_and_align.py	Python	bsd-2-clause	5,357	[ "VTK" ]	414b8c0d82019578c57f08a0083dc05df46e79e997a55ce50c75a211508ceb39
#!/usr/bin/env python3 # -- coding=utf-8 -- """ cry2cif\n\n Read the last geometry corresponding to the CRYSTALLOGRAPHIC CELL on a CRYSTAL09 output file and print it in a cif format. If geometry optimization did not converge, input geometry is printed instead. """ # TODO: # * returns coordinates instead of write a file # * make functions for various formats __author__ = "Germain Vallverdu" __email__ = "germain.vallverdu@univ-pau.fr" __licence__ = "GPL" import os import argparse from pymatgen import Structure, Lattice from crystalio import CrystalOutfile def get_options(): """ get options from command lines """ parser = argparse.ArgumentParser(prog="cry2cif", description=__doc__) # mandatory argument is CRYSTAL output filename parser.add_argument("filename", help="CRYSTAL output file", metavar="FILENAME", type=str) # choose either cif or POSCAR format parser.add_argument("-t", "--to", help="output format: either cif or VASP (POSCAR)", metavar="format", default="cif", choices=("cif", "vasp"), type=str) # center slab or nanotubes parser.add_argument("-i", "--center", help="move the slab or nanotubes in the center of the box", action="store_true", dest="center", default=False) parser.add_argument("-n", "--num_structure", help="Structure number to be extracted (default, the last)", metavar="N", default=-1, type=int) # sort atom along z or x for slab or nanotubes parser.add_argument("-z", "--sortz", help="Sort atoms along z axis (for slabs)", dest="sortz", action="store_true", default=False) parser.add_argument("-x", "--sortx", help="Sort atoms along x axis (for nanotubes)", dest="sortx", action="store_true", default=False) # in the case of slabs or nanotubes, you have to give a value for b or c parser.add_argument("-b", help="lattice parameter b", metavar="b", default=50, type=float) parser.add_argument("-c", help="lattice parameter c", metavar="c", default=50, type=float) return parser.parse_args() def cry2cif(filename, to="cif", center=False, sortx=False, sortz=False, b_dum=50, c_dum=50, istruct=-1): """ Read a CRYSTAL output file and return the structure in a cif or POSCAR format. Args: filename (str): crystal output filename to (str): 'cif' or 'vasp', format of the output file (default is cif) center (bool): if True, the slab or nanotube is translated to the center of the box (default is False) sortx (bool): Nanotube : if True, atoms are sorted along x axes (default is False). sortz (bool): slab : if True, atoms are sorted along z axes (default is False). b_dum (float): dummy lattice paramters b in angstrom for nanotubes (default 50 A) c_dum (float): dummy lattice paramters c in angstrom for nanotubes and slabs (default 50 A) istruct (int): structure to be extracted """ cryout = CrystalOutfile(filename) print("title : ", cryout.title) if cryout.group: print("group : ", cryout.group) # print("Number of structure read: ", len(cryout.structures)) if istruct == -1: print("structure : Final structure") structure = cryout.final_structure else: print("structure : Structure %d" % istruct) structure = cryout.get_structure(istruct) print("# atom : ", structure.num_sites) print("composition: ", structure.composition) print("Cell parameters:") print("a : %10.4f" % structure.lattice.a) print("b : %10.4f" % structure.lattice.b) print("c : %10.4f" % structure.lattice.c) print("alpha : %10.4f" % structure.lattice.alpha) print("beta : %10.4f" % structure.lattice.beta) print("gamma : %10.4f" % structure.lattice.gamma) # ---------------------------------------------------------- # New b and c axes # ---------------------------------------------------------- if cryout.slab: frac_coords = structure.frac_coords frac_coords[:, 2] = structure.lattice.c / c_dum matrix = structure.lattice.matrix.copy() matrix[2, 2] = c_dum structure = Structure(Lattice(matrix), structure.species, frac_coords) if cryout.nanotube: frac_coords = structure.frac_coords frac_coords[:, 1] = structure.lattice.c / c_dum frac_coords[:, 2] = structure.lattice.b / b_dum matrix = structure.lattice.matrix.copy() matrix[1, 1] = b_dum matrix[2, 2] = c_dum structure = Structure(Lattice(matrix), structure.species, frac_coords) # ---------------------------------------------------------- # move slab or nanotube to the center of the box # ---------------------------------------------------------- if center: if cryout.slab: coords = structure.frac_coords.copy() coords[:, 2] += .5 structure = Structure(structure.lattice, structure.species, coords) elif cryout.nanotube: coords = structure.frac_coords coords += .5 structure = Structure(structure.lattice, structure.species, coords) # ---------------------------------------------------------- # sort atom along x or z axis for slab # ---------------------------------------------------------- if sortz: isort = 2 elif sortx: isort = 0 axes = {2: "z", 0: "x"} if sortz or sortx: print("\nSort atoms along %s" % axes[isort]) data = zip(structure.species, structure.frac_coords) data = sorted(data, key=lambda d: d[-1][isort], reverse=True) species = [d[0] for d in data] coords = [d[1] for d in data] structure = Structure(structure.lattice, species, coords) # ---------------------------------------------------------- # export in the given format # ---------------------------------------------------------- basename, _ = os.path.splitext(filename) if to.lower() == "cif": ext = ".cif" elif to.lower() == "vasp": to = "POSCAR" ext = ".vasp" else: to = "POSCAR" ext = ".vasp" structure.to(to, filename=basename + ext) if __name__ == "__main__": # get arguments args = vars(get_options()) # rename some args args["b_dum"] = args.pop("b") args["c_dum"] = args.pop("c") args["istruct"] = args.pop("num_structure") # call main program cry2cif(*args)	gVallverdu/myScripts	CRYSTAL/cry2cif.py	Python	gpl-2.0	7,246	[ "CRYSTAL", "VASP", "pymatgen" ]	9f17d1ca622a9d8ac35c6fbed0c90143cc262316cfc129f48e071549c112913e
from __future__ import print_function from __future__ import division from __future__ import unicode_literals import numpy as np from rdkit import Chem import itertools, operator from deepchem.feat import Featurizer from deepchem.feat.mol_graphs import ConvMol def one_of_k_encoding(x, allowable_set): if x not in allowable_set: raise Exception( "input {0} not in allowable set{1}:".format(x, allowable_set)) return list(map(lambda s: x == s, allowable_set)) def one_of_k_encoding_unk(x, allowable_set): """Maps inputs not in the allowable set to the last element.""" if x not in allowable_set: x = allowable_set[-1] return list(map(lambda s: x == s, allowable_set)) def get_intervals(l): """For list of lists, gets the cumulative products of the lengths""" intervals = len(l) * [0] # Initalize with 1 intervals[0] = 1 for k in range(1, len(l)): intervals[k] = (len(l[k]) + 1) * intervals[k-1] return intervals def safe_index(l, e): """Gets the index of e in l, providing an index of len(l) if not found""" try: return l.index(e) except: return len(l) possible_atom_list = ['C', 'N', 'O', 'S', 'F', 'P', 'Cl', 'Mg', 'Na', 'Br', 'Fe', 'Ca', 'Cu', 'Mc', 'Pd', 'Pb', 'K','I','Al','Ni','Mn'] possible_numH_list = [0, 1, 2, 3, 4] possible_valence_list = [0, 1, 2, 3, 4, 5, 6] possible_formal_charge_list = [-3, -2, -1, 0, 1, 2, 3] possible_hybridization_list = [Chem.rdchem.HybridizationType.SP, Chem.rdchem.HybridizationType.SP2, Chem.rdchem.HybridizationType.SP3, Chem.rdchem.HybridizationType.SP3D, Chem.rdchem.HybridizationType.SP3D2] possible_number_radical_e_list = [0, 1, 2] reference_lists = [possible_atom_list, possible_numH_list, possible_valence_list, possible_formal_charge_list, possible_number_radical_e_list, possible_hybridization_list] intervals = get_intervals(reference_lists) def get_feature_list(atom): features = 6 * [0] features[0] = safe_index(possible_atom_list, atom.GetSymbol()) features[1] = safe_index(possible_numH_list, atom.GetTotalNumHs()) features[2] = safe_index(possible_valence_list, atom.GetImplicitValence()) features[3] = safe_index(possible_formal_charge_list, atom.GetFormalCharge()) features[4] = safe_index(possible_number_radical_e_list, atom.GetNumRadicalElectrons()) features[5] = safe_index(possible_hybridization_list, atom.GetHybridization()) return features def features_to_id(features, intervals): """Convert list of features into index using spacings provided in intervals""" id = 0 for k in range(len(intervals)): id += features[k] * intervals[k] # Allow 0 index to correspond to null molecule 1 id = id + 1 return id def id_to_features(id, intervals): features = 6* [0] # Correct for null id -= 1 for k in range(0,6-1): #print(6-k-1, id) features[6-k-1] = id // intervals[6-k-1] id -= features[6-k-1]intervals[6-k-1] # Correct for last one features[0] = id return features def atom_to_id(atom): """Return a unique id corresponding to the atom type""" features = get_feature_list(atom) return features_to_id(features, intervals) def atom_features(atom, bool_id_feat=False): if bool_id_feat: return np.array([atom_to_id(atom)]) else: return np.array(one_of_k_encoding_unk( atom.GetSymbol(), ['C', 'N', 'O', 'S', 'F', 'Si', 'P', 'Cl', 'Br', 'Mg', 'Na', 'Ca', 'Fe', 'As', 'Al', 'I', 'B', 'V', 'K', 'Tl', 'Yb', 'Sb', 'Sn', 'Ag', 'Pd', 'Co', 'Se', 'Ti', 'Zn', 'H', # H? 'Li', 'Ge', 'Cu', 'Au', 'Ni', 'Cd', 'In', 'Mn', 'Zr', 'Cr', 'Pt', 'Hg', 'Pb', 'Unknown']) + one_of_k_encoding(atom.GetDegree(), [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) + one_of_k_encoding_unk(atom.GetTotalNumHs(), [0, 1, 2, 3, 4]) + one_of_k_encoding_unk(atom.GetImplicitValence(), [0, 1, 2, 3, 4, 5, 6]) + [atom.GetFormalCharge(), atom.GetNumRadicalElectrons()] + one_of_k_encoding_unk( atom.GetHybridization(), [Chem.rdchem.HybridizationType.SP, Chem.rdchem.HybridizationType.SP2, Chem.rdchem.HybridizationType.SP3, Chem.rdchem.HybridizationType.SP3D, Chem.rdchem.HybridizationType.SP3D2]) + [atom.GetIsAromatic()]) def bond_features(bond): bt = bond.GetBondType() return np.array([bt == Chem.rdchem.BondType.SINGLE, bt == Chem.rdchem.BondType.DOUBLE, bt == Chem.rdchem.BondType.TRIPLE, bt == Chem.rdchem.BondType.AROMATIC, bond.GetIsConjugated(), bond.IsInRing()]) class ConvMolFeaturizer(Featurizer): name = ['conv_mol'] def __init__(self): # Since ConvMol is an object and not a numpy array, need to set dtype to # object. self.dtype = object def _featurize(self, mol): """Encodes mol as a ConvMol object.""" # Get the node features idx_nodes = [(a.GetIdx(), atom_features(a)) for a in mol.GetAtoms()] idx_nodes.sort() # Sort by ind to ensure same order as rd_kit idx, nodes = list(zip(idx_nodes)) # Stack nodes into an array nodes = np.vstack(nodes) # Get bond lists with reverse edges included edge_list = [(b.GetBeginAtomIdx(), b.GetEndAtomIdx()) for b in mol.GetBonds()] # Get canonical adjacency list canon_adj_list = [[] for mol_id in range(len(nodes))] for edge in edge_list: canon_adj_list[edge[0]].append(edge[1]) canon_adj_list[edge[1]].append(edge[0]) return ConvMol(nodes, canon_adj_list)	bowenliu16/deepchem	deepchem/feat/graph_features.py	Python	gpl-3.0	5,773	[ "RDKit" ]	3db79ed9e095690295e0992c0c4bdeb6ffc10f0a76c2912a83a6ed48e5f5623a
from django.conf import settings from django.db import models from django.utils import timezone from patients.models import Patient class BaseActe(models.Model): """ Base Abstract class for for differnets actions made by usej """ patient = models.ForeignKey( Patient, related_name="%(class)ss", on_delete=models.CASCADE) created = models.DateTimeField(auto_now_add=True) modified = models.DateTimeField(default=timezone.now) owner = models.ForeignKey( settings.AUTH_USER_MODEL, related_name="%(class)ss", on_delete=models.PROTECT) class Meta: abstract = True def save(self, args, *kwargs): self.modified = timezone.now() super().save() class Observation(BaseActe): """ A small text of user about a patient motif : purpose of the visit. can't be blank.this is the most minimam thing a user schould enter. """ motif = models.CharField(max_length=40, blank=False) body = models.TextField(blank=True) def __str__(self): return self.motif """ BAseActe: non modifiable if not today Observation : TA/pouls conclusion ordonnance vaccin certif titre texte courries dest corps courriers reçus spé nom contenu pdf examens: type effecteur pdf REGROUPER courrier et examens ? bio antécédants intolérances allergies """	jgirardet/unolog	unolog/actes/models.py	Python	gpl-3.0	1,489	[ "VisIt" ]	0b89dc5a4ddddea18047f66e5b2b2f662314ff240eac48725e7754089f9ed475
# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from collections import defaultdict from spack import * from spack.util.environment import is_system_path class Cdo(AutotoolsPackage): """CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data. """ homepage = 'https://code.mpimet.mpg.de/projects/cdo' url = 'https://code.mpimet.mpg.de/attachments/download/12760/cdo-1.7.2.tar.gz' list_url = 'https://code.mpimet.mpg.de/projects/cdo/files' maintainers = ['skosukhin', 'Try2Code'] version('2.0.2', sha256='34dfdd0d4126cfd35fc69e37e60901c8622d13ec5b3fa5f0fe6a1cc866cc5a70', url='https://code.mpimet.mpg.de/attachments/download/26654/cdo-2.0.2.tar.gz') version('2.0.1', sha256='d0794d261e22efa0adac8e6d18de2b60d54de5e1a4df6127c65fc417feb8fdac', url='https://code.mpimet.mpg.de/attachments/download/26477/cdo-2.0.1.tar.gz') version('2.0.0', sha256='6bca54e9d69d8c1f072f1996547b7347a65743d15ba751967e9bb16e0ff7a843', url='https://code.mpimet.mpg.de/attachments/download/26370/cdo-2.0.0.tar.gz') version('1.9.10', sha256='cc39c89bbb481d7b3945a06c56a8492047235f46ac363c4f0d980fccdde6677e', url='https://code.mpimet.mpg.de/attachments/download/24638/cdo-1.9.10.tar.gz') version('1.9.9', sha256='959b5b58f495d521a7fd1daa84644888ec87d6a0df43f22ad950d17aee5ba98d', url='https://code.mpimet.mpg.de/attachments/download/23323/cdo-1.9.9.tar.gz') version('1.9.8', sha256='f2660ac6f8bf3fa071cf2a3a196b3ec75ad007deb3a782455e80f28680c5252a', url='https://code.mpimet.mpg.de/attachments/download/20826/cdo-1.9.8.tar.gz') version('1.9.7.1', sha256='3771952e065bcf935d43e492707370ed2a0ecb59a06bea24f9ab69d77943962c', url='https://code.mpimet.mpg.de/attachments/download/20124/cdo-1.9.7.1.tar.gz') version('1.9.6', sha256='b31474c94548d21393758caa33f35cf7f423d5dfc84562ad80a2bdcb725b5585', url='https://code.mpimet.mpg.de/attachments/download/19299/cdo-1.9.6.tar.gz') version('1.9.5', sha256='48ed65cc5b436753c8e7f9eadd8aa97376698ce230ceafed2a4350a5b1a27148', url='https://code.mpimet.mpg.de/attachments/download/18264/cdo-1.9.5.tar.gz') version('1.9.4', sha256='3d1c0fd3f7d38c5d3d88139ca1546c9d24e1b1ff752a794a4194dfe624695def', url='https://code.mpimet.mpg.de/attachments/download/17374/cdo-1.9.4.tar.gz') version('1.9.3', sha256='e83a3de7b402600c0d9a5df18073d36d133ff9719d3c561a0efa90f9c1599f3f', url='https://code.mpimet.mpg.de/attachments/download/16435/cdo-1.9.3.tar.gz') version('1.9.2', sha256='d1c5092167034a48e4b8ada24cf78a1d4b84e364ffbb08b9ca70d13f428f300c', url='https://code.mpimet.mpg.de/attachments/download/16035/cdo-1.9.2.tar.gz') version('1.9.1', sha256='33cba3cfcc27e5896769143c5f8e2f300ca14c7a40d1f19ffd1ed24b49ea3d55', url='https://code.mpimet.mpg.de/attachments/download/15653/cdo-1.9.1.tar.gz') version('1.9.0', sha256='df367f8c3abf4ab085bcfc61e0205b28a5ecc69b7b83ba398b4d3c874dd69008', url='https://code.mpimet.mpg.de/attachments/download/15187/cdo-1.9.0.tar.gz') version('1.8.2', sha256='6ca6c1263af2237737728ac937a275f8aa27680507636a6b6320f347c69a369a', url='https://code.mpimet.mpg.de/attachments/download/14686/cdo-1.8.2.tar.gz') version('1.7.2', sha256='4c43eba7a95f77457bfe0d30fb82382b3b5f2b0cf90aca6f0f0a008f6cc7e697', url='https://code.mpimet.mpg.de/attachments/download/12760/cdo-1.7.2.tar.gz') variant('netcdf', default=True, description='Enable NetCDF support') variant('grib2', default='eccodes', values=('eccodes', 'grib-api', 'none'), description='Specify GRIB2 backend') variant('external-grib1', default=False, description='Ignore the built-in support and use the external ' 'GRIB2 backend for GRIB1 files') variant('szip', default=True, description='Enable szip compression for GRIB1') variant('hdf5', default=True, description='Enable HDF5 support') variant('udunits2', default=True, description='Enable UDUNITS2 support') variant('libxml2', default=True, description='Enable libxml2 support') variant('proj', default=True, description='Enable PROJ library for cartographic projections') variant('curl', default=False, description='Enable curl support') variant('fftw3', default=True, description='Enable support for fftw3') variant('magics', default=False, description='Enable Magics library support') variant('openmp', default=True, description='Enable OpenMP support') depends_on('pkgconfig', type='build') depends_on('netcdf-c', when='+netcdf') # The internal library of CDO implicitly links to hdf5. # We also need the backend of netcdf to be thread safe. depends_on('hdf5+threadsafe', when='+netcdf') depends_on('grib-api', when='grib2=grib-api') depends_on('eccodes', when='grib2=eccodes') depends_on('szip', when='+szip') depends_on('hdf5+threadsafe', when='+hdf5') depends_on('udunits', when='+udunits2') depends_on('libxml2', when='+libxml2') depends_on('proj@:5', when='@:1.9.6+proj') depends_on('proj@:7', when='@1.9.7+proj') depends_on('proj@5:', when='@1.9.8:+proj') depends_on('curl', when='+curl') depends_on('fftw-api@3:', when='+fftw3') depends_on('magics', when='+magics') depends_on('uuid') conflicts('+szip', when='+external-grib1 grib2=none', msg='The configuration does not support GRIB1') conflicts('%gcc@9:', when='@:1.9.6', msg='GCC 9 changed OpenMP data sharing behavior') def configure_args(self): config_args = [] flags = defaultdict(list) def yes_or_prefix(spec_name): prefix = self.spec[spec_name].prefix return 'yes' if is_system_path(prefix) else prefix if '+netcdf' in self.spec: config_args.append('--with-netcdf=' + yes_or_prefix('netcdf-c')) # We need to make sure that the libtool script of libcdi - the # internal library of CDO - finds the correct version of hdf5. # Note that the argument of --with-hdf5 is not passed to the # configure script of libcdi, therefore we have to provide # additional flags regardless of whether hdf5 support is enabled. hdf5_spec = self.spec['hdf5'] if not is_system_path(hdf5_spec.prefix): flags['LDFLAGS'].append(self.spec['hdf5'].libs.search_flags) else: config_args.append('--without-netcdf') if self.spec.variants['grib2'].value == 'eccodes': if self.spec.satisfies('@1.9:'): config_args.append('--with-eccodes=' + yes_or_prefix('eccodes')) config_args.append('--without-grib_api') else: config_args.append('--with-grib_api=yes') eccodes_spec = self.spec['eccodes'] eccodes_libs = eccodes_spec.libs flags['LIBS'].append(eccodes_libs.link_flags) if not is_system_path(eccodes_spec.prefix): flags['LDFLAGS'].append(eccodes_libs.search_flags) elif self.spec.variants['grib2'].value == 'grib-api': config_args.append('--with-grib_api=' + yes_or_prefix('grib-api')) if self.spec.satisfies('@1.9:'): config_args.append('--without-eccodes') else: config_args.append('--without-grib_api') if self.spec.satisfies('@1.9:'): config_args.append('--without-eccodes') if '+external-grib1' in self.spec: config_args.append('--disable-cgribex') else: config_args.append('--enable-cgribex') if '+szip' in self.spec: config_args.append('--with-szlib=' + yes_or_prefix('szip')) else: config_args.append('--without-szlib') config_args += self.with_or_without('hdf5', activation_value=yes_or_prefix) config_args += self.with_or_without( 'udunits2', activation_value=lambda x: yes_or_prefix('udunits')) if '+libxml2' in self.spec: libxml2_spec = self.spec['libxml2'] if is_system_path(libxml2_spec.prefix): config_args.append('--with-libxml2=yes') # Spack does not inject the header search flag in this case, # which is still required, unless libxml2 is installed to '/usr' # (handled by the configure script of CDO). if libxml2_spec.prefix != '/usr': flags['CPPFLAGS'].append(libxml2_spec.headers.include_flags) else: config_args.append('--with-libxml2=' + libxml2_spec.prefix) else: config_args.append('--without-libxml2') config_args += self.with_or_without('proj', activation_value=yes_or_prefix) config_args += self.with_or_without('curl', activation_value=yes_or_prefix) config_args += self.with_or_without('magics', activation_value=yes_or_prefix) config_args += self.with_or_without('fftw3') config_args += self.enable_or_disable('openmp') # Starting version 1.9.0 CDO is a C++ program but it uses the C # interface of HDF5 without the parallel features. To avoid # unnecessary dependencies on mpi's cxx library, we need to set the # following flags. This works for OpenMPI, MPICH, MVAPICH, Intel MPI, # IBM Spectrum MPI, bullx MPI, and Cray MPI. if self.spec.satisfies('@1.9:+hdf5^hdf5+mpi'): flags['CPPFLAGS'].append('-DOMPI_SKIP_MPICXX -DMPICH_SKIP_MPICXX') config_args.extend(['{0}={1}'.format(var, ' '.join(val)) for var, val in flags.items()]) return config_args	LLNL/spack	var/spack/repos/builtin/packages/cdo/package.py	Python	lgpl-2.1	10,082	[ "NetCDF" ]	5daf458f2e315d74110c9cee940cb6998d5a53797afdff00c9506eb6954783b6
######################################################################## # $HeadURL $ # File: FileCatalogHandler.py ######################################################################## """ :mod: FileCatalogHandler .. module: FileCatalogHandler :synopsis: FileCatalogHandler is a simple Replica and Metadata Catalog service """ __RCSID__ = "$Id$" ## imports import os from types import IntType, LongType, DictType, StringTypes, BooleanType, ListType ## from DIRAC from DIRAC.Core.DISET.RequestHandler import RequestHandler, getServiceOption from DIRAC import gLogger, S_OK, S_ERROR, gMonitor from DIRAC.DataManagementSystem.DB.FileCatalogDB import FileCatalogDB from DIRAC.Core.Utilities.List import sortList # This is a global instance of the FileCatalogDB class gFileCatalogDB = None def initializeFileCatalogHandler( serviceInfo ): """ handler initialisation """ global gFileCatalogDB dbLocation = getServiceOption( serviceInfo, 'Database', 'DataManagement/FileCatalogDB' ) gFileCatalogDB = FileCatalogDB( dbLocation ) databaseConfig = {} # Obtain the plugins to be used for DB interaction gLogger.info( "Initializing with FileCatalog with following managers:" ) defaultManagers = { 'UserGroupManager' : 'UserAndGroupManagerDB', 'SEManager' : 'SEManagerDB', 'SecurityManager' : 'NoSecurityManager', 'DirectoryManager' : 'DirectoryLevelTree', 'FileManager' : 'FileManager', 'DirectoryMetadata' : 'DirectoryMetadata', 'FileMetadata' : 'FileMetadata', 'DatasetManager' : 'DatasetManager' } for configKey in sortList( defaultManagers.keys() ): defaultValue = defaultManagers[configKey] configValue = getServiceOption( serviceInfo, configKey, defaultValue ) gLogger.info( "%-20s : %-20s" % ( str( configKey ), str( configValue ) ) ) databaseConfig[configKey] = configValue # Obtain some general configuration of the database gLogger.info( "Initializing the FileCatalog with the following configuration:" ) defaultConfig = { 'UniqueGUID' : False, 'GlobalReadAccess' : True, 'LFNPFNConvention' : 'Strong', 'ResolvePFN' : True, 'DefaultUmask' : 0775, 'ValidFileStatus' : ['AprioriGood','Trash','Removing','Probing'], 'ValidReplicaStatus' : ['AprioriGood','Trash','Removing','Probing'], 'VisibleFileStatus' : ['AprioriGood'], 'VisibleReplicaStatus': ['AprioriGood']} for configKey in sortList( defaultConfig.keys() ): defaultValue = defaultConfig[configKey] configValue = getServiceOption( serviceInfo, configKey, defaultValue ) gLogger.info( "%-20s : %-20s" % ( str( configKey ), str( configValue ) ) ) databaseConfig[configKey] = configValue res = gFileCatalogDB.setConfig( databaseConfig ) gMonitor.registerActivity( "AddFile", "Amount of addFile calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddFileSuccessful", "Files successfully added", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddFileFailed", "Files failed to add", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveFile", "Amount of removeFile calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveFileSuccessful", "Files successfully removed", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveFileFailed", "Files failed to remove", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddReplica", "Amount of addReplica calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddReplicaSuccessful", "Replicas successfully added", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddReplicaFailed", "Replicas failed to add", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveReplica", "Amount of removeReplica calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveReplicaSuccessful", "Replicas successfully removed", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveReplicaFailed", "Replicas failed to remove", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "ListDirectory", "Amount of listDirectory calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) return res class FileCatalogHandler( RequestHandler ): """ ..class:: FileCatalogHandler A simple Replica and Metadata Catalog service. """ ######################################################################## # Path operations (not updated) # types_changePathOwner = [ [ ListType, DictType ] + list( StringTypes ) ] def export_changePathOwner( self, lfns, recursive = False ): """ Get replica info for the given list of LFNs """ return gFileCatalogDB.changePathOwner( lfns, self.getRemoteCredentials(), recursive ) types_changePathGroup = [ [ ListType, DictType ] + list( StringTypes ) ] def export_changePathGroup( self, lfns, recursive = False ): """ Get replica info for the given list of LFNs """ return gFileCatalogDB.changePathGroup( lfns, self.getRemoteCredentials(), recursive ) types_changePathMode = [ [ ListType, DictType ] + list( StringTypes ) ] def export_changePathMode( self, lfns, recursive = False ): """ Get replica info for the given list of LFNs """ return gFileCatalogDB.changePathMode( lfns, self.getRemoteCredentials(), recursive ) ######################################################################## # ACL Operations # types_getPathPermissions = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getPathPermissions( self, lfns ): """ Determine the ACL information for a supplied path """ return gFileCatalogDB.getPathPermissions( lfns, self.getRemoteCredentials() ) ################################################################### # # isOK # types_isOK = [] @staticmethod def export_isOK(): """ returns S_OK if DB is connected """ if gFileCatalogDB and gFileCatalogDB._connected: return S_OK() return S_ERROR( 'Server not connected to DB' ) ################################################################### # # User/Group write operations # types_addUser = [ StringTypes ] def export_addUser( self, userName ): """ Add a new user to the File Catalog """ return gFileCatalogDB.addUser( userName, self.getRemoteCredentials() ) types_deleteUser = [ StringTypes ] def export_deleteUser( self, userName ): """ Delete user from the File Catalog """ return gFileCatalogDB.deleteUser( userName, self.getRemoteCredentials() ) types_addGroup = [ StringTypes ] def export_addGroup( self, groupName ): """ Add a new group to the File Catalog """ return gFileCatalogDB.addGroup( groupName, self.getRemoteCredentials() ) types_deleteGroup = [ StringTypes ] def export_deleteGroup( self, groupName ): """ Delete group from the File Catalog """ return gFileCatalogDB.deleteGroup( groupName, self.getRemoteCredentials() ) ################################################################### # # User/Group read operations # types_getUsers = [] def export_getUsers( self ): """ Get all the users defined in the File Catalog """ return gFileCatalogDB.getUsers( self.getRemoteCredentials() ) types_getGroups = [] def export_getGroups( self ): """ Get all the groups defined in the File Catalog """ return gFileCatalogDB.getGroups( self.getRemoteCredentials() ) ######################################################################## # # Path read operations # types_exists = [ [ ListType, DictType ] + list( StringTypes ) ] def export_exists( self, lfns ): """ Check whether the supplied paths exists """ return gFileCatalogDB.exists( lfns, self.getRemoteCredentials() ) ######################################################################## # # File write operations # types_addFile = [ [ ListType, DictType ] + list( StringTypes ) ] def export_addFile( self, lfns ): """ Register supplied files """ gMonitor.addMark( "AddFile", 1 ) res = gFileCatalogDB.addFile( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "AddFileSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "AddFileFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_removeFile = [ [ ListType, DictType ] + list( StringTypes ) ] def export_removeFile( self, lfns ): """ Remove the supplied lfns """ gMonitor.addMark( "RemoveFile", 1 ) res = gFileCatalogDB.removeFile( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "RemoveFileSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "RemoveFileFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_setFileStatus = [ DictType ] def export_setFileStatus( self, lfns ): """ Remove the supplied lfns """ return gFileCatalogDB.setFileStatus( lfns, self.getRemoteCredentials() ) types_addReplica = [ [ ListType, DictType ] + list( StringTypes ) ] def export_addReplica( self, lfns ): """ Register supplied replicas """ gMonitor.addMark( "AddReplica", 1 ) res = gFileCatalogDB.addReplica( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "AddReplicaSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "AddReplicaFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_removeReplica = [ [ ListType, DictType ] + list( StringTypes ) ] def export_removeReplica( self, lfns ): """ Remove the supplied replicas """ gMonitor.addMark( "RemoveReplica", 1 ) res = gFileCatalogDB.removeReplica( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "RemoveReplicaSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "RemoveReplicaFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_setReplicaStatus = [ [ ListType, DictType ] + list( StringTypes ) ] def export_setReplicaStatus( self, lfns ): """ Set the status for the supplied replicas """ return gFileCatalogDB.setReplicaStatus( lfns, self.getRemoteCredentials() ) types_setReplicaHost = [ [ ListType, DictType ] + list( StringTypes ) ] def export_setReplicaHost( self, lfns ): """ Change the registered SE for the supplied replicas """ return gFileCatalogDB.setReplicaHost( lfns, self.getRemoteCredentials() ) types_addFileAncestors = [ DictType ] def export_addFileAncestors( self, lfns ): """ Add file ancestor information for the given list of LFNs """ return gFileCatalogDB.addFileAncestors( lfns, self.getRemoteCredentials() ) ######################################################################## # # File read operations # types_isFile = [ [ ListType, DictType ] + list( StringTypes ) ] def export_isFile( self, lfns ): """ Check whether the supplied lfns are files """ return gFileCatalogDB.isFile( lfns, self.getRemoteCredentials() ) types_getFileSize = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getFileSize( self, lfns ): """ Get the size associated to supplied lfns """ return gFileCatalogDB.getFileSize( lfns, self.getRemoteCredentials() ) types_getFileMetadata = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getFileMetadata( self, lfns ): """ Get the metadata associated to supplied lfns """ return gFileCatalogDB.getFileMetadata( lfns, self.getRemoteCredentials() ) types_getReplicas = [ [ ListType, DictType ] + list( StringTypes ), BooleanType ] def export_getReplicas( self, lfns, allStatus = False ): """ Get replicas for supplied lfns """ return gFileCatalogDB.getReplicas( lfns, allStatus, self.getRemoteCredentials() ) types_getReplicaStatus = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getReplicaStatus( self, lfns ): """ Get the status for the supplied replicas """ return gFileCatalogDB.getReplicaStatus( lfns, self.getRemoteCredentials() ) types_getFileAncestors = [ ListType, [ ListType, IntType, LongType ] ] def export_getFileAncestors( self, lfns, depths ): """ Get the status for the supplied replicas """ dList = depths if type( dList ) != ListType: dList = [ depths ] lfnDict = dict.fromkeys( lfns, True ) return gFileCatalogDB.getFileAncestors( lfnDict, dList, self.getRemoteCredentials() ) types_getFileDescendents = [ ListType, [ ListType, IntType, LongType ] ] def export_getFileDescendents( self, lfns, depths ): """ Get the status for the supplied replicas """ dList = depths if type( dList ) != ListType: dList = [depths] lfnDict = dict.fromkeys( lfns, True ) return gFileCatalogDB.getFileDescendents( lfnDict, dList, self.getRemoteCredentials() ) ######################################################################## # # Directory write operations # types_createDirectory = [ [ ListType, DictType ] + list( StringTypes ) ] def export_createDirectory( self, lfns ): """ Create the supplied directories """ return gFileCatalogDB.createDirectory( lfns, self.getRemoteCredentials() ) types_removeDirectory = [ [ ListType, DictType ] + list( StringTypes ) ] def export_removeDirectory( self, lfns ): """ Remove the supplied directories """ return gFileCatalogDB.removeDirectory( lfns, self.getRemoteCredentials() ) ######################################################################## # # Directory read operations # types_listDirectory = [ [ ListType, DictType ] + list( StringTypes ), BooleanType ] def export_listDirectory( self, lfns, verbose ): """ List the contents of supplied directories """ gMonitor.addMark( 'ListDirectory', 1 ) return gFileCatalogDB.listDirectory( lfns, self.getRemoteCredentials(), verbose = verbose ) types_isDirectory = [ [ ListType, DictType ] + list( StringTypes ) ] def export_isDirectory( self, lfns ): """ Determine whether supplied path is a directory """ return gFileCatalogDB.isDirectory( lfns, self.getRemoteCredentials() ) types_getDirectorySize = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getDirectorySize( self, lfns, longOut = False, fromFiles = False ): """ Get the size of the supplied directory """ return gFileCatalogDB.getDirectorySize( lfns, longOut, fromFiles, self.getRemoteCredentials() ) types_getDirectoryReplicas = [ [ ListType, DictType ] + list( StringTypes ), BooleanType ] def export_getDirectoryReplicas( self, lfns, allStatus = False ): """ Get replicas for files in the supplied directory """ return gFileCatalogDB.getDirectoryReplicas( lfns, allStatus, self.getRemoteCredentials() ) ######################################################################## # # Administrative database operations # types_getCatalogCounters = [] def export_getCatalogCounters( self ): """ Get the number of registered directories, files and replicas in various tables """ return gFileCatalogDB.getCatalogCounters( self.getRemoteCredentials() ) types_rebuildDirectoryUsage = [] @staticmethod def export_rebuildDirectoryUsage(): """ Rebuild DirectoryUsage table from scratch """ return gFileCatalogDB.rebuildDirectoryUsage() types_repairCatalog = [] def export_repairCatalog( self ): """ Repair the catalog inconsistencies """ return gFileCatalogDB.repairCatalog( self.getRemoteCredentials() ) ######################################################################## # Metadata Catalog Operations # types_addMetadataField = [ StringTypes, StringTypes ] def export_addMetadataField( self, fieldName, fieldType, metaType = '-d' ): """ Add a new metadata field of the given type """ if metaType.lower() == "-d": return gFileCatalogDB.dmeta.addMetadataField( fieldName, fieldType, self.getRemoteCredentials() ) elif metaType.lower() == "-f": return gFileCatalogDB.fmeta.addMetadataField( fieldName, fieldType, self.getRemoteCredentials() ) else: return S_ERROR( 'Unknown metadata type %s' % metaType ) types_deleteMetadataField = [ StringTypes ] def export_deleteMetadataField( self, fieldName ): """ Delete the metadata field """ result = gFileCatalogDB.dmeta.deleteMetadataField( fieldName, self.getRemoteCredentials() ) error = '' if not result['OK']: error = result['Message'] result = gFileCatalogDB.fmeta.deleteMetadataField( fieldName, self.getRemoteCredentials() ) if not result['OK']: if error: result["Message"] = error + "; " + result["Message"] return result types_getMetadataFields = [ ] def export_getMetadataFields( self ): """ Get all the metadata fields """ resultDir = gFileCatalogDB.dmeta.getMetadataFields( self.getRemoteCredentials() ) if not resultDir['OK']: return resultDir resultFile = gFileCatalogDB.fmeta.getFileMetadataFields( self.getRemoteCredentials() ) if not resultFile['OK']: return resultFile return S_OK( { 'DirectoryMetaFields' : resultDir['Value'], 'FileMetaFields' : resultFile['Value'] } ) types_setMetadata = [ StringTypes, DictType ] def export_setMetadata( self, path, metadatadict ): """ Set metadata parameter for the given path """ return gFileCatalogDB.setMetadata( path, metadatadict, self.getRemoteCredentials() ) types_setMetadataBulk = [ DictType ] def export_setMetadataBulk( self, pathMetadataDict ): """ Set metadata parameter for the given path """ return gFileCatalogDB.setMetadataBulk( pathMetadataDict, self.getRemoteCredentials() ) types_removeMetadata = [ DictType ] def export_removeMetadata( self, pathMetadataDict ): """ Remove the specified metadata for the given path """ return gFileCatalogDB.removeMetadata( pathMetadataDict, self.getRemoteCredentials() ) types_getDirectoryMetadata = [ StringTypes ] def export_getDirectoryMetadata( self, path ): """ Get all the metadata valid for the given directory path """ return gFileCatalogDB.dmeta.getDirectoryMetadata( path, self.getRemoteCredentials() ) types_getFileUserMetadata = [ StringTypes ] def export_getFileUserMetadata( self, path ): """ Get all the metadata valid for the given file """ return gFileCatalogDB.fmeta.getFileUserMetadata( path, self.getRemoteCredentials() ) types_findDirectoriesByMetadata = [ DictType ] def export_findDirectoriesByMetadata( self, metaDict, path = '/' ): """ Find all the directories satisfying the given metadata set """ return gFileCatalogDB.dmeta.findDirectoriesByMetadata ( metaDict, path, self.getRemoteCredentials() ) types_findFilesByMetadata = [ DictType, StringTypes ] def export_findFilesByMetadata( self, metaDict, path = '/' ): """ Find all the files satisfying the given metadata set """ return gFileCatalogDB.fmeta.findFilesByMetadata( metaDict, path, self.getRemoteCredentials() ) types_getReplicasByMetadata = [ DictType, StringTypes, BooleanType ] def export_getReplicasByMetadata( self, metaDict, path = '/', allStatus = False ): """ Find all the files satisfying the given metadata set """ return gFileCatalogDB.fileManager.getReplicasByMetadata( metaDict, path, allStatus, self.getRemoteCredentials() ) types_findFilesByMetadataDetailed = [ DictType, StringTypes ] def export_findFilesByMetadataDetailed( self, metaDict, path = '/' ): """ Find all the files satisfying the given metadata set """ result = gFileCatalogDB.fmeta.findFilesByMetadata( metaDict, path, self.getRemoteCredentials() ) if not result['OK'] or not result['Value']: return result lfns = [] for directory in result['Value']: for fname in result['Value'][directory]: lfns.append( os.path.join( directory, fname ) ) return gFileCatalogDB.getFileDetails( lfns, self.getRemoteCredentials() ) types_findFilesByMetadataWeb = [ DictType, StringTypes, [IntType, LongType], [IntType, LongType]] def export_findFilesByMetadataWeb( self, metaDict, path, startItem, maxItems ): """ Find files satisfying the given metadata set """ result = gFileCatalogDB.dmeta.findFileIDsByMetadata( metaDict, path, self.getRemoteCredentials(), startItem, maxItems ) if not result['OK'] or not result['Value']: return result fileIDs = result['Value'] totalRecords = result['TotalRecords'] result = gFileCatalogDB.fileManager._getFileLFNs( fileIDs ) if not result['OK']: return result lfnsResultList = result['Value']['Successful'].values() resultDetails = gFileCatalogDB.getFileDetails( lfnsResultList, self.getRemoteCredentials() ) if not resultDetails['OK']: return resultDetails result = S_OK( {"TotalRecords":totalRecords, "Records":resultDetails['Value'] } ) return result def findFilesByMetadataWeb( self, metaDict, path, startItem, maxItems ): """ Find all the files satisfying the given metadata set """ result = gFileCatalogDB.fmeta.findFilesByMetadata( metaDict, path, self.getRemoteCredentials() ) if not result['OK'] or not result['Value']: return result lfns = [] for directory in result['Value']: for fname in result['Value'][directory]: lfns.append( os.path.join( directory, fname ) ) start = startItem totalRecords = len( lfns ) if start > totalRecords: return S_ERROR( 'Requested files out of existing range' ) end = start + maxItems if end > totalRecords: end = totalRecords lfnsResultList = lfns[start:end] resultDetails = gFileCatalogDB.getFileDetails( lfnsResultList, self.getRemoteCredentials() ) if not resultDetails['OK']: return resultDetails result = S_OK( {"TotalRecords":totalRecords, "Records":resultDetails['Value'] } ) return result types_getCompatibleMetadata = [ DictType, StringTypes ] def export_getCompatibleMetadata( self, metaDict, path = '/' ): """ Get metadata values compatible with the given metadata subset """ return gFileCatalogDB.dmeta.getCompatibleMetadata( metaDict, path, self.getRemoteCredentials() ) types_addMetadataSet = [ StringTypes, DictType ] def export_addMetadataSet( self, setName, setDict ): """ Add a new metadata set """ return gFileCatalogDB.dmeta.addMetadataSet( setName, setDict, self.getRemoteCredentials() ) types_getMetadataSet = [ StringTypes, BooleanType ] def export_getMetadataSet( self, setName, expandFlag ): """ Add a new metadata set """ return gFileCatalogDB.dmeta.getMetadataSet( setName, expandFlag, self.getRemoteCredentials() ) types_listMetadataSets = [] def export_listMetadataSets(self): """ Get the list of metadata sets with their definitions """ return gFileCatalogDB.dmeta.listMetadataSets(self.getRemoteCredentials()) ######################################################################################### # # Dataset manipulation methods # types_addDataset = [ StringTypes, DictType ] def export_addDataset( self, datasetName, metaQuery ): """ Add a new dynamic dataset defined by its meta query """ return gFileCatalogDB.datasetManager.addDataset( datasetName, metaQuery, self.getRemoteCredentials() ) types_addDatasetAnnotation = [ DictType ] def export_addDatasetAnnotation( self, datasetDict ): """ Add annotation to an already created dataset """ return gFileCatalogDB.datasetManager.addDatasetAnnotation( datasetDict, self.getRemoteCredentials() ) types_removeDataset = [ StringTypes ] def export_removeDataset( self, datasetName ): """ Check the given dynamic dataset for changes since its definition """ return gFileCatalogDB.datasetManager.removeDataset( datasetName, self.getRemoteCredentials() ) types_checkDataset = [ StringTypes ] def export_checkDataset( self, datasetName ): """ Check the given dynamic dataset for changes since its definition """ return gFileCatalogDB.datasetManager.checkDataset( datasetName, self.getRemoteCredentials() ) types_updateDataset = [ StringTypes ] def export_updateDataset( self, datasetName ): """ Update the given dynamic dataset for changes since its definition """ return gFileCatalogDB.datasetManager.updateDataset( datasetName, self.getRemoteCredentials() ) types_getDatasets = [ list( StringTypes ) + [ListType] ] def export_getDatasets( self, datasetName ): """ Get parameters of the given dynamic dataset as they are stored in the database """ return gFileCatalogDB.datasetManager.getDatasets( datasetName, self.getRemoteCredentials() ) types_getDatasetParameters = [ StringTypes ] def export_getDatasetParameters( self, datasetName ): """ Get parameters of the given dynamic dataset as they are stored in the database """ return gFileCatalogDB.datasetManager.getDatasetParameters( datasetName, self.getRemoteCredentials() ) types_getDatasetAnnotation = [ list( StringTypes ) + [ListType] ] def export_getDatasetAnnotation( self, datasetName ): """ Get annotation of the given datasets """ return gFileCatalogDB.datasetManager.getDatasetAnnotation( datasetName, self.getRemoteCredentials() ) types_freezeDataset = [ StringTypes ] def export_freezeDataset( self, datasetName ): """ Freeze the contents of the dataset making it effectively static """ return gFileCatalogDB.datasetManager.freezeDataset( datasetName, self.getRemoteCredentials() ) types_releaseDataset = [ StringTypes ] def export_releaseDataset( self, datasetName ): """ Release the contents of the frozen dataset allowing changes in its contents """ return gFileCatalogDB.datasetManager.releaseDataset( datasetName, self.getRemoteCredentials() ) types_getDatasetFiles = [ StringTypes ] def export_getDatasetFiles( self, datasetName ): """ Get lfns in the given dataset """ return gFileCatalogDB.datasetManager.getDatasetFiles( datasetName, self.getRemoteCredentials() )	Sbalbp/DIRAC	DataManagementSystem/Service/FileCatalogHandler.py	Python	gpl-3.0	27,381	[ "DIRAC" ]	3c8e5859724ef4e5a61a86e61ce03b65130071b9677124f53073409ceeeb5ab9
""" This is a setup.py script generated by py2applet Usage: python setup.py py2app """ from setuptools import setup APP = ['main.py'] DATA_FILES = [ 'config.json', 'firefly-blacklist.txt', 'firefly-blacklist.meta.json', 'firefly-hosts.txt', 'firefly-hosts.meta.json', 'firefly-hosts-disabled.txt', 'custom-blacklist.txt', 'custom-whitelist.txt', 'meek-relays.txt', 'cacert.pem', 'README.md', 'LICENSE', ('webpanel', ['webpanel/static', ]), ('webpanel', ['webpanel/templates', ]) ] OPTIONS = { 'iconfile': 'firefly.icns', 'plist': {'CFBundleShortVersionString':'0.3.0',}, 'argv_emulation': True } setup( name="Firefly", version="0.3.0", app=APP, data_files=DATA_FILES, options={'py2app': OPTIONS}, setup_requires=['py2app'], )	Jonavin/firefly-proxy	setup_mac.py	Python	bsd-2-clause	826	[ "Firefly" ]	71a96ba7e6006da35f4c2442ecc7f67e2eceffc652440d7d032d4d2b6cd8da8e
# Copyright 2016 Mingbo Cai, Princeton Neuroscience Instititute, # Princeton University # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Bayesian Representational Similarity Analysis (BRSA) This implementation is based on [Cai2016]_ and [Cai2019]_: .. [Cai2016] "A Bayesian method for reducing bias in neural representational similarity analysis", M.B. Cai, N.W. Schuck, J.W. Pillow, Y. Niv, Advances in Neural Information Processing Systems 29, 2016, 4952--4960 Available at: http://papers.nips.cc/paper/6131-a-bayesian-method-for-reducing-bias-in-neural-representational-similarity-analysis.pdf .. [Cai2019] "Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias", M.B. Cai, N.W. Schuck, J.W. Pillow, Y. Niv, PLoS computational biology 15.5 (2019): e1006299. https://doi.org/10.1371/journal.pcbi.1006299 `.BRSA` is based on [Cai2016] with additional consideration of spatial noise correlation proposed in [Cai2019]. `.GBRSA` is based on [Cai2019]. `.GBRSA` may perform better than `.BRSA` due to marginalization of all voxel-wise parameters. It can be use for single participant as well. """ # Authors: Mingbo Cai # Princeton Neuroscience Institute, Princeton University, 2016 import numpy as np import scipy import scipy.optimize import scipy.stats import scipy.special import time from sklearn.base import BaseEstimator, TransformerMixin from sklearn.utils import assert_all_finite, check_random_state from sklearn.decomposition import PCA, FactorAnalysis, SparsePCA, FastICA import logging import brainiak.utils.utils as utils import scipy.spatial.distance as spdist from nitime import algorithms as alg import copy logger = logging.getLogger(__name__) __all__ = [ "BRSA", "GBRSA", "Ncomp_SVHT_MG_DLD_approx", "prior_GP_var_inv_gamma", "prior_GP_var_half_cauchy", ] def prior_GP_var_inv_gamma(y_invK_y, n_y, tau_range): """ Imposing an inverse-Gamma prior onto the variance (tau^2) parameter of a Gaussian Process, which is in turn a prior imposed over an unknown function y = f(x). The inverse-Gamma prior of tau^2, tau^2 ~ invgamma(shape, scale) is described by a shape parameter alpha=2 and a scale parameter beta=tau_range^2. tau_range describes the reasonable range of tau in the inverse-Gamma prior. The data y's at locations x's are assumed to follow Gaussian Process: f(x, x') ~ N(0, K(x, x') / 2 tau^2), where K is a kernel function defined on x. For n observations, K(x1, x2, ..., xn) is an n by n positive definite matrix. Given the prior parameter tau_range, number of observations n_y, and y_invK_y = y * inv(K) * y', the function returns the MAP estimate of tau^2 and the log posterior probability of tau^2 at the MAP value: log(p(tau^2\|tau_range)). This function is written primarily for BRSA but can also be used elsewhere. y in this case corresponds to the log of SNR in each voxel. GBRSA does not rely on this function. An alternative form of prior is half-Cauchy prior on tau. Inverse-Gamma prior penalizes for both very small and very large values of tau, while half-Cauchy prior only penalizes for very large values of tau. For more information on usage, see description in BRSA class: `.BRSA` See also: `.prior_GP_var_half_cauchy` Parameters ---------- y_invK_y: float y * inv(K) * y^T, where y=f(x) is a vector of observations of unknown function f at different locations x. K is correlation matrix of f between different locations, based on a Gaussian Process (GP) describing the smoothness property of f. K fully incorporates the form of the kernel and the length scale of the GP, but not the variance of the GP (the purpose of this function is to estimate the variance). n_y: int, number of observations tau_range: float, The reasonable range of tau, the standard deviation of the Gaussian Process imposed on y=f(x). tau_range is parameter of the inverse-Gamma prior. Say, if you expect the standard deviation of the Gaussian process to be around 3, tau_range can be set to 3. The smaller it is, the more penalization is imposed on large variation of y. Returns ------- tau2: The MAP estimation of tau^2 based on the prior on tau and y_invK_y. log_ptau: log(p(tau)) of the returned tau^2 based on the inverse-Gamma prior. """ alpha = 2 tau2 = (y_invK_y + 2 * tau_range*2) / (alpha 2 + 2 + n_y) log_ptau = scipy.stats.invgamma.logpdf( tau2, scale=tau_range*2, a=2) return tau2, log_ptau def prior_GP_var_half_cauchy(y_invK_y, n_y, tau_range): """ Imposing a half-Cauchy prior onto the standard deviation (tau) of the Gaussian Process which is in turn a prior imposed over a function y = f(x). The scale parameter of the half-Cauchy prior is tau_range. The function returns the MAP estimate of tau^2 and log(p(tau\|tau_range)) for the MAP value of tau^2, where tau_range describes the reasonable range of tau in the half-Cauchy prior. An alternative form of prior is inverse-Gamma prior on tau^2. Inverse-Gamma prior penalizes for both very small and very large values of tau, while half-Cauchy prior only penalizes for very large values of tau. For more information on usage, see description in BRSA class: `.BRSA` """ tau2 = (y_invK_y - n_y tau_range2 + np.sqrt(n_y2 * tau_range*4 + (2 n_y + 8) * tau_range*2 y_invK_y + y_invK_y2))\ / 2 / (n_y + 2) log_ptau = scipy.stats.halfcauchy.logpdf( tau20.5, scale=tau_range) return tau2, log_ptau def Ncomp_SVHT_MG_DLD_approx(X, zscore=True): """ This function implements the approximate calculation of the optimal hard threshold for singular values, by Matan Gavish and David L. Donoho: "The optimal hard threshold for singular values is 4 / sqrt(3)" http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6846297 Parameters ---------- X: 2-D numpy array of size [n_T, n_V] The data to estimate the optimal rank for selecting principal components. zscore: Boolean Whether to z-score the data before calculating number of components. Returns ------- ncomp: integer The optimal number of components determined by the method of MG and DLD """ beta = X.shape[0] / X.shape[1] if beta > 1: beta = 1 / beta omega = 0.56 * beta ** 3 - 0.95 * beta ** 2 + 1.82 * beta + 1.43 if zscore: sing = np.linalg.svd(_zscore(X), False, False) else: sing = np.linalg.svd(X, False, False) thresh = omega * np.median(sing) ncomp = int(np.sum(np.logical_and(sing > thresh, np.logical_not( np.isclose(sing, thresh))))) # In the line above, we look for the singular values larger than # the threshold but excluding those that happen to be "just" larger # than the threshold by an amount close to the numerical precision. # This is to prevent close-to-zero singular values to be included if # the median of the eigenvalues is close to 0 (which could happen # when the input X has lower rank than its minimal size. return ncomp def _zscore(a): """ Calculating z-score of data on the first axis. If the numbers in any column are all equal, scipy.stats.zscore will return NaN for this column. We shall correct them all to be zeros. Parameters ---------- a: numpy array Returns ------- zscore: numpy array The z-scores of input "a", with any columns including non-finite numbers replaced by all zeros. """ assert a.ndim > 1, 'a must have more than one dimensions' zscore = scipy.stats.zscore(a, axis=0) zscore[:, np.logical_not(np.all(np.isfinite(zscore), axis=0))] = 0 return zscore class BRSA(BaseEstimator, TransformerMixin): """Bayesian representational Similarity Analysis (BRSA) Given the time series of neural imaging data in a region of interest (ROI) and the hypothetical neural response (design matrix) to each experimental condition of interest, calculate the shared covariance matrix U of the voxels(recording unit)' response profiles \\beta_i to each condition, and the relative SNR of each voxels. The relative SNR could be considered as the degree of contribution of each voxel to this shared covariance matrix. A correlation matrix converted from the covariance matrix U will be provided as a quantification of neural representational similarity. .. math:: Y = X \\cdot \\beta + X_0 \\cdot \\beta_0 + \\epsilon \\beta_i \\sim N(0,(s_{i} \\sigma_{i})^2 U) \\epsilon_i \\sim AR(1) Please note that the model assumes that the covariance matrix U which all \\beta_i follow is zero-meaned. This assumption does not imply there must be both positive and negative responses across voxels. However, it means that Bayesian RSA treats the task-evoked activity against baseline BOLD level as signal, while in other RSA tools the deviation of task-evoked activity in each voxel from the average task-evoked activity level across voxels may be considered as signal of interest. Due to this assumption in BRSA, relatively high degree of similarity may be expected when the activity patterns of two task conditions both include strong sensory driven signals regardless of their specific stimuli. When two task conditions elicit exactly the same activity patterns but only differ in their global magnitudes, under the assumption in BRSA, their similarity is 1; under the assumption that only deviation of pattern from average patterns is signal of interest, their similarity should be -1. Parameters ---------- n_iter : int. Number of maximum iterations to run the algorithm. rank : int. Default: None The rank of the covariance matrix. If not provided, the covariance matrix will be assumed to be full rank. When you have many conditions (e.g., calculating the similarity matrix of responses to each event), you might try specifying a lower rank. auto_nuisance: boolean. In order to model spatial correlation between voxels that cannot be accounted for by common response captured in the design matrix, we assume that a set of time courses not related to the task conditions are shared across voxels with unknown amplitudes. One approach is for users to provide time series which they consider as nuisance but exist in the noise (such as head motion). The other way is to take the first n_nureg principal components in the residual after subtracting the response to the design matrix from the data, and use these components as the nuisance regressor. This flag is for the second approach. If turned on, PCA or factor analysis will be applied to the residuals to obtain new nuisance regressors in each round of fitting. These two approaches can be combined. If the users provide nuisance regressors and set this flag as True, then the first n_nureg principal components of the residuals after subtracting both the responses to design matrix and the user-supplied nuisance regressors will be used in addition to the nuisance regressors provided by the users. Note that nuisance regressor is not required from user. If it is not provided, DC components for each run will be included as nuisance regressor regardless of the auto_nuisance parameter. n_nureg: Optional[int]. Number of nuisance regressors to use in order to model signals shared across voxels not captured by the design matrix. This number is in addition to any nuisance regressor that the user has already provided. If set to None, the number of nuisance regressors will be automatically determined based on M Gavish and D Donoho's approximate estimation of optimal hard threshold for singular values. This only takes effect if auto_nuisance is True. nureg_zscore: boolean. A flag to tell the algorithm whether data is z-scored before estimating the number of nuisance regressor components necessary to account for spatial noise correlation. It also determinie whether the residual noise is z-scored before estimating the nuisance regressors from residual. This only takes effect if auto_nuisance is True. nureg_method: string, naming a method from sklearn.decomposition. 'PCA', 'ICA', 'FA' or 'SPCA' are currently supported. The method to estimate the shared component in noise across voxels. This only takes effect if auto_nuisance is True. baseline_single: boolean. A time course of constant 1 will be included to the nuisance regressor regardless of whether the user requests. If baseline_single is set to False, one such regressor is included for each fMRI run, but a single component in beta0\\_ will be computed as the average of the weight maps corresponding to these regressors. This might cause underestimation of noise variance. If baseline_single is True, only one regressor of constant 1 will be used for the whole dataset. This might be desirable if you believe the average image intensity might not scale with the same proportion for different voxels across scan. In other words, it is possible that some part of the brain is more vulnerable to change in baseline intensity due to facts such as field inhomogeneity. Setting baseline_single to True will force the nuisance regressors automatically estimated from residuals to capture this. However, when each task condition only occurs in one run and when the design matrix in each run sums together close to a flat line, this option can cause the estimated similarity to be extremely high between conditions occuring in the same run. GP_space: boolean. Whether to impose a Gaussion Process (GP) prior on the log(pseudo-SNR). If true, the GP has a kernel defined over spatial coordinate of each voxel. The idea behind this option is that adjacent voxels should have similar SNRs. This is relatively slow for big ROI. We find that when SNR is generally low, smoothness can be overestimated. But such regularization may reduce variance in the estimated SNR map and similarity matrix. GP_inten: boolean. Whether to include a kernel defined over the intensity of image. GP_space should be True as well if you want to use this, because the smoothness should be primarily in space. Smoothness in intensity is just complementary. The idea behind this option is that voxels should have similar SNRs when they are both adjacent (imposed by GP_space) and are of the same tissue type (when their image intensities are close). If you accept the second assumption, then you can set GP_inten as True and provide an array to the `inten` variable, expressing the intensities (brightness) for each voxel. space_smooth_range: float. The distance (in unit the same as what you would use when supplying the spatial coordiates of each voxel, typically millimeter) which you believe is the maximum range of the length scale parameter of Gaussian Process defined over voxel location. This is used to impose a half-Cauchy prior on the length scale. If set to None, the program will default to half of the maximum distance between all voxels. inten_smooth_range: float. The difference in image intensity which you believe is the maximum range of plausible length scale for the Gaussian Process defined over image intensity. Length scales larger than this are allowed, but will be penalized. If set to None, this parameter will default to half of the maximal intensity difference. tau_range: float. The reasonable range of the standard deviation of log(SNR). This range should not be too large. 5 is a loose range. When a Gaussian Process is imposed on the log(SNR), this parameter is used in a half-Cauchy prior on the standard deviation, or an inverse-Gamma prior on the variance of the GP. tau2_prior: Callable[[float, int, float]], [float, float]], Default: prior_GP_var_inv_gamma. Can be prior_GP_var_inv_gamma or prior_GP_var_half_cauchy, or a custom function. The function which impose a prior for tau^2, the variance of the GP prior on log(SNR), and returns the MAP estimate of tau^2. It can be either prior_GP_var_inv_gamma for inverse-Gamma or prior_GP_var_half_cauchy for half-Cauchy. half-Cauchy prior is in fact imposed on tau. But tau_range describes the range of tau in the prior in both cases. Both functions are part of brsa module. See also `.prior_GP_var_inv_gamma` and `.prior_GP_var_half_cauchy` To use the default inverse-Gamma prior, you can ignore this argument:: from brainiak.reprsimil.brsa import BRSA brsa = BRSA() If you want to try the alternative half-Cauchy prior, then you need to import it in addition to BRSA:: from brainiak.reprsimil.brsa import BRSA, prior_GP_var_half_cauchy brsa = BRSA(tau2_prior=prior_GP_var_half_cauchy) eta: float. A small number added to the diagonal element of the covariance matrix in the Gaussian Process prior. This is to ensure that the matrix is invertible. init_iter: int. How many initial iterations to fit the model without introducing the GP prior before fitting with it, if GP_space or GP_inten is requested. This initial fitting is to give the parameters a good starting point. optimizer: str or callable. The optimizer to use for minimizing cost function which scipy.optimize.minimize can accept. We use 'L-BFGS-B' as a default. Users can try other strings corresponding to optimizer provided by scipy.optimize.minimize, or a custom optimizer, such as 'BFGS' or 'CG'. Note that BRSA fits a lot of parameters. So a chosen optimizer should accept gradient (Jacobian) of the cost function. Otherwise the fitting is likely to be unbarely slow. We do not calculate Hessian of the objective function. So an optimizer which requires Hessian cannot be used. random_state : RandomState or an int seed. A random number generator instance to define the state of the random permutations generator whenever the module needs to generate random number (e.g., initial parameter of the Cholesky factor). anneal_speed: float. Annealing is introduced in fitting of the Cholesky decomposition of the shared covariance matrix. The amount of perturbation decays exponentially. This parameter sets the ratio of the maximum number of iteration to the time constant of the exponential. anneal_speed=10 means by n_iter/10 iterations, the amount of perturbation is reduced by 2.713 times. minimize_options: dictionary. Default: {'gtol': 1e-4, 'disp': False, 'maxiter': 6} This is the dictionary passed as the options argument to scipy.optimize.minize which minimizes the cost function during fitting. Notice that the minimization is performed for many times, alternating between optimizing the covariance matrix U underlying the pattern similarity matrix, and SNR. At most n_iter times of this alternation is performed. So within each step of fitting, the step of iteration performed by scipy.optimize.minize does not have to be very large. In other words, scipy.optimize.minize does not need to converge within each step of the alternating fitting procedure. tol: float. Tolerance parameter passed to scipy.optimize.minimize. It is also used for determining convergence of the alternating fitting procedure. Attributes ---------- U_ : numpy array, shape=[condition,condition]. The shared covariance matrix. L_ : numpy array, shape=[condition,rank]. The Cholesky factor of the shared covariance matrix (lower-triangular matrix). C_: numpy array, shape=[condition,condition]. The correlation matrix derived from the shared covariance matrix. This is the estimated similarity matrix between neural patterns to your task conditions. Notice that it is recommended that you also check U\\_, which is the covariance matrix underlying this correlation matrix. In cases there is almost no response to your task conditions, the diagonal values of U\\_ would become very small and C\\_ might contain many correlation coefficients close to 1 or -1. This might not reflect true strong correlation or strong negative correlation, but a result of lack of task-related neural activity, design matrix that does not match true neural response, or not enough data. It is also recommended to check nSNR\\_ after mapping it back to the brain. A "reasonable" map should at least have higher values in gray matter in than white matter. nSNR_ : numpy array, shape=[voxels,]. The normalized pseuso-SNR of all voxels. They are normalized such that the geometric mean is 1. Note that this attribute can not be interpreted as true SNR, but the relative ratios between voxel indicates the contribution of each voxel to the representational similarity structure. sigma_ : numpy array, shape=[voxels,]. The estimated standard deviation of the noise in each voxel Assuming AR(1) model, this means the standard deviation of the innovation noise. rho_ : numpy array, shape=[voxels,]. The estimated autoregressive coefficient of each voxel bGP_ : float, only if GP_space or GP_inten is True. The standard deviation of the GP prior lGPspace_ : float, only if GP_space or GP_inten is True The length scale of Gaussian Process prior of log(SNR) lGPinten_: float, only if GP_inten is True The length scale in fMRI intensity of the GP prior of log(SNR) beta_: array, shape=[conditions, voxels] The maximum a posterior estimation of the response amplitudes of each voxel to each task condition. beta0_: numpy array, shape=[n_nureg + n_base, voxels] The loading weights of each voxel for the shared time courses not captured by the design matrix. This helps capture the structure of spatial covariance of task-unrelated signal. n_base is the number of columns of the user-supplied nuisance regressors plus one for DC component X0_: numpy array, shape=[time_points, n_nureg + n_base] The estimated time course that is shared across voxels but unrelated to the events of interest (design matrix). beta0_null_: numpy array, shape=[n_nureg + n_base, voxels] The equivalent of beta0\\_ in a null model which does not include the design matrix and response pattern beta. X0_null_: numpy array, shape=[time_points, n_nureg + n_base] The equivalent of X0\\_ in a null model which does not include the design matrix and response pattern beta n_nureg_: int Number of nuisance regressor in addition to such regressors provided by the user (if any), if auto_nuisance is set to True. If n_nureg is set to 'opt', this will be estimated from data. 'opt' will use M Gavish and D Donoho's approximate estimation of optimal hard threshold for singular values. random_state_: `RandomState` Random number generator initialized using random_state. """ def __init__( self, n_iter=100, rank=None, auto_nuisance=True, n_nureg=None, nureg_zscore=True, nureg_method='PCA', baseline_single=False, GP_space=False, GP_inten=False, space_smooth_range=None, inten_smooth_range=None, tau_range=5.0, tau2_prior=prior_GP_var_inv_gamma, eta=0.0001, init_iter=20, optimizer='L-BFGS-B', random_state=None, anneal_speed=10, tol=1e-4, minimize_options={'gtol': 1e-4, 'disp': False, 'maxiter': 6}): self.n_iter = n_iter self.rank = rank self.GP_space = GP_space self.GP_inten = GP_inten self.tol = tol self.auto_nuisance = auto_nuisance self.n_nureg = n_nureg self.nureg_zscore = nureg_zscore if auto_nuisance: assert (n_nureg is None) \ or (isinstance(n_nureg, int) and n_nureg > 0), \ 'n_nureg should be a positive integer or None'\ ' if auto_nuisance is True.' if self.nureg_zscore: self.preprocess_residual = lambda x: _zscore(x) else: self.preprocess_residual = lambda x: x if nureg_method == 'FA': self.nureg_method = lambda x: FactorAnalysis(n_components=x) elif nureg_method == 'PCA': self.nureg_method = lambda x: PCA(n_components=x, whiten=True) elif nureg_method == 'SPCA': self.nureg_method = lambda x: SparsePCA(n_components=x, max_iter=20, tol=tol) elif nureg_method == 'ICA': self.nureg_method = lambda x: FastICA(n_components=x, whiten=True) else: raise ValueError('nureg_method can only be FA, PCA, ' 'SPCA(for sparse PCA) or ICA') self.baseline_single = baseline_single self.minimize_options = minimize_options self.eta = eta # This is a tiny ridge added to the Gaussian Process # covariance matrix template to gaurantee that it is invertible. # Mathematically it means we assume that this proportion of the # variance is always independent between voxels for the log(SNR2). self.space_smooth_range = space_smooth_range self.inten_smooth_range = inten_smooth_range # The kernel of the Gaussian Process is the product of a kernel # defined on spatial coordinate and a kernel defined on # image intensity. self.tau_range = tau_range self.tau2_prior = tau2_prior self.init_iter = init_iter # When imposing smoothness prior, fit the model without this # prior for this number of iterations. self.optimizer = optimizer self.random_state = random_state self.anneal_speed = anneal_speed return def fit(self, X, design, nuisance=None, scan_onsets=None, coords=None, inten=None): """Compute the Bayesian RSA Parameters ---------- X: numpy array, shape=[time_points, voxels] If you have multiple scans of the same participants that you want to analyze together, you should concatenate them along the time dimension after proper preprocessing (e.g. spatial alignment), and specify the onsets of each scan in scan_onsets. design: numpy array, shape=[time_points, conditions] This is the design matrix. It should only include the hypothetic response for task conditions. You should not include regressors for a DC component or motion parameters, unless you want to estimate their pattern similarity with response patterns to your task conditions. If you want to model head motion, you should include them in nuisance regressors. If you have multiple run, the design matrix of all runs should be concatenated along the time dimension, with every column for one condition across runs. For example, if you have 3 runs of experiment of one participant, with each run lasting 200 TR. And you have 4 conditions, then design should be a 600 x 4 numpy array. nuisance: optional, numpy array, shape=[time_points, nuisance_factors] The responses to these regressors will be marginalized out from each voxel, which means they are considered, but won't be assumed to share the same pseudo-SNR map with the design matrix. Therefore, the pseudo-SNR map will only reflect the relative contribution of design matrix to each voxel. You can provide time courses such as those for head motion to this parameter. Note that if auto_nuisance is set to True, the first n_nureg principal components of residual (excluding the response to the design matrix and the user-provided nuisance regressors and a constant baseline) will be included as additional nuisance regressor after the first round of fitting. If auto_nuisance is set to False, the nuisance regressors supplied by the users together with DC components will be used as nuisance time series. Please do not include time course of constant baseline in nuisance. scan_onsets: optional, numpy array, shape=[runs,] This specifies the indices of X which correspond to the onset of each scanning run. For example, if you have two experimental runs of the same subject, each with 100 TRs, then scan_onsets should be [0,100]. If you do not provide the argument, the program will assume all data are from the same run. The effect of them is to make the inverse matrix of the temporal covariance matrix of noise block-diagonal. coords: optional, numpy array, shape=[voxels,3] This is the coordinate of each voxel, used for implementing Gaussian Process prior. inten: optional, numpy array, shape=[voxel,] This is the average fMRI intensity in each voxel. It should be calculated from your data without any preprocessing such as z-scoring. Because it should reflect whether a voxel is bright (grey matter) or dark (white matter). A Gaussian Process kernel defined on both coordinate and intensity imposes a smoothness prior on adjcent voxels but with the same tissue type. The Gaussian Process is experimental and has shown good performance on some visual datasets. """ logger.info('Running Bayesian RSA') self.random_state_ = check_random_state(self.random_state) # setting random seed logger.debug('RandState set to {}'.format(self.random_state_)) assert not self.GP_inten or (self.GP_inten and self.GP_space),\ 'You must speficiy GP_space to True'\ 'if you want to use GP_inten' # Check input data assert_all_finite(X) assert X.ndim == 2, 'The data should be 2-dimensional ndarray' assert np.all(np.std(X, axis=0) > 0),\ 'The time courses of some voxels do not change at all.'\ ' Please make sure all voxels are within the brain' # check design matrix assert_all_finite(design) assert design.ndim == 2,\ 'The design matrix should be 2-dimensional ndarray' assert np.linalg.matrix_rank(design) == design.shape[1], \ 'Your design matrix has rank smaller than the number of'\ ' columns. Some columns can be explained by linear '\ 'combination of other columns. Please check your design matrix.' assert np.size(design, axis=0) == np.size(X, axis=0),\ 'Design matrix and data do not '\ 'have the same number of time points.' assert self.rank is None or self.rank <= design.shape[1],\ 'Your design matrix has fewer columns than the rank you set' # Check the nuisance regressors. if nuisance is not None: assert_all_finite(nuisance) assert nuisance.ndim == 2,\ 'The nuisance regressor should be 2-dimensional ndarray' assert np.linalg.matrix_rank(nuisance) == nuisance.shape[1], \ 'The nuisance regressor has rank smaller than the number of'\ 'columns. Some columns can be explained by linear '\ 'combination of other columns. Please check your nuisance' \ 'regressors.' assert np.size(nuisance, axis=0) == np.size(X, axis=0), \ 'Nuisance regressor and data do not have the same '\ 'number of time points.' # check scan_onsets validity assert scan_onsets is None or\ (np.max(scan_onsets) <= X.shape[0] and np.min(scan_onsets) >= 0),\ 'Some scan onsets provided are out of the range of time points.' # check the size of coords and inten if self.GP_space: logger.info('Fitting with Gaussian Process prior on log(SNR)') assert coords is not None and coords.shape[0] == X.shape[1],\ 'Spatial smoothness was requested by setting GP_space. '\ 'But the voxel number of coords does not match that of '\ 'data X, or voxel coordinates are not provided. '\ 'Please make sure that coords is in the shape of '\ '[n_voxel x 3].' assert coords.ndim == 2,\ 'The coordinate matrix should be a 2-d array' if self.GP_inten: assert inten is not None and inten.shape[0] == X.shape[1],\ 'The voxel number of intensity does not '\ 'match that of data X, or intensity not provided.' assert np.var(inten) > 0,\ 'All voxels have the same intensity.' if (not self.GP_space and coords is not None) or\ (not self.GP_inten and inten is not None): logger.warning('Coordinates or image intensity provided' ' but GP_space or GP_inten is not set ' 'to True. The coordinates or intensity are' ' ignored.') # Estimate the number of necessary nuisance regressors if self.auto_nuisance: if self.n_nureg is None: logger.info('number of nuisance regressors is determined ' 'automatically.') run_TRs, n_runs = self._run_TR_from_scan_onsets( X.shape[0], scan_onsets) ts_dc = self._gen_legendre(run_TRs, [0]) _, ts_base, _ = self._merge_DC_to_base( ts_dc, nuisance, False) ts_reg = np.concatenate((ts_base, design), axis=1) beta_hat = np.linalg.lstsq(ts_reg, X, rcond=None)[0] residuals = X - np.dot(ts_reg, beta_hat) self.n_nureg_ = np.max( [1, Ncomp_SVHT_MG_DLD_approx(residuals, self.nureg_zscore)]) logger.info('Use {} nuisance regressors to model the spatial ' 'correlation in noise.'.format(self.n_nureg_)) self.n_nureg_ = np.int32(self.n_nureg_) else: self.n_nureg_ = self.n_nureg self.n_nureg_ = np.int32(self.n_nureg_) # Run Bayesian RSA # Note that we have a change of notation here. Within _fit_RSA_UV, # design matrix is named X and data is named Y, to reflect the # generative model that data Y is generated by mixing the response # X to experiment conditions and other neural activity. # However, in fit(), we keep the tradition of scikit-learn that # X is the input data to fit and y, a reserved name not used, is # the label to map to from X. if not self.GP_space: # If GP_space is not requested, then the model is fitted # without imposing any Gaussian Process prior on log(SNR^2) self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self._beta_latent_, self.sigma_, self.rho_, _, _, _,\ self.X0_ = self._fit_RSA_UV(X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets) elif not self.GP_inten: # If GP_space is requested, but GP_inten is not, a GP prior # based on spatial locations of voxels will be imposed. self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self._beta_latent_, self.sigma_, self.rho_, \ self.lGPspace_, self.bGP_, _, \ self.X0_ = self._fit_RSA_UV( X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets, coords=coords) else: # If both self.GP_space and self.GP_inten are True, # a GP prior based on both location and intensity is imposed. self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self._beta_latent_, self.sigma_, self.rho_, \ self.lGPspace_, self.bGP_, self.lGPinten_, self.X0_ = \ self._fit_RSA_UV(X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets, coords=coords, inten=inten) self.C_ = utils.cov2corr(self.U_) self.design_ = design.copy() self._rho_design_, self._sigma2_design_ = \ self._est_AR1(self.design_, same_para=True) self._rho_X0_, self._sigma2_X0_ = self._est_AR1(self.X0_) # AR(1) parameters of the design matrix and nuisance regressors, # which will be used in transform or score. # Finally, we fit a null model with the same setting except # that there is no response to X self.beta0_null_, self.sigma_null_, self.rho_null_, \ self.X0_null_ = self._fit_null(Y=X, X_base=nuisance, scan_onsets=scan_onsets) self._rho_X0_null_, self._sigma2_X0_null_ =\ self._est_AR1(self.X0_null_) return self def transform(self, X, y=None, scan_onsets=None): """ Use the model to estimate the time course of response to each condition (ts), and the time course unrelated to task (ts0) which is spread across the brain. This is equivalent to "decoding" the design matrix and nuisance regressors from a new dataset different from the training dataset on which fit() was applied. An AR(1) smooth prior is imposed on the decoded ts and ts0 with the AR(1) parameters learnt from the corresponding time courses in the training data. Notice: if you set the rank to be lower than the number of experimental conditions (number of columns in the design matrix), the recovered task-related activity will have collinearity (the recovered time courses of some conditions can be linearly explained by the recovered time courses of other conditions). Parameters ---------- X : numpy arrays, shape=[time_points, voxels] fMRI data of new data of the same subject. The voxels should match those used in the fit() function. If data are z-scored (recommended) when fitting the model, data should be z-scored as well when calling transform() y : not used (as it is unsupervised learning) scan_onsets : numpy array, shape=[number of runs]. A list of indices corresponding to the onsets of scans in the data X. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ts : numpy arrays, shape = [time_points, condition] The estimated response to the task conditions which have the response amplitudes estimated during the fit step. ts0: numpy array, shape = [time_points, n_nureg] The estimated time course spread across the brain, with the loading weights estimated during the fit step. """ assert X.ndim == 2 and X.shape[1] == self.beta_.shape[1], \ 'The shape of X is not consistent with the shape of data '\ 'used in the fitting step. They should have the same number '\ 'of voxels' assert scan_onsets is None or (scan_onsets.ndim == 1 and 0 in scan_onsets), \ 'scan_onsets should either be None or an array of indices '\ 'If it is given, it should include at least 0' if scan_onsets is None: scan_onsets = np.array([0], dtype=int) else: scan_onsets = np.int32(scan_onsets) ts, ts0, log_p = self._transform( Y=X, scan_onsets=scan_onsets, beta=self.beta_, beta0=self.beta0_, rho_e=self.rho_, sigma_e=self.sigma_, rho_X=self._rho_design_, sigma2_X=self._sigma2_design_, rho_X0=self._rho_X0_, sigma2_X0=self._sigma2_X0_) return ts, ts0 def score(self, X, design, scan_onsets=None): """ Use the model and parameters estimated by fit function from some data of a participant to evaluate the log likelihood of some new data of the same participant. Design matrix of the same set of experimental conditions in the testing data should be provided, with each column corresponding to the same condition as that column in the design matrix of the training data. Unknown nuisance time series will be marginalized, assuming they follow the same spatial pattern as in the training data. The hypothetical response captured by the design matrix will be subtracted from data before the marginalization when evaluating the log likelihood. For null model, nothing will be subtracted before marginalization. There is a difference between the form of likelihood function used in fit() and score(). In fit(), the response amplitude beta to design matrix X and the modulation beta0 by nuisance regressor X0 are both marginalized, with X provided and X0 estimated from data. In score(), posterior estimation of beta and beta0 from the fitting step are assumed unchanged to testing data and X0 is marginalized. The logic underlying score() is to transfer as much as what we can learn from training data when calculating a likelihood score for testing data. If you z-scored your data during fit step, you should z-score them for score function as well. If you did not z-score in fitting, you should not z-score here either. Parameters ---------- X : numpy arrays, shape=[time_points, voxels] fMRI data of new data of the same subject. The voxels should match those used in the fit() function. If data are z-scored (recommended) when fitting the model, data should be z-scored as well when calling transform() design : numpy array, shape=[time_points, conditions] Design matrix expressing the hypothetical response of the task conditions in data X. scan_onsets : numpy array, shape=[number of runs]. A list of indices corresponding to the onsets of scans in the data X. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ll: float. The log likelihood of the new data based on the model and its parameters fit to the training data. ll_null: float. The log likelihood of the new data based on a null model which assumes the same as the full model for everything except for that there is no response to any of the task conditions. """ assert X.ndim == 2 and X.shape[1] == self.beta_.shape[1], \ 'The shape of X is not consistent with the shape of data '\ 'used in the fitting step. They should have the same number '\ 'of voxels' assert scan_onsets is None or (scan_onsets.ndim == 1 and 0 in scan_onsets), \ 'scan_onsets should either be None or an array of indices '\ 'If it is given, it should include at least 0' if scan_onsets is None: scan_onsets = np.array([0], dtype=int) else: scan_onsets = np.int32(scan_onsets) ll = self._score(Y=X, design=design, beta=self.beta_, scan_onsets=scan_onsets, beta0=self.beta0_, rho_e=self.rho_, sigma_e=self.sigma_, rho_X0=self._rho_X0_, sigma2_X0=self._sigma2_X0_) ll_null = self._score(Y=X, design=None, beta=None, scan_onsets=scan_onsets, beta0=self.beta0_, rho_e=self.rho_, sigma_e=self.sigma_, rho_X0=self._rho_X0_, sigma2_X0=self._sigma2_X0_) return ll, ll_null # The following 2 functions _D_gen and _F_gen generate templates used # for constructing inverse of covariance matrix of AR(1) noise # The inverse of covarian matrix is # (I - rho1 * D + rho1*2 F) / sigma*2. D is a matrix where all the # elements adjacent to the diagonal are 1 and all others are 0. F is # a matrix which is 1 on all diagonal elements except for in the first # and last columns. We denote (I - rho1 D + rho1*2 F) with A. # In the function calculating likelihood function, # XTAX, YTAY_diag, YTAX all mean multiplying the inverse covariance matrix # in between either the design matrix or the data. # As one can see, even though rho1 and sigma2 might update as we keep # fitting parameters, several terms stay unchanged and do not need to # be re-calculated. # For example, in X'AX = X'(I + rho1D + rho12F)X / sigma2, # the products X'X, X'DX, X'FX, etc. can always be re-used if they # are pre-calculated. Therefore, _D_gen and _F_gen constructs matrices # D and F, and _prepare_data_* calculates these products that can be # re-used. In principle, once parameters have been fitted for a # dataset, they can be updated for new incoming data by adding the # products X'X, X'DX, X'FX, X'Y etc. from new data to those from # existing data, and refit the parameters starting from the ones # fitted from existing data. def _D_gen(self, TR): if TR > 0: return np.diag(np.ones(TR - 1), -1) \ + np.diag(np.ones(TR - 1), 1) else: return np.empty([0, 0]) def _F_gen(self, TR): if TR > 0: F = np.eye(TR) F[0, 0] = 0 F[TR - 1, TR - 1] = 0 return F else: return np.empty([0, 0]) def _run_TR_from_scan_onsets(self, n_T, scan_onsets=None): if scan_onsets is None: # assume that all data are acquired within the same scan. n_run = 1 run_TRs = np.array([n_T], dtype=int) else: # Each value in the scan_onsets tells the index at which # a new scan starts. For example, if n_T = 500, and # scan_onsets = [0,100,200,400], this means that the time points # of 0-99 are from the first scan, 100-199 are from the second, # 200-399 are from the third and 400-499 are from the fourth run_TRs = np.int32(np.diff(np.append(scan_onsets, n_T))) run_TRs = np.delete(run_TRs, np.where(run_TRs == 0)) n_run = run_TRs.size # delete run length of 0 in case of duplication in scan_onsets. logger.info('I infer that the number of volumes' ' in each scan are: {}'.format(run_TRs)) return run_TRs, n_run def _prepare_DF(self, n_T, scan_onsets=None): """ Prepare the essential template matrices D and F for pre-calculating some terms to be re-used. The inverse covariance matrix of AR(1) noise is sigma^-2 * (I - rho1D + rho12 F). And we denote A = I - rho1D + rho12 F""" run_TRs, n_run = self._run_TR_from_scan_onsets(n_T, scan_onsets) D_ele = map(self._D_gen, run_TRs) F_ele = map(self._F_gen, run_TRs) D = scipy.linalg.block_diag(D_ele) F = scipy.linalg.block_diag(F_ele) # D and F above are templates for constructing # the inverse of temporal covariance matrix of noise return D, F, run_TRs, n_run def _prepare_data_XY(self, X, Y, D, F): """Prepares different forms of products of design matrix X and data Y, or between themselves. These products are re-used a lot during fitting. So we pre-calculate them. Because these are reused, it is in principle possible to update the fitting as new data come in, by just incrementally adding the products of new data and their corresponding parts of design matrix to these pre-calculated terms. """ XTY, XTDY, XTFY = self._make_templates(D, F, X, Y) YTY_diag = np.sum(Y * Y, axis=0) YTDY_diag = np.sum(Y * np.dot(D, Y), axis=0) YTFY_diag = np.sum(Y * np.dot(F, Y), axis=0) XTX, XTDX, XTFX = self._make_templates(D, F, X, X) return XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, \ XTDX, XTFX def _gen_X_DC(self, run_TRs): if self.baseline_single: X_DC = np.ones((np.sum(run_TRs), 1)) else: X_DC = scipy.linalg.block_diag(map(np.ones, run_TRs)).T return X_DC def _gen_legendre(self, run_TRs, orders): def reg(x): return np.concatenate( [scipy.special.legendre(o)(np.linspace(-1, 1, x))[None, :] for o in orders], axis=0) reg_poly = scipy.linalg.block_diag( map(reg, run_TRs)).T return reg_poly def _prepare_data_XYX0(self, X, Y, X_base, X_res, D, F, run_TRs, no_DC=False): """Prepares different forms of products between design matrix X or data Y or nuisance regressors X0. These products are re-used a lot during fitting. So we pre-calculate them. no_DC means not inserting regressors for DC components into nuisance regressor. It will only take effect if X_base is not None. """ X_DC = self._gen_X_DC(run_TRs) reg_sol = np.linalg.lstsq(X_DC, X, rcond=None) if np.any(np.isclose(reg_sol[1], 0)): raise ValueError('Your design matrix appears to have ' 'included baseline time series.' 'Either remove them, or move them to' ' nuisance regressors.') X_DC, X_base, idx_DC = self._merge_DC_to_base(X_DC, X_base, no_DC) if X_res is None: X0 = X_base else: X0 = np.concatenate((X_base, X_res), axis=1) n_X0 = X0.shape[1] X0TX0, X0TDX0, X0TFX0 = self._make_templates(D, F, X0, X0) XTX0, XTDX0, XTFX0 = self._make_templates(D, F, X, X0) X0TY, X0TDY, X0TFY = self._make_templates(D, F, X0, Y) return X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, idx_DC def _merge_DC_to_base(self, X_DC, X_base, no_DC): """ Merge DC components X_DC to the baseline time series X_base (By baseline, this means any fixed nuisance regressors not updated during fitting, including DC components and any nuisance regressors provided by the user. X_DC is always in the first few columns of X_base. """ if X_base is not None: reg_sol = np.linalg.lstsq(X_DC, X_base, rcond=None) if not no_DC: if not np.any(np.isclose(reg_sol[1], 0)): # No columns in X_base can be explained by the # baseline regressors. So we insert them. X_base = np.concatenate((X_DC, X_base), axis=1) idx_DC = np.arange(0, X_DC.shape[1]) else: logger.warning('Provided regressors for uninteresting ' 'time series already include baseline. ' 'No additional baseline is inserted.') idx_DC = np.where(np.isclose(reg_sol[1], 0))[0] else: idx_DC = np.where(np.isclose(reg_sol[1], 0))[0] else: # If a set of regressors for non-interested signals is not # provided, then we simply include one baseline for each run. X_base = X_DC idx_DC = np.arange(0, X_base.shape[1]) logger.info('You did not provide time series of no interest ' 'such as DC component. Trivial regressors of' ' DC component are included for further modeling.' ' The final covariance matrix won''t ' 'reflect these components.') return X_DC, X_base, idx_DC def _make_ar1_quad_form(self, XTX, XTDX, XTFX, rho1): # Calculate the matrix X'AX = X'X - rho1 * X'DX + rho1^2 * X'FX # Here, rho1 is the AR(1) coefficient. X is a matrix of time series # with each row corresponding to a vector at one # time point. The forms of matrices D and F are defined in _prepare_DF # function. sigma^-2 * A would be the inverse of covariance matrix # of AR(1) process (precision matrix) with rho1 as the AR coefficient # and sigma^2 as the variance of independent noise at each time point. return XTX - rho1 * XTDX + rho1*2 XTFX def _make_ar1_quad_form_grad(self, XTDX, XTFX, rho1): # Calculate the derivative of the quadratic form X'AX with respect to # AR1 coefficient rho1, given precalculated terms X'DX and X'FX, # and rho1. return - XTDX + 2 * rho1 * XTFX def _make_templates(self, D, F, X, Y): XTY = np.dot(X.T, Y) XTDY = np.dot(np.dot(X.T, D), Y) XTFY = np.dot(np.dot(X.T, F), Y) return XTY, XTDY, XTFY def _precompute_ar1_quad_forms(self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0): # Calculate the sandwich terms which put A between X, Y and X0 # These terms are used a lot in the likelihood. But in the _fitV # step, they only need to be calculated once, since A is fixed. # In _fitU step, they need to be calculated at each iteration, # because rho1 changes. XTAY = self._make_ar1_quad_form(XTY, XTDY, XTFY, rho1) # dimension: featurespace YTAY = self._make_ar1_quad_form(YTY_diag, YTDY_diag, YTFY_diag, rho1) # dimension: space, # A/sigma2 is the inverse of noise covariance matrix in each voxel. # YTAY means Y'AY XTAX = XTX[None, :, :] - rho1[:, None, None] \ XTDX[None, :, :] \ + rho1[:, None, None]*2 XTFX[None, :, :] # dimension: spacefeaturefeature X0TAX0 = X0TX0[None, :, :] - rho1[:, None, None] \ * X0TDX0[None, :, :] \ + rho1[:, None, None]*2 X0TFX0[None, :, :] # dimension: space#baseline#baseline XTAX0 = XTX0[None, :, :] - rho1[:, None, None] \ * XTDX0[None, :, :] \ + rho1[:, None, None]*2 XTFX0[None, :, :] # dimension: spacefeature#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, rho1) # dimension: #baselinespace X0TAX0_i = np.linalg.solve(X0TAX0, np.identity(n_X0)[None, :, :]) # dimension: space#baseline#baseline XTAcorrX = XTAX # dimension: spacefeaturefeature XTAcorrY = XTAY # dimension: featurespace for i_v in range(n_V): XTAcorrX[i_v, :, :] -= \ np.dot(np.dot(XTAX0[i_v, :, :], X0TAX0_i[i_v, :, :]), XTAX0[i_v, :, :].T) XTAcorrY[:, i_v] -= np.dot(np.dot(XTAX0[i_v, :, :], X0TAX0_i[i_v, :, :]), X0TAY[:, i_v]) XTAcorrXL = np.dot(XTAcorrX, L) # dimension: spacefeaturerank LTXTAcorrXL = np.tensordot(XTAcorrXL, L, axes=(1, 0)) # dimension: rankfeaturerank LTXTAcorrY = np.dot(L.T, XTAcorrY) # dimension: rankspace YTAcorrY = YTAY - np.sum(X0TAY np.einsum('ijk,ki->ji', X0TAX0_i, X0TAY), axis=0) # dimension: space return X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL def _calc_LL(self, rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, SNR2, n_V, n_T, n_run, rank, n_X0): # Calculate the log likelihood (excluding the GP prior of log(SNR)) # for both _loglike_AR1_diagV_fitU and _loglike_AR1_diagV_fitV, # in addition to a few other terms. LAMBDA_i = LTXTAcorrXL * SNR2[:, None, None] + np.eye(rank) # dimension: spacerankrank LAMBDA = np.linalg.solve(LAMBDA_i, np.identity(rank)[None, :, :]) # dimension: spacerankrank # LAMBDA is essentially the inverse covariance matrix of the # posterior probability of alpha, which bears the relation with # beta by beta = L * alpha. L is the Cholesky factor of the # shared covariance matrix U. Refer to the explanation below # Equation 5 in the NIPS paper. YTAcorrXL_LAMBDA = np.einsum('ji,ijk->ik', LTXTAcorrY, LAMBDA) # dimension: spacerank sigma2 = (YTAcorrY - np.sum(LTXTAcorrY YTAcorrXL_LAMBDA.T, axis=0) * SNR2) / (n_T - n_X0) # dimension: space LL = - np.sum(np.log(sigma2)) * (n_T - n_X0) * 0.5 \ + np.sum(np.log(1 - rho1*2)) n_run * 0.5 \ - np.sum(self._half_log_det(X0TAX0)) \ - np.sum(self._half_log_det(LAMBDA_i)) \ - (n_T - n_X0) * n_V * (1 + np.log(2 * np.pi)) * 0.5 # Log likelihood return LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 def _calc_dist2_GP(self, coords=None, inten=None, GP_space=False, GP_inten=False): # calculate the square of difference between each voxel's location # coorinates and image intensity. if GP_space: assert coords is not None, 'coordinate is not provided' # square of spatial distance between every two voxels dist2 = spdist.squareform(spdist.pdist(coords, 'sqeuclidean')) # set the hyperparameter for the GP process: if self.space_smooth_range is None: space_smooth_range = np.max(dist2)0.5 / 2.0 # By default, we assume the length scale should be # within half the size of ROI. else: space_smooth_range = self.space_smooth_range if GP_inten: assert inten is not None, 'intensity is not provided' # squre of difference between intensities of # # every two voxels inten_diff2 = spdist.squareform( spdist.pdist(inten[:, None], 'sqeuclidean')) # set the hyperparameter for the GP process: if self.inten_smooth_range is None: inten_smooth_range = np.max(inten_diff2)0.5 / 2.0 # By default, we assume the length scale should be # within half the maximum difference of intensity. else: inten_smooth_range = self.inten_smooth_range n_smooth = 2 else: inten_diff2 = None inten_smooth_range = None n_smooth = 1 else: n_smooth = 0 dist2 = None inten_diff2 = None GP_inten = False space_smooth_range = None inten_smooth_range = None return dist2, inten_diff2, space_smooth_range, inten_smooth_range,\ n_smooth def _build_index_param(self, n_l, n_V, n_smooth): """ Build dictionaries to retrieve each parameter from the combined parameters. """ idx_param_sing = {'Cholesky': np.arange(n_l), 'a1': n_l} # for simplified fitting idx_param_fitU = {'Cholesky': np.arange(n_l), 'a1': np.arange(n_l, n_l + n_V)} # for the likelihood function when we fit U (the shared covariance). idx_param_fitV = {'log_SNR2': np.arange(n_V - 1), 'c_space': n_V - 1, 'c_inten': n_V, 'c_both': np.arange(n_V - 1, n_V - 1 + n_smooth)} # for the likelihood function when we fit V (reflected by SNR of # each voxel) return idx_param_sing, idx_param_fitU, idx_param_fitV def _half_log_det(self, M): """ Return log(\|M\|)0.5. For positive definite matrix M of more than 2 dimensions, calculate this for the last two dimension and return a value corresponding to each element in the first few dimensions. """ chol = np.linalg.cholesky(M) if M.ndim == 2: return np.sum(np.log(np.abs(np.diag(chol)))) else: return np.sum(np.log(np.abs(np.diagonal( chol, axis1=-2, axis2=-1))), axis=-1) def _chol_idx(self, n_C, rank): l_idx = np.tril_indices(n_C) if rank is not None: # The rank of covariance matrix is specified idx_rank = np.where(l_idx[1] < rank) l_idx = (l_idx[0][idx_rank], l_idx[1][idx_rank]) logger.info('Using the rank specified by the user: ' '{}'.format(rank)) else: rank = n_C # if not specified, we assume you want to # estimate a full rank matrix logger.warning('Please be aware that you did not specify the' ' rank of covariance matrix to estimate.' 'I will assume that the covariance matrix ' 'shared among voxels is of full rank.' 'Rank = {}'.format(rank)) logger.warning('Please be aware that estimating a matrix of ' 'high rank can be very slow.' 'If you have a good reason to specify a rank ' 'lower than the number of experiment conditions,' ' do so.') return l_idx, rank def _fit_RSA_UV(self, X, Y, X_base, scan_onsets=None, coords=None, inten=None): """ The major utility of fitting Bayesian RSA. Note that there is a naming change of variable. X in fit() is changed to Y here, and design in fit() is changed to X here. This is because we follow the tradition that X expresses the variable defined (controlled) by the experimenter, i.e., the time course of experimental conditions convolved by an HRF, and Y expresses data. However, in wrapper function fit(), we follow the naming routine of scikit-learn. """ GP_inten = self.GP_inten GP_space = self.GP_space rank = self.rank n_V = np.size(Y, axis=1) n_T = np.size(Y, axis=0) n_C = np.size(X, axis=1) l_idx, rank = self._chol_idx(n_C, rank) n_l = np.size(l_idx[0]) # the number of parameters for L t_start = time.time() D, F, run_TRs, n_run = self._prepare_DF( n_T, scan_onsets=scan_onsets) XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, \ XTDX, XTFX = self._prepare_data_XY(X, Y, D, F) X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, idx_DC = \ self._prepare_data_XYX0( X, Y, X_base, None, D, F, run_TRs, no_DC=False) # Prepare the data for fitting. These pre-calculated matrices # will be re-used a lot in evaluating likelihood function and # gradient. # DC component will be added to the nuisance regressors. # In later steps, we do not need to add DC components again dist2, inten_diff2, space_smooth_range, inten_smooth_range,\ n_smooth = self._calc_dist2_GP( coords=coords, inten=inten, GP_space=GP_space, GP_inten=GP_inten) # Calculating the distance between voxel locations and betweeen # voxel intensities. These are used if a Gaussian Process prior # is requested to regularize log(SNR^2) idx_param_sing, idx_param_fitU, idx_param_fitV = \ self._build_index_param(n_l, n_V, n_smooth) # Indexes to find each parameter in a combined parameter vector. current_GP = np.zeros(n_smooth) # We will perform the fitting in 2~3 steps: # (1) A preliminary fitting assuming all voxels share # exactly the same temporal covariance matrix for their noise. # SNR is assumed to be 1 for all voxels in this fitting. # Therefore, there are only n_l+2 free parameters. # (2) (optional) A fitting which allows each voxel to have their # own pseudo-SNR and AR(1) coefficients. But no Gaussian Process # prior is imposed on log(SNR). This step is neglected if GP # prior is not requested. This step allows the SNR parameters to # move closer to their correct values before GP is introduced. # This step alternately fits the shared covariance and voxel- # specific variance. It fits for init_iter steps and the # tolerance is also increased by a factor of 5 to speed up # fitting. # (3) Final fitting. If GP prior is requested, it will be # introduced in this step. Otherwise, just fit as the previous # step, but using un-altered tolerance setting, and n_iter # as the number of iteration. # Step 1 fitting, with a simplified model current_vec_U_chlsk_l, current_a1, current_logSigma2 = \ self._initial_fit_singpara( XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, X, Y, X0, idx_param_sing, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank) current_logSNR2 = -current_logSigma2 norm_factor = np.mean(current_logSNR2) current_logSNR2 = current_logSNR2 - norm_factor X_res = None # Step 2 fitting, which only happens if # GP prior is requested if GP_space: current_vec_U_chlsk_l, current_a1, current_logSNR2, X_res\ = self._fit_diagV_noGP( XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank) current_GP[0] = np.log(np.min( dist2[np.tril_indices_from(dist2, k=-1)])) # We start fitting the model with GP prior with a small # length scale: the size of voxels. # Alternatively, initialize with a large distance. # Further testing of initial parameters need to be done. # current_GP[0] = np.log(np.max(dist2)/4.0) logger.debug('current GP[0]:{}'.format(current_GP[0])) if GP_inten: current_GP[1] = np.log(np.maximum( np.percentile(inten_diff2[np.tril_indices_from( inten_diff2, k=-1)], 2), 0.5)) logger.debug( 'current GP[1]:{}'.format(current_GP[1])) # We start the length scale for intensity with # a small value. A heuristic is 2 percentile of # all the square differences. But it should not be # smaller than 0.5. This limit is set in case # many voxels have close to equal intensities, # which might render 2 percentile to 0. # Step 3 fitting. GP prior is imposed if requested. # In this step, unless auto_nuisance is set to False, X_res # will be re-estimated from the residuals after each step # of fitting. And X0 will be concatenation of X_base and X_res logger.debug('indexing:{}'.format(idx_param_fitV)) logger.debug('initial GP parameters:{}'.format(current_GP)) current_vec_U_chlsk_l, current_a1, current_logSNR2,\ current_GP, X_res = self._fit_diagV_GP( XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, current_GP, n_smooth, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank, GP_space, GP_inten, dist2, inten_diff2, space_smooth_range, inten_smooth_range) estU_chlsk_l_AR1_UV = np.zeros([n_C, rank]) estU_chlsk_l_AR1_UV[l_idx] = current_vec_U_chlsk_l est_cov_AR1_UV = np.dot(estU_chlsk_l_AR1_UV, estU_chlsk_l_AR1_UV.T) est_rho1_AR1_UV = 2 / np.pi np.arctan(current_a1) est_SNR_AR1_UV = np.exp(current_logSNR2 / 2.0) # Calculating est_sigma_AR1_UV, est_sigma_AR1_UV, # est_beta_AR1_UV and est_beta0_AR1_UV X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, _ \ = self._prepare_data_XYX0( X, Y, X_base, X_res, D, F, run_TRs, no_DC=True) X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL\ = self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, estU_chlsk_l_AR1_UV, est_rho1_AR1_UV, n_V, n_X0) LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 \ = self._calc_LL(est_rho1_AR1_UV, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, est_SNR_AR1_UV2, n_V, n_T, n_run, rank, n_X0) est_sigma_AR1_UV = sigma20.5 est_beta_AR1_UV = est_SNR_AR1_UV*2 \ np.dot(estU_chlsk_l_AR1_UV, YTAcorrXL_LAMBDA.T) est_beta_AR1_UV_latent = \ est_SNR_AR1_UV*2 YTAcorrXL_LAMBDA.T # the latent term means that XL multiplied by this term # is the same as Xbeta. This will be used for decoding # and cross-validating, in case L is low-rank est_beta0_AR1_UV = np.einsum( 'ijk,ki->ji', X0TAX0_i, (X0TAY - np.einsum('ikj,ki->ji', XTAX0, est_beta_AR1_UV))) # Now we want to collapse all beta0 corresponding to DC components # of different runs to a single map, and preserve only one DC component # across runs. This is because they should express the same component # and the new data to transform do not necessarily have the same # numbers of runs as the training data. if idx_DC.size > 1: collapsed_DC = np.sum(X0[:, idx_DC], axis=1) X0 = np.insert(np.delete(X0, idx_DC, axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(est_beta0_AR1_UV[idx_DC, :], axis=0) est_beta0_AR1_UV = np.insert( np.delete(est_beta0_AR1_UV, idx_DC, axis=0), 0, collapsed_beta0, axis=0) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) logger.debug('final GP parameters:{}'.format(current_GP)) if GP_space: est_space_smooth_r = np.exp(current_GP[0] / 2.0) if GP_inten: est_intensity_kernel_r = np.exp(current_GP[1] / 2.0) K_major = np.exp(- (dist2 / est_space_smooth_r2 + inten_diff2 / est_intensity_kernel_r2) / 2.0) else: est_intensity_kernel_r = None K_major = np.exp(- dist2 / est_space_smooth_r*2 / 2.0) K = K_major + np.diag(np.ones(n_V) self.eta) invK_tilde_log_SNR = np.linalg.solve(K, current_logSNR2) / 2 log_SNR_invK_tilde_log_SNR = np.dot(current_logSNR2, invK_tilde_log_SNR) / 2 tau2, _ = self.tau2_prior(log_SNR_invK_tilde_log_SNR, n_V, self.tau_range) est_std_log_SNR = tau2 0.5 else: est_space_smooth_r = None est_intensity_kernel_r = None est_std_log_SNR = None return est_cov_AR1_UV, estU_chlsk_l_AR1_UV, est_SNR_AR1_UV, \ est_beta_AR1_UV, est_beta0_AR1_UV, est_beta_AR1_UV_latent,\ est_sigma_AR1_UV, est_rho1_AR1_UV, est_space_smooth_r, \ est_std_log_SNR, est_intensity_kernel_r, X0 def _transform(self, Y, scan_onsets, beta, beta0, rho_e, sigma_e, rho_X, sigma2_X, rho_X0, sigma2_X0): """ Given the data Y and the response amplitudes beta and beta0 estimated in the fit step, estimate the corresponding X and X0. It is done by a forward-backward algorithm. We assume X and X0 both are vector autoregressive (VAR) processes, to capture temporal smoothness. Their VAR parameters are estimated from training data at the fit stage. """ logger.info('Transforming new data.') # Constructing the transition matrix and the variance of # innovation noise as prior for the latent variable X and X0 # in new data. n_C = beta.shape[0] n_T = Y.shape[0] weight = np.concatenate((beta, beta0), axis=0) T_X = np.diag(np.concatenate((rho_X, rho_X0))) Var_X = np.concatenate((sigma2_X / (1 - rho_X2), sigma2_X0 / (1 - rho_X02))) Var_dX = np.concatenate((sigma2_X, sigma2_X0)) sigma2_e = sigma_e 2 scan_onsets = np.setdiff1d(scan_onsets, n_T) n_scan = scan_onsets.size X = [None] * scan_onsets.size X0 = [None] * scan_onsets.size total_log_p = 0 for scan, onset in enumerate(scan_onsets): # Forward step if scan == n_scan - 1: offset = n_T else: offset = scan_onsets[scan + 1] mu, mu_Gamma_inv, Gamma_inv, log_p_data, Lambda_0, \ Lambda_1, H, deltaY, deltaY_sigma2inv_rho_weightT = \ self._forward_step(Y[onset:offset, :], T_X, Var_X, Var_dX, rho_e, sigma2_e, weight) total_log_p += log_p_data # Backward step mu_hat, mu_Gamma_inv_hat, Gamma_inv_hat \ = self._backward_step( deltaY, deltaY_sigma2inv_rho_weightT, sigma2_e, weight, mu, mu_Gamma_inv, Gamma_inv, Lambda_0, Lambda_1, H) X[scan] = np.concatenate( [mu_t[None, :n_C] for mu_t in mu_hat]) X0[scan] = np.concatenate( [mu_t[None, n_C:] for mu_t in mu_hat]) X = np.concatenate(X) X0 = np.concatenate(X0) return X, X0, total_log_p def _score(self, Y, design, beta, scan_onsets, beta0, rho_e, sigma_e, rho_X0, sigma2_X0): """ Given the data Y, and the spatial pattern beta0 of nuisance time series, return the cross-validated score of the data Y given all parameters of the subject estimated during the first step. It is assumed that the user has design matrix built for the data Y. Both beta and beta0 are posterior expectation estimated from training data with the estimated covariance matrix U and SNR serving as prior. We marginalize X0 instead of fitting it in this function because this function is for the purpose of evaluating model no new data. We should avoid doing any additional fitting when performing cross-validation. The hypothetic response to the task will be subtracted, and the unknown nuisance activity which contributes to the data through beta0 will be marginalized. """ logger.info('Estimating cross-validated score for new data.') n_T = Y.shape[0] if design is not None: Y = Y - np.dot(design, beta) # The function works for both full model and null model. # If design matrix is not provided, the whole data is # used as input for _forward_step. If design matrix is provided, # residual after subtracting design * beta is fed to _forward_step T_X = np.diag(rho_X0) Var_X = sigma2_X0 / (1 - rho_X02) Var_dX = sigma2_X0 # Prior parmeters for X0: T_X is transitioning matrix, Var_X # is the marginal variance of the first time point. Var_dX is the # variance of the updating noise. sigma2_e = sigma_e 2 # variance of voxel-specific updating noise component scan_onsets = np.setdiff1d(scan_onsets, n_T).astype(int) n_scan = scan_onsets.size total_log_p = 0 for scan, onset in enumerate(scan_onsets): # Forward step if scan == n_scan - 1: offset = n_T else: offset = scan_onsets[scan + 1] _, _, _, log_p_data, _, _, _, _, _ = \ self._forward_step( Y[onset:offset, :], T_X, Var_X, Var_dX, rho_e, sigma2_e, beta0) total_log_p += log_p_data return total_log_p def _est_AR1(self, x, same_para=False): """ Estimate the AR(1) parameters of input x. Each column of x is assumed as independent from other columns, and each column is treated as an AR(1) process. If same_para is set as True, then all columns of x are concatenated and a single set of AR(1) parameters is estimated. Strictly speaking the breaking point between each concatenated column should be considered. But for long time series, this is ignored. """ if same_para: n_c = x.shape[1] x = np.reshape(x, x.size, order='F') rho, sigma2 = alg.AR_est_YW(x, 1) # We concatenate all the design matrix to estimate common AR(1) # parameters. This creates some bias because the end of one column # and the beginning of the next column of the design matrix are # treated as consecutive samples. rho = np.ones(n_c) * rho sigma2 = np.ones(n_c) * sigma2 else: rho = np.zeros(np.shape(x)[1]) sigma2 = np.zeros(np.shape(x)[1]) for c in np.arange(np.shape(x)[1]): rho[c], sigma2[c] = alg.AR_est_YW(x[:, c], 1) return rho, sigma2 def _forward_step(self, Y, T_X, Var_X, Var_dX, rho_e, sigma2_e, weight): """ forward step for HMM, assuming both the hidden state and noise have 1-step dependence on the previous value. """ # We currently only implement diagonal form # of covariance matrix for Var_X, Var_dX and T_X, which means # each dimension of X is independent and their innovation noise # are also independent. Note that log_p_data takes this assumption. if Var_X.ndim == 1: inv_Var_X = np.diag(1 / Var_X) half_log_det_Var_X = np.sum(np.log(Var_X)) / 2.0 Var_X = np.diag(Var_X) # the marginal variance of X else: half_log_det_Var_X = self._half_log_det(Var_X) inv_Var_X = np.linalg.inv(Var_X) if Var_dX.ndim == 1: inv_Var_dX = np.diag(1 / Var_dX) half_log_det_Var_dX = np.sum(np.log(Var_dX)) / 2.0 Var_dX = np.diag(Var_dX) # the marginal variance of Delta X (the change of X from # previous time point) else: inv_Var_dX = np.linalg.inv(Var_dX) half_log_det_Var_dX = self._half_log_det(Var_dX) if T_X.ndim == 1: T_X = np.diag(T_X) # Transfer function of X: the expected mean of X at t+1 # time point is T_x * X [n_T, n_V] = np.shape(Y) # numbers of time points and voxels mu = [None] * n_T # posterior mean of X, conditioned on all data up till the current # time point Gamma_inv = [None] * n_T # inverse of poterior Gamma. mu_Gamma_inv = [None] * n_T # mu * inv(Gamma) log_p_data = - np.log(np.pi * 2) * (n_T * n_V) / 2 \ - half_log_det_Var_X - np.sum(np.log(sigma2_e)) * n_T / 2.0\ + np.sum(np.log(1 - rho_e*2)) / 2.0 - half_log_det_Var_dX \ (n_T - 1) # This is the term to be incremented by c_n at each time step. # We first add all the fixed terms to it. # The following are a few fixed terms. Lambda_0 = np.dot(T_X, np.dot(inv_Var_dX, T_X.T)) \ + np.dot(weight * rho_e*2 / sigma2_e, weight.T) H = np.dot(inv_Var_dX, T_X.T) + np.dot(weight rho_e / sigma2_e, weight.T) Lambda_1 = inv_Var_dX + np.dot(weight / sigma2_e, weight.T) Gamma_inv[0] = inv_Var_X + np.dot( weight * (1 - rho_e*2) / sigma2_e, weight.T) # We might not need this and only use linalg.solve for related terms. mu_Gamma_inv[0] = np.dot( Y[0, :] (1 - rho_e*2) / sigma2_e, weight.T) mu[0] = np.linalg.solve(Gamma_inv[0], mu_Gamma_inv[0]) log_p_data -= 0.5 np.sum(Y[0, :]*2 (1 - rho_e*2) / sigma2_e) # This is the term added for the first time point. deltaY = Y[1:, :] - rho_e Y[:-1, :] deltaY_sigma2inv_rho_weightT = np.dot( deltaY / sigma2_e * rho_e, weight.T) for t in np.arange(1, n_T): Gamma_tilde_inv = Lambda_0 + Gamma_inv[t - 1] tmp = np.linalg.solve(Gamma_tilde_inv, H.T) Gamma_inv[t] = Lambda_1 - np.dot(H, tmp) mu_Gamma_inv[t] = np.dot(deltaY[t - 1, :] / sigma2_e, weight.T) \ + np.dot(mu_Gamma_inv[t - 1] - deltaY_sigma2inv_rho_weightT[t - 1, :], tmp) mu[t] = np.linalg.solve(Gamma_inv[t], mu_Gamma_inv[t]) tmp2 = mu_Gamma_inv[t - 1] - deltaY_sigma2inv_rho_weightT[t - 1, :] log_p_data += -self._half_log_det(Gamma_tilde_inv) \ + np.dot(tmp2, np.linalg.solve(Gamma_tilde_inv, tmp2)) / 2.0 log_p_data += -self._half_log_det(Gamma_inv[-1]) \ + np.dot(mu_Gamma_inv[-1], mu[-1]) / 2.0 \ - np.sum(deltaY*2 / sigma2_e) / 2.0 return mu, mu_Gamma_inv, Gamma_inv, log_p_data, Lambda_0, \ Lambda_1, H, deltaY, deltaY_sigma2inv_rho_weightT def _backward_step(self, deltaY, deltaY_sigma2inv_rho_weightT, sigma2_e, weight, mu, mu_Gamma_inv, Gamma_inv, Lambda_0, Lambda_1, H): """ backward step for HMM, assuming both the hidden state and noise have 1-step dependence on the previous value. """ n_T = len(Gamma_inv) # All the terms with hat before are parameters of posterior # distributions of X conditioned on data from all time points, # whereas the ones without hat calculated by _forward_step # are mean and covariance of posterior of X conditioned on # data up to the time point. Gamma_inv_hat = [None] n_T mu_Gamma_inv_hat = [None] * n_T mu_hat = [None] * n_T mu_hat[-1] = mu[-1].copy() mu_Gamma_inv_hat[-1] = mu_Gamma_inv[-1].copy() Gamma_inv_hat[-1] = Gamma_inv[-1].copy() for t in np.arange(n_T - 2, -1, -1): tmp = np.linalg.solve(Gamma_inv_hat[t + 1] - Gamma_inv[t + 1] + Lambda_1, H) Gamma_inv_hat[t] = Gamma_inv[t] + Lambda_0 - np.dot(H.T, tmp) mu_Gamma_inv_hat[t] = mu_Gamma_inv[t] \ - deltaY_sigma2inv_rho_weightT[t, :] + np.dot( mu_Gamma_inv_hat[t + 1] - mu_Gamma_inv[t + 1] + np.dot(deltaY[t, :] / sigma2_e, weight.T), tmp) mu_hat[t] = np.linalg.solve(Gamma_inv_hat[t], mu_Gamma_inv_hat[t]) return mu_hat, mu_Gamma_inv_hat, Gamma_inv_hat def _initial_fit_singpara(self, XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, X, Y, X0, idx_param_sing, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank): """ Perform initial fitting of a simplified model, which assumes that all voxels share exactly the same temporal covariance matrix for their noise (the same noise variance and auto-correlation). The SNR is implicitly assumed to be 1 for all voxels. """ logger.info('Initial fitting assuming single parameter of ' 'noise for all voxels') X_joint = np.concatenate((X0, X), axis=1) beta_hat = np.linalg.lstsq(X_joint, Y, rcond=None)[0] residual = Y - np.dot(X_joint, beta_hat) # point estimates of betas and fitting residuals without assuming # the Bayesian model underlying RSA. # There are several possible ways of initializing the covariance. # (1) start from the point estimation of covariance cov_point_est = np.cov(beta_hat[n_X0:, :]) / np.var(residual) current_vec_U_chlsk_l = \ np.linalg.cholesky((cov_point_est + np.eye(n_C)) / 2)[l_idx] # We use the average of covariance of point estimation and an identity # matrix as the initial value of the covariance matrix, just in case # the user provides data in which n_V is smaller than n_C. # (2) start from identity matrix # current_vec_U_chlsk_l = np.eye(n_C)[l_idx] # (3) random initialization # current_vec_U_chlsk_l = self.random_state_.randn(n_l) # vectorized version of L, Cholesky factor of U, the shared # covariance matrix of betas across voxels. rho1 = np.sum( residual[0:-1, :] * residual[1:, :], axis=0) / \ np.sum(residual[0:-1, :] * residual[0:-1, :], axis=0) # Estimate of auto correlation assuming data includes pure noise. log_sigma2 = np.log(np.var( residual[1:, :] - residual[0:-1, :] * rho1, axis=0)) # log of estimates of the variance of the "innovation" noise # of AR(1) process at each time point. param0 = np.empty(np.sum(np.fromiter( (np.size(v) for v in idx_param_sing.values()), int))) # Initial parameter # Then we fill each part of the original guess of parameters param0[idx_param_sing['Cholesky']] = current_vec_U_chlsk_l param0[idx_param_sing['a1']] = np.median(np.tan(rho1 * np.pi / 2)) # Fit it. res = scipy.optimize.minimize( self._loglike_AR1_singpara, param0, args=(XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_sing, rank), method=self.optimizer, jac=True, tol=self.tol, options={'disp': self.minimize_options['disp'], 'maxiter': 100}) current_vec_U_chlsk_l = res.x[idx_param_sing['Cholesky']] current_a1 = res.x[idx_param_sing['a1']] * np.ones(n_V) # log(sigma^2) assuming the data include no signal is returned, # as a starting point for the iteration in the next step. # Although it should overestimate the variance, # setting it this way might allow it to track log(sigma^2) # more closely for each voxel. return current_vec_U_chlsk_l, current_a1, log_sigma2 def _fit_diagV_noGP( self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank): """ (optional) second step of fitting, full model but without GP prior on log(SNR). This step is only done if GP prior is requested. """ init_iter = self.init_iter logger.info('second fitting without GP prior' ' for {} times'.format(init_iter)) # Initial parameters param0_fitU = np.empty(np.sum(np.fromiter( (np.size(v) for v in idx_param_fitU.values()), int))) param0_fitV = np.empty(np.size(idx_param_fitV['log_SNR2'])) # We cannot use the same logic as the line above because # idx_param_fitV also includes entries for GP parameters. param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l.copy() param0_fitU[idx_param_fitU['a1']] = current_a1.copy() param0_fitV[idx_param_fitV['log_SNR2']] = \ current_logSNR2[:-1].copy() L = np.zeros((n_C, rank)) tol = self.tol * 5 for it in range(0, init_iter): X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, _ \ = self._prepare_data_XYX0( X, Y, X_base, X_res, D, F, run_TRs, no_DC=True) # fit U, the covariance matrix, together with AR(1) param param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l \ + self.random_state_.randn(n_l) \ * np.linalg.norm(current_vec_U_chlsk_l) \ / n_l*0.5 np.exp(-it / init_iter * self.anneal_speed - 1) param0_fitU[idx_param_fitU['a1']] = current_a1 res_fitU = scipy.optimize.minimize( self._loglike_AR1_diagV_fitU, param0_fitU, args=(XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, current_logSNR2, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitU, rank), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_vec_U_chlsk_l = \ res_fitU.x[idx_param_fitU['Cholesky']] current_a1 = res_fitU.x[idx_param_fitU['a1']] norm_fitUchange = np.linalg.norm(res_fitU.x - param0_fitU) logger.debug('norm of parameter change after fitting U: ' '{}'.format(norm_fitUchange)) param0_fitU = res_fitU.x.copy() # fit V, reflected in the log(SNR^2) of each voxel rho1 = np.arctan(current_a1) * 2 / np.pi L[l_idx] = current_vec_U_chlsk_l X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, \ LTXTAcorrY, XTAcorrXL, LTXTAcorrXL = \ self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0) res_fitV = scipy.optimize.minimize( self._loglike_AR1_diagV_fitV, param0_fitV, args=(X0TAX0, XTAX0, X0TAY, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL, current_vec_U_chlsk_l, current_a1, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitV, rank, False, False), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_logSNR2[0:n_V - 1] = res_fitV.x current_logSNR2[-1] = - np.sum(current_logSNR2[0:n_V - 1]) norm_fitVchange = np.linalg.norm(res_fitV.x - param0_fitV) logger.debug('norm of parameter change after fitting V: ' '{}'.format(norm_fitVchange)) logger.debug('E[log(SNR2)^2]: {}'.format( np.mean(current_logSNR2*2))) # The lines below are for debugging purpose. # If any voxel's log(SNR^2) gets to non-finite number, # something might be wrong -- could be that the data has # nothing to do with the design matrix. if np.any(np.logical_not(np.isfinite(current_logSNR2))): logger.warning('Initial fitting: iteration {}'.format(it)) logger.warning('current log(SNR^2): ' '{}'.format(current_logSNR2)) logger.warning('log(sigma^2) has non-finite number') param0_fitV = res_fitV.x.copy() # Re-estimating X_res from residuals current_SNR2 = np.exp(current_logSNR2) if self.auto_nuisance: LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, current_sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, current_SNR2, n_V, n_T, n_run, rank, n_X0) betas = current_SNR2 np.dot(L, YTAcorrXL_LAMBDA.T) beta0s = np.einsum( 'ijk,ki->ji', X0TAX0_i, (X0TAY - np.einsum('ikj,ki->ji', XTAX0, betas))) residuals = Y - np.dot(X, betas) - np.dot( X_base, beta0s[:np.shape(X_base)[1], :]) X_res = self.nureg_method( self.n_nureg_).fit_transform( self.preprocess_residual(residuals)) if norm_fitVchange / np.sqrt(param0_fitV.size) < tol \ and norm_fitUchange / np.sqrt(param0_fitU.size) \ < tol: break return current_vec_U_chlsk_l, current_a1, current_logSNR2, X_res def _fit_diagV_GP( self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, current_GP, n_smooth, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank, GP_space, GP_inten, dist2, inten_diff2, space_smooth_range, inten_smooth_range): """ Last step of fitting. If GP is not requested, this step will still be done, just without GP prior on log(SNR). """ tol = self.tol n_iter = self.n_iter logger.info('Last step of fitting.' ' for maximum {} times'.format(n_iter)) # Initial parameters param0_fitU = np.empty(np.sum(np.fromiter( (np.size(v) for v in idx_param_fitU.values()), int))) param0_fitV = np.empty(np.size(idx_param_fitV['log_SNR2']) + np.size(idx_param_fitV['c_both'])) # We cannot use the same logic as the line above because # idx_param_fitV also includes entries for GP parameters. param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l.copy() param0_fitU[idx_param_fitU['a1']] = current_a1.copy() param0_fitV[idx_param_fitV['log_SNR2']] = \ current_logSNR2[:-1].copy() L = np.zeros((n_C, rank)) L[l_idx] = current_vec_U_chlsk_l if self.GP_space: param0_fitV[idx_param_fitV['c_both']] = current_GP.copy() for it in range(0, n_iter): X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, _ = \ self._prepare_data_XYX0( X, Y, X_base, X_res, D, F, run_TRs, no_DC=True) # fit U param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l \ + self.random_state_.randn(n_l) \ * np.linalg.norm(current_vec_U_chlsk_l) \ / n_l*0.5 np.exp(-it / n_iter * self.anneal_speed - 1) param0_fitU[idx_param_fitU['a1']] = current_a1 res_fitU = scipy.optimize.minimize( self._loglike_AR1_diagV_fitU, param0_fitU, args=(XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, current_logSNR2, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitU, rank), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_vec_U_chlsk_l = \ res_fitU.x[idx_param_fitU['Cholesky']] current_a1 = res_fitU.x[idx_param_fitU['a1']] L[l_idx] = current_vec_U_chlsk_l fitUchange = res_fitU.x - param0_fitU norm_fitUchange = np.linalg.norm(fitUchange) logger.debug('norm of parameter change after fitting U: ' '{}'.format(norm_fitUchange)) param0_fitU = res_fitU.x.copy() # fit V rho1 = np.arctan(current_a1) * 2 / np.pi X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, \ LTXTAcorrY, XTAcorrXL, LTXTAcorrXL = \ self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0) res_fitV = scipy.optimize.minimize( self._loglike_AR1_diagV_fitV, param0_fitV, args=( X0TAX0, XTAX0, X0TAY, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL, current_vec_U_chlsk_l, current_a1, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitV, rank, GP_space, GP_inten, dist2, inten_diff2, space_smooth_range, inten_smooth_range), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_logSNR2[0:n_V - 1] = \ res_fitV.x[idx_param_fitV['log_SNR2']] current_logSNR2[n_V - 1] = -np.sum(current_logSNR2[0:n_V - 1]) current_GP = res_fitV.x[idx_param_fitV['c_both']] fitVchange = res_fitV.x - param0_fitV norm_fitVchange = np.linalg.norm(fitVchange) param0_fitV = res_fitV.x.copy() logger.debug('norm of parameter change after fitting V: ' '{}'.format(norm_fitVchange)) logger.debug('E[log(SNR2)^2]: {}'.format( np.mean(current_logSNR2*2))) # Re-estimating X_res from residuals current_SNR2 = np.exp(current_logSNR2) if self.auto_nuisance: LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, current_sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, current_SNR2, n_V, n_T, n_run, rank, n_X0) betas = current_SNR2 \ np.dot(L, YTAcorrXL_LAMBDA.T) beta0s = np.einsum( 'ijk,ki->ji', X0TAX0_i, (X0TAY - np.einsum('ikj,ki->ji', XTAX0, betas))) residuals = Y - np.dot(X, betas) - np.dot( X_base, beta0s[:np.shape(X_base)[1], :]) X_res = self.nureg_method(self.n_nureg_).fit_transform( self.preprocess_residual(residuals)) if GP_space: logger.debug('current GP[0]: {}'.format(current_GP[0])) logger.debug('gradient for GP[0]: {}'.format( res_fitV.jac[idx_param_fitV['c_space']])) if GP_inten: logger.debug('current GP[1]: {}'.format(current_GP[1])) logger.debug('gradient for GP[1]: {}'.format( res_fitV.jac[idx_param_fitV['c_inten']])) if np.max(np.abs(fitVchange)) < tol and \ np.max(np.abs(fitUchange)) < tol: break return current_vec_U_chlsk_l, current_a1, current_logSNR2,\ current_GP, X_res def _fit_null(self, Y, X_base, scan_onsets=None): """ Fit a null model. """ n_V = np.size(Y, axis=1) n_T = np.size(Y, axis=0) t_start = time.time() D, F, run_TRs, n_run = self._prepare_DF( n_T, scan_onsets=scan_onsets) YTY_diag = np.sum(Y * Y, axis=0) YTDY_diag = np.sum(Y * np.dot(D, Y), axis=0) YTFY_diag = np.sum(Y * np.dot(F, Y), axis=0) tol = self.tol n_iter = self.n_iter logger.info('Fitting null model' ' for maximum {} times'.format(n_iter)) # Add DC components capturing run-specific baselines. X_DC = self._gen_X_DC(run_TRs) X_DC, X_base, idx_DC = self._merge_DC_to_base( X_DC, X_base, no_DC=False) X_res = None param0 = np.zeros(n_V) for it in range(0, n_iter): if X_res is None: X0 = X_base else: X0 = np.concatenate((X_base, X_res), axis=1) n_X0 = X0.shape[1] X0TX0, X0TDX0, X0TFX0 = self._make_templates(D, F, X0, X0) X0TY, X0TDY, X0TFY = self._make_templates(D, F, X0, Y) res_null = scipy.optimize.minimize( self._loglike_AR1_null, param0, args=( YTY_diag, YTDY_diag, YTFY_diag, X0TX0, X0TDX0, X0TFX0, X0TY, X0TDY, X0TFY, n_T, n_V, n_run, n_X0), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) param_change = res_null.x - param0 param0 = res_null.x.copy() est_rho1_AR1_null = 2.0 / np.pi * np.arctan(param0) if self.auto_nuisance: X0TAX0 = X0TX0[None, :, :] \ - est_rho1_AR1_null[:, None, None] \ * X0TDX0[None, :, :] \ + est_rho1_AR1_null[:, None, None]*2 \ X0TFX0[None, :, :] # dimension: space#baseline#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, est_rho1_AR1_null) # dimension: #baselinespace beta0s = np.linalg.solve(X0TAX0, X0TAY.T).T residuals = Y - np.dot(X_base, beta0s[:np.shape(X_base)[1], :]) X_res = self.nureg_method(self.n_nureg_).fit_transform( self.preprocess_residual(residuals)) if np.max(np.abs(param_change)) < self.tol: logger.info('The change of parameters is smaller than ' 'the tolerance value {}. Fitting is finished ' 'after {} iterations'.format(self.tol, it + 1)) break X0TAX0 = X0TX0[None, :, :] \ - est_rho1_AR1_null[:, None, None] \ X0TDX0[None, :, :] \ + est_rho1_AR1_null[:, None, None]*2 \ X0TFX0[None, :, :] # dimension: space#baseline#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, est_rho1_AR1_null) # dimension: #baselinespace est_beta0_AR1_null = np.linalg.solve(X0TAX0, X0TAY.T).T YTAY = self._make_ar1_quad_form(YTY_diag, YTDY_diag, YTFY_diag, est_rho1_AR1_null) # dimension: space, YTAcorrY = YTAY - np.sum(X0TAY est_beta0_AR1_null, axis=0) # dimension: space, est_sigma_AR1_null = (YTAcorrY / (n_T - n_X0)) ** 0.5 if idx_DC.size > 1: collapsed_DC = np.sum(X0[:, idx_DC], axis=1) X0 = np.insert(np.delete(X0, idx_DC, axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(est_beta0_AR1_null[idx_DC, :], axis=0) est_beta0_AR1_null = np.insert( np.delete(est_beta0_AR1_null, idx_DC, axis=0), 0, collapsed_beta0, axis=0) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) return est_beta0_AR1_null, est_sigma_AR1_null, est_rho1_AR1_null, X0 # We fit two parts of the parameters iteratively. # The following are the corresponding negative log likelihood functions. def _loglike_AR1_diagV_fitU(self, param, XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, log_SNR2, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitU, rank): # This function calculates the log likelihood of data given cholesky # decomposition of U and AR(1) parameters of noise as free parameters. # Free parameters are in param. # The log of the square of signal to noise level in each voxel # (the ratio of the diagonal elements in V and # the noise variance) are fixed. This likelihood is iteratively # optimized with the one with suffix _fitV. # # The meaing of U and V follow this wiki page of matrix normal # distribution: # https://en.wikipedia.org/wiki/Matrix_normal_distribution # # We assume betas of all voxels as a matrix follow this distribution. # U describe the covariance between conditions. V describe the # covariance between voxels. # # In this version, we assume that beta is independent between voxels # and noise is also independent. # By the assumption that noise is independent, we only need to pass # the products X'X, X'Y and Y'Y, instead of X and Y # Y'Y is passed in the form of its diagonal elements. # DiagV means we assume that the variance of beta can be different # between voxels. This means that V is a diagonal matrix instead of # an identity matrix. The parameter includes the lower triangular # part of the cholesky decomposition # of U (flattened), then tan(rho1pi/2) where rho1 is # each voxel's autoregressive coefficient (assumging AR(1) model). # Such parametrization avoids the need of boundaries # for parameters. L = np.zeros([n_C, rank]) # lower triagular matrix L, cholesky decomposition of U L[l_idx] = param[idx_param_fitU['Cholesky']] a1 = param[idx_param_fitU['a1']] rho1 = 2.0 / np.pi np.arctan(a1) # auto-regressive coefficients SNR2 = np.exp(log_SNR2) # each element of SNR2 is the ratio of the diagonal element on V # to the variance of the fresh noise in that voxel X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, \ LTXTAcorrY, XTAcorrXL, LTXTAcorrXL = \ self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0) # Only starting from this point, SNR2 is involved LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, SNR2, n_V, n_T, n_run, rank, n_X0) if not np.isfinite(LL): logger.warning('NaN detected!') logger.warning('LL: {}'.format(LL)) logger.warning('sigma2: {}'.format(sigma2)) logger.warning('YTAcorrY: {}'.format(YTAcorrY)) logger.warning('LTXTAcorrY: {}'.format(LTXTAcorrY)) logger.warning('YTAcorrXL_LAMBDA: {}'.format(YTAcorrXL_LAMBDA)) logger.warning('SNR2: {}'.format(SNR2)) YTAcorrXL_LAMBDA_LT = np.dot(YTAcorrXL_LAMBDA, L.T) # dimension: spacefeature (feature can be larger than rank) deriv_L = -np.einsum('ijk,ikl,i', XTAcorrXL, LAMBDA, SNR2) \ - np.dot(np.einsum('ijk,ik->ji', XTAcorrXL, YTAcorrXL_LAMBDA) SNR2*2 / sigma2, YTAcorrXL_LAMBDA) \ + np.dot(XTAcorrY / sigma2 SNR2, YTAcorrXL_LAMBDA) # dimension: featurerank # The following are for calculating the derivative to a1 deriv_a1 = np.empty(n_V) dXTAX_drho1 = -XTDX + 2 rho1[:, None, None] * XTFX # dimension: spacefeaturefeature dXTAY_drho1 = self._make_ar1_quad_form_grad(XTDY, XTFY, rho1) # dimension: featurespace dYTAY_drho1 = self._make_ar1_quad_form_grad(YTDY_diag, YTFY_diag, rho1) # dimension: space, dX0TAX0_drho1 = - X0TDX0 \ + 2 rho1[:, None, None] * X0TFX0 # dimension: spacerankrank dXTAX0_drho1 = - XTDX0 \ + 2 * rho1[:, None, None] * XTFX0 # dimension: spacefeaturerank dX0TAY_drho1 = self._make_ar1_quad_form_grad(X0TDY, X0TFY, rho1) # dimension: rankspace # The following are executed for each voxel. for i_v in range(n_V): # All variables with _ele as suffix are for data of just one voxel invX0TAX0_X0TAX_ele = np.dot(X0TAX0_i[i_v, :, :], XTAX0[i_v, :, :].T) invX0TAX0_X0TAY_ele = np.dot(X0TAX0_i[i_v, :, :], X0TAY[:, i_v]) dXTAX0_drho1_invX0TAX0_X0TAX_ele = np.dot(dXTAX0_drho1[i_v, :, :], invX0TAX0_X0TAX_ele) # preparation for the variable below dXTAcorrX_drho1_ele = dXTAX_drho1[i_v, :, :] \ - dXTAX0_drho1_invX0TAX0_X0TAX_ele \ - dXTAX0_drho1_invX0TAX0_X0TAX_ele.T \ + np.dot(np.dot(invX0TAX0_X0TAX_ele.T, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAX_ele) dXTAcorrY_drho1_ele = dXTAY_drho1[:, i_v] \ - np.dot(invX0TAX0_X0TAX_ele.T, dX0TAY_drho1[:, i_v]) \ - np.dot(dXTAX0_drho1[i_v, :, :], invX0TAX0_X0TAY_ele) \ + np.dot(np.dot(invX0TAX0_X0TAX_ele.T, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAY_ele) dYTAcorrY_drho1_ele = dYTAY_drho1[i_v] \ - np.dot(dX0TAY_drho1[:, i_v], invX0TAX0_X0TAY_ele) 2\ + np.dot(np.dot(invX0TAX0_X0TAY_ele, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAY_ele) deriv_a1[i_v] = 2 / np.pi / (1 + a1[i_v]*2) \ (- n_run * rho1[i_v] / (1 - rho1[i_v]*2) - np.einsum('ij,ij', X0TAX0_i[i_v, :, :], dX0TAX0_drho1[i_v, :, :]) 0.5 - np.einsum('ij,ij', LAMBDA[i_v, :, :], np.dot(np.dot( L.T, dXTAcorrX_drho1_ele), L)) * (SNR2[i_v] * 0.5) - dYTAcorrY_drho1_ele * 0.5 / sigma2[i_v] + SNR2[i_v] / sigma2[i_v] * np.dot(dXTAcorrY_drho1_ele, YTAcorrXL_LAMBDA_LT[i_v, :]) - (0.5 * SNR2[i_v]*2 / sigma2[i_v]) np.dot(np.dot(YTAcorrXL_LAMBDA_LT[i_v, :], dXTAcorrX_drho1_ele), YTAcorrXL_LAMBDA_LT[i_v, :])) deriv = np.empty(np.size(param)) deriv[idx_param_fitU['Cholesky']] = deriv_L[l_idx] deriv[idx_param_fitU['a1']] = deriv_a1 return -LL, -deriv def _loglike_AR1_diagV_fitV(self, param, X0TAX0, XTAX0, X0TAY, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL, L_l, a1, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitV, rank=None, GP_space=False, GP_inten=False, dist2=None, inten_dist2=None, space_smooth_range=None, inten_smooth_range=None): # This function calculates the log likelihood of data given # the log of the square of pseudo signal to noise ratio in each voxel. # The free parameter log(SNR^2) is in param # This likelihood is iteratively optimized with the one with _fitU. # The cholesky factor of U and autoregressive coefficient # in temporal AR(1) model for noise are fixed. # Because the ML estimate of the variance of noise in each voxel # (sigma^2) given other parameters has analytic form, # we do not need to explicitly parametrize it. # Just set it to the ML value. # # L_l is the lower triangular part of L, a1 is tan(rho1pi/2), # where rho1 is the autoregressive coefficient in each voxel # We can optionally include Gaussion Process prior to log(SNR). # This term is not included in _fitU, because log(SNR) # are fixed in _fitU. # GP_space and GP_inten are Boolean, indicating whether we want to # include GP kernels either on voxel coordinates or intensity. # dist2 and inten_dist2 are the squares of spatial distances and # intensity differences ([n_voxel x n_voxel]. space_smooth_range # and inten_smooth_range are the range we believe the GP length # scale should reside in. They are used in additional half-cauchy # prior to constraint these length scales. n_l = np.size(l_idx[0]) # the number of parameters in the index of lower-triangular matrix if rank is None: rank = int((2 n_C + 1 - np.sqrt(n_C*2 4 + n_C * 4 + 1 - 8 * n_l)) / 2) L = np.zeros([n_C, rank]) L[l_idx] = L_l log_SNR2 = np.empty(n_V) log_SNR2[0:n_V - 1] = param[idx_param_fitV['log_SNR2']] log_SNR2[-1] = -np.sum(log_SNR2[0:n_V - 1]) # This is following the restriction that SNR's have geometric mean # of 1. That is why they are called pseudo-SNR. This restriction # is imposed because SNR and L are determined only up to a scale # Be cautious that during simulation, when there is absolute # no signal in the data, sometimes the fitting diverges, # presumably because we have created correlation between logS_NR2 # due to the constraint. But I have not reproduced this often. SNR2 = np.exp(log_SNR2) # If requested, a GP prior is imposed on log(SNR). rho1 = 2.0 / np.pi * np.arctan(a1) # AR(1) coefficient, dimension: space LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, SNR2, n_V, n_T, n_run, rank, n_X0) # Log likelihood of data given parameters, without the GP prior. deriv_log_SNR2 = (-rank + np.trace(LAMBDA, axis1=1, axis2=2)) * 0.5\ + np.sum(YTAcorrXL_LAMBDA*2, axis=1) SNR2 / sigma2 / 2 # Partial derivative of log likelihood over log(SNR^2) # dimension: space, # The second term above is due to the equation for calculating # sigma2 if GP_space: # Imposing GP prior on log(SNR) at least over # spatial coordinates c_space = param[idx_param_fitV['c_space']] l2_space = np.exp(c_space) # The square of the length scale of the GP kernel defined on # the spatial coordinates of voxels dl2_dc_space = l2_space # partial derivative of l^2 over b if GP_inten: c_inten = param[idx_param_fitV['c_inten']] l2_inten = np.exp(c_inten) # The square of the length scale of the GP kernel defined # on the image intensity of voxels dl2_dc_inten = l2_inten # partial derivative of l^2 over b K_major = np.exp(- (dist2 / l2_space + inten_dist2 / l2_inten) / 2.0) else: K_major = np.exp(- dist2 / l2_space / 2.0) # The kernel defined over the spatial coordinates of voxels. # This is a template: the diagonal values are all 1, meaning # the variance of log(SNR) has not been multiplied K_tilde = K_major + np.diag(np.ones(n_V) * self.eta) # We add a small number to the diagonal to make sure the matrix # is invertible. # Note that the K_tilder here is still template: # It is the correct K divided by the variance tau^2 # So it does not depend on the variance of the GP. L_K_tilde = np.linalg.cholesky(K_tilde) inv_L_K_tilde = np.linalg.solve(L_K_tilde, np.identity(n_V)) inv_K_tilde = np.dot(inv_L_K_tilde.T, inv_L_K_tilde) log_det_K_tilde = np.sum(np.log(np.diag(L_K_tilde)*2)) invK_tilde_log_SNR = np.dot(inv_K_tilde, log_SNR2) / 2 log_SNR_invK_tilde_log_SNR = np.dot(log_SNR2, invK_tilde_log_SNR) / 2 # MAP estimate of the variance of the Gaussian Process given # other parameters. tau2, log_ptau = self.tau2_prior(log_SNR_invK_tilde_log_SNR, n_V, self.tau_range) # log_ptau is log(p(tau)) given the form of prior for tau LL += log_ptau # GP prior terms added to the log likelihood LL = LL - log_det_K_tilde / 2.0 - n_V / 2.0 np.log(tau2) \ - np.log(2 * np.pi) * n_V / 2.0 \ - log_SNR_invK_tilde_log_SNR / tau2 / 2 deriv_log_SNR2 -= invK_tilde_log_SNR / tau2 / 2.0 # Note that the derivative to log(SNR) is # invK_tilde_log_SNR / tau2, but we are calculating the # derivative to log(SNR^2) dK_tilde_dl2_space = dist2 * (K_major) / 2.0 \ / l2_space*2 deriv_c_space = \ (np.dot(np.dot(invK_tilde_log_SNR, dK_tilde_dl2_space), invK_tilde_log_SNR) / tau2 / 2.0 - np.sum(inv_K_tilde dK_tilde_dl2_space) / 2.0)\ * dl2_dc_space # Prior on the length scales LL += scipy.stats.halfcauchy.logpdf( l2_space0.5, scale=space_smooth_range) deriv_c_space -= 1 / (l2_space + space_smooth_range2)\ * dl2_dc_space if GP_inten: dK_tilde_dl2_inten = inten_dist2 * K_major \ / 2.0 / l2_inten*2 deriv_c_inten = \ (np.dot(np.dot(invK_tilde_log_SNR, dK_tilde_dl2_inten), invK_tilde_log_SNR) / tau2 / 2.0 - np.sum(inv_K_tilde dK_tilde_dl2_inten) / 2.0)\ * dl2_dc_inten # Prior on the length scale LL += scipy.stats.halfcauchy.logpdf( l2_inten0.5, scale=inten_smooth_range) deriv_c_inten -= 1 / (l2_inten + inten_smooth_range2)\ * dl2_dc_inten else: LL += np.sum(scipy.stats.norm.logpdf(log_SNR2 / 2.0, scale=self.tau_range)) # If GP prior is not requested, we still want to regularize on # the magnitude of log(SNR). deriv_log_SNR2 += - log_SNR2 / self.tau_range*2 / 4.0 deriv = np.empty(np.size(param)) deriv[idx_param_fitV['log_SNR2']] = \ deriv_log_SNR2[0:n_V - 1] - deriv_log_SNR2[n_V - 1] if GP_space: deriv[idx_param_fitV['c_space']] = deriv_c_space if GP_inten: deriv[idx_param_fitV['c_inten']] = deriv_c_inten return -LL, -deriv def _loglike_AR1_singpara(self, param, XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_sing, rank=None): # In this version, we assume that beta is independent # between voxels and noise is also independent. # singpara version uses single parameter of sigma^2 and rho1 # to all voxels. This serves as the initial fitting to get # an estimate of L and sigma^2 and rho1. The SNR is inherently # assumed to be 1. n_l = np.size(l_idx[0]) # the number of parameters in the index of lower-triangular matrix if rank is None: rank = int((2 n_C + 1 - np.sqrt(n_C*2 4 + n_C * 4 + 1 - 8 * n_l)) / 2) L = np.zeros([n_C, rank]) L[l_idx] = param[idx_param_sing['Cholesky']] a1 = param[idx_param_sing['a1']] rho1 = 2.0 / np.pi * np.arctan(a1) XTAX = XTX - rho1 * XTDX + rho1*2 XTFX X0TAX0 = X0TX0 - rho1 * X0TDX0 + rho1*2 X0TFX0 XTAX0 = XTX0 - rho1 * XTDX0 + rho1*2 XTFX0 XTAcorrX = XTAX - np.dot(XTAX0, np.linalg.solve(X0TAX0, XTAX0.T)) XTAcorrXL = np.dot(XTAcorrX, L) LAMBDA_i = np.dot(np.dot(L.T, XTAcorrX), L) + np.eye(rank) XTAY = XTY - rho1 * XTDY + rho1*2 XTFY X0TAY = X0TY - rho1 * X0TDY + rho1*2 X0TFY XTAcorrY = XTAY - np.dot(XTAX0, np.linalg.solve(X0TAX0, X0TAY)) LTXTAcorrY = np.dot(L.T, XTAcorrY) YTAY = YTY_diag - rho1 * YTDY_diag + rho1*2 YTFY_diag YTAcorrY = YTAY \ - np.sum(X0TAY * np.linalg.solve(X0TAX0, X0TAY), axis=0) LAMBDA_LTXTAcorrY = np.linalg.solve(LAMBDA_i, LTXTAcorrY) L_LAMBDA_LTXTAcorrY = np.dot(L, LAMBDA_LTXTAcorrY) sigma2 = np.mean(YTAcorrY - np.sum(LTXTAcorrY * LAMBDA_LTXTAcorrY, axis=0))\ / (n_T - n_X0) LL = n_V * (-np.log(sigma2) * (n_T - n_X0) * 0.5 + np.log(1 - rho1*2) n_run * 0.5 - self._half_log_det(X0TAX0) - self._half_log_det(LAMBDA_i)) deriv_L = np.dot(XTAcorrY, LAMBDA_LTXTAcorrY.T) / sigma2 \ - np.dot(np.dot(XTAcorrXL, LAMBDA_LTXTAcorrY), LAMBDA_LTXTAcorrY.T) / sigma2 \ - np.linalg.solve(LAMBDA_i, XTAcorrXL.T).T * n_V # These terms are used to construct derivative to a1. dXTAX_drho1 = - XTDX + 2 * rho1 * XTFX dX0TAX0_drho1 = - X0TDX0 + 2 * rho1 * X0TFX0 dXTAX0_drho1 = - XTDX0 + 2 * rho1 * XTFX0 invX0TAX0_X0TAX = np.linalg.solve(X0TAX0, XTAX0.T) dXTAX0_drho1_invX0TAX0_X0TAX = np.dot(dXTAX0_drho1, invX0TAX0_X0TAX) dXTAcorrX_drho1 = dXTAX_drho1 - dXTAX0_drho1_invX0TAX0_X0TAX \ - dXTAX0_drho1_invX0TAX0_X0TAX.T \ + np.dot(np.dot(invX0TAX0_X0TAX.T, dX0TAX0_drho1), invX0TAX0_X0TAX) dLTXTAcorrXL_drho1 = np.dot(np.dot(L.T, dXTAcorrX_drho1), L) dYTAY_drho1 = - YTDY_diag + 2 * rho1 * YTFY_diag dX0TAY_drho1 = - X0TDY + 2 * rho1 * X0TFY invX0TAX0_X0TAY = np.linalg.solve(X0TAX0, X0TAY) dYTAX0_drho1_invX0TAX0_X0TAY = np.sum(dX0TAY_drho1 * invX0TAX0_X0TAY, axis=0) dYTAcorrY_drho1 = dYTAY_drho1 - dYTAX0_drho1_invX0TAX0_X0TAY * 2\ + np.sum(invX0TAX0_X0TAY * np.dot(dX0TAX0_drho1, invX0TAX0_X0TAY), axis=0) dXTAY_drho1 = - XTDY + 2 * rho1 * XTFY dXTAcorrY_drho1 = dXTAY_drho1 \ - np.dot(dXTAX0_drho1, invX0TAX0_X0TAY) \ - np.dot(invX0TAX0_X0TAX.T, dX0TAY_drho1) \ + np.dot(np.dot(invX0TAX0_X0TAX.T, dX0TAX0_drho1), invX0TAX0_X0TAY) deriv_a1 = 2.0 / (np.pi * (1 + a1*2)) \ (n_V * (- n_run * rho1 / (1 - rho1*2) - 0.5 np.trace(np.linalg.solve( X0TAX0, dX0TAX0_drho1)) - 0.5 * np.trace(np.linalg.solve( LAMBDA_i, dLTXTAcorrXL_drho1))) - 0.5 * np.sum(dYTAcorrY_drho1) / sigma2 + np.sum(dXTAcorrY_drho1 * L_LAMBDA_LTXTAcorrY) / sigma2 - 0.5 * np.sum(np.dot(dXTAcorrX_drho1, L_LAMBDA_LTXTAcorrY) * L_LAMBDA_LTXTAcorrY) / sigma2) deriv = np.empty(np.size(param)) deriv[idx_param_sing['Cholesky']] = deriv_L[l_idx] deriv[idx_param_sing['a1']] = deriv_a1 return -LL, -deriv def _loglike_AR1_null(self, param, YTY_diag, YTDY_diag, YTFY_diag, X0TX0, X0TDX0, X0TFX0, X0TY, X0TDY, X0TFY, n_T, n_V, n_run, n_X0): # This function calculates the log likelihood of data given AR(1) # parameters of noise as free parameters. # Free parameters are in param. # It serves as a null model which assumes no response to design # matrix. a1 = param rho1 = 2.0 / np.pi * np.arctan(a1) # auto-regressive coefficients YTAY = self._make_ar1_quad_form(YTY_diag, YTDY_diag, YTFY_diag, rho1) # dimension: space, # A/sigma2 is the inverse of noise covariance matrix in each voxel. # YTAY means Y'AY X0TAX0 = X0TX0[None, :, :] - rho1[:, None, None] \ * X0TDX0[None, :, :] \ + rho1[:, None, None]*2 X0TFX0[None, :, :] # dimension: space#baseline#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, rho1) # dimension: #baselinespace # X0TAX0_i = np.linalg.solve(X0TAX0, np.identity(n_X0)[None, :, :]) X0TAX0_i = np.linalg.inv(X0TAX0) # dimension: space#baseline#baseline YTAcorrY = YTAY - np.sum(X0TAY np.einsum('ijk,ki->ji', X0TAX0_i, X0TAY), axis=0) # dimension: space, sigma2 = YTAcorrY / (n_T - n_X0) # dimension: space, LL = - np.sum(np.log(sigma2)) * (n_T - n_X0) * 0.5 \ + np.sum(np.log(1 - rho1*2)) n_run * 0.5 \ - np.sum(self._half_log_det(X0TAX0)) \ - (n_T - n_X0) * n_V * (1 + np.log(2 * np.pi)) * 0.5 # The following are for calculating the derivative to a1 deriv_a1 = np.empty(n_V) dYTAY_drho1 = self._make_ar1_quad_form_grad(YTDY_diag, YTFY_diag, rho1) # dimension: space, dX0TAX0_drho1 = - X0TDX0 \ + 2 * rho1[:, None, None] * X0TFX0 # dimension: spacerankrank dX0TAY_drho1 = self._make_ar1_quad_form_grad(X0TDY, X0TFY, rho1) # dimension: rankspace # The following are executed for each voxel. for i_v in range(n_V): # All variables with _ele as suffix are for data of just one voxel invX0TAX0_X0TAY_ele = np.dot(X0TAX0_i[i_v, :, :], X0TAY[:, i_v]) # preparation for the variable below dYTAcorrY_drho1_ele = dYTAY_drho1[i_v] \ - np.dot(dX0TAY_drho1[:, i_v], invX0TAX0_X0TAY_ele) 2\ + np.dot(np.dot(invX0TAX0_X0TAY_ele, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAY_ele) deriv_a1[i_v] = 2 / np.pi / (1 + a1[i_v]*2) \ (- n_run * rho1[i_v] / (1 - rho1[i_v]*2) - np.einsum('ij,ij', X0TAX0_i[i_v, :, :], dX0TAX0_drho1[i_v, :, :]) 0.5 - dYTAcorrY_drho1_ele * 0.5 / sigma2[i_v]) deriv = deriv_a1 return -LL, -deriv class GBRSA(BRSA): """Group Bayesian representational Similarity Analysis (GBRSA) Given the time series of neural imaging data in a region of interest (ROI) and the hypothetical neural response (design matrix) to each experimental condition of interest, calculate the shared covariance matrix of the voxels(recording unit)' response to each condition, and the relative SNR of each voxels. The relative SNR could be considered as the degree of contribution of each voxel to this shared covariance matrix. A correlation matrix converted from the covariance matrix will be provided as a quantification of neural representational similarity. Both tools provide estimation of SNR and noise parameters at the end, and both tools provide empirical Bayesian estimates of activity patterns beta, together with weight map of nuisance signals beta0. The differences of this tool from BRSA are: (1) It allows fitting a shared covariance matrix (which can be converted to similarity matrix) across multiple subjects. This is analogous to SRM under funcalign submodule. Because of using multiple subjects, the result is less noisy. (2) In the fitting process, the SNR and noise parameters are marginalized for each voxel. Therefore, this tool should be faster than BRSA when analyzing an ROI of hundreds to thousands voxels. It does not provide a spatial smoothness prior on SNR though. (3) The voxel-wise pseudo-SNR and noise parameters estimated are posterior mean estimates, while those estimated by BRSA are maximum-a-posterior estimates. If your goal is to perform searchlight RSA with relatively fewer voxels on single subject, BRSA should be faster. However, GBRSA can in principle be used together with searchlight in a template space such as MNI. .. math:: Y = X \\cdot \\beta + X_0 \\cdot \\beta_0 + \\epsilon \\beta_i \\sim N(0,(s_{i} \\sigma_{i})^2 U) See also `.BRSA`. Please note that the model assumes that the covariance matrix U which all \\beta_i follow is zero-meaned. For more details of its implication, see documentation of `.BRSA` Parameters ---------- n_iter : int. Number of maximum iterations to run the algorithm. rank : int. The rank of the covariance matrix. If not provided, the covariance matrix will be assumed to be full rank. When you have many conditions (e.g., calculating the similarity matrix of responses to each event), you might want to start with specifying a lower rank and use metrics such as AIC or BIC to decide the optimal rank. The log likelihood for the fitted data can be retrieved through private attributes _LL_train\\_. Note that this log likelihood score is only used here for selecting hyperparameters such as rank. For any formal model comparison, we recommend using score() function on left-out data. auto_nuisance: Boolean. In order to model spatial correlation between voxels that cannot be accounted for by common response captured in the design matrix, we assume that a set of time courses not related to the task conditions are shared across voxels with unknown amplitudes. One approach is for users to provide time series which they consider as nuisance but exist in the noise (such as head motion). The other way is to take the first n_nureg principal components in the residual after subtracting the response to the design matrix from the data, and use these components as the nuisance regressor. This flag is for the second approach. If turned on, PCA or factor analysis will be applied to the residuals to obtain new nuisance regressors in each round of fitting. These two approaches can be combined. If the users provide nuisance regressors and set this flag as True, then the first n_nureg principal components of the residuals after subtracting both the responses to design matrix and the user-supplied nuisance regressors will be used in addition to the nuisance regressors provided by the users. Note that nuisance regressor is not required from user. If it is not provided, DC components for each run will be included as nuisance regressor regardless of the auto_nuisance parameter. n_nureg: Optional[int]. Number of nuisance regressors to use in order to model signals shared across voxels not captured by the design matrix. This number is in addition to any nuisance regressor that the user has already provided. If set to None, the number of nuisance regressors will be automatically determined based on M Gavish and D Donoho's approximate estimation of optimal hard threshold for singular values. (Gavish & Donoho, IEEE Transactions on Information Theory 60.8 (2014): 5040-5053.) This only takes effect if auto_nuisance is True. nureg_zscore: Boolean. A flag to tell the algorithm whether data is z-scored before estimating the number of nuisance regressor components necessary to account for spatial noise correlation. It also determinie whether the residual noise is z-scored before estimating the nuisance regressors from residual. This only takes effect if auto_nuisance is True. nureg_method: string, naming a method from sklearn.decomposition. 'PCA', 'ICA', 'FA' or 'SPCA' are currently supported. The method to estimate the shared component in noise across voxels. This only takes effect if auto_nuisance is True. baseline_single: Boolean. A time course of constant 1 will be included to the nuisance regressor for each participant. If baseline_single is set to False, one such regressor is included for each fMRI run, but at the end of fitting, a single component in beta0\\_ will be computed as the average of the weight maps corresponding to these regressors. This might cause underestimation of noise variance. If baseline_single is True, only one regressor of constant 1 will be used for the whole dataset. This might be desirable if you believe the average image intensity might not scale with the same proportion for different voxels across scan. In other words, it is possible that some part of the brain is more vulnerable to change in baseline intensity due to facts such as field inhomogeneity. Setting baseline_single to True will force the nuisance regressors automatically estimated from residuals to capture this. However, when each task condition only occurs in one run and when the design matrix in each run sums together close to a flat line, this option can cause the estimated similarity to be extremely high between conditions occuring in the same run. SNR_prior: string. The type of prior for pseudo-SNR. If set to 'exp', truncated exponential distribution with scale parameter of 1 is imposed on pseudo-SNR. If set to 'lognorm', a truncated log normal prior is imposed. In this case, the standard deviation of log(SNR) is set by the parameter logS_range. If set to 'unif', a uniform prior in [0,1] is imposed. In all above cases, SNR is numerically marginalized on a grid of parameters. So the parameter SNR_bins determines how accurate the numerical integration is. The more number of bins are used, the more accurate the numerical integration becomes. If set to 'equal', all voxels are assumed to have the same fixed SNR. Pseudo-SNR is 1.0 for all voxels. In all the cases, the grids used for pseudo-SNR do not really set an upper bound for SNR, because the real SNR is determined by both pseudo-SNR and U, the shared covariance structure. logS_range: float. The reasonable range of the spread of SNR in log scale. This parameter only takes effect if SNR_prior is set to 'lognorm'. It is effectively the `s` parameter of `scipy.stats.lognorm`, or the standard deviation of the distribution in log scale. logS_range specifies how variable you believe the SNRs to vary across voxels in log scale. This range should not be set too large, otherwise the fitting may encounter numerical issue. If it is set too small, the estimated SNR will turn to be too close to each other and the estimated similarity matrix might overfit to voxels of low SNR. If you increase logS_range, it is recommended to increase SNR_bins accordingly, otherwise the pseudo-SNR values evaluated might be too sparse, causing the posterior pseudo-SNR estimations to be clustered around the bins. SNR_bins: integer. The number of bins used to numerically marginalize the pseudo-SNR parameter. In general, you should try to choose a large number to the degree that decreasing SNR_bins does not change the result of fitting result. However, very large number of bins also causes slower computation and larger memory consumption. For SNR_prior='lognorm', the default value 21 is based on the default value of logS_range=1.0 and bin width of 0.3 on log scale. But it is also a reasonable choice for the other two options for SNR_prior. rho_bins: integer. The number of bins to divide the region of (-1, 1) for rho. This only takes effect for fitting the marginalized version. If set to 20, discrete numbers of {-0.95, -0.85, ..., 0.95} will be used to numerically integrate rho from -1 to 1. optimizer: str or callable. The optimizer to use for minimizing cost function which scipy.optimize.minimize can accept. We use 'L-BFGS-B' as a default. Users can try other strings corresponding to optimizer provided by scipy.optimize.minimize, or a custom optimizer, such as 'BFGS' or 'CG'. Note that BRSA fits a lot of parameters. So a chosen optimizer should accept gradient (Jacobian) of the cost function. Otherwise the fitting is likely to be unbarely slow. We do not calculate Hessian of the objective function. So an optimizer which requires Hessian cannot be used. minimize_options: dictionary. This is the dictionary passed as the options argument to scipy.optimize.minize which minimizes the cost function during fitting. Notice that the minimization is performed for up to n_iter times, with the nuisance regressor re-estimated each time. So within each of the n_iter steps of fitting, scipy.optimize.minize does not need to fully converge. The key 'maxiter' in this dictionary determines the maximum number of iteration done by scipy.optimize.minimize within each of the n_iter steps of fitting. tol: float. Tolerance parameter passed to scipy.optimize.minimize. It is also used for determining convergence of the alternating fitting procedure. random_state : RandomState or an int seed. A random number generator instance to define the state of the random permutations generator whenever the module needs to generate random number (e.g., initial parameter of the Cholesky factor). anneal_speed: float. Annealing is introduced in fitting of the Cholesky decomposition of the shared covariance matrix. The amount of perturbation decays exponentially. This parameter sets the ratio of the maximum number of iteration to the time constant of the exponential. anneal_speed=10 means by n_iter/10 iterations, the amount of perturbation is reduced by 2.713 times. Attributes ---------- U_ : numpy array, shape=[condition,condition]. The shared covariance matrix L_ : numpy array, shape=[condition,condition]. The Cholesky factor of the shared covariance matrix (lower-triangular matrix). C_: numpy array, shape=[condition,condition]. The correlation matrix derived from the shared covariance matrix. This is the estimated similarity matrix between neural patterns to your task conditions. Notice that it is recommended that you also check U\\_, which is the covariance matrix underlying this correlation matrix. In cases there is almost no response to your task conditions, the diagonal values of U\\_ would become very small and C\\_ might contain many correlation coefficients close to 1 or -1. This might not reflect true strong correlation or strong negative correlation, but a result of lack of task-related neural activity, design matrix that does not match true neural response, or not enough data. It is also recommended to check nSNR\\_ after mapping it back to the brain. A "reasonable" map should at least have higher values in gray matter in than white matter. nSNR_ : list of numpy arrays, shape=[voxels,] for each subject in the list. The pseuso-SNR of all voxels. If SNR_prior='lognormal', the geometric mean of nSNR\\_ would be approximately 1. If SNR_prior='unif', all nSNR\\_ would be in the range of (0,1). If SNR_prior='exp' (default), the range of values would vary depending on the data and SNR_bins, but many should have low values with few voxels with high values. Note that this attribute can not be interpreted as true SNR, but the relative ratios between voxels indicate the contribution of each voxel to the representational similarity structure. sigma_ : list of numpy arrays, shape=[voxels,] for each subject. The estimated standard deviation of the noise in each voxel Assuming AR(1) model, this means the standard deviation of the innovation noise. rho_ : list of numpy arrays, shape=[voxels,] for each subject. The estimated autoregressive coefficient of each voxel beta_: list of numpy arrays, shape=[conditions, voxels] for each subject. The posterior mean estimation of the response amplitudes of each voxel to each task condition. beta0_: list of numpy arrays, shape=[n_nureg + n_base, voxels] for each subject. The loading weights of each voxel for the shared time courses not captured by the design matrix. n_base is the number of columns of the user-supplied nuisance regressors plus one for DC component. X0_: list of numpy arrays, shape=[time_points, n_nureg + n_base] for each subject. The estimated time course that is shared across voxels but unrelated to the events of interest (design matrix). beta0_null_: list of numpy arrays, shape=[n_nureg + n_base, voxels] for each subject. The equivalent of beta0\\_ in a null model which does not include the design matrix and response pattern beta X0_null_: list of numpy arrays, shape=[time_points, n_nureg + n_base] for each subject. The equivalent of X0\\_ in a null model which does not include the design matrix and response pattern beta n_nureg_: 1-d numpy array Number of nuisance regressor used to model the spatial noise correlation of each participant. random_state_: `RandomState` Random number generator initialized using random_state. """ def __init__( self, n_iter=100, rank=None, auto_nuisance=True, n_nureg=None, nureg_zscore=True, nureg_method='PCA', baseline_single=False, logS_range=1.0, SNR_prior='exp', SNR_bins=21, rho_bins=20, tol=1e-4, optimizer='L-BFGS-B', minimize_options={'gtol': 1e-4, 'disp': False, 'maxiter': 20}, random_state=None, anneal_speed=10): self.n_iter = n_iter self.rank = rank self.auto_nuisance = auto_nuisance self.n_nureg = n_nureg self.nureg_zscore = nureg_zscore if auto_nuisance: assert (n_nureg is None) \ or (isinstance(n_nureg, int) and n_nureg > 0), \ 'n_nureg should be a positive integer or None'\ ' if auto_nuisance is True.' if self.nureg_zscore: self.preprocess_residual = lambda x: _zscore(x) else: self.preprocess_residual = lambda x: x if nureg_method == 'FA': self.nureg_method = lambda x: FactorAnalysis(n_components=x) elif nureg_method == 'PCA': self.nureg_method = lambda x: PCA(n_components=x, whiten=True) elif nureg_method == 'SPCA': self.nureg_method = lambda x: SparsePCA(n_components=x, max_iter=20, tol=tol) elif nureg_method == 'ICA': self.nureg_method = lambda x: FastICA(n_components=x, whiten=True) else: raise ValueError('nureg_method can only be FA, PCA, ' 'SPCA(for sparse PCA) or ICA') self.baseline_single = baseline_single if type(logS_range) is int: logS_range = float(logS_range) self.logS_range = logS_range assert SNR_prior in ['unif', 'lognorm', 'exp', 'equal'], \ 'SNR_prior can only be chosen from ''unif'', ''lognorm''' \ ' ''exp'' and ''equal''' self.SNR_prior = SNR_prior if self.SNR_prior == 'equal': self.SNR_bins = 1 else: self.SNR_bins = SNR_bins self.rho_bins = rho_bins self.tol = tol self.optimizer = optimizer self.minimize_options = minimize_options self.random_state = random_state self.anneal_speed = anneal_speed return def fit(self, X, design, nuisance=None, scan_onsets=None): """ Fit the model to data of all participants jointly. Parameters ---------- X: list of numpy arrays, shape=[time_points, voxels] for each entry. Data to be fitted. Each participant corresponds to one item in the list. If you have multiple scans of the same participants that you want to analyze together, you should concatenate them along the time dimension after proper preprocessing (e.g. spatial alignment), and specify the onsets of each scan in scan_onsets. design: list of numpy arrays, shape=[time_points, conditions] for each. This is the design matrix of each participant. It should only include the hypothetic response for task conditions. You should not include regressors for a DC component or motion parameters, unless with a strong reason. If you want to model head motion, you should include them in nuisance regressors. If you have multiple run, the design matrix of all runs should be concatenated along the time dimension for each participant, with every column for one condition across runs. If the design matrix is the same for all subjects, either provide a list as required, or provide single numpy array. nuisance: optional, list of numpy arrays, shape=[time_points, nuisance_factors] for each subject in the list. Nuisance regressors of each participant. The responses to these regressors will be marginalized out from each voxel, which means they are considered, but won't be assumed to share the same pseudo-SNR map with the design matrix. Therefore, the pseudo-SNR map will only reflect the relative contribution of design matrix to each voxel. You can provide time courses such as those for head motion to this parameter. Note that if auto_nuisance is set to True, the first n_nureg principal components of residual (excluding the response to the design matrix and the user-provided nuisance regressors) will be included as additional nuisance regressor after the first round of fitting. If auto_nuisance is set to False, the nuisance regressors supplied by the users together with DC components will be used as nuisance time series. scan_onsets: optional, list numpy arrays, shape=[runs,] for each. Each item in the list specifies the indices of X which correspond to the onset of each scanning run for one participant. For example, if you have two experimental runs of the first participant, each with 100 TRs, and one run of the second participant, with 150 TR, then scan_onsets should be [ndarry([0, 100]), ndarry([150])]. The effect of this argument is to make the inverse matrix of the temporal covariance matrix of noise block-diagonal. If you do not provide the argument, the program will assume all data are from the same run for each participant. """ logger.info('Running Group Bayesian RSA (which can also analyze' ' data of a single participant). Voxel-specific parameters' 'are all marginalized.') self.random_state_ = check_random_state(self.random_state) # setting random seed logger.debug('RandState set to {}'.format(self.random_state_)) # Checking all inputs. X = self._check_data_GBRSA(X) design = self._check_design_GBRSA(design, X) nuisance = self._check_nuisance_GBRSA( copy.deepcopy(nuisance), X) # The reason that we use copy of nuisance is because they # may be modified inside our code. scan_onsets = self._check_scan_onsets_GBRSA(scan_onsets, X) # Run Marginalized Bayesian RSA # Note that we have a change of notation here. # Within _fit_RSA_marginalized, design matrix is named X # and data is named Y, to reflect the # generative model that data Y is generated by mixing the response # X to experiment conditions and other neural activity. # However, in fit(), we keep the scikit-learn API that # X is the input data to fit and y, a reserved name not used, is # the label to map to from X. assert self.SNR_bins >= 10 and self.SNR_prior != 'equal' or \ self.SNR_bins == 1 and self.SNR_prior == 'equal', \ 'At least 10 bins are required to perform the numerical'\ ' integration over SNR, unless choosing SNR_prior=''equal'','\ ' in which case SNR_bins should be 1.' assert self.rho_bins >= 10, \ 'At least 10 bins are required to perform the numerical'\ ' integration over rho' assert self.logS_range * 6 / self.SNR_bins < 0.5 \ or self.SNR_prior != 'lognorm', \ 'The minimum grid of log(SNR) should not be larger than 0.5 '\ 'if log normal prior is chosen for SNR.' \ ' Please consider increasing SNR_bins or reducing logS_range' self.n_subj_ = len(X) self.n_V_ = [None] * self.n_subj_ for subj, x in enumerate(X): self.n_V_[subj] = x.shape[1] if self.auto_nuisance: if self.n_nureg is None: logger.info('numbers of nuisance regressors are determined ' 'automatically.') n_runs = np.zeros(self.n_subj_) n_comps = np.ones(self.n_subj_) for s_id in np.arange(self.n_subj_): # For each subject, determine the number of nuisance # regressors needed to account for the covariance # in residuals. # Residual is calculated by regrssing # out the design matrix and DC component and linear trend # from data of each run. run_TRs, n_runs[s_id] = self._run_TR_from_scan_onsets( X[s_id].shape[0], scan_onsets[s_id]) ts_dc = self._gen_legendre(run_TRs, [0]) _, ts_base, _ = self._merge_DC_to_base( ts_dc, nuisance[s_id], False) ts_reg = np.concatenate((ts_base, design[s_id]), axis=1) beta_hat = np.linalg.lstsq(ts_reg, X[s_id], rcond=None)[0] residuals = X[s_id] - np.dot(ts_reg, beta_hat) n_comps[s_id] = np.min( [np.max([Ncomp_SVHT_MG_DLD_approx( residuals, self.nureg_zscore), 1]), np.linalg.matrix_rank(residuals) - 1]) # n_nureg_ should not exceed the rank of # residual minus 1. self.n_nureg_ = n_comps logger.info('Use {} nuisance regressors to model the spatial ' 'correlation in noise.'.format(self.n_nureg_)) else: self.n_nureg_ = self.n_nureg * np.ones(self.n_subj_) self.n_nureg_ = np.int32(self.n_nureg_) self.beta0_null_, self.sigma_null_, self.rho_null_, self.X0_null_,\ self._LL_null_train_ = self._fit_RSA_marginalized_null( Y=X, X_base=nuisance, scan_onsets=scan_onsets) self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self.sigma_, self.rho_, self.X0_, self._LL_train_ = \ self._fit_RSA_marginalized( X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets) self.C_ = utils.cov2corr(self.U_) self.design_ = design.copy() self._rho_design_ = [None] * self.n_subj_ self._sigma2_design_ = [None] * self.n_subj_ self._rho_X0_ = [None] * self.n_subj_ self._sigma2_X0_ = [None] * self.n_subj_ self._rho_X0_null_ = [None] * self.n_subj_ self._sigma2_X0_null_ = [None] * self.n_subj_ for subj in np.arange(self.n_subj_): self._rho_design_[subj], self._sigma2_design_[subj] = \ self._est_AR1(self.design_[subj], same_para=True) self._rho_X0_[subj], self._sigma2_X0_[subj] = \ self._est_AR1(self.X0_[subj]) self._rho_X0_null_[subj], self._sigma2_X0_null_[subj] =\ self._est_AR1(self.X0_null_[subj]) # AR(1) parameters of the design matrix and nuisance regressors, # which will be used in transform or score. return self def transform(self, X, y=None, scan_onsets=None): """ Use the model to estimate the time course of response to each condition (ts), and the time course unrelated to task (ts0) which is spread across the brain. This is equivalent to "decoding" the design matrix and nuisance regressors from a new dataset different from the training dataset on which fit() was applied. An AR(1) smooth prior is imposed on the decoded ts and ts0 with the AR(1) parameters learnt from the corresponding time courses in the training data. Parameters ---------- X : list of 2-D arrays. For each item, shape=[time_points, voxels] New fMRI data of the same subjects. The voxels should match those used in the fit() function. The size of the list should match the size of the list X fed to fit(), with each item in the list corresponding to data from the same subject in the X fed to fit(). If you do not need to transform some subjects' data, leave the entry corresponding to that subject as None. If data are z-scored when fitting the model, data should be z-scored as well when calling transform() y : not used (as it is unsupervised learning) scan_onsets : list of 1-D numpy arrays, Each array corresponds to the onsets of scans in the data X for the particular subject. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ts : list of 2-D arrays. For each, shape = [time_points, condition] The estimated response to the cognitive dimensions （task dimensions) whose response amplitudes were estimated during the fit step. One item for each subject. If some subjects' data are not provided, None will be returned. ts0: list of 2-D array. For each, shape = [time_points, n_nureg] The estimated time courses spread across the brain, with the loading weights estimated during the fit step. One item for each subject. If some subjects' data are not provided, None will be returned. """ X = self._check_data_GBRSA(X, for_fit=False) scan_onsets = self._check_scan_onsets_GBRSA(scan_onsets, X) assert len(X) == self.n_subj_ ts = [None] * self.n_subj_ ts0 = [None] * self.n_subj_ log_p = [None] * self.n_subj_ for i, x in enumerate(X): if x is not None: s = scan_onsets[i] ts[i], ts0[i], log_p[i] = self._transform( Y=x, scan_onsets=s, beta=self.beta_[i], beta0=self.beta0_[i], rho_e=self.rho_[i], sigma_e=self.sigma_[i], rho_X=self._rho_design_[i], sigma2_X=self._sigma2_design_[i], rho_X0=self._rho_X0_[i], sigma2_X0=self._sigma2_X0_[i]) return ts, ts0 def score(self, X, design, scan_onsets=None): """ After fit() is applied to the data of a group of participants, use the parameters estimated by fit() function to evaluate from some data of a set of participants to evaluate the log likelihood of some new data of the same participants given these estimated parameters. Design matrices of the same set of experimental conditions in the testing data should be provided, with each column corresponding to the same condition as that column in the design matrix of the training data. Unknown nuisance time series will be marginalized, assuming they follow the same spatial pattern as in the training data. The hypothetical response captured by the design matrix will be subtracted from data before the marginalization when evaluating the log likelihood. For null model, nothing will be subtracted before marginalization. There is a difference between the form of likelihood function used in fit() and score(). In fit(), the response amplitude beta to design matrix X and the modulation beta0 by nuisance regressor X0 are both marginalized, with X provided and X0 estimated from data. In score(), posterior estimation of beta and beta0 from the fitting step are assumed unchanged in testing data; X is assumed given by the user, and X0 is marginalized. The logic underlying score() is to transfer as much as what we can learn from training data when calculating a likelihood score for testing data. This is done at the cost of using point estimation for beta and beta0. If you z-scored your data during fit step, you should z-score them for score function as well. If you did not z-score in fitting, you should not z-score here either. Parameters ---------- X : List of 2-D arrays. For each item, shape=[time_points, voxels] fMRI data of new data of the same participants. The voxels of each participants should match those used in the fit() function. If data are z-scored (recommended) when fitting the model, data should be z-scored as well when calling transform() design : List of 2-D arrays. shape=[time_points, conditions] for each Each corresponds to one participant. Design matrices expressing the hypothetical response of the task conditions in data X. scan_onsets : List of 2-D arrays, shape=[#fMRI runs] for each Each array corresponds to one participant. Lists of indices corresponding to the onsets of scans in the data X. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ll: list, shape=[number of participants] The log likelihoods of the new data based on the model and its parameters fit to the training data. If data of some participants are not provided, the corresponding entry will be None. ll_null: list, shape=[number of participants] The log likelihood of the new data based on a null model which assumes the same as the full model for everything except for that there is no response to any of the task conditions. """ X = self._check_data_GBRSA(X, for_fit=False) scan_onsets = self._check_scan_onsets_GBRSA(scan_onsets, X) design = self._check_design_GBRSA(design, X) assert len(X) == self.n_subj_ ll = [None] * self.n_subj_ ll_null = [None] * self.n_subj_ for subj in np.arange(self.n_subj_): if X[subj] is not None: ll[subj] = self._score( Y=X[subj], design=design[subj], beta=self.beta_[subj], scan_onsets=scan_onsets[subj], beta0=self.beta0_[subj], rho_e=self.rho_[subj], sigma_e=self.sigma_[subj], rho_X0=self._rho_X0_[subj], sigma2_X0=self._sigma2_X0_[subj]) ll_null[subj] = self._score( Y=X[subj], design=None, beta=None, scan_onsets=scan_onsets[subj], beta0=self.beta0_[subj], rho_e=self.rho_[subj], sigma_e=self.sigma_[subj], rho_X0=self._rho_X0_[subj], sigma2_X0=self._sigma2_X0_[subj]) return ll, ll_null def _precompute_ar1_quad_forms_marginalized( self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, rho1, n_V, n_X0): # Calculate the sandwich terms which put Acorr between X, Y and X0 # These terms are used a lot in the likelihood. This function # is used for the marginalized version. XTAY = XTY - rho1[:, None, None] * XTDY \ + rho1[:, None, None]*2 XTFY # dimension: #rhofeaturespace YTAY_diag = YTY_diag - rho1[:, None] * YTDY_diag \ + rho1[:, None]*2 YTFY_diag # dimension: #rhospace, # A/sigma2 is the inverse of noise covariance matrix in each voxel. # YTAY means Y'AY XTAX = XTX - rho1[:, None, None] XTDX \ + rho1[:, None, None]*2 XTFX # dimension: n_rhofeaturefeature X0TAX0 = X0TX0[None, :, :] - rho1[:, None, None] \ * X0TDX0[None, :, :] \ + rho1[:, None, None]*2 X0TFX0[None, :, :] # dimension: #rho#baseline#baseline XTAX0 = XTX0[None, :, :] - rho1[:, None, None] \ * XTDX0[None, :, :] \ + rho1[:, None, None]*2 XTFX0[None, :, :] # dimension: n_rhofeature#baseline X0TAY = X0TY - rho1[:, None, None] * X0TDY \ + rho1[:, None, None]*2 X0TFY # dimension: #rho#baselinespace X0TAX0_i = np.linalg.solve(X0TAX0, np.identity(n_X0)[None, :, :]) # dimension: #rho#baseline#baseline XTAcorrX = XTAX # dimension: #rhofeaturefeature XTAcorrY = XTAY # dimension: #rhofeaturespace YTAcorrY_diag = YTAY_diag for i_r in range(np.size(rho1)): XTAcorrX[i_r, :, :] -= \ np.dot(np.dot(XTAX0[i_r, :, :], X0TAX0_i[i_r, :, :]), XTAX0[i_r, :, :].T) XTAcorrY[i_r, :, :] -= np.dot(np.dot(XTAX0[i_r, :, :], X0TAX0_i[i_r, :, :]), X0TAY[i_r, :, :]) YTAcorrY_diag[i_r, :] -= np.sum( X0TAY[i_r, :, :] * np.dot(X0TAX0_i[i_r, :, :], X0TAY[i_r, :, :]), axis=0) return X0TAX0, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY_diag, \ X0TAY, XTAX0 def _fit_RSA_marginalized(self, X, Y, X_base, scan_onsets=None): """ The major utility of fitting Bayesian RSA (marginalized version). Note that there is a naming change of variable. X in fit() is changed to Y here, and design in fit() is changed to X here. This is because we follow the tradition that X expresses the variable defined (controlled) by the experimenter, i.e., the time course of experimental conditions convolved by an HRF, and Y expresses data. However, in wrapper function fit(), we follow the naming routine of scikit-learn. """ rank = self.rank n_subj = len(Y) n_V = [np.size(y, axis=1) for y in Y] n_T = [np.size(y, axis=0) for y in Y] n_C = np.size(X[0], axis=1) l_idx, rank = self._chol_idx(n_C, rank) n_l = np.size(l_idx[0]) # the number of parameters for L t_start = time.time() logger.info('Starting to fit the model. Maximum iteration: ' '{}.'.format(self.n_iter)) # log_SNR_grids, SNR_weights \ # = np.polynomial.hermite.hermgauss(SNR_bins) # SNR_weights = SNR_weights / np.pi*0.5 # SNR_grids = np.exp(log_SNR_grids self.logS_range * 2*.5) SNR_grids, SNR_weights = self._set_SNR_grids() logger.info('The grids of pseudo-SNR used for numerical integration ' 'is {}.'.format(SNR_grids)) assert np.max(SNR_grids) < 1e10, \ 'ATTENTION!! The range of grids of pseudo-SNR' \ ' to be marginalized is too large. Please ' \ 'consider reducing logS_range to 1 or 2' rho_grids, rho_weights = self._set_rho_grids() logger.info('The grids of rho used to do numerical integration ' 'is {}.'.format(rho_grids)) n_grid = self.SNR_bins self.rho_bins log_weights = np.reshape( np.log(SNR_weights[:, None]) + np.log(rho_weights), n_grid) all_rho_grids = np.reshape(np.repeat( rho_grids[None, :], self.SNR_bins, axis=0), n_grid) all_SNR_grids = np.reshape(np.repeat( SNR_grids[:, None], self.rho_bins, axis=1), n_grid) # Prepare the data for fitting. These pre-calculated matrices # will be re-used a lot in evaluating likelihood function and # gradient. D = [None] * n_subj F = [None] * n_subj run_TRs = [None] * n_subj n_run = [None] * n_subj XTY = [None] * n_subj XTDY = [None] * n_subj XTFY = [None] * n_subj YTY_diag = [None] * n_subj YTDY_diag = [None] * n_subj YTFY_diag = [None] * n_subj XTX = [None] * n_subj XTDX = [None] * n_subj XTFX = [None] * n_subj X0TX0 = [None] * n_subj X0TDX0 = [None] * n_subj X0TFX0 = [None] * n_subj XTX0 = [None] * n_subj XTDX0 = [None] * n_subj XTFX0 = [None] * n_subj X0TY = [None] * n_subj X0TDY = [None] * n_subj X0TFY = [None] * n_subj X0 = [None] * n_subj X_res = [None] * n_subj n_X0 = [None] * n_subj idx_DC = [None] * n_subj log_fixed_terms = [None] * n_subj # Initialization for L. # There are several possible ways of initializing the covariance. # (1) start from the point estimation of covariance cov_point_est = np.zeros((n_C, n_C)) for subj in range(n_subj): D[subj], F[subj], run_TRs[subj], n_run[subj] = self._prepare_DF( n_T[subj], scan_onsets=scan_onsets[subj]) XTY[subj], XTDY[subj], XTFY[subj], YTY_diag[subj], \ YTDY_diag[subj], YTFY_diag[subj], XTX[subj], XTDX[subj], \ XTFX[subj] = self._prepare_data_XY( X[subj], Y[subj], D[subj], F[subj]) # The contents above stay fixed during fitting. # Initializing X0 as DC baseline # DC component will be added to the nuisance regressors. # In later steps, we do not need to add DC components again X0TX0[subj], X0TDX0[subj], X0TFX0[subj], XTX0[subj], XTDX0[subj], \ XTFX0[subj], X0TY[subj], X0TDY[subj], X0TFY[subj], X0[subj], \ X_base[subj], n_X0[subj], idx_DC[subj] = \ self._prepare_data_XYX0( X[subj], Y[subj], X_base[subj], None, D[subj], F[subj], run_TRs[subj], no_DC=False) X_joint = np.concatenate((X0[subj], X[subj]), axis=1) beta_hat = np.linalg.lstsq(X_joint, Y[subj], rcond=None)[0] residual = Y[subj] - np.dot(X_joint, beta_hat) # point estimates of betas and fitting residuals without assuming # the Bayesian model underlying RSA. cov_point_est += np.cov(beta_hat[n_X0[subj]:, :] / np.std(residual, axis=0)) log_fixed_terms[subj] = - (n_T[subj] - n_X0[subj]) \ / 2 * np.log(2 * np.pi) + n_run[subj] \ / 2 * np.log(1 - all_rho_grids*2) \ + scipy.special.gammaln( (n_T[subj] - n_X0[subj] - 2) / 2) \ + (n_T[subj] - n_X0[subj] - 2) / 2 np.log(2) # These are terms in the log likelihood that do not # depend on L. Notice that the last term comes from # ther term of marginalizing sigma. We take the 2 in # the denominator out. Accordingly, the "denominator" # variable in the _raw_loglike_grids() function is not # divided by 2 cov_point_est = cov_point_est / n_subj current_vec_U_chlsk_l = np.linalg.cholesky( (cov_point_est + np.eye(n_C)) / 2)[l_idx] # We use the average of covariance of point estimation and an identity # matrix as the initial value of the covariance matrix, just in case # the user provides data in which n_V is smaller than n_C. # (2) start from identity matrix # current_vec_U_chlsk_l = np.eye(n_C)[l_idx] # (3) random initialization # current_vec_U_chlsk_l = self.random_state_.randn(n_l) # vectorized version of L, Cholesky factor of U, the shared # covariance matrix of betas across voxels. L = np.zeros((n_C, rank)) L[l_idx] = current_vec_U_chlsk_l X0TAX0 = [None] * n_subj X0TAX0_i = [None] * n_subj XTAcorrX = [None] * n_subj s2XTAcorrX = [None] * n_subj YTAcorrY_diag = [None] * n_subj XTAcorrY = [None] * n_subj sXTAcorrY = [None] * n_subj X0TAY = [None] * n_subj XTAX0 = [None] * n_subj half_log_det_X0TAX0 = [None] * n_subj s_post = [None] * n_subj rho_post = [None] * n_subj sigma_post = [None] * n_subj beta_post = [None] * n_subj beta0_post = [None] * n_subj # The contents below can be updated during fitting. # e.g., X0 will be re-estimated logger.info('start real fitting') LL = np.zeros(n_subj) for it in range(self.n_iter): logger.info('Iteration {}'.format(it)) # Re-estimate part of X0: X_res for subj in range(n_subj): if self.auto_nuisance and it > 0: residuals = Y[subj] - np.dot(X[subj], beta_post[subj]) \ - np.dot( X_base[subj], beta0_post[subj][:np.shape(X_base[subj])[1], :]) X_res[subj] = self.nureg_method( self.n_nureg_[subj]).fit_transform( self.preprocess_residual(residuals)) X0TX0[subj], X0TDX0[subj], X0TFX0[subj], XTX0[subj],\ XTDX0[subj], XTFX0[subj], X0TY[subj], X0TDY[subj], \ X0TFY[subj], X0[subj], X_base[subj], n_X0[subj], _ = \ self._prepare_data_XYX0( X[subj], Y[subj], X_base[subj], X_res[subj], D[subj], F[subj], run_TRs[subj], no_DC=True) X0TAX0[subj], X0TAX0_i[subj], XTAcorrX[subj], XTAcorrY[subj],\ YTAcorrY_diag[subj], X0TAY[subj], XTAX0[subj] \ = self._precompute_ar1_quad_forms_marginalized( XTY[subj], XTDY[subj], XTFY[subj], YTY_diag[subj], YTDY_diag[subj], YTFY_diag[subj], XTX[subj], XTDX[subj], XTFX[subj], X0TX0[subj], X0TDX0[subj], X0TFX0[subj], XTX0[subj], XTDX0[subj], XTFX0[subj], X0TY[subj], X0TDY[subj], X0TFY[subj], rho_grids, n_V[subj], n_X0[subj]) # Now we expand to another dimension including SNR # and collapse the dimension again. half_log_det_X0TAX0[subj], X0TAX0[subj], X0TAX0_i[subj], \ s2XTAcorrX[subj], YTAcorrY_diag[subj], sXTAcorrY[subj], \ X0TAY[subj], XTAX0[subj] = self._matrix_flattened_grid( X0TAX0[subj], X0TAX0_i[subj], SNR_grids, XTAcorrX[subj], YTAcorrY_diag[subj], XTAcorrY[subj], X0TAY[subj], XTAX0[subj], n_C, n_V[subj], n_X0[subj], n_grid) res = scipy.optimize.minimize( self._sum_loglike_marginalized, current_vec_U_chlsk_l + self.random_state_.randn(n_l) * np.linalg.norm(current_vec_U_chlsk_l) / n_l*0.5 np.exp(-it / self.n_iter * self.anneal_speed - 1), args=(s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, l_idx, n_C, n_T, n_V, n_X0, n_grid, rank), method=self.optimizer, jac=True, tol=self.tol, options=self.minimize_options) param_change = res.x - current_vec_U_chlsk_l current_vec_U_chlsk_l = res.x.copy() # Estimating a few parameters. L[l_idx] = current_vec_U_chlsk_l for subj in range(n_subj): LL_raw, denominator, L_LAMBDA, L_LAMBDA_LT = \ self._raw_loglike_grids( L, s2XTAcorrX[subj], YTAcorrY_diag[subj], sXTAcorrY[subj], half_log_det_X0TAX0[subj], log_weights, log_fixed_terms[subj], n_C, n_T[subj], n_V[subj], n_X0[subj], n_grid, rank) result_sum, max_value, result_exp = utils.sumexp_stable(LL_raw) LL[subj] = np.sum(np.log(result_sum) + max_value) weight_post = result_exp / result_sum s_post[subj] = np.sum(all_SNR_grids[:, None] * weight_post, axis=0) # Mean-posterior estimate of SNR. rho_post[subj] = np.sum(all_rho_grids[:, None] * weight_post, axis=0) # Mean-posterior estimate of rho. sigma_means = denominator ** 0.5 \ * (np.exp(scipy.special.gammaln( (n_T[subj] - n_X0[subj] - 3) / 2) - scipy.special.gammaln( (n_T[subj] - n_X0[subj] - 2) / 2)) / 2*0.5) sigma_post[subj] = np.sum(sigma_means weight_post, axis=0) # The mean of inverse-Gamma distribution is beta/(alpha-1) # The mode is beta/(alpha+1). Notice that beta here does not # refer to the brain activation, but the scale parameter of # inverse-Gamma distribution. In the _UV version, we use the # maximum likelihood estimate of sigma^2. So we divide by # (alpha+1), which is (n_T - n_X0). beta_post[subj] = np.zeros((n_C, n_V[subj])) beta0_post[subj] = np.zeros((n_X0[subj], n_V[subj])) for grid in range(n_grid): beta_post[subj] += np.dot(L_LAMBDA_LT[grid, :, :], sXTAcorrY[subj][grid, :, :])\ * all_SNR_grids[grid] \ * weight_post[grid, :] beta0_post[subj] += weight_post[grid, :] * np.dot( X0TAX0_i[subj][grid, :, :], (X0TAY[subj][grid, :, :] - np.dot(np.dot(XTAX0[subj][grid, :, :].T, L_LAMBDA_LT[grid, :, :]), sXTAcorrY[subj][grid, :, :]) * all_SNR_grids[grid])) if np.max(np.abs(param_change)) < self.tol: logger.info('The change of parameters is smaller than ' 'the tolerance value {}. Fitting is finished ' 'after {} iterations'.format(self.tol, it + 1)) break for subj in range(n_subj): if idx_DC[subj].size > 1: collapsed_DC = np.sum(X0[subj][:, idx_DC[subj]], axis=1) X0[subj] = np.insert(np.delete(X0[subj], idx_DC[subj], axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(beta0_post[subj][idx_DC[subj], :], axis=0) beta0_post[subj] = np.insert( np.delete(beta0_post[subj], idx_DC[subj], axis=0), 0, collapsed_beta0, axis=0) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) return np.dot(L, L.T), L, s_post, \ beta_post, beta0_post, sigma_post, \ rho_post, X0, LL def _fit_RSA_marginalized_null(self, Y, X_base, scan_onsets): """ The marginalized version of the null model for Bayesian RSA. The null model assumes no task-related response to the design matrix. Note that there is a naming change of variable. X in fit() is changed to Y here. This is because we follow the tradition that Y corresponds to data. However, in wrapper function fit(), we follow the naming routine of scikit-learn. """ # Because there is nothing to learn that is shared across # participants, we can run each subject in serial. # The only fitting required is to re-estimate X0 after # each iteration n_subj = len(Y) t_start = time.time() logger.info('Starting to fit the model. Maximum iteration: ' '{}.'.format(self.n_iter)) rho_grids, rho_weights = self._set_rho_grids() logger.info('The grids of rho used to do numerical integration ' 'is {}.'.format(rho_grids)) n_grid = self.rho_bins log_weights = np.log(rho_weights) rho_post = [None] * n_subj sigma_post = [None] * n_subj beta0_post = [None] * n_subj X0 = [None] * n_subj LL_null = np.zeros(n_subj) for subj in range(n_subj): logger.debug('Running on subject {}.'.format(subj)) [n_T, n_V] = np.shape(Y[subj]) D, F, run_TRs, n_run = self._prepare_DF( n_T, scan_onsets=scan_onsets[subj]) YTY_diag = np.sum(Y[subj] * Y[subj], axis=0) YTDY_diag = np.sum(Y[subj] * np.dot(D, Y[subj]), axis=0) YTFY_diag = np.sum(Y[subj] * np.dot(F, Y[subj]), axis=0) # Add DC components capturing run-specific baselines. X_DC = self._gen_X_DC(run_TRs) X_DC, X_base[subj], idx_DC = self._merge_DC_to_base( X_DC, X_base[subj], no_DC=False) X_res = np.empty((n_T, 0)) for it in range(0, self.n_iter): X0[subj] = np.concatenate( (X_base[subj], X_res), axis=1) n_X0 = X0[subj].shape[1] X0TX0, X0TDX0, X0TFX0 = self._make_templates( D, F, X0[subj], X0[subj]) X0TY, X0TDY, X0TFY = self._make_templates( D, F, X0[subj], Y[subj]) YTAY_diag = YTY_diag - rho_grids[:, None] * YTDY_diag \ + rho_grids[:, None]*2 YTFY_diag # dimension: #rhospace, # A/sigma2 is the inverse of noise covariance matrix. # YTAY means Y'AY X0TAX0 = X0TX0[None, :, :] \ - rho_grids[:, None, None] \ X0TDX0[None, :, :] \ + rho_grids[:, None, None]*2 \ X0TFX0[None, :, :] # dimension: #rho#baseline#baseline X0TAY = X0TY - rho_grids[:, None, None] * X0TDY \ + rho_grids[:, None, None]*2 X0TFY # dimension: #rho#baselinespace X0TAX0_i = np.linalg.solve( X0TAX0, np.identity(n_X0)[None, :, :]) # dimension: #rho#baseline#baseline YTAcorrY_diag = np.empty(np.shape(YTAY_diag)) for i_r in range(np.size(rho_grids)): YTAcorrY_diag[i_r, :] = YTAY_diag[i_r, :] \ - np.sum(X0TAY[i_r, :, :] * np.dot( X0TAX0_i[i_r, :, :], X0TAY[i_r, :, :]), axis=0) log_fixed_terms = - (n_T - n_X0) / 2 * np.log(2 * np.pi)\ + n_run / 2 * np.log(1 - rho_grids*2) \ + scipy.special.gammaln((n_T - n_X0 - 2) / 2) \ + (n_T - n_X0 - 2) / 2 np.log(2) # These are terms in the log likelihood that do not # depend on L. Notice that the last term comes from # ther term of marginalizing sigma. We take the 2 in # the denominator out. Accordingly, the "denominator" # variable in the _raw_loglike_grids() function is not # divided by 2 half_log_det_X0TAX0 = self._half_log_det(X0TAX0) LL_raw = -half_log_det_X0TAX0[:, None] \ - (n_T - n_X0 - 2) / 2 * np.log(YTAcorrY_diag) \ + log_weights[:, None] + log_fixed_terms[:, None] # dimension: n_grid * space # The log likelihood at each pair of values of rho1. # half_log_det_X0TAX0 is 0.5log(det(X0TAX0)) with the size of # number of parameter grids. So is the size of log_weights result_sum, max_value, result_exp = utils.sumexp_stable(LL_raw) weight_post = result_exp / result_sum rho_post[subj] = np.sum(rho_grids[:, None] weight_post, axis=0) # Mean-posterior estimate of rho. sigma_means = YTAcorrY_diag ** 0.5 \ * (np.exp(scipy.special.gammaln((n_T - n_X0 - 3) / 2) - scipy.special.gammaln((n_T - n_X0 - 2) / 2)) / 2*0.5) sigma_post[subj] = np.sum(sigma_means weight_post, axis=0) beta0_post[subj] = np.zeros((n_X0, n_V)) for grid in range(n_grid): beta0_post[subj] += weight_post[grid, :] * np.dot( X0TAX0_i[grid, :, :], X0TAY[grid, :, :]) if self.auto_nuisance: residuals = Y[subj] - np.dot( X_base[subj], beta0_post[subj][:np.size(X_base[subj], 1), :]) X_res_new = self.nureg_method( self.n_nureg_[subj]).fit_transform( self.preprocess_residual(residuals)) if it >= 1: if np.max(np.abs(X_res_new - X_res)) <= self.tol: logger.info('The change of X_res is ' 'smaller than the tolerance value {}.' 'Fitting is finished after {} ' 'iterations'.format(self.tol, it + 1)) break X_res = X_res_new if idx_DC.size > 1: collapsed_DC = np.sum(X0[subj][:, idx_DC], axis=1) X0[subj] = np.insert(np.delete(X0[subj], idx_DC, axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(beta0_post[subj][idx_DC, :], axis=0) beta0_post[subj] = np.insert( np.delete(beta0_post[subj], idx_DC, axis=0), 0, collapsed_beta0, axis=0) LL_null[subj] = np.sum(np.log(result_sum) + max_value) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) return beta0_post, sigma_post, rho_post, X0, LL_null def _raw_loglike_grids(self, L, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, n_C, n_T, n_V, n_X0, n_grid, rank): # LAMBDA_i = np.dot(np.einsum('ijk,jl->ilk', s2XTAcorrX, L), L) \ # + np.identity(rank) LAMBDA_i = np.empty((n_grid, rank, rank)) for grid in np.arange(n_grid): LAMBDA_i[grid, :, :] = np.dot(np.dot(L.T, s2XTAcorrX[grid, :, :]), L) LAMBDA_i += np.identity(rank) # dimension: n_grid * rank * rank Chol_LAMBDA_i = np.linalg.cholesky(LAMBDA_i) # dimension: n_grid * rank * rank half_log_det_LAMBDA_i = np.sum( np.log(np.abs(np.diagonal(Chol_LAMBDA_i, axis1=1, axis2=2))), axis=1) # dimension: n_grid L_LAMBDA = np.empty((n_grid, n_C, rank)) L_LAMBDA_LT = np.empty((n_grid, n_C, n_C)) s2YTAcorrXL_LAMBDA_LTXTAcorrY = np.empty((n_grid, n_V)) # dimension: space * n_grid for grid in np.arange(n_grid): L_LAMBDA[grid, :, :] = scipy.linalg.cho_solve( (Chol_LAMBDA_i[grid, :, :], True), L.T).T L_LAMBDA_LT[grid, :, :] = np.dot(L_LAMBDA[grid, :, :], L.T) s2YTAcorrXL_LAMBDA_LTXTAcorrY[grid, :] = np.sum( sXTAcorrY[grid, :, :] * np.dot(L_LAMBDA_LT[grid, :, :], sXTAcorrY[grid, :, :]), axis=0) denominator = (YTAcorrY_diag - s2YTAcorrXL_LAMBDA_LTXTAcorrY) # dimension: n_grid * space # Not necessary the best name for it. But this term appears # as the denominator within the gradient wrt L # In the equation of the log likelihood, this "denominator" # term is in fact divided by 2. But we absorb that into the # log fixted term. LL_raw = -half_log_det_X0TAX0[:, None] \ - half_log_det_LAMBDA_i[:, None] \ - (n_T - n_X0 - 2) / 2 * np.log(denominator) \ + log_weights[:, None] + log_fixed_terms[:, None] # dimension: n_grid * space # The log likelihood at each pair of values of SNR and rho1. # half_log_det_X0TAX0 is 0.5log(det(X0TAX0)) with the size of # number of parameter grids. So is the size of log_weights return LL_raw, denominator, L_LAMBDA, L_LAMBDA_LT def _sum_loglike_marginalized(self, L_vec, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, l_idx, n_C, n_T, n_V, n_X0, n_grid, rank=None): sum_LL_total = 0 sum_grad_L = np.zeros(np.size(l_idx[0])) for subj in range(len(YTAcorrY_diag)): LL_total, grad_L = self._loglike_marginalized( L_vec, s2XTAcorrX[subj], YTAcorrY_diag[subj], sXTAcorrY[subj], half_log_det_X0TAX0[subj], log_weights, log_fixed_terms[subj], l_idx, n_C, n_T[subj], n_V[subj], n_X0[subj], n_grid, rank) sum_LL_total += LL_total sum_grad_L += grad_L return sum_LL_total, sum_grad_L def _loglike_marginalized(self, L_vec, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, l_idx, n_C, n_T, n_V, n_X0, n_grid, rank=None): # In this version, we assume that beta is independent # between voxels and noise is also independent. X0 captures the # co-flucturation between voxels that is # not captured by design matrix X. # marginalized version marginalize sigma^2, s and rho1 # for all voxels. n_grid is the number of grid on which the numeric # integration is performed to marginalize s and rho1 for each voxel. # The log likelihood is an inverse-Gamma distribution sigma^2, # so we can analytically marginalize it assuming uniform prior. # n_grid is the number of grid in the parameter space of (s, rho1) # that is used for numerical integration over (s, rho1). n_l = np.size(l_idx[0]) # the number of parameters in the index of lower-triangular matrix if rank is None: rank = int((2 n_C + 1 - np.sqrt(n_C*2 4 + n_C * 4 + 1 - 8 * n_l)) / 2) L = np.zeros([n_C, rank]) L[l_idx] = L_vec LL_raw, denominator, L_LAMBDA, _ = self._raw_loglike_grids( L, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, n_C, n_T, n_V, n_X0, n_grid, rank) result_sum, max_value, result_exp = utils.sumexp_stable(LL_raw) LL_total = np.sum(np.log(result_sum) + max_value) # Now we start the gradient with respect to L # s2XTAcorrXL_LAMBDA = np.einsum('ijk,ikl->ijl', # s2XTAcorrX, L_LAMBDA) s2XTAcorrXL_LAMBDA = np.empty((n_grid, n_C, rank)) for grid in range(n_grid): s2XTAcorrXL_LAMBDA[grid, :, :] = np.dot(s2XTAcorrX[grid, :, :], L_LAMBDA[grid, :, :]) # dimension: n_grid * condition * rank I_minus_s2XTAcorrXL_LAMBDA_LT = np.identity(n_C) \ - np.dot(s2XTAcorrXL_LAMBDA, L.T) # dimension: n_grid * condition * condition # The step above may be calculated by einsum. Not sure # which is faster. weight_grad = result_exp / result_sum weight_grad_over_denominator = weight_grad / denominator # dimension: n_grid * space weighted_sXTAcorrY = sXTAcorrY \ * weight_grad_over_denominator[:, None, :] # dimension: n_grid * condition * space # sYTAcorrXL_LAMBDA = np.einsum('ijk,ijl->ikl', sXTAcorrY, L_LAMBDA) # dimension: n_grid * space * rank grad_L = np.zeros([n_C, rank]) for grid in range(n_grid): grad_L += np.dot( np.dot(I_minus_s2XTAcorrXL_LAMBDA_LT[grid, :, :], sXTAcorrY[grid, :, :]), np.dot(weighted_sXTAcorrY[grid, :, :].T, L_LAMBDA[grid, :, :])) * (n_T - n_X0 - 2) grad_L -= np.sum(s2XTAcorrXL_LAMBDA * np.sum(weight_grad, axis=1)[:, None, None], axis=0) # dimension: condition * rank return -LL_total, -grad_L[l_idx] def _check_data_GBRSA(self, X, for_fit=True): # Check input data if type(X) is np.ndarray: X = [X] assert type(X) is list, 'Input data X must be either a list '\ 'with each entry for one participant, or a numpy arrary '\ 'for single participant.' if for_fit: for i, x in enumerate(X): assert_all_finite(x) assert x.ndim == 2, 'Each participants'' data should be ' \ '2 dimension ndarray' assert np.all(np.std(x, axis=0) > 0),\ 'The time courses of some voxels in participant {} '\ 'do not change at all. Please make sure all voxels '\ 'are within the brain'.format(i) else: for i, x in enumerate(X): if x is not None: assert x.ndim == 2, 'Each participants'' data should be ' \ '2 dimension ndarray' assert x.shape[1] == self.n_V_[i], 'Number of voxels '\ 'does not match that in the data used for fitting: '\ 'subject {}'.format(i) # This program allows to fit a single subject. But to have a consistent # data structure, we make sure X and design are both lists. return X def _check_design_GBRSA(self, design, X): # check design matrix if type(design) is np.ndarray: design = [design] * len(X) if len(X) > 1: logger.warning('There are multiple subjects while ' 'there is only one design matrix. ' 'I assume that the design matrix ' 'is shared across all subjects.') assert type(design) is list, 'design matrix must be either a list '\ 'with each entry for one participant, or an numpy arrary '\ 'for single participant.' for i, d in enumerate(design): if X[i] is not None: assert_all_finite(d) assert d.ndim == 2,\ 'The design matrix should be 2 dimension ndarray' assert np.linalg.matrix_rank(d) == d.shape[1], \ 'Your design matrix of subject {} has rank ' \ 'smaller than the number of columns. Some columns '\ 'can be explained by linear combination of other columns.'\ 'Please check your design matrix.'.format(i) assert np.size(d, axis=0) == np.size(X[i], axis=0),\ 'Design matrix and data of subject {} do not '\ 'have the same number of time points.'.format(i) assert self.rank is None or self.rank <= d.shape[1],\ 'Your design matrix of subject {} '\ 'has fewer columns than the rank you set'.format(i) if i == 0: n_C = np.shape(d)[1] else: assert n_C == np.shape(d)[1], \ 'In Group Bayesian RSA, all subjects should have'\ ' the same set of experiment conditions, t'\ 'hus the same number of columns in design matrix' if X[i].shape[1] <= d.shape[1]: logger.warning('Your data have fewer voxels than the ' 'number of task conditions. This might ' 'cause problem in fitting. Please consider ' 'increasing the size of your ROI, or set ' 'the rank parameter to a lower number to ' 'estimate a low-rank representational ' 'structure.') return design def _check_nuisance_GBRSA(sef, nuisance, X): # Check the nuisance regressors. if nuisance is not None: if type(nuisance) is np.ndarray: nuisance = [nuisance] * len(X) if len(X) > 1: logger.warning('ATTENTION! There are multiple subjects ' 'while there is only one nuisance matrix. ' 'I assume that the nuisance matrix ' 'is shared across all subjects. ' 'Please double check.') assert type(nuisance) is list, \ 'nuisance matrix must be either a list '\ 'with each entry for one participant, or an numpy arrary '\ 'for single participant.' for i, n in enumerate(nuisance): assert_all_finite(n) if n is not None: assert n.ndim == 2,\ 'The nuisance regressor should be '\ '2 dimension ndarray or None' assert np.linalg.matrix_rank(n) == n.shape[1], \ 'The nuisance regressor of subject {} has rank '\ 'smaller than the number of columns.'\ 'Some columns can be explained by linear '\ 'combination of other columns. Please check your' \ ' nuisance regressors.'.format(i) assert np.size(n, axis=0) == np.size(X[i], axis=0), \ 'Nuisance regressor and data do not have the same '\ 'number of time points.' else: nuisance = [None] * len(X) logger.info('None was provided for nuisance matrix. Replicating ' 'it for all subjects.') return nuisance def _check_scan_onsets_GBRSA(self, scan_onsets, X): # check scan_onsets validity if scan_onsets is None or type(scan_onsets) is np.ndarray: if scan_onsets is None: scan_onsets = np.array([0], dtype=int) scan_onsets = [scan_onsets] * len(X) if len(X) > 1: logger.warning('There are multiple subjects while ' 'there is only one set of scan_onsets. ' 'I assume that it is the same for all' ' subjects. Please double check') for i in np.arange(len(scan_onsets)): if X[i] is not None: if scan_onsets[i] is None: scan_onsets[i] = np.array([0], dtype=int) logger.warning('No scan onsets were provided for subject' ' {}. Treating all data of this subject as' ' coming from the same run.') else: scan_onsets[i] = np.int32(scan_onsets[i]) assert (np.max(scan_onsets[i]) <= X[i].shape[0] and np.min(scan_onsets[i]) >= 0 and 0 in scan_onsets[i] and scan_onsets[i].ndim == 1), \ 'Scan onsets of subject {} has formatting ' \ 'issues: {}'.format(i, scan_onsets[i]) return scan_onsets def _bin_exp(self, n_bin, scale=1.0): """ Calculate the bin locations to approximate exponential distribution. It breaks the cumulative probability of exponential distribution into n_bin equal bins, each covering 1 / n_bin probability. Then it calculates the center of mass in each bins and returns the centers of mass. So, it approximates the exponential distribution with n_bin of Delta function weighted by 1 / n_bin, at the locations of these centers of mass. Parameters: ----------- n_bin: int The number of bins to approximate the exponential distribution scale: float. The scale parameter of the exponential distribution, defined in the same way as scipy.stats. It does not influence the ratios between the bins, but just controls the spacing between the bins. So generally users should not change its default. Returns: -------- bins: numpy array of size [n_bin,] The centers of mass for each segment of the exponential distribution. """ boundaries = np.flip(scipy.stats.expon.isf( np.linspace(0, 1, n_bin + 1), scale=scale), axis=0) bins = np.empty(n_bin) for i in np.arange(n_bin): bins[i] = utils.center_mass_exp( (boundaries[i], boundaries[i + 1]), scale=scale) return bins def _set_SNR_grids(self): """ Set the grids and weights for SNR used in numerical integration of SNR parameters. """ if self.SNR_prior == 'unif': SNR_grids = np.linspace(0, 1, self.SNR_bins) SNR_weights = np.ones(self.SNR_bins) / (self.SNR_bins - 1) SNR_weights[0] = SNR_weights[0] / 2.0 SNR_weights[-1] = SNR_weights[-1] / 2.0 elif self.SNR_prior == 'lognorm': dist = scipy.stats.lognorm alphas = np.arange(np.mod(self.SNR_bins, 2), self.SNR_bins + 2, 2) / self.SNR_bins # The goal here is to divide the area under the pdf curve # to segments representing equal probabilities. bounds = dist.interval(alphas, (self.logS_range,)) bounds = np.unique(bounds) # bounds contain the boundaries which equally separate # the probability mass of the distribution SNR_grids = np.zeros(self.SNR_bins) for i in np.arange(self.SNR_bins): SNR_grids[i] = dist.expect( lambda x: x, args=(self.logS_range,), lb=bounds[i], ub=bounds[i + 1]) * self.SNR_bins # Center of mass of each segment between consecutive # bounds are set as the grids for SNR. SNR_weights = np.ones(self.SNR_bins) / self.SNR_bins elif self.SNR_prior == 'exp': SNR_grids = self._bin_exp(self.SNR_bins) SNR_weights = np.ones(self.SNR_bins) / self.SNR_bins else: SNR_grids = np.ones(1) SNR_weights = np.ones(1) SNR_weights = SNR_weights / np.sum(SNR_weights) return SNR_grids, SNR_weights def _set_rho_grids(self): """ Set the grids and weights for rho used in numerical integration of AR(1) parameters. """ rho_grids = np.arange(self.rho_bins) * 2 / self.rho_bins - 1 \ + 1 / self.rho_bins rho_weights = np.ones(self.rho_bins) / self.rho_bins return rho_grids, rho_weights def _matrix_flattened_grid(self, X0TAX0, X0TAX0_i, SNR_grids, XTAcorrX, YTAcorrY_diag, XTAcorrY, X0TAY, XTAX0, n_C, n_V, n_X0, n_grid): """ We need to integrate parameters SNR and rho on 2-d discrete grids. This function generates matrices which have only one dimension for these two parameters, with each slice in that dimension corresponding to each combination of the discrete grids of SNR and discrete grids of rho. """ half_log_det_X0TAX0 = np.reshape( np.repeat(self._half_log_det(X0TAX0)[None, :], self.SNR_bins, axis=0), n_grid) X0TAX0 = np.reshape( np.repeat(X0TAX0[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_X0, n_X0)) X0TAX0_i = np.reshape(np.repeat( X0TAX0_i[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_X0, n_X0)) s2XTAcorrX = np.reshape( SNR_grids[:, None, None, None]*2 XTAcorrX, (n_grid, n_C, n_C)) YTAcorrY_diag = np.reshape(np.repeat( YTAcorrY_diag[None, :, :], self.SNR_bins, axis=0), (n_grid, n_V)) sXTAcorrY = np.reshape(SNR_grids[:, None, None, None] * XTAcorrY, (n_grid, n_C, n_V)) X0TAY = np.reshape(np.repeat(X0TAY[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_X0, n_V)) XTAX0 = np.reshape(np.repeat(XTAX0[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_C, n_X0)) return half_log_det_X0TAX0, X0TAX0, X0TAX0_i, s2XTAcorrX, \ YTAcorrY_diag, sXTAcorrY, X0TAY, XTAX0	lcnature/brainiak	brainiak/reprsimil/brsa.py	Python	apache-2.0	211,992	[ "Gaussian" ]	cd84a148f8270fb7a16c3150d7e0990c60922e2e55f0e7b09b4275ecb5b0bf42
class Display: def visit(self, state_machine): states = state_machine.states for state in states.values(): print "state: ", state.name for transition in state.transitions_out.values(): print " transition: ", transition.name, " attributes: ", for attribute_or_group in transition.attributes: print attribute_or_group.name, print	bwtaylor/statemach	visitors/display.py	Python	apache-2.0	392	[ "VisIt" ]	3890a196fc331e38d203619589ea33107eb5ae415f5eb88769a9189946aa9104
# $Id$ # # Copyright (C) 2003 Rational Discovery LLC # All Rights Reserved # from rdkit import six from rdkit.VLib.Node import VLibNode class SupplyNode(VLibNode): """ base class for nodes which supply things Assumptions: 1) no parents Usage Example: >>> supplier = SupplyNode(contents=[1,2,3]) >>> supplier.next() 1 >>> supplier.next() 2 >>> supplier.next() 3 >>> supplier.next() Traceback (most recent call last): ... StopIteration >>> supplier.reset() >>> supplier.next() 1 >>> [x for x in supplier] [1, 2, 3] """ def __init__(self, contents=None, kwargs): VLibNode.__init__(self, kwargs) if contents is not None: self._contents = contents else: self._contents = [] self._pos = 0 def reset(self): VLibNode.reset(self) self._pos = 0 def next(self): if self._pos == len(self._contents): raise StopIteration res = self._contents[self._pos] self._pos += 1 return res def AddParent(self, parent, notify=1): raise ValueError('SupplyNodes do not have parents') if six.PY3: SupplyNode.__next__ = SupplyNode.next # ------------------------------------ # # doctest boilerplate # def _runDoctests(verbose=None): # pragma: nocover import sys import doctest failed, _ = doctest.testmod(optionflags=doctest.ELLIPSIS, verbose=verbose) sys.exit(failed) if __name__ == '__main__': # pragma: nocover _runDoctests()	rvianello/rdkit	rdkit/VLib/Supply.py	Python	bsd-3-clause	1,492	[ "RDKit" ]	23af8f1b73244f7ed97781cf1ba0d7f295dd09e7355e900042556e92d6cb4d16
import os import sys import time import socket import inspect import traceback import pickle import uuid from GangaCore.Runtime.GPIexport import exportToGPI from GangaCore.GPIDev.Base.Proxy import addProxy, stripProxy from GangaCore.Utility.Config import getConfig from GangaCore.Utility.logging import getLogger #from GangaCore.Core.GangaThread.WorkerThreads.WorkerThreadPool import WorkerThreadPool #from GangaCore.Core.GangaThread.WorkerThreads.ThreadPoolQueueMonitor import ThreadPoolQueueMonitor from GangaDirac.Lib.Utilities.DiracUtilities import execute logger = getLogger() #user_threadpool = WorkerThreadPool() #monitoring_threadpool = WorkerThreadPool() #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def diracAPI(cmd, timeout=60, cred_req=None): ''' Args: cmd (str): This is the command you want to execute from within an active DIRAC session timeout (int): This is the maximum time(sec) the session has to complete the task cred_req (ICredentialRequirement): This is the (optional) credential passed to construct the correct DIRAC env Execute DIRAC API commands from w/in GangaCore. The stdout will be returned, e.g.: # this will simply return 87 diracAPI(\'print 87\') # this will return the status of job 66 # note a Dirac() object is already provided set up as \'dirac\' diracAPI(\'print(Dirac().getJobStatus([66]))\') diracAPI(\'print(dirac.getJobStatus([66]))\') # or can achieve the same using command defined and included from # getConfig('DIRAC')['DiracCommandFiles'] diracAPI(\'status([66])\') ''' return execute(cmd, timeout=timeout, cred_req=cred_req) exportToGPI('diracAPI', diracAPI, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# running_dirac_process = False dirac_process = None dirac_process_ids = None def startDiracProcess(): ''' Start a subprocess that runs the DIRAC commands ''' HOST = 'localhost' #Connect to localhost end_trans = '###END-TRANS###' import subprocess from GangaDirac.Lib.Utilities.DiracUtilities import getDiracEnv, getDiracCommandIncludes, GangaDiracError global dirac_process #Some magic to locate the python script to run from GangaDirac.Lib.Server.InspectionClient import runClient #Create a socket and bind it to 0 to find a free port s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.bind((HOST, 0)) PORT = s.getsockname()[1] s.close() #Pass the port no as an argument to the popen serverpath = os.path.join(os.path.dirname(inspect.getsourcefile(runClient)), 'DiracProcess.py') popen_cmd = ['python',serverpath, str(PORT)] dirac_process = subprocess.Popen(popen_cmd, env = getDiracEnv(), stdin=subprocess.PIPE) global running_dirac_process running_dirac_process = (dirac_process.pid, PORT) #Now set a random string to make sure only commands from this sessions are executed rand_hash = uuid.uuid4() global dirac_process_ids dirac_process_ids = (dirac_process.pid, PORT, rand_hash) #Pipe the random string without waiting for the process to finish. dirac_process.stdin.write(str(rand_hash).encode("utf-8")) dirac_process.stdin.close() data = '' #We have to wait a little bit for the subprocess to start the server so we try until the connection stops being refused. Set a limit of one minute. connection_timeout = time.time() + 60 started = False s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) while time.time()<connection_timeout and not started: try: s.connect((HOST, PORT)) started = True except socket.error as serr: time.sleep(1) if not started: raise GangaDiracError("Failed to start the Dirac server process!") #Now setup the Dirac environment in the subprocess dirac_command = str(rand_hash) dirac_command = dirac_command + getDiracCommandIncludes() dirac_command = dirac_command + end_trans s.sendall(dirac_command.encode("utf-8")) data = s.recv(1024) s.close() exportToGPI('startDiracProcess', startDiracProcess, 'Functions') def stopDiracProcess(): ''' Stop the Dirac process if it is running ''' global running_dirac_process if running_dirac_process: logger.info('Stopping the DIRAC process') dirac_process.kill() running_dirac_process = False exportToGPI('stopDiracProcess', stopDiracProcess, 'Functions') def diracAPI_interactive(connection_attempts=5): ''' Run an interactive server within the DIRAC environment. ''' from GangaDirac.Lib.Server.InspectionClient import runClient serverpath = os.path.join(os.path.dirname(inspect.getsourcefile(runClient)), 'InspectionServer.py') from GangaCore.Core.GangaThread.WorkerThreads import getQueues getQueues().add(execute("execfile('%s')" % serverpath, timeout=None, shell=False)) #time.sleep(1) sys.stdout.write( "\nType 'q' or 'Q' or 'exit' or 'exit()' to quit but NOT ctrl-D") i = 0 excpt = None while i < connection_attempts: try: runClient() break except: if i == (connection_attempts - 1): excpt = traceback.format_exc() finally: i += 1 return excpt exportToGPI('diracAPI_interactive', diracAPI_interactive, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def diracAPI_async(cmd, timeout=120): ''' Execute DIRAC API commands from w/in GangaCore. ''' from GangaCore.Core.GangaThread.WorkerThreads import getQueues return getQueues().add(execute(cmd, timeout=timeout)) exportToGPI('diracAPI_async', diracAPI_async, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def getDiracFiles(): from GangaDirac.Lib.Files.DiracFile import DiracFile from GangaCore.GPIDev.Lib.GangaList.GangaList import GangaList filename = DiracFile.diracLFNBase().replace('/', '-') + '.lfns' logger.info('Creating list, this can take a while if you have a large number of SE files, please wait...') execute('dirac-dms-user-lfns &> /dev/null', shell=True, timeout=None) g = GangaList() with open(filename[1:], 'r') as lfnlist: lfnlist.seek(0) g.extend((DiracFile(lfn='%s' % lfn.strip()) for lfn in lfnlist.readlines())) return addProxy(g) exportToGPI('getDiracFiles', getDiracFiles, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def dumpObject(object, filename): ''' These are complimentary functions to export/load which are already exported to the GPI from GangaCore.GPIDev.Persistency. The difference being that these functions will export the objects using the pickle persistency format rather than a Ganga streaming (human readable) format. ''' try: with open(os.path.expandvars(os.path.expanduser(filename)), 'wb') as f: pickle.dump(stripProxy(object), f) except: logger.error("Problem when dumping file '%s': %s" % (filename, traceback.format_exc())) exportToGPI('dumpObject', dumpObject, 'Functions') def loadObject(filename): ''' These are complimentary functions to export/load which are already exported to the GPI from GangaCore.GPIDev.Persistency. The difference being that these functions will export the objects using the pickle persistency format rather than a Ganga streaming (human readable) format. ''' try: with open(os.path.expandvars(os.path.expanduser(filename)), 'rb') as f: r = pickle.load(f) except: logger.error("Problem when loading file '%s': %s" % (filename, traceback.format_exc())) else: return addProxy(r) exportToGPI('loadObject', loadObject, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/#	ganga-devs/ganga	ganga/GangaDirac/BOOT.py	Python	gpl-3.0	7,982	[ "DIRAC" ]	1fdbc43fc2a4acec244fdc965c9779737728eb093d37a84b3d9ef6e741e02be0
""" NetCDF reader/writer module. This module is used to read and create NetCDF files. NetCDF files are accessed through the `netcdf_file` object. Data written to and from NetCDF files are contained in `netcdf_variable` objects. Attributes are given as member variables of the `netcdf_file` and `netcdf_variable` objects. Notes ----- NetCDF files are a self-describing binary data format. The file contains metadata that describes the dimensions and variables in the file. More details about NetCDF files can be found `here <http://www.unidata.ucar.edu/software/netcdf/docs/netcdf.html>`_. There are three main sections to a NetCDF data structure: 1. Dimensions 2. Variables 3. Attributes The dimensions section records the name and length of each dimension used by the variables. The variables would then indicate which dimensions it uses and any attributes such as data units, along with containing the data values for the variable. It is good practice to include a variable that is the same name as a dimension to provide the values for that axes. Lastly, the attributes section would contain additional information such as the name of the file creator or the instrument used to collect the data. When writing data to a NetCDF file, there is often the need to indicate the 'record dimension'. A record dimension is the unbounded dimension for a variable. For example, a temperature variable may have dimensions of latitude, longitude and time. If one wants to add more temperature data to the NetCDF file as time progresses, then the temperature variable should have the time dimension flagged as the record dimension. This module implements the Scientific.IO.NetCDF API to read and create NetCDF files. The same API is also used in the PyNIO and pynetcdf modules, allowing these modules to be used interchangeably when working with NetCDF files. The major advantage of this module over other modules is that it doesn't require the code to be linked to the NetCDF libraries. In addition, the NetCDF file header contains the position of the data in the file, so access can be done in an efficient manner without loading unnecessary data into memory. It uses the ``mmap`` module to create Numpy arrays mapped to the data on disk, for the same purpose. Examples -------- To create a NetCDF file: >>> from scipy.io import netcdf >>> f = netcdf.netcdf_file('simple.nc', 'w') >>> f.history = 'Created for a test' >>> f.createDimension('time', 10) >>> time = f.createVariable('time', 'i', ('time',)) >>> time[:] = range(10) >>> time.units = 'days since 2008-01-01' >>> f.close() Note the assignment of ``range(10)`` to ``time[:]``. Exposing the slice of the time variable allows for the data to be set in the object, rather than letting ``range(10)`` overwrite the ``time`` variable. To read the NetCDF file we just created: >>> from scipy.io import netcdf >>> f = netcdf.netcdf_file('simple.nc', 'r') >>> print f.history Created for a test >>> time = f.variables['time'] >>> print time.units days since 2008-01-01 >>> print time.shape (10,) >>> print time[-1] 9 >>> f.close() """ #TODO: # * properly implement ``_FillValue``. # * implement Jeff Whitaker's patch for masked variables. # * fix character variables. # * implement PAGESIZE for Python 2.6? #The Scientific.IO.NetCDF API allows attributes to be added directly to #instances of ``netcdf_file`` and ``netcdf_variable``. To differentiate #between user-set attributes and instance attributes, user-set attributes #are automatically stored in the ``_attributes`` attribute by overloading #``__setattr__``. This is the reason why the code sometimes uses #``obj.__dict__['key'] = value``, instead of simply ``obj.key = value``; #otherwise the key would be inserted into userspace attributes. __all__ = ['netcdf_file', 'netcdf_variable'] from operator import mul from mmap import mmap, ACCESS_READ import numpy as np from numpy.compat import asbytes, asstr from numpy import fromstring, ndarray, dtype, empty, array, asarray from numpy import little_endian as LITTLE_ENDIAN ABSENT = asbytes('\x00\x00\x00\x00\x00\x00\x00\x00') ZERO = asbytes('\x00\x00\x00\x00') NC_BYTE = asbytes('\x00\x00\x00\x01') NC_CHAR = asbytes('\x00\x00\x00\x02') NC_SHORT = asbytes('\x00\x00\x00\x03') NC_INT = asbytes('\x00\x00\x00\x04') NC_FLOAT = asbytes('\x00\x00\x00\x05') NC_DOUBLE = asbytes('\x00\x00\x00\x06') NC_DIMENSION = asbytes('\x00\x00\x00\n') NC_VARIABLE = asbytes('\x00\x00\x00\x0b') NC_ATTRIBUTE = asbytes('\x00\x00\x00\x0c') TYPEMAP = { NC_BYTE: ('b', 1), NC_CHAR: ('c', 1), NC_SHORT: ('h', 2), NC_INT: ('i', 4), NC_FLOAT: ('f', 4), NC_DOUBLE: ('d', 8) } REVERSE = { 'b': NC_BYTE, 'c': NC_CHAR, 'h': NC_SHORT, 'i': NC_INT, 'f': NC_FLOAT, 'd': NC_DOUBLE, # these come from asarray(1).dtype.char and asarray('foo').dtype.char, # used when getting the types from generic attributes. 'l': NC_INT, 'S': NC_CHAR } class netcdf_file(object): """ A file object for NetCDF data. A `netcdf_file` object has two standard attributes: `dimensions` and `variables`. The values of both are dictionaries, mapping dimension names to their associated lengths and variable names to variables, respectively. Application programs should never modify these dictionaries. All other attributes correspond to global attributes defined in the NetCDF file. Global file attributes are created by assigning to an attribute of the `netcdf_file` object. Parameters ---------- filename : string or file-like string -> filename mode : {'r', 'w'}, optional read-write mode, default is 'r' mmap : None or bool, optional Whether to mmap `filename` when reading. Default is True when `filename` is a file name, False when `filename` is a file-like object version : {1, 2}, optional version of netcdf to read / write, where 1 means Classic format and 2 means 64-bit offset format. Default is 1. See `here <http://www.unidata.ucar.edu/software/netcdf/docs/netcdf/Which-Format.html>`_ for more info. """ def __init__(self, filename, mode='r', mmap=None, version=1): """Initialize netcdf_file from fileobj (str or file-like).""" if hasattr(filename, 'seek'): # file-like self.fp = filename self.filename = 'None' if mmap is None: mmap = False elif mmap and not hasattr(filename, 'fileno'): raise ValueError('Cannot use file object for mmap') else: # maybe it's a string self.filename = filename self.fp = open(self.filename, '%sb' % mode) if mmap is None: mmap = True self.use_mmap = mmap self.version_byte = version if not mode in 'rw': raise ValueError("Mode must be either 'r' or 'w'.") self.mode = mode self.dimensions = {} self.variables = {} self._dims = [] self._recs = 0 self._recsize = 0 self._attributes = {} if mode == 'r': self._read() def __setattr__(self, attr, value): # Store user defined attributes in a separate dict, # so we can save them to file later. try: self._attributes[attr] = value except AttributeError: pass self.__dict__[attr] = value def close(self): """Closes the NetCDF file.""" if not self.fp.closed: try: self.flush() finally: self.fp.close() __del__ = close def createDimension(self, name, length): """ Adds a dimension to the Dimension section of the NetCDF data structure. Note that this function merely adds a new dimension that the variables can reference. The values for the dimension, if desired, should be added as a variable using `createVariable`, referring to this dimension. Parameters ---------- name : str Name of the dimension (Eg, 'lat' or 'time'). length : int Length of the dimension. See Also -------- createVariable """ self.dimensions[name] = length self._dims.append(name) def createVariable(self, name, type, dimensions): """ Create an empty variable for the `netcdf_file` object, specifying its data type and the dimensions it uses. Parameters ---------- name : str Name of the new variable. type : dtype or str Data type of the variable. dimensions : sequence of str List of the dimension names used by the variable, in the desired order. Returns ------- variable : netcdf_variable The newly created ``netcdf_variable`` object. This object has also been added to the `netcdf_file` object as well. See Also -------- createDimension Notes ----- Any dimensions to be used by the variable should already exist in the NetCDF data structure or should be created by `createDimension` prior to creating the NetCDF variable. """ shape = tuple([self.dimensions[dim] for dim in dimensions]) shape_ = tuple([dim or 0 for dim in shape]) # replace None with 0 for numpy if isinstance(type, basestring): type = dtype(type) typecode, size = type.char, type.itemsize dtype_ = '>%s' % typecode if size > 1: dtype_ += str(size) data = empty(shape_, dtype=dtype_) self.variables[name] = netcdf_variable(data, typecode, shape, dimensions) return self.variables[name] def flush(self): """ Perform a sync-to-disk flush if the `netcdf_file` object is in write mode. See Also -------- sync : Identical function """ if hasattr(self, 'mode') and self.mode is 'w': self._write() sync = flush def _write(self): self.fp.write(asbytes('CDF')) self.fp.write(array(self.version_byte, '>b').tostring()) # Write headers and data. self._write_numrecs() self._write_dim_array() self._write_gatt_array() self._write_var_array() def _write_numrecs(self): # Get highest record count from all record variables. for var in self.variables.values(): if var.isrec and len(var.data) > self._recs: self.__dict__['_recs'] = len(var.data) self._pack_int(self._recs) def _write_dim_array(self): if self.dimensions: self.fp.write(NC_DIMENSION) self._pack_int(len(self.dimensions)) for name in self._dims: self._pack_string(name) length = self.dimensions[name] self._pack_int(length or 0) # replace None with 0 for record dimension else: self.fp.write(ABSENT) def _write_gatt_array(self): self._write_att_array(self._attributes) def _write_att_array(self, attributes): if attributes: self.fp.write(NC_ATTRIBUTE) self._pack_int(len(attributes)) for name, values in attributes.items(): self._pack_string(name) self._write_values(values) else: self.fp.write(ABSENT) def _write_var_array(self): if self.variables: self.fp.write(NC_VARIABLE) self._pack_int(len(self.variables)) # Sort variables non-recs first, then recs. We use a DSU # since some people use pupynere with Python 2.3.x. deco = [ (v._shape and not v.isrec, k) for (k, v) in self.variables.items() ] deco.sort() variables = [ k for (unused, k) in deco ][::-1] # Set the metadata for all variables. for name in variables: self._write_var_metadata(name) # Now that we have the metadata, we know the vsize of # each record variable, so we can calculate recsize. self.__dict__['_recsize'] = sum([ var._vsize for var in self.variables.values() if var.isrec]) # Set the data for all variables. for name in variables: self._write_var_data(name) else: self.fp.write(ABSENT) def _write_var_metadata(self, name): var = self.variables[name] self._pack_string(name) self._pack_int(len(var.dimensions)) for dimname in var.dimensions: dimid = self._dims.index(dimname) self._pack_int(dimid) self._write_att_array(var._attributes) nc_type = REVERSE[var.typecode()] self.fp.write(asbytes(nc_type)) if not var.isrec: vsize = var.data.size * var.data.itemsize vsize += -vsize % 4 else: # record variable try: vsize = var.data[0].size * var.data.itemsize except IndexError: vsize = 0 rec_vars = len([var for var in self.variables.values() if var.isrec]) if rec_vars > 1: vsize += -vsize % 4 self.variables[name].__dict__['_vsize'] = vsize self._pack_int(vsize) # Pack a bogus begin, and set the real value later. self.variables[name].__dict__['_begin'] = self.fp.tell() self._pack_begin(0) def _write_var_data(self, name): var = self.variables[name] # Set begin in file header. the_beguine = self.fp.tell() self.fp.seek(var._begin) self._pack_begin(the_beguine) self.fp.seek(the_beguine) # Write data. if not var.isrec: self.fp.write(var.data.tostring()) count = var.data.size * var.data.itemsize self.fp.write(asbytes('0') * (var._vsize - count)) else: # record variable # Handle rec vars with shape[0] < nrecs. if self._recs > len(var.data): shape = (self._recs,) + var.data.shape[1:] var.data.resize(shape) pos0 = pos = self.fp.tell() for rec in var.data: # Apparently scalars cannot be converted to big endian. If we # try to convert a ``=i4`` scalar to, say, '>i4' the dtype # will remain as ``=i4``. if not rec.shape and (rec.dtype.byteorder == '<' or (rec.dtype.byteorder == '=' and LITTLE_ENDIAN)): rec = rec.byteswap() self.fp.write(rec.tostring()) # Padding count = rec.size * rec.itemsize self.fp.write(asbytes('0') * (var._vsize - count)) pos += self._recsize self.fp.seek(pos) self.fp.seek(pos0 + var._vsize) def _write_values(self, values): if hasattr(values, 'dtype'): nc_type = REVERSE[values.dtype.char] else: types = [ (int, NC_INT), (long, NC_INT), (float, NC_FLOAT), (basestring, NC_CHAR), ] try: sample = values[0] except TypeError: sample = values for class_, nc_type in types: if isinstance(sample, class_): break typecode, size = TYPEMAP[nc_type] if typecode is 'c': dtype_ = '>c' else: dtype_ = '>%s' % typecode if size > 1: dtype_ += str(size) values = asarray(values, dtype=dtype_) self.fp.write(asbytes(nc_type)) if values.dtype.char == 'S': nelems = values.itemsize else: nelems = values.size self._pack_int(nelems) if not values.shape and (values.dtype.byteorder == '<' or (values.dtype.byteorder == '=' and LITTLE_ENDIAN)): values = values.byteswap() self.fp.write(values.tostring()) count = values.size * values.itemsize self.fp.write(asbytes('0') * (-count % 4)) # pad def _read(self): # Check magic bytes and version magic = self.fp.read(3) if not magic == asbytes('CDF'): raise TypeError("Error: %s is not a valid NetCDF 3 file" % self.filename) self.__dict__['version_byte'] = fromstring(self.fp.read(1), '>b')[0] # Read file headers and set data. self._read_numrecs() self._read_dim_array() self._read_gatt_array() self._read_var_array() def _read_numrecs(self): self.__dict__['_recs'] = self._unpack_int() def _read_dim_array(self): header = self.fp.read(4) assert header in [ZERO, NC_DIMENSION] count = self._unpack_int() for dim in range(count): name = asstr(self._unpack_string()) length = self._unpack_int() or None # None for record dimension self.dimensions[name] = length self._dims.append(name) # preserve order def _read_gatt_array(self): for k, v in self._read_att_array().items(): self.__setattr__(k, v) def _read_att_array(self): header = self.fp.read(4) assert header in [ZERO, NC_ATTRIBUTE] count = self._unpack_int() attributes = {} for attr in range(count): name = asstr(self._unpack_string()) attributes[name] = self._read_values() return attributes def _read_var_array(self): header = self.fp.read(4) assert header in [ZERO, NC_VARIABLE] begin = 0 dtypes = {'names': [], 'formats': []} rec_vars = [] count = self._unpack_int() for var in range(count): (name, dimensions, shape, attributes, typecode, size, dtype_, begin_, vsize) = self._read_var() # http://www.unidata.ucar.edu/software/netcdf/docs/netcdf.html # Note that vsize is the product of the dimension lengths # (omitting the record dimension) and the number of bytes # per value (determined from the type), increased to the # next multiple of 4, for each variable. If a record # variable, this is the amount of space per record. The # netCDF "record size" is calculated as the sum of the # vsize's of all the record variables. # # The vsize field is actually redundant, because its value # may be computed from other information in the header. The # 32-bit vsize field is not large enough to contain the size # of variables that require more than 2^32 - 4 bytes, so # 2^32 - 1 is used in the vsize field for such variables. if shape and shape[0] is None: # record variable rec_vars.append(name) # The netCDF "record size" is calculated as the sum of # the vsize's of all the record variables. self.__dict__['_recsize'] += vsize if begin == 0: begin = begin_ dtypes['names'].append(name) dtypes['formats'].append(str(shape[1:]) + dtype_) # Handle padding with a virtual variable. if typecode in 'bch': actual_size = reduce(mul, (1,) + shape[1:]) * size padding = -actual_size % 4 if padding: dtypes['names'].append('_padding_%d' % var) dtypes['formats'].append('(%d,)>b' % padding) # Data will be set later. data = None else: # not a record variable # Calculate size to avoid problems with vsize (above) a_size = reduce(mul, shape, 1) * size if self.use_mmap: mm = mmap(self.fp.fileno(), begin_+a_size, access=ACCESS_READ) data = ndarray.__new__(ndarray, shape, dtype=dtype_, buffer=mm, offset=begin_, order=0) else: pos = self.fp.tell() self.fp.seek(begin_) data = fromstring(self.fp.read(a_size), dtype=dtype_) data.shape = shape self.fp.seek(pos) # Add variable. self.variables[name] = netcdf_variable( data, typecode, shape, dimensions, attributes) if rec_vars: # Remove padding when only one record variable. if len(rec_vars) == 1: dtypes['names'] = dtypes['names'][:1] dtypes['formats'] = dtypes['formats'][:1] # Build rec array. if self.use_mmap: mm = mmap(self.fp.fileno(), begin+self._recsself._recsize, access=ACCESS_READ) rec_array = ndarray.__new__(ndarray, (self._recs,), dtype=dtypes, buffer=mm, offset=begin, order=0) else: pos = self.fp.tell() self.fp.seek(begin) rec_array = fromstring(self.fp.read(self._recsself._recsize), dtype=dtypes) rec_array.shape = (self._recs,) self.fp.seek(pos) for var in rec_vars: self.variables[var].__dict__['data'] = rec_array[var] def _read_var(self): name = asstr(self._unpack_string()) dimensions = [] shape = [] dims = self._unpack_int() for i in range(dims): dimid = self._unpack_int() dimname = self._dims[dimid] dimensions.append(dimname) dim = self.dimensions[dimname] shape.append(dim) dimensions = tuple(dimensions) shape = tuple(shape) attributes = self._read_att_array() nc_type = self.fp.read(4) vsize = self._unpack_int() begin = [self._unpack_int, self._unpack_int64][self.version_byte-1]() typecode, size = TYPEMAP[nc_type] if typecode is 'c': dtype_ = '>c' else: dtype_ = '>%s' % typecode if size > 1: dtype_ += str(size) return name, dimensions, shape, attributes, typecode, size, dtype_, begin, vsize def _read_values(self): nc_type = self.fp.read(4) n = self._unpack_int() typecode, size = TYPEMAP[nc_type] count = nsize values = self.fp.read(int(count)) self.fp.read(-count % 4) # read padding if typecode is not 'c': values = fromstring(values, dtype='>%s%d' % (typecode, size)) if values.shape == (1,): values = values[0] else: values = values.rstrip(asbytes('\x00')) return values def _pack_begin(self, begin): if self.version_byte == 1: self._pack_int(begin) elif self.version_byte == 2: self._pack_int64(begin) def _pack_int(self, value): self.fp.write(array(value, '>i').tostring()) _pack_int32 = _pack_int def _unpack_int(self): return int(fromstring(self.fp.read(4), '>i')[0]) _unpack_int32 = _unpack_int def _pack_int64(self, value): self.fp.write(array(value, '>q').tostring()) def _unpack_int64(self): return fromstring(self.fp.read(8), '>q')[0] def _pack_string(self, s): count = len(s) self._pack_int(count) self.fp.write(asbytes(s)) self.fp.write(asbytes('0') (-count % 4)) # pad def _unpack_string(self): count = self._unpack_int() s = self.fp.read(count).rstrip(asbytes('\x00')) self.fp.read(-count % 4) # read padding return s class netcdf_variable(object): """ A data object for the `netcdf` module. `netcdf_variable` objects are constructed by calling the method `netcdf_file.createVariable` on the `netcdf_file` object. `netcdf_variable` objects behave much like array objects defined in numpy, except that their data resides in a file. Data is read by indexing and written by assigning to an indexed subset; the entire array can be accessed by the index ``[:]`` or (for scalars) by using the methods `getValue` and `assignValue`. `netcdf_variable` objects also have attribute `shape` with the same meaning as for arrays, but the shape cannot be modified. There is another read-only attribute `dimensions`, whose value is the tuple of dimension names. All other attributes correspond to variable attributes defined in the NetCDF file. Variable attributes are created by assigning to an attribute of the `netcdf_variable` object. Parameters ---------- data : array_like The data array that holds the values for the variable. Typically, this is initialized as empty, but with the proper shape. typecode : dtype character code Desired data-type for the data array. shape : sequence of ints The shape of the array. This should match the lengths of the variable's dimensions. dimensions : sequence of strings The names of the dimensions used by the variable. Must be in the same order of the dimension lengths given by `shape`. attributes : dict, optional Attribute values (any type) keyed by string names. These attributes become attributes for the netcdf_variable object. Attributes ---------- dimensions : list of str List of names of dimensions used by the variable object. isrec, shape Properties See also -------- isrec, shape """ def __init__(self, data, typecode, shape, dimensions, attributes=None): self.data = data self._typecode = typecode self._shape = shape self.dimensions = dimensions self._attributes = attributes or {} for k, v in self._attributes.items(): self.__dict__[k] = v def __setattr__(self, attr, value): # Store user defined attributes in a separate dict, # so we can save them to file later. try: self._attributes[attr] = value except AttributeError: pass self.__dict__[attr] = value def isrec(self): return self.data.shape and not self._shape[0] isrec = property(isrec) def shape(self): return self.data.shape shape = property(shape) def getValue(self): """ Retrieve a scalar value from a `netcdf_variable` of length one. Raises ------ ValueError If the netcdf variable is an array of length greater than one, this exception will be raised. """ return self.data.item() def assignValue(self, value): """ Assign a scalar value to a `netcdf_variable` of length one. Parameters ---------- value : scalar Scalar value (of compatible type) to assign to a length-one netcdf variable. This value will be written to file. Raises ------ ValueError If the input is not a scalar, or if the destination is not a length-one netcdf variable. """ self.data.itemset(value) def typecode(self): """ Return the typecode of the variable. Returns ------- typecode : char The character typecode of the variable (eg, 'i' for int). """ return self._typecode def __getitem__(self, index): return self.data[index] def __setitem__(self, index, data): # Expand data for record vars? if self.isrec: if isinstance(index, tuple): rec_index = index[0] else: rec_index = index if isinstance(rec_index, slice): recs = (rec_index.start or 0) + len(data) else: recs = rec_index + 1 if recs > len(self.data): shape = (recs,) + self._shape[1:] self.data.resize(shape) self.data[index] = data NetCDFFile = netcdf_file NetCDFVariable = netcdf_variable	scipy/scipy-svn	scipy/io/netcdf.py	Python	bsd-3-clause	28,822	[ "NetCDF" ]	2d65540f9b4ca31001e60b018553ac4a6c0c5d60c41031733483ec0a5224e468
""" Tools for the instructor dashboard """ import json import operator import dateutil from django.contrib.auth.models import User # lint-amnesty, pylint: disable=imported-auth-user from django.http import HttpResponseBadRequest from django.utils.translation import ugettext as _ from edx_when import api from opaque_keys.edx.keys import UsageKey from pytz import UTC from common.djangoapps.student.models import CourseEnrollment, get_user_by_username_or_email from openedx.core.djangoapps.schedules.models import Schedule class DashboardError(Exception): """ Errors arising from use of the instructor dashboard. """ def response(self): """ Generate an instance of HttpResponseBadRequest for this error. """ error = str(self) return HttpResponseBadRequest(json.dumps({'error': error})) def handle_dashboard_error(view): """ Decorator which adds seamless DashboardError handling to a view. If a DashboardError is raised during view processing, an HttpResponseBadRequest is sent back to the client with JSON data about the error. """ def wrapper(request, course_id): """ Wrap the view. """ try: return view(request, course_id=course_id) except DashboardError as error: return error.response() return wrapper def strip_if_string(value): if isinstance(value, str): return value.strip() return value def get_student_from_identifier(unique_student_identifier): """ Gets a student object using either an email address or username. Returns the student object associated with `unique_student_identifier` Raises User.DoesNotExist if no user object can be found, the user was retired, or the user is in the process of being retired. DEPRECATED: use student.models.get_user_by_username_or_email instead. """ return get_user_by_username_or_email(unique_student_identifier) def require_student_from_identifier(unique_student_identifier): """ Same as get_student_from_identifier() but will raise a DashboardError if the student does not exist. """ try: return get_student_from_identifier(unique_student_identifier) except User.DoesNotExist: raise DashboardError( # lint-amnesty, pylint: disable=raise-missing-from _("Could not find student matching identifier: {student_identifier}").format( student_identifier=unique_student_identifier ) ) def parse_datetime(datestr): """ Convert user input date string into an instance of `datetime.datetime` in UTC. """ try: return dateutil.parser.parse(datestr).replace(tzinfo=UTC) except ValueError: raise DashboardError(_("Unable to parse date: ") + datestr) # lint-amnesty, pylint: disable=raise-missing-from def find_unit(course, url): """ Finds the unit (block, module, whatever the terminology is) with the given url in the course tree and returns the unit. Raises DashboardError if no unit is found. """ def find(node, url): """ Find node in course tree for url. """ if str(node.location) == url: return node for child in node.get_children(): found = find(child, url) if found: return found return None unit = find(course, url) if unit is None: raise DashboardError(_("Couldn't find module for url: {0}").format(url)) return unit def get_units_with_due_date(course): """ Returns all top level units which have due dates. Does not return descendents of those nodes. """ units = [] # Pass in a schedule here so that we get back any relative dates in the course, but actual value # doesn't matter, since we don't care about the dates themselves, just whether they exist. # Thus we don't save or care about this temporary schedule object. schedule = Schedule(start_date=course.start) course_dates = api.get_dates_for_course(course.id, schedule=schedule) def visit(node): """ Visit a node. Checks to see if node has a due date and appends to `units` if it does. Otherwise recurses into children to search for nodes with due dates. """ if (node.location, 'due') in course_dates: units.append(node) else: for child in node.get_children(): visit(child) visit(course) #units.sort(key=_title_or_url) return units def title_or_url(node): """ Returns the `display_name` attribute of the passed in node of the course tree, if it has one. Otherwise returns the node's url. """ title = getattr(node, 'display_name', None) if not title: title = str(node.location) return title def set_due_date_extension(course, unit, student, due_date, actor=None, reason=''): """ Sets a due date extension. Raises: DashboardError if the unit or extended, due date is invalid or user is not enrolled in the course. """ mode, __ = CourseEnrollment.enrollment_mode_for_user(user=student, course_id=str(course.id)) if not mode: raise DashboardError(_("Could not find student enrollment in the course.")) # We normally set dates at the subsection level. But technically dates can be anywhere down the tree (and # usually are in self paced courses, where the subsection date gets propagated down). # So find all children that we need to set the date on, then set those dates. course_dates = api.get_dates_for_course(course.id, user=student) blocks_to_set = {unit} # always include the requested unit, even if it doesn't appear to have a due date now def visit(node): """ Visit a node. Checks to see if node has a due date and appends to `blocks_to_set` if it does. And recurses into children to search for nodes with due dates. """ if (node.location, 'due') in course_dates: blocks_to_set.add(node) for child in node.get_children(): visit(child) visit(unit) for block in blocks_to_set: if due_date: try: api.set_date_for_block(course.id, block.location, 'due', due_date, user=student, reason=reason, actor=actor) except api.MissingDateError as ex: raise DashboardError(_("Unit {0} has no due date to extend.").format(unit.location)) from ex except api.InvalidDateError as ex: raise DashboardError(_("An extended due date must be later than the original due date.")) from ex else: api.set_date_for_block(course.id, block.location, 'due', None, user=student, reason=reason, actor=actor) def dump_module_extensions(course, unit): """ Dumps data about students with due date extensions for a particular module, specified by 'url', in a particular course. """ header = [_("Username"), _("Full Name"), _("Extended Due Date")] data = [] for username, fullname, due_date in api.get_overrides_for_block(course.id, unit.location): due_date = due_date.strftime('%Y-%m-%d %H:%M') data.append(dict(list(zip(header, (username, fullname, due_date))))) data.sort(key=operator.itemgetter(_("Username"))) return { "header": header, "title": _("Users with due date extensions for {0}").format( title_or_url(unit)), "data": data } def dump_student_extensions(course, student): """ Dumps data about the due date extensions granted for a particular student in a particular course. """ data = [] header = [_("Unit"), _("Extended Due Date")] units = get_units_with_due_date(course) units = {u.location: u for u in units} query = api.get_overrides_for_user(course.id, student) for override in query: location = override['location'].replace(course_key=course.id) if location not in units: continue due = override['actual_date'] due = due.strftime("%Y-%m-%d %H:%M") title = title_or_url(units[location]) data.append(dict(list(zip(header, (title, due))))) data.sort(key=operator.itemgetter(_("Unit"))) return { "header": header, "title": _("Due date extensions for {0} {1} ({2})").format( student.first_name, student.last_name, student.username), "data": data} def add_block_ids(payload): """ rather than manually parsing block_ids from module_ids on the client, pass the block_ids explicitly in the payload """ if 'data' in payload: for ele in payload['data']: if 'module_id' in ele: ele['block_id'] = UsageKey.from_string(ele['module_id']).block_id	eduNEXT/edunext-platform	lms/djangoapps/instructor/views/tools.py	Python	agpl-3.0	8,924	[ "VisIt" ]	e998c91b2b60b135d494acbe790f69025ea0ba0296f749f72d282abb904f5639
# coding: utf-8 from __future__ import division, unicode_literals """ This module implements a Composition class to represent compositions, and a ChemicalPotential class to represent potentials. """ __author__ = "Shyue Ping Ong" __copyright__ = "Copyright 2011, The Materials Project" __version__ = "0.1" __maintainer__ = "Shyue Ping Ong" __email__ = "shyuep@gmail.com" __status__ = "Production" __date__ = "Nov 10, 2012" import collections import numbers import re import string import six from six.moves import filter, map, zip from fractions import gcd from functools import total_ordering from itertools import chain from pymatgen.core.periodic_table import get_el_sp, Element from pymatgen.util.string_utils import formula_double_format from pymatgen.serializers.json_coders import PMGSONable from pymatgen.core.units import unitized @total_ordering class Composition(collections.Mapping, collections.Hashable, PMGSONable): """ Represents a Composition, which is essentially a {element:amount} mapping type. Composition is written to be immutable and hashable, unlike a standard Python dict. Note that the key can be either an Element or a Specie. Elements and Specie are treated differently. i.e., a Fe2+ is not the same as a Fe3+ Specie and would be put in separate keys. This differentiation is deliberate to support using Composition to determine the fraction of a particular Specie. Works almost completely like a standard python dictionary, except that __getitem__ is overridden to return 0 when an element is not found. (somewhat like a defaultdict, except it is immutable). Also adds more convenience methods relevant to compositions, e.g., get_fraction. It should also be noted that many Composition related functionality takes in a standard string as a convenient input. For example, even though the internal representation of a Fe2O3 composition is {Element("Fe"): 2, Element("O"): 3}, you can obtain the amount of Fe simply by comp["Fe"] instead of the more verbose comp[Element("Fe")]. >>> comp = Composition("LiFePO4") >>> comp.get_atomic_fraction(Element("Li")) 0.14285714285714285 >>> comp.num_atoms 7.0 >>> comp.reduced_formula 'LiFePO4' >>> comp.formula 'Li1 Fe1 P1 O4' >>> comp.get_wt_fraction(Element("Li")) 0.04399794666951898 >>> comp.num_atoms 7.0 """ """ Tolerance in distinguishing different composition amounts. 1e-8 is fairly tight, but should cut out most floating point arithmetic errors. """ amount_tolerance = 1e-8 """ Special formula handling for peroxides and certain elements. This is so that formula output does not write LiO instead of Li2O2 for example. """ special_formulas = {"LiO": "Li2O2", "NaO": "Na2O2", "KO": "K2O2", "HO": "H2O2", "CsO": "Cs2O2", "RbO": "Rb2O2", "O": "O2", "N": "N2", "Cl": "Cl2", "H": "H2"} def __init__(self, args, kwargs): #allow_negative=False """ Very flexible Composition construction, similar to the built-in Python dict(). Also extended to allow simple string init. Args: Any form supported by the Python built-in dict() function. 1. A dict of either {Element/Specie: amount}, {string symbol:amount}, or {atomic number:amount} or any mixture of these. E.g., {Element("Li"):2 ,Element("O"):1}, {"Li":2, "O":1}, {3:2, 8:1} all result in a Li2O composition. 2. Keyword arg initialization, similar to a dict, e.g., Compostion(Li = 2, O = 1) In addition, the Composition constructor also allows a single string as an input formula. E.g., Composition("Li2O"). allow_negative: Whether to allow negative compositions. This argument must be popped from the \\kwargs due to \args ambiguity. """ self.allow_negative = kwargs.pop('allow_negative', False) if len(args) == 1 and isinstance(args[0], six.string_types): elmap = self._parse_formula(args[0]) else: elmap = dict(args, kwargs) for k, v in list(elmap.items()): if v < -Composition.amount_tolerance and not self.allow_negative: raise CompositionError("Amounts in Composition cannot be " "negative!") elif abs(v) < Composition.amount_tolerance: del elmap[k] self._elmap = {get_el_sp(k): v for k, v in elmap.items()} self._natoms = sum(map(abs, self._elmap.values())) def __getitem__(self, el): """ Get the amount for element. """ return self._elmap.get(get_el_sp(el), 0) def __eq__(self, other): for el in chain(self.elements, other.elements): if abs(self[el] - other[el]) > Composition.amount_tolerance: return False return True def __ge__(self, other): """ Defines >= for Compositions. Should ONLY be used for defining a sort order (the behavior is probably not what you'd expect) """ for el in sorted(set(self.elements + other.elements)): if other[el] - self[el] >= Composition.amount_tolerance: return False elif self[el] - other[el] >= Composition.amount_tolerance: return True return True def __ne__(self, other): return not self.__eq__(other) def __add__(self, other): """ Adds two compositions. For example, an Fe2O3 composition + an FeO composition gives a Fe3O4 composition. """ new_el_map = collections.defaultdict(float) new_el_map.update(self) for k, v in other.items(): new_el_map[get_el_sp(k)] += v return Composition(new_el_map, allow_negative=self.allow_negative) def __sub__(self, other): """ Subtracts two compositions. For example, an Fe2O3 composition - an FeO composition gives an FeO2 composition. Raises: CompositionError if the subtracted composition is greater than the original composition in any of its elements, unless allow_negative is True """ new_el_map = collections.defaultdict(float) new_el_map.update(self) for k, v in other.items(): new_el_map[get_el_sp(k)] -= v return Composition(new_el_map, allow_negative=self.allow_negative) def __mul__(self, other): """ Multiply a Composition by an integer or a float. Fe2O3 4 -> Fe8O12 """ if not isinstance(other, numbers.Number): return NotImplemented return Composition({el: self[el] * other for el in self}, allow_negative=self.allow_negative) __rmul__ = __mul__ def __truediv__(self, other): if not isinstance(other, numbers.Number): return NotImplemented return Composition({el: self[el] / other for el in self}, allow_negative=self.allow_negative) def __hash__(self): """ Minimally effective hash function that just distinguishes between Compositions with different elements. """ hashcode = 0 for el in self._elmap.keys(): hashcode += el.Z return hashcode def __contains__(self, el): return el in self._elmap def __len__(self): return len(self._elmap) def __iter__(self): return self._elmap.__iter__() @property def average_electroneg(self): return sum((el.X * abs(amt) for el, amt in self._elmap.items())) / \ self.num_atoms def almost_equals(self, other, rtol=0.1, atol=1e-8): """ Returns true if compositions are equal within a tolerance. Args: other (Composition): Other composition to check rtol (float): Relative tolerance atol (float): Absolute tolerance """ sps = set(self.elements + other.elements) for sp in sps: a = self[sp] b = other[sp] tol = atol + rtol * (abs(a) + abs(b)) / 2 if abs(b - a) > tol: return False return True @property def is_element(self): """ True if composition is for an element. """ return len(self._elmap) == 1 def copy(self): return Composition(self._elmap, allow_negative=self.allow_negative) @property def formula(self): """ Returns a formula string, with elements sorted by electronegativity, e.g., Li4 Fe4 P4 O16. """ sym_amt = self.get_el_amt_dict() syms = sorted(sym_amt.keys(), key=lambda sym: get_el_sp(sym).X) formula = [s + formula_double_format(sym_amt[s], False) for s in syms] return " ".join(formula) @property def alphabetical_formula(self): """ Returns a formula string, with elements sorted by alphabetically e.g., Fe4 Li4 O16 P4. """ sym_amt = self.get_el_amt_dict() syms = sorted(sym_amt.keys()) formula = [s + formula_double_format(sym_amt[s], False) for s in syms] return " ".join(formula) @property def element_composition(self): """ Returns the composition replacing any species by the corresponding element. """ return Composition(self.get_el_amt_dict(), allow_negative=self.allow_negative) @property def fractional_composition(self): """ Returns the normalized composition which the number of species sum to 1. Returns: Normalized composition which the number of species sum to 1. """ return self / self._natoms @property def reduced_composition(self): """ Returns the reduced composition,i.e. amounts normalized by greatest common denominator. e.g., Composition("FePO4") for Composition("Fe4P4O16"). """ return self.get_reduced_composition_and_factor()[0] def get_reduced_composition_and_factor(self): """ Calculates a reduced composition and factor. Returns: A normalized composition and a multiplicative factor, i.e., Li4Fe4P4O16 returns (Composition("LiFePO4"), 4). """ factor = self.get_reduced_formula_and_factor()[1] return self / factor, factor def get_reduced_formula_and_factor(self): """ Calculates a reduced formula and factor. Returns: A pretty normalized formula and a multiplicative factor, i.e., Li4Fe4P4O16 returns (LiFePO4, 4). """ all_int = all([x == int(x) for x in self._elmap.values()]) if not all_int: return self.formula.replace(" ", ""), 1 d = self.get_el_amt_dict() (formula, factor) = reduce_formula(d) if formula in Composition.special_formulas: formula = Composition.special_formulas[formula] factor /= 2 return formula, factor @property def reduced_formula(self): """ Returns a pretty normalized formula, i.e., LiFePO4 instead of Li4Fe4P4O16. """ return self.get_reduced_formula_and_factor()[0] @property def elements(self): """ Returns view of elements in Composition. """ return list(self._elmap.keys()) def __str__(self): return " ".join([ "{}{}".format(k, formula_double_format(v, ignore_ones=False)) for k, v in self.as_dict().items()]) @property def num_atoms(self): """ Total number of atoms in Composition. For negative amounts, sum of absolute values """ return self._natoms @property @unitized("amu") def weight(self): """ Total molecular weight of Composition """ return sum([amount * el.atomic_mass for el, amount in self._elmap.items()]) def get_atomic_fraction(self, el): """ Calculate atomic fraction of an Element or Specie. Args: el (Element/Specie): Element or Specie to get fraction for. Returns: Atomic fraction for element el in Composition """ return abs(self[el]) / self._natoms def get_wt_fraction(self, el): """ Calculate weight fraction of an Element or Specie. Args: el (Element/Specie): Element or Specie to get fraction for. Returns: Weight fraction for element el in Composition """ return get_el_sp(el).atomic_mass * abs(self[el]) / self.weight def _parse_formula(self, formula): """ Args: formula (str): A string formula, e.g. Fe2O3, Li3Fe2(PO4)3 Returns: Composition with that formula. """ def get_sym_dict(f, factor): sym_dict = collections.defaultdict(float) for m in re.finditer(r"([A-Z][a-z])([-\.\d])", f): el = m.group(1) amt = 1 if m.group(2).strip() != "": amt = float(m.group(2)) sym_dict[el] += amt factor f = f.replace(m.group(), "", 1) if f.strip(): raise CompositionError("{} is an invalid formula!".format(f)) return sym_dict m = re.search(r"\(([^\(\)]+)\)([\.\d])", formula) if m: factor = 1 if m.group(2) != "": factor = float(m.group(2)) unit_sym_dict = get_sym_dict(m.group(1), factor) expanded_sym = "".join(["{}{}".format(el, amt) for el, amt in unit_sym_dict.items()]) expanded_formula = formula.replace(m.group(), expanded_sym) return self._parse_formula(expanded_formula) return get_sym_dict(formula, 1) @property def anonymized_formula(self): """ An anonymized formula. Unique species are arranged in ordering of increasing amounts and assigned ascending alphabets. Useful for prototyping formulas. For example, all stoichiometric perovskites have anonymized_formula ABC3. """ reduced_comp = self.get_reduced_composition_and_factor()[0] els = sorted(reduced_comp.elements, key=lambda e: reduced_comp[e]) anon_formula = [] for anon, e in zip(string.ascii_uppercase, els): amt = reduced_comp[e] if amt > 0: if amt == 1: amt_str = "" elif abs(amt % 1) < 1e-8: amt_str = str(int(amt)) else: amt_str = str(amt) anon_formula.append("{}{}".format(anon, amt_str)) return "".join(anon_formula) def __repr__(self): return "Comp: " + self.formula @classmethod def from_dict(cls, d): """ Creates a composition from a dict generated by as_dict(). Strictly not necessary given that the standard constructor already takes in such an input, but this method preserves the standard pymatgen API of having from_dict methods to reconstitute objects generated by as_dict(). Allows for easier introspection. Args: d (dict): {symbol: amount} dict. """ return cls(d) def get_el_amt_dict(self): """ Returns: Dict with element symbol and (unreduced) amount e.g., {"Fe": 4.0, "O":6.0} or {"Fe3+": 4.0, "O2-":6.0} """ d = collections.defaultdict(float) for e, a in self.items(): d[e.symbol] += a return d def as_dict(self): """ Returns: dict with species symbol and (unreduced) amount e.g., {"Fe": 4.0, "O":6.0} or {"Fe3+": 4.0, "O2-":6.0} """ d = collections.defaultdict(float) for e, a in self.items(): d[str(e)] += a return d @property def to_reduced_dict(self): """ Returns: Dict with element symbol and reduced amount e.g., {"Fe": 2.0, "O":3.0} """ c = Composition(self.reduced_formula) return c.as_dict() @property def to_data_dict(self): """ Returns: A dict with many keys and values relating to Composition/Formula, including reduced_cell_composition, unit_cell_composition, reduced_cell_formula, elements and nelements. """ return {"reduced_cell_composition": self.to_reduced_dict, "unit_cell_composition": self.as_dict(), "reduced_cell_formula": self.reduced_formula, "elements": self.as_dict().keys(), "nelements": len(self.as_dict().keys())} @staticmethod def ranked_compositions_from_indeterminate_formula(fuzzy_formula, lock_if_strict=True): """ Takes in a formula where capitilization might not be correctly entered, and suggests a ranked list of potential Composition matches. Author: Anubhav Jain Args: fuzzy_formula (str): A formula string, such as "co2o3" or "MN", that may or may not have multiple interpretations lock_if_strict (bool): If true, a properly entered formula will only return the one correct interpretation. For example, "Co1" will only return "Co1" if true, but will return both "Co1" and "C1 O1" if false. Returns: A ranked list of potential Composition matches """ #if we have an exact match and the user specifies lock_if_strict, just #return the exact match! if lock_if_strict: #the strict composition parsing might throw an error, we can ignore #it and just get on with fuzzy matching try: comp = Composition(fuzzy_formula) return [comp] except (CompositionError, ValueError): pass all_matches = Composition._comps_from_fuzzy_formula(fuzzy_formula) #remove duplicates all_matches = list(set(all_matches)) #sort matches by rank descending all_matches = sorted(all_matches, key=lambda match: match[1], reverse=True) all_matches = [m[0] for m in all_matches] return all_matches @staticmethod def _comps_from_fuzzy_formula(fuzzy_formula, m_dict={}, m_points=0, factor=1): """ A recursive helper method for formula parsing that helps in interpreting and ranking indeterminate formulas. Author: Anubhav Jain Args: fuzzy_formula (str): A formula string, such as "co2o3" or "MN", that may or may not have multiple interpretations. m_dict (dict): A symbol:amt dictionary from the previously parsed formula. m_points: Number of points gained from the previously parsed formula. factor: Coefficient for this parse, e.g. (PO4)2 will feed in PO4 as the fuzzy_formula with a coefficient of 2. Returns: A list of tuples, with the first element being a Composition and the second element being the number of points awarded that Composition intepretation. """ def _parse_chomp_and_rank(m, f, m_dict, m_points): """ A helper method for formula parsing that helps in interpreting and ranking indeterminate formulas Author: Anubhav Jain Args: m: A regex match, with the first group being the element and the second group being the amount f: The formula part containing the match m_dict: A symbol:amt dictionary from the previously parsed formula m_points: Number of points gained from the previously parsed formula Returns: A tuple of (f, m_dict, points) where m_dict now contains data from the match and the match has been removed (chomped) from the formula f. The "goodness" of the match determines the number of points returned for chomping. Returns (None, None, None) if no element could be found... """ points = 0 # Points awarded if the first element of the element is correctly # specified as a capital points_first_capital = 100 # Points awarded if the second letter of the element is correctly # specified as lowercase points_second_lowercase = 100 #get element and amount from regex match el = m.group(1) if len(el) > 2 or len(el) < 1: raise CompositionError("Invalid element symbol entered!") amt = float(m.group(2)) if m.group(2).strip() != "" else 1 #convert the element string to proper [uppercase,lowercase] format #and award points if it is already in that format char1 = el[0] char2 = el[1] if len(el) > 1 else "" if char1 == char1.upper(): points += points_first_capital if char2 and char2 == char2.lower(): points += points_second_lowercase el = char1.upper() + char2.lower() #if it's a valid element, chomp and add to the points if Element.is_valid_symbol(el): if el in m_dict: m_dict[el] += amt factor else: m_dict[el] = amt * factor return f.replace(m.group(), "", 1), m_dict, m_points + points #else return None return None, None, None fuzzy_formula = fuzzy_formula.strip() if len(fuzzy_formula) == 0: #The entire formula has been parsed into m_dict. Return the #corresponding Composition and number of points if m_dict: yield (Composition.from_dict(m_dict), m_points) else: #if there is a parenthesis, remove it and match the remaining stuff #with the appropriate factor for mp in re.finditer(r"\(([^\(\)]+)\)([\.\d])", fuzzy_formula): mp_points = m_points mp_form = fuzzy_formula.replace(mp.group(), " ", 1) mp_dict = dict(m_dict) mp_factor = 1 if mp.group(2) == "" else float(mp.group(2)) #Match the stuff inside the parenthesis with the appropriate #factor for match in \ Composition._comps_from_fuzzy_formula(mp.group(1), mp_dict, mp_points, factor=mp_factor): only_me = True # Match the stuff outside the parentheses and return the # sum. for match2 in \ Composition._comps_from_fuzzy_formula(mp_form, mp_dict, mp_points, factor=1): only_me = False yield (match[0] + match2[0], match[1] + match2[1]) #if the stuff inside the parenthesis is nothing, then just #return the stuff inside the parentheses if only_me: yield match return #try to match the single-letter elements m1 = re.match(r"([A-z])([\.\d])", fuzzy_formula) if m1: m_points1 = m_points m_form1 = fuzzy_formula m_dict1 = dict(m_dict) (m_form1, m_dict1, m_points1) = \ _parse_chomp_and_rank(m1, m_form1, m_dict1, m_points1) if m_dict1: #there was a real match for match in \ Composition._comps_from_fuzzy_formula(m_form1, m_dict1, m_points1, factor): yield match #try to match two-letter elements m2 = re.match(r"([A-z]{2})([\.\d])", fuzzy_formula) if m2: m_points2 = m_points m_form2 = fuzzy_formula m_dict2 = dict(m_dict) (m_form2, m_dict2, m_points2) = \ _parse_chomp_and_rank(m2, m_form2, m_dict2, m_points2) if m_dict2: #there was a real match for match in \ Composition._comps_from_fuzzy_formula(m_form2, m_dict2, m_points2, factor): yield match def reduce_formula(sym_amt): """ Helper method to reduce a sym_amt dict to a reduced formula and factor. Args: sym_amt (dict): {symbol: amount}. Returns: (reduced_formula, factor). """ syms = sorted(sym_amt.keys(), key=lambda s: get_el_sp(s).X) syms = list(filter(lambda s: abs(sym_amt[s]) > Composition.amount_tolerance, syms)) num_el = len(syms) contains_polyanion = (num_el >= 3 and get_el_sp(syms[num_el - 1]).X - get_el_sp(syms[num_el - 2]).X < 1.65) factor = abs(six.moves.reduce(gcd, sym_amt.values())) reduced_form = [] n = num_el - 2 if contains_polyanion else num_el for i in range(0, n): s = syms[i] normamt = sym_amt[s] 1.0 / factor reduced_form.append(s) reduced_form.append(formula_double_format(normamt)) if contains_polyanion: poly_sym_amt = {syms[i]: sym_amt[syms[i]] / factor for i in range(n, num_el)} (poly_form, poly_factor) = reduce_formula(poly_sym_amt) if poly_factor != 1: reduced_form.append("({}){}".format(poly_form, int(poly_factor))) else: reduced_form.append(poly_form) reduced_form = "".join(reduced_form) return reduced_form, factor class CompositionError(Exception): """Exception class for composition errors""" pass class ChemicalPotential(dict, PMGSONable): """ Class to represent set of chemical potentials. Can be: multiplied/divided by a Number multiplied by a Composition (returns an energy) added/subtracted with other ChemicalPotentials. """ def __init__(self, args, kwargs): """ Args: args, *kwargs: any valid dict init arguments """ d = dict(args, *kwargs) super(ChemicalPotential, self).__init__((get_el_sp(k), v) for k, v in d.items()) if len(d) != len(self): raise ValueError("Duplicate potential specified") def __mul__(self, other): if isinstance(other, numbers.Number): return ChemicalPotential({k: v other for k, v in self.items()}) else: return NotImplemented __rmul__ = __mul__ def __truediv__(self, other): if isinstance(other, numbers.Number): return ChemicalPotential({k: v / other for k, v in self.items()}) else: return NotImplemented def __sub__(self, other): if isinstance(other, ChemicalPotential): els = set(self.keys()).union(other.keys()) return ChemicalPotential({e: self.get(e, 0) - other.get(e, 0) for e in els}) else: return NotImplemented def __add__(self, other): if isinstance(other, ChemicalPotential): els = set(self.keys()).union(other.keys()) return ChemicalPotential({e: self.get(e, 0) + other.get(e, 0) for e in els}) else: return NotImplemented def get_energy(self, composition, strict=True): """ Calculates the energy of a composition Args: composition (Composition): input composition strict (bool): Whether all potentials must be specified """ if strict and set(composition.keys()) > set(self.keys()): s = set(composition.keys()) - set(self.keys()) raise ValueError("Potentials not specified for {}".format(s)) return sum(self.get(k, 0) * v for k, v in composition.items()) def __repr__(self): return "ChemPots: " + super(ChemicalPotential, self).__repr__() if __name__ == "__main__": import doctest doctest.testmod()	yanikou19/pymatgen	pymatgen/core/composition.py	Python	mit	29,842	[ "pymatgen" ]	5668a8b25df2cf6e5ea176586f78aa8b3dc09316e32b260cfec894062031781d
# Copyright (c) 2012 Google Inc. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from __future__ import print_function import gyp.common import gyp.simple_copy import multiprocessing import optparse import os.path import re import shlex import signal import subprocess import sys import threading import time import traceback from gyp.common import GypError from gyp.common import OrderedSet _PYTHON3 = sys.version_info >= (3, 0, 0) if not _PYTHON3: from compiler.ast import Const, Dict, Discard, List, Module, Node, Stmt import compiler # A list of types that are treated as linkable. linkable_types = ['executable', 'shared_library', 'loadable_module'] # A list of sections that contain links to other targets. dependency_sections = ['dependencies', 'export_dependent_settings'] # base_path_sections is a list of sections defined by GYP that contain # pathnames. The generators can provide more keys, the two lists are merged # into path_sections, but you should call IsPathSection instead of using either # list directly. base_path_sections = [ 'destination', 'files', 'include_dirs', 'inputs', 'libraries', 'outputs', 'sources', ] path_sections = set() # These per-process dictionaries are used to cache build file data when loading # in parallel mode. per_process_data = {} per_process_aux_data = {} def IsPathSection(section): # If section ends in one of the '=+?!' characters, it's applied to a section # without the trailing characters. '/' is notably absent from this list, # because there's no way for a regular expression to be treated as a path. while section[-1:] in '=+?!': section = section[:-1] if section in path_sections: return True # Sections mathing the regexp '_(dir\|file\|path)s?$' are also # considered PathSections. Using manual string matching since that # is much faster than the regexp and this can be called hundreds of # thousands of times so micro performance matters. if "_" in section: tail = section[-6:] if tail[-1] == 's': tail = tail[:-1] if tail[-5:] in ('_file', '_path'): return True return tail[-4:] == '_dir' return False # base_non_configuration_keys is a list of key names that belong in the target # itself and should not be propagated into its configurations. It is merged # with a list that can come from the generator to # create non_configuration_keys. base_non_configuration_keys = [ # Sections that must exist inside targets and not configurations. 'actions', 'configurations', 'copies', 'default_configuration', 'dependencies', 'dependencies_original', 'libraries', 'postbuilds', 'product_dir', 'product_extension', 'product_name', 'product_prefix', 'rules', 'run_as', 'sources', 'standalone_static_library', 'suppress_wildcard', 'target_name', 'toolset', 'toolsets', 'type', # Sections that can be found inside targets or configurations, but that # should not be propagated from targets into their configurations. 'variables', ] non_configuration_keys = [] # Keys that do not belong inside a configuration dictionary. invalid_configuration_keys = [ 'actions', 'all_dependent_settings', 'configurations', 'dependencies', 'direct_dependent_settings', 'libraries', 'link_settings', 'sources', 'standalone_static_library', 'target_name', 'type', ] # Controls whether or not the generator supports multiple toolsets. multiple_toolsets = False # Paths for converting filelist paths to output paths: { # toplevel, # qualified_output_dir, # } generator_filelist_paths = None def GetIncludedBuildFiles(build_file_path, aux_data, included=None): """Return a list of all build files included into build_file_path. The returned list will contain build_file_path as well as all other files that it included, either directly or indirectly. Note that the list may contain files that were included into a conditional section that evaluated to false and was not merged into build_file_path's dict. aux_data is a dict containing a key for each build file or included build file. Those keys provide access to dicts whose "included" keys contain lists of all other files included by the build file. included should be left at its default None value by external callers. It is used for recursion. The returned list will not contain any duplicate entries. Each build file in the list will be relative to the current directory. """ if included == None: included = [] if build_file_path in included: return included included.append(build_file_path) for included_build_file in aux_data[build_file_path].get('included', []): GetIncludedBuildFiles(included_build_file, aux_data, included) return included def CheckedEval(file_contents): """Return the eval of a gyp file. The gyp file is restricted to dictionaries and lists only, and repeated keys are not allowed. Note that this is slower than eval() is. """ if _PYTHON3: return eval(build_file_contents, {'__builtins__': None}, None) ast = compiler.parse(file_contents) assert isinstance(ast, Module) c1 = ast.getChildren() assert c1[0] is None assert isinstance(c1[1], Stmt) c2 = c1[1].getChildren() assert isinstance(c2[0], Discard) c3 = c2[0].getChildren() assert len(c3) == 1 return CheckNode(c3[0], []) def CheckNode(node, keypath): if isinstance(node, Dict): c = node.getChildren() dict = {} for n in range(0, len(c), 2): assert isinstance(c[n], Const) key = c[n].getChildren()[0] if key in dict: raise GypError("Key '" + key + "' repeated at level " + repr(len(keypath) + 1) + " with key path '" + '.'.join(keypath) + "'") kp = list(keypath) # Make a copy of the list for descending this node. kp.append(key) dict[key] = CheckNode(c[n + 1], kp) return dict elif isinstance(node, List): c = node.getChildren() children = [] for index, child in enumerate(c): kp = list(keypath) # Copy list. kp.append(repr(index)) children.append(CheckNode(child, kp)) return children elif isinstance(node, Const): return node.getChildren()[0] else: raise TypeError("Unknown AST node at key path '" + '.'.join(keypath) + "': " + repr(node)) def LoadOneBuildFile(build_file_path, data, aux_data, includes, is_target, check): if build_file_path in data: return data[build_file_path] if os.path.exists(build_file_path): build_file_contents = open(build_file_path).read() else: raise GypError("%s not found (cwd: %s)" % (build_file_path, os.getcwd())) build_file_data = None try: if check: build_file_data = CheckedEval(build_file_contents) else: build_file_data = eval(build_file_contents, {'__builtins__': None}, None) except SyntaxError: e = sys.exc_info()[1] e.filename = build_file_path raise except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while reading ' + build_file_path) raise if type(build_file_data) is not dict: raise GypError("%s does not evaluate to a dictionary." % build_file_path) data[build_file_path] = build_file_data aux_data[build_file_path] = {} # Scan for includes and merge them in. if ('skip_includes' not in build_file_data or not build_file_data['skip_includes']): try: if is_target: LoadBuildFileIncludesIntoDict(build_file_data, build_file_path, data, aux_data, includes, check) else: LoadBuildFileIncludesIntoDict(build_file_data, build_file_path, data, aux_data, None, check) except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while reading includes of ' + build_file_path) raise return build_file_data def LoadBuildFileIncludesIntoDict(subdict, subdict_path, data, aux_data, includes, check): includes_list = [] if includes != None: includes_list.extend(includes) if 'includes' in subdict: for include in subdict['includes']: # "include" is specified relative to subdict_path, so compute the real # path to include by appending the provided "include" to the directory # in which subdict_path resides. relative_include = \ os.path.normpath(os.path.join(os.path.dirname(subdict_path), include)) includes_list.append(relative_include) # Unhook the includes list, it's no longer needed. del subdict['includes'] # Merge in the included files. for include in includes_list: if not 'included' in aux_data[subdict_path]: aux_data[subdict_path]['included'] = [] aux_data[subdict_path]['included'].append(include) gyp.DebugOutput(gyp.DEBUG_INCLUDES, "Loading Included File: '%s'", include) MergeDicts(subdict, LoadOneBuildFile(include, data, aux_data, None, False, check), subdict_path, include) # Recurse into subdictionaries. for k, v in subdict.items(): if type(v) is dict: LoadBuildFileIncludesIntoDict(v, subdict_path, data, aux_data, None, check) elif type(v) is list: LoadBuildFileIncludesIntoList(v, subdict_path, data, aux_data, check) # This recurses into lists so that it can look for dicts. def LoadBuildFileIncludesIntoList(sublist, sublist_path, data, aux_data, check): for item in sublist: if type(item) is dict: LoadBuildFileIncludesIntoDict(item, sublist_path, data, aux_data, None, check) elif type(item) is list: LoadBuildFileIncludesIntoList(item, sublist_path, data, aux_data, check) # Processes toolsets in all the targets. This recurses into condition entries # since they can contain toolsets as well. def ProcessToolsetsInDict(data): if 'targets' in data: target_list = data['targets'] new_target_list = [] for target in target_list: # If this target already has an explicit 'toolset', and no 'toolsets' # list, don't modify it further. if 'toolset' in target and 'toolsets' not in target: new_target_list.append(target) continue if multiple_toolsets: toolsets = target.get('toolsets', ['target']) else: toolsets = ['target'] # Make sure this 'toolsets' definition is only processed once. if 'toolsets' in target: del target['toolsets'] if len(toolsets) > 0: # Optimization: only do copies if more than one toolset is specified. for build in toolsets[1:]: new_target = gyp.simple_copy.deepcopy(target) new_target['toolset'] = build new_target_list.append(new_target) target['toolset'] = toolsets[0] new_target_list.append(target) data['targets'] = new_target_list if 'conditions' in data: for condition in data['conditions']: if type(condition) is list: for condition_dict in condition[1:]: if type(condition_dict) is dict: ProcessToolsetsInDict(condition_dict) # TODO(mark): I don't love this name. It just means that it's going to load # a build file that contains targets and is expected to provide a targets dict # that contains the targets... def LoadTargetBuildFile(build_file_path, data, aux_data, variables, includes, depth, check, load_dependencies): # If depth is set, predefine the DEPTH variable to be a relative path from # this build file's directory to the directory identified by depth. if depth: # TODO(dglazkov) The backslash/forward-slash replacement at the end is a # temporary measure. This should really be addressed by keeping all paths # in POSIX until actual project generation. d = gyp.common.RelativePath(depth, os.path.dirname(build_file_path)) if d == '': variables['DEPTH'] = '.' else: variables['DEPTH'] = d.replace('\\', '/') # The 'target_build_files' key is only set when loading target build files in # the non-parallel code path, where LoadTargetBuildFile is called # recursively. In the parallel code path, we don't need to check whether the # \|build_file_path\| has already been loaded, because the 'scheduled' set in # ParallelState guarantees that we never load the same \|build_file_path\| # twice. if 'target_build_files' in data: if build_file_path in data['target_build_files']: # Already loaded. return False data['target_build_files'].add(build_file_path) gyp.DebugOutput(gyp.DEBUG_INCLUDES, "Loading Target Build File '%s'", build_file_path) build_file_data = LoadOneBuildFile(build_file_path, data, aux_data, includes, True, check) # Store DEPTH for later use in generators. build_file_data['_DEPTH'] = depth # Set up the included_files key indicating which .gyp files contributed to # this target dict. if 'included_files' in build_file_data: raise GypError(build_file_path + ' must not contain included_files key') included = GetIncludedBuildFiles(build_file_path, aux_data) build_file_data['included_files'] = [] for included_file in included: # included_file is relative to the current directory, but it needs to # be made relative to build_file_path's directory. included_relative = \ gyp.common.RelativePath(included_file, os.path.dirname(build_file_path)) build_file_data['included_files'].append(included_relative) # Do a first round of toolsets expansion so that conditions can be defined # per toolset. ProcessToolsetsInDict(build_file_data) # Apply "pre"/"early" variable expansions and condition evaluations. ProcessVariablesAndConditionsInDict( build_file_data, PHASE_EARLY, variables, build_file_path) # Since some toolsets might have been defined conditionally, perform # a second round of toolsets expansion now. ProcessToolsetsInDict(build_file_data) # Look at each project's target_defaults dict, and merge settings into # targets. if 'target_defaults' in build_file_data: if 'targets' not in build_file_data: raise GypError("Unable to find targets in build file %s" % build_file_path) index = 0 while index < len(build_file_data['targets']): # This procedure needs to give the impression that target_defaults is # used as defaults, and the individual targets inherit from that. # The individual targets need to be merged into the defaults. Make # a deep copy of the defaults for each target, merge the target dict # as found in the input file into that copy, and then hook up the # copy with the target-specific data merged into it as the replacement # target dict. old_target_dict = build_file_data['targets'][index] new_target_dict = gyp.simple_copy.deepcopy( build_file_data['target_defaults']) MergeDicts(new_target_dict, old_target_dict, build_file_path, build_file_path) build_file_data['targets'][index] = new_target_dict index += 1 # No longer needed. del build_file_data['target_defaults'] # Look for dependencies. This means that dependency resolution occurs # after "pre" conditionals and variable expansion, but before "post" - # in other words, you can't put a "dependencies" section inside a "post" # conditional within a target. dependencies = [] if 'targets' in build_file_data: for target_dict in build_file_data['targets']: if 'dependencies' not in target_dict: continue for dependency in target_dict['dependencies']: dependencies.append( gyp.common.ResolveTarget(build_file_path, dependency, None)[0]) if load_dependencies: for dependency in dependencies: try: LoadTargetBuildFile(dependency, data, aux_data, variables, includes, depth, check, load_dependencies) except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend( e, 'while loading dependencies of %s' % build_file_path) raise else: return (build_file_path, dependencies) def CallLoadTargetBuildFile(global_flags, build_file_path, variables, includes, depth, check, generator_input_info): """Wrapper around LoadTargetBuildFile for parallel processing. This wrapper is used when LoadTargetBuildFile is executed in a worker process. """ try: signal.signal(signal.SIGINT, signal.SIG_IGN) # Apply globals so that the worker process behaves the same. for key, value in global_flags.items(): globals()[key] = value SetGeneratorGlobals(generator_input_info) result = LoadTargetBuildFile(build_file_path, per_process_data, per_process_aux_data, variables, includes, depth, check, False) if not result: return result (build_file_path, dependencies) = result # We can safely pop the build_file_data from per_process_data because it # will never be referenced by this process again, so we don't need to keep # it in the cache. build_file_data = per_process_data.pop(build_file_path) # This gets serialized and sent back to the main process via a pipe. # It's handled in LoadTargetBuildFileCallback. return (build_file_path, build_file_data, dependencies) except GypError: e = sys.exc_info()[1] sys.stderr.write("gyp: %s\n" % e) return None except Exception: e = sys.exc_info()[1] print('Exception:', e, file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) return None class ParallelProcessingError(Exception): pass class ParallelState(object): """Class to keep track of state when processing input files in parallel. If build files are loaded in parallel, use this to keep track of state during farming out and processing parallel jobs. It's stored in a global so that the callback function can have access to it. """ def __init__(self): # The multiprocessing pool. self.pool = None # The condition variable used to protect this object and notify # the main loop when there might be more data to process. self.condition = None # The "data" dict that was passed to LoadTargetBuildFileParallel self.data = None # The number of parallel calls outstanding; decremented when a response # was received. self.pending = 0 # The set of all build files that have been scheduled, so we don't # schedule the same one twice. self.scheduled = set() # A list of dependency build file paths that haven't been scheduled yet. self.dependencies = [] # Flag to indicate if there was an error in a child process. self.error = False def LoadTargetBuildFileCallback(self, result): """Handle the results of running LoadTargetBuildFile in another process. """ self.condition.acquire() if not result: self.error = True self.condition.notify() self.condition.release() return (build_file_path0, build_file_data0, dependencies0) = result self.data[build_file_path0] = build_file_data0 self.data['target_build_files'].add(build_file_path0) for new_dependency in dependencies0: if new_dependency not in self.scheduled: self.scheduled.add(new_dependency) self.dependencies.append(new_dependency) self.pending -= 1 self.condition.notify() self.condition.release() def LoadTargetBuildFilesParallel(build_files, data, variables, includes, depth, check, generator_input_info): parallel_state = ParallelState() parallel_state.condition = threading.Condition() # Make copies of the build_files argument that we can modify while working. parallel_state.dependencies = list(build_files) parallel_state.scheduled = set(build_files) parallel_state.pending = 0 parallel_state.data = data try: parallel_state.condition.acquire() while parallel_state.dependencies or parallel_state.pending: if parallel_state.error: break if not parallel_state.dependencies: parallel_state.condition.wait() continue dependency = parallel_state.dependencies.pop() parallel_state.pending += 1 global_flags = { 'path_sections': globals()['path_sections'], 'non_configuration_keys': globals()['non_configuration_keys'], 'multiple_toolsets': globals()['multiple_toolsets']} if not parallel_state.pool: parallel_state.pool = multiprocessing.Pool(multiprocessing.cpu_count()) parallel_state.pool.apply_async( CallLoadTargetBuildFile, args = (global_flags, dependency, variables, includes, depth, check, generator_input_info), callback = parallel_state.LoadTargetBuildFileCallback) except KeyboardInterrupt: e = sys.exc_info()[1] parallel_state.pool.terminate() raise e parallel_state.condition.release() parallel_state.pool.close() parallel_state.pool.join() parallel_state.pool = None if parallel_state.error: sys.exit(1) # Look for the bracket that matches the first bracket seen in a # string, and return the start and end as a tuple. For example, if # the input is something like "<(foo <(bar)) blah", then it would # return (1, 13), indicating the entire string except for the leading # "<" and trailing " blah". LBRACKETS= set('{[(') BRACKETS = {'}': '{', ']': '[', ')': '('} def FindEnclosingBracketGroup(input_str): stack = [] start = -1 for index, char in enumerate(input_str): if char in LBRACKETS: stack.append(char) if start == -1: start = index elif char in BRACKETS: if not stack: return (-1, -1) if stack.pop() != BRACKETS[char]: return (-1, -1) if not stack: return (start, index + 1) return (-1, -1) def IsStrCanonicalInt(string): """Returns True if \|string\| is in its canonical integer form. The canonical form is such that str(int(string)) == string. """ if type(string) is str: # This function is called a lot so for maximum performance, avoid # involving regexps which would otherwise make the code much # shorter. Regexps would need twice the time of this function. if string: if string == "0": return True if string[0] == "-": string = string[1:] if not string: return False if '1' <= string[0] <= '9': return string.isdigit() return False # This matches things like "<(asdf)", "<!(cmd)", "<!@(cmd)", "<\|(list)", # "<!interpreter(arguments)", "<([list])", and even "<([)" and "<(<())". # In the last case, the inner "<()" is captured in match['content']. early_variable_re = re.compile( r'(?P<replace>(?P<type><(?:(?:!?@?)\|\\|)?)' r'(?P<command_string>[-a-zA-Z0-9_.]+)?' r'\((?P<is_array>\s\[?)' r'(?P<content>.?)(\]?)\))') # This matches the same as early_variable_re, but with '>' instead of '<'. late_variable_re = re.compile( r'(?P<replace>(?P<type>>(?:(?:!?@?)\|\\|)?)' r'(?P<command_string>[-a-zA-Z0-9_.]+)?' r'\((?P<is_array>\s\[?)' r'(?P<content>.?)(\]?)\))') # This matches the same as early_variable_re, but with '^' instead of '<'. latelate_variable_re = re.compile( r'(?P<replace>(?P<type>[\^](?:(?:!?@?)\|\\|)?)' r'(?P<command_string>[-a-zA-Z0-9_.]+)?' r'\((?P<is_array>\s\[?)' r'(?P<content>.?)(\]?)\))') # Global cache of results from running commands so they don't have to be run # more then once. cached_command_results = {} def FixupPlatformCommand(cmd): if sys.platform == 'win32': if type(cmd) is list: cmd = [re.sub('^cat ', 'type ', cmd[0])] + cmd[1:] else: cmd = re.sub('^cat ', 'type ', cmd) return cmd PHASE_EARLY = 0 PHASE_LATE = 1 PHASE_LATELATE = 2 def ExpandVariables(input, phase, variables, build_file): # Look for the pattern that gets expanded into variables if phase == PHASE_EARLY: variable_re = early_variable_re expansion_symbol = '<' elif phase == PHASE_LATE: variable_re = late_variable_re expansion_symbol = '>' elif phase == PHASE_LATELATE: variable_re = latelate_variable_re expansion_symbol = '^' else: assert False input_str = str(input) if IsStrCanonicalInt(input_str): return int(input_str) # Do a quick scan to determine if an expensive regex search is warranted. if expansion_symbol not in input_str: return input_str # Get the entire list of matches as a list of MatchObject instances. # (using findall here would return strings instead of MatchObjects). matches = list(variable_re.finditer(input_str)) if not matches: return input_str output = input_str # Reverse the list of matches so that replacements are done right-to-left. # That ensures that earlier replacements won't mess up the string in a # way that causes later calls to find the earlier substituted text instead # of what's intended for replacement. matches.reverse() for match_group in matches: match = match_group.groupdict() gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Matches: %r", match) # match['replace'] is the substring to look for, match['type'] # is the character code for the replacement type (< > <! >! <\| >\| <@ # >@ <!@ >!@), match['is_array'] contains a '[' for command # arrays, and match['content'] is the name of the variable (< >) # or command to run (<! >!). match['command_string'] is an optional # command string. Currently, only 'pymod_do_main' is supported. # run_command is true if a ! variant is used. run_command = '!' in match['type'] command_string = match['command_string'] # file_list is true if a \| variant is used. file_list = '\|' in match['type'] # Capture these now so we can adjust them later. replace_start = match_group.start('replace') replace_end = match_group.end('replace') # Find the ending paren, and re-evaluate the contained string. (c_start, c_end) = FindEnclosingBracketGroup(input_str[replace_start:]) # Adjust the replacement range to match the entire command # found by FindEnclosingBracketGroup (since the variable_re # probably doesn't match the entire command if it contained # nested variables). replace_end = replace_start + c_end # Find the "real" replacement, matching the appropriate closing # paren, and adjust the replacement start and end. replacement = input_str[replace_start:replace_end] # Figure out what the contents of the variable parens are. contents_start = replace_start + c_start + 1 contents_end = replace_end - 1 contents = input_str[contents_start:contents_end] # Do filter substitution now for <\|(). # Admittedly, this is different than the evaluation order in other # contexts. However, since filtration has no chance to run on <\|(), # this seems like the only obvious way to give them access to filters. if file_list: processed_variables = gyp.simple_copy.deepcopy(variables) ProcessListFiltersInDict(contents, processed_variables) # Recurse to expand variables in the contents contents = ExpandVariables(contents, phase, processed_variables, build_file) else: # Recurse to expand variables in the contents contents = ExpandVariables(contents, phase, variables, build_file) # Strip off leading/trailing whitespace so that variable matches are # simpler below (and because they are rarely needed). contents = contents.strip() # expand_to_list is true if an @ variant is used. In that case, # the expansion should result in a list. Note that the caller # is to be expecting a list in return, and not all callers do # because not all are working in list context. Also, for list # expansions, there can be no other text besides the variable # expansion in the input string. expand_to_list = '@' in match['type'] and input_str == replacement if run_command or file_list: # Find the build file's directory, so commands can be run or file lists # generated relative to it. build_file_dir = os.path.dirname(build_file) if build_file_dir == '' and not file_list: # If build_file is just a leaf filename indicating a file in the # current directory, build_file_dir might be an empty string. Set # it to None to signal to subprocess.Popen that it should run the # command in the current directory. build_file_dir = None # Support <\|(listfile.txt ...) which generates a file # containing items from a gyp list, generated at gyp time. # This works around actions/rules which have more inputs than will # fit on the command line. if file_list: if type(contents) is list: contents_list = contents else: contents_list = contents.split(' ') replacement = contents_list[0] if os.path.isabs(replacement): raise GypError('\| cannot handle absolute paths, got "%s"' % replacement) if not generator_filelist_paths: path = os.path.join(build_file_dir, replacement) else: if os.path.isabs(build_file_dir): toplevel = generator_filelist_paths['toplevel'] rel_build_file_dir = gyp.common.RelativePath(build_file_dir, toplevel) else: rel_build_file_dir = build_file_dir qualified_out_dir = generator_filelist_paths['qualified_out_dir'] path = os.path.join(qualified_out_dir, rel_build_file_dir, replacement) gyp.common.EnsureDirExists(path) replacement = gyp.common.RelativePath(path, build_file_dir) f = gyp.common.WriteOnDiff(path) for i in contents_list[1:]: f.write('%s\n' % i) f.close() elif run_command: use_shell = True if match['is_array']: contents = eval(contents) use_shell = False # Check for a cached value to avoid executing commands, or generating # file lists more than once. The cache key contains the command to be # run as well as the directory to run it from, to account for commands # that depend on their current directory. # TODO(http://code.google.com/p/gyp/issues/detail?id=111): In theory, # someone could author a set of GYP files where each time the command # is invoked it produces different output by design. When the need # arises, the syntax should be extended to support no caching off a # command's output so it is run every time. cache_key = (str(contents), build_file_dir) cached_value = cached_command_results.get(cache_key, None) if cached_value is None: gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Executing command '%s' in directory '%s'", contents, build_file_dir) replacement = '' if command_string == 'pymod_do_main': # <!pymod_do_main(modulename param eters) loads \|modulename\| as a # python module and then calls that module's DoMain() function, # passing ["param", "eters"] as a single list argument. For modules # that don't load quickly, this can be faster than # <!(python modulename param eters). Do this in \|build_file_dir\|. oldwd = os.getcwd() # Python doesn't like os.open('.'): no fchdir. if build_file_dir: # build_file_dir may be None (see above). os.chdir(build_file_dir) try: parsed_contents = shlex.split(contents) try: py_module = __import__(parsed_contents[0]) except ImportError as e: raise GypError("Error importing pymod_do_main" "module (%s): %s" % (parsed_contents[0], e)) replacement = str(py_module.DoMain(parsed_contents[1:])).rstrip() finally: os.chdir(oldwd) assert replacement != None elif command_string: raise GypError("Unknown command string '%s' in '%s'." % (command_string, contents)) else: # Fix up command with platform specific workarounds. contents = FixupPlatformCommand(contents) p = subprocess.Popen(contents, shell=use_shell, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE, cwd=build_file_dir) p_stdout, p_stderr = p.communicate('') if p.wait() != 0 or p_stderr: sys.stderr.write(p_stderr) # Simulate check_call behavior, since check_call only exists # in python 2.5 and later. raise GypError("Call to '%s' returned exit status %d." % (contents, p.returncode)) replacement = p_stdout.rstrip() cached_command_results[cache_key] = replacement else: gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Had cache value for command '%s' in directory '%s'", contents,build_file_dir) replacement = cached_value else: if not contents in variables: if contents[-1] in ['!', '/']: # In order to allow cross-compiles (nacl) to happen more naturally, # we will allow references to >(sources/) etc. to resolve to # and empty list if undefined. This allows actions to: # 'action!': [ # '>@(_sources!)', # ], # 'action/': [ # '>@(_sources/)', # ], replacement = [] else: raise GypError('Undefined variable ' + contents + ' in ' + build_file) else: replacement = variables[contents] if type(replacement) is list: for item in replacement: if not contents[-1] == '/' and type(item) not in (str, int): raise GypError('Variable ' + contents + ' must expand to a string or list of strings; ' + 'list contains a ' + item.__class__.__name__) # Run through the list and handle variable expansions in it. Since # the list is guaranteed not to contain dicts, this won't do anything # with conditions sections. ProcessVariablesAndConditionsInList(replacement, phase, variables, build_file) elif type(replacement) not in (str, int): raise GypError('Variable ' + contents + ' must expand to a string or list of strings; ' + 'found a ' + replacement.__class__.__name__) if expand_to_list: # Expanding in list context. It's guaranteed that there's only one # replacement to do in \|input_str\| and that it's this replacement. See # above. if type(replacement) is list: # If it's already a list, make a copy. output = replacement[:] else: # Split it the same way sh would split arguments. output = shlex.split(str(replacement)) else: # Expanding in string context. encoded_replacement = '' if type(replacement) is list: # When expanding a list into string context, turn the list items # into a string in a way that will work with a subprocess call. # # TODO(mark): This isn't completely correct. This should # call a generator-provided function that observes the # proper list-to-argument quoting rules on a specific # platform instead of just calling the POSIX encoding # routine. encoded_replacement = gyp.common.EncodePOSIXShellList(replacement) else: encoded_replacement = replacement output = output[:replace_start] + str(encoded_replacement) + \ output[replace_end:] # Prepare for the next match iteration. input_str = output if output == input: gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Found only identity matches on %r, avoiding infinite " "recursion.", output) else: # Look for more matches now that we've replaced some, to deal with # expanding local variables (variables defined in the same # variables block as this one). gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Found output %r, recursing.", output) if type(output) is list: if output and type(output[0]) is list: # Leave output alone if it's a list of lists. # We don't want such lists to be stringified. pass else: new_output = [] for item in output: new_output.append( ExpandVariables(item, phase, variables, build_file)) output = new_output else: output = ExpandVariables(output, phase, variables, build_file) # Convert all strings that are canonically-represented integers into integers. if type(output) is list: for index in range(0, len(output)): if IsStrCanonicalInt(output[index]): output[index] = int(output[index]) elif IsStrCanonicalInt(output): output = int(output) return output # The same condition is often evaluated over and over again so it # makes sense to cache as much as possible between evaluations. cached_conditions_asts = {} def EvalCondition(condition, conditions_key, phase, variables, build_file): """Returns the dict that should be used or None if the result was that nothing should be used.""" if type(condition) is not list: raise GypError(conditions_key + ' must be a list') if len(condition) < 2: # It's possible that condition[0] won't work in which case this # attempt will raise its own IndexError. That's probably fine. raise GypError(conditions_key + ' ' + condition[0] + ' must be at least length 2, not ' + str(len(condition))) i = 0 result = None while i < len(condition): cond_expr = condition[i] true_dict = condition[i + 1] if type(true_dict) is not dict: raise GypError('{} {} must be followed by a dictionary, not {}'.format( conditions_key, cond_expr, type(true_dict))) if len(condition) > i + 2 and type(condition[i + 2]) is dict: false_dict = condition[i + 2] i = i + 3 if i != len(condition): raise GypError('{} {} has {} unexpected trailing items'.format( conditions_key, cond_expr, len(condition) - i)) else: false_dict = None i = i + 2 if result == None: result = EvalSingleCondition( cond_expr, true_dict, false_dict, phase, variables, build_file) return result def EvalSingleCondition( cond_expr, true_dict, false_dict, phase, variables, build_file): """Returns true_dict if cond_expr evaluates to true, and false_dict otherwise.""" # Do expansions on the condition itself. Since the conditon can naturally # contain variable references without needing to resort to GYP expansion # syntax, this is of dubious value for variables, but someone might want to # use a command expansion directly inside a condition. cond_expr_expanded = ExpandVariables(cond_expr, phase, variables, build_file) if type(cond_expr_expanded) not in (str, int): raise ValueError( 'Variable expansion in this context permits str and int ' + \ 'only, found ' + cond_expr_expanded.__class__.__name__) try: if cond_expr_expanded in cached_conditions_asts: ast_code = cached_conditions_asts[cond_expr_expanded] else: ast_code = compile(cond_expr_expanded, '<string>', 'eval') cached_conditions_asts[cond_expr_expanded] = ast_code if eval(ast_code, {'__builtins__': None}, variables): return true_dict return false_dict except SyntaxError: e = sys.exc_info()[1] syntax_error = SyntaxError('%s while evaluating condition \'%s\' in %s ' 'at character %d.' % (str(e.args[0]), e.text, build_file, e.offset), e.filename, e.lineno, e.offset, e.text) raise syntax_error except NameError: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while evaluating condition \'%s\' in %s' % (cond_expr_expanded, build_file)) raise GypError(e) def ProcessConditionsInDict(the_dict, phase, variables, build_file): # Process a 'conditions' or 'target_conditions' section in the_dict, # depending on phase. # early -> conditions # late -> target_conditions # latelate -> no conditions # # Each item in a conditions list consists of cond_expr, a string expression # evaluated as the condition, and true_dict, a dict that will be merged into # the_dict if cond_expr evaluates to true. Optionally, a third item, # false_dict, may be present. false_dict is merged into the_dict if # cond_expr evaluates to false. # # Any dict merged into the_dict will be recursively processed for nested # conditionals and other expansions, also according to phase, immediately # prior to being merged. if phase == PHASE_EARLY: conditions_key = 'conditions' elif phase == PHASE_LATE: conditions_key = 'target_conditions' elif phase == PHASE_LATELATE: return else: assert False if not conditions_key in the_dict: return conditions_list = the_dict[conditions_key] # Unhook the conditions list, it's no longer needed. del the_dict[conditions_key] for condition in conditions_list: merge_dict = EvalCondition(condition, conditions_key, phase, variables, build_file) if merge_dict != None: # Expand variables and nested conditinals in the merge_dict before # merging it. ProcessVariablesAndConditionsInDict(merge_dict, phase, variables, build_file) MergeDicts(the_dict, merge_dict, build_file, build_file) def LoadAutomaticVariablesFromDict(variables, the_dict): # Any keys with plain string values in the_dict become automatic variables. # The variable name is the key name with a "_" character prepended. for key, value in the_dict.items(): if type(value) in (str, int, list): variables['_' + key] = value # PYK: If `toolset` is in `the_dict`, map all {toolset}_x variables to the # value of `x`. if 'toolset' in the_dict: prefix = '%s_' % the_dict['toolset'] for key, value in variables.items(): if key.startswith(prefix) and isinstance(value, (str, int, list)): variables[key[len(prefix):]] = value if key == '%s_os' % the_dict['toolset']: variables['OS'] = value def LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key): # Any keys in the_dict's "variables" dict, if it has one, becomes a # variable. The variable name is the key name in the "variables" dict. # Variables that end with the % character are set only if they are unset in # the variables dict. the_dict_key is the name of the key that accesses # the_dict in the_dict's parent dict. If the_dict's parent is not a dict # (it could be a list or it could be parentless because it is a root dict), # the_dict_key will be None. for key, value in the_dict.get('variables', {}).items(): if type(value) not in (str, int, list): continue if key.endswith('%'): variable_name = key[:-1] if variable_name in variables: # If the variable is already set, don't set it. continue if the_dict_key is 'variables' and variable_name in the_dict: # If the variable is set without a % in the_dict, and the_dict is a # variables dict (making \|variables\| a varaibles sub-dict of a # variables dict), use the_dict's definition. value = the_dict[variable_name] else: variable_name = key variables[variable_name] = value def ProcessVariablesAndConditionsInDict(the_dict, phase, variables_in, build_file, the_dict_key=None): """Handle all variable and command expansion and conditional evaluation. This function is the public entry point for all variable expansions and conditional evaluations. The variables_in dictionary will not be modified by this function. """ # Make a copy of the variables_in dict that can be modified during the # loading of automatics and the loading of the variables dict. variables = variables_in.copy() LoadAutomaticVariablesFromDict(variables, the_dict) if 'variables' in the_dict: # Make sure all the local variables are added to the variables # list before we process them so that you can reference one # variable from another. They will be fully expanded by recursion # in ExpandVariables. for key, value in the_dict['variables'].items(): variables[key] = value # Handle the associated variables dict first, so that any variable # references within can be resolved prior to using them as variables. # Pass a copy of the variables dict to avoid having it be tainted. # Otherwise, it would have extra automatics added for everything that # should just be an ordinary variable in this scope. ProcessVariablesAndConditionsInDict(the_dict['variables'], phase, variables, build_file, 'variables') LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key) for key, value in the_dict.items(): # Skip "variables", which was already processed if present. if key != 'variables' and type(value) is str: expanded = ExpandVariables(value, phase, variables, build_file) if type(expanded) not in (str, int): raise ValueError( 'Variable expansion in this context permits str and int ' + \ 'only, found ' + expanded.__class__.__name__ + ' for ' + key) the_dict[key] = expanded # Variable expansion may have resulted in changes to automatics. Reload. # TODO(mark): Optimization: only reload if no changes were made. variables = variables_in.copy() LoadAutomaticVariablesFromDict(variables, the_dict) LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key) # Process conditions in this dict. This is done after variable expansion # so that conditions may take advantage of expanded variables. For example, # if the_dict contains: # {'type': '<(library_type)', # 'conditions': [['_type=="static_library"', { ... }]]}, # _type, as used in the condition, will only be set to the value of # library_type if variable expansion is performed before condition # processing. However, condition processing should occur prior to recursion # so that variables (both automatic and "variables" dict type) may be # adjusted by conditions sections, merged into the_dict, and have the # intended impact on contained dicts. # # This arrangement means that a "conditions" section containing a "variables" # section will only have those variables effective in subdicts, not in # the_dict. The workaround is to put a "conditions" section within a # "variables" section. For example: # {'conditions': [['os=="mac"', {'variables': {'define': 'IS_MAC'}}]], # 'defines': ['<(define)'], # 'my_subdict': {'defines': ['<(define)']}}, # will not result in "IS_MAC" being appended to the "defines" list in the # current scope but would result in it being appended to the "defines" list # within "my_subdict". By comparison: # {'variables': {'conditions': [['os=="mac"', {'define': 'IS_MAC'}]]}, # 'defines': ['<(define)'], # 'my_subdict': {'defines': ['<(define)']}}, # will append "IS_MAC" to both "defines" lists. # Evaluate conditions sections, allowing variable expansions within them # as well as nested conditionals. This will process a 'conditions' or # 'target_conditions' section, perform appropriate merging and recursive # conditional and variable processing, and then remove the conditions section # from the_dict if it is present. ProcessConditionsInDict(the_dict, phase, variables, build_file) # Conditional processing may have resulted in changes to automatics or the # variables dict. Reload. variables = variables_in.copy() LoadAutomaticVariablesFromDict(variables, the_dict) LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key) # Recurse into child dicts, or process child lists which may result in # further recursion into descendant dicts. for key, value in the_dict.items(): # Skip "variables" and string values, which were already processed if # present. if key == 'variables' or type(value) is str: continue if type(value) is dict: # Pass a copy of the variables dict so that subdicts can't influence # parents. ProcessVariablesAndConditionsInDict(value, phase, variables, build_file, key) elif type(value) is list: # The list itself can't influence the variables dict, and # ProcessVariablesAndConditionsInList will make copies of the variables # dict if it needs to pass it to something that can influence it. No # copy is necessary here. ProcessVariablesAndConditionsInList(value, phase, variables, build_file) elif type(value) is not int: raise TypeError('Unknown type ' + value.__class__.__name__ + \ ' for ' + key) def ProcessVariablesAndConditionsInList(the_list, phase, variables, build_file): # Iterate using an index so that new values can be assigned into the_list. index = 0 while index < len(the_list): item = the_list[index] if type(item) is dict: # Make a copy of the variables dict so that it won't influence anything # outside of its own scope. ProcessVariablesAndConditionsInDict(item, phase, variables, build_file) elif type(item) is list: ProcessVariablesAndConditionsInList(item, phase, variables, build_file) elif type(item) is str: expanded = ExpandVariables(item, phase, variables, build_file) if type(expanded) in (str, int): the_list[index] = expanded elif type(expanded) is list: the_list[index:index+1] = expanded index += len(expanded) # index now identifies the next item to examine. Continue right now # without falling into the index increment below. continue else: raise ValueError( 'Variable expansion in this context permits strings and ' + \ 'lists only, found ' + expanded.__class__.__name__ + ' at ' + \ index) elif type(item) is not int: raise TypeError('Unknown type ' + item.__class__.__name__ + \ ' at index ' + index) index = index + 1 def BuildTargetsDict(data): """Builds a dict mapping fully-qualified target names to their target dicts. \|data\| is a dict mapping loaded build files by pathname relative to the current directory. Values in \|data\| are build file contents. For each \|data\| value with a "targets" key, the value of the "targets" key is taken as a list containing target dicts. Each target's fully-qualified name is constructed from the pathname of the build file (\|data\| key) and its "target_name" property. These fully-qualified names are used as the keys in the returned dict. These keys provide access to the target dicts, the dicts in the "targets" lists. """ targets = {} for build_file in data['target_build_files']: for target in data[build_file].get('targets', []): target_name = gyp.common.QualifiedTarget(build_file, target['target_name'], target['toolset']) if target_name in targets: raise GypError('Duplicate target definitions for ' + target_name) targets[target_name] = target return targets def QualifyDependencies(targets): """Make dependency links fully-qualified relative to the current directory. \|targets\| is a dict mapping fully-qualified target names to their target dicts. For each target in this dict, keys known to contain dependency links are examined, and any dependencies referenced will be rewritten so that they are fully-qualified and relative to the current directory. All rewritten dependencies are suitable for use as keys to \|targets\| or a similar dict. """ all_dependency_sections = [dep + op for dep in dependency_sections for op in ('', '!', '/')] for target, target_dict in targets.items(): target_build_file = gyp.common.BuildFile(target) toolset = target_dict['toolset'] for dependency_key in all_dependency_sections: dependencies = target_dict.get(dependency_key, []) for index in range(0, len(dependencies)): dep_file, dep_target, dep_toolset = gyp.common.ResolveTarget( target_build_file, dependencies[index], toolset) if not multiple_toolsets: # Ignore toolset specification in the dependency if it is specified. dep_toolset = toolset dependency = gyp.common.QualifiedTarget(dep_file, dep_target, dep_toolset) dependencies[index] = dependency # Make sure anything appearing in a list other than "dependencies" also # appears in the "dependencies" list. if dependency_key != 'dependencies' and \ dependency not in target_dict['dependencies']: raise GypError('Found ' + dependency + ' in ' + dependency_key + ' of ' + target + ', but not in dependencies') def ExpandWildcardDependencies(targets, data): """Expands dependencies specified as build_file:. For each target in \|targets\|, examines sections containing links to other targets. If any such section contains a link of the form build_file:, it is taken as a wildcard link, and is expanded to list each target in build_file. The \|data\| dict provides access to build file dicts. Any target that does not wish to be included by wildcard can provide an optional "suppress_wildcard" key in its target dict. When present and true, a wildcard dependency link will not include such targets. All dependency names, including the keys to \|targets\| and the values in each dependency list, must be qualified when this function is called. """ for target, target_dict in targets.items(): toolset = target_dict['toolset'] target_build_file = gyp.common.BuildFile(target) for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) # Loop this way instead of "for dependency in" or "for index in range" # because the dependencies list will be modified within the loop body. index = 0 while index < len(dependencies): (dependency_build_file, dependency_target, dependency_toolset) = \ gyp.common.ParseQualifiedTarget(dependencies[index]) if dependency_target != '' and dependency_toolset != '': # Not a wildcard. Keep it moving. index = index + 1 continue if dependency_build_file == target_build_file: # It's an error for a target to depend on all other targets in # the same file, because a target cannot depend on itself. raise GypError('Found wildcard in ' + dependency_key + ' of ' + target + ' referring to same build file') # Take the wildcard out and adjust the index so that the next # dependency in the list will be processed the next time through the # loop. del dependencies[index] index = index - 1 # Loop through the targets in the other build file, adding them to # this target's list of dependencies in place of the removed # wildcard. dependency_target_dicts = data[dependency_build_file]['targets'] for dependency_target_dict in dependency_target_dicts: if int(dependency_target_dict.get('suppress_wildcard', False)): continue dependency_target_name = dependency_target_dict['target_name'] if (dependency_target != '' and dependency_target != dependency_target_name): continue dependency_target_toolset = dependency_target_dict['toolset'] if (dependency_toolset != '' and dependency_toolset != dependency_target_toolset): continue dependency = gyp.common.QualifiedTarget(dependency_build_file, dependency_target_name, dependency_target_toolset) index = index + 1 dependencies.insert(index, dependency) index = index + 1 def Unify(l): """Removes duplicate elements from l, keeping the first element.""" seen = {} return [seen.setdefault(e, e) for e in l if e not in seen] def RemoveDuplicateDependencies(targets): """Makes sure every dependency appears only once in all targets's dependency lists.""" for target_name, target_dict in targets.items(): for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) if dependencies: target_dict[dependency_key] = Unify(dependencies) def Filter(l, item): """Removes item from l.""" res = {} return [res.setdefault(e, e) for e in l if e != item] def RemoveSelfDependencies(targets): """Remove self dependencies from targets that have the prune_self_dependency variable set.""" for target_name, target_dict in targets.items(): for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) if dependencies: for t in dependencies: if t == target_name: if targets[t].get('variables', {}).get('prune_self_dependency', 0): target_dict[dependency_key] = Filter(dependencies, target_name) def RemoveLinkDependenciesFromNoneTargets(targets): """Remove dependencies having the 'link_dependency' attribute from the 'none' targets.""" for target_name, target_dict in targets.items(): for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) if dependencies: for t in dependencies: if target_dict.get('type', None) == 'none': if targets[t].get('variables', {}).get('link_dependency', 0): target_dict[dependency_key] = \ Filter(target_dict[dependency_key], t) class DependencyGraphNode(object): """ Attributes: ref: A reference to an object that this DependencyGraphNode represents. dependencies: List of DependencyGraphNodes on which this one depends. dependents: List of DependencyGraphNodes that depend on this one. """ class CircularException(GypError): pass def __init__(self, ref): self.ref = ref self.dependencies = [] self.dependents = [] def __repr__(self): return '<DependencyGraphNode: %r>' % self.ref def FlattenToList(self): # flat_list is the sorted list of dependencies - actually, the list items # are the "ref" attributes of DependencyGraphNodes. Every target will # appear in flat_list after all of its dependencies, and before all of its # dependents. flat_list = OrderedSet() # in_degree_zeros is the list of DependencyGraphNodes that have no # dependencies not in flat_list. Initially, it is a copy of the children # of this node, because when the graph was built, nodes with no # dependencies were made implicit dependents of the root node. in_degree_zeros = set(self.dependents[:]) while in_degree_zeros: # Nodes in in_degree_zeros have no dependencies not in flat_list, so they # can be appended to flat_list. Take these nodes out of in_degree_zeros # as work progresses, so that the next node to process from the list can # always be accessed at a consistent position. node = in_degree_zeros.pop() flat_list.add(node.ref) # Look at dependents of the node just added to flat_list. Some of them # may now belong in in_degree_zeros. for node_dependent in node.dependents: is_in_degree_zero = True # TODO: We want to check through the # node_dependent.dependencies list but if it's long and we # always start at the beginning, then we get O(n^2) behaviour. for node_dependent_dependency in node_dependent.dependencies: if not node_dependent_dependency.ref in flat_list: # The dependent one or more dependencies not in flat_list. There # will be more chances to add it to flat_list when examining # it again as a dependent of those other dependencies, provided # that there are no cycles. is_in_degree_zero = False break if is_in_degree_zero: # All of the dependent's dependencies are already in flat_list. Add # it to in_degree_zeros where it will be processed in a future # iteration of the outer loop. in_degree_zeros.add(node_dependent) return list(flat_list) def FindCycles(self): """ Returns a list of cycles in the graph, where each cycle is its own list. """ results = [] visited = set() def Visit(node, path): for child in node.dependents: if child in path: results.append([child] + path[:path.index(child) + 1]) elif not child in visited: visited.add(child) Visit(child, [child] + path) visited.add(self) Visit(self, [self]) return results def DirectDependencies(self, dependencies=None): """Returns a list of just direct dependencies.""" if dependencies == None: dependencies = [] for dependency in self.dependencies: # Check for None, corresponding to the root node. if dependency.ref != None and dependency.ref not in dependencies: dependencies.append(dependency.ref) return dependencies def _AddImportedDependencies(self, targets, dependencies=None): """Given a list of direct dependencies, adds indirect dependencies that other dependencies have declared to export their settings. This method does not operate on self. Rather, it operates on the list of dependencies in the \|dependencies\| argument. For each dependency in that list, if any declares that it exports the settings of one of its own dependencies, those dependencies whose settings are "passed through" are added to the list. As new items are added to the list, they too will be processed, so it is possible to import settings through multiple levels of dependencies. This method is not terribly useful on its own, it depends on being "primed" with a list of direct dependencies such as one provided by DirectDependencies. DirectAndImportedDependencies is intended to be the public entry point. """ if dependencies == None: dependencies = [] index = 0 while index < len(dependencies): dependency = dependencies[index] dependency_dict = targets[dependency] # Add any dependencies whose settings should be imported to the list # if not already present. Newly-added items will be checked for # their own imports when the list iteration reaches them. # Rather than simply appending new items, insert them after the # dependency that exported them. This is done to more closely match # the depth-first method used by DeepDependencies. add_index = 1 for imported_dependency in \ dependency_dict.get('export_dependent_settings', []): if imported_dependency not in dependencies: dependencies.insert(index + add_index, imported_dependency) add_index = add_index + 1 index = index + 1 return dependencies def DirectAndImportedDependencies(self, targets, dependencies=None): """Returns a list of a target's direct dependencies and all indirect dependencies that a dependency has advertised settings should be exported through the dependency for. """ dependencies = self.DirectDependencies(dependencies) return self._AddImportedDependencies(targets, dependencies) def DeepDependencies(self, dependencies=None): """Returns an OrderedSet of all of a target's dependencies, recursively.""" if dependencies is None: # Using a list to get ordered output and a set to do fast "is it # already added" checks. dependencies = OrderedSet() for dependency in self.dependencies: # Check for None, corresponding to the root node. if dependency.ref is None: continue if dependency.ref not in dependencies: dependencies.add(dependency.ref) dependency.DeepDependencies(dependencies) return dependencies def _LinkDependenciesInternal(self, targets, include_shared_libraries, dependencies=None, initial=True): """Returns an OrderedSet of dependency targets that are linked into this target. This function has a split personality, depending on the setting of \|initial\|. Outside callers should always leave \|initial\| at its default setting. When adding a target to the list of dependencies, this function will recurse into itself with \|initial\| set to False, to collect dependencies that are linked into the linkable target for which the list is being built. If \|include_shared_libraries\| is False, the resulting dependencies will not include shared_library targets that are linked into this target. """ if dependencies is None: # Using a list to get ordered output and a set to do fast "is it # already added" checks. dependencies = OrderedSet() # Check for None, corresponding to the root node. if self.ref is None: return dependencies # It's kind of sucky that \|targets\| has to be passed into this function, # but that's presently the easiest way to access the target dicts so that # this function can find target types. if 'target_name' not in targets[self.ref]: raise GypError("Missing 'target_name' field in target.") if 'type' not in targets[self.ref]: raise GypError("Missing 'type' field in target %s" % targets[self.ref]['target_name']) target_type = targets[self.ref]['type'] is_linkable = target_type in linkable_types if initial and not is_linkable: # If this is the first target being examined and it's not linkable, # return an empty list of link dependencies, because the link # dependencies are intended to apply to the target itself (initial is # True) and this target won't be linked. return dependencies # Don't traverse 'none' targets if explicitly excluded. if (target_type == 'none' and not targets[self.ref].get('dependencies_traverse', True)): dependencies.add(self.ref) return dependencies # Executables and loadable modules are already fully and finally linked. # Nothing else can be a link dependency of them, there can only be # dependencies in the sense that a dependent target might run an # executable or load the loadable_module. if not initial and target_type in ('executable', 'loadable_module'): return dependencies # Shared libraries are already fully linked. They should only be included # in \|dependencies\| when adjusting static library dependencies (in order to # link against the shared_library's import lib), but should not be included # in \|dependencies\| when propagating link_settings. # The \|include_shared_libraries\| flag controls which of these two cases we # are handling. if (not initial and target_type == 'shared_library' and not include_shared_libraries): return dependencies # The target is linkable, add it to the list of link dependencies. if self.ref not in dependencies: dependencies.add(self.ref) if initial or not is_linkable: # If this is a subsequent target and it's linkable, don't look any # further for linkable dependencies, as they'll already be linked into # this target linkable. Always look at dependencies of the initial # target, and always look at dependencies of non-linkables. for dependency in self.dependencies: dependency._LinkDependenciesInternal(targets, include_shared_libraries, dependencies, False) return dependencies def DependenciesForLinkSettings(self, targets): """ Returns a list of dependency targets whose link_settings should be merged into this target. """ # TODO(sbaig) Currently, chrome depends on the bug that shared libraries' # link_settings are propagated. So for now, we will allow it, unless the # 'allow_sharedlib_linksettings_propagation' flag is explicitly set to # False. Once chrome is fixed, we can remove this flag. include_shared_libraries = \ targets[self.ref].get('allow_sharedlib_linksettings_propagation', True) return self._LinkDependenciesInternal(targets, include_shared_libraries) def DependenciesToLinkAgainst(self, targets): """ Returns a list of dependency targets that are linked into this target. """ return self._LinkDependenciesInternal(targets, True) def BuildDependencyList(targets): # Create a DependencyGraphNode for each target. Put it into a dict for easy # access. dependency_nodes = {} for target, spec in targets.items(): if target not in dependency_nodes: dependency_nodes[target] = DependencyGraphNode(target) # Set up the dependency links. Targets that have no dependencies are treated # as dependent on root_node. root_node = DependencyGraphNode(None) for target, spec in targets.items(): target_node = dependency_nodes[target] target_build_file = gyp.common.BuildFile(target) dependencies = spec.get('dependencies') if not dependencies: target_node.dependencies = [root_node] root_node.dependents.append(target_node) else: for dependency in dependencies: dependency_node = dependency_nodes.get(dependency) if not dependency_node: raise GypError("Dependency '%s' not found while " "trying to load target %s" % (dependency, target)) target_node.dependencies.append(dependency_node) dependency_node.dependents.append(target_node) flat_list = root_node.FlattenToList() # If there's anything left unvisited, there must be a circular dependency # (cycle). if len(flat_list) != len(targets): if not root_node.dependents: # If all targets have dependencies, add the first target as a dependent # of root_node so that the cycle can be discovered from root_node. target = targets.keys()[0] target_node = dependency_nodes[target] target_node.dependencies.append(root_node) root_node.dependents.append(target_node) cycles = [] for cycle in root_node.FindCycles(): paths = [node.ref for node in cycle] cycles.append('Cycle: %s' % ' -> '.join(paths)) raise DependencyGraphNode.CircularException( 'Cycles in dependency graph detected:\n' + '\n'.join(cycles)) return [dependency_nodes, flat_list] def VerifyNoGYPFileCircularDependencies(targets): # Create a DependencyGraphNode for each gyp file containing a target. Put # it into a dict for easy access. dependency_nodes = {} for target in targets.keys(): build_file = gyp.common.BuildFile(target) if not build_file in dependency_nodes: dependency_nodes[build_file] = DependencyGraphNode(build_file) # Set up the dependency links. for target, spec in targets.items(): build_file = gyp.common.BuildFile(target) build_file_node = dependency_nodes[build_file] target_dependencies = spec.get('dependencies', []) for dependency in target_dependencies: try: dependency_build_file = gyp.common.BuildFile(dependency) except GypError: e = sys.exc_info()[1] gyp.common.ExceptionAppend( e, 'while computing dependencies of .gyp file %s' % build_file) raise if dependency_build_file == build_file: # A .gyp file is allowed to refer back to itself. continue dependency_node = dependency_nodes.get(dependency_build_file) if not dependency_node: raise GypError("Dependancy '%s' not found" % dependency_build_file) if dependency_node not in build_file_node.dependencies: build_file_node.dependencies.append(dependency_node) dependency_node.dependents.append(build_file_node) # Files that have no dependencies are treated as dependent on root_node. root_node = DependencyGraphNode(None) for build_file_node in dependency_nodes.values(): if len(build_file_node.dependencies) == 0: build_file_node.dependencies.append(root_node) root_node.dependents.append(build_file_node) flat_list = root_node.FlattenToList() # If there's anything left unvisited, there must be a circular dependency # (cycle). if len(flat_list) != len(dependency_nodes): if not root_node.dependents: # If all files have dependencies, add the first file as a dependent # of root_node so that the cycle can be discovered from root_node. file_node = dependency_nodes.values()[0] file_node.dependencies.append(root_node) root_node.dependents.append(file_node) cycles = [] for cycle in root_node.FindCycles(): paths = [node.ref for node in cycle] cycles.append('Cycle: %s' % ' -> '.join(paths)) raise DependencyGraphNode.CircularException( 'Cycles in .gyp file dependency graph detected:\n' + '\n'.join(cycles)) def DoDependentSettings(key, flat_list, targets, dependency_nodes): # key should be one of all_dependent_settings, direct_dependent_settings, # or link_settings. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) if key == 'all_dependent_settings': dependencies = dependency_nodes[target].DeepDependencies() elif key == 'direct_dependent_settings': dependencies = \ dependency_nodes[target].DirectAndImportedDependencies(targets) elif key == 'link_settings': dependencies = \ dependency_nodes[target].DependenciesForLinkSettings(targets) else: raise GypError("DoDependentSettings doesn't know how to determine " 'dependencies for ' + key) for dependency in dependencies: dependency_dict = targets[dependency] if not key in dependency_dict: continue dependency_build_file = gyp.common.BuildFile(dependency) MergeDicts(target_dict, dependency_dict[key], build_file, dependency_build_file) def AdjustStaticLibraryDependencies(flat_list, targets, dependency_nodes, sort_dependencies): # Recompute target "dependencies" properties. For each static library # target, remove "dependencies" entries referring to other static libraries, # unless the dependency has the "hard_dependency" attribute set. For each # linkable target, add a "dependencies" entry referring to all of the # target's computed list of link dependencies (including static libraries # if no such entry is already present. for target in flat_list: target_dict = targets[target] target_type = target_dict['type'] if target_type == 'static_library': if not 'dependencies' in target_dict: continue target_dict['dependencies_original'] = target_dict.get( 'dependencies', [])[:] # A static library should not depend on another static library unless # the dependency relationship is "hard," which should only be done when # a dependent relies on some side effect other than just the build # product, like a rule or action output. Further, if a target has a # non-hard dependency, but that dependency exports a hard dependency, # the non-hard dependency can safely be removed, but the exported hard # dependency must be added to the target to keep the same dependency # ordering. dependencies = \ dependency_nodes[target].DirectAndImportedDependencies(targets) index = 0 while index < len(dependencies): dependency = dependencies[index] dependency_dict = targets[dependency] # Remove every non-hard static library dependency and remove every # non-static library dependency that isn't a direct dependency. if (dependency_dict['type'] == 'static_library' and \ not dependency_dict.get('hard_dependency', False)) or \ (dependency_dict['type'] != 'static_library' and \ not dependency in target_dict['dependencies']): # Take the dependency out of the list, and don't increment index # because the next dependency to analyze will shift into the index # formerly occupied by the one being removed. del dependencies[index] else: index = index + 1 # Update the dependencies. If the dependencies list is empty, it's not # needed, so unhook it. if len(dependencies) > 0: target_dict['dependencies'] = dependencies else: del target_dict['dependencies'] elif target_type in linkable_types: # Get a list of dependency targets that should be linked into this # target. Add them to the dependencies list if they're not already # present. link_dependencies = \ dependency_nodes[target].DependenciesToLinkAgainst(targets) for dependency in link_dependencies: if dependency == target: continue if not 'dependencies' in target_dict: target_dict['dependencies'] = [] if not dependency in target_dict['dependencies']: target_dict['dependencies'].append(dependency) # Sort the dependencies list in the order from dependents to dependencies. # e.g. If A and B depend on C and C depends on D, sort them in A, B, C, D. # Note: flat_list is already sorted in the order from dependencies to # dependents. if sort_dependencies and 'dependencies' in target_dict: target_dict['dependencies'] = [dep for dep in reversed(flat_list) if dep in target_dict['dependencies']] # Initialize this here to speed up MakePathRelative. exception_re = re.compile(r'''["']?[-/$<>^]''') def MakePathRelative(to_file, fro_file, item): # If item is a relative path, it's relative to the build file dict that it's # coming from. Fix it up to make it relative to the build file dict that # it's going into. # Exception: any \|item\| that begins with these special characters is # returned without modification. # / Used when a path is already absolute (shortcut optimization; # such paths would be returned as absolute anyway) # $ Used for build environment variables # - Used for some build environment flags (such as -lapr-1 in a # "libraries" section) # < Used for our own variable and command expansions (see ExpandVariables) # > Used for our own variable and command expansions (see ExpandVariables) # ^ Used for our own variable and command expansions (see ExpandVariables) # # "/' Used when a value is quoted. If these are present, then we # check the second character instead. # if to_file == fro_file or exception_re.match(item): return item else: # TODO(dglazkov) The backslash/forward-slash replacement at the end is a # temporary measure. This should really be addressed by keeping all paths # in POSIX until actual project generation. ret = os.path.normpath(os.path.join( gyp.common.RelativePath(os.path.dirname(fro_file), os.path.dirname(to_file)), item)).replace('\\', '/') if item[-1] == '/': ret += '/' return ret def MergeLists(to, fro, to_file, fro_file, is_paths=False, append=True): # Python documentation recommends objects which do not support hash # set this value to None. Python library objects follow this rule. is_hashable = lambda val: val.__hash__ # If x is hashable, returns whether x is in s. Else returns whether x is in l. def is_in_set_or_list(x, s, l): if is_hashable(x): return x in s return x in l prepend_index = 0 # Make membership testing of hashables in \|to\| (in particular, strings) # faster. hashable_to_set = set(x for x in to if is_hashable(x)) for item in fro: singleton = False if type(item) in (str, int): # The cheap and easy case. if is_paths: to_item = MakePathRelative(to_file, fro_file, item) else: to_item = item if not (type(item) is str and item.startswith('-')): # Any string that doesn't begin with a "-" is a singleton - it can # only appear once in a list, to be enforced by the list merge append # or prepend. singleton = True elif type(item) is dict: # Make a copy of the dictionary, continuing to look for paths to fix. # The other intelligent aspects of merge processing won't apply because # item is being merged into an empty dict. to_item = {} MergeDicts(to_item, item, to_file, fro_file) elif type(item) is list: # Recurse, making a copy of the list. If the list contains any # descendant dicts, path fixing will occur. Note that here, custom # values for is_paths and append are dropped; those are only to be # applied to \|to\| and \|fro\|, not sublists of \|fro\|. append shouldn't # matter anyway because the new \|to_item\| list is empty. to_item = [] MergeLists(to_item, item, to_file, fro_file) else: raise TypeError( 'Attempt to merge list item of unsupported type ' + \ item.__class__.__name__) if append: # If appending a singleton that's already in the list, don't append. # This ensures that the earliest occurrence of the item will stay put. if not singleton or not is_in_set_or_list(to_item, hashable_to_set, to): to.append(to_item) if is_hashable(to_item): hashable_to_set.add(to_item) else: # If prepending a singleton that's already in the list, remove the # existing instance and proceed with the prepend. This ensures that the # item appears at the earliest possible position in the list. while singleton and to_item in to: to.remove(to_item) # Don't just insert everything at index 0. That would prepend the new # items to the list in reverse order, which would be an unwelcome # surprise. to.insert(prepend_index, to_item) if is_hashable(to_item): hashable_to_set.add(to_item) prepend_index = prepend_index + 1 def MergeDicts(to, fro, to_file, fro_file): # I wanted to name the parameter "from" but it's a Python keyword... for k, v in fro.items(): # It would be nice to do "if not k in to: to[k] = v" but that wouldn't give # copy semantics. Something else may want to merge from the \|fro\| dict # later, and having the same dict ref pointed to twice in the tree isn't # what anyone wants considering that the dicts may subsequently be # modified. if k in to: bad_merge = False if type(v) in (str, int): if type(to[k]) not in (str, int): bad_merge = True elif type(v) is not type(to[k]): bad_merge = True if bad_merge: raise TypeError( 'Attempt to merge dict value of type ' + v.__class__.__name__ + \ ' into incompatible type ' + to[k].__class__.__name__ + \ ' for key ' + k) if type(v) in (str, int): # Overwrite the existing value, if any. Cheap and easy. is_path = IsPathSection(k) if is_path: to[k] = MakePathRelative(to_file, fro_file, v) else: to[k] = v elif type(v) is dict: # Recurse, guaranteeing copies will be made of objects that require it. if not k in to: to[k] = {} MergeDicts(to[k], v, to_file, fro_file) elif type(v) is list: # Lists in dicts can be merged with different policies, depending on # how the key in the "from" dict (k, the from-key) is written. # # If the from-key has ...the to-list will have this action # this character appended:... applied when receiving the from-list: # = replace # + prepend # ? set, only if to-list does not yet exist # (none) append # # This logic is list-specific, but since it relies on the associated # dict key, it's checked in this dict-oriented function. ext = k[-1] append = True if ext == '=': list_base = k[:-1] lists_incompatible = [list_base, list_base + '?'] to[list_base] = [] elif ext == '+': list_base = k[:-1] lists_incompatible = [list_base + '=', list_base + '?'] append = False elif ext == '?': list_base = k[:-1] lists_incompatible = [list_base, list_base + '=', list_base + '+'] else: list_base = k lists_incompatible = [list_base + '=', list_base + '?'] # Some combinations of merge policies appearing together are meaningless. # It's stupid to replace and append simultaneously, for example. Append # and prepend are the only policies that can coexist. for list_incompatible in lists_incompatible: if list_incompatible in fro: raise GypError('Incompatible list policies ' + k + ' and ' + list_incompatible) if list_base in to: if ext == '?': # If the key ends in "?", the list will only be merged if it doesn't # already exist. continue elif type(to[list_base]) is not list: # This may not have been checked above if merging in a list with an # extension character. raise TypeError( 'Attempt to merge dict value of type ' + v.__class__.__name__ + \ ' into incompatible type ' + to[list_base].__class__.__name__ + \ ' for key ' + list_base + '(' + k + ')') else: to[list_base] = [] # Call MergeLists, which will make copies of objects that require it. # MergeLists can recurse back into MergeDicts, although this will be # to make copies of dicts (with paths fixed), there will be no # subsequent dict "merging" once entering a list because lists are # always replaced, appended to, or prepended to. is_paths = IsPathSection(list_base) MergeLists(to[list_base], v, to_file, fro_file, is_paths, append) else: raise TypeError( 'Attempt to merge dict value of unsupported type ' + \ v.__class__.__name__ + ' for key ' + k) def MergeConfigWithInheritance(new_configuration_dict, build_file, target_dict, configuration, visited): # Skip if previously visted. if configuration in visited: return # Look at this configuration. configuration_dict = target_dict['configurations'][configuration] # Merge in parents. for parent in configuration_dict.get('inherit_from', []): MergeConfigWithInheritance(new_configuration_dict, build_file, target_dict, parent, visited + [configuration]) # Merge it into the new config. MergeDicts(new_configuration_dict, configuration_dict, build_file, build_file) # Drop abstract. if 'abstract' in new_configuration_dict: del new_configuration_dict['abstract'] def SetUpConfigurations(target, target_dict): # key_suffixes is a list of key suffixes that might appear on key names. # These suffixes are handled in conditional evaluations (for =, +, and ?) # and rules/exclude processing (for ! and /). Keys with these suffixes # should be treated the same as keys without. key_suffixes = ['=', '+', '?', '!', '/'] build_file = gyp.common.BuildFile(target) # Provide a single configuration by default if none exists. # TODO(mark): Signal an error if default_configurations exists but # configurations does not. if not 'configurations' in target_dict: target_dict['configurations'] = {'Default': {}} if not 'default_configuration' in target_dict: concrete = [i for (i, config) in target_dict['configurations'].items() if not config.get('abstract')] target_dict['default_configuration'] = sorted(concrete)[0] merged_configurations = {} configs = target_dict['configurations'] for (configuration, old_configuration_dict) in configs.items(): # Skip abstract configurations (saves work only). if old_configuration_dict.get('abstract'): continue # Configurations inherit (most) settings from the enclosing target scope. # Get the inheritance relationship right by making a copy of the target # dict. new_configuration_dict = {} for (key, target_val) in target_dict.items(): key_ext = key[-1:] if key_ext in key_suffixes: key_base = key[:-1] else: key_base = key if not key_base in non_configuration_keys: new_configuration_dict[key] = gyp.simple_copy.deepcopy(target_val) # Merge in configuration (with all its parents first). MergeConfigWithInheritance(new_configuration_dict, build_file, target_dict, configuration, []) merged_configurations[configuration] = new_configuration_dict # Put the new configurations back into the target dict as a configuration. for configuration in merged_configurations.keys(): target_dict['configurations'][configuration] = ( merged_configurations[configuration]) # Now drop all the abstract ones. for configuration in target_dict['configurations'].keys(): old_configuration_dict = target_dict['configurations'][configuration] if old_configuration_dict.get('abstract'): del target_dict['configurations'][configuration] # Now that all of the target's configurations have been built, go through # the target dict's keys and remove everything that's been moved into a # "configurations" section. delete_keys = [] for key in target_dict: key_ext = key[-1:] if key_ext in key_suffixes: key_base = key[:-1] else: key_base = key if not key_base in non_configuration_keys: delete_keys.append(key) for key in delete_keys: del target_dict[key] # Check the configurations to see if they contain invalid keys. for configuration in target_dict['configurations'].keys(): configuration_dict = target_dict['configurations'][configuration] for key in configuration_dict.keys(): if key in invalid_configuration_keys: raise GypError('%s not allowed in the %s configuration, found in ' 'target %s' % (key, configuration, target)) def ProcessListFiltersInDict(name, the_dict): """Process regular expression and exclusion-based filters on lists. An exclusion list is in a dict key named with a trailing "!", like "sources!". Every item in such a list is removed from the associated main list, which in this example, would be "sources". Removed items are placed into a "sources_excluded" list in the dict. Regular expression (regex) filters are contained in dict keys named with a trailing "/", such as "sources/" to operate on the "sources" list. Regex filters in a dict take the form: 'sources/': [ ['exclude', '_(linux\|mac\|win)\\.cc$'], ['include', '_mac\\.cc$'] ], The first filter says to exclude all files ending in _linux.cc, _mac.cc, and _win.cc. The second filter then includes all files ending in _mac.cc that are now or were once in the "sources" list. Items matching an "exclude" filter are subject to the same processing as would occur if they were listed by name in an exclusion list (ending in "!"). Items matching an "include" filter are brought back into the main list if previously excluded by an exclusion list or exclusion regex filter. Subsequent matching "exclude" patterns can still cause items to be excluded after matching an "include". """ # Look through the dictionary for any lists whose keys end in "!" or "/". # These are lists that will be treated as exclude lists and regular # expression-based exclude/include lists. Collect the lists that are # needed first, looking for the lists that they operate on, and assemble # then into \|lists\|. This is done in a separate loop up front, because # the _included and _excluded keys need to be added to the_dict, and that # can't be done while iterating through it. lists = [] del_lists = [] for key, value in the_dict.items(): operation = key[-1] if operation != '!' and operation != '/': continue if type(value) is not list: raise ValueError(name + ' key ' + key + ' must be list, not ' + \ value.__class__.__name__) list_key = key[:-1] if list_key not in the_dict: # This happens when there's a list like "sources!" but no corresponding # "sources" list. Since there's nothing for it to operate on, queue up # the "sources!" list for deletion now. del_lists.append(key) continue if type(the_dict[list_key]) is not list: value = the_dict[list_key] raise ValueError(name + ' key ' + list_key + \ ' must be list, not ' + \ value.__class__.__name__ + ' when applying ' + \ {'!': 'exclusion', '/': 'regex'}[operation]) if not list_key in lists: lists.append(list_key) # Delete the lists that are known to be unneeded at this point. for del_list in del_lists: del the_dict[del_list] for list_key in lists: the_list = the_dict[list_key] # Initialize the list_actions list, which is parallel to the_list. Each # item in list_actions identifies whether the corresponding item in # the_list should be excluded, unconditionally preserved (included), or # whether no exclusion or inclusion has been applied. Items for which # no exclusion or inclusion has been applied (yet) have value -1, items # excluded have value 0, and items included have value 1. Includes and # excludes override previous actions. All items in list_actions are # initialized to -1 because no excludes or includes have been processed # yet. list_actions = list((-1,) * len(the_list)) exclude_key = list_key + '!' if exclude_key in the_dict: for exclude_item in the_dict[exclude_key]: for index in range(0, len(the_list)): if exclude_item == the_list[index]: # This item matches the exclude_item, so set its action to 0 # (exclude). list_actions[index] = 0 # The "whatever!" list is no longer needed, dump it. del the_dict[exclude_key] regex_key = list_key + '/' if regex_key in the_dict: for regex_item in the_dict[regex_key]: [action, pattern] = regex_item pattern_re = re.compile(pattern) if action == 'exclude': # This item matches an exclude regex, so set its value to 0 (exclude). action_value = 0 elif action == 'include': # This item matches an include regex, so set its value to 1 (include). action_value = 1 else: # This is an action that doesn't make any sense. raise ValueError('Unrecognized action ' + action + ' in ' + name + \ ' key ' + regex_key) for index in range(0, len(the_list)): list_item = the_list[index] if list_actions[index] == action_value: # Even if the regex matches, nothing will change so continue (regex # searches are expensive). continue if pattern_re.search(list_item): # Regular expression match. list_actions[index] = action_value # The "whatever/" list is no longer needed, dump it. del the_dict[regex_key] # Add excluded items to the excluded list. # # Note that exclude_key ("sources!") is different from excluded_key # ("sources_excluded"). The exclude_key list is input and it was already # processed and deleted; the excluded_key list is output and it's about # to be created. excluded_key = list_key + '_excluded' if excluded_key in the_dict: raise GypError(name + ' key ' + excluded_key + ' must not be present prior ' ' to applying exclusion/regex filters for ' + list_key) excluded_list = [] # Go backwards through the list_actions list so that as items are deleted, # the indices of items that haven't been seen yet don't shift. That means # that things need to be prepended to excluded_list to maintain them in the # same order that they existed in the_list. for index in range(len(list_actions) - 1, -1, -1): if list_actions[index] == 0: # Dump anything with action 0 (exclude). Keep anything with action 1 # (include) or -1 (no include or exclude seen for the item). excluded_list.insert(0, the_list[index]) del the_list[index] # If anything was excluded, put the excluded list into the_dict at # excluded_key. if len(excluded_list) > 0: the_dict[excluded_key] = excluded_list # Now recurse into subdicts and lists that may contain dicts. for key, value in the_dict.items(): if type(value) is dict: ProcessListFiltersInDict(key, value) elif type(value) is list: ProcessListFiltersInList(key, value) def ProcessListFiltersInList(name, the_list): for item in the_list: if type(item) is dict: ProcessListFiltersInDict(name, item) elif type(item) is list: ProcessListFiltersInList(name, item) def ValidateTargetType(target, target_dict): """Ensures the 'type' field on the target is one of the known types. Arguments: target: string, name of target. target_dict: dict, target spec. Raises an exception on error. """ VALID_TARGET_TYPES = ('executable', 'loadable_module', 'static_library', 'shared_library', 'none') target_type = target_dict.get('type', None) if target_type not in VALID_TARGET_TYPES: raise GypError("Target %s has an invalid target type '%s'. " "Must be one of %s." % (target, target_type, '/'.join(VALID_TARGET_TYPES))) if (target_dict.get('standalone_static_library', 0) and not target_type == 'static_library'): raise GypError('Target %s has type %s but standalone_static_library flag is' ' only valid for static_library type.' % (target, target_type)) def ValidateRulesInTarget(target, target_dict, extra_sources_for_rules): """Ensures that the rules sections in target_dict are valid and consistent, and determines which sources they apply to. Arguments: target: string, name of target. target_dict: dict, target spec containing "rules" and "sources" lists. extra_sources_for_rules: a list of keys to scan for rule matches in addition to 'sources'. """ # Dicts to map between values found in rules' 'rule_name' and 'extension' # keys and the rule dicts themselves. rule_names = {} rule_extensions = {} rules = target_dict.get('rules', []) for rule in rules: # Make sure that there's no conflict among rule names and extensions. rule_name = rule['rule_name'] if rule_name in rule_names: raise GypError('rule %s exists in duplicate, target %s' % (rule_name, target)) rule_names[rule_name] = rule rule_extension = rule['extension'] if rule_extension.startswith('.'): rule_extension = rule_extension[1:] if rule_extension in rule_extensions: raise GypError(('extension %s associated with multiple rules, ' + 'target %s rules %s and %s') % (rule_extension, target, rule_extensions[rule_extension]['rule_name'], rule_name)) rule_extensions[rule_extension] = rule # Make sure rule_sources isn't already there. It's going to be # created below if needed. if 'rule_sources' in rule: raise GypError( 'rule_sources must not exist in input, target %s rule %s' % (target, rule_name)) rule_sources = [] source_keys = ['sources'] source_keys.extend(extra_sources_for_rules) for source_key in source_keys: for source in target_dict.get(source_key, []): (source_root, source_extension) = os.path.splitext(source) if source_extension.startswith('.'): source_extension = source_extension[1:] if source_extension == rule_extension: rule_sources.append(source) if len(rule_sources) > 0: rule['rule_sources'] = rule_sources def ValidateRunAsInTarget(target, target_dict, build_file): target_name = target_dict.get('target_name') run_as = target_dict.get('run_as') if not run_as: return if type(run_as) is not dict: raise GypError("The 'run_as' in target %s from file %s should be a " "dictionary." % (target_name, build_file)) action = run_as.get('action') if not action: raise GypError("The 'run_as' in target %s from file %s must have an " "'action' section." % (target_name, build_file)) if type(action) is not list: raise GypError("The 'action' for 'run_as' in target %s from file %s " "must be a list." % (target_name, build_file)) working_directory = run_as.get('working_directory') if working_directory and type(working_directory) is not str: raise GypError("The 'working_directory' for 'run_as' in target %s " "in file %s should be a string." % (target_name, build_file)) environment = run_as.get('environment') if environment and type(environment) is not dict: raise GypError("The 'environment' for 'run_as' in target %s " "in file %s should be a dictionary." % (target_name, build_file)) def ValidateActionsInTarget(target, target_dict, build_file): '''Validates the inputs to the actions in a target.''' target_name = target_dict.get('target_name') actions = target_dict.get('actions', []) for action in actions: action_name = action.get('action_name') if not action_name: raise GypError("Anonymous action in target %s. " "An action must have an 'action_name' field." % target_name) inputs = action.get('inputs', None) if inputs is None: raise GypError('Action in target %s has no inputs.' % target_name) action_command = action.get('action') if action_command and not action_command[0]: raise GypError("Empty action as command in target %s." % target_name) def TurnIntIntoStrInDict(the_dict): """Given dict the_dict, recursively converts all integers into strings. """ # Use items instead of items because there's no need to try to look at # reinserted keys and their associated values. for k, v in the_dict.items(): if type(v) is int: v = str(v) the_dict[k] = v elif type(v) is dict: TurnIntIntoStrInDict(v) elif type(v) is list: TurnIntIntoStrInList(v) if type(k) is int: del the_dict[k] the_dict[str(k)] = v def TurnIntIntoStrInList(the_list): """Given list the_list, recursively converts all integers into strings. """ for index in range(0, len(the_list)): item = the_list[index] if type(item) is int: the_list[index] = str(item) elif type(item) is dict: TurnIntIntoStrInDict(item) elif type(item) is list: TurnIntIntoStrInList(item) def PruneUnwantedTargets(targets, flat_list, dependency_nodes, root_targets, data): """Return only the targets that are deep dependencies of \|root_targets\|.""" qualified_root_targets = [] for target in root_targets: target = target.strip() qualified_targets = gyp.common.FindQualifiedTargets(target, flat_list) if not qualified_targets: raise GypError("Could not find target %s" % target) qualified_root_targets.extend(qualified_targets) wanted_targets = {} for target in qualified_root_targets: wanted_targets[target] = targets[target] for dependency in dependency_nodes[target].DeepDependencies(): wanted_targets[dependency] = targets[dependency] wanted_flat_list = [t for t in flat_list if t in wanted_targets] # Prune unwanted targets from each build_file's data dict. for build_file in data['target_build_files']: if not 'targets' in data[build_file]: continue new_targets = [] for target in data[build_file]['targets']: qualified_name = gyp.common.QualifiedTarget(build_file, target['target_name'], target['toolset']) if qualified_name in wanted_targets: new_targets.append(target) data[build_file]['targets'] = new_targets return wanted_targets, wanted_flat_list def VerifyNoCollidingTargets(targets): """Verify that no two targets in the same directory share the same name. Arguments: targets: A list of targets in the form 'path/to/file.gyp:target_name'. """ # Keep a dict going from 'subdirectory:target_name' to 'foo.gyp'. used = {} for target in targets: # Separate out 'path/to/file.gyp, 'target_name' from # 'path/to/file.gyp:target_name'. path, name = target.rsplit(':', 1) # Separate out 'path/to', 'file.gyp' from 'path/to/file.gyp'. subdir, gyp = os.path.split(path) # Use '.' for the current directory '', so that the error messages make # more sense. if not subdir: subdir = '.' # Prepare a key like 'path/to:target_name'. key = subdir + ':' + name if key in used: # Complain if this target is already used. raise GypError('Duplicate target name "%s" in directory "%s" used both ' 'in "%s" and "%s".' % (name, subdir, gyp, used[key])) used[key] = gyp def SetGeneratorGlobals(generator_input_info): # Set up path_sections and non_configuration_keys with the default data plus # the generator-specific data. global path_sections path_sections = set(base_path_sections) path_sections.update(generator_input_info['path_sections']) global non_configuration_keys non_configuration_keys = base_non_configuration_keys[:] non_configuration_keys.extend(generator_input_info['non_configuration_keys']) global multiple_toolsets multiple_toolsets = generator_input_info[ 'generator_supports_multiple_toolsets'] global generator_filelist_paths generator_filelist_paths = generator_input_info['generator_filelist_paths'] def Load(build_files, variables, includes, depth, generator_input_info, check, circular_check, parallel, root_targets): SetGeneratorGlobals(generator_input_info) # A generator can have other lists (in addition to sources) be processed # for rules. extra_sources_for_rules = generator_input_info['extra_sources_for_rules'] # Load build files. This loads every target-containing build file into # the \|data\| dictionary such that the keys to \|data\| are build file names, # and the values are the entire build file contents after "early" or "pre" # processing has been done and includes have been resolved. # NOTE: data contains both "target" files (.gyp) and "includes" (.gypi), as # well as meta-data (e.g. 'included_files' key). 'target_build_files' keeps # track of the keys corresponding to "target" files. data = {'target_build_files': set()} # Normalize paths everywhere. This is important because paths will be # used as keys to the data dict and for references between input files. build_files = set(map(os.path.normpath, build_files)) if parallel: LoadTargetBuildFilesParallel(build_files, data, variables, includes, depth, check, generator_input_info) else: aux_data = {} for build_file in build_files: try: LoadTargetBuildFile(build_file, data, aux_data, variables, includes, depth, check, True) except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while trying to load %s' % build_file) raise # Build a dict to access each target's subdict by qualified name. targets = BuildTargetsDict(data) # Fully qualify all dependency links. QualifyDependencies(targets) # Remove self-dependencies from targets that have 'prune_self_dependencies' # set to 1. RemoveSelfDependencies(targets) # Expand dependencies specified as build_file:*. ExpandWildcardDependencies(targets, data) # Remove all dependencies marked as 'link_dependency' from the targets of # type 'none'. RemoveLinkDependenciesFromNoneTargets(targets) # Apply exclude (!) and regex (/) list filters only for dependency_sections. for target_name, target_dict in targets.items(): tmp_dict = {} for key_base in dependency_sections: for op in ('', '!', '/'): key = key_base + op if key in target_dict: tmp_dict[key] = target_dict[key] del target_dict[key] ProcessListFiltersInDict(target_name, tmp_dict) # Write the results back to \|target_dict\|. for key in tmp_dict: target_dict[key] = tmp_dict[key] # Make sure every dependency appears at most once. RemoveDuplicateDependencies(targets) if circular_check: # Make sure that any targets in a.gyp don't contain dependencies in other # .gyp files that further depend on a.gyp. VerifyNoGYPFileCircularDependencies(targets) [dependency_nodes, flat_list] = BuildDependencyList(targets) if root_targets: # Remove, from \|targets\| and \|flat_list\|, the targets that are not deep # dependencies of the targets specified in \|root_targets\|. targets, flat_list = PruneUnwantedTargets( targets, flat_list, dependency_nodes, root_targets, data) # Check that no two targets in the same directory have the same name. VerifyNoCollidingTargets(flat_list) # Handle dependent settings of various types. for settings_type in ['all_dependent_settings', 'direct_dependent_settings', 'link_settings']: DoDependentSettings(settings_type, flat_list, targets, dependency_nodes) # Take out the dependent settings now that they've been published to all # of the targets that require them. for target in flat_list: if settings_type in targets[target]: del targets[target][settings_type] # Make sure static libraries don't declare dependencies on other static # libraries, but that linkables depend on all unlinked static libraries # that they need so that their link steps will be correct. gii = generator_input_info if gii['generator_wants_static_library_dependencies_adjusted']: AdjustStaticLibraryDependencies(flat_list, targets, dependency_nodes, gii['generator_wants_sorted_dependencies']) # Apply "post"/"late"/"target" variable expansions and condition evaluations. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) ProcessVariablesAndConditionsInDict( target_dict, PHASE_LATE, variables, build_file) # Move everything that can go into a "configurations" section into one. for target in flat_list: target_dict = targets[target] SetUpConfigurations(target, target_dict) # Apply exclude (!) and regex (/) list filters. for target in flat_list: target_dict = targets[target] ProcessListFiltersInDict(target, target_dict) # Apply "latelate" variable expansions and condition evaluations. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) ProcessVariablesAndConditionsInDict( target_dict, PHASE_LATELATE, variables, build_file) # Make sure that the rules make sense, and build up rule_sources lists as # needed. Not all generators will need to use the rule_sources lists, but # some may, and it seems best to build the list in a common spot. # Also validate actions and run_as elements in targets. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) ValidateTargetType(target, target_dict) ValidateRulesInTarget(target, target_dict, extra_sources_for_rules) ValidateRunAsInTarget(target, target_dict, build_file) ValidateActionsInTarget(target, target_dict, build_file) # Generators might not expect ints. Turn them into strs. TurnIntIntoStrInDict(data) # TODO(mark): Return \|data\| for now because the generator needs a list of # build files that came in. In the future, maybe it should just accept # a list, and not the whole data dict. return [flat_list, targets, data] # vim: set ft=python expandtab tabstop=2 shiftwidth=2:	pyokagan/gyp	pylib/gyp/input.py	Python	bsd-3-clause	114,987	[ "VisIt" ]	10683fcc40c5524ada6a3da4400baf4c735feb5badae30c2c641c399c846e2f7
import json import glob import time import re import os from collections import Counter from itertools import chain import requests import settings from nltk.tokenize import word_tokenize PROFILE_URL = u'https://www.okcupid.com/profile/{username}' QUESTIONS_URL = u'https://www.okcupid.com/profile/{username}/questions' LOGIN_URL = 'http://www.okcupid.com/login' MATCH_URL = 'https://www.okcupid.com/match' QUICKMATCH_URL = 'https://www.okcupid.com/quickmatch/{username}' VISITORS_URL = 'https://www.okcupid.com/visitors/{username}' HEADERS = { 'User-agent' : settings.USER_AGENT, 'content-type': 'application/x-www-form-urlencoded; charset=UTF-8', } USER_DATA_FILE = 'USER_DATA' LOCATIONS = { 'melbourne' : 976925, 'sydney' : 974455, 'san_francisco' : 4265540, } MATCH_ORDERS = ( 'MATCH', 'SPECIAL_BLEND', 'RANDOM', 'ENEMY', 'JOIN', 'LOGIN', 'MATCH_AND_NEW', 'MATCH_AND_LOGIN', 'MATCH_AND_DISTANCE', ) def get_dataframe(path): users = okc.load_user_dicts(path) return pd.DataFrame(okc.get_stats(u) for u in users) def get_user_paths(path): """Returns an iterator with all sub-paths paths corresponding to .json""" return glob.glob(os.path.join(path, '.json')) def load_user(json_path): """Returns a User based on JSON profile file path""" with open(json_path, encoding='utf-8') as file: return User(json.loads(file.read())) def load_users(collection_path): """Return an iterator of User objects from a directory of JSON profiles.""" for path in get_user_paths(collection_path): try: yield load_user(path) except (ValueError, OkcIncompleteProfileError) as e: print(e) def load_user_dicts(collection_path): """Return an iterator of user dicts from a directory of JSON profiles.""" for path in get_user_paths(collection_path): try: with open(path, encoding='utf-8') as file: yield json.loads(file.read()) except (ValueError, OkcIncompleteProfileError) as e: print(e) def filter_users(paths, question_min): """Takes a list of user paths and filters out ones with fewer than question_min answered.""" filtered_paths = [] # load the additional user data stored alongside profiles user_data_path = os.path.join(os.path.split(paths[0])[0], USER_DATA_FILE) with open(user_data_path, encoding='utf-8') as f: user_data = json.loads(f.read()) for user_path in paths: username = os.path.splitext(os.path.basename(user_path))[0] if username not in user_data: print("user {} missing from user data dictionary".format(username)) else: data = user_data[username] if data['num_questions'] >= question_min: yield user_path def get_user_data(path): # TODO: Doesn't actually handle file not existing user_data_path = os.path.join(path, USER_DATA_FILE) if not os.path.exists(user_data_path): return {} with open(user_data_path) as f: return json.loads(f.read()) def write_user_data(data, path): user_data_path = os.path.join(path, USER_DATA_FILE) with open(user_data_path, 'w', encoding='utf-8') as f: f.write(json.dumps(data)) class OkcError(Exception): pass class OkcNoSuchUserError(OkcError): def __str__(self): return 'No such user: {}'.format(self.message) class OkcIncompleteProfileError(OkcError): def __str__(self): return 'Incomplete profile: {}'.format(self.message) def get_stats(data): if 'matchpercentage' not in data: raise OkcIncompleteProfileError(data['username']) height_str = data['skinny']['height'] if height_str == "": height = None height_inches = None else: height = int(100float(re.search(r'\(([^()]+)\)', height_str).group(1)[:-1])) bits = height_str.split() #height_inches = int(bits[0].strip("'"))12 + int(bits[1].strip('"')) stats = { 'username': data['username'], 'age': int(data['age']), 'gender': int(data['gender']), 'match': int(data['matchpercentage']), 'enemy': int(data['enemypercentage']), 'status': int(data['status']), 'orientation': int(data['orientation']), 'height': height, } # could also add a gender_str based field. either m, f, or other # or could actually pull out each of the multi-tags #eg: # gender_str = data['gender_str'] # if gender_str not in ('M', 'F'): # for label in gender_str.split(','): # stats[label.strip()] = True #what to do about "M" and "F""? # need to record these also so we know who didn't add extra things # orientation # 1 == straightish # 2 == gayish # 3 == bisexualish return stats class User(object): """Models an OKC user profile. Instance attributes: stats essay_titles list of essay titles (strings) essays list of essay contents (strings) text combined text from all essays (string) tokens The nth item in essay_titles is the title of the essay in the nth position in essays list. A value of None in the essays list indicates the user did not fillout that essay. """ def __init__(self, data): self.stats = get_stats(data) self.essays = self.process_essays(data) self._tokens = None self._words = None self._vocabulary = None def process_essays(self, data): found_essays = [] for essay in data['essays']: this_essay = essay['essay'] if this_essay == []: # User did not fill this essay out found_essays.append([]) else: text = this_essay[0]['rawtext'] found_essays.append(text) return found_essays def get_tokens(self, tokenize=word_tokenize): """Returns an iterator that yields tokens from all essays""" essay_tokens = (tokenize(essay) for essay in self.essays if essay) self._tokens = list(chain.from_iterable(essay_tokens)) return self._tokens def get_words(self): self._words = [token.lower() for token in self.tokens if token.isalpha()] return self._words def get_vocabulary(self): self._vocabulary = set(self.words) return self._vocabulary @property def lexical_diversity(self): if len(self.words) == 0: return 0 return len(self.vocabulary) / len(self.words) @property def vocabulary(self): if self._vocabulary is None: self.get_vocabulary() return self._vocabulary @property def words(self): if self._words is None: self.get_words() return self._words @property def tokens(self): if self._tokens is None: self.get_tokens() return self._tokens @property def text(self): """Returns the complete text from all essays in a user's profile""" text = '\n'.join(essay for essay in self.essays if essay) return text def __str__(self): return self.username class Session(object): """Class for interacting with okcupid.com.""" def __init__(self, username=settings.USERNAME, password=settings.PASSWORD): """Logs into okcupid.com. Uses parameters for logging in if provided, otherwise defaults to credentials specified in settings.py. """ self.login(username, password) def login(self, username, password): """Logs into okcupid.com.""" params = { 'username': username, 'password': password, 'okc_api' : '1', } r = requests.post(LOGIN_URL, params=params, headers=HEADERS) self.cookies = r.cookies def search(self, count=1000, matchorder='MATCH', location=None, distance=settings.DISTANCE, min_age=settings.MIN_AGE, max_age=settings.MAX_AGE, gender='all', orientation='all', time='year'): """Make a search GET request to OKC API. Note: POST does not work. Returns a dictionary with the following keys: 'username' : user logged in as 'foundany' : 0 or 1 'maxmatch' : highest match percentage found 'lquery', : ?? 'amateur_results' : list of user dictionary results 'total_matches' : the number of results 'cache_timekey' : ?? 'alist_results' : ?? 'last_online' : unknown format 'filters' : dictionary of filters applied 'numanswered' : number of match questions answered """ # Note that gender numbers depend on what has been specified # for orientation. This first set is for selecting # fine-grained every orientation possible -- ie 4095 genders = { 'male' : 21, 'female' : 42, 'all' : 63, } # for orientation = 'everybody'; ie no orientation param genders_orientation_everybody = { 'male' : 16, 'female' : 32, 'all' : 48, } #last online times = { 'now' : 3600, 'day' : 86400, 'week' : 604800, 'month' : 2678400, 'year' : 31536000, } # use most promiscuous values possible for rest... # This orientation number of 4095 is for selecting every tick # box possible in orientation. If you just want 'everyone', # omit this param. orientation = 4095 status = 0 # location if location is None: locid = 0 else: locid = LOCATIONS[location] # the filter names (eg 'filter1, 'filter2') are not relevant, # just indicate the nth filter applied. The value of the # filter parameters are themselves <key,value> pairs separated # by commas, indicating the filter type and value to be # filtered on. params = { 'okc_api' : 1, 'timekey' : 1, 'discard_prefs' : 1, 'count' : count, 'matchOrderBy' : matchorder, 'locid' : locid, 'filter1' : '0,{}'.format(genders[gender]), 'filter2' : '76,{}'.format(orientation), 'filter3' : '2,{},{}'.format(min_age, max_age), 'filter4' : '3,{}'.format(distance), 'filter5' : '5,{}'.format(times[time]), 'filter6' : '35,{}'.format(status), } result = requests.get(MATCH_URL, cookies=self.cookies, params=params) return result.json()['amateur_results'] def get_profile(self, username): """Given a username, return their profile as a JSON string.""" params = {'okc_api' : 1} url = PROFILE_URL.format(username=username) result = requests.get(url, cookies=self.cookies, params=params) if result.status_code != requests.codes.ok: message = "Error getting profile: {}\n{}".format(username, result.text) raise OkcNoSuchUserError(message) return result.json() def get_num_questions(self, username): params = {'okc_api' : 1} url = QUESTIONS_URL.format(username=username) result = requests.get(url, cookies=self.cookies, params=params) if result.status_code != requests.codes.ok: message = "Error getting profile: {}\n{}".format(username, result.text) raise OkcNoSuchUserError(message) json_data = result.json() num_questions = int(json_data['pagination']['raw']['total_num_results']) return num_questions def dump_profiles(self, usernames, path, resume=False): """Retrieves user profiles and write them all to disk.""" user_data = get_user_data(path) for count, username in enumerate(usernames): outpath = os.path.join(path, "{}.json".format(username)) if resume and os.path.exists(outpath): continue try: user = self.get_profile(username) num_questions = self.get_num_questions(username) if username not in user_data: user_data[username] = {} user_data[username]['num_questions'] = num_questions with open(outpath, 'w', encoding='utf-8') as file: json_string = json.dumps(user) file.write(json_string) write_user_data(user_data, path) print("{}: Wrote {}".format(count+1, username)) except OkcNoSuchUserError as error: print("NO SUCH USER: {}".format(username)) except requests.ConnectionError as error: print("CONNECTION ERROR: {}".format(username)) time.sleep(settings.SLEEP_TIME) def visit_profiles(self, usernames): """Retrieves the profiles of a sequence of usernames. Nothing is done with the profiles, but this has the effect of making you appear in their visitors list if you are not in invisible browsing mode. """ for count, username in enumerate(usernames): try: self.get_profile(username) print("{}: Visited {}".format(count+1, username)) except OkcNoSuchUserError as error: print("NO SUCH USER: {}".format(username)) except requests.ConnectionError as error: print("CONNECTION ERROR: {}".format(username)) time.sleep(settings.SLEEP_TIME) def find_and_visit_profiles(self, cutoff=None, threshold=None, kwargs): """Perform a custom search for users and then visit their profiles. threshold argument: minimum match percentage score to stop at. cuttoff argument: number of profiles to stop at. Also accepts all keyword arguments accepted by the search() method. """ profiles = self.search(kwargs) if threshold is not None: usernames = [profile['username'] for profile in profiles if int(profile['matchpercentage']) > threshold] if cutoff is not None: usernames = usernames[:cutoff] self.visit_profiles(usernames) def find_users(self, kwargs): """Given search parameters as keyword arguments, returns a set of usernames. Avoids the 1000 user response limit by repeating search for randomly sorted results until no new users are found. """ usernames = set() num_found = True while num_found: num_before = len(usernames) profiles = self.search(matchorder='RANDOM', kwargs) usernames.update(profile['username'] for profile in profiles) num_after = len(usernames) num_found = num_after - num_before print("Found {} new users".format(num_found)) time.sleep(settings.SLEEP_TIME) return usernames def find_all_users(self, binsize=5, *kwargs): """In addition to the 1000 user result limit, OKC seems to also silently filter out some users from the search results if there are too many potential* matches that could be returned. ie there are just some users that won't be returned no matter how many times you hit the RANDOM buttom. This can be avoided by searching over a smaller age range. This function gets around the limitation by invoking self.find_users() across a series of ranges of length specified by binsize. """ usernames = set() pairs = [] curr = settings.MIN_AGE while curr <= settings.MAX_AGE: if curr + binsize > settings.MAX_AGE: this_max = settings.MAX_AGE else: this_max = curr + binsize pairs.append((curr, this_max)) curr += binsize + 1 kwargs.pop('min_age', None) kwargs.pop('max_age', None) for min_age, max_age in pairs: found = self.find_users(min_age=min_age, max_age=max_age, **kwargs) usernames.update(found) print("====================================") print("Found {} users in age bracket {},{}\n".format(len(found), min_age, max_age)) return usernames	ned2/okdata	okc.py	Python	mit	16,915	[ "VisIt" ]	038678a7ca9dcc7b200a76ce66fcc0829e66b42de9fd17626ee151004ee20b32
""" ======= Plotter ======= .. moduleauthor:: Adam Ginsburg <adam.g.ginsburg@gmail.com> """ from __future__ import print_function import matplotlib import matplotlib.pyplot import matplotlib.figure import numpy as np import astropy.units as u import copy import inspect try: from matplotlib.cbook import BoundMethodProxy except ImportError: from matplotlib.cbook import _BoundMethodProxy as BoundMethodProxy from . import widgets from ..specwarnings import warn interactive_help_message = """ Interactive key commands for plotter. An additional help message may appear if you have initiated the fitter. '?' - bring up this message 'f' - initiate the /f/itter 'b' - initiate the /b/aseliner 'B' - initiate the /b/aseliner (reset the selection too) 'r' - re-attach matplotlib keys 'R' - redraw the plot cleanly 'i' : individual components / show each fitted component """ xlabel_table = {'speed': 'Velocity'} class Plotter(object): """ Class to plot a spectrum """ def __init__(self, Spectrum, autorefresh=True, title="", xlabel="", silent=True, plotscale=1.0, kwargs): self.figure = None self.axis = None self.Spectrum = Spectrum self._xunit = Spectrum.xarr.unit # plot parameters self.offset = 0.0 # vertical offset self.autorefresh = autorefresh self.xlabel = xlabel self.title = title self.errorplot = None self.plotkwargs = kwargs self._xlim = [None,None] self._ylim = [None,None] self.debug = False self.keyclick = None self.silent = silent self.plotscale = plotscale self._xclick1 = None self._xclick2 = None self.automake_fitter_tool = False def _get_prop(xy, minmax): def getprop(self): if self.Spectrum.xarr.unit != self._xunit: self._xunit = self.Spectrum.xarr.unit if xy == 'x': if minmax == 'min': if self._xlim[0] and self._xunit: try: self._xlim[0]._unit = self._xunit except AttributeError: self._xlim[0] = u.Quantity(self._xlim[0], self._xunit) return self._xlim[0] elif minmax == 'max': if self._xlim[1] and self._xunit: try: self._xlim[1]._unit = self._xunit except AttributeError: self._xlim[1] = u.Quantity(self._xlim[1], self._xunit) return self._xlim[1] elif xy == 'y': if minmax == 'min': return self._ylim[0] elif minmax == 'max': return self._ylim[1] return getprop def _set_prop(xy, minmax): def setprop(self, value): if self.debug: frm = inspect.stack() print(frm[1],"Setting %s%s to %s" % (xy,minmax,value)) if xy == 'x': if minmax == 'min': self._xlim[0] = value elif minmax == 'max': self._xlim[1] = value elif xy == 'y': if minmax == 'min': self._ylim[0] = value elif minmax == 'max': self._ylim[1] = value return setprop xmin = property(fget=_get_prop('x','min'),fset=_set_prop('x','min')) xmax = property(fget=_get_prop('x','max'),fset=_set_prop('x','max')) ymin = property(fget=_get_prop('y','min'),fset=_set_prop('y','min')) ymax = property(fget=_get_prop('y','max'),fset=_set_prop('y','max')) def _disconnect_matplotlib_keys(self): """ Disconnected the matplotlib key-press callbacks """ if self.figure is not None: cbs = self.figure.canvas.callbacks.callbacks # this may cause problems since the dict of key press events is a # dict, i.e. not ordered, and we want to pop the first one... mpl_keypress_handler = self.figure.canvas.manager.key_press_handler_id try: self._mpl_key_callbacks = {mpl_keypress_handler: cbs['key_press_event'].pop(mpl_keypress_handler)} except KeyError: bmp = BoundMethodProxy(self.figure.canvas.manager.key_press) self._mpl_key_callbacks = {mpl_keypress_handler: bmp} def _reconnect_matplotlib_keys(self): """ Reconnect the previously disconnected matplotlib keys """ if self.figure is not None and hasattr(self,'_mpl_key_callbacks'): self.figure.canvas.callbacks.callbacks['key_press_event'].update(self._mpl_key_callbacks) elif self.figure is not None: mpl_keypress_handler = self.figure.canvas.manager.key_press_handler_id bmp = BoundMethodProxy(self.figure.canvas.manager.key_press) self.figure.canvas.callbacks.callbacks['key_press_event'].update({mpl_keypress_handler: bmp}) def __call__(self, figure=None, axis=None, clear=True, autorefresh=None, plotscale=1.0, override_plotkwargs=False, kwargs): """ Plot a spectrum Keywords: figure - either a matplotlib figure instance or a figure number to pass into pyplot.figure. axis - Alternative to figure, can pass an axis instance and use it as the plotting canvas clear - Clear the axis before plotting? """ # figure out where to put the plot if isinstance(figure,matplotlib.figure.Figure): self.figure = figure self.axis = self.figure.gca() elif type(figure) is int: self.figure = matplotlib.pyplot.figure(figure) self.axis = self.figure.gca() elif self.figure is None: if isinstance(axis,matplotlib.axes.Axes): self.axis = axis self.figure = axis.figure else: self.figure = matplotlib.pyplot.figure() if not matplotlib.pyplot.fignum_exists(self.figure.number): self.figure = matplotlib.pyplot.figure(self.figure.number) # always re-connect the interactive keys to avoid frustration... self._mpl_reconnect() if axis is not None: self._mpl_disconnect() self.axis = axis self.figure = axis.figure self._mpl_connect() elif len(self.figure.axes) > 0 and self.axis is None: self.axis = self.figure.axes[0] # default to first axis elif self.axis is None: self.axis = self.figure.gca() # A check to deal with issue #117: if you close the figure, the axis # still exists, but it cannot be reattached to a figure if not (self.axis.get_figure() is matplotlib.pyplot.figure(self.axis.get_figure().number)): self.axis = self.figure.gca() if self.axis is not None and self.axis not in self.figure.axes: # if you've cleared the axis, but the figure is still open, you # need a new axis self.figure.add_axes(self.axis) if clear and self.axis is not None: self.axis.clear() # Need to empty the stored model plots if hasattr(self.Spectrum, 'fitter'): self.Spectrum.fitter.clear() if autorefresh is not None: self.autorefresh = autorefresh self.plotscale = plotscale if self.plotkwargs and not override_plotkwargs: self.plotkwargs.update(kwargs) else: self.plotkwargs = kwargs self.plot(kwargs) def _mpl_connect(self): if self.keyclick is None: self.keyclick = self.figure.canvas.mpl_connect('key_press_event',self.parse_keys) def _mpl_disconnect(self): self.figure.canvas.mpl_disconnect(self.keyclick) self.keyclick = None def _mpl_reconnect(self): self._mpl_disconnect() self._mpl_connect() # disable fullscreen & grid matplotlib.pyplot.rcParams['keymap.fullscreen'] = 'ctrl+f' matplotlib.pyplot.rcParams['keymap.grid'] = 'ctrl+g' def plot(self, offset=0.0, xoffset=0.0, color='k', linestyle='steps-mid', linewidth=0.5, errstyle=None, erralpha=0.2, errcolor=None, silent=None, reset=True, refresh=True, use_window_limits=None, useOffset=False, kwargs): """ Plot the spectrum! Tries to automatically find a reasonable plotting range if one is not set. Parameters ---------- offset : float vertical offset to add to the spectrum before plotting. Useful if you want to overlay multiple spectra on a single plot xoffset: float An x-axis shift. I don't know why you'd want this... color : str default to plotting spectrum in black linestyle : 'steps-mid' or str 'steps-mid' for histogram-style plotting. See matplotlib's plot for more information linewidth : float Line width in pixels. Narrow lines are helpful when histo-plotting errstyle : 'fill', 'bars', or None can be "fill", which draws partially transparent boxes around the data to show the error region, or "bars" which draws standard errorbars. ``None`` will display no errorbars useOffset : bool Use offset-style X/Y coordinates (e.g., 1 + 1.483e10)? Defaults to False because these are usually quite annoying. xmin/xmax/ymin/ymax : float override defaults for plot range. Once set, these parameters are sticky (i.e., replotting will use the same ranges). Passed to `reset_limits` reset_[xy]limits : bool Reset the limits to "sensible defaults". Passed to `reset_limits` ypeakscale : float Scale up the Y maximum value. Useful to keep the annotations away from the data. Passed to `reset_limits` reset : bool Reset the x/y axis limits? If set, `reset_limits` will be called. """ if self.axis is None: raise Exception("You must call the Plotter class to initiate the canvas before plotting.") self.offset = offset # there is a bug where this only seems to update the second time it is called self.label(kwargs) self.label(kwargs) for arg in ['title','xlabel','ylabel']: if arg in kwargs: kwargs.pop(arg) reset_kwargs = {} for arg in ['xmin', 'xmax', 'ymin', 'ymax', 'reset_xlimits', 'reset_ylimits', 'ypeakscale']: if arg in kwargs: reset_kwargs[arg] = kwargs.pop(arg) if (use_window_limits is None and any(k in reset_kwargs for k in ('xmin','xmax','reset_xlimits'))): use_window_limits = False if use_window_limits: self._stash_window_limits() # for filled errorbars, order matters. inds = np.argsort(self.Spectrum.xarr) if errstyle is not None: if errcolor is None: errcolor = color if errstyle == 'fill': self.errorplot = [self.axis.fill_between(steppify(self.Spectrum.xarr.value[inds]+xoffset, isX=True), steppify((self.Spectrum.dataself.plotscale+self.offset-self.Spectrum.errorself.plotscale)[inds]), steppify((self.Spectrum.dataself.plotscale+self.offset+self.Spectrum.errorself.plotscale)[inds]), facecolor=errcolor, edgecolor=errcolor, alpha=erralpha, *kwargs)] elif errstyle == 'bars': self.errorplot = self.axis.errorbar(self.Spectrum.xarr[inds].value+xoffset, self.Spectrum.data[inds]self.plotscale+self.offset, yerr=self.Spectrum.error[inds]self.plotscale, ecolor=errcolor, fmt='none', kwargs) self._spectrumplot = self.axis.plot(self.Spectrum.xarr.value[inds]+xoffset, self.Spectrum.data[inds]self.plotscale+self.offset, color=color, linestyle=linestyle, linewidth=linewidth, kwargs) self.axis.ticklabel_format(useOffset=useOffset) if use_window_limits: self._reset_to_stashed_limits() if silent is not None: self.silent = silent if reset: self.reset_limits(use_window_limits=use_window_limits, reset_kwargs) if self.autorefresh and refresh: self.refresh() def _stash_window_limits(self): self._window_limits = self.axis.get_xlim(),self.axis.get_ylim() if self.debug: print("Stashed window limits: ",self._window_limits) def _reset_to_stashed_limits(self): self.axis.set_xlim(self._window_limits[0]) self.axis.set_ylim(self._window_limits[1]) self.xmin,self.xmax = self._window_limits[0] self.ymin,self.ymax = self._window_limits[1] if self.debug: print("Recovered window limits: ",self._window_limits) def reset_limits(self, xmin=None, xmax=None, ymin=None, ymax=None, reset_xlimits=True, reset_ylimits=True, ypeakscale=1.2, silent=None, use_window_limits=False, kwargs): """ Automatically or manually reset the plot limits """ # if not use_window_limits: use_window_limits = False if self.debug: frame = inspect.currentframe() args, _, _, values = inspect.getargvalues(frame) print(zip(args,values)) if use_window_limits: # this means DO NOT reset! # it simply sets self.[xy][min/max] = current value self.set_limits_from_visible_window() else: if silent is not None: self.silent = silent # if self.xmin and self.xmax: if (reset_xlimits or self.Spectrum.xarr.min().value < self.xmin or self.Spectrum.xarr.max().value > self.xmax): if not self.silent: warn("Resetting X-axis min/max because the plot is out of bounds.") self.xmin = None self.xmax = None if xmin is not None: self.xmin = u.Quantity(xmin, self._xunit) elif self.xmin is None: self.xmin = u.Quantity(self.Spectrum.xarr.min().value, self._xunit) if xmax is not None: self.xmax = u.Quantity(xmax, self._xunit) elif self.xmax is None: self.xmax = u.Quantity(self.Spectrum.xarr.max().value, self._xunit) xpixmin = np.argmin(np.abs(self.Spectrum.xarr.value-self.xmin.value)) xpixmax = np.argmin(np.abs(self.Spectrum.xarr.value-self.xmax.value)) if xpixmin>xpixmax: xpixmin,xpixmax = xpixmax,xpixmin elif xpixmin == xpixmax: if reset_xlimits: raise Exception("Infinite recursion error. Maybe there are no valid data?") if not self.silent: warn("ERROR: the X axis limits specified were invalid. Resetting.") self.reset_limits(reset_xlimits=True, ymin=ymin, ymax=ymax, reset_ylimits=reset_ylimits, ypeakscale=ypeakscale, kwargs) return if self.ymin and self.ymax: # this is utter nonsense.... if (self.Spectrum.data.max() < self.ymin or self.Spectrum.data.min() > self.ymax or reset_ylimits): if not self.silent and not reset_ylimits: warn("Resetting Y-axis min/max because the plot is out of bounds.") self.ymin = None self.ymax = None if ymin is not None: self.ymin = ymin elif self.ymin is None: if hasattr(self.Spectrum.data, 'mask'): yminval = self.Spectrum.data[xpixmin:xpixmax].min() else: yminval = np.nanmin(self.Spectrum.data[xpixmin:xpixmax]) # Increase the range fractionally. This means dividing a positive #, multiplying a negative # if yminval < 0: self.ymin = float(yminval)float(ypeakscale) else: self.ymin = float(yminval)/float(ypeakscale) if ymax is not None: self.ymax = ymax elif self.ymax is None: if hasattr(self.Spectrum.data, 'mask'): ymaxval = ((self.Spectrum.data[xpixmin:xpixmax]).max()-self.ymin) else: ymaxval = (np.nanmax(self.Spectrum.data[xpixmin:xpixmax])-self.ymin) if ymaxval > 0: self.ymax = float(ymaxval) float(ypeakscale) + self.ymin else: self.ymax = float(ymaxval) / float(ypeakscale) + self.ymin self.ymin += self.offset self.ymax += self.offset self.axis.set_xlim(self.xmin.value if hasattr(self.xmin, 'value') else self.xmin, self.xmax.value if hasattr(self.xmax, 'value') else self.xmax) self.axis.set_ylim(self.ymin, self.ymax) def label(self, title=None, xlabel=None, ylabel=None, verbose_label=False, *kwargs): """ Label the plot, with an attempt to parse standard units into nice latex labels Parameters ---------- title : str xlabel : str ylabel : str verbose_label: bool """ if title is not None: self.title = title elif hasattr(self.Spectrum,'specname'): self.title = self.Spectrum.specname if self.title is not "": self.axis.set_title(self.title) if xlabel is not None: self.xlabel = xlabel elif self._xunit: # WAS: self.xlabel = self.Spectrum.xarr.xtype.title() try: self.xlabel = xlabel_table[self._xunit.physical_type.lower()] except KeyError: self.xlabel = self._xunit.physical_type.title() # WAS: self.xlabel += " ("+u.Unit(self._xunit).to_string()+")" self.xlabel += " ({0})".format(self._xunit.to_string()) if verbose_label: self.xlabel = "%s %s" % (self.Spectrum.xarr.velocity_convention.title(), self.xlabel) if self.xlabel is not None: self.axis.set_xlabel(self.xlabel) if ylabel is not None: self.axis.set_ylabel(ylabel) elif self.Spectrum.unit in ['Ta','Tastar']: self.axis.set_ylabel("$T_A^$ (K)") elif self.Spectrum.unit in ['K']: self.axis.set_ylabel("Brightness Temperature $T$ (K)") elif self.Spectrum.unit == 'mJy': self.axis.set_ylabel("$S_\\nu$ (mJy)") elif self.Spectrum.unit == 'Jy': self.axis.set_ylabel("$S_\\nu$ (Jy)") else: if isinstance(self.Spectrum.unit, str) and "$" in self.Spectrum.unit: # assume LaTeX already self.axis.set_ylabel(self.Spectrum.unit) elif isinstance(self.Spectrum.unit, str): self.axis.set_ylabel(self.Spectrum.unit) else: label_units = self.Spectrum.unit.to_string(format='latex') if 'mathring{A}' in label_units: label_units = label_units.replace('\mathring{A}', 'A') if '\overset' in label_units: label_units = label_units.replace('\overset', '^') self.axis.set_ylabel(label_units) @property def ylabel(self): return self.axis.get_ylabel() def refresh(self): if self.axis is not None: self.axis.figure.canvas.draw() def savefig(self,fname,bbox_inches='tight',kwargs): """ simple wrapper of maplotlib's savefig. """ self.axis.figure.savefig(fname,bbox_inches=bbox_inches,kwargs) def parse_keys(self,event): """ Parse key commands entered from the keyboard """ if hasattr(event,'key'): if event.key == '?': print(interactive_help_message) elif event.key == 'f': print("\n\nFitter initiated from the interactive plotter.") # extra optional text: # Matplotlib shortcut keys ('g','l','p',etc.) are disabled. Re-enable with 'r'" self._disconnect_matplotlib_keys() self.Spectrum.specfit(interactive=True) if not hasattr(self,'FitterTool') and self.automake_fitter_tool: self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif hasattr(self,'FitterTool') and self.FitterTool.toolfig.number not in matplotlib.pyplot.get_fignums(): self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif event.key is not None and event.key.lower() == 'b': if event.key == 'b': print("\n\nBaseline initiated from the interactive plotter") elif event.key == 'B': print("\n\nBaseline initiated from the interactive plotter (with reset)") print("Matplotlib shortcut keys ('g','l','p',etc.) are disabled. Re-enable with 'r'") self._disconnect_matplotlib_keys() self.Spectrum.baseline(interactive=True, reset_selection=(event.key=='B')) if not hasattr(self,'FitterTool') and self.automake_fitter_tool: self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif hasattr(self,'FitterTool') and self.FitterTool.toolfig.number not in matplotlib.pyplot.get_fignums(): self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif event.key == 'r': # print("\n\nReconnected matplotlib shortcut keys.") self._reconnect_matplotlib_keys() elif event.key == 'R': self() elif event.key == 'i': self.Spectrum.specfit.plot_fit(show_components=True) def get_two_clicks(self,event): if self._xclick1 is None: self._xclick1 = event.xdata elif self._xclick2 is None: self._xclick2 = event.xdata def set_limits_from_visible_window(self, debug=False): """ Hopefully self-descriptive: set the x and y limits from the currently visible window (use this if you use the pan/zoom tools or manually change the limits) """ if debug: print("Changing x limits from %f,%f to %f,%f" % (self.xmin,self.xmax,self.axis.get_xlim()[0],self.axis.get_xlim()[1])) print("Changing y limits from %f,%f to %f,%f" % (self.ymin,self.ymax,self.axis.get_ylim()[0],self.axis.get_ylim()[1])) self.xmin, self.xmax = self.axis.get_xlim() self.ymin, self.ymax = self.axis.get_ylim() if debug: print("New x limits %f,%f == %f,%f" % (self.xmin,self.xmax,self.axis.get_xlim()[0],self.axis.get_xlim()[1])) print("New y limits %f,%f == %f,%f" % (self.ymin,self.ymax,self.axis.get_ylim()[0],self.axis.get_ylim()[1])) def copy(self, parent=None): """ Create a copy of the plotter with blank (uninitialized) axis & figure [ parent ] A spectroscopic axis instance that is the parent of the specfit instance. This needs to be specified at some point, but defaults to None to prevent overwriting a previous plot. """ newplotter = copy.copy(self) newplotter.Spectrum = parent newplotter.axis = None newplotter.figure = None return newplotter def line_ids(self, line_names, line_xvals, xval_units=None, auto_yloc=True, velocity_offset=None, velocity_convention='radio', auto_yloc_fraction=0.9, kwargs): """ Add line ID labels to a plot using lineid_plot http://oneau.wordpress.com/2011/10/01/line-id-plot/ https://github.com/phn/lineid_plot http://packages.python.org/lineid_plot/ Parameters ---------- line_names : list A list of strings to label the specified x-axis values line_xvals : list List of x-axis values (e.g., wavelengths) at which to label the lines. Can be a list of quantities. xval_units : string The unit of the line_xvals if they are not given as quantities velocity_offset : quantity A velocity offset to apply to the inputs if they are in frequency or wavelength units velocity_convention : 'radio' or 'optical' or 'doppler' Used if the velocity offset is given auto_yloc : bool If set, overrides box_loc and arrow_tip (the vertical position of the lineid labels) in kwargs to be `auto_yloc_fraction` of the plot range auto_yloc_fraction: float in range [0,1] The fraction of the plot (vertically) at which to place labels Examples -------- >>> import numpy as np >>> import pyspeckit >>> sp = pyspeckit.Spectrum( xarr=pyspeckit.units.SpectroscopicAxis(np.linspace(-50,50,101), unit='km/s', refX=6562.8, refX_unit='angstrom'), data=np.random.randn(101), error=np.ones(101)) >>> sp.plotter() >>> sp.plotter.line_ids(['H$\\alpha$'],[6562.8],xval_units='angstrom') """ import lineid_plot if velocity_offset is not None: assert velocity_offset.unit.is_equivalent(u.km/u.s) doppler = getattr(u, 'doppler_{0}'.format(velocity_convention)) equivalency = doppler(self.Spectrum.xarr.refX) xvals = [] for xv in line_xvals: if hasattr(xv, 'unit'): pass else: xv = u.Quantity(xv, xval_units) xv = xv.to(u.km/u.s, equivalencies=equivalency) if velocity_offset is not None: xv = xv + velocity_offset xv = xv.to(self.Spectrum.xarr.unit, equivalencies=equivalency) xvals.append(xv.value) if auto_yloc: yr = self.axis.get_ylim() kwargs['box_loc'] = (yr[1]-yr[0])auto_yloc_fraction + yr[0] kwargs['arrow_tip'] = (yr[1]-yr[0])(auto_yloc_fraction0.9) + yr[0] lineid_plot.plot_line_ids(self.Spectrum.xarr, self.Spectrum.data, xvals, line_names, ax=self.axis, kwargs) def line_ids_from_measurements(self, auto_yloc=True, auto_yloc_fraction=0.9, kwargs): """ Add line ID labels to a plot using lineid_plot http://oneau.wordpress.com/2011/10/01/line-id-plot/ https://github.com/phn/lineid_plot http://packages.python.org/lineid_plot/ Parameters ---------- auto_yloc : bool If set, overrides box_loc and arrow_tip (the vertical position of the lineid labels) in kwargs to be `auto_yloc_fraction` of the plot range auto_yloc_fraction: float in range [0,1] The fraction of the plot (vertically) at which to place labels Examples -------- >>> import numpy as np >>> import pyspeckit >>> sp = pyspeckit.Spectrum( xarr=pyspeckit.units.SpectroscopicAxis(np.linspace(-50,50,101), units='km/s', refX=6562.8, refX_unit='angstroms'), data=np.random.randn(101), error=np.ones(101)) >>> sp.plotter() >>> sp.specfit(multifit=None, fittype='gaussian', guesses=[1,0,1]) # fitting noise.... >>> sp.measure() >>> sp.plotter.line_ids_from_measurements() """ import lineid_plot if hasattr(self.Spectrum,'measurements'): measurements = self.Spectrum.measurements if auto_yloc: yr = self.axis.get_ylim() kwargs['box_loc'] = (yr[1]-yr[0])auto_yloc_fraction + yr[0] kwargs['arrow_tip'] = (yr[1]-yr[0])(auto_yloc_fraction0.9) + yr[0] lineid_plot.plot_line_ids(self.Spectrum.xarr, self.Spectrum.data, [v['pos'] for v in measurements.lines.values()], measurements.lines.keys(), ax=self.axis, kwargs) else: warn("Cannot add line IDs from measurements unless measurements have been made!") def parse_units(labelstring): import re labelstring = re.sub("um","$\mu$m",labelstring) labelstring = re.sub("-1","$^{-1}$",labelstring) labelstring = re.sub("-2","$^{-2}$",labelstring) labelstring = re.sub("-3","$^{-3}$",labelstring) labelstring = re.sub("ergss","ergs s",labelstring) return labelstring def parse_norm(norm): """ Expected format: norm = 10E15 """ try: base, exp = norm.split('E') except ValueError: base, exp = norm.split('e') if float(base) == 1.0: norm = '10' else: norm = base norm += '^{%s}' % exp return norm def steppify(arr,isX=False): """ support function* Converts an array to double-length for step plotting """ if isX: interval = abs(arr[1:]-arr[:-1]) / 2.0 newarr = np.array(list(zip(arr[:-1]-interval,arr[:-1]+interval))).ravel() newarr = np.concatenate([newarr,2*[newarr[-1]+interval[-1]]]) else: newarr = np.array(list(zip(arr,arr))).ravel() return newarr	mikelum/pyspeckit	pyspeckit/spectrum/plotters.py	Python	mit	31,130	[ "Gaussian" ]	9cc62897613a994bdd8d2f4170d1b87e32bd5b29b76e3db73821152e187871ed
# Copyright 2000 by Andrew Dalke. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. # The Prosite patterns are defined at http://www.expasy.ch/txt/prosuser.txt # # The PA (PAttern) lines contains the definition of a PROSITE pattern. The # patterns are described using the following conventions: # # - The standard IUPAC one-letter codes for the amino acids are used. # - The symbol `x' is used for a position where any amino acid is accepted. # - Ambiguities are indicated by listing the acceptable amino acids for a # given position, between square parentheses `[ ]'. For example: [ALT] # stands for Ala or Leu or Thr. # - Ambiguities are also indicated by listing between a pair of curly # brackets `{ }' the amino acids that are not accepted at a given # position. For example: {AM} stands for any amino acid except Ala and # Met. # - Each element in a pattern is separated from its neighbor by a `-'. # - Repetition of an element of the pattern can be indicated by following # that element with a numerical value or a numerical range between # parenthesis. Examples: x(3) corresponds to x-x-x, x(2,4) corresponds to # x-x or x-x-x or x-x-x-x. # - When a pattern is restricted to either the N- or C-terminal of a # sequence, that pattern either starts with a `<' symbol or respectively # ends with a `>' symbol. # - A period ends the pattern. # # That boils down to doing these conversions # # [] -> [] # {} -> [^ ] # - -> # () -> {} # < -> ^ # > -> $ # x->X # . -> # Note: # [G>] is a valid Prosite pattern, equivalent to "([G]\|$)" # I assume then that # [>G] is equivalent to "(^\|[G])" # It is conceivable that [G>]-G-G is valid, meaning a "G" at the end # of the sequence or followed by two more Gs. I did not implement # this. I haven't gotten an answer to my query on either of these two # non-documented possibilities. import string, re from Bio import Seq, Alphabet # Syntactic conversion to two types of regular expressions _prosite_trans = string.maketrans("abcdefghijklmnopqrstuvwxyzX}()<>", "ABCDEFGHIJKLMNOPQRSTUVW.YZ.]{}^$") # This does not verify that the pattern is correct - invalid patterns # can be converted! def prosite_to_re(pattern): """convert a valid Prosite pattern into an re string""" flg = (pattern[:2] == "[<") s = pattern.replace("{", "[^") s = s.translate(_prosite_trans, "-.") # special case "[<" and ">]", if they exist if flg: i = s.index("]") s = "(?:^\|[" + s[2:i] + "])" + s[i+1:] if s[-2:] == "$]": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-2] + "]\|$)" elif s[-3:] == "$]$": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-3] + "]\|$)$" return s # This does not verify the pattern is correct - invalid patterns can # be converted! def prosite_to_grouped_re(pattern): """convert a valid Prosite pattern into an re with groups for each term""" flg = (pattern[:2] == "[<") s = pattern.replace("{", "[^") # Don't delete the "-" characters: use them to place the ()s s = s.translate(_prosite_trans, ".") # Get the [< and >] terms correct if flg: i = s.index("]") s = "(?:^\|[" + s[2:i] + "])" + s[i+1:] if s[-2:] == "$]": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-2] + "]\|$)" if s[-3:] == "$]$": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-3] + "]\|$)$" # Watch out for unescaped < and > terms if s[:1] == "^": s = "^(" + s[1:] else: s = "(" + s if s[-1:] == "$": s = s[:-1] + ")$" else: s = s + ")" return s.replace("-", ")(") # Both the Prosite pattern and match result act like sequences. class PrositeAlphabet(Alphabet.Alphabet): pass prosite_alphabet = PrositeAlphabet() def compile(pattern): if not verify_pattern(pattern): raise TypeError("not a legal prosite pattern") return Prosite(pattern = pattern) class Prosite: alphabet = prosite_alphabet # Don't like having two different types of input - not very pythonic # However, it is faster since I can assume the input has already been # verified (if it's a pattern). def __init__(self, pattern = None, data = None): assert (pattern is None and data is not None) ^ \ (pattern is not None and data is None), \ "one and only one of pattern and data can have a value" if pattern is not None: self.pattern = pattern if data is not None: self.data = data def __repr__(self): return "Prosite(%s)" % repr(str(self)) def __str__(self): return '-'.join(map(str, self.data)) + "." def __len__(self): return len(self.data) def __getitem__(self, i): return self.data[i] def __getslice__(self, i, j): i = max(i, 0); j = max(j, 0) return Prosite(data = self.data[i:j]) def __getattr__(self, name): # Lazy creation of these elements / cache results if name == "re": self.re = re.compile(prosite_to_re(self.pattern)) return self.re elif name == "grouped_re": self.grouped_re = re.compile(prosite_to_grouped_re(self.pattern)) return self.grouped_re elif name == "data": self.data = find_terms(self.pattern) return self.data elif name == "pattern": self.pattern = str(self) return self.pattern raise AttributeError(name) def tostring(self): return str(self) def search(self, seq, pos=0, endpos=None): if endpos is not None: m = self.grouped_re.search(buffer(seq.tostring()), pos, endpos) else: m = self.grouped_re.search(buffer(seq.tostring()), pos) if m is None: return None return PrositeMatch(self, seq, m) def match(self, seq, pos=0, endpos=None): if endpos is not None: m = self.grouped_re.match(buffer(seq.tostring()), pos, endpos) else: m = self.grouped_re.match(buffer(seq.tostring()), pos) if m is None: return None return PrositeMatch(self, seq, m) # I was thinking about adding sub, subn, findall, etc., but either # you just want the string (in which case, use the ".re") or # you could be changing to a different alphabet (eg, T->U). # Elements of a Prosite pattern class PrositeTerm: def __init__(self, letters, ignore, is_begin, is_end, \ min_count, max_count, can_begin, can_end): self.letters = letters self.ignore = ignore self.is_begin = is_begin self.is_end = is_end self.min_count = min_count self.max_count = max_count self.can_begin = can_begin self.can_end = can_end def copy(self): return PrositeTerm(self.letters, self.ignore, self.is_begin, self.is_end, self.min_count, self.max_count, self.can_begin, self.can_end) def __str__(self): # Convert the term back into Prosite form s = self.base_str() if self.min_count == self.max_count: if self.min_count == 1: pass else: s = s + "(%d)" % self.min_count else: s = s + "(%d,%d)" % (self.min_count, self.max_count) if self.is_end: s = s + ">" return s def base_str(self): # Convert the term back into Prosite form, without the repeat # count fields. if self.is_begin: s = "<" else: s = "" if self.ignore: s = s + "{" + self.letters + "}" elif len(self.letters) == 1 and \ (not self.can_begin and not self.can_end): s = s + self.letters else: s = s + "[" if self.can_begin: s = s + "<" s = s + self.letters if self.can_end: s = s + ">" s = s + "]" return s # Results of a Prosite match. Wrapper to the re.MatchObj, but returns # Seq objects instead of strings. And lookee - it implements the Seq # interface too! class PrositeMatch: def __init__(self, prosite, seq, match): self.prosite = prosite self.seq = seq self.match = match self.pos = match.pos self.endpos = match.pos # for Seq.Seq initialization self.data = match.group(0) self.alphabet = seq.alphabet def __repr__(self): # XXX this isn't the right way return "<PrositeMatch instance at %x>" % id(self) def __str__(self): return str(self.data) def __len__(self): return len(self.data) def __getitem__(self, i): return self.data[i] def __getslice__(self, i, j): i = max(i, 0); j = max(j, 0) return Seq.Seq(self.data[i:j], self.alphabet) def mapping(self): """return a list of numbers mapping to items of the original pattern For example, if the Prosite pattern is "[AP](2)-D." matched against "PAD", then the mapping is [1, 1, 2], meaning the first character of the match ("P") is from the first Prosite group ("[AP]"), as is the second letter ("A"). The 3rd letter ("D") is mapped to group 2 of the pattern. """ vals = [] i = 0 start = self.start(0) try: while 1: end = self.match.end(i+1) while start < end: vals.append(i) start = start + 1 i = i + 1 except IndexError: pass return vals def mapped_pattern(self): """returns the specific Prosite pattern used to find this sequence >>> p = Prosite.compile("[AP](2,3)-D.") >>> m = p.search(Seq.Seq("PAD")) >>> mapping = m.mapping() >>> mapped = m.mapped_pattern() >>> print str(m[1]), str(p[mapping[1]]), str(mapped[1]) P [AP](2,3) [AP] >>> print str(mapped) [AP]-[AP]-D. >>> Note that the original term includes the count, while the mapped pattern does the expansion. """ return pattern_mapping(self.prosite, self.mapping()) def start(self, g=0): return self.match.start(g) def end(self, g=0): return self.match.end(g) def span(self, g): return self.match.span(g) def groups(self, default=None): result = [] alphabet = self.alphabet for g in self.match.groups(default): result.append( Seq.Seq(g, alphabet) ) return tuple(result) def group(self, groups): result = self.match.group(groups) if result == (): return result if len(result) == 1: return Seq.Seq(result, self.alphabet) retval = [] for x in result: retval.append(Seq.Seq(x, self.alphabet)) return tuple(retval) def pattern_mapping(prosite, mapping): data = [] for i in mapping: x = prosite[i].copy() x.min_count = x.max_count = 1 data.append(x) return Prosite(data=data) prosite_term_re = re.compile(r""" (?: ([ABCDEFGHIKLMNPQRSTVWXYZx])\| # a character OR \[(<?)([ABCDEFGHIKLMNPQRSTVWXYZ]+)(>?)\]\| # something in []s OR \{([ABCDEFGHIKLMNPQRSTVWXYZ]+)\} # something in {}s )(?:\((\d+)(,\d+)?\))? # optional count of the form "(i,j)", ",j" optional $ """, re.VERBOSE) # This does not verify the pattern is correct - invalid patterns can # be converted! def find_terms(pattern): if pattern[-1:] != ".": raise TypeError("not a prosite pattern - needs a final '.'") pattern = pattern[:-1] terms = pattern.split("-") result = [] i = 0 for term in terms: can_begin = can_end = 0 # Starts with a "<"? if term[:1] == "<": term = term[1:] is_begin = 1 else: is_begin = 0 # Ends with a ">"? if term[-1:] == ">": term = term[:-1] is_end = 1 else: is_end = 0 match = prosite_term_re.match(term) if match is None: raise TypeError("not a Prosite term (%s)" % repr(term)) if match.group(1) is not None: # Single letter ignore = 0 letters = match.group(1) elif match.group(3) is not None: # Letters inside of "[]"s ignore = 0 letters = match.group(3) if match.group(2): can_begin = 1 if i != 0: raise TypeError("[<] only allowed for first term (%s)" \ % repr(term)) if match.group(4): can_end = 1 if i != len(terms) - 1: raise TypeError("[>] only allowed for last term (%s)" \ % repr(term)) elif match.group(5) is not None: # Letters inside of "{}"s ignore = 1 letters = match.group(5) else: raise TypeError("not a prosite term (%s)" % repr(term)) if match.group(6) is not None: # there is a minimum number min_count = int(match.group(6)) else: # no min, so it's 1 min_count = 1 if match.group(7) is not None: # there is a maximum number max_count = int(match.group(7)[1:]) else: # no max specified, so use the same as the min max_count = min_count result.append(PrositeTerm(letters, ignore, is_begin, is_end, min_count, max_count, can_begin, can_end)) i = i + 1 return result prosite_re = re.compile(r""" ^<? # starts with an optional "<" ( [ABCDEFGHIKLMNPQRSTVWXYZx]\| # a character OR (\[<?[ABCDEFGHIKLMNPQRSTVWXYZ]+>?\])\| # something in []s OR \{[ABCDEFGHIKLMNPQRSTVWXYZ]+\} # something in {}s )(\(\d+(,\d+)?\))? # optional count of the form "(i,j)" (",j" is optional) (- # new terms seperated by a '-' ( [ABCDEFGHIKLMNPQRSTVWXYZx]\| # a character OR \[[ABCDEFGHIKLMNPQRSTVWXYZ]+>?\]\| # something in []s OR \{[ABCDEFGHIKLMNPQRSTVWXYZ]+\} # something in {}s )(\(\d+(,\d+)?\))? # optional count )* # repeat until done >? # pattern ends with an optional ">" \.$ # description ends with a required "." """, re.VERBOSE) # This verifies the pattern is correct. def verify_pattern(pattern): """returns 1 if the Prosite pattern is syntactically correct, else 0""" x = prosite_re.match(pattern) if x is None: return 0 # check there's only one [< at the beginning, or >] at the end if pattern.find("[<", 1) != -1: return 0 if pattern.find(">]", 0, len(pattern)-2) != -1: return 0 return 1 def _verify_test(infile): """verify the patterns from a Prosite file handle""" pattern = "" while 1: line = infile.readline() if not line: break if line[:2] != "PA": continue pattern = pattern + line[5:-1] if line[-2] == ".": try: print "" 60 print pattern p = compile(pattern) print prosite_to_re(pattern) print repr(p.re) print prosite_to_grouped_re(pattern) print repr(p.grouped_re) terms = str(p) if terms != pattern: print "DIFFER", terms, pattern except TypeError, msg: print "PROBLEM", pattern, msg pattern = "" # Commented out by jchang 4/13/00. # Specific to Andrew's test environment. #if __name__ == "__main__": # import os # infile = os.popen("bzcat /home/dalke/ftps/prosite/prosite.dat.bz2 \| grep ^PA") # _verify_test(infile)	BlogomaticProject/Blogomatic	opt/blog-o-matic/usr/lib/python/Bio/Prosite/Pattern.py	Python	gpl-2.0	16,587	[ "Biopython" ]	61bc6d0fe983802639276b2f58443f70563a26a73b7b9eecbf2c3d6428db449a
""" Uniweb validator project w3c.py : Checks URL against W3C validators in various ways Copyright (c) 2009 Brian Shumate Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import datetime import httplib2 import urllib2 from datetime import timedelta from BeautifulSoup import BeautifulSoup from surfbot.validator.models import Website def checkhtml(site_pk): """ Checks URL against W3C HTML validator website Eventually, this will be pointed directly at a local instance as part of the whole appliance idea. """ today = datetime.date.today() w3chtml = "http://validator.w3.org/check?uri=" w = Website.objects.get(pk=site_pk) w.checkok = False w.htmlval = 'Fail' w.lastcheck = today week = timedelta(days=7) day = timedelta(hours=24) h = httplib2.Http(".cache") resp, content = h.request(w3chtml + w.rooturl, "GET") validator = BeautifulSoup(content) if validator.find('h3', 'invalid'): w.checkok = True w.nextcheck = today + day w.checktotal += 1 w.htmlval = 'Fail' w.htmlval_fcount += 1 w.save() return w.htmlval else: w.checkok = True w.nextcheck = today + week w.checktotal += 1 w.htmlval = 'Pass' w.htmlval_pcount += 1 w.save() return w.htmlval def checkcss(site_pk): """ Checks URL against W3C CSS validator website """ today = datetime.date.today() w3ccss = "http://jigsaw.w3.org/css-validator/validator?uri=" w = Website.objects.get(pk=site_pk) w.checkok = False w.cssval = 'Fail' w.lastcheck = today week = timedelta(days=7) day = timedelta(hours=24) h = httplib2.Http(".cache") resp, content = h.request(w3ccss + w.rooturl, "GET") validator = BeautifulSoup(content) if validator.find('div', id='errors'): w.checkok = True w.nextcheck = today + day w.checktotal += 1 w.cssval = 'Fail' w.cssval_fcount += 1 w.save() return w.cssval else: w.checkok = True w.nextcheck = today + week w.checktotal += 1 w.cssval = 'Pass' w.cssval_pcount += 1 w.save() return w.cssval	brianshumate/uniweb	surfbot/utils/w3c.py	Python	bsd-2-clause	3,219	[ "Brian" ]	13f910fd6b559f01446cac87f4b287fc2abd08956a2775895d7a9174147b2657
""" Extremely simple utility class to send mails """ import os import socket from smtplib import SMTP, SMTP_SSL from email.mime.application import MIMEApplication from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText from getpass import getuser from DIRAC import gLogger, S_OK, S_ERROR class Mail(object): def __init__(self): self._subject = "" self._message = "" self._mailAddress = "" self._html = False self._fromAddress = getuser() + "@" + socket.getfqdn() self._attachments = [] self.esmtp_features = {} self._smtpPtcl = None self._smtpHost = None self._smtpPort = None self._smtpLogin = None self._smtpPasswd = None def _create(self, addresses): """create a mail object :param list addresses: addresses :return: S_OK(object)/S_ERROR() -- contain MIMEMultipart object """ if not isinstance(addresses, list): addresses = [addresses] if not self._mailAddress: gLogger.warn("No mail address was provided. Mail not sent.") return S_ERROR("No mail address was provided. Mail not sent.") if not self._message: gLogger.warn("Message body is empty") if not self._subject: gLogger.warn("Subject and body empty. Mail not sent") return S_ERROR("Subject and body empty. Mail not sent") if self._html: mail = MIMEText(self._message, "html") else: mail = MIMEText(self._message, "plain") msg = MIMEMultipart() msg.attach(mail) msg["Subject"] = self._subject msg["From"] = self._fromAddress msg["To"] = ", ".join(addresses) for attachment in self._attachments: try: with open(attachment, "rb") as fil: part = MIMEApplication(fil.read(), Name=os.path.basename(attachment)) part["Content-Disposition"] = 'attachment; filename="%s"' % os.path.basename(attachment) msg.attach(part) except IOError as e: gLogger.exception("Could not attach %s" % attachment, lException=e) return S_OK(msg) def _send(self, msg=None): """send a single email message. If msg is in input, it is expected to be of email type, otherwise it will create it. :param object msg: MIMEMultipart object :return: S_OK()/S_ERROR() """ if msg is None: addresses = self._mailAddress if isinstance(self._mailAddress, str): addresses = self._mailAddress.split(", ") result = self._create(addresses) if not result["OK"]: return result msg = result["Value"] if self._smtpPtcl == "SSL": smtp = SMTP_SSL() else: smtp = SMTP() smtp.set_debuglevel(0) try: connParams = {} if self._smtpHost: connParams["host"] = self._smtpHost if self._smtpPort: connParams["port"] = int(self._smtpPort) smtp.connect(**connParams) smtp.ehlo_or_helo_if_needed() if self._smtpPtcl == "TLS": smtp.starttls() if self._smtpLogin and self._smtpPasswd: smtp.login(self._smtpLogin, self._smtpPasswd) smtp.ehlo_or_helo_if_needed() smtp.sendmail(self._fromAddress, addresses, msg.as_string()) except Exception as x: return S_ERROR("Sending mail failed %s" % str(x)) smtp.quit() return S_OK("The mail was successfully sent") def __eq__(self, other): """Comparing an email object to another""" if isinstance(other, Mail): if self.__dict__ == other.__dict__: return True return False def __hash__(self): """Comparing for sets""" return hash(self._subject + self._message + self._fromAddress + self._mailAddress)	DIRACGrid/DIRAC	src/DIRAC/Core/Utilities/Mail.py	Python	gpl-3.0	4,124	[ "DIRAC" ]	e1a7568481552cec7beb8ab3ae2fa1917ece72acc0281d8c538724fff3ff2fbb
# Adapted from Bio.AlignIO.FastaIO copyright 2008-2011 by Peter Cock. # Copyright 2012 by Wibowo Arindrarto. # All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. """Bio.SearchIO support for Bill Pearson's FASTA tools. This module adds support for parsing FASTA outputs. FASTA is a suite of programs that finds regions of local or global similarity between protein or nucleotide sequences, either by searching databases or identifying local duplications. Bio.SearchIO.FastaIO was tested on the following FASTA flavors and versions: - flavors: fasta, ssearch, tfastx - versions: 35, 36 Other flavors and/or versions may introduce some bugs. Please file a bug report if you see such problems to Biopython's bug tracker. More information on FASTA are available through these links: - Website: http://fasta.bioch.virginia.edu/fasta_www2/fasta_list2.shtml - User guide: http://fasta.bioch.virginia.edu/fasta_www2/fasta_guide.pdf Supported Formats ================= Bio.SearchIO.FastaIO supports parsing and indexing FASTA outputs triggered by the -m 10 flag. Other formats that mimic other programs (e.g. the BLAST tabular format using the -m 8 flag) may be parseable but using SearchIO's other parsers (in this case, using the 'blast-tab' parser). fasta-m10 ========= Note that in FASTA -m 10 outputs, HSPs from different strands are considered to be from different hits. They are listed as two separate entries in the hit table. FastaIO recognizes this and will group HSPs with the same hit ID into a single Hit object, regardless of strand. FASTA also sometimes output extra sequences adjacent to the HSP match. These extra sequences are discarded by FastaIO. Only regions containing the actual sequence match are extracted. The following object attributes are provided: +-----------------+-------------------------+----------------------------------+ \| Object \| Attribute \| Value \| +=================+=========================+==================================+ \| QueryResult \| description \| query sequence description \| \| +-------------------------+----------------------------------+ \| \| id \| query sequence ID \| \| +-------------------------+----------------------------------+ \| \| program \| FASTA flavor \| \| +-------------------------+----------------------------------+ \| \| seq_len \| full length of query sequence \| \| +-------------------------+----------------------------------+ \| \| target \| target search database \| \| +-------------------------+----------------------------------+ \| \| version \| FASTA version \| +-----------------+-------------------------+----------------------------------+ \| Hit \| seq_len \| full length of the hit sequence \| +-----------------+-------------------------+----------------------------------+ \| HSP \| bitscore \| \_bits line \| \| +-------------------------+----------------------------------+ \| \| evalue \| \_expect line \| \| +-------------------------+----------------------------------+ \| \| ident_pct \| \_ident line \| \| +-------------------------+----------------------------------+ \| \| init1_score \| \_init1 line \| \| +-------------------------+----------------------------------+ \| \| initn_score \| \_initn line \| \| +-------------------------+----------------------------------+ \| \| opt_score \| \_opt line, \_s-w opt line \| \| +-------------------------+----------------------------------+ \| \| pos_pct \| \_sim line \| \| +-------------------------+----------------------------------+ \| \| sw_score \| \_score line \| \| +-------------------------+----------------------------------+ \| \| z_score \| \_z-score line \| +-----------------+-------------------------+----------------------------------+ \| HSPFragment \| aln_annotation \| al_cons block, if present \| \| (also via HSP) +-------------------------+----------------------------------+ \| \| hit \| hit sequence \| \| +-------------------------+----------------------------------+ \| \| hit_end \| hit sequence end coordinate \| \| +-------------------------+----------------------------------+ \| \| hit_start \| hit sequence start coordinate \| \| +-------------------------+----------------------------------+ \| \| hit_strand \| hit sequence strand \| \| +-------------------------+----------------------------------+ \| \| query \| query sequence \| \| +-------------------------+----------------------------------+ \| \| query_end \| query sequence end coordinate \| \| +-------------------------+----------------------------------+ \| \| query_start \| query sequence start coordinate \| \| +-------------------------+----------------------------------+ \| \| query_strand \| query sequence strand \| +-----------------+-------------------------+----------------------------------+ """ import re from Bio._py3k import _as_bytes, _bytes_to_string from Bio.Alphabet import generic_dna, generic_protein from Bio.File import UndoHandle from Bio.SearchIO._index import SearchIndexer from Bio.SearchIO._model import QueryResult, Hit, HSP, HSPFragment __all__ = ['FastaM10Parser', 'FastaM10Indexer'] __docformat__ = "restructuredtext en" # precompile regex patterns # regex for program name _RE_FLAVS = re.compile(r't?fast[afmsxy]\|pr[sf][sx]\|lalign\|[gs]?[glso]search') # regex for sequence ID and length ~ deals with both \n and \r\n _PTR_ID_DESC_SEQLEN = r'>>>(.+?)\s+(.?) - (\d+) (?:aa\|nt)\s$' _RE_ID_DESC_SEQLEN = re.compile(_PTR_ID_DESC_SEQLEN) _RE_ID_DESC_SEQLEN_IDX = re.compile(_as_bytes(_PTR_ID_DESC_SEQLEN)) # regex for qresult, hit, or hsp attribute value _RE_ATTR = re.compile(r'^; [a-z]+(_[ \w-]+):\s+(.)$') # regex for capturing excess start and end sequences in alignments _RE_START_EXC = re.compile(r'^-') _RE_END_EXC = re.compile(r'-$') # attribute name mappings _HSP_ATTR_MAP = { '_initn': ('initn_score', int), '_init1': ('init1_score', int), '_opt': ('opt_score', int), '_s-w opt': ('opt_score', int), '_z-score': ('z_score', float), '_bits': ('bitscore', float), '_expect': ('evalue', float), '_score': ('sw_score', int), '_ident': ('ident_pct', float), '_sim': ('pos_pct', float), } # state flags _STATE_NONE = 0 _STATE_QUERY_BLOCK = 1 _STATE_HIT_BLOCK = 2 _STATE_CONS_BLOCK = 3 def _set_qresult_hits(qresult, hit_rows=[]): """Helper function for appending Hits without alignments into QueryResults.""" for hit_row in hit_rows: hit_id, remainder = hit_row.split(' ', 1) # TODO: parse hit and hsp properties properly; by dealing with: # - any character in the description (brackets, spaces, etc.) # - possible [f] or [r] presence (for frame info) # - possible presence of E2() column # - possible incomplete hit_id due to column length limit # The current method only looks at the Hit ID, none of the things above if hit_id not in qresult: frag = HSPFragment(hit_id, qresult.id) hsp = HSP([frag]) hit = Hit([hsp]) qresult.append(hit) return qresult def _set_hsp_seqs(hsp, parsed, program): """Helper function for the main parsing code. :param hsp: HSP whose properties will be set :type hsp: HSP :param parsed: parsed values of the HSP attributes :type parsed: dictionary {string: object} :param program: program name :type program: string """ # get aligned sequences and check if they have equal lengths start = 0 for seq_type in ('hit', 'query'): if 'tfast' not in program: pseq = parsed[seq_type] # adjust start and end coordinates based on the amount of # filler characters start, stop = _get_aln_slice_coords(pseq) start_adj = len(re.search(_RE_START_EXC, pseq['seq']).group(0)) stop_adj = len(re.search(_RE_END_EXC, pseq['seq']).group(0)) start = start + start_adj stop = stop + start_adj - stop_adj parsed[seq_type]['seq'] = pseq['seq'][start:stop] assert len(parsed['query']['seq']) == len(parsed['hit']['seq']), "%r %r" \ % (len(parsed['query']['seq']), len(parsed['hit']['seq'])) if 'similarity' in hsp.aln_annotation: # only using 'start' since FASTA seems to have trimmed the 'excess' # end part hsp.aln_annotation['similarity'] = hsp.aln_annotation['similarity'][start:] # hit or query works equally well here assert len(hsp.aln_annotation['similarity']) == len(parsed['hit']['seq']) # query and hit sequence types must be the same assert parsed['query']['_type'] == parsed['hit']['_type'] type_val = parsed['query']['_type'] # hit works fine too alphabet = generic_dna if type_val == 'D' else generic_protein setattr(hsp.fragment, 'alphabet', alphabet) for seq_type in ('hit', 'query'): # get and set start and end coordinates start = int(parsed[seq_type]['_start']) end = int(parsed[seq_type]['_stop']) setattr(hsp.fragment, seq_type + '_start', min(start, end) - 1) setattr(hsp.fragment, seq_type + '_end', max(start, end)) # set seq and alphabet setattr(hsp.fragment, seq_type, parsed[seq_type]['seq']) if alphabet is not generic_protein: # get strand from coordinate; start <= end is plus # start > end is minus if start <= end: setattr(hsp.fragment, seq_type + '_strand', 1) else: setattr(hsp.fragment, seq_type + '_strand', -1) else: setattr(hsp.fragment, seq_type + '_strand', 0) def _get_aln_slice_coords(parsed_hsp): """Helper function for the main parsing code. To get the actual pairwise alignment sequences, we must first translate the un-gapped sequence based coordinates into positions in the gapped sequence (which may have a flanking region shown using leading - characters). To date, I have never seen any trailing flanking region shown in the m10 file, but the following code should also cope with that. Note that this code seems to work fine even when the "sq_offset" entries are prsent as a result of using the -X command line option. """ seq = parsed_hsp['seq'] seq_stripped = seq.strip('-') disp_start = int(parsed_hsp['_display_start']) start = int(parsed_hsp['_start']) stop = int(parsed_hsp['_stop']) if start <= stop: start = start - disp_start stop = stop - disp_start + 1 else: start = disp_start - start stop = disp_start - stop + 1 stop += seq_stripped.count('-') assert 0 <= start and start < stop and stop <= len(seq_stripped), \ "Problem with sequence start/stop,\n%s[%i:%i]\n%s" \ % (seq, start, stop, parsed_hsp) return start, stop class FastaM10Parser(object): """Parser for Bill Pearson's FASTA suite's -m 10 output.""" def __init__(self, handle, __parse_hit_table=False): self.handle = UndoHandle(handle) self._preamble = self._parse_preamble() def __iter__(self): for qresult in self._parse_qresult(): # re-set desc, for hsp query description qresult.description = qresult.description yield qresult def _parse_preamble(self): """Parses the Fasta preamble for Fasta flavor and version.""" preamble = {} while True: self.line = self.handle.readline() # this should be the line just before the first qresult if self.line.startswith('Query'): break # try to match for version line elif self.line.startswith(' version'): preamble['version'] = self.line.split(' ')[2] else: # try to match for flavor line flav_match = re.match(_RE_FLAVS, self.line.lower()) if flav_match: preamble['program'] = flav_match.group(0) return preamble def __parse_hit_table(self): """Parses hit table rows.""" # move to the first row self.line = self.handle.readline() # parse hit table until we see an empty line hit_rows = [] while self.line and not self.line.strip(): hit_rows.append(self.line.strip()) self.line = self.handle.readline() return hit_rows def _parse_qresult(self): # initial qresult value qresult = None hit_rows = [] # state values state_QRES_NEW = 1 state_QRES_HITTAB = 3 state_QRES_CONTENT = 5 state_QRES_END = 7 while True: # one line before the hit table if self.line.startswith('The best scores are:'): qres_state = state_QRES_HITTAB # the end of a query or the file altogether elif self.line.strip() == '>>>///' or not self.line: qres_state = state_QRES_END # the beginning of a new query elif not self.line.startswith('>>>') and '>>>' in self.line: qres_state = state_QRES_NEW # the beginning of the query info and its hits + hsps elif self.line.startswith('>>>') and not \ self.line.strip() == '>>><<<': qres_state = state_QRES_CONTENT # default qres mark else: qres_state = None if qres_state is not None: if qres_state == state_QRES_HITTAB: # parse hit table if flag is set hit_rows = self.__parse_hit_table() elif qres_state == state_QRES_END: yield _set_qresult_hits(qresult, hit_rows) break elif qres_state == state_QRES_NEW: # if qresult is filled, yield it first if qresult is not None: yield _set_qresult_hits(qresult, hit_rows) regx = re.search(_RE_ID_DESC_SEQLEN, self.line) query_id = regx.group(1) seq_len = regx.group(3) desc = regx.group(2) qresult = QueryResult(id=query_id) qresult.seq_len = int(seq_len) # get target from the next line self.line = self.handle.readline() qresult.target = [x for x in self.line.split(' ') if x][1].strip() if desc is not None: qresult.description = desc # set values from preamble for key, value in self._preamble.items(): setattr(qresult, key, value) elif qres_state == state_QRES_CONTENT: assert self.line[3:].startswith(qresult.id), self.line for hit, strand in self._parse_hit(query_id): # HACK: re-set desc, for hsp hit and query description hit.description = hit.description hit.query_description = qresult.description # if hit is not in qresult, append it if hit.id not in qresult: qresult.append(hit) # otherwise, it might be the same hit with a different strand else: # make sure strand is different and then append hsp to # existing hit for hsp in hit.hsps: assert strand != hsp.query_strand qresult[hit.id].append(hsp) self.line = self.handle.readline() def _parse_hit(self, query_id): while True: self.line = self.handle.readline() if self.line.startswith('>>'): break state = _STATE_NONE strand = None hsp_list = [] while True: peekline = self.handle.peekline() # yield hit if we've reached the start of a new query or # the end of the search if peekline.strip() in [">>><<<", ">>>///"] or \ (not peekline.startswith('>>>') and '>>>' in peekline): # append last parsed_hsp['hit']['seq'] line if state == _STATE_HIT_BLOCK: parsed_hsp['hit']['seq'] += self.line.strip() elif state == _STATE_CONS_BLOCK: hsp.aln_annotation['similarity'] += \ self.line.strip('\r\n') # process HSP alignment and coordinates _set_hsp_seqs(hsp, parsed_hsp, self._preamble['program']) hit = Hit(hsp_list) hit.description = hit_desc hit.seq_len = seq_len yield hit, strand hsp_list = [] break # yield hit and create a new one if we're still in the same query elif self.line.startswith('>>'): # try yielding, if we have hsps if hsp_list: _set_hsp_seqs(hsp, parsed_hsp, self._preamble['program']) hit = Hit(hsp_list) hit.description = hit_desc hit.seq_len = seq_len yield hit, strand hsp_list = [] # try to get the hit id and desc, and handle cases without descs try: hit_id, hit_desc = self.line[2:].strip().split(' ', 1) except ValueError: hit_id = self.line[2:].strip().split(' ', 1)[0] hit_desc = '' # create the HSP object for Hit frag = HSPFragment(hit_id, query_id) hsp = HSP([frag]) hsp_list.append(hsp) # set or reset the state to none state = _STATE_NONE parsed_hsp = {'query': {}, 'hit': {}} # create and append a new HSP if line starts with '>--' elif self.line.startswith('>--'): # set seq attributes of previous hsp _set_hsp_seqs(hsp, parsed_hsp, self._preamble['program']) # and create a new one frag = HSPFragment(hit_id, query_id) hsp = HSP([frag]) hsp_list.append(hsp) # set the state ~ none yet state = _STATE_NONE parsed_hsp = {'query': {}, 'hit': {}} # this is either query or hit data in the HSP, depending on the state elif self.line.startswith('>'): if state == _STATE_NONE: # make sure it's the correct query assert query_id.startswith(self.line[1:].split(' ')[0]), \ "%r vs %r" % (query_id, self.line) state = _STATE_QUERY_BLOCK parsed_hsp['query']['seq'] = '' elif state == _STATE_QUERY_BLOCK: # make sure it's the correct hit assert hit_id.startswith(self.line[1:].split(' ')[0]) state = _STATE_HIT_BLOCK parsed_hsp['hit']['seq'] = '' # check for conservation block elif self.line.startswith('; al_cons'): state = _STATE_CONS_BLOCK hsp.fragment.aln_annotation['similarity'] = '' elif self.line.startswith(';'): # Fasta outputs do not make a clear distinction between Hit # and HSPs, so we check the attribute names to determine # whether it belongs to a Hit or HSP regx = re.search(_RE_ATTR, self.line.strip()) name = regx.group(1) value = regx.group(2) # for values before the '>...' query block if state == _STATE_NONE: if name in _HSP_ATTR_MAP: attr_name, caster = _HSP_ATTR_MAP[name] if caster is not str: value = caster(value) if name in ['_ident', '_sim']: value *= 100 setattr(hsp, attr_name, value) # otherwise, pool the values for processing later elif state == _STATE_QUERY_BLOCK: parsed_hsp['query'][name] = value elif state == _STATE_HIT_BLOCK: if name == '_len': seq_len = int(value) else: parsed_hsp['hit'][name] = value # for values in the hit block else: raise ValueError("Unexpected line: %r" % self.line) # otherwise, it must be lines containing the sequences else: assert '>' not in self.line # if we're in hit, parse into hsp.hit if state == _STATE_HIT_BLOCK: parsed_hsp['hit']['seq'] += self.line.strip() elif state == _STATE_QUERY_BLOCK: parsed_hsp['query']['seq'] += self.line.strip() elif state == _STATE_CONS_BLOCK: hsp.fragment.aln_annotation['similarity'] += \ self.line.strip('\r\n') # we should not get here! else: raise ValueError("Unexpected line: %r" % self.line) self.line = self.handle.readline() class FastaM10Indexer(SearchIndexer): """Indexer class for Bill Pearson's FASTA suite's -m 10 output.""" _parser = FastaM10Parser def __init__(self, filename): SearchIndexer.__init__(self, filename) self._handle = UndoHandle(self._handle) def __iter__(self): handle = self._handle handle.seek(0) start_offset = handle.tell() qresult_key = None query_mark = _as_bytes('>>>') while True: line = handle.readline() peekline = handle.peekline() end_offset = handle.tell() if not line.startswith(query_mark) and query_mark in line: regx = re.search(_RE_ID_DESC_SEQLEN_IDX, line) qresult_key = _bytes_to_string(regx.group(1)) start_offset = end_offset - len(line) # yield whenever we encounter a new query or at the end of the file if qresult_key is not None: if (not peekline.startswith(query_mark) and query_mark in peekline) or not line: yield qresult_key, start_offset, end_offset - start_offset if not line: break start_offset = end_offset def get_raw(self, offset): handle = self._handle qresult_raw = _as_bytes('') query_mark = _as_bytes('>>>') # read header first handle.seek(0) while True: line = handle.readline() peekline = handle.peekline() qresult_raw += line if not peekline.startswith(query_mark) and query_mark in peekline: break # and read the qresult raw string handle.seek(offset) while True: # preserve whitespace, don't use read_forward line = handle.readline() peekline = handle.peekline() qresult_raw += line # break when we've reached qresult end if (not peekline.startswith(query_mark) and query_mark in peekline) or \ not line: break # append mock end marker to qresult_raw, since it's not always present return qresult_raw + _as_bytes('>>><<<\n') # if not used as a module, run the doctest if __name__ == "__main__": from Bio._utils import run_doctest run_doctest()	poojavade/Genomics_Docker	Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/Bio/SearchIO/FastaIO.py	Python	apache-2.0	25,572	[ "BLAST", "Biopython" ]	bd8d3032fba626e4e600202a7d56298d0e352f1c5ed17de1be0f8edf7d535d2e
import os import glob import sys import shutil import pysam from bcbio.pipeline import config_utils from bcbio.distributed.transaction import file_transaction, tx_tmpdir from bcbio.utils import (safe_makedir, file_exists) from bcbio.provenance import do from bcbio import utils from bcbio.log import logger from bcbio.pipeline import datadict as dd from bcbio import bam from bcbio import broad from bcbio.wgbsseq import kits def align(fastq_file, pair_file, ref_file, names, align_dir, data): assert data["analysis"].lower().startswith("wgbs-seq"), "No comparible alignment." config = data["config"] sample = dd.get_sample_name(data) out_prefix = os.path.join(align_dir, dd.get_lane(data)) out_dir = os.path.join(align_dir, "%s_bismark" % dd.get_lane(data)) if not ref_file: logger.error("bismark index not found. You can install " "the index for your genome with: bcbio_nextgen.py upgrade " "--aligners bismark --genomes genome-build-name --data") sys.exit(1) final_out = os.path.join(align_dir, "{0}.bam".format(sample)) if file_exists(final_out): data = dd.set_work_bam(data, final_out) data["bam_report"] = glob.glob(os.path.join(out_dir, "report.txt"))[0] data = dd.update_summary_qc(data, "bismark", base=data["bam_report"]) return data bismark = config_utils.get_program("bismark", config) # bismark uses 5 threads/sample and ~12GB RAM/sample (hg38) resources = config_utils.get_resources("bismark", data["config"]) max_cores = dd.get_num_cores(data) max_mem = config_utils.convert_to_bytes(resources.get("memory", "1G")) / (1024.0 1024.0) instances = calculate_bismark_instances(max_cores, max_mem * max_cores) kit = kits.KITS.get(dd.get_kit(data), None) directional = "--non_directional" if kit and not kit.is_directional else "" other_opts = resources.get("options", []) other_opts = " ".join([str(x) for x in other_opts]).strip() fastq_files = " ".join([fastq_file, pair_file]) if pair_file else fastq_file safe_makedir(align_dir) cmd = "{bismark} {other_opts} {directional} --bowtie2 --temp_dir {tx_out_dir} --gzip --parallel {instances} -o {tx_out_dir} --unmapped {ref_file} {fastq_file} " if pair_file: fastq_file = "-1 %s -2 %s" % (fastq_file, pair_file) raw_bam = glob.glob(out_dir + "/bismarkbt2bam") if not raw_bam: with tx_tmpdir() as tx_out_dir: run_message = "Running Bismark aligner on %s and %s" % (fastq_file, ref_file) do.run(cmd.format(locals()), run_message, None) shutil.move(tx_out_dir, out_dir) raw_bam = glob.glob(out_dir + "/bismarkbt2bam") # don't process bam in the bismark pipeline! utils.symlink_plus(raw_bam[0], final_out) data = dd.set_work_bam(data, final_out) data["bam_report"] = glob.glob(os.path.join(out_dir, "report.txt"))[0] data = dd.update_summary_qc(data, "bismark", base=data["bam_report"]) return data def _process_bam(bam_file, in_fastq, sample, reference, config): broad_runner = broad.runner_from_config(config) names = {'rg': in_fastq, 'library': 'WGBS_LIB', 'pl': 'Illumina', 'pu': 'R1', 'sm': in_fastq, 'sample': sample} out_fix_bam = broad_runner.run_fn("picard_fix_rgs", bam_file, names) order_bam = utils.append_stem(out_fix_bam, "_order") broad_runner.run_fn("picard_reorder", out_fix_bam, reference, order_bam) bam.index(order_bam, config) # order_bam = _set_quality(order_bam) # bam.index(order_bam, config) return order_bam def remap_index_fn(ref_file): """Map sequence references to equivalent bismark indexes """ return os.path.join(os.path.dirname(os.path.dirname(ref_file)), "bismark") def _set_quality(in_bam): """ change all quality to 255 """ bam = pysam.AlignmentFile(in_bam, "rb") out_file = utils.append_stem(in_bam, "_normqual") if file_exists(out_file): return out_file with file_transaction(out_file) as tx_out: with pysam.AlignmentFile(tx_out, "wb", template=bam) as out_handle: for read in bam.fetch(): read.mapping_quality = 255 out_handle.write(read) return out_file def index(ref_file, out_dir, data): """Create a bismark index in the defined reference directory. """ (ref_dir, local_file) = os.path.split(ref_file) gtf_file = dd.get_transcriptome_gtf(data, default=dd.get_gtf_file(data)) bismark = config_utils.find_program("bismark", data["config"]) if not utils.file_exists(gtf_file): raise ValueError("%s not found, could not create a bismark index." % (gtf_file)) if not utils.file_exists(out_dir): with tx_tmpdir(data, os.path.dirname(out_dir)) as tx_out_dir: num_cores = dd.get_cores(data) other_opts = config_utils.get_resources("bismark", data["config"]).get("options", []) other_opts = " ".join([str(x) for x in other_opts]).strip() cmd = "{bismark} {other_opts} --bowtie2 -p {num_cores} -n 1 -o {tx_out_dir} --basename {sample} --unmapped {ref_file} {in_fastq}" do.run(cmd.format(*locals()), "Index STAR") if os.path.exists(out_dir): shutil.rmtree(out_dir) shutil.move(tx_out_dir, out_dir) return out_dir def calculate_bismark_instances(cores, memory): """ calculate number of parallel bismark instances to run, based on disussion here https://github.com/FelixKrueger/Bismark/issues/96 cores and memory here are the maximum amounts available for us to use """ BISMARK_CORES = 1 BOWTIE_CORES_PER_INSTANCE = 2 SAMTOOLS_CORES_PER_INSTANCE = 1 CORES_PER_INSTANCE = BOWTIE_CORES_PER_INSTANCE + SAMTOOLS_CORES_PER_INSTANCE GENOME_MEMORY_GB = 12 INSTANCE_MEMORY_GB = 10 available_instance_memory = memory - GENOME_MEMORY_GB instances_in_memory = max(available_instance_memory / INSTANCE_MEMORY_GB, 1) available_instance_cores = cores - BISMARK_CORES instances_in_cores = max(available_instance_cores / CORES_PER_INSTANCE, 1) instances = int(min(instances_in_memory, instances_in_cores)) logger.info(f"{cores} cores and {memory} memory are available. Spinning up {instances} instances of bismark.") return instances	chapmanb/bcbio-nextgen	bcbio/ngsalign/bismark.py	Python	mit	6,398	[ "pysam" ]	69365195a18e0530b7d8eb86b36268b1487ca523a86e49cf415b70de43c73404
#!/usr/bin/env python3 #pylint: disable=missing-docstring #* This file is part of the MOOSE framework #* https://www.mooseframework.org #* #* All rights reserved, see COPYRIGHT for full restrictions #* https://github.com/idaholab/moose/blob/master/COPYRIGHT #* #* Licensed under LGPL 2.1, please see LICENSE for details #* https://www.gnu.org/licenses/lgpl-2.1.html import chigger import time import shutil # Open the result shutil.copy('../input/diffusion_1.e', 'new_file.e') reader = chigger.exodus.ExodusReader('new_file.e') mug = chigger.exodus.ExodusResult(reader, variable='u', range=[0, 1], cmap='viridis') # Create the window window = chigger.RenderWindow(mug, size=[600,600], test=True) # Render the results and write a file filenames = ['../input/diffusion_2.e', '../input/diffusion_3.e', '../input/diffusion_4.e'] for i in range(4): window.write('new_files_' + str(i) + '.png') window.update() # Update the file if i < 3: time.sleep(1.5) print("{} --> {}".format(filenames[i], 'new_file.e')) shutil.copy(filenames[i], 'new_file.e') window.start()	nuclear-wizard/moose	python/chigger/tests/new_files/new_files.py	Python	lgpl-2.1	1,104	[ "MOOSE" ]	83a177d53678b899e842277ee96e78f45be0fc35a29ca6a2841cb530342c0ce4
#mono_gauss_coil model #conversion of DebyeModel.py #converted by Steve King, Mar 2016 r""" This Debye Gaussian coil model strictly describes the scattering from monodisperse polymer chains in theta solvents or polymer melts, conditions under which the distances between segments follow a Gaussian distribution. Provided the number of segments is large (ie, high molecular weight polymers) the single-chain form factor P(Q) is that described by Debye (1947). To describe the scattering from polydisperse polymer chains see the :ref:`poly-gauss-coil` model. Definition ---------- .. math:: I(q) = \text{scale} \cdot I_0 \cdot P(q) + \text{background} where .. math:: I_0 &= \phi_\text{poly} \cdot V \cdot (\rho_\text{poly} - \rho_\text{solv})^2 \\ P(q) &= 2 [\exp(-Z) + Z - 1] / Z^2 \\ Z &= (q R_g)^2 \\ V &= M / (N_A \delta) Here, $\phi_\text{poly}$ is the volume fraction of polymer, $V$ is the volume of a polymer coil, M is the molecular weight of the polymer, $N_A$ is Avogadro's Number, $\delta$ is the bulk density of the polymer, $\rho_\text{poly}$ is the sld of the polymer, $\rho\text{solv}$ is the sld of the solvent, and $R_g$ is the radius of gyration of the polymer coil. The 2D scattering intensity is calculated in the same way as the 1D, but where the q vector is redefined as .. math:: q = \sqrt{q_x^2 + q_y^2} References ---------- #. P Debye, J. Phys. Colloid. Chem., 51 (1947) 18. #. R J Roe, Methods of X-Ray and Neutron Scattering in Polymer Science, Oxford University Press, New York (2000). #. http://www.ncnr.nist.gov/staff/hammouda/distance_learning/chapter_28.pdf Authorship and Verification ---------------------------- * Author: * Last Modified by: * Last Reviewed by: """ import numpy as np from numpy import inf name = "mono_gauss_coil" title = "Scattering from monodisperse polymer coils" description = """ Evaluates the scattering from monodisperse polymer chains. """ category = "shape-independent" # pylint: disable=bad-whitespace, line-too-long # ["name", "units", default, [lower, upper], "type", "description"], parameters = [ ["i_zero", "1/cm", 70.0, [0.0, inf], "", "Intensity at q=0"], ["rg", "Ang", 75.0, [0.0, inf], "volume", "Radius of gyration"], ] # pylint: enable=bad-whitespace, line-too-long source = ["mono_gauss_coil.c"] have_Fq = False radius_effective_modes = ["R_g", "2R_g", "3R_g", "sqrt(5/3)R_g"] def random(): """Return a random parameter set for the model.""" rg = 10*np.random.uniform(0, 4) #rg = 1e3 pars = dict( #scale=1, background=0, i_zero=1e7, # i_zero is a simple scale rg=rg, ) return pars # these unit test values taken from SasView 3.1.2 tests = [ [{'scale': 1.0, 'i_zero': 70.0, 'rg': 75.0, 'background': 0.0}, [0.0106939, 0.469418], [57.1241, 0.112859]], ]	SasView/sasmodels	sasmodels/models/mono_gauss_coil.py	Python	bsd-3-clause	2,912	[ "Avogadro", "Gaussian" ]	120bbf6625d47904d80564e342134261f9d192ab6f7416fee5971d5883c6a183
import subprocess import sys import time from datetime import datetime #print(sys.argv[0]) print(""" Wifi Packet Sniffer v0.1 ------------------------------- Options: -c Channel to listen on -m Target address -i Interface to use Credits: Re-scripted by scriptedp0ison Original program airodump-ng created by Thomas d'Otreppe Visit http://www.aircrack-ng.org for more info """) if sys.argv > 1 and sys.argv > 2 and sys.argv > 3 and sys.argv > 4 and sys.argv > 5 and sys.argv > 6: #subprocess.call(sys.argv[1], shell=True) print('[+] Channel set to: {}'.format(sys.argv[2])) time.sleep(2) print('[+] Target mac set to: {}'.format(sys.argv[4])) time.sleep(2) print('[+] Network card set to listen on: {}'.format(sys.argv[6])) time.sleep(2) print('[+] Compiling system arguments...') time.sleep(1) print('[+] Executing system arguments...') time.sleep(2) launch_attack = 'airodump-ng -c {} --bssid {} {}'.format(sys.argv[2], sys.argv[4], sys.argv[6]) subprocess.call(launch_attack, shell=True) if sys.argv[1] == '-h' or sys.argv[1] == '-help' or sys.argv[1] == '--help': print(""" Wifi Dosser v0.1 - Do not use for illegal purposes! Do not test on networks you dont own or have permission to test! _____________________________________________________________________________________________________________________ Options: -h Display the help screen -m Target MAC Address -c channel to listen on -i Network Interface card Examples: python get_client.py -c <channel to listen on> -m <target mac address> -i <NIC> """)	scriptedp0ison/Kali-Linux-Wifi-Short-Cut-Scripts	get_client.py	Python	gpl-3.0	1,554	[ "VisIt" ]	022c12fff59a58346adccb3782c70b2e9f9c1f80c58ee7cda6f2914a468b57ab
#!/usr/bin/env python # -- coding: utf-8 -- # # king_phisher/client/client_rpc.py # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of the project nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # import code import collections import functools import logging import os import queue import ssl import sys from king_phisher import errors from king_phisher import find from king_phisher import geoip from king_phisher import serializers from king_phisher import utilities from king_phisher.client import gui_utilities import advancedhttpserver import boltons.typeutils import smoke_zephyr.utilities from gi.repository import Gtk _tag_mixin_slots = ('id', 'name', 'description') _tag_mixin_types = (int, str, str) _tag_tables = ('campaign_types', 'campaigns', 'companies', 'company_departments', 'industries') database_table_objects = utilities.FreezableDict() UNRESOLVED = boltons.typeutils.make_sentinel('UNRESOLVED', var_name='UNRESOLVED') """A sentinel value used for values in rows to indicate that the data has not been loaded from the server.""" _WorkItem = collections.namedtuple('_WorkItem', ('callback_on_success', 'callback_on_error', 'callback_when_idle', 'callback_args', 'callback_kwargs', 'method', 'args', 'kwargs') ) class RemoteRowMeta(type): def __new__(mcs, name, bases, dct): dct['__slots__'] = ('__rpc__',) + dct.get('__slots__', ()) return super(RemoteRowMeta, mcs).__new__(mcs, name, bases, dct) def __init__(cls, args, kwargs): table_name = getattr(cls, '__table__', None) if table_name: database_table_objects[table_name] = cls super(RemoteRowMeta, cls).__init__(args, *kwargs) # stylized metaclass definition to be Python 2.7 and 3.x compatible class RemoteRow(RemoteRowMeta('_RemoteRow', (object,), {})): """ A generic class representing a row of data from the remote King Phisher server. """ __table__ = None __xref_attr__ = None __slots__ = () def __init__(self, rpc, args, *kwargs): if not isinstance(rpc, KingPhisherRPCClient): raise ValueError('rpc is not a KingPhisherRPCClient instance') self.__rpc__ = rpc slots = self.__slots__[1:] values = collections.defaultdict(lambda: UNRESOLVED) if args: values.update(dict(zip(slots, args))) if kwargs: values.update(kwargs) for key in slots: value = values[key] if isinstance(value, bytes): value = value.decode('utf-8') setattr(self, key, value) def __getattr__(self, item): if hasattr(self, item + '_id'): row_id = getattr(self, item + '_id', None) for table, table_cls in database_table_objects.items(): if table_cls.__xref_attr__ == item: return self.__rpc__.remote_table_row(table, row_id) raise AttributeError("object has no attribute '{0}'".format(item)) def _asdict(self): return dict(zip(self.__slots__[1:], (getattr(self, prop) for prop in self.__slots__[1:]))) def commit(self): """Send this object to the server to update the remote instance.""" values = tuple(getattr(self, attr) for attr in self.__slots__[1:]) values = collections.OrderedDict(((k, v) for (k, v) in zip(self.__slots__[1:], values) if v is not UNRESOLVED)) self.__rpc__('db/table/set', self.__table__, self.id, tuple(values.keys()), tuple(values.values())) class AlertSubscription(RemoteRow): __table__ = 'alert_subscriptions' __slots__ = ('id', 'user_id', 'campaign_id', 'expiration') class Campaign(RemoteRow): __table__ = 'campaigns' __xref_attr__ = 'campaign' __slots__ = ('id', 'name', 'description', 'user_id', 'created', 'max_credentials', 'expiration', 'campaign_type_id', 'company_id') class CampaignType(RemoteRow): __table__ = 'campaign_types' __xref_attr__ = 'campaign_type' __slots__ = _tag_mixin_slots class Company(RemoteRow): __table__ = 'companies' __xref_attr__ = 'company' __slots__ = ('id', 'name', 'description', 'industry_id', 'url_main', 'url_email', 'url_remote_access') class CompanyDepartment(RemoteRow): __table__ = 'company_departments' __xref_attr__ = 'company_department' __slots__ = _tag_mixin_slots class Credential(RemoteRow): __table__ = 'credentials' __slots__ = ('id', 'visit_id', 'message_id', 'campaign_id', 'username', 'password', 'submitted') class DeaddropConnection(RemoteRow): __table__ = 'deaddrop_connections' __slots__ = ('id', 'deployment_id', 'campaign_id', 'count', 'ip', 'local_username', 'local_hostname', 'local_ip_addresses', 'first_seen', 'last_seen') class DeaddropDeployment(RemoteRow): __table__ = 'deaddrop_deployments' __xref_attr__ = 'deployment' __slots__ = ('id', 'campaign_id', 'destination') class Industry(RemoteRow): __table__ = 'industries' __xref_attr__ = 'industry' __slots__ = _tag_mixin_slots class LandingPage(RemoteRow): __table__ = 'landing_pages' __slots__ = ('id', 'campaign_id', 'hostname', 'page') class Message(RemoteRow): __table__ = 'messages' __xref_attr__ = 'message' __slots__ = ('id', 'campaign_id', 'target_email', 'first_name', 'last_name', 'opened', 'opener_ip', 'opener_user_agent', 'reported', 'delivery_status', 'delivery_details', 'testing', 'sent', 'trained', 'company_department_id') class User(RemoteRow): __table__ = 'users' __xref_attr__ = 'user' __slots__ = ('id', 'phone_carrier', 'phone_number', 'email_address', 'otp_secret', 'last_login', 'name', 'expiration', 'description') class Visit(RemoteRow): __table__ = 'visits' __xref_attr__ = 'visit' __slots__ = ('id', 'message_id', 'campaign_id', 'first_landing_page_id', 'count', 'ip', 'details', 'first_seen', 'last_seen', 'user_agent') database_table_objects.freeze() def _graphql_file(file_or_path): if isinstance(file_or_path, str): with open(file_or_path, 'r') as file_h: query = file_h.read() else: query = file_or_path.read() return query def _graphql_find_file(query_file): path = find.data_file(os.path.join('queries', query_file)) if path is None: raise errors.KingPhisherResourceError('could not find GraphQL query file: ' + query_file) return _graphql_file(path) class KingPhisherRPCClient(advancedhttpserver.RPCClientCached): """ The main RPC object for communicating with the King Phisher Server over RPC. .. _client-rpc-async-methods: .. versionadded:: 1.14.0 Asynchronous Methods This RPC object provides a few methods for asynchronously making RPC calls to the server. This makes it easier to issue and RPC call and then process the results without having to either wait (and by extension lock the GUI thread) or start and manage a separate thread. These methods use the name ``async_`` prefix and have many of the same arguments. In all cases, the callback parameters on_success* and on_error are called with the signature :samp:`callback((cb_args + ({results},)), cb_kwargs)` where ``results`` is either the return value of the RPC method in the case of on_success* or the exception instance in the case of on_error. The when_idle parameter can be used to specify that the callbacks must be executed within the main GUI thread and can thus access GObjects such as widgets. """ def __init__(self, args, kwargs): self.logger = logging.getLogger('KingPhisher.Client.RPC') super(KingPhisherRPCClient, self).__init__(args, *kwargs) self.set_serializer('binary/message-pack') self._async_queue = queue.Queue() self._async_thread = utilities.Thread(target=self._async_thread_routine, name='RPCAsyncWorker') self._async_thread.start() def __repr__(self): return "<{0} '{1}@{2}:{3}{4}'>".format(self.__class__.__name__, self.username, self.host, self.port, self.uri_base) def _async_thread_routine(self): logger = logging.getLogger('KingPhisher.Client.RPC.Async') logger.debug('the async RPC worker has started') while True: work_item = self._async_queue.get() if work_item is None: self._async_queue.task_done() break args = work_item.args or () kwargs = work_item.kwargs or {} callback_args = work_item.callback_args or () callback_kwargs = work_item.callback_kwargs or {} try: results = work_item.method(args, *kwargs) except Exception as error: logger.error("async rpc method: {} encountered an error".format(work_item.method.__name__), exc_info=True) callback = work_item.callback_on_error callback_args = callback_args + (error,) else: callback = work_item.callback_on_success callback_args = callback_args + (results,) if callback is not None: if work_item.callback_when_idle: gui_utilities.glib_idle_add_once(callback, callback_args, *callback_kwargs) else: try: callback(callback_args, *callback_kwargs) except Exception: logger.error("async rpc callback: {} encountered an error".format(callback.__name__), exc_info=True) self._async_queue.task_done() logger.debug('the async RPC worker is exiting') def async_call(self, method, args=None, kwargs=None, on_success=None, on_error=None, when_idle=False, cb_args=None, cb_kwargs=None): """ Perform an asynchronous RPC call to the server. This will queue a work item for a thread to issue the RPC call and then specifies the behavior for completion. See :ref:`Asynchronous Methods <client-rpc-async-methods>` for more information. .. versionadded:: 1.14.0 :param str method: The RPC method name to call. :param tuple args: The arguments to the RPC method. :param tuple kwargs: The keyword arguments to the RPC method. :param on_success: A callback function to be called after the RPC method returns successfully. :param on_error: A callback function to be called if the RPC method raises an exception. :param when_idle: Whether or not the on_success* and on_error callback functions should be called from the main GUI thread while it is idle. :param cb_args: The arguments to the on_success and on_error callback functions. :param cb_kwargs: The keyword arguments to the on_success and on_error callback functions. """ self._async_queue.put(_WorkItem( callback_on_success=on_success, callback_on_error=on_error, callback_when_idle=when_idle, callback_args=cb_args, callback_kwargs=cb_kwargs, method=self.call, args=(method,) + (args or ()), kwargs=kwargs )) def async_graphql(self, query, query_vars=None, on_success=None, on_error=None, when_idle=False, cb_args=None, cb_kwargs=None): """ Perform an asynchronous RPC GraphQL query to the server. This will queue a work item for a thread to issue the RPC call and then specifies the behavior for completion. See :ref:`Asynchronous Methods <client-rpc-async-methods>` for more information. .. versionadded:: 1.14.0 :param str query: The GraphQL query string to execute asynchronously. :param dict query_vars: Any variable definitions required by the GraphQL query. :param on_success: A callback function to be called after the RPC method returns successfully. :param on_error: A callback function to be called if the RPC method raises an exception. :param when_idle: Whether or not the on_success and on_error callback functions should be called from the main GUI thread while it is idle. :param cb_args: The arguments to the on_success and on_error callback functions. :param cb_kwargs: The keyword arguments to the on_success and on_error callback functions. """ self._async_queue.put(_WorkItem( callback_on_success=on_success, callback_on_error=on_error, callback_when_idle=when_idle, callback_args=cb_args, callback_kwargs=cb_kwargs, method=self.graphql, args=(query,), kwargs={'query_vars': query_vars} )) def async_graphql_file(self, file_or_path, args, kwargs): """ Perform an asynchronous RPC GraphQL query from a file on the server. This will queue a work item for a thread to issue the RPC call and then specifies the behavior for completion. See :ref:`Asynchronous Methods <client-rpc-async-methods>` for more information. .. versionadded:: 1.14.0 :param file_or_path: The file object or path to the file from which to read. """ query = _graphql_file(file_or_path) return self.async_graphql(query, args, *kwargs) def graphql(self, query, query_vars=None): """ Execute a GraphQL query on the server and return the results. This will raise :py:exc:`~king_phisher.errors.KingPhisherGraphQLQueryError` if the query fails. :param str query: The GraphQL query string to execute. :param query_vars: Any variable definitions required by the GraphQL query. :return: The query results. :rtype: dict """ response = self.call('graphql', query, query_vars=query_vars) if response['errors']: raise errors.KingPhisherGraphQLQueryError( 'the query failed', errors=response['errors'], query=query, query_vars=query_vars ) return response['data'] def graphql_file(self, file_or_path, query_vars=None): """ This method wraps :py:meth:`~.graphql` to provide a convenient way to execute GraphQL queries from files. :param file_or_path: The file object or path to the file from which to read. :param query_vars: The variables for query. :return: The query results. :rtype: dict """ query = _graphql_file(file_or_path) return self.graphql(query, query_vars=query_vars) def graphql_find_file(self, query_file, query_vars): """ This method is similar to :py:meth:`~.graphql_file`. The first argument (query_file) is the name of a query file that will be located using :py:func:`find.data_file`. Additional keyword arguments are passed as the variables to the query. :param str query_file: The name of the query file to locate. :param query_vars: These keyword arguments are passed as the variables to the query. :return: The query results. :rtype: dict """ query = _graphql_find_file(query_file) return self.graphql(query, query_vars=query_vars) def reconnect(self): """Reconnect to the remote server.""" self.lock.acquire() if self.use_ssl: if (sys.version_info[0] == 2 and sys.version_info >= (2, 7, 9)) or sys.version_info >= (3, 4, 3): context = ssl.create_default_context() context.check_hostname = False context.verify_mode = ssl.CERT_NONE self.client = advancedhttpserver.http.client.HTTPSConnection(self.host, self.port, context=context) else: self.client = advancedhttpserver.http.client.HTTPSConnection(self.host, self.port) else: self.client = advancedhttpserver.http.client.HTTPConnection(self.host, self.port) self.lock.release() def remote_row_resolve(self, row): """ Take a :py:class:`~.RemoteRow` instance and load all fields which are :py:data:`~.UNRESOLVED`. If all fields are present, no modifications are made. :param row: The row who's data is to be resolved. :rtype: :py:class:`~.RemoteRow` :return: The row with all of it's fields fully resolved. :rtype: :py:class:`~.RemoteRow` """ utilities.assert_arg_type(row, RemoteRow) slots = getattr(row, '__slots__')[1:] if not any(prop for prop in slots if getattr(row, prop) is UNRESOLVED): return row for key, value in self.call('db/table/get', getattr(row, '__table__'), row.id).items(): setattr(row, key, value) return row def remote_table(self, table, query_filter=None): """ Iterate over a remote database table hosted on the server. Rows are yielded as named tuples whose fields are the columns of the specified table. :param str table: The table name to retrieve. :return: A generator which yields rows of named tuples. :rtype: tuple """ page = 0 results = self.call('db/table/view', table, page, query_filter=query_filter) if results is None: return results_length = len(results['rows']) row_cls = database_table_objects[table] while results: for row in results['rows']: row = dict(zip(results['columns'], row)) yield row_cls(self, row) page += 1 if 'page_size' in results and 'total_rows' in results: if results['page_size'] page >= results['total_rows']: break if len(results['rows']) < results_length: break results = self.call('db/table/view', table, page, query_filter=query_filter) def remote_table_row(self, table, row_id, cache=False, refresh=False): """ Get a row from the specified table by it's id, optionally caching it. :param str table: The table in which the row exists. :param row_id: The value of the row's id column. :param bool cache: Whether to use the cache for this row. :param bool refresh: If cache is True, get the current row value and store it. :return: The remote row as a named tuple of the specified table. :rtype: tuple """ if cache and refresh: row = self.cache_call_refresh('db/table/get', table, row_id) elif cache and not refresh: row = self.cache_call('db/table/get', table, row_id) else: row = self.call('db/table/get', table, row_id) if row is None: return None row_cls = database_table_objects[table] return row_cls(self, *row) def remote_table_row_set(self, table, row_id, attributes): keys, values = zip(attributes.items()) return self.call('db/table/set', table, row_id, keys, values) def geoip_lookup(self, ip): """ Look up the geographic location information for the specified IP address in the server's geoip database. :param ip: The IP address to lookup. :type ip: :py:class:`ipaddress.IPv4Address`, str :return: The geographic location information for the specified IP address. :rtype: :py:class:`~king_phisher.geoip.GeoLocation` """ result = self.cache_call('geoip/lookup', str(ip)) if result: result = geoip.GeoLocation(ip, result=result) return result def geoip_lookup_multi(self, ips): """ Look up the geographic location information for the specified IP addresses in the server's geoip database. Because results are cached for optimal performance, IP addresses to be queried should be grouped and sorted in a way that is unlikely to change, i.e. by a timestamp. :param ips: The IP addresses to lookup. :type ips: list, set, tuple :return: The geographic location information for the specified IP address. :rtype: dict """ ips = [str(ip) for ip in ips] results = self.cache_call('geoip/lookup/multi', ips) for ip, data in results.items(): results[ip] = geoip.GeoLocation(ip, result=data) return results def get_tag_model(self, tag_table, model=None): """ Load tag information from a remote table into a :py:class:`Gtk.ListStore` instance. Tables compatible with the tag interface must have id, name and description fields. If no model is provided a new one will be created, else the current model will be cleared. :param str tag_table: The name of the table to load tag information from. :param model: The model to place the information into. :type model: :py:class:`Gtk.ListStore` :return: The model with the loaded data from the server. :rtype: :py:class:`Gtk.ListStore` """ if tag_table not in _tag_tables: raise ValueError('tag_table is not a valid tag interface exposing table') tag_table = smoke_zephyr.utilities.parse_case_snake_to_camel(tag_table, upper_first=False) if model is None: model = Gtk.ListStore(str, str, str) # sort by the name column, ascending model.set_sort_column_id(1, Gtk.SortType.ASCENDING) else: model.clear() graphql_query = 'query getTags { db { ' + tag_table + ' { edges { node { id name description } } } } }' tags = self.graphql(graphql_query)['db'][tag_table]['edges'] for tag in tags: tag = tag['node'] model.append((tag['id'], tag['name'], tag['description'])) return model def login(self, username, password, otp=None): """ Authenticate to the remote server. This is required before calling RPC methods which require an authenticated session. :param str username: The username to authenticate with. :param str password: The password to authenticate with. :param str otp: An optional one time password as a 6 digit string to provide if the account requires it. :return: The login result and an accompanying reason. :rtype: tuple """ login_result, login_reason, login_session = self.call('login', username, password, otp) if login_result: if self.headers is None: self.headers = {} self.headers['X-RPC-Auth'] = login_session return login_result, login_reason def ping(self): """ Call the ping RPC method on the remote server to ensure that it is responsive. On success this method will always return True, otherwise an exception will be thrown. :return: True :rtype: bool """ return self.call('ping') def shutdown(self): self._async_queue.put(None) self._async_queue.join() self._async_thread.join() def _magic_graphql(rpc, mode, line): if mode == 'file': line = os.path.expandvars(line) line = os.path.expanduser(line) if not os.access(line, os.R_OK): print('GraphQL Exception: invalid query file') return with open(line, 'r') as file_h: query = file_h.read() elif mode == 'query': query = line else: raise RuntimeError('unsupported magic mode: ' + mode) try: result = rpc.graphql(query) except errors.KingPhisherGraphQLQueryError as error: print('GraphQL Exception: ' + error.message) for message in error.errors: print(message.rstrip()) return return result def vte_child_routine(config): """ This is the method which is executed within the child process spawned by VTE. It expects additional values to be set in the config object so it can initialize a new :py:class:`.KingPhisherRPCClient` instance. It will then drop into an interpreter where the user may directly interact with the rpc object. :param str config: A JSON encoded client configuration. """ config = serializers.JSON.loads(config) try: import readline import rlcompleter # pylint: disable=unused-variable except ImportError: has_readline = False else: has_readline = True try: import IPython.terminal.embed except ImportError: has_ipython = False else: has_ipython = True for plugins_directory in ('rpc_plugins', 'rpc-plugins'): plugins_directory = find.data_directory(plugins_directory) if not plugins_directory: continue sys.path.append(plugins_directory) headers = config['rpc_data'].pop('headers') rpc = KingPhisherRPCClient(**config['rpc_data']) if rpc.headers is None: rpc.headers = {} for name, value in headers.items(): rpc.headers[str(name)] = str(value) user_data_path = config['user_data_path'] sys.path.append(config['user_library_path']) print("Python {0} on {1}".format(sys.version, sys.platform)) # pylint: disable=superfluous-parens print("Campaign Name: '{0}' ID: {1}".format(config['campaign_name'], config['campaign_id'])) # pylint: disable=superfluous-parens print('The \'rpc\' object holds the connected KingPhisherRPCClient instance') console_vars = { 'CAMPAIGN_NAME': config['campaign_name'], 'CAMPAIGN_ID': config['campaign_id'], 'os': os, 'rpc': rpc, 'sys': sys } if has_ipython: console = IPython.terminal.embed.InteractiveShellEmbed(ipython_dir=os.path.join(user_data_path, 'ipython')) console.register_magic_function(functools.partial(_magic_graphql, rpc, 'query'), 'line', 'graphql') console.register_magic_function(functools.partial(_magic_graphql, rpc, 'file'), 'line', 'graphql_file') console.mainloop(console_vars) else: if has_readline: readline.parse_and_bind('tab: complete') console = code.InteractiveConsole(console_vars) for var in tuple(console_vars.keys()): console.push("__builtins__['{0}'] = {0}".format(var)) console.interact('') return	securestate/king-phisher	king_phisher/client/client_rpc.py	Python	bsd-3-clause	24,921	[ "VisIt" ]	41742e828a64655a879610b5d744472cd750075df2b071d30fb2da4808fb5189
# electronics.py --- # # Filename: electronics.py # Description: # Author: Subhasis Ray # Maintainer: Dilawar Singh import numpy as np import moose class ClampCircuit(object): """Container for a Voltage-Clamp/Current clamp circuit.""" defaults = { 'level1': 25.0, 'width1': 50.0, 'delay1': 2.0, 'delay2': 1e6, 'trigMode': 0, 'delay3': 1e9 } def __init__(self, path, squid): self.path = path moose.Neutral(path) self.pulsegen = moose.PulseGen(path+"/pulse") # holding voltage/current generator self.pulsegen.count = 2 self.pulsegen.firstLevel = 25.0 self.pulsegen.firstWidth = 50.0 self.pulsegen.firstDelay = 2.0 self.pulsegen.secondDelay = 0.0 self.pulsegen.trigMode = 2 self.gate = moose.PulseGen(path + "/gate") # holding voltage/current generator self.gate.level[0] = 1.0 self.gate.delay[0] = 0.0 self.gate.width[0] = 1e9 moose.connect(self.gate, "output", self.pulsegen, "input") self.lowpass = moose.RC(path + "/lowpass") # lowpass filter self.lowpass.R = 1.0 self.lowpass.C = 0.03 self.vclamp = moose.DiffAmp(path + "/vclamp") self.vclamp.gain = 0.0 self.vclamp.saturation = 1e10 self.iclamp = moose.DiffAmp(path + "/iclamp") self.iclamp.gain = 0.0 self.iclamp.saturation = 1e10 self.pid = moose.PIDController(path + "/pid") self.pid.gain = 0.5 self.pid.tauI = 0.02 self.pid.tauD = 0.005 self.pid.saturation = 1e10 # Connect current clamp circuitry moose.connect(self.pulsegen, "output", self.iclamp, "plusIn") moose.connect(self.iclamp, "output", squid.C, "injectMsg") # Connect voltage clamp circuitry moose.connect(self.pulsegen, "output", self.lowpass, "injectIn") moose.connect(self.lowpass, "output", self.vclamp, "plusIn") moose.connect(self.vclamp, "output", self.pid, "commandIn") moose.connect(squid.C, "VmOut", self.pid, "sensedIn") moose.connect(self.pid, "output", squid.C, "injectMsg") current_table = moose.Table("/data/Im") moose.connect(current_table, "requestOut", squid.C, "getIm") def configure_pulses( self, baseLevel=0.0, firstLevel=0.1, firstDelay=5.0, firstWidth=40.0, secondLevel=0.0, secondDelay=1e6, secondWidth=0.0, singlePulse=True, ): """Set up the pulse generator.""" self.pulsegen.baseLevel = baseLevel self.pulsegen.firstLevel = firstLevel self.pulsegen.firstWidth = firstWidth self.pulsegen.firstDelay = firstDelay self.pulsegen.secondLevel = secondLevel self.pulsegen.secondDelay = secondDelay self.pulsegen.secondWidth = secondWidth if singlePulse: self.pulsegen.trigMode = 1 else: self.pulsegen.trigMode = 0 def do_voltage_clamp(self): """Switch to voltage clamp circuitry. After this the simdt may need to be changed for correct performance.""" self.vclamp.gain = 1.0 self.iclamp.gain = 0.0 self.pid.gain = 0.5 self.pid.tauD = 0.005 self.pid.tauI = 0.02 def do_current_clamp(self): """Switch to current clamp circuitry. After this the simdt may need to be changed for correct performance.""" self.iclamp.gain = 1.0 self.vclamp.gain = 0.0 self.pid.gain = 0.0	BhallaLab/moose-examples	squid/electronics.py	Python	gpl-2.0	3,586	[ "MOOSE" ]	585d9b83d5a7faee10ee1619bfc57d541d6baf9a6de101d11ce80c459a8c7858
'''------------------------------------------------------------------------------- Tool Name: CreateInflowFileFromECMWFRunoff Source Name: CreateInflowFileFromECMWFRunoff.py Version: ArcGIS 10.3 Author: Environmental Systems Research Institute Inc. Updated by: Environmental Systems Research Institute Inc. Description: Creates RAPID inflow file based on the WRF_Hydro land model output and the weight table previously created. History: Initial coding - 10/21/2014, version 1.0 Updated: Version 1.0, 10/23/2014, modified names of tool and parameters Version 1.0, 10/28/2014, added data validation Version 1.0, 10/30/2014, initial version completed Version 1.1, 11/05/2014, modified the algorithm for extracting runoff variable from the netcdf dataset to improve computation efficiency Version 1.2, 02/03/2015, bug fixing - output netcdf3-classic instead of netcdf4 as the format of RAPID inflow file Version 1.2, 02/03/2015, bug fixing - calculate inflow assuming that ECMWF runoff data is cumulative instead of incremental through time -------------------------------------------------------------------------------''' import os import netCDF4 as NET import numpy as NUM import csv class CreateInflowFileFromECMWFRunoff(object): def __init__(self): """Define the tool (tool name is the name of the class).""" self.label = "Create Inflow File From ECMWF Runoff" self.description = ("Creates RAPID NetCDF input of water inflow " + "based on ECMWF runoff results and previously created weight table.") self.canRunInBackground = False self.header_wt = ['StreamID', 'area_sqm', 'lon_index', 'lat_index', 'npoints', 'weight', 'Lon', 'Lat'] self.dims_oi = ['lon', 'lat', 'time'] self.vars_oi = ["lon", "lat", "time", "RO"] self.length_time = {"LowRes": 61, "HighRes": 125} self.length_time_opt = {"LowRes": 61, "HighRes-1hr": 91, "HighRes-3hr": 49, "HighRes-6hr": 41} self.errorMessages = ["Missing Variable 'time'", "Incorrect dimensions in the input ECMWF runoff file.", "Incorrect variables in the input ECMWF runoff file.", "Incorrect time variable in the input ECMWF runoff file", "Incorrect number of columns in the weight table", "No or incorrect header in the weight table", "Incorrect sequence of rows in the weight table"] def dataValidation(self, in_nc): """Check the necessary dimensions and variables in the input netcdf data""" data_nc = NET.Dataset(in_nc) dims = data_nc.dimensions.keys() if dims != self.dims_oi: raise Exception(self.errorMessages[1]) vars = data_nc.variables.keys() if vars != self.vars_oi: raise Exception(self.errorMessages[2]) return def dataIdentify(self, in_nc): """Check if the data is Ensemble 1-51 (low resolution) or 52 (high resolution)""" data_nc = NET.Dataset(in_nc) name_time = self.vars_oi[2] time = data_nc.variables[name_time][:] diff = NUM.unique(NUM.diff(time)) data_nc.close() time_interval_highres = NUM.array([1.0,3.0,6.0],dtype=float) time_interval_lowres = NUM.array([6.0],dtype=float) if (diff == time_interval_highres).all(): return "HighRes" elif (diff == time_interval_lowres).all(): return "LowRes" else: return None def execute(self, in_nc, in_weight_table, out_nc, in_time_interval="6hr"): """The source code of the tool.""" # Validate the netcdf dataset self.dataValidation(in_nc) # identify if the input netcdf data is the High Resolution data with three different time intervals id_data = self.dataIdentify(in_nc) if id_data is None: raise Exception(self.errorMessages[3]) ''' Read the netcdf dataset''' data_in_nc = NET.Dataset(in_nc) time = data_in_nc.variables[self.vars_oi[2]][:] # Check the size of time variable in the netcdf data if len(time) != self.length_time[id_data]: raise Exception(self.errorMessages[3]) ''' Read the weight table ''' print "Reading the weight table..." dict_list = {self.header_wt[0]:[], self.header_wt[1]:[], self.header_wt[2]:[], self.header_wt[3]:[], self.header_wt[4]:[], self.header_wt[5]:[], self.header_wt[6]:[], self.header_wt[7]:[]} streamID = "" with open(in_weight_table, "rb") as csvfile: reader = csv.reader(csvfile) count = 0 for row in reader: if count == 0: #check number of columns in the weight table if len(row) != len(self.header_wt): raise Exception(self.errorMessages[4]) #check header if row[1:len(self.header_wt)] != self.header_wt[1:len(self.header_wt)]: raise Exception(self.errorMessages[5]) streamID = row[0] count += 1 else: for i in range(0,8): dict_list[self.header_wt[i]].append(row[i]) count += 1 '''Calculate water inflows''' print "Calculating water inflows..." # Obtain size information if id_data == "LowRes": size_time = self.length_time_opt["LowRes"] else: if in_time_interval == "1hr": size_time = self.length_time_opt["HighRes-1hr"] elif in_time_interval == "3hr": size_time = self.length_time_opt["HighRes-3hr"] else: size_time = self.length_time_opt["HighRes-6hr"] size_streamID = len(set(dict_list[self.header_wt[0]])) # Create output inflow netcdf data # data_out_nc = NET.Dataset(out_nc, "w") # by default format = "NETCDF4" data_out_nc = NET.Dataset(out_nc, "w", format = "NETCDF3_CLASSIC") dim_Time = data_out_nc.createDimension('Time', size_time) dim_RiverID = data_out_nc.createDimension(streamID, size_streamID) var_m3_riv = data_out_nc.createVariable('m3_riv', 'f4', ('Time', streamID)) data_temp = NUM.empty(shape = [size_time, size_streamID]) lon_ind_all = [long(i) for i in dict_list[self.header_wt[2]]] lat_ind_all = [long(j) for j in dict_list[self.header_wt[3]]] # Obtain a subset of runoff data based on the indices in the weight table min_lon_ind_all = min(lon_ind_all) max_lon_ind_all = max(lon_ind_all) min_lat_ind_all = min(lat_ind_all) max_lat_ind_all = max(lat_ind_all) data_subset_all = data_in_nc.variables[self.vars_oi[3]][:, min_lat_ind_all:max_lat_ind_all+1, min_lon_ind_all:max_lon_ind_all+1] len_time_subset_all = data_subset_all.shape[0] len_lat_subset_all = data_subset_all.shape[1] len_lon_subset_all = data_subset_all.shape[2] data_subset_all = data_subset_all.reshape(len_time_subset_all, (len_lat_subset_all * len_lon_subset_all)) # compute new indices based on the data_subset_all index_new = [] for r in range(0,count-1): ind_lat_orig = lat_ind_all[r] ind_lon_orig = lon_ind_all[r] index_new.append((ind_lat_orig - min_lat_ind_all)len_lon_subset_all + (ind_lon_orig - min_lon_ind_all)) # obtain a new subset of data data_subset_new = data_subset_all[:,index_new] # start compute inflow pointer = 0 for s in range(0, size_streamID): npoints = int(dict_list[self.header_wt[4]][pointer]) # Check if all npoints points correspond to the same streamID if len(set(dict_list[self.header_wt[0]][pointer : (pointer + npoints)])) != 1: print "ROW INDEX", pointer print "COMID", dict_list[self.header_wt[0]][pointer] raise Exception(self.errorMessages[2]) area_sqm_npoints = [float(k) for k in dict_list[self.header_wt[1]][pointer : (pointer + npoints)]] area_sqm_npoints = NUM.array(area_sqm_npoints) area_sqm_npoints = area_sqm_npoints.reshape(1, npoints) data_goal = data_subset_new[:, pointer:(pointer + npoints)] ''''IMPORTANT NOTE: runoff variable in ECMWF dataset is cumulative instead of incremental through time''' # For data with Low Resolution, there's only one time interval 6 hrs if id_data == "LowRes": #ro_stream = data_goal area_sqm_npoints ro_stream = NUM.concatenate([data_goal[0:1,], NUM.subtract(data_goal[1:,],data_goal[:-1,])]) * area_sqm_npoints #For data with High Resolution, from Hour 0 to 90 (the first 91 time points) are of 1 hr time interval, # then from Hour 90 to 144 (19 time points) are of 3 hour time interval, and from Hour 144 to 240 (15 time points) # are of 6 hour time interval else: if in_time_interval == "1hr": ro_stream = NUM.concatenate([data_goal[0:1,], NUM.subtract(data_goal[1:91,],data_goal[:90,])]) * area_sqm_npoints elif in_time_interval == "3hr": # Hour = 0 is a single data point ro_3hr_a = data_goal[0:1,] # calculate time series of 3 hr data from 1 hr data ro_3hr_b = NUM.subtract(data_goal[3:91:3,],data_goal[:88:3,]) # get the time series of 3 hr data ro_3hr_c = NUM.subtract(data_goal[91:109,], data_goal[90:108,]) # concatenate all time series ro_stream = NUM.concatenate([ro_3hr_a, ro_3hr_b, ro_3hr_c]) * area_sqm_npoints else: # in_time_interval == "6hr" #arcpy.AddMessage("6hr") # Hour = 0 is a single data point ro_6hr_a = data_goal[0:1,] # calculate time series of 6 hr data from 1 hr data ro_6hr_b = NUM.subtract(data_goal[6:91:6,], data_goal[:85:6,]) # calculate time series of 6 hr data from 3 hr data ro_6hr_c = NUM.subtract(data_goal[92:109:2,], data_goal[90:107:2,]) # get the time series of 6 hr data ro_6hr_d = NUM.subtract(data_goal[109:,], data_goal[108:124,]) # concatenate all time series ro_stream = NUM.concatenate([ro_6hr_a, ro_6hr_b, ro_6hr_c, ro_6hr_d]) * area_sqm_npoints data_temp[:,s] = ro_stream.sum(axis = 1) pointer += npoints '''Write inflow data''' print "Writing inflow data..." var_m3_riv[:] = data_temp # close the input and output netcdf datasets data_in_nc.close() data_out_nc.close() return	CI-WATER/erfp_data_process_ubuntu_aws	CreateInflowFileFromECMWFRunoff.py	Python	mit	11,619	[ "NetCDF" ]	88fe13085be57276bc40cd97349ed41642501b727e3eccb1cc1106d818ae8130
# DEPTH-FIRST-SEARCH # A graph is searched depth first by visiting an initial # vertex and then visiting one of its neighbours. After # visiting this neighbour you visit one of its neighbours # and so on. If you come to a vertex with no neighbors you # backtrack one stage and visit another neighbour of the # previous vertex. # The algorithm # ------------------------------------------------------ # set the colour of v to black # ITERATE over all w that are neighbours of v # IF the colour of w is white # depth first search of G from w # ------------------------------------------------------ def dfs(v, g): g[v]['colour'] = 'black' for w in g[v]['neighbours']: if g[w]['colour'] is 'white': dfs(w, g) # An algorithm traversing the vertices of a graph needs # some way in which to detect when a vertex has already # been visited, or it might continue endlessly revisiting # vertices and never terminate. The traditional way to # record when a vertex has been visited is to give each # vertex a colour, white or black. Unvisited vertices are # coloured white. When a vertex is visited, its colour is # changed to black and black vertices are not revisited. def chatty_dfs(vertex, graph): v = vertex g = graph print( "Visited: ", v) g[v]['colour'] = 'black' for w in g[v]['neighbours']: if g[w]['colour'] is 'white': g = chatty_dfs(w, g) return g graph1 = { 1 : { 'colour' : 'white', 'neighbours' : [2, 3, 4] }, 2 : { 'colour' : 'white', 'neighbours' : [1, 4, 5] }, 3 : { 'colour' : 'white', 'neighbours' : [1, 4] }, 4 : { 'colour' : 'white', 'neighbours' : [1, 2, 3] }, 5 : { 'colour' : 'white', 'neighbours' : [2]} } print( graph1 ) print( chatty_dfs(3, graph1) )	melayev/algods	dfs.py	Python	mit	1,714	[ "VisIt" ]	c482ea83aa7c25cf86e5f87a0b563f2d08bc0814c00a9376a91478c27b33743f
"""Module for reading, writing, compressing and converting files. Please note, some of the functions in this module were created and tested using VTK 5. VTK 6 introduced a number of backwards-incompatible changes, including replacing 'SetInput()' with 'SetInputData()' and 'SetInputConnection'. """ import glob import os import csv import vtk import gzip import StringIO def compress(path='test.vtp'): """Compress file with gzip.""" with open(path, 'rb') as ifile: with gzip.open(path + '.gz', 'wb') as ofile: ofile.writelines(ifile) def decompress(path='test.vtp.gz'): """Decompress file with gzip.""" with gzip.open(path, 'rb') as ifile: with open(path[:-3], 'wb') as ofile: ofile.write(ifile.read()) def csv_to_list(path): """Convert CSV-file to a nested list of strings.""" with open(path, 'rb') as f: reader = csv.reader(f) return list(reader) def csv_to_dict(path): """Create nested dictionary from csv file. Workaround for when pandas is unavailable and you want to select 2D array elements with row and column names rather than integers. * First row is used for column names * First column is used for row names. * Access data from dictionary x using x['rowname']['columnname'] * Extract all row names with x.keys() * Extract all column names with x.values()[0].keys() Note: Expects '\n' as newline character. """ x = {} with open(path, 'rb') as f: header = f.next().strip().split(',')[1:] for line in f: row = line.strip().split(',') x[row[0]] = dict( (header[i], v) for i, v in enumerate(row[1:])) return x def listdir(path, match='', dirname=False, extension=False): """List all files and folders in specified directory. Args: path: Path to directory. match: Specify file name pattern according to rules used by Unix shell. For instance, 'match=.pdf' gives you a list of names of all the pdf-files in 'path'. dirname (bool): Include whole path name. extension (bool): Include file extension. """ items = glob.glob(os.path.join(path, match)) if not dirname: items = [os.path.basename(item) for item in items] if not extension: items = [os.path.splitext(item)[0] for item in items] return items def readvti(path): """Read VTI-file, i.e. image in VTK XML format.""" reader = vtk.vtkXMLImageDataReader() reader.SetFileName(path) reader.Update() return reader.GetOutput() def readvtk(path, datatype='polydata'): """Read VTK-file. Args: path: Path to file. type: 'imagedata', 'polydata', 'unstructeredgrid' """ if datatype=='imagedata': reader = vtk.vtkStructuredPointsReader() elif datatype=='polydata': reader = vtk.vtkPolyDataReader() elif datatype=='unstructeredgrid': reader = vtk.vtkUnstructuredGridReader() else: print 'Invalid datatype' reader.SetFileName(path) reader.Update() return reader.GetOutput() def readvtp(path, dataarrays=True): """Read VTP-file, i.e. polydata in VTK XML format. Args: dataarrays (bool): Include point and cell data. """ reader = vtk.vtkXMLPolyDataReader() reader.SetFileName(path) reader.Update() if dataarrays == False: for i in range(reader.GetNumberOfPointArrays()): arrayname = reader.GetPointArrayName(i) reader.SetPointArrayStatus(arrayname, 0) for i in range(reader.GetNumberOfCellArrays()): arrayname = reader.GetCellArrayName(i) reader.SetPointArrayStatus(arrayname, 0) reader.Update() return reader.GetOutput() def readvtu(path): """Read VTU-file, i.e. unstructured grid in VTK XML format.""" reader = vtk.vtkXMLUnstructuredGridReader() reader.SetFileName(path) reader.Update() return reader.GetOutput() def replacestring(lines, tag, value): """Replace string in list of strings. Args: lines: List of strings. tag: String to replace. value: String with which to replace 'tag'. """ output = [] for line in lines: line = line.replace(tag, value) output.append(line) return output def writepoints(points, filename): """Write points as VTP-file.""" polydata = vtk.vtkPolyData() cellarray = vtk.vtkCellArray() for i in range(points.GetNumberOfPoints()): cellarray.InsertNextCell(1) cellarray.InsertCellPoint(i) polydata.SetPoints(points) polydata.SetVerts(cellarray) writer = vtk.vtkXMLPolyDataWriter() writer.SetFileName(filename) writer.SetInput(polydata) writer.Write() def writevti(image, path): """Write VTI-files, i.e. images in VTK XML format.""" writer = vtk.vtkXMLImageDataWriter() writer.SetInput(image) writer.SetFileName(path) writer.Write() def writevtp(polydata, path): """Write VTP-files, i.e. polydata in VTK XML format.""" writer = vtk.vtkXMLPolyDataWriter() writer.SetInput(polydata) writer.SetFileName(path) writer.Write() def writevtu(grid, path): """Write VTU-files, i.e. unstructured grids in VTK XML format.""" writer = vtk.vtkXMLUnstructuredGridWriter() writer.SetInput(grid) writer.SetFileName(path) writer.Write() #------------------------------------------------------------------------------- # CFX #------------------------------------------------------------------------------- def cfx2vtp(inputfile, outputfile, surface=True, ascii=False): """Convert polydata exported from CFX-Post to VTP. Args: surface (bool): Convert surface or line polydata. ascii (bool): Return VTP file in ASCII format. Export surface in CFX-Post with following options: * file extension: csv * export geometry information: line and face connectivity * (optional) select variable(s) * vector display: scalar * separator: comma space * include header """ f = open(inputfile, 'rb') # derive data size from csv file if surface: for i, line in enumerate(f): if line.strip() == '[Data]': datalinenumber = i if line.strip() == '[Faces]': faceslinenumber = i lastlinenumber = i numberofnodes = faceslinenumber - datalinenumber - 3 numberofelements = lastlinenumber - faceslinenumber - 1 else: for i, line in enumerate(f): if line.strip() == '[Data]': datalinenumber = i if line.strip() == '[Lines]': lineslinenumber = i numberofnodes = lineslinenumber - datalinenumber - 3 # obtain list of variables names f.seek(0) for i in range(datalinenumber + 2): arrayline = f.readline() arraynames = arrayline.strip().split(', ') arraynames[0:3] = [] # define polydata points = vtk.vtkPoints() cells = vtk.vtkCellArray() points.SetNumberOfPoints(numberofnodes) polydata = vtk.vtkPolyData() polydata.SetPoints(points) polydata.SetPolys(cells) if surface else polydata.SetLines(cells) for arrayname in arraynames: array = vtk.vtkDoubleArray() array.SetName(arrayname) array.SetNumberOfTuples(numberofnodes) polydata.GetPointData().AddArray(array) # parse through the rest of the file using the csv module reader = csv.reader(f) # assign x,y,z coordinates and variable values to points for i in range(numberofnodes): dataline = reader.next() point = [float(dataline[0]), float(dataline[1]), float(dataline[2])] points.SetPoint(i, point) for j in range(len(arraynames)): dataarray = polydata.GetPointData().GetArray(arraynames[j]) dataarray.SetComponent(i, 0, float(dataline[j + 3])) # skip element '[Faces]' (or '[Lines]') in csv-file reader.next() reader.next() if surface: # obtain and set connectivity cellids = vtk.vtkIdList() for i in range(numberofelements): facesline = reader.next() cellids.Initialize() for j in range(len(facesline)): cellids.InsertNextId(int(facesline[j])) cells.InsertNextCell(cellids) else: # obtain connectivity connectivitylist = [] for row in reader: row = [int(item) for item in row] connectivitylist.append(row) connectivitylist = filter(None, connectivitylist) # rearrange connectivity linecounter = 0 for i in range(len(connectivitylist)): if i == 0: connectivity = [connectivitylist[i]] elif connectivitylist[i][0] == connectivitylist[i - 1][1]: connectivity[linecounter].append(connectivitylist[i][1]) else: connectivity.append([]) linecounter += 1 connectivity[linecounter].append(connectivitylist[i][0]) connectivity[linecounter].append(connectivitylist[i][1]) # set connectivity cellids = vtk.vtkIdList() for i in range(len(connectivity)): cellids.Initialize() for j in range(len(connectivity[i])): cellids.InsertNextId(int(connectivity[i][j])) cells.InsertNextCell(cellids) f.close() # write vtk polydata writer = vtk.vtkXMLPolyDataWriter() writer.SetInput(polydata) if ascii: writer.SetDataModeToAscii() writer.SetFileName(outputfile) writer.Write() def vtp2cfx(inputfile, outputfile, surface=True): """Convert VTP polydata to format that can be imported into CFX-Post. Args: surface (bool): Convert surface or line polydata. """ # read vtp file reader = vtk.vtkXMLPolyDataReader() reader.SetFileName(inputfile) reader.Update() polydata = reader.GetOutput() # read names of data arrays arraynames = [] dataarrays = polydata.GetPointData() numberofdataarrays = dataarrays.GetNumberOfArrays() for i in range(numberofdataarrays): array = dataarrays.GetArray(i) arrayname = array.GetName() arraynames.append(arrayname) # append names of data arrays to header and write header f = open(outputfile, 'wb') header = "\n[Name]\nSEGMENT\n\n[Data]\nX [ m ], Y [ m ], Z [ m ]" for i in range(numberofdataarrays): header += ", " + arraynames[i] header += "\n" f.write(header) # write values of x,y,z and data arrays row by row for i in range(polydata.GetNumberOfPoints()): point = polydata.GetPoint(i) line = str(point[0]) + ', ' + str(point[1]) + ', ' + str(point[2]) for arrayname in arraynames: array = dataarrays.GetArray(arrayname) line += ', ' + str(array.GetComponent(i, 0)) line += '\n' f.write(line) # write list of connectivity if surface: line = '\n[Faces]\n' f.write(line) for i in range(polydata.GetNumberOfCells()): cellpointids = polydata.GetCell(i).GetPointIds() line = '' for j in range(cellpointids.GetNumberOfIds()): if (j > 0): line += ', ' line += str(cellpointids.GetId(j)) line += '\n' f.write(line) else: line = '\n[Lines]\n' f.write(line) for i in range(polydata.GetNumberOfCells()): cellpointids = polydata.GetCell(i).GetPointIds() line = '' for j in range(cellpointids.GetNumberOfIds() - 1): line += (str(cellpointids.GetId(j)) + ', ' + str(cellpointids.GetId(j + 1)) + '\n') f.write(line) # add blank line to mimic exact same file structure as CFX-generated # csv-file line = '\n' f.write(line) f.close()	ajgeers/utils	utils/iolib.py	Python	bsd-2-clause	12,457	[ "VTK" ]	f14f80c2c947198e53f32800d8fabbb92bea1cbc0693bc2450c45be41462f8ec
try: import hashlib as md5 except: import md5 from DIRAC import S_OK, S_ERROR, gConfig from DIRAC.ConfigurationSystem.Client.PathFinder import getServiceSection from DIRAC.AccountingSystem.private.Plotters import gPlottersList from DIRAC.AccountingSystem.private.Policies import gPoliciesList class MainReporter: def __init__( self, db, setup ): self._db = db self.setup = setup self.csSection = getServiceSection( "Accounting/ReportGenerator", setup = setup ) def __calculateReportHash( self, reportRequest ): requestToHash = dict( reportRequest ) granularity = gConfig.getValue( "%s/CacheTimeGranularity" % self.csSection, 300 ) for key in ( 'startTime', 'endTime' ): epoch = requestToHash[ key ] requestToHash[ key ] = epoch - epoch % granularity md5Hash = md5.md5() md5Hash.update( repr( requestToHash ) ) md5Hash.update( self.setup ) return md5Hash.hexdigest() def generate( self, reportRequest, credDict ): typeName = reportRequest[ 'typeName' ] plotterClass = gPlottersList.getPlotterClass( typeName ) if not plotterClass: return S_ERROR( "There's no reporter registered for type %s" % typeName ) if typeName in gPoliciesList: retVal = gPoliciesList[ typeName ].checkRequest( reportRequest[ 'reportName' ], credDict, reportRequest[ 'condDict' ], reportRequest[ 'grouping' ] ) if not retVal[ 'OK' ]: return retVal reportRequest[ 'hash' ] = self.__calculateReportHash( reportRequest ) plotter = plotterClass( self._db, self.setup, reportRequest[ 'extraArgs' ] ) return plotter.generate( reportRequest ) def list( self, typeName ): plotterClass = gPlottersList.getPlotterClass( typeName ) if not plotterClass: return S_ERROR( "There's no plotter registered for type %s" % typeName ) plotter = plotterClass( self._db, self.setup ) return S_OK( plotter.plotsList() )	sposs/DIRAC	AccountingSystem/private/MainReporter.py	Python	gpl-3.0	2,070	[ "DIRAC" ]	505b6b1fa46df3aefa8eb7a19d7302124bf6ac32142463fdf5b24dc9f5ff5f19
########################################################################## # # Copyright 2008-2010 VMware, Inc. # All Rights Reserved. # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # ##########################################################################/ """GL tracing generator.""" import re import sys from trace import Tracer from dispatch import function_pointer_type, function_pointer_value import specs.stdapi as stdapi import specs.glapi as glapi import specs.glparams as glparams from specs.glxapi import glxapi class TypeGetter(stdapi.Visitor): '''Determine which glGetv function that matches the specified type.''' def __init__(self, prefix = 'glGet', long_suffix = True, ext_suffix = ''): self.prefix = prefix self.long_suffix = long_suffix self.ext_suffix = ext_suffix def visitConst(self, const): return self.visit(const.type) def visitAlias(self, alias): if alias.expr == 'GLboolean': if self.long_suffix: suffix = 'Booleanv' arg_type = alias.expr else: suffix = 'iv' arg_type = 'GLint' elif alias.expr == 'GLdouble': if self.long_suffix: suffix = 'Doublev' arg_type = alias.expr else: suffix = 'dv' arg_type = alias.expr elif alias.expr == 'GLfloat': if self.long_suffix: suffix = 'Floatv' arg_type = alias.expr else: suffix = 'fv' arg_type = alias.expr elif alias.expr in ('GLint', 'GLuint', 'GLsizei'): if self.long_suffix: suffix = 'Integerv' arg_type = 'GLint' else: suffix = 'iv' arg_type = 'GLint' else: print alias.expr assert False function_name = self.prefix + suffix + self.ext_suffix return function_name, arg_type def visitEnum(self, enum): return self.visit(glapi.GLint) def visitBitmask(self, bitmask): return self.visit(glapi.GLint) def visitOpaque(self, pointer): return self.prefix + 'Pointerv' + self.ext_suffix, 'GLvoid ' class GlTracer(Tracer): arrays = [ ("Vertex", "VERTEX"), ("Normal", "NORMAL"), ("Color", "COLOR"), ("Index", "INDEX"), ("TexCoord", "TEXTURE_COORD"), ("EdgeFlag", "EDGE_FLAG"), ("FogCoord", "FOG_COORD"), ("SecondaryColor", "SECONDARY_COLOR"), ] arrays.reverse() # arrays available in ES1 arrays_es1 = ("Vertex", "Normal", "Color", "TexCoord") def header(self, api): Tracer.header(self, api) print '#include <algorithm>' print print '#include "gltrace.hpp"' print # Which glVertexAttrib* variant to use print 'enum vertex_attrib {' print ' VERTEX_ATTRIB,' print ' VERTEX_ATTRIB_NV,' print '};' print print 'static vertex_attrib _get_vertex_attrib(void) {' print ' gltrace::Context ctx = gltrace::getContext();' print ' if (ctx->user_arrays_nv) {' print ' GLboolean _vertex_program = GL_FALSE;' print ' _glGetBooleanv(GL_VERTEX_PROGRAM_ARB, &_vertex_program);' print ' if (_vertex_program) {' print ' if (ctx->user_arrays_nv) {' print ' GLint _vertex_program_binding_nv = _glGetInteger(GL_VERTEX_PROGRAM_BINDING_NV);' print ' if (_vertex_program_binding_nv) {' print ' return VERTEX_ATTRIB_NV;' print ' }' print ' }' print ' }' print ' }' print ' return VERTEX_ATTRIB;' print '}' print self.defineShadowBufferHelper() # Whether we need user arrays print 'static inline bool _need_user_arrays(void)' print '{' print ' gltrace::Context ctx = gltrace::getContext();' print ' if (!ctx->user_arrays) {' print ' return false;' print ' }' print print ' glprofile::Profile profile = ctx->profile;' print ' bool es1 = profile.es() && profile.major == 1;' print for camelcase_name, uppercase_name in self.arrays: # in which profile is the array available? profile_check = 'profile.desktop()' if camelcase_name in self.arrays_es1: profile_check = '(' + profile_check + ' \|\| es1)'; function_name = 'gl%sPointer' % camelcase_name enable_name = 'GL_%s_ARRAY' % uppercase_name binding_name = 'GL_%s_ARRAY_BUFFER_BINDING' % uppercase_name print ' // %s' % function_name print ' if (%s) {' % profile_check self.array_prolog(api, uppercase_name) print ' if (_glIsEnabled(%s) &&' % enable_name print ' _glGetInteger(%s) == 0) {' % binding_name self.array_cleanup(api, uppercase_name) print ' return true;' print ' }' self.array_epilog(api, uppercase_name) print ' }' print print ' // ES1 does not support generic vertex attributes' print ' if (es1)' print ' return false;' print print ' vertex_attrib _vertex_attrib = _get_vertex_attrib();' print print ' // glVertexAttribPointer' print ' if (_vertex_attrib == VERTEX_ATTRIB) {' print ' GLint _max_vertex_attribs = _glGetInteger(GL_MAX_VERTEX_ATTRIBS);' print ' for (GLint index = 0; index < _max_vertex_attribs; ++index) {' print ' if (_glGetVertexAttribi(index, GL_VERTEX_ATTRIB_ARRAY_ENABLED) &&' print ' _glGetVertexAttribi(index, GL_VERTEX_ATTRIB_ARRAY_BUFFER_BINDING) == 0) {' print ' return true;' print ' }' print ' }' print ' }' print print ' // glVertexAttribPointerNV' print ' if (_vertex_attrib == VERTEX_ATTRIB_NV) {' print ' for (GLint index = 0; index < 16; ++index) {' print ' if (_glIsEnabled(GL_VERTEX_ATTRIB_ARRAY0_NV + index)) {' print ' return true;' print ' }' print ' }' print ' }' print print ' return false;' print '}' print print r'static void _trace_user_arrays(GLuint count);' print print r'static void _fakeStringMarker(GLsizei len, const GLvoid * string);' print print r'static inline void' print r'_fakeStringMarker(const std::string &s) {' print r' _fakeStringMarker(s.length(), s.data());' print r'}' print print '// whether glLockArraysEXT() has ever been called' print 'static bool _checkLockArraysEXT = false;' print # Buffer mappings print '// whether glMapBufferRange(GL_MAP_WRITE_BIT) has ever been called' print 'static bool _checkBufferMapRange = false;' print print '// whether glBufferParameteriAPPLE(GL_BUFFER_FLUSHING_UNMAP_APPLE, GL_FALSE) has ever been called' print 'static bool _checkBufferFlushingUnmapAPPLE = false;' print # Generate a helper function to determine whether a parameter name # refers to a symbolic value or not print 'static bool' print 'is_symbolic_pname(GLenum pname) {' print ' switch (pname) {' for function, type, count, name in glparams.parameters: if type is glapi.GLenum: print ' case %s:' % name print ' return true;' print ' default:' print ' return false;' print ' }' print '}' print # Generate a helper function to determine whether a parameter value is # potentially symbolic or not; i.e., if the value can be represented in # an enum or not print 'template<class T>' print 'static inline bool' print 'is_symbolic_param(T param) {' print ' return static_cast<T>(static_cast<GLenum>(param)) == param;' print '}' print # Generate a helper function to know how many elements a parameter has print 'static size_t' print '_gl_param_size(GLenum pname) {' print ' switch (pname) {' for function, type, count, name in glparams.parameters: if name == 'GL_PROGRAM_BINARY_FORMATS': count = 0 if type is not None: print ' case %s: return %s;' % (name, count) print ' default:' print r' os::log("apitrace: warning: %s: unknown GLenum 0x%04X\n", __FUNCTION__, pname);' print ' return 1;' print ' }' print '}' print # states such as GL_UNPACK_ROW_LENGTH are not available in GLES print 'static inline bool' print 'can_unpack_subimage(void) {' print ' gltrace::Context ctx = gltrace::getContext();' print ' return ctx->profile.desktop();' print '}' print # VMWX_map_buffer_debug print r'extern "C" PUBLIC' print r'void APIENTRY' print r'glNotifyMappedBufferRangeVMWX(const void start, GLsizeiptr length) {' self.emit_memcpy('start', 'length') print r'}' print getProcAddressFunctionNames = [] def traceApi(self, api): if self.getProcAddressFunctionNames: # Generate a function to wrap proc addresses getProcAddressFunction = api.getFunctionByName(self.getProcAddressFunctionNames[0]) argType = getProcAddressFunction.args[0].type retType = getProcAddressFunction.type print 'static %s _wrapProcAddress(%s procName, %s procPtr);' % (retType, argType, retType) print Tracer.traceApi(self, api) print 'static %s _wrapProcAddress(%s procName, %s procPtr) {' % (retType, argType, retType) # Provide fallback functions to missing debug functions print ' if (!procPtr) {' else_ = '' for function_name in self.debug_functions: if self.api.getFunctionByName(function_name): print ' %sif (strcmp("%s", (const char )procName) == 0) {' % (else_, function_name) print ' return (%s)&%s;' % (retType, function_name) print ' }' else_ = 'else ' print ' %s{' % else_ print ' return NULL;' print ' }' print ' }' for function in api.getAllFunctions(): ptype = function_pointer_type(function) pvalue = function_pointer_value(function) print ' if (strcmp("%s", (const char )procName) == 0) {' % function.name print ' assert(procPtr != (%s)&%s);' % (retType, function.name) print ' %s = (%s)procPtr;' % (pvalue, ptype) print ' return (%s)&%s;' % (retType, function.name,) print ' }' print ' os::log("apitrace: warning: unknown function \\"%s\\"\\n", (const char )procName);' print ' return procPtr;' print '}' print else: Tracer.traceApi(self, api) def defineShadowBufferHelper(self): print 'void _shadow_glGetBufferSubData(GLenum target, GLintptr offset,' print ' GLsizeiptr size, GLvoid data)' print '{' print ' gltrace::Context ctx = gltrace::getContext();' print ' if (!ctx->needsShadowBuffers() \|\| target != GL_ELEMENT_ARRAY_BUFFER) {' print ' _glGetBufferSubData(target, offset, size, data);' print ' return;' print ' }' print print ' GLint buffer_binding = _glGetInteger(GL_ELEMENT_ARRAY_BUFFER_BINDING);' print ' if (buffer_binding > 0) {' print ' gltrace::Buffer & buf = ctx->buffers[buffer_binding];' print ' buf.getSubData(offset, size, data);' print ' }' print '}' def shadowBufferMethod(self, method): # Emit code to fetch the shadow buffer, and invoke a method print ' gltrace::Context ctx = gltrace::getContext();' print ' if (ctx->needsShadowBuffers() && target == GL_ELEMENT_ARRAY_BUFFER) {' print ' GLint buffer_binding = _glGetInteger(GL_ELEMENT_ARRAY_BUFFER_BINDING);' print ' if (buffer_binding > 0) {' print ' gltrace::Buffer & buf = ctx->buffers[buffer_binding];' print ' buf.' + method + ';' print ' }' print ' }' print def shadowBufferProlog(self, function): if function.name == 'glBufferData': self.shadowBufferMethod('bufferData(size, data)') if function.name == 'glBufferSubData': self.shadowBufferMethod('bufferSubData(offset, size, data)') if function.name == 'glDeleteBuffers': print ' gltrace::Context ctx = gltrace::getContext();' print ' if (ctx->needsShadowBuffers()) {' print ' for (GLsizei i = 0; i < n; i++) {' print ' ctx->buffers.erase(buffer[i]);' print ' }' print ' }' array_pointer_function_names = set(( "glVertexPointer", "glNormalPointer", "glColorPointer", "glIndexPointer", "glTexCoordPointer", "glEdgeFlagPointer", "glFogCoordPointer", "glSecondaryColorPointer", "glInterleavedArrays", "glVertexPointerEXT", "glNormalPointerEXT", "glColorPointerEXT", "glIndexPointerEXT", "glTexCoordPointerEXT", "glEdgeFlagPointerEXT", "glFogCoordPointerEXT", "glSecondaryColorPointerEXT", "glVertexAttribPointer", "glVertexAttribPointerARB", "glVertexAttribPointerNV", "glVertexAttribIPointer", "glVertexAttribIPointerEXT", "glVertexAttribLPointer", "glVertexAttribLPointerEXT", #"glMatrixIndexPointerARB", )) # XXX: We currently ignore the glDrawElementArray functions draw_function_regex = re.compile(r'^gl([A-Z][a-z]+)Draw(Range)?(Arrays\|Elements)([A-Z][a-zA-Z])?$' ) interleaved_formats = [ 'GL_V2F', 'GL_V3F', 'GL_C4UB_V2F', 'GL_C4UB_V3F', 'GL_C3F_V3F', 'GL_N3F_V3F', 'GL_C4F_N3F_V3F', 'GL_T2F_V3F', 'GL_T4F_V4F', 'GL_T2F_C4UB_V3F', 'GL_T2F_C3F_V3F', 'GL_T2F_N3F_V3F', 'GL_T2F_C4F_N3F_V3F', 'GL_T4F_C4F_N3F_V4F', ] def traceFunctionImplBody(self, function): # Defer tracing of user array pointers... if function.name in self.array_pointer_function_names: print ' GLint _array_buffer = _glGetInteger(GL_ARRAY_BUFFER_BINDING);' print ' if (!_array_buffer) {' print ' static bool warned = false;' print ' if (!warned) {' print ' warned = true;' print ' os::log("apitrace: warning: %s: call will be faked due to pointer to user memory (https://github.com/apitrace/apitrace/blob/master/docs/BUGS.markdown#tracing)\\n", __FUNCTION__);' print ' }' print ' gltrace::Context ctx = gltrace::getContext();' print ' ctx->user_arrays = true;' if function.name == "glVertexAttribPointerNV": print ' ctx->user_arrays_nv = true;' self.invokeFunction(function) # And also break down glInterleavedArrays into the individual calls if function.name == 'glInterleavedArrays': print # Initialize the enable flags for camelcase_name, uppercase_name in self.arrays: flag_name = '_' + uppercase_name.lower() print ' GLboolean %s = GL_FALSE;' % flag_name print # Switch for the interleaved formats print ' switch (format) {' for format in self.interleaved_formats: print ' case %s:' % format for camelcase_name, uppercase_name in self.arrays: flag_name = '_' + uppercase_name.lower() if format.find('_' + uppercase_name[0]) >= 0: print ' %s = GL_TRUE;' % flag_name print ' break;' print ' default:' print ' return;' print ' }' print # Emit fake glEnableClientState/glDisableClientState flags for camelcase_name, uppercase_name in self.arrays: flag_name = '_' + uppercase_name.lower() enable_name = 'GL_%s_ARRAY' % uppercase_name # Emit a fake function print ' {' print ' static const trace::FunctionSig &_sig = %s ? _glEnableClientState_sig : _glDisableClientState_sig;' % flag_name print ' unsigned _call = trace::localWriter.beginEnter(&_sig, true);' print ' trace::localWriter.beginArg(0);' self.serializeValue(glapi.GLenum, enable_name) print ' trace::localWriter.endArg();' print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_call);' print ' trace::localWriter.endLeave();' print ' }' # Warn about buggy glGet(GL_ARRAY_SIZE) not returning GL_BGRA buggyFunctions = { 'glColorPointer': ('glGetIntegerv', '', 'GL_COLOR_ARRAY_SIZE'), 'glSecondaryColorPointer': ('glGetIntegerv', '', 'GL_SECONDARY_COLOR_ARRAY_SIZE'), 'glVertexAttribPointer': ('glGetVertexAttribiv', 'index, ', 'GL_VERTEX_ATTRIB_ARRAY_SIZE'), 'glVertexAttribPointerARB': ('glGetVertexAttribivARB', 'index, ', 'GL_VERTEX_ATTRIB_ARRAY_SIZE_ARB'), } if function.name in buggyFunctions: getter, extraArg, pname = buggyFunctions[function.name] print r' static bool _checked = false;' print r' if (!_checked && size == GL_BGRA) {' print r' GLint _size = 0;' print r' _%s(%s%s, &_size);' % (getter, extraArg, pname) print r' if (_size != GL_BGRA) {' print r' os::log("apitrace: warning: %s(%s) does not return GL_BGRA; trace will be incorrect (https://github.com/apitrace/apitrace/issues/261)\n");' % (getter, pname) print r' }' print r' _checked = true;' print r' }' print ' return;' print ' }' # ... to the draw calls if self.draw_function_regex.match(function.name): print ' if (_need_user_arrays()) {' if 'Indirect' in function.name: print r' os::log("apitrace: warning: %s: indirect user arrays not supported\n");' % (function.name,) else: arg_names = ', '.join([arg.name for arg in function.args[1:]]) print ' GLuint _count = _%s_count(%s);' % (function.name, arg_names) # Some apps, in particular Quake3, can tell the driver to lock more # vertices than those actually required for the draw call. print ' if (_checkLockArraysEXT) {' print ' GLuint _locked_count = _glGetInteger(GL_ARRAY_ELEMENT_LOCK_FIRST_EXT)' print ' + _glGetInteger(GL_ARRAY_ELEMENT_LOCK_COUNT_EXT);' print ' _count = std::max(_count, _locked_count);' print ' }' print ' _trace_user_arrays(_count);' print ' }' if function.name == 'glLockArraysEXT': print ' _checkLockArraysEXT = true;' # Warn if user arrays are used with glBegin/glArrayElement/glEnd. if function.name == 'glBegin': print r' gltrace::Context ctx = gltrace::getContext();' print r' ctx->userArraysOnBegin = _need_user_arrays();' if function.name.startswith('glArrayElement'): print r' gltrace::Context ctx = gltrace::getContext();' print r' if (ctx->userArraysOnBegin) {' print r' os::log("apitrace: warning: user arrays with glArrayElement not supported (https://github.com/apitrace/apitrace/issues/276)\n");' print r' ctx->userArraysOnBegin = false;' print r' }' # Emit a fake memcpy on buffer uploads if function.name == 'glBufferParameteriAPPLE': print ' if (pname == GL_BUFFER_FLUSHING_UNMAP_APPLE && param == GL_FALSE) {' print ' _checkBufferFlushingUnmapAPPLE = true;' print ' }' if function.name in ('glUnmapBuffer', 'glUnmapBufferARB'): if function.name.endswith('ARB'): suffix = 'ARB' else: suffix = '' print ' GLint access_flags = 0;' print ' GLint access = 0;' print ' bool flush;' print ' // GLES3 does not have GL_BUFFER_ACCESS;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_ACCESS_FLAGS, &access_flags);' % suffix print ' flush = (access_flags & GL_MAP_WRITE_BIT) && !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT \| GL_MAP_PERSISTENT_BIT));' print ' } else {' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_ACCESS, &access);' % suffix print ' flush = access != GL_READ_ONLY;' print ' }' print ' if (flush) {' print ' GLvoid map = NULL;' print ' _glGetBufferPointerv%s(target, GL_BUFFER_MAP_POINTER, &map);' % suffix print ' if (map) {' print ' GLint length = -1;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_MAP_LENGTH, &length);' % suffix print ' if (length == -1) {' print ' // Mesa drivers refuse GL_BUFFER_MAP_LENGTH without GL 3.0 up-to' print ' // http://cgit.freedesktop.org/mesa/mesa/commit/?id=ffee498fb848b253a7833373fe5430f8c7ca0c5f' print ' static bool warned = false;' print ' if (!warned) {' print ' os::log("apitrace: warning: glGetBufferParameteriv%s(GL_BUFFER_MAP_LENGTH) failed\\n");' % suffix print ' warned = true;' print ' }' print ' }' print ' } else {' print ' length = 0;' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_SIZE, &length);' % suffix print ' }' print ' if (_checkBufferFlushingUnmapAPPLE) {' print ' GLint flushing_unmap = GL_TRUE;' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_FLUSHING_UNMAP_APPLE, &flushing_unmap);' % suffix print ' flush = flush && flushing_unmap;' print ' }' print ' if (flush && length > 0) {' self.emit_memcpy('map', 'length') print ' }' print ' }' print ' }' if function.name == 'glUnmapBufferOES': print ' GLint access_flags = 0;' print ' GLint access = 0;' print ' bool flush;' print ' // GLES3 does not have GL_BUFFER_ACCESS;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv(target, GL_BUFFER_ACCESS_FLAGS, &access_flags);' print ' flush = (access_flags & GL_MAP_WRITE_BIT) && !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT \| GL_MAP_PERSISTENT_BIT));' print ' } else {' print ' _glGetBufferParameteriv(target, GL_BUFFER_ACCESS, &access);' print ' flush = access != GL_READ_ONLY;' print ' }' print ' if (flush) {' print ' GLvoid map = NULL;' print ' _glGetBufferPointervOES(target, GL_BUFFER_MAP_POINTER, &map);' print ' if (map) {' print ' GLint length = 0;' print ' GLint offset = 0;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv(target, GL_BUFFER_MAP_LENGTH, &length);' print ' _glGetBufferParameteriv(target, GL_BUFFER_MAP_OFFSET, &offset);' print ' } else {' print ' _glGetBufferParameteriv(target, GL_BUFFER_SIZE, &length);' print ' }' print ' if (flush && length > 0) {' self.emit_memcpy('map', 'length') self.shadowBufferMethod('bufferSubData(offset, length, map)') print ' }' print ' }' print ' }' if function.name == 'glUnmapNamedBuffer': print ' GLint access_flags = 0;' print ' _glGetNamedBufferParameteriv(buffer, GL_BUFFER_ACCESS_FLAGS, &access_flags);' print ' if ((access_flags & GL_MAP_WRITE_BIT) &&' print ' !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT \| GL_MAP_PERSISTENT_BIT))) {' print ' GLvoid map = NULL;' print ' _glGetNamedBufferPointerv(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' GLint length = 0;' print ' _glGetNamedBufferParameteriv(buffer, GL_BUFFER_MAP_LENGTH, &length);' print ' if (map && length > 0) {' self.emit_memcpy('map', 'length') print ' }' print ' }' if function.name == 'glUnmapNamedBufferEXT': print ' GLint access_flags = 0;' print ' _glGetNamedBufferParameterivEXT(buffer, GL_BUFFER_ACCESS_FLAGS, &access_flags);' print ' if ((access_flags & GL_MAP_WRITE_BIT) &&' print ' !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT \| GL_MAP_PERSISTENT_BIT))) {' print ' GLvoid map = NULL;' print ' _glGetNamedBufferPointervEXT(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' GLint length = 0;' print ' _glGetNamedBufferParameterivEXT(buffer, GL_BUFFER_MAP_LENGTH, &length);' print ' if (map && length > 0) {' self.emit_memcpy('map', 'length') print ' }' print ' }' if function.name == 'glFlushMappedBufferRange': print ' GLvoid map = NULL;' print ' _glGetBufferPointerv(target, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char )map + offset', 'length') print ' }' if function.name == 'glFlushMappedBufferRangeEXT': print ' GLvoid map = NULL;' print ' _glGetBufferPointervOES(target, GL_BUFFER_MAP_POINTER_OES, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char )map + offset', 'length') print ' }' if function.name == 'glFlushMappedBufferRangeAPPLE': print ' GLvoid map = NULL;' print ' _glGetBufferPointerv(target, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && size > 0) {' self.emit_memcpy('(const char )map + offset', 'size') print ' }' if function.name == 'glFlushMappedNamedBufferRange': print ' GLvoid map = NULL;' print ' _glGetNamedBufferPointerv(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char )map + offset', 'length') print ' }' if function.name == 'glFlushMappedNamedBufferRangeEXT': print ' GLvoid map = NULL;' print ' _glGetNamedBufferPointervEXT(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char )map + offset', 'length') print ' }' # FIXME: We don't support coherent/pinned memory mappings if function.name in ('glBufferStorage', 'glNamedBufferStorage', 'glNamedBufferStorageEXT'): print r' if (!(flags & GL_MAP_PERSISTENT_BIT)) {' print r' os::log("apitrace: warning: %s: MAP_NOTIFY_EXPLICIT_BIT_VMWX set w/o MAP_PERSISTENT_BIT\n", __FUNCTION__);' print r' }' print r' flags &= ~GL_MAP_NOTIFY_EXPLICIT_BIT_VMWX;' if function.name in ('glMapBufferRange', 'glMapBufferRangeEXT', 'glMapNamedBufferRange', 'glMapNamedBufferRangeEXT'): print r' if (access & GL_MAP_NOTIFY_EXPLICIT_BIT_VMWX) {' print r' if (!(access & GL_MAP_PERSISTENT_BIT)) {' print r' os::log("apitrace: warning: %s: MAP_NOTIFY_EXPLICIT_BIT_VMWX set w/o MAP_PERSISTENT_BIT\n", __FUNCTION__);' print r' }' print r' if (access & GL_MAP_FLUSH_EXPLICIT_BIT) {' print r' os::log("apitrace: warning: %s: MAP_NOTIFY_EXPLICIT_BIT_VMWX set w/ MAP_FLUSH_EXPLICIT_BIT\n", __FUNCTION__);' print r' }' print r' access &= ~GL_MAP_NOTIFY_EXPLICIT_BIT_VMWX;' print r' } else if (access & GL_MAP_COHERENT_BIT) {' print r' os::log("apitrace: warning: %s: MAP_COHERENT_BIT unsupported (https://github.com/apitrace/apitrace/issues/232)\n", __FUNCTION__);' print r' } else if ((access & GL_MAP_PERSISTENT_BIT) &&' print r' !(access & GL_MAP_FLUSH_EXPLICIT_BIT)) {' print r' os::log("apitrace: warning: %s: MAP_PERSISTENT_BIT w/o FLUSH_EXPLICIT_BIT unsupported (https://github.com/apitrace/apitrace/issues/232)\n", __FUNCTION__);' print r' }' if function.name in ('glBufferData', 'glBufferDataARB'): print r' if (target == GL_EXTERNAL_VIRTUAL_MEMORY_BUFFER_AMD) {' print r' os::log("apitrace: warning: GL_AMD_pinned_memory not fully supported\n");' print r' }' # TODO: We don't track GL_INTEL_map_texture mappings if function.name == 'glMapTexture2DINTEL': print r' if (access & GL_MAP_WRITE_BIT) {' print r' os::log("apitrace: warning: GL_INTEL_map_texture not fully supported\n");' print r' }' # Don't leave vertex attrib locations to chance. Instead emit fake # glBindAttribLocation calls to ensure that the same locations will be # used when retracing. Trying to remap locations after the fact would # be an herculian task given that vertex attrib locations appear in # many entry-points, including non-shader related ones. if function.name == 'glLinkProgram': Tracer.invokeFunction(self, function) print ' GLint active_attributes = 0;' print ' _glGetProgramiv(program, GL_ACTIVE_ATTRIBUTES, &active_attributes);' print ' for (GLint attrib = 0; attrib < active_attributes; ++attrib) {' print ' GLint size = 0;' print ' GLenum type = 0;' print ' GLchar name[256];' # TODO: Use ACTIVE_ATTRIBUTE_MAX_LENGTH instead of 256 print ' _glGetActiveAttrib(program, attrib, sizeof name, NULL, &size, &type, name);' print " if (name[0] != 'g' \|\| name[1] != 'l' \|\| name[2] != '_') {" print ' GLint location = _glGetAttribLocation(program, name);' print ' if (location >= 0) {' bind_function = glapi.glapi.getFunctionByName('glBindAttribLocation') self.fake_call(bind_function, ['program', 'location', 'name']) print ' }' print ' }' print ' }' if function.name == 'glLinkProgramARB': Tracer.invokeFunction(self, function) print ' GLint active_attributes = 0;' print ' _glGetObjectParameterivARB(programObj, GL_OBJECT_ACTIVE_ATTRIBUTES_ARB, &active_attributes);' print ' for (GLint attrib = 0; attrib < active_attributes; ++attrib) {' print ' GLint size = 0;' print ' GLenum type = 0;' print ' GLcharARB name[256];' # TODO: Use ACTIVE_ATTRIBUTE_MAX_LENGTH instead of 256 print ' _glGetActiveAttribARB(programObj, attrib, sizeof name, NULL, &size, &type, name);' print " if (name[0] != 'g' \|\| name[1] != 'l' \|\| name[2] != '_') {" print ' GLint location = _glGetAttribLocationARB(programObj, name);' print ' if (location >= 0) {' bind_function = glapi.glapi.getFunctionByName('glBindAttribLocationARB') self.fake_call(bind_function, ['programObj', 'location', 'name']) print ' }' print ' }' print ' }' self.shadowBufferProlog(function) Tracer.traceFunctionImplBody(self, function) # These entrypoints are only expected to be implemented by tools; # drivers will probably not implement them. marker_functions = [ # GL_GREMEDY_string_marker 'glStringMarkerGREMEDY', # GL_GREMEDY_frame_terminator 'glFrameTerminatorGREMEDY', ] # These entrypoints may be implemented by drivers, but are also very useful # for debugging / analysis tools. debug_functions = [ # GL_KHR_debug 'glDebugMessageControl', 'glDebugMessageInsert', 'glDebugMessageCallback', 'glGetDebugMessageLog', 'glPushDebugGroup', 'glPopDebugGroup', 'glObjectLabel', 'glGetObjectLabel', 'glObjectPtrLabel', 'glGetObjectPtrLabel', # GL_KHR_debug (for OpenGL ES) 'glDebugMessageControlKHR', 'glDebugMessageInsertKHR', 'glDebugMessageCallbackKHR', 'glGetDebugMessageLogKHR', 'glPushDebugGroupKHR', 'glPopDebugGroupKHR', 'glObjectLabelKHR', 'glGetObjectLabelKHR', 'glObjectPtrLabelKHR', 'glGetObjectPtrLabelKHR', # GL_ARB_debug_output 'glDebugMessageControlARB', 'glDebugMessageInsertARB', 'glDebugMessageCallbackARB', 'glGetDebugMessageLogARB', # GL_AMD_debug_output 'glDebugMessageEnableAMD', 'glDebugMessageInsertAMD', 'glDebugMessageCallbackAMD', 'glGetDebugMessageLogAMD', # GL_EXT_debug_label 'glLabelObjectEXT', 'glGetObjectLabelEXT', # GL_EXT_debug_marker 'glInsertEventMarkerEXT', 'glPushGroupMarkerEXT', 'glPopGroupMarkerEXT', ] def invokeFunction(self, function): if function.name in ('glLinkProgram', 'glLinkProgramARB'): # These functions have been dispatched already return # Force glProgramBinary to fail. Per ARB_get_program_binary this # should signal the app that it needs to recompile. if function.name in ('glProgramBinary', 'glProgramBinaryOES'): print r' binaryFormat = 0xDEADDEAD;' print r' binary = &binaryFormat;' print r' length = sizeof binaryFormat;' Tracer.invokeFunction(self, function) def doInvokeFunction(self, function): # Same as invokeFunction() but called both when trace is enabled or disabled. # # Used to modify the behavior of GL entry-points. # Override GL extensions if function.name in ('glGetString', 'glGetIntegerv', 'glGetStringi'): Tracer.doInvokeFunction(self, function, prefix = 'gltrace::_', suffix = '_override') return # We implement GL_GREMEDY_, etc., and not the driver if function.name in self.marker_functions: return # We may be faking KHR_debug, so ensure the pointer queries result is # always zeroed to prevent dereference of unitialized pointers if function.name == 'glGetPointerv': print ' if (params &&' print ' (pname == GL_DEBUG_CALLBACK_FUNCTION \|\|' print ' pname == GL_DEBUG_CALLBACK_USER_PARAM)) {' print ' params = NULL;' print ' }' if function.name in self.getProcAddressFunctionNames: nameArg = function.args[0].name print ' if (strcmp("glNotifyMappedBufferRangeVMWX", (const char )%s) == 0) {' % (nameArg,) print ' _result = (%s)&glNotifyMappedBufferRangeVMWX;' % (function.type,) for marker_function in self.marker_functions: if self.api.getFunctionByName(marker_function): print ' } else if (strcmp("%s", (const char )%s) == 0) {' % (marker_function, nameArg) print ' _result = (%s)&%s;' % (function.type, marker_function) print ' } else {' Tracer.doInvokeFunction(self, function) # Replace function addresses with ours # XXX: Doing this here instead of wrapRet means that the trace will # contain the addresses of the wrapper functions, and not the real # functions, but in practice this should make no difference. if function.name in self.getProcAddressFunctionNames: print ' _result = _wrapProcAddress(%s, _result);' % (nameArg,) print ' }' return if function.name in ('glGetProgramBinary', 'glGetProgramBinaryOES'): print r' bufSize = 0;' Tracer.doInvokeFunction(self, function) if function.name == 'glGetProgramiv': print r' if (params && pname == GL_PROGRAM_BINARY_LENGTH) {' print r' params = 0;' print r' }' if function.name in ('glGetProgramBinary', 'glGetProgramBinaryOES'): print r' if (length) {' print r' length = 0;' print r' }' buffer_targets = [ 'ARRAY_BUFFER', 'ELEMENT_ARRAY_BUFFER', 'PIXEL_PACK_BUFFER', 'PIXEL_UNPACK_BUFFER', 'UNIFORM_BUFFER', 'TEXTURE_BUFFER', 'TRANSFORM_FEEDBACK_BUFFER', 'COPY_READ_BUFFER', 'COPY_WRITE_BUFFER', 'DRAW_INDIRECT_BUFFER', 'ATOMIC_COUNTER_BUFFER', ] def wrapRet(self, function, instance): Tracer.wrapRet(self, function, instance) # Keep track of buffer mappings if function.name in ('glMapBufferRange', 'glMapBufferRangeEXT'): print ' if (access & GL_MAP_WRITE_BIT) {' print ' _checkBufferMapRange = true;' print ' }' boolean_names = [ 'GL_FALSE', 'GL_TRUE', ] def gl_boolean(self, value): return self.boolean_names[int(bool(value))] # Regular expression for the names of the functions that unpack from a # pixel buffer object. See the ARB_pixel_buffer_object specification. unpack_function_regex = re.compile(r'^gl(' + r'\|'.join([ r'Bitmap', r'PolygonStipple', r'PixelMap[a-z]+v', r'DrawPixels', r'Color(Sub)?Table', r'(Convolution\|Separable)Filter[12]D', r'(Compressed)?(Multi)?Tex(ture)?(Sub)?Image[1-4]D', ]) + r')[0-9A-Z]$') def serializeArgValue(self, function, arg): # Recognize offsets instead of blobs when a PBO is bound if self.unpack_function_regex.match(function.name) \ and (isinstance(arg.type, stdapi.Blob) \ or (isinstance(arg.type, stdapi.Const) \ and isinstance(arg.type.type, stdapi.Blob))): print ' {' print ' gltrace::Context ctx = gltrace::getContext();' print ' GLint _unpack_buffer = 0;' print ' if (ctx->profile.desktop())' print ' _glGetIntegerv(GL_PIXEL_UNPACK_BUFFER_BINDING, &_unpack_buffer);' print ' if (_unpack_buffer) {' print ' trace::localWriter.writePointer((uintptr_t)%s);' % arg.name print ' } else {' Tracer.serializeArgValue(self, function, arg) print ' }' print ' }' return # Several GL state functions take GLenum symbolic names as # integer/floats; so dump the symbolic name whenever possible if function.name.startswith('gl') \ and arg.type in (glapi.GLint, glapi.GLfloat, glapi.GLdouble) \ and arg.name == 'param': assert arg.index > 0 assert function.args[arg.index - 1].name == 'pname' assert function.args[arg.index - 1].type == glapi.GLenum print ' if (is_symbolic_pname(pname) && is_symbolic_param(%s)) {' % arg.name self.serializeValue(glapi.GLenum, arg.name) print ' } else {' Tracer.serializeArgValue(self, function, arg) print ' }' return Tracer.serializeArgValue(self, function, arg) def footer(self, api): Tracer.footer(self, api) # A simple state tracker to track the pointer values # update the state print 'static void _trace_user_arrays(GLuint count)' print '{' print ' gltrace::Context ctx = gltrace::getContext();' print print ' glprofile::Profile profile = ctx->profile;' print ' bool es1 = profile.es() && profile.major == 1;' print # Temporarily unbind the array buffer print ' GLint _array_buffer = _glGetInteger(GL_ARRAY_BUFFER_BINDING);' print ' if (_array_buffer) {' self.fake_glBindBuffer(api, 'GL_ARRAY_BUFFER', '0') print ' }' print for camelcase_name, uppercase_name in self.arrays: # in which profile is the array available? profile_check = 'profile.desktop()' if camelcase_name in self.arrays_es1: profile_check = '(' + profile_check + ' \|\| es1)'; function_name = 'gl%sPointer' % camelcase_name enable_name = 'GL_%s_ARRAY' % uppercase_name binding_name = 'GL_%s_ARRAY_BUFFER_BINDING' % uppercase_name function = api.getFunctionByName(function_name) print ' // %s' % function.prototype() print ' if (%s) {' % profile_check self.array_trace_prolog(api, uppercase_name) self.array_prolog(api, uppercase_name) print ' if (_glIsEnabled(%s)) {' % enable_name print ' GLint _binding = _glGetInteger(%s);' % binding_name print ' if (!_binding) {' # Get the arguments via glGet for arg in function.args: arg_get_enum = 'GL_%s_ARRAY_%s' % (uppercase_name, arg.name.upper()) arg_get_function, arg_type = TypeGetter().visit(arg.type) print ' %s %s = 0;' % (arg_type, arg.name) print ' _%s(%s, &%s);' % (arg_get_function, arg_get_enum, arg.name) arg_names = ', '.join([arg.name for arg in function.args[:-1]]) print ' size_t _size = _%s_size(%s, count);' % (function.name, arg_names) # Emit a fake function self.array_trace_intermezzo(api, uppercase_name) print ' unsigned _call = trace::localWriter.beginEnter(&_%s_sig, true);' % (function.name,) for arg in function.args: assert not arg.output print ' trace::localWriter.beginArg(%u);' % (arg.index,) if arg.name != 'pointer': self.serializeValue(arg.type, arg.name) else: print ' trace::localWriter.writeBlob((const void )%s, _size);' % (arg.name) print ' trace::localWriter.endArg();' print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_call);' print ' trace::localWriter.endLeave();' print ' }' print ' }' self.array_epilog(api, uppercase_name) self.array_trace_epilog(api, uppercase_name) print ' }' print # Samething, but for glVertexAttribPointer # # Some variants of glVertexAttribPointer alias conventional and generic attributes: # - glVertexAttribPointer: no # - glVertexAttribPointerARB: implementation dependent # - glVertexAttribPointerNV: yes # # This means that the implementations of these functions do not always # alias, and they need to be considered independently. # print ' // ES1 does not support generic vertex attributes' print ' if (es1)' print ' return;' print print ' vertex_attrib _vertex_attrib = _get_vertex_attrib();' print for suffix in ['', 'NV']: if suffix: SUFFIX = '_' + suffix else: SUFFIX = suffix function_name = 'glVertexAttribPointer' + suffix function = api.getFunctionByName(function_name) print ' // %s' % function.prototype() print ' if (_vertex_attrib == VERTEX_ATTRIB%s) {' % SUFFIX if suffix == 'NV': print ' GLint _max_vertex_attribs = 16;' else: print ' GLint _max_vertex_attribs = _glGetInteger(GL_MAX_VERTEX_ATTRIBS);' print ' for (GLint index = 0; index < _max_vertex_attribs; ++index) {' print ' GLint _enabled = 0;' if suffix == 'NV': print ' _glGetIntegerv(GL_VERTEX_ATTRIB_ARRAY0_NV + index, &_enabled);' else: print ' _glGetVertexAttribiv%s(index, GL_VERTEX_ATTRIB_ARRAY_ENABLED%s, &_enabled);' % (suffix, SUFFIX) print ' if (_enabled) {' print ' GLint _binding = 0;' if suffix != 'NV': # It doesn't seem possible to use VBOs with NV_vertex_program. print ' _glGetVertexAttribiv%s(index, GL_VERTEX_ATTRIB_ARRAY_BUFFER_BINDING%s, &_binding);' % (suffix, SUFFIX) print ' if (!_binding) {' # Get the arguments via glGet* for arg in function.args[1:]: if suffix == 'NV': arg_get_enum = 'GL_ATTRIB_ARRAY_%s%s' % (arg.name.upper(), SUFFIX) else: arg_get_enum = 'GL_VERTEX_ATTRIB_ARRAY_%s%s' % (arg.name.upper(), SUFFIX) arg_get_function, arg_type = TypeGetter('glGetVertexAttrib', False, suffix).visit(arg.type) print ' %s %s = 0;' % (arg_type, arg.name) print ' _%s(index, %s, &%s);' % (arg_get_function, arg_get_enum, arg.name) arg_names = ', '.join([arg.name for arg in function.args[1:-1]]) print ' size_t _size = _%s_size(%s, count);' % (function.name, arg_names) # Emit a fake function print ' unsigned _call = trace::localWriter.beginEnter(&_%s_sig, true);' % (function.name,) for arg in function.args: assert not arg.output print ' trace::localWriter.beginArg(%u);' % (arg.index,) if arg.name != 'pointer': self.serializeValue(arg.type, arg.name) else: print ' trace::localWriter.writeBlob((const void )%s, _size);' % (arg.name) print ' trace::localWriter.endArg();' print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_call);' print ' trace::localWriter.endLeave();' print ' }' print ' }' print ' }' print ' }' print # Restore the original array_buffer print ' if (_array_buffer) {' self.fake_glBindBuffer(api, 'GL_ARRAY_BUFFER', '_array_buffer') print ' }' print print '}' print # Fake glStringMarkerGREMEDY print r'static void _fakeStringMarker(GLsizei len, const GLvoid string) {' glStringMarkerGREMEDY = api.getFunctionByName('glStringMarkerGREMEDY') self.fake_call(glStringMarkerGREMEDY, ['len', 'string']) print r'}' # # Hooks for glTexCoordPointer, which is identical to the other array # pointers except the fact that it is indexed by glClientActiveTexture. # def array_prolog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' GLint max_units = 0;' print ' if (ctx->profile.desktop())' print ' _glGetIntegerv(GL_MAX_TEXTURE_COORDS, &max_units);' print ' else' print ' _glGetIntegerv(GL_MAX_TEXTURE_UNITS, &max_units);' print ' GLint client_active_texture = GL_TEXTURE0;' print ' if (max_units > 0) {' print ' _glGetIntegerv(GL_CLIENT_ACTIVE_TEXTURE, &client_active_texture);' print ' }' print ' GLint unit = 0;' print ' do {' print ' GLint texture = GL_TEXTURE0 + unit;' print ' if (max_units > 0) {' print ' _glClientActiveTexture(texture);' print ' }' def array_trace_prolog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' bool client_active_texture_dirty = false;' def array_epilog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' } while (++unit < max_units);' self.array_cleanup(api, uppercase_name) def array_cleanup(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' if (max_units > 0) {' print ' _glClientActiveTexture(client_active_texture);' print ' }' def array_trace_intermezzo(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' if (texture != client_active_texture \|\| client_active_texture_dirty) {' print ' client_active_texture_dirty = true;' self.fake_glClientActiveTexture_call(api, "texture"); print ' }' def array_trace_epilog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' if (client_active_texture_dirty) {' self.fake_glClientActiveTexture_call(api, "client_active_texture"); print ' }' def fake_glBindBuffer(self, api, target, buffer): function = api.getFunctionByName('glBindBuffer') self.fake_call(function, [target, buffer]) def fake_glClientActiveTexture_call(self, api, texture): function = api.getFunctionByName('glClientActiveTexture') self.fake_call(function, [texture]) def emitFakeTexture2D(self): function = glapi.glapi.getFunctionByName('glTexImage2D') instances = function.argNames() print ' unsigned _fake_call = trace::localWriter.beginEnter(&_%s_sig, true);' % (function.name,) for arg in function.args: assert not arg.output self.serializeArg(function, arg) print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_fake_call);' print ' trace::localWriter.endLeave();'	EoD/apitrace	wrappers/gltrace.py	Python	mit	55,234	[ "VisIt" ]	ceec5b69fc3bb5024a8f3e82ac6378b982d01f707413fb5c2df99f1717cf693a
import numpy as np import scipy.special from scipy import constants import computations import data_processing def test_mie(): """Test the functions involved in the Mie coefficients computation. Compare to values obtained with Wolfram Alpha. """ n = 1 a = 10e-9 omega = 2.48 / constants.hbar * constants.eV eps1 = 1.0 eps2 = -2.377 + 1j2.856 k1 = np.sqrt(eps1) omega / constants.c k2 = np.sqrt(eps2) * omega / constants.c rho1 = k1a rho2 = k2a jn1 = scipy.special.spherical_jn(n, rho1) assert np.isclose(jn1, 0.041827106236) jn2 = scipy.special.spherical_jn(n, rho2) assert np.isclose(np.real(jn2), 0.034734565982) assert np.isclose(np.imag(jn2), 0.073239296279) hn1 = computations.spherical_hankel(n, rho1, jn1) assert np.isclose(np.real(hn1), 0.0418271062361) assert np.isclose(np.imag(hn1), -63.8076276033) jnprime1 = scipy.special.spherical_jn(n, rho1, derivative=True) assert np.isclose(jnprime1, 0.331755278538607) jnprime2 = scipy.special.spherical_jn(n, rho2, derivative=True) assert np.isclose(np.real(jnprime2), 0.337084148426481) assert np.isclose(np.imag(jnprime2), -0.004531343067615) psinprime1 = computations.psi_n_prime(rho1, jn1, jnprime1) assert np.isclose(psinprime1, 0.0835220176842857) psinprime2 = computations.psi_n_prime(rho2, jn2, jnprime2) assert np.isclose(np.real(psinprime2), 0.070389454025903) assert np.isclose(np.imag(psinprime2), 0.146716099221274) zetanprime1 = computations.zeta_n_prime(n, rho1, jnprime1, hn1) assert np.isclose(np.real(zetanprime1), 0.0835220176842857) assert np.isclose(np.imag(zetanprime1), 62.8155149095646) an = computations.mie_bn(1.0, 1.0, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(an), -1.96544240e-6) assert np.isclose(np.imag(an), -2.34432221e-6) bn = computations.mie_bn(eps1, eps2, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(bn), -0.00140178) assert np.isclose(np.imag(bn), 0.00149810) return 'Tests pass: Mie local' def test_mie_nonlocal(): """Test the functions involved in the nonlocal Mie coefficients computation. Compare to values obtained with Wolfram Alpha. """ n = 1 a = 10e-9 omega = 2.48 / constants.hbar * constants.eV omega_p = 8.1 / constants.hbar * constants.eV gamma = 0.047 / constants.hbar * constants.eV v_F = 1.40e6 D = 8.62e-4 eps1 = 1.0 eps2 = -2.377 + 1j2.856 eps_inf = 1.0 k1 = np.sqrt(eps1) omega / constants.c k2 = np.sqrt(eps2) * omega / constants.c k2_nl = computations.k_longitudinal(True, eps2, eps_inf, omega_p, gamma, v_F, D, omega) assert np.isclose(np.real(k2_nl), -2.98397e9, atol=0.0, rtol=1.0e-3) assert np.isclose(np.imag(k2_nl), 5.25972e9, atol=0.0, rtol=1.0e-3) rho1 = k1a rho2 = k2a rho2_nl = k2_nla jn1 = scipy.special.spherical_jn(n, rho1) jn2 = scipy.special.spherical_jn(n, rho2) hn1 = computations.spherical_hankel(n, rho1, jn1) jnprime1 = scipy.special.spherical_jn(n, rho1, derivative=True) jnprime2 = scipy.special.spherical_jn(n, rho2, derivative=True) psinprime1 = computations.psi_n_prime(rho1, jn1, jnprime1) psinprime2 = computations.psi_n_prime(rho2, jn2, jnprime2) zetanprime1 = computations.zeta_n_prime(n, rho1, jnprime1, hn1) jn2_nl = scipy.special.spherical_jn(n, rho2_nl) assert np.isclose(np.real(jn2_nl), 5.119867079e20) assert np.isclose(np.imag(jn2_nl), -2.786558951e20) jnprime2_nl = scipy.special.spherical_jn(n, rho2_nl, derivative=True) assert np.isclose(np.real(jnprime2_nl), -2.7063597583597e20) assert np.isclose(np.imag(jnprime2_nl), -5.0690425090715e20) deltan = computations.delta_n(n, rho2_nl, eps2, eps_inf, jn2) assert np.isclose(np.real(deltan), -0.0119636) assert np.isclose(np.imag(deltan), 0.00117763) an = computations.mie_bn(1.0, 1.0, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(an), -1.96544240e-6) assert np.isclose(np.imag(an), -2.34432221e-6) bn = computations.mie_bn(eps1, eps2, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(bn), -0.00140178) assert np.isclose(np.imag(bn), 0.00149810) return 'Tests pass: Mie nonlocal' def test_decay_rates(): """Test the functions involved in the decay rates computation. Compare to values obtained with finite element methods. """ r = data_processing.convert_units(30, 'nm') metal = 'Drude' eps_inf = 1.0 hbar_omega_p = 8.1 omega_p = data_processing.convert_eV_to_Hz(hbar_omega_p) hbar_gamma = constants.hbar / (14.0e-15 constants.eV) gamma = data_processing.convert_eV_to_Hz(hbar_gamma) n_max = 111 test_fem_local_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) test_fem_local_emission_dielectric(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) test_fem_local_distance_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) test_fem_nonlocal_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) metal = 'Olmon single-crystal gold' test_fem_emission_exp_eps(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) return 'Tests pass: FEM comparison' def test_fem_local_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a varying emission frequency in air. Only the relative difference is evaluated. """ nonlocal = False v_F = 0.0 D = 0.0 d = data_processing.convert_units(np.array([5]), 'nm') emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_inf = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_inf, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_01.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) orientation = 'tangential' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_inf, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_02.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-2) return 'Tests pass: FEM comparison for changing emission parameter in air with local Drude metal' def test_fem_local_emission_dielectric(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a varying emission frequency in a dielectric medium. Only the relative difference is evaluated. """ nonlocal = False v_F = 0.0 D = 0.0 d = data_processing.convert_units(np.array([5]), 'nm') emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') gamma = data_processing.convert_eV_to_Hz(hbar_gamma) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_03.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) orientation = 'tangential' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_04.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) return 'Tests pass: FEM comparison for changing emission parameter in dielectric with local Drude metal' def test_fem_local_distance_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a varying distance frequency in air. Only the relative difference is evaluated. """ nonlocal = False v_F = 0.0 D = 0.0 distance = np.linspace(1.0, 10.0, num=10) d = data_processing.convert_units(distance, 'nm') emission = 2.5 omega = data_processing.convert_emission_to_omega(np.array([emission]), 'hbar omega (eV)') gamma = data_processing.convert_eV_to_Hz(hbar_gamma) eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_05.txt', skiprows=17) assert np.allclose(d, fem_data[:, 0]) assert np.allclose(gamma_tot, fem_data[:, 1], atol=0.0, rtol=3.0e-2) orientation = 'tangential' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_06.txt', skiprows=17) assert np.allclose(d, fem_data[:, 0]) assert np.allclose(gamma_tot, fem_data[:, 1], atol=0.0, rtol=3.0e-2) return 'Tests pass: FEM comparison for changing distance in air with local Drude metal' def test_fem_nonlocal_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a Drude metal with a nonlocal response. Only the relative difference is evaluated. """ nonlocal = True v_F = 1.40e6 D = 0.0 d = data_processing.convert_units(np.array([5]), 'nm') emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_07.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) D = 8.62e-4 gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_08.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-2) return 'Tests pass: FEM comparison for changing emission parameter in air with nonlocal Drude metal' def test_fem_emission_exp_eps(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a metal with permittivity of gold given by Olmon. Only the relative difference is evaluated. """ emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') orientation = 'radial' d = data_processing.convert_units(np.array([5]), 'nm') nonlocal = False v_F = 0.0 D = 0.0 eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_09.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_10.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) nonlocal = True v_F = 1.40e6 D = 0.0 eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_11.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_12.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) D = 8.62e-4 eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_13.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_14.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) return 'Tests pass: FEM comparison for metal with permittivity of gold given by Olmon' if __name__ == "__main__": print(test_mie()) print(test_mie_nonlocal()) print(test_decay_rates())	rjurga/plasmon-fluorescence	tests.py	Python	mit	16,104	[ "CRYSTAL" ]	74b5f81a13fe5e64c44ed9726bacbfa50303489ad0fad9674c5c4d530aa2e7ca
# -- coding: UTF-8 -- """ ``trinity_mapping`` ----------------------------------------------------------------- :Authors: Menachem Sklarz :Affiliation: Bioinformatics core facility :Organization: National Institute of Biotechnology in the Negev, Ben Gurion University. A class that defines a module for running ``align_and_estimate_abundance.pl`` on a Trinity assembly and the raw reads. Tested on versions 2.4.0 and 2.5.0 of Trinity. See the `align_and_estimate_abundance.pl`_ script documentation. .. _align_and_estimate_abundance.pl: https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Transcript-Quantification#estimating-transcript-abundance Requires ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ * ``fastq`` files in at least one of the following slots: * ``sample_data[<sample>]["fastq.F"]`` * ``sample_data[<sample>]["fastq.R"]`` * ``sample_data[<sample>]["fastq.S"]`` * A Trinity assembly in one of (depending on ``scope``) * ``sample_data[<sample>]["fasta.nucl"]`` * ``sample_data["fasta.nucl"]`` Output: ~~~~~~~~~~~~~ * Puts output files in the following slots: * ``sample_data[<sample>]["bam"]`` * ``sample_data[<sample>]["unsorted_bam"]`` (If ``--coordsort_bam`` is passed in redirects) * ``sample_data[<sample>]["isoforms.results"]`` * ``sample_data[<sample>]["genes.results"]`` Parameters that can be set ~~~~~~~~~~~~~~~~~~~~~~~~~~ .. csv-table:: :header: "Parameter", "Values", "Comments" "scope", "sample\|project", "Set if project-wide fasta slot should be used" "redirects: --gene_trans_map", "path or empty", "If empty, use internal gene_trans_map. If path, use path as gene_trans_map for all samples. If not passed, performs analysis on isoform level only" "redirects: --trinity_mode", "", "If set, will create a gene_trans_map for each sample and store it as sample gene_trans_map" Lines for parameter file ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :: trin_map1: module: trinity_mapping base: trinity1 script_path: {Vars.paths.align_and_estimate_abundance} redirects: --est_method: RSEM --aln_method: bowtie --trinity_mode: --seqType: fq References ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q. and Chen, Z., 2011. Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data. Nature biotechnology, 29(7), p.644. """ import os import sys import re from neatseq_flow.PLC_step import Step,AssertionExcept __author__ = "Menachem Sklarz" __version__ = "1.6.0" class Step_trinity_mapping(Step): def step_specific_init(self): self.shell = "bash" # Can be set to "bash" by inheriting instances self.file_tag = "trinity_mapping" if "--est_method" not in self.params["redir_params"]: raise AssertionExcept("You must pass an --est_method to trinity_mapping.\n") # Is used below... self.est_method = self.params["redir_params"]["--est_method"] if self.est_method == "kallisto": raise AssertionExcept("Method 'kallisto' is not defined yet!") # To define, find out what the per isoform and per gene output files are named and fill the names in the dictionary called file_suffix_ind, below. if "--aln_method" in self.params["redir_params"]: # raise AssertionExcept("You must pass an --aln_method to trinity_mapping\n") self.params["aln_method"] = self.params["redir_params"]["--aln_method"] del self.params["redir_params"]["--aln_method"] else: self.params["aln_method"] = None if not self.params["aln_method"] and self.est_method.lower() in ["rsem","express"]: raise AssertionExcept("For RSEM and eXpress, you must supply an 'aln_method' parameter") if "scope" not in self.params: raise AssertionExcept("Please specify a 'scope': Either 'sample' or 'project'.") for redir2remove in ["--transcripts", "--output_dir", "--left", "--right", "--single", "--prep_reference"]: if redir2remove in self.params["redir_params"]: del self.params["redir_params"][redir2remove] self.write_warning("You are not supposed to specify %s in redirects. We set it automatically" % redir2remove) def step_sample_initiation(self): """ A place to do initiation stages following setting of sample_data Here you should do testing for dependency output. These will NOT exist at initiation of this instance. They are set only following sample_data updating """ if self.params["scope"] == "sample": # Check that "fasta" and "assembly" exist (signs that trinity has been executed) for sample in self.sample_data["samples"]: if "fasta.nucl" not in self.sample_data[sample]: raise AssertionExcept("It seems there is no sample-wide assembly.", sample) elif self.params["scope"] == "project": # print self.sample_data.keys() if "fasta.nucl" not in self.sample_data["project_data"]: raise AssertionExcept("It seems there is no project-wide assembly.") else: raise AssertionExcept("'scope' must be either 'sample' or 'project'.") # If "bam" required as input method, make sure a bam exists for all samples: if self.params["aln_method"] == "bam": for sample in self.sample_data["samples"]: if "bam" not in self.sample_data[sample]: raise AssertionExcept("It seems there is no BAM file for the sample.", sample) # Dealing with gene_trans_map: if self.params["scope"] == "project": if "--gene_trans_map" in self.params["redir_params"]: self.use_gene_trans_map = True if self.params["redir_params"]["--gene_trans_map"]: # If value was passed self.sample_data["project_data"]["gene_trans_map"] = self.params["redir_params"]["--gene_trans_map"] else: # If passed empty, use internal: if "gene_trans_map" in self.sample_data["project_data"]: self.params["redir_params"]["--gene_trans_map"] = self.sample_data["project_data"]["gene_trans_map"] else: raise AssertionExcept("Expecting 'gene_trans_map' in project but none found.\n") elif "--trinity_mode" in self.params["redir_params"]: self.use_gene_trans_map = True else: self.use_gene_trans_map = False else: # sample scope if "--gene_trans_map" in self.params["redir_params"]: self.use_gene_trans_map = True if self.params["redir_params"]["--gene_trans_map"]: # If value was passed for sample in self.sample_data["samples"]: self.sample_data[sample]["gene_trans_map"] = self.params["redir_params"]["--gene_trans_map"] else: # If passed empty, use internal: if "gene_trans_map" in self.sample_data[sample]: self.params["redir_params"]["--gene_trans_map"] = self.sample_data[sample]["gene_trans_map"] else: raise AssertionExcept("Expecting 'gene_trans_map' in sample but none found.\n", sample) elif "--trinity_mode" in self.params["redir_params"]: self.sample_data[sample]["gene_trans_map"] = "%s.gene_trans_map" % self.sample_data[sample]["fasta.nucl"] self.use_gene_trans_map = True else: self.use_gene_trans_map = False def create_spec_wrapping_up_script(self): """ Add stuff to check and agglomerate the output data """ pass def create_spec_preliminary_script(self): """ Add script to run BEFORE all other steps """ if all([self.params["scope"] == "project", self.params["aln_method"] not in ["bam", None]]): self.script = "" # 1. Create link to fasta file in Reference dir # 2. Create link to gene_trans_map file as well, if it exists self.script += """\ # Creating a local sost link to the reference # The purpose is that the reference will not be built in the original location mkdir -p {dir} cp -rsf \\ {ref} \\{map} {dir} """.format(ref=self.sample_data["project_data"]["fasta.nucl"], map=("\n\t"+self.sample_data["project_data"]["gene_trans_map"]+" \\") if "gene_trans_map" in self.sample_data["project_data"] else "", dir=self.base_dir+"Reference") # Set fasta.nucl to new link to original fasta nucl self.sample_data["project_data"]["fasta.nucl"] = "{dir}Reference/{fn}".\ format(dir=self.base_dir, fn=os.path.basename(self.sample_data["project_data"]["fasta.nucl"])) # If it exists, and therefore linked, set gene_trans_map to new link to original file: if "gene_trans_map" in self.sample_data["project_data"]: self.sample_data["project_data"]["gene_trans_map"] = "{dir}Reference/{fn}".\ format(dir=self.base_dir, fn=os.path.basename(self.sample_data["project_data"]["gene_trans_map"])) # "%s.gene_trans_map" % self.sample_data["project_data"]["fasta.nucl"] # Create script and write to SCRPT # First: transcript preparation (with --pre_reference arg) self.script += """ {const}--aln_method {aln} \\ \t--transcripts {fasta} \\ \t--prep_reference """.format(const=self.get_script_const(), aln=self.params["aln_method"], fasta=self.sample_data["project_data"]["fasta.nucl"]) else: pass def build_scripts(self): file_suffix_ind = { "rsem": { "isoforms": "RSEM.isoforms.results", "genes": "RSEM.genes.results"}, "salmon": { "isoforms": "quant.sf", "genes": "quant.sf.genes"}, "kallisto": { "isoforms": "", "genes": "" }, "express": { "isoforms": "results.xprs", "genes": "results.xprs.genes"} } # Loop over samples and concatenate read files to $forward and $reverse respectively # add check if paired or single !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! for sample in self.sample_data["samples"]: # Getting list of samples out of samples_hash # Name of specific script: self.spec_script_name = self.set_spec_script_name(sample) self.script = "" # Make a dir for the current sample: sample_dir = self.make_folder_for_sample(sample) # This line should be left before every new script. It sees to local issues. # Use the dir it returns as the base_dir for this step. use_dir = self.local_start(sample_dir) # Procedure for preparing # Repeating procedure as done in trinity step: # If both F and R reads exist, adding them to forward and reverse # Assuming upstream input testing to check that if there are F reads then there are also R reads. # Setting variables to empty strings single = forward = reverse = "" if "fastq.F" in self.sample_data[sample]: forward = self.sample_data[sample]["fastq.F"] reverse = self.sample_data[sample]["fastq.R"] if "fastq.S" in self.sample_data[sample]: single = self.sample_data[sample]["fastq.S"] # # Adding single reads to end of left (=forward) reads # if single != "" and forward != "": # forward = ",".join([forward,single]) transcripts = self.sample_data[sample]["fasta.nucl"] \ if self.params["scope"] == "sample" \ else self.sample_data["project_data"]["fasta.nucl"] if all([self.params["scope"] == "sample", \ "aln_method" in self.params, \ self.params["aln_method"] not in ["bam", None]]): self.script += "# Preperaing the reference for analysis:\n\n" self.script += self.get_script_const() self.script += "--aln_method %s \\\n\t" % self.params["aln_method"] self.script += "--transcripts %s \\\n\t" % transcripts self.script += "--prep_reference \n\n" # Create script and write to SCRPT # First: transcript preparation (with --pre_reference arg) # - This is done with preliminary script (see create_spec_preliminary_script()) self.script += self.get_script_const() if self.params["aln_method"] == "bam": self.script += "--aln_method %s \\\n\t" % self.sample_data[sample]["bam"] # Checked above. BAM must exist. elif self.params["aln_method"] == None: pass else: self.script += "--aln_method %s \\\n\t" % self.params["aln_method"] self.script += "--transcripts %s \\\n\t" % transcripts self.script += "--output_dir %s \\\n\t" % use_dir if (forward): self.script += "--left %s \\\n\t" % forward self.script += "--right %s \\\n\t" % reverse elif (single): self.script += "--single %s \\\n\t" % single else: pass # No reads. This should be caught above... self.script = self.script.rstrip("\\\n\t") + "\n\n" # Storing files: mv_data = {"dir" : use_dir, "src" : file_suffix_ind[self.est_method.lower()]["isoforms"], "trg" : ".".join([sample,file_suffix_ind[self.est_method.lower()]["isoforms"]])} self.script += "mv {dir}{src} {dir}{trg}\n".format(mv_data) self.sample_data[sample]["isoforms.results"] = "{dir}{trg}".format(mv_data) self.stamp_file(self.sample_data[sample]["isoforms.results"]) if self.use_gene_trans_map: # Produce gene files: mv_data["src"] = file_suffix_ind[self.est_method.lower()]["genes"] mv_data["trg"] = ".".join([sample,file_suffix_ind[self.est_method.lower()]["genes"]]) self.script += "mv {dir}{src} {dir}{trg}\n".format(mv_data) self.sample_data[sample]["genes.results"] = "{dir}{trg}".format(mv_data) self.stamp_file(self.sample_data[sample]["genes.results"]) # Store bam files if self.est_method.lower() in ["rsem","express"]: self.sample_data[sample]["bam"] = "{dir}{method}.bam".format(dir = sample_dir, \ method = self.params["aln_method"]) self.stamp_file(self.sample_data[sample]["bam"]) self.sample_data[sample]["mapper"] = "%s" % self.params["aln_method"] if "--coordsort_bam" in self.params["redir_params"]: self.sample_data[sample]["unsorted_bam"] = self.sample_data[sample]["bam"] self.stamp_file(self.sample_data[sample]["unsorted_bam"]) self.sample_data[sample]["bam"] = "{dir}{method}.csorted.bam".format(dir = sample_dir, \ method = self.params["aln_method"]) self.stamp_file(self.sample_data[sample]["bam"]) self.sample_data[sample]["reference"] = transcripts # Move all files from temporary local dir to permanent base_dir self.local_finish(use_dir,self.base_dir) # Sees to copying local files to final destination (and other stuff) self.create_low_level_script()	bioinfo-core-BGU/neatseq-flow_modules	neatseq_flow_modules/RNA_seq/trinity_mapping.py	Python	gpl-3.0	17,105	[ "Bowtie" ]	6f1a6baa94708be445935242dc409ac60d0ddac45614a084d6d906edf6e17aae
############################################################################## ## ## Copyright (C) 2014-2016, New York University. ## Copyright (C) 2011-2014, NYU-Poly. ## Copyright (C) 2006-2011, University of Utah. ## All rights reserved. ## Contact: contact@vistrails.org ## ## This file is part of VisTrails. ## ## "Redistribution and use in source and binary forms, with or without ## modification, are permitted provided that the following conditions are met: ## ## - Redistributions of source code must retain the above copyright notice, ## this list of conditions and the following disclaimer. ## - Redistributions in binary form must reproduce the above copyright ## notice, this list of conditions and the following disclaimer in the ## documentation and/or other materials provided with the distribution. ## - Neither the name of the New York University nor the names of its ## contributors may be used to endorse or promote products derived from ## this software without specific prior written permission. ## ## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" ## AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, ## THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR ## PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR ## CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, ## EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, ## PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; ## OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, ## WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR ## OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ## ADVISED OF THE POSSIBILITY OF SUCH DAMAGE." ## ############################################################################### """Configuration variables for controlling specific things in VisTrails. """ from __future__ import division import atexit import email.utils import json import os import requests import tempfile import usagestats import weakref from vistrails.core import debug from vistrails.core.system import vistrails_version, \ vistrails_examples_directory usage_report = None def setup_usage_report(): """Sets up the usagestats module. """ global usage_report certificate_file = get_ca_certificate() usage_report = usagestats.Stats( '~/.vistrails/usage_stats', usagestats.Prompt( "\nUploading usage statistics is currently disabled\n" "Please help us by providing anonymous usage statistics; " "you can enable this\neither from the GUI or by using " "--enable-usage-stats\n" "If you do not want to see this message again, you can disable " "it from the GUI or with --disable-usage-stats\n" "Nothing will be uploaded before you opt in.\n"), 'https://reprozip-stats.poly.edu/', version='VisTrails %s' % vistrails_version(), unique_user_id=True, env_var='VISTRAILS_USAGE_STATS', ssl_verify=certificate_file) cwd = os.getcwd() record_usage(cwd_spaces=b' ' in cwd) try: cwd.decode('ascii') except UnicodeDecodeError: record_usage(cwd_ascii=False) else: record_usage(cwd_ascii=True) def update_config(configuration): if getattr(configuration, 'enableUsage', False): usage_report.enable_reporting() configuration.reportUsage = 1 return True elif getattr(configuration, 'disableUsage', False): usage_report.disable_reporting() configuration.reportUsage = 0 return True return False def record_usage(kwargs): """Records some info in the current usage report. """ if usage_report is not None: debug.debug("record_usage %r" % (kwargs,)) usage_report.note(kwargs) saved_vistrails = weakref.WeakValueDictionary() features = set() features_for_vistrails = {} def record_vistrail(what, vistrail): """Record info about a vistrail we used. """ if not usage_report.recording: return from vistrails.core.vistrail.controller import VistrailController from vistrails.core.vistrail.pipeline import Pipeline from vistrails.core.vistrail.vistrail import Vistrail from vistrails.db.services.locator import XMLFileLocator if isinstance(vistrail, VistrailController): vistrail = vistrail.vistrail if what == 'save': # Don't report now, but mark it for reporting when it gets closed saved_vistrails[id(vistrail)] = vistrail return elif what == 'close': i = id(vistrail) if i in saved_vistrails: del saved_vistrails[i] what = 'saved_close' else: return if isinstance(vistrail, Vistrail): upgrade_from = set() upgrade_to = set() nb_notes = 0 nb_paramexplorations = 0 for annotation in vistrail.action_annotations: if annotation.key == Vistrail.UPGRADE_ANNOTATION: upgrade_from.add(annotation.action_id) upgrade_to.add(int(annotation.value)) elif annotation.key == Vistrail.NOTES_ANNOTATION: nb_notes += 1 elif annotation.key == Vistrail.PARAMEXP_ANNOTATION: nb_paramexplorations += 1 nb_upgrades = len(upgrade_from - upgrade_to) if isinstance(vistrail.locator, XMLFileLocator): usage_report.note({'in_examples_dir': os.path.realpath(vistrail.locator._name).startswith( os.path.realpath(vistrails_examples_directory()))}) nb_modules = 0 nb_groups = 0 nb_abstractions = 0 for action in vistrail.actions: if action.id in upgrade_to or action.description == "Upgrade": continue for operation in action.operations: if operation.vtType == 'add' or operation.vtType == 'change': if operation.what == 'module': nb_modules += 1 if operation.data.is_group(): nb_groups += 1 elif operation.data.is_abstraction(): nb_abstractions += 1 usage_report.note(dict(use_vistrail=what, nb_versions=len(vistrail.actionMap), nb_tags=len(vistrail.get_tagMap()), nb_notes=nb_notes, nb_paramexplorations=nb_paramexplorations, nb_upgrades=nb_upgrades, nb_variables=len(vistrail.vistrail_variables), nb_modules=nb_modules, nb_groups=nb_groups, nb_abstractions=nb_abstractions)) for feature in features_for_vistrails.pop(id(vistrail), ()): usage_report.note({'feature_for_vistrail': feature}) elif isinstance(vistrail, Pipeline): usage_report.note(dict(use_workflow=what, nb_modules=len(vistrail.module_list))) else: raise TypeError def record_feature(feature, vistrail=None): """Record that a feature was used. """ from vistrails.core.vistrail.controller import VistrailController if vistrail is not None: if isinstance(vistrail, VistrailController): vistrail = vistrail.vistrail features_for_vistrails.setdefault(id(vistrail), set()).add(feature) else: features.add(feature) def submit_usage_report(kwargs): """Submits the current usage report to the usagestats server. """ debug.debug("submit_usage_report %r" % (kwargs,)) for pkg in ('numpy', 'scipy', 'matplotlib'): try: pkg_o = __import__(pkg, globals(), locals()) usage_report.note({pkg: getattr(pkg_o, '__version__', '')}) except ImportError: pass try: import vtk usage_report.note({'vtk': vtk.vtkVersion().GetVTKVersion()}) except ImportError: pass features.update(*features_for_vistrails.values()) for feature in features: usage_report.note({'feature': feature}) usage_report.submit(kwargs, usagestats.OPERATING_SYSTEM, usagestats.SESSION_TIME, usagestats.PYTHON_VERSION) _server_news = None def get_server_news(): global _server_news if _server_news is not None: return _server_news dot_vistrails = os.path.expanduser('~/.vistrails') if not os.path.exists(dot_vistrails): os.mkdir(dot_vistrails) file_name = os.path.join(dot_vistrails, 'server_news.json') file_exists = os.path.exists(file_name) headers = {} if file_exists: mtime = email.utils.formatdate(os.path.getmtime(file_name), usegmt=True) headers['If-Modified-Since'] = mtime try: resp = requests.get( 'https://reprozip-stats.poly.edu/vistrails_news/%s' % vistrails_version(), headers=headers, timeout=2 if file_exists else 10, stream=True, verify=get_ca_certificate()) resp.raise_for_status() if resp.status_code == 304: raise requests.HTTPError( '304 File is up to date, no data returned', response=resp) except requests.RequestException, e: if not e.response or e.response.status_code != 304: debug.warning("Can't download server news", e) else: try: with open(file_name, 'wb') as f: for chunk in resp.iter_content(4096): f.write(chunk) resp.close() except Exception, e: try: os.remove(file_name) except OSError: pass raise e debug.log("Downloaded server news") if os.path.exists(file_name): with open(file_name, 'r') as f: _server_news = json.load(f) else: _server_news = _default_news return _server_news def get_ca_certificate(): fd, certificate_file = tempfile.mkstemp(prefix='vistrails_stats_ca_', suffix='.pem') with open(certificate_file, 'wb') as fp: fp.write(_ca_certificate) os.close(fd) atexit.register(os.remove, certificate_file) return certificate_file _default_news = { 'version': '20160304', 'news_html': None, 'usage_report_prompt_html': u"<p>Please help us by reporting anonymous statistics about how you " u"use VisTrails.</p><p>We would like to collect high-level details " u"like which packages you use, which features, the size of your " u"workflows and version trees, ... This information is reported " u"anonymously and will only be used by the VisTrails team, to help " u"guide our efforts.</p>", } _ca_certificate = b'''\ -----BEGIN CERTIFICATE----- MIIDzzCCAregAwIBAgIJAMmlcDnTidBEMA0GCSqGSIb3DQEBCwUAMH4xCzAJBgNV BAYTAlVTMREwDwYDVQQIDAhOZXcgWW9yazERMA8GA1UEBwwITmV3IFlvcmsxDDAK BgNVBAoMA05ZVTERMA8GA1UEAwwIUmVwcm9aaXAxKDAmBgkqhkiG9w0BCQEWGXJl cHJvemlwLWRldkB2Z2MucG9seS5lZHUwHhcNMTQxMTA3MDUxOTA5WhcNMjQxMTA0 MDUxOTA5WjB+MQswCQYDVQQGEwJVUzERMA8GA1UECAwITmV3IFlvcmsxETAPBgNV BAcMCE5ldyBZb3JrMQwwCgYDVQQKDANOWVUxETAPBgNVBAMMCFJlcHJvWmlwMSgw JgYJKoZIhvcNAQkBFhlyZXByb3ppcC1kZXZAdmdjLnBvbHkuZWR1MIIBIjANBgkq hkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA1fuTW2snrVji51vGVl9hXAAZbNJ+dxG+ /LOOxZrF2f1RRNy8YWpeCfGbsZqiIEjorBv8lvdd9P+tD3M5sh9L0zQPU9dFvDb+ OOrV0jx59hbK3QcCQju3YFuAtD1lu8TBIPgGEab0eJhLVIX+XU5cYXrfoBmwCpN/ 1wXWkUhN91ZVMA0ylATAxTpnoNuMKzfTxT8pyOWajiTskYkKmVBAxgYJQe1YDFA8 fglBNkQuHqP8jgYAniEBCAPZRMMq8WpOtyFx+L9LX9/WcHtAQyDPPb9M81KKgPQq urtCqtuDKxuqcX9zg4/O8l4nZ50pwaJjbH4kMW/wnLzTPvzZCPtJYQIDAQABo1Aw TjAdBgNVHQ4EFgQUJjhDDOup4P0cdrAVq1F9ap3yTj8wHwYDVR0jBBgwFoAUJjhD DOup4P0cdrAVq1F9ap3yTj8wDAYDVR0TBAUwAwEB/zANBgkqhkiG9w0BAQsFAAOC AQEAeKpTiy2WYPqevHseTCJDIL44zghDJ9w5JmECOhFgPXR9Hl5Nh9S1j4qHBs4G cn8d1p2+8tgcJpNAysjuSl4/MM6hQNecW0QVqvJDQGPn33bruMB4DYRT5du1Zpz1 YIKRjGU7Of3CycOCbaT50VZHhEd5GS2Lvg41ngxtsE8JKnvPuim92dnCutD0beV+ 4TEvoleIi/K4AZWIaekIyqazd0c7eQjgSclNGgePcdbaxIo0u6tmdTYk3RNzo99t DCfXxuMMg3wo5pbqG+MvTdECaLwt14zWU259z8JX0BoeVG32kHlt2eUpm5PCfxqc dYuwZmAXksp0T0cWo0DnjJKRGQ== -----END CERTIFICATE----- '''	VisTrails/VisTrails	vistrails/core/reportusage.py	Python	bsd-3-clause	12,618	[ "VTK" ]	68d73abebf4c6c69c6bf8f048be1792fc6af5cdc6139deba2aaee297b8eca5fe
from __future__ import print_function import psi4 from psi4.driver import qcdb #! A test of the basis specification. Various basis sets are specified outright and in blocks, both #! orbital and auxiliary. Constructs libmints BasisSet objects through the constructor that calls #! qcdb.BasisSet infrastructure. Checks that the resulting bases are of the right size and checks #! that symmetry of the Molecule observes the basis assignment to atoms. # cc-pvdz aug-cc-pvdz # BASIS H 5/ 5 C 14/15 H +4/ 4 C +9/10 # RIFIT H 14/15 C 56/66 H +9/10 C +16/20 # JKFIT H 23/25 C 70/81 H +9/10 C +16/20 mymol = psi4.geometry(""" C 0.0 0.0 0.0 O 1.4 0.0 0.0 H_r -0.5 -0.7 0.0 H_l -0.5 0.7 0.0 """) psi4.set_options({'basis': 'cc-pvdz'}) print('[1] <<< uniform cc-pVDZ >>>') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_strings('CC-PVDZ', psi4.core.get_global_option('BASIS'), 'name') #TEST psi4.compare_integers(38, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(40, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('CC-PVDZ', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[2] <<< RIFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(140, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(162, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(CC-PVDZ AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PVDZ-RI', wert.blend(), 'blend') #TEST mymol.print_out() print('[3] <<< cc-pVDZ w/ aug-cc-pVDZ on C >>>') psi4.basis_helper(""" assign cc-pvdz assign c aug-cc-pvdz """, name='dz_PLUS') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(47, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(50, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[4] <<< RIFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS')) mymol.print_out() wert.print_out() psi4.compare_integers(156, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(182, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(DZ_PLUS AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-RI + CC-PVDZ-RI', wert.blend(), 'blend') #TEST mymol.print_out() print('[5] <<< cc-pVDZ w/ aug-cc-pVDZ on C, H_R >>>') psi4.basis_helper(""" assign cc-pvdz assign c aug-cc-pvdz assign h_r aug-cc-pvdz """, name='dz_PLUSplus', key='BASis') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_strings('DZ_PLUSPLUS', psi4.core.get_global_option('BASIS'), 'name') #TEST psi4.compare_integers(51, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(54, wert.nao(), 'nao()') #TEST psi4.compare_strings('cs', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[6] <<< RIFIT (custom: force cc-pVDZ on H, default on C, O) >>>') psi4.basis_helper(""" assign h cc-pvdz-ri """, name='dz_PLUSplusRI', key='df_basis_mp2') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', psi4.core.get_global_option('DF_BASIS_MP2'), 'RIFIT', psi4.core.get_global_option('BASIS')) mymol.print_out() psi4.compare_integers(156, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(182, wert.nao(), 'nao()') #TEST psi4.compare_strings('cs', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUSRI', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-RI + CC-PVDZ-RI', wert.blend(), 'blend') #TEST mymol.print_out() print('[7] <<< cc-pVDZ w/ aug-cc-pVDZ on C, H >>>') psi4.basis_helper(""" assign cc-pvdz assign c aug-cc-pvdz assign h aug-cc-pvdz """, name = 'dz_PLUSplusplus') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(55, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(58, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUSPLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[8] <<< JKFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(220, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(252, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(DZ_PLUSPLUSPLUS AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-JKFIT + CC-PVDZ-JKFIT', wert.blend(), 'blend') #TEST mymol.print_out() psi4.set_options({'basis': 'aug-cc-pvdz'}) print('[9] <<< aug-cc-pVDZ >>>') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(64, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(68, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('AUG-CC-PVDZ', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[10] <<< JKFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(236, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(272, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(AUG-CC-PVDZ AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-JKFIT', wert.blend(), 'blend') #TEST mymol.print_out() mymol2 = psi4.geometry(""" C 0.0 0.0 0.0 O 1.4 0.0 0.0 H_r -0.5 -0.6 0.3 H_l -0.5 0.6 0.3 H_c -0.5 0.0 0.7 """) psi4.set_options({'basis': 'dz_plusplusplus'}) print('[11] <<< cc-pVDZ w/ aug-cc-pVDZ on C, H >>>') wert = psi4.core.BasisSet.build(mymol2, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(64, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(67, wert.nao(), 'nao()') #TEST psi4.compare_strings('cs', mymol2.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUSPLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol2.print_out() hene = psi4.geometry(""" He Ne 1 2.0 """) psi4.basis_helper(""" assign cc-pv5z """, name='disguised5z') psi4.core.set_global_option('DF_BASIS_MP2', '') # clear df_basis_mp2 {...} to get autoaux below print('[12] <<< cc-pV5Z on HeNe >>>') wert = psi4.core.BasisSet.build(hene, 'BASIS', psi4.core.get_global_option('BASIS')) hene.print_out() psi4.compare_integers(146, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(196, wert.nao(), 'nao()') #TEST psi4.compare_strings('DISGUISED5Z', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PV5Z', wert.blend(), 'blend') #TEST print('[13] <<< RI for cc-pV5Z on HeNe >>>') wert = psi4.core.BasisSet.build(hene, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS')) hene.print_out() psi4.compare_integers(284, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(413, wert.nao(), 'nao()') #TEST psi4.compare_strings('(DISGUISED5Z AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PV5Z-RI', wert.blend(), 'blend') #TEST print('[14] <<< impossible JK for cc-pV5Z on HeNe >>>') error_tripped = 0 try: wert = psi4.core.BasisSet.build(hene, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) except qcdb.BasisSetNotFound: error_tripped = 1 psi4.compare_integers(1, error_tripped, 'squashed 4z aux for 5z orb') #TEST psi4.basis_helper(key='df_basis_scf', name='uggh', block=""" assign he DEF2-QZVPP-JKFIT """) hene.print_out() print('[15] <<< forced JK for cc-pV5Z on HeNe >>>') wert = psi4.core.BasisSet.build(hene, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(169, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(241, wert.nao(), 'nao()') #TEST psi4.compare_strings('UGGH', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PV5Z-JKFIT + DEF2-QZVPP-JKFIT', wert.blend(), 'blend') #TEST	kratman/psi4public	tests/python/mints9/input.py	Python	gpl-2.0	8,970	[ "Psi4" ]	6e5ebbef360a1a6cf2bb4bf50d6d44da19cfe56f43bc5bf83451f1fc46a2bf4a
#!/usr/bin/env python """ modules for large scale experiment runs includes: - reading of genome sequence in fasta format - manual cleaning of genome and annotation files - feature annotation db for querying details - creating star genome indicies Requirement: STAR aligner: https://github.com/alexdobin/STAR gfftools: https://github.com/vipints/genomeutils/tree/master/gfftools Biopython: http://biopython.org """ import os import re import sys import shutil import subprocess from Bio import SeqIO from gfftools import helper, GFFParser def stop_err(msg): """ stop the execution and print out the captured error message. """ sys.stderr.write('%s\n' % msg) sys.exit(-1) def clean_anno_file(chr_names, gtf_file, gtf_out): """ make stable annotation file with valid contig name @args chr_names: different contig names with a valid genome sequence @type chr_names: dict @args gtf_file: genome annotation in gtf/gff form @type gtf_file: str @args gtf_out: new genome annotation in gtf/gff form @type gtf_out: str """ # get the filehandler from input file try: fh = helper.open_file(gtf_file) except Exception, errmsg: stop_err('error %s in reading file %s' % (errmsg, gtf_file)) # check the out filehandler try: outfh = open(gtf_out, "w") except Exception, errmsg: stop_err('error %s in writing file %s' % (errmsg, gtf_out)) for line in fh: line = line.strip('\n\r') ## preserving the fasta header if present if line[0] in ['#', '>']: outfh.write(line + '\n') continue ## preserving the genome sequence if present if not re.search('\t', line): outfh.write(line + '\n') continue ## looking for gtf/gff files fields = line.split('\t') assert len(fields) >= 8, fields if fields[0] in chr_names: outfh.write(line + '\n') fh.close() outfh.close() def read_genome_file(fas_file): """ read genome file in fasta and return the list of chromosomes/contigs @args fas_file: genome sequence in fasta file @type fas_file: str returns a list with contig_names and length """ # get the filehandler from input file try: fh = helper.open_file(fas_file) except Exception, errmsg: stop_err('error in reading file '+ errmsg) chrom_names = [] for rec in SeqIO.parse(fh, "fasta"): print "parsing contig %s details" % rec.id chrom_names.append((rec.id, len(rec.seq))) fh.close() # return the list with chromosome identifier and its sequence length return chrom_names """ based on eye inspection, the returned list can be trimmed and create a dictionary with the best chromosomes , something like: Take the list 0-15 chr_best = chrom_names[0:15] change to dict chr_best = dict(chr_best) and finally this dictionary can be passed to the genome cleaning function - clean_genome_file """ def clean_genome_file(chr_names, fas_file, fas_out): """ make a stable genome file with valid contigs @args chr_names: different contig names with a valid genome sequence @type chr_names: dict @args fas_file: genome sequence in fasta file @type fas_file: str @args fas_out: new genome sequence file in fasta format @type fas_out: str """ # get the filehandler from input file try: fh = helper.open_file(fas_file) except Exception, errmsg: stop_err('error in reading file '+ errmsg) # check the out filehandler try: outfh = open(fas_out, "w") except Exception, errmsg: stop_err('error in writing file '+ errmsg) # writing stable contig genome sequence in FASTA format for rec in SeqIO.parse(fh, "fasta"): if rec.id in chr_names: outfh.write(rec.format("fasta")) print "writing the contig %s details" % rec.id fh.close() outfh.close() def genome_file_rec_extract(chr_pattn, fas_file, fas_out): """ get all contings based on a matiching string in the record identifier @args chr_pattn: pattern to be searched in contig names @type chr_pattn: str @args fas_file: genome sequence in fasta file @type fas_file: str @args fas_out: new genome sequence file in fasta format @type fas_out: str """ # get the filehandler from input file try: fh = helper.open_file(fas_file) except Exception, errmsg: stop_err('error in reading file '+ errmsg) # check the out filehandler try: outfh = open(fas_out, "w") except Exception, errmsg: stop_err('error in writing file '+ errmsg) # writing stable contig genome sequence in FASTA format for rec in SeqIO.parse(fh, "fasta"): if re.search(chr_pattn, rec.id): outfh.write(rec.format("fasta")) print "writing the contig %s details" % rec.id fh.close() outfh.close() def make_anno_db(gff_file): """ extract the features from a gtf/gff file and store efficiently to query @args gff_file: genome annotation file @type gff_file: str """ gff_cont = GFFParser.Parse(gff_file) intron_size = dict() exon_size = dict() for rec in gff_cont: for idx, tid in enumerate(rec['transcripts']): if not rec['exons'][idx].any(): continue try: # (Pdb) rec['exons'][0] -> array(nan) import numpy as np if np.isnan(rec['exons'][idx]): continue except: pass try: exon_cnt = len(rec['exons'][idx]) except: continue if exon_cnt > 1: intron_start = 0 for xq, excod in enumerate(rec['exons'][idx]): if xq > 0: #print intron_start, excod[0]-1 if excod[0]-intron_start==1: intron_start = excod[1]+1 exon_size[intron_start-excod[0]] = 1 continue intron_size[excod[0]-intron_start] = 1 #print excod[0]-intron_start intron_start = excod[1]+1 exon_size[intron_start-excod[0]] = 1 #print intron_start-excod[0] feat_db = dict() if intron_size: keys_int = sorted(intron_size) keys_ex = sorted(exon_size) #print 'MaxIntronLength %d %d %d' %(keys_int[-1], keys_int[-2], keys_int[-3]) feat_db['min_intron'] = int(keys_int[0]) feat_db['max_intron'] = int(keys_int[-3]) feat_db['min_exon'] = int(keys_ex[0]) feat_db['max_exon'] = int(keys_ex[-3]) #print 'MaxExonLength %d %d %d' %(keys_ex[-1], keys_ex[-2], keys_ex[-3]) return feat_db else: print "Error in feature mapping in file %s, please check the source of parent child features" % gff_file sys.exit(-1) def create_star_genome_index(fasta_file, out_dir, genome_anno=None, num_workers=1, onematelength=100): """ Creating STAR genome index with or without using genome annotation @args fasta_file: reference genome sequence file .fasta format @type fasta_file: str @args out_dir: genome index binary file storage place @type out_dir: str @args genome_anno: genome annotation file (optional) @type genome_anno: str @args num_workers: number of threads to run (default value = 1) @type num_workers: int @args onematelength: One Mate Length (default value=100) @type onematelength: int """ try: subprocess.call(["STAR"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) except: exit("Please make sure that the `STAR` binary is in your $PATH") file_prefx, ext = os.path.splitext(fasta_file) if ext in [".bz2", ".gz", ".lzma"]: ## checking for the compressed form of the file extension exit("error: STAR - Generating genome indexes - recommended to use the uncompressed FASTA file %s." % fasta_file) if not genome_anno: cli_cmd = 'STAR \ --runMode genomeGenerate \ --genomeDir %s \ --genomeFastaFiles %s \ --runThreadN %d' % (out_dir, fasta_file, num_workers) else: file_prefx, ext = os.path.splitext(genome_anno) if ext in [".bz2", ".gz", ".lzma"]: exit("error: STAR - Generating genome indexes - recommended to use the uncompressed GTF/GFF file %s." % genome_anno) ## check for the file type gff_hand = helper.open_file(genome_anno) for rec in gff_hand: rec = rec.strip('\n\r') # skip empty line fasta identifier and commented line if not rec or rec[0] in ['#', '>']: continue # skip the genome sequence if not re.search('\t', rec): continue parts = rec.split('\t') assert len(parts) >= 8, rec ftype, tags = GFFParser.attribute_tags(parts[-1]) break gff_hand.close() ## according to the file type if ftype: cli_cmd = 'STAR \ --runMode genomeGenerate \ --genomeDir %s \ --genomeFastaFiles %s \ --runThreadN %d \ --sjdbGTFfile %s \ --sjdbGTFtagExonParentTranscript Parent \ --sjdbOverhang %d' % (out_dir, fasta_file, num_workers, genome_anno, onematelength) else: cli_cmd = 'STAR \ --runMode genomeGenerate \ --genomeDir %s \ --genomeFastaFiles %s \ --runThreadN %d \ --sjdbGTFfile %s \ --sjdbGTFfeatureExon exon \ --sjdbOverhang %d' % (out_dir, fasta_file, num_workers, genome_anno, onematelength) ## create downloadpath if doesnot exists if not os.path.exists(out_dir): try: os.makedirs(out_dir) except OSError: exit("error: cannot create the directory %s." % out_dir) else:## if present any other old index files clean up the folder for the_file in os.listdir(out_dir): file_path = os.path.join(out_dir, the_file) try: if os.path.isfile(file_path): os.unlink(file_path) elif os.path.isdir(file_path): shutil.rmtree(file_path) except Exception, e: print(e) ## start the indexing job sys.stdout.write('\trunning program as: %s \n' % cli_cmd) try: ## changing the working dir to run STAR os.chdir(out_dir) ## Run command. process = subprocess.Popen(cli_cmd, shell=True) returncode = process.wait() ## Error checking. if returncode != 0: raise Exception, "return code = %i" % returncode print("\nGenome index files are stored at %s\n" % out_dir) except Exception, e: exit('Error running STAR.\n%s' % str( e )) def parse_list(line, nb_elts): """ specific to BWA-MEM stderr format """ return map(lambda x: int(float(x)), ' '.join(line.strip().replace(',','').split()[-nb_elts:])[1:-1].split()) def calculate_insert_size_fastq(ref_genome, fastq_dir, fq_files): """ calculate the library insert size from raw read files and reference genome sequence @args ref_genome: genome sequence file @type ref_genome: str @args fastq_dir: fastq directory for the experiment @type fastq_dir: str @args fq_files: fastq file names in python list @type fq_files: list """ try: subprocess.call(["bwa"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) except: exit("Please make sure that the `bwa` binary is in your $PATH") ## check for the bwa index if not os.path.isfile("%s.sa" % ref_genome): try: cmd_idx = "bwa index %s" % ref_genome sys.stdout.write("bwa indexing starting...\n") process = subprocess.Popen(cmd_idx, shell=True) returncode = process.wait() if returncode !=0: raise Exception, "Exit status return code = %i" % returncode sys.stdout.write("bwa indexing finished\n") except Exception, e: exit('Error running bwa index.\n%s' % str( e )) ##adapted from: ##Quickly estimates insert sizes of read datasets, given some sequence(s) they can be mapped to. ##Author: Rayan Chikhi ##example: ## estimate-insert-sizes contigs.fa readsA_1.fq readsA_2.fq readsB_1.fq readsB_2.fq if len(fq_files) > 1: nb_cpu = 1 zip_type = {".gz" : "gzip -c", ".bz2" : "bzip2 -d -c"} file_prefx, ext = os.path.splitext(fq_files[0]) stats = dict() read1 = "%s/%s" % (fastq_dir, fq_files[0]) read2 = "%s/%s" % (fastq_dir, fq_files[1]) print("processing : \n %s \n %s " % (read1, read2)) cmd = ["bwa", "mem"] + ["-t %d" % nb_cpu, ref_genome] + ["<(%s %s)" % (zip_type[ext], read1)] \ +["<(%s %s)" % ( zip_type[ext], read2)] DEVNULL = open(os.devnull, 'wb') process = subprocess.Popen(cmd, stdout=DEVNULL, stderr=subprocess.PIPE) seen_candidate_line = False while True: line = process.stderr.readline() if line == '' and process.poll() != None: break if "worker" in line: break if "pestat" not in line: continue if "candidate unique pairs for" in line: if seen_candidate_line: break seen_candidate_line = True nb_pairs = parse_list(line,4) for i in xrange(4): stats[['FF', 'FR', 'RF', 'RR'][i]] = { 'nb_pairs' : nb_pairs[i] } if "orientation" in line: orientation = line.strip().split()[-1].replace('.','') if "mem_pestat] mean and std.dev:" in line: mean, stdev = parse_list(line,2) stats[orientation]['mean'] = mean stats[orientation]['stdev'] = stdev if orientation == 'RR': # stats are complete break sys.stdout.write(line) sys.stdout.flush() if process.poll() is None: process.terminate() results = sorted(stats.items(), key = lambda x: x[1]['nb_pairs'], reverse=True) most_likely = results[0] mean = most_likely[1]['mean'] stdev = most_likely[1]['stdev'] print "Orientation", most_likely[0], "mean", mean, "stdev", stdev if __name__=="__main__": print __doc__	vipints/genomeutils	fetch_remote_data/prepare_data.py	Python	bsd-3-clause	15,195	[ "BWA", "Biopython" ]	51ac0fb0ed692f6e7fc0ae882fe9ff6e7492eecc5430ad614efcb9e0429469fe
#!/usr/bin/env python # -- coding: utf-8 -- # # shapes.py # # Copyright 2015 Carlos Eduardo Sequeiros Borja <casebor@gmail.com> # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, # MA 02110-1301, USA. # # import math from optparse import OptionParser """ ############################################################################## # # # This script increment the X position of an Atom a determined quantity # # # ############################################################################## """ def amberAtomType(atom): '''amberAtoms = ('H', 'HC', 'HO', 'HS', 'HW', 'H2', 'H3', 'C', 'CA', 'CB', 'CC', 'CK', 'CM', 'CN',\ 'CQ', 'CR', 'CT', 'CV', 'CW', 'C', 'CD', 'CE', 'CF', 'CG', 'CH', 'CI', 'CJ', 'CP', 'C2', 'C3',\ 'N', 'NA', 'NB', 'NC', 'NT', 'N2', 'N3', 'N', 'O', 'OH', 'OS', 'OW', 'O2', 'S', 'SH', 'P',\ 'CU', 'C0', 'I', 'IM', 'MG', 'QC', 'QK', 'QL', 'QN', 'QR', 'LP')''' amberAtoms = {'C', 'O', 'N', 'S', 'P', 'MG', 'F', 'Ar', 'CL', 'NA', 'H', 'BR', 'CA', 'ZN'} return atom in amberAtoms def isANearB(elemA, aX, aY, aZ, radA, cadPdb): resp = False cads = cadPdb.split('\n') i = 0 while i<len(cads) and not resp: if elemA in cads[i]: cadsA = cads[i].split() x = float(cadsA[5]) y = float(cadsA[6]) z = float(cadsA[7]) distAB = ((aX-x)2 + (aY-y)2 + (aZ-z)2)0.5 if distAB<radA: resp = True i += 1 return resp def complexOK(): if len(options.complexF)<7: return False else: elems = options.complexF.split('-') if len(elems)<>4: parse.error('Option complex must have 4 elements, and they must be valid Amber ATOMS!!!') quit() else: for i in elems: if not amberAtomType(i): parse.error('Option complex must have 4 elements, and they must be valid Amber ATOMS!!!') quit() return True def add_tapa(): global AT_POS cad = '' i = -3.6 temp = int(options.Ri/3.6) #AT_POS = 1 cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, 0.0, 0.0) AT_POS += 1 for t in range(1, temp+1): rad = 3.6 * t perim = 2math.pirad razon = perim/(int(perim/3.6)) ang = razon/rad temp = razon/rad while temp <= (2math.pi)+0.1: j = radmath.cos(temp) k = radmath.sin(temp) cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 temp += ang return cad def main(): global AT_POS AT_POS = 1 cad = add_tapa() dAtAt = 3.55 dAtAt2 = 3.55 cont = 1 i = 0.0 arco = 3.6 if options.shapeS.upper() == 'CONE': while (i<options.TxC): perim = 2math.pioptions.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang <= (2math.pi)+0.1: j = options.Rimath.cos(ang) k = options.Rimath.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 if cont%3 == 0: dAtAt2 -= 0.2 cont += 1 i += dAtAt2 options.Ri = options.Ri+1.3math.log10(options.Ri)2 elif options.shapeS.upper() == 'TUBE': while (i<options.TxT): perim = 2math.pioptions.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang < (2math.pi)+0.1: j = options.Rimath.cos(ang) k = options.Rimath.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 i += dAtAt elif options.shapeS.upper() == 'FUNNEL' and not complexOK(): while (i<options.TxT+options.TxC): if i<=options.TxT: perim = 2math.pioptions.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang < (2math.pi)+0.1: j = options.Rimath.cos(ang) k = options.Rimath.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 else: perim = 2math.pioptions.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang <= (2math.pi)+0.1: j = options.Rimath.cos(ang) k = options.Rimath.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 options.Ri += 1.3math.log10(options.Ri)2 i += dAtAt elif options.shapeS.upper() == 'FUNNEL' and complexOK(): elems = options.complexF.split('-') elem1 = elems[0] elem2 = elems[1] elem3 = elems[2] elem4 = elems[3] while (i<options.TxT+options.TxC): if i<=options.TxT: perim = 2math.pioptions.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang < (2math.pi)+0.1: j = options.Rimath.cos(ang) k = options.Rimath.sin(ang) ang += temp if not isANearB(elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem2, elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem1, elem1, AT_POS, i, j, k) AT_POS += 1 else: perim = 2math.pioptions.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang <= (2math.pi)+0.1: j = options.Rimath.cos(ang) k = options.Rimath.sin(ang) ang += temp if not isANearB(elem4, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem4, elem4, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem3, elem3, AT_POS, i, j, k) AT_POS += 1 #options.Ri += 1.3math.log10(options.Ri)**2 dAtAt -= 0.2 options.Ri += 3.6 i += dAtAt else: print 'Error in shape type' parser.print_help() quit() if len(options.outFile) > 0: arch = open(options.outFile, 'w') else: if not complexOK(): if len(options.elem2)>0: outF = options.shapeS + '-' + options.elem + '-' + options.elem2 + '.pdb' else: outF = options.shapeS + '-' + options.elem + '.pdb' else: elems = options.complexF.split('-') outF = options.shapeS + '-' + elems[0] + '-' + elems[1] + '-' + elems[2] + '-' + elems[3] + '.pdb' arch = open(outF, 'w') arch.write(cad) arch.close() return 0 if __name__ == '__main__': usage = 'usage: \"%prog [options] args\" or \"%prog\"' parser = OptionParser(usage) parser.add_option('-o', '--out', action='store', type='string', dest='outFile', help='Defines the name of the output pdb file. Default is the SHAPE+_+ELEMENT+.pdb', default='') parser.add_option('-w', '--with', action='store', type='string', dest='elem2', help='Use this option to add other ATOM in your shape in regular intervals. You can change the interval with -i or --interval', default='') parser.add_option('-s', '--shape', action='store', type='string', dest='shapeS', help='Defines the shape of the object to be created. Values admitted are CONE, TUBE or FUNNEL. Default is CONE', default='CONE') parser.add_option('-r', '--radius', action='store', type='float', dest='Ri', help='This option set the radius of the desired shape in ANGSTROMS. Default is 10.0 A', default='10.0') parser.add_option('-e', '--element', action='store', type='string', dest='elem', help='Is the element used to make the structure', default='Ar') parser.add_option('-c', '--complex', action='store', type='string', dest='complexF', help='Use this option ONLY if you want to make your FUNNEL with different elements on the TUBE part than those in the CONE part. The syntax is: elem1TUBE-elem2TUBE-elem1CONE-elem2CONE, note that you need to use the \'-\' between elements. You can change the interval with -i or --interval', default='') parser.add_option('-d', '--distcone', action='store', type='float', dest='TxC', help='If you have chosen the cone shape, this option set the HEIGHT of the cone in ANGSTROMS; if you have chosen the funnel shape, this set the HEIGHT part of the funnel. Default is 40.0 A', default='40.0') parser.add_option('-i', '--interval', action='store', type='float', dest='interval', help='Set the interval for the addition of other ATOMS. Default 6.0A. Use this option only if you use -w, --with, -c or --complex!!!', default='6.0') parser.add_option('-l', '--disttunnel', action='store', type='float', dest='TxT', help='If you have chosen the tunnel shape, this option ser the LENGTH of the tunnel in ANGSTROMS; if you have chosen the funnel shape, this set the LENGTH of the tunnel part of the funnel. Default is 40.0 A', default='40.0') (options, args) = parser.parse_args() if (options.TxT<0) or (options.TxC<0) or (options.Ri<0): parser.error('Options -l, -d and -r must be positive or 0!!!') exit if not amberAtomType(options.elem): parse.error('Option element must be a valid Amber ATOM!!!') quit() if len(options.elem2)>0 and not amberAtomType(options.elem2): parse.error('Option with must be a valid Amber ATOM!!!') quit() main()	casebor/labioscripts	python/shapes_tapa.py	Python	gpl-3.0	10,847	[ "Amber" ]	f3b28716bd3e807e6b0d3a1084800076584283a0c67b59e0db19a9887eebf09f
# -- coding: utf-8 -- """Tests for :mod:`pybel.manager`."""	pybel/pybel	tests/test_manager/__init__.py	Python	mit	63	[ "Pybel" ]	c559c00364647dcb3fce6dde582359d525e79dc9e80c70d172fb19aedbf0b35a
######################################################################## # $Id$ ######################################################################## """ FileManagerBase is a base class for all the specific File Managers """ __RCSID__ = "$Id$" from DIRAC import S_OK, S_ERROR, gLogger from DIRAC.Core.Utilities.List import intListToString from DIRAC.Core.Utilities.Pfn import pfnparse, pfnunparse import os import stat class FileManagerBase( object ): def __init__( self, database = None ): self.db = database self.statusDict = {} def _getConnection( self, connection ): if connection: return connection res = self.db._getConnection() if res['OK']: return res['Value'] gLogger.warn( "Failed to get MySQL connection", res['Message'] ) return connection def setDatabase( self, database ): self.db = database def getFileCounters( self, connection = False ): """ Get a number of counters to verify the sanity of the Files in the catalog """ connection = self._getConnection( connection ) resultDict = {} req = "SELECT COUNT() FROM FC_Files;" res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Files'] = res['Value'][0][0] req = "SELECT COUNT(FileID) FROM FC_Files WHERE FileID NOT IN ( SELECT FileID FROM FC_Replicas )" res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Files w/o Replicas'] = res['Value'][0][0] req = "SELECT COUNT(RepID) FROM FC_Replicas WHERE FileID NOT IN ( SELECT FileID FROM FC_Files )" res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Replicas w/o Files'] = res['Value'][0][0] treeTable = self.db.dtree.getTreeTable() req = "SELECT COUNT(FileID) FROM FC_Files WHERE DirID NOT IN ( SELECT DirID FROM %s)" % treeTable res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Orphan Files'] = res['Value'][0][0] req = "SELECT COUNT(FileID) FROM FC_Files WHERE FileID NOT IN ( SELECT FileID FROM FC_FileInfo)" res = self.db._query( req, connection ) if not res['OK']: resultDict['Files w/o FileInfo'] = 0 else: resultDict['Files w/o FileInfo'] = res['Value'][0][0] req = "SELECT COUNT(FileID) FROM FC_FileInfo WHERE FileID NOT IN ( SELECT FileID FROM FC_Files)" res = self.db._query( req, connection ) if not res['OK']: resultDict['FileInfo w/o Files'] = 0 else: resultDict['FileInfo w/o Files'] = res['Value'][0][0] return S_OK( resultDict ) def getReplicaCounters( self, connection = False ): """ Get a number of counters to verify the sanity of the Replicas in the catalog """ connection = self._getConnection( connection ) req = "SELECT COUNT() FROM FC_Replicas;" res = self.db._query( req, connection ) if not res['OK']: return res return S_OK( {'Replicas':res['Value'][0][0]} ) ###################################################### # # File write methods # def _insertFiles( self, lfns, uid, gid, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _deleteFiles( self, toPurge, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _insertReplicas( self, lfns, master = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _findFiles( self, lfns, metadata = ["FileID"], allStatus = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getFileReplicas( self, fileIDs, fields_input = ['PFN'], allStatus = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getFileIDFromGUID( self, guid, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def getLFNForGUID( self, guids, connection = False ): """Returns the LFN matching a given GUID """ return S_ERROR( "To be implemented on derived class" ) def _setFileParameter( self, fileID, paramName, paramValue, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _deleteReplicas( self, lfns, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _setReplicaStatus( self, fileID, se, status, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _setReplicaHost( self, fileID, se, newSE, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getDirectoryFiles( self, dirID, fileNames, metadata, allStatus = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getDirectoryFileIDs( self, dirID, requestString = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _findFileIDs( self, lfns, connection=False ): """ To be implemented on derived class Should return following the successful/failed convention Successful is a dictionary with keys the lfn, and values the FileID""" return S_ERROR( "To be implemented on derived class" ) def _getDirectoryReplicas( self, dirID, allStatus = False, connection = False ): """ To be implemented on derived class Should return with only one value, being a list of all the replicas (FileName,FileID,SEID,PFN) """ return S_ERROR( "To be implemented on derived class" ) def countFilesInDir( self, dirId ): """ Count how many files there is in a given Directory :param dirID : directory id :returns S_OK(value) or S_ERROR """ return S_ERROR( "To be implemented on derived class" ) def _getFileLFNs(self,fileIDs): """ Get the file LFNs for a given list of file IDs """ stringIDs = intListToString(fileIDs) treeTable = self.db.dtree.getTreeTable() req = "SELECT F.FileID, CONCAT(D.DirName,'/',F.FileName) from FC_Files as F, %s as D WHERE F.FileID IN ( %s ) AND F.DirID=D.DirID" % (treeTable,stringIDs) result = self.db._query(req) if not result['OK']: return result fileNameDict = {} for row in result['Value']: fileNameDict[row[0]] = row[1] failed = {} successful = fileNameDict if len(fileNameDict) != len(fileIDs): for id_ in fileIDs: if not id_ in fileNameDict: failed[id_] = "File ID not found" return S_OK({'Successful':successful,'Failed':failed}) def addFile( self, lfns, credDict, connection = False ): """ Add files to the catalog :param lfns : dict { lfn : info}. 'info' is a dict containing PFN, SE, Size and Checksum the SE parameter can be a list if we have several replicas to register """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['PFN', 'SE', 'Size', 'Checksum'] ) if not res['OK']: failed[lfn] = res['Message'] lfns.pop( lfn ) res = self._addFiles( lfns, credDict, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: failed.update( res['Value']['Failed'] ) successful.update( res['Value']['Successful'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def _addFiles( self, lfns, credDict, connection = False ): """ Main file adding method """ connection = self._getConnection( connection ) successful = {} result = self.db.ugManager.getUserAndGroupID( credDict ) if not result['OK']: return result uid, gid = result['Value'] # prepare lfns with master replicas - the first in the list or a unique replica masterLfns = {} extraLfns = {} for lfn in lfns: masterLfns[lfn] = dict( lfns[lfn] ) if isinstance( lfns[lfn].get( 'SE' ), list ): masterLfns[lfn]['SE'] = lfns[lfn]['SE'][0] if len( lfns[lfn]['SE'] ) > 1: extraLfns[lfn] = dict( lfns[lfn] ) extraLfns[lfn]['SE'] = lfns[lfn]['SE'][1:] # Check whether the supplied files have been registered already existingMetadata, failed = self._getExistingMetadata( masterLfns.keys(), connection = connection ) if existingMetadata: success, fail = self._checkExistingMetadata( existingMetadata, masterLfns ) successful.update( success ) failed.update( fail ) for lfn in ( success.keys() + fail.keys() ): masterLfns.pop( lfn ) # If GUIDs are supposed to be unique check their pre-existance if self.db.uniqueGUID: fail = self._checkUniqueGUID( masterLfns, connection = connection ) failed.update( fail ) for lfn in fail: masterLfns.pop( lfn ) # If we have files left to register if masterLfns: # Create the directories for the supplied files and store their IDs directories = self._getFileDirectories( masterLfns.keys() ) for directory, fileNames in directories.items(): res = self.db.dtree.makeDirectories( directory, credDict ) if not res['OK']: for fileName in fileNames: lfn = os.path.join( directory, fileName ) failed[lfn] = res['Message'] masterLfns.pop( lfn ) continue for fileName in fileNames: if not fileName: failed[directory] = "Is no a valid file" masterLfns.pop( directory ) continue lfn = "%s/%s" % ( directory, fileName ) lfn = lfn.replace( '//', '/' ) # This condition should never be true, we would not be here otherwise... if not res['OK']: failed[lfn] = "Failed to create directory for file" masterLfns.pop( lfn ) else: masterLfns[lfn]['DirID'] = res['Value'] # If we still have files left to register if masterLfns: res = self._insertFiles( masterLfns, uid, gid, connection = connection ) if not res['OK']: for lfn in masterLfns.keys(): failed[lfn] = res['Message'] masterLfns.pop( lfn ) else: for lfn, error in res['Value']['Failed'].items(): failed[lfn] = error masterLfns.pop( lfn ) masterLfns = res['Value']['Successful'] # Add the ancestors if masterLfns: res = self._populateFileAncestors( masterLfns, connection = connection ) toPurge = [] if not res['OK']: for lfn in masterLfns.keys(): failed[lfn] = "Failed while registering ancestors" toPurge.append( masterLfns[lfn]['FileID'] ) else: failed.update( res['Value']['Failed'] ) for lfn, error in res['Value']['Failed'].items(): toPurge.append( masterLfns[lfn]['FileID'] ) if toPurge: self._deleteFiles( toPurge, connection = connection ) # Register the replicas newlyRegistered = {} if masterLfns: res = self._insertReplicas( masterLfns, master = True, connection = connection ) toPurge = [] if not res['OK']: for lfn in masterLfns.keys(): failed[lfn] = "Failed while registering replica" toPurge.append( masterLfns[lfn]['FileID'] ) else: newlyRegistered = res['Value']['Successful'] successful.update( newlyRegistered ) failed.update( res['Value']['Failed'] ) for lfn, error in res['Value']['Failed'].items(): toPurge.append( masterLfns[lfn]['FileID'] ) if toPurge: self._deleteFiles( toPurge, connection = connection ) # Add extra replicas for successfully registered LFNs for lfn in extraLfns.keys(): if not lfn in successful: extraLfns.pop( lfn ) if extraLfns: res = self._findFiles( extraLfns.keys(), ['FileID','DirID'], connection=connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = 'Failed while registering extra replicas' successful.pop( lfn ) extraLfns.pop( lfn ) else: failed.update(res['Value']['Failed']) for lfn in res['Value']['Failed'].keys(): successful.pop(lfn) extraLfns.pop( lfn ) for lfn,fileDict in res['Value']['Successful'].items(): extraLfns[lfn]['FileID'] = fileDict['FileID'] extraLfns[lfn]['DirID'] = fileDict['DirID'] if extraLfns: res = self._insertReplicas( extraLfns, master = False, connection = connection ) if not res['OK']: for lfn in extraLfns.keys(): failed[lfn] = "Failed while registering extra replicas" successful.pop( lfn ) else: newlyRegistered = res['Value']['Successful'] successful.update( newlyRegistered ) failed.update( res['Value']['Failed'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def _updateDirectoryUsage( self, directorySEDict, change, connection = False ): connection = self._getConnection( connection ) for directoryID in directorySEDict.keys(): result = self.db.dtree.getPathIDsByID( directoryID ) if not result['OK']: return result parentIDs = result['Value'] dirDict = directorySEDict[directoryID] for seID in dirDict.keys() : seDict = dirDict[seID] files = seDict['Files'] size = seDict['Size'] insertTuples = [] for dirID in parentIDs: insertTuples.append( '(%d,%d,%d,%d,UTC_TIMESTAMP())' % ( dirID, seID, size, files ) ) req = "INSERT INTO FC_DirectoryUsage (DirID,SEID,SESize,SEFiles,LastUpdate) " req += "VALUES %s" % ','.join( insertTuples ) req += " ON DUPLICATE KEY UPDATE SESize=SESize%s%d, SEFiles=SEFiles%s%d, LastUpdate=UTC_TIMESTAMP() " \ % ( change, size, change, files ) res = self.db._update( req ) if not res['OK']: gLogger.warn( "Failed to update FC_DirectoryUsage", res['Message'] ) return S_OK() def _populateFileAncestors( self, lfns, connection = False ): connection = self._getConnection( connection ) successful = {} failed = {} for lfn, lfnDict in lfns.items(): originalFileID = lfnDict['FileID'] originalDepth = lfnDict.get( 'AncestorDepth', 1 ) ancestors = lfnDict.get( 'Ancestors', [] ) if type( ancestors ) == type( ' ' ): ancestors = [ancestors] if lfn in ancestors: ancestors.remove( lfn ) if not ancestors: successful[lfn] = True continue res = self._findFiles( ancestors, connection = connection ) if res['Value']['Failed']: failed[lfn] = "Failed to resolve ancestor files" continue ancestorIDs = res['Value']['Successful'] fileIDLFNs = {} toInsert = {} for ancestor in ancestorIDs.keys(): fileIDLFNs[ancestorIDs[ancestor]['FileID']] = ancestor toInsert[ancestorIDs[ancestor]['FileID']] = originalDepth res = self._getFileAncestors( fileIDLFNs.keys() ) if not res['OK']: failed[lfn] = "Failed to obtain all ancestors" continue fileIDAncestorDict = res['Value'] for fileIDDict in fileIDAncestorDict.values(): for ancestorID, relativeDepth in fileIDDict.items(): toInsert[ancestorID] = relativeDepth + originalDepth res = self._insertFileAncestors( originalFileID, toInsert, connection = connection ) if not res['OK']: if "Duplicate" in res['Message']: failed[lfn] = "Failed to insert ancestor files: duplicate entry" else: failed[lfn] = "Failed to insert ancestor files" else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def _insertFileAncestors( self, fileID, ancestorDict, connection = False ): connection = self._getConnection( connection ) ancestorTuples = [] for ancestorID, depth in ancestorDict.items(): ancestorTuples.append( "(%d,%d,%d)" % ( fileID, ancestorID, depth ) ) if not ancestorTuples: return S_OK() req = "INSERT INTO FC_FileAncestors (FileID, AncestorID, AncestorDepth) VALUES %s" \ % intListToString( ancestorTuples ) return self.db._update( req, connection ) def _getFileAncestors( self, fileIDs, depths = [], connection = False ): connection = self._getConnection( connection ) req = "SELECT FileID, AncestorID, AncestorDepth FROM FC_FileAncestors WHERE FileID IN (%s)" \ % intListToString( fileIDs ) if depths: req = "%s AND AncestorDepth IN (%s);" % ( req, intListToString( depths ) ) res = self.db._query( req, connection ) if not res['OK']: return res fileIDAncestors = {} for fileID, ancestorID, depth in res['Value']: if not fileIDAncestors.has_key( fileID ): fileIDAncestors[fileID] = {} fileIDAncestors[fileID][ancestorID] = depth return S_OK( fileIDAncestors ) def _getFileDescendents( self, fileIDs, depths, connection = False ): connection = self._getConnection( connection ) req = "SELECT AncestorID, FileID, AncestorDepth FROM FC_FileAncestors WHERE AncestorID IN (%s)" \ % intListToString( fileIDs ) if depths: req = "%s AND AncestorDepth IN (%s);" % ( req, intListToString( depths ) ) res = self.db._query( req, connection ) if not res['OK']: return res fileIDAncestors = {} for ancestorID, fileID, depth in res['Value']: if not fileIDAncestors.has_key( ancestorID ): fileIDAncestors[ancestorID] = {} fileIDAncestors[ancestorID][fileID] = depth return S_OK( fileIDAncestors ) def addFileAncestors(self,lfns, connection = False ): """ Add file ancestors to the catalog """ connection = self._getConnection( connection ) failed = {} successful = {} result = self._findFiles( lfns.keys(), connection = connection ) if not result['OK']: return result if result['Value']['Failed']: failed.update(result['Value']['Failed']) for lfn in result['Value']['Failed']: lfns.pop(lfn) if not lfns: return S_OK({'Successful':successful,'Failed':failed}) for lfn in result['Value']['Successful']: lfns[lfn]['FileID'] = result['Value']['Successful'][lfn]['FileID'] result = self._populateFileAncestors(lfns, connection) if not result['OK']: return result failed.update(result['Value']['Failed']) successful = result['Value']['Successful'] return S_OK({'Successful':successful,'Failed':failed}) def _getFileRelatives( self, lfns, depths, relation, connection = False ): connection = self._getConnection( connection ) failed = {} successful = {} result = self._findFiles( lfns.keys(), connection = connection ) if not result['OK']: return result if result['Value']['Failed']: failed.update(result['Value']['Failed']) for lfn in result['Value']['Failed']: lfns.pop(lfn) if not lfns: return S_OK({'Successful':successful,'Failed':failed}) inputIDDict = {} for lfn in result['Value']['Successful']: inputIDDict[ result['Value']['Successful'][lfn]['FileID'] ] = lfn inputIDs = inputIDDict.keys() if relation == 'ancestor': result = self._getFileAncestors(inputIDs,depths, connection) else: result = self._getFileDescendents(inputIDs,depths, connection) if not result['OK']: return result failed = {} successful = {} relDict = result['Value'] for id_ in inputIDs: if id_ in relDict: aList = relDict[id_].keys() result = self._getFileLFNs(aList) if not result['OK']: failed[inputIDDict[id]] = "Failed to find %s" % relation else: if result['Value']['Successful']: resDict = {} for aID in result['Value']['Successful']: resDict[ result['Value']['Successful'][aID] ] = relDict[id_][aID] successful[inputIDDict[id_]] = resDict for aID in result['Value']['Failed']: failed[inputIDDict[id_]] = "Failed to get the ancestor LFN" else: successful[inputIDDict[id_]] = {} return S_OK({'Successful':successful,'Failed':failed}) def getFileAncestors( self, lfns, depths, connection = False ): return self._getFileRelatives(lfns, depths, 'ancestor', connection) def getFileDescendents( self, lfns, depths, connection = False ): return self._getFileRelatives(lfns, depths, 'descendent', connection) def _getExistingMetadata( self, lfns, connection = False ): connection = self._getConnection( connection ) # Check whether the files already exist before adding res = self._findFiles( lfns, ['FileID', 'Size', 'Checksum', 'GUID'], connection = connection ) successful = res['Value']['Successful'] failed = res['Value']['Failed'] for lfn, error in res['Value']['Failed'].items(): if error == 'No such file or directory': failed.pop( lfn ) return successful, failed def _checkExistingMetadata( self, existingLfns, lfns ): failed = {} successful = {} fileIDLFNs = {} for lfn, fileDict in existingLfns.items(): fileIDLFNs[fileDict['FileID']] = lfn # For those that exist get the replicas to determine whether they are already registered res = self._getFileReplicas( fileIDLFNs.keys() ) if not res['OK']: for lfn in fileIDLFNs.values(): failed[lfn] = 'Failed checking pre-existing replicas' else: replicaDict = res['Value'] for fileID, lfn in fileIDLFNs.items(): fileMetadata = existingLfns[lfn] existingGuid = fileMetadata['GUID'] existingSize = fileMetadata['Size'] existingChecksum = fileMetadata['Checksum'] newGuid = lfns[lfn]['GUID'] newSize = lfns[lfn]['Size'] newChecksum = lfns[lfn]['Checksum'] # Ensure that the key file metadata is the same if ( existingGuid != newGuid ) or \ ( existingSize != newSize ) or \ ( existingChecksum != newChecksum ): failed[lfn] = "File already registered with alternative metadata" # If the DB does not have replicas for this file return an error elif not fileID in replicaDict or not replicaDict[fileID]: failed[lfn] = "File already registered with no replicas" # If the supplied SE is not in the existing replicas return an error elif not lfns[lfn]['SE'] in replicaDict[fileID].keys(): failed[lfn] = "File already registered with alternative replicas" # If we get here the file being registered already exists exactly in the DB else: successful[lfn] = True return successful, failed def _checkUniqueGUID( self, lfns, connection = False ): connection = self._getConnection( connection ) guidLFNs = {} failed = {} for lfn, fileDict in lfns.items(): guidLFNs[fileDict['GUID']] = lfn res = self._getFileIDFromGUID( guidLFNs.keys(), connection = connection ) if not res['OK']: return dict.fromkeys( lfns, res['Message'] ) for guid, fileID in res['Value'].items(): failed[guidLFNs[guid]] = "GUID already registered for another file %s" % fileID # resolve this to LFN return failed def removeFile( self, lfns, connection = False ): connection = self._getConnection( connection ) """ Remove file from the catalog """ successful = {} failed = {} res = self._findFiles( lfns, ['DirID', 'FileID', 'Size'], connection = connection ) if not res['OK']: return res for lfn, error in res['Value']['Failed'].items(): if error == 'No such file or directory': successful[lfn] = True else: failed[lfn] = error fileIDLfns = {} lfns = res['Value']['Successful'] for lfn, lfnDict in lfns.items(): fileIDLfns[lfnDict['FileID']] = lfn res = self._computeStorageUsageOnRemoveFile( lfns, connection = connection ) if not res['OK']: return res directorySESizeDict = res['Value'] # Now do removal res = self._deleteFiles( fileIDLfns.keys(), connection = connection ) if not res['OK']: for lfn in fileIDLfns.values(): failed[lfn] = res['Message'] else: # Update the directory usage self._updateDirectoryUsage( directorySESizeDict, '-', connection = connection ) for lfn in fileIDLfns.values(): successful[lfn] = True return S_OK( {"Successful":successful, "Failed":failed} ) def _computeStorageUsageOnRemoveFile( self, lfns, connection = False ): # Resolve the replicas to calculate reduction in storage usage fileIDLfns = {} for lfn, lfnDict in lfns.items(): fileIDLfns[lfnDict['FileID']] = lfn res = self._getFileReplicas( fileIDLfns.keys(), connection = connection ) if not res['OK']: return res directorySESizeDict = {} for fileID, seDict in res['Value'].items(): dirID = lfns[fileIDLfns[fileID]]['DirID'] size = lfns[fileIDLfns[fileID]]['Size'] directorySESizeDict.setdefault( dirID, {} ) directorySESizeDict[dirID].setdefault( 0, {'Files':0,'Size':0} ) directorySESizeDict[dirID][0]['Size'] += size directorySESizeDict[dirID][0]['Files'] += 1 for seName in seDict.keys(): res = self.db.seManager.findSE( seName ) if not res['OK']: return res seID = res['Value'] size = lfns[fileIDLfns[fileID]]['Size'] directorySESizeDict[dirID].setdefault( seID, {'Files':0,'Size':0} ) directorySESizeDict[dirID][seID]['Size'] += size directorySESizeDict[dirID][seID]['Files'] += 1 return S_OK( directorySESizeDict ) def setFileStatus( self, lfns, connection = False ): """ Get set the group for the supplied files """ connection = self._getConnection( connection ) res = self._findFiles( lfns, ['FileID', 'UID'], connection = connection ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): status = lfns[lfn] if isinstance( status, basestring ): if not status in self.db.validFileStatus: failed[lfn] = 'Invalid file status %s' % status continue result = self._getStatusInt( status, connection = connection ) if not result['OK']: failed[lfn] = res['Message'] continue status = result['Value'] fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "Status", status, connection = connection ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) ###################################################### # # Replica write methods # def addReplica( self, lfns, connection = False ): """ Add replica to the catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['PFN', 'SE'] ) if not res['OK']: failed[lfn] = res['Message'] lfns.pop( lfn ) res = self._addReplicas( lfns, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: failed.update( res['Value']['Failed'] ) successful.update( res['Value']['Successful'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def _addReplicas( self, lfns, connection = False ): connection = self._getConnection( connection ) successful = {} res = self._findFiles( lfns.keys(), ['DirID', 'FileID', 'Size'], connection = connection ) if not res['OK']: return res failed = res['Value']['Failed'] for lfn in failed.keys(): lfns.pop( lfn ) lfnFileIDDict = res['Value']['Successful'] for lfn, fileDict in lfnFileIDDict.items(): lfns[lfn].update( fileDict ) res = self._insertReplicas( lfns, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: successful = res['Value']['Successful'] failed.update( res['Value']['Failed'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def removeReplica( self, lfns, connection = False ): """ Remove replica from catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['SE'] ) if not res['OK']: failed[lfn] = res['Message'] lfns.pop( lfn ) res = self._deleteReplicas( lfns, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: failed.update( res['Value']['Failed'] ) successful.update( res['Value']['Successful'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def setReplicaStatus( self, lfns, connection = False ): """ Set replica status in the catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['SE', 'Status'] ) if not res['OK']: failed[lfn] = res['Message'] continue status = info['Status'] se = info['SE'] res = self._findFiles( [lfn], ['FileID'], connection = connection ) if not res['Value']['Successful'].has_key( lfn ): failed[lfn] = res['Value']['Failed'][lfn] continue fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setReplicaStatus( fileID, se, status, connection = connection ) if res['OK']: successful[lfn] = res['Value'] else: failed[lfn] = res['Message'] return S_OK( {'Successful':successful, 'Failed':failed} ) def setReplicaHost( self, lfns, connection = False ): """ Set replica host in the catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['SE', 'NewSE'] ) if not res['OK']: failed[lfn] = res['Message'] continue newSE = info['NewSE'] se = info['SE'] res = self._findFiles( [lfn], ['FileID'], connection = connection ) if not res['Value']['Successful'].has_key( lfn ): failed[lfn] = res['Value']['Failed'][lfn] continue fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setReplicaHost( fileID, se, newSE, connection = connection ) if res['OK']: successful[lfn] = res['Value'] else: failed[lfn] = res['Message'] return S_OK( {'Successful':successful, 'Failed':failed} ) ###################################################### # # File read methods # def exists( self, lfns, connection = False ): """ Determine whether a file exists in the catalog """ connection = self._getConnection( connection ) res = self._findFiles( lfns, allStatus = True, connection = connection ) successful = res['Value']['Successful'] origFailed = res['Value']['Failed'] for lfn in successful: successful[lfn] = lfn failed = {} if self.db.uniqueGUID: guidList = [] val = None #Try to identify if the GUID is given # We consider only 2 options : # either {lfn : guid} # or P lfn : {PFN : .., GUID : ..} } if isinstance( lfns, dict ): val = lfns.values() # We have values, take the first to identify the type if val: val = val[0] if isinstance( val, dict ) and 'GUID' in val: # We are in the case {lfn : {PFN:.., GUID:..}} guidList = [lfns[lfn]['GUID'] for lfn in lfns] pass elif isinstance( val, basestring ): # We hope that it is the GUID which is given guidList = lfns.values() if guidList: # A dict { guid: lfn to which it is supposed to be associated } guidToGivenLfn = dict( zip( guidList, lfns ) ) res = self.getLFNForGUID( guidList, connection ) if not res['OK']: return res guidLfns = res['Value']['Successful'] for guid, realLfn in guidLfns.items(): successful[guidToGivenLfn[guid]] = realLfn for lfn, error in origFailed.items(): # It could be in successful because the guid exists with another lfn if lfn in successful: continue if error == 'No such file or directory': successful[lfn] = False else: failed[lfn] = error return S_OK( {"Successful":successful, "Failed":failed} ) def isFile( self, lfns, connection = False ): """ Determine whether a path is a file in the catalog """ connection = self._getConnection( connection ) #TO DO, should check whether it is a directory if it fails return self.exists( lfns, connection = connection ) def getFileSize( self, lfns, connection = False ): """ Get file size from the catalog """ connection = self._getConnection( connection ) #TO DO, should check whether it is a directory if it fails res = self._findFiles( lfns, ['Size'], connection = connection ) if not res['OK']: return res totalSize = 0 for lfn in res['Value']['Successful'].keys(): size = res['Value']['Successful'][lfn]['Size'] res['Value']['Successful'][lfn] = size totalSize += size res['TotalSize'] = totalSize return res def getFileMetadata( self, lfns, connection = False ): """ Get file metadata from the catalog """ connection = self._getConnection( connection ) #TO DO, should check whether it is a directory if it fails return self._findFiles( lfns, ['Size', 'Checksum', 'ChecksumType', 'UID', 'GID', 'GUID', 'CreationDate', 'ModificationDate', 'Mode', 'Status'], connection = connection ) def getPathPermissions( self, paths, credDict, connection = False ): """ Get the permissions for the supplied paths """ connection = self._getConnection( connection ) res = self.db.ugManager.getUserAndGroupID( credDict ) if not res['OK']: return res uid, gid = res['Value'] res = self._findFiles( paths, metadata = ['Mode', 'UID', 'GID'], connection = connection ) if not res['OK']: return res successful = {} for dirName, dirDict in res['Value']['Successful'].items(): mode = dirDict['Mode'] p_uid = dirDict['UID'] p_gid = dirDict['GID'] successful[dirName] = {} if p_uid == uid: successful[dirName]['Read'] = mode & stat.S_IRUSR successful[dirName]['Write'] = mode & stat.S_IWUSR successful[dirName]['Execute'] = mode & stat.S_IXUSR elif p_gid == gid: successful[dirName]['Read'] = mode & stat.S_IRGRP successful[dirName]['Write'] = mode & stat.S_IWGRP successful[dirName]['Execute'] = mode & stat.S_IXGRP else: successful[dirName]['Read'] = mode & stat.S_IROTH successful[dirName]['Write'] = mode & stat.S_IWOTH successful[dirName]['Execute'] = mode & stat.S_IXOTH return S_OK( {'Successful':successful, 'Failed':res['Value']['Failed']} ) ###################################################### # # Replica read methods # def __getReplicasForIDs( self, fileIDLfnDict, allStatus, connection = False ): """ Get replicas for files with already resolved IDs """ replicas = {} if fileIDLfnDict: fields = [] if not self.db.lfnPfnConvention or self.db.lfnPfnConvention == "Weak": fields = ['PFN'] res = self._getFileReplicas( fileIDLfnDict.keys(), fields_input=fields, allStatus = allStatus, connection = connection ) if not res['OK']: return res for fileID, seDict in res['Value'].items(): lfn = fileIDLfnDict[fileID] replicas[lfn] = {} for se, repDict in seDict.items(): pfn = repDict.get('PFN','') #if not pfn or self.db.lfnPfnConvention: # res = self._resolvePFN( lfn, se ) # if res['OK']: # pfn = res['Value'] replicas[lfn][se] = pfn result = S_OK( replicas ) return result def getReplicas( self, lfns, allStatus, connection = False ): """ Get file replicas from the catalog """ connection = self._getConnection( connection ) # Get FileID <-> LFN correspondence first res = self._findFileIDs( lfns, connection = connection ) if not res['OK']: return res failed = res['Value']['Failed'] fileIDLFNs = {} for lfn, fileID in res['Value']['Successful'].items(): fileIDLFNs[fileID] = lfn result = self.__getReplicasForIDs( fileIDLFNs, allStatus, connection) if not result['OK']: return result replicas = result['Value'] result = S_OK( { "Successful": replicas, 'Failed': failed } ) if self.db.lfnPfnConvention: sePrefixDict = {} resSE = self.db.seManager.getSEPrefixes() if resSE['OK']: sePrefixDict = resSE['Value'] result['Value']['SEPrefixes'] = sePrefixDict return result def getReplicasByMetadata( self, metaDict, path, allStatus, credDict, connection = False ): """ Get file replicas for files corresponding to the given metadata """ connection = self._getConnection( connection ) # Get FileID <-> LFN correspondence first failed = {} result = self.db.fmeta.findFilesByMetadata( metaDict, path, credDict, extra = True) if not result['OK']: return result fileIDLFNs = result['Value'] result = self.__getReplicasForIDs( fileIDLFNs, allStatus, connection) if not result['OK']: return result replicas = result['Value'] result = S_OK( { "Successful": replicas, 'Failed': failed } ) if self.db.lfnPfnConvention: sePrefixDict = {} resSE = self.db.seManager.getSEPrefixes() if resSE['OK']: sePrefixDict = resSE['Value'] result['Value']['SEPrefixes'] = sePrefixDict return result def _resolvePFN(self,lfn,se): resSE = self.db.seManager.getSEDefinition(se) if not resSE['OK']: return resSE pfnDict = dict(resSE['Value']['SEDict']) if "PFNPrefix" in pfnDict: return S_OK(pfnDict['PFNPrefix']+lfn) else: pfnDict['FileName'] = lfn return pfnunparse(pfnDict) def getReplicaStatus( self, lfns, connection = False ): """ Get replica status from the catalog """ connection = self._getConnection( connection ) res = self._findFiles( lfns, connection = connection ) failed = res['Value']['Failed'] fileIDLFNs = {} for lfn, fileDict in res['Value']['Successful'].items(): fileID = fileDict['FileID'] fileIDLFNs[fileID] = lfn successful = {} if fileIDLFNs: res = self._getFileReplicas( fileIDLFNs.keys(), allStatus = True, connection = connection ) if not res['OK']: return res for fileID, seDict in res['Value'].items(): lfn = fileIDLFNs[fileID] requestedSE = lfns[lfn] if not requestedSE: failed[lfn] = "Replica info not supplied" elif requestedSE not in seDict.keys(): failed[lfn] = "No replica at supplied site" else: successful[lfn] = seDict[requestedSE]['Status'] return S_OK( {'Successful':successful, 'Failed':failed} ) ###################################################### # # General usage methods # def _getStatusInt( self, status, connection = False ): connection = self._getConnection( connection ) req = "SELECT StatusID FROM FC_Statuses WHERE Status = '%s';" % status res = self.db._query( req, connection ) if not res['OK']: return res if res['Value']: return S_OK( res['Value'][0][0] ) req = "INSERT INTO FC_Statuses (Status) VALUES ('%s');" % status res = self.db._update( req, connection ) if not res['OK']: return res return S_OK( res['lastRowId'] ) def _getIntStatus(self,statusID,connection=False): if statusID in self.statusDict: return S_OK(self.statusDict[statusID]) connection = self._getConnection(connection) req = "SELECT StatusID,Status FROM FC_Statuses" res = self.db._query(req,connection) if not res['OK']: return res if res['Value']: for row in res['Value']: self.statusDict[int(row[0])] = row[1] if statusID in self.statusDict: return S_OK(self.statusDict[statusID]) return S_OK('Unknown') def getFileIDsInDirectory( self, dirID, requestString = False ): """ Get a list of IDs for all the files stored in given directories or their subdirectories :param mixt dirID: single directory ID or a list of directory IDs :param boolean requestString: if True return result as a SQL SELECT string :return: list of file IDs or SELECT string """ return self._getDirectoryFileIDs( dirID, requestString = requestString ) def getFilesInDirectory( self, dirID, verbose = False, connection = False ): connection = self._getConnection( connection ) files = {} res = self._getDirectoryFiles( dirID, [], ['FileID', 'Size', 'GUID', 'Checksum', 'ChecksumType', 'Type', 'UID', 'GID', 'CreationDate', 'ModificationDate', 'Mode', 'Status'], connection = connection ) if not res['OK']: return res if not res['Value']: return S_OK( files ) fileIDNames = {} for fileName, fileDict in res['Value'].items(): files[fileName] = {} files[fileName]['MetaData'] = fileDict fileIDNames[fileDict['FileID']] = fileName if verbose: result = self._getFileReplicas( fileIDNames.keys(), connection = connection ) if not result['OK']: return result for fileID, seDict in result['Value'].items(): fileName = fileIDNames[fileID] files[fileName]['Replicas'] = seDict return S_OK( files ) def getDirectoryReplicas( self, dirID, path, allStatus = False, connection = False ): """ Get the replicas for all the Files in the given Directory :param DirID : ID of the directory :param path : useless :param allStatus : whether all replicas and file status are considered If False, take the visibleFileStatus and visibleReplicaStatus values from the configuration """ connection = self._getConnection( connection ) result = self._getDirectoryReplicas( dirID, allStatus, connection) if not result['OK']: return result resultDict = {} seDict = {} for fileName, fileID, seID, pfn in result['Value']: resultDict.setdefault( fileName, {} ) if not seID in seDict: res = self.db.seManager.getSEName(seID) if not res['OK']: seDict[seID] = 'Unknown' else: seDict[seID] = res['Value'] se = seDict[seID] resultDict[fileName][se] = pfn return S_OK( resultDict ) def _getFileDirectories( self, lfns ): """ For a list of lfn, returns a dictionary with key the directory, and value the files in that directory. It does not make any query, just splits the names :param lfns list of lfns """ dirDict = {} for lfn in lfns: lfnDir = os.path.dirname( lfn ) lfnFile = os.path.basename( lfn ) dirDict.setdefault( lfnDir, [] ) dirDict[lfnDir].append( lfnFile ) return dirDict def _checkInfo( self, info, requiredKeys ): if not info: return S_ERROR( "Missing parameters" ) for key in requiredKeys: if not key in info: return S_ERROR( "Missing '%s' parameter" % key ) return S_OK() # def _checkLFNPFNConvention( self, lfn, pfn, se ): # """ Check that the PFN corresponds to the LFN-PFN convention """ # if pfn == lfn: # return S_OK() # if ( len( pfn ) < len( lfn ) ) or ( pfn[-len( lfn ):] != lfn ) : # return S_ERROR( 'PFN does not correspond to the LFN convention' ) # return S_OK() def changeFileGroup( self, lfns ): """ Get set the group for the supplied files :param lfns : dictionary < lfn : group > :param int/str newGroup: optional new group/groupID the same for all the supplied lfns """ res = self._findFiles( lfns, ['FileID', 'GID'] ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): group = lfns[lfn] if isinstance( group, basestring ): groupRes = self.db.ugManager.findGroup( group ) if not groupRes['OK']: return groupRes group = groupRes['Value'] currentGroup = res['Value']['Successful'][lfn]['GID'] if int( group ) == int( currentGroup ): successful[lfn] = True else: fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "GID", group ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def changeFileOwner( self, lfns ): """ Set the owner for the supplied files :param lfns : dictionary < lfn : owner > :param int/str newOwner: optional new user/userID the same for all the supplied lfns """ res = self._findFiles( lfns, ['FileID', 'UID'] ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): owner = lfns[lfn] if isinstance( owner, basestring ): userRes = self.db.ugManager.findUser( owner ) if not userRes['OK']: return userRes owner = userRes['Value'] currentOwner = res['Value']['Successful'][lfn]['UID'] if int( owner ) == int( currentOwner ): successful[lfn] = True else: fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "UID", owner ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def changeFileMode( self, lfns ): """" Set the mode for the supplied files :param lfns : dictionary < lfn : mode > :param int newMode: optional new mode the same for all the supplied lfns """ res = self._findFiles( lfns, ['FileID', 'Mode'] ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): mode = lfns[lfn] currentMode = res['Value']['Successful'][lfn]['Mode'] if int( currentMode ) == int( mode ): successful[lfn] = True else: fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "Mode", mode ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def setFileOwner( self, path, owner ): """ Set the file owner :param mixed path: file path as a string or int or list of ints or select statement :param mixt group: new user as a string or int uid """ result = self.db.ugManager.findUser( owner ) if not result['OK']: return result uid = result['Value'] return self._setFileParameter( path, 'UID', uid ) def setFileGroup( self, path, gname ): """ Set the file group :param mixed path: file path as a string or int or list of ints or select statement :param mixt group: new group as a string or int gid """ result = self.db.ugManager.findGroup( gname ) if not result['OK']: return result gid = result['Value'] return self._setFileParameter( path, 'GID', gid ) def setFileMode( self, path, mode ): """ Set the file mode :param mixed path: file path as a string or int or list of ints or select statement :param int mode: new mode """ return self._setFileParameter( path, 'Mode', mode )	vmendez/DIRAC	DataManagementSystem/DB/FileCatalogComponents/FileManagerBase.py	Python	gpl-3.0	49,658	[ "DIRAC" ]	e797ffd57e4f23510a8f12a6674886299038f0268225ec538bfaff0e0844d4b5
# Copyright (c) 2012 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Top-level presubmit script for Chromium. See http://dev.chromium.org/developers/how-tos/depottools/presubmit-scripts for more details about the presubmit API built into depot_tools. """ _EXCLUDED_PATHS = ( r"^breakpad[\\\/].", r"^native_client_sdk[\\\/]src[\\\/]build_tools[\\\/]make_rules.py", r"^native_client_sdk[\\\/]src[\\\/]build_tools[\\\/]make_simple.py", r"^native_client_sdk[\\\/]src[\\\/]tools[\\\/]..mk", r"^net[\\\/]tools[\\\/]spdyshark[\\\/].", r"^skia[\\\/].", r"^v8[\\\/].", r".MakeFile$", r".+_autogen\.h$", r".+[\\\/]pnacl_shim\.c$", r"^gpu[\\\/]config[\\\/]._list_json\.cc$", r"^chrome[\\\/]browser[\\\/]resources[\\\/]pdf[\\\/]index.js" ) # The NetscapePlugIn library is excluded from pan-project as it will soon # be deleted together with the rest of the NPAPI and it's not worthwhile to # update the coding style until then. _TESTRUNNER_PATHS = ( r"^content[\\\/]shell[\\\/]tools[\\\/]plugin[\\\/].", ) # Fragment of a regular expression that matches C++ and Objective-C++ # implementation files. _IMPLEMENTATION_EXTENSIONS = r'\.(cc\|cpp\|cxx\|mm)$' # Regular expression that matches code only used for test binaries # (best effort). _TEST_CODE_EXCLUDED_PATHS = ( r'.[\\\/](fake_\|test_\|mock_).+%s' % _IMPLEMENTATION_EXTENSIONS, r'.+_test_(base\|support\|util)%s' % _IMPLEMENTATION_EXTENSIONS, r'.+_(api\|browser\|kif\|perf\|pixel\|unit\|ui)?test(_[a-z]+)?%s' % _IMPLEMENTATION_EXTENSIONS, r'.+profile_sync_service_harness%s' % _IMPLEMENTATION_EXTENSIONS, r'.[\\\/](test\|tool(s)?)[\\\/].', # content_shell is used for running layout tests. r'content[\\\/]shell[\\\/].', # At request of folks maintaining this folder. r'chrome[\\\/]browser[\\\/]automation[\\\/].', # Non-production example code. r'mojo[\\\/]examples[\\\/].', # Launcher for running iOS tests on the simulator. r'testing[\\\/]iossim[\\\/]iossim\.mm$', ) _TEST_ONLY_WARNING = ( 'You might be calling functions intended only for testing from\n' 'production code. It is OK to ignore this warning if you know what\n' 'you are doing, as the heuristics used to detect the situation are\n' 'not perfect. The commit queue will not block on this warning.') _INCLUDE_ORDER_WARNING = ( 'Your #include order seems to be broken. Remember to use the right ' 'collation (LC_COLLATE=C) and check https://google-styleguide.googlecode' '.com/svn/trunk/cppguide.html#Names_and_Order_of_Includes') _BANNED_OBJC_FUNCTIONS = ( ( 'addTrackingRect:', ( 'The use of -[NSView addTrackingRect:owner:userData:assumeInside:] is' 'prohibited. Please use CrTrackingArea instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), False, ), ( r'/NSTrackingArea\W', ( 'The use of NSTrackingAreas is prohibited. Please use CrTrackingArea', 'instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), False, ), ( 'convertPointFromBase:', ( 'The use of -[NSView convertPointFromBase:] is almost certainly wrong.', 'Please use \|convertPoint:(point) fromView:nil\| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertPointToBase:', ( 'The use of -[NSView convertPointToBase:] is almost certainly wrong.', 'Please use \|convertPoint:(point) toView:nil\| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertRectFromBase:', ( 'The use of -[NSView convertRectFromBase:] is almost certainly wrong.', 'Please use \|convertRect:(point) fromView:nil\| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertRectToBase:', ( 'The use of -[NSView convertRectToBase:] is almost certainly wrong.', 'Please use \|convertRect:(point) toView:nil\| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertSizeFromBase:', ( 'The use of -[NSView convertSizeFromBase:] is almost certainly wrong.', 'Please use \|convertSize:(point) fromView:nil\| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertSizeToBase:', ( 'The use of -[NSView convertSizeToBase:] is almost certainly wrong.', 'Please use \|convertSize:(point) toView:nil\| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ) _BANNED_CPP_FUNCTIONS = ( # Make sure that gtest's FRIEND_TEST() macro is not used; the # FRIEND_TEST_ALL_PREFIXES() macro from base/gtest_prod_util.h should be # used instead since that allows for FLAKY_ and DISABLED_ prefixes. ( 'FRIEND_TEST(', ( 'Chromium code should not use gtest\'s FRIEND_TEST() macro. Include', 'base/gtest_prod_util.h and use FRIEND_TEST_ALL_PREFIXES() instead.', ), False, (), ), ( 'ScopedAllowIO', ( 'New code should not use ScopedAllowIO. Post a task to the blocking', 'pool or the FILE thread instead.', ), True, ( r"^base[\\\/]process[\\\/]process_metrics_linux\.cc$", r"^chrome[\\\/]browser[\\\/]chromeos[\\\/]boot_times_recorder\.cc$", r"^chrome[\\\/]browser[\\\/]chromeos[\\\/]" "customization_document_browsertest\.cc$", r"^components[\\\/]crash[\\\/]app[\\\/]breakpad_mac\.mm$", r"^content[\\\/]shell[\\\/]browser[\\\/]shell_browser_main\.cc$", r"^content[\\\/]shell[\\\/]browser[\\\/]shell_message_filter\.cc$", r"^mojo[\\\/]edk[\\\/]embedder[\\\/]" + r"simple_platform_shared_buffer_posix\.cc$", r"^net[\\\/]disk_cache[\\\/]cache_util\.cc$", r"^net[\\\/]url_request[\\\/]test_url_fetcher_factory\.cc$", r"^ui[\\\/]ozone[\\\/]platform[\\\/]drm[\\\/]host[\\\/]" "drm_native_display_delegate\.cc$", ), ), ( 'SkRefPtr', ( 'The use of SkRefPtr is prohibited. ', 'Please use skia::RefPtr instead.' ), True, (), ), ( 'SkAutoRef', ( 'The indirect use of SkRefPtr via SkAutoRef is prohibited. ', 'Please use skia::RefPtr instead.' ), True, (), ), ( 'SkAutoTUnref', ( 'The use of SkAutoTUnref is dangerous because it implicitly ', 'converts to a raw pointer. Please use skia::RefPtr instead.' ), True, (), ), ( 'SkAutoUnref', ( 'The indirect use of SkAutoTUnref through SkAutoUnref is dangerous ', 'because it implicitly converts to a raw pointer. ', 'Please use skia::RefPtr instead.' ), True, (), ), ( r'/HANDLE_EINTR\(.close', ( 'HANDLE_EINTR(close) is invalid. If close fails with EINTR, the file', 'descriptor will be closed, and it is incorrect to retry the close.', 'Either call close directly and ignore its return value, or wrap close', 'in IGNORE_EINTR to use its return value. See http://crbug.com/269623' ), True, (), ), ( r'/IGNORE_EINTR\((?!.close)', ( 'IGNORE_EINTR is only valid when wrapping close. To wrap other system', 'calls, use HANDLE_EINTR. See http://crbug.com/269623', ), True, ( # Files that #define IGNORE_EINTR. r'^base[\\\/]posix[\\\/]eintr_wrapper\.h$', r'^ppapi[\\\/]tests[\\\/]test_broker\.cc$', ), ), ( r'/v8::Extension\(', ( 'Do not introduce new v8::Extensions into the code base, use', 'gin::Wrappable instead. See http://crbug.com/334679', ), True, ( r'extensions[\\\/]renderer[\\\/]safe_builtins\.', ), ), ) _IPC_ENUM_TRAITS_DEPRECATED = ( 'You are using IPC_ENUM_TRAITS() in your code. It has been deprecated.\n' 'See http://www.chromium.org/Home/chromium-security/education/security-tips-for-ipc') _VALID_OS_MACROS = ( # Please keep sorted. 'OS_ANDROID', 'OS_ANDROID_HOST', 'OS_BSD', 'OS_CAT', # For testing. 'OS_CHROMEOS', 'OS_FREEBSD', 'OS_IOS', 'OS_LINUX', 'OS_MACOSX', 'OS_NACL', 'OS_NACL_NONSFI', 'OS_NACL_SFI', 'OS_OPENBSD', 'OS_POSIX', 'OS_QNX', 'OS_SOLARIS', 'OS_WIN', ) def _CheckNoProductionCodeUsingTestOnlyFunctions(input_api, output_api): """Attempts to prevent use of functions intended only for testing in non-testing code. For now this is just a best-effort implementation that ignores header files and may have some false positives. A better implementation would probably need a proper C++ parser. """ # We only scan .cc files and the like, as the declaration of # for-testing functions in header files are hard to distinguish from # calls to such functions without a proper C++ parser. file_inclusion_pattern = r'.+%s' % _IMPLEMENTATION_EXTENSIONS base_function_pattern = r'[ :]test::[^\s]+\|ForTest(ing)?\|for_test(ing)?' inclusion_pattern = input_api.re.compile(r'(%s)\s\(' % base_function_pattern) comment_pattern = input_api.re.compile(r'//.(%s)' % base_function_pattern) exclusion_pattern = input_api.re.compile( r'::[A-Za-z0-9_]+(%s)\|(%s)[^;]+\{' % ( base_function_pattern, base_function_pattern)) def FilterFile(affected_file): black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) return input_api.FilterSourceFile( affected_file, white_list=(file_inclusion_pattern, ), black_list=black_list) problems = [] for f in input_api.AffectedSourceFiles(FilterFile): local_path = f.LocalPath() for line_number, line in f.ChangedContents(): if (inclusion_pattern.search(line) and not comment_pattern.search(line) and not exclusion_pattern.search(line)): problems.append( '%s:%d\n %s' % (local_path, line_number, line.strip())) if problems: return [output_api.PresubmitPromptOrNotify(_TEST_ONLY_WARNING, problems)] else: return [] def _CheckNoIOStreamInHeaders(input_api, output_api): """Checks to make sure no .h files include <iostream>.""" files = [] pattern = input_api.re.compile(r'^#include\s<iostream>', input_api.re.MULTILINE) for f in input_api.AffectedSourceFiles(input_api.FilterSourceFile): if not f.LocalPath().endswith('.h'): continue contents = input_api.ReadFile(f) if pattern.search(contents): files.append(f) if len(files): return [ output_api.PresubmitError( 'Do not #include <iostream> in header files, since it inserts static ' 'initialization into every file including the header. Instead, ' '#include <ostream>. See http://crbug.com/94794', files) ] return [] def _CheckNoUNIT_TESTInSourceFiles(input_api, output_api): """Checks to make sure no source files use UNIT_TEST""" problems = [] for f in input_api.AffectedFiles(): if (not f.LocalPath().endswith(('.cc', '.mm'))): continue for line_num, line in f.ChangedContents(): if 'UNIT_TEST ' in line or line.endswith('UNIT_TEST'): problems.append(' %s:%d' % (f.LocalPath(), line_num)) if not problems: return [] return [output_api.PresubmitPromptWarning('UNIT_TEST is only for headers.\n' + '\n'.join(problems))] def _FindHistogramNameInLine(histogram_name, line): """Tries to find a histogram name or prefix in a line.""" if not "affected-histogram" in line: return histogram_name in line # A histogram_suffixes tag type has an affected-histogram name as a prefix of # the histogram_name. if not '"' in line: return False histogram_prefix = line.split('\"')[1] return histogram_prefix in histogram_name def _CheckUmaHistogramChanges(input_api, output_api): """Check that UMA histogram names in touched lines can still be found in other lines of the patch or in histograms.xml. Note that this check would not catch the reverse: changes in histograms.xml not matched in the code itself.""" touched_histograms = [] histograms_xml_modifications = [] pattern = input_api.re.compile('UMA_HISTOGRAM.\("(.)"') for f in input_api.AffectedFiles(): # If histograms.xml itself is modified, keep the modified lines for later. if f.LocalPath().endswith(('histograms.xml')): histograms_xml_modifications = f.ChangedContents() continue if not f.LocalPath().endswith(('cc', 'mm', 'cpp')): continue for line_num, line in f.ChangedContents(): found = pattern.search(line) if found: touched_histograms.append([found.group(1), f, line_num]) # Search for the touched histogram names in the local modifications to # histograms.xml, and, if not found, on the base histograms.xml file. unmatched_histograms = [] for histogram_info in touched_histograms: histogram_name_found = False for line_num, line in histograms_xml_modifications: histogram_name_found = _FindHistogramNameInLine(histogram_info[0], line) if histogram_name_found: break if not histogram_name_found: unmatched_histograms.append(histogram_info) histograms_xml_path = 'tools/metrics/histograms/histograms.xml' problems = [] if unmatched_histograms: with open(histograms_xml_path) as histograms_xml: for histogram_name, f, line_num in unmatched_histograms: histograms_xml.seek(0) histogram_name_found = False for line in histograms_xml: histogram_name_found = _FindHistogramNameInLine(histogram_name, line) if histogram_name_found: break if not histogram_name_found: problems.append(' [%s:%d] %s' % (f.LocalPath(), line_num, histogram_name)) if not problems: return [] return [output_api.PresubmitPromptWarning('Some UMA_HISTOGRAM lines have ' 'been modified and the associated histogram name has no match in either ' '%s or the modifications of it:' % (histograms_xml_path), problems)] def _CheckNoNewWStrings(input_api, output_api): """Checks to make sure we don't introduce use of wstrings.""" problems = [] for f in input_api.AffectedFiles(): if (not f.LocalPath().endswith(('.cc', '.h')) or f.LocalPath().endswith(('test.cc', '_win.cc', '_win.h')) or '/win/' in f.LocalPath()): continue allowWString = False for line_num, line in f.ChangedContents(): if 'presubmit: allow wstring' in line: allowWString = True elif not allowWString and 'wstring' in line: problems.append(' %s:%d' % (f.LocalPath(), line_num)) allowWString = False else: allowWString = False if not problems: return [] return [output_api.PresubmitPromptWarning('New code should not use wstrings.' ' If you are calling a cross-platform API that accepts a wstring, ' 'fix the API.\n' + '\n'.join(problems))] def _CheckNoDEPSGIT(input_api, output_api): """Make sure .DEPS.git is never modified manually.""" if any(f.LocalPath().endswith('.DEPS.git') for f in input_api.AffectedFiles()): return [output_api.PresubmitError( 'Never commit changes to .DEPS.git. This file is maintained by an\n' 'automated system based on what\'s in DEPS and your changes will be\n' 'overwritten.\n' 'See https://sites.google.com/a/chromium.org/dev/developers/how-tos/get-the-code#Rolling_DEPS\n' 'for more information')] return [] def _CheckValidHostsInDEPS(input_api, output_api): """Checks that DEPS file deps are from allowed_hosts.""" # Run only if DEPS file has been modified to annoy fewer bystanders. if all(f.LocalPath() != 'DEPS' for f in input_api.AffectedFiles()): return [] # Outsource work to gclient verify try: input_api.subprocess.check_output(['gclient', 'verify']) return [] except input_api.subprocess.CalledProcessError, error: return [output_api.PresubmitError( 'DEPS file must have only git dependencies.', long_text=error.output)] def _CheckNoBannedFunctions(input_api, output_api): """Make sure that banned functions are not used.""" warnings = [] errors = [] file_filter = lambda f: f.LocalPath().endswith(('.mm', '.m', '.h')) for f in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in f.ChangedContents(): for func_name, message, error in _BANNED_OBJC_FUNCTIONS: matched = False if func_name[0:1] == '/': regex = func_name[1:] if input_api.re.search(regex, line): matched = True elif func_name in line: matched = True if matched: problems = warnings; if error: problems = errors; problems.append(' %s:%d:' % (f.LocalPath(), line_num)) for message_line in message: problems.append(' %s' % message_line) file_filter = lambda f: f.LocalPath().endswith(('.cc', '.mm', '.h')) for f in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in f.ChangedContents(): for func_name, message, error, excluded_paths in _BANNED_CPP_FUNCTIONS: def IsBlacklisted(affected_file, blacklist): local_path = affected_file.LocalPath() for item in blacklist: if input_api.re.match(item, local_path): return True return False if IsBlacklisted(f, excluded_paths): continue matched = False if func_name[0:1] == '/': regex = func_name[1:] if input_api.re.search(regex, line): matched = True elif func_name in line: matched = True if matched: problems = warnings; if error: problems = errors; problems.append(' %s:%d:' % (f.LocalPath(), line_num)) for message_line in message: problems.append(' %s' % message_line) result = [] if (warnings): result.append(output_api.PresubmitPromptWarning( 'Banned functions were used.\n' + '\n'.join(warnings))) if (errors): result.append(output_api.PresubmitError( 'Banned functions were used.\n' + '\n'.join(errors))) return result def _CheckNoPragmaOnce(input_api, output_api): """Make sure that banned functions are not used.""" files = [] pattern = input_api.re.compile(r'^#pragma\s+once', input_api.re.MULTILINE) for f in input_api.AffectedSourceFiles(input_api.FilterSourceFile): if not f.LocalPath().endswith('.h'): continue contents = input_api.ReadFile(f) if pattern.search(contents): files.append(f) if files: return [output_api.PresubmitError( 'Do not use #pragma once in header files.\n' 'See http://www.chromium.org/developers/coding-style#TOC-File-headers', files)] return [] def _CheckNoTrinaryTrueFalse(input_api, output_api): """Checks to make sure we don't introduce use of foo ? true : false.""" problems = [] pattern = input_api.re.compile(r'\?\s(true\|false)\s:\s(true\|false)') for f in input_api.AffectedFiles(): if not f.LocalPath().endswith(('.cc', '.h', '.inl', '.m', '.mm')): continue for line_num, line in f.ChangedContents(): if pattern.match(line): problems.append(' %s:%d' % (f.LocalPath(), line_num)) if not problems: return [] return [output_api.PresubmitPromptWarning( 'Please consider avoiding the "? true : false" pattern if possible.\n' + '\n'.join(problems))] def _CheckUnwantedDependencies(input_api, output_api): """Runs checkdeps on #include statements added in this change. Breaking - rules is an error, breaking ! rules is a warning. """ import sys # We need to wait until we have an input_api object and use this # roundabout construct to import checkdeps because this file is # eval-ed and thus doesn't have __file__. original_sys_path = sys.path try: sys.path = sys.path + [input_api.os_path.join( input_api.PresubmitLocalPath(), 'buildtools', 'checkdeps')] import checkdeps from cpp_checker import CppChecker from rules import Rule finally: # Restore sys.path to what it was before. sys.path = original_sys_path added_includes = [] for f in input_api.AffectedFiles(): if not CppChecker.IsCppFile(f.LocalPath()): continue changed_lines = [line for line_num, line in f.ChangedContents()] added_includes.append([f.LocalPath(), changed_lines]) deps_checker = checkdeps.DepsChecker(input_api.PresubmitLocalPath()) error_descriptions = [] warning_descriptions = [] for path, rule_type, rule_description in deps_checker.CheckAddedCppIncludes( added_includes): description_with_path = '%s\n %s' % (path, rule_description) if rule_type == Rule.DISALLOW: error_descriptions.append(description_with_path) else: warning_descriptions.append(description_with_path) results = [] if error_descriptions: results.append(output_api.PresubmitError( 'You added one or more #includes that violate checkdeps rules.', error_descriptions)) if warning_descriptions: results.append(output_api.PresubmitPromptOrNotify( 'You added one or more #includes of files that are temporarily\n' 'allowed but being removed. Can you avoid introducing the\n' '#include? See relevant DEPS file(s) for details and contacts.', warning_descriptions)) return results def _CheckFilePermissions(input_api, output_api): """Check that all files have their permissions properly set.""" if input_api.platform == 'win32': return [] args = [input_api.python_executable, 'tools/checkperms/checkperms.py', '--root', input_api.change.RepositoryRoot()] for f in input_api.AffectedFiles(): args += ['--file', f.LocalPath()] checkperms = input_api.subprocess.Popen(args, stdout=input_api.subprocess.PIPE) errors = checkperms.communicate()[0].strip() if errors: return [output_api.PresubmitError('checkperms.py failed.', errors.splitlines())] return [] def _CheckNoAuraWindowPropertyHInHeaders(input_api, output_api): """Makes sure we don't include ui/aura/window_property.h in header files. """ pattern = input_api.re.compile(r'^#include\s"ui/aura/window_property.h"') errors = [] for f in input_api.AffectedFiles(): if not f.LocalPath().endswith('.h'): continue for line_num, line in f.ChangedContents(): if pattern.match(line): errors.append(' %s:%d' % (f.LocalPath(), line_num)) results = [] if errors: results.append(output_api.PresubmitError( 'Header files should not include ui/aura/window_property.h', errors)) return results def _CheckIncludeOrderForScope(scope, input_api, file_path, changed_linenums): """Checks that the lines in scope occur in the right order. 1. C system files in alphabetical order 2. C++ system files in alphabetical order 3. Project's .h files """ c_system_include_pattern = input_api.re.compile(r'\s#include <.\.h>') cpp_system_include_pattern = input_api.re.compile(r'\s#include <.>') custom_include_pattern = input_api.re.compile(r'\s#include ".') C_SYSTEM_INCLUDES, CPP_SYSTEM_INCLUDES, CUSTOM_INCLUDES = range(3) state = C_SYSTEM_INCLUDES previous_line = '' previous_line_num = 0 problem_linenums = [] for line_num, line in scope: if c_system_include_pattern.match(line): if state != C_SYSTEM_INCLUDES: problem_linenums.append((line_num, previous_line_num)) elif previous_line and previous_line > line: problem_linenums.append((line_num, previous_line_num)) elif cpp_system_include_pattern.match(line): if state == C_SYSTEM_INCLUDES: state = CPP_SYSTEM_INCLUDES elif state == CUSTOM_INCLUDES: problem_linenums.append((line_num, previous_line_num)) elif previous_line and previous_line > line: problem_linenums.append((line_num, previous_line_num)) elif custom_include_pattern.match(line): if state != CUSTOM_INCLUDES: state = CUSTOM_INCLUDES elif previous_line and previous_line > line: problem_linenums.append((line_num, previous_line_num)) else: problem_linenums.append(line_num) previous_line = line previous_line_num = line_num warnings = [] for (line_num, previous_line_num) in problem_linenums: if line_num in changed_linenums or previous_line_num in changed_linenums: warnings.append(' %s:%d' % (file_path, line_num)) return warnings def _CheckIncludeOrderInFile(input_api, f, changed_linenums): """Checks the #include order for the given file f.""" system_include_pattern = input_api.re.compile(r'\s#include \<.') # Exclude the following includes from the check: # 1) #include <.../...>, e.g., <sys/...> includes often need to appear in a # specific order. # 2) <atlbase.h>, "build/build_config.h" excluded_include_pattern = input_api.re.compile( r'\s#include (\<./.\|\<atlbase\.h\>\|"build/build_config.h")') custom_include_pattern = input_api.re.compile(r'\s#include "(?P<FILE>.)"') # Match the final or penultimate token if it is xxxtest so we can ignore it # when considering the special first include. test_file_tag_pattern = input_api.re.compile( r'_[a-z]+test(?=(_[a-zA-Z0-9]+)?\.)') if_pattern = input_api.re.compile( r'\s#\s(if\|elif\|else\|endif\|define\|undef).') # Some files need specialized order of includes; exclude such files from this # check. uncheckable_includes_pattern = input_api.re.compile( r'\s#include ' '("ipc/.macros\.h"\|<windows\.h>\|".gl.autogen.h")\s') contents = f.NewContents() warnings = [] line_num = 0 # Handle the special first include. If the first include file is # some/path/file.h, the corresponding including file can be some/path/file.cc, # some/other/path/file.cc, some/path/file_platform.cc, some/path/file-suffix.h # etc. It's also possible that no special first include exists. # If the included file is some/path/file_platform.h the including file could # also be some/path/file_xxxtest_platform.h. including_file_base_name = test_file_tag_pattern.sub( '', input_api.os_path.basename(f.LocalPath())) for line in contents: line_num += 1 if system_include_pattern.match(line): # No special first include -> process the line again along with normal # includes. line_num -= 1 break match = custom_include_pattern.match(line) if match: match_dict = match.groupdict() header_basename = test_file_tag_pattern.sub( '', input_api.os_path.basename(match_dict['FILE'])).replace('.h', '') if header_basename not in including_file_base_name: # No special first include -> process the line again along with normal # includes. line_num -= 1 break # Split into scopes: Each region between #if and #endif is its own scope. scopes = [] current_scope = [] for line in contents[line_num:]: line_num += 1 if uncheckable_includes_pattern.match(line): continue if if_pattern.match(line): scopes.append(current_scope) current_scope = [] elif ((system_include_pattern.match(line) or custom_include_pattern.match(line)) and not excluded_include_pattern.match(line)): current_scope.append((line_num, line)) scopes.append(current_scope) for scope in scopes: warnings.extend(_CheckIncludeOrderForScope(scope, input_api, f.LocalPath(), changed_linenums)) return warnings def _CheckIncludeOrder(input_api, output_api): """Checks that the #include order is correct. 1. The corresponding header for source files. 2. C system files in alphabetical order 3. C++ system files in alphabetical order 4. Project's .h files in alphabetical order Each region separated by #if, #elif, #else, #endif, #define and #undef follows these rules separately. """ def FileFilterIncludeOrder(affected_file): black_list = (_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) return input_api.FilterSourceFile(affected_file, black_list=black_list) warnings = [] for f in input_api.AffectedFiles(file_filter=FileFilterIncludeOrder): if f.LocalPath().endswith(('.cc', '.h')): changed_linenums = set(line_num for line_num, _ in f.ChangedContents()) warnings.extend(_CheckIncludeOrderInFile(input_api, f, changed_linenums)) results = [] if warnings: results.append(output_api.PresubmitPromptOrNotify(_INCLUDE_ORDER_WARNING, warnings)) return results def _CheckForVersionControlConflictsInFile(input_api, f): pattern = input_api.re.compile('^(?:<<<<<<<\|>>>>>>>) \|^=======$') errors = [] for line_num, line in f.ChangedContents(): if pattern.match(line): errors.append(' %s:%d %s' % (f.LocalPath(), line_num, line)) return errors def _CheckForVersionControlConflicts(input_api, output_api): """Usually this is not intentional and will cause a compile failure.""" errors = [] for f in input_api.AffectedFiles(): errors.extend(_CheckForVersionControlConflictsInFile(input_api, f)) results = [] if errors: results.append(output_api.PresubmitError( 'Version control conflict markers found, please resolve.', errors)) return results def _CheckHardcodedGoogleHostsInLowerLayers(input_api, output_api): def FilterFile(affected_file): """Filter function for use with input_api.AffectedSourceFiles, below. This filters out everything except non-test files from top-level directories that generally speaking should not hard-code service URLs (e.g. src/android_webview/, src/content/ and others). """ return input_api.FilterSourceFile( affected_file, white_list=(r'^(android_webview\|base\|content\|net)[\\\/].', ), black_list=(_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST)) base_pattern = '"[^"]google\.com[^"]"' comment_pattern = input_api.re.compile('//.%s' % base_pattern) pattern = input_api.re.compile(base_pattern) problems = [] # items are (filename, line_number, line) for f in input_api.AffectedSourceFiles(FilterFile): for line_num, line in f.ChangedContents(): if not comment_pattern.search(line) and pattern.search(line): problems.append((f.LocalPath(), line_num, line)) if problems: return [output_api.PresubmitPromptOrNotify( 'Most layers below src/chrome/ should not hardcode service URLs.\n' 'Are you sure this is correct?', [' %s:%d: %s' % ( problem[0], problem[1], problem[2]) for problem in problems])] else: return [] def _CheckNoAbbreviationInPngFileName(input_api, output_api): """Makes sure there are no abbreviations in the name of PNG files. The native_client_sdk directory is excluded because it has auto-generated PNG files for documentation. """ errors = [] white_list = (r'._[a-z]_.\.png$\|._[a-z]\.png$',) black_list = (r'^native_client_sdk[\\\/]',) file_filter = lambda f: input_api.FilterSourceFile( f, white_list=white_list, black_list=black_list) for f in input_api.AffectedFiles(include_deletes=False, file_filter=file_filter): errors.append(' %s' % f.LocalPath()) results = [] if errors: results.append(output_api.PresubmitError( 'The name of PNG files should not have abbreviations. \n' 'Use _hover.png, _center.png, instead of _h.png, _c.png.\n' 'Contact oshima@chromium.org if you have questions.', errors)) return results def _FilesToCheckForIncomingDeps(re, changed_lines): """Helper method for _CheckAddedDepsHaveTargetApprovals. Returns a set of DEPS entries that we should look up. For a directory (rather than a specific filename) we fake a path to a specific filename by adding /DEPS. This is chosen as a file that will seldom or never be subject to per-file include_rules. """ # We ignore deps entries on auto-generated directories. AUTO_GENERATED_DIRS = ['grit', 'jni'] # This pattern grabs the path without basename in the first # parentheses, and the basename (if present) in the second. It # relies on the simple heuristic that if there is a basename it will # be a header file ending in ".h". pattern = re.compile( r"""['"]\+([^'"]+?)(/[a-zA-Z0-9_]+\.h)?['"].""") results = set() for changed_line in changed_lines: m = pattern.match(changed_line) if m: path = m.group(1) if path.split('/')[0] not in AUTO_GENERATED_DIRS: if m.group(2): results.add('%s%s' % (path, m.group(2))) else: results.add('%s/DEPS' % path) return results def _CheckAddedDepsHaveTargetApprovals(input_api, output_api): """When a dependency prefixed with + is added to a DEPS file, we want to make sure that the change is reviewed by an OWNER of the target file or directory, to avoid layering violations from being introduced. This check verifies that this happens. """ changed_lines = set() for f in input_api.AffectedFiles(): filename = input_api.os_path.basename(f.LocalPath()) if filename == 'DEPS': changed_lines \|= set(line.strip() for line_num, line in f.ChangedContents()) if not changed_lines: return [] virtual_depended_on_files = _FilesToCheckForIncomingDeps(input_api.re, changed_lines) if not virtual_depended_on_files: return [] if input_api.is_committing: if input_api.tbr: return [output_api.PresubmitNotifyResult( '--tbr was specified, skipping OWNERS check for DEPS additions')] if not input_api.change.issue: return [output_api.PresubmitError( "DEPS approval by OWNERS check failed: this change has " "no Rietveld issue number, so we can't check it for approvals.")] output = output_api.PresubmitError else: output = output_api.PresubmitNotifyResult owners_db = input_api.owners_db owner_email, reviewers = input_api.canned_checks._RietveldOwnerAndReviewers( input_api, owners_db.email_regexp, approval_needed=input_api.is_committing) owner_email = owner_email or input_api.change.author_email reviewers_plus_owner = set(reviewers) if owner_email: reviewers_plus_owner.add(owner_email) missing_files = owners_db.files_not_covered_by(virtual_depended_on_files, reviewers_plus_owner) # We strip the /DEPS part that was added by # _FilesToCheckForIncomingDeps to fake a path to a file in a # directory. def StripDeps(path): start_deps = path.rfind('/DEPS') if start_deps != -1: return path[:start_deps] else: return path unapproved_dependencies = ["'+%s'," % StripDeps(path) for path in missing_files] if unapproved_dependencies: output_list = [ output('Missing LGTM from OWNERS of dependencies added to DEPS:\n %s' % '\n '.join(sorted(unapproved_dependencies)))] if not input_api.is_committing: suggested_owners = owners_db.reviewers_for(missing_files, owner_email) output_list.append(output( 'Suggested missing target path OWNERS:\n %s' % '\n '.join(suggested_owners or []))) return output_list return [] def _CheckSpamLogging(input_api, output_api): file_inclusion_pattern = r'.+%s' % _IMPLEMENTATION_EXTENSIONS black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST + (r"^base[\\\/]logging\.h$", r"^base[\\\/]logging\.cc$", r"^chrome[\\\/]app[\\\/]chrome_main_delegate\.cc$", r"^chrome[\\\/]browser[\\\/]chrome_browser_main\.cc$", r"^chrome[\\\/]browser[\\\/]ui[\\\/]startup[\\\/]" r"startup_browser_creator\.cc$", r"^chrome[\\\/]installer[\\\/]setup[\\\/].", r"chrome[\\\/]browser[\\\/]diagnostics[\\\/]" + r"diagnostics_writer\.cc$", r"^chrome_elf[\\\/]dll_hash[\\\/]dll_hash_main\.cc$", r"^chromecast[\\\/]", r"^cloud_print[\\\/]", r"^content[\\\/]common[\\\/]gpu[\\\/]client[\\\/]" r"gl_helper_benchmark\.cc$", r"^courgette[\\\/]courgette_tool\.cc$", r"^extensions[\\\/]renderer[\\\/]logging_native_handler\.cc$", r"^ipc[\\\/]ipc_logging\.cc$", r"^native_client_sdk[\\\/]", r"^remoting[\\\/]base[\\\/]logging\.h$", r"^remoting[\\\/]host[\\\/].", r"^sandbox[\\\/]linux[\\\/].", r"^tools[\\\/]", r"^ui[\\\/]aura[\\\/]bench[\\\/]bench_main\.cc$", r"^storage[\\\/]browser[\\\/]fileapi[\\\/]" + r"dump_file_system.cc$",)) source_file_filter = lambda x: input_api.FilterSourceFile( x, white_list=(file_inclusion_pattern,), black_list=black_list) log_info = [] printf = [] for f in input_api.AffectedSourceFiles(source_file_filter): contents = input_api.ReadFile(f, 'rb') if input_api.re.search(r"\bD?LOG\s\(\sINFO\s\)", contents): log_info.append(f.LocalPath()) elif input_api.re.search(r"\bD?LOG_IF\s\(\sINFO\s,", contents): log_info.append(f.LocalPath()) if input_api.re.search(r"\bprintf\(", contents): printf.append(f.LocalPath()) elif input_api.re.search(r"\bfprintf\((stdout\|stderr)", contents): printf.append(f.LocalPath()) if log_info: return [output_api.PresubmitError( 'These files spam the console log with LOG(INFO):', items=log_info)] if printf: return [output_api.PresubmitError( 'These files spam the console log with printf/fprintf:', items=printf)] return [] def _CheckForAnonymousVariables(input_api, output_api): """These types are all expected to hold locks while in scope and so should never be anonymous (which causes them to be immediately destroyed).""" they_who_must_be_named = [ 'base::AutoLock', 'base::AutoReset', 'base::AutoUnlock', 'SkAutoAlphaRestore', 'SkAutoBitmapShaderInstall', 'SkAutoBlitterChoose', 'SkAutoBounderCommit', 'SkAutoCallProc', 'SkAutoCanvasRestore', 'SkAutoCommentBlock', 'SkAutoDescriptor', 'SkAutoDisableDirectionCheck', 'SkAutoDisableOvalCheck', 'SkAutoFree', 'SkAutoGlyphCache', 'SkAutoHDC', 'SkAutoLockColors', 'SkAutoLockPixels', 'SkAutoMalloc', 'SkAutoMaskFreeImage', 'SkAutoMutexAcquire', 'SkAutoPathBoundsUpdate', 'SkAutoPDFRelease', 'SkAutoRasterClipValidate', 'SkAutoRef', 'SkAutoTime', 'SkAutoTrace', 'SkAutoUnref', ] anonymous = r'(%s)\s[({]' % '\|'.join(they_who_must_be_named) # bad: base::AutoLock(lock.get()); # not bad: base::AutoLock lock(lock.get()); bad_pattern = input_api.re.compile(anonymous) # good: new base::AutoLock(lock.get()) good_pattern = input_api.re.compile(r'\bnew\s' + anonymous) errors = [] for f in input_api.AffectedFiles(): if not f.LocalPath().endswith(('.cc', '.h', '.inl', '.m', '.mm')): continue for linenum, line in f.ChangedContents(): if bad_pattern.search(line) and not good_pattern.search(line): errors.append('%s:%d' % (f.LocalPath(), linenum)) if errors: return [output_api.PresubmitError( 'These lines create anonymous variables that need to be named:', items=errors)] return [] def _CheckCygwinShell(input_api, output_api): source_file_filter = lambda x: input_api.FilterSourceFile( x, white_list=(r'.+\.(gyp\|gypi)$',)) cygwin_shell = [] for f in input_api.AffectedSourceFiles(source_file_filter): for linenum, line in f.ChangedContents(): if 'msvs_cygwin_shell' in line: cygwin_shell.append(f.LocalPath()) break if cygwin_shell: return [output_api.PresubmitError( 'These files should not use msvs_cygwin_shell (the default is 0):', items=cygwin_shell)] return [] def _CheckUserActionUpdate(input_api, output_api): """Checks if any new user action has been added.""" if any('actions.xml' == input_api.os_path.basename(f) for f in input_api.LocalPaths()): # If actions.xml is already included in the changelist, the PRESUBMIT # for actions.xml will do a more complete presubmit check. return [] file_filter = lambda f: f.LocalPath().endswith(('.cc', '.mm')) action_re = r'[^a-zA-Z]UserMetricsAction\("([^"])' current_actions = None for f in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in f.ChangedContents(): match = input_api.re.search(action_re, line) if match: # Loads contents in tools/metrics/actions/actions.xml to memory. It's # loaded only once. if not current_actions: with open('tools/metrics/actions/actions.xml') as actions_f: current_actions = actions_f.read() # Search for the matched user action name in \|current_actions\|. for action_name in match.groups(): action = 'name="{0}"'.format(action_name) if action not in current_actions: return [output_api.PresubmitPromptWarning( 'File %s line %d: %s is missing in ' 'tools/metrics/actions/actions.xml. Please run ' 'tools/metrics/actions/extract_actions.py to update.' % (f.LocalPath(), line_num, action_name))] return [] def _GetJSONParseError(input_api, filename, eat_comments=True): try: contents = input_api.ReadFile(filename) if eat_comments: json_comment_eater = input_api.os_path.join( input_api.PresubmitLocalPath(), 'tools', 'json_comment_eater', 'json_comment_eater.py') process = input_api.subprocess.Popen( [input_api.python_executable, json_comment_eater], stdin=input_api.subprocess.PIPE, stdout=input_api.subprocess.PIPE, universal_newlines=True) (contents, _) = process.communicate(input=contents) input_api.json.loads(contents) except ValueError as e: return e return None def _GetIDLParseError(input_api, filename): try: contents = input_api.ReadFile(filename) idl_schema = input_api.os_path.join( input_api.PresubmitLocalPath(), 'tools', 'json_schema_compiler', 'idl_schema.py') process = input_api.subprocess.Popen( [input_api.python_executable, idl_schema], stdin=input_api.subprocess.PIPE, stdout=input_api.subprocess.PIPE, stderr=input_api.subprocess.PIPE, universal_newlines=True) (_, error) = process.communicate(input=contents) return error or None except ValueError as e: return e def _CheckParseErrors(input_api, output_api): """Check that IDL and JSON files do not contain syntax errors.""" actions = { '.idl': _GetIDLParseError, '.json': _GetJSONParseError, } # These paths contain test data and other known invalid JSON files. excluded_patterns = [ r'test[\\\/]data[\\\/]', r'^components[\\\/]policy[\\\/]resources[\\\/]policy_templates\.json$', ] # Most JSON files are preprocessed and support comments, but these do not. json_no_comments_patterns = [ r'^testing[\\\/]', ] # Only run IDL checker on files in these directories. idl_included_patterns = [ r'^chrome[\\\/]common[\\\/]extensions[\\\/]api[\\\/]', r'^extensions[\\\/]common[\\\/]api[\\\/]', ] def get_action(affected_file): filename = affected_file.LocalPath() return actions.get(input_api.os_path.splitext(filename)[1]) def MatchesFile(patterns, path): for pattern in patterns: if input_api.re.search(pattern, path): return True return False def FilterFile(affected_file): action = get_action(affected_file) if not action: return False path = affected_file.LocalPath() if MatchesFile(excluded_patterns, path): return False if (action == _GetIDLParseError and not MatchesFile(idl_included_patterns, path)): return False return True results = [] for affected_file in input_api.AffectedFiles( file_filter=FilterFile, include_deletes=False): action = get_action(affected_file) kwargs = {} if (action == _GetJSONParseError and MatchesFile(json_no_comments_patterns, affected_file.LocalPath())): kwargs['eat_comments'] = False parse_error = action(input_api, affected_file.AbsoluteLocalPath(), kwargs) if parse_error: results.append(output_api.PresubmitError('%s could not be parsed: %s' % (affected_file.LocalPath(), parse_error))) return results def _CheckJavaStyle(input_api, output_api): """Runs checkstyle on changed java files and returns errors if any exist.""" import sys original_sys_path = sys.path try: sys.path = sys.path + [input_api.os_path.join( input_api.PresubmitLocalPath(), 'tools', 'android', 'checkstyle')] import checkstyle finally: # Restore sys.path to what it was before. sys.path = original_sys_path return checkstyle.RunCheckstyle( input_api, output_api, 'tools/android/checkstyle/chromium-style-5.0.xml', black_list=_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) def _CheckForCopyrightedCode(input_api, output_api): """Verifies that newly added code doesn't contain copyrighted material and is properly licensed under the standard Chromium license. As there can be false positives, we maintain a whitelist file. This check also verifies that the whitelist file is up to date. """ import sys original_sys_path = sys.path try: sys.path = sys.path + [input_api.os_path.join( input_api.PresubmitLocalPath(), 'android_webview', 'tools')] import copyright_scanner finally: # Restore sys.path to what it was before. sys.path = original_sys_path return copyright_scanner.ScanAtPresubmit(input_api, output_api) def _CheckSingletonInHeaders(input_api, output_api): """Checks to make sure no header files have \|Singleton<\|.""" def FileFilter(affected_file): # It's ok for base/memory/singleton.h to have \|Singleton<\|. black_list = (_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST + (r"^base[\\\/]memory[\\\/]singleton\.h$",)) return input_api.FilterSourceFile(affected_file, black_list=black_list) pattern = input_api.re.compile(r'(?<!class\s)Singleton\s<') files = [] for f in input_api.AffectedSourceFiles(FileFilter): if (f.LocalPath().endswith('.h') or f.LocalPath().endswith('.hxx') or f.LocalPath().endswith('.hpp') or f.LocalPath().endswith('.inl')): contents = input_api.ReadFile(f) for line in contents.splitlines(False): if (not input_api.re.match(r'//', line) and # Strip C++ comment. pattern.search(line)): files.append(f) break if files: return [ output_api.PresubmitError( 'Found Singleton<T> in the following header files.\n' + 'Please move them to an appropriate source file so that the ' + 'template gets instantiated in a single compilation unit.', files) ] return [] _DEPRECATED_CSS = [ # Values ( "-webkit-box", "flex" ), ( "-webkit-inline-box", "inline-flex" ), ( "-webkit-flex", "flex" ), ( "-webkit-inline-flex", "inline-flex" ), ( "-webkit-min-content", "min-content" ), ( "-webkit-max-content", "max-content" ), # Properties ( "-webkit-background-clip", "background-clip" ), ( "-webkit-background-origin", "background-origin" ), ( "-webkit-background-size", "background-size" ), ( "-webkit-box-shadow", "box-shadow" ), # Functions ( "-webkit-gradient", "gradient" ), ( "-webkit-repeating-gradient", "repeating-gradient" ), ( "-webkit-linear-gradient", "linear-gradient" ), ( "-webkit-repeating-linear-gradient", "repeating-linear-gradient" ), ( "-webkit-radial-gradient", "radial-gradient" ), ( "-webkit-repeating-radial-gradient", "repeating-radial-gradient" ), ] def _CheckNoDeprecatedCSS(input_api, output_api): """ Make sure that we don't use deprecated CSS properties, functions or values. Our external documentation is ignored by the hooks as it needs to be consumed by WebKit. """ results = [] file_inclusion_pattern = (r".+\.css$",) black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST + (r"^chrome/common/extensions/docs", r"^chrome/docs", r"^native_client_sdk")) file_filter = lambda f: input_api.FilterSourceFile( f, white_list=file_inclusion_pattern, black_list=black_list) for fpath in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in fpath.ChangedContents(): for (deprecated_value, value) in _DEPRECATED_CSS: if deprecated_value in line: results.append(output_api.PresubmitError( "%s:%d: Use of deprecated CSS %s, use %s instead" % (fpath.LocalPath(), line_num, deprecated_value, value))) return results _DEPRECATED_JS = [ ( "__lookupGetter__", "Object.getOwnPropertyDescriptor" ), ( "__defineGetter__", "Object.defineProperty" ), ( "__defineSetter__", "Object.defineProperty" ), ] def _CheckNoDeprecatedJS(input_api, output_api): """Make sure that we don't use deprecated JS in Chrome code.""" results = [] file_inclusion_pattern = (r".+\.js$",) # TODO(dbeam): .html? black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) file_filter = lambda f: input_api.FilterSourceFile( f, white_list=file_inclusion_pattern, black_list=black_list) for fpath in input_api.AffectedFiles(file_filter=file_filter): for lnum, line in fpath.ChangedContents(): for (deprecated, replacement) in _DEPRECATED_JS: if deprecated in line: results.append(output_api.PresubmitError( "%s:%d: Use of deprecated JS %s, use %s instead" % (fpath.LocalPath(), lnum, deprecated, replacement))) return results def _CommonChecks(input_api, output_api): """Checks common to both upload and commit.""" results = [] results.extend(input_api.canned_checks.PanProjectChecks( input_api, output_api, excluded_paths=_EXCLUDED_PATHS + _TESTRUNNER_PATHS)) results.extend(_CheckAuthorizedAuthor(input_api, output_api)) results.extend( _CheckNoProductionCodeUsingTestOnlyFunctions(input_api, output_api)) results.extend(_CheckNoIOStreamInHeaders(input_api, output_api)) results.extend(_CheckNoUNIT_TESTInSourceFiles(input_api, output_api)) results.extend(_CheckNoNewWStrings(input_api, output_api)) results.extend(_CheckNoDEPSGIT(input_api, output_api)) results.extend(_CheckNoBannedFunctions(input_api, output_api)) results.extend(_CheckNoPragmaOnce(input_api, output_api)) results.extend(_CheckNoTrinaryTrueFalse(input_api, output_api)) results.extend(_CheckUnwantedDependencies(input_api, output_api)) results.extend(_CheckFilePermissions(input_api, output_api)) results.extend(_CheckNoAuraWindowPropertyHInHeaders(input_api, output_api)) results.extend(_CheckIncludeOrder(input_api, output_api)) results.extend(_CheckForVersionControlConflicts(input_api, output_api)) results.extend(_CheckPatchFiles(input_api, output_api)) results.extend(_CheckHardcodedGoogleHostsInLowerLayers(input_api, output_api)) results.extend(_CheckNoAbbreviationInPngFileName(input_api, output_api)) results.extend(_CheckForInvalidOSMacros(input_api, output_api)) results.extend(_CheckForInvalidIfDefinedMacros(input_api, output_api)) # TODO(danakj): Remove this when base/move.h is removed. results.extend(_CheckForUsingSideEffectsOfPass(input_api, output_api)) results.extend(_CheckAddedDepsHaveTargetApprovals(input_api, output_api)) results.extend( input_api.canned_checks.CheckChangeHasNoTabs( input_api, output_api, source_file_filter=lambda x: x.LocalPath().endswith('.grd'))) results.extend(_CheckSpamLogging(input_api, output_api)) results.extend(_CheckForAnonymousVariables(input_api, output_api)) results.extend(_CheckCygwinShell(input_api, output_api)) results.extend(_CheckUserActionUpdate(input_api, output_api)) results.extend(_CheckNoDeprecatedCSS(input_api, output_api)) results.extend(_CheckNoDeprecatedJS(input_api, output_api)) results.extend(_CheckParseErrors(input_api, output_api)) results.extend(_CheckForIPCRules(input_api, output_api)) results.extend(_CheckForCopyrightedCode(input_api, output_api)) results.extend(_CheckForWindowsLineEndings(input_api, output_api)) results.extend(_CheckSingletonInHeaders(input_api, output_api)) if any('PRESUBMIT.py' == f.LocalPath() for f in input_api.AffectedFiles()): results.extend(input_api.canned_checks.RunUnitTestsInDirectory( input_api, output_api, input_api.PresubmitLocalPath(), whitelist=[r'^PRESUBMIT_test\.py$'])) return results def _CheckAuthorizedAuthor(input_api, output_api): """For non-googler/chromites committers, verify the author's email address is in AUTHORS. """ # TODO(maruel): Add it to input_api? import fnmatch author = input_api.change.author_email if not author: input_api.logging.info('No author, skipping AUTHOR check') return [] authors_path = input_api.os_path.join( input_api.PresubmitLocalPath(), 'AUTHORS') valid_authors = ( input_api.re.match(r'[^#]+\s+\<(.+?)\>\s$', line) for line in open(authors_path)) valid_authors = [item.group(1).lower() for item in valid_authors if item] if not any(fnmatch.fnmatch(author.lower(), valid) for valid in valid_authors): input_api.logging.info('Valid authors are %s', ', '.join(valid_authors)) return [output_api.PresubmitPromptWarning( ('%s is not in AUTHORS file. If you are a new contributor, please visit' '\n' 'http://www.chromium.org/developers/contributing-code and read the ' '"Legal" section\n' 'If you are a chromite, verify the contributor signed the CLA.') % author)] return [] def _CheckPatchFiles(input_api, output_api): problems = [f.LocalPath() for f in input_api.AffectedFiles() if f.LocalPath().endswith(('.orig', '.rej'))] if problems: return [output_api.PresubmitError( "Don't commit .rej and .orig files.", problems)] else: return [] def _DidYouMeanOSMacro(bad_macro): try: return {'A': 'OS_ANDROID', 'B': 'OS_BSD', 'C': 'OS_CHROMEOS', 'F': 'OS_FREEBSD', 'L': 'OS_LINUX', 'M': 'OS_MACOSX', 'N': 'OS_NACL', 'O': 'OS_OPENBSD', 'P': 'OS_POSIX', 'S': 'OS_SOLARIS', 'W': 'OS_WIN'}[bad_macro[3].upper()] except KeyError: return '' def _CheckForInvalidOSMacrosInFile(input_api, f): """Check for sensible looking, totally invalid OS macros.""" preprocessor_statement = input_api.re.compile(r'^\s#') os_macro = input_api.re.compile(r'defined\((OS_[^)]+)\)') results = [] for lnum, line in f.ChangedContents(): if preprocessor_statement.search(line): for match in os_macro.finditer(line): if not match.group(1) in _VALID_OS_MACROS: good = _DidYouMeanOSMacro(match.group(1)) did_you_mean = ' (did you mean %s?)' % good if good else '' results.append(' %s:%d %s%s' % (f.LocalPath(), lnum, match.group(1), did_you_mean)) return results def _CheckForInvalidOSMacros(input_api, output_api): """Check all affected files for invalid OS macros.""" bad_macros = [] for f in input_api.AffectedFiles(): if not f.LocalPath().endswith(('.py', '.js', '.html', '.css')): bad_macros.extend(_CheckForInvalidOSMacrosInFile(input_api, f)) if not bad_macros: return [] return [output_api.PresubmitError( 'Possibly invalid OS macro[s] found. Please fix your code\n' 'or add your macro to src/PRESUBMIT.py.', bad_macros)] def _CheckForInvalidIfDefinedMacrosInFile(input_api, f): """Check all affected files for invalid "if defined" macros.""" ALWAYS_DEFINED_MACROS = ( "TARGET_CPU_PPC", "TARGET_CPU_PPC64", "TARGET_CPU_68K", "TARGET_CPU_X86", "TARGET_CPU_ARM", "TARGET_CPU_MIPS", "TARGET_CPU_SPARC", "TARGET_CPU_ALPHA", "TARGET_IPHONE_SIMULATOR", "TARGET_OS_EMBEDDED", "TARGET_OS_IPHONE", "TARGET_OS_MAC", "TARGET_OS_UNIX", "TARGET_OS_WIN32", ) ifdef_macro = input_api.re.compile(r'^\s#.(?:ifdef\s\|defined\()([^\s\)]+)') results = [] for lnum, line in f.ChangedContents(): for match in ifdef_macro.finditer(line): if match.group(1) in ALWAYS_DEFINED_MACROS: always_defined = ' %s is always defined. ' % match.group(1) did_you_mean = 'Did you mean \'#if %s\'?' % match.group(1) results.append(' %s:%d %s\n\t%s' % (f.LocalPath(), lnum, always_defined, did_you_mean)) return results def _CheckForInvalidIfDefinedMacros(input_api, output_api): """Check all affected files for invalid "if defined" macros.""" bad_macros = [] for f in input_api.AffectedFiles(): if f.LocalPath().endswith(('.h', '.c', '.cc', '.m', '.mm')): bad_macros.extend(_CheckForInvalidIfDefinedMacrosInFile(input_api, f)) if not bad_macros: return [] return [output_api.PresubmitError( 'Found ifdef check on always-defined macro[s]. Please fix your code\n' 'or check the list of ALWAYS_DEFINED_MACROS in src/PRESUBMIT.py.', bad_macros)] def _CheckForUsingSideEffectsOfPass(input_api, output_api): """Check all affected files for using side effects of Pass.""" errors = [] for f in input_api.AffectedFiles(): if f.LocalPath().endswith(('.h', '.c', '.cc', '.m', '.mm')): for lnum, line in f.ChangedContents(): # Disallow Foo(my_scoped_thing.Pass()); See crbug.com/418297. if input_api.re.search(r'\[a-zA-Z0-9_]+\.Pass\(\)', line): errors.append(output_api.PresubmitError( ('%s:%d uses foo.Pass() to delete the contents of scoped_ptr. ' + 'See crbug.com/418297.') % (f.LocalPath(), lnum))) return errors def _CheckForIPCRules(input_api, output_api): """Check for same IPC rules described in http://www.chromium.org/Home/chromium-security/education/security-tips-for-ipc """ base_pattern = r'IPC_ENUM_TRAITS\(' inclusion_pattern = input_api.re.compile(r'(%s)' % base_pattern) comment_pattern = input_api.re.compile(r'//.(%s)' % base_pattern) problems = [] for f in input_api.AffectedSourceFiles(None): local_path = f.LocalPath() if not local_path.endswith('.h'): continue for line_number, line in f.ChangedContents(): if inclusion_pattern.search(line) and not comment_pattern.search(line): problems.append( '%s:%d\n %s' % (local_path, line_number, line.strip())) if problems: return [output_api.PresubmitPromptWarning( _IPC_ENUM_TRAITS_DEPRECATED, problems)] else: return [] def _CheckForWindowsLineEndings(input_api, output_api): """Check source code and known ascii text files for Windows style line endings. """ known_text_files = r'.*\.(txt\|html\|htm\|mhtml\|py\|gyp\|gypi\|gn\|isolate)$' file_inclusion_pattern = ( known_text_files, r'.+%s' % _IMPLEMENTATION_EXTENSIONS ) filter = lambda f: input_api.FilterSourceFile( f, white_list=file_inclusion_pattern, black_list=None) files = [f.LocalPath() for f in input_api.AffectedSourceFiles(filter)] problems = [] for file in files: fp = open(file, 'r') for line in fp: if line.endswith('\r\n'): problems.append(file) break fp.close() if problems: return [output_api.PresubmitPromptWarning('Are you sure that you want ' 'these files to contain Windows style line endings?\n' + '\n'.join(problems))] return [] def CheckChangeOnUpload(input_api, output_api): results = [] results.extend(_CommonChecks(input_api, output_api)) results.extend(_CheckValidHostsInDEPS(input_api, output_api)) results.extend(_CheckJavaStyle(input_api, output_api)) results.extend( input_api.canned_checks.CheckGNFormatted(input_api, output_api)) results.extend(_CheckUmaHistogramChanges(input_api, output_api)) return results def GetTryServerMasterForBot(bot): """Returns the Try Server master for the given bot. It tries to guess the master from the bot name, but may still fail and return None. There is no longer a default master. """ # Potentially ambiguous bot names are listed explicitly. master_map = { 'chromium_presubmit': 'tryserver.chromium.linux', 'blink_presubmit': 'tryserver.chromium.linux', 'tools_build_presubmit': 'tryserver.chromium.linux', } master = master_map.get(bot) if not master: if 'linux' in bot or 'android' in bot or 'presubmit' in bot: master = 'tryserver.chromium.linux' elif 'win' in bot: master = 'tryserver.chromium.win' elif 'mac' in bot or 'ios' in bot: master = 'tryserver.chromium.mac' return master def GetDefaultTryConfigs(bots): """Returns a list of ('bot', set(['tests']), filtered by [bots]. """ builders_and_tests = dict((bot, set(['defaulttests'])) for bot in bots) # Build up the mapping from tryserver master to bot/test. out = dict() for bot, tests in builders_and_tests.iteritems(): out.setdefault(GetTryServerMasterForBot(bot), {})[bot] = tests return out def CheckChangeOnCommit(input_api, output_api): results = [] results.extend(_CommonChecks(input_api, output_api)) # TODO(thestig) temporarily disabled, doesn't work in third_party/ #results.extend(input_api.canned_checks.CheckSvnModifiedDirectories( # input_api, output_api, sources)) # Make sure the tree is 'open'. results.extend(input_api.canned_checks.CheckTreeIsOpen( input_api, output_api, json_url='http://chromium-status.appspot.com/current?format=json')) results.extend(input_api.canned_checks.CheckChangeHasBugField( input_api, output_api)) results.extend(input_api.canned_checks.CheckChangeHasDescription( input_api, output_api)) return results def GetPreferredTryMasters(project, change): import re files = change.LocalPaths() import os import json with open(os.path.join( change.RepositoryRoot(), 'testing', 'commit_queue', 'config.json')) as f: cq_config = json.load(f) cq_verifiers = cq_config.get('verifiers_no_patch', {}) cq_try_jobs = cq_verifiers.get('try_job_verifier', {}) builders = cq_try_jobs.get('launched', {}) for master, master_config in cq_try_jobs.get('triggered', {}).iteritems(): for triggered_bot in master_config: builders.get(master, {}).pop(triggered_bot, None) # Explicitly iterate over copies of dicts since we mutate them. for master in builders.keys(): for builder in builders[master].keys(): # Do not trigger presubmit builders, since they're likely to fail # (e.g. OWNERS checks before finished code review), and we're # running local presubmit anyway. if 'presubmit' in builder: builders[master].pop(builder) return builders	mou4e/zirconium	PRESUBMIT.py	Python	bsd-3-clause	64,946	[ "VisIt" ]	73c03dc325168a0a5d63c158ec65589a3800f14bea235698dcf21bc3646d5706
# coding=utf-8 """Create contour from shakemap raster layer.""" import logging import os import shutil from datetime import datetime import numpy as np from osgeo import gdal, ogr from osgeo.gdalconst import GA_ReadOnly from qgis.core import QgsFeatureRequest, QgsVectorLayer from safe.common.exceptions import ( ContourCreationError, FileNotFoundError, InvalidLayerError ) from safe.common.utilities import ( romanise, temp_dir, unique_filename ) from safe.definitions import contour_id_field from safe.definitions.constants import NUMPY_SMOOTHING from safe.definitions.fields import ( contour_colour_field, contour_fields, contour_halign_field, contour_length_field, contour_mmi_field, contour_roman_field, contour_valign_field, contour_x_field, contour_y_field ) from safe.definitions.layer_geometry import layer_geometry_line from safe.definitions.layer_modes import layer_mode_classified from safe.definitions.layer_purposes import layer_purpose_earthquake_contour from safe.gis.vector.tools import ( create_ogr_field_from_definition, field_index_from_definition ) from safe.utilities.i18n import tr from safe.utilities.metadata import write_iso19115_metadata from safe.utilities.resources import resources_path from safe.utilities.styling import mmi_colour __copyright__ = "Copyright 2017, The InaSAFE Project" __license__ = "GPL version 3" __email__ = "info@inasafe.org" __revision__ = '$Format:%H$' LOGGER = logging.getLogger('InaSAFE') def gaussian_kernel(sigma, truncate=4.0): """Return Gaussian that truncates at the given number of std deviations. Adapted from https://github.com/nicjhan/gaussian-filter """ sigma = float(sigma) radius = int(truncate * sigma + 0.5) x, y = np.mgrid[-radius:radius + 1, -radius:radius + 1] sigma = sigma ** 2 k = 2 * np.exp(-0.5 * (x 2 + y 2) / sigma) k = k / np.sum(k) return k def tile_and_reflect(input): """Make 3x3 tiled array. Central area is 'input', surrounding areas are reflected. Adapted from https://github.com/nicjhan/gaussian-filter """ tiled_input = np.tile(input, (3, 3)) rows = input.shape[0] cols = input.shape[1] # Now we have a 3x3 tiles - do the reflections. # All those on the sides need to be flipped left-to-right. for i in range(3): # Left hand side tiles tiled_input[i * rows:(i + 1) * rows, 0:cols] = \ np.fliplr(tiled_input[i * rows:(i + 1) * rows, 0:cols]) # Right hand side tiles tiled_input[i * rows:(i + 1) * rows, -cols:] = \ np.fliplr(tiled_input[i * rows:(i + 1) * rows, -cols:]) # All those on the top and bottom need to be flipped up-to-down for i in range(3): # Top row tiled_input[0:rows, i * cols:(i + 1) * cols] = \ np.flipud(tiled_input[0:rows, i * cols:(i + 1) * cols]) # Bottom row tiled_input[-rows:, i * cols:(i + 1) * cols] = \ np.flipud(tiled_input[-rows:, i * cols:(i + 1) * cols]) # The central array should be unchanged. assert (np.array_equal(input, tiled_input[rows:2 * rows, cols:2 * cols])) # All sides of the middle array should be the same as those bordering them. # Check this starting at the top and going around clockwise. This can be # visually checked by plotting the 'tiled_input' array. assert (np.array_equal(input[0, :], tiled_input[rows - 1, cols:2 * cols])) assert (np.array_equal(input[:, -1], tiled_input[rows:2 * rows, 2 * cols])) assert (np.array_equal(input[-1, :], tiled_input[2 * rows, cols:2 * cols])) assert (np.array_equal(input[:, 0], tiled_input[rows:2 * rows, cols - 1])) return tiled_input def convolve(input, weights, mask=None, slow=False): """2 dimensional convolution. This is a Python implementation of what will be written in Fortran. Borders are handled with reflection. Masking is supported in the following way: * Masked points are skipped. * Parts of the input which are masked have weight 0 in the kernel. * Since the kernel as a whole needs to have value 1, the weights of the masked parts of the kernel are evenly distributed over the non-masked parts. Adapted from https://github.com/nicjhan/gaussian-filter """ assert (len(input.shape) == 2) assert (len(weights.shape) == 2) # Only one reflection is done on each side so the weights array cannot be # bigger than width/height of input +1. assert (weights.shape[0] < input.shape[0] + 1) assert (weights.shape[1] < input.shape[1] + 1) if mask is not None: # The slow convolve does not support masking. assert (not slow) assert (input.shape == mask.shape) tiled_mask = tile_and_reflect(mask) output = np.copy(input) tiled_input = tile_and_reflect(input) rows = input.shape[0] cols = input.shape[1] # Stands for half weights row. hw_row = np.int(weights.shape[0] / 2) hw_col = np.int(weights.shape[1] / 2) # Stands for full weights row. fw_row = weights.shape[0] fw_col = weights.shape[0] # Now do convolution on central array. # Iterate over tiled_input. for i, io in zip(list(range(rows, rows * 2)), list(range(rows))): for j, jo in zip(list(range(cols, cols * 2)), list(range(cols))): # The current central pixel is at (i, j) # Skip masked points. if mask is not None and tiled_mask[i, j]: continue average = 0.0 if slow: # Iterate over weights/kernel. for k in range(weights.shape[0]): # NOQA for l in range(weights.shape[1]): # NOQA # Get coordinates of tiled_input array that match given # weights m = i + k - hw_row n = j + l - hw_col average += tiled_input[m, n] * weights[k, l] else: # Find the part of the tiled_input array that overlaps with the # weights array. overlapping = tiled_input[ i - hw_row:i - hw_row + fw_row, j - hw_col:j - hw_col + fw_col] assert (overlapping.shape == weights.shape) # If any of 'overlapping' is masked then set the corresponding # points in the weights matrix to 0 and redistribute these to # non-masked points. if mask is not None: overlapping_mask = tiled_mask[ i - hw_row:i - hw_row + fw_row, j - hw_col:j - hw_col + fw_row] assert (overlapping_mask.shape == weights.shape) # Total value and number of weights clobbered by the mask. clobber_total = np.sum(weights[overlapping_mask]) remaining_num = np.sum(np.logical_not(overlapping_mask)) # This is impossible since at least i, j is not masked. assert (remaining_num > 0) correction = clobber_total / remaining_num # It is OK if nothing is masked - the weights will not be # changed. if correction == 0: assert (not overlapping_mask.any()) # Redistribute to non-masked points. tmp_weights = np.copy(weights) tmp_weights[overlapping_mask] = 0.0 tmp_weights[np.where(tmp_weights != 0)] += correction # Should be very close to 1. May not be exact due to # rounding. assert (abs(np.sum(tmp_weights) - 1) < 1e-15) else: tmp_weights = weights merged = tmp_weights[:] * overlapping average = np.sum(merged) # Set new output value. output[io, jo] = average return output def create_smooth_contour( shakemap_layer, output_file_path='', active_band=1, smoothing_method=NUMPY_SMOOTHING, smoothing_sigma=0.9): """Create contour from a shake map layer by using smoothing method. :param shakemap_layer: The shake map raster layer. :type shakemap_layer: QgsRasterLayer :param active_band: The band which the data located, default to 1. :type active_band: int :param smoothing_method: The smoothing method that wanted to be used. :type smoothing_method: NONE_SMOOTHING, NUMPY_SMOOTHING, SCIPY_SMOOTHING :param smooth_sigma: parameter for gaussian filter used in smoothing function. :type smooth_sigma: float :returns: The contour of the shake map layer path. :rtype: basestring """ timestamp = datetime.now() temp_smoothed_shakemap_path = unique_filename( prefix='temp-shake-map' + timestamp.strftime('%Y%m%d-%H%M%S'), suffix='.tif', dir=temp_dir('temp')) temp_smoothed_shakemap_path = smooth_shakemap( shakemap_layer.source(), output_file_path=temp_smoothed_shakemap_path, active_band=active_band, smoothing_method=smoothing_method, smoothing_sigma=smoothing_sigma ) return shakemap_contour( temp_smoothed_shakemap_path, output_file_path=output_file_path, active_band=active_band ) def smooth_shakemap( shakemap_layer_path, output_file_path='', active_band=1, smoothing_method=NUMPY_SMOOTHING, smoothing_sigma=0.9): """Make a smoother shakemap layer from a shake map. :param shakemap_layer_path: The shake map raster layer path. :type shakemap_layer_path: basestring :param active_band: The band which the data located, default to 1. :type active_band: int :param smoothing_method: The smoothing method that wanted to be used. :type smoothing_method: NONE_SMOOTHING, NUMPY_SMOOTHING, SCIPY_SMOOTHING :param smooth_sigma: parameter for gaussian filter used in smoothing function. :type smooth_sigma: float :returns: The contour of the shake map layer. :rtype: QgsRasterLayer """ # Set output path if not output_file_path: output_file_path = unique_filename(suffix='.tiff', dir=temp_dir()) # convert to numpy shakemap_file = gdal.Open(shakemap_layer_path) shakemap_array = np.array( shakemap_file.GetRasterBand(active_band).ReadAsArray()) # do smoothing if smoothing_method == NUMPY_SMOOTHING: smoothed_array = convolve(shakemap_array, gaussian_kernel( smoothing_sigma)) else: smoothed_array = shakemap_array # Create smoothed shakemap raster layer driver = gdal.GetDriverByName('GTiff') smoothed_shakemap_file = driver.Create( output_file_path, shakemap_file.RasterXSize, shakemap_file.RasterYSize, 1, gdal.GDT_Float32 # Important, since the default is integer ) smoothed_shakemap_file.GetRasterBand(1).WriteArray(smoothed_array) # CRS smoothed_shakemap_file.SetProjection(shakemap_file.GetProjection()) smoothed_shakemap_file.SetGeoTransform(shakemap_file.GetGeoTransform()) smoothed_shakemap_file.FlushCache() del smoothed_shakemap_file if not os.path.isfile(output_file_path): raise FileNotFoundError(tr( 'The smoothed shakemap is not created. It should be at ' '{output_file_path}'.format(output_file_path=output_file_path))) return output_file_path def shakemap_contour(shakemap_layer_path, output_file_path='', active_band=1): """Creating contour from a shakemap layer. :param shakemap_layer_path: The shake map raster layer path. :type shakemap_layer_path: basestring :param output_file_path: The path where the contour will be saved. :type output_file_path: basestring :param active_band: The band which the data located, default to 1. :type active_band: int :returns: The contour of the shake map layer path. :rtype: basestring """ # Set output path if not output_file_path: # There are minor issues with shapefile, so we switch to gpkg # See https://github.com/inasafe/inasafe/issues/5063 output_file_path = unique_filename(suffix='.gpkg', dir=temp_dir()) output_directory = os.path.dirname(output_file_path) output_file_name = os.path.basename(output_file_path) output_base_name = os.path.splitext(output_file_name)[0] # Based largely on # http://svn.osgeo.org/gdal/trunk/autotest/alg/contour.py # Use Geopackage driver to overcome this: # See https://github.com/inasafe/inasafe/issues/5063 driver = ogr.GetDriverByName('GPKG') ogr_dataset = driver.CreateDataSource(output_file_path) if ogr_dataset is None: # Probably the file existed and could not be overriden raise ContourCreationError( 'Could not create datasource for:\n%s. Check that the file ' 'does not already exist and that you do not have file system ' 'permissions issues' % output_file_path) # Set default fid options = ['FID={}'.format(contour_id_field['field_name'])] layer = ogr_dataset.CreateLayer('contour', options=options) for contour_field in contour_fields: field_definition = create_ogr_field_from_definition(contour_field) layer.CreateField(field_definition) shakemap_data = gdal.Open(shakemap_layer_path, GA_ReadOnly) # see http://gdal.org/java/org/gdal/gdal/gdal.html for these options contour_interval = 0.5 contour_base = 0 fixed_level_list = [] use_no_data_flag = 0 no_data_value = -9999 id_field = 0 # first field defined above elevation_field = 1 # second (MMI) field defined above try: gdal.ContourGenerate( shakemap_data.GetRasterBand(active_band), contour_interval, contour_base, fixed_level_list, use_no_data_flag, no_data_value, layer, id_field, elevation_field) except Exception as e: LOGGER.exception('Contour creation failed') raise ContourCreationError(str(e)) finally: ogr_dataset.Release() # Copy over the standard .prj file since ContourGenerate does not # create a projection definition projection_path = os.path.join( output_directory, output_base_name + '.prj') source_projection_path = resources_path( 'converter_data', 'mmi-contours.prj') shutil.copyfile(source_projection_path, projection_path) # Lastly copy over the standard qml (QGIS Style file) qml_path = os.path.join( output_directory, output_base_name + '.qml') source_qml_path = resources_path('converter_data', 'mmi-contours.qml') shutil.copyfile(source_qml_path, qml_path) # Create metadata file create_contour_metadata(output_file_path) # Now update the additional columns - X,Y, ROMAN and RGB try: set_contour_properties(output_file_path) except InvalidLayerError: raise del shakemap_data return output_file_path def set_contour_properties(contour_file_path): """Set the X, Y, RGB, ROMAN attributes of the contour layer. :param contour_file_path: Path of the contour layer. :type contour_file_path: str :raise: InvalidLayerError if anything is amiss with the layer. """ LOGGER.debug( 'Set_contour_properties requested for %s.' % contour_file_path) layer = QgsVectorLayer(contour_file_path, 'mmi-contours', "ogr") if not layer.isValid(): raise InvalidLayerError(contour_file_path) layer.startEditing() # Now loop through the db adding selected features to mem layer request = QgsFeatureRequest() for feature in layer.getFeatures(request): if not feature.isValid(): LOGGER.debug('Skipping feature') continue # Work out x and y line = feature.geometry().asPolyline() y = line[0].y() x_max = line[0].x() x_min = x_max for point in line: if point.y() < y: y = point.y() x = point.x() if x < x_min: x_min = x if x > x_max: x_max = x x = x_min + ((x_max - x_min) / 2) # Get length length = feature.geometry().length() mmi_value = float(feature[contour_mmi_field['field_name']]) # We only want labels on the whole number contours if mmi_value != round(mmi_value): roman = '' else: roman = romanise(mmi_value) # RGB from http://en.wikipedia.org/wiki/Mercalli_intensity_scale rgb = mmi_colour(mmi_value) # Now update the feature feature_id = feature.id() layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_x_field), x) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_y_field), y) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_colour_field), rgb) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_roman_field), roman) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_halign_field), 'Center') layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_valign_field), 'HALF') layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_length_field), length) layer.commitChanges() def create_contour_metadata(contour_path): """Create metadata file for contour layer. :param contour_path: Path where the contour is located. :type contour_path: basestring """ metadata = { 'title': tr('Earthquake Contour'), 'layer_purpose': layer_purpose_earthquake_contour['key'], 'layer_geometry': layer_geometry_line['key'], 'layer_mode': layer_mode_classified['key'], 'inasafe_fields': {} } for contour_field in contour_fields: metadata['inasafe_fields'][contour_field['key']] = contour_field[ 'field_name'] write_iso19115_metadata(contour_path, metadata)	AIFDR/inasafe	safe/gis/raster/contour.py	Python	gpl-3.0	18,679	[ "Gaussian" ]	61ad390e4f573a37be00e1e748a00f5c41563a5635e07af7e996311935e6f936
# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from spack import * class RSummarizedexperiment(RPackage): """SummarizedExperiment container. The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.""" homepage = "https://bioconductor.org/packages/SummarizedExperiment" git = "https://git.bioconductor.org/packages/SummarizedExperiment.git" version('1.18.2', commit='e22fafe') version('1.14.1', commit='2c68d99e11c7345e5ed388370822ea48395c64a4') version('1.12.0', commit='5f8416864636add121ec1d6737ebb89a42227fd7') version('1.10.1', commit='7ad2e991c8285bfc4b2e15b29d94cc86d07f8f2b') version('1.8.1', commit='9d8a29aa9c78bbc7dcc6472537e13fc0d11dc1f7') version('1.6.5', commit='ec69cd5cfbccaef148a9f6abdfb3e22e888695d0') depends_on('r@3.2:', type=('build', 'run')) depends_on('r-genomicranges@1.27.22:', type=('build', 'run')) depends_on('r-biobase', type=('build', 'run')) depends_on('r-delayedarray@0.1.9:', type=('build', 'run')) depends_on('r-matrix', type=('build', 'run')) depends_on('r-biocgenerics@0.15.3:', type=('build', 'run')) depends_on('r-s4vectors@0.13.13:', type=('build', 'run')) depends_on('r-iranges@2.7.2:', type=('build', 'run')) depends_on('r-genomeinfodb@1.11.4:', type=('build', 'run')) depends_on('r-genomicranges@1.29.14:', when='@1.8.1:', type=('build', 'run')) depends_on('r-delayedarray@0.3.20:', when='@1.8.1:', type=('build', 'run')) depends_on('r-iranges@2.11.17:', when='@1.8.1:', type=('build', 'run')) depends_on('r-genomeinfodb@1.13.1:', when='@1.8.1:', type=('build', 'run')) depends_on('r-genomicranges@1.31.17:', when='@1.10.1:', type=('build', 'run')) depends_on('r-s4vectors@0.17.25:', when='@1.10.1:', type=('build', 'run')) depends_on('r-iranges@2.13.16:', when='@1.10.1:', type=('build', 'run')) depends_on('r-genomicranges@1.33.6:', when='@1.12.0:', type=('build', 'run'))	iulian787/spack	var/spack/repos/builtin/packages/r-summarizedexperiment/package.py	Python	lgpl-2.1	2,278	[ "Bioconductor" ]	822b0de0d413974025eb6111d683bbb51713ed1eebc3db6bf9b50b02c38ebe2a
# -- coding: utf-8 -- # SPDX-FileCopyrightText: 2016-2019 The Atlite Authors # # SPDX-License-Identifier: GPL-3.0-or-later """ Base class for Atlite. """ # There is a binary incompatibility between the pip wheels of netCDF4 and # rasterio, which leads to the first one to work correctly while the second # loaded one fails by loading netCDF4 first, we ensure that most of atlite's # functionality works fine, even when the pip wheels have been used, only for # resampling the sarah dataset it is important to use conda. # Refer to # https://github.com/pydata/xarray/issues/2535, # https://github.com/rasterio/rasterio-wheels/issues/12 import xarray as xr import pandas as pd import numpy as np import dask import rasterio as rio import geopandas as gpd from tempfile import mktemp from numpy import atleast_1d, append from warnings import warn from shapely.geometry import box from pathlib import Path from pyproj import CRS from .utils import CachedAttribute from .data import cutout_prepare, available_features from .gis import get_coords, compute_indicatormatrix, compute_availabilitymatrix from .convert import (convert_and_aggregate, heat_demand, hydro, temperature, wind, pv, runoff, solar_thermal, soil_temperature) from .datasets import modules as datamodules import logging logger = logging.getLogger(__name__) class Cutout: """ Cutout base class. This class builds the starting point for most atlite functionalities. """ def __init__(self, path, cutoutparams): """ Provide an Atlite cutout object. Create a cutout object to use atlite operations on it. Based on the provided parameters, atlite first checks whether this cutout already exists on disk and if yes, loads this cutout. If the cutout does not yet exist on disk, then atlite creates an "unprepared" cutout object. This does not yet contain the full data. The process of preparing (loading the data) can then be started with `cutout.prepare()`. Parameters ---------- path : str \| path-like NetCDF from which to load or where to store the cutout. module : str or list The dataset(s) which works as a basis for the cutout. Available modules are "era5", "sarah" and "gebco". This is necessary when building a new cutout. If more than one module is given, their order determines how atlite fills up missing features when preparing the cutout with `Cutout.prepare()`. For example `influx_diffuse` is provided by the `sarah` and the `era5` module. Prioritizing sarah and setting module=['sarah', 'era5'] will load `influx_diffuse` from the sarah module and ignoring the era5 'influx_diffuse' data. time : str \| slice Time range to include in the cutout, e.g. "2011" or ("2011-01-05", "2011-01-25") This is necessary when building a new cutout. bounds : GeoSeries.bounds \| DataFrame, optional The outer bounds of the cutout or as a DataFrame containing (min.long, min.lat, max.long, max.lat). x : slice, optional Outer longitudinal bounds for the cutout (west, east). y : slice, optional Outer latitudinal bounds for the cutout (south, north). dx : float, optional Step size of the x coordinate. The default is 0.25. dy : float, optional Step size of the y coordinate. The default is 0.25. dt : str, optional Frequency of the time coordinate. The default is 'h'. Valid are all pandas offset aliases. chunks : dict Chunks when opening netcdf files. For cutout preparation recommand to chunk only along the time dimension. Defaults to {'time': 20} data : xr.Dataset User provided cutout data. Save the cutout using `Cutout.to_file()` afterwards. Other Parameters ---------------- sanitize : bool, default True Whether to sanitize the data when preparing the cutout. Takes effect for 'era5' data loading. sarah_dir : str, Path Directory of on-disk sarah data. This must be given when using the sarah module. sarah_interpolate : bool, default True Whether to interpolate NaN's in the SARAH data. This takes effect for sarah data which has missing data for areas where dawn and nightfall happens (ca. 30 min gap). gebco_path: str Path to find the gebco netcdf file. Only necessary when including the gebco module. parallel : bool, default False Whether to open dataset in parallel mode. Take effect for all xr.open_mfdataset usages. """ name = cutoutparams.get("name", None) cutout_dir = cutoutparams.get("cutout_dir", None) if cutout_dir or name or Path(path).is_dir(): raise ValueError( "Old style format not supported. You can migrate the old " "cutout directory using the function " "`atlite.utils.migrate_from_cutout_directory()`. The argument " "`cutout_dir` and `name` have been deprecated in favour of `path`.") path = Path(path).with_suffix(".nc") chunks = cutoutparams.pop('chunks', {'time': 100}) storable_chunks = {f'chunksize_{k}': v for k, v in (chunks or {}).items()} # Backward compatibility for xs, ys, months and years if {'xs', 'ys'}.intersection(cutoutparams): warn( "The arguments `xs` and `ys` have been deprecated in favour of " "`x` and `y`", DeprecationWarning) if 'xs' in cutoutparams: cutoutparams['x'] = cutoutparams.pop('xs') if 'ys' in cutoutparams: cutoutparams['y'] = cutoutparams.pop('ys') if {'years', 'months'}.intersection(cutoutparams): warn("The arguments `years` and `months` have been deprecated in " "favour of `time`", DeprecationWarning) assert 'years' in cutoutparams months = cutoutparams.pop("months", slice(1, 12)) years = cutoutparams.pop("years") cutoutparams["time"] = slice(f"{years.start}-{months.start}", f"{years.stop}-{months.stop}") # Three cases. First, cutout exists -> take the data. # Second, data is given -> take it. Third, else -> build a new cutout if path.is_file(): data = xr.open_dataset(str(path), chunks=chunks) data.attrs.update(storable_chunks) if cutoutparams: warn(f'Arguments {", ".join(cutoutparams)} are ignored, since ' 'cutout is already built.') elif 'data' in cutoutparams: data = cutoutparams.pop('data') else: logger.info(f"Building new cutout {path}") if 'bounds' in cutoutparams: x1, y1, x2, y2 = cutoutparams.pop('bounds') cutoutparams.update(x=slice(x1, x2), y=slice(y1, y2)) try: x = cutoutparams.pop('x') y = cutoutparams.pop('y') time = cutoutparams.pop('time') module = cutoutparams.pop('module') except KeyError as exc: raise TypeError("Arguments 'time' and 'module' must be " "specified. Spatial bounds must either be " "passed via argument 'bounds' or 'x' and 'y'.") from exc # TODO: check for dx, dy, x, y fine with module requirements coords = get_coords(x, y, time, cutoutparams) attrs = {'module': module, 'prepared_features': [], storable_chunks, cutoutparams} data = xr.Dataset(coords=coords, attrs=attrs) # Check compatibility of CRS modules = atleast_1d(data.attrs.get('module')) crs = set(CRS(datamodules[m].crs) for m in modules) assert len(crs) == 1, f'CRS of {module} not compatible' self.path = path self.data = data @property def name(self): return self.path.stem @property def module(self): return self.data.attrs.get('module') @property def crs(self): return CRS(datamodules[atleast_1d(self.module)[0]].crs) @property def available_features(self): return available_features(self.module) @property def chunks(self): chunks = {k.lstrip('chunksize_'): v for k, v in self.data.attrs.items() if k.startswith('chunksize_')} return None if chunks == {} else chunks @property def coords(self): return self.data.coords @property def meta(self): warn("The `meta` attribute is deprecated in favour of direct " "access to `data`", DeprecationWarning) return xr.Dataset(self.coords, attrs=self.data.attrs) @property def shape(self): return len(self.coords["y"]), len(self.coords["x"]) @property def extent(self): """Total extent of the area covered by the cutout (x, X, y, Y).""" xs, ys = self.coords['x'].values, self.coords['y'].values dx , dy = self.dx, self.dy return np.array([xs[0]-dx/2, xs[-1]+dx/2, ys[0]-dy/2, ys[-1]+dy/2]) @property def bounds(self): """Total bounds of the area covered by the cutout (x, y, X, Y).""" return self.extent[[0,2,1,3]] @property def transform(self): """Get the affine transform of the cutout. """ return rio.Affine(self.dx, 0, self.coords['x'].values[0] - self.dx/2, 0, self.dy, self.coords['y'].values[0] - self.dy/2) @property def transform_r(self): """Get the affine transform of the cutout with reverse y-order.""" return rio.Affine(self.dx, 0, self.coords['x'].values[0] - self.dx/2, 0, -self.dy, self.coords['y'].values[-1] + self.dy/2) @property def dx(self): x = self.coords['x'] return round((x[-1] - x[0]).item() / (x.size - 1), 8) @property def dy(self): y = self.coords['y'] return round((y[-1] - y[0]).item() / (y.size - 1), 8) @property def dt(self): return pd.infer_freq(self.coords['time'].to_index()) @property def prepared(self): return (self.prepared_features.sort_index() .equals(self.available_features.sort_index())) @property def prepared_features(self): index = [(self.data[v].attrs['module'], self.data[v].attrs['feature']) for v in self.data] index = pd.MultiIndex.from_tuples(index, names=['module', 'feature']) return pd.Series(list(self.data), index, dtype=object) def grid_coordinates(self): warn("The function `grid_coordinates` has been deprecated in favour of " "`grid`", DeprecationWarning) logger.warning("The order of elements returned by `grid_coordinates` changed. " "Check the output of your workflow for correctness.") return self.grid[['x', 'y']].values def grid_cells(self): warn("The function `grid_cells` has been deprecated in favour of `grid`", DeprecationWarning) logger.warning("The order of elements in `grid_cells` changed. " "Check the output of your workflow for correctness.") return self.grid.geometry.to_list() @CachedAttribute def grid(self): xs, ys = np.meshgrid(self.coords["x"], self.coords["y"]) coords = np.asarray((np.ravel(xs), np.ravel(ys))).T span = (coords[self.shape[1] + 1] - coords[0]) / 2 cells = [box(c) for c in np.hstack((coords - span, coords + span))] return gpd.GeoDataFrame({'x': coords[:, 0], 'y': coords[:, 1], 'geometry': cells,}, crs=self.crs) def sel(self, path=None, bounds=None, buffer=0, kwargs): ''' Select parts of the cutout. Parameters ---------- path : str \| path-like File where to store the sub-cutout. Defaults to a temporary file. bounds : GeoSeries.bounds \| DataFrame, optional The outer bounds of the cutout or as a DataFrame containing (min.long, min.lat, max.long, max.lat). buffer : float, optional Buffer around the bounds. The default is 0. kwargs : Passed to `xr.Dataset.sel` for data selection. Returns ------- selected : Cutout Selected cutout. ''' if path is None: path = mktemp(prefix=f"{self.path.stem}-", suffix=self.path.suffix, dir=self.path.parent) if bounds is not None: if buffer > 0: bounds = box(bounds).buffer(buffer).bounds x1, y1, x2, y2 = bounds kwargs.update(x=slice(x1, x2), y=slice(y1, y2)) data = self.data.sel(kwargs) return Cutout(path, data=data) def merge(self, other, path=None, kwargs): ''' Merge two cutouts into a single cutout. Parameters ---------- other : atlite.Cutout Other cutout to merge. path : str \| path-like File where to store the merged cutout. Defaults to a temporary file. kwargs Keyword arguments passed to `xarray.merge()`. Returns ------- merged : Cutout Merged cutout. ''' assert isinstance(other, Cutout) if path is None: path = mktemp(prefix=f"{self.path.stem}-", suffix=self.path.suffix, dir=self.path.parent) attrs = {self.data.attrs, *other.data.attrs} attrs['module'] = list(set(append(atleast_1d(self.module, other.module)))) features = self.prepared_features.index.unique('feature') otherfeatures = other.prepared_features.index.unique('feature') attrs['prepared_features'] = list(features.union(otherfeatures)) data = self.data.merge(other.data, kwargs).assign_attrs(attrs) return Cutout(path, data=data) def to_file(self, fn=None): ''' Save cutout to a netcdf file. Parameters ---------- fn : str \| path-like File name where to store the cutout, defaults to `cutout.path`. ''' if fn is None: fn = self.path self.data.to_netcdf(fn) def __repr__(self): start = np.datetime_as_string(self.coords['time'].values[0], unit='D') end = np.datetime_as_string(self.coords['time'].values[-1], unit='D') return ('<Cutout "{}">\n' ' x = {:.2f} ⟷ {:.2f}, dx = {:.2f}\n' ' y = {:.2f} ⟷ {:.2f}, dy = {:.2f}\n' ' time = {} ⟷ {}, dt = {}\n' ' module = {}\n' ' prepared_features = {}' .format(self.name, self.coords['x'].values[0], self.coords['x'].values[-1], self.dx, self.coords['y'].values[0], self.coords['y'].values[-1], self.dy, start, end, self.dt, self.module, list(self.prepared_features.index.unique('feature')))) def indicatormatrix(self, shapes, shapes_crs=4326): """ Compute the indicatormatrix. The indicatormatrix I[i,j] is a sparse representation of the ratio of the area in orig[j] lying in dest[i], where orig and dest are collections of polygons, i.e. A value of I[i,j] = 1 indicates that the shape orig[j] is fully contained in shape dest[j]. Note that the polygons must be in the same crs. Parameters --------- shapes : Collection of shapely polygons Returns ------- I : sp.sparse.lil_matrix Indicatormatrix """ return compute_indicatormatrix(self.grid, shapes, self.crs, shapes_crs) def uniform_layout(self): """Get a uniform capacity layout for all grid cells.""" return xr.DataArray(1, [self.coords['y'], self.coords['x']]) def layout_from_capacity_list(self, data, col='Capacity'): """ Get a capacity layout aligned to the cutout based on a capacity list. Parameters ---------- data : pandas.DataFrame Capacity list with columns 'x', 'y' and col. Each capacity entry is added to the grid cell intersecting with the coordinate (x,y). col : str, optional Name of the column with capacity values. The default is 'Capacity'. Returns ------- xr.DataArray Capacity layout with dimensions 'x' and 'y' indicating the total capacity placed within one grid cell. Example ------- >>> import atlite >>> import powerplantmatching as pm >>> data = pm.data.OPSD_VRE_country('DE') >>> data = (data.query('Fueltype == "Solar"') .rename(columns={'lon':'x', 'lat':'y'})) >>> cutout = atlite.Cutout('Germany', x = slice(-5, 15), y = slice(40, 55), time='2013-06-01', module='era5') >>> cutout.prepare(features=['influx', 'temperature']) >>> layout = cutout.layout_from_capacity_list(data) >>> pv = cutout.pv('CdTe', 'latitude_optimal', layout=layout) >>> pv.plot() """ with dask.config.set(**{'array.slicing.split_large_chunks': False}): nearest = (self.uniform_layout().chunk() .sel({'x': data.x.values, 'y': data.y.values}, 'nearest')) data = (data.assign(x=nearest.x.data, y=nearest.y.data) .groupby(['y', 'x'])[col].sum()) return data.to_xarray().reindex_like(self.data).fillna(0) availabilitymatrix = compute_availabilitymatrix # Preparation functions prepare = cutout_prepare # Conversion and aggregation functions convert_and_aggregate = convert_and_aggregate heat_demand = heat_demand temperature = temperature soil_temperature = soil_temperature solar_thermal = solar_thermal wind = wind pv = pv runoff = runoff hydro = hydro	FRESNA/atlite	atlite/cutout.py	Python	gpl-3.0	18,723	[ "NetCDF" ]	fa0ce0dd611a34f2b050fc135f65e2aed2ba29d12100772c6d8eef2f9a9df09c
__RCSID__ = "$Id$" import socket import select import time import os from DIRAC.Core.DISET.private.Transports.BaseTransport import BaseTransport from DIRAC.FrameworkSystem.Client.Logger import gLogger from DIRAC.Core.Utilities.ReturnValues import S_ERROR, S_OK class PlainTransport(BaseTransport): def initAsClient(self): timeout = None if 'timeout' in self.extraArgsDict: timeout = self.extraArgsDict['timeout'] try: self.oSocket = socket.create_connection(self.stServerAddress, timeout) except socket.error as e: if e.args[0] != 115: return S_ERROR("Can't connect: %s" % str(e)) #Connect in progress oL = select.select([], [self.oSocket], [], self.extraArgsDict['timeout'])[1] if len(oL) == 0: self.oSocket.close() return S_ERROR("Connection timeout") errno = self.oSocket.getsockopt(socket.SOL_SOCKET, socket.SO_ERROR) if errno != 0: return S_ERROR("Can't connect: %s" % str((errno, os.strerror(errno)))) self.remoteAddress = self.oSocket.getpeername() return S_OK(self.oSocket) def initAsServer(self): if not self.serverMode(): raise RuntimeError("Must be initialized as server mode") try: self.oSocket = socket.socket(socket.AF_INET6, socket.SOCK_STREAM) except socket.error: # IPv6 is probably disabled on this node, try IPv4 only instead self.oSocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) if self.bAllowReuseAddress: self.oSocket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.oSocket.bind(self.stServerAddress) self.oSocket.listen(self.iListenQueueSize) return S_OK(self.oSocket) def close(self): gLogger.debug("Closing socket") try: self.oSocket.shutdown(socket.SHUT_RDWR) except BaseException: pass self.oSocket.close() def setClientSocket(self, oSocket): if self.serverMode(): raise RuntimeError("Mustbe initialized as client mode") self.oSocket = oSocket if 'timeout' in self.extraArgsDict: self.oSocket.settimeout(self.extraArgsDict['timeout']) self.remoteAddress = self.oSocket.getpeername() def acceptConnection(self): # HACK: Was = PlainTransport( self ) oClientTransport = PlainTransport(self.stServerAddress) oClientSocket, stClientAddress = self.oSocket.accept() oClientTransport.setClientSocket(oClientSocket) return S_OK(oClientTransport) def _read(self, bufSize=4096, skipReadyCheck=False): start = time.time() timeout = False if 'timeout' in self.extraArgsDict: timeout = self.extraArgsDict['timeout'] while True: if timeout: if time.time() - start > timeout: return S_ERROR("Socket read timeout exceeded") try: data = self.oSocket.recv(bufSize) return S_OK(data) except socket.error as e: if e[0] == 11: time.sleep(0.001) else: return S_ERROR("Exception while reading from peer: %s" % str(e)) except Exception as e: return S_ERROR("Exception while reading from peer: %s" % str(e)) def _write(self, buf): sentBytes = 0 timeout = False if 'timeout' in self.extraArgsDict: timeout = self.extraArgsDict['timeout'] if timeout: start = time.time() while sentBytes < len(buf): try: if timeout: if time.time() - start > timeout: return S_ERROR("Socket write timeout exceeded") sent = self.oSocket.send(buf[sentBytes:]) if sent == 0: return S_ERROR("Connection closed by peer") if sent > 0: sentBytes += sent except socket.error as e: if e[0] == 11: time.sleep(0.001) else: return S_ERROR("Exception while sending to peer: %s" % str(e)) except Exception as e: return S_ERROR("Error while sending: %s" % str(e)) return S_OK(sentBytes) def checkSanity(args, *kwargs): return S_OK({}) def delegate(delegationRequest, kwargs): """ Check delegate! """ return S_OK()	fstagni/DIRAC	Core/DISET/private/Transports/PlainTransport.py	Python	gpl-3.0	4,076	[ "DIRAC" ]	cfd65e8191edeee8f91b2c7c23251d1293863b536f2ec1f8bda9fe03a9e808df
""" This is the boilerplate default configuration file. Changes and additions to settings should be done in the config module located in the application root rather than this config. """ config = { # webapp2 sessions 'webapp2_extras.sessions' : {'secret_key': 'Force_be_with'}, # webapp2 authentication 'webapp2_extras.auth' : {'user_model': 'boilerplate.models.User', 'cookie_name': 'session_name'}, # jinja2 templates 'webapp2_extras.jinja2' : {'template_path': ['templates','boilerplate/templates', 'admin/templates'], 'environment_args': {'extensions': ['jinja2.ext.i18n']}}, # application name 'app_name' : "reviewringer", # the default language code for the application. # should match whatever language the site uses when i18n is disabled 'app_lang' : 'en', # Locale code = <language>_<territory> (ie 'en_US') # to pick locale codes see http://cldr.unicode.org/index/cldr-spec/picking-the-right-language-code # also see http://www.sil.org/iso639-3/codes.asp # Language codes defined under iso 639-1 http://en.wikipedia.org/wiki/List_of_ISO_639-1_codes # Territory codes defined under iso 3166-1 alpha-2 http://en.wikipedia.org/wiki/ISO_3166-1 # disable i18n if locales array is empty or None 'locales' : ['en_US', 'es_ES', 'it_IT', 'zh_CN', 'id_ID', 'fr_FR', 'de_DE', 'ru_RU', 'pt_BR', 'cs_CZ'], # contact page email settings 'contact_sender' : "PUT_SENDER_EMAIL_HERE", 'contact_recipient' : "PUT_RECIPIENT_EMAIL_HERE", # Password AES Encryption Parameters 'aes_key' : "12_24_32_BYTES_KEY_FOR_PASSWORDS", 'salt' : "_PUT_SALT_HERE_TO_SHA512_PASSWORDS_", # get your own consumer key and consumer secret by registering at https://dev.twitter.com/apps # callback url must be: http://[YOUR DOMAIN]/login/twitter/complete 'twitter_consumer_key' : 'PUT_YOUR_TWITTER_CONSUMER_KEY_HERE', 'twitter_consumer_secret' : 'PUT_YOUR_TWITTER_CONSUMER_SECRET_HERE', #Facebook Login # get your own consumer key and consumer secret by registering at https://developers.facebook.com/apps #Very Important: set the site_url= your domain in the application settings in the facebook app settings page # callback url must be: http://[YOUR DOMAIN]/login/facebook/complete 'fb_api_key' : 'PUT_YOUR_FACEBOOK_PUBLIC_KEY_HERE', 'fb_secret' : 'PUT_YOUR_FACEBOOK_PUBLIC_KEY_HERE', #Linkedin Login #Get you own api key and secret from https://www.linkedin.com/secure/developer 'linkedin_api' : 'PUT_YOUR_LINKEDIN_PUBLIC_KEY_HERE', 'linkedin_secret' : 'PUT_YOUR_LINKEDIN_PUBLIC_KEY_HERE', # Github login # Register apps here: https://github.com/settings/applications/new 'github_server' : 'github.com', 'github_redirect_uri' : 'http://www.example.com/social_login/github/complete', 'github_client_id' : 'PUT_YOUR_GITHUB_CLIENT_ID_HERE', 'github_client_secret' : 'PUT_YOUR_GITHUB_CLIENT_SECRET_HERE', # get your own recaptcha keys by registering at http://www.google.com/recaptcha/ 'captcha_public_key' : "PUT_YOUR_RECAPCHA_PUBLIC_KEY_HERE", 'captcha_private_key' : "PUT_YOUR_RECAPCHA_PRIVATE_KEY_HERE", # Leave blank "google_analytics_domain" if you only want Analytics code 'google_analytics_domain' : "YOUR_PRIMARY_DOMAIN (e.g. google.com)", 'google_analytics_code' : "UA-XXXXX-X", # add status codes and templates used to catch and display errors # if a status code is not listed here it will use the default app engine # stacktrace error page or browser error page 'error_templates' : { 403: 'errors/default_error.html', 404: 'errors/default_error.html', 500: 'errors/default_error.html', }, # Enable Federated login (OpenID and OAuth) # Google App Engine Settings must be set to Authentication Options: Federated Login 'enable_federated_login' : True, # jinja2 base layout template 'base_layout' : 'base.html', # send error emails to developers 'send_mail_developer' : False, # fellas' list 'developers' : ( ('Santa Klauss', 'snowypal@northpole.com'), ), # If true, it will write in datastore a log of every email sent 'log_email' : True, # If true, it will write in datastore a log of every visit 'log_visit' : True, # ----> ADD MORE CONFIGURATION OPTIONS HERE <---- } # end config	LuckDragon82/demo	config/localhost.py	Python	lgpl-3.0	4,151	[ "VisIt" ]	c70d2e63d2557596455290420b4700112f05bf3dca829fcd9fd18f60ba6d5347
# Copyright 2021 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os.path as osp import multiworld.envs.mujoco as mwmj import rlkit.util.hyperparameter as hyp from multiworld.envs.mujoco.cameras import sawyer_door_env_camera_v0 from rlkit.launchers.launcher_util import run_experiment import rlkit.torch.vae.vae_schedules as vae_schedules from rlkit.launchers.skewfit_experiments import \ skewfit_full_experiment from rlkit.torch.vae.conv_vae import imsize48_default_architecture if __name__ == "__main__": variant = dict( algorithm='Skew-Fit-SAC', double_algo=False, online_vae_exploration=False, imsize=48, env_id='SawyerDoorHookResetFreeEnv-v1', init_camera=sawyer_door_env_camera_v0, skewfit_variant=dict( save_video=True, custom_goal_sampler='replay_buffer', online_vae_trainer_kwargs=dict( beta=20, lr=1e-3, ), save_video_period=50, qf_kwargs=dict( hidden_sizes=[400, 300], ), policy_kwargs=dict( hidden_sizes=[400, 300], ), twin_sac_trainer_kwargs=dict( reward_scale=1, discount=0.99, soft_target_tau=1e-3, target_update_period=1, use_automatic_entropy_tuning=True, ), max_path_length=100, algo_kwargs=dict( batch_size=1024, num_epochs=170, num_eval_steps_per_epoch=500, num_expl_steps_per_train_loop=500, num_trains_per_train_loop=1000, min_num_steps_before_training=10000, vae_training_schedule=vae_schedules.custom_schedule, oracle_data=False, vae_save_period=50, parallel_vae_train=False, ), replay_buffer_kwargs=dict( start_skew_epoch=10, max_size=int(100000), fraction_goals_rollout_goals=0.2, fraction_goals_env_goals=0.5, exploration_rewards_type='None', vae_priority_type='vae_prob', priority_function_kwargs=dict( sampling_method='importance_sampling', decoder_distribution='gaussian_identity_variance', num_latents_to_sample=10, ), power=-0.5, relabeling_goal_sampling_mode='custom_goal_sampler', ), exploration_goal_sampling_mode='custom_goal_sampler', evaluation_goal_sampling_mode='presampled', training_mode='train', testing_mode='test', reward_params=dict( type='latent_distance', ), observation_key='latent_observation', desired_goal_key='latent_desired_goal', presampled_goals_path=osp.join( osp.dirname(mwmj.__file__), "goals", "door_goals.npy", ), presample_goals=True, vae_wrapped_env_kwargs=dict( sample_from_true_prior=True, ), ), train_vae_variant=dict( representation_size=16, beta=20, num_epochs=0, dump_skew_debug_plots=False, decoder_activation='gaussian', generate_vae_dataset_kwargs=dict( N=2, test_p=.9, use_cached=True, show=False, oracle_dataset=False, n_random_steps=1, non_presampled_goal_img_is_garbage=True, ), vae_kwargs=dict( decoder_distribution='gaussian_identity_variance', input_channels=3, architecture=imsize48_default_architecture, ), algo_kwargs=dict( lr=1e-3, ), save_period=1, ), ) search_space = { } sweeper = hyp.DeterministicHyperparameterSweeper( search_space, default_parameters=variant, ) n_seeds = 1 mode = 'local' exp_prefix = 'dev-{}'.format( __file__.replace('/', '-').replace('_', '-').split('.')[0] ) for exp_id, variant in enumerate(sweeper.iterate_hyperparameters()): for _ in range(n_seeds): run_experiment( skewfit_full_experiment, exp_prefix=exp_prefix, mode=mode, variant=variant, use_gpu=True, )	google-research/DBAP-algorithm	third_party/rlkit_library/examples/skewfit/sawyer_door.py	Python	apache-2.0	5,220	[ "Gaussian" ]	36815222cc8bc60bb7c582b9f511a6c9a9d150cf860b48da6cca4b61183b7845
import logging import multiprocessing import re import os import tempfile import yaml import sys from collections import OrderedDict import click import urllib # Adapted from: https://github.com/pnnl/atlas/blob/master/atlas/conf.py logging.basicConfig(level=logging.INFO, datefmt="%Y-%m-%d %H:%M", format="[%(asctime)s %(levelname)s] %(message)s") host = "ftp.sra.ebi.ac.uk" project = "PRJEB14409" #project = "PRJNA319605" # http://stackoverflow.com/a/3675423 def replace_last(source_string, replace_what, replace_with): head, _sep, tail = source_string.rpartition(replace_what) if _sep == '': return tail else: return head + replace_with + tail def get_ena(project): from urllib import request samples = "" try: samples = request.urlopen("http://www.ebi.ac.uk/ena/data/warehouse/filereport?accession=%s&result=read_run&fields=fastq_ftp" % project).readlines()[1:] except urllib.error.HTTPError: print("Not a valid ENA project") for sample in samples: for fastq in sample.strip().split(b';'): dirpath = os.path.dirname(fastq).decode("utf-8") filename = os.path.basename(fastq).decode("utf-8") yield (dirpath,"",[filename]) def get_sample_files(path, remote): samples = OrderedDict() seen = set() walker = "" if remote != None: walker = get_ena(remote) else: walker = os.walk(path, followlinks=True) for dir_name, sub_dirs, files in walker: for fname in files: if ".fastq" in fname or ".fq" in fname: sample_id = fname.partition(".fastq")[0] if ".fq" in sample_id: sample_id = fname.partition(".fq")[0].replace("_","-") sample_id = sample_id.replace("_R1", "").replace("_r1", "").replace("_R2", "").replace("_r2", "") sample_id = re.sub("_1$", "", sample_id) sample_id = re.sub("_2$", "", sample_id) sample_id = sample_id.replace("_", "-").replace(" ", "-") fq_path = os.path.join(dir_name, fname) fastq_paths = [fq_path] if fq_path in seen: continue if "_R1" in fname or "_r1" in fname or "_1" in fname: fname = replace_last(fname,"_1.","_2.") r2_path = os.path.join(dir_name, fname.replace("_R1", "_R2").replace("_r1", "_r2")) if not r2_path == fq_path: seen.add(r2_path) fastq_paths.append(r2_path) if "_R2" in fname or "_r2" in fname or "_2" in fname: fname = replace_last(fname,"_2.","_1.") r1_path = os.path.join(dir_name, fname.replace("_R2", "_R1").replace("_r2", "_r1")) if not r1_path == fq_path: seen.add(r1_path) fastq_paths.insert(0, r1_path) if sample_id in samples: logging.warn("Duplicate sample %s was found after renaming; skipping..." % sample_id) continue samples[sample_id] = {'path': fastq_paths } return samples def create_metadata_template(outfile, samples): with open(outfile, "w") as f: print("#SampleID\tAlias", file=f) for sample in samples: print("%s\t%s" % (sample,sample), file=f) @click.command() @click.option('--project', prompt="Give your project a unique name", required=True, help='Give your project a nice name') @click.option('--config', default="config.yaml", show_default=True, help='File to write the configuration to') @click.option('--remote', help='Specify a ENA project to use as remote data (for example PRJEB14409') @click.option('--path', default="../data", show_default=True, help='path to data folder') @click.option('--rename', required=False, help='provide a file for renaming samples') @click.option('--forward_primer', prompt="Which forward primer did you use?", required=True, default="CCTACGGGNGGCWGCAG", help="Which forward primer did you use?") @click.option('--reverse_primer', prompt="Which reverse primer did you use?", required=True, default="GACTACHVGGGTATCTAATCC", help="Which reverse primer did you use?") @click.option('--mergepairs', prompt="Choose wich method to use for stitching paired reads (vsearch, pandaseq)", required=True, default="vsearch", type=click.Choice(['pandaseq', 'vsearch', 'none']), help="Choose wich method to use for stitching paired reads") @click.option('--classification', prompt="Choose wich classification option you want to use (sina, stampa, rdp, blast)", required=True, type=click.Choice(['sina', 'stampa', 'rdp', 'blast']), help="Choose wich classification option you want to use") @click.option('--reference_db', prompt="Choose wich reference database to use (silva, unite)", required=True, type=click.Choice(['silva', 'unite']), help="Choose wich reference database to use") @click.option('--clustering', prompt="Choose wich clustering method you want to use (usearch_smallmem, swarm)", required=True, default="usearch_smallmem", type=click.Choice(['usearch_smallmem', 'swarm']), help="Choose wich clustering method you want to use") def make_config(project,config,path,remote, rename, forward_primer, reverse_primer, mergepairs, classification, reference_db, clustering): """Write the file `config` and complete the sample names and paths for all files in `path`.""" represent_dict_order = lambda self, data: self.represent_mapping('tag:yaml.org,2002:map', data.items()) yaml.add_representer(OrderedDict, represent_dict_order) path = os.path.realpath(path) conf = OrderedDict() samples = get_sample_files(path, remote) if rename: renamed = 0 for line in open(rename): sample, newname = line.split() if sample in samples: newname = newname.replace("_","-") samples[newname] = samples.pop(sample) renamed += 1 create_metadata_template("metadata.txt", samples.keys()) logging.info("Found %d samples under %s" % (len(samples), path if remote == None else "remote project %s " % remote)) if rename: logging.info("Renamed %d samples" % renamed) conf["project"] = project conf["minsize"] = 2 conf["adapters_fasta"] = "/data/ngs/adapters/contaminant_list.txt" conf["pandaseq_overlap"] = "10" conf["pandaseq_quality"] = "25" conf["pandaseq_minlength"] = "100" conf["pandaseq_maxlength"] = "700" conf["quality_control"] = OrderedDict() conf["quality_control"]["barcode"] = OrderedDict() conf["quality_control"]["barcode"]["threshold"] = 5 conf["quality_control"]["barcode"]["length"] = 8 conf["quality_control"]["barcode"]["seperator"] = "#" conf["quality_control"]["trimming"] = OrderedDict() conf["quality_control"]["trimming"]["quality"] = 25 conf["forward_primer"] = forward_primer conf["reverse_primer"] = reverse_primer conf["mergepairs"] = mergepairs conf["vsearch_minmergelen"] = "200" conf["metadata"] = "metadata.txt" if remote != None: conf["remote"] = True else: conf["remote"] = False conf["barcode_in_header"] = False conf["its"] = False conf["its_region"] = "ITS2" conf["clustering"] = clustering conf["classification"] = classification conf["use_full_lineage"] = False conf["rdp_confidence_cutoff"] = 0.80 conf["reference_db"] = reference_db conf["convert_to_casava1.8"] = False conf["data"] = samples with open(config, "w") as f: print(yaml.dump(conf, default_flow_style=False), file=f) logging.info("Configuration file written to %s" % config) if __name__ == "__main__": make_config()	nioo-knaw/hydra	conf.py	Python	mit	7,810	[ "BLAST" ]	21439bdfe8c043ee7defdea4c8918ad8d50dcb1cad23c72f055715701c5a66ea
""" Cost layers. TODO: write more documentation """ __docformat__ = 'restructedtext en' __authors__ = ("Razvan Pascanu " "KyungHyun Cho " "Caglar Gulcehre ") __contact__ = "Razvan Pascanu <r.pascanu@gmail>" import numpy import copy import logging import theano import theano.tensor as TT from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams from groundhog import utils from groundhog.utils import sample_weights, sample_weights_classic,\ init_bias, constant_shape, sample_zeros from .basic import Layer logger = logging.getLogger(__name__) class CostLayer(Layer): """ Base class for all cost layers """ def __init__(self, rng, n_in, n_out, scale, sparsity, rank_n_approx=0, rank_n_activ='lambda x: x', weight_noise=False, init_fn='sample_weights_classic', bias_fn='init_bias', bias_scale=0., sum_over_time=True, additional_inputs=None, grad_scale=1., use_nce=False, # added by Zhaopeng Tu, 2015-11-07 use_coverage_cost=False, name=None): """ :type rng: numpy random generator :param rng: numpy random generator used to sample weights :type n_in: int :param n_in: number of input units :type n_out: int :param n_out: number of output units :type scale: float or list of :param scale: depending on the initialization function, it can be the standard deviation of the Gaussian from which the weights are sampled or the largest singular value. If a single value it will be used for each layer, otherwise it has to have one value for each layer :type sparsity: int or list of :param sparsity: if a single value, it will be used for each layer, otherwise it has to be a list with as many values as layers. If negative, it means the weight matrix is dense. Otherwise it means this many randomly selected input units are connected to an output unit :type rank_n_approx: int :param rank_n_approx: It applies to the first layer only. If positive and larger than 0, the first weight matrix is factorized into two matrices. The first one goes from input to `rank_n_approx` hidden units, the second from `rank_n_approx` to the number of units on the second layer :type rank_n_activ: string or function :param rank_n_activ: Function that is applied on on the intermediary layer formed from factorizing the first weight matrix (Q: do we need this?) :type weight_noise: bool :param weight_noise: If true, the model is used with weight noise (and the right shared variable are constructed, to keep track of the noise) :type init_fn: string or function :param init_fn: function used to initialize the weights of the layer. We recommend using either `sample_weights_classic` or `sample_weights` defined in the utils :type bias_fn: string or function :param bias_fn: function used to initialize the biases. We recommend using `init_bias` defined in the utils :type bias_scale: float :param bias_scale: argument passed to `bias_fn`, depicting the scale of the initial bias :type sum_over_time: bool :param sum_over_time: flag, stating if, when computing the cost, we should take the sum over time, or the mean. If you have variable length sequences, please take the sum over time :type additional_inputs: None or list of ints :param additional_inputs: dimensionality of each additional input :type grad_scale: float or theano scalar :param grad_scale: factor with which the gradients with respect to the parameters of this layer are scaled. It is used for differentiating between the different parameters of a model. :type use_nce: bool :param use_nce: flag, if true, do not use MLE, but NCE-like cost :type name: string :param name: name of the layer (used to name parameters). NB: in this library names are very important because certain parts of the code relies on name to disambiguate between variables, therefore each layer should have a unique name. """ self.grad_scale = grad_scale assert rank_n_approx >= 0, "Please enter a valid rank_n_approx" self.rank_n_approx = rank_n_approx if type(rank_n_activ) is str: rank_n_activ = eval(rank_n_activ) self.rank_n_activ = rank_n_activ super(CostLayer, self).__init__(n_in, n_out, rng, name) self.trng = RandomStreams(self.rng.randint(int(1e6))) self.scale = scale if isinstance(bias_fn, str): self.bias_fn = eval(bias_fn) else: self.bias_fn = bias_fn self.bias_scale = bias_scale self.sum_over_time = sum_over_time self.weight_noise = weight_noise self.sparsity = sparsity if self.sparsity < 0: self.sparsity = n_out if type(init_fn) is str: init_fn = eval(init_fn) self.init_fn = init_fn self.additional_inputs = additional_inputs self.use_nce = use_nce # added by Zhaopeng Tu, 2015-11-07 self.use_coverage_cost = use_coverage_cost self._init_params() def _init_params(self): """ Initialize the parameters of the layer, either by using sparse initialization or small isotropic noise. """ # added by Zhaopeng Tu, 2015-11-29 if self.use_coverage_cost: self.CC = theano.shared(numpy.cast[theano.config.floatX](1.0), name='CC_%s' % self.name) self.params += [self.CC] if self.rank_n_approx: W_em1 = self.init_fn(self.n_in, self.rank_n_approx, self.sparsity, self.scale, self.rng) W_em2 = self.init_fn(self.rank_n_approx, self.n_out, self.sparsity, self.scale, self.rng) self.W_em1 = theano.shared(W_em1, name='W1_%s' % self.name) self.W_em2 = theano.shared(W_em2, name='W2_%s' % self.name) self.b_em = theano.shared( self.bias_fn(self.n_out, self.bias_scale, self.rng), name='b_%s' % self.name) self.params += [self.W_em1, self.W_em2, self.b_em] if self.weight_noise: self.nW_em1 = theano.shared(W_em10., name='noise_W1_%s' % self.name) self.nW_em2 = theano.shared(W_em0., name='noise_W2_%s' % self.name) self.nb_em = theano.shared(b_em0., name='noise_b_%s' % self.name) self.noise_params = [self.nW_em1, self.nW_em2, self.nb_em] self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] else: W_em = self.init_fn(self.n_in, self.n_out, self.sparsity, self.scale, self.rng) self.W_em = theano.shared(W_em, name='W_%s' % self.name) self.b_em = theano.shared( self.bias_fn(self.n_out, self.bias_scale, self.rng), name='b_%s' % self.name) self.params += [self.W_em, self.b_em] if self.weight_noise: self.nW_em = theano.shared(W_em0., name='noise_W_%s' % self.name) self.nb_em = theano.shared( numpy.zeros((self.n_out,), dtype=theano.config.floatX), name='noise_b_%s' % self.name) self.noise_params = [self.nW_em, self.nb_em] self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] self.additional_weights = [] self.noise_additional_weights = [] if self.additional_inputs: for pos, size in enumerate(self.additional_inputs): W_add = self.init_fn(size, self.n_out, self.sparsity, self.scale, self.rng) self.additional_weights += [theano.shared(W_add, name='W_add%d_%s'%(pos, self.name))] if self.weight_noise: self.noise_additional_weights += [ theano.shared(W_add0., name='noise_W_add%d_%s'%(pos, self.name))] self.params = self.params + self.additional_weights self.noise_params += self.noise_additional_weights self.noise_params_shape_fn += [ constant_shape(x.get_value().shape) for x in self.noise_additional_weights] self.params_grad_scale = [self.grad_scale for x in self.params] def compute_sample(self, state_below, temp=1, use_noise=False): """ Constructs the theano expression that samples from the output layer. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model """ raise NotImplemented def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=None, use_noise=True, additional_inputs=None, no_noise_bias=False): """ Computes the expression of the cost of the model (given the type of layer used). :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type target: tensor or layer :param target: The theano expression (or groundhog layer) representing the target (used to evaluate the prediction of the output layer) :type mask: None or mask or layer :param mask: Mask, depicting which of the predictions should be ignored (e.g. due to them resulting from padding a sequence with 0s) :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type reg: None or layer or theano scalar expression :param reg: additional regularization term that should be added to the cost :type scale: float or None or theano scalar :param scale: scaling factor with which the cost is multiplied :type sum_over_time: bool or None :param sum_over_time: this flag overwrites the value given to this property in the constructor of the class :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type additional_inputs: list theano variable or layers :param additional_inputs: list of theano variables or layers representing the additional inputs :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ raise NotImplemented def get_grads(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, additional_gradients=None, sum_over_time=None, use_noise=True, additional_inputs=None, # added by Zhaopeng Tu, 2015-11-07 coverages=None, c_mask=None, no_noise_bias=False): """ Computes the expression of the gradients of the cost with respect to all parameters of the model. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type target: tensor or layer :param target: The theano expression (or groundhog layer) representing the target (used to evaluate the prediction of the output layer) :type mask: None or mask or layer :param mask: Mask, depicting which of the predictions should be ignored (e.g. due to them resulting from padding a sequence with 0s) :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type reg: None or layer or theano scalar expression :param reg: additional regularization term that should be added to the cost :type scale: float or None or theano scalar :param scale: scaling factor with which the cost is multiplied :type additional_gradients: list of tuples of the form (param, gradient) :param additional_gradiens: A list of tuples. Each tuple has as its first element the parameter, and as second element a gradient expression that should be added to the gradient resulting from the cost. Not all parameters need to have an additional gradient. :type sum_over_time: bool or None :param sum_over_time: this flag overwrites the value given to this property in the constructor of the class :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ cost = self.get_cost(state_below, target, mask=mask, reg=reg, scale=scale, sum_over_time=sum_over_time, use_noise=use_noise, additional_inputs=additional_inputs, # added by Zhaopeng Tu, 2015-11-29 coverages=coverages, c_mask=c_mask, no_noise_bias=no_noise_bias) logger.debug("Get grads") grads = TT.grad(cost.mean(), self.params) logger.debug("Got grads") if additional_gradients: for p, gp in additional_gradients: if p in self.params: grads[self.params.index(p)] += gp if self.additional_gradients: for new_grads, to_replace, properties in self.additional_gradients: gparams, params = new_grads prop_expr = [x[1] for x in properties] replace = [(x[0], TT.grad(cost, x[1])) for x in to_replace] rval = theano.clone(gparams + prop_expr, replace=replace) gparams = rval[:len(gparams)] prop_expr = rval[len(gparams):] self.properties += [(x[0], y) for x, y in zip(properties, prop_expr)] for gp, p in zip(gparams, params): grads[self.params.index(p)] += gp self.cost = cost self.grads = grads return cost, grads def _get_samples(self, model, length=30, temp=1, inps): """ Sample a sequence from the model `model` whose output layer is given by `self`. :type model: groundhog model class :param model: model that has `self` as its output layer :type length: int :param length: length of the sequence to sample :type temp: float :param temp: temperature to use during sampling """ raise NotImplemented class LinearLayer(CostLayer): """ Linear output layer. """ def _init_params(self): """ Initialize the parameters of the layer, either by using sparse initialization or small isotropic noise. """ if self.rank_n_approx: W_em1 = self.init_fn(self.nin, self.rank_n_approx, self.sparsity, self.scale, self.rng) W_em2 = self.init_fn(self.rank_n_approx, self.nout, self.sparsity, self.scale, self.rng) self.W_em1 = theano.shared(W_em1, name='W1_%s'%self.name) self.W_em2 = theano.shared(W_em2, name='W2_%s'%self.name) self.b_em = theano.shared( numpy.zeros((self.nout,), dtype=theano.config.floatX), name='b_%s'%self.name) self.params += [self.W_em1, self.W_em2, self.b_em] self.myparams = []#[self.W_em1, self.W_em2, self.b_em] if self.weight_noise: self.nW_em1 = theano.shared(W_em10., name='noise_W1_%s'%self.name) self.nW_em2 = theano.shared(W_em0., name='noise_W2_%s'%self.name) self.nb_em = theano.shared(b_em0., name='noise_b_%s'%self.name) self.noise_params = [self.nW_em1, self.nW_em2, self.nb_em] self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] else: W_em = self.init_fn(self.nin, self.nout, self.sparsity, self.scale, self.rng) self.W_em = theano.shared(W_em, name='W_%s'%self.name) self.b_em = theano.shared( numpy.zeros((self.nout,), dtype=theano.config.floatX), name='b_%s'%self.name) self.add_wghs = [] self.n_add_wghs = [] if self.additional_inputs: for pos, sz in enumerate(self.additional_inputs): W_add = self.init_fn(sz, self.nout, self.sparsity, self.scale, self.rng) self.add_wghs += [theano.shared(W_add, name='W_add%d_%s'%(pos, self.name))] if self.weight_noise: self.n_add_wghs += [theano.shared(W_add0., name='noise_W_add%d_%s'%(pos, self.name))] self.params += [self.W_em, self.b_em] + self.add_wghs self.myparams = []#[self.W_em, self.b_em] + self.add_wghs if self.weight_noise: self.nW_em = theano.shared(W_em0., name='noise_W_%s'%self.name) self.nb_em = theano.shared(numpy.zeros((self.nout,), dtype=theano.config.floatX), name='noise_b_%s'%self.name) self.noise_params = [self.nW_em, self.nb_em] + self.n_add_wghs self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] def _check_dtype(self, matrix, inp): if 'int' in inp.dtype and inp.ndim==2: return matrix[inp.flatten()] elif 'int' in inp.dtype: return matrix[inp] elif 'float' in inp.dtype and inp.ndim == 3: shape0 = inp.shape[0] shape1 = inp.shape[1] shape2 = inp.shape[2] return TT.dot(inp.reshape((shape0shape1, shape2)), matrix) else: return TT.dot(inp, matrix) def fprop(self, state_below, temp = numpy.float32(1), use_noise=True, additional_inputs = None): """ Constructs the computational graph of this layer. """ if self.rank_n_approx: if use_noise and self.noise_params: emb_val = self._check_dtype(self.W_em1+self.nW_em1, state_below) emb_val = TT.dot(self.W_em2 + self.nW_em2, emb_val) else: emb_val = self._check_dtype(self.W_em1, state_below) emb_val = TT.dot(self.W_em2, emb_val) else: if use_noise and self.noise_params: emb_val = self._check_dtype(self.W_em + self.nW_em, state_below) else: emb_val = self._check_dtype(self.W_em, state_below) if additional_inputs: for st, wgs in zip(additional_inputs, self.add_wghs): emb_val += self._check_dtype(wgs, st) if use_noise and self.noise_params: emb_val = (emb_val + self.b_em+ self.nb_em) else: emb_val = (emb_val + self.b_em) self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def get_cost(self, state_below, target=None, mask = None, temp=1, reg = None, scale=None, sum_over_time=True, use_noise=True, additional_inputs=None): """ This function computes the cost of this layer. :param state_below: theano variable representing the input to the softmax layer :param target: theano variable representing the target for this layer :return: mean cross entropy """ class_probs = self.fprop(state_below, temp = temp, use_noise=use_noise, additional_inputs=additional_inputs) pvals = class_probs assert target, 'Computing the cost requires a target' if target.ndim == 3: target = target.reshape((target.shape[0]target.shape[1], target.shape[2])) assert 'float' in target.dtype cost = (class_probs - target)2 if mask: mask = mask.flatten() cost = cost TT.cast(mask, theano.config.floatX) if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim ==3: sh0 = TT.cast(state_below.shape[0], theano.config.floatX) sh1 = TT.cast(state_below.shape[1], theano.config.floatX) self.cost = cost.sum()/sh1 else: self.cost =cost.sum() else: self.cost = cost.mean() if scale: self.cost = self.costscale if reg: self.cost = self.cost + reg self.out = self.cost self.mask = mask self.cost_scale = scale return self.cost def get_grads(self, state_below, target, mask = None, reg = None, scale=None, sum_over_time=True, use_noise=True, additional_inputs=None): """ This function implements both the forward and backwards pass of this layer. The reason we do this in a single function is because for the factorized softmax layer is hard to rely on grad and get an optimized graph. For uniformity I've implemented this method for this layer as well (though one doesn't need to use it) :param state_below: theano variable representing the input to the softmax layer :param target: theano variable representing the target for this layer :return: cost, dC_dstate_below, param_grads, new_properties dC_dstate_below is a computational graph representing the gradient of the cost wrt to state_below param_grads is a list containing the gradients wrt to the different parameters of the layer new_properties is a dictionary containing additional properties of the model; properties are theano expression that are evaluated and reported by the model """ cost = self.get_cost(state_below, target, mask = mask, reg = reg, scale=scale, sum_over_time=sum_over_time, use_noise=use_noise, additional_inputs=additional_inputs) grads = TT.grad(cost, self.params) if self.additional_gradients: for new_grads, to_replace, properties in self.additional_gradients: gparams, params = new_grads prop_expr = [x[1] for x in properties] replace = [(x[0], TT.grad(cost, x[1])) for x in to_replace] rval = theano.clone(gparams + prop_expr, replace=replace) gparams = rval[:len(gparams)] prop_expr = rval[len(gparams):] self.properties += [(x[0], y) for x,y in zip(properties, prop_expr)] for gp, p in zip(gparams, params): grads[self.params.index(p)] += gp self.cost = cost self.grads = grads def Gvs_fn(args): w = (1 - self.model_output) * self.model_output * state_below.shape[1] Gvs = TT.Lop(self.model_output, self.params, TT.Rop(self.model_output, self.params, args)/w) return Gvs self.Gvs = Gvs_fn return cost, grads class SigmoidLayer(CostLayer): """ Sigmoid output layer. """ def _get_samples(self, model, length=30, temp=1, inps): """ See parent class. """ if not hasattr(model, 'word_indxs_src'): model.word_indxs_src = model.word_indxs character_level = False if hasattr(model, 'character_level'): character_level = model.character_level if model.del_noise: model.del_noise() if model.maintain_coverage: [values, probs, coverages] = model.sample_fn(length, temp, inps) else: [values, probs] = model.sample_fn(length, temp, inps) # Assumes values matrix #print 'Generated sample is:' #print if values.ndim > 1: for d in range(2): print('%d-th sentence' % d) print('Input: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k][d]] == '<eol>': break sen.append(model.word_indxs_src[inps[0][k][d]]) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print(model.word_indxs_src[inps[0][k][d]], end=' ') if model.word_indxs_src[inps[0][k][d]] == '<eol>': break print('') print('Output: ', end=' ') if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k][d]] == '<eol>': break sen.append(model.word_indxs[values[k][d]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k][d]], end=' ') if model.word_indxs[values[k][d]] == '<eol>': break print() print() else: print('Output: ', end=' ') coverage_step = 0 if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k]] == '<eol>': coverage_step = k break sen.append(model.word_indxs[values[k]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k]], end=' ') if model.word_indxs[values[k]] == '<eol>': coverage_step = k break print() if model.maintain_coverage and model.coverage_dim == 1: coverage = coverages[coverage_step] print('Coverage: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k]] == '<eol>': break sen.append('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k])) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k]), end=' ') if model.word_indxs_src[inps[0][k]] == '<eol>': break print('') print() def fprop(self, state_below, temp=numpy.float32(1), use_noise=True, additional_inputs=None, no_noise_bias=False): """ Forward pass through the cost layer. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ if self.rank_n_approx: if use_noise and self.noise_params: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1+self.nW_em1)) emb_val = TT.dot(self.W_em2 + self.nW_em2, emb_val) else: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1)) emb_val = TT.dot(self.W_em2, emb_val) else: if use_noise and self.noise_params: emb_val = utils.dot(state_below, self.W_em + self.nW_em) else: emb_val = utils.dot(state_below, self.W_em) if additional_inputs: if use_noise and self.noise_params: for inp, weight, noise_weight in zip( additional_inputs, self.additional_weights, self.noise_additional_weights): emb_val += utils.dot(inp, (noise_weight + weight)) else: for inp, weight in zip(additional_inputs, self.additional_weights): emb_val += utils.dot(inp, weight) self.preactiv = emb_val if use_noise and self.noise_params and not no_noise_bias: emb_val = TT.nnet.sigmoid(temp (emb_val + self.b_em + self.nb_em)) else: emb_val = TT.nnet.sigmoid(temp * (emb_val + self.b_em)) self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def compute_sample(self, state_below, temp=1, additional_inputs=None, use_noise=False): """ See parent class. """ class_probs = self.fprop(state_below, temp=temp, additional_inputs=additional_inputs, use_noise=use_noise) pvals = class_probs if pvals.ndim == 1: pvals = pvals.dimshuffle('x', 0) sample = self.trng.binomial(pvals.shape, p=pvals, dtype='int64') if class_probs.ndim == 1: sample = sample[0] self.sample = sample return sample def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=None, use_noise=True, additional_inputs=None, no_noise_bias=False): """ See parent class """ class_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias) pvals = class_probs assert target, 'Computing the cost requires a target' if target.ndim == 3: target = target.reshape((target.shape[0]target.shape[1], target.shape[2])) assert 'float' in target.dtype # Do we need the safety net of 1e-12 ? cost = -TT.log(TT.maximum(1e-12, class_probs)) target -\ TT.log(TT.maximum(1e-12, 1 - class_probs)) * (1 - target) if cost.ndim > 1: cost = cost.sum(1) if mask: mask = mask.flatten() cost = cost * TT.cast(mask, theano.config.floatX) if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim == 3: sh0 = TT.cast(state_below.shape[0], theano.config.floatX) sh1 = TT.cast(state_below.shape[1], theano.config.floatX) self.cost = cost.sum()/sh1 else: self.cost = cost.sum() else: self.cost = cost.mean() if scale: self.cost = self.costscale if reg: self.cost = self.cost + reg self.out = self.cost self.mask = mask self.cost_scale = scale return self.cost class SoftmaxLayer(CostLayer): """ Softmax output layer. """ def _get_samples(self, model, length=30, temp=1, inps): """ See parent class """ if not hasattr(model, 'word_indxs_src'): model.word_indxs_src = model.word_indxs character_level = False if hasattr(model, 'character_level'): character_level = model.character_level if model.del_noise: model.del_noise() if model.maintain_coverage: [values, probs, coverages] = model.sample_fn(length, temp, inps) else: [values, probs] = model.sample_fn(length, temp, inps) #print 'Generated sample is:' #print if values.ndim > 1: for d in range(2): print('%d-th sentence' % d) print('Input: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k][d]] == '<eol>': break sen.append(model.word_indxs_src[inps[0][k][d]]) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print(model.word_indxs_src[inps[0][k][d]], end=' ') if model.word_indxs_src[inps[0][k][d]] == '<eol>': break print('') print('Output: ', end=' ') if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k][d]] == '<eol>': break sen.append(model.word_indxs[values[k][d]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k][d]], end=' ') if model.word_indxs[values[k][d]] == '<eol>': break print() print() else: print('Output: ', end=' ') coverage_step = 0 if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k]] == '<eol>': coverage_step = k break sen.append(model.word_indxs[values[k]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k]], end=' ') if model.word_indxs[values[k]] == '<eol>': coverage_step = k break print() if model.maintain_coverage and model.coverage_dim == 1: coverage = coverages[coverage_step] print('Coverage: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k]] == '<eol>': break sen.append('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k])) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k]), end=' ') if model.word_indxs_src[inps[0][k]] == '<eol>': break print('') print() def fprop(self, state_below, temp=numpy.float32(1), use_noise=True, additional_inputs=None, no_noise_bias=False, target=None, full_softmax=True): """ Forward pass through the cost layer. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ if not full_softmax: assert target != None, 'target must be given' if self.rank_n_approx: if self.weight_noise and use_noise and self.noise_params: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1+self.nW_em1)) nW_em = self.nW_em2 else: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1)) W_em = self.W_em2 else: W_em = self.W_em if self.weight_noise: nW_em = self.nW_em emb_val = state_below if full_softmax: if self.weight_noise and use_noise and self.noise_params: emb_val = TT.dot(emb_val, W_em + nW_em) else: emb_val = TT.dot(emb_val, W_em) if additional_inputs: if use_noise and self.noise_params: for inp, weight, noise_weight in zip( additional_inputs, self.additional_weights, self.noise_additional_weights): emb_val += utils.dot(inp, (noise_weight + weight)) else: for inp, weight in zip(additional_inputs, self.additional_weights): emb_val += utils.dot(inp, weight) if self.weight_noise and use_noise and self.noise_params and \ not no_noise_bias: emb_val = temp * (emb_val + self.b_em + self.nb_em) else: emb_val = temp * (emb_val + self.b_em) else: W_em = W_em[:, target] if self.weight_noise: nW_em = nW_em[:, target] W_em += nW_em if emb_val.ndim == 3: emb_val = emb_val.reshape([emb_val.shape[0]emb_val.shape[1], emb_val.shape[2]]) emb_val = (W_em.T emb_val).sum(1) + self.b_em[target] if self.weight_noise and use_noise: emb_val += self.nb_em[target] emb_val = temp * emb_val self.preactiv = emb_val if full_softmax: emb_val = utils.softmax(emb_val) else: emb_val = TT.nnet.sigmoid(emb_val) self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def compute_sample(self, state_below, temp=1, use_noise=False, additional_inputs=None): class_probs = self.fprop(state_below, temp=temp, additional_inputs=additional_inputs, use_noise=use_noise) pvals = class_probs if pvals.ndim == 1: pvals = pvals.dimshuffle('x', 0) sample = self.trng.multinomial(pvals=pvals, dtype='int64').argmax(axis=-1) if class_probs.ndim == 1: sample = sample[0] self.sample = sample return sample def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=False, no_noise_bias=False, additional_inputs=None, # added by Zhaopeng Tu, 2015-11-07 coverages=None, c_mask=None, use_noise=True): """ See parent class """ def _grab_probs(class_probs, target): shape0 = class_probs.shape[0] shape1 = class_probs.shape[1] target_ndim = target.ndim target_shape = target.shape if target.ndim > 1: target = target.flatten() assert target.ndim == 1, 'make sure target is a vector of ints' assert 'int' in target.dtype pos = TT.arange(shape0)shape1 new_targ = target + pos return class_probs.flatten()[new_targ] assert target, 'Computing the cost requires a target' target_shape = target.shape target_ndim = target.ndim if self.use_nce: logger.debug("Using NCE") # positive samples: true targets class_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias, target=target.flatten(), full_softmax=False) # negative samples: a single uniform random sample per training sample nsamples = TT.cast(self.trng.uniform(class_probs.shape[0].reshape([1])) self.n_out, 'int64') neg_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias, target=nsamples.flatten(), full_softmax=False) cost_target = class_probs cost_nsamples = 1. - neg_probs cost = -TT.log(cost_target) cost = cost - TT.cast(neg_probs.shape[0], 'float32') * TT.log(cost_nsamples) else: class_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias) cost = -TT.log(_grab_probs(class_probs, target)) self.word_probs = TT.exp(-cost.reshape(target_shape)) # Set all the probs after the end-of-line to one if mask: self.word_probs = self.word_probs * mask + 1 - mask if mask: cost = cost * TT.cast(mask.flatten(), theano.config.floatX) self.cost_per_sample = (cost.reshape(target_shape).sum(axis=0) if target_ndim > 1 else cost) # added by Zhaopeng Tu, 2015-11-27 # use coverage variance for cost # we expect the coverage be in a uniform distribution, to make all the input words are touched equally # coverages is only available in EVALUATION mode if self.use_coverage_cost and coverages: # here we only consider the variance for all non-zero elems (with mask) # coverages consists of coverage at each time step # coverages: (target_length, source_length, batch_size) # we use the variance of final coverage as the bias coverage = coverages[-1][:,:,0] length = c_mask.sum(axis=0) coverage_mean = coverage.sum(axis=0)/length # samples in a batch have different lengths # added by Zhaopeng Tu, 2015-12-02 # for additive or subtractive coverage, the coverage_var would be too large (especially for long sentence) # which means the cost would be negative thus the traning would be stopped # additive: .. iter 27502 cost -988.954 grad_norm 7.71e+03 log2_p_word -1.78e+00 log2_p_expl 4.89e+01 step time 0.713 sec whole time 12.753 h lr 1.00e+00 # therefore, we use standard variance # coverage_var = TT.sqr((coverage-coverage_mean.dimshuffle('x', 0))c_mask).sum(axis=0)/length coverage_var = TT.sqrt(TT.sqr((coverage-coverage_mean.dimshuffle('x', 0))c_mask).sum(axis=0)/length) # added by Zhaopeng Tu, 2015-12-02 # we should not add the coverage_var to each word, which will remove the effect of normalizer length # thus the longer the sentence, the heavier effect the coverage_var, which is not suitable # therefore, we add the coverage_var to the final cost (as an overall bias) ''' # expand the coverage_var to match the shape of targets coverage_var = (coverage_var.dimshuffle('x', 0) * mask).flatten() # self.cost = self.cost + coverage_var * self.CC.dimshuffle('x', 0) cost = cost + coverage_var * self.CC ''' if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim == 3: cost = cost.reshape((state_below.shape[0], state_below.shape[1])) self.cost = cost.mean(1).sum() else: self.cost = cost.sum() # added by Zhaopeng Tu, 2015-12-02 if self.use_coverage_cost and coverages: coverage_var = coverage_var.sum() else: self.cost = cost.mean() # added by Zhaopeng Tu, 2015-12-02 if self.use_coverage_cost and coverages: coverage_var = coverage_var.mean() # added by Zhaopeng Tu, 2015-12-02 if self.use_coverage_cost and coverages: self.cost = self.cost + self.CC * coverage_var if scale: self.cost = self.costscale if reg: self.cost = self.cost + reg self.mask = mask self.cost_scale = scale return self.cost class HierarchicalSoftmaxLayer(SoftmaxLayer): """ Hierarchical Softmax output layer (2 layer) This is a preliminary implementation of 2-level hierarchical softmax layer (GPU only) """ def __init__(self, rng, n_in, n_out, scale, sparsity, weight_noise=False, init_fn='sample_weights_classic', bias_fn='init_bias', bias_scale=0., sum_over_time=True, grad_scale=1., name=None, kwargs): assert theano.config.device[:3] == 'gpu', 'Hierarchical softmax is not supported without GPU' from theano.sandbox.cuda.blocksparse import sparse_block_dot_SS self.sparse_block_dot_SS = sparse_block_dot_SS self.grad_scale = grad_scale super(CostLayer, self).__init__(n_in, n_out, rng, name) self.n_words_class = numpy.ceil(numpy.sqrt(self.n_out)).astype('int64') # oSize self.n_class = numpy.ceil(self.n_out/float(self.n_words_class)).astype('int64') # oBlocks logger.debug("n_words_class = %d, n_class = %d"%(self.n_words_class, self.n_class)) self.trng = RandomStreams(self.rng.randint(int(1e6))) if isinstance(bias_fn, str): self.bias_fn = eval(bias_fn) else: self.bias_fn = bias_fn self.bias_scale = bias_scale self.scale = scale self.sum_over_time = sum_over_time self.weight_noise = weight_noise self.sparsity = sparsity if self.sparsity < 0: self.sparsity = n_out if type(init_fn) is str: init_fn = eval(init_fn) self.init_fn = init_fn self._init_params() def _init_params(self): self.iBlocks = 1 # number of blocks in the input (from lower layer) W_em = self.init_fn(self.n_in, self.n_class, self.sparsity, self.scale, self.rng) self.W_em = theano.shared(W_em, name='W_%s' % self.name) self.b_em = theano.shared( self.bias_fn(self.n_class, self.bias_scale, self.rng), name='b_%s' % self.name) U_em = theano.shared(((self.rng.rand(self.iBlocks, self.n_class, self.n_in, self.n_words_class)-0.5)/(self.n_words_classself.n_in) ).astype(theano.config.floatX), name='U_%s'%self.name) self.U_em = U_em c_em = numpy.zeros((self.n_class, self.n_words_class), dtype='float32') n_words_last_class = self.n_out % self.n_words_class #c_em[-1, n_words_last_class:] = -numpy.inf self.c_em = theano.shared(c_em, name='c_%s' % self.name) self.params = [self.W_em, self.b_em, self.U_em, self.c_em] self.params_grad_scale = [self.grad_scale for x in self.params] def fprop(self, state_below, temp=numpy.float32(1), use_noise=True, additional_inputs=None, no_noise_bias=False, target=None, full_softmax=True, *kwargs): if not full_softmax: assert target != None, 'target must be given' W_em = self.W_em U_em = self.U_em b_em = self.b_em c_em = self.c_em emb_val = state_below bs = emb_val.shape[0] if full_softmax: # compute the probability of every word using scan # for all classes class_vecs = TT.arange(self.n_class) class_val = utils.softmax(TT.dot(emb_val, W_em) + b_em) def _compute_inclass(classid): # compute the word probabilities outputIdx = TT.alloc(classid, bs)[:, None] word_val = utils.softmax(TT.dot(emb_val, U_em[0, classid, :, :])+c_em[classid,:]) word_val = word_val class_val[:, classid][:,None] return word_val.T rval = theano.scan(_compute_inclass, class_vecs, None, name='compute_inclass') all_word_val = rval[0].reshape([rval[0].shape[0]rval[0].shape[1], rval[0].shape[2]]).T all_word_val = all_word_val[:,:self.n_out] emb_val = all_word_val else: # compute only the probability of given targets if emb_val.ndim == 3: emb_val = emb_val.reshape([emb_val.shape[0]emb_val.shape[1], emb_val.shape[2]]) # extract class id's from target indices target = target.flatten() class_vec = target // self.n_words_class # need to be int/int class_idx_vec = target % self.n_words_class outputIdx = class_vec[:, None] # compute the class probabilities class_val = utils.softmax(TT.dot(emb_val, W_em) + b_em) # compute the word probabilities word_val = utils.softmax(self.sparse_block_dot_SS(U_em, emb_val[:, None, :], TT.zeros((bs, 1), dtype='int64'), c_em, outputIdx)[:, 0, :]) class_val = class_val[TT.arange(bs), class_vec] word_val = word_val[TT.arange(bs), class_idx_vec] emb_val = class_val * word_val #self.preactiv = emb_val self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=False, no_noise_bias=False, additional_inputs=None, use_noise=True): """ See parent class """ assert target, 'Computing the cost requires a target' target_shape = target.shape target_ndim = target.ndim target_shape = target.shape if state_below.ndim == 3: shp = state_below.shape state_below = state_below.reshape([shp[0]shp[1], shp[2]]) class_probs = self.fprop(state_below, temp=temp, target=target, full_softmax=False, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias) cost = -TT.log(class_probs) self.word_probs = TT.exp(-cost.reshape(target_shape)) # Set all the probs after the end-of-line to one if mask: self.word_probs = self.word_probs mask + 1 - mask if mask: cost = cost * TT.cast(mask.flatten(), theano.config.floatX) self.cost_per_sample = (cost.reshape(target_shape).sum(axis=0) if target_ndim > 1 else cost) if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim == 3: cost = cost.reshape((state_below.shape[0], state_below.shape[1])) self.cost = cost.mean(1).sum() else: self.cost = cost.sum() else: self.cost = cost.mean() if scale: self.cost = self.cost*scale if reg: self.cost = self.cost + reg self.mask = mask self.cost_scale = scale return self.cost	neozhangthe1/coverage_model	build/lib/groundhog/layers/cost_layers.py	Python	bsd-3-clause	59,101	[ "Gaussian" ]	97f8ad9d8431fd85098bdfcfca04910d0432d701d38b38fa2189e2dd2402f4fd
#!/usr/bin/env python3 ##ON APP MACHINE import sys from os import listdir, mkdir from os.path import isdir, dirname, abspath import os import subprocess import weakref from scipy import fftpack import numpy as np ## some global variables, this needs to be fixed at some point default_raw_data_loc = None#"/exp_app2/appexp1/public/raw_data" default_processed_data_loc = None#"/home/brian/processed_files" MetaData_directory = dirname(abspath(__file__)) + '/data' ## change this if antenna_response_model is in a folder different from this module #### constants C = 299792458.0 RTD = 180.0/3.1415926 ##radians to degrees n_air = 1.000293 v_air = C/n_air latlonCS002 = np.array([52.91512249, 6.869837540]) ## lattitude and longitude of CS002 in degrees #### log data to screen and to a file class logger(object): class std_writer(object): def __init__(self, logger): self.logger_ref = weakref.ref(logger) def write(self, msg): logger=self.logger_ref() logger.out_file.write(msg) if logger.to_screen: logger.old_stdout.write(msg) def flush(self): logger=self.logger_ref() logger.out_file.flush() def __init__(self): self.has_stderr = False self.has_stdout = False self.old_stderr = sys.stderr self.old_stdout = sys.stdout self.set("out_log") def set(self, fname, to_screen=True): self.out_file = open(fname, 'w') self.set_to_screen( to_screen ) def __call__(self, args): for a in args: if self.to_screen: self.old_stdout.write(str(a)) self.old_stdout.write(" ") self.out_file.write(str(a)) self.out_file.write(" ") self.out_file.write("\n") if self.to_screen: self.old_stdout.write("\n") self.out_file.flush() self.old_stdout.flush() def set_to_screen(self, to_screen=True): self.to_screen = to_screen def take_stdout(self): if not self.has_stdout: sys.stdout = self.std_writer(self) self.has_stdout = True def take_stderr(self): if not self.has_stderr: sys.stderr = self.std_writer(self) self.has_stderr = True def restore_stdout(self): if self.has_stdout: sys.stdout = self.old_stdout self.has_stdout = False def restore_stderr(self): if self.has_stderr: sys.stderr = self.old_stderr self.has_stderr = False def flush(self): self.out_file.flush() # def __del__(self): # self.restore_stderr() # self.restore_stdout() #log = logger() def iterate_pairs(list_one, list_two, list_one_avoid=[], list_two_avoid=[]): """returns an iterator that loops over all pairs of the two lists""" for item_one in list_one: if item_one in list_one_avoid: continue for item_two in list_two: if item_two in list_two_avoid: continue yield (item_one, item_two) import re natural_regex_pattern = re.compile('([0-9]+)') def natural_sort( l ): """ Sort the given iterable in the way that humans expect. Usefull for sorting station names.""" convert = lambda text: int(text) if text.isdigit() else text alphanum_key = lambda key: [ convert(c) for c in natural_regex_pattern.split(key) ] return sorted(l, key = alphanum_key) #### some file utils def Fname_data(Fpath): """ takes both pulse data file names and h5 file names and returns UTC_time, station_name, Fpath""" Fname = Fpath.split('/')[-1] data = Fname.split('_') timeID = data[1] station_name = data[2] if len(data[3][1:])==0: file_number = 0 else: file_number = int(data[3][1:]) return timeID, station_name, Fpath, file_number ##note that timeID is a string representing the datetime of a LOFAR trigger. such as: D20130619T094846.507Z ## the timeID is used to uniquely identify triggers def get_timeID(fname): data=fname.split("_") return data[1] def year_from_timeID(timeID): return timeID[1:5] def raw_data_dir(timeID, data_loc=None): """gives path to the raw data folder for a particular timeID, given location of data structure. Defaults to default_raw_data_loc""" if data_loc is None: data_loc = default_raw_data_loc if default_raw_data_loc is None: print("ERROR: 'default_raw_data_loc' in utilities is not set.") quit() path = data_loc + '/' + year_from_timeID(timeID)+"/"+timeID return path def processed_data_dir(timeID, data_loc=None): """gives path to the analysis folders for a particular timeID, given location of data structure. Defaults to default_processed_data_loc makes the directory if it doesn't exist""" if data_loc is None: data_loc = default_processed_data_loc if default_processed_data_loc is None: print("ERROR: 'default_processed_data_loc' in utilities is not set.") quit() path=data_loc + "/" + year_from_timeID(timeID)+"/"+timeID if not isdir(path): mkdir(path) return path ## a python list where the keys are the number of a station and the values are the station name SId_to_Sname = [None]209 #just to pre-initilize list, so syntax below is possible SId_to_Sname[1] = "CS001" SId_to_Sname[2] = "CS002" SId_to_Sname[3] = "CS003" SId_to_Sname[4] = "CS004" SId_to_Sname[5] = "CS005" SId_to_Sname[6] = "CS006" SId_to_Sname[7] = "CS007" #SId_to_Sname[8] = "CS008" #SId_to_Sname[9] = "CS009" #SId_to_Sname[10] = "CS010" SId_to_Sname[11] = "CS011" #SId_to_Sname[12] = "CS012" SId_to_Sname[13] = "CS013" #SId_to_Sname[14] = "CS014" #SId_to_Sname[15] = "CS015" #SId_to_Sname[16] = "CS016" SId_to_Sname[17] = "CS017" #SId_to_Sname[18] = "CS018" #SId_to_Sname[19] = "CS019" #SId_to_Sname[20] = "CS020" SId_to_Sname[21] = "CS021" #SId_to_Sname[22] = "CS022" #SId_to_Sname[23] = "CS023" SId_to_Sname[24] = "CS024" #SId_to_Sname[25] = "CS025" SId_to_Sname[26] = "CS026" #SId_to_Sname[27] = "CS027" SId_to_Sname[28] = "CS028" #SId_to_Sname[29] = "CS029" SId_to_Sname[30] = "CS030" SId_to_Sname[31] = "CS031" SId_to_Sname[32] = "CS032" SId_to_Sname[101] = "CS101" #SId_to_Sname[102] = "CS102" SId_to_Sname[103] = "CS103" SId_to_Sname[121] = "CS201" SId_to_Sname[141] = "CS301" SId_to_Sname[142] = "CS302" SId_to_Sname[161] = "CS401" SId_to_Sname[181] = "CS501" #SId_to_Sname[104] = "RS104" #SId_to_Sname[105] = "RS105" SId_to_Sname[106] = "RS106" #SId_to_Sname[107] = "RS107" #SId_to_Sname[108] = "RS108" #SId_to_Sname[109] = "RS109" #SId_to_Sname[122] = "RS202" #SId_to_Sname[123] = "RS203" #SId_to_Sname[124] = "RS204" SId_to_Sname[125] = "RS205" #SId_to_Sname[126] = "RS206" #SId_to_Sname[127] = "RS207" SId_to_Sname[128] = "RS208" #SId_to_Sname[129] = "RS209" SId_to_Sname[130] = "RS210" #SId_to_Sname[143] = "RS303" #SId_to_Sname[144] = "RS304" SId_to_Sname[145] = "RS305" SId_to_Sname[146] = "RS306" SId_to_Sname[147] = "RS307" #SId_to_Sname[148] = "RS308" #SId_to_Sname[149] = "RS309" SId_to_Sname[150] = "RS310" SId_to_Sname[166] = "RS406" SId_to_Sname[167] = "RS407" SId_to_Sname[169] = "RS409" SId_to_Sname[183] = "RS503" SId_to_Sname[188] = "RS508" SId_to_Sname[189] = "RS509" SId_to_Sname[201] = "DE601" SId_to_Sname[202] = "DE602" SId_to_Sname[203] = "DE603" SId_to_Sname[204] = "DE604" SId_to_Sname[205] = "DE605" SId_to_Sname[206] = "FR606" SId_to_Sname[207] = "SE607" SId_to_Sname[208] = "UK608" ## this just "inverts" the previous list, discarding unused values Sname_to_SId_dict = {name:ID for ID,name in enumerate(SId_to_Sname) if name is not None} def even_antName_to_odd(even_ant_name): even_num = int(even_ant_name) odd_num = even_num + 1 return str( odd_num ).zfill( 9 ) def antName_is_even(ant_name): return not int(ant_name)%2 def odd_antName_to_even(odd_ant_name): odd_num = int(odd_ant_name) even_num = odd_num - 1 return str( even_num ).zfill( 9 ) def antName_to_even(ant_name): if antName_is_even(ant_name): return ant_name else: odd_antName_to_even( ant_name ) def antName_to_odd(ant_name): if antName_is_even(ant_name): even_antName_to_odd( ant_name ) else: return ant_name #### plotting utilities #### def set_axes_equal(ax): '''Make axes of 3D plot have equal scale so that spheres appear as spheres, cubes as cubes, etc.. This is one possible solution to Matplotlib's ax.set_aspect('equal') and ax.axis('equal') not working for 3D. Input ax: a matplotlib axis, e.g., as output from plt.gca(). ''' x_limits = ax.get_xlim3d() y_limits = ax.get_ylim3d() z_limits = ax.get_zlim3d() x_range = abs(x_limits[1] - x_limits[0]) x_middle = np.mean(x_limits) y_range = abs(y_limits[1] - y_limits[0]) y_middle = np.mean(y_limits) z_range = abs(z_limits[1] - z_limits[0]) z_middle = np.mean(z_limits) # The plot bounding box is a sphere in the sense of the infinity # norm, hence I call half the max range the plot radius. plot_radius = 0.5max([x_range, y_range, z_range]) ax.set_xlim3d([x_middle - plot_radius, x_middle + plot_radius]) ax.set_ylim3d([y_middle - plot_radius, y_middle + plot_radius]) ax.set_zlim3d([z_middle - plot_radius, z_middle + plot_radius]) ### some math functions? ### def normalize_angle_radians( angle_radians ): """For an angle in radians, return the equivalent angle that is garunteed be between -pi and pi""" while angle_radians > np.pi: angle_radians -= 2.0np.pi while angle_radians < -np.pi: angle_radians += 2.0*np.pi return angle_radians def BoundingBox_collision(BB1, BB2): """ return true if two N-D bounding boxes collide, False otherwise""" for B1, B2 in zip(BB1,BB2): if (B1[1] < B2[0]) or (B2[1] < B1[0]): return False return True ### some build tools #### def GSL_include(): """return directory for location of GSL headers, useful when combining GSL and cython""" try: gsl_include = subprocess.check_output('gsl-config --cflags', shell=True).decode('utf-8')[2:-1] except subprocess.CalledProcessError: gsl_include = os.getenv('LIB_GSL') if gsl_include is None: # Environmental variable LIB_GSL not set, use hardcoded path. gsl_include = r"c:\Program Files\GnuWin32\include" else: gsl_include += "/include" assert gsl_include != '', "Couldn't find gsl. Make sure it's installed and in the path." return gsl_include def GSL_library_dir(): """return directory for location of GSL binaries, useful when combining GSL and cython""" try: lib_gsl_dir = subprocess.check_output('gsl-config --libs', shell=True).decode('utf-8').split()[0][2:] except subprocess.CalledProcessError: lib_gsl_dir = os.getenv('LIB_GSL') if lib_gsl_dir is None: # Environmental variable LIB_GSL not set, use hardcoded path. lib_gsl_dir = r"c:\Program Files\GnuWin32\lib" else: lib_gsl_dir += "/lib" return lib_gsl_dir	Bhare8972/LOFAR-LIM	LIM_scripts/utilities.py	Python	mit	11,568	[ "Brian" ]	de9aee678156fe3e80ea9ddab17931f7cf83cd3694d606bc560ca66b24286ea8
#!/usr/bin/env python # Script to convert Amber protein hydrogens (created by ambpdb) into Gromacs # names. For some reason, eg. HB2 + HB3 are expected to be HB1 and HB2 in the # Gromacs aminoacids.rtp parameter files. # Requirements: Biopython # Desired PDB file should be the first argument. Output is renamed PDB with # 'GMX_' prepended. import sys from Bio.PDB import PDBIO from Bio.PDB.PDBParser import PDBParser proteins = ['ALA','ARG','ASH','ASP','ASN','CYS','CYX','GLH','GLN','GLU','GLY','HID','HIE','HIP','HIS','ILE','LEU','LYN','LYS','MET','PHE','PRO','SER','THR','TRP','TYR','VAL'] # Argparse this... try: pdbname = sys.argv[1] except IndexError: print "PDB file required as first argument. " sys.exit() try: sys.argv[2] print "Renaming termini (providing any character as a second argument will turn this on)" termini = True except IndexError: termini = False print "Not renaming termini (add a second argument if you want to turn this on)" parser = PDBParser(QUIET=True) # Lack of atom symbols = warnings if verbose structure = parser.get_structure('ambpdb',pdbname) # Convert first and last residues to termini def rename_termini(struct): """Rename termini of chains to be NXXX and CXXX. TAKE CARE - RESULTS IN NON-STANDARD PDB FORMAT (residue names should be 3 characters). Input = Biopython structure object, returns structure object with modified first/last resnames in each chain.""" for chain in struct.get_chains(): first = chain.child_list[0] last = chain.child_list[-1] if first.resname in proteins: first.resname = 'N'+first.resname else: print """The first residue is either already an N-terminus, or doesn't appear to be a natural amino acid. Continuing anyway.""" if last.resname in proteins: last.resname = 'C'+last.resname else: for idx,res in enumerate(chain.child_list,-1): if res.resname in proteins: continue else: last = chain.child_list[idx] # idx starts from -1 print "You seem to have non-protein residues in a chain. Renaming residue %s %s as C-terminus" % (last.resname,last.id[1]) last.resname = 'C'+last.resname return struct def amb2gmx(struct): """Rename Amber atoms to those expected in the Gromacs amber parameter files. Mainly e.g. HB2/HB3 -> HB1/HB2. Cycles over all residues. Input = Biopython structure object, returns structure object with modified atom names""" for residue in struct.get_residues(): if residue.resname in ['GLY','NGLY','CGLY']: residue['HA2'].fullname = ' HA1' residue['HA3'].fullname = ' HA2' elif residue.resname in ['SER','NSER','CSER']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['LEU','NLEU','CLEU']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['ILE','NILE','CILE']: residue['HG12'].fullname = 'HG11' residue['HG13'].fullname = 'HG12' elif residue.resname in ['ASN','NASN','CASN']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['GLN','NGLN','CGLN']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' elif residue.resname in ['ARG','NARG','CARG']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' residue['HD2'].fullname = ' HD1' residue['HD3'].fullname = ' HD2' elif residue.resname in ['HID','NHID','CHID','HIE','NHIE','CHIE','HIP','NHIP','CHIP','HIS','NHIS','CHIS']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['TRP','NTRP','CTRP']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['PHE','NPHE','CPHE']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['TYR','NTYR','CTYR']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['GLU','NGLU','CGLU','GLH','NGLH','CGLH']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' elif residue.resname in ['ASP','NASP','CASP','ASH','NASH','CASH']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['LYS','NLYS','CLYS','LYN','NLYN','CLYN']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' residue['HD2'].fullname = ' HD1' residue['HD3'].fullname = ' HD2' residue['HE2'].fullname = ' HE1' residue['HE3'].fullname = ' HE2' elif residue.resname in ['PRO','NPRO','CPRO']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' residue['HD2'].fullname = ' HD1' residue['HD3'].fullname = ' HD2' elif residue.resname in ['CYS','NCYS','CCYS','CYX','NCYX','CCYX']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['MET','NMET','CMET']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' return struct def write_struct(struct,name): """Writes a corrected PDB file to disk with 'GMX_' prepended""" w = PDBIO() w.set_structure(struct) w.save('GMX_'+name) #### Main below here #### if termini is True: structure = rename_termini(structure) print """If you have separate chains in your PDB (separated by a TER card), make sure they have a chain identifier in column 22, in accordance with the PDB version 3 format. Biopython is expecting this!""" structure = amb2gmx(structure) write_struct(structure,pdbname) print "Done."	rtb1c13/scripts	SAXS_MD/AmbPDB_2_GMX.py	Python	gpl-2.0	6,501	[ "Amber", "Biopython", "Gromacs" ]	ef2ce9d4ecd396bf5562d88bec49c12ec76cbe6a0c9dd41ca5ef1a6ce5a4eb81
""" Test Logger Wrapper """ __RCSID__ = "$Id$" import logging from io import StringIO from DIRAC.FrameworkSystem.private.standardLogging.LoggingRoot import LoggingRoot from DIRAC.FrameworkSystem.private.standardLogging.Logging import Logging gLogger = LoggingRoot() def cleaningLog(log): """ Remove date and space from the log string """ log = log.split("UTC ")[-1] return log def captureBackend(): """ Dirac logger is wrapped by LoggingRoot and represent the root of the DIRAC logging system Modify the output to capture logs of LoggingRoot """ bufferDirac = StringIO() if logging.getLogger("dirac").handlers: logging.getLogger("dirac").handlers[0].stream = bufferDirac return bufferDirac def gLoggerReset(): """ Reinitialize gLogger as only one instance exists It avoids any unexpected behaviour due to multiple different usages """ # Reinitialize the system/component name after other tests # because LoggingRoot is a singleton and can not be reinstancied Logging._componentName = "Framework" # reset gLogger gLogger.setLevel("notice") gLogger.showHeaders(True) gLogger.showThreadIDs(False) gLogger.showContexts(True) gLogger.showTimeStamps(True) # modify the output to capture the log records into a buffer bufferDirac = captureBackend() del logging.getLogger("dirac").handlers[1:] del gLogger._backendsList[1:] # reset log logging.getLogger("dirac").getChild("log").setLevel(logging.NOTSET) log = gLogger.getSubLogger("log") log.showHeaders(True) log.showThreadIDs(False) log.showContexts(True) log.showTimeStamps(True) for option in log._optionsModified: log._optionsModified[option] = False del logging.getLogger("dirac.log").handlers[:] del log._backendsList[:] # reset sublog logging.getLogger("dirac.log").getChild("sublog").setLevel(logging.NOTSET) sublog = log.getSubLogger("sublog") sublog.showHeaders(True) sublog.showThreadIDs(False) sublog.showContexts(True) sublog.showTimeStamps(True) for option in sublog._optionsModified: sublog._optionsModified[option] = False del logging.getLogger("dirac.log.sublog").handlers[:] del sublog._backendsList[:] return (bufferDirac, log, sublog)	ic-hep/DIRAC	src/DIRAC/FrameworkSystem/private/standardLogging/test/TestLogUtilities.py	Python	gpl-3.0	2,343	[ "DIRAC" ]	0c73c24856295f6a80de3e83612c8a746db0d7a3b3ad20b15810cb2f7985bfa5
import unittest from .enum import Enum class TestEnum(unittest.TestCase): def test_string_conversion(self): column = Enum('test_column', 'ENUM', enum_values=['asdf', 'qwerty'], default='qwerty') self.assertEquals("`test_column` ENUM('asdf', 'qwerty') DEFAULT \'qwerty\'", str(column)) self.assertEquals([], column.schema_errors) self.assertEquals([], column.schema_warnings) def test_default_errors(self): column = Enum('test_column', 'ENUM', enum_values=['asdf', 'qwerty'], default='adf') self.assertEquals(["Default value for 'ENUM' column 'test_column' is not in the list of allowed values"], column.schema_errors) self.assertEquals([], Enum('test_column', 'ENUM', enum_values=['asdf', 'qwerty']).schema_errors)	cmancone/mygrations	mygrations/core/definitions/columns/enum_test.py	Python	mit	808	[ "ADF" ]	bc3fb2e51273b0caa965ff6bfee4401902a2ada14a27681259bade9939c00070
#!/usr/bin/env python # # Copyright (C) 2014 Brian Caswell <bmc@lungetech.com> # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included # in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS # OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. # IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY # CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # from generator.actions import Actions from random import choice, randint import imp import os import random import string print os.path.realpath(__file__) filename = os.path.sep.join(os.path.realpath(__file__).split(os.path.sep)[:-1] + ['books.py']) books = imp.load_source('books', filename).books def random_alpha(a, b): return ''.join(choice(string.letters) for _ in range(randint(a, b))) def random_string(a, b): chars = string.letters + string.digits return ''.join(choice(chars) for _ in range(randint(a, b))) class Bookworm(Actions): def start(self): self.read(delim='\n', expect='Welcome to the book review server\n') self.state['reviews'] = [] def menu(self): self.read(delim='Selection: ', expect="1. List Available " "Books\n2. Books you have reviewed\n3. Review " "more books\n4. Exit\nSelection: ") def list_books(self): self.write_number(1) expected = ['\nAvailable Books'] for i, book in enumerate(books, 1): expected.append('%d: %s' % (i, book)) self.read(delim='\n\n', expect='\n'.join(expected) + '\n\n') def reviewed(self): self.write_number(2) if 'reviews' not in self.state: self.state['reviews'] = [] expected = ['Book Title: Your rating'] + self.state['reviews'] self.read(delim='\n\n', expect='\n' + '\n'.join(expected) + '\n\n') def write_number(self, digit): trail = '' if self.chance(.01): trail = random_alpha(1, 30) self.write('%d%s\n' % (digit, trail)) def review(self): self.write_number(3) self.read(delim='?: ', expect='\nWhat book would you like to ' 'review (1 - 100)?: ') # 1% of the time, review an invalid book. sometimes with strings, # sometimes with numbers, sometimes both if self.chance(.01): invalid = None while invalid is None: invalid = random_string(1, 30) if re.match('^0*(\d\|\d{2}\|100)\D', invalid): invalid = None self.write("%s\n" % invalid) self.read(delim='\n', expect='Invalid book\n') else: choice = randint(1, 100) self.write_number(choice) self.read(delim='? ', expect='What rating would you like ' 'to give this book? ') rating = 0 # 1% of the time, send random jiberish as a response if self.chance(.01): self.write(random_alpha(1, 30)) else: rating = randint(0, 0xFFFF) self.write_number(rating) if 'reviews' not in self.state: self.state['reviews'] = [] self.state['reviews'].append("%s: %d" % (books[choice - 1], rating)) def bad_menu(self): if self.chance(.5): self.write_number(randint(6, 30)) else: self.write('%s\n' % random_alpha(1, 98)) self.read(delim='\n', expect='Invalid menu selection\n') def exit(self): self.write_number(4) self.read(delim='\n', expect='k, bye\n') def hidden(self): # This is the vulnerable condition. Do we want to expose this? if 0: self.write_number(5)	f0rki/cb-multios	tools/generate-polls/examples/bookworm/bookworm.py	Python	mit	4,548	[ "Brian" ]	2195f59586e15efd01f33e7f70afe61bafd52618b64cdb1d9c8dafd3fefbe1f3
# This module is free software. You can redistribute it and/or modify it under # the terms of the MIT License, see the file COPYING included with this # distribution. from __future__ import division """ General utils files for general purpose functions """ import re import os #Biopython from Bio import SeqIO import motif_utils def getSeqMotifDict(fimoDict): """ Make a dict between the seq names and list of motifs that occur in it Args: fimoDict: dict between motif names and the seqs it hits Returns: a dict between seq names and a list of motif IDs that hit it """ seqMotifDict = {} tmpCount = 0 for motifId, seqList in fimoDict.items(): for seqName in seqList: if seqName not in seqMotifDict: seqMotifDict[seqName] = [] if motifId not in seqMotifDict[seqName]: seqMotifDict[seqName].append(motifId) return seqMotifDict def makeMotifDictFromPwmFile(pwmFileName): """ read a PWM file that we would like to scan and make a motif dict between motif ID and motif object Args: PWM file in MEME format """ #print 'PP:', pwmFileName #dict between motif IDs and motif objects motifDict = {} motifName = '' motifId = 0 #dicts between motif IDs and motif names with open(pwmFileName, 'rb') as handler: for line in handler: line = line.strip() if not line.strip() or re.search(r'letter', line) or re.search(r'version', line) or re.search(r'ALPHABET',line) or re.search(r'strands', line)\ or re.search(r'A 0.25000', line): continue #print 'l:',line if re.search(r'MOTIF', line): split = line.split() line = '_'.join(split[1:]) motifName = line motifId += 1 motifObj = motif_utils.MyMotif() motifObj.Id = motifId motifObj.regExp = motifName #notice here it is actually the motif name not a reg. expression motifDict[motifName] = motifObj continue #add the PWM lines to the motif motifDict[motifName].pwmLines.append(line) ##check the hash #for motifName in motifDict.iterkeys(): #print motifName #motifObj = motifDict[motifName] #print '\t',motifObj.regExp #for line in motifObj.pwmLines: #print '\t', line return motifDict def processMotifHitFile_1(inFile): """ Process a motif hit/occurrence file and return a universe set (U) and a dict of set of sets The inFile should look like: >motif_name_1 sequence name sequence name >motif_name_2 sequence name sequence name You can check the wiki page about set cover problem to get an idea about Universe (U) set and set S of subsets Args: inFile: name of file of motif hits in the format explained above Returns: motifIdDict: A dict between motif names and motif numbers (IDs) idMotifDict: A dict between seq names and seq numbers (IDs) seqIdDict: A dict between seq numbers (IDs) and seq names idSeqDict: A dict between seq numbers (IDs) and seq names and Uset : universe set of all seq IDs Sdict: dict between motif IDs and the sequence IDs the motif hits """ #a dict between motif names in the file and motif numbers (IDs) motifIdDict = {} #a dict between motif numbers (IDs) and motif names idMotifDict = {} #a dict between seq names and seq numbers (IDs) seqIdDict = {} #a dict between seq numbers and seq names idSeqDict = {} #all numbers/IDs start from 1 inside the dicts/sets motifId = 0 seqId = 0 #Universe set which is the set of all the sequences, the U set Uset = set() #A dict between motif names and the set of seqs that occur in them, the S set Sdict = {} print 'in process motif hit' #start reading the file with open(inFile, 'rb') as handler: for line in handler: line = line.strip() #skip empty spaces if not line.strip(): continue if re.search(r'>', line):#found a motif motifId += 1 motifName = line[1:]#take off the > character if motifName not in motifIdDict: motifIdDict[motifName] = motifId else: print 'There are motif names duplicates. the file should have unique motif names' exit() idMotifDict[motifId] = motifName #initialize the element in the Sdict Sdict[motifId] = set() continue #all the other lines are sequence names, check if the seq name has been checked and inserted or not seqName = line if seqName not in seqIdDict: seqId += 1 seqIdDict[seqName] = seqId idSeqDict[seqId] = seqName tmpSeqId = seqId else: tmpSeqId = seqIdDict[seqName] if tmpSeqId not in Sdict[motifId]: Sdict[motifId].add(tmpSeqId) #add the seqs to the U universe dict if tmpSeqId not in Uset: Uset.add(seqId) #check the U dict #print Uset #check the S dict #for motifId, seqSet in Sdict.items(): #print 'motifId:', motifId, 'set:', seqSet return motifIdDict, idMotifDict, seqIdDict, idSeqDict, Uset, Sdict def processMotifHitFile(foreMotifFile, backMotifFile): """Read the fore and back motif hit files and make motif dict and dict of motifs with their hits The input motf hit file should look like: >motif_name_1 sequence name sequence name >motif_name_2 sequence name sequence name """ motifId = 0 #dict between motif names and motif object motifObjDict = {} #dict between the motif name and list of seqs it occurs in foreHitDict = {} #list of sequences in the foreground file foreSeqList = [] motifName = '' #start reading the foreground file with open(foreMotifFile, 'rb') as handler: for line in handler: line = line.strip() #skip empty spaces if not line.strip(): continue if re.search(r'>', line):#found a motif motifId += 1 motifName = line[1:]#take off the > character #make a motif object motifObj = motif_utils.MyMotif() motifObj.Id = motifId motifObj.regExp = motifName #notice here it is actually the motif name not a reg. expression if motifName not in motifObjDict: motifObjDict[motifName] = motifObj else: print 'motif names should be unique. Exiting' exit() continue #add the seqs to the motif if motifName not in foreHitDict: foreHitDict[motifName] = [] foreHitDict[motifName].append(line) if line not in foreSeqList: foreSeqList.append(line) ##check the motif dict #for motifName in motifObjDict: #print 'mName:', motifName #for motifName in foreHitDict: #print 'mName:', motifName,'seqs:', foreHitDict[motifName] #print 'whole seq list:', foreSeqList #process the background #dict between the motif name and list of seqs it occurs in the background backHitDict = {} #list of sequences in the background file backSeqList = [] #check if there is a background file as well and make data for it backMotifName = '' if backMotifFile != 'none': with open(backMotifFile, 'rb') as handler: for line in handler: line = line.strip() #skip empty spaces if not line.strip(): continue if re.search(r'>', line):#found a motif backMotifName = line[1:]#take off the > character continue #add the seqs to the motif if backMotifName not in backHitDict: backHitDict[backMotifName] = [] backHitDict[backMotifName].append(line) if line not in backSeqList: backSeqList.append(line) #for motifName in backHitDict: # print 'mName:', motifName,'seqs:', backHitDict[motifName] #print 'whole seq list:', backSeqList return motifObjDict, foreHitDict, backHitDict, foreSeqList, backSeqList def writePWMFromMotifs(motifDict, pwmFileName): """Go thru the motif dict og BioPython objects and write them to a file in MEME PWM format Args: motif dictionary between motif IDs and MyMotif objects Returns: name of PWM motif file """ pwmFile = open(pwmFileName, 'wb') pwmFile.write('MEME version 4.4\nALPHABET= ACGT\nstrands: + -\nBackground letter frequencies (from web form):\nA 0.25000 C 0.25000 G 0.25000 T 0.25000\n\n') alphaList = ['A', 'C', 'G', 'T'] #loop thru the motifs for motifId in motifDict.iterkeys(): motifObj = motifDict[motifId].bioMotifObj #get motif length motifLength = len(motifObj) pwmFile.write('\nMOTIF ' + str(motifId) + '\n') pwmFile.write('letter-probability matrix:\n') pwm = motifObj.counts.normalize(pseudocounts=0) for i in range(motifLength): for alpha in alphaList: pwmFile.write(' ' + str(pwm[alpha][i])) pwmFile.write('\n') #close the file pwmFile.close() def writePWMFromMotifsSelected(motifDict, pwmFileName, selectIdList, idMotifDict): """Write the PWMs to a file, only write the IDs chosen in the selectIdList """ pwmFile = open(pwmFileName, 'wb') pwmFile.write('MEME version 4.4\nALPHABET= ACGT\nstrands: + -\nBackground letter frequencies (from web form):\nA 0.25000 C 0.25000 G 0.25000 T 0.25000\n\n') alphaList = ['A', 'C', 'G', 'T'] #loop thru the motifs for motifId in selectIdList: if motifId not in idMotifDict: motifName = motifId else: motifName = idMotifDict[motifId] #print 'motifId:', motifId,motifName motifObj = motifDict[motifName].bioMotifObj #get motif length motifLength = len(motifObj) pwmFile.write('\nMOTIF ' + str(motifName) + '\n') pwmFile.write('letter-probability matrix:\n') pwm = motifObj.counts.normalize(pseudocounts=0) for i in range(motifLength): for alpha in alphaList: pwmFile.write(' ' + str(pwm[alpha][i])) pwmFile.write('\n') #close the file pwmFile.close() def writePWMFromMotifsSelectedScan(motifDict, pwmFileName, selectIdList, idMotifDict, finalSelectMotifList): """Write the PWMs to a file, only write the IDs chosen in the selectIdList This is for the motif PWM scan problem where the PWm is already privided as input """ pwmFile = open(pwmFileName, 'wb') pwmFile.write('MEME version 4.4\nALPHABET= ACGT\nstrands: + -\nBackground letter frequencies (from web form):\nA 0.25000 C 0.25000 G 0.25000 T 0.25000\n\n') for motifId in selectIdList: if motifId not in idMotifDict: motifName = motifId else: motifName = idMotifDict[motifId] if motifName not in finalSelectMotifList: continue motifObj = motifDict[motifName] #motifName = motifObj.regExp pwmFile.write('\nMOTIF ' + motifName + '\n') pwmFile.write('letter-probability matrix:\n') for line in motifObj.pwmLines: pwmFile.write(line+'\n') #close the file pwmFile.close() def writeMotifSeqFile(motifDict, outFileName): """take a dict between motif IDs and seqs it occurs in and write to a file The format is: >motif_name seq_1 seq_2 Args: motifDict: dict between motif IDs/names and a list of sequences the motif occurs in outFileName" name of file to write to """ outFile = open(outFileName, 'wb') for motifId in sorted(motifDict.iterkeys()): seqList = motifDict[motifId] outFile.write('>' + str(motifId) + '\n') for seqName in seqList: outFile.write(seqName + '\n') outFile.close() def writeMotifSeqFileFromMotifDict(motifDict, outFileName): """Take a motif dict beween motif Ids and MyMotif objects and write the seq of each motif to a file use the seq coverage file format >motif_name seq_1 seq_2 Args: motifDIct: dict between motif IDs and MyMotif objects outFileName" name of file to write to """ outFile = open(outFileName, 'wb') for motifId in motifDict.iterkeys(): motifObj = motifDict[motifId] seqList = motifObj.foreSeqList outFile.write('>' + str(motifId) + '\n') for seqName in seqList: outFile.write(seqName + '\n') outFile.close() def findNumSeqs(fastaFile): """Use Biopython to find the number of fasta seqeunces in a fasta file Args: fasta file Returns: number of fasta sequences """ handle = open(fastaFile, "rU") numSeqs = 0 for record in SeqIO.parse(handle, "fasta"): seqId = str(record.id) numSeqs += 1 handle.close() return numSeqs def findSeqList(fastaFile): """ Read the fasta file and return a list of sequence names in the fasta file """ handle = open(fastaFile, "rU") numSeqs = 0 seqList = [] for record in SeqIO.parse(handle, "fasta"): seqId = str(record.id) seqList.append(seqId) numSeqs += 1 handle.close() return seqList def getSeqList(fastaFile): """Use Biopython to return a list of fasta seq names Args: fasta file Returns: list of seqNames """ handle = open(fastaFile, "rU") numSeqs = 0 seqList = [] for record in SeqIO.parse(handle, "fasta"): seqId = str(record.id) seqList.append(seqId) numSeqs += 1 handle.close() return seqList def makeMotifLogo(motifIdList, motifDict, outDirName, pwmFileName, idMotifDict, op, finalSelectMotifList): """Make motif logos for a set of motifs as specified in the motifIdList Add a motif logo ID (logo file name) to each motif object Args: motifIdList: list of motif IDs to make logos for motifDict: a dict between motif ID and a MyMotif object idMotifDict: dict from IDs to motif names op: operation; is it motif disocvery or a cov finalSelectMotifList: list of motif names , final filtered list Return: """ if op == 'disc': writePWMFromMotifsSelected(motifDict, pwmFileName, motifIdList, idMotifDict) if op== 'cov': writePWMFromMotifsSelectedScan(motifDict, pwmFileName, motifIdList, idMotifDict, finalSelectMotifList) #get the path of the module utils_path = os.path.realpath(__file__) #remove the name of the module from the end of it. Replace won't work since w ehave DME.py and DME.pyc split = utils_path.split('/') utils_path = '/'.join(split[:len(split)-1]) inPath = os.path.realpath(__file__) split = inPath.split('/') inPath = '/'.join(split[:len(split)-2]) command = inPath + '/' + 'meme2images -png ' + pwmFileName + ' ' + outDirName #print 'meme2image command:', command try: os.system(command) except: print 'meme2image execution failed. Exiting' exit() def makeMotifLogoFromPwm(pwmFileName, outDirName): """ Given the pwm file in MEME format make the logos """ #get the path of the module utils_path = os.path.realpath(__file__) #remove the name of the module from the end of it. Replace won't work since w ehave DME.py and DME.pyc split = utils_path.split('/') utils_path = '/'.join(split[:len(split)-1]) inPath = os.path.realpath(__file__) split = inPath.split('/') inPath = '/'.join(split[:len(split)-2]) command = inPath + '/' + 'meme2images -png ' + pwmFileName + ' ' + outDirName print 'meme2image command:', command try: os.system(command) except: print 'meme2image execution failed. Exiting' exit() def writeMotifBasicStat(motifDict, foreFimoDict, backFimoDict, foreNumSeqs, backNumSeqs, outFileName, tomtomDict): """ Write a file with basic info about the motif stats like coverage Args: motifDict: dict between motif names and motif objects """ outFile = open(outFileName, 'wb') headerList = ['#MotifName','Num_Fg_seqs','Fg_cov','Num_Bg_seqs', 'Bg_cov','FG/BG','similar_motifs'] headerLine = ','.join(headerList) outFile.write(headerLine + '\n') #go thru the motif dict for motifName in motifDict.iterkeys(): motifObj = motifDict[motifName] if motifName in foreFimoDict: foreSeqs = len(foreFimoDict[motifName]) foreCov = 100(foreSeqs/foreNumSeqs) else: foreSeqs = 0 foreCov = 0 if motifName in backFimoDict: backSeqs = len(backFimoDict[motifName]) backCov = 100(backSeqs/backNumSeqs) fg_over_bg = foreCov/backCov else: backSeqs = 0 backCov = 0 fg_over_bg = foreCov/1 #find similar motifs to this motif simList = [] simStr = '' if motifName in tomtomDict: simList = tomtomDict[motifName] simStr = '//'.join(simList) lineList = [motifName, str(foreSeqs), str(foreCov), str(backSeqs), str(backCov), str(fg_over_bg), simStr] lineStr = ','.join(lineList) outFile.write(lineStr + '\n') outFile.close() def main(args): pass ## if( __name__ == "__main__" ): main(sys.argv) #--eof--#	RamiOran/SeqCov	utils/general_utils.py	Python	mit	15,763	[ "Biopython" ]	388d15a4d3ae61d1a7589262922c3f9e662edcb16e5fc76211258538833db0bd
# (c) 2014, Brian Coca <bcoca@ansible.com> # # This file is part of Ansible # # Ansible is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # Ansible is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Ansible. If not, see <http://www.gnu.org/licenses/>. from __future__ import absolute_import import math import collections from ansible import errors def unique(a): if isinstance(a,collections.Hashable): c = set(a) else: c = [] for x in a: if x not in c: c.append(x) return c def intersect(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) & set(b) else: c = unique(filter(lambda x: x in b, a)) return c def difference(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) - set(b) else: c = unique(filter(lambda x: x not in b, a)) return c def symmetric_difference(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) ^ set(b) else: c = unique(filter(lambda x: x not in intersect(a,b), union(a,b))) return c def union(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) \| set(b) else: c = unique(a + b) return c def min(a): _min = __builtins__.get('min') return _min(a) def max(a): _max = __builtins__.get('max') return _max(a) def isnotanumber(x): try: return math.isnan(x) except TypeError: return False def logarithm(x, base=math.e): try: if base == 10: return math.log10(x) else: return math.log(x, base) except TypeError as e: raise errors.AnsibleFilterError('log() can only be used on numbers: %s' % str(e)) def power(x, y): try: return math.pow(x, y) except TypeError as e: raise errors.AnsibleFilterError('pow() can only be used on numbers: %s' % str(e)) def inversepower(x, base=2): try: if base == 2: return math.sqrt(x) else: return math.pow(x, 1.0/float(base)) except TypeError as e: raise errors.AnsibleFilterError('root() can only be used on numbers: %s' % str(e)) def human_readable(size, isbits=False, unit=None): base = 'bits' if isbits else 'Bytes' suffix = '' ranges = ( (1<<70, 'Z'), (1<<60, 'E'), (1<<50, 'P'), (1<<40, 'T'), (1<<30, 'G'), (1<<20, 'M'), (1<<10, 'K'), (1, base) ) for limit, suffix in ranges: if (unit is None and size >= limit) or \ unit is not None and unit.upper() == suffix: break if limit != 1: suffix += base[0] return '%.2f %s' % (float(size)/ limit, suffix) class FilterModule(object): ''' Ansible math jinja2 filters ''' def filters(self): return { # general math 'isnan': isnotanumber, 'min' : min, 'max' : max, # exponents and logarithms 'log': logarithm, 'pow': power, 'root': inversepower, # set theory 'unique' : unique, 'intersect': intersect, 'difference': difference, 'symmetric_difference': symmetric_difference, 'union': union, # computer theory 'human_readable' : human_readable, }	pheanex/ansible	lib/ansible/plugins/filter/mathstuff.py	Python	gpl-3.0	4,023	[ "Brian" ]	aa6a5ec4800e08af8d376ca09c52ff18e4728d95b885aba743cf79c1edd148c8
# -- coding: utf-8 -- # # # TheVirtualBrain-Scientific Package. This package holds all simulators, and # analysers necessary to run brain-simulations. You can use it stand alone or # in conjunction with TheVirtualBrain-Framework Package. See content of the # documentation-folder for more details. See also http://www.thevirtualbrain.org # # (c) 2012-2013, Baycrest Centre for Geriatric Care ("Baycrest") # # This program is free software; you can redistribute it and/or modify it under # the terms of the GNU General Public License version 2 as published by the Free # Software Foundation. This program is distributed in the hope that it will be # useful, but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public # License for more details. You should have received a copy of the GNU General # Public License along with this program; if not, you can download it here # http://www.gnu.org/licenses/old-licenses/gpl-2.0 # # # CITATION: # When using The Virtual Brain for scientific publications, please cite it as follows: # # Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide, # Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013) # The Virtual Brain: a simulator of primate brain network dynamics. # Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010) # # """ The Data component of Spectral datatypes. .. moduleauthor:: Stuart A. Knock <Stuart@tvb.invalid> .. moduleauthor:: Paula Sanz Leon <Paula@tvb.invalid> """ import tvb.basic.traits.core as core import tvb.basic.traits.types_basic as basic import tvb.datatypes.arrays as arrays import tvb.datatypes.time_series as time_series from tvb.basic.traits.types_mapped import MappedType class PrincipalComponentsData(MappedType): """ Result of a Principal Component Analysis (PCA). """ source = time_series.TimeSeries( label="Source time-series", doc="Links to the time-series on which the PCA is applied.") weights = arrays.FloatArray( label="Principal vectors", doc="""The vectors of the 'weights' with which each time-series is represented in each component.""", file_storage=core.FILE_STORAGE_EXPAND) fractions = arrays.FloatArray( label="Fraction explained", doc="""A vector or collection of vectors representing the fraction of the variance explained by each principal component.""", file_storage=core.FILE_STORAGE_EXPAND) norm_source = arrays.FloatArray( label="Normalised source time series", file_storage=core.FILE_STORAGE_EXPAND) component_time_series = arrays.FloatArray( label="Component time series", file_storage=core.FILE_STORAGE_EXPAND) normalised_component_time_series = arrays.FloatArray( label="Normalised component time series", file_storage=core.FILE_STORAGE_EXPAND) __generate_table__ = True class IndependentComponentsData(MappedType): """ Result of TEMPORAL (Fast) Independent Component Analysis """ source = time_series.TimeSeries( label="Source time-series", doc="Links to the time-series on which the ICA is applied.") mixing_matrix = arrays.FloatArray( label="Mixing matrix - Spatial Maps", doc="""The linear mixing matrix (Mixing matrix) """) unmixing_matrix = arrays.FloatArray( label="Unmixing matrix - Spatial maps", doc="""The estimated unmixing matrix used to obtain the unmixed sources from the data""") prewhitening_matrix = arrays.FloatArray( label="Pre-whitening matrix", doc=""" """) n_components = basic.Integer( label="Number of independent components", doc=""" Observed data matrix is considered to be a linear combination of :math:`n` non-Gaussian independent components""") norm_source = arrays.FloatArray( label="Normalised source time series. Zero centered and whitened.", file_storage=core.FILE_STORAGE_EXPAND) component_time_series = arrays.FloatArray( label="Component time series. Unmixed sources.", file_storage=core.FILE_STORAGE_EXPAND) normalised_component_time_series = arrays.FloatArray( label="Normalised component time series", file_storage=core.FILE_STORAGE_EXPAND) __generate_table__ = True	rajul/tvb-library	tvb/datatypes/mode_decompositions_data.py	Python	gpl-2.0	4,446	[ "Gaussian" ]	ccb5844d1e3a2c76a1fc63ab70b20c9914c2027022f29247faac97560e8f09a4
#!/usr/bin/env python # from distutils.core import setup,Extension from distutils import sysconfig import os, sys, re, glob, shutil version='2009.Q1b2' module_ext = sysconfig.get_config_var('SO') if sys.platform=="win32": install_base="Lib/site-packages" else: install_base = os.path.join(sysconfig.get_config_var('LIBDEST'),'site-packages') ext_modules=[] child_packages = [ "rdkit.Chem", "rdkit.DataManip", "rdkit.DataStructs", "rdkit.Dbase", "rdkit.DistanceGeometry", "rdkit.ForceField", "rdkit.Geometry", "rdkit.Logger", "rdkit.ML", "rdkit.Numerics", "rdkit.SimDivFilters", "rdkit.VLib", "rdkit.sping", "rdkit.utils", ] sos = [(os.path.join(install_base,'rdkit'),['rdkit/rdBase'+module_ext])] py_packages = ["rdkit"]+child_packages for pkg in child_packages: for root,dirs,files in os.walk(pkg.replace('.','/')): if '.svn' in dirs: dirs.remove('.svn') if 'test_data' in dirs: dirs.remove('test_data') modName=root.replace(os.path.sep,'.') if '__init__.py' in files and modName not in py_packages: py_packages.append(modName) files=[os.path.join(root,file) for file in files if (os.path.splitext(file)[-1]==module_ext or\ 'test_data' in root)] sos.extend([(os.path.join(install_base,root),files)]) extraBase='share/rdkit' projects=[] for root,dirs,files in os.walk('Projects'): if '.svn' in dirs: dirs.remove('.svn') files=[os.path.join(root,filen) for filen in files] projects.append((extraBase+'/'+root,files)) data_files = [(extraBase+'/Data',glob.glob('Data/.'))] data_files.extend([(extraBase,glob.glob('./.txt'))]) if sys.platform=='win32': data_files.extend([(extraBase+'/lib',glob.glob('bin/.dll'))]) else: data_files.extend([(extraBase+'/lib',glob.glob('bin/*'))]) data_files.extend(sos) documentation = [] for root,dirs,files in os.walk('Docs'): if '.svn' in dirs: dirs.remove('.svn') files=[os.path.join(root,filen) for filen in files] documentation.append((extraBase+'/'+root,files)) setup( name='rdkit', version=version, description='RDKit Cheminformatics Library', long_description="""Data structures, algorithms, and scripts for cheminformatics.""", author='Greg Landrum', author_email='glandrum@users.sourceforge.net', url='http://www.rdkit.org/', download_url = 'http://code.google.com/p/rdkit/downloads/list', license='BSD', platforms=['Windows','Linux','Mac OS-X'], classifiers = ['Development Status :: 5 - Production/Stable', 'Environment :: Console', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'Programming Language :: Python', 'Programming Language :: C++', 'License :: OSI Approved :: BSD License', 'Topic :: Scientific/Engineering :: Chemistry', ], packages=py_packages, ext_modules=ext_modules, package_dir={'rdkit':'rdkit'}, data_files=data_files+documentation+projects, )	rdkit/rdkit-orig	setup.py	Python	bsd-3-clause	3,461	[ "RDKit" ]	8ebfd24860d2f7a12d003e962f02b1ab2a9714329175073c423c7dbd49d517e6
'''Parameter sweep (2D): shared procedures.''' from __future__ import absolute_import, print_function import numpy as np from grid_cell_model.submitting.factory import SubmitterFactory from grid_cell_model.submitting.arguments import ArgumentCreator from grid_cell_model.submitting.noise.slopes import (DefaultSelector, NoThetaSelector) from grid_cell_model.otherpkg.log import log_info from simtools.storage import DataStorage def submitParamSweep(p, startG, endG, Nvals, ENV, simRootDir, simLabel, appName, rtLimit, numCPU, blocking, timePrefix, numRepeat, dry_run, extraIterparams=None, rc=None, kwargs): '''Submit and save metadata for the gE vs gI parameter sweep.''' printout = kwargs.pop('printout', True) if extraIterparams is None: extraIterparams = {} ac = ArgumentCreator(p, printout=printout) GArr = np.linspace(startG, endG, Nvals) print(GArr) g_AMPA_total_arr = [] g_GABA_total_arr = [] for E_coupling in GArr: for I_coupling in GArr: g_AMPA_total_arr.append(E_coupling) g_GABA_total_arr.append(I_coupling) iterparams = { 'g_AMPA_total' : np.array(g_AMPA_total_arr), 'g_GABA_total' : np.array(g_GABA_total_arr), } dimension_labels = ['g_AMPA_total', 'g_GABA_total'] dimensions = [Nvals, Nvals] iterparams.update(extraIterparams) ac.insertDict(iterparams, mult=False) ############################################################################### submitter = SubmitterFactory.getSubmitter( ac, appName, envType=ENV, rtLimit=rtLimit, output_dir=simRootDir, label=simLabel, blocking=blocking, timePrefix=timePrefix, numCPU=numCPU, kwargs) ac.setOption('output_dir', submitter.outputDir()) startJobNum = 0 filter = rc[0]len(GArr) + rc[1] if rc is not None else None submitter.submitAll(startJobNum, numRepeat, dry_run=dry_run, filter=filter) submitter.saveIterParams(iterparams, dimension_labels, dimensions, dry_run=dry_run) ############################################################################### def getBumpCurrentSlope(noise_sigma, threshold=0, type=None): ''' Parameters ---------- noise_sigma : int Noise level (sigma of the Gaussian) threshold : float Threshold below which slope values will be replaced with ``NaN``. type : string, optional If ``None`` the regular bump slope files will be used. If ``no_theta``, the bump slope files specific for the simulations wihtout theta oscillations will be used. ''' data_root = 'bump_slope_data' selector_cls = None if type is None: selector_cls = DefaultSelector elif type == 'no_theta': selector_cls = NoThetaSelector else: raise ValueError('Invalid bump slope type.') selector = selector_cls(data_root, threshold) return selector.get_slopes(noise_sigma) def getSpeedPercentile(p, path, grid_lambda, Nx): ''' Retrieve the file containing animal positions and calculate the bump speed value at the specified percentile. Parameters ---------- p : float The specified percentile. path : string Path to the file containing rat velocities grid_lambda : float Grid field spacing (cm) Nx : int Neural sheet size (neurons). THe bump has to travel this distance (in units of neurons) in order to return back to its original position, i.e. form a grid field. output : float The bump speed at the p-th percentile ''' from scipy.io import loadmat data = loadmat(path) dt = float(data['dt']) pos_x = data['pos_x'].flatten() pos_y = data['pos_y'].flatten() vel_x = np.diff(pos_x)/dt vel_y = np.diff(pos_y)/dt animal_s = np.abs(np.hstack((vel_x, vel_y))) bump_s = float(Nx) / grid_lambda animal_s res = np.percentile(bump_s, p) msg = "Loaded velocity data from: {0}".format(path) log_info("getAnimalSpeedPercentile", msg) msg = "{0:.2f}th percentile: {1:.3f}".format(p, res) log_info("getAnimalSpeedPercentile", msg) return res	MattNolanLab/ei-attractor	grid_cell_model/simulations/007_noise/param_sweep.py	Python	gpl-3.0	4,305	[ "Gaussian" ]	4627cc6cbde8cb855d56bc2f334bbf45457401c9b88c9ae8074d576265cd0c2b
from ase import * print [a.get_potential_energy() for a in PickleTrajectory('H.traj')] images = [PickleTrajectory('H.traj')[-1]] for i in range(4): images.append(images[0].copy()) images[-1].positions[6, 1] = 2 - images[0].positions[6, 1] neb = NEB(images) neb.interpolate() for image in images: image.set_calculator(LennardJones()) for a in neb.images: print a.positions[-1], a.get_potential_energy() dyn = QuasiNewton(neb, trajectory='mep.traj') print dyn.run(fmax=0.01, steps=25) for a in neb.images: print a.positions[-1], a.get_potential_energy()	freephys/python_ase	ase/test/neb.py	Python	gpl-3.0	571	[ "ASE" ]	a5485ed1457edd09bf32274909b48ba1b9e3dfe381c1c620cd4f14b014f8578e
# This file is part of PyEMMA. # # Copyright (c) 2015, 2014 Computational Molecular Biology Group, Freie Universitaet Berlin (GER) # # PyEMMA is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. import os import unittest import pkg_resources import mdtraj import numpy as np import pyemma.coordinates as coor from pyemma.coordinates.data.fragmented_trajectory_reader import FragmentedTrajectoryReader class TestFragmentedTrajectory(unittest.TestCase): @classmethod def setUpClass(cls): d = np.array([[i] for i in range(0, 100)]) # np.atleast_2d(np.arange(100)) cls.d = d return cls def test_full_trajectory(self): reader = FragmentedTrajectoryReader([self.d, self.d]) reader.chunksize = 0 expected = np.vstack((self.d, self.d)) output = reader.get_output(stride=1)[0] np.testing.assert_array_almost_equal(expected, output) def test_full_trajectory_random_access(self): reader = FragmentedTrajectoryReader([self.d, self.d]) indices = np.asarray([[0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199]]) out = reader.get_output(stride=indices, chunk=0) np.testing.assert_array_equal(np.array(out).squeeze(), np.array([1, 3, 3, 99, 0, 99])) def test_chunked_trajectory_random_access(self): reader = FragmentedTrajectoryReader([self.d, self.d]) indices = np.asarray([[0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199]]) out = reader.get_output(stride=indices, chunk=1) np.testing.assert_array_equal(np.array(out).squeeze(), np.array([1,3,3,99,0,99])) def test_full_trajectory_stridden(self): for stride in [1, 3, 5, 7, 13, 20]: reader = FragmentedTrajectoryReader([self.d, self.d]) reader.chunksize = 0 expected = np.vstack((self.d, self.d))[::stride] out = reader.get_output(stride=stride)[0] np.testing.assert_array_almost_equal(expected, out, err_msg="Failed for stride=%s" % stride) def test_full_trajectory_stridden_with_lag(self): reader = FragmentedTrajectoryReader([self.d, self.d]) data = np.vstack((self.d, self.d)) for lag in [1, 5, 7]: for stride in [1, 3, 5, 7, 13, 20]: reader.chunksize = 0 X, Y = None, None # not chunked for itraj, X, Y in reader.iterator(stride=stride, lag=lag): pass np.testing.assert_array_almost_equal(data[::stride][0:len(Y)], X) np.testing.assert_array_almost_equal(data[lag::stride], Y, err_msg='lag={lag}, stride={stride}'.format(stride=stride, lag=lag)) def test_fragmented_xtc(self): from pyemma.coordinates.tests.util import create_traj top_file = pkg_resources.resource_filename(__name__, 'data/test.pdb') trajfiles = [] for _ in range(3): f, _, _ = create_traj(top_file) trajfiles.append(f) try: # three trajectories: one consisting of all three, one consisting of the first, # one consisting of the first and the last source = coor.source([trajfiles, [trajfiles[0]], [trajfiles[0], trajfiles[2]]], top=top_file) source.chunksize = 1000 out = source.get_output(stride=1) trajs = [mdtraj.load(trajfiles[i], top=top_file).xyz.reshape(-1,9) for i in range(0,3)] np.testing.assert_equal(out[0], np.vstack(trajs)) np.testing.assert_equal(out[1], trajs[0]) np.testing.assert_equal(out[2], np.vstack((trajs[0], trajs[2]))) finally: for t in trajfiles: try: os.unlink(t) except EnvironmentError: pass def test_multiple_input_trajectories_random_access(self): indices = np.asarray([ [0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199], [1, 0], [1, 5], [1, 99], [2, 5], [2, 7], [2, 23] ]) expected = [np.array([1, 3, 3, 99, 0, 99]), np.array([0, 5, 99]), np.array([5, 7, 23])] for chunk_size in [0, 1, 3, 5, 13]: reader = FragmentedTrajectoryReader([[self.d, self.d], self.d, [self.d, self.d]]) out_full_trajectory_mode = reader.get_output(chunk=chunk_size, stride=indices) for i in range(3): np.testing.assert_array_equal(expected[i], out_full_trajectory_mode[i].squeeze()) def test_multiple_input_trajectories(self): reader = FragmentedTrajectoryReader([[self.d, self.d], self.d, [self.d, self.d]]) reader.chunksize = 37 out = reader.get_output() reader.chunksize = 0 out2 = reader.get_output() expected0_2 = np.vstack((self.d, self.d)) for itraj in range(0, 3): np.testing.assert_array_almost_equal(out[itraj], out2[itraj]) np.testing.assert_array_almost_equal(out[0], expected0_2) np.testing.assert_array_almost_equal(out[1], self.d) np.testing.assert_array_almost_equal(out[2], expected0_2) def test_chunked_trajectory_with_lag(self): data = np.vstack((self.d, self.d)) reader = FragmentedTrajectoryReader([self.d, self.d]) for lag in [0, 1, 3]: for stride in [1, 3, 5]: for chunksize in [1, 34, 53, 72]: reader.chunksize = chunksize if lag > 0: collected = None collected_lagged = None for itraj, X, Y in reader.iterator(stride=stride, lag=lag): collected = X if collected is None else np.vstack((collected, X)) collected_lagged = Y if collected_lagged is None else np.vstack((collected_lagged, Y)) np.testing.assert_array_almost_equal(data[::stride][0:len(collected_lagged)], collected, err_msg="lag={}, stride={}, cs={}".format( lag, stride, chunksize )) np.testing.assert_array_almost_equal(data[lag::stride], collected_lagged) else: collected = None for itraj, X in reader.iterator(stride=stride): collected = X if collected is None else np.vstack((collected, X)) np.testing.assert_array_almost_equal(data[::stride], collected) def test_index_to_reader_index(self): reader = FragmentedTrajectoryReader([self.d, self.d]) assert (0, 0) == reader._index_to_reader_index(0, 0), "first frame is first frame of first reader" assert (0, 1) == reader._index_to_reader_index(1, 0), "second frame is second frame of first reader" assert (1, 0) == reader._index_to_reader_index(100, 0), "101'st frame is first frame of second reader" assert (1, 1) == reader._index_to_reader_index(101, 0), "102'nd frame is second frame of second reader" with self.assertRaises(ValueError): reader._index_to_reader_index(-1, 0) with self.assertRaises(ValueError): reader._index_to_reader_index(200, 0) def test_cols(self): dim = 5 arr = np.arange(60).reshape(-1, dim) data = [(arr, arr), arr, (arr, arr, arr)] reader = FragmentedTrajectoryReader(data) cols = (0, 3) for itraj, x in reader.iterator(chunk=0, return_trajindex=True, cols=cols): if isinstance(data[itraj], tuple): syn_traj = np.concatenate(data[itraj]) else: syn_traj = data[itraj] np.testing.assert_equal(x, syn_traj[:, cols]) def test_raise_different_dims(self): data = [self.d, np.array([[1,2,3], [4,5,6]])] with self.assertRaises(ValueError): FragmentedTrajectoryReader(data) def test_with_save_traj(self): path = pkg_resources.resource_filename(__name__, 'data') + os.path.sep pdb_file = os.path.join(path, 'bpti_ca.pdb') traj_files = [ os.path.join(path, 'bpti_001-033.xtc'), os.path.join(path, 'bpti_034-066.xtc'), os.path.join(path, 'bpti_067-100.xtc') ] source_frag = coor.source([traj_files], top=pdb_file) full_data = source_frag.get_output()[0] last_frame_fragment_0 = [0,32] first_frame_fragment_1 = [0,33] first_frame_fragment_2 = [0,66] reshape = lambda f: f.xyz.reshape((f.xyz.shape[0],f.xyz.shape[1] * f.xyz.shape[2])).squeeze() # Frames in the first fragment: frames = coor.save_traj(source_frag, [last_frame_fragment_0], None) np.testing.assert_equal(reshape(frames), full_data[32]) # Frames the first and second fragments frames = coor.save_traj(source_frag, [last_frame_fragment_0, first_frame_fragment_1], None) np.testing.assert_equal(reshape(frames), full_data[np.array([32, 33])]) # Frames only in the second fragment frames = coor.save_traj(source_frag, [first_frame_fragment_1], None) np.testing.assert_equal(reshape(frames), full_data[33]) # Frames only in the second and third fragment frames = coor.save_traj(source_frag, [first_frame_fragment_1, first_frame_fragment_2], None) np.testing.assert_equal(reshape(frames), full_data[np.array([33, 66])])	markovmodel/PyEMMA	pyemma/coordinates/tests/test_fragmented_trajectory.py	Python	lgpl-3.0	10,158	[ "MDTraj" ]	30fe81e077be5276421e4b866bcad5eea5d7341a1a80220eab70e42df09a6612
""" .. versionadded:: v6r20 FTS3Agent implementation. It is in charge of submitting and monitoring all the transfers. It can be duplicated. .. literalinclude:: ../ConfigTemplate.cfg :start-after: ##BEGIN FTS3Agent :end-before: ##END FTS3Agent :dedent: 2 :caption: FTS3Agent options """ from __future__ import absolute_import from __future__ import division from __future__ import print_function __RCSID__ = "$Id$" import errno import time # from threading import current_thread from multiprocessing.pool import ThreadPool # We use the dummy module because we use the ThreadPool from multiprocessing.dummy import current_process from socket import gethostname from DIRAC import S_OK, S_ERROR from DIRAC.AccountingSystem.Client.Types.DataOperation import DataOperation from DIRAC.Core.Base.AgentModule import AgentModule from DIRAC.Core.Utilities.DErrno import cmpError from DIRAC.Core.Utilities.DictCache import DictCache from DIRAC.Core.Utilities.Time import fromString from DIRAC.ConfigurationSystem.Client.Helpers.Resources import getFTS3ServerDict from DIRAC.ConfigurationSystem.Client.Helpers.Operations import Operations as opHelper from DIRAC.ConfigurationSystem.Client.Helpers.Registry import getDNForUsername from DIRAC.FrameworkSystem.Client.Logger import gLogger from DIRAC.FrameworkSystem.Client.ProxyManagerClient import gProxyManager from DIRAC.DataManagementSystem.private import FTS3Utilities from DIRAC.DataManagementSystem.DB.FTS3DB import FTS3DB from DIRAC.DataManagementSystem.Client.FTS3Job import FTS3Job from DIRAC.RequestManagementSystem.Client.ReqClient import ReqClient # pylint: disable=attribute-defined-outside-init AGENT_NAME = "DataManagement/FTS3Agent" # Lifetime in seconds of the proxy we download for submission PROXY_LIFETIME = 43200 # 12 hours class FTS3Agent(AgentModule): """ This Agent is responsible of interacting with the FTS3 services. Several of them can run in parallel. It first treats the Operations, by creating new FTS jobs and performing callback. Then, it monitors the current jobs. CAUTION: This agent and the FTSAgent cannot run together. """ def __readConf(self): """ Read configurations :return: S_OK()/S_ERROR() """ # Getting all the possible servers res = getFTS3ServerDict() if not res['OK']: gLogger.error(res['Message']) return res srvDict = res['Value'] serverPolicyType = opHelper().getValue('DataManagement/FTSPlacement/FTS3/ServerPolicy', 'Random') self._serverPolicy = FTS3Utilities.FTS3ServerPolicy(srvDict, serverPolicy=serverPolicyType) self.maxNumberOfThreads = self.am_getOption("MaxThreads", 10) # Number of Operation we treat in one loop self.operationBulkSize = self.am_getOption("OperationBulkSize", 20) # Number of Jobs we treat in one loop self.jobBulkSize = self.am_getOption("JobBulkSize", 20) self.maxFilesPerJob = self.am_getOption("MaxFilesPerJob", 100) self.maxAttemptsPerFile = self.am_getOption("MaxAttemptsPerFile", 256) self.kickDelay = self.am_getOption("KickAssignedHours", 1) self.maxKick = self.am_getOption("KickLimitPerCycle", 100) self.deleteDelay = self.am_getOption("DeleteGraceDays", 180) self.maxDelete = self.am_getOption("DeleteLimitPerCycle", 100) # lifetime of the proxy we download to delegate to FTS self.proxyLifetime = self.am_getOption("ProxyLifetime", PROXY_LIFETIME) return S_OK() def initialize(self): """ Agent's initialization :return: S_OK()/S_ERROR() """ self._globalContextCache = {} # name that will be used in DB for assignment tag self.assignmentTag = gethostname().split('.')[0] res = self.__readConf() # We multiply by two because of the two threadPools self.fts3db = FTS3DB(pool_size=2 * self.maxNumberOfThreads) self.jobsThreadPool = ThreadPool(self.maxNumberOfThreads) self.opsThreadPool = ThreadPool(self.maxNumberOfThreads) return res def beginExecution(self): """ Reload configurations before start of a cycle :return: S_OK()/S_ERROR() """ return self.__readConf() def getFTS3Context(self, username, group, ftsServer, threadID): """ Returns an fts3 context for a given user, group and fts server The context pool is per thread, and there is one context per tuple (user, group, server). We dump the proxy of a user to a file (shared by all the threads), and use it to make the context. The proxy needs a lifetime of self.proxyLifetime, is cached for cacheTime = (2lifeTime/3) - 10mn, and the lifetime of the context is 45mn The reason for cacheTime to be what it is is because the FTS3 server will ask for a new proxy after 2/3rd of the existing proxy has expired, so we renew it just before :param str username: name of the user :param str group: group of the user :param str ftsServer: address of the server :param str threadID: thread ID :returns: S_OK with the context object """ log = gLogger.getSubLogger("getFTS3Context", child=True) contextes = self._globalContextCache.setdefault(threadID, DictCache()) idTuple = (username, group, ftsServer) log.debug("Getting context for %s" % (idTuple, )) # We keep a context in the cache for 45 minutes # (so it needs to be valid at least 15 since we add it for one hour) if not contextes.exists(idTuple, 15 60): res = getDNForUsername(username) if not res['OK']: return res # We take the first DN returned userDN = res['Value'][0] log.debug("UserDN %s" % userDN) # We dump the proxy to a file. # It has to have a lifetime of self.proxyLifetime # Because the FTS3 servers cache it for 2/3rd of the lifetime # we should make our cache a bit less than 2/3rd of the lifetime cacheTime = int(2 * self.proxyLifetime / 3) - 600 res = gProxyManager.downloadVOMSProxyToFile( userDN, group, requiredTimeLeft=self.proxyLifetime, cacheTime=cacheTime) if not res['OK']: return res proxyFile = res['Value'] log.debug("Proxy file %s" % proxyFile) # We generate the context # In practice, the lifetime will be less than proxyLifetime # because we reuse a cached proxy. However, the cached proxy will # never forced a redelegation, because it is recent enough for FTS3 servers. # The delegation is forced when 2/3 rd of the lifetime are left, and we get a fresh # one just before. So no problem res = FTS3Job.generateContext(ftsServer, proxyFile, lifetime=self.proxyLifetime) if not res['OK']: return res context = res['Value'] # we add it to the cache for this thread for 1h contextes.add(idTuple, 3600, context) return S_OK(contextes.get(idTuple)) def _monitorJob(self, ftsJob): """ * query the FTS servers * update the FTSFile status * update the FTSJob status :param ftsJob: FTS job :return: ftsJob, S_OK()/S_ERROR() """ # General try catch to avoid that the tread dies try: threadID = current_process().name log = gLogger.getSubLogger("_monitorJob/%s" % ftsJob.jobID, child=True) res = self.getFTS3Context( ftsJob.username, ftsJob.userGroup, ftsJob.ftsServer, threadID=threadID) if not res['OK']: log.error("Error getting context", res) return ftsJob, res context = res['Value'] res = ftsJob.monitor(context=context) if not res['OK']: log.error("Error monitoring job", res) # If the job was not found on the server, update the DB if cmpError(res, errno.ESRCH): res = self.fts3db.cancelNonExistingJob(ftsJob.operationID, ftsJob.ftsGUID) return ftsJob, res # { fileID : { Status, Error } } filesStatus = res['Value'] # Specify the job ftsGUID to make sure we do not overwrite # status of files already taken by newer jobs res = self.fts3db.updateFileStatus(filesStatus, ftsGUID=ftsJob.ftsGUID) if not res['OK']: log.error("Error updating file fts status", "%s, %s" % (ftsJob.ftsGUID, res)) return ftsJob, res upDict = { ftsJob.jobID: { 'status': ftsJob.status, 'error': ftsJob.error, 'completeness': ftsJob.completeness, 'operationID': ftsJob.operationID, 'lastMonitor': True, } } res = self.fts3db.updateJobStatus(upDict) if ftsJob.status in ftsJob.FINAL_STATES: self.__sendAccounting(ftsJob) return ftsJob, res except Exception as e: log.exception("Exception while monitoring job", repr(e)) return ftsJob, S_ERROR(0, "Exception %s" % repr(e)) @staticmethod def _monitorJobCallback(returnedValue): """ Callback when a job has been monitored :param returnedValue: value returned by the _monitorJob method (ftsJob, standard dirac return struct) """ ftsJob, res = returnedValue log = gLogger.getSubLogger("_monitorJobCallback/%s" % ftsJob.jobID, child=True) if not res['OK']: log.error("Error updating job status", res) else: log.debug("Successfully updated job status") def monitorJobsLoop(self): """ * fetch the active FTSJobs from the DB * spawn a thread to monitor each of them :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("monitorJobs", child=True) log.debug("Size of the context cache %s" % len(self._globalContextCache)) log.debug("Getting active jobs") # get jobs from DB res = self.fts3db.getActiveJobs(limit=self.jobBulkSize, jobAssignmentTag=self.assignmentTag) if not res['OK']: log.error("Could not retrieve ftsJobs from the DB", res) return res activeJobs = res['Value'] log.info("%s jobs to queue for monitoring" % len(activeJobs)) # We store here the AsyncResult object on which we are going to wait applyAsyncResults = [] # Starting the monitoring threads for ftsJob in activeJobs: log.debug("Queuing executing of ftsJob %s" % ftsJob.jobID) # queue the execution of self._monitorJob( ftsJob ) in the thread pool # The returned value is passed to _monitorJobCallback applyAsyncResults.append(self.jobsThreadPool.apply_async( self._monitorJob, (ftsJob, ), callback=self._monitorJobCallback)) log.debug("All execution queued") # Waiting for all the monitoring to finish while not all([r.ready() for r in applyAsyncResults]): log.debug("Not all the tasks are finished") time.sleep(0.5) log.debug("All the tasks have completed") return S_OK() @staticmethod def _treatOperationCallback(returnedValue): """ Callback when an operation has been treated :param returnedValue: value returned by the _treatOperation method (ftsOperation, standard dirac return struct) """ operation, res = returnedValue log = gLogger.getSubLogger("_treatOperationCallback/%s" % operation.operationID, child=True) if not res['OK']: log.error("Error treating operation", res) else: log.debug("Successfully treated operation") def _treatOperation(self, operation): """ Treat one operation: * does the callback if the operation is finished * generate new jobs and submits them :param operation: the operation to treat :return: operation, S_OK()/S_ERROR() """ try: threadID = current_process().name log = gLogger.getSubLogger("treatOperation/%s" % operation.operationID, child=True) # If the operation is totally processed # we perform the callback if operation.isTotallyProcessed(): log.debug("FTS3Operation %s is totally processed" % operation.operationID) res = operation.callback() if not res['OK']: log.error("Error performing the callback", res) log.info("Putting back the operation") dbRes = self.fts3db.persistOperation(operation) if not dbRes['OK']: log.error("Could not persist operation", dbRes) return operation, res else: log.debug("FTS3Operation %s is not totally processed yet" % operation.operationID) # This flag is set to False if we want to stop the ongoing processing # of an operation, typically when the matching RMS Request has been # canceled (see below) continueOperationProcessing = True # Check the status of the associated RMS Request. # If it is canceled or does not exist anymore then we will not create new FTS3Jobs, and mark # this as FTS3Operation canceled. if operation.rmsReqID: res = ReqClient().getRequestStatus(operation.rmsReqID) if not res['OK']: # If the Request does not exist anymore if cmpError(res, errno.ENOENT): log.info( "The RMS Request does not exist anymore, canceling the FTS3Operation", "rmsReqID: %s, FTS3OperationID: %s" % (operation.rmsReqID, operation.operationID)) operation.status = 'Canceled' continueOperationProcessing = False else: log.error("Could not get request status", res) return operation, res else: rmsReqStatus = res['Value'] if rmsReqStatus == 'Canceled': log.info( "The RMS Request is canceled, canceling the FTS3Operation", "rmsReqID: %s, FTS3OperationID: %s" % (operation.rmsReqID, operation.operationID)) operation.status = 'Canceled' continueOperationProcessing = False if continueOperationProcessing: res = operation.prepareNewJobs( maxFilesPerJob=self.maxFilesPerJob, maxAttemptsPerFile=self.maxAttemptsPerFile) if not res['OK']: log.error("Cannot prepare new Jobs", "FTS3Operation %s : %s" % (operation.operationID, res)) return operation, res newJobs = res['Value'] log.debug("FTS3Operation %s: %s new jobs to be submitted" % (operation.operationID, len(newJobs))) for ftsJob in newJobs: res = self._serverPolicy.chooseFTS3Server() if not res['OK']: log.error(res) continue ftsServer = res['Value'] log.debug("Use %s server" % ftsServer) ftsJob.ftsServer = ftsServer res = self.getFTS3Context( ftsJob.username, ftsJob.userGroup, ftsServer, threadID=threadID) if not res['OK']: log.error("Could not get context", res) continue context = res['Value'] try: tpcProtocols = operation.fts3Plugin.selectTPCProtocols(ftsJob=ftsJob) except ValueError as e: log.error("Could not select TPC list", repr(e)) continue res = ftsJob.submit(context=context, protocols=tpcProtocols) if not res['OK']: log.error("Could not submit FTS3Job", "FTS3Operation %s : %s" % (operation.operationID, res)) continue operation.ftsJobs.append(ftsJob) submittedFileIds = res['Value'] log.info("FTS3Operation %s: Submitted job for %s transfers" % (operation.operationID, len(submittedFileIds))) # new jobs are put in the DB at the same time res = self.fts3db.persistOperation(operation) if not res['OK']: log.error("Could not persist operation", res) return operation, res except Exception as e: log.exception('Exception in the thread', repr(e)) return operation, S_ERROR("Exception %s" % repr(e)) def treatOperationsLoop(self): """ * Fetch all the FTSOperations which are not finished * Spawn a thread to treat each operation :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("treatOperations", child=True) log.debug("Size of the context cache %s" % len(self._globalContextCache)) log.info("Getting non finished operations") res = self.fts3db.getNonFinishedOperations( limit=self.operationBulkSize, operationAssignmentTag=self.assignmentTag) if not res['OK']: log.error("Could not get incomplete operations", res) return res incompleteOperations = res['Value'] log.info("Treating %s incomplete operations" % len(incompleteOperations)) applyAsyncResults = [] for operation in incompleteOperations: log.debug("Queuing executing of operation %s" % operation.operationID) # queue the execution of self._treatOperation( operation ) in the thread pool # The returned value is passed to _treatOperationCallback applyAsyncResults.append(self.opsThreadPool.apply_async( self._treatOperation, (operation, ), callback=self._treatOperationCallback)) log.debug("All execution queued") # Waiting for all the treatments to finish while not all([r.ready() for r in applyAsyncResults]): log.debug("Not all the tasks are finished") time.sleep(0.5) log.debug("All the tasks have completed") return S_OK() def kickOperations(self): """ Kick stuck operations :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("kickOperations", child=True) res = self.fts3db.kickStuckOperations(limit=self.maxKick, kickDelay=self.kickDelay) if not res['OK']: return res kickedOperations = res['Value'] log.info("Kicked %s stuck operations" % kickedOperations) return S_OK() def kickJobs(self): """ Kick stuck jobs :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("kickJobs", child=True) res = self.fts3db.kickStuckJobs(limit=self.maxKick, kickDelay=self.kickDelay) if not res['OK']: return res kickedJobs = res['Value'] log.info("Kicked %s stuck jobs" % kickedJobs) return S_OK() def deleteOperations(self): """ Delete final operations :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("deleteOperations", child=True) res = self.fts3db.deleteFinalOperations(limit=self.maxDelete, deleteDelay=self.deleteDelay) if not res['OK']: return res deletedOperations = res['Value'] log.info("Deleted %s final operations" % deletedOperations) return S_OK() def finalize(self): """ Finalize processing :return: S_OK()/S_ERROR() """ # Joining all the ThreadPools log = gLogger.getSubLogger("Finalize") log.debug("Closing jobsThreadPool") self.jobsThreadPool.close() self.jobsThreadPool.join() log.debug("jobsThreadPool joined") log.debug("Closing opsThreadPool") self.opsThreadPool.close() self.opsThreadPool.join() log.debug("opsThreadPool joined") return S_OK() def execute(self): """ One cycle execution :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("execute", child=True) log.info("Monitoring job") res = self.monitorJobsLoop() if not res['OK']: log.error("Error monitoring jobs", res) return res log.info("Treating operations") res = self.treatOperationsLoop() if not res['OK']: log.error("Error treating operations", res) return res log.info("Kicking stuck jobs") res = self.kickJobs() if not res['OK']: log.error("Error kicking jobs", res) return res log.info("Kicking stuck operations") res = self.kickOperations() if not res['OK']: log.error("Error kicking operations", res) return res log.info("Deleting final operations") res = self.deleteOperations() if not res['OK']: log.error("Error deleting operations", res) return res return S_OK() @staticmethod def __sendAccounting(ftsJob): """ prepare and send DataOperation to AccountingDB :param ftsJob: the FTS3Job from which we send the accounting info """ dataOp = DataOperation() dataOp.setStartTime(fromString(ftsJob.submitTime)) dataOp.setEndTime(fromString(ftsJob.lastUpdate)) dataOp.setValuesFromDict(ftsJob.accountingDict) dataOp.delayedCommit()	yujikato/DIRAC	src/DIRAC/DataManagementSystem/Agent/FTS3Agent.py	Python	gpl-3.0	20,683	[ "DIRAC" ]	71fa26820bd2db8ffe5b25e6d3df90c58dd7ac29bf9d4354921be905923ffd1a
# Rebinding to a cluster # Run by: # $ python run.py [N] [runs] [outFilename] [Logmode, default=False] # # Arguments: # - N: Number of particles in cluster # - runs: Number of simulation runs # - outFilename: Name of output file # - Logmode: false by default, if True, only 1 VTK-logged run is # performed. # # E.g.: # $ python run.py 7 1000 data.out # Or: # $ python run.py 7 1 data.out True # Modules # =============================== import sys #Also, set relative egfrd directory path sys.path.append('../../') import os import shutil import datetime import math from egfrd import * import model import gfrdbase import _gfrd from visualization import vtklogger if __name__ == "__main__": # Constants # =============================== # Number of particles in the cluster N = int(sys.argv[1]) # Number of runs runs = int(sys.argv[2]) # Output file outFilename = sys.argv[3] # LOGGING mode try: LOGGING = bool(sys.argv[4]) if (LOGGING==True): print "* Performing only 1 logging run." runs = 1 except: LOGGING = False # Particle constants sigma = 1e-5 # Diameter particle; big:1e-5 D = 1e-8 # Diffusion constant; big:1e-8 world_size = 1e-3 # Lengths of simulation box; normal: 1e-3 k1 = 1e-10 k2 = 1e2 # Spacing inbetween cluster particles AND cluster/B-particle spacing = sigma/1e5 # Create "unique" seed # =============================== currenttime = (long(datetime.datetime.now().year360024365+ datetime.datetime.now().month30.5243600+ datetime.datetime.now().day243600+datetime.datetime.now().hour3600+ datetime.datetime.now().minute60+datetime.datetime.now().second)) myrandom.seed(currenttime) print str('Seed: '+str(currenttime)) # Functions # =============================== def cartesian(g1, g2, ng1, ng2): """ Converts lattice coordinates (ng1, ng2) to cartesian coordinates Arguments: - Lattice vectors g1=[x1,y1] and g2=[x2,y2] - Lattice coordinates (ng1, ng2) """ cartesian_x = (ng1 * (g1[0]) + ng2 * (g2[0])) cartesian_y = (ng2 * (g2[1]) + ng1 * (g1[1])) return cartesian_x, cartesian_y def distance(x1, y1, x2, y2): """ Calculates the distance between points (x1, y1) and (x2, y2) """ return math.sqrt(math.pow((x1-x2),2)+math.pow((y1-y2),2)) def generate_possible_positions(N): """ Generates a list with possible coordinates and distances to center This function does the following: - It loops over square area of an hexagonal lattice (of size calculated to facilitate N particles) - Lattice coordinates and distance to the center of the area are stored if they are within circular boundaries. (The latter check is only done to be absolutely sure a circular shape is formed.) This information can be used in a later function. If the list of generated coordinates is sorted by distance to the center, N particles can be placed within a circular geometry by looping over the coordinates. Arguments: - N: number of particles to place. """ global w, A, spacing, sigma #, g1, g2, cartesian_x, cartesian_y, ng1, ng2 # Lattice vectors d1 = [1,0] d2 = [math.cos((math.pi)/3.0),math.sin((math.pi)/3.0)] # Scaled lattice vectors lengthLatticeVector = (sigma+spacing) g1 = [lengthLatticeVectord1[0], lengthLatticeVectord1[1]] g2 = [lengthLatticeVectord2[0], lengthLatticeVectord2[1]] # Factors to calculate square area of lattice needed """ factorNonSquareGrid = math.sqrt(1/(d1[0]d2[1]-d1[1]d2[0])) factorSquareToCircle = math.pi/2 #math.sqrt(math.pow((math.pi0.5),2)) # Calculate diameter of sphere L = (spacing+sigma)(math.ceil(math.sqrt(N))+2)factorNonSquareGridfactorSquareToCircle # "(math.ceil(math.sqrt(N))+2)"; ceil and +2: some margin diamondSide = (L/2)math.tan(pi/6)+(L/2)/math.tan(pi/6) diamondDiagonal = sin(pi/3)L #2sin(pi/3)L/2 """ # d1xd2y-d1yd2x diamondToSquare = math.sqrt((4d2[0]d2[1])/(0.25math.pi)) vectorsOnDiameter = math.ceil(math.sqrt(N)+2) numberOfVectors = diamondToSquare vectorsOnDiameter diameterCircle = math.ceil(math.sqrt(N)+2)lengthLatticeVector radiusCircle = diameterCircle/2 # Cartesian coordinates cartesian_x = 0 cartesian_y = 0 cartesian_z = 0 # The list with possible coordinates and distances to center clusterParticleCoordinates = [] for ng1 in range(int(-math.ceil(numberOfVectors/2)), int(math.ceil(numberOfVectors/2))): for ng2 in range(int(-math.ceil(numberOfVectors/2)), int(math.ceil(numberOfVectors/2))): cartesian_x, cartesian_y = cartesian(g1, g2, ng1, ng2) distanceToCenter = distance(cartesian_x, cartesian_y, 0, 0) if (distanceToCenter < radiusCircle): clusterParticleCoordinates.append([ distanceToCenter, cartesian_x, cartesian_y, cartesian_z ]) return clusterParticleCoordinates def make_cluster(N, coord_x, coord_y, coord_z): """ Places N particles on hexagonal lattice in spherical symmetry Arguments: - N: number of particles to place - coord_x, coord_y, coord_z: Coordinates where to place cluster """ # Generate list of positions and there distance to the center clusterParticleCoordinates = generate_possible_positions(N) # Sort this list clusterParticleCoordinates.sort(key=lambda x: x[0]) # Place center particle place_particle(w, C, [clusterParticleCoordinates[0][1]+coord_x, clusterParticleCoordinates[0][2]+coord_y, clusterParticleCoordinates[0][3]+coord_z]) # Place N particles starting with the particle closest to the # center, then placing the second closest particle, etc.. for i in range(1,N): try: place_particle(w, A, [clusterParticleCoordinates[i][1]+coord_x, clusterParticleCoordinates[i][2]+coord_y, clusterParticleCoordinates[i][3]+coord_z]) except: print "ERROR: couldn't place particle." def single_run(N, LOGGING): """ Single run of simulation """ global w, A, C, k1, k2 # Basic set up simulator # =============================== # Model m = model.ParticleModel(world_size) # Species A = model.Species('A', 0, sigma/2) m.add_species_type(A) B = model.Species('B', D, sigma/2) m.add_species_type(B) C = model.Species('C', 0, sigma/2) m.add_species_type(C) # Reaction rules r1 = model.create_binding_reaction_rule(A, B, C, k1) m.network_rules.add_reaction_rule(r1) r2 = model.create_unbinding_reaction_rule(C, A, B, k2) m.network_rules.add_reaction_rule(r2) # World w = gfrdbase.create_world(m, 3) # Simulator s = EGFRDSimulator(w, myrandom.rng) # Put in cluster make_cluster(N, world_size/2, world_size/2, world_size/2) # Put in reactants # place_particle(w, B, [world_size/2, world_size/2, world_size/2+sigma+spacing]) # Enable VTK Logger # =============================== if (LOGGING == True): vtk_output_directory = 'VTK_out' if (os.path.exists(vtk_output_directory)): print '* Warning: VTK directory already exists.' l = vtklogger.VTKLogger(s, vtk_output_directory, extra_particle_step=True) # Running # =============================== numberDetected = 0 if (LOGGING == True): while 1: l.log() # log s.step() # and make eGFRD step if s.last_reaction: numberDetected = numberDetected+1 if (numberDetected == 2): # print "2nd Reaction detected at: " + str(s.t) + "(" + str(s.last_reaction) + ")" reaction_time = s.t - previous_time break else: previous_time = s.t l.stop() else: while 1: s.step() # make eGFRD step if s.last_reaction: numberDetected = numberDetected+1 if (numberDetected == 2): # print "2nd Reaction detected at: " + str(s.t) + "(" + str(s.last_reaction) + ")" reaction_time = s.t - previous_time break else: previous_time = s.t s.stop(s.t) #TODO #del w #del s # If this one is thrown in, the runs suddenly stop?! #del m return (reaction_time) # Main part # =============================== if __name__ == "__main__": # Output file outFile = open(outFilename, 'w') outFile.close() outFile = open(outFilename, 'a') for M in range(runs): outFile.write(str(single_run(N, LOGGING)) + '\n') outFile.flush outFile.close() timetaken = (long(datetime.datetime.now().year360024365+ datetime.datetime.now().month30.5243600+ datetime.datetime.now().day243600+datetime.datetime.now().hour3600+ datetime.datetime.now().minute60+datetime.datetime.now().second)-currenttime) print "Done in "+ str(timetaken) +" seconds." # #### OLD CODE #def in_circle(cartesian_x, cartesian_y, r_x, r_y, R): # if (math.sqrt(math.pow((cartesian_x-r_x),2)+math.pow((cartesian_y-r_y),2)) < R): # return True # else: # return False # while end time hasn't come and #timesteps still below limit # while ((s.get_next_time() < endTime) and (n < EARLY_STOP)): # TODO # Terminate the simulation at appropriate time #""" #if (n >= EARLY_STOP): # print "Early stop (timestep limit)." # s.stop(s.t) # reaction_time = INF #else: # print "Early stop (time limit)." # s.stop(s.get_next_time()) # reaction_time = INF #""" # Make sure logger writes away information. # l.stop() #TODO REMOVED LOGGING	gfrd/egfrd	samples/memorytools/cluster.py	Python	gpl-2.0	10,318	[ "VTK" ]	1e5590b7745cf6758174b45f4093df4c6ea49e2ed2d5317b6521b7d139bef950
#! /usr/bin/env python """Calculate viral taxonomy abundance from BLAST and Bowtie inputs. Use '-h' for parameter help. """ import os import re import argparse import blast parser = argparse.ArgumentParser(description = ('Calculate viral taxonomy abundance for each sample from PHAST' 'viral database BLAST results and bowtie mapping information.')) parser.add_argument('--blast', help=('BLAST output file from search against the viral db.' 'Output format should be "-m 8".'), type=str, required=True) parser.add_argument('--bowtie_dir', help=('Directory containing output from bowtie in which reads ' 'were mapped to ORFs. Filenames should end in ".psl".'), type=str, required=True) parser.add_argument('--viral_db', help=('Phast viral database used for assigning taxonomy ' 'downloaded via' 'wget http://www.phantome.org/Downloads/Viruses/2016_05_01.tgz'), type=str, required=True) args = parser.parse_args() orf_gene_dict = blast.get_orf_gene_dict(args.blast) blast.setup_viral_taxa_sql_db() viral_orf_fam_dict, viral_orf_genus_dict = blast.get_viral_orf_taxa_dicts( orf_gene_dict, args.viral_db) bowtie_files = [os.path.join(args.bowtie_dir, f) for f in os.listdir(args.bowtie_dir) if f.endswith('.psl')] count_mapped_reads = 0 count_fam_reads = 0 count_genus_reads = 0 count_total_reads = 0 for bowtie_file in bowtie_files: match = re.search(r'([\w.]+/)([\w.]+)([.]psl)', bowtie_file) sample = match.group(2) read_count, mapped_reads = blast.count_sample_reads_bowtie(bowtie_file) count_mapped_reads = count_mapped_reads + mapped_reads count_total_reads = count_total_reads + read_count orf_abundance_dict = blast.get_orf_abundance_dict(bowtie_file) sample_viral_fam_dict, sample_viral_genus_dict = ( blast.get_sample_viral_taxa_abundances( orf_abundance_dict,viral_orf_fam_dict,viral_orf_genus_dict) ) fam_count = 0 viral_raw_fam_ab_file = sample + '.fam_raw_abundance.txt' viral_raw_fam_ab_output = open(viral_raw_fam_ab_file, 'w') viral_raw_fam_ab_output.write('ID\t%s\n' % sample) for fam, ab in sample_viral_fam_dict.items(): fam_count += 1 viral_raw_fam_ab_output.write('%s\t%d\n' % (fam, ab)) viral_raw_fam_ab_output.close() #viral_norm_fam_ab_file = sample + '.fam_norm_abundance.txt' #viral_norm_fam_ab_output = open(viral_norm_fam_ab_file, 'w') #viral_norm_fam_ab_output.write('ID\t%s\n' % sample) #for fam, ab in sample_viral_fam_dict.items(): # norm_ab = float(ab) / float(count_total_reads) # viral_norm_fam_ab_output.write('%s\t%e\n' % (fam, norm_ab)) #viral_norm_fam_ab_output.close() genus_count = 0 viral_raw_genus_ab_file = sample + '.genus_raw_abundance.txt' viral_raw_genus_ab_output = open(viral_raw_genus_ab_file, 'w') viral_raw_genus_ab_output.write('ID\t%s\n' % sample) for genus, ab in sample_viral_genus_dict.items(): genus_count += 1 viral_raw_genus_ab_output.write('%s\t%d\n' % (genus, ab)) viral_raw_genus_ab_output.close() count_fam_reads = (count_fam_reads + (sum(sample_viral_fam_dict.values()))) count_genus_reads = (count_genus_reads + (sum(sample_viral_genus_dict.values()))) output = ('Sample: %s\nReads - %d\nFamilies: %s\nGenera: %s\n\n' % (sample, read_count, fam_count, genus_count)) print(output) output = ('Number of total reads: %d\nNumber of mapped reads: %d\n' 'Number of mapped reads with family annotation: %d\n' 'Number of mapped reads with genus annotation: %d') % ( count_total_reads, count_mapped_reads, count_fam_reads, count_genus_reads) print(output)	chrisLanderson/rumen_virome	scripts/viral_taxa_blast2tsv.py	Python	mit	3,865	[ "BLAST", "Bowtie" ]	48ad6214500daaa4c9527c3fca2bf10b925a68d821e8ff3834d5b1aa5d889467
# coding: utf-8 # Copyright (c) Pymatgen Development Team. # Distributed under the terms of the MIT License. """ This module implements representations of slabs and surfaces, as well as algorithms for generating them. If you use this module, please consider citing the following work:: R. Tran, Z. Xu, B. Radhakrishnan, D. Winston, W. Sun, K. A. Persson, S. P. Ong, "Surface Energies of Elemental Crystals", Scientific Data, 2016, 3:160080, doi: 10.1038/sdata.2016.80. as well as:: Sun, W.; Ceder, G. Efficient creation and convergence of surface slabs, Surface Science, 2013, 617, 53–59, doi:10.1016/j.susc.2013.05.016. """ import copy import itertools import json import logging import math import os import warnings from functools import reduce from math import gcd import numpy as np from monty.fractions import lcm from scipy.cluster.hierarchy import fcluster, linkage from scipy.spatial.distance import squareform from pymatgen.analysis.structure_matcher import StructureMatcher from pymatgen.core.lattice import Lattice from pymatgen.core.periodic_table import get_el_sp from pymatgen.core.sites import PeriodicSite from pymatgen.core.structure import Structure from pymatgen.symmetry.analyzer import SpacegroupAnalyzer from pymatgen.util.coord import in_coord_list __author__ = "Richard Tran, Wenhao Sun, Zihan Xu, Shyue Ping Ong" logger = logging.getLogger(__name__) class Slab(Structure): """ Subclass of Structure representing a Slab. Implements additional attributes pertaining to slabs, but the init method does not actually implement any algorithm that creates a slab. This is a DUMMY class who's init method only holds information about the slab. Also has additional methods that returns other information about a slab such as the surface area, normal, and atom adsorption. Note that all Slabs have the surface normal oriented perpendicular to the a and b lattice vectors. This means the lattice vectors a and b are in the surface plane and the c vector is out of the surface plane (though not necessarily perpendicular to the surface). .. attribute:: miller_index Miller index of plane parallel to surface. .. attribute:: scale_factor Final computed scale factor that brings the parent cell to the surface cell. .. attribute:: shift The shift value in Angstrom that indicates how much this slab has been shifted. """ def __init__( self, lattice, species, coords, miller_index, oriented_unit_cell, shift, scale_factor, reorient_lattice=True, validate_proximity=False, to_unit_cell=False, reconstruction=None, coords_are_cartesian=False, site_properties=None, energy=None, ): """ Makes a Slab structure, a structure object with additional information and methods pertaining to slabs. Args: lattice (Lattice/3x3 array): The lattice, either as a :class:`pymatgen.core.lattice.Lattice` or simply as any 2D array. Each row should correspond to a lattice vector. E.g., [[10,0,0], [20,10,0], [0,0,30]] specifies a lattice with lattice vectors [10,0,0], [20,10,0] and [0,0,30]. species ([Species]): Sequence of species on each site. Can take in flexible input, including: i. A sequence of element / species specified either as string symbols, e.g. ["Li", "Fe2+", "P", ...] or atomic numbers, e.g., (3, 56, ...) or actual Element or Species objects. ii. List of dict of elements/species and occupancies, e.g., [{"Fe" : 0.5, "Mn":0.5}, ...]. This allows the setup of disordered structures. coords (Nx3 array): list of fractional/cartesian coordinates of each species. miller_index ([h, k, l]): Miller index of plane parallel to surface. Note that this is referenced to the input structure. If you need this to be based on the conventional cell, you should supply the conventional structure. oriented_unit_cell (Structure): The oriented_unit_cell from which this Slab is created (by scaling in the c-direction). shift (float): The shift in the c-direction applied to get the termination. scale_factor (np.ndarray): scale_factor Final computed scale factor that brings the parent cell to the surface cell. reorient_lattice (bool): reorients the lattice parameters such that the c direction is along the z axis. validate_proximity (bool): Whether to check if there are sites that are less than 0.01 Ang apart. Defaults to False. reconstruction (str): Type of reconstruction. Defaults to None if the slab is not reconstructed. coords_are_cartesian (bool): Set to True if you are providing coordinates in cartesian coordinates. Defaults to False. site_properties (dict): Properties associated with the sites as a dict of sequences, e.g., {"magmom":[5,5,5,5]}. The sequences have to be the same length as the atomic species and fractional_coords. Defaults to None for no properties. energy (float): A value for the energy. """ self.oriented_unit_cell = oriented_unit_cell self.miller_index = tuple(miller_index) self.shift = shift self.reconstruction = reconstruction self.scale_factor = np.array(scale_factor) self.energy = energy self.reorient_lattice = reorient_lattice if self.reorient_lattice: if coords_are_cartesian: coords = lattice.get_fractional_coords(coords) coords_are_cartesian = False lattice = Lattice.from_parameters( lattice.a, lattice.b, lattice.c, lattice.alpha, lattice.beta, lattice.gamma, ) super().__init__( lattice, species, coords, validate_proximity=validate_proximity, to_unit_cell=to_unit_cell, coords_are_cartesian=coords_are_cartesian, site_properties=site_properties, ) def get_orthogonal_c_slab(self): """ This method returns a Slab where the normal (c lattice vector) is "forced" to be exactly orthogonal to the surface a and b lattice vectors. Note that this breaks inherent symmetries in the slab. It should be pointed out that orthogonality is not required to get good surface energies, but it can be useful in cases where the slabs are subsequently used for postprocessing of some kind, e.g. generating GBs or interfaces. """ a, b, c = self.lattice.matrix new_c = np.cross(a, b) new_c /= np.linalg.norm(new_c) new_c = np.dot(c, new_c) * new_c new_latt = Lattice([a, b, new_c]) return Slab( lattice=new_latt, species=self.species_and_occu, coords=self.cart_coords, miller_index=self.miller_index, oriented_unit_cell=self.oriented_unit_cell, shift=self.shift, scale_factor=self.scale_factor, coords_are_cartesian=True, energy=self.energy, reorient_lattice=self.reorient_lattice, site_properties=self.site_properties, ) def get_tasker2_slabs(self, tol=0.01, same_species_only=True): """ Get a list of slabs that have been Tasker 2 corrected. Args: tol (float): Tolerance to determine if atoms are within same plane. This is a fractional tolerance, not an absolute one. same_species_only (bool): If True, only that are of the exact same species as the atom at the outermost surface are considered for moving. Otherwise, all atoms regardless of species that is within tol are considered for moving. Default is True (usually the desired behavior). Returns: ([Slab]) List of tasker 2 corrected slabs. """ sites = list(self.sites) slabs = [] sortedcsites = sorted(sites, key=lambda site: site.c) # Determine what fraction the slab is of the total cell size in the # c direction. Round to nearest rational number. nlayers_total = int(round(self.lattice.c / self.oriented_unit_cell.lattice.c)) nlayers_slab = int(round((sortedcsites[-1].c - sortedcsites[0].c) * nlayers_total)) slab_ratio = nlayers_slab / nlayers_total a = SpacegroupAnalyzer(self) symm_structure = a.get_symmetrized_structure() def equi_index(site): for i, equi_sites in enumerate(symm_structure.equivalent_sites): if site in equi_sites: return i raise ValueError("Cannot determine equi index!") for surface_site, shift in [ (sortedcsites[0], slab_ratio), (sortedcsites[-1], -slab_ratio), ]: tomove = [] fixed = [] for site in sites: if abs(site.c - surface_site.c) < tol and ( (not same_species_only) or site.species == surface_site.species ): tomove.append(site) else: fixed.append(site) # Sort and group the sites by the species and symmetry equivalence tomove = sorted(tomove, key=lambda s: equi_index(s)) grouped = [list(sites) for k, sites in itertools.groupby(tomove, key=lambda s: equi_index(s))] if len(tomove) == 0 or any(len(g) % 2 != 0 for g in grouped): warnings.warn( "Odd number of sites to divide! Try changing " "the tolerance to ensure even division of " "sites or create supercells in a or b directions " "to allow for atoms to be moved!" ) continue combinations = [] for g in grouped: combinations.append(list(itertools.combinations(g, int(len(g) / 2)))) for selection in itertools.product(combinations): species = [site.species for site in fixed] fcoords = [site.frac_coords for site in fixed] for s in tomove: species.append(s.species) for group in selection: if s in group: fcoords.append(s.frac_coords) break else: # Move unselected atom to the opposite surface. fcoords.append(s.frac_coords + [0, 0, shift]) # sort by species to put all similar species together. sp_fcoord = sorted(zip(species, fcoords), key=lambda x: x[0]) species = [x[0] for x in sp_fcoord] fcoords = [x[1] for x in sp_fcoord] slab = Slab( self.lattice, species, fcoords, self.miller_index, self.oriented_unit_cell, self.shift, self.scale_factor, energy=self.energy, reorient_lattice=self.reorient_lattice, ) slabs.append(slab) s = StructureMatcher() unique = [ss[0] for ss in s.group_structures(slabs)] return unique def is_symmetric(self, symprec=0.1): """ Checks if slab is symmetric, i.e., contains inversion symmetry. Args: symprec (float): Symmetry precision used for SpaceGroup analyzer. Returns: (bool) Whether slab contains inversion symmetry. """ sg = SpacegroupAnalyzer(self, symprec=symprec) return sg.is_laue() def get_sorted_structure(self, key=None, reverse=False): """ Get a sorted copy of the structure. The parameters have the same meaning as in list.sort. By default, sites are sorted by the electronegativity of the species. Note that Slab has to override this because of the different __init__ args. Args: key: Specifies a function of one argument that is used to extract a comparison key from each list element: key=str.lower. The default value is None (compare the elements directly). reverse (bool): If set to True, then the list elements are sorted as if each comparison were reversed. """ sites = sorted(self, key=key, reverse=reverse) s = Structure.from_sites(sites) return Slab( s.lattice, s.species_and_occu, s.frac_coords, self.miller_index, self.oriented_unit_cell, self.shift, self.scale_factor, site_properties=s.site_properties, reorient_lattice=self.reorient_lattice, ) def copy(self, site_properties=None, sanitize=False): """ Convenience method to get a copy of the structure, with options to add site properties. Args: site_properties (dict): Properties to add or override. The properties are specified in the same way as the constructor, i.e., as a dict of the form {property: [values]}. The properties should be in the order of the original* structure if you are performing sanitization. sanitize (bool): If True, this method will return a sanitized structure. Sanitization performs a few things: (i) The sites are sorted by electronegativity, (ii) a LLL lattice reduction is carried out to obtain a relatively orthogonalized cell, (iii) all fractional coords for sites are mapped into the unit cell. Returns: A copy of the Structure, with optionally new site_properties and optionally sanitized. """ props = self.site_properties if site_properties: props.update(site_properties) return Slab( self.lattice, self.species_and_occu, self.frac_coords, self.miller_index, self.oriented_unit_cell, self.shift, self.scale_factor, site_properties=props, reorient_lattice=self.reorient_lattice, ) @property def dipole(self): """ Calculates the dipole of the Slab in the direction of the surface normal. Note that the Slab must be oxidation state-decorated for this to work properly. Otherwise, the Slab will always have a dipole of 0. """ dipole = np.zeros(3) mid_pt = np.sum(self.cart_coords, axis=0) / len(self) normal = self.normal for site in self: charge = sum([getattr(sp, "oxi_state", 0) * amt for sp, amt in site.species.items()]) dipole += charge * np.dot(site.coords - mid_pt, normal) * normal return dipole def is_polar(self, tol_dipole_per_unit_area=1e-3): """ Checks whether the surface is polar by computing the dipole per unit area. Note that the Slab must be oxidation state-decorated for this to work properly. Otherwise, the Slab will always be non-polar. Args: tol_dipole_per_unit_area (float): A tolerance. If the dipole magnitude per unit area is less than this value, the Slab is considered non-polar. Defaults to 1e-3, which is usually pretty good. Normalized dipole per unit area is used as it is more reliable than using the total, which tends to be larger for slabs with larger surface areas. """ dip_per_unit_area = self.dipole / self.surface_area return np.linalg.norm(dip_per_unit_area) > tol_dipole_per_unit_area @property def normal(self): """ Calculates the surface normal vector of the slab """ normal = np.cross(self.lattice.matrix[0], self.lattice.matrix[1]) normal /= np.linalg.norm(normal) return normal @property def surface_area(self): """ Calculates the surface area of the slab """ m = self.lattice.matrix return np.linalg.norm(np.cross(m[0], m[1])) @property def center_of_mass(self): """ Calculates the center of mass of the slab """ weights = [s.species.weight for s in self] center_of_mass = np.average(self.frac_coords, weights=weights, axis=0) return center_of_mass def add_adsorbate_atom(self, indices, specie, distance): """ Gets the structure of single atom adsorption. slab structure from the Slab class(in [0, 0, 1]) Args: indices ([int]): Indices of sites on which to put the absorbate. Absorbed atom will be displaced relative to the center of these sites. specie (Species/Element/str): adsorbed atom species distance (float): between centers of the adsorbed atom and the given site in Angstroms. """ # Let's do the work in cartesian coords center = np.sum([self[i].coords for i in indices], axis=0) / len(indices) coords = center + self.normal * distance / np.linalg.norm(self.normal) self.append(specie, coords, coords_are_cartesian=True) def __str__(self): comp = self.composition outs = [ "Slab Summary (%s)" % comp.formula, "Reduced Formula: %s" % comp.reduced_formula, "Miller index: %s" % (self.miller_index,), "Shift: %.4f, Scale Factor: %s" % (self.shift, self.scale_factor.__str__()), ] def to_s(x): return "%0.6f" % x outs.append("abc : " + " ".join([to_s(i).rjust(10) for i in self.lattice.abc])) outs.append("angles: " + " ".join([to_s(i).rjust(10) for i in self.lattice.angles])) outs.append("Sites ({i})".format(i=len(self))) for i, site in enumerate(self): outs.append( " ".join( [ str(i + 1), site.species_string, " ".join([to_s(j).rjust(12) for j in site.frac_coords]), ] ) ) return "\n".join(outs) def as_dict(self): """ :return: MSONAble dict """ d = super().as_dict() d["@module"] = self.__class__.__module__ d["@class"] = self.__class__.__name__ d["oriented_unit_cell"] = self.oriented_unit_cell.as_dict() d["miller_index"] = self.miller_index d["shift"] = self.shift d["scale_factor"] = self.scale_factor.tolist() d["reconstruction"] = self.reconstruction d["energy"] = self.energy return d @classmethod def from_dict(cls, d): """ :param d: dict :return: Creates slab from dict. """ lattice = Lattice.from_dict(d["lattice"]) sites = [PeriodicSite.from_dict(sd, lattice) for sd in d["sites"]] s = Structure.from_sites(sites) return Slab( lattice=lattice, species=s.species_and_occu, coords=s.frac_coords, miller_index=d["miller_index"], oriented_unit_cell=Structure.from_dict(d["oriented_unit_cell"]), shift=d["shift"], scale_factor=d["scale_factor"], site_properties=s.site_properties, energy=d["energy"], ) def get_surface_sites(self, tag=False): """ Returns the surface sites and their indices in a dictionary. The oriented unit cell of the slab will determine the coordination number of a typical site. We use VoronoiNN to determine the coordination number of bulk sites and slab sites. Due to the pathological error resulting from some surface sites in the VoronoiNN, we assume any site that has this error is a surface site as well. This will work for elemental systems only for now. Useful for analysis involving broken bonds and for finding adsorption sites. Args: tag (bool): Option to adds site attribute "is_surfsite" (bool) to all sites of slab. Defaults to False Returns: A dictionary grouping sites on top and bottom of the slab together. {"top": [sites with indices], "bottom": [sites with indices} TODO: Is there a way to determine site equivalence between sites in a slab and bulk system? This would allow us get the coordination number of a specific site for multi-elemental systems or systems with more than one unequivalent site. This will allow us to use this for compound systems. """ from pymatgen.analysis.local_env import VoronoiNN # Get a dictionary of coordination numbers # for each distinct site in the structure a = SpacegroupAnalyzer(self.oriented_unit_cell) ucell = a.get_symmetrized_structure() cn_dict = {} v = VoronoiNN() unique_indices = [equ[0] for equ in ucell.equivalent_indices] for i in unique_indices: el = ucell[i].species_string if el not in cn_dict.keys(): cn_dict[el] = [] # Since this will get the cn as a result of the weighted polyhedra, the # slightest difference in cn will indicate a different environment for a # species, eg. bond distance of each neighbor or neighbor species. The # decimal place to get some cn to be equal. cn = v.get_cn(ucell, i, use_weights=True) cn = float("%.5f" % (round(cn, 5))) if cn not in cn_dict[el]: cn_dict[el].append(cn) v = VoronoiNN() surf_sites_dict, properties = {"top": [], "bottom": []}, [] for i, site in enumerate(self): # Determine if site is closer to the top or bottom of the slab top = site.frac_coords[2] > self.center_of_mass[2] try: # A site is a surface site, if its environment does # not fit the environment of other sites cn = float("%.5f" % (round(v.get_cn(self, i, use_weights=True), 5))) if cn < min(cn_dict[site.species_string]): properties.append(True) key = "top" if top else "bottom" surf_sites_dict[key].append([site, i]) else: properties.append(False) except RuntimeError: # or if pathological error is returned, indicating a surface site properties.append(True) key = "top" if top else "bottom" surf_sites_dict[key].append([site, i]) if tag: self.add_site_property("is_surf_site", properties) return surf_sites_dict def have_equivalent_surfaces(self): """ Check if we have same number of equivalent sites on both surfaces. This is an alternative to checking Laue symmetry (is_symmetric()) if we want to ensure both surfaces in the slab are the same """ # tag the sites as either surface sites or not self.get_surface_sites(tag=True) a = SpacegroupAnalyzer(self) symm_structure = a.get_symmetrized_structure() # ensure each site on one surface has a # corresponding equivalent site on the other equal_surf_sites = [] for equ in symm_structure.equivalent_sites: # Top and bottom are arbitrary, we will just determine # if one site is on one side of the slab or the other top, bottom = 0, 0 for s in equ: if s.is_surf_site: if s.frac_coords[2] > self.center_of_mass[2]: top += 1 else: bottom += 1 # Check to see if the number of equivalent sites # on one side of the slab are equal to the other equal_surf_sites.append(top == bottom) return all(equal_surf_sites) def get_symmetric_site(self, point, cartesian=False): """ This method uses symmetry operations to find equivalent sites on both sides of the slab. Works mainly for slabs with Laue symmetry. This is useful for retaining the non-polar and symmetric properties of a slab when creating adsorbed structures or symmetric reconstructions. Arg: point: Fractional coordinate. Returns: point: Fractional coordinate. A point equivalent to the parameter point, but on the other side of the slab """ sg = SpacegroupAnalyzer(self) ops = sg.get_symmetry_operations(cartesian=cartesian) # Each operation on a point will return an equivalent point. # We want to find the point on the other side of the slab. for op in ops: slab = self.copy() site2 = op.operate(point) if "%.6f" % (site2[2]) == "%.6f" % (point[2]): continue # Add dummy site to check the overall structure is symmetric slab.append("O", point, coords_are_cartesian=cartesian) slab.append("O", site2, coords_are_cartesian=cartesian) sg = SpacegroupAnalyzer(slab) if sg.is_laue(): break # If not symmetric, remove the two added # sites and try another symmetry operator slab.remove_sites([len(slab) - 1]) slab.remove_sites([len(slab) - 1]) return site2 def symmetrically_add_atom(self, specie, point, coords_are_cartesian=False): """ Class method for adding a site at a specified point in a slab. Will add the corresponding site on the other side of the slab to maintain equivalent surfaces. Arg: specie (str): The specie to add point (coords): The coordinate of the site in the slab to add. coords_are_cartesian (bool): Is the point in cartesian coordinates Returns: (Slab): The modified slab """ # For now just use the species of the # surface atom as the element to add # Get the index of the corresponding site at the bottom point2 = self.get_symmetric_site(point, cartesian=coords_are_cartesian) self.append(specie, point, coords_are_cartesian=coords_are_cartesian) self.append(specie, point2, coords_are_cartesian=coords_are_cartesian) def symmetrically_remove_atoms(self, indices): """ Class method for removing sites corresponding to a list of indices. Will remove the corresponding site on the other side of the slab to maintain equivalent surfaces. Arg: indices ([indices]): The indices of the sites in the slab to remove. """ slabcopy = SpacegroupAnalyzer(self.copy()).get_symmetrized_structure() points = [slabcopy[i].frac_coords for i in indices] removal_list = [] for pt in points: # Get the index of the original site on top cart_point = slabcopy.lattice.get_cartesian_coords(pt) dist = [site.distance_from_point(cart_point) for site in slabcopy] site1 = dist.index(min(dist)) # Get the index of the corresponding site at the bottom for i, eq_sites in enumerate(slabcopy.equivalent_sites): if slabcopy[site1] in eq_sites: eq_indices = slabcopy.equivalent_indices[i] break i1 = eq_indices[eq_sites.index(slabcopy[site1])] for i2 in eq_indices: if i2 == i1: continue if slabcopy[i2].frac_coords[2] == slabcopy[i1].frac_coords[2]: continue # Test site remove to see if it results in symmetric slab s = self.copy() s.remove_sites([i1, i2]) if s.is_symmetric(): removal_list.extend([i1, i2]) break # If expected, 2 atoms are removed per index if len(removal_list) == 2 * len(indices): self.remove_sites(removal_list) else: warnings.warn("Equivalent sites could not be found for removal for all indices. Surface unchanged.") class SlabGenerator: """ This class generates different slabs using shift values determined by where a unique termination can be found along with other criterias such as where a termination doesn't break a polyhedral bond. The shift value then indicates where the slab layer will begin and terminate in the slab-vacuum system. .. attribute:: oriented_unit_cell A unit cell of the parent structure with the miller index of plane parallel to surface .. attribute:: parent Parent structure from which Slab was derived. .. attribute:: lll_reduce Whether or not the slabs will be orthogonalized .. attribute:: center_slab Whether or not the slabs will be centered between the vacuum layer .. attribute:: slab_scale_factor Final computed scale factor that brings the parent cell to the surface cell. .. attribute:: miller_index Miller index of plane parallel to surface. .. attribute:: min_slab_size Minimum size in angstroms of layers containing atoms .. attribute:: min_vac_size Minimize size in angstroms of layers containing vacuum """ def __init__( self, initial_structure, miller_index, min_slab_size, min_vacuum_size, lll_reduce=False, center_slab=False, in_unit_planes=False, primitive=True, max_normal_search=None, reorient_lattice=True, ): """ Calculates the slab scale factor and uses it to generate a unit cell of the initial structure that has been oriented by its miller index. Also stores the initial information needed later on to generate a slab. Args: initial_structure (Structure): Initial input structure. Note that to ensure that the miller indices correspond to usual crystallographic definitions, you should supply a conventional unit cell structure. miller_index ([h, k, l]): Miller index of plane parallel to surface. Note that this is referenced to the input structure. If you need this to be based on the conventional cell, you should supply the conventional structure. min_slab_size (float): In Angstroms or number of hkl planes min_vacuum_size (float): In Angstroms or number of hkl planes lll_reduce (bool): Whether to perform an LLL reduction on the eventual structure. center_slab (bool): Whether to center the slab in the cell with equal vacuum spacing from the top and bottom. in_unit_planes (bool): Whether to set min_slab_size and min_vac_size in units of hkl planes (True) or Angstrom (False/default). Setting in units of planes is useful for ensuring some slabs have a certain nlayer of atoms. e.g. for Cs (100), a 10 Ang slab will result in a slab with only 2 layer of atoms, whereas Fe (100) will have more layer of atoms. By using units of hkl planes instead, we ensure both slabs have the same number of atoms. The slab thickness will be in min_slab_size/math.ceil(self._proj_height/dhkl) multiples of oriented unit cells. primitive (bool): Whether to reduce any generated slabs to a primitive cell (this does not mean the slab is generated from a primitive cell, it simply means that after slab generation, we attempt to find shorter lattice vectors, which lead to less surface area and smaller cells). max_normal_search (int): If set to a positive integer, the code will conduct a search for a normal lattice vector that is as perpendicular to the surface as possible by considering multiples linear combinations of lattice vectors up to max_normal_search. This has no bearing on surface energies, but may be useful as a preliminary step to generating slabs for absorption and other sizes. It is typical that this will not be the smallest possible cell for simulation. Normality is not guaranteed, but the oriented cell will have the c vector as normal as possible (within the search range) to the surface. A value of up to the max absolute Miller index is usually sufficient. reorient_lattice (bool): reorients the lattice parameters such that the c direction is the third vector of the lattice matrix """ # pylint: disable=E1130 # Add Wyckoff symbols of the bulk, will help with # identfying types of sites in the slab system sg = SpacegroupAnalyzer(initial_structure) initial_structure.add_site_property("bulk_wyckoff", sg.get_symmetry_dataset()["wyckoffs"]) initial_structure.add_site_property("bulk_equivalent", sg.get_symmetry_dataset()["equivalent_atoms"].tolist()) latt = initial_structure.lattice miller_index = _reduce_vector(miller_index) # Calculate the surface normal using the reciprocal lattice vector. recp = latt.reciprocal_lattice_crystallographic normal = recp.get_cartesian_coords(miller_index) normal /= np.linalg.norm(normal) slab_scale_factor = [] non_orth_ind = [] eye = np.eye(3, dtype=np.int_) for i, j in enumerate(miller_index): if j == 0: # Lattice vector is perpendicular to surface normal, i.e., # in plane of surface. We will simply choose this lattice # vector as one of the basis vectors. slab_scale_factor.append(eye[i]) else: # Calculate projection of lattice vector onto surface normal. d = abs(np.dot(normal, latt.matrix[i])) / latt.abc[i] non_orth_ind.append((i, d)) # We want the vector that has maximum magnitude in the # direction of the surface normal as the c-direction. # Results in a more "orthogonal" unit cell. c_index, dist = max(non_orth_ind, key=lambda t: t[1]) if len(non_orth_ind) > 1: lcm_miller = lcm([miller_index[i] for i, d in non_orth_ind]) for (i, di), (j, dj) in itertools.combinations(non_orth_ind, 2): l = [0, 0, 0] l[i] = -int(round(lcm_miller / miller_index[i])) l[j] = int(round(lcm_miller / miller_index[j])) slab_scale_factor.append(l) if len(slab_scale_factor) == 2: break if max_normal_search is None: slab_scale_factor.append(eye[c_index]) else: index_range = sorted( reversed(range(-max_normal_search, max_normal_search + 1)), key=lambda x: abs(x), ) candidates = [] for uvw in itertools.product(index_range, index_range, index_range): if (not any(uvw)) or abs(np.linalg.det(slab_scale_factor + [uvw])) < 1e-8: continue vec = latt.get_cartesian_coords(uvw) l = np.linalg.norm(vec) cosine = abs(np.dot(vec, normal) / l) candidates.append((uvw, cosine, l)) if abs(abs(cosine) - 1) < 1e-8: # If cosine of 1 is found, no need to search further. break # We want the indices with the maximum absolute cosine, # but smallest possible length. uvw, cosine, l = max(candidates, key=lambda x: (x[1], -x[2])) slab_scale_factor.append(uvw) slab_scale_factor = np.array(slab_scale_factor) # Let's make sure we have a left-handed crystallographic system if np.linalg.det(slab_scale_factor) < 0: slab_scale_factor = -1 # Make sure the slab_scale_factor is reduced to avoid # unnecessarily large slabs reduced_scale_factor = [_reduce_vector(v) for v in slab_scale_factor] slab_scale_factor = np.array(reduced_scale_factor) single = initial_structure.copy() single.make_supercell(slab_scale_factor) # When getting the OUC, lets return the most reduced # structure as possible to reduce calculations self.oriented_unit_cell = Structure.from_sites(single, to_unit_cell=True) self.max_normal_search = max_normal_search self.parent = initial_structure self.lll_reduce = lll_reduce self.center_slab = center_slab self.slab_scale_factor = slab_scale_factor self.miller_index = miller_index self.min_vac_size = min_vacuum_size self.min_slab_size = min_slab_size self.in_unit_planes = in_unit_planes self.primitive = primitive self._normal = normal a, b, c = self.oriented_unit_cell.lattice.matrix self._proj_height = abs(np.dot(normal, c)) self.reorient_lattice = reorient_lattice def get_slab(self, shift=0, tol=0.1, energy=None): """ This method takes in shift value for the c lattice direction and generates a slab based on the given shift. You should rarely use this method. Instead, it is used by other generation algorithms to obtain all slabs. Arg: shift (float): A shift value in Angstrom that determines how much a slab should be shifted. tol (float): Tolerance to determine primitive cell. energy (float): An energy to assign to the slab. Returns: (Slab) A Slab object with a particular shifted oriented unit cell. """ h = self._proj_height p = round(h / self.parent.lattice.d_hkl(self.miller_index), 8) if self.in_unit_planes: nlayers_slab = int(math.ceil(self.min_slab_size / p)) nlayers_vac = int(math.ceil(self.min_vac_size / p)) else: nlayers_slab = int(math.ceil(self.min_slab_size / h)) nlayers_vac = int(math.ceil(self.min_vac_size / h)) nlayers = nlayers_slab + nlayers_vac species = self.oriented_unit_cell.species_and_occu props = self.oriented_unit_cell.site_properties props = {k: v * nlayers_slab for k, v in props.items()} frac_coords = self.oriented_unit_cell.frac_coords frac_coords = np.array(frac_coords) + np.array([0, 0, -shift])[None, :] frac_coords -= np.floor(frac_coords) a, b, c = self.oriented_unit_cell.lattice.matrix new_lattice = [a, b, nlayers * c] frac_coords[:, 2] = frac_coords[:, 2] / nlayers all_coords = [] for i in range(nlayers_slab): fcoords = frac_coords.copy() fcoords[:, 2] += i / nlayers all_coords.extend(fcoords) slab = Structure(new_lattice, species * nlayers_slab, all_coords, site_properties=props) scale_factor = self.slab_scale_factor # Whether or not to orthogonalize the structure if self.lll_reduce: lll_slab = slab.copy(sanitize=True) mapping = lll_slab.lattice.find_mapping(slab.lattice) scale_factor = np.dot(mapping[2], scale_factor) slab = lll_slab # Whether or not to center the slab layer around the vacuum if self.center_slab: avg_c = np.average([c[2] for c in slab.frac_coords]) slab.translate_sites(list(range(len(slab))), [0, 0, 0.5 - avg_c]) if self.primitive: prim = slab.get_primitive_structure(tolerance=tol) if energy is not None: energy = prim.volume / slab.volume * energy slab = prim # Reorient the lattice to get the correct reduced cell ouc = self.oriented_unit_cell.copy() if self.primitive: # find a reduced ouc slab_l = slab.lattice ouc = ouc.get_primitive_structure( constrain_latt={ "a": slab_l.a, "b": slab_l.b, "alpha": slab_l.alpha, "beta": slab_l.beta, "gamma": slab_l.gamma, } ) # Check this is the correct oriented unit cell ouc = self.oriented_unit_cell if slab_l.a != ouc.lattice.a or slab_l.b != ouc.lattice.b else ouc return Slab( slab.lattice, slab.species_and_occu, slab.frac_coords, self.miller_index, ouc, shift, scale_factor, energy=energy, site_properties=slab.site_properties, reorient_lattice=self.reorient_lattice, ) def _calculate_possible_shifts(self, tol=0.1): frac_coords = self.oriented_unit_cell.frac_coords n = len(frac_coords) if n == 1: # Clustering does not work when there is only one data point. shift = frac_coords[0][2] + 0.5 return [shift - math.floor(shift)] # We cluster the sites according to the c coordinates. But we need to # take into account PBC. Let's compute a fractional c-coordinate # distance matrix that accounts for PBC. dist_matrix = np.zeros((n, n)) h = self._proj_height # Projection of c lattice vector in # direction of surface normal. for i, j in itertools.combinations(list(range(n)), 2): if i != j: cdist = frac_coords[i][2] - frac_coords[j][2] cdist = abs(cdist - round(cdist)) * h dist_matrix[i, j] = cdist dist_matrix[j, i] = cdist condensed_m = squareform(dist_matrix) z = linkage(condensed_m) clusters = fcluster(z, tol, criterion="distance") # Generate dict of cluster# to c val - doesn't matter what the c is. c_loc = {c: frac_coords[i][2] for i, c in enumerate(clusters)} # Put all c into the unit cell. possible_c = [c - math.floor(c) for c in sorted(c_loc.values())] # Calculate the shifts nshifts = len(possible_c) shifts = [] for i in range(nshifts): if i == nshifts - 1: # There is an additional shift between the first and last c # coordinate. But this needs special handling because of PBC. shift = (possible_c[0] + 1 + possible_c[i]) * 0.5 if shift > 1: shift -= 1 else: shift = (possible_c[i] + possible_c[i + 1]) * 0.5 shifts.append(shift - math.floor(shift)) shifts = sorted(shifts) return shifts def _get_c_ranges(self, bonds): c_ranges = [] bonds = {(get_el_sp(s1), get_el_sp(s2)): dist for (s1, s2), dist in bonds.items()} for (sp1, sp2), bond_dist in bonds.items(): for site in self.oriented_unit_cell: if sp1 in site.species: for nn in self.oriented_unit_cell.get_neighbors(site, bond_dist): if sp2 in nn.species: c_range = tuple(sorted([site.frac_coords[2], nn.frac_coords[2]])) if c_range[1] > 1: # Takes care of PBC when c coordinate of site # goes beyond the upper boundary of the cell c_ranges.append((c_range[0], 1)) c_ranges.append((0, c_range[1] - 1)) elif c_range[0] < 0: # Takes care of PBC when c coordinate of site # is below the lower boundary of the unit cell c_ranges.append((0, c_range[1])) c_ranges.append((c_range[0] + 1, 1)) elif c_range[0] != c_range[1]: c_ranges.append((c_range[0], c_range[1])) return c_ranges def get_slabs( self, bonds=None, ftol=0.1, tol=0.1, max_broken_bonds=0, symmetrize=False, repair=False, ): """ This method returns a list of slabs that are generated using the list of shift values from the method, _calculate_possible_shifts(). Before the shifts are used to create the slabs however, if the user decides to take into account whether or not a termination will break any polyhedral structure (bonds is not None), this method will filter out any shift values that do so. Args: bonds ({(specie1, specie2): max_bond_dist}: bonds are specified as a dict of tuples: float of specie1, specie2 and the max bonding distance. For example, PO4 groups may be defined as {("P", "O"): 3}. tol (float): General tolerance paramter for getting primitive cells and matching structures ftol (float): Threshold parameter in fcluster in order to check if two atoms are lying on the same plane. Default thresh set to 0.1 Angstrom in the direction of the surface normal. max_broken_bonds (int): Maximum number of allowable broken bonds for the slab. Use this to limit # of slabs (some structures may have a lot of slabs). Defaults to zero, which means no defined bonds must be broken. symmetrize (bool): Whether or not to ensure the surfaces of the slabs are equivalent. repair (bool): Whether to repair terminations with broken bonds or just omit them. Set to False as repairing terminations can lead to many possible slabs as oppose to just omitting them. Returns: ([Slab]) List of all possible terminations of a particular surface. Slabs are sorted by the # of bonds broken. """ c_ranges = [] if bonds is None else self._get_c_ranges(bonds) slabs = [] for shift in self._calculate_possible_shifts(tol=ftol): bonds_broken = 0 for r in c_ranges: if r[0] <= shift <= r[1]: bonds_broken += 1 slab = self.get_slab(shift, tol=tol, energy=bonds_broken) if bonds_broken <= max_broken_bonds: slabs.append(slab) elif repair: # If the number of broken bonds is exceeded, # we repair the broken bonds on the slab slabs.append(self.repair_broken_bonds(slab, bonds)) # Further filters out any surfaces made that might be the same m = StructureMatcher(ltol=tol, stol=tol, primitive_cell=False, scale=False) new_slabs = [] for g in m.group_structures(slabs): # For each unique termination, symmetrize the # surfaces by removing sites from the bottom. if symmetrize: slabs = self.nonstoichiometric_symmetrized_slab(g[0]) new_slabs.extend(slabs) else: new_slabs.append(g[0]) match = StructureMatcher(ltol=tol, stol=tol, primitive_cell=False, scale=False) new_slabs = [g[0] for g in match.group_structures(new_slabs)] return sorted(new_slabs, key=lambda s: s.energy) def repair_broken_bonds(self, slab, bonds): """ This method will find undercoordinated atoms due to slab cleaving specified by the bonds parameter and move them to the other surface to make sure the bond is kept intact. In a future release of surface.py, the ghost_sites will be used to tell us how the repair bonds should look like. Arg: slab (structure): A structure object representing a slab. bonds ({(specie1, specie2): max_bond_dist}: bonds are specified as a dict of tuples: float of specie1, specie2 and the max bonding distance. For example, PO4 groups may be defined as {("P", "O"): 3}. Returns: (Slab) A Slab object with a particular shifted oriented unit cell. """ for pair in bonds.keys(): blength = bonds[pair] # First lets determine which element should be the # reference (center element) to determine broken bonds. # e.g. P for a PO4 bond. Find integer coordination # numbers of the pair of elements wrt to each other cn_dict = {} for i, el in enumerate(pair): cnlist = [] for site in self.oriented_unit_cell: poly_coord = 0 if site.species_string == el: for nn in self.oriented_unit_cell.get_neighbors(site, blength): if nn[0].species_string == pair[i - 1]: poly_coord += 1 cnlist.append(poly_coord) cn_dict[el] = cnlist # We make the element with the higher coordination our reference if max(cn_dict[pair[0]]) > max(cn_dict[pair[1]]): element1, element2 = pair else: element2, element1 = pair for i, site in enumerate(slab): # Determine the coordination of our reference if site.species_string == element1: poly_coord = 0 for neighbor in slab.get_neighbors(site, blength): poly_coord += 1 if neighbor.species_string == element2 else 0 # suppose we find an undercoordinated reference atom if poly_coord not in cn_dict[element1]: # We get the reference atom of the broken bonds # (undercoordinated), move it to the other surface slab = self.move_to_other_side(slab, [i]) # find its NNs with the corresponding # species it should be coordinated with neighbors = slab.get_neighbors(slab[i], blength, include_index=True) tomove = [nn[2] for nn in neighbors if nn[0].species_string == element2] tomove.append(i) # and then move those NNs along with the central # atom back to the other side of the slab again slab = self.move_to_other_side(slab, tomove) return slab def move_to_other_side(self, init_slab, index_of_sites): """ This method will Move a set of sites to the other side of the slab (opposite surface). Arg: init_slab (structure): A structure object representing a slab. index_of_sites (list of ints): The list of indices representing the sites we want to move to the other side. Returns: (Slab) A Slab object with a particular shifted oriented unit cell. """ slab = init_slab.copy() # Determine what fraction the slab is of the total cell size # in the c direction. Round to nearest rational number. h = self._proj_height p = h / self.parent.lattice.d_hkl(self.miller_index) if self.in_unit_planes: nlayers_slab = int(math.ceil(self.min_slab_size / p)) nlayers_vac = int(math.ceil(self.min_vac_size / p)) else: nlayers_slab = int(math.ceil(self.min_slab_size / h)) nlayers_vac = int(math.ceil(self.min_vac_size / h)) nlayers = nlayers_slab + nlayers_vac slab_ratio = nlayers_slab / nlayers # Sort the index of sites based on which side they are on top_site_index = [i for i in index_of_sites if slab[i].frac_coords[2] > slab.center_of_mass[2]] bottom_site_index = [i for i in index_of_sites if slab[i].frac_coords[2] < slab.center_of_mass[2]] # Translate sites to the opposite surfaces slab.translate_sites(top_site_index, [0, 0, slab_ratio]) slab.translate_sites(bottom_site_index, [0, 0, -slab_ratio]) return Slab( init_slab.lattice, slab.species, slab.frac_coords, init_slab.miller_index, init_slab.oriented_unit_cell, init_slab.shift, init_slab.scale_factor, energy=init_slab.energy, ) def nonstoichiometric_symmetrized_slab(self, init_slab, tol=1e-3): """ This method checks whether or not the two surfaces of the slab are equivalent. If the point group of the slab has an inversion symmetry ( ie. belong to one of the Laue groups), then it is assumed that the surfaces should be equivalent. Otherwise, sites at the bottom of the slab will be removed until the slab is symmetric. Note the removal of sites can destroy the stoichiometry of the slab. For non-elemental structures, the chemical potential will be needed to calculate surface energy. Arg: init_slab (Structure): A single slab structure tol (float): Tolerance for SpaceGroupanalyzer. Returns: Slab (structure): A symmetrized Slab object. """ sg = SpacegroupAnalyzer(init_slab, symprec=tol) if sg.is_laue(): return [init_slab] nonstoich_slabs = [] # Build an equivalent surface slab for each of the different surfaces for top in [True, False]: asym = True slab = init_slab.copy() slab.energy = init_slab.energy while asym: # Keep removing sites from the bottom one by one until both # surfaces are symmetric or the number of sites removed has # exceeded 10 percent of the original slab c_dir = [site[2] for i, site in enumerate(slab.frac_coords)] if top: slab.remove_sites([c_dir.index(max(c_dir))]) else: slab.remove_sites([c_dir.index(min(c_dir))]) if len(slab) <= len(self.parent): break # Check if the altered surface is symmetric sg = SpacegroupAnalyzer(slab, symprec=tol) if sg.is_laue(): asym = False nonstoich_slabs.append(slab) if len(slab) <= len(self.parent): warnings.warn("Too many sites removed, please use a larger slab " "size.") return nonstoich_slabs module_dir = os.path.dirname(os.path.abspath(__file__)) with open(os.path.join(module_dir, "reconstructions_archive.json")) as data_file: reconstructions_archive = json.load(data_file) class ReconstructionGenerator: """ This class takes in a pre-defined dictionary specifying the parameters need to build a reconstructed slab such as the SlabGenerator parameters, transformation matrix, sites to remove/add and slab/vacuum size. It will then use the formatted instructions provided by the dictionary to build the desired reconstructed slab from the initial structure. .. attribute:: slabgen_params Parameters for the SlabGenerator .. trans_matrix:: A 3x3 transformation matrix to generate the reconstructed slab. Only the a and b lattice vectors are actually changed while the c vector remains the same. This matrix is what the Wood's notation is based on. .. reconstruction_json:: The full json or dictionary containing the instructions for building the reconstructed slab .. termination:: The index of the termination of the slab TODO: - Right now there is no way to specify what atom is being added. In the future, use basis sets? """ def __init__(self, initial_structure, min_slab_size, min_vacuum_size, reconstruction_name): """ Generates reconstructed slabs from a set of instructions specified by a dictionary or json file. Args: initial_structure (Structure): Initial input structure. Note that to ensure that the miller indices correspond to usual crystallographic definitions, you should supply a conventional unit cell structure. min_slab_size (float): In Angstroms min_vacuum_size (float): In Angstroms reconstruction (str): Name of the dict containing the instructions for building a reconstructed slab. The dictionary can contain any item the creator deems relevant, however any instructions archived in pymatgen for public use needs to contain the following keys and items to ensure compatibility with the ReconstructionGenerator: "name" (str): A descriptive name for the type of reconstruction. Typically the name will have the type of structure the reconstruction is for, the Miller index, and Wood's notation along with anything to describe the reconstruction: e.g.: "fcc_110_missing_row_1x2" "description" (str): A longer description of your reconstruction. This is to help future contributors who want to add other types of reconstructions to the archive on pymatgen to check if the reconstruction already exists. Please read the descriptions carefully before adding a new type of reconstruction to ensure it is not in the archive yet. "reference" (str): Optional reference to where the reconstruction was taken from or first observed. "spacegroup" (dict): e.g. {"symbol": "Fm-3m", "number": 225} Indicates what kind of structure is this reconstruction. "miller_index" ([h,k,l]): Miller index of your reconstruction "Woods_notation" (str): For a reconstruction, the a and b lattice may change to accomodate the symmetry of the reconstruction. This notation indicates the change in the vectors relative to the primitive (p) or conventional (c) slab cell. E.g. p(2x1): Wood, E. A. (1964). Vocabulary of surface crystallography. Journal of Applied Physics, 35(4), 1306–1312. "transformation_matrix" (numpy array): A 3x3 matrix to transform the slab. Only the a and b lattice vectors should change while the c vector remains the same. "SlabGenerator_parameters" (dict): A dictionary containing the parameters for the SlabGenerator class excluding the miller_index, min_slab_size and min_vac_size as the Miller index is already specified and the min_slab_size and min_vac_size can be changed regardless of what type of reconstruction is used. Having a consistent set of SlabGenerator parameters allows for the instructions to be reused to consistently build a reconstructed slab. "points_to_remove" (list of coords): A list of sites to remove where the first two indices are fraction (in a and b) and the third index is in units of 1/d (in c). "points_to_add" (list of frac_coords): A list of sites to add where the first two indices are fraction (in a an b) and the third index is in units of 1/d (in c). "base_reconstruction" (dict): Option to base a reconstruction on an existing reconstruction model also exists to easily build the instructions without repeating previous work. E.g. the alpha reconstruction of halites is based on the octopolar reconstruction but with the topmost atom removed. The dictionary for the alpha reconstruction would therefore contain the item "reconstruction_base": "halite_111_octopolar_2x2", and additional sites for "points_to_remove" and "points_to_add" can be added to modify this reconstruction. For "points_to_remove" and "points_to_add", the third index for the c vector is in units of 1/d where d is the spacing between atoms along hkl (the c vector) and is relative to the topmost site in the unreconstructed slab. e.g. a point of [0.5, 0.25, 1] corresponds to the 0.5 frac_coord of a, 0.25 frac_coord of b and a distance of 1 atomic layer above the topmost site. [0.5, 0.25, -0.5] where the third index corresponds to a point half a atomic layer below the topmost site. [0.5, 0.25, 0] corresponds to a point in the same position along c as the topmost site. This is done because while the primitive units of a and b will remain constant, the user can vary the length of the c direction by changing the slab layer or the vacuum layer. NOTE: THE DICTIONARY SHOULD ONLY CONTAIN "points_to_remove" AND "points_to_add" FOR THE TOP SURFACE. THE ReconstructionGenerator WILL MODIFY THE BOTTOM SURFACE ACCORDINGLY TO RETURN A SLAB WITH EQUIVALENT SURFACES. """ if reconstruction_name not in reconstructions_archive.keys(): raise KeyError( "The reconstruction_name entered (%s) does not exist in the " "archive. Please select from one of the following reconstructions: %s " "or add the appropriate dictionary to the archive file " "reconstructions_archive.json." % (reconstruction_name, list(reconstructions_archive.keys())) ) # Get the instructions to build the reconstruction # from the reconstruction_archive recon_json = copy.deepcopy(reconstructions_archive[reconstruction_name]) new_points_to_add, new_points_to_remove = [], [] if "base_reconstruction" in recon_json.keys(): if "points_to_add" in recon_json.keys(): new_points_to_add = recon_json["points_to_add"] if "points_to_remove" in recon_json.keys(): new_points_to_remove = recon_json["points_to_remove"] # Build new instructions from a base reconstruction recon_json = copy.deepcopy(reconstructions_archive[recon_json["base_reconstruction"]]) if "points_to_add" in recon_json.keys(): del recon_json["points_to_add"] if "points_to_remove" in recon_json.keys(): del recon_json["points_to_remove"] if new_points_to_add: recon_json["points_to_add"] = new_points_to_add if new_points_to_remove: recon_json["points_to_remove"] = new_points_to_remove slabgen_params = copy.deepcopy(recon_json["SlabGenerator_parameters"]) slabgen_params["initial_structure"] = initial_structure.copy() slabgen_params["miller_index"] = recon_json["miller_index"] slabgen_params["min_slab_size"] = min_slab_size slabgen_params["min_vacuum_size"] = min_vacuum_size self.slabgen_params = slabgen_params self.trans_matrix = recon_json["transformation_matrix"] self.reconstruction_json = recon_json self.name = reconstruction_name def build_slabs(self): """ Builds the reconstructed slab by: (1) Obtaining the unreconstructed slab using the specified parameters for the SlabGenerator. (2) Applying the appropriate lattice transformation in the a and b lattice vectors. (3) Remove any specified sites from both surfaces. (4) Add any specified sites to both surfaces. Returns: (Slab): The reconstructed slab. """ slabs = self.get_unreconstructed_slabs() recon_slabs = [] for slab in slabs: d = get_d(slab) top_site = sorted(slab, key=lambda site: site.frac_coords[2])[-1].coords # Remove any specified sites if "points_to_remove" in self.reconstruction_json.keys(): pts_to_rm = copy.deepcopy(self.reconstruction_json["points_to_remove"]) for p in pts_to_rm: p[2] = slab.lattice.get_fractional_coords([top_site[0], top_site[1], top_site[2] + p[2] * d])[2] cart_point = slab.lattice.get_cartesian_coords(p) dist = [site.distance_from_point(cart_point) for site in slab] site1 = dist.index(min(dist)) slab.symmetrically_remove_atoms([site1]) # Add any specified sites if "points_to_add" in self.reconstruction_json.keys(): pts_to_add = copy.deepcopy(self.reconstruction_json["points_to_add"]) for p in pts_to_add: p[2] = slab.lattice.get_fractional_coords([top_site[0], top_site[1], top_site[2] + p[2] * d])[2] slab.symmetrically_add_atom(slab[0].specie, p) slab.reconstruction = self.name setattr(slab, "recon_trans_matrix", self.trans_matrix) # Get the oriented_unit_cell with the same axb area. ouc = slab.oriented_unit_cell.copy() ouc.make_supercell(self.trans_matrix) slab.oriented_unit_cell = ouc recon_slabs.append(slab) return recon_slabs def get_unreconstructed_slabs(self): """ Generates the unreconstructed or pristine super slab. """ slabs = [] for slab in SlabGenerator(*self.slabgen_params).get_slabs(): slab.make_supercell(self.trans_matrix) slabs.append(slab) return slabs def get_d(slab): """ Determine the distance of space between each layer of atoms along c """ sorted_sites = sorted(slab, key=lambda site: site.frac_coords[2]) for i, site in enumerate(sorted_sites): if not "%.6f" % (site.frac_coords[2]) == "%.6f" % (sorted_sites[i + 1].frac_coords[2]): d = abs(site.frac_coords[2] - sorted_sites[i + 1].frac_coords[2]) break return slab.lattice.get_cartesian_coords([0, 0, d])[2] def is_already_analyzed(miller_index: tuple, miller_list: list, symm_ops: list) -> bool: """ Helper function to check if a given Miller index is part of the family of indices of any index in a list Args: miller_index (tuple): The Miller index to analyze miller_list (list): List of Miller indices. If the given Miller index belongs in the same family as any of the indices in this list, return True, else return False symm_ops (list): Symmetry operations of a lattice, used to define family of indices """ for op in symm_ops: if in_coord_list(miller_list, op.operate(miller_index)): return True return False def get_symmetrically_equivalent_miller_indices(structure, miller_index, return_hkil=True): """ Returns all symmetrically equivalent indices for a given structure. Analysis is based on the symmetry of the reciprocal lattice of the structure. Args: miller_index (tuple): Designates the family of Miller indices to find. Can be hkl or hkil for hexagonal systems return_hkil (bool): If true, return hkil form of Miller index for hexagonal systems, otherwise return hkl """ # Change to hkl if hkil because in_coord_list only handles tuples of 3 miller_index = (miller_index[0], miller_index[1], miller_index[3]) if len(miller_index) == 4 else miller_index mmi = max(np.abs(miller_index)) r = list(range(-mmi, mmi + 1)) r.reverse() sg = SpacegroupAnalyzer(structure) # Get distinct hkl planes from the rhombohedral setting if trigonal if sg.get_crystal_system() == "trigonal": prim_structure = SpacegroupAnalyzer(structure).get_primitive_standard_structure() symm_ops = prim_structure.lattice.get_recp_symmetry_operation() else: symm_ops = structure.lattice.get_recp_symmetry_operation() equivalent_millers = [miller_index] for miller in itertools.product(r, r, r): if miller == miller_index: continue if any(i != 0 for i in miller): if is_already_analyzed(miller, equivalent_millers, symm_ops): equivalent_millers.append(miller) # include larger Miller indices in the family of planes if all(mmi > i for i in np.abs(miller)) and not in_coord_list(equivalent_millers, miller): if is_already_analyzed(mmi np.array(miller), equivalent_millers, symm_ops): equivalent_millers.append(miller) if return_hkil and sg.get_crystal_system() in ["trigonal", "hexagonal"]: return [(hkl[0], hkl[1], -1 * hkl[0] - hkl[1], hkl[2]) for hkl in equivalent_millers] return equivalent_millers def get_symmetrically_distinct_miller_indices(structure, max_index, return_hkil=False): """ Returns all symmetrically distinct indices below a certain max-index for a given structure. Analysis is based on the symmetry of the reciprocal lattice of the structure. Args: structure (Structure): input structure. max_index (int): The maximum index. For example, a max_index of 1 means that (100), (110), and (111) are returned for the cubic structure. All other indices are equivalent to one of these. return_hkil (bool): If true, return hkil form of Miller index for hexagonal systems, otherwise return hkl """ r = list(range(-max_index, max_index + 1)) r.reverse() # First we get a list of all hkls for conventional (including equivalent) conv_hkl_list = [miller for miller in itertools.product(r, r, r) if any(i != 0 for i in miller)] sg = SpacegroupAnalyzer(structure) # Get distinct hkl planes from the rhombohedral setting if trigonal if sg.get_crystal_system() == "trigonal": transf = sg.get_conventional_to_primitive_transformation_matrix() miller_list = [hkl_transformation(transf, hkl) for hkl in conv_hkl_list] prim_structure = SpacegroupAnalyzer(structure).get_primitive_standard_structure() symm_ops = prim_structure.lattice.get_recp_symmetry_operation() else: miller_list = conv_hkl_list symm_ops = structure.lattice.get_recp_symmetry_operation() unique_millers, unique_millers_conv = [], [] for i, miller in enumerate(miller_list): d = abs(reduce(gcd, miller)) miller = tuple(int(i / d) for i in miller) if not is_already_analyzed(miller, unique_millers, symm_ops): if sg.get_crystal_system() == "trigonal": # Now we find the distinct primitive hkls using # the primitive symmetry operations and their # corresponding hkls in the conventional setting unique_millers.append(miller) d = abs(reduce(gcd, conv_hkl_list[i])) cmiller = tuple(int(i / d) for i in conv_hkl_list[i]) unique_millers_conv.append(cmiller) else: unique_millers.append(miller) unique_millers_conv.append(miller) if return_hkil and sg.get_crystal_system() in ["trigonal", "hexagonal"]: return [(hkl[0], hkl[1], -1 * hkl[0] - hkl[1], hkl[2]) for hkl in unique_millers_conv] return unique_millers_conv def hkl_transformation(transf, miller_index): """ Returns the Miller index from setting A to B using a transformation matrix Args: transf (3x3 array): The transformation matrix that transforms a lattice of A to B miller_index ([h, k, l]): Miller index to transform to setting B """ # Get a matrix of whole numbers (ints) def lcm(a, b): return a * b // math.gcd(a, b) reduced_transf = reduce(lcm, [int(1 / i) for i in itertools.chain(transf) if i != 0]) transf reduced_transf = reduced_transf.astype(int) # perform the transformation t_hkl = np.dot(reduced_transf, miller_index) d = abs(reduce(gcd, t_hkl)) t_hkl = np.array([int(i / d) for i in t_hkl]) # get mostly positive oriented Miller index if len([i for i in t_hkl if i < 0]) > 1: t_hkl = -1 return tuple(t_hkl) def generate_all_slabs( structure, max_index, min_slab_size, min_vacuum_size, bonds=None, tol=0.1, ftol=0.1, max_broken_bonds=0, lll_reduce=False, center_slab=False, primitive=True, max_normal_search=None, symmetrize=False, repair=False, include_reconstructions=False, in_unit_planes=False, ): """ A function that finds all different slabs up to a certain miller index. Slabs oriented under certain Miller indices that are equivalent to other slabs in other Miller indices are filtered out using symmetry operations to get rid of any repetitive slabs. For example, under symmetry operations, CsCl has equivalent slabs in the (0,0,1), (0,1,0), and (1,0,0) direction. Args: structure (Structure): Initial input structure. Note that to ensure that the miller indices correspond to usual crystallographic definitions, you should supply a conventional unit cell structure. max_index (int): The maximum Miller index to go up to. min_slab_size (float): In Angstroms min_vacuum_size (float): In Angstroms bonds ({(specie1, specie2): max_bond_dist}: bonds are specified as a dict of tuples: float of specie1, specie2 and the max bonding distance. For example, PO4 groups may be defined as {("P", "O"): 3}. tol (float): Threshold parameter in fcluster in order to check if two atoms are lying on the same plane. Default thresh set to 0.1 Angstrom in the direction of the surface normal. max_broken_bonds (int): Maximum number of allowable broken bonds for the slab. Use this to limit # of slabs (some structures may have a lot of slabs). Defaults to zero, which means no defined bonds must be broken. lll_reduce (bool): Whether to perform an LLL reduction on the eventual structure. center_slab (bool): Whether to center the slab in the cell with equal vacuum spacing from the top and bottom. primitive (bool): Whether to reduce any generated slabs to a primitive cell (this does not* mean the slab is generated from a primitive cell, it simply means that after slab generation, we attempt to find shorter lattice vectors, which lead to less surface area and smaller cells). max_normal_search (int): If set to a positive integer, the code will conduct a search for a normal lattice vector that is as perpendicular to the surface as possible by considering multiples linear combinations of lattice vectors up to max_normal_search. This has no bearing on surface energies, but may be useful as a preliminary step to generating slabs for absorption and other sizes. It is typical that this will not be the smallest possible cell for simulation. Normality is not guaranteed, but the oriented cell will have the c vector as normal as possible (within the search range) to the surface. A value of up to the max absolute Miller index is usually sufficient. symmetrize (bool): Whether or not to ensure the surfaces of the slabs are equivalent. repair (bool): Whether to repair terminations with broken bonds or just omit them include_reconstructions (bool): Whether to include reconstructed slabs available in the reconstructions_archive.json file. """ all_slabs = [] for miller in get_symmetrically_distinct_miller_indices(structure, max_index): gen = SlabGenerator( structure, miller, min_slab_size, min_vacuum_size, lll_reduce=lll_reduce, center_slab=center_slab, primitive=primitive, max_normal_search=max_normal_search, in_unit_planes=in_unit_planes, ) slabs = gen.get_slabs( bonds=bonds, tol=tol, ftol=ftol, symmetrize=symmetrize, max_broken_bonds=max_broken_bonds, repair=repair, ) if len(slabs) > 0: logger.debug("%s has %d slabs... " % (miller, len(slabs))) all_slabs.extend(slabs) if include_reconstructions: sg = SpacegroupAnalyzer(structure) symbol = sg.get_space_group_symbol() # enumerate through all posisble reconstructions in the # archive available for this particular structure (spacegroup) for name, instructions in reconstructions_archive.items(): if "base_reconstruction" in instructions.keys(): instructions = reconstructions_archive[instructions["base_reconstruction"]] if instructions["spacegroup"]["symbol"] == symbol: # check if this reconstruction has a max index # equal or less than the given max index if max(instructions["miller_index"]) > max_index: continue recon = ReconstructionGenerator(structure, min_slab_size, min_vacuum_size, name) all_slabs.extend(recon.build_slabs()) return all_slabs def get_slab_regions(slab, blength=3.5): """ Function to get the ranges of the slab regions. Useful for discerning where the slab ends and vacuum begins if the slab is not fully within the cell Args: slab (Structure): Structure object modelling the surface blength (float, Ang): The bondlength between atoms. You generally want this value to be larger than the actual bondlengths in order to find atoms that are part of the slab """ fcoords, indices, all_indices = [], [], [] for site in slab: # find sites with c < 0 (noncontiguous) neighbors = slab.get_neighbors(site, blength, include_index=True, include_image=True) for nn in neighbors: if nn[0].frac_coords[2] < 0: # sites are noncontiguous within cell fcoords.append(nn[0].frac_coords[2]) indices.append(nn[-2]) if nn[-2] not in all_indices: all_indices.append(nn[-2]) if fcoords: # If slab is noncontiguous, locate the lowest # site within the upper region of the slab while fcoords: last_fcoords = copy.copy(fcoords) last_indices = copy.copy(indices) site = slab[indices[fcoords.index(min(fcoords))]] neighbors = slab.get_neighbors(site, blength, include_index=True, include_image=True) fcoords, indices = [], [] for nn in neighbors: if 1 > nn[0].frac_coords[2] > 0 and nn[0].frac_coords[2] < site.frac_coords[2]: # sites are noncontiguous within cell fcoords.append(nn[0].frac_coords[2]) indices.append(nn[-2]) if nn[-2] not in all_indices: all_indices.append(nn[-2]) # Now locate the highest site within the lower region of the slab upper_fcoords = [] for site in slab: if all(nn.index not in all_indices for nn in slab.get_neighbors(site, blength)): upper_fcoords.append(site.frac_coords[2]) coords = copy.copy(last_fcoords) if not fcoords else copy.copy(fcoords) min_top = slab[last_indices[coords.index(min(coords))]].frac_coords[2] ranges = [[0, max(upper_fcoords)], [min_top, 1]] else: # If the entire slab region is within the slab cell, just # set the range as the highest and lowest site in the slab sorted_sites = sorted(slab, key=lambda site: site.frac_coords[2]) ranges = [[sorted_sites[0].frac_coords[2], sorted_sites[-1].frac_coords[2]]] return ranges def miller_index_from_sites(lattice, coords, coords_are_cartesian=True, round_dp=4, verbose=True): """ Get the Miller index of a plane from a list of site coordinates. A minimum of 3 sets of coordinates are required. If more than 3 sets of coordinates are given, the best plane that minimises the distance to all points will be calculated. Args: lattice (list or Lattice): A 3x3 lattice matrix or `Lattice` object (for example obtained from Structure.lattice). coords (iterable): A list or numpy array of coordinates. Can be cartesian or fractional coordinates. If more than three sets of coordinates are provided, the best plane that minimises the distance to all sites will be calculated. coords_are_cartesian (bool, optional): Whether the coordinates are in cartesian space. If using fractional coordinates set to False. round_dp (int, optional): The number of decimal places to round the miller index to. verbose (bool, optional): Whether to print warnings. Returns: (tuple): The Miller index. """ if not isinstance(lattice, Lattice): lattice = Lattice(lattice) return lattice.get_miller_index_from_coords( coords, coords_are_cartesian=coords_are_cartesian, round_dp=round_dp, verbose=verbose, ) def center_slab(slab): """ The goal here is to ensure the center of the slab region is centered close to c=0.5. This makes it easier to find the surface sites and apply operations like doping. There are three cases where the slab in not centered: 1. The slab region is completely between two vacuums in the box but not necessarily centered. We simply shift the slab by the difference in its center of mass and 0.5 along the c direction. 2. The slab completely spills outside the box from the bottom and into the top. This makes it incredibly difficult to locate surface sites. We iterate through all sites that spill over (z>c) and shift all sites such that this specific site is now on the other side. Repeat for all sites with z>c. 3. This is a simpler case of scenario 2. Either the top or bottom slab sites are at c=0 or c=1. Treat as scenario 2. Args: slab (Slab): Slab structure to center Returns: Returns a centered slab structure """ # get a reasonable r cutoff to sample neighbors bdists = sorted([nn[1] for nn in slab.get_neighbors(slab[0], 10) if nn[1] > 0]) r = bdists[0] * 3 all_indices = [i for i, site in enumerate(slab)] # check if structure is case 2 or 3, shift all the # sites up to the other side until it is case 1 for site in slab: if any(nn[1] > slab.lattice.c for nn in slab.get_neighbors(site, r)): shift = 1 - site.frac_coords[2] + 0.05 slab.translate_sites(all_indices, [0, 0, shift]) # now the slab is case 1, shift the center of mass of the slab to 0.5 weights = [s.species.weight for s in slab] center_of_mass = np.average(slab.frac_coords, weights=weights, axis=0) shift = 0.5 - center_of_mass[2] slab.translate_sites(all_indices, [0, 0, shift]) return slab def _reduce_vector(vector): # small function to reduce vectors d = abs(reduce(gcd, vector)) vector = tuple(int(i / d) for i in vector) return vector	richardtran415/pymatgen	pymatgen/core/surface.py	Python	mit	87,059	[ "pymatgen" ]	fcd6904ea24f3d4fb398844871fb7b03f16e5f70221c17f3a63a111965856383
# -- coding: utf-8 -- # # tsodyks_facilitating.py # # This file is part of NEST. # # Copyright (C) 2004 The NEST Initiative # # NEST is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 2 of the License, or # (at your option) any later version. # # NEST is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with NEST. If not, see <http://www.gnu.org/licenses/>. """Tsodyks facilitating example -------------------------------- This scripts simulates two neurons. One is driven with dc-input and connected to the other one with a facilitating Tsodyks synapse. The membrane potential trace of the second neuron is recorded. This example reproduces figure 1B of [1]_ This example is analog to ``tsodyks_depressing.py``, except that different synapse parameters are used. Here, a small facilitation parameter ``U`` causes a slow saturation of the synaptic efficacy (Eq. 2.2), enabling a facilitating behavior. References ~~~~~~~~~~~~ .. [1] Tsodyks M, Pawelzik K, Markram H (1998). Neural networks with dynamic synapses. Neural computation, http://dx.doi.org/10.1162/089976698300017502 See Also ~~~~~~~~~~ :doc:`tsodyks_depressing` """ ############################################################################### # First, we import all necessary modules for simulation and plotting. import nest import nest.voltage_trace from numpy import exp ############################################################################### # Second, the simulation parameters are assigned to variables. The neuron # and synapse parameters are stored into a dictionary. h = 0.1 # simulation step size (ms) Tau = 40. # membrane time constant Theta = 15. # threshold E_L = 0. # reset potential of membrane potential R = 1. # membrane resistance (GOhm) C = Tau / R # Tau (ms)/R in NEST units TauR = 2. # refractory time Tau_psc = 1.5 # time constant of PSC (= Tau_inact) Tau_rec = 130. # recovery time Tau_fac = 530. # facilitation time U = 0.03 # facilitation parameter U A = 1540. # PSC weight in pA f = 20. / 1000. # frequency in Hz converted to 1/ms Tend = 1200. # simulation time TIstart = 50. # start time of dc TIend = 1050. # end time of dc I0 = Theta * C / Tau / (1 - exp(-(1 / f - TauR) / Tau)) # dc amplitude neuron_param = {"tau_m": Tau, "t_ref": TauR, "tau_syn_ex": Tau_psc, "tau_syn_in": Tau_psc, "C_m": C, "V_reset": E_L, "E_L": E_L, "V_m": E_L, "V_th": Theta} syn_param = {"tau_psc": Tau_psc, "tau_rec": Tau_rec, "tau_fac": Tau_fac, "U": U, "delay": 0.1, "weight": A, "u": 0.0, "x": 1.0} ############################################################################### # Third, we reset the kernel and set the resolution using ``SetKernelStatus``. nest.ResetKernel() nest.SetKernelStatus({"resolution": h}) ############################################################################### # Fourth, the nodes are created using ``Create``. We store the returned # handles in variables for later reference. neurons = nest.Create("iaf_psc_exp", 2) dc_gen = nest.Create("dc_generator") volts = nest.Create("voltmeter") ############################################################################### # Fifth, the ``iaf_psc_exp`` neurons, the ``dc_generator`` and the ``voltmeter`` # are configured using ``SetStatus``, which expects a list of node handles and # a parameter dictionary or a list of parameter dictionaries. neurons.set(neuron_param) dc_gen.set(amplitude=I0, start=TIstart, stop=TIend) volts.set(label="voltmeter", interval=1.) ############################################################################### # Sixth, the ``dc_generator`` is connected to the first neuron # (`neurons[0]`) and the `voltmeter` is connected to the second neuron # (`neurons[1]`). The command `Connect` has different variants. Plain # ``Connect`` just takes the handles of pre- and postsynaptic nodes and # uses the default values for weight and delay. Note that the connection # direction for the ``voltmeter`` reflects the signal flow in the simulation # kernel, because it observes the neuron instead of receiving events from it. nest.Connect(dc_gen, neurons[0]) nest.Connect(volts, neurons[1]) ############################################################################### # Seventh, the first neuron (`neurons[0]`) is connected to the second # neuron (`neurons[1]`). The command ``CopyModel`` copies the # ``tsodyks_synapse`` model to the new name ``syn`` with parameters # ``syn_param``. The manually defined model ``syn`` is used in the # connection routine via the ``syn_spec`` parameter. nest.CopyModel("tsodyks_synapse", "syn", syn_param) nest.Connect(neurons[0], neurons[1], syn_spec="syn") ############################################################################### # Finally, we simulate the configuration using the command ``Simulate``, # where the simulation time `Tend` is passed as the argument. We plot the # target neuron's membrane potential as function of time. nest.Simulate(Tend) nest.voltage_trace.from_device(volts) nest.voltage_trace.show()	SepehrMN/nest-simulator	pynest/examples/tsodyks_facilitating.py	Python	gpl-2.0	5,620	[ "NEURON" ]	bfa8dd5e82947eb4a03baee8f29d510fd0dd9295ed84e02ee11602a5720cd14f
# Generate UV-Vis spectra from electronic structure TDHF/TDDFT output files. # Copyright (C) 2014 Li Research Group (University of Washington) # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. """Generate UV-Vis spectra from electronic structure TDHF/TDDFT output files. The top-level and main functions for the ``uvspecgen`` script are stored here. Functions for updating and resetting the Gaussian fit parameters are defined here. """ import sys from uvspec.config import settings from uvspec.config.settings import ConfigFile from uvspec.spectrum import AbsorptionSpectrum def _update_fit_parameters(): # Update the fit parameters in the configuration file with the values # provdied by the user at run-time. If no values are specified, the # current default values are maintained. config = ConfigFile() for parameter, value in settings.parameters.iteritems(): config.update(parameter, value) print ' Fit paramters have been updated' def _reset_fit_parameters(): # Reset the fit parameters to their originally installed default values. ConfigFile().reset() print ' Fit parameters have been reset to their original default values' def _generate_spectrum(): # Spectrum generation using the ``AbsorptionSpectrum`` class and methods. spectrum = AbsorptionSpectrum() if settings.join: spectrum.join(settings.logfile) else: spectrum.extract(settings.logfile[0]) spectrum.generate(settings.parameters) spectrum.write(settings.outfile, settings.output, settings.nometa) if settings.plot: spectrum.plot() def main(): """The core function that drives the ``uvspecgen`` program. First handle updates/resetting of the configuration file containing the Gaussian fit parameters. The ``uvspecgen`` program can be run without an electronic structure output filename specified solely for the purposes of updating/resetting the Gaussian fit parameters in the configuration file. If the ``--save`` or ``--reset`` flag is not specified, and a logfile is not given, the program will terminate with an error message and usage instructions. """ if settings.save: _update_fit_parameters() elif settings.reset: _reset_fit_parameters() if settings.logfile: _generate_spectrum() elif not settings.save and not settings.reset: settings.parser.error('Must specify at least one logfile name') else: sys.exit()	liresearchgroup/uvspecgen	uvspec/generate.py	Python	gpl-3.0	3,106	[ "Gaussian" ]	c708c61675dc0c8ed7e330569fd2ffcbf42c133336e46c11495d163fa9f02a38
# This file is part of Buildbot. Buildbot is free software: you can # redistribute it and/or modify it under the terms of the GNU General Public # License as published by the Free Software Foundation, version 2. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU General Public License for more # details. # # You should have received a copy of the GNU General Public License along with # this program; if not, write to the Free Software Foundation, Inc., 51 # Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. # # Copyright Buildbot Team Members from __future__ import with_statement # Based on the work of Dave Peticolas for the P4poll # Changed to svn (using xml.dom.minidom) by Niklaus Giger # Hacked beyond recognition by Brian Warner from twisted.python import log from twisted.internet import defer, utils from buildbot import util from buildbot.changes import base import xml.dom.minidom import os, urllib # these split_file_* functions are available for use as values to the # split_file= argument. def split_file_alwaystrunk(path): return dict(path=path) def split_file_branches(path): # turn "trunk/subdir/file.c" into (None, "subdir/file.c") # and "trunk/subdir/" into (None, "subdir/") # and "trunk/" into (None, "") # and "branches/1.5.x/subdir/file.c" into ("branches/1.5.x", "subdir/file.c") # and "branches/1.5.x/subdir/" into ("branches/1.5.x", "subdir/") # and "branches/1.5.x/" into ("branches/1.5.x", "") pieces = path.split('/') if len(pieces) > 1 and pieces[0] == 'trunk': return (None, '/'.join(pieces[1:])) elif len(pieces) > 2 and pieces[0] == 'branches': return ('/'.join(pieces[0:2]), '/'.join(pieces[2:])) else: return None def split_file_projects_branches(path): # turn projectname/trunk/subdir/file.c into dict(project=projectname, branch=trunk, path=subdir/file.c) if not "/" in path: return None project, path = path.split("/", 1) f = split_file_branches(path) if f: info = dict(project=project, path=f[1]) if f[0]: info['branch'] = f[0] return info return f class SVNPoller(base.PollingChangeSource, util.ComparableMixin): """ Poll a Subversion repository for changes and submit them to the change master. """ compare_attrs = ["svnurl", "split_file", "svnuser", "svnpasswd", "project", "pollInterval", "histmax", "svnbin", "category", "cachepath"] parent = None # filled in when we're added last_change = None loop = None def __init__(self, svnurl, split_file=None, svnuser=None, svnpasswd=None, pollInterval=1060, histmax=100, svnbin='svn', revlinktmpl='', category=None, project='', cachepath=None, pollinterval=-2, extra_args=None): # for backward compatibility; the parameter used to be spelled with 'i' if pollinterval != -2: pollInterval = pollinterval base.PollingChangeSource.__init__(self, name=svnurl, pollInterval=pollInterval) if svnurl.endswith("/"): svnurl = svnurl[:-1] # strip the trailing slash self.svnurl = svnurl self.extra_args = extra_args self.split_file = split_file or split_file_alwaystrunk self.svnuser = svnuser self.svnpasswd = svnpasswd self.revlinktmpl = revlinktmpl self.environ = os.environ.copy() # include environment variables # required for ssh-agent auth self.svnbin = svnbin self.histmax = histmax self._prefix = None self.category = category self.project = project self.cachepath = cachepath if self.cachepath and os.path.exists(self.cachepath): try: with open(self.cachepath, "r") as f: self.last_change = int(f.read().strip()) log.msg("SVNPoller: SVNPoller(%s) setting last_change to %s" % (self.svnurl, self.last_change)) # try writing it, too with open(self.cachepath, "w") as f: f.write(str(self.last_change)) except: self.cachepath = None log.msg(("SVNPoller: SVNPoller(%s) cache file corrupt or unwriteable; " + "skipping and not using") % self.svnurl) log.err() def describe(self): return "SVNPoller: watching %s" % self.svnurl def poll(self): # Our return value is only used for unit testing. # we need to figure out the repository root, so we can figure out # repository-relative pathnames later. Each SVNURL is in the form # (ROOT)/(PROJECT)/(BRANCH)/(FILEPATH), where (ROOT) is something # like svn://svn.twistedmatrix.com/svn/Twisted (i.e. there is a # physical repository at /svn/Twisted on that host), (PROJECT) is # something like Projects/Twisted (i.e. within the repository's # internal namespace, everything under Projects/Twisted/ has # something to do with Twisted, but these directory names do not # actually appear on the repository host), (BRANCH) is something like # "trunk" or "branches/2.0.x", and (FILEPATH) is a tree-relative # filename like "twisted/internet/defer.py". # our self.svnurl attribute contains (ROOT)/(PROJECT) combined # together in a way that we can't separate without svn's help. If the # user is not using the split_file= argument, then self.svnurl might # be (ROOT)/(PROJECT)/(BRANCH) . In any case, the filenames we will # get back from 'svn log' will be of the form # (PROJECT)/(BRANCH)/(FILEPATH), but we want to be able to remove # that (PROJECT) prefix from them. To do this without requiring the # user to tell us how svnurl is split into ROOT and PROJECT, we do an # 'svn info --xml' command at startup. This command will include a # <root> element that tells us ROOT. We then strip this prefix from # self.svnurl to determine PROJECT, and then later we strip the # PROJECT prefix from the filenames reported by 'svn log --xml' to # get a (BRANCH)/(FILEPATH) that can be passed to split_file() to # turn into separate BRANCH and FILEPATH values. # whew. if self.project: log.msg("SVNPoller: polling " + self.project) else: log.msg("SVNPoller: polling") d = defer.succeed(None) if not self._prefix: d.addCallback(lambda _ : self.get_prefix()) def set_prefix(prefix): self._prefix = prefix d.addCallback(set_prefix) d.addCallback(self.get_logs) d.addCallback(self.parse_logs) d.addCallback(self.get_new_logentries) d.addCallback(self.create_changes) d.addCallback(self.submit_changes) d.addCallback(self.finished_ok) d.addErrback(log.err, 'SVNPoller: Error in while polling') # eat errors return d def getProcessOutput(self, args): # this exists so we can override it during the unit tests d = utils.getProcessOutput(self.svnbin, args, self.environ) return d def get_prefix(self): args = ["info", "--xml", "--non-interactive", self.svnurl] if self.svnuser: args.extend(["--username=%s" % self.svnuser]) if self.svnpasswd: args.extend(["--password=%s" % self.svnpasswd]) if self.extra_args: args.extend(self.extra_args) d = self.getProcessOutput(args) def determine_prefix(output): try: doc = xml.dom.minidom.parseString(output) except xml.parsers.expat.ExpatError: log.msg("SVNPoller: SVNPoller._determine_prefix_2: ExpatError in '%s'" % output) raise rootnodes = doc.getElementsByTagName("root") if not rootnodes: # this happens if the URL we gave was already the root. In this # case, our prefix is empty. self._prefix = "" return self._prefix rootnode = rootnodes[0] root = "".join([c.data for c in rootnode.childNodes]) # root will be a unicode string if not self.svnurl.startswith(root): log.msg(format="svnurl='%(svnurl)s' doesn't start with <root>='%(root)s'", svnurl=self.svnurl, root=root) raise RuntimeError("Can't handle redirected svn connections!? " "This shouldn't happen.") prefix = self.svnurl[len(root):] if prefix.startswith("/"): prefix = prefix[1:] log.msg("SVNPoller: svnurl=%s, root=%s, so prefix=%s" % (self.svnurl, root, prefix)) return prefix d.addCallback(determine_prefix) return d def get_logs(self, _): args = [] args.extend(["log", "--xml", "--verbose", "--non-interactive"]) if self.svnuser: args.extend(["--username=%s" % self.svnuser]) if self.svnpasswd: args.extend(["--password=%s" % self.svnpasswd]) if self.extra_args: args.extend(self.extra_args) args.extend(["--limit=%d" % (self.histmax), self.svnurl]) d = self.getProcessOutput(args) return d def parse_logs(self, output): # parse the XML output, return a list of <logentry> nodes try: doc = xml.dom.minidom.parseString(output) except xml.parsers.expat.ExpatError: log.msg("SVNPoller: SVNPoller.parse_logs: ExpatError in '%s'" % output) raise logentries = doc.getElementsByTagName("logentry") return logentries def get_new_logentries(self, logentries): last_change = old_last_change = self.last_change # given a list of logentries, calculate new_last_change, and # new_logentries, where new_logentries contains only the ones after # last_change new_last_change = None new_logentries = [] if logentries: new_last_change = int(logentries[0].getAttribute("revision")) if last_change is None: # if this is the first time we've been run, ignore any changes # that occurred before now. This prevents a build at every # startup. log.msg('SVNPoller: starting at change %s' % new_last_change) elif last_change == new_last_change: # an unmodified repository will hit this case log.msg('SVNPoller: no changes') else: for el in logentries: if last_change == int(el.getAttribute("revision")): break new_logentries.append(el) new_logentries.reverse() # return oldest first self.last_change = new_last_change log.msg('SVNPoller: _process_changes %s .. %s' % (old_last_change, new_last_change)) return new_logentries def _get_text(self, element, tag_name): try: child_nodes = element.getElementsByTagName(tag_name)[0].childNodes text = "".join([t.data for t in child_nodes]) except: text = "<unknown>" return text def _transform_path(self, path): if not path.startswith(self._prefix): log.msg(format="SVNPoller: ignoring path '%(path)s' which doesn't" "start with prefix '%(prefix)s'", path=path, prefix=self._prefix) return relative_path = path[len(self._prefix):] if relative_path.startswith("/"): relative_path = relative_path[1:] where = self.split_file(relative_path) # 'where' is either None, (branch, final_path) or a dict if not where: return if isinstance(where, tuple): where = dict(branch=where[0], path=where[1]) return where def create_changes(self, new_logentries): changes = [] for el in new_logentries: revision = str(el.getAttribute("revision")) revlink='' if self.revlinktmpl: if revision: revlink = self.revlinktmpl % urllib.quote_plus(revision) log.msg("Adding change revision %s" % (revision,)) author = self._get_text(el, "author") comments = self._get_text(el, "msg") # there is a "date" field, but it provides localtime in the # repository's timezone, whereas we care about buildmaster's # localtime (since this will get used to position the boxes on # the Waterfall display, etc). So ignore the date field, and # addChange will fill in with the current time branches = {} try: pathlist = el.getElementsByTagName("paths")[0] except IndexError: # weird, we got an empty revision log.msg("ignoring commit with no paths") continue for p in pathlist.getElementsByTagName("path"): kind = p.getAttribute("kind") action = p.getAttribute("action") path = "".join([t.data for t in p.childNodes]) # the rest of buildbot is certaily not yet ready to handle # unicode filenames, because they get put in RemoteCommands # which get sent via PB to the buildslave, and PB doesn't # handle unicode. path = path.encode("ascii") if path.startswith("/"): path = path[1:] if kind == "dir" and not path.endswith("/"): path += "/" where = self._transform_path(path) # if 'where' is None, the file was outside any project that # we care about and we should ignore it if where: branch = where.get("branch", None) filename = where["path"] if not branch in branches: branches[branch] = { 'files': [], 'number_of_directories': 0} if filename == "": # root directory of branch branches[branch]['files'].append(filename) branches[branch]['number_of_directories'] += 1 elif filename.endswith("/"): # subdirectory of branch branches[branch]['files'].append(filename[:-1]) branches[branch]['number_of_directories'] += 1 else: branches[branch]['files'].append(filename) if not branches[branch].has_key('action'): branches[branch]['action'] = action for key in ("repository", "project", "codebase"): if key in where: branches[branch][key] = where[key] for branch in branches.keys(): action = branches[branch]['action'] files = branches[branch]['files'] number_of_directories_changed = branches[branch]['number_of_directories'] number_of_files_changed = len(files) if action == u'D' and number_of_directories_changed == 1 and number_of_files_changed == 1 and files[0] == '': log.msg("Ignoring deletion of branch '%s'" % branch) else: chdict = dict( author=author, files=files, comments=comments, revision=revision, branch=branch, revlink=revlink, category=self.category, repository=branches[branch].get('repository', self.svnurl), project=branches[branch].get('project', self.project), codebase=branches[branch].get('codebase', None)) changes.append(chdict) return changes @defer.inlineCallbacks def submit_changes(self, changes): for chdict in changes: yield self.master.addChange(src='svn', *chdict) def finished_ok(self, res): if self.cachepath: with open(self.cachepath, "w") as f: f.write(str(self.last_change)) log.msg("SVNPoller: finished polling %s" % res) return res	denny820909/builder	lib/python2.7/site-packages/buildbot-0.8.8-py2.7.egg/buildbot/changes/svnpoller.py	Python	mit	17,125	[ "Brian" ]	c6ee6cebb5316101c9122b06b364bf802cc40a90f4ed3ada65b71884900d110d
# Databricks notebook source # MAGIC %md # MAGIC # MAGIC # [SDS-2.2, Scalable Data Science](https://lamastex.github.io/scalable-data-science/sds/2/2/) # MAGIC # MAGIC This is used in a non-profit educational setting with kind permission of [Adam Breindel](https://www.linkedin.com/in/adbreind). # MAGIC This is not licensed by Adam for use in a for-profit setting. Please contact Adam directly at `adbreind@gmail.com` to request or report such use cases or abuses. # MAGIC A few minor modifications and additional mathematical statistical pointers have been added by Raazesh Sainudiin when teaching PhD students in Uppsala University. # COMMAND ---------- # MAGIC %md # MAGIC Archived YouTube video of this live unedited lab-lecture: # MAGIC # MAGIC [![Archived YouTube video of this live unedited lab-lecture](http://img.youtube.com/vi/Vwou20grUD4/0.jpg)](https://www.youtube.com/embed/Vwou20grUD4?start=378&end=2146&autoplay=1) [![Archived YouTube video of this live unedited lab-lecture](http://img.youtube.com/vi/-LLL3MUl9ps/0.jpg)](https://www.youtube.com/embed/-LLL3MUl9ps?start=0&end=2467&autoplay=1) # COMMAND ---------- # MAGIC %md # MAGIC #### We can also implement the model with mini-batches -- this will let us see matrix ops in action: # MAGIC # MAGIC (N.b., feed_dict is intended for small data / experimentation. For more info on ingesting data at scale, see https://www.tensorflow.org/api_guides/python/reading_data) # COMMAND ---------- # we know these params, but we're making TF learn them REAL_SLOPE_X1 = 2 # slope along axis 1 (x-axis) REAL_SLOPE_X2 = 3 # slope along axis 2 (y-axis) REAL_INTERCEPT = 5 # intercept along axis 3 (z-axis), think of (x,y,z) axes in the usual way # COMMAND ---------- import numpy as np # GENERATE a batch of true data, with a little Gaussian noise added def make_mini_batch(size=10): X = np.random.rand(size, 2) # Y = np.matmul(X, [REAL_SLOPE_X1, REAL_SLOPE_X2]) + REAL_INTERCEPT + 0.2 * np.random.randn(size) return X.reshape(size,2), Y.reshape(size,1) # COMMAND ---------- # MAGIC %md # MAGIC To digest what's going on inside the function above, let's take it step by step. # COMMAND ---------- Xex = np.random.rand(10, 2) # Xex is simulating PRNGs from independent Uniform [0,1] RVs Xex # visualize these as 10 orddered pairs of points in the x-y plane that makes up our x-axis and y-axis (or x1 and x2 axes) # COMMAND ---------- Yex = np.matmul(Xex, [REAL_SLOPE_X1, REAL_SLOPE_X2]) # + REAL_INTERCEPT + 0.2 * np.random.randn(size) Yex # COMMAND ---------- # MAGIC %md # MAGIC The first entry in Yex is obtained as follows (change the numbers in the produc below if you reevaluated the cells above) and geometrically it is the location in z-axis of the plane with slopes given by REAL_SLOPE_X1 in the x-axis and REAL_SLOPE_X2 in the y-aixs with intercept 0 at the point in the x-y or x1-x2 plane given by (0.68729439, 0.58462379). # COMMAND ---------- 0.68729439REAL_SLOPE_X1 + 0.58462379REAL_SLOPE_X2 # COMMAND ---------- # MAGIC %md # MAGIC The next steps are adding an intercept term to translate the plane in the z-axis and then a scaled (the multiplication by 0.2 here) gaussian noise from independetly drawn pseudo-random samples from the standard normal or Normal(0,1) random variable via `np.random.randn(size)`. # COMMAND ---------- Yex = np.matmul(Xex, [REAL_SLOPE_X1, REAL_SLOPE_X2]) + REAL_INTERCEPT # + 0.2 * np.random.randn(10) Yex # COMMAND ---------- Yex = np.matmul(Xex, [REAL_SLOPE_X1, REAL_SLOPE_X2]) + REAL_INTERCEPT + 0.2 * np.random.randn(10) Yex # note how each entry in Yex is jiggled independently a bit by 0.2 * np.random.randn() # COMMAND ---------- # MAGIC %md # MAGIC Thus we can now fully appreciate what is going on in `make_mini_batch`. This is meant to substitute for pulling random sub-samples of batches of the real data during stochastic gradient descent. # COMMAND ---------- make_mini_batch() # our mini-batch of Xx and Ys # COMMAND ---------- import tensorflow as tf batch = 5 # size of batch tf.reset_default_graph() # this is important to do before you do something new in TF # we will work with single floating point precision and this is specified in the tf.float32 type argument to each tf object/method x = tf.placeholder(tf.float32, shape=(batch, 2)) # placeholder node for the pairs of x variables (predictors) in batches of size batch x_aug = tf.concat( (x, tf.ones((batch, 1))), 1 ) # x_aug is a concatenation of a vector of 1`s along the first dimension y = tf.placeholder(tf.float32, shape=(batch, 1)) # placeholder node for the univariate response y with batch many rows and 1 column model_params = tf.get_variable("model_params", [3,1]) # these are the x1 slope, x2 slope and the intercept (3 rows and 1 column) y_model = tf.matmul(x_aug, model_params) # our two-factor regression model is defined by this matrix multiplication # note that the noise is formally part of the model and what we are actually modeling is the mean response... error = tf.reduce_sum(tf.square(y - y_model))/batch # this is mean square error where the sum is computed by a reduce call on addition train_op = tf.train.GradientDescentOptimizer(0.02).minimize(error) # learning rate is set to 0.02 init = tf.global_variables_initializer() # our way into running the TF session errors = [] # list to track errors over iterations with tf.Session() as session: session.run(init) for i in range(500): x_data, y_data = make_mini_batch(batch) # simulate the mini-batch of data x1,x2 and response y with noise _, error_val = session.run([train_op, error], feed_dict={x: x_data, y: y_data}) errors.append(error_val) out = session.run(model_params) print(out) # COMMAND ---------- REAL_SLOPE_X1, REAL_SLOPE_X2, REAL_INTERCEPT # compare with rue parameter values - it's not too far from the estimates # COMMAND ---------- import matplotlib.pyplot as plt fig, ax = plt.subplots() fig.set_size_inches((4,3)) plt.plot(errors) display(fig)	raazesh-sainudiin/scalable-data-science	db/2/2/054_DLbyABr_03a-BatchTensorFlowWithMatrices.py	Python	unlicense	6,018	[ "Gaussian" ]	92f383182ba078dd5dc208a7c21eb9590de9c853b924891811d41203a89d0556
#! CCSD dipole with user-specified basis set import psi4 psi4.set_output_file("output.dat", False) h2o = psi4.geometry(""" 0 1 H O 1 0.957 H 2 0.957 1 104.5 """) psi4.set_options({'freeze_core': 'false'}) psi4.basis_helper(""" # Sadlej-pVTZ spherical ** H 0 S 4 1.00 33.8650140000 0.0060680000 5.0947880000 0.0453160000 1.1587860000 0.2028460000 0.3258400000 0.5037090000 S 1 1.00 0.1027410000 1.0000000000 S 1 1.00 0.0324000000 1.0000000000 P 2 1.00 1.1588000000 0.1884400000 0.3258000000 0.8824200000 P 2 1.00 0.1027000000 0.1178000000 0.0324000000 0.0042000000 C 0 S 5 1.00 5240.6353000000 0.0009370000 782.2048000000 0.0072280000 178.3508300000 0.0363440000 50.8159420000 0.1306000000 16.8235620000 0.3189310000 S 2 1.00 6.1757760000 0.4387420000 2.4180490000 0.2149740000 S 1 1.00 0.5119000000 1.0000000000 S 1 1.00 0.1565900000 1.0000000000 S 1 1.00 0.0479000000 1.0000000000 P 4 1.00 18.8418000000 0.0138870000 4.1592400000 0.0862790000 1.2067100000 0.2887440000 0.3855400000 0.4994110000 P 1 1.00 0.1219400000 1.0000000000 P 1 1.00 0.0385680000 1.0000000000 D 2 1.00 1.2067000000 0.2628500000 0.3855000000 0.8043000000 D 2 1.00 0.1219000000 0.6535000000 0.0386000000 0.8636000000 O 0 S 5 1.00 10662.2850000000 0.0007990000 1599.7097000000 0.0061530000 364.7252600000 0.0311570000 103.6517900000 0.1155960000 33.9058050000 0.3015520000 S 2 1.00 12.2874690000 0.4448700000 4.7568050000 0.2431720000 S 1 1.00 1.0042710000 1.0000000000 S 1 1.00 0.3006860000 1.0000000000 S 1 1.00 0.0900300000 1.0000000000 P 4 1.00 34.8564630000 0.0156480000 7.8431310000 0.0981970000 2.3062490000 0.3077680000 0.7231640000 0.4924700000 P 1 1.00 0.2148820000 1.0000000000 P 1 1.00 0.0638500000 1.0000000000 D 2 1.00 2.3062000000 0.2027000000 0.7232000000 0.5791000000 D 2 1.00 0.2149000000 0.7854500000 0.0639000000 0.5338700000 ** """) ccsd_e, wfn = psi4.properties('ccsd',properties=['dipole'],return_wfn=True) psi4.oeprop(wfn,"DIPOLE", "QUADRUPOLE", title="(OEPROP)CC") import warnings #TEST with warnings.catch_warnings(): #TEST warnings.simplefilter("ignore") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC DIPOLE X"), 0.000000000000,6,"CC DIPOLE X") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC DIPOLE Y"), 0.000000000000,6,"CC DIPOLE Y") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC DIPOLE Z"),-1.840334899884,6,"CC DIPOLE Z") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE XX"),-7.864006962064,6,"CC QUADRUPOLE XX") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE XY"), 0.000000000000,6,"CC QUADRUPOLE XY") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE XZ"), 0.000000000000,6,"CC QUADRUPOLE XZ") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE YY"),-4.537386915305,6,"CC QUADRUPOLE YY") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE YZ"), 0.000000000000,6,"CC QUADRUPOLE YZ") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE ZZ"),-6.325836255265,6,"CC QUADRUPOLE ZZ") #TEST psi4.core.print_variables()	ashutoshvt/psi4	tests/python/cc54/input.py	Python	lgpl-3.0	4,053	[ "Psi4" ]	185c8664d8dbe6d1925c118436247e52e717768f8114d504ada7143e2181dfe2
from __future__ import print_function import numpy as np from numpy import zeros, ones, einsum from .constants import tol6, tol8, tol12, Ha2eV, kb_HaK from .mathutil import delta_lorentzian from . import EigFile, Eigr2dFile, FanFile, DdbFile, GkkFile __author__ = "Gabriel Antonius" __all__ = ['QptAnalyzer'] class QptAnalyzer(object): def __init__(self, ddb_fname=None, eigq_fname=None, eigk_fname=None, eigr2d_fname=None, eigr2d0_fname=None, eigi2d_fname=None, fan_fname=None, fan0_fname=None, gkk_fname=None, gkk0_fname=None, wtq=1.0, smearing=0.00367, temperatures=None, omegase=None, asr=True, mu=None, ): # Files self.ddb = DdbFile(ddb_fname, read=False, asr=asr) self.eigq = EigFile(eigq_fname, read=False) self.eigr2d = Eigr2dFile(eigr2d_fname, read=False) self.eigi2d = Eigr2dFile(eigi2d_fname, read=False) self.fan = FanFile(fan_fname, read=False) self.eig0 = EigFile(eigk_fname, read=False) self.eigr2d0 = Eigr2dFile(eigr2d0_fname, read=False) self.fan0 = FanFile(fan0_fname, read=False) self.gkk = GkkFile(gkk_fname, read=False) self.gkk0 = GkkFile(gkk0_fname, read=False) self.wtq = wtq self.smearing = smearing self.omegase = omegase if omegase else list() self.temperatures = temperatures if temperatures else list() self.mu = mu @property def nkpt(self): if self.eigr2d.fname: return self.eigr2d.nkpt elif self.fan.fname: return self.fan.nkpt elif self.gkk.fname: return self.gkk.nkpt else: raise Exception("Don't know nkpt. No files to read.") @property def nband(self): if self.eigr2d.fname: return self.eigr2d.nband elif self.fan.fname: return self.fan.nband elif self.gkk.fname: return self.gkk.nband else: raise Exception("Don't know nband. No files to read.") @property def natom(self): return self.ddb.natom @property def nmode(self): return self.ddb.nmode @property def is_gamma(self): return self.ddb.is_gamma @property def qred(self): return self.ddb.qred @property def omega(self): return self.ddb.omega @property def nomegase(self): return len(self.omegase) @property def ntemp(self): return len(self.temperatures) @property def use_gkk(self): return (bool(self.gkk.fname) and bool(self.gkk0.fname)) @property def has_active(self): return (bool(self.fan.fname) and bool(self.fan0.fname)) or self.use_gkk def read_nonzero_files(self): """Read all nc files that are not specifically related to q=0.""" for f in (self.ddb, self.eigq, self.eigr2d, self.eigi2d, self.fan, self.gkk): if f.fname: f.read_nc() self.ddb.compute_dynmat() def read_ddb(self): """Read the ddb and diagonalize the matrix, setting omega.""" self.ddb.read_nc() self.ddb.compute_dynmat() def read_zero_files(self): """Read all nc files that are not specifically related to q=0.""" for f in (self.eig0, self.eigr2d0, self.fan0, self.gkk0): if f.fname: f.read_nc() def broadcast_zero_files(self): """Broadcast the data related to q=0 from master to all workers.""" if self.eig0.fname: self.eig0.broadcast() self.eig0.get_degen() if self.eigr2d0.fname: self.eigr2d0.broadcast() if self.fan0.fname: self.fan0.broadcast() if self.gkk0.fname: self.gkk0.broadcast() def get_occ_kq_nospin(self): """ Get the occupations, being either 0 or 1, regardless of spinor. Assumes a gapped system, where occupations are the same at all kpts. Returns: occ[nband] """ if self.eigr2d.fname: occ = self.eigr2d.occ[0,0,:] elif self.fan.fname: occ = self.fan.occ[0,0,:] elif self.gkk.fname: occ = self.gkk.occ[0,0,:] else: raise Exception("Don't know nband. No files to read.") if any(occ == 2.0): occ = occ / 2.0 return occ def get_max_val(self): """Get the maximum valence band energy.""" occ0 = self.get_occ_kq_nospin() eig = self.eigq.EIG[0,0,:] E_last = eig[0] for f, E in zip(occ0, eig): if f < 0.5: break E_last = E return E_last def get_min_cond(self): """Get the minimum conduction band energy.""" occ0 = self.get_occ_kq_nospin() eig = self.eigq.EIG[0,0,:] for f, E in zip(occ0, eig): if f <= 0.5: break return E def find_fermi_level(self): """ Find the Fermi level locally, using the eigenvalues at all k+q points available. Assuming a gapped system. """ return (self.get_max_val() + self.get_min_cond()) / 2.0 @staticmethod def reduce_array(arr, mode=False, temperature=False, omega=False): """ Eliminate dimensions from an array of shape (nmode, ntemp, nomegase, nkpt, nband) by summing over any or all of the first three dimension. mode: Keep the first dimension temperature: Keep the second dimension omega: Keep the third dimension """ # Find the final order of final_indices = '' if mode: final_indices += 'o' if temperature: final_indices += 't' if omega: final_indices += 'l' final_indices += 'kn' summation = 'otlkn->' + final_indices return einsum(summation, arr) def get_fan_ddw_sternheimer(self, mode=False, omega=False, temperature=False): """ Compute the fan and ddw contribution to the self-energy obtained from the Sternheimer equation, that is, the contribution of the upper bands. Do not include the q-point weight. Returns: fan, ddw The return arrays vary in dimensions, depending on the input arguments. These arrays are at most of dimension 5, as fan[nmode, ntemp, nomegase, nkpt, nband] ddw[nmode, ntemp, nomegase, nkpt, nband] Depending on the truth value of the input arguments, the dimension nomegase (omega) and ntemp (temperature) will be eliminated. The dimension nmode will be summed over in case mode=False. In the semi-static approximation, these quantities do not actually depend on omega, so the arrays are simply repated along the omega axis. """ nkpt = self.nkpt nband = self.nband natom = self.natom nmode = self.nmode nomegase = self.nomegase ntemp = self.ntemp # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() # FIXME this will not work for nsppol=2 # nmode, nkpt, nband fan = einsum('knabij,objai->okn', self.eigr2d.EIG2D, displ_red_FAN2) ddw = einsum('knabij,objai->okn', self.eigr2d0.EIG2D, displ_red_DDW2) # Temperature dependence factor n_B = self.ddb.get_bose(self.temperatures) tdep = 2 * n_B + 1 if temperature else ones((nmode,1)) # Omega dependence factor odep = ones(nomegase) if omega else ones(1) # nmode, ntemp, nkpt, nband fan = einsum('okn,ot->otkn', fan, tdep) ddw = einsum('okn,ot->otkn', ddw, tdep) # nmode, ntemp, nomega, nkpt, nband fan = einsum('otkn,l->otlkn', fan, odep) ddw = einsum('otkn,l->otlkn', ddw, odep) # Reduce the arrays fan = self.reduce_array(fan, mode=mode, temperature=temperature, omega=omega) ddw = self.reduce_array(ddw, mode=mode, temperature=temperature, omega=omega) return fan, ddw def get_fan_ddw_gkk2_active(self): """ Compute the squared gkk elements for the fan ddw terms. Returns: fan[nkpt, nband, nband, nmode] ddw[nkpt, nband, nband, nmode] """ if not self.has_active: raise Exception('You should provide GKK files or FAN files ' 'to compute active space contribution.') # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() if self.use_gkk: gkk2 = self.gkk.get_gkk_squared() gkk02 = self.gkk0.get_gkk_squared() else: gkk2 = self.fan.FAN gkk02 = self.fan0.FAN # nkpt, nband, nband, nmode fan = einsum('kniajbm,oabij->knmo', gkk2, displ_red_FAN2) ddw = einsum('kniajbm,oabij->knmo', gkk02, displ_red_DDW2) # Enforce the diagonal coupling terms to be zero at Gamma ddw = self.eig0.symmetrize_fan_degen(ddw) if self.is_gamma: fan = self.eig0.symmetrize_fan_degen(fan) return fan, ddw def get_fan_ddw_active(self, mode=False, omega=False, temperature=False, dynamical=True): """ Compute the fan and ddw contributions to the self-energy from the active space, that is, the the lower bands. Do not include the q-point weight. Returns: fan, ddw The return arrays vary in dimensions, depending on the input arguments. These arrays are at most of dimension 5, as fan[nmode, ntemp, nomegase, nkpt, nband] ddw[nmode, ntemp, nomegase, nkpt, nband] Depending on the truth value of the input arguments, the dimension nomegase (omega) and ntemp (temperature) will be eliminated. The dimension nmode will be summed over in case mode=False. The Debye-Waller term does not actually depends on omega, but this dimension is kept anyway. """ nkpt = self.nkpt nband = self.nband nmode = self.nmode if temperature: ntemp = self.ntemp temperatures = self.temperatures # Bose-Enstein occupation number # nmode, ntemp n_B = self.ddb.get_bose(temperatures) else: ntemp = 1 temperatures = zeros(1) n_B = zeros((nmode,1)) if omega: nomegase = self.nomegase omega_se = self.omegase else: # omega_se is measured from the bare eigenvalues nomegase = 1 omega_se = zeros(1) if dynamical: omega_q = self.ddb.omega[:].real else: omega_q = zeros(nmode) # Fermi-Dirac occupation number # nspin, nkpt, nband, ntemp occ = self.eigq.get_fermi_function(self.mu, temperatures) # G^2 # nkpt, nband, nband, nmode fan_g2, ddw_g2 = self.get_fan_ddw_gkk2_active() # DDW term # -------- # nkpt, nband occ0 = self.eig0.get_fermi_function_T0(self.mu)[0,:,:] # nkpt, nband, nband delta_E_ddw = (einsum('kn,m->knm', self.eig0.EIG[0,:,:].real, ones(nband)) - einsum('kn,m->kmn', self.eig0.EIG[0,:,:].real, ones(nband)) - einsum('m,kn->knm', ones(nband), (2occ0-1)) self.smearing * 1j) # nmode, nkpt, nband ddw = einsum('knmo,knm->okn', ddw_g2, 1.0 / delta_E_ddw) # nmode, ntemp tdep = 2 * n_B + 1 # FIXME This is not optimal: The mode indices will be summed # so there is no need to create an array this big. # in case omega=True and mode=False # nmode, ntemp, nkpt, nband ddw = einsum('okn,ot->otkn', ddw, tdep) odep = ones(nomegase) if omega else ones(0) # ntemp, nomega, nkpt, nband ddw = einsum('otkn,l->otlkn', ddw, ones(nomegase)) # Reduce the arrays ddw = self.reduce_array(ddw, mode=mode, temperature=temperature, omega=omega) # Fan term # -------- # nmode, ntemp, nomegase, nkpt, nband fan = zeros((nmode, ntemp, nomegase, nkpt, nband), dtype=complex) # n + 1 - f # nkpt, nband, nmode, ntemp num1 = (einsum('ot,kn->knot', n_B, ones((nkpt,nband))) + 1. - einsum('knt,o->knot', occ[0,:,:,:], ones(nmode))) # n + f # nkpt, nband, nmode, ntemp num2 = (einsum('ot,kn->knot', n_B, ones((nkpt,nband))) + einsum('knt,o->knot', occ[0,:,:,:], ones(nmode))) # nkpt, nband eta = (2 * occ0 - 1) * self.smearing * 1j for jband in range(nband): # nkpt, nband delta_E = ( self.eig0.EIG[0,:,:].real - einsum('k,n->kn', self.eigq.EIG[0,:,jband].real, ones(nband)) - eta) # nkpt, nband, nomegase delta_E_omega = (einsum('kn,l->knl', delta_E, ones(nomegase)) + einsum('kn,l->knl', ones((nkpt,nband)), omega_se)) # nkpt, nband, nomegase, nmode deno1 = (einsum('knl,o->knlo', delta_E_omega, ones(nmode)) - einsum('knl,o->knlo', ones((nkpt,nband,nomegase)), omega_q)) # nmode, nkpt, nband, nomegase, ntemp div1 = einsum('kot,knlo->oknlt', num1[:,jband,:,:], 1.0 / deno1) del deno1 # nkpt, nband, nomegase, nmode deno2 = (einsum('knl,o->knlo', delta_E_omega, ones(nmode)) + einsum('knl,o->knlo', ones((nkpt,nband,nomegase)), omega_q)) # nmode, nkpt, nband, nomegase, ntemp div2 = einsum('kot,knlo->oknlt', num2[:,jband,:,:], 1.0 / deno2) del deno2 # FIXME This is not optimal: The mode indices will be summed # so there is no need to create an array this big. # in case omega=True and mode=False # nmode, ntemp, nomegase, nkpt, nband fan += einsum('kno,oknlt->otlkn', fan_g2[:,:,jband,:], div1 + div2) del div1, div2 # Reduce the arrays fan = self.reduce_array(fan, mode=mode, temperature=temperature, omega=omega) return fan, ddw def get_fan_ddw(self, mode=False, temperature=False, omega=False, dynamical=False): kwargs = dict( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) fan_stern, ddw_stern = self.get_fan_ddw_sternheimer( mode=mode, temperature=temperature, omega=omega, ) fan_active, ddw_active = self.get_fan_ddw_active( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) fan = fan_active + fan_stern ddw = ddw_active + ddw_stern return fan, ddw def get_self_energy(self, mode=False, temperature=False, omega=False, dynamical=True, only_sternheimer=False, only_active=False, only_fan=False, only_ddw=False, ): if only_sternheimer and only_active: raise Exception( 'only_sternheimer and only_active cannot be True at the same time') elif only_sternheimer: fan, ddw = self.get_fan_ddw_sternheimer( mode=mode, temperature=temperature, omega=omega, ) elif only_active: fan, ddw = self.get_fan_ddw_active( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) else: fan, ddw = self.get_fan_ddw( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) if only_fan: se_q = fan elif only_ddw: se_q = - ddw else: se_q = fan - ddw se = self.wtq * se_q se = self.eig0.make_average(se) return se def get_broadening(self, mode=False, temperature=False, omega=False, dynamical=True): """ Compute the zp broadening contribution from one q-point in a dynamical scheme. Only take the active space contribution. """ nkpt = self.nkpt nband = self.nband nmode = self.nmode if temperature: ntemp = self.ntemp temperatures = self.temperatures # Bose-Enstein occupation number # nmode, ntemp n_B = self.ddb.get_bose(temperatures) else: ntemp = 1 temperatures = zeros(1) n_B = zeros((nmode,1)) if omega: nomegase = self.nomegase omega_se = self.omegase else: # omega_se is measured from the bare eigenvalues nomegase = 1 omega_se = zeros(1) if dynamical: omega_q = self.ddb.omega[:].real else: omega_q = zeros(nmode) # Fermi-Dirac occupation number # nspin, nkpt, nband, ntemp occ = self.eigq.get_fermi_function(self.mu, temperatures) # nkpt, nband, ntemp f = occ[0] # nkpt, nband occ0 = self.eig0.get_fermi_function_T0(self.mu)[0,:,:] # nkpt, nband, nband, nmode fan_g2, ddw_g2 = self.get_fan_ddw_gkk2_active() # nmode, ntemp, nkpt n_B = einsum('ot,q->otq', n_B, ones(nkpt)) # nmode, ntemp, nkpt,nband f = einsum('qmt,o->otqm', f, ones(nmode)) # nkpt, nband sign = np.sign(- (2 * occ0 - 1.)) broadening = zeros((nmode,ntemp,nomegase,nkpt,nband)) for jband in range(nband): # nmode, ntemp, nkpt num1 = (n_B + f[...,jband]) num2 = (n_B + 1 - f[...,jband]) # nkpt, nband delta_E = ( self.eig0.EIG[0,:,:].real - einsum('q,n->qn', self.eigq.EIG[0,:,jband].real, ones(nband)) ) # nkpt, nband, nomegase delta_E_omega = (einsum('kn,l->knl', delta_E, ones(nomegase)) + einsum('kn,l->knl', ones((nkpt,nband)), omega_se)) # nmode, nkpt, nband, nomegase deno1 = ( einsum('knl,o->oknl', delta_E_omega, ones(nmode)) + einsum('o,knl->oknl', omega_q, ones((nkpt,nband,nomegase))) ) # nmode, nkpt, nband, nomegase deno2 = ( einsum('knl,o->oknl', delta_E_omega, ones(nmode)) - einsum('o,knl->oknl', omega_q, ones((nkpt,nband,nomegase))) ) # nmode, nkpt, nband, nomegase delta1 = np.pi * delta_lorentzian(deno1, self.smearing) delta2 = np.pi * delta_lorentzian(deno2, self.smearing) # nmode, ntemp, nomegase, nkpt, nband term1 = einsum('otk,oknl->otlkn', num1, delta1) term2 = einsum('otk,oknl->otlkn', num2, delta2) deltas = einsum('kn,otlkn->otlkn', sign, term1 + term2) broadening_j = einsum('kno,otlkn->otlkn', fan_g2[:,:,jband,:], deltas) broadening += broadening_j.real # Reduce the arrays broadening = self.reduce_array(broadening, mode=mode, temperature=temperature, omega=omega) broadening = self.wtq broadening = self.eig0.make_average(broadening) return broadening def get_zp_self_energy(self): """ Compute the zp frequency-dependent dynamical self-energy from one q-point. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega) = Sigma_kn(omega + E^0_kn) Returns: sigma[nkpt,nband,nomegase] """ self.sigma = self.get_self_energy( mode=False, temperature=False, omega=True, dynamical=True, only_sternheimer=False, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('lkn->knl', self.sigma) # FIXME why?? return self.sigma def get_td_self_energy(self): """ Compute the temperature depended and frequency-dependent dynamical self-energy from one q-point. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega,T) = Sigma_kn(omega + E^0_kn, T) Returns: sigma[nkpt,nband,nomegase,ntemp] """ self.sigma = self.get_self_energy( mode=False, temperature=True, omega=True, dynamical=True, only_sternheimer=False, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('tlkn->knlt', self.sigma) # FIXME why?? return self.sigma def get_zp_self_energy_active(self): """ Compute the zp frequency-dependent dynamical self-energy from one q-point. Only include the active space contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega) = Sigma_kn(omega + E^0_kn) Returns: sigma[nkpt,nband,nomegase] """ self.sigma = self.get_self_energy( mode=False, temperature=False, omega=True, dynamical=True, only_sternheimer=False, only_active=True, ) # nkpt, nband, nomegase, nband self.sigma = einsum('lkn->knl', self.sigma) # FIXME why?? return self.sigma def get_zp_self_energy_sternheimer(self): """ Compute the zp frequency-dependent dynamical self-energy from one q-point. Only include the Sternheimer contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega) = Sigma_kn(omega + E^0_kn) Returns: sigma[nkpt,nband,nomegase] """ self.sigma = self.get_self_energy( mode=False, temperature=False, omega=True, dynamical=True, only_sternheimer=True, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('lkn->knl', self.sigma) # FIXME why?? return self.sigma def get_td_self_energy_active(self): """ Compute the temperature depended and frequency-dependent dynamical self-energy from one q-point. Only include the active space contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega,T) = Sigma_kn(omega + E^0_kn, T) Returns: sigma[nkpt,nband,nomegase,ntemp] """ self.sigma = self.get_self_energy( mode=False, temperature=True, omega=True, dynamical=True, only_sternheimer=False, only_active=True, ) # nkpt, nband, nomegase, nband self.sigma = einsum('tlkn->knlt', self.sigma) # FIXME why?? return self.sigma def get_td_self_energy_sternheimer(self): """ Compute the temperature depended and frequency-dependent dynamical self-energy from one q-point. Only include the Sternheimer contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega,T) = Sigma_kn(omega + E^0_kn, T) Returns: sigma[nkpt,nband,nomegase,ntemp] """ self.sigma = self.get_self_energy( mode=False, temperature=True, omega=True, dynamical=True, only_sternheimer=True, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('tlkn->knlt', self.sigma) # FIXME why?? return self.sigma def get_zpr_static_sternheimer(self): """Compute the q-point zpr contribution in a static scheme.""" self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=False, only_sternheimer=True, only_active=False, ).real return self.zpr def get_zpr_static(self): """ Compute the q-point zpr contribution in a static scheme, with the transitions split between active and sternheimer. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=False, only_sternheimer=False, only_active=False, ).real return self.zpr def get_zpr_dynamical(self): """ Compute the q-point zpr contribution in a static scheme with the transitions split between active and sternheimer. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=True, only_sternheimer=False, only_active=False, ).real return self.zpr def get_tdr_static(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a static scheme, with the transitions split between active and sternheimer. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=False, only_sternheimer=False, only_active=False, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_tdr_dynamical(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a dynamical scheme. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=True, only_sternheimer=False, only_active=False, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_tdr_static_nosplit(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a static scheme. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=False, only_sternheimer=True, only_active=False, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_tdr_dynamical_active(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a dynamical scheme, taking only the active space contribution. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=True, only_sternheimer=False, only_active=True, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_zpr_dynamical_active(self): """ Compute the q-point contribution to the zero point renormalization in a dynamical scheme, taking only the active space contribution. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=True, only_sternheimer=False, only_active=True, ).real # nkpt, nband, ntemp return self.zpr def get_zpr_static_modes(self): """ Compute the q-point zpr contribution in a static scheme, with the transitions split between active and sternheimer. Retain the mode decomposition of the zpr. """ self.zpr = self.get_self_energy( mode=True, temperature=False, omega=False, dynamical=False, only_sternheimer=False, only_active=False, ).real # nmode, nkpt, nband return self.zpr # FIXME use self.zpr_mode? def get_zpb_dynamical(self): """ Compute the zp broadening contribution from one q-point in a dynamical scheme. Only take the active space contribution. Returns: zpb[nkpt,nband] """ self.zpb = self.get_broadening(mode=False, temperature=False, omega=False, dynamical=True) return self.zpb def get_tdb_dynamical(self): """ Compute the td broadening contribution from one q-point in a dynamical scheme. Only take the active space contribution. Returns: zpb[nkpt,nband,ntemp] """ self.tdb = self.get_broadening(mode=False, temperature=True, omega=False, dynamical=True) self.tdb = einsum('tkn->knt', self.tdb) # FIXME why?? return self.tdb def get_zpb_static(self): """ Compute the zp broadening contribution from one q-point in a static scheme. Only take the active space contribution. Returns: zpb[nkpt,nband] """ self.zpb = self.get_broadening(mode=False, temperature=False, omega=False, dynamical=False) return self.zpb def get_tdb_static(self): """ Compute the td broadening contribution from one q-point in a static scheme. Only take the active space contribution. Returns: zpb[nkpt,nband,ntemp] """ self.tdb = self.get_broadening(mode=False, temperature=True, omega=False, dynamical=False) self.tdb = einsum('tkn->knt', self.tdb) # FIXME why?? return self.tdb def get_tdb_static_nosplit(self): """ Compute the q-point contribution to the temperature-dependent broadening in a static scheme from the EIGI2D files. """ nkpt = self.nkpt nband = self.nband natom = self.natom ntemp = self.ntemp # These indicies be swapped at the end self.tdb = zeros((ntemp, nkpt, nband), dtype=complex) # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() bose = self.ddb.get_bose(self.temperatures) fan_corrQ = einsum('ijklmn,olnkm->oij', self.eigi2d.EIG2D, displ_red_FAN2) for imode in np.arange(3natom): for tt, T in enumerate(self.temperatures): self.tdb[tt,:,:] += np.pi * fan_corrQ[imode,:,:] * (2bose[imode,tt] + 1.) self.tdb = self.tdb self.wtq self.tdb = self.eig0.make_average(self.tdb) # nkpt, nband, ntemp self.tdb = np.einsum('tkn->knt', self.tdb) return self.tdb def get_zpb_static_nosplit(self): """ Compute the zp broadening contribution from one q-point in a static scheme from the EIGI2D files. """ nkpt = self.nkpt nband = self.nband natom = self.natom self.zpb = zeros((nkpt, nband), dtype=complex) # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() fan_corrQ = einsum('ijklmn,olnkm->oij', self.eigi2d.EIG2D, displ_red_FAN2) self.zpb += np.pi * np.sum(fan_corrQ, axis=0) self.zpb = self.zpb * self.wtq if np.any(self.zpb[:,:].imag > tol12): warnings.warn("The real part of the broadening is non zero: {}".format(broadening)) self.zpb = self.eig0.make_average(self.zpb) return self.zpb def get_zpr_ddw_active(self): """ Compute the q-point zpr contribution in a static scheme with the transitions split between active and sternheimer. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=False, only_sternheimer=False, only_active=True, only_ddw=True, ).real return self.zpr	jmbeuken/abinit	scripts/post_processing/ElectronPhononCoupling/ElectronPhononCoupling/core/qptanalyzer.py	Python	gpl-3.0	34,212	[ "DIRAC" ]	b0b8dbe6d1c83ea8b9b09f42206c7561554a5156367c4b677ffa30ccc2ff52aa
# # tsne.py # # Implementation of t-SNE in Python. The implementation was tested on Python 2.5.1, and it requires a working # installation of NumPy. The implementation comes with an example on the MNIST dataset. In order to plot the # results of this example, a working installation of matplotlib is required. # The example can be run by executing: ipython tsne.py -pylab # # # Created by Laurens van der Maaten on 20-12-08. # Copyright (c) 2008 Tilburg University. All rights reserved. import numpy as np def Hbeta(D = np.array([]), beta = 1.0): """Compute the perplexity and the P-row for a specific value of the precision of a Gaussian distribution.""" # Compute P-row and corresponding perplexity P = np.exp(-D.copy() * beta); sumP = sum(P); H = np.log(sumP) + beta * np.sum(D * P) / sumP; P = P / sumP; return H, P; def x2p(X = np.array([]), tol = 1e-5, perplexity = 30.0): """Performs a binary search to get P-values in such a way that each conditional Gaussian has the same perplexity.""" # Initialize some variables print "Computing pairwise distances..." (n, d) = X.shape; sum_X = np.sum(np.square(X), 1); D = np.add(np.add(-2 * np.dot(X, X.T), sum_X).T, sum_X); P = np.zeros((n, n)); beta = np.ones((n, 1)); logU = np.log(perplexity); # Loop over all datapoints for i in range(n): # Print progress if i % 500 == 0: print "Computing P-values for point ", i, " of ", n, "..." # Compute the Gaussian kernel and entropy for the current precision betamin = -np.inf; betamax = np.inf; Di = D[i, np.concatenate((np.r_[0:i], np.r_[i+1:n]))]; (H, thisP) = Hbeta(Di, beta[i]); # Evaluate whether the perplexity is within tolerance Hdiff = H - logU; tries = 0; while np.abs(Hdiff) > tol and tries < 50: # If not, increase or decrease precision if Hdiff > 0: betamin = beta[i]; if betamax == np.inf or betamax == -np.inf: beta[i] = beta[i] * 2; else: beta[i] = (beta[i] + betamax) / 2; else: betamax = beta[i]; if betamin == np.inf or betamin == -np.inf: beta[i] = beta[i] / 2; else: beta[i] = (beta[i] + betamin) / 2; # Recompute the values (H, thisP) = Hbeta(Di, beta[i]); Hdiff = H - logU; tries = tries + 1; # Set the final row of P P[i, np.concatenate((np.r_[0:i], np.r_[i+1:n]))] = thisP; # Return final P-matrix print "Mean value of sigma: ", np.mean(np.sqrt(1 / beta)) return P; def pca(X = np.array([]), no_dims = 50): """Runs PCA on the NxD array X in order to reduce its dimensionality to no_dims dimensions.""" print "Preprocessing the data using PCA..." (n, d) = X.shape; X = X - np.tile(np.mean(X, 0), (n, 1)); (l, M) = np.linalg.eig(np.dot(X.T, X)); Y = np.dot(X, M[:,0:no_dims]); np.testing.assert_array_almost_equal(np.imag(Y), np.zeros(Y.shape)) return np.real(Y); def tsne(X = np.array([]), no_dims = 2, initial_dims = 50, perplexity = 30.0): """Runs t-SNE on the dataset in the NxD array X to reduce its dimensionality to no_dims dimensions. The syntaxis of the function is Y = tsne.tsne(X, no_dims, perplexity), where X is an NxD NumPy array.""" # Check inputs if X.dtype != "float64": print "Error: array X should have type float64."; return -1; #if no_dims.__class__ != "<type 'int'>": # doesn't work yet! # print "Error: number of dimensions should be an integer."; # return -1; # Initialize variables X = pca(X, initial_dims); (n, d) = X.shape; max_iter = 1000; initial_momentum = 0.5; final_momentum = 0.8; eta = 500; min_gain = 0.01; Y = np.random.randn(n, no_dims); dY = np.zeros((n, no_dims)); iY = np.zeros((n, no_dims)); gains = np.ones((n, no_dims)); # Compute P-values P = x2p(X, 1e-5, perplexity); P = P + np.transpose(P); P = P / np.sum(P); P = P * 4; # early exaggeration P = np.maximum(P, 1e-12); # Run iterations for iter in range(max_iter): # Compute pairwise affinities sum_Y = np.sum(np.square(Y), 1); num = 1 / (1 + np.add(np.add(-2 * np.dot(Y, Y.T), sum_Y).T, sum_Y)); num[range(n), range(n)] = 0; Q = num / np.sum(num); Q = np.maximum(Q, 1e-12); # Compute gradient PQ = P - Q; for i in range(n): dY[i,:] = np.sum(np.tile(PQ[:,i] * num[:,i], (no_dims, 1)).T * (Y[i,:] - Y), 0); # Perform the update if iter < 20: momentum = initial_momentum else: momentum = final_momentum gains = (gains + 0.2) * ((dY > 0) != (iY > 0)) + (gains * 0.8) * ((dY > 0) == (iY > 0)); gains[gains < min_gain] = min_gain; iY = momentum * iY - eta * (gains * dY); Y = Y + iY; Y = Y - np.tile(np.mean(Y, 0), (n, 1)); # Compute current value of cost function if (iter + 1) % 10 == 0: C = np.sum(P * np.log(P / Q)); print "Iteration ", (iter + 1), ": error is ", C # Stop lying about P-values if iter == 100: P = P / 4; # Return solution return Y; if __name__ == "__main__": import pylab print "Run Y = tsne.tsne(X, no_dims, perplexity) to perform t-SNE on your dataset." print "Running example on 2,500 MNIST digits..." X = np.loadtxt("mnist2500_X.txt"); labels = np.loadtxt("mnist2500_labels.txt"); Y = tsne(X, 2, 50, 20.0); pylab.scatter(Y[:,0], Y[:,1], 20, labels);	afraser/CellProfiler-Analyst	cpa/tsne.py	Python	gpl-2.0	5,205	[ "Gaussian" ]	19443cc85cf3ba62aad79dc3d4331e460883e83ce4333dcc8455d6f9c891d732
# Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You may not # use this file except in compliance with the License. A copy of the License # is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is distributed on # an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either # express or implied. See the License for the specific language governing # permissions and limitations under the License. import logging import math from typing import Dict, Optional, Tuple, Union import mxnet as mx import numpy as np from . import constants as C from . import utils logger = logging.getLogger(__name__) def activation(data: mx.sym.Symbol, act_type: str) -> mx.sym.Symbol: """ Apply custom or standard activation. Custom activation types include: - Swish-1, also called Sigmoid-Weighted Linear Unit (SiLU): Ramachandran et al. (https://arxiv.org/pdf/1710.05941.pdf), Elfwing et al. (https://arxiv.org/pdf/1702.03118.pdf) - Gaussian Error Linear Unit (GELU): Hendrycks and Gimpel (https://arxiv.org/pdf/1606.08415.pdf) :param data: input Symbol of any shape. :param act_type: Type of activation. :return: output Symbol with same shape as input. """ # TODO: Contribute these to MXNet? For now it appears that registered activation types must be implemented in C++. if act_type == C.SWISH1: return data * mx.sym.Activation(data, act_type="sigmoid") elif act_type == C.GELU: # Approximation of x * gaussian_cdf(x) used by Hendrycks and Gimpel return 0.5 * data * (1 + mx.sym.Activation((math.sqrt(2 / math.pi) * (data + (0.044715 * (data*3)))), act_type="tanh")) else: return mx.sym.Activation(data, act_type=act_type) class LayerNormalization: """ Implements Ba et al, Layer Normalization (https://arxiv.org/abs/1607.06450). :param prefix: Optional prefix of layer name. :param scale: Optional variable for scaling of shape (num_hidden,). Will be created if None. :param shift: Optional variable for shifting of shape (num_hidden,). Will be created if None. :param scale_init: Initial value of scale variable if scale is None. Default 1.0. :param shift_init: Initial value of shift variable if shift is None. Default 0.0. """ def __init__(self, prefix: str = 'layernorm', scale: Optional[mx.sym.Symbol] = None, shift: Optional[mx.sym.Symbol] = None, scale_init: float = 1.0, shift_init: float = 0.0) -> None: self.prefix = prefix self.scale = scale if scale is not None else mx.sym.Variable('%s_gamma' % prefix, init=mx.init.Constant(value=scale_init)) self.shift = shift if shift is not None else mx.sym.Variable('%s_beta' % prefix, init=mx.init.Constant(value=shift_init)) def __call__(self, data: mx.sym.Symbol, eps: float = 1e-06) -> mx.sym.Symbol: """ Normalizes hidden units of data as follows: data = scale (data - mean) / sqrt(var + eps) + shift Normalization is performed over the last dimension of the input data. :param data: Data to normalize. Shape: (d0, ..., dn, num_hidden). :param eps: Variance epsilon. :return: inputs_norm: Normalized inputs. Shape: (d0, ..., dn, num_hidden). """ return mx.sym.LayerNorm(data=data, gamma=self.scale, beta=self.shift, axis=-1, eps=eps, output_mean_var=False, name=self.prefix) class LHUC: """ Learning Hidden Unit Contribution David Vilar. "Learning Hidden Unit Contribution for Adapting Neural Machine Translation Models" NAACL 2018 :param num_hidden: Number of hidden units of the layer to be modified. :param weight: Optional parameter vector. :param prefix: Optional prefix for created parameters (if not given as weight). """ def __init__(self, num_hidden: int, weight: Optional[mx.sym.Symbol] = None, prefix: str = "") -> None: self.num_hidden = num_hidden self.prefix = prefix if weight is None: self.params = mx.sym.Variable(self.prefix + C.LHUC_NAME, shape=(self.num_hidden,), init=mx.init.Uniform(0.1), dtype="float32") else: self.params = weight def __call__(self, inputs: mx.sym.Symbol, name: Optional[str] = None) -> mx.sym.Symbol: # We use a sigmoid with amplitude 2 for weighting the hidden units. The # activation is dampened when the value of the sigmoid is close to 0, and # strengthened when it's close to 2 (see also original paper) weight_vector = 2 * mx.sym.Activation(data=self.params, act_type="sigmoid") out = mx.sym.broadcast_mul(weight_vector, inputs, name=name) return out class WeightNormalization: """ Implements Weight Normalization, see Salimans & Kingma 2016 (https://arxiv.org/abs/1602.07868). For a given tensor the normalization is done per hidden dimension. :param weight: Weight tensor of shape: (num_hidden, d1, d2, ...). :param num_hidden: Size of the first dimension. :param ndim: The total number of dimensions of the weight tensor. :param prefix: The prefix used for naming. """ def __init__(self, weight, num_hidden, ndim=2, prefix: str = '') -> None: self.prefix = prefix self.weight = weight self.num_hidden = num_hidden self.scale = mx.sym.Variable("%swn_scale" % prefix, shape=tuple([num_hidden] + [1] * (ndim - 1)), init=mx.init.Constant(value=1.0)) def __call__(self, weight: Optional[mx.nd.NDArray] = None, scale: Optional[mx.nd.NDArray] = None) -> mx.sym.Symbol: """ Normalize each hidden dimension and scale afterwards :return: A weight normalized weight tensor. """ if weight is None and scale is None: return mx.sym.broadcast_mul(lhs=mx.sym.L2Normalization(self.weight, mode='instance'), rhs=self.scale, name="%swn_scale" % self.prefix) else: assert isinstance(weight, mx.nd.NDArray) assert isinstance(scale, mx.nd.NDArray) return mx.nd.broadcast_mul(lhs=mx.nd.L2Normalization(weight, mode='instance'), rhs=scale) class OutputLayer: """ Defines the output layer of Sockeye decoders. Supports weight tying and weight normalization. :param hidden_size: Decoder hidden size. :param vocab_size: Target vocabulary size. :param weight_normalization: Whether to apply weight normalization. :param prefix: Prefix used for naming. """ def __init__(self, hidden_size: int, vocab_size: int, weight: Optional[mx.sym.Symbol], weight_normalization: bool, prefix: str = C.DEFAULT_OUTPUT_LAYER_PREFIX) -> None: self.vocab_size = vocab_size self.prefix = prefix if weight is None: self.w = mx.sym.Variable("%sweight" % self.prefix, shape=(vocab_size, hidden_size)) else: self.w = weight self.weight_normalization = weight_normalization if weight_normalization: logger.info("Normalizing output layer weights.") self.weight_norm = WeightNormalization(self.w, num_hidden=vocab_size, ndim=2, prefix=self.prefix) self.w = self.weight_norm() self.b = mx.sym.Variable("%sbias" % self.prefix) def __call__(self, hidden: Union[mx.sym.Symbol, mx.nd.NDArray], weight: Optional[mx.nd.NDArray] = None, bias: Optional[mx.nd.NDArray] = None): """ Linear transformation to vocab size. Returns logits. :param hidden: Decoder representation for n elements. Shape: (n, self.num_hidden). :return: Logits. Shape(n, self.vocab_size). """ if isinstance(hidden, mx.sym.Symbol): # TODO dropout? return mx.sym.FullyConnected(data=hidden, num_hidden=self.vocab_size, weight=self.w, bias=self.b, flatten=False, name=C.LOGITS_NAME) # Equivalent NDArray implementation (requires passed weights/biases) assert isinstance(hidden, mx.nd.NDArray) utils.check_condition(weight is not None and bias is not None, "OutputLayer NDArray implementation requires passing weight and bias NDArrays.") return mx.nd.FullyConnected(data=hidden, num_hidden=bias.shape[0], weight=weight, bias=bias, flatten=False) def split_heads(x: mx.sym.Symbol, depth_per_head: int, heads: int) -> mx.sym.Symbol: """ Returns a symbol with head dimension folded into batch and depth divided by the number of heads. :param x: Symbol of shape (batch, length, depth). :param depth_per_head: Depth per head. :param heads: Number of heads. :return: Symbol of shape (batch * heads, length, depth_per_heads). """ # (batch, length, heads, depth_per_head) x = mx.sym.reshape(data=x, shape=(0, -1, heads, depth_per_head)) # (batch, heads, length, depth/heads) x = mx.sym.transpose(data=x, axes=(0, 2, 1, 3)) # (batch * heads, length, depth/heads) return mx.sym.reshape(data=x, shape=(-3, -1, depth_per_head)) def combine_heads(x: mx.sym.Symbol, depth_per_head: int, heads: int) -> mx.sym.Symbol: """ Returns a symbol with both batch & length, and head & depth dimensions combined. :param x: Symbol of shape (batch * heads, length, depth_per_head). :param depth_per_head: Depth per head. :param heads: Number of heads. :return: Symbol of shape (batch, length, depth). """ # (batch, heads, length, depth_per_head) x = mx.sym.reshape(data=x, shape=(-4, -1, heads, 0, depth_per_head)) # (batch, length, heads, depth_per_head) x = mx.sym.transpose(x, axes=(0, 2, 1, 3)) # (batch, length, depth) return mx.sym.reshape(x, shape=(-1, 0, depth_per_head * heads)) def broadcast_to_heads(x: mx.sym.Symbol, num_heads: int, ndim: int, fold_heads: bool = True) -> mx.sym.Symbol: """ Broadcasts batch-major input of shape (batch, d1 ... dn-1) to (batchheads, d1 ... dn-1). :param x: Batch-major input. Shape: (batch, d1 ... dn-1). :param num_heads: Number of heads. :param ndim: Number of dimensions in x. :param fold_heads: Whether to fold heads dimension into batch dimension. :return: Tensor with each sample repeated heads-many times. Shape: (batch heads, d1 ... dn-1) if fold_heads == True, (batch, heads, d1 ... dn-1) else. """ dims = [0] * (ndim - 1) # x: (batch, 1) x = mx.sym.expand_dims(x, axis=1) # x: (batch, heads, dims...) x = mx.sym.broadcast_to(x, shape=[0, num_heads] + dims) if fold_heads: # (batch * heads, dims...) return mx.sym.reshape(x, shape=[-3] + dims) else: # x: (batch, heads, dims...) return x def dot_attention(queries: mx.sym.Symbol, keys: mx.sym.Symbol, values: mx.sym.Symbol, lengths: Optional[mx.sym.Symbol] = None, dropout: float = 0.0, bias: Optional[mx.sym.Symbol] = None, prefix: Optional[str] = ''): """ Computes dot attention for a set of queries, keys, and values. :param queries: Attention queries. Shape: (n, lq, d). :param keys: Attention keys. Shape: (n, lk, d). :param values: Attention values. Shape: (n, lk, dv). :param lengths: Optional sequence lengths of the keys. Shape: (n,). :param dropout: Dropout probability. :param bias: Optional 3d bias tensor. :param prefix: Optional prefix :return: 'Context' vectors for each query. Shape: (n, lq, dv). """ utils.check_condition(lengths is not None or bias is not None, "Must provide either length or bias argument for masking") # (n, lq, lk) logits = mx.sym.batch_dot(lhs=queries, rhs=keys, transpose_b=True, name='%sdot' % prefix) if lengths is not None: # mask lk dimension # (lk, n, lq) logits = mx.sym.transpose(data=logits, axes=(2, 0, 1)) logits = mx.sym.SequenceMask(data=logits, use_sequence_length=True, sequence_length=lengths, value=C.LARGE_NEGATIVE_VALUE) # (n, lq, lk) logits = mx.sym.transpose(data=logits, axes=(1, 2, 0)) if bias is not None: logits = mx.sym.broadcast_add(logits, bias, name='%sbias_add' % prefix) probs = mx.sym.softmax(logits, axis=-1) probs = mx.sym.Dropout(probs, p=dropout) if dropout > 0.0 else probs # (n, lq, lk) x (n, lk, dv) -> (n, lq, dv) return mx.sym.batch_dot(lhs=probs, rhs=values, name='%scontexts' % prefix) class MultiHeadAttentionBase: """ Base class for Multi-head attention. :param prefix: Attention prefix. :param depth_att: Attention depth / number of hidden units. :param heads: Number of attention heads. :param depth_out: Output depth / number of output units. :param dropout: Dropout probability on attention scores """ def __init__(self, prefix: str, depth_att: int = 512, heads: int = 8, depth_out: int = 512, dropout: float = 0.0) -> None: self.prefix = prefix utils.check_condition(depth_att % heads == 0, "Number of heads (%d) must divide attention depth (%d)" % (heads, depth_att)) self.depth = depth_att self.heads = heads self.depth_out = depth_out self.dropout = dropout self.depth_per_head = self.depth // self.heads self.w_h2o = mx.sym.Variable("%sh2o_weight" % prefix) def _attend(self, queries: mx.sym.Symbol, keys: mx.sym.Symbol, values: mx.sym.Symbol, lengths: Optional[mx.sym.Symbol] = None, bias: Optional[mx.sym.Symbol] = None) -> mx.sym.Symbol: """ Returns context vectors of multi-head dot attention. :param queries: Query tensor. Shape: (batch_size, query_max_length, depth). :param keys: Keys. Shape: (batch_size, memory_max_length, depth). :param values: Values. Shape: (batch_size, memory_max_length, depth). :param lengths: Optional lengths of keys. Shape: (batch_size,). :param bias: Optional 3d bias. :return: Context vectors. Shape: (batch_size, query_max_length, output_depth). """ # scale by sqrt(depth_per_head) queries = queries * (self.depth_per_head ** -0.5) # (batchheads, length, depth/heads) queries = split_heads(queries, self.depth_per_head, self.heads) keys = split_heads(keys, self.depth_per_head, self.heads) values = split_heads(values, self.depth_per_head, self.heads) lengths = broadcast_to_heads(lengths, self.heads, ndim=1, fold_heads=True) if lengths is not None else lengths # (batchheads, query_max_length, depth_per_head) contexts = dot_attention(queries, keys, values, lengths=lengths, dropout=self.dropout, bias=bias, prefix=self.prefix) # (batch, query_max_length, depth) contexts = combine_heads(contexts, self.depth_per_head, self.heads) # contexts: (batch, query_max_length, output_depth) contexts = mx.sym.FullyConnected(data=contexts, weight=self.w_h2o, no_bias=True, num_hidden=self.depth_out, flatten=False) return contexts class MultiHeadSelfAttention(MultiHeadAttentionBase): """ Multi-head self-attention. Independent linear projections of inputs serve as queries, keys, and values for the attention. :param prefix: Attention prefix. :param depth_att: Attention depth / number of hidden units. :param heads: Number of attention heads. :param depth_out: Output depth / number of output units. :param dropout: Dropout probability on attention scores """ def __init__(self, prefix: str, depth_att: int = 512, heads: int = 8, depth_out: int = 512, dropout: float = 0.0) -> None: super().__init__(prefix, depth_att, heads, depth_out, dropout) self.w_i2h = mx.sym.Variable("%si2h_weight" % prefix) def __call__(self, inputs: mx.sym.Symbol, input_lengths: Optional[mx.sym.Symbol] = None, bias: Optional[mx.sym.Symbol] = None, cache: Optional[Dict[str, Optional[mx.sym.Symbol]]] = None) -> mx.sym.Symbol: """ Computes multi-head attention on a set of inputs, serving as queries, keys, and values. If sequence lengths are provided, they will be used to mask the attention scores. A bias mask may also be used to mask the attention scores. May also use a cache of previously computed inputs. Returns a symbol of shape (batch, max_length, output_depth). :param inputs: Input Data. Shape: (batch, max_length, input_depth). :param input_lengths: Optional lengths of inputs to mask attention scores. Shape: (batch, 1). :param bias: Optional 3d bias tensor to mask attention scores. :param cache: Optional dictionary of previously computed keys and values. :return: Symbol of shape (batch, max_length, output_depth). """ # combined: (batch, max_length, depth * 3) combined = mx.sym.FullyConnected(data=inputs, weight=self.w_i2h, no_bias=True, num_hidden=self.depth * 3, flatten=False, name="%sqkv_transform" % self.prefix) # split into query, keys and values # (batch, max_length, depth) # pylint: disable=unbalanced-tuple-unpacking queries, keys, values = mx.sym.split(data=combined, num_outputs=3, axis=2) if cache is not None: # append new keys & values to cache, update the cache keys = cache['k'] = keys if cache['k'] is None else mx.sym.concat(cache['k'], keys, dim=1) values = cache['v'] = values if cache['v'] is None else mx.sym.concat(cache['v'], values, dim=1) return self._attend(queries, keys, values, lengths=input_lengths, bias=bias) class MultiHeadAttention(MultiHeadAttentionBase): """ Multi-head attention layer for queries independent from keys/values. :param prefix: Attention prefix. :param depth_att: Attention depth / number of hidden units. :param heads: Number of attention heads. :param depth_out: Output depth / number of output units. :param dropout: Dropout probability on attention scores """ def __init__(self, prefix: str, depth_att: int = 512, heads: int = 8, depth_out: int = 512, dropout: float = 0.0) -> None: super().__init__(prefix, depth_att, heads, depth_out, dropout) self.w_q2h = mx.sym.Variable("%sq2h_weight" % prefix) self.w_k2h = mx.sym.Variable("%sk2h_weight" % prefix) self.w_v2h = mx.sym.Variable("%sv2h_weight" % prefix) def __call__(self, queries: mx.sym.Symbol, memory: mx.sym.Symbol, memory_lengths: Optional[mx.sym.Symbol] = None, bias: Optional[mx.sym.Symbol] = None) -> mx.sym.Symbol: """ Computes multi-head attention for queries given a memory tensor. If sequence lengths are provided, they will be used to mask the attention scores. A bias mask may also be used to mask the attention scores. Returns a symbol of shape (batch, max_length, output_depth). :param queries: Query tensor. Shape: (batch, query_max_length, input_depth). :param memory: Memory data to attend to. Shape: (batch, memory_max_length, input_depth). :param memory_lengths: Optional lengths of memory to mask attention scores. Shape: (batch, 1). :param bias: Optional 3d bias tensor to mask attention scores. :return: Symbol of shape (batch, query_seq_len, output_depth). """ # (batch, query_max_length, depth) queries = mx.sym.FullyConnected(data=queries, weight=self.w_q2h, no_bias=True, num_hidden=self.depth, flatten=False, name="%sq_transform" % self.prefix) # (batch, memory_max_length, depth) keys = mx.sym.FullyConnected(data=memory, weight=self.w_k2h, no_bias=True, num_hidden=self.depth, flatten=False, name="%sk_transform" % self.prefix) # (batch, memory_max_length, depth) values = mx.sym.FullyConnected(data=memory, weight=self.w_v2h, no_bias=True, num_hidden=self.depth, flatten=False, name="%sv_transform" % self.prefix) return self._attend(queries, keys, values, bias=bias, lengths=memory_lengths) class ProjectedDotAttention: """ Dot attention layer for queries independent from keys/values. :param prefix: Attention prefix. :param num_hidden: Attention depth / number of hidden units. """ def __init__(self, prefix: str, num_hidden) -> None: self.prefix = prefix self.num_hidden = num_hidden self.w_q2h = mx.sym.Variable("%sq2h_weight" % prefix) self.b_q2h = mx.sym.Variable("%sq2h_bias" % prefix) self.w_kv2h = mx.sym.Variable("%skv2h_weight" % prefix) self.b_kv2h = mx.sym.Variable("%skv2h_bias" % prefix) def __call__(self, queries: mx.sym.Symbol, memory: mx.sym.Symbol, memory_lengths: mx.sym.Symbol) -> mx.sym.Symbol: """ Apply project, apply dot attention and return new context vectors. :param queries: Symbol of shape (batch, queries_max_length, input_num_hidden). :param memory: Symbol of shape (batch, memory_max_length, input_num_hidden). :param memory_lengths: Symbol of shape (batch, 1). :return: Symbol of shape (batch, queries_max_length, num_hidden). """ # (batch, memory_max_length, num_hidden * 2) combined = mx.sym.FullyConnected(data=memory, weight=self.w_kv2h, bias=self.b_kv2h, num_hidden=self.num_hidden * 2, flatten=False, name="%skv_transform" % self.prefix) # split into keys and values # pylint: disable=unbalanced-tuple-unpacking keys, values = mx.sym.split(data=combined, num_outputs=2, axis=2) # (batch, queries_max_length, num_hidden) queries = mx.sym.FullyConnected(data=queries, weight=self.w_q2h, bias=self.b_q2h, num_hidden=self.num_hidden, flatten=False, name="%sq_transform" % self.prefix) # scale by sqrt(num_hidden) queries = queries * (self.num_hidden ** -0.5) # (batch, queries_max_length, num_hidden) contexts = dot_attention(queries, keys, values, memory_lengths) return contexts class PlainDotAttention: """ Dot attention layer for queries independent from keys/values. """ def __call__(self, queries: mx.sym.Symbol, memory: mx.sym.Symbol, memory_lengths: mx.sym.Symbol) -> mx.sym.Symbol: """ Returns a symbol of shape (batch, max_length, output_depth). :param queries: Symbol of shape (batch, queries_max_length, input_depth). :param memory: Symbol of shape (batch, memory_max_length, input_depth). :param memory_lengths: Symbol of shape (batch, 1). :return: Symbol of shape (batch, queries_max_length, output_depth). """ # (batchheads, queries_max_length, depth_per_head) contexts = dot_attention(queries, memory, memory, memory_lengths) return contexts class PositionalEncodings(mx.operator.CustomOp): """ Returns a symbol of shape (1, max_seq_len, num_embed) with positional encodings as in Vaswani et al, 2017. :param length: Maximum sequence length. :param depth: Embedding size. """ def __init__(self, length: int, depth: int) -> None: super().__init__() self.encodings = self.get_encodings(length, depth) @staticmethod def get_encodings(length, depth) -> np.ndarray: utils.check_condition(depth % 2 == 0, "Positional embeddings require an even embedding size it " "is however %d." % depth) # (1, depth) channels = np.arange(depth // 2).reshape((1, -1)) # (length, 1) positions = np.arange(0, length).reshape((-1, 1)) scaled_positions = positions / np.power(10000, (2 channels) / depth) # sinusoids: sin = np.sin(scaled_positions) # cosines: cos = np.cos(scaled_positions) # interleave: (1, length, num_embed) encodings = np.hstack([sin, cos]).reshape(1, length, depth) return encodings def forward(self, is_train, req, in_data, out_data, aux): self.assign(out_data[0], req[0], self.encodings) def backward(self, req, out_grad, in_data, out_data, in_grad, aux): pass @mx.operator.register("positional_encodings") class PositionalEncodingsProp(mx.operator.CustomOpProp): def __init__(self, length: str, depth: str) -> None: super().__init__() self.length = int(length) self.depth = int(depth) def list_arguments(self): return [] def list_outputs(self): return ['output'] def infer_shape(self, in_shape): return [], [(1, self.length, self.depth)], [] def infer_type(self, in_type): return [], [np.float32], [] def create_operator(self, ctx, shapes, dtypes): return PositionalEncodings(length=self.length, depth=self.depth)	artemsok/sockeye	sockeye/layers.py	Python	apache-2.0	28,551	[ "Gaussian" ]	9a3f8675dfffca44bf2ab512c14ef444a2c07019fbbd675c1ad0352c1412c641
import copy import hyperchamber as hc import inspect import math import operator import os import re from functools import reduce import pyparsing import hypergan import torch import torch.nn as nn from .gan_component import GANComponent from hypergan.gan_component import ValidationException from hypergan.layer_shape import LayerShape from hypergan.distributions.base_distribution import BaseDistribution from hypergan.modules.adaptive_instance_norm import AdaptiveInstanceNorm from hypergan.modules.attention import Attention from hypergan.modules.const import Const from hypergan.modules.learned_noise import LearnedNoise from hypergan.modules.modulated_conv2d import ModulatedConv2d, Blur, EqualLinear from hypergan.modules.multi_head_attention import MultiHeadAttention from hypergan.modules.reshape import Reshape from hypergan.modules.no_op import NoOp from hypergan.modules.scaled_conv2d import ScaledConv2d from hypergan.modules.variational import Variational from hypergan.modules.pixel_norm import PixelNorm import torchvision import hypergan as hg class ConfigurableComponent(GANComponent): custom_layers = {} def __init__(self, gan, config, input=None, input_shape=None, context_shapes = {}, input_is_latent=False): self.current_size = LayerShape(gan.channels(), gan.height(), gan.width()) if isinstance(input, GANComponent): if hasattr(input, 'current_height'): self.current_size = LayerShape(input.current_channels, input.current_height, input.current_width) elif hasattr(input, 'current_channels'): self.current_size = LayerShape(input.current_channels) else: self.current_size = input.current_size if input_shape is not None: self.current_size = LayerShape(input_shape) self.layers = [] self.layer_shapes = [] self.untrainable_parameters = set() self.layer_output_sizes = {} self.nn_layers = [] self.layer_options = {} self.parsed_layers = [] self.parser = hypergan.parser.Parser() self.context_shapes = context_shapes for key, shape in self.context_shapes.items(): self.layer_output_sizes[key] = shape if isinstance(input, BaseDistribution): self.is_latent = True else: self.is_latent = False self._latent_parameters = [] self.layer_ops = {self.activations(), ConfigurableComponent.custom_layers, "add": hg.layers.Add, "cat": hg.layers.Cat, "channel_attention": hg.layers.ChannelAttention, "efficient_attention": hg.layers.EfficientAttention, "ez_norm": hg.layers.EzNorm, "layer": hg.layers.Layer, "minibatch": hg.layers.Minibatch, "mul": hg.layers.Mul, "multi_head_attention2": hg.layers.MultiHeadAttention, #TODO rename "noise": hg.layers.Noise, "pixel_shuffle": hg.layers.PixelShuffle, "residual": hg.layers.Residual, "resizable_stack": hg.layers.ResizableStack, "segment_softmax": hg.layers.SegmentSoftmax, "upsample": hg.layers.Upsample, #easy to convert "dropout": self.layer_dropout, "identity": self.layer_identity, "flatten": self.layer_flatten, "pretrained": self.layer_pretrained, "avg_pool": self.layer_avg_pool,#TODO handle dims "pad": self.layer_pad, "reshape": self.layer_reshape, "split": self.layer_split, #hard to convert "adaptive_avg_pool": self.layer_adaptive_avg_pool, "adaptive_avg_pool1d": self.layer_adaptive_avg_pool1d, "adaptive_avg_pool3d": self.layer_adaptive_avg_pool3d, "adaptive_instance_norm": self.layer_adaptive_instance_norm, "attention": self.layer_attention, "batch_norm": self.layer_batch_norm, "batch_norm1d": self.layer_batch_norm1d, "blur": self.layer_blur, "const": self.layer_const, "conv": self.layer_conv, "conv1d": self.layer_conv1d, "conv2d": self.layer_conv2d, "conv3d": self.layer_conv3d, "deconv": self.layer_deconv, "equal_linear": self.layer_equal_linear, "instance_norm": self.layer_instance_norm, "instance_norm1d": self.layer_instance_norm1d, "instance_norm3d": self.layer_instance_norm3d, "latent": self.layer_latent, "layer_norm": self.layer_norm, "learned_noise": self.layer_learned_noise, "linear": self.layer_linear, "modulated_conv2d": self.layer_modulated_conv2d, "multi_head_attention": self.layer_multi_head_attention, "pixel_norm": self.layer_pixel_norm, "resize_conv": self.layer_resize_conv, "resize_conv2d": self.layer_resize_conv2d, "resize_conv1d": self.layer_resize_conv1d, "scaled_conv2d": self.layer_scaled_conv2d, "subpixel": self.layer_subpixel, "vae": self.layer_vae #"linear_attention": hg.layers.LinearAttention, #"make2d": self.layer_make2d, #"make3d": self.layer_make3d, # "crop": self.layer_crop, # "dropout": self.layer_dropout, # "noise": self.layer_noise, #TODO #"attention": self.layer_attention, #TODO #"const": self.layer_const, #TODO #"gram_matrix": self.layer_gram_matrix, #TODO #"image_statistics": self.layer_image_statistics, #TODO #"knowledge_base": self.layer_knowledge_base, #TODO #"layer_norm": self.layer_layer_norm,#TODO #"mask": self.layer_mask,#TODO #"match_support": self.layer_match_support,#TODO #"pixel_norm": self.layer_pixel_norm,#TODO #"progressive_replace": self.layer_progressive_replace,#TODO #"reduce_sum": self.layer_reduce_sum,#TODO might want to just do "reduce sum" instead #"relational": self.layer_relational,#TODO #"unpool": self.layer_unpool, #TODO https://arxiv.org/abs/1505.04366 #"squash": self.layer_squash, #TODO #"tensorflowcv": self.layer_tensorflowcv, #TODO layer torchvision instead? #"turing_test": self.layer_turing_test, #TODO #"two_sample_stack": self.layer_two_sample_stack, #TODO #"zeros": self.layer_zeros, #TODO #"zeros_like": self.layer_zeros_like #TODO } self.named_layers = {} if not hasattr(gan, "named_layers"): gan.named_layers = {} self.subnets = hc.Config(hc.Config(config).subnets or {}) GANComponent.__init__(self, gan, config) self.device = self.config.device or "cuda:0" self.const_two = torch.Tensor([2.0]).float()[0].cuda() self.const_one = torch.Tensor([1.0]).float()[0].cuda() def required(self): return "layers".split() def layer(self, name): if name in self.gan.named_layers: return self.gan.named_layers[name] if name in self.named_layers: return self.named_layers[name] return None def create(self): for layer in self.config.layers: net = self.create_parsed_layer(layer) self.nn_layers.append(net) self.net = nn.ModuleList(self.nn_layers) def create_parsed_layer(self, layer_defn): config = self.config parsed, layer = self.parse_layer(layer_defn) self.parsed_layers.append(parsed) self.layer_shapes.append(self.current_size) return layer def parse_layer(self, layer_defn): print("Parsing layer:", layer_defn) parsed = self.parser.parse_string(layer_defn) parsed.parsed_options = hc.Config(parsed.options) parsed.layer_defn = layer_defn print("Parsed layer:", parsed.to_list()) layer = self.build_layer(parsed.layer_name, parsed.args, parsed.parsed_options) return parsed, layer def build_layer(self, op, args, options): if self.layer_ops[op]: try: is_hg_layer = issubclass(self.layer_ops[op], hg.Layer) except TypeError: is_hg_layer = False if is_hg_layer: net = self.layer_ops[op](self, args, options) self.current_size = net.output_size() if self.is_latent: self._latent_parameters += net.latent_parameters() self.is_latent = False elif isinstance(self.layer_ops[op], nn.Module): net = self.layer_ops[op] else: net = self.layer_ops[op](None, args, options) if 'name' in options: self.set_layer(options['name'], net) if options.trainable == False: self.untrainable_parameters = self.untrainable_parameters.union(set(net.parameters())) return net else: print("ConfigurableComponent: Op not defined", op) def set_layer(self, name, net): self.gan.named_layers[name] = net self.named_layers[name] = net self.layer_output_sizes[name] = self.current_size def activations(self): return { "celu": nn.CELU(), "gelu": nn.GELU(), "lrelu": nn.LeakyReLU(0.2), "prelu": nn.PReLU(), "relu": nn.ReLU(), "relu6": nn.ReLU6(), "selu": nn.SELU(), "sigmoid": nn.Sigmoid(), "softplus": nn.Softplus(), "softshrink": nn.Softshrink(), "softsign": nn.Softsign(), "hardsigmoid": nn.Hardsigmoid(), "hardtanh": nn.Hardtanh(), "tanh": nn.Tanh(), "tanhshrink": nn.Tanhshrink() } def layer_dropout(self, net, args, options): return nn.Dropout2d(float(args[0])) def layer_identity(self, net, args, options): return NoOp() def layer_equal_linear(self, net, args, options): lr_mul = 1 if options.lr_mul is not None: lr_mul = options.lr_mul result = EqualLinear(options.input_size or self.current_size.size(), args[0], lr_mul=lr_mul) self.current_size = LayerShape(args[0]) return result def get_device(self): return torch.device(self.device or "cuda:0") def get_same_padding(self, input_rows, filter_rows, stride, dilation): out_rows = (input_rows + stride - 1) // stride return max(0, (out_rows - 1) stride + (filter_rows - 1) * dilation + 1 - input_rows) // 2 def layer_const(self, net, args, options): return Const(self.current_size.dims) #from https://discuss.pytorch.org/t/utility-function-for-calculating-the-shape-of-a-conv-output/11173/3 def conv_output_shape(self, h_w, kernel_size=1, stride=1, pad=0, dilation=1): if type(kernel_size) is not tuple: kernel_size = (kernel_size, kernel_size) h = math.floor( ((h_w[0] + (2 pad) - ( dilation * (kernel_size[0] - 1) ) - 1 )/ stride) + 1) w = math.floor( ((h_w[1] + (2 * pad) - ( dilation * (kernel_size[1] - 1) ) - 1 )/ stride) + 1) return h, w def layer_conv(self, net, args, options): return self.layer_conv2d(net, args, options) def layer_conv2d(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels options = hc.Config(options) stride = 1 if options.stride is not None: stride = options.stride filter = 3 if options.filter is not None: filter = options.filter padding = 1 if options.padding is not None: padding = options.padding dilation = 1 layer = nn.Conv2d(options.input_channels or self.current_size.channels, channels, filter, stride, padding = (padding, padding)) self.nn_init(layer, options.initializer) h, w = self.conv_output_shape((self.current_size.height, self.current_size.width), filter, stride, padding, dilation) self.current_size = LayerShape(channels, h, w) return layer def layer_conv1d(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels print("Options:", options) options = hc.Config(options) stride = options.stride or 1 fltr = options.filter or 3 dilation = 1 padding = 1 if options.padding is not None: padding = options.padding layers = [nn.Conv1d(options.input_channels or self.current_size.channels, channels, fltr, stride, padding = padding)] self.nn_init(layers[-1], options.initializer) h, _ = self.conv_output_shape((self.current_size.height, self.current_size.height), options.filter or 3, stride, padding, 1) self.current_size = LayerShape(channels, h) return nn.Sequential(layers) def layer_conv3d(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels options = hc.Config(options) stride = options.stride or 1 fltr = options.filter or 3 dilation = 1 padding = options.padding or 1#self.get_same_padding(self.current_width, self.current_width, stride, dilation) if options.padding0: padding = [options.padding0, padding, padding] if options.stride0: stride = [options.stride0, stride, stride] else: stride = [stride, stride, stride] layers = [nn.Conv3d(options.input_channels or self.current_size.channels, channels, fltr, stride, padding = padding)] self.nn_init(layer, options.initializer) self.current_size = LayerShape(frames, channels, self.current_size.height // stride[1], self.current_size.width // stride[2]) #TODO this doesn't work, what is frames? Also chw calculation like conv2d return nn.Sequential(layers) def layer_linear(self, net, args, options): options = hc.Config(options) shape = [int(x) for x in str(args[0]).split("")] bias = True if options.bias == False: bias = False output_size = 1 for dim in shape: output_size = dim layers = [] if len(self.current_size.dims) != 1: layers += [nn.Flatten()] layers += [nn.Linear(options.input_size or self.current_size.size(), output_size, bias=bias)] self.nn_init(layers[-1], options.initializer) self.current_size = LayerShape(list(reversed(shape))) if len(shape) != 1: layers.append(Reshape(self.current_size.dims)) if self.is_latent: self._latent_parameters += [layers[0].weight] self.is_latent = False return nn.Sequential(layers) def layer_modulated_conv2d(self, net, args, options): channels = self.current_size.channels if len(args) > 0: channels = args[0] method = "conv" if len(args) > 1: method = args[1] upsample = method == "upsample" downsample = method == "downsample" demodulate = True if options.demodulate == False: demodulate = False filter = 3 if options.filter: filter = options.filter lr_mul = 1.0 if options.lr_mul: lr_mul = options.lr_mul input_channels = self.current_size.channels if options.input_channels: input_channels = options.input_channels result = ModulatedConv2d(input_channels, channels, filter, self.layer_output_sizes['w'].size(), upsample=upsample, demodulate=demodulate, downsample=downsample, lr_mul=lr_mul) if upsample: self.current_size = LayerShape(channels, self.current_size.height 2, self.current_size.width * 2) elif downsample: self.current_size = LayerShape(channels, self.current_size.height // 2, self.current_size.width // 2) return result def layer_blur(self, net, args, options): blur_kernel=[1, 3, 3, 1] kernel_size=3 factor = 2 p = (len(blur_kernel) - factor) - (kernel_size - 1) pad0 = (p + 1) // 2 + factor - 1 pad1 = p // 2 + 1 return Blur(blur_kernel, pad=(pad0, pad1), upsample_factor=factor) def layer_reshape(self, net, args, options): dims_args = [int(x) for x in args[0].split("")] dims = list(reversed(dims_args)) self.current_size = LayerShape(dims) return Reshape(dims) def layer_adaptive_avg_pool(self, net, args, options): self.current_size = LayerShape(self.current_size.channels, self.current_size.height // 2, self.current_size.width // 2) return nn.AdaptiveAvgPool2d([self.current_size.height, self.current_size.width]) def layer_adaptive_avg_pool1d (self, net, args, options): self.current_size = LayerShape(self.current_size.channels, self.current_size.height // 2) return nn.AdaptiveAvgPool1d(self.current_size.height) def layer_avg_pool(self, net, args, options): self.current_size = LayerShape(self.current_size.channels, self.current_size.height // 2, self.current_size.width // 2) return nn.AvgPool2d(2, 2) def layer_adaptive_avg_pool3d(self, net, args, options): frames = 4 #TODO self.current_size = LayerShape(frames, self.current_size.channels, self.current_size.height // 2, self.current_size.width // 2) return nn.AdaptiveAvgPool3d([self.current_size.frames, self.current_size.height, self.current_size.width]) #TODO looks wrong def layer_instance_norm(self, net, args, options): options = hc.Config(options) affine = True if options.affine == False: affine = False return nn.InstanceNorm2d(self.current_size.channels, affine=affine) def layer_instance_norm1d(self, net, args, options): options = hc.Config(options) affine = True if options.affine == False: affine = False return nn.InstanceNorm1d(self.current_size.channels, affine=affine) def layer_instance_norm3d(self, net, args, options): options = hc.Config(options) affine = True if options.affine == False: affine = False return nn.InstanceNorm3d(self.current_size.channels, affine=affine) def layer_batch_norm(self, net, args, options): return nn.BatchNorm2d(self.current_size.channels) def layer_batch_norm1d(self, net, args, options): return nn.BatchNorm1d(self.current_size.size()) def get_conv_options(self, config, options): stride = options.stride or self.ops.config_option("stride", [1,1]) fltr = options.filter or self.ops.config_option("filter", [3,3]) avg_pool = options.avg_pool or self.ops.config_option("avg_pool", [1,1]) if type(stride) != type([]): stride = [stride, stride] if type(avg_pool) != type([]): avg_pool = [avg_pool, avg_pool] if type(fltr) != type([]): fltr = [fltr, fltr] return stride, fltr, avg_pool def layer_deconv(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels options = hc.Config(options) filter = 4 #TODO if options.filter: filter = options.filter stride = 2 if options.stride: stride = options.stride padding = 1 if options.padding: padding = options.padding layer = nn.ConvTranspose2d(options.input_channels or self.current_size.channels, channels, filter, stride, padding) self.nn_init(layer, options.initializer) self.current_size = LayerShape(channels, self.current_size.height 2, self.current_size.width * 2) return layer def layer_pad(self, net, args, options): options = hc.Config(options) return nn.ZeroPad2d((args[0], args[1], args[2], args[3])) def layer_pixel_norm(self, net, args, options): return PixelNorm() def layer_pretrained(self, net, args, options): model = getattr(torchvision.models, args[0])(pretrained=True) model.train(True) if options.layer: layers = list(model.children())[:options.layer] if options.sublayer: layers[-1] = nn.Sequential(layers[-1][:options.sublayer]) else: layers = [model] print("List of pretrained layers:", layers) raise ValidationException("layer=-1 required for pretrained, sublayer=-1 optional. Layers outputted above.") return nn.Sequential(layers) def layer_resize_conv(self, net, args, options): return self.layer_resize_conv2d(net, args, options) def layer_resize_conv2d(self, net, args, options): options = hc.Config(options) channels = args[0] w = options.w or self.current_size.width * 2 h = options.h or self.current_size.height * 2 layers = [nn.Upsample((h, w), mode="bilinear"), nn.Conv2d(options.input_channels or self.current_size.channels, channels, options.filter or 3, 1, 1)] self.nn_init(layers[-1], options.initializer) self.current_size = LayerShape(channels, h, w) return nn.Sequential(layers) def layer_resize_conv1d(self, net, args, options): options = hc.Config(options) channels = args[0] h = options.h or self.current_size.height 2 padding = 1 if options.padding is not None: padding = options.padding layers = [nn.Upsample((h)), nn.Conv1d(options.input_channels or self.current_size.channels, channels, options.filter or 3, 1, padding=padding)] self.nn_init(layers[-1], options.initializer) h, _ = self.conv_output_shape((h, h), options.filter or 3, 1, padding, 1) self.current_size = LayerShape(channels, h) return nn.Sequential(layers) def layer_scaled_conv2d(self, net, args, options): channels = self.current_size.channels if len(args) > 0: channels = args[0] method = "conv" if len(args) > 1: method = args[1] upsample = method == "upsample" downsample = method == "downsample" demodulate = True if options.demodulate == False: demodulate = False filter = 3 if options.filter: filter = options.filter lr_mul = 1.0 if options.lr_mul: lr_mul = options.lr_mul input_channels = self.current_size.channels if options.input_channels: input_channels = options.input_channels result = ScaledConv2d(input_channels, channels, filter, 0, upsample=upsample, demodulate=demodulate, downsample=downsample, lr_mul=lr_mul) self.nn_init(result, options.initializer) if upsample: self.current_size = LayerShape(channels, self.current_size.height 2, self.current_size.width * 2) else: self.current_size = LayerShape(channels, self.current_size.height - 2, self.current_size.width - 2) return result def layer_split(self, net, args, options): options = hc.Config(options) split_size = args[0] select = args[1] dim = -1 if options.dim: dim = options.dim #TODO better validation #TODO increase dim options if dim == -1: dims = list(self.current_size.dims).copy() dims[0] = split_size if (select + 1) * split_size > self.current_size.channels: dims[0] = self.current_size.channels % split_size self.current_size = LayerShape(dims) return NoOp() def layer_subpixel(self, net, args, options): options = hc.Config(options) channels = args[0] layers = [nn.Conv2d(options.input_channels or self.current_size.channels, channels4, options.filter or 3, 1, 1), nn.PixelShuffle(2)] self.nn_init(layers[0], options.initializer) self.current_size = LayerShape(channels, self.current_size.height * 2, self.current_size.width * 2) return nn.Sequential(layers) def layer_latent(self, net, args, options): self.current_size = LayerShape(self.gan.latent.current_input_size) self.is_latent = True return NoOp() def layer_linformer(self, net, args, options): model = Linformer( input_size = self.current_size.size(), channels = self.current_size.height # TODO wtf ) return model def layer_vae(self, net, args, options): self.vae = Variational(self.current_size.channels) return self.vae def layer_multi_head_attention(self, net, args, options): output_size = self.current_size.size() if len(args) > 0: output_size = args[0] layer = MultiHeadAttention(self.current_size.size(), output_size, heads=options.heads or 4) self.current_size = LayerShape(output_size) self.nn_init(layer.o, options.initializer) self.nn_init(layer.h, options.initializer) self.nn_init(layer.g, options.initializer) self.nn_init(layer.f, options.initializer) if self.is_latent: self._latent_parameters += [layer.h.weight, layer.g.weight, layer.f.weight] self.is_latent = False return layer def layer_attention(self, net, args, options): layer = Attention(self.current_size.channels) self.nn_init(layer.v, options.initializer) self.nn_init(layer.h, options.initializer) self.nn_init(layer.g, options.initializer) self.nn_init(layer.f, options.initializer) return layer def layer_norm(self, net, args, options): affine = True if options.affine == False: affine = False return nn.LayerNorm(self.current_size.dims, elementwise_affine=affine) def layer_learned_noise(self, net, args, options): return LearnedNoise(([self.gan.batch_size(), self.current_size.dims])) def layer_adaptive_instance_norm(self, net, args, options): return AdaptiveInstanceNorm(self.layer_output_sizes['w'].size(), self.current_size.channels, equal_linear=options.equal_linear) def layer_flatten(self, net, args, options): self.current_size = LayerShape(self.current_size.size()) return nn.Flatten() def layer_zeros_like(self, net, args, options): return Zeros(self.gan.latent.sample().shape) def nn_init(self, layer, initializer_option): if initializer_option is None: return if type(initializer_option) == pyparsing.ParseResults and type(initializer_option[0]) == hypergan.parser.Pattern: args = [initializer_option[0].layer_name] + initializer_option[0].args options = hc.Config(initializer_option[0].options) else: args = [initializer_option] options = hc.Config({}) layer_data = layer.weight.data if args[0] == "uniform": a = float(args[1]) b = float(args[2]) nn.init.uniform_(layer_data, a, b) elif args[0] == "normal": mean = float(args[1]) std = float(args[2]) nn.init.normal_(layer_data, mean, std) elif args[0] == "constant": val = float(args[1]) nn.init.constant_(layer_data, val) elif args[0] == "ones": nn.init.ones_(layer_data) elif args[0] == "zeros": nn.init.zeros_(layer_data) elif args[0] == "eye": nn.init.eye_(layer_data) elif args[0] == "dirac": nn.init.dirac_(layer_data) elif args[0] == "xavier_uniform": gain = nn.init.calculate_gain(options.gain or "relu") nn.init.xavier_uniform_(layer_data, gain=gain) elif args[0] == "xavier_normal": gain = nn.init.calculate_gain(options.gain or "relu") nn.init.xavier_normal_(layer_data, gain=gain) elif args[0] == "kaiming_uniform": a = 0 #TODO wrong nn.init.kaiming_uniform_(layer_data, mode=(options.mode or "fan_in"), nonlinearity=options.gain or "relu") elif args[0] == "kaiming_normal": a = 0 #TODO wrong nn.init.kaiming_normal_(layer_data, mode=(options.mode or "fan_in"), nonlinearity=options.gain or "relu") elif args[0] == "orthogonal": if "gain" in options: gain = nn.init.calculate_gain(options["gain"]) else: gain = 1 nn.init.orthogonal_(layer_data, gain=gain) else: print("Warning: No initializer found for " + args[0]) if "gain" in options: layer_data.mul_(nn.init.calculate_gain(options["gain"])) return NoOp() def forward(self, input, context={}): if self.get_device().index != input.device.index: input = input.to(self.get_device()) for module, parsed, layer_shape in zip(self.net, self.parsed_layers, self.layer_shapes): try: options = parsed.parsed_options args = parsed.args layer_name = parsed.layer_name name = options.name if isinstance(module, hg.Layer): input = module(input, context) elif layer_name == "adaptive_instance_norm": input = module(input, context['w']) elif layer_name == "ez_norm": input = module(input, context['w']) elif layer_name == "split": input = torch.split(input, args[0], options.dim or -1)[args[1]] elif layer_name == "latent": input = self.gan.latent.z#sample() elif layer_name == "modulated_conv2d": input = module(input, context['w']) elif layer_name == "pretrained": in_zero_one = (input + self.const_one) / self.const_two mean = torch.as_tensor([0.485, 0.456, 0.406], device='cuda:0').view(1, 3, 1, 1) std = torch.as_tensor([0.229, 0.224, 0.225], device='cuda:0').view(1, 3, 1, 1) input = module(input.clone().sub_(mean).div_(std)) else: input = module(input) if self.gan.steps == 0: size = LayerShape(list(input.shape[1:])) if size.squeeze_dims() != layer_shape.squeeze_dims(): print("Error: Size error on", layer_name) print("Error: Expected output size", layer_shape.dims) print("Error: Actual output size", size.dims) raise "Layer size error, cannot continue" else: pass if name is not None: context[name] = input except: raise ValidationException("Error on " + parsed.layer_defn + " - input size " + ",".join([str(x) for x in input.shape])) self.sample = input return input def latent_parameters(self): return self._latent_parameters def set_trainable(self, flag): for p in (set(list(self.parameters())) - self.untrainable_parameters): p.requires_grad = flag def layer_shape(self): return self.current_size def __getstate__(self): obj = dict(self.__dict__) del obj["parser"] return obj def __setstate__(self, d): self.__dict__ = d self.parser = hypergan.parser.Parser()	255BITS/HyperGAN	hypergan/configurable_component.py	Python	mit	32,342	[ "DIRAC" ]	57f453c1a9b980ac591391d18e935227cc73f49512d324d5cb70ff70a6a0272e
# ---------------------------------------------------------------------------------------------------- # # Copyright (c) 2020, Oracle and/or its affiliates. All rights reserved. # DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. # # This code is free software; you can redistribute it and/or modify it # under the terms of the GNU General Public License version 2 only, as # published by the Free Software Foundation. # # This code is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or # FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License # version 2 for more details (a copy is included in the LICENSE file that # accompanied this code). # # You should have received a copy of the GNU General Public License version # 2 along with this work; if not, write to the Free Software Foundation, # Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. # # Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA # or visit www.oracle.com if you need additional information or have any # questions. # # ---------------------------------------------------------------------------------------------------- import json import os import re import subprocess from multiprocessing import Lock import mx _bear_version_regex = re.compile(r"bear ([0-9]+).([0-9]+).([0-9]+)", re.IGNORECASE) _bear_version = '<uninitialized>' def _get_bear_version(): global _bear_version if _bear_version == '<uninitialized>': try: output = mx._check_output_str(['bear', '--version'], stderr=subprocess.STDOUT) except OSError: output = '' m = _bear_version_regex.search(output) if m: _bear_version = int(m.group(1)) else: mx.warn("Could not find bear, will not produce compilation database for make projects.") _bear_version = None return _bear_version def gmake_with_bear(out=None, append=False, context=None): v = _get_bear_version() if v is None: return [mx.gmake_cmd(context=context)] else: ret = ['bear'] if append: ret.append('--append' if v >= 3 else '-a') if out is not None: ret.append('--output' if v >= 3 else '-o') ret.append(out) if v >= 3: ret.append('--') ret.append(mx.gmake_cmd(context=context)) return ret _compdb_path = None _compdb_lock = None def _default_compdb_path(): suite = mx.primary_suite() if suite is None: # no primary suite, don't try to enable compdb return None if suite.vc_dir: return os.path.join(os.path.dirname(suite.vc_dir), 'compile_commands.json') else: return os.path.join(suite.dir, 'compile_commands.json') def init(): global _compdb_path global _compdb_lock o = mx.get_opts().compdb if o is None: o = mx.get_env('MX_COMPDB') if o is not None and o != 'none': _compdb_lock = Lock() if o == 'default': _compdb_path = _default_compdb_path() else: _compdb_path = os.path.abspath(o) def enabled(): return _compdb_path is not None def gmake_with_compdb_cmd(context=None): if enabled(): return gmake_with_bear(append=True, context=context) else: return [mx.gmake_cmd(context=context)] class Compdb: def __init__(self): self.content = {} def __enter__(self): _compdb_lock.acquire() if os.path.exists(_compdb_path): self.mergeFile(_compdb_path) return self def __exit__(self, args): with open(_compdb_path, 'w') as f: json.dump(list(self.content.values()), f, indent=4) _compdb_lock.release() def merge(self, data): for item in data: key = item['file'] if not os.path.isabs(key): key = os.path.normpath(os.path.join(item['directory'], item['file'])) self.content[item['file']] = item def mergeString(self, string): try: self.merge(json.loads(string)) except json.JSONDecodeError: mx.warn("Error decoding JSON compilation database. Ignoring.") def mergeFile(self, path): with open(path, 'r') as f: try: self.merge(json.load(f)) except json.JSONDecodeError: mx.warn("Error decoding JSON compilation database from '%s'. Ignoring." % path) class CompdbCapture: def __init__(self, suite): self.data = "" def __call__(self, data): self.data += data def __enter__(self): if enabled(): return self else: return None def __exit__(self, args): if enabled(): with Compdb() as db: db.mergeString(self.data) def merge_compdb(subject, path): if enabled(): with Compdb() as db: inFile = os.path.join(path, 'compile_commands.json') if os.path.exists(inFile): db.mergeFile(inFile) else: mx.warn("JSON compilation database for %s not found (expected at %s)." % (subject, inFile))	graalvm/mx	mx_compdb.py	Python	gpl-2.0	5,256	[ "VisIt" ]	318b30996a0bfb1c7510967f8cdff0925a84f2be3ee143d009c6bec87092ec4a
"""Rewrite assertion AST to produce nice error messages""" import ast import _ast import errno import itertools import imp import marshal import os import re import struct import sys import types from fnmatch import fnmatch import py from _pytest.assertion import util # pytest caches rewritten pycs in __pycache__. if hasattr(imp, "get_tag"): PYTEST_TAG = imp.get_tag() + "-PYTEST" else: if hasattr(sys, "pypy_version_info"): impl = "pypy" elif sys.platform == "java": impl = "jython" else: impl = "cpython" ver = sys.version_info PYTEST_TAG = "%s-%s%s-PYTEST" % (impl, ver[0], ver[1]) del ver, impl PYC_EXT = ".py" + (__debug__ and "c" or "o") PYC_TAIL = "." + PYTEST_TAG + PYC_EXT REWRITE_NEWLINES = sys.version_info[:2] != (2, 7) and sys.version_info < (3, 2) ASCII_IS_DEFAULT_ENCODING = sys.version_info[0] < 3 if sys.version_info >= (3,5): ast_Call = ast.Call else: ast_Call = lambda a,b,c: ast.Call(a, b, c, None, None) class AssertionRewritingHook(object): """PEP302 Import hook which rewrites asserts.""" def __init__(self, config): self.config = config self.fnpats = config.getini("python_files") self.session = None self.modules = {} self._rewritten_names = set() self._register_with_pkg_resources() self._must_rewrite = set() def set_session(self, session): self.session = session def find_module(self, name, path=None): state = self.config._assertstate state.trace("find_module called for: %s" % name) names = name.rsplit(".", 1) lastname = names[-1] pth = None if path is not None: # Starting with Python 3.3, path is a _NamespacePath(), which # causes problems if not converted to list. path = list(path) if len(path) == 1: pth = path[0] if pth is None: try: fd, fn, desc = imp.find_module(lastname, path) except ImportError: return None if fd is not None: fd.close() tp = desc[2] if tp == imp.PY_COMPILED: if hasattr(imp, "source_from_cache"): try: fn = imp.source_from_cache(fn) except ValueError: # Python 3 doesn't like orphaned but still-importable # .pyc files. fn = fn[:-1] else: fn = fn[:-1] elif tp != imp.PY_SOURCE: # Don't know what this is. return None else: fn = os.path.join(pth, name.rpartition(".")[2] + ".py") fn_pypath = py.path.local(fn) if not self._should_rewrite(name, fn_pypath, state): return None self._rewritten_names.add(name) # The requested module looks like a test file, so rewrite it. This is # the most magical part of the process: load the source, rewrite the # asserts, and load the rewritten source. We also cache the rewritten # module code in a special pyc. We must be aware of the possibility of # concurrent pytest processes rewriting and loading pycs. To avoid # tricky race conditions, we maintain the following invariant: The # cached pyc is always a complete, valid pyc. Operations on it must be # atomic. POSIX's atomic rename comes in handy. write = not sys.dont_write_bytecode cache_dir = os.path.join(fn_pypath.dirname, "__pycache__") if write: try: os.mkdir(cache_dir) except OSError: e = sys.exc_info()[1].errno if e == errno.EEXIST: # Either the __pycache__ directory already exists (the # common case) or it's blocked by a non-dir node. In the # latter case, we'll ignore it in _write_pyc. pass elif e in [errno.ENOENT, errno.ENOTDIR]: # One of the path components was not a directory, likely # because we're in a zip file. write = False elif e in [errno.EACCES, errno.EROFS, errno.EPERM]: state.trace("read only directory: %r" % fn_pypath.dirname) write = False else: raise cache_name = fn_pypath.basename[:-3] + PYC_TAIL pyc = os.path.join(cache_dir, cache_name) # Notice that even if we're in a read-only directory, I'm going # to check for a cached pyc. This may not be optimal... co = _read_pyc(fn_pypath, pyc, state.trace) if co is None: state.trace("rewriting %r" % (fn,)) source_stat, co = _rewrite_test(self.config, fn_pypath) if co is None: # Probably a SyntaxError in the test. return None if write: _make_rewritten_pyc(state, source_stat, pyc, co) else: state.trace("found cached rewritten pyc for %r" % (fn,)) self.modules[name] = co, pyc return self def _should_rewrite(self, name, fn_pypath, state): # always rewrite conftest files fn = str(fn_pypath) if fn_pypath.basename == 'conftest.py': state.trace("rewriting conftest file: %r" % (fn,)) return True if self.session is not None: if self.session.isinitpath(fn): state.trace("matched test file (was specified on cmdline): %r" % (fn,)) return True # modules not passed explicitly on the command line are only # rewritten if they match the naming convention for test files for pat in self.fnpats: # use fnmatch instead of fn_pypath.fnmatch because the # latter might trigger an import to fnmatch.fnmatch # internally, which would cause this method to be # called recursively if fnmatch(fn_pypath.basename, pat): state.trace("matched test file %r" % (fn,)) return True for marked in self._must_rewrite: if name.startswith(marked): state.trace("matched marked file %r (from %r)" % (name, marked)) return True return False def mark_rewrite(self, names): """Mark import names as needing to be re-written. The named module or package as well as any nested modules will be re-written on import. """ already_imported = set(names).intersection(set(sys.modules)) if already_imported: for name in already_imported: if name not in self._rewritten_names: self._warn_already_imported(name) self._must_rewrite.update(names) def _warn_already_imported(self, name): self.config.warn( 'P1', 'Module already imported so can not be re-written: %s' % name) def load_module(self, name): # If there is an existing module object named 'fullname' in # sys.modules, the loader must use that existing module. (Otherwise, # the reload() builtin will not work correctly.) if name in sys.modules: return sys.modules[name] co, pyc = self.modules.pop(name) # I wish I could just call imp.load_compiled here, but __file__ has to # be set properly. In Python 3.2+, this all would be handled correctly # by load_compiled. mod = sys.modules[name] = imp.new_module(name) try: mod.__file__ = co.co_filename # Normally, this attribute is 3.2+. mod.__cached__ = pyc mod.__loader__ = self py.builtin.exec_(co, mod.__dict__) except: if name in sys.modules: del sys.modules[name] raise return sys.modules[name] def is_package(self, name): try: fd, fn, desc = imp.find_module(name) except ImportError: return False if fd is not None: fd.close() tp = desc[2] return tp == imp.PKG_DIRECTORY @classmethod def _register_with_pkg_resources(cls): """ Ensure package resources can be loaded from this loader. May be called multiple times, as the operation is idempotent. """ try: import pkg_resources # access an attribute in case a deferred importer is present pkg_resources.__name__ except ImportError: return # Since pytest tests are always located in the file system, the # DefaultProvider is appropriate. pkg_resources.register_loader_type(cls, pkg_resources.DefaultProvider) def get_data(self, pathname): """Optional PEP302 get_data API. """ with open(pathname, 'rb') as f: return f.read() def _write_pyc(state, co, source_stat, pyc): # Technically, we don't have to have the same pyc format as # (C)Python, since these "pycs" should never be seen by builtin # import. However, there's little reason deviate, and I hope # sometime to be able to use imp.load_compiled to load them. (See # the comment in load_module above.) try: fp = open(pyc, "wb") except IOError: err = sys.exc_info()[1].errno state.trace("error writing pyc file at %s: errno=%s" %(pyc, err)) # we ignore any failure to write the cache file # there are many reasons, permission-denied, __pycache__ being a # file etc. return False try: fp.write(imp.get_magic()) mtime = int(source_stat.mtime) size = source_stat.size & 0xFFFFFFFF fp.write(struct.pack("<ll", mtime, size)) marshal.dump(co, fp) finally: fp.close() return True RN = "\r\n".encode("utf-8") N = "\n".encode("utf-8") cookie_re = re.compile(r"^[ \t\f]#.coding[:=][ \t][-\w.]+") BOM_UTF8 = '\xef\xbb\xbf' def _rewrite_test(config, fn): """Try to read and rewrite fn and return the code object.""" state = config._assertstate try: stat = fn.stat() source = fn.read("rb") except EnvironmentError: return None, None if ASCII_IS_DEFAULT_ENCODING: # ASCII is the default encoding in Python 2. Without a coding # declaration, Python 2 will complain about any bytes in the file # outside the ASCII range. Sadly, this behavior does not extend to # compile() or ast.parse(), which prefer to interpret the bytes as # latin-1. (At least they properly handle explicit coding cookies.) To # preserve this error behavior, we could force ast.parse() to use ASCII # as the encoding by inserting a coding cookie. Unfortunately, that # messes up line numbers. Thus, we have to check ourselves if anything # is outside the ASCII range in the case no encoding is explicitly # declared. For more context, see issue #269. Yay for Python 3 which # gets this right. end1 = source.find("\n") end2 = source.find("\n", end1 + 1) if (not source.startswith(BOM_UTF8) and cookie_re.match(source[0:end1]) is None and cookie_re.match(source[end1 + 1:end2]) is None): if hasattr(state, "_indecode"): # encodings imported us again, so don't rewrite. return None, None state._indecode = True try: try: source.decode("ascii") except UnicodeDecodeError: # Let it fail in real import. return None, None finally: del state._indecode # On Python versions which are not 2.7 and less than or equal to 3.1, the # parser expects nix newlines. if REWRITE_NEWLINES: source = source.replace(RN, N) + N try: tree = ast.parse(source) except SyntaxError: # Let this pop up again in the real import. state.trace("failed to parse: %r" % (fn,)) return None, None rewrite_asserts(tree, fn, config) try: co = compile(tree, fn.strpath, "exec") except SyntaxError: # It's possible that this error is from some bug in the # assertion rewriting, but I don't know of a fast way to tell. state.trace("failed to compile: %r" % (fn,)) return None, None return stat, co def _make_rewritten_pyc(state, source_stat, pyc, co): """Try to dump rewritten code to pyc.""" if sys.platform.startswith("win"): # Windows grants exclusive access to open files and doesn't have atomic # rename, so just write into the final file. _write_pyc(state, co, source_stat, pyc) else: # When not on windows, assume rename is atomic. Dump the code object # into a file specific to this process and atomically replace it. proc_pyc = pyc + "." + str(os.getpid()) if _write_pyc(state, co, source_stat, proc_pyc): os.rename(proc_pyc, pyc) def _read_pyc(source, pyc, trace=lambda x: None): """Possibly read a pytest pyc containing rewritten code. Return rewritten code if successful or None if not. """ try: fp = open(pyc, "rb") except IOError: return None with fp: try: mtime = int(source.mtime()) size = source.size() data = fp.read(12) except EnvironmentError as e: trace('_read_pyc(%s): EnvironmentError %s' % (source, e)) return None # Check for invalid or out of date pyc file. if (len(data) != 12 or data[:4] != imp.get_magic() or struct.unpack("<ll", data[4:]) != (mtime, size)): trace('_read_pyc(%s): invalid or out of date pyc' % source) return None try: co = marshal.load(fp) except Exception as e: trace('_read_pyc(%s): marshal.load error %s' % (source, e)) return None if not isinstance(co, types.CodeType): trace('_read_pyc(%s): not a code object' % source) return None return co def rewrite_asserts(mod, module_path=None, config=None): """Rewrite the assert statements in mod.""" AssertionRewriter(module_path, config).run(mod) def _saferepr(obj): """Get a safe repr of an object for assertion error messages. The assertion formatting (util.format_explanation()) requires newlines to be escaped since they are a special character for it. Normally assertion.util.format_explanation() does this but for a custom repr it is possible to contain one of the special escape sequences, especially '\n{' and '\n}' are likely to be present in JSON reprs. """ repr = py.io.saferepr(obj) if py.builtin._istext(repr): t = py.builtin.text else: t = py.builtin.bytes return repr.replace(t("\n"), t("\\n")) from _pytest.assertion.util import format_explanation as _format_explanation # noqa def _format_assertmsg(obj): """Format the custom assertion message given. For strings this simply replaces newlines with '\n~' so that util.format_explanation() will preserve them instead of escaping newlines. For other objects py.io.saferepr() is used first. """ # reprlib appears to have a bug which means that if a string # contains a newline it gets escaped, however if an object has a # .__repr__() which contains newlines it does not get escaped. # However in either case we want to preserve the newline. if py.builtin._istext(obj) or py.builtin._isbytes(obj): s = obj is_repr = False else: s = py.io.saferepr(obj) is_repr = True if py.builtin._istext(s): t = py.builtin.text else: t = py.builtin.bytes s = s.replace(t("\n"), t("\n~")).replace(t("%"), t("%%")) if is_repr: s = s.replace(t("\\n"), t("\n~")) return s def _should_repr_global_name(obj): return not hasattr(obj, "__name__") and not py.builtin.callable(obj) def _format_boolop(explanations, is_or): explanation = "(" + (is_or and " or " or " and ").join(explanations) + ")" if py.builtin._istext(explanation): t = py.builtin.text else: t = py.builtin.bytes return explanation.replace(t('%'), t('%%')) def _call_reprcompare(ops, results, expls, each_obj): for i, res, expl in zip(range(len(ops)), results, expls): try: done = not res except Exception: done = True if done: break if util._reprcompare is not None: custom = util._reprcompare(ops[i], each_obj[i], each_obj[i + 1]) if custom is not None: return custom return expl unary_map = { ast.Not: "not %s", ast.Invert: "~%s", ast.USub: "-%s", ast.UAdd: "+%s" } binop_map = { ast.BitOr: "\|", ast.BitXor: "^", ast.BitAnd: "&", ast.LShift: "<<", ast.RShift: ">>", ast.Add: "+", ast.Sub: "-", ast.Mult: "", ast.Div: "/", ast.FloorDiv: "//", ast.Mod: "%%", # escaped for string formatting ast.Eq: "==", ast.NotEq: "!=", ast.Lt: "<", ast.LtE: "<=", ast.Gt: ">", ast.GtE: ">=", ast.Pow: "*", ast.Is: "is", ast.IsNot: "is not", ast.In: "in", ast.NotIn: "not in" } # Python 3.5+ compatibility try: binop_map[ast.MatMult] = "@" except AttributeError: pass # Python 3.4+ compatibility if hasattr(ast, "NameConstant"): _NameConstant = ast.NameConstant else: def _NameConstant(c): return ast.Name(str(c), ast.Load()) def set_location(node, lineno, col_offset): """Set node location information recursively.""" def _fix(node, lineno, col_offset): if "lineno" in node._attributes: node.lineno = lineno if "col_offset" in node._attributes: node.col_offset = col_offset for child in ast.iter_child_nodes(node): _fix(child, lineno, col_offset) _fix(node, lineno, col_offset) return node class AssertionRewriter(ast.NodeVisitor): """Assertion rewriting implementation. The main entrypoint is to call .run() with an ast.Module instance, this will then find all the assert statements and re-write them to provide intermediate values and a detailed assertion error. See http://pybites.blogspot.be/2011/07/behind-scenes-of-pytests-new-assertion.html for an overview of how this works. The entry point here is .run() which will iterate over all the statements in an ast.Module and for each ast.Assert statement it finds call .visit() with it. Then .visit_Assert() takes over and is responsible for creating new ast statements to replace the original assert statement: it re-writes the test of an assertion to provide intermediate values and replace it with an if statement which raises an assertion error with a detailed explanation in case the expression is false. For this .visit_Assert() uses the visitor pattern to visit all the AST nodes of the ast.Assert.test field, each visit call returning an AST node and the corresponding explanation string. During this state is kept in several instance attributes: :statements: All the AST statements which will replace the assert statement. :variables: This is populated by .variable() with each variable used by the statements so that they can all be set to None at the end of the statements. :variable_counter: Counter to create new unique variables needed by statements. Variables are created using .variable() and have the form of "@py_assert0". :on_failure: The AST statements which will be executed if the assertion test fails. This is the code which will construct the failure message and raises the AssertionError. :explanation_specifiers: A dict filled by .explanation_param() with %-formatting placeholders and their corresponding expressions to use in the building of an assertion message. This is used by .pop_format_context() to build a message. :stack: A stack of the explanation_specifiers dicts maintained by .push_format_context() and .pop_format_context() which allows to build another %-formatted string while already building one. This state is reset on every new assert statement visited and used by the other visitors. """ def __init__(self, module_path, config): super(AssertionRewriter, self).__init__() self.module_path = module_path self.config = config def run(self, mod): """Find all assert statements in mod* and rewrite them.""" if not mod.body: # Nothing to do. return # Insert some special imports at the top of the module but after any # docstrings and __future__ imports. aliases = [ast.alias(py.builtin.builtins.__name__, "@py_builtins"), ast.alias("_pytest.assertion.rewrite", "@pytest_ar")] expect_docstring = True pos = 0 lineno = 0 for item in mod.body: if (expect_docstring and isinstance(item, ast.Expr) and isinstance(item.value, ast.Str)): doc = item.value.s if "PYTEST_DONT_REWRITE" in doc: # The module has disabled assertion rewriting. return lineno += len(doc) - 1 expect_docstring = False elif (not isinstance(item, ast.ImportFrom) or item.level > 0 or item.module != "__future__"): lineno = item.lineno break pos += 1 imports = [ast.Import([alias], lineno=lineno, col_offset=0) for alias in aliases] mod.body[pos:pos] = imports # Collect asserts. nodes = [mod] while nodes: node = nodes.pop() for name, field in ast.iter_fields(node): if isinstance(field, list): new = [] for i, child in enumerate(field): if isinstance(child, ast.Assert): # Transform assert. new.extend(self.visit(child)) else: new.append(child) if isinstance(child, ast.AST): nodes.append(child) setattr(node, name, new) elif (isinstance(field, ast.AST) and # Don't recurse into expressions as they can't contain # asserts. not isinstance(field, ast.expr)): nodes.append(field) def variable(self): """Get a new variable.""" # Use a character invalid in python identifiers to avoid clashing. name = "@py_assert" + str(next(self.variable_counter)) self.variables.append(name) return name def assign(self, expr): """Give expr a name.""" name = self.variable() self.statements.append(ast.Assign([ast.Name(name, ast.Store())], expr)) return ast.Name(name, ast.Load()) def display(self, expr): """Call py.io.saferepr on the expression.""" return self.helper("saferepr", expr) def helper(self, name, args): """Call a helper in this module.""" py_name = ast.Name("@pytest_ar", ast.Load()) attr = ast.Attribute(py_name, "_" + name, ast.Load()) return ast_Call(attr, list(args), []) def builtin(self, name): """Return the builtin called name.""" builtin_name = ast.Name("@py_builtins", ast.Load()) return ast.Attribute(builtin_name, name, ast.Load()) def explanation_param(self, expr): """Return a new named %-formatting placeholder for expr. This creates a %-formatting placeholder for expr in the current formatting context, e.g. ``%(py0)s``. The placeholder and expr are placed in the current format context so that it can be used on the next call to .pop_format_context(). """ specifier = "py" + str(next(self.variable_counter)) self.explanation_specifiers[specifier] = expr return "%(" + specifier + ")s" def push_format_context(self): """Create a new formatting context. The format context is used for when an explanation wants to have a variable value formatted in the assertion message. In this case the value required can be added using .explanation_param(). Finally .pop_format_context() is used to format a string of %-formatted values as added by .explanation_param(). """ self.explanation_specifiers = {} self.stack.append(self.explanation_specifiers) def pop_format_context(self, expl_expr): """Format the %-formatted string with current format context. The expl_expr should be an ast.Str instance constructed from the %-placeholders created by .explanation_param(). This will add the required code to format said string to .on_failure and return the ast.Name instance of the formatted string. """ current = self.stack.pop() if self.stack: self.explanation_specifiers = self.stack[-1] keys = [ast.Str(key) for key in current.keys()] format_dict = ast.Dict(keys, list(current.values())) form = ast.BinOp(expl_expr, ast.Mod(), format_dict) name = "@py_format" + str(next(self.variable_counter)) self.on_failure.append(ast.Assign([ast.Name(name, ast.Store())], form)) return ast.Name(name, ast.Load()) def generic_visit(self, node): """Handle expressions we don't have custom code for.""" assert isinstance(node, ast.expr) res = self.assign(node) return res, self.explanation_param(self.display(res)) def visit_Assert(self, assert_): """Return the AST statements to replace the ast.Assert instance. This re-writes the test of an assertion to provide intermediate values and replace it with an if statement which raises an assertion error with a detailed explanation in case the expression is false. """ if isinstance(assert_.test, ast.Tuple) and self.config is not None: fslocation = (self.module_path, assert_.lineno) self.config.warn('R1', 'assertion is always true, perhaps ' 'remove parentheses?', fslocation=fslocation) self.statements = [] self.variables = [] self.variable_counter = itertools.count() self.stack = [] self.on_failure = [] self.push_format_context() # Rewrite assert into a bunch of statements. top_condition, explanation = self.visit(assert_.test) # Create failure message. body = self.on_failure negation = ast.UnaryOp(ast.Not(), top_condition) self.statements.append(ast.If(negation, body, [])) if assert_.msg: assertmsg = self.helper('format_assertmsg', assert_.msg) explanation = "\n>assert " + explanation else: assertmsg = ast.Str("") explanation = "assert " + explanation template = ast.BinOp(assertmsg, ast.Add(), ast.Str(explanation)) msg = self.pop_format_context(template) fmt = self.helper("format_explanation", msg) err_name = ast.Name("AssertionError", ast.Load()) exc = ast_Call(err_name, [fmt], []) if sys.version_info[0] >= 3: raise_ = ast.Raise(exc, None) else: raise_ = ast.Raise(exc, None, None) body.append(raise_) # Clear temporary variables by setting them to None. if self.variables: variables = [ast.Name(name, ast.Store()) for name in self.variables] clear = ast.Assign(variables, _NameConstant(None)) self.statements.append(clear) # Fix line numbers. for stmt in self.statements: set_location(stmt, assert_.lineno, assert_.col_offset) return self.statements def visit_Name(self, name): # Display the repr of the name if it's a local variable or # _should_repr_global_name() thinks it's acceptable. locs = ast_Call(self.builtin("locals"), [], []) inlocs = ast.Compare(ast.Str(name.id), [ast.In()], [locs]) dorepr = self.helper("should_repr_global_name", name) test = ast.BoolOp(ast.Or(), [inlocs, dorepr]) expr = ast.IfExp(test, self.display(name), ast.Str(name.id)) return name, self.explanation_param(expr) def visit_BoolOp(self, boolop): res_var = self.variable() expl_list = self.assign(ast.List([], ast.Load())) app = ast.Attribute(expl_list, "append", ast.Load()) is_or = int(isinstance(boolop.op, ast.Or)) body = save = self.statements fail_save = self.on_failure levels = len(boolop.values) - 1 self.push_format_context() # Process each operand, short-circuting if needed. for i, v in enumerate(boolop.values): if i: fail_inner = [] # cond is set in a prior loop iteration below self.on_failure.append(ast.If(cond, fail_inner, [])) # noqa self.on_failure = fail_inner self.push_format_context() res, expl = self.visit(v) body.append(ast.Assign([ast.Name(res_var, ast.Store())], res)) expl_format = self.pop_format_context(ast.Str(expl)) call = ast_Call(app, [expl_format], []) self.on_failure.append(ast.Expr(call)) if i < levels: cond = res if is_or: cond = ast.UnaryOp(ast.Not(), cond) inner = [] self.statements.append(ast.If(cond, inner, [])) self.statements = body = inner self.statements = save self.on_failure = fail_save expl_template = self.helper("format_boolop", expl_list, ast.Num(is_or)) expl = self.pop_format_context(expl_template) return ast.Name(res_var, ast.Load()), self.explanation_param(expl) def visit_UnaryOp(self, unary): pattern = unary_map[unary.op.__class__] operand_res, operand_expl = self.visit(unary.operand) res = self.assign(ast.UnaryOp(unary.op, operand_res)) return res, pattern % (operand_expl,) def visit_BinOp(self, binop): symbol = binop_map[binop.op.__class__] left_expr, left_expl = self.visit(binop.left) right_expr, right_expl = self.visit(binop.right) explanation = "(%s %s %s)" % (left_expl, symbol, right_expl) res = self.assign(ast.BinOp(left_expr, binop.op, right_expr)) return res, explanation def visit_Call_35(self, call): """ visit `ast.Call` nodes on Python3.5 and after """ new_func, func_expl = self.visit(call.func) arg_expls = [] new_args = [] new_kwargs = [] for arg in call.args: res, expl = self.visit(arg) arg_expls.append(expl) new_args.append(res) for keyword in call.keywords: res, expl = self.visit(keyword.value) new_kwargs.append(ast.keyword(keyword.arg, res)) if keyword.arg: arg_expls.append(keyword.arg + "=" + expl) else: ## args have `arg` keywords with an .arg of None arg_expls.append("" + expl) expl = "%s(%s)" % (func_expl, ', '.join(arg_expls)) new_call = ast.Call(new_func, new_args, new_kwargs) res = self.assign(new_call) res_expl = self.explanation_param(self.display(res)) outer_expl = "%s\n{%s = %s\n}" % (res_expl, res_expl, expl) return res, outer_expl def visit_Starred(self, starred): # From Python 3.5, a Starred node can appear in a function call res, expl = self.visit(starred.value) return starred, '' + expl def visit_Call_legacy(self, call): """ visit `ast.Call nodes on 3.4 and below` """ new_func, func_expl = self.visit(call.func) arg_expls = [] new_args = [] new_kwargs = [] new_star = new_kwarg = None for arg in call.args: res, expl = self.visit(arg) new_args.append(res) arg_expls.append(expl) for keyword in call.keywords: res, expl = self.visit(keyword.value) new_kwargs.append(ast.keyword(keyword.arg, res)) arg_expls.append(keyword.arg + "=" + expl) if call.starargs: new_star, expl = self.visit(call.starargs) arg_expls.append("" + expl) if call.kwargs: new_kwarg, expl = self.visit(call.kwargs) arg_expls.append("*" + expl) expl = "%s(%s)" % (func_expl, ', '.join(arg_expls)) new_call = ast.Call(new_func, new_args, new_kwargs, new_star, new_kwarg) res = self.assign(new_call) res_expl = self.explanation_param(self.display(res)) outer_expl = "%s\n{%s = %s\n}" % (res_expl, res_expl, expl) return res, outer_expl # ast.Call signature changed on 3.5, # conditionally change which methods is named # visit_Call depending on Python version if sys.version_info >= (3, 5): visit_Call = visit_Call_35 else: visit_Call = visit_Call_legacy def visit_Attribute(self, attr): if not isinstance(attr.ctx, ast.Load): return self.generic_visit(attr) value, value_expl = self.visit(attr.value) res = self.assign(ast.Attribute(value, attr.attr, ast.Load())) res_expl = self.explanation_param(self.display(res)) pat = "%s\n{%s = %s.%s\n}" expl = pat % (res_expl, res_expl, value_expl, attr.attr) return res, expl def visit_Compare(self, comp): self.push_format_context() left_res, left_expl = self.visit(comp.left) if isinstance(comp.left, (_ast.Compare, _ast.BoolOp)): left_expl = "({0})".format(left_expl) res_variables = [self.variable() for i in range(len(comp.ops))] load_names = [ast.Name(v, ast.Load()) for v in res_variables] store_names = [ast.Name(v, ast.Store()) for v in res_variables] it = zip(range(len(comp.ops)), comp.ops, comp.comparators) expls = [] syms = [] results = [left_res] for i, op, next_operand in it: next_res, next_expl = self.visit(next_operand) if isinstance(next_operand, (_ast.Compare, _ast.BoolOp)): next_expl = "({0})".format(next_expl) results.append(next_res) sym = binop_map[op.__class__] syms.append(ast.Str(sym)) expl = "%s %s %s" % (left_expl, sym, next_expl) expls.append(ast.Str(expl)) res_expr = ast.Compare(left_res, [op], [next_res]) self.statements.append(ast.Assign([store_names[i]], res_expr)) left_res, left_expl = next_res, next_expl # Use pytest.assertion.util._reprcompare if that's available. expl_call = self.helper("call_reprcompare", ast.Tuple(syms, ast.Load()), ast.Tuple(load_names, ast.Load()), ast.Tuple(expls, ast.Load()), ast.Tuple(results, ast.Load())) if len(comp.ops) > 1: res = ast.BoolOp(ast.And(), load_names) else: res = load_names[0] return res, self.explanation_param(self.pop_format_context(expl_call))	jaraco/pytest	_pytest/assertion/rewrite.py	Python	mit	36,408	[ "VisIt" ]	eb323067c6c1fa56007179e82feaebc742ee2ed5bfdff1b103a1e8c0c2e52b69
# -- coding: utf-8 -- # Form implementation generated from reading ui file 'ui/ui_semiautomaticclassificationplugin.ui' # # Created by: PyQt5 UI code generator 5.11.3 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_SemiAutomaticClassificationPlugin(object): def setupUi(self, SemiAutomaticClassificationPlugin): SemiAutomaticClassificationPlugin.setObjectName("SemiAutomaticClassificationPlugin") SemiAutomaticClassificationPlugin.setEnabled(True) SemiAutomaticClassificationPlugin.resize(951, 529) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(SemiAutomaticClassificationPlugin.sizePolicy().hasHeightForWidth()) SemiAutomaticClassificationPlugin.setSizePolicy(sizePolicy) SemiAutomaticClassificationPlugin.setMinimumSize(QtCore.QSize(400, 400)) icon = QtGui.QIcon() icon.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) SemiAutomaticClassificationPlugin.setWindowIcon(icon) SemiAutomaticClassificationPlugin.setSizeGripEnabled(True) self.gridLayout_301 = QtWidgets.QGridLayout(SemiAutomaticClassificationPlugin) self.gridLayout_301.setContentsMargins(2, 2, 2, 2) self.gridLayout_301.setObjectName("gridLayout_301") self.splitter = QtWidgets.QSplitter(SemiAutomaticClassificationPlugin) self.splitter.setFrameShape(QtWidgets.QFrame.NoFrame) self.splitter.setOrientation(QtCore.Qt.Horizontal) self.splitter.setChildrenCollapsible(False) self.splitter.setObjectName("splitter") self.widget = QtWidgets.QWidget(self.splitter) self.widget.setMinimumSize(QtCore.QSize(50, 0)) self.widget.setMaximumSize(QtCore.QSize(250, 16777215)) self.widget.setObjectName("widget") self.gridLayout_193 = QtWidgets.QGridLayout(self.widget) self.gridLayout_193.setContentsMargins(1, 1, 1, 1) self.gridLayout_193.setObjectName("gridLayout_193") self.f_filter_lineEdit = QtWidgets.QLineEdit(self.widget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.f_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.f_filter_lineEdit.setSizePolicy(sizePolicy) self.f_filter_lineEdit.setMinimumSize(QtCore.QSize(100, 0)) self.f_filter_lineEdit.setObjectName("f_filter_lineEdit") self.gridLayout_193.addWidget(self.f_filter_lineEdit, 0, 0, 1, 1) self.menu_treeWidget = QtWidgets.QTreeWidget(self.widget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.menu_treeWidget.sizePolicy().hasHeightForWidth()) self.menu_treeWidget.setSizePolicy(sizePolicy) self.menu_treeWidget.setMinimumSize(QtCore.QSize(100, 0)) self.menu_treeWidget.setFrameShape(QtWidgets.QFrame.StyledPanel) self.menu_treeWidget.setFrameShadow(QtWidgets.QFrame.Sunken) self.menu_treeWidget.setEditTriggers(QtWidgets.QAbstractItemView.CurrentChanged\|QtWidgets.QAbstractItemView.DoubleClicked) self.menu_treeWidget.setProperty("showDropIndicator", False) self.menu_treeWidget.setAlternatingRowColors(True) self.menu_treeWidget.setTextElideMode(QtCore.Qt.ElideNone) self.menu_treeWidget.setIndentation(15) self.menu_treeWidget.setRootIsDecorated(True) self.menu_treeWidget.setHeaderHidden(True) self.menu_treeWidget.setObjectName("menu_treeWidget") item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon1 = QtGui.QIcon() icon1.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandset_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon1) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon2 = QtGui.QIcon() icon2.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_roi_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon2) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon3 = QtGui.QIcon() icon3.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_weight_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon3) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_1.setIcon(0, icon1) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon4 = QtGui.QIcon() icon4.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_export_spectral_library.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon4) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon5 = QtGui.QIcon() icon5.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_import_spectral_library.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon5) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon6 = QtGui.QIcon() icon6.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_LCS_threshold_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon6) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon7 = QtGui.QIcon() icon7.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_roi_multiple.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon7) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon8 = QtGui.QIcon() icon8.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_rgb_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon8) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon9 = QtGui.QIcon() icon9.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_threshold_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon9) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon10 = QtGui.QIcon() icon10.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_arrow.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon10) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon11 = QtGui.QIcon() icon11.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_class_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon11) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon12 = QtGui.QIcon() icon12.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_aster_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon12) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon13 = QtGui.QIcon() icon13.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_goes_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon13) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon14 = QtGui.QIcon() icon14.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_landsat8_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon14) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon15 = QtGui.QIcon() icon15.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_modis_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon15) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon16 = QtGui.QIcon() icon16.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sentinel1_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon16) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon17 = QtGui.QIcon() icon17.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sentinel_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon17) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon18 = QtGui.QIcon() icon18.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sentinel3_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon18) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon19 = QtGui.QIcon() icon19.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_clip_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon19) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon20 = QtGui.QIcon() icon20.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_cloud_masking_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon20) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon21 = QtGui.QIcon() icon21.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_mosaic_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon21) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon22 = QtGui.QIcon() icon22.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_neighbor_pixels.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon22) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon23 = QtGui.QIcon() icon23.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reproject_raster_bands.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon23) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon24 = QtGui.QIcon() icon24.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_split_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon24) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon25 = QtGui.QIcon() icon25.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_stack_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon25) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon26 = QtGui.QIcon() icon26.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_vector_to_raster_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon26) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon27 = QtGui.QIcon() icon27.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_band_processing.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon27) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon28 = QtGui.QIcon() icon28.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_band_combination_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon28) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon29 = QtGui.QIcon() icon29.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon29) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon30 = QtGui.QIcon() icon30.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_kmeans_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon30) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon31 = QtGui.QIcon() icon31.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_pca_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon31) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon32 = QtGui.QIcon() icon32.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_random_forest.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon32) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon33 = QtGui.QIcon() icon33.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_spectral_distance.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon33) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon34 = QtGui.QIcon() icon34.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_post_process.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon34) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon35 = QtGui.QIcon() icon35.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_accuracy_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon35) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon36 = QtGui.QIcon() icon36.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification_dilation.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon36) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon37 = QtGui.QIcon() icon37.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification_erosion.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon37) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon38 = QtGui.QIcon() icon38.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_report_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon38) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon39 = QtGui.QIcon() icon39.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_class_to_vector_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon39) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon40 = QtGui.QIcon() icon40.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification_sieve.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon40) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon41 = QtGui.QIcon() icon41.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_class_signature_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon41) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon42 = QtGui.QIcon() icon42.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_cross_classification.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon42) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon43 = QtGui.QIcon() icon43.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_edit_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon43) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon44 = QtGui.QIcon() icon44.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_land_cover_change.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon44) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon45 = QtGui.QIcon() icon45.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reclassification_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon45) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon46 = QtGui.QIcon() icon46.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_zonal_stat_raster_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon46) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon47 = QtGui.QIcon() icon47.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandcalc_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon47) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon48 = QtGui.QIcon() icon48.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_batch.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon48) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon49 = QtGui.QIcon() icon49.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_settings_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon49) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) icon50 = QtGui.QIcon() icon50.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/guide.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon50) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) icon51 = QtGui.QIcon() icon51.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/help.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon51) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon52 = QtGui.QIcon() icon52.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/fromGIStoRS.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon52) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) font.setStrikeOut(False) item_0.setFont(0, font) brush = QtGui.QBrush(QtGui.QColor(92, 184, 92)) brush.setStyle(QtCore.Qt.SolidPattern) item_0.setBackground(0, brush) brush = QtGui.QBrush(QtGui.QColor(255, 255, 255)) brush.setStyle(QtCore.Qt.NoBrush) item_0.setForeground(0, brush) item_0.setIcon(0, icon) self.gridLayout_193.addWidget(self.menu_treeWidget, 1, 0, 1, 1) self.main_tabWidget = QtWidgets.QTabWidget(self.splitter) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.main_tabWidget.sizePolicy().hasHeightForWidth()) self.main_tabWidget.setSizePolicy(sizePolicy) self.main_tabWidget.setMinimumSize(QtCore.QSize(400, 0)) self.main_tabWidget.setTabPosition(QtWidgets.QTabWidget.East) self.main_tabWidget.setTabShape(QtWidgets.QTabWidget.Rounded) self.main_tabWidget.setIconSize(QtCore.QSize(12, 12)) self.main_tabWidget.setDocumentMode(True) self.main_tabWidget.setObjectName("main_tabWidget") self.tool_tab = QtWidgets.QWidget() self.tool_tab.setObjectName("tool_tab") self.gridLayout_262 = QtWidgets.QGridLayout(self.tool_tab) self.gridLayout_262.setObjectName("gridLayout_262") self.SCP_tabs = QtWidgets.QTabWidget(self.tool_tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.SCP_tabs.sizePolicy().hasHeightForWidth()) self.SCP_tabs.setSizePolicy(sizePolicy) self.SCP_tabs.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates)) self.SCP_tabs.setIconSize(QtCore.QSize(20, 20)) self.SCP_tabs.setDocumentMode(True) self.SCP_tabs.setObjectName("SCP_tabs") self.tab_band_set = QtWidgets.QWidget() self.tab_band_set.setObjectName("tab_band_set") self.gridLayout_219 = QtWidgets.QGridLayout(self.tab_band_set) self.gridLayout_219.setObjectName("gridLayout_219") self.gridLayout_52 = QtWidgets.QGridLayout() self.gridLayout_52.setObjectName("gridLayout_52") self.label_59 = QtWidgets.QLabel(self.tab_band_set) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_59.sizePolicy().hasHeightForWidth()) self.label_59.setSizePolicy(sizePolicy) self.label_59.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_59.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_59.setWordWrap(False) self.label_59.setObjectName("label_59") self.gridLayout_52.addWidget(self.label_59, 0, 0, 1, 1) self.wavelength_sat_combo = QtWidgets.QComboBox(self.tab_band_set) self.wavelength_sat_combo.setObjectName("wavelength_sat_combo") self.gridLayout_52.addWidget(self.wavelength_sat_combo, 0, 1, 1, 1) self.gridLayout_50 = QtWidgets.QGridLayout() self.gridLayout_50.setObjectName("gridLayout_50") self.label_60 = QtWidgets.QLabel(self.tab_band_set) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_60.sizePolicy().hasHeightForWidth()) self.label_60.setSizePolicy(sizePolicy) self.label_60.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_60.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_60.setObjectName("label_60") self.gridLayout_50.addWidget(self.label_60, 0, 0, 1, 1) self.unit_combo = QtWidgets.QComboBox(self.tab_band_set) self.unit_combo.setMinimumSize(QtCore.QSize(100, 0)) self.unit_combo.setObjectName("unit_combo") self.gridLayout_50.addWidget(self.unit_combo, 0, 1, 1, 1) self.export_bandset_toolButton = QtWidgets.QToolButton(self.tab_band_set) self.export_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon53 = QtGui.QIcon() icon53.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_export.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.export_bandset_toolButton.setIcon(icon53) self.export_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_bandset_toolButton.setObjectName("export_bandset_toolButton") self.gridLayout_50.addWidget(self.export_bandset_toolButton, 0, 5, 1, 1) self.import_bandset_toolButton = QtWidgets.QToolButton(self.tab_band_set) self.import_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon54 = QtGui.QIcon() icon54.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_import.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.import_bandset_toolButton.setIcon(icon54) self.import_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_bandset_toolButton.setObjectName("import_bandset_toolButton") self.gridLayout_50.addWidget(self.import_bandset_toolButton, 0, 4, 1, 1) self.bandset_dateEdit = QtWidgets.QDateEdit(self.tab_band_set) self.bandset_dateEdit.setDateTime(QtCore.QDateTime(QtCore.QDate(2020, 1, 1), QtCore.QTime(0, 0, 0))) self.bandset_dateEdit.setMaximumDate(QtCore.QDate(2045, 12, 31)) self.bandset_dateEdit.setMinimumDate(QtCore.QDate(1972, 1, 1)) self.bandset_dateEdit.setCalendarPopup(True) self.bandset_dateEdit.setDate(QtCore.QDate(2020, 1, 1)) self.bandset_dateEdit.setObjectName("bandset_dateEdit") self.gridLayout_50.addWidget(self.bandset_dateEdit, 0, 3, 1, 1) self.label_3 = QtWidgets.QLabel(self.tab_band_set) self.label_3.setObjectName("label_3") self.gridLayout_50.addWidget(self.label_3, 0, 2, 1, 1) self.gridLayout_52.addLayout(self.gridLayout_50, 0, 2, 1, 1) self.gridLayout_219.addLayout(self.gridLayout_52, 2, 0, 1, 2) self.splitter_3 = QtWidgets.QSplitter(self.tab_band_set) self.splitter_3.setOrientation(QtCore.Qt.Vertical) self.splitter_3.setChildrenCollapsible(False) self.splitter_3.setObjectName("splitter_3") self.widget_5 = QtWidgets.QWidget(self.splitter_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_5.sizePolicy().hasHeightForWidth()) self.widget_5.setSizePolicy(sizePolicy) self.widget_5.setMinimumSize(QtCore.QSize(0, 50)) self.widget_5.setObjectName("widget_5") self.gridLayout_203 = QtWidgets.QGridLayout(self.widget_5) self.gridLayout_203.setContentsMargins(1, 1, 1, 1) self.gridLayout_203.setObjectName("gridLayout_203") self.gridLayout_59 = QtWidgets.QGridLayout() self.gridLayout_59.setObjectName("gridLayout_59") spacerItem = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_59.addItem(spacerItem, 2, 1, 1, 1) self.label_52 = QtWidgets.QLabel(self.widget_5) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_52.sizePolicy().hasHeightForWidth()) self.label_52.setSizePolicy(sizePolicy) self.label_52.setStyleSheet("background-color : #656565; color : white") self.label_52.setFrameShape(QtWidgets.QFrame.Panel) self.label_52.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_52.setObjectName("label_52") self.gridLayout_59.addWidget(self.label_52, 0, 0, 1, 1) self.bands_filter_lineEdit = QtWidgets.QLineEdit(self.widget_5) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.bands_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.bands_filter_lineEdit.setSizePolicy(sizePolicy) self.bands_filter_lineEdit.setObjectName("bands_filter_lineEdit") self.gridLayout_59.addWidget(self.bands_filter_lineEdit, 0, 1, 1, 1) self.gridLayout_69 = QtWidgets.QGridLayout() self.gridLayout_69.setObjectName("gridLayout_69") self.bands_tableWidget = QtWidgets.QTableWidget(self.widget_5) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.bands_tableWidget.sizePolicy().hasHeightForWidth()) self.bands_tableWidget.setSizePolicy(sizePolicy) self.bands_tableWidget.setMinimumSize(QtCore.QSize(0, 30)) self.bands_tableWidget.setFrameShadow(QtWidgets.QFrame.Sunken) self.bands_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.bands_tableWidget.setTabKeyNavigation(True) self.bands_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.bands_tableWidget.setObjectName("bands_tableWidget") self.bands_tableWidget.setColumnCount(1) self.bands_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.bands_tableWidget.setHorizontalHeaderItem(0, item) self.bands_tableWidget.horizontalHeader().setVisible(False) self.bands_tableWidget.horizontalHeader().setStretchLastSection(True) self.bands_tableWidget.verticalHeader().setVisible(False) self.gridLayout_69.addWidget(self.bands_tableWidget, 0, 0, 1, 1) self.gridLayout_60 = QtWidgets.QGridLayout() self.gridLayout_60.setObjectName("gridLayout_60") self.toolButton_reload_3 = QtWidgets.QToolButton(self.widget_5) self.toolButton_reload_3.setStyleSheet("margin: 0px;padding: 0px") icon55 = QtGui.QIcon() icon55.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reload.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_reload_3.setIcon(icon55) self.toolButton_reload_3.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_3.setObjectName("toolButton_reload_3") self.gridLayout_60.addWidget(self.toolButton_reload_3, 1, 0, 1, 1) self.select_all_bands_Button = QtWidgets.QToolButton(self.widget_5) self.select_all_bands_Button.setStyleSheet("margin: 0px;padding: 0px;") icon56 = QtGui.QIcon() icon56.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_select_all.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.select_all_bands_Button.setIcon(icon56) self.select_all_bands_Button.setIconSize(QtCore.QSize(22, 22)) self.select_all_bands_Button.setObjectName("select_all_bands_Button") self.gridLayout_60.addWidget(self.select_all_bands_Button, 2, 0, 1, 1) self.add_raster_bands_Button = QtWidgets.QToolButton(self.widget_5) self.add_raster_bands_Button.setStyleSheet("margin: 0px;padding: 0px") icon57 = QtGui.QIcon() icon57.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_plus.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.add_raster_bands_Button.setIcon(icon57) self.add_raster_bands_Button.setIconSize(QtCore.QSize(22, 22)) self.add_raster_bands_Button.setObjectName("add_raster_bands_Button") self.gridLayout_60.addWidget(self.add_raster_bands_Button, 3, 0, 1, 1) self.gridLayout_69.addLayout(self.gridLayout_60, 0, 1, 1, 1) self.gridLayout_59.addLayout(self.gridLayout_69, 1, 0, 2, 2) self.gridLayout_203.addLayout(self.gridLayout_59, 0, 0, 1, 1) self.widget_6 = QtWidgets.QWidget(self.splitter_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_6.sizePolicy().hasHeightForWidth()) self.widget_6.setSizePolicy(sizePolicy) self.widget_6.setMinimumSize(QtCore.QSize(0, 50)) self.widget_6.setObjectName("widget_6") self.gridLayout_217 = QtWidgets.QGridLayout(self.widget_6) self.gridLayout_217.setContentsMargins(1, 1, 1, 1) self.gridLayout_217.setObjectName("gridLayout_217") self.gridLayout_11 = QtWidgets.QGridLayout() self.gridLayout_11.setObjectName("gridLayout_11") self.gridLayout_42 = QtWidgets.QGridLayout() self.gridLayout_42.setObjectName("gridLayout_42") self.label_53 = QtWidgets.QLabel(self.widget_6) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_53.sizePolicy().hasHeightForWidth()) self.label_53.setSizePolicy(sizePolicy) self.label_53.setStyleSheet("background-color : #656565; color : white") self.label_53.setFrameShape(QtWidgets.QFrame.Panel) self.label_53.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_53.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_53.setObjectName("label_53") self.gridLayout_42.addWidget(self.label_53, 0, 0, 1, 1) self.gridLayout_11.addLayout(self.gridLayout_42, 0, 0, 1, 2) self.Band_set_tabWidget = QtWidgets.QTabWidget(self.widget_6) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.Band_set_tabWidget.sizePolicy().hasHeightForWidth()) self.Band_set_tabWidget.setSizePolicy(sizePolicy) self.Band_set_tabWidget.setMinimumSize(QtCore.QSize(0, 20)) self.Band_set_tabWidget.setStyleSheet("QTabBar::tab {\n" "min-height: 30px;\n" "min-width: 120px;\n" "}\n" "QTabBar::tab:selected { font: bold; color: green; }") self.Band_set_tabWidget.setTabPosition(QtWidgets.QTabWidget.North) self.Band_set_tabWidget.setDocumentMode(True) self.Band_set_tabWidget.setTabsClosable(True) self.Band_set_tabWidget.setMovable(True) self.Band_set_tabWidget.setObjectName("Band_set_tabWidget") self.gridLayout_11.addWidget(self.Band_set_tabWidget, 1, 0, 1, 1) self.gridLayout_65 = QtWidgets.QGridLayout() self.gridLayout_65.setObjectName("gridLayout_65") self.gridLayout_169 = QtWidgets.QGridLayout() self.gridLayout_169.setObjectName("gridLayout_169") self.remove_toolButton = QtWidgets.QToolButton(self.widget_6) self.remove_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon58 = QtGui.QIcon() icon58.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_remove.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.remove_toolButton.setIcon(icon58) self.remove_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_toolButton.setObjectName("remove_toolButton") self.gridLayout_169.addWidget(self.remove_toolButton, 0, 0, 1, 1) self.clear_bandset_toolButton = QtWidgets.QToolButton(self.widget_6) self.clear_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon59 = QtGui.QIcon() icon59.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reset.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.clear_bandset_toolButton.setIcon(icon59) self.clear_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_bandset_toolButton.setObjectName("clear_bandset_toolButton") self.gridLayout_169.addWidget(self.clear_bandset_toolButton, 1, 0, 1, 1) self.gridLayout_65.addLayout(self.gridLayout_169, 1, 0, 1, 2) self.gridLayout_127 = QtWidgets.QGridLayout() self.gridLayout_127.setObjectName("gridLayout_127") self.sort_by_name_toolButton = QtWidgets.QToolButton(self.widget_6) self.sort_by_name_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon60 = QtGui.QIcon() icon60.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_order_by_name.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.sort_by_name_toolButton.setIcon(icon60) self.sort_by_name_toolButton.setIconSize(QtCore.QSize(22, 22)) self.sort_by_name_toolButton.setObjectName("sort_by_name_toolButton") self.gridLayout_127.addWidget(self.sort_by_name_toolButton, 3, 0, 1, 1) self.move_up_toolButton = QtWidgets.QToolButton(self.widget_6) self.move_up_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon61 = QtGui.QIcon() icon61.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_move_up.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.move_up_toolButton.setIcon(icon61) self.move_up_toolButton.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton.setObjectName("move_up_toolButton") self.gridLayout_127.addWidget(self.move_up_toolButton, 1, 0, 1, 1) self.move_down_toolButton = QtWidgets.QToolButton(self.widget_6) self.move_down_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon62 = QtGui.QIcon() icon62.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_move_down.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.move_down_toolButton.setIcon(icon62) self.move_down_toolButton.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton.setObjectName("move_down_toolButton") self.gridLayout_127.addWidget(self.move_down_toolButton, 2, 0, 1, 1) self.add_band_set_toolButton = QtWidgets.QToolButton(self.widget_6) self.add_band_set_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon63 = QtGui.QIcon() icon63.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_add_bandset_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.add_band_set_toolButton.setIcon(icon63) self.add_band_set_toolButton.setIconSize(QtCore.QSize(22, 22)) self.add_band_set_toolButton.setObjectName("add_band_set_toolButton") self.gridLayout_127.addWidget(self.add_band_set_toolButton, 0, 0, 1, 1) self.gridLayout_65.addLayout(self.gridLayout_127, 0, 0, 1, 2) self.gridLayout_11.addLayout(self.gridLayout_65, 1, 1, 1, 1) self.gridLayout_217.addLayout(self.gridLayout_11, 0, 0, 1, 1) self.gridLayout_219.addWidget(self.splitter_3, 1, 0, 1, 2) self.gridLayout_53 = QtWidgets.QGridLayout() self.gridLayout_53.setObjectName("gridLayout_53") self.virtual_raster_bandset_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.virtual_raster_bandset_checkBox.setObjectName("virtual_raster_bandset_checkBox") self.gridLayout_53.addWidget(self.virtual_raster_bandset_checkBox, 1, 0, 1, 1) self.band_calc_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.band_calc_checkBox.setObjectName("band_calc_checkBox") self.gridLayout_53.addWidget(self.band_calc_checkBox, 1, 3, 1, 1) self.stack_raster_bandset_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.stack_raster_bandset_checkBox.setObjectName("stack_raster_bandset_checkBox") self.gridLayout_53.addWidget(self.stack_raster_bandset_checkBox, 1, 1, 1, 1) self.overview_raster_bandset_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.overview_raster_bandset_checkBox.setObjectName("overview_raster_bandset_checkBox") self.gridLayout_53.addWidget(self.overview_raster_bandset_checkBox, 1, 2, 1, 1) self.label_94 = QtWidgets.QLabel(self.tab_band_set) self.label_94.setStyleSheet("background-color : #656565; color : white") self.label_94.setFrameShape(QtWidgets.QFrame.Panel) self.label_94.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_94.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_94.setObjectName("label_94") self.gridLayout_53.addWidget(self.label_94, 0, 0, 1, 7) spacerItem1 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_53.addItem(spacerItem1, 1, 4, 1, 1) self.band_set_process_toolButton = QtWidgets.QToolButton(self.tab_band_set) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.band_set_process_toolButton.setFont(font) self.band_set_process_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.band_set_process_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon64 = QtGui.QIcon() icon64.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_run.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.band_set_process_toolButton.setIcon(icon64) self.band_set_process_toolButton.setIconSize(QtCore.QSize(34, 34)) self.band_set_process_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.band_set_process_toolButton.setObjectName("band_set_process_toolButton") self.gridLayout_53.addWidget(self.band_set_process_toolButton, 1, 5, 1, 1) self.gridLayout_219.addLayout(self.gridLayout_53, 3, 0, 1, 2) self.gridLayout_130 = QtWidgets.QGridLayout() self.gridLayout_130.setObjectName("gridLayout_130") self.toolButton_reload = QtWidgets.QToolButton(self.tab_band_set) self.toolButton_reload.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload.setIcon(icon55) self.toolButton_reload.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload.setObjectName("toolButton_reload") self.gridLayout_130.addWidget(self.toolButton_reload, 1, 4, 1, 1) self.label_39 = QtWidgets.QLabel(self.tab_band_set) self.label_39.setStyleSheet("background-color : #656565; color : white") self.label_39.setFrameShape(QtWidgets.QFrame.Panel) self.label_39.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_39.setObjectName("label_39") self.gridLayout_130.addWidget(self.label_39, 0, 0, 1, 5) self.toolButton_input_raster = QtWidgets.QToolButton(self.tab_band_set) self.toolButton_input_raster.setStyleSheet("margin: 0px;padding: 0px;") icon65 = QtGui.QIcon() icon65.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_open_file.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_input_raster.setIcon(icon65) self.toolButton_input_raster.setIconSize(QtCore.QSize(22, 22)) self.toolButton_input_raster.setObjectName("toolButton_input_raster") self.gridLayout_130.addWidget(self.toolButton_input_raster, 1, 3, 1, 1) self.image_raster_name_combo = QtWidgets.QComboBox(self.tab_band_set) self.image_raster_name_combo.setObjectName("image_raster_name_combo") self.gridLayout_130.addWidget(self.image_raster_name_combo, 1, 0, 1, 3) self.gridLayout_219.addLayout(self.gridLayout_130, 0, 0, 1, 2) self.SCP_tabs.addTab(self.tab_band_set, "") self.tab_basic_tools = QtWidgets.QWidget() self.tab_basic_tools.setObjectName("tab_basic_tools") self.gridLayout_216 = QtWidgets.QGridLayout(self.tab_basic_tools) self.gridLayout_216.setObjectName("gridLayout_216") self.tabWidget_5 = QtWidgets.QTabWidget(self.tab_basic_tools) self.tabWidget_5.setStyleSheet("") self.tabWidget_5.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_5.setDocumentMode(True) self.tabWidget_5.setObjectName("tabWidget_5") self.tab_RGB = QtWidgets.QWidget() self.tab_RGB.setObjectName("tab_RGB") self.gridLayout_213 = QtWidgets.QGridLayout(self.tab_RGB) self.gridLayout_213.setObjectName("gridLayout_213") self.gridLayout_243 = QtWidgets.QGridLayout() self.gridLayout_243.setObjectName("gridLayout_243") self.gridLayout_234 = QtWidgets.QGridLayout() self.gridLayout_234.setObjectName("gridLayout_234") self.label_126 = QtWidgets.QLabel(self.tab_RGB) self.label_126.setStyleSheet("background-color : #656565; color : white") self.label_126.setFrameShape(QtWidgets.QFrame.Panel) self.label_126.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_126.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_126.setObjectName("label_126") self.gridLayout_234.addWidget(self.label_126, 0, 0, 1, 1) self.gridLayout_243.addLayout(self.gridLayout_234, 0, 0, 1, 2) self.gridLayout_244 = QtWidgets.QGridLayout() self.gridLayout_244.setObjectName("gridLayout_244") spacerItem2 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_244.addItem(spacerItem2, 3, 0, 1, 1) self.sort_by_name_toolButton_2 = QtWidgets.QToolButton(self.tab_RGB) self.sort_by_name_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.sort_by_name_toolButton_2.setIcon(icon60) self.sort_by_name_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.sort_by_name_toolButton_2.setObjectName("sort_by_name_toolButton_2") self.gridLayout_244.addWidget(self.sort_by_name_toolButton_2, 2, 0, 1, 1) self.move_down_toolButton_3 = QtWidgets.QToolButton(self.tab_RGB) self.move_down_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") self.move_down_toolButton_3.setIcon(icon62) self.move_down_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton_3.setObjectName("move_down_toolButton_3") self.gridLayout_244.addWidget(self.move_down_toolButton_3, 1, 0, 1, 1) self.move_up_toolButton_3 = QtWidgets.QToolButton(self.tab_RGB) self.move_up_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") self.move_up_toolButton_3.setIcon(icon61) self.move_up_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton_3.setObjectName("move_up_toolButton_3") self.gridLayout_244.addWidget(self.move_up_toolButton_3, 0, 0, 1, 1) self.gridLayout_243.addLayout(self.gridLayout_244, 1, 1, 1, 1) self.gridLayout_245 = QtWidgets.QGridLayout() self.gridLayout_245.setObjectName("gridLayout_245") self.add_RGB_pushButton = QtWidgets.QToolButton(self.tab_RGB) self.add_RGB_pushButton.setStyleSheet("margin: 0px;padding: 0px") icon66 = QtGui.QIcon() icon66.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_add.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.add_RGB_pushButton.setIcon(icon66) self.add_RGB_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_RGB_pushButton.setObjectName("add_RGB_pushButton") self.gridLayout_245.addWidget(self.add_RGB_pushButton, 0, 0, 1, 1) self.export_RGB_List_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.export_RGB_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_RGB_List_toolButton.setIcon(icon53) self.export_RGB_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_RGB_List_toolButton.setObjectName("export_RGB_List_toolButton") self.gridLayout_245.addWidget(self.export_RGB_List_toolButton, 4, 0, 1, 1) self.import_RGB_List_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.import_RGB_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_RGB_List_toolButton.setIcon(icon54) self.import_RGB_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_RGB_List_toolButton.setObjectName("import_RGB_List_toolButton") self.gridLayout_245.addWidget(self.import_RGB_List_toolButton, 5, 0, 1, 1) self.clear_RGB_list_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.clear_RGB_list_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_RGB_list_toolButton.setIcon(icon59) self.clear_RGB_list_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_RGB_list_toolButton.setObjectName("clear_RGB_list_toolButton") self.gridLayout_245.addWidget(self.clear_RGB_list_toolButton, 2, 0, 1, 1) self.remove_RGB_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.remove_RGB_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_RGB_toolButton.setIcon(icon58) self.remove_RGB_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_RGB_toolButton.setObjectName("remove_RGB_toolButton") self.gridLayout_245.addWidget(self.remove_RGB_toolButton, 1, 0, 1, 1) spacerItem3 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_245.addItem(spacerItem3, 3, 0, 1, 1) self.gridLayout_243.addLayout(self.gridLayout_245, 2, 1, 1, 1) self.RGB_tableWidget = QtWidgets.QTableWidget(self.tab_RGB) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.RGB_tableWidget.sizePolicy().hasHeightForWidth()) self.RGB_tableWidget.setSizePolicy(sizePolicy) self.RGB_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.DoubleClicked) self.RGB_tableWidget.setAlternatingRowColors(True) self.RGB_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.MultiSelection) self.RGB_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.RGB_tableWidget.setObjectName("RGB_tableWidget") self.RGB_tableWidget.setColumnCount(1) self.RGB_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.RGB_tableWidget.setHorizontalHeaderItem(0, item) self.RGB_tableWidget.horizontalHeader().setDefaultSectionSize(50) self.RGB_tableWidget.horizontalHeader().setStretchLastSection(True) self.RGB_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_243.addWidget(self.RGB_tableWidget, 1, 0, 2, 1) self.gridLayout_213.addLayout(self.gridLayout_243, 0, 0, 1, 1) self.gridLayout_246 = QtWidgets.QGridLayout() self.gridLayout_246.setObjectName("gridLayout_246") self.label_196 = QtWidgets.QLabel(self.tab_RGB) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_196.sizePolicy().hasHeightForWidth()) self.label_196.setSizePolicy(sizePolicy) self.label_196.setStyleSheet("background-color : #656565; color : white") self.label_196.setFrameShape(QtWidgets.QFrame.Panel) self.label_196.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_196.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_196.setObjectName("label_196") self.gridLayout_246.addWidget(self.label_196, 0, 0, 1, 2) self.horizontalLayout_27 = QtWidgets.QHBoxLayout() self.horizontalLayout_27.setObjectName("horizontalLayout_27") self.label_192 = QtWidgets.QLabel(self.tab_RGB) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_192.sizePolicy().hasHeightForWidth()) self.label_192.setSizePolicy(sizePolicy) self.label_192.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_192.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_192.setObjectName("label_192") self.horizontalLayout_27.addWidget(self.label_192) self.all_RGB_list_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.all_RGB_list_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon67 = QtGui.QIcon() icon67.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_enter.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.all_RGB_list_toolButton.setIcon(icon67) self.all_RGB_list_toolButton.setIconSize(QtCore.QSize(22, 22)) self.all_RGB_list_toolButton.setObjectName("all_RGB_list_toolButton") self.horizontalLayout_27.addWidget(self.all_RGB_list_toolButton) spacerItem4 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_27.addItem(spacerItem4) self.gridLayout_246.addLayout(self.horizontalLayout_27, 1, 0, 1, 2) self.gridLayout_213.addLayout(self.gridLayout_246, 1, 0, 1, 1) self.tabWidget_5.addTab(self.tab_RGB, "") self.tab_band_set_list = QtWidgets.QWidget() self.tab_band_set_list.setObjectName("tab_band_set_list") self.gridLayout_197 = QtWidgets.QGridLayout(self.tab_band_set_list) self.gridLayout_197.setObjectName("gridLayout_197") self.gridLayout_267 = QtWidgets.QGridLayout() self.gridLayout_267.setObjectName("gridLayout_267") self.label_208 = QtWidgets.QLabel(self.tab_band_set_list) self.label_208.setStyleSheet("background-color : #656565; color : white") self.label_208.setFrameShape(QtWidgets.QFrame.Panel) self.label_208.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_208.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_208.setObjectName("label_208") self.gridLayout_267.addWidget(self.label_208, 0, 0, 1, 1) self.band_set_filter_lineEdit = QtWidgets.QLineEdit(self.tab_band_set_list) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.band_set_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.band_set_filter_lineEdit.setSizePolicy(sizePolicy) self.band_set_filter_lineEdit.setObjectName("band_set_filter_lineEdit") self.gridLayout_267.addWidget(self.band_set_filter_lineEdit, 0, 1, 1, 1) self.gridLayout_197.addLayout(self.gridLayout_267, 0, 0, 1, 1) self.band_set_list_tableWidget = QtWidgets.QTableWidget(self.tab_band_set_list) self.band_set_list_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.band_set_list_tableWidget.setAlternatingRowColors(True) self.band_set_list_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.MultiSelection) self.band_set_list_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.band_set_list_tableWidget.setObjectName("band_set_list_tableWidget") self.band_set_list_tableWidget.setColumnCount(3) self.band_set_list_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.band_set_list_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.band_set_list_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.band_set_list_tableWidget.setHorizontalHeaderItem(2, item) self.band_set_list_tableWidget.horizontalHeader().setDefaultSectionSize(68) self.band_set_list_tableWidget.horizontalHeader().setStretchLastSection(True) self.band_set_list_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_197.addWidget(self.band_set_list_tableWidget, 1, 0, 2, 1) self.verticalLayout_2 = QtWidgets.QVBoxLayout() self.verticalLayout_2.setObjectName("verticalLayout_2") self.move_down_toolButton_4 = QtWidgets.QToolButton(self.tab_band_set_list) self.move_down_toolButton_4.setStyleSheet("margin: 0px;padding: 0px;") self.move_down_toolButton_4.setIcon(icon62) self.move_down_toolButton_4.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton_4.setObjectName("move_down_toolButton_4") self.verticalLayout_2.addWidget(self.move_down_toolButton_4) self.move_up_toolButton_4 = QtWidgets.QToolButton(self.tab_band_set_list) self.move_up_toolButton_4.setStyleSheet("margin: 0px;padding: 0px;") self.move_up_toolButton_4.setIcon(icon61) self.move_up_toolButton_4.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton_4.setObjectName("move_up_toolButton_4") self.verticalLayout_2.addWidget(self.move_up_toolButton_4) spacerItem5 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.verticalLayout_2.addItem(spacerItem5) self.rgb_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.rgb_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.rgb_toolButton.setIcon(icon8) self.rgb_toolButton.setIconSize(QtCore.QSize(22, 22)) self.rgb_toolButton.setObjectName("rgb_toolButton") self.verticalLayout_2.addWidget(self.rgb_toolButton) self.gridLayout_197.addLayout(self.verticalLayout_2, 1, 1, 1, 1) self.gridLayout_269 = QtWidgets.QGridLayout() self.gridLayout_269.setObjectName("gridLayout_269") self.add_bandset_pushButton = QtWidgets.QToolButton(self.tab_band_set_list) self.add_bandset_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.add_bandset_pushButton.setIcon(icon66) self.add_bandset_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_bandset_pushButton.setObjectName("add_bandset_pushButton") self.gridLayout_269.addWidget(self.add_bandset_pushButton, 2, 0, 1, 1) self.export_bandset_List_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.export_bandset_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_bandset_List_toolButton.setIcon(icon53) self.export_bandset_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_bandset_List_toolButton.setObjectName("export_bandset_List_toolButton") self.gridLayout_269.addWidget(self.export_bandset_List_toolButton, 5, 0, 1, 1) self.import_bandset_List_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.import_bandset_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_bandset_List_toolButton.setIcon(icon54) self.import_bandset_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_bandset_List_toolButton.setObjectName("import_bandset_List_toolButton") self.gridLayout_269.addWidget(self.import_bandset_List_toolButton, 6, 0, 1, 1) spacerItem6 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_269.addItem(spacerItem6, 4, 0, 1, 1) self.remove_bandset_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.remove_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_bandset_toolButton.setIcon(icon58) self.remove_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_bandset_toolButton.setObjectName("remove_bandset_toolButton") self.gridLayout_269.addWidget(self.remove_bandset_toolButton, 3, 0, 1, 1) spacerItem7 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_269.addItem(spacerItem7, 1, 0, 1, 1) self.sort_by_date = QtWidgets.QToolButton(self.tab_band_set_list) self.sort_by_date.setStyleSheet("margin: 0px;padding: 0px;") self.sort_by_date.setIcon(icon60) self.sort_by_date.setIconSize(QtCore.QSize(22, 22)) self.sort_by_date.setObjectName("sort_by_date") self.gridLayout_269.addWidget(self.sort_by_date, 0, 0, 1, 1) self.gridLayout_197.addLayout(self.gridLayout_269, 2, 1, 1, 1) self.tabWidget_5.addTab(self.tab_band_set_list, "") self.tab_algorithm_weight = QtWidgets.QWidget() self.tab_algorithm_weight.setObjectName("tab_algorithm_weight") self.gridLayout_150 = QtWidgets.QGridLayout(self.tab_algorithm_weight) self.gridLayout_150.setObjectName("gridLayout_150") self.gridLayout_100 = QtWidgets.QGridLayout() self.gridLayout_100.setObjectName("gridLayout_100") self.gridLayout_108 = QtWidgets.QGridLayout() self.gridLayout_108.setObjectName("gridLayout_108") self.label_79 = QtWidgets.QLabel(self.tab_algorithm_weight) self.label_79.setStyleSheet("background-color : #656565; color : white") self.label_79.setFrameShape(QtWidgets.QFrame.Panel) self.label_79.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_79.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_79.setObjectName("label_79") self.gridLayout_108.addWidget(self.label_79, 0, 0, 1, 1) self.gridLayout_100.addLayout(self.gridLayout_108, 0, 0, 1, 2) self.gridLayout_101 = QtWidgets.QGridLayout() self.gridLayout_101.setObjectName("gridLayout_101") spacerItem8 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_101.addItem(spacerItem8, 6, 1, 1, 1) self.gridLayout_104 = QtWidgets.QGridLayout() self.gridLayout_104.setObjectName("gridLayout_104") self.gridLayout_102 = QtWidgets.QGridLayout() self.gridLayout_102.setObjectName("gridLayout_102") self.reset_weights_pushButton = QtWidgets.QToolButton(self.tab_algorithm_weight) self.reset_weights_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.reset_weights_pushButton.setIcon(icon59) self.reset_weights_pushButton.setIconSize(QtCore.QSize(22, 22)) self.reset_weights_pushButton.setObjectName("reset_weights_pushButton") self.gridLayout_102.addWidget(self.reset_weights_pushButton, 0, 0, 1, 1) self.gridLayout_104.addLayout(self.gridLayout_102, 0, 0, 1, 1) self.gridLayout_101.addLayout(self.gridLayout_104, 5, 0, 1, 3) spacerItem9 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_101.addItem(spacerItem9, 3, 1, 1, 1) self.gridLayout_100.addLayout(self.gridLayout_101, 1, 1, 1, 1) self.gridLayout_103 = QtWidgets.QGridLayout() self.gridLayout_103.setObjectName("gridLayout_103") self.set_weight_value_pushButton = QtWidgets.QToolButton(self.tab_algorithm_weight) self.set_weight_value_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.set_weight_value_pushButton.setIcon(icon67) self.set_weight_value_pushButton.setIconSize(QtCore.QSize(22, 22)) self.set_weight_value_pushButton.setObjectName("set_weight_value_pushButton") self.gridLayout_103.addWidget(self.set_weight_value_pushButton, 1, 2, 1, 1) self.label_131 = QtWidgets.QLabel(self.tab_algorithm_weight) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_131.sizePolicy().hasHeightForWidth()) self.label_131.setSizePolicy(sizePolicy) self.label_131.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_131.setObjectName("label_131") self.gridLayout_103.addWidget(self.label_131, 1, 0, 1, 1) self.weight_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.tab_algorithm_weight) self.weight_doubleSpinBox.setMaximum(1000.0) self.weight_doubleSpinBox.setProperty("value", 1.0) self.weight_doubleSpinBox.setObjectName("weight_doubleSpinBox") self.gridLayout_103.addWidget(self.weight_doubleSpinBox, 1, 1, 1, 1) spacerItem10 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_103.addItem(spacerItem10, 1, 3, 1, 1) self.label_93 = QtWidgets.QLabel(self.tab_algorithm_weight) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_93.sizePolicy().hasHeightForWidth()) self.label_93.setSizePolicy(sizePolicy) self.label_93.setStyleSheet("background-color : #656565; color : white") self.label_93.setFrameShape(QtWidgets.QFrame.Panel) self.label_93.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_93.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_93.setObjectName("label_93") self.gridLayout_103.addWidget(self.label_93, 0, 0, 1, 4) self.gridLayout_100.addLayout(self.gridLayout_103, 2, 0, 1, 2) self.alg_band_weight_tabWidget = QtWidgets.QTabWidget(self.tab_algorithm_weight) self.alg_band_weight_tabWidget.setTabPosition(QtWidgets.QTabWidget.North) self.alg_band_weight_tabWidget.setObjectName("alg_band_weight_tabWidget") self.gridLayout_100.addWidget(self.alg_band_weight_tabWidget, 1, 0, 1, 1) self.gridLayout_150.addLayout(self.gridLayout_100, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_algorithm_weight, "") self.tab_multiple_ROI = QtWidgets.QWidget() self.tab_multiple_ROI.setObjectName("tab_multiple_ROI") self.gridLayout_247 = QtWidgets.QGridLayout(self.tab_multiple_ROI) self.gridLayout_247.setObjectName("gridLayout_247") self.gridLayout_8 = QtWidgets.QGridLayout() self.gridLayout_8.setObjectName("gridLayout_8") self.point_distance_spinBox = QtWidgets.QSpinBox(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.point_distance_spinBox.sizePolicy().hasHeightForWidth()) self.point_distance_spinBox.setSizePolicy(sizePolicy) self.point_distance_spinBox.setMinimumSize(QtCore.QSize(40, 0)) self.point_distance_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.point_distance_spinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.point_distance_spinBox.setMinimum(1) self.point_distance_spinBox.setMaximum(999999999) self.point_distance_spinBox.setProperty("value", 100) self.point_distance_spinBox.setObjectName("point_distance_spinBox") self.gridLayout_8.addWidget(self.point_distance_spinBox, 1, 5, 1, 1) self.point_grid_spinBox = QtWidgets.QSpinBox(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.point_grid_spinBox.sizePolicy().hasHeightForWidth()) self.point_grid_spinBox.setSizePolicy(sizePolicy) self.point_grid_spinBox.setMinimumSize(QtCore.QSize(40, 0)) self.point_grid_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.point_grid_spinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.point_grid_spinBox.setMinimum(1) self.point_grid_spinBox.setMaximum(999999999) self.point_grid_spinBox.setProperty("value", 10000) self.point_grid_spinBox.setObjectName("point_grid_spinBox") self.gridLayout_8.addWidget(self.point_grid_spinBox, 1, 3, 1, 1) self.label_48 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_48.setStyleSheet("background-color : #656565; color : white") self.label_48.setFrameShape(QtWidgets.QFrame.Panel) self.label_48.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_48.setObjectName("label_48") self.gridLayout_8.addWidget(self.label_48, 0, 0, 1, 9) self.label_139 = QtWidgets.QLabel(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_139.sizePolicy().hasHeightForWidth()) self.label_139.setSizePolicy(sizePolicy) self.label_139.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_139.setObjectName("label_139") self.gridLayout_8.addWidget(self.label_139, 1, 7, 1, 1) self.label_19 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_19.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_19.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_19.setObjectName("label_19") self.gridLayout_8.addWidget(self.label_19, 1, 0, 1, 1) self.point_number_spinBox = QtWidgets.QSpinBox(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.point_number_spinBox.sizePolicy().hasHeightForWidth()) self.point_number_spinBox.setSizePolicy(sizePolicy) self.point_number_spinBox.setMinimumSize(QtCore.QSize(40, 0)) self.point_number_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.point_number_spinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.point_number_spinBox.setMinimum(1) self.point_number_spinBox.setMaximum(999999999) self.point_number_spinBox.setProperty("value", 100) self.point_number_spinBox.setObjectName("point_number_spinBox") self.gridLayout_8.addWidget(self.point_number_spinBox, 1, 1, 1, 1) self.add_random_point_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.add_random_point_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.add_random_point_pushButton.setIcon(icon67) self.add_random_point_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_random_point_pushButton.setObjectName("add_random_point_pushButton") self.gridLayout_8.addWidget(self.add_random_point_pushButton, 1, 8, 1, 1) self.point_distance_checkBox = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.point_distance_checkBox.setObjectName("point_distance_checkBox") self.gridLayout_8.addWidget(self.point_distance_checkBox, 1, 4, 1, 1) self.point_grid_checkBox = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.point_grid_checkBox.setObjectName("point_grid_checkBox") self.gridLayout_8.addWidget(self.point_grid_checkBox, 1, 2, 1, 1) spacerItem11 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_8.addItem(spacerItem11, 1, 6, 1, 1) self.stratified_point_checkBox = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.stratified_point_checkBox.setObjectName("stratified_point_checkBox") self.gridLayout_8.addWidget(self.stratified_point_checkBox, 2, 0, 1, 2) self.stratified_lineEdit = QtWidgets.QLineEdit(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.stratified_lineEdit.sizePolicy().hasHeightForWidth()) self.stratified_lineEdit.setSizePolicy(sizePolicy) self.stratified_lineEdit.setMinimumSize(QtCore.QSize(400, 0)) self.stratified_lineEdit.setMaxLength(10000) self.stratified_lineEdit.setObjectName("stratified_lineEdit") self.gridLayout_8.addWidget(self.stratified_lineEdit, 2, 2, 1, 4) self.band_set_comb_spinBox_10 = QtWidgets.QSpinBox(self.tab_multiple_ROI) self.band_set_comb_spinBox_10.setMinimum(1) self.band_set_comb_spinBox_10.setMaximum(100000) self.band_set_comb_spinBox_10.setObjectName("band_set_comb_spinBox_10") self.gridLayout_8.addWidget(self.band_set_comb_spinBox_10, 2, 8, 1, 1) self.label_25 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_25.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_25.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_25.setObjectName("label_25") self.gridLayout_8.addWidget(self.label_25, 2, 6, 1, 2) self.gridLayout_247.addLayout(self.gridLayout_8, 0, 0, 1, 1) self.gridLayout_32 = QtWidgets.QGridLayout() self.gridLayout_32.setObjectName("gridLayout_32") self.label_47 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_47.setStyleSheet("background-color : #656565; color : white") self.label_47.setFrameShape(QtWidgets.QFrame.Panel) self.label_47.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_47.setObjectName("label_47") self.gridLayout_32.addWidget(self.label_47, 0, 0, 1, 2) self.point_tableWidget = QtWidgets.QTableWidget(self.tab_multiple_ROI) self.point_tableWidget.setAlternatingRowColors(True) self.point_tableWidget.setObjectName("point_tableWidget") self.point_tableWidget.setColumnCount(10) self.point_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(6, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(7, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(8, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(9, item) self.point_tableWidget.horizontalHeader().setDefaultSectionSize(90) self.point_tableWidget.verticalHeader().setDefaultSectionSize(24) self.gridLayout_32.addWidget(self.point_tableWidget, 1, 0, 1, 1) self.gridLayout_72 = QtWidgets.QGridLayout() self.gridLayout_72.setObjectName("gridLayout_72") self.gridLayout_39 = QtWidgets.QGridLayout() self.gridLayout_39.setObjectName("gridLayout_39") spacerItem12 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_39.addItem(spacerItem12, 3, 0, 1, 1) self.add_point_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.add_point_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.add_point_pushButton.setIcon(icon66) self.add_point_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_point_pushButton.setObjectName("add_point_pushButton") self.gridLayout_39.addWidget(self.add_point_pushButton, 1, 0, 1, 1) self.remove_point_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.remove_point_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_point_pushButton.setIcon(icon58) self.remove_point_pushButton.setIconSize(QtCore.QSize(22, 22)) self.remove_point_pushButton.setObjectName("remove_point_pushButton") self.gridLayout_39.addWidget(self.remove_point_pushButton, 2, 0, 1, 1) self.export_point_list_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.export_point_list_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.export_point_list_pushButton.setIcon(icon53) self.export_point_list_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_point_list_pushButton.setObjectName("export_point_list_pushButton") self.gridLayout_39.addWidget(self.export_point_list_pushButton, 5, 0, 1, 1) spacerItem13 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_39.addItem(spacerItem13, 6, 0, 1, 1) self.import_point_list_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.import_point_list_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.import_point_list_pushButton.setIcon(icon54) self.import_point_list_pushButton.setIconSize(QtCore.QSize(22, 22)) self.import_point_list_pushButton.setObjectName("import_point_list_pushButton") self.gridLayout_39.addWidget(self.import_point_list_pushButton, 4, 0, 1, 1) spacerItem14 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_39.addItem(spacerItem14, 0, 0, 1, 1) self.gridLayout_72.addLayout(self.gridLayout_39, 2, 0, 1, 1) self.gridLayout_32.addLayout(self.gridLayout_72, 1, 1, 1, 1) self.gridLayout_73 = QtWidgets.QGridLayout() self.gridLayout_73.setObjectName("gridLayout_73") spacerItem15 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_73.addItem(spacerItem15, 1, 4, 1, 1) self.signature_checkBox2 = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.signature_checkBox2.setChecked(True) self.signature_checkBox2.setObjectName("signature_checkBox2") self.gridLayout_73.addWidget(self.signature_checkBox2, 1, 5, 1, 1) self.label_159 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_159.setStyleSheet("background-color : #656565; color : white") self.label_159.setFrameShape(QtWidgets.QFrame.Panel) self.label_159.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_159.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_159.setObjectName("label_159") self.gridLayout_73.addWidget(self.label_159, 0, 4, 1, 3) self.save_point_rois_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.save_point_rois_pushButton.setFont(font) self.save_point_rois_pushButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.save_point_rois_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.save_point_rois_pushButton.setIcon(icon64) self.save_point_rois_pushButton.setIconSize(QtCore.QSize(34, 34)) self.save_point_rois_pushButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.save_point_rois_pushButton.setObjectName("save_point_rois_pushButton") self.gridLayout_73.addWidget(self.save_point_rois_pushButton, 1, 6, 1, 1) self.gridLayout_32.addLayout(self.gridLayout_73, 3, 0, 1, 2) self.gridLayout_247.addLayout(self.gridLayout_32, 1, 0, 1, 1) self.tabWidget_5.addTab(self.tab_multiple_ROI, "") self.tab_Import = QtWidgets.QWidget() self.tab_Import.setObjectName("tab_Import") self.gridLayout_168 = QtWidgets.QGridLayout(self.tab_Import) self.gridLayout_168.setObjectName("gridLayout_168") self.toolBox_4 = QtWidgets.QToolBox(self.tab_Import) self.toolBox_4.setObjectName("toolBox_4") self.page_8 = QtWidgets.QWidget() self.page_8.setGeometry(QtCore.QRect(0, 0, 357, 448)) self.page_8.setObjectName("page_8") self.gridLayout_4 = QtWidgets.QGridLayout(self.page_8) self.gridLayout_4.setObjectName("gridLayout_4") self.gridLayout_31 = QtWidgets.QGridLayout() self.gridLayout_31.setObjectName("gridLayout_31") self.usgs_chapter_comboBox = QtWidgets.QComboBox(self.page_8) self.usgs_chapter_comboBox.setObjectName("usgs_chapter_comboBox") self.gridLayout_31.addWidget(self.usgs_chapter_comboBox, 0, 1, 1, 1) self.usgs_library_comboBox = QtWidgets.QComboBox(self.page_8) self.usgs_library_comboBox.setObjectName("usgs_library_comboBox") self.gridLayout_31.addWidget(self.usgs_library_comboBox, 1, 1, 1, 1) self.gridLayout_14 = QtWidgets.QGridLayout() self.gridLayout_14.setObjectName("gridLayout_14") self.gridLayout_31.addLayout(self.gridLayout_14, 2, 1, 1, 1) self.label_123 = QtWidgets.QLabel(self.page_8) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_123.sizePolicy().hasHeightForWidth()) self.label_123.setSizePolicy(sizePolicy) self.label_123.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_123.setObjectName("label_123") self.gridLayout_31.addWidget(self.label_123, 0, 0, 1, 1) self.label_124 = QtWidgets.QLabel(self.page_8) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_124.sizePolicy().hasHeightForWidth()) self.label_124.setSizePolicy(sizePolicy) self.label_124.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_124.setObjectName("label_124") self.gridLayout_31.addWidget(self.label_124, 1, 0, 1, 1) self.gridLayout_12 = QtWidgets.QGridLayout() self.gridLayout_12.setObjectName("gridLayout_12") spacerItem16 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_12.addItem(spacerItem16, 0, 0, 1, 1) self.label_130 = QtWidgets.QLabel(self.page_8) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_130.sizePolicy().hasHeightForWidth()) self.label_130.setSizePolicy(sizePolicy) self.label_130.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_130.setObjectName("label_130") self.gridLayout_12.addWidget(self.label_130, 0, 1, 1, 1) self.add_usgs_library_pushButton = QtWidgets.QToolButton(self.page_8) self.add_usgs_library_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.add_usgs_library_pushButton.setIcon(icon67) self.add_usgs_library_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_usgs_library_pushButton.setObjectName("add_usgs_library_pushButton") self.gridLayout_12.addWidget(self.add_usgs_library_pushButton, 0, 2, 1, 1) self.gridLayout_31.addLayout(self.gridLayout_12, 3, 0, 1, 2) self.USGS_library_textBrowser = QtWidgets.QTextBrowser(self.page_8) self.USGS_library_textBrowser.setFrameShape(QtWidgets.QFrame.Panel) self.USGS_library_textBrowser.setFrameShadow(QtWidgets.QFrame.Sunken) self.USGS_library_textBrowser.setOpenExternalLinks(True) self.USGS_library_textBrowser.setObjectName("USGS_library_textBrowser") self.gridLayout_31.addWidget(self.USGS_library_textBrowser, 5, 0, 1, 2) self.label = QtWidgets.QLabel(self.page_8) font = QtGui.QFont() font.setPointSize(8) self.label.setFont(font) self.label.setFrameShape(QtWidgets.QFrame.Panel) self.label.setFrameShadow(QtWidgets.QFrame.Sunken) self.label.setWordWrap(True) self.label.setOpenExternalLinks(True) self.label.setObjectName("label") self.gridLayout_31.addWidget(self.label, 6, 0, 1, 2) self.label_129 = QtWidgets.QLabel(self.page_8) self.label_129.setStyleSheet("background-color : #656565; color : white") self.label_129.setFrameShape(QtWidgets.QFrame.Panel) self.label_129.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_129.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_129.setObjectName("label_129") self.gridLayout_31.addWidget(self.label_129, 4, 0, 1, 2) self.gridLayout_4.addLayout(self.gridLayout_31, 0, 1, 1, 1) self.toolBox_4.addItem(self.page_8, "") self.page_6 = QtWidgets.QWidget() self.page_6.setGeometry(QtCore.QRect(0, 0, 604, 53)) self.page_6.setObjectName("page_6") self.gridLayout_175 = QtWidgets.QGridLayout(self.page_6) self.gridLayout_175.setObjectName("gridLayout_175") self.gridLayout_174 = QtWidgets.QGridLayout() self.gridLayout_174.setObjectName("gridLayout_174") self.label_9 = QtWidgets.QLabel(self.page_6) self.label_9.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_9.setObjectName("label_9") self.gridLayout_174.addWidget(self.label_9, 0, 0, 1, 1) self.open_library_pushButton = QtWidgets.QToolButton(self.page_6) self.open_library_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.open_library_pushButton.setIcon(icon65) self.open_library_pushButton.setIconSize(QtCore.QSize(22, 22)) self.open_library_pushButton.setObjectName("open_library_pushButton") self.gridLayout_174.addWidget(self.open_library_pushButton, 0, 1, 1, 1) spacerItem17 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_174.addItem(spacerItem17, 2, 0, 1, 1) self.gridLayout_175.addLayout(self.gridLayout_174, 0, 0, 1, 1) self.toolBox_4.addItem(self.page_6, "") self.page_9 = QtWidgets.QWidget() self.page_9.setGeometry(QtCore.QRect(0, 0, 417, 165)) self.page_9.setObjectName("page_9") self.gridLayout_181 = QtWidgets.QGridLayout(self.page_9) self.gridLayout_181.setObjectName("gridLayout_181") self.gridLayout_178 = QtWidgets.QGridLayout() self.gridLayout_178.setObjectName("gridLayout_178") self.open_shapefile_pushButton = QtWidgets.QToolButton(self.page_9) self.open_shapefile_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.open_shapefile_pushButton.setIcon(icon65) self.open_shapefile_pushButton.setIconSize(QtCore.QSize(20, 20)) self.open_shapefile_pushButton.setObjectName("open_shapefile_pushButton") self.gridLayout_178.addWidget(self.open_shapefile_pushButton, 0, 2, 1, 1) self.label_120 = QtWidgets.QLabel(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_120.sizePolicy().hasHeightForWidth()) self.label_120.setSizePolicy(sizePolicy) self.label_120.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_120.setObjectName("label_120") self.gridLayout_178.addWidget(self.label_120, 0, 0, 1, 1) self.gridLayout_179 = QtWidgets.QGridLayout() self.gridLayout_179.setObjectName("gridLayout_179") self.C_ID_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.C_ID_combo.sizePolicy().hasHeightForWidth()) self.C_ID_combo.setSizePolicy(sizePolicy) self.C_ID_combo.setObjectName("C_ID_combo") self.gridLayout_179.addWidget(self.C_ID_combo, 2, 2, 1, 1) self.MC_ID_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.MC_ID_combo.sizePolicy().hasHeightForWidth()) self.MC_ID_combo.setSizePolicy(sizePolicy) self.MC_ID_combo.setObjectName("MC_ID_combo") self.gridLayout_179.addWidget(self.MC_ID_combo, 2, 0, 1, 1) self.MC_Info_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.MC_Info_combo.sizePolicy().hasHeightForWidth()) self.MC_Info_combo.setSizePolicy(sizePolicy) self.MC_Info_combo.setObjectName("MC_Info_combo") self.gridLayout_179.addWidget(self.MC_Info_combo, 2, 1, 1, 1) self.label_99 = QtWidgets.QLabel(self.page_9) self.label_99.setFrameShape(QtWidgets.QFrame.Panel) self.label_99.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_99.setObjectName("label_99") self.gridLayout_179.addWidget(self.label_99, 1, 3, 1, 1) self.C_Info_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.C_Info_combo.sizePolicy().hasHeightForWidth()) self.C_Info_combo.setSizePolicy(sizePolicy) self.C_Info_combo.setObjectName("C_Info_combo") self.gridLayout_179.addWidget(self.C_Info_combo, 2, 3, 1, 1) self.label_119 = QtWidgets.QLabel(self.page_9) self.label_119.setStyleSheet("background-color : #656565; color : white") self.label_119.setFrameShape(QtWidgets.QFrame.Panel) self.label_119.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_119.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_119.setObjectName("label_119") self.gridLayout_179.addWidget(self.label_119, 0, 0, 1, 5) self.MC_ID_combo_2 = QtWidgets.QLabel(self.page_9) self.MC_ID_combo_2.setFrameShape(QtWidgets.QFrame.Panel) self.MC_ID_combo_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.MC_ID_combo_2.setObjectName("MC_ID_combo_2") self.gridLayout_179.addWidget(self.MC_ID_combo_2, 1, 2, 1, 1) self.label_121 = QtWidgets.QLabel(self.page_9) self.label_121.setFrameShape(QtWidgets.QFrame.Panel) self.label_121.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_121.setObjectName("label_121") self.gridLayout_179.addWidget(self.label_121, 1, 0, 1, 1) self.label_122 = QtWidgets.QLabel(self.page_9) self.label_122.setFrameShape(QtWidgets.QFrame.Panel) self.label_122.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_122.setObjectName("label_122") self.gridLayout_179.addWidget(self.label_122, 1, 1, 1, 1) self.gridLayout_178.addLayout(self.gridLayout_179, 3, 0, 1, 3) spacerItem18 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_178.addItem(spacerItem18, 5, 0, 1, 1) self.gridLayout_180 = QtWidgets.QGridLayout() self.gridLayout_180.setObjectName("gridLayout_180") self.label_2 = QtWidgets.QLabel(self.page_9) self.label_2.setObjectName("label_2") self.gridLayout_180.addWidget(self.label_2, 0, 2, 1, 1) spacerItem19 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_180.addItem(spacerItem19, 0, 0, 1, 1) self.signature_checkBox_2 = QtWidgets.QCheckBox(self.page_9) self.signature_checkBox_2.setChecked(True) self.signature_checkBox_2.setObjectName("signature_checkBox_2") self.gridLayout_180.addWidget(self.signature_checkBox_2, 0, 1, 1, 1) self.import_shapefile_pushButton = QtWidgets.QToolButton(self.page_9) self.import_shapefile_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.import_shapefile_pushButton.setIcon(icon67) self.import_shapefile_pushButton.setIconSize(QtCore.QSize(22, 22)) self.import_shapefile_pushButton.setObjectName("import_shapefile_pushButton") self.gridLayout_180.addWidget(self.import_shapefile_pushButton, 0, 3, 1, 1) self.gridLayout_178.addLayout(self.gridLayout_180, 4, 0, 1, 3) self.select_shapefile_label = QtWidgets.QLabel(self.page_9) self.select_shapefile_label.setFrameShape(QtWidgets.QFrame.Panel) self.select_shapefile_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.select_shapefile_label.setText("") self.select_shapefile_label.setObjectName("select_shapefile_label") self.gridLayout_178.addWidget(self.select_shapefile_label, 0, 1, 1, 1) self.gridLayout_181.addLayout(self.gridLayout_178, 0, 1, 1, 1) self.toolBox_4.addItem(self.page_9, "") self.gridLayout_168.addWidget(self.toolBox_4, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_Import, "") self.tab_export = QtWidgets.QWidget() self.tab_export.setObjectName("tab_export") self.gridLayout_142 = QtWidgets.QGridLayout(self.tab_export) self.gridLayout_142.setObjectName("gridLayout_142") self.gridLayout_176 = QtWidgets.QGridLayout() self.gridLayout_176.setObjectName("gridLayout_176") self.label_97 = QtWidgets.QLabel(self.tab_export) self.label_97.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_97.setObjectName("label_97") self.gridLayout_176.addWidget(self.label_97, 1, 0, 1, 1) self.export_SCP_pushButton = QtWidgets.QToolButton(self.tab_export) self.export_SCP_pushButton.setStyleSheet("margin: 0px;padding: 0px;") icon68 = QtGui.QIcon() icon68.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_new_file.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.export_SCP_pushButton.setIcon(icon68) self.export_SCP_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_SCP_pushButton.setObjectName("export_SCP_pushButton") self.gridLayout_176.addWidget(self.export_SCP_pushButton, 1, 1, 1, 1) self.export_CSV_library_toolButton = QtWidgets.QToolButton(self.tab_export) self.export_CSV_library_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon69 = QtGui.QIcon() icon69.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_open_dir.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.export_CSV_library_toolButton.setIcon(icon69) self.export_CSV_library_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_CSV_library_toolButton.setObjectName("export_CSV_library_toolButton") self.gridLayout_176.addWidget(self.export_CSV_library_toolButton, 3, 1, 1, 1) self.label_96 = QtWidgets.QLabel(self.tab_export) self.label_96.setStyleSheet("background-color : #656565; color : white") self.label_96.setFrameShape(QtWidgets.QFrame.Panel) self.label_96.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_96.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_96.setObjectName("label_96") self.gridLayout_176.addWidget(self.label_96, 0, 0, 1, 2) self.label_222 = QtWidgets.QLabel(self.tab_export) self.label_222.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_222.setObjectName("label_222") self.gridLayout_176.addWidget(self.label_222, 2, 0, 1, 1) self.label_20 = QtWidgets.QLabel(self.tab_export) self.label_20.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_20.setObjectName("label_20") self.gridLayout_176.addWidget(self.label_20, 3, 0, 1, 1) self.export_SHP_pushButton = QtWidgets.QToolButton(self.tab_export) self.export_SHP_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.export_SHP_pushButton.setIcon(icon68) self.export_SHP_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_SHP_pushButton.setObjectName("export_SHP_pushButton") self.gridLayout_176.addWidget(self.export_SHP_pushButton, 2, 1, 1, 1) spacerItem20 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_176.addItem(spacerItem20, 4, 0, 1, 1) self.gridLayout_142.addLayout(self.gridLayout_176, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_export, "") self.tab_threshold = QtWidgets.QWidget() self.tab_threshold.setObjectName("tab_threshold") self.gridLayout_177 = QtWidgets.QGridLayout(self.tab_threshold) self.gridLayout_177.setObjectName("gridLayout_177") self.gridLayout_110 = QtWidgets.QGridLayout() self.gridLayout_110.setObjectName("gridLayout_110") self.gridLayout_161 = QtWidgets.QGridLayout() self.gridLayout_161.setObjectName("gridLayout_161") self.gridLayout_198 = QtWidgets.QGridLayout() self.gridLayout_198.setObjectName("gridLayout_198") spacerItem21 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_198.addItem(spacerItem21, 0, 0, 1, 1) self.gridLayout_161.addLayout(self.gridLayout_198, 0, 0, 1, 1) spacerItem22 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_161.addItem(spacerItem22, 3, 0, 1, 1) self.gridLayout_129 = QtWidgets.QGridLayout() self.gridLayout_129.setObjectName("gridLayout_129") self.reset_threshold_pushButton = QtWidgets.QToolButton(self.tab_threshold) self.reset_threshold_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.reset_threshold_pushButton.setIcon(icon59) self.reset_threshold_pushButton.setIconSize(QtCore.QSize(22, 22)) self.reset_threshold_pushButton.setObjectName("reset_threshold_pushButton") self.gridLayout_129.addWidget(self.reset_threshold_pushButton, 0, 0, 1, 1) self.gridLayout_161.addLayout(self.gridLayout_129, 1, 0, 1, 1) self.gridLayout_110.addLayout(self.gridLayout_161, 1, 1, 1, 1) self.signature_threshold_tableWidget = QtWidgets.QTableWidget(self.tab_threshold) self.signature_threshold_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.ExtendedSelection) self.signature_threshold_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectItems) self.signature_threshold_tableWidget.setObjectName("signature_threshold_tableWidget") self.signature_threshold_tableWidget.setColumnCount(7) self.signature_threshold_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(6, item) self.signature_threshold_tableWidget.horizontalHeader().setDefaultSectionSize(50) self.signature_threshold_tableWidget.horizontalHeader().setStretchLastSection(True) self.signature_threshold_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_110.addWidget(self.signature_threshold_tableWidget, 1, 0, 1, 1) self.gridLayout_109 = QtWidgets.QGridLayout() self.gridLayout_109.setObjectName("gridLayout_109") self.label_80 = QtWidgets.QLabel(self.tab_threshold) self.label_80.setStyleSheet("background-color : #656565; color : white") self.label_80.setFrameShape(QtWidgets.QFrame.Panel) self.label_80.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_80.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_80.setObjectName("label_80") self.gridLayout_109.addWidget(self.label_80, 0, 0, 1, 1) self.gridLayout_110.addLayout(self.gridLayout_109, 0, 0, 1, 2) self.gridLayout_111 = QtWidgets.QGridLayout() self.gridLayout_111.setObjectName("gridLayout_111") self.label_85 = QtWidgets.QLabel(self.tab_threshold) self.label_85.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_85.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_85.setObjectName("label_85") self.gridLayout_111.addWidget(self.label_85, 1, 2, 1, 1) self.multiplicative_threshold_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.tab_threshold) self.multiplicative_threshold_doubleSpinBox.setDecimals(1) self.multiplicative_threshold_doubleSpinBox.setMaximum(10000.0) self.multiplicative_threshold_doubleSpinBox.setProperty("value", 1.0) self.multiplicative_threshold_doubleSpinBox.setObjectName("multiplicative_threshold_doubleSpinBox") self.gridLayout_111.addWidget(self.multiplicative_threshold_doubleSpinBox, 1, 3, 1, 1) self.automatic_threshold_pushButton = QtWidgets.QToolButton(self.tab_threshold) self.automatic_threshold_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.automatic_threshold_pushButton.setIcon(icon67) self.automatic_threshold_pushButton.setIconSize(QtCore.QSize(22, 22)) self.automatic_threshold_pushButton.setObjectName("automatic_threshold_pushButton") self.gridLayout_111.addWidget(self.automatic_threshold_pushButton, 1, 4, 1, 1) self.horizontalLayout_3 = QtWidgets.QHBoxLayout() self.horizontalLayout_3.setObjectName("horizontalLayout_3") self.label_132 = QtWidgets.QLabel(self.tab_threshold) self.label_132.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_132.setObjectName("label_132") self.horizontalLayout_3.addWidget(self.label_132) self.threshold_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.tab_threshold) self.threshold_doubleSpinBox.setDecimals(4) self.threshold_doubleSpinBox.setMaximum(10000.0) self.threshold_doubleSpinBox.setProperty("value", 0.0) self.threshold_doubleSpinBox.setObjectName("threshold_doubleSpinBox") self.horizontalLayout_3.addWidget(self.threshold_doubleSpinBox) self.set_threshold_value_pushButton = QtWidgets.QToolButton(self.tab_threshold) self.set_threshold_value_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.set_threshold_value_pushButton.setIcon(icon67) self.set_threshold_value_pushButton.setIconSize(QtCore.QSize(22, 22)) self.set_threshold_value_pushButton.setObjectName("set_threshold_value_pushButton") self.horizontalLayout_3.addWidget(self.set_threshold_value_pushButton) self.gridLayout_111.addLayout(self.horizontalLayout_3, 1, 0, 1, 1) spacerItem23 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_111.addItem(spacerItem23, 1, 1, 1, 1) spacerItem24 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_111.addItem(spacerItem24, 1, 5, 1, 1) self.label_88 = QtWidgets.QLabel(self.tab_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_88.sizePolicy().hasHeightForWidth()) self.label_88.setSizePolicy(sizePolicy) self.label_88.setStyleSheet("background-color : #656565; color : white") self.label_88.setFrameShape(QtWidgets.QFrame.Panel) self.label_88.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_88.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_88.setObjectName("label_88") self.gridLayout_111.addWidget(self.label_88, 0, 0, 1, 6) self.gridLayout_110.addLayout(self.gridLayout_111, 2, 0, 1, 2) self.gridLayout_177.addLayout(self.gridLayout_110, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_threshold, "") self.tab_LCS_threshold = QtWidgets.QWidget() self.tab_LCS_threshold.setObjectName("tab_LCS_threshold") self.gridLayout_105 = QtWidgets.QGridLayout(self.tab_LCS_threshold) self.gridLayout_105.setObjectName("gridLayout_105") self.gridLayout_137 = QtWidgets.QGridLayout() self.gridLayout_137.setObjectName("gridLayout_137") self.LCS_tableWidget = QtWidgets.QTableWidget(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.LCS_tableWidget.sizePolicy().hasHeightForWidth()) self.LCS_tableWidget.setSizePolicy(sizePolicy) self.LCS_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.SelectedClicked) self.LCS_tableWidget.setAlternatingRowColors(True) self.LCS_tableWidget.setObjectName("LCS_tableWidget") self.LCS_tableWidget.setColumnCount(5) self.LCS_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(4, item) self.LCS_tableWidget.horizontalHeader().setDefaultSectionSize(50) self.LCS_tableWidget.horizontalHeader().setStretchLastSection(True) self.LCS_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_137.addWidget(self.LCS_tableWidget, 1, 0, 1, 1) self.gridLayout_138 = QtWidgets.QGridLayout() self.gridLayout_138.setObjectName("gridLayout_138") self.label_86 = QtWidgets.QLabel(self.tab_LCS_threshold) self.label_86.setStyleSheet("background-color : #656565; color : white") self.label_86.setFrameShape(QtWidgets.QFrame.Panel) self.label_86.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_86.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_86.setObjectName("label_86") self.gridLayout_138.addWidget(self.label_86, 0, 0, 1, 1) self.gridLayout_137.addLayout(self.gridLayout_138, 0, 0, 1, 2) self.verticalLayout = QtWidgets.QVBoxLayout() self.verticalLayout.setObjectName("verticalLayout") self.signature_spectral_plot_toolButton_2 = QtWidgets.QToolButton(self.tab_LCS_threshold) self.signature_spectral_plot_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") icon70 = QtGui.QIcon() icon70.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sign_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.signature_spectral_plot_toolButton_2.setIcon(icon70) self.signature_spectral_plot_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.signature_spectral_plot_toolButton_2.setObjectName("signature_spectral_plot_toolButton_2") self.verticalLayout.addWidget(self.signature_spectral_plot_toolButton_2) self.gridLayout_137.addLayout(self.verticalLayout, 1, 1, 1, 1) self.gridLayout_139 = QtWidgets.QGridLayout() self.gridLayout_139.setObjectName("gridLayout_139") self.horizontalLayout = QtWidgets.QHBoxLayout() self.horizontalLayout.setObjectName("horizontalLayout") self.label_102 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_102.sizePolicy().hasHeightForWidth()) self.label_102.setSizePolicy(sizePolicy) self.label_102.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_102.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_102.setObjectName("label_102") self.horizontalLayout.addWidget(self.label_102) self.set_min_max_Button = QtWidgets.QToolButton(self.tab_LCS_threshold) self.set_min_max_Button.setStyleSheet("margin: 0px;padding: 0px;") self.set_min_max_Button.setIcon(icon67) self.set_min_max_Button.setIconSize(QtCore.QSize(22, 22)) self.set_min_max_Button.setObjectName("set_min_max_Button") self.horizontalLayout.addWidget(self.set_min_max_Button) self.gridLayout_139.addLayout(self.horizontalLayout, 1, 0, 1, 1) self.horizontalLayout_2 = QtWidgets.QHBoxLayout() self.horizontalLayout_2.setObjectName("horizontalLayout_2") spacerItem25 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_2.addItem(spacerItem25) self.label_101 = QtWidgets.QLabel(self.tab_LCS_threshold) self.label_101.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_101.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_101.setObjectName("label_101") self.horizontalLayout_2.addWidget(self.label_101) self.multiplicative_threshold_doubleSpinBox_2 = QtWidgets.QDoubleSpinBox(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.multiplicative_threshold_doubleSpinBox_2.sizePolicy().hasHeightForWidth()) self.multiplicative_threshold_doubleSpinBox_2.setSizePolicy(sizePolicy) self.multiplicative_threshold_doubleSpinBox_2.setDecimals(1) self.multiplicative_threshold_doubleSpinBox_2.setMaximum(10000.0) self.multiplicative_threshold_doubleSpinBox_2.setProperty("value", 1.0) self.multiplicative_threshold_doubleSpinBox_2.setObjectName("multiplicative_threshold_doubleSpinBox_2") self.horizontalLayout_2.addWidget(self.multiplicative_threshold_doubleSpinBox_2) self.automatic_threshold_pushButton_2 = QtWidgets.QToolButton(self.tab_LCS_threshold) self.automatic_threshold_pushButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.automatic_threshold_pushButton_2.setIcon(icon67) self.automatic_threshold_pushButton_2.setIconSize(QtCore.QSize(22, 22)) self.automatic_threshold_pushButton_2.setObjectName("automatic_threshold_pushButton_2") self.horizontalLayout_2.addWidget(self.automatic_threshold_pushButton_2) spacerItem26 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_2.addItem(spacerItem26) self.gridLayout_140 = QtWidgets.QGridLayout() self.gridLayout_140.setObjectName("gridLayout_140") self.label_89 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_89.sizePolicy().hasHeightForWidth()) self.label_89.setSizePolicy(sizePolicy) self.label_89.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_89.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_89.setObjectName("label_89") self.gridLayout_140.addWidget(self.label_89, 0, 2, 1, 3) self.LCS_pointerButton = QtWidgets.QToolButton(self.tab_LCS_threshold) self.LCS_pointerButton.setStyleSheet("margin: 0px;padding: 0px;") icon71 = QtGui.QIcon() icon71.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_LCS_threshold_set_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.LCS_pointerButton.setIcon(icon71) self.LCS_pointerButton.setIconSize(QtCore.QSize(22, 22)) self.LCS_pointerButton.setObjectName("LCS_pointerButton") self.gridLayout_140.addWidget(self.LCS_pointerButton, 0, 5, 1, 1) self.gridLayout_144 = QtWidgets.QGridLayout() self.gridLayout_144.setObjectName("gridLayout_144") self.LCS_include_checkBox = QtWidgets.QCheckBox(self.tab_LCS_threshold) self.LCS_include_checkBox.setText("") self.LCS_include_checkBox.setIcon(icon57) self.LCS_include_checkBox.setChecked(True) self.LCS_include_checkBox.setObjectName("LCS_include_checkBox") self.gridLayout_144.addWidget(self.LCS_include_checkBox, 0, 0, 1, 1) self.LCS_cut_checkBox = QtWidgets.QCheckBox(self.tab_LCS_threshold) self.LCS_cut_checkBox.setText("") icon72 = QtGui.QIcon() icon72.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_minus.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.LCS_cut_checkBox.setIcon(icon72) self.LCS_cut_checkBox.setObjectName("LCS_cut_checkBox") self.gridLayout_144.addWidget(self.LCS_cut_checkBox, 1, 0, 1, 1) self.gridLayout_140.addLayout(self.gridLayout_144, 0, 6, 1, 1) self.label_178 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_178.sizePolicy().hasHeightForWidth()) self.label_178.setSizePolicy(sizePolicy) self.label_178.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_178.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_178.setObjectName("label_178") self.gridLayout_140.addWidget(self.label_178, 0, 0, 1, 1) self.LCS_ROI_button = QtWidgets.QToolButton(self.tab_LCS_threshold) self.LCS_ROI_button.setStyleSheet("margin: 0px;padding: 0px;") icon73 = QtGui.QIcon() icon73.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_LCS_threshold_ROI_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.LCS_ROI_button.setIcon(icon73) self.LCS_ROI_button.setIconSize(QtCore.QSize(22, 22)) self.LCS_ROI_button.setObjectName("LCS_ROI_button") self.gridLayout_140.addWidget(self.LCS_ROI_button, 0, 1, 1, 1) self.horizontalLayout_2.addLayout(self.gridLayout_140) self.gridLayout_139.addLayout(self.horizontalLayout_2, 1, 1, 1, 1) self.label_125 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_125.sizePolicy().hasHeightForWidth()) self.label_125.setSizePolicy(sizePolicy) self.label_125.setStyleSheet("background-color : #656565; color : white") self.label_125.setFrameShape(QtWidgets.QFrame.Panel) self.label_125.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_125.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_125.setObjectName("label_125") self.gridLayout_139.addWidget(self.label_125, 0, 0, 1, 2) self.gridLayout_137.addLayout(self.gridLayout_139, 2, 0, 1, 2) self.gridLayout_105.addLayout(self.gridLayout_137, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_LCS_threshold, "") self.gridLayout_216.addWidget(self.tabWidget_5, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_basic_tools, "") self.tab_download_products = QtWidgets.QWidget() self.tab_download_products.setObjectName("tab_download_products") self.gridLayout_68 = QtWidgets.QGridLayout(self.tab_download_products) self.gridLayout_68.setObjectName("gridLayout_68") self.gridLayout_113 = QtWidgets.QGridLayout() self.gridLayout_113.setObjectName("gridLayout_113") self.tabWidget_3 = QtWidgets.QTabWidget(self.tab_download_products) self.tabWidget_3.setStyleSheet("QTabBar::tab {\n" "padding: 10px;\n" "min-height: 18px;\n" "}") self.tabWidget_3.setTabPosition(QtWidgets.QTabWidget.North) self.tabWidget_3.setObjectName("tabWidget_3") self.tab_login = QtWidgets.QWidget() self.tab_login.setObjectName("tab_login") self.gridLayout_238 = QtWidgets.QGridLayout(self.tab_login) self.gridLayout_238.setObjectName("gridLayout_238") self.gridLayout_227 = QtWidgets.QGridLayout() self.gridLayout_227.setObjectName("gridLayout_227") self.remember_user_checkBox_2 = QtWidgets.QCheckBox(self.tab_login) self.remember_user_checkBox_2.setChecked(True) self.remember_user_checkBox_2.setObjectName("remember_user_checkBox_2") self.gridLayout_227.addWidget(self.remember_user_checkBox_2, 1, 4, 1, 1) self.password_usgs_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.password_usgs_lineEdit.setObjectName("password_usgs_lineEdit") self.gridLayout_227.addWidget(self.password_usgs_lineEdit, 1, 3, 1, 1) self.password_scihub_label_3 = QtWidgets.QLabel(self.tab_login) self.password_scihub_label_3.setObjectName("password_scihub_label_3") self.gridLayout_227.addWidget(self.password_scihub_label_3, 1, 2, 1, 1) self.label_180 = QtWidgets.QLabel(self.tab_login) self.label_180.setStyleSheet("background-color : #656565; color : white") self.label_180.setFrameShape(QtWidgets.QFrame.Panel) self.label_180.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_180.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_180.setOpenExternalLinks(True) self.label_180.setObjectName("label_180") self.gridLayout_227.addWidget(self.label_180, 0, 0, 1, 6) self.user_usgs_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.user_usgs_lineEdit.setObjectName("user_usgs_lineEdit") self.gridLayout_227.addWidget(self.user_usgs_lineEdit, 1, 1, 1, 1) self.user_scihub_label_2 = QtWidgets.QLabel(self.tab_login) self.user_scihub_label_2.setObjectName("user_scihub_label_2") self.gridLayout_227.addWidget(self.user_scihub_label_2, 1, 0, 1, 1) self.gridLayout_238.addLayout(self.gridLayout_227, 0, 0, 1, 1) self.gridLayout_242 = QtWidgets.QGridLayout() self.gridLayout_242.setObjectName("gridLayout_242") self.remember_user_checkBox_3 = QtWidgets.QCheckBox(self.tab_login) self.remember_user_checkBox_3.setChecked(True) self.remember_user_checkBox_3.setObjectName("remember_user_checkBox_3") self.gridLayout_242.addWidget(self.remember_user_checkBox_3, 1, 4, 1, 1) self.password_usgs_lineEdit_2 = QtWidgets.QLineEdit(self.tab_login) self.password_usgs_lineEdit_2.setObjectName("password_usgs_lineEdit_2") self.gridLayout_242.addWidget(self.password_usgs_lineEdit_2, 1, 3, 1, 1) self.password_scihub_label_4 = QtWidgets.QLabel(self.tab_login) self.password_scihub_label_4.setObjectName("password_scihub_label_4") self.gridLayout_242.addWidget(self.password_scihub_label_4, 1, 2, 1, 1) self.label_191 = QtWidgets.QLabel(self.tab_login) self.label_191.setStyleSheet("background-color : #656565; color : white") self.label_191.setFrameShape(QtWidgets.QFrame.Panel) self.label_191.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_191.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_191.setOpenExternalLinks(True) self.label_191.setObjectName("label_191") self.gridLayout_242.addWidget(self.label_191, 0, 0, 1, 6) self.user_usgs_lineEdit_2 = QtWidgets.QLineEdit(self.tab_login) self.user_usgs_lineEdit_2.setObjectName("user_usgs_lineEdit_2") self.gridLayout_242.addWidget(self.user_usgs_lineEdit_2, 1, 1, 1, 1) self.user_scihub_label_3 = QtWidgets.QLabel(self.tab_login) self.user_scihub_label_3.setObjectName("user_scihub_label_3") self.gridLayout_242.addWidget(self.user_scihub_label_3, 1, 0, 1, 1) self.gridLayout_238.addLayout(self.gridLayout_242, 1, 0, 1, 1) self.gridLayout_159 = QtWidgets.QGridLayout() self.gridLayout_159.setObjectName("gridLayout_159") self.user_scihub_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.user_scihub_lineEdit.setObjectName("user_scihub_lineEdit") self.gridLayout_159.addWidget(self.user_scihub_lineEdit, 2, 1, 1, 1) self.password_scihub_label = QtWidgets.QLabel(self.tab_login) self.password_scihub_label.setObjectName("password_scihub_label") self.gridLayout_159.addWidget(self.password_scihub_label, 2, 2, 1, 1) self.label_147 = QtWidgets.QLabel(self.tab_login) self.label_147.setStyleSheet("background-color : #656565; color : white") self.label_147.setFrameShape(QtWidgets.QFrame.Panel) self.label_147.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_147.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_147.setOpenExternalLinks(True) self.label_147.setObjectName("label_147") self.gridLayout_159.addWidget(self.label_147, 0, 0, 1, 6) self.remember_user_checkBox = QtWidgets.QCheckBox(self.tab_login) self.remember_user_checkBox.setChecked(True) self.remember_user_checkBox.setObjectName("remember_user_checkBox") self.gridLayout_159.addWidget(self.remember_user_checkBox, 2, 4, 1, 1) self.user_scihub_label = QtWidgets.QLabel(self.tab_login) self.user_scihub_label.setObjectName("user_scihub_label") self.gridLayout_159.addWidget(self.user_scihub_label, 2, 0, 1, 1) self.password_scihub_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.password_scihub_lineEdit.setObjectName("password_scihub_lineEdit") self.gridLayout_159.addWidget(self.password_scihub_lineEdit, 2, 3, 1, 1) self.horizontalLayout_10 = QtWidgets.QHBoxLayout() self.horizontalLayout_10.setObjectName("horizontalLayout_10") self.password_scihub_label_2 = QtWidgets.QLabel(self.tab_login) self.password_scihub_label_2.setObjectName("password_scihub_label_2") self.horizontalLayout_10.addWidget(self.password_scihub_label_2) self.sentinel_service_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.sentinel_service_lineEdit.setText("") self.sentinel_service_lineEdit.setObjectName("sentinel_service_lineEdit") self.horizontalLayout_10.addWidget(self.sentinel_service_lineEdit) self.reset_sentinel_service_toolButton = QtWidgets.QToolButton(self.tab_login) self.reset_sentinel_service_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.reset_sentinel_service_toolButton.setIcon(icon59) self.reset_sentinel_service_toolButton.setIconSize(QtCore.QSize(22, 22)) self.reset_sentinel_service_toolButton.setObjectName("reset_sentinel_service_toolButton") self.horizontalLayout_10.addWidget(self.reset_sentinel_service_toolButton) self.gridLayout_159.addLayout(self.horizontalLayout_10, 1, 0, 1, 5) self.sentinel2_alternative_search_checkBox = QtWidgets.QCheckBox(self.tab_login) self.sentinel2_alternative_search_checkBox.setObjectName("sentinel2_alternative_search_checkBox") self.gridLayout_159.addWidget(self.sentinel2_alternative_search_checkBox, 3, 0, 1, 5) self.gridLayout_238.addLayout(self.gridLayout_159, 2, 0, 1, 1) spacerItem27 = QtWidgets.QSpacerItem(20, 251, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_238.addItem(spacerItem27, 3, 0, 1, 1) icon74 = QtGui.QIcon() icon74.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_login.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.tabWidget_3.addTab(self.tab_login, icon74, "") self.tab_search = QtWidgets.QWidget() self.tab_search.setObjectName("tab_search") self.gridLayout_264 = QtWidgets.QGridLayout(self.tab_search) self.gridLayout_264.setObjectName("gridLayout_264") self.gridLayout_search = QtWidgets.QGridLayout() self.gridLayout_search.setObjectName("gridLayout_search") self.gridLayout_132 = QtWidgets.QGridLayout() self.gridLayout_132.setObjectName("gridLayout_132") self.remove_image_toolButton = QtWidgets.QToolButton(self.tab_search) self.remove_image_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.remove_image_toolButton.setIcon(icon58) self.remove_image_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_image_toolButton.setObjectName("remove_image_toolButton") self.gridLayout_132.addWidget(self.remove_image_toolButton, 1, 1, 1, 1) self.toolButton_display = QtWidgets.QToolButton(self.tab_search) self.toolButton_display.setStyleSheet("margin: 0px;padding: 0px;") icon75 = QtGui.QIcon() icon75.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_image_preview.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_display.setIcon(icon75) self.toolButton_display.setIconSize(QtCore.QSize(22, 22)) self.toolButton_display.setObjectName("toolButton_display") self.gridLayout_132.addWidget(self.toolButton_display, 0, 1, 1, 1) self.clear_table_toolButton = QtWidgets.QToolButton(self.tab_search) self.clear_table_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_table_toolButton.setIcon(icon59) self.clear_table_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_table_toolButton.setObjectName("clear_table_toolButton") self.gridLayout_132.addWidget(self.clear_table_toolButton, 2, 1, 1, 1) self.export_table_pushButton = QtWidgets.QToolButton(self.tab_search) self.export_table_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.export_table_pushButton.setIcon(icon53) self.export_table_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_table_pushButton.setObjectName("export_table_pushButton") self.gridLayout_132.addWidget(self.export_table_pushButton, 4, 1, 1, 1) self.import_table_pushButton = QtWidgets.QToolButton(self.tab_search) self.import_table_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.import_table_pushButton.setIcon(icon54) self.import_table_pushButton.setIconSize(QtCore.QSize(22, 22)) self.import_table_pushButton.setObjectName("import_table_pushButton") self.gridLayout_132.addWidget(self.import_table_pushButton, 3, 1, 1, 1) self.gridLayout_121 = QtWidgets.QGridLayout() self.gridLayout_121.setObjectName("gridLayout_121") self.image_preview_label = QtWidgets.QLabel(self.tab_search) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.image_preview_label.sizePolicy().hasHeightForWidth()) self.image_preview_label.setSizePolicy(sizePolicy) self.image_preview_label.setMinimumSize(QtCore.QSize(300, 300)) self.image_preview_label.setFrameShape(QtWidgets.QFrame.Panel) self.image_preview_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.image_preview_label.setAlignment(QtCore.Qt.AlignCenter) self.image_preview_label.setObjectName("image_preview_label") self.gridLayout_121.addWidget(self.image_preview_label, 0, 0, 1, 1) self.gridLayout_132.addLayout(self.gridLayout_121, 0, 0, 5, 1) self.gridLayout_search.addLayout(self.gridLayout_132, 2, 1, 1, 1) self.download_images_tableWidget = QtWidgets.QTableWidget(self.tab_search) self.download_images_tableWidget.setFrameShadow(QtWidgets.QFrame.Sunken) self.download_images_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.download_images_tableWidget.setTabKeyNavigation(True) self.download_images_tableWidget.setAlternatingRowColors(True) self.download_images_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.download_images_tableWidget.setObjectName("download_images_tableWidget") self.download_images_tableWidget.setColumnCount(14) self.download_images_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(6, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(7, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(8, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(9, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(10, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(11, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(12, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(13, item) self.download_images_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_search.addWidget(self.download_images_tableWidget, 2, 0, 1, 1) self.label_100 = QtWidgets.QLabel(self.tab_search) self.label_100.setStyleSheet("background-color : #656565; color : white") self.label_100.setFrameShape(QtWidgets.QFrame.Panel) self.label_100.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_100.setObjectName("label_100") self.gridLayout_search.addWidget(self.label_100, 0, 0, 1, 1) self.products_filter_lineEdit = QtWidgets.QLineEdit(self.tab_search) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.products_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.products_filter_lineEdit.setSizePolicy(sizePolicy) self.products_filter_lineEdit.setObjectName("products_filter_lineEdit") self.gridLayout_search.addWidget(self.products_filter_lineEdit, 0, 1, 1, 1) self.gridLayout_264.addLayout(self.gridLayout_search, 1, 0, 1, 1) self.gridLayout_133 = QtWidgets.QGridLayout() self.gridLayout_133.setObjectName("gridLayout_133") self.gridLayout_54 = QtWidgets.QGridLayout() self.gridLayout_54.setObjectName("gridLayout_54") self.toolButton_OSM = QtWidgets.QToolButton(self.tab_search) self.toolButton_OSM.setStyleSheet("margin: 0px;padding: 0px;") icon76 = QtGui.QIcon() icon76.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_osm_add.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_OSM.setIcon(icon76) self.toolButton_OSM.setIconSize(QtCore.QSize(22, 22)) self.toolButton_OSM.setObjectName("toolButton_OSM") self.gridLayout_54.addWidget(self.toolButton_OSM, 0, 0, 1, 1) self.label_205 = QtWidgets.QLabel(self.tab_search) self.label_205.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_205.setAlignment(QtCore.Qt.AlignCenter) self.label_205.setOpenExternalLinks(True) self.label_205.setObjectName("label_205") self.gridLayout_54.addWidget(self.label_205, 0, 1, 1, 1) self.label_206 = QtWidgets.QLabel(self.tab_search) self.label_206.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_206.setAlignment(QtCore.Qt.AlignCenter) self.label_206.setOpenExternalLinks(True) self.label_206.setObjectName("label_206") self.gridLayout_54.addWidget(self.label_206, 0, 2, 1, 1) spacerItem28 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_54.addItem(spacerItem28, 0, 3, 1, 2) self.gridLayout_133.addLayout(self.gridLayout_54, 3, 0, 1, 2) self.label_103 = QtWidgets.QLabel(self.tab_search) self.label_103.setStyleSheet("background-color : #656565; color : white") self.label_103.setFrameShape(QtWidgets.QFrame.Panel) self.label_103.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_103.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_103.setObjectName("label_103") self.gridLayout_133.addWidget(self.label_103, 0, 0, 1, 2) self.gridLayout_122 = QtWidgets.QGridLayout() self.gridLayout_122.setObjectName("gridLayout_122") self.selectUL_toolButton_3 = QtWidgets.QToolButton(self.tab_search) self.selectUL_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") icon77 = QtGui.QIcon() icon77.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_pointer_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.selectUL_toolButton_3.setIcon(icon77) self.selectUL_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.selectUL_toolButton_3.setObjectName("selectUL_toolButton_3") self.gridLayout_122.addWidget(self.selectUL_toolButton_3, 0, 7, 1, 1) self.LX_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.LX_lineEdit_3.setText("") self.LX_lineEdit_3.setMaxLength(15) self.LX_lineEdit_3.setObjectName("LX_lineEdit_3") self.gridLayout_122.addWidget(self.LX_lineEdit_3, 0, 4, 1, 1) self.UX_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.UX_lineEdit_3.setMaxLength(15) self.UX_lineEdit_3.setObjectName("UX_lineEdit_3") self.gridLayout_122.addWidget(self.UX_lineEdit_3, 0, 1, 1, 1) self.label_105 = QtWidgets.QLabel(self.tab_search) self.label_105.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_105.setAlignment(QtCore.Qt.AlignCenter) self.label_105.setObjectName("label_105") self.gridLayout_122.addWidget(self.label_105, 0, 3, 1, 1) self.label_107 = QtWidgets.QLabel(self.tab_search) self.label_107.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_107.setAlignment(QtCore.Qt.AlignCenter) self.label_107.setObjectName("label_107") self.gridLayout_122.addWidget(self.label_107, 0, 0, 1, 1) self.LY_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.LY_lineEdit_3.setMaxLength(15) self.LY_lineEdit_3.setObjectName("LY_lineEdit_3") self.gridLayout_122.addWidget(self.LY_lineEdit_3, 0, 5, 1, 1) self.UY_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.UY_lineEdit_3.setMaxLength(15) self.UY_lineEdit_3.setObjectName("UY_lineEdit_3") self.gridLayout_122.addWidget(self.UY_lineEdit_3, 0, 2, 1, 1) self.show_area_radioButton_2 = QtWidgets.QRadioButton(self.tab_search) self.show_area_radioButton_2.setChecked(True) self.show_area_radioButton_2.setAutoExclusive(False) self.show_area_radioButton_2.setObjectName("show_area_radioButton_2") self.gridLayout_122.addWidget(self.show_area_radioButton_2, 0, 6, 1, 1) self.gridLayout_115 = QtWidgets.QGridLayout() self.gridLayout_115.setObjectName("gridLayout_115") self.find_images_toolButton = QtWidgets.QToolButton(self.tab_search) self.find_images_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon78 = QtGui.QIcon() icon78.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_search_images.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.find_images_toolButton.setIcon(icon78) self.find_images_toolButton.setIconSize(QtCore.QSize(22, 22)) self.find_images_toolButton.setObjectName("find_images_toolButton") self.gridLayout_115.addWidget(self.find_images_toolButton, 1, 8, 1, 1) self.label_35 = QtWidgets.QLabel(self.tab_search) self.label_35.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.label_35.setObjectName("label_35") self.gridLayout_115.addWidget(self.label_35, 1, 7, 1, 1) self.gridLayout_114 = QtWidgets.QGridLayout() self.gridLayout_114.setObjectName("gridLayout_114") self.landsat_satellite_combo = QtWidgets.QComboBox(self.tab_search) self.landsat_satellite_combo.setObjectName("landsat_satellite_combo") self.gridLayout_114.addWidget(self.landsat_satellite_combo, 0, 1, 1, 1) self.dateEdit_from = QtWidgets.QDateEdit(self.tab_search) self.dateEdit_from.setDateTime(QtCore.QDateTime(QtCore.QDate(2016, 1, 1), QtCore.QTime(0, 0, 0))) self.dateEdit_from.setMaximumDate(QtCore.QDate(2045, 12, 31)) self.dateEdit_from.setMinimumDate(QtCore.QDate(1972, 1, 1)) self.dateEdit_from.setCalendarPopup(True) self.dateEdit_from.setDate(QtCore.QDate(2016, 1, 1)) self.dateEdit_from.setObjectName("dateEdit_from") self.gridLayout_114.addWidget(self.dateEdit_from, 0, 4, 1, 1) self.label_110 = QtWidgets.QLabel(self.tab_search) self.label_110.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_110.setAlignment(QtCore.Qt.AlignCenter) self.label_110.setObjectName("label_110") self.gridLayout_114.addWidget(self.label_110, 0, 8, 1, 1) self.dateEdit_to = QtWidgets.QDateEdit(self.tab_search) self.dateEdit_to.setMaximumDate(QtCore.QDate(2045, 12, 31)) self.dateEdit_to.setMinimumDate(QtCore.QDate(1980, 1, 2)) self.dateEdit_to.setCalendarPopup(True) self.dateEdit_to.setDate(QtCore.QDate(2045, 12, 31)) self.dateEdit_to.setObjectName("dateEdit_to") self.gridLayout_114.addWidget(self.dateEdit_to, 0, 6, 1, 1) self.label_112 = QtWidgets.QLabel(self.tab_search) self.label_112.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_112.setAlignment(QtCore.Qt.AlignCenter) self.label_112.setObjectName("label_112") self.gridLayout_114.addWidget(self.label_112, 0, 5, 1, 1) self.label_111 = QtWidgets.QLabel(self.tab_search) self.label_111.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_111.setAlignment(QtCore.Qt.AlignCenter) self.label_111.setObjectName("label_111") self.gridLayout_114.addWidget(self.label_111, 0, 3, 1, 1) self.cloud_cover_spinBox = QtWidgets.QSpinBox(self.tab_search) self.cloud_cover_spinBox.setMinimumSize(QtCore.QSize(50, 0)) self.cloud_cover_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.cloud_cover_spinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.cloud_cover_spinBox.setMinimum(0) self.cloud_cover_spinBox.setMaximum(100) self.cloud_cover_spinBox.setSingleStep(10) self.cloud_cover_spinBox.setProperty("value", 100) self.cloud_cover_spinBox.setObjectName("cloud_cover_spinBox") self.gridLayout_114.addWidget(self.cloud_cover_spinBox, 0, 9, 1, 1) self.label_114 = QtWidgets.QLabel(self.tab_search) self.label_114.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_114.setAlignment(QtCore.Qt.AlignCenter) self.label_114.setObjectName("label_114") self.gridLayout_114.addWidget(self.label_114, 0, 0, 1, 1) spacerItem29 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_114.addItem(spacerItem29, 0, 7, 1, 1) spacerItem30 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_114.addItem(spacerItem30, 0, 2, 1, 1) self.gridLayout_115.addLayout(self.gridLayout_114, 0, 0, 1, 9) self.gridLayout_120 = QtWidgets.QGridLayout() self.gridLayout_120.setObjectName("gridLayout_120") self.label_194 = QtWidgets.QLabel(self.tab_search) self.label_194.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_194.setAlignment(QtCore.Qt.AlignCenter) self.label_194.setObjectName("label_194") self.gridLayout_120.addWidget(self.label_194, 0, 0, 1, 1) self.label_113 = QtWidgets.QLabel(self.tab_search) self.label_113.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_113.setAlignment(QtCore.Qt.AlignCenter) self.label_113.setObjectName("label_113") self.gridLayout_120.addWidget(self.label_113, 0, 2, 1, 1) self.imageID_lineEdit = QtWidgets.QLineEdit(self.tab_search) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.imageID_lineEdit.sizePolicy().hasHeightForWidth()) self.imageID_lineEdit.setSizePolicy(sizePolicy) self.imageID_lineEdit.setMinimumSize(QtCore.QSize(200, 0)) self.imageID_lineEdit.setMaxLength(10000) self.imageID_lineEdit.setObjectName("imageID_lineEdit") self.gridLayout_120.addWidget(self.imageID_lineEdit, 0, 3, 1, 1) self.result_number_spinBox_2 = QtWidgets.QSpinBox(self.tab_search) self.result_number_spinBox_2.setMinimumSize(QtCore.QSize(50, 0)) self.result_number_spinBox_2.setMaximumSize(QtCore.QSize(100, 16777215)) self.result_number_spinBox_2.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.result_number_spinBox_2.setMinimum(5) self.result_number_spinBox_2.setMaximum(2000) self.result_number_spinBox_2.setSingleStep(5) self.result_number_spinBox_2.setProperty("value", 20) self.result_number_spinBox_2.setObjectName("result_number_spinBox_2") self.gridLayout_120.addWidget(self.result_number_spinBox_2, 0, 1, 1, 1) self.gridLayout_115.addLayout(self.gridLayout_120, 1, 0, 1, 7) self.gridLayout_122.addLayout(self.gridLayout_115, 1, 0, 1, 8) self.gridLayout_133.addLayout(self.gridLayout_122, 1, 0, 2, 2) self.gridLayout_264.addLayout(self.gridLayout_133, 0, 0, 1, 1) icon79 = QtGui.QIcon() icon79.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_search.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.tabWidget_3.addTab(self.tab_search, icon79, "") self.tab_options = QtWidgets.QWidget() self.tab_options.setObjectName("tab_options") self.gridLayout_199 = QtWidgets.QGridLayout(self.tab_options) self.gridLayout_199.setObjectName("gridLayout_199") self.gridLayout_116 = QtWidgets.QGridLayout() self.gridLayout_116.setObjectName("gridLayout_116") self.checkBox_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_6.setChecked(True) self.checkBox_band_6.setObjectName("checkBox_band_6") self.gridLayout_116.addWidget(self.checkBox_band_6, 1, 5, 1, 1) self.checkBox_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_4.setChecked(True) self.checkBox_band_4.setObjectName("checkBox_band_4") self.gridLayout_116.addWidget(self.checkBox_band_4, 1, 3, 1, 1) self.checkBox_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_1.setChecked(True) self.checkBox_band_1.setObjectName("checkBox_band_1") self.gridLayout_116.addWidget(self.checkBox_band_1, 1, 0, 1, 1) self.checkBox_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_3.setChecked(True) self.checkBox_band_3.setObjectName("checkBox_band_3") self.gridLayout_116.addWidget(self.checkBox_band_3, 1, 2, 1, 1) self.checkBox_band_12 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_12.setChecked(True) self.checkBox_band_12.setObjectName("checkBox_band_12") self.gridLayout_116.addWidget(self.checkBox_band_12, 2, 5, 1, 1) self.checkBox_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_2.setChecked(True) self.checkBox_band_2.setObjectName("checkBox_band_2") self.gridLayout_116.addWidget(self.checkBox_band_2, 1, 1, 1, 1) self.checkBox_band_11 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_11.setChecked(True) self.checkBox_band_11.setObjectName("checkBox_band_11") self.gridLayout_116.addWidget(self.checkBox_band_11, 2, 4, 1, 1) self.checkBox_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_5.setChecked(True) self.checkBox_band_5.setObjectName("checkBox_band_5") self.gridLayout_116.addWidget(self.checkBox_band_5, 1, 4, 1, 1) self.check_toolButton = QtWidgets.QToolButton(self.tab_options) self.check_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton.setIcon(icon56) self.check_toolButton.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton.setObjectName("check_toolButton") self.gridLayout_116.addWidget(self.check_toolButton, 1, 6, 1, 1) self.label_108 = QtWidgets.QLabel(self.tab_options) self.label_108.setStyleSheet("background-color : #656565; color : white") self.label_108.setFrameShape(QtWidgets.QFrame.Panel) self.label_108.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_108.setObjectName("label_108") self.gridLayout_116.addWidget(self.label_108, 0, 0, 1, 7) self.gridLayout_117 = QtWidgets.QGridLayout() self.gridLayout_117.setObjectName("gridLayout_117") spacerItem31 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_117.addItem(spacerItem31, 3, 1, 1, 1) self.gridLayout_136 = QtWidgets.QGridLayout() self.gridLayout_136.setObjectName("gridLayout_136") self.checkBoxs_band_9 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_9.setChecked(True) self.checkBoxs_band_9.setObjectName("checkBoxs_band_9") self.gridLayout_136.addWidget(self.checkBoxs_band_9, 1, 8, 1, 1) self.checkBoxs_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_1.setChecked(True) self.checkBoxs_band_1.setObjectName("checkBoxs_band_1") self.gridLayout_136.addWidget(self.checkBoxs_band_1, 1, 0, 1, 1) self.check_toolButton_2 = QtWidgets.QToolButton(self.tab_options) self.check_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton_2.setIcon(icon56) self.check_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton_2.setObjectName("check_toolButton_2") self.gridLayout_136.addWidget(self.check_toolButton_2, 1, 14, 1, 1) self.label_118 = QtWidgets.QLabel(self.tab_options) self.label_118.setStyleSheet("background-color : #656565; color : white") self.label_118.setFrameShape(QtWidgets.QFrame.Panel) self.label_118.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_118.setObjectName("label_118") self.gridLayout_136.addWidget(self.label_118, 0, 0, 1, 15) self.checkBoxs_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_2.setChecked(True) self.checkBoxs_band_2.setObjectName("checkBoxs_band_2") self.gridLayout_136.addWidget(self.checkBoxs_band_2, 1, 1, 1, 1) self.checkBoxs_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_3.setChecked(True) self.checkBoxs_band_3.setObjectName("checkBoxs_band_3") self.gridLayout_136.addWidget(self.checkBoxs_band_3, 1, 2, 1, 1) self.checkBoxs_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_4.setChecked(True) self.checkBoxs_band_4.setObjectName("checkBoxs_band_4") self.gridLayout_136.addWidget(self.checkBoxs_band_4, 1, 3, 1, 1) self.checkBoxs_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_5.setChecked(True) self.checkBoxs_band_5.setObjectName("checkBoxs_band_5") self.gridLayout_136.addWidget(self.checkBoxs_band_5, 1, 4, 1, 1) self.checkBoxs_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_6.setChecked(True) self.checkBoxs_band_6.setObjectName("checkBoxs_band_6") self.gridLayout_136.addWidget(self.checkBoxs_band_6, 1, 5, 1, 1) self.checkBoxs_band_7 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_7.setChecked(True) self.checkBoxs_band_7.setObjectName("checkBoxs_band_7") self.gridLayout_136.addWidget(self.checkBoxs_band_7, 1, 6, 1, 1) self.checkBoxs_band_12 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_12.setChecked(True) self.checkBoxs_band_12.setObjectName("checkBoxs_band_12") self.gridLayout_136.addWidget(self.checkBoxs_band_12, 1, 11, 1, 1) self.checkBoxs_band_8 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_8.setChecked(True) self.checkBoxs_band_8.setObjectName("checkBoxs_band_8") self.gridLayout_136.addWidget(self.checkBoxs_band_8, 1, 7, 1, 1) self.checkBoxs_band_10 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_10.setChecked(True) self.checkBoxs_band_10.setObjectName("checkBoxs_band_10") self.gridLayout_136.addWidget(self.checkBoxs_band_10, 1, 9, 1, 1) self.ancillary_data_checkBox = QtWidgets.QCheckBox(self.tab_options) self.ancillary_data_checkBox.setChecked(True) self.ancillary_data_checkBox.setObjectName("ancillary_data_checkBox") self.gridLayout_136.addWidget(self.ancillary_data_checkBox, 1, 13, 1, 1) self.checkBoxs_band_13 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_13.setChecked(True) self.checkBoxs_band_13.setObjectName("checkBoxs_band_13") self.gridLayout_136.addWidget(self.checkBoxs_band_13, 1, 12, 1, 1) self.checkBoxs_band_11 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_11.setChecked(True) self.checkBoxs_band_11.setObjectName("checkBoxs_band_11") self.gridLayout_136.addWidget(self.checkBoxs_band_11, 1, 10, 1, 1) self.gridLayout_117.addLayout(self.gridLayout_136, 0, 1, 1, 1) self.gridLayout_160 = QtWidgets.QGridLayout() self.gridLayout_160.setObjectName("gridLayout_160") self.checkBoxs3_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_6.setChecked(True) self.checkBoxs3_band_6.setObjectName("checkBoxs3_band_6") self.gridLayout_160.addWidget(self.checkBoxs3_band_6, 1, 5, 1, 1) self.checkBoxs3_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_2.setChecked(True) self.checkBoxs3_band_2.setObjectName("checkBoxs3_band_2") self.gridLayout_160.addWidget(self.checkBoxs3_band_2, 1, 1, 1, 1) self.checkBoxs3_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_5.setChecked(True) self.checkBoxs3_band_5.setObjectName("checkBoxs3_band_5") self.gridLayout_160.addWidget(self.checkBoxs3_band_5, 1, 4, 1, 1) self.checkBoxs3_band_8 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_8.setChecked(True) self.checkBoxs3_band_8.setObjectName("checkBoxs3_band_8") self.gridLayout_160.addWidget(self.checkBoxs3_band_8, 1, 7, 1, 1) self.checkBoxs3_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_1.setChecked(True) self.checkBoxs3_band_1.setObjectName("checkBoxs3_band_1") self.gridLayout_160.addWidget(self.checkBoxs3_band_1, 1, 0, 1, 1) self.checkBoxs3_band_16 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_16.setChecked(True) self.checkBoxs3_band_16.setObjectName("checkBoxs3_band_16") self.gridLayout_160.addWidget(self.checkBoxs3_band_16, 2, 4, 1, 1) self.checkBoxs3_band_10 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_10.setChecked(True) self.checkBoxs3_band_10.setObjectName("checkBoxs3_band_10") self.gridLayout_160.addWidget(self.checkBoxs3_band_10, 1, 9, 1, 1) self.checkBoxs3_band_12 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_12.setChecked(True) self.checkBoxs3_band_12.setObjectName("checkBoxs3_band_12") self.gridLayout_160.addWidget(self.checkBoxs3_band_12, 2, 0, 1, 1) self.s3_ancillary_data_checkBox = QtWidgets.QCheckBox(self.tab_options) self.s3_ancillary_data_checkBox.setChecked(True) self.s3_ancillary_data_checkBox.setObjectName("s3_ancillary_data_checkBox") self.gridLayout_160.addWidget(self.s3_ancillary_data_checkBox, 2, 10, 1, 1) self.checkBoxs3_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_3.setChecked(True) self.checkBoxs3_band_3.setObjectName("checkBoxs3_band_3") self.gridLayout_160.addWidget(self.checkBoxs3_band_3, 1, 2, 1, 1) self.label_127 = QtWidgets.QLabel(self.tab_options) self.label_127.setStyleSheet("background-color : #656565; color : white") self.label_127.setFrameShape(QtWidgets.QFrame.Panel) self.label_127.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_127.setObjectName("label_127") self.gridLayout_160.addWidget(self.label_127, 0, 0, 1, 12) self.checkBoxs3_band_20 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_20.setChecked(True) self.checkBoxs3_band_20.setObjectName("checkBoxs3_band_20") self.gridLayout_160.addWidget(self.checkBoxs3_band_20, 2, 8, 1, 1) self.checkBoxs3_band_17 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_17.setChecked(True) self.checkBoxs3_band_17.setObjectName("checkBoxs3_band_17") self.gridLayout_160.addWidget(self.checkBoxs3_band_17, 2, 5, 1, 1) self.checkBoxs3_band_14 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_14.setChecked(True) self.checkBoxs3_band_14.setObjectName("checkBoxs3_band_14") self.gridLayout_160.addWidget(self.checkBoxs3_band_14, 2, 2, 1, 1) self.checkBoxs3_band_9 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_9.setChecked(True) self.checkBoxs3_band_9.setObjectName("checkBoxs3_band_9") self.gridLayout_160.addWidget(self.checkBoxs3_band_9, 1, 8, 1, 1) self.checkBoxs3_band_13 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_13.setChecked(True) self.checkBoxs3_band_13.setObjectName("checkBoxs3_band_13") self.gridLayout_160.addWidget(self.checkBoxs3_band_13, 2, 1, 1, 1) self.checkBoxs3_band_19 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_19.setChecked(True) self.checkBoxs3_band_19.setObjectName("checkBoxs3_band_19") self.gridLayout_160.addWidget(self.checkBoxs3_band_19, 2, 7, 1, 1) self.check_toolButton_3 = QtWidgets.QToolButton(self.tab_options) self.check_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton_3.setIcon(icon56) self.check_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton_3.setObjectName("check_toolButton_3") self.gridLayout_160.addWidget(self.check_toolButton_3, 1, 11, 1, 1) self.checkBoxs3_band_7 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_7.setChecked(True) self.checkBoxs3_band_7.setObjectName("checkBoxs3_band_7") self.gridLayout_160.addWidget(self.checkBoxs3_band_7, 1, 6, 1, 1) self.checkBoxs3_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_4.setChecked(True) self.checkBoxs3_band_4.setObjectName("checkBoxs3_band_4") self.gridLayout_160.addWidget(self.checkBoxs3_band_4, 1, 3, 1, 1) self.checkBoxs3_band_11 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_11.setChecked(True) self.checkBoxs3_band_11.setObjectName("checkBoxs3_band_11") self.gridLayout_160.addWidget(self.checkBoxs3_band_11, 1, 10, 1, 1) self.checkBoxs3_band_15 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_15.setChecked(True) self.checkBoxs3_band_15.setObjectName("checkBoxs3_band_15") self.gridLayout_160.addWidget(self.checkBoxs3_band_15, 2, 3, 1, 1) self.checkBoxs3_band_21 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_21.setChecked(True) self.checkBoxs3_band_21.setObjectName("checkBoxs3_band_21") self.gridLayout_160.addWidget(self.checkBoxs3_band_21, 2, 9, 1, 1) self.checkBoxs3_band_18 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_18.setChecked(True) self.checkBoxs3_band_18.setObjectName("checkBoxs3_band_18") self.gridLayout_160.addWidget(self.checkBoxs3_band_18, 2, 6, 1, 1) self.gridLayout_117.addLayout(self.gridLayout_160, 1, 1, 1, 1) self.gridLayout_141 = QtWidgets.QGridLayout() self.gridLayout_141.setObjectName("gridLayout_141") self.checkBoxs_goes_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_1.setChecked(True) self.checkBoxs_goes_band_1.setObjectName("checkBoxs_goes_band_1") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_1, 1, 0, 1, 1) self.label_272 = QtWidgets.QLabel(self.tab_options) self.label_272.setStyleSheet("background-color : #656565; color : white") self.label_272.setFrameShape(QtWidgets.QFrame.Panel) self.label_272.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_272.setObjectName("label_272") self.gridLayout_141.addWidget(self.label_272, 0, 0, 1, 8) self.checkBoxs_goes_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_5.setChecked(True) self.checkBoxs_goes_band_5.setObjectName("checkBoxs_goes_band_5") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_5, 1, 4, 1, 1) self.checkBoxs_goes_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_3.setChecked(True) self.checkBoxs_goes_band_3.setObjectName("checkBoxs_goes_band_3") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_3, 1, 2, 1, 1) self.checkBoxs_goes_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_4.setChecked(True) self.checkBoxs_goes_band_4.setObjectName("checkBoxs_goes_band_4") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_4, 1, 3, 1, 1) self.checkBoxs_goes_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_2.setChecked(True) self.checkBoxs_goes_band_2.setObjectName("checkBoxs_goes_band_2") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_2, 1, 1, 1, 1) self.checkBoxs_goes_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_6.setChecked(True) self.checkBoxs_goes_band_6.setObjectName("checkBoxs_goes_band_6") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_6, 1, 5, 1, 1) self.check_toolButton_4 = QtWidgets.QToolButton(self.tab_options) self.check_toolButton_4.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton_4.setIcon(icon56) self.check_toolButton_4.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton_4.setObjectName("check_toolButton_4") self.gridLayout_141.addWidget(self.check_toolButton_4, 1, 7, 1, 1) spacerItem32 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_141.addItem(spacerItem32, 1, 6, 1, 1) self.gridLayout_117.addLayout(self.gridLayout_141, 2, 1, 1, 1) self.gridLayout_116.addLayout(self.gridLayout_117, 3, 0, 1, 7) self.checkBox_band_8 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_8.setChecked(True) self.checkBox_band_8.setObjectName("checkBox_band_8") self.gridLayout_116.addWidget(self.checkBox_band_8, 2, 1, 1, 1) self.checkBox_band_10 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_10.setChecked(True) self.checkBox_band_10.setObjectName("checkBox_band_10") self.gridLayout_116.addWidget(self.checkBox_band_10, 2, 3, 1, 1) self.checkBox_band_9 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_9.setChecked(True) self.checkBox_band_9.setObjectName("checkBox_band_9") self.gridLayout_116.addWidget(self.checkBox_band_9, 2, 2, 1, 1) self.checkBox_band_7 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_7.setChecked(True) self.checkBox_band_7.setObjectName("checkBox_band_7") self.gridLayout_116.addWidget(self.checkBox_band_7, 2, 0, 1, 1) self.gridLayout_199.addLayout(self.gridLayout_116, 0, 0, 1, 1) icon80 = QtGui.QIcon() icon80.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_options.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.tabWidget_3.addTab(self.tab_options, icon80, "") self.gridLayout_113.addWidget(self.tabWidget_3, 0, 1, 1, 1) self.gridLayout_68.addLayout(self.gridLayout_113, 0, 0, 1, 1) self.gridLayout_320 = QtWidgets.QGridLayout() self.gridLayout_320.setObjectName("gridLayout_320") self.label_258 = QtWidgets.QLabel(self.tab_download_products) self.label_258.setStyleSheet("background-color : #656565; color : white") self.label_258.setFrameShape(QtWidgets.QFrame.Panel) self.label_258.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_258.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_258.setOpenExternalLinks(True) self.label_258.setObjectName("label_258") self.gridLayout_320.addWidget(self.label_258, 0, 0, 1, 8) self.preprocess_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.preprocess_checkBox.setChecked(True) self.preprocess_checkBox.setObjectName("preprocess_checkBox") self.gridLayout_320.addWidget(self.preprocess_checkBox, 1, 2, 1, 1) self.load_in_QGIS_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.load_in_QGIS_checkBox.setChecked(True) self.load_in_QGIS_checkBox.setObjectName("load_in_QGIS_checkBox") self.gridLayout_320.addWidget(self.load_in_QGIS_checkBox, 1, 3, 1, 1) self.download_if_preview_in_legend_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.download_if_preview_in_legend_checkBox.setChecked(True) self.download_if_preview_in_legend_checkBox.setObjectName("download_if_preview_in_legend_checkBox") self.gridLayout_320.addWidget(self.download_if_preview_in_legend_checkBox, 1, 1, 1, 1) spacerItem33 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_320.addItem(spacerItem33, 1, 5, 1, 1) self.export_links_Button = QtWidgets.QToolButton(self.tab_download_products) self.export_links_Button.setStyleSheet("margin: 0px;padding: 0px;") self.export_links_Button.setIcon(icon53) self.export_links_Button.setIconSize(QtCore.QSize(22, 22)) self.export_links_Button.setObjectName("export_links_Button") self.gridLayout_320.addWidget(self.export_links_Button, 1, 6, 1, 1) self.download_images_Button = QtWidgets.QToolButton(self.tab_download_products) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.download_images_Button.setFont(font) self.download_images_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.download_images_Button.setStyleSheet("margin: 0px;padding: 0px;") self.download_images_Button.setIcon(icon64) self.download_images_Button.setIconSize(QtCore.QSize(34, 34)) self.download_images_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.download_images_Button.setObjectName("download_images_Button") self.gridLayout_320.addWidget(self.download_images_Button, 1, 7, 1, 1) self.virtual_download_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.virtual_download_checkBox.setObjectName("virtual_download_checkBox") self.gridLayout_320.addWidget(self.virtual_download_checkBox, 1, 4, 1, 1) self.gridLayout_68.addLayout(self.gridLayout_320, 1, 0, 1, 1) self.SCP_tabs.addTab(self.tab_download_products, "") self.tab_preprocessing = QtWidgets.QWidget() self.tab_preprocessing.setStyleSheet("") self.tab_preprocessing.setObjectName("tab_preprocessing") self.gridLayout_6 = QtWidgets.QGridLayout(self.tab_preprocessing) self.gridLayout_6.setObjectName("gridLayout_6") self.tabWidget_preprocessing = QtWidgets.QTabWidget(self.tab_preprocessing) self.tabWidget_preprocessing.setStyleSheet("") self.tabWidget_preprocessing.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_preprocessing.setDocumentMode(True) self.tabWidget_preprocessing.setObjectName("tabWidget_preprocessing") self.tab_Landsat = QtWidgets.QWidget() self.tab_Landsat.setObjectName("tab_Landsat") self.gridLayout_18 = QtWidgets.QGridLayout(self.tab_Landsat) self.gridLayout_18.setObjectName("gridLayout_18") self.gridLayout_37 = QtWidgets.QGridLayout() self.gridLayout_37.setObjectName("gridLayout_37") self.label_36 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_36.sizePolicy().hasHeightForWidth()) self.label_36.setSizePolicy(sizePolicy) self.label_36.setMinimumSize(QtCore.QSize(229, 0)) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_36.setFont(font) self.label_36.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_36.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_36.setObjectName("label_36") self.gridLayout_37.addWidget(self.label_36, 1, 0, 1, 1) self.label_37 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_37.sizePolicy().hasHeightForWidth()) self.label_37.setSizePolicy(sizePolicy) self.label_37.setStyleSheet("background-color : #656565; color : white") self.label_37.setFrameShape(QtWidgets.QFrame.Panel) self.label_37.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_37.setObjectName("label_37") self.gridLayout_37.addWidget(self.label_37, 0, 0, 1, 4) self.celsius_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.celsius_checkBox.setChecked(False) self.celsius_checkBox.setTristate(False) self.celsius_checkBox.setObjectName("celsius_checkBox") self.gridLayout_37.addWidget(self.celsius_checkBox, 3, 0, 1, 1) self.DOS1_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.DOS1_checkBox.setChecked(False) self.DOS1_checkBox.setTristate(False) self.DOS1_checkBox.setObjectName("DOS1_checkBox") self.gridLayout_37.addWidget(self.DOS1_checkBox, 4, 0, 1, 1) self.gridLayout_29 = QtWidgets.QGridLayout() self.gridLayout_29.setObjectName("gridLayout_29") self.nodata_spinBox_3 = QtWidgets.QSpinBox(self.tab_Landsat) self.nodata_spinBox_3.setMinimum(-999) self.nodata_spinBox_3.setMaximum(100000) self.nodata_spinBox_3.setObjectName("nodata_spinBox_3") self.gridLayout_29.addWidget(self.nodata_spinBox_3, 0, 2, 1, 1) self.nodata_checkBox_2 = QtWidgets.QCheckBox(self.tab_Landsat) self.nodata_checkBox_2.setChecked(True) self.nodata_checkBox_2.setObjectName("nodata_checkBox_2") self.gridLayout_29.addWidget(self.nodata_checkBox_2, 0, 1, 1, 1) spacerItem34 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_29.addItem(spacerItem34, 0, 0, 1, 1) self.gridLayout_37.addLayout(self.gridLayout_29, 4, 1, 1, 3) self.label_41 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_41.sizePolicy().hasHeightForWidth()) self.label_41.setSizePolicy(sizePolicy) self.label_41.setMinimumSize(QtCore.QSize(229, 0)) self.label_41.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_41.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_41.setObjectName("label_41") self.gridLayout_37.addWidget(self.label_41, 2, 0, 1, 1) self.toolButton_directoryInput = QtWidgets.QToolButton(self.tab_Landsat) self.toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput.setIcon(icon69) self.toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput.setObjectName("toolButton_directoryInput") self.gridLayout_37.addWidget(self.toolButton_directoryInput, 1, 3, 1, 1) self.label_26 = QtWidgets.QLabel(self.tab_Landsat) self.label_26.setFrameShape(QtWidgets.QFrame.Panel) self.label_26.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_26.setText("") self.label_26.setObjectName("label_26") self.gridLayout_37.addWidget(self.label_26, 1, 1, 1, 2) self.label_27 = QtWidgets.QLabel(self.tab_Landsat) self.label_27.setFrameShape(QtWidgets.QFrame.Panel) self.label_27.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_27.setText("") self.label_27.setObjectName("label_27") self.gridLayout_37.addWidget(self.label_27, 2, 1, 1, 2) self.gridLayout_183 = QtWidgets.QGridLayout() self.gridLayout_183.setObjectName("gridLayout_183") self.pansharpening_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.pansharpening_checkBox.setChecked(False) self.pansharpening_checkBox.setTristate(False) self.pansharpening_checkBox.setObjectName("pansharpening_checkBox") self.gridLayout_183.addWidget(self.pansharpening_checkBox, 0, 0, 1, 1) self.create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.create_bandset_checkBox.setChecked(True) self.create_bandset_checkBox.setTristate(False) self.create_bandset_checkBox.setObjectName("create_bandset_checkBox") self.gridLayout_183.addWidget(self.create_bandset_checkBox, 1, 0, 1, 1) self.add_new_bandset_checkBox_1 = QtWidgets.QCheckBox(self.tab_Landsat) self.add_new_bandset_checkBox_1.setChecked(True) self.add_new_bandset_checkBox_1.setTristate(False) self.add_new_bandset_checkBox_1.setObjectName("add_new_bandset_checkBox_1") self.gridLayout_183.addWidget(self.add_new_bandset_checkBox_1, 1, 1, 1, 1) spacerItem35 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_183.addItem(spacerItem35, 1, 2, 1, 1) self.gridLayout_37.addLayout(self.gridLayout_183, 5, 0, 1, 4) self.toolButton_directoryInput_MTL = QtWidgets.QToolButton(self.tab_Landsat) self.toolButton_directoryInput_MTL.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput_MTL.setIcon(icon65) self.toolButton_directoryInput_MTL.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput_MTL.setObjectName("toolButton_directoryInput_MTL") self.gridLayout_37.addWidget(self.toolButton_directoryInput_MTL, 2, 3, 1, 1) self.gridLayout_18.addLayout(self.gridLayout_37, 0, 0, 1, 1) self.gridLayout_95 = QtWidgets.QGridLayout() self.gridLayout_95.setObjectName("gridLayout_95") self.landsat_tableWidget = QtWidgets.QTableWidget(self.tab_Landsat) self.landsat_tableWidget.setObjectName("landsat_tableWidget") self.landsat_tableWidget.setColumnCount(13) self.landsat_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(6, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(7, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(8, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(9, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(10, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(11, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(12, item) self.landsat_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.gridLayout_95.addWidget(self.landsat_tableWidget, 1, 0, 1, 1) self.gridLayout_15 = QtWidgets.QGridLayout() self.gridLayout_15.setObjectName("gridLayout_15") self.pushButton_remove_band = QtWidgets.QToolButton(self.tab_Landsat) self.pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_remove_band.setIcon(icon58) self.pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.pushButton_remove_band.setObjectName("pushButton_remove_band") self.gridLayout_15.addWidget(self.pushButton_remove_band, 0, 0, 1, 1) self.gridLayout_95.addLayout(self.gridLayout_15, 1, 1, 1, 1) self.gridLayout_98 = QtWidgets.QGridLayout() self.gridLayout_98.setObjectName("gridLayout_98") self.satellite_label = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label.sizePolicy().hasHeightForWidth()) self.satellite_label.setSizePolicy(sizePolicy) self.satellite_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label.setObjectName("satellite_label") self.gridLayout_98.addWidget(self.satellite_label, 1, 0, 1, 1) self.satellite_label_3 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_3.sizePolicy().hasHeightForWidth()) self.satellite_label_3.setSizePolicy(sizePolicy) self.satellite_label_3.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_3.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_3.setObjectName("satellite_label_3") self.gridLayout_98.addWidget(self.satellite_label_3, 1, 4, 1, 1) self.date_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.date_lineEdit.setObjectName("date_lineEdit") self.gridLayout_98.addWidget(self.date_lineEdit, 1, 3, 1, 1) self.satellite_label_2 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_2.sizePolicy().hasHeightForWidth()) self.satellite_label_2.setSizePolicy(sizePolicy) self.satellite_label_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_2.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_2.setObjectName("satellite_label_2") self.gridLayout_98.addWidget(self.satellite_label_2, 1, 2, 1, 1) self.satellite_label_4 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_4.sizePolicy().hasHeightForWidth()) self.satellite_label_4.setSizePolicy(sizePolicy) self.satellite_label_4.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_4.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_4.setObjectName("satellite_label_4") self.gridLayout_98.addWidget(self.satellite_label_4, 1, 6, 1, 1) self.sun_elev_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.sun_elev_lineEdit.setObjectName("sun_elev_lineEdit") self.gridLayout_98.addWidget(self.sun_elev_lineEdit, 1, 5, 1, 1) self.earth_sun_dist_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.earth_sun_dist_lineEdit.setObjectName("earth_sun_dist_lineEdit") self.gridLayout_98.addWidget(self.earth_sun_dist_lineEdit, 1, 7, 1, 1) self.label_74 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_74.sizePolicy().hasHeightForWidth()) self.label_74.setSizePolicy(sizePolicy) self.label_74.setStyleSheet("background-color : #656565; color : white") self.label_74.setFrameShape(QtWidgets.QFrame.Panel) self.label_74.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_74.setObjectName("label_74") self.gridLayout_98.addWidget(self.label_74, 0, 0, 1, 9) self.satellite_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.satellite_lineEdit.setObjectName("satellite_lineEdit") self.gridLayout_98.addWidget(self.satellite_lineEdit, 1, 1, 1, 1) self.gridLayout_95.addLayout(self.gridLayout_98, 0, 0, 1, 2) self.gridLayout_18.addLayout(self.gridLayout_95, 1, 0, 1, 1) self.gridLayout_97 = QtWidgets.QGridLayout() self.gridLayout_97.setObjectName("gridLayout_97") spacerItem36 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_97.addItem(spacerItem36, 1, 1, 1, 1) self.label_161 = QtWidgets.QLabel(self.tab_Landsat) self.label_161.setStyleSheet("background-color : #656565; color : white") self.label_161.setFrameShape(QtWidgets.QFrame.Panel) self.label_161.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_161.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_161.setObjectName("label_161") self.gridLayout_97.addWidget(self.label_161, 0, 1, 1, 3) self.pushButton_Conversion = QtWidgets.QToolButton(self.tab_Landsat) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion.setFont(font) self.pushButton_Conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion.setIcon(icon64) self.pushButton_Conversion.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion.setObjectName("pushButton_Conversion") self.gridLayout_97.addWidget(self.pushButton_Conversion, 1, 3, 1, 1) self.landsat_conversion = QtWidgets.QToolButton(self.tab_Landsat) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.landsat_conversion.setFont(font) self.landsat_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.landsat_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.landsat_conversion.setIcon(icon48) self.landsat_conversion.setIconSize(QtCore.QSize(34, 34)) self.landsat_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.landsat_conversion.setObjectName("landsat_conversion") self.gridLayout_97.addWidget(self.landsat_conversion, 1, 2, 1, 1) self.gridLayout_18.addLayout(self.gridLayout_97, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Landsat, "") self.tab_Sentinel1 = QtWidgets.QWidget() self.tab_Sentinel1.setObjectName("tab_Sentinel1") self.gridLayout_167 = QtWidgets.QGridLayout(self.tab_Sentinel1) self.gridLayout_167.setObjectName("gridLayout_167") self.gridLayout_265 = QtWidgets.QGridLayout() self.gridLayout_265.setObjectName("gridLayout_265") self.gridLayout_279 = QtWidgets.QGridLayout() self.gridLayout_279.setObjectName("gridLayout_279") self.S1_label_95 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_95.sizePolicy().hasHeightForWidth()) self.S1_label_95.setSizePolicy(sizePolicy) self.S1_label_95.setMinimumSize(QtCore.QSize(229, 0)) self.S1_label_95.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_95.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.S1_label_95.setObjectName("S1_label_95") self.gridLayout_279.addWidget(self.S1_label_95, 0, 0, 1, 1) self.S1_label_96 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_96.sizePolicy().hasHeightForWidth()) self.S1_label_96.setSizePolicy(sizePolicy) self.S1_label_96.setFrameShape(QtWidgets.QFrame.Panel) self.S1_label_96.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_96.setText("") self.S1_label_96.setObjectName("S1_label_96") self.gridLayout_279.addWidget(self.S1_label_96, 0, 1, 1, 1) self.S1_toolButton_directoryInput_xml = QtWidgets.QToolButton(self.tab_Sentinel1) self.S1_toolButton_directoryInput_xml.setStyleSheet("margin: 0px;padding: 0px;") self.S1_toolButton_directoryInput_xml.setIcon(icon65) self.S1_toolButton_directoryInput_xml.setIconSize(QtCore.QSize(22, 22)) self.S1_toolButton_directoryInput_xml.setObjectName("S1_toolButton_directoryInput_xml") self.gridLayout_279.addWidget(self.S1_toolButton_directoryInput_xml, 0, 2, 1, 1) self.horizontalLayout_48 = QtWidgets.QHBoxLayout() self.horizontalLayout_48.setObjectName("horizontalLayout_48") self.S1_label_97 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_97.sizePolicy().hasHeightForWidth()) self.S1_label_97.setSizePolicy(sizePolicy) self.S1_label_97.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_97.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.S1_label_97.setObjectName("S1_label_97") self.horizontalLayout_48.addWidget(self.S1_label_97) self.VH_checkBox_S1 = QtWidgets.QCheckBox(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.VH_checkBox_S1.sizePolicy().hasHeightForWidth()) self.VH_checkBox_S1.setSizePolicy(sizePolicy) self.VH_checkBox_S1.setChecked(True) self.VH_checkBox_S1.setTristate(False) self.VH_checkBox_S1.setObjectName("VH_checkBox_S1") self.horizontalLayout_48.addWidget(self.VH_checkBox_S1) self.VV_checkBox_S1 = QtWidgets.QCheckBox(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.VV_checkBox_S1.sizePolicy().hasHeightForWidth()) self.VV_checkBox_S1.setSizePolicy(sizePolicy) self.VV_checkBox_S1.setChecked(True) self.VV_checkBox_S1.setTristate(False) self.VV_checkBox_S1.setObjectName("VV_checkBox_S1") self.horizontalLayout_48.addWidget(self.VV_checkBox_S1) self.gridLayout_279.addLayout(self.horizontalLayout_48, 1, 0, 1, 1) self.gridLayout_265.addLayout(self.gridLayout_279, 3, 0, 1, 3) self.label_209 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_209.sizePolicy().hasHeightForWidth()) self.label_209.setSizePolicy(sizePolicy) self.label_209.setStyleSheet("background-color : #656565; color : white") self.label_209.setFrameShape(QtWidgets.QFrame.Panel) self.label_209.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_209.setObjectName("label_209") self.gridLayout_265.addWidget(self.label_209, 0, 0, 1, 3) self.S1_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel1) self.S1_create_bandset_checkBox.setChecked(True) self.S1_create_bandset_checkBox.setTristate(False) self.S1_create_bandset_checkBox.setObjectName("S1_create_bandset_checkBox") self.gridLayout_265.addWidget(self.S1_create_bandset_checkBox, 5, 0, 1, 1) self.add_new_bandset_checkBox_6 = QtWidgets.QCheckBox(self.tab_Sentinel1) self.add_new_bandset_checkBox_6.setChecked(True) self.add_new_bandset_checkBox_6.setTristate(False) self.add_new_bandset_checkBox_6.setObjectName("add_new_bandset_checkBox_6") self.gridLayout_265.addWidget(self.add_new_bandset_checkBox_6, 5, 1, 1, 2) self.gridLayout_266 = QtWidgets.QGridLayout() self.gridLayout_266.setObjectName("gridLayout_266") self.S1_label_87 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_87.sizePolicy().hasHeightForWidth()) self.S1_label_87.setSizePolicy(sizePolicy) self.S1_label_87.setFrameShape(QtWidgets.QFrame.Panel) self.S1_label_87.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_87.setText("") self.S1_label_87.setObjectName("S1_label_87") self.gridLayout_266.addWidget(self.S1_label_87, 0, 1, 1, 1) self.S1_toolButton_fileInput = QtWidgets.QToolButton(self.tab_Sentinel1) self.S1_toolButton_fileInput.setStyleSheet("margin: 0px;padding: 0px;") self.S1_toolButton_fileInput.setIcon(icon65) self.S1_toolButton_fileInput.setIconSize(QtCore.QSize(22, 22)) self.S1_toolButton_fileInput.setObjectName("S1_toolButton_fileInput") self.gridLayout_266.addWidget(self.S1_toolButton_fileInput, 0, 2, 1, 1) self.label_207 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_207.sizePolicy().hasHeightForWidth()) self.label_207.setSizePolicy(sizePolicy) self.label_207.setMinimumSize(QtCore.QSize(229, 0)) self.label_207.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_207.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_207.setObjectName("label_207") self.gridLayout_266.addWidget(self.label_207, 0, 0, 1, 1) self.gridLayout_265.addLayout(self.gridLayout_266, 2, 0, 1, 3) self.horizontalLayout_46 = QtWidgets.QHBoxLayout() self.horizontalLayout_46.setObjectName("horizontalLayout_46") self.projection_checkBox_S1 = QtWidgets.QCheckBox(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.projection_checkBox_S1.sizePolicy().hasHeightForWidth()) self.projection_checkBox_S1.setSizePolicy(sizePolicy) self.projection_checkBox_S1.setTristate(False) self.projection_checkBox_S1.setObjectName("projection_checkBox_S1") self.horizontalLayout_46.addWidget(self.projection_checkBox_S1) self.band_set_comb_spinBox_11 = QtWidgets.QSpinBox(self.tab_Sentinel1) self.band_set_comb_spinBox_11.setMinimum(1) self.band_set_comb_spinBox_11.setMaximum(100000) self.band_set_comb_spinBox_11.setObjectName("band_set_comb_spinBox_11") self.horizontalLayout_46.addWidget(self.band_set_comb_spinBox_11) spacerItem37 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_46.addItem(spacerItem37) self.convert_to_db_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel1) self.convert_to_db_checkBox.setChecked(True) self.convert_to_db_checkBox.setTristate(False) self.convert_to_db_checkBox.setObjectName("convert_to_db_checkBox") self.horizontalLayout_46.addWidget(self.convert_to_db_checkBox) spacerItem38 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_46.addItem(spacerItem38) self.S1_nodata_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel1) self.S1_nodata_checkBox.setChecked(True) self.S1_nodata_checkBox.setObjectName("S1_nodata_checkBox") self.horizontalLayout_46.addWidget(self.S1_nodata_checkBox) self.S1_nodata_spinBox = QtWidgets.QSpinBox(self.tab_Sentinel1) self.S1_nodata_spinBox.setMinimum(-999) self.S1_nodata_spinBox.setMaximum(100000) self.S1_nodata_spinBox.setObjectName("S1_nodata_spinBox") self.horizontalLayout_46.addWidget(self.S1_nodata_spinBox) self.gridLayout_265.addLayout(self.horizontalLayout_46, 4, 0, 1, 3) self.gridLayout_167.addLayout(self.gridLayout_265, 0, 0, 1, 1) spacerItem39 = QtWidgets.QSpacerItem(20, 296, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_167.addItem(spacerItem39, 1, 0, 1, 1) self.gridLayout_268 = QtWidgets.QGridLayout() self.gridLayout_268.setObjectName("gridLayout_268") self.label_210 = QtWidgets.QLabel(self.tab_Sentinel1) self.label_210.setStyleSheet("background-color : #656565; color : white") self.label_210.setFrameShape(QtWidgets.QFrame.Panel) self.label_210.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_210.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_210.setObjectName("label_210") self.gridLayout_268.addWidget(self.label_210, 0, 0, 1, 3) spacerItem40 = QtWidgets.QSpacerItem(782, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_268.addItem(spacerItem40, 1, 0, 1, 1) self.pushButton_Conversion_6 = QtWidgets.QToolButton(self.tab_Sentinel1) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_6.setFont(font) self.pushButton_Conversion_6.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_6.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_6.setIcon(icon64) self.pushButton_Conversion_6.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_6.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_6.setObjectName("pushButton_Conversion_6") self.gridLayout_268.addWidget(self.pushButton_Conversion_6, 1, 2, 1, 1) self.sentinel1_conversion = QtWidgets.QToolButton(self.tab_Sentinel1) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sentinel1_conversion.setFont(font) self.sentinel1_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.sentinel1_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.sentinel1_conversion.setIcon(icon48) self.sentinel1_conversion.setIconSize(QtCore.QSize(34, 34)) self.sentinel1_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sentinel1_conversion.setObjectName("sentinel1_conversion") self.gridLayout_268.addWidget(self.sentinel1_conversion, 1, 1, 1, 1) self.gridLayout_167.addLayout(self.gridLayout_268, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Sentinel1, "") self.tab_Sentinel2 = QtWidgets.QWidget() self.tab_Sentinel2.setObjectName("tab_Sentinel2") self.gridLayout_164 = QtWidgets.QGridLayout(self.tab_Sentinel2) self.gridLayout_164.setObjectName("gridLayout_164") self.gridLayout_146 = QtWidgets.QGridLayout() self.gridLayout_146.setObjectName("gridLayout_146") self.label_90 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_90.sizePolicy().hasHeightForWidth()) self.label_90.setSizePolicy(sizePolicy) self.label_90.setMinimumSize(QtCore.QSize(229, 0)) self.label_90.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_90.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_90.setObjectName("label_90") self.gridLayout_146.addWidget(self.label_90, 1, 0, 1, 1) self.gridLayout_147 = QtWidgets.QGridLayout() self.gridLayout_147.setObjectName("gridLayout_147") self.S2_toolButton_directoryInput = QtWidgets.QToolButton(self.tab_Sentinel2) self.S2_toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.S2_toolButton_directoryInput.setIcon(icon69) self.S2_toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.S2_toolButton_directoryInput.setObjectName("S2_toolButton_directoryInput") self.gridLayout_147.addWidget(self.S2_toolButton_directoryInput, 0, 1, 1, 1) self.S2_label_86 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S2_label_86.sizePolicy().hasHeightForWidth()) self.S2_label_86.setSizePolicy(sizePolicy) self.S2_label_86.setFrameShape(QtWidgets.QFrame.Panel) self.S2_label_86.setFrameShadow(QtWidgets.QFrame.Sunken) self.S2_label_86.setText("") self.S2_label_86.setObjectName("S2_label_86") self.gridLayout_147.addWidget(self.S2_label_86, 0, 0, 1, 1) self.gridLayout_146.addLayout(self.gridLayout_147, 1, 1, 1, 2) self.DOS1_checkBox_S2 = QtWidgets.QCheckBox(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.DOS1_checkBox_S2.sizePolicy().hasHeightForWidth()) self.DOS1_checkBox_S2.setSizePolicy(sizePolicy) self.DOS1_checkBox_S2.setChecked(False) self.DOS1_checkBox_S2.setTristate(False) self.DOS1_checkBox_S2.setObjectName("DOS1_checkBox_S2") self.gridLayout_146.addWidget(self.DOS1_checkBox_S2, 3, 0, 1, 1) self.gridLayout_148 = QtWidgets.QGridLayout() self.gridLayout_148.setObjectName("gridLayout_148") self.S2_nodata_spinBox = QtWidgets.QSpinBox(self.tab_Sentinel2) self.S2_nodata_spinBox.setMinimum(-999) self.S2_nodata_spinBox.setMaximum(100000) self.S2_nodata_spinBox.setObjectName("S2_nodata_spinBox") self.gridLayout_148.addWidget(self.S2_nodata_spinBox, 0, 2, 1, 1) self.S2_nodata_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel2) self.S2_nodata_checkBox.setChecked(True) self.S2_nodata_checkBox.setObjectName("S2_nodata_checkBox") self.gridLayout_148.addWidget(self.S2_nodata_checkBox, 0, 1, 1, 1) spacerItem41 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_148.addItem(spacerItem41, 0, 0, 1, 1) self.gridLayout_146.addLayout(self.gridLayout_148, 3, 1, 1, 2) self.label_91 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_91.sizePolicy().hasHeightForWidth()) self.label_91.setSizePolicy(sizePolicy) self.label_91.setStyleSheet("background-color : #656565; color : white") self.label_91.setFrameShape(QtWidgets.QFrame.Panel) self.label_91.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_91.setObjectName("label_91") self.gridLayout_146.addWidget(self.label_91, 0, 0, 1, 3) self.S2_label_93 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S2_label_93.sizePolicy().hasHeightForWidth()) self.S2_label_93.setSizePolicy(sizePolicy) self.S2_label_93.setMinimumSize(QtCore.QSize(229, 0)) self.S2_label_93.setFrameShadow(QtWidgets.QFrame.Sunken) self.S2_label_93.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.S2_label_93.setObjectName("S2_label_93") self.gridLayout_146.addWidget(self.S2_label_93, 2, 0, 1, 1) self.gridLayout_156 = QtWidgets.QGridLayout() self.gridLayout_156.setObjectName("gridLayout_156") self.S2_label_94 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S2_label_94.sizePolicy().hasHeightForWidth()) self.S2_label_94.setSizePolicy(sizePolicy) self.S2_label_94.setFrameShape(QtWidgets.QFrame.Panel) self.S2_label_94.setFrameShadow(QtWidgets.QFrame.Sunken) self.S2_label_94.setText("") self.S2_label_94.setObjectName("S2_label_94") self.gridLayout_156.addWidget(self.S2_label_94, 0, 0, 1, 1) self.S2_toolButton_directoryInput_xml2 = QtWidgets.QToolButton(self.tab_Sentinel2) self.S2_toolButton_directoryInput_xml2.setStyleSheet("margin: 0px;padding: 0px;") self.S2_toolButton_directoryInput_xml2.setIcon(icon65) self.S2_toolButton_directoryInput_xml2.setIconSize(QtCore.QSize(22, 22)) self.S2_toolButton_directoryInput_xml2.setObjectName("S2_toolButton_directoryInput_xml2") self.gridLayout_156.addWidget(self.S2_toolButton_directoryInput_xml2, 0, 1, 1, 1) self.gridLayout_146.addLayout(self.gridLayout_156, 2, 1, 1, 2) self.S2_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel2) self.S2_create_bandset_checkBox.setChecked(True) self.S2_create_bandset_checkBox.setTristate(False) self.S2_create_bandset_checkBox.setObjectName("S2_create_bandset_checkBox") self.gridLayout_146.addWidget(self.S2_create_bandset_checkBox, 5, 0, 1, 1) self.add_new_bandset_checkBox_2 = QtWidgets.QCheckBox(self.tab_Sentinel2) self.add_new_bandset_checkBox_2.setChecked(True) self.add_new_bandset_checkBox_2.setTristate(False) self.add_new_bandset_checkBox_2.setObjectName("add_new_bandset_checkBox_2") self.gridLayout_146.addWidget(self.add_new_bandset_checkBox_2, 5, 1, 1, 2) self.preprocess_b_1_9_10_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel2) self.preprocess_b_1_9_10_checkBox.setTristate(False) self.preprocess_b_1_9_10_checkBox.setObjectName("preprocess_b_1_9_10_checkBox") self.gridLayout_146.addWidget(self.preprocess_b_1_9_10_checkBox, 4, 0, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_146, 0, 0, 1, 1) self.gridLayout_166 = QtWidgets.QGridLayout() self.gridLayout_166.setObjectName("gridLayout_166") self.S2_satellite_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel2) self.S2_satellite_lineEdit.setObjectName("S2_satellite_lineEdit") self.gridLayout_166.addWidget(self.S2_satellite_lineEdit, 1, 1, 1, 1) self.satellite_label_5 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_5.sizePolicy().hasHeightForWidth()) self.satellite_label_5.setSizePolicy(sizePolicy) self.satellite_label_5.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_5.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_5.setObjectName("satellite_label_5") self.gridLayout_166.addWidget(self.satellite_label_5, 1, 0, 1, 1) spacerItem42 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_166.addItem(spacerItem42, 1, 2, 1, 1) self.satellite_label_6 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_6.sizePolicy().hasHeightForWidth()) self.satellite_label_6.setSizePolicy(sizePolicy) self.satellite_label_6.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_6.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_6.setObjectName("satellite_label_6") self.gridLayout_166.addWidget(self.satellite_label_6, 1, 7, 1, 1) self.S2_product_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel2) self.S2_product_lineEdit.setObjectName("S2_product_lineEdit") self.gridLayout_166.addWidget(self.S2_product_lineEdit, 1, 8, 1, 1) self.label_92 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_92.sizePolicy().hasHeightForWidth()) self.label_92.setSizePolicy(sizePolicy) self.label_92.setStyleSheet("background-color : #656565; color : white") self.label_92.setFrameShape(QtWidgets.QFrame.Panel) self.label_92.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_92.setObjectName("label_92") self.gridLayout_166.addWidget(self.label_92, 0, 0, 1, 9) self.date_lineEdit_3 = QtWidgets.QLineEdit(self.tab_Sentinel2) self.date_lineEdit_3.setObjectName("date_lineEdit_3") self.gridLayout_166.addWidget(self.date_lineEdit_3, 1, 4, 1, 1) spacerItem43 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_166.addItem(spacerItem43, 1, 6, 1, 1) self.satellite_label_15 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_15.sizePolicy().hasHeightForWidth()) self.satellite_label_15.setSizePolicy(sizePolicy) self.satellite_label_15.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_15.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_15.setObjectName("satellite_label_15") self.gridLayout_166.addWidget(self.satellite_label_15, 1, 3, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_166, 1, 0, 1, 1) self.gridLayout_162 = QtWidgets.QGridLayout() self.gridLayout_162.setObjectName("gridLayout_162") self.sentinel_2_tableWidget = QtWidgets.QTableWidget(self.tab_Sentinel2) self.sentinel_2_tableWidget.setTextElideMode(QtCore.Qt.ElideMiddle) self.sentinel_2_tableWidget.setObjectName("sentinel_2_tableWidget") self.sentinel_2_tableWidget.setColumnCount(3) self.sentinel_2_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.sentinel_2_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.sentinel_2_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.sentinel_2_tableWidget.setHorizontalHeaderItem(2, item) self.sentinel_2_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.sentinel_2_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_162.addWidget(self.sentinel_2_tableWidget, 0, 0, 1, 1) self.S2_pushButton_remove_band = QtWidgets.QToolButton(self.tab_Sentinel2) self.S2_pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.S2_pushButton_remove_band.setIcon(icon58) self.S2_pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.S2_pushButton_remove_band.setObjectName("S2_pushButton_remove_band") self.gridLayout_162.addWidget(self.S2_pushButton_remove_band, 0, 1, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_162, 2, 0, 1, 1) self.gridLayout_165 = QtWidgets.QGridLayout() self.gridLayout_165.setObjectName("gridLayout_165") spacerItem44 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_165.addItem(spacerItem44, 1, 1, 1, 1) self.label_162 = QtWidgets.QLabel(self.tab_Sentinel2) self.label_162.setStyleSheet("background-color : #656565; color : white") self.label_162.setFrameShape(QtWidgets.QFrame.Panel) self.label_162.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_162.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_162.setObjectName("label_162") self.gridLayout_165.addWidget(self.label_162, 0, 1, 1, 3) self.pushButton_Conversion_2 = QtWidgets.QToolButton(self.tab_Sentinel2) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_2.setFont(font) self.pushButton_Conversion_2.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_2.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_2.setIcon(icon64) self.pushButton_Conversion_2.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_2.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_2.setObjectName("pushButton_Conversion_2") self.gridLayout_165.addWidget(self.pushButton_Conversion_2, 1, 3, 1, 1) self.sentinel2_conversion = QtWidgets.QToolButton(self.tab_Sentinel2) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sentinel2_conversion.setFont(font) self.sentinel2_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.sentinel2_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.sentinel2_conversion.setIcon(icon48) self.sentinel2_conversion.setIconSize(QtCore.QSize(34, 34)) self.sentinel2_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sentinel2_conversion.setObjectName("sentinel2_conversion") self.gridLayout_165.addWidget(self.sentinel2_conversion, 1, 2, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_165, 3, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Sentinel2, "") self.tab_Sentinel3 = QtWidgets.QWidget() self.tab_Sentinel3.setObjectName("tab_Sentinel3") self.gridLayout_158 = QtWidgets.QGridLayout(self.tab_Sentinel3) self.gridLayout_158.setObjectName("gridLayout_158") self.gridLayout_153 = QtWidgets.QGridLayout() self.gridLayout_153.setObjectName("gridLayout_153") self.gridLayout_157 = QtWidgets.QGridLayout() self.gridLayout_157.setObjectName("gridLayout_157") self.S2_nodata_spinBox_2 = QtWidgets.QSpinBox(self.tab_Sentinel3) self.S2_nodata_spinBox_2.setMinimum(-999) self.S2_nodata_spinBox_2.setMaximum(100000) self.S2_nodata_spinBox_2.setObjectName("S2_nodata_spinBox_2") self.gridLayout_157.addWidget(self.S2_nodata_spinBox_2, 0, 2, 1, 1) self.S3_nodata_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel3) self.S3_nodata_checkBox.setChecked(True) self.S3_nodata_checkBox.setObjectName("S3_nodata_checkBox") self.gridLayout_157.addWidget(self.S3_nodata_checkBox, 0, 1, 1, 1) spacerItem45 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_157.addItem(spacerItem45, 0, 0, 1, 1) self.gridLayout_153.addLayout(self.gridLayout_157, 3, 1, 1, 2) self.label_109 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_109.sizePolicy().hasHeightForWidth()) self.label_109.setSizePolicy(sizePolicy) self.label_109.setStyleSheet("background-color : #656565; color : white") self.label_109.setFrameShape(QtWidgets.QFrame.Panel) self.label_109.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_109.setObjectName("label_109") self.gridLayout_153.addWidget(self.label_109, 0, 0, 1, 3) self.S3_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel3) self.S3_create_bandset_checkBox.setChecked(True) self.S3_create_bandset_checkBox.setTristate(False) self.S3_create_bandset_checkBox.setObjectName("S3_create_bandset_checkBox") self.gridLayout_153.addWidget(self.S3_create_bandset_checkBox, 4, 0, 1, 1) self.label_106 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_106.sizePolicy().hasHeightForWidth()) self.label_106.setSizePolicy(sizePolicy) self.label_106.setMinimumSize(QtCore.QSize(229, 0)) self.label_106.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_106.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_106.setObjectName("label_106") self.gridLayout_153.addWidget(self.label_106, 2, 0, 1, 1) self.gridLayout_155 = QtWidgets.QGridLayout() self.gridLayout_155.setObjectName("gridLayout_155") self.S3_toolButton_directoryInput = QtWidgets.QToolButton(self.tab_Sentinel3) self.S3_toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.S3_toolButton_directoryInput.setIcon(icon69) self.S3_toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.S3_toolButton_directoryInput.setObjectName("S3_toolButton_directoryInput") self.gridLayout_155.addWidget(self.S3_toolButton_directoryInput, 0, 1, 1, 1) self.S3_label_87 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S3_label_87.sizePolicy().hasHeightForWidth()) self.S3_label_87.setSizePolicy(sizePolicy) self.S3_label_87.setFrameShape(QtWidgets.QFrame.Panel) self.S3_label_87.setFrameShadow(QtWidgets.QFrame.Sunken) self.S3_label_87.setText("") self.S3_label_87.setObjectName("S3_label_87") self.gridLayout_155.addWidget(self.S3_label_87, 0, 0, 1, 1) self.gridLayout_153.addLayout(self.gridLayout_155, 2, 1, 1, 2) self.DOS1_checkBox_S3 = QtWidgets.QCheckBox(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.DOS1_checkBox_S3.sizePolicy().hasHeightForWidth()) self.DOS1_checkBox_S3.setSizePolicy(sizePolicy) self.DOS1_checkBox_S3.setChecked(False) self.DOS1_checkBox_S3.setTristate(False) self.DOS1_checkBox_S3.setObjectName("DOS1_checkBox_S3") self.gridLayout_153.addWidget(self.DOS1_checkBox_S3, 3, 0, 1, 1) self.add_new_bandset_checkBox_3 = QtWidgets.QCheckBox(self.tab_Sentinel3) self.add_new_bandset_checkBox_3.setChecked(True) self.add_new_bandset_checkBox_3.setTristate(False) self.add_new_bandset_checkBox_3.setObjectName("add_new_bandset_checkBox_3") self.gridLayout_153.addWidget(self.add_new_bandset_checkBox_3, 4, 1, 1, 2) self.gridLayout_158.addLayout(self.gridLayout_153, 0, 0, 1, 1) self.gridLayout_212 = QtWidgets.QGridLayout() self.gridLayout_212.setObjectName("gridLayout_212") self.sentinel_3_tableWidget = QtWidgets.QTableWidget(self.tab_Sentinel3) self.sentinel_3_tableWidget.setTextElideMode(QtCore.Qt.ElideMiddle) self.sentinel_3_tableWidget.setObjectName("sentinel_3_tableWidget") self.sentinel_3_tableWidget.setColumnCount(1) self.sentinel_3_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.sentinel_3_tableWidget.setHorizontalHeaderItem(0, item) self.sentinel_3_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.sentinel_3_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_212.addWidget(self.sentinel_3_tableWidget, 1, 0, 1, 1) self.gridLayout_229 = QtWidgets.QGridLayout() self.gridLayout_229.setObjectName("gridLayout_229") self.S3_pushButton_remove_band = QtWidgets.QToolButton(self.tab_Sentinel3) self.S3_pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.S3_pushButton_remove_band.setIcon(icon58) self.S3_pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.S3_pushButton_remove_band.setObjectName("S3_pushButton_remove_band") self.gridLayout_229.addWidget(self.S3_pushButton_remove_band, 0, 0, 1, 1) self.gridLayout_212.addLayout(self.gridLayout_229, 1, 1, 1, 1) self.gridLayout_230 = QtWidgets.QGridLayout() self.gridLayout_230.setObjectName("gridLayout_230") self.S3_satellite_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel3) self.S3_satellite_lineEdit.setObjectName("S3_satellite_lineEdit") self.gridLayout_230.addWidget(self.S3_satellite_lineEdit, 1, 1, 1, 1) self.satellite_label_12 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_12.sizePolicy().hasHeightForWidth()) self.satellite_label_12.setSizePolicy(sizePolicy) self.satellite_label_12.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_12.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_12.setObjectName("satellite_label_12") self.gridLayout_230.addWidget(self.satellite_label_12, 1, 0, 1, 1) spacerItem46 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_230.addItem(spacerItem46, 1, 2, 1, 1) self.satellite_label_14 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_14.sizePolicy().hasHeightForWidth()) self.satellite_label_14.setSizePolicy(sizePolicy) self.satellite_label_14.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_14.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_14.setObjectName("satellite_label_14") self.gridLayout_230.addWidget(self.satellite_label_14, 1, 3, 1, 1) self.S3_product_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel3) self.S3_product_lineEdit.setObjectName("S3_product_lineEdit") self.gridLayout_230.addWidget(self.S3_product_lineEdit, 1, 4, 1, 1) self.label_115 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_115.sizePolicy().hasHeightForWidth()) self.label_115.setSizePolicy(sizePolicy) self.label_115.setStyleSheet("background-color : #656565; color : white") self.label_115.setFrameShape(QtWidgets.QFrame.Panel) self.label_115.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_115.setObjectName("label_115") self.gridLayout_230.addWidget(self.label_115, 0, 0, 1, 5) self.gridLayout_212.addLayout(self.gridLayout_230, 0, 0, 1, 2) self.gridLayout_232 = QtWidgets.QGridLayout() self.gridLayout_232.setObjectName("gridLayout_232") spacerItem47 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_232.addItem(spacerItem47, 1, 1, 1, 1) self.label_181 = QtWidgets.QLabel(self.tab_Sentinel3) self.label_181.setStyleSheet("background-color : #656565; color : white") self.label_181.setFrameShape(QtWidgets.QFrame.Panel) self.label_181.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_181.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_181.setObjectName("label_181") self.gridLayout_232.addWidget(self.label_181, 0, 1, 1, 3) self.pushButton_Conversion_5 = QtWidgets.QToolButton(self.tab_Sentinel3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_5.setFont(font) self.pushButton_Conversion_5.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_5.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_5.setIcon(icon64) self.pushButton_Conversion_5.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_5.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_5.setObjectName("pushButton_Conversion_5") self.gridLayout_232.addWidget(self.pushButton_Conversion_5, 1, 3, 1, 1) self.sentinel3_conversion = QtWidgets.QToolButton(self.tab_Sentinel3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sentinel3_conversion.setFont(font) self.sentinel3_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.sentinel3_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.sentinel3_conversion.setIcon(icon48) self.sentinel3_conversion.setIconSize(QtCore.QSize(34, 34)) self.sentinel3_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sentinel3_conversion.setObjectName("sentinel3_conversion") self.gridLayout_232.addWidget(self.sentinel3_conversion, 1, 2, 1, 1) self.gridLayout_212.addLayout(self.gridLayout_232, 2, 0, 1, 2) self.gridLayout_158.addLayout(self.gridLayout_212, 1, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Sentinel3, "") self.tab_ASTER = QtWidgets.QWidget() self.tab_ASTER.setObjectName("tab_ASTER") self.gridLayout_118 = QtWidgets.QGridLayout(self.tab_ASTER) self.gridLayout_118.setObjectName("gridLayout_118") self.gridLayout_92 = QtWidgets.QGridLayout() self.gridLayout_92.setObjectName("gridLayout_92") self.gridLayout_94 = QtWidgets.QGridLayout() self.gridLayout_94.setObjectName("gridLayout_94") self.nodata_spinBox_6 = QtWidgets.QSpinBox(self.tab_ASTER) self.nodata_spinBox_6.setMinimum(-999) self.nodata_spinBox_6.setMaximum(100000) self.nodata_spinBox_6.setObjectName("nodata_spinBox_6") self.gridLayout_94.addWidget(self.nodata_spinBox_6, 0, 2, 1, 1) self.nodata_checkBox_5 = QtWidgets.QCheckBox(self.tab_ASTER) self.nodata_checkBox_5.setChecked(True) self.nodata_checkBox_5.setObjectName("nodata_checkBox_5") self.gridLayout_94.addWidget(self.nodata_checkBox_5, 0, 1, 1, 1) spacerItem48 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_94.addItem(spacerItem48, 0, 0, 1, 1) self.gridLayout_92.addLayout(self.gridLayout_94, 3, 1, 1, 3) self.label_143 = QtWidgets.QLabel(self.tab_ASTER) self.label_143.setFrameShape(QtWidgets.QFrame.Panel) self.label_143.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_143.setText("") self.label_143.setObjectName("label_143") self.gridLayout_92.addWidget(self.label_143, 1, 1, 1, 2) self.toolButton_directoryInput_ASTER = QtWidgets.QToolButton(self.tab_ASTER) self.toolButton_directoryInput_ASTER.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput_ASTER.setIcon(icon65) self.toolButton_directoryInput_ASTER.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput_ASTER.setObjectName("toolButton_directoryInput_ASTER") self.gridLayout_92.addWidget(self.toolButton_directoryInput_ASTER, 1, 3, 1, 1) self.DOS1_checkBox_2 = QtWidgets.QCheckBox(self.tab_ASTER) self.DOS1_checkBox_2.setChecked(False) self.DOS1_checkBox_2.setTristate(False) self.DOS1_checkBox_2.setObjectName("DOS1_checkBox_2") self.gridLayout_92.addWidget(self.DOS1_checkBox_2, 3, 0, 1, 1) self.label_67 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_67.sizePolicy().hasHeightForWidth()) self.label_67.setSizePolicy(sizePolicy) self.label_67.setStyleSheet("background-color : #656565; color : white") self.label_67.setFrameShape(QtWidgets.QFrame.Panel) self.label_67.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_67.setObjectName("label_67") self.gridLayout_92.addWidget(self.label_67, 0, 0, 1, 4) self.label_55 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_55.sizePolicy().hasHeightForWidth()) self.label_55.setSizePolicy(sizePolicy) self.label_55.setMinimumSize(QtCore.QSize(229, 0)) self.label_55.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_55.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_55.setObjectName("label_55") self.gridLayout_92.addWidget(self.label_55, 1, 0, 1, 1) self.gridLayout_221 = QtWidgets.QGridLayout() self.gridLayout_221.setObjectName("gridLayout_221") self.create_bandset_checkBox_2 = QtWidgets.QCheckBox(self.tab_ASTER) self.create_bandset_checkBox_2.setChecked(True) self.create_bandset_checkBox_2.setTristate(False) self.create_bandset_checkBox_2.setObjectName("create_bandset_checkBox_2") self.gridLayout_221.addWidget(self.create_bandset_checkBox_2, 0, 0, 1, 1) self.add_new_bandset_checkBox_4 = QtWidgets.QCheckBox(self.tab_ASTER) self.add_new_bandset_checkBox_4.setChecked(True) self.add_new_bandset_checkBox_4.setTristate(False) self.add_new_bandset_checkBox_4.setObjectName("add_new_bandset_checkBox_4") self.gridLayout_221.addWidget(self.add_new_bandset_checkBox_4, 0, 1, 1, 1) spacerItem49 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_221.addItem(spacerItem49, 0, 2, 1, 1) self.gridLayout_92.addLayout(self.gridLayout_221, 4, 0, 1, 4) self.celsius_checkBox_2 = QtWidgets.QCheckBox(self.tab_ASTER) self.celsius_checkBox_2.setChecked(False) self.celsius_checkBox_2.setTristate(False) self.celsius_checkBox_2.setObjectName("celsius_checkBox_2") self.gridLayout_92.addWidget(self.celsius_checkBox_2, 2, 0, 1, 3) self.gridLayout_118.addLayout(self.gridLayout_92, 0, 0, 1, 1) self.gridLayout_96 = QtWidgets.QGridLayout() self.gridLayout_96.setObjectName("gridLayout_96") self.ASTER_tableWidget = QtWidgets.QTableWidget(self.tab_ASTER) self.ASTER_tableWidget.setObjectName("ASTER_tableWidget") self.ASTER_tableWidget.setColumnCount(3) self.ASTER_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.ASTER_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.ASTER_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.ASTER_tableWidget.setHorizontalHeaderItem(2, item) self.ASTER_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.ASTER_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_96.addWidget(self.ASTER_tableWidget, 1, 0, 1, 1) self.gridLayout_222 = QtWidgets.QGridLayout() self.gridLayout_222.setObjectName("gridLayout_222") self.pushButton_remove_band_2 = QtWidgets.QToolButton(self.tab_ASTER) self.pushButton_remove_band_2.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_remove_band_2.setIcon(icon58) self.pushButton_remove_band_2.setIconSize(QtCore.QSize(22, 22)) self.pushButton_remove_band_2.setObjectName("pushButton_remove_band_2") self.gridLayout_222.addWidget(self.pushButton_remove_band_2, 0, 0, 1, 1) self.gridLayout_96.addLayout(self.gridLayout_222, 1, 1, 1, 1) self.gridLayout_223 = QtWidgets.QGridLayout() self.gridLayout_223.setObjectName("gridLayout_223") self.date_lineEdit_2 = QtWidgets.QLineEdit(self.tab_ASTER) self.date_lineEdit_2.setObjectName("date_lineEdit_2") self.gridLayout_223.addWidget(self.date_lineEdit_2, 1, 2, 1, 1) self.earth_sun_dist_lineEdit_2 = QtWidgets.QLineEdit(self.tab_ASTER) self.earth_sun_dist_lineEdit_2.setObjectName("earth_sun_dist_lineEdit_2") self.gridLayout_223.addWidget(self.earth_sun_dist_lineEdit_2, 1, 6, 1, 1) self.satellite_label_9 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_9.sizePolicy().hasHeightForWidth()) self.satellite_label_9.setSizePolicy(sizePolicy) self.satellite_label_9.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_9.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_9.setObjectName("satellite_label_9") self.gridLayout_223.addWidget(self.satellite_label_9, 1, 5, 1, 1) self.satellite_label_8 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_8.sizePolicy().hasHeightForWidth()) self.satellite_label_8.setSizePolicy(sizePolicy) self.satellite_label_8.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_8.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_8.setObjectName("satellite_label_8") self.gridLayout_223.addWidget(self.satellite_label_8, 1, 1, 1, 1) self.satellite_label_7 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_7.sizePolicy().hasHeightForWidth()) self.satellite_label_7.setSizePolicy(sizePolicy) self.satellite_label_7.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_7.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_7.setObjectName("satellite_label_7") self.gridLayout_223.addWidget(self.satellite_label_7, 1, 3, 1, 1) self.sun_elev_lineEdit_2 = QtWidgets.QLineEdit(self.tab_ASTER) self.sun_elev_lineEdit_2.setObjectName("sun_elev_lineEdit_2") self.gridLayout_223.addWidget(self.sun_elev_lineEdit_2, 1, 4, 1, 1) self.ulm_lineEdit = QtWidgets.QLineEdit(self.tab_ASTER) self.ulm_lineEdit.setObjectName("ulm_lineEdit") self.gridLayout_223.addWidget(self.ulm_lineEdit, 1, 10, 1, 1) self.satellite_label_10 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_10.sizePolicy().hasHeightForWidth()) self.satellite_label_10.setSizePolicy(sizePolicy) self.satellite_label_10.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_10.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_10.setObjectName("satellite_label_10") self.gridLayout_223.addWidget(self.satellite_label_10, 1, 7, 1, 1) self.utm_zone_lineEdit = QtWidgets.QLineEdit(self.tab_ASTER) self.utm_zone_lineEdit.setObjectName("utm_zone_lineEdit") self.gridLayout_223.addWidget(self.utm_zone_lineEdit, 1, 8, 1, 1) self.satellite_label_11 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_11.sizePolicy().hasHeightForWidth()) self.satellite_label_11.setSizePolicy(sizePolicy) self.satellite_label_11.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_11.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_11.setObjectName("satellite_label_11") self.gridLayout_223.addWidget(self.satellite_label_11, 1, 9, 1, 1) self.satellite_label_17 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_17.sizePolicy().hasHeightForWidth()) self.satellite_label_17.setSizePolicy(sizePolicy) self.satellite_label_17.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_17.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_17.setObjectName("satellite_label_17") self.gridLayout_223.addWidget(self.satellite_label_17, 1, 11, 1, 1) self.lrm_lineEdit = QtWidgets.QLineEdit(self.tab_ASTER) self.lrm_lineEdit.setObjectName("lrm_lineEdit") self.gridLayout_223.addWidget(self.lrm_lineEdit, 1, 12, 1, 1) self.label_160 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_160.sizePolicy().hasHeightForWidth()) self.label_160.setSizePolicy(sizePolicy) self.label_160.setStyleSheet("background-color : #656565; color : white") self.label_160.setFrameShape(QtWidgets.QFrame.Panel) self.label_160.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_160.setObjectName("label_160") self.gridLayout_223.addWidget(self.label_160, 0, 0, 1, 13) self.gridLayout_96.addLayout(self.gridLayout_223, 0, 0, 1, 2) self.gridLayout_118.addLayout(self.gridLayout_96, 1, 0, 1, 1) self.gridLayout_224 = QtWidgets.QGridLayout() self.gridLayout_224.setObjectName("gridLayout_224") spacerItem50 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_224.addItem(spacerItem50, 1, 1, 1, 1) self.label_163 = QtWidgets.QLabel(self.tab_ASTER) self.label_163.setStyleSheet("background-color : #656565; color : white") self.label_163.setFrameShape(QtWidgets.QFrame.Panel) self.label_163.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_163.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_163.setObjectName("label_163") self.gridLayout_224.addWidget(self.label_163, 0, 1, 1, 3) self.pushButton_Conversion_3 = QtWidgets.QToolButton(self.tab_ASTER) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_3.setFont(font) self.pushButton_Conversion_3.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_3.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_3.setIcon(icon64) self.pushButton_Conversion_3.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_3.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_3.setObjectName("pushButton_Conversion_3") self.gridLayout_224.addWidget(self.pushButton_Conversion_3, 1, 3, 1, 1) self.aster_conversion = QtWidgets.QToolButton(self.tab_ASTER) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.aster_conversion.setFont(font) self.aster_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.aster_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.aster_conversion.setIcon(icon48) self.aster_conversion.setIconSize(QtCore.QSize(34, 34)) self.aster_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.aster_conversion.setObjectName("aster_conversion") self.gridLayout_224.addWidget(self.aster_conversion, 1, 2, 1, 1) self.gridLayout_118.addLayout(self.gridLayout_224, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_ASTER, "") self.tab_MODIS = QtWidgets.QWidget() self.tab_MODIS.setObjectName("tab_MODIS") self.gridLayout_70 = QtWidgets.QGridLayout(self.tab_MODIS) self.gridLayout_70.setObjectName("gridLayout_70") self.gridLayout_270 = QtWidgets.QGridLayout() self.gridLayout_270.setObjectName("gridLayout_270") self.label_218 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_218.sizePolicy().hasHeightForWidth()) self.label_218.setSizePolicy(sizePolicy) self.label_218.setStyleSheet("background-color : #656565; color : white") self.label_218.setFrameShape(QtWidgets.QFrame.Panel) self.label_218.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_218.setObjectName("label_218") self.gridLayout_270.addWidget(self.label_218, 0, 0, 1, 4) self.label_217 = QtWidgets.QLabel(self.tab_MODIS) self.label_217.setFrameShape(QtWidgets.QFrame.Panel) self.label_217.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_217.setText("") self.label_217.setObjectName("label_217") self.gridLayout_270.addWidget(self.label_217, 2, 1, 1, 2) self.gridLayout_272 = QtWidgets.QGridLayout() self.gridLayout_272.setObjectName("gridLayout_272") self.create_bandset_checkBox_3 = QtWidgets.QCheckBox(self.tab_MODIS) self.create_bandset_checkBox_3.setChecked(True) self.create_bandset_checkBox_3.setTristate(False) self.create_bandset_checkBox_3.setObjectName("create_bandset_checkBox_3") self.gridLayout_272.addWidget(self.create_bandset_checkBox_3, 0, 0, 1, 1) self.add_new_bandset_checkBox_5 = QtWidgets.QCheckBox(self.tab_MODIS) self.add_new_bandset_checkBox_5.setChecked(True) self.add_new_bandset_checkBox_5.setTristate(False) self.add_new_bandset_checkBox_5.setObjectName("add_new_bandset_checkBox_5") self.gridLayout_272.addWidget(self.add_new_bandset_checkBox_5, 0, 1, 1, 1) spacerItem51 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_272.addItem(spacerItem51, 0, 2, 1, 1) self.gridLayout_270.addLayout(self.gridLayout_272, 4, 0, 1, 4) self.label_219 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_219.sizePolicy().hasHeightForWidth()) self.label_219.setSizePolicy(sizePolicy) self.label_219.setMinimumSize(QtCore.QSize(229, 0)) self.label_219.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_219.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_219.setObjectName("label_219") self.gridLayout_270.addWidget(self.label_219, 2, 0, 1, 1) self.toolButton_directoryInput_MODIS = QtWidgets.QToolButton(self.tab_MODIS) self.toolButton_directoryInput_MODIS.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput_MODIS.setIcon(icon65) self.toolButton_directoryInput_MODIS.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput_MODIS.setObjectName("toolButton_directoryInput_MODIS") self.gridLayout_270.addWidget(self.toolButton_directoryInput_MODIS, 2, 3, 1, 1) self.gridLayout_271 = QtWidgets.QGridLayout() self.gridLayout_271.setObjectName("gridLayout_271") self.nodata_spinBox_8 = QtWidgets.QSpinBox(self.tab_MODIS) self.nodata_spinBox_8.setMinimum(-100000) self.nodata_spinBox_8.setMaximum(100000) self.nodata_spinBox_8.setProperty("value", -999) self.nodata_spinBox_8.setObjectName("nodata_spinBox_8") self.gridLayout_271.addWidget(self.nodata_spinBox_8, 0, 2, 1, 1) self.nodata_checkBox_7 = QtWidgets.QCheckBox(self.tab_MODIS) self.nodata_checkBox_7.setChecked(True) self.nodata_checkBox_7.setObjectName("nodata_checkBox_7") self.gridLayout_271.addWidget(self.nodata_checkBox_7, 0, 1, 1, 1) spacerItem52 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_271.addItem(spacerItem52, 0, 0, 1, 1) self.gridLayout_270.addLayout(self.gridLayout_271, 3, 1, 1, 3) self.reproject_modis_checkBox = QtWidgets.QCheckBox(self.tab_MODIS) self.reproject_modis_checkBox.setChecked(True) self.reproject_modis_checkBox.setTristate(False) self.reproject_modis_checkBox.setObjectName("reproject_modis_checkBox") self.gridLayout_270.addWidget(self.reproject_modis_checkBox, 3, 0, 1, 1) self.gridLayout_70.addLayout(self.gridLayout_270, 0, 0, 1, 1) self.gridLayout_273 = QtWidgets.QGridLayout() self.gridLayout_273.setObjectName("gridLayout_273") self.MODIS_tableWidget = QtWidgets.QTableWidget(self.tab_MODIS) self.MODIS_tableWidget.setObjectName("MODIS_tableWidget") self.MODIS_tableWidget.setColumnCount(2) self.MODIS_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.MODIS_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.MODIS_tableWidget.setHorizontalHeaderItem(1, item) self.MODIS_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.MODIS_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_273.addWidget(self.MODIS_tableWidget, 1, 0, 1, 1) self.gridLayout_274 = QtWidgets.QGridLayout() self.gridLayout_274.setObjectName("gridLayout_274") self.pushButton_remove_band_3 = QtWidgets.QToolButton(self.tab_MODIS) self.pushButton_remove_band_3.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_remove_band_3.setIcon(icon58) self.pushButton_remove_band_3.setIconSize(QtCore.QSize(22, 22)) self.pushButton_remove_band_3.setObjectName("pushButton_remove_band_3") self.gridLayout_274.addWidget(self.pushButton_remove_band_3, 0, 0, 1, 1) self.gridLayout_273.addLayout(self.gridLayout_274, 1, 1, 1, 1) self.gridLayout_275 = QtWidgets.QGridLayout() self.gridLayout_275.setObjectName("gridLayout_275") self.satellite_label_16 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_16.sizePolicy().hasHeightForWidth()) self.satellite_label_16.setSizePolicy(sizePolicy) self.satellite_label_16.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_16.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_16.setObjectName("satellite_label_16") self.gridLayout_275.addWidget(self.satellite_label_16, 1, 4, 1, 1) self.MODIS_ID_lineEdit = QtWidgets.QLineEdit(self.tab_MODIS) self.MODIS_ID_lineEdit.setObjectName("MODIS_ID_lineEdit") self.gridLayout_275.addWidget(self.MODIS_ID_lineEdit, 1, 2, 1, 1) self.satellite_label_13 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_13.sizePolicy().hasHeightForWidth()) self.satellite_label_13.setSizePolicy(sizePolicy) self.satellite_label_13.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_13.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_13.setObjectName("satellite_label_13") self.gridLayout_275.addWidget(self.satellite_label_13, 1, 1, 1, 1) self.MODIS_date_lineEdit = QtWidgets.QLineEdit(self.tab_MODIS) self.MODIS_date_lineEdit.setObjectName("MODIS_date_lineEdit") self.gridLayout_275.addWidget(self.MODIS_date_lineEdit, 1, 5, 1, 1) self.label_220 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_220.sizePolicy().hasHeightForWidth()) self.label_220.setSizePolicy(sizePolicy) self.label_220.setStyleSheet("background-color : #656565; color : white") self.label_220.setFrameShape(QtWidgets.QFrame.Panel) self.label_220.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_220.setObjectName("label_220") self.gridLayout_275.addWidget(self.label_220, 0, 0, 1, 6) spacerItem53 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_275.addItem(spacerItem53, 1, 3, 1, 1) self.gridLayout_273.addLayout(self.gridLayout_275, 0, 0, 1, 2) self.gridLayout_70.addLayout(self.gridLayout_273, 1, 0, 1, 1) self.gridLayout_276 = QtWidgets.QGridLayout() self.gridLayout_276.setObjectName("gridLayout_276") spacerItem54 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_276.addItem(spacerItem54, 1, 1, 1, 1) self.label_221 = QtWidgets.QLabel(self.tab_MODIS) self.label_221.setStyleSheet("background-color : #656565; color : white") self.label_221.setFrameShape(QtWidgets.QFrame.Panel) self.label_221.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_221.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_221.setObjectName("label_221") self.gridLayout_276.addWidget(self.label_221, 0, 1, 1, 3) self.pushButton_Conversion_4 = QtWidgets.QToolButton(self.tab_MODIS) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_4.setFont(font) self.pushButton_Conversion_4.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_4.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_4.setIcon(icon64) self.pushButton_Conversion_4.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_4.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_4.setObjectName("pushButton_Conversion_4") self.gridLayout_276.addWidget(self.pushButton_Conversion_4, 1, 3, 1, 1) self.modis_conversion = QtWidgets.QToolButton(self.tab_MODIS) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.modis_conversion.setFont(font) self.modis_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.modis_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.modis_conversion.setIcon(icon48) self.modis_conversion.setIconSize(QtCore.QSize(34, 34)) self.modis_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.modis_conversion.setObjectName("modis_conversion") self.gridLayout_276.addWidget(self.modis_conversion, 1, 2, 1, 1) self.gridLayout_70.addLayout(self.gridLayout_276, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_MODIS, "") self.tab_spectral_distance = QtWidgets.QWidget() self.tab_spectral_distance.setObjectName("tab_spectral_distance") self.gridLayout_61 = QtWidgets.QGridLayout(self.tab_spectral_distance) self.gridLayout_61.setObjectName("gridLayout_61") self.gridLayout_119 = QtWidgets.QGridLayout() self.gridLayout_119.setObjectName("gridLayout_119") self.label_142 = QtWidgets.QLabel(self.tab_spectral_distance) self.label_142.setStyleSheet("background-color : #656565; color : white") self.label_142.setFrameShape(QtWidgets.QFrame.Panel) self.label_142.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_142.setObjectName("label_142") self.gridLayout_119.addWidget(self.label_142, 0, 0, 1, 1) self.gridLayout_61.addLayout(self.gridLayout_119, 0, 0, 1, 1) self.horizontalLayout_22 = QtWidgets.QHBoxLayout() self.horizontalLayout_22.setObjectName("horizontalLayout_22") self.label_64 = QtWidgets.QLabel(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_64.sizePolicy().hasHeightForWidth()) self.label_64.setSizePolicy(sizePolicy) self.label_64.setMinimumSize(QtCore.QSize(229, 0)) self.label_64.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_64.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_64.setObjectName("label_64") self.horizontalLayout_22.addWidget(self.label_64) self.vector_name_combo = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.vector_name_combo.sizePolicy().hasHeightForWidth()) self.vector_name_combo.setSizePolicy(sizePolicy) self.vector_name_combo.setObjectName("vector_name_combo") self.horizontalLayout_22.addWidget(self.vector_name_combo) self.toolButton_reload_16 = QtWidgets.QToolButton(self.tab_spectral_distance) self.toolButton_reload_16.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_16.setIcon(icon55) self.toolButton_reload_16.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_16.setObjectName("toolButton_reload_16") self.horizontalLayout_22.addWidget(self.toolButton_reload_16) self.gridLayout_61.addLayout(self.horizontalLayout_22, 1, 0, 1, 1) self.horizontalLayout_19 = QtWidgets.QHBoxLayout() self.horizontalLayout_19.setObjectName("horizontalLayout_19") self.field_checkBox = QtWidgets.QCheckBox(self.tab_spectral_distance) self.field_checkBox.setChecked(True) self.field_checkBox.setObjectName("field_checkBox") self.horizontalLayout_19.addWidget(self.field_checkBox) self.field_comboBox = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.field_comboBox.sizePolicy().hasHeightForWidth()) self.field_comboBox.setSizePolicy(sizePolicy) self.field_comboBox.setObjectName("field_comboBox") self.horizontalLayout_19.addWidget(self.field_comboBox) self.gridLayout_61.addLayout(self.horizontalLayout_19, 2, 0, 1, 1) self.horizontalLayout_25 = QtWidgets.QHBoxLayout() self.horizontalLayout_25.setObjectName("horizontalLayout_25") self.constant_value_checkBox = QtWidgets.QCheckBox(self.tab_spectral_distance) self.constant_value_checkBox.setObjectName("constant_value_checkBox") self.horizontalLayout_25.addWidget(self.constant_value_checkBox) self.constant_value_spinBox = QtWidgets.QSpinBox(self.tab_spectral_distance) self.constant_value_spinBox.setMinimum(-100000) self.constant_value_spinBox.setMaximum(100000) self.constant_value_spinBox.setProperty("value", 1) self.constant_value_spinBox.setObjectName("constant_value_spinBox") self.horizontalLayout_25.addWidget(self.constant_value_spinBox) self.gridLayout_61.addLayout(self.horizontalLayout_25, 3, 0, 1, 1) self.horizontalLayout_20 = QtWidgets.QHBoxLayout() self.horizontalLayout_20.setObjectName("horizontalLayout_20") self.label_157 = QtWidgets.QLabel(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_157.sizePolicy().hasHeightForWidth()) self.label_157.setSizePolicy(sizePolicy) self.label_157.setMinimumSize(QtCore.QSize(229, 0)) self.label_157.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_157.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_157.setObjectName("label_157") self.horizontalLayout_20.addWidget(self.label_157) self.conversion_type_combo = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.conversion_type_combo.sizePolicy().hasHeightForWidth()) self.conversion_type_combo.setSizePolicy(sizePolicy) self.conversion_type_combo.setObjectName("conversion_type_combo") self.horizontalLayout_20.addWidget(self.conversion_type_combo) self.gridLayout_61.addLayout(self.horizontalLayout_20, 4, 0, 1, 1) self.gridLayout_194 = QtWidgets.QGridLayout() self.gridLayout_194.setObjectName("gridLayout_194") self.label_156 = QtWidgets.QLabel(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_156.sizePolicy().hasHeightForWidth()) self.label_156.setSizePolicy(sizePolicy) self.label_156.setMinimumSize(QtCore.QSize(229, 0)) self.label_156.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_156.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_156.setObjectName("label_156") self.gridLayout_194.addWidget(self.label_156, 0, 0, 1, 1) self.toolButton_reload_17 = QtWidgets.QToolButton(self.tab_spectral_distance) self.toolButton_reload_17.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_17.setIcon(icon55) self.toolButton_reload_17.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_17.setObjectName("toolButton_reload_17") self.gridLayout_194.addWidget(self.toolButton_reload_17, 0, 2, 1, 1) self.reference_raster_name_combo = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_raster_name_combo.sizePolicy().hasHeightForWidth()) self.reference_raster_name_combo.setSizePolicy(sizePolicy) self.reference_raster_name_combo.setObjectName("reference_raster_name_combo") self.gridLayout_194.addWidget(self.reference_raster_name_combo, 0, 1, 1, 1) self.gridLayout_61.addLayout(self.gridLayout_194, 5, 0, 1, 1) self.horizontalLayout_47 = QtWidgets.QHBoxLayout() self.horizontalLayout_47.setObjectName("horizontalLayout_47") self.extent_checkBox_2 = QtWidgets.QCheckBox(self.tab_spectral_distance) self.extent_checkBox_2.setObjectName("extent_checkBox_2") self.horizontalLayout_47.addWidget(self.extent_checkBox_2) self.gridLayout_61.addLayout(self.horizontalLayout_47, 6, 0, 1, 1) self.gridLayout_210 = QtWidgets.QGridLayout() self.gridLayout_210.setObjectName("gridLayout_210") spacerItem55 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_210.addItem(spacerItem55, 0, 2, 1, 1) self.label_167 = QtWidgets.QLabel(self.tab_spectral_distance) self.label_167.setStyleSheet("background-color : #656565; color : white") self.label_167.setFrameShape(QtWidgets.QFrame.Panel) self.label_167.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_167.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_167.setObjectName("label_167") self.gridLayout_210.addWidget(self.label_167, 1, 0, 1, 3) spacerItem56 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_210.addItem(spacerItem56, 2, 0, 1, 1) self.convert_vector_toolButton = QtWidgets.QToolButton(self.tab_spectral_distance) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.convert_vector_toolButton.setFont(font) self.convert_vector_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.convert_vector_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.convert_vector_toolButton.setIcon(icon64) self.convert_vector_toolButton.setIconSize(QtCore.QSize(34, 34)) self.convert_vector_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.convert_vector_toolButton.setObjectName("convert_vector_toolButton") self.gridLayout_210.addWidget(self.convert_vector_toolButton, 2, 2, 1, 1) self.vector_to_raster = QtWidgets.QToolButton(self.tab_spectral_distance) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.vector_to_raster.setFont(font) self.vector_to_raster.setLayoutDirection(QtCore.Qt.RightToLeft) self.vector_to_raster.setStyleSheet("margin: 0px;padding: 0px;") self.vector_to_raster.setIcon(icon48) self.vector_to_raster.setIconSize(QtCore.QSize(34, 34)) self.vector_to_raster.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.vector_to_raster.setObjectName("vector_to_raster") self.gridLayout_210.addWidget(self.vector_to_raster, 2, 1, 1, 1) self.gridLayout_61.addLayout(self.gridLayout_210, 7, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_spectral_distance, "") self.tab_clip = QtWidgets.QWidget() self.tab_clip.setObjectName("tab_clip") self.gridLayout_58 = QtWidgets.QGridLayout(self.tab_clip) self.gridLayout_58.setObjectName("gridLayout_58") self.gridLayout_51 = QtWidgets.QGridLayout() self.gridLayout_51.setObjectName("gridLayout_51") self.label_128 = QtWidgets.QLabel(self.tab_clip) self.label_128.setStyleSheet("background-color : #656565; color : white") self.label_128.setFrameShape(QtWidgets.QFrame.Panel) self.label_128.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_128.setObjectName("label_128") self.gridLayout_51.addWidget(self.label_128, 0, 0, 1, 1) self.gridLayout_58.addLayout(self.gridLayout_51, 0, 0, 1, 1) self.gridLayout_24 = QtWidgets.QGridLayout() self.gridLayout_24.setObjectName("gridLayout_24") self.nodata_spinBox = QtWidgets.QSpinBox(self.tab_clip) self.nodata_spinBox.setMinimum(-2147483647) self.nodata_spinBox.setMaximum(2147483647) self.nodata_spinBox.setObjectName("nodata_spinBox") self.gridLayout_24.addWidget(self.nodata_spinBox, 1, 1, 1, 1) self.band_set_comb_spinBox_2 = QtWidgets.QSpinBox(self.tab_clip) self.band_set_comb_spinBox_2.setMinimum(1) self.band_set_comb_spinBox_2.setMaximum(100000) self.band_set_comb_spinBox_2.setObjectName("band_set_comb_spinBox_2") self.gridLayout_24.addWidget(self.band_set_comb_spinBox_2, 0, 1, 1, 1) self.label_251 = QtWidgets.QLabel(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_251.sizePolicy().hasHeightForWidth()) self.label_251.setSizePolicy(sizePolicy) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_251.setFont(font) self.label_251.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_251.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_251.setObjectName("label_251") self.gridLayout_24.addWidget(self.label_251, 0, 0, 1, 1) self.label_62 = QtWidgets.QLabel(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_62.sizePolicy().hasHeightForWidth()) self.label_62.setSizePolicy(sizePolicy) self.label_62.setMinimumSize(QtCore.QSize(150, 0)) self.label_62.setMaximumSize(QtCore.QSize(100, 16777215)) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_62.setFont(font) self.label_62.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_62.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_62.setObjectName("label_62") self.gridLayout_24.addWidget(self.label_62, 2, 0, 1, 1) self.label_16 = QtWidgets.QLabel(self.tab_clip) self.label_16.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_16.setObjectName("label_16") self.gridLayout_24.addWidget(self.label_16, 1, 0, 1, 1) spacerItem57 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_24.addItem(spacerItem57, 1, 2, 1, 1) self.output_clip_name_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.output_clip_name_lineEdit.setMaxLength(10) self.output_clip_name_lineEdit.setObjectName("output_clip_name_lineEdit") self.gridLayout_24.addWidget(self.output_clip_name_lineEdit, 2, 1, 1, 2) self.gridLayout_58.addLayout(self.gridLayout_24, 1, 0, 1, 1) self.gridLayout_20 = QtWidgets.QGridLayout() self.gridLayout_20.setObjectName("gridLayout_20") spacerItem58 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_20.addItem(spacerItem58, 1, 8, 1, 1) self.LX_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.LX_lineEdit.setMaxLength(10) self.LX_lineEdit.setObjectName("LX_lineEdit") self.gridLayout_20.addWidget(self.LX_lineEdit, 1, 6, 1, 1) self.UX_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.UX_lineEdit.setMaxLength(10) self.UX_lineEdit.setObjectName("UX_lineEdit") self.gridLayout_20.addWidget(self.UX_lineEdit, 1, 3, 1, 1) self.UY_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.UY_lineEdit.setMaxLength(10) self.UY_lineEdit.setObjectName("UY_lineEdit") self.gridLayout_20.addWidget(self.UY_lineEdit, 1, 4, 1, 1) self.LY_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.LY_lineEdit.setMaxLength(10) self.LY_lineEdit.setObjectName("LY_lineEdit") self.gridLayout_20.addWidget(self.LY_lineEdit, 1, 7, 1, 1) self.label_12 = QtWidgets.QLabel(self.tab_clip) self.label_12.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_12.setAlignment(QtCore.Qt.AlignCenter) self.label_12.setObjectName("label_12") self.gridLayout_20.addWidget(self.label_12, 1, 5, 1, 1) self.selectUL_toolButton = QtWidgets.QToolButton(self.tab_clip) self.selectUL_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.selectUL_toolButton.setIcon(icon77) self.selectUL_toolButton.setIconSize(QtCore.QSize(22, 22)) self.selectUL_toolButton.setObjectName("selectUL_toolButton") self.gridLayout_20.addWidget(self.selectUL_toolButton, 1, 10, 1, 1) self.label_29 = QtWidgets.QLabel(self.tab_clip) self.label_29.setStyleSheet("background-color : #656565; color : white") self.label_29.setFrameShape(QtWidgets.QFrame.Panel) self.label_29.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_29.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_29.setObjectName("label_29") self.gridLayout_20.addWidget(self.label_29, 0, 0, 1, 11) self.show_area_radioButton_3 = QtWidgets.QRadioButton(self.tab_clip) self.show_area_radioButton_3.setChecked(True) self.show_area_radioButton_3.setAutoExclusive(False) self.show_area_radioButton_3.setObjectName("show_area_radioButton_3") self.gridLayout_20.addWidget(self.show_area_radioButton_3, 1, 9, 1, 1) self.label_11 = QtWidgets.QLabel(self.tab_clip) self.label_11.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_11.setAlignment(QtCore.Qt.AlignCenter) self.label_11.setObjectName("label_11") self.gridLayout_20.addWidget(self.label_11, 1, 0, 1, 3) self.gridLayout_58.addLayout(self.gridLayout_20, 2, 0, 1, 1) self.gridLayout_22 = QtWidgets.QGridLayout() self.gridLayout_22.setObjectName("gridLayout_22") self.shapefile_comboBox = QtWidgets.QComboBox(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.shapefile_comboBox.sizePolicy().hasHeightForWidth()) self.shapefile_comboBox.setSizePolicy(sizePolicy) self.shapefile_comboBox.setObjectName("shapefile_comboBox") self.gridLayout_22.addWidget(self.shapefile_comboBox, 0, 1, 1, 1) self.shapefile_checkBox = QtWidgets.QCheckBox(self.tab_clip) self.shapefile_checkBox.setObjectName("shapefile_checkBox") self.gridLayout_22.addWidget(self.shapefile_checkBox, 0, 0, 1, 1) self.toolButton_reload_8 = QtWidgets.QToolButton(self.tab_clip) self.toolButton_reload_8.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_8.setIcon(icon55) self.toolButton_reload_8.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_8.setObjectName("toolButton_reload_8") self.gridLayout_22.addWidget(self.toolButton_reload_8, 0, 2, 1, 1) self.temporary_ROI_checkBox = QtWidgets.QCheckBox(self.tab_clip) self.temporary_ROI_checkBox.setObjectName("temporary_ROI_checkBox") self.gridLayout_22.addWidget(self.temporary_ROI_checkBox, 2, 0, 1, 1) self.gridLayout_19 = QtWidgets.QGridLayout() self.gridLayout_19.setObjectName("gridLayout_19") self.vector_field_checkBox = QtWidgets.QCheckBox(self.tab_clip) self.vector_field_checkBox.setObjectName("vector_field_checkBox") self.gridLayout_19.addWidget(self.vector_field_checkBox, 0, 0, 1, 1) self.class_field_comboBox_3 = QtWidgets.QComboBox(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox_3.sizePolicy().hasHeightForWidth()) self.class_field_comboBox_3.setSizePolicy(sizePolicy) self.class_field_comboBox_3.setObjectName("class_field_comboBox_3") self.gridLayout_19.addWidget(self.class_field_comboBox_3, 0, 1, 1, 1) self.gridLayout_22.addLayout(self.gridLayout_19, 1, 1, 1, 1) self.gridLayout_58.addLayout(self.gridLayout_22, 3, 0, 1, 1) self.gridLayout_28 = QtWidgets.QGridLayout() self.gridLayout_28.setObjectName("gridLayout_28") spacerItem59 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_28.addItem(spacerItem59, 2, 0, 1, 1) self.label_164 = QtWidgets.QLabel(self.tab_clip) self.label_164.setStyleSheet("background-color : #656565; color : white") self.label_164.setFrameShape(QtWidgets.QFrame.Panel) self.label_164.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_164.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_164.setObjectName("label_164") self.gridLayout_28.addWidget(self.label_164, 1, 0, 1, 3) self.clip_Button = QtWidgets.QToolButton(self.tab_clip) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.clip_Button.setFont(font) self.clip_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.clip_Button.setStyleSheet("margin: 0px;padding: 0px;") self.clip_Button.setIcon(icon64) self.clip_Button.setIconSize(QtCore.QSize(34, 34)) self.clip_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.clip_Button.setObjectName("clip_Button") self.gridLayout_28.addWidget(self.clip_Button, 2, 2, 1, 1) spacerItem60 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_28.addItem(spacerItem60, 0, 0, 1, 1) self.clip_multiple_rasters = QtWidgets.QToolButton(self.tab_clip) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.clip_multiple_rasters.setFont(font) self.clip_multiple_rasters.setLayoutDirection(QtCore.Qt.RightToLeft) self.clip_multiple_rasters.setStyleSheet("margin: 0px;padding: 0px;") self.clip_multiple_rasters.setIcon(icon48) self.clip_multiple_rasters.setIconSize(QtCore.QSize(34, 34)) self.clip_multiple_rasters.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.clip_multiple_rasters.setObjectName("clip_multiple_rasters") self.gridLayout_28.addWidget(self.clip_multiple_rasters, 2, 1, 1, 1) self.gridLayout_58.addLayout(self.gridLayout_28, 4, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_clip, "") self.tab_reproject_bands = QtWidgets.QWidget() self.tab_reproject_bands.setObjectName("tab_reproject_bands") self.gridLayout_295 = QtWidgets.QGridLayout(self.tab_reproject_bands) self.gridLayout_295.setObjectName("gridLayout_295") self.gridLayout_289 = QtWidgets.QGridLayout() self.gridLayout_289.setObjectName("gridLayout_289") self.band_set_comb_spinBox_14 = QtWidgets.QSpinBox(self.tab_reproject_bands) self.band_set_comb_spinBox_14.setMinimum(1) self.band_set_comb_spinBox_14.setMaximum(100000) self.band_set_comb_spinBox_14.setObjectName("band_set_comb_spinBox_14") self.gridLayout_289.addWidget(self.band_set_comb_spinBox_14, 1, 1, 1, 1) self.label_264 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_264.sizePolicy().hasHeightForWidth()) self.label_264.setSizePolicy(sizePolicy) self.label_264.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_264.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_264.setObjectName("label_264") self.gridLayout_289.addWidget(self.label_264, 1, 0, 1, 1) spacerItem61 = QtWidgets.QSpacerItem(605, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_289.addItem(spacerItem61, 1, 2, 1, 1) self.label_249 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_249.sizePolicy().hasHeightForWidth()) self.label_249.setSizePolicy(sizePolicy) self.label_249.setStyleSheet("background-color : #656565; color : white") self.label_249.setFrameShape(QtWidgets.QFrame.Panel) self.label_249.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_249.setObjectName("label_249") self.gridLayout_289.addWidget(self.label_249, 0, 0, 1, 3) self.gridLayout_295.addLayout(self.gridLayout_289, 0, 0, 1, 1) self.gridLayout_291 = QtWidgets.QGridLayout() self.gridLayout_291.setObjectName("gridLayout_291") self.raster_align_comboBox = QtWidgets.QComboBox(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_align_comboBox.sizePolicy().hasHeightForWidth()) self.raster_align_comboBox.setSizePolicy(sizePolicy) self.raster_align_comboBox.setObjectName("raster_align_comboBox") self.gridLayout_291.addWidget(self.raster_align_comboBox, 0, 2, 1, 1) self.use_align_raster_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.use_align_raster_checkBox.setObjectName("use_align_raster_checkBox") self.gridLayout_291.addWidget(self.use_align_raster_checkBox, 0, 0, 1, 1) self.toolButton_reload_25 = QtWidgets.QToolButton(self.tab_reproject_bands) self.toolButton_reload_25.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_25.setIcon(icon55) self.toolButton_reload_25.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_25.setObjectName("toolButton_reload_25") self.gridLayout_291.addWidget(self.toolButton_reload_25, 0, 3, 1, 1) self.same_extent_raster_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.same_extent_raster_checkBox.setObjectName("same_extent_raster_checkBox") self.gridLayout_291.addWidget(self.same_extent_raster_checkBox, 0, 1, 1, 1) self.gridLayout_295.addLayout(self.gridLayout_291, 1, 0, 1, 1) self.gridLayout_292 = QtWidgets.QGridLayout() self.gridLayout_292.setObjectName("gridLayout_292") self.epsg_code_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.epsg_code_lineEdit.setText("") self.epsg_code_lineEdit.setMaxLength(10) self.epsg_code_lineEdit.setObjectName("epsg_code_lineEdit") self.gridLayout_292.addWidget(self.epsg_code_lineEdit, 0, 1, 1, 1) self.use_epsg_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.use_epsg_checkBox.setObjectName("use_epsg_checkBox") self.gridLayout_292.addWidget(self.use_epsg_checkBox, 0, 0, 1, 1) self.label_267 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_267.sizePolicy().hasHeightForWidth()) self.label_267.setSizePolicy(sizePolicy) self.label_267.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_267.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_267.setObjectName("label_267") self.gridLayout_292.addWidget(self.label_267, 0, 6, 1, 1) self.label_266 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_266.sizePolicy().hasHeightForWidth()) self.label_266.setSizePolicy(sizePolicy) self.label_266.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_266.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_266.setObjectName("label_266") self.gridLayout_292.addWidget(self.label_266, 0, 3, 1, 1) self.x_resolution_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.x_resolution_lineEdit.setText("") self.x_resolution_lineEdit.setMaxLength(10) self.x_resolution_lineEdit.setObjectName("x_resolution_lineEdit") self.gridLayout_292.addWidget(self.x_resolution_lineEdit, 0, 4, 1, 1) self.y_resolution_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.y_resolution_lineEdit.setText("") self.y_resolution_lineEdit.setMaxLength(10) self.y_resolution_lineEdit.setObjectName("y_resolution_lineEdit") self.gridLayout_292.addWidget(self.y_resolution_lineEdit, 0, 7, 1, 1) spacerItem62 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_292.addItem(spacerItem62, 0, 2, 1, 1) spacerItem63 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_292.addItem(spacerItem63, 0, 5, 1, 1) self.gridLayout_295.addLayout(self.gridLayout_292, 2, 0, 1, 1) self.horizontalLayout_63 = QtWidgets.QHBoxLayout() self.horizontalLayout_63.setObjectName("horizontalLayout_63") self.resample_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.resample_checkBox.setObjectName("resample_checkBox") self.horizontalLayout_63.addWidget(self.resample_checkBox) self.resample_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.resample_lineEdit.setMaxLength(10) self.resample_lineEdit.setObjectName("resample_lineEdit") self.horizontalLayout_63.addWidget(self.resample_lineEdit) self.gridLayout_295.addLayout(self.horizontalLayout_63, 3, 0, 1, 1) self.horizontalLayout_64 = QtWidgets.QHBoxLayout() self.horizontalLayout_64.setObjectName("horizontalLayout_64") self.label_269 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_269.sizePolicy().hasHeightForWidth()) self.label_269.setSizePolicy(sizePolicy) self.label_269.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_269.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_269.setObjectName("label_269") self.horizontalLayout_64.addWidget(self.label_269) self.resampling_method_comboBox = QtWidgets.QComboBox(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.resampling_method_comboBox.sizePolicy().hasHeightForWidth()) self.resampling_method_comboBox.setSizePolicy(sizePolicy) self.resampling_method_comboBox.setObjectName("resampling_method_comboBox") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.horizontalLayout_64.addWidget(self.resampling_method_comboBox) spacerItem64 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_64.addItem(spacerItem64) self.label_270 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_270.sizePolicy().hasHeightForWidth()) self.label_270.setSizePolicy(sizePolicy) self.label_270.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_270.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_270.setObjectName("label_270") self.horizontalLayout_64.addWidget(self.label_270) self.raster_type_combo_2 = QtWidgets.QComboBox(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_type_combo_2.sizePolicy().hasHeightForWidth()) self.raster_type_combo_2.setSizePolicy(sizePolicy) self.raster_type_combo_2.setObjectName("raster_type_combo_2") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.horizontalLayout_64.addWidget(self.raster_type_combo_2) self.gridLayout_295.addLayout(self.horizontalLayout_64, 4, 0, 1, 1) self.horizontalLayout_66 = QtWidgets.QHBoxLayout() self.horizontalLayout_66.setObjectName("horizontalLayout_66") self.change_nodata_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.change_nodata_checkBox.setObjectName("change_nodata_checkBox") self.horizontalLayout_66.addWidget(self.change_nodata_checkBox) self.nodata_spinBox_14 = QtWidgets.QSpinBox(self.tab_reproject_bands) self.nodata_spinBox_14.setMinimum(-2147483647) self.nodata_spinBox_14.setMaximum(2147483647) self.nodata_spinBox_14.setProperty("value", -32768) self.nodata_spinBox_14.setObjectName("nodata_spinBox_14") self.horizontalLayout_66.addWidget(self.nodata_spinBox_14) spacerItem65 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_66.addItem(spacerItem65) self.gridLayout_295.addLayout(self.horizontalLayout_66, 5, 0, 1, 1) self.horizontalLayout_68 = QtWidgets.QHBoxLayout() self.horizontalLayout_68.setObjectName("horizontalLayout_68") self.label_265 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_265.sizePolicy().hasHeightForWidth()) self.label_265.setSizePolicy(sizePolicy) self.label_265.setMinimumSize(QtCore.QSize(229, 0)) self.label_265.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_265.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_265.setObjectName("label_265") self.horizontalLayout_68.addWidget(self.label_265) self.reproj_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.reproj_output_name_lineEdit.setMaxLength(10) self.reproj_output_name_lineEdit.setObjectName("reproj_output_name_lineEdit") self.horizontalLayout_68.addWidget(self.reproj_output_name_lineEdit) self.gridLayout_295.addLayout(self.horizontalLayout_68, 6, 0, 1, 1) spacerItem66 = QtWidgets.QSpacerItem(20, 198, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_295.addItem(spacerItem66, 7, 0, 1, 1) self.gridLayout_290 = QtWidgets.QGridLayout() self.gridLayout_290.setObjectName("gridLayout_290") self.label_263 = QtWidgets.QLabel(self.tab_reproject_bands) self.label_263.setStyleSheet("background-color : #656565; color : white") self.label_263.setFrameShape(QtWidgets.QFrame.Panel) self.label_263.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_263.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_263.setObjectName("label_263") self.gridLayout_290.addWidget(self.label_263, 0, 0, 1, 2) self.horizontalLayout_59 = QtWidgets.QHBoxLayout() self.horizontalLayout_59.setObjectName("horizontalLayout_59") spacerItem67 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_59.addItem(spacerItem67) self.reproject_raster_bands = QtWidgets.QToolButton(self.tab_reproject_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reproject_raster_bands.setFont(font) self.reproject_raster_bands.setLayoutDirection(QtCore.Qt.RightToLeft) self.reproject_raster_bands.setStyleSheet("margin: 0px;padding: 0px;") self.reproject_raster_bands.setIcon(icon48) self.reproject_raster_bands.setIconSize(QtCore.QSize(34, 34)) self.reproject_raster_bands.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reproject_raster_bands.setObjectName("reproject_raster_bands") self.horizontalLayout_59.addWidget(self.reproject_raster_bands) self.reproject_Button = QtWidgets.QToolButton(self.tab_reproject_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reproject_Button.setFont(font) self.reproject_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.reproject_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reproject_Button.setIcon(icon64) self.reproject_Button.setIconSize(QtCore.QSize(34, 34)) self.reproject_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reproject_Button.setObjectName("reproject_Button") self.horizontalLayout_59.addWidget(self.reproject_Button) self.gridLayout_290.addLayout(self.horizontalLayout_59, 2, 0, 1, 2) self.gridLayout_295.addLayout(self.gridLayout_290, 8, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_reproject_bands, "") self.tab_split_raster = QtWidgets.QWidget() self.tab_split_raster.setObjectName("tab_split_raster") self.gridLayout_57 = QtWidgets.QGridLayout(self.tab_split_raster) self.gridLayout_57.setObjectName("gridLayout_57") spacerItem68 = QtWidgets.QSpacerItem(20, 302, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_57.addItem(spacerItem68, 3, 1, 1, 1) self.gridLayout_190 = QtWidgets.QGridLayout() self.gridLayout_190.setObjectName("gridLayout_190") self.raster_name_combo = QtWidgets.QComboBox(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_name_combo.sizePolicy().hasHeightForWidth()) self.raster_name_combo.setSizePolicy(sizePolicy) self.raster_name_combo.setObjectName("raster_name_combo") self.gridLayout_190.addWidget(self.raster_name_combo, 1, 1, 1, 1) self.label_57 = QtWidgets.QLabel(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_57.sizePolicy().hasHeightForWidth()) self.label_57.setSizePolicy(sizePolicy) self.label_57.setStyleSheet("background-color : #656565; color : white") self.label_57.setFrameShape(QtWidgets.QFrame.Panel) self.label_57.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_57.setObjectName("label_57") self.gridLayout_190.addWidget(self.label_57, 0, 0, 1, 3) self.label_50 = QtWidgets.QLabel(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_50.sizePolicy().hasHeightForWidth()) self.label_50.setSizePolicy(sizePolicy) self.label_50.setMinimumSize(QtCore.QSize(229, 0)) self.label_50.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_50.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_50.setObjectName("label_50") self.gridLayout_190.addWidget(self.label_50, 1, 0, 1, 1) self.toolButton_reload_9 = QtWidgets.QToolButton(self.tab_split_raster) self.toolButton_reload_9.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_9.setIcon(icon55) self.toolButton_reload_9.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_9.setObjectName("toolButton_reload_9") self.gridLayout_190.addWidget(self.toolButton_reload_9, 1, 2, 1, 1) self.gridLayout_57.addLayout(self.gridLayout_190, 0, 0, 1, 4) self.label_165 = QtWidgets.QLabel(self.tab_split_raster) self.label_165.setStyleSheet("background-color : #656565; color : white") self.label_165.setFrameShape(QtWidgets.QFrame.Panel) self.label_165.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_165.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_165.setObjectName("label_165") self.gridLayout_57.addWidget(self.label_165, 4, 0, 1, 4) self.horizontalLayout_57 = QtWidgets.QHBoxLayout() self.horizontalLayout_57.setObjectName("horizontalLayout_57") self.label_61 = QtWidgets.QLabel(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_61.sizePolicy().hasHeightForWidth()) self.label_61.setSizePolicy(sizePolicy) self.label_61.setMinimumSize(QtCore.QSize(229, 0)) self.label_61.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_61.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_61.setObjectName("label_61") self.horizontalLayout_57.addWidget(self.label_61) self.output_name_lineEdit = QtWidgets.QLineEdit(self.tab_split_raster) self.output_name_lineEdit.setMaxLength(10) self.output_name_lineEdit.setObjectName("output_name_lineEdit") self.horizontalLayout_57.addWidget(self.output_name_lineEdit) self.gridLayout_57.addLayout(self.horizontalLayout_57, 1, 0, 1, 4) self.horizontalLayout_54 = QtWidgets.QHBoxLayout() self.horizontalLayout_54.setObjectName("horizontalLayout_54") spacerItem69 = QtWidgets.QSpacerItem(667, 38, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_54.addItem(spacerItem69) self.split_raster_bands = QtWidgets.QToolButton(self.tab_split_raster) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.split_raster_bands.setFont(font) self.split_raster_bands.setLayoutDirection(QtCore.Qt.RightToLeft) self.split_raster_bands.setStyleSheet("margin: 0px;padding: 0px;") self.split_raster_bands.setIcon(icon48) self.split_raster_bands.setIconSize(QtCore.QSize(34, 34)) self.split_raster_bands.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.split_raster_bands.setObjectName("split_raster_bands") self.horizontalLayout_54.addWidget(self.split_raster_bands) self.split_Button = QtWidgets.QToolButton(self.tab_split_raster) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.split_Button.setFont(font) self.split_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.split_Button.setStyleSheet("margin: 0px;padding: 0px;") self.split_Button.setIcon(icon64) self.split_Button.setIconSize(QtCore.QSize(34, 34)) self.split_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.split_Button.setObjectName("split_Button") self.horizontalLayout_54.addWidget(self.split_Button) self.gridLayout_57.addLayout(self.horizontalLayout_54, 5, 0, 1, 4) self.tabWidget_preprocessing.addTab(self.tab_split_raster, "") self.tab_stack_bands = QtWidgets.QWidget() self.tab_stack_bands.setObjectName("tab_stack_bands") self.gridLayout_23 = QtWidgets.QGridLayout(self.tab_stack_bands) self.gridLayout_23.setObjectName("gridLayout_23") self.label_252 = QtWidgets.QLabel(self.tab_stack_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_252.sizePolicy().hasHeightForWidth()) self.label_252.setSizePolicy(sizePolicy) self.label_252.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_252.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_252.setObjectName("label_252") self.gridLayout_23.addWidget(self.label_252, 1, 0, 1, 1) self.band_set_comb_spinBox_3 = QtWidgets.QSpinBox(self.tab_stack_bands) self.band_set_comb_spinBox_3.setMinimum(1) self.band_set_comb_spinBox_3.setMaximum(100000) self.band_set_comb_spinBox_3.setObjectName("band_set_comb_spinBox_3") self.gridLayout_23.addWidget(self.band_set_comb_spinBox_3, 1, 1, 1, 1) spacerItem70 = QtWidgets.QSpacerItem(647, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_23.addItem(spacerItem70, 1, 3, 1, 1) spacerItem71 = QtWidgets.QSpacerItem(20, 339, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_23.addItem(spacerItem71, 2, 0, 1, 1) self.horizontalLayout_53 = QtWidgets.QHBoxLayout() self.horizontalLayout_53.setObjectName("horizontalLayout_53") spacerItem72 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_53.addItem(spacerItem72) self.stack_raster_bands = QtWidgets.QToolButton(self.tab_stack_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.stack_raster_bands.setFont(font) self.stack_raster_bands.setLayoutDirection(QtCore.Qt.RightToLeft) self.stack_raster_bands.setStyleSheet("margin: 0px;padding: 0px;") self.stack_raster_bands.setIcon(icon48) self.stack_raster_bands.setIconSize(QtCore.QSize(34, 34)) self.stack_raster_bands.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.stack_raster_bands.setObjectName("stack_raster_bands") self.horizontalLayout_53.addWidget(self.stack_raster_bands) self.stack_Button = QtWidgets.QToolButton(self.tab_stack_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.stack_Button.setFont(font) self.stack_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.stack_Button.setStyleSheet("margin: 0px;padding: 0px;") self.stack_Button.setIcon(icon64) self.stack_Button.setIconSize(QtCore.QSize(34, 34)) self.stack_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.stack_Button.setObjectName("stack_Button") self.horizontalLayout_53.addWidget(self.stack_Button) self.gridLayout_23.addLayout(self.horizontalLayout_53, 4, 0, 1, 4) self.label_223 = QtWidgets.QLabel(self.tab_stack_bands) self.label_223.setStyleSheet("background-color : #656565; color : white") self.label_223.setFrameShape(QtWidgets.QFrame.Panel) self.label_223.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_223.setObjectName("label_223") self.gridLayout_23.addWidget(self.label_223, 0, 0, 1, 4) self.label_226 = QtWidgets.QLabel(self.tab_stack_bands) self.label_226.setStyleSheet("background-color : #656565; color : white") self.label_226.setFrameShape(QtWidgets.QFrame.Panel) self.label_226.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_226.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_226.setObjectName("label_226") self.gridLayout_23.addWidget(self.label_226, 3, 0, 1, 4) self.tabWidget_preprocessing.addTab(self.tab_stack_bands, "") self.tab_mosaic_band_sets = QtWidgets.QWidget() self.tab_mosaic_band_sets.setObjectName("tab_mosaic_band_sets") self.gridLayout_278 = QtWidgets.QGridLayout(self.tab_mosaic_band_sets) self.gridLayout_278.setObjectName("gridLayout_278") self.horizontalLayout_28 = QtWidgets.QHBoxLayout() self.horizontalLayout_28.setObjectName("horizontalLayout_28") self.label_134 = QtWidgets.QLabel(self.tab_mosaic_band_sets) self.label_134.setStyleSheet("background-color : #656565; color : white") self.label_134.setFrameShape(QtWidgets.QFrame.Panel) self.label_134.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_134.setObjectName("label_134") self.horizontalLayout_28.addWidget(self.label_134) self.gridLayout_278.addLayout(self.horizontalLayout_28, 0, 0, 1, 1) self.gridLayout_66 = QtWidgets.QGridLayout() self.gridLayout_66.setObjectName("gridLayout_66") self.label_135 = QtWidgets.QLabel(self.tab_mosaic_band_sets) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_135.sizePolicy().hasHeightForWidth()) self.label_135.setSizePolicy(sizePolicy) self.label_135.setMinimumSize(QtCore.QSize(229, 0)) self.label_135.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_135.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_135.setObjectName("label_135") self.gridLayout_66.addWidget(self.label_135, 3, 0, 1, 1) self.nodata_checkBox_9 = QtWidgets.QCheckBox(self.tab_mosaic_band_sets) self.nodata_checkBox_9.setChecked(True) self.nodata_checkBox_9.setObjectName("nodata_checkBox_9") self.gridLayout_66.addWidget(self.nodata_checkBox_9, 1, 0, 1, 1) self.nodata_spinBox_10 = QtWidgets.QSpinBox(self.tab_mosaic_band_sets) self.nodata_spinBox_10.setMinimum(-2147483647) self.nodata_spinBox_10.setMaximum(2147483647) self.nodata_spinBox_10.setObjectName("nodata_spinBox_10") self.gridLayout_66.addWidget(self.nodata_spinBox_10, 1, 1, 1, 1) spacerItem73 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_66.addItem(spacerItem73, 1, 2, 1, 1) self.mosaic_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_mosaic_band_sets) self.mosaic_output_name_lineEdit.setMaxLength(10) self.mosaic_output_name_lineEdit.setObjectName("mosaic_output_name_lineEdit") self.gridLayout_66.addWidget(self.mosaic_output_name_lineEdit, 3, 1, 1, 2) self.label_144 = QtWidgets.QLabel(self.tab_mosaic_band_sets) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_144.sizePolicy().hasHeightForWidth()) self.label_144.setSizePolicy(sizePolicy) self.label_144.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_144.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_144.setObjectName("label_144") self.gridLayout_66.addWidget(self.label_144, 0, 0, 1, 1) self.mosaic_band_sets_lineEdit = QtWidgets.QLineEdit(self.tab_mosaic_band_sets) self.mosaic_band_sets_lineEdit.setObjectName("mosaic_band_sets_lineEdit") self.gridLayout_66.addWidget(self.mosaic_band_sets_lineEdit, 0, 1, 1, 2) self.mosaic_virtual_checkBox = QtWidgets.QCheckBox(self.tab_mosaic_band_sets) self.mosaic_virtual_checkBox.setObjectName("mosaic_virtual_checkBox") self.gridLayout_66.addWidget(self.mosaic_virtual_checkBox, 2, 0, 1, 1) self.gridLayout_278.addLayout(self.gridLayout_66, 1, 0, 1, 1) spacerItem74 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_278.addItem(spacerItem74, 2, 0, 1, 1) self.gridLayout_228 = QtWidgets.QGridLayout() self.gridLayout_228.setObjectName("gridLayout_228") spacerItem75 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_228.addItem(spacerItem75, 1, 0, 1, 1) self.mosaic_bandsets_toolButton = QtWidgets.QToolButton(self.tab_mosaic_band_sets) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.mosaic_bandsets_toolButton.setFont(font) self.mosaic_bandsets_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.mosaic_bandsets_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.mosaic_bandsets_toolButton.setIcon(icon64) self.mosaic_bandsets_toolButton.setIconSize(QtCore.QSize(34, 34)) self.mosaic_bandsets_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.mosaic_bandsets_toolButton.setObjectName("mosaic_bandsets_toolButton") self.gridLayout_228.addWidget(self.mosaic_bandsets_toolButton, 1, 2, 1, 1) self.mosaic_bandsets = QtWidgets.QToolButton(self.tab_mosaic_band_sets) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.mosaic_bandsets.setFont(font) self.mosaic_bandsets.setLayoutDirection(QtCore.Qt.RightToLeft) self.mosaic_bandsets.setStyleSheet("margin: 0px;padding: 0px;") self.mosaic_bandsets.setIcon(icon48) self.mosaic_bandsets.setIconSize(QtCore.QSize(34, 34)) self.mosaic_bandsets.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.mosaic_bandsets.setObjectName("mosaic_bandsets") self.gridLayout_228.addWidget(self.mosaic_bandsets, 1, 1, 1, 1) self.label_182 = QtWidgets.QLabel(self.tab_mosaic_band_sets) self.label_182.setStyleSheet("background-color : #656565; color : white") self.label_182.setFrameShape(QtWidgets.QFrame.Panel) self.label_182.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_182.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_182.setObjectName("label_182") self.gridLayout_228.addWidget(self.label_182, 0, 0, 1, 3) self.gridLayout_278.addLayout(self.gridLayout_228, 3, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_mosaic_band_sets, "") self.tab_cloud_mask = QtWidgets.QWidget() self.tab_cloud_mask.setObjectName("tab_cloud_mask") self.gridLayout_296 = QtWidgets.QGridLayout(self.tab_cloud_mask) self.gridLayout_296.setObjectName("gridLayout_296") self.gridLayout_261 = QtWidgets.QGridLayout() self.gridLayout_261.setObjectName("gridLayout_261") self.label_260 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_260.sizePolicy().hasHeightForWidth()) self.label_260.setSizePolicy(sizePolicy) self.label_260.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_260.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_260.setObjectName("label_260") self.gridLayout_261.addWidget(self.label_260, 0, 0, 1, 1) spacerItem76 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_261.addItem(spacerItem76, 0, 2, 1, 1) self.band_set_comb_spinBox_9 = QtWidgets.QSpinBox(self.tab_cloud_mask) self.band_set_comb_spinBox_9.setMinimum(1) self.band_set_comb_spinBox_9.setMaximum(100000) self.band_set_comb_spinBox_9.setObjectName("band_set_comb_spinBox_9") self.gridLayout_261.addWidget(self.band_set_comb_spinBox_9, 0, 1, 1, 1) self.gridLayout_296.addLayout(self.gridLayout_261, 1, 0, 1, 2) self.gridLayout_106 = QtWidgets.QGridLayout() self.gridLayout_106.setObjectName("gridLayout_106") self.classification_name_combo_4 = QtWidgets.QComboBox(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_4.sizePolicy().hasHeightForWidth()) self.classification_name_combo_4.setSizePolicy(sizePolicy) self.classification_name_combo_4.setObjectName("classification_name_combo_4") self.gridLayout_106.addWidget(self.classification_name_combo_4, 0, 1, 1, 1) self.cloud_mask_classes_lineEdit = QtWidgets.QLineEdit(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.cloud_mask_classes_lineEdit.sizePolicy().hasHeightForWidth()) self.cloud_mask_classes_lineEdit.setSizePolicy(sizePolicy) self.cloud_mask_classes_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.cloud_mask_classes_lineEdit.setText("") self.cloud_mask_classes_lineEdit.setMaxLength(10000) self.cloud_mask_classes_lineEdit.setObjectName("cloud_mask_classes_lineEdit") self.gridLayout_106.addWidget(self.cloud_mask_classes_lineEdit, 1, 1, 1, 1) self.label_203 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_203.sizePolicy().hasHeightForWidth()) self.label_203.setSizePolicy(sizePolicy) self.label_203.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_203.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_203.setObjectName("label_203") self.gridLayout_106.addWidget(self.label_203, 1, 0, 1, 1) self.label_186 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_186.sizePolicy().hasHeightForWidth()) self.label_186.setSizePolicy(sizePolicy) self.label_186.setMinimumSize(QtCore.QSize(229, 0)) self.label_186.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_186.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_186.setObjectName("label_186") self.gridLayout_106.addWidget(self.label_186, 0, 0, 1, 1) self.toolButton_reload_23 = QtWidgets.QToolButton(self.tab_cloud_mask) self.toolButton_reload_23.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_23.setIcon(icon55) self.toolButton_reload_23.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_23.setObjectName("toolButton_reload_23") self.gridLayout_106.addWidget(self.toolButton_reload_23, 0, 2, 1, 1) self.gridLayout_296.addLayout(self.gridLayout_106, 2, 0, 1, 2) self.gridLayout_143 = QtWidgets.QGridLayout() self.gridLayout_143.setObjectName("gridLayout_143") self.label_140 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_140.sizePolicy().hasHeightForWidth()) self.label_140.setSizePolicy(sizePolicy) self.label_140.setMinimumSize(QtCore.QSize(229, 0)) self.label_140.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_140.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_140.setObjectName("label_140") self.gridLayout_143.addWidget(self.label_140, 1, 0, 1, 1) self.mask_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_cloud_mask) self.mask_output_name_lineEdit.setMaxLength(10) self.mask_output_name_lineEdit.setObjectName("mask_output_name_lineEdit") self.gridLayout_143.addWidget(self.mask_output_name_lineEdit, 1, 1, 1, 1) self.gridLayout_145 = QtWidgets.QGridLayout() self.gridLayout_145.setObjectName("gridLayout_145") self.cloud_buffer_spinBox = QtWidgets.QSpinBox(self.tab_cloud_mask) self.cloud_buffer_spinBox.setMinimum(1) self.cloud_buffer_spinBox.setMaximum(1000) self.cloud_buffer_spinBox.setProperty("value", 1) self.cloud_buffer_spinBox.setObjectName("cloud_buffer_spinBox") self.gridLayout_145.addWidget(self.cloud_buffer_spinBox, 0, 1, 1, 1) spacerItem77 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_145.addItem(spacerItem77, 0, 2, 1, 1) self.cloud_buffer_checkBox = QtWidgets.QCheckBox(self.tab_cloud_mask) self.cloud_buffer_checkBox.setEnabled(True) self.cloud_buffer_checkBox.setObjectName("cloud_buffer_checkBox") self.gridLayout_145.addWidget(self.cloud_buffer_checkBox, 0, 0, 1, 1) self.nodata_spinBox_11 = QtWidgets.QSpinBox(self.tab_cloud_mask) self.nodata_spinBox_11.setMinimum(-2147483647) self.nodata_spinBox_11.setMaximum(2147483647) self.nodata_spinBox_11.setProperty("value", -32768) self.nodata_spinBox_11.setObjectName("nodata_spinBox_11") self.gridLayout_145.addWidget(self.nodata_spinBox_11, 1, 1, 1, 1) self.label_141 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_141.sizePolicy().hasHeightForWidth()) self.label_141.setSizePolicy(sizePolicy) self.label_141.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_141.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_141.setObjectName("label_141") self.gridLayout_145.addWidget(self.label_141, 1, 0, 1, 1) self.gridLayout_143.addLayout(self.gridLayout_145, 0, 0, 1, 2) self.gridLayout_296.addLayout(self.gridLayout_143, 3, 0, 1, 2) spacerItem78 = QtWidgets.QSpacerItem(20, 173, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_296.addItem(spacerItem78, 4, 1, 1, 1) self.gridLayout_257 = QtWidgets.QGridLayout() self.gridLayout_257.setObjectName("gridLayout_257") self.cloud_mask_toolButton = QtWidgets.QToolButton(self.tab_cloud_mask) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.cloud_mask_toolButton.setFont(font) self.cloud_mask_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.cloud_mask_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.cloud_mask_toolButton.setIcon(icon64) self.cloud_mask_toolButton.setIconSize(QtCore.QSize(34, 34)) self.cloud_mask_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.cloud_mask_toolButton.setObjectName("cloud_mask_toolButton") self.gridLayout_257.addWidget(self.cloud_mask_toolButton, 1, 2, 1, 1) self.cloud_masking = QtWidgets.QToolButton(self.tab_cloud_mask) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.cloud_masking.setFont(font) self.cloud_masking.setLayoutDirection(QtCore.Qt.RightToLeft) self.cloud_masking.setStyleSheet("margin: 0px;padding: 0px;") self.cloud_masking.setIcon(icon48) self.cloud_masking.setIconSize(QtCore.QSize(34, 34)) self.cloud_masking.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.cloud_masking.setObjectName("cloud_masking") self.gridLayout_257.addWidget(self.cloud_masking, 1, 1, 1, 1) spacerItem79 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_257.addItem(spacerItem79, 1, 0, 1, 1) self.label_185 = QtWidgets.QLabel(self.tab_cloud_mask) self.label_185.setStyleSheet("background-color : #656565; color : white") self.label_185.setFrameShape(QtWidgets.QFrame.Panel) self.label_185.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_185.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_185.setObjectName("label_185") self.gridLayout_257.addWidget(self.label_185, 0, 0, 1, 3) self.gridLayout_296.addLayout(self.gridLayout_257, 5, 0, 1, 2) self.horizontalLayout_33 = QtWidgets.QHBoxLayout() self.horizontalLayout_33.setObjectName("horizontalLayout_33") self.label_138 = QtWidgets.QLabel(self.tab_cloud_mask) self.label_138.setStyleSheet("background-color : #656565; color : white") self.label_138.setFrameShape(QtWidgets.QFrame.Panel) self.label_138.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_138.setObjectName("label_138") self.horizontalLayout_33.addWidget(self.label_138) self.gridLayout_296.addLayout(self.horizontalLayout_33, 0, 0, 1, 2) self.tabWidget_preprocessing.addTab(self.tab_cloud_mask, "") self.tab_GOES = QtWidgets.QWidget() self.tab_GOES.setObjectName("tab_GOES") self.gridLayout_308 = QtWidgets.QGridLayout(self.tab_GOES) self.gridLayout_308.setObjectName("gridLayout_308") self.gridLayout_297 = QtWidgets.QGridLayout() self.gridLayout_297.setObjectName("gridLayout_297") self.gridLayout_298 = QtWidgets.QGridLayout() self.gridLayout_298.setObjectName("gridLayout_298") self.GOES_nodata_spinBox = QtWidgets.QSpinBox(self.tab_GOES) self.GOES_nodata_spinBox.setMinimum(-999) self.GOES_nodata_spinBox.setMaximum(100000) self.GOES_nodata_spinBox.setObjectName("GOES_nodata_spinBox") self.gridLayout_298.addWidget(self.GOES_nodata_spinBox, 0, 2, 1, 1) self.GOES_nodata_checkBox = QtWidgets.QCheckBox(self.tab_GOES) self.GOES_nodata_checkBox.setChecked(True) self.GOES_nodata_checkBox.setObjectName("GOES_nodata_checkBox") self.gridLayout_298.addWidget(self.GOES_nodata_checkBox, 0, 1, 1, 1) spacerItem80 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_298.addItem(spacerItem80, 0, 0, 1, 1) self.gridLayout_297.addLayout(self.gridLayout_298, 3, 1, 1, 2) self.label_273 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_273.sizePolicy().hasHeightForWidth()) self.label_273.setSizePolicy(sizePolicy) self.label_273.setStyleSheet("background-color : #656565; color : white") self.label_273.setFrameShape(QtWidgets.QFrame.Panel) self.label_273.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_273.setObjectName("label_273") self.gridLayout_297.addWidget(self.label_273, 0, 0, 1, 3) self.GOES_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_GOES) self.GOES_create_bandset_checkBox.setChecked(True) self.GOES_create_bandset_checkBox.setTristate(False) self.GOES_create_bandset_checkBox.setObjectName("GOES_create_bandset_checkBox") self.gridLayout_297.addWidget(self.GOES_create_bandset_checkBox, 4, 0, 1, 1) self.label_274 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_274.sizePolicy().hasHeightForWidth()) self.label_274.setSizePolicy(sizePolicy) self.label_274.setMinimumSize(QtCore.QSize(229, 0)) self.label_274.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_274.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_274.setObjectName("label_274") self.gridLayout_297.addWidget(self.label_274, 2, 0, 1, 1) self.gridLayout_299 = QtWidgets.QGridLayout() self.gridLayout_299.setObjectName("gridLayout_299") self.GOES_toolButton_directoryInput = QtWidgets.QToolButton(self.tab_GOES) self.GOES_toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.GOES_toolButton_directoryInput.setIcon(icon69) self.GOES_toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.GOES_toolButton_directoryInput.setObjectName("GOES_toolButton_directoryInput") self.gridLayout_299.addWidget(self.GOES_toolButton_directoryInput, 0, 1, 1, 1) self.GOES_label = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.GOES_label.sizePolicy().hasHeightForWidth()) self.GOES_label.setSizePolicy(sizePolicy) self.GOES_label.setFrameShape(QtWidgets.QFrame.Panel) self.GOES_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.GOES_label.setText("") self.GOES_label.setObjectName("GOES_label") self.gridLayout_299.addWidget(self.GOES_label, 0, 0, 1, 1) self.gridLayout_297.addLayout(self.gridLayout_299, 2, 1, 1, 2) self.add_new_bandset_checkBox_7 = QtWidgets.QCheckBox(self.tab_GOES) self.add_new_bandset_checkBox_7.setChecked(True) self.add_new_bandset_checkBox_7.setTristate(False) self.add_new_bandset_checkBox_7.setObjectName("add_new_bandset_checkBox_7") self.gridLayout_297.addWidget(self.add_new_bandset_checkBox_7, 4, 1, 1, 2) self.gridLayout_308.addLayout(self.gridLayout_297, 0, 0, 1, 1) self.gridLayout_304 = QtWidgets.QGridLayout() self.gridLayout_304.setObjectName("gridLayout_304") self.GOES_tableWidget = QtWidgets.QTableWidget(self.tab_GOES) self.GOES_tableWidget.setTextElideMode(QtCore.Qt.ElideMiddle) self.GOES_tableWidget.setObjectName("GOES_tableWidget") self.GOES_tableWidget.setColumnCount(1) self.GOES_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.GOES_tableWidget.setHorizontalHeaderItem(0, item) self.GOES_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.GOES_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_304.addWidget(self.GOES_tableWidget, 1, 0, 1, 1) self.gridLayout_305 = QtWidgets.QGridLayout() self.gridLayout_305.setObjectName("gridLayout_305") self.GOES_pushButton_remove_band = QtWidgets.QToolButton(self.tab_GOES) self.GOES_pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.GOES_pushButton_remove_band.setIcon(icon58) self.GOES_pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.GOES_pushButton_remove_band.setObjectName("GOES_pushButton_remove_band") self.gridLayout_305.addWidget(self.GOES_pushButton_remove_band, 0, 0, 1, 1) self.gridLayout_304.addLayout(self.gridLayout_305, 1, 1, 1, 1) self.gridLayout_306 = QtWidgets.QGridLayout() self.gridLayout_306.setObjectName("gridLayout_306") self.label_277 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_277.sizePolicy().hasHeightForWidth()) self.label_277.setSizePolicy(sizePolicy) self.label_277.setStyleSheet("background-color : #656565; color : white") self.label_277.setFrameShape(QtWidgets.QFrame.Panel) self.label_277.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_277.setObjectName("label_277") self.gridLayout_306.addWidget(self.label_277, 0, 0, 1, 4) self.satellite_label_20 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_20.sizePolicy().hasHeightForWidth()) self.satellite_label_20.setSizePolicy(sizePolicy) self.satellite_label_20.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_20.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.satellite_label_20.setObjectName("satellite_label_20") self.gridLayout_306.addWidget(self.satellite_label_20, 1, 0, 1, 1) self.GOES_satellite_lineEdit = QtWidgets.QLineEdit(self.tab_GOES) self.GOES_satellite_lineEdit.setObjectName("GOES_satellite_lineEdit") self.gridLayout_306.addWidget(self.GOES_satellite_lineEdit, 1, 1, 1, 1) spacerItem81 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_306.addItem(spacerItem81, 1, 2, 1, 1) self.gridLayout_304.addLayout(self.gridLayout_306, 0, 0, 1, 2) self.gridLayout_307 = QtWidgets.QGridLayout() self.gridLayout_307.setObjectName("gridLayout_307") spacerItem82 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_307.addItem(spacerItem82, 1, 1, 1, 1) self.label_278 = QtWidgets.QLabel(self.tab_GOES) self.label_278.setStyleSheet("background-color : #656565; color : white") self.label_278.setFrameShape(QtWidgets.QFrame.Panel) self.label_278.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_278.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_278.setObjectName("label_278") self.gridLayout_307.addWidget(self.label_278, 0, 1, 1, 3) self.pushButton_Conversion_8 = QtWidgets.QToolButton(self.tab_GOES) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_8.setFont(font) self.pushButton_Conversion_8.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_8.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_8.setIcon(icon64) self.pushButton_Conversion_8.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_8.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_8.setObjectName("pushButton_Conversion_8") self.gridLayout_307.addWidget(self.pushButton_Conversion_8, 1, 3, 1, 1) self.goes_conversion = QtWidgets.QToolButton(self.tab_GOES) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.goes_conversion.setFont(font) self.goes_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.goes_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.goes_conversion.setIcon(icon48) self.goes_conversion.setIconSize(QtCore.QSize(34, 34)) self.goes_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.goes_conversion.setObjectName("goes_conversion") self.gridLayout_307.addWidget(self.goes_conversion, 1, 2, 1, 1) self.gridLayout_304.addLayout(self.gridLayout_307, 2, 0, 1, 2) self.gridLayout_308.addLayout(self.gridLayout_304, 1, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_GOES, "") self.tab_neighbor_pixels = QtWidgets.QWidget() self.tab_neighbor_pixels.setObjectName("tab_neighbor_pixels") self.gridLayout_310 = QtWidgets.QGridLayout(self.tab_neighbor_pixels) self.gridLayout_310.setObjectName("gridLayout_310") self.gridLayout_240 = QtWidgets.QGridLayout() self.gridLayout_240.setObjectName("gridLayout_240") self.label_283 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_283.setStyleSheet("background-color : #656565; color : white") self.label_283.setFrameShape(QtWidgets.QFrame.Panel) self.label_283.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_283.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_283.setObjectName("label_283") self.gridLayout_240.addWidget(self.label_283, 8, 0, 1, 3) self.gridLayout_309 = QtWidgets.QGridLayout() self.gridLayout_309.setObjectName("gridLayout_309") self.label_287 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_287.sizePolicy().hasHeightForWidth()) self.label_287.setSizePolicy(sizePolicy) self.label_287.setFrameShape(QtWidgets.QFrame.Panel) self.label_287.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_287.setText("") self.label_287.setObjectName("label_287") self.gridLayout_309.addWidget(self.label_287, 0, 1, 1, 1) self.label_281 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_281.sizePolicy().hasHeightForWidth()) self.label_281.setSizePolicy(sizePolicy) self.label_281.setMinimumSize(QtCore.QSize(229, 0)) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_281.setFont(font) self.label_281.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_281.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_281.setObjectName("label_281") self.gridLayout_309.addWidget(self.label_281, 0, 0, 1, 1) self.toolButton_input_matrix = QtWidgets.QToolButton(self.tab_neighbor_pixels) self.toolButton_input_matrix.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_input_matrix.setIcon(icon65) self.toolButton_input_matrix.setIconSize(QtCore.QSize(22, 22)) self.toolButton_input_matrix.setObjectName("toolButton_input_matrix") self.gridLayout_309.addWidget(self.toolButton_input_matrix, 0, 2, 1, 1) self.horizontalLayout_71 = QtWidgets.QHBoxLayout() self.horizontalLayout_71.setObjectName("horizontalLayout_71") self.label_279 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_279.sizePolicy().hasHeightForWidth()) self.label_279.setSizePolicy(sizePolicy) self.label_279.setMinimumSize(QtCore.QSize(229, 0)) self.label_279.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_279.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_279.setObjectName("label_279") self.horizontalLayout_71.addWidget(self.label_279) self.neighbor_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_neighbor_pixels) self.neighbor_output_name_lineEdit.setMaxLength(10) self.neighbor_output_name_lineEdit.setObjectName("neighbor_output_name_lineEdit") self.horizontalLayout_71.addWidget(self.neighbor_output_name_lineEdit) self.gridLayout_309.addLayout(self.horizontalLayout_71, 2, 0, 1, 3) self.neighbor_virtual_checkBox = QtWidgets.QCheckBox(self.tab_neighbor_pixels) self.neighbor_virtual_checkBox.setObjectName("neighbor_virtual_checkBox") self.gridLayout_309.addWidget(self.neighbor_virtual_checkBox, 1, 0, 1, 1) self.gridLayout_240.addLayout(self.gridLayout_309, 2, 0, 1, 3) self.neighbor_pixels = QtWidgets.QToolButton(self.tab_neighbor_pixels) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.neighbor_pixels.setFont(font) self.neighbor_pixels.setLayoutDirection(QtCore.Qt.RightToLeft) self.neighbor_pixels.setStyleSheet("margin: 0px;padding: 0px;") self.neighbor_pixels.setIcon(icon48) self.neighbor_pixels.setIconSize(QtCore.QSize(34, 34)) self.neighbor_pixels.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.neighbor_pixels.setObjectName("neighbor_pixels") self.gridLayout_240.addWidget(self.neighbor_pixels, 9, 1, 1, 1) spacerItem83 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_240.addItem(spacerItem83, 9, 0, 1, 1) self.class_neighbor_toolButton = QtWidgets.QToolButton(self.tab_neighbor_pixels) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_neighbor_toolButton.setFont(font) self.class_neighbor_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_neighbor_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.class_neighbor_toolButton.setIcon(icon64) self.class_neighbor_toolButton.setIconSize(QtCore.QSize(34, 34)) self.class_neighbor_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_neighbor_toolButton.setObjectName("class_neighbor_toolButton") self.gridLayout_240.addWidget(self.class_neighbor_toolButton, 9, 2, 1, 1) spacerItem84 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_240.addItem(spacerItem84, 7, 2, 1, 1) self.horizontalLayout_70 = QtWidgets.QHBoxLayout() self.horizontalLayout_70.setObjectName("horizontalLayout_70") self.label_286 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_286.setStyleSheet("background-color : #656565; color : white") self.label_286.setFrameShape(QtWidgets.QFrame.Panel) self.label_286.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_286.setObjectName("label_286") self.horizontalLayout_70.addWidget(self.label_286) self.gridLayout_240.addLayout(self.horizontalLayout_70, 0, 0, 1, 3) self.gridLayout_277 = QtWidgets.QGridLayout() self.gridLayout_277.setObjectName("gridLayout_277") self.statistic_lineEdit_2 = QtWidgets.QLineEdit(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_lineEdit_2.sizePolicy().hasHeightForWidth()) self.statistic_lineEdit_2.setSizePolicy(sizePolicy) self.statistic_lineEdit_2.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_lineEdit_2.setText("") self.statistic_lineEdit_2.setMaxLength(10000) self.statistic_lineEdit_2.setObjectName("statistic_lineEdit_2") self.gridLayout_277.addWidget(self.statistic_lineEdit_2, 1, 2, 1, 1) self.statistic_name_combobox_2 = QtWidgets.QComboBox(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_name_combobox_2.sizePolicy().hasHeightForWidth()) self.statistic_name_combobox_2.setSizePolicy(sizePolicy) self.statistic_name_combobox_2.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_name_combobox_2.setObjectName("statistic_name_combobox_2") self.gridLayout_277.addWidget(self.statistic_name_combobox_2, 1, 1, 1, 1) self.label_284 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_284.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_284.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_284.setObjectName("label_284") self.gridLayout_277.addWidget(self.label_284, 1, 0, 1, 1) spacerItem85 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_277.addItem(spacerItem85, 1, 3, 1, 1) self.label_285 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_285.setStyleSheet("background-color : #656565; color : white") self.label_285.setFrameShape(QtWidgets.QFrame.Panel) self.label_285.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_285.setObjectName("label_285") self.gridLayout_277.addWidget(self.label_285, 0, 0, 1, 4) self.gridLayout_240.addLayout(self.gridLayout_277, 6, 0, 1, 3) self.gridLayout_300 = QtWidgets.QGridLayout() self.gridLayout_300.setObjectName("gridLayout_300") self.label_282 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_282.sizePolicy().hasHeightForWidth()) self.label_282.setSizePolicy(sizePolicy) self.label_282.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_282.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_282.setObjectName("label_282") self.gridLayout_300.addWidget(self.label_282, 0, 0, 1, 1) self.label_280 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_280.sizePolicy().hasHeightForWidth()) self.label_280.setSizePolicy(sizePolicy) self.label_280.setMinimumSize(QtCore.QSize(229, 0)) self.label_280.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_280.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_280.setObjectName("label_280") self.gridLayout_300.addWidget(self.label_280, 1, 0, 1, 1) self.band_set_comb_spinBox_15 = QtWidgets.QSpinBox(self.tab_neighbor_pixels) self.band_set_comb_spinBox_15.setMinimum(1) self.band_set_comb_spinBox_15.setMaximum(100000) self.band_set_comb_spinBox_15.setObjectName("band_set_comb_spinBox_15") self.gridLayout_300.addWidget(self.band_set_comb_spinBox_15, 0, 1, 1, 1) self.class_neighbor_threshold_spinBox = QtWidgets.QSpinBox(self.tab_neighbor_pixels) self.class_neighbor_threshold_spinBox.setMinimum(1) self.class_neighbor_threshold_spinBox.setMaximum(1000) self.class_neighbor_threshold_spinBox.setProperty("value", 1) self.class_neighbor_threshold_spinBox.setObjectName("class_neighbor_threshold_spinBox") self.gridLayout_300.addWidget(self.class_neighbor_threshold_spinBox, 1, 1, 1, 1) spacerItem86 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_300.addItem(spacerItem86, 1, 3, 1, 1) self.circular_structure_checkBox = QtWidgets.QCheckBox(self.tab_neighbor_pixels) self.circular_structure_checkBox.setObjectName("circular_structure_checkBox") self.gridLayout_300.addWidget(self.circular_structure_checkBox, 1, 2, 1, 1) self.gridLayout_240.addLayout(self.gridLayout_300, 1, 0, 1, 3) self.horizontalLayout_72 = QtWidgets.QHBoxLayout() self.horizontalLayout_72.setObjectName("horizontalLayout_72") spacerItem87 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_72.addItem(spacerItem87) self.gridLayout_240.addLayout(self.horizontalLayout_72, 3, 0, 1, 3) self.gridLayout_310.addLayout(self.gridLayout_240, 0, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_neighbor_pixels, "") self.gridLayout_6.addWidget(self.tabWidget_preprocessing, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_preprocessing, "") self.tab_band_processing = QtWidgets.QWidget() self.tab_band_processing.setObjectName("tab_band_processing") self.gridLayout_163 = QtWidgets.QGridLayout(self.tab_band_processing) self.gridLayout_163.setObjectName("gridLayout_163") self.tabWidget_4 = QtWidgets.QTabWidget(self.tab_band_processing) self.tabWidget_4.setStyleSheet("") self.tabWidget_4.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_4.setDocumentMode(True) self.tabWidget_4.setObjectName("tabWidget_4") self.tab_bandset_combination_2 = QtWidgets.QWidget() self.tab_bandset_combination_2.setObjectName("tab_bandset_combination_2") self.gridLayout_62 = QtWidgets.QGridLayout(self.tab_bandset_combination_2) self.gridLayout_62.setObjectName("gridLayout_62") self.toolBox_band_set_combination = QtWidgets.QToolBox(self.tab_bandset_combination_2) self.toolBox_band_set_combination.setObjectName("toolBox_band_set_combination") self.page_29 = QtWidgets.QWidget() self.page_29.setGeometry(QtCore.QRect(0, 0, 723, 351)) self.page_29.setObjectName("page_29") self.gridLayout_330 = QtWidgets.QGridLayout(self.page_29) self.gridLayout_330.setObjectName("gridLayout_330") self.gridLayout_333 = QtWidgets.QGridLayout() self.gridLayout_333.setObjectName("gridLayout_333") spacerItem88 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_333.addItem(spacerItem88, 0, 2, 1, 1) spacerItem89 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_333.addItem(spacerItem89, 2, 0, 1, 1) self.label_253 = QtWidgets.QLabel(self.page_29) self.label_253.setStyleSheet("background-color : #656565; color : white") self.label_253.setFrameShape(QtWidgets.QFrame.Panel) self.label_253.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_253.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_253.setObjectName("label_253") self.gridLayout_333.addWidget(self.label_253, 1, 0, 1, 3) self.calculateBandSetComb_toolButton = QtWidgets.QToolButton(self.page_29) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateBandSetComb_toolButton.setFont(font) self.calculateBandSetComb_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateBandSetComb_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateBandSetComb_toolButton.setIcon(icon64) self.calculateBandSetComb_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateBandSetComb_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateBandSetComb_toolButton.setObjectName("calculateBandSetComb_toolButton") self.gridLayout_333.addWidget(self.calculateBandSetComb_toolButton, 2, 2, 1, 1) self.band_combination = QtWidgets.QToolButton(self.page_29) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.band_combination.setFont(font) self.band_combination.setLayoutDirection(QtCore.Qt.RightToLeft) self.band_combination.setStyleSheet("margin: 0px;padding: 0px;") self.band_combination.setIcon(icon48) self.band_combination.setIconSize(QtCore.QSize(34, 34)) self.band_combination.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.band_combination.setObjectName("band_combination") self.gridLayout_333.addWidget(self.band_combination, 2, 1, 1, 1) self.gridLayout_330.addLayout(self.gridLayout_333, 2, 1, 1, 1) self.gridLayout_331 = QtWidgets.QGridLayout() self.gridLayout_331.setObjectName("gridLayout_331") self.label_250 = QtWidgets.QLabel(self.page_29) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_250.sizePolicy().hasHeightForWidth()) self.label_250.setSizePolicy(sizePolicy) self.label_250.setMinimumSize(QtCore.QSize(229, 0)) self.label_250.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_250.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_250.setWordWrap(True) self.label_250.setObjectName("label_250") self.gridLayout_331.addWidget(self.label_250, 1, 0, 1, 2) self.band_set_comb_spinBox = QtWidgets.QSpinBox(self.page_29) self.band_set_comb_spinBox.setMinimum(1) self.band_set_comb_spinBox.setMaximum(100000) self.band_set_comb_spinBox.setObjectName("band_set_comb_spinBox") self.gridLayout_331.addWidget(self.band_set_comb_spinBox, 1, 2, 1, 1) spacerItem90 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_331.addItem(spacerItem90, 1, 3, 1, 1) self.gridLayout_330.addLayout(self.gridLayout_331, 1, 1, 1, 1) self.horizontalLayout_34 = QtWidgets.QHBoxLayout() self.horizontalLayout_34.setObjectName("horizontalLayout_34") self.label_72 = QtWidgets.QLabel(self.page_29) self.label_72.setStyleSheet("background-color : #656565; color : white") self.label_72.setFrameShape(QtWidgets.QFrame.Panel) self.label_72.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_72.setObjectName("label_72") self.horizontalLayout_34.addWidget(self.label_72) self.gridLayout_330.addLayout(self.horizontalLayout_34, 0, 1, 1, 1) self.toolBox_band_set_combination.addItem(self.page_29, "") self.page_30 = QtWidgets.QWidget() self.page_30.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_30.setObjectName("page_30") self.gridLayout_334 = QtWidgets.QGridLayout(self.page_30) self.gridLayout_334.setObjectName("gridLayout_334") self.gridLayout_335 = QtWidgets.QGridLayout() self.gridLayout_335.setObjectName("gridLayout_335") self.band_set_comb_textBrowser = QtWidgets.QTextBrowser(self.page_30) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.band_set_comb_textBrowser.setFont(font) self.band_set_comb_textBrowser.setTabChangesFocus(True) self.band_set_comb_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.band_set_comb_textBrowser.setTabStopWidth(120) self.band_set_comb_textBrowser.setOpenLinks(False) self.band_set_comb_textBrowser.setObjectName("band_set_comb_textBrowser") self.gridLayout_335.addWidget(self.band_set_comb_textBrowser, 0, 0, 1, 1) self.gridLayout_334.addLayout(self.gridLayout_335, 0, 0, 1, 1) self.toolBox_band_set_combination.addItem(self.page_30, "") self.gridLayout_62.addWidget(self.toolBox_band_set_combination, 0, 0, 1, 1) self.tabWidget_4.addTab(self.tab_bandset_combination_2, "") self.PCA_tab = QtWidgets.QWidget() self.PCA_tab.setObjectName("PCA_tab") self.gridLayout_170 = QtWidgets.QGridLayout(self.PCA_tab) self.gridLayout_170.setObjectName("gridLayout_170") self.toolBox_PCA = QtWidgets.QToolBox(self.PCA_tab) self.toolBox_PCA.setStyleSheet("") self.toolBox_PCA.setObjectName("toolBox_PCA") self.page_16 = QtWidgets.QWidget() self.page_16.setGeometry(QtCore.QRect(0, 0, 459, 196)) self.page_16.setObjectName("page_16") self.gridLayout_182 = QtWidgets.QGridLayout(self.page_16) self.gridLayout_182.setObjectName("gridLayout_182") self.horizontalLayout_5 = QtWidgets.QHBoxLayout() self.horizontalLayout_5.setObjectName("horizontalLayout_5") self.label_58 = QtWidgets.QLabel(self.page_16) self.label_58.setStyleSheet("background-color : #656565; color : white") self.label_58.setFrameShape(QtWidgets.QFrame.Panel) self.label_58.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_58.setObjectName("label_58") self.horizontalLayout_5.addWidget(self.label_58) self.gridLayout_182.addLayout(self.horizontalLayout_5, 0, 0, 1, 1) self.gridLayout_173 = QtWidgets.QGridLayout() self.gridLayout_173.setObjectName("gridLayout_173") self.nodata_checkBox_4 = QtWidgets.QCheckBox(self.page_16) self.nodata_checkBox_4.setObjectName("nodata_checkBox_4") self.gridLayout_173.addWidget(self.nodata_checkBox_4, 2, 0, 1, 1) self.num_comp_checkBox = QtWidgets.QCheckBox(self.page_16) self.num_comp_checkBox.setObjectName("num_comp_checkBox") self.gridLayout_173.addWidget(self.num_comp_checkBox, 1, 0, 1, 1) self.nodata_spinBox_5 = QtWidgets.QSpinBox(self.page_16) self.nodata_spinBox_5.setMinimum(-999999999) self.nodata_spinBox_5.setMaximum(999999999) self.nodata_spinBox_5.setProperty("value", 0) self.nodata_spinBox_5.setObjectName("nodata_spinBox_5") self.gridLayout_173.addWidget(self.nodata_spinBox_5, 2, 1, 1, 1) spacerItem91 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_173.addItem(spacerItem91, 3, 4, 1, 1) self.pca_Button = QtWidgets.QToolButton(self.page_16) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pca_Button.setFont(font) self.pca_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.pca_Button.setStyleSheet("margin: 0px;padding: 0px;") self.pca_Button.setIcon(icon64) self.pca_Button.setIconSize(QtCore.QSize(34, 34)) self.pca_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pca_Button.setObjectName("pca_Button") self.gridLayout_173.addWidget(self.pca_Button, 5, 4, 1, 1) self.label_254 = QtWidgets.QLabel(self.page_16) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_254.sizePolicy().hasHeightForWidth()) self.label_254.setSizePolicy(sizePolicy) self.label_254.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_254.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_254.setObjectName("label_254") self.gridLayout_173.addWidget(self.label_254, 0, 0, 1, 1) self.band_set_comb_spinBox_4 = QtWidgets.QSpinBox(self.page_16) self.band_set_comb_spinBox_4.setMinimum(1) self.band_set_comb_spinBox_4.setMaximum(100000) self.band_set_comb_spinBox_4.setObjectName("band_set_comb_spinBox_4") self.gridLayout_173.addWidget(self.band_set_comb_spinBox_4, 0, 1, 1, 1) self.pca_components_spinBox = QtWidgets.QSpinBox(self.page_16) self.pca_components_spinBox.setMinimum(2) self.pca_components_spinBox.setMaximum(1000) self.pca_components_spinBox.setObjectName("pca_components_spinBox") self.gridLayout_173.addWidget(self.pca_components_spinBox, 1, 1, 1, 1) self.label_166 = QtWidgets.QLabel(self.page_16) self.label_166.setStyleSheet("background-color : #656565; color : white") self.label_166.setFrameShape(QtWidgets.QFrame.Panel) self.label_166.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_166.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_166.setObjectName("label_166") self.gridLayout_173.addWidget(self.label_166, 4, 0, 1, 5) spacerItem92 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_173.addItem(spacerItem92, 5, 2, 1, 1) self.pca = QtWidgets.QToolButton(self.page_16) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pca.setFont(font) self.pca.setLayoutDirection(QtCore.Qt.RightToLeft) self.pca.setStyleSheet("margin: 0px;padding: 0px;") self.pca.setIcon(icon48) self.pca.setIconSize(QtCore.QSize(34, 34)) self.pca.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pca.setObjectName("pca") self.gridLayout_173.addWidget(self.pca, 5, 3, 1, 1) self.gridLayout_182.addLayout(self.gridLayout_173, 1, 0, 1, 1) self.toolBox_PCA.addItem(self.page_16, "") self.page_17 = QtWidgets.QWidget() self.page_17.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_17.setObjectName("page_17") self.gridLayout_200 = QtWidgets.QGridLayout(self.page_17) self.gridLayout_200.setObjectName("gridLayout_200") self.gridLayout_201 = QtWidgets.QGridLayout() self.gridLayout_201.setObjectName("gridLayout_201") self.report_textBrowser_2 = QtWidgets.QTextBrowser(self.page_17) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_2.setFont(font) self.report_textBrowser_2.setTabChangesFocus(True) self.report_textBrowser_2.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_2.setTabStopWidth(160) self.report_textBrowser_2.setOpenLinks(False) self.report_textBrowser_2.setObjectName("report_textBrowser_2") self.gridLayout_201.addWidget(self.report_textBrowser_2, 0, 0, 1, 1) self.gridLayout_200.addLayout(self.gridLayout_201, 0, 0, 1, 1) self.toolBox_PCA.addItem(self.page_17, "") self.gridLayout_170.addWidget(self.toolBox_PCA, 0, 0, 1, 1) self.tabWidget_4.addTab(self.PCA_tab, "") self.tab_kmeans = QtWidgets.QWidget() self.tab_kmeans.setObjectName("tab_kmeans") self.gridLayout_208 = QtWidgets.QGridLayout(self.tab_kmeans) self.gridLayout_208.setObjectName("gridLayout_208") self.toolBox_kmeans = QtWidgets.QToolBox(self.tab_kmeans) self.toolBox_kmeans.setStyleSheet("") self.toolBox_kmeans.setObjectName("toolBox_kmeans") self.page_18 = QtWidgets.QWidget() self.page_18.setGeometry(QtCore.QRect(0, 0, 764, 390)) self.page_18.setObjectName("page_18") self.gridLayout_152 = QtWidgets.QGridLayout(self.page_18) self.gridLayout_152.setObjectName("gridLayout_152") self.horizontalLayout_29 = QtWidgets.QHBoxLayout() self.horizontalLayout_29.setObjectName("horizontalLayout_29") self.label_78 = QtWidgets.QLabel(self.page_18) self.label_78.setStyleSheet("background-color : #656565; color : white") self.label_78.setFrameShape(QtWidgets.QFrame.Panel) self.label_78.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_78.setObjectName("label_78") self.horizontalLayout_29.addWidget(self.label_78) self.gridLayout_152.addLayout(self.horizontalLayout_29, 0, 0, 1, 1) self.gridLayout_151 = QtWidgets.QGridLayout() self.gridLayout_151.setObjectName("gridLayout_151") self.isodata_radioButton = QtWidgets.QRadioButton(self.page_18) self.isodata_radioButton.setChecked(False) self.isodata_radioButton.setAutoExclusive(False) self.isodata_radioButton.setObjectName("isodata_radioButton") self.gridLayout_151.addWidget(self.isodata_radioButton, 0, 5, 1, 1) self.band_set_comb_spinBox_5 = QtWidgets.QSpinBox(self.page_18) self.band_set_comb_spinBox_5.setMinimum(1) self.band_set_comb_spinBox_5.setMaximum(100000) self.band_set_comb_spinBox_5.setObjectName("band_set_comb_spinBox_5") self.gridLayout_151.addWidget(self.band_set_comb_spinBox_5, 0, 1, 1, 1) self.label_230 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_230.sizePolicy().hasHeightForWidth()) self.label_230.setSizePolicy(sizePolicy) self.label_230.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_230.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_230.setObjectName("label_230") self.gridLayout_151.addWidget(self.label_230, 0, 3, 1, 1) self.label_255 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_255.sizePolicy().hasHeightForWidth()) self.label_255.setSizePolicy(sizePolicy) self.label_255.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_255.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_255.setObjectName("label_255") self.gridLayout_151.addWidget(self.label_255, 0, 0, 1, 1) self.kmeans_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmeans_radioButton.setChecked(True) self.kmeans_radioButton.setAutoExclusive(False) self.kmeans_radioButton.setObjectName("kmeans_radioButton") self.gridLayout_151.addWidget(self.kmeans_radioButton, 0, 4, 1, 1) spacerItem93 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_151.addItem(spacerItem93, 0, 2, 1, 1) spacerItem94 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_151.addItem(spacerItem94, 0, 6, 1, 1) self.gridLayout_152.addLayout(self.gridLayout_151, 1, 0, 1, 1) self.gridLayout_125 = QtWidgets.QGridLayout() self.gridLayout_125.setObjectName("gridLayout_125") self.label_225 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_225.sizePolicy().hasHeightForWidth()) self.label_225.setSizePolicy(sizePolicy) self.label_225.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_225.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_225.setObjectName("label_225") self.gridLayout_125.addWidget(self.label_225, 1, 0, 1, 1) self.thresh_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.page_18) self.thresh_doubleSpinBox.setDecimals(7) self.thresh_doubleSpinBox.setMinimum(1e-06) self.thresh_doubleSpinBox.setMaximum(10000000.0) self.thresh_doubleSpinBox.setSingleStep(1e-05) self.thresh_doubleSpinBox.setProperty("value", 0.0001) self.thresh_doubleSpinBox.setObjectName("thresh_doubleSpinBox") self.gridLayout_125.addWidget(self.thresh_doubleSpinBox, 0, 1, 1, 1) self.std_dev_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.page_18) self.std_dev_doubleSpinBox.setDecimals(7) self.std_dev_doubleSpinBox.setMinimum(1e-06) self.std_dev_doubleSpinBox.setMaximum(1000000000.0) self.std_dev_doubleSpinBox.setSingleStep(1e-05) self.std_dev_doubleSpinBox.setProperty("value", 0.0001) self.std_dev_doubleSpinBox.setObjectName("std_dev_doubleSpinBox") self.gridLayout_125.addWidget(self.std_dev_doubleSpinBox, 2, 1, 1, 1) self.kmean_threshold_checkBox = QtWidgets.QCheckBox(self.page_18) self.kmean_threshold_checkBox.setChecked(True) self.kmean_threshold_checkBox.setObjectName("kmean_threshold_checkBox") self.gridLayout_125.addWidget(self.kmean_threshold_checkBox, 0, 0, 1, 1) self.nodata_spinBox_9 = QtWidgets.QSpinBox(self.page_18) self.nodata_spinBox_9.setMinimum(-999999999) self.nodata_spinBox_9.setMaximum(999999999) self.nodata_spinBox_9.setProperty("value", 0) self.nodata_spinBox_9.setObjectName("nodata_spinBox_9") self.gridLayout_125.addWidget(self.nodata_spinBox_9, 4, 1, 1, 1) self.kmeans_iter_spinBox = QtWidgets.QSpinBox(self.page_18) self.kmeans_iter_spinBox.setMinimum(1) self.kmeans_iter_spinBox.setMaximum(1000) self.kmeans_iter_spinBox.setProperty("value", 10) self.kmeans_iter_spinBox.setObjectName("kmeans_iter_spinBox") self.gridLayout_125.addWidget(self.kmeans_iter_spinBox, 1, 1, 1, 1) self.label_228 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_228.sizePolicy().hasHeightForWidth()) self.label_228.setSizePolicy(sizePolicy) self.label_228.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_228.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_228.setWordWrap(True) self.label_228.setObjectName("label_228") self.gridLayout_125.addWidget(self.label_228, 2, 0, 1, 1) self.nodata_checkBox_8 = QtWidgets.QCheckBox(self.page_18) self.nodata_checkBox_8.setObjectName("nodata_checkBox_8") self.gridLayout_125.addWidget(self.nodata_checkBox_8, 4, 0, 1, 1) self.kmeans_classes_spinBox = QtWidgets.QSpinBox(self.page_18) self.kmeans_classes_spinBox.setMinimum(1) self.kmeans_classes_spinBox.setMaximum(1000) self.kmeans_classes_spinBox.setProperty("value", 10) self.kmeans_classes_spinBox.setObjectName("kmeans_classes_spinBox") self.gridLayout_125.addWidget(self.kmeans_classes_spinBox, 0, 3, 1, 1) self.label_224 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_224.sizePolicy().hasHeightForWidth()) self.label_224.setSizePolicy(sizePolicy) self.label_224.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_224.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_224.setObjectName("label_224") self.gridLayout_125.addWidget(self.label_224, 0, 2, 1, 1) spacerItem95 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_125.addItem(spacerItem95, 0, 4, 1, 1) self.label_229 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_229.sizePolicy().hasHeightForWidth()) self.label_229.setSizePolicy(sizePolicy) self.label_229.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_229.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_229.setWordWrap(True) self.label_229.setObjectName("label_229") self.gridLayout_125.addWidget(self.label_229, 2, 2, 1, 1) self.min_size_class_spinBox = QtWidgets.QSpinBox(self.page_18) self.min_size_class_spinBox.setMinimum(1) self.min_size_class_spinBox.setMaximum(1000000) self.min_size_class_spinBox.setProperty("value", 10) self.min_size_class_spinBox.setObjectName("min_size_class_spinBox") self.gridLayout_125.addWidget(self.min_size_class_spinBox, 2, 3, 1, 1) self.gridLayout_152.addLayout(self.gridLayout_125, 2, 0, 1, 1) self.gridLayout_231 = QtWidgets.QGridLayout() self.gridLayout_231.setObjectName("gridLayout_231") self.gridLayout_135 = QtWidgets.QGridLayout() self.gridLayout_135.setObjectName("gridLayout_135") self.min_distance_radioButton = QtWidgets.QRadioButton(self.page_18) self.min_distance_radioButton.setChecked(True) self.min_distance_radioButton.setAutoExclusive(False) self.min_distance_radioButton.setObjectName("min_distance_radioButton") self.gridLayout_135.addWidget(self.min_distance_radioButton, 2, 1, 1, 1) self.kmean_save_siglist_checkBox = QtWidgets.QCheckBox(self.page_18) self.kmean_save_siglist_checkBox.setObjectName("kmean_save_siglist_checkBox") self.gridLayout_135.addWidget(self.kmean_save_siglist_checkBox, 3, 0, 1, 4) self.label_227 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_227.sizePolicy().hasHeightForWidth()) self.label_227.setSizePolicy(sizePolicy) self.label_227.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_227.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_227.setObjectName("label_227") self.gridLayout_135.addWidget(self.label_227, 2, 0, 1, 1) self.horizontalLayout_30 = QtWidgets.QHBoxLayout() self.horizontalLayout_30.setObjectName("horizontalLayout_30") self.label_104 = QtWidgets.QLabel(self.page_18) self.label_104.setStyleSheet("background-color : #656565; color : white") self.label_104.setFrameShape(QtWidgets.QFrame.Panel) self.label_104.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_104.setObjectName("label_104") self.horizontalLayout_30.addWidget(self.label_104) self.gridLayout_135.addLayout(self.horizontalLayout_30, 0, 0, 1, 4) self.gridLayout_10 = QtWidgets.QGridLayout() self.gridLayout_10.setObjectName("gridLayout_10") self.gridLayout_226 = QtWidgets.QGridLayout() self.gridLayout_226.setObjectName("gridLayout_226") self.kmean_siglist_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmean_siglist_radioButton.setChecked(False) self.kmean_siglist_radioButton.setAutoExclusive(False) self.kmean_siglist_radioButton.setObjectName("kmean_siglist_radioButton") self.gridLayout_226.addWidget(self.kmean_siglist_radioButton, 0, 1, 1, 1) self.kmean_randomsiglist_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmean_randomsiglist_radioButton.setChecked(False) self.kmean_randomsiglist_radioButton.setAutoExclusive(False) self.kmean_randomsiglist_radioButton.setObjectName("kmean_randomsiglist_radioButton") self.gridLayout_226.addWidget(self.kmean_randomsiglist_radioButton, 0, 2, 1, 1) self.kmean_minmax_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmean_minmax_radioButton.setChecked(True) self.kmean_minmax_radioButton.setAutoExclusive(False) self.kmean_minmax_radioButton.setObjectName("kmean_minmax_radioButton") self.gridLayout_226.addWidget(self.kmean_minmax_radioButton, 0, 0, 1, 1) self.gridLayout_10.addLayout(self.gridLayout_226, 1, 0, 1, 1) self.gridLayout_135.addLayout(self.gridLayout_10, 1, 0, 1, 4) self.spectral_angle_map_radioButton = QtWidgets.QRadioButton(self.page_18) self.spectral_angle_map_radioButton.setChecked(False) self.spectral_angle_map_radioButton.setAutoExclusive(False) self.spectral_angle_map_radioButton.setObjectName("spectral_angle_map_radioButton") self.gridLayout_135.addWidget(self.spectral_angle_map_radioButton, 2, 2, 1, 1) self.gridLayout_231.addLayout(self.gridLayout_135, 0, 0, 1, 4) self.label_179 = QtWidgets.QLabel(self.page_18) self.label_179.setStyleSheet("background-color : #656565; color : white") self.label_179.setFrameShape(QtWidgets.QFrame.Panel) self.label_179.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_179.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_179.setObjectName("label_179") self.gridLayout_231.addWidget(self.label_179, 2, 0, 1, 4) spacerItem96 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_231.addItem(spacerItem96, 3, 0, 1, 2) self.kmeans_Button = QtWidgets.QToolButton(self.page_18) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.kmeans_Button.setFont(font) self.kmeans_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.kmeans_Button.setStyleSheet("margin: 0px;padding: 0px;") self.kmeans_Button.setIcon(icon64) self.kmeans_Button.setIconSize(QtCore.QSize(34, 34)) self.kmeans_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.kmeans_Button.setObjectName("kmeans_Button") self.gridLayout_231.addWidget(self.kmeans_Button, 3, 3, 1, 1) self.clustering = QtWidgets.QToolButton(self.page_18) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.clustering.setFont(font) self.clustering.setLayoutDirection(QtCore.Qt.RightToLeft) self.clustering.setStyleSheet("margin: 0px;padding: 0px;") self.clustering.setIcon(icon48) self.clustering.setIconSize(QtCore.QSize(34, 34)) self.clustering.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.clustering.setObjectName("clustering") self.gridLayout_231.addWidget(self.clustering, 3, 2, 1, 1) spacerItem97 = QtWidgets.QSpacerItem(38, 0, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_231.addItem(spacerItem97, 1, 3, 1, 1) self.gridLayout_152.addLayout(self.gridLayout_231, 3, 0, 1, 1) self.toolBox_kmeans.addItem(self.page_18, "") self.page_23 = QtWidgets.QWidget() self.page_23.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_23.setObjectName("page_23") self.gridLayout_235 = QtWidgets.QGridLayout(self.page_23) self.gridLayout_235.setObjectName("gridLayout_235") self.gridLayout_236 = QtWidgets.QGridLayout() self.gridLayout_236.setObjectName("gridLayout_236") self.report_textBrowser_3 = QtWidgets.QTextBrowser(self.page_23) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_3.setFont(font) self.report_textBrowser_3.setTabChangesFocus(True) self.report_textBrowser_3.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_3.setTabStopWidth(160) self.report_textBrowser_3.setOpenLinks(False) self.report_textBrowser_3.setObjectName("report_textBrowser_3") self.gridLayout_236.addWidget(self.report_textBrowser_3, 0, 0, 1, 1) self.gridLayout_235.addLayout(self.gridLayout_236, 0, 0, 1, 1) self.toolBox_kmeans.addItem(self.page_23, "") self.gridLayout_208.addWidget(self.toolBox_kmeans, 0, 0, 1, 1) self.tabWidget_4.addTab(self.tab_kmeans, "") self.tab_spectral_dist = QtWidgets.QWidget() self.tab_spectral_dist.setObjectName("tab_spectral_dist") self.gridLayout_154 = QtWidgets.QGridLayout(self.tab_spectral_dist) self.gridLayout_154.setObjectName("gridLayout_154") self.gridLayout_149 = QtWidgets.QGridLayout() self.gridLayout_149.setObjectName("gridLayout_149") self.min_distance_radioButton_2 = QtWidgets.QRadioButton(self.tab_spectral_dist) self.min_distance_radioButton_2.setChecked(True) self.min_distance_radioButton_2.setAutoExclusive(False) self.min_distance_radioButton_2.setObjectName("min_distance_radioButton_2") self.gridLayout_149.addWidget(self.min_distance_radioButton_2, 2, 1, 1, 1) self.label_231 = QtWidgets.QLabel(self.tab_spectral_dist) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_231.sizePolicy().hasHeightForWidth()) self.label_231.setSizePolicy(sizePolicy) self.label_231.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_231.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_231.setObjectName("label_231") self.gridLayout_149.addWidget(self.label_231, 2, 0, 1, 1) self.spectral_angle_map_radioButton_2 = QtWidgets.QRadioButton(self.tab_spectral_dist) self.spectral_angle_map_radioButton_2.setChecked(False) self.spectral_angle_map_radioButton_2.setAutoExclusive(False) self.spectral_angle_map_radioButton_2.setObjectName("spectral_angle_map_radioButton_2") self.gridLayout_149.addWidget(self.spectral_angle_map_radioButton_2, 2, 2, 1, 1) self.horizontalLayout_32 = QtWidgets.QHBoxLayout() self.horizontalLayout_32.setObjectName("horizontalLayout_32") self.horizontalLayout_31 = QtWidgets.QHBoxLayout() self.horizontalLayout_31.setObjectName("horizontalLayout_31") self.label_137 = QtWidgets.QLabel(self.tab_spectral_dist) self.label_137.setStyleSheet("background-color : #656565; color : white") self.label_137.setFrameShape(QtWidgets.QFrame.Panel) self.label_137.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_137.setObjectName("label_137") self.horizontalLayout_31.addWidget(self.label_137) self.horizontalLayout_32.addLayout(self.horizontalLayout_31) self.gridLayout_149.addLayout(self.horizontalLayout_32, 0, 0, 1, 4) self.distance_threshold_checkBox = QtWidgets.QCheckBox(self.tab_spectral_dist) self.distance_threshold_checkBox.setChecked(True) self.distance_threshold_checkBox.setObjectName("distance_threshold_checkBox") self.gridLayout_149.addWidget(self.distance_threshold_checkBox, 3, 0, 1, 1) self.thresh_doubleSpinBox_2 = QtWidgets.QDoubleSpinBox(self.tab_spectral_dist) self.thresh_doubleSpinBox_2.setDecimals(7) self.thresh_doubleSpinBox_2.setMinimum(1e-06) self.thresh_doubleSpinBox_2.setMaximum(1000.0) self.thresh_doubleSpinBox_2.setSingleStep(1.0) self.thresh_doubleSpinBox_2.setProperty("value", 0.1) self.thresh_doubleSpinBox_2.setObjectName("thresh_doubleSpinBox_2") self.gridLayout_149.addWidget(self.thresh_doubleSpinBox_2, 3, 1, 1, 1) self.gridLayout_41 = QtWidgets.QGridLayout() self.gridLayout_41.setObjectName("gridLayout_41") self.label_256 = QtWidgets.QLabel(self.tab_spectral_dist) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_256.sizePolicy().hasHeightForWidth()) self.label_256.setSizePolicy(sizePolicy) self.label_256.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_256.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_256.setObjectName("label_256") self.gridLayout_41.addWidget(self.label_256, 0, 0, 1, 1) self.band_set_comb_spinBox_7 = QtWidgets.QSpinBox(self.tab_spectral_dist) self.band_set_comb_spinBox_7.setMinimum(1) self.band_set_comb_spinBox_7.setMaximum(100000) self.band_set_comb_spinBox_7.setProperty("value", 2) self.band_set_comb_spinBox_7.setObjectName("band_set_comb_spinBox_7") self.gridLayout_41.addWidget(self.band_set_comb_spinBox_7, 1, 1, 1, 1) self.label_257 = QtWidgets.QLabel(self.tab_spectral_dist) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_257.sizePolicy().hasHeightForWidth()) self.label_257.setSizePolicy(sizePolicy) self.label_257.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_257.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_257.setObjectName("label_257") self.gridLayout_41.addWidget(self.label_257, 1, 0, 1, 1) self.band_set_comb_spinBox_6 = QtWidgets.QSpinBox(self.tab_spectral_dist) self.band_set_comb_spinBox_6.setMinimum(1) self.band_set_comb_spinBox_6.setMaximum(100000) self.band_set_comb_spinBox_6.setObjectName("band_set_comb_spinBox_6") self.gridLayout_41.addWidget(self.band_set_comb_spinBox_6, 0, 1, 1, 1) spacerItem98 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_41.addItem(spacerItem98, 1, 2, 1, 1) self.gridLayout_149.addLayout(self.gridLayout_41, 1, 0, 1, 4) self.gridLayout_154.addLayout(self.gridLayout_149, 0, 0, 1, 1) self.gridLayout_233 = QtWidgets.QGridLayout() self.gridLayout_233.setObjectName("gridLayout_233") self.label_183 = QtWidgets.QLabel(self.tab_spectral_dist) self.label_183.setStyleSheet("background-color : #656565; color : white") self.label_183.setFrameShape(QtWidgets.QFrame.Panel) self.label_183.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_183.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_183.setObjectName("label_183") self.gridLayout_233.addWidget(self.label_183, 1, 0, 1, 4) spacerItem99 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_233.addItem(spacerItem99, 2, 0, 1, 2) spacerItem100 = QtWidgets.QSpacerItem(38, 37, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_233.addItem(spacerItem100, 0, 3, 1, 1) self.spectral_distance_bandsets_toolButton = QtWidgets.QToolButton(self.tab_spectral_dist) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.spectral_distance_bandsets_toolButton.setFont(font) self.spectral_distance_bandsets_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.spectral_distance_bandsets_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.spectral_distance_bandsets_toolButton.setIcon(icon64) self.spectral_distance_bandsets_toolButton.setIconSize(QtCore.QSize(34, 34)) self.spectral_distance_bandsets_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.spectral_distance_bandsets_toolButton.setObjectName("spectral_distance_bandsets_toolButton") self.gridLayout_233.addWidget(self.spectral_distance_bandsets_toolButton, 2, 3, 1, 1) self.spectral_distance = QtWidgets.QToolButton(self.tab_spectral_dist) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.spectral_distance.setFont(font) self.spectral_distance.setLayoutDirection(QtCore.Qt.RightToLeft) self.spectral_distance.setStyleSheet("margin: 0px;padding: 0px;") self.spectral_distance.setIcon(icon48) self.spectral_distance.setIconSize(QtCore.QSize(34, 34)) self.spectral_distance.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.spectral_distance.setObjectName("spectral_distance") self.gridLayout_233.addWidget(self.spectral_distance, 2, 2, 1, 1) self.gridLayout_154.addLayout(self.gridLayout_233, 1, 0, 1, 1) self.tabWidget_4.addTab(self.tab_spectral_dist, "") self.tab_classification = QtWidgets.QWidget() self.tab_classification.setObjectName("tab_classification") self.gridLayout_260 = QtWidgets.QGridLayout(self.tab_classification) self.gridLayout_260.setObjectName("gridLayout_260") self.gridLayout_218 = QtWidgets.QGridLayout() self.gridLayout_218.setObjectName("gridLayout_218") self.horizontalLayout_55 = QtWidgets.QHBoxLayout() self.horizontalLayout_55.setObjectName("horizontalLayout_55") self.label_32 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_32.sizePolicy().hasHeightForWidth()) self.label_32.setSizePolicy(sizePolicy) self.label_32.setObjectName("label_32") self.horizontalLayout_55.addWidget(self.label_32) self.macroclass_checkBox = QtWidgets.QCheckBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.macroclass_checkBox.sizePolicy().hasHeightForWidth()) self.macroclass_checkBox.setSizePolicy(sizePolicy) self.macroclass_checkBox.setObjectName("macroclass_checkBox") self.horizontalLayout_55.addWidget(self.macroclass_checkBox) self.class_checkBox = QtWidgets.QCheckBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_checkBox.sizePolicy().hasHeightForWidth()) self.class_checkBox.setSizePolicy(sizePolicy) self.class_checkBox.setObjectName("class_checkBox") self.horizontalLayout_55.addWidget(self.class_checkBox) spacerItem101 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_55.addItem(spacerItem101) self.algorithm_weight_button = QtWidgets.QToolButton(self.tab_classification) self.algorithm_weight_button.setStyleSheet("margin: 0px;padding: 0px;") self.algorithm_weight_button.setIcon(icon3) self.algorithm_weight_button.setIconSize(QtCore.QSize(22, 22)) self.algorithm_weight_button.setObjectName("algorithm_weight_button") self.horizontalLayout_55.addWidget(self.algorithm_weight_button) self.gridLayout_218.addLayout(self.horizontalLayout_55, 2, 0, 1, 4) self.algorithm_combo = QtWidgets.QComboBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.algorithm_combo.sizePolicy().hasHeightForWidth()) self.algorithm_combo.setSizePolicy(sizePolicy) self.algorithm_combo.setMinimumSize(QtCore.QSize(100, 0)) self.algorithm_combo.setObjectName("algorithm_combo") self.algorithm_combo.addItem("") self.algorithm_combo.addItem("") self.algorithm_combo.addItem("") self.gridLayout_218.addWidget(self.algorithm_combo, 4, 0, 1, 3) self.band_set_comb_spinBox_12 = QtWidgets.QSpinBox(self.tab_classification) self.band_set_comb_spinBox_12.setMinimum(1) self.band_set_comb_spinBox_12.setMaximum(100000) self.band_set_comb_spinBox_12.setObjectName("band_set_comb_spinBox_12") self.gridLayout_218.addWidget(self.band_set_comb_spinBox_12, 1, 1, 1, 1) self.label_261 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_261.sizePolicy().hasHeightForWidth()) self.label_261.setSizePolicy(sizePolicy) self.label_261.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_261.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_261.setObjectName("label_261") self.gridLayout_218.addWidget(self.label_261, 1, 0, 1, 1) self.label_240 = QtWidgets.QLabel(self.tab_classification) self.label_240.setStyleSheet("background-color : #656565; color : white") self.label_240.setFrameShape(QtWidgets.QFrame.Panel) self.label_240.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_240.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_240.setObjectName("label_240") self.gridLayout_218.addWidget(self.label_240, 3, 0, 1, 4) self.gridLayout_255 = QtWidgets.QGridLayout() self.gridLayout_255.setObjectName("gridLayout_255") self.alg_threshold_SpinBox = QtWidgets.QDoubleSpinBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.alg_threshold_SpinBox.sizePolicy().hasHeightForWidth()) self.alg_threshold_SpinBox.setSizePolicy(sizePolicy) self.alg_threshold_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.alg_threshold_SpinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.alg_threshold_SpinBox.setDecimals(4) self.alg_threshold_SpinBox.setMaximum(10000.0) self.alg_threshold_SpinBox.setObjectName("alg_threshold_SpinBox") self.gridLayout_255.addWidget(self.alg_threshold_SpinBox, 0, 1, 1, 1) self.algorithm_threshold_button = QtWidgets.QToolButton(self.tab_classification) self.algorithm_threshold_button.setStyleSheet("margin: 0px;padding: 0px;") self.algorithm_threshold_button.setIcon(icon9) self.algorithm_threshold_button.setIconSize(QtCore.QSize(22, 22)) self.algorithm_threshold_button.setObjectName("algorithm_threshold_button") self.gridLayout_255.addWidget(self.algorithm_threshold_button, 0, 3, 1, 1) self.label_234 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_234.sizePolicy().hasHeightForWidth()) self.label_234.setSizePolicy(sizePolicy) self.label_234.setMaximumSize(QtCore.QSize(100, 16777215)) self.label_234.setObjectName("label_234") self.gridLayout_255.addWidget(self.label_234, 0, 0, 1, 1) spacerItem102 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_255.addItem(spacerItem102, 0, 2, 1, 1) self.gridLayout_218.addLayout(self.gridLayout_255, 4, 3, 1, 1) self.label_243 = QtWidgets.QLabel(self.tab_classification) self.label_243.setStyleSheet("background-color : #656565; color : white") self.label_243.setFrameShape(QtWidgets.QFrame.Panel) self.label_243.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_243.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_243.setObjectName("label_243") self.gridLayout_218.addWidget(self.label_243, 0, 0, 1, 4) spacerItem103 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_218.addItem(spacerItem103, 1, 3, 1, 1) self.gridLayout_260.addLayout(self.gridLayout_218, 0, 0, 1, 1) self.verticalLayout_4 = QtWidgets.QVBoxLayout() self.verticalLayout_4.setObjectName("verticalLayout_4") self.gridLayout_225 = QtWidgets.QGridLayout() self.gridLayout_225.setObjectName("gridLayout_225") self.LC_signature_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.LC_signature_checkBox.setObjectName("LC_signature_checkBox") self.gridLayout_225.addWidget(self.LC_signature_checkBox, 1, 1, 1, 1) self.label_235 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_235.sizePolicy().hasHeightForWidth()) self.label_235.setSizePolicy(sizePolicy) self.label_235.setObjectName("label_235") self.gridLayout_225.addWidget(self.label_235, 1, 0, 1, 1) self.LC_signature_button = QtWidgets.QToolButton(self.tab_classification) self.LC_signature_button.setStyleSheet("margin: 0px;padding: 0px;") self.LC_signature_button.setText("") self.LC_signature_button.setIcon(icon6) self.LC_signature_button.setIconSize(QtCore.QSize(22, 22)) self.LC_signature_button.setObjectName("LC_signature_button") self.gridLayout_225.addWidget(self.LC_signature_button, 1, 5, 1, 1) self.LCS_leave_unclassified_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.LCS_leave_unclassified_checkBox.setObjectName("LCS_leave_unclassified_checkBox") self.gridLayout_225.addWidget(self.LCS_leave_unclassified_checkBox, 1, 3, 1, 1) self.label_241 = QtWidgets.QLabel(self.tab_classification) self.label_241.setStyleSheet("background-color : #656565; color : white") self.label_241.setFrameShape(QtWidgets.QFrame.Panel) self.label_241.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_241.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_241.setObjectName("label_241") self.gridLayout_225.addWidget(self.label_241, 0, 0, 1, 6) self.LCS_class_algorithm_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.LCS_class_algorithm_checkBox.setObjectName("LCS_class_algorithm_checkBox") self.gridLayout_225.addWidget(self.LCS_class_algorithm_checkBox, 1, 2, 1, 1) self.verticalLayout_4.addLayout(self.gridLayout_225) self.label_242 = QtWidgets.QLabel(self.tab_classification) self.label_242.setStyleSheet("background-color : #656565; color : white") self.label_242.setFrameShape(QtWidgets.QFrame.Panel) self.label_242.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_242.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_242.setObjectName("label_242") self.verticalLayout_4.addWidget(self.label_242) self.gridLayout_239 = QtWidgets.QGridLayout() self.gridLayout_239.setSpacing(4) self.gridLayout_239.setObjectName("gridLayout_239") self.resetQmlButton = QtWidgets.QToolButton(self.tab_classification) self.resetQmlButton.setStyleSheet("margin: 0px;padding: 0px;") self.resetQmlButton.setIcon(icon59) self.resetQmlButton.setIconSize(QtCore.QSize(22, 22)) self.resetQmlButton.setObjectName("resetQmlButton") self.gridLayout_239.addWidget(self.resetQmlButton, 0, 3, 1, 1) self.label_238 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_238.sizePolicy().hasHeightForWidth()) self.label_238.setSizePolicy(sizePolicy) self.label_238.setObjectName("label_238") self.gridLayout_239.addWidget(self.label_238, 0, 0, 1, 1) self.qml_Button = QtWidgets.QToolButton(self.tab_classification) self.qml_Button.setStyleSheet("margin: 0px;padding: 0px;") self.qml_Button.setIcon(icon65) self.qml_Button.setIconSize(QtCore.QSize(22, 22)) self.qml_Button.setObjectName("qml_Button") self.gridLayout_239.addWidget(self.qml_Button, 0, 2, 1, 1) self.qml_lineEdit = QtWidgets.QLineEdit(self.tab_classification) self.qml_lineEdit.setEnabled(False) self.qml_lineEdit.setObjectName("qml_lineEdit") self.gridLayout_239.addWidget(self.qml_lineEdit, 0, 1, 1, 1) self.verticalLayout_4.addLayout(self.gridLayout_239) self.gridLayout_241 = QtWidgets.QGridLayout() self.gridLayout_241.setObjectName("gridLayout_241") self.mask_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.mask_checkBox.setObjectName("mask_checkBox") self.gridLayout_241.addWidget(self.mask_checkBox, 0, 0, 1, 1) self.resetMaskButton = QtWidgets.QToolButton(self.tab_classification) self.resetMaskButton.setStyleSheet("margin: 0px;padding: 0px;") self.resetMaskButton.setIcon(icon59) self.resetMaskButton.setIconSize(QtCore.QSize(22, 22)) self.resetMaskButton.setObjectName("resetMaskButton") self.gridLayout_241.addWidget(self.resetMaskButton, 0, 3, 1, 1) self.mask_lineEdit = QtWidgets.QLineEdit(self.tab_classification) self.mask_lineEdit.setEnabled(False) self.mask_lineEdit.setInputMethodHints(QtCore.Qt.ImhUrlCharactersOnly) self.mask_lineEdit.setText("") self.mask_lineEdit.setObjectName("mask_lineEdit") self.gridLayout_241.addWidget(self.mask_lineEdit, 0, 1, 1, 2) self.verticalLayout_4.addLayout(self.gridLayout_241) self.horizontalLayout_56 = QtWidgets.QHBoxLayout() self.horizontalLayout_56.setObjectName("horizontalLayout_56") self.vector_output_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.vector_output_checkBox.setObjectName("vector_output_checkBox") self.horizontalLayout_56.addWidget(self.vector_output_checkBox) self.report_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.report_checkBox.setObjectName("report_checkBox") self.horizontalLayout_56.addWidget(self.report_checkBox) self.alg_files_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.alg_files_checkBox.setObjectName("alg_files_checkBox") self.horizontalLayout_56.addWidget(self.alg_files_checkBox) self.verticalLayout_4.addLayout(self.horizontalLayout_56) self.gridLayout_249 = QtWidgets.QGridLayout() self.gridLayout_249.setObjectName("gridLayout_249") self.button_classification = QtWidgets.QToolButton(self.tab_classification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.button_classification.setFont(font) self.button_classification.setLayoutDirection(QtCore.Qt.RightToLeft) self.button_classification.setStyleSheet("margin: 0px;padding: 0px;") self.button_classification.setIcon(icon64) self.button_classification.setIconSize(QtCore.QSize(34, 34)) self.button_classification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.button_classification.setObjectName("button_classification") self.gridLayout_249.addWidget(self.button_classification, 2, 2, 1, 1) self.label_239 = QtWidgets.QLabel(self.tab_classification) self.label_239.setStyleSheet("background-color : #656565; color : white") self.label_239.setFrameShape(QtWidgets.QFrame.Panel) self.label_239.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_239.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_239.setObjectName("label_239") self.gridLayout_249.addWidget(self.label_239, 1, 0, 1, 3) spacerItem104 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_249.addItem(spacerItem104, 0, 2, 1, 1) spacerItem105 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_249.addItem(spacerItem105, 2, 0, 1, 1) self.classification = QtWidgets.QToolButton(self.tab_classification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification.setFont(font) self.classification.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification.setStyleSheet("margin: 0px;padding: 0px;") self.classification.setIcon(icon48) self.classification.setIconSize(QtCore.QSize(34, 34)) self.classification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification.setObjectName("classification") self.gridLayout_249.addWidget(self.classification, 2, 1, 1, 1) self.verticalLayout_4.addLayout(self.gridLayout_249) self.gridLayout_260.addLayout(self.verticalLayout_4, 1, 0, 1, 1) self.tabWidget_4.addTab(self.tab_classification, "") self.tab_random_forest = QtWidgets.QWidget() self.tab_random_forest.setObjectName("tab_random_forest") self.gridLayout_288 = QtWidgets.QGridLayout(self.tab_random_forest) self.gridLayout_288.setObjectName("gridLayout_288") self.toolBox_random_forest = QtWidgets.QToolBox(self.tab_random_forest) self.toolBox_random_forest.setStyleSheet("") self.toolBox_random_forest.setObjectName("toolBox_random_forest") self.page_21 = QtWidgets.QWidget() self.page_21.setGeometry(QtCore.QRect(0, 0, 634, 327)) self.page_21.setObjectName("page_21") self.gridLayout_287 = QtWidgets.QGridLayout(self.page_21) self.gridLayout_287.setObjectName("gridLayout_287") self.gridLayout_280 = QtWidgets.QGridLayout() self.gridLayout_280.setObjectName("gridLayout_280") self.horizontalLayout_58 = QtWidgets.QHBoxLayout() self.horizontalLayout_58.setObjectName("horizontalLayout_58") self.label_233 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_233.sizePolicy().hasHeightForWidth()) self.label_233.setSizePolicy(sizePolicy) self.label_233.setObjectName("label_233") self.horizontalLayout_58.addWidget(self.label_233) self.macroclass_checkBox_rf = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.macroclass_checkBox_rf.sizePolicy().hasHeightForWidth()) self.macroclass_checkBox_rf.setSizePolicy(sizePolicy) self.macroclass_checkBox_rf.setChecked(True) self.macroclass_checkBox_rf.setObjectName("macroclass_checkBox_rf") self.horizontalLayout_58.addWidget(self.macroclass_checkBox_rf) self.class_checkBox_rf = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_checkBox_rf.sizePolicy().hasHeightForWidth()) self.class_checkBox_rf.setSizePolicy(sizePolicy) self.class_checkBox_rf.setObjectName("class_checkBox_rf") self.horizontalLayout_58.addWidget(self.class_checkBox_rf) spacerItem106 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_58.addItem(spacerItem106) self.gridLayout_280.addLayout(self.horizontalLayout_58, 2, 0, 1, 3) self.band_set_comb_spinBox_13 = QtWidgets.QSpinBox(self.page_21) self.band_set_comb_spinBox_13.setMinimum(1) self.band_set_comb_spinBox_13.setMaximum(100000) self.band_set_comb_spinBox_13.setObjectName("band_set_comb_spinBox_13") self.gridLayout_280.addWidget(self.band_set_comb_spinBox_13, 1, 1, 1, 1) self.label_262 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_262.sizePolicy().hasHeightForWidth()) self.label_262.setSizePolicy(sizePolicy) self.label_262.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_262.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_262.setObjectName("label_262") self.gridLayout_280.addWidget(self.label_262, 1, 0, 1, 1) self.label_245 = QtWidgets.QLabel(self.page_21) self.label_245.setStyleSheet("background-color : #656565; color : white") self.label_245.setFrameShape(QtWidgets.QFrame.Panel) self.label_245.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_245.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_245.setObjectName("label_245") self.gridLayout_280.addWidget(self.label_245, 0, 0, 1, 3) self.gridLayout_284 = QtWidgets.QGridLayout() self.gridLayout_284.setObjectName("gridLayout_284") self.number_trees_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.number_trees_SpinBox.sizePolicy().hasHeightForWidth()) self.number_trees_SpinBox.setSizePolicy(sizePolicy) self.number_trees_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.number_trees_SpinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.number_trees_SpinBox.setDecimals(0) self.number_trees_SpinBox.setMinimum(1.0) self.number_trees_SpinBox.setMaximum(1000000.0) self.number_trees_SpinBox.setSingleStep(1.0) self.number_trees_SpinBox.setProperty("value", 10.0) self.number_trees_SpinBox.setObjectName("number_trees_SpinBox") self.gridLayout_284.addWidget(self.number_trees_SpinBox, 0, 1, 1, 1) self.label_237 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_237.sizePolicy().hasHeightForWidth()) self.label_237.setSizePolicy(sizePolicy) self.label_237.setMaximumSize(QtCore.QSize(150, 16777215)) self.label_237.setObjectName("label_237") self.gridLayout_284.addWidget(self.label_237, 0, 0, 1, 1) spacerItem107 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_284.addItem(spacerItem107, 0, 2, 1, 1) self.gridLayout_280.addLayout(self.gridLayout_284, 4, 0, 1, 3) self.gridLayout_282 = QtWidgets.QGridLayout() self.gridLayout_282.setObjectName("gridLayout_282") self.number_training_samples_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.number_training_samples_SpinBox.sizePolicy().hasHeightForWidth()) self.number_training_samples_SpinBox.setSizePolicy(sizePolicy) self.number_training_samples_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.number_training_samples_SpinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.number_training_samples_SpinBox.setDecimals(0) self.number_training_samples_SpinBox.setMinimum(1.0) self.number_training_samples_SpinBox.setMaximum(1000000.0) self.number_training_samples_SpinBox.setSingleStep(100.0) self.number_training_samples_SpinBox.setProperty("value", 5000.0) self.number_training_samples_SpinBox.setObjectName("number_training_samples_SpinBox") self.gridLayout_282.addWidget(self.number_training_samples_SpinBox, 0, 1, 1, 1) self.label_236 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_236.sizePolicy().hasHeightForWidth()) self.label_236.setSizePolicy(sizePolicy) self.label_236.setMaximumSize(QtCore.QSize(208, 16777215)) self.label_236.setObjectName("label_236") self.gridLayout_282.addWidget(self.label_236, 0, 0, 1, 1) spacerItem108 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_282.addItem(spacerItem108, 0, 2, 1, 1) self.gridLayout_280.addLayout(self.gridLayout_282, 3, 0, 1, 3) spacerItem109 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_280.addItem(spacerItem109, 1, 2, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_280, 0, 0, 1, 1) self.gridLayout_285 = QtWidgets.QGridLayout() self.gridLayout_285.setObjectName("gridLayout_285") self.evaluate_classifier_checkBox = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.evaluate_classifier_checkBox.sizePolicy().hasHeightForWidth()) self.evaluate_classifier_checkBox.setSizePolicy(sizePolicy) self.evaluate_classifier_checkBox.setObjectName("evaluate_classifier_checkBox") self.gridLayout_285.addWidget(self.evaluate_classifier_checkBox, 0, 0, 1, 1) self.evaluate_feature_power_set_checkBox = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.evaluate_feature_power_set_checkBox.sizePolicy().hasHeightForWidth()) self.evaluate_feature_power_set_checkBox.setSizePolicy(sizePolicy) self.evaluate_feature_power_set_checkBox.setObjectName("evaluate_feature_power_set_checkBox") self.gridLayout_285.addWidget(self.evaluate_feature_power_set_checkBox, 0, 1, 1, 1) spacerItem110 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_285.addItem(spacerItem110, 0, 6, 1, 1) self.label_248 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_248.sizePolicy().hasHeightForWidth()) self.label_248.setSizePolicy(sizePolicy) self.label_248.setMaximumSize(QtCore.QSize(100, 16777215)) self.label_248.setObjectName("label_248") self.gridLayout_285.addWidget(self.label_248, 0, 4, 1, 1) self.rf_power_min_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.rf_power_min_SpinBox.sizePolicy().hasHeightForWidth()) self.rf_power_min_SpinBox.setSizePolicy(sizePolicy) self.rf_power_min_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.rf_power_min_SpinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.rf_power_min_SpinBox.setDecimals(0) self.rf_power_min_SpinBox.setMinimum(1.0) self.rf_power_min_SpinBox.setMaximum(1000000.0) self.rf_power_min_SpinBox.setSingleStep(1.0) self.rf_power_min_SpinBox.setProperty("value", 2.0) self.rf_power_min_SpinBox.setObjectName("rf_power_min_SpinBox") self.gridLayout_285.addWidget(self.rf_power_min_SpinBox, 0, 3, 1, 1) self.label_247 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_247.sizePolicy().hasHeightForWidth()) self.label_247.setSizePolicy(sizePolicy) self.label_247.setMaximumSize(QtCore.QSize(100, 16777215)) self.label_247.setObjectName("label_247") self.gridLayout_285.addWidget(self.label_247, 0, 2, 1, 1) self.rf_power_max_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.rf_power_max_SpinBox.sizePolicy().hasHeightForWidth()) self.rf_power_max_SpinBox.setSizePolicy(sizePolicy) self.rf_power_max_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.rf_power_max_SpinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.rf_power_max_SpinBox.setDecimals(0) self.rf_power_max_SpinBox.setMinimum(1.0) self.rf_power_max_SpinBox.setMaximum(1000000.0) self.rf_power_max_SpinBox.setSingleStep(1.0) self.rf_power_max_SpinBox.setProperty("value", 7.0) self.rf_power_max_SpinBox.setObjectName("rf_power_max_SpinBox") self.gridLayout_285.addWidget(self.rf_power_max_SpinBox, 0, 5, 1, 1) self.save_classifier_checkBox = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.save_classifier_checkBox.sizePolicy().hasHeightForWidth()) self.save_classifier_checkBox.setSizePolicy(sizePolicy) self.save_classifier_checkBox.setObjectName("save_classifier_checkBox") self.gridLayout_285.addWidget(self.save_classifier_checkBox, 1, 0, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_285, 1, 0, 1, 1) self.gridLayout_286 = QtWidgets.QGridLayout() self.gridLayout_286.setObjectName("gridLayout_286") self.label_244 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_244.sizePolicy().hasHeightForWidth()) self.label_244.setSizePolicy(sizePolicy) self.label_244.setObjectName("label_244") self.gridLayout_286.addWidget(self.label_244, 0, 0, 1, 1) self.classifier_Button = QtWidgets.QToolButton(self.page_21) self.classifier_Button.setStyleSheet("margin: 0px;padding: 0px;") self.classifier_Button.setIcon(icon65) self.classifier_Button.setIconSize(QtCore.QSize(22, 22)) self.classifier_Button.setObjectName("classifier_Button") self.gridLayout_286.addWidget(self.classifier_Button, 0, 2, 1, 1) self.classifier_lineEdit_ = QtWidgets.QLineEdit(self.page_21) self.classifier_lineEdit_.setEnabled(False) self.classifier_lineEdit_.setObjectName("classifier_lineEdit_") self.gridLayout_286.addWidget(self.classifier_lineEdit_, 0, 1, 1, 1) self.resetClassifierButton = QtWidgets.QToolButton(self.page_21) self.resetClassifierButton.setStyleSheet("margin: 0px;padding: 0px;") self.resetClassifierButton.setIcon(icon59) self.resetClassifierButton.setIconSize(QtCore.QSize(22, 22)) self.resetClassifierButton.setObjectName("resetClassifierButton") self.gridLayout_286.addWidget(self.resetClassifierButton, 0, 3, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_286, 2, 0, 1, 1) self.gridLayout_283 = QtWidgets.QGridLayout() self.gridLayout_283.setObjectName("gridLayout_283") self.button_random_forest = QtWidgets.QToolButton(self.page_21) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.button_random_forest.setFont(font) self.button_random_forest.setLayoutDirection(QtCore.Qt.RightToLeft) self.button_random_forest.setStyleSheet("margin: 0px;padding: 0px;") self.button_random_forest.setIcon(icon64) self.button_random_forest.setIconSize(QtCore.QSize(34, 34)) self.button_random_forest.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.button_random_forest.setObjectName("button_random_forest") self.gridLayout_283.addWidget(self.button_random_forest, 2, 2, 1, 1) self.label_246 = QtWidgets.QLabel(self.page_21) self.label_246.setStyleSheet("background-color : #656565; color : white") self.label_246.setFrameShape(QtWidgets.QFrame.Panel) self.label_246.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_246.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_246.setObjectName("label_246") self.gridLayout_283.addWidget(self.label_246, 1, 0, 1, 3) spacerItem111 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_283.addItem(spacerItem111, 0, 2, 1, 1) spacerItem112 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_283.addItem(spacerItem112, 2, 0, 1, 1) self.random_forest = QtWidgets.QToolButton(self.page_21) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.random_forest.setFont(font) self.random_forest.setLayoutDirection(QtCore.Qt.RightToLeft) self.random_forest.setStyleSheet("margin: 0px;padding: 0px;") self.random_forest.setIcon(icon48) self.random_forest.setIconSize(QtCore.QSize(34, 34)) self.random_forest.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.random_forest.setObjectName("random_forest") self.gridLayout_283.addWidget(self.random_forest, 2, 1, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_283, 3, 0, 1, 1) self.toolBox_random_forest.addItem(self.page_21, "") self.page_25 = QtWidgets.QWidget() self.page_25.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_25.setObjectName("page_25") self.gridLayout_293 = QtWidgets.QGridLayout(self.page_25) self.gridLayout_293.setObjectName("gridLayout_293") self.gridLayout_294 = QtWidgets.QGridLayout() self.gridLayout_294.setObjectName("gridLayout_294") self.report_textBrowser_5 = QtWidgets.QTextBrowser(self.page_25) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_5.setFont(font) self.report_textBrowser_5.setTabChangesFocus(True) self.report_textBrowser_5.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_5.setTabStopWidth(160) self.report_textBrowser_5.setOpenLinks(False) self.report_textBrowser_5.setObjectName("report_textBrowser_5") self.gridLayout_294.addWidget(self.report_textBrowser_5, 0, 0, 1, 1) self.gridLayout_293.addLayout(self.gridLayout_294, 0, 0, 1, 1) self.toolBox_random_forest.addItem(self.page_25, "") self.gridLayout_288.addWidget(self.toolBox_random_forest, 0, 0, 1, 1) self.tabWidget_4.addTab(self.tab_random_forest, "") self.gridLayout_163.addWidget(self.tabWidget_4, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_band_processing, "") self.tab_postProcessing = QtWidgets.QWidget() self.tab_postProcessing.setObjectName("tab_postProcessing") self.gridLayout_552 = QtWidgets.QGridLayout(self.tab_postProcessing) self.gridLayout_552.setObjectName("gridLayout_552") self.tabWidget_2 = QtWidgets.QTabWidget(self.tab_postProcessing) self.tabWidget_2.setStyleSheet("") self.tabWidget_2.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_2.setDocumentMode(True) self.tabWidget_2.setObjectName("tabWidget_2") self.tab_accuracy = QtWidgets.QWidget() self.tab_accuracy.setObjectName("tab_accuracy") self.gridLayout_184 = QtWidgets.QGridLayout(self.tab_accuracy) self.gridLayout_184.setObjectName("gridLayout_184") self.toolBox_accuracy = QtWidgets.QToolBox(self.tab_accuracy) self.toolBox_accuracy.setObjectName("toolBox_accuracy") self.page_10 = QtWidgets.QWidget() self.page_10.setGeometry(QtCore.QRect(0, 0, 723, 351)) self.page_10.setObjectName("page_10") self.gridLayout_36 = QtWidgets.QGridLayout(self.page_10) self.gridLayout_36.setObjectName("gridLayout_36") self.gridLayout_33 = QtWidgets.QGridLayout() self.gridLayout_33.setObjectName("gridLayout_33") self.label_33 = QtWidgets.QLabel(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_33.sizePolicy().hasHeightForWidth()) self.label_33.setSizePolicy(sizePolicy) self.label_33.setMinimumSize(QtCore.QSize(229, 0)) self.label_33.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_33.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_33.setObjectName("label_33") self.gridLayout_33.addWidget(self.label_33, 1, 0, 1, 1) self.label_34 = QtWidgets.QLabel(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_34.sizePolicy().hasHeightForWidth()) self.label_34.setSizePolicy(sizePolicy) self.label_34.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_34.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_34.setObjectName("label_34") self.gridLayout_33.addWidget(self.label_34, 2, 0, 1, 1) self.classification_name_combo = QtWidgets.QComboBox(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo.sizePolicy().hasHeightForWidth()) self.classification_name_combo.setSizePolicy(sizePolicy) self.classification_name_combo.setObjectName("classification_name_combo") self.gridLayout_33.addWidget(self.classification_name_combo, 1, 1, 1, 3) self.buttonReload_shape_4 = QtWidgets.QToolButton(self.page_10) self.buttonReload_shape_4.setStyleSheet("margin: 0px;padding: 0px;") self.buttonReload_shape_4.setIcon(icon55) self.buttonReload_shape_4.setIconSize(QtCore.QSize(22, 22)) self.buttonReload_shape_4.setObjectName("buttonReload_shape_4") self.gridLayout_33.addWidget(self.buttonReload_shape_4, 2, 4, 1, 1) self.toolButton_reload_4 = QtWidgets.QToolButton(self.page_10) self.toolButton_reload_4.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_4.setIcon(icon55) self.toolButton_reload_4.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_4.setObjectName("toolButton_reload_4") self.gridLayout_33.addWidget(self.toolButton_reload_4, 1, 4, 1, 1) self.reference_name_combo = QtWidgets.QComboBox(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_name_combo.sizePolicy().hasHeightForWidth()) self.reference_name_combo.setSizePolicy(sizePolicy) self.reference_name_combo.setObjectName("reference_name_combo") self.gridLayout_33.addWidget(self.reference_name_combo, 2, 1, 1, 3) self.horizontalLayout_36 = QtWidgets.QHBoxLayout() self.horizontalLayout_36.setObjectName("horizontalLayout_36") self.label_145 = QtWidgets.QLabel(self.page_10) self.label_145.setStyleSheet("background-color : #656565; color : white") self.label_145.setFrameShape(QtWidgets.QFrame.Panel) self.label_145.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_145.setObjectName("label_145") self.horizontalLayout_36.addWidget(self.label_145) self.gridLayout_33.addLayout(self.horizontalLayout_36, 0, 0, 1, 5) self.label_82 = QtWidgets.QLabel(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_82.sizePolicy().hasHeightForWidth()) self.label_82.setSizePolicy(sizePolicy) self.label_82.setMinimumSize(QtCore.QSize(6, 0)) self.label_82.setMaximumSize(QtCore.QSize(100, 200)) self.label_82.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_82.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_82.setObjectName("label_82") self.gridLayout_33.addWidget(self.label_82, 3, 1, 1, 1) self.class_field_comboBox = QtWidgets.QComboBox(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox.sizePolicy().hasHeightForWidth()) self.class_field_comboBox.setSizePolicy(sizePolicy) self.class_field_comboBox.setObjectName("class_field_comboBox") self.gridLayout_33.addWidget(self.class_field_comboBox, 3, 2, 1, 2) self.horizontalLayout_67 = QtWidgets.QHBoxLayout() self.horizontalLayout_67.setObjectName("horizontalLayout_67") self.nodata_checkBox_11 = QtWidgets.QCheckBox(self.page_10) self.nodata_checkBox_11.setObjectName("nodata_checkBox_11") self.horizontalLayout_67.addWidget(self.nodata_checkBox_11) self.nodata_spinBox_15 = QtWidgets.QSpinBox(self.page_10) self.nodata_spinBox_15.setMinimum(-2147483647) self.nodata_spinBox_15.setMaximum(2147483647) self.nodata_spinBox_15.setProperty("value", 0) self.nodata_spinBox_15.setObjectName("nodata_spinBox_15") self.horizontalLayout_67.addWidget(self.nodata_spinBox_15) spacerItem113 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_67.addItem(spacerItem113) self.gridLayout_33.addLayout(self.horizontalLayout_67, 4, 0, 1, 5) self.gridLayout_36.addLayout(self.gridLayout_33, 0, 0, 1, 1) self.gridLayout_25 = QtWidgets.QGridLayout() self.gridLayout_25.setObjectName("gridLayout_25") spacerItem114 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_25.addItem(spacerItem114, 0, 2, 1, 1) spacerItem115 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_25.addItem(spacerItem115, 2, 0, 1, 1) self.label_168 = QtWidgets.QLabel(self.page_10) self.label_168.setStyleSheet("background-color : #656565; color : white") self.label_168.setFrameShape(QtWidgets.QFrame.Panel) self.label_168.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_168.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_168.setObjectName("label_168") self.gridLayout_25.addWidget(self.label_168, 1, 0, 1, 3) self.calculateMatrix_toolButton = QtWidgets.QToolButton(self.page_10) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateMatrix_toolButton.setFont(font) self.calculateMatrix_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateMatrix_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateMatrix_toolButton.setIcon(icon64) self.calculateMatrix_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateMatrix_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateMatrix_toolButton.setObjectName("calculateMatrix_toolButton") self.gridLayout_25.addWidget(self.calculateMatrix_toolButton, 2, 2, 1, 1) self.accuracy = QtWidgets.QToolButton(self.page_10) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.accuracy.setFont(font) self.accuracy.setLayoutDirection(QtCore.Qt.RightToLeft) self.accuracy.setStyleSheet("margin: 0px;padding: 0px;") self.accuracy.setIcon(icon48) self.accuracy.setIconSize(QtCore.QSize(34, 34)) self.accuracy.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.accuracy.setObjectName("accuracy") self.gridLayout_25.addWidget(self.accuracy, 2, 1, 1, 1) self.gridLayout_36.addLayout(self.gridLayout_25, 1, 0, 1, 1) self.toolBox_accuracy.addItem(self.page_10, "") self.page_11 = QtWidgets.QWidget() self.page_11.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_11.setObjectName("page_11") self.gridLayout_35 = QtWidgets.QGridLayout(self.page_11) self.gridLayout_35.setObjectName("gridLayout_35") self.gridLayout_34 = QtWidgets.QGridLayout() self.gridLayout_34.setObjectName("gridLayout_34") self.error_matrix_textBrowser = QtWidgets.QTextBrowser(self.page_11) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.error_matrix_textBrowser.setFont(font) self.error_matrix_textBrowser.setTabChangesFocus(True) self.error_matrix_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.error_matrix_textBrowser.setTabStopWidth(120) self.error_matrix_textBrowser.setOpenLinks(False) self.error_matrix_textBrowser.setObjectName("error_matrix_textBrowser") self.gridLayout_34.addWidget(self.error_matrix_textBrowser, 0, 0, 1, 1) self.gridLayout_35.addLayout(self.gridLayout_34, 0, 0, 1, 1) self.toolBox_accuracy.addItem(self.page_11, "") self.gridLayout_184.addWidget(self.toolBox_accuracy, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_accuracy, "") self.tab_landCoverChange = QtWidgets.QWidget() self.tab_landCoverChange.setObjectName("tab_landCoverChange") self.gridLayout_187 = QtWidgets.QGridLayout(self.tab_landCoverChange) self.gridLayout_187.setObjectName("gridLayout_187") self.toolBox_landCoverChange = QtWidgets.QToolBox(self.tab_landCoverChange) self.toolBox_landCoverChange.setObjectName("toolBox_landCoverChange") self.page_12 = QtWidgets.QWidget() self.page_12.setGeometry(QtCore.QRect(0, 0, 385, 193)) self.page_12.setObjectName("page_12") self.gridLayout_186 = QtWidgets.QGridLayout(self.page_12) self.gridLayout_186.setObjectName("gridLayout_186") self.gridLayout_44 = QtWidgets.QGridLayout() self.gridLayout_44.setObjectName("gridLayout_44") self.mask_unchanged_checkBox = QtWidgets.QCheckBox(self.page_12) self.mask_unchanged_checkBox.setChecked(True) self.mask_unchanged_checkBox.setObjectName("mask_unchanged_checkBox") self.gridLayout_44.addWidget(self.mask_unchanged_checkBox, 3, 0, 1, 1) self.classification_reference_name_combo = QtWidgets.QComboBox(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_reference_name_combo.sizePolicy().hasHeightForWidth()) self.classification_reference_name_combo.setSizePolicy(sizePolicy) self.classification_reference_name_combo.setObjectName("classification_reference_name_combo") self.gridLayout_44.addWidget(self.classification_reference_name_combo, 1, 1, 1, 1) self.label_40 = QtWidgets.QLabel(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_40.sizePolicy().hasHeightForWidth()) self.label_40.setSizePolicy(sizePolicy) self.label_40.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_40.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_40.setObjectName("label_40") self.gridLayout_44.addWidget(self.label_40, 2, 0, 1, 1) self.label_38 = QtWidgets.QLabel(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_38.sizePolicy().hasHeightForWidth()) self.label_38.setSizePolicy(sizePolicy) self.label_38.setMinimumSize(QtCore.QSize(229, 0)) self.label_38.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_38.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_38.setObjectName("label_38") self.gridLayout_44.addWidget(self.label_38, 1, 0, 1, 1) self.new_classification_name_combo = QtWidgets.QComboBox(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.new_classification_name_combo.sizePolicy().hasHeightForWidth()) self.new_classification_name_combo.setSizePolicy(sizePolicy) self.new_classification_name_combo.setObjectName("new_classification_name_combo") self.gridLayout_44.addWidget(self.new_classification_name_combo, 2, 1, 1, 1) self.toolButton_reload_5 = QtWidgets.QToolButton(self.page_12) self.toolButton_reload_5.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_5.setIcon(icon55) self.toolButton_reload_5.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_5.setObjectName("toolButton_reload_5") self.gridLayout_44.addWidget(self.toolButton_reload_5, 1, 2, 1, 1) self.toolButton_reload_6 = QtWidgets.QToolButton(self.page_12) self.toolButton_reload_6.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_6.setIcon(icon55) self.toolButton_reload_6.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_6.setObjectName("toolButton_reload_6") self.gridLayout_44.addWidget(self.toolButton_reload_6, 2, 2, 1, 1) self.horizontalLayout_35 = QtWidgets.QHBoxLayout() self.horizontalLayout_35.setObjectName("horizontalLayout_35") self.label_116 = QtWidgets.QLabel(self.page_12) self.label_116.setStyleSheet("background-color : #656565; color : white") self.label_116.setFrameShape(QtWidgets.QFrame.Panel) self.label_116.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_116.setObjectName("label_116") self.horizontalLayout_35.addWidget(self.label_116) self.gridLayout_44.addLayout(self.horizontalLayout_35, 0, 0, 1, 3) self.gridLayout_186.addLayout(self.gridLayout_44, 0, 0, 1, 1) self.gridLayout_45 = QtWidgets.QGridLayout() self.gridLayout_45.setObjectName("gridLayout_45") spacerItem116 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_45.addItem(spacerItem116, 2, 0, 1, 1) spacerItem117 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_45.addItem(spacerItem117, 0, 2, 1, 1) self.label_169 = QtWidgets.QLabel(self.page_12) self.label_169.setStyleSheet("background-color : #656565; color : white") self.label_169.setFrameShape(QtWidgets.QFrame.Panel) self.label_169.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_169.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_169.setObjectName("label_169") self.gridLayout_45.addWidget(self.label_169, 1, 0, 1, 3) self.calculateLandCoverChange_toolButton = QtWidgets.QToolButton(self.page_12) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateLandCoverChange_toolButton.setFont(font) self.calculateLandCoverChange_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateLandCoverChange_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateLandCoverChange_toolButton.setIcon(icon64) self.calculateLandCoverChange_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateLandCoverChange_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateLandCoverChange_toolButton.setObjectName("calculateLandCoverChange_toolButton") self.gridLayout_45.addWidget(self.calculateLandCoverChange_toolButton, 2, 2, 1, 1) self.land_cover_change = QtWidgets.QToolButton(self.page_12) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.land_cover_change.setFont(font) self.land_cover_change.setLayoutDirection(QtCore.Qt.RightToLeft) self.land_cover_change.setStyleSheet("margin: 0px;padding: 0px;") self.land_cover_change.setIcon(icon48) self.land_cover_change.setIconSize(QtCore.QSize(34, 34)) self.land_cover_change.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.land_cover_change.setObjectName("land_cover_change") self.gridLayout_45.addWidget(self.land_cover_change, 2, 1, 1, 1) self.gridLayout_186.addLayout(self.gridLayout_45, 1, 0, 1, 1) self.toolBox_landCoverChange.addItem(self.page_12, "") self.page_13 = QtWidgets.QWidget() self.page_13.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_13.setObjectName("page_13") self.gridLayout_185 = QtWidgets.QGridLayout(self.page_13) self.gridLayout_185.setObjectName("gridLayout_185") self.gridLayout_46 = QtWidgets.QGridLayout() self.gridLayout_46.setObjectName("gridLayout_46") self.change_textBrowser = QtWidgets.QTextBrowser(self.page_13) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.change_textBrowser.setFont(font) self.change_textBrowser.setTabChangesFocus(True) self.change_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.change_textBrowser.setTabStopWidth(160) self.change_textBrowser.setOpenLinks(False) self.change_textBrowser.setObjectName("change_textBrowser") self.gridLayout_46.addWidget(self.change_textBrowser, 0, 0, 1, 1) self.gridLayout_185.addLayout(self.gridLayout_46, 0, 0, 1, 1) self.toolBox_landCoverChange.addItem(self.page_13, "") self.gridLayout_187.addWidget(self.toolBox_landCoverChange, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_landCoverChange, "") self.tab_class_report = QtWidgets.QWidget() self.tab_class_report.setObjectName("tab_class_report") self.gridLayout_27 = QtWidgets.QGridLayout(self.tab_class_report) self.gridLayout_27.setObjectName("gridLayout_27") self.toolBox_class_report = QtWidgets.QToolBox(self.tab_class_report) self.toolBox_class_report.setStyleSheet("") self.toolBox_class_report.setObjectName("toolBox_class_report") self.page_14 = QtWidgets.QWidget() self.page_14.setGeometry(QtCore.QRect(0, 0, 444, 167)) self.page_14.setObjectName("page_14") self.gridLayout_48 = QtWidgets.QGridLayout(self.page_14) self.gridLayout_48.setObjectName("gridLayout_48") self.gridLayout_47 = QtWidgets.QGridLayout() self.gridLayout_47.setObjectName("gridLayout_47") self.classification_report_name_combo = QtWidgets.QComboBox(self.page_14) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_report_name_combo.sizePolicy().hasHeightForWidth()) self.classification_report_name_combo.setSizePolicy(sizePolicy) self.classification_report_name_combo.setObjectName("classification_report_name_combo") self.gridLayout_47.addWidget(self.classification_report_name_combo, 1, 1, 1, 1) self.label_44 = QtWidgets.QLabel(self.page_14) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_44.sizePolicy().hasHeightForWidth()) self.label_44.setSizePolicy(sizePolicy) self.label_44.setMinimumSize(QtCore.QSize(229, 0)) self.label_44.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_44.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_44.setObjectName("label_44") self.gridLayout_47.addWidget(self.label_44, 1, 0, 1, 1) self.gridLayout_26 = QtWidgets.QGridLayout() self.gridLayout_26.setObjectName("gridLayout_26") self.nodata_checkBox = QtWidgets.QCheckBox(self.page_14) self.nodata_checkBox.setObjectName("nodata_checkBox") self.gridLayout_26.addWidget(self.nodata_checkBox, 0, 0, 1, 1) self.nodata_spinBox_2 = QtWidgets.QSpinBox(self.page_14) self.nodata_spinBox_2.setMinimum(-2147483647) self.nodata_spinBox_2.setMaximum(2147483647) self.nodata_spinBox_2.setProperty("value", 0) self.nodata_spinBox_2.setObjectName("nodata_spinBox_2") self.gridLayout_26.addWidget(self.nodata_spinBox_2, 0, 1, 1, 1) self.gridLayout_47.addLayout(self.gridLayout_26, 2, 0, 1, 1) self.toolButton_reload_10 = QtWidgets.QToolButton(self.page_14) self.toolButton_reload_10.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_10.setIcon(icon55) self.toolButton_reload_10.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_10.setObjectName("toolButton_reload_10") self.gridLayout_47.addWidget(self.toolButton_reload_10, 1, 2, 1, 1) self.gridLayout_48.addLayout(self.gridLayout_47, 1, 1, 1, 1) self.gridLayout_189 = QtWidgets.QGridLayout() self.gridLayout_189.setObjectName("gridLayout_189") spacerItem118 = QtWidgets.QSpacerItem(358, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_189.addItem(spacerItem118, 2, 1, 1, 1) self.label_170 = QtWidgets.QLabel(self.page_14) self.label_170.setStyleSheet("background-color : #656565; color : white") self.label_170.setFrameShape(QtWidgets.QFrame.Panel) self.label_170.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_170.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_170.setObjectName("label_170") self.gridLayout_189.addWidget(self.label_170, 1, 0, 1, 4) self.calculateReport_toolButton = QtWidgets.QToolButton(self.page_14) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateReport_toolButton.setFont(font) self.calculateReport_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateReport_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateReport_toolButton.setIcon(icon64) self.calculateReport_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateReport_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateReport_toolButton.setObjectName("calculateReport_toolButton") self.gridLayout_189.addWidget(self.calculateReport_toolButton, 2, 3, 1, 1) spacerItem119 = QtWidgets.QSpacerItem(20, 82, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_189.addItem(spacerItem119, 0, 0, 1, 2) self.classification_report = QtWidgets.QToolButton(self.page_14) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_report.setFont(font) self.classification_report.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_report.setStyleSheet("margin: 0px;padding: 0px;") self.classification_report.setIcon(icon48) self.classification_report.setIconSize(QtCore.QSize(34, 34)) self.classification_report.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_report.setObjectName("classification_report") self.gridLayout_189.addWidget(self.classification_report, 2, 2, 1, 1) self.gridLayout_48.addLayout(self.gridLayout_189, 2, 1, 1, 1) self.horizontalLayout_37 = QtWidgets.QHBoxLayout() self.horizontalLayout_37.setObjectName("horizontalLayout_37") self.label_148 = QtWidgets.QLabel(self.page_14) self.label_148.setStyleSheet("background-color : #656565; color : white") self.label_148.setFrameShape(QtWidgets.QFrame.Panel) self.label_148.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_148.setObjectName("label_148") self.horizontalLayout_37.addWidget(self.label_148) self.gridLayout_48.addLayout(self.horizontalLayout_37, 0, 1, 1, 1) self.toolBox_class_report.addItem(self.page_14, "") self.page_15 = QtWidgets.QWidget() self.page_15.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_15.setObjectName("page_15") self.gridLayout_188 = QtWidgets.QGridLayout(self.page_15) self.gridLayout_188.setObjectName("gridLayout_188") self.gridLayout_43 = QtWidgets.QGridLayout() self.gridLayout_43.setObjectName("gridLayout_43") self.report_textBrowser = QtWidgets.QTextBrowser(self.page_15) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser.setFont(font) self.report_textBrowser.setTabChangesFocus(True) self.report_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser.setTabStopWidth(160) self.report_textBrowser.setOpenLinks(False) self.report_textBrowser.setObjectName("report_textBrowser") self.gridLayout_43.addWidget(self.report_textBrowser, 0, 0, 1, 1) self.gridLayout_188.addLayout(self.gridLayout_43, 0, 0, 1, 1) self.toolBox_class_report.addItem(self.page_15, "") self.gridLayout_27.addWidget(self.toolBox_class_report, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_class_report, "") self.tab_cross_classification = QtWidgets.QWidget() self.tab_cross_classification.setObjectName("tab_cross_classification") self.gridLayout_254 = QtWidgets.QGridLayout(self.tab_cross_classification) self.gridLayout_254.setObjectName("gridLayout_254") self.toolBox_cross_classification = QtWidgets.QToolBox(self.tab_cross_classification) self.toolBox_cross_classification.setObjectName("toolBox_cross_classification") self.page_19 = QtWidgets.QWidget() self.page_19.setGeometry(QtCore.QRect(0, 0, 456, 229)) self.page_19.setObjectName("page_19") self.gridLayout_192 = QtWidgets.QGridLayout(self.page_19) self.gridLayout_192.setObjectName("gridLayout_192") self.horizontalLayout_38 = QtWidgets.QHBoxLayout() self.horizontalLayout_38.setObjectName("horizontalLayout_38") self.label_187 = QtWidgets.QLabel(self.page_19) self.label_187.setStyleSheet("background-color : #656565; color : white") self.label_187.setFrameShape(QtWidgets.QFrame.Panel) self.label_187.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_187.setObjectName("label_187") self.horizontalLayout_38.addWidget(self.label_187) self.gridLayout_192.addLayout(self.horizontalLayout_38, 0, 0, 1, 1) self.gridLayout_250 = QtWidgets.QGridLayout() self.gridLayout_250.setObjectName("gridLayout_250") self.gridLayout_248 = QtWidgets.QGridLayout() self.gridLayout_248.setObjectName("gridLayout_248") self.nodata_checkBox_6 = QtWidgets.QCheckBox(self.page_19) self.nodata_checkBox_6.setObjectName("nodata_checkBox_6") self.gridLayout_248.addWidget(self.nodata_checkBox_6, 0, 0, 1, 1) self.nodata_spinBox_7 = QtWidgets.QSpinBox(self.page_19) self.nodata_spinBox_7.setMinimum(-2147483647) self.nodata_spinBox_7.setMaximum(2147483647) self.nodata_spinBox_7.setObjectName("nodata_spinBox_7") self.gridLayout_248.addWidget(self.nodata_spinBox_7, 0, 1, 1, 1) self.gridLayout_250.addLayout(self.gridLayout_248, 2, 0, 1, 1) self.label_197 = QtWidgets.QLabel(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_197.sizePolicy().hasHeightForWidth()) self.label_197.setSizePolicy(sizePolicy) self.label_197.setMinimumSize(QtCore.QSize(229, 0)) self.label_197.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_197.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_197.setObjectName("label_197") self.gridLayout_250.addWidget(self.label_197, 1, 0, 1, 1) self.label_199 = QtWidgets.QLabel(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_199.sizePolicy().hasHeightForWidth()) self.label_199.setSizePolicy(sizePolicy) self.label_199.setMinimumSize(QtCore.QSize(6, 0)) self.label_199.setMaximumSize(QtCore.QSize(100, 200)) self.label_199.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_199.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_199.setObjectName("label_199") self.gridLayout_250.addWidget(self.label_199, 4, 1, 1, 1) self.class_field_comboBox_2 = QtWidgets.QComboBox(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox_2.sizePolicy().hasHeightForWidth()) self.class_field_comboBox_2.setSizePolicy(sizePolicy) self.class_field_comboBox_2.setObjectName("class_field_comboBox_2") self.gridLayout_250.addWidget(self.class_field_comboBox_2, 4, 2, 1, 2) self.toolButton_reload_21 = QtWidgets.QToolButton(self.page_19) self.toolButton_reload_21.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_21.setIcon(icon55) self.toolButton_reload_21.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_21.setObjectName("toolButton_reload_21") self.gridLayout_250.addWidget(self.toolButton_reload_21, 1, 4, 1, 1) self.classification_name_combo_2 = QtWidgets.QComboBox(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_2.sizePolicy().hasHeightForWidth()) self.classification_name_combo_2.setSizePolicy(sizePolicy) self.classification_name_combo_2.setObjectName("classification_name_combo_2") self.gridLayout_250.addWidget(self.classification_name_combo_2, 1, 1, 1, 3) self.buttonReload_shape_5 = QtWidgets.QToolButton(self.page_19) self.buttonReload_shape_5.setStyleSheet("margin: 0px;padding: 0px;") self.buttonReload_shape_5.setIcon(icon55) self.buttonReload_shape_5.setIconSize(QtCore.QSize(22, 22)) self.buttonReload_shape_5.setObjectName("buttonReload_shape_5") self.gridLayout_250.addWidget(self.buttonReload_shape_5, 3, 4, 1, 1) self.reference_name_combo_2 = QtWidgets.QComboBox(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_name_combo_2.sizePolicy().hasHeightForWidth()) self.reference_name_combo_2.setSizePolicy(sizePolicy) self.reference_name_combo_2.setObjectName("reference_name_combo_2") self.gridLayout_250.addWidget(self.reference_name_combo_2, 3, 1, 1, 3) self.label_198 = QtWidgets.QLabel(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_198.sizePolicy().hasHeightForWidth()) self.label_198.setSizePolicy(sizePolicy) self.label_198.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_198.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_198.setObjectName("label_198") self.gridLayout_250.addWidget(self.label_198, 3, 0, 1, 1) self.gridLayout_192.addLayout(self.gridLayout_250, 1, 0, 1, 1) self.gridLayout_251 = QtWidgets.QGridLayout() self.gridLayout_251.setObjectName("gridLayout_251") spacerItem120 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_251.addItem(spacerItem120, 0, 2, 1, 1) spacerItem121 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_251.addItem(spacerItem121, 2, 0, 1, 1) self.label_200 = QtWidgets.QLabel(self.page_19) self.label_200.setStyleSheet("background-color : #656565; color : white") self.label_200.setFrameShape(QtWidgets.QFrame.Panel) self.label_200.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_200.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_200.setObjectName("label_200") self.gridLayout_251.addWidget(self.label_200, 1, 0, 1, 3) self.calculatecrossClass_toolButton = QtWidgets.QToolButton(self.page_19) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculatecrossClass_toolButton.setFont(font) self.calculatecrossClass_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculatecrossClass_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculatecrossClass_toolButton.setIcon(icon64) self.calculatecrossClass_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculatecrossClass_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculatecrossClass_toolButton.setObjectName("calculatecrossClass_toolButton") self.gridLayout_251.addWidget(self.calculatecrossClass_toolButton, 2, 2, 1, 1) self.cross_classification = QtWidgets.QToolButton(self.page_19) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.cross_classification.setFont(font) self.cross_classification.setLayoutDirection(QtCore.Qt.RightToLeft) self.cross_classification.setStyleSheet("margin: 0px;padding: 0px;") self.cross_classification.setIcon(icon48) self.cross_classification.setIconSize(QtCore.QSize(34, 34)) self.cross_classification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.cross_classification.setObjectName("cross_classification") self.gridLayout_251.addWidget(self.cross_classification, 2, 1, 1, 1) self.gridLayout_192.addLayout(self.gridLayout_251, 2, 0, 1, 1) self.toolBox_cross_classification.addItem(self.page_19, "") self.page_22 = QtWidgets.QWidget() self.page_22.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_22.setObjectName("page_22") self.gridLayout_252 = QtWidgets.QGridLayout(self.page_22) self.gridLayout_252.setObjectName("gridLayout_252") self.gridLayout_253 = QtWidgets.QGridLayout() self.gridLayout_253.setObjectName("gridLayout_253") self.cross_matrix_textBrowser = QtWidgets.QTextBrowser(self.page_22) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.cross_matrix_textBrowser.setFont(font) self.cross_matrix_textBrowser.setTabChangesFocus(True) self.cross_matrix_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.cross_matrix_textBrowser.setTabStopWidth(120) self.cross_matrix_textBrowser.setOpenLinks(False) self.cross_matrix_textBrowser.setObjectName("cross_matrix_textBrowser") self.gridLayout_253.addWidget(self.cross_matrix_textBrowser, 0, 0, 1, 1) self.gridLayout_252.addLayout(self.gridLayout_253, 0, 0, 1, 1) self.toolBox_cross_classification.addItem(self.page_22, "") self.gridLayout_254.addWidget(self.toolBox_cross_classification, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_cross_classification, "") self.tab_class_signature = QtWidgets.QWidget() self.tab_class_signature.setObjectName("tab_class_signature") self.gridLayout_123 = QtWidgets.QGridLayout(self.tab_class_signature) self.gridLayout_123.setObjectName("gridLayout_123") self.toolBox_class_signature = QtWidgets.QToolBox(self.tab_class_signature) self.toolBox_class_signature.setStyleSheet("") self.toolBox_class_signature.setObjectName("toolBox_class_signature") self.page_20 = QtWidgets.QWidget() self.page_20.setGeometry(QtCore.QRect(0, 0, 387, 196)) self.page_20.setObjectName("page_20") self.gridLayout_209 = QtWidgets.QGridLayout(self.page_20) self.gridLayout_209.setObjectName("gridLayout_209") self.horizontalLayout_39 = QtWidgets.QHBoxLayout() self.horizontalLayout_39.setObjectName("horizontalLayout_39") self.label_188 = QtWidgets.QLabel(self.page_20) self.label_188.setStyleSheet("background-color : #656565; color : white") self.label_188.setFrameShape(QtWidgets.QFrame.Panel) self.label_188.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_188.setObjectName("label_188") self.horizontalLayout_39.addWidget(self.label_188) self.gridLayout_209.addLayout(self.horizontalLayout_39, 0, 0, 1, 1) self.gridLayout_211 = QtWidgets.QGridLayout() self.gridLayout_211.setObjectName("gridLayout_211") self.gridLayout_112 = QtWidgets.QGridLayout() self.gridLayout_112.setObjectName("gridLayout_112") self.classification_name_combo_3 = QtWidgets.QComboBox(self.page_20) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_3.sizePolicy().hasHeightForWidth()) self.classification_name_combo_3.setSizePolicy(sizePolicy) self.classification_name_combo_3.setObjectName("classification_name_combo_3") self.gridLayout_112.addWidget(self.classification_name_combo_3, 0, 1, 1, 1) self.label_201 = QtWidgets.QLabel(self.page_20) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_201.sizePolicy().hasHeightForWidth()) self.label_201.setSizePolicy(sizePolicy) self.label_201.setMinimumSize(QtCore.QSize(229, 0)) self.label_201.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_201.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_201.setObjectName("label_201") self.gridLayout_112.addWidget(self.label_201, 0, 0, 1, 1) self.toolButton_reload_22 = QtWidgets.QToolButton(self.page_20) self.toolButton_reload_22.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_22.setIcon(icon55) self.toolButton_reload_22.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_22.setObjectName("toolButton_reload_22") self.gridLayout_112.addWidget(self.toolButton_reload_22, 0, 2, 1, 1) self.gridLayout_211.addLayout(self.gridLayout_112, 0, 0, 1, 3) self.label_259 = QtWidgets.QLabel(self.page_20) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_259.sizePolicy().hasHeightForWidth()) self.label_259.setSizePolicy(sizePolicy) self.label_259.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_259.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_259.setObjectName("label_259") self.gridLayout_211.addWidget(self.label_259, 1, 0, 1, 1) self.band_set_comb_spinBox_8 = QtWidgets.QSpinBox(self.page_20) self.band_set_comb_spinBox_8.setMinimum(1) self.band_set_comb_spinBox_8.setMaximum(100000) self.band_set_comb_spinBox_8.setObjectName("band_set_comb_spinBox_8") self.gridLayout_211.addWidget(self.band_set_comb_spinBox_8, 1, 1, 1, 1) spacerItem122 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_211.addItem(spacerItem122, 1, 2, 1, 1) self.gridLayout_209.addLayout(self.gridLayout_211, 1, 0, 1, 1) self.gridLayout_256 = QtWidgets.QGridLayout() self.gridLayout_256.setObjectName("gridLayout_256") self.label_184 = QtWidgets.QLabel(self.page_20) self.label_184.setStyleSheet("background-color : #656565; color : white") self.label_184.setFrameShape(QtWidgets.QFrame.Panel) self.label_184.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_184.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_184.setObjectName("label_184") self.gridLayout_256.addWidget(self.label_184, 2, 0, 1, 4) self.class_signature_Button = QtWidgets.QToolButton(self.page_20) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_signature_Button.setFont(font) self.class_signature_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_signature_Button.setStyleSheet("margin: 0px;padding: 0px;") self.class_signature_Button.setIcon(icon64) self.class_signature_Button.setIconSize(QtCore.QSize(34, 34)) self.class_signature_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_signature_Button.setObjectName("class_signature_Button") self.gridLayout_256.addWidget(self.class_signature_Button, 3, 3, 1, 1) spacerItem123 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_256.addItem(spacerItem123, 3, 0, 1, 2) spacerItem124 = QtWidgets.QSpacerItem(38, 37, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_256.addItem(spacerItem124, 1, 0, 1, 1) self.class_signature_save_siglist_checkBox = QtWidgets.QCheckBox(self.page_20) self.class_signature_save_siglist_checkBox.setChecked(True) self.class_signature_save_siglist_checkBox.setObjectName("class_signature_save_siglist_checkBox") self.gridLayout_256.addWidget(self.class_signature_save_siglist_checkBox, 0, 0, 1, 4) self.class_signature = QtWidgets.QToolButton(self.page_20) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_signature.setFont(font) self.class_signature.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_signature.setStyleSheet("margin: 0px;padding: 0px;") self.class_signature.setIcon(icon48) self.class_signature.setIconSize(QtCore.QSize(34, 34)) self.class_signature.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_signature.setObjectName("class_signature") self.gridLayout_256.addWidget(self.class_signature, 3, 2, 1, 1) self.gridLayout_209.addLayout(self.gridLayout_256, 2, 0, 1, 1) self.toolBox_class_signature.addItem(self.page_20, "") self.page_24 = QtWidgets.QWidget() self.page_24.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_24.setObjectName("page_24") self.gridLayout_258 = QtWidgets.QGridLayout(self.page_24) self.gridLayout_258.setObjectName("gridLayout_258") self.gridLayout_259 = QtWidgets.QGridLayout() self.gridLayout_259.setObjectName("gridLayout_259") self.report_textBrowser_4 = QtWidgets.QTextBrowser(self.page_24) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_4.setFont(font) self.report_textBrowser_4.setTabChangesFocus(True) self.report_textBrowser_4.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_4.setTabStopWidth(160) self.report_textBrowser_4.setOpenLinks(False) self.report_textBrowser_4.setObjectName("report_textBrowser_4") self.gridLayout_259.addWidget(self.report_textBrowser_4, 0, 0, 1, 1) self.gridLayout_258.addLayout(self.gridLayout_259, 0, 0, 1, 1) self.toolBox_class_signature.addItem(self.page_24, "") self.gridLayout_123.addWidget(self.toolBox_class_signature, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_class_signature, "") self.tab_class_to_vector = QtWidgets.QWidget() self.tab_class_to_vector.setObjectName("tab_class_to_vector") self.gridLayout_49 = QtWidgets.QGridLayout(self.tab_class_to_vector) self.gridLayout_49.setObjectName("gridLayout_49") self.horizontalLayout_40 = QtWidgets.QHBoxLayout() self.horizontalLayout_40.setObjectName("horizontalLayout_40") self.label_189 = QtWidgets.QLabel(self.tab_class_to_vector) self.label_189.setStyleSheet("background-color : #656565; color : white") self.label_189.setFrameShape(QtWidgets.QFrame.Panel) self.label_189.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_189.setObjectName("label_189") self.horizontalLayout_40.addWidget(self.label_189) self.gridLayout_49.addLayout(self.horizontalLayout_40, 0, 0, 1, 1) self.gridLayout_71 = QtWidgets.QGridLayout() self.gridLayout_71.setObjectName("gridLayout_71") self.label_63 = QtWidgets.QLabel(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_63.sizePolicy().hasHeightForWidth()) self.label_63.setSizePolicy(sizePolicy) self.label_63.setMinimumSize(QtCore.QSize(229, 0)) self.label_63.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_63.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_63.setObjectName("label_63") self.gridLayout_71.addWidget(self.label_63, 0, 0, 1, 1) self.classification_vector_name_combo = QtWidgets.QComboBox(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_vector_name_combo.sizePolicy().hasHeightForWidth()) self.classification_vector_name_combo.setSizePolicy(sizePolicy) self.classification_vector_name_combo.setObjectName("classification_vector_name_combo") self.gridLayout_71.addWidget(self.classification_vector_name_combo, 0, 1, 1, 1) self.toolButton_reload_11 = QtWidgets.QToolButton(self.tab_class_to_vector) self.toolButton_reload_11.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_11.setIcon(icon55) self.toolButton_reload_11.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_11.setObjectName("toolButton_reload_11") self.gridLayout_71.addWidget(self.toolButton_reload_11, 0, 2, 1, 1) self.gridLayout_49.addLayout(self.gridLayout_71, 1, 0, 1, 1) self.gridLayout_74 = QtWidgets.QGridLayout() self.gridLayout_74.setObjectName("gridLayout_74") self.class_macroclass_comboBox = QtWidgets.QComboBox(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_macroclass_comboBox.sizePolicy().hasHeightForWidth()) self.class_macroclass_comboBox.setSizePolicy(sizePolicy) self.class_macroclass_comboBox.setObjectName("class_macroclass_comboBox") self.class_macroclass_comboBox.addItem("") self.class_macroclass_comboBox.addItem("") self.gridLayout_74.addWidget(self.class_macroclass_comboBox, 1, 1, 1, 1) self.use_class_code_checkBox = QtWidgets.QCheckBox(self.tab_class_to_vector) self.use_class_code_checkBox.setObjectName("use_class_code_checkBox") self.gridLayout_74.addWidget(self.use_class_code_checkBox, 1, 0, 1, 1) self.label_49 = QtWidgets.QLabel(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_49.sizePolicy().hasHeightForWidth()) self.label_49.setSizePolicy(sizePolicy) self.label_49.setStyleSheet("background-color : #656565; color : white") self.label_49.setFrameShape(QtWidgets.QFrame.Panel) self.label_49.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_49.setObjectName("label_49") self.gridLayout_74.addWidget(self.label_49, 0, 0, 1, 2) self.dissolve_output_checkBox = QtWidgets.QCheckBox(self.tab_class_to_vector) self.dissolve_output_checkBox.setObjectName("dissolve_output_checkBox") self.gridLayout_74.addWidget(self.dissolve_output_checkBox, 2, 0, 1, 1) self.gridLayout_49.addLayout(self.gridLayout_74, 2, 0, 1, 1) self.gridLayout_75 = QtWidgets.QGridLayout() self.gridLayout_75.setObjectName("gridLayout_75") spacerItem125 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_75.addItem(spacerItem125, 0, 1, 1, 1) spacerItem126 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_75.addItem(spacerItem126, 0, 0, 1, 1) self.convert_toolButton = QtWidgets.QToolButton(self.tab_class_to_vector) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.convert_toolButton.setFont(font) self.convert_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.convert_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.convert_toolButton.setIcon(icon64) self.convert_toolButton.setIconSize(QtCore.QSize(34, 34)) self.convert_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.convert_toolButton.setObjectName("convert_toolButton") self.gridLayout_75.addWidget(self.convert_toolButton, 2, 2, 1, 1) self.label_171 = QtWidgets.QLabel(self.tab_class_to_vector) self.label_171.setStyleSheet("background-color : #656565; color : white") self.label_171.setFrameShape(QtWidgets.QFrame.Panel) self.label_171.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_171.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_171.setObjectName("label_171") self.gridLayout_75.addWidget(self.label_171, 1, 0, 1, 3) self.classification_to_vector = QtWidgets.QToolButton(self.tab_class_to_vector) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_to_vector.setFont(font) self.classification_to_vector.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_to_vector.setStyleSheet("margin: 0px;padding: 0px;") self.classification_to_vector.setIcon(icon48) self.classification_to_vector.setIconSize(QtCore.QSize(34, 34)) self.classification_to_vector.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_to_vector.setObjectName("classification_to_vector") self.gridLayout_75.addWidget(self.classification_to_vector, 2, 1, 1, 1) self.gridLayout_49.addLayout(self.gridLayout_75, 3, 0, 1, 1) self.tabWidget_2.addTab(self.tab_class_to_vector, "") self.tab_reclassification = QtWidgets.QWidget() self.tab_reclassification.setObjectName("tab_reclassification") self.gridLayout_191 = QtWidgets.QGridLayout(self.tab_reclassification) self.gridLayout_191.setObjectName("gridLayout_191") self.gridLayout_78 = QtWidgets.QGridLayout() self.gridLayout_78.setObjectName("gridLayout_78") self.label_65 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_65.sizePolicy().hasHeightForWidth()) self.label_65.setSizePolicy(sizePolicy) self.label_65.setMinimumSize(QtCore.QSize(229, 0)) self.label_65.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_65.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_65.setObjectName("label_65") self.gridLayout_78.addWidget(self.label_65, 1, 0, 1, 1) self.reclassification_name_combo = QtWidgets.QComboBox(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reclassification_name_combo.sizePolicy().hasHeightForWidth()) self.reclassification_name_combo.setSizePolicy(sizePolicy) self.reclassification_name_combo.setObjectName("reclassification_name_combo") self.gridLayout_78.addWidget(self.reclassification_name_combo, 1, 1, 1, 1) self.toolButton_reload_12 = QtWidgets.QToolButton(self.tab_reclassification) self.toolButton_reload_12.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_12.setIcon(icon55) self.toolButton_reload_12.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_12.setObjectName("toolButton_reload_12") self.gridLayout_78.addWidget(self.toolButton_reload_12, 1, 2, 1, 1) self.horizontalLayout_41 = QtWidgets.QHBoxLayout() self.horizontalLayout_41.setObjectName("horizontalLayout_41") self.label_190 = QtWidgets.QLabel(self.tab_reclassification) self.label_190.setStyleSheet("background-color : #656565; color : white") self.label_190.setFrameShape(QtWidgets.QFrame.Panel) self.label_190.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_190.setObjectName("label_190") self.horizontalLayout_41.addWidget(self.label_190) self.gridLayout_78.addLayout(self.horizontalLayout_41, 0, 0, 1, 3) self.gridLayout_191.addLayout(self.gridLayout_78, 0, 0, 1, 1) self.gridLayout_79 = QtWidgets.QGridLayout() self.gridLayout_79.setObjectName("gridLayout_79") self.calculate_unique_values_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.calculate_unique_values_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculate_unique_values_toolButton.setIcon(icon67) self.calculate_unique_values_toolButton.setIconSize(QtCore.QSize(22, 22)) self.calculate_unique_values_toolButton.setObjectName("calculate_unique_values_toolButton") self.gridLayout_79.addWidget(self.calculate_unique_values_toolButton, 1, 4, 1, 1) self.CID_MCID_code_checkBox = QtWidgets.QCheckBox(self.tab_reclassification) self.CID_MCID_code_checkBox.setObjectName("CID_MCID_code_checkBox") self.gridLayout_79.addWidget(self.CID_MCID_code_checkBox, 1, 2, 1, 1) self.label_98 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_98.sizePolicy().hasHeightForWidth()) self.label_98.setSizePolicy(sizePolicy) self.label_98.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_98.setObjectName("label_98") self.gridLayout_79.addWidget(self.label_98, 1, 3, 1, 1) self.label_54 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_54.sizePolicy().hasHeightForWidth()) self.label_54.setSizePolicy(sizePolicy) self.label_54.setStyleSheet("background-color : #656565; color : white") self.label_54.setFrameShape(QtWidgets.QFrame.Panel) self.label_54.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_54.setObjectName("label_54") self.gridLayout_79.addWidget(self.label_54, 0, 2, 1, 3) self.incremental_new_values_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.incremental_new_values_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.incremental_new_values_toolButton.setIcon(icon67) self.incremental_new_values_toolButton.setIconSize(QtCore.QSize(22, 22)) self.incremental_new_values_toolButton.setObjectName("incremental_new_values_toolButton") self.gridLayout_79.addWidget(self.incremental_new_values_toolButton, 2, 4, 1, 1) self.label_271 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_271.sizePolicy().hasHeightForWidth()) self.label_271.setSizePolicy(sizePolicy) self.label_271.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_271.setObjectName("label_271") self.gridLayout_79.addWidget(self.label_271, 2, 3, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_79, 1, 0, 1, 1) self.gridLayout_77 = QtWidgets.QGridLayout() self.gridLayout_77.setObjectName("gridLayout_77") self.reclass_values_tableWidget = QtWidgets.QTableWidget(self.tab_reclassification) self.reclass_values_tableWidget.setAlternatingRowColors(True) self.reclass_values_tableWidget.setObjectName("reclass_values_tableWidget") self.reclass_values_tableWidget.setColumnCount(2) self.reclass_values_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.reclass_values_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.reclass_values_tableWidget.setHorizontalHeaderItem(1, item) self.reclass_values_tableWidget.horizontalHeader().setStretchLastSection(True) self.reclass_values_tableWidget.verticalHeader().setDefaultSectionSize(24) self.gridLayout_77.addWidget(self.reclass_values_tableWidget, 0, 0, 1, 1) self.gridLayout_81 = QtWidgets.QGridLayout() self.gridLayout_81.setObjectName("gridLayout_81") self.add_value_pushButton = QtWidgets.QToolButton(self.tab_reclassification) self.add_value_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.add_value_pushButton.setIcon(icon66) self.add_value_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_value_pushButton.setObjectName("add_value_pushButton") self.gridLayout_81.addWidget(self.add_value_pushButton, 1, 0, 1, 1) self.remove_row_pushButton = QtWidgets.QToolButton(self.tab_reclassification) self.remove_row_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.remove_row_pushButton.setIcon(icon58) self.remove_row_pushButton.setIconSize(QtCore.QSize(22, 22)) self.remove_row_pushButton.setObjectName("remove_row_pushButton") self.gridLayout_81.addWidget(self.remove_row_pushButton, 2, 0, 1, 1) spacerItem127 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_81.addItem(spacerItem127, 0, 0, 1, 1) spacerItem128 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_81.addItem(spacerItem128, 6, 0, 1, 1) self.import_reclass_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.import_reclass_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_reclass_toolButton.setIcon(icon54) self.import_reclass_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_reclass_toolButton.setObjectName("import_reclass_toolButton") self.gridLayout_81.addWidget(self.import_reclass_toolButton, 4, 0, 1, 1) self.export_reclass_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.export_reclass_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_reclass_toolButton.setIcon(icon53) self.export_reclass_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_reclass_toolButton.setObjectName("export_reclass_toolButton") self.gridLayout_81.addWidget(self.export_reclass_toolButton, 5, 0, 1, 1) spacerItem129 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_81.addItem(spacerItem129, 3, 0, 1, 1) self.gridLayout_77.addLayout(self.gridLayout_81, 0, 1, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_77, 2, 0, 1, 1) self.gridLayout_80 = QtWidgets.QGridLayout() self.gridLayout_80.setObjectName("gridLayout_80") self.gridLayout_82 = QtWidgets.QGridLayout() self.gridLayout_82.setObjectName("gridLayout_82") self.apply_symbology_checkBox = QtWidgets.QCheckBox(self.tab_reclassification) self.apply_symbology_checkBox.setChecked(False) self.apply_symbology_checkBox.setObjectName("apply_symbology_checkBox") self.gridLayout_82.addWidget(self.apply_symbology_checkBox, 1, 0, 1, 1) self.class_macroclass_comboBox_2 = QtWidgets.QComboBox(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_macroclass_comboBox_2.sizePolicy().hasHeightForWidth()) self.class_macroclass_comboBox_2.setSizePolicy(sizePolicy) self.class_macroclass_comboBox_2.setObjectName("class_macroclass_comboBox_2") self.class_macroclass_comboBox_2.addItem("") self.class_macroclass_comboBox_2.addItem("") self.gridLayout_82.addWidget(self.class_macroclass_comboBox_2, 1, 1, 1, 1) self.label_51 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_51.sizePolicy().hasHeightForWidth()) self.label_51.setSizePolicy(sizePolicy) self.label_51.setStyleSheet("background-color : #656565; color : white") self.label_51.setFrameShape(QtWidgets.QFrame.Panel) self.label_51.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_51.setObjectName("label_51") self.gridLayout_82.addWidget(self.label_51, 0, 0, 1, 2) self.gridLayout_80.addLayout(self.gridLayout_82, 0, 0, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_80, 3, 0, 1, 1) self.gridLayout_83 = QtWidgets.QGridLayout() self.gridLayout_83.setObjectName("gridLayout_83") spacerItem130 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_83.addItem(spacerItem130, 1, 0, 1, 1) self.label_172 = QtWidgets.QLabel(self.tab_reclassification) self.label_172.setStyleSheet("background-color : #656565; color : white") self.label_172.setFrameShape(QtWidgets.QFrame.Panel) self.label_172.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_172.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_172.setObjectName("label_172") self.gridLayout_83.addWidget(self.label_172, 0, 0, 1, 3) self.reclassify_toolButton = QtWidgets.QToolButton(self.tab_reclassification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reclassify_toolButton.setFont(font) self.reclassify_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.reclassify_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.reclassify_toolButton.setIcon(icon64) self.reclassify_toolButton.setIconSize(QtCore.QSize(34, 34)) self.reclassify_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reclassify_toolButton.setObjectName("reclassify_toolButton") self.gridLayout_83.addWidget(self.reclassify_toolButton, 1, 2, 1, 1) self.reclassification = QtWidgets.QToolButton(self.tab_reclassification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reclassification.setFont(font) self.reclassification.setLayoutDirection(QtCore.Qt.RightToLeft) self.reclassification.setStyleSheet("margin: 0px;padding: 0px;") self.reclassification.setIcon(icon48) self.reclassification.setIconSize(QtCore.QSize(34, 34)) self.reclassification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reclassification.setObjectName("reclassification") self.gridLayout_83.addWidget(self.reclassification, 1, 1, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_83, 4, 0, 1, 1) self.tabWidget_2.addTab(self.tab_reclassification, "") self.tab = QtWidgets.QWidget() self.tab.setObjectName("tab") self.gridLayout_359 = QtWidgets.QGridLayout(self.tab) self.gridLayout_359.setObjectName("gridLayout_359") self.horizontalLayout_42 = QtWidgets.QHBoxLayout() self.horizontalLayout_42.setObjectName("horizontalLayout_42") self.label_193 = QtWidgets.QLabel(self.tab) self.label_193.setStyleSheet("background-color : #656565; color : white") self.label_193.setFrameShape(QtWidgets.QFrame.Panel) self.label_193.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_193.setObjectName("label_193") self.horizontalLayout_42.addWidget(self.label_193) self.gridLayout_359.addLayout(self.horizontalLayout_42, 0, 0, 1, 1) self.gridLayout_196 = QtWidgets.QGridLayout() self.gridLayout_196.setObjectName("gridLayout_196") self.undo_edit_Button = QtWidgets.QToolButton(self.tab) self.undo_edit_Button.setEnabled(False) self.undo_edit_Button.setStyleSheet("margin: 0px;padding: 0px;") icon81 = QtGui.QIcon() icon81.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_undo_edit_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.undo_edit_Button.setIcon(icon81) self.undo_edit_Button.setIconSize(QtCore.QSize(22, 22)) self.undo_edit_Button.setObjectName("undo_edit_Button") self.gridLayout_196.addWidget(self.undo_edit_Button, 10, 0, 1, 1) self.label_173 = QtWidgets.QLabel(self.tab) self.label_173.setStyleSheet("background-color : #656565; color : white") self.label_173.setFrameShape(QtWidgets.QFrame.Panel) self.label_173.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_173.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_173.setObjectName("label_173") self.gridLayout_196.addWidget(self.label_173, 9, 0, 1, 4) self.horizontalLayout_8 = QtWidgets.QHBoxLayout() self.horizontalLayout_8.setObjectName("horizontalLayout_8") self.label_66 = QtWidgets.QLabel(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_66.sizePolicy().hasHeightForWidth()) self.label_66.setSizePolicy(sizePolicy) self.label_66.setMinimumSize(QtCore.QSize(229, 0)) self.label_66.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_66.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_66.setObjectName("label_66") self.horizontalLayout_8.addWidget(self.label_66) self.edit_raster_name_combo = QtWidgets.QComboBox(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.edit_raster_name_combo.sizePolicy().hasHeightForWidth()) self.edit_raster_name_combo.setSizePolicy(sizePolicy) self.edit_raster_name_combo.setObjectName("edit_raster_name_combo") self.horizontalLayout_8.addWidget(self.edit_raster_name_combo) self.toolButton_reload_14 = QtWidgets.QToolButton(self.tab) self.toolButton_reload_14.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_14.setIcon(icon55) self.toolButton_reload_14.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_14.setObjectName("toolButton_reload_14") self.horizontalLayout_8.addWidget(self.toolButton_reload_14) self.gridLayout_196.addLayout(self.horizontalLayout_8, 0, 0, 1, 4) self.horizontalLayout_6 = QtWidgets.QHBoxLayout() self.horizontalLayout_6.setObjectName("horizontalLayout_6") self.use_constant_val_checkBox = QtWidgets.QCheckBox(self.tab) self.use_constant_val_checkBox.setChecked(True) self.use_constant_val_checkBox.setObjectName("use_constant_val_checkBox") self.horizontalLayout_6.addWidget(self.use_constant_val_checkBox) self.value_spinBox = QtWidgets.QSpinBox(self.tab) self.value_spinBox.setMinimum(-2147483647) self.value_spinBox.setMaximum(2147483647) self.value_spinBox.setObjectName("value_spinBox") self.horizontalLayout_6.addWidget(self.value_spinBox) spacerItem131 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_6.addItem(spacerItem131) self.gridLayout_196.addLayout(self.horizontalLayout_6, 6, 0, 1, 4) self.horizontalLayout_7 = QtWidgets.QHBoxLayout() self.horizontalLayout_7.setObjectName("horizontalLayout_7") self.use_expression_checkBox = QtWidgets.QCheckBox(self.tab) self.use_expression_checkBox.setObjectName("use_expression_checkBox") self.horizontalLayout_7.addWidget(self.use_expression_checkBox) self.expression_lineEdit = QtWidgets.QLineEdit(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.expression_lineEdit.sizePolicy().hasHeightForWidth()) self.expression_lineEdit.setSizePolicy(sizePolicy) self.expression_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.expression_lineEdit.setMaxLength(10000) self.expression_lineEdit.setObjectName("expression_lineEdit") self.horizontalLayout_7.addWidget(self.expression_lineEdit) self.gridLayout_196.addLayout(self.horizontalLayout_7, 7, 0, 1, 4) spacerItem132 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_196.addItem(spacerItem132, 10, 1, 1, 1) spacerItem133 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_196.addItem(spacerItem133, 8, 3, 1, 1) self.horizontalLayout_9 = QtWidgets.QHBoxLayout() self.horizontalLayout_9.setObjectName("horizontalLayout_9") self.label_81 = QtWidgets.QLabel(self.tab) self.label_81.setStyleSheet("background-color : #656565; color : white") self.label_81.setFrameShape(QtWidgets.QFrame.Panel) self.label_81.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_81.setObjectName("label_81") self.horizontalLayout_9.addWidget(self.label_81) self.gridLayout_196.addLayout(self.horizontalLayout_9, 1, 0, 1, 4) self.horizontalLayout_24 = QtWidgets.QHBoxLayout() self.horizontalLayout_24.setObjectName("horizontalLayout_24") self.use_field_vector_checkBox = QtWidgets.QCheckBox(self.tab) self.use_field_vector_checkBox.setObjectName("use_field_vector_checkBox") self.horizontalLayout_24.addWidget(self.use_field_vector_checkBox) self.field_comboBox_2 = QtWidgets.QComboBox(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.field_comboBox_2.sizePolicy().hasHeightForWidth()) self.field_comboBox_2.setSizePolicy(sizePolicy) self.field_comboBox_2.setObjectName("field_comboBox_2") self.horizontalLayout_24.addWidget(self.field_comboBox_2) self.gridLayout_196.addLayout(self.horizontalLayout_24, 5, 0, 1, 4) self.horizontalLayout_21 = QtWidgets.QHBoxLayout() self.horizontalLayout_21.setObjectName("horizontalLayout_21") self.edit_val_use_vector_radioButton = QtWidgets.QRadioButton(self.tab) self.edit_val_use_vector_radioButton.setObjectName("edit_val_use_vector_radioButton") self.horizontalLayout_21.addWidget(self.edit_val_use_vector_radioButton) self.vector_name_combo_2 = QtWidgets.QComboBox(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.vector_name_combo_2.sizePolicy().hasHeightForWidth()) self.vector_name_combo_2.setSizePolicy(sizePolicy) self.vector_name_combo_2.setObjectName("vector_name_combo_2") self.horizontalLayout_21.addWidget(self.vector_name_combo_2) self.toolButton_reload_20 = QtWidgets.QToolButton(self.tab) self.toolButton_reload_20.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_20.setIcon(icon55) self.toolButton_reload_20.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_20.setObjectName("toolButton_reload_20") self.horizontalLayout_21.addWidget(self.toolButton_reload_20) self.gridLayout_196.addLayout(self.horizontalLayout_21, 3, 0, 1, 4) self.horizontalLayout_23 = QtWidgets.QHBoxLayout() self.horizontalLayout_23.setObjectName("horizontalLayout_23") self.edit_val_use_ROI_radioButton = QtWidgets.QRadioButton(self.tab) self.edit_val_use_ROI_radioButton.setChecked(True) self.edit_val_use_ROI_radioButton.setObjectName("edit_val_use_ROI_radioButton") self.horizontalLayout_23.addWidget(self.edit_val_use_ROI_radioButton) self.gridLayout_196.addLayout(self.horizontalLayout_23, 2, 0, 1, 4) self.horizontalLayout_26 = QtWidgets.QHBoxLayout() self.horizontalLayout_26.setObjectName("horizontalLayout_26") self.label_158 = QtWidgets.QLabel(self.tab) self.label_158.setStyleSheet("background-color : #656565; color : white") self.label_158.setFrameShape(QtWidgets.QFrame.Panel) self.label_158.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_158.setObjectName("label_158") self.horizontalLayout_26.addWidget(self.label_158) self.gridLayout_196.addLayout(self.horizontalLayout_26, 4, 0, 1, 4) self.raster_set_value_toolButton = QtWidgets.QToolButton(self.tab) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.raster_set_value_toolButton.setFont(font) self.raster_set_value_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.raster_set_value_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.raster_set_value_toolButton.setIcon(icon64) self.raster_set_value_toolButton.setIconSize(QtCore.QSize(34, 34)) self.raster_set_value_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.raster_set_value_toolButton.setObjectName("raster_set_value_toolButton") self.gridLayout_196.addWidget(self.raster_set_value_toolButton, 10, 3, 1, 1) self.edit_raster_using_vector = QtWidgets.QToolButton(self.tab) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.edit_raster_using_vector.setFont(font) self.edit_raster_using_vector.setLayoutDirection(QtCore.Qt.RightToLeft) self.edit_raster_using_vector.setStyleSheet("margin: 0px;padding: 0px;") self.edit_raster_using_vector.setIcon(icon48) self.edit_raster_using_vector.setIconSize(QtCore.QSize(34, 34)) self.edit_raster_using_vector.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.edit_raster_using_vector.setObjectName("edit_raster_using_vector") self.gridLayout_196.addWidget(self.edit_raster_using_vector, 10, 2, 1, 1) self.gridLayout_359.addLayout(self.gridLayout_196, 1, 0, 1, 1) self.tabWidget_2.addTab(self.tab, "") self.tab_sieve = QtWidgets.QWidget() self.tab_sieve.setObjectName("tab_sieve") self.gridLayout_202 = QtWidgets.QGridLayout(self.tab_sieve) self.gridLayout_202.setObjectName("gridLayout_202") self.gridLayout_64 = QtWidgets.QGridLayout() self.gridLayout_64.setObjectName("gridLayout_64") spacerItem134 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_64.addItem(spacerItem134, 2, 2, 1, 1) spacerItem135 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_64.addItem(spacerItem135, 4, 0, 1, 1) self.horizontalLayout_11 = QtWidgets.QHBoxLayout() self.horizontalLayout_11.setObjectName("horizontalLayout_11") self.label_70 = QtWidgets.QLabel(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_70.sizePolicy().hasHeightForWidth()) self.label_70.setSizePolicy(sizePolicy) self.label_70.setMinimumSize(QtCore.QSize(229, 0)) self.label_70.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_70.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_70.setObjectName("label_70") self.horizontalLayout_11.addWidget(self.label_70) self.sieve_raster_name_combo = QtWidgets.QComboBox(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.sieve_raster_name_combo.sizePolicy().hasHeightForWidth()) self.sieve_raster_name_combo.setSizePolicy(sizePolicy) self.sieve_raster_name_combo.setObjectName("sieve_raster_name_combo") self.horizontalLayout_11.addWidget(self.sieve_raster_name_combo) self.toolButton_reload_15 = QtWidgets.QToolButton(self.tab_sieve) self.toolButton_reload_15.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_15.setIcon(icon55) self.toolButton_reload_15.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_15.setObjectName("toolButton_reload_15") self.horizontalLayout_11.addWidget(self.toolButton_reload_15) self.gridLayout_64.addLayout(self.horizontalLayout_11, 0, 0, 1, 3) self.horizontalLayout_12 = QtWidgets.QHBoxLayout() self.horizontalLayout_12.setObjectName("horizontalLayout_12") self.label_133 = QtWidgets.QLabel(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_133.sizePolicy().hasHeightForWidth()) self.label_133.setSizePolicy(sizePolicy) self.label_133.setMinimumSize(QtCore.QSize(229, 0)) self.label_133.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_133.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_133.setObjectName("label_133") self.horizontalLayout_12.addWidget(self.label_133) self.sieve_threshold_spinBox = QtWidgets.QSpinBox(self.tab_sieve) self.sieve_threshold_spinBox.setMinimum(2) self.sieve_threshold_spinBox.setMaximum(10000) self.sieve_threshold_spinBox.setObjectName("sieve_threshold_spinBox") self.horizontalLayout_12.addWidget(self.sieve_threshold_spinBox) spacerItem136 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_12.addItem(spacerItem136) self.label_136 = QtWidgets.QLabel(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_136.sizePolicy().hasHeightForWidth()) self.label_136.setSizePolicy(sizePolicy) self.label_136.setMinimumSize(QtCore.QSize(229, 0)) self.label_136.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_136.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_136.setObjectName("label_136") self.horizontalLayout_12.addWidget(self.label_136) self.sieve_connection_combo = QtWidgets.QComboBox(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.sieve_connection_combo.sizePolicy().hasHeightForWidth()) self.sieve_connection_combo.setSizePolicy(sizePolicy) self.sieve_connection_combo.setMaximumSize(QtCore.QSize(80, 16777215)) self.sieve_connection_combo.setObjectName("sieve_connection_combo") self.sieve_connection_combo.addItem("") self.sieve_connection_combo.addItem("") self.horizontalLayout_12.addWidget(self.sieve_connection_combo) self.gridLayout_64.addLayout(self.horizontalLayout_12, 1, 0, 1, 3) self.label_174 = QtWidgets.QLabel(self.tab_sieve) self.label_174.setStyleSheet("background-color : #656565; color : white") self.label_174.setFrameShape(QtWidgets.QFrame.Panel) self.label_174.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_174.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_174.setObjectName("label_174") self.gridLayout_64.addWidget(self.label_174, 3, 0, 1, 3) self.sieve_toolButton = QtWidgets.QToolButton(self.tab_sieve) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sieve_toolButton.setFont(font) self.sieve_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.sieve_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.sieve_toolButton.setIcon(icon64) self.sieve_toolButton.setIconSize(QtCore.QSize(34, 34)) self.sieve_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sieve_toolButton.setObjectName("sieve_toolButton") self.gridLayout_64.addWidget(self.sieve_toolButton, 4, 2, 1, 1) self.classification_sieve = QtWidgets.QToolButton(self.tab_sieve) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_sieve.setFont(font) self.classification_sieve.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_sieve.setStyleSheet("margin: 0px;padding: 0px;") self.classification_sieve.setIcon(icon48) self.classification_sieve.setIconSize(QtCore.QSize(34, 34)) self.classification_sieve.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_sieve.setObjectName("classification_sieve") self.gridLayout_64.addWidget(self.classification_sieve, 4, 1, 1, 1) self.gridLayout_202.addLayout(self.gridLayout_64, 1, 0, 1, 1) self.horizontalLayout_43 = QtWidgets.QHBoxLayout() self.horizontalLayout_43.setObjectName("horizontalLayout_43") self.label_195 = QtWidgets.QLabel(self.tab_sieve) self.label_195.setStyleSheet("background-color : #656565; color : white") self.label_195.setFrameShape(QtWidgets.QFrame.Panel) self.label_195.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_195.setObjectName("label_195") self.horizontalLayout_43.addWidget(self.label_195) self.gridLayout_202.addLayout(self.horizontalLayout_43, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_sieve, "") self.tab_erosion = QtWidgets.QWidget() self.tab_erosion.setObjectName("tab_erosion") self.gridLayout_205 = QtWidgets.QGridLayout(self.tab_erosion) self.gridLayout_205.setObjectName("gridLayout_205") self.horizontalLayout_44 = QtWidgets.QHBoxLayout() self.horizontalLayout_44.setObjectName("horizontalLayout_44") self.label_202 = QtWidgets.QLabel(self.tab_erosion) self.label_202.setStyleSheet("background-color : #656565; color : white") self.label_202.setFrameShape(QtWidgets.QFrame.Panel) self.label_202.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_202.setObjectName("label_202") self.horizontalLayout_44.addWidget(self.label_202) self.gridLayout_205.addLayout(self.horizontalLayout_44, 0, 0, 1, 1) self.gridLayout_204 = QtWidgets.QGridLayout() self.gridLayout_204.setObjectName("gridLayout_204") spacerItem137 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_204.addItem(spacerItem137, 3, 2, 1, 1) spacerItem138 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_204.addItem(spacerItem138, 5, 0, 1, 1) self.horizontalLayout_13 = QtWidgets.QHBoxLayout() self.horizontalLayout_13.setObjectName("horizontalLayout_13") self.label_146 = QtWidgets.QLabel(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_146.sizePolicy().hasHeightForWidth()) self.label_146.setSizePolicy(sizePolicy) self.label_146.setMinimumSize(QtCore.QSize(229, 0)) self.label_146.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_146.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_146.setObjectName("label_146") self.horizontalLayout_13.addWidget(self.label_146) self.erosion_raster_name_combo = QtWidgets.QComboBox(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.erosion_raster_name_combo.sizePolicy().hasHeightForWidth()) self.erosion_raster_name_combo.setSizePolicy(sizePolicy) self.erosion_raster_name_combo.setObjectName("erosion_raster_name_combo") self.horizontalLayout_13.addWidget(self.erosion_raster_name_combo) self.toolButton_reload_18 = QtWidgets.QToolButton(self.tab_erosion) self.toolButton_reload_18.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_18.setIcon(icon55) self.toolButton_reload_18.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_18.setObjectName("toolButton_reload_18") self.horizontalLayout_13.addWidget(self.toolButton_reload_18) self.gridLayout_204.addLayout(self.horizontalLayout_13, 0, 0, 1, 3) self.horizontalLayout_14 = QtWidgets.QHBoxLayout() self.horizontalLayout_14.setObjectName("horizontalLayout_14") self.label_149 = QtWidgets.QLabel(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_149.sizePolicy().hasHeightForWidth()) self.label_149.setSizePolicy(sizePolicy) self.label_149.setMinimumSize(QtCore.QSize(229, 0)) self.label_149.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_149.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_149.setObjectName("label_149") self.horizontalLayout_14.addWidget(self.label_149) self.erosion_threshold_spinBox = QtWidgets.QSpinBox(self.tab_erosion) self.erosion_threshold_spinBox.setMinimum(1) self.erosion_threshold_spinBox.setMaximum(1000) self.erosion_threshold_spinBox.setProperty("value", 1) self.erosion_threshold_spinBox.setObjectName("erosion_threshold_spinBox") self.horizontalLayout_14.addWidget(self.erosion_threshold_spinBox) self.circular_structure_checkBox_3 = QtWidgets.QCheckBox(self.tab_erosion) self.circular_structure_checkBox_3.setObjectName("circular_structure_checkBox_3") self.horizontalLayout_14.addWidget(self.circular_structure_checkBox_3) spacerItem139 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_14.addItem(spacerItem139) self.gridLayout_204.addLayout(self.horizontalLayout_14, 2, 0, 1, 3) self.horizontalLayout_15 = QtWidgets.QHBoxLayout() self.horizontalLayout_15.setObjectName("horizontalLayout_15") self.label_151 = QtWidgets.QLabel(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_151.sizePolicy().hasHeightForWidth()) self.label_151.setSizePolicy(sizePolicy) self.label_151.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_151.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_151.setObjectName("label_151") self.horizontalLayout_15.addWidget(self.label_151) self.erosion_classes_lineEdit = QtWidgets.QLineEdit(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.erosion_classes_lineEdit.sizePolicy().hasHeightForWidth()) self.erosion_classes_lineEdit.setSizePolicy(sizePolicy) self.erosion_classes_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.erosion_classes_lineEdit.setText("") self.erosion_classes_lineEdit.setMaxLength(10000) self.erosion_classes_lineEdit.setObjectName("erosion_classes_lineEdit") self.horizontalLayout_15.addWidget(self.erosion_classes_lineEdit) self.gridLayout_204.addLayout(self.horizontalLayout_15, 1, 0, 1, 3) self.label_175 = QtWidgets.QLabel(self.tab_erosion) self.label_175.setStyleSheet("background-color : #656565; color : white") self.label_175.setFrameShape(QtWidgets.QFrame.Panel) self.label_175.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_175.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_175.setObjectName("label_175") self.gridLayout_204.addWidget(self.label_175, 4, 0, 1, 3) self.class_erosion_toolButton = QtWidgets.QToolButton(self.tab_erosion) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_erosion_toolButton.setFont(font) self.class_erosion_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_erosion_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.class_erosion_toolButton.setIcon(icon64) self.class_erosion_toolButton.setIconSize(QtCore.QSize(34, 34)) self.class_erosion_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_erosion_toolButton.setObjectName("class_erosion_toolButton") self.gridLayout_204.addWidget(self.class_erosion_toolButton, 5, 2, 1, 1) self.classification_erosion = QtWidgets.QToolButton(self.tab_erosion) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_erosion.setFont(font) self.classification_erosion.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_erosion.setStyleSheet("margin: 0px;padding: 0px;") self.classification_erosion.setIcon(icon48) self.classification_erosion.setIconSize(QtCore.QSize(34, 34)) self.classification_erosion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_erosion.setObjectName("classification_erosion") self.gridLayout_204.addWidget(self.classification_erosion, 5, 1, 1, 1) self.gridLayout_205.addLayout(self.gridLayout_204, 1, 0, 1, 1) self.tabWidget_2.addTab(self.tab_erosion, "") self.tab_dilation = QtWidgets.QWidget() self.tab_dilation.setObjectName("tab_dilation") self.gridLayout_207 = QtWidgets.QGridLayout(self.tab_dilation) self.gridLayout_207.setObjectName("gridLayout_207") self.horizontalLayout_45 = QtWidgets.QHBoxLayout() self.horizontalLayout_45.setObjectName("horizontalLayout_45") self.label_204 = QtWidgets.QLabel(self.tab_dilation) self.label_204.setStyleSheet("background-color : #656565; color : white") self.label_204.setFrameShape(QtWidgets.QFrame.Panel) self.label_204.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_204.setObjectName("label_204") self.horizontalLayout_45.addWidget(self.label_204) self.gridLayout_207.addLayout(self.horizontalLayout_45, 0, 0, 1, 1) self.gridLayout_206 = QtWidgets.QGridLayout() self.gridLayout_206.setObjectName("gridLayout_206") spacerItem140 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_206.addItem(spacerItem140, 3, 2, 1, 1) spacerItem141 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_206.addItem(spacerItem141, 5, 0, 1, 1) self.horizontalLayout_16 = QtWidgets.QHBoxLayout() self.horizontalLayout_16.setObjectName("horizontalLayout_16") self.label_152 = QtWidgets.QLabel(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_152.sizePolicy().hasHeightForWidth()) self.label_152.setSizePolicy(sizePolicy) self.label_152.setMinimumSize(QtCore.QSize(229, 0)) self.label_152.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_152.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_152.setObjectName("label_152") self.horizontalLayout_16.addWidget(self.label_152) self.dilation_raster_name_combo = QtWidgets.QComboBox(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.dilation_raster_name_combo.sizePolicy().hasHeightForWidth()) self.dilation_raster_name_combo.setSizePolicy(sizePolicy) self.dilation_raster_name_combo.setObjectName("dilation_raster_name_combo") self.horizontalLayout_16.addWidget(self.dilation_raster_name_combo) self.toolButton_reload_19 = QtWidgets.QToolButton(self.tab_dilation) self.toolButton_reload_19.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_19.setIcon(icon55) self.toolButton_reload_19.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_19.setObjectName("toolButton_reload_19") self.horizontalLayout_16.addWidget(self.toolButton_reload_19) self.gridLayout_206.addLayout(self.horizontalLayout_16, 0, 0, 1, 3) self.horizontalLayout_17 = QtWidgets.QHBoxLayout() self.horizontalLayout_17.setObjectName("horizontalLayout_17") self.label_153 = QtWidgets.QLabel(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_153.sizePolicy().hasHeightForWidth()) self.label_153.setSizePolicy(sizePolicy) self.label_153.setMinimumSize(QtCore.QSize(229, 0)) self.label_153.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_153.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_153.setObjectName("label_153") self.horizontalLayout_17.addWidget(self.label_153) self.dilation_threshold_spinBox = QtWidgets.QSpinBox(self.tab_dilation) self.dilation_threshold_spinBox.setMinimum(1) self.dilation_threshold_spinBox.setMaximum(1000) self.dilation_threshold_spinBox.setProperty("value", 1) self.dilation_threshold_spinBox.setObjectName("dilation_threshold_spinBox") self.horizontalLayout_17.addWidget(self.dilation_threshold_spinBox) self.circular_structure_checkBox_2 = QtWidgets.QCheckBox(self.tab_dilation) self.circular_structure_checkBox_2.setObjectName("circular_structure_checkBox_2") self.horizontalLayout_17.addWidget(self.circular_structure_checkBox_2) spacerItem142 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_17.addItem(spacerItem142) self.gridLayout_206.addLayout(self.horizontalLayout_17, 2, 0, 1, 3) self.horizontalLayout_18 = QtWidgets.QHBoxLayout() self.horizontalLayout_18.setObjectName("horizontalLayout_18") self.label_155 = QtWidgets.QLabel(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_155.sizePolicy().hasHeightForWidth()) self.label_155.setSizePolicy(sizePolicy) self.label_155.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_155.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_155.setObjectName("label_155") self.horizontalLayout_18.addWidget(self.label_155) self.dilation_classes_lineEdit = QtWidgets.QLineEdit(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.dilation_classes_lineEdit.sizePolicy().hasHeightForWidth()) self.dilation_classes_lineEdit.setSizePolicy(sizePolicy) self.dilation_classes_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.dilation_classes_lineEdit.setText("") self.dilation_classes_lineEdit.setMaxLength(10000) self.dilation_classes_lineEdit.setObjectName("dilation_classes_lineEdit") self.horizontalLayout_18.addWidget(self.dilation_classes_lineEdit) self.gridLayout_206.addLayout(self.horizontalLayout_18, 1, 0, 1, 3) self.label_176 = QtWidgets.QLabel(self.tab_dilation) self.label_176.setStyleSheet("background-color : #656565; color : white") self.label_176.setFrameShape(QtWidgets.QFrame.Panel) self.label_176.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_176.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_176.setObjectName("label_176") self.gridLayout_206.addWidget(self.label_176, 4, 0, 1, 3) self.class_dilation_toolButton = QtWidgets.QToolButton(self.tab_dilation) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_dilation_toolButton.setFont(font) self.class_dilation_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_dilation_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.class_dilation_toolButton.setIcon(icon64) self.class_dilation_toolButton.setIconSize(QtCore.QSize(34, 34)) self.class_dilation_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_dilation_toolButton.setObjectName("class_dilation_toolButton") self.gridLayout_206.addWidget(self.class_dilation_toolButton, 5, 2, 1, 1) self.classification_dilation = QtWidgets.QToolButton(self.tab_dilation) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_dilation.setFont(font) self.classification_dilation.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_dilation.setStyleSheet("margin: 0px;padding: 0px;") self.classification_dilation.setIcon(icon48) self.classification_dilation.setIconSize(QtCore.QSize(34, 34)) self.classification_dilation.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_dilation.setObjectName("classification_dilation") self.gridLayout_206.addWidget(self.classification_dilation, 5, 1, 1, 1) self.gridLayout_207.addLayout(self.gridLayout_206, 1, 0, 1, 1) self.tabWidget_2.addTab(self.tab_dilation, "") self.tab_zonal_stats_rasters = QtWidgets.QWidget() self.tab_zonal_stats_rasters.setObjectName("tab_zonal_stats_rasters") self.gridLayout_281 = QtWidgets.QGridLayout(self.tab_zonal_stats_rasters) self.gridLayout_281.setObjectName("gridLayout_281") self.gridLayout_87 = QtWidgets.QGridLayout() self.gridLayout_87.setObjectName("gridLayout_87") self.horizontalLayout_50 = QtWidgets.QHBoxLayout() self.horizontalLayout_50.setObjectName("horizontalLayout_50") self.label_212 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_212.setStyleSheet("background-color : #656565; color : white") self.label_212.setFrameShape(QtWidgets.QFrame.Panel) self.label_212.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_212.setObjectName("label_212") self.horizontalLayout_50.addWidget(self.label_212) self.gridLayout_87.addLayout(self.horizontalLayout_50, 0, 0, 1, 1) self.horizontalLayout_51 = QtWidgets.QHBoxLayout() self.horizontalLayout_51.setObjectName("horizontalLayout_51") self.label_77 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_77.sizePolicy().hasHeightForWidth()) self.label_77.setSizePolicy(sizePolicy) self.label_77.setMinimumSize(QtCore.QSize(229, 0)) self.label_77.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_77.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_77.setObjectName("label_77") self.horizontalLayout_51.addWidget(self.label_77) self.classification_name_combo_5 = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_5.sizePolicy().hasHeightForWidth()) self.classification_name_combo_5.setSizePolicy(sizePolicy) self.classification_name_combo_5.setObjectName("classification_name_combo_5") self.horizontalLayout_51.addWidget(self.classification_name_combo_5) self.toolButton_reload_24 = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) self.toolButton_reload_24.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_24.setIcon(icon55) self.toolButton_reload_24.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_24.setObjectName("toolButton_reload_24") self.horizontalLayout_51.addWidget(self.toolButton_reload_24) self.gridLayout_87.addLayout(self.horizontalLayout_51, 1, 0, 1, 1) self.horizontalLayout_52 = QtWidgets.QHBoxLayout() self.horizontalLayout_52.setObjectName("horizontalLayout_52") self.nodata_checkBox_10 = QtWidgets.QCheckBox(self.tab_zonal_stats_rasters) self.nodata_checkBox_10.setObjectName("nodata_checkBox_10") self.horizontalLayout_52.addWidget(self.nodata_checkBox_10) self.nodata_spinBox_12 = QtWidgets.QSpinBox(self.tab_zonal_stats_rasters) self.nodata_spinBox_12.setMinimum(-2147483647) self.nodata_spinBox_12.setMaximum(2147483647) self.nodata_spinBox_12.setObjectName("nodata_spinBox_12") self.horizontalLayout_52.addWidget(self.nodata_spinBox_12) spacerItem143 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_52.addItem(spacerItem143) self.gridLayout_87.addLayout(self.horizontalLayout_52, 2, 0, 1, 1) self.gridLayout_281.addLayout(self.gridLayout_87, 0, 0, 1, 1) self.gridLayout_91 = QtWidgets.QGridLayout() self.gridLayout_91.setObjectName("gridLayout_91") self.class_field_comboBox_4 = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox_4.sizePolicy().hasHeightForWidth()) self.class_field_comboBox_4.setSizePolicy(sizePolicy) self.class_field_comboBox_4.setObjectName("class_field_comboBox_4") self.gridLayout_91.addWidget(self.class_field_comboBox_4, 1, 2, 1, 1) self.label_214 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_214.sizePolicy().hasHeightForWidth()) self.label_214.setSizePolicy(sizePolicy) self.label_214.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_214.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_214.setObjectName("label_214") self.gridLayout_91.addWidget(self.label_214, 0, 0, 1, 1) self.buttonReload_shape_6 = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) self.buttonReload_shape_6.setStyleSheet("margin: 0px;padding: 0px;") self.buttonReload_shape_6.setIcon(icon55) self.buttonReload_shape_6.setIconSize(QtCore.QSize(22, 22)) self.buttonReload_shape_6.setObjectName("buttonReload_shape_6") self.gridLayout_91.addWidget(self.buttonReload_shape_6, 0, 3, 1, 1) self.label_213 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_213.sizePolicy().hasHeightForWidth()) self.label_213.setSizePolicy(sizePolicy) self.label_213.setMinimumSize(QtCore.QSize(6, 0)) self.label_213.setMaximumSize(QtCore.QSize(100, 200)) self.label_213.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_213.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_213.setObjectName("label_213") self.gridLayout_91.addWidget(self.label_213, 1, 1, 1, 1) self.reference_name_combo_3 = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_name_combo_3.sizePolicy().hasHeightForWidth()) self.reference_name_combo_3.setSizePolicy(sizePolicy) self.reference_name_combo_3.setObjectName("reference_name_combo_3") self.gridLayout_91.addWidget(self.reference_name_combo_3, 0, 1, 1, 2) self.gridLayout_281.addLayout(self.gridLayout_91, 1, 0, 1, 1) self.gridLayout_131 = QtWidgets.QGridLayout() self.gridLayout_131.setObjectName("gridLayout_131") self.statistic_lineEdit = QtWidgets.QLineEdit(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_lineEdit.sizePolicy().hasHeightForWidth()) self.statistic_lineEdit.setSizePolicy(sizePolicy) self.statistic_lineEdit.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_lineEdit.setText("") self.statistic_lineEdit.setMaxLength(10000) self.statistic_lineEdit.setObjectName("statistic_lineEdit") self.gridLayout_131.addWidget(self.statistic_lineEdit, 1, 2, 1, 1) self.statistic_name_combobox = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_name_combobox.sizePolicy().hasHeightForWidth()) self.statistic_name_combobox.setSizePolicy(sizePolicy) self.statistic_name_combobox.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_name_combobox.setObjectName("statistic_name_combobox") self.gridLayout_131.addWidget(self.statistic_name_combobox, 1, 1, 1, 1) self.label_232 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_232.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_232.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_232.setObjectName("label_232") self.gridLayout_131.addWidget(self.label_232, 1, 0, 1, 1) spacerItem144 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_131.addItem(spacerItem144, 1, 3, 1, 1) self.label_216 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_216.setStyleSheet("background-color : #656565; color : white") self.label_216.setFrameShape(QtWidgets.QFrame.Panel) self.label_216.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_216.setObjectName("label_216") self.gridLayout_131.addWidget(self.label_216, 0, 0, 1, 4) self.gridLayout_281.addLayout(self.gridLayout_131, 2, 0, 1, 1) self.gridLayout_128 = QtWidgets.QGridLayout() self.gridLayout_128.setObjectName("gridLayout_128") self.zonal_stat_raster_toolButton = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.zonal_stat_raster_toolButton.setFont(font) self.zonal_stat_raster_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.zonal_stat_raster_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.zonal_stat_raster_toolButton.setIcon(icon64) self.zonal_stat_raster_toolButton.setIconSize(QtCore.QSize(34, 34)) self.zonal_stat_raster_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.zonal_stat_raster_toolButton.setObjectName("zonal_stat_raster_toolButton") self.gridLayout_128.addWidget(self.zonal_stat_raster_toolButton, 2, 2, 1, 1) self.label_215 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_215.setStyleSheet("background-color : #656565; color : white") self.label_215.setFrameShape(QtWidgets.QFrame.Panel) self.label_215.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_215.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_215.setObjectName("label_215") self.gridLayout_128.addWidget(self.label_215, 1, 0, 1, 3) spacerItem145 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_128.addItem(spacerItem145, 2, 0, 1, 1) spacerItem146 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_128.addItem(spacerItem146, 0, 0, 1, 1) self.zonal_stat_raster = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.zonal_stat_raster.setFont(font) self.zonal_stat_raster.setLayoutDirection(QtCore.Qt.RightToLeft) self.zonal_stat_raster.setStyleSheet("margin: 0px;padding: 0px;") self.zonal_stat_raster.setIcon(icon48) self.zonal_stat_raster.setIconSize(QtCore.QSize(34, 34)) self.zonal_stat_raster.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.zonal_stat_raster.setObjectName("zonal_stat_raster") self.gridLayout_128.addWidget(self.zonal_stat_raster, 2, 1, 1, 1) self.gridLayout_281.addLayout(self.gridLayout_128, 3, 0, 1, 1) self.tabWidget_2.addTab(self.tab_zonal_stats_rasters, "") self.gridLayout_552.addWidget(self.tabWidget_2, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_postProcessing, "") self.tab_band_calc = QtWidgets.QWidget() self.tab_band_calc.setObjectName("tab_band_calc") self.gridLayout_303 = QtWidgets.QGridLayout(self.tab_band_calc) self.gridLayout_303.setObjectName("gridLayout_303") self.splitter_band_calc = QtWidgets.QSplitter(self.tab_band_calc) self.splitter_band_calc.setOrientation(QtCore.Qt.Vertical) self.splitter_band_calc.setChildrenCollapsible(False) self.splitter_band_calc.setObjectName("splitter_band_calc") self.widget_2 = QtWidgets.QWidget(self.splitter_band_calc) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_2.sizePolicy().hasHeightForWidth()) self.widget_2.setSizePolicy(sizePolicy) self.widget_2.setMinimumSize(QtCore.QSize(0, 150)) self.widget_2.setObjectName("widget_2") self.gridLayout_126 = QtWidgets.QGridLayout(self.widget_2) self.gridLayout_126.setContentsMargins(1, 1, 1, 1) self.gridLayout_126.setObjectName("gridLayout_126") self.gridLayout_86 = QtWidgets.QGridLayout() self.gridLayout_86.setObjectName("gridLayout_86") self.gridLayout_171 = QtWidgets.QGridLayout() self.gridLayout_171.setObjectName("gridLayout_171") self.toolButton_reload_13 = QtWidgets.QToolButton(self.widget_2) self.toolButton_reload_13.setStyleSheet("margin: 0px;padding: 0px") self.toolButton_reload_13.setIcon(icon55) self.toolButton_reload_13.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_13.setObjectName("toolButton_reload_13") self.gridLayout_171.addWidget(self.toolButton_reload_13, 0, 0, 1, 1) self.gridLayout_86.addLayout(self.gridLayout_171, 1, 1, 2, 1) self.tableWidget_band_calc = QtWidgets.QTableWidget(self.widget_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.tableWidget_band_calc.sizePolicy().hasHeightForWidth()) self.tableWidget_band_calc.setSizePolicy(sizePolicy) self.tableWidget_band_calc.setFrameShape(QtWidgets.QFrame.WinPanel) self.tableWidget_band_calc.setFrameShadow(QtWidgets.QFrame.Sunken) self.tableWidget_band_calc.setAlternatingRowColors(True) self.tableWidget_band_calc.setSelectionMode(QtWidgets.QAbstractItemView.NoSelection) self.tableWidget_band_calc.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.tableWidget_band_calc.setColumnCount(2) self.tableWidget_band_calc.setObjectName("tableWidget_band_calc") self.tableWidget_band_calc.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.tableWidget_band_calc.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.tableWidget_band_calc.setHorizontalHeaderItem(1, item) self.tableWidget_band_calc.horizontalHeader().setDefaultSectionSize(200) self.tableWidget_band_calc.horizontalHeader().setStretchLastSection(True) self.gridLayout_86.addWidget(self.tableWidget_band_calc, 1, 0, 2, 1) self.gridLayout_85 = QtWidgets.QGridLayout() self.gridLayout_85.setObjectName("gridLayout_85") self.bandcalc_filter_lineEdit = QtWidgets.QLineEdit(self.widget_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.bandcalc_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.bandcalc_filter_lineEdit.setSizePolicy(sizePolicy) self.bandcalc_filter_lineEdit.setObjectName("bandcalc_filter_lineEdit") self.gridLayout_85.addWidget(self.bandcalc_filter_lineEdit, 0, 1, 1, 1) self.label_71 = QtWidgets.QLabel(self.widget_2) self.label_71.setStyleSheet("background-color : #656565; color : white") self.label_71.setFrameShape(QtWidgets.QFrame.Panel) self.label_71.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_71.setObjectName("label_71") self.gridLayout_85.addWidget(self.label_71, 0, 0, 1, 1) self.gridLayout_86.addLayout(self.gridLayout_85, 0, 0, 1, 2) self.gridLayout_126.addLayout(self.gridLayout_86, 0, 0, 1, 1) self.widget_3 = QtWidgets.QWidget(self.splitter_band_calc) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_3.sizePolicy().hasHeightForWidth()) self.widget_3.setSizePolicy(sizePolicy) self.widget_3.setMinimumSize(QtCore.QSize(0, 250)) self.widget_3.setObjectName("widget_3") self.gridLayout_40 = QtWidgets.QGridLayout(self.widget_3) self.gridLayout_40.setContentsMargins(0, 0, 0, 0) self.gridLayout_40.setObjectName("gridLayout_40") self.band_calc_tabWidget = QtWidgets.QTabWidget(self.widget_3) self.band_calc_tabWidget.setStyleSheet("QTabBar::tab {\n" "padding: 10px;\n" "min-height: 18px;\n" "}") self.band_calc_tabWidget.setTabPosition(QtWidgets.QTabWidget.North) self.band_calc_tabWidget.setObjectName("band_calc_tabWidget") self.tab_expression = QtWidgets.QWidget() self.tab_expression.setObjectName("tab_expression") self.gridLayout_2 = QtWidgets.QGridLayout(self.tab_expression) self.gridLayout_2.setObjectName("gridLayout_2") self.splitter_2 = QtWidgets.QSplitter(self.tab_expression) self.splitter_2.setOrientation(QtCore.Qt.Horizontal) self.splitter_2.setChildrenCollapsible(False) self.splitter_2.setObjectName("splitter_2") self.plainTextEdit_calc = QtWidgets.QPlainTextEdit(self.splitter_2) self.plainTextEdit_calc.setMinimumSize(QtCore.QSize(100, 0)) self.plainTextEdit_calc.setMaximumSize(QtCore.QSize(16777215, 400)) font = QtGui.QFont() font.setPointSize(11) self.plainTextEdit_calc.setFont(font) self.plainTextEdit_calc.setPlainText("") self.plainTextEdit_calc.setObjectName("plainTextEdit_calc") self.frame = QtWidgets.QFrame(self.splitter_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.frame.sizePolicy().hasHeightForWidth()) self.frame.setSizePolicy(sizePolicy) self.frame.setMinimumSize(QtCore.QSize(100, 0)) self.frame.setMaximumSize(QtCore.QSize(300, 16777215)) self.frame.setFrameShape(QtWidgets.QFrame.StyledPanel) self.frame.setFrameShadow(QtWidgets.QFrame.Raised) self.frame.setObjectName("frame") self.gridLayout_67 = QtWidgets.QGridLayout(self.frame) self.gridLayout_67.setContentsMargins(2, 2, 2, 2) self.gridLayout_67.setObjectName("gridLayout_67") self.gridLayout_88 = QtWidgets.QGridLayout() self.gridLayout_88.setObjectName("gridLayout_88") self.gridLayout_90 = QtWidgets.QGridLayout() self.gridLayout_90.setObjectName("gridLayout_90") self.horizontalLayout_49 = QtWidgets.QHBoxLayout() self.horizontalLayout_49.setObjectName("horizontalLayout_49") self.toolButton_less = QtWidgets.QToolButton(self.frame) self.toolButton_less.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_less.setObjectName("toolButton_less") self.horizontalLayout_49.addWidget(self.toolButton_less) self.toolButton_greater = QtWidgets.QToolButton(self.frame) self.toolButton_greater.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_greater.setObjectName("toolButton_greater") self.horizontalLayout_49.addWidget(self.toolButton_greater) self.toolButton_lbracket = QtWidgets.QToolButton(self.frame) self.toolButton_lbracket.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_lbracket.setObjectName("toolButton_lbracket") self.horizontalLayout_49.addWidget(self.toolButton_lbracket) self.toolButton_rbracket = QtWidgets.QToolButton(self.frame) self.toolButton_rbracket.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_rbracket.setObjectName("toolButton_rbracket") self.horizontalLayout_49.addWidget(self.toolButton_rbracket) self.toolButton_power = QtWidgets.QToolButton(self.frame) self.toolButton_power.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_power.setObjectName("toolButton_power") self.horizontalLayout_49.addWidget(self.toolButton_power) self.toolButton_sqrt = QtWidgets.QToolButton(self.frame) self.toolButton_sqrt.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_sqrt.setObjectName("toolButton_sqrt") self.horizontalLayout_49.addWidget(self.toolButton_sqrt) self.gridLayout_90.addLayout(self.horizontalLayout_49, 1, 0, 1, 1) self.horizontalLayout_4 = QtWidgets.QHBoxLayout() self.horizontalLayout_4.setObjectName("horizontalLayout_4") self.toolButton_plus = QtWidgets.QToolButton(self.frame) self.toolButton_plus.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_plus.setObjectName("toolButton_plus") self.horizontalLayout_4.addWidget(self.toolButton_plus) self.toolButton_minus = QtWidgets.QToolButton(self.frame) self.toolButton_minus.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_minus.setObjectName("toolButton_minus") self.horizontalLayout_4.addWidget(self.toolButton_minus) self.toolButton_product = QtWidgets.QToolButton(self.frame) self.toolButton_product.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_product.setObjectName("toolButton_product") self.horizontalLayout_4.addWidget(self.toolButton_product) self.toolButton_ratio = QtWidgets.QToolButton(self.frame) self.toolButton_ratio.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_ratio.setObjectName("toolButton_ratio") self.horizontalLayout_4.addWidget(self.toolButton_ratio) self.toolButton_equal = QtWidgets.QToolButton(self.frame) self.toolButton_equal.setMinimumSize(QtCore.QSize(45, 25)) self.toolButton_equal.setObjectName("toolButton_equal") self.horizontalLayout_4.addWidget(self.toolButton_equal) self.toolButton_unequal = QtWidgets.QToolButton(self.frame) self.toolButton_unequal.setMinimumSize(QtCore.QSize(45, 25)) self.toolButton_unequal.setObjectName("toolButton_unequal") self.horizontalLayout_4.addWidget(self.toolButton_unequal) self.gridLayout_90.addLayout(self.horizontalLayout_4, 0, 0, 1, 2) self.toolButton_import_expression = QtWidgets.QToolButton(self.frame) self.toolButton_import_expression.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_import_expression.setIcon(icon65) self.toolButton_import_expression.setIconSize(QtCore.QSize(22, 22)) self.toolButton_import_expression.setObjectName("toolButton_import_expression") self.gridLayout_90.addWidget(self.toolButton_import_expression, 1, 1, 1, 1) self.gridLayout_88.addLayout(self.gridLayout_90, 0, 0, 2, 3) self.gridLayout_93 = QtWidgets.QGridLayout() self.gridLayout_93.setObjectName("gridLayout_93") self.gridLayout_38 = QtWidgets.QGridLayout() self.gridLayout_38.setObjectName("gridLayout_38") self.band_calc_function_tableWidget = QtWidgets.QTableWidget(self.frame) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.band_calc_function_tableWidget.sizePolicy().hasHeightForWidth()) self.band_calc_function_tableWidget.setSizePolicy(sizePolicy) self.band_calc_function_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.band_calc_function_tableWidget.setAlternatingRowColors(True) self.band_calc_function_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.SingleSelection) self.band_calc_function_tableWidget.setObjectName("band_calc_function_tableWidget") self.band_calc_function_tableWidget.setColumnCount(1) self.band_calc_function_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.band_calc_function_tableWidget.setHorizontalHeaderItem(0, item) self.band_calc_function_tableWidget.horizontalHeader().setStretchLastSection(True) self.band_calc_function_tableWidget.verticalHeader().setVisible(False) self.gridLayout_38.addWidget(self.band_calc_function_tableWidget, 0, 0, 1, 1) self.gridLayout_93.addLayout(self.gridLayout_38, 0, 0, 1, 2) self.gridLayout_88.addLayout(self.gridLayout_93, 3, 0, 1, 3) self.gridLayout_67.addLayout(self.gridLayout_88, 0, 0, 1, 1) self.gridLayout_2.addWidget(self.splitter_2, 0, 0, 1, 1) icon82 = QtGui.QIcon() icon82.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandcalc_expression.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.band_calc_tabWidget.addTab(self.tab_expression, icon82, "") self.tab_decision_rules = QtWidgets.QWidget() self.tab_decision_rules.setObjectName("tab_decision_rules") self.gridLayout_89 = QtWidgets.QGridLayout(self.tab_decision_rules) self.gridLayout_89.setObjectName("gridLayout_89") self.gridLayout_215 = QtWidgets.QGridLayout() self.gridLayout_215.setObjectName("gridLayout_215") self.decision_rules_tableWidget = QtWidgets.QTableWidget(self.tab_decision_rules) font = QtGui.QFont() font.setPointSize(10) self.decision_rules_tableWidget.setFont(font) self.decision_rules_tableWidget.setObjectName("decision_rules_tableWidget") self.decision_rules_tableWidget.setColumnCount(2) self.decision_rules_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.decision_rules_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.decision_rules_tableWidget.setHorizontalHeaderItem(1, item) self.decision_rules_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_215.addWidget(self.decision_rules_tableWidget, 0, 0, 1, 1) self.gridLayout_89.addLayout(self.gridLayout_215, 0, 0, 1, 1) self.gridLayout_220 = QtWidgets.QGridLayout() self.gridLayout_220.setObjectName("gridLayout_220") spacerItem147 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_220.addItem(spacerItem147, 6, 0, 1, 1) self.remove_rule_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.remove_rule_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_rule_toolButton.setIcon(icon58) self.remove_rule_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_rule_toolButton.setObjectName("remove_rule_toolButton") self.gridLayout_220.addWidget(self.remove_rule_toolButton, 4, 0, 1, 1) self.move_up_toolButton_2 = QtWidgets.QToolButton(self.tab_decision_rules) self.move_up_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.move_up_toolButton_2.setIcon(icon61) self.move_up_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton_2.setObjectName("move_up_toolButton_2") self.gridLayout_220.addWidget(self.move_up_toolButton_2, 0, 0, 1, 1) self.import_rules_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.import_rules_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_rules_toolButton.setIcon(icon54) self.import_rules_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_rules_toolButton.setObjectName("import_rules_toolButton") self.gridLayout_220.addWidget(self.import_rules_toolButton, 7, 0, 1, 1) self.clear_rules_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.clear_rules_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_rules_toolButton.setIcon(icon59) self.clear_rules_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_rules_toolButton.setObjectName("clear_rules_toolButton") self.gridLayout_220.addWidget(self.clear_rules_toolButton, 5, 0, 1, 1) spacerItem148 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_220.addItem(spacerItem148, 9, 0, 1, 1) self.add_rule_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.add_rule_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.add_rule_toolButton.setIcon(icon66) self.add_rule_toolButton.setIconSize(QtCore.QSize(22, 22)) self.add_rule_toolButton.setObjectName("add_rule_toolButton") self.gridLayout_220.addWidget(self.add_rule_toolButton, 3, 0, 1, 1) spacerItem149 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_220.addItem(spacerItem149, 2, 0, 1, 1) self.move_down_toolButton_2 = QtWidgets.QToolButton(self.tab_decision_rules) self.move_down_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.move_down_toolButton_2.setIcon(icon62) self.move_down_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton_2.setObjectName("move_down_toolButton_2") self.gridLayout_220.addWidget(self.move_down_toolButton_2, 1, 0, 1, 1) self.export_rules_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.export_rules_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_rules_toolButton.setIcon(icon53) self.export_rules_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_rules_toolButton.setObjectName("export_rules_toolButton") self.gridLayout_220.addWidget(self.export_rules_toolButton, 8, 0, 1, 1) self.gridLayout_89.addLayout(self.gridLayout_220, 0, 1, 1, 1) icon83 = QtGui.QIcon() icon83.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandcalc_rules.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.band_calc_tabWidget.addTab(self.tab_decision_rules, icon83, "") self.gridLayout_40.addWidget(self.band_calc_tabWidget, 0, 0, 1, 1) self.horizontalLayout_73 = QtWidgets.QHBoxLayout() self.horizontalLayout_73.setObjectName("horizontalLayout_73") self.nodata_as_value_checkBox = QtWidgets.QCheckBox(self.widget_3) self.nodata_as_value_checkBox.setObjectName("nodata_as_value_checkBox") self.horizontalLayout_73.addWidget(self.nodata_as_value_checkBox) self.nodata_checkBox_3 = QtWidgets.QCheckBox(self.widget_3) self.nodata_checkBox_3.setObjectName("nodata_checkBox_3") self.horizontalLayout_73.addWidget(self.nodata_checkBox_3) self.nodata_spinBox_13 = QtWidgets.QSpinBox(self.widget_3) self.nodata_spinBox_13.setMinimum(-2147483647) self.nodata_spinBox_13.setMaximum(2147483647) self.nodata_spinBox_13.setObjectName("nodata_spinBox_13") self.horizontalLayout_73.addWidget(self.nodata_spinBox_13) self.label_4 = QtWidgets.QLabel(self.widget_3) self.label_4.setObjectName("label_4") self.horizontalLayout_73.addWidget(self.label_4) self.calc_type_combo = QtWidgets.QComboBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.calc_type_combo.sizePolicy().hasHeightForWidth()) self.calc_type_combo.setSizePolicy(sizePolicy) self.calc_type_combo.setObjectName("calc_type_combo") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.horizontalLayout_73.addWidget(self.calc_type_combo) spacerItem150 = QtWidgets.QSpacerItem(214, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_73.addItem(spacerItem150) self.label_83 = QtWidgets.QLabel(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_83.sizePolicy().hasHeightForWidth()) self.label_83.setSizePolicy(sizePolicy) self.label_83.setMinimumSize(QtCore.QSize(40, 0)) self.label_83.setMaximumSize(QtCore.QSize(120, 16777215)) self.label_83.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_83.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_83.setObjectName("label_83") self.horizontalLayout_73.addWidget(self.label_83) self.intersection_checkBox = QtWidgets.QCheckBox(self.widget_3) self.intersection_checkBox.setChecked(True) self.intersection_checkBox.setObjectName("intersection_checkBox") self.horizontalLayout_73.addWidget(self.intersection_checkBox) self.extent_checkBox = QtWidgets.QCheckBox(self.widget_3) self.extent_checkBox.setObjectName("extent_checkBox") self.horizontalLayout_73.addWidget(self.extent_checkBox) self.raster_extent_combo = QtWidgets.QComboBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_extent_combo.sizePolicy().hasHeightForWidth()) self.raster_extent_combo.setSizePolicy(sizePolicy) self.raster_extent_combo.setObjectName("raster_extent_combo") self.horizontalLayout_73.addWidget(self.raster_extent_combo) self.align_radioButton = QtWidgets.QRadioButton(self.widget_3) self.align_radioButton.setChecked(True) self.align_radioButton.setObjectName("align_radioButton") self.horizontalLayout_73.addWidget(self.align_radioButton) self.gridLayout_40.addLayout(self.horizontalLayout_73, 1, 0, 1, 1) self.label_84 = QtWidgets.QLabel(self.widget_3) self.label_84.setStyleSheet("background-color : #656565; color : white") self.label_84.setFrameShape(QtWidgets.QFrame.Panel) self.label_84.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_84.setObjectName("label_84") self.gridLayout_40.addWidget(self.label_84, 2, 0, 1, 1) self.horizontalLayout_60 = QtWidgets.QHBoxLayout() self.horizontalLayout_60.setObjectName("horizontalLayout_60") self.raster_type_combo = QtWidgets.QComboBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_type_combo.sizePolicy().hasHeightForWidth()) self.raster_type_combo.setSizePolicy(sizePolicy) self.raster_type_combo.setObjectName("raster_type_combo") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.horizontalLayout_60.addWidget(self.raster_type_combo) self.label_268 = QtWidgets.QLabel(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_268.sizePolicy().hasHeightForWidth()) self.label_268.setSizePolicy(sizePolicy) self.label_268.setMinimumSize(QtCore.QSize(50, 0)) self.label_268.setMaximumSize(QtCore.QSize(130, 16777215)) self.label_268.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_268.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_268.setObjectName("label_268") self.horizontalLayout_60.addWidget(self.label_268) self.nodata_spinBox_4 = QtWidgets.QSpinBox(self.widget_3) self.nodata_spinBox_4.setMinimum(-2147483647) self.nodata_spinBox_4.setMaximum(2147483647) self.nodata_spinBox_4.setProperty("value", -32768) self.nodata_spinBox_4.setObjectName("nodata_spinBox_4") self.horizontalLayout_60.addWidget(self.nodata_spinBox_4) self.nodata_mask_checkBox = QtWidgets.QCheckBox(self.widget_3) self.nodata_mask_checkBox.setChecked(True) self.nodata_mask_checkBox.setObjectName("nodata_mask_checkBox") self.horizontalLayout_60.addWidget(self.nodata_mask_checkBox) self.set_scale_checkBox = QtWidgets.QCheckBox(self.widget_3) self.set_scale_checkBox.setObjectName("set_scale_checkBox") self.horizontalLayout_60.addWidget(self.set_scale_checkBox) self.scale_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.scale_doubleSpinBox.sizePolicy().hasHeightForWidth()) self.scale_doubleSpinBox.setSizePolicy(sizePolicy) self.scale_doubleSpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.scale_doubleSpinBox.setDecimals(7) self.scale_doubleSpinBox.setMinimum(-1e+34) self.scale_doubleSpinBox.setMaximum(1e+34) self.scale_doubleSpinBox.setProperty("value", 1.0) self.scale_doubleSpinBox.setObjectName("scale_doubleSpinBox") self.horizontalLayout_60.addWidget(self.scale_doubleSpinBox) self.set_offset_checkBox = QtWidgets.QCheckBox(self.widget_3) self.set_offset_checkBox.setObjectName("set_offset_checkBox") self.horizontalLayout_60.addWidget(self.set_offset_checkBox) self.offset_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.offset_doubleSpinBox.sizePolicy().hasHeightForWidth()) self.offset_doubleSpinBox.setSizePolicy(sizePolicy) self.offset_doubleSpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.offset_doubleSpinBox.setDecimals(7) self.offset_doubleSpinBox.setMinimum(-1e+34) self.offset_doubleSpinBox.setMaximum(1e+34) self.offset_doubleSpinBox.setProperty("value", 0.0) self.offset_doubleSpinBox.setObjectName("offset_doubleSpinBox") self.horizontalLayout_60.addWidget(self.offset_doubleSpinBox) spacerItem151 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_60.addItem(spacerItem151) self.band_calc = QtWidgets.QToolButton(self.widget_3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.band_calc.setFont(font) self.band_calc.setLayoutDirection(QtCore.Qt.RightToLeft) self.band_calc.setStyleSheet("margin: 0px;padding: 0px;") self.band_calc.setIcon(icon48) self.band_calc.setIconSize(QtCore.QSize(34, 34)) self.band_calc.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.band_calc.setObjectName("band_calc") self.horizontalLayout_60.addWidget(self.band_calc) self.toolButton_calculate = QtWidgets.QToolButton(self.widget_3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.toolButton_calculate.setFont(font) self.toolButton_calculate.setLayoutDirection(QtCore.Qt.RightToLeft) self.toolButton_calculate.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_calculate.setIcon(icon64) self.toolButton_calculate.setIconSize(QtCore.QSize(34, 34)) self.toolButton_calculate.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.toolButton_calculate.setObjectName("toolButton_calculate") self.horizontalLayout_60.addWidget(self.toolButton_calculate) self.gridLayout_40.addLayout(self.horizontalLayout_60, 3, 0, 1, 1) self.gridLayout_303.addWidget(self.splitter_band_calc, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_band_calc, "") self.tab_batch = QtWidgets.QWidget() self.tab_batch.setObjectName("tab_batch") self.verticalLayout_5 = QtWidgets.QVBoxLayout(self.tab_batch) self.verticalLayout_5.setObjectName("verticalLayout_5") self.verticalLayout_3 = QtWidgets.QVBoxLayout() self.verticalLayout_3.setObjectName("verticalLayout_3") self.label_73 = QtWidgets.QLabel(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_73.sizePolicy().hasHeightForWidth()) self.label_73.setSizePolicy(sizePolicy) self.label_73.setStyleSheet("background-color : #656565; color : white") self.label_73.setFrameShape(QtWidgets.QFrame.Panel) self.label_73.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_73.setObjectName("label_73") self.verticalLayout_3.addWidget(self.label_73) self.splitter_batch = QtWidgets.QSplitter(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.splitter_batch.sizePolicy().hasHeightForWidth()) self.splitter_batch.setSizePolicy(sizePolicy) self.splitter_batch.setMinimumSize(QtCore.QSize(100, 0)) self.splitter_batch.setOrientation(QtCore.Qt.Horizontal) self.splitter_batch.setChildrenCollapsible(False) self.splitter_batch.setObjectName("splitter_batch") self.plainTextEdit_batch = QtWidgets.QPlainTextEdit(self.splitter_batch) self.plainTextEdit_batch.setMinimumSize(QtCore.QSize(200, 0)) font = QtGui.QFont() font.setPointSize(11) self.plainTextEdit_batch.setFont(font) self.plainTextEdit_batch.setPlainText("") self.plainTextEdit_batch.setObjectName("plainTextEdit_batch") self.widget_4 = QtWidgets.QWidget(self.splitter_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Ignored) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_4.sizePolicy().hasHeightForWidth()) self.widget_4.setSizePolicy(sizePolicy) self.widget_4.setMinimumSize(QtCore.QSize(100, 400)) self.widget_4.setMaximumSize(QtCore.QSize(250, 16777215)) self.widget_4.setObjectName("widget_4") self.gridLayout_76 = QtWidgets.QGridLayout(self.widget_4) self.gridLayout_76.setContentsMargins(1, 1, 1, 1) self.gridLayout_76.setObjectName("gridLayout_76") self.gridLayout_214 = QtWidgets.QGridLayout() self.gridLayout_214.setObjectName("gridLayout_214") self.export_batch_toolButton = QtWidgets.QToolButton(self.widget_4) self.export_batch_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_batch_toolButton.setIcon(icon53) self.export_batch_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_batch_toolButton.setObjectName("export_batch_toolButton") self.gridLayout_214.addWidget(self.export_batch_toolButton, 0, 2, 1, 1) self.clear_batch_toolButton = QtWidgets.QToolButton(self.widget_4) self.clear_batch_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_batch_toolButton.setIcon(icon59) self.clear_batch_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_batch_toolButton.setObjectName("clear_batch_toolButton") self.gridLayout_214.addWidget(self.clear_batch_toolButton, 0, 0, 1, 1) self.import_batch_toolButton = QtWidgets.QToolButton(self.widget_4) self.import_batch_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_batch_toolButton.setIcon(icon54) self.import_batch_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_batch_toolButton.setObjectName("import_batch_toolButton") self.gridLayout_214.addWidget(self.import_batch_toolButton, 0, 1, 1, 1) self.gridLayout_76.addLayout(self.gridLayout_214, 1, 0, 1, 1) self.batch_tableWidget = QtWidgets.QTableWidget(self.widget_4) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.batch_tableWidget.sizePolicy().hasHeightForWidth()) self.batch_tableWidget.setSizePolicy(sizePolicy) self.batch_tableWidget.setMaximumSize(QtCore.QSize(300, 16777215)) self.batch_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.batch_tableWidget.setAlternatingRowColors(True) self.batch_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.SingleSelection) self.batch_tableWidget.setObjectName("batch_tableWidget") self.batch_tableWidget.setColumnCount(1) self.batch_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.batch_tableWidget.setHorizontalHeaderItem(0, item) self.batch_tableWidget.horizontalHeader().setStretchLastSection(True) self.batch_tableWidget.verticalHeader().setVisible(False) self.gridLayout_76.addWidget(self.batch_tableWidget, 0, 0, 1, 1) self.verticalLayout_3.addWidget(self.splitter_batch) self.batch_label = QtWidgets.QLabel(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.batch_label.sizePolicy().hasHeightForWidth()) self.batch_label.setSizePolicy(sizePolicy) self.batch_label.setText("") self.batch_label.setObjectName("batch_label") self.verticalLayout_3.addWidget(self.batch_label) self.label_177 = QtWidgets.QLabel(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_177.sizePolicy().hasHeightForWidth()) self.label_177.setSizePolicy(sizePolicy) self.label_177.setStyleSheet("background-color : #656565; color : white") self.label_177.setFrameShape(QtWidgets.QFrame.Panel) self.label_177.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_177.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_177.setObjectName("label_177") self.verticalLayout_3.addWidget(self.label_177) self.horizontalLayout_69 = QtWidgets.QHBoxLayout() self.horizontalLayout_69.setObjectName("horizontalLayout_69") spacerItem152 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_69.addItem(spacerItem152) self.check_batch = QtWidgets.QToolButton(self.tab_batch) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.check_batch.setFont(font) self.check_batch.setLayoutDirection(QtCore.Qt.RightToLeft) self.check_batch.setStyleSheet("margin: 0px;padding: 0px;") icon84 = QtGui.QIcon() icon84.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_batch_check.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.check_batch.setIcon(icon84) self.check_batch.setIconSize(QtCore.QSize(34, 34)) self.check_batch.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.check_batch.setObjectName("check_batch") self.horizontalLayout_69.addWidget(self.check_batch) self.toolButton_run_batch = QtWidgets.QToolButton(self.tab_batch) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.toolButton_run_batch.setFont(font) self.toolButton_run_batch.setLayoutDirection(QtCore.Qt.RightToLeft) self.toolButton_run_batch.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_run_batch.setIcon(icon64) self.toolButton_run_batch.setIconSize(QtCore.QSize(34, 34)) self.toolButton_run_batch.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.toolButton_run_batch.setObjectName("toolButton_run_batch") self.horizontalLayout_69.addWidget(self.toolButton_run_batch) self.verticalLayout_3.addLayout(self.horizontalLayout_69) self.verticalLayout_5.addLayout(self.verticalLayout_3) self.SCP_tabs.addTab(self.tab_batch, "") self.tab_Settings = QtWidgets.QWidget() sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.tab_Settings.sizePolicy().hasHeightForWidth()) self.tab_Settings.setSizePolicy(sizePolicy) self.tab_Settings.setMinimumSize(QtCore.QSize(454, 0)) self.tab_Settings.setMaximumSize(QtCore.QSize(16777215, 16777215)) self.tab_Settings.setObjectName("tab_Settings") self.gridLayout_134 = QtWidgets.QGridLayout(self.tab_Settings) self.gridLayout_134.setObjectName("gridLayout_134") self.settings_tabWidget = QtWidgets.QTabWidget(self.tab_Settings) self.settings_tabWidget.setDocumentMode(True) self.settings_tabWidget.setObjectName("settings_tabWidget") self.tabWidgetProcessing = QtWidgets.QWidget() self.tabWidgetProcessing.setObjectName("tabWidgetProcessing") self.gridLayout_195 = QtWidgets.QGridLayout(self.tabWidgetProcessing) self.gridLayout_195.setObjectName("gridLayout_195") self.gridLayout_3 = QtWidgets.QGridLayout() self.gridLayout_3.setObjectName("gridLayout_3") self.label_28 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_28.setStyleSheet("background-color : #656565; color : white") self.label_28.setFrameShape(QtWidgets.QFrame.Panel) self.label_28.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_28.setObjectName("label_28") self.gridLayout_3.addWidget(self.label_28, 0, 0, 1, 1) self.gridLayout = QtWidgets.QGridLayout() self.gridLayout.setObjectName("gridLayout") self.RAM_spinBox = QtWidgets.QSpinBox(self.tabWidgetProcessing) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.RAM_spinBox.sizePolicy().hasHeightForWidth()) self.RAM_spinBox.setSizePolicy(sizePolicy) self.RAM_spinBox.setMinimumSize(QtCore.QSize(50, 0)) self.RAM_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.RAM_spinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.RAM_spinBox.setMinimum(128) self.RAM_spinBox.setMaximum(196608) self.RAM_spinBox.setSingleStep(10) self.RAM_spinBox.setProperty("value", 512) self.RAM_spinBox.setObjectName("RAM_spinBox") self.gridLayout.addWidget(self.RAM_spinBox, 0, 1, 1, 1) self.label_23 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_23.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_23.setObjectName("label_23") self.gridLayout.addWidget(self.label_23, 0, 0, 1, 1) self.label_56 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_56.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_56.setObjectName("label_56") self.gridLayout.addWidget(self.label_56, 1, 0, 1, 1) self.CPU_spinBox = QtWidgets.QSpinBox(self.tabWidgetProcessing) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.CPU_spinBox.sizePolicy().hasHeightForWidth()) self.CPU_spinBox.setSizePolicy(sizePolicy) self.CPU_spinBox.setMinimumSize(QtCore.QSize(50, 0)) self.CPU_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.CPU_spinBox.setAlignment(QtCore.Qt.AlignRight\|QtCore.Qt.AlignTrailing\|QtCore.Qt.AlignVCenter) self.CPU_spinBox.setMinimum(1) self.CPU_spinBox.setMaximum(1000) self.CPU_spinBox.setSingleStep(1) self.CPU_spinBox.setProperty("value", 1) self.CPU_spinBox.setObjectName("CPU_spinBox") self.gridLayout.addWidget(self.CPU_spinBox, 1, 1, 1, 1) self.gridLayout_3.addLayout(self.gridLayout, 1, 0, 1, 1) self.gridLayout_195.addLayout(self.gridLayout_3, 0, 0, 1, 1) self.gridLayout_237 = QtWidgets.QGridLayout() self.gridLayout_237.setObjectName("gridLayout_237") self.label_13 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_13.setFrameShape(QtWidgets.QFrame.Panel) self.label_13.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_13.setObjectName("label_13") self.gridLayout_237.addWidget(self.label_13, 1, 1, 1, 1) self.label_18 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_18.setFrameShape(QtWidgets.QFrame.Panel) self.label_18.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_18.setObjectName("label_18") self.gridLayout_237.addWidget(self.label_18, 1, 3, 1, 1) self.smtp_user_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.smtp_user_lineEdit.setObjectName("smtp_user_lineEdit") self.gridLayout_237.addWidget(self.smtp_user_lineEdit, 2, 2, 1, 1) self.smtp_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.smtp_checkBox.setChecked(True) self.smtp_checkBox.setTristate(False) self.smtp_checkBox.setObjectName("smtp_checkBox") self.gridLayout_237.addWidget(self.smtp_checkBox, 3, 1, 1, 1) self.label_117 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_117.setStyleSheet("background-color : #656565; color : white") self.label_117.setFrameShape(QtWidgets.QFrame.Panel) self.label_117.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_117.setObjectName("label_117") self.gridLayout_237.addWidget(self.label_117, 0, 0, 1, 5) self.smtp_password_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.smtp_password_lineEdit.setObjectName("smtp_password_lineEdit") self.gridLayout_237.addWidget(self.smtp_password_lineEdit, 2, 3, 1, 1) self.smtp_server_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.smtp_server_lineEdit.setObjectName("smtp_server_lineEdit") self.gridLayout_237.addWidget(self.smtp_server_lineEdit, 2, 1, 1, 1) self.label_14 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_14.setFrameShape(QtWidgets.QFrame.Panel) self.label_14.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_14.setObjectName("label_14") self.gridLayout_237.addWidget(self.label_14, 1, 2, 1, 1) self.to_email_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.to_email_lineEdit.setObjectName("to_email_lineEdit") self.gridLayout_237.addWidget(self.to_email_lineEdit, 3, 2, 1, 3) self.remeber_settings_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.remeber_settings_checkBox.setChecked(True) self.remeber_settings_checkBox.setObjectName("remeber_settings_checkBox") self.gridLayout_237.addWidget(self.remeber_settings_checkBox, 2, 4, 1, 1) self.gridLayout_195.addLayout(self.gridLayout_237, 2, 0, 1, 1) self.gridLayout_124 = QtWidgets.QGridLayout() self.gridLayout_124.setObjectName("gridLayout_124") self.reset_temp_directory_Button = QtWidgets.QToolButton(self.tabWidgetProcessing) self.reset_temp_directory_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_temp_directory_Button.setIcon(icon59) self.reset_temp_directory_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_temp_directory_Button.setObjectName("reset_temp_directory_Button") self.gridLayout_124.addWidget(self.reset_temp_directory_Button, 2, 3, 1, 1) self.temp_directory_Button = QtWidgets.QToolButton(self.tabWidgetProcessing) self.temp_directory_Button.setStyleSheet("margin: 0px;padding: 0px;") self.temp_directory_Button.setIcon(icon69) self.temp_directory_Button.setIconSize(QtCore.QSize(22, 22)) self.temp_directory_Button.setObjectName("temp_directory_Button") self.gridLayout_124.addWidget(self.temp_directory_Button, 2, 0, 1, 1) self.label_87 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_87.setStyleSheet("background-color : #656565; color : white") self.label_87.setFrameShape(QtWidgets.QFrame.Panel) self.label_87.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_87.setObjectName("label_87") self.gridLayout_124.addWidget(self.label_87, 0, 0, 1, 4) self.temp_directory_label = QtWidgets.QLabel(self.tabWidgetProcessing) self.temp_directory_label.setFrameShape(QtWidgets.QFrame.Panel) self.temp_directory_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.temp_directory_label.setText("") self.temp_directory_label.setObjectName("temp_directory_label") self.gridLayout_124.addWidget(self.temp_directory_label, 2, 1, 1, 2) self.gridLayout_195.addLayout(self.gridLayout_124, 3, 0, 1, 1) self.gridLayout_107 = QtWidgets.QGridLayout() self.gridLayout_107.setObjectName("gridLayout_107") self.verticalLayout_6 = QtWidgets.QVBoxLayout() self.verticalLayout_6.setObjectName("verticalLayout_6") self.SNAP_label = QtWidgets.QLabel(self.tabWidgetProcessing) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.SNAP_label.sizePolicy().hasHeightForWidth()) self.SNAP_label.setSizePolicy(sizePolicy) self.SNAP_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.SNAP_label.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.SNAP_label.setObjectName("SNAP_label") self.verticalLayout_6.addWidget(self.SNAP_label) self.label_276 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_276.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_276.setObjectName("label_276") self.verticalLayout_6.addWidget(self.label_276) self.label_288 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_288.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_288.setObjectName("label_288") self.verticalLayout_6.addWidget(self.label_288) self.label_275 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_275.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_275.setObjectName("label_275") self.verticalLayout_6.addWidget(self.label_275) self.gridLayout_107.addLayout(self.verticalLayout_6, 1, 0, 1, 1) self.verticalLayout_7 = QtWidgets.QVBoxLayout() self.verticalLayout_7.setObjectName("verticalLayout_7") self.SNAP_GPT_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.SNAP_GPT_lineEdit.setObjectName("SNAP_GPT_lineEdit") self.verticalLayout_7.addWidget(self.SNAP_GPT_lineEdit) self.python_path_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.python_path_lineEdit.setObjectName("python_path_lineEdit") self.verticalLayout_7.addWidget(self.python_path_lineEdit) self.python_path_lineEdit_2 = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.python_path_lineEdit_2.setObjectName("python_path_lineEdit_2") self.verticalLayout_7.addWidget(self.python_path_lineEdit_2) self.gdal_path_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.gdal_path_lineEdit.setObjectName("gdal_path_lineEdit") self.verticalLayout_7.addWidget(self.gdal_path_lineEdit) self.gridLayout_107.addLayout(self.verticalLayout_7, 1, 1, 1, 1) self.label_211 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_211.setStyleSheet("background-color : #656565; color : white") self.label_211.setFrameShape(QtWidgets.QFrame.Panel) self.label_211.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_211.setObjectName("label_211") self.gridLayout_107.addWidget(self.label_211, 0, 0, 1, 2) self.gridLayout_195.addLayout(self.gridLayout_107, 4, 0, 1, 1) self.gridLayout_30 = QtWidgets.QGridLayout() self.gridLayout_30.setObjectName("gridLayout_30") self.sound_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.sound_checkBox.setChecked(True) self.sound_checkBox.setTristate(False) self.sound_checkBox.setObjectName("sound_checkBox") self.gridLayout_30.addWidget(self.sound_checkBox, 1, 0, 1, 1) self.virtual_raster_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.virtual_raster_checkBox.setChecked(True) self.virtual_raster_checkBox.setObjectName("virtual_raster_checkBox") self.gridLayout_30.addWidget(self.virtual_raster_checkBox, 1, 1, 1, 1) self.label_45 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_45.setStyleSheet("background-color : #656565; color : white") self.label_45.setFrameShape(QtWidgets.QFrame.Panel) self.label_45.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_45.setObjectName("label_45") self.gridLayout_30.addWidget(self.label_45, 0, 0, 1, 3) self.raster_compression_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.raster_compression_checkBox.setChecked(True) self.raster_compression_checkBox.setObjectName("raster_compression_checkBox") self.gridLayout_30.addWidget(self.raster_compression_checkBox, 1, 2, 1, 1) self.horizontalLayout_65 = QtWidgets.QHBoxLayout() self.horizontalLayout_65.setObjectName("horizontalLayout_65") self.parallel_writing_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.parallel_writing_checkBox.setObjectName("parallel_writing_checkBox") self.horizontalLayout_65.addWidget(self.parallel_writing_checkBox) self.gridLayout_30.addLayout(self.horizontalLayout_65, 2, 0, 1, 3) self.gridLayout_195.addLayout(self.gridLayout_30, 1, 0, 1, 1) spacerItem153 = QtWidgets.QSpacerItem(17, 17, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_195.addItem(spacerItem153, 5, 0, 1, 1) self.settings_tabWidget.addTab(self.tabWidgetProcessing, "") self.tabWidgetInterface = QtWidgets.QWidget() self.tabWidgetInterface.setObjectName("tabWidgetInterface") self.gridLayout_63 = QtWidgets.QGridLayout(self.tabWidgetInterface) self.gridLayout_63.setObjectName("gridLayout_63") self.gridLayout_13 = QtWidgets.QGridLayout() self.gridLayout_13.setObjectName("gridLayout_13") self.label_31 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_31.setFrameShape(QtWidgets.QFrame.Panel) self.label_31.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_31.setObjectName("label_31") self.gridLayout_13.addWidget(self.label_31, 1, 3, 1, 1) self.Info_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.Info_field_name_lineEdit.setMaxLength(10) self.Info_field_name_lineEdit.setObjectName("Info_field_name_lineEdit") self.gridLayout_13.addWidget(self.Info_field_name_lineEdit, 2, 3, 1, 1) self.label_24 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_24.setStyleSheet("background-color : #656565; color : white") self.label_24.setFrameShape(QtWidgets.QFrame.Panel) self.label_24.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_24.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_24.setObjectName("label_24") self.gridLayout_13.addWidget(self.label_24, 0, 0, 1, 5) self.ID_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.ID_field_name_lineEdit.setMaxLength(10) self.ID_field_name_lineEdit.setObjectName("ID_field_name_lineEdit") self.gridLayout_13.addWidget(self.ID_field_name_lineEdit, 2, 2, 1, 1) self.MID_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.MID_field_name_lineEdit.setMaxLength(10) self.MID_field_name_lineEdit.setObjectName("MID_field_name_lineEdit") self.gridLayout_13.addWidget(self.MID_field_name_lineEdit, 2, 0, 1, 1) self.label_10 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_10.setFrameShape(QtWidgets.QFrame.Panel) self.label_10.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_10.setObjectName("label_10") self.gridLayout_13.addWidget(self.label_10, 1, 2, 1, 1) self.MCInfo_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.MCInfo_field_name_lineEdit.setMaxLength(10) self.MCInfo_field_name_lineEdit.setObjectName("MCInfo_field_name_lineEdit") self.gridLayout_13.addWidget(self.MCInfo_field_name_lineEdit, 2, 1, 1, 1) self.label_17 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_17.setFrameShape(QtWidgets.QFrame.Panel) self.label_17.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_17.setObjectName("label_17") self.gridLayout_13.addWidget(self.label_17, 1, 0, 1, 1) self.label_46 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_46.setFrameShape(QtWidgets.QFrame.Panel) self.label_46.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_46.setObjectName("label_46") self.gridLayout_13.addWidget(self.label_46, 1, 1, 1, 1) self.reset_field_names_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_field_names_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_field_names_Button.setIcon(icon59) self.reset_field_names_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_field_names_Button.setObjectName("reset_field_names_Button") self.gridLayout_13.addWidget(self.reset_field_names_Button, 2, 4, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_13, 0, 0, 1, 1) self.gridLayout_21 = QtWidgets.QGridLayout() self.gridLayout_21.setObjectName("gridLayout_21") self.label_21 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_21.setStyleSheet("background-color : #656565; color : white") self.label_21.setFrameShape(QtWidgets.QFrame.Panel) self.label_21.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_21.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_21.setObjectName("label_21") self.gridLayout_21.addWidget(self.label_21, 0, 1, 1, 3) self.gridLayout_172 = QtWidgets.QGridLayout() self.gridLayout_172.setObjectName("gridLayout_172") self.change_color_Button = QtWidgets.QPushButton(self.tabWidgetInterface) self.change_color_Button.setStyleSheet("background-color : #FFAA00") self.change_color_Button.setText("") self.change_color_Button.setObjectName("change_color_Button") self.gridLayout_172.addWidget(self.change_color_Button, 0, 1, 1, 1) self.label_22 = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_22.sizePolicy().hasHeightForWidth()) self.label_22.setSizePolicy(sizePolicy) self.label_22.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_22.setObjectName("label_22") self.gridLayout_172.addWidget(self.label_22, 0, 0, 1, 1) self.transparency_Label = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.transparency_Label.sizePolicy().hasHeightForWidth()) self.transparency_Label.setSizePolicy(sizePolicy) self.transparency_Label.setMinimumSize(QtCore.QSize(100, 0)) self.transparency_Label.setFrameShadow(QtWidgets.QFrame.Sunken) self.transparency_Label.setObjectName("transparency_Label") self.gridLayout_172.addWidget(self.transparency_Label, 0, 2, 1, 1) self.transparency_Slider = QtWidgets.QSlider(self.tabWidgetInterface) self.transparency_Slider.setMaximum(100) self.transparency_Slider.setSingleStep(10) self.transparency_Slider.setProperty("value", 50) self.transparency_Slider.setOrientation(QtCore.Qt.Horizontal) self.transparency_Slider.setTickPosition(QtWidgets.QSlider.TicksBelow) self.transparency_Slider.setTickInterval(10) self.transparency_Slider.setObjectName("transparency_Slider") self.gridLayout_172.addWidget(self.transparency_Slider, 0, 3, 1, 1) self.gridLayout_21.addLayout(self.gridLayout_172, 2, 1, 1, 1) self.reset_color_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_color_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_color_Button.setIcon(icon59) self.reset_color_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_color_Button.setObjectName("reset_color_Button") self.gridLayout_21.addWidget(self.reset_color_Button, 2, 2, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_21, 1, 0, 1, 1) self.gridLayout_84 = QtWidgets.QGridLayout() self.gridLayout_84.setObjectName("gridLayout_84") self.label_68 = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_68.sizePolicy().hasHeightForWidth()) self.label_68.setSizePolicy(sizePolicy) self.label_68.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_68.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_68.setObjectName("label_68") self.gridLayout_84.addWidget(self.label_68, 1, 0, 1, 1) self.variable_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.variable_name_lineEdit.sizePolicy().hasHeightForWidth()) self.variable_name_lineEdit.setSizePolicy(sizePolicy) self.variable_name_lineEdit.setMaxLength(20) self.variable_name_lineEdit.setObjectName("variable_name_lineEdit") self.gridLayout_84.addWidget(self.variable_name_lineEdit, 1, 1, 1, 1) self.label_69 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_69.setStyleSheet("background-color : #656565; color : white") self.label_69.setFrameShape(QtWidgets.QFrame.Panel) self.label_69.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_69.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_69.setObjectName("label_69") self.gridLayout_84.addWidget(self.label_69, 0, 0, 1, 3) self.reset_variable_name_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_variable_name_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_variable_name_Button.setIcon(icon59) self.reset_variable_name_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_variable_name_Button.setObjectName("reset_variable_name_Button") self.gridLayout_84.addWidget(self.reset_variable_name_Button, 1, 2, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_84, 2, 0, 1, 1) self.gridLayout_17 = QtWidgets.QGridLayout() self.gridLayout_17.setObjectName("gridLayout_17") self.label_95 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_95.setStyleSheet("background-color : #656565; color : white") self.label_95.setFrameShape(QtWidgets.QFrame.Panel) self.label_95.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_95.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_95.setObjectName("label_95") self.gridLayout_17.addWidget(self.label_95, 0, 0, 1, 1) spacerItem154 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_17.addItem(spacerItem154, 2, 0, 1, 1) self.download_news_checkBox = QtWidgets.QCheckBox(self.tabWidgetInterface) self.download_news_checkBox.setChecked(True) self.download_news_checkBox.setObjectName("download_news_checkBox") self.gridLayout_17.addWidget(self.download_news_checkBox, 1, 0, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_17, 4, 0, 1, 1) self.gridLayout_99 = QtWidgets.QGridLayout() self.gridLayout_99.setObjectName("gridLayout_99") self.label_76 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_76.setStyleSheet("background-color : #656565; color : white") self.label_76.setFrameShape(QtWidgets.QFrame.Panel) self.label_76.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_76.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_76.setObjectName("label_76") self.gridLayout_99.addWidget(self.label_76, 0, 0, 1, 3) self.reset_group_name_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_group_name_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_group_name_Button.setIcon(icon59) self.reset_group_name_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_group_name_Button.setObjectName("reset_group_name_Button") self.gridLayout_99.addWidget(self.reset_group_name_Button, 1, 2, 1, 1) self.virtual_raster_load_checkBox = QtWidgets.QCheckBox(self.tabWidgetInterface) self.virtual_raster_load_checkBox.setObjectName("virtual_raster_load_checkBox") self.gridLayout_99.addWidget(self.virtual_raster_load_checkBox, 2, 0, 1, 1) self.horizontalLayout_61 = QtWidgets.QHBoxLayout() self.horizontalLayout_61.setObjectName("horizontalLayout_61") self.label_75 = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_75.sizePolicy().hasHeightForWidth()) self.label_75.setSizePolicy(sizePolicy) self.label_75.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_75.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_75.setObjectName("label_75") self.horizontalLayout_61.addWidget(self.label_75) self.group_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.group_name_lineEdit.sizePolicy().hasHeightForWidth()) self.group_name_lineEdit.setSizePolicy(sizePolicy) self.group_name_lineEdit.setMaxLength(20) self.group_name_lineEdit.setObjectName("group_name_lineEdit") self.horizontalLayout_61.addWidget(self.group_name_lineEdit) self.gridLayout_99.addLayout(self.horizontalLayout_61, 1, 0, 1, 2) self.gridLayout_63.addLayout(self.gridLayout_99, 3, 0, 1, 1) self.settings_tabWidget.addTab(self.tabWidgetInterface, "") self.tabWidgetDebug = QtWidgets.QWidget() self.tabWidgetDebug.setObjectName("tabWidgetDebug") self.gridLayout_56 = QtWidgets.QGridLayout(self.tabWidgetDebug) self.gridLayout_56.setObjectName("gridLayout_56") self.gridLayout_7 = QtWidgets.QGridLayout() self.gridLayout_7.setObjectName("gridLayout_7") self.log_checkBox = QtWidgets.QCheckBox(self.tabWidgetDebug) self.log_checkBox.setChecked(False) self.log_checkBox.setTristate(False) self.log_checkBox.setObjectName("log_checkBox") self.gridLayout_7.addWidget(self.log_checkBox, 1, 0, 1, 1) self.exportLog_Button = QtWidgets.QToolButton(self.tabWidgetDebug) self.exportLog_Button.setStyleSheet("margin: 0px;padding: 0px;") self.exportLog_Button.setIcon(icon53) self.exportLog_Button.setIconSize(QtCore.QSize(22, 22)) self.exportLog_Button.setObjectName("exportLog_Button") self.gridLayout_7.addWidget(self.exportLog_Button, 1, 1, 1, 1) self.clearLog_Button = QtWidgets.QToolButton(self.tabWidgetDebug) self.clearLog_Button.setStyleSheet("margin: 0px;padding: 0px;") self.clearLog_Button.setIcon(icon59) self.clearLog_Button.setIconSize(QtCore.QSize(22, 22)) self.clearLog_Button.setObjectName("clearLog_Button") self.gridLayout_7.addWidget(self.clearLog_Button, 1, 2, 1, 1) self.label_30 = QtWidgets.QLabel(self.tabWidgetDebug) self.label_30.setStyleSheet("background-color : #656565; color : white") self.label_30.setFrameShape(QtWidgets.QFrame.Panel) self.label_30.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_30.setObjectName("label_30") self.gridLayout_7.addWidget(self.label_30, 0, 0, 1, 3) self.log_tableWidget = QtWidgets.QTableWidget(self.tabWidgetDebug) self.log_tableWidget.setObjectName("log_tableWidget") self.log_tableWidget.setColumnCount(3) self.log_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.log_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.log_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.log_tableWidget.setHorizontalHeaderItem(2, item) self.log_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_7.addWidget(self.log_tableWidget, 2, 0, 1, 3) self.gridLayout_56.addLayout(self.gridLayout_7, 0, 0, 1, 1) self.gridLayout_55 = QtWidgets.QGridLayout() self.gridLayout_55.setObjectName("gridLayout_55") self.test_dependencies_Button = QtWidgets.QToolButton(self.tabWidgetDebug) self.test_dependencies_Button.setStyleSheet("margin: 0px;padding: 0px;") self.test_dependencies_Button.setIcon(icon67) self.test_dependencies_Button.setIconSize(QtCore.QSize(22, 22)) self.test_dependencies_Button.setObjectName("test_dependencies_Button") self.gridLayout_55.addWidget(self.test_dependencies_Button, 2, 2, 1, 1) self.label_42 = QtWidgets.QLabel(self.tabWidgetDebug) self.label_42.setAlignment(QtCore.Qt.AlignLeading\|QtCore.Qt.AlignLeft\|QtCore.Qt.AlignVCenter) self.label_42.setObjectName("label_42") self.gridLayout_55.addWidget(self.label_42, 2, 1, 1, 1) spacerItem155 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_55.addItem(spacerItem155, 2, 3, 1, 1) self.label_43 = QtWidgets.QLabel(self.tabWidgetDebug) self.label_43.setStyleSheet("background-color : #656565; color : white") self.label_43.setFrameShape(QtWidgets.QFrame.Panel) self.label_43.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_43.setObjectName("label_43") self.gridLayout_55.addWidget(self.label_43, 0, 0, 1, 4) self.gridLayout_56.addLayout(self.gridLayout_55, 1, 0, 1, 1) self.settings_tabWidget.addTab(self.tabWidgetDebug, "") self.gridLayout_134.addWidget(self.settings_tabWidget, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_Settings, "") self.tab_About = QtWidgets.QWidget() sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.tab_About.sizePolicy().hasHeightForWidth()) self.tab_About.setSizePolicy(sizePolicy) self.tab_About.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates)) self.tab_About.setObjectName("tab_About") self.gridLayout_16 = QtWidgets.QGridLayout(self.tab_About) self.gridLayout_16.setObjectName("gridLayout_16") self.gridLayout_5 = QtWidgets.QGridLayout() self.gridLayout_5.setObjectName("gridLayout_5") self.plugin_version_label = QtWidgets.QLabel(self.tab_About) self.plugin_version_label.setFrameShape(QtWidgets.QFrame.NoFrame) self.plugin_version_label.setFrameShadow(QtWidgets.QFrame.Raised) self.plugin_version_label.setText("") self.plugin_version_label.setTextFormat(QtCore.Qt.PlainText) self.plugin_version_label.setAlignment(QtCore.Qt.AlignCenter) self.plugin_version_label.setObjectName("plugin_version_label") self.gridLayout_5.addWidget(self.plugin_version_label, 1, 0, 1, 1) self.plugin_label = QtWidgets.QLabel(self.tab_About) self.plugin_label.setFrameShape(QtWidgets.QFrame.NoFrame) self.plugin_label.setFrameShadow(QtWidgets.QFrame.Raised) self.plugin_label.setTextFormat(QtCore.Qt.PlainText) self.plugin_label.setAlignment(QtCore.Qt.AlignCenter) self.plugin_label.setObjectName("plugin_label") self.gridLayout_5.addWidget(self.plugin_label, 0, 0, 1, 1) self.gridLayout_16.addLayout(self.gridLayout_5, 0, 0, 1, 1) self.gridLayout_9 = QtWidgets.QGridLayout() self.gridLayout_9.setObjectName("gridLayout_9") self.textBrowser = QtWidgets.QTextBrowser(self.tab_About) self.textBrowser.setFrameShape(QtWidgets.QFrame.Panel) self.textBrowser.setFrameShadow(QtWidgets.QFrame.Sunken) self.textBrowser.setOpenExternalLinks(True) self.textBrowser.setObjectName("textBrowser") self.gridLayout_9.addWidget(self.textBrowser, 0, 0, 1, 1) self.gridLayout_16.addLayout(self.gridLayout_9, 1, 0, 1, 1) self.SCP_tabs.addTab(self.tab_About, "") self.gridLayout_262.addWidget(self.SCP_tabs, 0, 0, 1, 1) self.main_tabWidget.addTab(self.tool_tab, icon, "") self.help_tab = QtWidgets.QWidget() self.help_tab.setObjectName("help_tab") self.gridLayout_263 = QtWidgets.QGridLayout(self.help_tab) self.gridLayout_263.setObjectName("gridLayout_263") self.help_textBrowser = QtWidgets.QTextBrowser(self.help_tab) self.help_textBrowser.setOpenExternalLinks(True) self.help_textBrowser.setOpenLinks(False) self.help_textBrowser.setObjectName("help_textBrowser") self.gridLayout_263.addWidget(self.help_textBrowser, 1, 0, 1, 1) self.main_tabWidget.addTab(self.help_tab, icon51, "") self.gridLayout_301.addWidget(self.splitter, 0, 0, 1, 1) self.retranslateUi(SemiAutomaticClassificationPlugin) self.main_tabWidget.setCurrentIndex(0) self.SCP_tabs.setCurrentIndex(0) self.Band_set_tabWidget.setCurrentIndex(-1) self.tabWidget_5.setCurrentIndex(0) self.alg_band_weight_tabWidget.setCurrentIndex(-1) self.toolBox_4.setCurrentIndex(2) self.tabWidget_3.setCurrentIndex(1) self.tabWidget_preprocessing.setCurrentIndex(0) self.tabWidget_4.setCurrentIndex(0) self.toolBox_band_set_combination.setCurrentIndex(0) self.toolBox_PCA.setCurrentIndex(0) self.toolBox_kmeans.setCurrentIndex(0) self.toolBox_random_forest.setCurrentIndex(0) self.tabWidget_2.setCurrentIndex(0) self.toolBox_accuracy.setCurrentIndex(0) self.toolBox_landCoverChange.setCurrentIndex(0) self.toolBox_class_report.setCurrentIndex(0) self.toolBox_cross_classification.setCurrentIndex(0) self.toolBox_class_signature.setCurrentIndex(0) self.band_calc_tabWidget.setCurrentIndex(0) self.settings_tabWidget.setCurrentIndex(0) QtCore.QMetaObject.connectSlotsByName(SemiAutomaticClassificationPlugin) def retranslateUi(self, SemiAutomaticClassificationPlugin): _translate = QtCore.QCoreApplication.translate SemiAutomaticClassificationPlugin.setWindowTitle(_translate("SemiAutomaticClassificationPlugin", "Semi-Automatic Classification Plugin")) self.f_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) __sortingEnabled = self.menu_treeWidget.isSortingEnabled() self.menu_treeWidget.setSortingEnabled(False) self.menu_treeWidget.topLevelItem(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band set")) self.menu_treeWidget.topLevelItem(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Basic tools")) self.menu_treeWidget.topLevelItem(1).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Algorithm band weight")) self.menu_treeWidget.topLevelItem(1).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band set list")) self.menu_treeWidget.topLevelItem(1).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Export signatures")) self.menu_treeWidget.topLevelItem(1).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "Import signatures")) self.menu_treeWidget.topLevelItem(1).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "LCS threshold")) self.menu_treeWidget.topLevelItem(1).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Multiple ROI creation")) self.menu_treeWidget.topLevelItem(1).child(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "RGB list")) self.menu_treeWidget.topLevelItem(1).child(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Signature threshold")) self.menu_treeWidget.topLevelItem(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Download products")) self.menu_treeWidget.topLevelItem(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "Preprocessing")) self.menu_treeWidget.topLevelItem(3).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "ASTER")) self.menu_treeWidget.topLevelItem(3).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "GOES")) self.menu_treeWidget.topLevelItem(3).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Landsat")) self.menu_treeWidget.topLevelItem(3).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "MODIS")) self.menu_treeWidget.topLevelItem(3).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Sentinel-1")) self.menu_treeWidget.topLevelItem(3).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Sentinel-2")) self.menu_treeWidget.topLevelItem(3).child(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "Sentinel-3")) self.menu_treeWidget.topLevelItem(3).child(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Clip multiple rasters")) self.menu_treeWidget.topLevelItem(3).child(8).setText(0, _translate("SemiAutomaticClassificationPlugin", "Cloud masking")) self.menu_treeWidget.topLevelItem(3).child(9).setText(0, _translate("SemiAutomaticClassificationPlugin", "Mosaic band sets")) self.menu_treeWidget.topLevelItem(3).child(10).setText(0, _translate("SemiAutomaticClassificationPlugin", "Neighbor pixels")) self.menu_treeWidget.topLevelItem(3).child(11).setText(0, _translate("SemiAutomaticClassificationPlugin", "Reproject raster bands")) self.menu_treeWidget.topLevelItem(3).child(12).setText(0, _translate("SemiAutomaticClassificationPlugin", "Split raster bands")) self.menu_treeWidget.topLevelItem(3).child(13).setText(0, _translate("SemiAutomaticClassificationPlugin", "Stack raster bands")) self.menu_treeWidget.topLevelItem(3).child(14).setText(0, _translate("SemiAutomaticClassificationPlugin", "Vector to raster")) self.menu_treeWidget.topLevelItem(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band processing")) self.menu_treeWidget.topLevelItem(4).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band combination")) self.menu_treeWidget.topLevelItem(4).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification")) self.menu_treeWidget.topLevelItem(4).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Clustering")) self.menu_treeWidget.topLevelItem(4).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "PCA")) self.menu_treeWidget.topLevelItem(4).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Random forest")) self.menu_treeWidget.topLevelItem(4).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Spectral distance")) self.menu_treeWidget.topLevelItem(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Postprocessing")) self.menu_treeWidget.topLevelItem(5).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Accuracy")) self.menu_treeWidget.topLevelItem(5).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification dilation")) self.menu_treeWidget.topLevelItem(5).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification erosion")) self.menu_treeWidget.topLevelItem(5).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification report")) self.menu_treeWidget.topLevelItem(5).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification to vector")) self.menu_treeWidget.topLevelItem(5).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification sieve")) self.menu_treeWidget.topLevelItem(5).child(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "Class signature")) self.menu_treeWidget.topLevelItem(5).child(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Cross classification")) self.menu_treeWidget.topLevelItem(5).child(8).setText(0, _translate("SemiAutomaticClassificationPlugin", "Edit raster")) self.menu_treeWidget.topLevelItem(5).child(9).setText(0, _translate("SemiAutomaticClassificationPlugin", "Land cover change")) self.menu_treeWidget.topLevelItem(5).child(10).setText(0, _translate("SemiAutomaticClassificationPlugin", "Reclassification")) self.menu_treeWidget.topLevelItem(5).child(11).setText(0, _translate("SemiAutomaticClassificationPlugin", "Zonal stat raster")) self.menu_treeWidget.topLevelItem(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band calc")) self.menu_treeWidget.topLevelItem(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Batch")) self.menu_treeWidget.topLevelItem(8).setText(0, _translate("SemiAutomaticClassificationPlugin", "Settings")) self.menu_treeWidget.topLevelItem(8).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Debug")) self.menu_treeWidget.topLevelItem(8).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Interface")) self.menu_treeWidget.topLevelItem(8).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Processing setting")) self.menu_treeWidget.topLevelItem(9).setText(0, _translate("SemiAutomaticClassificationPlugin", "User manual")) self.menu_treeWidget.topLevelItem(10).setText(0, _translate("SemiAutomaticClassificationPlugin", "Help")) self.menu_treeWidget.topLevelItem(11).setText(0, _translate("SemiAutomaticClassificationPlugin", "About")) self.menu_treeWidget.topLevelItem(12).setText(0, _translate("SemiAutomaticClassificationPlugin", "Support the SCP")) self.menu_treeWidget.setSortingEnabled(__sortingEnabled) self.label_59.setText(_translate("SemiAutomaticClassificationPlugin", "Wavelength\n" "quick settings")) self.wavelength_sat_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a configuration for setting band center wavelengths</p></body></html>")) self.label_60.setText(_translate("SemiAutomaticClassificationPlugin", "Wavelength \n" "unit")) self.unit_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Wavelength unit</p></body></html>")) self.export_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export band set to text file</p></body></html>")) self.export_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import band set from text file</p></body></html>")) self.import_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.bandset_dateEdit.setDisplayFormat(_translate("SemiAutomaticClassificationPlugin", "yyyy-MM-dd")) self.label_3.setText(_translate("SemiAutomaticClassificationPlugin", "Date")) self.label_52.setText(_translate("SemiAutomaticClassificationPlugin", " Single band list")) self.bands_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Filter</p></body></html>")) self.bands_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) item = self.bands_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) self.toolButton_reload_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_3.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.select_all_bands_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select all / Unselect all</p></body></html>")) self.select_all_bands_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.add_raster_bands_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Add band to Band set</p></body></html>")) self.add_raster_bands_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_53.setText(_translate("SemiAutomaticClassificationPlugin", " Band set definition")) self.remove_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.clear_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.sort_by_name_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Sort bands by name (priority to ending number)</p></body></html>")) self.sort_by_name_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_up_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted band up</p></body></html>")) self.move_up_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_down_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted band down</p></body></html>")) self.move_down_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_band_set_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Add a new band set</p></body></html>")) self.add_band_set_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.virtual_raster_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a virtual raster of active band set</p></body></html>")) self.virtual_raster_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create virtual raster of band set")) self.band_calc_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Calculate expression in Band calc</p></body></html>")) self.band_calc_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Band calc expressions")) self.stack_raster_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a .tif raster stacking the bands of the active band set</p></body></html>")) self.stack_raster_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create raster of band set \n" "(stack bands)")) self.overview_raster_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Build band overviews (external pyramids) of active band set for faster visualization</p></body></html>")) self.overview_raster_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Build band overviews")) self.label_94.setText(_translate("SemiAutomaticClassificationPlugin", " Band set tools")) self.band_set_process_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.band_set_process_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.toolButton_reload.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_39.setText(_translate("SemiAutomaticClassificationPlugin", " Multiband image list")) self.toolButton_input_raster.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.image_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a multiband image</p></body></html>")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_band_set), _translate("SemiAutomaticClassificationPlugin", "Band set")) self.label_126.setText(_translate("SemiAutomaticClassificationPlugin", "RGB list")) self.sort_by_name_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Sort RGB automatically</p></body></html>")) self.sort_by_name_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_down_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted RGB down</p></body></html>")) self.move_down_toolButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_up_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted RGB up</p></body></html>")) self.move_up_toolButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_RGB_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add row</p></body></html>")) self.add_RGB_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_RGB_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export RGB list to text file</p></body></html>")) self.export_RGB_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_RGB_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import RGB list from text file</p></body></html>")) self.import_RGB_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_RGB_list_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.clear_RGB_list_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.remove_RGB_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_RGB_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) item = self.RGB_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "RGB")) self.label_196.setText(_translate("SemiAutomaticClassificationPlugin", "Automatic RGB")) self.label_192.setText(_translate("SemiAutomaticClassificationPlugin", "Band combinations")) self.all_RGB_list_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Add all combinations of bands</p></body></html>")) self.all_RGB_list_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_RGB), _translate("SemiAutomaticClassificationPlugin", "RGB list")) self.label_208.setText(_translate("SemiAutomaticClassificationPlugin", "Band set list")) self.band_set_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Filter</p></body></html>")) self.band_set_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) item = self.band_set_list_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Number")) item = self.band_set_list_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Bands")) item = self.band_set_list_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "Date")) self.move_down_toolButton_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted Band sets down</p></body></html>")) self.move_down_toolButton_4.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_up_toolButton_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted Band sets up</p></body></html>")) self.move_up_toolButton_4.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.rgb_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add row</p></body></html>")) self.rgb_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.add_bandset_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add row</p></body></html>")) self.add_bandset_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_bandset_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export Band set list to file</p></body></html>")) self.export_bandset_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_bandset_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import Band set list from file</p></body></html>")) self.import_bandset_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.remove_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.sort_by_date.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Sort band sets by date</p></body></html>")) self.sort_by_date.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_band_set_list), _translate("SemiAutomaticClassificationPlugin", "Band set list")) self.label_79.setText(_translate("SemiAutomaticClassificationPlugin", "Algorithm band weight")) self.reset_weights_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Reset</p></body></html>\n" "")) self.set_weight_value_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Set</p></body></html>\n" "")) self.label_131.setText(_translate("SemiAutomaticClassificationPlugin", "Set weight")) self.weight_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set a value</p></body></html>")) self.label_93.setText(_translate("SemiAutomaticClassificationPlugin", "Automatic weight")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_algorithm_weight), _translate("SemiAutomaticClassificationPlugin", "Algorithm band weight")) self.point_distance_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p align=\"justify\">Minimum distance between points</p></body></html>")) self.point_grid_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p align=\"justify\">Size of a grid cell within points are created randomly</p></body></html>")) self.label_48.setText(_translate("SemiAutomaticClassificationPlugin", " Create random points")) self.label_139.setText(_translate("SemiAutomaticClassificationPlugin", "Create points")) self.label_19.setText(_translate("SemiAutomaticClassificationPlugin", "Number of points")) self.point_number_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p align=\"justify\">Number of points created randomly</p></body></html>")) self.add_random_point_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create points</p></body></html>")) self.point_distance_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create random points with a minimum distance</p></body></html>")) self.point_distance_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "min distance")) self.point_grid_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create random points inside each cell of a grid with this size</p></body></html>")) self.point_grid_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "inside grid")) self.stratified_point_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create stratified random points</p></body></html>")) self.stratified_point_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "stratified for the values")) self.stratified_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter one or more rules separated by semicolon (e.g. raster > 0; raster == 1 )</p></body></html>")) self.stratified_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "raster > 0")) self.band_set_comb_spinBox_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_25.setText(_translate("SemiAutomaticClassificationPlugin", "of first band of band set")) self.label_47.setText(_translate("SemiAutomaticClassificationPlugin", " Point coordinates and ROI definition")) self.point_tableWidget.setSortingEnabled(False) item = self.point_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "X")) item = self.point_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Y")) item = self.point_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) item = self.point_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name")) item = self.point_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) item = self.point_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "C Name")) item = self.point_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "Min")) item = self.point_tableWidget.horizontalHeaderItem(7) item.setText(_translate("SemiAutomaticClassificationPlugin", "Max")) item = self.point_tableWidget.horizontalHeaderItem(8) item.setText(_translate("SemiAutomaticClassificationPlugin", "Dist")) item = self.point_tableWidget.horizontalHeaderItem(9) item.setText(_translate("SemiAutomaticClassificationPlugin", "Rapid ROI band")) self.add_point_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add row</p></body></html>")) self.add_point_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.remove_point_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_point_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_point_list_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Export point list to text file</p></body></html>")) self.export_point_list_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_point_list_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Import point list from text file</p></body></html>")) self.import_point_list_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.signature_checkBox2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Add ROI spectral signatures to signature list</p></body></html>")) self.signature_checkBox2.setText(_translate("SemiAutomaticClassificationPlugin", "Calculate sig.")) self.label_159.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.save_point_rois_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.save_point_rois_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_multiple_ROI), _translate("SemiAutomaticClassificationPlugin", "Multiple ROI creation")) self.usgs_chapter_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a chapter</p></body></html>")) self.usgs_library_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a library</p></body></html>")) self.label_123.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a chapter</p></body></html>")) self.label_124.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a library</p></body></html>")) self.label_130.setText(_translate("SemiAutomaticClassificationPlugin", "Import spectral library")) self.add_usgs_library_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import spectral library</p></body></html>")) self.USGS_library_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Sans\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" "<p style=\"-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-family:\'Droid Sans\'; font-size:9pt;\"><br /></p></body></html>")) self.label.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>USGS Spectral Library Version 7 downloaded from <a href=\"https://crustal.usgs.gov/speclab/QueryAll07a.php\"><span style=\" text-decoration: underline; color:#0000ff;\">https://crustal.usgs.gov/speclab/QueryAll07a.php</span></a>.<br/><span style=\" font-weight:600;\">Reference</span>: Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L., and Klein, A.J., 2017, USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p., https://doi.org/10.3133/ds1035.</p></body></html>")) self.label_129.setText(_translate("SemiAutomaticClassificationPlugin", " Library Description (requires internet connection)")) self.toolBox_4.setItemText(self.toolBox_4.indexOf(self.page_8), _translate("SemiAutomaticClassificationPlugin", "Download USGS Spectral Library")) self.label_9.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a file: SCP file (.scp) ; USGS library (.asc) ; ASTER library (.txt) ; CSV (.csv)</p></body></html>")) self.open_library_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.toolBox_4.setItemText(self.toolBox_4.indexOf(self.page_6), _translate("SemiAutomaticClassificationPlugin", "Import library file")) self.open_shapefile_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open a file</p></body></html>")) self.label_120.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a vector (.shp;.gpkg)</p></body></html>")) self.C_ID_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>C ID field</p></body></html>")) self.MC_ID_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>MC ID field</p></body></html>")) self.MC_Info_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>MC Name field</p></body></html>")) self.label_99.setText(_translate("SemiAutomaticClassificationPlugin", "C Name field")) self.C_Info_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>C Name field</p></body></html>")) self.label_119.setText(_translate("SemiAutomaticClassificationPlugin", " Vector fields")) self.MC_ID_combo_2.setText(_translate("SemiAutomaticClassificationPlugin", "C ID field")) self.label_121.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID field")) self.label_122.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name field")) self.label_2.setText(_translate("SemiAutomaticClassificationPlugin", " Import vector")) self.signature_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Add ROI spectral signature to signature list</p></body></html>")) self.signature_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Calculate sig.")) self.import_shapefile_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import vector</p></body></html>")) self.import_shapefile_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.toolBox_4.setItemText(self.toolBox_4.indexOf(self.page_9), _translate("SemiAutomaticClassificationPlugin", "Import vector")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_Import), _translate("SemiAutomaticClassificationPlugin", "Import signatures")) self.label_97.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export as SCP file (.scp)</p></body></html>")) self.export_SCP_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Export highlighted spectral signatures</p></body></html>\n" "")) self.export_CSV_library_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a directory where highlighted spectral signatures are saved as .csv</p></body></html>")) self.export_CSV_library_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_96.setText(_translate("SemiAutomaticClassificationPlugin", "Export ")) self.label_222.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export as shapefile (.shp) or geopackage (.gpkg)</p></body></html>")) self.label_20.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export as CSV file (.csv)</p></body></html>")) self.export_SHP_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Export highlighted spectral signatures</p></body></html>\n" "")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_export), _translate("SemiAutomaticClassificationPlugin", "Export signatures")) self.reset_threshold_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Reset</p></body></html>\n" "")) self.signature_threshold_tableWidget.setSortingEnabled(True) item = self.signature_threshold_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "C Name")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "MD Threshold")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "ML Threshold")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "SAM Threshold")) self.label_80.setText(_translate("SemiAutomaticClassificationPlugin", " Signature threshold")) self.label_85.setText(_translate("SemiAutomaticClassificationPlugin", "Set threshold = σ ")) self.multiplicative_threshold_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set a value that will be multiplied by standard deviation</p></body></html>")) self.automatic_threshold_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set automatic threshold σ</p></body></html>")) self.label_132.setText(_translate("SemiAutomaticClassificationPlugin", "Set threshold")) self.threshold_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set a value</p></body></html>")) self.set_threshold_value_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Set</p></body></html>\n" "")) self.label_88.setText(_translate("SemiAutomaticClassificationPlugin", " Automatic thresholds")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_threshold), _translate("SemiAutomaticClassificationPlugin", "Signature threshold")) self.LCS_tableWidget.setSortingEnabled(True) item = self.LCS_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) item = self.LCS_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name")) item = self.LCS_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) item = self.LCS_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "C Name")) item = self.LCS_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "Color [overlap MC_ID-C_ID]")) self.label_86.setText(_translate("SemiAutomaticClassificationPlugin", " LC Signature threshold")) self.signature_spectral_plot_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add highlighted signatures to spectral signature plot</p></body></html>")) self.signature_spectral_plot_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_102.setText(_translate("SemiAutomaticClassificationPlugin", "Min Max")) self.set_min_max_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set automatic threshold Min Max</p></body></html>")) self.label_101.setText(_translate("SemiAutomaticClassificationPlugin", "σ ")) self.multiplicative_threshold_doubleSpinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set a value that will be multiplied by standard deviation</p></body></html>")) self.automatic_threshold_pushButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set automatic threshold σ</p></body></html>")) self.label_89.setText(_translate("SemiAutomaticClassificationPlugin", "From pixel")) self.LCS_pointerButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Activate pointer for setting thresholds from pixel</p></body></html>")) self.LCS_include_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, signature threshold is extended to include pixel signature</p></body></html>")) self.LCS_cut_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, signature threshold is reduced to exclude pixel signature</p></body></html>")) self.label_178.setText(_translate("SemiAutomaticClassificationPlugin", "From ROI")) self.LCS_ROI_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set thresholds from temporary ROI</p></body></html>")) self.label_125.setText(_translate("SemiAutomaticClassificationPlugin", "Automatic thresholds")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_LCS_threshold), _translate("SemiAutomaticClassificationPlugin", "LCS threshold")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_basic_tools), _translate("SemiAutomaticClassificationPlugin", "Basic tools")) self.remember_user_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, remember user name and password locally in QGIS</p></body></html>")) self.remember_user_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.password_usgs_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Password</p></body></html>")) self.password_scihub_label_3.setText(_translate("SemiAutomaticClassificationPlugin", "Password")) self.label_180.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Login Landsat (<a href=\"https://ers.cr.usgs.gov\"><span style=\" text-decoration: underline; color:#ffffff;\">https://ers.cr.usgs.gov</span></a>)</p></body></html>")) self.user_usgs_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>User name</p></body></html>")) self.user_scihub_label_2.setText(_translate("SemiAutomaticClassificationPlugin", "User")) self.remember_user_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, remember user name and password locally in QGIS</p></body></html>")) self.remember_user_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.password_usgs_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Password</p></body></html>")) self.password_scihub_label_4.setText(_translate("SemiAutomaticClassificationPlugin", "Password")) self.label_191.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Login ASTER and MODIS (<a href=\"https://urs.earthdata.nasa.gov\"><span style=\" text-decoration: underline; color:#ffffff;\">https://urs.earthdata.nasa.gov</span></a>)</p></body></html>")) self.user_usgs_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>User name</p></body></html>")) self.user_scihub_label_3.setText(_translate("SemiAutomaticClassificationPlugin", "User")) self.user_scihub_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>User name</p></body></html>")) self.password_scihub_label.setText(_translate("SemiAutomaticClassificationPlugin", "Password")) self.label_147.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Login Sentinels</p></body></html>")) self.remember_user_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, remember user name and password locally in QGIS</p></body></html>")) self.remember_user_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.user_scihub_label.setText(_translate("SemiAutomaticClassificationPlugin", "User")) self.password_scihub_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Password</p></body></html>")) self.password_scihub_label_2.setText(_translate("SemiAutomaticClassificationPlugin", "Service")) self.sentinel_service_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Service</p></body></html>")) self.reset_sentinel_service_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.reset_sentinel_service_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.sentinel2_alternative_search_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use alternative search for Sentinel-2 (no authentication required)</p></body></html>")) self.sentinel2_alternative_search_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use alternative search for Sentinel-2 (no authentication required)")) self.tabWidget_3.setTabText(self.tabWidget_3.indexOf(self.tab_login), _translate("SemiAutomaticClassificationPlugin", "Login data")) self.remove_image_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_image_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.toolButton_display.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Display preview of highlighted images in map</p></body></html>")) self.toolButton_display.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_table_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.clear_table_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.export_table_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export table to text file</p></body></html>")) self.export_table_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_table_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import table from text file</p></body></html>")) self.import_table_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.image_preview_label.setText(_translate("SemiAutomaticClassificationPlugin", "Preview")) self.download_images_tableWidget.setSortingEnabled(True) item = self.download_images_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Product")) item = self.download_images_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "ProductID")) item = self.download_images_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "AcquisitionDate")) item = self.download_images_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "CloudCover")) item = self.download_images_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "Zone/Path")) item = self.download_images_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "Row/DayNight")) item = self.download_images_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "min_lat")) item = self.download_images_tableWidget.horizontalHeaderItem(7) item.setText(_translate("SemiAutomaticClassificationPlugin", "min_lon")) item = self.download_images_tableWidget.horizontalHeaderItem(8) item.setText(_translate("SemiAutomaticClassificationPlugin", "max_lat")) item = self.download_images_tableWidget.horizontalHeaderItem(9) item.setText(_translate("SemiAutomaticClassificationPlugin", "max_lon")) item = self.download_images_tableWidget.horizontalHeaderItem(10) item.setText(_translate("SemiAutomaticClassificationPlugin", "Collection/Size")) item = self.download_images_tableWidget.horizontalHeaderItem(11) item.setText(_translate("SemiAutomaticClassificationPlugin", "Preview")) item = self.download_images_tableWidget.horizontalHeaderItem(12) item.setText(_translate("SemiAutomaticClassificationPlugin", "Collection/ID")) item = self.download_images_tableWidget.horizontalHeaderItem(13) item.setText(_translate("SemiAutomaticClassificationPlugin", "Collection/Image")) self.label_100.setText(_translate("SemiAutomaticClassificationPlugin", " Product list")) self.products_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Filter</p></body></html>")) self.products_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) self.toolButton_OSM.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Add OpenStreetMap to the map</p></body></html>")) self.toolButton_OSM.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_205.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span style=\" color:#000000;\">Add OpenStreetMap to the map</span></p></body></html>")) self.label_206.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>(© <a href=\"http://www.openstreetmap.org/copyright\"><span style=\" text-decoration: underline; color:#0000ff;\">OpenStreetMap</span></a> contributors. The cartography is licensed as CC BY-SA. <a href=\"https://operations.osmfoundation.org/policies/tiles/\"><span style=\" text-decoration: underline; color:#0000ff;\">Tile Usage Policy</span></a>)</p></body></html>")) self.label_103.setText(_translate("SemiAutomaticClassificationPlugin", " Search parameters")) self.selectUL_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set area in the map</p></body></html>")) self.LX_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Lower right X</p></body></html>")) self.LX_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X (Lon)")) self.UX_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Upper left X</p></body></html>")) self.UX_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X (Lon)")) self.label_105.setText(_translate("SemiAutomaticClassificationPlugin", "LR")) self.label_107.setText(_translate("SemiAutomaticClassificationPlugin", "UL")) self.LY_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Lower right Y</p></body></html>")) self.LY_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y (Lat)")) self.UY_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Upper left Y</p></body></html>")) self.UY_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y (Lat)")) self.show_area_radioButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Show / hide area</p></body></html>")) self.show_area_radioButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Show")) self.find_images_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Find images</p></body></html>")) self.label_35.setText(_translate("SemiAutomaticClassificationPlugin", "Find")) self.landsat_satellite_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a product</p></body></html>")) self.dateEdit_from.setDisplayFormat(_translate("SemiAutomaticClassificationPlugin", "yyyy-MM-dd")) self.label_110.setText(_translate("SemiAutomaticClassificationPlugin", "Max cloud cover (%)")) self.dateEdit_to.setDisplayFormat(_translate("SemiAutomaticClassificationPlugin", "yyyy-MM-dd")) self.label_112.setText(_translate("SemiAutomaticClassificationPlugin", "to")) self.label_111.setText(_translate("SemiAutomaticClassificationPlugin", "Date from")) self.cloud_cover_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Maximum cloud cover percentage</p></body></html>")) self.label_114.setText(_translate("SemiAutomaticClassificationPlugin", "Products")) self.label_194.setText(_translate("SemiAutomaticClassificationPlugin", "Results")) self.label_113.setText(_translate("SemiAutomaticClassificationPlugin", "Advanced search")) self.imageID_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Filter images</p></body></html>")) self.result_number_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Maximum number of results (images)</p></body></html>")) self.tabWidget_3.setTabText(self.tabWidget_3.indexOf(self.tab_search), _translate("SemiAutomaticClassificationPlugin", "Search")) self.checkBox_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6 (Landsat 1-8)")) self.checkBox_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4 (Landsat 1-8)")) self.checkBox_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1 (Landsat 4-8)")) self.checkBox_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3 (Landsat 4-8)")) self.checkBox_band_12.setText(_translate("SemiAutomaticClassificationPlugin", "Ancillary data")) self.checkBox_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2 (Landsat 4-8)")) self.checkBox_band_11.setText(_translate("SemiAutomaticClassificationPlugin", "11 (Landsat 8)")) self.checkBox_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5 (Landsat 1-8)")) self.check_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select all</p></body></html>")) self.check_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_108.setText(_translate("SemiAutomaticClassificationPlugin", " Landsat bands")) self.checkBoxs_band_9.setText(_translate("SemiAutomaticClassificationPlugin", "8A")) self.checkBoxs_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.check_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select all</p></body></html>")) self.check_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_118.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-2 bands")) self.checkBoxs_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2")) self.checkBoxs_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3")) self.checkBoxs_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4")) self.checkBoxs_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5")) self.checkBoxs_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6")) self.checkBoxs_band_7.setText(_translate("SemiAutomaticClassificationPlugin", "7")) self.checkBoxs_band_12.setText(_translate("SemiAutomaticClassificationPlugin", "11")) self.checkBoxs_band_8.setText(_translate("SemiAutomaticClassificationPlugin", "8")) self.checkBoxs_band_10.setText(_translate("SemiAutomaticClassificationPlugin", "9")) self.ancillary_data_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Ancillary data")) self.checkBoxs_band_13.setText(_translate("SemiAutomaticClassificationPlugin", "12")) self.checkBoxs_band_11.setText(_translate("SemiAutomaticClassificationPlugin", "10")) self.checkBoxs3_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6")) self.checkBoxs3_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2")) self.checkBoxs3_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5")) self.checkBoxs3_band_8.setText(_translate("SemiAutomaticClassificationPlugin", "8")) self.checkBoxs3_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.checkBoxs3_band_16.setText(_translate("SemiAutomaticClassificationPlugin", "16")) self.checkBoxs3_band_10.setText(_translate("SemiAutomaticClassificationPlugin", "10")) self.checkBoxs3_band_12.setText(_translate("SemiAutomaticClassificationPlugin", "12")) self.s3_ancillary_data_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Ancillary data")) self.checkBoxs3_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3")) self.label_127.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-3 bands")) self.checkBoxs3_band_20.setText(_translate("SemiAutomaticClassificationPlugin", "20")) self.checkBoxs3_band_17.setText(_translate("SemiAutomaticClassificationPlugin", "17")) self.checkBoxs3_band_14.setText(_translate("SemiAutomaticClassificationPlugin", "14")) self.checkBoxs3_band_9.setText(_translate("SemiAutomaticClassificationPlugin", "9")) self.checkBoxs3_band_13.setText(_translate("SemiAutomaticClassificationPlugin", "13")) self.checkBoxs3_band_19.setText(_translate("SemiAutomaticClassificationPlugin", "19")) self.check_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select all</p></body></html>")) self.check_toolButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.checkBoxs3_band_7.setText(_translate("SemiAutomaticClassificationPlugin", "7")) self.checkBoxs3_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4")) self.checkBoxs3_band_11.setText(_translate("SemiAutomaticClassificationPlugin", "11")) self.checkBoxs3_band_15.setText(_translate("SemiAutomaticClassificationPlugin", "15")) self.checkBoxs3_band_21.setText(_translate("SemiAutomaticClassificationPlugin", "21")) self.checkBoxs3_band_18.setText(_translate("SemiAutomaticClassificationPlugin", "18")) self.checkBoxs_goes_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.label_272.setText(_translate("SemiAutomaticClassificationPlugin", " GOES bands")) self.checkBoxs_goes_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5")) self.checkBoxs_goes_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3")) self.checkBoxs_goes_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4")) self.checkBoxs_goes_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2")) self.checkBoxs_goes_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6")) self.check_toolButton_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select all</p></body></html>")) self.check_toolButton_4.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.checkBox_band_8.setText(_translate("SemiAutomaticClassificationPlugin", "8 (Landsat 7, 8)")) self.checkBox_band_10.setText(_translate("SemiAutomaticClassificationPlugin", "10 (Landsat 8)")) self.checkBox_band_9.setText(_translate("SemiAutomaticClassificationPlugin", "9 (Landsat 8)")) self.checkBox_band_7.setText(_translate("SemiAutomaticClassificationPlugin", "7 (Landsat 1-8)")) self.tabWidget_3.setTabText(self.tabWidget_3.indexOf(self.tab_options), _translate("SemiAutomaticClassificationPlugin", "Download options")) self.label_258.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span style=\" color:#ffffff;\"> Download</span></p></body></html>")) self.preprocess_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Preprocess images</p></body></html>")) self.preprocess_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Preprocess images")) self.load_in_QGIS_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Load images in QGIS after download</p></body></html>")) self.load_in_QGIS_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Load bands in QGIS")) self.download_if_preview_in_legend_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Download images from list only if the corresponding previews are loaded in QGIS</p></body></html>")) self.download_if_preview_in_legend_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Only if preview in Layers")) self.export_links_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export download links to a text file</p></body></html>")) self.export_links_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.download_images_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.download_images_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.virtual_download_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, download as virtual file only the portion of the image defined by search coordinates (does not work for all the sources)</p></body></html>")) self.virtual_download_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Virtual download")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_download_products), _translate("SemiAutomaticClassificationPlugin", "Download products")) self.label_36.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing Landsat bands")) self.label_37.setText(_translate("SemiAutomaticClassificationPlugin", " Landsat conversion to TOA reflectance and brightness temperature")) self.celsius_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable calculation of temperature in Celsius from thermal band</p></body></html>")) self.celsius_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", " Brightness temperature in Celsius")) self.DOS1_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the DOS1 atmospheric correction (thermal band is not corrected)</p></body></html>")) self.DOS1_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.nodata_spinBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.nodata_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_41.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select MTL file (if not in Landsat directory)</p></body></html>")) self.label_41.setText(_translate("SemiAutomaticClassificationPlugin", "Select MTL file")) self.toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select a directory</p></body></html>")) self.toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.pansharpening_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Perform pan-sharpening (Brovey Transform)</p></body></html>")) self.pansharpening_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Perform pansharpening (Landsat 7 or 8)")) self.create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_1.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.toolButton_directoryInput_MTL.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.landsat_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit metadata</p></body></html>")) item = self.landsat_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.landsat_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "RADIANCE_MULT")) item = self.landsat_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "RADIANCE_ADD")) item = self.landsat_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "REFLECTANCE_MULT")) item = self.landsat_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "REFLECTANCE_ADD")) item = self.landsat_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "RADIANCE_MAXIMUM")) item = self.landsat_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "REFLECTANCE_MAXIMUM")) item = self.landsat_tableWidget.horizontalHeaderItem(7) item.setText(_translate("SemiAutomaticClassificationPlugin", "K1_CONSTANT")) item = self.landsat_tableWidget.horizontalHeaderItem(8) item.setText(_translate("SemiAutomaticClassificationPlugin", "K2_CONSTANT")) item = self.landsat_tableWidget.horizontalHeaderItem(9) item.setText(_translate("SemiAutomaticClassificationPlugin", "LMAX")) item = self.landsat_tableWidget.horizontalHeaderItem(10) item.setText(_translate("SemiAutomaticClassificationPlugin", "LMIN")) item = self.landsat_tableWidget.horizontalHeaderItem(11) item.setText(_translate("SemiAutomaticClassificationPlugin", "QCALMAX")) item = self.landsat_tableWidget.horizontalHeaderItem(12) item.setText(_translate("SemiAutomaticClassificationPlugin", "QCALMIN")) self.pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.satellite_label.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.satellite_label_3.setText(_translate("SemiAutomaticClassificationPlugin", "Sun elevation")) self.date_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>DATE ACQUIRED</p></body></html>")) self.satellite_label_2.setText(_translate("SemiAutomaticClassificationPlugin", "Date (YYYY-MM-DD)")) self.satellite_label_4.setText(_translate("SemiAutomaticClassificationPlugin", "Earth sun distance")) self.sun_elev_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>SUN ELEVATION</p></body></html>")) self.earth_sun_dist_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Earth sun distance</p></body></html>")) self.label_74.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Satellite (e.g. LANDSAT8)</p></body></html>")) self.label_161.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.landsat_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.landsat_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Landsat), _translate("SemiAutomaticClassificationPlugin", "Landsat")) self.S1_label_95.setText(_translate("SemiAutomaticClassificationPlugin", "Select SNAP xml graph (optional)")) self.S1_toolButton_directoryInput_xml.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.S1_label_97.setText(_translate("SemiAutomaticClassificationPlugin", "Polarization")) self.VH_checkBox_S1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select VH polarization</p></body></html>")) self.VH_checkBox_S1.setText(_translate("SemiAutomaticClassificationPlugin", "VH")) self.VV_checkBox_S1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select VV polarization</p></body></html>")) self.VV_checkBox_S1.setText(_translate("SemiAutomaticClassificationPlugin", "VV")) self.label_209.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-1 conversion (ESA SNAP software required)")) self.S1_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.S1_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_6.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.S1_toolButton_fileInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.label_207.setText(_translate("SemiAutomaticClassificationPlugin", "Sentinel-1 file")) self.projection_checkBox_S1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, project the output to the same projection as selected Band set</p></body></html>")) self.projection_checkBox_S1.setText(_translate("SemiAutomaticClassificationPlugin", "Raster projection as Band set")) self.band_set_comb_spinBox_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.convert_to_db_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, convert to dB</p></body></html>")) self.convert_to_db_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", " convert to dB")) self.S1_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.S1_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.S1_nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.label_210.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion_6.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.sentinel1_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.sentinel1_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Sentinel1), _translate("SemiAutomaticClassificationPlugin", "Sentinel-1")) self.label_90.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing Sentinel-2 bands")) self.S2_toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select a directory</p></body></html>")) self.S2_toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.DOS1_checkBox_S2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the DOS1 atmospheric correction</p></body></html>")) self.DOS1_checkBox_S2.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.S2_nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.S2_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.S2_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_91.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-2 conversion")) self.S2_label_93.setText(_translate("SemiAutomaticClassificationPlugin", "Select metadata file (MTD_MSI)")) self.S2_toolButton_directoryInput_xml2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.S2_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.S2_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.preprocess_b_1_9_10_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.preprocess_b_1_9_10_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Preprocess bands 1, 9, 10")) self.S2_satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Satellite (e.g. Sentinel-2A)</p></body></html>")) self.satellite_label_5.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.satellite_label_6.setText(_translate("SemiAutomaticClassificationPlugin", "Product")) self.S2_product_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Satellite (e.g. Sentinel-2A)</p></body></html>")) self.label_92.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.date_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>DATE ACQUIRED</p></body></html>")) self.satellite_label_15.setText(_translate("SemiAutomaticClassificationPlugin", "Date (YYYY-MM-DD)")) self.sentinel_2_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit metadata</p></body></html>")) item = self.sentinel_2_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.sentinel_2_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Quantification value")) item = self.sentinel_2_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "Solar irradiance")) self.S2_pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.S2_pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_162.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion_2.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.sentinel2_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.sentinel2_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Sentinel2), _translate("SemiAutomaticClassificationPlugin", "Sentinel-2")) self.S2_nodata_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.S3_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.S3_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_109.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-3 conversion")) self.S3_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.S3_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.label_106.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing Sentinel-3 bands")) self.S3_toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select a directory</p></body></html>")) self.S3_toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.DOS1_checkBox_S3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the DOS1 atmospheric correction</p></body></html>")) self.DOS1_checkBox_S3.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.add_new_bandset_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.sentinel_3_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit metadata</p></body></html>")) item = self.sentinel_3_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) self.S3_pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.S3_pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.S3_satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Satellite (e.g. Sentinel-3A)</p></body></html>")) self.satellite_label_12.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.satellite_label_14.setText(_translate("SemiAutomaticClassificationPlugin", "Product")) self.S3_product_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Satellite (e.g. Sentinel-3A)</p></body></html>")) self.label_115.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.label_181.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion_5.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.sentinel3_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.sentinel3_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Sentinel3), _translate("SemiAutomaticClassificationPlugin", "Sentinel-3")) self.nodata_spinBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.nodata_checkBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_5.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.toolButton_directoryInput_ASTER.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open a file</p></body></html>")) self.toolButton_directoryInput_ASTER.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.DOS1_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the DOS1 atmospheric correction (thermal band is not corrected)</p></body></html>")) self.DOS1_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.label_67.setText(_translate("SemiAutomaticClassificationPlugin", " ASTER conversion to TOA reflectance and brightness temperature")) self.label_55.setText(_translate("SemiAutomaticClassificationPlugin", "Select file ASTER L1T (.hdf)")) self.create_bandset_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.create_bandset_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_4.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.celsius_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable calculation of temperature in Celsius from thermal band</p></body></html>")) self.celsius_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", " Brightness temperature in Celsius")) self.ASTER_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit metadata</p></body></html>")) item = self.ASTER_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.ASTER_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "UnitConversionCoeff")) item = self.ASTER_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "PixelSize")) self.pushButton_remove_band_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.pushButton_remove_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.date_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>DATE ACQUIRED</p></body></html>")) self.earth_sun_dist_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Earth sun distance</p></body></html>")) self.satellite_label_9.setText(_translate("SemiAutomaticClassificationPlugin", "Earth sun \n" "distance")) self.satellite_label_8.setText(_translate("SemiAutomaticClassificationPlugin", "Date\n" " (YYYYMMDD)")) self.satellite_label_7.setText(_translate("SemiAutomaticClassificationPlugin", "Sun elevation")) self.sun_elev_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>SUN ELEVATION</p></body></html>")) self.ulm_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Upper left</p></body></html>")) self.satellite_label_10.setText(_translate("SemiAutomaticClassificationPlugin", "UTM zone")) self.utm_zone_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>UTM zone</p></body></html>")) self.satellite_label_11.setText(_translate("SemiAutomaticClassificationPlugin", "UPPERLEFTM")) self.satellite_label_17.setText(_translate("SemiAutomaticClassificationPlugin", "LOWERRIGHTM")) self.lrm_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Lower right</p></body></html>")) self.label_160.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.label_163.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion_3.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.aster_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.aster_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_ASTER), _translate("SemiAutomaticClassificationPlugin", "ASTER")) self.label_218.setText(_translate("SemiAutomaticClassificationPlugin", " MODIS conversion")) self.create_bandset_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.create_bandset_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_5.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.label_219.setText(_translate("SemiAutomaticClassificationPlugin", "Select file MODIS (.hdf)")) self.toolButton_directoryInput_MODIS.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open a file</p></body></html>")) self.toolButton_directoryInput_MODIS.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.nodata_spinBox_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.nodata_checkBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_7.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.reproject_modis_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Reproject bands to WGS 84</p></body></html>")) self.reproject_modis_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Reproject to WGS 84")) self.MODIS_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit metadata</p></body></html>")) item = self.MODIS_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.MODIS_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "UnitConversionCoeff")) self.pushButton_remove_band_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.pushButton_remove_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.satellite_label_16.setText(_translate("SemiAutomaticClassificationPlugin", "Date (YYYY-MM-DD)")) self.MODIS_ID_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>DATE ACQUIRED</p></body></html>")) self.satellite_label_13.setText(_translate("SemiAutomaticClassificationPlugin", "ID")) self.MODIS_date_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>DATE ACQUIRED</p></body></html>")) self.label_220.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.label_221.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion_4.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.modis_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.modis_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_MODIS), _translate("SemiAutomaticClassificationPlugin", "MODIS")) self.label_142.setText(_translate("SemiAutomaticClassificationPlugin", " Convert vector to raster")) self.label_64.setText(_translate("SemiAutomaticClassificationPlugin", "Select the vector")) self.vector_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the vector</p></body></html>")) self.toolButton_reload_16.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_16.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.field_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the value field of the vector</p></body></html>")) self.field_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use the value field of the vector")) self.field_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the value field</p></body></html>")) self.constant_value_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use constant value</p></body></html>")) self.constant_value_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use constant value")) self.constant_value_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Value</p></body></html>")) self.label_157.setText(_translate("SemiAutomaticClassificationPlugin", "Select the type of conversion")) self.conversion_type_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the type of conversion</p></body></html>")) self.label_156.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference raster")) self.toolButton_reload_17.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_17.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.reference_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the reference raster</p></body></html>")) self.extent_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the same extent as reference raster</p></body></html>")) self.extent_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Same extent as reference raster")) self.label_167.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.convert_vector_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.convert_vector_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.vector_to_raster.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.vector_to_raster.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_spectral_distance), _translate("SemiAutomaticClassificationPlugin", "Vector to raster")) self.label_128.setText(_translate("SemiAutomaticClassificationPlugin", " Clip band set")) self.nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.band_set_comb_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_251.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_62.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.label_16.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.output_clip_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Output name prefix</p></body></html>")) self.output_clip_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "clip")) self.LX_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Lower right X</p></body></html>")) self.LX_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X")) self.UX_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Upper left X</p></body></html>")) self.UX_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X")) self.UY_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Upper left Y</p></body></html>")) self.UY_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y")) self.LY_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Lower right Y</p></body></html>")) self.LY_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y")) self.label_12.setText(_translate("SemiAutomaticClassificationPlugin", "LR")) self.selectUL_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set area in the map</p></body></html>")) self.label_29.setText(_translate("SemiAutomaticClassificationPlugin", " Clip coordinates")) self.show_area_radioButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Show / hide area</p></body></html>")) self.show_area_radioButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Show")) self.label_11.setText(_translate("SemiAutomaticClassificationPlugin", "UL")) self.shapefile_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the vector for clipping</p></body></html>")) self.shapefile_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use vector boundaries for clipping rasters</p></body></html>")) self.shapefile_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use vector for clipping")) self.toolButton_reload_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_8.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.temporary_ROI_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use temporary ROI boundaries for clipping rasters</p></body></html>")) self.temporary_ROI_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use temporary ROI for clipping")) self.vector_field_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, clip iterating through each vector polygon and add field value to the output name</p></body></html>")) self.vector_field_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use vector field for output name")) self.class_field_comboBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the vector field</p></body></html>")) self.label_164.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.clip_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.clip_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.clip_multiple_rasters.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.clip_multiple_rasters.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_clip), _translate("SemiAutomaticClassificationPlugin", "Clip multiple rasters")) self.band_set_comb_spinBox_14.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_264.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_249.setText(_translate("SemiAutomaticClassificationPlugin", " Reproject raster bands")) self.raster_align_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the reference raster</p></body></html>")) self.use_align_raster_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Align to raster</p></body></html>")) self.use_align_raster_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Align to raster")) self.toolButton_reload_25.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_25.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.same_extent_raster_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Keep the same extent as the reference raster</p></body></html>")) self.same_extent_raster_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "same extent as reference")) self.epsg_code_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>EPSG value</p></body></html>")) self.use_epsg_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use EPSG value</p></body></html>")) self.use_epsg_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use EPSG code")) self.label_267.setText(_translate("SemiAutomaticClassificationPlugin", " Y resolution")) self.label_266.setText(_translate("SemiAutomaticClassificationPlugin", " X resolution")) self.x_resolution_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>X resolution</p></body></html>")) self.y_resolution_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Y resolution</p></body></html>")) self.resample_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, new pixel size is original pixel size times this factor</p></body></html>")) self.resample_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Resample pixel factor")) self.resample_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Resample factor</p></body></html>")) self.resample_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.label_269.setText(_translate("SemiAutomaticClassificationPlugin", "Resampling method")) self.resampling_method_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the resampling method</p></body></html>")) self.resampling_method_comboBox.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "nearest_neighbour")) self.resampling_method_comboBox.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "average")) self.resampling_method_comboBox.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "sum")) self.resampling_method_comboBox.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "maximum")) self.resampling_method_comboBox.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "minimum")) self.resampling_method_comboBox.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "mode")) self.resampling_method_comboBox.setItemText(6, _translate("SemiAutomaticClassificationPlugin", "median")) self.resampling_method_comboBox.setItemText(7, _translate("SemiAutomaticClassificationPlugin", "first_quartile")) self.resampling_method_comboBox.setItemText(8, _translate("SemiAutomaticClassificationPlugin", "third_quartile")) self.label_270.setText(_translate("SemiAutomaticClassificationPlugin", "Output type")) self.raster_type_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a type</p></body></html>")) self.raster_type_combo_2.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Auto")) self.raster_type_combo_2.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Float32")) self.raster_type_combo_2.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "Int32")) self.raster_type_combo_2.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "UInt32")) self.raster_type_combo_2.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "Int16")) self.raster_type_combo_2.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "UInt16")) self.raster_type_combo_2.setItemText(6, _translate("SemiAutomaticClassificationPlugin", "Byte")) self.change_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, change output NoData value</p></body></html>")) self.change_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Change output NoData value")) self.nodata_spinBox_14.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value of the output raster</p></body></html>")) self.label_265.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.reproj_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Output name prefix</p></body></html>")) self.reproj_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "reproj")) self.label_263.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.reproject_raster_bands.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.reproject_raster_bands.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.reproject_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.reproject_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_reproject_bands), _translate("SemiAutomaticClassificationPlugin", "Reproject raster bands")) self.raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the image to be split</p></body></html>")) self.label_57.setText(_translate("SemiAutomaticClassificationPlugin", " Split raster bands")) self.label_50.setText(_translate("SemiAutomaticClassificationPlugin", "Select a multiband raster")) self.toolButton_reload_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_9.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_165.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_61.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Output name prefix</p></body></html>")) self.output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "split")) self.split_raster_bands.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.split_raster_bands.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.split_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.split_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_split_raster), _translate("SemiAutomaticClassificationPlugin", "Split raster bands")) self.label_252.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.stack_raster_bands.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.stack_raster_bands.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.stack_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.stack_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_223.setText(_translate("SemiAutomaticClassificationPlugin", " Stack band set")) self.label_226.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_stack_bands), _translate("SemiAutomaticClassificationPlugin", "Stack raster bands")) self.label_134.setText(_translate("SemiAutomaticClassificationPlugin", " Mosaic of band sets")) self.label_135.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.nodata_checkBox_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_9.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.mosaic_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Output name prefix</p></body></html>")) self.mosaic_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "mosaic")) self.label_144.setText(_translate("SemiAutomaticClassificationPlugin", "Band set list")) self.mosaic_band_sets_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>List of band set numbers separated by comma ,<br/>Use for selecting all the band sets</p></body></html>")) self.mosaic_band_sets_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "1, 2")) self.mosaic_virtual_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, output bands are virtual rasters</p></body></html>")) self.mosaic_virtual_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create virtual raster output")) self.mosaic_bandsets_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.mosaic_bandsets_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.mosaic_bandsets.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.mosaic_bandsets.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_182.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_mosaic_band_sets), _translate("SemiAutomaticClassificationPlugin", "Mosaic band sets")) self.label_260.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.classification_name_combo_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification</p></body></html>")) self.cloud_mask_classes_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter class values separated by , or -</p></body></html>")) self.label_203.setText(_translate("SemiAutomaticClassificationPlugin", "Mask class values")) self.label_186.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.toolButton_reload_23.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_23.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_140.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.mask_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Output name prefix</p></body></html>")) self.mask_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "mask")) self.cloud_buffer_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Size in pixels</p></body></html>")) self.cloud_buffer_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, create a buffer for class values</p></body></html>")) self.cloud_buffer_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use buffer of pixel size")) self.nodata_spinBox_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.label_141.setText(_translate("SemiAutomaticClassificationPlugin", "Output NoData value")) self.cloud_mask_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.cloud_mask_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.cloud_masking.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.cloud_masking.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_185.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_138.setText(_translate("SemiAutomaticClassificationPlugin", " Mask of band set")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_cloud_mask), _translate("SemiAutomaticClassificationPlugin", "Cloud masking")) self.GOES_nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>No data value</p></body></html>")) self.GOES_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.GOES_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_273.setText(_translate("SemiAutomaticClassificationPlugin", " GOES conversion")) self.GOES_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create the Band set automatically and use the checked Band set tools</p></body></html>")) self.GOES_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.label_274.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing GOES bands")) self.GOES_toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select a directory</p></body></html>")) self.GOES_toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_new_bandset_checkBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a new band set where bands are added</p></body></html>")) self.add_new_bandset_checkBox_7.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.GOES_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit metadata</p></body></html>")) item = self.GOES_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) self.GOES_pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.GOES_pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_277.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.satellite_label_20.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.GOES_satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Satellite (e.g. Sentinel-3A)</p></body></html>")) self.label_278.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pushButton_Conversion_8.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.goes_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.goes_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_GOES), _translate("SemiAutomaticClassificationPlugin", "GOES")) self.label_283.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_281.setText(_translate("SemiAutomaticClassificationPlugin", "Matrix file (optional)")) self.toolButton_input_matrix.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Open a file</span></p></body></html>")) self.label_279.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.neighbor_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Output name prefix</p></body></html>")) self.neighbor_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "neighbor")) self.neighbor_virtual_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, output bands are virtual rasters</p></body></html>")) self.neighbor_virtual_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create virtual raster output")) self.neighbor_pixels.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.neighbor_pixels.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.class_neighbor_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.class_neighbor_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_286.setText(_translate("SemiAutomaticClassificationPlugin", " Neighbor pixels")) self.statistic_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter a value</p></body></html>")) self.statistic_name_combobox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a statistic</p></body></html>")) self.label_284.setText(_translate("SemiAutomaticClassificationPlugin", "Select a statistic")) self.label_285.setText(_translate("SemiAutomaticClassificationPlugin", " Statistic")) self.label_282.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_280.setText(_translate("SemiAutomaticClassificationPlugin", "Neighbor distance in pixels")) self.band_set_comb_spinBox_15.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.class_neighbor_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Distance in pixels</p></body></html>")) self.circular_structure_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, neighbor pixels are calculated inside a circle of radius equal to the distance in pixels</p></body></html>")) self.circular_structure_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Circular")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_neighbor_pixels), _translate("SemiAutomaticClassificationPlugin", "Neighbor pixels")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_preprocessing), _translate("SemiAutomaticClassificationPlugin", "Preprocessing")) self.label_253.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateBandSetComb_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.calculateBandSetComb_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.band_combination.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.band_combination.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_250.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set (of classifications)")) self.band_set_comb_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_72.setText(_translate("SemiAutomaticClassificationPlugin", " Combination of band values")) self.toolBox_band_set_combination.setItemText(self.toolBox_band_set_combination.indexOf(self.page_29), _translate("SemiAutomaticClassificationPlugin", "Input")) self.band_set_comb_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Courier 10 Pitch\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" "<p style=\"-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:9pt;\"><br /></p></body></html>")) self.toolBox_band_set_combination.setItemText(self.toolBox_band_set_combination.indexOf(self.page_30), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_bandset_combination_2), _translate("SemiAutomaticClassificationPlugin", "Band combination")) self.label_58.setText(_translate("SemiAutomaticClassificationPlugin", " Principal Components Analysis of band set")) self.nodata_checkBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_4.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.num_comp_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, calculate this number of components only</p></body></html>")) self.num_comp_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Number of components")) self.nodata_spinBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.pca_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.pca_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_254.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.pca_components_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Number of components</p></body></html>")) self.label_166.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pca.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.pca.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_PCA.setItemText(self.toolBox_PCA.indexOf(self.page_16), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_PCA.setItemText(self.toolBox_PCA.indexOf(self.page_17), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.PCA_tab), _translate("SemiAutomaticClassificationPlugin", "PCA")) self.label_78.setText(_translate("SemiAutomaticClassificationPlugin", " Clustering of band set")) self.isodata_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use ISODATA</p></body></html>")) self.isodata_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "ISODATA")) self.band_set_comb_spinBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_230.setText(_translate("SemiAutomaticClassificationPlugin", "Method ")) self.label_255.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.kmeans_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use K-means</p></body></html>")) self.kmeans_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "&K-means ")) self.label_225.setText(_translate("SemiAutomaticClassificationPlugin", "Max number of iterations")) self.thresh_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Threshold</p></body></html>")) self.std_dev_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Threshold</p></body></html>")) self.kmean_threshold_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, for K-means: iteration is terminated if distance is lower than threshold; for ISODATA: signatures are merged if distance is greater than threshold</p></body></html>")) self.kmean_threshold_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Distance threshold")) self.nodata_spinBox_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.kmeans_iter_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the maximum number of iterations</p></body></html>")) self.label_228.setText(_translate("SemiAutomaticClassificationPlugin", "ISODATA max standard deviation")) self.nodata_checkBox_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_8.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.kmeans_classes_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Number of classes</p></body></html>")) self.label_224.setText(_translate("SemiAutomaticClassificationPlugin", "Number of classes")) self.label_229.setText(_translate("SemiAutomaticClassificationPlugin", "ISODATA minimum class size in pixels")) self.min_size_class_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Minimum class size in pixels</p></body></html>")) self.min_distance_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use Minimum Distance algorithm</p></body></html>")) self.min_distance_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Minimum Distance")) self.kmean_save_siglist_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, save the resulting signatures to Signature list</p></body></html>")) self.kmean_save_siglist_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save resulting signatures to Signature list")) self.label_227.setText(_translate("SemiAutomaticClassificationPlugin", "Distance algorithm")) self.label_104.setText(_translate("SemiAutomaticClassificationPlugin", " Seed signatures")) self.kmean_siglist_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use signatures in Signature list as seed signatures</p></body></html>")) self.kmean_siglist_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Use Signature list as seed signatures")) self.kmean_randomsiglist_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, calculate seed signatures from random pixels</p></body></html>")) self.kmean_randomsiglist_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Use random seed signatures")) self.kmean_minmax_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, calculate seed signatures from minimum and maximum values of bands</p></body></html>")) self.kmean_minmax_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Seed signatures from band values")) self.spectral_angle_map_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use Spectral Angle Mapping algorithm (only for K-means)</p></body></html>")) self.spectral_angle_map_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Spectral Angle Mapping")) self.label_179.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.kmeans_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.kmeans_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.clustering.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.clustering.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_kmeans.setItemText(self.toolBox_kmeans.indexOf(self.page_18), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_kmeans.setItemText(self.toolBox_kmeans.indexOf(self.page_23), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_kmeans), _translate("SemiAutomaticClassificationPlugin", "Clustering")) self.min_distance_radioButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use Minimum Distance algorithm</p></body></html>")) self.min_distance_radioButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Minimum Distance")) self.label_231.setText(_translate("SemiAutomaticClassificationPlugin", "Distance algorithm")) self.spectral_angle_map_radioButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, use Spectral Angle Mapping algorithm (only for K-means)</p></body></html>")) self.spectral_angle_map_radioButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Spectral Angle Mapping")) self.label_137.setText(_translate("SemiAutomaticClassificationPlugin", "Spectral distance of band sets")) self.distance_threshold_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, calculate a raster of changes where distance is above threshold</p></body></html>")) self.distance_threshold_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Distance threshold")) self.thresh_doubleSpinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Threshold</p></body></html>")) self.label_256.setText(_translate("SemiAutomaticClassificationPlugin", "Select first input band set")) self.band_set_comb_spinBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_257.setText(_translate("SemiAutomaticClassificationPlugin", "Select second input band set")) self.band_set_comb_spinBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_183.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.spectral_distance_bandsets_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.spectral_distance_bandsets_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.spectral_distance.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.spectral_distance.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_spectral_dist), _translate("SemiAutomaticClassificationPlugin", "Spectral distance")) self.label_32.setText(_translate("SemiAutomaticClassificationPlugin", "Use")) self.macroclass_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the ID of macroclasses for the classification</p></body></html>")) self.macroclass_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) self.class_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the ID of classes for the classification</p></body></html>")) self.class_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) self.algorithm_weight_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open tab Algorithm band weight</p></body></html>")) self.algorithm_weight_button.setText(_translate("SemiAutomaticClassificationPlugin", "W")) self.algorithm_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a classification algorithm</p></body></html>")) self.algorithm_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Minimum Distance")) self.algorithm_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Maximum Likelihood")) self.algorithm_combo.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "Spectral Angle Mapping")) self.band_set_comb_spinBox_12.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_261.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_240.setText(_translate("SemiAutomaticClassificationPlugin", " Algorithm")) self.alg_threshold_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set a classification threshold for all signatures</p></body></html>")) self.algorithm_threshold_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open tab Signature threshold</p></body></html>")) self.algorithm_threshold_button.setText(_translate("SemiAutomaticClassificationPlugin", "W")) self.label_234.setText(_translate("SemiAutomaticClassificationPlugin", "Threshold")) self.label_243.setText(_translate("SemiAutomaticClassificationPlugin", "Classification")) self.LC_signature_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the Land Cover Signature Classification is used</p></body></html>")) self.LC_signature_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "LCS")) self.label_235.setText(_translate("SemiAutomaticClassificationPlugin", "Use")) self.LC_signature_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open tab LCS threshold</p></body></html>")) self.LCS_leave_unclassified_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the selected Algorithm is used only for class overlapping pixels of the Land Cover Signature Classification</p></body></html>")) self.LCS_leave_unclassified_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "only overlap")) self.label_241.setText(_translate("SemiAutomaticClassificationPlugin", " Land Cover Signature Classification")) self.LCS_class_algorithm_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the selected Algorithm is used for unclassified pixels of the Land Cover Signature Classification</p></body></html>")) self.LCS_class_algorithm_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Algorithm")) self.label_242.setText(_translate("SemiAutomaticClassificationPlugin", " Classification output")) self.resetQmlButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.resetQmlButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_238.setText(_translate("SemiAutomaticClassificationPlugin", "Load qml style")) self.qml_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Select qml style</span></p></body></html>")) self.qml_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.qml_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Qml file path</p></body></html>")) self.mask_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select an optional mask vector</p></body></html>")) self.mask_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Apply mask")) self.resetMaskButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.resetMaskButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.mask_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Path of the optional mask shapefile</p></body></html>")) self.vector_output_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Create a classification shapefile after the classification process</p></body></html>")) self.vector_output_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create vector")) self.report_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Calculate a classification report</p></body></html>")) self.report_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Classification report")) self.alg_files_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If enabled, the rasters calculated by the classification algorithm (one per signature) are saved along with the classification</p></body></html>")) self.alg_files_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save algorithm files")) self.button_classification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.button_classification.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_239.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.classification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.classification.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_classification), _translate("SemiAutomaticClassificationPlugin", "Classification")) self.label_233.setText(_translate("SemiAutomaticClassificationPlugin", "Use")) self.macroclass_checkBox_rf.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the ID of macroclasses for the classification</p></body></html>")) self.macroclass_checkBox_rf.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) self.class_checkBox_rf.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the ID of classes for the classification</p></body></html>")) self.class_checkBox_rf.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) self.band_set_comb_spinBox_13.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_262.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_245.setText(_translate("SemiAutomaticClassificationPlugin", "Random Forest classification (ESA SNAP software required)")) self.number_trees_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Number of trees</p></body></html>")) self.label_237.setText(_translate("SemiAutomaticClassificationPlugin", "Number of trees")) self.number_training_samples_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Number of training samples</p></body></html>")) self.label_236.setText(_translate("SemiAutomaticClassificationPlugin", "Number of training samples ")) self.evaluate_classifier_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Evaluate classifier</p></body></html>")) self.evaluate_classifier_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Evaluate classifier")) self.evaluate_feature_power_set_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, evaluate feature power set</p></body></html>")) self.evaluate_feature_power_set_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Evaluate feature power set")) self.label_248.setText(_translate("SemiAutomaticClassificationPlugin", "Max")) self.rf_power_min_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Minumum power</p></body></html>")) self.label_247.setText(_translate("SemiAutomaticClassificationPlugin", "Min")) self.rf_power_max_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Maximum power</p></body></html>")) self.save_classifier_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, save classifier</p></body></html>")) self.save_classifier_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save classifier")) self.label_244.setText(_translate("SemiAutomaticClassificationPlugin", "Load classifier")) self.classifier_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a previosly saved classifier</p></body></html>")) self.classifier_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.classifier_lineEdit_.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Classifier file path</p></body></html>")) self.resetClassifierButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.resetClassifierButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.button_random_forest.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.button_random_forest.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_246.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.random_forest.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.random_forest.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_random_forest.setItemText(self.toolBox_random_forest.indexOf(self.page_21), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_random_forest.setItemText(self.toolBox_random_forest.indexOf(self.page_25), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_random_forest), _translate("SemiAutomaticClassificationPlugin", "Random forest")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_band_processing), _translate("SemiAutomaticClassificationPlugin", "Band processing")) self.label_33.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification to assess")) self.label_34.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference vector or raster")) self.classification_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification to assess</p></body></html>")) self.buttonReload_shape_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.buttonReload_shape_4.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.toolButton_reload_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_4.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.reference_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the reference vector or raster</p></body></html>")) self.label_145.setText(_translate("SemiAutomaticClassificationPlugin", " Accuracy assessment")) self.label_82.setText(_translate("SemiAutomaticClassificationPlugin", "Vector field")) self.class_field_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the field of the classification code </p></body></html>")) self.nodata_checkBox_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_11.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_15.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.label_168.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateMatrix_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.calculateMatrix_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.accuracy.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.accuracy.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_accuracy.setItemText(self.toolBox_accuracy.indexOf(self.page_10), _translate("SemiAutomaticClassificationPlugin", "Input")) self.error_matrix_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Courier 10 Pitch\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" "<p style=\"-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:9pt;\"><br /></p></body></html>")) self.toolBox_accuracy.setItemText(self.toolBox_accuracy.indexOf(self.page_11), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_accuracy), _translate("SemiAutomaticClassificationPlugin", "Accuracy")) self.mask_unchanged_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p align=\"justify\">If enabled, pixels having the same values in both classifications will be reported; if not enabled, 0 value is set for unchanged pixels</p></body></html>")) self.mask_unchanged_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Report unchanged pixels")) self.classification_reference_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the reference classification raster</p></body></html>")) self.label_40.setText(_translate("SemiAutomaticClassificationPlugin", "Select the new classification")) self.label_38.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference classification")) self.new_classification_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a new raster to be compared with the reference raster</p></body></html>")) self.toolButton_reload_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_5.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.toolButton_reload_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_6.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_116.setText(_translate("SemiAutomaticClassificationPlugin", " Land cover change")) self.label_169.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateLandCoverChange_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.calculateLandCoverChange_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.land_cover_change.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.land_cover_change.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_landCoverChange.setItemText(self.toolBox_landCoverChange.indexOf(self.page_12), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_landCoverChange.setItemText(self.toolBox_landCoverChange.indexOf(self.page_13), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_landCoverChange), _translate("SemiAutomaticClassificationPlugin", "Land cover change")) self.classification_report_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification raster</p></body></html>")) self.label_44.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the report</p></body></html>")) self.nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.toolButton_reload_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_10.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_170.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateReport_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.calculateReport_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_report.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.classification_report.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_148.setText(_translate("SemiAutomaticClassificationPlugin", " Classification report")) self.toolBox_class_report.setItemText(self.toolBox_class_report.indexOf(self.page_14), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_class_report.setItemText(self.toolBox_class_report.indexOf(self.page_15), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_class_report), _translate("SemiAutomaticClassificationPlugin", "Classification report")) self.label_187.setText(_translate("SemiAutomaticClassificationPlugin", " Cross classification")) self.nodata_checkBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_6.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.label_197.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.label_199.setText(_translate("SemiAutomaticClassificationPlugin", "Vector field")) self.class_field_comboBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the vector field</p></body></html>")) self.toolButton_reload_21.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_21.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.classification_name_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification</p></body></html>")) self.buttonReload_shape_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.buttonReload_shape_5.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.reference_name_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the reference vector or raster</p></body></html>")) self.label_198.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference vector or raster")) self.label_200.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculatecrossClass_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.calculatecrossClass_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.cross_classification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.cross_classification.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_cross_classification.setItemText(self.toolBox_cross_classification.indexOf(self.page_19), _translate("SemiAutomaticClassificationPlugin", "Input")) self.cross_matrix_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Courier 10 Pitch\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" "<p style=\"-qt-paragraph-type:empty; margin-top:0px; margin-bottom:0px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:9pt;\"><br /></p></body></html>")) self.toolBox_cross_classification.setItemText(self.toolBox_cross_classification.indexOf(self.page_22), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_cross_classification), _translate("SemiAutomaticClassificationPlugin", "Cross classification")) self.label_188.setText(_translate("SemiAutomaticClassificationPlugin", " Class signature")) self.classification_name_combo_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification</p></body></html>")) self.label_201.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.toolButton_reload_22.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_22.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_259.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band set number</p></body></html>")) self.label_184.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.class_signature_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.class_signature_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.class_signature_save_siglist_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, save the resulting signatures to Signature list</p></body></html>")) self.class_signature_save_siglist_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save resulting signatures to Signature list")) self.class_signature.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.class_signature.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_class_signature.setItemText(self.toolBox_class_signature.indexOf(self.page_20), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_class_signature.setItemText(self.toolBox_class_signature.indexOf(self.page_24), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_class_signature), _translate("SemiAutomaticClassificationPlugin", "Class signature")) self.label_189.setText(_translate("SemiAutomaticClassificationPlugin", " Classification to vector")) self.label_63.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.classification_vector_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification raster</p></body></html>")) self.toolButton_reload_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_11.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.class_macroclass_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the code field</p></body></html>")) self.class_macroclass_comboBox.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "C_ID")) self.class_macroclass_comboBox.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "MC_ID")) self.use_class_code_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the codes from Signature list table for vector symbology</p></body></html>")) self.use_class_code_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use code from Signature list")) self.label_49.setText(_translate("SemiAutomaticClassificationPlugin", " Symbology")) self.dissolve_output_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the polygons are dissolved to avoid discontinuity between processed blocks (slower)</p></body></html>")) self.dissolve_output_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Dissolve output")) self.convert_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.convert_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_171.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.classification_to_vector.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.classification_to_vector.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_class_to_vector), _translate("SemiAutomaticClassificationPlugin", "Classification to vector")) self.label_65.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.reclassification_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification raster</p></body></html>")) self.toolButton_reload_12.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_12.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_190.setText(_translate("SemiAutomaticClassificationPlugin", " Reclassification")) self.calculate_unique_values_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Calculate unique values</p></body></html>")) self.CID_MCID_code_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable this for reclassification from C ID to MC ID; if checked, unique values are calculated from the Signature list, setting old value C ID and new value MC ID</p></body></html>")) self.CID_MCID_code_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "calculate C ID to MC ID values")) self.label_98.setText(_translate("SemiAutomaticClassificationPlugin", "Calculate unique values")) self.label_54.setText(_translate("SemiAutomaticClassificationPlugin", " Values")) self.incremental_new_values_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set incremental new values</p></body></html>")) self.label_271.setText(_translate("SemiAutomaticClassificationPlugin", "Incremental new values")) self.reclass_values_tableWidget.setSortingEnabled(False) item = self.reclass_values_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Old value")) item = self.reclass_values_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "New value")) self.add_value_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add row</p></body></html>")) self.add_value_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.remove_row_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_row_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_reclass_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import reclassification table from text file</p></body></html>")) self.import_reclass_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_reclass_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export reclassification table to text file</p></body></html>")) self.export_reclass_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.apply_symbology_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the codes from Signature list table for vector symbology</p></body></html>")) self.apply_symbology_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use code from Signature list")) self.class_macroclass_comboBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the code field</p></body></html>")) self.class_macroclass_comboBox_2.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "MC_ID")) self.class_macroclass_comboBox_2.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "C_ID")) self.label_51.setText(_translate("SemiAutomaticClassificationPlugin", " Symbology")) self.label_172.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.reclassify_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.reclassify_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.reclassification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.reclassification.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_reclassification), _translate("SemiAutomaticClassificationPlugin", "Reclassification")) self.label_193.setText(_translate("SemiAutomaticClassificationPlugin", " Edit raster")) self.undo_edit_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Undo edit (only for ROI polygons)</p></body></html>")) self.undo_edit_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_173.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_66.setText(_translate("SemiAutomaticClassificationPlugin", "Select the input raster")) self.edit_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the raster to edit</p></body></html>")) self.toolButton_reload_14.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_14.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.use_constant_val_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use constant value</p></body></html>")) self.use_constant_val_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use constant value")) self.value_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Value</p></body></html>")) self.use_expression_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use expression</p></body></html>")) self.use_expression_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use expression")) self.expression_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter expression</p></body></html>")) self.expression_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "where(raster == 1, 2, raster)")) self.label_81.setText(_translate("SemiAutomaticClassificationPlugin", " Edit raster values")) self.use_field_vector_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Use the value field of the vector</p></body></html>")) self.use_field_vector_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use the value field of the vector")) self.field_comboBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the value field</p></body></html>")) self.edit_val_use_vector_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit values using a vector</p></body></html>")) self.edit_val_use_vector_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", " Edit values using a vector")) self.vector_name_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the vector</p></body></html>")) self.toolButton_reload_20.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_20.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.edit_val_use_ROI_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Edit values using temporary ROIs</p></body></html>")) self.edit_val_use_ROI_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", " Edit values using ROI polygons")) self.label_158.setText(_translate("SemiAutomaticClassificationPlugin", " Edit options")) self.raster_set_value_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.raster_set_value_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.edit_raster_using_vector.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.edit_raster_using_vector.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab), _translate("SemiAutomaticClassificationPlugin", "Edit raster")) self.label_70.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.sieve_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification</p></body></html>")) self.toolButton_reload_15.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_15.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_133.setText(_translate("SemiAutomaticClassificationPlugin", "Size threshold")) self.sieve_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Size threshold in pixels</p></body></html>")) self.label_136.setText(_translate("SemiAutomaticClassificationPlugin", "Pixel connection")) self.sieve_connection_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Pixel connection</p></body></html>")) self.sieve_connection_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "4")) self.sieve_connection_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "8")) self.label_174.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.sieve_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.sieve_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_sieve.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.classification_sieve.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_195.setText(_translate("SemiAutomaticClassificationPlugin", " Classification sieve")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_sieve), _translate("SemiAutomaticClassificationPlugin", "Classification sieve")) self.label_202.setText(_translate("SemiAutomaticClassificationPlugin", " Classification erosion")) self.label_146.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.erosion_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification</p></body></html>")) self.toolButton_reload_18.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_18.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_149.setText(_translate("SemiAutomaticClassificationPlugin", "Size in pixels")) self.erosion_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Size in pixels</p></body></html>")) self.circular_structure_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, neighbor pixels are calculated inside a circle of radius equal to the distance in pixels</p></body></html>")) self.circular_structure_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Circular")) self.label_151.setText(_translate("SemiAutomaticClassificationPlugin", "Class values")) self.erosion_classes_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter class values separated by , or -</p></body></html>")) self.label_175.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.class_erosion_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.class_erosion_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_erosion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.classification_erosion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_erosion), _translate("SemiAutomaticClassificationPlugin", "Classification erosion")) self.label_204.setText(_translate("SemiAutomaticClassificationPlugin", " Classification dilation")) self.label_152.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.dilation_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the classification</p></body></html>")) self.toolButton_reload_19.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_19.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_153.setText(_translate("SemiAutomaticClassificationPlugin", "Size in pixels")) self.dilation_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Size in pixels</p></body></html>")) self.circular_structure_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, neighbor pixels are calculated inside a circle of radius equal to the distance in pixels</p></body></html>")) self.circular_structure_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Circular")) self.label_155.setText(_translate("SemiAutomaticClassificationPlugin", "Class values")) self.dilation_classes_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter class values separated by , or -</p></body></html>")) self.label_176.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.class_dilation_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.class_dilation_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_dilation.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.classification_dilation.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_dilation), _translate("SemiAutomaticClassificationPlugin", "Classification dilation")) self.label_212.setText(_translate("SemiAutomaticClassificationPlugin", " Zonal stat rasters")) self.label_77.setText(_translate("SemiAutomaticClassificationPlugin", "Select the input raster")) self.classification_name_combo_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the raster to edit</p></body></html>")) self.toolButton_reload_24.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_24.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.nodata_checkBox_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_10.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_12.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.class_field_comboBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the vector field</p></body></html>")) self.label_214.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference vector or raster")) self.buttonReload_shape_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.buttonReload_shape_6.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_213.setText(_translate("SemiAutomaticClassificationPlugin", "Vector field")) self.reference_name_combo_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select the reference vector or raster</p></body></html>")) self.statistic_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter a value</p></body></html>")) self.statistic_name_combobox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a statistic</p></body></html>")) self.label_232.setText(_translate("SemiAutomaticClassificationPlugin", "Select a statistic")) self.label_216.setText(_translate("SemiAutomaticClassificationPlugin", " Statistic")) self.zonal_stat_raster_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.zonal_stat_raster_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_215.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.zonal_stat_raster.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.zonal_stat_raster.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_zonal_stats_rasters), _translate("SemiAutomaticClassificationPlugin", " Zonal stat rasters")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_postProcessing), _translate("SemiAutomaticClassificationPlugin", "Postprocessing")) self.toolButton_reload_13.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Refresh list</p></body></html>")) self.toolButton_reload_13.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.tableWidget_band_calc.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Band list</p></body></html>")) item = self.tableWidget_band_calc.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Variable")) item = self.tableWidget_band_calc.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band name")) self.bandcalc_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Filter</p></body></html>")) self.bandcalc_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) self.label_71.setText(_translate("SemiAutomaticClassificationPlugin", " Band list")) self.plainTextEdit_calc.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter an expression (e.g. "raster1" + "raster2" )</p></body></html>")) self.toolButton_less.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Less than</p></body></html>")) self.toolButton_less.setText(_translate("SemiAutomaticClassificationPlugin", "<")) self.toolButton_greater.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Greater than</p></body></html>")) self.toolButton_greater.setText(_translate("SemiAutomaticClassificationPlugin", ">")) self.toolButton_lbracket.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open parenthesis</p></body></html>")) self.toolButton_lbracket.setText(_translate("SemiAutomaticClassificationPlugin", "(")) self.toolButton_rbracket.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Close parenthesis</p></body></html>")) self.toolButton_rbracket.setText(_translate("SemiAutomaticClassificationPlugin", ")")) self.toolButton_power.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Power</p></body></html>")) self.toolButton_power.setText(_translate("SemiAutomaticClassificationPlugin", "^")) self.toolButton_sqrt.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Square root</p></body></html>")) self.toolButton_sqrt.setText(_translate("SemiAutomaticClassificationPlugin", "√")) self.toolButton_plus.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Plus</p></body></html>")) self.toolButton_plus.setText(_translate("SemiAutomaticClassificationPlugin", "+")) self.toolButton_minus.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Minus</p></body></html>")) self.toolButton_minus.setText(_translate("SemiAutomaticClassificationPlugin", "-")) self.toolButton_product.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Multiplication</p></body></html>")) self.toolButton_product.setText(_translate("SemiAutomaticClassificationPlugin", "*")) self.toolButton_ratio.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Division</p></body></html>")) self.toolButton_ratio.setText(_translate("SemiAutomaticClassificationPlugin", "/")) self.toolButton_equal.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Equals</p></body></html>")) self.toolButton_equal.setText(_translate("SemiAutomaticClassificationPlugin", "==")) self.toolButton_unequal.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Not equals</p></body></html>")) self.toolButton_unequal.setText(_translate("SemiAutomaticClassificationPlugin", "!=")) self.toolButton_import_expression.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Open a text file to add custom functions</p></body></html>")) item = self.band_calc_function_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Functions")) self.band_calc_tabWidget.setTabText(self.band_calc_tabWidget.indexOf(self.tab_expression), _translate("SemiAutomaticClassificationPlugin", "Expression")) self.decision_rules_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter one or more rules separated by semicolon (e.g. "raster1" > 0; "raster2" > 0 )</p></body></html>")) item = self.decision_rules_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Value")) item = self.decision_rules_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Rule")) self.remove_rule_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Delete row</p></body></html>")) self.remove_rule_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.move_up_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted rule up</p></body></html>")) self.move_up_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.import_rules_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import rules from text file</p></body></html>")) self.import_rules_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_rules_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.clear_rules_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_rule_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Add row</p></body></html>")) self.add_rule_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.move_down_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Move highlighted rule down</p></body></html>")) self.move_down_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.export_rules_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export rules to text file</p></body></html>")) self.export_rules_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.band_calc_tabWidget.setTabText(self.band_calc_tabWidget.indexOf(self.tab_decision_rules), _translate("SemiAutomaticClassificationPlugin", "Decision rules")) self.nodata_as_value_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, input NoData pixels will be evaluated as regular values</p></body></html>")) self.nodata_as_value_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Input NoData \n" " as value")) self.nodata_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, pixels equal to NoData value will be excluded from the output raster</p></body></html>")) self.nodata_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Use value\n" "as NoData")) self.nodata_spinBox_13.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value</p></body></html>")) self.label_4.setText(_translate("SemiAutomaticClassificationPlugin", "Calculation\n" "data type")) self.calc_type_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a type</p></body></html>")) self.calc_type_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Float32")) self.calc_type_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Int32")) self.calc_type_combo.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "UInt32")) self.calc_type_combo.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "Int16")) self.calc_type_combo.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "UInt16")) self.calc_type_combo.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "Byte")) self.label_83.setText(_translate("SemiAutomaticClassificationPlugin", "Extent:")) self.intersection_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the extent of raster ouput equals the intersection of input rasters</p></body></html>")) self.intersection_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Intersection")) self.extent_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the extent of raster ouput equals the extent of selected raster</p></body></html>")) self.extent_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Same as")) self.raster_extent_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a raster</p></body></html>")) self.align_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Align")) self.label_84.setText(_translate("SemiAutomaticClassificationPlugin", "Output raster")) self.raster_type_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select a type</p></body></html>")) self.raster_type_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Float32")) self.raster_type_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Int32")) self.raster_type_combo.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "UInt32")) self.raster_type_combo.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "Int16")) self.raster_type_combo.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "UInt16")) self.raster_type_combo.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "Byte")) self.label_268.setText(_translate("SemiAutomaticClassificationPlugin", "Output \n" "NoData value")) self.nodata_spinBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>NoData value of the output raster</p></body></html>")) self.nodata_mask_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, every NoData pixel in input will be NoData pixel in output</p></body></html>")) self.nodata_mask_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "NoData mask")) self.set_scale_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, set a scale</p></body></html>")) self.set_scale_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Set \n" "scale")) self.scale_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Scale</p></body></html>")) self.set_offset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, set an offset</p></body></html>")) self.set_offset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Set \n" "offset")) self.band_calc.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Function to Batch</p></body></html>")) self.band_calc.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolButton_calculate.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.toolButton_calculate.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_band_calc), _translate("SemiAutomaticClassificationPlugin", "Band calc")) self.label_73.setText(_translate("SemiAutomaticClassificationPlugin", "Batch")) self.plainTextEdit_batch.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enter a batch function</p></body></html>")) self.export_batch_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export batch to text file</p></body></html>")) self.export_batch_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_batch_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.clear_batch_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.import_batch_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Import batch from text file</p></body></html>")) self.import_batch_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) item = self.batch_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Functions")) self.label_177.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.check_batch.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Check batch function</p></body></html>")) self.check_batch.setText(_translate("SemiAutomaticClassificationPlugin", " CHECK")) self.toolButton_run_batch.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Run</span></p></body></html>")) self.toolButton_run_batch.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_batch), _translate("SemiAutomaticClassificationPlugin", "Batch")) self.label_28.setText(_translate("SemiAutomaticClassificationPlugin", " System")) self.RAM_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set available RAM for processes</p></body></html>")) self.label_23.setText(_translate("SemiAutomaticClassificationPlugin", "Available RAM (MB)")) self.label_56.setText(_translate("SemiAutomaticClassificationPlugin", "CPU threads")) self.CPU_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the number of CPU threads </p></body></html>")) self.label_13.setText(_translate("SemiAutomaticClassificationPlugin", "SMTP server")) self.label_18.setText(_translate("SemiAutomaticClassificationPlugin", "password")) self.smtp_user_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the Class ID field name</p><p>[max 10 characters]</p></body></html>")) self.smtp_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the sending of email of completed process</p></body></html>")) self.smtp_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Send email of completed process to")) self.label_117.setText(_translate("SemiAutomaticClassificationPlugin", "SMTP process notification")) self.smtp_password_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Password</p></body></html>")) self.smtp_server_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the Class ID field name</p><p>[max 10 characters]</p></body></html>")) self.label_14.setText(_translate("SemiAutomaticClassificationPlugin", "user")) self.to_email_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>A list of addresses (separated by comma , ) to send this mail to </p></body></html>")) self.remeber_settings_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, remember user name and password locally in QGIS</p></body></html>")) self.remeber_settings_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.reset_temp_directory_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Reset to default temporary directory</p></body></html>")) self.reset_temp_directory_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.temp_directory_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p >Select a directory</p></body></html>")) self.temp_directory_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_87.setText(_translate("SemiAutomaticClassificationPlugin", "Temporary directory")) self.SNAP_label.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><a href=\"https://step.esa.int/main/download/snap-download/\"><span style=\" text-decoration: underline; color:#0000ff;\">ESA SNAP GPT executable</span></a></p></body></html>")) self.label_276.setText(_translate("SemiAutomaticClassificationPlugin", "Python executable path")) self.label_288.setText(_translate("SemiAutomaticClassificationPlugin", "Python modules path")) self.label_275.setText(_translate("SemiAutomaticClassificationPlugin", "GDAL installation directory")) self.SNAP_GPT_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Path to the GPT executable (e.g. C:\\Program Files\\snap\\bin\\gpt.exe)</p></body></html>")) self.python_path_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Path to the Python executable (e.g. /usr/local/bin/python3)</p></body></html>")) self.python_path_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Path to Python modules (e.g. /Applications/QGIS.app/Contents/MacOS/lib/python3.8/site-packages).<br/>Multiple paths can be entered separated by ;</p><p>Restart is required.</p></body></html>")) self.gdal_path_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Path to the GDAL directory containing tools such as gdal_translate and gdalwarp (e.g. /usr/bin)</p></body></html>")) self.label_211.setText(_translate("SemiAutomaticClassificationPlugin", "External programs")) self.sound_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the sound when the process is finished</p></body></html>")) self.sound_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Play sound when finished")) self.virtual_raster_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, create virtual rasters for certain temporary files</p></body></html>")) self.virtual_raster_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use virtual raster for temp files")) self.label_45.setText(_translate("SemiAutomaticClassificationPlugin", "Calculation process")) self.raster_compression_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, a lossless compression is applied to rasters in order to save disk space</p></body></html>")) self.raster_compression_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Raster compression")) self.parallel_writing_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, the output raster is compared to output calculation to avoid writing errors. It could slightly slow the process.</p></body></html>")) self.parallel_writing_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Enable writing verification")) self.settings_tabWidget.setTabText(self.settings_tabWidget.indexOf(self.tabWidgetProcessing), _translate("SemiAutomaticClassificationPlugin", "Processing")) self.label_31.setText(_translate("SemiAutomaticClassificationPlugin", "C Name field")) self.Info_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the Class name field</p><p>[max 10 characters]</p></body></html>")) self.label_24.setText(_translate("SemiAutomaticClassificationPlugin", " Field names of training input")) self.ID_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the Class ID field name</p><p>[max 10 characters]</p></body></html>")) self.MID_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the Macroclass ID field name</p><p>[max 10 characters]</p></body></html>")) self.label_10.setText(_translate("SemiAutomaticClassificationPlugin", "C ID field")) self.MCInfo_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Set the Macroclass name field</p><p>[max 10 characters]</p></body></html>")) self.label_17.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID field")) self.label_46.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name field")) self.reset_field_names_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.reset_field_names_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_21.setText(_translate("SemiAutomaticClassificationPlugin", " ROI style")) self.change_color_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Select temporary ROI color</p></body></html>")) self.label_22.setText(_translate("SemiAutomaticClassificationPlugin", "ROI color")) self.transparency_Label.setText(_translate("SemiAutomaticClassificationPlugin", "Transparency")) self.transparency_Slider.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Change temporary ROI transparency</p></body></html>")) self.reset_color_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.reset_color_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_68.setText(_translate("SemiAutomaticClassificationPlugin", " Variable name")) self.variable_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Variable name for expressions</p></body></html>")) self.variable_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "raster")) self.label_69.setText(_translate("SemiAutomaticClassificationPlugin", " Variable name for expressions (tab Reclassification and Edit raster)")) self.reset_variable_name_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.reset_variable_name_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_95.setText(_translate("SemiAutomaticClassificationPlugin", " Dock")) self.download_news_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, news about the SCP are downloaded on startup and displayed in Dock</p></body></html>")) self.download_news_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Download news on startup")) self.label_76.setText(_translate("SemiAutomaticClassificationPlugin", " Project")) self.reset_group_name_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p><span >Reset</span></p></body></html>")) self.reset_group_name_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.virtual_raster_load_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>If checked, an RGB composite of the active band set is created when a previous project is loaded</p></body></html>")) self.virtual_raster_load_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create RGB composite of band set when a project is loaded")) self.label_75.setText(_translate("SemiAutomaticClassificationPlugin", "Group name")) self.group_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Group name</p></body></html>")) self.group_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "Class_temp_group")) self.settings_tabWidget.setTabText(self.settings_tabWidget.indexOf(self.tabWidgetInterface), _translate("SemiAutomaticClassificationPlugin", "Interface")) self.log_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Enable/Disable the Log of events</p></body></html>")) self.log_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Record events in a Log file")) self.exportLog_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Export the Log file</p></body></html>")) self.exportLog_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.clearLog_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Clear the Log file content</p></body></html>")) self.clearLog_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_30.setText(_translate("SemiAutomaticClassificationPlugin", " Log file")) item = self.log_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Date")) item = self.log_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Function")) item = self.log_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "Message")) self.test_dependencies_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><p>Test dependencies</p></body></html>")) self.label_42.setText(_translate("SemiAutomaticClassificationPlugin", "Test dependencies")) self.label_43.setText(_translate("SemiAutomaticClassificationPlugin", " Test")) self.settings_tabWidget.setTabText(self.settings_tabWidget.indexOf(self.tabWidgetDebug), _translate("SemiAutomaticClassificationPlugin", "Debug")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_Settings), _translate("SemiAutomaticClassificationPlugin", "Settings")) self.plugin_label.setText(_translate("SemiAutomaticClassificationPlugin", "Semi-Automatic Classification Plugin")) self.textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Sans\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\';\">Developed by </span><a href=\"http://www.researchgate.net/profile/Luca_Congedo\"><span style=\" font-family:\'Droid Sans\'; text-decoration: underline; color:#0057ae;\">Luca Congedo</span></a><span style=\" font-family:\'Droid Sans\';\"> (ing.congedoluca@gmail.com), the </span><span style=\" font-family:\'Droid Sans\'; font-weight:600;\">Semi-Automatic Classification Plugin</span><span style=\" font-family:\'Droid Sans\';\"> (SCP) is a free open source plugin for QGIS that allows for the semi-automatic classification (also supervised classification) of remote sensing images.</span></p>\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\';\">It provides several tools for the download of free images, the preprocessing, the postprocessing, and the raster calculation.</span></p>\n" "<p align=\"justify\" style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\';\">For more information and tutorials visit the official site </span><span style=\" font-family:\'Droid Sans\'; font-weight:600;\">From GIS to Remote Sensing.</span></p>\n" "<p align=\"center\" style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><img src=\":/plugins/semiautomaticclassificationplugin/icons/fromGIStoRS.png\" /><a href=\"https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html?spref=sacp\"><span style=\" font-family:\'Droid Sans\'; font-size:24pt; text-decoration: underline; color:#0000ff;\">From GIS to Remote Sensing</span></a></p>\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:9pt;\"><br />Please join the </span><a href=\"https://www.facebook.com/groups/SemiAutomaticClassificationPlugin\"><span style=\" font-family:\'Droid Sans\'; font-size:9pt; text-decoration: underline; color:#0057ae;\">Semi-Automatic Classification Plugin group on Facebook</span></a><span style=\" font-size:9pt;\"> or </span><a href=\"https://github.com/semiautomaticgit/SemiAutomaticClassificationPlugin/discussions\"><span style=\" font-size:9pt; text-decoration: underline; color:#0000ff;\">GitHub discussions</span></a></p>\n" "<p style=\"-qt-paragraph-type:empty; margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px; font-size:9pt;\"><br /></p>\n" "<p align=\"justify\" style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-style:italic;\">This plugin requires the installation of GDAL, OGR, Numpy, SciPy, and Matplotlib (already bundled with QGIS).</span></p>\n" "<p align=\"justify\" style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-style:italic;\">Some tools require the additional installation of: ESA SNAP</span></p>\n" "<hr />\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-weight:600;\">How to cite:</span></p>\n" "<p align=\"justify\" style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\';\">Congedo, Luca, (2021). Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. Journal of Open Source Software, 6(64), 3172, </span><a href=\"https://doi.org/10.21105/joss.03172\"><span style=\" text-decoration: underline; color:#0000ff;\">https://doi.org/10.21105/joss.03172</span></a></p>\n" "<hr />\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\"><br />The Semi-Automatic Classification Plugin is developed by Luca Congedo.</span></p>\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\">Translators:</span></p>\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\">Language: Author<br /></span></p>\n" "<p align=\"justify\" style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\">Semi-Automatic Classification Plugin is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 of the License.</span></p>\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\">Semi-Automatic Classification Plugin is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.</span></p>\n" "<p style=\" margin-top:12px; margin-bottom:12px; margin-left:0px; margin-right:0px; -qt-block-indent:0; text-indent:0px;\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\">See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with Semi-Automatic Classification Plugin. If not, see <</span><a href=\"http://www.gnu.org/licenses/\"><span style=\" font-family:\'Droid Sans\'; font-size:8pt; text-decoration: underline; color:#0000ff;\">http://www.gnu.org/licenses/</span></a><span style=\" font-family:\'Droid Sans\'; font-size:8pt;\">>.</span></p></body></html>")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_About), _translate("SemiAutomaticClassificationPlugin", "About")) self.main_tabWidget.setTabText(self.main_tabWidget.indexOf(self.tool_tab), _translate("SemiAutomaticClassificationPlugin", "Tool")) self.main_tabWidget.setTabText(self.main_tabWidget.indexOf(self.help_tab), _translate("SemiAutomaticClassificationPlugin", "Help")) from . import resources_rc	semiautomaticgit/SemiAutomaticClassificationPlugin	ui/ui_semiautomaticclassificationplugin.py	Python	gpl-3.0	841,489	[ "VisIt" ]	67be0e08edb3b7528cc32326b3247b48a02507661e0af18d4a74ce0f927cc464
#!/usr/bin/env python # Author: Andrew Jewett (jewett.aij at g mail) # http://www.chem.ucsb.edu/~sheagroup # License: 3-clause BSD License (See LICENSE.TXT) # Copyright (c) 2011, Regents of the University of California # All rights reserved. man_page_text = """ nbody_by_type.py reads a LAMMPS data file (or an excerpt of a LAMMPS) data file containing bonded many-body interactions by atom type (and bond type), and generates a list of additional interactions in LAMMPS format consistent with those type (to the standard out). Typical Usage: nbody_by_type.py X < old.data > new.data --or-- nbody_by_type.py X \\ -atoms atoms.data \\ -bonds bonds.data \\ -nbody X.data \\ -nbodybytype X_by_type.data \\ > new_X.data In both cases "X" denotes the interaction type, which is either "Angles", "Dihedrals", or "Impropers". (Support for other interaction types can be added by the user. See below.) -------- Example 1 ------- nbody_by_type.py X < old.data > new.data In this example, nbody_by_type.py reads a LAMMPS data file "orig.data", and extracts the relevant section ("Angles", "Dihedrals", or "Impropers"). It also looks a section named "X By Type", (eg. "Angles By type", "Impropers By type", "Impropers By type") which contains a list of criteria for automatically defining additional interactions of that type. For example, this file might contain: Angle By Type 7 1 2 1 * * 8 2 2 * * * 9 3 4 3 * * The first column is an interaction type ID. The next 3 columns are atom type identifiers. The final 2 columns are bond type identifiers. The * is a wildcard symbol indicating there is no preference for bond types in this example. (Optionally, regular expressions can also be used to define a type match, by enclosing the atom or bond type in / slashes.) The first line tells us to that there should be a 3-body "Angle" interaction of type "7" whenever an atom of type 1 is bonded to an atom of type "2", which is bonded to another atom of type "1" again. The second line tells us that an angle is defined whenever three atoms are bonded together and the first two are of type "2". (Redundant angle interactions are filtered.) New interactions are created for every group of bonded atoms which match these criteria if they are bonded together in the relevant way for that interaction type (as determined by nbody_X.py), and printed to the standard output. For example, suppose you are automatically generating 3-body "Angle" interactions using: nbody_by_type Angles < old.data > new.data The file "new.data" will be identical to "old.data", however the "Angles By Type" section will be deleted, and the following lines of text will be added to the "Angles" section: 394 7 5983 5894 5895 395 7 5984 5895 5896 396 7 5985 5896 5897 : : : : : 847 9 14827 14848 14849 The numbers in the first column are counters which assign a ID to every interaction of that type, and start where the original "Angles" data left off (New angle ID numbers do not overlap with old ID numbers). The text in the second column ("7", "9", ...) matches the text from the first column of the "Angle By Type" section of the input file. -------- Example 2 ------- nbody_by_type.py X \\ -atoms atoms.data \\ -bonds bonds.data \\ -nbody X.data \\ -nbodybytype X_by_type.data \\ -prefix "SOMESTRING" -suffix "ANOTHERSTRING" \\ > new_X.data In particular, for Angle interactions: nbody_by_type.py Angles \\ -atoms atoms.data \\ -bonds bonds.data \\ -nbody angles.data \\ -nbodybytype angles_by_type.data \\ > new_Angles.data When run this way, nbody_by_type.py behaves exactly the same way as in Example 1, however only the lines of text corresponding to the new generated interactions are printed, (not the entire data file). Also note, that when run this way, nbody_by_type.py does not read the LAMMPS data from the standard input. Instead, it reads each section of the data file from a different file indicated by the arguments following the "-atoms", "-bonds", "-nbody", and "-nbodybytype" flags. "Angles" is a 3-body interaction style. So when run this way, nbody_by_type.py will create a 5 (=3+2) column file (new_Angles.data). Note: the atom, bond and other IDs/types in need not be integers. Note: This program must be distributed with several python modules, including: nbody_Angles.py, nbody_Dihedrals.py, and nbody_Impropers.py. These contain bond definitions for angular, dihedral, and improper interactions. (In case any new interaction types are ever added to LAMMPS, with only a few lines of python it is easy to edit to define new bonded interaction types by supplying new "nbody_X.py" python module. Refer to the modules listed above for examples.) Note: Optional "-prefix" and "-suffix" arguments can be included to decorate the interaction IDs (first column). For example, -prefix "auto_" and -suffix "_angle", causes "new_Angles.data" to contain the following text: auto_394_angle 7 5983 5894 5895 auto_395_angle 7 5984 5895 5896 auto_396_angle 7 5985 5896 5897 : : : : : auto_847_angle 9 14827 14848 14849 """ g_program_name = __file__.split('/')[-1] # = 'nbody_by_type.py' g_date_str = '2017-2-06' g_version_str = '0.20.0' bond_pattern_module_name = "" import os import sys sys.path.append(os.getcwd()) import importlib if sys.version < '2.6': raise InputError('Error: Using python ' + sys.version + '\n' ' Alas, you must upgrade to a newer version of python (2.6 or later).') elif sys.version < '2.7': sys.stderr.write('--------------------------------------------------------\n' '----------------- WARNING: OLD PYTHON VERSION ----------\n' ' This program is untested on your python version (' + sys.version + ').\n' ' PLEASE LET ME KNOW IF THIS PROGRAM CRASHES (and upgrade python).\n' ' -Andrew 2013-10-25\n' '--------------------------------------------------------\n' '--------------------------------------------------------\n') from ordereddict import OrderedDict else: from collections import OrderedDict try: from .extract_lammps_data import * from .nbody_by_type_lib import GenInteractions_str from .ttree_lex import * from .lttree_styles import AtomStyle2ColNames, ColNames2AidAtypeMolid except (ImportError, SystemError, ValueError): from extract_lammps_data import * from nbody_by_type_lib import GenInteractions_str from ttree_lex import * from lttree_styles import AtomStyle2ColNames, ColNames2AidAtypeMolid def GenInteractions_lines(lines_atoms, lines_bonds, lines_nbody, lines_nbodybytype, atom_style, g_bond_pattern, canonical_order, # function to sort atoms and bonds prefix='', suffix='', report_progress=False, check_undefined=False): column_names = AtomStyle2ColNames(atom_style) i_atomid, i_atomtype, i_molid = ColNames2AidAtypeMolid(column_names) atomids_str = [] atomtypes_str = [] for iv in range(0, len(lines_atoms)): line = lines_atoms[iv].strip() if '#' in line: icomment = line.find('#') line = (line[:icomment]).strip() if len(line) > 0: tokens = SplitQuotedString(line) if ((len(tokens) <= i_atomid) or (len(tokens) <= i_atomtype)): raise(InputError('Error not enough columns on line ' + str(iv + 1) + ' of \"Atoms\" section.')) tokens = SplitQuotedString(line) atomids_str.append(EscCharStrToChar(tokens[i_atomid])) atomtypes_str.append(EscCharStrToChar(tokens[i_atomtype])) bondids_str = [] bondtypes_str = [] bond_pairs = [] for ie in range(0, len(lines_bonds)): line = lines_bonds[ie].strip() if '#' in line: icomment = line.find('#') line = (line[:icomment]).strip() if len(line) > 0: tokens = SplitQuotedString(line) if len(tokens) < 4: raise(InputError('Error not enough columns on line ' + str(ie + 1) + ' of \"Bonds\" section.')) bondids_str.append(EscCharStrToChar(tokens[0])) bondtypes_str.append(EscCharStrToChar(tokens[1])) bond_pairs.append((EscCharStrToChar(tokens[2]), EscCharStrToChar(tokens[3]))) typepattern_to_coefftypes = [] for i in range(0, len(lines_nbodybytype)): line = lines_nbodybytype[i].strip() if '#' in line: icomment = line.find('#') line = (line[:icomment]).strip() if len(line) > 0: tokens = SplitQuotedString(line) if ((len(tokens) != 1 + g_bond_pattern.GetNumVerts()) and (len(tokens) != 1 + g_bond_pattern.GetNumVerts() + g_bond_pattern.GetNumEdges())): raise(InputError('Error: Wrong number of columns in \"By Type\" section of data file.\n' 'Offending line:\n' + '\"' + line + '\"\n' 'Expected either ' + str(1 + g_bond_pattern.GetNumVerts()) + ' or ' + str(1 + g_bond_pattern.GetNumVerts() + g_bond_pattern.GetNumEdges()) + ' colunms.')) coefftype = EscCharStrToChar(tokens[0]) typepattern = [] for typestr in tokens[1:]: if ((len(typestr) >= 2) and (typestr[0] == '/') and (typestr[-1] == '/')): regex_str = typestr[1:-1] typepattern.append(re.compile(regex_str)) else: typepattern.append(EscCharStrToChar(typestr)) # If the user neglected to specify the bond types, assume '' if len(tokens) == 1 + g_bond_pattern.GetNumVerts(): typepattern += [''] * g_bond_pattern.GetNumEdges() typepattern_to_coefftypes.append([typepattern, coefftype]) coefftype_to_atomids_str = GenInteractions_str(bond_pairs, g_bond_pattern, typepattern_to_coefftypes, canonical_order, atomids_str, atomtypes_str, bondids_str, bondtypes_str, report_progress, check_undefined) lines_nbody_new = [] for coefftype, atomids_list in coefftype_to_atomids_str.items(): for atomids_found in atomids_list: n = len(lines_nbody) + len(lines_nbody_new) + 1 line = prefix + str(n) + suffix + ' ' + \ coefftype + ' ' + (' '.join(atomids_found)) + '\n' lines_nbody_new.append(line) return lines_nbody_new def GenInteractions_files(lines_data, src_bond_pattern, fname_atoms, fname_bonds, fname_nbody, fname_nbodybytype, section_name, section_name_bytype, atom_style, prefix='', suffix='', report_progress=False, check_undefined=False): if fname_atoms == None: lines_atoms = [ line for line in ExtractDataSection(lines_data, 'Atoms')] else: try: f = open(fname_atoms, 'r') except: sys.stderr.write('Error: Unable to open file \"' + fname_atoms + '\" for reading.\n') sys.exit(-1) lines_atoms = [line for line in f.readlines() if ((len(line.strip()) > 0) and (line.strip()[0] != '#'))] f.close() if fname_bonds == None: lines_bonds = [ line for line in ExtractDataSection(lines_data, 'Bonds')] else: try: f = open(fname_bonds, 'r') except IOError: sys.stderr.write('Error: Unable to open file \"' + fname_bonds + '\" for reading.\n') sys.exit(-1) lines_bonds = [line for line in f.readlines() if ((len(line.strip()) > 0) and (line.strip()[0] != '#'))] f.close() if fname_nbody == None: lines_nbody = [line for line in ExtractDataSection( lines_data, section_name)] else: try: f = open(fname_nbody, 'r') lines_nbody = [line for line in f.readlines() if ((len(line.strip()) > 0) and (line.strip()[0] != '#'))] f.close() except IOError: #sys.stderr.write(' (omitting optional file \"'+fname_nbody+'\")\n') lines_nbody = [] if fname_nbodybytype == None: lines_nbodybytype = [line for line in ExtractDataSection(lines_data, section_name_bytype)] else: try: f = open(fname_nbodybytype, 'r') except: sys.stderr.write('Error: Unable to open file \"' + fname_nbodybytype + '\" for reading.\n') sys.exit(-1) lines_nbodybytype = [line for line in f.readlines() if((len(line.strip()) > 0)and(line.strip()[0] != '#'))] f.close() # search locations package_opts = [[src_bond_pattern, __package__], ['nbody_alt_symmetry.'+src_bond_pattern, __package__]] if __package__: for i in range(0, len(package_opts)): package_opts[i][0] = '.' + package_opts[i][0] package_opts.append(['.'+src_bond_pattern, __package__+'.nbody_alt_symmetry']) g = None for name, pkg in package_opts: try: g = importlib.import_module(name, pkg) break except (ImportError, SystemError, ValueError): pass if g is None: sys.stderr.write('Error: Unable to locate file \"' + src_bond_pattern + '.py\"\n' ' (Did you mispell the file name?\n' ' Check the \"nbody_alt_symmetry/\" directory.)\n') sys.exit(-1) return GenInteractions_lines(lines_atoms, lines_bonds, lines_nbody, lines_nbodybytype, atom_style, g.bond_pattern, g.canonical_order, prefix, suffix, report_progress, check_undefined) def main(): sys.stderr.write(g_program_name + ' v' + g_version_str + ' ' + g_date_str + ' ') if sys.version < '3': sys.stderr.write(' (python version < 3)\n') else: sys.stderr.write('\n') try: fname_atoms = None fname_bonds = None fname_nbody = None fname_nbodybytype = None atom_style = 'full' prefix = '' suffix = '' check_undefined = False argv = [arg for arg in sys.argv] if len(argv) == 1: raise InputError('Error: Missing argument required.\n' ' The \"' + g_program_name + '\" program requires an argument containing the\n' ' name of a section from a LAMMPS data file storing bonded interactions.\n' ' (For example: "Angles", "Dihedrals", or "Impropers".)\n' #' Note: The first letter of each section is usually capitalized.)\n' '\n' '--------------- general documentation -------------\n' '\n' + man_page_text + '\n') section_name = '' # (This will be replaced later.) section_name_bytype = '' # (This will be replaced later.) # Loop over the remaining arguments not processed yet. # These arguments are specific to the lttree.py program # and are not understood by ttree.py: i = 1 while i < len(argv): #sys.stderr.write('argv['+str(i)+'] = \"'+argv[i]+'\"\n') if ((argv[i].lower() == '-?') or (argv[i].lower() == '--?') or (argv[i].lower() == '-help') or (argv[i].lower() == '-help')): if i + 1 >= len(argv): sys.stdout.write(man_page_text + '\n') sys.exit(0) elif argv[i].lower() == '-atoms': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a file name containing lines of\n' ' text which might appear in the "Atoms" section of a LAMMPS data file.\n') fname_atoms = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-bonds': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a file name containing lines of\n' ' text which might appear in the "Bonds" section of a LAMMPS data file.\n') fname_bonds = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-nbody': if i + 1 >= len(argv): raise InputError( 'Error: ' + argv[i] + ' flag should be followed by a file name\n') # raise InputError('Error: '+argv[i]+' flag should be followed by a file name containing lines of\n' # ' text which might appear in the "'+section_name+' section of a LAMMPS data file.\n') fname_nbody = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-nbodybytype': if i + 1 >= len(argv): raise InputError( 'Error: ' + argv[i] + ' flag should be followed by a file name\n') # raise InputError('Error: '+argv[i]+' flag should be followed by a file name containing\n' # ' text which might appear in the "'+section_name+' By Type" section\n' # ' of a LAMMPS data file.\n') fname_nbodybytype = argv[i + 1] del(argv[i:i + 2]) elif ((argv[i].lower() == '-atom-style') or (argv[i].lower() == '-atom_style')): if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a an atom_style name.\n' ' (Or single quoted string which includes a space-separated\n' ' list of column names.)\n') atom_style = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-prefix': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a prefix string\n' ' (a string you want to appear to the left of the integer\n' ' which counts the bonded interactions you have generated.)\n') prefix = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-suffix': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a suffix string\n' ' (a string you want to appear to the right of the integer\n' ' which counts the bonded interactions you have generated.)\n') prefix = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-subgraph': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by the name of a python file\n' ' containing the definition of the subgraph you are searching for\n' ' and it\'s symmetry properties.\n' ' (See nbody_Dihedrals.py for example.)\n') bond_pattern_module_name = argv[i + 1] # If the file name ends in ".py", then strip off this suffix. # The next line does not work. Too lazy to care why. # bond_pattern_module_name=bond_pattern_module_name.rstrip('.py') # Do this instead pc = bond_pattern_module_name.rfind('.py') if pc != -1: bond_pattern_module_name = bond_pattern_module_name[0:pc] del(argv[i:i + 2]) elif argv[i].lower() == '-section': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by the name of the LAMMPS\n' ' Data section describing the type of interaction being generated.\n' ' (For example: \"Angles\", \"Dihedrals\", \"Impropers\", etc...)\n') section_name = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-sectionbytype': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by the name of the\n' ' write_once(\"???? By Type\") section describing how to create the\n' ' interactions. (For example: \"Angles By Type\", \"Dihedrals By Type\",\n' ' \"Impropers By Type\", etc... Note that this argument\n' ' will contain spaces, so surround it with quotes.)\n') section_name_bytype = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-checkff': check_undefined = True del(argv[i:i + 1]) elif argv[i][0] == '-': raise InputError('Error(' + g_program_name + '):\n' 'Unrecogized command line argument \"' + argv[i] + '\"\n') else: i += 1 # if len(argv) == 1: # raise InputError('Error: Missing argument required.\n' # ' The \"'+g_program_name+'\" program requires an argument containing the\n' # ' name of a section from a LAMMPS data file storing bonded interactions.\n' # ' (For example: "Angles", "Dihedrals", or "Impropers".)\n') # #' Note: The first letter of each section is usually capitalized.)\n' if len(argv) == 1: pass elif len(argv) == 2: section_name = argv[1] section_name_bytype = section_name + ' By Type' # default bond_pattern_module name if bond_pattern_module_name == "": # <--if not set by user bond_pattern_module_name = 'nbody_' + section_name del(argv[1:2]) else: # if there are more than 2 remaining arguments, problem_args = ['\"' + arg + '\"' for arg in argv[1:]] raise InputError('Syntax Error(' + g_program_name + '):\n\n' ' Problem with argument list.\n' ' The remaining arguments are:\n\n' ' ' + (' '.join(problem_args)) + '\n\n' ' (The actual problem may be earlier in the argument list.)\n') if ((section_name == '') or (section_name_bytype == '') or (bond_pattern_module_name == '')): raise InputError('Syntax Error(' + g_program_name + '):\n\n' ' You have not defined the following arguments:\n' ' -section name\n' ' -sectionbytype namebytype\n' ' -subgraph pythonfile.py\n') # ------------ Done parsing argument list ---------- if (fname_atoms or fname_bonds or fname_nbody or fname_nbodybytype): output_full_DATA_file = False lines_data = [] else: output_full_DATA_file = True lines_data = sys.stdin.readlines() # Calculate the interactions and generate a list of lines of text lines_new_interactions = \ GenInteractions_files(lines_data, bond_pattern_module_name, fname_atoms, fname_bonds, fname_nbody, fname_nbodybytype, section_name, section_name_bytype, atom_style, prefix, suffix, True, check_undefined) # Print this text to the standard out. # Question: Do we write out the entire DATA file, # or just the portion that was generated by this program? if not output_full_DATA_file: # ...then only print out the interactions which were generated # by this program, omitting any lines from the original data file: # (This is the way I usually run this program.) for line in lines_new_interactions: sys.stdout.write(line) else: # ...then print out the entire data file, deleting the "By Type" # section, and adding the generated lines of text to the # corresponding # If present, update the interaction counter at the beginning # of the LAMMPS data file. (For example, if if 100 new "Angles" # interactions were generated, replace "2 Angles" with "102 Angles") # for i in range(0, len(lines_data)): line = lines_data[i].strip() tokens = SplitQuotedString(line) # updating the interaction counter if ((len(tokens) == 2) and (tokens[1] == (section_name).lower())): tokens[0] = str(int(tokens[0]) + len(lines_new_interactions)) lines_data[i] = ' '.join(tokens) + '\n' # stop when you come to a section header elif line in lammps_data_sections: #"lammps_data_sections" is defined in "extract_lammps_data.py" break # locate the appropriate section of the data file # (storing the type of interactions we just created) i_nbody_a, i_nbody_b = \ FindDataSection(lines_data, section_name) if i_nbody_a == -1: if len(lines_new_interactions) > 0: # If not found, create a new section at the end of the file, # containing a section name followed by the list of lines lines_data += ['\n', section_name + '\n', '\n'] + \ lines_new_interactions + ['\n'] else: # Insert the new lines into the existing section lines_data[i_nbody_b:i_nbody_b] = lines_new_interactions # Figure out where the "By Type" section is located # (so we skip over it) i_bytype_a, i_bytype_b = \ FindDataSection(lines_data, section_name_bytype) in_bytype_section = False for i in range(0, len(lines_data)): line = lines_data[i].strip() # Omit all lines of text in the 'By Type' section (including the # header and commments or blank lines which immediately follow # it.) if line == section_name_bytype: in_bytype_section = True elif i == i_bytype_b: in_bytype_section = False if not in_bytype_section: sys.stdout.write(lines_data[i]) except (ValueError, InputError) as err: sys.stderr.write('\n' + str(err) + '\n') sys.exit(-1) return if __name__ == '__main__': main()	smsaladi/moltemplate	moltemplate/nbody_by_type.py	Python	bsd-3-clause	30,585	[ "LAMMPS" ]	fd6035b4c399d258841e8f670a900cfc9dfd4c7e1e9510eb84222f416d182e67
import os from gpaw import GPAW, restart from ase import Atoms from gpaw.test import equal from math import sqrt import numpy as np modes = ['gpw'] try: import h5py modes.append('hdf5') except ImportError: pass d = 3.0 atoms = Atoms('Na3', positions=[( 0, 0, 0), ( 0, 0, d), ( 0, d*sqrt(3./4.), d/2.)], magmoms=[1.0, 1.0, 1.0], cell=(3.5, 3.5, 4.+2/3.), pbc=True) # Only a short, non-converged calcuation conv = {'eigenstates': 1e-2, 'energy':2e-1, 'density':1e-1} calc = GPAW(h=0.30, nbands=3, convergence=conv) atoms.set_calculator(calc) e0 = atoms.get_potential_energy() niter0 = calc.get_number_of_iterations() f0 = atoms.get_forces() m0 = atoms.get_magnetic_moments() eig00 = calc.get_eigenvalues(spin=0) eig01 = calc.get_eigenvalues(spin=1) # Write the restart file(s) for mode in modes: calc.write('tmp.%s' % mode) del atoms, calc # Try restarting from all the files for mode in modes: atoms, calc = restart('tmp.%s' % mode) e1 = atoms.get_potential_energy() try: # number of iterations needed in restart niter1 = calc.get_number_of_iterations() except: pass f1 = atoms.get_forces() m1 = atoms.get_magnetic_moments() eig10 = calc.get_eigenvalues(spin=0) eig11 = calc.get_eigenvalues(spin=1) print e0, e1 equal(e0, e1, 1e-10) print f0, f1 for ff0, ff1 in zip(f0, f1): err = np.linalg.norm(ff0-ff1) assert err <= 1e-10 print m0, m1 for mm0, mm1 in zip(m0, m1): equal(mm0, mm1, 1e-10) print 'A',eig00, eig10 for eig0, eig1 in zip(eig00, eig10): equal(eig0, eig1, 1e-10) print 'B',eig01, eig11 for eig0, eig1 in zip(eig01, eig11): equal(eig0, eig1, 1e-10) energy_tolerance = 0.0002 niter_tolerance = 0 equal(e0, -0.52198, energy_tolerance) equal(niter0, 6, niter_tolerance) equal(e1, -0.52198, energy_tolerance)	qsnake/gpaw	gpaw/test/restart.py	Python	gpl-3.0	1,993	[ "ASE", "GPAW" ]	17ba3efe1c985142c070950707458a585896b4e2b80e1a0c46c6cea70e9d53a7
#!/usr/bin/env python # -- coding: utf-8 -- # (c) 2012 Michal Kalewski <mkalewski at cs.put.poznan.pl> # # This file is a part of the Simple Network Simulator (sim2net) project. # USE, MODIFICATION, COPYING AND DISTRIBUTION OF THIS SOFTWARE IS SUBJECT TO # THE TERMS AND CONDITIONS OF THE MIT LICENSE. YOU SHOULD HAVE RECEIVED A COPY # OF THE MIT LICENSE ALONG WITH THIS SOFTWARE; IF NOT, YOU CAN DOWNLOAD A COPY # FROM HTTP://WWW.OPENSOURCE.ORG/. # # For bug reports, feature and support requests please visit # <https://github.com/mkalewski/sim2net/issues>. """ This package contains miscellaneous utility modules and classes. """ __docformat__ = 'reStructuredText' __all__ = ['logger', 'randomness', 'verification']	mkalewski/sim2net	sim2net/utility/__init__.py	Python	mit	728	[ "VisIt" ]	49b99d9de0234e377c759063a39809ee521f369092b1270de7eb4906e7ba0a9b
#!/usr/bin/python # -- coding: utf-8 -- # # --- BEGIN_HEADER --- # # tail - [insert a few words of module description on this line] # Copyright (C) 2003-2009 The MiG Project lead by Brian Vinter # # This file is part of MiG. # # MiG is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # MiG is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # -- END_HEADER --- # import cgi import cgitb cgitb.enable() from shared.functionality.tail import main from shared.cgiscriptstub import run_cgi_script run_cgi_script(main)	heromod/migrid	mig/cgi-bin/tail.py	Python	gpl-2.0	1,096	[ "Brian" ]	35c1a80cdf3cdf2f65ed0b700bce4192ff847f506b471b5e68068faf1a3ab094
# Python standard modules import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.mlab as mlab from mpl_toolkits.mplot3d import Axes3D import seaborn as sns import statsmodels.api as sm import matplotlib.colors as mcolors import matplotlib as mpl from matplotlib.pylab import * from mpl_toolkits.axes_grid1 import host_subplot resultsdf_plot1 = pd.read_excel('PLR_plots.xlsx', 'plot1') # Results WindLevel = resultsdf_plot1['wind_pen'].tolist() Energycost = resultsdf_plot1['cost_energy'].tolist() EnergycostWind = resultsdf_plot1['cost_wind'].tolist() PLRcost = resultsdf_plot1['cost_plr'].tolist() Fixedcost = resultsdf_plot1['mm_fixedcost'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig = plt.figure(1) width = 0.35 ind = np.arange(len(WindLevel)) p3 = plt.bar(ind, Energycost, width, color=sns.xkcd_rgb["windows blue"], label='$Cost\ of\ Energy$') p2 = plt.bar(ind, EnergycostWind, width, color=sns.xkcd_rgb["medium green"],bottom=Energycost, label='$Cost\ of\ Wind$') new = [x + y for x, y in zip(Energycost, EnergycostWind)] p1 = plt.bar(ind, Fixedcost, width, color=sns.xkcd_rgb["amber"],bottom=new, label='$Variable\ and\ Fixed\ Cost\ Not\ Covered$') new = [x + y for x, y in zip(new, Fixedcost)] p4 = plt.bar(ind, PLRcost, width, color=sns.xkcd_rgb["pale red"],bottom=new, label='$Cost\ of\ PLR$') plt.grid(True, linestyle='-', which='major', color='lightgray', alpha=0.5) plt.axis([-1, 10, 0, 2.5]) plt.ylabel('$Cost\ (M$€$/day)$') plt.xlabel('$Average\ Wind\ Penetration\ Level\ ($%$)$') plt.xticks(ind + width/2., ('0', '9.5', '19', '28', '38', '47', '56', '66','70','77')) plt.yticks(np.arange(0, 3, 0.5)) plt.legend(loc='upper center', bbox_to_anchor=(.5, 1.15), ncol=2, fancybox=True, shadow=True) axes = plt.gca() axes.set_axis_bgcolor('whitesmoke') # plt.savefig('SEpeakloadreserve.pdf') plt.show() resultsdf_plot6 = pd.read_excel('PLR_plots.xlsx', 'plot6') # Results WindLevel = resultsdf_plot6['wind_pen'].tolist() PLR20 = resultsdf_plot6['PLR20'].tolist() PLR15 = resultsdf_plot6['PLR15'].tolist() PLR10 = resultsdf_plot6['PLR10'].tolist() PLR5 = resultsdf_plot6['PLR5'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig = plt.figure(1) plt.plot(WindLevel, PLR5, c=sns.xkcd_rgb["windows blue"],alpha=1, label = r"$5\;$%$\;PLR$") plt.plot(WindLevel, PLR10, c=sns.xkcd_rgb["medium green"],alpha=1, label = r"$10\;$%$\;PLR$") plt.plot(WindLevel, PLR15, c=sns.xkcd_rgb["amber"],alpha=1, label = r"$15\;$%$\;PLR$") plt.plot(WindLevel, PLR20, c=sns.xkcd_rgb["pale red"],alpha=1, label = r"$20\;$%$\;PLR$") plt.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5) plt.axis([0.0, 77, 0, 35]) plt.ylabel('$Number\ of\ Activations$') plt.xlabel('$Average\ Wind\ Penetration\ Level\ ($%$)$') plt.legend(loc='upper center', bbox_to_anchor=(.5, 1.10), ncol=4, fancybox=True, shadow=True) axes = plt.gca() axes.set_axis_bgcolor('whitesmoke') # plt.savefig('peakloadreserveNOA.pdf') plt.show() resultsdf_plot2 = pd.read_excel('PLR_plots.xlsx', 'plot2') resultsdf_plot3 = pd.read_excel('PLR_plots.xlsx', 'plot3') WindLevel = resultsdf_plot2['wind_pen'].tolist() Energycost5 = resultsdf_plot2['CostOfEnergy005'].tolist() Energycost10 = resultsdf_plot2['CostOfEnergy010'].tolist() Energycost15 = resultsdf_plot2['CostOfEnergy015'].tolist() Energycost20 = resultsdf_plot2['CostOfEnergy020'].tolist() MM5 = resultsdf_plot3['mm005'].tolist() MM10 = resultsdf_plot3['mm010'].tolist() MM15 = resultsdf_plot3['mm015'].tolist() MM20 = resultsdf_plot3['mm020'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') f0 = figure(num = 0, figsize = (8, 12))#, dpi = 300) f0.suptitle("$Peak\ Load\ Reserve\ Demand\ Increase$", fontsize=14) ax01 = subplot2grid((2, 2), (0, 0)) ax02 = subplot2grid((2, 2), (0, 1)) ax01.set_ylim(0,4) ax02.set_ylim(0,0.4) ax01.set_xlim(0,77) ax02.set_xlim(0,77) ax01.grid(True) ax02.grid(True) ax01.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax01.set_ylabel("$Total\ Cost\ (M$€$/day)$") ax02.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax02.set_ylabel("$Missing\ Money\ from\ Var.\ and\ Fixed\ Cost\ (M$€$/day)$") ax02.yaxis.tick_right() p011, = ax01.plot(WindLevel, Energycost5, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$5$%$\ PLR$") p012, = ax01.plot(WindLevel, Energycost10, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$10$%$\ PLR$") p013, = ax01.plot(WindLevel, Energycost15, c=sns.xkcd_rgb["amber"],alpha=1, label = "$15$%$\ PLR$") p014, = ax01.plot(WindLevel, Energycost20, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$20$%$\ PLR$") p021, = ax02.plot(WindLevel, MM5, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$5$%$\ PLR$") p022, = ax02.plot(WindLevel, MM10, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$10$%$\ PLR$") p023, = ax02.plot(WindLevel, MM15, c=sns.xkcd_rgb["amber"],alpha=1, label = "$15$%$\ PLR$") p024, = ax02.plot(WindLevel, MM20, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$20$%$\ PLR$") ax01.legend([p011,p012,p013,p014], [p011.get_label(),p012.get_label(),p013.get_label(),p014.get_label()]) legend = ax01.legend(loc='upper center', bbox_to_anchor=(1, 1.15), ncol=4, fancybox=True, shadow=True) ax01.set_axis_bgcolor('whitesmoke') ax02.set_axis_bgcolor('whitesmoke') figure(0) # f0.savefig('PLRdemandincrease.pdf') show() resultsdf_plot7 = pd.read_excel('PLR_plots.xlsx', 'plot7') resultsdf_plot8 = pd.read_excel('PLR_plots.xlsx', 'plot8') WindLevel = resultsdf_plot7['wind_pen'].tolist() MMHB = resultsdf_plot7['HighestBid'].tolist() MM500 = resultsdf_plot7['AP500'].tolist() MM1000 = resultsdf_plot7['AP1000'].tolist() MMHB2 = resultsdf_plot8['wind_pen'].tolist() MM150 = resultsdf_plot8['AP150'].tolist() MM250 = resultsdf_plot8['AP250'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') f0 = figure(num = 0, figsize = (8, 12)) ax01 = subplot2grid((2, 2), (0, 0)) ax02 = subplot2grid((2, 2), (0, 1)) ax01.set_title(r'$PLR\ demand\ 15\ \%$', y=1.12) ax02.set_title(r'$PLR\ demand\ 20\ \%$', y=1.12) ax01.set_ylim(0,0.4) ax02.set_ylim(0,0.3) ax01.set_xlim(0,77) ax02.set_xlim(0,77) ax01.grid(True) ax02.grid(True) ax01.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax01.set_ylabel("$Missing\ Money\ from\ Var.\ and\ Fixed\ Cost\ (M$€$/day)$") ax02.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax02.set_ylabel("$Missing\ Money\ from\ Var.\ and\ Fixed\ Cost\ (M$€$/day)$") p011, = ax01.plot(WindLevel, MMHB, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p012, = ax01.plot(WindLevel, MM500, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$500\ $€$/MWh$") p013, = ax01.plot(WindLevel, MM1000, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$1000\ $€$/MWh$") p021, = ax02.plot(WindLevel, MMHB2, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p022, = ax02.plot(WindLevel, MM150, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$150\ $€$/MWh$") p023, = ax02.plot(WindLevel, MM250, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$250\ $€$/MWh$") ax02.yaxis.tick_right() ax01.legend([p011,p012,p013], [p011.get_label(),p012.get_label(),p013.get_label()]) ax02.legend([p021,p022,p023], [p021.get_label(),p022.get_label(),p023.get_label()]) legend = ax01.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) legend = ax02.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) ax01.set_axis_bgcolor('whitesmoke') ax02.set_axis_bgcolor('whitesmoke') figure(0) # f0.savefig('PLRmissingmoney.pdf') show() resultsdf_plot9 = pd.read_excel('PLR_plots.xlsx', 'plot9') resultsdf_plot10 = pd.read_excel('PLR_plots.xlsx', 'plot10') WindLevel = resultsdf_plot9['wind_pen'].tolist() MMHB = resultsdf_plot9['HighestBid'].tolist() MM500 = resultsdf_plot9['AP500'].tolist() MM1000 = resultsdf_plot9['AP1000'].tolist() MMHB2 = resultsdf_plot10['HighestBid'].tolist() MM150 = resultsdf_plot10['AP150'].tolist() MM250 = resultsdf_plot10['AP250'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') f0 = figure(num = 0, figsize = (8, 12)) ax01 = subplot2grid((2, 2), (0, 0)) ax02 = subplot2grid((2, 2), (0, 1)) ax01.set_title(r'$PLR\ demand\ 15\ \%$', y=1.12) ax02.set_title(r'$PLR\ demand\ 20\ \%$', y=1.12) ax01.set_ylim(0,9) ax02.set_ylim(0,6.5) ax01.set_xlim(0,77) ax02.set_xlim(0,77) ax01.grid(True) ax02.grid(True) ax01.set_xlabel("$Total\ Wind\ Penetration\ Level\ ($%$)$") ax01.set_ylabel("$Total\ Cost\ (M$€$/day)$") ax02.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax02.set_ylabel("$Total\ Cost\ (M$€$/day)$") p011, = ax01.plot(WindLevel, MMHB, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p012, = ax01.plot(WindLevel, MM500, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$500\ $€$/MWh$") p013, = ax01.plot(WindLevel, MM1000, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$1000\ $€$/MWh$") p021, = ax02.plot(WindLevel, MMHB2, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p022, = ax02.plot(WindLevel, MM150, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$150\ $€$/MWh$") p023, = ax02.plot(WindLevel, MM250, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$250\ $€$/MWh$") ax02.yaxis.tick_right() ax01.legend([p011,p012,p013], [p011.get_label(),p012.get_label(),p013.get_label()]) ax02.legend([p021,p022,p023], [p021.get_label(),p022.get_label(),p023.get_label()]) legend = ax01.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) legend = ax02.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) ax01.set_axis_bgcolor('whitesmoke') ax02.set_axis_bgcolor('whitesmoke') figure(0) # f0.savefig('PLRenergycost.pdf') show() resultsdf_plot1 = pd.read_excel('PLR_plots.xlsx', 'plot11') WindLevel = resultsdf_plot1['wind_pen'].tolist() Energycost = resultsdf_plot1['cost_energy'].tolist() Fixedcost = resultsdf_plot1['relfixedcosts'].tolist() EnergycostPLR = resultsdf_plot1['cost_energyplr'].tolist() EnergycostWindPLR = resultsdf_plot1['cost_wind'].tolist() FixedcostPLR = resultsdf_plot1['relfixedcosts_plr'].tolist() PLRcost = resultsdf_plot1['cost_plr'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig = plt.figure(1) width = 0.35 ind = np.arange(len(WindLevel)) p3 = plt.bar(ind, EnergycostPLR, width, color=sns.xkcd_rgb["windows blue"], label='$Cost\ of\ Energy$') p3 = plt.bar(ind, EnergycostWindPLR, width, color=sns.xkcd_rgb["medium green"], bottom=EnergycostPLR,label='$Cost\ of\ Wind$') new = [x + y for x, y in zip(EnergycostPLR, EnergycostWindPLR)] p5 = plt.bar(ind, FixedcostPLR, width, color=sns.xkcd_rgb["amber"],bottom=new, label='$Variable\ and\ Fixed\ Cost\ Not\ Covered$') new = [x + y for x, y in zip(new, FixedcostPLR)] p4 = plt.bar(ind, PLRcost, width, color=sns.xkcd_rgb["pale red"],bottom=new, label='$Cost\ of\ PLR$') plt.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5) plt.axis([-1, 6, 0, 450]) plt.ylabel('$Cost\ (M$€$/day)$') plt.xlabel('$Average\ Wind\ Penetration\ Level\ ($%$)$') plt.xticks(ind + width/2., ('0', '19', '33', '43', '50', '55')) plt.yticks(np.arange(0, 475, 50)) plt.legend(loc='upper center', bbox_to_anchor=(.5, 1.15), ncol=2, fancybox=True, shadow=True) axes = plt.gca() axes.set_axis_bgcolor('whitesmoke') # plt.savefig('EUPLRBARPLOT.pdf') plt.show() resultsdf_plot1 = pd.read_excel('PLR_plots.xlsx', 'plot12') # Results Iteration = resultsdf_plot1['Iterations'].tolist() Nuclear = resultsdf_plot1['NuclearProd'].tolist() Coal = resultsdf_plot1['CoalProd'].tolist() Gas = resultsdf_plot1['GasProd'].tolist() Hydro = resultsdf_plot1['HydroProd'].tolist() Oil = resultsdf_plot1['OilProd'].tolist() CapReq = resultsdf_plot1['CapRequirement'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig, ax1 = plt.subplots() width = 0.35 # the width of the bars: can also be len(x) sequence ind = np.arange(len(Iteration)) p3 = ax1.bar(ind, Nuclear, width, color='olive', label='$Nuclear$') p4 = ax1.bar(ind, Coal, width, color='darkgreen',bottom=Nuclear, label='$Coal$') new = [x + y for x, y in zip(Nuclear, Coal)] p5 = ax1.bar(ind, Hydro, width, color='midnightblue',bottom=new, label='$Hydro$') new = [x + y for x, y in zip(new, Hydro)] p6 = ax1.bar(ind, Gas, width, color='blue',bottom=new, label='$Gas$') new = [x + y for x, y in zip(new, Gas)] p7 = ax1.bar(ind, Oil, width, color='silver',bottom=new, label='$Oil$') newxlist = (ind + width/2).tolist() Iteration = newxlist ax1.plot(Iteration, CapReq, linestyle='--', c='darkred',alpha=1, label = '$Cap.\ Req.$') ax1.grid(True, linestyle='-', which='major', color='lightgray', alpha=10000) ax1.set_xlim([-1,5]) ax1.set_ylim([0,4500]) ax1.set_ylabel('$Installed\ Capacity\ (MW)$') ax1.set_xlabel('$Iteration\ Number$') plt.xticks(ind + width/2., ('0', '1', '2', '3', '4')) ax1.legend(loc='upper center', bbox_to_anchor=(.5, 1.1), ncol=6, fancybox=True, shadow=True) ax1.set_axis_bgcolor('whitesmoke') # plt.savefig('PLR24busIteration.pdf') plt.show()	Thomsen22/MissingMoney	Plots/Peak Load Reserve Plots/plotsPLR.py	Python	gpl-3.0	13,539	[ "Amber" ]	8eeba3750c47fb27ad41bc92813e226e75697c0502a966e8b04a30a40259dc9b
import HTSeq import argparse import os.path from CommonFastaFunctions import Create_Blastdb from CommonFastaFunctions import LoadAlelleFasta from CommonFastaFunctions import LoadAlellicProfileGeneric from CommonFastaFunctions import WriteFasta from CommonFastaFunctions import runBlast from CommonFastaFunctions import runBlastParser from Bio.Blast.Applications import NcbiblastnCommandline def main(): parser = argparse.ArgumentParser(description="Given an ffn file, recovers the genes that are not paralogs and have a size bigger than the g parameter provided") parser.add_argument('-i', nargs='?', type=str, help='ffn file', required=True) parser.add_argument('-g', nargs='?', type=int, help='int minimum size', required=True) args = parser.parse_args() genes = args.i sizethresh = args.g gene_fp = HTSeq.FastaReader(genes) geneFile = os.path.abspath( genes ) Gene_Blast_DB_name = Create_Blastdb( geneFile, 1 ) geneF = os.path.splitext( geneFile )[0] blast_out_file = geneF + '.xml' # list of results - the output of the function resultsList = [] # ------------------------------ RUNNING BLAST ------------------------------ # cline = NcbiblastnCommandline(query=geneFile, db=Gene_Blast_DB_name, evalue=0.001, out=blast_out_file, outfmt=5) blast_records = runBlastParser(cline, blast_out_file, geneFile) paralogs=[] for blast_record in blast_records: try: alignment=blast_record.alignments[1] paralogs.append( alignment.hit_def) except: continue pathfiles=os.path.dirname(geneFile) pathfiles=pathfiles+"/" print pathfiles g_fp = HTSeq.FastaReader( genes ) removedparalogs=0 removedsize=0 for contig in g_fp: name = contig.name+" "+contig.descr if name not in paralogs: if int(len(contig.seq))>sizethresh: namefile=contig.name namefile=namefile.replace("\|","_") with open(pathfiles+namefile+".fasta", "wb") as f: f.write(">1\n"+contig.seq+"\n") else: removedsize+=1 else: print name removedparalogs+=1 print "Removed %s paralog genes" % str(removedparalogs) print "Removed %s because of size :" % str(removedsize) if __name__ == "__main__": main()	mickaelsilva/pythonscripts	AlleleCalling/ParalogRemove.py	Python	gpl-2.0	2,157	[ "BLAST", "HTSeq" ]	f83585c846b49b185a113d693e3bb14157435f965a52d0696133988828962194
# encoding: utf-8 import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding field 'Indicator.source' db.add_column('profiles_indicator', 'source', self.gf('django.db.models.fields.CharField')(default='U.S. Census Bureau', max_length=300, blank=True), keep_default=False) def backwards(self, orm): # Deleting field 'Indicator.source' db.delete_column('profiles_indicator', 'source') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'profiles.datadomain': { 'Meta': {'ordering': "['weight']", 'object_name': 'DataDomain'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicators': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.Indicator']", 'through': "orm['profiles.IndicatorDomain']", 'symmetrical': 'False'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100', 'db_index': 'True'}), 'subdomain_only': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'subdomains': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.DataDomain']", 'symmetrical': 'False', 'blank': 'True'}), 'weight': ('django.db.models.fields.PositiveIntegerField', [], {'default': '1'}) }, 'profiles.datapoint': { 'Meta': {'unique_together': "(('indicator', 'record', 'time'),)", 'object_name': 'DataPoint'}, 'change_from_time': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'datapoint_as_change_from'", 'null': 'True', 'to': "orm['profiles.Time']"}), 'change_to_time': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'datapoint_as_change_to'", 'null': 'True', 'to': "orm['profiles.Time']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'image': ('sorl.thumbnail.fields.ImageField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'record': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoRecord']"}), 'time': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Time']", 'null': 'True'}) }, 'profiles.datasource': { 'Meta': {'object_name': 'DataSource'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'implementation': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}) }, 'profiles.denominator': { 'Meta': {'object_name': 'Denominator'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '50'}), 'multiplier': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}), 'sort': ('django.db.models.fields.PositiveIntegerField', [], {'default': '1'}) }, 'profiles.denominatorpart': { 'Meta': {'object_name': 'DenominatorPart'}, 'data': ('django.db.models.fields.files.FileField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'data_source': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataSource']"}), 'denominator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Denominator']"}), 'formula': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'part': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.IndicatorPart']"}) }, 'profiles.geolevel': { 'Meta': {'object_name': 'GeoLevel'}, 'data_sources': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.DataSource']", 'symmetrical': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '200'}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoLevel']", 'null': 'True', 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '200', 'db_index': 'True'}) }, 'profiles.georecord': { 'Meta': {'unique_together': "(('slug', 'level'), ('level', 'geo_id', 'custom_name', 'owner'))", 'object_name': 'GeoRecord'}, 'components': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'components_rel_+'", 'blank': 'True', 'to': "orm['profiles.GeoRecord']"}), 'custom_name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'geo_id': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'geom': ('django.contrib.gis.db.models.fields.GeometryField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'level': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoLevel']"}), 'mappings': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'mappings_rel_+'", 'blank': 'True', 'to': "orm['profiles.GeoRecord']"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'notes': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']", 'null': 'True', 'blank': 'True'}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoRecord']", 'null': 'True', 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'db_index': 'True', 'max_length': '100', 'blank': 'True'}) }, 'profiles.indicator': { 'Meta': {'object_name': 'Indicator'}, 'data_domains': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.DataDomain']", 'through': "orm['profiles.IndicatorDomain']", 'symmetrical': 'False'}), 'data_type': ('django.db.models.fields.CharField', [], {'default': "'COUNT'", 'max_length': '30'}), 'display_change': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'display_distribution': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'display_name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'display_percent': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'levels': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.GeoLevel']", 'symmetrical': 'False'}), 'limitations': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'long_definition': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}), 'notes': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'published': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'purpose': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'routine_use': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'short_definition': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100', 'db_index': 'True'}), 'source': ('django.db.models.fields.CharField', [], {'default': "'U.S. Census Bureau'", 'max_length': '300', 'blank': 'True'}), 'universe': ('django.db.models.fields.CharField', [], {'max_length': '300', 'blank': 'True'}) }, 'profiles.indicatordomain': { 'Meta': {'object_name': 'IndicatorDomain'}, 'default': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'domain': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataDomain']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}) }, 'profiles.indicatorpart': { 'Meta': {'object_name': 'IndicatorPart'}, 'data': ('django.db.models.fields.files.FileField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'data_source': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataSource']"}), 'formula': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'time': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Time']"}) }, 'profiles.precalculatedvalue': { 'Meta': {'object_name': 'PrecalculatedValue'}, 'data_source': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataSource']"}), 'geo_record': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoRecord']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'notes': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'table': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'value': ('django.db.models.fields.TextField', [], {'blank': 'True'}) }, 'profiles.time': { 'Meta': {'object_name': 'Time'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'sort': ('django.db.models.fields.DecimalField', [], {'max_digits': '5', 'decimal_places': '1'}) }, 'profiles.value': { 'Meta': {'object_name': 'Value'}, 'datapoint': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataPoint']"}), 'denominator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Denominator']", 'null': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'moe': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'number': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'percent': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}) } } complete_apps = ['profiles']	216software/Profiles	communityprofiles/profiles/oldmigrations/0045_auto__add_field_indicator_source.py	Python	mit	15,170	[ "MOE" ]	0501be25706d5ba972b8c72750649f4327d8fc1a03b25d4bad9751e6f62d4086
# Licensed under a 3-clause BSD style license - see LICENSE.rst """ LAMDA Query Tool ---------------- :Author: Brian Svoboda (svobodb@email.arizona.edu) This package is for querying the Leiden Atomic and Molecular Database (LAMDA) hosted at: http://home.strw.leidenuniv.nl/~moldata/. Note: If you use the data files from LAMDA in your research work please refer to the publication by Schoier, F.L., van der Tak, F.F.S., van Dishoeck E.F., Black, J.H. 2005, A&A 432, 369-379. When individual molecules are considered, references to the original papers providing the spectroscopic and collisional data are encouraged. """ from .core import Lamda, parse_lamda_datafile, write_lamda_datafile	ceb8/astroquery	astroquery/lamda/__init__.py	Python	bsd-3-clause	701	[ "Brian" ]	3a2623fb883c350d2543abca0bfee4951d9f0ce1a0980c9277e3bce4f3ae77de
# -- coding: utf-8 -- from __future__ import absolute_import from django.conf import settings from django.http import HttpResponse from django.test import TestCase from zilencer.models import Deployment from zerver.views import get_invitee_emails_set, do_change_password from zerver.models import ( get_realm, get_user_profile_by_email, PreregistrationUser, Realm, Recipient, ScheduledJob, UserProfile, UserMessage, ) from zerver.lib.actions import ( create_stream_if_needed, do_add_subscription, set_default_streams, ) from zerver.lib.initial_password import initial_password from zerver.lib.actions import do_set_realm_default_language from zerver.lib.digest import send_digest_email from zerver.lib.notifications import enqueue_welcome_emails, one_click_unsubscribe_link from zerver.lib.test_helpers import ZulipTestCase, find_key_by_email, queries_captured from zerver.lib.test_runner import slow from zerver.lib.session_user import get_session_dict_user import re import ujson from six.moves import urllib from six.moves import range import six from six import text_type class PublicURLTest(ZulipTestCase): """ Account creation URLs are accessible even when not logged in. Authenticated URLs redirect to a page. """ def fetch(self, method, urls, expected_status): # type: (str, List[str], int) -> None for url in urls: response = getattr(self.client, method)(url) # e.g. self.client_post(url) if method is "post" self.assertEqual(response.status_code, expected_status, msg="Expected %d, received %d for %s to %s" % ( expected_status, response.status_code, method, url)) def test_public_urls(self): # type: () -> None """ Test which views are accessible when not logged in. """ # FIXME: We should also test the Tornado URLs -- this codepath # can't do so because this Django test mechanism doesn't go # through Tornado. get_urls = {200: ["/accounts/home/", "/accounts/login/"], 302: ["/"], 401: ["/api/v1/streams/Denmark/members", "/api/v1/users/me/subscriptions", "/api/v1/messages", "/json/messages", "/json/streams", ], } post_urls = {200: ["/accounts/login/"], 302: ["/accounts/logout/"], 401: ["/json/messages", "/json/invite_users", "/json/settings/change", "/json/subscriptions/remove", "/json/subscriptions/exists", "/json/subscriptions/property", "/json/get_subscribers", "/json/fetch_api_key", "/json/users/me/subscriptions", "/api/v1/users/me/subscriptions", ], 400: ["/api/v1/send_message", "/api/v1/external/github", "/api/v1/fetch_api_key", ], } put_urls = {401: ["/json/users/me/pointer"], } for status_code, url_set in six.iteritems(get_urls): self.fetch("get", url_set, status_code) for status_code, url_set in six.iteritems(post_urls): self.fetch("post", url_set, status_code) for status_code, url_set in six.iteritems(put_urls): self.fetch("put", url_set, status_code) def test_get_gcid_when_not_configured(self): # type: () -> None with self.settings(GOOGLE_CLIENT_ID=None): resp = self.client_get("/api/v1/fetch_google_client_id") self.assertEquals(400, resp.status_code, msg="Expected 400, received %d for GET /api/v1/fetch_google_client_id" % resp.status_code, ) data = ujson.loads(resp.content) self.assertEqual('error', data['result']) def test_get_gcid_when_configured(self): # type: () -> None with self.settings(GOOGLE_CLIENT_ID="ABCD"): resp = self.client_get("/api/v1/fetch_google_client_id") self.assertEquals(200, resp.status_code, msg="Expected 200, received %d for GET /api/v1/fetch_google_client_id" % resp.status_code, ) data = ujson.loads(resp.content) self.assertEqual('success', data['result']) self.assertEqual('ABCD', data['google_client_id']) class PasswordResetTest(ZulipTestCase): """ Log in, reset password, log out, log in with new password. """ def test_password_reset(self): # type: () -> None email = 'hamlet@zulip.com' old_password = initial_password(email) self.login(email) # start the password reset process by supplying an email address result = self.client_post('/accounts/password/reset/', {'email': email}) # check the redirect link telling you to check mail for password reset link self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/password/reset/done/")) result = self.client_get(result["Location"]) self.assert_in_response("Check your email to finish the process.", result) # visit password reset link from django.core.mail import outbox for message in reversed(outbox): if email in message.to: password_reset_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)") password_reset_url = password_reset_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a password reset email.") result = self.client_get(password_reset_url) self.assertEquals(result.status_code, 200) # Reset your password result = self.client_post(password_reset_url, {'new_password1': 'new_password', 'new_password2': 'new_password'}) # password reset succeeded self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith("/password/done/")) # log back in with new password self.login(email, password='new_password') user_profile = get_user_profile_by_email('hamlet@zulip.com') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) # make sure old password no longer works self.login(email, password=old_password, fails=True) class LoginTest(ZulipTestCase): """ Logging in, registration, and logging out. """ def test_login(self): # type: () -> None self.login("hamlet@zulip.com") user_profile = get_user_profile_by_email('hamlet@zulip.com') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_login_bad_password(self): # type: () -> None self.login("hamlet@zulip.com", password="wrongpassword", fails=True) self.assertIsNone(get_session_dict_user(self.client.session)) def test_login_nonexist_user(self): # type: () -> None result = self.login_with_return("xxx@zulip.com", "xxx") self.assert_in_response("Please enter a correct email and password", result) def test_register(self): # type: () -> None realm = get_realm("zulip.com") streams = ["stream_%s" % i for i in range(40)] for stream in streams: create_stream_if_needed(realm, stream) set_default_streams(realm, streams) with queries_captured() as queries: self.register("test", "test") # Ensure the number of queries we make is not O(streams) self.assert_length(queries, 67) user_profile = get_user_profile_by_email('test@zulip.com') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_register_deactivated(self): # type: () -> None """ If you try to register for a deactivated realm, you get a clear error page. """ realm = get_realm("zulip.com") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.register("test", "test") self.assert_in_response("has been deactivated", result) with self.assertRaises(UserProfile.DoesNotExist): get_user_profile_by_email('test@zulip.com') def test_login_deactivated(self): # type: () -> None """ If you try to log in to a deactivated realm, you get a clear error page. """ realm = get_realm("zulip.com") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.login_with_return("hamlet@zulip.com") self.assert_in_response("has been deactivated", result) def test_logout(self): # type: () -> None self.login("hamlet@zulip.com") self.client_post('/accounts/logout/') self.assertIsNone(get_session_dict_user(self.client.session)) def test_non_ascii_login(self): # type: () -> None """ You can log in even if your password contain non-ASCII characters. """ email = "test@zulip.com" password = u"hÃ¼mbÃ¼Çµ" # Registering succeeds. self.register("test", password) user_profile = get_user_profile_by_email(email) self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) self.client_post('/accounts/logout/') self.assertIsNone(get_session_dict_user(self.client.session)) # Logging in succeeds. self.client_post('/accounts/logout/') self.login(email, password) self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_register_first_user_with_invites(self): # type: () -> None """ The first user in a realm has a special step in their signup workflow for inviting other users. Do as realistic an end-to-end test as we can without Tornado running. """ username = "user1" password = "test" domain = "test.com" email = "user1@test.com" # Create a new realm to ensure that we're the first user in it. Realm.objects.create(domain=domain, name="Test Inc.") # Start the signup process by supplying an email address. result = self.client_post('/accounts/home/', {'email': email}) # Check the redirect telling you to check your mail for a confirmation # link. self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s@%s" % (username, domain))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url) self.assertEquals(result.status_code, 200) # Pick a password and agree to the ToS. result = self.submit_reg_form_for_user(username, password, domain) self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith("/invite/")) # Invite other users to join you. result = self.client_get(result["Location"]) self.assert_in_response("You're the first one here!", result) # Reset the outbox for our invites. outbox.pop() invitees = ['alice@' + domain, 'bob@' + domain] params = { 'invitee_emails': ujson.dumps(invitees) } result = self.client_post('/json/bulk_invite_users', params) self.assert_json_success(result) # We really did email these users, and they have PreregistrationUser # objects. email_recipients = [message.recipients()[0] for message in outbox] self.assertEqual(len(outbox), len(invitees)) self.assertEqual(sorted(email_recipients), sorted(invitees)) user_profile = get_user_profile_by_email(email) self.assertEqual(len(invitees), PreregistrationUser.objects.filter( referred_by=user_profile).count()) # After this we start manipulating browser information, so stop here. class InviteUserTest(ZulipTestCase): def invite(self, users, streams): # type: (str, List[text_type]) -> HttpResponse """ Invites the specified users to Zulip with the specified streams. users should be a string containing the users to invite, comma or newline separated. streams should be a list of strings. """ return self.client_post("/json/invite_users", {"invitee_emails": users, "stream": streams}) def check_sent_emails(self, correct_recipients): # type: (List[str]) -> None from django.core.mail import outbox self.assertEqual(len(outbox), len(correct_recipients)) email_recipients = [email.recipients()[0] for email in outbox] self.assertEqual(sorted(email_recipients), sorted(correct_recipients)) def test_bulk_invite_users(self): # type: () -> None """The bulk_invite_users code path is for the first user in a realm.""" self.login('hamlet@zulip.com') invitees = ['alice@zulip.com', 'bob@zulip.com'] params = { 'invitee_emails': ujson.dumps(invitees) } result = self.client_post('/json/bulk_invite_users', params) self.assert_json_success(result) self.check_sent_emails(invitees) def test_successful_invite_user(self): # type: () -> None """ A call to /json/invite_users with valid parameters causes an invitation email to be sent. """ self.login("hamlet@zulip.com") invitee = "alice-test@zulip.com" self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(invitee)) self.check_sent_emails([invitee]) def test_successful_invite_user_with_name(self): # type: () -> None """ A call to /json/invite_users with valid parameters causes an invitation email to be sent. """ self.login("hamlet@zulip.com") email = "alice-test@zulip.com" invitee = "Alice Test <{}>".format(email) self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.check_sent_emails([email]) def test_successful_invite_user_with_name_and_normal_one(self): # type: () -> None """ A call to /json/invite_users with valid parameters causes an invitation email to be sent. """ self.login("hamlet@zulip.com") email = "alice-test@zulip.com" email2 = "bob-test@zulip.com" invitee = "Alice Test <{}>, {}".format(email, email2) self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.assertTrue(find_key_by_email(email2)) self.check_sent_emails([email, email2]) def test_invite_user_signup_initial_history(self): # type: () -> None """ Test that a new user invited to a stream receives some initial history but only from public streams. """ self.login("hamlet@zulip.com") user_profile = get_user_profile_by_email("hamlet@zulip.com") private_stream_name = "Secret" (stream, _) = create_stream_if_needed(user_profile.realm, private_stream_name, invite_only=True) do_add_subscription(user_profile, stream) public_msg_id = self.send_message("hamlet@zulip.com", "Denmark", Recipient.STREAM, "Public topic", "Public message") secret_msg_id = self.send_message("hamlet@zulip.com", private_stream_name, Recipient.STREAM, "Secret topic", "Secret message") invitee = "alice-test@zulip.com" self.assert_json_success(self.invite(invitee, [private_stream_name, "Denmark"])) self.assertTrue(find_key_by_email(invitee)) self.submit_reg_form_for_user("alice-test", "password") invitee_profile = get_user_profile_by_email(invitee) invitee_msg_ids = [um.message_id for um in UserMessage.objects.filter(user_profile=invitee_profile)] self.assertTrue(public_msg_id in invitee_msg_ids) self.assertFalse(secret_msg_id in invitee_msg_ids) def test_multi_user_invite(self): # type: () -> None """ Invites multiple users with a variety of delimiters. """ self.login("hamlet@zulip.com") # Intentionally use a weird string. self.assert_json_success(self.invite( """bob-test@zulip.com, carol-test@zulip.com, dave-test@zulip.com earl-test@zulip.com""", ["Denmark"])) for user in ("bob", "carol", "dave", "earl"): self.assertTrue(find_key_by_email("%s-test@zulip.com" % (user,))) self.check_sent_emails(["bob-test@zulip.com", "carol-test@zulip.com", "dave-test@zulip.com", "earl-test@zulip.com"]) def test_missing_or_invalid_params(self): # type: () -> None """ Tests inviting with various missing or invalid parameters. """ self.login("hamlet@zulip.com") self.assert_json_error( self.client_post("/json/invite_users", {"invitee_emails": "foo@zulip.com"}), "You must specify at least one stream for invitees to join.") for address in ("noatsign.com", "outsideyourdomain@example.net"): self.assert_json_error( self.invite(address, ["Denmark"]), "Some emails did not validate, so we didn't send any invitations.") self.check_sent_emails([]) def test_invalid_stream(self): # type: () -> None """ Tests inviting to a non-existent stream. """ self.login("hamlet@zulip.com") self.assert_json_error(self.invite("iago-test@zulip.com", ["NotARealStream"]), "Stream does not exist: NotARealStream. No invites were sent.") self.check_sent_emails([]) def test_invite_existing_user(self): # type: () -> None """ If you invite an address already using Zulip, no invitation is sent. """ self.login("hamlet@zulip.com") self.assert_json_error( self.client_post("/json/invite_users", {"invitee_emails": "hamlet@zulip.com", "stream": ["Denmark"]}), "We weren't able to invite anyone.") self.assertRaises(PreregistrationUser.DoesNotExist, lambda: PreregistrationUser.objects.get( email="hamlet@zulip.com")) self.check_sent_emails([]) def test_invite_some_existing_some_new(self): # type: () -> None """ If you invite a mix of already existing and new users, invitations are only sent to the new users. """ self.login("hamlet@zulip.com") existing = ["hamlet@zulip.com", "othello@zulip.com"] new = ["foo-test@zulip.com", "bar-test@zulip.com"] result = self.client_post("/json/invite_users", {"invitee_emails": "\n".join(existing + new), "stream": ["Denmark"]}) self.assert_json_error(result, "Some of those addresses are already using Zulip, \ so we didn't send them an invitation. We did send invitations to everyone else!") # We only created accounts for the new users. for email in existing: self.assertRaises(PreregistrationUser.DoesNotExist, lambda: PreregistrationUser.objects.get( email=email)) for email in new: self.assertTrue(PreregistrationUser.objects.get(email=email)) # We only sent emails to the new users. self.check_sent_emails(new) def test_invite_outside_domain_in_closed_realm(self): # type: () -> None """ In a realm with `restricted_to_domain = True`, you can't invite people with a different domain from that of the realm or your e-mail address. """ zulip_realm = get_realm("zulip.com") zulip_realm.restricted_to_domain = True zulip_realm.save() self.login("hamlet@zulip.com") external_address = "foo@example.com" self.assert_json_error( self.invite(external_address, ["Denmark"]), "Some emails did not validate, so we didn't send any invitations.") def test_invite_outside_domain_in_open_realm(self): # type: () -> None """ In a realm with `restricted_to_domain = False`, you can invite people with a different domain from that of the realm or your e-mail address. """ zulip_realm = get_realm("zulip.com") zulip_realm.restricted_to_domain = False zulip_realm.save() self.login("hamlet@zulip.com") external_address = "foo@example.com" self.assert_json_success(self.invite(external_address, ["Denmark"])) self.check_sent_emails([external_address]) def test_invite_with_non_ascii_streams(self): # type: () -> None """ Inviting someone to streams with non-ASCII characters succeeds. """ self.login("hamlet@zulip.com") invitee = "alice-test@zulip.com" stream_name = u"hÃ¼mbÃ¼Çµ" realm = get_realm("zulip.com") stream, _ = create_stream_if_needed(realm, stream_name) # Make sure we're subscribed before inviting someone. do_add_subscription( get_user_profile_by_email("hamlet@zulip.com"), stream, no_log=True) self.assert_json_success(self.invite(invitee, [stream_name])) class InviteeEmailsParserTests(TestCase): def setUp(self): # type: () -> None self.email1 = "email1@zulip.com" self.email2 = "email2@zulip.com" self.email3 = "email3@zulip.com" def test_if_emails_separated_by_commas_are_parsed_and_striped_correctly(self): # type: () -> None emails_raw = "{} ,{}, {}".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_separated_by_newlines_are_parsed_and_striped_correctly(self): # type: () -> None emails_raw = "{}\n {}\n {} ".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_from_email_client_separated_by_newlines_are_parsed_correctly(self): # type: () -> None emails_raw = "Email One <{}>\nEmailTwo<{}>\nEmail Three<{}>".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_in_mixed_style_are_parsed_correctly(self): # type: () -> None emails_raw = "Email One <{}>,EmailTwo<{}>\n{}".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) class EmailUnsubscribeTests(ZulipTestCase): def test_missedmessage_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in missed message e-mails that you can click even when logged out to update your email notification settings. """ user_profile = get_user_profile_by_email("hamlet@zulip.com") user_profile.enable_offline_email_notifications = True user_profile.save() unsubscribe_link = one_click_unsubscribe_link(user_profile, "missed_messages") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) self.assertEqual(result.status_code, 200) # Circumvent user_profile caching. user_profile = UserProfile.objects.get(email="hamlet@zulip.com") self.assertFalse(user_profile.enable_offline_email_notifications) def test_welcome_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in welcome e-mails that you can click even when logged out to stop receiving them. """ email = "hamlet@zulip.com" user_profile = get_user_profile_by_email("hamlet@zulip.com") # Simulate a new user signing up, which enqueues 2 welcome e-mails. enqueue_welcome_emails(email, "King Hamlet") self.assertEqual(2, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) # Simulate unsubscribing from the welcome e-mails. unsubscribe_link = one_click_unsubscribe_link(user_profile, "welcome") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) # The welcome email jobs are no longer scheduled. self.assertEqual(result.status_code, 200) self.assertEqual(0, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) def test_digest_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in digest e-mails that you can click even when logged out to stop receiving them. Unsubscribing from these emails also dequeues any digest email jobs that have been queued. """ email = "hamlet@zulip.com" user_profile = get_user_profile_by_email("hamlet@zulip.com") self.assertTrue(user_profile.enable_digest_emails) # Enqueue a fake digest email. send_digest_email(user_profile, "", "") self.assertEqual(1, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) # Simulate unsubscribing from digest e-mails. unsubscribe_link = one_click_unsubscribe_link(user_profile, "digest") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) # The setting is toggled off, and scheduled jobs have been removed. self.assertEqual(result.status_code, 200) # Circumvent user_profile caching. user_profile = UserProfile.objects.get(email="hamlet@zulip.com") self.assertFalse(user_profile.enable_digest_emails) self.assertEqual(0, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) class RealmCreationTest(ZulipTestCase): def test_create_realm(self): # type: () -> None username = "user1" password = "test" domain = "test.com" email = "user1@test.com" # Make sure the realm does not exist self.assertIsNone(get_realm("test.com")) with self.settings(OPEN_REALM_CREATION=True): # Create new realm with the email result = self.client_post('/create_realm/', {'email': email}) self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s@%s" % (username, domain))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url) self.assertEquals(result.status_code, 200) result = self.submit_reg_form_for_user(username, password, domain) self.assertEquals(result.status_code, 302) # Make sure the realm is created realm = get_realm("test.com") self.assertIsNotNone(realm) self.assertEqual(realm.domain, domain) self.assertEqual(get_user_profile_by_email(email).realm, realm) self.assertTrue(result["Location"].endswith("/invite/")) result = self.client_get(result["Location"]) self.assert_in_response("You're the first one here!", result) class UserSignUpTest(ZulipTestCase): def test_user_default_language(self): # type: () -> None """ Check if the default language of new user is the default language of the realm. """ username = "newguy" email = "newguy@zulip.com" domain = "zulip.com" password = "newpassword" realm = get_realm(domain) do_set_realm_default_language(realm, "de") result = self.client_post('/accounts/home/', {'email': email}) self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s@%s" % (username, domain))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url) self.assertEquals(result.status_code, 200) # Pick a password and agree to the ToS. result = self.submit_reg_form_for_user(username, password, domain) self.assertEquals(result.status_code, 302) user_profile = get_user_profile_by_email(email) self.assertEqual(user_profile.default_language, realm.default_language) outbox.pop()	ahmadassaf/zulip	zerver/tests/test_signup.py	Python	apache-2.0	31,655	[ "VisIt" ]	ea8c3e7a34939c0b000c13755754e3d1b118bf899c57479e78f62df46521e184
# -- coding: utf-8 -- ## begin license ## # # "Meresco Components" are components to build searchengines, repositories # and archives, based on "Meresco Core". # # Copyright (C) 2007-2008 SURF Foundation. http://www.surf.nl # Copyright (C) 2007-2011 Seek You Too (CQ2) http://www.cq2.nl # Copyright (C) 2007-2009 Stichting Kennisnet Ict op school. http://www.kennisnetictopschool.nl # Copyright (C) 2009 Delft University of Technology http://www.tudelft.nl # Copyright (C) 2009 Tilburg University http://www.uvt.nl # Copyright (C) 2011, 2015, 2020 Stichting Kennisnet https://www.kennisnet.nl # Copyright (C) 2012, 2015, 2017-2018, 2020 Seecr (Seek You Too B.V.) https://seecr.nl # Copyright (C) 2017, 2020 SURF https://www.surf.nl # Copyright (C) 2020 Data Archiving and Network Services https://dans.knaw.nl # Copyright (C) 2020 The Netherlands Institute for Sound and Vision https://beeldengeluid.nl # # This file is part of "Meresco Components" # # "Meresco Components" is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # "Meresco Components" is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with "Meresco Components"; if not, write to the Free Software # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA # ## end license ## import re UNQUOTED_STRING = r'(?P<unquoted>[\+\-]?[^"\s]+)' QUOTED_STRING = r'(?P<quotedString>[\+\-]?(?P<quot>\")(?P<quoted>.+?)((?<!\\)(?P=quot)))' QUOTED_LABEL_STRING = r'(?P<labelString>[\+\-]?(?P<label>[^"\s]+)=(?P<quot1>\")(?P<quoted1>.+?)((?<!\\)(?P=quot1)))' STRINGS = [QUOTED_LABEL_STRING ,QUOTED_STRING, UNQUOTED_STRING] SPLITTED_STRINGS = re.compile(r'\s*(%s)' % '\|'.join(STRINGS)) from cqlparser import parseString, CQLParseException, cql2string, CqlIdentityVisitor, cqlToExpression, CQLTokenizerException, quotTerm from cqlparser.cqlparser import CQL_QUERY, SCOPED_CLAUSE, SEARCH_CLAUSE, SEARCH_TERM, TERM, BOOLEAN, INDEX, RELATION, COMPARITOR DEFAULT_KIND, PLUSMINUS_KIND, BOOLEAN_KIND = list(range(3)) class WebQuery(object): def __init__(self, aString, antiUnaryClause=""): self.original = aString try: plusminus = _feelsLikePlusMinusQuery(aString) boolean = _feelsLikeBooleanQuery(aString) self._needsHelp = boolean and plusminus if plusminus and not boolean: self._kind = PLUSMINUS_KIND self.ast = parseString(_plusminus2Cql(aString, antiUnaryClause)) elif boolean and not plusminus: try: self._kind = BOOLEAN_KIND self.ast = parseString(_boolean2Cql(aString, antiUnaryClause)) except CQLParseException: self._needsHelp = True self._kind = DEFAULT_KIND self.ast = parseString(_default2CqlWithQuotes(aString, antiUnaryClause=antiUnaryClause)) else: self._kind = DEFAULT_KIND try: self.ast = parseString(_default2Cql(aString, antiUnaryClause=antiUnaryClause)) except CQLParseException: self._needsHelp = True self.ast = parseString(_default2CqlWithQuotes(aString, antiUnaryClause=antiUnaryClause)) except (CQLParseException, CQLTokenizerException): self.ast = parseString(quotTerm(self.original)) self.originalAst = self.ast self._filters = [] def addTermFilter(self, term): self._addFilter(SEARCH_CLAUSE( SEARCH_TERM( TERM(term) ) )) @property def query(self): return cqlToExpression(self.ast) def addFilter(self, field, term): self._addFilter(SEARCH_CLAUSE( INDEX(TERM(field)), RELATION(COMPARITOR('exact')), SEARCH_TERM(TERM(term)) )) def _addFilter(self, filterQuery): self._filters.append(filterQuery) insertOriginalAst = SCOPED_CLAUSE(SEARCH_CLAUSE(self.ast)) if len(self._filters) == 1 else self.ast.children[0] self.ast = CQL_QUERY( SCOPED_CLAUSE( insertOriginalAst, BOOLEAN('and'), filterQuery ) ) def replaceTerm(self, oldTerm, newTerm): newAst = CqlReplaceTerm(self.originalAst, oldTerm, newTerm).visit() result = WebQuery(cql2string(newAst)) for f in self._filters: result._addFilter(f) return result def replaceIndex(self, mapping): newAst = CqlReplaceIndex(self.originalAst, mapping).visit() result = WebQuery(cql2string(newAst)) for f in self._filters: result._addFilter(f) return result def asString(self): return cql2string(self.ast) def isBooleanQuery(self): return self._kind == BOOLEAN_KIND def isPlusMinusQuery(self): return self._kind == PLUSMINUS_KIND def isDefaultQuery(self): return self._kind == DEFAULT_KIND def needsBooleanHelp(self): return self._needsHelp def hasFilters(self): return len(self._filters) > 0 class CqlReplaceTerm(CqlIdentityVisitor): def __init__(self, ast, oldTerm, newTerm): CqlIdentityVisitor.__init__(self, ast) self._oldTerm = oldTerm self._newTerm = newTerm def visitTERM(self, node): if node.children[0] == self._oldTerm: return node.__class__(self._newTerm) return CqlIdentityVisitor.visitTERM(self, node) class CqlReplaceIndex(CqlIdentityVisitor): def __init__(self, ast, mapping): CqlIdentityVisitor.__init__(self, ast) self._mapping = mapping def visitINDEX(self, node): indexTerm = node.children[0].children[0] if indexTerm in self._mapping: return INDEX(TERM(self._mapping[indexTerm])) return CqlIdentityVisitor.visitINDEX(self, node) def _feelsLikePlusMinusQuery(aString): for part in (_valueFromGroupdict(m.groupdict()).lower() for m in SPLITTED_STRINGS.finditer(aString)): if part[0] in ['-', '+'] and len(part) > 1: return part[1] not in ['-', '+'] return False def _feelsLikeBooleanQuery(aString): for part in (_valueFromGroupdict(m.groupdict()).lower() for m in SPLITTED_STRINGS.finditer(aString)): if part in ['and', 'or', 'not']: return True elif part[0] == '(' or part[-1] == ')': return True return False def _joinFieldAndTerm(fieldAndTermList): results = [] for field, term in (tuple(fieldAndTerm.split(':', 1)) for fieldAndTerm in fieldAndTermList): if ' ' in term: term = '"%s"' % term results.append('%s exact %s' % (field, term)) if len(results) == 1: return results[0] return ' AND '.join('(%s)' % result for result in results) def _plusminus2Cql(aString, antiUnaryClause): newParts = [] for match in SPLITTED_STRINGS.finditer(aString): part = _valueFromGroupdict(match.groupdict()) if part[0] == '+': newParts.append(part[1:]) elif part[0] == '-': notStatement = 'NOT ' + part[1:] if len(newParts) == 0: newParts.append(antiUnaryClause + " " + notStatement) else: newParts[-1] = newParts[-1] + ' ' + notStatement else: newParts.append(part) return ' AND '.join(newParts) def _boolean2Cql(aString, antiUnaryClause): aString = aString.replace('(', ' ( ').replace(')', ' ) ') newParts = [] for match in SPLITTED_STRINGS.finditer(aString): part = _valueFromGroupdict(match.groupdict()) partAsToken = part.lower() if partAsToken == 'not': if len(newParts) == 0 or newParts[-1] == '(': newParts.append(antiUnaryClause) if partAsToken in ['not', 'and', 'or']: part = part.upper() newParts.append(part) return ' '.join(newParts) def _default2CqlWithQuotes(aString, antiUnaryClause="ignored"): if aString.strip() == '': return antiUnaryClause return ' AND '.join(quot(_valueFromGroupdict(match.groupdict())) for match in SPLITTED_STRINGS.finditer(aString)) def _default2Cql(aString, antiUnaryClause="ignored"): if aString.strip() == '': return antiUnaryClause try: cqlToExpression(aString) return aString except (CQLParseException, CQLTokenizerException): return ' AND '.join(_valueFromGroupdict(match.groupdict()) for match in SPLITTED_STRINGS.finditer(aString)) def quot(aString): if aString[-1] == '"' == aString[0]: return aString return '"%s"' % aString def _valueFromGroupdict(groupdict): return groupdict['unquoted'] or groupdict['quotedString'] or groupdict['labelString']	seecr/meresco-components	meresco/components/web/webquery.py	Python	gpl-2.0	9,266	[ "VisIt" ]	1cc83756ba59b8ce612424796ea1a397539c1b273ed29d9c8d5ed3a8605d799d
from suggestive.util import retry_function, retry from suggestive.error import RetryError import logging import webbrowser import pylastfm logger = logging.getLogger(__name__) logger.addHandler(logging.NullHandler()) def get(data, keys, default=None): if not keys: return data if not isinstance(data, dict): raise TypeError('not a dictionary') key, rest = keys[0], keys[1:] if key not in data: return default return get(data[key], rest, default=default) class LastFM(object): """ Helper class for communicating with Last.FM servers """ def __init__(self, config): self.config = config self.client = self._initialize_client() def _get_user_permission(self, token): """Attempt to open up authorization URL in browser. If this fails, simply display a message in the console asking user to manually open URL""" url = 'http://www.last.fm/api/auth/?api_key={0}&token={1}'.format( self.config.lastfm.api_key, token) try: webbrowser.open_new_tab(url) except Exception: pass message = """\ No LastFM session found; to authorize suggestive, visit this URL and click 'Yes, allow access', then return to this window: {url} Press Enter to continue...""".format(url=url) input(message) def _save_session(self, session_key): """Save session key (in plaintext) to a file""" logger.info('Saving session key to file') with open(self.config.general.session_file, 'w') as handle: handle.write(session_key) def _authorize_application(self, client): """Go through the LastFM desktop application authorization process, saving a session key to a file for future use""" token = retry_function(client.auth.get_token) self._get_user_permission(token) try: session_key = retry_function(client.auth.get_session, token) except pylastfm.AuthenticationError as exc: logger.debug('Unable to get authenticated LastFM session', exc_info=exc) raise self._save_session(session_key) @retry(exceptions=RetryError) def _initialize_client(self): config = self.config client = pylastfm.LastFM(config.lastfm.api_key, config.lastfm.api_secret, username=config.lastfm.user, url=config.lastfm.url, auth_method='session_key_file', session_key=config.general.session_file) try: client.authenticate() return client except pylastfm.FileError: logger.info('Authenticating suggestive with LastFM') self._authorize_application(client) raise RetryError except pylastfm.AuthenticationError as exc: logger.debug('Failed to authenticate', exc_info=exc) raise except pylastfm.LastfmError as exc: logger.error( 'Unable to authenticate to LastFM due to unknown error', exc_info=exc) raise def scrobbles(self, user, start=None, end=None): """Get user scrobbles in the given date range""" return self.client.user.get_recent_tracks(user, start=start, end=end) def loved_tracks(self, user): """Get all of the user's loved tracks""" return self.client.user.get_loved_tracks(user) def love_track(self, artist, track): """Mark the given track loved""" try: self.client.track.love(artist, track) return True except pylastfm.APIError as exc: logger.error('Unable to love track', exc_info=exc) return False def unlove_track(self, artist, track): """Set the track as not loved""" try: self.client.track.unlove(artist, track) return True except pylastfm.APIError as exc: logger.error('Unable to unlove track', exc_info=exc) return False	thesquelched/suggestive	suggestive/lastfm.py	Python	bsd-2-clause	4,198	[ "VisIt" ]	be5fb648a8b05eaf2c9a8451e1de9c123d77d50f527c1c656624b31cbe60fba2

# -*- coding: utf-8 -*- """ Module gifted Provides functionality for reading and writing animated GIF images. Use write_gif to write a series of numpy arrays or PIL images as an animated GIF. Use read_gif to read an animated gif as a series of numpy arrays. Note that since July 2004, all patents on the LZW compression patent have expired. Therefore the GIF format may now be used freely. Acknowledgements ---------------- Many thanks to Ant1 for: * noting the use of "palette=PIL.Image.ADAPTIVE", which significantly improves the results. * the modifications to save each image with its own palette, or optionally the global palette (if its the same). Many thanks to Marius van Voorden for porting the NeuQuant quantization algorithm of Anthony Dekker to Python (See the NeuQuant class for its license). Many thanks to Alex Robinson for implementing the concept of subrectangles, which (depening on image content) can give a very significant reduction in file size. This code is based on gifmaker (in the scripts folder of the source distribution of PIL) Usefull links ------------- * http://tronche.com/computer-graphics/gif/ * http://en.wikipedia.org/wiki/Graphics_Interchange_Format * http://www.w3.org/Graphics/GIF/spec-gif89a.txt """ import os from fnmatch import fnmatch try: import PIL from PIL import Image from PIL.GifImagePlugin import getheader, getdata except ImportError: PIL = None try: import numpy as np except ImportError: np = None def get_cKDTree(): try: from scipy.spatial import cKDTree except ImportError: cKDTree = None return cKDTree # getheader gives a 87a header and a color palette (two elements in a list). # getdata()[0] gives the Image Descriptor up to (including) "LZW min code size". # getdatas()[1:] is the image data itself in chuncks of 256 bytes (well # technically the first byte says how many bytes follow, after which that # amount (max 255) follows). def check_images(images): """ check_images(images) Check numpy images and correct intensity range etc. The same for all movie formats. """ # Init results images2 = [] for img in images: if PIL and isinstance(img, PIL.Image.Image): # We assume PIL images are allright images2.append(img) elif np and isinstance(img, np.ndarray): # Check and convert dtype if img.dtype == np.uint8: images2.append(img) # Ok elif img.dtype in [np.float32, np.float64]: img = img.copy() img[img < 0] = 0 img[img > 1] = 1 img *= 255 images2.append(img.astype(np.uint8)) else: img = img.astype(np.uint8) images2.append(img) # Check size if img.ndim == 2: pass # ok elif img.ndim == 3: if img.shape[2] not in [3, 4]: raise ValueError('This array can not represent an image.') else: raise ValueError('This array can not represent an image.') else: raise ValueError('Invalid image type: ' + str(type(img))) # Done return images2 def int_to_bin(i): """ Integer to two bytes """ # make string (little endian) return i.to_bytes(2, byteorder='little') class GifWriter(object): """ GifWriter() Class that contains methods for helping write the animated GIF file. """ def __init__(self): self.transparency = None @staticmethod def get_header_anim(img): """ get_header_anim(img) Get animation header. To replace PILs getheader()[0] """ header = b'GIF89a' header += int_to_bin(img.size[0]) header += int_to_bin(img.size[1]) header += b'\x87\x00\x00' return header @staticmethod def get_image_descriptor(img, coords=None): """ get_image_descriptor(img, coords=None) Used for the local color table properties per image. Otherwise global color table applies to all frames irrespective of whether additional colors comes in play that require a redefined palette. Still a maximum of 256 color per frame, obviously. Written by Ant1 on 2010-08-22 Modified by Alex Robinson in Janurari 2011 to implement subrectangles. """ # Defaule use full image and place at upper left if coords is None: coords = (0, 0) # Image separator descriptor = b'\x2C' # Image position and size descriptor += int_to_bin(coords[0]) # Left position descriptor += int_to_bin(coords[1]) # Top position descriptor += int_to_bin(img.size[0]) # image width descriptor += int_to_bin(img.size[1]) # image height # packed field: local color table flag1, interlace0, sorted table0, # reserved00, lct size111=7=2^(7+1)=256. descriptor += b'\x87' # LZW minimum size code now comes later, begining of [image data] blocks return descriptor @staticmethod def get_app_ext(loops=float('inf')): """ get_app_ext(loops=float('inf')) Application extention. This part specifies the amount of loops. If loops is 0 or inf, it goes on infinitely. """ if loops == 0 or loops == float('inf'): loops = 2**16-1 # bb = "" # application extension should not be used # # (the extension interprets zero loops # # to mean an infinite number of loops) # # Mmm, does not seem to work ext = b"\x21\xFF\x0B" # application extension ext += b"NETSCAPE2.0" ext += b"\x03\x01" ext += int_to_bin(loops) ext += b'\x00' # end return ext @staticmethod def get_graphics_control_ext( duration=0.1, dispose=2, transparent_flag=0, transparency_index=0): """ get_graphics_control_ext(duration=0.1, dispose=2) Graphics Control Extension. A sort of header at the start of each image. Specifies duration and transparancy. Dispose ------- * 0 - No disposal specified. * 1 - Do not dispose. The graphic is to be left in place. * 2 - Restore to background color. The area used by the graphic must be restored to the background color. * 3 - Restore to previous. The decoder is required to restore the area overwritten by the graphic with what was there prior to rendering the graphic. * 4-7 -To be defined. """ ext = b'\x21\xF9\x04' ext += bytes([((dispose & 3) << 2) | (transparent_flag & 1)]) # low bit 1 == transparency, # 2nd bit 1 == user input , next 3 bits, the low two of which are used, # are dispose. ext += int_to_bin(int(duration * 100)) # in 100th of seconds ext += bytes([transparency_index]) ext += b'\x00' # end return ext def handle_sub_rectangles(self, images, sub_rectangles): """ handle_sub_rectangles(images) Handle the sub-rectangle stuff. If the rectangles are given by the user, the values are checked. Otherwise the subrectangles are calculated automatically. """ if isinstance(sub_rectangles, (tuple, list)): # xy given directly # Check xy sub_recs = sub_rectangles if sub_recs is None: sub_recs = (0, 0) if hasattr(sub_recs, '__len__'): if len(sub_recs) == len(images): sub_recs = [xxyy for xxyy in sub_recs] else: raise ValueError("len(sub_recs) doesn't match amount of images.") else: sub_recs = [sub_recs for image in images] sub_recs[0] = (0, 0) else: # Calculate xy using some basic image processing # Check Numpy if np is None: raise RuntimeError("Need Numpy to use auto-sub_rectangles.") # First make numpy arrays if required for i in range(len(images)): image = images[i] if isinstance(image, Image.Image): tmp = image.convert() # Make without palette array_ = np.asarray(tmp) if len(array_.shape) == 0: raise MemoryError("Too little memory to convert PIL image to array") images[i] = array_ # Determine the sub rectangles images, sub_rec = self.get_sub_rectangles(images) # Done return images, sub_rec @staticmethod def get_sub_rectangles(images): """ get_sub_rectangles(images) Calculate the minimal rectangles that need updating each frame. Returns a two-element tuple containing the cropped images and a list of x-y positions. Calculating the subrectangles takes extra time, obviously. However, if the image sizes were reduced, the actual writing of the GIF goes faster. In some cases applying this method produces a GIF faster. """ # Check image count if len(images) < 2: return images, [(0, 0) for i in images] # We need numpy if np is None: raise RuntimeError("Need Numpy to calculate sub-rectangles. ") # Prepare ims2 = [images[0]] coords = [(0, 0)] # Iterate over images prev = images[0] for image in images[1:]: # Get difference, sum over colors diff = np.abs(image - prev) if diff.ndim == 3: diff = diff.sum(2) # Get begin and end for both dimensions X = np.argwhere(diff.sum(0)) Y = np.argwhere(diff.sum(1)) # Get rect coordinates if X.size and Y.size: x0, x1 = int(X[0][0]), int(X[-1][0]+1) y0, y1 = int(Y[0][0]), int(Y[-1][0]+1) else: # No change ... make it minimal x0, x1 = 0, 2 y0, y1 = 0, 2 # Cut out and store im2 = image[y0:y1, x0:x1] prev = image ims2.append(im2) coords.append((x0, y0)) return ims2, coords def convert_images_to_PIL(self, images, dither, nq=0): """ convert_images_to_PIL(images, nq=0) Convert images to Paletted PIL images, which can then be written to a single animaged GIF. """ # Convert to PIL images images2 = [] for image in images: if isinstance(image, Image.Image): images2.append(image) elif np and isinstance(image, np.ndarray): if image.ndim == 3 and image.shape[2] == 3: image = Image.fromarray(image, 'RGB') elif image.ndim == 3 and image.shape[2] == 4: # image = Image.fromarray(image[:,:,:3],'RGB') self.transparency = True image = Image.fromarray(image[:, :, :4], 'RGBA') elif image.ndim == 2: image = Image.fromarray(image, 'L') images2.append(image) # Convert to paletted PIL images images, images2 = images2, [] if nq >= 1: # NeuQuant algorithm for image in images: image = image.convert("RGBA") # NQ assumes RGBA # Learn colors from image nq_instance = NeuQuant(image, int(nq)) if dither: image = image.convert("RGB").quantize( palette=nq_instance.paletteImage(), colors=255) else: # Use to quantize the image itself image = nq_instance.quantize(image, colors=255) # since NQ assumes transparency self.transparency = True if self.transparency: alpha = image.split()[3] mask = Image.eval(alpha, lambda a: 255 if a <= 128 else 0) image.paste(255, mask=mask) images2.append(image) else: # for index,image in enumerate(images): for i in range(len(images)): image = images[i].convert('RGB').convert( 'P', palette=Image.ADAPTIVE, # Adaptive PIL algorithm dither=dither, colors=255 ) if self.transparency: alpha = images[i].split()[3] mask = Image.eval(alpha, lambda a: 255 if a <= 128 else 0) image.paste(255, mask=mask) images2.append(image) # Done return images2 def write_gif_to_file(self, file_, images, durations, loops, xys, disposes): """ write_gif_to_file(file_, images, durations, loops, xys, disposes) Given a set of images writes the bytes to the specified stream. """ # Obtain palette for all images and count each occurance palettes, occur = [], [] for image in images: palettes.append(getheader(image)[0][3]) for palette in palettes: occur.append(palettes.count(palette)) # Select most-used palette as the global one (or first in case no max) global_palette = palettes[occur.index(max(occur))] # Init frames = 0 first_frame = True for image, palette in zip(images, palettes): if first_frame: # Write header # Gather info header = self.get_header_anim(image) appext = self.get_app_ext(loops) # Write file_.write(header) file_.write(global_palette) file_.write(appext) # Next frame is not the first first_frame = False if True: # Write palette and image data # Gather info data = getdata(image) imdes, data = data[0], data[1:] transparent_flag = 1 if self.transparency else 0 graphext = self.get_graphics_control_ext( durations[frames], disposes[frames], transparent_flag=transparent_flag, transparency_index=255 ) # Make image descriptor suitable for using 256 local color palette lid = self.get_image_descriptor(image, xys[frames]) # Write local header if (palette != global_palette) or (disposes[frames] != 2): # Use local color palette file_.write(graphext) file_.write(lid) # write suitable image descriptor file_.write(palette) # write local color table file_.write(b'\x08') # LZW minimum size code else: # Use global color palette file_.write(graphext) file_.write(imdes) # write suitable image descriptor # Write image data for datum in data: file_.write(datum) # Prepare for next round frames = frames + 1 file_.write(b';') # end gif return frames # Exposed functions def write_gif(filename, images, duration=0.1, repeat=True, dither=False, nq=0, sub_rectangles=True, dispose=None): """ write_gif(filename, images, duration=0.1, repeat=True, dither=False, nq=0, sub_rectangles=True, dispose=None) Write an animated gif from the specified images. Parameters ---------- filename : string The name of the file to write the image to. images : list Should be a list consisting of PIL images or numpy arrays. The latter should be between 0 and 255 for integer types, and between 0 and 1 for float types. duration : scalar or list of scalars The duration for all frames, or (if a list) for each frame. repeat : bool or integer The amount of loops. If True, loops infinitetely. dither : bool Whether to apply dithering nq : integer If nonzero, applies the NeuQuant quantization algorithm to create the color palette. This algorithm is superior, but slower than the standard PIL algorithm. The value of nq is the quality parameter. 1 represents the best quality. 10 is in general a good tradeoff between quality and speed. When using this option, better results are usually obtained when sub_rectangles is False. sub_rectangles : False, True, or a list of 2-element tuples Whether to use sub-rectangles. If True, the minimal rectangle that is required to update each frame is automatically detected. This can give significant reductions in file size, particularly if only a part of the image changes. One can also give a list of x-y coordinates if you want to do the cropping yourself. The default is True. dispose : int How to dispose each frame. 1 means that each frame is to be left in place. 2 means the background color should be restored after each frame. 3 means the decoder should restore the previous frame. If sub_rectangles==False, the default is 2, otherwise it is 1. """ # Check PIL if PIL is None: raise RuntimeError("Need PIL to write animated gif files.") # Check images images = check_images(images) # Instantiate writer object gif_writer = GifWriter() gif_writer.transparency = False # init transparency flag used in GifWriter functions # Check loops if repeat is False: loops = 1 elif repeat is True: loops = 0 # zero means infinite else: loops = int(repeat) # Check duration if hasattr(duration, '__len__'): if len(duration) == len(images): duration = [d for d in duration] else: raise ValueError("len(duration) doesn't match amount of images.") else: duration = [duration for im in images] # Check subrectangles if sub_rectangles: images, xy = gif_writer.handle_sub_rectangles(images, sub_rectangles) default_dispose = 1 # Leave image in place else: # Normal mode xy = [(0, 0) for im in images] default_dispose = 2 # Restore to background color. # Check dispose if dispose is None: dispose = default_dispose if hasattr(dispose, '__len__'): if len(dispose) != len(images): raise ValueError("len(xy) doesn't match amount of images.") else: dispose = [dispose for im in images] # Make images in a format that we can write easy images = gif_writer.convert_images_to_PIL(images, dither, nq) # Write with open(filename, 'wb') as file_: gif_writer.write_gif_to_file(file_, images, duration, loops, xy, dispose) def read_gif(filename, as_numpy=True): """ read_gif(filename, as_numpy=True) Read images from an animated GIF file. Returns a list of numpy arrays, or, if as_numpy is false, a list if PIL images. """ # Check PIL if PIL is None: raise RuntimeError("Need PIL to read animated gif files.") # Check Numpy if np is None: raise RuntimeError("Need Numpy to read animated gif files.") # Check whether it exists if not os.path.isfile(filename): raise IOError('File not found: '+str(filename)) # Load file using PIL pil_image = PIL.Image.open(filename) pil_image.seek(0) # Read all images inside images = [] try: while True: # Get image as numpy array tmp = pil_image.convert() # Make without palette array_ = np.asarray(tmp) if len(array_.shape) == 0: raise MemoryError("Too little memory to convert PIL image to array") # Store, and next images.append(array_) pil_image.seek(pil_image.tell()+1) except EOFError: pass # Convert to normal PIL images if needed if not as_numpy: images2 = images images = [] for image in images2: tmp = PIL.Image.fromarray(image) images.append(tmp) # Done return images class NeuQuant: """ NeuQuant(image, samplefac=10, colors=256) samplefac should be an integer number of 1 or higher, 1 being the highest quality, but the slowest performance. With avalue of 10, one tenth of all pixels are used during training. This value seems a nice tradeof between speed and quality. colors is the amount of colors to reduce the image to. This should best be a power of two. See also: http://members.ozemail.com.au/~dekker/NEUQUANT.HTML License of the NeuQuant Neural-Net Quantization Algorithm --------------------------------------------------------- Copyright (c) 1994 Anthony Dekker Ported to python by Marius van Voorden in 2010 NEUQUANT Neural-Net quantization algorithm by Anthony Dekker, 1994. See "Kohonen neural networks for optimal colour quantization" in "network: Computation in Neural Systems" Vol. 5 (1994) pp 351-367. for a discussion of the algorithm. See also http://members.ozemail.com.au/~dekker/NEUQUANT.HTML Any party obtaining a copy of these files from the author, directly or indirectly, is granted, free of charge, a full and unrestricted irrevocable, world-wide, paid up, royalty-free, nonexclusive right and license to deal in this software and documentation files (the "Software"), including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons who receive copies from any such party to do so, with the only requirement being that this copyright notice remain intact. """ NCYCLES = None # Number of learning cycles NETSIZE = None # Number of colours used SPECIALS = None # Number of reserved colours used BGCOLOR = None # Reserved background colour CUTNETSIZE = None MAXNETPOS = None INITRAD = None # For 256 colours, radius starts at 32 RADIUSBIASSHIFT = None RADIUSBIAS = None INITBIASRADIUS = None RADIUSDEC = None # Factor of 1/30 each cycle ALPHABIASSHIFT = None INITALPHA = None # biased by 10 bits GAMMA = None BETA = None BETAGAMMA = None network = None # The network itself colormap = None # The network itself netindex = None # For network lookup - really 256 bias = None # Bias and freq arrays for learning freq = None pimage = None # Four primes near 500 - assume no image has a length so large # that it is divisible by all four primes PRIME1 = 499 PRIME2 = 491 PRIME3 = 487 PRIME4 = 503 MAXPRIME = PRIME4 pixels = None samplefac = None a_s = None def __init__(self, image, samplefac=10, colors=256): # Check Numpy if np is None: raise RuntimeError("Need Numpy for the NeuQuant algorithm.") # Check image if image.size[0] * image.size[1] < NeuQuant.MAXPRIME: raise IOError("Image is too small") if image.mode != "RGBA": raise IOError("Image mode should be RGBA.") # Initialize self.setconstants(samplefac, colors) self.pixels = np.fromstring(image.tostring(), np.uint32) self.set_up_arrays() self.learn() self.fix() self.inxbuild() def setconstants(self, samplefac, colors): """ Sets class constants """ self.NCYCLES = 100 # Number of learning cycles self.NETSIZE = colors # Number of colours used self.SPECIALS = 3 # Number of reserved colours used self.BGCOLOR = self.SPECIALS-1 # Reserved background colour self.CUTNETSIZE = self.NETSIZE - self.SPECIALS self.MAXNETPOS = self.NETSIZE - 1 self.INITRAD = self.NETSIZE/8 # For 256 colours, radius starts at 32 self.RADIUSBIASSHIFT = 6 self.RADIUSBIAS = 1 << self.RADIUSBIASSHIFT self.INITBIASRADIUS = self.INITRAD * self.RADIUSBIAS self.RADIUSDEC = 30 # Factor of 1/30 each cycle self.ALPHABIASSHIFT = 10 # Alpha starts at 1 self.INITALPHA = 1 << self.ALPHABIASSHIFT # biased by 10 bits self.GAMMA = 1024.0 self.BETA = 1.0/1024.0 self.BETAGAMMA = self.BETA * self.GAMMA self.network = np.empty((self.NETSIZE, 3), dtype='float64') # The network itself self.colormap = np.empty((self.NETSIZE, 4), dtype='int32') # The network itself self.netindex = np.empty(256, dtype='int32') # For network lookup - really 256 self.bias = np.empty(self.NETSIZE, dtype='float64') # Bias and freq arrays for learning self.freq = np.empty(self.NETSIZE, dtype='float64') self.pixels = None self.samplefac = samplefac self.a_s = dict() def write_colour_map(self, rgb, outstream): """ """ for i in range(self.NETSIZE): blue = self.colormap[i, 0] green = self.colormap[i, 1] red = self.colormap[i, 2] outstream.write(red if rgb else blue) outstream.write(green) outstream.write(blue if rgb else red) return self.NETSIZE def set_up_arrays(self): """ """ self.network[0, 0] = 0.0 # Black self.network[0, 1] = 0.0 self.network[0, 2] = 0.0 self.network[1, 0] = 255.0 # White self.network[1, 1] = 255.0 self.network[1, 2] = 255.0 # RESERVED self.BGCOLOR # Background for i in range(self.SPECIALS): self.freq[i] = 1.0 / self.NETSIZE self.bias[i] = 0.0 for i in range(self.SPECIALS, self.NETSIZE): p = self.network[i] p[:] = (255.0 * (i-self.SPECIALS)) / self.CUTNETSIZE self.freq[i] = 1.0 / self.NETSIZE self.bias[i] = 0.0 # Omitted: setPixels def altersingle(self, alpha, i, b, g, r): """Move neuron i towards biased (b,g,r) by factor alpha""" n = self.network[i] # Alter hit neuron n[0] -= (alpha*(n[0] - b)) n[1] -= (alpha*(n[1] - g)) n[2] -= (alpha*(n[2] - r)) def geta(self, alpha, rad): try: return self.a_s[(alpha, rad)] except KeyError: length = rad*2-1 mid = length/2 q = np.array(list(range(mid-1, -1, -1))+list(range(-1, mid))) a = alpha*(rad*rad - q*q)/(rad*rad) a[mid] = 0 self.a_s[(alpha, rad)] = a return a def alterneigh(self, alpha, rad, i, b, g, r): if i-rad >= self.SPECIALS-1: lo = i-rad start = 0 else: lo = self.SPECIALS-1 start = (self.SPECIALS-1 - (i-rad)) if i+rad <= self.NETSIZE: hi = i+rad end = rad*2-1 else: hi = self.NETSIZE end = (self.NETSIZE - (i+rad)) a = self.geta(alpha, rad)[start:end] p = self.network[lo+1:hi] p -= np.transpose(np.transpose(p - np.array([b, g, r])) * a) def contest(self, b, g, r): """ Search for biased BGR values Finds closest neuron (min dist) and updates self.freq finds best neuron (min dist-self.bias) and returns position for frequently chosen neurons, self.freq[i] is high and self.bias[i] is negative self.bias[i] = self.GAMMA*((1/self.NETSIZE)-self.freq[i])""" i, j = self.SPECIALS, self.NETSIZE dists = abs(self.network[i:j] - np.array([b, g, r])).sum(1) bestpos = i + np.argmin(dists) biasdists = dists - self.bias[i:j] bestbiaspos = i + np.argmin(biasdists) self.freq[i:j] *= (1-self.BETA) self.bias[i:j] += self.BETAGAMMA * self.freq[i:j] self.freq[bestpos] += self.BETA self.bias[bestpos] -= self.BETAGAMMA return bestbiaspos def special_find(self, b, g, r): for i in range(self.SPECIALS): n = self.network[i] if n[0] == b and n[1] == g and n[2] == r: return i return -1 def learn(self): biasRadius = self.INITBIASRADIUS alphadec = 30 + ((self.samplefac-1)/3) lengthcount = self.pixels.size samplepixels = lengthcount / self.samplefac delta = samplepixels / self.NCYCLES alpha = self.INITALPHA i = 0 rad = biasRadius >> self.RADIUSBIASSHIFT if rad <= 1: rad = 0 print("Beginning 1D learning: samplepixels = %1.2f rad = %i" % (samplepixels, rad)) step = 0 pos = 0 if lengthcount % NeuQuant.PRIME1 != 0: step = NeuQuant.PRIME1 elif lengthcount % NeuQuant.PRIME2 != 0: step = NeuQuant.PRIME2 elif lengthcount % NeuQuant.PRIME3 != 0: step = NeuQuant.PRIME3 else: step = NeuQuant.PRIME4 i = 0 printed_string = '' while i < samplepixels: if i % 100 == 99: tmp = '\b'*len(printed_string) printed_string = str((i+1)*100/samplepixels)+"%\n" print(tmp + printed_string) p = self.pixels[pos] r = (p >> 16) & 0xff g = (p >> 8) & 0xff b = (p) & 0xff if i == 0: # Remember background colour self.network[self.BGCOLOR] = [b, g, r] j = self.special_find(b, g, r) if j < 0: j = self.contest(b, g, r) if j >= self.SPECIALS: # Don't learn for specials a = (1.0 * alpha) / self.INITALPHA self.altersingle(a, j, b, g, r) if rad > 0: self.alterneigh(a, rad, j, b, g, r) pos = (pos+step) % lengthcount i += 1 if i % delta == 0: alpha -= alpha / alphadec biasRadius -= biasRadius / self.RADIUSDEC rad = biasRadius >> self.RADIUSBIASSHIFT if rad <= 1: rad = 0 finalAlpha = (1.0*alpha)/self.INITALPHA print("Finished 1D learning: final alpha = %1.2f!" % finalAlpha) def fix(self): for i in range(self.NETSIZE): for j in range(3): x = int(0.5 + self.network[i, j]) x = max(0, x) x = min(255, x) self.colormap[i, j] = x self.colormap[i, 3] = i def inxbuild(self): previouscol = 0 startpos = 0 for i in range(self.NETSIZE): p = self.colormap[i] q = None smallpos = i smallval = p[1] # Index on g # Find smallest in i..self.NETSIZE-1 for j in range(i+1, self.NETSIZE): q = self.colormap[j] if q[1] < smallval: # Index on g smallpos = j smallval = q[1] # Index on g q = self.colormap[smallpos] # Swap p (i) and q (smallpos) entries if i != smallpos: p[:], q[:] = q, p.copy() # smallval entry is now in position i if smallval != previouscol: self.netindex[previouscol] = (startpos+i) >> 1 for j in range(previouscol+1, smallval): self.netindex[j] = i previouscol = smallval startpos = i self.netindex[previouscol] = (startpos+self.MAXNETPOS) >> 1 for j in range(previouscol+1, 256): # Really 256 self.netindex[j] = self.MAXNETPOS def paletteImage(self): """ PIL weird interface for making a paletted image: create an image which already has the palette, and use that in Image.quantize. This function returns this palette image. """ if self.pimage is None: palette = [] for i in range(self.NETSIZE): palette.extend(self.colormap[i][:3]) palette.extend([0]*(256-self.NETSIZE)*3) # a palette image to use for quant self.pimage = Image.new("P", (1, 1), 0) self.pimage.putpalette(palette) return self.pimage def quantize(self, image): """ Use a kdtree to quickly find the closest palette colors for the pixels """ if get_cKDTree(): return self.quantize_with_scipy(image) else: print('Scipy not available, falling back to slower version.') return self.quantize_without_scipy(image) def quantize_with_scipy(self, image): w, h = image.size px = np.asarray(image).copy() px2 = px[:, :, :3].reshape((w*h, 3)) cKDTree = get_cKDTree() kdtree = cKDTree(self.colormap[:, :3], leafsize=10) result = kdtree.query(px2) colorindex = result[1] print("Distance: %1.2f" % (result[0].sum()/(w*h))) px2[:] = self.colormap[colorindex, :3] return Image.fromarray(px).convert("RGB").quantize(palette=self.paletteImage()) def quantize_without_scipy(self, image): """" This function can be used if no scipy is availabe. It's 7 times slower though. """ w, h = image.size px = np.asarray(image).copy() memo = {} for j in range(w): for i in range(h): key = (px[i, j, 0], px[i, j, 1], px[i, j, 2]) try: val = memo[key] except KeyError: val = self.convert(*key) memo[key] = val px[i, j, 0], px[i, j, 1], px[i, j, 2] = val return Image.fromarray(px).convert("RGB").quantize(palette=self.paletteImage()) def convert(self, *color): i = self.inxsearch(*color) return self.colormap[i, :3] def inxsearch(self, r, g, b): """Search for BGR values 0..255 and return colour index""" dists = (self.colormap[:, :3] - np.array([r, g, b])) a = np.argmin((dists*dists).sum(1)) return a def load_images(image_directory, extension, prefix=None): """ Locates image files in image_directory with the specified extension and/or prefix, and loads them into memory as PIL/Pillow objects :param image_directory: string :param extension: string :param prefix: string :returns: List of PIL Image objects """ exl = extension.lower() exu = extension.upper() # List everything in dir: all_files = os.listdir(image_directory) # Prune out unwanted extension types images = [i for i in all_files if fnmatch(i, "*." + exl) or fnmatch(i, "*." + exu)] # Prune out unwanted prefix types if prefix: images = [i for i in images if fnmatch(i, prefix + "*")] # Sort to maintain order during GIF creation images.sort() return [Image.open(os.path.join(image_directory, i)) for i in images]

levi-rs/gifted

gifted/gifted.py

Python

bsd-3-clause

35,791

[ "NEURON" ]

d4cff7f9a898e05a253a5ee978ea665cb18629fd3b6178484bc7a01ed9dd3027

# Orca # # Copyright 2004-2009 Sun Microsystems Inc. # Copyright 2010-2011 The Orca Team # Copyright 2012 Igalia, S.L. # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the # Free Software Foundation, Inc., Franklin Street, Fifth Floor, # Boston MA 02110-1301 USA. """The main module for the Orca screen reader.""" __id__ = "$Id$" __version__ = "$Revision$" __date__ = "$Date$" __copyright__ = "Copyright (c) 2004-2009 Sun Microsystems Inc." \ "Copyright (c) 2010-2011 The Orca Team" \ "Copyright (c) 2012 Igalia, S.L." __license__ = "LGPL" import faulthandler import gi import importlib import os import pyatspi import re import signal import subprocess import sys try: from gi.repository.Gio import Settings a11yAppSettings = Settings(schema_id='org.gnome.desktop.a11y.applications') except: a11yAppSettings = None try: # This can fail due to gtk not being available. We want to # be able to recover from that if possible. The main driver # for this is to allow "orca --text-setup" to work even if # the desktop is not running. # gi.require_version("Gtk", "3.0") from gi.repository import Gtk gi.require_version("Gdk", "3.0") from gi.repository import Gdk # Note: This last import is here due to bgo #673396. # See bgo#673397 for the rest of the story. gi.require_version("GdkX11", "3.0") from gi.repository.GdkX11 import X11Screen except: pass from . import braille from . import debug from . import event_manager from . import keybindings from . import logger from . import messages from . import mouse_review from . import notification_messages from . import orca_state from . import orca_platform from . import script_manager from . import settings from . import settings_manager from . import speech from . import sound from .input_event import BrailleEvent _eventManager = event_manager.getManager() _scriptManager = script_manager.getManager() _settingsManager = settings_manager.getManager() _logger = logger.getLogger() def onEnabledChanged(gsetting, key): try: enabled = gsetting.get_boolean(key) except: return if key == 'screen-reader-enabled' and not enabled: shutdown() def getSettingsManager(): return _settingsManager def getLogger(): return _logger EXIT_CODE_HANG = 50 # The user-settings module (see loadUserSettings). # _userSettings = None # A subset of the original Xmodmap info prior to our stomping on it. # Right now, this is just for the user's chosen Orca modifier(s). # _originalXmodmap = "" _orcaModifiers = settings.DESKTOP_MODIFIER_KEYS + settings.LAPTOP_MODIFIER_KEYS _capsLockCleared = False _restoreOrcaKeys = False ######################################################################## # # # METHODS TO HANDLE APPLICATION LIST AND FOCUSED OBJECTS # # # ######################################################################## CARET_TRACKING = "caret-tracking" FOCUS_TRACKING = "focus-tracking" FLAT_REVIEW = "flat-review" MOUSE_REVIEW = "mouse-review" SAY_ALL = "say-all" def emitRegionChanged(obj, startOffset=None, endOffset=None, mode=None): """Notifies interested clients that the current region of interest has changed.""" if startOffset is None: startOffset = 0 if endOffset is None: endOffset = startOffset if mode is None: mode = FOCUS_TRACKING try: obj.emit("mode-changed::" + mode, 1, "") except: msg = "ORCA: Exception emitting mode-changed notification" debug.println(debug.LEVEL_INFO, msg, True) if mode != orca_state.activeMode: msg = "ORCA: Switching active mode from %s to %s" % (orca_state.activeMode, mode) debug.println(debug.LEVEL_INFO, msg, True) orca_state.activeMode = mode try: msg = "ORCA: Region of interest: %s (%i, %i)" % (obj, startOffset, endOffset) debug.println(debug.LEVEL_INFO, msg, True) obj.emit("region-changed", startOffset, endOffset) except: msg = "ORCA: Exception emitting region-changed notification" debug.println(debug.LEVEL_INFO, msg, True) def setLocusOfFocus(event, obj, notifyScript=True, force=False): """Sets the locus of focus (i.e., the object with visual focus) and notifies the script of the change should the script wish to present the change to the user. Arguments: - event: if not None, the Event that caused this to happen - obj: the Accessible with the new locus of focus. - notifyScript: if True, propagate this event - force: if True, don't worry if this is the same object as the current locusOfFocus """ if not force and obj == orca_state.locusOfFocus: msg = "ORCA: Setting locusOfFocus to existing locusOfFocus" debug.println(debug.LEVEL_INFO, msg, True) return if event and (orca_state.activeScript and not orca_state.activeScript.app): script = _scriptManager.getScript(event.host_application, event.source) _scriptManager.setActiveScript(script, "Setting locusOfFocus") oldFocus = orca_state.locusOfFocus try: oldFocus.getRole() except: msg = "ORCA: Old locusOfFocus is null or defunct" debug.println(debug.LEVEL_INFO, msg, True) oldFocus = None if not obj: msg = "ORCA: New locusOfFocus is null (being cleared)" debug.println(debug.LEVEL_INFO, msg, True) orca_state.locusOfFocus = None return if orca_state.activeScript: msg = "ORCA: Active script is: %s" % orca_state.activeScript debug.println(debug.LEVEL_INFO, msg, True) if orca_state.activeScript.utilities.isZombie(obj): msg = "ERROR: New locusOfFocus (%s) is zombie. Not updating." % obj debug.println(debug.LEVEL_INFO, msg, True) return if orca_state.activeScript.utilities.isDead(obj): msg = "ERROR: New locusOfFocus (%s) is dead. Not updating." % obj debug.println(debug.LEVEL_INFO, msg, True) return msg = "ORCA: Changing locusOfFocus from %s to %s" % (oldFocus, obj) debug.println(debug.LEVEL_INFO, msg, True) orca_state.locusOfFocus = obj if not notifyScript: return if not orca_state.activeScript: msg = "ORCA: Cannot notify active script because there isn't one" debug.println(debug.LEVEL_INFO, msg, True) return orca_state.activeScript.locusOfFocusChanged(event, oldFocus, orca_state.locusOfFocus) ######################################################################## # # # METHODS FOR PRE-PROCESSING AND MASSAGING BRAILLE EVENTS. # # # ######################################################################## def _processBrailleEvent(event): """Called whenever a key is pressed on the Braille display. Arguments: - command: the BrlAPI event for the key that was pressed. Returns True if the event was consumed; otherwise False """ consumed = False # Braille key presses always interrupt speech. # event = BrailleEvent(event) if event.event['command'] not in braille.dontInteruptSpeechKeys: speech.stop() orca_state.lastInputEvent = event try: consumed = _eventManager.processBrailleEvent(event) except: debug.printException(debug.LEVEL_SEVERE) if (not consumed) and orca_state.learnModeEnabled: consumed = True return consumed ######################################################################## # # # METHODS FOR HANDLING INITIALIZATION, SHUTDOWN, AND USE. # # # ######################################################################## def deviceChangeHandler(deviceManager, device): """New keyboards being plugged in stomp on our changes to the keymappings, so we have to re-apply""" source = device.get_source() if source == Gdk.InputSource.KEYBOARD: msg = "ORCA: Keyboard change detected, re-creating the xmodmap" debug.println(debug.LEVEL_INFO, msg, True) _createOrcaXmodmap() def updateKeyMap(keyboardEvent): """Unsupported convenience method to call sad hacks which should go away.""" global _restoreOrcaKeys if keyboardEvent.isPressedKey(): return if keyboardEvent.event_string in settings.orcaModifierKeys \ and orca_state.bypassNextCommand: _restoreXmodmap() _restoreOrcaKeys = True return if _restoreOrcaKeys and not orca_state.bypassNextCommand: _createOrcaXmodmap() _restoreOrcaKeys = False def _setXmodmap(xkbmap): """Set the keyboard map using xkbcomp.""" p = subprocess.Popen(['xkbcomp', '-w0', '-', os.environ['DISPLAY']], stdin=subprocess.PIPE, stdout=None, stderr=None) p.communicate(xkbmap) def _setCapsLockAsOrcaModifier(enable): """Enable or disable use of the caps lock key as an Orca modifier key.""" interpretCapsLineProg = re.compile( r'^\s*interpret\s+Caps[_+]Lock[_+]AnyOfOrNone\s*$all$\s*{\s*$', re.I) normalCapsLineProg = re.compile( r'^\s*action\s*=\s*LockMods\s*$\s*modifiers\s*=\s*Lock\s*$\s*;\s*$', re.I) interpretShiftLineProg = re.compile( r'^\s*interpret\s+Shift[_+]Lock[_+]AnyOf\s*$\s*Shift\s*\+\s*Lock\s*$\s*{\s*$', re.I) normalShiftLineProg = re.compile( r'^\s*action\s*=\s*LockMods\s*$\s*modifiers\s*=\s*Shift\s*$\s*;\s*$', re.I) disabledModLineProg = re.compile( r'^\s*action\s*=\s*NoAction\s*$\s*$\s*;\s*$', re.I) normalCapsLine = ' action= LockMods(modifiers=Lock);' normalShiftLine = ' action= LockMods(modifiers=Shift);' disabledModLine = ' action= NoAction();' lines = _originalXmodmap.decode('UTF-8').split('\n') foundCapsInterpretSection = False foundShiftInterpretSection = False modified = False for i, line in enumerate(lines): if not foundCapsInterpretSection and not foundShiftInterpretSection: if interpretCapsLineProg.match(line): foundCapsInterpretSection = True elif interpretShiftLineProg.match(line): foundShiftInterpretSection = True elif foundCapsInterpretSection: if enable: if normalCapsLineProg.match(line): lines[i] = disabledModLine modified = True else: if disabledModLineProg.match(line): lines[i] = normalCapsLine modified = True if line.find('}'): foundCapsInterpretSection = False else: # foundShiftInterpretSection if enable: if normalShiftLineProg.match(line): lines[i] = disabledModLine modified = True else: if disabledModLineProg.match(line): lines[i] = normalShiftLine modified = True if line.find('}'): foundShiftInterpretSection = False if modified: _setXmodmap(bytes('\n'.join(lines), 'UTF-8')) def _createOrcaXmodmap(): """Makes an Orca-specific Xmodmap so that the keys behave as we need them to do. This is especially the case for the Orca modifier. """ global _capsLockCleared cmd = [] if "Caps_Lock" in settings.orcaModifierKeys \ or "Shift_Lock" in settings.orcaModifierKeys: _setCapsLockAsOrcaModifier(True) _capsLockCleared = True elif _capsLockCleared: _setCapsLockAsOrcaModifier(False) _capsLockCleared = False def _storeXmodmap(keyList): """Save the original xmodmap for the keys in keyList before we alter it. Arguments: - keyList: A list of named keys to look for. """ global _originalXmodmap _originalXmodmap = subprocess.check_output(['xkbcomp', os.environ['DISPLAY'], '-']) def _restoreXmodmap(keyList=[]): """Restore the original xmodmap values for the keys in keyList. Arguments: - keyList: A list of named keys to look for. An empty list means to restore the entire saved xmodmap. """ global _capsLockCleared _capsLockCleared = False p = subprocess.Popen(['xkbcomp', '-w0', '-', os.environ['DISPLAY']], stdin=subprocess.PIPE, stdout=None, stderr=None) p.communicate(_originalXmodmap) def setKeyHandling(new): """Toggle use of the new vs. legacy key handling mode. """ _eventManager.setKeyHandling(new) def loadUserSettings(script=None, inputEvent=None, skipReloadMessage=False): """Loads (and reloads) the user settings module, reinitializing things such as speech if necessary. Returns True to indicate the input event has been consumed. """ debug.println(debug.LEVEL_INFO, 'ORCA: Loading User Settings', True) global _userSettings # Shutdown the output drivers and give them a chance to die. player = sound.getPlayer() player.shutdown() speech.shutdown() braille.shutdown() _scriptManager.deactivate() reloaded = False if _userSettings: _profile = _settingsManager.getSetting('activeProfile')[1] try: _userSettings = _settingsManager.getGeneralSettings(_profile) _settingsManager.setProfile(_profile) reloaded = True except ImportError: debug.printException(debug.LEVEL_INFO) except: debug.printException(debug.LEVEL_SEVERE) else: _profile = _settingsManager.profile try: _userSettings = _settingsManager.getGeneralSettings(_profile) except ImportError: debug.printException(debug.LEVEL_INFO) except: debug.printException(debug.LEVEL_SEVERE) if not script: script = _scriptManager.getDefaultScript() _settingsManager.loadAppSettings(script) if _settingsManager.getSetting('enableSpeech'): msg = 'ORCA: About to enable speech' debug.println(debug.LEVEL_INFO, msg, True) try: speech.init() if reloaded and not skipReloadMessage: script.speakMessage(messages.SETTINGS_RELOADED) except: debug.printException(debug.LEVEL_SEVERE) else: msg = 'ORCA: Speech is not enabled in settings' debug.println(debug.LEVEL_INFO, msg, True) if _settingsManager.getSetting('enableBraille'): msg = 'ORCA: About to enable braille' debug.println(debug.LEVEL_INFO, msg, True) try: braille.init(_processBrailleEvent) except: debug.printException(debug.LEVEL_WARNING) msg = 'ORCA: Could not initialize connection to braille.' debug.println(debug.LEVEL_WARNING, msg, True) else: msg = 'ORCA: Braille is not enabled in settings' debug.println(debug.LEVEL_INFO, msg, True) if _settingsManager.getSetting('enableMouseReview'): mouse_review.reviewer.activate() else: mouse_review.reviewer.deactivate() if _settingsManager.getSetting('enableSound'): player.init() global _orcaModifiers custom = [k for k in settings.orcaModifierKeys if k not in _orcaModifiers] _orcaModifiers += custom # Handle the case where a change was made in the Orca Preferences dialog. # if _originalXmodmap: _restoreXmodmap(_orcaModifiers) _storeXmodmap(_orcaModifiers) _createOrcaXmodmap() _scriptManager.activate() _eventManager.activate() debug.println(debug.LEVEL_INFO, 'ORCA: User Settings Loaded', True) return True def _showPreferencesUI(script, prefs): if orca_state.orcaOS: orca_state.orcaOS.showGUI() return try: module = importlib.import_module('.orca_gui_prefs', 'orca') except: debug.printException(debug.LEVEL_SEVERE) return uiFile = os.path.join(orca_platform.datadir, orca_platform.package, "ui", "orca-setup.ui") orca_state.orcaOS = module.OrcaSetupGUI(uiFile, "orcaSetupWindow", prefs) orca_state.orcaOS.init(script) orca_state.orcaOS.showGUI() def showAppPreferencesGUI(script=None, inputEvent=None): """Displays the user interface to configure the settings for a specific applications within Orca and set up those app-specific user preferences using a GUI. Returns True to indicate the input event has been consumed. """ prefs = {} for key in settings.userCustomizableSettings: prefs[key] = _settingsManager.getSetting(key) script = script or orca_state.activeScript _showPreferencesUI(script, prefs) return True def showPreferencesGUI(script=None, inputEvent=None): """Displays the user interface to configure Orca and set up user preferences using a GUI. Returns True to indicate the input event has been consumed. """ prefs = _settingsManager.getGeneralSettings(_settingsManager.profile) script = _scriptManager.getDefaultScript() _showPreferencesUI(script, prefs) return True def helpForOrca(script=None, inputEvent=None, page=""): """Show Orca Help window (part of the GNOME Access Guide). Returns True to indicate the input event has been consumed. """ orca_state.learnModeEnabled = False uri = "help:orca" if page: uri += "?%s" % page Gtk.show_uri(Gdk.Screen.get_default(), uri, Gtk.get_current_event_time()) return True def addKeyGrab(binding): """ Add a key grab for the given key binding. """ ret = [] for kd in binding.keyDefs(): ret.append(orca_state.device.add_key_grab(kd, None)) return ret def removeKeyGrab(id): """ Remove the key grab for the given key binding. """ orca_state.device.remove_key_grab(id) def mapModifier(keycode): return orca_state.device.map_modifier(keycode) def quitOrca(script=None, inputEvent=None): """Quit Orca. Check if the user wants to confirm this action. If so, show the confirmation GUI otherwise just shutdown. Returns True to indicate the input event has been consumed. """ shutdown() return True def showFindGUI(script=None, inputEvent=None): """Displays the user interface to perform an Orca Find. Returns True to indicate the input event has been consumed. """ try: module = importlib.import_module('.orca_gui_find', 'orca') module.showFindUI() except: debug.printException(debug.LEVEL_SEVERE) # If True, this module has been initialized. # _initialized = False def init(registry): """Initialize the orca module, which initializes the speech and braille modules. Also builds up the application list, registers for AT-SPI events, and creates scripts for all known applications. Returns True if the initialization procedure has run, or False if this module has already been initialized. """ debug.println(debug.LEVEL_INFO, 'ORCA: Initializing', True) global _initialized if _initialized and _settingsManager.isScreenReaderServiceEnabled(): debug.println(debug.LEVEL_INFO, 'ORCA: Already initialized', True) return False # Do not hang on initialization if we can help it. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) loadUserSettings() if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) _initialized = True # In theory, we can do this through dbus. In practice, it fails to # work sometimes. Until we know why, we need to leave this as-is # so that we respond when gnome-control-center is used to stop Orca. if a11yAppSettings: a11yAppSettings.connect('changed', onEnabledChanged) debug.println(debug.LEVEL_INFO, 'ORCA: Initialized', True) return True def start(registry, cacheValues): """Starts Orca.""" debug.println(debug.LEVEL_INFO, 'ORCA: Starting', True) if not _initialized: init(registry) # Do not hang on startup if we can help it. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) if cacheValues: pyatspi.setCacheLevel(pyatspi.CACHE_PROPERTIES) # Event handlers for input devices being plugged in/unplugged. # Used to re-create the Xmodmap when a new keyboard is plugged in. # Necessary, because plugging in a new keyboard resets the Xmodmap # and stomps our changes display = Gdk.Display.get_default() devmanager=display.get_device_manager() devmanager.connect("device-added", deviceChangeHandler) devmanager.connect("device-removed", deviceChangeHandler) Gdk.notify_startup_complete() msg = 'ORCA: Startup complete notification made' debug.println(debug.LEVEL_INFO, msg, True) debug.println(debug.LEVEL_INFO, 'ORCA: Starting registry', True) registry.start(gil=False) def die(exitCode=1): pid = os.getpid() if exitCode == EXIT_CODE_HANG: # Someting is hung and we wish to abort. os.kill(pid, signal.SIGKILL) return shutdown() sys.exit(exitCode) if exitCode > 1: os.kill(pid, signal.SIGTERM) def timeout(signum=None, frame=None): msg = 'TIMEOUT: something has hung. Aborting.' debug.println(debug.LEVEL_SEVERE, msg, True) debug.printStack(debug.LEVEL_SEVERE) debug.examineProcesses(force=True) die(EXIT_CODE_HANG) def shutdown(script=None, inputEvent=None): """Exits Orca. Unregisters any event listeners and cleans up. Returns True if the shutdown procedure ran or False if this module was never initialized. """ debug.println(debug.LEVEL_INFO, 'ORCA: Shutting down', True) global _initialized if not _initialized: return False # Try to say goodbye, but be defensive if something has hung. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) orca_state.activeScript.presentMessage(messages.STOP_ORCA, resetStyles=False) _scriptManager.deactivate() _eventManager.deactivate() # Shutdown all the other support. # if settings.enableSpeech: speech.shutdown() if settings.enableBraille: braille.shutdown() if settings.enableSound: player = sound.getPlayer() player.shutdown() if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) _initialized = False _restoreXmodmap(_orcaModifiers) debug.println(debug.LEVEL_INFO, 'ORCA: Stopping registry', True) pyatspi.Registry.stop() debug.println(debug.LEVEL_INFO, 'ORCA: Shutdown complete', True) return True exitCount = 0 def shutdownOnSignal(signum, frame): global exitCount try: # Requires python 3.8 signalString = '(%s)' % signal.strsignal(signum) except: signalString = '' msg = 'ORCA: Shutting down and exiting due to signal=%d %s' % \ (signum, signalString) debug.println(debug.LEVEL_INFO, msg, True) # Well...we'll try to exit nicely, but if we keep getting called, # something bad is happening, so just quit. # if exitCount: die(signum) else: exitCount += 1 # Try to do a graceful shutdown if we can. # if settings.timeoutCallback and (settings.timeoutTime > 0): signal.signal(signal.SIGALRM, settings.timeoutCallback) signal.alarm(settings.timeoutTime) try: if _initialized: shutdown() else: # We always want to try to shutdown speech since the # speech servers are very persistent about living. # speech.shutdown() shutdown() cleanExit = True except: cleanExit = False if settings.timeoutCallback and (settings.timeoutTime > 0): signal.alarm(0) if not cleanExit: die(EXIT_CODE_HANG) def crashOnSignal(signum, frame): signal.signal(signum, signal.SIG_DFL) _restoreXmodmap(_orcaModifiers) os.kill(os.getpid(), signum) def main(cacheValues=True): """The main entry point for Orca. The exit codes for Orca will loosely be based on signals, where the exit code will be the signal used to terminate Orca (if a signal was used). Otherwise, an exit code of 0 means normal completion and an exit code of 50 means Orca exited because of a hang.""" msg = "ORCA: Launching version %s" % orca_platform.version if orca_platform.revision: msg += " (rev %s)" % orca_platform.revision debug.println(debug.LEVEL_INFO, msg, True) if debug.debugFile and os.path.exists(debug.debugFile.name): faulthandler.enable(file=debug.debugFile, all_threads=True) else: faulthandler.enable(all_threads=False) # Method to call when we think something might be hung. # settings.timeoutCallback = timeout # Various signal handlers we want to listen for. # signal.signal(signal.SIGHUP, shutdownOnSignal) signal.signal(signal.SIGINT, shutdownOnSignal) signal.signal(signal.SIGTERM, shutdownOnSignal) signal.signal(signal.SIGQUIT, shutdownOnSignal) signal.signal(signal.SIGSEGV, crashOnSignal) debug.println(debug.LEVEL_INFO, "ORCA: Enabling accessibility (if needed).", True) if not _settingsManager.isAccessibilityEnabled(): _settingsManager.setAccessibility(True) debug.println(debug.LEVEL_INFO, "ORCA: Initializing ATSPI registry.", True) init(pyatspi.Registry) debug.println(debug.LEVEL_INFO, "ORCA: ATSPI registry initialized.", True) try: message = messages.START_ORCA script = _scriptManager.getDefaultScript() script.presentMessage(message) except: debug.printException(debug.LEVEL_SEVERE) script = orca_state.activeScript if script: window = script.utilities.activeWindow() if window and not orca_state.locusOfFocus: try: app = window.getApplication() except: msg = "ORCA: Exception getting app for %s" % window debug.println(debug.LEVEL_INFO, msg, True) else: script = _scriptManager.getScript(app, window) _scriptManager.setActiveScript(script, "Launching.") setLocusOfFocus(None, window) focusedObject = script.utilities.focusedObject(window) if focusedObject: setLocusOfFocus(None, focusedObject) script = _scriptManager.getScript(focusedObject.getApplication(), focusedObject) _scriptManager.setActiveScript(script, "Found focused object.") try: debug.println(debug.LEVEL_INFO, "ORCA: Starting ATSPI registry.", True) start(pyatspi.Registry, cacheValues) # waits until we stop the registry except: debug.println(debug.LEVEL_SEVERE, "ORCA: Exception starting ATSPI registry.", True) die(EXIT_CODE_HANG) return 0 if __name__ == "__main__": sys.exit(main())

GNOME/orca

src/orca/orca.py

Python

lgpl-2.1

28,530

[ "ORCA" ]

be57ace019f253f6ab90683e8b93150aa12254b13ba006ccdf7c4cc334484296

# CLEANUP NOTES (for ISHAN): # - add documentation for each method # - add comments inline explaining each piece # - add a unit test for each method (at least) # future from __future__ import annotations # stdlib from typing import Any from typing import List as TypeList from typing import Optional # third party from nacl.signing import VerifyKey # the most generic class class Scalar: """ A Scalar is the most generic class, which keeps track of the current value, and a data-independent min-val and max-val. """ def publish( self, acc: Any, user_key: VerifyKey, sigma: float = 1.5 ) -> TypeList[Any]: """Adversarial accountant adds Gaussian noise and publishes the scalar's value""" # relative from ...publish import publish return publish([self], acc=acc, sigma=sigma, user_key=user_key) @property def max_val(self) -> Optional[float]: raise NotImplementedError @property def min_val(self) -> Optional[float]: raise NotImplementedError @property def value(self) -> Optional[float]: raise NotImplementedError def __str__(self) -> str: return ( "<" + str(type(self).__name__) + ": (" + str(self.min_val) + " < " + str(self.value) + " < " + str(self.max_val) + ")>" ) def __repr__(self) -> str: return str(self)

OpenMined/PySyft

packages/syft/src/syft/core/adp/scalar/abstract/scalar.py

Python

apache-2.0

1,478

[ "Gaussian" ]

051f3bb25a3a1228174127d25559591a4c7e84a22877463c805b14b9f5283f4b

"""Forest of trees-based ensemble methods Those methods include random forests and extremely randomized trees. The module structure is the following: - The ``BaseForest`` base class implements a common ``fit`` method for all the estimators in the module. The ``fit`` method of the base ``Forest`` class calls the ``fit`` method of each sub-estimator on random samples (with replacement, a.k.a. bootstrap) of the training set. The init of the sub-estimator is further delegated to the ``BaseEnsemble`` constructor. - The ``ForestClassifier`` and ``ForestRegressor`` base classes further implement the prediction logic by computing an average of the predicted outcomes of the sub-estimators. - The ``RandomForestClassifier`` and ``RandomForestRegressor`` derived classes provide the user with concrete implementations of the forest ensemble method using classical, deterministic ``DecisionTreeClassifier`` and ``DecisionTreeRegressor`` as sub-estimator implementations. - The ``ExtraTreesClassifier`` and ``ExtraTreesRegressor`` derived classes provide the user with concrete implementations of the forest ensemble method using the extremly randomized trees ``ExtraTreeClassifier`` and ``ExtraTreeRegressor`` as sub-estimator implementations. Single and multi-output problems are both handled. """ # Authors: Gilles Louppe, Brian Holt # License: BSD 3 import itertools import numpy as np from warnings import warn from abc import ABCMeta, abstractmethod from ..base import ClassifierMixin, RegressorMixin from ..externals.joblib import Parallel, delayed, cpu_count from ..feature_selection.selector_mixin import SelectorMixin from ..tree import DecisionTreeClassifier, DecisionTreeRegressor, \ ExtraTreeClassifier, ExtraTreeRegressor from ..tree._tree import DTYPE, DOUBLE from ..utils import array2d, check_random_state, check_arrays from ..metrics import r2_score from .base import BaseEnsemble __all__ = ["RandomForestClassifier", "RandomForestRegressor", "ExtraTreesClassifier", "ExtraTreesRegressor"] MAX_INT = np.iinfo(np.int32).max def _parallel_build_trees(n_trees, forest, X, y, sample_mask, X_argsorted, seed, verbose): """Private function used to build a batch of trees within a job.""" random_state = check_random_state(seed) trees = [] for i in xrange(n_trees): if verbose > 1: print("building tree %d of %d" % (i + 1, n_trees)) seed = random_state.randint(MAX_INT) tree = forest._make_estimator(append=False) tree.set_params(compute_importances=forest.compute_importances) tree.set_params(random_state=check_random_state(seed)) if forest.bootstrap: n_samples = X.shape[0] indices = random_state.randint(0, n_samples, n_samples) tree.fit(X[indices], y[indices], sample_mask=sample_mask, X_argsorted=X_argsorted) tree.indices_ = indices else: tree.fit(X, y, sample_mask=sample_mask, X_argsorted=X_argsorted) trees.append(tree) return trees def _parallel_predict_proba(trees, X, n_classes, n_outputs): """Private function used to compute a batch of predictions within a job.""" n_samples = X.shape[0] p = [] for k in xrange(n_outputs): p.append(np.zeros((n_samples, n_classes[k]))) for tree in trees: p_tree = tree.predict_proba(X) if n_outputs == 1: p_tree = [p_tree] for k in xrange(n_outputs): if n_classes[k] == tree.n_classes_[k]: p[k] += p_tree[k] else: for j, c in enumerate(tree.classes_[k]): p[k][:, c] += p_tree[k][:, j] return p def _parallel_predict_regression(trees, X): """Private function used to compute a batch of predictions within a job.""" return sum(tree.predict(X) for tree in trees) def _partition_trees(forest): """Private function used to partition trees between jobs.""" # Compute the number of jobs if forest.n_jobs == -1: n_jobs = min(cpu_count(), forest.n_estimators) else: n_jobs = min(forest.n_jobs, forest.n_estimators) # Partition trees between jobs n_trees = [int(forest.n_estimators / n_jobs)] * n_jobs for i in xrange(forest.n_estimators % n_jobs): n_trees[i] += 1 starts = [0] * (n_jobs + 1) for i in xrange(1, n_jobs + 1): starts[i] = starts[i - 1] + n_trees[i - 1] return n_jobs, n_trees, starts def _parallel_X_argsort(X): """Private function used to sort the features of X.""" return np.asarray(np.argsort(X.T, axis=1).T, dtype=np.int32, order="F") def _partition_features(forest, n_total_features): """Private function used to partition features between jobs.""" # Compute the number of jobs if forest.n_jobs == -1: n_jobs = min(cpu_count(), n_total_features) else: n_jobs = min(forest.n_jobs, n_total_features) # Partition features between jobs n_features = [n_total_features / n_jobs] * n_jobs for i in xrange(n_total_features % n_jobs): n_features[i] += 1 starts = [0] * (n_jobs + 1) for i in xrange(1, n_jobs + 1): starts[i] = starts[i - 1] + n_features[i - 1] return n_jobs, n_features, starts class BaseForest(BaseEnsemble, SelectorMixin): """Base class for forests of trees. Warning: This class should not be used directly. Use derived classes instead. """ __metaclass__ = ABCMeta @abstractmethod def __init__(self, base_estimator, n_estimators=10, estimator_params=[], bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(BaseForest, self).__init__( base_estimator=base_estimator, n_estimators=n_estimators, estimator_params=estimator_params) self.bootstrap = bootstrap self.compute_importances = compute_importances self.oob_score = oob_score self.n_jobs = n_jobs self.random_state = random_state self.n_features_ = None self.n_outputs_ = None self.classes_ = None self.n_classes_ = None self.feature_importances_ = None self.verbose = verbose def fit(self, X, y): """Build a forest of trees from the training set (X, y). Parameters ---------- X : array-like of shape = [n_samples, n_features] The training input samples. y : array-like, shape = [n_samples] or [n_samples, n_outputs] The target values (integers that correspond to classes in classification, real numbers in regression). Returns ------- self : object Returns self. """ self.random_state = check_random_state(self.random_state) # Precompute some data X, y = check_arrays(X, y, sparse_format="dense") if getattr(X, "dtype", None) != DTYPE or \ X.ndim != 2 or not X.flags.fortran: X = array2d(X, dtype=DTYPE, order="F") n_samples, self.n_features_ = X.shape if self.bootstrap: sample_mask = None X_argsorted = None else: if self.oob_score: raise ValueError("Out of bag estimation only available" " if bootstrap=True") sample_mask = np.ones((n_samples,), dtype=np.bool) n_jobs, _, starts = _partition_features(self, self.n_features_) all_X_argsorted = Parallel(n_jobs=n_jobs)( delayed(_parallel_X_argsort)( X[:, starts[i]:starts[i + 1]]) for i in xrange(n_jobs)) X_argsorted = np.asfortranarray(np.hstack(all_X_argsorted)) y = np.atleast_1d(y) if y.ndim == 1: y = y[:, np.newaxis] self.classes_ = [] self.n_classes_ = [] self.n_outputs_ = y.shape[1] if isinstance(self.base_estimator, ClassifierMixin): y = np.copy(y) for k in xrange(self.n_outputs_): unique = np.unique(y[:, k]) self.classes_.append(unique) self.n_classes_.append(unique.shape[0]) y[:, k] = np.searchsorted(unique, y[:, k]) if getattr(y, "dtype", None) != DTYPE or not y.flags.contiguous: y = np.ascontiguousarray(y, dtype=DOUBLE) # Assign chunk of trees to jobs n_jobs, n_trees, _ = _partition_trees(self) # Parallel loop all_trees = Parallel(n_jobs=n_jobs, verbose=self.verbose)( delayed(_parallel_build_trees)( n_trees[i], self, X, y, sample_mask, X_argsorted, self.random_state.randint(MAX_INT), verbose=self.verbose) for i in xrange(n_jobs)) # Reduce self.estimators_ = [tree for tree in itertools.chain(*all_trees)] # Calculate out of bag predictions and score if self.oob_score: if isinstance(self, ClassifierMixin): self.oob_decision_function_ = [] self.oob_score_ = 0.0 predictions = [] for k in xrange(self.n_outputs_): predictions.append(np.zeros((n_samples, self.n_classes_[k]))) for estimator in self.estimators_: mask = np.ones(n_samples, dtype=np.bool) mask[estimator.indices_] = False p_estimator = estimator.predict_proba(X[mask, :]) if self.n_outputs_ == 1: p_estimator = [p_estimator] for k in xrange(self.n_outputs_): predictions[k][mask, :] += p_estimator[k] for k in xrange(self.n_outputs_): if (predictions[k].sum(axis=1) == 0).any(): warn("Some inputs do not have OOB scores. " "This probably means too few trees were used " "to compute any reliable oob estimates.") decision = predictions[k] \ / predictions[k].sum(axis=1)[:, np.newaxis] self.oob_decision_function_.append(decision) self.oob_score_ += np.mean(y[:, k] \ == np.argmax(predictions[k], axis=1)) if self.n_outputs_ == 1: self.oob_decision_function_ = \ self.oob_decision_function_[0] self.oob_score_ /= self.n_outputs_ else: # Regression: predictions = np.zeros((n_samples, self.n_outputs_)) n_predictions = np.zeros((n_samples, self.n_outputs_)) for estimator in self.estimators_: mask = np.ones(n_samples, dtype=np.bool) mask[estimator.indices_] = False p_estimator = estimator.predict(X[mask, :]) if self.n_outputs_ == 1: p_estimator = p_estimator[:, np.newaxis] predictions[mask, :] += p_estimator n_predictions[mask, :] += 1 if (n_predictions == 0).any(): warn("Some inputs do not have OOB scores. " "This probably means too few trees were used " "to compute any reliable oob estimates.") n_predictions[n_predictions == 0] = 1 predictions /= n_predictions self.oob_prediction_ = predictions if self.n_outputs_ == 1: self.oob_prediction_ = \ self.oob_prediction_.reshape((n_samples, )) self.oob_score_ = 0.0 for k in xrange(self.n_outputs_): self.oob_score_ += r2_score(y[:, k], predictions[:, k]) self.oob_score_ /= self.n_outputs_ # Sum the importances if self.compute_importances: self.feature_importances_ = \ sum(tree.feature_importances_ for tree in self.estimators_) \ / self.n_estimators return self class ForestClassifier(BaseForest, ClassifierMixin): """Base class for forest of trees-based classifiers. Warning: This class should not be used directly. Use derived classes instead. """ __metaclass__ = ABCMeta @abstractmethod def __init__(self, base_estimator, n_estimators=10, estimator_params=[], bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ForestClassifier, self).__init__( base_estimator, n_estimators=n_estimators, estimator_params=estimator_params, bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) def predict(self, X): """Predict class for X. The predicted class of an input sample is computed as the majority prediction of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- y : array of shape = [n_samples] or [n_samples, n_outputs] The predicted classes. """ n_samples = len(X) P = self.predict_proba(X) if self.n_outputs_ == 1: P = [P] predictions = np.zeros((n_samples, self.n_outputs_)) for k in xrange(self.n_outputs_): predictions[:, k] = self.classes_[k].take(np.argmax(P[k], axis=1), axis=0) if self.n_outputs_ == 1: predictions = predictions.reshape((n_samples, )) return predictions def predict_proba(self, X): """Predict class probabilities for X. The predicted class probabilities of an input sample is computed as the mean predicted class probabilities of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- p : array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1. The class probabilities of the input samples. Classes are ordered by arithmetical order. """ # Check data if getattr(X, "dtype", None) != DTYPE or X.ndim != 2: X = array2d(X, dtype=DTYPE) # Assign chunk of trees to jobs n_jobs, n_trees, starts = _partition_trees(self) # Parallel loop all_p = Parallel(n_jobs=n_jobs)( delayed(_parallel_predict_proba)( self.estimators_[starts[i]:starts[i + 1]], X, self.n_classes_, self.n_outputs_) for i in xrange(n_jobs)) # Reduce p = all_p[0] for j in xrange(1, len(all_p)): for k in xrange(self.n_outputs_): p[k] += all_p[j][k] for k in xrange(self.n_outputs_): p[k] /= self.n_estimators if self.n_outputs_ == 1: return p[0] else: return p def predict_log_proba(self, X): """Predict class log-probabilities for X. The predicted class log-probabilities of an input sample is computed as the mean predicted class log-probabilities of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- p : array of shape = [n_samples, n_classes], or a list of n_outputs such arrays if n_outputs > 1. The class log-probabilities of the input samples. Classes are ordered by arithmetical order. """ proba = self.predict_proba(X) if self.n_outputs_ == 1: return np.log(proba) else: for k in xrange(self.n_outputs_): proba[k] = np.log(proba[k]) return proba class ForestRegressor(BaseForest, RegressorMixin): """Base class for forest of trees-based regressors. Warning: This class should not be used directly. Use derived classes instead. """ __metaclass__ = ABCMeta @abstractmethod def __init__(self, base_estimator, n_estimators=10, estimator_params=[], bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ForestRegressor, self).__init__( base_estimator, n_estimators=n_estimators, estimator_params=estimator_params, bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) def predict(self, X): """Predict regression target for X. The predicted regression target of an input sample is computed as the mean predicted regression targets of the trees in the forest. Parameters ---------- X : array-like of shape = [n_samples, n_features] The input samples. Returns ------- y: array of shape = [n_samples] or [n_samples, n_outputs] The predicted values. """ # Check data if getattr(X, "dtype", None) != DTYPE or X.ndim != 2: X = array2d(X, dtype=DTYPE) # Assign chunk of trees to jobs n_jobs, n_trees, starts = _partition_trees(self) # Parallel loop all_y_hat = Parallel(n_jobs=n_jobs)( delayed(_parallel_predict_regression)( self.estimators_[starts[i]:starts[i + 1]], X) for i in xrange(n_jobs)) # Reduce y_hat = sum(all_y_hat) / self.n_estimators return y_hat class RandomForestClassifier(ForestClassifier): """A random forest classifier. A random forest is a meta estimator that fits a number of classifical decision trees on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="gini") The function to measure the quality of a split. Supported criteria are "gini" for the Gini impurity and "entropy" for the information gain. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split: - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=True) Whether bootstrap samples are used when building trees. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool Whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeClassifier The collection of fitted sub-estimators. `feature_importances_` : array, shape = [n_features] The feature importances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_decision_function_` : array, shape = [n_samples, n_classes] Decision function computed with out-of-bag estimate on the training set. References ---------- .. [1] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32, 2001. See also -------- DecisionTreeClassifier, ExtraTreesClassifier """ def __init__(self, n_estimators=10, criterion="gini", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=True, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(RandomForestClassifier, self).__init__( base_estimator=DecisionTreeClassifier(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features class RandomForestRegressor(ForestRegressor): """A random forest regressor. A random forest is a meta estimator that fits a number of classifical decision trees on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="mse") The function to measure the quality of a split. The only supported criterion is "mse" for the mean squared error. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split: - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=True) Whether bootstrap samples are used when building trees. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeRegressor The collection of fitted sub-estimators. `feature_importances_` : array of shape = [n_features] The feature mportances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_prediction_` : array, shape = [n_samples] Prediction computed with out-of-bag estimate on the training set. References ---------- .. [1] L. Breiman, "Random Forests", Machine Learning, 45(1), 5-32, 2001. See also -------- DecisionTreeRegressor, ExtraTreesRegressor """ def __init__(self, n_estimators=10, criterion="mse", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=True, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(RandomForestRegressor, self).__init__( base_estimator=DecisionTreeRegressor(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features class ExtraTreesClassifier(ForestClassifier): """An extra-trees classifier. This class implements a meta estimator that fits a number of randomized decision trees (a.k.a. extra-trees) on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="gini") The function to measure the quality of a split. Supported criteria are "gini" for the Gini impurity and "entropy" for the information gain. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split. - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=False) Whether bootstrap samples are used when building trees. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool Whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeClassifier The collection of fitted sub-estimators. `feature_importances_` : array of shape = [n_features] The feature mportances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_decision_function_` : array, shape = [n_samples, n_classes] Decision function computed with out-of-bag estimate on the training set. References ---------- .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", Machine Learning, 63(1), 3-42, 2006. See also -------- sklearn.tree.ExtraTreeClassifier : Base classifier for this ensemble. RandomForestClassifier : Ensemble Classifier based on trees with optimal splits. """ def __init__(self, n_estimators=10, criterion="gini", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ExtraTreesClassifier, self).__init__( base_estimator=ExtraTreeClassifier(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features class ExtraTreesRegressor(ForestRegressor): """An extra-trees regressor. This class implements a meta estimator that fits a number of randomized decision trees (a.k.a. extra-trees) on various sub-samples of the dataset and use averaging to improve the predictive accuracy and control over-fitting. Parameters ---------- n_estimators : integer, optional (default=10) The number of trees in the forest. criterion : string, optional (default="mse") The function to measure the quality of a split. The only supported criterion is "mse" for the mean squared error. Note: this parameter is tree-specific. max_depth : integer or None, optional (default=None) The maximum depth of the tree. If None, then nodes are expanded until all leaves are pure or until all leaves contain less than min_samples_split samples. Note: this parameter is tree-specific. min_samples_split : integer, optional (default=1) The minimum number of samples required to split an internal node. Note: this parameter is tree-specific. min_samples_leaf : integer, optional (default=1) The minimum number of samples in newly created leaves. A split is discarded if after the split, one of the leaves would contain less then ``min_samples_leaf`` samples. Note: this parameter is tree-specific. min_density : float, optional (default=0.1) This parameter controls a trade-off in an optimization heuristic. It controls the minimum density of the `sample_mask` (i.e. the fraction of samples in the mask). If the density falls below this threshold the mask is recomputed and the input data is packed which results in data copying. If `min_density` equals to one, the partitions are always represented as copies of the original data. Otherwise, partitions are represented as bit masks (aka sample masks). Note: this parameter is tree-specific. max_features : int, string or None, optional (default="auto") The number of features to consider when looking for the best split: - If "auto", then `max_features=sqrt(n_features)` on classification tasks and `max_features=n_features` on regression problems. - If "sqrt", then `max_features=sqrt(n_features)`. - If "log2", then `max_features=log2(n_features)`. - If None, then `max_features=n_features`. Note: this parameter is tree-specific. bootstrap : boolean, optional (default=False) Whether bootstrap samples are used when building trees. Note: this parameter is tree-specific. compute_importances : boolean, optional (default=True) Whether feature importances are computed and stored into the ``feature_importances_`` attribute when calling fit. oob_score : bool Whether to use out-of-bag samples to estimate the generalization error. n_jobs : integer, optional (default=1) The number of jobs to run in parallel. If -1, then the number of jobs is set to the number of cores. random_state : int, RandomState instance or None, optional (default=None) If int, random_state is the seed used by the random number generator; If RandomState instance, random_state is the random number generator; If None, the random number generator is the RandomState instance used by `np.random`. verbose : int, optional (default=0) Controlls the verbosity of the tree building process. Attributes ---------- `estimators_`: list of DecisionTreeRegressor The collection of fitted sub-estimators. `feature_importances_` : array of shape = [n_features] The feature mportances (the higher, the more important the feature). `oob_score_` : float Score of the training dataset obtained using an out-of-bag estimate. `oob_prediction_` : array, shape = [n_samples] Prediction computed with out-of-bag estimate on the training set. References ---------- .. [1] P. Geurts, D. Ernst., and L. Wehenkel, "Extremely randomized trees", Machine Learning, 63(1), 3-42, 2006. See also -------- sklearn.tree.ExtraTreeRegressor: Base estimator for this ensemble. RandomForestRegressor: Ensemble regressor using trees with optimal splits. """ def __init__(self, n_estimators=10, criterion="mse", max_depth=None, min_samples_split=1, min_samples_leaf=1, min_density=0.1, max_features="auto", bootstrap=False, compute_importances=False, oob_score=False, n_jobs=1, random_state=None, verbose=0): super(ExtraTreesRegressor, self).__init__( base_estimator=ExtraTreeRegressor(), n_estimators=n_estimators, estimator_params=("criterion", "max_depth", "min_samples_split", "min_samples_leaf", "min_density", "max_features", "random_state"), bootstrap=bootstrap, compute_importances=compute_importances, oob_score=oob_score, n_jobs=n_jobs, random_state=random_state, verbose=verbose) self.criterion = criterion self.max_depth = max_depth self.min_samples_split = min_samples_split self.min_samples_leaf = min_samples_leaf self.min_density = min_density self.max_features = max_features

GbalsaC/bitnamiP

venv/lib/python2.7/site-packages/sklearn/ensemble/forest.py

Python

agpl-3.0

41,898

[ "Brian" ]

70332f50177c22d4fc5fbc0263d3b9fe04fe68ac988453836d627fac9f9cc463

# Copyright 2003-2009 by Bartek Wilczynski. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. """Tools for sequence motif analysis (DEPRECATED, see Bio.motifs instead). This module (Bio.Motif) has been deprecated and will be removed in a future release of release of Biopython. Please use the new module Bio.motifs instead. This contains the core Motif class containing various I/O methods as well as methods for motif comparisons and motif searching in sequences. It also inlcudes functionality for parsing AlignACE and MEME programs. """ from __future__ import print_function import warnings from Bio import BiopythonDeprecationWarning warnings.warn("The module Bio.Motif has been deprecated and will be " "removed in a future release of Biopython. Instead " "please use the new module Bio.motifs instead. Please " "be aware that though the functionality of Bio.Motif " "is retained (and extended) in Bio.motifs, usage may " "be different.", BiopythonDeprecationWarning) from Bio.Motif._Motif import Motif from Bio.Motif.Parsers.AlignAce import read as _AlignAce_read from Bio.Motif.Parsers.MEME import read as _MEME_read from Bio.Motif.Thresholds import ScoreDistribution __docformat__ = "restructuredtext en" _parsers = {"AlignAce": _AlignAce_read, "MEME": _MEME_read, } def _from_pfm(handle): return Motif()._from_jaspar_pfm(handle) def _from_sites(handle): return Motif()._from_jaspar_sites(handle) _readers = {"jaspar-pfm": _from_pfm, "jaspar-sites": _from_sites } def parse(handle, format): """Parses an output file of motif finding programs. Currently supported formats: - AlignAce - MEME You can also use single-motif formats, although the Bio.Motif.read() function is simpler to use in this situation. - jaspar-pfm - jaspar-sites For example: >>> from Bio import Motif >>> with open("Motif/alignace.out") as handle: ... for motif in Motif.parse(handle, "AlignAce"): ... print(motif.consensus()) ... TCTACGATTGAG CTGCACCTAGCTACGAGTGAG GTGCCCTAAGCATACTAGGCG GCCACTAGCAGAGCAGGGGGC CGACTCAGAGGTT CCACGCTAAGAGAAGTGCCGGAG GCACGTCCCTGAGCA GTCCATCGCAAAGCGTGGGGC GAGATCAGAGGGCCG TGGACGCGGGG GACCAGAGCCTCGCATGGGGG AGCGCGCGTG GCCGGTTGCTGTTCATTAGG ACCGACGGCAGCTAAAAGGG GACGCCGGGGAT CGACTCGCGCTTACAAGG """ try: parser = _parsers[format] except KeyError: try: # not a true parser, try reader formats reader = _readers[format] except: raise ValueError("Wrong parser format") else: # we have a proper reader yield reader(handle) else: # we have a proper reader for m in parser(handle).motifs: yield m def read(handle, format): """Reads a motif from a handle using a specified file-format. This supports the same formats as Bio.Motif.parse(), but only for files containing exactly one record. For example, reading a pfm file: >>> from Bio import Motif >>> with open("Motif/SRF.pfm") as handle: ... motif = Motif.read(handle, "jaspar-pfm") ... >>> motif.consensus() Seq('GCCCATATATGG', IUPACUnambiguousDNA()) Or a single-motif MEME file, >>> from Bio import Motif >>> with open("Motif/meme.out") as handle: ... motif = Motif.read(handle, "MEME") ... >>> motif.consensus() Seq('CTCAATCGTA', IUPACUnambiguousDNA()) If the handle contains no records, or more than one record, an exception is raised: >>> from Bio import Motif >>> with open("Motif/alignace.out") as handle: ... motif = Motif.read(handle, "AlignAce") ... Traceback (most recent call last): ... ValueError: More than one motif found in handle If however you want the first record from a file containing multiple records this function would raise an exception (as shown in the example above). Instead use: >>> from Bio import Motif >>> with open("Motif/alignace.out") as handle: ... motif = next(Motif.parse(handle, "AlignAce")) ... >>> motif.consensus() Seq('TCTACGATTGAG', IUPACUnambiguousDNA()) Use the Bio.Motif.parse(handle, format) function if you want to read multiple records from the handle. """ iterator = parse(handle, format) try: first = next(iterator) except StopIteration: first = None if first is None: raise ValueError("No motifs found in handle") try: second = next(iterator) except StopIteration: second = None if second is not None: raise ValueError("More than one motif found in handle") return first if __name__ == "__main__": from Bio._utils import run_doctest run_doctest(verbose=0)

poojavade/Genomics_Docker

Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/Bio/Motif/__init__.py

Python

apache-2.0

5,092

[ "Biopython" ]

50f49464dde1ec92bb843b0d8ab985b5bf3bb24937d76bd3da88f8c18c7a305e

import sys sys.path.insert(1, "../../../") import h2o def link_incompatible_error(ip,port): print("Reading in original prostate data.") prostate = h2o.import_file(path=h2o.locate("smalldata/prostate/prostate.csv.zip")) print("Throw error when trying to create model with incompatible logit link.") try: h2o.model = h2o.glm(x=prostate[1:8], y=prostate[8], family="gaussian", link="logit") assert False, "expected an error" except EnvironmentError: assert True try: h2o.model = h2o.glm(x=prostate[1:8], y=prostate[8], family="tweedie", link="log") assert False, "expected an error" except EnvironmentError: assert True try: h2o.model = h2o.glm(x=prostate[2:9], y=prostate[1], family="binomial", link="inverse") assert False, "expected an error" except EnvironmentError: assert True if __name__ == "__main__": h2o.run_test(sys.argv, link_incompatible_error)

weaver-viii/h2o-3

h2o-py/tests/testdir_algos/glm/pyunit_link_incompatible_errorGLM.py

Python

apache-2.0

985

[ "Gaussian" ]

3a9fc598563419cb040746c614494c41bccc4ecf70c4859e4b17b2a3bb6fe05d

from setuptools import setup, find_packages import imp version = imp.load_source('crema.version', 'crema/version.py') setup( name='crema', version=version.version, description="Convolutional-recurrent estimators for music analysis", author='Brian McFee', url='http://github.com/bmcfee/crema', download_url='http://github.com/bmcfee/crema/releases', packages=find_packages(), package_data={'': ['models/*/*.pkl', 'models/*/*.h5', 'models/*/*.json', 'models/*/*.txt']}, long_description="Convolutional-recurrent estimators for music analysis", classifiers=[ "License :: OSI Approved :: ISC License (ISCL)", "Programming Language :: Python", "Development Status :: 3 - Alpha", "Intended Audience :: Developers", "Topic :: Software Development", "Programming Language :: Python :: 3", "Programming Language :: Python :: 3.5", "Programming Language :: Python :: 3.6", ], keywords='audio music learning', license='ISC', install_requires=['six', 'librosa>=0.6', 'jams>=0.3', 'scikit-learn>=0.18', 'keras>=2.0', 'tensorflow>=1.0', 'mir_eval>=0.5', 'pumpp>=0.4', 'h5py>=2.7'], extras_require={ 'docs': ['numpydoc', 'sphinx'], 'tests': ['pytest', 'pytest-cov'], 'training': ['pescador>=2.0.1', 'muda'] } )

bmcfee/crema

setup.py

Python

bsd-2-clause

1,596

[ "Brian" ]

a4f22d0c98b76281108b318ac7ce0442d560c9c0f21ae153547a89aaa9087b6c

""" Django settings for Exchange project. For more information on this file, see https://docs.djangoproject.com/en/1.7/topics/settings/ For the full list of settings and their values, see https://docs.djangoproject.com/en/1.7/ref/settings/ """ # Build paths inside the project like this: os.path.join(BASE_DIR, ...) import os import uuid BASE_DIR = os.path.dirname(os.path.dirname(__file__)) # Quick-start development settings - unsuitable for production # See https://docs.djangoproject.com/en/1.7/howto/deployment/checklist/ # SECURITY WARNING: keep the secret key used in production secret! SECRET_KEY = '%p*m%z8z)jxkgvt1b0m)ha=e$uexa$i5o5-tifc=-t#9%7p+gg' # SECURITY WARNING: don't run with debug turned on in production! DEBUG = True MEDIA_URL = '/api/1.0/files/' MEDIA_ROOT = os.path.join(BASE_DIR, 'assets') TEMPLATE_DEBUG = True ALLOWED_HOSTS = [] SENDER = '84e847f929d34f66a94bf376cf30d12c' LOGIN_URL = 'login' LOGIN_REDIRECT_URL = 'dashboard' # Application definition INSTALLED_APPS = ( 'sslserver', 'flat', 'activelink', 'django.contrib.admin', 'django.contrib.auth', 'django.contrib.contenttypes', 'django.contrib.sessions', 'django.contrib.messages', 'django.contrib.staticfiles', 'incidents', 'sending', 'corsheaders', 'oauth2_provider', 'rest_framework', 'widget_tweaks', 'datetimewidget', 'bootstrap_pagination', 'a_ppl_e', ) MIDDLEWARE_CLASSES = ( 'django.contrib.sessions.middleware.SessionMiddleware', 'corsheaders.middleware.CorsMiddleware', 'django.middleware.common.CommonMiddleware', 'django.middleware.csrf.CsrfViewMiddleware', 'django.middleware.locale.LocaleMiddleware', 'django.contrib.auth.middleware.AuthenticationMiddleware', 'django.contrib.auth.middleware.SessionAuthenticationMiddleware', 'django.contrib.messages.middleware.MessageMiddleware', 'django.middleware.clickjacking.XFrameOptionsMiddleware', ) TEMPLATE_DIRS = [os.path.join(BASE_DIR, 'Exchange', 'templates')] TEMPLATE_CONTEXT_PROCESSORS = ( 'django.core.context_processors.request', 'django.contrib.auth.context_processors.auth', 'django.core.context_processors.media', 'django.core.context_processors.request', ) ROOT_URLCONF = 'Exchange.urls' WSGI_APPLICATION = 'Exchange.wsgi.application' # Database # https://docs.djangoproject.com/en/1.7/ref/settings/#databases DATABASES = { 'default': { 'ENGINE': 'django.db.backends.sqlite3', 'NAME': os.path.join(BASE_DIR, 'db.sqlite3'), } } # Internationalization # https://docs.djangoproject.com/en/1.7/topics/i18n/ LANGUAGE_CODE = 'en-us' TIME_ZONE = 'UTC' USE_I18N = True USE_L10N = True USE_TZ = True # Static files (CSS, JavaScript, Images) # https://docs.djangoproject.com/en/1.7/howto/static-files/ STATIC_URL = '/static/' # Additional locations of static files STATICFILES_DIRS = ( os.path.join(BASE_DIR, 'assets'), ) # RestFramework REST_FRAMEWORK = { 'DEFAULT_AUTHENTICATION_CLASSES': ( 'oauth2_provider.ext.rest_framework.OAuth2Authentication', 'rest_framework.authentication.SessionAuthentication', ), # 'DEFAULT_PERMISSION_CLASSES': ( # 'rest_framework.permissions.IsAuthenticated', # ), 'PAGINATE_BY': 10, 'DEFAULT_PARSER_CLASSES': ( 'rest_framework.parsers.JSONParser', 'rest_framework.renderers.BrowsableAPIRenderer', ) } OAUTH2_PROVIDER = { # this is the list of available scopes 'SCOPES': {'subscriber': 'Subscriber', 'provider': 'Provider'} } CORS_ORIGIN_WHITELIST = ( 'localhost:8000', 'localhost:8800', ) OAUTH2_PROVIDER_APPLICATION_MODEL = 'oauth2_provider.Application' # TLP TLP_SCHEME = 'enisa' # US-CERT or ENISA TLP_DEFAULT_VALUE = 'green' # red, amber, green or white

SINTEF-Infosec/Incident-Information-Sharing-Tool

Exchange/settings.py

Python

apache-2.0

3,811

[ "Amber" ]

95a55d281d2c94d3d57a8c79eaceeff3567a526787b4272e1d7c3a5c4c5eef4b

# This file is part of PyEMMA. # # Copyright (c) 2015, 2014 Computational Molecular Biology Group, Freie Universitaet Berlin (GER) # # PyEMMA is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. from __future__ import absolute_import import warnings from pyemma._base.logging import Loggable from pyemma.util.types import is_string import mdtraj import six from pyemma.coordinates.data.featurization.util import (_parse_pairwise_input, _parse_groupwise_input) from .misc import CustomFeature import numpy as np __author__ = 'Frank Noe, Martin Scherer' __all__ = ['MDFeaturizer'] class MDFeaturizer(Loggable): r"""Extracts features from MD trajectories.""" def __init__(self, topfile): """extracts features from MD trajectories. Parameters ---------- topfile : str or mdtraj.Topology a path to a topology file (pdb etc.) or an mdtraj Topology() object """ self.topologyfile = None if isinstance(topfile, six.string_types): self.topology = (mdtraj.load(topfile)).topology self.topologyfile = topfile elif isinstance(topfile, mdtraj.Topology): self.topology = topfile else: raise ValueError("no valid topfile arg: type was %s, " "but only string or mdtraj.Topology allowed." % type(topfile)) self.active_features = [] self._dim = 0 self._showed_warning_empty_feature_list = False def __add_feature(self, f): # perform sanity checks if f.dimension == 0: self._logger.error("given an empty feature (eg. due to an empty/" "ineffective selection). Skipping it." " Feature desc: %s" % f.describe()) return if f not in self.active_features: self.active_features.append(f) else: self._logger.warning("tried to re-add the same feature %s" % f.__class__.__name__) def describe(self): """ Returns a list of strings, one for each feature selected, with human-readable descriptions of the features. Returns ------- labels : list of str An ordered list of strings, one for each feature selected, with human-readable descriptions of the features. """ all_labels = [] for f in self.active_features: all_labels += f.describe() return all_labels def select(self, selstring): """ Returns the indexes of atoms matching the given selection Parameters ---------- selstring : str Selection string. See mdtraj documentation for details: http://mdtraj.org/latest/atom_selection.html Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select(selstring) def select_Ca(self): """ Returns the indexes of all Ca-atoms Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select("name CA") def select_Backbone(self): """ Returns the indexes of backbone C, CA and N atoms Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select("backbone and (name C or name CA or name N)") def select_Heavy(self): """ Returns the indexes of all heavy atoms (Mass >= 2) Returns ------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ return self.topology.select("mass >= 2") @staticmethod def pairs(sel, excluded_neighbors=0): """ Creates all pairs between indexes. Will exclude closest neighbors up to :py:obj:`excluded_neighbors` The self-pair (i,i) is always excluded Parameters ---------- sel : ndarray((n), dtype=int) array with selected atom indexes excluded_neighbors: int, default = 0 number of neighbors that will be excluded when creating the pairs Returns ------- sel : ndarray((m,2), dtype=int) m x 2 array with all pair indexes between different atoms that are at least :obj:`excluded_neighbors` indexes apart, i.e. if i is the index of an atom, the pairs [i,i-2], [i,i-1], [i,i], [i,i+1], [i,i+2], will not be in :py:obj:`sel` (n=excluded_neighbors) if :py:obj:`excluded_neighbors` = 2. Moreover, the list is non-redundant,i.e. if [i,j] is in sel, then [j,i] is not. """ assert isinstance(excluded_neighbors,int) p = [] for i in range(len(sel)): for j in range(i + 1, len(sel)): # get ordered pair I = sel[i] J = sel[j] if (I > J): I = sel[j] J = sel[i] # exclude 1 and 2 neighbors if (J > I + excluded_neighbors): p.append([I, J]) return np.array(p) def _check_indices(self, pair_inds, pair_n=2): """ensure pairs are valid (shapes, all atom indices available?, etc.) """ pair_inds = np.array(pair_inds).astype(dtype=np.int, casting='safe') if pair_inds.ndim != 2: raise ValueError("pair indices has to be a matrix.") if pair_inds.shape[1] != pair_n: raise ValueError("pair indices shape has to be (x, %i)." % pair_n) if pair_inds.max() > self.topology.n_atoms: raise ValueError("index out of bounds: %i." " Maximum atom index available: %i" % (pair_inds.max(), self.topology.n_atoms)) return pair_inds def add_all(self): """ Adds all atom coordinates to the feature list. The coordinates are flattened as follows: [x1, y1, z1, x2, y2, z2, ...] """ # TODO: add possibility to align to a reference structure self.add_selection(list(range(self.topology.n_atoms))) def add_selection(self, indexes): """ Adds the coordinates of the selected atom indexes to the feature list. The coordinates of the selection [1, 2, ...] are flattened as follows: [x1, y1, z1, x2, y2, z2, ...] Parameters ---------- indexes : ndarray((n), dtype=int) array with selected atom indexes """ # TODO: add possibility to align to a reference structure from .misc import SelectionFeature f = SelectionFeature(self.topology, indexes) self.__add_feature(f) def add_distances(self, indices, periodic=True, indices2=None): r""" Adds the distances between atoms to the feature list. Parameters ---------- indices : can be of two types: ndarray((n, 2), dtype=int): n x 2 array with the pairs of atoms between which the distances shall be computed iterable of integers (either list or ndarray(n, dtype=int)): indices (not pairs of indices) of the atoms between which the distances shall be computed. periodic : optional, boolean, default is True If periodic is True and the trajectory contains unitcell information, distances will be computed under the minimum image convention. indices2: iterable of integers (either list or ndarray(n, dtype=int)), optional: Only has effect if :py:obj:`indices` is an iterable of integers. Instead of the above behaviour, only the distances between the atoms in :py:obj:`indices` and :py:obj:`indices2` will be computed. .. note:: When using the iterable of integers input, :py:obj:`indices` and :py:obj:`indices2` will be sorted numerically and made unique before converting them to a pairlist. Please look carefully at the output of :py:func:`describe()` to see what features exactly have been added. """ from .distances import DistanceFeature atom_pairs = _parse_pairwise_input( indices, indices2, self._logger, fname='add_distances()') atom_pairs = self._check_indices(atom_pairs) f = DistanceFeature(self.topology, atom_pairs, periodic=periodic) self.__add_feature(f) def add_distances_ca(self, periodic=True, excluded_neighbors=2): """ Adds the distances between all Ca's to the feature list. Parameters ---------- periodic : boolean, default is True Use the minimum image convetion when computing distances excluded_neighbors : int, default is 2 Number of exclusions when compiling the list of pairs. Two CA-atoms are considered neighbors if they belong to adjacent residues. """ # Atom indices for CAs at_idxs_ca = self.select_Ca() # Residue indices for residues contatinig CAs res_idxs_ca = [self.topology.atom(ca).residue.index for ca in at_idxs_ca] # Pairs of those residues, with possibility to exclude neighbors res_idxs_ca_pairs = self.pairs(res_idxs_ca, excluded_neighbors=excluded_neighbors) # Mapping back pairs of residue indices to pairs of CA indices distance_indexes = [] for ri, rj in res_idxs_ca_pairs: distance_indexes.append([self.topology.residue(ri).atom('CA').index, self.topology.residue(rj).atom('CA').index ]) distance_indexes = np.array(distance_indexes) self.add_distances(distance_indexes, periodic=periodic) def add_inverse_distances(self, indices, periodic=True, indices2=None): """ Adds the inverse distances between atoms to the feature list. Parameters ---------- indices : can be of two types: ndarray((n, 2), dtype=int): n x 2 array with the pairs of atoms between which the inverse distances shall be computed iterable of integers (either list or ndarray(n, dtype=int)): indices (not pairs of indices) of the atoms between which the inverse distances shall be computed. periodic : optional, boolean, default is True If periodic is True and the trajectory contains unitcell information, distances will be computed under the minimum image convention. indices2: iterable of integers (either list or ndarray(n, dtype=int)), optional: Only has effect if :py:obj:`indices` is an iterable of integers. Instead of the above behaviour, only the inverse distances between the atoms in :py:obj:`indices` and :py:obj:`indices2` will be computed. .. note:: When using the *iterable of integers* input, :py:obj:`indices` and :py:obj:`indices2` will be sorted numerically and made unique before converting them to a pairlist. Please look carefully at the output of :py:func:`describe()` to see what features exactly have been added. """ from .distances import InverseDistanceFeature atom_pairs = _parse_pairwise_input( indices, indices2, self._logger, fname='add_inverse_distances()') atom_pairs = self._check_indices(atom_pairs) f = InverseDistanceFeature(self.topology, atom_pairs, periodic=periodic) self.__add_feature(f) def add_contacts(self, indices, indices2=None, threshold=0.3, periodic=True, count_contacts=False): r""" Adds the contacts to the feature list. Parameters ---------- indices : can be of two types: ndarray((n, 2), dtype=int): n x 2 array with the pairs of atoms between which the contacts shall be computed iterable of integers (either list or ndarray(n, dtype=int)): indices (not pairs of indices) of the atoms between which the contacts shall be computed. indices2: iterable of integers (either list or ndarray(n, dtype=int)), optional: Only has effect if :py:obj:`indices` is an iterable of integers. Instead of the above behaviour, only the contacts between the atoms in :py:obj:`indices` and :py:obj:`indices2` will be computed. threshold : float, optional, default = .3 distances below this threshold (in nm) will result in a feature 1.0, distances above will result in 0.0. The default is set to .3 nm (3 Angstrom) periodic : boolean, default True use the minimum image convention if unitcell information is available count_contacts : boolean, default False If set to true, this feature will return the number of formed contacts (and not feature values with either 1.0 or 0) The ouput of this feature will be of shape (Nt,1), and not (Nt, nr_of_contacts) .. note:: When using the *iterable of integers* input, :py:obj:`indices` and :py:obj:`indices2` will be sorted numerically and made unique before converting them to a pairlist. Please look carefully at the output of :py:func:`describe()` to see what features exactly have been added. """ from .distances import ContactFeature atom_pairs = _parse_pairwise_input( indices, indices2, self._logger, fname='add_contacts()') atom_pairs = self._check_indices(atom_pairs) f = ContactFeature(self.topology, atom_pairs, threshold, periodic, count_contacts) self.__add_feature(f) def add_residue_mindist(self, residue_pairs='all', scheme='closest-heavy', ignore_nonprotein=True, threshold=None, periodic=True): r""" Adds the minimum distance between residues to the feature list. See below how the minimum distance can be defined. If the topology generated out of :py:obj:`topfile` contains information on periodic boundary conditions, the minimum image convention will be used when computing distances. Parameters ---------- residue_pairs : can be of two types: 'all' Computes distances between all pairs of residues excluding first and second neighbors ndarray((n, 2), dtype=int): n x 2 array with the pairs residues for which distances will be computed scheme : 'ca', 'closest', 'closest-heavy', default is closest-heavy Within a residue, determines the sub-group atoms that will be considered when computing distances ignore_nonprotein : boolean, default True Ignore residues that are not of protein type (e.g. water molecules, post-traslational modifications etc) threshold : float, optional, default is None distances below this threshold (in nm) will result in a feature 1.0, distances above will result in 0.0. If left to None, the numerical value will be returned periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. .. note:: Using :py:obj:`scheme` = 'closest' or 'closest-heavy' with :py:obj:`residue pairs` = 'all' will compute nearly all interatomic distances, for every frame, before extracting the closest pairs. This can be very time consuming. Those schemes are intended to be used with a subset of residues chosen via :py:obj:`residue_pairs`. """ from .distances import ResidueMinDistanceFeature if scheme != 'ca' and is_string(residue_pairs): if residue_pairs == 'all': self._logger.warning("Using all residue pairs with schemes like closest or closest-heavy is " "very time consuming. Consider reducing the residue pairs") f = ResidueMinDistanceFeature(self.topology, residue_pairs, scheme, ignore_nonprotein, threshold, periodic) self.__add_feature(f) def add_group_mindist(self, group_definitions, group_pairs='all', threshold=None, periodic=True, ): r""" Adds the minimum distance between groups of atoms to the feature list. If the groups of atoms are identical to residues, use :py:obj:`add_residue_mindist <pyemma.coordinates.data.featurizer.MDFeaturizer.add_residue_mindist>`. Parameters ---------- group_definition : list of 1D-arrays/iterables containing the group definitions via atom indices. If there is only one group_definition, it is assumed the minimum distance within this group (excluding the self-distance) is wanted. In this case, :py:obj:`group_pairs` is ignored. group_pairs : Can be of two types: 'all' Computes minimum distances between all pairs of groups contained in the group definitions ndarray((n, 2), dtype=int): n x 2 array with the pairs of groups for which the minimum distances will be computed. threshold : float, optional, default is None distances below this threshold (in nm) will result in a feature 1.0, distances above will result in 0.0. If left to None, the numerical value will be returned periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .distances import GroupMinDistanceFeature # Some thorough input checking and reformatting group_definitions, group_pairs, distance_list, group_identifiers = \ _parse_groupwise_input(group_definitions, group_pairs, self._logger, 'add_group_mindist') distance_list = self._check_indices(distance_list) f = GroupMinDistanceFeature(self.topology, group_definitions, group_pairs, distance_list, group_identifiers, threshold, periodic) self.__add_feature(f) def add_angles(self, indexes, deg=False, cossin=False, periodic=True): """ Adds the list of angles to the feature list Parameters ---------- indexes : np.ndarray, shape=(num_pairs, 3), dtype=int an array with triplets of atom indices deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import AngleFeature indexes = self._check_indices(indexes, pair_n=3) f = AngleFeature(self.topology, indexes, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_dihedrals(self, indexes, deg=False, cossin=False, periodic=True): """ Adds the list of dihedrals to the feature list Parameters ---------- indexes : np.ndarray, shape=(num_pairs, 4), dtype=int an array with quadruplets of atom indices deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import DihedralFeature indexes = self._check_indices(indexes, pair_n=4) f = DihedralFeature(self.topology, indexes, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_backbone_torsions(self, selstr=None, deg=False, cossin=False, periodic=True): """ Adds all backbone phi/psi angles or the ones specified in :obj:`selstr` to the feature list. Parameters ---------- selstr : str, optional, default = "" selection string specifying the atom selection used to specify a specific set of backbone angles If "" (default), all phi/psi angles found in the topology will be computed deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import BackboneTorsionFeature f = BackboneTorsionFeature( self.topology, selstr=selstr, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_chi1_torsions(self, selstr="", deg=False, cossin=False, periodic=True): """ Adds all chi1 angles or the ones specified in :obj:`selstr` to the feature list. Parameters ---------- selstr : str, optional, default = "" selection string specifying the atom selection used to specify a specific set of backbone angles If "" (default), all chi1 angles found in the topology will be computed deg : bool, optional, default = False If False (default), angles will be computed in radians. If True, angles will be computed in degrees. cossin : bool, optional, default = False If True, each angle will be returned as a pair of (sin(x), cos(x)). This is useful, if you calculate the mean (e.g TICA/PCA, clustering) in that space. periodic : bool, optional, default = True If `periodic` is True and the trajectory contains unitcell information, we will treat dihedrals that cross periodic images using the minimum image convention. """ from .angles import Chi1TorsionFeature f = Chi1TorsionFeature( self.topology, selstr=selstr, deg=deg, cossin=cossin, periodic=periodic) self.__add_feature(f) def add_custom_feature(self, feature): """ Adds a custom feature to the feature list. Parameters ---------- feature : object an object with interface like CustomFeature (map, describe methods) """ if feature.dimension <= 0: raise ValueError("Dimension has to be positive. " "Please override dimension attribute in feature!") if not hasattr(feature, 'map'): raise ValueError("no map method in given feature") else: if not callable(getattr(feature, 'map')): raise ValueError("map exists but is not a method") self.__add_feature(feature) def add_minrmsd_to_ref(self, ref, ref_frame=0, atom_indices=None, precentered=False): r""" Adds the minimum root-mean-square-deviation (minrmsd) with respect to a reference structure to the feature list. Parameters ---------- ref: Reference structure for computing the minrmsd. Can be of two types: 1. :py:obj:`mdtraj.Trajectory` object 2. filename for mdtraj to load. In this case, only the :py:obj:`ref_frame` of that file will be used. ref_frame: integer, default=0 Reference frame of the filename specified in :py:obj:`ref`. This parameter has no effect if :py:obj:`ref` is not a filename. atom_indices: array_like, default=None Atoms that will be used for: 1. aligning the target and reference geometries. 2. computing rmsd after the alignment. If left to None, all atoms of :py:obj:`ref` will be used. precentered: bool, default=False Use this boolean at your own risk to let mdtraj know that the target conformations are already centered at the origin, i.e., their (uniformly weighted) center of mass lies at the origin. This will speed up the computation of the rmsd. """ from .misc import MinRmsdFeature f = MinRmsdFeature(ref, ref_frame=ref_frame, atom_indices=atom_indices, topology=self.topology, precentered=precentered) self.__add_feature(f) def add_custom_func(self, func, dim, *args, **kwargs): """ adds a user defined function to extract features Parameters ---------- func : function a user-defined function, which accepts mdtraj.Trajectory object as first parameter and as many optional and named arguments as desired. Has to return a numpy.ndarray dim : int output dimension of :py:obj:`function` args : any number of positional arguments these have to be in the same order as :py:obj:`func` is expecting them kwargs : dictionary named arguments passed to func """ f = CustomFeature(func, dim=dim, *args, **kwargs) self.add_custom_feature(f) def dimension(self): """ current dimension due to selected features Returns ------- dim : int total dimension due to all selection features """ dim = sum(f.dimension for f in self.active_features) return dim def transform(self, traj): """ Maps an mdtraj Trajectory object to the selected output features Parameters ---------- traj : mdtraj Trajectory Trajectory object used as an input Returns ------- out : ndarray((T, n), dtype=float32) Output features: For each of T time steps in the given trajectory, a vector with all n output features selected. """ # if there are no features selected, return given trajectory if len(self.active_features) == 0: if not self._showed_warning_empty_feature_list: warnings.warn("You have no features selected." " Returning plain coordinates.") self._showed_warning_empty_feature_list = True s = traj.xyz.shape new_shape = (s[0], s[1] * s[2]) return traj.xyz.reshape(new_shape) # handle empty chunks (which might occur due to time lagged access if traj.xyz.shape[0] == 0: return np.empty((0, self.dimension())) # otherwise build feature vector. feature_vec = [] # TODO: consider parallel evaluation computation here, this effort is # only worth it, if computation time dominates memory transfers for f in self.active_features: # perform sanity checks for custom feature input if isinstance(f, CustomFeature): # NOTE: casting=safe raises in numpy>=1.9 vec = f.transform(traj).astype(np.float32, casting='safe') if vec.shape[0] == 0: vec = np.empty((0, f.dimension)) if not isinstance(vec, np.ndarray): raise ValueError('Your custom feature %s did not return' ' a numpy.ndarray!' % str(f.describe())) if not vec.ndim == 2: raise ValueError('Your custom feature %s did not return' ' a 2d array. Shape was %s' % (str(f.describe()), str(vec.shape))) if not vec.shape[0] == traj.xyz.shape[0]: raise ValueError('Your custom feature %s did not return' ' as many frames as it received!' 'Input was %i, output was %i' % (str(f.describe()), traj.xyz.shape[0], vec.shape[0])) else: vec = f.transform(traj).astype(np.float32) feature_vec.append(vec) if len(feature_vec) > 1: res = np.hstack(feature_vec) else: res = feature_vec[0] return res

gph82/PyEMMA

pyemma/coordinates/data/featurization/featurizer.py

Python

lgpl-3.0

30,879

[ "MDTraj" ]

49dc7204a2fb3d28b1d66bed6ea44ace927f8d09f42d9f001d7bcfc79ad3a925

from galaxy.managers import base as manager_base class LDDAManager( manager_base.ModelManager ): """ A fairly sparse manager for LDDAs. """ def __init__( self ): """ Set up and initialize other managers needed by lddas. """ pass def get( self, trans, id, check_accessible=True ): return manager_base.get_object( trans, id, 'LibraryDatasetDatasetAssociation', check_ownership=False, check_accessible=check_accessible )

mikel-egana-aranguren/SADI-Galaxy-Docker

galaxy-dist/lib/galaxy/managers/lddas.py

Python

gpl-3.0

518

[ "Galaxy" ]

4b54a33fb41741bb6224aa150894db633364138649df440007428d39e30e0dd4

# Orca # # Copyright 2006-2008 Sun Microsystems Inc. # # This library is free software; you can redistribute it and/or # modify it under the terms of the GNU Lesser General Public # License as published by the Free Software Foundation; either # version 2.1 of the License, or (at your option) any later version. # # This library is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU # Lesser General Public License for more details. # # You should have received a copy of the GNU Lesser General Public # License along with this library; if not, write to the # Free Software Foundation, Inc., Franklin Street, Fifth Floor, # Boston MA 02110-1301 USA. """Provides an HTTP server for Orca. This currently serves mainly as something that self-voicing applications can use as their speech service.""" __id__ = "$Id$" __version__ = "$Revision$" __date__ = "$Date$" __copyright__ = "Copyright (c) 2006-2008 Sun Microsystems Inc." __license__ = "LGPL" import threading import BaseHTTPServer import debug import orca_platform import settings import speech _httpRequestThread = None # Handlers for logging speech and braille output. # loggingFileHandlers = {} loggingStreamHandlers = {} class _HTTPRequestHandler(BaseHTTPServer.BaseHTTPRequestHandler): """Provides support for communicating with Orca via HTTP. This is mainly to support self-voicing applications that want to use Orca as a speech service. The protocol is simple: POST content is 'stop', 'speak:<text>', or 'isSpeaking'. To test this, run: wget --post-data='speak:hello world' localhost:20433 """ def log_request(self, code=None, size=None): """Override to avoid getting a log message on stdout for each GET, POST, etc. request""" pass def do_GET(self): self.send_response(200) self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write("<html><body>Orca %s</body></html>" \ % orca_platform.version) def do_POST(self): contentLength = self.headers.getheader('content-length') if contentLength: contentLength = int(contentLength) inputBody = self.rfile.read(contentLength) debug.println(debug.LEVEL_FINEST, "httpserver._HTTPRequestHandler received %s" \ % inputBody) if inputBody.startswith("speak:"): speech.speak(inputBody[6:]) self.send_response(200, 'OK') elif inputBody == "stop": speech.stop() self.send_response(200, 'OK') elif inputBody == "isSpeaking": self.send_response(200, 'OK') self.send_header("Content-type", "text/html") self.end_headers() self.wfile.write("%s" % speech.isSpeaking()) else: debug.println(debug.LEVEL_FINEST, "httpserver._HTTPRequestHandler received no data") class _HTTPRequestThread(threading.Thread): """Runs a _HTTPRequestHandler in a separate thread.""" def run(self): """Try to start an HTTP server on settings.httpServerPort. If this fails, retry settings.maxHttpServerRetries times, each time incrementing the server port number by 1. If we are still unable to start a server, just fail gracefully. """ portNo = settings.httpServerPort connected = False while not connected and \ (portNo < settings.httpServerPort + settings.maxHttpServerRetries): try: httpd = BaseHTTPServer.HTTPServer(('', portNo), _HTTPRequestHandler) connected = True except: if portNo == settings.httpServerPort: debug.printException(debug.LEVEL_WARNING) debug.println(debug.LEVEL_WARNING, "httpserver._HTTPRequestThread unable to start server " \ "on port %d" % portNo) portNo += 1 if not connected: debug.println(debug.LEVEL_WARNING, "httpserver._HTTPRequestThread server startup failed.") else: httpd.serve_forever() def init(): """Creates an HTTP server that listens for speak commands from a separate port defined by settings.httpServerPort. We run this as a daemon so it will die automatically when orca dies.""" global _httpRequestThread if settings.httpServerPort and (not _httpRequestThread): try: _httpRequestThread = _HTTPRequestThread() _httpRequestThread.setDaemon(True) _httpRequestThread.start() except: debug.printException(debug.LEVEL_WARNING) def shutdown(): """Stops the HTTP server. [[[WDW - not implemented yet.]]]""" pass

Alberto-Beralix/Beralix

i386-squashfs-root/usr/share/pyshared/orca/httpserver.py

Python

gpl-3.0

5,107

[ "ORCA" ]

356d67d915e45a058b3e20f617101c38246fab42fb4dcc54af998eca3affba62

import re from pygments.lexers.theorem import IsabelleLexer from pygments.lexer import RegexLexer, inherit, bygroups, words from pygments.token import * from . import encoding __all__ = ['IsarLexer'] class IsarLexer(IsabelleLexer): name = 'Isabelle/Isar' keyword_cartouche_text = ('text', 'txt', 'text_raw', 'chapter', 'section', 'subsection', 'subsubsection', 'paragraph', 'subparagraph', ) tokens = { 'root': [ (words(keyword_cartouche_text, prefix=r'\b', suffix=r'(%\w+)?(\s*\\<open>)'), bygroups(Keyword, Comment.Preproc, Comment), 'cartouche-text'), (r'\\<comment>.*$', Comment), (r'%\w+', Comment.Preproc), (r'\\<open>', String.Other, 'fact'), inherit, ], 'cartouche-text': [ (r'[^\\@]', Comment), (r'(@\{)(\w+)', bygroups(String.Other, Keyword), 'antiquotation'), (r'\\<open>', Text, '#push'), (r'\\<close>', Comment, '#pop'), (r'\\<[\^\w]+>', Comment.Symbol), (r'\\', Comment), ], 'antiquotation': [ (r'[^\{\}\\]', Text), (r'\{', String.Other, '#push'), (r'\}', String.Other, '#pop'), (r'\\<[\^\w]+>', String.Symbol), (r'\\', Text), ], 'fact': [ (r'\\<close>', String.Other, '#pop'), inherit, ], } def get_tokens_unprocessed(self, text): for index, token, value in RegexLexer.get_tokens_unprocessed(self, text): value = isar_decode(value) yield index, token, value def isar_decode(raw): global symbol_table if symbol_table is None: symbol_table = {} for line in symbols_raw.splitlines(): if line: if re.match(r"^#", line): continue m = re.match(r"^(\\<.*>)\s+code:\s+0x([0-9a-f]+).*$", line) assert m, "Failed to parse " + line n = int(m.group(2), 16) if n < 0x10000: symbol_table[m.group(1)] = chr(n) if isinstance(raw, str): raw = encoding.get_unicode(raw) def repl(m): if m.group(0) in symbol_table: return symbol_table[m.group(0)] else: return m.group(0) return re.sub(r"\\<[\^a-zA-Z]+>", repl, raw) # ~~/etc/symbols from Isabelle2016 symbol_table = None symbols_raw = """ \<zero> code: 0x01d7ec group: digit \<one> code: 0x01d7ed group: digit \<two> code: 0x01d7ee group: digit \<three> code: 0x01d7ef group: digit \<four> code: 0x01d7f0 group: digit \<five> code: 0x01d7f1 group: digit \<six> code: 0x01d7f2 group: digit \<seven> code: 0x01d7f3 group: digit \<eight> code: 0x01d7f4 group: digit \<nine> code: 0x01d7f5 group: digit \<A> code: 0x01d49c group: letter \ code: 0x00212c group: letter \<C> code: 0x01d49e group: letter \<D> code: 0x01d49f group: letter \<E> code: 0x002130 group: letter \<F> code: 0x002131 group: letter \<G> code: 0x01d4a2 group: letter \<H> code: 0x00210b group: letter \ code: 0x002110 group: letter \<J> code: 0x01d4a5 group: letter \<K> code: 0x01d4a6 group: letter \<L> code: 0x002112 group: letter \<M> code: 0x002133 group: letter \<N> code: 0x01d4a9 group: letter \<O> code: 0x01d4aa group: letter \ code: 0x01d4ab group: letter \<Q> code: 0x01d4ac group: letter \<R> code: 0x00211b group: letter \<S> code: 0x01d4ae group: letter \<T> code: 0x01d4af group: letter \ code: 0x01d4b0 group: letter \<V> code: 0x01d4b1 group: letter \<W> code: 0x01d4b2 group: letter \<X> code: 0x01d4b3 group: letter \<Y> code: 0x01d4b4 group: letter \<Z> code: 0x01d4b5 group: letter \<a> code: 0x01d5ba group: letter \ code: 0x01d5bb group: letter \<c> code: 0x01d5bc group: letter \<d> code: 0x01d5bd group: letter \<e> code: 0x01d5be group: letter \<f> code: 0x01d5bf group: letter \<g> code: 0x01d5c0 group: letter \<h> code: 0x01d5c1 group: letter \ code: 0x01d5c2 group: letter \<j> code: 0x01d5c3 group: letter \<k> code: 0x01d5c4 group: letter \<l> code: 0x01d5c5 group: letter \<m> code: 0x01d5c6 group: letter \<n> code: 0x01d5c7 group: letter \<o> code: 0x01d5c8 group: letter \ code: 0x01d5c9 group: letter \<q> code: 0x01d5ca group: letter \<r> code: 0x01d5cb group: letter \<s> code: 0x01d5cc group: letter \<t> code: 0x01d5cd group: letter \ code: 0x01d5ce group: letter \<v> code: 0x01d5cf group: letter \<w> code: 0x01d5d0 group: letter \<x> code: 0x01d5d1 group: letter \<y> code: 0x01d5d2 group: letter \<z> code: 0x01d5d3 group: letter \<AA> code: 0x01d504 group: letter \<BB> code: 0x01d505 group: letter \<CC> code: 0x00212d group: letter \<DD> code: 0x01d507 group: letter \<EE> code: 0x01d508 group: letter \<FF> code: 0x01d509 group: letter \<GG> code: 0x01d50a group: letter \<HH> code: 0x00210c group: letter \<II> code: 0x002111 group: letter \<JJ> code: 0x01d50d group: letter \<KK> code: 0x01d50e group: letter \<LL> code: 0x01d50f group: letter \<MM> code: 0x01d510 group: letter \<NN> code: 0x01d511 group: letter \<OO> code: 0x01d512 group: letter \<PP> code: 0x01d513 group: letter \<QQ> code: 0x01d514 group: letter \<RR> code: 0x00211c group: letter \<SS> code: 0x01d516 group: letter \<TT> code: 0x01d517 group: letter \<UU> code: 0x01d518 group: letter \<VV> code: 0x01d519 group: letter \<WW> code: 0x01d51a group: letter \<XX> code: 0x01d51b group: letter \<YY> code: 0x01d51c group: letter \<ZZ> code: 0x002128 group: letter \<aa> code: 0x01d51e group: letter \<bb> code: 0x01d51f group: letter \<cc> code: 0x01d520 group: letter \<dd> code: 0x01d521 group: letter \<ee> code: 0x01d522 group: letter \<ff> code: 0x01d523 group: letter \<gg> code: 0x01d524 group: letter \<hh> code: 0x01d525 group: letter \<ii> code: 0x01d526 group: letter \<jj> code: 0x01d527 group: letter \<kk> code: 0x01d528 group: letter \<ll> code: 0x01d529 group: letter \<mm> code: 0x01d52a group: letter \<nn> code: 0x01d52b group: letter \<oo> code: 0x01d52c group: letter \<pp> code: 0x01d52d group: letter \<qq> code: 0x01d52e group: letter \<rr> code: 0x01d52f group: letter \<ss> code: 0x01d530 group: letter \<tt> code: 0x01d531 group: letter \<uu> code: 0x01d532 group: letter \<vv> code: 0x01d533 group: letter \<ww> code: 0x01d534 group: letter \<xx> code: 0x01d535 group: letter \<yy> code: 0x01d536 group: letter \<zz> code: 0x01d537 group: letter \<alpha> code: 0x0003b1 group: greek \<beta> code: 0x0003b2 group: greek \<gamma> code: 0x0003b3 group: greek \<delta> code: 0x0003b4 group: greek \<epsilon> code: 0x0003b5 group: greek \<zeta> code: 0x0003b6 group: greek \<eta> code: 0x0003b7 group: greek \<theta> code: 0x0003b8 group: greek \<iota> code: 0x0003b9 group: greek \<kappa> code: 0x0003ba group: greek \<lambda> code: 0x0003bb group: greek abbrev: % \<mu> code: 0x0003bc group: greek \<nu> code: 0x0003bd group: greek \<xi> code: 0x0003be group: greek \<pi> code: 0x0003c0 group: greek \<rho> code: 0x0003c1 group: greek \<sigma> code: 0x0003c3 group: greek \<tau> code: 0x0003c4 group: greek \<upsilon> code: 0x0003c5 group: greek \<phi> code: 0x0003c6 group: greek \<chi> code: 0x0003c7 group: greek \<psi> code: 0x0003c8 group: greek \<omega> code: 0x0003c9 group: greek \<Gamma> code: 0x000393 group: greek \<Delta> code: 0x000394 group: greek \<Theta> code: 0x000398 group: greek \<Lambda> code: 0x00039b group: greek \<Xi> code: 0x00039e group: greek \<Pi> code: 0x0003a0 group: greek \<Sigma> code: 0x0003a3 group: greek \<Upsilon> code: 0x0003a5 group: greek \<Phi> code: 0x0003a6 group: greek \<Psi> code: 0x0003a8 group: greek \<Omega> code: 0x0003a9 group: greek \<bool> code: 0x01d539 group: letter \<complex> code: 0x002102 group: letter \<nat> code: 0x002115 group: letter \<rat> code: 0x00211a group: letter \<real> code: 0x00211d group: letter \<int> code: 0x002124 group: letter \<leftarrow> code: 0x002190 group: arrow abbrev: <. \<longleftarrow> code: 0x0027f5 group: arrow abbrev: <. \<longlongleftarrow> code: 0x00290e group: arrow abbrev: <. \<longlonglongleftarrow> code: 0x0021e0 group: arrow abbrev: <. \<rightarrow> code: 0x002192 group: arrow abbrev: .> abbrev: -> \<longrightarrow> code: 0x0027f6 group: arrow abbrev: .> abbrev: --> \<longlongrightarrow> code: 0x00290f group: arrow abbrev: .> abbrev: ---> \<longlonglongrightarrow> code: 0x0021e2 group: arrow abbrev: .> abbrev: ---> \<Leftarrow> code: 0x0021d0 group: arrow abbrev: <. \<Longleftarrow> code: 0x0027f8 group: arrow abbrev: <. \<Lleftarrow> code: 0x0021da group: arrow abbrev: <. \<Rightarrow> code: 0x0021d2 group: arrow abbrev: .> abbrev: => \<Longrightarrow> code: 0x0027f9 group: arrow abbrev: .> abbrev: ==> \<Rrightarrow> code: 0x0021db group: arrow abbrev: .> \<leftrightarrow> code: 0x002194 group: arrow abbrev: <> abbrev: <-> \<longleftrightarrow> code: 0x0027f7 group: arrow abbrev: <> abbrev: <-> abbrev: <--> \<Leftrightarrow> code: 0x0021d4 group: arrow abbrev: <> \<Longleftrightarrow> code: 0x0027fa group: arrow abbrev: <> \<mapsto> code: 0x0021a6 group: arrow abbrev: .> abbrev: |-> \<longmapsto> code: 0x0027fc group: arrow abbrev: .> abbrev: |--> \<midarrow> code: 0x002500 group: arrow abbrev: <> \<Midarrow> code: 0x002550 group: arrow abbrev: <> \<hookleftarrow> code: 0x0021a9 group: arrow abbrev: <. \<hookrightarrow> code: 0x0021aa group: arrow abbrev: .> \<leftharpoondown> code: 0x0021bd group: arrow abbrev: <. \<rightharpoondown> code: 0x0021c1 group: arrow abbrev: .> \<leftharpoonup> code: 0x0021bc group: arrow abbrev: <. \<rightharpoonup> code: 0x0021c0 group: arrow abbrev: .> \<rightleftharpoons> code: 0x0021cc group: arrow abbrev: <> abbrev: == \<leadsto> code: 0x00219d group: arrow abbrev: .> abbrev: ~> \<downharpoonleft> code: 0x0021c3 group: arrow \<downharpoonright> code: 0x0021c2 group: arrow \<upharpoonleft> code: 0x0021bf group: arrow #\<upharpoonright> code: 0x0021be group: arrow \<restriction> code: 0x0021be group: punctuation \<Colon> code: 0x002237 group: punctuation \<up> code: 0x002191 group: arrow \<Up> code: 0x0021d1 group: arrow \<down> code: 0x002193 group: arrow \<Down> code: 0x0021d3 group: arrow \<updown> code: 0x002195 group: arrow \<Updown> code: 0x0021d5 group: arrow \<langle> code: 0x0027e8 group: punctuation abbrev: << \<rangle> code: 0x0027e9 group: punctuation abbrev: >> \<lceil> code: 0x002308 group: punctuation abbrev: [. \<rceil> code: 0x002309 group: punctuation abbrev: .] \<lfloor> code: 0x00230a group: punctuation abbrev: [. \<rfloor> code: 0x00230b group: punctuation abbrev: .] \<lparr> code: 0x002987 group: punctuation abbrev: (| \<rparr> code: 0x002988 group: punctuation abbrev: |) \<lbrakk> code: 0x0027e6 group: punctuation abbrev: [| \<rbrakk> code: 0x0027e7 group: punctuation abbrev: |] \<lbrace> code: 0x002983 group: punctuation abbrev: {| \<rbrace> code: 0x002984 group: punctuation abbrev: |} \<guillemotleft> code: 0x0000ab group: punctuation abbrev: << \<guillemotright> code: 0x0000bb group: punctuation abbrev: >> \<bottom> code: 0x0022a5 group: logic \<top> code: 0x0022a4 group: logic \<and> code: 0x002227 group: logic abbrev: /\ abbrev: & \<And> code: 0x0022c0 group: logic abbrev: !! \<or> code: 0x002228 group: logic abbrev: \/ abbrev: | \<Or> code: 0x0022c1 group: logic abbrev: ?? \<forall> code: 0x002200 group: logic abbrev: ! abbrev: ALL \<exists> code: 0x002203 group: logic abbrev: ? abbrev: EX \<nexists> code: 0x002204 group: logic abbrev: ~? \<not> code: 0x0000ac group: logic abbrev: ~ \<box> code: 0x0025a1 group: logic \<diamond> code: 0x0025c7 group: logic \<diamondop> code: 0x0022c4 group: operator \<turnstile> code: 0x0022a2 group: relation abbrev: |- \<Turnstile> code: 0x0022a8 group: relation abbrev: |= \<tturnstile> code: 0x0022a9 group: relation abbrev: |- \<TTurnstile> code: 0x0022ab group: relation abbrev: |= \<stileturn> code: 0x0022a3 group: relation abbrev: -| \<surd> code: 0x00221a group: relation \<le> code: 0x002264 group: relation abbrev: <= \<ge> code: 0x002265 group: relation abbrev: >= \<lless> code: 0x00226a group: relation abbrev: << \<ggreater> code: 0x00226b group: relation abbrev: >> \<lesssim> code: 0x002272 group: relation \<greatersim> code: 0x002273 group: relation \<lessapprox> code: 0x002a85 group: relation \<greaterapprox> code: 0x002a86 group: relation \<in> code: 0x002208 group: relation abbrev: : \<notin> code: 0x002209 group: relation abbrev: ~: \<subset> code: 0x002282 group: relation \<supset> code: 0x002283 group: relation \<subseteq> code: 0x002286 group: relation abbrev: (= \<supseteq> code: 0x002287 group: relation abbrev: )= \<sqsubset> code: 0x00228f group: relation \<sqsupset> code: 0x002290 group: relation \<sqsubseteq> code: 0x002291 group: relation abbrev: [= \<sqsupseteq> code: 0x002292 group: relation abbrev: ]= \<inter> code: 0x002229 group: operator abbrev: Int \<Inter> code: 0x0022c2 group: operator abbrev: Inter abbrev: INT \<union> code: 0x00222a group: operator abbrev: Un \<Union> code: 0x0022c3 group: operator abbrev: Union abbrev: UN \<squnion> code: 0x002294 group: operator \<Squnion> code: 0x002a06 group: operator abbrev: SUP \<sqinter> code: 0x002293 group: operator \<Sqinter> code: 0x002a05 group: operator abbrev: INF \<setminus> code: 0x002216 group: operator \<propto> code: 0x00221d group: operator \<uplus> code: 0x00228e group: operator \<Uplus> code: 0x002a04 group: operator \<noteq> code: 0x002260 group: relation abbrev: ~= \<sim> code: 0x00223c group: relation \<doteq> code: 0x002250 group: relation abbrev: .= \<simeq> code: 0x002243 group: relation \<approx> code: 0x002248 group: relation \<asymp> code: 0x00224d group: relation \<cong> code: 0x002245 group: relation \<smile> code: 0x002323 group: relation \<equiv> code: 0x002261 group: relation abbrev: == \<frown> code: 0x002322 group: relation \<Join> code: 0x0022c8 \<bowtie> code: 0x002a1d \<prec> code: 0x00227a group: relation \<succ> code: 0x00227b group: relation \<preceq> code: 0x00227c group: relation \<succeq> code: 0x00227d group: relation \<parallel> code: 0x002225 group: punctuation abbrev: || \<bar> code: 0x0000a6 group: punctuation abbrev: || \<plusminus> code: 0x0000b1 group: operator \<minusplus> code: 0x002213 group: operator \<times> code: 0x0000d7 group: operator abbrev: <*> \<div> code: 0x0000f7 group: operator \<cdot> code: 0x0022c5 group: operator \<star> code: 0x0022c6 group: operator \<bullet> code: 0x002219 group: operator \<circ> code: 0x002218 group: operator \<dagger> code: 0x002020 \<ddagger> code: 0x002021 \<lhd> code: 0x0022b2 group: relation \<rhd> code: 0x0022b3 group: relation \<unlhd> code: 0x0022b4 group: relation \<unrhd> code: 0x0022b5 group: relation \<triangleleft> code: 0x0025c3 group: relation \<triangleright> code: 0x0025b9 group: relation \<triangle> code: 0x0025b3 group: relation \<triangleq> code: 0x00225c group: relation \<oplus> code: 0x002295 group: operator \<Oplus> code: 0x002a01 group: operator \<otimes> code: 0x002297 group: operator \<Otimes> code: 0x002a02 group: operator \<odot> code: 0x002299 group: operator \<Odot> code: 0x002a00 group: operator \<ominus> code: 0x002296 group: operator \<oslash> code: 0x002298 group: operator \<dots> code: 0x002026 group: punctuation abbrev: ... \<cdots> code: 0x0022ef group: punctuation \<Sum> code: 0x002211 group: operator abbrev: SUM \<Prod> code: 0x00220f group: operator abbrev: PROD \<Coprod> code: 0x002210 group: operator \<infinity> code: 0x00221e \<integral> code: 0x00222b group: operator \<ointegral> code: 0x00222e group: operator \<clubsuit> code: 0x002663 \<diamondsuit> code: 0x002662 \<heartsuit> code: 0x002661 \<spadesuit> code: 0x002660 \<aleph> code: 0x002135 \<emptyset> code: 0x002205 \<nabla> code: 0x002207 \<partial> code: 0x002202 \<flat> code: 0x00266d \<natural> code: 0x00266e \<sharp> code: 0x00266f \<angle> code: 0x002220 \<copyright> code: 0x0000a9 \<registered> code: 0x0000ae \<hyphen> code: 0x0000ad group: punctuation \<inverse> code: 0x0000af group: punctuation \<onequarter> code: 0x0000bc group: digit \<onehalf> code: 0x0000bd group: digit \<threequarters> code: 0x0000be group: digit \<ordfeminine> code: 0x0000aa \<ordmasculine> code: 0x0000ba \<section> code: 0x0000a7 \<paragraph> code: 0x0000b6 \<exclamdown> code: 0x0000a1 \<questiondown> code: 0x0000bf \<euro> code: 0x0020ac \<pounds> code: 0x0000a3 \<yen> code: 0x0000a5 \<cent> code: 0x0000a2 \<currency> code: 0x0000a4 \<degree> code: 0x0000b0 \<amalg> code: 0x002a3f group: operator \<mho> code: 0x002127 group: operator \<lozenge> code: 0x0025ca \<wp> code: 0x002118 \<wrong> code: 0x002240 group: relation \<acute> code: 0x0000b4 \<index> code: 0x000131 \<dieresis> code: 0x0000a8 \<cedilla> code: 0x0000b8 \<hungarumlaut> code: 0x0002dd \<bind> code: 0x00291c abbrev: >>= \<then> code: 0x002aa2 abbrev: >> \<some> code: 0x0003f5 \<hole> code: 0x002311 \<newline> code: 0x0023ce \<comment> code: 0x002015 group: document font: IsabelleText \<open> code: 0x002039 group: punctuation font: IsabelleText abbrev: << \<close> code: 0x00203a group: punctuation font: IsabelleText abbrev: >> \<here> code: 0x002302 font: IsabelleText \<^undefined> code: 0x002756 font: IsabelleText \<^noindent> code: 0x0021e4 group: document font: IsabelleText \<^smallskip> code: 0x002508 group: document font: IsabelleText \<^medskip> code: 0x002509 group: document font: IsabelleText \<^bigskip> code: 0x002501 group: document font: IsabelleText \<^item> code: 0x0025aa group: document font: IsabelleText \<^enum> code: 0x0025b8 group: document font: IsabelleText \<^descr> code: 0x0027a7 group: document font: IsabelleText \<^footnote> code: 0x00204b group: document font: IsabelleText \<^verbatim> code: 0x0025a9 group: document font: IsabelleText \<^theory_text> code: 0x002b1a group: document font: IsabelleText \<^emph> code: 0x002217 group: document font: IsabelleText \<^bold> code: 0x002759 group: control group: document font: IsabelleText \<^sub> code: 0x0021e9 group: control font: IsabelleText \<^sup> code: 0x0021e7 group: control font: IsabelleText \<^bsub> code: 0x0021d8 group: control_block font: IsabelleText abbrev: =_( \<^esub> code: 0x0021d9 group: control_block font: IsabelleText abbrev: =_) \<^bsup> code: 0x0021d7 group: control_block font: IsabelleText abbrev: =^( \<^esup> code: 0x0021d6 group: control_block font: IsabelleText abbrev: =^) """

KITPraktomatTeam/Praktomat

src/utilities/isar_lexer.py

Python

gpl-2.0

24,376

[ "Bowtie" ]

61c5a9afbe1245838a7e7f294fb623705327ad256a0d1dac8550c029e047e0c9

import os from os.path import join as pjoin import numpy as np import h5py from gps_viewer import read_gps_fields from WGS84toENU import WGS84toECEF, WGS84toENU from pipeline_config import EXPORT_STEP, EXPORT_START, MAPPING_PATH, ICP_ITERS, ICP_MAX_DIST, NUM_CPUS from graphslam_config import MATCH_JSON_DATA, CHUNK_SIZE, GRAPHSLAM_CHUNK_DIR, GRAPHSLAM_ALIGN_DIR, REALIGN_EVERY from pipeline_utils import print_and_call, dset_dir_from_rss from joblib import Parallel, delayed ''' For every alignment, we need to create two small chunks of the full maps that we want to align. These chunks are selected by looking at the best NN matches. We compute a new alignment every REALIGN_EVERY steps Since the chunks are stored relative to IMU 0, we need to first transform them by the global position of IMU 0 ''' def get_ecef0(gps_file): llh = read_gps_fields(gps_file, ['lat', 'long', 'height']) llh = np.array(llh, dtype=np.float64).T ecef = WGS84toECEF(llh) return ecef[:, 0] def get_enu0(gps_file, gps_ref_file): llh = read_gps_fields(gps_file, ['lat', 'long', 'height']) llh = np.array(llh, dtype=np.float64).T llh_ref = read_gps_fields(gps_ref_file, ['lat', 'long', 'height']) llh_ref = np.array(llh_ref, dtype=np.float64).T return WGS84toENU(llh_ref[0, :], llh)[:, 0] def vtk_filename(pcd_file): return os.path.splitext(pcd_file)[0] + '.vtk' # Helper function for chunk_and_align all def chunk_and_align(start1, start2, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num, debug=False): chunk1_files = list() chunk2_files = list() for k in range(0, CHUNK_SIZE): ind1 = start1 + k chunk1_files.append('%s/%d.pcd' % (pcd_dir1, ind1)) assert os.path.exists(chunk1_files[-1]) ind2 = start2 + k chunk2_files.append('%s/%d.pcd' % (pcd_dir2, ind2)) assert os.path.exists(chunk2_files[-1]) merged_chunks1 = '%s/%s' % (GRAPHSLAM_CHUNK_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '%d_1.pcd' % chunk_num) merged_chunks2 = '%s/%s' % (GRAPHSLAM_CHUNK_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '%d_2.pcd' % chunk_num) # Concatenate cmd = 'concatenate_points_pcd %s %s' % (' '.join(chunk1_files), merged_chunks1) print_and_call(cmd) cmd = 'concatenate_points_pcd %s %s' % (' '.join(chunk2_files), merged_chunks2) print_and_call(cmd) # Translate cmd = 'transform_point_cloud %s %s -trans %f,%f,%f' % (merged_chunks1, merged_chunks1, enu1[0]-enu2[0], enu1[1]-enu2[1], enu1[2]-enu2[2]) print_and_call(cmd) #cmd = 'transform_point_cloud %s %s -trans %f,%f,%f' % (merged_chunks2, merged_chunks2, -1*enu2[0], -1*enu2[1], -1*enu2[2]) #print_and_call(cmd) # Generate VTK files so we can easily visualize to debug if debug: cmd = 'pcl_pcd2vtk %s %s' % (merged_chunks1, vtk_filename(merged_chunks1)) print_and_call(cmd) cmd = 'pcl_pcd2vtk %s %s' % (merged_chunks2, vtk_filename(merged_chunks2)) print_and_call(cmd) # Finally perform alignment reg = '%s/bin/align_clouds' % MAPPING_PATH h5f = '%s/%s' % (GRAPHSLAM_ALIGN_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '--%d' % chunk_num + '.h5') cmd = '{reg} --pcd_tgt {tgt} --pcd_src {src} --h5_file {h5f} --icp_iters {iters} --max_dist {dist}'.format( reg=reg, tgt=merged_chunks1, src=merged_chunks2, h5f=h5f, iters=ICP_ITERS, dist=ICP_MAX_DIST) print_and_call(cmd) def get_closest_key_value(k, d, max_shift=5): shift = -1 while k not in d: k = k + shift shift = -1 * (abs(shift) + 1) * cmp(shift, 0) assert abs(shift) < max_shift, 'Index %d shift %d' % (k, shift) return d[k] def chunk_and_align_all(d): print d['match_file'] rss1 = d['rss1'] rss2 = d['rss2'] pcd_dir1 = pjoin(dset_dir_from_rss(rss1), 'pcd_downsampled_normals') pcd_dir2 = pjoin(dset_dir_from_rss(rss2), 'pcd_downsampled_normals') # Read and save initial transform files enu1 = get_enu0(d['gps_file1'], d['gps_file1']) enu2 = get_enu0(d['gps_file2'], d['gps_file1']) h5f = h5py.File(d['match_file'], 'r') nn_matches = h5f['matches'][...] nn_dict = dict(zip(nn_matches[:, 1], nn_matches[:, 0])) h5f.close() assert EXPORT_START == 0 start1 = nn_matches[0, 1] / EXPORT_STEP args_all = list() chunk_num = 0 for k in range(start1, nn_matches[-1, 1] / EXPORT_STEP - CHUNK_SIZE, REALIGN_EVERY): #def chunk_and_align(start1, start2, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num): try: k2 = get_closest_key_value(k * EXPORT_STEP, nn_dict, max_shift=10) except: # TODO Think this sometimes occurs near end of alignments break args_all.append((k, k2 / EXPORT_STEP, enu1, enu2, rss1, rss2, pcd_dir1, pcd_dir2, chunk_num)) chunk_num += 1 Parallel(n_jobs=NUM_CPUS)(delayed(chunk_and_align)(*args) for args in args_all) # For debugging ''' for args in args_all: _, _, _, _, rss1, rss2, _, _, chunk_num = args h5f = '%s/%s' % (GRAPHSLAM_ALIGN_DIR, '--'.join(rss1) + '+' + '--'.join(rss2) + '--%d' % chunk_num + '.h5') if os.path.exists(h5f): continue chunk_and_align(*args) ''' if __name__ == '__main__': for d in MATCH_JSON_DATA: chunk_and_align_all(d)

sameeptandon/sail-car-log

mapping/sandbox/graphslam/chunk_and_align.py

Python

bsd-2-clause

5,357

[ "VTK" ]

414b8c0d82019578c57f08a0083dc05df46e79e997a55ce50c75a211508ceb39

#!/usr/bin/env python3 # -*- coding=utf-8 -*- """ cry2cif\n\n Read the last geometry corresponding to the CRYSTALLOGRAPHIC CELL on a CRYSTAL09 output file and print it in a cif format. If geometry optimization did not converge, input geometry is printed instead. """ # TODO: # * returns coordinates instead of write a file # * make functions for various formats __author__ = "Germain Vallverdu" __email__ = "germain.vallverdu@univ-pau.fr" __licence__ = "GPL" import os import argparse from pymatgen import Structure, Lattice from crystalio import CrystalOutfile def get_options(): """ get options from command lines """ parser = argparse.ArgumentParser(prog="cry2cif", description=__doc__) # mandatory argument is CRYSTAL output filename parser.add_argument("filename", help="CRYSTAL output file", metavar="FILENAME", type=str) # choose either cif or POSCAR format parser.add_argument("-t", "--to", help="output format: either cif or VASP (POSCAR)", metavar="format", default="cif", choices=("cif", "vasp"), type=str) # center slab or nanotubes parser.add_argument("-i", "--center", help="move the slab or nanotubes in the center of the box", action="store_true", dest="center", default=False) parser.add_argument("-n", "--num_structure", help="Structure number to be extracted (default, the last)", metavar="N", default=-1, type=int) # sort atom along z or x for slab or nanotubes parser.add_argument("-z", "--sortz", help="Sort atoms along z axis (for slabs)", dest="sortz", action="store_true", default=False) parser.add_argument("-x", "--sortx", help="Sort atoms along x axis (for nanotubes)", dest="sortx", action="store_true", default=False) # in the case of slabs or nanotubes, you have to give a value for b or c parser.add_argument("-b", help="lattice parameter b", metavar="b", default=50, type=float) parser.add_argument("-c", help="lattice parameter c", metavar="c", default=50, type=float) return parser.parse_args() def cry2cif(filename, to="cif", center=False, sortx=False, sortz=False, b_dum=50, c_dum=50, istruct=-1): """ Read a CRYSTAL output file and return the structure in a cif or POSCAR format. Args: filename (str): crystal output filename to (str): 'cif' or 'vasp', format of the output file (default is cif) center (bool): if True, the slab or nanotube is translated to the center of the box (default is False) sortx (bool): Nanotube : if True, atoms are sorted along x axes (default is False). sortz (bool): slab : if True, atoms are sorted along z axes (default is False). b_dum (float): dummy lattice paramters b in angstrom for nanotubes (default 50 A) c_dum (float): dummy lattice paramters c in angstrom for nanotubes and slabs (default 50 A) istruct (int): structure to be extracted """ cryout = CrystalOutfile(filename) print("title : ", cryout.title) if cryout.group: print("group : ", cryout.group) # print("Number of structure read: ", len(cryout.structures)) if istruct == -1: print("structure : Final structure") structure = cryout.final_structure else: print("structure : Structure %d" % istruct) structure = cryout.get_structure(istruct) print("# atom : ", structure.num_sites) print("composition: ", structure.composition) print("Cell parameters:") print("a : %10.4f" % structure.lattice.a) print("b : %10.4f" % structure.lattice.b) print("c : %10.4f" % structure.lattice.c) print("alpha : %10.4f" % structure.lattice.alpha) print("beta : %10.4f" % structure.lattice.beta) print("gamma : %10.4f" % structure.lattice.gamma) # ---------------------------------------------------------- # New b and c axes # ---------------------------------------------------------- if cryout.slab: frac_coords = structure.frac_coords frac_coords[:, 2] *= structure.lattice.c / c_dum matrix = structure.lattice.matrix.copy() matrix[2, 2] = c_dum structure = Structure(Lattice(matrix), structure.species, frac_coords) if cryout.nanotube: frac_coords = structure.frac_coords frac_coords[:, 1] *= structure.lattice.c / c_dum frac_coords[:, 2] *= structure.lattice.b / b_dum matrix = structure.lattice.matrix.copy() matrix[1, 1] = b_dum matrix[2, 2] = c_dum structure = Structure(Lattice(matrix), structure.species, frac_coords) # ---------------------------------------------------------- # move slab or nanotube to the center of the box # ---------------------------------------------------------- if center: if cryout.slab: coords = structure.frac_coords.copy() coords[:, 2] += .5 structure = Structure(structure.lattice, structure.species, coords) elif cryout.nanotube: coords = structure.frac_coords coords += .5 structure = Structure(structure.lattice, structure.species, coords) # ---------------------------------------------------------- # sort atom along x or z axis for slab # ---------------------------------------------------------- if sortz: isort = 2 elif sortx: isort = 0 axes = {2: "z", 0: "x"} if sortz or sortx: print("\nSort atoms along %s" % axes[isort]) data = zip(structure.species, structure.frac_coords) data = sorted(data, key=lambda d: d[-1][isort], reverse=True) species = [d[0] for d in data] coords = [d[1] for d in data] structure = Structure(structure.lattice, species, coords) # ---------------------------------------------------------- # export in the given format # ---------------------------------------------------------- basename, _ = os.path.splitext(filename) if to.lower() == "cif": ext = ".cif" elif to.lower() == "vasp": to = "POSCAR" ext = ".vasp" else: to = "POSCAR" ext = ".vasp" structure.to(to, filename=basename + ext) if __name__ == "__main__": # get arguments args = vars(get_options()) # rename some args args["b_dum"] = args.pop("b") args["c_dum"] = args.pop("c") args["istruct"] = args.pop("num_structure") # call main program cry2cif(**args)

gVallverdu/myScripts

CRYSTAL/cry2cif.py

Python

gpl-2.0

7,246

[ "CRYSTAL", "VASP", "pymatgen" ]

9f17d1ca622a9d8ac35c6fbed0c90143cc262316cfc129f48e071549c112913e

from __future__ import print_function from __future__ import division from __future__ import unicode_literals import numpy as np from rdkit import Chem import itertools, operator from deepchem.feat import Featurizer from deepchem.feat.mol_graphs import ConvMol def one_of_k_encoding(x, allowable_set): if x not in allowable_set: raise Exception( "input {0} not in allowable set{1}:".format(x, allowable_set)) return list(map(lambda s: x == s, allowable_set)) def one_of_k_encoding_unk(x, allowable_set): """Maps inputs not in the allowable set to the last element.""" if x not in allowable_set: x = allowable_set[-1] return list(map(lambda s: x == s, allowable_set)) def get_intervals(l): """For list of lists, gets the cumulative products of the lengths""" intervals = len(l) * [0] # Initalize with 1 intervals[0] = 1 for k in range(1, len(l)): intervals[k] = (len(l[k]) + 1) * intervals[k-1] return intervals def safe_index(l, e): """Gets the index of e in l, providing an index of len(l) if not found""" try: return l.index(e) except: return len(l) possible_atom_list = ['C', 'N', 'O', 'S', 'F', 'P', 'Cl', 'Mg', 'Na', 'Br', 'Fe', 'Ca', 'Cu', 'Mc', 'Pd', 'Pb', 'K','I','Al','Ni','Mn'] possible_numH_list = [0, 1, 2, 3, 4] possible_valence_list = [0, 1, 2, 3, 4, 5, 6] possible_formal_charge_list = [-3, -2, -1, 0, 1, 2, 3] possible_hybridization_list = [Chem.rdchem.HybridizationType.SP, Chem.rdchem.HybridizationType.SP2, Chem.rdchem.HybridizationType.SP3, Chem.rdchem.HybridizationType.SP3D, Chem.rdchem.HybridizationType.SP3D2] possible_number_radical_e_list = [0, 1, 2] reference_lists = [possible_atom_list, possible_numH_list, possible_valence_list, possible_formal_charge_list, possible_number_radical_e_list, possible_hybridization_list] intervals = get_intervals(reference_lists) def get_feature_list(atom): features = 6 * [0] features[0] = safe_index(possible_atom_list, atom.GetSymbol()) features[1] = safe_index(possible_numH_list, atom.GetTotalNumHs()) features[2] = safe_index(possible_valence_list, atom.GetImplicitValence()) features[3] = safe_index(possible_formal_charge_list, atom.GetFormalCharge()) features[4] = safe_index(possible_number_radical_e_list, atom.GetNumRadicalElectrons()) features[5] = safe_index(possible_hybridization_list, atom.GetHybridization()) return features def features_to_id(features, intervals): """Convert list of features into index using spacings provided in intervals""" id = 0 for k in range(len(intervals)): id += features[k] * intervals[k] # Allow 0 index to correspond to null molecule 1 id = id + 1 return id def id_to_features(id, intervals): features = 6* [0] # Correct for null id -= 1 for k in range(0,6-1): #print(6-k-1, id) features[6-k-1] = id // intervals[6-k-1] id -= features[6-k-1]*intervals[6-k-1] # Correct for last one features[0] = id return features def atom_to_id(atom): """Return a unique id corresponding to the atom type""" features = get_feature_list(atom) return features_to_id(features, intervals) def atom_features(atom, bool_id_feat=False): if bool_id_feat: return np.array([atom_to_id(atom)]) else: return np.array(one_of_k_encoding_unk( atom.GetSymbol(), ['C', 'N', 'O', 'S', 'F', 'Si', 'P', 'Cl', 'Br', 'Mg', 'Na', 'Ca', 'Fe', 'As', 'Al', 'I', 'B', 'V', 'K', 'Tl', 'Yb', 'Sb', 'Sn', 'Ag', 'Pd', 'Co', 'Se', 'Ti', 'Zn', 'H', # H? 'Li', 'Ge', 'Cu', 'Au', 'Ni', 'Cd', 'In', 'Mn', 'Zr', 'Cr', 'Pt', 'Hg', 'Pb', 'Unknown']) + one_of_k_encoding(atom.GetDegree(), [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]) + one_of_k_encoding_unk(atom.GetTotalNumHs(), [0, 1, 2, 3, 4]) + one_of_k_encoding_unk(atom.GetImplicitValence(), [0, 1, 2, 3, 4, 5, 6]) + [atom.GetFormalCharge(), atom.GetNumRadicalElectrons()] + one_of_k_encoding_unk( atom.GetHybridization(), [Chem.rdchem.HybridizationType.SP, Chem.rdchem.HybridizationType.SP2, Chem.rdchem.HybridizationType.SP3, Chem.rdchem.HybridizationType.SP3D, Chem.rdchem.HybridizationType.SP3D2]) + [atom.GetIsAromatic()]) def bond_features(bond): bt = bond.GetBondType() return np.array([bt == Chem.rdchem.BondType.SINGLE, bt == Chem.rdchem.BondType.DOUBLE, bt == Chem.rdchem.BondType.TRIPLE, bt == Chem.rdchem.BondType.AROMATIC, bond.GetIsConjugated(), bond.IsInRing()]) class ConvMolFeaturizer(Featurizer): name = ['conv_mol'] def __init__(self): # Since ConvMol is an object and not a numpy array, need to set dtype to # object. self.dtype = object def _featurize(self, mol): """Encodes mol as a ConvMol object.""" # Get the node features idx_nodes = [(a.GetIdx(), atom_features(a)) for a in mol.GetAtoms()] idx_nodes.sort() # Sort by ind to ensure same order as rd_kit idx, nodes = list(zip(*idx_nodes)) # Stack nodes into an array nodes = np.vstack(nodes) # Get bond lists with reverse edges included edge_list = [(b.GetBeginAtomIdx(), b.GetEndAtomIdx()) for b in mol.GetBonds()] # Get canonical adjacency list canon_adj_list = [[] for mol_id in range(len(nodes))] for edge in edge_list: canon_adj_list[edge[0]].append(edge[1]) canon_adj_list[edge[1]].append(edge[0]) return ConvMol(nodes, canon_adj_list)

bowenliu16/deepchem

deepchem/feat/graph_features.py

Python

gpl-3.0

5,773

[ "RDKit" ]

3db79ed9e095690295e0992c0c4bdeb6ffc10f0a76c2912a83a6ed48e5f5623a

from django.conf import settings from django.db import models from django.utils import timezone from patients.models import Patient class BaseActe(models.Model): """ Base Abstract class for for differnets actions made by usej """ patient = models.ForeignKey( Patient, related_name="%(class)ss", on_delete=models.CASCADE) created = models.DateTimeField(auto_now_add=True) modified = models.DateTimeField(default=timezone.now) owner = models.ForeignKey( settings.AUTH_USER_MODEL, related_name="%(class)ss", on_delete=models.PROTECT) class Meta: abstract = True def save(self, *args, **kwargs): self.modified = timezone.now() super().save() class Observation(BaseActe): """ A small text of user about a patient motif : purpose of the visit. can't be blank.this is the most minimam thing a user schould enter. """ motif = models.CharField(max_length=40, blank=False) body = models.TextField(blank=True) def __str__(self): return self.motif """ BAseActe: non modifiable if not today Observation : TA/pouls conclusion ordonnance vaccin certif titre texte courries dest corps courriers reçus spé nom contenu pdf examens: type effecteur pdf REGROUPER courrier et examens ? bio antécédants intolérances allergies """

jgirardet/unolog

unolog/actes/models.py

Python

gpl-3.0

1,489

[ "VisIt" ]

0b89dc5a4ddddea18047f66e5b2b2f662314ff240eac48725e7754089f9ed475

# Copyright 2013-2021 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from collections import defaultdict from spack import * from spack.util.environment import is_system_path class Cdo(AutotoolsPackage): """CDO is a collection of command line Operators to manipulate and analyse Climate and NWP model Data. """ homepage = 'https://code.mpimet.mpg.de/projects/cdo' url = 'https://code.mpimet.mpg.de/attachments/download/12760/cdo-1.7.2.tar.gz' list_url = 'https://code.mpimet.mpg.de/projects/cdo/files' maintainers = ['skosukhin', 'Try2Code'] version('2.0.2', sha256='34dfdd0d4126cfd35fc69e37e60901c8622d13ec5b3fa5f0fe6a1cc866cc5a70', url='https://code.mpimet.mpg.de/attachments/download/26654/cdo-2.0.2.tar.gz') version('2.0.1', sha256='d0794d261e22efa0adac8e6d18de2b60d54de5e1a4df6127c65fc417feb8fdac', url='https://code.mpimet.mpg.de/attachments/download/26477/cdo-2.0.1.tar.gz') version('2.0.0', sha256='6bca54e9d69d8c1f072f1996547b7347a65743d15ba751967e9bb16e0ff7a843', url='https://code.mpimet.mpg.de/attachments/download/26370/cdo-2.0.0.tar.gz') version('1.9.10', sha256='cc39c89bbb481d7b3945a06c56a8492047235f46ac363c4f0d980fccdde6677e', url='https://code.mpimet.mpg.de/attachments/download/24638/cdo-1.9.10.tar.gz') version('1.9.9', sha256='959b5b58f495d521a7fd1daa84644888ec87d6a0df43f22ad950d17aee5ba98d', url='https://code.mpimet.mpg.de/attachments/download/23323/cdo-1.9.9.tar.gz') version('1.9.8', sha256='f2660ac6f8bf3fa071cf2a3a196b3ec75ad007deb3a782455e80f28680c5252a', url='https://code.mpimet.mpg.de/attachments/download/20826/cdo-1.9.8.tar.gz') version('1.9.7.1', sha256='3771952e065bcf935d43e492707370ed2a0ecb59a06bea24f9ab69d77943962c', url='https://code.mpimet.mpg.de/attachments/download/20124/cdo-1.9.7.1.tar.gz') version('1.9.6', sha256='b31474c94548d21393758caa33f35cf7f423d5dfc84562ad80a2bdcb725b5585', url='https://code.mpimet.mpg.de/attachments/download/19299/cdo-1.9.6.tar.gz') version('1.9.5', sha256='48ed65cc5b436753c8e7f9eadd8aa97376698ce230ceafed2a4350a5b1a27148', url='https://code.mpimet.mpg.de/attachments/download/18264/cdo-1.9.5.tar.gz') version('1.9.4', sha256='3d1c0fd3f7d38c5d3d88139ca1546c9d24e1b1ff752a794a4194dfe624695def', url='https://code.mpimet.mpg.de/attachments/download/17374/cdo-1.9.4.tar.gz') version('1.9.3', sha256='e83a3de7b402600c0d9a5df18073d36d133ff9719d3c561a0efa90f9c1599f3f', url='https://code.mpimet.mpg.de/attachments/download/16435/cdo-1.9.3.tar.gz') version('1.9.2', sha256='d1c5092167034a48e4b8ada24cf78a1d4b84e364ffbb08b9ca70d13f428f300c', url='https://code.mpimet.mpg.de/attachments/download/16035/cdo-1.9.2.tar.gz') version('1.9.1', sha256='33cba3cfcc27e5896769143c5f8e2f300ca14c7a40d1f19ffd1ed24b49ea3d55', url='https://code.mpimet.mpg.de/attachments/download/15653/cdo-1.9.1.tar.gz') version('1.9.0', sha256='df367f8c3abf4ab085bcfc61e0205b28a5ecc69b7b83ba398b4d3c874dd69008', url='https://code.mpimet.mpg.de/attachments/download/15187/cdo-1.9.0.tar.gz') version('1.8.2', sha256='6ca6c1263af2237737728ac937a275f8aa27680507636a6b6320f347c69a369a', url='https://code.mpimet.mpg.de/attachments/download/14686/cdo-1.8.2.tar.gz') version('1.7.2', sha256='4c43eba7a95f77457bfe0d30fb82382b3b5f2b0cf90aca6f0f0a008f6cc7e697', url='https://code.mpimet.mpg.de/attachments/download/12760/cdo-1.7.2.tar.gz') variant('netcdf', default=True, description='Enable NetCDF support') variant('grib2', default='eccodes', values=('eccodes', 'grib-api', 'none'), description='Specify GRIB2 backend') variant('external-grib1', default=False, description='Ignore the built-in support and use the external ' 'GRIB2 backend for GRIB1 files') variant('szip', default=True, description='Enable szip compression for GRIB1') variant('hdf5', default=True, description='Enable HDF5 support') variant('udunits2', default=True, description='Enable UDUNITS2 support') variant('libxml2', default=True, description='Enable libxml2 support') variant('proj', default=True, description='Enable PROJ library for cartographic projections') variant('curl', default=False, description='Enable curl support') variant('fftw3', default=True, description='Enable support for fftw3') variant('magics', default=False, description='Enable Magics library support') variant('openmp', default=True, description='Enable OpenMP support') depends_on('pkgconfig', type='build') depends_on('netcdf-c', when='+netcdf') # The internal library of CDO implicitly links to hdf5. # We also need the backend of netcdf to be thread safe. depends_on('hdf5+threadsafe', when='+netcdf') depends_on('grib-api', when='grib2=grib-api') depends_on('eccodes', when='grib2=eccodes') depends_on('szip', when='+szip') depends_on('hdf5+threadsafe', when='+hdf5') depends_on('udunits', when='+udunits2') depends_on('libxml2', when='+libxml2') depends_on('proj@:5', when='@:1.9.6+proj') depends_on('proj@:7', when='@1.9.7+proj') depends_on('proj@5:', when='@1.9.8:+proj') depends_on('curl', when='+curl') depends_on('fftw-api@3:', when='+fftw3') depends_on('magics', when='+magics') depends_on('uuid') conflicts('+szip', when='+external-grib1 grib2=none', msg='The configuration does not support GRIB1') conflicts('%gcc@9:', when='@:1.9.6', msg='GCC 9 changed OpenMP data sharing behavior') def configure_args(self): config_args = [] flags = defaultdict(list) def yes_or_prefix(spec_name): prefix = self.spec[spec_name].prefix return 'yes' if is_system_path(prefix) else prefix if '+netcdf' in self.spec: config_args.append('--with-netcdf=' + yes_or_prefix('netcdf-c')) # We need to make sure that the libtool script of libcdi - the # internal library of CDO - finds the correct version of hdf5. # Note that the argument of --with-hdf5 is not passed to the # configure script of libcdi, therefore we have to provide # additional flags regardless of whether hdf5 support is enabled. hdf5_spec = self.spec['hdf5'] if not is_system_path(hdf5_spec.prefix): flags['LDFLAGS'].append(self.spec['hdf5'].libs.search_flags) else: config_args.append('--without-netcdf') if self.spec.variants['grib2'].value == 'eccodes': if self.spec.satisfies('@1.9:'): config_args.append('--with-eccodes=' + yes_or_prefix('eccodes')) config_args.append('--without-grib_api') else: config_args.append('--with-grib_api=yes') eccodes_spec = self.spec['eccodes'] eccodes_libs = eccodes_spec.libs flags['LIBS'].append(eccodes_libs.link_flags) if not is_system_path(eccodes_spec.prefix): flags['LDFLAGS'].append(eccodes_libs.search_flags) elif self.spec.variants['grib2'].value == 'grib-api': config_args.append('--with-grib_api=' + yes_or_prefix('grib-api')) if self.spec.satisfies('@1.9:'): config_args.append('--without-eccodes') else: config_args.append('--without-grib_api') if self.spec.satisfies('@1.9:'): config_args.append('--without-eccodes') if '+external-grib1' in self.spec: config_args.append('--disable-cgribex') else: config_args.append('--enable-cgribex') if '+szip' in self.spec: config_args.append('--with-szlib=' + yes_or_prefix('szip')) else: config_args.append('--without-szlib') config_args += self.with_or_without('hdf5', activation_value=yes_or_prefix) config_args += self.with_or_without( 'udunits2', activation_value=lambda x: yes_or_prefix('udunits')) if '+libxml2' in self.spec: libxml2_spec = self.spec['libxml2'] if is_system_path(libxml2_spec.prefix): config_args.append('--with-libxml2=yes') # Spack does not inject the header search flag in this case, # which is still required, unless libxml2 is installed to '/usr' # (handled by the configure script of CDO). if libxml2_spec.prefix != '/usr': flags['CPPFLAGS'].append(libxml2_spec.headers.include_flags) else: config_args.append('--with-libxml2=' + libxml2_spec.prefix) else: config_args.append('--without-libxml2') config_args += self.with_or_without('proj', activation_value=yes_or_prefix) config_args += self.with_or_without('curl', activation_value=yes_or_prefix) config_args += self.with_or_without('magics', activation_value=yes_or_prefix) config_args += self.with_or_without('fftw3') config_args += self.enable_or_disable('openmp') # Starting version 1.9.0 CDO is a C++ program but it uses the C # interface of HDF5 without the parallel features. To avoid # unnecessary dependencies on mpi's cxx library, we need to set the # following flags. This works for OpenMPI, MPICH, MVAPICH, Intel MPI, # IBM Spectrum MPI, bullx MPI, and Cray MPI. if self.spec.satisfies('@1.9:+hdf5^hdf5+mpi'): flags['CPPFLAGS'].append('-DOMPI_SKIP_MPICXX -DMPICH_SKIP_MPICXX') config_args.extend(['{0}={1}'.format(var, ' '.join(val)) for var, val in flags.items()]) return config_args

LLNL/spack

var/spack/repos/builtin/packages/cdo/package.py

Python

lgpl-2.1

10,082

[ "NetCDF" ]

5daf458f2e315d74110c9cee940cb6998d5a53797afdff00c9506eb6954783b6

######################################################################## # $HeadURL $ # File: FileCatalogHandler.py ######################################################################## """ :mod: FileCatalogHandler .. module: FileCatalogHandler :synopsis: FileCatalogHandler is a simple Replica and Metadata Catalog service """ __RCSID__ = "$Id$" ## imports import os from types import IntType, LongType, DictType, StringTypes, BooleanType, ListType ## from DIRAC from DIRAC.Core.DISET.RequestHandler import RequestHandler, getServiceOption from DIRAC import gLogger, S_OK, S_ERROR, gMonitor from DIRAC.DataManagementSystem.DB.FileCatalogDB import FileCatalogDB from DIRAC.Core.Utilities.List import sortList # This is a global instance of the FileCatalogDB class gFileCatalogDB = None def initializeFileCatalogHandler( serviceInfo ): """ handler initialisation """ global gFileCatalogDB dbLocation = getServiceOption( serviceInfo, 'Database', 'DataManagement/FileCatalogDB' ) gFileCatalogDB = FileCatalogDB( dbLocation ) databaseConfig = {} # Obtain the plugins to be used for DB interaction gLogger.info( "Initializing with FileCatalog with following managers:" ) defaultManagers = { 'UserGroupManager' : 'UserAndGroupManagerDB', 'SEManager' : 'SEManagerDB', 'SecurityManager' : 'NoSecurityManager', 'DirectoryManager' : 'DirectoryLevelTree', 'FileManager' : 'FileManager', 'DirectoryMetadata' : 'DirectoryMetadata', 'FileMetadata' : 'FileMetadata', 'DatasetManager' : 'DatasetManager' } for configKey in sortList( defaultManagers.keys() ): defaultValue = defaultManagers[configKey] configValue = getServiceOption( serviceInfo, configKey, defaultValue ) gLogger.info( "%-20s : %-20s" % ( str( configKey ), str( configValue ) ) ) databaseConfig[configKey] = configValue # Obtain some general configuration of the database gLogger.info( "Initializing the FileCatalog with the following configuration:" ) defaultConfig = { 'UniqueGUID' : False, 'GlobalReadAccess' : True, 'LFNPFNConvention' : 'Strong', 'ResolvePFN' : True, 'DefaultUmask' : 0775, 'ValidFileStatus' : ['AprioriGood','Trash','Removing','Probing'], 'ValidReplicaStatus' : ['AprioriGood','Trash','Removing','Probing'], 'VisibleFileStatus' : ['AprioriGood'], 'VisibleReplicaStatus': ['AprioriGood']} for configKey in sortList( defaultConfig.keys() ): defaultValue = defaultConfig[configKey] configValue = getServiceOption( serviceInfo, configKey, defaultValue ) gLogger.info( "%-20s : %-20s" % ( str( configKey ), str( configValue ) ) ) databaseConfig[configKey] = configValue res = gFileCatalogDB.setConfig( databaseConfig ) gMonitor.registerActivity( "AddFile", "Amount of addFile calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddFileSuccessful", "Files successfully added", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddFileFailed", "Files failed to add", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveFile", "Amount of removeFile calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveFileSuccessful", "Files successfully removed", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveFileFailed", "Files failed to remove", "FileCatalogHandler", "files/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddReplica", "Amount of addReplica calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddReplicaSuccessful", "Replicas successfully added", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "AddReplicaFailed", "Replicas failed to add", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveReplica", "Amount of removeReplica calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveReplicaSuccessful", "Replicas successfully removed", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "RemoveReplicaFailed", "Replicas failed to remove", "FileCatalogHandler", "replicas/min", gMonitor.OP_SUM ) gMonitor.registerActivity( "ListDirectory", "Amount of listDirectory calls", "FileCatalogHandler", "calls/min", gMonitor.OP_SUM ) return res class FileCatalogHandler( RequestHandler ): """ ..class:: FileCatalogHandler A simple Replica and Metadata Catalog service. """ ######################################################################## # Path operations (not updated) # types_changePathOwner = [ [ ListType, DictType ] + list( StringTypes ) ] def export_changePathOwner( self, lfns, recursive = False ): """ Get replica info for the given list of LFNs """ return gFileCatalogDB.changePathOwner( lfns, self.getRemoteCredentials(), recursive ) types_changePathGroup = [ [ ListType, DictType ] + list( StringTypes ) ] def export_changePathGroup( self, lfns, recursive = False ): """ Get replica info for the given list of LFNs """ return gFileCatalogDB.changePathGroup( lfns, self.getRemoteCredentials(), recursive ) types_changePathMode = [ [ ListType, DictType ] + list( StringTypes ) ] def export_changePathMode( self, lfns, recursive = False ): """ Get replica info for the given list of LFNs """ return gFileCatalogDB.changePathMode( lfns, self.getRemoteCredentials(), recursive ) ######################################################################## # ACL Operations # types_getPathPermissions = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getPathPermissions( self, lfns ): """ Determine the ACL information for a supplied path """ return gFileCatalogDB.getPathPermissions( lfns, self.getRemoteCredentials() ) ################################################################### # # isOK # types_isOK = [] @staticmethod def export_isOK(): """ returns S_OK if DB is connected """ if gFileCatalogDB and gFileCatalogDB._connected: return S_OK() return S_ERROR( 'Server not connected to DB' ) ################################################################### # # User/Group write operations # types_addUser = [ StringTypes ] def export_addUser( self, userName ): """ Add a new user to the File Catalog """ return gFileCatalogDB.addUser( userName, self.getRemoteCredentials() ) types_deleteUser = [ StringTypes ] def export_deleteUser( self, userName ): """ Delete user from the File Catalog """ return gFileCatalogDB.deleteUser( userName, self.getRemoteCredentials() ) types_addGroup = [ StringTypes ] def export_addGroup( self, groupName ): """ Add a new group to the File Catalog """ return gFileCatalogDB.addGroup( groupName, self.getRemoteCredentials() ) types_deleteGroup = [ StringTypes ] def export_deleteGroup( self, groupName ): """ Delete group from the File Catalog """ return gFileCatalogDB.deleteGroup( groupName, self.getRemoteCredentials() ) ################################################################### # # User/Group read operations # types_getUsers = [] def export_getUsers( self ): """ Get all the users defined in the File Catalog """ return gFileCatalogDB.getUsers( self.getRemoteCredentials() ) types_getGroups = [] def export_getGroups( self ): """ Get all the groups defined in the File Catalog """ return gFileCatalogDB.getGroups( self.getRemoteCredentials() ) ######################################################################## # # Path read operations # types_exists = [ [ ListType, DictType ] + list( StringTypes ) ] def export_exists( self, lfns ): """ Check whether the supplied paths exists """ return gFileCatalogDB.exists( lfns, self.getRemoteCredentials() ) ######################################################################## # # File write operations # types_addFile = [ [ ListType, DictType ] + list( StringTypes ) ] def export_addFile( self, lfns ): """ Register supplied files """ gMonitor.addMark( "AddFile", 1 ) res = gFileCatalogDB.addFile( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "AddFileSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "AddFileFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_removeFile = [ [ ListType, DictType ] + list( StringTypes ) ] def export_removeFile( self, lfns ): """ Remove the supplied lfns """ gMonitor.addMark( "RemoveFile", 1 ) res = gFileCatalogDB.removeFile( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "RemoveFileSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "RemoveFileFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_setFileStatus = [ DictType ] def export_setFileStatus( self, lfns ): """ Remove the supplied lfns """ return gFileCatalogDB.setFileStatus( lfns, self.getRemoteCredentials() ) types_addReplica = [ [ ListType, DictType ] + list( StringTypes ) ] def export_addReplica( self, lfns ): """ Register supplied replicas """ gMonitor.addMark( "AddReplica", 1 ) res = gFileCatalogDB.addReplica( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "AddReplicaSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "AddReplicaFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_removeReplica = [ [ ListType, DictType ] + list( StringTypes ) ] def export_removeReplica( self, lfns ): """ Remove the supplied replicas """ gMonitor.addMark( "RemoveReplica", 1 ) res = gFileCatalogDB.removeReplica( lfns, self.getRemoteCredentials() ) if res['OK']: gMonitor.addMark( "RemoveReplicaSuccessful", len( res.get( 'Value', {} ).get( 'Successful', [] ) ) ) gMonitor.addMark( "RemoveReplicaFailed", len( res.get( 'Value', {} ).get( 'Failed', [] ) ) ) return res types_setReplicaStatus = [ [ ListType, DictType ] + list( StringTypes ) ] def export_setReplicaStatus( self, lfns ): """ Set the status for the supplied replicas """ return gFileCatalogDB.setReplicaStatus( lfns, self.getRemoteCredentials() ) types_setReplicaHost = [ [ ListType, DictType ] + list( StringTypes ) ] def export_setReplicaHost( self, lfns ): """ Change the registered SE for the supplied replicas """ return gFileCatalogDB.setReplicaHost( lfns, self.getRemoteCredentials() ) types_addFileAncestors = [ DictType ] def export_addFileAncestors( self, lfns ): """ Add file ancestor information for the given list of LFNs """ return gFileCatalogDB.addFileAncestors( lfns, self.getRemoteCredentials() ) ######################################################################## # # File read operations # types_isFile = [ [ ListType, DictType ] + list( StringTypes ) ] def export_isFile( self, lfns ): """ Check whether the supplied lfns are files """ return gFileCatalogDB.isFile( lfns, self.getRemoteCredentials() ) types_getFileSize = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getFileSize( self, lfns ): """ Get the size associated to supplied lfns """ return gFileCatalogDB.getFileSize( lfns, self.getRemoteCredentials() ) types_getFileMetadata = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getFileMetadata( self, lfns ): """ Get the metadata associated to supplied lfns """ return gFileCatalogDB.getFileMetadata( lfns, self.getRemoteCredentials() ) types_getReplicas = [ [ ListType, DictType ] + list( StringTypes ), BooleanType ] def export_getReplicas( self, lfns, allStatus = False ): """ Get replicas for supplied lfns """ return gFileCatalogDB.getReplicas( lfns, allStatus, self.getRemoteCredentials() ) types_getReplicaStatus = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getReplicaStatus( self, lfns ): """ Get the status for the supplied replicas """ return gFileCatalogDB.getReplicaStatus( lfns, self.getRemoteCredentials() ) types_getFileAncestors = [ ListType, [ ListType, IntType, LongType ] ] def export_getFileAncestors( self, lfns, depths ): """ Get the status for the supplied replicas """ dList = depths if type( dList ) != ListType: dList = [ depths ] lfnDict = dict.fromkeys( lfns, True ) return gFileCatalogDB.getFileAncestors( lfnDict, dList, self.getRemoteCredentials() ) types_getFileDescendents = [ ListType, [ ListType, IntType, LongType ] ] def export_getFileDescendents( self, lfns, depths ): """ Get the status for the supplied replicas """ dList = depths if type( dList ) != ListType: dList = [depths] lfnDict = dict.fromkeys( lfns, True ) return gFileCatalogDB.getFileDescendents( lfnDict, dList, self.getRemoteCredentials() ) ######################################################################## # # Directory write operations # types_createDirectory = [ [ ListType, DictType ] + list( StringTypes ) ] def export_createDirectory( self, lfns ): """ Create the supplied directories """ return gFileCatalogDB.createDirectory( lfns, self.getRemoteCredentials() ) types_removeDirectory = [ [ ListType, DictType ] + list( StringTypes ) ] def export_removeDirectory( self, lfns ): """ Remove the supplied directories """ return gFileCatalogDB.removeDirectory( lfns, self.getRemoteCredentials() ) ######################################################################## # # Directory read operations # types_listDirectory = [ [ ListType, DictType ] + list( StringTypes ), BooleanType ] def export_listDirectory( self, lfns, verbose ): """ List the contents of supplied directories """ gMonitor.addMark( 'ListDirectory', 1 ) return gFileCatalogDB.listDirectory( lfns, self.getRemoteCredentials(), verbose = verbose ) types_isDirectory = [ [ ListType, DictType ] + list( StringTypes ) ] def export_isDirectory( self, lfns ): """ Determine whether supplied path is a directory """ return gFileCatalogDB.isDirectory( lfns, self.getRemoteCredentials() ) types_getDirectorySize = [ [ ListType, DictType ] + list( StringTypes ) ] def export_getDirectorySize( self, lfns, longOut = False, fromFiles = False ): """ Get the size of the supplied directory """ return gFileCatalogDB.getDirectorySize( lfns, longOut, fromFiles, self.getRemoteCredentials() ) types_getDirectoryReplicas = [ [ ListType, DictType ] + list( StringTypes ), BooleanType ] def export_getDirectoryReplicas( self, lfns, allStatus = False ): """ Get replicas for files in the supplied directory """ return gFileCatalogDB.getDirectoryReplicas( lfns, allStatus, self.getRemoteCredentials() ) ######################################################################## # # Administrative database operations # types_getCatalogCounters = [] def export_getCatalogCounters( self ): """ Get the number of registered directories, files and replicas in various tables """ return gFileCatalogDB.getCatalogCounters( self.getRemoteCredentials() ) types_rebuildDirectoryUsage = [] @staticmethod def export_rebuildDirectoryUsage(): """ Rebuild DirectoryUsage table from scratch """ return gFileCatalogDB.rebuildDirectoryUsage() types_repairCatalog = [] def export_repairCatalog( self ): """ Repair the catalog inconsistencies """ return gFileCatalogDB.repairCatalog( self.getRemoteCredentials() ) ######################################################################## # Metadata Catalog Operations # types_addMetadataField = [ StringTypes, StringTypes ] def export_addMetadataField( self, fieldName, fieldType, metaType = '-d' ): """ Add a new metadata field of the given type """ if metaType.lower() == "-d": return gFileCatalogDB.dmeta.addMetadataField( fieldName, fieldType, self.getRemoteCredentials() ) elif metaType.lower() == "-f": return gFileCatalogDB.fmeta.addMetadataField( fieldName, fieldType, self.getRemoteCredentials() ) else: return S_ERROR( 'Unknown metadata type %s' % metaType ) types_deleteMetadataField = [ StringTypes ] def export_deleteMetadataField( self, fieldName ): """ Delete the metadata field """ result = gFileCatalogDB.dmeta.deleteMetadataField( fieldName, self.getRemoteCredentials() ) error = '' if not result['OK']: error = result['Message'] result = gFileCatalogDB.fmeta.deleteMetadataField( fieldName, self.getRemoteCredentials() ) if not result['OK']: if error: result["Message"] = error + "; " + result["Message"] return result types_getMetadataFields = [ ] def export_getMetadataFields( self ): """ Get all the metadata fields """ resultDir = gFileCatalogDB.dmeta.getMetadataFields( self.getRemoteCredentials() ) if not resultDir['OK']: return resultDir resultFile = gFileCatalogDB.fmeta.getFileMetadataFields( self.getRemoteCredentials() ) if not resultFile['OK']: return resultFile return S_OK( { 'DirectoryMetaFields' : resultDir['Value'], 'FileMetaFields' : resultFile['Value'] } ) types_setMetadata = [ StringTypes, DictType ] def export_setMetadata( self, path, metadatadict ): """ Set metadata parameter for the given path """ return gFileCatalogDB.setMetadata( path, metadatadict, self.getRemoteCredentials() ) types_setMetadataBulk = [ DictType ] def export_setMetadataBulk( self, pathMetadataDict ): """ Set metadata parameter for the given path """ return gFileCatalogDB.setMetadataBulk( pathMetadataDict, self.getRemoteCredentials() ) types_removeMetadata = [ DictType ] def export_removeMetadata( self, pathMetadataDict ): """ Remove the specified metadata for the given path """ return gFileCatalogDB.removeMetadata( pathMetadataDict, self.getRemoteCredentials() ) types_getDirectoryMetadata = [ StringTypes ] def export_getDirectoryMetadata( self, path ): """ Get all the metadata valid for the given directory path """ return gFileCatalogDB.dmeta.getDirectoryMetadata( path, self.getRemoteCredentials() ) types_getFileUserMetadata = [ StringTypes ] def export_getFileUserMetadata( self, path ): """ Get all the metadata valid for the given file """ return gFileCatalogDB.fmeta.getFileUserMetadata( path, self.getRemoteCredentials() ) types_findDirectoriesByMetadata = [ DictType ] def export_findDirectoriesByMetadata( self, metaDict, path = '/' ): """ Find all the directories satisfying the given metadata set """ return gFileCatalogDB.dmeta.findDirectoriesByMetadata ( metaDict, path, self.getRemoteCredentials() ) types_findFilesByMetadata = [ DictType, StringTypes ] def export_findFilesByMetadata( self, metaDict, path = '/' ): """ Find all the files satisfying the given metadata set """ return gFileCatalogDB.fmeta.findFilesByMetadata( metaDict, path, self.getRemoteCredentials() ) types_getReplicasByMetadata = [ DictType, StringTypes, BooleanType ] def export_getReplicasByMetadata( self, metaDict, path = '/', allStatus = False ): """ Find all the files satisfying the given metadata set """ return gFileCatalogDB.fileManager.getReplicasByMetadata( metaDict, path, allStatus, self.getRemoteCredentials() ) types_findFilesByMetadataDetailed = [ DictType, StringTypes ] def export_findFilesByMetadataDetailed( self, metaDict, path = '/' ): """ Find all the files satisfying the given metadata set """ result = gFileCatalogDB.fmeta.findFilesByMetadata( metaDict, path, self.getRemoteCredentials() ) if not result['OK'] or not result['Value']: return result lfns = [] for directory in result['Value']: for fname in result['Value'][directory]: lfns.append( os.path.join( directory, fname ) ) return gFileCatalogDB.getFileDetails( lfns, self.getRemoteCredentials() ) types_findFilesByMetadataWeb = [ DictType, StringTypes, [IntType, LongType], [IntType, LongType]] def export_findFilesByMetadataWeb( self, metaDict, path, startItem, maxItems ): """ Find files satisfying the given metadata set """ result = gFileCatalogDB.dmeta.findFileIDsByMetadata( metaDict, path, self.getRemoteCredentials(), startItem, maxItems ) if not result['OK'] or not result['Value']: return result fileIDs = result['Value'] totalRecords = result['TotalRecords'] result = gFileCatalogDB.fileManager._getFileLFNs( fileIDs ) if not result['OK']: return result lfnsResultList = result['Value']['Successful'].values() resultDetails = gFileCatalogDB.getFileDetails( lfnsResultList, self.getRemoteCredentials() ) if not resultDetails['OK']: return resultDetails result = S_OK( {"TotalRecords":totalRecords, "Records":resultDetails['Value'] } ) return result def findFilesByMetadataWeb( self, metaDict, path, startItem, maxItems ): """ Find all the files satisfying the given metadata set """ result = gFileCatalogDB.fmeta.findFilesByMetadata( metaDict, path, self.getRemoteCredentials() ) if not result['OK'] or not result['Value']: return result lfns = [] for directory in result['Value']: for fname in result['Value'][directory]: lfns.append( os.path.join( directory, fname ) ) start = startItem totalRecords = len( lfns ) if start > totalRecords: return S_ERROR( 'Requested files out of existing range' ) end = start + maxItems if end > totalRecords: end = totalRecords lfnsResultList = lfns[start:end] resultDetails = gFileCatalogDB.getFileDetails( lfnsResultList, self.getRemoteCredentials() ) if not resultDetails['OK']: return resultDetails result = S_OK( {"TotalRecords":totalRecords, "Records":resultDetails['Value'] } ) return result types_getCompatibleMetadata = [ DictType, StringTypes ] def export_getCompatibleMetadata( self, metaDict, path = '/' ): """ Get metadata values compatible with the given metadata subset """ return gFileCatalogDB.dmeta.getCompatibleMetadata( metaDict, path, self.getRemoteCredentials() ) types_addMetadataSet = [ StringTypes, DictType ] def export_addMetadataSet( self, setName, setDict ): """ Add a new metadata set """ return gFileCatalogDB.dmeta.addMetadataSet( setName, setDict, self.getRemoteCredentials() ) types_getMetadataSet = [ StringTypes, BooleanType ] def export_getMetadataSet( self, setName, expandFlag ): """ Add a new metadata set """ return gFileCatalogDB.dmeta.getMetadataSet( setName, expandFlag, self.getRemoteCredentials() ) types_listMetadataSets = [] def export_listMetadataSets(self): """ Get the list of metadata sets with their definitions """ return gFileCatalogDB.dmeta.listMetadataSets(self.getRemoteCredentials()) ######################################################################################### # # Dataset manipulation methods # types_addDataset = [ StringTypes, DictType ] def export_addDataset( self, datasetName, metaQuery ): """ Add a new dynamic dataset defined by its meta query """ return gFileCatalogDB.datasetManager.addDataset( datasetName, metaQuery, self.getRemoteCredentials() ) types_addDatasetAnnotation = [ DictType ] def export_addDatasetAnnotation( self, datasetDict ): """ Add annotation to an already created dataset """ return gFileCatalogDB.datasetManager.addDatasetAnnotation( datasetDict, self.getRemoteCredentials() ) types_removeDataset = [ StringTypes ] def export_removeDataset( self, datasetName ): """ Check the given dynamic dataset for changes since its definition """ return gFileCatalogDB.datasetManager.removeDataset( datasetName, self.getRemoteCredentials() ) types_checkDataset = [ StringTypes ] def export_checkDataset( self, datasetName ): """ Check the given dynamic dataset for changes since its definition """ return gFileCatalogDB.datasetManager.checkDataset( datasetName, self.getRemoteCredentials() ) types_updateDataset = [ StringTypes ] def export_updateDataset( self, datasetName ): """ Update the given dynamic dataset for changes since its definition """ return gFileCatalogDB.datasetManager.updateDataset( datasetName, self.getRemoteCredentials() ) types_getDatasets = [ list( StringTypes ) + [ListType] ] def export_getDatasets( self, datasetName ): """ Get parameters of the given dynamic dataset as they are stored in the database """ return gFileCatalogDB.datasetManager.getDatasets( datasetName, self.getRemoteCredentials() ) types_getDatasetParameters = [ StringTypes ] def export_getDatasetParameters( self, datasetName ): """ Get parameters of the given dynamic dataset as they are stored in the database """ return gFileCatalogDB.datasetManager.getDatasetParameters( datasetName, self.getRemoteCredentials() ) types_getDatasetAnnotation = [ list( StringTypes ) + [ListType] ] def export_getDatasetAnnotation( self, datasetName ): """ Get annotation of the given datasets """ return gFileCatalogDB.datasetManager.getDatasetAnnotation( datasetName, self.getRemoteCredentials() ) types_freezeDataset = [ StringTypes ] def export_freezeDataset( self, datasetName ): """ Freeze the contents of the dataset making it effectively static """ return gFileCatalogDB.datasetManager.freezeDataset( datasetName, self.getRemoteCredentials() ) types_releaseDataset = [ StringTypes ] def export_releaseDataset( self, datasetName ): """ Release the contents of the frozen dataset allowing changes in its contents """ return gFileCatalogDB.datasetManager.releaseDataset( datasetName, self.getRemoteCredentials() ) types_getDatasetFiles = [ StringTypes ] def export_getDatasetFiles( self, datasetName ): """ Get lfns in the given dataset """ return gFileCatalogDB.datasetManager.getDatasetFiles( datasetName, self.getRemoteCredentials() )

Sbalbp/DIRAC

DataManagementSystem/Service/FileCatalogHandler.py

Python

gpl-3.0

27,381

[ "DIRAC" ]

3c8e5859724ef4e5a61a86e61ce03b65130071b9677124f53073409ceeeb5ab9

""" This is a setup.py script generated by py2applet Usage: python setup.py py2app """ from setuptools import setup APP = ['main.py'] DATA_FILES = [ 'config.json', 'firefly-blacklist.txt', 'firefly-blacklist.meta.json', 'firefly-hosts.txt', 'firefly-hosts.meta.json', 'firefly-hosts-disabled.txt', 'custom-blacklist.txt', 'custom-whitelist.txt', 'meek-relays.txt', 'cacert.pem', 'README.md', 'LICENSE', ('webpanel', ['webpanel/static', ]), ('webpanel', ['webpanel/templates', ]) ] OPTIONS = { 'iconfile': 'firefly.icns', 'plist': {'CFBundleShortVersionString':'0.3.0',}, 'argv_emulation': True } setup( name="Firefly", version="0.3.0", app=APP, data_files=DATA_FILES, options={'py2app': OPTIONS}, setup_requires=['py2app'], )

Jonavin/firefly-proxy

setup_mac.py

Python

bsd-2-clause

826

[ "Firefly" ]

71a96ba7e6006da35f4c2442ecc7f67e2eceffc652440d7d032d4d2b6cd8da8e

# Copyright 2016 Mingbo Cai, Princeton Neuroscience Instititute, # Princeton University # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. """ Bayesian Representational Similarity Analysis (BRSA) This implementation is based on [Cai2016]_ and [Cai2019]_: .. [Cai2016] "A Bayesian method for reducing bias in neural representational similarity analysis", M.B. Cai, N.W. Schuck, J.W. Pillow, Y. Niv, Advances in Neural Information Processing Systems 29, 2016, 4952--4960 Available at: http://papers.nips.cc/paper/6131-a-bayesian-method-for-reducing-bias-in-neural-representational-similarity-analysis.pdf .. [Cai2019] "Representational structure or task structure? Bias in neural representational similarity analysis and a Bayesian method for reducing bias", M.B. Cai, N.W. Schuck, J.W. Pillow, Y. Niv, PLoS computational biology 15.5 (2019): e1006299. https://doi.org/10.1371/journal.pcbi.1006299 `.BRSA` is based on [Cai2016] with additional consideration of spatial noise correlation proposed in [Cai2019]. `.GBRSA` is based on [Cai2019]. `.GBRSA` may perform better than `.BRSA` due to marginalization of all voxel-wise parameters. It can be use for single participant as well. """ # Authors: Mingbo Cai # Princeton Neuroscience Institute, Princeton University, 2016 import numpy as np import scipy import scipy.optimize import scipy.stats import scipy.special import time from sklearn.base import BaseEstimator, TransformerMixin from sklearn.utils import assert_all_finite, check_random_state from sklearn.decomposition import PCA, FactorAnalysis, SparsePCA, FastICA import logging import brainiak.utils.utils as utils import scipy.spatial.distance as spdist from nitime import algorithms as alg import copy logger = logging.getLogger(__name__) __all__ = [ "BRSA", "GBRSA", "Ncomp_SVHT_MG_DLD_approx", "prior_GP_var_inv_gamma", "prior_GP_var_half_cauchy", ] def prior_GP_var_inv_gamma(y_invK_y, n_y, tau_range): """ Imposing an inverse-Gamma prior onto the variance (tau^2) parameter of a Gaussian Process, which is in turn a prior imposed over an unknown function y = f(x). The inverse-Gamma prior of tau^2, tau^2 ~ invgamma(shape, scale) is described by a shape parameter alpha=2 and a scale parameter beta=tau_range^2. tau_range describes the reasonable range of tau in the inverse-Gamma prior. The data y's at locations x's are assumed to follow Gaussian Process: f(x, x') ~ N(0, K(x, x') / 2 tau^2), where K is a kernel function defined on x. For n observations, K(x1, x2, ..., xn) is an n by n positive definite matrix. Given the prior parameter tau_range, number of observations n_y, and y_invK_y = y * inv(K) * y', the function returns the MAP estimate of tau^2 and the log posterior probability of tau^2 at the MAP value: log(p(tau^2|tau_range)). This function is written primarily for BRSA but can also be used elsewhere. y in this case corresponds to the log of SNR in each voxel. GBRSA does not rely on this function. An alternative form of prior is half-Cauchy prior on tau. Inverse-Gamma prior penalizes for both very small and very large values of tau, while half-Cauchy prior only penalizes for very large values of tau. For more information on usage, see description in BRSA class: `.BRSA` See also: `.prior_GP_var_half_cauchy` Parameters ---------- y_invK_y: float y * inv(K) * y^T, where y=f(x) is a vector of observations of unknown function f at different locations x. K is correlation matrix of f between different locations, based on a Gaussian Process (GP) describing the smoothness property of f. K fully incorporates the form of the kernel and the length scale of the GP, but not the variance of the GP (the purpose of this function is to estimate the variance). n_y: int, number of observations tau_range: float, The reasonable range of tau, the standard deviation of the Gaussian Process imposed on y=f(x). tau_range is parameter of the inverse-Gamma prior. Say, if you expect the standard deviation of the Gaussian process to be around 3, tau_range can be set to 3. The smaller it is, the more penalization is imposed on large variation of y. Returns ------- tau2: The MAP estimation of tau^2 based on the prior on tau and y_invK_y. log_ptau: log(p(tau)) of the returned tau^2 based on the inverse-Gamma prior. """ alpha = 2 tau2 = (y_invK_y + 2 * tau_range**2) / (alpha * 2 + 2 + n_y) log_ptau = scipy.stats.invgamma.logpdf( tau2, scale=tau_range**2, a=2) return tau2, log_ptau def prior_GP_var_half_cauchy(y_invK_y, n_y, tau_range): """ Imposing a half-Cauchy prior onto the standard deviation (tau) of the Gaussian Process which is in turn a prior imposed over a function y = f(x). The scale parameter of the half-Cauchy prior is tau_range. The function returns the MAP estimate of tau^2 and log(p(tau|tau_range)) for the MAP value of tau^2, where tau_range describes the reasonable range of tau in the half-Cauchy prior. An alternative form of prior is inverse-Gamma prior on tau^2. Inverse-Gamma prior penalizes for both very small and very large values of tau, while half-Cauchy prior only penalizes for very large values of tau. For more information on usage, see description in BRSA class: `.BRSA` """ tau2 = (y_invK_y - n_y * tau_range**2 + np.sqrt(n_y**2 * tau_range**4 + (2 * n_y + 8) * tau_range**2 * y_invK_y + y_invK_y**2))\ / 2 / (n_y + 2) log_ptau = scipy.stats.halfcauchy.logpdf( tau2**0.5, scale=tau_range) return tau2, log_ptau def Ncomp_SVHT_MG_DLD_approx(X, zscore=True): """ This function implements the approximate calculation of the optimal hard threshold for singular values, by Matan Gavish and David L. Donoho: "The optimal hard threshold for singular values is 4 / sqrt(3)" http://ieeexplore.ieee.org/stamp/stamp.jsp?arnumber=6846297 Parameters ---------- X: 2-D numpy array of size [n_T, n_V] The data to estimate the optimal rank for selecting principal components. zscore: Boolean Whether to z-score the data before calculating number of components. Returns ------- ncomp: integer The optimal number of components determined by the method of MG and DLD """ beta = X.shape[0] / X.shape[1] if beta > 1: beta = 1 / beta omega = 0.56 * beta ** 3 - 0.95 * beta ** 2 + 1.82 * beta + 1.43 if zscore: sing = np.linalg.svd(_zscore(X), False, False) else: sing = np.linalg.svd(X, False, False) thresh = omega * np.median(sing) ncomp = int(np.sum(np.logical_and(sing > thresh, np.logical_not( np.isclose(sing, thresh))))) # In the line above, we look for the singular values larger than # the threshold but excluding those that happen to be "just" larger # than the threshold by an amount close to the numerical precision. # This is to prevent close-to-zero singular values to be included if # the median of the eigenvalues is close to 0 (which could happen # when the input X has lower rank than its minimal size. return ncomp def _zscore(a): """ Calculating z-score of data on the first axis. If the numbers in any column are all equal, scipy.stats.zscore will return NaN for this column. We shall correct them all to be zeros. Parameters ---------- a: numpy array Returns ------- zscore: numpy array The z-scores of input "a", with any columns including non-finite numbers replaced by all zeros. """ assert a.ndim > 1, 'a must have more than one dimensions' zscore = scipy.stats.zscore(a, axis=0) zscore[:, np.logical_not(np.all(np.isfinite(zscore), axis=0))] = 0 return zscore class BRSA(BaseEstimator, TransformerMixin): """Bayesian representational Similarity Analysis (BRSA) Given the time series of neural imaging data in a region of interest (ROI) and the hypothetical neural response (design matrix) to each experimental condition of interest, calculate the shared covariance matrix U of the voxels(recording unit)' response profiles \\beta_i to each condition, and the relative SNR of each voxels. The relative SNR could be considered as the degree of contribution of each voxel to this shared covariance matrix. A correlation matrix converted from the covariance matrix U will be provided as a quantification of neural representational similarity. .. math:: Y = X \\cdot \\beta + X_0 \\cdot \\beta_0 + \\epsilon \\beta_i \\sim N(0,(s_{i} \\sigma_{i})^2 U) \\epsilon_i \\sim AR(1) Please note that the model assumes that the covariance matrix U which all \\beta_i follow is zero-meaned. This assumption does not imply there must be both positive and negative responses across voxels. However, it means that Bayesian RSA treats the task-evoked activity against baseline BOLD level as signal, while in other RSA tools the deviation of task-evoked activity in each voxel from the average task-evoked activity level across voxels may be considered as signal of interest. Due to this assumption in BRSA, relatively high degree of similarity may be expected when the activity patterns of two task conditions both include strong sensory driven signals regardless of their specific stimuli. When two task conditions elicit exactly the same activity patterns but only differ in their global magnitudes, under the assumption in BRSA, their similarity is 1; under the assumption that only deviation of pattern from average patterns is signal of interest, their similarity should be -1. Parameters ---------- n_iter : int. Number of maximum iterations to run the algorithm. rank : int. Default: None The rank of the covariance matrix. If not provided, the covariance matrix will be assumed to be full rank. When you have many conditions (e.g., calculating the similarity matrix of responses to each event), you might try specifying a lower rank. auto_nuisance: boolean. In order to model spatial correlation between voxels that cannot be accounted for by common response captured in the design matrix, we assume that a set of time courses not related to the task conditions are shared across voxels with unknown amplitudes. One approach is for users to provide time series which they consider as nuisance but exist in the noise (such as head motion). The other way is to take the first n_nureg principal components in the residual after subtracting the response to the design matrix from the data, and use these components as the nuisance regressor. This flag is for the second approach. If turned on, PCA or factor analysis will be applied to the residuals to obtain new nuisance regressors in each round of fitting. These two approaches can be combined. If the users provide nuisance regressors and set this flag as True, then the first n_nureg principal components of the residuals after subtracting both the responses to design matrix and the user-supplied nuisance regressors will be used in addition to the nuisance regressors provided by the users. Note that nuisance regressor is not required from user. If it is not provided, DC components for each run will be included as nuisance regressor regardless of the auto_nuisance parameter. n_nureg: Optional[int]. Number of nuisance regressors to use in order to model signals shared across voxels not captured by the design matrix. This number is in addition to any nuisance regressor that the user has already provided. If set to None, the number of nuisance regressors will be automatically determined based on M Gavish and D Donoho's approximate estimation of optimal hard threshold for singular values. This only takes effect if auto_nuisance is True. nureg_zscore: boolean. A flag to tell the algorithm whether data is z-scored before estimating the number of nuisance regressor components necessary to account for spatial noise correlation. It also determinie whether the residual noise is z-scored before estimating the nuisance regressors from residual. This only takes effect if auto_nuisance is True. nureg_method: string, naming a method from sklearn.decomposition. 'PCA', 'ICA', 'FA' or 'SPCA' are currently supported. The method to estimate the shared component in noise across voxels. This only takes effect if auto_nuisance is True. baseline_single: boolean. A time course of constant 1 will be included to the nuisance regressor regardless of whether the user requests. If baseline_single is set to False, one such regressor is included for each fMRI run, but a single component in beta0\\_ will be computed as the average of the weight maps corresponding to these regressors. This might cause underestimation of noise variance. If baseline_single is True, only one regressor of constant 1 will be used for the whole dataset. This might be desirable if you believe the average image intensity might not scale with the same proportion for different voxels across scan. In other words, it is possible that some part of the brain is more vulnerable to change in baseline intensity due to facts such as field inhomogeneity. Setting baseline_single to True will force the nuisance regressors automatically estimated from residuals to capture this. However, when each task condition only occurs in one run and when the design matrix in each run sums together close to a flat line, this option can cause the estimated similarity to be extremely high between conditions occuring in the same run. GP_space: boolean. Whether to impose a Gaussion Process (GP) prior on the log(pseudo-SNR). If true, the GP has a kernel defined over spatial coordinate of each voxel. The idea behind this option is that adjacent voxels should have similar SNRs. This is relatively slow for big ROI. We find that when SNR is generally low, smoothness can be overestimated. But such regularization may reduce variance in the estimated SNR map and similarity matrix. GP_inten: boolean. Whether to include a kernel defined over the intensity of image. GP_space should be True as well if you want to use this, because the smoothness should be primarily in space. Smoothness in intensity is just complementary. The idea behind this option is that voxels should have similar SNRs when they are both adjacent (imposed by GP_space) and are of the same tissue type (when their image intensities are close). If you accept the second assumption, then you can set GP_inten as True and provide an array to the `inten` variable, expressing the intensities (brightness) for each voxel. space_smooth_range: float. The distance (in unit the same as what you would use when supplying the spatial coordiates of each voxel, typically millimeter) which you believe is the maximum range of the length scale parameter of Gaussian Process defined over voxel location. This is used to impose a half-Cauchy prior on the length scale. If set to None, the program will default to half of the maximum distance between all voxels. inten_smooth_range: float. The difference in image intensity which you believe is the maximum range of plausible length scale for the Gaussian Process defined over image intensity. Length scales larger than this are allowed, but will be penalized. If set to None, this parameter will default to half of the maximal intensity difference. tau_range: float. The reasonable range of the standard deviation of log(SNR). This range should not be too large. 5 is a loose range. When a Gaussian Process is imposed on the log(SNR), this parameter is used in a half-Cauchy prior on the standard deviation, or an inverse-Gamma prior on the variance of the GP. tau2_prior: Callable[[float, int, float]], [float, float]], Default: prior_GP_var_inv_gamma. Can be prior_GP_var_inv_gamma or prior_GP_var_half_cauchy, or a custom function. The function which impose a prior for tau^2, the variance of the GP prior on log(SNR), and returns the MAP estimate of tau^2. It can be either prior_GP_var_inv_gamma for inverse-Gamma or prior_GP_var_half_cauchy for half-Cauchy. half-Cauchy prior is in fact imposed on tau. But tau_range describes the range of tau in the prior in both cases. Both functions are part of brsa module. See also `.prior_GP_var_inv_gamma` and `.prior_GP_var_half_cauchy` To use the default inverse-Gamma prior, you can ignore this argument:: from brainiak.reprsimil.brsa import BRSA brsa = BRSA() If you want to try the alternative half-Cauchy prior, then you need to import it in addition to BRSA:: from brainiak.reprsimil.brsa import BRSA, prior_GP_var_half_cauchy brsa = BRSA(tau2_prior=prior_GP_var_half_cauchy) eta: float. A small number added to the diagonal element of the covariance matrix in the Gaussian Process prior. This is to ensure that the matrix is invertible. init_iter: int. How many initial iterations to fit the model without introducing the GP prior before fitting with it, if GP_space or GP_inten is requested. This initial fitting is to give the parameters a good starting point. optimizer: str or callable. The optimizer to use for minimizing cost function which scipy.optimize.minimize can accept. We use 'L-BFGS-B' as a default. Users can try other strings corresponding to optimizer provided by scipy.optimize.minimize, or a custom optimizer, such as 'BFGS' or 'CG'. Note that BRSA fits a lot of parameters. So a chosen optimizer should accept gradient (Jacobian) of the cost function. Otherwise the fitting is likely to be unbarely slow. We do not calculate Hessian of the objective function. So an optimizer which requires Hessian cannot be used. random_state : RandomState or an int seed. A random number generator instance to define the state of the random permutations generator whenever the module needs to generate random number (e.g., initial parameter of the Cholesky factor). anneal_speed: float. Annealing is introduced in fitting of the Cholesky decomposition of the shared covariance matrix. The amount of perturbation decays exponentially. This parameter sets the ratio of the maximum number of iteration to the time constant of the exponential. anneal_speed=10 means by n_iter/10 iterations, the amount of perturbation is reduced by 2.713 times. minimize_options: dictionary. Default: {'gtol': 1e-4, 'disp': False, 'maxiter': 6} This is the dictionary passed as the options argument to scipy.optimize.minize which minimizes the cost function during fitting. Notice that the minimization is performed for many times, alternating between optimizing the covariance matrix U underlying the pattern similarity matrix, and SNR. At most n_iter times of this alternation is performed. So within each step of fitting, the step of iteration performed by scipy.optimize.minize does not have to be very large. In other words, scipy.optimize.minize does not need to converge within each step of the alternating fitting procedure. tol: float. Tolerance parameter passed to scipy.optimize.minimize. It is also used for determining convergence of the alternating fitting procedure. Attributes ---------- U_ : numpy array, shape=[condition,condition]. The shared covariance matrix. L_ : numpy array, shape=[condition,rank]. The Cholesky factor of the shared covariance matrix (lower-triangular matrix). C_: numpy array, shape=[condition,condition]. The correlation matrix derived from the shared covariance matrix. This is the estimated similarity matrix between neural patterns to your task conditions. Notice that it is recommended that you also check U\\_, which is the covariance matrix underlying this correlation matrix. In cases there is almost no response to your task conditions, the diagonal values of U\\_ would become very small and C\\_ might contain many correlation coefficients close to 1 or -1. This might not reflect true strong correlation or strong negative correlation, but a result of lack of task-related neural activity, design matrix that does not match true neural response, or not enough data. It is also recommended to check nSNR\\_ after mapping it back to the brain. A "reasonable" map should at least have higher values in gray matter in than white matter. nSNR_ : numpy array, shape=[voxels,]. The normalized pseuso-SNR of all voxels. They are normalized such that the geometric mean is 1. Note that this attribute can not be interpreted as true SNR, but the relative ratios between voxel indicates the contribution of each voxel to the representational similarity structure. sigma_ : numpy array, shape=[voxels,]. The estimated standard deviation of the noise in each voxel Assuming AR(1) model, this means the standard deviation of the innovation noise. rho_ : numpy array, shape=[voxels,]. The estimated autoregressive coefficient of each voxel bGP_ : float, only if GP_space or GP_inten is True. The standard deviation of the GP prior lGPspace_ : float, only if GP_space or GP_inten is True The length scale of Gaussian Process prior of log(SNR) lGPinten_: float, only if GP_inten is True The length scale in fMRI intensity of the GP prior of log(SNR) beta_: array, shape=[conditions, voxels] The maximum a posterior estimation of the response amplitudes of each voxel to each task condition. beta0_: numpy array, shape=[n_nureg + n_base, voxels] The loading weights of each voxel for the shared time courses not captured by the design matrix. This helps capture the structure of spatial covariance of task-unrelated signal. n_base is the number of columns of the user-supplied nuisance regressors plus one for DC component X0_: numpy array, shape=[time_points, n_nureg + n_base] The estimated time course that is shared across voxels but unrelated to the events of interest (design matrix). beta0_null_: numpy array, shape=[n_nureg + n_base, voxels] The equivalent of beta0\\_ in a null model which does not include the design matrix and response pattern beta. X0_null_: numpy array, shape=[time_points, n_nureg + n_base] The equivalent of X0\\_ in a null model which does not include the design matrix and response pattern beta n_nureg_: int Number of nuisance regressor in addition to such regressors provided by the user (if any), if auto_nuisance is set to True. If n_nureg is set to 'opt', this will be estimated from data. 'opt' will use M Gavish and D Donoho's approximate estimation of optimal hard threshold for singular values. random_state_: `RandomState` Random number generator initialized using random_state. """ def __init__( self, n_iter=100, rank=None, auto_nuisance=True, n_nureg=None, nureg_zscore=True, nureg_method='PCA', baseline_single=False, GP_space=False, GP_inten=False, space_smooth_range=None, inten_smooth_range=None, tau_range=5.0, tau2_prior=prior_GP_var_inv_gamma, eta=0.0001, init_iter=20, optimizer='L-BFGS-B', random_state=None, anneal_speed=10, tol=1e-4, minimize_options={'gtol': 1e-4, 'disp': False, 'maxiter': 6}): self.n_iter = n_iter self.rank = rank self.GP_space = GP_space self.GP_inten = GP_inten self.tol = tol self.auto_nuisance = auto_nuisance self.n_nureg = n_nureg self.nureg_zscore = nureg_zscore if auto_nuisance: assert (n_nureg is None) \ or (isinstance(n_nureg, int) and n_nureg > 0), \ 'n_nureg should be a positive integer or None'\ ' if auto_nuisance is True.' if self.nureg_zscore: self.preprocess_residual = lambda x: _zscore(x) else: self.preprocess_residual = lambda x: x if nureg_method == 'FA': self.nureg_method = lambda x: FactorAnalysis(n_components=x) elif nureg_method == 'PCA': self.nureg_method = lambda x: PCA(n_components=x, whiten=True) elif nureg_method == 'SPCA': self.nureg_method = lambda x: SparsePCA(n_components=x, max_iter=20, tol=tol) elif nureg_method == 'ICA': self.nureg_method = lambda x: FastICA(n_components=x, whiten=True) else: raise ValueError('nureg_method can only be FA, PCA, ' 'SPCA(for sparse PCA) or ICA') self.baseline_single = baseline_single self.minimize_options = minimize_options self.eta = eta # This is a tiny ridge added to the Gaussian Process # covariance matrix template to gaurantee that it is invertible. # Mathematically it means we assume that this proportion of the # variance is always independent between voxels for the log(SNR2). self.space_smooth_range = space_smooth_range self.inten_smooth_range = inten_smooth_range # The kernel of the Gaussian Process is the product of a kernel # defined on spatial coordinate and a kernel defined on # image intensity. self.tau_range = tau_range self.tau2_prior = tau2_prior self.init_iter = init_iter # When imposing smoothness prior, fit the model without this # prior for this number of iterations. self.optimizer = optimizer self.random_state = random_state self.anneal_speed = anneal_speed return def fit(self, X, design, nuisance=None, scan_onsets=None, coords=None, inten=None): """Compute the Bayesian RSA Parameters ---------- X: numpy array, shape=[time_points, voxels] If you have multiple scans of the same participants that you want to analyze together, you should concatenate them along the time dimension after proper preprocessing (e.g. spatial alignment), and specify the onsets of each scan in scan_onsets. design: numpy array, shape=[time_points, conditions] This is the design matrix. It should only include the hypothetic response for task conditions. You should not include regressors for a DC component or motion parameters, unless you want to estimate their pattern similarity with response patterns to your task conditions. If you want to model head motion, you should include them in nuisance regressors. If you have multiple run, the design matrix of all runs should be concatenated along the time dimension, with every column for one condition across runs. For example, if you have 3 runs of experiment of one participant, with each run lasting 200 TR. And you have 4 conditions, then design should be a 600 x 4 numpy array. nuisance: optional, numpy array, shape=[time_points, nuisance_factors] The responses to these regressors will be marginalized out from each voxel, which means they are considered, but won't be assumed to share the same pseudo-SNR map with the design matrix. Therefore, the pseudo-SNR map will only reflect the relative contribution of design matrix to each voxel. You can provide time courses such as those for head motion to this parameter. Note that if auto_nuisance is set to True, the first n_nureg principal components of residual (excluding the response to the design matrix and the user-provided nuisance regressors and a constant baseline) will be included as additional nuisance regressor after the first round of fitting. If auto_nuisance is set to False, the nuisance regressors supplied by the users together with DC components will be used as nuisance time series. Please do not include time course of constant baseline in nuisance. scan_onsets: optional, numpy array, shape=[runs,] This specifies the indices of X which correspond to the onset of each scanning run. For example, if you have two experimental runs of the same subject, each with 100 TRs, then scan_onsets should be [0,100]. If you do not provide the argument, the program will assume all data are from the same run. The effect of them is to make the inverse matrix of the temporal covariance matrix of noise block-diagonal. coords: optional, numpy array, shape=[voxels,3] This is the coordinate of each voxel, used for implementing Gaussian Process prior. inten: optional, numpy array, shape=[voxel,] This is the average fMRI intensity in each voxel. It should be calculated from your data without any preprocessing such as z-scoring. Because it should reflect whether a voxel is bright (grey matter) or dark (white matter). A Gaussian Process kernel defined on both coordinate and intensity imposes a smoothness prior on adjcent voxels but with the same tissue type. The Gaussian Process is experimental and has shown good performance on some visual datasets. """ logger.info('Running Bayesian RSA') self.random_state_ = check_random_state(self.random_state) # setting random seed logger.debug('RandState set to {}'.format(self.random_state_)) assert not self.GP_inten or (self.GP_inten and self.GP_space),\ 'You must speficiy GP_space to True'\ 'if you want to use GP_inten' # Check input data assert_all_finite(X) assert X.ndim == 2, 'The data should be 2-dimensional ndarray' assert np.all(np.std(X, axis=0) > 0),\ 'The time courses of some voxels do not change at all.'\ ' Please make sure all voxels are within the brain' # check design matrix assert_all_finite(design) assert design.ndim == 2,\ 'The design matrix should be 2-dimensional ndarray' assert np.linalg.matrix_rank(design) == design.shape[1], \ 'Your design matrix has rank smaller than the number of'\ ' columns. Some columns can be explained by linear '\ 'combination of other columns. Please check your design matrix.' assert np.size(design, axis=0) == np.size(X, axis=0),\ 'Design matrix and data do not '\ 'have the same number of time points.' assert self.rank is None or self.rank <= design.shape[1],\ 'Your design matrix has fewer columns than the rank you set' # Check the nuisance regressors. if nuisance is not None: assert_all_finite(nuisance) assert nuisance.ndim == 2,\ 'The nuisance regressor should be 2-dimensional ndarray' assert np.linalg.matrix_rank(nuisance) == nuisance.shape[1], \ 'The nuisance regressor has rank smaller than the number of'\ 'columns. Some columns can be explained by linear '\ 'combination of other columns. Please check your nuisance' \ 'regressors.' assert np.size(nuisance, axis=0) == np.size(X, axis=0), \ 'Nuisance regressor and data do not have the same '\ 'number of time points.' # check scan_onsets validity assert scan_onsets is None or\ (np.max(scan_onsets) <= X.shape[0] and np.min(scan_onsets) >= 0),\ 'Some scan onsets provided are out of the range of time points.' # check the size of coords and inten if self.GP_space: logger.info('Fitting with Gaussian Process prior on log(SNR)') assert coords is not None and coords.shape[0] == X.shape[1],\ 'Spatial smoothness was requested by setting GP_space. '\ 'But the voxel number of coords does not match that of '\ 'data X, or voxel coordinates are not provided. '\ 'Please make sure that coords is in the shape of '\ '[n_voxel x 3].' assert coords.ndim == 2,\ 'The coordinate matrix should be a 2-d array' if self.GP_inten: assert inten is not None and inten.shape[0] == X.shape[1],\ 'The voxel number of intensity does not '\ 'match that of data X, or intensity not provided.' assert np.var(inten) > 0,\ 'All voxels have the same intensity.' if (not self.GP_space and coords is not None) or\ (not self.GP_inten and inten is not None): logger.warning('Coordinates or image intensity provided' ' but GP_space or GP_inten is not set ' 'to True. The coordinates or intensity are' ' ignored.') # Estimate the number of necessary nuisance regressors if self.auto_nuisance: if self.n_nureg is None: logger.info('number of nuisance regressors is determined ' 'automatically.') run_TRs, n_runs = self._run_TR_from_scan_onsets( X.shape[0], scan_onsets) ts_dc = self._gen_legendre(run_TRs, [0]) _, ts_base, _ = self._merge_DC_to_base( ts_dc, nuisance, False) ts_reg = np.concatenate((ts_base, design), axis=1) beta_hat = np.linalg.lstsq(ts_reg, X, rcond=None)[0] residuals = X - np.dot(ts_reg, beta_hat) self.n_nureg_ = np.max( [1, Ncomp_SVHT_MG_DLD_approx(residuals, self.nureg_zscore)]) logger.info('Use {} nuisance regressors to model the spatial ' 'correlation in noise.'.format(self.n_nureg_)) self.n_nureg_ = np.int32(self.n_nureg_) else: self.n_nureg_ = self.n_nureg self.n_nureg_ = np.int32(self.n_nureg_) # Run Bayesian RSA # Note that we have a change of notation here. Within _fit_RSA_UV, # design matrix is named X and data is named Y, to reflect the # generative model that data Y is generated by mixing the response # X to experiment conditions and other neural activity. # However, in fit(), we keep the tradition of scikit-learn that # X is the input data to fit and y, a reserved name not used, is # the label to map to from X. if not self.GP_space: # If GP_space is not requested, then the model is fitted # without imposing any Gaussian Process prior on log(SNR^2) self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self._beta_latent_, self.sigma_, self.rho_, _, _, _,\ self.X0_ = self._fit_RSA_UV(X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets) elif not self.GP_inten: # If GP_space is requested, but GP_inten is not, a GP prior # based on spatial locations of voxels will be imposed. self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self._beta_latent_, self.sigma_, self.rho_, \ self.lGPspace_, self.bGP_, _, \ self.X0_ = self._fit_RSA_UV( X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets, coords=coords) else: # If both self.GP_space and self.GP_inten are True, # a GP prior based on both location and intensity is imposed. self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self._beta_latent_, self.sigma_, self.rho_, \ self.lGPspace_, self.bGP_, self.lGPinten_, self.X0_ = \ self._fit_RSA_UV(X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets, coords=coords, inten=inten) self.C_ = utils.cov2corr(self.U_) self.design_ = design.copy() self._rho_design_, self._sigma2_design_ = \ self._est_AR1(self.design_, same_para=True) self._rho_X0_, self._sigma2_X0_ = self._est_AR1(self.X0_) # AR(1) parameters of the design matrix and nuisance regressors, # which will be used in transform or score. # Finally, we fit a null model with the same setting except # that there is no response to X self.beta0_null_, self.sigma_null_, self.rho_null_, \ self.X0_null_ = self._fit_null(Y=X, X_base=nuisance, scan_onsets=scan_onsets) self._rho_X0_null_, self._sigma2_X0_null_ =\ self._est_AR1(self.X0_null_) return self def transform(self, X, y=None, scan_onsets=None): """ Use the model to estimate the time course of response to each condition (ts), and the time course unrelated to task (ts0) which is spread across the brain. This is equivalent to "decoding" the design matrix and nuisance regressors from a new dataset different from the training dataset on which fit() was applied. An AR(1) smooth prior is imposed on the decoded ts and ts0 with the AR(1) parameters learnt from the corresponding time courses in the training data. Notice: if you set the rank to be lower than the number of experimental conditions (number of columns in the design matrix), the recovered task-related activity will have collinearity (the recovered time courses of some conditions can be linearly explained by the recovered time courses of other conditions). Parameters ---------- X : numpy arrays, shape=[time_points, voxels] fMRI data of new data of the same subject. The voxels should match those used in the fit() function. If data are z-scored (recommended) when fitting the model, data should be z-scored as well when calling transform() y : not used (as it is unsupervised learning) scan_onsets : numpy array, shape=[number of runs]. A list of indices corresponding to the onsets of scans in the data X. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ts : numpy arrays, shape = [time_points, condition] The estimated response to the task conditions which have the response amplitudes estimated during the fit step. ts0: numpy array, shape = [time_points, n_nureg] The estimated time course spread across the brain, with the loading weights estimated during the fit step. """ assert X.ndim == 2 and X.shape[1] == self.beta_.shape[1], \ 'The shape of X is not consistent with the shape of data '\ 'used in the fitting step. They should have the same number '\ 'of voxels' assert scan_onsets is None or (scan_onsets.ndim == 1 and 0 in scan_onsets), \ 'scan_onsets should either be None or an array of indices '\ 'If it is given, it should include at least 0' if scan_onsets is None: scan_onsets = np.array([0], dtype=int) else: scan_onsets = np.int32(scan_onsets) ts, ts0, log_p = self._transform( Y=X, scan_onsets=scan_onsets, beta=self.beta_, beta0=self.beta0_, rho_e=self.rho_, sigma_e=self.sigma_, rho_X=self._rho_design_, sigma2_X=self._sigma2_design_, rho_X0=self._rho_X0_, sigma2_X0=self._sigma2_X0_) return ts, ts0 def score(self, X, design, scan_onsets=None): """ Use the model and parameters estimated by fit function from some data of a participant to evaluate the log likelihood of some new data of the same participant. Design matrix of the same set of experimental conditions in the testing data should be provided, with each column corresponding to the same condition as that column in the design matrix of the training data. Unknown nuisance time series will be marginalized, assuming they follow the same spatial pattern as in the training data. The hypothetical response captured by the design matrix will be subtracted from data before the marginalization when evaluating the log likelihood. For null model, nothing will be subtracted before marginalization. There is a difference between the form of likelihood function used in fit() and score(). In fit(), the response amplitude beta to design matrix X and the modulation beta0 by nuisance regressor X0 are both marginalized, with X provided and X0 estimated from data. In score(), posterior estimation of beta and beta0 from the fitting step are assumed unchanged to testing data and X0 is marginalized. The logic underlying score() is to transfer as much as what we can learn from training data when calculating a likelihood score for testing data. If you z-scored your data during fit step, you should z-score them for score function as well. If you did not z-score in fitting, you should not z-score here either. Parameters ---------- X : numpy arrays, shape=[time_points, voxels] fMRI data of new data of the same subject. The voxels should match those used in the fit() function. If data are z-scored (recommended) when fitting the model, data should be z-scored as well when calling transform() design : numpy array, shape=[time_points, conditions] Design matrix expressing the hypothetical response of the task conditions in data X. scan_onsets : numpy array, shape=[number of runs]. A list of indices corresponding to the onsets of scans in the data X. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ll: float. The log likelihood of the new data based on the model and its parameters fit to the training data. ll_null: float. The log likelihood of the new data based on a null model which assumes the same as the full model for everything except for that there is no response to any of the task conditions. """ assert X.ndim == 2 and X.shape[1] == self.beta_.shape[1], \ 'The shape of X is not consistent with the shape of data '\ 'used in the fitting step. They should have the same number '\ 'of voxels' assert scan_onsets is None or (scan_onsets.ndim == 1 and 0 in scan_onsets), \ 'scan_onsets should either be None or an array of indices '\ 'If it is given, it should include at least 0' if scan_onsets is None: scan_onsets = np.array([0], dtype=int) else: scan_onsets = np.int32(scan_onsets) ll = self._score(Y=X, design=design, beta=self.beta_, scan_onsets=scan_onsets, beta0=self.beta0_, rho_e=self.rho_, sigma_e=self.sigma_, rho_X0=self._rho_X0_, sigma2_X0=self._sigma2_X0_) ll_null = self._score(Y=X, design=None, beta=None, scan_onsets=scan_onsets, beta0=self.beta0_, rho_e=self.rho_, sigma_e=self.sigma_, rho_X0=self._rho_X0_, sigma2_X0=self._sigma2_X0_) return ll, ll_null # The following 2 functions _D_gen and _F_gen generate templates used # for constructing inverse of covariance matrix of AR(1) noise # The inverse of covarian matrix is # (I - rho1 * D + rho1**2 * F) / sigma**2. D is a matrix where all the # elements adjacent to the diagonal are 1 and all others are 0. F is # a matrix which is 1 on all diagonal elements except for in the first # and last columns. We denote (I - rho1 * D + rho1**2 * F) with A. # In the function calculating likelihood function, # XTAX, YTAY_diag, YTAX all mean multiplying the inverse covariance matrix # in between either the design matrix or the data. # As one can see, even though rho1 and sigma2 might update as we keep # fitting parameters, several terms stay unchanged and do not need to # be re-calculated. # For example, in X'AX = X'(I + rho1*D + rho1**2*F)X / sigma2, # the products X'X, X'DX, X'FX, etc. can always be re-used if they # are pre-calculated. Therefore, _D_gen and _F_gen constructs matrices # D and F, and _prepare_data_* calculates these products that can be # re-used. In principle, once parameters have been fitted for a # dataset, they can be updated for new incoming data by adding the # products X'X, X'DX, X'FX, X'Y etc. from new data to those from # existing data, and refit the parameters starting from the ones # fitted from existing data. def _D_gen(self, TR): if TR > 0: return np.diag(np.ones(TR - 1), -1) \ + np.diag(np.ones(TR - 1), 1) else: return np.empty([0, 0]) def _F_gen(self, TR): if TR > 0: F = np.eye(TR) F[0, 0] = 0 F[TR - 1, TR - 1] = 0 return F else: return np.empty([0, 0]) def _run_TR_from_scan_onsets(self, n_T, scan_onsets=None): if scan_onsets is None: # assume that all data are acquired within the same scan. n_run = 1 run_TRs = np.array([n_T], dtype=int) else: # Each value in the scan_onsets tells the index at which # a new scan starts. For example, if n_T = 500, and # scan_onsets = [0,100,200,400], this means that the time points # of 0-99 are from the first scan, 100-199 are from the second, # 200-399 are from the third and 400-499 are from the fourth run_TRs = np.int32(np.diff(np.append(scan_onsets, n_T))) run_TRs = np.delete(run_TRs, np.where(run_TRs == 0)) n_run = run_TRs.size # delete run length of 0 in case of duplication in scan_onsets. logger.info('I infer that the number of volumes' ' in each scan are: {}'.format(run_TRs)) return run_TRs, n_run def _prepare_DF(self, n_T, scan_onsets=None): """ Prepare the essential template matrices D and F for pre-calculating some terms to be re-used. The inverse covariance matrix of AR(1) noise is sigma^-2 * (I - rho1*D + rho1**2 * F). And we denote A = I - rho1*D + rho1**2 * F""" run_TRs, n_run = self._run_TR_from_scan_onsets(n_T, scan_onsets) D_ele = map(self._D_gen, run_TRs) F_ele = map(self._F_gen, run_TRs) D = scipy.linalg.block_diag(*D_ele) F = scipy.linalg.block_diag(*F_ele) # D and F above are templates for constructing # the inverse of temporal covariance matrix of noise return D, F, run_TRs, n_run def _prepare_data_XY(self, X, Y, D, F): """Prepares different forms of products of design matrix X and data Y, or between themselves. These products are re-used a lot during fitting. So we pre-calculate them. Because these are reused, it is in principle possible to update the fitting as new data come in, by just incrementally adding the products of new data and their corresponding parts of design matrix to these pre-calculated terms. """ XTY, XTDY, XTFY = self._make_templates(D, F, X, Y) YTY_diag = np.sum(Y * Y, axis=0) YTDY_diag = np.sum(Y * np.dot(D, Y), axis=0) YTFY_diag = np.sum(Y * np.dot(F, Y), axis=0) XTX, XTDX, XTFX = self._make_templates(D, F, X, X) return XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, \ XTDX, XTFX def _gen_X_DC(self, run_TRs): if self.baseline_single: X_DC = np.ones((np.sum(run_TRs), 1)) else: X_DC = scipy.linalg.block_diag(*map(np.ones, run_TRs)).T return X_DC def _gen_legendre(self, run_TRs, orders): def reg(x): return np.concatenate( [scipy.special.legendre(o)(np.linspace(-1, 1, x))[None, :] for o in orders], axis=0) reg_poly = scipy.linalg.block_diag( *map(reg, run_TRs)).T return reg_poly def _prepare_data_XYX0(self, X, Y, X_base, X_res, D, F, run_TRs, no_DC=False): """Prepares different forms of products between design matrix X or data Y or nuisance regressors X0. These products are re-used a lot during fitting. So we pre-calculate them. no_DC means not inserting regressors for DC components into nuisance regressor. It will only take effect if X_base is not None. """ X_DC = self._gen_X_DC(run_TRs) reg_sol = np.linalg.lstsq(X_DC, X, rcond=None) if np.any(np.isclose(reg_sol[1], 0)): raise ValueError('Your design matrix appears to have ' 'included baseline time series.' 'Either remove them, or move them to' ' nuisance regressors.') X_DC, X_base, idx_DC = self._merge_DC_to_base(X_DC, X_base, no_DC) if X_res is None: X0 = X_base else: X0 = np.concatenate((X_base, X_res), axis=1) n_X0 = X0.shape[1] X0TX0, X0TDX0, X0TFX0 = self._make_templates(D, F, X0, X0) XTX0, XTDX0, XTFX0 = self._make_templates(D, F, X, X0) X0TY, X0TDY, X0TFY = self._make_templates(D, F, X0, Y) return X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, idx_DC def _merge_DC_to_base(self, X_DC, X_base, no_DC): """ Merge DC components X_DC to the baseline time series X_base (By baseline, this means any fixed nuisance regressors not updated during fitting, including DC components and any nuisance regressors provided by the user. X_DC is always in the first few columns of X_base. """ if X_base is not None: reg_sol = np.linalg.lstsq(X_DC, X_base, rcond=None) if not no_DC: if not np.any(np.isclose(reg_sol[1], 0)): # No columns in X_base can be explained by the # baseline regressors. So we insert them. X_base = np.concatenate((X_DC, X_base), axis=1) idx_DC = np.arange(0, X_DC.shape[1]) else: logger.warning('Provided regressors for uninteresting ' 'time series already include baseline. ' 'No additional baseline is inserted.') idx_DC = np.where(np.isclose(reg_sol[1], 0))[0] else: idx_DC = np.where(np.isclose(reg_sol[1], 0))[0] else: # If a set of regressors for non-interested signals is not # provided, then we simply include one baseline for each run. X_base = X_DC idx_DC = np.arange(0, X_base.shape[1]) logger.info('You did not provide time series of no interest ' 'such as DC component. Trivial regressors of' ' DC component are included for further modeling.' ' The final covariance matrix won''t ' 'reflect these components.') return X_DC, X_base, idx_DC def _make_ar1_quad_form(self, XTX, XTDX, XTFX, rho1): # Calculate the matrix X'AX = X'X - rho1 * X'DX + rho1^2 * X'FX # Here, rho1 is the AR(1) coefficient. X is a matrix of time series # with each row corresponding to a vector at one # time point. The forms of matrices D and F are defined in _prepare_DF # function. sigma^-2 * A would be the inverse of covariance matrix # of AR(1) process (precision matrix) with rho1 as the AR coefficient # and sigma^2 as the variance of independent noise at each time point. return XTX - rho1 * XTDX + rho1**2 * XTFX def _make_ar1_quad_form_grad(self, XTDX, XTFX, rho1): # Calculate the derivative of the quadratic form X'AX with respect to # AR1 coefficient rho1, given precalculated terms X'DX and X'FX, # and rho1. return - XTDX + 2 * rho1 * XTFX def _make_templates(self, D, F, X, Y): XTY = np.dot(X.T, Y) XTDY = np.dot(np.dot(X.T, D), Y) XTFY = np.dot(np.dot(X.T, F), Y) return XTY, XTDY, XTFY def _precompute_ar1_quad_forms(self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0): # Calculate the sandwich terms which put A between X, Y and X0 # These terms are used a lot in the likelihood. But in the _fitV # step, they only need to be calculated once, since A is fixed. # In _fitU step, they need to be calculated at each iteration, # because rho1 changes. XTAY = self._make_ar1_quad_form(XTY, XTDY, XTFY, rho1) # dimension: feature*space YTAY = self._make_ar1_quad_form(YTY_diag, YTDY_diag, YTFY_diag, rho1) # dimension: space, # A/sigma2 is the inverse of noise covariance matrix in each voxel. # YTAY means Y'AY XTAX = XTX[None, :, :] - rho1[:, None, None] \ * XTDX[None, :, :] \ + rho1[:, None, None]**2 * XTFX[None, :, :] # dimension: space*feature*feature X0TAX0 = X0TX0[None, :, :] - rho1[:, None, None] \ * X0TDX0[None, :, :] \ + rho1[:, None, None]**2 * X0TFX0[None, :, :] # dimension: space*#baseline*#baseline XTAX0 = XTX0[None, :, :] - rho1[:, None, None] \ * XTDX0[None, :, :] \ + rho1[:, None, None]**2 * XTFX0[None, :, :] # dimension: space*feature*#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, rho1) # dimension: #baseline*space X0TAX0_i = np.linalg.solve(X0TAX0, np.identity(n_X0)[None, :, :]) # dimension: space*#baseline*#baseline XTAcorrX = XTAX # dimension: space*feature*feature XTAcorrY = XTAY # dimension: feature*space for i_v in range(n_V): XTAcorrX[i_v, :, :] -= \ np.dot(np.dot(XTAX0[i_v, :, :], X0TAX0_i[i_v, :, :]), XTAX0[i_v, :, :].T) XTAcorrY[:, i_v] -= np.dot(np.dot(XTAX0[i_v, :, :], X0TAX0_i[i_v, :, :]), X0TAY[:, i_v]) XTAcorrXL = np.dot(XTAcorrX, L) # dimension: space*feature*rank LTXTAcorrXL = np.tensordot(XTAcorrXL, L, axes=(1, 0)) # dimension: rank*feature*rank LTXTAcorrY = np.dot(L.T, XTAcorrY) # dimension: rank*space YTAcorrY = YTAY - np.sum(X0TAY * np.einsum('ijk,ki->ji', X0TAX0_i, X0TAY), axis=0) # dimension: space return X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL def _calc_LL(self, rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, SNR2, n_V, n_T, n_run, rank, n_X0): # Calculate the log likelihood (excluding the GP prior of log(SNR)) # for both _loglike_AR1_diagV_fitU and _loglike_AR1_diagV_fitV, # in addition to a few other terms. LAMBDA_i = LTXTAcorrXL * SNR2[:, None, None] + np.eye(rank) # dimension: space*rank*rank LAMBDA = np.linalg.solve(LAMBDA_i, np.identity(rank)[None, :, :]) # dimension: space*rank*rank # LAMBDA is essentially the inverse covariance matrix of the # posterior probability of alpha, which bears the relation with # beta by beta = L * alpha. L is the Cholesky factor of the # shared covariance matrix U. Refer to the explanation below # Equation 5 in the NIPS paper. YTAcorrXL_LAMBDA = np.einsum('ji,ijk->ik', LTXTAcorrY, LAMBDA) # dimension: space*rank sigma2 = (YTAcorrY - np.sum(LTXTAcorrY * YTAcorrXL_LAMBDA.T, axis=0) * SNR2) / (n_T - n_X0) # dimension: space LL = - np.sum(np.log(sigma2)) * (n_T - n_X0) * 0.5 \ + np.sum(np.log(1 - rho1**2)) * n_run * 0.5 \ - np.sum(self._half_log_det(X0TAX0)) \ - np.sum(self._half_log_det(LAMBDA_i)) \ - (n_T - n_X0) * n_V * (1 + np.log(2 * np.pi)) * 0.5 # Log likelihood return LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 def _calc_dist2_GP(self, coords=None, inten=None, GP_space=False, GP_inten=False): # calculate the square of difference between each voxel's location # coorinates and image intensity. if GP_space: assert coords is not None, 'coordinate is not provided' # square of spatial distance between every two voxels dist2 = spdist.squareform(spdist.pdist(coords, 'sqeuclidean')) # set the hyperparameter for the GP process: if self.space_smooth_range is None: space_smooth_range = np.max(dist2)**0.5 / 2.0 # By default, we assume the length scale should be # within half the size of ROI. else: space_smooth_range = self.space_smooth_range if GP_inten: assert inten is not None, 'intensity is not provided' # squre of difference between intensities of # # every two voxels inten_diff2 = spdist.squareform( spdist.pdist(inten[:, None], 'sqeuclidean')) # set the hyperparameter for the GP process: if self.inten_smooth_range is None: inten_smooth_range = np.max(inten_diff2)**0.5 / 2.0 # By default, we assume the length scale should be # within half the maximum difference of intensity. else: inten_smooth_range = self.inten_smooth_range n_smooth = 2 else: inten_diff2 = None inten_smooth_range = None n_smooth = 1 else: n_smooth = 0 dist2 = None inten_diff2 = None GP_inten = False space_smooth_range = None inten_smooth_range = None return dist2, inten_diff2, space_smooth_range, inten_smooth_range,\ n_smooth def _build_index_param(self, n_l, n_V, n_smooth): """ Build dictionaries to retrieve each parameter from the combined parameters. """ idx_param_sing = {'Cholesky': np.arange(n_l), 'a1': n_l} # for simplified fitting idx_param_fitU = {'Cholesky': np.arange(n_l), 'a1': np.arange(n_l, n_l + n_V)} # for the likelihood function when we fit U (the shared covariance). idx_param_fitV = {'log_SNR2': np.arange(n_V - 1), 'c_space': n_V - 1, 'c_inten': n_V, 'c_both': np.arange(n_V - 1, n_V - 1 + n_smooth)} # for the likelihood function when we fit V (reflected by SNR of # each voxel) return idx_param_sing, idx_param_fitU, idx_param_fitV def _half_log_det(self, M): """ Return log(|M|)*0.5. For positive definite matrix M of more than 2 dimensions, calculate this for the last two dimension and return a value corresponding to each element in the first few dimensions. """ chol = np.linalg.cholesky(M) if M.ndim == 2: return np.sum(np.log(np.abs(np.diag(chol)))) else: return np.sum(np.log(np.abs(np.diagonal( chol, axis1=-2, axis2=-1))), axis=-1) def _chol_idx(self, n_C, rank): l_idx = np.tril_indices(n_C) if rank is not None: # The rank of covariance matrix is specified idx_rank = np.where(l_idx[1] < rank) l_idx = (l_idx[0][idx_rank], l_idx[1][idx_rank]) logger.info('Using the rank specified by the user: ' '{}'.format(rank)) else: rank = n_C # if not specified, we assume you want to # estimate a full rank matrix logger.warning('Please be aware that you did not specify the' ' rank of covariance matrix to estimate.' 'I will assume that the covariance matrix ' 'shared among voxels is of full rank.' 'Rank = {}'.format(rank)) logger.warning('Please be aware that estimating a matrix of ' 'high rank can be very slow.' 'If you have a good reason to specify a rank ' 'lower than the number of experiment conditions,' ' do so.') return l_idx, rank def _fit_RSA_UV(self, X, Y, X_base, scan_onsets=None, coords=None, inten=None): """ The major utility of fitting Bayesian RSA. Note that there is a naming change of variable. X in fit() is changed to Y here, and design in fit() is changed to X here. This is because we follow the tradition that X expresses the variable defined (controlled) by the experimenter, i.e., the time course of experimental conditions convolved by an HRF, and Y expresses data. However, in wrapper function fit(), we follow the naming routine of scikit-learn. """ GP_inten = self.GP_inten GP_space = self.GP_space rank = self.rank n_V = np.size(Y, axis=1) n_T = np.size(Y, axis=0) n_C = np.size(X, axis=1) l_idx, rank = self._chol_idx(n_C, rank) n_l = np.size(l_idx[0]) # the number of parameters for L t_start = time.time() D, F, run_TRs, n_run = self._prepare_DF( n_T, scan_onsets=scan_onsets) XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, \ XTDX, XTFX = self._prepare_data_XY(X, Y, D, F) X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, idx_DC = \ self._prepare_data_XYX0( X, Y, X_base, None, D, F, run_TRs, no_DC=False) # Prepare the data for fitting. These pre-calculated matrices # will be re-used a lot in evaluating likelihood function and # gradient. # DC component will be added to the nuisance regressors. # In later steps, we do not need to add DC components again dist2, inten_diff2, space_smooth_range, inten_smooth_range,\ n_smooth = self._calc_dist2_GP( coords=coords, inten=inten, GP_space=GP_space, GP_inten=GP_inten) # Calculating the distance between voxel locations and betweeen # voxel intensities. These are used if a Gaussian Process prior # is requested to regularize log(SNR^2) idx_param_sing, idx_param_fitU, idx_param_fitV = \ self._build_index_param(n_l, n_V, n_smooth) # Indexes to find each parameter in a combined parameter vector. current_GP = np.zeros(n_smooth) # We will perform the fitting in 2~3 steps: # (1) A preliminary fitting assuming all voxels share # exactly the same temporal covariance matrix for their noise. # SNR is assumed to be 1 for all voxels in this fitting. # Therefore, there are only n_l+2 free parameters. # (2) (optional) A fitting which allows each voxel to have their # own pseudo-SNR and AR(1) coefficients. But no Gaussian Process # prior is imposed on log(SNR). This step is neglected if GP # prior is not requested. This step allows the SNR parameters to # move closer to their correct values before GP is introduced. # This step alternately fits the shared covariance and voxel- # specific variance. It fits for init_iter steps and the # tolerance is also increased by a factor of 5 to speed up # fitting. # (3) Final fitting. If GP prior is requested, it will be # introduced in this step. Otherwise, just fit as the previous # step, but using un-altered tolerance setting, and n_iter # as the number of iteration. # Step 1 fitting, with a simplified model current_vec_U_chlsk_l, current_a1, current_logSigma2 = \ self._initial_fit_singpara( XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, X, Y, X0, idx_param_sing, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank) current_logSNR2 = -current_logSigma2 norm_factor = np.mean(current_logSNR2) current_logSNR2 = current_logSNR2 - norm_factor X_res = None # Step 2 fitting, which only happens if # GP prior is requested if GP_space: current_vec_U_chlsk_l, current_a1, current_logSNR2, X_res\ = self._fit_diagV_noGP( XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank) current_GP[0] = np.log(np.min( dist2[np.tril_indices_from(dist2, k=-1)])) # We start fitting the model with GP prior with a small # length scale: the size of voxels. # Alternatively, initialize with a large distance. # Further testing of initial parameters need to be done. # current_GP[0] = np.log(np.max(dist2)/4.0) logger.debug('current GP[0]:{}'.format(current_GP[0])) if GP_inten: current_GP[1] = np.log(np.maximum( np.percentile(inten_diff2[np.tril_indices_from( inten_diff2, k=-1)], 2), 0.5)) logger.debug( 'current GP[1]:{}'.format(current_GP[1])) # We start the length scale for intensity with # a small value. A heuristic is 2 percentile of # all the square differences. But it should not be # smaller than 0.5. This limit is set in case # many voxels have close to equal intensities, # which might render 2 percentile to 0. # Step 3 fitting. GP prior is imposed if requested. # In this step, unless auto_nuisance is set to False, X_res # will be re-estimated from the residuals after each step # of fitting. And X0 will be concatenation of X_base and X_res logger.debug('indexing:{}'.format(idx_param_fitV)) logger.debug('initial GP parameters:{}'.format(current_GP)) current_vec_U_chlsk_l, current_a1, current_logSNR2,\ current_GP, X_res = self._fit_diagV_GP( XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, current_GP, n_smooth, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank, GP_space, GP_inten, dist2, inten_diff2, space_smooth_range, inten_smooth_range) estU_chlsk_l_AR1_UV = np.zeros([n_C, rank]) estU_chlsk_l_AR1_UV[l_idx] = current_vec_U_chlsk_l est_cov_AR1_UV = np.dot(estU_chlsk_l_AR1_UV, estU_chlsk_l_AR1_UV.T) est_rho1_AR1_UV = 2 / np.pi * np.arctan(current_a1) est_SNR_AR1_UV = np.exp(current_logSNR2 / 2.0) # Calculating est_sigma_AR1_UV, est_sigma_AR1_UV, # est_beta_AR1_UV and est_beta0_AR1_UV X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, _ \ = self._prepare_data_XYX0( X, Y, X_base, X_res, D, F, run_TRs, no_DC=True) X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL\ = self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, estU_chlsk_l_AR1_UV, est_rho1_AR1_UV, n_V, n_X0) LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 \ = self._calc_LL(est_rho1_AR1_UV, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, est_SNR_AR1_UV**2, n_V, n_T, n_run, rank, n_X0) est_sigma_AR1_UV = sigma2**0.5 est_beta_AR1_UV = est_SNR_AR1_UV**2 \ * np.dot(estU_chlsk_l_AR1_UV, YTAcorrXL_LAMBDA.T) est_beta_AR1_UV_latent = \ est_SNR_AR1_UV**2 * YTAcorrXL_LAMBDA.T # the latent term means that X*L multiplied by this term # is the same as X*beta. This will be used for decoding # and cross-validating, in case L is low-rank est_beta0_AR1_UV = np.einsum( 'ijk,ki->ji', X0TAX0_i, (X0TAY - np.einsum('ikj,ki->ji', XTAX0, est_beta_AR1_UV))) # Now we want to collapse all beta0 corresponding to DC components # of different runs to a single map, and preserve only one DC component # across runs. This is because they should express the same component # and the new data to transform do not necessarily have the same # numbers of runs as the training data. if idx_DC.size > 1: collapsed_DC = np.sum(X0[:, idx_DC], axis=1) X0 = np.insert(np.delete(X0, idx_DC, axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(est_beta0_AR1_UV[idx_DC, :], axis=0) est_beta0_AR1_UV = np.insert( np.delete(est_beta0_AR1_UV, idx_DC, axis=0), 0, collapsed_beta0, axis=0) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) logger.debug('final GP parameters:{}'.format(current_GP)) if GP_space: est_space_smooth_r = np.exp(current_GP[0] / 2.0) if GP_inten: est_intensity_kernel_r = np.exp(current_GP[1] / 2.0) K_major = np.exp(- (dist2 / est_space_smooth_r**2 + inten_diff2 / est_intensity_kernel_r**2) / 2.0) else: est_intensity_kernel_r = None K_major = np.exp(- dist2 / est_space_smooth_r**2 / 2.0) K = K_major + np.diag(np.ones(n_V) * self.eta) invK_tilde_log_SNR = np.linalg.solve(K, current_logSNR2) / 2 log_SNR_invK_tilde_log_SNR = np.dot(current_logSNR2, invK_tilde_log_SNR) / 2 tau2, _ = self.tau2_prior(log_SNR_invK_tilde_log_SNR, n_V, self.tau_range) est_std_log_SNR = tau2 ** 0.5 else: est_space_smooth_r = None est_intensity_kernel_r = None est_std_log_SNR = None return est_cov_AR1_UV, estU_chlsk_l_AR1_UV, est_SNR_AR1_UV, \ est_beta_AR1_UV, est_beta0_AR1_UV, est_beta_AR1_UV_latent,\ est_sigma_AR1_UV, est_rho1_AR1_UV, est_space_smooth_r, \ est_std_log_SNR, est_intensity_kernel_r, X0 def _transform(self, Y, scan_onsets, beta, beta0, rho_e, sigma_e, rho_X, sigma2_X, rho_X0, sigma2_X0): """ Given the data Y and the response amplitudes beta and beta0 estimated in the fit step, estimate the corresponding X and X0. It is done by a forward-backward algorithm. We assume X and X0 both are vector autoregressive (VAR) processes, to capture temporal smoothness. Their VAR parameters are estimated from training data at the fit stage. """ logger.info('Transforming new data.') # Constructing the transition matrix and the variance of # innovation noise as prior for the latent variable X and X0 # in new data. n_C = beta.shape[0] n_T = Y.shape[0] weight = np.concatenate((beta, beta0), axis=0) T_X = np.diag(np.concatenate((rho_X, rho_X0))) Var_X = np.concatenate((sigma2_X / (1 - rho_X**2), sigma2_X0 / (1 - rho_X0**2))) Var_dX = np.concatenate((sigma2_X, sigma2_X0)) sigma2_e = sigma_e ** 2 scan_onsets = np.setdiff1d(scan_onsets, n_T) n_scan = scan_onsets.size X = [None] * scan_onsets.size X0 = [None] * scan_onsets.size total_log_p = 0 for scan, onset in enumerate(scan_onsets): # Forward step if scan == n_scan - 1: offset = n_T else: offset = scan_onsets[scan + 1] mu, mu_Gamma_inv, Gamma_inv, log_p_data, Lambda_0, \ Lambda_1, H, deltaY, deltaY_sigma2inv_rho_weightT = \ self._forward_step(Y[onset:offset, :], T_X, Var_X, Var_dX, rho_e, sigma2_e, weight) total_log_p += log_p_data # Backward step mu_hat, mu_Gamma_inv_hat, Gamma_inv_hat \ = self._backward_step( deltaY, deltaY_sigma2inv_rho_weightT, sigma2_e, weight, mu, mu_Gamma_inv, Gamma_inv, Lambda_0, Lambda_1, H) X[scan] = np.concatenate( [mu_t[None, :n_C] for mu_t in mu_hat]) X0[scan] = np.concatenate( [mu_t[None, n_C:] for mu_t in mu_hat]) X = np.concatenate(X) X0 = np.concatenate(X0) return X, X0, total_log_p def _score(self, Y, design, beta, scan_onsets, beta0, rho_e, sigma_e, rho_X0, sigma2_X0): """ Given the data Y, and the spatial pattern beta0 of nuisance time series, return the cross-validated score of the data Y given all parameters of the subject estimated during the first step. It is assumed that the user has design matrix built for the data Y. Both beta and beta0 are posterior expectation estimated from training data with the estimated covariance matrix U and SNR serving as prior. We marginalize X0 instead of fitting it in this function because this function is for the purpose of evaluating model no new data. We should avoid doing any additional fitting when performing cross-validation. The hypothetic response to the task will be subtracted, and the unknown nuisance activity which contributes to the data through beta0 will be marginalized. """ logger.info('Estimating cross-validated score for new data.') n_T = Y.shape[0] if design is not None: Y = Y - np.dot(design, beta) # The function works for both full model and null model. # If design matrix is not provided, the whole data is # used as input for _forward_step. If design matrix is provided, # residual after subtracting design * beta is fed to _forward_step T_X = np.diag(rho_X0) Var_X = sigma2_X0 / (1 - rho_X0**2) Var_dX = sigma2_X0 # Prior parmeters for X0: T_X is transitioning matrix, Var_X # is the marginal variance of the first time point. Var_dX is the # variance of the updating noise. sigma2_e = sigma_e ** 2 # variance of voxel-specific updating noise component scan_onsets = np.setdiff1d(scan_onsets, n_T).astype(int) n_scan = scan_onsets.size total_log_p = 0 for scan, onset in enumerate(scan_onsets): # Forward step if scan == n_scan - 1: offset = n_T else: offset = scan_onsets[scan + 1] _, _, _, log_p_data, _, _, _, _, _ = \ self._forward_step( Y[onset:offset, :], T_X, Var_X, Var_dX, rho_e, sigma2_e, beta0) total_log_p += log_p_data return total_log_p def _est_AR1(self, x, same_para=False): """ Estimate the AR(1) parameters of input x. Each column of x is assumed as independent from other columns, and each column is treated as an AR(1) process. If same_para is set as True, then all columns of x are concatenated and a single set of AR(1) parameters is estimated. Strictly speaking the breaking point between each concatenated column should be considered. But for long time series, this is ignored. """ if same_para: n_c = x.shape[1] x = np.reshape(x, x.size, order='F') rho, sigma2 = alg.AR_est_YW(x, 1) # We concatenate all the design matrix to estimate common AR(1) # parameters. This creates some bias because the end of one column # and the beginning of the next column of the design matrix are # treated as consecutive samples. rho = np.ones(n_c) * rho sigma2 = np.ones(n_c) * sigma2 else: rho = np.zeros(np.shape(x)[1]) sigma2 = np.zeros(np.shape(x)[1]) for c in np.arange(np.shape(x)[1]): rho[c], sigma2[c] = alg.AR_est_YW(x[:, c], 1) return rho, sigma2 def _forward_step(self, Y, T_X, Var_X, Var_dX, rho_e, sigma2_e, weight): """ forward step for HMM, assuming both the hidden state and noise have 1-step dependence on the previous value. """ # We currently only implement diagonal form # of covariance matrix for Var_X, Var_dX and T_X, which means # each dimension of X is independent and their innovation noise # are also independent. Note that log_p_data takes this assumption. if Var_X.ndim == 1: inv_Var_X = np.diag(1 / Var_X) half_log_det_Var_X = np.sum(np.log(Var_X)) / 2.0 Var_X = np.diag(Var_X) # the marginal variance of X else: half_log_det_Var_X = self._half_log_det(Var_X) inv_Var_X = np.linalg.inv(Var_X) if Var_dX.ndim == 1: inv_Var_dX = np.diag(1 / Var_dX) half_log_det_Var_dX = np.sum(np.log(Var_dX)) / 2.0 Var_dX = np.diag(Var_dX) # the marginal variance of Delta X (the change of X from # previous time point) else: inv_Var_dX = np.linalg.inv(Var_dX) half_log_det_Var_dX = self._half_log_det(Var_dX) if T_X.ndim == 1: T_X = np.diag(T_X) # Transfer function of X: the expected mean of X at t+1 # time point is T_x * X [n_T, n_V] = np.shape(Y) # numbers of time points and voxels mu = [None] * n_T # posterior mean of X, conditioned on all data up till the current # time point Gamma_inv = [None] * n_T # inverse of poterior Gamma. mu_Gamma_inv = [None] * n_T # mu * inv(Gamma) log_p_data = - np.log(np.pi * 2) * (n_T * n_V) / 2 \ - half_log_det_Var_X - np.sum(np.log(sigma2_e)) * n_T / 2.0\ + np.sum(np.log(1 - rho_e**2)) / 2.0 - half_log_det_Var_dX \ * (n_T - 1) # This is the term to be incremented by c_n at each time step. # We first add all the fixed terms to it. # The following are a few fixed terms. Lambda_0 = np.dot(T_X, np.dot(inv_Var_dX, T_X.T)) \ + np.dot(weight * rho_e**2 / sigma2_e, weight.T) H = np.dot(inv_Var_dX, T_X.T) + np.dot(weight * rho_e / sigma2_e, weight.T) Lambda_1 = inv_Var_dX + np.dot(weight / sigma2_e, weight.T) Gamma_inv[0] = inv_Var_X + np.dot( weight * (1 - rho_e**2) / sigma2_e, weight.T) # We might not need this and only use linalg.solve for related terms. mu_Gamma_inv[0] = np.dot( Y[0, :] * (1 - rho_e**2) / sigma2_e, weight.T) mu[0] = np.linalg.solve(Gamma_inv[0], mu_Gamma_inv[0]) log_p_data -= 0.5 * np.sum(Y[0, :]**2 * (1 - rho_e**2) / sigma2_e) # This is the term added for the first time point. deltaY = Y[1:, :] - rho_e * Y[:-1, :] deltaY_sigma2inv_rho_weightT = np.dot( deltaY / sigma2_e * rho_e, weight.T) for t in np.arange(1, n_T): Gamma_tilde_inv = Lambda_0 + Gamma_inv[t - 1] tmp = np.linalg.solve(Gamma_tilde_inv, H.T) Gamma_inv[t] = Lambda_1 - np.dot(H, tmp) mu_Gamma_inv[t] = np.dot(deltaY[t - 1, :] / sigma2_e, weight.T) \ + np.dot(mu_Gamma_inv[t - 1] - deltaY_sigma2inv_rho_weightT[t - 1, :], tmp) mu[t] = np.linalg.solve(Gamma_inv[t], mu_Gamma_inv[t]) tmp2 = mu_Gamma_inv[t - 1] - deltaY_sigma2inv_rho_weightT[t - 1, :] log_p_data += -self._half_log_det(Gamma_tilde_inv) \ + np.dot(tmp2, np.linalg.solve(Gamma_tilde_inv, tmp2)) / 2.0 log_p_data += -self._half_log_det(Gamma_inv[-1]) \ + np.dot(mu_Gamma_inv[-1], mu[-1]) / 2.0 \ - np.sum(deltaY**2 / sigma2_e) / 2.0 return mu, mu_Gamma_inv, Gamma_inv, log_p_data, Lambda_0, \ Lambda_1, H, deltaY, deltaY_sigma2inv_rho_weightT def _backward_step(self, deltaY, deltaY_sigma2inv_rho_weightT, sigma2_e, weight, mu, mu_Gamma_inv, Gamma_inv, Lambda_0, Lambda_1, H): """ backward step for HMM, assuming both the hidden state and noise have 1-step dependence on the previous value. """ n_T = len(Gamma_inv) # All the terms with hat before are parameters of posterior # distributions of X conditioned on data from all time points, # whereas the ones without hat calculated by _forward_step # are mean and covariance of posterior of X conditioned on # data up to the time point. Gamma_inv_hat = [None] * n_T mu_Gamma_inv_hat = [None] * n_T mu_hat = [None] * n_T mu_hat[-1] = mu[-1].copy() mu_Gamma_inv_hat[-1] = mu_Gamma_inv[-1].copy() Gamma_inv_hat[-1] = Gamma_inv[-1].copy() for t in np.arange(n_T - 2, -1, -1): tmp = np.linalg.solve(Gamma_inv_hat[t + 1] - Gamma_inv[t + 1] + Lambda_1, H) Gamma_inv_hat[t] = Gamma_inv[t] + Lambda_0 - np.dot(H.T, tmp) mu_Gamma_inv_hat[t] = mu_Gamma_inv[t] \ - deltaY_sigma2inv_rho_weightT[t, :] + np.dot( mu_Gamma_inv_hat[t + 1] - mu_Gamma_inv[t + 1] + np.dot(deltaY[t, :] / sigma2_e, weight.T), tmp) mu_hat[t] = np.linalg.solve(Gamma_inv_hat[t], mu_Gamma_inv_hat[t]) return mu_hat, mu_Gamma_inv_hat, Gamma_inv_hat def _initial_fit_singpara(self, XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, X, Y, X0, idx_param_sing, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank): """ Perform initial fitting of a simplified model, which assumes that all voxels share exactly the same temporal covariance matrix for their noise (the same noise variance and auto-correlation). The SNR is implicitly assumed to be 1 for all voxels. """ logger.info('Initial fitting assuming single parameter of ' 'noise for all voxels') X_joint = np.concatenate((X0, X), axis=1) beta_hat = np.linalg.lstsq(X_joint, Y, rcond=None)[0] residual = Y - np.dot(X_joint, beta_hat) # point estimates of betas and fitting residuals without assuming # the Bayesian model underlying RSA. # There are several possible ways of initializing the covariance. # (1) start from the point estimation of covariance cov_point_est = np.cov(beta_hat[n_X0:, :]) / np.var(residual) current_vec_U_chlsk_l = \ np.linalg.cholesky((cov_point_est + np.eye(n_C)) / 2)[l_idx] # We use the average of covariance of point estimation and an identity # matrix as the initial value of the covariance matrix, just in case # the user provides data in which n_V is smaller than n_C. # (2) start from identity matrix # current_vec_U_chlsk_l = np.eye(n_C)[l_idx] # (3) random initialization # current_vec_U_chlsk_l = self.random_state_.randn(n_l) # vectorized version of L, Cholesky factor of U, the shared # covariance matrix of betas across voxels. rho1 = np.sum( residual[0:-1, :] * residual[1:, :], axis=0) / \ np.sum(residual[0:-1, :] * residual[0:-1, :], axis=0) # Estimate of auto correlation assuming data includes pure noise. log_sigma2 = np.log(np.var( residual[1:, :] - residual[0:-1, :] * rho1, axis=0)) # log of estimates of the variance of the "innovation" noise # of AR(1) process at each time point. param0 = np.empty(np.sum(np.fromiter( (np.size(v) for v in idx_param_sing.values()), int))) # Initial parameter # Then we fill each part of the original guess of parameters param0[idx_param_sing['Cholesky']] = current_vec_U_chlsk_l param0[idx_param_sing['a1']] = np.median(np.tan(rho1 * np.pi / 2)) # Fit it. res = scipy.optimize.minimize( self._loglike_AR1_singpara, param0, args=(XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_sing, rank), method=self.optimizer, jac=True, tol=self.tol, options={'disp': self.minimize_options['disp'], 'maxiter': 100}) current_vec_U_chlsk_l = res.x[idx_param_sing['Cholesky']] current_a1 = res.x[idx_param_sing['a1']] * np.ones(n_V) # log(sigma^2) assuming the data include no signal is returned, # as a starting point for the iteration in the next step. # Although it should overestimate the variance, # setting it this way might allow it to track log(sigma^2) # more closely for each voxel. return current_vec_U_chlsk_l, current_a1, log_sigma2 def _fit_diagV_noGP( self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank): """ (optional) second step of fitting, full model but without GP prior on log(SNR). This step is only done if GP prior is requested. """ init_iter = self.init_iter logger.info('second fitting without GP prior' ' for {} times'.format(init_iter)) # Initial parameters param0_fitU = np.empty(np.sum(np.fromiter( (np.size(v) for v in idx_param_fitU.values()), int))) param0_fitV = np.empty(np.size(idx_param_fitV['log_SNR2'])) # We cannot use the same logic as the line above because # idx_param_fitV also includes entries for GP parameters. param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l.copy() param0_fitU[idx_param_fitU['a1']] = current_a1.copy() param0_fitV[idx_param_fitV['log_SNR2']] = \ current_logSNR2[:-1].copy() L = np.zeros((n_C, rank)) tol = self.tol * 5 for it in range(0, init_iter): X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, _ \ = self._prepare_data_XYX0( X, Y, X_base, X_res, D, F, run_TRs, no_DC=True) # fit U, the covariance matrix, together with AR(1) param param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l \ + self.random_state_.randn(n_l) \ * np.linalg.norm(current_vec_U_chlsk_l) \ / n_l**0.5 * np.exp(-it / init_iter * self.anneal_speed - 1) param0_fitU[idx_param_fitU['a1']] = current_a1 res_fitU = scipy.optimize.minimize( self._loglike_AR1_diagV_fitU, param0_fitU, args=(XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, current_logSNR2, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitU, rank), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_vec_U_chlsk_l = \ res_fitU.x[idx_param_fitU['Cholesky']] current_a1 = res_fitU.x[idx_param_fitU['a1']] norm_fitUchange = np.linalg.norm(res_fitU.x - param0_fitU) logger.debug('norm of parameter change after fitting U: ' '{}'.format(norm_fitUchange)) param0_fitU = res_fitU.x.copy() # fit V, reflected in the log(SNR^2) of each voxel rho1 = np.arctan(current_a1) * 2 / np.pi L[l_idx] = current_vec_U_chlsk_l X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, \ LTXTAcorrY, XTAcorrXL, LTXTAcorrXL = \ self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0) res_fitV = scipy.optimize.minimize( self._loglike_AR1_diagV_fitV, param0_fitV, args=(X0TAX0, XTAX0, X0TAY, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL, current_vec_U_chlsk_l, current_a1, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitV, rank, False, False), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_logSNR2[0:n_V - 1] = res_fitV.x current_logSNR2[-1] = - np.sum(current_logSNR2[0:n_V - 1]) norm_fitVchange = np.linalg.norm(res_fitV.x - param0_fitV) logger.debug('norm of parameter change after fitting V: ' '{}'.format(norm_fitVchange)) logger.debug('E[log(SNR2)^2]: {}'.format( np.mean(current_logSNR2**2))) # The lines below are for debugging purpose. # If any voxel's log(SNR^2) gets to non-finite number, # something might be wrong -- could be that the data has # nothing to do with the design matrix. if np.any(np.logical_not(np.isfinite(current_logSNR2))): logger.warning('Initial fitting: iteration {}'.format(it)) logger.warning('current log(SNR^2): ' '{}'.format(current_logSNR2)) logger.warning('log(sigma^2) has non-finite number') param0_fitV = res_fitV.x.copy() # Re-estimating X_res from residuals current_SNR2 = np.exp(current_logSNR2) if self.auto_nuisance: LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, current_sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, current_SNR2, n_V, n_T, n_run, rank, n_X0) betas = current_SNR2 * np.dot(L, YTAcorrXL_LAMBDA.T) beta0s = np.einsum( 'ijk,ki->ji', X0TAX0_i, (X0TAY - np.einsum('ikj,ki->ji', XTAX0, betas))) residuals = Y - np.dot(X, betas) - np.dot( X_base, beta0s[:np.shape(X_base)[1], :]) X_res = self.nureg_method( self.n_nureg_).fit_transform( self.preprocess_residual(residuals)) if norm_fitVchange / np.sqrt(param0_fitV.size) < tol \ and norm_fitUchange / np.sqrt(param0_fitU.size) \ < tol: break return current_vec_U_chlsk_l, current_a1, current_logSNR2, X_res def _fit_diagV_GP( self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X, Y, X_base, X_res, D, F, run_TRs, current_vec_U_chlsk_l, current_a1, current_logSNR2, current_GP, n_smooth, idx_param_fitU, idx_param_fitV, l_idx, n_C, n_T, n_V, n_l, n_run, n_X0, rank, GP_space, GP_inten, dist2, inten_diff2, space_smooth_range, inten_smooth_range): """ Last step of fitting. If GP is not requested, this step will still be done, just without GP prior on log(SNR). """ tol = self.tol n_iter = self.n_iter logger.info('Last step of fitting.' ' for maximum {} times'.format(n_iter)) # Initial parameters param0_fitU = np.empty(np.sum(np.fromiter( (np.size(v) for v in idx_param_fitU.values()), int))) param0_fitV = np.empty(np.size(idx_param_fitV['log_SNR2']) + np.size(idx_param_fitV['c_both'])) # We cannot use the same logic as the line above because # idx_param_fitV also includes entries for GP parameters. param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l.copy() param0_fitU[idx_param_fitU['a1']] = current_a1.copy() param0_fitV[idx_param_fitV['log_SNR2']] = \ current_logSNR2[:-1].copy() L = np.zeros((n_C, rank)) L[l_idx] = current_vec_U_chlsk_l if self.GP_space: param0_fitV[idx_param_fitV['c_both']] = current_GP.copy() for it in range(0, n_iter): X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, \ X0TY, X0TDY, X0TFY, X0, X_base, n_X0, _ = \ self._prepare_data_XYX0( X, Y, X_base, X_res, D, F, run_TRs, no_DC=True) # fit U param0_fitU[idx_param_fitU['Cholesky']] = \ current_vec_U_chlsk_l \ + self.random_state_.randn(n_l) \ * np.linalg.norm(current_vec_U_chlsk_l) \ / n_l**0.5 * np.exp(-it / n_iter * self.anneal_speed - 1) param0_fitU[idx_param_fitU['a1']] = current_a1 res_fitU = scipy.optimize.minimize( self._loglike_AR1_diagV_fitU, param0_fitU, args=(XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, current_logSNR2, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitU, rank), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_vec_U_chlsk_l = \ res_fitU.x[idx_param_fitU['Cholesky']] current_a1 = res_fitU.x[idx_param_fitU['a1']] L[l_idx] = current_vec_U_chlsk_l fitUchange = res_fitU.x - param0_fitU norm_fitUchange = np.linalg.norm(fitUchange) logger.debug('norm of parameter change after fitting U: ' '{}'.format(norm_fitUchange)) param0_fitU = res_fitU.x.copy() # fit V rho1 = np.arctan(current_a1) * 2 / np.pi X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, \ LTXTAcorrY, XTAcorrXL, LTXTAcorrXL = \ self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0) res_fitV = scipy.optimize.minimize( self._loglike_AR1_diagV_fitV, param0_fitV, args=( X0TAX0, XTAX0, X0TAY, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL, current_vec_U_chlsk_l, current_a1, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitV, rank, GP_space, GP_inten, dist2, inten_diff2, space_smooth_range, inten_smooth_range), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) current_logSNR2[0:n_V - 1] = \ res_fitV.x[idx_param_fitV['log_SNR2']] current_logSNR2[n_V - 1] = -np.sum(current_logSNR2[0:n_V - 1]) current_GP = res_fitV.x[idx_param_fitV['c_both']] fitVchange = res_fitV.x - param0_fitV norm_fitVchange = np.linalg.norm(fitVchange) param0_fitV = res_fitV.x.copy() logger.debug('norm of parameter change after fitting V: ' '{}'.format(norm_fitVchange)) logger.debug('E[log(SNR2)^2]: {}'.format( np.mean(current_logSNR2**2))) # Re-estimating X_res from residuals current_SNR2 = np.exp(current_logSNR2) if self.auto_nuisance: LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, current_sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, current_SNR2, n_V, n_T, n_run, rank, n_X0) betas = current_SNR2 \ * np.dot(L, YTAcorrXL_LAMBDA.T) beta0s = np.einsum( 'ijk,ki->ji', X0TAX0_i, (X0TAY - np.einsum('ikj,ki->ji', XTAX0, betas))) residuals = Y - np.dot(X, betas) - np.dot( X_base, beta0s[:np.shape(X_base)[1], :]) X_res = self.nureg_method(self.n_nureg_).fit_transform( self.preprocess_residual(residuals)) if GP_space: logger.debug('current GP[0]: {}'.format(current_GP[0])) logger.debug('gradient for GP[0]: {}'.format( res_fitV.jac[idx_param_fitV['c_space']])) if GP_inten: logger.debug('current GP[1]: {}'.format(current_GP[1])) logger.debug('gradient for GP[1]: {}'.format( res_fitV.jac[idx_param_fitV['c_inten']])) if np.max(np.abs(fitVchange)) < tol and \ np.max(np.abs(fitUchange)) < tol: break return current_vec_U_chlsk_l, current_a1, current_logSNR2,\ current_GP, X_res def _fit_null(self, Y, X_base, scan_onsets=None): """ Fit a null model. """ n_V = np.size(Y, axis=1) n_T = np.size(Y, axis=0) t_start = time.time() D, F, run_TRs, n_run = self._prepare_DF( n_T, scan_onsets=scan_onsets) YTY_diag = np.sum(Y * Y, axis=0) YTDY_diag = np.sum(Y * np.dot(D, Y), axis=0) YTFY_diag = np.sum(Y * np.dot(F, Y), axis=0) tol = self.tol n_iter = self.n_iter logger.info('Fitting null model' ' for maximum {} times'.format(n_iter)) # Add DC components capturing run-specific baselines. X_DC = self._gen_X_DC(run_TRs) X_DC, X_base, idx_DC = self._merge_DC_to_base( X_DC, X_base, no_DC=False) X_res = None param0 = np.zeros(n_V) for it in range(0, n_iter): if X_res is None: X0 = X_base else: X0 = np.concatenate((X_base, X_res), axis=1) n_X0 = X0.shape[1] X0TX0, X0TDX0, X0TFX0 = self._make_templates(D, F, X0, X0) X0TY, X0TDY, X0TFY = self._make_templates(D, F, X0, Y) res_null = scipy.optimize.minimize( self._loglike_AR1_null, param0, args=( YTY_diag, YTDY_diag, YTFY_diag, X0TX0, X0TDX0, X0TFX0, X0TY, X0TDY, X0TFY, n_T, n_V, n_run, n_X0), method=self.optimizer, jac=True, tol=tol, options=self.minimize_options) param_change = res_null.x - param0 param0 = res_null.x.copy() est_rho1_AR1_null = 2.0 / np.pi * np.arctan(param0) if self.auto_nuisance: X0TAX0 = X0TX0[None, :, :] \ - est_rho1_AR1_null[:, None, None] \ * X0TDX0[None, :, :] \ + est_rho1_AR1_null[:, None, None]**2 \ * X0TFX0[None, :, :] # dimension: space*#baseline*#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, est_rho1_AR1_null) # dimension: #baseline*space beta0s = np.linalg.solve(X0TAX0, X0TAY.T).T residuals = Y - np.dot(X_base, beta0s[:np.shape(X_base)[1], :]) X_res = self.nureg_method(self.n_nureg_).fit_transform( self.preprocess_residual(residuals)) if np.max(np.abs(param_change)) < self.tol: logger.info('The change of parameters is smaller than ' 'the tolerance value {}. Fitting is finished ' 'after {} iterations'.format(self.tol, it + 1)) break X0TAX0 = X0TX0[None, :, :] \ - est_rho1_AR1_null[:, None, None] \ * X0TDX0[None, :, :] \ + est_rho1_AR1_null[:, None, None]**2 \ * X0TFX0[None, :, :] # dimension: space*#baseline*#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, est_rho1_AR1_null) # dimension: #baseline*space est_beta0_AR1_null = np.linalg.solve(X0TAX0, X0TAY.T).T YTAY = self._make_ar1_quad_form(YTY_diag, YTDY_diag, YTFY_diag, est_rho1_AR1_null) # dimension: space, YTAcorrY = YTAY - np.sum(X0TAY * est_beta0_AR1_null, axis=0) # dimension: space, est_sigma_AR1_null = (YTAcorrY / (n_T - n_X0)) ** 0.5 if idx_DC.size > 1: collapsed_DC = np.sum(X0[:, idx_DC], axis=1) X0 = np.insert(np.delete(X0, idx_DC, axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(est_beta0_AR1_null[idx_DC, :], axis=0) est_beta0_AR1_null = np.insert( np.delete(est_beta0_AR1_null, idx_DC, axis=0), 0, collapsed_beta0, axis=0) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) return est_beta0_AR1_null, est_sigma_AR1_null, est_rho1_AR1_null, X0 # We fit two parts of the parameters iteratively. # The following are the corresponding negative log likelihood functions. def _loglike_AR1_diagV_fitU(self, param, XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, log_SNR2, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitU, rank): # This function calculates the log likelihood of data given cholesky # decomposition of U and AR(1) parameters of noise as free parameters. # Free parameters are in param. # The log of the square of signal to noise level in each voxel # (the ratio of the diagonal elements in V and # the noise variance) are fixed. This likelihood is iteratively # optimized with the one with suffix _fitV. # # The meaing of U and V follow this wiki page of matrix normal # distribution: # https://en.wikipedia.org/wiki/Matrix_normal_distribution # # We assume betas of all voxels as a matrix follow this distribution. # U describe the covariance between conditions. V describe the # covariance between voxels. # # In this version, we assume that beta is independent between voxels # and noise is also independent. # By the assumption that noise is independent, we only need to pass # the products X'X, X'Y and Y'Y, instead of X and Y # Y'Y is passed in the form of its diagonal elements. # DiagV means we assume that the variance of beta can be different # between voxels. This means that V is a diagonal matrix instead of # an identity matrix. The parameter includes the lower triangular # part of the cholesky decomposition # of U (flattened), then tan(rho1*pi/2) where rho1 is # each voxel's autoregressive coefficient (assumging AR(1) model). # Such parametrization avoids the need of boundaries # for parameters. L = np.zeros([n_C, rank]) # lower triagular matrix L, cholesky decomposition of U L[l_idx] = param[idx_param_fitU['Cholesky']] a1 = param[idx_param_fitU['a1']] rho1 = 2.0 / np.pi * np.arctan(a1) # auto-regressive coefficients SNR2 = np.exp(log_SNR2) # each element of SNR2 is the ratio of the diagonal element on V # to the variance of the fresh noise in that voxel X0TAX0, XTAX0, X0TAY, X0TAX0_i, \ XTAcorrX, XTAcorrY, YTAcorrY, \ LTXTAcorrY, XTAcorrXL, LTXTAcorrXL = \ self._precompute_ar1_quad_forms(XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, L, rho1, n_V, n_X0) # Only starting from this point, SNR2 is involved LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, SNR2, n_V, n_T, n_run, rank, n_X0) if not np.isfinite(LL): logger.warning('NaN detected!') logger.warning('LL: {}'.format(LL)) logger.warning('sigma2: {}'.format(sigma2)) logger.warning('YTAcorrY: {}'.format(YTAcorrY)) logger.warning('LTXTAcorrY: {}'.format(LTXTAcorrY)) logger.warning('YTAcorrXL_LAMBDA: {}'.format(YTAcorrXL_LAMBDA)) logger.warning('SNR2: {}'.format(SNR2)) YTAcorrXL_LAMBDA_LT = np.dot(YTAcorrXL_LAMBDA, L.T) # dimension: space*feature (feature can be larger than rank) deriv_L = -np.einsum('ijk,ikl,i', XTAcorrXL, LAMBDA, SNR2) \ - np.dot(np.einsum('ijk,ik->ji', XTAcorrXL, YTAcorrXL_LAMBDA) * SNR2**2 / sigma2, YTAcorrXL_LAMBDA) \ + np.dot(XTAcorrY / sigma2 * SNR2, YTAcorrXL_LAMBDA) # dimension: feature*rank # The following are for calculating the derivative to a1 deriv_a1 = np.empty(n_V) dXTAX_drho1 = -XTDX + 2 * rho1[:, None, None] * XTFX # dimension: space*feature*feature dXTAY_drho1 = self._make_ar1_quad_form_grad(XTDY, XTFY, rho1) # dimension: feature*space dYTAY_drho1 = self._make_ar1_quad_form_grad(YTDY_diag, YTFY_diag, rho1) # dimension: space, dX0TAX0_drho1 = - X0TDX0 \ + 2 * rho1[:, None, None] * X0TFX0 # dimension: space*rank*rank dXTAX0_drho1 = - XTDX0 \ + 2 * rho1[:, None, None] * XTFX0 # dimension: space*feature*rank dX0TAY_drho1 = self._make_ar1_quad_form_grad(X0TDY, X0TFY, rho1) # dimension: rank*space # The following are executed for each voxel. for i_v in range(n_V): # All variables with _ele as suffix are for data of just one voxel invX0TAX0_X0TAX_ele = np.dot(X0TAX0_i[i_v, :, :], XTAX0[i_v, :, :].T) invX0TAX0_X0TAY_ele = np.dot(X0TAX0_i[i_v, :, :], X0TAY[:, i_v]) dXTAX0_drho1_invX0TAX0_X0TAX_ele = np.dot(dXTAX0_drho1[i_v, :, :], invX0TAX0_X0TAX_ele) # preparation for the variable below dXTAcorrX_drho1_ele = dXTAX_drho1[i_v, :, :] \ - dXTAX0_drho1_invX0TAX0_X0TAX_ele \ - dXTAX0_drho1_invX0TAX0_X0TAX_ele.T \ + np.dot(np.dot(invX0TAX0_X0TAX_ele.T, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAX_ele) dXTAcorrY_drho1_ele = dXTAY_drho1[:, i_v] \ - np.dot(invX0TAX0_X0TAX_ele.T, dX0TAY_drho1[:, i_v]) \ - np.dot(dXTAX0_drho1[i_v, :, :], invX0TAX0_X0TAY_ele) \ + np.dot(np.dot(invX0TAX0_X0TAX_ele.T, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAY_ele) dYTAcorrY_drho1_ele = dYTAY_drho1[i_v] \ - np.dot(dX0TAY_drho1[:, i_v], invX0TAX0_X0TAY_ele) * 2\ + np.dot(np.dot(invX0TAX0_X0TAY_ele, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAY_ele) deriv_a1[i_v] = 2 / np.pi / (1 + a1[i_v]**2) \ * (- n_run * rho1[i_v] / (1 - rho1[i_v]**2) - np.einsum('ij,ij', X0TAX0_i[i_v, :, :], dX0TAX0_drho1[i_v, :, :]) * 0.5 - np.einsum('ij,ij', LAMBDA[i_v, :, :], np.dot(np.dot( L.T, dXTAcorrX_drho1_ele), L)) * (SNR2[i_v] * 0.5) - dYTAcorrY_drho1_ele * 0.5 / sigma2[i_v] + SNR2[i_v] / sigma2[i_v] * np.dot(dXTAcorrY_drho1_ele, YTAcorrXL_LAMBDA_LT[i_v, :]) - (0.5 * SNR2[i_v]**2 / sigma2[i_v]) * np.dot(np.dot(YTAcorrXL_LAMBDA_LT[i_v, :], dXTAcorrX_drho1_ele), YTAcorrXL_LAMBDA_LT[i_v, :])) deriv = np.empty(np.size(param)) deriv[idx_param_fitU['Cholesky']] = deriv_L[l_idx] deriv[idx_param_fitU['a1']] = deriv_a1 return -LL, -deriv def _loglike_AR1_diagV_fitV(self, param, X0TAX0, XTAX0, X0TAY, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY, LTXTAcorrY, XTAcorrXL, LTXTAcorrXL, L_l, a1, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_fitV, rank=None, GP_space=False, GP_inten=False, dist2=None, inten_dist2=None, space_smooth_range=None, inten_smooth_range=None): # This function calculates the log likelihood of data given # the log of the square of pseudo signal to noise ratio in each voxel. # The free parameter log(SNR^2) is in param # This likelihood is iteratively optimized with the one with _fitU. # The cholesky factor of U and autoregressive coefficient # in temporal AR(1) model for noise are fixed. # Because the ML estimate of the variance of noise in each voxel # (sigma^2) given other parameters has analytic form, # we do not need to explicitly parametrize it. # Just set it to the ML value. # # L_l is the lower triangular part of L, a1 is tan(rho1*pi/2), # where rho1 is the autoregressive coefficient in each voxel # We can optionally include Gaussion Process prior to log(SNR). # This term is not included in _fitU, because log(SNR) # are fixed in _fitU. # GP_space and GP_inten are Boolean, indicating whether we want to # include GP kernels either on voxel coordinates or intensity. # dist2 and inten_dist2 are the squares of spatial distances and # intensity differences ([n_voxel x n_voxel]. space_smooth_range # and inten_smooth_range are the range we believe the GP length # scale should reside in. They are used in additional half-cauchy # prior to constraint these length scales. n_l = np.size(l_idx[0]) # the number of parameters in the index of lower-triangular matrix if rank is None: rank = int((2 * n_C + 1 - np.sqrt(n_C**2 * 4 + n_C * 4 + 1 - 8 * n_l)) / 2) L = np.zeros([n_C, rank]) L[l_idx] = L_l log_SNR2 = np.empty(n_V) log_SNR2[0:n_V - 1] = param[idx_param_fitV['log_SNR2']] log_SNR2[-1] = -np.sum(log_SNR2[0:n_V - 1]) # This is following the restriction that SNR's have geometric mean # of 1. That is why they are called pseudo-SNR. This restriction # is imposed because SNR and L are determined only up to a scale # Be cautious that during simulation, when there is absolute # no signal in the data, sometimes the fitting diverges, # presumably because we have created correlation between logS_NR2 # due to the constraint. But I have not reproduced this often. SNR2 = np.exp(log_SNR2) # If requested, a GP prior is imposed on log(SNR). rho1 = 2.0 / np.pi * np.arctan(a1) # AR(1) coefficient, dimension: space LL, LAMBDA_i, LAMBDA, YTAcorrXL_LAMBDA, sigma2 \ = self._calc_LL(rho1, LTXTAcorrXL, LTXTAcorrY, YTAcorrY, X0TAX0, SNR2, n_V, n_T, n_run, rank, n_X0) # Log likelihood of data given parameters, without the GP prior. deriv_log_SNR2 = (-rank + np.trace(LAMBDA, axis1=1, axis2=2)) * 0.5\ + np.sum(YTAcorrXL_LAMBDA**2, axis=1) * SNR2 / sigma2 / 2 # Partial derivative of log likelihood over log(SNR^2) # dimension: space, # The second term above is due to the equation for calculating # sigma2 if GP_space: # Imposing GP prior on log(SNR) at least over # spatial coordinates c_space = param[idx_param_fitV['c_space']] l2_space = np.exp(c_space) # The square of the length scale of the GP kernel defined on # the spatial coordinates of voxels dl2_dc_space = l2_space # partial derivative of l^2 over b if GP_inten: c_inten = param[idx_param_fitV['c_inten']] l2_inten = np.exp(c_inten) # The square of the length scale of the GP kernel defined # on the image intensity of voxels dl2_dc_inten = l2_inten # partial derivative of l^2 over b K_major = np.exp(- (dist2 / l2_space + inten_dist2 / l2_inten) / 2.0) else: K_major = np.exp(- dist2 / l2_space / 2.0) # The kernel defined over the spatial coordinates of voxels. # This is a template: the diagonal values are all 1, meaning # the variance of log(SNR) has not been multiplied K_tilde = K_major + np.diag(np.ones(n_V) * self.eta) # We add a small number to the diagonal to make sure the matrix # is invertible. # Note that the K_tilder here is still template: # It is the correct K divided by the variance tau^2 # So it does not depend on the variance of the GP. L_K_tilde = np.linalg.cholesky(K_tilde) inv_L_K_tilde = np.linalg.solve(L_K_tilde, np.identity(n_V)) inv_K_tilde = np.dot(inv_L_K_tilde.T, inv_L_K_tilde) log_det_K_tilde = np.sum(np.log(np.diag(L_K_tilde)**2)) invK_tilde_log_SNR = np.dot(inv_K_tilde, log_SNR2) / 2 log_SNR_invK_tilde_log_SNR = np.dot(log_SNR2, invK_tilde_log_SNR) / 2 # MAP estimate of the variance of the Gaussian Process given # other parameters. tau2, log_ptau = self.tau2_prior(log_SNR_invK_tilde_log_SNR, n_V, self.tau_range) # log_ptau is log(p(tau)) given the form of prior for tau LL += log_ptau # GP prior terms added to the log likelihood LL = LL - log_det_K_tilde / 2.0 - n_V / 2.0 * np.log(tau2) \ - np.log(2 * np.pi) * n_V / 2.0 \ - log_SNR_invK_tilde_log_SNR / tau2 / 2 deriv_log_SNR2 -= invK_tilde_log_SNR / tau2 / 2.0 # Note that the derivative to log(SNR) is # invK_tilde_log_SNR / tau2, but we are calculating the # derivative to log(SNR^2) dK_tilde_dl2_space = dist2 * (K_major) / 2.0 \ / l2_space**2 deriv_c_space = \ (np.dot(np.dot(invK_tilde_log_SNR, dK_tilde_dl2_space), invK_tilde_log_SNR) / tau2 / 2.0 - np.sum(inv_K_tilde * dK_tilde_dl2_space) / 2.0)\ * dl2_dc_space # Prior on the length scales LL += scipy.stats.halfcauchy.logpdf( l2_space**0.5, scale=space_smooth_range) deriv_c_space -= 1 / (l2_space + space_smooth_range**2)\ * dl2_dc_space if GP_inten: dK_tilde_dl2_inten = inten_dist2 * K_major \ / 2.0 / l2_inten**2 deriv_c_inten = \ (np.dot(np.dot(invK_tilde_log_SNR, dK_tilde_dl2_inten), invK_tilde_log_SNR) / tau2 / 2.0 - np.sum(inv_K_tilde * dK_tilde_dl2_inten) / 2.0)\ * dl2_dc_inten # Prior on the length scale LL += scipy.stats.halfcauchy.logpdf( l2_inten**0.5, scale=inten_smooth_range) deriv_c_inten -= 1 / (l2_inten + inten_smooth_range**2)\ * dl2_dc_inten else: LL += np.sum(scipy.stats.norm.logpdf(log_SNR2 / 2.0, scale=self.tau_range)) # If GP prior is not requested, we still want to regularize on # the magnitude of log(SNR). deriv_log_SNR2 += - log_SNR2 / self.tau_range**2 / 4.0 deriv = np.empty(np.size(param)) deriv[idx_param_fitV['log_SNR2']] = \ deriv_log_SNR2[0:n_V - 1] - deriv_log_SNR2[n_V - 1] if GP_space: deriv[idx_param_fitV['c_space']] = deriv_c_space if GP_inten: deriv[idx_param_fitV['c_inten']] = deriv_c_inten return -LL, -deriv def _loglike_AR1_singpara(self, param, XTX, XTDX, XTFX, YTY_diag, YTDY_diag, YTFY_diag, XTY, XTDY, XTFY, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, l_idx, n_C, n_T, n_V, n_run, n_X0, idx_param_sing, rank=None): # In this version, we assume that beta is independent # between voxels and noise is also independent. # singpara version uses single parameter of sigma^2 and rho1 # to all voxels. This serves as the initial fitting to get # an estimate of L and sigma^2 and rho1. The SNR is inherently # assumed to be 1. n_l = np.size(l_idx[0]) # the number of parameters in the index of lower-triangular matrix if rank is None: rank = int((2 * n_C + 1 - np.sqrt(n_C**2 * 4 + n_C * 4 + 1 - 8 * n_l)) / 2) L = np.zeros([n_C, rank]) L[l_idx] = param[idx_param_sing['Cholesky']] a1 = param[idx_param_sing['a1']] rho1 = 2.0 / np.pi * np.arctan(a1) XTAX = XTX - rho1 * XTDX + rho1**2 * XTFX X0TAX0 = X0TX0 - rho1 * X0TDX0 + rho1**2 * X0TFX0 XTAX0 = XTX0 - rho1 * XTDX0 + rho1**2 * XTFX0 XTAcorrX = XTAX - np.dot(XTAX0, np.linalg.solve(X0TAX0, XTAX0.T)) XTAcorrXL = np.dot(XTAcorrX, L) LAMBDA_i = np.dot(np.dot(L.T, XTAcorrX), L) + np.eye(rank) XTAY = XTY - rho1 * XTDY + rho1**2 * XTFY X0TAY = X0TY - rho1 * X0TDY + rho1**2 * X0TFY XTAcorrY = XTAY - np.dot(XTAX0, np.linalg.solve(X0TAX0, X0TAY)) LTXTAcorrY = np.dot(L.T, XTAcorrY) YTAY = YTY_diag - rho1 * YTDY_diag + rho1**2 * YTFY_diag YTAcorrY = YTAY \ - np.sum(X0TAY * np.linalg.solve(X0TAX0, X0TAY), axis=0) LAMBDA_LTXTAcorrY = np.linalg.solve(LAMBDA_i, LTXTAcorrY) L_LAMBDA_LTXTAcorrY = np.dot(L, LAMBDA_LTXTAcorrY) sigma2 = np.mean(YTAcorrY - np.sum(LTXTAcorrY * LAMBDA_LTXTAcorrY, axis=0))\ / (n_T - n_X0) LL = n_V * (-np.log(sigma2) * (n_T - n_X0) * 0.5 + np.log(1 - rho1**2) * n_run * 0.5 - self._half_log_det(X0TAX0) - self._half_log_det(LAMBDA_i)) deriv_L = np.dot(XTAcorrY, LAMBDA_LTXTAcorrY.T) / sigma2 \ - np.dot(np.dot(XTAcorrXL, LAMBDA_LTXTAcorrY), LAMBDA_LTXTAcorrY.T) / sigma2 \ - np.linalg.solve(LAMBDA_i, XTAcorrXL.T).T * n_V # These terms are used to construct derivative to a1. dXTAX_drho1 = - XTDX + 2 * rho1 * XTFX dX0TAX0_drho1 = - X0TDX0 + 2 * rho1 * X0TFX0 dXTAX0_drho1 = - XTDX0 + 2 * rho1 * XTFX0 invX0TAX0_X0TAX = np.linalg.solve(X0TAX0, XTAX0.T) dXTAX0_drho1_invX0TAX0_X0TAX = np.dot(dXTAX0_drho1, invX0TAX0_X0TAX) dXTAcorrX_drho1 = dXTAX_drho1 - dXTAX0_drho1_invX0TAX0_X0TAX \ - dXTAX0_drho1_invX0TAX0_X0TAX.T \ + np.dot(np.dot(invX0TAX0_X0TAX.T, dX0TAX0_drho1), invX0TAX0_X0TAX) dLTXTAcorrXL_drho1 = np.dot(np.dot(L.T, dXTAcorrX_drho1), L) dYTAY_drho1 = - YTDY_diag + 2 * rho1 * YTFY_diag dX0TAY_drho1 = - X0TDY + 2 * rho1 * X0TFY invX0TAX0_X0TAY = np.linalg.solve(X0TAX0, X0TAY) dYTAX0_drho1_invX0TAX0_X0TAY = np.sum(dX0TAY_drho1 * invX0TAX0_X0TAY, axis=0) dYTAcorrY_drho1 = dYTAY_drho1 - dYTAX0_drho1_invX0TAX0_X0TAY * 2\ + np.sum(invX0TAX0_X0TAY * np.dot(dX0TAX0_drho1, invX0TAX0_X0TAY), axis=0) dXTAY_drho1 = - XTDY + 2 * rho1 * XTFY dXTAcorrY_drho1 = dXTAY_drho1 \ - np.dot(dXTAX0_drho1, invX0TAX0_X0TAY) \ - np.dot(invX0TAX0_X0TAX.T, dX0TAY_drho1) \ + np.dot(np.dot(invX0TAX0_X0TAX.T, dX0TAX0_drho1), invX0TAX0_X0TAY) deriv_a1 = 2.0 / (np.pi * (1 + a1**2)) \ * (n_V * (- n_run * rho1 / (1 - rho1**2) - 0.5 * np.trace(np.linalg.solve( X0TAX0, dX0TAX0_drho1)) - 0.5 * np.trace(np.linalg.solve( LAMBDA_i, dLTXTAcorrXL_drho1))) - 0.5 * np.sum(dYTAcorrY_drho1) / sigma2 + np.sum(dXTAcorrY_drho1 * L_LAMBDA_LTXTAcorrY) / sigma2 - 0.5 * np.sum(np.dot(dXTAcorrX_drho1, L_LAMBDA_LTXTAcorrY) * L_LAMBDA_LTXTAcorrY) / sigma2) deriv = np.empty(np.size(param)) deriv[idx_param_sing['Cholesky']] = deriv_L[l_idx] deriv[idx_param_sing['a1']] = deriv_a1 return -LL, -deriv def _loglike_AR1_null(self, param, YTY_diag, YTDY_diag, YTFY_diag, X0TX0, X0TDX0, X0TFX0, X0TY, X0TDY, X0TFY, n_T, n_V, n_run, n_X0): # This function calculates the log likelihood of data given AR(1) # parameters of noise as free parameters. # Free parameters are in param. # It serves as a null model which assumes no response to design # matrix. a1 = param rho1 = 2.0 / np.pi * np.arctan(a1) # auto-regressive coefficients YTAY = self._make_ar1_quad_form(YTY_diag, YTDY_diag, YTFY_diag, rho1) # dimension: space, # A/sigma2 is the inverse of noise covariance matrix in each voxel. # YTAY means Y'AY X0TAX0 = X0TX0[None, :, :] - rho1[:, None, None] \ * X0TDX0[None, :, :] \ + rho1[:, None, None]**2 * X0TFX0[None, :, :] # dimension: space*#baseline*#baseline X0TAY = self._make_ar1_quad_form(X0TY, X0TDY, X0TFY, rho1) # dimension: #baseline*space # X0TAX0_i = np.linalg.solve(X0TAX0, np.identity(n_X0)[None, :, :]) X0TAX0_i = np.linalg.inv(X0TAX0) # dimension: space*#baseline*#baseline YTAcorrY = YTAY - np.sum(X0TAY * np.einsum('ijk,ki->ji', X0TAX0_i, X0TAY), axis=0) # dimension: space, sigma2 = YTAcorrY / (n_T - n_X0) # dimension: space, LL = - np.sum(np.log(sigma2)) * (n_T - n_X0) * 0.5 \ + np.sum(np.log(1 - rho1**2)) * n_run * 0.5 \ - np.sum(self._half_log_det(X0TAX0)) \ - (n_T - n_X0) * n_V * (1 + np.log(2 * np.pi)) * 0.5 # The following are for calculating the derivative to a1 deriv_a1 = np.empty(n_V) dYTAY_drho1 = self._make_ar1_quad_form_grad(YTDY_diag, YTFY_diag, rho1) # dimension: space, dX0TAX0_drho1 = - X0TDX0 \ + 2 * rho1[:, None, None] * X0TFX0 # dimension: space*rank*rank dX0TAY_drho1 = self._make_ar1_quad_form_grad(X0TDY, X0TFY, rho1) # dimension: rank*space # The following are executed for each voxel. for i_v in range(n_V): # All variables with _ele as suffix are for data of just one voxel invX0TAX0_X0TAY_ele = np.dot(X0TAX0_i[i_v, :, :], X0TAY[:, i_v]) # preparation for the variable below dYTAcorrY_drho1_ele = dYTAY_drho1[i_v] \ - np.dot(dX0TAY_drho1[:, i_v], invX0TAX0_X0TAY_ele) * 2\ + np.dot(np.dot(invX0TAX0_X0TAY_ele, dX0TAX0_drho1[i_v, :, :]), invX0TAX0_X0TAY_ele) deriv_a1[i_v] = 2 / np.pi / (1 + a1[i_v]**2) \ * (- n_run * rho1[i_v] / (1 - rho1[i_v]**2) - np.einsum('ij,ij', X0TAX0_i[i_v, :, :], dX0TAX0_drho1[i_v, :, :]) * 0.5 - dYTAcorrY_drho1_ele * 0.5 / sigma2[i_v]) deriv = deriv_a1 return -LL, -deriv class GBRSA(BRSA): """Group Bayesian representational Similarity Analysis (GBRSA) Given the time series of neural imaging data in a region of interest (ROI) and the hypothetical neural response (design matrix) to each experimental condition of interest, calculate the shared covariance matrix of the voxels(recording unit)' response to each condition, and the relative SNR of each voxels. The relative SNR could be considered as the degree of contribution of each voxel to this shared covariance matrix. A correlation matrix converted from the covariance matrix will be provided as a quantification of neural representational similarity. Both tools provide estimation of SNR and noise parameters at the end, and both tools provide empirical Bayesian estimates of activity patterns beta, together with weight map of nuisance signals beta0. The differences of this tool from BRSA are: (1) It allows fitting a shared covariance matrix (which can be converted to similarity matrix) across multiple subjects. This is analogous to SRM under funcalign submodule. Because of using multiple subjects, the result is less noisy. (2) In the fitting process, the SNR and noise parameters are marginalized for each voxel. Therefore, this tool should be faster than BRSA when analyzing an ROI of hundreds to thousands voxels. It does not provide a spatial smoothness prior on SNR though. (3) The voxel-wise pseudo-SNR and noise parameters estimated are posterior mean estimates, while those estimated by BRSA are maximum-a-posterior estimates. If your goal is to perform searchlight RSA with relatively fewer voxels on single subject, BRSA should be faster. However, GBRSA can in principle be used together with searchlight in a template space such as MNI. .. math:: Y = X \\cdot \\beta + X_0 \\cdot \\beta_0 + \\epsilon \\beta_i \\sim N(0,(s_{i} \\sigma_{i})^2 U) See also `.BRSA`. Please note that the model assumes that the covariance matrix U which all \\beta_i follow is zero-meaned. For more details of its implication, see documentation of `.BRSA` Parameters ---------- n_iter : int. Number of maximum iterations to run the algorithm. rank : int. The rank of the covariance matrix. If not provided, the covariance matrix will be assumed to be full rank. When you have many conditions (e.g., calculating the similarity matrix of responses to each event), you might want to start with specifying a lower rank and use metrics such as AIC or BIC to decide the optimal rank. The log likelihood for the fitted data can be retrieved through private attributes _LL_train\\_. Note that this log likelihood score is only used here for selecting hyperparameters such as rank. For any formal model comparison, we recommend using score() function on left-out data. auto_nuisance: Boolean. In order to model spatial correlation between voxels that cannot be accounted for by common response captured in the design matrix, we assume that a set of time courses not related to the task conditions are shared across voxels with unknown amplitudes. One approach is for users to provide time series which they consider as nuisance but exist in the noise (such as head motion). The other way is to take the first n_nureg principal components in the residual after subtracting the response to the design matrix from the data, and use these components as the nuisance regressor. This flag is for the second approach. If turned on, PCA or factor analysis will be applied to the residuals to obtain new nuisance regressors in each round of fitting. These two approaches can be combined. If the users provide nuisance regressors and set this flag as True, then the first n_nureg principal components of the residuals after subtracting both the responses to design matrix and the user-supplied nuisance regressors will be used in addition to the nuisance regressors provided by the users. Note that nuisance regressor is not required from user. If it is not provided, DC components for each run will be included as nuisance regressor regardless of the auto_nuisance parameter. n_nureg: Optional[int]. Number of nuisance regressors to use in order to model signals shared across voxels not captured by the design matrix. This number is in addition to any nuisance regressor that the user has already provided. If set to None, the number of nuisance regressors will be automatically determined based on M Gavish and D Donoho's approximate estimation of optimal hard threshold for singular values. (Gavish & Donoho, IEEE Transactions on Information Theory 60.8 (2014): 5040-5053.) This only takes effect if auto_nuisance is True. nureg_zscore: Boolean. A flag to tell the algorithm whether data is z-scored before estimating the number of nuisance regressor components necessary to account for spatial noise correlation. It also determinie whether the residual noise is z-scored before estimating the nuisance regressors from residual. This only takes effect if auto_nuisance is True. nureg_method: string, naming a method from sklearn.decomposition. 'PCA', 'ICA', 'FA' or 'SPCA' are currently supported. The method to estimate the shared component in noise across voxels. This only takes effect if auto_nuisance is True. baseline_single: Boolean. A time course of constant 1 will be included to the nuisance regressor for each participant. If baseline_single is set to False, one such regressor is included for each fMRI run, but at the end of fitting, a single component in beta0\\_ will be computed as the average of the weight maps corresponding to these regressors. This might cause underestimation of noise variance. If baseline_single is True, only one regressor of constant 1 will be used for the whole dataset. This might be desirable if you believe the average image intensity might not scale with the same proportion for different voxels across scan. In other words, it is possible that some part of the brain is more vulnerable to change in baseline intensity due to facts such as field inhomogeneity. Setting baseline_single to True will force the nuisance regressors automatically estimated from residuals to capture this. However, when each task condition only occurs in one run and when the design matrix in each run sums together close to a flat line, this option can cause the estimated similarity to be extremely high between conditions occuring in the same run. SNR_prior: string. The type of prior for pseudo-SNR. If set to 'exp', truncated exponential distribution with scale parameter of 1 is imposed on pseudo-SNR. If set to 'lognorm', a truncated log normal prior is imposed. In this case, the standard deviation of log(SNR) is set by the parameter logS_range. If set to 'unif', a uniform prior in [0,1] is imposed. In all above cases, SNR is numerically marginalized on a grid of parameters. So the parameter SNR_bins determines how accurate the numerical integration is. The more number of bins are used, the more accurate the numerical integration becomes. If set to 'equal', all voxels are assumed to have the same fixed SNR. Pseudo-SNR is 1.0 for all voxels. In all the cases, the grids used for pseudo-SNR do not really set an upper bound for SNR, because the real SNR is determined by both pseudo-SNR and U, the shared covariance structure. logS_range: float. The reasonable range of the spread of SNR in log scale. This parameter only takes effect if SNR_prior is set to 'lognorm'. It is effectively the `s` parameter of `scipy.stats.lognorm`, or the standard deviation of the distribution in log scale. logS_range specifies how variable you believe the SNRs to vary across voxels in log scale. This range should not be set too large, otherwise the fitting may encounter numerical issue. If it is set too small, the estimated SNR will turn to be too close to each other and the estimated similarity matrix might overfit to voxels of low SNR. If you increase logS_range, it is recommended to increase SNR_bins accordingly, otherwise the pseudo-SNR values evaluated might be too sparse, causing the posterior pseudo-SNR estimations to be clustered around the bins. SNR_bins: integer. The number of bins used to numerically marginalize the pseudo-SNR parameter. In general, you should try to choose a large number to the degree that decreasing SNR_bins does not change the result of fitting result. However, very large number of bins also causes slower computation and larger memory consumption. For SNR_prior='lognorm', the default value 21 is based on the default value of logS_range=1.0 and bin width of 0.3 on log scale. But it is also a reasonable choice for the other two options for SNR_prior. rho_bins: integer. The number of bins to divide the region of (-1, 1) for rho. This only takes effect for fitting the marginalized version. If set to 20, discrete numbers of {-0.95, -0.85, ..., 0.95} will be used to numerically integrate rho from -1 to 1. optimizer: str or callable. The optimizer to use for minimizing cost function which scipy.optimize.minimize can accept. We use 'L-BFGS-B' as a default. Users can try other strings corresponding to optimizer provided by scipy.optimize.minimize, or a custom optimizer, such as 'BFGS' or 'CG'. Note that BRSA fits a lot of parameters. So a chosen optimizer should accept gradient (Jacobian) of the cost function. Otherwise the fitting is likely to be unbarely slow. We do not calculate Hessian of the objective function. So an optimizer which requires Hessian cannot be used. minimize_options: dictionary. This is the dictionary passed as the options argument to scipy.optimize.minize which minimizes the cost function during fitting. Notice that the minimization is performed for up to n_iter times, with the nuisance regressor re-estimated each time. So within each of the n_iter steps of fitting, scipy.optimize.minize does not need to fully converge. The key 'maxiter' in this dictionary determines the maximum number of iteration done by scipy.optimize.minimize within each of the n_iter steps of fitting. tol: float. Tolerance parameter passed to scipy.optimize.minimize. It is also used for determining convergence of the alternating fitting procedure. random_state : RandomState or an int seed. A random number generator instance to define the state of the random permutations generator whenever the module needs to generate random number (e.g., initial parameter of the Cholesky factor). anneal_speed: float. Annealing is introduced in fitting of the Cholesky decomposition of the shared covariance matrix. The amount of perturbation decays exponentially. This parameter sets the ratio of the maximum number of iteration to the time constant of the exponential. anneal_speed=10 means by n_iter/10 iterations, the amount of perturbation is reduced by 2.713 times. Attributes ---------- U_ : numpy array, shape=[condition,condition]. The shared covariance matrix L_ : numpy array, shape=[condition,condition]. The Cholesky factor of the shared covariance matrix (lower-triangular matrix). C_: numpy array, shape=[condition,condition]. The correlation matrix derived from the shared covariance matrix. This is the estimated similarity matrix between neural patterns to your task conditions. Notice that it is recommended that you also check U\\_, which is the covariance matrix underlying this correlation matrix. In cases there is almost no response to your task conditions, the diagonal values of U\\_ would become very small and C\\_ might contain many correlation coefficients close to 1 or -1. This might not reflect true strong correlation or strong negative correlation, but a result of lack of task-related neural activity, design matrix that does not match true neural response, or not enough data. It is also recommended to check nSNR\\_ after mapping it back to the brain. A "reasonable" map should at least have higher values in gray matter in than white matter. nSNR_ : list of numpy arrays, shape=[voxels,] for each subject in the list. The pseuso-SNR of all voxels. If SNR_prior='lognormal', the geometric mean of nSNR\\_ would be approximately 1. If SNR_prior='unif', all nSNR\\_ would be in the range of (0,1). If SNR_prior='exp' (default), the range of values would vary depending on the data and SNR_bins, but many should have low values with few voxels with high values. Note that this attribute can not be interpreted as true SNR, but the relative ratios between voxels indicate the contribution of each voxel to the representational similarity structure. sigma_ : list of numpy arrays, shape=[voxels,] for each subject. The estimated standard deviation of the noise in each voxel Assuming AR(1) model, this means the standard deviation of the innovation noise. rho_ : list of numpy arrays, shape=[voxels,] for each subject. The estimated autoregressive coefficient of each voxel beta_: list of numpy arrays, shape=[conditions, voxels] for each subject. The posterior mean estimation of the response amplitudes of each voxel to each task condition. beta0_: list of numpy arrays, shape=[n_nureg + n_base, voxels] for each subject. The loading weights of each voxel for the shared time courses not captured by the design matrix. n_base is the number of columns of the user-supplied nuisance regressors plus one for DC component. X0_: list of numpy arrays, shape=[time_points, n_nureg + n_base] for each subject. The estimated time course that is shared across voxels but unrelated to the events of interest (design matrix). beta0_null_: list of numpy arrays, shape=[n_nureg + n_base, voxels] for each subject. The equivalent of beta0\\_ in a null model which does not include the design matrix and response pattern beta X0_null_: list of numpy arrays, shape=[time_points, n_nureg + n_base] for each subject. The equivalent of X0\\_ in a null model which does not include the design matrix and response pattern beta n_nureg_: 1-d numpy array Number of nuisance regressor used to model the spatial noise correlation of each participant. random_state_: `RandomState` Random number generator initialized using random_state. """ def __init__( self, n_iter=100, rank=None, auto_nuisance=True, n_nureg=None, nureg_zscore=True, nureg_method='PCA', baseline_single=False, logS_range=1.0, SNR_prior='exp', SNR_bins=21, rho_bins=20, tol=1e-4, optimizer='L-BFGS-B', minimize_options={'gtol': 1e-4, 'disp': False, 'maxiter': 20}, random_state=None, anneal_speed=10): self.n_iter = n_iter self.rank = rank self.auto_nuisance = auto_nuisance self.n_nureg = n_nureg self.nureg_zscore = nureg_zscore if auto_nuisance: assert (n_nureg is None) \ or (isinstance(n_nureg, int) and n_nureg > 0), \ 'n_nureg should be a positive integer or None'\ ' if auto_nuisance is True.' if self.nureg_zscore: self.preprocess_residual = lambda x: _zscore(x) else: self.preprocess_residual = lambda x: x if nureg_method == 'FA': self.nureg_method = lambda x: FactorAnalysis(n_components=x) elif nureg_method == 'PCA': self.nureg_method = lambda x: PCA(n_components=x, whiten=True) elif nureg_method == 'SPCA': self.nureg_method = lambda x: SparsePCA(n_components=x, max_iter=20, tol=tol) elif nureg_method == 'ICA': self.nureg_method = lambda x: FastICA(n_components=x, whiten=True) else: raise ValueError('nureg_method can only be FA, PCA, ' 'SPCA(for sparse PCA) or ICA') self.baseline_single = baseline_single if type(logS_range) is int: logS_range = float(logS_range) self.logS_range = logS_range assert SNR_prior in ['unif', 'lognorm', 'exp', 'equal'], \ 'SNR_prior can only be chosen from ''unif'', ''lognorm''' \ ' ''exp'' and ''equal''' self.SNR_prior = SNR_prior if self.SNR_prior == 'equal': self.SNR_bins = 1 else: self.SNR_bins = SNR_bins self.rho_bins = rho_bins self.tol = tol self.optimizer = optimizer self.minimize_options = minimize_options self.random_state = random_state self.anneal_speed = anneal_speed return def fit(self, X, design, nuisance=None, scan_onsets=None): """ Fit the model to data of all participants jointly. Parameters ---------- X: list of numpy arrays, shape=[time_points, voxels] for each entry. Data to be fitted. Each participant corresponds to one item in the list. If you have multiple scans of the same participants that you want to analyze together, you should concatenate them along the time dimension after proper preprocessing (e.g. spatial alignment), and specify the onsets of each scan in scan_onsets. design: list of numpy arrays, shape=[time_points, conditions] for each. This is the design matrix of each participant. It should only include the hypothetic response for task conditions. You should not include regressors for a DC component or motion parameters, unless with a strong reason. If you want to model head motion, you should include them in nuisance regressors. If you have multiple run, the design matrix of all runs should be concatenated along the time dimension for each participant, with every column for one condition across runs. If the design matrix is the same for all subjects, either provide a list as required, or provide single numpy array. nuisance: optional, list of numpy arrays, shape=[time_points, nuisance_factors] for each subject in the list. Nuisance regressors of each participant. The responses to these regressors will be marginalized out from each voxel, which means they are considered, but won't be assumed to share the same pseudo-SNR map with the design matrix. Therefore, the pseudo-SNR map will only reflect the relative contribution of design matrix to each voxel. You can provide time courses such as those for head motion to this parameter. Note that if auto_nuisance is set to True, the first n_nureg principal components of residual (excluding the response to the design matrix and the user-provided nuisance regressors) will be included as additional nuisance regressor after the first round of fitting. If auto_nuisance is set to False, the nuisance regressors supplied by the users together with DC components will be used as nuisance time series. scan_onsets: optional, list numpy arrays, shape=[runs,] for each. Each item in the list specifies the indices of X which correspond to the onset of each scanning run for one participant. For example, if you have two experimental runs of the first participant, each with 100 TRs, and one run of the second participant, with 150 TR, then scan_onsets should be [ndarry([0, 100]), ndarry([150])]. The effect of this argument is to make the inverse matrix of the temporal covariance matrix of noise block-diagonal. If you do not provide the argument, the program will assume all data are from the same run for each participant. """ logger.info('Running Group Bayesian RSA (which can also analyze' ' data of a single participant). Voxel-specific parameters' 'are all marginalized.') self.random_state_ = check_random_state(self.random_state) # setting random seed logger.debug('RandState set to {}'.format(self.random_state_)) # Checking all inputs. X = self._check_data_GBRSA(X) design = self._check_design_GBRSA(design, X) nuisance = self._check_nuisance_GBRSA( copy.deepcopy(nuisance), X) # The reason that we use copy of nuisance is because they # may be modified inside our code. scan_onsets = self._check_scan_onsets_GBRSA(scan_onsets, X) # Run Marginalized Bayesian RSA # Note that we have a change of notation here. # Within _fit_RSA_marginalized, design matrix is named X # and data is named Y, to reflect the # generative model that data Y is generated by mixing the response # X to experiment conditions and other neural activity. # However, in fit(), we keep the scikit-learn API that # X is the input data to fit and y, a reserved name not used, is # the label to map to from X. assert self.SNR_bins >= 10 and self.SNR_prior != 'equal' or \ self.SNR_bins == 1 and self.SNR_prior == 'equal', \ 'At least 10 bins are required to perform the numerical'\ ' integration over SNR, unless choosing SNR_prior=''equal'','\ ' in which case SNR_bins should be 1.' assert self.rho_bins >= 10, \ 'At least 10 bins are required to perform the numerical'\ ' integration over rho' assert self.logS_range * 6 / self.SNR_bins < 0.5 \ or self.SNR_prior != 'lognorm', \ 'The minimum grid of log(SNR) should not be larger than 0.5 '\ 'if log normal prior is chosen for SNR.' \ ' Please consider increasing SNR_bins or reducing logS_range' self.n_subj_ = len(X) self.n_V_ = [None] * self.n_subj_ for subj, x in enumerate(X): self.n_V_[subj] = x.shape[1] if self.auto_nuisance: if self.n_nureg is None: logger.info('numbers of nuisance regressors are determined ' 'automatically.') n_runs = np.zeros(self.n_subj_) n_comps = np.ones(self.n_subj_) for s_id in np.arange(self.n_subj_): # For each subject, determine the number of nuisance # regressors needed to account for the covariance # in residuals. # Residual is calculated by regrssing # out the design matrix and DC component and linear trend # from data of each run. run_TRs, n_runs[s_id] = self._run_TR_from_scan_onsets( X[s_id].shape[0], scan_onsets[s_id]) ts_dc = self._gen_legendre(run_TRs, [0]) _, ts_base, _ = self._merge_DC_to_base( ts_dc, nuisance[s_id], False) ts_reg = np.concatenate((ts_base, design[s_id]), axis=1) beta_hat = np.linalg.lstsq(ts_reg, X[s_id], rcond=None)[0] residuals = X[s_id] - np.dot(ts_reg, beta_hat) n_comps[s_id] = np.min( [np.max([Ncomp_SVHT_MG_DLD_approx( residuals, self.nureg_zscore), 1]), np.linalg.matrix_rank(residuals) - 1]) # n_nureg_ should not exceed the rank of # residual minus 1. self.n_nureg_ = n_comps logger.info('Use {} nuisance regressors to model the spatial ' 'correlation in noise.'.format(self.n_nureg_)) else: self.n_nureg_ = self.n_nureg * np.ones(self.n_subj_) self.n_nureg_ = np.int32(self.n_nureg_) self.beta0_null_, self.sigma_null_, self.rho_null_, self.X0_null_,\ self._LL_null_train_ = self._fit_RSA_marginalized_null( Y=X, X_base=nuisance, scan_onsets=scan_onsets) self.U_, self.L_, self.nSNR_, self.beta_, self.beta0_,\ self.sigma_, self.rho_, self.X0_, self._LL_train_ = \ self._fit_RSA_marginalized( X=design, Y=X, X_base=nuisance, scan_onsets=scan_onsets) self.C_ = utils.cov2corr(self.U_) self.design_ = design.copy() self._rho_design_ = [None] * self.n_subj_ self._sigma2_design_ = [None] * self.n_subj_ self._rho_X0_ = [None] * self.n_subj_ self._sigma2_X0_ = [None] * self.n_subj_ self._rho_X0_null_ = [None] * self.n_subj_ self._sigma2_X0_null_ = [None] * self.n_subj_ for subj in np.arange(self.n_subj_): self._rho_design_[subj], self._sigma2_design_[subj] = \ self._est_AR1(self.design_[subj], same_para=True) self._rho_X0_[subj], self._sigma2_X0_[subj] = \ self._est_AR1(self.X0_[subj]) self._rho_X0_null_[subj], self._sigma2_X0_null_[subj] =\ self._est_AR1(self.X0_null_[subj]) # AR(1) parameters of the design matrix and nuisance regressors, # which will be used in transform or score. return self def transform(self, X, y=None, scan_onsets=None): """ Use the model to estimate the time course of response to each condition (ts), and the time course unrelated to task (ts0) which is spread across the brain. This is equivalent to "decoding" the design matrix and nuisance regressors from a new dataset different from the training dataset on which fit() was applied. An AR(1) smooth prior is imposed on the decoded ts and ts0 with the AR(1) parameters learnt from the corresponding time courses in the training data. Parameters ---------- X : list of 2-D arrays. For each item, shape=[time_points, voxels] New fMRI data of the same subjects. The voxels should match those used in the fit() function. The size of the list should match the size of the list X fed to fit(), with each item in the list corresponding to data from the same subject in the X fed to fit(). If you do not need to transform some subjects' data, leave the entry corresponding to that subject as None. If data are z-scored when fitting the model, data should be z-scored as well when calling transform() y : not used (as it is unsupervised learning) scan_onsets : list of 1-D numpy arrays, Each array corresponds to the onsets of scans in the data X for the particular subject. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ts : list of 2-D arrays. For each, shape = [time_points, condition] The estimated response to the cognitive dimensions （task dimensions) whose response amplitudes were estimated during the fit step. One item for each subject. If some subjects' data are not provided, None will be returned. ts0: list of 2-D array. For each, shape = [time_points, n_nureg] The estimated time courses spread across the brain, with the loading weights estimated during the fit step. One item for each subject. If some subjects' data are not provided, None will be returned. """ X = self._check_data_GBRSA(X, for_fit=False) scan_onsets = self._check_scan_onsets_GBRSA(scan_onsets, X) assert len(X) == self.n_subj_ ts = [None] * self.n_subj_ ts0 = [None] * self.n_subj_ log_p = [None] * self.n_subj_ for i, x in enumerate(X): if x is not None: s = scan_onsets[i] ts[i], ts0[i], log_p[i] = self._transform( Y=x, scan_onsets=s, beta=self.beta_[i], beta0=self.beta0_[i], rho_e=self.rho_[i], sigma_e=self.sigma_[i], rho_X=self._rho_design_[i], sigma2_X=self._sigma2_design_[i], rho_X0=self._rho_X0_[i], sigma2_X0=self._sigma2_X0_[i]) return ts, ts0 def score(self, X, design, scan_onsets=None): """ After fit() is applied to the data of a group of participants, use the parameters estimated by fit() function to evaluate from some data of a set of participants to evaluate the log likelihood of some new data of the same participants given these estimated parameters. Design matrices of the same set of experimental conditions in the testing data should be provided, with each column corresponding to the same condition as that column in the design matrix of the training data. Unknown nuisance time series will be marginalized, assuming they follow the same spatial pattern as in the training data. The hypothetical response captured by the design matrix will be subtracted from data before the marginalization when evaluating the log likelihood. For null model, nothing will be subtracted before marginalization. There is a difference between the form of likelihood function used in fit() and score(). In fit(), the response amplitude beta to design matrix X and the modulation beta0 by nuisance regressor X0 are both marginalized, with X provided and X0 estimated from data. In score(), posterior estimation of beta and beta0 from the fitting step are assumed unchanged in testing data; X is assumed given by the user, and X0 is marginalized. The logic underlying score() is to transfer as much as what we can learn from training data when calculating a likelihood score for testing data. This is done at the cost of using point estimation for beta and beta0. If you z-scored your data during fit step, you should z-score them for score function as well. If you did not z-score in fitting, you should not z-score here either. Parameters ---------- X : List of 2-D arrays. For each item, shape=[time_points, voxels] fMRI data of new data of the same participants. The voxels of each participants should match those used in the fit() function. If data are z-scored (recommended) when fitting the model, data should be z-scored as well when calling transform() design : List of 2-D arrays. shape=[time_points, conditions] for each Each corresponds to one participant. Design matrices expressing the hypothetical response of the task conditions in data X. scan_onsets : List of 2-D arrays, shape=[#fMRI runs] for each Each array corresponds to one participant. Lists of indices corresponding to the onsets of scans in the data X. If not provided, data will be assumed to be acquired in a continuous scan. Returns ------- ll: list, shape=[number of participants] The log likelihoods of the new data based on the model and its parameters fit to the training data. If data of some participants are not provided, the corresponding entry will be None. ll_null: list, shape=[number of participants] The log likelihood of the new data based on a null model which assumes the same as the full model for everything except for that there is no response to any of the task conditions. """ X = self._check_data_GBRSA(X, for_fit=False) scan_onsets = self._check_scan_onsets_GBRSA(scan_onsets, X) design = self._check_design_GBRSA(design, X) assert len(X) == self.n_subj_ ll = [None] * self.n_subj_ ll_null = [None] * self.n_subj_ for subj in np.arange(self.n_subj_): if X[subj] is not None: ll[subj] = self._score( Y=X[subj], design=design[subj], beta=self.beta_[subj], scan_onsets=scan_onsets[subj], beta0=self.beta0_[subj], rho_e=self.rho_[subj], sigma_e=self.sigma_[subj], rho_X0=self._rho_X0_[subj], sigma2_X0=self._sigma2_X0_[subj]) ll_null[subj] = self._score( Y=X[subj], design=None, beta=None, scan_onsets=scan_onsets[subj], beta0=self.beta0_[subj], rho_e=self.rho_[subj], sigma_e=self.sigma_[subj], rho_X0=self._rho_X0_[subj], sigma2_X0=self._sigma2_X0_[subj]) return ll, ll_null def _precompute_ar1_quad_forms_marginalized( self, XTY, XTDY, XTFY, YTY_diag, YTDY_diag, YTFY_diag, XTX, XTDX, XTFX, X0TX0, X0TDX0, X0TFX0, XTX0, XTDX0, XTFX0, X0TY, X0TDY, X0TFY, rho1, n_V, n_X0): # Calculate the sandwich terms which put Acorr between X, Y and X0 # These terms are used a lot in the likelihood. This function # is used for the marginalized version. XTAY = XTY - rho1[:, None, None] * XTDY \ + rho1[:, None, None]**2 * XTFY # dimension: #rho*feature*space YTAY_diag = YTY_diag - rho1[:, None] * YTDY_diag \ + rho1[:, None]**2 * YTFY_diag # dimension: #rho*space, # A/sigma2 is the inverse of noise covariance matrix in each voxel. # YTAY means Y'AY XTAX = XTX - rho1[:, None, None] * XTDX \ + rho1[:, None, None]**2 * XTFX # dimension: n_rho*feature*feature X0TAX0 = X0TX0[None, :, :] - rho1[:, None, None] \ * X0TDX0[None, :, :] \ + rho1[:, None, None]**2 * X0TFX0[None, :, :] # dimension: #rho*#baseline*#baseline XTAX0 = XTX0[None, :, :] - rho1[:, None, None] \ * XTDX0[None, :, :] \ + rho1[:, None, None]**2 * XTFX0[None, :, :] # dimension: n_rho*feature*#baseline X0TAY = X0TY - rho1[:, None, None] * X0TDY \ + rho1[:, None, None]**2 * X0TFY # dimension: #rho*#baseline*space X0TAX0_i = np.linalg.solve(X0TAX0, np.identity(n_X0)[None, :, :]) # dimension: #rho*#baseline*#baseline XTAcorrX = XTAX # dimension: #rho*feature*feature XTAcorrY = XTAY # dimension: #rho*feature*space YTAcorrY_diag = YTAY_diag for i_r in range(np.size(rho1)): XTAcorrX[i_r, :, :] -= \ np.dot(np.dot(XTAX0[i_r, :, :], X0TAX0_i[i_r, :, :]), XTAX0[i_r, :, :].T) XTAcorrY[i_r, :, :] -= np.dot(np.dot(XTAX0[i_r, :, :], X0TAX0_i[i_r, :, :]), X0TAY[i_r, :, :]) YTAcorrY_diag[i_r, :] -= np.sum( X0TAY[i_r, :, :] * np.dot(X0TAX0_i[i_r, :, :], X0TAY[i_r, :, :]), axis=0) return X0TAX0, X0TAX0_i, XTAcorrX, XTAcorrY, YTAcorrY_diag, \ X0TAY, XTAX0 def _fit_RSA_marginalized(self, X, Y, X_base, scan_onsets=None): """ The major utility of fitting Bayesian RSA (marginalized version). Note that there is a naming change of variable. X in fit() is changed to Y here, and design in fit() is changed to X here. This is because we follow the tradition that X expresses the variable defined (controlled) by the experimenter, i.e., the time course of experimental conditions convolved by an HRF, and Y expresses data. However, in wrapper function fit(), we follow the naming routine of scikit-learn. """ rank = self.rank n_subj = len(Y) n_V = [np.size(y, axis=1) for y in Y] n_T = [np.size(y, axis=0) for y in Y] n_C = np.size(X[0], axis=1) l_idx, rank = self._chol_idx(n_C, rank) n_l = np.size(l_idx[0]) # the number of parameters for L t_start = time.time() logger.info('Starting to fit the model. Maximum iteration: ' '{}.'.format(self.n_iter)) # log_SNR_grids, SNR_weights \ # = np.polynomial.hermite.hermgauss(SNR_bins) # SNR_weights = SNR_weights / np.pi**0.5 # SNR_grids = np.exp(log_SNR_grids * self.logS_range * 2**.5) SNR_grids, SNR_weights = self._set_SNR_grids() logger.info('The grids of pseudo-SNR used for numerical integration ' 'is {}.'.format(SNR_grids)) assert np.max(SNR_grids) < 1e10, \ 'ATTENTION!! The range of grids of pseudo-SNR' \ ' to be marginalized is too large. Please ' \ 'consider reducing logS_range to 1 or 2' rho_grids, rho_weights = self._set_rho_grids() logger.info('The grids of rho used to do numerical integration ' 'is {}.'.format(rho_grids)) n_grid = self.SNR_bins * self.rho_bins log_weights = np.reshape( np.log(SNR_weights[:, None]) + np.log(rho_weights), n_grid) all_rho_grids = np.reshape(np.repeat( rho_grids[None, :], self.SNR_bins, axis=0), n_grid) all_SNR_grids = np.reshape(np.repeat( SNR_grids[:, None], self.rho_bins, axis=1), n_grid) # Prepare the data for fitting. These pre-calculated matrices # will be re-used a lot in evaluating likelihood function and # gradient. D = [None] * n_subj F = [None] * n_subj run_TRs = [None] * n_subj n_run = [None] * n_subj XTY = [None] * n_subj XTDY = [None] * n_subj XTFY = [None] * n_subj YTY_diag = [None] * n_subj YTDY_diag = [None] * n_subj YTFY_diag = [None] * n_subj XTX = [None] * n_subj XTDX = [None] * n_subj XTFX = [None] * n_subj X0TX0 = [None] * n_subj X0TDX0 = [None] * n_subj X0TFX0 = [None] * n_subj XTX0 = [None] * n_subj XTDX0 = [None] * n_subj XTFX0 = [None] * n_subj X0TY = [None] * n_subj X0TDY = [None] * n_subj X0TFY = [None] * n_subj X0 = [None] * n_subj X_res = [None] * n_subj n_X0 = [None] * n_subj idx_DC = [None] * n_subj log_fixed_terms = [None] * n_subj # Initialization for L. # There are several possible ways of initializing the covariance. # (1) start from the point estimation of covariance cov_point_est = np.zeros((n_C, n_C)) for subj in range(n_subj): D[subj], F[subj], run_TRs[subj], n_run[subj] = self._prepare_DF( n_T[subj], scan_onsets=scan_onsets[subj]) XTY[subj], XTDY[subj], XTFY[subj], YTY_diag[subj], \ YTDY_diag[subj], YTFY_diag[subj], XTX[subj], XTDX[subj], \ XTFX[subj] = self._prepare_data_XY( X[subj], Y[subj], D[subj], F[subj]) # The contents above stay fixed during fitting. # Initializing X0 as DC baseline # DC component will be added to the nuisance regressors. # In later steps, we do not need to add DC components again X0TX0[subj], X0TDX0[subj], X0TFX0[subj], XTX0[subj], XTDX0[subj], \ XTFX0[subj], X0TY[subj], X0TDY[subj], X0TFY[subj], X0[subj], \ X_base[subj], n_X0[subj], idx_DC[subj] = \ self._prepare_data_XYX0( X[subj], Y[subj], X_base[subj], None, D[subj], F[subj], run_TRs[subj], no_DC=False) X_joint = np.concatenate((X0[subj], X[subj]), axis=1) beta_hat = np.linalg.lstsq(X_joint, Y[subj], rcond=None)[0] residual = Y[subj] - np.dot(X_joint, beta_hat) # point estimates of betas and fitting residuals without assuming # the Bayesian model underlying RSA. cov_point_est += np.cov(beta_hat[n_X0[subj]:, :] / np.std(residual, axis=0)) log_fixed_terms[subj] = - (n_T[subj] - n_X0[subj]) \ / 2 * np.log(2 * np.pi) + n_run[subj] \ / 2 * np.log(1 - all_rho_grids**2) \ + scipy.special.gammaln( (n_T[subj] - n_X0[subj] - 2) / 2) \ + (n_T[subj] - n_X0[subj] - 2) / 2 * np.log(2) # These are terms in the log likelihood that do not # depend on L. Notice that the last term comes from # ther term of marginalizing sigma. We take the 2 in # the denominator out. Accordingly, the "denominator" # variable in the _raw_loglike_grids() function is not # divided by 2 cov_point_est = cov_point_est / n_subj current_vec_U_chlsk_l = np.linalg.cholesky( (cov_point_est + np.eye(n_C)) / 2)[l_idx] # We use the average of covariance of point estimation and an identity # matrix as the initial value of the covariance matrix, just in case # the user provides data in which n_V is smaller than n_C. # (2) start from identity matrix # current_vec_U_chlsk_l = np.eye(n_C)[l_idx] # (3) random initialization # current_vec_U_chlsk_l = self.random_state_.randn(n_l) # vectorized version of L, Cholesky factor of U, the shared # covariance matrix of betas across voxels. L = np.zeros((n_C, rank)) L[l_idx] = current_vec_U_chlsk_l X0TAX0 = [None] * n_subj X0TAX0_i = [None] * n_subj XTAcorrX = [None] * n_subj s2XTAcorrX = [None] * n_subj YTAcorrY_diag = [None] * n_subj XTAcorrY = [None] * n_subj sXTAcorrY = [None] * n_subj X0TAY = [None] * n_subj XTAX0 = [None] * n_subj half_log_det_X0TAX0 = [None] * n_subj s_post = [None] * n_subj rho_post = [None] * n_subj sigma_post = [None] * n_subj beta_post = [None] * n_subj beta0_post = [None] * n_subj # The contents below can be updated during fitting. # e.g., X0 will be re-estimated logger.info('start real fitting') LL = np.zeros(n_subj) for it in range(self.n_iter): logger.info('Iteration {}'.format(it)) # Re-estimate part of X0: X_res for subj in range(n_subj): if self.auto_nuisance and it > 0: residuals = Y[subj] - np.dot(X[subj], beta_post[subj]) \ - np.dot( X_base[subj], beta0_post[subj][:np.shape(X_base[subj])[1], :]) X_res[subj] = self.nureg_method( self.n_nureg_[subj]).fit_transform( self.preprocess_residual(residuals)) X0TX0[subj], X0TDX0[subj], X0TFX0[subj], XTX0[subj],\ XTDX0[subj], XTFX0[subj], X0TY[subj], X0TDY[subj], \ X0TFY[subj], X0[subj], X_base[subj], n_X0[subj], _ = \ self._prepare_data_XYX0( X[subj], Y[subj], X_base[subj], X_res[subj], D[subj], F[subj], run_TRs[subj], no_DC=True) X0TAX0[subj], X0TAX0_i[subj], XTAcorrX[subj], XTAcorrY[subj],\ YTAcorrY_diag[subj], X0TAY[subj], XTAX0[subj] \ = self._precompute_ar1_quad_forms_marginalized( XTY[subj], XTDY[subj], XTFY[subj], YTY_diag[subj], YTDY_diag[subj], YTFY_diag[subj], XTX[subj], XTDX[subj], XTFX[subj], X0TX0[subj], X0TDX0[subj], X0TFX0[subj], XTX0[subj], XTDX0[subj], XTFX0[subj], X0TY[subj], X0TDY[subj], X0TFY[subj], rho_grids, n_V[subj], n_X0[subj]) # Now we expand to another dimension including SNR # and collapse the dimension again. half_log_det_X0TAX0[subj], X0TAX0[subj], X0TAX0_i[subj], \ s2XTAcorrX[subj], YTAcorrY_diag[subj], sXTAcorrY[subj], \ X0TAY[subj], XTAX0[subj] = self._matrix_flattened_grid( X0TAX0[subj], X0TAX0_i[subj], SNR_grids, XTAcorrX[subj], YTAcorrY_diag[subj], XTAcorrY[subj], X0TAY[subj], XTAX0[subj], n_C, n_V[subj], n_X0[subj], n_grid) res = scipy.optimize.minimize( self._sum_loglike_marginalized, current_vec_U_chlsk_l + self.random_state_.randn(n_l) * np.linalg.norm(current_vec_U_chlsk_l) / n_l**0.5 * np.exp(-it / self.n_iter * self.anneal_speed - 1), args=(s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, l_idx, n_C, n_T, n_V, n_X0, n_grid, rank), method=self.optimizer, jac=True, tol=self.tol, options=self.minimize_options) param_change = res.x - current_vec_U_chlsk_l current_vec_U_chlsk_l = res.x.copy() # Estimating a few parameters. L[l_idx] = current_vec_U_chlsk_l for subj in range(n_subj): LL_raw, denominator, L_LAMBDA, L_LAMBDA_LT = \ self._raw_loglike_grids( L, s2XTAcorrX[subj], YTAcorrY_diag[subj], sXTAcorrY[subj], half_log_det_X0TAX0[subj], log_weights, log_fixed_terms[subj], n_C, n_T[subj], n_V[subj], n_X0[subj], n_grid, rank) result_sum, max_value, result_exp = utils.sumexp_stable(LL_raw) LL[subj] = np.sum(np.log(result_sum) + max_value) weight_post = result_exp / result_sum s_post[subj] = np.sum(all_SNR_grids[:, None] * weight_post, axis=0) # Mean-posterior estimate of SNR. rho_post[subj] = np.sum(all_rho_grids[:, None] * weight_post, axis=0) # Mean-posterior estimate of rho. sigma_means = denominator ** 0.5 \ * (np.exp(scipy.special.gammaln( (n_T[subj] - n_X0[subj] - 3) / 2) - scipy.special.gammaln( (n_T[subj] - n_X0[subj] - 2) / 2)) / 2**0.5) sigma_post[subj] = np.sum(sigma_means * weight_post, axis=0) # The mean of inverse-Gamma distribution is beta/(alpha-1) # The mode is beta/(alpha+1). Notice that beta here does not # refer to the brain activation, but the scale parameter of # inverse-Gamma distribution. In the _UV version, we use the # maximum likelihood estimate of sigma^2. So we divide by # (alpha+1), which is (n_T - n_X0). beta_post[subj] = np.zeros((n_C, n_V[subj])) beta0_post[subj] = np.zeros((n_X0[subj], n_V[subj])) for grid in range(n_grid): beta_post[subj] += np.dot(L_LAMBDA_LT[grid, :, :], sXTAcorrY[subj][grid, :, :])\ * all_SNR_grids[grid] \ * weight_post[grid, :] beta0_post[subj] += weight_post[grid, :] * np.dot( X0TAX0_i[subj][grid, :, :], (X0TAY[subj][grid, :, :] - np.dot(np.dot(XTAX0[subj][grid, :, :].T, L_LAMBDA_LT[grid, :, :]), sXTAcorrY[subj][grid, :, :]) * all_SNR_grids[grid])) if np.max(np.abs(param_change)) < self.tol: logger.info('The change of parameters is smaller than ' 'the tolerance value {}. Fitting is finished ' 'after {} iterations'.format(self.tol, it + 1)) break for subj in range(n_subj): if idx_DC[subj].size > 1: collapsed_DC = np.sum(X0[subj][:, idx_DC[subj]], axis=1) X0[subj] = np.insert(np.delete(X0[subj], idx_DC[subj], axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(beta0_post[subj][idx_DC[subj], :], axis=0) beta0_post[subj] = np.insert( np.delete(beta0_post[subj], idx_DC[subj], axis=0), 0, collapsed_beta0, axis=0) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) return np.dot(L, L.T), L, s_post, \ beta_post, beta0_post, sigma_post, \ rho_post, X0, LL def _fit_RSA_marginalized_null(self, Y, X_base, scan_onsets): """ The marginalized version of the null model for Bayesian RSA. The null model assumes no task-related response to the design matrix. Note that there is a naming change of variable. X in fit() is changed to Y here. This is because we follow the tradition that Y corresponds to data. However, in wrapper function fit(), we follow the naming routine of scikit-learn. """ # Because there is nothing to learn that is shared across # participants, we can run each subject in serial. # The only fitting required is to re-estimate X0 after # each iteration n_subj = len(Y) t_start = time.time() logger.info('Starting to fit the model. Maximum iteration: ' '{}.'.format(self.n_iter)) rho_grids, rho_weights = self._set_rho_grids() logger.info('The grids of rho used to do numerical integration ' 'is {}.'.format(rho_grids)) n_grid = self.rho_bins log_weights = np.log(rho_weights) rho_post = [None] * n_subj sigma_post = [None] * n_subj beta0_post = [None] * n_subj X0 = [None] * n_subj LL_null = np.zeros(n_subj) for subj in range(n_subj): logger.debug('Running on subject {}.'.format(subj)) [n_T, n_V] = np.shape(Y[subj]) D, F, run_TRs, n_run = self._prepare_DF( n_T, scan_onsets=scan_onsets[subj]) YTY_diag = np.sum(Y[subj] * Y[subj], axis=0) YTDY_diag = np.sum(Y[subj] * np.dot(D, Y[subj]), axis=0) YTFY_diag = np.sum(Y[subj] * np.dot(F, Y[subj]), axis=0) # Add DC components capturing run-specific baselines. X_DC = self._gen_X_DC(run_TRs) X_DC, X_base[subj], idx_DC = self._merge_DC_to_base( X_DC, X_base[subj], no_DC=False) X_res = np.empty((n_T, 0)) for it in range(0, self.n_iter): X0[subj] = np.concatenate( (X_base[subj], X_res), axis=1) n_X0 = X0[subj].shape[1] X0TX0, X0TDX0, X0TFX0 = self._make_templates( D, F, X0[subj], X0[subj]) X0TY, X0TDY, X0TFY = self._make_templates( D, F, X0[subj], Y[subj]) YTAY_diag = YTY_diag - rho_grids[:, None] * YTDY_diag \ + rho_grids[:, None]**2 * YTFY_diag # dimension: #rho*space, # A/sigma2 is the inverse of noise covariance matrix. # YTAY means Y'AY X0TAX0 = X0TX0[None, :, :] \ - rho_grids[:, None, None] \ * X0TDX0[None, :, :] \ + rho_grids[:, None, None]**2 \ * X0TFX0[None, :, :] # dimension: #rho*#baseline*#baseline X0TAY = X0TY - rho_grids[:, None, None] * X0TDY \ + rho_grids[:, None, None]**2 * X0TFY # dimension: #rho*#baseline*space X0TAX0_i = np.linalg.solve( X0TAX0, np.identity(n_X0)[None, :, :]) # dimension: #rho*#baseline*#baseline YTAcorrY_diag = np.empty(np.shape(YTAY_diag)) for i_r in range(np.size(rho_grids)): YTAcorrY_diag[i_r, :] = YTAY_diag[i_r, :] \ - np.sum(X0TAY[i_r, :, :] * np.dot( X0TAX0_i[i_r, :, :], X0TAY[i_r, :, :]), axis=0) log_fixed_terms = - (n_T - n_X0) / 2 * np.log(2 * np.pi)\ + n_run / 2 * np.log(1 - rho_grids**2) \ + scipy.special.gammaln((n_T - n_X0 - 2) / 2) \ + (n_T - n_X0 - 2) / 2 * np.log(2) # These are terms in the log likelihood that do not # depend on L. Notice that the last term comes from # ther term of marginalizing sigma. We take the 2 in # the denominator out. Accordingly, the "denominator" # variable in the _raw_loglike_grids() function is not # divided by 2 half_log_det_X0TAX0 = self._half_log_det(X0TAX0) LL_raw = -half_log_det_X0TAX0[:, None] \ - (n_T - n_X0 - 2) / 2 * np.log(YTAcorrY_diag) \ + log_weights[:, None] + log_fixed_terms[:, None] # dimension: n_grid * space # The log likelihood at each pair of values of rho1. # half_log_det_X0TAX0 is 0.5*log(det(X0TAX0)) with the size of # number of parameter grids. So is the size of log_weights result_sum, max_value, result_exp = utils.sumexp_stable(LL_raw) weight_post = result_exp / result_sum rho_post[subj] = np.sum(rho_grids[:, None] * weight_post, axis=0) # Mean-posterior estimate of rho. sigma_means = YTAcorrY_diag ** 0.5 \ * (np.exp(scipy.special.gammaln((n_T - n_X0 - 3) / 2) - scipy.special.gammaln((n_T - n_X0 - 2) / 2)) / 2**0.5) sigma_post[subj] = np.sum(sigma_means * weight_post, axis=0) beta0_post[subj] = np.zeros((n_X0, n_V)) for grid in range(n_grid): beta0_post[subj] += weight_post[grid, :] * np.dot( X0TAX0_i[grid, :, :], X0TAY[grid, :, :]) if self.auto_nuisance: residuals = Y[subj] - np.dot( X_base[subj], beta0_post[subj][:np.size(X_base[subj], 1), :]) X_res_new = self.nureg_method( self.n_nureg_[subj]).fit_transform( self.preprocess_residual(residuals)) if it >= 1: if np.max(np.abs(X_res_new - X_res)) <= self.tol: logger.info('The change of X_res is ' 'smaller than the tolerance value {}.' 'Fitting is finished after {} ' 'iterations'.format(self.tol, it + 1)) break X_res = X_res_new if idx_DC.size > 1: collapsed_DC = np.sum(X0[subj][:, idx_DC], axis=1) X0[subj] = np.insert(np.delete(X0[subj], idx_DC, axis=1), 0, collapsed_DC, axis=1) collapsed_beta0 = np.mean(beta0_post[subj][idx_DC, :], axis=0) beta0_post[subj] = np.insert( np.delete(beta0_post[subj], idx_DC, axis=0), 0, collapsed_beta0, axis=0) LL_null[subj] = np.sum(np.log(result_sum) + max_value) t_finish = time.time() logger.info( 'total time of fitting: {} seconds'.format(t_finish - t_start)) return beta0_post, sigma_post, rho_post, X0, LL_null def _raw_loglike_grids(self, L, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, n_C, n_T, n_V, n_X0, n_grid, rank): # LAMBDA_i = np.dot(np.einsum('ijk,jl->ilk', s2XTAcorrX, L), L) \ # + np.identity(rank) LAMBDA_i = np.empty((n_grid, rank, rank)) for grid in np.arange(n_grid): LAMBDA_i[grid, :, :] = np.dot(np.dot(L.T, s2XTAcorrX[grid, :, :]), L) LAMBDA_i += np.identity(rank) # dimension: n_grid * rank * rank Chol_LAMBDA_i = np.linalg.cholesky(LAMBDA_i) # dimension: n_grid * rank * rank half_log_det_LAMBDA_i = np.sum( np.log(np.abs(np.diagonal(Chol_LAMBDA_i, axis1=1, axis2=2))), axis=1) # dimension: n_grid L_LAMBDA = np.empty((n_grid, n_C, rank)) L_LAMBDA_LT = np.empty((n_grid, n_C, n_C)) s2YTAcorrXL_LAMBDA_LTXTAcorrY = np.empty((n_grid, n_V)) # dimension: space * n_grid for grid in np.arange(n_grid): L_LAMBDA[grid, :, :] = scipy.linalg.cho_solve( (Chol_LAMBDA_i[grid, :, :], True), L.T).T L_LAMBDA_LT[grid, :, :] = np.dot(L_LAMBDA[grid, :, :], L.T) s2YTAcorrXL_LAMBDA_LTXTAcorrY[grid, :] = np.sum( sXTAcorrY[grid, :, :] * np.dot(L_LAMBDA_LT[grid, :, :], sXTAcorrY[grid, :, :]), axis=0) denominator = (YTAcorrY_diag - s2YTAcorrXL_LAMBDA_LTXTAcorrY) # dimension: n_grid * space # Not necessary the best name for it. But this term appears # as the denominator within the gradient wrt L # In the equation of the log likelihood, this "denominator" # term is in fact divided by 2. But we absorb that into the # log fixted term. LL_raw = -half_log_det_X0TAX0[:, None] \ - half_log_det_LAMBDA_i[:, None] \ - (n_T - n_X0 - 2) / 2 * np.log(denominator) \ + log_weights[:, None] + log_fixed_terms[:, None] # dimension: n_grid * space # The log likelihood at each pair of values of SNR and rho1. # half_log_det_X0TAX0 is 0.5*log(det(X0TAX0)) with the size of # number of parameter grids. So is the size of log_weights return LL_raw, denominator, L_LAMBDA, L_LAMBDA_LT def _sum_loglike_marginalized(self, L_vec, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, l_idx, n_C, n_T, n_V, n_X0, n_grid, rank=None): sum_LL_total = 0 sum_grad_L = np.zeros(np.size(l_idx[0])) for subj in range(len(YTAcorrY_diag)): LL_total, grad_L = self._loglike_marginalized( L_vec, s2XTAcorrX[subj], YTAcorrY_diag[subj], sXTAcorrY[subj], half_log_det_X0TAX0[subj], log_weights, log_fixed_terms[subj], l_idx, n_C, n_T[subj], n_V[subj], n_X0[subj], n_grid, rank) sum_LL_total += LL_total sum_grad_L += grad_L return sum_LL_total, sum_grad_L def _loglike_marginalized(self, L_vec, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, l_idx, n_C, n_T, n_V, n_X0, n_grid, rank=None): # In this version, we assume that beta is independent # between voxels and noise is also independent. X0 captures the # co-flucturation between voxels that is # not captured by design matrix X. # marginalized version marginalize sigma^2, s and rho1 # for all voxels. n_grid is the number of grid on which the numeric # integration is performed to marginalize s and rho1 for each voxel. # The log likelihood is an inverse-Gamma distribution sigma^2, # so we can analytically marginalize it assuming uniform prior. # n_grid is the number of grid in the parameter space of (s, rho1) # that is used for numerical integration over (s, rho1). n_l = np.size(l_idx[0]) # the number of parameters in the index of lower-triangular matrix if rank is None: rank = int((2 * n_C + 1 - np.sqrt(n_C**2 * 4 + n_C * 4 + 1 - 8 * n_l)) / 2) L = np.zeros([n_C, rank]) L[l_idx] = L_vec LL_raw, denominator, L_LAMBDA, _ = self._raw_loglike_grids( L, s2XTAcorrX, YTAcorrY_diag, sXTAcorrY, half_log_det_X0TAX0, log_weights, log_fixed_terms, n_C, n_T, n_V, n_X0, n_grid, rank) result_sum, max_value, result_exp = utils.sumexp_stable(LL_raw) LL_total = np.sum(np.log(result_sum) + max_value) # Now we start the gradient with respect to L # s2XTAcorrXL_LAMBDA = np.einsum('ijk,ikl->ijl', # s2XTAcorrX, L_LAMBDA) s2XTAcorrXL_LAMBDA = np.empty((n_grid, n_C, rank)) for grid in range(n_grid): s2XTAcorrXL_LAMBDA[grid, :, :] = np.dot(s2XTAcorrX[grid, :, :], L_LAMBDA[grid, :, :]) # dimension: n_grid * condition * rank I_minus_s2XTAcorrXL_LAMBDA_LT = np.identity(n_C) \ - np.dot(s2XTAcorrXL_LAMBDA, L.T) # dimension: n_grid * condition * condition # The step above may be calculated by einsum. Not sure # which is faster. weight_grad = result_exp / result_sum weight_grad_over_denominator = weight_grad / denominator # dimension: n_grid * space weighted_sXTAcorrY = sXTAcorrY \ * weight_grad_over_denominator[:, None, :] # dimension: n_grid * condition * space # sYTAcorrXL_LAMBDA = np.einsum('ijk,ijl->ikl', sXTAcorrY, L_LAMBDA) # dimension: n_grid * space * rank grad_L = np.zeros([n_C, rank]) for grid in range(n_grid): grad_L += np.dot( np.dot(I_minus_s2XTAcorrXL_LAMBDA_LT[grid, :, :], sXTAcorrY[grid, :, :]), np.dot(weighted_sXTAcorrY[grid, :, :].T, L_LAMBDA[grid, :, :])) * (n_T - n_X0 - 2) grad_L -= np.sum(s2XTAcorrXL_LAMBDA * np.sum(weight_grad, axis=1)[:, None, None], axis=0) # dimension: condition * rank return -LL_total, -grad_L[l_idx] def _check_data_GBRSA(self, X, for_fit=True): # Check input data if type(X) is np.ndarray: X = [X] assert type(X) is list, 'Input data X must be either a list '\ 'with each entry for one participant, or a numpy arrary '\ 'for single participant.' if for_fit: for i, x in enumerate(X): assert_all_finite(x) assert x.ndim == 2, 'Each participants'' data should be ' \ '2 dimension ndarray' assert np.all(np.std(x, axis=0) > 0),\ 'The time courses of some voxels in participant {} '\ 'do not change at all. Please make sure all voxels '\ 'are within the brain'.format(i) else: for i, x in enumerate(X): if x is not None: assert x.ndim == 2, 'Each participants'' data should be ' \ '2 dimension ndarray' assert x.shape[1] == self.n_V_[i], 'Number of voxels '\ 'does not match that in the data used for fitting: '\ 'subject {}'.format(i) # This program allows to fit a single subject. But to have a consistent # data structure, we make sure X and design are both lists. return X def _check_design_GBRSA(self, design, X): # check design matrix if type(design) is np.ndarray: design = [design] * len(X) if len(X) > 1: logger.warning('There are multiple subjects while ' 'there is only one design matrix. ' 'I assume that the design matrix ' 'is shared across all subjects.') assert type(design) is list, 'design matrix must be either a list '\ 'with each entry for one participant, or an numpy arrary '\ 'for single participant.' for i, d in enumerate(design): if X[i] is not None: assert_all_finite(d) assert d.ndim == 2,\ 'The design matrix should be 2 dimension ndarray' assert np.linalg.matrix_rank(d) == d.shape[1], \ 'Your design matrix of subject {} has rank ' \ 'smaller than the number of columns. Some columns '\ 'can be explained by linear combination of other columns.'\ 'Please check your design matrix.'.format(i) assert np.size(d, axis=0) == np.size(X[i], axis=0),\ 'Design matrix and data of subject {} do not '\ 'have the same number of time points.'.format(i) assert self.rank is None or self.rank <= d.shape[1],\ 'Your design matrix of subject {} '\ 'has fewer columns than the rank you set'.format(i) if i == 0: n_C = np.shape(d)[1] else: assert n_C == np.shape(d)[1], \ 'In Group Bayesian RSA, all subjects should have'\ ' the same set of experiment conditions, t'\ 'hus the same number of columns in design matrix' if X[i].shape[1] <= d.shape[1]: logger.warning('Your data have fewer voxels than the ' 'number of task conditions. This might ' 'cause problem in fitting. Please consider ' 'increasing the size of your ROI, or set ' 'the rank parameter to a lower number to ' 'estimate a low-rank representational ' 'structure.') return design def _check_nuisance_GBRSA(sef, nuisance, X): # Check the nuisance regressors. if nuisance is not None: if type(nuisance) is np.ndarray: nuisance = [nuisance] * len(X) if len(X) > 1: logger.warning('ATTENTION! There are multiple subjects ' 'while there is only one nuisance matrix. ' 'I assume that the nuisance matrix ' 'is shared across all subjects. ' 'Please double check.') assert type(nuisance) is list, \ 'nuisance matrix must be either a list '\ 'with each entry for one participant, or an numpy arrary '\ 'for single participant.' for i, n in enumerate(nuisance): assert_all_finite(n) if n is not None: assert n.ndim == 2,\ 'The nuisance regressor should be '\ '2 dimension ndarray or None' assert np.linalg.matrix_rank(n) == n.shape[1], \ 'The nuisance regressor of subject {} has rank '\ 'smaller than the number of columns.'\ 'Some columns can be explained by linear '\ 'combination of other columns. Please check your' \ ' nuisance regressors.'.format(i) assert np.size(n, axis=0) == np.size(X[i], axis=0), \ 'Nuisance regressor and data do not have the same '\ 'number of time points.' else: nuisance = [None] * len(X) logger.info('None was provided for nuisance matrix. Replicating ' 'it for all subjects.') return nuisance def _check_scan_onsets_GBRSA(self, scan_onsets, X): # check scan_onsets validity if scan_onsets is None or type(scan_onsets) is np.ndarray: if scan_onsets is None: scan_onsets = np.array([0], dtype=int) scan_onsets = [scan_onsets] * len(X) if len(X) > 1: logger.warning('There are multiple subjects while ' 'there is only one set of scan_onsets. ' 'I assume that it is the same for all' ' subjects. Please double check') for i in np.arange(len(scan_onsets)): if X[i] is not None: if scan_onsets[i] is None: scan_onsets[i] = np.array([0], dtype=int) logger.warning('No scan onsets were provided for subject' ' {}. Treating all data of this subject as' ' coming from the same run.') else: scan_onsets[i] = np.int32(scan_onsets[i]) assert (np.max(scan_onsets[i]) <= X[i].shape[0] and np.min(scan_onsets[i]) >= 0 and 0 in scan_onsets[i] and scan_onsets[i].ndim == 1), \ 'Scan onsets of subject {} has formatting ' \ 'issues: {}'.format(i, scan_onsets[i]) return scan_onsets def _bin_exp(self, n_bin, scale=1.0): """ Calculate the bin locations to approximate exponential distribution. It breaks the cumulative probability of exponential distribution into n_bin equal bins, each covering 1 / n_bin probability. Then it calculates the center of mass in each bins and returns the centers of mass. So, it approximates the exponential distribution with n_bin of Delta function weighted by 1 / n_bin, at the locations of these centers of mass. Parameters: ----------- n_bin: int The number of bins to approximate the exponential distribution scale: float. The scale parameter of the exponential distribution, defined in the same way as scipy.stats. It does not influence the ratios between the bins, but just controls the spacing between the bins. So generally users should not change its default. Returns: -------- bins: numpy array of size [n_bin,] The centers of mass for each segment of the exponential distribution. """ boundaries = np.flip(scipy.stats.expon.isf( np.linspace(0, 1, n_bin + 1), scale=scale), axis=0) bins = np.empty(n_bin) for i in np.arange(n_bin): bins[i] = utils.center_mass_exp( (boundaries[i], boundaries[i + 1]), scale=scale) return bins def _set_SNR_grids(self): """ Set the grids and weights for SNR used in numerical integration of SNR parameters. """ if self.SNR_prior == 'unif': SNR_grids = np.linspace(0, 1, self.SNR_bins) SNR_weights = np.ones(self.SNR_bins) / (self.SNR_bins - 1) SNR_weights[0] = SNR_weights[0] / 2.0 SNR_weights[-1] = SNR_weights[-1] / 2.0 elif self.SNR_prior == 'lognorm': dist = scipy.stats.lognorm alphas = np.arange(np.mod(self.SNR_bins, 2), self.SNR_bins + 2, 2) / self.SNR_bins # The goal here is to divide the area under the pdf curve # to segments representing equal probabilities. bounds = dist.interval(alphas, (self.logS_range,)) bounds = np.unique(bounds) # bounds contain the boundaries which equally separate # the probability mass of the distribution SNR_grids = np.zeros(self.SNR_bins) for i in np.arange(self.SNR_bins): SNR_grids[i] = dist.expect( lambda x: x, args=(self.logS_range,), lb=bounds[i], ub=bounds[i + 1]) * self.SNR_bins # Center of mass of each segment between consecutive # bounds are set as the grids for SNR. SNR_weights = np.ones(self.SNR_bins) / self.SNR_bins elif self.SNR_prior == 'exp': SNR_grids = self._bin_exp(self.SNR_bins) SNR_weights = np.ones(self.SNR_bins) / self.SNR_bins else: SNR_grids = np.ones(1) SNR_weights = np.ones(1) SNR_weights = SNR_weights / np.sum(SNR_weights) return SNR_grids, SNR_weights def _set_rho_grids(self): """ Set the grids and weights for rho used in numerical integration of AR(1) parameters. """ rho_grids = np.arange(self.rho_bins) * 2 / self.rho_bins - 1 \ + 1 / self.rho_bins rho_weights = np.ones(self.rho_bins) / self.rho_bins return rho_grids, rho_weights def _matrix_flattened_grid(self, X0TAX0, X0TAX0_i, SNR_grids, XTAcorrX, YTAcorrY_diag, XTAcorrY, X0TAY, XTAX0, n_C, n_V, n_X0, n_grid): """ We need to integrate parameters SNR and rho on 2-d discrete grids. This function generates matrices which have only one dimension for these two parameters, with each slice in that dimension corresponding to each combination of the discrete grids of SNR and discrete grids of rho. """ half_log_det_X0TAX0 = np.reshape( np.repeat(self._half_log_det(X0TAX0)[None, :], self.SNR_bins, axis=0), n_grid) X0TAX0 = np.reshape( np.repeat(X0TAX0[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_X0, n_X0)) X0TAX0_i = np.reshape(np.repeat( X0TAX0_i[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_X0, n_X0)) s2XTAcorrX = np.reshape( SNR_grids[:, None, None, None]**2 * XTAcorrX, (n_grid, n_C, n_C)) YTAcorrY_diag = np.reshape(np.repeat( YTAcorrY_diag[None, :, :], self.SNR_bins, axis=0), (n_grid, n_V)) sXTAcorrY = np.reshape(SNR_grids[:, None, None, None] * XTAcorrY, (n_grid, n_C, n_V)) X0TAY = np.reshape(np.repeat(X0TAY[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_X0, n_V)) XTAX0 = np.reshape(np.repeat(XTAX0[None, :, :, :], self.SNR_bins, axis=0), (n_grid, n_C, n_X0)) return half_log_det_X0TAX0, X0TAX0, X0TAX0_i, s2XTAcorrX, \ YTAcorrY_diag, sXTAcorrY, X0TAY, XTAX0

lcnature/brainiak

brainiak/reprsimil/brsa.py

Python

apache-2.0

211,992

[ "Gaussian" ]

cd84a148f8270fb7a16c3150d7e0990c60922e2e55f0e7b09b4275ecb5b0bf42

class Display: def visit(self, state_machine): states = state_machine.states for state in states.values(): print "state: ", state.name for transition in state.transitions_out.values(): print " transition: ", transition.name, " attributes: ", for attribute_or_group in transition.attributes: print attribute_or_group.name, print

bwtaylor/statemach

visitors/display.py

Python

apache-2.0

392

[ "VisIt" ]

3890a196fc331e38d203619589ea33107eb5ae415f5eb88769a9189946aa9104

# $Id$ # # Copyright (C) 2003 Rational Discovery LLC # All Rights Reserved # from rdkit import six from rdkit.VLib.Node import VLibNode class SupplyNode(VLibNode): """ base class for nodes which supply things Assumptions: 1) no parents Usage Example: >>> supplier = SupplyNode(contents=[1,2,3]) >>> supplier.next() 1 >>> supplier.next() 2 >>> supplier.next() 3 >>> supplier.next() Traceback (most recent call last): ... StopIteration >>> supplier.reset() >>> supplier.next() 1 >>> [x for x in supplier] [1, 2, 3] """ def __init__(self, contents=None, **kwargs): VLibNode.__init__(self, **kwargs) if contents is not None: self._contents = contents else: self._contents = [] self._pos = 0 def reset(self): VLibNode.reset(self) self._pos = 0 def next(self): if self._pos == len(self._contents): raise StopIteration res = self._contents[self._pos] self._pos += 1 return res def AddParent(self, parent, notify=1): raise ValueError('SupplyNodes do not have parents') if six.PY3: SupplyNode.__next__ = SupplyNode.next # ------------------------------------ # # doctest boilerplate # def _runDoctests(verbose=None): # pragma: nocover import sys import doctest failed, _ = doctest.testmod(optionflags=doctest.ELLIPSIS, verbose=verbose) sys.exit(failed) if __name__ == '__main__': # pragma: nocover _runDoctests()

rvianello/rdkit

rdkit/VLib/Supply.py

Python

bsd-3-clause

1,492

[ "RDKit" ]

23af8f1b73244f7ed97781cf1ba0d7f295dd09e7355e900042556e92d6cb4d16

import os import sys import time import socket import inspect import traceback import pickle import uuid from GangaCore.Runtime.GPIexport import exportToGPI from GangaCore.GPIDev.Base.Proxy import addProxy, stripProxy from GangaCore.Utility.Config import getConfig from GangaCore.Utility.logging import getLogger #from GangaCore.Core.GangaThread.WorkerThreads.WorkerThreadPool import WorkerThreadPool #from GangaCore.Core.GangaThread.WorkerThreads.ThreadPoolQueueMonitor import ThreadPoolQueueMonitor from GangaDirac.Lib.Utilities.DiracUtilities import execute logger = getLogger() #user_threadpool = WorkerThreadPool() #monitoring_threadpool = WorkerThreadPool() #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def diracAPI(cmd, timeout=60, cred_req=None): ''' Args: cmd (str): This is the command you want to execute from within an active DIRAC session timeout (int): This is the maximum time(sec) the session has to complete the task cred_req (ICredentialRequirement): This is the (optional) credential passed to construct the correct DIRAC env Execute DIRAC API commands from w/in GangaCore. The stdout will be returned, e.g.: # this will simply return 87 diracAPI(\'print 87\') # this will return the status of job 66 # note a Dirac() object is already provided set up as \'dirac\' diracAPI(\'print(Dirac().getJobStatus([66]))\') diracAPI(\'print(dirac.getJobStatus([66]))\') # or can achieve the same using command defined and included from # getConfig('DIRAC')['DiracCommandFiles'] diracAPI(\'status([66])\') ''' return execute(cmd, timeout=timeout, cred_req=cred_req) exportToGPI('diracAPI', diracAPI, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# running_dirac_process = False dirac_process = None dirac_process_ids = None def startDiracProcess(): ''' Start a subprocess that runs the DIRAC commands ''' HOST = 'localhost' #Connect to localhost end_trans = '###END-TRANS###' import subprocess from GangaDirac.Lib.Utilities.DiracUtilities import getDiracEnv, getDiracCommandIncludes, GangaDiracError global dirac_process #Some magic to locate the python script to run from GangaDirac.Lib.Server.InspectionClient import runClient #Create a socket and bind it to 0 to find a free port s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) s.bind((HOST, 0)) PORT = s.getsockname()[1] s.close() #Pass the port no as an argument to the popen serverpath = os.path.join(os.path.dirname(inspect.getsourcefile(runClient)), 'DiracProcess.py') popen_cmd = ['python',serverpath, str(PORT)] dirac_process = subprocess.Popen(popen_cmd, env = getDiracEnv(), stdin=subprocess.PIPE) global running_dirac_process running_dirac_process = (dirac_process.pid, PORT) #Now set a random string to make sure only commands from this sessions are executed rand_hash = uuid.uuid4() global dirac_process_ids dirac_process_ids = (dirac_process.pid, PORT, rand_hash) #Pipe the random string without waiting for the process to finish. dirac_process.stdin.write(str(rand_hash).encode("utf-8")) dirac_process.stdin.close() data = '' #We have to wait a little bit for the subprocess to start the server so we try until the connection stops being refused. Set a limit of one minute. connection_timeout = time.time() + 60 started = False s = socket.socket(socket.AF_INET, socket.SOCK_STREAM) while time.time()<connection_timeout and not started: try: s.connect((HOST, PORT)) started = True except socket.error as serr: time.sleep(1) if not started: raise GangaDiracError("Failed to start the Dirac server process!") #Now setup the Dirac environment in the subprocess dirac_command = str(rand_hash) dirac_command = dirac_command + getDiracCommandIncludes() dirac_command = dirac_command + end_trans s.sendall(dirac_command.encode("utf-8")) data = s.recv(1024) s.close() exportToGPI('startDiracProcess', startDiracProcess, 'Functions') def stopDiracProcess(): ''' Stop the Dirac process if it is running ''' global running_dirac_process if running_dirac_process: logger.info('Stopping the DIRAC process') dirac_process.kill() running_dirac_process = False exportToGPI('stopDiracProcess', stopDiracProcess, 'Functions') def diracAPI_interactive(connection_attempts=5): ''' Run an interactive server within the DIRAC environment. ''' from GangaDirac.Lib.Server.InspectionClient import runClient serverpath = os.path.join(os.path.dirname(inspect.getsourcefile(runClient)), 'InspectionServer.py') from GangaCore.Core.GangaThread.WorkerThreads import getQueues getQueues().add(execute("execfile('%s')" % serverpath, timeout=None, shell=False)) #time.sleep(1) sys.stdout.write( "\nType 'q' or 'Q' or 'exit' or 'exit()' to quit but NOT ctrl-D") i = 0 excpt = None while i < connection_attempts: try: runClient() break except: if i == (connection_attempts - 1): excpt = traceback.format_exc() finally: i += 1 return excpt exportToGPI('diracAPI_interactive', diracAPI_interactive, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def diracAPI_async(cmd, timeout=120): ''' Execute DIRAC API commands from w/in GangaCore. ''' from GangaCore.Core.GangaThread.WorkerThreads import getQueues return getQueues().add(execute(cmd, timeout=timeout)) exportToGPI('diracAPI_async', diracAPI_async, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def getDiracFiles(): from GangaDirac.Lib.Files.DiracFile import DiracFile from GangaCore.GPIDev.Lib.GangaList.GangaList import GangaList filename = DiracFile.diracLFNBase().replace('/', '-') + '.lfns' logger.info('Creating list, this can take a while if you have a large number of SE files, please wait...') execute('dirac-dms-user-lfns &> /dev/null', shell=True, timeout=None) g = GangaList() with open(filename[1:], 'r') as lfnlist: lfnlist.seek(0) g.extend((DiracFile(lfn='%s' % lfn.strip()) for lfn in lfnlist.readlines())) return addProxy(g) exportToGPI('getDiracFiles', getDiracFiles, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/# def dumpObject(object, filename): ''' These are complimentary functions to export/load which are already exported to the GPI from GangaCore.GPIDev.Persistency. The difference being that these functions will export the objects using the pickle persistency format rather than a Ganga streaming (human readable) format. ''' try: with open(os.path.expandvars(os.path.expanduser(filename)), 'wb') as f: pickle.dump(stripProxy(object), f) except: logger.error("Problem when dumping file '%s': %s" % (filename, traceback.format_exc())) exportToGPI('dumpObject', dumpObject, 'Functions') def loadObject(filename): ''' These are complimentary functions to export/load which are already exported to the GPI from GangaCore.GPIDev.Persistency. The difference being that these functions will export the objects using the pickle persistency format rather than a Ganga streaming (human readable) format. ''' try: with open(os.path.expandvars(os.path.expanduser(filename)), 'rb') as f: r = pickle.load(f) except: logger.error("Problem when loading file '%s': %s" % (filename, traceback.format_exc())) else: return addProxy(r) exportToGPI('loadObject', loadObject, 'Functions') #\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/\/#

ganga-devs/ganga

ganga/GangaDirac/BOOT.py

Python

gpl-3.0

7,982

[ "DIRAC" ]

1fdbc43fc2a4acec244fdc965c9779737728eb093d37a84b3d9ef6e741e02be0

""" NetCDF reader/writer module. This module is used to read and create NetCDF files. NetCDF files are accessed through the `netcdf_file` object. Data written to and from NetCDF files are contained in `netcdf_variable` objects. Attributes are given as member variables of the `netcdf_file` and `netcdf_variable` objects. Notes ----- NetCDF files are a self-describing binary data format. The file contains metadata that describes the dimensions and variables in the file. More details about NetCDF files can be found `here <http://www.unidata.ucar.edu/software/netcdf/docs/netcdf.html>`_. There are three main sections to a NetCDF data structure: 1. Dimensions 2. Variables 3. Attributes The dimensions section records the name and length of each dimension used by the variables. The variables would then indicate which dimensions it uses and any attributes such as data units, along with containing the data values for the variable. It is good practice to include a variable that is the same name as a dimension to provide the values for that axes. Lastly, the attributes section would contain additional information such as the name of the file creator or the instrument used to collect the data. When writing data to a NetCDF file, there is often the need to indicate the 'record dimension'. A record dimension is the unbounded dimension for a variable. For example, a temperature variable may have dimensions of latitude, longitude and time. If one wants to add more temperature data to the NetCDF file as time progresses, then the temperature variable should have the time dimension flagged as the record dimension. This module implements the Scientific.IO.NetCDF API to read and create NetCDF files. The same API is also used in the PyNIO and pynetcdf modules, allowing these modules to be used interchangeably when working with NetCDF files. The major advantage of this module over other modules is that it doesn't require the code to be linked to the NetCDF libraries. In addition, the NetCDF file header contains the position of the data in the file, so access can be done in an efficient manner without loading unnecessary data into memory. It uses the ``mmap`` module to create Numpy arrays mapped to the data on disk, for the same purpose. Examples -------- To create a NetCDF file: >>> from scipy.io import netcdf >>> f = netcdf.netcdf_file('simple.nc', 'w') >>> f.history = 'Created for a test' >>> f.createDimension('time', 10) >>> time = f.createVariable('time', 'i', ('time',)) >>> time[:] = range(10) >>> time.units = 'days since 2008-01-01' >>> f.close() Note the assignment of ``range(10)`` to ``time[:]``. Exposing the slice of the time variable allows for the data to be set in the object, rather than letting ``range(10)`` overwrite the ``time`` variable. To read the NetCDF file we just created: >>> from scipy.io import netcdf >>> f = netcdf.netcdf_file('simple.nc', 'r') >>> print f.history Created for a test >>> time = f.variables['time'] >>> print time.units days since 2008-01-01 >>> print time.shape (10,) >>> print time[-1] 9 >>> f.close() """ #TODO: # * properly implement ``_FillValue``. # * implement Jeff Whitaker's patch for masked variables. # * fix character variables. # * implement PAGESIZE for Python 2.6? #The Scientific.IO.NetCDF API allows attributes to be added directly to #instances of ``netcdf_file`` and ``netcdf_variable``. To differentiate #between user-set attributes and instance attributes, user-set attributes #are automatically stored in the ``_attributes`` attribute by overloading #``__setattr__``. This is the reason why the code sometimes uses #``obj.__dict__['key'] = value``, instead of simply ``obj.key = value``; #otherwise the key would be inserted into userspace attributes. __all__ = ['netcdf_file', 'netcdf_variable'] from operator import mul from mmap import mmap, ACCESS_READ import numpy as np from numpy.compat import asbytes, asstr from numpy import fromstring, ndarray, dtype, empty, array, asarray from numpy import little_endian as LITTLE_ENDIAN ABSENT = asbytes('\x00\x00\x00\x00\x00\x00\x00\x00') ZERO = asbytes('\x00\x00\x00\x00') NC_BYTE = asbytes('\x00\x00\x00\x01') NC_CHAR = asbytes('\x00\x00\x00\x02') NC_SHORT = asbytes('\x00\x00\x00\x03') NC_INT = asbytes('\x00\x00\x00\x04') NC_FLOAT = asbytes('\x00\x00\x00\x05') NC_DOUBLE = asbytes('\x00\x00\x00\x06') NC_DIMENSION = asbytes('\x00\x00\x00\n') NC_VARIABLE = asbytes('\x00\x00\x00\x0b') NC_ATTRIBUTE = asbytes('\x00\x00\x00\x0c') TYPEMAP = { NC_BYTE: ('b', 1), NC_CHAR: ('c', 1), NC_SHORT: ('h', 2), NC_INT: ('i', 4), NC_FLOAT: ('f', 4), NC_DOUBLE: ('d', 8) } REVERSE = { 'b': NC_BYTE, 'c': NC_CHAR, 'h': NC_SHORT, 'i': NC_INT, 'f': NC_FLOAT, 'd': NC_DOUBLE, # these come from asarray(1).dtype.char and asarray('foo').dtype.char, # used when getting the types from generic attributes. 'l': NC_INT, 'S': NC_CHAR } class netcdf_file(object): """ A file object for NetCDF data. A `netcdf_file` object has two standard attributes: `dimensions` and `variables`. The values of both are dictionaries, mapping dimension names to their associated lengths and variable names to variables, respectively. Application programs should never modify these dictionaries. All other attributes correspond to global attributes defined in the NetCDF file. Global file attributes are created by assigning to an attribute of the `netcdf_file` object. Parameters ---------- filename : string or file-like string -> filename mode : {'r', 'w'}, optional read-write mode, default is 'r' mmap : None or bool, optional Whether to mmap `filename` when reading. Default is True when `filename` is a file name, False when `filename` is a file-like object version : {1, 2}, optional version of netcdf to read / write, where 1 means *Classic format* and 2 means *64-bit offset format*. Default is 1. See `here <http://www.unidata.ucar.edu/software/netcdf/docs/netcdf/Which-Format.html>`_ for more info. """ def __init__(self, filename, mode='r', mmap=None, version=1): """Initialize netcdf_file from fileobj (str or file-like).""" if hasattr(filename, 'seek'): # file-like self.fp = filename self.filename = 'None' if mmap is None: mmap = False elif mmap and not hasattr(filename, 'fileno'): raise ValueError('Cannot use file object for mmap') else: # maybe it's a string self.filename = filename self.fp = open(self.filename, '%sb' % mode) if mmap is None: mmap = True self.use_mmap = mmap self.version_byte = version if not mode in 'rw': raise ValueError("Mode must be either 'r' or 'w'.") self.mode = mode self.dimensions = {} self.variables = {} self._dims = [] self._recs = 0 self._recsize = 0 self._attributes = {} if mode == 'r': self._read() def __setattr__(self, attr, value): # Store user defined attributes in a separate dict, # so we can save them to file later. try: self._attributes[attr] = value except AttributeError: pass self.__dict__[attr] = value def close(self): """Closes the NetCDF file.""" if not self.fp.closed: try: self.flush() finally: self.fp.close() __del__ = close def createDimension(self, name, length): """ Adds a dimension to the Dimension section of the NetCDF data structure. Note that this function merely adds a new dimension that the variables can reference. The values for the dimension, if desired, should be added as a variable using `createVariable`, referring to this dimension. Parameters ---------- name : str Name of the dimension (Eg, 'lat' or 'time'). length : int Length of the dimension. See Also -------- createVariable """ self.dimensions[name] = length self._dims.append(name) def createVariable(self, name, type, dimensions): """ Create an empty variable for the `netcdf_file` object, specifying its data type and the dimensions it uses. Parameters ---------- name : str Name of the new variable. type : dtype or str Data type of the variable. dimensions : sequence of str List of the dimension names used by the variable, in the desired order. Returns ------- variable : netcdf_variable The newly created ``netcdf_variable`` object. This object has also been added to the `netcdf_file` object as well. See Also -------- createDimension Notes ----- Any dimensions to be used by the variable should already exist in the NetCDF data structure or should be created by `createDimension` prior to creating the NetCDF variable. """ shape = tuple([self.dimensions[dim] for dim in dimensions]) shape_ = tuple([dim or 0 for dim in shape]) # replace None with 0 for numpy if isinstance(type, basestring): type = dtype(type) typecode, size = type.char, type.itemsize dtype_ = '>%s' % typecode if size > 1: dtype_ += str(size) data = empty(shape_, dtype=dtype_) self.variables[name] = netcdf_variable(data, typecode, shape, dimensions) return self.variables[name] def flush(self): """ Perform a sync-to-disk flush if the `netcdf_file` object is in write mode. See Also -------- sync : Identical function """ if hasattr(self, 'mode') and self.mode is 'w': self._write() sync = flush def _write(self): self.fp.write(asbytes('CDF')) self.fp.write(array(self.version_byte, '>b').tostring()) # Write headers and data. self._write_numrecs() self._write_dim_array() self._write_gatt_array() self._write_var_array() def _write_numrecs(self): # Get highest record count from all record variables. for var in self.variables.values(): if var.isrec and len(var.data) > self._recs: self.__dict__['_recs'] = len(var.data) self._pack_int(self._recs) def _write_dim_array(self): if self.dimensions: self.fp.write(NC_DIMENSION) self._pack_int(len(self.dimensions)) for name in self._dims: self._pack_string(name) length = self.dimensions[name] self._pack_int(length or 0) # replace None with 0 for record dimension else: self.fp.write(ABSENT) def _write_gatt_array(self): self._write_att_array(self._attributes) def _write_att_array(self, attributes): if attributes: self.fp.write(NC_ATTRIBUTE) self._pack_int(len(attributes)) for name, values in attributes.items(): self._pack_string(name) self._write_values(values) else: self.fp.write(ABSENT) def _write_var_array(self): if self.variables: self.fp.write(NC_VARIABLE) self._pack_int(len(self.variables)) # Sort variables non-recs first, then recs. We use a DSU # since some people use pupynere with Python 2.3.x. deco = [ (v._shape and not v.isrec, k) for (k, v) in self.variables.items() ] deco.sort() variables = [ k for (unused, k) in deco ][::-1] # Set the metadata for all variables. for name in variables: self._write_var_metadata(name) # Now that we have the metadata, we know the vsize of # each record variable, so we can calculate recsize. self.__dict__['_recsize'] = sum([ var._vsize for var in self.variables.values() if var.isrec]) # Set the data for all variables. for name in variables: self._write_var_data(name) else: self.fp.write(ABSENT) def _write_var_metadata(self, name): var = self.variables[name] self._pack_string(name) self._pack_int(len(var.dimensions)) for dimname in var.dimensions: dimid = self._dims.index(dimname) self._pack_int(dimid) self._write_att_array(var._attributes) nc_type = REVERSE[var.typecode()] self.fp.write(asbytes(nc_type)) if not var.isrec: vsize = var.data.size * var.data.itemsize vsize += -vsize % 4 else: # record variable try: vsize = var.data[0].size * var.data.itemsize except IndexError: vsize = 0 rec_vars = len([var for var in self.variables.values() if var.isrec]) if rec_vars > 1: vsize += -vsize % 4 self.variables[name].__dict__['_vsize'] = vsize self._pack_int(vsize) # Pack a bogus begin, and set the real value later. self.variables[name].__dict__['_begin'] = self.fp.tell() self._pack_begin(0) def _write_var_data(self, name): var = self.variables[name] # Set begin in file header. the_beguine = self.fp.tell() self.fp.seek(var._begin) self._pack_begin(the_beguine) self.fp.seek(the_beguine) # Write data. if not var.isrec: self.fp.write(var.data.tostring()) count = var.data.size * var.data.itemsize self.fp.write(asbytes('0') * (var._vsize - count)) else: # record variable # Handle rec vars with shape[0] < nrecs. if self._recs > len(var.data): shape = (self._recs,) + var.data.shape[1:] var.data.resize(shape) pos0 = pos = self.fp.tell() for rec in var.data: # Apparently scalars cannot be converted to big endian. If we # try to convert a ``=i4`` scalar to, say, '>i4' the dtype # will remain as ``=i4``. if not rec.shape and (rec.dtype.byteorder == '<' or (rec.dtype.byteorder == '=' and LITTLE_ENDIAN)): rec = rec.byteswap() self.fp.write(rec.tostring()) # Padding count = rec.size * rec.itemsize self.fp.write(asbytes('0') * (var._vsize - count)) pos += self._recsize self.fp.seek(pos) self.fp.seek(pos0 + var._vsize) def _write_values(self, values): if hasattr(values, 'dtype'): nc_type = REVERSE[values.dtype.char] else: types = [ (int, NC_INT), (long, NC_INT), (float, NC_FLOAT), (basestring, NC_CHAR), ] try: sample = values[0] except TypeError: sample = values for class_, nc_type in types: if isinstance(sample, class_): break typecode, size = TYPEMAP[nc_type] if typecode is 'c': dtype_ = '>c' else: dtype_ = '>%s' % typecode if size > 1: dtype_ += str(size) values = asarray(values, dtype=dtype_) self.fp.write(asbytes(nc_type)) if values.dtype.char == 'S': nelems = values.itemsize else: nelems = values.size self._pack_int(nelems) if not values.shape and (values.dtype.byteorder == '<' or (values.dtype.byteorder == '=' and LITTLE_ENDIAN)): values = values.byteswap() self.fp.write(values.tostring()) count = values.size * values.itemsize self.fp.write(asbytes('0') * (-count % 4)) # pad def _read(self): # Check magic bytes and version magic = self.fp.read(3) if not magic == asbytes('CDF'): raise TypeError("Error: %s is not a valid NetCDF 3 file" % self.filename) self.__dict__['version_byte'] = fromstring(self.fp.read(1), '>b')[0] # Read file headers and set data. self._read_numrecs() self._read_dim_array() self._read_gatt_array() self._read_var_array() def _read_numrecs(self): self.__dict__['_recs'] = self._unpack_int() def _read_dim_array(self): header = self.fp.read(4) assert header in [ZERO, NC_DIMENSION] count = self._unpack_int() for dim in range(count): name = asstr(self._unpack_string()) length = self._unpack_int() or None # None for record dimension self.dimensions[name] = length self._dims.append(name) # preserve order def _read_gatt_array(self): for k, v in self._read_att_array().items(): self.__setattr__(k, v) def _read_att_array(self): header = self.fp.read(4) assert header in [ZERO, NC_ATTRIBUTE] count = self._unpack_int() attributes = {} for attr in range(count): name = asstr(self._unpack_string()) attributes[name] = self._read_values() return attributes def _read_var_array(self): header = self.fp.read(4) assert header in [ZERO, NC_VARIABLE] begin = 0 dtypes = {'names': [], 'formats': []} rec_vars = [] count = self._unpack_int() for var in range(count): (name, dimensions, shape, attributes, typecode, size, dtype_, begin_, vsize) = self._read_var() # http://www.unidata.ucar.edu/software/netcdf/docs/netcdf.html # Note that vsize is the product of the dimension lengths # (omitting the record dimension) and the number of bytes # per value (determined from the type), increased to the # next multiple of 4, for each variable. If a record # variable, this is the amount of space per record. The # netCDF "record size" is calculated as the sum of the # vsize's of all the record variables. # # The vsize field is actually redundant, because its value # may be computed from other information in the header. The # 32-bit vsize field is not large enough to contain the size # of variables that require more than 2^32 - 4 bytes, so # 2^32 - 1 is used in the vsize field for such variables. if shape and shape[0] is None: # record variable rec_vars.append(name) # The netCDF "record size" is calculated as the sum of # the vsize's of all the record variables. self.__dict__['_recsize'] += vsize if begin == 0: begin = begin_ dtypes['names'].append(name) dtypes['formats'].append(str(shape[1:]) + dtype_) # Handle padding with a virtual variable. if typecode in 'bch': actual_size = reduce(mul, (1,) + shape[1:]) * size padding = -actual_size % 4 if padding: dtypes['names'].append('_padding_%d' % var) dtypes['formats'].append('(%d,)>b' % padding) # Data will be set later. data = None else: # not a record variable # Calculate size to avoid problems with vsize (above) a_size = reduce(mul, shape, 1) * size if self.use_mmap: mm = mmap(self.fp.fileno(), begin_+a_size, access=ACCESS_READ) data = ndarray.__new__(ndarray, shape, dtype=dtype_, buffer=mm, offset=begin_, order=0) else: pos = self.fp.tell() self.fp.seek(begin_) data = fromstring(self.fp.read(a_size), dtype=dtype_) data.shape = shape self.fp.seek(pos) # Add variable. self.variables[name] = netcdf_variable( data, typecode, shape, dimensions, attributes) if rec_vars: # Remove padding when only one record variable. if len(rec_vars) == 1: dtypes['names'] = dtypes['names'][:1] dtypes['formats'] = dtypes['formats'][:1] # Build rec array. if self.use_mmap: mm = mmap(self.fp.fileno(), begin+self._recs*self._recsize, access=ACCESS_READ) rec_array = ndarray.__new__(ndarray, (self._recs,), dtype=dtypes, buffer=mm, offset=begin, order=0) else: pos = self.fp.tell() self.fp.seek(begin) rec_array = fromstring(self.fp.read(self._recs*self._recsize), dtype=dtypes) rec_array.shape = (self._recs,) self.fp.seek(pos) for var in rec_vars: self.variables[var].__dict__['data'] = rec_array[var] def _read_var(self): name = asstr(self._unpack_string()) dimensions = [] shape = [] dims = self._unpack_int() for i in range(dims): dimid = self._unpack_int() dimname = self._dims[dimid] dimensions.append(dimname) dim = self.dimensions[dimname] shape.append(dim) dimensions = tuple(dimensions) shape = tuple(shape) attributes = self._read_att_array() nc_type = self.fp.read(4) vsize = self._unpack_int() begin = [self._unpack_int, self._unpack_int64][self.version_byte-1]() typecode, size = TYPEMAP[nc_type] if typecode is 'c': dtype_ = '>c' else: dtype_ = '>%s' % typecode if size > 1: dtype_ += str(size) return name, dimensions, shape, attributes, typecode, size, dtype_, begin, vsize def _read_values(self): nc_type = self.fp.read(4) n = self._unpack_int() typecode, size = TYPEMAP[nc_type] count = n*size values = self.fp.read(int(count)) self.fp.read(-count % 4) # read padding if typecode is not 'c': values = fromstring(values, dtype='>%s%d' % (typecode, size)) if values.shape == (1,): values = values[0] else: values = values.rstrip(asbytes('\x00')) return values def _pack_begin(self, begin): if self.version_byte == 1: self._pack_int(begin) elif self.version_byte == 2: self._pack_int64(begin) def _pack_int(self, value): self.fp.write(array(value, '>i').tostring()) _pack_int32 = _pack_int def _unpack_int(self): return int(fromstring(self.fp.read(4), '>i')[0]) _unpack_int32 = _unpack_int def _pack_int64(self, value): self.fp.write(array(value, '>q').tostring()) def _unpack_int64(self): return fromstring(self.fp.read(8), '>q')[0] def _pack_string(self, s): count = len(s) self._pack_int(count) self.fp.write(asbytes(s)) self.fp.write(asbytes('0') * (-count % 4)) # pad def _unpack_string(self): count = self._unpack_int() s = self.fp.read(count).rstrip(asbytes('\x00')) self.fp.read(-count % 4) # read padding return s class netcdf_variable(object): """ A data object for the `netcdf` module. `netcdf_variable` objects are constructed by calling the method `netcdf_file.createVariable` on the `netcdf_file` object. `netcdf_variable` objects behave much like array objects defined in numpy, except that their data resides in a file. Data is read by indexing and written by assigning to an indexed subset; the entire array can be accessed by the index ``[:]`` or (for scalars) by using the methods `getValue` and `assignValue`. `netcdf_variable` objects also have attribute `shape` with the same meaning as for arrays, but the shape cannot be modified. There is another read-only attribute `dimensions`, whose value is the tuple of dimension names. All other attributes correspond to variable attributes defined in the NetCDF file. Variable attributes are created by assigning to an attribute of the `netcdf_variable` object. Parameters ---------- data : array_like The data array that holds the values for the variable. Typically, this is initialized as empty, but with the proper shape. typecode : dtype character code Desired data-type for the data array. shape : sequence of ints The shape of the array. This should match the lengths of the variable's dimensions. dimensions : sequence of strings The names of the dimensions used by the variable. Must be in the same order of the dimension lengths given by `shape`. attributes : dict, optional Attribute values (any type) keyed by string names. These attributes become attributes for the netcdf_variable object. Attributes ---------- dimensions : list of str List of names of dimensions used by the variable object. isrec, shape Properties See also -------- isrec, shape """ def __init__(self, data, typecode, shape, dimensions, attributes=None): self.data = data self._typecode = typecode self._shape = shape self.dimensions = dimensions self._attributes = attributes or {} for k, v in self._attributes.items(): self.__dict__[k] = v def __setattr__(self, attr, value): # Store user defined attributes in a separate dict, # so we can save them to file later. try: self._attributes[attr] = value except AttributeError: pass self.__dict__[attr] = value def isrec(self): return self.data.shape and not self._shape[0] isrec = property(isrec) def shape(self): return self.data.shape shape = property(shape) def getValue(self): """ Retrieve a scalar value from a `netcdf_variable` of length one. Raises ------ ValueError If the netcdf variable is an array of length greater than one, this exception will be raised. """ return self.data.item() def assignValue(self, value): """ Assign a scalar value to a `netcdf_variable` of length one. Parameters ---------- value : scalar Scalar value (of compatible type) to assign to a length-one netcdf variable. This value will be written to file. Raises ------ ValueError If the input is not a scalar, or if the destination is not a length-one netcdf variable. """ self.data.itemset(value) def typecode(self): """ Return the typecode of the variable. Returns ------- typecode : char The character typecode of the variable (eg, 'i' for int). """ return self._typecode def __getitem__(self, index): return self.data[index] def __setitem__(self, index, data): # Expand data for record vars? if self.isrec: if isinstance(index, tuple): rec_index = index[0] else: rec_index = index if isinstance(rec_index, slice): recs = (rec_index.start or 0) + len(data) else: recs = rec_index + 1 if recs > len(self.data): shape = (recs,) + self._shape[1:] self.data.resize(shape) self.data[index] = data NetCDFFile = netcdf_file NetCDFVariable = netcdf_variable

scipy/scipy-svn

scipy/io/netcdf.py

Python

bsd-3-clause

28,822

[ "NetCDF" ]

2d65540f9b4ca31001e60b018553ac4a6c0c5d60c41031733483ec0a5224e468

""" Tools for the instructor dashboard """ import json import operator import dateutil from django.contrib.auth.models import User # lint-amnesty, pylint: disable=imported-auth-user from django.http import HttpResponseBadRequest from django.utils.translation import ugettext as _ from edx_when import api from opaque_keys.edx.keys import UsageKey from pytz import UTC from common.djangoapps.student.models import CourseEnrollment, get_user_by_username_or_email from openedx.core.djangoapps.schedules.models import Schedule class DashboardError(Exception): """ Errors arising from use of the instructor dashboard. """ def response(self): """ Generate an instance of HttpResponseBadRequest for this error. """ error = str(self) return HttpResponseBadRequest(json.dumps({'error': error})) def handle_dashboard_error(view): """ Decorator which adds seamless DashboardError handling to a view. If a DashboardError is raised during view processing, an HttpResponseBadRequest is sent back to the client with JSON data about the error. """ def wrapper(request, course_id): """ Wrap the view. """ try: return view(request, course_id=course_id) except DashboardError as error: return error.response() return wrapper def strip_if_string(value): if isinstance(value, str): return value.strip() return value def get_student_from_identifier(unique_student_identifier): """ Gets a student object using either an email address or username. Returns the student object associated with `unique_student_identifier` Raises User.DoesNotExist if no user object can be found, the user was retired, or the user is in the process of being retired. DEPRECATED: use student.models.get_user_by_username_or_email instead. """ return get_user_by_username_or_email(unique_student_identifier) def require_student_from_identifier(unique_student_identifier): """ Same as get_student_from_identifier() but will raise a DashboardError if the student does not exist. """ try: return get_student_from_identifier(unique_student_identifier) except User.DoesNotExist: raise DashboardError( # lint-amnesty, pylint: disable=raise-missing-from _("Could not find student matching identifier: {student_identifier}").format( student_identifier=unique_student_identifier ) ) def parse_datetime(datestr): """ Convert user input date string into an instance of `datetime.datetime` in UTC. """ try: return dateutil.parser.parse(datestr).replace(tzinfo=UTC) except ValueError: raise DashboardError(_("Unable to parse date: ") + datestr) # lint-amnesty, pylint: disable=raise-missing-from def find_unit(course, url): """ Finds the unit (block, module, whatever the terminology is) with the given url in the course tree and returns the unit. Raises DashboardError if no unit is found. """ def find(node, url): """ Find node in course tree for url. """ if str(node.location) == url: return node for child in node.get_children(): found = find(child, url) if found: return found return None unit = find(course, url) if unit is None: raise DashboardError(_("Couldn't find module for url: {0}").format(url)) return unit def get_units_with_due_date(course): """ Returns all top level units which have due dates. Does not return descendents of those nodes. """ units = [] # Pass in a schedule here so that we get back any relative dates in the course, but actual value # doesn't matter, since we don't care about the dates themselves, just whether they exist. # Thus we don't save or care about this temporary schedule object. schedule = Schedule(start_date=course.start) course_dates = api.get_dates_for_course(course.id, schedule=schedule) def visit(node): """ Visit a node. Checks to see if node has a due date and appends to `units` if it does. Otherwise recurses into children to search for nodes with due dates. """ if (node.location, 'due') in course_dates: units.append(node) else: for child in node.get_children(): visit(child) visit(course) #units.sort(key=_title_or_url) return units def title_or_url(node): """ Returns the `display_name` attribute of the passed in node of the course tree, if it has one. Otherwise returns the node's url. """ title = getattr(node, 'display_name', None) if not title: title = str(node.location) return title def set_due_date_extension(course, unit, student, due_date, actor=None, reason=''): """ Sets a due date extension. Raises: DashboardError if the unit or extended, due date is invalid or user is not enrolled in the course. """ mode, __ = CourseEnrollment.enrollment_mode_for_user(user=student, course_id=str(course.id)) if not mode: raise DashboardError(_("Could not find student enrollment in the course.")) # We normally set dates at the subsection level. But technically dates can be anywhere down the tree (and # usually are in self paced courses, where the subsection date gets propagated down). # So find all children that we need to set the date on, then set those dates. course_dates = api.get_dates_for_course(course.id, user=student) blocks_to_set = {unit} # always include the requested unit, even if it doesn't appear to have a due date now def visit(node): """ Visit a node. Checks to see if node has a due date and appends to `blocks_to_set` if it does. And recurses into children to search for nodes with due dates. """ if (node.location, 'due') in course_dates: blocks_to_set.add(node) for child in node.get_children(): visit(child) visit(unit) for block in blocks_to_set: if due_date: try: api.set_date_for_block(course.id, block.location, 'due', due_date, user=student, reason=reason, actor=actor) except api.MissingDateError as ex: raise DashboardError(_("Unit {0} has no due date to extend.").format(unit.location)) from ex except api.InvalidDateError as ex: raise DashboardError(_("An extended due date must be later than the original due date.")) from ex else: api.set_date_for_block(course.id, block.location, 'due', None, user=student, reason=reason, actor=actor) def dump_module_extensions(course, unit): """ Dumps data about students with due date extensions for a particular module, specified by 'url', in a particular course. """ header = [_("Username"), _("Full Name"), _("Extended Due Date")] data = [] for username, fullname, due_date in api.get_overrides_for_block(course.id, unit.location): due_date = due_date.strftime('%Y-%m-%d %H:%M') data.append(dict(list(zip(header, (username, fullname, due_date))))) data.sort(key=operator.itemgetter(_("Username"))) return { "header": header, "title": _("Users with due date extensions for {0}").format( title_or_url(unit)), "data": data } def dump_student_extensions(course, student): """ Dumps data about the due date extensions granted for a particular student in a particular course. """ data = [] header = [_("Unit"), _("Extended Due Date")] units = get_units_with_due_date(course) units = {u.location: u for u in units} query = api.get_overrides_for_user(course.id, student) for override in query: location = override['location'].replace(course_key=course.id) if location not in units: continue due = override['actual_date'] due = due.strftime("%Y-%m-%d %H:%M") title = title_or_url(units[location]) data.append(dict(list(zip(header, (title, due))))) data.sort(key=operator.itemgetter(_("Unit"))) return { "header": header, "title": _("Due date extensions for {0} {1} ({2})").format( student.first_name, student.last_name, student.username), "data": data} def add_block_ids(payload): """ rather than manually parsing block_ids from module_ids on the client, pass the block_ids explicitly in the payload """ if 'data' in payload: for ele in payload['data']: if 'module_id' in ele: ele['block_id'] = UsageKey.from_string(ele['module_id']).block_id

eduNEXT/edunext-platform

lms/djangoapps/instructor/views/tools.py

Python

agpl-3.0

8,924

[ "VisIt" ]

e998c91b2b60b135d494acbe790f69025ea0ba0296f749f72d282abb904f5639

# coding: utf-8 from __future__ import division, unicode_literals """ This module implements a Composition class to represent compositions, and a ChemicalPotential class to represent potentials. """ __author__ = "Shyue Ping Ong" __copyright__ = "Copyright 2011, The Materials Project" __version__ = "0.1" __maintainer__ = "Shyue Ping Ong" __email__ = "shyuep@gmail.com" __status__ = "Production" __date__ = "Nov 10, 2012" import collections import numbers import re import string import six from six.moves import filter, map, zip from fractions import gcd from functools import total_ordering from itertools import chain from pymatgen.core.periodic_table import get_el_sp, Element from pymatgen.util.string_utils import formula_double_format from pymatgen.serializers.json_coders import PMGSONable from pymatgen.core.units import unitized @total_ordering class Composition(collections.Mapping, collections.Hashable, PMGSONable): """ Represents a Composition, which is essentially a {element:amount} mapping type. Composition is written to be immutable and hashable, unlike a standard Python dict. Note that the key can be either an Element or a Specie. Elements and Specie are treated differently. i.e., a Fe2+ is not the same as a Fe3+ Specie and would be put in separate keys. This differentiation is deliberate to support using Composition to determine the fraction of a particular Specie. Works almost completely like a standard python dictionary, except that __getitem__ is overridden to return 0 when an element is not found. (somewhat like a defaultdict, except it is immutable). Also adds more convenience methods relevant to compositions, e.g., get_fraction. It should also be noted that many Composition related functionality takes in a standard string as a convenient input. For example, even though the internal representation of a Fe2O3 composition is {Element("Fe"): 2, Element("O"): 3}, you can obtain the amount of Fe simply by comp["Fe"] instead of the more verbose comp[Element("Fe")]. >>> comp = Composition("LiFePO4") >>> comp.get_atomic_fraction(Element("Li")) 0.14285714285714285 >>> comp.num_atoms 7.0 >>> comp.reduced_formula 'LiFePO4' >>> comp.formula 'Li1 Fe1 P1 O4' >>> comp.get_wt_fraction(Element("Li")) 0.04399794666951898 >>> comp.num_atoms 7.0 """ """ Tolerance in distinguishing different composition amounts. 1e-8 is fairly tight, but should cut out most floating point arithmetic errors. """ amount_tolerance = 1e-8 """ Special formula handling for peroxides and certain elements. This is so that formula output does not write LiO instead of Li2O2 for example. """ special_formulas = {"LiO": "Li2O2", "NaO": "Na2O2", "KO": "K2O2", "HO": "H2O2", "CsO": "Cs2O2", "RbO": "Rb2O2", "O": "O2", "N": "N2", "Cl": "Cl2", "H": "H2"} def __init__(self, *args, **kwargs): #allow_negative=False """ Very flexible Composition construction, similar to the built-in Python dict(). Also extended to allow simple string init. Args: Any form supported by the Python built-in dict() function. 1. A dict of either {Element/Specie: amount}, {string symbol:amount}, or {atomic number:amount} or any mixture of these. E.g., {Element("Li"):2 ,Element("O"):1}, {"Li":2, "O":1}, {3:2, 8:1} all result in a Li2O composition. 2. Keyword arg initialization, similar to a dict, e.g., Compostion(Li = 2, O = 1) In addition, the Composition constructor also allows a single string as an input formula. E.g., Composition("Li2O"). allow_negative: Whether to allow negative compositions. This argument must be popped from the \*\*kwargs due to \*args ambiguity. """ self.allow_negative = kwargs.pop('allow_negative', False) if len(args) == 1 and isinstance(args[0], six.string_types): elmap = self._parse_formula(args[0]) else: elmap = dict(*args, **kwargs) for k, v in list(elmap.items()): if v < -Composition.amount_tolerance and not self.allow_negative: raise CompositionError("Amounts in Composition cannot be " "negative!") elif abs(v) < Composition.amount_tolerance: del elmap[k] self._elmap = {get_el_sp(k): v for k, v in elmap.items()} self._natoms = sum(map(abs, self._elmap.values())) def __getitem__(self, el): """ Get the amount for element. """ return self._elmap.get(get_el_sp(el), 0) def __eq__(self, other): for el in chain(self.elements, other.elements): if abs(self[el] - other[el]) > Composition.amount_tolerance: return False return True def __ge__(self, other): """ Defines >= for Compositions. Should ONLY be used for defining a sort order (the behavior is probably not what you'd expect) """ for el in sorted(set(self.elements + other.elements)): if other[el] - self[el] >= Composition.amount_tolerance: return False elif self[el] - other[el] >= Composition.amount_tolerance: return True return True def __ne__(self, other): return not self.__eq__(other) def __add__(self, other): """ Adds two compositions. For example, an Fe2O3 composition + an FeO composition gives a Fe3O4 composition. """ new_el_map = collections.defaultdict(float) new_el_map.update(self) for k, v in other.items(): new_el_map[get_el_sp(k)] += v return Composition(new_el_map, allow_negative=self.allow_negative) def __sub__(self, other): """ Subtracts two compositions. For example, an Fe2O3 composition - an FeO composition gives an FeO2 composition. Raises: CompositionError if the subtracted composition is greater than the original composition in any of its elements, unless allow_negative is True """ new_el_map = collections.defaultdict(float) new_el_map.update(self) for k, v in other.items(): new_el_map[get_el_sp(k)] -= v return Composition(new_el_map, allow_negative=self.allow_negative) def __mul__(self, other): """ Multiply a Composition by an integer or a float. Fe2O3 * 4 -> Fe8O12 """ if not isinstance(other, numbers.Number): return NotImplemented return Composition({el: self[el] * other for el in self}, allow_negative=self.allow_negative) __rmul__ = __mul__ def __truediv__(self, other): if not isinstance(other, numbers.Number): return NotImplemented return Composition({el: self[el] / other for el in self}, allow_negative=self.allow_negative) def __hash__(self): """ Minimally effective hash function that just distinguishes between Compositions with different elements. """ hashcode = 0 for el in self._elmap.keys(): hashcode += el.Z return hashcode def __contains__(self, el): return el in self._elmap def __len__(self): return len(self._elmap) def __iter__(self): return self._elmap.__iter__() @property def average_electroneg(self): return sum((el.X * abs(amt) for el, amt in self._elmap.items())) / \ self.num_atoms def almost_equals(self, other, rtol=0.1, atol=1e-8): """ Returns true if compositions are equal within a tolerance. Args: other (Composition): Other composition to check rtol (float): Relative tolerance atol (float): Absolute tolerance """ sps = set(self.elements + other.elements) for sp in sps: a = self[sp] b = other[sp] tol = atol + rtol * (abs(a) + abs(b)) / 2 if abs(b - a) > tol: return False return True @property def is_element(self): """ True if composition is for an element. """ return len(self._elmap) == 1 def copy(self): return Composition(self._elmap, allow_negative=self.allow_negative) @property def formula(self): """ Returns a formula string, with elements sorted by electronegativity, e.g., Li4 Fe4 P4 O16. """ sym_amt = self.get_el_amt_dict() syms = sorted(sym_amt.keys(), key=lambda sym: get_el_sp(sym).X) formula = [s + formula_double_format(sym_amt[s], False) for s in syms] return " ".join(formula) @property def alphabetical_formula(self): """ Returns a formula string, with elements sorted by alphabetically e.g., Fe4 Li4 O16 P4. """ sym_amt = self.get_el_amt_dict() syms = sorted(sym_amt.keys()) formula = [s + formula_double_format(sym_amt[s], False) for s in syms] return " ".join(formula) @property def element_composition(self): """ Returns the composition replacing any species by the corresponding element. """ return Composition(self.get_el_amt_dict(), allow_negative=self.allow_negative) @property def fractional_composition(self): """ Returns the normalized composition which the number of species sum to 1. Returns: Normalized composition which the number of species sum to 1. """ return self / self._natoms @property def reduced_composition(self): """ Returns the reduced composition,i.e. amounts normalized by greatest common denominator. e.g., Composition("FePO4") for Composition("Fe4P4O16"). """ return self.get_reduced_composition_and_factor()[0] def get_reduced_composition_and_factor(self): """ Calculates a reduced composition and factor. Returns: A normalized composition and a multiplicative factor, i.e., Li4Fe4P4O16 returns (Composition("LiFePO4"), 4). """ factor = self.get_reduced_formula_and_factor()[1] return self / factor, factor def get_reduced_formula_and_factor(self): """ Calculates a reduced formula and factor. Returns: A pretty normalized formula and a multiplicative factor, i.e., Li4Fe4P4O16 returns (LiFePO4, 4). """ all_int = all([x == int(x) for x in self._elmap.values()]) if not all_int: return self.formula.replace(" ", ""), 1 d = self.get_el_amt_dict() (formula, factor) = reduce_formula(d) if formula in Composition.special_formulas: formula = Composition.special_formulas[formula] factor /= 2 return formula, factor @property def reduced_formula(self): """ Returns a pretty normalized formula, i.e., LiFePO4 instead of Li4Fe4P4O16. """ return self.get_reduced_formula_and_factor()[0] @property def elements(self): """ Returns view of elements in Composition. """ return list(self._elmap.keys()) def __str__(self): return " ".join([ "{}{}".format(k, formula_double_format(v, ignore_ones=False)) for k, v in self.as_dict().items()]) @property def num_atoms(self): """ Total number of atoms in Composition. For negative amounts, sum of absolute values """ return self._natoms @property @unitized("amu") def weight(self): """ Total molecular weight of Composition """ return sum([amount * el.atomic_mass for el, amount in self._elmap.items()]) def get_atomic_fraction(self, el): """ Calculate atomic fraction of an Element or Specie. Args: el (Element/Specie): Element or Specie to get fraction for. Returns: Atomic fraction for element el in Composition """ return abs(self[el]) / self._natoms def get_wt_fraction(self, el): """ Calculate weight fraction of an Element or Specie. Args: el (Element/Specie): Element or Specie to get fraction for. Returns: Weight fraction for element el in Composition """ return get_el_sp(el).atomic_mass * abs(self[el]) / self.weight def _parse_formula(self, formula): """ Args: formula (str): A string formula, e.g. Fe2O3, Li3Fe2(PO4)3 Returns: Composition with that formula. """ def get_sym_dict(f, factor): sym_dict = collections.defaultdict(float) for m in re.finditer(r"([A-Z][a-z]*)([-*\.\d]*)", f): el = m.group(1) amt = 1 if m.group(2).strip() != "": amt = float(m.group(2)) sym_dict[el] += amt * factor f = f.replace(m.group(), "", 1) if f.strip(): raise CompositionError("{} is an invalid formula!".format(f)) return sym_dict m = re.search(r"$([^\($]+)\)([\.\d]*)", formula) if m: factor = 1 if m.group(2) != "": factor = float(m.group(2)) unit_sym_dict = get_sym_dict(m.group(1), factor) expanded_sym = "".join(["{}{}".format(el, amt) for el, amt in unit_sym_dict.items()]) expanded_formula = formula.replace(m.group(), expanded_sym) return self._parse_formula(expanded_formula) return get_sym_dict(formula, 1) @property def anonymized_formula(self): """ An anonymized formula. Unique species are arranged in ordering of increasing amounts and assigned ascending alphabets. Useful for prototyping formulas. For example, all stoichiometric perovskites have anonymized_formula ABC3. """ reduced_comp = self.get_reduced_composition_and_factor()[0] els = sorted(reduced_comp.elements, key=lambda e: reduced_comp[e]) anon_formula = [] for anon, e in zip(string.ascii_uppercase, els): amt = reduced_comp[e] if amt > 0: if amt == 1: amt_str = "" elif abs(amt % 1) < 1e-8: amt_str = str(int(amt)) else: amt_str = str(amt) anon_formula.append("{}{}".format(anon, amt_str)) return "".join(anon_formula) def __repr__(self): return "Comp: " + self.formula @classmethod def from_dict(cls, d): """ Creates a composition from a dict generated by as_dict(). Strictly not necessary given that the standard constructor already takes in such an input, but this method preserves the standard pymatgen API of having from_dict methods to reconstitute objects generated by as_dict(). Allows for easier introspection. Args: d (dict): {symbol: amount} dict. """ return cls(d) def get_el_amt_dict(self): """ Returns: Dict with element symbol and (unreduced) amount e.g., {"Fe": 4.0, "O":6.0} or {"Fe3+": 4.0, "O2-":6.0} """ d = collections.defaultdict(float) for e, a in self.items(): d[e.symbol] += a return d def as_dict(self): """ Returns: dict with species symbol and (unreduced) amount e.g., {"Fe": 4.0, "O":6.0} or {"Fe3+": 4.0, "O2-":6.0} """ d = collections.defaultdict(float) for e, a in self.items(): d[str(e)] += a return d @property def to_reduced_dict(self): """ Returns: Dict with element symbol and reduced amount e.g., {"Fe": 2.0, "O":3.0} """ c = Composition(self.reduced_formula) return c.as_dict() @property def to_data_dict(self): """ Returns: A dict with many keys and values relating to Composition/Formula, including reduced_cell_composition, unit_cell_composition, reduced_cell_formula, elements and nelements. """ return {"reduced_cell_composition": self.to_reduced_dict, "unit_cell_composition": self.as_dict(), "reduced_cell_formula": self.reduced_formula, "elements": self.as_dict().keys(), "nelements": len(self.as_dict().keys())} @staticmethod def ranked_compositions_from_indeterminate_formula(fuzzy_formula, lock_if_strict=True): """ Takes in a formula where capitilization might not be correctly entered, and suggests a ranked list of potential Composition matches. Author: Anubhav Jain Args: fuzzy_formula (str): A formula string, such as "co2o3" or "MN", that may or may not have multiple interpretations lock_if_strict (bool): If true, a properly entered formula will only return the one correct interpretation. For example, "Co1" will only return "Co1" if true, but will return both "Co1" and "C1 O1" if false. Returns: A ranked list of potential Composition matches """ #if we have an exact match and the user specifies lock_if_strict, just #return the exact match! if lock_if_strict: #the strict composition parsing might throw an error, we can ignore #it and just get on with fuzzy matching try: comp = Composition(fuzzy_formula) return [comp] except (CompositionError, ValueError): pass all_matches = Composition._comps_from_fuzzy_formula(fuzzy_formula) #remove duplicates all_matches = list(set(all_matches)) #sort matches by rank descending all_matches = sorted(all_matches, key=lambda match: match[1], reverse=True) all_matches = [m[0] for m in all_matches] return all_matches @staticmethod def _comps_from_fuzzy_formula(fuzzy_formula, m_dict={}, m_points=0, factor=1): """ A recursive helper method for formula parsing that helps in interpreting and ranking indeterminate formulas. Author: Anubhav Jain Args: fuzzy_formula (str): A formula string, such as "co2o3" or "MN", that may or may not have multiple interpretations. m_dict (dict): A symbol:amt dictionary from the previously parsed formula. m_points: Number of points gained from the previously parsed formula. factor: Coefficient for this parse, e.g. (PO4)2 will feed in PO4 as the fuzzy_formula with a coefficient of 2. Returns: A list of tuples, with the first element being a Composition and the second element being the number of points awarded that Composition intepretation. """ def _parse_chomp_and_rank(m, f, m_dict, m_points): """ A helper method for formula parsing that helps in interpreting and ranking indeterminate formulas Author: Anubhav Jain Args: m: A regex match, with the first group being the element and the second group being the amount f: The formula part containing the match m_dict: A symbol:amt dictionary from the previously parsed formula m_points: Number of points gained from the previously parsed formula Returns: A tuple of (f, m_dict, points) where m_dict now contains data from the match and the match has been removed (chomped) from the formula f. The "goodness" of the match determines the number of points returned for chomping. Returns (None, None, None) if no element could be found... """ points = 0 # Points awarded if the first element of the element is correctly # specified as a capital points_first_capital = 100 # Points awarded if the second letter of the element is correctly # specified as lowercase points_second_lowercase = 100 #get element and amount from regex match el = m.group(1) if len(el) > 2 or len(el) < 1: raise CompositionError("Invalid element symbol entered!") amt = float(m.group(2)) if m.group(2).strip() != "" else 1 #convert the element string to proper [uppercase,lowercase] format #and award points if it is already in that format char1 = el[0] char2 = el[1] if len(el) > 1 else "" if char1 == char1.upper(): points += points_first_capital if char2 and char2 == char2.lower(): points += points_second_lowercase el = char1.upper() + char2.lower() #if it's a valid element, chomp and add to the points if Element.is_valid_symbol(el): if el in m_dict: m_dict[el] += amt * factor else: m_dict[el] = amt * factor return f.replace(m.group(), "", 1), m_dict, m_points + points #else return None return None, None, None fuzzy_formula = fuzzy_formula.strip() if len(fuzzy_formula) == 0: #The entire formula has been parsed into m_dict. Return the #corresponding Composition and number of points if m_dict: yield (Composition.from_dict(m_dict), m_points) else: #if there is a parenthesis, remove it and match the remaining stuff #with the appropriate factor for mp in re.finditer(r"$([^\($]+)\)([\.\d]*)", fuzzy_formula): mp_points = m_points mp_form = fuzzy_formula.replace(mp.group(), " ", 1) mp_dict = dict(m_dict) mp_factor = 1 if mp.group(2) == "" else float(mp.group(2)) #Match the stuff inside the parenthesis with the appropriate #factor for match in \ Composition._comps_from_fuzzy_formula(mp.group(1), mp_dict, mp_points, factor=mp_factor): only_me = True # Match the stuff outside the parentheses and return the # sum. for match2 in \ Composition._comps_from_fuzzy_formula(mp_form, mp_dict, mp_points, factor=1): only_me = False yield (match[0] + match2[0], match[1] + match2[1]) #if the stuff inside the parenthesis is nothing, then just #return the stuff inside the parentheses if only_me: yield match return #try to match the single-letter elements m1 = re.match(r"([A-z])([\.\d]*)", fuzzy_formula) if m1: m_points1 = m_points m_form1 = fuzzy_formula m_dict1 = dict(m_dict) (m_form1, m_dict1, m_points1) = \ _parse_chomp_and_rank(m1, m_form1, m_dict1, m_points1) if m_dict1: #there was a real match for match in \ Composition._comps_from_fuzzy_formula(m_form1, m_dict1, m_points1, factor): yield match #try to match two-letter elements m2 = re.match(r"([A-z]{2})([\.\d]*)", fuzzy_formula) if m2: m_points2 = m_points m_form2 = fuzzy_formula m_dict2 = dict(m_dict) (m_form2, m_dict2, m_points2) = \ _parse_chomp_and_rank(m2, m_form2, m_dict2, m_points2) if m_dict2: #there was a real match for match in \ Composition._comps_from_fuzzy_formula(m_form2, m_dict2, m_points2, factor): yield match def reduce_formula(sym_amt): """ Helper method to reduce a sym_amt dict to a reduced formula and factor. Args: sym_amt (dict): {symbol: amount}. Returns: (reduced_formula, factor). """ syms = sorted(sym_amt.keys(), key=lambda s: get_el_sp(s).X) syms = list(filter(lambda s: abs(sym_amt[s]) > Composition.amount_tolerance, syms)) num_el = len(syms) contains_polyanion = (num_el >= 3 and get_el_sp(syms[num_el - 1]).X - get_el_sp(syms[num_el - 2]).X < 1.65) factor = abs(six.moves.reduce(gcd, sym_amt.values())) reduced_form = [] n = num_el - 2 if contains_polyanion else num_el for i in range(0, n): s = syms[i] normamt = sym_amt[s] * 1.0 / factor reduced_form.append(s) reduced_form.append(formula_double_format(normamt)) if contains_polyanion: poly_sym_amt = {syms[i]: sym_amt[syms[i]] / factor for i in range(n, num_el)} (poly_form, poly_factor) = reduce_formula(poly_sym_amt) if poly_factor != 1: reduced_form.append("({}){}".format(poly_form, int(poly_factor))) else: reduced_form.append(poly_form) reduced_form = "".join(reduced_form) return reduced_form, factor class CompositionError(Exception): """Exception class for composition errors""" pass class ChemicalPotential(dict, PMGSONable): """ Class to represent set of chemical potentials. Can be: multiplied/divided by a Number multiplied by a Composition (returns an energy) added/subtracted with other ChemicalPotentials. """ def __init__(self, *args, **kwargs): """ Args: *args, **kwargs: any valid dict init arguments """ d = dict(*args, **kwargs) super(ChemicalPotential, self).__init__((get_el_sp(k), v) for k, v in d.items()) if len(d) != len(self): raise ValueError("Duplicate potential specified") def __mul__(self, other): if isinstance(other, numbers.Number): return ChemicalPotential({k: v * other for k, v in self.items()}) else: return NotImplemented __rmul__ = __mul__ def __truediv__(self, other): if isinstance(other, numbers.Number): return ChemicalPotential({k: v / other for k, v in self.items()}) else: return NotImplemented def __sub__(self, other): if isinstance(other, ChemicalPotential): els = set(self.keys()).union(other.keys()) return ChemicalPotential({e: self.get(e, 0) - other.get(e, 0) for e in els}) else: return NotImplemented def __add__(self, other): if isinstance(other, ChemicalPotential): els = set(self.keys()).union(other.keys()) return ChemicalPotential({e: self.get(e, 0) + other.get(e, 0) for e in els}) else: return NotImplemented def get_energy(self, composition, strict=True): """ Calculates the energy of a composition Args: composition (Composition): input composition strict (bool): Whether all potentials must be specified """ if strict and set(composition.keys()) > set(self.keys()): s = set(composition.keys()) - set(self.keys()) raise ValueError("Potentials not specified for {}".format(s)) return sum(self.get(k, 0) * v for k, v in composition.items()) def __repr__(self): return "ChemPots: " + super(ChemicalPotential, self).__repr__() if __name__ == "__main__": import doctest doctest.testmod()

yanikou19/pymatgen

pymatgen/core/composition.py

Python

mit

29,842

[ "pymatgen" ]

5668a8b25df2cf6e5ea176586f78aa8b3dc09316e32b260cfec894062031781d

# Copyright (c) 2012 Google Inc. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. from __future__ import print_function import gyp.common import gyp.simple_copy import multiprocessing import optparse import os.path import re import shlex import signal import subprocess import sys import threading import time import traceback from gyp.common import GypError from gyp.common import OrderedSet _PYTHON3 = sys.version_info >= (3, 0, 0) if not _PYTHON3: from compiler.ast import Const, Dict, Discard, List, Module, Node, Stmt import compiler # A list of types that are treated as linkable. linkable_types = ['executable', 'shared_library', 'loadable_module'] # A list of sections that contain links to other targets. dependency_sections = ['dependencies', 'export_dependent_settings'] # base_path_sections is a list of sections defined by GYP that contain # pathnames. The generators can provide more keys, the two lists are merged # into path_sections, but you should call IsPathSection instead of using either # list directly. base_path_sections = [ 'destination', 'files', 'include_dirs', 'inputs', 'libraries', 'outputs', 'sources', ] path_sections = set() # These per-process dictionaries are used to cache build file data when loading # in parallel mode. per_process_data = {} per_process_aux_data = {} def IsPathSection(section): # If section ends in one of the '=+?!' characters, it's applied to a section # without the trailing characters. '/' is notably absent from this list, # because there's no way for a regular expression to be treated as a path. while section[-1:] in '=+?!': section = section[:-1] if section in path_sections: return True # Sections mathing the regexp '_(dir|file|path)s?$' are also # considered PathSections. Using manual string matching since that # is much faster than the regexp and this can be called hundreds of # thousands of times so micro performance matters. if "_" in section: tail = section[-6:] if tail[-1] == 's': tail = tail[:-1] if tail[-5:] in ('_file', '_path'): return True return tail[-4:] == '_dir' return False # base_non_configuration_keys is a list of key names that belong in the target # itself and should not be propagated into its configurations. It is merged # with a list that can come from the generator to # create non_configuration_keys. base_non_configuration_keys = [ # Sections that must exist inside targets and not configurations. 'actions', 'configurations', 'copies', 'default_configuration', 'dependencies', 'dependencies_original', 'libraries', 'postbuilds', 'product_dir', 'product_extension', 'product_name', 'product_prefix', 'rules', 'run_as', 'sources', 'standalone_static_library', 'suppress_wildcard', 'target_name', 'toolset', 'toolsets', 'type', # Sections that can be found inside targets or configurations, but that # should not be propagated from targets into their configurations. 'variables', ] non_configuration_keys = [] # Keys that do not belong inside a configuration dictionary. invalid_configuration_keys = [ 'actions', 'all_dependent_settings', 'configurations', 'dependencies', 'direct_dependent_settings', 'libraries', 'link_settings', 'sources', 'standalone_static_library', 'target_name', 'type', ] # Controls whether or not the generator supports multiple toolsets. multiple_toolsets = False # Paths for converting filelist paths to output paths: { # toplevel, # qualified_output_dir, # } generator_filelist_paths = None def GetIncludedBuildFiles(build_file_path, aux_data, included=None): """Return a list of all build files included into build_file_path. The returned list will contain build_file_path as well as all other files that it included, either directly or indirectly. Note that the list may contain files that were included into a conditional section that evaluated to false and was not merged into build_file_path's dict. aux_data is a dict containing a key for each build file or included build file. Those keys provide access to dicts whose "included" keys contain lists of all other files included by the build file. included should be left at its default None value by external callers. It is used for recursion. The returned list will not contain any duplicate entries. Each build file in the list will be relative to the current directory. """ if included == None: included = [] if build_file_path in included: return included included.append(build_file_path) for included_build_file in aux_data[build_file_path].get('included', []): GetIncludedBuildFiles(included_build_file, aux_data, included) return included def CheckedEval(file_contents): """Return the eval of a gyp file. The gyp file is restricted to dictionaries and lists only, and repeated keys are not allowed. Note that this is slower than eval() is. """ if _PYTHON3: return eval(build_file_contents, {'__builtins__': None}, None) ast = compiler.parse(file_contents) assert isinstance(ast, Module) c1 = ast.getChildren() assert c1[0] is None assert isinstance(c1[1], Stmt) c2 = c1[1].getChildren() assert isinstance(c2[0], Discard) c3 = c2[0].getChildren() assert len(c3) == 1 return CheckNode(c3[0], []) def CheckNode(node, keypath): if isinstance(node, Dict): c = node.getChildren() dict = {} for n in range(0, len(c), 2): assert isinstance(c[n], Const) key = c[n].getChildren()[0] if key in dict: raise GypError("Key '" + key + "' repeated at level " + repr(len(keypath) + 1) + " with key path '" + '.'.join(keypath) + "'") kp = list(keypath) # Make a copy of the list for descending this node. kp.append(key) dict[key] = CheckNode(c[n + 1], kp) return dict elif isinstance(node, List): c = node.getChildren() children = [] for index, child in enumerate(c): kp = list(keypath) # Copy list. kp.append(repr(index)) children.append(CheckNode(child, kp)) return children elif isinstance(node, Const): return node.getChildren()[0] else: raise TypeError("Unknown AST node at key path '" + '.'.join(keypath) + "': " + repr(node)) def LoadOneBuildFile(build_file_path, data, aux_data, includes, is_target, check): if build_file_path in data: return data[build_file_path] if os.path.exists(build_file_path): build_file_contents = open(build_file_path).read() else: raise GypError("%s not found (cwd: %s)" % (build_file_path, os.getcwd())) build_file_data = None try: if check: build_file_data = CheckedEval(build_file_contents) else: build_file_data = eval(build_file_contents, {'__builtins__': None}, None) except SyntaxError: e = sys.exc_info()[1] e.filename = build_file_path raise except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while reading ' + build_file_path) raise if type(build_file_data) is not dict: raise GypError("%s does not evaluate to a dictionary." % build_file_path) data[build_file_path] = build_file_data aux_data[build_file_path] = {} # Scan for includes and merge them in. if ('skip_includes' not in build_file_data or not build_file_data['skip_includes']): try: if is_target: LoadBuildFileIncludesIntoDict(build_file_data, build_file_path, data, aux_data, includes, check) else: LoadBuildFileIncludesIntoDict(build_file_data, build_file_path, data, aux_data, None, check) except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while reading includes of ' + build_file_path) raise return build_file_data def LoadBuildFileIncludesIntoDict(subdict, subdict_path, data, aux_data, includes, check): includes_list = [] if includes != None: includes_list.extend(includes) if 'includes' in subdict: for include in subdict['includes']: # "include" is specified relative to subdict_path, so compute the real # path to include by appending the provided "include" to the directory # in which subdict_path resides. relative_include = \ os.path.normpath(os.path.join(os.path.dirname(subdict_path), include)) includes_list.append(relative_include) # Unhook the includes list, it's no longer needed. del subdict['includes'] # Merge in the included files. for include in includes_list: if not 'included' in aux_data[subdict_path]: aux_data[subdict_path]['included'] = [] aux_data[subdict_path]['included'].append(include) gyp.DebugOutput(gyp.DEBUG_INCLUDES, "Loading Included File: '%s'", include) MergeDicts(subdict, LoadOneBuildFile(include, data, aux_data, None, False, check), subdict_path, include) # Recurse into subdictionaries. for k, v in subdict.items(): if type(v) is dict: LoadBuildFileIncludesIntoDict(v, subdict_path, data, aux_data, None, check) elif type(v) is list: LoadBuildFileIncludesIntoList(v, subdict_path, data, aux_data, check) # This recurses into lists so that it can look for dicts. def LoadBuildFileIncludesIntoList(sublist, sublist_path, data, aux_data, check): for item in sublist: if type(item) is dict: LoadBuildFileIncludesIntoDict(item, sublist_path, data, aux_data, None, check) elif type(item) is list: LoadBuildFileIncludesIntoList(item, sublist_path, data, aux_data, check) # Processes toolsets in all the targets. This recurses into condition entries # since they can contain toolsets as well. def ProcessToolsetsInDict(data): if 'targets' in data: target_list = data['targets'] new_target_list = [] for target in target_list: # If this target already has an explicit 'toolset', and no 'toolsets' # list, don't modify it further. if 'toolset' in target and 'toolsets' not in target: new_target_list.append(target) continue if multiple_toolsets: toolsets = target.get('toolsets', ['target']) else: toolsets = ['target'] # Make sure this 'toolsets' definition is only processed once. if 'toolsets' in target: del target['toolsets'] if len(toolsets) > 0: # Optimization: only do copies if more than one toolset is specified. for build in toolsets[1:]: new_target = gyp.simple_copy.deepcopy(target) new_target['toolset'] = build new_target_list.append(new_target) target['toolset'] = toolsets[0] new_target_list.append(target) data['targets'] = new_target_list if 'conditions' in data: for condition in data['conditions']: if type(condition) is list: for condition_dict in condition[1:]: if type(condition_dict) is dict: ProcessToolsetsInDict(condition_dict) # TODO(mark): I don't love this name. It just means that it's going to load # a build file that contains targets and is expected to provide a targets dict # that contains the targets... def LoadTargetBuildFile(build_file_path, data, aux_data, variables, includes, depth, check, load_dependencies): # If depth is set, predefine the DEPTH variable to be a relative path from # this build file's directory to the directory identified by depth. if depth: # TODO(dglazkov) The backslash/forward-slash replacement at the end is a # temporary measure. This should really be addressed by keeping all paths # in POSIX until actual project generation. d = gyp.common.RelativePath(depth, os.path.dirname(build_file_path)) if d == '': variables['DEPTH'] = '.' else: variables['DEPTH'] = d.replace('\\', '/') # The 'target_build_files' key is only set when loading target build files in # the non-parallel code path, where LoadTargetBuildFile is called # recursively. In the parallel code path, we don't need to check whether the # |build_file_path| has already been loaded, because the 'scheduled' set in # ParallelState guarantees that we never load the same |build_file_path| # twice. if 'target_build_files' in data: if build_file_path in data['target_build_files']: # Already loaded. return False data['target_build_files'].add(build_file_path) gyp.DebugOutput(gyp.DEBUG_INCLUDES, "Loading Target Build File '%s'", build_file_path) build_file_data = LoadOneBuildFile(build_file_path, data, aux_data, includes, True, check) # Store DEPTH for later use in generators. build_file_data['_DEPTH'] = depth # Set up the included_files key indicating which .gyp files contributed to # this target dict. if 'included_files' in build_file_data: raise GypError(build_file_path + ' must not contain included_files key') included = GetIncludedBuildFiles(build_file_path, aux_data) build_file_data['included_files'] = [] for included_file in included: # included_file is relative to the current directory, but it needs to # be made relative to build_file_path's directory. included_relative = \ gyp.common.RelativePath(included_file, os.path.dirname(build_file_path)) build_file_data['included_files'].append(included_relative) # Do a first round of toolsets expansion so that conditions can be defined # per toolset. ProcessToolsetsInDict(build_file_data) # Apply "pre"/"early" variable expansions and condition evaluations. ProcessVariablesAndConditionsInDict( build_file_data, PHASE_EARLY, variables, build_file_path) # Since some toolsets might have been defined conditionally, perform # a second round of toolsets expansion now. ProcessToolsetsInDict(build_file_data) # Look at each project's target_defaults dict, and merge settings into # targets. if 'target_defaults' in build_file_data: if 'targets' not in build_file_data: raise GypError("Unable to find targets in build file %s" % build_file_path) index = 0 while index < len(build_file_data['targets']): # This procedure needs to give the impression that target_defaults is # used as defaults, and the individual targets inherit from that. # The individual targets need to be merged into the defaults. Make # a deep copy of the defaults for each target, merge the target dict # as found in the input file into that copy, and then hook up the # copy with the target-specific data merged into it as the replacement # target dict. old_target_dict = build_file_data['targets'][index] new_target_dict = gyp.simple_copy.deepcopy( build_file_data['target_defaults']) MergeDicts(new_target_dict, old_target_dict, build_file_path, build_file_path) build_file_data['targets'][index] = new_target_dict index += 1 # No longer needed. del build_file_data['target_defaults'] # Look for dependencies. This means that dependency resolution occurs # after "pre" conditionals and variable expansion, but before "post" - # in other words, you can't put a "dependencies" section inside a "post" # conditional within a target. dependencies = [] if 'targets' in build_file_data: for target_dict in build_file_data['targets']: if 'dependencies' not in target_dict: continue for dependency in target_dict['dependencies']: dependencies.append( gyp.common.ResolveTarget(build_file_path, dependency, None)[0]) if load_dependencies: for dependency in dependencies: try: LoadTargetBuildFile(dependency, data, aux_data, variables, includes, depth, check, load_dependencies) except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend( e, 'while loading dependencies of %s' % build_file_path) raise else: return (build_file_path, dependencies) def CallLoadTargetBuildFile(global_flags, build_file_path, variables, includes, depth, check, generator_input_info): """Wrapper around LoadTargetBuildFile for parallel processing. This wrapper is used when LoadTargetBuildFile is executed in a worker process. """ try: signal.signal(signal.SIGINT, signal.SIG_IGN) # Apply globals so that the worker process behaves the same. for key, value in global_flags.items(): globals()[key] = value SetGeneratorGlobals(generator_input_info) result = LoadTargetBuildFile(build_file_path, per_process_data, per_process_aux_data, variables, includes, depth, check, False) if not result: return result (build_file_path, dependencies) = result # We can safely pop the build_file_data from per_process_data because it # will never be referenced by this process again, so we don't need to keep # it in the cache. build_file_data = per_process_data.pop(build_file_path) # This gets serialized and sent back to the main process via a pipe. # It's handled in LoadTargetBuildFileCallback. return (build_file_path, build_file_data, dependencies) except GypError: e = sys.exc_info()[1] sys.stderr.write("gyp: %s\n" % e) return None except Exception: e = sys.exc_info()[1] print('Exception:', e, file=sys.stderr) print(traceback.format_exc(), file=sys.stderr) return None class ParallelProcessingError(Exception): pass class ParallelState(object): """Class to keep track of state when processing input files in parallel. If build files are loaded in parallel, use this to keep track of state during farming out and processing parallel jobs. It's stored in a global so that the callback function can have access to it. """ def __init__(self): # The multiprocessing pool. self.pool = None # The condition variable used to protect this object and notify # the main loop when there might be more data to process. self.condition = None # The "data" dict that was passed to LoadTargetBuildFileParallel self.data = None # The number of parallel calls outstanding; decremented when a response # was received. self.pending = 0 # The set of all build files that have been scheduled, so we don't # schedule the same one twice. self.scheduled = set() # A list of dependency build file paths that haven't been scheduled yet. self.dependencies = [] # Flag to indicate if there was an error in a child process. self.error = False def LoadTargetBuildFileCallback(self, result): """Handle the results of running LoadTargetBuildFile in another process. """ self.condition.acquire() if not result: self.error = True self.condition.notify() self.condition.release() return (build_file_path0, build_file_data0, dependencies0) = result self.data[build_file_path0] = build_file_data0 self.data['target_build_files'].add(build_file_path0) for new_dependency in dependencies0: if new_dependency not in self.scheduled: self.scheduled.add(new_dependency) self.dependencies.append(new_dependency) self.pending -= 1 self.condition.notify() self.condition.release() def LoadTargetBuildFilesParallel(build_files, data, variables, includes, depth, check, generator_input_info): parallel_state = ParallelState() parallel_state.condition = threading.Condition() # Make copies of the build_files argument that we can modify while working. parallel_state.dependencies = list(build_files) parallel_state.scheduled = set(build_files) parallel_state.pending = 0 parallel_state.data = data try: parallel_state.condition.acquire() while parallel_state.dependencies or parallel_state.pending: if parallel_state.error: break if not parallel_state.dependencies: parallel_state.condition.wait() continue dependency = parallel_state.dependencies.pop() parallel_state.pending += 1 global_flags = { 'path_sections': globals()['path_sections'], 'non_configuration_keys': globals()['non_configuration_keys'], 'multiple_toolsets': globals()['multiple_toolsets']} if not parallel_state.pool: parallel_state.pool = multiprocessing.Pool(multiprocessing.cpu_count()) parallel_state.pool.apply_async( CallLoadTargetBuildFile, args = (global_flags, dependency, variables, includes, depth, check, generator_input_info), callback = parallel_state.LoadTargetBuildFileCallback) except KeyboardInterrupt: e = sys.exc_info()[1] parallel_state.pool.terminate() raise e parallel_state.condition.release() parallel_state.pool.close() parallel_state.pool.join() parallel_state.pool = None if parallel_state.error: sys.exit(1) # Look for the bracket that matches the first bracket seen in a # string, and return the start and end as a tuple. For example, if # the input is something like "<(foo <(bar)) blah", then it would # return (1, 13), indicating the entire string except for the leading # "<" and trailing " blah". LBRACKETS= set('{[(') BRACKETS = {'}': '{', ']': '[', ')': '('} def FindEnclosingBracketGroup(input_str): stack = [] start = -1 for index, char in enumerate(input_str): if char in LBRACKETS: stack.append(char) if start == -1: start = index elif char in BRACKETS: if not stack: return (-1, -1) if stack.pop() != BRACKETS[char]: return (-1, -1) if not stack: return (start, index + 1) return (-1, -1) def IsStrCanonicalInt(string): """Returns True if |string| is in its canonical integer form. The canonical form is such that str(int(string)) == string. """ if type(string) is str: # This function is called a lot so for maximum performance, avoid # involving regexps which would otherwise make the code much # shorter. Regexps would need twice the time of this function. if string: if string == "0": return True if string[0] == "-": string = string[1:] if not string: return False if '1' <= string[0] <= '9': return string.isdigit() return False # This matches things like "<(asdf)", "<!(cmd)", "<!@(cmd)", "<|(list)", # "<!interpreter(arguments)", "<([list])", and even "<([)" and "<(<())". # In the last case, the inner "<()" is captured in match['content']. early_variable_re = re.compile( r'(?P<replace>(?P<type><(?:(?:!?@?)|\|)?)' r'(?P<command_string>[-a-zA-Z0-9_.]+)?' r'$(?P<is_array>\s*\[?)' r'(?P<content>.*?)(\]?)$)') # This matches the same as early_variable_re, but with '>' instead of '<'. late_variable_re = re.compile( r'(?P<replace>(?P<type>>(?:(?:!?@?)|\|)?)' r'(?P<command_string>[-a-zA-Z0-9_.]+)?' r'$(?P<is_array>\s*\[?)' r'(?P<content>.*?)(\]?)$)') # This matches the same as early_variable_re, but with '^' instead of '<'. latelate_variable_re = re.compile( r'(?P<replace>(?P<type>[\^](?:(?:!?@?)|\|)?)' r'(?P<command_string>[-a-zA-Z0-9_.]+)?' r'$(?P<is_array>\s*\[?)' r'(?P<content>.*?)(\]?)$)') # Global cache of results from running commands so they don't have to be run # more then once. cached_command_results = {} def FixupPlatformCommand(cmd): if sys.platform == 'win32': if type(cmd) is list: cmd = [re.sub('^cat ', 'type ', cmd[0])] + cmd[1:] else: cmd = re.sub('^cat ', 'type ', cmd) return cmd PHASE_EARLY = 0 PHASE_LATE = 1 PHASE_LATELATE = 2 def ExpandVariables(input, phase, variables, build_file): # Look for the pattern that gets expanded into variables if phase == PHASE_EARLY: variable_re = early_variable_re expansion_symbol = '<' elif phase == PHASE_LATE: variable_re = late_variable_re expansion_symbol = '>' elif phase == PHASE_LATELATE: variable_re = latelate_variable_re expansion_symbol = '^' else: assert False input_str = str(input) if IsStrCanonicalInt(input_str): return int(input_str) # Do a quick scan to determine if an expensive regex search is warranted. if expansion_symbol not in input_str: return input_str # Get the entire list of matches as a list of MatchObject instances. # (using findall here would return strings instead of MatchObjects). matches = list(variable_re.finditer(input_str)) if not matches: return input_str output = input_str # Reverse the list of matches so that replacements are done right-to-left. # That ensures that earlier replacements won't mess up the string in a # way that causes later calls to find the earlier substituted text instead # of what's intended for replacement. matches.reverse() for match_group in matches: match = match_group.groupdict() gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Matches: %r", match) # match['replace'] is the substring to look for, match['type'] # is the character code for the replacement type (< > <! >! <| >| <@ # >@ <!@ >!@), match['is_array'] contains a '[' for command # arrays, and match['content'] is the name of the variable (< >) # or command to run (<! >!). match['command_string'] is an optional # command string. Currently, only 'pymod_do_main' is supported. # run_command is true if a ! variant is used. run_command = '!' in match['type'] command_string = match['command_string'] # file_list is true if a | variant is used. file_list = '|' in match['type'] # Capture these now so we can adjust them later. replace_start = match_group.start('replace') replace_end = match_group.end('replace') # Find the ending paren, and re-evaluate the contained string. (c_start, c_end) = FindEnclosingBracketGroup(input_str[replace_start:]) # Adjust the replacement range to match the entire command # found by FindEnclosingBracketGroup (since the variable_re # probably doesn't match the entire command if it contained # nested variables). replace_end = replace_start + c_end # Find the "real" replacement, matching the appropriate closing # paren, and adjust the replacement start and end. replacement = input_str[replace_start:replace_end] # Figure out what the contents of the variable parens are. contents_start = replace_start + c_start + 1 contents_end = replace_end - 1 contents = input_str[contents_start:contents_end] # Do filter substitution now for <|(). # Admittedly, this is different than the evaluation order in other # contexts. However, since filtration has no chance to run on <|(), # this seems like the only obvious way to give them access to filters. if file_list: processed_variables = gyp.simple_copy.deepcopy(variables) ProcessListFiltersInDict(contents, processed_variables) # Recurse to expand variables in the contents contents = ExpandVariables(contents, phase, processed_variables, build_file) else: # Recurse to expand variables in the contents contents = ExpandVariables(contents, phase, variables, build_file) # Strip off leading/trailing whitespace so that variable matches are # simpler below (and because they are rarely needed). contents = contents.strip() # expand_to_list is true if an @ variant is used. In that case, # the expansion should result in a list. Note that the caller # is to be expecting a list in return, and not all callers do # because not all are working in list context. Also, for list # expansions, there can be no other text besides the variable # expansion in the input string. expand_to_list = '@' in match['type'] and input_str == replacement if run_command or file_list: # Find the build file's directory, so commands can be run or file lists # generated relative to it. build_file_dir = os.path.dirname(build_file) if build_file_dir == '' and not file_list: # If build_file is just a leaf filename indicating a file in the # current directory, build_file_dir might be an empty string. Set # it to None to signal to subprocess.Popen that it should run the # command in the current directory. build_file_dir = None # Support <|(listfile.txt ...) which generates a file # containing items from a gyp list, generated at gyp time. # This works around actions/rules which have more inputs than will # fit on the command line. if file_list: if type(contents) is list: contents_list = contents else: contents_list = contents.split(' ') replacement = contents_list[0] if os.path.isabs(replacement): raise GypError('| cannot handle absolute paths, got "%s"' % replacement) if not generator_filelist_paths: path = os.path.join(build_file_dir, replacement) else: if os.path.isabs(build_file_dir): toplevel = generator_filelist_paths['toplevel'] rel_build_file_dir = gyp.common.RelativePath(build_file_dir, toplevel) else: rel_build_file_dir = build_file_dir qualified_out_dir = generator_filelist_paths['qualified_out_dir'] path = os.path.join(qualified_out_dir, rel_build_file_dir, replacement) gyp.common.EnsureDirExists(path) replacement = gyp.common.RelativePath(path, build_file_dir) f = gyp.common.WriteOnDiff(path) for i in contents_list[1:]: f.write('%s\n' % i) f.close() elif run_command: use_shell = True if match['is_array']: contents = eval(contents) use_shell = False # Check for a cached value to avoid executing commands, or generating # file lists more than once. The cache key contains the command to be # run as well as the directory to run it from, to account for commands # that depend on their current directory. # TODO(http://code.google.com/p/gyp/issues/detail?id=111): In theory, # someone could author a set of GYP files where each time the command # is invoked it produces different output by design. When the need # arises, the syntax should be extended to support no caching off a # command's output so it is run every time. cache_key = (str(contents), build_file_dir) cached_value = cached_command_results.get(cache_key, None) if cached_value is None: gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Executing command '%s' in directory '%s'", contents, build_file_dir) replacement = '' if command_string == 'pymod_do_main': # <!pymod_do_main(modulename param eters) loads |modulename| as a # python module and then calls that module's DoMain() function, # passing ["param", "eters"] as a single list argument. For modules # that don't load quickly, this can be faster than # <!(python modulename param eters). Do this in |build_file_dir|. oldwd = os.getcwd() # Python doesn't like os.open('.'): no fchdir. if build_file_dir: # build_file_dir may be None (see above). os.chdir(build_file_dir) try: parsed_contents = shlex.split(contents) try: py_module = __import__(parsed_contents[0]) except ImportError as e: raise GypError("Error importing pymod_do_main" "module (%s): %s" % (parsed_contents[0], e)) replacement = str(py_module.DoMain(parsed_contents[1:])).rstrip() finally: os.chdir(oldwd) assert replacement != None elif command_string: raise GypError("Unknown command string '%s' in '%s'." % (command_string, contents)) else: # Fix up command with platform specific workarounds. contents = FixupPlatformCommand(contents) p = subprocess.Popen(contents, shell=use_shell, stdout=subprocess.PIPE, stderr=subprocess.PIPE, stdin=subprocess.PIPE, cwd=build_file_dir) p_stdout, p_stderr = p.communicate('') if p.wait() != 0 or p_stderr: sys.stderr.write(p_stderr) # Simulate check_call behavior, since check_call only exists # in python 2.5 and later. raise GypError("Call to '%s' returned exit status %d." % (contents, p.returncode)) replacement = p_stdout.rstrip() cached_command_results[cache_key] = replacement else: gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Had cache value for command '%s' in directory '%s'", contents,build_file_dir) replacement = cached_value else: if not contents in variables: if contents[-1] in ['!', '/']: # In order to allow cross-compiles (nacl) to happen more naturally, # we will allow references to >(sources/) etc. to resolve to # and empty list if undefined. This allows actions to: # 'action!': [ # '>@(_sources!)', # ], # 'action/': [ # '>@(_sources/)', # ], replacement = [] else: raise GypError('Undefined variable ' + contents + ' in ' + build_file) else: replacement = variables[contents] if type(replacement) is list: for item in replacement: if not contents[-1] == '/' and type(item) not in (str, int): raise GypError('Variable ' + contents + ' must expand to a string or list of strings; ' + 'list contains a ' + item.__class__.__name__) # Run through the list and handle variable expansions in it. Since # the list is guaranteed not to contain dicts, this won't do anything # with conditions sections. ProcessVariablesAndConditionsInList(replacement, phase, variables, build_file) elif type(replacement) not in (str, int): raise GypError('Variable ' + contents + ' must expand to a string or list of strings; ' + 'found a ' + replacement.__class__.__name__) if expand_to_list: # Expanding in list context. It's guaranteed that there's only one # replacement to do in |input_str| and that it's this replacement. See # above. if type(replacement) is list: # If it's already a list, make a copy. output = replacement[:] else: # Split it the same way sh would split arguments. output = shlex.split(str(replacement)) else: # Expanding in string context. encoded_replacement = '' if type(replacement) is list: # When expanding a list into string context, turn the list items # into a string in a way that will work with a subprocess call. # # TODO(mark): This isn't completely correct. This should # call a generator-provided function that observes the # proper list-to-argument quoting rules on a specific # platform instead of just calling the POSIX encoding # routine. encoded_replacement = gyp.common.EncodePOSIXShellList(replacement) else: encoded_replacement = replacement output = output[:replace_start] + str(encoded_replacement) + \ output[replace_end:] # Prepare for the next match iteration. input_str = output if output == input: gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Found only identity matches on %r, avoiding infinite " "recursion.", output) else: # Look for more matches now that we've replaced some, to deal with # expanding local variables (variables defined in the same # variables block as this one). gyp.DebugOutput(gyp.DEBUG_VARIABLES, "Found output %r, recursing.", output) if type(output) is list: if output and type(output[0]) is list: # Leave output alone if it's a list of lists. # We don't want such lists to be stringified. pass else: new_output = [] for item in output: new_output.append( ExpandVariables(item, phase, variables, build_file)) output = new_output else: output = ExpandVariables(output, phase, variables, build_file) # Convert all strings that are canonically-represented integers into integers. if type(output) is list: for index in range(0, len(output)): if IsStrCanonicalInt(output[index]): output[index] = int(output[index]) elif IsStrCanonicalInt(output): output = int(output) return output # The same condition is often evaluated over and over again so it # makes sense to cache as much as possible between evaluations. cached_conditions_asts = {} def EvalCondition(condition, conditions_key, phase, variables, build_file): """Returns the dict that should be used or None if the result was that nothing should be used.""" if type(condition) is not list: raise GypError(conditions_key + ' must be a list') if len(condition) < 2: # It's possible that condition[0] won't work in which case this # attempt will raise its own IndexError. That's probably fine. raise GypError(conditions_key + ' ' + condition[0] + ' must be at least length 2, not ' + str(len(condition))) i = 0 result = None while i < len(condition): cond_expr = condition[i] true_dict = condition[i + 1] if type(true_dict) is not dict: raise GypError('{} {} must be followed by a dictionary, not {}'.format( conditions_key, cond_expr, type(true_dict))) if len(condition) > i + 2 and type(condition[i + 2]) is dict: false_dict = condition[i + 2] i = i + 3 if i != len(condition): raise GypError('{} {} has {} unexpected trailing items'.format( conditions_key, cond_expr, len(condition) - i)) else: false_dict = None i = i + 2 if result == None: result = EvalSingleCondition( cond_expr, true_dict, false_dict, phase, variables, build_file) return result def EvalSingleCondition( cond_expr, true_dict, false_dict, phase, variables, build_file): """Returns true_dict if cond_expr evaluates to true, and false_dict otherwise.""" # Do expansions on the condition itself. Since the conditon can naturally # contain variable references without needing to resort to GYP expansion # syntax, this is of dubious value for variables, but someone might want to # use a command expansion directly inside a condition. cond_expr_expanded = ExpandVariables(cond_expr, phase, variables, build_file) if type(cond_expr_expanded) not in (str, int): raise ValueError( 'Variable expansion in this context permits str and int ' + \ 'only, found ' + cond_expr_expanded.__class__.__name__) try: if cond_expr_expanded in cached_conditions_asts: ast_code = cached_conditions_asts[cond_expr_expanded] else: ast_code = compile(cond_expr_expanded, '<string>', 'eval') cached_conditions_asts[cond_expr_expanded] = ast_code if eval(ast_code, {'__builtins__': None}, variables): return true_dict return false_dict except SyntaxError: e = sys.exc_info()[1] syntax_error = SyntaxError('%s while evaluating condition \'%s\' in %s ' 'at character %d.' % (str(e.args[0]), e.text, build_file, e.offset), e.filename, e.lineno, e.offset, e.text) raise syntax_error except NameError: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while evaluating condition \'%s\' in %s' % (cond_expr_expanded, build_file)) raise GypError(e) def ProcessConditionsInDict(the_dict, phase, variables, build_file): # Process a 'conditions' or 'target_conditions' section in the_dict, # depending on phase. # early -> conditions # late -> target_conditions # latelate -> no conditions # # Each item in a conditions list consists of cond_expr, a string expression # evaluated as the condition, and true_dict, a dict that will be merged into # the_dict if cond_expr evaluates to true. Optionally, a third item, # false_dict, may be present. false_dict is merged into the_dict if # cond_expr evaluates to false. # # Any dict merged into the_dict will be recursively processed for nested # conditionals and other expansions, also according to phase, immediately # prior to being merged. if phase == PHASE_EARLY: conditions_key = 'conditions' elif phase == PHASE_LATE: conditions_key = 'target_conditions' elif phase == PHASE_LATELATE: return else: assert False if not conditions_key in the_dict: return conditions_list = the_dict[conditions_key] # Unhook the conditions list, it's no longer needed. del the_dict[conditions_key] for condition in conditions_list: merge_dict = EvalCondition(condition, conditions_key, phase, variables, build_file) if merge_dict != None: # Expand variables and nested conditinals in the merge_dict before # merging it. ProcessVariablesAndConditionsInDict(merge_dict, phase, variables, build_file) MergeDicts(the_dict, merge_dict, build_file, build_file) def LoadAutomaticVariablesFromDict(variables, the_dict): # Any keys with plain string values in the_dict become automatic variables. # The variable name is the key name with a "_" character prepended. for key, value in the_dict.items(): if type(value) in (str, int, list): variables['_' + key] = value # PYK: If `toolset` is in `the_dict`, map all {toolset}_x variables to the # value of `x`. if 'toolset' in the_dict: prefix = '%s_' % the_dict['toolset'] for key, value in variables.items(): if key.startswith(prefix) and isinstance(value, (str, int, list)): variables[key[len(prefix):]] = value if key == '%s_os' % the_dict['toolset']: variables['OS'] = value def LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key): # Any keys in the_dict's "variables" dict, if it has one, becomes a # variable. The variable name is the key name in the "variables" dict. # Variables that end with the % character are set only if they are unset in # the variables dict. the_dict_key is the name of the key that accesses # the_dict in the_dict's parent dict. If the_dict's parent is not a dict # (it could be a list or it could be parentless because it is a root dict), # the_dict_key will be None. for key, value in the_dict.get('variables', {}).items(): if type(value) not in (str, int, list): continue if key.endswith('%'): variable_name = key[:-1] if variable_name in variables: # If the variable is already set, don't set it. continue if the_dict_key is 'variables' and variable_name in the_dict: # If the variable is set without a % in the_dict, and the_dict is a # variables dict (making |variables| a varaibles sub-dict of a # variables dict), use the_dict's definition. value = the_dict[variable_name] else: variable_name = key variables[variable_name] = value def ProcessVariablesAndConditionsInDict(the_dict, phase, variables_in, build_file, the_dict_key=None): """Handle all variable and command expansion and conditional evaluation. This function is the public entry point for all variable expansions and conditional evaluations. The variables_in dictionary will not be modified by this function. """ # Make a copy of the variables_in dict that can be modified during the # loading of automatics and the loading of the variables dict. variables = variables_in.copy() LoadAutomaticVariablesFromDict(variables, the_dict) if 'variables' in the_dict: # Make sure all the local variables are added to the variables # list before we process them so that you can reference one # variable from another. They will be fully expanded by recursion # in ExpandVariables. for key, value in the_dict['variables'].items(): variables[key] = value # Handle the associated variables dict first, so that any variable # references within can be resolved prior to using them as variables. # Pass a copy of the variables dict to avoid having it be tainted. # Otherwise, it would have extra automatics added for everything that # should just be an ordinary variable in this scope. ProcessVariablesAndConditionsInDict(the_dict['variables'], phase, variables, build_file, 'variables') LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key) for key, value in the_dict.items(): # Skip "variables", which was already processed if present. if key != 'variables' and type(value) is str: expanded = ExpandVariables(value, phase, variables, build_file) if type(expanded) not in (str, int): raise ValueError( 'Variable expansion in this context permits str and int ' + \ 'only, found ' + expanded.__class__.__name__ + ' for ' + key) the_dict[key] = expanded # Variable expansion may have resulted in changes to automatics. Reload. # TODO(mark): Optimization: only reload if no changes were made. variables = variables_in.copy() LoadAutomaticVariablesFromDict(variables, the_dict) LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key) # Process conditions in this dict. This is done after variable expansion # so that conditions may take advantage of expanded variables. For example, # if the_dict contains: # {'type': '<(library_type)', # 'conditions': [['_type=="static_library"', { ... }]]}, # _type, as used in the condition, will only be set to the value of # library_type if variable expansion is performed before condition # processing. However, condition processing should occur prior to recursion # so that variables (both automatic and "variables" dict type) may be # adjusted by conditions sections, merged into the_dict, and have the # intended impact on contained dicts. # # This arrangement means that a "conditions" section containing a "variables" # section will only have those variables effective in subdicts, not in # the_dict. The workaround is to put a "conditions" section within a # "variables" section. For example: # {'conditions': [['os=="mac"', {'variables': {'define': 'IS_MAC'}}]], # 'defines': ['<(define)'], # 'my_subdict': {'defines': ['<(define)']}}, # will not result in "IS_MAC" being appended to the "defines" list in the # current scope but would result in it being appended to the "defines" list # within "my_subdict". By comparison: # {'variables': {'conditions': [['os=="mac"', {'define': 'IS_MAC'}]]}, # 'defines': ['<(define)'], # 'my_subdict': {'defines': ['<(define)']}}, # will append "IS_MAC" to both "defines" lists. # Evaluate conditions sections, allowing variable expansions within them # as well as nested conditionals. This will process a 'conditions' or # 'target_conditions' section, perform appropriate merging and recursive # conditional and variable processing, and then remove the conditions section # from the_dict if it is present. ProcessConditionsInDict(the_dict, phase, variables, build_file) # Conditional processing may have resulted in changes to automatics or the # variables dict. Reload. variables = variables_in.copy() LoadAutomaticVariablesFromDict(variables, the_dict) LoadVariablesFromVariablesDict(variables, the_dict, the_dict_key) # Recurse into child dicts, or process child lists which may result in # further recursion into descendant dicts. for key, value in the_dict.items(): # Skip "variables" and string values, which were already processed if # present. if key == 'variables' or type(value) is str: continue if type(value) is dict: # Pass a copy of the variables dict so that subdicts can't influence # parents. ProcessVariablesAndConditionsInDict(value, phase, variables, build_file, key) elif type(value) is list: # The list itself can't influence the variables dict, and # ProcessVariablesAndConditionsInList will make copies of the variables # dict if it needs to pass it to something that can influence it. No # copy is necessary here. ProcessVariablesAndConditionsInList(value, phase, variables, build_file) elif type(value) is not int: raise TypeError('Unknown type ' + value.__class__.__name__ + \ ' for ' + key) def ProcessVariablesAndConditionsInList(the_list, phase, variables, build_file): # Iterate using an index so that new values can be assigned into the_list. index = 0 while index < len(the_list): item = the_list[index] if type(item) is dict: # Make a copy of the variables dict so that it won't influence anything # outside of its own scope. ProcessVariablesAndConditionsInDict(item, phase, variables, build_file) elif type(item) is list: ProcessVariablesAndConditionsInList(item, phase, variables, build_file) elif type(item) is str: expanded = ExpandVariables(item, phase, variables, build_file) if type(expanded) in (str, int): the_list[index] = expanded elif type(expanded) is list: the_list[index:index+1] = expanded index += len(expanded) # index now identifies the next item to examine. Continue right now # without falling into the index increment below. continue else: raise ValueError( 'Variable expansion in this context permits strings and ' + \ 'lists only, found ' + expanded.__class__.__name__ + ' at ' + \ index) elif type(item) is not int: raise TypeError('Unknown type ' + item.__class__.__name__ + \ ' at index ' + index) index = index + 1 def BuildTargetsDict(data): """Builds a dict mapping fully-qualified target names to their target dicts. |data| is a dict mapping loaded build files by pathname relative to the current directory. Values in |data| are build file contents. For each |data| value with a "targets" key, the value of the "targets" key is taken as a list containing target dicts. Each target's fully-qualified name is constructed from the pathname of the build file (|data| key) and its "target_name" property. These fully-qualified names are used as the keys in the returned dict. These keys provide access to the target dicts, the dicts in the "targets" lists. """ targets = {} for build_file in data['target_build_files']: for target in data[build_file].get('targets', []): target_name = gyp.common.QualifiedTarget(build_file, target['target_name'], target['toolset']) if target_name in targets: raise GypError('Duplicate target definitions for ' + target_name) targets[target_name] = target return targets def QualifyDependencies(targets): """Make dependency links fully-qualified relative to the current directory. |targets| is a dict mapping fully-qualified target names to their target dicts. For each target in this dict, keys known to contain dependency links are examined, and any dependencies referenced will be rewritten so that they are fully-qualified and relative to the current directory. All rewritten dependencies are suitable for use as keys to |targets| or a similar dict. """ all_dependency_sections = [dep + op for dep in dependency_sections for op in ('', '!', '/')] for target, target_dict in targets.items(): target_build_file = gyp.common.BuildFile(target) toolset = target_dict['toolset'] for dependency_key in all_dependency_sections: dependencies = target_dict.get(dependency_key, []) for index in range(0, len(dependencies)): dep_file, dep_target, dep_toolset = gyp.common.ResolveTarget( target_build_file, dependencies[index], toolset) if not multiple_toolsets: # Ignore toolset specification in the dependency if it is specified. dep_toolset = toolset dependency = gyp.common.QualifiedTarget(dep_file, dep_target, dep_toolset) dependencies[index] = dependency # Make sure anything appearing in a list other than "dependencies" also # appears in the "dependencies" list. if dependency_key != 'dependencies' and \ dependency not in target_dict['dependencies']: raise GypError('Found ' + dependency + ' in ' + dependency_key + ' of ' + target + ', but not in dependencies') def ExpandWildcardDependencies(targets, data): """Expands dependencies specified as build_file:*. For each target in |targets|, examines sections containing links to other targets. If any such section contains a link of the form build_file:*, it is taken as a wildcard link, and is expanded to list each target in build_file. The |data| dict provides access to build file dicts. Any target that does not wish to be included by wildcard can provide an optional "suppress_wildcard" key in its target dict. When present and true, a wildcard dependency link will not include such targets. All dependency names, including the keys to |targets| and the values in each dependency list, must be qualified when this function is called. """ for target, target_dict in targets.items(): toolset = target_dict['toolset'] target_build_file = gyp.common.BuildFile(target) for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) # Loop this way instead of "for dependency in" or "for index in range" # because the dependencies list will be modified within the loop body. index = 0 while index < len(dependencies): (dependency_build_file, dependency_target, dependency_toolset) = \ gyp.common.ParseQualifiedTarget(dependencies[index]) if dependency_target != '*' and dependency_toolset != '*': # Not a wildcard. Keep it moving. index = index + 1 continue if dependency_build_file == target_build_file: # It's an error for a target to depend on all other targets in # the same file, because a target cannot depend on itself. raise GypError('Found wildcard in ' + dependency_key + ' of ' + target + ' referring to same build file') # Take the wildcard out and adjust the index so that the next # dependency in the list will be processed the next time through the # loop. del dependencies[index] index = index - 1 # Loop through the targets in the other build file, adding them to # this target's list of dependencies in place of the removed # wildcard. dependency_target_dicts = data[dependency_build_file]['targets'] for dependency_target_dict in dependency_target_dicts: if int(dependency_target_dict.get('suppress_wildcard', False)): continue dependency_target_name = dependency_target_dict['target_name'] if (dependency_target != '*' and dependency_target != dependency_target_name): continue dependency_target_toolset = dependency_target_dict['toolset'] if (dependency_toolset != '*' and dependency_toolset != dependency_target_toolset): continue dependency = gyp.common.QualifiedTarget(dependency_build_file, dependency_target_name, dependency_target_toolset) index = index + 1 dependencies.insert(index, dependency) index = index + 1 def Unify(l): """Removes duplicate elements from l, keeping the first element.""" seen = {} return [seen.setdefault(e, e) for e in l if e not in seen] def RemoveDuplicateDependencies(targets): """Makes sure every dependency appears only once in all targets's dependency lists.""" for target_name, target_dict in targets.items(): for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) if dependencies: target_dict[dependency_key] = Unify(dependencies) def Filter(l, item): """Removes item from l.""" res = {} return [res.setdefault(e, e) for e in l if e != item] def RemoveSelfDependencies(targets): """Remove self dependencies from targets that have the prune_self_dependency variable set.""" for target_name, target_dict in targets.items(): for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) if dependencies: for t in dependencies: if t == target_name: if targets[t].get('variables', {}).get('prune_self_dependency', 0): target_dict[dependency_key] = Filter(dependencies, target_name) def RemoveLinkDependenciesFromNoneTargets(targets): """Remove dependencies having the 'link_dependency' attribute from the 'none' targets.""" for target_name, target_dict in targets.items(): for dependency_key in dependency_sections: dependencies = target_dict.get(dependency_key, []) if dependencies: for t in dependencies: if target_dict.get('type', None) == 'none': if targets[t].get('variables', {}).get('link_dependency', 0): target_dict[dependency_key] = \ Filter(target_dict[dependency_key], t) class DependencyGraphNode(object): """ Attributes: ref: A reference to an object that this DependencyGraphNode represents. dependencies: List of DependencyGraphNodes on which this one depends. dependents: List of DependencyGraphNodes that depend on this one. """ class CircularException(GypError): pass def __init__(self, ref): self.ref = ref self.dependencies = [] self.dependents = [] def __repr__(self): return '<DependencyGraphNode: %r>' % self.ref def FlattenToList(self): # flat_list is the sorted list of dependencies - actually, the list items # are the "ref" attributes of DependencyGraphNodes. Every target will # appear in flat_list after all of its dependencies, and before all of its # dependents. flat_list = OrderedSet() # in_degree_zeros is the list of DependencyGraphNodes that have no # dependencies not in flat_list. Initially, it is a copy of the children # of this node, because when the graph was built, nodes with no # dependencies were made implicit dependents of the root node. in_degree_zeros = set(self.dependents[:]) while in_degree_zeros: # Nodes in in_degree_zeros have no dependencies not in flat_list, so they # can be appended to flat_list. Take these nodes out of in_degree_zeros # as work progresses, so that the next node to process from the list can # always be accessed at a consistent position. node = in_degree_zeros.pop() flat_list.add(node.ref) # Look at dependents of the node just added to flat_list. Some of them # may now belong in in_degree_zeros. for node_dependent in node.dependents: is_in_degree_zero = True # TODO: We want to check through the # node_dependent.dependencies list but if it's long and we # always start at the beginning, then we get O(n^2) behaviour. for node_dependent_dependency in node_dependent.dependencies: if not node_dependent_dependency.ref in flat_list: # The dependent one or more dependencies not in flat_list. There # will be more chances to add it to flat_list when examining # it again as a dependent of those other dependencies, provided # that there are no cycles. is_in_degree_zero = False break if is_in_degree_zero: # All of the dependent's dependencies are already in flat_list. Add # it to in_degree_zeros where it will be processed in a future # iteration of the outer loop. in_degree_zeros.add(node_dependent) return list(flat_list) def FindCycles(self): """ Returns a list of cycles in the graph, where each cycle is its own list. """ results = [] visited = set() def Visit(node, path): for child in node.dependents: if child in path: results.append([child] + path[:path.index(child) + 1]) elif not child in visited: visited.add(child) Visit(child, [child] + path) visited.add(self) Visit(self, [self]) return results def DirectDependencies(self, dependencies=None): """Returns a list of just direct dependencies.""" if dependencies == None: dependencies = [] for dependency in self.dependencies: # Check for None, corresponding to the root node. if dependency.ref != None and dependency.ref not in dependencies: dependencies.append(dependency.ref) return dependencies def _AddImportedDependencies(self, targets, dependencies=None): """Given a list of direct dependencies, adds indirect dependencies that other dependencies have declared to export their settings. This method does not operate on self. Rather, it operates on the list of dependencies in the |dependencies| argument. For each dependency in that list, if any declares that it exports the settings of one of its own dependencies, those dependencies whose settings are "passed through" are added to the list. As new items are added to the list, they too will be processed, so it is possible to import settings through multiple levels of dependencies. This method is not terribly useful on its own, it depends on being "primed" with a list of direct dependencies such as one provided by DirectDependencies. DirectAndImportedDependencies is intended to be the public entry point. """ if dependencies == None: dependencies = [] index = 0 while index < len(dependencies): dependency = dependencies[index] dependency_dict = targets[dependency] # Add any dependencies whose settings should be imported to the list # if not already present. Newly-added items will be checked for # their own imports when the list iteration reaches them. # Rather than simply appending new items, insert them after the # dependency that exported them. This is done to more closely match # the depth-first method used by DeepDependencies. add_index = 1 for imported_dependency in \ dependency_dict.get('export_dependent_settings', []): if imported_dependency not in dependencies: dependencies.insert(index + add_index, imported_dependency) add_index = add_index + 1 index = index + 1 return dependencies def DirectAndImportedDependencies(self, targets, dependencies=None): """Returns a list of a target's direct dependencies and all indirect dependencies that a dependency has advertised settings should be exported through the dependency for. """ dependencies = self.DirectDependencies(dependencies) return self._AddImportedDependencies(targets, dependencies) def DeepDependencies(self, dependencies=None): """Returns an OrderedSet of all of a target's dependencies, recursively.""" if dependencies is None: # Using a list to get ordered output and a set to do fast "is it # already added" checks. dependencies = OrderedSet() for dependency in self.dependencies: # Check for None, corresponding to the root node. if dependency.ref is None: continue if dependency.ref not in dependencies: dependencies.add(dependency.ref) dependency.DeepDependencies(dependencies) return dependencies def _LinkDependenciesInternal(self, targets, include_shared_libraries, dependencies=None, initial=True): """Returns an OrderedSet of dependency targets that are linked into this target. This function has a split personality, depending on the setting of |initial|. Outside callers should always leave |initial| at its default setting. When adding a target to the list of dependencies, this function will recurse into itself with |initial| set to False, to collect dependencies that are linked into the linkable target for which the list is being built. If |include_shared_libraries| is False, the resulting dependencies will not include shared_library targets that are linked into this target. """ if dependencies is None: # Using a list to get ordered output and a set to do fast "is it # already added" checks. dependencies = OrderedSet() # Check for None, corresponding to the root node. if self.ref is None: return dependencies # It's kind of sucky that |targets| has to be passed into this function, # but that's presently the easiest way to access the target dicts so that # this function can find target types. if 'target_name' not in targets[self.ref]: raise GypError("Missing 'target_name' field in target.") if 'type' not in targets[self.ref]: raise GypError("Missing 'type' field in target %s" % targets[self.ref]['target_name']) target_type = targets[self.ref]['type'] is_linkable = target_type in linkable_types if initial and not is_linkable: # If this is the first target being examined and it's not linkable, # return an empty list of link dependencies, because the link # dependencies are intended to apply to the target itself (initial is # True) and this target won't be linked. return dependencies # Don't traverse 'none' targets if explicitly excluded. if (target_type == 'none' and not targets[self.ref].get('dependencies_traverse', True)): dependencies.add(self.ref) return dependencies # Executables and loadable modules are already fully and finally linked. # Nothing else can be a link dependency of them, there can only be # dependencies in the sense that a dependent target might run an # executable or load the loadable_module. if not initial and target_type in ('executable', 'loadable_module'): return dependencies # Shared libraries are already fully linked. They should only be included # in |dependencies| when adjusting static library dependencies (in order to # link against the shared_library's import lib), but should not be included # in |dependencies| when propagating link_settings. # The |include_shared_libraries| flag controls which of these two cases we # are handling. if (not initial and target_type == 'shared_library' and not include_shared_libraries): return dependencies # The target is linkable, add it to the list of link dependencies. if self.ref not in dependencies: dependencies.add(self.ref) if initial or not is_linkable: # If this is a subsequent target and it's linkable, don't look any # further for linkable dependencies, as they'll already be linked into # this target linkable. Always look at dependencies of the initial # target, and always look at dependencies of non-linkables. for dependency in self.dependencies: dependency._LinkDependenciesInternal(targets, include_shared_libraries, dependencies, False) return dependencies def DependenciesForLinkSettings(self, targets): """ Returns a list of dependency targets whose link_settings should be merged into this target. """ # TODO(sbaig) Currently, chrome depends on the bug that shared libraries' # link_settings are propagated. So for now, we will allow it, unless the # 'allow_sharedlib_linksettings_propagation' flag is explicitly set to # False. Once chrome is fixed, we can remove this flag. include_shared_libraries = \ targets[self.ref].get('allow_sharedlib_linksettings_propagation', True) return self._LinkDependenciesInternal(targets, include_shared_libraries) def DependenciesToLinkAgainst(self, targets): """ Returns a list of dependency targets that are linked into this target. """ return self._LinkDependenciesInternal(targets, True) def BuildDependencyList(targets): # Create a DependencyGraphNode for each target. Put it into a dict for easy # access. dependency_nodes = {} for target, spec in targets.items(): if target not in dependency_nodes: dependency_nodes[target] = DependencyGraphNode(target) # Set up the dependency links. Targets that have no dependencies are treated # as dependent on root_node. root_node = DependencyGraphNode(None) for target, spec in targets.items(): target_node = dependency_nodes[target] target_build_file = gyp.common.BuildFile(target) dependencies = spec.get('dependencies') if not dependencies: target_node.dependencies = [root_node] root_node.dependents.append(target_node) else: for dependency in dependencies: dependency_node = dependency_nodes.get(dependency) if not dependency_node: raise GypError("Dependency '%s' not found while " "trying to load target %s" % (dependency, target)) target_node.dependencies.append(dependency_node) dependency_node.dependents.append(target_node) flat_list = root_node.FlattenToList() # If there's anything left unvisited, there must be a circular dependency # (cycle). if len(flat_list) != len(targets): if not root_node.dependents: # If all targets have dependencies, add the first target as a dependent # of root_node so that the cycle can be discovered from root_node. target = targets.keys()[0] target_node = dependency_nodes[target] target_node.dependencies.append(root_node) root_node.dependents.append(target_node) cycles = [] for cycle in root_node.FindCycles(): paths = [node.ref for node in cycle] cycles.append('Cycle: %s' % ' -> '.join(paths)) raise DependencyGraphNode.CircularException( 'Cycles in dependency graph detected:\n' + '\n'.join(cycles)) return [dependency_nodes, flat_list] def VerifyNoGYPFileCircularDependencies(targets): # Create a DependencyGraphNode for each gyp file containing a target. Put # it into a dict for easy access. dependency_nodes = {} for target in targets.keys(): build_file = gyp.common.BuildFile(target) if not build_file in dependency_nodes: dependency_nodes[build_file] = DependencyGraphNode(build_file) # Set up the dependency links. for target, spec in targets.items(): build_file = gyp.common.BuildFile(target) build_file_node = dependency_nodes[build_file] target_dependencies = spec.get('dependencies', []) for dependency in target_dependencies: try: dependency_build_file = gyp.common.BuildFile(dependency) except GypError: e = sys.exc_info()[1] gyp.common.ExceptionAppend( e, 'while computing dependencies of .gyp file %s' % build_file) raise if dependency_build_file == build_file: # A .gyp file is allowed to refer back to itself. continue dependency_node = dependency_nodes.get(dependency_build_file) if not dependency_node: raise GypError("Dependancy '%s' not found" % dependency_build_file) if dependency_node not in build_file_node.dependencies: build_file_node.dependencies.append(dependency_node) dependency_node.dependents.append(build_file_node) # Files that have no dependencies are treated as dependent on root_node. root_node = DependencyGraphNode(None) for build_file_node in dependency_nodes.values(): if len(build_file_node.dependencies) == 0: build_file_node.dependencies.append(root_node) root_node.dependents.append(build_file_node) flat_list = root_node.FlattenToList() # If there's anything left unvisited, there must be a circular dependency # (cycle). if len(flat_list) != len(dependency_nodes): if not root_node.dependents: # If all files have dependencies, add the first file as a dependent # of root_node so that the cycle can be discovered from root_node. file_node = dependency_nodes.values()[0] file_node.dependencies.append(root_node) root_node.dependents.append(file_node) cycles = [] for cycle in root_node.FindCycles(): paths = [node.ref for node in cycle] cycles.append('Cycle: %s' % ' -> '.join(paths)) raise DependencyGraphNode.CircularException( 'Cycles in .gyp file dependency graph detected:\n' + '\n'.join(cycles)) def DoDependentSettings(key, flat_list, targets, dependency_nodes): # key should be one of all_dependent_settings, direct_dependent_settings, # or link_settings. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) if key == 'all_dependent_settings': dependencies = dependency_nodes[target].DeepDependencies() elif key == 'direct_dependent_settings': dependencies = \ dependency_nodes[target].DirectAndImportedDependencies(targets) elif key == 'link_settings': dependencies = \ dependency_nodes[target].DependenciesForLinkSettings(targets) else: raise GypError("DoDependentSettings doesn't know how to determine " 'dependencies for ' + key) for dependency in dependencies: dependency_dict = targets[dependency] if not key in dependency_dict: continue dependency_build_file = gyp.common.BuildFile(dependency) MergeDicts(target_dict, dependency_dict[key], build_file, dependency_build_file) def AdjustStaticLibraryDependencies(flat_list, targets, dependency_nodes, sort_dependencies): # Recompute target "dependencies" properties. For each static library # target, remove "dependencies" entries referring to other static libraries, # unless the dependency has the "hard_dependency" attribute set. For each # linkable target, add a "dependencies" entry referring to all of the # target's computed list of link dependencies (including static libraries # if no such entry is already present. for target in flat_list: target_dict = targets[target] target_type = target_dict['type'] if target_type == 'static_library': if not 'dependencies' in target_dict: continue target_dict['dependencies_original'] = target_dict.get( 'dependencies', [])[:] # A static library should not depend on another static library unless # the dependency relationship is "hard," which should only be done when # a dependent relies on some side effect other than just the build # product, like a rule or action output. Further, if a target has a # non-hard dependency, but that dependency exports a hard dependency, # the non-hard dependency can safely be removed, but the exported hard # dependency must be added to the target to keep the same dependency # ordering. dependencies = \ dependency_nodes[target].DirectAndImportedDependencies(targets) index = 0 while index < len(dependencies): dependency = dependencies[index] dependency_dict = targets[dependency] # Remove every non-hard static library dependency and remove every # non-static library dependency that isn't a direct dependency. if (dependency_dict['type'] == 'static_library' and \ not dependency_dict.get('hard_dependency', False)) or \ (dependency_dict['type'] != 'static_library' and \ not dependency in target_dict['dependencies']): # Take the dependency out of the list, and don't increment index # because the next dependency to analyze will shift into the index # formerly occupied by the one being removed. del dependencies[index] else: index = index + 1 # Update the dependencies. If the dependencies list is empty, it's not # needed, so unhook it. if len(dependencies) > 0: target_dict['dependencies'] = dependencies else: del target_dict['dependencies'] elif target_type in linkable_types: # Get a list of dependency targets that should be linked into this # target. Add them to the dependencies list if they're not already # present. link_dependencies = \ dependency_nodes[target].DependenciesToLinkAgainst(targets) for dependency in link_dependencies: if dependency == target: continue if not 'dependencies' in target_dict: target_dict['dependencies'] = [] if not dependency in target_dict['dependencies']: target_dict['dependencies'].append(dependency) # Sort the dependencies list in the order from dependents to dependencies. # e.g. If A and B depend on C and C depends on D, sort them in A, B, C, D. # Note: flat_list is already sorted in the order from dependencies to # dependents. if sort_dependencies and 'dependencies' in target_dict: target_dict['dependencies'] = [dep for dep in reversed(flat_list) if dep in target_dict['dependencies']] # Initialize this here to speed up MakePathRelative. exception_re = re.compile(r'''["']?[-/$<>^]''') def MakePathRelative(to_file, fro_file, item): # If item is a relative path, it's relative to the build file dict that it's # coming from. Fix it up to make it relative to the build file dict that # it's going into. # Exception: any |item| that begins with these special characters is # returned without modification. # / Used when a path is already absolute (shortcut optimization; # such paths would be returned as absolute anyway) # $ Used for build environment variables # - Used for some build environment flags (such as -lapr-1 in a # "libraries" section) # < Used for our own variable and command expansions (see ExpandVariables) # > Used for our own variable and command expansions (see ExpandVariables) # ^ Used for our own variable and command expansions (see ExpandVariables) # # "/' Used when a value is quoted. If these are present, then we # check the second character instead. # if to_file == fro_file or exception_re.match(item): return item else: # TODO(dglazkov) The backslash/forward-slash replacement at the end is a # temporary measure. This should really be addressed by keeping all paths # in POSIX until actual project generation. ret = os.path.normpath(os.path.join( gyp.common.RelativePath(os.path.dirname(fro_file), os.path.dirname(to_file)), item)).replace('\\', '/') if item[-1] == '/': ret += '/' return ret def MergeLists(to, fro, to_file, fro_file, is_paths=False, append=True): # Python documentation recommends objects which do not support hash # set this value to None. Python library objects follow this rule. is_hashable = lambda val: val.__hash__ # If x is hashable, returns whether x is in s. Else returns whether x is in l. def is_in_set_or_list(x, s, l): if is_hashable(x): return x in s return x in l prepend_index = 0 # Make membership testing of hashables in |to| (in particular, strings) # faster. hashable_to_set = set(x for x in to if is_hashable(x)) for item in fro: singleton = False if type(item) in (str, int): # The cheap and easy case. if is_paths: to_item = MakePathRelative(to_file, fro_file, item) else: to_item = item if not (type(item) is str and item.startswith('-')): # Any string that doesn't begin with a "-" is a singleton - it can # only appear once in a list, to be enforced by the list merge append # or prepend. singleton = True elif type(item) is dict: # Make a copy of the dictionary, continuing to look for paths to fix. # The other intelligent aspects of merge processing won't apply because # item is being merged into an empty dict. to_item = {} MergeDicts(to_item, item, to_file, fro_file) elif type(item) is list: # Recurse, making a copy of the list. If the list contains any # descendant dicts, path fixing will occur. Note that here, custom # values for is_paths and append are dropped; those are only to be # applied to |to| and |fro|, not sublists of |fro|. append shouldn't # matter anyway because the new |to_item| list is empty. to_item = [] MergeLists(to_item, item, to_file, fro_file) else: raise TypeError( 'Attempt to merge list item of unsupported type ' + \ item.__class__.__name__) if append: # If appending a singleton that's already in the list, don't append. # This ensures that the earliest occurrence of the item will stay put. if not singleton or not is_in_set_or_list(to_item, hashable_to_set, to): to.append(to_item) if is_hashable(to_item): hashable_to_set.add(to_item) else: # If prepending a singleton that's already in the list, remove the # existing instance and proceed with the prepend. This ensures that the # item appears at the earliest possible position in the list. while singleton and to_item in to: to.remove(to_item) # Don't just insert everything at index 0. That would prepend the new # items to the list in reverse order, which would be an unwelcome # surprise. to.insert(prepend_index, to_item) if is_hashable(to_item): hashable_to_set.add(to_item) prepend_index = prepend_index + 1 def MergeDicts(to, fro, to_file, fro_file): # I wanted to name the parameter "from" but it's a Python keyword... for k, v in fro.items(): # It would be nice to do "if not k in to: to[k] = v" but that wouldn't give # copy semantics. Something else may want to merge from the |fro| dict # later, and having the same dict ref pointed to twice in the tree isn't # what anyone wants considering that the dicts may subsequently be # modified. if k in to: bad_merge = False if type(v) in (str, int): if type(to[k]) not in (str, int): bad_merge = True elif type(v) is not type(to[k]): bad_merge = True if bad_merge: raise TypeError( 'Attempt to merge dict value of type ' + v.__class__.__name__ + \ ' into incompatible type ' + to[k].__class__.__name__ + \ ' for key ' + k) if type(v) in (str, int): # Overwrite the existing value, if any. Cheap and easy. is_path = IsPathSection(k) if is_path: to[k] = MakePathRelative(to_file, fro_file, v) else: to[k] = v elif type(v) is dict: # Recurse, guaranteeing copies will be made of objects that require it. if not k in to: to[k] = {} MergeDicts(to[k], v, to_file, fro_file) elif type(v) is list: # Lists in dicts can be merged with different policies, depending on # how the key in the "from" dict (k, the from-key) is written. # # If the from-key has ...the to-list will have this action # this character appended:... applied when receiving the from-list: # = replace # + prepend # ? set, only if to-list does not yet exist # (none) append # # This logic is list-specific, but since it relies on the associated # dict key, it's checked in this dict-oriented function. ext = k[-1] append = True if ext == '=': list_base = k[:-1] lists_incompatible = [list_base, list_base + '?'] to[list_base] = [] elif ext == '+': list_base = k[:-1] lists_incompatible = [list_base + '=', list_base + '?'] append = False elif ext == '?': list_base = k[:-1] lists_incompatible = [list_base, list_base + '=', list_base + '+'] else: list_base = k lists_incompatible = [list_base + '=', list_base + '?'] # Some combinations of merge policies appearing together are meaningless. # It's stupid to replace and append simultaneously, for example. Append # and prepend are the only policies that can coexist. for list_incompatible in lists_incompatible: if list_incompatible in fro: raise GypError('Incompatible list policies ' + k + ' and ' + list_incompatible) if list_base in to: if ext == '?': # If the key ends in "?", the list will only be merged if it doesn't # already exist. continue elif type(to[list_base]) is not list: # This may not have been checked above if merging in a list with an # extension character. raise TypeError( 'Attempt to merge dict value of type ' + v.__class__.__name__ + \ ' into incompatible type ' + to[list_base].__class__.__name__ + \ ' for key ' + list_base + '(' + k + ')') else: to[list_base] = [] # Call MergeLists, which will make copies of objects that require it. # MergeLists can recurse back into MergeDicts, although this will be # to make copies of dicts (with paths fixed), there will be no # subsequent dict "merging" once entering a list because lists are # always replaced, appended to, or prepended to. is_paths = IsPathSection(list_base) MergeLists(to[list_base], v, to_file, fro_file, is_paths, append) else: raise TypeError( 'Attempt to merge dict value of unsupported type ' + \ v.__class__.__name__ + ' for key ' + k) def MergeConfigWithInheritance(new_configuration_dict, build_file, target_dict, configuration, visited): # Skip if previously visted. if configuration in visited: return # Look at this configuration. configuration_dict = target_dict['configurations'][configuration] # Merge in parents. for parent in configuration_dict.get('inherit_from', []): MergeConfigWithInheritance(new_configuration_dict, build_file, target_dict, parent, visited + [configuration]) # Merge it into the new config. MergeDicts(new_configuration_dict, configuration_dict, build_file, build_file) # Drop abstract. if 'abstract' in new_configuration_dict: del new_configuration_dict['abstract'] def SetUpConfigurations(target, target_dict): # key_suffixes is a list of key suffixes that might appear on key names. # These suffixes are handled in conditional evaluations (for =, +, and ?) # and rules/exclude processing (for ! and /). Keys with these suffixes # should be treated the same as keys without. key_suffixes = ['=', '+', '?', '!', '/'] build_file = gyp.common.BuildFile(target) # Provide a single configuration by default if none exists. # TODO(mark): Signal an error if default_configurations exists but # configurations does not. if not 'configurations' in target_dict: target_dict['configurations'] = {'Default': {}} if not 'default_configuration' in target_dict: concrete = [i for (i, config) in target_dict['configurations'].items() if not config.get('abstract')] target_dict['default_configuration'] = sorted(concrete)[0] merged_configurations = {} configs = target_dict['configurations'] for (configuration, old_configuration_dict) in configs.items(): # Skip abstract configurations (saves work only). if old_configuration_dict.get('abstract'): continue # Configurations inherit (most) settings from the enclosing target scope. # Get the inheritance relationship right by making a copy of the target # dict. new_configuration_dict = {} for (key, target_val) in target_dict.items(): key_ext = key[-1:] if key_ext in key_suffixes: key_base = key[:-1] else: key_base = key if not key_base in non_configuration_keys: new_configuration_dict[key] = gyp.simple_copy.deepcopy(target_val) # Merge in configuration (with all its parents first). MergeConfigWithInheritance(new_configuration_dict, build_file, target_dict, configuration, []) merged_configurations[configuration] = new_configuration_dict # Put the new configurations back into the target dict as a configuration. for configuration in merged_configurations.keys(): target_dict['configurations'][configuration] = ( merged_configurations[configuration]) # Now drop all the abstract ones. for configuration in target_dict['configurations'].keys(): old_configuration_dict = target_dict['configurations'][configuration] if old_configuration_dict.get('abstract'): del target_dict['configurations'][configuration] # Now that all of the target's configurations have been built, go through # the target dict's keys and remove everything that's been moved into a # "configurations" section. delete_keys = [] for key in target_dict: key_ext = key[-1:] if key_ext in key_suffixes: key_base = key[:-1] else: key_base = key if not key_base in non_configuration_keys: delete_keys.append(key) for key in delete_keys: del target_dict[key] # Check the configurations to see if they contain invalid keys. for configuration in target_dict['configurations'].keys(): configuration_dict = target_dict['configurations'][configuration] for key in configuration_dict.keys(): if key in invalid_configuration_keys: raise GypError('%s not allowed in the %s configuration, found in ' 'target %s' % (key, configuration, target)) def ProcessListFiltersInDict(name, the_dict): """Process regular expression and exclusion-based filters on lists. An exclusion list is in a dict key named with a trailing "!", like "sources!". Every item in such a list is removed from the associated main list, which in this example, would be "sources". Removed items are placed into a "sources_excluded" list in the dict. Regular expression (regex) filters are contained in dict keys named with a trailing "/", such as "sources/" to operate on the "sources" list. Regex filters in a dict take the form: 'sources/': [ ['exclude', '_(linux|mac|win)\\.cc$'], ['include', '_mac\\.cc$'] ], The first filter says to exclude all files ending in _linux.cc, _mac.cc, and _win.cc. The second filter then includes all files ending in _mac.cc that are now or were once in the "sources" list. Items matching an "exclude" filter are subject to the same processing as would occur if they were listed by name in an exclusion list (ending in "!"). Items matching an "include" filter are brought back into the main list if previously excluded by an exclusion list or exclusion regex filter. Subsequent matching "exclude" patterns can still cause items to be excluded after matching an "include". """ # Look through the dictionary for any lists whose keys end in "!" or "/". # These are lists that will be treated as exclude lists and regular # expression-based exclude/include lists. Collect the lists that are # needed first, looking for the lists that they operate on, and assemble # then into |lists|. This is done in a separate loop up front, because # the _included and _excluded keys need to be added to the_dict, and that # can't be done while iterating through it. lists = [] del_lists = [] for key, value in the_dict.items(): operation = key[-1] if operation != '!' and operation != '/': continue if type(value) is not list: raise ValueError(name + ' key ' + key + ' must be list, not ' + \ value.__class__.__name__) list_key = key[:-1] if list_key not in the_dict: # This happens when there's a list like "sources!" but no corresponding # "sources" list. Since there's nothing for it to operate on, queue up # the "sources!" list for deletion now. del_lists.append(key) continue if type(the_dict[list_key]) is not list: value = the_dict[list_key] raise ValueError(name + ' key ' + list_key + \ ' must be list, not ' + \ value.__class__.__name__ + ' when applying ' + \ {'!': 'exclusion', '/': 'regex'}[operation]) if not list_key in lists: lists.append(list_key) # Delete the lists that are known to be unneeded at this point. for del_list in del_lists: del the_dict[del_list] for list_key in lists: the_list = the_dict[list_key] # Initialize the list_actions list, which is parallel to the_list. Each # item in list_actions identifies whether the corresponding item in # the_list should be excluded, unconditionally preserved (included), or # whether no exclusion or inclusion has been applied. Items for which # no exclusion or inclusion has been applied (yet) have value -1, items # excluded have value 0, and items included have value 1. Includes and # excludes override previous actions. All items in list_actions are # initialized to -1 because no excludes or includes have been processed # yet. list_actions = list((-1,) * len(the_list)) exclude_key = list_key + '!' if exclude_key in the_dict: for exclude_item in the_dict[exclude_key]: for index in range(0, len(the_list)): if exclude_item == the_list[index]: # This item matches the exclude_item, so set its action to 0 # (exclude). list_actions[index] = 0 # The "whatever!" list is no longer needed, dump it. del the_dict[exclude_key] regex_key = list_key + '/' if regex_key in the_dict: for regex_item in the_dict[regex_key]: [action, pattern] = regex_item pattern_re = re.compile(pattern) if action == 'exclude': # This item matches an exclude regex, so set its value to 0 (exclude). action_value = 0 elif action == 'include': # This item matches an include regex, so set its value to 1 (include). action_value = 1 else: # This is an action that doesn't make any sense. raise ValueError('Unrecognized action ' + action + ' in ' + name + \ ' key ' + regex_key) for index in range(0, len(the_list)): list_item = the_list[index] if list_actions[index] == action_value: # Even if the regex matches, nothing will change so continue (regex # searches are expensive). continue if pattern_re.search(list_item): # Regular expression match. list_actions[index] = action_value # The "whatever/" list is no longer needed, dump it. del the_dict[regex_key] # Add excluded items to the excluded list. # # Note that exclude_key ("sources!") is different from excluded_key # ("sources_excluded"). The exclude_key list is input and it was already # processed and deleted; the excluded_key list is output and it's about # to be created. excluded_key = list_key + '_excluded' if excluded_key in the_dict: raise GypError(name + ' key ' + excluded_key + ' must not be present prior ' ' to applying exclusion/regex filters for ' + list_key) excluded_list = [] # Go backwards through the list_actions list so that as items are deleted, # the indices of items that haven't been seen yet don't shift. That means # that things need to be prepended to excluded_list to maintain them in the # same order that they existed in the_list. for index in range(len(list_actions) - 1, -1, -1): if list_actions[index] == 0: # Dump anything with action 0 (exclude). Keep anything with action 1 # (include) or -1 (no include or exclude seen for the item). excluded_list.insert(0, the_list[index]) del the_list[index] # If anything was excluded, put the excluded list into the_dict at # excluded_key. if len(excluded_list) > 0: the_dict[excluded_key] = excluded_list # Now recurse into subdicts and lists that may contain dicts. for key, value in the_dict.items(): if type(value) is dict: ProcessListFiltersInDict(key, value) elif type(value) is list: ProcessListFiltersInList(key, value) def ProcessListFiltersInList(name, the_list): for item in the_list: if type(item) is dict: ProcessListFiltersInDict(name, item) elif type(item) is list: ProcessListFiltersInList(name, item) def ValidateTargetType(target, target_dict): """Ensures the 'type' field on the target is one of the known types. Arguments: target: string, name of target. target_dict: dict, target spec. Raises an exception on error. """ VALID_TARGET_TYPES = ('executable', 'loadable_module', 'static_library', 'shared_library', 'none') target_type = target_dict.get('type', None) if target_type not in VALID_TARGET_TYPES: raise GypError("Target %s has an invalid target type '%s'. " "Must be one of %s." % (target, target_type, '/'.join(VALID_TARGET_TYPES))) if (target_dict.get('standalone_static_library', 0) and not target_type == 'static_library'): raise GypError('Target %s has type %s but standalone_static_library flag is' ' only valid for static_library type.' % (target, target_type)) def ValidateRulesInTarget(target, target_dict, extra_sources_for_rules): """Ensures that the rules sections in target_dict are valid and consistent, and determines which sources they apply to. Arguments: target: string, name of target. target_dict: dict, target spec containing "rules" and "sources" lists. extra_sources_for_rules: a list of keys to scan for rule matches in addition to 'sources'. """ # Dicts to map between values found in rules' 'rule_name' and 'extension' # keys and the rule dicts themselves. rule_names = {} rule_extensions = {} rules = target_dict.get('rules', []) for rule in rules: # Make sure that there's no conflict among rule names and extensions. rule_name = rule['rule_name'] if rule_name in rule_names: raise GypError('rule %s exists in duplicate, target %s' % (rule_name, target)) rule_names[rule_name] = rule rule_extension = rule['extension'] if rule_extension.startswith('.'): rule_extension = rule_extension[1:] if rule_extension in rule_extensions: raise GypError(('extension %s associated with multiple rules, ' + 'target %s rules %s and %s') % (rule_extension, target, rule_extensions[rule_extension]['rule_name'], rule_name)) rule_extensions[rule_extension] = rule # Make sure rule_sources isn't already there. It's going to be # created below if needed. if 'rule_sources' in rule: raise GypError( 'rule_sources must not exist in input, target %s rule %s' % (target, rule_name)) rule_sources = [] source_keys = ['sources'] source_keys.extend(extra_sources_for_rules) for source_key in source_keys: for source in target_dict.get(source_key, []): (source_root, source_extension) = os.path.splitext(source) if source_extension.startswith('.'): source_extension = source_extension[1:] if source_extension == rule_extension: rule_sources.append(source) if len(rule_sources) > 0: rule['rule_sources'] = rule_sources def ValidateRunAsInTarget(target, target_dict, build_file): target_name = target_dict.get('target_name') run_as = target_dict.get('run_as') if not run_as: return if type(run_as) is not dict: raise GypError("The 'run_as' in target %s from file %s should be a " "dictionary." % (target_name, build_file)) action = run_as.get('action') if not action: raise GypError("The 'run_as' in target %s from file %s must have an " "'action' section." % (target_name, build_file)) if type(action) is not list: raise GypError("The 'action' for 'run_as' in target %s from file %s " "must be a list." % (target_name, build_file)) working_directory = run_as.get('working_directory') if working_directory and type(working_directory) is not str: raise GypError("The 'working_directory' for 'run_as' in target %s " "in file %s should be a string." % (target_name, build_file)) environment = run_as.get('environment') if environment and type(environment) is not dict: raise GypError("The 'environment' for 'run_as' in target %s " "in file %s should be a dictionary." % (target_name, build_file)) def ValidateActionsInTarget(target, target_dict, build_file): '''Validates the inputs to the actions in a target.''' target_name = target_dict.get('target_name') actions = target_dict.get('actions', []) for action in actions: action_name = action.get('action_name') if not action_name: raise GypError("Anonymous action in target %s. " "An action must have an 'action_name' field." % target_name) inputs = action.get('inputs', None) if inputs is None: raise GypError('Action in target %s has no inputs.' % target_name) action_command = action.get('action') if action_command and not action_command[0]: raise GypError("Empty action as command in target %s." % target_name) def TurnIntIntoStrInDict(the_dict): """Given dict the_dict, recursively converts all integers into strings. """ # Use items instead of items because there's no need to try to look at # reinserted keys and their associated values. for k, v in the_dict.items(): if type(v) is int: v = str(v) the_dict[k] = v elif type(v) is dict: TurnIntIntoStrInDict(v) elif type(v) is list: TurnIntIntoStrInList(v) if type(k) is int: del the_dict[k] the_dict[str(k)] = v def TurnIntIntoStrInList(the_list): """Given list the_list, recursively converts all integers into strings. """ for index in range(0, len(the_list)): item = the_list[index] if type(item) is int: the_list[index] = str(item) elif type(item) is dict: TurnIntIntoStrInDict(item) elif type(item) is list: TurnIntIntoStrInList(item) def PruneUnwantedTargets(targets, flat_list, dependency_nodes, root_targets, data): """Return only the targets that are deep dependencies of |root_targets|.""" qualified_root_targets = [] for target in root_targets: target = target.strip() qualified_targets = gyp.common.FindQualifiedTargets(target, flat_list) if not qualified_targets: raise GypError("Could not find target %s" % target) qualified_root_targets.extend(qualified_targets) wanted_targets = {} for target in qualified_root_targets: wanted_targets[target] = targets[target] for dependency in dependency_nodes[target].DeepDependencies(): wanted_targets[dependency] = targets[dependency] wanted_flat_list = [t for t in flat_list if t in wanted_targets] # Prune unwanted targets from each build_file's data dict. for build_file in data['target_build_files']: if not 'targets' in data[build_file]: continue new_targets = [] for target in data[build_file]['targets']: qualified_name = gyp.common.QualifiedTarget(build_file, target['target_name'], target['toolset']) if qualified_name in wanted_targets: new_targets.append(target) data[build_file]['targets'] = new_targets return wanted_targets, wanted_flat_list def VerifyNoCollidingTargets(targets): """Verify that no two targets in the same directory share the same name. Arguments: targets: A list of targets in the form 'path/to/file.gyp:target_name'. """ # Keep a dict going from 'subdirectory:target_name' to 'foo.gyp'. used = {} for target in targets: # Separate out 'path/to/file.gyp, 'target_name' from # 'path/to/file.gyp:target_name'. path, name = target.rsplit(':', 1) # Separate out 'path/to', 'file.gyp' from 'path/to/file.gyp'. subdir, gyp = os.path.split(path) # Use '.' for the current directory '', so that the error messages make # more sense. if not subdir: subdir = '.' # Prepare a key like 'path/to:target_name'. key = subdir + ':' + name if key in used: # Complain if this target is already used. raise GypError('Duplicate target name "%s" in directory "%s" used both ' 'in "%s" and "%s".' % (name, subdir, gyp, used[key])) used[key] = gyp def SetGeneratorGlobals(generator_input_info): # Set up path_sections and non_configuration_keys with the default data plus # the generator-specific data. global path_sections path_sections = set(base_path_sections) path_sections.update(generator_input_info['path_sections']) global non_configuration_keys non_configuration_keys = base_non_configuration_keys[:] non_configuration_keys.extend(generator_input_info['non_configuration_keys']) global multiple_toolsets multiple_toolsets = generator_input_info[ 'generator_supports_multiple_toolsets'] global generator_filelist_paths generator_filelist_paths = generator_input_info['generator_filelist_paths'] def Load(build_files, variables, includes, depth, generator_input_info, check, circular_check, parallel, root_targets): SetGeneratorGlobals(generator_input_info) # A generator can have other lists (in addition to sources) be processed # for rules. extra_sources_for_rules = generator_input_info['extra_sources_for_rules'] # Load build files. This loads every target-containing build file into # the |data| dictionary such that the keys to |data| are build file names, # and the values are the entire build file contents after "early" or "pre" # processing has been done and includes have been resolved. # NOTE: data contains both "target" files (.gyp) and "includes" (.gypi), as # well as meta-data (e.g. 'included_files' key). 'target_build_files' keeps # track of the keys corresponding to "target" files. data = {'target_build_files': set()} # Normalize paths everywhere. This is important because paths will be # used as keys to the data dict and for references between input files. build_files = set(map(os.path.normpath, build_files)) if parallel: LoadTargetBuildFilesParallel(build_files, data, variables, includes, depth, check, generator_input_info) else: aux_data = {} for build_file in build_files: try: LoadTargetBuildFile(build_file, data, aux_data, variables, includes, depth, check, True) except Exception: e = sys.exc_info()[1] gyp.common.ExceptionAppend(e, 'while trying to load %s' % build_file) raise # Build a dict to access each target's subdict by qualified name. targets = BuildTargetsDict(data) # Fully qualify all dependency links. QualifyDependencies(targets) # Remove self-dependencies from targets that have 'prune_self_dependencies' # set to 1. RemoveSelfDependencies(targets) # Expand dependencies specified as build_file:*. ExpandWildcardDependencies(targets, data) # Remove all dependencies marked as 'link_dependency' from the targets of # type 'none'. RemoveLinkDependenciesFromNoneTargets(targets) # Apply exclude (!) and regex (/) list filters only for dependency_sections. for target_name, target_dict in targets.items(): tmp_dict = {} for key_base in dependency_sections: for op in ('', '!', '/'): key = key_base + op if key in target_dict: tmp_dict[key] = target_dict[key] del target_dict[key] ProcessListFiltersInDict(target_name, tmp_dict) # Write the results back to |target_dict|. for key in tmp_dict: target_dict[key] = tmp_dict[key] # Make sure every dependency appears at most once. RemoveDuplicateDependencies(targets) if circular_check: # Make sure that any targets in a.gyp don't contain dependencies in other # .gyp files that further depend on a.gyp. VerifyNoGYPFileCircularDependencies(targets) [dependency_nodes, flat_list] = BuildDependencyList(targets) if root_targets: # Remove, from |targets| and |flat_list|, the targets that are not deep # dependencies of the targets specified in |root_targets|. targets, flat_list = PruneUnwantedTargets( targets, flat_list, dependency_nodes, root_targets, data) # Check that no two targets in the same directory have the same name. VerifyNoCollidingTargets(flat_list) # Handle dependent settings of various types. for settings_type in ['all_dependent_settings', 'direct_dependent_settings', 'link_settings']: DoDependentSettings(settings_type, flat_list, targets, dependency_nodes) # Take out the dependent settings now that they've been published to all # of the targets that require them. for target in flat_list: if settings_type in targets[target]: del targets[target][settings_type] # Make sure static libraries don't declare dependencies on other static # libraries, but that linkables depend on all unlinked static libraries # that they need so that their link steps will be correct. gii = generator_input_info if gii['generator_wants_static_library_dependencies_adjusted']: AdjustStaticLibraryDependencies(flat_list, targets, dependency_nodes, gii['generator_wants_sorted_dependencies']) # Apply "post"/"late"/"target" variable expansions and condition evaluations. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) ProcessVariablesAndConditionsInDict( target_dict, PHASE_LATE, variables, build_file) # Move everything that can go into a "configurations" section into one. for target in flat_list: target_dict = targets[target] SetUpConfigurations(target, target_dict) # Apply exclude (!) and regex (/) list filters. for target in flat_list: target_dict = targets[target] ProcessListFiltersInDict(target, target_dict) # Apply "latelate" variable expansions and condition evaluations. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) ProcessVariablesAndConditionsInDict( target_dict, PHASE_LATELATE, variables, build_file) # Make sure that the rules make sense, and build up rule_sources lists as # needed. Not all generators will need to use the rule_sources lists, but # some may, and it seems best to build the list in a common spot. # Also validate actions and run_as elements in targets. for target in flat_list: target_dict = targets[target] build_file = gyp.common.BuildFile(target) ValidateTargetType(target, target_dict) ValidateRulesInTarget(target, target_dict, extra_sources_for_rules) ValidateRunAsInTarget(target, target_dict, build_file) ValidateActionsInTarget(target, target_dict, build_file) # Generators might not expect ints. Turn them into strs. TurnIntIntoStrInDict(data) # TODO(mark): Return |data| for now because the generator needs a list of # build files that came in. In the future, maybe it should just accept # a list, and not the whole data dict. return [flat_list, targets, data] # vim: set ft=python expandtab tabstop=2 shiftwidth=2:

pyokagan/gyp

pylib/gyp/input.py

Python

bsd-3-clause

114,987

[ "VisIt" ]

10683fcc40c5524ada6a3da4400baf4c735feb5badae30c2c641c399c846e2f7

import json import glob import time import re import os from collections import Counter from itertools import chain import requests import settings from nltk.tokenize import word_tokenize PROFILE_URL = u'https://www.okcupid.com/profile/{username}' QUESTIONS_URL = u'https://www.okcupid.com/profile/{username}/questions' LOGIN_URL = 'http://www.okcupid.com/login' MATCH_URL = 'https://www.okcupid.com/match' QUICKMATCH_URL = 'https://www.okcupid.com/quickmatch/{username}' VISITORS_URL = 'https://www.okcupid.com/visitors/{username}' HEADERS = { 'User-agent' : settings.USER_AGENT, 'content-type': 'application/x-www-form-urlencoded; charset=UTF-8', } USER_DATA_FILE = 'USER_DATA' LOCATIONS = { 'melbourne' : 976925, 'sydney' : 974455, 'san_francisco' : 4265540, } MATCH_ORDERS = ( 'MATCH', 'SPECIAL_BLEND', 'RANDOM', 'ENEMY', 'JOIN', 'LOGIN', 'MATCH_AND_NEW', 'MATCH_AND_LOGIN', 'MATCH_AND_DISTANCE', ) def get_dataframe(path): users = okc.load_user_dicts(path) return pd.DataFrame(okc.get_stats(u) for u in users) def get_user_paths(path): """Returns an iterator with all sub-paths paths corresponding to *.json""" return glob.glob(os.path.join(path, '*.json')) def load_user(json_path): """Returns a User based on JSON profile file path""" with open(json_path, encoding='utf-8') as file: return User(json.loads(file.read())) def load_users(collection_path): """Return an iterator of User objects from a directory of JSON profiles.""" for path in get_user_paths(collection_path): try: yield load_user(path) except (ValueError, OkcIncompleteProfileError) as e: print(e) def load_user_dicts(collection_path): """Return an iterator of user dicts from a directory of JSON profiles.""" for path in get_user_paths(collection_path): try: with open(path, encoding='utf-8') as file: yield json.loads(file.read()) except (ValueError, OkcIncompleteProfileError) as e: print(e) def filter_users(paths, question_min): """Takes a list of user paths and filters out ones with fewer than question_min answered.""" filtered_paths = [] # load the additional user data stored alongside profiles user_data_path = os.path.join(os.path.split(paths[0])[0], USER_DATA_FILE) with open(user_data_path, encoding='utf-8') as f: user_data = json.loads(f.read()) for user_path in paths: username = os.path.splitext(os.path.basename(user_path))[0] if username not in user_data: print("user {} missing from user data dictionary".format(username)) else: data = user_data[username] if data['num_questions'] >= question_min: yield user_path def get_user_data(path): # TODO: Doesn't actually handle file not existing user_data_path = os.path.join(path, USER_DATA_FILE) if not os.path.exists(user_data_path): return {} with open(user_data_path) as f: return json.loads(f.read()) def write_user_data(data, path): user_data_path = os.path.join(path, USER_DATA_FILE) with open(user_data_path, 'w', encoding='utf-8') as f: f.write(json.dumps(data)) class OkcError(Exception): pass class OkcNoSuchUserError(OkcError): def __str__(self): return 'No such user: {}'.format(self.message) class OkcIncompleteProfileError(OkcError): def __str__(self): return 'Incomplete profile: {}'.format(self.message) def get_stats(data): if 'matchpercentage' not in data: raise OkcIncompleteProfileError(data['username']) height_str = data['skinny']['height'] if height_str == "": height = None height_inches = None else: height = int(100*float(re.search(r'$([^()]+)$', height_str).group(1)[:-1])) bits = height_str.split() #height_inches = int(bits[0].strip("'"))*12 + int(bits[1].strip('"')) stats = { 'username': data['username'], 'age': int(data['age']), 'gender': int(data['gender']), 'match': int(data['matchpercentage']), 'enemy': int(data['enemypercentage']), 'status': int(data['status']), 'orientation': int(data['orientation']), 'height': height, } # could also add a gender_str based field. either m, f, or other # or could actually pull out each of the multi-tags #eg: # gender_str = data['gender_str'] # if gender_str not in ('M', 'F'): # for label in gender_str.split(','): # stats[label.strip()] = True #what to do about "M" and "F""? # need to record these also so we know who didn't add extra things # orientation # 1 == straightish # 2 == gayish # 3 == bisexualish return stats class User(object): """Models an OKC user profile. Instance attributes: stats essay_titles list of essay titles (strings) essays list of essay contents (strings) text combined text from all essays (string) tokens The nth item in essay_titles is the title of the essay in the nth position in essays list. A value of None in the essays list indicates the user did not fillout that essay. """ def __init__(self, data): self.stats = get_stats(data) self.essays = self.process_essays(data) self._tokens = None self._words = None self._vocabulary = None def process_essays(self, data): found_essays = [] for essay in data['essays']: this_essay = essay['essay'] if this_essay == []: # User did not fill this essay out found_essays.append([]) else: text = this_essay[0]['rawtext'] found_essays.append(text) return found_essays def get_tokens(self, tokenize=word_tokenize): """Returns an iterator that yields tokens from all essays""" essay_tokens = (tokenize(essay) for essay in self.essays if essay) self._tokens = list(chain.from_iterable(essay_tokens)) return self._tokens def get_words(self): self._words = [token.lower() for token in self.tokens if token.isalpha()] return self._words def get_vocabulary(self): self._vocabulary = set(self.words) return self._vocabulary @property def lexical_diversity(self): if len(self.words) == 0: return 0 return len(self.vocabulary) / len(self.words) @property def vocabulary(self): if self._vocabulary is None: self.get_vocabulary() return self._vocabulary @property def words(self): if self._words is None: self.get_words() return self._words @property def tokens(self): if self._tokens is None: self.get_tokens() return self._tokens @property def text(self): """Returns the complete text from all essays in a user's profile""" text = '\n'.join(essay for essay in self.essays if essay) return text def __str__(self): return self.username class Session(object): """Class for interacting with okcupid.com.""" def __init__(self, username=settings.USERNAME, password=settings.PASSWORD): """Logs into okcupid.com. Uses parameters for logging in if provided, otherwise defaults to credentials specified in settings.py. """ self.login(username, password) def login(self, username, password): """Logs into okcupid.com.""" params = { 'username': username, 'password': password, 'okc_api' : '1', } r = requests.post(LOGIN_URL, params=params, headers=HEADERS) self.cookies = r.cookies def search(self, count=1000, matchorder='MATCH', location=None, distance=settings.DISTANCE, min_age=settings.MIN_AGE, max_age=settings.MAX_AGE, gender='all', orientation='all', time='year'): """Make a search GET request to OKC API. Note: POST does not work. Returns a dictionary with the following keys: 'username' : user logged in as 'foundany' : 0 or 1 'maxmatch' : highest match percentage found 'lquery', : ?? 'amateur_results' : list of user dictionary results 'total_matches' : the number of results 'cache_timekey' : ?? 'alist_results' : ?? 'last_online' : unknown format 'filters' : dictionary of filters applied 'numanswered' : number of match questions answered """ # Note that gender numbers depend on what has been specified # for orientation. This first set is for selecting # fine-grained every orientation possible -- ie 4095 genders = { 'male' : 21, 'female' : 42, 'all' : 63, } # for orientation = 'everybody'; ie no orientation param genders_orientation_everybody = { 'male' : 16, 'female' : 32, 'all' : 48, } #last online times = { 'now' : 3600, 'day' : 86400, 'week' : 604800, 'month' : 2678400, 'year' : 31536000, } # use most promiscuous values possible for rest... # This orientation number of 4095 is for selecting every tick # box possible in orientation. If you just want 'everyone', # omit this param. orientation = 4095 status = 0 # location if location is None: locid = 0 else: locid = LOCATIONS[location] # the filter names (eg 'filter1, 'filter2') are not relevant, # just indicate the nth filter applied. The value of the # filter parameters are themselves <key,value> pairs separated # by commas, indicating the filter type and value to be # filtered on. params = { 'okc_api' : 1, 'timekey' : 1, 'discard_prefs' : 1, 'count' : count, 'matchOrderBy' : matchorder, 'locid' : locid, 'filter1' : '0,{}'.format(genders[gender]), 'filter2' : '76,{}'.format(orientation), 'filter3' : '2,{},{}'.format(min_age, max_age), 'filter4' : '3,{}'.format(distance), 'filter5' : '5,{}'.format(times[time]), 'filter6' : '35,{}'.format(status), } result = requests.get(MATCH_URL, cookies=self.cookies, params=params) return result.json()['amateur_results'] def get_profile(self, username): """Given a username, return their profile as a JSON string.""" params = {'okc_api' : 1} url = PROFILE_URL.format(username=username) result = requests.get(url, cookies=self.cookies, params=params) if result.status_code != requests.codes.ok: message = "Error getting profile: {}\n{}".format(username, result.text) raise OkcNoSuchUserError(message) return result.json() def get_num_questions(self, username): params = {'okc_api' : 1} url = QUESTIONS_URL.format(username=username) result = requests.get(url, cookies=self.cookies, params=params) if result.status_code != requests.codes.ok: message = "Error getting profile: {}\n{}".format(username, result.text) raise OkcNoSuchUserError(message) json_data = result.json() num_questions = int(json_data['pagination']['raw']['total_num_results']) return num_questions def dump_profiles(self, usernames, path, resume=False): """Retrieves user profiles and write them all to disk.""" user_data = get_user_data(path) for count, username in enumerate(usernames): outpath = os.path.join(path, "{}.json".format(username)) if resume and os.path.exists(outpath): continue try: user = self.get_profile(username) num_questions = self.get_num_questions(username) if username not in user_data: user_data[username] = {} user_data[username]['num_questions'] = num_questions with open(outpath, 'w', encoding='utf-8') as file: json_string = json.dumps(user) file.write(json_string) write_user_data(user_data, path) print("{}: Wrote {}".format(count+1, username)) except OkcNoSuchUserError as error: print("NO SUCH USER: {}".format(username)) except requests.ConnectionError as error: print("CONNECTION ERROR: {}".format(username)) time.sleep(settings.SLEEP_TIME) def visit_profiles(self, usernames): """Retrieves the profiles of a sequence of usernames. Nothing is done with the profiles, but this has the effect of making you appear in their visitors list if you are not in invisible browsing mode. """ for count, username in enumerate(usernames): try: self.get_profile(username) print("{}: Visited {}".format(count+1, username)) except OkcNoSuchUserError as error: print("NO SUCH USER: {}".format(username)) except requests.ConnectionError as error: print("CONNECTION ERROR: {}".format(username)) time.sleep(settings.SLEEP_TIME) def find_and_visit_profiles(self, cutoff=None, threshold=None, **kwargs): """Perform a custom search for users and then visit their profiles. threshold argument: minimum match percentage score to stop at. cuttoff argument: number of profiles to stop at. Also accepts all keyword arguments accepted by the search() method. """ profiles = self.search(**kwargs) if threshold is not None: usernames = [profile['username'] for profile in profiles if int(profile['matchpercentage']) > threshold] if cutoff is not None: usernames = usernames[:cutoff] self.visit_profiles(usernames) def find_users(self, **kwargs): """Given search parameters as keyword arguments, returns a set of usernames. Avoids the 1000 user response limit by repeating search for randomly sorted results until no new users are found. """ usernames = set() num_found = True while num_found: num_before = len(usernames) profiles = self.search(matchorder='RANDOM', **kwargs) usernames.update(profile['username'] for profile in profiles) num_after = len(usernames) num_found = num_after - num_before print("Found {} new users".format(num_found)) time.sleep(settings.SLEEP_TIME) return usernames def find_all_users(self, binsize=5, **kwargs): """In addition to the 1000 user result limit, OKC seems to also silently filter out some users from the search results if there are too many *potential* matches that could be returned. ie there are just some users that won't be returned no matter how many times you hit the RANDOM buttom. This can be avoided by searching over a smaller age range. This function gets around the limitation by invoking self.find_users() across a series of ranges of length specified by binsize. """ usernames = set() pairs = [] curr = settings.MIN_AGE while curr <= settings.MAX_AGE: if curr + binsize > settings.MAX_AGE: this_max = settings.MAX_AGE else: this_max = curr + binsize pairs.append((curr, this_max)) curr += binsize + 1 kwargs.pop('min_age', None) kwargs.pop('max_age', None) for min_age, max_age in pairs: found = self.find_users(min_age=min_age, max_age=max_age, **kwargs) usernames.update(found) print("====================================") print("Found {} users in age bracket {},{}\n".format(len(found), min_age, max_age)) return usernames

ned2/okdata

okc.py

Python

mit

16,915

[ "VisIt" ]

038678a7ca9dcc7b200a76ce66fcc0829e66b42de9fd17626ee151004ee20b32

""" ======= Plotter ======= .. moduleauthor:: Adam Ginsburg <adam.g.ginsburg@gmail.com> """ from __future__ import print_function import matplotlib import matplotlib.pyplot import matplotlib.figure import numpy as np import astropy.units as u import copy import inspect try: from matplotlib.cbook import BoundMethodProxy except ImportError: from matplotlib.cbook import _BoundMethodProxy as BoundMethodProxy from . import widgets from ..specwarnings import warn interactive_help_message = """ Interactive key commands for plotter. An additional help message may appear if you have initiated the fitter. '?' - bring up this message 'f' - initiate the /f/itter 'b' - initiate the /b/aseliner 'B' - initiate the /b/aseliner (reset the selection too) 'r' - re-attach matplotlib keys 'R' - redraw the plot cleanly 'i' : individual components / show each fitted component """ xlabel_table = {'speed': 'Velocity'} class Plotter(object): """ Class to plot a spectrum """ def __init__(self, Spectrum, autorefresh=True, title="", xlabel="", silent=True, plotscale=1.0, **kwargs): self.figure = None self.axis = None self.Spectrum = Spectrum self._xunit = Spectrum.xarr.unit # plot parameters self.offset = 0.0 # vertical offset self.autorefresh = autorefresh self.xlabel = xlabel self.title = title self.errorplot = None self.plotkwargs = kwargs self._xlim = [None,None] self._ylim = [None,None] self.debug = False self.keyclick = None self.silent = silent self.plotscale = plotscale self._xclick1 = None self._xclick2 = None self.automake_fitter_tool = False def _get_prop(xy, minmax): def getprop(self): if self.Spectrum.xarr.unit != self._xunit: self._xunit = self.Spectrum.xarr.unit if xy == 'x': if minmax == 'min': if self._xlim[0] and self._xunit: try: self._xlim[0]._unit = self._xunit except AttributeError: self._xlim[0] = u.Quantity(self._xlim[0], self._xunit) return self._xlim[0] elif minmax == 'max': if self._xlim[1] and self._xunit: try: self._xlim[1]._unit = self._xunit except AttributeError: self._xlim[1] = u.Quantity(self._xlim[1], self._xunit) return self._xlim[1] elif xy == 'y': if minmax == 'min': return self._ylim[0] elif minmax == 'max': return self._ylim[1] return getprop def _set_prop(xy, minmax): def setprop(self, value): if self.debug: frm = inspect.stack() print(frm[1],"Setting %s%s to %s" % (xy,minmax,value)) if xy == 'x': if minmax == 'min': self._xlim[0] = value elif minmax == 'max': self._xlim[1] = value elif xy == 'y': if minmax == 'min': self._ylim[0] = value elif minmax == 'max': self._ylim[1] = value return setprop xmin = property(fget=_get_prop('x','min'),fset=_set_prop('x','min')) xmax = property(fget=_get_prop('x','max'),fset=_set_prop('x','max')) ymin = property(fget=_get_prop('y','min'),fset=_set_prop('y','min')) ymax = property(fget=_get_prop('y','max'),fset=_set_prop('y','max')) def _disconnect_matplotlib_keys(self): """ Disconnected the matplotlib key-press callbacks """ if self.figure is not None: cbs = self.figure.canvas.callbacks.callbacks # this may cause problems since the dict of key press events is a # dict, i.e. not ordered, and we want to pop the first one... mpl_keypress_handler = self.figure.canvas.manager.key_press_handler_id try: self._mpl_key_callbacks = {mpl_keypress_handler: cbs['key_press_event'].pop(mpl_keypress_handler)} except KeyError: bmp = BoundMethodProxy(self.figure.canvas.manager.key_press) self._mpl_key_callbacks = {mpl_keypress_handler: bmp} def _reconnect_matplotlib_keys(self): """ Reconnect the previously disconnected matplotlib keys """ if self.figure is not None and hasattr(self,'_mpl_key_callbacks'): self.figure.canvas.callbacks.callbacks['key_press_event'].update(self._mpl_key_callbacks) elif self.figure is not None: mpl_keypress_handler = self.figure.canvas.manager.key_press_handler_id bmp = BoundMethodProxy(self.figure.canvas.manager.key_press) self.figure.canvas.callbacks.callbacks['key_press_event'].update({mpl_keypress_handler: bmp}) def __call__(self, figure=None, axis=None, clear=True, autorefresh=None, plotscale=1.0, override_plotkwargs=False, **kwargs): """ Plot a spectrum Keywords: figure - either a matplotlib figure instance or a figure number to pass into pyplot.figure. axis - Alternative to figure, can pass an axis instance and use it as the plotting canvas clear - Clear the axis before plotting? """ # figure out where to put the plot if isinstance(figure,matplotlib.figure.Figure): self.figure = figure self.axis = self.figure.gca() elif type(figure) is int: self.figure = matplotlib.pyplot.figure(figure) self.axis = self.figure.gca() elif self.figure is None: if isinstance(axis,matplotlib.axes.Axes): self.axis = axis self.figure = axis.figure else: self.figure = matplotlib.pyplot.figure() if not matplotlib.pyplot.fignum_exists(self.figure.number): self.figure = matplotlib.pyplot.figure(self.figure.number) # always re-connect the interactive keys to avoid frustration... self._mpl_reconnect() if axis is not None: self._mpl_disconnect() self.axis = axis self.figure = axis.figure self._mpl_connect() elif len(self.figure.axes) > 0 and self.axis is None: self.axis = self.figure.axes[0] # default to first axis elif self.axis is None: self.axis = self.figure.gca() # A check to deal with issue #117: if you close the figure, the axis # still exists, but it cannot be reattached to a figure if not (self.axis.get_figure() is matplotlib.pyplot.figure(self.axis.get_figure().number)): self.axis = self.figure.gca() if self.axis is not None and self.axis not in self.figure.axes: # if you've cleared the axis, but the figure is still open, you # need a new axis self.figure.add_axes(self.axis) if clear and self.axis is not None: self.axis.clear() # Need to empty the stored model plots if hasattr(self.Spectrum, 'fitter'): self.Spectrum.fitter.clear() if autorefresh is not None: self.autorefresh = autorefresh self.plotscale = plotscale if self.plotkwargs and not override_plotkwargs: self.plotkwargs.update(kwargs) else: self.plotkwargs = kwargs self.plot(**kwargs) def _mpl_connect(self): if self.keyclick is None: self.keyclick = self.figure.canvas.mpl_connect('key_press_event',self.parse_keys) def _mpl_disconnect(self): self.figure.canvas.mpl_disconnect(self.keyclick) self.keyclick = None def _mpl_reconnect(self): self._mpl_disconnect() self._mpl_connect() # disable fullscreen & grid matplotlib.pyplot.rcParams['keymap.fullscreen'] = 'ctrl+f' matplotlib.pyplot.rcParams['keymap.grid'] = 'ctrl+g' def plot(self, offset=0.0, xoffset=0.0, color='k', linestyle='steps-mid', linewidth=0.5, errstyle=None, erralpha=0.2, errcolor=None, silent=None, reset=True, refresh=True, use_window_limits=None, useOffset=False, **kwargs): """ Plot the spectrum! Tries to automatically find a reasonable plotting range if one is not set. Parameters ---------- offset : float vertical offset to add to the spectrum before plotting. Useful if you want to overlay multiple spectra on a single plot xoffset: float An x-axis shift. I don't know why you'd want this... color : str default to plotting spectrum in black linestyle : 'steps-mid' or str 'steps-mid' for histogram-style plotting. See matplotlib's plot for more information linewidth : float Line width in pixels. Narrow lines are helpful when histo-plotting errstyle : 'fill', 'bars', or None can be "fill", which draws partially transparent boxes around the data to show the error region, or "bars" which draws standard errorbars. ``None`` will display no errorbars useOffset : bool Use offset-style X/Y coordinates (e.g., 1 + 1.483e10)? Defaults to False because these are usually quite annoying. xmin/xmax/ymin/ymax : float override defaults for plot range. Once set, these parameters are sticky (i.e., replotting will use the same ranges). Passed to `reset_limits` reset_[xy]limits : bool Reset the limits to "sensible defaults". Passed to `reset_limits` ypeakscale : float Scale up the Y maximum value. Useful to keep the annotations away from the data. Passed to `reset_limits` reset : bool Reset the x/y axis limits? If set, `reset_limits` will be called. """ if self.axis is None: raise Exception("You must call the Plotter class to initiate the canvas before plotting.") self.offset = offset # there is a bug where this only seems to update the second time it is called self.label(**kwargs) self.label(**kwargs) for arg in ['title','xlabel','ylabel']: if arg in kwargs: kwargs.pop(arg) reset_kwargs = {} for arg in ['xmin', 'xmax', 'ymin', 'ymax', 'reset_xlimits', 'reset_ylimits', 'ypeakscale']: if arg in kwargs: reset_kwargs[arg] = kwargs.pop(arg) if (use_window_limits is None and any(k in reset_kwargs for k in ('xmin','xmax','reset_xlimits'))): use_window_limits = False if use_window_limits: self._stash_window_limits() # for filled errorbars, order matters. inds = np.argsort(self.Spectrum.xarr) if errstyle is not None: if errcolor is None: errcolor = color if errstyle == 'fill': self.errorplot = [self.axis.fill_between(steppify(self.Spectrum.xarr.value[inds]+xoffset, isX=True), steppify((self.Spectrum.data*self.plotscale+self.offset-self.Spectrum.error*self.plotscale)[inds]), steppify((self.Spectrum.data*self.plotscale+self.offset+self.Spectrum.error*self.plotscale)[inds]), facecolor=errcolor, edgecolor=errcolor, alpha=erralpha, **kwargs)] elif errstyle == 'bars': self.errorplot = self.axis.errorbar(self.Spectrum.xarr[inds].value+xoffset, self.Spectrum.data[inds]*self.plotscale+self.offset, yerr=self.Spectrum.error[inds]*self.plotscale, ecolor=errcolor, fmt='none', **kwargs) self._spectrumplot = self.axis.plot(self.Spectrum.xarr.value[inds]+xoffset, self.Spectrum.data[inds]*self.plotscale+self.offset, color=color, linestyle=linestyle, linewidth=linewidth, **kwargs) self.axis.ticklabel_format(useOffset=useOffset) if use_window_limits: self._reset_to_stashed_limits() if silent is not None: self.silent = silent if reset: self.reset_limits(use_window_limits=use_window_limits, **reset_kwargs) if self.autorefresh and refresh: self.refresh() def _stash_window_limits(self): self._window_limits = self.axis.get_xlim(),self.axis.get_ylim() if self.debug: print("Stashed window limits: ",self._window_limits) def _reset_to_stashed_limits(self): self.axis.set_xlim(*self._window_limits[0]) self.axis.set_ylim(*self._window_limits[1]) self.xmin,self.xmax = self._window_limits[0] self.ymin,self.ymax = self._window_limits[1] if self.debug: print("Recovered window limits: ",self._window_limits) def reset_limits(self, xmin=None, xmax=None, ymin=None, ymax=None, reset_xlimits=True, reset_ylimits=True, ypeakscale=1.2, silent=None, use_window_limits=False, **kwargs): """ Automatically or manually reset the plot limits """ # if not use_window_limits: use_window_limits = False if self.debug: frame = inspect.currentframe() args, _, _, values = inspect.getargvalues(frame) print(zip(args,values)) if use_window_limits: # this means DO NOT reset! # it simply sets self.[xy][min/max] = current value self.set_limits_from_visible_window() else: if silent is not None: self.silent = silent # if self.xmin and self.xmax: if (reset_xlimits or self.Spectrum.xarr.min().value < self.xmin or self.Spectrum.xarr.max().value > self.xmax): if not self.silent: warn("Resetting X-axis min/max because the plot is out of bounds.") self.xmin = None self.xmax = None if xmin is not None: self.xmin = u.Quantity(xmin, self._xunit) elif self.xmin is None: self.xmin = u.Quantity(self.Spectrum.xarr.min().value, self._xunit) if xmax is not None: self.xmax = u.Quantity(xmax, self._xunit) elif self.xmax is None: self.xmax = u.Quantity(self.Spectrum.xarr.max().value, self._xunit) xpixmin = np.argmin(np.abs(self.Spectrum.xarr.value-self.xmin.value)) xpixmax = np.argmin(np.abs(self.Spectrum.xarr.value-self.xmax.value)) if xpixmin>xpixmax: xpixmin,xpixmax = xpixmax,xpixmin elif xpixmin == xpixmax: if reset_xlimits: raise Exception("Infinite recursion error. Maybe there are no valid data?") if not self.silent: warn("ERROR: the X axis limits specified were invalid. Resetting.") self.reset_limits(reset_xlimits=True, ymin=ymin, ymax=ymax, reset_ylimits=reset_ylimits, ypeakscale=ypeakscale, **kwargs) return if self.ymin and self.ymax: # this is utter nonsense.... if (self.Spectrum.data.max() < self.ymin or self.Spectrum.data.min() > self.ymax or reset_ylimits): if not self.silent and not reset_ylimits: warn("Resetting Y-axis min/max because the plot is out of bounds.") self.ymin = None self.ymax = None if ymin is not None: self.ymin = ymin elif self.ymin is None: if hasattr(self.Spectrum.data, 'mask'): yminval = self.Spectrum.data[xpixmin:xpixmax].min() else: yminval = np.nanmin(self.Spectrum.data[xpixmin:xpixmax]) # Increase the range fractionally. This means dividing a positive #, multiplying a negative # if yminval < 0: self.ymin = float(yminval)*float(ypeakscale) else: self.ymin = float(yminval)/float(ypeakscale) if ymax is not None: self.ymax = ymax elif self.ymax is None: if hasattr(self.Spectrum.data, 'mask'): ymaxval = ((self.Spectrum.data[xpixmin:xpixmax]).max()-self.ymin) else: ymaxval = (np.nanmax(self.Spectrum.data[xpixmin:xpixmax])-self.ymin) if ymaxval > 0: self.ymax = float(ymaxval) * float(ypeakscale) + self.ymin else: self.ymax = float(ymaxval) / float(ypeakscale) + self.ymin self.ymin += self.offset self.ymax += self.offset self.axis.set_xlim(self.xmin.value if hasattr(self.xmin, 'value') else self.xmin, self.xmax.value if hasattr(self.xmax, 'value') else self.xmax) self.axis.set_ylim(self.ymin, self.ymax) def label(self, title=None, xlabel=None, ylabel=None, verbose_label=False, **kwargs): """ Label the plot, with an attempt to parse standard units into nice latex labels Parameters ---------- title : str xlabel : str ylabel : str verbose_label: bool """ if title is not None: self.title = title elif hasattr(self.Spectrum,'specname'): self.title = self.Spectrum.specname if self.title is not "": self.axis.set_title(self.title) if xlabel is not None: self.xlabel = xlabel elif self._xunit: # WAS: self.xlabel = self.Spectrum.xarr.xtype.title() try: self.xlabel = xlabel_table[self._xunit.physical_type.lower()] except KeyError: self.xlabel = self._xunit.physical_type.title() # WAS: self.xlabel += " ("+u.Unit(self._xunit).to_string()+")" self.xlabel += " ({0})".format(self._xunit.to_string()) if verbose_label: self.xlabel = "%s %s" % (self.Spectrum.xarr.velocity_convention.title(), self.xlabel) if self.xlabel is not None: self.axis.set_xlabel(self.xlabel) if ylabel is not None: self.axis.set_ylabel(ylabel) elif self.Spectrum.unit in ['Ta*','Tastar']: self.axis.set_ylabel("$T_A^*$ (K)") elif self.Spectrum.unit in ['K']: self.axis.set_ylabel("Brightness Temperature $T$ (K)") elif self.Spectrum.unit == 'mJy': self.axis.set_ylabel("$S_\\nu$ (mJy)") elif self.Spectrum.unit == 'Jy': self.axis.set_ylabel("$S_\\nu$ (Jy)") else: if isinstance(self.Spectrum.unit, str) and "$" in self.Spectrum.unit: # assume LaTeX already self.axis.set_ylabel(self.Spectrum.unit) elif isinstance(self.Spectrum.unit, str): self.axis.set_ylabel(self.Spectrum.unit) else: label_units = self.Spectrum.unit.to_string(format='latex') if 'mathring{A}' in label_units: label_units = label_units.replace('\mathring{A}', 'A') if '\overset' in label_units: label_units = label_units.replace('\overset', '^') self.axis.set_ylabel(label_units) @property def ylabel(self): return self.axis.get_ylabel() def refresh(self): if self.axis is not None: self.axis.figure.canvas.draw() def savefig(self,fname,bbox_inches='tight',**kwargs): """ simple wrapper of maplotlib's savefig. """ self.axis.figure.savefig(fname,bbox_inches=bbox_inches,**kwargs) def parse_keys(self,event): """ Parse key commands entered from the keyboard """ if hasattr(event,'key'): if event.key == '?': print(interactive_help_message) elif event.key == 'f': print("\n\nFitter initiated from the interactive plotter.") # extra optional text: # Matplotlib shortcut keys ('g','l','p',etc.) are disabled. Re-enable with 'r'" self._disconnect_matplotlib_keys() self.Spectrum.specfit(interactive=True) if not hasattr(self,'FitterTool') and self.automake_fitter_tool: self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif hasattr(self,'FitterTool') and self.FitterTool.toolfig.number not in matplotlib.pyplot.get_fignums(): self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif event.key is not None and event.key.lower() == 'b': if event.key == 'b': print("\n\nBaseline initiated from the interactive plotter") elif event.key == 'B': print("\n\nBaseline initiated from the interactive plotter (with reset)") print("Matplotlib shortcut keys ('g','l','p',etc.) are disabled. Re-enable with 'r'") self._disconnect_matplotlib_keys() self.Spectrum.baseline(interactive=True, reset_selection=(event.key=='B')) if not hasattr(self,'FitterTool') and self.automake_fitter_tool: self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif hasattr(self,'FitterTool') and self.FitterTool.toolfig.number not in matplotlib.pyplot.get_fignums(): self.FitterTool = widgets.FitterTools(self.Spectrum.specfit, self.figure) elif event.key == 'r': # print("\n\nReconnected matplotlib shortcut keys.") self._reconnect_matplotlib_keys() elif event.key == 'R': self() elif event.key == 'i': self.Spectrum.specfit.plot_fit(show_components=True) def get_two_clicks(self,event): if self._xclick1 is None: self._xclick1 = event.xdata elif self._xclick2 is None: self._xclick2 = event.xdata def set_limits_from_visible_window(self, debug=False): """ Hopefully self-descriptive: set the x and y limits from the currently visible window (use this if you use the pan/zoom tools or manually change the limits) """ if debug: print("Changing x limits from %f,%f to %f,%f" % (self.xmin,self.xmax,self.axis.get_xlim()[0],self.axis.get_xlim()[1])) print("Changing y limits from %f,%f to %f,%f" % (self.ymin,self.ymax,self.axis.get_ylim()[0],self.axis.get_ylim()[1])) self.xmin, self.xmax = self.axis.get_xlim() self.ymin, self.ymax = self.axis.get_ylim() if debug: print("New x limits %f,%f == %f,%f" % (self.xmin,self.xmax,self.axis.get_xlim()[0],self.axis.get_xlim()[1])) print("New y limits %f,%f == %f,%f" % (self.ymin,self.ymax,self.axis.get_ylim()[0],self.axis.get_ylim()[1])) def copy(self, parent=None): """ Create a copy of the plotter with blank (uninitialized) axis & figure [ parent ] A spectroscopic axis instance that is the parent of the specfit instance. This needs to be specified at some point, but defaults to None to prevent overwriting a previous plot. """ newplotter = copy.copy(self) newplotter.Spectrum = parent newplotter.axis = None newplotter.figure = None return newplotter def line_ids(self, line_names, line_xvals, xval_units=None, auto_yloc=True, velocity_offset=None, velocity_convention='radio', auto_yloc_fraction=0.9, **kwargs): """ Add line ID labels to a plot using lineid_plot http://oneau.wordpress.com/2011/10/01/line-id-plot/ https://github.com/phn/lineid_plot http://packages.python.org/lineid_plot/ Parameters ---------- line_names : list A list of strings to label the specified x-axis values line_xvals : list List of x-axis values (e.g., wavelengths) at which to label the lines. Can be a list of quantities. xval_units : string The unit of the line_xvals if they are not given as quantities velocity_offset : quantity A velocity offset to apply to the inputs if they are in frequency or wavelength units velocity_convention : 'radio' or 'optical' or 'doppler' Used if the velocity offset is given auto_yloc : bool If set, overrides box_loc and arrow_tip (the vertical position of the lineid labels) in kwargs to be `auto_yloc_fraction` of the plot range auto_yloc_fraction: float in range [0,1] The fraction of the plot (vertically) at which to place labels Examples -------- >>> import numpy as np >>> import pyspeckit >>> sp = pyspeckit.Spectrum( xarr=pyspeckit.units.SpectroscopicAxis(np.linspace(-50,50,101), unit='km/s', refX=6562.8, refX_unit='angstrom'), data=np.random.randn(101), error=np.ones(101)) >>> sp.plotter() >>> sp.plotter.line_ids(['H$\\alpha$'],[6562.8],xval_units='angstrom') """ import lineid_plot if velocity_offset is not None: assert velocity_offset.unit.is_equivalent(u.km/u.s) doppler = getattr(u, 'doppler_{0}'.format(velocity_convention)) equivalency = doppler(self.Spectrum.xarr.refX) xvals = [] for xv in line_xvals: if hasattr(xv, 'unit'): pass else: xv = u.Quantity(xv, xval_units) xv = xv.to(u.km/u.s, equivalencies=equivalency) if velocity_offset is not None: xv = xv + velocity_offset xv = xv.to(self.Spectrum.xarr.unit, equivalencies=equivalency) xvals.append(xv.value) if auto_yloc: yr = self.axis.get_ylim() kwargs['box_loc'] = (yr[1]-yr[0])*auto_yloc_fraction + yr[0] kwargs['arrow_tip'] = (yr[1]-yr[0])*(auto_yloc_fraction*0.9) + yr[0] lineid_plot.plot_line_ids(self.Spectrum.xarr, self.Spectrum.data, xvals, line_names, ax=self.axis, **kwargs) def line_ids_from_measurements(self, auto_yloc=True, auto_yloc_fraction=0.9, **kwargs): """ Add line ID labels to a plot using lineid_plot http://oneau.wordpress.com/2011/10/01/line-id-plot/ https://github.com/phn/lineid_plot http://packages.python.org/lineid_plot/ Parameters ---------- auto_yloc : bool If set, overrides box_loc and arrow_tip (the vertical position of the lineid labels) in kwargs to be `auto_yloc_fraction` of the plot range auto_yloc_fraction: float in range [0,1] The fraction of the plot (vertically) at which to place labels Examples -------- >>> import numpy as np >>> import pyspeckit >>> sp = pyspeckit.Spectrum( xarr=pyspeckit.units.SpectroscopicAxis(np.linspace(-50,50,101), units='km/s', refX=6562.8, refX_unit='angstroms'), data=np.random.randn(101), error=np.ones(101)) >>> sp.plotter() >>> sp.specfit(multifit=None, fittype='gaussian', guesses=[1,0,1]) # fitting noise.... >>> sp.measure() >>> sp.plotter.line_ids_from_measurements() """ import lineid_plot if hasattr(self.Spectrum,'measurements'): measurements = self.Spectrum.measurements if auto_yloc: yr = self.axis.get_ylim() kwargs['box_loc'] = (yr[1]-yr[0])*auto_yloc_fraction + yr[0] kwargs['arrow_tip'] = (yr[1]-yr[0])*(auto_yloc_fraction*0.9) + yr[0] lineid_plot.plot_line_ids(self.Spectrum.xarr, self.Spectrum.data, [v['pos'] for v in measurements.lines.values()], measurements.lines.keys(), ax=self.axis, **kwargs) else: warn("Cannot add line IDs from measurements unless measurements have been made!") def parse_units(labelstring): import re labelstring = re.sub("um","$\mu$m",labelstring) labelstring = re.sub("-1","$^{-1}$",labelstring) labelstring = re.sub("-2","$^{-2}$",labelstring) labelstring = re.sub("-3","$^{-3}$",labelstring) labelstring = re.sub("ergss","ergs s",labelstring) return labelstring def parse_norm(norm): """ Expected format: norm = 10E15 """ try: base, exp = norm.split('E') except ValueError: base, exp = norm.split('e') if float(base) == 1.0: norm = '10' else: norm = base norm += '^{%s}' % exp return norm def steppify(arr,isX=False): """ *support function* Converts an array to double-length for step plotting """ if isX: interval = abs(arr[1:]-arr[:-1]) / 2.0 newarr = np.array(list(zip(arr[:-1]-interval,arr[:-1]+interval))).ravel() newarr = np.concatenate([newarr,2*[newarr[-1]+interval[-1]]]) else: newarr = np.array(list(zip(arr,arr))).ravel() return newarr

mikelum/pyspeckit

pyspeckit/spectrum/plotters.py

Python

mit

31,130

[ "Gaussian" ]

9cc62897613a994bdd8d2f4170d1b87e32bd5b29b76e3db73821152e187871ed

# Copyright 2000 by Andrew Dalke. All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. # The Prosite patterns are defined at http://www.expasy.ch/txt/prosuser.txt # # The PA (PAttern) lines contains the definition of a PROSITE pattern. The # patterns are described using the following conventions: # # - The standard IUPAC one-letter codes for the amino acids are used. # - The symbol `x' is used for a position where any amino acid is accepted. # - Ambiguities are indicated by listing the acceptable amino acids for a # given position, between square parentheses `[ ]'. For example: [ALT] # stands for Ala or Leu or Thr. # - Ambiguities are also indicated by listing between a pair of curly # brackets `{ }' the amino acids that are not accepted at a given # position. For example: {AM} stands for any amino acid except Ala and # Met. # - Each element in a pattern is separated from its neighbor by a `-'. # - Repetition of an element of the pattern can be indicated by following # that element with a numerical value or a numerical range between # parenthesis. Examples: x(3) corresponds to x-x-x, x(2,4) corresponds to # x-x or x-x-x or x-x-x-x. # - When a pattern is restricted to either the N- or C-terminal of a # sequence, that pattern either starts with a `<' symbol or respectively # ends with a `>' symbol. # - A period ends the pattern. # # That boils down to doing these conversions # # [] -> [] # {} -> [^ ] # - -> # () -> {} # < -> ^ # > -> $ # x->X # . -> # Note: # [G>] is a valid Prosite pattern, equivalent to "([G]|$)" # I assume then that # [>G] is equivalent to "(^|[G])" # It is conceivable that [G>]-G-G is valid, meaning a "G" at the end # of the sequence or followed by two more Gs. I did not implement # this. I haven't gotten an answer to my query on either of these two # non-documented possibilities. import string, re from Bio import Seq, Alphabet # Syntactic conversion to two types of regular expressions _prosite_trans = string.maketrans("abcdefghijklmnopqrstuvwxyzX}()<>", "ABCDEFGHIJKLMNOPQRSTUVW.YZ.]{}^$") # This does not verify that the pattern is correct - invalid patterns # can be converted! def prosite_to_re(pattern): """convert a valid Prosite pattern into an re string""" flg = (pattern[:2] == "[<") s = pattern.replace("{", "[^") s = s.translate(_prosite_trans, "-.") # special case "[<" and ">]", if they exist if flg: i = s.index("]") s = "(?:^|[" + s[2:i] + "])" + s[i+1:] if s[-2:] == "$]": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-2] + "]|$)" elif s[-3:] == "$]$": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-3] + "]|$)$" return s # This does not verify the pattern is correct - invalid patterns can # be converted! def prosite_to_grouped_re(pattern): """convert a valid Prosite pattern into an re with groups for each term""" flg = (pattern[:2] == "[<") s = pattern.replace("{", "[^") # Don't delete the "-" characters: use them to place the ()s s = s.translate(_prosite_trans, ".") # Get the [< and >] terms correct if flg: i = s.index("]") s = "(?:^|[" + s[2:i] + "])" + s[i+1:] if s[-2:] == "$]": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-2] + "]|$)" if s[-3:] == "$]$": i = s.rindex("[") s = s[:i] + "(?:" + s[i:-3] + "]|$)$" # Watch out for unescaped < and > terms if s[:1] == "^": s = "^(" + s[1:] else: s = "(" + s if s[-1:] == "$": s = s[:-1] + ")$" else: s = s + ")" return s.replace("-", ")(") # Both the Prosite pattern and match result act like sequences. class PrositeAlphabet(Alphabet.Alphabet): pass prosite_alphabet = PrositeAlphabet() def compile(pattern): if not verify_pattern(pattern): raise TypeError("not a legal prosite pattern") return Prosite(pattern = pattern) class Prosite: alphabet = prosite_alphabet # Don't like having two different types of input - not very pythonic # However, it is faster since I can assume the input has already been # verified (if it's a pattern). def __init__(self, pattern = None, data = None): assert (pattern is None and data is not None) ^ \ (pattern is not None and data is None), \ "one and only one of pattern and data can have a value" if pattern is not None: self.pattern = pattern if data is not None: self.data = data def __repr__(self): return "Prosite(%s)" % repr(str(self)) def __str__(self): return '-'.join(map(str, self.data)) + "." def __len__(self): return len(self.data) def __getitem__(self, i): return self.data[i] def __getslice__(self, i, j): i = max(i, 0); j = max(j, 0) return Prosite(data = self.data[i:j]) def __getattr__(self, name): # Lazy creation of these elements / cache results if name == "re": self.re = re.compile(prosite_to_re(self.pattern)) return self.re elif name == "grouped_re": self.grouped_re = re.compile(prosite_to_grouped_re(self.pattern)) return self.grouped_re elif name == "data": self.data = find_terms(self.pattern) return self.data elif name == "pattern": self.pattern = str(self) return self.pattern raise AttributeError(name) def tostring(self): return str(self) def search(self, seq, pos=0, endpos=None): if endpos is not None: m = self.grouped_re.search(buffer(seq.tostring()), pos, endpos) else: m = self.grouped_re.search(buffer(seq.tostring()), pos) if m is None: return None return PrositeMatch(self, seq, m) def match(self, seq, pos=0, endpos=None): if endpos is not None: m = self.grouped_re.match(buffer(seq.tostring()), pos, endpos) else: m = self.grouped_re.match(buffer(seq.tostring()), pos) if m is None: return None return PrositeMatch(self, seq, m) # I was thinking about adding sub, subn, findall, etc., but either # you just want the string (in which case, use the ".re") or # you could be changing to a different alphabet (eg, T->U). # Elements of a Prosite pattern class PrositeTerm: def __init__(self, letters, ignore, is_begin, is_end, \ min_count, max_count, can_begin, can_end): self.letters = letters self.ignore = ignore self.is_begin = is_begin self.is_end = is_end self.min_count = min_count self.max_count = max_count self.can_begin = can_begin self.can_end = can_end def copy(self): return PrositeTerm(self.letters, self.ignore, self.is_begin, self.is_end, self.min_count, self.max_count, self.can_begin, self.can_end) def __str__(self): # Convert the term back into Prosite form s = self.base_str() if self.min_count == self.max_count: if self.min_count == 1: pass else: s = s + "(%d)" % self.min_count else: s = s + "(%d,%d)" % (self.min_count, self.max_count) if self.is_end: s = s + ">" return s def base_str(self): # Convert the term back into Prosite form, without the repeat # count fields. if self.is_begin: s = "<" else: s = "" if self.ignore: s = s + "{" + self.letters + "}" elif len(self.letters) == 1 and \ (not self.can_begin and not self.can_end): s = s + self.letters else: s = s + "[" if self.can_begin: s = s + "<" s = s + self.letters if self.can_end: s = s + ">" s = s + "]" return s # Results of a Prosite match. Wrapper to the re.MatchObj, but returns # Seq objects instead of strings. And lookee - it implements the Seq # interface too! class PrositeMatch: def __init__(self, prosite, seq, match): self.prosite = prosite self.seq = seq self.match = match self.pos = match.pos self.endpos = match.pos # for Seq.Seq initialization self.data = match.group(0) self.alphabet = seq.alphabet def __repr__(self): # XXX this isn't the right way return "<PrositeMatch instance at %x>" % id(self) def __str__(self): return str(self.data) def __len__(self): return len(self.data) def __getitem__(self, i): return self.data[i] def __getslice__(self, i, j): i = max(i, 0); j = max(j, 0) return Seq.Seq(self.data[i:j], self.alphabet) def mapping(self): """return a list of numbers mapping to items of the original pattern For example, if the Prosite pattern is "[AP](2)-D." matched against "PAD", then the mapping is [1, 1, 2], meaning the first character of the match ("P") is from the first Prosite group ("[AP]"), as is the second letter ("A"). The 3rd letter ("D") is mapped to group 2 of the pattern. """ vals = [] i = 0 start = self.start(0) try: while 1: end = self.match.end(i+1) while start < end: vals.append(i) start = start + 1 i = i + 1 except IndexError: pass return vals def mapped_pattern(self): """returns the specific Prosite pattern used to find this sequence >>> p = Prosite.compile("[AP](2,3)-D.") >>> m = p.search(Seq.Seq("PAD")) >>> mapping = m.mapping() >>> mapped = m.mapped_pattern() >>> print str(m[1]), str(p[mapping[1]]), str(mapped[1]) P [AP](2,3) [AP] >>> print str(mapped) [AP]-[AP]-D. >>> Note that the original term includes the count, while the mapped pattern does the expansion. """ return pattern_mapping(self.prosite, self.mapping()) def start(self, g=0): return self.match.start(g) def end(self, g=0): return self.match.end(g) def span(self, g): return self.match.span(g) def groups(self, default=None): result = [] alphabet = self.alphabet for g in self.match.groups(default): result.append( Seq.Seq(g, alphabet) ) return tuple(result) def group(self, *groups): result = self.match.group(*groups) if result == (): return result if len(result) == 1: return Seq.Seq(result, self.alphabet) retval = [] for x in result: retval.append(Seq.Seq(x, self.alphabet)) return tuple(retval) def pattern_mapping(prosite, mapping): data = [] for i in mapping: x = prosite[i].copy() x.min_count = x.max_count = 1 data.append(x) return Prosite(data=data) prosite_term_re = re.compile(r""" (?: ([ABCDEFGHIKLMNPQRSTVWXYZx])| # a character OR \[(<?)([ABCDEFGHIKLMNPQRSTVWXYZ]+)(>?)\]| # something in []s OR \{([ABCDEFGHIKLMNPQRSTVWXYZ]+)\} # something in {}s )(?:$(\d+)(,\d+)?$)? # optional count of the form "(i,j)", ",j" optional $ """, re.VERBOSE) # This does not verify the pattern is correct - invalid patterns can # be converted! def find_terms(pattern): if pattern[-1:] != ".": raise TypeError("not a prosite pattern - needs a final '.'") pattern = pattern[:-1] terms = pattern.split("-") result = [] i = 0 for term in terms: can_begin = can_end = 0 # Starts with a "<"? if term[:1] == "<": term = term[1:] is_begin = 1 else: is_begin = 0 # Ends with a ">"? if term[-1:] == ">": term = term[:-1] is_end = 1 else: is_end = 0 match = prosite_term_re.match(term) if match is None: raise TypeError("not a Prosite term (%s)" % repr(term)) if match.group(1) is not None: # Single letter ignore = 0 letters = match.group(1) elif match.group(3) is not None: # Letters inside of "[]"s ignore = 0 letters = match.group(3) if match.group(2): can_begin = 1 if i != 0: raise TypeError("[<] only allowed for first term (%s)" \ % repr(term)) if match.group(4): can_end = 1 if i != len(terms) - 1: raise TypeError("[>] only allowed for last term (%s)" \ % repr(term)) elif match.group(5) is not None: # Letters inside of "{}"s ignore = 1 letters = match.group(5) else: raise TypeError("not a prosite term (%s)" % repr(term)) if match.group(6) is not None: # there is a minimum number min_count = int(match.group(6)) else: # no min, so it's 1 min_count = 1 if match.group(7) is not None: # there is a maximum number max_count = int(match.group(7)[1:]) else: # no max specified, so use the same as the min max_count = min_count result.append(PrositeTerm(letters, ignore, is_begin, is_end, min_count, max_count, can_begin, can_end)) i = i + 1 return result prosite_re = re.compile(r""" ^<? # starts with an optional "<" ( [ABCDEFGHIKLMNPQRSTVWXYZx]| # a character OR (\[<?[ABCDEFGHIKLMNPQRSTVWXYZ]+>?\])| # something in []s OR \{[ABCDEFGHIKLMNPQRSTVWXYZ]+\} # something in {}s )($\d+(,\d+)?$)? # optional count of the form "(i,j)" (",j" is optional) (- # new terms seperated by a '-' ( [ABCDEFGHIKLMNPQRSTVWXYZx]| # a character OR \[[ABCDEFGHIKLMNPQRSTVWXYZ]+>?\]| # something in []s OR \{[ABCDEFGHIKLMNPQRSTVWXYZ]+\} # something in {}s )($\d+(,\d+)?$)? # optional count )* # repeat until done >? # pattern ends with an optional ">" \.$ # description ends with a required "." """, re.VERBOSE) # This verifies the pattern is correct. def verify_pattern(pattern): """returns 1 if the Prosite pattern is syntactically correct, else 0""" x = prosite_re.match(pattern) if x is None: return 0 # check there's only one [< at the beginning, or >] at the end if pattern.find("[<", 1) != -1: return 0 if pattern.find(">]", 0, len(pattern)-2) != -1: return 0 return 1 def _verify_test(infile): """verify the patterns from a Prosite file handle""" pattern = "" while 1: line = infile.readline() if not line: break if line[:2] != "PA": continue pattern = pattern + line[5:-1] if line[-2] == ".": try: print "*" * 60 print pattern p = compile(pattern) print prosite_to_re(pattern) print repr(p.re) print prosite_to_grouped_re(pattern) print repr(p.grouped_re) terms = str(p) if terms != pattern: print "DIFFER", terms, pattern except TypeError, msg: print "PROBLEM", pattern, msg pattern = "" # Commented out by jchang 4/13/00. # Specific to Andrew's test environment. #if __name__ == "__main__": # import os # infile = os.popen("bzcat /home/dalke/ftps/prosite/prosite.dat.bz2 | grep ^PA") # _verify_test(infile)

BlogomaticProject/Blogomatic

opt/blog-o-matic/usr/lib/python/Bio/Prosite/Pattern.py

Python

gpl-2.0

16,587

[ "Biopython" ]

61bc6d0fe983802639276b2f58443f70563a26a73b7b9eecbf2c3d6428db449a

""" Uniweb validator project w3c.py : Checks URL against W3C validators in various ways Copyright (c) 2009 Brian Shumate Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"), to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense, and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions: The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software. THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. """ import datetime import httplib2 import urllib2 from datetime import timedelta from BeautifulSoup import BeautifulSoup from surfbot.validator.models import Website def checkhtml(site_pk): """ Checks URL against W3C HTML validator website Eventually, this will be pointed directly at a local instance as part of the whole appliance idea. """ today = datetime.date.today() w3chtml = "http://validator.w3.org/check?uri=" w = Website.objects.get(pk=site_pk) w.checkok = False w.htmlval = 'Fail' w.lastcheck = today week = timedelta(days=7) day = timedelta(hours=24) h = httplib2.Http(".cache") resp, content = h.request(w3chtml + w.rooturl, "GET") validator = BeautifulSoup(content) if validator.find('h3', 'invalid'): w.checkok = True w.nextcheck = today + day w.checktotal += 1 w.htmlval = 'Fail' w.htmlval_fcount += 1 w.save() return w.htmlval else: w.checkok = True w.nextcheck = today + week w.checktotal += 1 w.htmlval = 'Pass' w.htmlval_pcount += 1 w.save() return w.htmlval def checkcss(site_pk): """ Checks URL against W3C CSS validator website """ today = datetime.date.today() w3ccss = "http://jigsaw.w3.org/css-validator/validator?uri=" w = Website.objects.get(pk=site_pk) w.checkok = False w.cssval = 'Fail' w.lastcheck = today week = timedelta(days=7) day = timedelta(hours=24) h = httplib2.Http(".cache") resp, content = h.request(w3ccss + w.rooturl, "GET") validator = BeautifulSoup(content) if validator.find('div', id='errors'): w.checkok = True w.nextcheck = today + day w.checktotal += 1 w.cssval = 'Fail' w.cssval_fcount += 1 w.save() return w.cssval else: w.checkok = True w.nextcheck = today + week w.checktotal += 1 w.cssval = 'Pass' w.cssval_pcount += 1 w.save() return w.cssval

brianshumate/uniweb

surfbot/utils/w3c.py

Python

bsd-2-clause

3,219

[ "Brian" ]

13f910fd6b559f01446cac87f4b287fc2abd08956a2775895d7a9174147b2657

""" Extremely simple utility class to send mails """ import os import socket from smtplib import SMTP, SMTP_SSL from email.mime.application import MIMEApplication from email.mime.multipart import MIMEMultipart from email.mime.text import MIMEText from getpass import getuser from DIRAC import gLogger, S_OK, S_ERROR class Mail(object): def __init__(self): self._subject = "" self._message = "" self._mailAddress = "" self._html = False self._fromAddress = getuser() + "@" + socket.getfqdn() self._attachments = [] self.esmtp_features = {} self._smtpPtcl = None self._smtpHost = None self._smtpPort = None self._smtpLogin = None self._smtpPasswd = None def _create(self, addresses): """create a mail object :param list addresses: addresses :return: S_OK(object)/S_ERROR() -- contain MIMEMultipart object """ if not isinstance(addresses, list): addresses = [addresses] if not self._mailAddress: gLogger.warn("No mail address was provided. Mail not sent.") return S_ERROR("No mail address was provided. Mail not sent.") if not self._message: gLogger.warn("Message body is empty") if not self._subject: gLogger.warn("Subject and body empty. Mail not sent") return S_ERROR("Subject and body empty. Mail not sent") if self._html: mail = MIMEText(self._message, "html") else: mail = MIMEText(self._message, "plain") msg = MIMEMultipart() msg.attach(mail) msg["Subject"] = self._subject msg["From"] = self._fromAddress msg["To"] = ", ".join(addresses) for attachment in self._attachments: try: with open(attachment, "rb") as fil: part = MIMEApplication(fil.read(), Name=os.path.basename(attachment)) part["Content-Disposition"] = 'attachment; filename="%s"' % os.path.basename(attachment) msg.attach(part) except IOError as e: gLogger.exception("Could not attach %s" % attachment, lException=e) return S_OK(msg) def _send(self, msg=None): """send a single email message. If msg is in input, it is expected to be of email type, otherwise it will create it. :param object msg: MIMEMultipart object :return: S_OK()/S_ERROR() """ if msg is None: addresses = self._mailAddress if isinstance(self._mailAddress, str): addresses = self._mailAddress.split(", ") result = self._create(addresses) if not result["OK"]: return result msg = result["Value"] if self._smtpPtcl == "SSL": smtp = SMTP_SSL() else: smtp = SMTP() smtp.set_debuglevel(0) try: connParams = {} if self._smtpHost: connParams["host"] = self._smtpHost if self._smtpPort: connParams["port"] = int(self._smtpPort) smtp.connect(**connParams) smtp.ehlo_or_helo_if_needed() if self._smtpPtcl == "TLS": smtp.starttls() if self._smtpLogin and self._smtpPasswd: smtp.login(self._smtpLogin, self._smtpPasswd) smtp.ehlo_or_helo_if_needed() smtp.sendmail(self._fromAddress, addresses, msg.as_string()) except Exception as x: return S_ERROR("Sending mail failed %s" % str(x)) smtp.quit() return S_OK("The mail was successfully sent") def __eq__(self, other): """Comparing an email object to another""" if isinstance(other, Mail): if self.__dict__ == other.__dict__: return True return False def __hash__(self): """Comparing for sets""" return hash(self._subject + self._message + self._fromAddress + self._mailAddress)

DIRACGrid/DIRAC

src/DIRAC/Core/Utilities/Mail.py

Python

gpl-3.0

4,124

[ "DIRAC" ]

e1a7568481552cec7beb8ab3ae2fa1917ece72acc0281d8c538724fff3ff2fbb

# Adapted from Bio.AlignIO.FastaIO copyright 2008-2011 by Peter Cock. # Copyright 2012 by Wibowo Arindrarto. # All rights reserved. # This code is part of the Biopython distribution and governed by its # license. Please see the LICENSE file that should have been included # as part of this package. """Bio.SearchIO support for Bill Pearson's FASTA tools. This module adds support for parsing FASTA outputs. FASTA is a suite of programs that finds regions of local or global similarity between protein or nucleotide sequences, either by searching databases or identifying local duplications. Bio.SearchIO.FastaIO was tested on the following FASTA flavors and versions: - flavors: fasta, ssearch, tfastx - versions: 35, 36 Other flavors and/or versions may introduce some bugs. Please file a bug report if you see such problems to Biopython's bug tracker. More information on FASTA are available through these links: - Website: http://fasta.bioch.virginia.edu/fasta_www2/fasta_list2.shtml - User guide: http://fasta.bioch.virginia.edu/fasta_www2/fasta_guide.pdf Supported Formats ================= Bio.SearchIO.FastaIO supports parsing and indexing FASTA outputs triggered by the -m 10 flag. Other formats that mimic other programs (e.g. the BLAST tabular format using the -m 8 flag) may be parseable but using SearchIO's other parsers (in this case, using the 'blast-tab' parser). fasta-m10 ========= Note that in FASTA -m 10 outputs, HSPs from different strands are considered to be from different hits. They are listed as two separate entries in the hit table. FastaIO recognizes this and will group HSPs with the same hit ID into a single Hit object, regardless of strand. FASTA also sometimes output extra sequences adjacent to the HSP match. These extra sequences are discarded by FastaIO. Only regions containing the actual sequence match are extracted. The following object attributes are provided: +-----------------+-------------------------+----------------------------------+ | Object | Attribute | Value | +=================+=========================+==================================+ | QueryResult | description | query sequence description | | +-------------------------+----------------------------------+ | | id | query sequence ID | | +-------------------------+----------------------------------+ | | program | FASTA flavor | | +-------------------------+----------------------------------+ | | seq_len | full length of query sequence | | +-------------------------+----------------------------------+ | | target | target search database | | +-------------------------+----------------------------------+ | | version | FASTA version | +-----------------+-------------------------+----------------------------------+ | Hit | seq_len | full length of the hit sequence | +-----------------+-------------------------+----------------------------------+ | HSP | bitscore | \*_bits line | | +-------------------------+----------------------------------+ | | evalue | \*_expect line | | +-------------------------+----------------------------------+ | | ident_pct | \*_ident line | | +-------------------------+----------------------------------+ | | init1_score | \*_init1 line | | +-------------------------+----------------------------------+ | | initn_score | \*_initn line | | +-------------------------+----------------------------------+ | | opt_score | \*_opt line, \*_s-w opt line | | +-------------------------+----------------------------------+ | | pos_pct | \*_sim line | | +-------------------------+----------------------------------+ | | sw_score | \*_score line | | +-------------------------+----------------------------------+ | | z_score | \*_z-score line | +-----------------+-------------------------+----------------------------------+ | HSPFragment | aln_annotation | al_cons block, if present | | (also via HSP) +-------------------------+----------------------------------+ | | hit | hit sequence | | +-------------------------+----------------------------------+ | | hit_end | hit sequence end coordinate | | +-------------------------+----------------------------------+ | | hit_start | hit sequence start coordinate | | +-------------------------+----------------------------------+ | | hit_strand | hit sequence strand | | +-------------------------+----------------------------------+ | | query | query sequence | | +-------------------------+----------------------------------+ | | query_end | query sequence end coordinate | | +-------------------------+----------------------------------+ | | query_start | query sequence start coordinate | | +-------------------------+----------------------------------+ | | query_strand | query sequence strand | +-----------------+-------------------------+----------------------------------+ """ import re from Bio._py3k import _as_bytes, _bytes_to_string from Bio.Alphabet import generic_dna, generic_protein from Bio.File import UndoHandle from Bio.SearchIO._index import SearchIndexer from Bio.SearchIO._model import QueryResult, Hit, HSP, HSPFragment __all__ = ['FastaM10Parser', 'FastaM10Indexer'] __docformat__ = "restructuredtext en" # precompile regex patterns # regex for program name _RE_FLAVS = re.compile(r't?fast[afmsxy]|pr[sf][sx]|lalign|[gs]?[glso]search') # regex for sequence ID and length ~ deals with both \n and \r\n _PTR_ID_DESC_SEQLEN = r'>>>(.+?)\s+(.*?) *- (\d+) (?:aa|nt)\s*$' _RE_ID_DESC_SEQLEN = re.compile(_PTR_ID_DESC_SEQLEN) _RE_ID_DESC_SEQLEN_IDX = re.compile(_as_bytes(_PTR_ID_DESC_SEQLEN)) # regex for qresult, hit, or hsp attribute value _RE_ATTR = re.compile(r'^; [a-z]+(_[ \w-]+):\s+(.*)$') # regex for capturing excess start and end sequences in alignments _RE_START_EXC = re.compile(r'^-*') _RE_END_EXC = re.compile(r'-*$') # attribute name mappings _HSP_ATTR_MAP = { '_initn': ('initn_score', int), '_init1': ('init1_score', int), '_opt': ('opt_score', int), '_s-w opt': ('opt_score', int), '_z-score': ('z_score', float), '_bits': ('bitscore', float), '_expect': ('evalue', float), '_score': ('sw_score', int), '_ident': ('ident_pct', float), '_sim': ('pos_pct', float), } # state flags _STATE_NONE = 0 _STATE_QUERY_BLOCK = 1 _STATE_HIT_BLOCK = 2 _STATE_CONS_BLOCK = 3 def _set_qresult_hits(qresult, hit_rows=[]): """Helper function for appending Hits without alignments into QueryResults.""" for hit_row in hit_rows: hit_id, remainder = hit_row.split(' ', 1) # TODO: parse hit and hsp properties properly; by dealing with: # - any character in the description (brackets, spaces, etc.) # - possible [f] or [r] presence (for frame info) # - possible presence of E2() column # - possible incomplete hit_id due to column length limit # The current method only looks at the Hit ID, none of the things above if hit_id not in qresult: frag = HSPFragment(hit_id, qresult.id) hsp = HSP([frag]) hit = Hit([hsp]) qresult.append(hit) return qresult def _set_hsp_seqs(hsp, parsed, program): """Helper function for the main parsing code. :param hsp: HSP whose properties will be set :type hsp: HSP :param parsed: parsed values of the HSP attributes :type parsed: dictionary {string: object} :param program: program name :type program: string """ # get aligned sequences and check if they have equal lengths start = 0 for seq_type in ('hit', 'query'): if 'tfast' not in program: pseq = parsed[seq_type] # adjust start and end coordinates based on the amount of # filler characters start, stop = _get_aln_slice_coords(pseq) start_adj = len(re.search(_RE_START_EXC, pseq['seq']).group(0)) stop_adj = len(re.search(_RE_END_EXC, pseq['seq']).group(0)) start = start + start_adj stop = stop + start_adj - stop_adj parsed[seq_type]['seq'] = pseq['seq'][start:stop] assert len(parsed['query']['seq']) == len(parsed['hit']['seq']), "%r %r" \ % (len(parsed['query']['seq']), len(parsed['hit']['seq'])) if 'similarity' in hsp.aln_annotation: # only using 'start' since FASTA seems to have trimmed the 'excess' # end part hsp.aln_annotation['similarity'] = hsp.aln_annotation['similarity'][start:] # hit or query works equally well here assert len(hsp.aln_annotation['similarity']) == len(parsed['hit']['seq']) # query and hit sequence types must be the same assert parsed['query']['_type'] == parsed['hit']['_type'] type_val = parsed['query']['_type'] # hit works fine too alphabet = generic_dna if type_val == 'D' else generic_protein setattr(hsp.fragment, 'alphabet', alphabet) for seq_type in ('hit', 'query'): # get and set start and end coordinates start = int(parsed[seq_type]['_start']) end = int(parsed[seq_type]['_stop']) setattr(hsp.fragment, seq_type + '_start', min(start, end) - 1) setattr(hsp.fragment, seq_type + '_end', max(start, end)) # set seq and alphabet setattr(hsp.fragment, seq_type, parsed[seq_type]['seq']) if alphabet is not generic_protein: # get strand from coordinate; start <= end is plus # start > end is minus if start <= end: setattr(hsp.fragment, seq_type + '_strand', 1) else: setattr(hsp.fragment, seq_type + '_strand', -1) else: setattr(hsp.fragment, seq_type + '_strand', 0) def _get_aln_slice_coords(parsed_hsp): """Helper function for the main parsing code. To get the actual pairwise alignment sequences, we must first translate the un-gapped sequence based coordinates into positions in the gapped sequence (which may have a flanking region shown using leading - characters). To date, I have never seen any trailing flanking region shown in the m10 file, but the following code should also cope with that. Note that this code seems to work fine even when the "sq_offset" entries are prsent as a result of using the -X command line option. """ seq = parsed_hsp['seq'] seq_stripped = seq.strip('-') disp_start = int(parsed_hsp['_display_start']) start = int(parsed_hsp['_start']) stop = int(parsed_hsp['_stop']) if start <= stop: start = start - disp_start stop = stop - disp_start + 1 else: start = disp_start - start stop = disp_start - stop + 1 stop += seq_stripped.count('-') assert 0 <= start and start < stop and stop <= len(seq_stripped), \ "Problem with sequence start/stop,\n%s[%i:%i]\n%s" \ % (seq, start, stop, parsed_hsp) return start, stop class FastaM10Parser(object): """Parser for Bill Pearson's FASTA suite's -m 10 output.""" def __init__(self, handle, __parse_hit_table=False): self.handle = UndoHandle(handle) self._preamble = self._parse_preamble() def __iter__(self): for qresult in self._parse_qresult(): # re-set desc, for hsp query description qresult.description = qresult.description yield qresult def _parse_preamble(self): """Parses the Fasta preamble for Fasta flavor and version.""" preamble = {} while True: self.line = self.handle.readline() # this should be the line just before the first qresult if self.line.startswith('Query'): break # try to match for version line elif self.line.startswith(' version'): preamble['version'] = self.line.split(' ')[2] else: # try to match for flavor line flav_match = re.match(_RE_FLAVS, self.line.lower()) if flav_match: preamble['program'] = flav_match.group(0) return preamble def __parse_hit_table(self): """Parses hit table rows.""" # move to the first row self.line = self.handle.readline() # parse hit table until we see an empty line hit_rows = [] while self.line and not self.line.strip(): hit_rows.append(self.line.strip()) self.line = self.handle.readline() return hit_rows def _parse_qresult(self): # initial qresult value qresult = None hit_rows = [] # state values state_QRES_NEW = 1 state_QRES_HITTAB = 3 state_QRES_CONTENT = 5 state_QRES_END = 7 while True: # one line before the hit table if self.line.startswith('The best scores are:'): qres_state = state_QRES_HITTAB # the end of a query or the file altogether elif self.line.strip() == '>>>///' or not self.line: qres_state = state_QRES_END # the beginning of a new query elif not self.line.startswith('>>>') and '>>>' in self.line: qres_state = state_QRES_NEW # the beginning of the query info and its hits + hsps elif self.line.startswith('>>>') and not \ self.line.strip() == '>>><<<': qres_state = state_QRES_CONTENT # default qres mark else: qres_state = None if qres_state is not None: if qres_state == state_QRES_HITTAB: # parse hit table if flag is set hit_rows = self.__parse_hit_table() elif qres_state == state_QRES_END: yield _set_qresult_hits(qresult, hit_rows) break elif qres_state == state_QRES_NEW: # if qresult is filled, yield it first if qresult is not None: yield _set_qresult_hits(qresult, hit_rows) regx = re.search(_RE_ID_DESC_SEQLEN, self.line) query_id = regx.group(1) seq_len = regx.group(3) desc = regx.group(2) qresult = QueryResult(id=query_id) qresult.seq_len = int(seq_len) # get target from the next line self.line = self.handle.readline() qresult.target = [x for x in self.line.split(' ') if x][1].strip() if desc is not None: qresult.description = desc # set values from preamble for key, value in self._preamble.items(): setattr(qresult, key, value) elif qres_state == state_QRES_CONTENT: assert self.line[3:].startswith(qresult.id), self.line for hit, strand in self._parse_hit(query_id): # HACK: re-set desc, for hsp hit and query description hit.description = hit.description hit.query_description = qresult.description # if hit is not in qresult, append it if hit.id not in qresult: qresult.append(hit) # otherwise, it might be the same hit with a different strand else: # make sure strand is different and then append hsp to # existing hit for hsp in hit.hsps: assert strand != hsp.query_strand qresult[hit.id].append(hsp) self.line = self.handle.readline() def _parse_hit(self, query_id): while True: self.line = self.handle.readline() if self.line.startswith('>>'): break state = _STATE_NONE strand = None hsp_list = [] while True: peekline = self.handle.peekline() # yield hit if we've reached the start of a new query or # the end of the search if peekline.strip() in [">>><<<", ">>>///"] or \ (not peekline.startswith('>>>') and '>>>' in peekline): # append last parsed_hsp['hit']['seq'] line if state == _STATE_HIT_BLOCK: parsed_hsp['hit']['seq'] += self.line.strip() elif state == _STATE_CONS_BLOCK: hsp.aln_annotation['similarity'] += \ self.line.strip('\r\n') # process HSP alignment and coordinates _set_hsp_seqs(hsp, parsed_hsp, self._preamble['program']) hit = Hit(hsp_list) hit.description = hit_desc hit.seq_len = seq_len yield hit, strand hsp_list = [] break # yield hit and create a new one if we're still in the same query elif self.line.startswith('>>'): # try yielding, if we have hsps if hsp_list: _set_hsp_seqs(hsp, parsed_hsp, self._preamble['program']) hit = Hit(hsp_list) hit.description = hit_desc hit.seq_len = seq_len yield hit, strand hsp_list = [] # try to get the hit id and desc, and handle cases without descs try: hit_id, hit_desc = self.line[2:].strip().split(' ', 1) except ValueError: hit_id = self.line[2:].strip().split(' ', 1)[0] hit_desc = '' # create the HSP object for Hit frag = HSPFragment(hit_id, query_id) hsp = HSP([frag]) hsp_list.append(hsp) # set or reset the state to none state = _STATE_NONE parsed_hsp = {'query': {}, 'hit': {}} # create and append a new HSP if line starts with '>--' elif self.line.startswith('>--'): # set seq attributes of previous hsp _set_hsp_seqs(hsp, parsed_hsp, self._preamble['program']) # and create a new one frag = HSPFragment(hit_id, query_id) hsp = HSP([frag]) hsp_list.append(hsp) # set the state ~ none yet state = _STATE_NONE parsed_hsp = {'query': {}, 'hit': {}} # this is either query or hit data in the HSP, depending on the state elif self.line.startswith('>'): if state == _STATE_NONE: # make sure it's the correct query assert query_id.startswith(self.line[1:].split(' ')[0]), \ "%r vs %r" % (query_id, self.line) state = _STATE_QUERY_BLOCK parsed_hsp['query']['seq'] = '' elif state == _STATE_QUERY_BLOCK: # make sure it's the correct hit assert hit_id.startswith(self.line[1:].split(' ')[0]) state = _STATE_HIT_BLOCK parsed_hsp['hit']['seq'] = '' # check for conservation block elif self.line.startswith('; al_cons'): state = _STATE_CONS_BLOCK hsp.fragment.aln_annotation['similarity'] = '' elif self.line.startswith(';'): # Fasta outputs do not make a clear distinction between Hit # and HSPs, so we check the attribute names to determine # whether it belongs to a Hit or HSP regx = re.search(_RE_ATTR, self.line.strip()) name = regx.group(1) value = regx.group(2) # for values before the '>...' query block if state == _STATE_NONE: if name in _HSP_ATTR_MAP: attr_name, caster = _HSP_ATTR_MAP[name] if caster is not str: value = caster(value) if name in ['_ident', '_sim']: value *= 100 setattr(hsp, attr_name, value) # otherwise, pool the values for processing later elif state == _STATE_QUERY_BLOCK: parsed_hsp['query'][name] = value elif state == _STATE_HIT_BLOCK: if name == '_len': seq_len = int(value) else: parsed_hsp['hit'][name] = value # for values in the hit block else: raise ValueError("Unexpected line: %r" % self.line) # otherwise, it must be lines containing the sequences else: assert '>' not in self.line # if we're in hit, parse into hsp.hit if state == _STATE_HIT_BLOCK: parsed_hsp['hit']['seq'] += self.line.strip() elif state == _STATE_QUERY_BLOCK: parsed_hsp['query']['seq'] += self.line.strip() elif state == _STATE_CONS_BLOCK: hsp.fragment.aln_annotation['similarity'] += \ self.line.strip('\r\n') # we should not get here! else: raise ValueError("Unexpected line: %r" % self.line) self.line = self.handle.readline() class FastaM10Indexer(SearchIndexer): """Indexer class for Bill Pearson's FASTA suite's -m 10 output.""" _parser = FastaM10Parser def __init__(self, filename): SearchIndexer.__init__(self, filename) self._handle = UndoHandle(self._handle) def __iter__(self): handle = self._handle handle.seek(0) start_offset = handle.tell() qresult_key = None query_mark = _as_bytes('>>>') while True: line = handle.readline() peekline = handle.peekline() end_offset = handle.tell() if not line.startswith(query_mark) and query_mark in line: regx = re.search(_RE_ID_DESC_SEQLEN_IDX, line) qresult_key = _bytes_to_string(regx.group(1)) start_offset = end_offset - len(line) # yield whenever we encounter a new query or at the end of the file if qresult_key is not None: if (not peekline.startswith(query_mark) and query_mark in peekline) or not line: yield qresult_key, start_offset, end_offset - start_offset if not line: break start_offset = end_offset def get_raw(self, offset): handle = self._handle qresult_raw = _as_bytes('') query_mark = _as_bytes('>>>') # read header first handle.seek(0) while True: line = handle.readline() peekline = handle.peekline() qresult_raw += line if not peekline.startswith(query_mark) and query_mark in peekline: break # and read the qresult raw string handle.seek(offset) while True: # preserve whitespace, don't use read_forward line = handle.readline() peekline = handle.peekline() qresult_raw += line # break when we've reached qresult end if (not peekline.startswith(query_mark) and query_mark in peekline) or \ not line: break # append mock end marker to qresult_raw, since it's not always present return qresult_raw + _as_bytes('>>><<<\n') # if not used as a module, run the doctest if __name__ == "__main__": from Bio._utils import run_doctest run_doctest()

poojavade/Genomics_Docker

Dockerfiles/gedlab-khmer-filter-abund/pymodules/python2.7/lib/python/Bio/SearchIO/FastaIO.py

Python

apache-2.0

25,572

[ "BLAST", "Biopython" ]

bd8d3032fba626e4e600202a7d56298d0e352f1c5ed17de1be0f8edf7d535d2e

import os import glob import sys import shutil import pysam from bcbio.pipeline import config_utils from bcbio.distributed.transaction import file_transaction, tx_tmpdir from bcbio.utils import (safe_makedir, file_exists) from bcbio.provenance import do from bcbio import utils from bcbio.log import logger from bcbio.pipeline import datadict as dd from bcbio import bam from bcbio import broad from bcbio.wgbsseq import kits def align(fastq_file, pair_file, ref_file, names, align_dir, data): assert data["analysis"].lower().startswith("wgbs-seq"), "No comparible alignment." config = data["config"] sample = dd.get_sample_name(data) out_prefix = os.path.join(align_dir, dd.get_lane(data)) out_dir = os.path.join(align_dir, "%s_bismark" % dd.get_lane(data)) if not ref_file: logger.error("bismark index not found. You can install " "the index for your genome with: bcbio_nextgen.py upgrade " "--aligners bismark --genomes genome-build-name --data") sys.exit(1) final_out = os.path.join(align_dir, "{0}.bam".format(sample)) if file_exists(final_out): data = dd.set_work_bam(data, final_out) data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0] data = dd.update_summary_qc(data, "bismark", base=data["bam_report"]) return data bismark = config_utils.get_program("bismark", config) # bismark uses 5 threads/sample and ~12GB RAM/sample (hg38) resources = config_utils.get_resources("bismark", data["config"]) max_cores = dd.get_num_cores(data) max_mem = config_utils.convert_to_bytes(resources.get("memory", "1G")) / (1024.0 * 1024.0) instances = calculate_bismark_instances(max_cores, max_mem * max_cores) kit = kits.KITS.get(dd.get_kit(data), None) directional = "--non_directional" if kit and not kit.is_directional else "" other_opts = resources.get("options", []) other_opts = " ".join([str(x) for x in other_opts]).strip() fastq_files = " ".join([fastq_file, pair_file]) if pair_file else fastq_file safe_makedir(align_dir) cmd = "{bismark} {other_opts} {directional} --bowtie2 --temp_dir {tx_out_dir} --gzip --parallel {instances} -o {tx_out_dir} --unmapped {ref_file} {fastq_file} " if pair_file: fastq_file = "-1 %s -2 %s" % (fastq_file, pair_file) raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam") if not raw_bam: with tx_tmpdir() as tx_out_dir: run_message = "Running Bismark aligner on %s and %s" % (fastq_file, ref_file) do.run(cmd.format(**locals()), run_message, None) shutil.move(tx_out_dir, out_dir) raw_bam = glob.glob(out_dir + "/*bismark*bt2*bam") # don't process bam in the bismark pipeline! utils.symlink_plus(raw_bam[0], final_out) data = dd.set_work_bam(data, final_out) data["bam_report"] = glob.glob(os.path.join(out_dir, "*report.txt"))[0] data = dd.update_summary_qc(data, "bismark", base=data["bam_report"]) return data def _process_bam(bam_file, in_fastq, sample, reference, config): broad_runner = broad.runner_from_config(config) names = {'rg': in_fastq, 'library': 'WGBS_LIB', 'pl': 'Illumina', 'pu': 'R1', 'sm': in_fastq, 'sample': sample} out_fix_bam = broad_runner.run_fn("picard_fix_rgs", bam_file, names) order_bam = utils.append_stem(out_fix_bam, "_order") broad_runner.run_fn("picard_reorder", out_fix_bam, reference, order_bam) bam.index(order_bam, config) # order_bam = _set_quality(order_bam) # bam.index(order_bam, config) return order_bam def remap_index_fn(ref_file): """Map sequence references to equivalent bismark indexes """ return os.path.join(os.path.dirname(os.path.dirname(ref_file)), "bismark") def _set_quality(in_bam): """ change all quality to 255 """ bam = pysam.AlignmentFile(in_bam, "rb") out_file = utils.append_stem(in_bam, "_normqual") if file_exists(out_file): return out_file with file_transaction(out_file) as tx_out: with pysam.AlignmentFile(tx_out, "wb", template=bam) as out_handle: for read in bam.fetch(): read.mapping_quality = 255 out_handle.write(read) return out_file def index(ref_file, out_dir, data): """Create a bismark index in the defined reference directory. """ (ref_dir, local_file) = os.path.split(ref_file) gtf_file = dd.get_transcriptome_gtf(data, default=dd.get_gtf_file(data)) bismark = config_utils.find_program("bismark", data["config"]) if not utils.file_exists(gtf_file): raise ValueError("%s not found, could not create a bismark index." % (gtf_file)) if not utils.file_exists(out_dir): with tx_tmpdir(data, os.path.dirname(out_dir)) as tx_out_dir: num_cores = dd.get_cores(data) other_opts = config_utils.get_resources("bismark", data["config"]).get("options", []) other_opts = " ".join([str(x) for x in other_opts]).strip() cmd = "{bismark} {other_opts} --bowtie2 -p {num_cores} -n 1 -o {tx_out_dir} --basename {sample} --unmapped {ref_file} {in_fastq}" do.run(cmd.format(**locals()), "Index STAR") if os.path.exists(out_dir): shutil.rmtree(out_dir) shutil.move(tx_out_dir, out_dir) return out_dir def calculate_bismark_instances(cores, memory): """ calculate number of parallel bismark instances to run, based on disussion here https://github.com/FelixKrueger/Bismark/issues/96 cores and memory here are the maximum amounts available for us to use """ BISMARK_CORES = 1 BOWTIE_CORES_PER_INSTANCE = 2 SAMTOOLS_CORES_PER_INSTANCE = 1 CORES_PER_INSTANCE = BOWTIE_CORES_PER_INSTANCE + SAMTOOLS_CORES_PER_INSTANCE GENOME_MEMORY_GB = 12 INSTANCE_MEMORY_GB = 10 available_instance_memory = memory - GENOME_MEMORY_GB instances_in_memory = max(available_instance_memory / INSTANCE_MEMORY_GB, 1) available_instance_cores = cores - BISMARK_CORES instances_in_cores = max(available_instance_cores / CORES_PER_INSTANCE, 1) instances = int(min(instances_in_memory, instances_in_cores)) logger.info(f"{cores} cores and {memory} memory are available. Spinning up {instances} instances of bismark.") return instances

chapmanb/bcbio-nextgen

bcbio/ngsalign/bismark.py

Python

mit

6,398

[ "pysam" ]

69365195a18e0530b7d8eb86b36268b1487ca523a86e49cf415b70de43c73404

#!/usr/bin/env python3 #pylint: disable=missing-docstring #* This file is part of the MOOSE framework #* https://www.mooseframework.org #* #* All rights reserved, see COPYRIGHT for full restrictions #* https://github.com/idaholab/moose/blob/master/COPYRIGHT #* #* Licensed under LGPL 2.1, please see LICENSE for details #* https://www.gnu.org/licenses/lgpl-2.1.html import chigger import time import shutil # Open the result shutil.copy('../input/diffusion_1.e', 'new_file.e') reader = chigger.exodus.ExodusReader('new_file.e') mug = chigger.exodus.ExodusResult(reader, variable='u', range=[0, 1], cmap='viridis') # Create the window window = chigger.RenderWindow(mug, size=[600,600], test=True) # Render the results and write a file filenames = ['../input/diffusion_2.e', '../input/diffusion_3.e', '../input/diffusion_4.e'] for i in range(4): window.write('new_files_' + str(i) + '.png') window.update() # Update the file if i < 3: time.sleep(1.5) print("{} --> {}".format(filenames[i], 'new_file.e')) shutil.copy(filenames[i], 'new_file.e') window.start()

nuclear-wizard/moose

python/chigger/tests/new_files/new_files.py

Python

lgpl-2.1

1,104

[ "MOOSE" ]

83a177d53678b899e842277ee96e78f45be0fc35a29ca6a2841cb530342c0ce4

#mono_gauss_coil model #conversion of DebyeModel.py #converted by Steve King, Mar 2016 r""" This Debye Gaussian coil model strictly describes the scattering from *monodisperse* polymer chains in theta solvents or polymer melts, conditions under which the distances between segments follow a Gaussian distribution. Provided the number of segments is large (ie, high molecular weight polymers) the single-chain form factor P(Q) is that described by Debye (1947). To describe the scattering from *polydisperse* polymer chains see the :ref:`poly-gauss-coil` model. Definition ---------- .. math:: I(q) = \text{scale} \cdot I_0 \cdot P(q) + \text{background} where .. math:: I_0 &= \phi_\text{poly} \cdot V \cdot (\rho_\text{poly} - \rho_\text{solv})^2 \\ P(q) &= 2 [\exp(-Z) + Z - 1] / Z^2 \\ Z &= (q R_g)^2 \\ V &= M / (N_A \delta) Here, $\phi_\text{poly}$ is the volume fraction of polymer, $V$ is the volume of a polymer coil, *M* is the molecular weight of the polymer, $N_A$ is Avogadro's Number, $\delta$ is the bulk density of the polymer, $\rho_\text{poly}$ is the sld of the polymer, $\rho\text{solv}$ is the sld of the solvent, and $R_g$ is the radius of gyration of the polymer coil. The 2D scattering intensity is calculated in the same way as the 1D, but where the *q* vector is redefined as .. math:: q = \sqrt{q_x^2 + q_y^2} References ---------- #. P Debye, *J. Phys. Colloid. Chem.*, 51 (1947) 18. #. R J Roe, *Methods of X-Ray and Neutron Scattering in Polymer Science*, Oxford University Press, New York (2000). #. http://www.ncnr.nist.gov/staff/hammouda/distance_learning/chapter_28.pdf Authorship and Verification ---------------------------- * **Author:** * **Last Modified by:** * **Last Reviewed by:** """ import numpy as np from numpy import inf name = "mono_gauss_coil" title = "Scattering from monodisperse polymer coils" description = """ Evaluates the scattering from monodisperse polymer chains. """ category = "shape-independent" # pylint: disable=bad-whitespace, line-too-long # ["name", "units", default, [lower, upper], "type", "description"], parameters = [ ["i_zero", "1/cm", 70.0, [0.0, inf], "", "Intensity at q=0"], ["rg", "Ang", 75.0, [0.0, inf], "volume", "Radius of gyration"], ] # pylint: enable=bad-whitespace, line-too-long source = ["mono_gauss_coil.c"] have_Fq = False radius_effective_modes = ["R_g", "2R_g", "3R_g", "sqrt(5/3)*R_g"] def random(): """Return a random parameter set for the model.""" rg = 10**np.random.uniform(0, 4) #rg = 1e3 pars = dict( #scale=1, background=0, i_zero=1e7, # i_zero is a simple scale rg=rg, ) return pars # these unit test values taken from SasView 3.1.2 tests = [ [{'scale': 1.0, 'i_zero': 70.0, 'rg': 75.0, 'background': 0.0}, [0.0106939, 0.469418], [57.1241, 0.112859]], ]

SasView/sasmodels

sasmodels/models/mono_gauss_coil.py

Python

bsd-3-clause

2,912

[ "Avogadro", "Gaussian" ]

120bbf6625d47904d80564e342134261f9d192ab6f7416fee5971d5883c6a183

import subprocess import sys import time from datetime import datetime #print(sys.argv[0]) print(""" Wifi Packet Sniffer v0.1 ------------------------------- Options: -c Channel to listen on -m Target address -i Interface to use Credits: Re-scripted by scriptedp0ison Original program airodump-ng created by Thomas d'Otreppe Visit http://www.aircrack-ng.org for more info """) if sys.argv > 1 and sys.argv > 2 and sys.argv > 3 and sys.argv > 4 and sys.argv > 5 and sys.argv > 6: #subprocess.call(sys.argv[1], shell=True) print('[+] Channel set to: {}'.format(sys.argv[2])) time.sleep(2) print('[+] Target mac set to: {}'.format(sys.argv[4])) time.sleep(2) print('[+] Network card set to listen on: {}'.format(sys.argv[6])) time.sleep(2) print('[+] Compiling system arguments...') time.sleep(1) print('[+] Executing system arguments...') time.sleep(2) launch_attack = 'airodump-ng -c {} --bssid {} {}'.format(sys.argv[2], sys.argv[4], sys.argv[6]) subprocess.call(launch_attack, shell=True) if sys.argv[1] == '-h' or sys.argv[1] == '-help' or sys.argv[1] == '--help': print(""" Wifi Dosser v0.1 - Do not use for illegal purposes! Do not test on networks you dont own or have permission to test! _____________________________________________________________________________________________________________________ Options: -h Display the help screen -m Target MAC Address -c channel to listen on -i Network Interface card Examples: python get_client.py -c <channel to listen on> -m <target mac address> -i <NIC> """)

scriptedp0ison/Kali-Linux-Wifi-Short-Cut-Scripts

get_client.py

Python

gpl-3.0

1,554

[ "VisIt" ]

022c12fff59a58346adccb3782c70b2e9f9c1f80c58ee7cda6f2914a468b57ab

#!/usr/bin/env python # -*- coding: utf-8 -*- # # king_phisher/client/client_rpc.py # # Redistribution and use in source and binary forms, with or without # modification, are permitted provided that the following conditions are # met: # # * Redistributions of source code must retain the above copyright # notice, this list of conditions and the following disclaimer. # * Redistributions in binary form must reproduce the above # copyright notice, this list of conditions and the following disclaimer # in the documentation and/or other materials provided with the # distribution. # * Neither the name of the project nor the names of its # contributors may be used to endorse or promote products derived from # this software without specific prior written permission. # # THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS # "AS IS" AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT # LIMITED TO, THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR # A PARTICULAR PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT # OWNER OR CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, # SPECIAL, EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT # LIMITED TO, PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, # DATA, OR PROFITS; OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY # THEORY OF LIABILITY, WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT # (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE # OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE. # import code import collections import functools import logging import os import queue import ssl import sys from king_phisher import errors from king_phisher import find from king_phisher import geoip from king_phisher import serializers from king_phisher import utilities from king_phisher.client import gui_utilities import advancedhttpserver import boltons.typeutils import smoke_zephyr.utilities from gi.repository import Gtk _tag_mixin_slots = ('id', 'name', 'description') _tag_mixin_types = (int, str, str) _tag_tables = ('campaign_types', 'campaigns', 'companies', 'company_departments', 'industries') database_table_objects = utilities.FreezableDict() UNRESOLVED = boltons.typeutils.make_sentinel('UNRESOLVED', var_name='UNRESOLVED') """A sentinel value used for values in rows to indicate that the data has not been loaded from the server.""" _WorkItem = collections.namedtuple('_WorkItem', ('callback_on_success', 'callback_on_error', 'callback_when_idle', 'callback_args', 'callback_kwargs', 'method', 'args', 'kwargs') ) class RemoteRowMeta(type): def __new__(mcs, name, bases, dct): dct['__slots__'] = ('__rpc__',) + dct.get('__slots__', ()) return super(RemoteRowMeta, mcs).__new__(mcs, name, bases, dct) def __init__(cls, *args, **kwargs): table_name = getattr(cls, '__table__', None) if table_name: database_table_objects[table_name] = cls super(RemoteRowMeta, cls).__init__(*args, **kwargs) # stylized metaclass definition to be Python 2.7 and 3.x compatible class RemoteRow(RemoteRowMeta('_RemoteRow', (object,), {})): """ A generic class representing a row of data from the remote King Phisher server. """ __table__ = None __xref_attr__ = None __slots__ = () def __init__(self, rpc, *args, **kwargs): if not isinstance(rpc, KingPhisherRPCClient): raise ValueError('rpc is not a KingPhisherRPCClient instance') self.__rpc__ = rpc slots = self.__slots__[1:] values = collections.defaultdict(lambda: UNRESOLVED) if args: values.update(dict(zip(slots, args))) if kwargs: values.update(kwargs) for key in slots: value = values[key] if isinstance(value, bytes): value = value.decode('utf-8') setattr(self, key, value) def __getattr__(self, item): if hasattr(self, item + '_id'): row_id = getattr(self, item + '_id', None) for table, table_cls in database_table_objects.items(): if table_cls.__xref_attr__ == item: return self.__rpc__.remote_table_row(table, row_id) raise AttributeError("object has no attribute '{0}'".format(item)) def _asdict(self): return dict(zip(self.__slots__[1:], (getattr(self, prop) for prop in self.__slots__[1:]))) def commit(self): """Send this object to the server to update the remote instance.""" values = tuple(getattr(self, attr) for attr in self.__slots__[1:]) values = collections.OrderedDict(((k, v) for (k, v) in zip(self.__slots__[1:], values) if v is not UNRESOLVED)) self.__rpc__('db/table/set', self.__table__, self.id, tuple(values.keys()), tuple(values.values())) class AlertSubscription(RemoteRow): __table__ = 'alert_subscriptions' __slots__ = ('id', 'user_id', 'campaign_id', 'expiration') class Campaign(RemoteRow): __table__ = 'campaigns' __xref_attr__ = 'campaign' __slots__ = ('id', 'name', 'description', 'user_id', 'created', 'max_credentials', 'expiration', 'campaign_type_id', 'company_id') class CampaignType(RemoteRow): __table__ = 'campaign_types' __xref_attr__ = 'campaign_type' __slots__ = _tag_mixin_slots class Company(RemoteRow): __table__ = 'companies' __xref_attr__ = 'company' __slots__ = ('id', 'name', 'description', 'industry_id', 'url_main', 'url_email', 'url_remote_access') class CompanyDepartment(RemoteRow): __table__ = 'company_departments' __xref_attr__ = 'company_department' __slots__ = _tag_mixin_slots class Credential(RemoteRow): __table__ = 'credentials' __slots__ = ('id', 'visit_id', 'message_id', 'campaign_id', 'username', 'password', 'submitted') class DeaddropConnection(RemoteRow): __table__ = 'deaddrop_connections' __slots__ = ('id', 'deployment_id', 'campaign_id', 'count', 'ip', 'local_username', 'local_hostname', 'local_ip_addresses', 'first_seen', 'last_seen') class DeaddropDeployment(RemoteRow): __table__ = 'deaddrop_deployments' __xref_attr__ = 'deployment' __slots__ = ('id', 'campaign_id', 'destination') class Industry(RemoteRow): __table__ = 'industries' __xref_attr__ = 'industry' __slots__ = _tag_mixin_slots class LandingPage(RemoteRow): __table__ = 'landing_pages' __slots__ = ('id', 'campaign_id', 'hostname', 'page') class Message(RemoteRow): __table__ = 'messages' __xref_attr__ = 'message' __slots__ = ('id', 'campaign_id', 'target_email', 'first_name', 'last_name', 'opened', 'opener_ip', 'opener_user_agent', 'reported', 'delivery_status', 'delivery_details', 'testing', 'sent', 'trained', 'company_department_id') class User(RemoteRow): __table__ = 'users' __xref_attr__ = 'user' __slots__ = ('id', 'phone_carrier', 'phone_number', 'email_address', 'otp_secret', 'last_login', 'name', 'expiration', 'description') class Visit(RemoteRow): __table__ = 'visits' __xref_attr__ = 'visit' __slots__ = ('id', 'message_id', 'campaign_id', 'first_landing_page_id', 'count', 'ip', 'details', 'first_seen', 'last_seen', 'user_agent') database_table_objects.freeze() def _graphql_file(file_or_path): if isinstance(file_or_path, str): with open(file_or_path, 'r') as file_h: query = file_h.read() else: query = file_or_path.read() return query def _graphql_find_file(query_file): path = find.data_file(os.path.join('queries', query_file)) if path is None: raise errors.KingPhisherResourceError('could not find GraphQL query file: ' + query_file) return _graphql_file(path) class KingPhisherRPCClient(advancedhttpserver.RPCClientCached): """ The main RPC object for communicating with the King Phisher Server over RPC. .. _client-rpc-async-methods: .. versionadded:: 1.14.0 Asynchronous Methods This RPC object provides a few methods for asynchronously making RPC calls to the server. This makes it easier to issue and RPC call and then process the results without having to either wait (and by extension lock the GUI thread) or start and manage a separate thread. These methods use the name ``async_`` prefix and have many of the same arguments. In all cases, the callback parameters *on_success* and *on_error* are called with the signature :samp:`callback(*(cb_args + ({results},)), **cb_kwargs)` where ``results`` is either the return value of the RPC method in the case of *on_success* or the exception instance in the case of *on_error*. The *when_idle* parameter can be used to specify that the callbacks must be executed within the main GUI thread and can thus access GObjects such as widgets. """ def __init__(self, *args, **kwargs): self.logger = logging.getLogger('KingPhisher.Client.RPC') super(KingPhisherRPCClient, self).__init__(*args, **kwargs) self.set_serializer('binary/message-pack') self._async_queue = queue.Queue() self._async_thread = utilities.Thread(target=self._async_thread_routine, name='RPCAsyncWorker') self._async_thread.start() def __repr__(self): return "<{0} '{1}@{2}:{3}{4}'>".format(self.__class__.__name__, self.username, self.host, self.port, self.uri_base) def _async_thread_routine(self): logger = logging.getLogger('KingPhisher.Client.RPC.Async') logger.debug('the async RPC worker has started') while True: work_item = self._async_queue.get() if work_item is None: self._async_queue.task_done() break args = work_item.args or () kwargs = work_item.kwargs or {} callback_args = work_item.callback_args or () callback_kwargs = work_item.callback_kwargs or {} try: results = work_item.method(*args, **kwargs) except Exception as error: logger.error("async rpc method: {} encountered an error".format(work_item.method.__name__), exc_info=True) callback = work_item.callback_on_error callback_args = callback_args + (error,) else: callback = work_item.callback_on_success callback_args = callback_args + (results,) if callback is not None: if work_item.callback_when_idle: gui_utilities.glib_idle_add_once(callback, *callback_args, **callback_kwargs) else: try: callback(*callback_args, **callback_kwargs) except Exception: logger.error("async rpc callback: {} encountered an error".format(callback.__name__), exc_info=True) self._async_queue.task_done() logger.debug('the async RPC worker is exiting') def async_call(self, method, args=None, kwargs=None, on_success=None, on_error=None, when_idle=False, cb_args=None, cb_kwargs=None): """ Perform an asynchronous RPC call to the server. This will queue a work item for a thread to issue the RPC call and then specifies the behavior for completion. See :ref:`Asynchronous Methods <client-rpc-async-methods>` for more information. .. versionadded:: 1.14.0 :param str method: The RPC method name to call. :param tuple args: The arguments to the RPC method. :param tuple kwargs: The keyword arguments to the RPC method. :param on_success: A callback function to be called after the RPC method returns successfully. :param on_error: A callback function to be called if the RPC method raises an exception. :param when_idle: Whether or not the *on_success* and *on_error* callback functions should be called from the main GUI thread while it is idle. :param cb_args: The arguments to the *on_success* and *on_error* callback functions. :param cb_kwargs: The keyword arguments to the *on_success* and *on_error* callback functions. """ self._async_queue.put(_WorkItem( callback_on_success=on_success, callback_on_error=on_error, callback_when_idle=when_idle, callback_args=cb_args, callback_kwargs=cb_kwargs, method=self.call, args=(method,) + (args or ()), kwargs=kwargs )) def async_graphql(self, query, query_vars=None, on_success=None, on_error=None, when_idle=False, cb_args=None, cb_kwargs=None): """ Perform an asynchronous RPC GraphQL query to the server. This will queue a work item for a thread to issue the RPC call and then specifies the behavior for completion. See :ref:`Asynchronous Methods <client-rpc-async-methods>` for more information. .. versionadded:: 1.14.0 :param str query: The GraphQL query string to execute asynchronously. :param dict query_vars: Any variable definitions required by the GraphQL query. :param on_success: A callback function to be called after the RPC method returns successfully. :param on_error: A callback function to be called if the RPC method raises an exception. :param when_idle: Whether or not the *on_success* and *on_error* callback functions should be called from the main GUI thread while it is idle. :param cb_args: The arguments to the *on_success* and *on_error* callback functions. :param cb_kwargs: The keyword arguments to the *on_success* and *on_error* callback functions. """ self._async_queue.put(_WorkItem( callback_on_success=on_success, callback_on_error=on_error, callback_when_idle=when_idle, callback_args=cb_args, callback_kwargs=cb_kwargs, method=self.graphql, args=(query,), kwargs={'query_vars': query_vars} )) def async_graphql_file(self, file_or_path, *args, **kwargs): """ Perform an asynchronous RPC GraphQL query from a file on the server. This will queue a work item for a thread to issue the RPC call and then specifies the behavior for completion. See :ref:`Asynchronous Methods <client-rpc-async-methods>` for more information. .. versionadded:: 1.14.0 :param file_or_path: The file object or path to the file from which to read. """ query = _graphql_file(file_or_path) return self.async_graphql(query, *args, **kwargs) def graphql(self, query, query_vars=None): """ Execute a GraphQL query on the server and return the results. This will raise :py:exc:`~king_phisher.errors.KingPhisherGraphQLQueryError` if the query fails. :param str query: The GraphQL query string to execute. :param query_vars: Any variable definitions required by the GraphQL *query*. :return: The query results. :rtype: dict """ response = self.call('graphql', query, query_vars=query_vars) if response['errors']: raise errors.KingPhisherGraphQLQueryError( 'the query failed', errors=response['errors'], query=query, query_vars=query_vars ) return response['data'] def graphql_file(self, file_or_path, query_vars=None): """ This method wraps :py:meth:`~.graphql` to provide a convenient way to execute GraphQL queries from files. :param file_or_path: The file object or path to the file from which to read. :param query_vars: The variables for *query*. :return: The query results. :rtype: dict """ query = _graphql_file(file_or_path) return self.graphql(query, query_vars=query_vars) def graphql_find_file(self, query_file, **query_vars): """ This method is similar to :py:meth:`~.graphql_file`. The first argument (*query_file*) is the name of a query file that will be located using :py:func:`find.data_file`. Additional keyword arguments are passed as the variables to the query. :param str query_file: The name of the query file to locate. :param query_vars: These keyword arguments are passed as the variables to the query. :return: The query results. :rtype: dict """ query = _graphql_find_file(query_file) return self.graphql(query, query_vars=query_vars) def reconnect(self): """Reconnect to the remote server.""" self.lock.acquire() if self.use_ssl: if (sys.version_info[0] == 2 and sys.version_info >= (2, 7, 9)) or sys.version_info >= (3, 4, 3): context = ssl.create_default_context() context.check_hostname = False context.verify_mode = ssl.CERT_NONE self.client = advancedhttpserver.http.client.HTTPSConnection(self.host, self.port, context=context) else: self.client = advancedhttpserver.http.client.HTTPSConnection(self.host, self.port) else: self.client = advancedhttpserver.http.client.HTTPConnection(self.host, self.port) self.lock.release() def remote_row_resolve(self, row): """ Take a :py:class:`~.RemoteRow` instance and load all fields which are :py:data:`~.UNRESOLVED`. If all fields are present, no modifications are made. :param row: The row who's data is to be resolved. :rtype: :py:class:`~.RemoteRow` :return: The row with all of it's fields fully resolved. :rtype: :py:class:`~.RemoteRow` """ utilities.assert_arg_type(row, RemoteRow) slots = getattr(row, '__slots__')[1:] if not any(prop for prop in slots if getattr(row, prop) is UNRESOLVED): return row for key, value in self.call('db/table/get', getattr(row, '__table__'), row.id).items(): setattr(row, key, value) return row def remote_table(self, table, query_filter=None): """ Iterate over a remote database table hosted on the server. Rows are yielded as named tuples whose fields are the columns of the specified table. :param str table: The table name to retrieve. :return: A generator which yields rows of named tuples. :rtype: tuple """ page = 0 results = self.call('db/table/view', table, page, query_filter=query_filter) if results is None: return results_length = len(results['rows']) row_cls = database_table_objects[table] while results: for row in results['rows']: row = dict(zip(results['columns'], row)) yield row_cls(self, **row) page += 1 if 'page_size' in results and 'total_rows' in results: if results['page_size'] * page >= results['total_rows']: break if len(results['rows']) < results_length: break results = self.call('db/table/view', table, page, query_filter=query_filter) def remote_table_row(self, table, row_id, cache=False, refresh=False): """ Get a row from the specified table by it's id, optionally caching it. :param str table: The table in which the row exists. :param row_id: The value of the row's id column. :param bool cache: Whether to use the cache for this row. :param bool refresh: If *cache* is True, get the current row value and store it. :return: The remote row as a named tuple of the specified table. :rtype: tuple """ if cache and refresh: row = self.cache_call_refresh('db/table/get', table, row_id) elif cache and not refresh: row = self.cache_call('db/table/get', table, row_id) else: row = self.call('db/table/get', table, row_id) if row is None: return None row_cls = database_table_objects[table] return row_cls(self, **row) def remote_table_row_set(self, table, row_id, attributes): keys, values = zip(*attributes.items()) return self.call('db/table/set', table, row_id, keys, values) def geoip_lookup(self, ip): """ Look up the geographic location information for the specified IP address in the server's geoip database. :param ip: The IP address to lookup. :type ip: :py:class:`ipaddress.IPv4Address`, str :return: The geographic location information for the specified IP address. :rtype: :py:class:`~king_phisher.geoip.GeoLocation` """ result = self.cache_call('geoip/lookup', str(ip)) if result: result = geoip.GeoLocation(ip, result=result) return result def geoip_lookup_multi(self, ips): """ Look up the geographic location information for the specified IP addresses in the server's geoip database. Because results are cached for optimal performance, IP addresses to be queried should be grouped and sorted in a way that is unlikely to change, i.e. by a timestamp. :param ips: The IP addresses to lookup. :type ips: list, set, tuple :return: The geographic location information for the specified IP address. :rtype: dict """ ips = [str(ip) for ip in ips] results = self.cache_call('geoip/lookup/multi', ips) for ip, data in results.items(): results[ip] = geoip.GeoLocation(ip, result=data) return results def get_tag_model(self, tag_table, model=None): """ Load tag information from a remote table into a :py:class:`Gtk.ListStore` instance. Tables compatible with the tag interface must have id, name and description fields. If no *model* is provided a new one will be created, else the current model will be cleared. :param str tag_table: The name of the table to load tag information from. :param model: The model to place the information into. :type model: :py:class:`Gtk.ListStore` :return: The model with the loaded data from the server. :rtype: :py:class:`Gtk.ListStore` """ if tag_table not in _tag_tables: raise ValueError('tag_table is not a valid tag interface exposing table') tag_table = smoke_zephyr.utilities.parse_case_snake_to_camel(tag_table, upper_first=False) if model is None: model = Gtk.ListStore(str, str, str) # sort by the name column, ascending model.set_sort_column_id(1, Gtk.SortType.ASCENDING) else: model.clear() graphql_query = 'query getTags { db { ' + tag_table + ' { edges { node { id name description } } } } }' tags = self.graphql(graphql_query)['db'][tag_table]['edges'] for tag in tags: tag = tag['node'] model.append((tag['id'], tag['name'], tag['description'])) return model def login(self, username, password, otp=None): """ Authenticate to the remote server. This is required before calling RPC methods which require an authenticated session. :param str username: The username to authenticate with. :param str password: The password to authenticate with. :param str otp: An optional one time password as a 6 digit string to provide if the account requires it. :return: The login result and an accompanying reason. :rtype: tuple """ login_result, login_reason, login_session = self.call('login', username, password, otp) if login_result: if self.headers is None: self.headers = {} self.headers['X-RPC-Auth'] = login_session return login_result, login_reason def ping(self): """ Call the ping RPC method on the remote server to ensure that it is responsive. On success this method will always return True, otherwise an exception will be thrown. :return: True :rtype: bool """ return self.call('ping') def shutdown(self): self._async_queue.put(None) self._async_queue.join() self._async_thread.join() def _magic_graphql(rpc, mode, line): if mode == 'file': line = os.path.expandvars(line) line = os.path.expanduser(line) if not os.access(line, os.R_OK): print('GraphQL Exception: invalid query file') return with open(line, 'r') as file_h: query = file_h.read() elif mode == 'query': query = line else: raise RuntimeError('unsupported magic mode: ' + mode) try: result = rpc.graphql(query) except errors.KingPhisherGraphQLQueryError as error: print('GraphQL Exception: ' + error.message) for message in error.errors: print(message.rstrip()) return return result def vte_child_routine(config): """ This is the method which is executed within the child process spawned by VTE. It expects additional values to be set in the *config* object so it can initialize a new :py:class:`.KingPhisherRPCClient` instance. It will then drop into an interpreter where the user may directly interact with the rpc object. :param str config: A JSON encoded client configuration. """ config = serializers.JSON.loads(config) try: import readline import rlcompleter # pylint: disable=unused-variable except ImportError: has_readline = False else: has_readline = True try: import IPython.terminal.embed except ImportError: has_ipython = False else: has_ipython = True for plugins_directory in ('rpc_plugins', 'rpc-plugins'): plugins_directory = find.data_directory(plugins_directory) if not plugins_directory: continue sys.path.append(plugins_directory) headers = config['rpc_data'].pop('headers') rpc = KingPhisherRPCClient(**config['rpc_data']) if rpc.headers is None: rpc.headers = {} for name, value in headers.items(): rpc.headers[str(name)] = str(value) user_data_path = config['user_data_path'] sys.path.append(config['user_library_path']) print("Python {0} on {1}".format(sys.version, sys.platform)) # pylint: disable=superfluous-parens print("Campaign Name: '{0}' ID: {1}".format(config['campaign_name'], config['campaign_id'])) # pylint: disable=superfluous-parens print('The \'rpc\' object holds the connected KingPhisherRPCClient instance') console_vars = { 'CAMPAIGN_NAME': config['campaign_name'], 'CAMPAIGN_ID': config['campaign_id'], 'os': os, 'rpc': rpc, 'sys': sys } if has_ipython: console = IPython.terminal.embed.InteractiveShellEmbed(ipython_dir=os.path.join(user_data_path, 'ipython')) console.register_magic_function(functools.partial(_magic_graphql, rpc, 'query'), 'line', 'graphql') console.register_magic_function(functools.partial(_magic_graphql, rpc, 'file'), 'line', 'graphql_file') console.mainloop(console_vars) else: if has_readline: readline.parse_and_bind('tab: complete') console = code.InteractiveConsole(console_vars) for var in tuple(console_vars.keys()): console.push("__builtins__['{0}'] = {0}".format(var)) console.interact('') return

securestate/king-phisher

king_phisher/client/client_rpc.py

Python

bsd-3-clause

24,921

[ "VisIt" ]

41742e828a64655a879610b5d744472cd750075df2b071d30fb2da4808fb5189

# electronics.py --- # # Filename: electronics.py # Description: # Author: Subhasis Ray # Maintainer: Dilawar Singh import numpy as np import moose class ClampCircuit(object): """Container for a Voltage-Clamp/Current clamp circuit.""" defaults = { 'level1': 25.0, 'width1': 50.0, 'delay1': 2.0, 'delay2': 1e6, 'trigMode': 0, 'delay3': 1e9 } def __init__(self, path, squid): self.path = path moose.Neutral(path) self.pulsegen = moose.PulseGen(path+"/pulse") # holding voltage/current generator self.pulsegen.count = 2 self.pulsegen.firstLevel = 25.0 self.pulsegen.firstWidth = 50.0 self.pulsegen.firstDelay = 2.0 self.pulsegen.secondDelay = 0.0 self.pulsegen.trigMode = 2 self.gate = moose.PulseGen(path + "/gate") # holding voltage/current generator self.gate.level[0] = 1.0 self.gate.delay[0] = 0.0 self.gate.width[0] = 1e9 moose.connect(self.gate, "output", self.pulsegen, "input") self.lowpass = moose.RC(path + "/lowpass") # lowpass filter self.lowpass.R = 1.0 self.lowpass.C = 0.03 self.vclamp = moose.DiffAmp(path + "/vclamp") self.vclamp.gain = 0.0 self.vclamp.saturation = 1e10 self.iclamp = moose.DiffAmp(path + "/iclamp") self.iclamp.gain = 0.0 self.iclamp.saturation = 1e10 self.pid = moose.PIDController(path + "/pid") self.pid.gain = 0.5 self.pid.tauI = 0.02 self.pid.tauD = 0.005 self.pid.saturation = 1e10 # Connect current clamp circuitry moose.connect(self.pulsegen, "output", self.iclamp, "plusIn") moose.connect(self.iclamp, "output", squid.C, "injectMsg") # Connect voltage clamp circuitry moose.connect(self.pulsegen, "output", self.lowpass, "injectIn") moose.connect(self.lowpass, "output", self.vclamp, "plusIn") moose.connect(self.vclamp, "output", self.pid, "commandIn") moose.connect(squid.C, "VmOut", self.pid, "sensedIn") moose.connect(self.pid, "output", squid.C, "injectMsg") current_table = moose.Table("/data/Im") moose.connect(current_table, "requestOut", squid.C, "getIm") def configure_pulses( self, baseLevel=0.0, firstLevel=0.1, firstDelay=5.0, firstWidth=40.0, secondLevel=0.0, secondDelay=1e6, secondWidth=0.0, singlePulse=True, ): """Set up the pulse generator.""" self.pulsegen.baseLevel = baseLevel self.pulsegen.firstLevel = firstLevel self.pulsegen.firstWidth = firstWidth self.pulsegen.firstDelay = firstDelay self.pulsegen.secondLevel = secondLevel self.pulsegen.secondDelay = secondDelay self.pulsegen.secondWidth = secondWidth if singlePulse: self.pulsegen.trigMode = 1 else: self.pulsegen.trigMode = 0 def do_voltage_clamp(self): """Switch to voltage clamp circuitry. After this the simdt may need to be changed for correct performance.""" self.vclamp.gain = 1.0 self.iclamp.gain = 0.0 self.pid.gain = 0.5 self.pid.tauD = 0.005 self.pid.tauI = 0.02 def do_current_clamp(self): """Switch to current clamp circuitry. After this the simdt may need to be changed for correct performance.""" self.iclamp.gain = 1.0 self.vclamp.gain = 0.0 self.pid.gain = 0.0

BhallaLab/moose-examples

squid/electronics.py

Python

gpl-2.0

3,586

[ "MOOSE" ]

585d9b83d5a7faee10ee1619bfc57d541d6baf9a6de101d11ce80c459a8c7858

'''------------------------------------------------------------------------------- Tool Name: CreateInflowFileFromECMWFRunoff Source Name: CreateInflowFileFromECMWFRunoff.py Version: ArcGIS 10.3 Author: Environmental Systems Research Institute Inc. Updated by: Environmental Systems Research Institute Inc. Description: Creates RAPID inflow file based on the WRF_Hydro land model output and the weight table previously created. History: Initial coding - 10/21/2014, version 1.0 Updated: Version 1.0, 10/23/2014, modified names of tool and parameters Version 1.0, 10/28/2014, added data validation Version 1.0, 10/30/2014, initial version completed Version 1.1, 11/05/2014, modified the algorithm for extracting runoff variable from the netcdf dataset to improve computation efficiency Version 1.2, 02/03/2015, bug fixing - output netcdf3-classic instead of netcdf4 as the format of RAPID inflow file Version 1.2, 02/03/2015, bug fixing - calculate inflow assuming that ECMWF runoff data is cumulative instead of incremental through time -------------------------------------------------------------------------------''' import os import netCDF4 as NET import numpy as NUM import csv class CreateInflowFileFromECMWFRunoff(object): def __init__(self): """Define the tool (tool name is the name of the class).""" self.label = "Create Inflow File From ECMWF Runoff" self.description = ("Creates RAPID NetCDF input of water inflow " + "based on ECMWF runoff results and previously created weight table.") self.canRunInBackground = False self.header_wt = ['StreamID', 'area_sqm', 'lon_index', 'lat_index', 'npoints', 'weight', 'Lon', 'Lat'] self.dims_oi = ['lon', 'lat', 'time'] self.vars_oi = ["lon", "lat", "time", "RO"] self.length_time = {"LowRes": 61, "HighRes": 125} self.length_time_opt = {"LowRes": 61, "HighRes-1hr": 91, "HighRes-3hr": 49, "HighRes-6hr": 41} self.errorMessages = ["Missing Variable 'time'", "Incorrect dimensions in the input ECMWF runoff file.", "Incorrect variables in the input ECMWF runoff file.", "Incorrect time variable in the input ECMWF runoff file", "Incorrect number of columns in the weight table", "No or incorrect header in the weight table", "Incorrect sequence of rows in the weight table"] def dataValidation(self, in_nc): """Check the necessary dimensions and variables in the input netcdf data""" data_nc = NET.Dataset(in_nc) dims = data_nc.dimensions.keys() if dims != self.dims_oi: raise Exception(self.errorMessages[1]) vars = data_nc.variables.keys() if vars != self.vars_oi: raise Exception(self.errorMessages[2]) return def dataIdentify(self, in_nc): """Check if the data is Ensemble 1-51 (low resolution) or 52 (high resolution)""" data_nc = NET.Dataset(in_nc) name_time = self.vars_oi[2] time = data_nc.variables[name_time][:] diff = NUM.unique(NUM.diff(time)) data_nc.close() time_interval_highres = NUM.array([1.0,3.0,6.0],dtype=float) time_interval_lowres = NUM.array([6.0],dtype=float) if (diff == time_interval_highres).all(): return "HighRes" elif (diff == time_interval_lowres).all(): return "LowRes" else: return None def execute(self, in_nc, in_weight_table, out_nc, in_time_interval="6hr"): """The source code of the tool.""" # Validate the netcdf dataset self.dataValidation(in_nc) # identify if the input netcdf data is the High Resolution data with three different time intervals id_data = self.dataIdentify(in_nc) if id_data is None: raise Exception(self.errorMessages[3]) ''' Read the netcdf dataset''' data_in_nc = NET.Dataset(in_nc) time = data_in_nc.variables[self.vars_oi[2]][:] # Check the size of time variable in the netcdf data if len(time) != self.length_time[id_data]: raise Exception(self.errorMessages[3]) ''' Read the weight table ''' print "Reading the weight table..." dict_list = {self.header_wt[0]:[], self.header_wt[1]:[], self.header_wt[2]:[], self.header_wt[3]:[], self.header_wt[4]:[], self.header_wt[5]:[], self.header_wt[6]:[], self.header_wt[7]:[]} streamID = "" with open(in_weight_table, "rb") as csvfile: reader = csv.reader(csvfile) count = 0 for row in reader: if count == 0: #check number of columns in the weight table if len(row) != len(self.header_wt): raise Exception(self.errorMessages[4]) #check header if row[1:len(self.header_wt)] != self.header_wt[1:len(self.header_wt)]: raise Exception(self.errorMessages[5]) streamID = row[0] count += 1 else: for i in range(0,8): dict_list[self.header_wt[i]].append(row[i]) count += 1 '''Calculate water inflows''' print "Calculating water inflows..." # Obtain size information if id_data == "LowRes": size_time = self.length_time_opt["LowRes"] else: if in_time_interval == "1hr": size_time = self.length_time_opt["HighRes-1hr"] elif in_time_interval == "3hr": size_time = self.length_time_opt["HighRes-3hr"] else: size_time = self.length_time_opt["HighRes-6hr"] size_streamID = len(set(dict_list[self.header_wt[0]])) # Create output inflow netcdf data # data_out_nc = NET.Dataset(out_nc, "w") # by default format = "NETCDF4" data_out_nc = NET.Dataset(out_nc, "w", format = "NETCDF3_CLASSIC") dim_Time = data_out_nc.createDimension('Time', size_time) dim_RiverID = data_out_nc.createDimension(streamID, size_streamID) var_m3_riv = data_out_nc.createVariable('m3_riv', 'f4', ('Time', streamID)) data_temp = NUM.empty(shape = [size_time, size_streamID]) lon_ind_all = [long(i) for i in dict_list[self.header_wt[2]]] lat_ind_all = [long(j) for j in dict_list[self.header_wt[3]]] # Obtain a subset of runoff data based on the indices in the weight table min_lon_ind_all = min(lon_ind_all) max_lon_ind_all = max(lon_ind_all) min_lat_ind_all = min(lat_ind_all) max_lat_ind_all = max(lat_ind_all) data_subset_all = data_in_nc.variables[self.vars_oi[3]][:, min_lat_ind_all:max_lat_ind_all+1, min_lon_ind_all:max_lon_ind_all+1] len_time_subset_all = data_subset_all.shape[0] len_lat_subset_all = data_subset_all.shape[1] len_lon_subset_all = data_subset_all.shape[2] data_subset_all = data_subset_all.reshape(len_time_subset_all, (len_lat_subset_all * len_lon_subset_all)) # compute new indices based on the data_subset_all index_new = [] for r in range(0,count-1): ind_lat_orig = lat_ind_all[r] ind_lon_orig = lon_ind_all[r] index_new.append((ind_lat_orig - min_lat_ind_all)*len_lon_subset_all + (ind_lon_orig - min_lon_ind_all)) # obtain a new subset of data data_subset_new = data_subset_all[:,index_new] # start compute inflow pointer = 0 for s in range(0, size_streamID): npoints = int(dict_list[self.header_wt[4]][pointer]) # Check if all npoints points correspond to the same streamID if len(set(dict_list[self.header_wt[0]][pointer : (pointer + npoints)])) != 1: print "ROW INDEX", pointer print "COMID", dict_list[self.header_wt[0]][pointer] raise Exception(self.errorMessages[2]) area_sqm_npoints = [float(k) for k in dict_list[self.header_wt[1]][pointer : (pointer + npoints)]] area_sqm_npoints = NUM.array(area_sqm_npoints) area_sqm_npoints = area_sqm_npoints.reshape(1, npoints) data_goal = data_subset_new[:, pointer:(pointer + npoints)] ''''IMPORTANT NOTE: runoff variable in ECMWF dataset is cumulative instead of incremental through time''' # For data with Low Resolution, there's only one time interval 6 hrs if id_data == "LowRes": #ro_stream = data_goal * area_sqm_npoints ro_stream = NUM.concatenate([data_goal[0:1,], NUM.subtract(data_goal[1:,],data_goal[:-1,])]) * area_sqm_npoints #For data with High Resolution, from Hour 0 to 90 (the first 91 time points) are of 1 hr time interval, # then from Hour 90 to 144 (19 time points) are of 3 hour time interval, and from Hour 144 to 240 (15 time points) # are of 6 hour time interval else: if in_time_interval == "1hr": ro_stream = NUM.concatenate([data_goal[0:1,], NUM.subtract(data_goal[1:91,],data_goal[:90,])]) * area_sqm_npoints elif in_time_interval == "3hr": # Hour = 0 is a single data point ro_3hr_a = data_goal[0:1,] # calculate time series of 3 hr data from 1 hr data ro_3hr_b = NUM.subtract(data_goal[3:91:3,],data_goal[:88:3,]) # get the time series of 3 hr data ro_3hr_c = NUM.subtract(data_goal[91:109,], data_goal[90:108,]) # concatenate all time series ro_stream = NUM.concatenate([ro_3hr_a, ro_3hr_b, ro_3hr_c]) * area_sqm_npoints else: # in_time_interval == "6hr" #arcpy.AddMessage("6hr") # Hour = 0 is a single data point ro_6hr_a = data_goal[0:1,] # calculate time series of 6 hr data from 1 hr data ro_6hr_b = NUM.subtract(data_goal[6:91:6,], data_goal[:85:6,]) # calculate time series of 6 hr data from 3 hr data ro_6hr_c = NUM.subtract(data_goal[92:109:2,], data_goal[90:107:2,]) # get the time series of 6 hr data ro_6hr_d = NUM.subtract(data_goal[109:,], data_goal[108:124,]) # concatenate all time series ro_stream = NUM.concatenate([ro_6hr_a, ro_6hr_b, ro_6hr_c, ro_6hr_d]) * area_sqm_npoints data_temp[:,s] = ro_stream.sum(axis = 1) pointer += npoints '''Write inflow data''' print "Writing inflow data..." var_m3_riv[:] = data_temp # close the input and output netcdf datasets data_in_nc.close() data_out_nc.close() return

CI-WATER/erfp_data_process_ubuntu_aws

CreateInflowFileFromECMWFRunoff.py

Python

mit

11,619

[ "NetCDF" ]

88fe13085be57276bc40cd97349ed41642501b727e3eccb1cc1106d818ae8130

# DEPTH-FIRST-SEARCH # A graph is searched depth first by visiting an initial # vertex and then visiting one of its neighbours. After # visiting this neighbour you visit one of its neighbours # and so on. If you come to a vertex with no neighbors you # backtrack one stage and visit another neighbour of the # previous vertex. # The algorithm # ------------------------------------------------------ # set the colour of v to black # ITERATE over all w that are neighbours of v # IF the colour of w is white # depth first search of G from w # ------------------------------------------------------ def dfs(v, g): g[v]['colour'] = 'black' for w in g[v]['neighbours']: if g[w]['colour'] is 'white': dfs(w, g) # An algorithm traversing the vertices of a graph needs # some way in which to detect when a vertex has already # been visited, or it might continue endlessly revisiting # vertices and never terminate. The traditional way to # record when a vertex has been visited is to give each # vertex a colour, white or black. Unvisited vertices are # coloured white. When a vertex is visited, its colour is # changed to black and black vertices are not revisited. def chatty_dfs(vertex, graph): v = vertex g = graph print( "Visited: ", v) g[v]['colour'] = 'black' for w in g[v]['neighbours']: if g[w]['colour'] is 'white': g = chatty_dfs(w, g) return g graph1 = { 1 : { 'colour' : 'white', 'neighbours' : [2, 3, 4] }, 2 : { 'colour' : 'white', 'neighbours' : [1, 4, 5] }, 3 : { 'colour' : 'white', 'neighbours' : [1, 4] }, 4 : { 'colour' : 'white', 'neighbours' : [1, 2, 3] }, 5 : { 'colour' : 'white', 'neighbours' : [2]} } print( graph1 ) print( chatty_dfs(3, graph1) )

melayev/algods

dfs.py

Python

mit

1,714

[ "VisIt" ]

c482ea83aa7c25cf86e5f87a0b563f2d08bc0814c00a9376a91478c27b33743f

"""Module for reading, writing, compressing and converting files. Please note, some of the functions in this module were created and tested using VTK 5. VTK 6 introduced a number of backwards-incompatible changes, including replacing 'SetInput()' with 'SetInputData()' and 'SetInputConnection'. """ import glob import os import csv import vtk import gzip import StringIO def compress(path='test.vtp'): """Compress file with gzip.""" with open(path, 'rb') as ifile: with gzip.open(path + '.gz', 'wb') as ofile: ofile.writelines(ifile) def decompress(path='test.vtp.gz'): """Decompress file with gzip.""" with gzip.open(path, 'rb') as ifile: with open(path[:-3], 'wb') as ofile: ofile.write(ifile.read()) def csv_to_list(path): """Convert CSV-file to a nested list of strings.""" with open(path, 'rb') as f: reader = csv.reader(f) return list(reader) def csv_to_dict(path): """Create nested dictionary from csv file. Workaround for when pandas is unavailable and you want to select 2D array elements with row and column names rather than integers. * First row is used for column names * First column is used for row names. * Access data from dictionary x using x['rowname']['columnname'] * Extract all row names with x.keys() * Extract all column names with x.values()[0].keys() Note: Expects '\n' as newline character. """ x = {} with open(path, 'rb') as f: header = f.next().strip().split(',')[1:] for line in f: row = line.strip().split(',') x[row[0]] = dict( (header[i], v) for i, v in enumerate(row[1:])) return x def listdir(path, match='*', dirname=False, extension=False): """List all files and folders in specified directory. Args: path: Path to directory. match: Specify file name pattern according to rules used by Unix shell. For instance, 'match=*.pdf' gives you a list of names of all the pdf-files in 'path'. dirname (bool): Include whole path name. extension (bool): Include file extension. """ items = glob.glob(os.path.join(path, match)) if not dirname: items = [os.path.basename(item) for item in items] if not extension: items = [os.path.splitext(item)[0] for item in items] return items def readvti(path): """Read VTI-file, i.e. image in VTK XML format.""" reader = vtk.vtkXMLImageDataReader() reader.SetFileName(path) reader.Update() return reader.GetOutput() def readvtk(path, datatype='polydata'): """Read VTK-file. Args: path: Path to file. type: 'imagedata', 'polydata', 'unstructeredgrid' """ if datatype=='imagedata': reader = vtk.vtkStructuredPointsReader() elif datatype=='polydata': reader = vtk.vtkPolyDataReader() elif datatype=='unstructeredgrid': reader = vtk.vtkUnstructuredGridReader() else: print 'Invalid datatype' reader.SetFileName(path) reader.Update() return reader.GetOutput() def readvtp(path, dataarrays=True): """Read VTP-file, i.e. polydata in VTK XML format. Args: dataarrays (bool): Include point and cell data. """ reader = vtk.vtkXMLPolyDataReader() reader.SetFileName(path) reader.Update() if dataarrays == False: for i in range(reader.GetNumberOfPointArrays()): arrayname = reader.GetPointArrayName(i) reader.SetPointArrayStatus(arrayname, 0) for i in range(reader.GetNumberOfCellArrays()): arrayname = reader.GetCellArrayName(i) reader.SetPointArrayStatus(arrayname, 0) reader.Update() return reader.GetOutput() def readvtu(path): """Read VTU-file, i.e. unstructured grid in VTK XML format.""" reader = vtk.vtkXMLUnstructuredGridReader() reader.SetFileName(path) reader.Update() return reader.GetOutput() def replacestring(lines, tag, value): """Replace string in list of strings. Args: lines: List of strings. tag: String to replace. value: String with which to replace 'tag'. """ output = [] for line in lines: line = line.replace(tag, value) output.append(line) return output def writepoints(points, filename): """Write points as VTP-file.""" polydata = vtk.vtkPolyData() cellarray = vtk.vtkCellArray() for i in range(points.GetNumberOfPoints()): cellarray.InsertNextCell(1) cellarray.InsertCellPoint(i) polydata.SetPoints(points) polydata.SetVerts(cellarray) writer = vtk.vtkXMLPolyDataWriter() writer.SetFileName(filename) writer.SetInput(polydata) writer.Write() def writevti(image, path): """Write VTI-files, i.e. images in VTK XML format.""" writer = vtk.vtkXMLImageDataWriter() writer.SetInput(image) writer.SetFileName(path) writer.Write() def writevtp(polydata, path): """Write VTP-files, i.e. polydata in VTK XML format.""" writer = vtk.vtkXMLPolyDataWriter() writer.SetInput(polydata) writer.SetFileName(path) writer.Write() def writevtu(grid, path): """Write VTU-files, i.e. unstructured grids in VTK XML format.""" writer = vtk.vtkXMLUnstructuredGridWriter() writer.SetInput(grid) writer.SetFileName(path) writer.Write() #------------------------------------------------------------------------------- # CFX #------------------------------------------------------------------------------- def cfx2vtp(inputfile, outputfile, surface=True, ascii=False): """Convert polydata exported from CFX-Post to VTP. Args: surface (bool): Convert surface or line polydata. ascii (bool): Return VTP file in ASCII format. Export surface in CFX-Post with following options: * file extension: csv * export geometry information: line and face connectivity * (optional) select variable(s) * vector display: scalar * separator: comma space * include header """ f = open(inputfile, 'rb') # derive data size from csv file if surface: for i, line in enumerate(f): if line.strip() == '[Data]': datalinenumber = i if line.strip() == '[Faces]': faceslinenumber = i lastlinenumber = i numberofnodes = faceslinenumber - datalinenumber - 3 numberofelements = lastlinenumber - faceslinenumber - 1 else: for i, line in enumerate(f): if line.strip() == '[Data]': datalinenumber = i if line.strip() == '[Lines]': lineslinenumber = i numberofnodes = lineslinenumber - datalinenumber - 3 # obtain list of variables names f.seek(0) for i in range(datalinenumber + 2): arrayline = f.readline() arraynames = arrayline.strip().split(', ') arraynames[0:3] = [] # define polydata points = vtk.vtkPoints() cells = vtk.vtkCellArray() points.SetNumberOfPoints(numberofnodes) polydata = vtk.vtkPolyData() polydata.SetPoints(points) polydata.SetPolys(cells) if surface else polydata.SetLines(cells) for arrayname in arraynames: array = vtk.vtkDoubleArray() array.SetName(arrayname) array.SetNumberOfTuples(numberofnodes) polydata.GetPointData().AddArray(array) # parse through the rest of the file using the csv module reader = csv.reader(f) # assign x,y,z coordinates and variable values to points for i in range(numberofnodes): dataline = reader.next() point = [float(dataline[0]), float(dataline[1]), float(dataline[2])] points.SetPoint(i, point) for j in range(len(arraynames)): dataarray = polydata.GetPointData().GetArray(arraynames[j]) dataarray.SetComponent(i, 0, float(dataline[j + 3])) # skip element '[Faces]' (or '[Lines]') in csv-file reader.next() reader.next() if surface: # obtain and set connectivity cellids = vtk.vtkIdList() for i in range(numberofelements): facesline = reader.next() cellids.Initialize() for j in range(len(facesline)): cellids.InsertNextId(int(facesline[j])) cells.InsertNextCell(cellids) else: # obtain connectivity connectivitylist = [] for row in reader: row = [int(item) for item in row] connectivitylist.append(row) connectivitylist = filter(None, connectivitylist) # rearrange connectivity linecounter = 0 for i in range(len(connectivitylist)): if i == 0: connectivity = [connectivitylist[i]] elif connectivitylist[i][0] == connectivitylist[i - 1][1]: connectivity[linecounter].append(connectivitylist[i][1]) else: connectivity.append([]) linecounter += 1 connectivity[linecounter].append(connectivitylist[i][0]) connectivity[linecounter].append(connectivitylist[i][1]) # set connectivity cellids = vtk.vtkIdList() for i in range(len(connectivity)): cellids.Initialize() for j in range(len(connectivity[i])): cellids.InsertNextId(int(connectivity[i][j])) cells.InsertNextCell(cellids) f.close() # write vtk polydata writer = vtk.vtkXMLPolyDataWriter() writer.SetInput(polydata) if ascii: writer.SetDataModeToAscii() writer.SetFileName(outputfile) writer.Write() def vtp2cfx(inputfile, outputfile, surface=True): """Convert VTP polydata to format that can be imported into CFX-Post. Args: surface (bool): Convert surface or line polydata. """ # read vtp file reader = vtk.vtkXMLPolyDataReader() reader.SetFileName(inputfile) reader.Update() polydata = reader.GetOutput() # read names of data arrays arraynames = [] dataarrays = polydata.GetPointData() numberofdataarrays = dataarrays.GetNumberOfArrays() for i in range(numberofdataarrays): array = dataarrays.GetArray(i) arrayname = array.GetName() arraynames.append(arrayname) # append names of data arrays to header and write header f = open(outputfile, 'wb') header = "\n[Name]\nSEGMENT\n\n[Data]\nX [ m ], Y [ m ], Z [ m ]" for i in range(numberofdataarrays): header += ", " + arraynames[i] header += "\n" f.write(header) # write values of x,y,z and data arrays row by row for i in range(polydata.GetNumberOfPoints()): point = polydata.GetPoint(i) line = str(point[0]) + ', ' + str(point[1]) + ', ' + str(point[2]) for arrayname in arraynames: array = dataarrays.GetArray(arrayname) line += ', ' + str(array.GetComponent(i, 0)) line += '\n' f.write(line) # write list of connectivity if surface: line = '\n[Faces]\n' f.write(line) for i in range(polydata.GetNumberOfCells()): cellpointids = polydata.GetCell(i).GetPointIds() line = '' for j in range(cellpointids.GetNumberOfIds()): if (j > 0): line += ', ' line += str(cellpointids.GetId(j)) line += '\n' f.write(line) else: line = '\n[Lines]\n' f.write(line) for i in range(polydata.GetNumberOfCells()): cellpointids = polydata.GetCell(i).GetPointIds() line = '' for j in range(cellpointids.GetNumberOfIds() - 1): line += (str(cellpointids.GetId(j)) + ', ' + str(cellpointids.GetId(j + 1)) + '\n') f.write(line) # add blank line to mimic exact same file structure as CFX-generated # csv-file line = '\n' f.write(line) f.close()

ajgeers/utils

utils/iolib.py

Python

bsd-2-clause

12,457

[ "VTK" ]

f14f80c2c947198e53f32800d8fabbb92bea1cbc0693bc2450c45be41462f8ec

try: import hashlib as md5 except: import md5 from DIRAC import S_OK, S_ERROR, gConfig from DIRAC.ConfigurationSystem.Client.PathFinder import getServiceSection from DIRAC.AccountingSystem.private.Plotters import gPlottersList from DIRAC.AccountingSystem.private.Policies import gPoliciesList class MainReporter: def __init__( self, db, setup ): self._db = db self.setup = setup self.csSection = getServiceSection( "Accounting/ReportGenerator", setup = setup ) def __calculateReportHash( self, reportRequest ): requestToHash = dict( reportRequest ) granularity = gConfig.getValue( "%s/CacheTimeGranularity" % self.csSection, 300 ) for key in ( 'startTime', 'endTime' ): epoch = requestToHash[ key ] requestToHash[ key ] = epoch - epoch % granularity md5Hash = md5.md5() md5Hash.update( repr( requestToHash ) ) md5Hash.update( self.setup ) return md5Hash.hexdigest() def generate( self, reportRequest, credDict ): typeName = reportRequest[ 'typeName' ] plotterClass = gPlottersList.getPlotterClass( typeName ) if not plotterClass: return S_ERROR( "There's no reporter registered for type %s" % typeName ) if typeName in gPoliciesList: retVal = gPoliciesList[ typeName ].checkRequest( reportRequest[ 'reportName' ], credDict, reportRequest[ 'condDict' ], reportRequest[ 'grouping' ] ) if not retVal[ 'OK' ]: return retVal reportRequest[ 'hash' ] = self.__calculateReportHash( reportRequest ) plotter = plotterClass( self._db, self.setup, reportRequest[ 'extraArgs' ] ) return plotter.generate( reportRequest ) def list( self, typeName ): plotterClass = gPlottersList.getPlotterClass( typeName ) if not plotterClass: return S_ERROR( "There's no plotter registered for type %s" % typeName ) plotter = plotterClass( self._db, self.setup ) return S_OK( plotter.plotsList() )

sposs/DIRAC

AccountingSystem/private/MainReporter.py

Python

gpl-3.0

2,070

[ "DIRAC" ]

505b6b1fa46df3aefa8eb7a19d7302124bf6ac32142463fdf5b24dc9f5ff5f19

########################################################################## # # Copyright 2008-2010 VMware, Inc. # All Rights Reserved. # # Permission is hereby granted, free of charge, to any person obtaining a copy # of this software and associated documentation files (the "Software"), to deal # in the Software without restriction, including without limitation the rights # to use, copy, modify, merge, publish, distribute, sublicense, and/or sell # copies of the Software, and to permit persons to whom the Software is # furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included in # all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR # IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, # FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE # AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER # LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN # THE SOFTWARE. # ##########################################################################/ """GL tracing generator.""" import re import sys from trace import Tracer from dispatch import function_pointer_type, function_pointer_value import specs.stdapi as stdapi import specs.glapi as glapi import specs.glparams as glparams from specs.glxapi import glxapi class TypeGetter(stdapi.Visitor): '''Determine which glGet*v function that matches the specified type.''' def __init__(self, prefix = 'glGet', long_suffix = True, ext_suffix = ''): self.prefix = prefix self.long_suffix = long_suffix self.ext_suffix = ext_suffix def visitConst(self, const): return self.visit(const.type) def visitAlias(self, alias): if alias.expr == 'GLboolean': if self.long_suffix: suffix = 'Booleanv' arg_type = alias.expr else: suffix = 'iv' arg_type = 'GLint' elif alias.expr == 'GLdouble': if self.long_suffix: suffix = 'Doublev' arg_type = alias.expr else: suffix = 'dv' arg_type = alias.expr elif alias.expr == 'GLfloat': if self.long_suffix: suffix = 'Floatv' arg_type = alias.expr else: suffix = 'fv' arg_type = alias.expr elif alias.expr in ('GLint', 'GLuint', 'GLsizei'): if self.long_suffix: suffix = 'Integerv' arg_type = 'GLint' else: suffix = 'iv' arg_type = 'GLint' else: print alias.expr assert False function_name = self.prefix + suffix + self.ext_suffix return function_name, arg_type def visitEnum(self, enum): return self.visit(glapi.GLint) def visitBitmask(self, bitmask): return self.visit(glapi.GLint) def visitOpaque(self, pointer): return self.prefix + 'Pointerv' + self.ext_suffix, 'GLvoid *' class GlTracer(Tracer): arrays = [ ("Vertex", "VERTEX"), ("Normal", "NORMAL"), ("Color", "COLOR"), ("Index", "INDEX"), ("TexCoord", "TEXTURE_COORD"), ("EdgeFlag", "EDGE_FLAG"), ("FogCoord", "FOG_COORD"), ("SecondaryColor", "SECONDARY_COLOR"), ] arrays.reverse() # arrays available in ES1 arrays_es1 = ("Vertex", "Normal", "Color", "TexCoord") def header(self, api): Tracer.header(self, api) print '#include <algorithm>' print print '#include "gltrace.hpp"' print # Which glVertexAttrib* variant to use print 'enum vertex_attrib {' print ' VERTEX_ATTRIB,' print ' VERTEX_ATTRIB_NV,' print '};' print print 'static vertex_attrib _get_vertex_attrib(void) {' print ' gltrace::Context *ctx = gltrace::getContext();' print ' if (ctx->user_arrays_nv) {' print ' GLboolean _vertex_program = GL_FALSE;' print ' _glGetBooleanv(GL_VERTEX_PROGRAM_ARB, &_vertex_program);' print ' if (_vertex_program) {' print ' if (ctx->user_arrays_nv) {' print ' GLint _vertex_program_binding_nv = _glGetInteger(GL_VERTEX_PROGRAM_BINDING_NV);' print ' if (_vertex_program_binding_nv) {' print ' return VERTEX_ATTRIB_NV;' print ' }' print ' }' print ' }' print ' }' print ' return VERTEX_ATTRIB;' print '}' print self.defineShadowBufferHelper() # Whether we need user arrays print 'static inline bool _need_user_arrays(void)' print '{' print ' gltrace::Context *ctx = gltrace::getContext();' print ' if (!ctx->user_arrays) {' print ' return false;' print ' }' print print ' glprofile::Profile profile = ctx->profile;' print ' bool es1 = profile.es() && profile.major == 1;' print for camelcase_name, uppercase_name in self.arrays: # in which profile is the array available? profile_check = 'profile.desktop()' if camelcase_name in self.arrays_es1: profile_check = '(' + profile_check + ' || es1)'; function_name = 'gl%sPointer' % camelcase_name enable_name = 'GL_%s_ARRAY' % uppercase_name binding_name = 'GL_%s_ARRAY_BUFFER_BINDING' % uppercase_name print ' // %s' % function_name print ' if (%s) {' % profile_check self.array_prolog(api, uppercase_name) print ' if (_glIsEnabled(%s) &&' % enable_name print ' _glGetInteger(%s) == 0) {' % binding_name self.array_cleanup(api, uppercase_name) print ' return true;' print ' }' self.array_epilog(api, uppercase_name) print ' }' print print ' // ES1 does not support generic vertex attributes' print ' if (es1)' print ' return false;' print print ' vertex_attrib _vertex_attrib = _get_vertex_attrib();' print print ' // glVertexAttribPointer' print ' if (_vertex_attrib == VERTEX_ATTRIB) {' print ' GLint _max_vertex_attribs = _glGetInteger(GL_MAX_VERTEX_ATTRIBS);' print ' for (GLint index = 0; index < _max_vertex_attribs; ++index) {' print ' if (_glGetVertexAttribi(index, GL_VERTEX_ATTRIB_ARRAY_ENABLED) &&' print ' _glGetVertexAttribi(index, GL_VERTEX_ATTRIB_ARRAY_BUFFER_BINDING) == 0) {' print ' return true;' print ' }' print ' }' print ' }' print print ' // glVertexAttribPointerNV' print ' if (_vertex_attrib == VERTEX_ATTRIB_NV) {' print ' for (GLint index = 0; index < 16; ++index) {' print ' if (_glIsEnabled(GL_VERTEX_ATTRIB_ARRAY0_NV + index)) {' print ' return true;' print ' }' print ' }' print ' }' print print ' return false;' print '}' print print r'static void _trace_user_arrays(GLuint count);' print print r'static void _fakeStringMarker(GLsizei len, const GLvoid * string);' print print r'static inline void' print r'_fakeStringMarker(const std::string &s) {' print r' _fakeStringMarker(s.length(), s.data());' print r'}' print print '// whether glLockArraysEXT() has ever been called' print 'static bool _checkLockArraysEXT = false;' print # Buffer mappings print '// whether glMapBufferRange(GL_MAP_WRITE_BIT) has ever been called' print 'static bool _checkBufferMapRange = false;' print print '// whether glBufferParameteriAPPLE(GL_BUFFER_FLUSHING_UNMAP_APPLE, GL_FALSE) has ever been called' print 'static bool _checkBufferFlushingUnmapAPPLE = false;' print # Generate a helper function to determine whether a parameter name # refers to a symbolic value or not print 'static bool' print 'is_symbolic_pname(GLenum pname) {' print ' switch (pname) {' for function, type, count, name in glparams.parameters: if type is glapi.GLenum: print ' case %s:' % name print ' return true;' print ' default:' print ' return false;' print ' }' print '}' print # Generate a helper function to determine whether a parameter value is # potentially symbolic or not; i.e., if the value can be represented in # an enum or not print 'template<class T>' print 'static inline bool' print 'is_symbolic_param(T param) {' print ' return static_cast<T>(static_cast<GLenum>(param)) == param;' print '}' print # Generate a helper function to know how many elements a parameter has print 'static size_t' print '_gl_param_size(GLenum pname) {' print ' switch (pname) {' for function, type, count, name in glparams.parameters: if name == 'GL_PROGRAM_BINARY_FORMATS': count = 0 if type is not None: print ' case %s: return %s;' % (name, count) print ' default:' print r' os::log("apitrace: warning: %s: unknown GLenum 0x%04X\n", __FUNCTION__, pname);' print ' return 1;' print ' }' print '}' print # states such as GL_UNPACK_ROW_LENGTH are not available in GLES print 'static inline bool' print 'can_unpack_subimage(void) {' print ' gltrace::Context *ctx = gltrace::getContext();' print ' return ctx->profile.desktop();' print '}' print # VMWX_map_buffer_debug print r'extern "C" PUBLIC' print r'void APIENTRY' print r'glNotifyMappedBufferRangeVMWX(const void * start, GLsizeiptr length) {' self.emit_memcpy('start', 'length') print r'}' print getProcAddressFunctionNames = [] def traceApi(self, api): if self.getProcAddressFunctionNames: # Generate a function to wrap proc addresses getProcAddressFunction = api.getFunctionByName(self.getProcAddressFunctionNames[0]) argType = getProcAddressFunction.args[0].type retType = getProcAddressFunction.type print 'static %s _wrapProcAddress(%s procName, %s procPtr);' % (retType, argType, retType) print Tracer.traceApi(self, api) print 'static %s _wrapProcAddress(%s procName, %s procPtr) {' % (retType, argType, retType) # Provide fallback functions to missing debug functions print ' if (!procPtr) {' else_ = '' for function_name in self.debug_functions: if self.api.getFunctionByName(function_name): print ' %sif (strcmp("%s", (const char *)procName) == 0) {' % (else_, function_name) print ' return (%s)&%s;' % (retType, function_name) print ' }' else_ = 'else ' print ' %s{' % else_ print ' return NULL;' print ' }' print ' }' for function in api.getAllFunctions(): ptype = function_pointer_type(function) pvalue = function_pointer_value(function) print ' if (strcmp("%s", (const char *)procName) == 0) {' % function.name print ' assert(procPtr != (%s)&%s);' % (retType, function.name) print ' %s = (%s)procPtr;' % (pvalue, ptype) print ' return (%s)&%s;' % (retType, function.name,) print ' }' print ' os::log("apitrace: warning: unknown function \\"%s\\"\\n", (const char *)procName);' print ' return procPtr;' print '}' print else: Tracer.traceApi(self, api) def defineShadowBufferHelper(self): print 'void _shadow_glGetBufferSubData(GLenum target, GLintptr offset,' print ' GLsizeiptr size, GLvoid *data)' print '{' print ' gltrace::Context *ctx = gltrace::getContext();' print ' if (!ctx->needsShadowBuffers() || target != GL_ELEMENT_ARRAY_BUFFER) {' print ' _glGetBufferSubData(target, offset, size, data);' print ' return;' print ' }' print print ' GLint buffer_binding = _glGetInteger(GL_ELEMENT_ARRAY_BUFFER_BINDING);' print ' if (buffer_binding > 0) {' print ' gltrace::Buffer & buf = ctx->buffers[buffer_binding];' print ' buf.getSubData(offset, size, data);' print ' }' print '}' def shadowBufferMethod(self, method): # Emit code to fetch the shadow buffer, and invoke a method print ' gltrace::Context *ctx = gltrace::getContext();' print ' if (ctx->needsShadowBuffers() && target == GL_ELEMENT_ARRAY_BUFFER) {' print ' GLint buffer_binding = _glGetInteger(GL_ELEMENT_ARRAY_BUFFER_BINDING);' print ' if (buffer_binding > 0) {' print ' gltrace::Buffer & buf = ctx->buffers[buffer_binding];' print ' buf.' + method + ';' print ' }' print ' }' print def shadowBufferProlog(self, function): if function.name == 'glBufferData': self.shadowBufferMethod('bufferData(size, data)') if function.name == 'glBufferSubData': self.shadowBufferMethod('bufferSubData(offset, size, data)') if function.name == 'glDeleteBuffers': print ' gltrace::Context *ctx = gltrace::getContext();' print ' if (ctx->needsShadowBuffers()) {' print ' for (GLsizei i = 0; i < n; i++) {' print ' ctx->buffers.erase(buffer[i]);' print ' }' print ' }' array_pointer_function_names = set(( "glVertexPointer", "glNormalPointer", "glColorPointer", "glIndexPointer", "glTexCoordPointer", "glEdgeFlagPointer", "glFogCoordPointer", "glSecondaryColorPointer", "glInterleavedArrays", "glVertexPointerEXT", "glNormalPointerEXT", "glColorPointerEXT", "glIndexPointerEXT", "glTexCoordPointerEXT", "glEdgeFlagPointerEXT", "glFogCoordPointerEXT", "glSecondaryColorPointerEXT", "glVertexAttribPointer", "glVertexAttribPointerARB", "glVertexAttribPointerNV", "glVertexAttribIPointer", "glVertexAttribIPointerEXT", "glVertexAttribLPointer", "glVertexAttribLPointerEXT", #"glMatrixIndexPointerARB", )) # XXX: We currently ignore the gl*Draw*ElementArray* functions draw_function_regex = re.compile(r'^gl([A-Z][a-z]+)*Draw(Range)?(Arrays|Elements)([A-Z][a-zA-Z]*)?$' ) interleaved_formats = [ 'GL_V2F', 'GL_V3F', 'GL_C4UB_V2F', 'GL_C4UB_V3F', 'GL_C3F_V3F', 'GL_N3F_V3F', 'GL_C4F_N3F_V3F', 'GL_T2F_V3F', 'GL_T4F_V4F', 'GL_T2F_C4UB_V3F', 'GL_T2F_C3F_V3F', 'GL_T2F_N3F_V3F', 'GL_T2F_C4F_N3F_V3F', 'GL_T4F_C4F_N3F_V4F', ] def traceFunctionImplBody(self, function): # Defer tracing of user array pointers... if function.name in self.array_pointer_function_names: print ' GLint _array_buffer = _glGetInteger(GL_ARRAY_BUFFER_BINDING);' print ' if (!_array_buffer) {' print ' static bool warned = false;' print ' if (!warned) {' print ' warned = true;' print ' os::log("apitrace: warning: %s: call will be faked due to pointer to user memory (https://github.com/apitrace/apitrace/blob/master/docs/BUGS.markdown#tracing)\\n", __FUNCTION__);' print ' }' print ' gltrace::Context *ctx = gltrace::getContext();' print ' ctx->user_arrays = true;' if function.name == "glVertexAttribPointerNV": print ' ctx->user_arrays_nv = true;' self.invokeFunction(function) # And also break down glInterleavedArrays into the individual calls if function.name == 'glInterleavedArrays': print # Initialize the enable flags for camelcase_name, uppercase_name in self.arrays: flag_name = '_' + uppercase_name.lower() print ' GLboolean %s = GL_FALSE;' % flag_name print # Switch for the interleaved formats print ' switch (format) {' for format in self.interleaved_formats: print ' case %s:' % format for camelcase_name, uppercase_name in self.arrays: flag_name = '_' + uppercase_name.lower() if format.find('_' + uppercase_name[0]) >= 0: print ' %s = GL_TRUE;' % flag_name print ' break;' print ' default:' print ' return;' print ' }' print # Emit fake glEnableClientState/glDisableClientState flags for camelcase_name, uppercase_name in self.arrays: flag_name = '_' + uppercase_name.lower() enable_name = 'GL_%s_ARRAY' % uppercase_name # Emit a fake function print ' {' print ' static const trace::FunctionSig &_sig = %s ? _glEnableClientState_sig : _glDisableClientState_sig;' % flag_name print ' unsigned _call = trace::localWriter.beginEnter(&_sig, true);' print ' trace::localWriter.beginArg(0);' self.serializeValue(glapi.GLenum, enable_name) print ' trace::localWriter.endArg();' print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_call);' print ' trace::localWriter.endLeave();' print ' }' # Warn about buggy glGet(GL_*ARRAY_SIZE) not returning GL_BGRA buggyFunctions = { 'glColorPointer': ('glGetIntegerv', '', 'GL_COLOR_ARRAY_SIZE'), 'glSecondaryColorPointer': ('glGetIntegerv', '', 'GL_SECONDARY_COLOR_ARRAY_SIZE'), 'glVertexAttribPointer': ('glGetVertexAttribiv', 'index, ', 'GL_VERTEX_ATTRIB_ARRAY_SIZE'), 'glVertexAttribPointerARB': ('glGetVertexAttribivARB', 'index, ', 'GL_VERTEX_ATTRIB_ARRAY_SIZE_ARB'), } if function.name in buggyFunctions: getter, extraArg, pname = buggyFunctions[function.name] print r' static bool _checked = false;' print r' if (!_checked && size == GL_BGRA) {' print r' GLint _size = 0;' print r' _%s(%s%s, &_size);' % (getter, extraArg, pname) print r' if (_size != GL_BGRA) {' print r' os::log("apitrace: warning: %s(%s) does not return GL_BGRA; trace will be incorrect (https://github.com/apitrace/apitrace/issues/261)\n");' % (getter, pname) print r' }' print r' _checked = true;' print r' }' print ' return;' print ' }' # ... to the draw calls if self.draw_function_regex.match(function.name): print ' if (_need_user_arrays()) {' if 'Indirect' in function.name: print r' os::log("apitrace: warning: %s: indirect user arrays not supported\n");' % (function.name,) else: arg_names = ', '.join([arg.name for arg in function.args[1:]]) print ' GLuint _count = _%s_count(%s);' % (function.name, arg_names) # Some apps, in particular Quake3, can tell the driver to lock more # vertices than those actually required for the draw call. print ' if (_checkLockArraysEXT) {' print ' GLuint _locked_count = _glGetInteger(GL_ARRAY_ELEMENT_LOCK_FIRST_EXT)' print ' + _glGetInteger(GL_ARRAY_ELEMENT_LOCK_COUNT_EXT);' print ' _count = std::max(_count, _locked_count);' print ' }' print ' _trace_user_arrays(_count);' print ' }' if function.name == 'glLockArraysEXT': print ' _checkLockArraysEXT = true;' # Warn if user arrays are used with glBegin/glArrayElement/glEnd. if function.name == 'glBegin': print r' gltrace::Context *ctx = gltrace::getContext();' print r' ctx->userArraysOnBegin = _need_user_arrays();' if function.name.startswith('glArrayElement'): print r' gltrace::Context *ctx = gltrace::getContext();' print r' if (ctx->userArraysOnBegin) {' print r' os::log("apitrace: warning: user arrays with glArrayElement not supported (https://github.com/apitrace/apitrace/issues/276)\n");' print r' ctx->userArraysOnBegin = false;' print r' }' # Emit a fake memcpy on buffer uploads if function.name == 'glBufferParameteriAPPLE': print ' if (pname == GL_BUFFER_FLUSHING_UNMAP_APPLE && param == GL_FALSE) {' print ' _checkBufferFlushingUnmapAPPLE = true;' print ' }' if function.name in ('glUnmapBuffer', 'glUnmapBufferARB'): if function.name.endswith('ARB'): suffix = 'ARB' else: suffix = '' print ' GLint access_flags = 0;' print ' GLint access = 0;' print ' bool flush;' print ' // GLES3 does not have GL_BUFFER_ACCESS;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_ACCESS_FLAGS, &access_flags);' % suffix print ' flush = (access_flags & GL_MAP_WRITE_BIT) && !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT | GL_MAP_PERSISTENT_BIT));' print ' } else {' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_ACCESS, &access);' % suffix print ' flush = access != GL_READ_ONLY;' print ' }' print ' if (flush) {' print ' GLvoid *map = NULL;' print ' _glGetBufferPointerv%s(target, GL_BUFFER_MAP_POINTER, &map);' % suffix print ' if (map) {' print ' GLint length = -1;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_MAP_LENGTH, &length);' % suffix print ' if (length == -1) {' print ' // Mesa drivers refuse GL_BUFFER_MAP_LENGTH without GL 3.0 up-to' print ' // http://cgit.freedesktop.org/mesa/mesa/commit/?id=ffee498fb848b253a7833373fe5430f8c7ca0c5f' print ' static bool warned = false;' print ' if (!warned) {' print ' os::log("apitrace: warning: glGetBufferParameteriv%s(GL_BUFFER_MAP_LENGTH) failed\\n");' % suffix print ' warned = true;' print ' }' print ' }' print ' } else {' print ' length = 0;' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_SIZE, &length);' % suffix print ' }' print ' if (_checkBufferFlushingUnmapAPPLE) {' print ' GLint flushing_unmap = GL_TRUE;' print ' _glGetBufferParameteriv%s(target, GL_BUFFER_FLUSHING_UNMAP_APPLE, &flushing_unmap);' % suffix print ' flush = flush && flushing_unmap;' print ' }' print ' if (flush && length > 0) {' self.emit_memcpy('map', 'length') print ' }' print ' }' print ' }' if function.name == 'glUnmapBufferOES': print ' GLint access_flags = 0;' print ' GLint access = 0;' print ' bool flush;' print ' // GLES3 does not have GL_BUFFER_ACCESS;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv(target, GL_BUFFER_ACCESS_FLAGS, &access_flags);' print ' flush = (access_flags & GL_MAP_WRITE_BIT) && !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT | GL_MAP_PERSISTENT_BIT));' print ' } else {' print ' _glGetBufferParameteriv(target, GL_BUFFER_ACCESS, &access);' print ' flush = access != GL_READ_ONLY;' print ' }' print ' if (flush) {' print ' GLvoid *map = NULL;' print ' _glGetBufferPointervOES(target, GL_BUFFER_MAP_POINTER, &map);' print ' if (map) {' print ' GLint length = 0;' print ' GLint offset = 0;' print ' if (_checkBufferMapRange) {' print ' _glGetBufferParameteriv(target, GL_BUFFER_MAP_LENGTH, &length);' print ' _glGetBufferParameteriv(target, GL_BUFFER_MAP_OFFSET, &offset);' print ' } else {' print ' _glGetBufferParameteriv(target, GL_BUFFER_SIZE, &length);' print ' }' print ' if (flush && length > 0) {' self.emit_memcpy('map', 'length') self.shadowBufferMethod('bufferSubData(offset, length, map)') print ' }' print ' }' print ' }' if function.name == 'glUnmapNamedBuffer': print ' GLint access_flags = 0;' print ' _glGetNamedBufferParameteriv(buffer, GL_BUFFER_ACCESS_FLAGS, &access_flags);' print ' if ((access_flags & GL_MAP_WRITE_BIT) &&' print ' !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT | GL_MAP_PERSISTENT_BIT))) {' print ' GLvoid *map = NULL;' print ' _glGetNamedBufferPointerv(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' GLint length = 0;' print ' _glGetNamedBufferParameteriv(buffer, GL_BUFFER_MAP_LENGTH, &length);' print ' if (map && length > 0) {' self.emit_memcpy('map', 'length') print ' }' print ' }' if function.name == 'glUnmapNamedBufferEXT': print ' GLint access_flags = 0;' print ' _glGetNamedBufferParameterivEXT(buffer, GL_BUFFER_ACCESS_FLAGS, &access_flags);' print ' if ((access_flags & GL_MAP_WRITE_BIT) &&' print ' !(access_flags & (GL_MAP_FLUSH_EXPLICIT_BIT | GL_MAP_PERSISTENT_BIT))) {' print ' GLvoid *map = NULL;' print ' _glGetNamedBufferPointervEXT(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' GLint length = 0;' print ' _glGetNamedBufferParameterivEXT(buffer, GL_BUFFER_MAP_LENGTH, &length);' print ' if (map && length > 0) {' self.emit_memcpy('map', 'length') print ' }' print ' }' if function.name == 'glFlushMappedBufferRange': print ' GLvoid *map = NULL;' print ' _glGetBufferPointerv(target, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char *)map + offset', 'length') print ' }' if function.name == 'glFlushMappedBufferRangeEXT': print ' GLvoid *map = NULL;' print ' _glGetBufferPointervOES(target, GL_BUFFER_MAP_POINTER_OES, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char *)map + offset', 'length') print ' }' if function.name == 'glFlushMappedBufferRangeAPPLE': print ' GLvoid *map = NULL;' print ' _glGetBufferPointerv(target, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && size > 0) {' self.emit_memcpy('(const char *)map + offset', 'size') print ' }' if function.name == 'glFlushMappedNamedBufferRange': print ' GLvoid *map = NULL;' print ' _glGetNamedBufferPointerv(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char *)map + offset', 'length') print ' }' if function.name == 'glFlushMappedNamedBufferRangeEXT': print ' GLvoid *map = NULL;' print ' _glGetNamedBufferPointervEXT(buffer, GL_BUFFER_MAP_POINTER, &map);' print ' if (map && length > 0) {' self.emit_memcpy('(const char *)map + offset', 'length') print ' }' # FIXME: We don't support coherent/pinned memory mappings if function.name in ('glBufferStorage', 'glNamedBufferStorage', 'glNamedBufferStorageEXT'): print r' if (!(flags & GL_MAP_PERSISTENT_BIT)) {' print r' os::log("apitrace: warning: %s: MAP_NOTIFY_EXPLICIT_BIT_VMWX set w/o MAP_PERSISTENT_BIT\n", __FUNCTION__);' print r' }' print r' flags &= ~GL_MAP_NOTIFY_EXPLICIT_BIT_VMWX;' if function.name in ('glMapBufferRange', 'glMapBufferRangeEXT', 'glMapNamedBufferRange', 'glMapNamedBufferRangeEXT'): print r' if (access & GL_MAP_NOTIFY_EXPLICIT_BIT_VMWX) {' print r' if (!(access & GL_MAP_PERSISTENT_BIT)) {' print r' os::log("apitrace: warning: %s: MAP_NOTIFY_EXPLICIT_BIT_VMWX set w/o MAP_PERSISTENT_BIT\n", __FUNCTION__);' print r' }' print r' if (access & GL_MAP_FLUSH_EXPLICIT_BIT) {' print r' os::log("apitrace: warning: %s: MAP_NOTIFY_EXPLICIT_BIT_VMWX set w/ MAP_FLUSH_EXPLICIT_BIT\n", __FUNCTION__);' print r' }' print r' access &= ~GL_MAP_NOTIFY_EXPLICIT_BIT_VMWX;' print r' } else if (access & GL_MAP_COHERENT_BIT) {' print r' os::log("apitrace: warning: %s: MAP_COHERENT_BIT unsupported (https://github.com/apitrace/apitrace/issues/232)\n", __FUNCTION__);' print r' } else if ((access & GL_MAP_PERSISTENT_BIT) &&' print r' !(access & GL_MAP_FLUSH_EXPLICIT_BIT)) {' print r' os::log("apitrace: warning: %s: MAP_PERSISTENT_BIT w/o FLUSH_EXPLICIT_BIT unsupported (https://github.com/apitrace/apitrace/issues/232)\n", __FUNCTION__);' print r' }' if function.name in ('glBufferData', 'glBufferDataARB'): print r' if (target == GL_EXTERNAL_VIRTUAL_MEMORY_BUFFER_AMD) {' print r' os::log("apitrace: warning: GL_AMD_pinned_memory not fully supported\n");' print r' }' # TODO: We don't track GL_INTEL_map_texture mappings if function.name == 'glMapTexture2DINTEL': print r' if (access & GL_MAP_WRITE_BIT) {' print r' os::log("apitrace: warning: GL_INTEL_map_texture not fully supported\n");' print r' }' # Don't leave vertex attrib locations to chance. Instead emit fake # glBindAttribLocation calls to ensure that the same locations will be # used when retracing. Trying to remap locations after the fact would # be an herculian task given that vertex attrib locations appear in # many entry-points, including non-shader related ones. if function.name == 'glLinkProgram': Tracer.invokeFunction(self, function) print ' GLint active_attributes = 0;' print ' _glGetProgramiv(program, GL_ACTIVE_ATTRIBUTES, &active_attributes);' print ' for (GLint attrib = 0; attrib < active_attributes; ++attrib) {' print ' GLint size = 0;' print ' GLenum type = 0;' print ' GLchar name[256];' # TODO: Use ACTIVE_ATTRIBUTE_MAX_LENGTH instead of 256 print ' _glGetActiveAttrib(program, attrib, sizeof name, NULL, &size, &type, name);' print " if (name[0] != 'g' || name[1] != 'l' || name[2] != '_') {" print ' GLint location = _glGetAttribLocation(program, name);' print ' if (location >= 0) {' bind_function = glapi.glapi.getFunctionByName('glBindAttribLocation') self.fake_call(bind_function, ['program', 'location', 'name']) print ' }' print ' }' print ' }' if function.name == 'glLinkProgramARB': Tracer.invokeFunction(self, function) print ' GLint active_attributes = 0;' print ' _glGetObjectParameterivARB(programObj, GL_OBJECT_ACTIVE_ATTRIBUTES_ARB, &active_attributes);' print ' for (GLint attrib = 0; attrib < active_attributes; ++attrib) {' print ' GLint size = 0;' print ' GLenum type = 0;' print ' GLcharARB name[256];' # TODO: Use ACTIVE_ATTRIBUTE_MAX_LENGTH instead of 256 print ' _glGetActiveAttribARB(programObj, attrib, sizeof name, NULL, &size, &type, name);' print " if (name[0] != 'g' || name[1] != 'l' || name[2] != '_') {" print ' GLint location = _glGetAttribLocationARB(programObj, name);' print ' if (location >= 0) {' bind_function = glapi.glapi.getFunctionByName('glBindAttribLocationARB') self.fake_call(bind_function, ['programObj', 'location', 'name']) print ' }' print ' }' print ' }' self.shadowBufferProlog(function) Tracer.traceFunctionImplBody(self, function) # These entrypoints are only expected to be implemented by tools; # drivers will probably not implement them. marker_functions = [ # GL_GREMEDY_string_marker 'glStringMarkerGREMEDY', # GL_GREMEDY_frame_terminator 'glFrameTerminatorGREMEDY', ] # These entrypoints may be implemented by drivers, but are also very useful # for debugging / analysis tools. debug_functions = [ # GL_KHR_debug 'glDebugMessageControl', 'glDebugMessageInsert', 'glDebugMessageCallback', 'glGetDebugMessageLog', 'glPushDebugGroup', 'glPopDebugGroup', 'glObjectLabel', 'glGetObjectLabel', 'glObjectPtrLabel', 'glGetObjectPtrLabel', # GL_KHR_debug (for OpenGL ES) 'glDebugMessageControlKHR', 'glDebugMessageInsertKHR', 'glDebugMessageCallbackKHR', 'glGetDebugMessageLogKHR', 'glPushDebugGroupKHR', 'glPopDebugGroupKHR', 'glObjectLabelKHR', 'glGetObjectLabelKHR', 'glObjectPtrLabelKHR', 'glGetObjectPtrLabelKHR', # GL_ARB_debug_output 'glDebugMessageControlARB', 'glDebugMessageInsertARB', 'glDebugMessageCallbackARB', 'glGetDebugMessageLogARB', # GL_AMD_debug_output 'glDebugMessageEnableAMD', 'glDebugMessageInsertAMD', 'glDebugMessageCallbackAMD', 'glGetDebugMessageLogAMD', # GL_EXT_debug_label 'glLabelObjectEXT', 'glGetObjectLabelEXT', # GL_EXT_debug_marker 'glInsertEventMarkerEXT', 'glPushGroupMarkerEXT', 'glPopGroupMarkerEXT', ] def invokeFunction(self, function): if function.name in ('glLinkProgram', 'glLinkProgramARB'): # These functions have been dispatched already return # Force glProgramBinary to fail. Per ARB_get_program_binary this # should signal the app that it needs to recompile. if function.name in ('glProgramBinary', 'glProgramBinaryOES'): print r' binaryFormat = 0xDEADDEAD;' print r' binary = &binaryFormat;' print r' length = sizeof binaryFormat;' Tracer.invokeFunction(self, function) def doInvokeFunction(self, function): # Same as invokeFunction() but called both when trace is enabled or disabled. # # Used to modify the behavior of GL entry-points. # Override GL extensions if function.name in ('glGetString', 'glGetIntegerv', 'glGetStringi'): Tracer.doInvokeFunction(self, function, prefix = 'gltrace::_', suffix = '_override') return # We implement GL_GREMEDY_*, etc., and not the driver if function.name in self.marker_functions: return # We may be faking KHR_debug, so ensure the pointer queries result is # always zeroed to prevent dereference of unitialized pointers if function.name == 'glGetPointerv': print ' if (params &&' print ' (pname == GL_DEBUG_CALLBACK_FUNCTION ||' print ' pname == GL_DEBUG_CALLBACK_USER_PARAM)) {' print ' *params = NULL;' print ' }' if function.name in self.getProcAddressFunctionNames: nameArg = function.args[0].name print ' if (strcmp("glNotifyMappedBufferRangeVMWX", (const char *)%s) == 0) {' % (nameArg,) print ' _result = (%s)&glNotifyMappedBufferRangeVMWX;' % (function.type,) for marker_function in self.marker_functions: if self.api.getFunctionByName(marker_function): print ' } else if (strcmp("%s", (const char *)%s) == 0) {' % (marker_function, nameArg) print ' _result = (%s)&%s;' % (function.type, marker_function) print ' } else {' Tracer.doInvokeFunction(self, function) # Replace function addresses with ours # XXX: Doing this here instead of wrapRet means that the trace will # contain the addresses of the wrapper functions, and not the real # functions, but in practice this should make no difference. if function.name in self.getProcAddressFunctionNames: print ' _result = _wrapProcAddress(%s, _result);' % (nameArg,) print ' }' return if function.name in ('glGetProgramBinary', 'glGetProgramBinaryOES'): print r' bufSize = 0;' Tracer.doInvokeFunction(self, function) if function.name == 'glGetProgramiv': print r' if (params && pname == GL_PROGRAM_BINARY_LENGTH) {' print r' *params = 0;' print r' }' if function.name in ('glGetProgramBinary', 'glGetProgramBinaryOES'): print r' if (length) {' print r' *length = 0;' print r' }' buffer_targets = [ 'ARRAY_BUFFER', 'ELEMENT_ARRAY_BUFFER', 'PIXEL_PACK_BUFFER', 'PIXEL_UNPACK_BUFFER', 'UNIFORM_BUFFER', 'TEXTURE_BUFFER', 'TRANSFORM_FEEDBACK_BUFFER', 'COPY_READ_BUFFER', 'COPY_WRITE_BUFFER', 'DRAW_INDIRECT_BUFFER', 'ATOMIC_COUNTER_BUFFER', ] def wrapRet(self, function, instance): Tracer.wrapRet(self, function, instance) # Keep track of buffer mappings if function.name in ('glMapBufferRange', 'glMapBufferRangeEXT'): print ' if (access & GL_MAP_WRITE_BIT) {' print ' _checkBufferMapRange = true;' print ' }' boolean_names = [ 'GL_FALSE', 'GL_TRUE', ] def gl_boolean(self, value): return self.boolean_names[int(bool(value))] # Regular expression for the names of the functions that unpack from a # pixel buffer object. See the ARB_pixel_buffer_object specification. unpack_function_regex = re.compile(r'^gl(' + r'|'.join([ r'Bitmap', r'PolygonStipple', r'PixelMap[a-z]+v', r'DrawPixels', r'Color(Sub)?Table', r'(Convolution|Separable)Filter[12]D', r'(Compressed)?(Multi)?Tex(ture)?(Sub)?Image[1-4]D', ]) + r')[0-9A-Z]*$') def serializeArgValue(self, function, arg): # Recognize offsets instead of blobs when a PBO is bound if self.unpack_function_regex.match(function.name) \ and (isinstance(arg.type, stdapi.Blob) \ or (isinstance(arg.type, stdapi.Const) \ and isinstance(arg.type.type, stdapi.Blob))): print ' {' print ' gltrace::Context *ctx = gltrace::getContext();' print ' GLint _unpack_buffer = 0;' print ' if (ctx->profile.desktop())' print ' _glGetIntegerv(GL_PIXEL_UNPACK_BUFFER_BINDING, &_unpack_buffer);' print ' if (_unpack_buffer) {' print ' trace::localWriter.writePointer((uintptr_t)%s);' % arg.name print ' } else {' Tracer.serializeArgValue(self, function, arg) print ' }' print ' }' return # Several GL state functions take GLenum symbolic names as # integer/floats; so dump the symbolic name whenever possible if function.name.startswith('gl') \ and arg.type in (glapi.GLint, glapi.GLfloat, glapi.GLdouble) \ and arg.name == 'param': assert arg.index > 0 assert function.args[arg.index - 1].name == 'pname' assert function.args[arg.index - 1].type == glapi.GLenum print ' if (is_symbolic_pname(pname) && is_symbolic_param(%s)) {' % arg.name self.serializeValue(glapi.GLenum, arg.name) print ' } else {' Tracer.serializeArgValue(self, function, arg) print ' }' return Tracer.serializeArgValue(self, function, arg) def footer(self, api): Tracer.footer(self, api) # A simple state tracker to track the pointer values # update the state print 'static void _trace_user_arrays(GLuint count)' print '{' print ' gltrace::Context *ctx = gltrace::getContext();' print print ' glprofile::Profile profile = ctx->profile;' print ' bool es1 = profile.es() && profile.major == 1;' print # Temporarily unbind the array buffer print ' GLint _array_buffer = _glGetInteger(GL_ARRAY_BUFFER_BINDING);' print ' if (_array_buffer) {' self.fake_glBindBuffer(api, 'GL_ARRAY_BUFFER', '0') print ' }' print for camelcase_name, uppercase_name in self.arrays: # in which profile is the array available? profile_check = 'profile.desktop()' if camelcase_name in self.arrays_es1: profile_check = '(' + profile_check + ' || es1)'; function_name = 'gl%sPointer' % camelcase_name enable_name = 'GL_%s_ARRAY' % uppercase_name binding_name = 'GL_%s_ARRAY_BUFFER_BINDING' % uppercase_name function = api.getFunctionByName(function_name) print ' // %s' % function.prototype() print ' if (%s) {' % profile_check self.array_trace_prolog(api, uppercase_name) self.array_prolog(api, uppercase_name) print ' if (_glIsEnabled(%s)) {' % enable_name print ' GLint _binding = _glGetInteger(%s);' % binding_name print ' if (!_binding) {' # Get the arguments via glGet* for arg in function.args: arg_get_enum = 'GL_%s_ARRAY_%s' % (uppercase_name, arg.name.upper()) arg_get_function, arg_type = TypeGetter().visit(arg.type) print ' %s %s = 0;' % (arg_type, arg.name) print ' _%s(%s, &%s);' % (arg_get_function, arg_get_enum, arg.name) arg_names = ', '.join([arg.name for arg in function.args[:-1]]) print ' size_t _size = _%s_size(%s, count);' % (function.name, arg_names) # Emit a fake function self.array_trace_intermezzo(api, uppercase_name) print ' unsigned _call = trace::localWriter.beginEnter(&_%s_sig, true);' % (function.name,) for arg in function.args: assert not arg.output print ' trace::localWriter.beginArg(%u);' % (arg.index,) if arg.name != 'pointer': self.serializeValue(arg.type, arg.name) else: print ' trace::localWriter.writeBlob((const void *)%s, _size);' % (arg.name) print ' trace::localWriter.endArg();' print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_call);' print ' trace::localWriter.endLeave();' print ' }' print ' }' self.array_epilog(api, uppercase_name) self.array_trace_epilog(api, uppercase_name) print ' }' print # Samething, but for glVertexAttribPointer* # # Some variants of glVertexAttribPointer alias conventional and generic attributes: # - glVertexAttribPointer: no # - glVertexAttribPointerARB: implementation dependent # - glVertexAttribPointerNV: yes # # This means that the implementations of these functions do not always # alias, and they need to be considered independently. # print ' // ES1 does not support generic vertex attributes' print ' if (es1)' print ' return;' print print ' vertex_attrib _vertex_attrib = _get_vertex_attrib();' print for suffix in ['', 'NV']: if suffix: SUFFIX = '_' + suffix else: SUFFIX = suffix function_name = 'glVertexAttribPointer' + suffix function = api.getFunctionByName(function_name) print ' // %s' % function.prototype() print ' if (_vertex_attrib == VERTEX_ATTRIB%s) {' % SUFFIX if suffix == 'NV': print ' GLint _max_vertex_attribs = 16;' else: print ' GLint _max_vertex_attribs = _glGetInteger(GL_MAX_VERTEX_ATTRIBS);' print ' for (GLint index = 0; index < _max_vertex_attribs; ++index) {' print ' GLint _enabled = 0;' if suffix == 'NV': print ' _glGetIntegerv(GL_VERTEX_ATTRIB_ARRAY0_NV + index, &_enabled);' else: print ' _glGetVertexAttribiv%s(index, GL_VERTEX_ATTRIB_ARRAY_ENABLED%s, &_enabled);' % (suffix, SUFFIX) print ' if (_enabled) {' print ' GLint _binding = 0;' if suffix != 'NV': # It doesn't seem possible to use VBOs with NV_vertex_program. print ' _glGetVertexAttribiv%s(index, GL_VERTEX_ATTRIB_ARRAY_BUFFER_BINDING%s, &_binding);' % (suffix, SUFFIX) print ' if (!_binding) {' # Get the arguments via glGet* for arg in function.args[1:]: if suffix == 'NV': arg_get_enum = 'GL_ATTRIB_ARRAY_%s%s' % (arg.name.upper(), SUFFIX) else: arg_get_enum = 'GL_VERTEX_ATTRIB_ARRAY_%s%s' % (arg.name.upper(), SUFFIX) arg_get_function, arg_type = TypeGetter('glGetVertexAttrib', False, suffix).visit(arg.type) print ' %s %s = 0;' % (arg_type, arg.name) print ' _%s(index, %s, &%s);' % (arg_get_function, arg_get_enum, arg.name) arg_names = ', '.join([arg.name for arg in function.args[1:-1]]) print ' size_t _size = _%s_size(%s, count);' % (function.name, arg_names) # Emit a fake function print ' unsigned _call = trace::localWriter.beginEnter(&_%s_sig, true);' % (function.name,) for arg in function.args: assert not arg.output print ' trace::localWriter.beginArg(%u);' % (arg.index,) if arg.name != 'pointer': self.serializeValue(arg.type, arg.name) else: print ' trace::localWriter.writeBlob((const void *)%s, _size);' % (arg.name) print ' trace::localWriter.endArg();' print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_call);' print ' trace::localWriter.endLeave();' print ' }' print ' }' print ' }' print ' }' print # Restore the original array_buffer print ' if (_array_buffer) {' self.fake_glBindBuffer(api, 'GL_ARRAY_BUFFER', '_array_buffer') print ' }' print print '}' print # Fake glStringMarkerGREMEDY print r'static void _fakeStringMarker(GLsizei len, const GLvoid * string) {' glStringMarkerGREMEDY = api.getFunctionByName('glStringMarkerGREMEDY') self.fake_call(glStringMarkerGREMEDY, ['len', 'string']) print r'}' # # Hooks for glTexCoordPointer, which is identical to the other array # pointers except the fact that it is indexed by glClientActiveTexture. # def array_prolog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' GLint max_units = 0;' print ' if (ctx->profile.desktop())' print ' _glGetIntegerv(GL_MAX_TEXTURE_COORDS, &max_units);' print ' else' print ' _glGetIntegerv(GL_MAX_TEXTURE_UNITS, &max_units);' print ' GLint client_active_texture = GL_TEXTURE0;' print ' if (max_units > 0) {' print ' _glGetIntegerv(GL_CLIENT_ACTIVE_TEXTURE, &client_active_texture);' print ' }' print ' GLint unit = 0;' print ' do {' print ' GLint texture = GL_TEXTURE0 + unit;' print ' if (max_units > 0) {' print ' _glClientActiveTexture(texture);' print ' }' def array_trace_prolog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' bool client_active_texture_dirty = false;' def array_epilog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' } while (++unit < max_units);' self.array_cleanup(api, uppercase_name) def array_cleanup(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' if (max_units > 0) {' print ' _glClientActiveTexture(client_active_texture);' print ' }' def array_trace_intermezzo(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' if (texture != client_active_texture || client_active_texture_dirty) {' print ' client_active_texture_dirty = true;' self.fake_glClientActiveTexture_call(api, "texture"); print ' }' def array_trace_epilog(self, api, uppercase_name): if uppercase_name == 'TEXTURE_COORD': print ' if (client_active_texture_dirty) {' self.fake_glClientActiveTexture_call(api, "client_active_texture"); print ' }' def fake_glBindBuffer(self, api, target, buffer): function = api.getFunctionByName('glBindBuffer') self.fake_call(function, [target, buffer]) def fake_glClientActiveTexture_call(self, api, texture): function = api.getFunctionByName('glClientActiveTexture') self.fake_call(function, [texture]) def emitFakeTexture2D(self): function = glapi.glapi.getFunctionByName('glTexImage2D') instances = function.argNames() print ' unsigned _fake_call = trace::localWriter.beginEnter(&_%s_sig, true);' % (function.name,) for arg in function.args: assert not arg.output self.serializeArg(function, arg) print ' trace::localWriter.endEnter();' print ' trace::localWriter.beginLeave(_fake_call);' print ' trace::localWriter.endLeave();'

EoD/apitrace

wrappers/gltrace.py

Python

mit

55,234

[ "VisIt" ]

ceec5b69fc3bb5024a8f3e82ac6378b982d01f707413fb5c2df99f1717cf693a

import numpy as np import scipy.special from scipy import constants import computations import data_processing def test_mie(): """Test the functions involved in the Mie coefficients computation. Compare to values obtained with Wolfram Alpha. """ n = 1 a = 10e-9 omega = 2.48 / constants.hbar * constants.eV eps1 = 1.0 eps2 = -2.377 + 1j*2.856 k1 = np.sqrt(eps1) * omega / constants.c k2 = np.sqrt(eps2) * omega / constants.c rho1 = k1*a rho2 = k2*a jn1 = scipy.special.spherical_jn(n, rho1) assert np.isclose(jn1, 0.041827106236) jn2 = scipy.special.spherical_jn(n, rho2) assert np.isclose(np.real(jn2), 0.034734565982) assert np.isclose(np.imag(jn2), 0.073239296279) hn1 = computations.spherical_hankel(n, rho1, jn1) assert np.isclose(np.real(hn1), 0.0418271062361) assert np.isclose(np.imag(hn1), -63.8076276033) jnprime1 = scipy.special.spherical_jn(n, rho1, derivative=True) assert np.isclose(jnprime1, 0.331755278538607) jnprime2 = scipy.special.spherical_jn(n, rho2, derivative=True) assert np.isclose(np.real(jnprime2), 0.337084148426481) assert np.isclose(np.imag(jnprime2), -0.004531343067615) psinprime1 = computations.psi_n_prime(rho1, jn1, jnprime1) assert np.isclose(psinprime1, 0.0835220176842857) psinprime2 = computations.psi_n_prime(rho2, jn2, jnprime2) assert np.isclose(np.real(psinprime2), 0.070389454025903) assert np.isclose(np.imag(psinprime2), 0.146716099221274) zetanprime1 = computations.zeta_n_prime(n, rho1, jnprime1, hn1) assert np.isclose(np.real(zetanprime1), 0.0835220176842857) assert np.isclose(np.imag(zetanprime1), 62.8155149095646) an = computations.mie_bn(1.0, 1.0, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(an), -1.96544240e-6) assert np.isclose(np.imag(an), -2.34432221e-6) bn = computations.mie_bn(eps1, eps2, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(bn), -0.00140178) assert np.isclose(np.imag(bn), 0.00149810) return 'Tests pass: Mie local' def test_mie_nonlocal(): """Test the functions involved in the nonlocal Mie coefficients computation. Compare to values obtained with Wolfram Alpha. """ n = 1 a = 10e-9 omega = 2.48 / constants.hbar * constants.eV omega_p = 8.1 / constants.hbar * constants.eV gamma = 0.047 / constants.hbar * constants.eV v_F = 1.40e6 D = 8.62e-4 eps1 = 1.0 eps2 = -2.377 + 1j*2.856 eps_inf = 1.0 k1 = np.sqrt(eps1) * omega / constants.c k2 = np.sqrt(eps2) * omega / constants.c k2_nl = computations.k_longitudinal(True, eps2, eps_inf, omega_p, gamma, v_F, D, omega) assert np.isclose(np.real(k2_nl), -2.98397e9, atol=0.0, rtol=1.0e-3) assert np.isclose(np.imag(k2_nl), 5.25972e9, atol=0.0, rtol=1.0e-3) rho1 = k1*a rho2 = k2*a rho2_nl = k2_nl*a jn1 = scipy.special.spherical_jn(n, rho1) jn2 = scipy.special.spherical_jn(n, rho2) hn1 = computations.spherical_hankel(n, rho1, jn1) jnprime1 = scipy.special.spherical_jn(n, rho1, derivative=True) jnprime2 = scipy.special.spherical_jn(n, rho2, derivative=True) psinprime1 = computations.psi_n_prime(rho1, jn1, jnprime1) psinprime2 = computations.psi_n_prime(rho2, jn2, jnprime2) zetanprime1 = computations.zeta_n_prime(n, rho1, jnprime1, hn1) jn2_nl = scipy.special.spherical_jn(n, rho2_nl) assert np.isclose(np.real(jn2_nl), 5.119867079e20) assert np.isclose(np.imag(jn2_nl), -2.786558951e20) jnprime2_nl = scipy.special.spherical_jn(n, rho2_nl, derivative=True) assert np.isclose(np.real(jnprime2_nl), -2.7063597583597e20) assert np.isclose(np.imag(jnprime2_nl), -5.0690425090715e20) deltan = computations.delta_n(n, rho2_nl, eps2, eps_inf, jn2) assert np.isclose(np.real(deltan), -0.0119636) assert np.isclose(np.imag(deltan), 0.00117763) an = computations.mie_bn(1.0, 1.0, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(an), -1.96544240e-6) assert np.isclose(np.imag(an), -2.34432221e-6) bn = computations.mie_bn(eps1, eps2, jn1, jn2, hn1, psinprime1, psinprime2, zetanprime1, 0.0) assert np.isclose(np.real(bn), -0.00140178) assert np.isclose(np.imag(bn), 0.00149810) return 'Tests pass: Mie nonlocal' def test_decay_rates(): """Test the functions involved in the decay rates computation. Compare to values obtained with finite element methods. """ r = data_processing.convert_units(30, 'nm') metal = 'Drude' eps_inf = 1.0 hbar_omega_p = 8.1 omega_p = data_processing.convert_eV_to_Hz(hbar_omega_p) hbar_gamma = constants.hbar / (14.0e-15 * constants.eV) gamma = data_processing.convert_eV_to_Hz(hbar_gamma) n_max = 111 test_fem_local_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) test_fem_local_emission_dielectric(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) test_fem_local_distance_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) test_fem_nonlocal_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) metal = 'Olmon single-crystal gold' test_fem_emission_exp_eps(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max) return 'Tests pass: FEM comparison' def test_fem_local_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a varying emission frequency in air. Only the relative difference is evaluated. """ nonlocal = False v_F = 0.0 D = 0.0 d = data_processing.convert_units(np.array([5]), 'nm') emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_inf = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_inf, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_01.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) orientation = 'tangential' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_inf, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_02.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-2) return 'Tests pass: FEM comparison for changing emission parameter in air with local Drude metal' def test_fem_local_emission_dielectric(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a varying emission frequency in a dielectric medium. Only the relative difference is evaluated. """ nonlocal = False v_F = 0.0 D = 0.0 d = data_processing.convert_units(np.array([5]), 'nm') emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') gamma = data_processing.convert_eV_to_Hz(hbar_gamma) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_03.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) orientation = 'tangential' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_04.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) return 'Tests pass: FEM comparison for changing emission parameter in dielectric with local Drude metal' def test_fem_local_distance_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a varying distance frequency in air. Only the relative difference is evaluated. """ nonlocal = False v_F = 0.0 D = 0.0 distance = np.linspace(1.0, 10.0, num=10) d = data_processing.convert_units(distance, 'nm') emission = 2.5 omega = data_processing.convert_emission_to_omega(np.array([emission]), 'hbar omega (eV)') gamma = data_processing.convert_eV_to_Hz(hbar_gamma) eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_05.txt', skiprows=17) assert np.allclose(d, fem_data[:, 0]) assert np.allclose(gamma_tot, fem_data[:, 1], atol=0.0, rtol=3.0e-2) orientation = 'tangential' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_06.txt', skiprows=17) assert np.allclose(d, fem_data[:, 0]) assert np.allclose(gamma_tot, fem_data[:, 1], atol=0.0, rtol=3.0e-2) return 'Tests pass: FEM comparison for changing distance in air with local Drude metal' def test_fem_nonlocal_emission_air(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a Drude metal with a nonlocal response. Only the relative difference is evaluated. """ nonlocal = True v_F = 1.40e6 D = 0.0 d = data_processing.convert_units(np.array([5]), 'nm') emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) orientation = 'radial' gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_07.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) D = 8.62e-4 gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_08.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-2) return 'Tests pass: FEM comparison for changing emission parameter in air with nonlocal Drude metal' def test_fem_emission_exp_eps(r, metal, eps_inf, hbar_omega_p, omega_p, hbar_gamma, gamma, n_max): """Compare decay rates with FEM calculations. The comparison is for a metal with permittivity of gold given by Olmon. Only the relative difference is evaluated. """ emission = np.linspace(1.0, 4.0, num=10) omega = data_processing.convert_emission_to_omega(emission, 'hbar omega (eV)') orientation = 'radial' d = data_processing.convert_units(np.array([5]), 'nm') nonlocal = False v_F = 0.0 D = 0.0 eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_09.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_10.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) nonlocal = True v_F = 1.40e6 D = 0.0 eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_11.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_12.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=2.0e-2) D = 8.62e-4 eps_medium = 1.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_13.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) eps_medium = 2.0 eps_metal = data_processing.permittivity(omega, metal, eps_inf, hbar_omega_p, hbar_gamma) eps_local = data_processing.bound_response(eps_metal, omega, hbar_omega_p, hbar_gamma) gamma_tot, gamma_r = computations.decay_rates_vectorized(n_max, nonlocal, eps_medium, eps_metal, eps_local, omega_p, gamma, v_F, D, omega, r, d, orientation) fem_data = np.loadtxt('Tests/FEM_14.txt', skiprows=17) assert np.allclose(emission, fem_data[:, 0]) assert np.allclose(np.transpose(gamma_tot), fem_data[:, 1], atol=0.0, rtol=1.0e-3) return 'Tests pass: FEM comparison for metal with permittivity of gold given by Olmon' if __name__ == "__main__": print(test_mie()) print(test_mie_nonlocal()) print(test_decay_rates())

rjurga/plasmon-fluorescence

tests.py

Python

mit

16,104

[ "CRYSTAL" ]

74b5f81a13fe5e64c44ed9726bacbfa50303489ad0fad9674c5c4d530aa2e7ca

# -*- coding: UTF-8 -*- """ ``trinity_mapping`` ----------------------------------------------------------------- :Authors: Menachem Sklarz :Affiliation: Bioinformatics core facility :Organization: National Institute of Biotechnology in the Negev, Ben Gurion University. A class that defines a module for running ``align_and_estimate_abundance.pl`` on a Trinity assembly and the raw reads. Tested on versions 2.4.0 and 2.5.0 of Trinity. See the `align_and_estimate_abundance.pl`_ script documentation. .. _align_and_estimate_abundance.pl: https://github.com/trinityrnaseq/trinityrnaseq/wiki/Trinity-Transcript-Quantification#estimating-transcript-abundance Requires ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ * ``fastq`` files in at least one of the following slots: * ``sample_data[<sample>]["fastq.F"]`` * ``sample_data[<sample>]["fastq.R"]`` * ``sample_data[<sample>]["fastq.S"]`` * A Trinity assembly in one of (depending on ``scope``) * ``sample_data[<sample>]["fasta.nucl"]`` * ``sample_data["fasta.nucl"]`` Output: ~~~~~~~~~~~~~ * Puts output files in the following slots: * ``sample_data[<sample>]["bam"]`` * ``sample_data[<sample>]["unsorted_bam"]`` (If ``--coordsort_bam`` is passed in redirects) * ``sample_data[<sample>]["isoforms.results"]`` * ``sample_data[<sample>]["genes.results"]`` Parameters that can be set ~~~~~~~~~~~~~~~~~~~~~~~~~~ .. csv-table:: :header: "Parameter", "Values", "Comments" "scope", "sample|project", "Set if project-wide fasta slot should be used" "redirects: --gene_trans_map", "path or empty", "If empty, use internal gene_trans_map. If path, use path as gene_trans_map for all samples. If not passed, performs analysis on isoform level only" "redirects: --trinity_mode", "", "If set, will create a gene_trans_map for each sample and store it as sample gene_trans_map" Lines for parameter file ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ :: trin_map1: module: trinity_mapping base: trinity1 script_path: {Vars.paths.align_and_estimate_abundance} redirects: --est_method: RSEM --aln_method: bowtie --trinity_mode: --seqType: fq References ~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Grabherr, M.G., Haas, B.J., Yassour, M., Levin, J.Z., Thompson, D.A., Amit, I., Adiconis, X., Fan, L., Raychowdhury, R., Zeng, Q. and Chen, Z., 2011. **Trinity: reconstructing a full-length transcriptome without a genome from RNA-Seq data**. *Nature biotechnology*, 29(7), p.644. """ import os import sys import re from neatseq_flow.PLC_step import Step,AssertionExcept __author__ = "Menachem Sklarz" __version__ = "1.6.0" class Step_trinity_mapping(Step): def step_specific_init(self): self.shell = "bash" # Can be set to "bash" by inheriting instances self.file_tag = "trinity_mapping" if "--est_method" not in self.params["redir_params"]: raise AssertionExcept("You must pass an --est_method to trinity_mapping.\n") # Is used below... self.est_method = self.params["redir_params"]["--est_method"] if self.est_method == "kallisto": raise AssertionExcept("Method 'kallisto' is not defined yet!") # To define, find out what the per isoform and per gene output files are named and fill the names in the dictionary called file_suffix_ind, below. if "--aln_method" in self.params["redir_params"]: # raise AssertionExcept("You must pass an --aln_method to trinity_mapping\n") self.params["aln_method"] = self.params["redir_params"]["--aln_method"] del self.params["redir_params"]["--aln_method"] else: self.params["aln_method"] = None if not self.params["aln_method"] and self.est_method.lower() in ["rsem","express"]: raise AssertionExcept("For RSEM and eXpress, you must supply an 'aln_method' parameter") if "scope" not in self.params: raise AssertionExcept("Please specify a 'scope': Either 'sample' or 'project'.") for redir2remove in ["--transcripts", "--output_dir", "--left", "--right", "--single", "--prep_reference"]: if redir2remove in self.params["redir_params"]: del self.params["redir_params"][redir2remove] self.write_warning("You are not supposed to specify %s in redirects. We set it automatically" % redir2remove) def step_sample_initiation(self): """ A place to do initiation stages following setting of sample_data Here you should do testing for dependency output. These will NOT exist at initiation of this instance. They are set only following sample_data updating """ if self.params["scope"] == "sample": # Check that "fasta" and "assembly" exist (signs that trinity has been executed) for sample in self.sample_data["samples"]: if "fasta.nucl" not in self.sample_data[sample]: raise AssertionExcept("It seems there is no sample-wide assembly.", sample) elif self.params["scope"] == "project": # print self.sample_data.keys() if "fasta.nucl" not in self.sample_data["project_data"]: raise AssertionExcept("It seems there is no project-wide assembly.") else: raise AssertionExcept("'scope' must be either 'sample' or 'project'.") # If "bam" required as input method, make sure a bam exists for all samples: if self.params["aln_method"] == "bam": for sample in self.sample_data["samples"]: if "bam" not in self.sample_data[sample]: raise AssertionExcept("It seems there is no BAM file for the sample.", sample) # Dealing with gene_trans_map: if self.params["scope"] == "project": if "--gene_trans_map" in self.params["redir_params"]: self.use_gene_trans_map = True if self.params["redir_params"]["--gene_trans_map"]: # If value was passed self.sample_data["project_data"]["gene_trans_map"] = self.params["redir_params"]["--gene_trans_map"] else: # If passed empty, use internal: if "gene_trans_map" in self.sample_data["project_data"]: self.params["redir_params"]["--gene_trans_map"] = self.sample_data["project_data"]["gene_trans_map"] else: raise AssertionExcept("Expecting 'gene_trans_map' in project but none found.\n") elif "--trinity_mode" in self.params["redir_params"]: self.use_gene_trans_map = True else: self.use_gene_trans_map = False else: # sample scope if "--gene_trans_map" in self.params["redir_params"]: self.use_gene_trans_map = True if self.params["redir_params"]["--gene_trans_map"]: # If value was passed for sample in self.sample_data["samples"]: self.sample_data[sample]["gene_trans_map"] = self.params["redir_params"]["--gene_trans_map"] else: # If passed empty, use internal: if "gene_trans_map" in self.sample_data[sample]: self.params["redir_params"]["--gene_trans_map"] = self.sample_data[sample]["gene_trans_map"] else: raise AssertionExcept("Expecting 'gene_trans_map' in sample but none found.\n", sample) elif "--trinity_mode" in self.params["redir_params"]: self.sample_data[sample]["gene_trans_map"] = "%s.gene_trans_map" % self.sample_data[sample]["fasta.nucl"] self.use_gene_trans_map = True else: self.use_gene_trans_map = False def create_spec_wrapping_up_script(self): """ Add stuff to check and agglomerate the output data """ pass def create_spec_preliminary_script(self): """ Add script to run BEFORE all other steps """ if all([self.params["scope"] == "project", self.params["aln_method"] not in ["bam", None]]): self.script = "" # 1. Create link to fasta file in Reference dir # 2. Create link to gene_trans_map file as well, if it exists self.script += """\ # Creating a local sost link to the reference # The purpose is that the reference will not be built in the original location mkdir -p {dir} cp -rsf \\ {ref} \\{map} {dir} """.format(ref=self.sample_data["project_data"]["fasta.nucl"], map=("\n\t"+self.sample_data["project_data"]["gene_trans_map"]+" \\") if "gene_trans_map" in self.sample_data["project_data"] else "", dir=self.base_dir+"Reference") # Set fasta.nucl to new link to original fasta nucl self.sample_data["project_data"]["fasta.nucl"] = "{dir}Reference/{fn}".\ format(dir=self.base_dir, fn=os.path.basename(self.sample_data["project_data"]["fasta.nucl"])) # If it exists, and therefore linked, set gene_trans_map to new link to original file: if "gene_trans_map" in self.sample_data["project_data"]: self.sample_data["project_data"]["gene_trans_map"] = "{dir}Reference/{fn}".\ format(dir=self.base_dir, fn=os.path.basename(self.sample_data["project_data"]["gene_trans_map"])) # "%s.gene_trans_map" % self.sample_data["project_data"]["fasta.nucl"] # Create script and write to SCRPT # First: transcript preparation (with --pre_reference arg) self.script += """ {const}--aln_method {aln} \\ \t--transcripts {fasta} \\ \t--prep_reference """.format(const=self.get_script_const(), aln=self.params["aln_method"], fasta=self.sample_data["project_data"]["fasta.nucl"]) else: pass def build_scripts(self): file_suffix_ind = { "rsem": { "isoforms": "RSEM.isoforms.results", "genes": "RSEM.genes.results"}, "salmon": { "isoforms": "quant.sf", "genes": "quant.sf.genes"}, "kallisto": { "isoforms": "", "genes": "" }, "express": { "isoforms": "results.xprs", "genes": "results.xprs.genes"} } # Loop over samples and concatenate read files to $forward and $reverse respectively # add check if paired or single !!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!!! for sample in self.sample_data["samples"]: # Getting list of samples out of samples_hash # Name of specific script: self.spec_script_name = self.set_spec_script_name(sample) self.script = "" # Make a dir for the current sample: sample_dir = self.make_folder_for_sample(sample) # This line should be left before every new script. It sees to local issues. # Use the dir it returns as the base_dir for this step. use_dir = self.local_start(sample_dir) # Procedure for preparing # Repeating procedure as done in trinity step: # If both F and R reads exist, adding them to forward and reverse # Assuming upstream input testing to check that if there are F reads then there are also R reads. # Setting variables to empty strings single = forward = reverse = "" if "fastq.F" in self.sample_data[sample]: forward = self.sample_data[sample]["fastq.F"] reverse = self.sample_data[sample]["fastq.R"] if "fastq.S" in self.sample_data[sample]: single = self.sample_data[sample]["fastq.S"] # # Adding single reads to end of left (=forward) reads # if single != "" and forward != "": # forward = ",".join([forward,single]) transcripts = self.sample_data[sample]["fasta.nucl"] \ if self.params["scope"] == "sample" \ else self.sample_data["project_data"]["fasta.nucl"] if all([self.params["scope"] == "sample", \ "aln_method" in self.params, \ self.params["aln_method"] not in ["bam", None]]): self.script += "# Preperaing the reference for analysis:\n\n" self.script += self.get_script_const() self.script += "--aln_method %s \\\n\t" % self.params["aln_method"] self.script += "--transcripts %s \\\n\t" % transcripts self.script += "--prep_reference \n\n" # Create script and write to SCRPT # First: transcript preparation (with --pre_reference arg) # - This is done with preliminary script (see create_spec_preliminary_script()) self.script += self.get_script_const() if self.params["aln_method"] == "bam": self.script += "--aln_method %s \\\n\t" % self.sample_data[sample]["bam"] # Checked above. BAM must exist. elif self.params["aln_method"] == None: pass else: self.script += "--aln_method %s \\\n\t" % self.params["aln_method"] self.script += "--transcripts %s \\\n\t" % transcripts self.script += "--output_dir %s \\\n\t" % use_dir if (forward): self.script += "--left %s \\\n\t" % forward self.script += "--right %s \\\n\t" % reverse elif (single): self.script += "--single %s \\\n\t" % single else: pass # No reads. This should be caught above... self.script = self.script.rstrip("\\\n\t") + "\n\n" # Storing files: mv_data = {"dir" : use_dir, "src" : file_suffix_ind[self.est_method.lower()]["isoforms"], "trg" : ".".join([sample,file_suffix_ind[self.est_method.lower()]["isoforms"]])} self.script += "mv {dir}{src} {dir}{trg}\n".format(**mv_data) self.sample_data[sample]["isoforms.results"] = "{dir}{trg}".format(**mv_data) self.stamp_file(self.sample_data[sample]["isoforms.results"]) if self.use_gene_trans_map: # Produce gene files: mv_data["src"] = file_suffix_ind[self.est_method.lower()]["genes"] mv_data["trg"] = ".".join([sample,file_suffix_ind[self.est_method.lower()]["genes"]]) self.script += "mv {dir}{src} {dir}{trg}\n".format(**mv_data) self.sample_data[sample]["genes.results"] = "{dir}{trg}".format(**mv_data) self.stamp_file(self.sample_data[sample]["genes.results"]) # Store bam files if self.est_method.lower() in ["rsem","express"]: self.sample_data[sample]["bam"] = "{dir}{method}.bam".format(dir = sample_dir, \ method = self.params["aln_method"]) self.stamp_file(self.sample_data[sample]["bam"]) self.sample_data[sample]["mapper"] = "%s" % self.params["aln_method"] if "--coordsort_bam" in self.params["redir_params"]: self.sample_data[sample]["unsorted_bam"] = self.sample_data[sample]["bam"] self.stamp_file(self.sample_data[sample]["unsorted_bam"]) self.sample_data[sample]["bam"] = "{dir}{method}.csorted.bam".format(dir = sample_dir, \ method = self.params["aln_method"]) self.stamp_file(self.sample_data[sample]["bam"]) self.sample_data[sample]["reference"] = transcripts # Move all files from temporary local dir to permanent base_dir self.local_finish(use_dir,self.base_dir) # Sees to copying local files to final destination (and other stuff) self.create_low_level_script()

bioinfo-core-BGU/neatseq-flow_modules

neatseq_flow_modules/RNA_seq/trinity_mapping.py

Python

gpl-3.0

17,105

[ "Bowtie" ]

6f1a6baa94708be445935242dc409ac60d0ddac45614a084d6d906edf6e17aae

############################################################################## ## ## Copyright (C) 2014-2016, New York University. ## Copyright (C) 2011-2014, NYU-Poly. ## Copyright (C) 2006-2011, University of Utah. ## All rights reserved. ## Contact: contact@vistrails.org ## ## This file is part of VisTrails. ## ## "Redistribution and use in source and binary forms, with or without ## modification, are permitted provided that the following conditions are met: ## ## - Redistributions of source code must retain the above copyright notice, ## this list of conditions and the following disclaimer. ## - Redistributions in binary form must reproduce the above copyright ## notice, this list of conditions and the following disclaimer in the ## documentation and/or other materials provided with the distribution. ## - Neither the name of the New York University nor the names of its ## contributors may be used to endorse or promote products derived from ## this software without specific prior written permission. ## ## THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" ## AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, ## THE IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR ## PURPOSE ARE DISCLAIMED. IN NO EVENT SHALL THE COPYRIGHT HOLDER OR ## CONTRIBUTORS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL, ## EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO, ## PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS; ## OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY, ## WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR ## OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF ## ADVISED OF THE POSSIBILITY OF SUCH DAMAGE." ## ############################################################################### """Configuration variables for controlling specific things in VisTrails. """ from __future__ import division import atexit import email.utils import json import os import requests import tempfile import usagestats import weakref from vistrails.core import debug from vistrails.core.system import vistrails_version, \ vistrails_examples_directory usage_report = None def setup_usage_report(): """Sets up the usagestats module. """ global usage_report certificate_file = get_ca_certificate() usage_report = usagestats.Stats( '~/.vistrails/usage_stats', usagestats.Prompt( "\nUploading usage statistics is currently disabled\n" "Please help us by providing anonymous usage statistics; " "you can enable this\neither from the GUI or by using " "--enable-usage-stats\n" "If you do not want to see this message again, you can disable " "it from the GUI or with --disable-usage-stats\n" "Nothing will be uploaded before you opt in.\n"), 'https://reprozip-stats.poly.edu/', version='VisTrails %s' % vistrails_version(), unique_user_id=True, env_var='VISTRAILS_USAGE_STATS', ssl_verify=certificate_file) cwd = os.getcwd() record_usage(cwd_spaces=b' ' in cwd) try: cwd.decode('ascii') except UnicodeDecodeError: record_usage(cwd_ascii=False) else: record_usage(cwd_ascii=True) def update_config(configuration): if getattr(configuration, 'enableUsage', False): usage_report.enable_reporting() configuration.reportUsage = 1 return True elif getattr(configuration, 'disableUsage', False): usage_report.disable_reporting() configuration.reportUsage = 0 return True return False def record_usage(**kwargs): """Records some info in the current usage report. """ if usage_report is not None: debug.debug("record_usage %r" % (kwargs,)) usage_report.note(kwargs) saved_vistrails = weakref.WeakValueDictionary() features = set() features_for_vistrails = {} def record_vistrail(what, vistrail): """Record info about a vistrail we used. """ if not usage_report.recording: return from vistrails.core.vistrail.controller import VistrailController from vistrails.core.vistrail.pipeline import Pipeline from vistrails.core.vistrail.vistrail import Vistrail from vistrails.db.services.locator import XMLFileLocator if isinstance(vistrail, VistrailController): vistrail = vistrail.vistrail if what == 'save': # Don't report now, but mark it for reporting when it gets closed saved_vistrails[id(vistrail)] = vistrail return elif what == 'close': i = id(vistrail) if i in saved_vistrails: del saved_vistrails[i] what = 'saved_close' else: return if isinstance(vistrail, Vistrail): upgrade_from = set() upgrade_to = set() nb_notes = 0 nb_paramexplorations = 0 for annotation in vistrail.action_annotations: if annotation.key == Vistrail.UPGRADE_ANNOTATION: upgrade_from.add(annotation.action_id) upgrade_to.add(int(annotation.value)) elif annotation.key == Vistrail.NOTES_ANNOTATION: nb_notes += 1 elif annotation.key == Vistrail.PARAMEXP_ANNOTATION: nb_paramexplorations += 1 nb_upgrades = len(upgrade_from - upgrade_to) if isinstance(vistrail.locator, XMLFileLocator): usage_report.note({'in_examples_dir': os.path.realpath(vistrail.locator._name).startswith( os.path.realpath(vistrails_examples_directory()))}) nb_modules = 0 nb_groups = 0 nb_abstractions = 0 for action in vistrail.actions: if action.id in upgrade_to or action.description == "Upgrade": continue for operation in action.operations: if operation.vtType == 'add' or operation.vtType == 'change': if operation.what == 'module': nb_modules += 1 if operation.data.is_group(): nb_groups += 1 elif operation.data.is_abstraction(): nb_abstractions += 1 usage_report.note(dict(use_vistrail=what, nb_versions=len(vistrail.actionMap), nb_tags=len(vistrail.get_tagMap()), nb_notes=nb_notes, nb_paramexplorations=nb_paramexplorations, nb_upgrades=nb_upgrades, nb_variables=len(vistrail.vistrail_variables), nb_modules=nb_modules, nb_groups=nb_groups, nb_abstractions=nb_abstractions)) for feature in features_for_vistrails.pop(id(vistrail), ()): usage_report.note({'feature_for_vistrail': feature}) elif isinstance(vistrail, Pipeline): usage_report.note(dict(use_workflow=what, nb_modules=len(vistrail.module_list))) else: raise TypeError def record_feature(feature, vistrail=None): """Record that a feature was used. """ from vistrails.core.vistrail.controller import VistrailController if vistrail is not None: if isinstance(vistrail, VistrailController): vistrail = vistrail.vistrail features_for_vistrails.setdefault(id(vistrail), set()).add(feature) else: features.add(feature) def submit_usage_report(**kwargs): """Submits the current usage report to the usagestats server. """ debug.debug("submit_usage_report %r" % (kwargs,)) for pkg in ('numpy', 'scipy', 'matplotlib'): try: pkg_o = __import__(pkg, globals(), locals()) usage_report.note({pkg: getattr(pkg_o, '__version__', '')}) except ImportError: pass try: import vtk usage_report.note({'vtk': vtk.vtkVersion().GetVTKVersion()}) except ImportError: pass features.update(*features_for_vistrails.values()) for feature in features: usage_report.note({'feature': feature}) usage_report.submit(kwargs, usagestats.OPERATING_SYSTEM, usagestats.SESSION_TIME, usagestats.PYTHON_VERSION) _server_news = None def get_server_news(): global _server_news if _server_news is not None: return _server_news dot_vistrails = os.path.expanduser('~/.vistrails') if not os.path.exists(dot_vistrails): os.mkdir(dot_vistrails) file_name = os.path.join(dot_vistrails, 'server_news.json') file_exists = os.path.exists(file_name) headers = {} if file_exists: mtime = email.utils.formatdate(os.path.getmtime(file_name), usegmt=True) headers['If-Modified-Since'] = mtime try: resp = requests.get( 'https://reprozip-stats.poly.edu/vistrails_news/%s' % vistrails_version(), headers=headers, timeout=2 if file_exists else 10, stream=True, verify=get_ca_certificate()) resp.raise_for_status() if resp.status_code == 304: raise requests.HTTPError( '304 File is up to date, no data returned', response=resp) except requests.RequestException, e: if not e.response or e.response.status_code != 304: debug.warning("Can't download server news", e) else: try: with open(file_name, 'wb') as f: for chunk in resp.iter_content(4096): f.write(chunk) resp.close() except Exception, e: try: os.remove(file_name) except OSError: pass raise e debug.log("Downloaded server news") if os.path.exists(file_name): with open(file_name, 'r') as f: _server_news = json.load(f) else: _server_news = _default_news return _server_news def get_ca_certificate(): fd, certificate_file = tempfile.mkstemp(prefix='vistrails_stats_ca_', suffix='.pem') with open(certificate_file, 'wb') as fp: fp.write(_ca_certificate) os.close(fd) atexit.register(os.remove, certificate_file) return certificate_file _default_news = { 'version': '20160304', 'news_html': None, 'usage_report_prompt_html': u"Please help us by reporting anonymous statistics about how you " u"use VisTrails.We would like to collect high-level details " u"like which packages you use, which features, the size of your " u"workflows and version trees, ... This information is reported " u"anonymously and will only be used by the VisTrails team, to help " u"guide our efforts.", } _ca_certificate = b'''\ -----BEGIN CERTIFICATE----- MIIDzzCCAregAwIBAgIJAMmlcDnTidBEMA0GCSqGSIb3DQEBCwUAMH4xCzAJBgNV BAYTAlVTMREwDwYDVQQIDAhOZXcgWW9yazERMA8GA1UEBwwITmV3IFlvcmsxDDAK BgNVBAoMA05ZVTERMA8GA1UEAwwIUmVwcm9aaXAxKDAmBgkqhkiG9w0BCQEWGXJl cHJvemlwLWRldkB2Z2MucG9seS5lZHUwHhcNMTQxMTA3MDUxOTA5WhcNMjQxMTA0 MDUxOTA5WjB+MQswCQYDVQQGEwJVUzERMA8GA1UECAwITmV3IFlvcmsxETAPBgNV BAcMCE5ldyBZb3JrMQwwCgYDVQQKDANOWVUxETAPBgNVBAMMCFJlcHJvWmlwMSgw JgYJKoZIhvcNAQkBFhlyZXByb3ppcC1kZXZAdmdjLnBvbHkuZWR1MIIBIjANBgkq hkiG9w0BAQEFAAOCAQ8AMIIBCgKCAQEA1fuTW2snrVji51vGVl9hXAAZbNJ+dxG+ /LOOxZrF2f1RRNy8YWpeCfGbsZqiIEjorBv8lvdd9P+tD3M5sh9L0zQPU9dFvDb+ OOrV0jx59hbK3QcCQju3YFuAtD1lu8TBIPgGEab0eJhLVIX+XU5cYXrfoBmwCpN/ 1wXWkUhN91ZVMA0ylATAxTpnoNuMKzfTxT8pyOWajiTskYkKmVBAxgYJQe1YDFA8 fglBNkQuHqP8jgYAniEBCAPZRMMq8WpOtyFx+L9LX9/WcHtAQyDPPb9M81KKgPQq urtCqtuDKxuqcX9zg4/O8l4nZ50pwaJjbH4kMW/wnLzTPvzZCPtJYQIDAQABo1Aw TjAdBgNVHQ4EFgQUJjhDDOup4P0cdrAVq1F9ap3yTj8wHwYDVR0jBBgwFoAUJjhD DOup4P0cdrAVq1F9ap3yTj8wDAYDVR0TBAUwAwEB/zANBgkqhkiG9w0BAQsFAAOC AQEAeKpTiy2WYPqevHseTCJDIL44zghDJ9w5JmECOhFgPXR9Hl5Nh9S1j4qHBs4G cn8d1p2+8tgcJpNAysjuSl4/MM6hQNecW0QVqvJDQGPn33bruMB4DYRT5du1Zpz1 YIKRjGU7Of3CycOCbaT50VZHhEd5GS2Lvg41ngxtsE8JKnvPuim92dnCutD0beV+ 4TEvoleIi/K4AZWIaekIyqazd0c7eQjgSclNGgePcdbaxIo0u6tmdTYk3RNzo99t DCfXxuMMg3wo5pbqG+MvTdECaLwt14zWU259z8JX0BoeVG32kHlt2eUpm5PCfxqc dYuwZmAXksp0T0cWo0DnjJKRGQ== -----END CERTIFICATE----- '''

VisTrails/VisTrails

vistrails/core/reportusage.py

Python

bsd-3-clause

12,618

[ "VTK" ]

68d73abebf4c6c69c6bf8f048be1792fc6af5cdc6139deba2aaee297b8eca5fe

from __future__ import print_function import psi4 from psi4.driver import qcdb #! A test of the basis specification. Various basis sets are specified outright and in blocks, both #! orbital and auxiliary. Constructs libmints BasisSet objects through the constructor that calls #! qcdb.BasisSet infrastructure. Checks that the resulting bases are of the right size and checks #! that symmetry of the Molecule observes the basis assignment to atoms. # cc-pvdz aug-cc-pvdz # BASIS H 5/ 5 C 14/15 H +4/ 4 C +9/10 # RIFIT H 14/15 C 56/66 H +9/10 C +16/20 # JKFIT H 23/25 C 70/81 H +9/10 C +16/20 mymol = psi4.geometry(""" C 0.0 0.0 0.0 O 1.4 0.0 0.0 H_r -0.5 -0.7 0.0 H_l -0.5 0.7 0.0 """) psi4.set_options({'basis': 'cc-pvdz'}) print('[1] <<< uniform cc-pVDZ >>>') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_strings('CC-PVDZ', psi4.core.get_global_option('BASIS'), 'name') #TEST psi4.compare_integers(38, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(40, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('CC-PVDZ', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[2] <<< RIFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(140, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(162, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(CC-PVDZ AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PVDZ-RI', wert.blend(), 'blend') #TEST mymol.print_out() print('[3] <<< cc-pVDZ w/ aug-cc-pVDZ on C >>>') psi4.basis_helper(""" assign cc-pvdz assign c aug-cc-pvdz """, name='dz_PLUS') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(47, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(50, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[4] <<< RIFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS')) mymol.print_out() wert.print_out() psi4.compare_integers(156, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(182, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(DZ_PLUS AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-RI + CC-PVDZ-RI', wert.blend(), 'blend') #TEST mymol.print_out() print('[5] <<< cc-pVDZ w/ aug-cc-pVDZ on C, H_R >>>') psi4.basis_helper(""" assign cc-pvdz assign c aug-cc-pvdz assign h_r aug-cc-pvdz """, name='dz_PLUSplus', key='BASis') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_strings('DZ_PLUSPLUS', psi4.core.get_global_option('BASIS'), 'name') #TEST psi4.compare_integers(51, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(54, wert.nao(), 'nao()') #TEST psi4.compare_strings('cs', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[6] <<< RIFIT (custom: force cc-pVDZ on H, default on C, O) >>>') psi4.basis_helper(""" assign h cc-pvdz-ri """, name='dz_PLUSplusRI', key='df_basis_mp2') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_MP2', psi4.core.get_global_option('DF_BASIS_MP2'), 'RIFIT', psi4.core.get_global_option('BASIS')) mymol.print_out() psi4.compare_integers(156, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(182, wert.nao(), 'nao()') #TEST psi4.compare_strings('cs', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUSRI', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-RI + CC-PVDZ-RI', wert.blend(), 'blend') #TEST mymol.print_out() print('[7] <<< cc-pVDZ w/ aug-cc-pVDZ on C, H >>>') psi4.basis_helper(""" assign cc-pvdz assign c aug-cc-pvdz assign h aug-cc-pvdz """, name = 'dz_PLUSplusplus') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(55, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(58, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUSPLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[8] <<< JKFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(220, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(252, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(DZ_PLUSPLUSPLUS AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-JKFIT + CC-PVDZ-JKFIT', wert.blend(), 'blend') #TEST mymol.print_out() psi4.set_options({'basis': 'aug-cc-pvdz'}) print('[9] <<< aug-cc-pVDZ >>>') wert = psi4.core.BasisSet.build(mymol, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(64, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(68, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('AUG-CC-PVDZ', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ', wert.blend(), 'blend') #TEST mymol.print_out() print('[10] <<< JKFIT (default) >>>') wert = psi4.core.BasisSet.build(mymol, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(236, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(272, wert.nao(), 'nao()') #TEST psi4.compare_strings('c2v', mymol.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('(AUG-CC-PVDZ AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ-JKFIT', wert.blend(), 'blend') #TEST mymol.print_out() mymol2 = psi4.geometry(""" C 0.0 0.0 0.0 O 1.4 0.0 0.0 H_r -0.5 -0.6 0.3 H_l -0.5 0.6 0.3 H_c -0.5 0.0 0.7 """) psi4.set_options({'basis': 'dz_plusplusplus'}) print('[11] <<< cc-pVDZ w/ aug-cc-pVDZ on C, H >>>') wert = psi4.core.BasisSet.build(mymol2, 'BASIS', psi4.core.get_global_option('BASIS')) psi4.compare_integers(64, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(67, wert.nao(), 'nao()') #TEST psi4.compare_strings('cs', mymol2.schoenflies_symbol(), 'symm') #TEST psi4.compare_strings('DZ_PLUSPLUSPLUS', wert.name(), 'callby') #TEST psi4.compare_strings('AUG-CC-PVDZ + CC-PVDZ', wert.blend(), 'blend') #TEST mymol2.print_out() hene = psi4.geometry(""" He Ne 1 2.0 """) psi4.basis_helper(""" assign cc-pv5z """, name='disguised5z') psi4.core.set_global_option('DF_BASIS_MP2', '') # clear df_basis_mp2 {...} to get autoaux below print('[12] <<< cc-pV5Z on HeNe >>>') wert = psi4.core.BasisSet.build(hene, 'BASIS', psi4.core.get_global_option('BASIS')) hene.print_out() psi4.compare_integers(146, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(196, wert.nao(), 'nao()') #TEST psi4.compare_strings('DISGUISED5Z', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PV5Z', wert.blend(), 'blend') #TEST print('[13] <<< RI for cc-pV5Z on HeNe >>>') wert = psi4.core.BasisSet.build(hene, 'DF_BASIS_MP2', '', 'RIFIT', psi4.core.get_global_option('BASIS')) hene.print_out() psi4.compare_integers(284, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(413, wert.nao(), 'nao()') #TEST psi4.compare_strings('(DISGUISED5Z AUX)', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PV5Z-RI', wert.blend(), 'blend') #TEST print('[14] <<< impossible JK for cc-pV5Z on HeNe >>>') error_tripped = 0 try: wert = psi4.core.BasisSet.build(hene, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) except qcdb.BasisSetNotFound: error_tripped = 1 psi4.compare_integers(1, error_tripped, 'squashed 4z aux for 5z orb') #TEST psi4.basis_helper(key='df_basis_scf', name='uggh', block=""" assign he DEF2-QZVPP-JKFIT """) hene.print_out() print('[15] <<< forced JK for cc-pV5Z on HeNe >>>') wert = psi4.core.BasisSet.build(hene, 'DF_BASIS_SCF', '', 'JKFIT', psi4.core.get_global_option('BASIS')) psi4.compare_integers(169, wert.nbf(), 'nbf()') #TEST psi4.compare_integers(241, wert.nao(), 'nao()') #TEST psi4.compare_strings('UGGH', wert.name(), 'callby') #TEST psi4.compare_strings('CC-PV5Z-JKFIT + DEF2-QZVPP-JKFIT', wert.blend(), 'blend') #TEST

kratman/psi4public

tests/python/mints9/input.py

Python

gpl-2.0

8,970

[ "Psi4" ]

6e5ebbef360a1a6cf2bb4bf50d6d44da19cfe56f43bc5bf83451f1fc46a2bf4a

#!/usr/bin/env python """ modules for large scale experiment runs includes: - reading of genome sequence in fasta format - manual cleaning of genome and annotation files - feature annotation db for querying details - creating star genome indicies Requirement: STAR aligner: https://github.com/alexdobin/STAR gfftools: https://github.com/vipints/genomeutils/tree/master/gfftools Biopython: http://biopython.org """ import os import re import sys import shutil import subprocess from Bio import SeqIO from gfftools import helper, GFFParser def stop_err(msg): """ stop the execution and print out the captured error message. """ sys.stderr.write('%s\n' % msg) sys.exit(-1) def clean_anno_file(chr_names, gtf_file, gtf_out): """ make stable annotation file with valid contig name @args chr_names: different contig names with a valid genome sequence @type chr_names: dict @args gtf_file: genome annotation in gtf/gff form @type gtf_file: str @args gtf_out: new genome annotation in gtf/gff form @type gtf_out: str """ # get the filehandler from input file try: fh = helper.open_file(gtf_file) except Exception, errmsg: stop_err('error %s in reading file %s' % (errmsg, gtf_file)) # check the out filehandler try: outfh = open(gtf_out, "w") except Exception, errmsg: stop_err('error %s in writing file %s' % (errmsg, gtf_out)) for line in fh: line = line.strip('\n\r') ## preserving the fasta header if present if line[0] in ['#', '>']: outfh.write(line + '\n') continue ## preserving the genome sequence if present if not re.search('\t', line): outfh.write(line + '\n') continue ## looking for gtf/gff files fields = line.split('\t') assert len(fields) >= 8, fields if fields[0] in chr_names: outfh.write(line + '\n') fh.close() outfh.close() def read_genome_file(fas_file): """ read genome file in fasta and return the list of chromosomes/contigs @args fas_file: genome sequence in fasta file @type fas_file: str returns a list with contig_names and length """ # get the filehandler from input file try: fh = helper.open_file(fas_file) except Exception, errmsg: stop_err('error in reading file '+ errmsg) chrom_names = [] for rec in SeqIO.parse(fh, "fasta"): print "parsing contig %s details" % rec.id chrom_names.append((rec.id, len(rec.seq))) fh.close() # return the list with chromosome identifier and its sequence length return chrom_names """ based on eye inspection, the returned list can be trimmed and create a dictionary with the best chromosomes , something like: Take the list 0-15 chr_best = chrom_names[0:15] change to dict chr_best = dict(chr_best) and finally this dictionary can be passed to the genome cleaning function - clean_genome_file """ def clean_genome_file(chr_names, fas_file, fas_out): """ make a stable genome file with valid contigs @args chr_names: different contig names with a valid genome sequence @type chr_names: dict @args fas_file: genome sequence in fasta file @type fas_file: str @args fas_out: new genome sequence file in fasta format @type fas_out: str """ # get the filehandler from input file try: fh = helper.open_file(fas_file) except Exception, errmsg: stop_err('error in reading file '+ errmsg) # check the out filehandler try: outfh = open(fas_out, "w") except Exception, errmsg: stop_err('error in writing file '+ errmsg) # writing stable contig genome sequence in FASTA format for rec in SeqIO.parse(fh, "fasta"): if rec.id in chr_names: outfh.write(rec.format("fasta")) print "writing the contig %s details" % rec.id fh.close() outfh.close() def genome_file_rec_extract(chr_pattn, fas_file, fas_out): """ get all contings based on a matiching string in the record identifier @args chr_pattn: pattern to be searched in contig names @type chr_pattn: str @args fas_file: genome sequence in fasta file @type fas_file: str @args fas_out: new genome sequence file in fasta format @type fas_out: str """ # get the filehandler from input file try: fh = helper.open_file(fas_file) except Exception, errmsg: stop_err('error in reading file '+ errmsg) # check the out filehandler try: outfh = open(fas_out, "w") except Exception, errmsg: stop_err('error in writing file '+ errmsg) # writing stable contig genome sequence in FASTA format for rec in SeqIO.parse(fh, "fasta"): if re.search(chr_pattn, rec.id): outfh.write(rec.format("fasta")) print "writing the contig %s details" % rec.id fh.close() outfh.close() def make_anno_db(gff_file): """ extract the features from a gtf/gff file and store efficiently to query @args gff_file: genome annotation file @type gff_file: str """ gff_cont = GFFParser.Parse(gff_file) intron_size = dict() exon_size = dict() for rec in gff_cont: for idx, tid in enumerate(rec['transcripts']): if not rec['exons'][idx].any(): continue try: # (Pdb) rec['exons'][0] -> array(nan) import numpy as np if np.isnan(rec['exons'][idx]): continue except: pass try: exon_cnt = len(rec['exons'][idx]) except: continue if exon_cnt > 1: intron_start = 0 for xq, excod in enumerate(rec['exons'][idx]): if xq > 0: #print intron_start, excod[0]-1 if excod[0]-intron_start==1: intron_start = excod[1]+1 exon_size[intron_start-excod[0]] = 1 continue intron_size[excod[0]-intron_start] = 1 #print excod[0]-intron_start intron_start = excod[1]+1 exon_size[intron_start-excod[0]] = 1 #print intron_start-excod[0] feat_db = dict() if intron_size: keys_int = sorted(intron_size) keys_ex = sorted(exon_size) #print 'MaxIntronLength %d %d %d' %(keys_int[-1], keys_int[-2], keys_int[-3]) feat_db['min_intron'] = int(keys_int[0]) feat_db['max_intron'] = int(keys_int[-3]) feat_db['min_exon'] = int(keys_ex[0]) feat_db['max_exon'] = int(keys_ex[-3]) #print 'MaxExonLength %d %d %d' %(keys_ex[-1], keys_ex[-2], keys_ex[-3]) return feat_db else: print "Error in feature mapping in file %s, please check the source of parent child features" % gff_file sys.exit(-1) def create_star_genome_index(fasta_file, out_dir, genome_anno=None, num_workers=1, onematelength=100): """ Creating STAR genome index with or without using genome annotation @args fasta_file: reference genome sequence file .fasta format @type fasta_file: str @args out_dir: genome index binary file storage place @type out_dir: str @args genome_anno: genome annotation file (optional) @type genome_anno: str @args num_workers: number of threads to run (default value = 1) @type num_workers: int @args onematelength: One Mate Length (default value=100) @type onematelength: int """ try: subprocess.call(["STAR"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) except: exit("Please make sure that the `STAR` binary is in your $PATH") file_prefx, ext = os.path.splitext(fasta_file) if ext in [".bz2", ".gz", ".lzma"]: ## checking for the compressed form of the file extension exit("error: STAR - Generating genome indexes - recommended to use the uncompressed FASTA file %s." % fasta_file) if not genome_anno: cli_cmd = 'STAR \ --runMode genomeGenerate \ --genomeDir %s \ --genomeFastaFiles %s \ --runThreadN %d' % (out_dir, fasta_file, num_workers) else: file_prefx, ext = os.path.splitext(genome_anno) if ext in [".bz2", ".gz", ".lzma"]: exit("error: STAR - Generating genome indexes - recommended to use the uncompressed GTF/GFF file %s." % genome_anno) ## check for the file type gff_hand = helper.open_file(genome_anno) for rec in gff_hand: rec = rec.strip('\n\r') # skip empty line fasta identifier and commented line if not rec or rec[0] in ['#', '>']: continue # skip the genome sequence if not re.search('\t', rec): continue parts = rec.split('\t') assert len(parts) >= 8, rec ftype, tags = GFFParser.attribute_tags(parts[-1]) break gff_hand.close() ## according to the file type if ftype: cli_cmd = 'STAR \ --runMode genomeGenerate \ --genomeDir %s \ --genomeFastaFiles %s \ --runThreadN %d \ --sjdbGTFfile %s \ --sjdbGTFtagExonParentTranscript Parent \ --sjdbOverhang %d' % (out_dir, fasta_file, num_workers, genome_anno, onematelength) else: cli_cmd = 'STAR \ --runMode genomeGenerate \ --genomeDir %s \ --genomeFastaFiles %s \ --runThreadN %d \ --sjdbGTFfile %s \ --sjdbGTFfeatureExon exon \ --sjdbOverhang %d' % (out_dir, fasta_file, num_workers, genome_anno, onematelength) ## create downloadpath if doesnot exists if not os.path.exists(out_dir): try: os.makedirs(out_dir) except OSError: exit("error: cannot create the directory %s." % out_dir) else:## if present any other old index files clean up the folder for the_file in os.listdir(out_dir): file_path = os.path.join(out_dir, the_file) try: if os.path.isfile(file_path): os.unlink(file_path) elif os.path.isdir(file_path): shutil.rmtree(file_path) except Exception, e: print(e) ## start the indexing job sys.stdout.write('\trunning program as: %s \n' % cli_cmd) try: ## changing the working dir to run STAR os.chdir(out_dir) ## Run command. process = subprocess.Popen(cli_cmd, shell=True) returncode = process.wait() ## Error checking. if returncode != 0: raise Exception, "return code = %i" % returncode print("\nGenome index files are stored at %s\n" % out_dir) except Exception, e: exit('Error running STAR.\n%s' % str( e )) def parse_list(line, nb_elts): """ specific to BWA-MEM stderr format """ return map(lambda x: int(float(x)), ' '.join(line.strip().replace(',','').split()[-nb_elts:])[1:-1].split()) def calculate_insert_size_fastq(ref_genome, fastq_dir, fq_files): """ calculate the library insert size from raw read files and reference genome sequence @args ref_genome: genome sequence file @type ref_genome: str @args fastq_dir: fastq directory for the experiment @type fastq_dir: str @args fq_files: fastq file names in python list @type fq_files: list """ try: subprocess.call(["bwa"], stdout=subprocess.PIPE, stderr=subprocess.PIPE) except: exit("Please make sure that the `bwa` binary is in your $PATH") ## check for the bwa index if not os.path.isfile("%s.sa" % ref_genome): try: cmd_idx = "bwa index %s" % ref_genome sys.stdout.write("bwa indexing starting...\n") process = subprocess.Popen(cmd_idx, shell=True) returncode = process.wait() if returncode !=0: raise Exception, "Exit status return code = %i" % returncode sys.stdout.write("bwa indexing finished\n") except Exception, e: exit('Error running bwa index.\n%s' % str( e )) ##adapted from: ##Quickly estimates insert sizes of read datasets, given some sequence(s) they can be mapped to. ##Author: Rayan Chikhi ##example: ## estimate-insert-sizes contigs.fa readsA_1.fq readsA_2.fq readsB_1.fq readsB_2.fq if len(fq_files) > 1: nb_cpu = 1 zip_type = {".gz" : "gzip -c", ".bz2" : "bzip2 -d -c"} file_prefx, ext = os.path.splitext(fq_files[0]) stats = dict() read1 = "%s/%s" % (fastq_dir, fq_files[0]) read2 = "%s/%s" % (fastq_dir, fq_files[1]) print("processing : \n %s \n %s " % (read1, read2)) cmd = ["bwa", "mem"] + ["-t %d" % nb_cpu, ref_genome] + ["<(%s %s)" % (zip_type[ext], read1)] \ +["<(%s %s)" % ( zip_type[ext], read2)] DEVNULL = open(os.devnull, 'wb') process = subprocess.Popen(cmd, stdout=DEVNULL, stderr=subprocess.PIPE) seen_candidate_line = False while True: line = process.stderr.readline() if line == '' and process.poll() != None: break if "worker" in line: break if "pestat" not in line: continue if "candidate unique pairs for" in line: if seen_candidate_line: break seen_candidate_line = True nb_pairs = parse_list(line,4) for i in xrange(4): stats[['FF', 'FR', 'RF', 'RR'][i]] = { 'nb_pairs' : nb_pairs[i] } if "orientation" in line: orientation = line.strip().split()[-1].replace('.','') if "mem_pestat] mean and std.dev:" in line: mean, stdev = parse_list(line,2) stats[orientation]['mean'] = mean stats[orientation]['stdev'] = stdev if orientation == 'RR': # stats are complete break sys.stdout.write(line) sys.stdout.flush() if process.poll() is None: process.terminate() results = sorted(stats.items(), key = lambda x: x[1]['nb_pairs'], reverse=True) most_likely = results[0] mean = most_likely[1]['mean'] stdev = most_likely[1]['stdev'] print "Orientation", most_likely[0], "mean", mean, "stdev", stdev if __name__=="__main__": print __doc__

vipints/genomeutils

fetch_remote_data/prepare_data.py

Python

bsd-3-clause

15,195

[ "BWA", "Biopython" ]

51ac0fb0ed692f6e7fc0ae882fe9ff6e7492eecc5430ad614efcb9e0429469fe

#!/usr/bin/env python # -*- coding: utf-8 -*- # # shapes.py # # Copyright 2015 Carlos Eduardo Sequeiros Borja <casebor@gmail.com> # # This program is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, # MA 02110-1301, USA. # # import math from optparse import OptionParser """ ############################################################################## # # # This script increment the X position of an Atom a determined quantity # # # ############################################################################## """ def amberAtomType(atom): '''amberAtoms = ('H', 'HC', 'HO', 'HS', 'HW', 'H2', 'H3', 'C', 'CA', 'CB', 'CC', 'CK', 'CM', 'CN',\ 'CQ', 'CR', 'CT', 'CV', 'CW', 'C*', 'CD', 'CE', 'CF', 'CG', 'CH', 'CI', 'CJ', 'CP', 'C2', 'C3',\ 'N', 'NA', 'NB', 'NC', 'NT', 'N2', 'N3', 'N*', 'O', 'OH', 'OS', 'OW', 'O2', 'S', 'SH', 'P',\ 'CU', 'C0', 'I', 'IM', 'MG', 'QC', 'QK', 'QL', 'QN', 'QR', 'LP')''' amberAtoms = {'C', 'O', 'N', 'S', 'P', 'MG', 'F', 'Ar', 'CL', 'NA', 'H', 'BR', 'CA', 'ZN'} return atom in amberAtoms def isANearB(elemA, aX, aY, aZ, radA, cadPdb): resp = False cads = cadPdb.split('\n') i = 0 while i<len(cads) and not resp: if elemA in cads[i]: cadsA = cads[i].split() x = float(cadsA[5]) y = float(cadsA[6]) z = float(cadsA[7]) distAB = ((aX-x)**2 + (aY-y)**2 + (aZ-z)**2)**0.5 if distAB<radA: resp = True i += 1 return resp def complexOK(): if len(options.complexF)<7: return False else: elems = options.complexF.split('-') if len(elems)<>4: parse.error('Option complex must have 4 elements, and they must be valid Amber ATOMS!!!') quit() else: for i in elems: if not amberAtomType(i): parse.error('Option complex must have 4 elements, and they must be valid Amber ATOMS!!!') quit() return True def add_tapa(): global AT_POS cad = '' i = -3.6 temp = int(options.Ri/3.6) #AT_POS = 1 cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, 0.0, 0.0) AT_POS += 1 for t in range(1, temp+1): rad = 3.6 * t perim = 2*math.pi*rad razon = perim/(int(perim/3.6)) ang = razon/rad temp = razon/rad while temp <= (2*math.pi)+0.1: j = rad*math.cos(temp) k = rad*math.sin(temp) cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 temp += ang return cad def main(): global AT_POS AT_POS = 1 cad = add_tapa() dAtAt = 3.55 dAtAt2 = 3.55 cont = 1 i = 0.0 arco = 3.6 if options.shapeS.upper() == 'CONE': while (i<options.TxC): perim = 2*math.pi*options.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang <= (2*math.pi)+0.1: j = options.Ri*math.cos(ang) k = options.Ri*math.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 if cont%3 == 0: dAtAt2 -= 0.2 cont += 1 i += dAtAt2 options.Ri = options.Ri+1.3*math.log10(options.Ri)**2 elif options.shapeS.upper() == 'TUBE': while (i<options.TxT): perim = 2*math.pi*options.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang < (2*math.pi)+0.1: j = options.Ri*math.cos(ang) k = options.Ri*math.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 i += dAtAt elif options.shapeS.upper() == 'FUNNEL' and not complexOK(): while (i<options.TxT+options.TxC): if i<=options.TxT: perim = 2*math.pi*options.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang < (2*math.pi)+0.1: j = options.Ri*math.cos(ang) k = options.Ri*math.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 else: perim = 2*math.pi*options.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang <= (2*math.pi)+0.1: j = options.Ri*math.cos(ang) k = options.Ri*math.sin(ang) ang += temp if len(options.elem2)>0 and not isANearB(options.elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem2, options.elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, options.elem, options.elem, AT_POS, i, j, k) AT_POS += 1 options.Ri += 1.3*math.log10(options.Ri)**2 i += dAtAt elif options.shapeS.upper() == 'FUNNEL' and complexOK(): elems = options.complexF.split('-') elem1 = elems[0] elem2 = elems[1] elem3 = elems[2] elem4 = elems[3] while (i<options.TxT+options.TxC): if i<=options.TxT: perim = 2*math.pi*options.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang < (2*math.pi)+0.1: j = options.Ri*math.cos(ang) k = options.Ri*math.sin(ang) ang += temp if not isANearB(elem2, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem2, elem2, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem1, elem1, AT_POS, i, j, k) AT_POS += 1 else: perim = 2*math.pi*options.Ri razon = perim/(int(perim/arco)) ang = razon/options.Ri temp = ang while ang <= (2*math.pi)+0.1: j = options.Ri*math.cos(ang) k = options.Ri*math.sin(ang) ang += temp if not isANearB(elem4, i, j, k, options.interval, cad): cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem4, elem4, AT_POS, i, j, k) else: cad += 'ATOM %5d %4s %3s %5d %8.3f%8.3f%8.3f 1.00 0.00\n' %(AT_POS, elem3, elem3, AT_POS, i, j, k) AT_POS += 1 #options.Ri += 1.3*math.log10(options.Ri)**2 dAtAt -= 0.2 options.Ri += 3.6 i += dAtAt else: print 'Error in shape type' parser.print_help() quit() if len(options.outFile) > 0: arch = open(options.outFile, 'w') else: if not complexOK(): if len(options.elem2)>0: outF = options.shapeS + '-' + options.elem + '-' + options.elem2 + '.pdb' else: outF = options.shapeS + '-' + options.elem + '.pdb' else: elems = options.complexF.split('-') outF = options.shapeS + '-' + elems[0] + '-' + elems[1] + '-' + elems[2] + '-' + elems[3] + '.pdb' arch = open(outF, 'w') arch.write(cad) arch.close() return 0 if __name__ == '__main__': usage = 'usage: \"%prog [options] args\" or \"%prog\"' parser = OptionParser(usage) parser.add_option('-o', '--out', action='store', type='string', dest='outFile', help='Defines the name of the output pdb file. Default is the SHAPE+_+ELEMENT+.pdb', default='') parser.add_option('-w', '--with', action='store', type='string', dest='elem2', help='Use this option to add other ATOM in your shape in regular intervals. You can change the interval with -i or --interval', default='') parser.add_option('-s', '--shape', action='store', type='string', dest='shapeS', help='Defines the shape of the object to be created. Values admitted are CONE, TUBE or FUNNEL. Default is CONE', default='CONE') parser.add_option('-r', '--radius', action='store', type='float', dest='Ri', help='This option set the radius of the desired shape in ANGSTROMS. Default is 10.0 A', default='10.0') parser.add_option('-e', '--element', action='store', type='string', dest='elem', help='Is the element used to make the structure', default='Ar') parser.add_option('-c', '--complex', action='store', type='string', dest='complexF', help='Use this option ONLY if you want to make your FUNNEL with different elements on the TUBE part than those in the CONE part. The syntax is: elem1TUBE-elem2TUBE-elem1CONE-elem2CONE, note that you need to use the \'-\' between elements. You can change the interval with -i or --interval', default='') parser.add_option('-d', '--distcone', action='store', type='float', dest='TxC', help='If you have chosen the cone shape, this option set the HEIGHT of the cone in ANGSTROMS; if you have chosen the funnel shape, this set the HEIGHT part of the funnel. Default is 40.0 A', default='40.0') parser.add_option('-i', '--interval', action='store', type='float', dest='interval', help='Set the interval for the addition of other ATOMS. Default 6.0A. Use this option only if you use -w, --with, -c or --complex!!!', default='6.0') parser.add_option('-l', '--disttunnel', action='store', type='float', dest='TxT', help='If you have chosen the tunnel shape, this option ser the LENGTH of the tunnel in ANGSTROMS; if you have chosen the funnel shape, this set the LENGTH of the tunnel part of the funnel. Default is 40.0 A', default='40.0') (options, args) = parser.parse_args() if (options.TxT<0) or (options.TxC<0) or (options.Ri<0): parser.error('Options -l, -d and -r must be positive or 0!!!') exit if not amberAtomType(options.elem): parse.error('Option element must be a valid Amber ATOM!!!') quit() if len(options.elem2)>0 and not amberAtomType(options.elem2): parse.error('Option with must be a valid Amber ATOM!!!') quit() main()

casebor/labioscripts

python/shapes_tapa.py

Python

gpl-3.0

10,847

[ "Amber" ]

f3b28716bd3e807e6b0d3a1084800076584283a0c67b59e0db19a9887eebf09f

# -*- coding: utf-8 -*- """Tests for :mod:`pybel.manager`."""

pybel/pybel

tests/test_manager/__init__.py

Python

mit

63

[ "Pybel" ]

c559c00364647dcb3fce6dde582359d525e79dc9e80c70d172fb19aedbf0b35a

######################################################################## # $Id$ ######################################################################## """ FileManagerBase is a base class for all the specific File Managers """ __RCSID__ = "$Id$" from DIRAC import S_OK, S_ERROR, gLogger from DIRAC.Core.Utilities.List import intListToString from DIRAC.Core.Utilities.Pfn import pfnparse, pfnunparse import os import stat class FileManagerBase( object ): def __init__( self, database = None ): self.db = database self.statusDict = {} def _getConnection( self, connection ): if connection: return connection res = self.db._getConnection() if res['OK']: return res['Value'] gLogger.warn( "Failed to get MySQL connection", res['Message'] ) return connection def setDatabase( self, database ): self.db = database def getFileCounters( self, connection = False ): """ Get a number of counters to verify the sanity of the Files in the catalog """ connection = self._getConnection( connection ) resultDict = {} req = "SELECT COUNT(*) FROM FC_Files;" res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Files'] = res['Value'][0][0] req = "SELECT COUNT(FileID) FROM FC_Files WHERE FileID NOT IN ( SELECT FileID FROM FC_Replicas )" res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Files w/o Replicas'] = res['Value'][0][0] req = "SELECT COUNT(RepID) FROM FC_Replicas WHERE FileID NOT IN ( SELECT FileID FROM FC_Files )" res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Replicas w/o Files'] = res['Value'][0][0] treeTable = self.db.dtree.getTreeTable() req = "SELECT COUNT(FileID) FROM FC_Files WHERE DirID NOT IN ( SELECT DirID FROM %s)" % treeTable res = self.db._query( req, connection ) if not res['OK']: return res resultDict['Orphan Files'] = res['Value'][0][0] req = "SELECT COUNT(FileID) FROM FC_Files WHERE FileID NOT IN ( SELECT FileID FROM FC_FileInfo)" res = self.db._query( req, connection ) if not res['OK']: resultDict['Files w/o FileInfo'] = 0 else: resultDict['Files w/o FileInfo'] = res['Value'][0][0] req = "SELECT COUNT(FileID) FROM FC_FileInfo WHERE FileID NOT IN ( SELECT FileID FROM FC_Files)" res = self.db._query( req, connection ) if not res['OK']: resultDict['FileInfo w/o Files'] = 0 else: resultDict['FileInfo w/o Files'] = res['Value'][0][0] return S_OK( resultDict ) def getReplicaCounters( self, connection = False ): """ Get a number of counters to verify the sanity of the Replicas in the catalog """ connection = self._getConnection( connection ) req = "SELECT COUNT(*) FROM FC_Replicas;" res = self.db._query( req, connection ) if not res['OK']: return res return S_OK( {'Replicas':res['Value'][0][0]} ) ###################################################### # # File write methods # def _insertFiles( self, lfns, uid, gid, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _deleteFiles( self, toPurge, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _insertReplicas( self, lfns, master = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _findFiles( self, lfns, metadata = ["FileID"], allStatus = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getFileReplicas( self, fileIDs, fields_input = ['PFN'], allStatus = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getFileIDFromGUID( self, guid, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def getLFNForGUID( self, guids, connection = False ): """Returns the LFN matching a given GUID """ return S_ERROR( "To be implemented on derived class" ) def _setFileParameter( self, fileID, paramName, paramValue, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _deleteReplicas( self, lfns, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _setReplicaStatus( self, fileID, se, status, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _setReplicaHost( self, fileID, se, newSE, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getDirectoryFiles( self, dirID, fileNames, metadata, allStatus = False, connection = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _getDirectoryFileIDs( self, dirID, requestString = False ): """To be implemented on derived class """ return S_ERROR( "To be implemented on derived class" ) def _findFileIDs( self, lfns, connection=False ): """ To be implemented on derived class Should return following the successful/failed convention Successful is a dictionary with keys the lfn, and values the FileID""" return S_ERROR( "To be implemented on derived class" ) def _getDirectoryReplicas( self, dirID, allStatus = False, connection = False ): """ To be implemented on derived class Should return with only one value, being a list of all the replicas (FileName,FileID,SEID,PFN) """ return S_ERROR( "To be implemented on derived class" ) def countFilesInDir( self, dirId ): """ Count how many files there is in a given Directory :param dirID : directory id :returns S_OK(value) or S_ERROR """ return S_ERROR( "To be implemented on derived class" ) def _getFileLFNs(self,fileIDs): """ Get the file LFNs for a given list of file IDs """ stringIDs = intListToString(fileIDs) treeTable = self.db.dtree.getTreeTable() req = "SELECT F.FileID, CONCAT(D.DirName,'/',F.FileName) from FC_Files as F, %s as D WHERE F.FileID IN ( %s ) AND F.DirID=D.DirID" % (treeTable,stringIDs) result = self.db._query(req) if not result['OK']: return result fileNameDict = {} for row in result['Value']: fileNameDict[row[0]] = row[1] failed = {} successful = fileNameDict if len(fileNameDict) != len(fileIDs): for id_ in fileIDs: if not id_ in fileNameDict: failed[id_] = "File ID not found" return S_OK({'Successful':successful,'Failed':failed}) def addFile( self, lfns, credDict, connection = False ): """ Add files to the catalog :param lfns : dict { lfn : info}. 'info' is a dict containing PFN, SE, Size and Checksum the SE parameter can be a list if we have several replicas to register """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['PFN', 'SE', 'Size', 'Checksum'] ) if not res['OK']: failed[lfn] = res['Message'] lfns.pop( lfn ) res = self._addFiles( lfns, credDict, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: failed.update( res['Value']['Failed'] ) successful.update( res['Value']['Successful'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def _addFiles( self, lfns, credDict, connection = False ): """ Main file adding method """ connection = self._getConnection( connection ) successful = {} result = self.db.ugManager.getUserAndGroupID( credDict ) if not result['OK']: return result uid, gid = result['Value'] # prepare lfns with master replicas - the first in the list or a unique replica masterLfns = {} extraLfns = {} for lfn in lfns: masterLfns[lfn] = dict( lfns[lfn] ) if isinstance( lfns[lfn].get( 'SE' ), list ): masterLfns[lfn]['SE'] = lfns[lfn]['SE'][0] if len( lfns[lfn]['SE'] ) > 1: extraLfns[lfn] = dict( lfns[lfn] ) extraLfns[lfn]['SE'] = lfns[lfn]['SE'][1:] # Check whether the supplied files have been registered already existingMetadata, failed = self._getExistingMetadata( masterLfns.keys(), connection = connection ) if existingMetadata: success, fail = self._checkExistingMetadata( existingMetadata, masterLfns ) successful.update( success ) failed.update( fail ) for lfn in ( success.keys() + fail.keys() ): masterLfns.pop( lfn ) # If GUIDs are supposed to be unique check their pre-existance if self.db.uniqueGUID: fail = self._checkUniqueGUID( masterLfns, connection = connection ) failed.update( fail ) for lfn in fail: masterLfns.pop( lfn ) # If we have files left to register if masterLfns: # Create the directories for the supplied files and store their IDs directories = self._getFileDirectories( masterLfns.keys() ) for directory, fileNames in directories.items(): res = self.db.dtree.makeDirectories( directory, credDict ) if not res['OK']: for fileName in fileNames: lfn = os.path.join( directory, fileName ) failed[lfn] = res['Message'] masterLfns.pop( lfn ) continue for fileName in fileNames: if not fileName: failed[directory] = "Is no a valid file" masterLfns.pop( directory ) continue lfn = "%s/%s" % ( directory, fileName ) lfn = lfn.replace( '//', '/' ) # This condition should never be true, we would not be here otherwise... if not res['OK']: failed[lfn] = "Failed to create directory for file" masterLfns.pop( lfn ) else: masterLfns[lfn]['DirID'] = res['Value'] # If we still have files left to register if masterLfns: res = self._insertFiles( masterLfns, uid, gid, connection = connection ) if not res['OK']: for lfn in masterLfns.keys(): failed[lfn] = res['Message'] masterLfns.pop( lfn ) else: for lfn, error in res['Value']['Failed'].items(): failed[lfn] = error masterLfns.pop( lfn ) masterLfns = res['Value']['Successful'] # Add the ancestors if masterLfns: res = self._populateFileAncestors( masterLfns, connection = connection ) toPurge = [] if not res['OK']: for lfn in masterLfns.keys(): failed[lfn] = "Failed while registering ancestors" toPurge.append( masterLfns[lfn]['FileID'] ) else: failed.update( res['Value']['Failed'] ) for lfn, error in res['Value']['Failed'].items(): toPurge.append( masterLfns[lfn]['FileID'] ) if toPurge: self._deleteFiles( toPurge, connection = connection ) # Register the replicas newlyRegistered = {} if masterLfns: res = self._insertReplicas( masterLfns, master = True, connection = connection ) toPurge = [] if not res['OK']: for lfn in masterLfns.keys(): failed[lfn] = "Failed while registering replica" toPurge.append( masterLfns[lfn]['FileID'] ) else: newlyRegistered = res['Value']['Successful'] successful.update( newlyRegistered ) failed.update( res['Value']['Failed'] ) for lfn, error in res['Value']['Failed'].items(): toPurge.append( masterLfns[lfn]['FileID'] ) if toPurge: self._deleteFiles( toPurge, connection = connection ) # Add extra replicas for successfully registered LFNs for lfn in extraLfns.keys(): if not lfn in successful: extraLfns.pop( lfn ) if extraLfns: res = self._findFiles( extraLfns.keys(), ['FileID','DirID'], connection=connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = 'Failed while registering extra replicas' successful.pop( lfn ) extraLfns.pop( lfn ) else: failed.update(res['Value']['Failed']) for lfn in res['Value']['Failed'].keys(): successful.pop(lfn) extraLfns.pop( lfn ) for lfn,fileDict in res['Value']['Successful'].items(): extraLfns[lfn]['FileID'] = fileDict['FileID'] extraLfns[lfn]['DirID'] = fileDict['DirID'] if extraLfns: res = self._insertReplicas( extraLfns, master = False, connection = connection ) if not res['OK']: for lfn in extraLfns.keys(): failed[lfn] = "Failed while registering extra replicas" successful.pop( lfn ) else: newlyRegistered = res['Value']['Successful'] successful.update( newlyRegistered ) failed.update( res['Value']['Failed'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def _updateDirectoryUsage( self, directorySEDict, change, connection = False ): connection = self._getConnection( connection ) for directoryID in directorySEDict.keys(): result = self.db.dtree.getPathIDsByID( directoryID ) if not result['OK']: return result parentIDs = result['Value'] dirDict = directorySEDict[directoryID] for seID in dirDict.keys() : seDict = dirDict[seID] files = seDict['Files'] size = seDict['Size'] insertTuples = [] for dirID in parentIDs: insertTuples.append( '(%d,%d,%d,%d,UTC_TIMESTAMP())' % ( dirID, seID, size, files ) ) req = "INSERT INTO FC_DirectoryUsage (DirID,SEID,SESize,SEFiles,LastUpdate) " req += "VALUES %s" % ','.join( insertTuples ) req += " ON DUPLICATE KEY UPDATE SESize=SESize%s%d, SEFiles=SEFiles%s%d, LastUpdate=UTC_TIMESTAMP() " \ % ( change, size, change, files ) res = self.db._update( req ) if not res['OK']: gLogger.warn( "Failed to update FC_DirectoryUsage", res['Message'] ) return S_OK() def _populateFileAncestors( self, lfns, connection = False ): connection = self._getConnection( connection ) successful = {} failed = {} for lfn, lfnDict in lfns.items(): originalFileID = lfnDict['FileID'] originalDepth = lfnDict.get( 'AncestorDepth', 1 ) ancestors = lfnDict.get( 'Ancestors', [] ) if type( ancestors ) == type( ' ' ): ancestors = [ancestors] if lfn in ancestors: ancestors.remove( lfn ) if not ancestors: successful[lfn] = True continue res = self._findFiles( ancestors, connection = connection ) if res['Value']['Failed']: failed[lfn] = "Failed to resolve ancestor files" continue ancestorIDs = res['Value']['Successful'] fileIDLFNs = {} toInsert = {} for ancestor in ancestorIDs.keys(): fileIDLFNs[ancestorIDs[ancestor]['FileID']] = ancestor toInsert[ancestorIDs[ancestor]['FileID']] = originalDepth res = self._getFileAncestors( fileIDLFNs.keys() ) if not res['OK']: failed[lfn] = "Failed to obtain all ancestors" continue fileIDAncestorDict = res['Value'] for fileIDDict in fileIDAncestorDict.values(): for ancestorID, relativeDepth in fileIDDict.items(): toInsert[ancestorID] = relativeDepth + originalDepth res = self._insertFileAncestors( originalFileID, toInsert, connection = connection ) if not res['OK']: if "Duplicate" in res['Message']: failed[lfn] = "Failed to insert ancestor files: duplicate entry" else: failed[lfn] = "Failed to insert ancestor files" else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def _insertFileAncestors( self, fileID, ancestorDict, connection = False ): connection = self._getConnection( connection ) ancestorTuples = [] for ancestorID, depth in ancestorDict.items(): ancestorTuples.append( "(%d,%d,%d)" % ( fileID, ancestorID, depth ) ) if not ancestorTuples: return S_OK() req = "INSERT INTO FC_FileAncestors (FileID, AncestorID, AncestorDepth) VALUES %s" \ % intListToString( ancestorTuples ) return self.db._update( req, connection ) def _getFileAncestors( self, fileIDs, depths = [], connection = False ): connection = self._getConnection( connection ) req = "SELECT FileID, AncestorID, AncestorDepth FROM FC_FileAncestors WHERE FileID IN (%s)" \ % intListToString( fileIDs ) if depths: req = "%s AND AncestorDepth IN (%s);" % ( req, intListToString( depths ) ) res = self.db._query( req, connection ) if not res['OK']: return res fileIDAncestors = {} for fileID, ancestorID, depth in res['Value']: if not fileIDAncestors.has_key( fileID ): fileIDAncestors[fileID] = {} fileIDAncestors[fileID][ancestorID] = depth return S_OK( fileIDAncestors ) def _getFileDescendents( self, fileIDs, depths, connection = False ): connection = self._getConnection( connection ) req = "SELECT AncestorID, FileID, AncestorDepth FROM FC_FileAncestors WHERE AncestorID IN (%s)" \ % intListToString( fileIDs ) if depths: req = "%s AND AncestorDepth IN (%s);" % ( req, intListToString( depths ) ) res = self.db._query( req, connection ) if not res['OK']: return res fileIDAncestors = {} for ancestorID, fileID, depth in res['Value']: if not fileIDAncestors.has_key( ancestorID ): fileIDAncestors[ancestorID] = {} fileIDAncestors[ancestorID][fileID] = depth return S_OK( fileIDAncestors ) def addFileAncestors(self,lfns, connection = False ): """ Add file ancestors to the catalog """ connection = self._getConnection( connection ) failed = {} successful = {} result = self._findFiles( lfns.keys(), connection = connection ) if not result['OK']: return result if result['Value']['Failed']: failed.update(result['Value']['Failed']) for lfn in result['Value']['Failed']: lfns.pop(lfn) if not lfns: return S_OK({'Successful':successful,'Failed':failed}) for lfn in result['Value']['Successful']: lfns[lfn]['FileID'] = result['Value']['Successful'][lfn]['FileID'] result = self._populateFileAncestors(lfns, connection) if not result['OK']: return result failed.update(result['Value']['Failed']) successful = result['Value']['Successful'] return S_OK({'Successful':successful,'Failed':failed}) def _getFileRelatives( self, lfns, depths, relation, connection = False ): connection = self._getConnection( connection ) failed = {} successful = {} result = self._findFiles( lfns.keys(), connection = connection ) if not result['OK']: return result if result['Value']['Failed']: failed.update(result['Value']['Failed']) for lfn in result['Value']['Failed']: lfns.pop(lfn) if not lfns: return S_OK({'Successful':successful,'Failed':failed}) inputIDDict = {} for lfn in result['Value']['Successful']: inputIDDict[ result['Value']['Successful'][lfn]['FileID'] ] = lfn inputIDs = inputIDDict.keys() if relation == 'ancestor': result = self._getFileAncestors(inputIDs,depths, connection) else: result = self._getFileDescendents(inputIDs,depths, connection) if not result['OK']: return result failed = {} successful = {} relDict = result['Value'] for id_ in inputIDs: if id_ in relDict: aList = relDict[id_].keys() result = self._getFileLFNs(aList) if not result['OK']: failed[inputIDDict[id]] = "Failed to find %s" % relation else: if result['Value']['Successful']: resDict = {} for aID in result['Value']['Successful']: resDict[ result['Value']['Successful'][aID] ] = relDict[id_][aID] successful[inputIDDict[id_]] = resDict for aID in result['Value']['Failed']: failed[inputIDDict[id_]] = "Failed to get the ancestor LFN" else: successful[inputIDDict[id_]] = {} return S_OK({'Successful':successful,'Failed':failed}) def getFileAncestors( self, lfns, depths, connection = False ): return self._getFileRelatives(lfns, depths, 'ancestor', connection) def getFileDescendents( self, lfns, depths, connection = False ): return self._getFileRelatives(lfns, depths, 'descendent', connection) def _getExistingMetadata( self, lfns, connection = False ): connection = self._getConnection( connection ) # Check whether the files already exist before adding res = self._findFiles( lfns, ['FileID', 'Size', 'Checksum', 'GUID'], connection = connection ) successful = res['Value']['Successful'] failed = res['Value']['Failed'] for lfn, error in res['Value']['Failed'].items(): if error == 'No such file or directory': failed.pop( lfn ) return successful, failed def _checkExistingMetadata( self, existingLfns, lfns ): failed = {} successful = {} fileIDLFNs = {} for lfn, fileDict in existingLfns.items(): fileIDLFNs[fileDict['FileID']] = lfn # For those that exist get the replicas to determine whether they are already registered res = self._getFileReplicas( fileIDLFNs.keys() ) if not res['OK']: for lfn in fileIDLFNs.values(): failed[lfn] = 'Failed checking pre-existing replicas' else: replicaDict = res['Value'] for fileID, lfn in fileIDLFNs.items(): fileMetadata = existingLfns[lfn] existingGuid = fileMetadata['GUID'] existingSize = fileMetadata['Size'] existingChecksum = fileMetadata['Checksum'] newGuid = lfns[lfn]['GUID'] newSize = lfns[lfn]['Size'] newChecksum = lfns[lfn]['Checksum'] # Ensure that the key file metadata is the same if ( existingGuid != newGuid ) or \ ( existingSize != newSize ) or \ ( existingChecksum != newChecksum ): failed[lfn] = "File already registered with alternative metadata" # If the DB does not have replicas for this file return an error elif not fileID in replicaDict or not replicaDict[fileID]: failed[lfn] = "File already registered with no replicas" # If the supplied SE is not in the existing replicas return an error elif not lfns[lfn]['SE'] in replicaDict[fileID].keys(): failed[lfn] = "File already registered with alternative replicas" # If we get here the file being registered already exists exactly in the DB else: successful[lfn] = True return successful, failed def _checkUniqueGUID( self, lfns, connection = False ): connection = self._getConnection( connection ) guidLFNs = {} failed = {} for lfn, fileDict in lfns.items(): guidLFNs[fileDict['GUID']] = lfn res = self._getFileIDFromGUID( guidLFNs.keys(), connection = connection ) if not res['OK']: return dict.fromkeys( lfns, res['Message'] ) for guid, fileID in res['Value'].items(): failed[guidLFNs[guid]] = "GUID already registered for another file %s" % fileID # resolve this to LFN return failed def removeFile( self, lfns, connection = False ): connection = self._getConnection( connection ) """ Remove file from the catalog """ successful = {} failed = {} res = self._findFiles( lfns, ['DirID', 'FileID', 'Size'], connection = connection ) if not res['OK']: return res for lfn, error in res['Value']['Failed'].items(): if error == 'No such file or directory': successful[lfn] = True else: failed[lfn] = error fileIDLfns = {} lfns = res['Value']['Successful'] for lfn, lfnDict in lfns.items(): fileIDLfns[lfnDict['FileID']] = lfn res = self._computeStorageUsageOnRemoveFile( lfns, connection = connection ) if not res['OK']: return res directorySESizeDict = res['Value'] # Now do removal res = self._deleteFiles( fileIDLfns.keys(), connection = connection ) if not res['OK']: for lfn in fileIDLfns.values(): failed[lfn] = res['Message'] else: # Update the directory usage self._updateDirectoryUsage( directorySESizeDict, '-', connection = connection ) for lfn in fileIDLfns.values(): successful[lfn] = True return S_OK( {"Successful":successful, "Failed":failed} ) def _computeStorageUsageOnRemoveFile( self, lfns, connection = False ): # Resolve the replicas to calculate reduction in storage usage fileIDLfns = {} for lfn, lfnDict in lfns.items(): fileIDLfns[lfnDict['FileID']] = lfn res = self._getFileReplicas( fileIDLfns.keys(), connection = connection ) if not res['OK']: return res directorySESizeDict = {} for fileID, seDict in res['Value'].items(): dirID = lfns[fileIDLfns[fileID]]['DirID'] size = lfns[fileIDLfns[fileID]]['Size'] directorySESizeDict.setdefault( dirID, {} ) directorySESizeDict[dirID].setdefault( 0, {'Files':0,'Size':0} ) directorySESizeDict[dirID][0]['Size'] += size directorySESizeDict[dirID][0]['Files'] += 1 for seName in seDict.keys(): res = self.db.seManager.findSE( seName ) if not res['OK']: return res seID = res['Value'] size = lfns[fileIDLfns[fileID]]['Size'] directorySESizeDict[dirID].setdefault( seID, {'Files':0,'Size':0} ) directorySESizeDict[dirID][seID]['Size'] += size directorySESizeDict[dirID][seID]['Files'] += 1 return S_OK( directorySESizeDict ) def setFileStatus( self, lfns, connection = False ): """ Get set the group for the supplied files """ connection = self._getConnection( connection ) res = self._findFiles( lfns, ['FileID', 'UID'], connection = connection ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): status = lfns[lfn] if isinstance( status, basestring ): if not status in self.db.validFileStatus: failed[lfn] = 'Invalid file status %s' % status continue result = self._getStatusInt( status, connection = connection ) if not result['OK']: failed[lfn] = res['Message'] continue status = result['Value'] fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "Status", status, connection = connection ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) ###################################################### # # Replica write methods # def addReplica( self, lfns, connection = False ): """ Add replica to the catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['PFN', 'SE'] ) if not res['OK']: failed[lfn] = res['Message'] lfns.pop( lfn ) res = self._addReplicas( lfns, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: failed.update( res['Value']['Failed'] ) successful.update( res['Value']['Successful'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def _addReplicas( self, lfns, connection = False ): connection = self._getConnection( connection ) successful = {} res = self._findFiles( lfns.keys(), ['DirID', 'FileID', 'Size'], connection = connection ) if not res['OK']: return res failed = res['Value']['Failed'] for lfn in failed.keys(): lfns.pop( lfn ) lfnFileIDDict = res['Value']['Successful'] for lfn, fileDict in lfnFileIDDict.items(): lfns[lfn].update( fileDict ) res = self._insertReplicas( lfns, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: successful = res['Value']['Successful'] failed.update( res['Value']['Failed'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def removeReplica( self, lfns, connection = False ): """ Remove replica from catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['SE'] ) if not res['OK']: failed[lfn] = res['Message'] lfns.pop( lfn ) res = self._deleteReplicas( lfns, connection = connection ) if not res['OK']: for lfn in lfns.keys(): failed[lfn] = res['Message'] else: failed.update( res['Value']['Failed'] ) successful.update( res['Value']['Successful'] ) return S_OK( {'Successful':successful, 'Failed':failed} ) def setReplicaStatus( self, lfns, connection = False ): """ Set replica status in the catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['SE', 'Status'] ) if not res['OK']: failed[lfn] = res['Message'] continue status = info['Status'] se = info['SE'] res = self._findFiles( [lfn], ['FileID'], connection = connection ) if not res['Value']['Successful'].has_key( lfn ): failed[lfn] = res['Value']['Failed'][lfn] continue fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setReplicaStatus( fileID, se, status, connection = connection ) if res['OK']: successful[lfn] = res['Value'] else: failed[lfn] = res['Message'] return S_OK( {'Successful':successful, 'Failed':failed} ) def setReplicaHost( self, lfns, connection = False ): """ Set replica host in the catalog """ connection = self._getConnection( connection ) successful = {} failed = {} for lfn, info in lfns.items(): res = self._checkInfo( info, ['SE', 'NewSE'] ) if not res['OK']: failed[lfn] = res['Message'] continue newSE = info['NewSE'] se = info['SE'] res = self._findFiles( [lfn], ['FileID'], connection = connection ) if not res['Value']['Successful'].has_key( lfn ): failed[lfn] = res['Value']['Failed'][lfn] continue fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setReplicaHost( fileID, se, newSE, connection = connection ) if res['OK']: successful[lfn] = res['Value'] else: failed[lfn] = res['Message'] return S_OK( {'Successful':successful, 'Failed':failed} ) ###################################################### # # File read methods # def exists( self, lfns, connection = False ): """ Determine whether a file exists in the catalog """ connection = self._getConnection( connection ) res = self._findFiles( lfns, allStatus = True, connection = connection ) successful = res['Value']['Successful'] origFailed = res['Value']['Failed'] for lfn in successful: successful[lfn] = lfn failed = {} if self.db.uniqueGUID: guidList = [] val = None #Try to identify if the GUID is given # We consider only 2 options : # either {lfn : guid} # or P lfn : {PFN : .., GUID : ..} } if isinstance( lfns, dict ): val = lfns.values() # We have values, take the first to identify the type if val: val = val[0] if isinstance( val, dict ) and 'GUID' in val: # We are in the case {lfn : {PFN:.., GUID:..}} guidList = [lfns[lfn]['GUID'] for lfn in lfns] pass elif isinstance( val, basestring ): # We hope that it is the GUID which is given guidList = lfns.values() if guidList: # A dict { guid: lfn to which it is supposed to be associated } guidToGivenLfn = dict( zip( guidList, lfns ) ) res = self.getLFNForGUID( guidList, connection ) if not res['OK']: return res guidLfns = res['Value']['Successful'] for guid, realLfn in guidLfns.items(): successful[guidToGivenLfn[guid]] = realLfn for lfn, error in origFailed.items(): # It could be in successful because the guid exists with another lfn if lfn in successful: continue if error == 'No such file or directory': successful[lfn] = False else: failed[lfn] = error return S_OK( {"Successful":successful, "Failed":failed} ) def isFile( self, lfns, connection = False ): """ Determine whether a path is a file in the catalog """ connection = self._getConnection( connection ) #TO DO, should check whether it is a directory if it fails return self.exists( lfns, connection = connection ) def getFileSize( self, lfns, connection = False ): """ Get file size from the catalog """ connection = self._getConnection( connection ) #TO DO, should check whether it is a directory if it fails res = self._findFiles( lfns, ['Size'], connection = connection ) if not res['OK']: return res totalSize = 0 for lfn in res['Value']['Successful'].keys(): size = res['Value']['Successful'][lfn]['Size'] res['Value']['Successful'][lfn] = size totalSize += size res['TotalSize'] = totalSize return res def getFileMetadata( self, lfns, connection = False ): """ Get file metadata from the catalog """ connection = self._getConnection( connection ) #TO DO, should check whether it is a directory if it fails return self._findFiles( lfns, ['Size', 'Checksum', 'ChecksumType', 'UID', 'GID', 'GUID', 'CreationDate', 'ModificationDate', 'Mode', 'Status'], connection = connection ) def getPathPermissions( self, paths, credDict, connection = False ): """ Get the permissions for the supplied paths """ connection = self._getConnection( connection ) res = self.db.ugManager.getUserAndGroupID( credDict ) if not res['OK']: return res uid, gid = res['Value'] res = self._findFiles( paths, metadata = ['Mode', 'UID', 'GID'], connection = connection ) if not res['OK']: return res successful = {} for dirName, dirDict in res['Value']['Successful'].items(): mode = dirDict['Mode'] p_uid = dirDict['UID'] p_gid = dirDict['GID'] successful[dirName] = {} if p_uid == uid: successful[dirName]['Read'] = mode & stat.S_IRUSR successful[dirName]['Write'] = mode & stat.S_IWUSR successful[dirName]['Execute'] = mode & stat.S_IXUSR elif p_gid == gid: successful[dirName]['Read'] = mode & stat.S_IRGRP successful[dirName]['Write'] = mode & stat.S_IWGRP successful[dirName]['Execute'] = mode & stat.S_IXGRP else: successful[dirName]['Read'] = mode & stat.S_IROTH successful[dirName]['Write'] = mode & stat.S_IWOTH successful[dirName]['Execute'] = mode & stat.S_IXOTH return S_OK( {'Successful':successful, 'Failed':res['Value']['Failed']} ) ###################################################### # # Replica read methods # def __getReplicasForIDs( self, fileIDLfnDict, allStatus, connection = False ): """ Get replicas for files with already resolved IDs """ replicas = {} if fileIDLfnDict: fields = [] if not self.db.lfnPfnConvention or self.db.lfnPfnConvention == "Weak": fields = ['PFN'] res = self._getFileReplicas( fileIDLfnDict.keys(), fields_input=fields, allStatus = allStatus, connection = connection ) if not res['OK']: return res for fileID, seDict in res['Value'].items(): lfn = fileIDLfnDict[fileID] replicas[lfn] = {} for se, repDict in seDict.items(): pfn = repDict.get('PFN','') #if not pfn or self.db.lfnPfnConvention: # res = self._resolvePFN( lfn, se ) # if res['OK']: # pfn = res['Value'] replicas[lfn][se] = pfn result = S_OK( replicas ) return result def getReplicas( self, lfns, allStatus, connection = False ): """ Get file replicas from the catalog """ connection = self._getConnection( connection ) # Get FileID <-> LFN correspondence first res = self._findFileIDs( lfns, connection = connection ) if not res['OK']: return res failed = res['Value']['Failed'] fileIDLFNs = {} for lfn, fileID in res['Value']['Successful'].items(): fileIDLFNs[fileID] = lfn result = self.__getReplicasForIDs( fileIDLFNs, allStatus, connection) if not result['OK']: return result replicas = result['Value'] result = S_OK( { "Successful": replicas, 'Failed': failed } ) if self.db.lfnPfnConvention: sePrefixDict = {} resSE = self.db.seManager.getSEPrefixes() if resSE['OK']: sePrefixDict = resSE['Value'] result['Value']['SEPrefixes'] = sePrefixDict return result def getReplicasByMetadata( self, metaDict, path, allStatus, credDict, connection = False ): """ Get file replicas for files corresponding to the given metadata """ connection = self._getConnection( connection ) # Get FileID <-> LFN correspondence first failed = {} result = self.db.fmeta.findFilesByMetadata( metaDict, path, credDict, extra = True) if not result['OK']: return result fileIDLFNs = result['Value'] result = self.__getReplicasForIDs( fileIDLFNs, allStatus, connection) if not result['OK']: return result replicas = result['Value'] result = S_OK( { "Successful": replicas, 'Failed': failed } ) if self.db.lfnPfnConvention: sePrefixDict = {} resSE = self.db.seManager.getSEPrefixes() if resSE['OK']: sePrefixDict = resSE['Value'] result['Value']['SEPrefixes'] = sePrefixDict return result def _resolvePFN(self,lfn,se): resSE = self.db.seManager.getSEDefinition(se) if not resSE['OK']: return resSE pfnDict = dict(resSE['Value']['SEDict']) if "PFNPrefix" in pfnDict: return S_OK(pfnDict['PFNPrefix']+lfn) else: pfnDict['FileName'] = lfn return pfnunparse(pfnDict) def getReplicaStatus( self, lfns, connection = False ): """ Get replica status from the catalog """ connection = self._getConnection( connection ) res = self._findFiles( lfns, connection = connection ) failed = res['Value']['Failed'] fileIDLFNs = {} for lfn, fileDict in res['Value']['Successful'].items(): fileID = fileDict['FileID'] fileIDLFNs[fileID] = lfn successful = {} if fileIDLFNs: res = self._getFileReplicas( fileIDLFNs.keys(), allStatus = True, connection = connection ) if not res['OK']: return res for fileID, seDict in res['Value'].items(): lfn = fileIDLFNs[fileID] requestedSE = lfns[lfn] if not requestedSE: failed[lfn] = "Replica info not supplied" elif requestedSE not in seDict.keys(): failed[lfn] = "No replica at supplied site" else: successful[lfn] = seDict[requestedSE]['Status'] return S_OK( {'Successful':successful, 'Failed':failed} ) ###################################################### # # General usage methods # def _getStatusInt( self, status, connection = False ): connection = self._getConnection( connection ) req = "SELECT StatusID FROM FC_Statuses WHERE Status = '%s';" % status res = self.db._query( req, connection ) if not res['OK']: return res if res['Value']: return S_OK( res['Value'][0][0] ) req = "INSERT INTO FC_Statuses (Status) VALUES ('%s');" % status res = self.db._update( req, connection ) if not res['OK']: return res return S_OK( res['lastRowId'] ) def _getIntStatus(self,statusID,connection=False): if statusID in self.statusDict: return S_OK(self.statusDict[statusID]) connection = self._getConnection(connection) req = "SELECT StatusID,Status FROM FC_Statuses" res = self.db._query(req,connection) if not res['OK']: return res if res['Value']: for row in res['Value']: self.statusDict[int(row[0])] = row[1] if statusID in self.statusDict: return S_OK(self.statusDict[statusID]) return S_OK('Unknown') def getFileIDsInDirectory( self, dirID, requestString = False ): """ Get a list of IDs for all the files stored in given directories or their subdirectories :param mixt dirID: single directory ID or a list of directory IDs :param boolean requestString: if True return result as a SQL SELECT string :return: list of file IDs or SELECT string """ return self._getDirectoryFileIDs( dirID, requestString = requestString ) def getFilesInDirectory( self, dirID, verbose = False, connection = False ): connection = self._getConnection( connection ) files = {} res = self._getDirectoryFiles( dirID, [], ['FileID', 'Size', 'GUID', 'Checksum', 'ChecksumType', 'Type', 'UID', 'GID', 'CreationDate', 'ModificationDate', 'Mode', 'Status'], connection = connection ) if not res['OK']: return res if not res['Value']: return S_OK( files ) fileIDNames = {} for fileName, fileDict in res['Value'].items(): files[fileName] = {} files[fileName]['MetaData'] = fileDict fileIDNames[fileDict['FileID']] = fileName if verbose: result = self._getFileReplicas( fileIDNames.keys(), connection = connection ) if not result['OK']: return result for fileID, seDict in result['Value'].items(): fileName = fileIDNames[fileID] files[fileName]['Replicas'] = seDict return S_OK( files ) def getDirectoryReplicas( self, dirID, path, allStatus = False, connection = False ): """ Get the replicas for all the Files in the given Directory :param DirID : ID of the directory :param path : useless :param allStatus : whether all replicas and file status are considered If False, take the visibleFileStatus and visibleReplicaStatus values from the configuration """ connection = self._getConnection( connection ) result = self._getDirectoryReplicas( dirID, allStatus, connection) if not result['OK']: return result resultDict = {} seDict = {} for fileName, fileID, seID, pfn in result['Value']: resultDict.setdefault( fileName, {} ) if not seID in seDict: res = self.db.seManager.getSEName(seID) if not res['OK']: seDict[seID] = 'Unknown' else: seDict[seID] = res['Value'] se = seDict[seID] resultDict[fileName][se] = pfn return S_OK( resultDict ) def _getFileDirectories( self, lfns ): """ For a list of lfn, returns a dictionary with key the directory, and value the files in that directory. It does not make any query, just splits the names :param lfns list of lfns """ dirDict = {} for lfn in lfns: lfnDir = os.path.dirname( lfn ) lfnFile = os.path.basename( lfn ) dirDict.setdefault( lfnDir, [] ) dirDict[lfnDir].append( lfnFile ) return dirDict def _checkInfo( self, info, requiredKeys ): if not info: return S_ERROR( "Missing parameters" ) for key in requiredKeys: if not key in info: return S_ERROR( "Missing '%s' parameter" % key ) return S_OK() # def _checkLFNPFNConvention( self, lfn, pfn, se ): # """ Check that the PFN corresponds to the LFN-PFN convention """ # if pfn == lfn: # return S_OK() # if ( len( pfn ) < len( lfn ) ) or ( pfn[-len( lfn ):] != lfn ) : # return S_ERROR( 'PFN does not correspond to the LFN convention' ) # return S_OK() def changeFileGroup( self, lfns ): """ Get set the group for the supplied files :param lfns : dictionary < lfn : group > :param int/str newGroup: optional new group/groupID the same for all the supplied lfns """ res = self._findFiles( lfns, ['FileID', 'GID'] ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): group = lfns[lfn] if isinstance( group, basestring ): groupRes = self.db.ugManager.findGroup( group ) if not groupRes['OK']: return groupRes group = groupRes['Value'] currentGroup = res['Value']['Successful'][lfn]['GID'] if int( group ) == int( currentGroup ): successful[lfn] = True else: fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "GID", group ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def changeFileOwner( self, lfns ): """ Set the owner for the supplied files :param lfns : dictionary < lfn : owner > :param int/str newOwner: optional new user/userID the same for all the supplied lfns """ res = self._findFiles( lfns, ['FileID', 'UID'] ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): owner = lfns[lfn] if isinstance( owner, basestring ): userRes = self.db.ugManager.findUser( owner ) if not userRes['OK']: return userRes owner = userRes['Value'] currentOwner = res['Value']['Successful'][lfn]['UID'] if int( owner ) == int( currentOwner ): successful[lfn] = True else: fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "UID", owner ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def changeFileMode( self, lfns ): """" Set the mode for the supplied files :param lfns : dictionary < lfn : mode > :param int newMode: optional new mode the same for all the supplied lfns """ res = self._findFiles( lfns, ['FileID', 'Mode'] ) if not res['OK']: return res failed = res['Value']['Failed'] successful = {} for lfn in res['Value']['Successful'].keys(): mode = lfns[lfn] currentMode = res['Value']['Successful'][lfn]['Mode'] if int( currentMode ) == int( mode ): successful[lfn] = True else: fileID = res['Value']['Successful'][lfn]['FileID'] res = self._setFileParameter( fileID, "Mode", mode ) if not res['OK']: failed[lfn] = res['Message'] else: successful[lfn] = True return S_OK( {'Successful':successful, 'Failed':failed} ) def setFileOwner( self, path, owner ): """ Set the file owner :param mixed path: file path as a string or int or list of ints or select statement :param mixt group: new user as a string or int uid """ result = self.db.ugManager.findUser( owner ) if not result['OK']: return result uid = result['Value'] return self._setFileParameter( path, 'UID', uid ) def setFileGroup( self, path, gname ): """ Set the file group :param mixed path: file path as a string or int or list of ints or select statement :param mixt group: new group as a string or int gid """ result = self.db.ugManager.findGroup( gname ) if not result['OK']: return result gid = result['Value'] return self._setFileParameter( path, 'GID', gid ) def setFileMode( self, path, mode ): """ Set the file mode :param mixed path: file path as a string or int or list of ints or select statement :param int mode: new mode """ return self._setFileParameter( path, 'Mode', mode )

vmendez/DIRAC

DataManagementSystem/DB/FileCatalogComponents/FileManagerBase.py

Python

gpl-3.0

49,658

[ "DIRAC" ]

e797ffd57e4f23510a8f12a6674886299038f0268225ec538bfaff0e0844d4b5

# Copyright (c) 2012 The Chromium Authors. All rights reserved. # Use of this source code is governed by a BSD-style license that can be # found in the LICENSE file. """Top-level presubmit script for Chromium. See http://dev.chromium.org/developers/how-tos/depottools/presubmit-scripts for more details about the presubmit API built into depot_tools. """ _EXCLUDED_PATHS = ( r"^breakpad[\\\/].*", r"^native_client_sdk[\\\/]src[\\\/]build_tools[\\\/]make_rules.py", r"^native_client_sdk[\\\/]src[\\\/]build_tools[\\\/]make_simple.py", r"^native_client_sdk[\\\/]src[\\\/]tools[\\\/].*.mk", r"^net[\\\/]tools[\\\/]spdyshark[\\\/].*", r"^skia[\\\/].*", r"^v8[\\\/].*", r".*MakeFile$", r".+_autogen\.h$", r".+[\\\/]pnacl_shim\.c$", r"^gpu[\\\/]config[\\\/].*_list_json\.cc$", r"^chrome[\\\/]browser[\\\/]resources[\\\/]pdf[\\\/]index.js" ) # The NetscapePlugIn library is excluded from pan-project as it will soon # be deleted together with the rest of the NPAPI and it's not worthwhile to # update the coding style until then. _TESTRUNNER_PATHS = ( r"^content[\\\/]shell[\\\/]tools[\\\/]plugin[\\\/].*", ) # Fragment of a regular expression that matches C++ and Objective-C++ # implementation files. _IMPLEMENTATION_EXTENSIONS = r'\.(cc|cpp|cxx|mm)$' # Regular expression that matches code only used for test binaries # (best effort). _TEST_CODE_EXCLUDED_PATHS = ( r'.*[\\\/](fake_|test_|mock_).+%s' % _IMPLEMENTATION_EXTENSIONS, r'.+_test_(base|support|util)%s' % _IMPLEMENTATION_EXTENSIONS, r'.+_(api|browser|kif|perf|pixel|unit|ui)?test(_[a-z]+)?%s' % _IMPLEMENTATION_EXTENSIONS, r'.+profile_sync_service_harness%s' % _IMPLEMENTATION_EXTENSIONS, r'.*[\\\/](test|tool(s)?)[\\\/].*', # content_shell is used for running layout tests. r'content[\\\/]shell[\\\/].*', # At request of folks maintaining this folder. r'chrome[\\\/]browser[\\\/]automation[\\\/].*', # Non-production example code. r'mojo[\\\/]examples[\\\/].*', # Launcher for running iOS tests on the simulator. r'testing[\\\/]iossim[\\\/]iossim\.mm$', ) _TEST_ONLY_WARNING = ( 'You might be calling functions intended only for testing from\n' 'production code. It is OK to ignore this warning if you know what\n' 'you are doing, as the heuristics used to detect the situation are\n' 'not perfect. The commit queue will not block on this warning.') _INCLUDE_ORDER_WARNING = ( 'Your #include order seems to be broken. Remember to use the right ' 'collation (LC_COLLATE=C) and check https://google-styleguide.googlecode' '.com/svn/trunk/cppguide.html#Names_and_Order_of_Includes') _BANNED_OBJC_FUNCTIONS = ( ( 'addTrackingRect:', ( 'The use of -[NSView addTrackingRect:owner:userData:assumeInside:] is' 'prohibited. Please use CrTrackingArea instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), False, ), ( r'/NSTrackingArea\W', ( 'The use of NSTrackingAreas is prohibited. Please use CrTrackingArea', 'instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), False, ), ( 'convertPointFromBase:', ( 'The use of -[NSView convertPointFromBase:] is almost certainly wrong.', 'Please use |convertPoint:(point) fromView:nil| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertPointToBase:', ( 'The use of -[NSView convertPointToBase:] is almost certainly wrong.', 'Please use |convertPoint:(point) toView:nil| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertRectFromBase:', ( 'The use of -[NSView convertRectFromBase:] is almost certainly wrong.', 'Please use |convertRect:(point) fromView:nil| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertRectToBase:', ( 'The use of -[NSView convertRectToBase:] is almost certainly wrong.', 'Please use |convertRect:(point) toView:nil| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertSizeFromBase:', ( 'The use of -[NSView convertSizeFromBase:] is almost certainly wrong.', 'Please use |convertSize:(point) fromView:nil| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ( 'convertSizeToBase:', ( 'The use of -[NSView convertSizeToBase:] is almost certainly wrong.', 'Please use |convertSize:(point) toView:nil| instead.', 'http://dev.chromium.org/developers/coding-style/cocoa-dos-and-donts', ), True, ), ) _BANNED_CPP_FUNCTIONS = ( # Make sure that gtest's FRIEND_TEST() macro is not used; the # FRIEND_TEST_ALL_PREFIXES() macro from base/gtest_prod_util.h should be # used instead since that allows for FLAKY_ and DISABLED_ prefixes. ( 'FRIEND_TEST(', ( 'Chromium code should not use gtest\'s FRIEND_TEST() macro. Include', 'base/gtest_prod_util.h and use FRIEND_TEST_ALL_PREFIXES() instead.', ), False, (), ), ( 'ScopedAllowIO', ( 'New code should not use ScopedAllowIO. Post a task to the blocking', 'pool or the FILE thread instead.', ), True, ( r"^base[\\\/]process[\\\/]process_metrics_linux\.cc$", r"^chrome[\\\/]browser[\\\/]chromeos[\\\/]boot_times_recorder\.cc$", r"^chrome[\\\/]browser[\\\/]chromeos[\\\/]" "customization_document_browsertest\.cc$", r"^components[\\\/]crash[\\\/]app[\\\/]breakpad_mac\.mm$", r"^content[\\\/]shell[\\\/]browser[\\\/]shell_browser_main\.cc$", r"^content[\\\/]shell[\\\/]browser[\\\/]shell_message_filter\.cc$", r"^mojo[\\\/]edk[\\\/]embedder[\\\/]" + r"simple_platform_shared_buffer_posix\.cc$", r"^net[\\\/]disk_cache[\\\/]cache_util\.cc$", r"^net[\\\/]url_request[\\\/]test_url_fetcher_factory\.cc$", r"^ui[\\\/]ozone[\\\/]platform[\\\/]drm[\\\/]host[\\\/]" "drm_native_display_delegate\.cc$", ), ), ( 'SkRefPtr', ( 'The use of SkRefPtr is prohibited. ', 'Please use skia::RefPtr instead.' ), True, (), ), ( 'SkAutoRef', ( 'The indirect use of SkRefPtr via SkAutoRef is prohibited. ', 'Please use skia::RefPtr instead.' ), True, (), ), ( 'SkAutoTUnref', ( 'The use of SkAutoTUnref is dangerous because it implicitly ', 'converts to a raw pointer. Please use skia::RefPtr instead.' ), True, (), ), ( 'SkAutoUnref', ( 'The indirect use of SkAutoTUnref through SkAutoUnref is dangerous ', 'because it implicitly converts to a raw pointer. ', 'Please use skia::RefPtr instead.' ), True, (), ), ( r'/HANDLE_EINTR\(.*close', ( 'HANDLE_EINTR(close) is invalid. If close fails with EINTR, the file', 'descriptor will be closed, and it is incorrect to retry the close.', 'Either call close directly and ignore its return value, or wrap close', 'in IGNORE_EINTR to use its return value. See http://crbug.com/269623' ), True, (), ), ( r'/IGNORE_EINTR\((?!.*close)', ( 'IGNORE_EINTR is only valid when wrapping close. To wrap other system', 'calls, use HANDLE_EINTR. See http://crbug.com/269623', ), True, ( # Files that #define IGNORE_EINTR. r'^base[\\\/]posix[\\\/]eintr_wrapper\.h$', r'^ppapi[\\\/]tests[\\\/]test_broker\.cc$', ), ), ( r'/v8::Extension\(', ( 'Do not introduce new v8::Extensions into the code base, use', 'gin::Wrappable instead. See http://crbug.com/334679', ), True, ( r'extensions[\\\/]renderer[\\\/]safe_builtins\.*', ), ), ) _IPC_ENUM_TRAITS_DEPRECATED = ( 'You are using IPC_ENUM_TRAITS() in your code. It has been deprecated.\n' 'See http://www.chromium.org/Home/chromium-security/education/security-tips-for-ipc') _VALID_OS_MACROS = ( # Please keep sorted. 'OS_ANDROID', 'OS_ANDROID_HOST', 'OS_BSD', 'OS_CAT', # For testing. 'OS_CHROMEOS', 'OS_FREEBSD', 'OS_IOS', 'OS_LINUX', 'OS_MACOSX', 'OS_NACL', 'OS_NACL_NONSFI', 'OS_NACL_SFI', 'OS_OPENBSD', 'OS_POSIX', 'OS_QNX', 'OS_SOLARIS', 'OS_WIN', ) def _CheckNoProductionCodeUsingTestOnlyFunctions(input_api, output_api): """Attempts to prevent use of functions intended only for testing in non-testing code. For now this is just a best-effort implementation that ignores header files and may have some false positives. A better implementation would probably need a proper C++ parser. """ # We only scan .cc files and the like, as the declaration of # for-testing functions in header files are hard to distinguish from # calls to such functions without a proper C++ parser. file_inclusion_pattern = r'.+%s' % _IMPLEMENTATION_EXTENSIONS base_function_pattern = r'[ :]test::[^\s]+|ForTest(ing)?|for_test(ing)?' inclusion_pattern = input_api.re.compile(r'(%s)\s*\(' % base_function_pattern) comment_pattern = input_api.re.compile(r'//.*(%s)' % base_function_pattern) exclusion_pattern = input_api.re.compile( r'::[A-Za-z0-9_]+(%s)|(%s)[^;]+\{' % ( base_function_pattern, base_function_pattern)) def FilterFile(affected_file): black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) return input_api.FilterSourceFile( affected_file, white_list=(file_inclusion_pattern, ), black_list=black_list) problems = [] for f in input_api.AffectedSourceFiles(FilterFile): local_path = f.LocalPath() for line_number, line in f.ChangedContents(): if (inclusion_pattern.search(line) and not comment_pattern.search(line) and not exclusion_pattern.search(line)): problems.append( '%s:%d\n %s' % (local_path, line_number, line.strip())) if problems: return [output_api.PresubmitPromptOrNotify(_TEST_ONLY_WARNING, problems)] else: return [] def _CheckNoIOStreamInHeaders(input_api, output_api): """Checks to make sure no .h files include <iostream>.""" files = [] pattern = input_api.re.compile(r'^#include\s*<iostream>', input_api.re.MULTILINE) for f in input_api.AffectedSourceFiles(input_api.FilterSourceFile): if not f.LocalPath().endswith('.h'): continue contents = input_api.ReadFile(f) if pattern.search(contents): files.append(f) if len(files): return [ output_api.PresubmitError( 'Do not #include <iostream> in header files, since it inserts static ' 'initialization into every file including the header. Instead, ' '#include <ostream>. See http://crbug.com/94794', files) ] return [] def _CheckNoUNIT_TESTInSourceFiles(input_api, output_api): """Checks to make sure no source files use UNIT_TEST""" problems = [] for f in input_api.AffectedFiles(): if (not f.LocalPath().endswith(('.cc', '.mm'))): continue for line_num, line in f.ChangedContents(): if 'UNIT_TEST ' in line or line.endswith('UNIT_TEST'): problems.append(' %s:%d' % (f.LocalPath(), line_num)) if not problems: return [] return [output_api.PresubmitPromptWarning('UNIT_TEST is only for headers.\n' + '\n'.join(problems))] def _FindHistogramNameInLine(histogram_name, line): """Tries to find a histogram name or prefix in a line.""" if not "affected-histogram" in line: return histogram_name in line # A histogram_suffixes tag type has an affected-histogram name as a prefix of # the histogram_name. if not '"' in line: return False histogram_prefix = line.split('\"')[1] return histogram_prefix in histogram_name def _CheckUmaHistogramChanges(input_api, output_api): """Check that UMA histogram names in touched lines can still be found in other lines of the patch or in histograms.xml. Note that this check would not catch the reverse: changes in histograms.xml not matched in the code itself.""" touched_histograms = [] histograms_xml_modifications = [] pattern = input_api.re.compile('UMA_HISTOGRAM.*\("(.*)"') for f in input_api.AffectedFiles(): # If histograms.xml itself is modified, keep the modified lines for later. if f.LocalPath().endswith(('histograms.xml')): histograms_xml_modifications = f.ChangedContents() continue if not f.LocalPath().endswith(('cc', 'mm', 'cpp')): continue for line_num, line in f.ChangedContents(): found = pattern.search(line) if found: touched_histograms.append([found.group(1), f, line_num]) # Search for the touched histogram names in the local modifications to # histograms.xml, and, if not found, on the base histograms.xml file. unmatched_histograms = [] for histogram_info in touched_histograms: histogram_name_found = False for line_num, line in histograms_xml_modifications: histogram_name_found = _FindHistogramNameInLine(histogram_info[0], line) if histogram_name_found: break if not histogram_name_found: unmatched_histograms.append(histogram_info) histograms_xml_path = 'tools/metrics/histograms/histograms.xml' problems = [] if unmatched_histograms: with open(histograms_xml_path) as histograms_xml: for histogram_name, f, line_num in unmatched_histograms: histograms_xml.seek(0) histogram_name_found = False for line in histograms_xml: histogram_name_found = _FindHistogramNameInLine(histogram_name, line) if histogram_name_found: break if not histogram_name_found: problems.append(' [%s:%d] %s' % (f.LocalPath(), line_num, histogram_name)) if not problems: return [] return [output_api.PresubmitPromptWarning('Some UMA_HISTOGRAM lines have ' 'been modified and the associated histogram name has no match in either ' '%s or the modifications of it:' % (histograms_xml_path), problems)] def _CheckNoNewWStrings(input_api, output_api): """Checks to make sure we don't introduce use of wstrings.""" problems = [] for f in input_api.AffectedFiles(): if (not f.LocalPath().endswith(('.cc', '.h')) or f.LocalPath().endswith(('test.cc', '_win.cc', '_win.h')) or '/win/' in f.LocalPath()): continue allowWString = False for line_num, line in f.ChangedContents(): if 'presubmit: allow wstring' in line: allowWString = True elif not allowWString and 'wstring' in line: problems.append(' %s:%d' % (f.LocalPath(), line_num)) allowWString = False else: allowWString = False if not problems: return [] return [output_api.PresubmitPromptWarning('New code should not use wstrings.' ' If you are calling a cross-platform API that accepts a wstring, ' 'fix the API.\n' + '\n'.join(problems))] def _CheckNoDEPSGIT(input_api, output_api): """Make sure .DEPS.git is never modified manually.""" if any(f.LocalPath().endswith('.DEPS.git') for f in input_api.AffectedFiles()): return [output_api.PresubmitError( 'Never commit changes to .DEPS.git. This file is maintained by an\n' 'automated system based on what\'s in DEPS and your changes will be\n' 'overwritten.\n' 'See https://sites.google.com/a/chromium.org/dev/developers/how-tos/get-the-code#Rolling_DEPS\n' 'for more information')] return [] def _CheckValidHostsInDEPS(input_api, output_api): """Checks that DEPS file deps are from allowed_hosts.""" # Run only if DEPS file has been modified to annoy fewer bystanders. if all(f.LocalPath() != 'DEPS' for f in input_api.AffectedFiles()): return [] # Outsource work to gclient verify try: input_api.subprocess.check_output(['gclient', 'verify']) return [] except input_api.subprocess.CalledProcessError, error: return [output_api.PresubmitError( 'DEPS file must have only git dependencies.', long_text=error.output)] def _CheckNoBannedFunctions(input_api, output_api): """Make sure that banned functions are not used.""" warnings = [] errors = [] file_filter = lambda f: f.LocalPath().endswith(('.mm', '.m', '.h')) for f in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in f.ChangedContents(): for func_name, message, error in _BANNED_OBJC_FUNCTIONS: matched = False if func_name[0:1] == '/': regex = func_name[1:] if input_api.re.search(regex, line): matched = True elif func_name in line: matched = True if matched: problems = warnings; if error: problems = errors; problems.append(' %s:%d:' % (f.LocalPath(), line_num)) for message_line in message: problems.append(' %s' % message_line) file_filter = lambda f: f.LocalPath().endswith(('.cc', '.mm', '.h')) for f in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in f.ChangedContents(): for func_name, message, error, excluded_paths in _BANNED_CPP_FUNCTIONS: def IsBlacklisted(affected_file, blacklist): local_path = affected_file.LocalPath() for item in blacklist: if input_api.re.match(item, local_path): return True return False if IsBlacklisted(f, excluded_paths): continue matched = False if func_name[0:1] == '/': regex = func_name[1:] if input_api.re.search(regex, line): matched = True elif func_name in line: matched = True if matched: problems = warnings; if error: problems = errors; problems.append(' %s:%d:' % (f.LocalPath(), line_num)) for message_line in message: problems.append(' %s' % message_line) result = [] if (warnings): result.append(output_api.PresubmitPromptWarning( 'Banned functions were used.\n' + '\n'.join(warnings))) if (errors): result.append(output_api.PresubmitError( 'Banned functions were used.\n' + '\n'.join(errors))) return result def _CheckNoPragmaOnce(input_api, output_api): """Make sure that banned functions are not used.""" files = [] pattern = input_api.re.compile(r'^#pragma\s+once', input_api.re.MULTILINE) for f in input_api.AffectedSourceFiles(input_api.FilterSourceFile): if not f.LocalPath().endswith('.h'): continue contents = input_api.ReadFile(f) if pattern.search(contents): files.append(f) if files: return [output_api.PresubmitError( 'Do not use #pragma once in header files.\n' 'See http://www.chromium.org/developers/coding-style#TOC-File-headers', files)] return [] def _CheckNoTrinaryTrueFalse(input_api, output_api): """Checks to make sure we don't introduce use of foo ? true : false.""" problems = [] pattern = input_api.re.compile(r'\?\s*(true|false)\s*:\s*(true|false)') for f in input_api.AffectedFiles(): if not f.LocalPath().endswith(('.cc', '.h', '.inl', '.m', '.mm')): continue for line_num, line in f.ChangedContents(): if pattern.match(line): problems.append(' %s:%d' % (f.LocalPath(), line_num)) if not problems: return [] return [output_api.PresubmitPromptWarning( 'Please consider avoiding the "? true : false" pattern if possible.\n' + '\n'.join(problems))] def _CheckUnwantedDependencies(input_api, output_api): """Runs checkdeps on #include statements added in this change. Breaking - rules is an error, breaking ! rules is a warning. """ import sys # We need to wait until we have an input_api object and use this # roundabout construct to import checkdeps because this file is # eval-ed and thus doesn't have __file__. original_sys_path = sys.path try: sys.path = sys.path + [input_api.os_path.join( input_api.PresubmitLocalPath(), 'buildtools', 'checkdeps')] import checkdeps from cpp_checker import CppChecker from rules import Rule finally: # Restore sys.path to what it was before. sys.path = original_sys_path added_includes = [] for f in input_api.AffectedFiles(): if not CppChecker.IsCppFile(f.LocalPath()): continue changed_lines = [line for line_num, line in f.ChangedContents()] added_includes.append([f.LocalPath(), changed_lines]) deps_checker = checkdeps.DepsChecker(input_api.PresubmitLocalPath()) error_descriptions = [] warning_descriptions = [] for path, rule_type, rule_description in deps_checker.CheckAddedCppIncludes( added_includes): description_with_path = '%s\n %s' % (path, rule_description) if rule_type == Rule.DISALLOW: error_descriptions.append(description_with_path) else: warning_descriptions.append(description_with_path) results = [] if error_descriptions: results.append(output_api.PresubmitError( 'You added one or more #includes that violate checkdeps rules.', error_descriptions)) if warning_descriptions: results.append(output_api.PresubmitPromptOrNotify( 'You added one or more #includes of files that are temporarily\n' 'allowed but being removed. Can you avoid introducing the\n' '#include? See relevant DEPS file(s) for details and contacts.', warning_descriptions)) return results def _CheckFilePermissions(input_api, output_api): """Check that all files have their permissions properly set.""" if input_api.platform == 'win32': return [] args = [input_api.python_executable, 'tools/checkperms/checkperms.py', '--root', input_api.change.RepositoryRoot()] for f in input_api.AffectedFiles(): args += ['--file', f.LocalPath()] checkperms = input_api.subprocess.Popen(args, stdout=input_api.subprocess.PIPE) errors = checkperms.communicate()[0].strip() if errors: return [output_api.PresubmitError('checkperms.py failed.', errors.splitlines())] return [] def _CheckNoAuraWindowPropertyHInHeaders(input_api, output_api): """Makes sure we don't include ui/aura/window_property.h in header files. """ pattern = input_api.re.compile(r'^#include\s*"ui/aura/window_property.h"') errors = [] for f in input_api.AffectedFiles(): if not f.LocalPath().endswith('.h'): continue for line_num, line in f.ChangedContents(): if pattern.match(line): errors.append(' %s:%d' % (f.LocalPath(), line_num)) results = [] if errors: results.append(output_api.PresubmitError( 'Header files should not include ui/aura/window_property.h', errors)) return results def _CheckIncludeOrderForScope(scope, input_api, file_path, changed_linenums): """Checks that the lines in scope occur in the right order. 1. C system files in alphabetical order 2. C++ system files in alphabetical order 3. Project's .h files """ c_system_include_pattern = input_api.re.compile(r'\s*#include <.*\.h>') cpp_system_include_pattern = input_api.re.compile(r'\s*#include <.*>') custom_include_pattern = input_api.re.compile(r'\s*#include ".*') C_SYSTEM_INCLUDES, CPP_SYSTEM_INCLUDES, CUSTOM_INCLUDES = range(3) state = C_SYSTEM_INCLUDES previous_line = '' previous_line_num = 0 problem_linenums = [] for line_num, line in scope: if c_system_include_pattern.match(line): if state != C_SYSTEM_INCLUDES: problem_linenums.append((line_num, previous_line_num)) elif previous_line and previous_line > line: problem_linenums.append((line_num, previous_line_num)) elif cpp_system_include_pattern.match(line): if state == C_SYSTEM_INCLUDES: state = CPP_SYSTEM_INCLUDES elif state == CUSTOM_INCLUDES: problem_linenums.append((line_num, previous_line_num)) elif previous_line and previous_line > line: problem_linenums.append((line_num, previous_line_num)) elif custom_include_pattern.match(line): if state != CUSTOM_INCLUDES: state = CUSTOM_INCLUDES elif previous_line and previous_line > line: problem_linenums.append((line_num, previous_line_num)) else: problem_linenums.append(line_num) previous_line = line previous_line_num = line_num warnings = [] for (line_num, previous_line_num) in problem_linenums: if line_num in changed_linenums or previous_line_num in changed_linenums: warnings.append(' %s:%d' % (file_path, line_num)) return warnings def _CheckIncludeOrderInFile(input_api, f, changed_linenums): """Checks the #include order for the given file f.""" system_include_pattern = input_api.re.compile(r'\s*#include \<.*') # Exclude the following includes from the check: # 1) #include <.../...>, e.g., <sys/...> includes often need to appear in a # specific order. # 2) <atlbase.h>, "build/build_config.h" excluded_include_pattern = input_api.re.compile( r'\s*#include (\<.*/.*|\<atlbase\.h\>|"build/build_config.h")') custom_include_pattern = input_api.re.compile(r'\s*#include "(?P<FILE>.*)"') # Match the final or penultimate token if it is xxxtest so we can ignore it # when considering the special first include. test_file_tag_pattern = input_api.re.compile( r'_[a-z]+test(?=(_[a-zA-Z0-9]+)?\.)') if_pattern = input_api.re.compile( r'\s*#\s*(if|elif|else|endif|define|undef).*') # Some files need specialized order of includes; exclude such files from this # check. uncheckable_includes_pattern = input_api.re.compile( r'\s*#include ' '("ipc/.*macros\.h"|<windows\.h>|".*gl.*autogen.h")\s*') contents = f.NewContents() warnings = [] line_num = 0 # Handle the special first include. If the first include file is # some/path/file.h, the corresponding including file can be some/path/file.cc, # some/other/path/file.cc, some/path/file_platform.cc, some/path/file-suffix.h # etc. It's also possible that no special first include exists. # If the included file is some/path/file_platform.h the including file could # also be some/path/file_xxxtest_platform.h. including_file_base_name = test_file_tag_pattern.sub( '', input_api.os_path.basename(f.LocalPath())) for line in contents: line_num += 1 if system_include_pattern.match(line): # No special first include -> process the line again along with normal # includes. line_num -= 1 break match = custom_include_pattern.match(line) if match: match_dict = match.groupdict() header_basename = test_file_tag_pattern.sub( '', input_api.os_path.basename(match_dict['FILE'])).replace('.h', '') if header_basename not in including_file_base_name: # No special first include -> process the line again along with normal # includes. line_num -= 1 break # Split into scopes: Each region between #if and #endif is its own scope. scopes = [] current_scope = [] for line in contents[line_num:]: line_num += 1 if uncheckable_includes_pattern.match(line): continue if if_pattern.match(line): scopes.append(current_scope) current_scope = [] elif ((system_include_pattern.match(line) or custom_include_pattern.match(line)) and not excluded_include_pattern.match(line)): current_scope.append((line_num, line)) scopes.append(current_scope) for scope in scopes: warnings.extend(_CheckIncludeOrderForScope(scope, input_api, f.LocalPath(), changed_linenums)) return warnings def _CheckIncludeOrder(input_api, output_api): """Checks that the #include order is correct. 1. The corresponding header for source files. 2. C system files in alphabetical order 3. C++ system files in alphabetical order 4. Project's .h files in alphabetical order Each region separated by #if, #elif, #else, #endif, #define and #undef follows these rules separately. """ def FileFilterIncludeOrder(affected_file): black_list = (_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) return input_api.FilterSourceFile(affected_file, black_list=black_list) warnings = [] for f in input_api.AffectedFiles(file_filter=FileFilterIncludeOrder): if f.LocalPath().endswith(('.cc', '.h')): changed_linenums = set(line_num for line_num, _ in f.ChangedContents()) warnings.extend(_CheckIncludeOrderInFile(input_api, f, changed_linenums)) results = [] if warnings: results.append(output_api.PresubmitPromptOrNotify(_INCLUDE_ORDER_WARNING, warnings)) return results def _CheckForVersionControlConflictsInFile(input_api, f): pattern = input_api.re.compile('^(?:<<<<<<<|>>>>>>>) |^=======$') errors = [] for line_num, line in f.ChangedContents(): if pattern.match(line): errors.append(' %s:%d %s' % (f.LocalPath(), line_num, line)) return errors def _CheckForVersionControlConflicts(input_api, output_api): """Usually this is not intentional and will cause a compile failure.""" errors = [] for f in input_api.AffectedFiles(): errors.extend(_CheckForVersionControlConflictsInFile(input_api, f)) results = [] if errors: results.append(output_api.PresubmitError( 'Version control conflict markers found, please resolve.', errors)) return results def _CheckHardcodedGoogleHostsInLowerLayers(input_api, output_api): def FilterFile(affected_file): """Filter function for use with input_api.AffectedSourceFiles, below. This filters out everything except non-test files from top-level directories that generally speaking should not hard-code service URLs (e.g. src/android_webview/, src/content/ and others). """ return input_api.FilterSourceFile( affected_file, white_list=(r'^(android_webview|base|content|net)[\\\/].*', ), black_list=(_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST)) base_pattern = '"[^"]*google\.com[^"]*"' comment_pattern = input_api.re.compile('//.*%s' % base_pattern) pattern = input_api.re.compile(base_pattern) problems = [] # items are (filename, line_number, line) for f in input_api.AffectedSourceFiles(FilterFile): for line_num, line in f.ChangedContents(): if not comment_pattern.search(line) and pattern.search(line): problems.append((f.LocalPath(), line_num, line)) if problems: return [output_api.PresubmitPromptOrNotify( 'Most layers below src/chrome/ should not hardcode service URLs.\n' 'Are you sure this is correct?', [' %s:%d: %s' % ( problem[0], problem[1], problem[2]) for problem in problems])] else: return [] def _CheckNoAbbreviationInPngFileName(input_api, output_api): """Makes sure there are no abbreviations in the name of PNG files. The native_client_sdk directory is excluded because it has auto-generated PNG files for documentation. """ errors = [] white_list = (r'.*_[a-z]_.*\.png$|.*_[a-z]\.png$',) black_list = (r'^native_client_sdk[\\\/]',) file_filter = lambda f: input_api.FilterSourceFile( f, white_list=white_list, black_list=black_list) for f in input_api.AffectedFiles(include_deletes=False, file_filter=file_filter): errors.append(' %s' % f.LocalPath()) results = [] if errors: results.append(output_api.PresubmitError( 'The name of PNG files should not have abbreviations. \n' 'Use _hover.png, _center.png, instead of _h.png, _c.png.\n' 'Contact oshima@chromium.org if you have questions.', errors)) return results def _FilesToCheckForIncomingDeps(re, changed_lines): """Helper method for _CheckAddedDepsHaveTargetApprovals. Returns a set of DEPS entries that we should look up. For a directory (rather than a specific filename) we fake a path to a specific filename by adding /DEPS. This is chosen as a file that will seldom or never be subject to per-file include_rules. """ # We ignore deps entries on auto-generated directories. AUTO_GENERATED_DIRS = ['grit', 'jni'] # This pattern grabs the path without basename in the first # parentheses, and the basename (if present) in the second. It # relies on the simple heuristic that if there is a basename it will # be a header file ending in ".h". pattern = re.compile( r"""['"]\+([^'"]+?)(/[a-zA-Z0-9_]+\.h)?['"].*""") results = set() for changed_line in changed_lines: m = pattern.match(changed_line) if m: path = m.group(1) if path.split('/')[0] not in AUTO_GENERATED_DIRS: if m.group(2): results.add('%s%s' % (path, m.group(2))) else: results.add('%s/DEPS' % path) return results def _CheckAddedDepsHaveTargetApprovals(input_api, output_api): """When a dependency prefixed with + is added to a DEPS file, we want to make sure that the change is reviewed by an OWNER of the target file or directory, to avoid layering violations from being introduced. This check verifies that this happens. """ changed_lines = set() for f in input_api.AffectedFiles(): filename = input_api.os_path.basename(f.LocalPath()) if filename == 'DEPS': changed_lines |= set(line.strip() for line_num, line in f.ChangedContents()) if not changed_lines: return [] virtual_depended_on_files = _FilesToCheckForIncomingDeps(input_api.re, changed_lines) if not virtual_depended_on_files: return [] if input_api.is_committing: if input_api.tbr: return [output_api.PresubmitNotifyResult( '--tbr was specified, skipping OWNERS check for DEPS additions')] if not input_api.change.issue: return [output_api.PresubmitError( "DEPS approval by OWNERS check failed: this change has " "no Rietveld issue number, so we can't check it for approvals.")] output = output_api.PresubmitError else: output = output_api.PresubmitNotifyResult owners_db = input_api.owners_db owner_email, reviewers = input_api.canned_checks._RietveldOwnerAndReviewers( input_api, owners_db.email_regexp, approval_needed=input_api.is_committing) owner_email = owner_email or input_api.change.author_email reviewers_plus_owner = set(reviewers) if owner_email: reviewers_plus_owner.add(owner_email) missing_files = owners_db.files_not_covered_by(virtual_depended_on_files, reviewers_plus_owner) # We strip the /DEPS part that was added by # _FilesToCheckForIncomingDeps to fake a path to a file in a # directory. def StripDeps(path): start_deps = path.rfind('/DEPS') if start_deps != -1: return path[:start_deps] else: return path unapproved_dependencies = ["'+%s'," % StripDeps(path) for path in missing_files] if unapproved_dependencies: output_list = [ output('Missing LGTM from OWNERS of dependencies added to DEPS:\n %s' % '\n '.join(sorted(unapproved_dependencies)))] if not input_api.is_committing: suggested_owners = owners_db.reviewers_for(missing_files, owner_email) output_list.append(output( 'Suggested missing target path OWNERS:\n %s' % '\n '.join(suggested_owners or []))) return output_list return [] def _CheckSpamLogging(input_api, output_api): file_inclusion_pattern = r'.+%s' % _IMPLEMENTATION_EXTENSIONS black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST + (r"^base[\\\/]logging\.h$", r"^base[\\\/]logging\.cc$", r"^chrome[\\\/]app[\\\/]chrome_main_delegate\.cc$", r"^chrome[\\\/]browser[\\\/]chrome_browser_main\.cc$", r"^chrome[\\\/]browser[\\\/]ui[\\\/]startup[\\\/]" r"startup_browser_creator\.cc$", r"^chrome[\\\/]installer[\\\/]setup[\\\/].*", r"chrome[\\\/]browser[\\\/]diagnostics[\\\/]" + r"diagnostics_writer\.cc$", r"^chrome_elf[\\\/]dll_hash[\\\/]dll_hash_main\.cc$", r"^chromecast[\\\/]", r"^cloud_print[\\\/]", r"^content[\\\/]common[\\\/]gpu[\\\/]client[\\\/]" r"gl_helper_benchmark\.cc$", r"^courgette[\\\/]courgette_tool\.cc$", r"^extensions[\\\/]renderer[\\\/]logging_native_handler\.cc$", r"^ipc[\\\/]ipc_logging\.cc$", r"^native_client_sdk[\\\/]", r"^remoting[\\\/]base[\\\/]logging\.h$", r"^remoting[\\\/]host[\\\/].*", r"^sandbox[\\\/]linux[\\\/].*", r"^tools[\\\/]", r"^ui[\\\/]aura[\\\/]bench[\\\/]bench_main\.cc$", r"^storage[\\\/]browser[\\\/]fileapi[\\\/]" + r"dump_file_system.cc$",)) source_file_filter = lambda x: input_api.FilterSourceFile( x, white_list=(file_inclusion_pattern,), black_list=black_list) log_info = [] printf = [] for f in input_api.AffectedSourceFiles(source_file_filter): contents = input_api.ReadFile(f, 'rb') if input_api.re.search(r"\bD?LOG\s*$\s*INFO\s*$", contents): log_info.append(f.LocalPath()) elif input_api.re.search(r"\bD?LOG_IF\s*\(\s*INFO\s*,", contents): log_info.append(f.LocalPath()) if input_api.re.search(r"\bprintf\(", contents): printf.append(f.LocalPath()) elif input_api.re.search(r"\bfprintf\((stdout|stderr)", contents): printf.append(f.LocalPath()) if log_info: return [output_api.PresubmitError( 'These files spam the console log with LOG(INFO):', items=log_info)] if printf: return [output_api.PresubmitError( 'These files spam the console log with printf/fprintf:', items=printf)] return [] def _CheckForAnonymousVariables(input_api, output_api): """These types are all expected to hold locks while in scope and so should never be anonymous (which causes them to be immediately destroyed).""" they_who_must_be_named = [ 'base::AutoLock', 'base::AutoReset', 'base::AutoUnlock', 'SkAutoAlphaRestore', 'SkAutoBitmapShaderInstall', 'SkAutoBlitterChoose', 'SkAutoBounderCommit', 'SkAutoCallProc', 'SkAutoCanvasRestore', 'SkAutoCommentBlock', 'SkAutoDescriptor', 'SkAutoDisableDirectionCheck', 'SkAutoDisableOvalCheck', 'SkAutoFree', 'SkAutoGlyphCache', 'SkAutoHDC', 'SkAutoLockColors', 'SkAutoLockPixels', 'SkAutoMalloc', 'SkAutoMaskFreeImage', 'SkAutoMutexAcquire', 'SkAutoPathBoundsUpdate', 'SkAutoPDFRelease', 'SkAutoRasterClipValidate', 'SkAutoRef', 'SkAutoTime', 'SkAutoTrace', 'SkAutoUnref', ] anonymous = r'(%s)\s*[({]' % '|'.join(they_who_must_be_named) # bad: base::AutoLock(lock.get()); # not bad: base::AutoLock lock(lock.get()); bad_pattern = input_api.re.compile(anonymous) # good: new base::AutoLock(lock.get()) good_pattern = input_api.re.compile(r'\bnew\s*' + anonymous) errors = [] for f in input_api.AffectedFiles(): if not f.LocalPath().endswith(('.cc', '.h', '.inl', '.m', '.mm')): continue for linenum, line in f.ChangedContents(): if bad_pattern.search(line) and not good_pattern.search(line): errors.append('%s:%d' % (f.LocalPath(), linenum)) if errors: return [output_api.PresubmitError( 'These lines create anonymous variables that need to be named:', items=errors)] return [] def _CheckCygwinShell(input_api, output_api): source_file_filter = lambda x: input_api.FilterSourceFile( x, white_list=(r'.+\.(gyp|gypi)$',)) cygwin_shell = [] for f in input_api.AffectedSourceFiles(source_file_filter): for linenum, line in f.ChangedContents(): if 'msvs_cygwin_shell' in line: cygwin_shell.append(f.LocalPath()) break if cygwin_shell: return [output_api.PresubmitError( 'These files should not use msvs_cygwin_shell (the default is 0):', items=cygwin_shell)] return [] def _CheckUserActionUpdate(input_api, output_api): """Checks if any new user action has been added.""" if any('actions.xml' == input_api.os_path.basename(f) for f in input_api.LocalPaths()): # If actions.xml is already included in the changelist, the PRESUBMIT # for actions.xml will do a more complete presubmit check. return [] file_filter = lambda f: f.LocalPath().endswith(('.cc', '.mm')) action_re = r'[^a-zA-Z]UserMetricsAction\("([^"]*)' current_actions = None for f in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in f.ChangedContents(): match = input_api.re.search(action_re, line) if match: # Loads contents in tools/metrics/actions/actions.xml to memory. It's # loaded only once. if not current_actions: with open('tools/metrics/actions/actions.xml') as actions_f: current_actions = actions_f.read() # Search for the matched user action name in |current_actions|. for action_name in match.groups(): action = 'name="{0}"'.format(action_name) if action not in current_actions: return [output_api.PresubmitPromptWarning( 'File %s line %d: %s is missing in ' 'tools/metrics/actions/actions.xml. Please run ' 'tools/metrics/actions/extract_actions.py to update.' % (f.LocalPath(), line_num, action_name))] return [] def _GetJSONParseError(input_api, filename, eat_comments=True): try: contents = input_api.ReadFile(filename) if eat_comments: json_comment_eater = input_api.os_path.join( input_api.PresubmitLocalPath(), 'tools', 'json_comment_eater', 'json_comment_eater.py') process = input_api.subprocess.Popen( [input_api.python_executable, json_comment_eater], stdin=input_api.subprocess.PIPE, stdout=input_api.subprocess.PIPE, universal_newlines=True) (contents, _) = process.communicate(input=contents) input_api.json.loads(contents) except ValueError as e: return e return None def _GetIDLParseError(input_api, filename): try: contents = input_api.ReadFile(filename) idl_schema = input_api.os_path.join( input_api.PresubmitLocalPath(), 'tools', 'json_schema_compiler', 'idl_schema.py') process = input_api.subprocess.Popen( [input_api.python_executable, idl_schema], stdin=input_api.subprocess.PIPE, stdout=input_api.subprocess.PIPE, stderr=input_api.subprocess.PIPE, universal_newlines=True) (_, error) = process.communicate(input=contents) return error or None except ValueError as e: return e def _CheckParseErrors(input_api, output_api): """Check that IDL and JSON files do not contain syntax errors.""" actions = { '.idl': _GetIDLParseError, '.json': _GetJSONParseError, } # These paths contain test data and other known invalid JSON files. excluded_patterns = [ r'test[\\\/]data[\\\/]', r'^components[\\\/]policy[\\\/]resources[\\\/]policy_templates\.json$', ] # Most JSON files are preprocessed and support comments, but these do not. json_no_comments_patterns = [ r'^testing[\\\/]', ] # Only run IDL checker on files in these directories. idl_included_patterns = [ r'^chrome[\\\/]common[\\\/]extensions[\\\/]api[\\\/]', r'^extensions[\\\/]common[\\\/]api[\\\/]', ] def get_action(affected_file): filename = affected_file.LocalPath() return actions.get(input_api.os_path.splitext(filename)[1]) def MatchesFile(patterns, path): for pattern in patterns: if input_api.re.search(pattern, path): return True return False def FilterFile(affected_file): action = get_action(affected_file) if not action: return False path = affected_file.LocalPath() if MatchesFile(excluded_patterns, path): return False if (action == _GetIDLParseError and not MatchesFile(idl_included_patterns, path)): return False return True results = [] for affected_file in input_api.AffectedFiles( file_filter=FilterFile, include_deletes=False): action = get_action(affected_file) kwargs = {} if (action == _GetJSONParseError and MatchesFile(json_no_comments_patterns, affected_file.LocalPath())): kwargs['eat_comments'] = False parse_error = action(input_api, affected_file.AbsoluteLocalPath(), **kwargs) if parse_error: results.append(output_api.PresubmitError('%s could not be parsed: %s' % (affected_file.LocalPath(), parse_error))) return results def _CheckJavaStyle(input_api, output_api): """Runs checkstyle on changed java files and returns errors if any exist.""" import sys original_sys_path = sys.path try: sys.path = sys.path + [input_api.os_path.join( input_api.PresubmitLocalPath(), 'tools', 'android', 'checkstyle')] import checkstyle finally: # Restore sys.path to what it was before. sys.path = original_sys_path return checkstyle.RunCheckstyle( input_api, output_api, 'tools/android/checkstyle/chromium-style-5.0.xml', black_list=_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) def _CheckForCopyrightedCode(input_api, output_api): """Verifies that newly added code doesn't contain copyrighted material and is properly licensed under the standard Chromium license. As there can be false positives, we maintain a whitelist file. This check also verifies that the whitelist file is up to date. """ import sys original_sys_path = sys.path try: sys.path = sys.path + [input_api.os_path.join( input_api.PresubmitLocalPath(), 'android_webview', 'tools')] import copyright_scanner finally: # Restore sys.path to what it was before. sys.path = original_sys_path return copyright_scanner.ScanAtPresubmit(input_api, output_api) def _CheckSingletonInHeaders(input_api, output_api): """Checks to make sure no header files have |Singleton<|.""" def FileFilter(affected_file): # It's ok for base/memory/singleton.h to have |Singleton<|. black_list = (_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST + (r"^base[\\\/]memory[\\\/]singleton\.h$",)) return input_api.FilterSourceFile(affected_file, black_list=black_list) pattern = input_api.re.compile(r'(?<!class\s)Singleton\s*<') files = [] for f in input_api.AffectedSourceFiles(FileFilter): if (f.LocalPath().endswith('.h') or f.LocalPath().endswith('.hxx') or f.LocalPath().endswith('.hpp') or f.LocalPath().endswith('.inl')): contents = input_api.ReadFile(f) for line in contents.splitlines(False): if (not input_api.re.match(r'//', line) and # Strip C++ comment. pattern.search(line)): files.append(f) break if files: return [ output_api.PresubmitError( 'Found Singleton<T> in the following header files.\n' + 'Please move them to an appropriate source file so that the ' + 'template gets instantiated in a single compilation unit.', files) ] return [] _DEPRECATED_CSS = [ # Values ( "-webkit-box", "flex" ), ( "-webkit-inline-box", "inline-flex" ), ( "-webkit-flex", "flex" ), ( "-webkit-inline-flex", "inline-flex" ), ( "-webkit-min-content", "min-content" ), ( "-webkit-max-content", "max-content" ), # Properties ( "-webkit-background-clip", "background-clip" ), ( "-webkit-background-origin", "background-origin" ), ( "-webkit-background-size", "background-size" ), ( "-webkit-box-shadow", "box-shadow" ), # Functions ( "-webkit-gradient", "gradient" ), ( "-webkit-repeating-gradient", "repeating-gradient" ), ( "-webkit-linear-gradient", "linear-gradient" ), ( "-webkit-repeating-linear-gradient", "repeating-linear-gradient" ), ( "-webkit-radial-gradient", "radial-gradient" ), ( "-webkit-repeating-radial-gradient", "repeating-radial-gradient" ), ] def _CheckNoDeprecatedCSS(input_api, output_api): """ Make sure that we don't use deprecated CSS properties, functions or values. Our external documentation is ignored by the hooks as it needs to be consumed by WebKit. """ results = [] file_inclusion_pattern = (r".+\.css$",) black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST + (r"^chrome/common/extensions/docs", r"^chrome/docs", r"^native_client_sdk")) file_filter = lambda f: input_api.FilterSourceFile( f, white_list=file_inclusion_pattern, black_list=black_list) for fpath in input_api.AffectedFiles(file_filter=file_filter): for line_num, line in fpath.ChangedContents(): for (deprecated_value, value) in _DEPRECATED_CSS: if deprecated_value in line: results.append(output_api.PresubmitError( "%s:%d: Use of deprecated CSS %s, use %s instead" % (fpath.LocalPath(), line_num, deprecated_value, value))) return results _DEPRECATED_JS = [ ( "__lookupGetter__", "Object.getOwnPropertyDescriptor" ), ( "__defineGetter__", "Object.defineProperty" ), ( "__defineSetter__", "Object.defineProperty" ), ] def _CheckNoDeprecatedJS(input_api, output_api): """Make sure that we don't use deprecated JS in Chrome code.""" results = [] file_inclusion_pattern = (r".+\.js$",) # TODO(dbeam): .html? black_list = (_EXCLUDED_PATHS + _TEST_CODE_EXCLUDED_PATHS + input_api.DEFAULT_BLACK_LIST) file_filter = lambda f: input_api.FilterSourceFile( f, white_list=file_inclusion_pattern, black_list=black_list) for fpath in input_api.AffectedFiles(file_filter=file_filter): for lnum, line in fpath.ChangedContents(): for (deprecated, replacement) in _DEPRECATED_JS: if deprecated in line: results.append(output_api.PresubmitError( "%s:%d: Use of deprecated JS %s, use %s instead" % (fpath.LocalPath(), lnum, deprecated, replacement))) return results def _CommonChecks(input_api, output_api): """Checks common to both upload and commit.""" results = [] results.extend(input_api.canned_checks.PanProjectChecks( input_api, output_api, excluded_paths=_EXCLUDED_PATHS + _TESTRUNNER_PATHS)) results.extend(_CheckAuthorizedAuthor(input_api, output_api)) results.extend( _CheckNoProductionCodeUsingTestOnlyFunctions(input_api, output_api)) results.extend(_CheckNoIOStreamInHeaders(input_api, output_api)) results.extend(_CheckNoUNIT_TESTInSourceFiles(input_api, output_api)) results.extend(_CheckNoNewWStrings(input_api, output_api)) results.extend(_CheckNoDEPSGIT(input_api, output_api)) results.extend(_CheckNoBannedFunctions(input_api, output_api)) results.extend(_CheckNoPragmaOnce(input_api, output_api)) results.extend(_CheckNoTrinaryTrueFalse(input_api, output_api)) results.extend(_CheckUnwantedDependencies(input_api, output_api)) results.extend(_CheckFilePermissions(input_api, output_api)) results.extend(_CheckNoAuraWindowPropertyHInHeaders(input_api, output_api)) results.extend(_CheckIncludeOrder(input_api, output_api)) results.extend(_CheckForVersionControlConflicts(input_api, output_api)) results.extend(_CheckPatchFiles(input_api, output_api)) results.extend(_CheckHardcodedGoogleHostsInLowerLayers(input_api, output_api)) results.extend(_CheckNoAbbreviationInPngFileName(input_api, output_api)) results.extend(_CheckForInvalidOSMacros(input_api, output_api)) results.extend(_CheckForInvalidIfDefinedMacros(input_api, output_api)) # TODO(danakj): Remove this when base/move.h is removed. results.extend(_CheckForUsingSideEffectsOfPass(input_api, output_api)) results.extend(_CheckAddedDepsHaveTargetApprovals(input_api, output_api)) results.extend( input_api.canned_checks.CheckChangeHasNoTabs( input_api, output_api, source_file_filter=lambda x: x.LocalPath().endswith('.grd'))) results.extend(_CheckSpamLogging(input_api, output_api)) results.extend(_CheckForAnonymousVariables(input_api, output_api)) results.extend(_CheckCygwinShell(input_api, output_api)) results.extend(_CheckUserActionUpdate(input_api, output_api)) results.extend(_CheckNoDeprecatedCSS(input_api, output_api)) results.extend(_CheckNoDeprecatedJS(input_api, output_api)) results.extend(_CheckParseErrors(input_api, output_api)) results.extend(_CheckForIPCRules(input_api, output_api)) results.extend(_CheckForCopyrightedCode(input_api, output_api)) results.extend(_CheckForWindowsLineEndings(input_api, output_api)) results.extend(_CheckSingletonInHeaders(input_api, output_api)) if any('PRESUBMIT.py' == f.LocalPath() for f in input_api.AffectedFiles()): results.extend(input_api.canned_checks.RunUnitTestsInDirectory( input_api, output_api, input_api.PresubmitLocalPath(), whitelist=[r'^PRESUBMIT_test\.py$'])) return results def _CheckAuthorizedAuthor(input_api, output_api): """For non-googler/chromites committers, verify the author's email address is in AUTHORS. """ # TODO(maruel): Add it to input_api? import fnmatch author = input_api.change.author_email if not author: input_api.logging.info('No author, skipping AUTHOR check') return [] authors_path = input_api.os_path.join( input_api.PresubmitLocalPath(), 'AUTHORS') valid_authors = ( input_api.re.match(r'[^#]+\s+\<(.+?)\>\s*$', line) for line in open(authors_path)) valid_authors = [item.group(1).lower() for item in valid_authors if item] if not any(fnmatch.fnmatch(author.lower(), valid) for valid in valid_authors): input_api.logging.info('Valid authors are %s', ', '.join(valid_authors)) return [output_api.PresubmitPromptWarning( ('%s is not in AUTHORS file. If you are a new contributor, please visit' '\n' 'http://www.chromium.org/developers/contributing-code and read the ' '"Legal" section\n' 'If you are a chromite, verify the contributor signed the CLA.') % author)] return [] def _CheckPatchFiles(input_api, output_api): problems = [f.LocalPath() for f in input_api.AffectedFiles() if f.LocalPath().endswith(('.orig', '.rej'))] if problems: return [output_api.PresubmitError( "Don't commit .rej and .orig files.", problems)] else: return [] def _DidYouMeanOSMacro(bad_macro): try: return {'A': 'OS_ANDROID', 'B': 'OS_BSD', 'C': 'OS_CHROMEOS', 'F': 'OS_FREEBSD', 'L': 'OS_LINUX', 'M': 'OS_MACOSX', 'N': 'OS_NACL', 'O': 'OS_OPENBSD', 'P': 'OS_POSIX', 'S': 'OS_SOLARIS', 'W': 'OS_WIN'}[bad_macro[3].upper()] except KeyError: return '' def _CheckForInvalidOSMacrosInFile(input_api, f): """Check for sensible looking, totally invalid OS macros.""" preprocessor_statement = input_api.re.compile(r'^\s*#') os_macro = input_api.re.compile(r'defined$(OS_[^)]+)$') results = [] for lnum, line in f.ChangedContents(): if preprocessor_statement.search(line): for match in os_macro.finditer(line): if not match.group(1) in _VALID_OS_MACROS: good = _DidYouMeanOSMacro(match.group(1)) did_you_mean = ' (did you mean %s?)' % good if good else '' results.append(' %s:%d %s%s' % (f.LocalPath(), lnum, match.group(1), did_you_mean)) return results def _CheckForInvalidOSMacros(input_api, output_api): """Check all affected files for invalid OS macros.""" bad_macros = [] for f in input_api.AffectedFiles(): if not f.LocalPath().endswith(('.py', '.js', '.html', '.css')): bad_macros.extend(_CheckForInvalidOSMacrosInFile(input_api, f)) if not bad_macros: return [] return [output_api.PresubmitError( 'Possibly invalid OS macro[s] found. Please fix your code\n' 'or add your macro to src/PRESUBMIT.py.', bad_macros)] def _CheckForInvalidIfDefinedMacrosInFile(input_api, f): """Check all affected files for invalid "if defined" macros.""" ALWAYS_DEFINED_MACROS = ( "TARGET_CPU_PPC", "TARGET_CPU_PPC64", "TARGET_CPU_68K", "TARGET_CPU_X86", "TARGET_CPU_ARM", "TARGET_CPU_MIPS", "TARGET_CPU_SPARC", "TARGET_CPU_ALPHA", "TARGET_IPHONE_SIMULATOR", "TARGET_OS_EMBEDDED", "TARGET_OS_IPHONE", "TARGET_OS_MAC", "TARGET_OS_UNIX", "TARGET_OS_WIN32", ) ifdef_macro = input_api.re.compile(r'^\s*#.*(?:ifdef\s|defined$)([^\s$]+)') results = [] for lnum, line in f.ChangedContents(): for match in ifdef_macro.finditer(line): if match.group(1) in ALWAYS_DEFINED_MACROS: always_defined = ' %s is always defined. ' % match.group(1) did_you_mean = 'Did you mean \'#if %s\'?' % match.group(1) results.append(' %s:%d %s\n\t%s' % (f.LocalPath(), lnum, always_defined, did_you_mean)) return results def _CheckForInvalidIfDefinedMacros(input_api, output_api): """Check all affected files for invalid "if defined" macros.""" bad_macros = [] for f in input_api.AffectedFiles(): if f.LocalPath().endswith(('.h', '.c', '.cc', '.m', '.mm')): bad_macros.extend(_CheckForInvalidIfDefinedMacrosInFile(input_api, f)) if not bad_macros: return [] return [output_api.PresubmitError( 'Found ifdef check on always-defined macro[s]. Please fix your code\n' 'or check the list of ALWAYS_DEFINED_MACROS in src/PRESUBMIT.py.', bad_macros)] def _CheckForUsingSideEffectsOfPass(input_api, output_api): """Check all affected files for using side effects of Pass.""" errors = [] for f in input_api.AffectedFiles(): if f.LocalPath().endswith(('.h', '.c', '.cc', '.m', '.mm')): for lnum, line in f.ChangedContents(): # Disallow Foo(*my_scoped_thing.Pass()); See crbug.com/418297. if input_api.re.search(r'\*[a-zA-Z0-9_]+\.Pass', line): errors.append(output_api.PresubmitError( ('%s:%d uses *foo.Pass() to delete the contents of scoped_ptr. ' + 'See crbug.com/418297.') % (f.LocalPath(), lnum))) return errors def _CheckForIPCRules(input_api, output_api): """Check for same IPC rules described in http://www.chromium.org/Home/chromium-security/education/security-tips-for-ipc """ base_pattern = r'IPC_ENUM_TRAITS\(' inclusion_pattern = input_api.re.compile(r'(%s)' % base_pattern) comment_pattern = input_api.re.compile(r'//.*(%s)' % base_pattern) problems = [] for f in input_api.AffectedSourceFiles(None): local_path = f.LocalPath() if not local_path.endswith('.h'): continue for line_number, line in f.ChangedContents(): if inclusion_pattern.search(line) and not comment_pattern.search(line): problems.append( '%s:%d\n %s' % (local_path, line_number, line.strip())) if problems: return [output_api.PresubmitPromptWarning( _IPC_ENUM_TRAITS_DEPRECATED, problems)] else: return [] def _CheckForWindowsLineEndings(input_api, output_api): """Check source code and known ascii text files for Windows style line endings. """ known_text_files = r'.*\.(txt|html|htm|mhtml|py|gyp|gypi|gn|isolate)$' file_inclusion_pattern = ( known_text_files, r'.+%s' % _IMPLEMENTATION_EXTENSIONS ) filter = lambda f: input_api.FilterSourceFile( f, white_list=file_inclusion_pattern, black_list=None) files = [f.LocalPath() for f in input_api.AffectedSourceFiles(filter)] problems = [] for file in files: fp = open(file, 'r') for line in fp: if line.endswith('\r\n'): problems.append(file) break fp.close() if problems: return [output_api.PresubmitPromptWarning('Are you sure that you want ' 'these files to contain Windows style line endings?\n' + '\n'.join(problems))] return [] def CheckChangeOnUpload(input_api, output_api): results = [] results.extend(_CommonChecks(input_api, output_api)) results.extend(_CheckValidHostsInDEPS(input_api, output_api)) results.extend(_CheckJavaStyle(input_api, output_api)) results.extend( input_api.canned_checks.CheckGNFormatted(input_api, output_api)) results.extend(_CheckUmaHistogramChanges(input_api, output_api)) return results def GetTryServerMasterForBot(bot): """Returns the Try Server master for the given bot. It tries to guess the master from the bot name, but may still fail and return None. There is no longer a default master. """ # Potentially ambiguous bot names are listed explicitly. master_map = { 'chromium_presubmit': 'tryserver.chromium.linux', 'blink_presubmit': 'tryserver.chromium.linux', 'tools_build_presubmit': 'tryserver.chromium.linux', } master = master_map.get(bot) if not master: if 'linux' in bot or 'android' in bot or 'presubmit' in bot: master = 'tryserver.chromium.linux' elif 'win' in bot: master = 'tryserver.chromium.win' elif 'mac' in bot or 'ios' in bot: master = 'tryserver.chromium.mac' return master def GetDefaultTryConfigs(bots): """Returns a list of ('bot', set(['tests']), filtered by [bots]. """ builders_and_tests = dict((bot, set(['defaulttests'])) for bot in bots) # Build up the mapping from tryserver master to bot/test. out = dict() for bot, tests in builders_and_tests.iteritems(): out.setdefault(GetTryServerMasterForBot(bot), {})[bot] = tests return out def CheckChangeOnCommit(input_api, output_api): results = [] results.extend(_CommonChecks(input_api, output_api)) # TODO(thestig) temporarily disabled, doesn't work in third_party/ #results.extend(input_api.canned_checks.CheckSvnModifiedDirectories( # input_api, output_api, sources)) # Make sure the tree is 'open'. results.extend(input_api.canned_checks.CheckTreeIsOpen( input_api, output_api, json_url='http://chromium-status.appspot.com/current?format=json')) results.extend(input_api.canned_checks.CheckChangeHasBugField( input_api, output_api)) results.extend(input_api.canned_checks.CheckChangeHasDescription( input_api, output_api)) return results def GetPreferredTryMasters(project, change): import re files = change.LocalPaths() import os import json with open(os.path.join( change.RepositoryRoot(), 'testing', 'commit_queue', 'config.json')) as f: cq_config = json.load(f) cq_verifiers = cq_config.get('verifiers_no_patch', {}) cq_try_jobs = cq_verifiers.get('try_job_verifier', {}) builders = cq_try_jobs.get('launched', {}) for master, master_config in cq_try_jobs.get('triggered', {}).iteritems(): for triggered_bot in master_config: builders.get(master, {}).pop(triggered_bot, None) # Explicitly iterate over copies of dicts since we mutate them. for master in builders.keys(): for builder in builders[master].keys(): # Do not trigger presubmit builders, since they're likely to fail # (e.g. OWNERS checks before finished code review), and we're # running local presubmit anyway. if 'presubmit' in builder: builders[master].pop(builder) return builders

mou4e/zirconium

PRESUBMIT.py

Python

bsd-3-clause

64,946

[ "VisIt" ]

73c03dc325168a0a5d63c158ec65589a3800f14bea235698dcf21bc3646d5706

# coding=utf-8 """Create contour from shakemap raster layer.""" import logging import os import shutil from datetime import datetime import numpy as np from osgeo import gdal, ogr from osgeo.gdalconst import GA_ReadOnly from qgis.core import QgsFeatureRequest, QgsVectorLayer from safe.common.exceptions import ( ContourCreationError, FileNotFoundError, InvalidLayerError ) from safe.common.utilities import ( romanise, temp_dir, unique_filename ) from safe.definitions import contour_id_field from safe.definitions.constants import NUMPY_SMOOTHING from safe.definitions.fields import ( contour_colour_field, contour_fields, contour_halign_field, contour_length_field, contour_mmi_field, contour_roman_field, contour_valign_field, contour_x_field, contour_y_field ) from safe.definitions.layer_geometry import layer_geometry_line from safe.definitions.layer_modes import layer_mode_classified from safe.definitions.layer_purposes import layer_purpose_earthquake_contour from safe.gis.vector.tools import ( create_ogr_field_from_definition, field_index_from_definition ) from safe.utilities.i18n import tr from safe.utilities.metadata import write_iso19115_metadata from safe.utilities.resources import resources_path from safe.utilities.styling import mmi_colour __copyright__ = "Copyright 2017, The InaSAFE Project" __license__ = "GPL version 3" __email__ = "info@inasafe.org" __revision__ = '$Format:%H$' LOGGER = logging.getLogger('InaSAFE') def gaussian_kernel(sigma, truncate=4.0): """Return Gaussian that truncates at the given number of std deviations. Adapted from https://github.com/nicjhan/gaussian-filter """ sigma = float(sigma) radius = int(truncate * sigma + 0.5) x, y = np.mgrid[-radius:radius + 1, -radius:radius + 1] sigma = sigma ** 2 k = 2 * np.exp(-0.5 * (x ** 2 + y ** 2) / sigma) k = k / np.sum(k) return k def tile_and_reflect(input): """Make 3x3 tiled array. Central area is 'input', surrounding areas are reflected. Adapted from https://github.com/nicjhan/gaussian-filter """ tiled_input = np.tile(input, (3, 3)) rows = input.shape[0] cols = input.shape[1] # Now we have a 3x3 tiles - do the reflections. # All those on the sides need to be flipped left-to-right. for i in range(3): # Left hand side tiles tiled_input[i * rows:(i + 1) * rows, 0:cols] = \ np.fliplr(tiled_input[i * rows:(i + 1) * rows, 0:cols]) # Right hand side tiles tiled_input[i * rows:(i + 1) * rows, -cols:] = \ np.fliplr(tiled_input[i * rows:(i + 1) * rows, -cols:]) # All those on the top and bottom need to be flipped up-to-down for i in range(3): # Top row tiled_input[0:rows, i * cols:(i + 1) * cols] = \ np.flipud(tiled_input[0:rows, i * cols:(i + 1) * cols]) # Bottom row tiled_input[-rows:, i * cols:(i + 1) * cols] = \ np.flipud(tiled_input[-rows:, i * cols:(i + 1) * cols]) # The central array should be unchanged. assert (np.array_equal(input, tiled_input[rows:2 * rows, cols:2 * cols])) # All sides of the middle array should be the same as those bordering them. # Check this starting at the top and going around clockwise. This can be # visually checked by plotting the 'tiled_input' array. assert (np.array_equal(input[0, :], tiled_input[rows - 1, cols:2 * cols])) assert (np.array_equal(input[:, -1], tiled_input[rows:2 * rows, 2 * cols])) assert (np.array_equal(input[-1, :], tiled_input[2 * rows, cols:2 * cols])) assert (np.array_equal(input[:, 0], tiled_input[rows:2 * rows, cols - 1])) return tiled_input def convolve(input, weights, mask=None, slow=False): """2 dimensional convolution. This is a Python implementation of what will be written in Fortran. Borders are handled with reflection. Masking is supported in the following way: * Masked points are skipped. * Parts of the input which are masked have weight 0 in the kernel. * Since the kernel as a whole needs to have value 1, the weights of the masked parts of the kernel are evenly distributed over the non-masked parts. Adapted from https://github.com/nicjhan/gaussian-filter """ assert (len(input.shape) == 2) assert (len(weights.shape) == 2) # Only one reflection is done on each side so the weights array cannot be # bigger than width/height of input +1. assert (weights.shape[0] < input.shape[0] + 1) assert (weights.shape[1] < input.shape[1] + 1) if mask is not None: # The slow convolve does not support masking. assert (not slow) assert (input.shape == mask.shape) tiled_mask = tile_and_reflect(mask) output = np.copy(input) tiled_input = tile_and_reflect(input) rows = input.shape[0] cols = input.shape[1] # Stands for half weights row. hw_row = np.int(weights.shape[0] / 2) hw_col = np.int(weights.shape[1] / 2) # Stands for full weights row. fw_row = weights.shape[0] fw_col = weights.shape[0] # Now do convolution on central array. # Iterate over tiled_input. for i, io in zip(list(range(rows, rows * 2)), list(range(rows))): for j, jo in zip(list(range(cols, cols * 2)), list(range(cols))): # The current central pixel is at (i, j) # Skip masked points. if mask is not None and tiled_mask[i, j]: continue average = 0.0 if slow: # Iterate over weights/kernel. for k in range(weights.shape[0]): # NOQA for l in range(weights.shape[1]): # NOQA # Get coordinates of tiled_input array that match given # weights m = i + k - hw_row n = j + l - hw_col average += tiled_input[m, n] * weights[k, l] else: # Find the part of the tiled_input array that overlaps with the # weights array. overlapping = tiled_input[ i - hw_row:i - hw_row + fw_row, j - hw_col:j - hw_col + fw_col] assert (overlapping.shape == weights.shape) # If any of 'overlapping' is masked then set the corresponding # points in the weights matrix to 0 and redistribute these to # non-masked points. if mask is not None: overlapping_mask = tiled_mask[ i - hw_row:i - hw_row + fw_row, j - hw_col:j - hw_col + fw_row] assert (overlapping_mask.shape == weights.shape) # Total value and number of weights clobbered by the mask. clobber_total = np.sum(weights[overlapping_mask]) remaining_num = np.sum(np.logical_not(overlapping_mask)) # This is impossible since at least i, j is not masked. assert (remaining_num > 0) correction = clobber_total / remaining_num # It is OK if nothing is masked - the weights will not be # changed. if correction == 0: assert (not overlapping_mask.any()) # Redistribute to non-masked points. tmp_weights = np.copy(weights) tmp_weights[overlapping_mask] = 0.0 tmp_weights[np.where(tmp_weights != 0)] += correction # Should be very close to 1. May not be exact due to # rounding. assert (abs(np.sum(tmp_weights) - 1) < 1e-15) else: tmp_weights = weights merged = tmp_weights[:] * overlapping average = np.sum(merged) # Set new output value. output[io, jo] = average return output def create_smooth_contour( shakemap_layer, output_file_path='', active_band=1, smoothing_method=NUMPY_SMOOTHING, smoothing_sigma=0.9): """Create contour from a shake map layer by using smoothing method. :param shakemap_layer: The shake map raster layer. :type shakemap_layer: QgsRasterLayer :param active_band: The band which the data located, default to 1. :type active_band: int :param smoothing_method: The smoothing method that wanted to be used. :type smoothing_method: NONE_SMOOTHING, NUMPY_SMOOTHING, SCIPY_SMOOTHING :param smooth_sigma: parameter for gaussian filter used in smoothing function. :type smooth_sigma: float :returns: The contour of the shake map layer path. :rtype: basestring """ timestamp = datetime.now() temp_smoothed_shakemap_path = unique_filename( prefix='temp-shake-map' + timestamp.strftime('%Y%m%d-%H%M%S'), suffix='.tif', dir=temp_dir('temp')) temp_smoothed_shakemap_path = smooth_shakemap( shakemap_layer.source(), output_file_path=temp_smoothed_shakemap_path, active_band=active_band, smoothing_method=smoothing_method, smoothing_sigma=smoothing_sigma ) return shakemap_contour( temp_smoothed_shakemap_path, output_file_path=output_file_path, active_band=active_band ) def smooth_shakemap( shakemap_layer_path, output_file_path='', active_band=1, smoothing_method=NUMPY_SMOOTHING, smoothing_sigma=0.9): """Make a smoother shakemap layer from a shake map. :param shakemap_layer_path: The shake map raster layer path. :type shakemap_layer_path: basestring :param active_band: The band which the data located, default to 1. :type active_band: int :param smoothing_method: The smoothing method that wanted to be used. :type smoothing_method: NONE_SMOOTHING, NUMPY_SMOOTHING, SCIPY_SMOOTHING :param smooth_sigma: parameter for gaussian filter used in smoothing function. :type smooth_sigma: float :returns: The contour of the shake map layer. :rtype: QgsRasterLayer """ # Set output path if not output_file_path: output_file_path = unique_filename(suffix='.tiff', dir=temp_dir()) # convert to numpy shakemap_file = gdal.Open(shakemap_layer_path) shakemap_array = np.array( shakemap_file.GetRasterBand(active_band).ReadAsArray()) # do smoothing if smoothing_method == NUMPY_SMOOTHING: smoothed_array = convolve(shakemap_array, gaussian_kernel( smoothing_sigma)) else: smoothed_array = shakemap_array # Create smoothed shakemap raster layer driver = gdal.GetDriverByName('GTiff') smoothed_shakemap_file = driver.Create( output_file_path, shakemap_file.RasterXSize, shakemap_file.RasterYSize, 1, gdal.GDT_Float32 # Important, since the default is integer ) smoothed_shakemap_file.GetRasterBand(1).WriteArray(smoothed_array) # CRS smoothed_shakemap_file.SetProjection(shakemap_file.GetProjection()) smoothed_shakemap_file.SetGeoTransform(shakemap_file.GetGeoTransform()) smoothed_shakemap_file.FlushCache() del smoothed_shakemap_file if not os.path.isfile(output_file_path): raise FileNotFoundError(tr( 'The smoothed shakemap is not created. It should be at ' '{output_file_path}'.format(output_file_path=output_file_path))) return output_file_path def shakemap_contour(shakemap_layer_path, output_file_path='', active_band=1): """Creating contour from a shakemap layer. :param shakemap_layer_path: The shake map raster layer path. :type shakemap_layer_path: basestring :param output_file_path: The path where the contour will be saved. :type output_file_path: basestring :param active_band: The band which the data located, default to 1. :type active_band: int :returns: The contour of the shake map layer path. :rtype: basestring """ # Set output path if not output_file_path: # There are minor issues with shapefile, so we switch to gpkg # See https://github.com/inasafe/inasafe/issues/5063 output_file_path = unique_filename(suffix='.gpkg', dir=temp_dir()) output_directory = os.path.dirname(output_file_path) output_file_name = os.path.basename(output_file_path) output_base_name = os.path.splitext(output_file_name)[0] # Based largely on # http://svn.osgeo.org/gdal/trunk/autotest/alg/contour.py # Use Geopackage driver to overcome this: # See https://github.com/inasafe/inasafe/issues/5063 driver = ogr.GetDriverByName('GPKG') ogr_dataset = driver.CreateDataSource(output_file_path) if ogr_dataset is None: # Probably the file existed and could not be overriden raise ContourCreationError( 'Could not create datasource for:\n%s. Check that the file ' 'does not already exist and that you do not have file system ' 'permissions issues' % output_file_path) # Set default fid options = ['FID={}'.format(contour_id_field['field_name'])] layer = ogr_dataset.CreateLayer('contour', options=options) for contour_field in contour_fields: field_definition = create_ogr_field_from_definition(contour_field) layer.CreateField(field_definition) shakemap_data = gdal.Open(shakemap_layer_path, GA_ReadOnly) # see http://gdal.org/java/org/gdal/gdal/gdal.html for these options contour_interval = 0.5 contour_base = 0 fixed_level_list = [] use_no_data_flag = 0 no_data_value = -9999 id_field = 0 # first field defined above elevation_field = 1 # second (MMI) field defined above try: gdal.ContourGenerate( shakemap_data.GetRasterBand(active_band), contour_interval, contour_base, fixed_level_list, use_no_data_flag, no_data_value, layer, id_field, elevation_field) except Exception as e: LOGGER.exception('Contour creation failed') raise ContourCreationError(str(e)) finally: ogr_dataset.Release() # Copy over the standard .prj file since ContourGenerate does not # create a projection definition projection_path = os.path.join( output_directory, output_base_name + '.prj') source_projection_path = resources_path( 'converter_data', 'mmi-contours.prj') shutil.copyfile(source_projection_path, projection_path) # Lastly copy over the standard qml (QGIS Style file) qml_path = os.path.join( output_directory, output_base_name + '.qml') source_qml_path = resources_path('converter_data', 'mmi-contours.qml') shutil.copyfile(source_qml_path, qml_path) # Create metadata file create_contour_metadata(output_file_path) # Now update the additional columns - X,Y, ROMAN and RGB try: set_contour_properties(output_file_path) except InvalidLayerError: raise del shakemap_data return output_file_path def set_contour_properties(contour_file_path): """Set the X, Y, RGB, ROMAN attributes of the contour layer. :param contour_file_path: Path of the contour layer. :type contour_file_path: str :raise: InvalidLayerError if anything is amiss with the layer. """ LOGGER.debug( 'Set_contour_properties requested for %s.' % contour_file_path) layer = QgsVectorLayer(contour_file_path, 'mmi-contours', "ogr") if not layer.isValid(): raise InvalidLayerError(contour_file_path) layer.startEditing() # Now loop through the db adding selected features to mem layer request = QgsFeatureRequest() for feature in layer.getFeatures(request): if not feature.isValid(): LOGGER.debug('Skipping feature') continue # Work out x and y line = feature.geometry().asPolyline() y = line[0].y() x_max = line[0].x() x_min = x_max for point in line: if point.y() < y: y = point.y() x = point.x() if x < x_min: x_min = x if x > x_max: x_max = x x = x_min + ((x_max - x_min) / 2) # Get length length = feature.geometry().length() mmi_value = float(feature[contour_mmi_field['field_name']]) # We only want labels on the whole number contours if mmi_value != round(mmi_value): roman = '' else: roman = romanise(mmi_value) # RGB from http://en.wikipedia.org/wiki/Mercalli_intensity_scale rgb = mmi_colour(mmi_value) # Now update the feature feature_id = feature.id() layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_x_field), x) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_y_field), y) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_colour_field), rgb) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_roman_field), roman) layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_halign_field), 'Center') layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_valign_field), 'HALF') layer.changeAttributeValue( feature_id, field_index_from_definition(layer, contour_length_field), length) layer.commitChanges() def create_contour_metadata(contour_path): """Create metadata file for contour layer. :param contour_path: Path where the contour is located. :type contour_path: basestring """ metadata = { 'title': tr('Earthquake Contour'), 'layer_purpose': layer_purpose_earthquake_contour['key'], 'layer_geometry': layer_geometry_line['key'], 'layer_mode': layer_mode_classified['key'], 'inasafe_fields': {} } for contour_field in contour_fields: metadata['inasafe_fields'][contour_field['key']] = contour_field[ 'field_name'] write_iso19115_metadata(contour_path, metadata)

AIFDR/inasafe

safe/gis/raster/contour.py

Python

gpl-3.0

18,679

[ "Gaussian" ]

61ad390e4f573a37be00e1e748a00f5c41563a5635e07af7e996311935e6f936

# Copyright 2013-2020 Lawrence Livermore National Security, LLC and other # Spack Project Developers. See the top-level COPYRIGHT file for details. # # SPDX-License-Identifier: (Apache-2.0 OR MIT) from spack import * class RSummarizedexperiment(RPackage): """SummarizedExperiment container. The SummarizedExperiment container contains one or more assays, each represented by a matrix-like object of numeric or other mode. The rows typically represent genomic ranges of interest and the columns represent samples.""" homepage = "https://bioconductor.org/packages/SummarizedExperiment" git = "https://git.bioconductor.org/packages/SummarizedExperiment.git" version('1.18.2', commit='e22fafe') version('1.14.1', commit='2c68d99e11c7345e5ed388370822ea48395c64a4') version('1.12.0', commit='5f8416864636add121ec1d6737ebb89a42227fd7') version('1.10.1', commit='7ad2e991c8285bfc4b2e15b29d94cc86d07f8f2b') version('1.8.1', commit='9d8a29aa9c78bbc7dcc6472537e13fc0d11dc1f7') version('1.6.5', commit='ec69cd5cfbccaef148a9f6abdfb3e22e888695d0') depends_on('r@3.2:', type=('build', 'run')) depends_on('r-genomicranges@1.27.22:', type=('build', 'run')) depends_on('r-biobase', type=('build', 'run')) depends_on('r-delayedarray@0.1.9:', type=('build', 'run')) depends_on('r-matrix', type=('build', 'run')) depends_on('r-biocgenerics@0.15.3:', type=('build', 'run')) depends_on('r-s4vectors@0.13.13:', type=('build', 'run')) depends_on('r-iranges@2.7.2:', type=('build', 'run')) depends_on('r-genomeinfodb@1.11.4:', type=('build', 'run')) depends_on('r-genomicranges@1.29.14:', when='@1.8.1:', type=('build', 'run')) depends_on('r-delayedarray@0.3.20:', when='@1.8.1:', type=('build', 'run')) depends_on('r-iranges@2.11.17:', when='@1.8.1:', type=('build', 'run')) depends_on('r-genomeinfodb@1.13.1:', when='@1.8.1:', type=('build', 'run')) depends_on('r-genomicranges@1.31.17:', when='@1.10.1:', type=('build', 'run')) depends_on('r-s4vectors@0.17.25:', when='@1.10.1:', type=('build', 'run')) depends_on('r-iranges@2.13.16:', when='@1.10.1:', type=('build', 'run')) depends_on('r-genomicranges@1.33.6:', when='@1.12.0:', type=('build', 'run'))

iulian787/spack

var/spack/repos/builtin/packages/r-summarizedexperiment/package.py

Python

lgpl-2.1

2,278

[ "Bioconductor" ]

822b0de0d413974025eb6111d683bbb51713ed1eebc3db6bf9b50b02c38ebe2a

# -*- coding: utf-8 -*- # SPDX-FileCopyrightText: 2016-2019 The Atlite Authors # # SPDX-License-Identifier: GPL-3.0-or-later """ Base class for Atlite. """ # There is a binary incompatibility between the pip wheels of netCDF4 and # rasterio, which leads to the first one to work correctly while the second # loaded one fails by loading netCDF4 first, we ensure that most of atlite's # functionality works fine, even when the pip wheels have been used, only for # resampling the sarah dataset it is important to use conda. # Refer to # https://github.com/pydata/xarray/issues/2535, # https://github.com/rasterio/rasterio-wheels/issues/12 import xarray as xr import pandas as pd import numpy as np import dask import rasterio as rio import geopandas as gpd from tempfile import mktemp from numpy import atleast_1d, append from warnings import warn from shapely.geometry import box from pathlib import Path from pyproj import CRS from .utils import CachedAttribute from .data import cutout_prepare, available_features from .gis import get_coords, compute_indicatormatrix, compute_availabilitymatrix from .convert import (convert_and_aggregate, heat_demand, hydro, temperature, wind, pv, runoff, solar_thermal, soil_temperature) from .datasets import modules as datamodules import logging logger = logging.getLogger(__name__) class Cutout: """ Cutout base class. This class builds the starting point for most atlite functionalities. """ def __init__(self, path, **cutoutparams): """ Provide an Atlite cutout object. Create a cutout object to use atlite operations on it. Based on the provided parameters, atlite first checks whether this cutout already exists on disk and if yes, loads this cutout. If the cutout does not yet exist on disk, then atlite creates an "unprepared" cutout object. This does not yet contain the full data. The process of preparing (loading the data) can then be started with `cutout.prepare()`. Parameters ---------- path : str | path-like NetCDF from which to load or where to store the cutout. module : str or list The dataset(s) which works as a basis for the cutout. Available modules are "era5", "sarah" and "gebco". This is necessary when building a new cutout. If more than one module is given, their order determines how atlite fills up missing features when preparing the cutout with `Cutout.prepare()`. For example `influx_diffuse` is provided by the `sarah` and the `era5` module. Prioritizing sarah and setting module=['sarah', 'era5'] will load `influx_diffuse` from the sarah module and ignoring the era5 'influx_diffuse' data. time : str | slice Time range to include in the cutout, e.g. "2011" or ("2011-01-05", "2011-01-25") This is necessary when building a new cutout. bounds : GeoSeries.bounds | DataFrame, optional The outer bounds of the cutout or as a DataFrame containing (min.long, min.lat, max.long, max.lat). x : slice, optional Outer longitudinal bounds for the cutout (west, east). y : slice, optional Outer latitudinal bounds for the cutout (south, north). dx : float, optional Step size of the x coordinate. The default is 0.25. dy : float, optional Step size of the y coordinate. The default is 0.25. dt : str, optional Frequency of the time coordinate. The default is 'h'. Valid are all pandas offset aliases. chunks : dict Chunks when opening netcdf files. For cutout preparation recommand to chunk only along the time dimension. Defaults to {'time': 20} data : xr.Dataset User provided cutout data. Save the cutout using `Cutout.to_file()` afterwards. Other Parameters ---------------- sanitize : bool, default True Whether to sanitize the data when preparing the cutout. Takes effect for 'era5' data loading. sarah_dir : str, Path Directory of on-disk sarah data. This must be given when using the sarah module. sarah_interpolate : bool, default True Whether to interpolate NaN's in the SARAH data. This takes effect for sarah data which has missing data for areas where dawn and nightfall happens (ca. 30 min gap). gebco_path: str Path to find the gebco netcdf file. Only necessary when including the gebco module. parallel : bool, default False Whether to open dataset in parallel mode. Take effect for all xr.open_mfdataset usages. """ name = cutoutparams.get("name", None) cutout_dir = cutoutparams.get("cutout_dir", None) if cutout_dir or name or Path(path).is_dir(): raise ValueError( "Old style format not supported. You can migrate the old " "cutout directory using the function " "`atlite.utils.migrate_from_cutout_directory()`. The argument " "`cutout_dir` and `name` have been deprecated in favour of `path`.") path = Path(path).with_suffix(".nc") chunks = cutoutparams.pop('chunks', {'time': 100}) storable_chunks = {f'chunksize_{k}': v for k, v in (chunks or {}).items()} # Backward compatibility for xs, ys, months and years if {'xs', 'ys'}.intersection(cutoutparams): warn( "The arguments `xs` and `ys` have been deprecated in favour of " "`x` and `y`", DeprecationWarning) if 'xs' in cutoutparams: cutoutparams['x'] = cutoutparams.pop('xs') if 'ys' in cutoutparams: cutoutparams['y'] = cutoutparams.pop('ys') if {'years', 'months'}.intersection(cutoutparams): warn("The arguments `years` and `months` have been deprecated in " "favour of `time`", DeprecationWarning) assert 'years' in cutoutparams months = cutoutparams.pop("months", slice(1, 12)) years = cutoutparams.pop("years") cutoutparams["time"] = slice(f"{years.start}-{months.start}", f"{years.stop}-{months.stop}") # Three cases. First, cutout exists -> take the data. # Second, data is given -> take it. Third, else -> build a new cutout if path.is_file(): data = xr.open_dataset(str(path), chunks=chunks) data.attrs.update(storable_chunks) if cutoutparams: warn(f'Arguments {", ".join(cutoutparams)} are ignored, since ' 'cutout is already built.') elif 'data' in cutoutparams: data = cutoutparams.pop('data') else: logger.info(f"Building new cutout {path}") if 'bounds' in cutoutparams: x1, y1, x2, y2 = cutoutparams.pop('bounds') cutoutparams.update(x=slice(x1, x2), y=slice(y1, y2)) try: x = cutoutparams.pop('x') y = cutoutparams.pop('y') time = cutoutparams.pop('time') module = cutoutparams.pop('module') except KeyError as exc: raise TypeError("Arguments 'time' and 'module' must be " "specified. Spatial bounds must either be " "passed via argument 'bounds' or 'x' and 'y'.") from exc # TODO: check for dx, dy, x, y fine with module requirements coords = get_coords(x, y, time, **cutoutparams) attrs = {'module': module, 'prepared_features': [], **storable_chunks, **cutoutparams} data = xr.Dataset(coords=coords, attrs=attrs) # Check compatibility of CRS modules = atleast_1d(data.attrs.get('module')) crs = set(CRS(datamodules[m].crs) for m in modules) assert len(crs) == 1, f'CRS of {module} not compatible' self.path = path self.data = data @property def name(self): return self.path.stem @property def module(self): return self.data.attrs.get('module') @property def crs(self): return CRS(datamodules[atleast_1d(self.module)[0]].crs) @property def available_features(self): return available_features(self.module) @property def chunks(self): chunks = {k.lstrip('chunksize_'): v for k, v in self.data.attrs.items() if k.startswith('chunksize_')} return None if chunks == {} else chunks @property def coords(self): return self.data.coords @property def meta(self): warn("The `meta` attribute is deprecated in favour of direct " "access to `data`", DeprecationWarning) return xr.Dataset(self.coords, attrs=self.data.attrs) @property def shape(self): return len(self.coords["y"]), len(self.coords["x"]) @property def extent(self): """Total extent of the area covered by the cutout (x, X, y, Y).""" xs, ys = self.coords['x'].values, self.coords['y'].values dx , dy = self.dx, self.dy return np.array([xs[0]-dx/2, xs[-1]+dx/2, ys[0]-dy/2, ys[-1]+dy/2]) @property def bounds(self): """Total bounds of the area covered by the cutout (x, y, X, Y).""" return self.extent[[0,2,1,3]] @property def transform(self): """Get the affine transform of the cutout. """ return rio.Affine(self.dx, 0, self.coords['x'].values[0] - self.dx/2, 0, self.dy, self.coords['y'].values[0] - self.dy/2) @property def transform_r(self): """Get the affine transform of the cutout with reverse y-order.""" return rio.Affine(self.dx, 0, self.coords['x'].values[0] - self.dx/2, 0, -self.dy, self.coords['y'].values[-1] + self.dy/2) @property def dx(self): x = self.coords['x'] return round((x[-1] - x[0]).item() / (x.size - 1), 8) @property def dy(self): y = self.coords['y'] return round((y[-1] - y[0]).item() / (y.size - 1), 8) @property def dt(self): return pd.infer_freq(self.coords['time'].to_index()) @property def prepared(self): return (self.prepared_features.sort_index() .equals(self.available_features.sort_index())) @property def prepared_features(self): index = [(self.data[v].attrs['module'], self.data[v].attrs['feature']) for v in self.data] index = pd.MultiIndex.from_tuples(index, names=['module', 'feature']) return pd.Series(list(self.data), index, dtype=object) def grid_coordinates(self): warn("The function `grid_coordinates` has been deprecated in favour of " "`grid`", DeprecationWarning) logger.warning("The order of elements returned by `grid_coordinates` changed. " "Check the output of your workflow for correctness.") return self.grid[['x', 'y']].values def grid_cells(self): warn("The function `grid_cells` has been deprecated in favour of `grid`", DeprecationWarning) logger.warning("The order of elements in `grid_cells` changed. " "Check the output of your workflow for correctness.") return self.grid.geometry.to_list() @CachedAttribute def grid(self): xs, ys = np.meshgrid(self.coords["x"], self.coords["y"]) coords = np.asarray((np.ravel(xs), np.ravel(ys))).T span = (coords[self.shape[1] + 1] - coords[0]) / 2 cells = [box(*c) for c in np.hstack((coords - span, coords + span))] return gpd.GeoDataFrame({'x': coords[:, 0], 'y': coords[:, 1], 'geometry': cells,}, crs=self.crs) def sel(self, path=None, bounds=None, buffer=0, **kwargs): ''' Select parts of the cutout. Parameters ---------- path : str | path-like File where to store the sub-cutout. Defaults to a temporary file. bounds : GeoSeries.bounds | DataFrame, optional The outer bounds of the cutout or as a DataFrame containing (min.long, min.lat, max.long, max.lat). buffer : float, optional Buffer around the bounds. The default is 0. **kwargs : Passed to `xr.Dataset.sel` for data selection. Returns ------- selected : Cutout Selected cutout. ''' if path is None: path = mktemp(prefix=f"{self.path.stem}-", suffix=self.path.suffix, dir=self.path.parent) if bounds is not None: if buffer > 0: bounds = box(*bounds).buffer(buffer).bounds x1, y1, x2, y2 = bounds kwargs.update(x=slice(x1, x2), y=slice(y1, y2)) data = self.data.sel(**kwargs) return Cutout(path, data=data) def merge(self, other, path=None, **kwargs): ''' Merge two cutouts into a single cutout. Parameters ---------- other : atlite.Cutout Other cutout to merge. path : str | path-like File where to store the merged cutout. Defaults to a temporary file. **kwargs Keyword arguments passed to `xarray.merge()`. Returns ------- merged : Cutout Merged cutout. ''' assert isinstance(other, Cutout) if path is None: path = mktemp(prefix=f"{self.path.stem}-", suffix=self.path.suffix, dir=self.path.parent) attrs = {**self.data.attrs, **other.data.attrs} attrs['module'] = list(set(append(*atleast_1d(self.module, other.module)))) features = self.prepared_features.index.unique('feature') otherfeatures = other.prepared_features.index.unique('feature') attrs['prepared_features'] = list(features.union(otherfeatures)) data = self.data.merge(other.data, **kwargs).assign_attrs(**attrs) return Cutout(path, data=data) def to_file(self, fn=None): ''' Save cutout to a netcdf file. Parameters ---------- fn : str | path-like File name where to store the cutout, defaults to `cutout.path`. ''' if fn is None: fn = self.path self.data.to_netcdf(fn) def __repr__(self): start = np.datetime_as_string(self.coords['time'].values[0], unit='D') end = np.datetime_as_string(self.coords['time'].values[-1], unit='D') return ('<Cutout "{}">\n' ' x = {:.2f} ⟷ {:.2f}, dx = {:.2f}\n' ' y = {:.2f} ⟷ {:.2f}, dy = {:.2f}\n' ' time = {} ⟷ {}, dt = {}\n' ' module = {}\n' ' prepared_features = {}' .format(self.name, self.coords['x'].values[0], self.coords['x'].values[-1], self.dx, self.coords['y'].values[0], self.coords['y'].values[-1], self.dy, start, end, self.dt, self.module, list(self.prepared_features.index.unique('feature')))) def indicatormatrix(self, shapes, shapes_crs=4326): """ Compute the indicatormatrix. The indicatormatrix I[i,j] is a sparse representation of the ratio of the area in orig[j] lying in dest[i], where orig and dest are collections of polygons, i.e. A value of I[i,j] = 1 indicates that the shape orig[j] is fully contained in shape dest[j]. Note that the polygons must be in the same crs. Parameters --------- shapes : Collection of shapely polygons Returns ------- I : sp.sparse.lil_matrix Indicatormatrix """ return compute_indicatormatrix(self.grid, shapes, self.crs, shapes_crs) def uniform_layout(self): """Get a uniform capacity layout for all grid cells.""" return xr.DataArray(1, [self.coords['y'], self.coords['x']]) def layout_from_capacity_list(self, data, col='Capacity'): """ Get a capacity layout aligned to the cutout based on a capacity list. Parameters ---------- data : pandas.DataFrame Capacity list with columns 'x', 'y' and col. Each capacity entry is added to the grid cell intersecting with the coordinate (x,y). col : str, optional Name of the column with capacity values. The default is 'Capacity'. Returns ------- xr.DataArray Capacity layout with dimensions 'x' and 'y' indicating the total capacity placed within one grid cell. Example ------- >>> import atlite >>> import powerplantmatching as pm >>> data = pm.data.OPSD_VRE_country('DE') >>> data = (data.query('Fueltype == "Solar"') .rename(columns={'lon':'x', 'lat':'y'})) >>> cutout = atlite.Cutout('Germany', x = slice(-5, 15), y = slice(40, 55), time='2013-06-01', module='era5') >>> cutout.prepare(features=['influx', 'temperature']) >>> layout = cutout.layout_from_capacity_list(data) >>> pv = cutout.pv('CdTe', 'latitude_optimal', layout=layout) >>> pv.plot() """ with dask.config.set(**{'array.slicing.split_large_chunks': False}): nearest = (self.uniform_layout().chunk() .sel({'x': data.x.values, 'y': data.y.values}, 'nearest')) data = (data.assign(x=nearest.x.data, y=nearest.y.data) .groupby(['y', 'x'])[col].sum()) return data.to_xarray().reindex_like(self.data).fillna(0) availabilitymatrix = compute_availabilitymatrix # Preparation functions prepare = cutout_prepare # Conversion and aggregation functions convert_and_aggregate = convert_and_aggregate heat_demand = heat_demand temperature = temperature soil_temperature = soil_temperature solar_thermal = solar_thermal wind = wind pv = pv runoff = runoff hydro = hydro

FRESNA/atlite

atlite/cutout.py

Python

gpl-3.0

18,723

[ "NetCDF" ]

fa0ce0dd611a34f2b050fc135f65e2aed2ba29d12100772c6d8eef2f9a9df09c

__RCSID__ = "$Id$" import socket import select import time import os from DIRAC.Core.DISET.private.Transports.BaseTransport import BaseTransport from DIRAC.FrameworkSystem.Client.Logger import gLogger from DIRAC.Core.Utilities.ReturnValues import S_ERROR, S_OK class PlainTransport(BaseTransport): def initAsClient(self): timeout = None if 'timeout' in self.extraArgsDict: timeout = self.extraArgsDict['timeout'] try: self.oSocket = socket.create_connection(self.stServerAddress, timeout) except socket.error as e: if e.args[0] != 115: return S_ERROR("Can't connect: %s" % str(e)) #Connect in progress oL = select.select([], [self.oSocket], [], self.extraArgsDict['timeout'])[1] if len(oL) == 0: self.oSocket.close() return S_ERROR("Connection timeout") errno = self.oSocket.getsockopt(socket.SOL_SOCKET, socket.SO_ERROR) if errno != 0: return S_ERROR("Can't connect: %s" % str((errno, os.strerror(errno)))) self.remoteAddress = self.oSocket.getpeername() return S_OK(self.oSocket) def initAsServer(self): if not self.serverMode(): raise RuntimeError("Must be initialized as server mode") try: self.oSocket = socket.socket(socket.AF_INET6, socket.SOCK_STREAM) except socket.error: # IPv6 is probably disabled on this node, try IPv4 only instead self.oSocket = socket.socket(socket.AF_INET, socket.SOCK_STREAM) if self.bAllowReuseAddress: self.oSocket.setsockopt(socket.SOL_SOCKET, socket.SO_REUSEADDR, 1) self.oSocket.bind(self.stServerAddress) self.oSocket.listen(self.iListenQueueSize) return S_OK(self.oSocket) def close(self): gLogger.debug("Closing socket") try: self.oSocket.shutdown(socket.SHUT_RDWR) except BaseException: pass self.oSocket.close() def setClientSocket(self, oSocket): if self.serverMode(): raise RuntimeError("Mustbe initialized as client mode") self.oSocket = oSocket if 'timeout' in self.extraArgsDict: self.oSocket.settimeout(self.extraArgsDict['timeout']) self.remoteAddress = self.oSocket.getpeername() def acceptConnection(self): # HACK: Was = PlainTransport( self ) oClientTransport = PlainTransport(self.stServerAddress) oClientSocket, stClientAddress = self.oSocket.accept() oClientTransport.setClientSocket(oClientSocket) return S_OK(oClientTransport) def _read(self, bufSize=4096, skipReadyCheck=False): start = time.time() timeout = False if 'timeout' in self.extraArgsDict: timeout = self.extraArgsDict['timeout'] while True: if timeout: if time.time() - start > timeout: return S_ERROR("Socket read timeout exceeded") try: data = self.oSocket.recv(bufSize) return S_OK(data) except socket.error as e: if e[0] == 11: time.sleep(0.001) else: return S_ERROR("Exception while reading from peer: %s" % str(e)) except Exception as e: return S_ERROR("Exception while reading from peer: %s" % str(e)) def _write(self, buf): sentBytes = 0 timeout = False if 'timeout' in self.extraArgsDict: timeout = self.extraArgsDict['timeout'] if timeout: start = time.time() while sentBytes < len(buf): try: if timeout: if time.time() - start > timeout: return S_ERROR("Socket write timeout exceeded") sent = self.oSocket.send(buf[sentBytes:]) if sent == 0: return S_ERROR("Connection closed by peer") if sent > 0: sentBytes += sent except socket.error as e: if e[0] == 11: time.sleep(0.001) else: return S_ERROR("Exception while sending to peer: %s" % str(e)) except Exception as e: return S_ERROR("Error while sending: %s" % str(e)) return S_OK(sentBytes) def checkSanity(*args, **kwargs): return S_OK({}) def delegate(delegationRequest, kwargs): """ Check delegate! """ return S_OK()

fstagni/DIRAC

Core/DISET/private/Transports/PlainTransport.py

Python

gpl-3.0

4,076

[ "DIRAC" ]

cfd65e8191edeee8f91b2c7c23251d1293863b536f2ec1f8bda9fe03a9e808df

""" This is the boilerplate default configuration file. Changes and additions to settings should be done in the config module located in the application root rather than this config. """ config = { # webapp2 sessions 'webapp2_extras.sessions' : {'secret_key': 'Force_be_with'}, # webapp2 authentication 'webapp2_extras.auth' : {'user_model': 'boilerplate.models.User', 'cookie_name': 'session_name'}, # jinja2 templates 'webapp2_extras.jinja2' : {'template_path': ['templates','boilerplate/templates', 'admin/templates'], 'environment_args': {'extensions': ['jinja2.ext.i18n']}}, # application name 'app_name' : "reviewringer", # the default language code for the application. # should match whatever language the site uses when i18n is disabled 'app_lang' : 'en', # Locale code = <language>_<territory> (ie 'en_US') # to pick locale codes see http://cldr.unicode.org/index/cldr-spec/picking-the-right-language-code # also see http://www.sil.org/iso639-3/codes.asp # Language codes defined under iso 639-1 http://en.wikipedia.org/wiki/List_of_ISO_639-1_codes # Territory codes defined under iso 3166-1 alpha-2 http://en.wikipedia.org/wiki/ISO_3166-1 # disable i18n if locales array is empty or None 'locales' : ['en_US', 'es_ES', 'it_IT', 'zh_CN', 'id_ID', 'fr_FR', 'de_DE', 'ru_RU', 'pt_BR', 'cs_CZ'], # contact page email settings 'contact_sender' : "PUT_SENDER_EMAIL_HERE", 'contact_recipient' : "PUT_RECIPIENT_EMAIL_HERE", # Password AES Encryption Parameters 'aes_key' : "12_24_32_BYTES_KEY_FOR_PASSWORDS", 'salt' : "_PUT_SALT_HERE_TO_SHA512_PASSWORDS_", # get your own consumer key and consumer secret by registering at https://dev.twitter.com/apps # callback url must be: http://[YOUR DOMAIN]/login/twitter/complete 'twitter_consumer_key' : 'PUT_YOUR_TWITTER_CONSUMER_KEY_HERE', 'twitter_consumer_secret' : 'PUT_YOUR_TWITTER_CONSUMER_SECRET_HERE', #Facebook Login # get your own consumer key and consumer secret by registering at https://developers.facebook.com/apps #Very Important: set the site_url= your domain in the application settings in the facebook app settings page # callback url must be: http://[YOUR DOMAIN]/login/facebook/complete 'fb_api_key' : 'PUT_YOUR_FACEBOOK_PUBLIC_KEY_HERE', 'fb_secret' : 'PUT_YOUR_FACEBOOK_PUBLIC_KEY_HERE', #Linkedin Login #Get you own api key and secret from https://www.linkedin.com/secure/developer 'linkedin_api' : 'PUT_YOUR_LINKEDIN_PUBLIC_KEY_HERE', 'linkedin_secret' : 'PUT_YOUR_LINKEDIN_PUBLIC_KEY_HERE', # Github login # Register apps here: https://github.com/settings/applications/new 'github_server' : 'github.com', 'github_redirect_uri' : 'http://www.example.com/social_login/github/complete', 'github_client_id' : 'PUT_YOUR_GITHUB_CLIENT_ID_HERE', 'github_client_secret' : 'PUT_YOUR_GITHUB_CLIENT_SECRET_HERE', # get your own recaptcha keys by registering at http://www.google.com/recaptcha/ 'captcha_public_key' : "PUT_YOUR_RECAPCHA_PUBLIC_KEY_HERE", 'captcha_private_key' : "PUT_YOUR_RECAPCHA_PRIVATE_KEY_HERE", # Leave blank "google_analytics_domain" if you only want Analytics code 'google_analytics_domain' : "YOUR_PRIMARY_DOMAIN (e.g. google.com)", 'google_analytics_code' : "UA-XXXXX-X", # add status codes and templates used to catch and display errors # if a status code is not listed here it will use the default app engine # stacktrace error page or browser error page 'error_templates' : { 403: 'errors/default_error.html', 404: 'errors/default_error.html', 500: 'errors/default_error.html', }, # Enable Federated login (OpenID and OAuth) # Google App Engine Settings must be set to Authentication Options: Federated Login 'enable_federated_login' : True, # jinja2 base layout template 'base_layout' : 'base.html', # send error emails to developers 'send_mail_developer' : False, # fellas' list 'developers' : ( ('Santa Klauss', 'snowypal@northpole.com'), ), # If true, it will write in datastore a log of every email sent 'log_email' : True, # If true, it will write in datastore a log of every visit 'log_visit' : True, # ----> ADD MORE CONFIGURATION OPTIONS HERE <---- } # end config

LuckDragon82/demo

config/localhost.py

Python

lgpl-3.0

4,151

[ "VisIt" ]

c70d2e63d2557596455290420b4700112f05bf3dca829fcd9fd18f60ba6d5347

# Copyright 2021 Google LLC # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os.path as osp import multiworld.envs.mujoco as mwmj import rlkit.util.hyperparameter as hyp from multiworld.envs.mujoco.cameras import sawyer_door_env_camera_v0 from rlkit.launchers.launcher_util import run_experiment import rlkit.torch.vae.vae_schedules as vae_schedules from rlkit.launchers.skewfit_experiments import \ skewfit_full_experiment from rlkit.torch.vae.conv_vae import imsize48_default_architecture if __name__ == "__main__": variant = dict( algorithm='Skew-Fit-SAC', double_algo=False, online_vae_exploration=False, imsize=48, env_id='SawyerDoorHookResetFreeEnv-v1', init_camera=sawyer_door_env_camera_v0, skewfit_variant=dict( save_video=True, custom_goal_sampler='replay_buffer', online_vae_trainer_kwargs=dict( beta=20, lr=1e-3, ), save_video_period=50, qf_kwargs=dict( hidden_sizes=[400, 300], ), policy_kwargs=dict( hidden_sizes=[400, 300], ), twin_sac_trainer_kwargs=dict( reward_scale=1, discount=0.99, soft_target_tau=1e-3, target_update_period=1, use_automatic_entropy_tuning=True, ), max_path_length=100, algo_kwargs=dict( batch_size=1024, num_epochs=170, num_eval_steps_per_epoch=500, num_expl_steps_per_train_loop=500, num_trains_per_train_loop=1000, min_num_steps_before_training=10000, vae_training_schedule=vae_schedules.custom_schedule, oracle_data=False, vae_save_period=50, parallel_vae_train=False, ), replay_buffer_kwargs=dict( start_skew_epoch=10, max_size=int(100000), fraction_goals_rollout_goals=0.2, fraction_goals_env_goals=0.5, exploration_rewards_type='None', vae_priority_type='vae_prob', priority_function_kwargs=dict( sampling_method='importance_sampling', decoder_distribution='gaussian_identity_variance', num_latents_to_sample=10, ), power=-0.5, relabeling_goal_sampling_mode='custom_goal_sampler', ), exploration_goal_sampling_mode='custom_goal_sampler', evaluation_goal_sampling_mode='presampled', training_mode='train', testing_mode='test', reward_params=dict( type='latent_distance', ), observation_key='latent_observation', desired_goal_key='latent_desired_goal', presampled_goals_path=osp.join( osp.dirname(mwmj.__file__), "goals", "door_goals.npy", ), presample_goals=True, vae_wrapped_env_kwargs=dict( sample_from_true_prior=True, ), ), train_vae_variant=dict( representation_size=16, beta=20, num_epochs=0, dump_skew_debug_plots=False, decoder_activation='gaussian', generate_vae_dataset_kwargs=dict( N=2, test_p=.9, use_cached=True, show=False, oracle_dataset=False, n_random_steps=1, non_presampled_goal_img_is_garbage=True, ), vae_kwargs=dict( decoder_distribution='gaussian_identity_variance', input_channels=3, architecture=imsize48_default_architecture, ), algo_kwargs=dict( lr=1e-3, ), save_period=1, ), ) search_space = { } sweeper = hyp.DeterministicHyperparameterSweeper( search_space, default_parameters=variant, ) n_seeds = 1 mode = 'local' exp_prefix = 'dev-{}'.format( __file__.replace('/', '-').replace('_', '-').split('.')[0] ) for exp_id, variant in enumerate(sweeper.iterate_hyperparameters()): for _ in range(n_seeds): run_experiment( skewfit_full_experiment, exp_prefix=exp_prefix, mode=mode, variant=variant, use_gpu=True, )

google-research/DBAP-algorithm

third_party/rlkit_library/examples/skewfit/sawyer_door.py

Python

apache-2.0

5,220

[ "Gaussian" ]

36815222cc8bc60bb7c582b9f511a6c9a9d150cf860b48da6cca4b61183b7845

import logging import multiprocessing import re import os import tempfile import yaml import sys from collections import OrderedDict import click import urllib # Adapted from: https://github.com/pnnl/atlas/blob/master/atlas/conf.py logging.basicConfig(level=logging.INFO, datefmt="%Y-%m-%d %H:%M", format="[%(asctime)s %(levelname)s] %(message)s") host = "ftp.sra.ebi.ac.uk" project = "PRJEB14409" #project = "PRJNA319605" # http://stackoverflow.com/a/3675423 def replace_last(source_string, replace_what, replace_with): head, _sep, tail = source_string.rpartition(replace_what) if _sep == '': return tail else: return head + replace_with + tail def get_ena(project): from urllib import request samples = "" try: samples = request.urlopen("http://www.ebi.ac.uk/ena/data/warehouse/filereport?accession=%s&result=read_run&fields=fastq_ftp" % project).readlines()[1:] except urllib.error.HTTPError: print("Not a valid ENA project") for sample in samples: for fastq in sample.strip().split(b';'): dirpath = os.path.dirname(fastq).decode("utf-8") filename = os.path.basename(fastq).decode("utf-8") yield (dirpath,"",[filename]) def get_sample_files(path, remote): samples = OrderedDict() seen = set() walker = "" if remote != None: walker = get_ena(remote) else: walker = os.walk(path, followlinks=True) for dir_name, sub_dirs, files in walker: for fname in files: if ".fastq" in fname or ".fq" in fname: sample_id = fname.partition(".fastq")[0] if ".fq" in sample_id: sample_id = fname.partition(".fq")[0].replace("_","-") sample_id = sample_id.replace("_R1", "").replace("_r1", "").replace("_R2", "").replace("_r2", "") sample_id = re.sub("_1$", "", sample_id) sample_id = re.sub("_2$", "", sample_id) sample_id = sample_id.replace("_", "-").replace(" ", "-") fq_path = os.path.join(dir_name, fname) fastq_paths = [fq_path] if fq_path in seen: continue if "_R1" in fname or "_r1" in fname or "_1" in fname: fname = replace_last(fname,"_1.","_2.") r2_path = os.path.join(dir_name, fname.replace("_R1", "_R2").replace("_r1", "_r2")) if not r2_path == fq_path: seen.add(r2_path) fastq_paths.append(r2_path) if "_R2" in fname or "_r2" in fname or "_2" in fname: fname = replace_last(fname,"_2.","_1.") r1_path = os.path.join(dir_name, fname.replace("_R2", "_R1").replace("_r2", "_r1")) if not r1_path == fq_path: seen.add(r1_path) fastq_paths.insert(0, r1_path) if sample_id in samples: logging.warn("Duplicate sample %s was found after renaming; skipping..." % sample_id) continue samples[sample_id] = {'path': fastq_paths } return samples def create_metadata_template(outfile, samples): with open(outfile, "w") as f: print("#SampleID\tAlias", file=f) for sample in samples: print("%s\t%s" % (sample,sample), file=f) @click.command() @click.option('--project', prompt="Give your project a unique name", required=True, help='Give your project a nice name') @click.option('--config', default="config.yaml", show_default=True, help='File to write the configuration to') @click.option('--remote', help='Specify a ENA project to use as remote data (for example PRJEB14409') @click.option('--path', default="../data", show_default=True, help='path to data folder') @click.option('--rename', required=False, help='provide a file for renaming samples') @click.option('--forward_primer', prompt="Which forward primer did you use?", required=True, default="CCTACGGGNGGCWGCAG", help="Which forward primer did you use?") @click.option('--reverse_primer', prompt="Which reverse primer did you use?", required=True, default="GACTACHVGGGTATCTAATCC", help="Which reverse primer did you use?") @click.option('--mergepairs', prompt="Choose wich method to use for stitching paired reads (vsearch, pandaseq)", required=True, default="vsearch", type=click.Choice(['pandaseq', 'vsearch', 'none']), help="Choose wich method to use for stitching paired reads") @click.option('--classification', prompt="Choose wich classification option you want to use (sina, stampa, rdp, blast)", required=True, type=click.Choice(['sina', 'stampa', 'rdp', 'blast']), help="Choose wich classification option you want to use") @click.option('--reference_db', prompt="Choose wich reference database to use (silva, unite)", required=True, type=click.Choice(['silva', 'unite']), help="Choose wich reference database to use") @click.option('--clustering', prompt="Choose wich clustering method you want to use (usearch_smallmem, swarm)", required=True, default="usearch_smallmem", type=click.Choice(['usearch_smallmem', 'swarm']), help="Choose wich clustering method you want to use") def make_config(project,config,path,remote, rename, forward_primer, reverse_primer, mergepairs, classification, reference_db, clustering): """Write the file `config` and complete the sample names and paths for all files in `path`.""" represent_dict_order = lambda self, data: self.represent_mapping('tag:yaml.org,2002:map', data.items()) yaml.add_representer(OrderedDict, represent_dict_order) path = os.path.realpath(path) conf = OrderedDict() samples = get_sample_files(path, remote) if rename: renamed = 0 for line in open(rename): sample, newname = line.split() if sample in samples: newname = newname.replace("_","-") samples[newname] = samples.pop(sample) renamed += 1 create_metadata_template("metadata.txt", samples.keys()) logging.info("Found %d samples under %s" % (len(samples), path if remote == None else "remote project %s " % remote)) if rename: logging.info("Renamed %d samples" % renamed) conf["project"] = project conf["minsize"] = 2 conf["adapters_fasta"] = "/data/ngs/adapters/contaminant_list.txt" conf["pandaseq_overlap"] = "10" conf["pandaseq_quality"] = "25" conf["pandaseq_minlength"] = "100" conf["pandaseq_maxlength"] = "700" conf["quality_control"] = OrderedDict() conf["quality_control"]["barcode"] = OrderedDict() conf["quality_control"]["barcode"]["threshold"] = 5 conf["quality_control"]["barcode"]["length"] = 8 conf["quality_control"]["barcode"]["seperator"] = "#" conf["quality_control"]["trimming"] = OrderedDict() conf["quality_control"]["trimming"]["quality"] = 25 conf["forward_primer"] = forward_primer conf["reverse_primer"] = reverse_primer conf["mergepairs"] = mergepairs conf["vsearch_minmergelen"] = "200" conf["metadata"] = "metadata.txt" if remote != None: conf["remote"] = True else: conf["remote"] = False conf["barcode_in_header"] = False conf["its"] = False conf["its_region"] = "ITS2" conf["clustering"] = clustering conf["classification"] = classification conf["use_full_lineage"] = False conf["rdp_confidence_cutoff"] = 0.80 conf["reference_db"] = reference_db conf["convert_to_casava1.8"] = False conf["data"] = samples with open(config, "w") as f: print(yaml.dump(conf, default_flow_style=False), file=f) logging.info("Configuration file written to %s" % config) if __name__ == "__main__": make_config()

nioo-knaw/hydra

conf.py

Python

mit

7,810

[ "BLAST" ]

21439bdfe8c043ee7defdea4c8918ad8d50dcb1cad23c72f055715701c5a66ea

""" Cost layers. TODO: write more documentation """ __docformat__ = 'restructedtext en' __authors__ = ("Razvan Pascanu " "KyungHyun Cho " "Caglar Gulcehre ") __contact__ = "Razvan Pascanu <r.pascanu@gmail>" import numpy import copy import logging import theano import theano.tensor as TT from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams from groundhog import utils from groundhog.utils import sample_weights, sample_weights_classic,\ init_bias, constant_shape, sample_zeros from .basic import Layer logger = logging.getLogger(__name__) class CostLayer(Layer): """ Base class for all cost layers """ def __init__(self, rng, n_in, n_out, scale, sparsity, rank_n_approx=0, rank_n_activ='lambda x: x', weight_noise=False, init_fn='sample_weights_classic', bias_fn='init_bias', bias_scale=0., sum_over_time=True, additional_inputs=None, grad_scale=1., use_nce=False, # added by Zhaopeng Tu, 2015-11-07 use_coverage_cost=False, name=None): """ :type rng: numpy random generator :param rng: numpy random generator used to sample weights :type n_in: int :param n_in: number of input units :type n_out: int :param n_out: number of output units :type scale: float or list of :param scale: depending on the initialization function, it can be the standard deviation of the Gaussian from which the weights are sampled or the largest singular value. If a single value it will be used for each layer, otherwise it has to have one value for each layer :type sparsity: int or list of :param sparsity: if a single value, it will be used for each layer, otherwise it has to be a list with as many values as layers. If negative, it means the weight matrix is dense. Otherwise it means this many randomly selected input units are connected to an output unit :type rank_n_approx: int :param rank_n_approx: It applies to the first layer only. If positive and larger than 0, the first weight matrix is factorized into two matrices. The first one goes from input to `rank_n_approx` hidden units, the second from `rank_n_approx` to the number of units on the second layer :type rank_n_activ: string or function :param rank_n_activ: Function that is applied on on the intermediary layer formed from factorizing the first weight matrix (Q: do we need this?) :type weight_noise: bool :param weight_noise: If true, the model is used with weight noise (and the right shared variable are constructed, to keep track of the noise) :type init_fn: string or function :param init_fn: function used to initialize the weights of the layer. We recommend using either `sample_weights_classic` or `sample_weights` defined in the utils :type bias_fn: string or function :param bias_fn: function used to initialize the biases. We recommend using `init_bias` defined in the utils :type bias_scale: float :param bias_scale: argument passed to `bias_fn`, depicting the scale of the initial bias :type sum_over_time: bool :param sum_over_time: flag, stating if, when computing the cost, we should take the sum over time, or the mean. If you have variable length sequences, please take the sum over time :type additional_inputs: None or list of ints :param additional_inputs: dimensionality of each additional input :type grad_scale: float or theano scalar :param grad_scale: factor with which the gradients with respect to the parameters of this layer are scaled. It is used for differentiating between the different parameters of a model. :type use_nce: bool :param use_nce: flag, if true, do not use MLE, but NCE-like cost :type name: string :param name: name of the layer (used to name parameters). NB: in this library names are very important because certain parts of the code relies on name to disambiguate between variables, therefore each layer should have a unique name. """ self.grad_scale = grad_scale assert rank_n_approx >= 0, "Please enter a valid rank_n_approx" self.rank_n_approx = rank_n_approx if type(rank_n_activ) is str: rank_n_activ = eval(rank_n_activ) self.rank_n_activ = rank_n_activ super(CostLayer, self).__init__(n_in, n_out, rng, name) self.trng = RandomStreams(self.rng.randint(int(1e6))) self.scale = scale if isinstance(bias_fn, str): self.bias_fn = eval(bias_fn) else: self.bias_fn = bias_fn self.bias_scale = bias_scale self.sum_over_time = sum_over_time self.weight_noise = weight_noise self.sparsity = sparsity if self.sparsity < 0: self.sparsity = n_out if type(init_fn) is str: init_fn = eval(init_fn) self.init_fn = init_fn self.additional_inputs = additional_inputs self.use_nce = use_nce # added by Zhaopeng Tu, 2015-11-07 self.use_coverage_cost = use_coverage_cost self._init_params() def _init_params(self): """ Initialize the parameters of the layer, either by using sparse initialization or small isotropic noise. """ # added by Zhaopeng Tu, 2015-11-29 if self.use_coverage_cost: self.CC = theano.shared(numpy.cast[theano.config.floatX](1.0), name='CC_%s' % self.name) self.params += [self.CC] if self.rank_n_approx: W_em1 = self.init_fn(self.n_in, self.rank_n_approx, self.sparsity, self.scale, self.rng) W_em2 = self.init_fn(self.rank_n_approx, self.n_out, self.sparsity, self.scale, self.rng) self.W_em1 = theano.shared(W_em1, name='W1_%s' % self.name) self.W_em2 = theano.shared(W_em2, name='W2_%s' % self.name) self.b_em = theano.shared( self.bias_fn(self.n_out, self.bias_scale, self.rng), name='b_%s' % self.name) self.params += [self.W_em1, self.W_em2, self.b_em] if self.weight_noise: self.nW_em1 = theano.shared(W_em1*0., name='noise_W1_%s' % self.name) self.nW_em2 = theano.shared(W_em*0., name='noise_W2_%s' % self.name) self.nb_em = theano.shared(b_em*0., name='noise_b_%s' % self.name) self.noise_params = [self.nW_em1, self.nW_em2, self.nb_em] self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] else: W_em = self.init_fn(self.n_in, self.n_out, self.sparsity, self.scale, self.rng) self.W_em = theano.shared(W_em, name='W_%s' % self.name) self.b_em = theano.shared( self.bias_fn(self.n_out, self.bias_scale, self.rng), name='b_%s' % self.name) self.params += [self.W_em, self.b_em] if self.weight_noise: self.nW_em = theano.shared(W_em*0., name='noise_W_%s' % self.name) self.nb_em = theano.shared( numpy.zeros((self.n_out,), dtype=theano.config.floatX), name='noise_b_%s' % self.name) self.noise_params = [self.nW_em, self.nb_em] self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] self.additional_weights = [] self.noise_additional_weights = [] if self.additional_inputs: for pos, size in enumerate(self.additional_inputs): W_add = self.init_fn(size, self.n_out, self.sparsity, self.scale, self.rng) self.additional_weights += [theano.shared(W_add, name='W_add%d_%s'%(pos, self.name))] if self.weight_noise: self.noise_additional_weights += [ theano.shared(W_add*0., name='noise_W_add%d_%s'%(pos, self.name))] self.params = self.params + self.additional_weights self.noise_params += self.noise_additional_weights self.noise_params_shape_fn += [ constant_shape(x.get_value().shape) for x in self.noise_additional_weights] self.params_grad_scale = [self.grad_scale for x in self.params] def compute_sample(self, state_below, temp=1, use_noise=False): """ Constructs the theano expression that samples from the output layer. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model """ raise NotImplemented def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=None, use_noise=True, additional_inputs=None, no_noise_bias=False): """ Computes the expression of the cost of the model (given the type of layer used). :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type target: tensor or layer :param target: The theano expression (or groundhog layer) representing the target (used to evaluate the prediction of the output layer) :type mask: None or mask or layer :param mask: Mask, depicting which of the predictions should be ignored (e.g. due to them resulting from padding a sequence with 0s) :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type reg: None or layer or theano scalar expression :param reg: additional regularization term that should be added to the cost :type scale: float or None or theano scalar :param scale: scaling factor with which the cost is multiplied :type sum_over_time: bool or None :param sum_over_time: this flag overwrites the value given to this property in the constructor of the class :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type additional_inputs: list theano variable or layers :param additional_inputs: list of theano variables or layers representing the additional inputs :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ raise NotImplemented def get_grads(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, additional_gradients=None, sum_over_time=None, use_noise=True, additional_inputs=None, # added by Zhaopeng Tu, 2015-11-07 coverages=None, c_mask=None, no_noise_bias=False): """ Computes the expression of the gradients of the cost with respect to all parameters of the model. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type target: tensor or layer :param target: The theano expression (or groundhog layer) representing the target (used to evaluate the prediction of the output layer) :type mask: None or mask or layer :param mask: Mask, depicting which of the predictions should be ignored (e.g. due to them resulting from padding a sequence with 0s) :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type reg: None or layer or theano scalar expression :param reg: additional regularization term that should be added to the cost :type scale: float or None or theano scalar :param scale: scaling factor with which the cost is multiplied :type additional_gradients: list of tuples of the form (param, gradient) :param additional_gradiens: A list of tuples. Each tuple has as its first element the parameter, and as second element a gradient expression that should be added to the gradient resulting from the cost. Not all parameters need to have an additional gradient. :type sum_over_time: bool or None :param sum_over_time: this flag overwrites the value given to this property in the constructor of the class :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ cost = self.get_cost(state_below, target, mask=mask, reg=reg, scale=scale, sum_over_time=sum_over_time, use_noise=use_noise, additional_inputs=additional_inputs, # added by Zhaopeng Tu, 2015-11-29 coverages=coverages, c_mask=c_mask, no_noise_bias=no_noise_bias) logger.debug("Get grads") grads = TT.grad(cost.mean(), self.params) logger.debug("Got grads") if additional_gradients: for p, gp in additional_gradients: if p in self.params: grads[self.params.index(p)] += gp if self.additional_gradients: for new_grads, to_replace, properties in self.additional_gradients: gparams, params = new_grads prop_expr = [x[1] for x in properties] replace = [(x[0], TT.grad(cost, x[1])) for x in to_replace] rval = theano.clone(gparams + prop_expr, replace=replace) gparams = rval[:len(gparams)] prop_expr = rval[len(gparams):] self.properties += [(x[0], y) for x, y in zip(properties, prop_expr)] for gp, p in zip(gparams, params): grads[self.params.index(p)] += gp self.cost = cost self.grads = grads return cost, grads def _get_samples(self, model, length=30, temp=1, *inps): """ Sample a sequence from the model `model` whose output layer is given by `self`. :type model: groundhog model class :param model: model that has `self` as its output layer :type length: int :param length: length of the sequence to sample :type temp: float :param temp: temperature to use during sampling """ raise NotImplemented class LinearLayer(CostLayer): """ Linear output layer. """ def _init_params(self): """ Initialize the parameters of the layer, either by using sparse initialization or small isotropic noise. """ if self.rank_n_approx: W_em1 = self.init_fn(self.nin, self.rank_n_approx, self.sparsity, self.scale, self.rng) W_em2 = self.init_fn(self.rank_n_approx, self.nout, self.sparsity, self.scale, self.rng) self.W_em1 = theano.shared(W_em1, name='W1_%s'%self.name) self.W_em2 = theano.shared(W_em2, name='W2_%s'%self.name) self.b_em = theano.shared( numpy.zeros((self.nout,), dtype=theano.config.floatX), name='b_%s'%self.name) self.params += [self.W_em1, self.W_em2, self.b_em] self.myparams = []#[self.W_em1, self.W_em2, self.b_em] if self.weight_noise: self.nW_em1 = theano.shared(W_em1*0., name='noise_W1_%s'%self.name) self.nW_em2 = theano.shared(W_em*0., name='noise_W2_%s'%self.name) self.nb_em = theano.shared(b_em*0., name='noise_b_%s'%self.name) self.noise_params = [self.nW_em1, self.nW_em2, self.nb_em] self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] else: W_em = self.init_fn(self.nin, self.nout, self.sparsity, self.scale, self.rng) self.W_em = theano.shared(W_em, name='W_%s'%self.name) self.b_em = theano.shared( numpy.zeros((self.nout,), dtype=theano.config.floatX), name='b_%s'%self.name) self.add_wghs = [] self.n_add_wghs = [] if self.additional_inputs: for pos, sz in enumerate(self.additional_inputs): W_add = self.init_fn(sz, self.nout, self.sparsity, self.scale, self.rng) self.add_wghs += [theano.shared(W_add, name='W_add%d_%s'%(pos, self.name))] if self.weight_noise: self.n_add_wghs += [theano.shared(W_add*0., name='noise_W_add%d_%s'%(pos, self.name))] self.params += [self.W_em, self.b_em] + self.add_wghs self.myparams = []#[self.W_em, self.b_em] + self.add_wghs if self.weight_noise: self.nW_em = theano.shared(W_em*0., name='noise_W_%s'%self.name) self.nb_em = theano.shared(numpy.zeros((self.nout,), dtype=theano.config.floatX), name='noise_b_%s'%self.name) self.noise_params = [self.nW_em, self.nb_em] + self.n_add_wghs self.noise_params_shape_fn = [ constant_shape(x.get_value().shape) for x in self.noise_params] def _check_dtype(self, matrix, inp): if 'int' in inp.dtype and inp.ndim==2: return matrix[inp.flatten()] elif 'int' in inp.dtype: return matrix[inp] elif 'float' in inp.dtype and inp.ndim == 3: shape0 = inp.shape[0] shape1 = inp.shape[1] shape2 = inp.shape[2] return TT.dot(inp.reshape((shape0*shape1, shape2)), matrix) else: return TT.dot(inp, matrix) def fprop(self, state_below, temp = numpy.float32(1), use_noise=True, additional_inputs = None): """ Constructs the computational graph of this layer. """ if self.rank_n_approx: if use_noise and self.noise_params: emb_val = self._check_dtype(self.W_em1+self.nW_em1, state_below) emb_val = TT.dot(self.W_em2 + self.nW_em2, emb_val) else: emb_val = self._check_dtype(self.W_em1, state_below) emb_val = TT.dot(self.W_em2, emb_val) else: if use_noise and self.noise_params: emb_val = self._check_dtype(self.W_em + self.nW_em, state_below) else: emb_val = self._check_dtype(self.W_em, state_below) if additional_inputs: for st, wgs in zip(additional_inputs, self.add_wghs): emb_val += self._check_dtype(wgs, st) if use_noise and self.noise_params: emb_val = (emb_val + self.b_em+ self.nb_em) else: emb_val = (emb_val + self.b_em) self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def get_cost(self, state_below, target=None, mask = None, temp=1, reg = None, scale=None, sum_over_time=True, use_noise=True, additional_inputs=None): """ This function computes the cost of this layer. :param state_below: theano variable representing the input to the softmax layer :param target: theano variable representing the target for this layer :return: mean cross entropy """ class_probs = self.fprop(state_below, temp = temp, use_noise=use_noise, additional_inputs=additional_inputs) pvals = class_probs assert target, 'Computing the cost requires a target' if target.ndim == 3: target = target.reshape((target.shape[0]*target.shape[1], target.shape[2])) assert 'float' in target.dtype cost = (class_probs - target)**2 if mask: mask = mask.flatten() cost = cost * TT.cast(mask, theano.config.floatX) if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim ==3: sh0 = TT.cast(state_below.shape[0], theano.config.floatX) sh1 = TT.cast(state_below.shape[1], theano.config.floatX) self.cost = cost.sum()/sh1 else: self.cost =cost.sum() else: self.cost = cost.mean() if scale: self.cost = self.cost*scale if reg: self.cost = self.cost + reg self.out = self.cost self.mask = mask self.cost_scale = scale return self.cost def get_grads(self, state_below, target, mask = None, reg = None, scale=None, sum_over_time=True, use_noise=True, additional_inputs=None): """ This function implements both the forward and backwards pass of this layer. The reason we do this in a single function is because for the factorized softmax layer is hard to rely on grad and get an optimized graph. For uniformity I've implemented this method for this layer as well (though one doesn't need to use it) :param state_below: theano variable representing the input to the softmax layer :param target: theano variable representing the target for this layer :return: cost, dC_dstate_below, param_grads, new_properties dC_dstate_below is a computational graph representing the gradient of the cost wrt to state_below param_grads is a list containing the gradients wrt to the different parameters of the layer new_properties is a dictionary containing additional properties of the model; properties are theano expression that are evaluated and reported by the model """ cost = self.get_cost(state_below, target, mask = mask, reg = reg, scale=scale, sum_over_time=sum_over_time, use_noise=use_noise, additional_inputs=additional_inputs) grads = TT.grad(cost, self.params) if self.additional_gradients: for new_grads, to_replace, properties in self.additional_gradients: gparams, params = new_grads prop_expr = [x[1] for x in properties] replace = [(x[0], TT.grad(cost, x[1])) for x in to_replace] rval = theano.clone(gparams + prop_expr, replace=replace) gparams = rval[:len(gparams)] prop_expr = rval[len(gparams):] self.properties += [(x[0], y) for x,y in zip(properties, prop_expr)] for gp, p in zip(gparams, params): grads[self.params.index(p)] += gp self.cost = cost self.grads = grads def Gvs_fn(*args): w = (1 - self.model_output) * self.model_output * state_below.shape[1] Gvs = TT.Lop(self.model_output, self.params, TT.Rop(self.model_output, self.params, args)/w) return Gvs self.Gvs = Gvs_fn return cost, grads class SigmoidLayer(CostLayer): """ Sigmoid output layer. """ def _get_samples(self, model, length=30, temp=1, *inps): """ See parent class. """ if not hasattr(model, 'word_indxs_src'): model.word_indxs_src = model.word_indxs character_level = False if hasattr(model, 'character_level'): character_level = model.character_level if model.del_noise: model.del_noise() if model.maintain_coverage: [values, probs, coverages] = model.sample_fn(length, temp, *inps) else: [values, probs] = model.sample_fn(length, temp, *inps) # Assumes values matrix #print 'Generated sample is:' #print if values.ndim > 1: for d in range(2): print('%d-th sentence' % d) print('Input: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k][d]] == '<eol>': break sen.append(model.word_indxs_src[inps[0][k][d]]) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print(model.word_indxs_src[inps[0][k][d]], end=' ') if model.word_indxs_src[inps[0][k][d]] == '<eol>': break print('') print('Output: ', end=' ') if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k][d]] == '<eol>': break sen.append(model.word_indxs[values[k][d]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k][d]], end=' ') if model.word_indxs[values[k][d]] == '<eol>': break print() print() else: print('Output: ', end=' ') coverage_step = 0 if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k]] == '<eol>': coverage_step = k break sen.append(model.word_indxs[values[k]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k]], end=' ') if model.word_indxs[values[k]] == '<eol>': coverage_step = k break print() if model.maintain_coverage and model.coverage_dim == 1: coverage = coverages[coverage_step] print('Coverage: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k]] == '<eol>': break sen.append('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k])) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k]), end=' ') if model.word_indxs_src[inps[0][k]] == '<eol>': break print('') print() def fprop(self, state_below, temp=numpy.float32(1), use_noise=True, additional_inputs=None, no_noise_bias=False): """ Forward pass through the cost layer. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ if self.rank_n_approx: if use_noise and self.noise_params: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1+self.nW_em1)) emb_val = TT.dot(self.W_em2 + self.nW_em2, emb_val) else: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1)) emb_val = TT.dot(self.W_em2, emb_val) else: if use_noise and self.noise_params: emb_val = utils.dot(state_below, self.W_em + self.nW_em) else: emb_val = utils.dot(state_below, self.W_em) if additional_inputs: if use_noise and self.noise_params: for inp, weight, noise_weight in zip( additional_inputs, self.additional_weights, self.noise_additional_weights): emb_val += utils.dot(inp, (noise_weight + weight)) else: for inp, weight in zip(additional_inputs, self.additional_weights): emb_val += utils.dot(inp, weight) self.preactiv = emb_val if use_noise and self.noise_params and not no_noise_bias: emb_val = TT.nnet.sigmoid(temp * (emb_val + self.b_em + self.nb_em)) else: emb_val = TT.nnet.sigmoid(temp * (emb_val + self.b_em)) self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def compute_sample(self, state_below, temp=1, additional_inputs=None, use_noise=False): """ See parent class. """ class_probs = self.fprop(state_below, temp=temp, additional_inputs=additional_inputs, use_noise=use_noise) pvals = class_probs if pvals.ndim == 1: pvals = pvals.dimshuffle('x', 0) sample = self.trng.binomial(pvals.shape, p=pvals, dtype='int64') if class_probs.ndim == 1: sample = sample[0] self.sample = sample return sample def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=None, use_noise=True, additional_inputs=None, no_noise_bias=False): """ See parent class """ class_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias) pvals = class_probs assert target, 'Computing the cost requires a target' if target.ndim == 3: target = target.reshape((target.shape[0]*target.shape[1], target.shape[2])) assert 'float' in target.dtype # Do we need the safety net of 1e-12 ? cost = -TT.log(TT.maximum(1e-12, class_probs)) * target -\ TT.log(TT.maximum(1e-12, 1 - class_probs)) * (1 - target) if cost.ndim > 1: cost = cost.sum(1) if mask: mask = mask.flatten() cost = cost * TT.cast(mask, theano.config.floatX) if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim == 3: sh0 = TT.cast(state_below.shape[0], theano.config.floatX) sh1 = TT.cast(state_below.shape[1], theano.config.floatX) self.cost = cost.sum()/sh1 else: self.cost = cost.sum() else: self.cost = cost.mean() if scale: self.cost = self.cost*scale if reg: self.cost = self.cost + reg self.out = self.cost self.mask = mask self.cost_scale = scale return self.cost class SoftmaxLayer(CostLayer): """ Softmax output layer. """ def _get_samples(self, model, length=30, temp=1, *inps): """ See parent class """ if not hasattr(model, 'word_indxs_src'): model.word_indxs_src = model.word_indxs character_level = False if hasattr(model, 'character_level'): character_level = model.character_level if model.del_noise: model.del_noise() if model.maintain_coverage: [values, probs, coverages] = model.sample_fn(length, temp, *inps) else: [values, probs] = model.sample_fn(length, temp, *inps) #print 'Generated sample is:' #print if values.ndim > 1: for d in range(2): print('%d-th sentence' % d) print('Input: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k][d]] == '<eol>': break sen.append(model.word_indxs_src[inps[0][k][d]]) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print(model.word_indxs_src[inps[0][k][d]], end=' ') if model.word_indxs_src[inps[0][k][d]] == '<eol>': break print('') print('Output: ', end=' ') if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k][d]] == '<eol>': break sen.append(model.word_indxs[values[k][d]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k][d]], end=' ') if model.word_indxs[values[k][d]] == '<eol>': break print() print() else: print('Output: ', end=' ') coverage_step = 0 if character_level: sen = [] for k in range(values.shape[0]): if model.word_indxs[values[k]] == '<eol>': coverage_step = k break sen.append(model.word_indxs[values[k]]) print("".join(sen), end=' ') else: for k in range(values.shape[0]): print(model.word_indxs[values[k]], end=' ') if model.word_indxs[values[k]] == '<eol>': coverage_step = k break print() if model.maintain_coverage and model.coverage_dim == 1: coverage = coverages[coverage_step] print('Coverage: ', end=' ') if character_level: sen = [] for k in range(inps[0].shape[0]): if model.word_indxs_src[inps[0][k]] == '<eol>': break sen.append('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k])) print("".join(sen), end=' ') else: for k in range(inps[0].shape[0]): print('%s/%.2f'%(model.word_indxs_src[inps[0][k]], coverage[k]), end=' ') if model.word_indxs_src[inps[0][k]] == '<eol>': break print('') print() def fprop(self, state_below, temp=numpy.float32(1), use_noise=True, additional_inputs=None, no_noise_bias=False, target=None, full_softmax=True): """ Forward pass through the cost layer. :type state_below: tensor or layer :param state_below: The theano expression (or groundhog layer) representing the input of the cost layer :type temp: float or tensor scalar :param temp: scalar representing the temperature that should be used when sampling from the output distribution :type use_noise: bool :param use_noise: flag. If true, noise is used when computing the output of the model :type no_noise_bias: bool :param no_noise_bias: flag, stating if weight noise should be added to the bias as well, or only to the weights """ if not full_softmax: assert target != None, 'target must be given' if self.rank_n_approx: if self.weight_noise and use_noise and self.noise_params: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1+self.nW_em1)) nW_em = self.nW_em2 else: emb_val = self.rank_n_activ(utils.dot(state_below, self.W_em1)) W_em = self.W_em2 else: W_em = self.W_em if self.weight_noise: nW_em = self.nW_em emb_val = state_below if full_softmax: if self.weight_noise and use_noise and self.noise_params: emb_val = TT.dot(emb_val, W_em + nW_em) else: emb_val = TT.dot(emb_val, W_em) if additional_inputs: if use_noise and self.noise_params: for inp, weight, noise_weight in zip( additional_inputs, self.additional_weights, self.noise_additional_weights): emb_val += utils.dot(inp, (noise_weight + weight)) else: for inp, weight in zip(additional_inputs, self.additional_weights): emb_val += utils.dot(inp, weight) if self.weight_noise and use_noise and self.noise_params and \ not no_noise_bias: emb_val = temp * (emb_val + self.b_em + self.nb_em) else: emb_val = temp * (emb_val + self.b_em) else: W_em = W_em[:, target] if self.weight_noise: nW_em = nW_em[:, target] W_em += nW_em if emb_val.ndim == 3: emb_val = emb_val.reshape([emb_val.shape[0]*emb_val.shape[1], emb_val.shape[2]]) emb_val = (W_em.T * emb_val).sum(1) + self.b_em[target] if self.weight_noise and use_noise: emb_val += self.nb_em[target] emb_val = temp * emb_val self.preactiv = emb_val if full_softmax: emb_val = utils.softmax(emb_val) else: emb_val = TT.nnet.sigmoid(emb_val) self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def compute_sample(self, state_below, temp=1, use_noise=False, additional_inputs=None): class_probs = self.fprop(state_below, temp=temp, additional_inputs=additional_inputs, use_noise=use_noise) pvals = class_probs if pvals.ndim == 1: pvals = pvals.dimshuffle('x', 0) sample = self.trng.multinomial(pvals=pvals, dtype='int64').argmax(axis=-1) if class_probs.ndim == 1: sample = sample[0] self.sample = sample return sample def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=False, no_noise_bias=False, additional_inputs=None, # added by Zhaopeng Tu, 2015-11-07 coverages=None, c_mask=None, use_noise=True): """ See parent class """ def _grab_probs(class_probs, target): shape0 = class_probs.shape[0] shape1 = class_probs.shape[1] target_ndim = target.ndim target_shape = target.shape if target.ndim > 1: target = target.flatten() assert target.ndim == 1, 'make sure target is a vector of ints' assert 'int' in target.dtype pos = TT.arange(shape0)*shape1 new_targ = target + pos return class_probs.flatten()[new_targ] assert target, 'Computing the cost requires a target' target_shape = target.shape target_ndim = target.ndim if self.use_nce: logger.debug("Using NCE") # positive samples: true targets class_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias, target=target.flatten(), full_softmax=False) # negative samples: a single uniform random sample per training sample nsamples = TT.cast(self.trng.uniform(class_probs.shape[0].reshape([1])) * self.n_out, 'int64') neg_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias, target=nsamples.flatten(), full_softmax=False) cost_target = class_probs cost_nsamples = 1. - neg_probs cost = -TT.log(cost_target) cost = cost - TT.cast(neg_probs.shape[0], 'float32') * TT.log(cost_nsamples) else: class_probs = self.fprop(state_below, temp=temp, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias) cost = -TT.log(_grab_probs(class_probs, target)) self.word_probs = TT.exp(-cost.reshape(target_shape)) # Set all the probs after the end-of-line to one if mask: self.word_probs = self.word_probs * mask + 1 - mask if mask: cost = cost * TT.cast(mask.flatten(), theano.config.floatX) self.cost_per_sample = (cost.reshape(target_shape).sum(axis=0) if target_ndim > 1 else cost) # added by Zhaopeng Tu, 2015-11-27 # use coverage variance for cost # we expect the coverage be in a uniform distribution, to make all the input words are touched equally # coverages is only available in EVALUATION mode if self.use_coverage_cost and coverages: # here we only consider the variance for all non-zero elems (with mask) # coverages consists of coverage at each time step # coverages: (target_length, source_length, batch_size) # we use the variance of final coverage as the bias coverage = coverages[-1][:,:,0] length = c_mask.sum(axis=0) coverage_mean = coverage.sum(axis=0)/length # samples in a batch have different lengths # added by Zhaopeng Tu, 2015-12-02 # for additive or subtractive coverage, the coverage_var would be too large (especially for long sentence) # which means the cost would be negative thus the traning would be stopped # additive: .. iter 27502 cost -988.954 grad_norm 7.71e+03 log2_p_word -1.78e+00 log2_p_expl 4.89e+01 step time 0.713 sec whole time 12.753 h lr 1.00e+00 # therefore, we use standard variance # coverage_var = TT.sqr((coverage-coverage_mean.dimshuffle('x', 0))*c_mask).sum(axis=0)/length coverage_var = TT.sqrt(TT.sqr((coverage-coverage_mean.dimshuffle('x', 0))*c_mask).sum(axis=0)/length) # added by Zhaopeng Tu, 2015-12-02 # we should not add the coverage_var to each word, which will remove the effect of normalizer length # thus the longer the sentence, the heavier effect the coverage_var, which is not suitable # therefore, we add the coverage_var to the final cost (as an overall bias) ''' # expand the coverage_var to match the shape of targets coverage_var = (coverage_var.dimshuffle('x', 0) * mask).flatten() # self.cost = self.cost + coverage_var * self.CC.dimshuffle('x', 0) cost = cost + coverage_var * self.CC ''' if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim == 3: cost = cost.reshape((state_below.shape[0], state_below.shape[1])) self.cost = cost.mean(1).sum() else: self.cost = cost.sum() # added by Zhaopeng Tu, 2015-12-02 if self.use_coverage_cost and coverages: coverage_var = coverage_var.sum() else: self.cost = cost.mean() # added by Zhaopeng Tu, 2015-12-02 if self.use_coverage_cost and coverages: coverage_var = coverage_var.mean() # added by Zhaopeng Tu, 2015-12-02 if self.use_coverage_cost and coverages: self.cost = self.cost + self.CC * coverage_var if scale: self.cost = self.cost*scale if reg: self.cost = self.cost + reg self.mask = mask self.cost_scale = scale return self.cost class HierarchicalSoftmaxLayer(SoftmaxLayer): """ Hierarchical Softmax output layer (2 layer) This is a preliminary implementation of 2-level hierarchical softmax layer (GPU only) """ def __init__(self, rng, n_in, n_out, scale, sparsity, weight_noise=False, init_fn='sample_weights_classic', bias_fn='init_bias', bias_scale=0., sum_over_time=True, grad_scale=1., name=None, **kwargs): assert theano.config.device[:3] == 'gpu', 'Hierarchical softmax is not supported without GPU' from theano.sandbox.cuda.blocksparse import sparse_block_dot_SS self.sparse_block_dot_SS = sparse_block_dot_SS self.grad_scale = grad_scale super(CostLayer, self).__init__(n_in, n_out, rng, name) self.n_words_class = numpy.ceil(numpy.sqrt(self.n_out)).astype('int64') # oSize self.n_class = numpy.ceil(self.n_out/float(self.n_words_class)).astype('int64') # oBlocks logger.debug("n_words_class = %d, n_class = %d"%(self.n_words_class, self.n_class)) self.trng = RandomStreams(self.rng.randint(int(1e6))) if isinstance(bias_fn, str): self.bias_fn = eval(bias_fn) else: self.bias_fn = bias_fn self.bias_scale = bias_scale self.scale = scale self.sum_over_time = sum_over_time self.weight_noise = weight_noise self.sparsity = sparsity if self.sparsity < 0: self.sparsity = n_out if type(init_fn) is str: init_fn = eval(init_fn) self.init_fn = init_fn self._init_params() def _init_params(self): self.iBlocks = 1 # number of blocks in the input (from lower layer) W_em = self.init_fn(self.n_in, self.n_class, self.sparsity, self.scale, self.rng) self.W_em = theano.shared(W_em, name='W_%s' % self.name) self.b_em = theano.shared( self.bias_fn(self.n_class, self.bias_scale, self.rng), name='b_%s' % self.name) U_em = theano.shared(((self.rng.rand(self.iBlocks, self.n_class, self.n_in, self.n_words_class)-0.5)/(self.n_words_class*self.n_in) ).astype(theano.config.floatX), name='U_%s'%self.name) self.U_em = U_em c_em = numpy.zeros((self.n_class, self.n_words_class), dtype='float32') n_words_last_class = self.n_out % self.n_words_class #c_em[-1, n_words_last_class:] = -numpy.inf self.c_em = theano.shared(c_em, name='c_%s' % self.name) self.params = [self.W_em, self.b_em, self.U_em, self.c_em] self.params_grad_scale = [self.grad_scale for x in self.params] def fprop(self, state_below, temp=numpy.float32(1), use_noise=True, additional_inputs=None, no_noise_bias=False, target=None, full_softmax=True, **kwargs): if not full_softmax: assert target != None, 'target must be given' W_em = self.W_em U_em = self.U_em b_em = self.b_em c_em = self.c_em emb_val = state_below bs = emb_val.shape[0] if full_softmax: # compute the probability of every word using scan # for all classes class_vecs = TT.arange(self.n_class) class_val = utils.softmax(TT.dot(emb_val, W_em) + b_em) def _compute_inclass(classid): # compute the word probabilities outputIdx = TT.alloc(classid, bs)[:, None] word_val = utils.softmax(TT.dot(emb_val, U_em[0, classid, :, :])+c_em[classid,:]) word_val = word_val * class_val[:, classid][:,None] return word_val.T rval = theano.scan(_compute_inclass, class_vecs, None, name='compute_inclass') all_word_val = rval[0].reshape([rval[0].shape[0]*rval[0].shape[1], rval[0].shape[2]]).T all_word_val = all_word_val[:,:self.n_out] emb_val = all_word_val else: # compute only the probability of given targets if emb_val.ndim == 3: emb_val = emb_val.reshape([emb_val.shape[0]*emb_val.shape[1], emb_val.shape[2]]) # extract class id's from target indices target = target.flatten() class_vec = target // self.n_words_class # need to be int/int class_idx_vec = target % self.n_words_class outputIdx = class_vec[:, None] # compute the class probabilities class_val = utils.softmax(TT.dot(emb_val, W_em) + b_em) # compute the word probabilities word_val = utils.softmax(self.sparse_block_dot_SS(U_em, emb_val[:, None, :], TT.zeros((bs, 1), dtype='int64'), c_em, outputIdx)[:, 0, :]) class_val = class_val[TT.arange(bs), class_vec] word_val = word_val[TT.arange(bs), class_idx_vec] emb_val = class_val * word_val #self.preactiv = emb_val self.out = emb_val self.state_below = state_below self.model_output = emb_val return emb_val def get_cost(self, state_below, target=None, mask=None, temp=1, reg=None, scale=None, sum_over_time=False, no_noise_bias=False, additional_inputs=None, use_noise=True): """ See parent class """ assert target, 'Computing the cost requires a target' target_shape = target.shape target_ndim = target.ndim target_shape = target.shape if state_below.ndim == 3: shp = state_below.shape state_below = state_below.reshape([shp[0]*shp[1], shp[2]]) class_probs = self.fprop(state_below, temp=temp, target=target, full_softmax=False, use_noise=use_noise, additional_inputs=additional_inputs, no_noise_bias=no_noise_bias) cost = -TT.log(class_probs) self.word_probs = TT.exp(-cost.reshape(target_shape)) # Set all the probs after the end-of-line to one if mask: self.word_probs = self.word_probs * mask + 1 - mask if mask: cost = cost * TT.cast(mask.flatten(), theano.config.floatX) self.cost_per_sample = (cost.reshape(target_shape).sum(axis=0) if target_ndim > 1 else cost) if sum_over_time is None: sum_over_time = self.sum_over_time if sum_over_time: if state_below.ndim == 3: cost = cost.reshape((state_below.shape[0], state_below.shape[1])) self.cost = cost.mean(1).sum() else: self.cost = cost.sum() else: self.cost = cost.mean() if scale: self.cost = self.cost*scale if reg: self.cost = self.cost + reg self.mask = mask self.cost_scale = scale return self.cost

neozhangthe1/coverage_model

build/lib/groundhog/layers/cost_layers.py

Python

bsd-3-clause

59,101

[ "Gaussian" ]

97f8ad9d8431fd85098bdfcfca04910d0432d701d38b38fa2189e2dd2402f4fd

#!/usr/bin/env python3 ##ON APP MACHINE import sys from os import listdir, mkdir from os.path import isdir, dirname, abspath import os import subprocess import weakref from scipy import fftpack import numpy as np ## some global variables, this needs to be fixed at some point default_raw_data_loc = None#"/exp_app2/appexp1/public/raw_data" default_processed_data_loc = None#"/home/brian/processed_files" MetaData_directory = dirname(abspath(__file__)) + '/data' ## change this if antenna_response_model is in a folder different from this module #### constants C = 299792458.0 RTD = 180.0/3.1415926 ##radians to degrees n_air = 1.000293 v_air = C/n_air latlonCS002 = np.array([52.91512249, 6.869837540]) ## lattitude and longitude of CS002 in degrees #### log data to screen and to a file class logger(object): class std_writer(object): def __init__(self, logger): self.logger_ref = weakref.ref(logger) def write(self, msg): logger=self.logger_ref() logger.out_file.write(msg) if logger.to_screen: logger.old_stdout.write(msg) def flush(self): logger=self.logger_ref() logger.out_file.flush() def __init__(self): self.has_stderr = False self.has_stdout = False self.old_stderr = sys.stderr self.old_stdout = sys.stdout self.set("out_log") def set(self, fname, to_screen=True): self.out_file = open(fname, 'w') self.set_to_screen( to_screen ) def __call__(self, *args): for a in args: if self.to_screen: self.old_stdout.write(str(a)) self.old_stdout.write(" ") self.out_file.write(str(a)) self.out_file.write(" ") self.out_file.write("\n") if self.to_screen: self.old_stdout.write("\n") self.out_file.flush() self.old_stdout.flush() def set_to_screen(self, to_screen=True): self.to_screen = to_screen def take_stdout(self): if not self.has_stdout: sys.stdout = self.std_writer(self) self.has_stdout = True def take_stderr(self): if not self.has_stderr: sys.stderr = self.std_writer(self) self.has_stderr = True def restore_stdout(self): if self.has_stdout: sys.stdout = self.old_stdout self.has_stdout = False def restore_stderr(self): if self.has_stderr: sys.stderr = self.old_stderr self.has_stderr = False def flush(self): self.out_file.flush() # def __del__(self): # self.restore_stderr() # self.restore_stdout() #log = logger() def iterate_pairs(list_one, list_two, list_one_avoid=[], list_two_avoid=[]): """returns an iterator that loops over all pairs of the two lists""" for item_one in list_one: if item_one in list_one_avoid: continue for item_two in list_two: if item_two in list_two_avoid: continue yield (item_one, item_two) import re natural_regex_pattern = re.compile('([0-9]+)') def natural_sort( l ): """ Sort the given iterable in the way that humans expect. Usefull for sorting station names.""" convert = lambda text: int(text) if text.isdigit() else text alphanum_key = lambda key: [ convert(c) for c in natural_regex_pattern.split(key) ] return sorted(l, key = alphanum_key) #### some file utils def Fname_data(Fpath): """ takes both pulse data file names and h5 file names and returns UTC_time, station_name, Fpath""" Fname = Fpath.split('/')[-1] data = Fname.split('_') timeID = data[1] station_name = data[2] if len(data[3][1:])==0: file_number = 0 else: file_number = int(data[3][1:]) return timeID, station_name, Fpath, file_number ##note that timeID is a string representing the datetime of a LOFAR trigger. such as: D20130619T094846.507Z ## the timeID is used to uniquely identify triggers def get_timeID(fname): data=fname.split("_") return data[1] def year_from_timeID(timeID): return timeID[1:5] def raw_data_dir(timeID, data_loc=None): """gives path to the raw data folder for a particular timeID, given location of data structure. Defaults to default_raw_data_loc""" if data_loc is None: data_loc = default_raw_data_loc if default_raw_data_loc is None: print("ERROR: 'default_raw_data_loc' in utilities is not set.") quit() path = data_loc + '/' + year_from_timeID(timeID)+"/"+timeID return path def processed_data_dir(timeID, data_loc=None): """gives path to the analysis folders for a particular timeID, given location of data structure. Defaults to default_processed_data_loc makes the directory if it doesn't exist""" if data_loc is None: data_loc = default_processed_data_loc if default_processed_data_loc is None: print("ERROR: 'default_processed_data_loc' in utilities is not set.") quit() path=data_loc + "/" + year_from_timeID(timeID)+"/"+timeID if not isdir(path): mkdir(path) return path ## a python list where the keys are the number of a station and the values are the station name SId_to_Sname = [None]*209 #just to pre-initilize list, so syntax below is possible SId_to_Sname[1] = "CS001" SId_to_Sname[2] = "CS002" SId_to_Sname[3] = "CS003" SId_to_Sname[4] = "CS004" SId_to_Sname[5] = "CS005" SId_to_Sname[6] = "CS006" SId_to_Sname[7] = "CS007" #SId_to_Sname[8] = "CS008" #SId_to_Sname[9] = "CS009" #SId_to_Sname[10] = "CS010" SId_to_Sname[11] = "CS011" #SId_to_Sname[12] = "CS012" SId_to_Sname[13] = "CS013" #SId_to_Sname[14] = "CS014" #SId_to_Sname[15] = "CS015" #SId_to_Sname[16] = "CS016" SId_to_Sname[17] = "CS017" #SId_to_Sname[18] = "CS018" #SId_to_Sname[19] = "CS019" #SId_to_Sname[20] = "CS020" SId_to_Sname[21] = "CS021" #SId_to_Sname[22] = "CS022" #SId_to_Sname[23] = "CS023" SId_to_Sname[24] = "CS024" #SId_to_Sname[25] = "CS025" SId_to_Sname[26] = "CS026" #SId_to_Sname[27] = "CS027" SId_to_Sname[28] = "CS028" #SId_to_Sname[29] = "CS029" SId_to_Sname[30] = "CS030" SId_to_Sname[31] = "CS031" SId_to_Sname[32] = "CS032" SId_to_Sname[101] = "CS101" #SId_to_Sname[102] = "CS102" SId_to_Sname[103] = "CS103" SId_to_Sname[121] = "CS201" SId_to_Sname[141] = "CS301" SId_to_Sname[142] = "CS302" SId_to_Sname[161] = "CS401" SId_to_Sname[181] = "CS501" #SId_to_Sname[104] = "RS104" #SId_to_Sname[105] = "RS105" SId_to_Sname[106] = "RS106" #SId_to_Sname[107] = "RS107" #SId_to_Sname[108] = "RS108" #SId_to_Sname[109] = "RS109" #SId_to_Sname[122] = "RS202" #SId_to_Sname[123] = "RS203" #SId_to_Sname[124] = "RS204" SId_to_Sname[125] = "RS205" #SId_to_Sname[126] = "RS206" #SId_to_Sname[127] = "RS207" SId_to_Sname[128] = "RS208" #SId_to_Sname[129] = "RS209" SId_to_Sname[130] = "RS210" #SId_to_Sname[143] = "RS303" #SId_to_Sname[144] = "RS304" SId_to_Sname[145] = "RS305" SId_to_Sname[146] = "RS306" SId_to_Sname[147] = "RS307" #SId_to_Sname[148] = "RS308" #SId_to_Sname[149] = "RS309" SId_to_Sname[150] = "RS310" SId_to_Sname[166] = "RS406" SId_to_Sname[167] = "RS407" SId_to_Sname[169] = "RS409" SId_to_Sname[183] = "RS503" SId_to_Sname[188] = "RS508" SId_to_Sname[189] = "RS509" SId_to_Sname[201] = "DE601" SId_to_Sname[202] = "DE602" SId_to_Sname[203] = "DE603" SId_to_Sname[204] = "DE604" SId_to_Sname[205] = "DE605" SId_to_Sname[206] = "FR606" SId_to_Sname[207] = "SE607" SId_to_Sname[208] = "UK608" ## this just "inverts" the previous list, discarding unused values Sname_to_SId_dict = {name:ID for ID,name in enumerate(SId_to_Sname) if name is not None} def even_antName_to_odd(even_ant_name): even_num = int(even_ant_name) odd_num = even_num + 1 return str( odd_num ).zfill( 9 ) def antName_is_even(ant_name): return not int(ant_name)%2 def odd_antName_to_even(odd_ant_name): odd_num = int(odd_ant_name) even_num = odd_num - 1 return str( even_num ).zfill( 9 ) def antName_to_even(ant_name): if antName_is_even(ant_name): return ant_name else: odd_antName_to_even( ant_name ) def antName_to_odd(ant_name): if antName_is_even(ant_name): even_antName_to_odd( ant_name ) else: return ant_name #### plotting utilities #### def set_axes_equal(ax): '''Make axes of 3D plot have equal scale so that spheres appear as spheres, cubes as cubes, etc.. This is one possible solution to Matplotlib's ax.set_aspect('equal') and ax.axis('equal') not working for 3D. Input ax: a matplotlib axis, e.g., as output from plt.gca(). ''' x_limits = ax.get_xlim3d() y_limits = ax.get_ylim3d() z_limits = ax.get_zlim3d() x_range = abs(x_limits[1] - x_limits[0]) x_middle = np.mean(x_limits) y_range = abs(y_limits[1] - y_limits[0]) y_middle = np.mean(y_limits) z_range = abs(z_limits[1] - z_limits[0]) z_middle = np.mean(z_limits) # The plot bounding box is a sphere in the sense of the infinity # norm, hence I call half the max range the plot radius. plot_radius = 0.5*max([x_range, y_range, z_range]) ax.set_xlim3d([x_middle - plot_radius, x_middle + plot_radius]) ax.set_ylim3d([y_middle - plot_radius, y_middle + plot_radius]) ax.set_zlim3d([z_middle - plot_radius, z_middle + plot_radius]) ### some math functions? ### def normalize_angle_radians( angle_radians ): """For an angle in radians, return the equivalent angle that is garunteed be between -pi and pi""" while angle_radians > np.pi: angle_radians -= 2.0*np.pi while angle_radians < -np.pi: angle_radians += 2.0*np.pi return angle_radians def BoundingBox_collision(BB1, BB2): """ return true if two N-D bounding boxes collide, False otherwise""" for B1, B2 in zip(BB1,BB2): if (B1[1] < B2[0]) or (B2[1] < B1[0]): return False return True ### some build tools #### def GSL_include(): """return directory for location of GSL headers, useful when combining GSL and cython""" try: gsl_include = subprocess.check_output('gsl-config --cflags', shell=True).decode('utf-8')[2:-1] except subprocess.CalledProcessError: gsl_include = os.getenv('LIB_GSL') if gsl_include is None: # Environmental variable LIB_GSL not set, use hardcoded path. gsl_include = r"c:\Program Files\GnuWin32\include" else: gsl_include += "/include" assert gsl_include != '', "Couldn't find gsl. Make sure it's installed and in the path." return gsl_include def GSL_library_dir(): """return directory for location of GSL binaries, useful when combining GSL and cython""" try: lib_gsl_dir = subprocess.check_output('gsl-config --libs', shell=True).decode('utf-8').split()[0][2:] except subprocess.CalledProcessError: lib_gsl_dir = os.getenv('LIB_GSL') if lib_gsl_dir is None: # Environmental variable LIB_GSL not set, use hardcoded path. lib_gsl_dir = r"c:\Program Files\GnuWin32\lib" else: lib_gsl_dir += "/lib" return lib_gsl_dir

Bhare8972/LOFAR-LIM

LIM_scripts/utilities.py

Python

mit

11,568

[ "Brian" ]

de9aee678156fe3e80ea9ddab17931f7cf83cd3694d606bc560ca66b24286ea8

#!/usr/bin/env python # Script to convert Amber protein hydrogens (created by ambpdb) into Gromacs # names. For some reason, eg. HB2 + HB3 are expected to be HB1 and HB2 in the # Gromacs aminoacids.rtp parameter files. # Requirements: Biopython # Desired PDB file should be the first argument. Output is renamed PDB with # 'GMX_' prepended. import sys from Bio.PDB import PDBIO from Bio.PDB.PDBParser import PDBParser proteins = ['ALA','ARG','ASH','ASP','ASN','CYS','CYX','GLH','GLN','GLU','GLY','HID','HIE','HIP','HIS','ILE','LEU','LYN','LYS','MET','PHE','PRO','SER','THR','TRP','TYR','VAL'] # Argparse this... try: pdbname = sys.argv[1] except IndexError: print "PDB file required as first argument. " sys.exit() try: sys.argv[2] print "Renaming termini (providing any character as a second argument will turn this on)" termini = True except IndexError: termini = False print "Not renaming termini (add a second argument if you want to turn this on)" parser = PDBParser(QUIET=True) # Lack of atom symbols = warnings if verbose structure = parser.get_structure('ambpdb',pdbname) # Convert first and last residues to termini def rename_termini(struct): """Rename termini of chains to be NXXX and CXXX. TAKE CARE - RESULTS IN NON-STANDARD PDB FORMAT (residue names should be 3 characters). Input = Biopython structure object, returns structure object with modified first/last resnames in each chain.""" for chain in struct.get_chains(): first = chain.child_list[0] last = chain.child_list[-1] if first.resname in proteins: first.resname = 'N'+first.resname else: print """The first residue is either already an N-terminus, or doesn't appear to be a natural amino acid. Continuing anyway.""" if last.resname in proteins: last.resname = 'C'+last.resname else: for idx,res in enumerate(chain.child_list,-1): if res.resname in proteins: continue else: last = chain.child_list[idx] # idx starts from -1 print "You seem to have non-protein residues in a chain. Renaming residue %s %s as C-terminus" % (last.resname,last.id[1]) last.resname = 'C'+last.resname return struct def amb2gmx(struct): """Rename Amber atoms to those expected in the Gromacs amber parameter files. Mainly e.g. HB2/HB3 -> HB1/HB2. Cycles over all residues. Input = Biopython structure object, returns structure object with modified atom names""" for residue in struct.get_residues(): if residue.resname in ['GLY','NGLY','CGLY']: residue['HA2'].fullname = ' HA1' residue['HA3'].fullname = ' HA2' elif residue.resname in ['SER','NSER','CSER']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['LEU','NLEU','CLEU']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['ILE','NILE','CILE']: residue['HG12'].fullname = 'HG11' residue['HG13'].fullname = 'HG12' elif residue.resname in ['ASN','NASN','CASN']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['GLN','NGLN','CGLN']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' elif residue.resname in ['ARG','NARG','CARG']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' residue['HD2'].fullname = ' HD1' residue['HD3'].fullname = ' HD2' elif residue.resname in ['HID','NHID','CHID','HIE','NHIE','CHIE','HIP','NHIP','CHIP','HIS','NHIS','CHIS']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['TRP','NTRP','CTRP']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['PHE','NPHE','CPHE']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['TYR','NTYR','CTYR']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['GLU','NGLU','CGLU','GLH','NGLH','CGLH']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' elif residue.resname in ['ASP','NASP','CASP','ASH','NASH','CASH']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['LYS','NLYS','CLYS','LYN','NLYN','CLYN']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' residue['HD2'].fullname = ' HD1' residue['HD3'].fullname = ' HD2' residue['HE2'].fullname = ' HE1' residue['HE3'].fullname = ' HE2' elif residue.resname in ['PRO','NPRO','CPRO']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' residue['HD2'].fullname = ' HD1' residue['HD3'].fullname = ' HD2' elif residue.resname in ['CYS','NCYS','CCYS','CYX','NCYX','CCYX']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' elif residue.resname in ['MET','NMET','CMET']: residue['HB2'].fullname = ' HB1' residue['HB3'].fullname = ' HB2' residue['HG2'].fullname = ' HG1' residue['HG3'].fullname = ' HG2' return struct def write_struct(struct,name): """Writes a corrected PDB file to disk with 'GMX_' prepended""" w = PDBIO() w.set_structure(struct) w.save('GMX_'+name) #### Main below here #### if termini is True: structure = rename_termini(structure) print """If you have separate chains in your PDB (separated by a TER card), make sure they have a chain identifier in column 22, in accordance with the PDB version 3 format. Biopython is expecting this!""" structure = amb2gmx(structure) write_struct(structure,pdbname) print "Done."

rtb1c13/scripts

SAXS_MD/AmbPDB_2_GMX.py

Python

gpl-2.0

6,501

[ "Amber", "Biopython", "Gromacs" ]

ef2ce9d4ecd396bf5562d88bec49c12ec76cbe6a0c9dd41ca5ef1a6ce5a4eb81

""" Test Logger Wrapper """ __RCSID__ = "$Id$" import logging from io import StringIO from DIRAC.FrameworkSystem.private.standardLogging.LoggingRoot import LoggingRoot from DIRAC.FrameworkSystem.private.standardLogging.Logging import Logging gLogger = LoggingRoot() def cleaningLog(log): """ Remove date and space from the log string """ log = log.split("UTC ")[-1] return log def captureBackend(): """ Dirac logger is wrapped by LoggingRoot and represent the root of the DIRAC logging system Modify the output to capture logs of LoggingRoot """ bufferDirac = StringIO() if logging.getLogger("dirac").handlers: logging.getLogger("dirac").handlers[0].stream = bufferDirac return bufferDirac def gLoggerReset(): """ Reinitialize gLogger as only one instance exists It avoids any unexpected behaviour due to multiple different usages """ # Reinitialize the system/component name after other tests # because LoggingRoot is a singleton and can not be reinstancied Logging._componentName = "Framework" # reset gLogger gLogger.setLevel("notice") gLogger.showHeaders(True) gLogger.showThreadIDs(False) gLogger.showContexts(True) gLogger.showTimeStamps(True) # modify the output to capture the log records into a buffer bufferDirac = captureBackend() del logging.getLogger("dirac").handlers[1:] del gLogger._backendsList[1:] # reset log logging.getLogger("dirac").getChild("log").setLevel(logging.NOTSET) log = gLogger.getSubLogger("log") log.showHeaders(True) log.showThreadIDs(False) log.showContexts(True) log.showTimeStamps(True) for option in log._optionsModified: log._optionsModified[option] = False del logging.getLogger("dirac.log").handlers[:] del log._backendsList[:] # reset sublog logging.getLogger("dirac.log").getChild("sublog").setLevel(logging.NOTSET) sublog = log.getSubLogger("sublog") sublog.showHeaders(True) sublog.showThreadIDs(False) sublog.showContexts(True) sublog.showTimeStamps(True) for option in sublog._optionsModified: sublog._optionsModified[option] = False del logging.getLogger("dirac.log.sublog").handlers[:] del sublog._backendsList[:] return (bufferDirac, log, sublog)

ic-hep/DIRAC

src/DIRAC/FrameworkSystem/private/standardLogging/test/TestLogUtilities.py

Python

gpl-3.0

2,343

[ "DIRAC" ]

0c73c24856295f6a80de3e83612c8a746db0d7a3b3ad20b15810cb2f7985bfa5

import unittest from .enum import Enum class TestEnum(unittest.TestCase): def test_string_conversion(self): column = Enum('test_column', 'ENUM', enum_values=['asdf', 'qwerty'], default='qwerty') self.assertEquals("`test_column` ENUM('asdf', 'qwerty') DEFAULT \'qwerty\'", str(column)) self.assertEquals([], column.schema_errors) self.assertEquals([], column.schema_warnings) def test_default_errors(self): column = Enum('test_column', 'ENUM', enum_values=['asdf', 'qwerty'], default='adf') self.assertEquals(["Default value for 'ENUM' column 'test_column' is not in the list of allowed values"], column.schema_errors) self.assertEquals([], Enum('test_column', 'ENUM', enum_values=['asdf', 'qwerty']).schema_errors)

cmancone/mygrations

mygrations/core/definitions/columns/enum_test.py

Python

mit

808

[ "ADF" ]

bc3fb2e51273b0caa965ff6bfee4401902a2ada14a27681259bade9939c00070

#!/usr/bin/env python # # Copyright (C) 2014 Brian Caswell <bmc@lungetech.com> # # Permission is hereby granted, free of charge, to any person obtaining a # copy of this software and associated documentation files (the "Software"), # to deal in the Software without restriction, including without limitation # the rights to use, copy, modify, merge, publish, distribute, sublicense, # and/or sell copies of the Software, and to permit persons to whom the # Software is furnished to do so, subject to the following conditions: # # The above copyright notice and this permission notice shall be included # in all copies or substantial portions of the Software. # # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS # OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF # MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. # IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY # CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, # TORT OR OTHERWISE, ARISING FROM, OUT OF OR IN CONNECTION WITH THE # SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE. # from generator.actions import Actions from random import choice, randint import imp import os import random import string print os.path.realpath(__file__) filename = os.path.sep.join(os.path.realpath(__file__).split(os.path.sep)[:-1] + ['books.py']) books = imp.load_source('books', filename).books def random_alpha(a, b): return ''.join(choice(string.letters) for _ in range(randint(a, b))) def random_string(a, b): chars = string.letters + string.digits return ''.join(choice(chars) for _ in range(randint(a, b))) class Bookworm(Actions): def start(self): self.read(delim='\n', expect='Welcome to the book review server\n') self.state['reviews'] = [] def menu(self): self.read(delim='Selection: ', expect="1. List Available " "Books\n2. Books you have reviewed\n3. Review " "more books\n4. Exit\nSelection: ") def list_books(self): self.write_number(1) expected = ['\nAvailable Books'] for i, book in enumerate(books, 1): expected.append('%d: %s' % (i, book)) self.read(delim='\n\n', expect='\n'.join(expected) + '\n\n') def reviewed(self): self.write_number(2) if 'reviews' not in self.state: self.state['reviews'] = [] expected = ['Book Title: Your rating'] + self.state['reviews'] self.read(delim='\n\n', expect='\n' + '\n'.join(expected) + '\n\n') def write_number(self, digit): trail = '' if self.chance(.01): trail = random_alpha(1, 30) self.write('%d%s\n' % (digit, trail)) def review(self): self.write_number(3) self.read(delim='?: ', expect='\nWhat book would you like to ' 'review (1 - 100)?: ') # 1% of the time, review an invalid book. sometimes with strings, # sometimes with numbers, sometimes both if self.chance(.01): invalid = None while invalid is None: invalid = random_string(1, 30) if re.match('^0*(\d|\d{2}|100)\D', invalid): invalid = None self.write("%s\n" % invalid) self.read(delim='\n', expect='Invalid book\n') else: choice = randint(1, 100) self.write_number(choice) self.read(delim='? ', expect='What rating would you like ' 'to give this book? ') rating = 0 # 1% of the time, send random jiberish as a response if self.chance(.01): self.write(random_alpha(1, 30)) else: rating = randint(0, 0xFFFF) self.write_number(rating) if 'reviews' not in self.state: self.state['reviews'] = [] self.state['reviews'].append("%s: %d" % (books[choice - 1], rating)) def bad_menu(self): if self.chance(.5): self.write_number(randint(6, 30)) else: self.write('%s\n' % random_alpha(1, 98)) self.read(delim='\n', expect='Invalid menu selection\n') def exit(self): self.write_number(4) self.read(delim='\n', expect='k, bye\n') def hidden(self): # This is the vulnerable condition. Do we want to expose this? if 0: self.write_number(5)

f0rki/cb-multios

tools/generate-polls/examples/bookworm/bookworm.py

Python

mit

4,548

[ "Brian" ]

2195f59586e15efd01f33e7f70afe61bafd52618b64cdb1d9c8dafd3fefbe1f3

# This module is free software. You can redistribute it and/or modify it under # the terms of the MIT License, see the file COPYING included with this # distribution. from __future__ import division """ General utils files for general purpose functions """ import re import os #Biopython from Bio import SeqIO import motif_utils def getSeqMotifDict(fimoDict): """ Make a dict between the seq names and list of motifs that occur in it Args: fimoDict: dict between motif names and the seqs it hits Returns: a dict between seq names and a list of motif IDs that hit it """ seqMotifDict = {} tmpCount = 0 for motifId, seqList in fimoDict.items(): for seqName in seqList: if seqName not in seqMotifDict: seqMotifDict[seqName] = [] if motifId not in seqMotifDict[seqName]: seqMotifDict[seqName].append(motifId) return seqMotifDict def makeMotifDictFromPwmFile(pwmFileName): """ read a PWM file that we would like to scan and make a motif dict between motif ID and motif object Args: PWM file in MEME format """ #print 'PP:', pwmFileName #dict between motif IDs and motif objects motifDict = {} motifName = '' motifId = 0 #dicts between motif IDs and motif names with open(pwmFileName, 'rb') as handler: for line in handler: line = line.strip() if not line.strip() or re.search(r'letter', line) or re.search(r'version', line) or re.search(r'ALPHABET',line) or re.search(r'strands', line)\ or re.search(r'A 0.25000', line): continue #print 'l:',line if re.search(r'MOTIF', line): split = line.split() line = '_'.join(split[1:]) motifName = line motifId += 1 motifObj = motif_utils.MyMotif() motifObj.Id = motifId motifObj.regExp = motifName #notice here it is actually the motif name not a reg. expression motifDict[motifName] = motifObj continue #add the PWM lines to the motif motifDict[motifName].pwmLines.append(line) ##check the hash #for motifName in motifDict.iterkeys(): #print motifName #motifObj = motifDict[motifName] #print '\t',motifObj.regExp #for line in motifObj.pwmLines: #print '\t', line return motifDict def processMotifHitFile_1(inFile): """ Process a motif hit/occurrence file and return a universe set (U) and a dict of set of sets The inFile should look like: >motif_name_1 sequence name sequence name >motif_name_2 sequence name sequence name You can check the wiki page about set cover problem to get an idea about Universe (U) set and set S of subsets Args: inFile: name of file of motif hits in the format explained above Returns: motifIdDict: A dict between motif names and motif numbers (IDs) idMotifDict: A dict between seq names and seq numbers (IDs) seqIdDict: A dict between seq numbers (IDs) and seq names idSeqDict: A dict between seq numbers (IDs) and seq names and Uset : universe set of all seq IDs Sdict: dict between motif IDs and the sequence IDs the motif hits """ #a dict between motif names in the file and motif numbers (IDs) motifIdDict = {} #a dict between motif numbers (IDs) and motif names idMotifDict = {} #a dict between seq names and seq numbers (IDs) seqIdDict = {} #a dict between seq numbers and seq names idSeqDict = {} #all numbers/IDs start from 1 inside the dicts/sets motifId = 0 seqId = 0 #Universe set which is the set of all the sequences, the U set Uset = set() #A dict between motif names and the set of seqs that occur in them, the S set Sdict = {} print 'in process motif hit' #start reading the file with open(inFile, 'rb') as handler: for line in handler: line = line.strip() #skip empty spaces if not line.strip(): continue if re.search(r'>', line):#found a motif motifId += 1 motifName = line[1:]#take off the > character if motifName not in motifIdDict: motifIdDict[motifName] = motifId else: print 'There are motif names duplicates. the file should have unique motif names' exit() idMotifDict[motifId] = motifName #initialize the element in the Sdict Sdict[motifId] = set() continue #all the other lines are sequence names, check if the seq name has been checked and inserted or not seqName = line if seqName not in seqIdDict: seqId += 1 seqIdDict[seqName] = seqId idSeqDict[seqId] = seqName tmpSeqId = seqId else: tmpSeqId = seqIdDict[seqName] if tmpSeqId not in Sdict[motifId]: Sdict[motifId].add(tmpSeqId) #add the seqs to the U universe dict if tmpSeqId not in Uset: Uset.add(seqId) #check the U dict #print Uset #check the S dict #for motifId, seqSet in Sdict.items(): #print 'motifId:', motifId, 'set:', seqSet return motifIdDict, idMotifDict, seqIdDict, idSeqDict, Uset, Sdict def processMotifHitFile(foreMotifFile, backMotifFile): """Read the fore and back motif hit files and make motif dict and dict of motifs with their hits The input motf hit file should look like: >motif_name_1 sequence name sequence name >motif_name_2 sequence name sequence name """ motifId = 0 #dict between motif names and motif object motifObjDict = {} #dict between the motif name and list of seqs it occurs in foreHitDict = {} #list of sequences in the foreground file foreSeqList = [] motifName = '' #start reading the foreground file with open(foreMotifFile, 'rb') as handler: for line in handler: line = line.strip() #skip empty spaces if not line.strip(): continue if re.search(r'>', line):#found a motif motifId += 1 motifName = line[1:]#take off the > character #make a motif object motifObj = motif_utils.MyMotif() motifObj.Id = motifId motifObj.regExp = motifName #notice here it is actually the motif name not a reg. expression if motifName not in motifObjDict: motifObjDict[motifName] = motifObj else: print 'motif names should be unique. Exiting' exit() continue #add the seqs to the motif if motifName not in foreHitDict: foreHitDict[motifName] = [] foreHitDict[motifName].append(line) if line not in foreSeqList: foreSeqList.append(line) ##check the motif dict #for motifName in motifObjDict: #print 'mName:', motifName #for motifName in foreHitDict: #print 'mName:', motifName,'seqs:', foreHitDict[motifName] #print 'whole seq list:', foreSeqList #process the background #dict between the motif name and list of seqs it occurs in the background backHitDict = {} #list of sequences in the background file backSeqList = [] #check if there is a background file as well and make data for it backMotifName = '' if backMotifFile != 'none': with open(backMotifFile, 'rb') as handler: for line in handler: line = line.strip() #skip empty spaces if not line.strip(): continue if re.search(r'>', line):#found a motif backMotifName = line[1:]#take off the > character continue #add the seqs to the motif if backMotifName not in backHitDict: backHitDict[backMotifName] = [] backHitDict[backMotifName].append(line) if line not in backSeqList: backSeqList.append(line) #for motifName in backHitDict: # print 'mName:', motifName,'seqs:', backHitDict[motifName] #print 'whole seq list:', backSeqList return motifObjDict, foreHitDict, backHitDict, foreSeqList, backSeqList def writePWMFromMotifs(motifDict, pwmFileName): """Go thru the motif dict og BioPython objects and write them to a file in MEME PWM format Args: motif dictionary between motif IDs and MyMotif objects Returns: name of PWM motif file """ pwmFile = open(pwmFileName, 'wb') pwmFile.write('MEME version 4.4\nALPHABET= ACGT\nstrands: + -\nBackground letter frequencies (from web form):\nA 0.25000 C 0.25000 G 0.25000 T 0.25000\n\n') alphaList = ['A', 'C', 'G', 'T'] #loop thru the motifs for motifId in motifDict.iterkeys(): motifObj = motifDict[motifId].bioMotifObj #get motif length motifLength = len(motifObj) pwmFile.write('\nMOTIF ' + str(motifId) + '\n') pwmFile.write('letter-probability matrix:\n') pwm = motifObj.counts.normalize(pseudocounts=0) for i in range(motifLength): for alpha in alphaList: pwmFile.write(' ' + str(pwm[alpha][i])) pwmFile.write('\n') #close the file pwmFile.close() def writePWMFromMotifsSelected(motifDict, pwmFileName, selectIdList, idMotifDict): """Write the PWMs to a file, only write the IDs chosen in the selectIdList """ pwmFile = open(pwmFileName, 'wb') pwmFile.write('MEME version 4.4\nALPHABET= ACGT\nstrands: + -\nBackground letter frequencies (from web form):\nA 0.25000 C 0.25000 G 0.25000 T 0.25000\n\n') alphaList = ['A', 'C', 'G', 'T'] #loop thru the motifs for motifId in selectIdList: if motifId not in idMotifDict: motifName = motifId else: motifName = idMotifDict[motifId] #print 'motifId:', motifId,motifName motifObj = motifDict[motifName].bioMotifObj #get motif length motifLength = len(motifObj) pwmFile.write('\nMOTIF ' + str(motifName) + '\n') pwmFile.write('letter-probability matrix:\n') pwm = motifObj.counts.normalize(pseudocounts=0) for i in range(motifLength): for alpha in alphaList: pwmFile.write(' ' + str(pwm[alpha][i])) pwmFile.write('\n') #close the file pwmFile.close() def writePWMFromMotifsSelectedScan(motifDict, pwmFileName, selectIdList, idMotifDict, finalSelectMotifList): """Write the PWMs to a file, only write the IDs chosen in the selectIdList This is for the motif PWM scan problem where the PWm is already privided as input """ pwmFile = open(pwmFileName, 'wb') pwmFile.write('MEME version 4.4\nALPHABET= ACGT\nstrands: + -\nBackground letter frequencies (from web form):\nA 0.25000 C 0.25000 G 0.25000 T 0.25000\n\n') for motifId in selectIdList: if motifId not in idMotifDict: motifName = motifId else: motifName = idMotifDict[motifId] if motifName not in finalSelectMotifList: continue motifObj = motifDict[motifName] #motifName = motifObj.regExp pwmFile.write('\nMOTIF ' + motifName + '\n') pwmFile.write('letter-probability matrix:\n') for line in motifObj.pwmLines: pwmFile.write(line+'\n') #close the file pwmFile.close() def writeMotifSeqFile(motifDict, outFileName): """take a dict between motif IDs and seqs it occurs in and write to a file The format is: >motif_name seq_1 seq_2 Args: motifDict: dict between motif IDs/names and a list of sequences the motif occurs in outFileName" name of file to write to """ outFile = open(outFileName, 'wb') for motifId in sorted(motifDict.iterkeys()): seqList = motifDict[motifId] outFile.write('>' + str(motifId) + '\n') for seqName in seqList: outFile.write(seqName + '\n') outFile.close() def writeMotifSeqFileFromMotifDict(motifDict, outFileName): """Take a motif dict beween motif Ids and MyMotif objects and write the seq of each motif to a file use the seq coverage file format >motif_name seq_1 seq_2 Args: motifDIct: dict between motif IDs and MyMotif objects outFileName" name of file to write to """ outFile = open(outFileName, 'wb') for motifId in motifDict.iterkeys(): motifObj = motifDict[motifId] seqList = motifObj.foreSeqList outFile.write('>' + str(motifId) + '\n') for seqName in seqList: outFile.write(seqName + '\n') outFile.close() def findNumSeqs(fastaFile): """Use Biopython to find the number of fasta seqeunces in a fasta file Args: fasta file Returns: number of fasta sequences """ handle = open(fastaFile, "rU") numSeqs = 0 for record in SeqIO.parse(handle, "fasta"): seqId = str(record.id) numSeqs += 1 handle.close() return numSeqs def findSeqList(fastaFile): """ Read the fasta file and return a list of sequence names in the fasta file """ handle = open(fastaFile, "rU") numSeqs = 0 seqList = [] for record in SeqIO.parse(handle, "fasta"): seqId = str(record.id) seqList.append(seqId) numSeqs += 1 handle.close() return seqList def getSeqList(fastaFile): """Use Biopython to return a list of fasta seq names Args: fasta file Returns: list of seqNames """ handle = open(fastaFile, "rU") numSeqs = 0 seqList = [] for record in SeqIO.parse(handle, "fasta"): seqId = str(record.id) seqList.append(seqId) numSeqs += 1 handle.close() return seqList def makeMotifLogo(motifIdList, motifDict, outDirName, pwmFileName, idMotifDict, op, finalSelectMotifList): """Make motif logos for a set of motifs as specified in the motifIdList Add a motif logo ID (logo file name) to each motif object Args: motifIdList: list of motif IDs to make logos for motifDict: a dict between motif ID and a MyMotif object idMotifDict: dict from IDs to motif names op: operation; is it motif disocvery or a cov finalSelectMotifList: list of motif names , final filtered list Return: """ if op == 'disc': writePWMFromMotifsSelected(motifDict, pwmFileName, motifIdList, idMotifDict) if op== 'cov': writePWMFromMotifsSelectedScan(motifDict, pwmFileName, motifIdList, idMotifDict, finalSelectMotifList) #get the path of the module utils_path = os.path.realpath(__file__) #remove the name of the module from the end of it. Replace won't work since w ehave DME.py and DME.pyc split = utils_path.split('/') utils_path = '/'.join(split[:len(split)-1]) inPath = os.path.realpath(__file__) split = inPath.split('/') inPath = '/'.join(split[:len(split)-2]) command = inPath + '/' + 'meme2images -png ' + pwmFileName + ' ' + outDirName #print 'meme2image command:', command try: os.system(command) except: print 'meme2image execution failed. Exiting' exit() def makeMotifLogoFromPwm(pwmFileName, outDirName): """ Given the pwm file in MEME format make the logos """ #get the path of the module utils_path = os.path.realpath(__file__) #remove the name of the module from the end of it. Replace won't work since w ehave DME.py and DME.pyc split = utils_path.split('/') utils_path = '/'.join(split[:len(split)-1]) inPath = os.path.realpath(__file__) split = inPath.split('/') inPath = '/'.join(split[:len(split)-2]) command = inPath + '/' + 'meme2images -png ' + pwmFileName + ' ' + outDirName print 'meme2image command:', command try: os.system(command) except: print 'meme2image execution failed. Exiting' exit() def writeMotifBasicStat(motifDict, foreFimoDict, backFimoDict, foreNumSeqs, backNumSeqs, outFileName, tomtomDict): """ Write a file with basic info about the motif stats like coverage Args: motifDict: dict between motif names and motif objects """ outFile = open(outFileName, 'wb') headerList = ['#MotifName','Num_Fg_seqs','Fg_cov','Num_Bg_seqs', 'Bg_cov','FG/BG','similar_motifs'] headerLine = ','.join(headerList) outFile.write(headerLine + '\n') #go thru the motif dict for motifName in motifDict.iterkeys(): motifObj = motifDict[motifName] if motifName in foreFimoDict: foreSeqs = len(foreFimoDict[motifName]) foreCov = 100*(foreSeqs/foreNumSeqs) else: foreSeqs = 0 foreCov = 0 if motifName in backFimoDict: backSeqs = len(backFimoDict[motifName]) backCov = 100*(backSeqs/backNumSeqs) fg_over_bg = foreCov/backCov else: backSeqs = 0 backCov = 0 fg_over_bg = foreCov/1 #find similar motifs to this motif simList = [] simStr = '' if motifName in tomtomDict: simList = tomtomDict[motifName] simStr = '//'.join(simList) lineList = [motifName, str(foreSeqs), str(foreCov), str(backSeqs), str(backCov), str(fg_over_bg), simStr] lineStr = ','.join(lineList) outFile.write(lineStr + '\n') outFile.close() def main(args): pass ## if( __name__ == "__main__" ): main(sys.argv) #--eof--#

RamiOran/SeqCov

utils/general_utils.py

Python

mit

15,763

[ "Biopython" ]

388d15a4d3ae61d1a7589262922c3f9e662edcb16e5fc76211258538833db0bd

# (c) 2014, Brian Coca <bcoca@ansible.com> # # This file is part of Ansible # # Ansible is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # Ansible is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with Ansible. If not, see <http://www.gnu.org/licenses/>. from __future__ import absolute_import import math import collections from ansible import errors def unique(a): if isinstance(a,collections.Hashable): c = set(a) else: c = [] for x in a: if x not in c: c.append(x) return c def intersect(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) & set(b) else: c = unique(filter(lambda x: x in b, a)) return c def difference(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) - set(b) else: c = unique(filter(lambda x: x not in b, a)) return c def symmetric_difference(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) ^ set(b) else: c = unique(filter(lambda x: x not in intersect(a,b), union(a,b))) return c def union(a, b): if isinstance(a,collections.Hashable) and isinstance(b,collections.Hashable): c = set(a) | set(b) else: c = unique(a + b) return c def min(a): _min = __builtins__.get('min') return _min(a) def max(a): _max = __builtins__.get('max') return _max(a) def isnotanumber(x): try: return math.isnan(x) except TypeError: return False def logarithm(x, base=math.e): try: if base == 10: return math.log10(x) else: return math.log(x, base) except TypeError as e: raise errors.AnsibleFilterError('log() can only be used on numbers: %s' % str(e)) def power(x, y): try: return math.pow(x, y) except TypeError as e: raise errors.AnsibleFilterError('pow() can only be used on numbers: %s' % str(e)) def inversepower(x, base=2): try: if base == 2: return math.sqrt(x) else: return math.pow(x, 1.0/float(base)) except TypeError as e: raise errors.AnsibleFilterError('root() can only be used on numbers: %s' % str(e)) def human_readable(size, isbits=False, unit=None): base = 'bits' if isbits else 'Bytes' suffix = '' ranges = ( (1<<70, 'Z'), (1<<60, 'E'), (1<<50, 'P'), (1<<40, 'T'), (1<<30, 'G'), (1<<20, 'M'), (1<<10, 'K'), (1, base) ) for limit, suffix in ranges: if (unit is None and size >= limit) or \ unit is not None and unit.upper() == suffix: break if limit != 1: suffix += base[0] return '%.2f %s' % (float(size)/ limit, suffix) class FilterModule(object): ''' Ansible math jinja2 filters ''' def filters(self): return { # general math 'isnan': isnotanumber, 'min' : min, 'max' : max, # exponents and logarithms 'log': logarithm, 'pow': power, 'root': inversepower, # set theory 'unique' : unique, 'intersect': intersect, 'difference': difference, 'symmetric_difference': symmetric_difference, 'union': union, # computer theory 'human_readable' : human_readable, }

pheanex/ansible

lib/ansible/plugins/filter/mathstuff.py

Python

gpl-3.0

4,023

[ "Brian" ]

aa6a5ec4800e08af8d376ca09c52ff18e4728d95b885aba743cf79c1edd148c8

# -*- coding: utf-8 -*- # # # TheVirtualBrain-Scientific Package. This package holds all simulators, and # analysers necessary to run brain-simulations. You can use it stand alone or # in conjunction with TheVirtualBrain-Framework Package. See content of the # documentation-folder for more details. See also http://www.thevirtualbrain.org # # (c) 2012-2013, Baycrest Centre for Geriatric Care ("Baycrest") # # This program is free software; you can redistribute it and/or modify it under # the terms of the GNU General Public License version 2 as published by the Free # Software Foundation. This program is distributed in the hope that it will be # useful, but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public # License for more details. You should have received a copy of the GNU General # Public License along with this program; if not, you can download it here # http://www.gnu.org/licenses/old-licenses/gpl-2.0 # # # CITATION: # When using The Virtual Brain for scientific publications, please cite it as follows: # # Paula Sanz Leon, Stuart A. Knock, M. Marmaduke Woodman, Lia Domide, # Jochen Mersmann, Anthony R. McIntosh, Viktor Jirsa (2013) # The Virtual Brain: a simulator of primate brain network dynamics. # Frontiers in Neuroinformatics (7:10. doi: 10.3389/fninf.2013.00010) # # """ The Data component of Spectral datatypes. .. moduleauthor:: Stuart A. Knock <Stuart@tvb.invalid> .. moduleauthor:: Paula Sanz Leon <Paula@tvb.invalid> """ import tvb.basic.traits.core as core import tvb.basic.traits.types_basic as basic import tvb.datatypes.arrays as arrays import tvb.datatypes.time_series as time_series from tvb.basic.traits.types_mapped import MappedType class PrincipalComponentsData(MappedType): """ Result of a Principal Component Analysis (PCA). """ source = time_series.TimeSeries( label="Source time-series", doc="Links to the time-series on which the PCA is applied.") weights = arrays.FloatArray( label="Principal vectors", doc="""The vectors of the 'weights' with which each time-series is represented in each component.""", file_storage=core.FILE_STORAGE_EXPAND) fractions = arrays.FloatArray( label="Fraction explained", doc="""A vector or collection of vectors representing the fraction of the variance explained by each principal component.""", file_storage=core.FILE_STORAGE_EXPAND) norm_source = arrays.FloatArray( label="Normalised source time series", file_storage=core.FILE_STORAGE_EXPAND) component_time_series = arrays.FloatArray( label="Component time series", file_storage=core.FILE_STORAGE_EXPAND) normalised_component_time_series = arrays.FloatArray( label="Normalised component time series", file_storage=core.FILE_STORAGE_EXPAND) __generate_table__ = True class IndependentComponentsData(MappedType): """ Result of TEMPORAL (Fast) Independent Component Analysis """ source = time_series.TimeSeries( label="Source time-series", doc="Links to the time-series on which the ICA is applied.") mixing_matrix = arrays.FloatArray( label="Mixing matrix - Spatial Maps", doc="""The linear mixing matrix (Mixing matrix) """) unmixing_matrix = arrays.FloatArray( label="Unmixing matrix - Spatial maps", doc="""The estimated unmixing matrix used to obtain the unmixed sources from the data""") prewhitening_matrix = arrays.FloatArray( label="Pre-whitening matrix", doc=""" """) n_components = basic.Integer( label="Number of independent components", doc=""" Observed data matrix is considered to be a linear combination of :math:`n` non-Gaussian independent components""") norm_source = arrays.FloatArray( label="Normalised source time series. Zero centered and whitened.", file_storage=core.FILE_STORAGE_EXPAND) component_time_series = arrays.FloatArray( label="Component time series. Unmixed sources.", file_storage=core.FILE_STORAGE_EXPAND) normalised_component_time_series = arrays.FloatArray( label="Normalised component time series", file_storage=core.FILE_STORAGE_EXPAND) __generate_table__ = True

rajul/tvb-library

tvb/datatypes/mode_decompositions_data.py

Python

gpl-2.0

4,446

[ "Gaussian" ]

ccb5844d1e3a2c76a1fc63ab70b20c9914c2027022f29247faac97560e8f09a4

#!/usr/bin/env python # from distutils.core import setup,Extension from distutils import sysconfig import os, sys, re, glob, shutil version='2009.Q1b2' module_ext = sysconfig.get_config_var('SO') if sys.platform=="win32": install_base="Lib/site-packages" else: install_base = os.path.join(sysconfig.get_config_var('LIBDEST'),'site-packages') ext_modules=[] child_packages = [ "rdkit.Chem", "rdkit.DataManip", "rdkit.DataStructs", "rdkit.Dbase", "rdkit.DistanceGeometry", "rdkit.ForceField", "rdkit.Geometry", "rdkit.Logger", "rdkit.ML", "rdkit.Numerics", "rdkit.SimDivFilters", "rdkit.VLib", "rdkit.sping", "rdkit.utils", ] sos = [(os.path.join(install_base,'rdkit'),['rdkit/rdBase'+module_ext])] py_packages = ["rdkit"]+child_packages for pkg in child_packages: for root,dirs,files in os.walk(pkg.replace('.','/')): if '.svn' in dirs: dirs.remove('.svn') if 'test_data' in dirs: dirs.remove('test_data') modName=root.replace(os.path.sep,'.') if '__init__.py' in files and modName not in py_packages: py_packages.append(modName) files=[os.path.join(root,file) for file in files if (os.path.splitext(file)[-1]==module_ext or\ 'test_data' in root)] sos.extend([(os.path.join(install_base,root),files)]) extraBase='share/rdkit' projects=[] for root,dirs,files in os.walk('Projects'): if '.svn' in dirs: dirs.remove('.svn') files=[os.path.join(root,filen) for filen in files] projects.append((extraBase+'/'+root,files)) data_files = [(extraBase+'/Data',glob.glob('Data/*.*'))] data_files.extend([(extraBase,glob.glob('./*.txt'))]) if sys.platform=='win32': data_files.extend([(extraBase+'/lib',glob.glob('bin/*.dll'))]) else: data_files.extend([(extraBase+'/lib',glob.glob('bin/*'))]) data_files.extend(sos) documentation = [] for root,dirs,files in os.walk('Docs'): if '.svn' in dirs: dirs.remove('.svn') files=[os.path.join(root,filen) for filen in files] documentation.append((extraBase+'/'+root,files)) setup( name='rdkit', version=version, description='RDKit Cheminformatics Library', long_description="""Data structures, algorithms, and scripts for cheminformatics.""", author='Greg Landrum', author_email='glandrum@users.sourceforge.net', url='http://www.rdkit.org/', download_url = 'http://code.google.com/p/rdkit/downloads/list', license='BSD', platforms=['Windows','Linux','Mac OS-X'], classifiers = ['Development Status :: 5 - Production/Stable', 'Environment :: Console', 'Intended Audience :: Developers', 'Intended Audience :: Science/Research', 'Programming Language :: Python', 'Programming Language :: C++', 'License :: OSI Approved :: BSD License', 'Topic :: Scientific/Engineering :: Chemistry', ], packages=py_packages, ext_modules=ext_modules, package_dir={'rdkit':'rdkit'}, data_files=data_files+documentation+projects, )

rdkit/rdkit-orig

setup.py

Python

bsd-3-clause

3,461

[ "RDKit" ]

8ebfd24860d2f7a12d003e962f02b1ab2a9714329175073c423c7dbd49d517e6

'''Parameter sweep (2D): shared procedures.''' from __future__ import absolute_import, print_function import numpy as np from grid_cell_model.submitting.factory import SubmitterFactory from grid_cell_model.submitting.arguments import ArgumentCreator from grid_cell_model.submitting.noise.slopes import (DefaultSelector, NoThetaSelector) from grid_cell_model.otherpkg.log import log_info from simtools.storage import DataStorage def submitParamSweep(p, startG, endG, Nvals, ENV, simRootDir, simLabel, appName, rtLimit, numCPU, blocking, timePrefix, numRepeat, dry_run, extraIterparams=None, rc=None, **kwargs): '''Submit and save metadata for the gE vs gI parameter sweep.''' printout = kwargs.pop('printout', True) if extraIterparams is None: extraIterparams = {} ac = ArgumentCreator(p, printout=printout) GArr = np.linspace(startG, endG, Nvals) print(GArr) g_AMPA_total_arr = [] g_GABA_total_arr = [] for E_coupling in GArr: for I_coupling in GArr: g_AMPA_total_arr.append(E_coupling) g_GABA_total_arr.append(I_coupling) iterparams = { 'g_AMPA_total' : np.array(g_AMPA_total_arr), 'g_GABA_total' : np.array(g_GABA_total_arr), } dimension_labels = ['g_AMPA_total', 'g_GABA_total'] dimensions = [Nvals, Nvals] iterparams.update(extraIterparams) ac.insertDict(iterparams, mult=False) ############################################################################### submitter = SubmitterFactory.getSubmitter( ac, appName, envType=ENV, rtLimit=rtLimit, output_dir=simRootDir, label=simLabel, blocking=blocking, timePrefix=timePrefix, numCPU=numCPU, **kwargs) ac.setOption('output_dir', submitter.outputDir()) startJobNum = 0 filter = rc[0]*len(GArr) + rc[1] if rc is not None else None submitter.submitAll(startJobNum, numRepeat, dry_run=dry_run, filter=filter) submitter.saveIterParams(iterparams, dimension_labels, dimensions, dry_run=dry_run) ############################################################################### def getBumpCurrentSlope(noise_sigma, threshold=0, type=None): ''' Parameters ---------- noise_sigma : int Noise level (sigma of the Gaussian) threshold : float Threshold below which slope values will be replaced with ``NaN``. type : string, optional If ``None`` the regular bump slope files will be used. If ``no_theta``, the bump slope files specific for the simulations wihtout theta oscillations will be used. ''' data_root = 'bump_slope_data' selector_cls = None if type is None: selector_cls = DefaultSelector elif type == 'no_theta': selector_cls = NoThetaSelector else: raise ValueError('Invalid bump slope type.') selector = selector_cls(data_root, threshold) return selector.get_slopes(noise_sigma) def getSpeedPercentile(p, path, grid_lambda, Nx): ''' Retrieve the file containing animal positions and calculate the bump speed value at the specified percentile. Parameters ---------- p : float The specified percentile. path : string Path to the file containing rat velocities grid_lambda : float Grid field spacing (cm) Nx : int Neural sheet size (neurons). THe bump has to travel this distance (in units of neurons) in order to return back to its original position, i.e. form a grid field. output : float The bump speed at the p-th percentile ''' from scipy.io import loadmat data = loadmat(path) dt = float(data['dt']) pos_x = data['pos_x'].flatten() pos_y = data['pos_y'].flatten() vel_x = np.diff(pos_x)/dt vel_y = np.diff(pos_y)/dt animal_s = np.abs(np.hstack((vel_x, vel_y))) bump_s = float(Nx) / grid_lambda * animal_s res = np.percentile(bump_s, p) msg = "Loaded velocity data from: {0}".format(path) log_info("getAnimalSpeedPercentile", msg) msg = "{0:.2f}th percentile: {1:.3f}".format(p, res) log_info("getAnimalSpeedPercentile", msg) return res

MattNolanLab/ei-attractor

grid_cell_model/simulations/007_noise/param_sweep.py

Python

gpl-3.0

4,305

[ "Gaussian" ]

4627cc6cbde8cb855d56bc2f334bbf45457401c9b88c9ae8074d576265cd0c2b

from ase import * print [a.get_potential_energy() for a in PickleTrajectory('H.traj')] images = [PickleTrajectory('H.traj')[-1]] for i in range(4): images.append(images[0].copy()) images[-1].positions[6, 1] = 2 - images[0].positions[6, 1] neb = NEB(images) neb.interpolate() for image in images: image.set_calculator(LennardJones()) for a in neb.images: print a.positions[-1], a.get_potential_energy() dyn = QuasiNewton(neb, trajectory='mep.traj') print dyn.run(fmax=0.01, steps=25) for a in neb.images: print a.positions[-1], a.get_potential_energy()

freephys/python_ase

ase/test/neb.py

Python

gpl-3.0

571

[ "ASE" ]

a5485ed1457edd09bf32274909b48ba1b9e3dfe381c1c620cd4f14b014f8578e

# This file is part of PyEMMA. # # Copyright (c) 2015, 2014 Computational Molecular Biology Group, Freie Universitaet Berlin (GER) # # PyEMMA is free software: you can redistribute it and/or modify # it under the terms of the GNU Lesser General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU Lesser General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. import os import unittest import pkg_resources import mdtraj import numpy as np import pyemma.coordinates as coor from pyemma.coordinates.data.fragmented_trajectory_reader import FragmentedTrajectoryReader class TestFragmentedTrajectory(unittest.TestCase): @classmethod def setUpClass(cls): d = np.array([[i] for i in range(0, 100)]) # np.atleast_2d(np.arange(100)) cls.d = d return cls def test_full_trajectory(self): reader = FragmentedTrajectoryReader([self.d, self.d]) reader.chunksize = 0 expected = np.vstack((self.d, self.d)) output = reader.get_output(stride=1)[0] np.testing.assert_array_almost_equal(expected, output) def test_full_trajectory_random_access(self): reader = FragmentedTrajectoryReader([self.d, self.d]) indices = np.asarray([[0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199]]) out = reader.get_output(stride=indices, chunk=0) np.testing.assert_array_equal(np.array(out).squeeze(), np.array([1, 3, 3, 99, 0, 99])) def test_chunked_trajectory_random_access(self): reader = FragmentedTrajectoryReader([self.d, self.d]) indices = np.asarray([[0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199]]) out = reader.get_output(stride=indices, chunk=1) np.testing.assert_array_equal(np.array(out).squeeze(), np.array([1,3,3,99,0,99])) def test_full_trajectory_stridden(self): for stride in [1, 3, 5, 7, 13, 20]: reader = FragmentedTrajectoryReader([self.d, self.d]) reader.chunksize = 0 expected = np.vstack((self.d, self.d))[::stride] out = reader.get_output(stride=stride)[0] np.testing.assert_array_almost_equal(expected, out, err_msg="Failed for stride=%s" % stride) def test_full_trajectory_stridden_with_lag(self): reader = FragmentedTrajectoryReader([self.d, self.d]) data = np.vstack((self.d, self.d)) for lag in [1, 5, 7]: for stride in [1, 3, 5, 7, 13, 20]: reader.chunksize = 0 X, Y = None, None # not chunked for itraj, X, Y in reader.iterator(stride=stride, lag=lag): pass np.testing.assert_array_almost_equal(data[::stride][0:len(Y)], X) np.testing.assert_array_almost_equal(data[lag::stride], Y, err_msg='lag={lag}, stride={stride}'.format(stride=stride, lag=lag)) def test_fragmented_xtc(self): from pyemma.coordinates.tests.util import create_traj top_file = pkg_resources.resource_filename(__name__, 'data/test.pdb') trajfiles = [] for _ in range(3): f, _, _ = create_traj(top_file) trajfiles.append(f) try: # three trajectories: one consisting of all three, one consisting of the first, # one consisting of the first and the last source = coor.source([trajfiles, [trajfiles[0]], [trajfiles[0], trajfiles[2]]], top=top_file) source.chunksize = 1000 out = source.get_output(stride=1) trajs = [mdtraj.load(trajfiles[i], top=top_file).xyz.reshape(-1,9) for i in range(0,3)] np.testing.assert_equal(out[0], np.vstack(trajs)) np.testing.assert_equal(out[1], trajs[0]) np.testing.assert_equal(out[2], np.vstack((trajs[0], trajs[2]))) finally: for t in trajfiles: try: os.unlink(t) except EnvironmentError: pass def test_multiple_input_trajectories_random_access(self): indices = np.asarray([ [0, 1], [0, 3], [0, 3], [0, 99], [0, 100], [0, 199], [1, 0], [1, 5], [1, 99], [2, 5], [2, 7], [2, 23] ]) expected = [np.array([1, 3, 3, 99, 0, 99]), np.array([0, 5, 99]), np.array([5, 7, 23])] for chunk_size in [0, 1, 3, 5, 13]: reader = FragmentedTrajectoryReader([[self.d, self.d], self.d, [self.d, self.d]]) out_full_trajectory_mode = reader.get_output(chunk=chunk_size, stride=indices) for i in range(3): np.testing.assert_array_equal(expected[i], out_full_trajectory_mode[i].squeeze()) def test_multiple_input_trajectories(self): reader = FragmentedTrajectoryReader([[self.d, self.d], self.d, [self.d, self.d]]) reader.chunksize = 37 out = reader.get_output() reader.chunksize = 0 out2 = reader.get_output() expected0_2 = np.vstack((self.d, self.d)) for itraj in range(0, 3): np.testing.assert_array_almost_equal(out[itraj], out2[itraj]) np.testing.assert_array_almost_equal(out[0], expected0_2) np.testing.assert_array_almost_equal(out[1], self.d) np.testing.assert_array_almost_equal(out[2], expected0_2) def test_chunked_trajectory_with_lag(self): data = np.vstack((self.d, self.d)) reader = FragmentedTrajectoryReader([self.d, self.d]) for lag in [0, 1, 3]: for stride in [1, 3, 5]: for chunksize in [1, 34, 53, 72]: reader.chunksize = chunksize if lag > 0: collected = None collected_lagged = None for itraj, X, Y in reader.iterator(stride=stride, lag=lag): collected = X if collected is None else np.vstack((collected, X)) collected_lagged = Y if collected_lagged is None else np.vstack((collected_lagged, Y)) np.testing.assert_array_almost_equal(data[::stride][0:len(collected_lagged)], collected, err_msg="lag={}, stride={}, cs={}".format( lag, stride, chunksize )) np.testing.assert_array_almost_equal(data[lag::stride], collected_lagged) else: collected = None for itraj, X in reader.iterator(stride=stride): collected = X if collected is None else np.vstack((collected, X)) np.testing.assert_array_almost_equal(data[::stride], collected) def test_index_to_reader_index(self): reader = FragmentedTrajectoryReader([self.d, self.d]) assert (0, 0) == reader._index_to_reader_index(0, 0), "first frame is first frame of first reader" assert (0, 1) == reader._index_to_reader_index(1, 0), "second frame is second frame of first reader" assert (1, 0) == reader._index_to_reader_index(100, 0), "101'st frame is first frame of second reader" assert (1, 1) == reader._index_to_reader_index(101, 0), "102'nd frame is second frame of second reader" with self.assertRaises(ValueError): reader._index_to_reader_index(-1, 0) with self.assertRaises(ValueError): reader._index_to_reader_index(200, 0) def test_cols(self): dim = 5 arr = np.arange(60).reshape(-1, dim) data = [(arr, arr), arr, (arr, arr, arr)] reader = FragmentedTrajectoryReader(data) cols = (0, 3) for itraj, x in reader.iterator(chunk=0, return_trajindex=True, cols=cols): if isinstance(data[itraj], tuple): syn_traj = np.concatenate(data[itraj]) else: syn_traj = data[itraj] np.testing.assert_equal(x, syn_traj[:, cols]) def test_raise_different_dims(self): data = [self.d, np.array([[1,2,3], [4,5,6]])] with self.assertRaises(ValueError): FragmentedTrajectoryReader(data) def test_with_save_traj(self): path = pkg_resources.resource_filename(__name__, 'data') + os.path.sep pdb_file = os.path.join(path, 'bpti_ca.pdb') traj_files = [ os.path.join(path, 'bpti_001-033.xtc'), os.path.join(path, 'bpti_034-066.xtc'), os.path.join(path, 'bpti_067-100.xtc') ] source_frag = coor.source([traj_files], top=pdb_file) full_data = source_frag.get_output()[0] last_frame_fragment_0 = [0,32] first_frame_fragment_1 = [0,33] first_frame_fragment_2 = [0,66] reshape = lambda f: f.xyz.reshape((f.xyz.shape[0],f.xyz.shape[1] * f.xyz.shape[2])).squeeze() # Frames in the first fragment: frames = coor.save_traj(source_frag, [last_frame_fragment_0], None) np.testing.assert_equal(reshape(frames), full_data[32]) # Frames the first and second fragments frames = coor.save_traj(source_frag, [last_frame_fragment_0, first_frame_fragment_1], None) np.testing.assert_equal(reshape(frames), full_data[np.array([32, 33])]) # Frames only in the second fragment frames = coor.save_traj(source_frag, [first_frame_fragment_1], None) np.testing.assert_equal(reshape(frames), full_data[33]) # Frames only in the second and third fragment frames = coor.save_traj(source_frag, [first_frame_fragment_1, first_frame_fragment_2], None) np.testing.assert_equal(reshape(frames), full_data[np.array([33, 66])])

markovmodel/PyEMMA

pyemma/coordinates/tests/test_fragmented_trajectory.py

Python

lgpl-3.0

10,158

[ "MDTraj" ]

30fe81e077be5276421e4b866bcad5eea5d7341a1a80220eab70e42df09a6612

""" .. versionadded:: v6r20 FTS3Agent implementation. It is in charge of submitting and monitoring all the transfers. It can be duplicated. .. literalinclude:: ../ConfigTemplate.cfg :start-after: ##BEGIN FTS3Agent :end-before: ##END FTS3Agent :dedent: 2 :caption: FTS3Agent options """ from __future__ import absolute_import from __future__ import division from __future__ import print_function __RCSID__ = "$Id$" import errno import time # from threading import current_thread from multiprocessing.pool import ThreadPool # We use the dummy module because we use the ThreadPool from multiprocessing.dummy import current_process from socket import gethostname from DIRAC import S_OK, S_ERROR from DIRAC.AccountingSystem.Client.Types.DataOperation import DataOperation from DIRAC.Core.Base.AgentModule import AgentModule from DIRAC.Core.Utilities.DErrno import cmpError from DIRAC.Core.Utilities.DictCache import DictCache from DIRAC.Core.Utilities.Time import fromString from DIRAC.ConfigurationSystem.Client.Helpers.Resources import getFTS3ServerDict from DIRAC.ConfigurationSystem.Client.Helpers.Operations import Operations as opHelper from DIRAC.ConfigurationSystem.Client.Helpers.Registry import getDNForUsername from DIRAC.FrameworkSystem.Client.Logger import gLogger from DIRAC.FrameworkSystem.Client.ProxyManagerClient import gProxyManager from DIRAC.DataManagementSystem.private import FTS3Utilities from DIRAC.DataManagementSystem.DB.FTS3DB import FTS3DB from DIRAC.DataManagementSystem.Client.FTS3Job import FTS3Job from DIRAC.RequestManagementSystem.Client.ReqClient import ReqClient # pylint: disable=attribute-defined-outside-init AGENT_NAME = "DataManagement/FTS3Agent" # Lifetime in seconds of the proxy we download for submission PROXY_LIFETIME = 43200 # 12 hours class FTS3Agent(AgentModule): """ This Agent is responsible of interacting with the FTS3 services. Several of them can run in parallel. It first treats the Operations, by creating new FTS jobs and performing callback. Then, it monitors the current jobs. CAUTION: This agent and the FTSAgent cannot run together. """ def __readConf(self): """ Read configurations :return: S_OK()/S_ERROR() """ # Getting all the possible servers res = getFTS3ServerDict() if not res['OK']: gLogger.error(res['Message']) return res srvDict = res['Value'] serverPolicyType = opHelper().getValue('DataManagement/FTSPlacement/FTS3/ServerPolicy', 'Random') self._serverPolicy = FTS3Utilities.FTS3ServerPolicy(srvDict, serverPolicy=serverPolicyType) self.maxNumberOfThreads = self.am_getOption("MaxThreads", 10) # Number of Operation we treat in one loop self.operationBulkSize = self.am_getOption("OperationBulkSize", 20) # Number of Jobs we treat in one loop self.jobBulkSize = self.am_getOption("JobBulkSize", 20) self.maxFilesPerJob = self.am_getOption("MaxFilesPerJob", 100) self.maxAttemptsPerFile = self.am_getOption("MaxAttemptsPerFile", 256) self.kickDelay = self.am_getOption("KickAssignedHours", 1) self.maxKick = self.am_getOption("KickLimitPerCycle", 100) self.deleteDelay = self.am_getOption("DeleteGraceDays", 180) self.maxDelete = self.am_getOption("DeleteLimitPerCycle", 100) # lifetime of the proxy we download to delegate to FTS self.proxyLifetime = self.am_getOption("ProxyLifetime", PROXY_LIFETIME) return S_OK() def initialize(self): """ Agent's initialization :return: S_OK()/S_ERROR() """ self._globalContextCache = {} # name that will be used in DB for assignment tag self.assignmentTag = gethostname().split('.')[0] res = self.__readConf() # We multiply by two because of the two threadPools self.fts3db = FTS3DB(pool_size=2 * self.maxNumberOfThreads) self.jobsThreadPool = ThreadPool(self.maxNumberOfThreads) self.opsThreadPool = ThreadPool(self.maxNumberOfThreads) return res def beginExecution(self): """ Reload configurations before start of a cycle :return: S_OK()/S_ERROR() """ return self.__readConf() def getFTS3Context(self, username, group, ftsServer, threadID): """ Returns an fts3 context for a given user, group and fts server The context pool is per thread, and there is one context per tuple (user, group, server). We dump the proxy of a user to a file (shared by all the threads), and use it to make the context. The proxy needs a lifetime of self.proxyLifetime, is cached for cacheTime = (2*lifeTime/3) - 10mn, and the lifetime of the context is 45mn The reason for cacheTime to be what it is is because the FTS3 server will ask for a new proxy after 2/3rd of the existing proxy has expired, so we renew it just before :param str username: name of the user :param str group: group of the user :param str ftsServer: address of the server :param str threadID: thread ID :returns: S_OK with the context object """ log = gLogger.getSubLogger("getFTS3Context", child=True) contextes = self._globalContextCache.setdefault(threadID, DictCache()) idTuple = (username, group, ftsServer) log.debug("Getting context for %s" % (idTuple, )) # We keep a context in the cache for 45 minutes # (so it needs to be valid at least 15 since we add it for one hour) if not contextes.exists(idTuple, 15 * 60): res = getDNForUsername(username) if not res['OK']: return res # We take the first DN returned userDN = res['Value'][0] log.debug("UserDN %s" % userDN) # We dump the proxy to a file. # It has to have a lifetime of self.proxyLifetime # Because the FTS3 servers cache it for 2/3rd of the lifetime # we should make our cache a bit less than 2/3rd of the lifetime cacheTime = int(2 * self.proxyLifetime / 3) - 600 res = gProxyManager.downloadVOMSProxyToFile( userDN, group, requiredTimeLeft=self.proxyLifetime, cacheTime=cacheTime) if not res['OK']: return res proxyFile = res['Value'] log.debug("Proxy file %s" % proxyFile) # We generate the context # In practice, the lifetime will be less than proxyLifetime # because we reuse a cached proxy. However, the cached proxy will # never forced a redelegation, because it is recent enough for FTS3 servers. # The delegation is forced when 2/3 rd of the lifetime are left, and we get a fresh # one just before. So no problem res = FTS3Job.generateContext(ftsServer, proxyFile, lifetime=self.proxyLifetime) if not res['OK']: return res context = res['Value'] # we add it to the cache for this thread for 1h contextes.add(idTuple, 3600, context) return S_OK(contextes.get(idTuple)) def _monitorJob(self, ftsJob): """ * query the FTS servers * update the FTSFile status * update the FTSJob status :param ftsJob: FTS job :return: ftsJob, S_OK()/S_ERROR() """ # General try catch to avoid that the tread dies try: threadID = current_process().name log = gLogger.getSubLogger("_monitorJob/%s" % ftsJob.jobID, child=True) res = self.getFTS3Context( ftsJob.username, ftsJob.userGroup, ftsJob.ftsServer, threadID=threadID) if not res['OK']: log.error("Error getting context", res) return ftsJob, res context = res['Value'] res = ftsJob.monitor(context=context) if not res['OK']: log.error("Error monitoring job", res) # If the job was not found on the server, update the DB if cmpError(res, errno.ESRCH): res = self.fts3db.cancelNonExistingJob(ftsJob.operationID, ftsJob.ftsGUID) return ftsJob, res # { fileID : { Status, Error } } filesStatus = res['Value'] # Specify the job ftsGUID to make sure we do not overwrite # status of files already taken by newer jobs res = self.fts3db.updateFileStatus(filesStatus, ftsGUID=ftsJob.ftsGUID) if not res['OK']: log.error("Error updating file fts status", "%s, %s" % (ftsJob.ftsGUID, res)) return ftsJob, res upDict = { ftsJob.jobID: { 'status': ftsJob.status, 'error': ftsJob.error, 'completeness': ftsJob.completeness, 'operationID': ftsJob.operationID, 'lastMonitor': True, } } res = self.fts3db.updateJobStatus(upDict) if ftsJob.status in ftsJob.FINAL_STATES: self.__sendAccounting(ftsJob) return ftsJob, res except Exception as e: log.exception("Exception while monitoring job", repr(e)) return ftsJob, S_ERROR(0, "Exception %s" % repr(e)) @staticmethod def _monitorJobCallback(returnedValue): """ Callback when a job has been monitored :param returnedValue: value returned by the _monitorJob method (ftsJob, standard dirac return struct) """ ftsJob, res = returnedValue log = gLogger.getSubLogger("_monitorJobCallback/%s" % ftsJob.jobID, child=True) if not res['OK']: log.error("Error updating job status", res) else: log.debug("Successfully updated job status") def monitorJobsLoop(self): """ * fetch the active FTSJobs from the DB * spawn a thread to monitor each of them :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("monitorJobs", child=True) log.debug("Size of the context cache %s" % len(self._globalContextCache)) log.debug("Getting active jobs") # get jobs from DB res = self.fts3db.getActiveJobs(limit=self.jobBulkSize, jobAssignmentTag=self.assignmentTag) if not res['OK']: log.error("Could not retrieve ftsJobs from the DB", res) return res activeJobs = res['Value'] log.info("%s jobs to queue for monitoring" % len(activeJobs)) # We store here the AsyncResult object on which we are going to wait applyAsyncResults = [] # Starting the monitoring threads for ftsJob in activeJobs: log.debug("Queuing executing of ftsJob %s" % ftsJob.jobID) # queue the execution of self._monitorJob( ftsJob ) in the thread pool # The returned value is passed to _monitorJobCallback applyAsyncResults.append(self.jobsThreadPool.apply_async( self._monitorJob, (ftsJob, ), callback=self._monitorJobCallback)) log.debug("All execution queued") # Waiting for all the monitoring to finish while not all([r.ready() for r in applyAsyncResults]): log.debug("Not all the tasks are finished") time.sleep(0.5) log.debug("All the tasks have completed") return S_OK() @staticmethod def _treatOperationCallback(returnedValue): """ Callback when an operation has been treated :param returnedValue: value returned by the _treatOperation method (ftsOperation, standard dirac return struct) """ operation, res = returnedValue log = gLogger.getSubLogger("_treatOperationCallback/%s" % operation.operationID, child=True) if not res['OK']: log.error("Error treating operation", res) else: log.debug("Successfully treated operation") def _treatOperation(self, operation): """ Treat one operation: * does the callback if the operation is finished * generate new jobs and submits them :param operation: the operation to treat :return: operation, S_OK()/S_ERROR() """ try: threadID = current_process().name log = gLogger.getSubLogger("treatOperation/%s" % operation.operationID, child=True) # If the operation is totally processed # we perform the callback if operation.isTotallyProcessed(): log.debug("FTS3Operation %s is totally processed" % operation.operationID) res = operation.callback() if not res['OK']: log.error("Error performing the callback", res) log.info("Putting back the operation") dbRes = self.fts3db.persistOperation(operation) if not dbRes['OK']: log.error("Could not persist operation", dbRes) return operation, res else: log.debug("FTS3Operation %s is not totally processed yet" % operation.operationID) # This flag is set to False if we want to stop the ongoing processing # of an operation, typically when the matching RMS Request has been # canceled (see below) continueOperationProcessing = True # Check the status of the associated RMS Request. # If it is canceled or does not exist anymore then we will not create new FTS3Jobs, and mark # this as FTS3Operation canceled. if operation.rmsReqID: res = ReqClient().getRequestStatus(operation.rmsReqID) if not res['OK']: # If the Request does not exist anymore if cmpError(res, errno.ENOENT): log.info( "The RMS Request does not exist anymore, canceling the FTS3Operation", "rmsReqID: %s, FTS3OperationID: %s" % (operation.rmsReqID, operation.operationID)) operation.status = 'Canceled' continueOperationProcessing = False else: log.error("Could not get request status", res) return operation, res else: rmsReqStatus = res['Value'] if rmsReqStatus == 'Canceled': log.info( "The RMS Request is canceled, canceling the FTS3Operation", "rmsReqID: %s, FTS3OperationID: %s" % (operation.rmsReqID, operation.operationID)) operation.status = 'Canceled' continueOperationProcessing = False if continueOperationProcessing: res = operation.prepareNewJobs( maxFilesPerJob=self.maxFilesPerJob, maxAttemptsPerFile=self.maxAttemptsPerFile) if not res['OK']: log.error("Cannot prepare new Jobs", "FTS3Operation %s : %s" % (operation.operationID, res)) return operation, res newJobs = res['Value'] log.debug("FTS3Operation %s: %s new jobs to be submitted" % (operation.operationID, len(newJobs))) for ftsJob in newJobs: res = self._serverPolicy.chooseFTS3Server() if not res['OK']: log.error(res) continue ftsServer = res['Value'] log.debug("Use %s server" % ftsServer) ftsJob.ftsServer = ftsServer res = self.getFTS3Context( ftsJob.username, ftsJob.userGroup, ftsServer, threadID=threadID) if not res['OK']: log.error("Could not get context", res) continue context = res['Value'] try: tpcProtocols = operation.fts3Plugin.selectTPCProtocols(ftsJob=ftsJob) except ValueError as e: log.error("Could not select TPC list", repr(e)) continue res = ftsJob.submit(context=context, protocols=tpcProtocols) if not res['OK']: log.error("Could not submit FTS3Job", "FTS3Operation %s : %s" % (operation.operationID, res)) continue operation.ftsJobs.append(ftsJob) submittedFileIds = res['Value'] log.info("FTS3Operation %s: Submitted job for %s transfers" % (operation.operationID, len(submittedFileIds))) # new jobs are put in the DB at the same time res = self.fts3db.persistOperation(operation) if not res['OK']: log.error("Could not persist operation", res) return operation, res except Exception as e: log.exception('Exception in the thread', repr(e)) return operation, S_ERROR("Exception %s" % repr(e)) def treatOperationsLoop(self): """ * Fetch all the FTSOperations which are not finished * Spawn a thread to treat each operation :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("treatOperations", child=True) log.debug("Size of the context cache %s" % len(self._globalContextCache)) log.info("Getting non finished operations") res = self.fts3db.getNonFinishedOperations( limit=self.operationBulkSize, operationAssignmentTag=self.assignmentTag) if not res['OK']: log.error("Could not get incomplete operations", res) return res incompleteOperations = res['Value'] log.info("Treating %s incomplete operations" % len(incompleteOperations)) applyAsyncResults = [] for operation in incompleteOperations: log.debug("Queuing executing of operation %s" % operation.operationID) # queue the execution of self._treatOperation( operation ) in the thread pool # The returned value is passed to _treatOperationCallback applyAsyncResults.append(self.opsThreadPool.apply_async( self._treatOperation, (operation, ), callback=self._treatOperationCallback)) log.debug("All execution queued") # Waiting for all the treatments to finish while not all([r.ready() for r in applyAsyncResults]): log.debug("Not all the tasks are finished") time.sleep(0.5) log.debug("All the tasks have completed") return S_OK() def kickOperations(self): """ Kick stuck operations :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("kickOperations", child=True) res = self.fts3db.kickStuckOperations(limit=self.maxKick, kickDelay=self.kickDelay) if not res['OK']: return res kickedOperations = res['Value'] log.info("Kicked %s stuck operations" % kickedOperations) return S_OK() def kickJobs(self): """ Kick stuck jobs :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("kickJobs", child=True) res = self.fts3db.kickStuckJobs(limit=self.maxKick, kickDelay=self.kickDelay) if not res['OK']: return res kickedJobs = res['Value'] log.info("Kicked %s stuck jobs" % kickedJobs) return S_OK() def deleteOperations(self): """ Delete final operations :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("deleteOperations", child=True) res = self.fts3db.deleteFinalOperations(limit=self.maxDelete, deleteDelay=self.deleteDelay) if not res['OK']: return res deletedOperations = res['Value'] log.info("Deleted %s final operations" % deletedOperations) return S_OK() def finalize(self): """ Finalize processing :return: S_OK()/S_ERROR() """ # Joining all the ThreadPools log = gLogger.getSubLogger("Finalize") log.debug("Closing jobsThreadPool") self.jobsThreadPool.close() self.jobsThreadPool.join() log.debug("jobsThreadPool joined") log.debug("Closing opsThreadPool") self.opsThreadPool.close() self.opsThreadPool.join() log.debug("opsThreadPool joined") return S_OK() def execute(self): """ One cycle execution :return: S_OK()/S_ERROR() """ log = gLogger.getSubLogger("execute", child=True) log.info("Monitoring job") res = self.monitorJobsLoop() if not res['OK']: log.error("Error monitoring jobs", res) return res log.info("Treating operations") res = self.treatOperationsLoop() if not res['OK']: log.error("Error treating operations", res) return res log.info("Kicking stuck jobs") res = self.kickJobs() if not res['OK']: log.error("Error kicking jobs", res) return res log.info("Kicking stuck operations") res = self.kickOperations() if not res['OK']: log.error("Error kicking operations", res) return res log.info("Deleting final operations") res = self.deleteOperations() if not res['OK']: log.error("Error deleting operations", res) return res return S_OK() @staticmethod def __sendAccounting(ftsJob): """ prepare and send DataOperation to AccountingDB :param ftsJob: the FTS3Job from which we send the accounting info """ dataOp = DataOperation() dataOp.setStartTime(fromString(ftsJob.submitTime)) dataOp.setEndTime(fromString(ftsJob.lastUpdate)) dataOp.setValuesFromDict(ftsJob.accountingDict) dataOp.delayedCommit()

yujikato/DIRAC

src/DIRAC/DataManagementSystem/Agent/FTS3Agent.py

Python

gpl-3.0

20,683

[ "DIRAC" ]

71fa26820bd2db8ffe5b25e6d3df90c58dd7ac29bf9d4354921be905923ffd1a

# Rebinding to a cluster # Run by: # $ python run.py [N] [runs] [outFilename] [Logmode, default=False] # # Arguments: # - N: Number of particles in cluster # - runs: Number of simulation runs # - outFilename: Name of output file # - Logmode: false by default, if True, only 1 VTK-logged run is # performed. # # E.g.: # $ python run.py 7 1000 data.out # Or: # $ python run.py 7 1 data.out True # Modules # =============================== import sys #Also, set relative egfrd directory path sys.path.append('../../') import os import shutil import datetime import math from egfrd import * import model import gfrdbase import _gfrd from visualization import vtklogger if __name__ == "__main__": # Constants # =============================== # Number of particles in the cluster N = int(sys.argv[1]) # Number of runs runs = int(sys.argv[2]) # Output file outFilename = sys.argv[3] # LOGGING mode try: LOGGING = bool(sys.argv[4]) if (LOGGING==True): print "* Performing only 1 logging run." runs = 1 except: LOGGING = False # Particle constants sigma = 1e-5 # Diameter particle; big:1e-5 D = 1e-8 # Diffusion constant; big:1e-8 world_size = 1e-3 # Lengths of simulation box; normal: 1e-3 k1 = 1e-10 k2 = 1e2 # Spacing inbetween cluster particles AND cluster/B-particle spacing = sigma/1e5 # Create "unique" seed # =============================== currenttime = (long(datetime.datetime.now().year*3600*24*365+ datetime.datetime.now().month*30.5*24*3600+ datetime.datetime.now().day*24*3600+datetime.datetime.now().hour*3600+ datetime.datetime.now().minute*60+datetime.datetime.now().second)) myrandom.seed(currenttime) print str('Seed: '+str(currenttime)) # Functions # =============================== def cartesian(g1, g2, ng1, ng2): """ Converts lattice coordinates (ng1, ng2) to cartesian coordinates Arguments: - Lattice vectors g1=[x1,y1] and g2=[x2,y2] - Lattice coordinates (ng1, ng2) """ cartesian_x = (ng1 * (g1[0]) + ng2 * (g2[0])) cartesian_y = (ng2 * (g2[1]) + ng1 * (g1[1])) return cartesian_x, cartesian_y def distance(x1, y1, x2, y2): """ Calculates the distance between points (x1, y1) and (x2, y2) """ return math.sqrt(math.pow((x1-x2),2)+math.pow((y1-y2),2)) def generate_possible_positions(N): """ Generates a list with possible coordinates and distances to center This function does the following: - It loops over square area of an hexagonal lattice (of size calculated to facilitate N particles) - Lattice coordinates and distance to the center of the area are stored if they are within circular boundaries. (The latter check is only done to be absolutely sure a circular shape is formed.) This information can be used in a later function. If the list of generated coordinates is sorted by distance to the center, N particles can be placed within a circular geometry by looping over the coordinates. Arguments: - N: number of particles to place. """ global w, A, spacing, sigma #, g1, g2, cartesian_x, cartesian_y, ng1, ng2 # Lattice vectors d1 = [1,0] d2 = [math.cos((math.pi)/3.0),math.sin((math.pi)/3.0)] # Scaled lattice vectors lengthLatticeVector = (sigma+spacing) g1 = [lengthLatticeVector*d1[0], lengthLatticeVector*d1[1]] g2 = [lengthLatticeVector*d2[0], lengthLatticeVector*d2[1]] # Factors to calculate square area of lattice needed """ factorNonSquareGrid = math.sqrt(1/(d1[0]*d2[1]-d1[1]*d2[0])) factorSquareToCircle = math.pi/2 #math.sqrt(math.pow((math.pi*0.5),2)) # Calculate diameter of sphere L = (spacing+sigma)*(math.ceil(math.sqrt(N))+2)*factorNonSquareGrid*factorSquareToCircle # "(math.ceil(math.sqrt(N))+2)"; ceil and +2: some margin diamondSide = (L/2)*math.tan(pi/6)+(L/2)/math.tan(pi/6) diamondDiagonal = sin(pi/3)*L #2*sin(pi/3)*L/2 """ # d1x*d2y-d1y*d2x diamondToSquare = math.sqrt((4*d2[0]*d2[1])/(0.25*math.pi)) vectorsOnDiameter = math.ceil(math.sqrt(N)+2) numberOfVectors = diamondToSquare * vectorsOnDiameter diameterCircle = math.ceil(math.sqrt(N)+2)*lengthLatticeVector radiusCircle = diameterCircle/2 # Cartesian coordinates cartesian_x = 0 cartesian_y = 0 cartesian_z = 0 # The list with possible coordinates and distances to center clusterParticleCoordinates = [] for ng1 in range(int(-math.ceil(numberOfVectors/2)), int(math.ceil(numberOfVectors/2))): for ng2 in range(int(-math.ceil(numberOfVectors/2)), int(math.ceil(numberOfVectors/2))): cartesian_x, cartesian_y = cartesian(g1, g2, ng1, ng2) distanceToCenter = distance(cartesian_x, cartesian_y, 0, 0) if (distanceToCenter < radiusCircle): clusterParticleCoordinates.append([ distanceToCenter, cartesian_x, cartesian_y, cartesian_z ]) return clusterParticleCoordinates def make_cluster(N, coord_x, coord_y, coord_z): """ Places N particles on hexagonal lattice in spherical symmetry Arguments: - N: number of particles to place - coord_x, coord_y, coord_z: Coordinates where to place cluster """ # Generate list of positions and there distance to the center clusterParticleCoordinates = generate_possible_positions(N) # Sort this list clusterParticleCoordinates.sort(key=lambda x: x[0]) # Place center particle place_particle(w, C, [clusterParticleCoordinates[0][1]+coord_x, clusterParticleCoordinates[0][2]+coord_y, clusterParticleCoordinates[0][3]+coord_z]) # Place N particles starting with the particle closest to the # center, then placing the second closest particle, etc.. for i in range(1,N): try: place_particle(w, A, [clusterParticleCoordinates[i][1]+coord_x, clusterParticleCoordinates[i][2]+coord_y, clusterParticleCoordinates[i][3]+coord_z]) except: print "ERROR: couldn't place particle." def single_run(N, LOGGING): """ Single run of simulation """ global w, A, C, k1, k2 # Basic set up simulator # =============================== # Model m = model.ParticleModel(world_size) # Species A = model.Species('A', 0, sigma/2) m.add_species_type(A) B = model.Species('B', D, sigma/2) m.add_species_type(B) C = model.Species('C', 0, sigma/2) m.add_species_type(C) # Reaction rules r1 = model.create_binding_reaction_rule(A, B, C, k1) m.network_rules.add_reaction_rule(r1) r2 = model.create_unbinding_reaction_rule(C, A, B, k2) m.network_rules.add_reaction_rule(r2) # World w = gfrdbase.create_world(m, 3) # Simulator s = EGFRDSimulator(w, myrandom.rng) # Put in cluster make_cluster(N, world_size/2, world_size/2, world_size/2) # Put in reactants # place_particle(w, B, [world_size/2, world_size/2, world_size/2+sigma+spacing]) # Enable VTK Logger # =============================== if (LOGGING == True): vtk_output_directory = 'VTK_out' if (os.path.exists(vtk_output_directory)): print '** Warning: VTK directory already exists.' l = vtklogger.VTKLogger(s, vtk_output_directory, extra_particle_step=True) # Running # =============================== numberDetected = 0 if (LOGGING == True): while 1: l.log() # log s.step() # and make eGFRD step if s.last_reaction: numberDetected = numberDetected+1 if (numberDetected == 2): # print "2nd Reaction detected at: " + str(s.t) + "(" + str(s.last_reaction) + ")" reaction_time = s.t - previous_time break else: previous_time = s.t l.stop() else: while 1: s.step() # make eGFRD step if s.last_reaction: numberDetected = numberDetected+1 if (numberDetected == 2): # print "2nd Reaction detected at: " + str(s.t) + "(" + str(s.last_reaction) + ")" reaction_time = s.t - previous_time break else: previous_time = s.t s.stop(s.t) #TODO #del w #del s # If this one is thrown in, the runs suddenly stop?! #del m return (reaction_time) # Main part # =============================== if __name__ == "__main__": # Output file outFile = open(outFilename, 'w') outFile.close() outFile = open(outFilename, 'a') for M in range(runs): outFile.write(str(single_run(N, LOGGING)) + '\n') outFile.flush outFile.close() timetaken = (long(datetime.datetime.now().year*3600*24*365+ datetime.datetime.now().month*30.5*24*3600+ datetime.datetime.now().day*24*3600+datetime.datetime.now().hour*3600+ datetime.datetime.now().minute*60+datetime.datetime.now().second)-currenttime) print "Done in "+ str(timetaken) +" seconds." # #### OLD CODE #def in_circle(cartesian_x, cartesian_y, r_x, r_y, R): # if (math.sqrt(math.pow((cartesian_x-r_x),2)+math.pow((cartesian_y-r_y),2)) < R): # return True # else: # return False # while end time hasn't come and #timesteps still below limit # while ((s.get_next_time() < endTime) and (n < EARLY_STOP)): # TODO # Terminate the simulation at appropriate time #""" #if (n >= EARLY_STOP): # print "Early stop (timestep limit)." # s.stop(s.t) # reaction_time = INF #else: # print "Early stop (time limit)." # s.stop(s.get_next_time()) # reaction_time = INF #""" # Make sure logger writes away information. # l.stop() #TODO REMOVED LOGGING

gfrd/egfrd

samples/memorytools/cluster.py

Python

gpl-2.0

10,318

[ "VTK" ]

1e5590b7745cf6758174b45f4093df4c6ea49e2ed2d5317b6521b7d139bef950

#! /usr/bin/env python """Calculate viral taxonomy abundance from BLAST and Bowtie inputs. Use '-h' for parameter help. """ import os import re import argparse import blast parser = argparse.ArgumentParser(description = ('Calculate viral taxonomy abundance for each sample from PHAST' 'viral database BLAST results and bowtie mapping information.')) parser.add_argument('--blast', help=('BLAST output file from search against the viral db.' 'Output format should be "-m 8".'), type=str, required=True) parser.add_argument('--bowtie_dir', help=('Directory containing output from bowtie in which reads ' 'were mapped to ORFs. Filenames should end in ".psl".'), type=str, required=True) parser.add_argument('--viral_db', help=('Phast viral database used for assigning taxonomy ' 'downloaded via' 'wget http://www.phantome.org/Downloads/Viruses/2016_05_01.tgz'), type=str, required=True) args = parser.parse_args() orf_gene_dict = blast.get_orf_gene_dict(args.blast) blast.setup_viral_taxa_sql_db() viral_orf_fam_dict, viral_orf_genus_dict = blast.get_viral_orf_taxa_dicts( orf_gene_dict, args.viral_db) bowtie_files = [os.path.join(args.bowtie_dir, f) for f in os.listdir(args.bowtie_dir) if f.endswith('.psl')] count_mapped_reads = 0 count_fam_reads = 0 count_genus_reads = 0 count_total_reads = 0 for bowtie_file in bowtie_files: match = re.search(r'([\w.]+/)([\w.]+)([.]psl)', bowtie_file) sample = match.group(2) read_count, mapped_reads = blast.count_sample_reads_bowtie(bowtie_file) count_mapped_reads = count_mapped_reads + mapped_reads count_total_reads = count_total_reads + read_count orf_abundance_dict = blast.get_orf_abundance_dict(bowtie_file) sample_viral_fam_dict, sample_viral_genus_dict = ( blast.get_sample_viral_taxa_abundances( orf_abundance_dict,viral_orf_fam_dict,viral_orf_genus_dict) ) fam_count = 0 viral_raw_fam_ab_file = sample + '.fam_raw_abundance.txt' viral_raw_fam_ab_output = open(viral_raw_fam_ab_file, 'w') viral_raw_fam_ab_output.write('ID\t%s\n' % sample) for fam, ab in sample_viral_fam_dict.items(): fam_count += 1 viral_raw_fam_ab_output.write('%s\t%d\n' % (fam, ab)) viral_raw_fam_ab_output.close() #viral_norm_fam_ab_file = sample + '.fam_norm_abundance.txt' #viral_norm_fam_ab_output = open(viral_norm_fam_ab_file, 'w') #viral_norm_fam_ab_output.write('ID\t%s\n' % sample) #for fam, ab in sample_viral_fam_dict.items(): # norm_ab = float(ab) / float(count_total_reads) # viral_norm_fam_ab_output.write('%s\t%e\n' % (fam, norm_ab)) #viral_norm_fam_ab_output.close() genus_count = 0 viral_raw_genus_ab_file = sample + '.genus_raw_abundance.txt' viral_raw_genus_ab_output = open(viral_raw_genus_ab_file, 'w') viral_raw_genus_ab_output.write('ID\t%s\n' % sample) for genus, ab in sample_viral_genus_dict.items(): genus_count += 1 viral_raw_genus_ab_output.write('%s\t%d\n' % (genus, ab)) viral_raw_genus_ab_output.close() count_fam_reads = (count_fam_reads + (sum(sample_viral_fam_dict.values()))) count_genus_reads = (count_genus_reads + (sum(sample_viral_genus_dict.values()))) output = ('Sample: %s\nReads - %d\nFamilies: %s\nGenera: %s\n\n' % (sample, read_count, fam_count, genus_count)) print(output) output = ('Number of total reads: %d\nNumber of mapped reads: %d\n' 'Number of mapped reads with family annotation: %d\n' 'Number of mapped reads with genus annotation: %d') % ( count_total_reads, count_mapped_reads, count_fam_reads, count_genus_reads) print(output)

chrisLanderson/rumen_virome

scripts/viral_taxa_blast2tsv.py

Python

mit

3,865

[ "BLAST", "Bowtie" ]

48ad6214500daaa4c9527c3fca2bf10b925a68d821e8ff3834d5b1aa5d889467

# coding: utf-8 # Copyright (c) Pymatgen Development Team. # Distributed under the terms of the MIT License. """ This module implements representations of slabs and surfaces, as well as algorithms for generating them. If you use this module, please consider citing the following work:: R. Tran, Z. Xu, B. Radhakrishnan, D. Winston, W. Sun, K. A. Persson, S. P. Ong, "Surface Energies of Elemental Crystals", Scientific Data, 2016, 3:160080, doi: 10.1038/sdata.2016.80. as well as:: Sun, W.; Ceder, G. Efficient creation and convergence of surface slabs, Surface Science, 2013, 617, 53–59, doi:10.1016/j.susc.2013.05.016. """ import copy import itertools import json import logging import math import os import warnings from functools import reduce from math import gcd import numpy as np from monty.fractions import lcm from scipy.cluster.hierarchy import fcluster, linkage from scipy.spatial.distance import squareform from pymatgen.analysis.structure_matcher import StructureMatcher from pymatgen.core.lattice import Lattice from pymatgen.core.periodic_table import get_el_sp from pymatgen.core.sites import PeriodicSite from pymatgen.core.structure import Structure from pymatgen.symmetry.analyzer import SpacegroupAnalyzer from pymatgen.util.coord import in_coord_list __author__ = "Richard Tran, Wenhao Sun, Zihan Xu, Shyue Ping Ong" logger = logging.getLogger(__name__) class Slab(Structure): """ Subclass of Structure representing a Slab. Implements additional attributes pertaining to slabs, but the init method does not actually implement any algorithm that creates a slab. This is a DUMMY class who's init method only holds information about the slab. Also has additional methods that returns other information about a slab such as the surface area, normal, and atom adsorption. Note that all Slabs have the surface normal oriented perpendicular to the a and b lattice vectors. This means the lattice vectors a and b are in the surface plane and the c vector is out of the surface plane (though not necessarily perpendicular to the surface). .. attribute:: miller_index Miller index of plane parallel to surface. .. attribute:: scale_factor Final computed scale factor that brings the parent cell to the surface cell. .. attribute:: shift The shift value in Angstrom that indicates how much this slab has been shifted. """ def __init__( self, lattice, species, coords, miller_index, oriented_unit_cell, shift, scale_factor, reorient_lattice=True, validate_proximity=False, to_unit_cell=False, reconstruction=None, coords_are_cartesian=False, site_properties=None, energy=None, ): """ Makes a Slab structure, a structure object with additional information and methods pertaining to slabs. Args: lattice (Lattice/3x3 array): The lattice, either as a :class:`pymatgen.core.lattice.Lattice` or simply as any 2D array. Each row should correspond to a lattice vector. E.g., [[10,0,0], [20,10,0], [0,0,30]] specifies a lattice with lattice vectors [10,0,0], [20,10,0] and [0,0,30]. species ([Species]): Sequence of species on each site. Can take in flexible input, including: i. A sequence of element / species specified either as string symbols, e.g. ["Li", "Fe2+", "P", ...] or atomic numbers, e.g., (3, 56, ...) or actual Element or Species objects. ii. List of dict of elements/species and occupancies, e.g., [{"Fe" : 0.5, "Mn":0.5}, ...]. This allows the setup of disordered structures. coords (Nx3 array): list of fractional/cartesian coordinates of each species. miller_index ([h, k, l]): Miller index of plane parallel to surface. Note that this is referenced to the input structure. If you need this to be based on the conventional cell, you should supply the conventional structure. oriented_unit_cell (Structure): The oriented_unit_cell from which this Slab is created (by scaling in the c-direction). shift (float): The shift in the c-direction applied to get the termination. scale_factor (np.ndarray): scale_factor Final computed scale factor that brings the parent cell to the surface cell. reorient_lattice (bool): reorients the lattice parameters such that the c direction is along the z axis. validate_proximity (bool): Whether to check if there are sites that are less than 0.01 Ang apart. Defaults to False. reconstruction (str): Type of reconstruction. Defaults to None if the slab is not reconstructed. coords_are_cartesian (bool): Set to True if you are providing coordinates in cartesian coordinates. Defaults to False. site_properties (dict): Properties associated with the sites as a dict of sequences, e.g., {"magmom":[5,5,5,5]}. The sequences have to be the same length as the atomic species and fractional_coords. Defaults to None for no properties. energy (float): A value for the energy. """ self.oriented_unit_cell = oriented_unit_cell self.miller_index = tuple(miller_index) self.shift = shift self.reconstruction = reconstruction self.scale_factor = np.array(scale_factor) self.energy = energy self.reorient_lattice = reorient_lattice if self.reorient_lattice: if coords_are_cartesian: coords = lattice.get_fractional_coords(coords) coords_are_cartesian = False lattice = Lattice.from_parameters( lattice.a, lattice.b, lattice.c, lattice.alpha, lattice.beta, lattice.gamma, ) super().__init__( lattice, species, coords, validate_proximity=validate_proximity, to_unit_cell=to_unit_cell, coords_are_cartesian=coords_are_cartesian, site_properties=site_properties, ) def get_orthogonal_c_slab(self): """ This method returns a Slab where the normal (c lattice vector) is "forced" to be exactly orthogonal to the surface a and b lattice vectors. **Note that this breaks inherent symmetries in the slab.** It should be pointed out that orthogonality is not required to get good surface energies, but it can be useful in cases where the slabs are subsequently used for postprocessing of some kind, e.g. generating GBs or interfaces. """ a, b, c = self.lattice.matrix new_c = np.cross(a, b) new_c /= np.linalg.norm(new_c) new_c = np.dot(c, new_c) * new_c new_latt = Lattice([a, b, new_c]) return Slab( lattice=new_latt, species=self.species_and_occu, coords=self.cart_coords, miller_index=self.miller_index, oriented_unit_cell=self.oriented_unit_cell, shift=self.shift, scale_factor=self.scale_factor, coords_are_cartesian=True, energy=self.energy, reorient_lattice=self.reorient_lattice, site_properties=self.site_properties, ) def get_tasker2_slabs(self, tol=0.01, same_species_only=True): """ Get a list of slabs that have been Tasker 2 corrected. Args: tol (float): Tolerance to determine if atoms are within same plane. This is a fractional tolerance, not an absolute one. same_species_only (bool): If True, only that are of the exact same species as the atom at the outermost surface are considered for moving. Otherwise, all atoms regardless of species that is within tol are considered for moving. Default is True (usually the desired behavior). Returns: ([Slab]) List of tasker 2 corrected slabs. """ sites = list(self.sites) slabs = [] sortedcsites = sorted(sites, key=lambda site: site.c) # Determine what fraction the slab is of the total cell size in the # c direction. Round to nearest rational number. nlayers_total = int(round(self.lattice.c / self.oriented_unit_cell.lattice.c)) nlayers_slab = int(round((sortedcsites[-1].c - sortedcsites[0].c) * nlayers_total)) slab_ratio = nlayers_slab / nlayers_total a = SpacegroupAnalyzer(self) symm_structure = a.get_symmetrized_structure() def equi_index(site): for i, equi_sites in enumerate(symm_structure.equivalent_sites): if site in equi_sites: return i raise ValueError("Cannot determine equi index!") for surface_site, shift in [ (sortedcsites[0], slab_ratio), (sortedcsites[-1], -slab_ratio), ]: tomove = [] fixed = [] for site in sites: if abs(site.c - surface_site.c) < tol and ( (not same_species_only) or site.species == surface_site.species ): tomove.append(site) else: fixed.append(site) # Sort and group the sites by the species and symmetry equivalence tomove = sorted(tomove, key=lambda s: equi_index(s)) grouped = [list(sites) for k, sites in itertools.groupby(tomove, key=lambda s: equi_index(s))] if len(tomove) == 0 or any(len(g) % 2 != 0 for g in grouped): warnings.warn( "Odd number of sites to divide! Try changing " "the tolerance to ensure even division of " "sites or create supercells in a or b directions " "to allow for atoms to be moved!" ) continue combinations = [] for g in grouped: combinations.append(list(itertools.combinations(g, int(len(g) / 2)))) for selection in itertools.product(*combinations): species = [site.species for site in fixed] fcoords = [site.frac_coords for site in fixed] for s in tomove: species.append(s.species) for group in selection: if s in group: fcoords.append(s.frac_coords) break else: # Move unselected atom to the opposite surface. fcoords.append(s.frac_coords + [0, 0, shift]) # sort by species to put all similar species together. sp_fcoord = sorted(zip(species, fcoords), key=lambda x: x[0]) species = [x[0] for x in sp_fcoord] fcoords = [x[1] for x in sp_fcoord] slab = Slab( self.lattice, species, fcoords, self.miller_index, self.oriented_unit_cell, self.shift, self.scale_factor, energy=self.energy, reorient_lattice=self.reorient_lattice, ) slabs.append(slab) s = StructureMatcher() unique = [ss[0] for ss in s.group_structures(slabs)] return unique def is_symmetric(self, symprec=0.1): """ Checks if slab is symmetric, i.e., contains inversion symmetry. Args: symprec (float): Symmetry precision used for SpaceGroup analyzer. Returns: (bool) Whether slab contains inversion symmetry. """ sg = SpacegroupAnalyzer(self, symprec=symprec) return sg.is_laue() def get_sorted_structure(self, key=None, reverse=False): """ Get a sorted copy of the structure. The parameters have the same meaning as in list.sort. By default, sites are sorted by the electronegativity of the species. Note that Slab has to override this because of the different __init__ args. Args: key: Specifies a function of one argument that is used to extract a comparison key from each list element: key=str.lower. The default value is None (compare the elements directly). reverse (bool): If set to True, then the list elements are sorted as if each comparison were reversed. """ sites = sorted(self, key=key, reverse=reverse) s = Structure.from_sites(sites) return Slab( s.lattice, s.species_and_occu, s.frac_coords, self.miller_index, self.oriented_unit_cell, self.shift, self.scale_factor, site_properties=s.site_properties, reorient_lattice=self.reorient_lattice, ) def copy(self, site_properties=None, sanitize=False): """ Convenience method to get a copy of the structure, with options to add site properties. Args: site_properties (dict): Properties to add or override. The properties are specified in the same way as the constructor, i.e., as a dict of the form {property: [values]}. The properties should be in the order of the *original* structure if you are performing sanitization. sanitize (bool): If True, this method will return a sanitized structure. Sanitization performs a few things: (i) The sites are sorted by electronegativity, (ii) a LLL lattice reduction is carried out to obtain a relatively orthogonalized cell, (iii) all fractional coords for sites are mapped into the unit cell. Returns: A copy of the Structure, with optionally new site_properties and optionally sanitized. """ props = self.site_properties if site_properties: props.update(site_properties) return Slab( self.lattice, self.species_and_occu, self.frac_coords, self.miller_index, self.oriented_unit_cell, self.shift, self.scale_factor, site_properties=props, reorient_lattice=self.reorient_lattice, ) @property def dipole(self): """ Calculates the dipole of the Slab in the direction of the surface normal. Note that the Slab must be oxidation state-decorated for this to work properly. Otherwise, the Slab will always have a dipole of 0. """ dipole = np.zeros(3) mid_pt = np.sum(self.cart_coords, axis=0) / len(self) normal = self.normal for site in self: charge = sum([getattr(sp, "oxi_state", 0) * amt for sp, amt in site.species.items()]) dipole += charge * np.dot(site.coords - mid_pt, normal) * normal return dipole def is_polar(self, tol_dipole_per_unit_area=1e-3): """ Checks whether the surface is polar by computing the dipole per unit area. Note that the Slab must be oxidation state-decorated for this to work properly. Otherwise, the Slab will always be non-polar. Args: tol_dipole_per_unit_area (float): A tolerance. If the dipole magnitude per unit area is less than this value, the Slab is considered non-polar. Defaults to 1e-3, which is usually pretty good. Normalized dipole per unit area is used as it is more reliable than using the total, which tends to be larger for slabs with larger surface areas. """ dip_per_unit_area = self.dipole / self.surface_area return np.linalg.norm(dip_per_unit_area) > tol_dipole_per_unit_area @property def normal(self): """ Calculates the surface normal vector of the slab """ normal = np.cross(self.lattice.matrix[0], self.lattice.matrix[1]) normal /= np.linalg.norm(normal) return normal @property def surface_area(self): """ Calculates the surface area of the slab """ m = self.lattice.matrix return np.linalg.norm(np.cross(m[0], m[1])) @property def center_of_mass(self): """ Calculates the center of mass of the slab """ weights = [s.species.weight for s in self] center_of_mass = np.average(self.frac_coords, weights=weights, axis=0) return center_of_mass def add_adsorbate_atom(self, indices, specie, distance): """ Gets the structure of single atom adsorption. slab structure from the Slab class(in [0, 0, 1]) Args: indices ([int]): Indices of sites on which to put the absorbate. Absorbed atom will be displaced relative to the center of these sites. specie (Species/Element/str): adsorbed atom species distance (float): between centers of the adsorbed atom and the given site in Angstroms. """ # Let's do the work in cartesian coords center = np.sum([self[i].coords for i in indices], axis=0) / len(indices) coords = center + self.normal * distance / np.linalg.norm(self.normal) self.append(specie, coords, coords_are_cartesian=True) def __str__(self): comp = self.composition outs = [ "Slab Summary (%s)" % comp.formula, "Reduced Formula: %s" % comp.reduced_formula, "Miller index: %s" % (self.miller_index,), "Shift: %.4f, Scale Factor: %s" % (self.shift, self.scale_factor.__str__()), ] def to_s(x): return "%0.6f" % x outs.append("abc : " + " ".join([to_s(i).rjust(10) for i in self.lattice.abc])) outs.append("angles: " + " ".join([to_s(i).rjust(10) for i in self.lattice.angles])) outs.append("Sites ({i})".format(i=len(self))) for i, site in enumerate(self): outs.append( " ".join( [ str(i + 1), site.species_string, " ".join([to_s(j).rjust(12) for j in site.frac_coords]), ] ) ) return "\n".join(outs) def as_dict(self): """ :return: MSONAble dict """ d = super().as_dict() d["@module"] = self.__class__.__module__ d["@class"] = self.__class__.__name__ d["oriented_unit_cell"] = self.oriented_unit_cell.as_dict() d["miller_index"] = self.miller_index d["shift"] = self.shift d["scale_factor"] = self.scale_factor.tolist() d["reconstruction"] = self.reconstruction d["energy"] = self.energy return d @classmethod def from_dict(cls, d): """ :param d: dict :return: Creates slab from dict. """ lattice = Lattice.from_dict(d["lattice"]) sites = [PeriodicSite.from_dict(sd, lattice) for sd in d["sites"]] s = Structure.from_sites(sites) return Slab( lattice=lattice, species=s.species_and_occu, coords=s.frac_coords, miller_index=d["miller_index"], oriented_unit_cell=Structure.from_dict(d["oriented_unit_cell"]), shift=d["shift"], scale_factor=d["scale_factor"], site_properties=s.site_properties, energy=d["energy"], ) def get_surface_sites(self, tag=False): """ Returns the surface sites and their indices in a dictionary. The oriented unit cell of the slab will determine the coordination number of a typical site. We use VoronoiNN to determine the coordination number of bulk sites and slab sites. Due to the pathological error resulting from some surface sites in the VoronoiNN, we assume any site that has this error is a surface site as well. This will work for elemental systems only for now. Useful for analysis involving broken bonds and for finding adsorption sites. Args: tag (bool): Option to adds site attribute "is_surfsite" (bool) to all sites of slab. Defaults to False Returns: A dictionary grouping sites on top and bottom of the slab together. {"top": [sites with indices], "bottom": [sites with indices} TODO: Is there a way to determine site equivalence between sites in a slab and bulk system? This would allow us get the coordination number of a specific site for multi-elemental systems or systems with more than one unequivalent site. This will allow us to use this for compound systems. """ from pymatgen.analysis.local_env import VoronoiNN # Get a dictionary of coordination numbers # for each distinct site in the structure a = SpacegroupAnalyzer(self.oriented_unit_cell) ucell = a.get_symmetrized_structure() cn_dict = {} v = VoronoiNN() unique_indices = [equ[0] for equ in ucell.equivalent_indices] for i in unique_indices: el = ucell[i].species_string if el not in cn_dict.keys(): cn_dict[el] = [] # Since this will get the cn as a result of the weighted polyhedra, the # slightest difference in cn will indicate a different environment for a # species, eg. bond distance of each neighbor or neighbor species. The # decimal place to get some cn to be equal. cn = v.get_cn(ucell, i, use_weights=True) cn = float("%.5f" % (round(cn, 5))) if cn not in cn_dict[el]: cn_dict[el].append(cn) v = VoronoiNN() surf_sites_dict, properties = {"top": [], "bottom": []}, [] for i, site in enumerate(self): # Determine if site is closer to the top or bottom of the slab top = site.frac_coords[2] > self.center_of_mass[2] try: # A site is a surface site, if its environment does # not fit the environment of other sites cn = float("%.5f" % (round(v.get_cn(self, i, use_weights=True), 5))) if cn < min(cn_dict[site.species_string]): properties.append(True) key = "top" if top else "bottom" surf_sites_dict[key].append([site, i]) else: properties.append(False) except RuntimeError: # or if pathological error is returned, indicating a surface site properties.append(True) key = "top" if top else "bottom" surf_sites_dict[key].append([site, i]) if tag: self.add_site_property("is_surf_site", properties) return surf_sites_dict def have_equivalent_surfaces(self): """ Check if we have same number of equivalent sites on both surfaces. This is an alternative to checking Laue symmetry (is_symmetric()) if we want to ensure both surfaces in the slab are the same """ # tag the sites as either surface sites or not self.get_surface_sites(tag=True) a = SpacegroupAnalyzer(self) symm_structure = a.get_symmetrized_structure() # ensure each site on one surface has a # corresponding equivalent site on the other equal_surf_sites = [] for equ in symm_structure.equivalent_sites: # Top and bottom are arbitrary, we will just determine # if one site is on one side of the slab or the other top, bottom = 0, 0 for s in equ: if s.is_surf_site: if s.frac_coords[2] > self.center_of_mass[2]: top += 1 else: bottom += 1 # Check to see if the number of equivalent sites # on one side of the slab are equal to the other equal_surf_sites.append(top == bottom) return all(equal_surf_sites) def get_symmetric_site(self, point, cartesian=False): """ This method uses symmetry operations to find equivalent sites on both sides of the slab. Works mainly for slabs with Laue symmetry. This is useful for retaining the non-polar and symmetric properties of a slab when creating adsorbed structures or symmetric reconstructions. Arg: point: Fractional coordinate. Returns: point: Fractional coordinate. A point equivalent to the parameter point, but on the other side of the slab """ sg = SpacegroupAnalyzer(self) ops = sg.get_symmetry_operations(cartesian=cartesian) # Each operation on a point will return an equivalent point. # We want to find the point on the other side of the slab. for op in ops: slab = self.copy() site2 = op.operate(point) if "%.6f" % (site2[2]) == "%.6f" % (point[2]): continue # Add dummy site to check the overall structure is symmetric slab.append("O", point, coords_are_cartesian=cartesian) slab.append("O", site2, coords_are_cartesian=cartesian) sg = SpacegroupAnalyzer(slab) if sg.is_laue(): break # If not symmetric, remove the two added # sites and try another symmetry operator slab.remove_sites([len(slab) - 1]) slab.remove_sites([len(slab) - 1]) return site2 def symmetrically_add_atom(self, specie, point, coords_are_cartesian=False): """ Class method for adding a site at a specified point in a slab. Will add the corresponding site on the other side of the slab to maintain equivalent surfaces. Arg: specie (str): The specie to add point (coords): The coordinate of the site in the slab to add. coords_are_cartesian (bool): Is the point in cartesian coordinates Returns: (Slab): The modified slab """ # For now just use the species of the # surface atom as the element to add # Get the index of the corresponding site at the bottom point2 = self.get_symmetric_site(point, cartesian=coords_are_cartesian) self.append(specie, point, coords_are_cartesian=coords_are_cartesian) self.append(specie, point2, coords_are_cartesian=coords_are_cartesian) def symmetrically_remove_atoms(self, indices): """ Class method for removing sites corresponding to a list of indices. Will remove the corresponding site on the other side of the slab to maintain equivalent surfaces. Arg: indices ([indices]): The indices of the sites in the slab to remove. """ slabcopy = SpacegroupAnalyzer(self.copy()).get_symmetrized_structure() points = [slabcopy[i].frac_coords for i in indices] removal_list = [] for pt in points: # Get the index of the original site on top cart_point = slabcopy.lattice.get_cartesian_coords(pt) dist = [site.distance_from_point(cart_point) for site in slabcopy] site1 = dist.index(min(dist)) # Get the index of the corresponding site at the bottom for i, eq_sites in enumerate(slabcopy.equivalent_sites): if slabcopy[site1] in eq_sites: eq_indices = slabcopy.equivalent_indices[i] break i1 = eq_indices[eq_sites.index(slabcopy[site1])] for i2 in eq_indices: if i2 == i1: continue if slabcopy[i2].frac_coords[2] == slabcopy[i1].frac_coords[2]: continue # Test site remove to see if it results in symmetric slab s = self.copy() s.remove_sites([i1, i2]) if s.is_symmetric(): removal_list.extend([i1, i2]) break # If expected, 2 atoms are removed per index if len(removal_list) == 2 * len(indices): self.remove_sites(removal_list) else: warnings.warn("Equivalent sites could not be found for removal for all indices. Surface unchanged.") class SlabGenerator: """ This class generates different slabs using shift values determined by where a unique termination can be found along with other criterias such as where a termination doesn't break a polyhedral bond. The shift value then indicates where the slab layer will begin and terminate in the slab-vacuum system. .. attribute:: oriented_unit_cell A unit cell of the parent structure with the miller index of plane parallel to surface .. attribute:: parent Parent structure from which Slab was derived. .. attribute:: lll_reduce Whether or not the slabs will be orthogonalized .. attribute:: center_slab Whether or not the slabs will be centered between the vacuum layer .. attribute:: slab_scale_factor Final computed scale factor that brings the parent cell to the surface cell. .. attribute:: miller_index Miller index of plane parallel to surface. .. attribute:: min_slab_size Minimum size in angstroms of layers containing atoms .. attribute:: min_vac_size Minimize size in angstroms of layers containing vacuum """ def __init__( self, initial_structure, miller_index, min_slab_size, min_vacuum_size, lll_reduce=False, center_slab=False, in_unit_planes=False, primitive=True, max_normal_search=None, reorient_lattice=True, ): """ Calculates the slab scale factor and uses it to generate a unit cell of the initial structure that has been oriented by its miller index. Also stores the initial information needed later on to generate a slab. Args: initial_structure (Structure): Initial input structure. Note that to ensure that the miller indices correspond to usual crystallographic definitions, you should supply a conventional unit cell structure. miller_index ([h, k, l]): Miller index of plane parallel to surface. Note that this is referenced to the input structure. If you need this to be based on the conventional cell, you should supply the conventional structure. min_slab_size (float): In Angstroms or number of hkl planes min_vacuum_size (float): In Angstroms or number of hkl planes lll_reduce (bool): Whether to perform an LLL reduction on the eventual structure. center_slab (bool): Whether to center the slab in the cell with equal vacuum spacing from the top and bottom. in_unit_planes (bool): Whether to set min_slab_size and min_vac_size in units of hkl planes (True) or Angstrom (False/default). Setting in units of planes is useful for ensuring some slabs have a certain nlayer of atoms. e.g. for Cs (100), a 10 Ang slab will result in a slab with only 2 layer of atoms, whereas Fe (100) will have more layer of atoms. By using units of hkl planes instead, we ensure both slabs have the same number of atoms. The slab thickness will be in min_slab_size/math.ceil(self._proj_height/dhkl) multiples of oriented unit cells. primitive (bool): Whether to reduce any generated slabs to a primitive cell (this does **not** mean the slab is generated from a primitive cell, it simply means that after slab generation, we attempt to find shorter lattice vectors, which lead to less surface area and smaller cells). max_normal_search (int): If set to a positive integer, the code will conduct a search for a normal lattice vector that is as perpendicular to the surface as possible by considering multiples linear combinations of lattice vectors up to max_normal_search. This has no bearing on surface energies, but may be useful as a preliminary step to generating slabs for absorption and other sizes. It is typical that this will not be the smallest possible cell for simulation. Normality is not guaranteed, but the oriented cell will have the c vector as normal as possible (within the search range) to the surface. A value of up to the max absolute Miller index is usually sufficient. reorient_lattice (bool): reorients the lattice parameters such that the c direction is the third vector of the lattice matrix """ # pylint: disable=E1130 # Add Wyckoff symbols of the bulk, will help with # identfying types of sites in the slab system sg = SpacegroupAnalyzer(initial_structure) initial_structure.add_site_property("bulk_wyckoff", sg.get_symmetry_dataset()["wyckoffs"]) initial_structure.add_site_property("bulk_equivalent", sg.get_symmetry_dataset()["equivalent_atoms"].tolist()) latt = initial_structure.lattice miller_index = _reduce_vector(miller_index) # Calculate the surface normal using the reciprocal lattice vector. recp = latt.reciprocal_lattice_crystallographic normal = recp.get_cartesian_coords(miller_index) normal /= np.linalg.norm(normal) slab_scale_factor = [] non_orth_ind = [] eye = np.eye(3, dtype=np.int_) for i, j in enumerate(miller_index): if j == 0: # Lattice vector is perpendicular to surface normal, i.e., # in plane of surface. We will simply choose this lattice # vector as one of the basis vectors. slab_scale_factor.append(eye[i]) else: # Calculate projection of lattice vector onto surface normal. d = abs(np.dot(normal, latt.matrix[i])) / latt.abc[i] non_orth_ind.append((i, d)) # We want the vector that has maximum magnitude in the # direction of the surface normal as the c-direction. # Results in a more "orthogonal" unit cell. c_index, dist = max(non_orth_ind, key=lambda t: t[1]) if len(non_orth_ind) > 1: lcm_miller = lcm(*[miller_index[i] for i, d in non_orth_ind]) for (i, di), (j, dj) in itertools.combinations(non_orth_ind, 2): l = [0, 0, 0] l[i] = -int(round(lcm_miller / miller_index[i])) l[j] = int(round(lcm_miller / miller_index[j])) slab_scale_factor.append(l) if len(slab_scale_factor) == 2: break if max_normal_search is None: slab_scale_factor.append(eye[c_index]) else: index_range = sorted( reversed(range(-max_normal_search, max_normal_search + 1)), key=lambda x: abs(x), ) candidates = [] for uvw in itertools.product(index_range, index_range, index_range): if (not any(uvw)) or abs(np.linalg.det(slab_scale_factor + [uvw])) < 1e-8: continue vec = latt.get_cartesian_coords(uvw) l = np.linalg.norm(vec) cosine = abs(np.dot(vec, normal) / l) candidates.append((uvw, cosine, l)) if abs(abs(cosine) - 1) < 1e-8: # If cosine of 1 is found, no need to search further. break # We want the indices with the maximum absolute cosine, # but smallest possible length. uvw, cosine, l = max(candidates, key=lambda x: (x[1], -x[2])) slab_scale_factor.append(uvw) slab_scale_factor = np.array(slab_scale_factor) # Let's make sure we have a left-handed crystallographic system if np.linalg.det(slab_scale_factor) < 0: slab_scale_factor *= -1 # Make sure the slab_scale_factor is reduced to avoid # unnecessarily large slabs reduced_scale_factor = [_reduce_vector(v) for v in slab_scale_factor] slab_scale_factor = np.array(reduced_scale_factor) single = initial_structure.copy() single.make_supercell(slab_scale_factor) # When getting the OUC, lets return the most reduced # structure as possible to reduce calculations self.oriented_unit_cell = Structure.from_sites(single, to_unit_cell=True) self.max_normal_search = max_normal_search self.parent = initial_structure self.lll_reduce = lll_reduce self.center_slab = center_slab self.slab_scale_factor = slab_scale_factor self.miller_index = miller_index self.min_vac_size = min_vacuum_size self.min_slab_size = min_slab_size self.in_unit_planes = in_unit_planes self.primitive = primitive self._normal = normal a, b, c = self.oriented_unit_cell.lattice.matrix self._proj_height = abs(np.dot(normal, c)) self.reorient_lattice = reorient_lattice def get_slab(self, shift=0, tol=0.1, energy=None): """ This method takes in shift value for the c lattice direction and generates a slab based on the given shift. You should rarely use this method. Instead, it is used by other generation algorithms to obtain all slabs. Arg: shift (float): A shift value in Angstrom that determines how much a slab should be shifted. tol (float): Tolerance to determine primitive cell. energy (float): An energy to assign to the slab. Returns: (Slab) A Slab object with a particular shifted oriented unit cell. """ h = self._proj_height p = round(h / self.parent.lattice.d_hkl(self.miller_index), 8) if self.in_unit_planes: nlayers_slab = int(math.ceil(self.min_slab_size / p)) nlayers_vac = int(math.ceil(self.min_vac_size / p)) else: nlayers_slab = int(math.ceil(self.min_slab_size / h)) nlayers_vac = int(math.ceil(self.min_vac_size / h)) nlayers = nlayers_slab + nlayers_vac species = self.oriented_unit_cell.species_and_occu props = self.oriented_unit_cell.site_properties props = {k: v * nlayers_slab for k, v in props.items()} frac_coords = self.oriented_unit_cell.frac_coords frac_coords = np.array(frac_coords) + np.array([0, 0, -shift])[None, :] frac_coords -= np.floor(frac_coords) a, b, c = self.oriented_unit_cell.lattice.matrix new_lattice = [a, b, nlayers * c] frac_coords[:, 2] = frac_coords[:, 2] / nlayers all_coords = [] for i in range(nlayers_slab): fcoords = frac_coords.copy() fcoords[:, 2] += i / nlayers all_coords.extend(fcoords) slab = Structure(new_lattice, species * nlayers_slab, all_coords, site_properties=props) scale_factor = self.slab_scale_factor # Whether or not to orthogonalize the structure if self.lll_reduce: lll_slab = slab.copy(sanitize=True) mapping = lll_slab.lattice.find_mapping(slab.lattice) scale_factor = np.dot(mapping[2], scale_factor) slab = lll_slab # Whether or not to center the slab layer around the vacuum if self.center_slab: avg_c = np.average([c[2] for c in slab.frac_coords]) slab.translate_sites(list(range(len(slab))), [0, 0, 0.5 - avg_c]) if self.primitive: prim = slab.get_primitive_structure(tolerance=tol) if energy is not None: energy = prim.volume / slab.volume * energy slab = prim # Reorient the lattice to get the correct reduced cell ouc = self.oriented_unit_cell.copy() if self.primitive: # find a reduced ouc slab_l = slab.lattice ouc = ouc.get_primitive_structure( constrain_latt={ "a": slab_l.a, "b": slab_l.b, "alpha": slab_l.alpha, "beta": slab_l.beta, "gamma": slab_l.gamma, } ) # Check this is the correct oriented unit cell ouc = self.oriented_unit_cell if slab_l.a != ouc.lattice.a or slab_l.b != ouc.lattice.b else ouc return Slab( slab.lattice, slab.species_and_occu, slab.frac_coords, self.miller_index, ouc, shift, scale_factor, energy=energy, site_properties=slab.site_properties, reorient_lattice=self.reorient_lattice, ) def _calculate_possible_shifts(self, tol=0.1): frac_coords = self.oriented_unit_cell.frac_coords n = len(frac_coords) if n == 1: # Clustering does not work when there is only one data point. shift = frac_coords[0][2] + 0.5 return [shift - math.floor(shift)] # We cluster the sites according to the c coordinates. But we need to # take into account PBC. Let's compute a fractional c-coordinate # distance matrix that accounts for PBC. dist_matrix = np.zeros((n, n)) h = self._proj_height # Projection of c lattice vector in # direction of surface normal. for i, j in itertools.combinations(list(range(n)), 2): if i != j: cdist = frac_coords[i][2] - frac_coords[j][2] cdist = abs(cdist - round(cdist)) * h dist_matrix[i, j] = cdist dist_matrix[j, i] = cdist condensed_m = squareform(dist_matrix) z = linkage(condensed_m) clusters = fcluster(z, tol, criterion="distance") # Generate dict of cluster# to c val - doesn't matter what the c is. c_loc = {c: frac_coords[i][2] for i, c in enumerate(clusters)} # Put all c into the unit cell. possible_c = [c - math.floor(c) for c in sorted(c_loc.values())] # Calculate the shifts nshifts = len(possible_c) shifts = [] for i in range(nshifts): if i == nshifts - 1: # There is an additional shift between the first and last c # coordinate. But this needs special handling because of PBC. shift = (possible_c[0] + 1 + possible_c[i]) * 0.5 if shift > 1: shift -= 1 else: shift = (possible_c[i] + possible_c[i + 1]) * 0.5 shifts.append(shift - math.floor(shift)) shifts = sorted(shifts) return shifts def _get_c_ranges(self, bonds): c_ranges = [] bonds = {(get_el_sp(s1), get_el_sp(s2)): dist for (s1, s2), dist in bonds.items()} for (sp1, sp2), bond_dist in bonds.items(): for site in self.oriented_unit_cell: if sp1 in site.species: for nn in self.oriented_unit_cell.get_neighbors(site, bond_dist): if sp2 in nn.species: c_range = tuple(sorted([site.frac_coords[2], nn.frac_coords[2]])) if c_range[1] > 1: # Takes care of PBC when c coordinate of site # goes beyond the upper boundary of the cell c_ranges.append((c_range[0], 1)) c_ranges.append((0, c_range[1] - 1)) elif c_range[0] < 0: # Takes care of PBC when c coordinate of site # is below the lower boundary of the unit cell c_ranges.append((0, c_range[1])) c_ranges.append((c_range[0] + 1, 1)) elif c_range[0] != c_range[1]: c_ranges.append((c_range[0], c_range[1])) return c_ranges def get_slabs( self, bonds=None, ftol=0.1, tol=0.1, max_broken_bonds=0, symmetrize=False, repair=False, ): """ This method returns a list of slabs that are generated using the list of shift values from the method, _calculate_possible_shifts(). Before the shifts are used to create the slabs however, if the user decides to take into account whether or not a termination will break any polyhedral structure (bonds is not None), this method will filter out any shift values that do so. Args: bonds ({(specie1, specie2): max_bond_dist}: bonds are specified as a dict of tuples: float of specie1, specie2 and the max bonding distance. For example, PO4 groups may be defined as {("P", "O"): 3}. tol (float): General tolerance paramter for getting primitive cells and matching structures ftol (float): Threshold parameter in fcluster in order to check if two atoms are lying on the same plane. Default thresh set to 0.1 Angstrom in the direction of the surface normal. max_broken_bonds (int): Maximum number of allowable broken bonds for the slab. Use this to limit # of slabs (some structures may have a lot of slabs). Defaults to zero, which means no defined bonds must be broken. symmetrize (bool): Whether or not to ensure the surfaces of the slabs are equivalent. repair (bool): Whether to repair terminations with broken bonds or just omit them. Set to False as repairing terminations can lead to many possible slabs as oppose to just omitting them. Returns: ([Slab]) List of all possible terminations of a particular surface. Slabs are sorted by the # of bonds broken. """ c_ranges = [] if bonds is None else self._get_c_ranges(bonds) slabs = [] for shift in self._calculate_possible_shifts(tol=ftol): bonds_broken = 0 for r in c_ranges: if r[0] <= shift <= r[1]: bonds_broken += 1 slab = self.get_slab(shift, tol=tol, energy=bonds_broken) if bonds_broken <= max_broken_bonds: slabs.append(slab) elif repair: # If the number of broken bonds is exceeded, # we repair the broken bonds on the slab slabs.append(self.repair_broken_bonds(slab, bonds)) # Further filters out any surfaces made that might be the same m = StructureMatcher(ltol=tol, stol=tol, primitive_cell=False, scale=False) new_slabs = [] for g in m.group_structures(slabs): # For each unique termination, symmetrize the # surfaces by removing sites from the bottom. if symmetrize: slabs = self.nonstoichiometric_symmetrized_slab(g[0]) new_slabs.extend(slabs) else: new_slabs.append(g[0]) match = StructureMatcher(ltol=tol, stol=tol, primitive_cell=False, scale=False) new_slabs = [g[0] for g in match.group_structures(new_slabs)] return sorted(new_slabs, key=lambda s: s.energy) def repair_broken_bonds(self, slab, bonds): """ This method will find undercoordinated atoms due to slab cleaving specified by the bonds parameter and move them to the other surface to make sure the bond is kept intact. In a future release of surface.py, the ghost_sites will be used to tell us how the repair bonds should look like. Arg: slab (structure): A structure object representing a slab. bonds ({(specie1, specie2): max_bond_dist}: bonds are specified as a dict of tuples: float of specie1, specie2 and the max bonding distance. For example, PO4 groups may be defined as {("P", "O"): 3}. Returns: (Slab) A Slab object with a particular shifted oriented unit cell. """ for pair in bonds.keys(): blength = bonds[pair] # First lets determine which element should be the # reference (center element) to determine broken bonds. # e.g. P for a PO4 bond. Find integer coordination # numbers of the pair of elements wrt to each other cn_dict = {} for i, el in enumerate(pair): cnlist = [] for site in self.oriented_unit_cell: poly_coord = 0 if site.species_string == el: for nn in self.oriented_unit_cell.get_neighbors(site, blength): if nn[0].species_string == pair[i - 1]: poly_coord += 1 cnlist.append(poly_coord) cn_dict[el] = cnlist # We make the element with the higher coordination our reference if max(cn_dict[pair[0]]) > max(cn_dict[pair[1]]): element1, element2 = pair else: element2, element1 = pair for i, site in enumerate(slab): # Determine the coordination of our reference if site.species_string == element1: poly_coord = 0 for neighbor in slab.get_neighbors(site, blength): poly_coord += 1 if neighbor.species_string == element2 else 0 # suppose we find an undercoordinated reference atom if poly_coord not in cn_dict[element1]: # We get the reference atom of the broken bonds # (undercoordinated), move it to the other surface slab = self.move_to_other_side(slab, [i]) # find its NNs with the corresponding # species it should be coordinated with neighbors = slab.get_neighbors(slab[i], blength, include_index=True) tomove = [nn[2] for nn in neighbors if nn[0].species_string == element2] tomove.append(i) # and then move those NNs along with the central # atom back to the other side of the slab again slab = self.move_to_other_side(slab, tomove) return slab def move_to_other_side(self, init_slab, index_of_sites): """ This method will Move a set of sites to the other side of the slab (opposite surface). Arg: init_slab (structure): A structure object representing a slab. index_of_sites (list of ints): The list of indices representing the sites we want to move to the other side. Returns: (Slab) A Slab object with a particular shifted oriented unit cell. """ slab = init_slab.copy() # Determine what fraction the slab is of the total cell size # in the c direction. Round to nearest rational number. h = self._proj_height p = h / self.parent.lattice.d_hkl(self.miller_index) if self.in_unit_planes: nlayers_slab = int(math.ceil(self.min_slab_size / p)) nlayers_vac = int(math.ceil(self.min_vac_size / p)) else: nlayers_slab = int(math.ceil(self.min_slab_size / h)) nlayers_vac = int(math.ceil(self.min_vac_size / h)) nlayers = nlayers_slab + nlayers_vac slab_ratio = nlayers_slab / nlayers # Sort the index of sites based on which side they are on top_site_index = [i for i in index_of_sites if slab[i].frac_coords[2] > slab.center_of_mass[2]] bottom_site_index = [i for i in index_of_sites if slab[i].frac_coords[2] < slab.center_of_mass[2]] # Translate sites to the opposite surfaces slab.translate_sites(top_site_index, [0, 0, slab_ratio]) slab.translate_sites(bottom_site_index, [0, 0, -slab_ratio]) return Slab( init_slab.lattice, slab.species, slab.frac_coords, init_slab.miller_index, init_slab.oriented_unit_cell, init_slab.shift, init_slab.scale_factor, energy=init_slab.energy, ) def nonstoichiometric_symmetrized_slab(self, init_slab, tol=1e-3): """ This method checks whether or not the two surfaces of the slab are equivalent. If the point group of the slab has an inversion symmetry ( ie. belong to one of the Laue groups), then it is assumed that the surfaces should be equivalent. Otherwise, sites at the bottom of the slab will be removed until the slab is symmetric. Note the removal of sites can destroy the stoichiometry of the slab. For non-elemental structures, the chemical potential will be needed to calculate surface energy. Arg: init_slab (Structure): A single slab structure tol (float): Tolerance for SpaceGroupanalyzer. Returns: Slab (structure): A symmetrized Slab object. """ sg = SpacegroupAnalyzer(init_slab, symprec=tol) if sg.is_laue(): return [init_slab] nonstoich_slabs = [] # Build an equivalent surface slab for each of the different surfaces for top in [True, False]: asym = True slab = init_slab.copy() slab.energy = init_slab.energy while asym: # Keep removing sites from the bottom one by one until both # surfaces are symmetric or the number of sites removed has # exceeded 10 percent of the original slab c_dir = [site[2] for i, site in enumerate(slab.frac_coords)] if top: slab.remove_sites([c_dir.index(max(c_dir))]) else: slab.remove_sites([c_dir.index(min(c_dir))]) if len(slab) <= len(self.parent): break # Check if the altered surface is symmetric sg = SpacegroupAnalyzer(slab, symprec=tol) if sg.is_laue(): asym = False nonstoich_slabs.append(slab) if len(slab) <= len(self.parent): warnings.warn("Too many sites removed, please use a larger slab " "size.") return nonstoich_slabs module_dir = os.path.dirname(os.path.abspath(__file__)) with open(os.path.join(module_dir, "reconstructions_archive.json")) as data_file: reconstructions_archive = json.load(data_file) class ReconstructionGenerator: """ This class takes in a pre-defined dictionary specifying the parameters need to build a reconstructed slab such as the SlabGenerator parameters, transformation matrix, sites to remove/add and slab/vacuum size. It will then use the formatted instructions provided by the dictionary to build the desired reconstructed slab from the initial structure. .. attribute:: slabgen_params Parameters for the SlabGenerator .. trans_matrix:: A 3x3 transformation matrix to generate the reconstructed slab. Only the a and b lattice vectors are actually changed while the c vector remains the same. This matrix is what the Wood's notation is based on. .. reconstruction_json:: The full json or dictionary containing the instructions for building the reconstructed slab .. termination:: The index of the termination of the slab TODO: - Right now there is no way to specify what atom is being added. In the future, use basis sets? """ def __init__(self, initial_structure, min_slab_size, min_vacuum_size, reconstruction_name): """ Generates reconstructed slabs from a set of instructions specified by a dictionary or json file. Args: initial_structure (Structure): Initial input structure. Note that to ensure that the miller indices correspond to usual crystallographic definitions, you should supply a conventional unit cell structure. min_slab_size (float): In Angstroms min_vacuum_size (float): In Angstroms reconstruction (str): Name of the dict containing the instructions for building a reconstructed slab. The dictionary can contain any item the creator deems relevant, however any instructions archived in pymatgen for public use needs to contain the following keys and items to ensure compatibility with the ReconstructionGenerator: "name" (str): A descriptive name for the type of reconstruction. Typically the name will have the type of structure the reconstruction is for, the Miller index, and Wood's notation along with anything to describe the reconstruction: e.g.: "fcc_110_missing_row_1x2" "description" (str): A longer description of your reconstruction. This is to help future contributors who want to add other types of reconstructions to the archive on pymatgen to check if the reconstruction already exists. Please read the descriptions carefully before adding a new type of reconstruction to ensure it is not in the archive yet. "reference" (str): Optional reference to where the reconstruction was taken from or first observed. "spacegroup" (dict): e.g. {"symbol": "Fm-3m", "number": 225} Indicates what kind of structure is this reconstruction. "miller_index" ([h,k,l]): Miller index of your reconstruction "Woods_notation" (str): For a reconstruction, the a and b lattice may change to accomodate the symmetry of the reconstruction. This notation indicates the change in the vectors relative to the primitive (p) or conventional (c) slab cell. E.g. p(2x1): Wood, E. A. (1964). Vocabulary of surface crystallography. Journal of Applied Physics, 35(4), 1306–1312. "transformation_matrix" (numpy array): A 3x3 matrix to transform the slab. Only the a and b lattice vectors should change while the c vector remains the same. "SlabGenerator_parameters" (dict): A dictionary containing the parameters for the SlabGenerator class excluding the miller_index, min_slab_size and min_vac_size as the Miller index is already specified and the min_slab_size and min_vac_size can be changed regardless of what type of reconstruction is used. Having a consistent set of SlabGenerator parameters allows for the instructions to be reused to consistently build a reconstructed slab. "points_to_remove" (list of coords): A list of sites to remove where the first two indices are fraction (in a and b) and the third index is in units of 1/d (in c). "points_to_add" (list of frac_coords): A list of sites to add where the first two indices are fraction (in a an b) and the third index is in units of 1/d (in c). "base_reconstruction" (dict): Option to base a reconstruction on an existing reconstruction model also exists to easily build the instructions without repeating previous work. E.g. the alpha reconstruction of halites is based on the octopolar reconstruction but with the topmost atom removed. The dictionary for the alpha reconstruction would therefore contain the item "reconstruction_base": "halite_111_octopolar_2x2", and additional sites for "points_to_remove" and "points_to_add" can be added to modify this reconstruction. For "points_to_remove" and "points_to_add", the third index for the c vector is in units of 1/d where d is the spacing between atoms along hkl (the c vector) and is relative to the topmost site in the unreconstructed slab. e.g. a point of [0.5, 0.25, 1] corresponds to the 0.5 frac_coord of a, 0.25 frac_coord of b and a distance of 1 atomic layer above the topmost site. [0.5, 0.25, -0.5] where the third index corresponds to a point half a atomic layer below the topmost site. [0.5, 0.25, 0] corresponds to a point in the same position along c as the topmost site. This is done because while the primitive units of a and b will remain constant, the user can vary the length of the c direction by changing the slab layer or the vacuum layer. NOTE: THE DICTIONARY SHOULD ONLY CONTAIN "points_to_remove" AND "points_to_add" FOR THE TOP SURFACE. THE ReconstructionGenerator WILL MODIFY THE BOTTOM SURFACE ACCORDINGLY TO RETURN A SLAB WITH EQUIVALENT SURFACES. """ if reconstruction_name not in reconstructions_archive.keys(): raise KeyError( "The reconstruction_name entered (%s) does not exist in the " "archive. Please select from one of the following reconstructions: %s " "or add the appropriate dictionary to the archive file " "reconstructions_archive.json." % (reconstruction_name, list(reconstructions_archive.keys())) ) # Get the instructions to build the reconstruction # from the reconstruction_archive recon_json = copy.deepcopy(reconstructions_archive[reconstruction_name]) new_points_to_add, new_points_to_remove = [], [] if "base_reconstruction" in recon_json.keys(): if "points_to_add" in recon_json.keys(): new_points_to_add = recon_json["points_to_add"] if "points_to_remove" in recon_json.keys(): new_points_to_remove = recon_json["points_to_remove"] # Build new instructions from a base reconstruction recon_json = copy.deepcopy(reconstructions_archive[recon_json["base_reconstruction"]]) if "points_to_add" in recon_json.keys(): del recon_json["points_to_add"] if "points_to_remove" in recon_json.keys(): del recon_json["points_to_remove"] if new_points_to_add: recon_json["points_to_add"] = new_points_to_add if new_points_to_remove: recon_json["points_to_remove"] = new_points_to_remove slabgen_params = copy.deepcopy(recon_json["SlabGenerator_parameters"]) slabgen_params["initial_structure"] = initial_structure.copy() slabgen_params["miller_index"] = recon_json["miller_index"] slabgen_params["min_slab_size"] = min_slab_size slabgen_params["min_vacuum_size"] = min_vacuum_size self.slabgen_params = slabgen_params self.trans_matrix = recon_json["transformation_matrix"] self.reconstruction_json = recon_json self.name = reconstruction_name def build_slabs(self): """ Builds the reconstructed slab by: (1) Obtaining the unreconstructed slab using the specified parameters for the SlabGenerator. (2) Applying the appropriate lattice transformation in the a and b lattice vectors. (3) Remove any specified sites from both surfaces. (4) Add any specified sites to both surfaces. Returns: (Slab): The reconstructed slab. """ slabs = self.get_unreconstructed_slabs() recon_slabs = [] for slab in slabs: d = get_d(slab) top_site = sorted(slab, key=lambda site: site.frac_coords[2])[-1].coords # Remove any specified sites if "points_to_remove" in self.reconstruction_json.keys(): pts_to_rm = copy.deepcopy(self.reconstruction_json["points_to_remove"]) for p in pts_to_rm: p[2] = slab.lattice.get_fractional_coords([top_site[0], top_site[1], top_site[2] + p[2] * d])[2] cart_point = slab.lattice.get_cartesian_coords(p) dist = [site.distance_from_point(cart_point) for site in slab] site1 = dist.index(min(dist)) slab.symmetrically_remove_atoms([site1]) # Add any specified sites if "points_to_add" in self.reconstruction_json.keys(): pts_to_add = copy.deepcopy(self.reconstruction_json["points_to_add"]) for p in pts_to_add: p[2] = slab.lattice.get_fractional_coords([top_site[0], top_site[1], top_site[2] + p[2] * d])[2] slab.symmetrically_add_atom(slab[0].specie, p) slab.reconstruction = self.name setattr(slab, "recon_trans_matrix", self.trans_matrix) # Get the oriented_unit_cell with the same axb area. ouc = slab.oriented_unit_cell.copy() ouc.make_supercell(self.trans_matrix) slab.oriented_unit_cell = ouc recon_slabs.append(slab) return recon_slabs def get_unreconstructed_slabs(self): """ Generates the unreconstructed or pristine super slab. """ slabs = [] for slab in SlabGenerator(**self.slabgen_params).get_slabs(): slab.make_supercell(self.trans_matrix) slabs.append(slab) return slabs def get_d(slab): """ Determine the distance of space between each layer of atoms along c """ sorted_sites = sorted(slab, key=lambda site: site.frac_coords[2]) for i, site in enumerate(sorted_sites): if not "%.6f" % (site.frac_coords[2]) == "%.6f" % (sorted_sites[i + 1].frac_coords[2]): d = abs(site.frac_coords[2] - sorted_sites[i + 1].frac_coords[2]) break return slab.lattice.get_cartesian_coords([0, 0, d])[2] def is_already_analyzed(miller_index: tuple, miller_list: list, symm_ops: list) -> bool: """ Helper function to check if a given Miller index is part of the family of indices of any index in a list Args: miller_index (tuple): The Miller index to analyze miller_list (list): List of Miller indices. If the given Miller index belongs in the same family as any of the indices in this list, return True, else return False symm_ops (list): Symmetry operations of a lattice, used to define family of indices """ for op in symm_ops: if in_coord_list(miller_list, op.operate(miller_index)): return True return False def get_symmetrically_equivalent_miller_indices(structure, miller_index, return_hkil=True): """ Returns all symmetrically equivalent indices for a given structure. Analysis is based on the symmetry of the reciprocal lattice of the structure. Args: miller_index (tuple): Designates the family of Miller indices to find. Can be hkl or hkil for hexagonal systems return_hkil (bool): If true, return hkil form of Miller index for hexagonal systems, otherwise return hkl """ # Change to hkl if hkil because in_coord_list only handles tuples of 3 miller_index = (miller_index[0], miller_index[1], miller_index[3]) if len(miller_index) == 4 else miller_index mmi = max(np.abs(miller_index)) r = list(range(-mmi, mmi + 1)) r.reverse() sg = SpacegroupAnalyzer(structure) # Get distinct hkl planes from the rhombohedral setting if trigonal if sg.get_crystal_system() == "trigonal": prim_structure = SpacegroupAnalyzer(structure).get_primitive_standard_structure() symm_ops = prim_structure.lattice.get_recp_symmetry_operation() else: symm_ops = structure.lattice.get_recp_symmetry_operation() equivalent_millers = [miller_index] for miller in itertools.product(r, r, r): if miller == miller_index: continue if any(i != 0 for i in miller): if is_already_analyzed(miller, equivalent_millers, symm_ops): equivalent_millers.append(miller) # include larger Miller indices in the family of planes if all(mmi > i for i in np.abs(miller)) and not in_coord_list(equivalent_millers, miller): if is_already_analyzed(mmi * np.array(miller), equivalent_millers, symm_ops): equivalent_millers.append(miller) if return_hkil and sg.get_crystal_system() in ["trigonal", "hexagonal"]: return [(hkl[0], hkl[1], -1 * hkl[0] - hkl[1], hkl[2]) for hkl in equivalent_millers] return equivalent_millers def get_symmetrically_distinct_miller_indices(structure, max_index, return_hkil=False): """ Returns all symmetrically distinct indices below a certain max-index for a given structure. Analysis is based on the symmetry of the reciprocal lattice of the structure. Args: structure (Structure): input structure. max_index (int): The maximum index. For example, a max_index of 1 means that (100), (110), and (111) are returned for the cubic structure. All other indices are equivalent to one of these. return_hkil (bool): If true, return hkil form of Miller index for hexagonal systems, otherwise return hkl """ r = list(range(-max_index, max_index + 1)) r.reverse() # First we get a list of all hkls for conventional (including equivalent) conv_hkl_list = [miller for miller in itertools.product(r, r, r) if any(i != 0 for i in miller)] sg = SpacegroupAnalyzer(structure) # Get distinct hkl planes from the rhombohedral setting if trigonal if sg.get_crystal_system() == "trigonal": transf = sg.get_conventional_to_primitive_transformation_matrix() miller_list = [hkl_transformation(transf, hkl) for hkl in conv_hkl_list] prim_structure = SpacegroupAnalyzer(structure).get_primitive_standard_structure() symm_ops = prim_structure.lattice.get_recp_symmetry_operation() else: miller_list = conv_hkl_list symm_ops = structure.lattice.get_recp_symmetry_operation() unique_millers, unique_millers_conv = [], [] for i, miller in enumerate(miller_list): d = abs(reduce(gcd, miller)) miller = tuple(int(i / d) for i in miller) if not is_already_analyzed(miller, unique_millers, symm_ops): if sg.get_crystal_system() == "trigonal": # Now we find the distinct primitive hkls using # the primitive symmetry operations and their # corresponding hkls in the conventional setting unique_millers.append(miller) d = abs(reduce(gcd, conv_hkl_list[i])) cmiller = tuple(int(i / d) for i in conv_hkl_list[i]) unique_millers_conv.append(cmiller) else: unique_millers.append(miller) unique_millers_conv.append(miller) if return_hkil and sg.get_crystal_system() in ["trigonal", "hexagonal"]: return [(hkl[0], hkl[1], -1 * hkl[0] - hkl[1], hkl[2]) for hkl in unique_millers_conv] return unique_millers_conv def hkl_transformation(transf, miller_index): """ Returns the Miller index from setting A to B using a transformation matrix Args: transf (3x3 array): The transformation matrix that transforms a lattice of A to B miller_index ([h, k, l]): Miller index to transform to setting B """ # Get a matrix of whole numbers (ints) def lcm(a, b): return a * b // math.gcd(a, b) reduced_transf = reduce(lcm, [int(1 / i) for i in itertools.chain(*transf) if i != 0]) * transf reduced_transf = reduced_transf.astype(int) # perform the transformation t_hkl = np.dot(reduced_transf, miller_index) d = abs(reduce(gcd, t_hkl)) t_hkl = np.array([int(i / d) for i in t_hkl]) # get mostly positive oriented Miller index if len([i for i in t_hkl if i < 0]) > 1: t_hkl *= -1 return tuple(t_hkl) def generate_all_slabs( structure, max_index, min_slab_size, min_vacuum_size, bonds=None, tol=0.1, ftol=0.1, max_broken_bonds=0, lll_reduce=False, center_slab=False, primitive=True, max_normal_search=None, symmetrize=False, repair=False, include_reconstructions=False, in_unit_planes=False, ): """ A function that finds all different slabs up to a certain miller index. Slabs oriented under certain Miller indices that are equivalent to other slabs in other Miller indices are filtered out using symmetry operations to get rid of any repetitive slabs. For example, under symmetry operations, CsCl has equivalent slabs in the (0,0,1), (0,1,0), and (1,0,0) direction. Args: structure (Structure): Initial input structure. Note that to ensure that the miller indices correspond to usual crystallographic definitions, you should supply a conventional unit cell structure. max_index (int): The maximum Miller index to go up to. min_slab_size (float): In Angstroms min_vacuum_size (float): In Angstroms bonds ({(specie1, specie2): max_bond_dist}: bonds are specified as a dict of tuples: float of specie1, specie2 and the max bonding distance. For example, PO4 groups may be defined as {("P", "O"): 3}. tol (float): Threshold parameter in fcluster in order to check if two atoms are lying on the same plane. Default thresh set to 0.1 Angstrom in the direction of the surface normal. max_broken_bonds (int): Maximum number of allowable broken bonds for the slab. Use this to limit # of slabs (some structures may have a lot of slabs). Defaults to zero, which means no defined bonds must be broken. lll_reduce (bool): Whether to perform an LLL reduction on the eventual structure. center_slab (bool): Whether to center the slab in the cell with equal vacuum spacing from the top and bottom. primitive (bool): Whether to reduce any generated slabs to a primitive cell (this does **not** mean the slab is generated from a primitive cell, it simply means that after slab generation, we attempt to find shorter lattice vectors, which lead to less surface area and smaller cells). max_normal_search (int): If set to a positive integer, the code will conduct a search for a normal lattice vector that is as perpendicular to the surface as possible by considering multiples linear combinations of lattice vectors up to max_normal_search. This has no bearing on surface energies, but may be useful as a preliminary step to generating slabs for absorption and other sizes. It is typical that this will not be the smallest possible cell for simulation. Normality is not guaranteed, but the oriented cell will have the c vector as normal as possible (within the search range) to the surface. A value of up to the max absolute Miller index is usually sufficient. symmetrize (bool): Whether or not to ensure the surfaces of the slabs are equivalent. repair (bool): Whether to repair terminations with broken bonds or just omit them include_reconstructions (bool): Whether to include reconstructed slabs available in the reconstructions_archive.json file. """ all_slabs = [] for miller in get_symmetrically_distinct_miller_indices(structure, max_index): gen = SlabGenerator( structure, miller, min_slab_size, min_vacuum_size, lll_reduce=lll_reduce, center_slab=center_slab, primitive=primitive, max_normal_search=max_normal_search, in_unit_planes=in_unit_planes, ) slabs = gen.get_slabs( bonds=bonds, tol=tol, ftol=ftol, symmetrize=symmetrize, max_broken_bonds=max_broken_bonds, repair=repair, ) if len(slabs) > 0: logger.debug("%s has %d slabs... " % (miller, len(slabs))) all_slabs.extend(slabs) if include_reconstructions: sg = SpacegroupAnalyzer(structure) symbol = sg.get_space_group_symbol() # enumerate through all posisble reconstructions in the # archive available for this particular structure (spacegroup) for name, instructions in reconstructions_archive.items(): if "base_reconstruction" in instructions.keys(): instructions = reconstructions_archive[instructions["base_reconstruction"]] if instructions["spacegroup"]["symbol"] == symbol: # check if this reconstruction has a max index # equal or less than the given max index if max(instructions["miller_index"]) > max_index: continue recon = ReconstructionGenerator(structure, min_slab_size, min_vacuum_size, name) all_slabs.extend(recon.build_slabs()) return all_slabs def get_slab_regions(slab, blength=3.5): """ Function to get the ranges of the slab regions. Useful for discerning where the slab ends and vacuum begins if the slab is not fully within the cell Args: slab (Structure): Structure object modelling the surface blength (float, Ang): The bondlength between atoms. You generally want this value to be larger than the actual bondlengths in order to find atoms that are part of the slab """ fcoords, indices, all_indices = [], [], [] for site in slab: # find sites with c < 0 (noncontiguous) neighbors = slab.get_neighbors(site, blength, include_index=True, include_image=True) for nn in neighbors: if nn[0].frac_coords[2] < 0: # sites are noncontiguous within cell fcoords.append(nn[0].frac_coords[2]) indices.append(nn[-2]) if nn[-2] not in all_indices: all_indices.append(nn[-2]) if fcoords: # If slab is noncontiguous, locate the lowest # site within the upper region of the slab while fcoords: last_fcoords = copy.copy(fcoords) last_indices = copy.copy(indices) site = slab[indices[fcoords.index(min(fcoords))]] neighbors = slab.get_neighbors(site, blength, include_index=True, include_image=True) fcoords, indices = [], [] for nn in neighbors: if 1 > nn[0].frac_coords[2] > 0 and nn[0].frac_coords[2] < site.frac_coords[2]: # sites are noncontiguous within cell fcoords.append(nn[0].frac_coords[2]) indices.append(nn[-2]) if nn[-2] not in all_indices: all_indices.append(nn[-2]) # Now locate the highest site within the lower region of the slab upper_fcoords = [] for site in slab: if all(nn.index not in all_indices for nn in slab.get_neighbors(site, blength)): upper_fcoords.append(site.frac_coords[2]) coords = copy.copy(last_fcoords) if not fcoords else copy.copy(fcoords) min_top = slab[last_indices[coords.index(min(coords))]].frac_coords[2] ranges = [[0, max(upper_fcoords)], [min_top, 1]] else: # If the entire slab region is within the slab cell, just # set the range as the highest and lowest site in the slab sorted_sites = sorted(slab, key=lambda site: site.frac_coords[2]) ranges = [[sorted_sites[0].frac_coords[2], sorted_sites[-1].frac_coords[2]]] return ranges def miller_index_from_sites(lattice, coords, coords_are_cartesian=True, round_dp=4, verbose=True): """ Get the Miller index of a plane from a list of site coordinates. A minimum of 3 sets of coordinates are required. If more than 3 sets of coordinates are given, the best plane that minimises the distance to all points will be calculated. Args: lattice (list or Lattice): A 3x3 lattice matrix or `Lattice` object (for example obtained from Structure.lattice). coords (iterable): A list or numpy array of coordinates. Can be cartesian or fractional coordinates. If more than three sets of coordinates are provided, the best plane that minimises the distance to all sites will be calculated. coords_are_cartesian (bool, optional): Whether the coordinates are in cartesian space. If using fractional coordinates set to False. round_dp (int, optional): The number of decimal places to round the miller index to. verbose (bool, optional): Whether to print warnings. Returns: (tuple): The Miller index. """ if not isinstance(lattice, Lattice): lattice = Lattice(lattice) return lattice.get_miller_index_from_coords( coords, coords_are_cartesian=coords_are_cartesian, round_dp=round_dp, verbose=verbose, ) def center_slab(slab): """ The goal here is to ensure the center of the slab region is centered close to c=0.5. This makes it easier to find the surface sites and apply operations like doping. There are three cases where the slab in not centered: 1. The slab region is completely between two vacuums in the box but not necessarily centered. We simply shift the slab by the difference in its center of mass and 0.5 along the c direction. 2. The slab completely spills outside the box from the bottom and into the top. This makes it incredibly difficult to locate surface sites. We iterate through all sites that spill over (z>c) and shift all sites such that this specific site is now on the other side. Repeat for all sites with z>c. 3. This is a simpler case of scenario 2. Either the top or bottom slab sites are at c=0 or c=1. Treat as scenario 2. Args: slab (Slab): Slab structure to center Returns: Returns a centered slab structure """ # get a reasonable r cutoff to sample neighbors bdists = sorted([nn[1] for nn in slab.get_neighbors(slab[0], 10) if nn[1] > 0]) r = bdists[0] * 3 all_indices = [i for i, site in enumerate(slab)] # check if structure is case 2 or 3, shift all the # sites up to the other side until it is case 1 for site in slab: if any(nn[1] > slab.lattice.c for nn in slab.get_neighbors(site, r)): shift = 1 - site.frac_coords[2] + 0.05 slab.translate_sites(all_indices, [0, 0, shift]) # now the slab is case 1, shift the center of mass of the slab to 0.5 weights = [s.species.weight for s in slab] center_of_mass = np.average(slab.frac_coords, weights=weights, axis=0) shift = 0.5 - center_of_mass[2] slab.translate_sites(all_indices, [0, 0, shift]) return slab def _reduce_vector(vector): # small function to reduce vectors d = abs(reduce(gcd, vector)) vector = tuple(int(i / d) for i in vector) return vector

richardtran415/pymatgen

pymatgen/core/surface.py

Python

mit

87,059

[ "pymatgen" ]

fcd6904ea24f3d4fb398844871fb7b03f16e5f70221c17f3a63a111965856383

# -*- coding: utf-8 -*- # # tsodyks_facilitating.py # # This file is part of NEST. # # Copyright (C) 2004 The NEST Initiative # # NEST is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 2 of the License, or # (at your option) any later version. # # NEST is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with NEST. If not, see <http://www.gnu.org/licenses/>. """Tsodyks facilitating example -------------------------------- This scripts simulates two neurons. One is driven with dc-input and connected to the other one with a facilitating Tsodyks synapse. The membrane potential trace of the second neuron is recorded. This example reproduces figure 1B of [1]_ This example is analog to ``tsodyks_depressing.py``, except that different synapse parameters are used. Here, a small facilitation parameter ``U`` causes a slow saturation of the synaptic efficacy (Eq. 2.2), enabling a facilitating behavior. References ~~~~~~~~~~~~ .. [1] Tsodyks M, Pawelzik K, Markram H (1998). Neural networks with dynamic synapses. Neural computation, http://dx.doi.org/10.1162/089976698300017502 See Also ~~~~~~~~~~ :doc:`tsodyks_depressing` """ ############################################################################### # First, we import all necessary modules for simulation and plotting. import nest import nest.voltage_trace from numpy import exp ############################################################################### # Second, the simulation parameters are assigned to variables. The neuron # and synapse parameters are stored into a dictionary. h = 0.1 # simulation step size (ms) Tau = 40. # membrane time constant Theta = 15. # threshold E_L = 0. # reset potential of membrane potential R = 1. # membrane resistance (GOhm) C = Tau / R # Tau (ms)/R in NEST units TauR = 2. # refractory time Tau_psc = 1.5 # time constant of PSC (= Tau_inact) Tau_rec = 130. # recovery time Tau_fac = 530. # facilitation time U = 0.03 # facilitation parameter U A = 1540. # PSC weight in pA f = 20. / 1000. # frequency in Hz converted to 1/ms Tend = 1200. # simulation time TIstart = 50. # start time of dc TIend = 1050. # end time of dc I0 = Theta * C / Tau / (1 - exp(-(1 / f - TauR) / Tau)) # dc amplitude neuron_param = {"tau_m": Tau, "t_ref": TauR, "tau_syn_ex": Tau_psc, "tau_syn_in": Tau_psc, "C_m": C, "V_reset": E_L, "E_L": E_L, "V_m": E_L, "V_th": Theta} syn_param = {"tau_psc": Tau_psc, "tau_rec": Tau_rec, "tau_fac": Tau_fac, "U": U, "delay": 0.1, "weight": A, "u": 0.0, "x": 1.0} ############################################################################### # Third, we reset the kernel and set the resolution using ``SetKernelStatus``. nest.ResetKernel() nest.SetKernelStatus({"resolution": h}) ############################################################################### # Fourth, the nodes are created using ``Create``. We store the returned # handles in variables for later reference. neurons = nest.Create("iaf_psc_exp", 2) dc_gen = nest.Create("dc_generator") volts = nest.Create("voltmeter") ############################################################################### # Fifth, the ``iaf_psc_exp`` neurons, the ``dc_generator`` and the ``voltmeter`` # are configured using ``SetStatus``, which expects a list of node handles and # a parameter dictionary or a list of parameter dictionaries. neurons.set(neuron_param) dc_gen.set(amplitude=I0, start=TIstart, stop=TIend) volts.set(label="voltmeter", interval=1.) ############################################################################### # Sixth, the ``dc_generator`` is connected to the first neuron # (`neurons[0]`) and the `voltmeter` is connected to the second neuron # (`neurons[1]`). The command `Connect` has different variants. Plain # ``Connect`` just takes the handles of pre- and postsynaptic nodes and # uses the default values for weight and delay. Note that the connection # direction for the ``voltmeter`` reflects the signal flow in the simulation # kernel, because it observes the neuron instead of receiving events from it. nest.Connect(dc_gen, neurons[0]) nest.Connect(volts, neurons[1]) ############################################################################### # Seventh, the first neuron (`neurons[0]`) is connected to the second # neuron (`neurons[1]`). The command ``CopyModel`` copies the # ``tsodyks_synapse`` model to the new name ``syn`` with parameters # ``syn_param``. The manually defined model ``syn`` is used in the # connection routine via the ``syn_spec`` parameter. nest.CopyModel("tsodyks_synapse", "syn", syn_param) nest.Connect(neurons[0], neurons[1], syn_spec="syn") ############################################################################### # Finally, we simulate the configuration using the command ``Simulate``, # where the simulation time `Tend` is passed as the argument. We plot the # target neuron's membrane potential as function of time. nest.Simulate(Tend) nest.voltage_trace.from_device(volts) nest.voltage_trace.show()

SepehrMN/nest-simulator

pynest/examples/tsodyks_facilitating.py

Python

gpl-2.0

5,620

[ "NEURON" ]

bfa8dd5e82947eb4a03baee8f29d510fd0dd9295ed84e02ee11602a5720cd14f

# Generate UV-Vis spectra from electronic structure TDHF/TDDFT output files. # Copyright (C) 2014 Li Research Group (University of Washington) # # This program is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation, either version 3 of the License, or # (at your option) any later version. # # This program is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program. If not, see <http://www.gnu.org/licenses/>. """Generate UV-Vis spectra from electronic structure TDHF/TDDFT output files. The top-level and main functions for the ``uvspecgen`` script are stored here. Functions for updating and resetting the Gaussian fit parameters are defined here. """ import sys from uvspec.config import settings from uvspec.config.settings import ConfigFile from uvspec.spectrum import AbsorptionSpectrum def _update_fit_parameters(): # Update the fit parameters in the configuration file with the values # provdied by the user at run-time. If no values are specified, the # current default values are maintained. config = ConfigFile() for parameter, value in settings.parameters.iteritems(): config.update(parameter, value) print ' Fit paramters have been updated' def _reset_fit_parameters(): # Reset the fit parameters to their originally installed default values. ConfigFile().reset() print ' Fit parameters have been reset to their original default values' def _generate_spectrum(): # Spectrum generation using the ``AbsorptionSpectrum`` class and methods. spectrum = AbsorptionSpectrum() if settings.join: spectrum.join(settings.logfile) else: spectrum.extract(settings.logfile[0]) spectrum.generate(settings.parameters) spectrum.write(settings.outfile, settings.output, settings.nometa) if settings.plot: spectrum.plot() def main(): """The core function that drives the ``uvspecgen`` program. First handle updates/resetting of the configuration file containing the Gaussian fit parameters. The ``uvspecgen`` program can be run without an electronic structure output filename specified solely for the purposes of updating/resetting the Gaussian fit parameters in the configuration file. If the ``--save`` or ``--reset`` flag is not specified, and a logfile is not given, the program will terminate with an error message and usage instructions. """ if settings.save: _update_fit_parameters() elif settings.reset: _reset_fit_parameters() if settings.logfile: _generate_spectrum() elif not settings.save and not settings.reset: settings.parser.error('Must specify at least one logfile name') else: sys.exit()

liresearchgroup/uvspecgen

uvspec/generate.py

Python

gpl-3.0

3,106

[ "Gaussian" ]

c708c61675dc0c8ed7e330569fd2ffcbf42c133336e46c11495d163fa9f02a38

# This file is part of Buildbot. Buildbot is free software: you can # redistribute it and/or modify it under the terms of the GNU General Public # License as published by the Free Software Foundation, version 2. # # This program is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS # FOR A PARTICULAR PURPOSE. See the GNU General Public License for more # details. # # You should have received a copy of the GNU General Public License along with # this program; if not, write to the Free Software Foundation, Inc., 51 # Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA. # # Copyright Buildbot Team Members from __future__ import with_statement # Based on the work of Dave Peticolas for the P4poll # Changed to svn (using xml.dom.minidom) by Niklaus Giger # Hacked beyond recognition by Brian Warner from twisted.python import log from twisted.internet import defer, utils from buildbot import util from buildbot.changes import base import xml.dom.minidom import os, urllib # these split_file_* functions are available for use as values to the # split_file= argument. def split_file_alwaystrunk(path): return dict(path=path) def split_file_branches(path): # turn "trunk/subdir/file.c" into (None, "subdir/file.c") # and "trunk/subdir/" into (None, "subdir/") # and "trunk/" into (None, "") # and "branches/1.5.x/subdir/file.c" into ("branches/1.5.x", "subdir/file.c") # and "branches/1.5.x/subdir/" into ("branches/1.5.x", "subdir/") # and "branches/1.5.x/" into ("branches/1.5.x", "") pieces = path.split('/') if len(pieces) > 1 and pieces[0] == 'trunk': return (None, '/'.join(pieces[1:])) elif len(pieces) > 2 and pieces[0] == 'branches': return ('/'.join(pieces[0:2]), '/'.join(pieces[2:])) else: return None def split_file_projects_branches(path): # turn projectname/trunk/subdir/file.c into dict(project=projectname, branch=trunk, path=subdir/file.c) if not "/" in path: return None project, path = path.split("/", 1) f = split_file_branches(path) if f: info = dict(project=project, path=f[1]) if f[0]: info['branch'] = f[0] return info return f class SVNPoller(base.PollingChangeSource, util.ComparableMixin): """ Poll a Subversion repository for changes and submit them to the change master. """ compare_attrs = ["svnurl", "split_file", "svnuser", "svnpasswd", "project", "pollInterval", "histmax", "svnbin", "category", "cachepath"] parent = None # filled in when we're added last_change = None loop = None def __init__(self, svnurl, split_file=None, svnuser=None, svnpasswd=None, pollInterval=10*60, histmax=100, svnbin='svn', revlinktmpl='', category=None, project='', cachepath=None, pollinterval=-2, extra_args=None): # for backward compatibility; the parameter used to be spelled with 'i' if pollinterval != -2: pollInterval = pollinterval base.PollingChangeSource.__init__(self, name=svnurl, pollInterval=pollInterval) if svnurl.endswith("/"): svnurl = svnurl[:-1] # strip the trailing slash self.svnurl = svnurl self.extra_args = extra_args self.split_file = split_file or split_file_alwaystrunk self.svnuser = svnuser self.svnpasswd = svnpasswd self.revlinktmpl = revlinktmpl self.environ = os.environ.copy() # include environment variables # required for ssh-agent auth self.svnbin = svnbin self.histmax = histmax self._prefix = None self.category = category self.project = project self.cachepath = cachepath if self.cachepath and os.path.exists(self.cachepath): try: with open(self.cachepath, "r") as f: self.last_change = int(f.read().strip()) log.msg("SVNPoller: SVNPoller(%s) setting last_change to %s" % (self.svnurl, self.last_change)) # try writing it, too with open(self.cachepath, "w") as f: f.write(str(self.last_change)) except: self.cachepath = None log.msg(("SVNPoller: SVNPoller(%s) cache file corrupt or unwriteable; " + "skipping and not using") % self.svnurl) log.err() def describe(self): return "SVNPoller: watching %s" % self.svnurl def poll(self): # Our return value is only used for unit testing. # we need to figure out the repository root, so we can figure out # repository-relative pathnames later. Each SVNURL is in the form # (ROOT)/(PROJECT)/(BRANCH)/(FILEPATH), where (ROOT) is something # like svn://svn.twistedmatrix.com/svn/Twisted (i.e. there is a # physical repository at /svn/Twisted on that host), (PROJECT) is # something like Projects/Twisted (i.e. within the repository's # internal namespace, everything under Projects/Twisted/ has # something to do with Twisted, but these directory names do not # actually appear on the repository host), (BRANCH) is something like # "trunk" or "branches/2.0.x", and (FILEPATH) is a tree-relative # filename like "twisted/internet/defer.py". # our self.svnurl attribute contains (ROOT)/(PROJECT) combined # together in a way that we can't separate without svn's help. If the # user is not using the split_file= argument, then self.svnurl might # be (ROOT)/(PROJECT)/(BRANCH) . In any case, the filenames we will # get back from 'svn log' will be of the form # (PROJECT)/(BRANCH)/(FILEPATH), but we want to be able to remove # that (PROJECT) prefix from them. To do this without requiring the # user to tell us how svnurl is split into ROOT and PROJECT, we do an # 'svn info --xml' command at startup. This command will include a # <root> element that tells us ROOT. We then strip this prefix from # self.svnurl to determine PROJECT, and then later we strip the # PROJECT prefix from the filenames reported by 'svn log --xml' to # get a (BRANCH)/(FILEPATH) that can be passed to split_file() to # turn into separate BRANCH and FILEPATH values. # whew. if self.project: log.msg("SVNPoller: polling " + self.project) else: log.msg("SVNPoller: polling") d = defer.succeed(None) if not self._prefix: d.addCallback(lambda _ : self.get_prefix()) def set_prefix(prefix): self._prefix = prefix d.addCallback(set_prefix) d.addCallback(self.get_logs) d.addCallback(self.parse_logs) d.addCallback(self.get_new_logentries) d.addCallback(self.create_changes) d.addCallback(self.submit_changes) d.addCallback(self.finished_ok) d.addErrback(log.err, 'SVNPoller: Error in while polling') # eat errors return d def getProcessOutput(self, args): # this exists so we can override it during the unit tests d = utils.getProcessOutput(self.svnbin, args, self.environ) return d def get_prefix(self): args = ["info", "--xml", "--non-interactive", self.svnurl] if self.svnuser: args.extend(["--username=%s" % self.svnuser]) if self.svnpasswd: args.extend(["--password=%s" % self.svnpasswd]) if self.extra_args: args.extend(self.extra_args) d = self.getProcessOutput(args) def determine_prefix(output): try: doc = xml.dom.minidom.parseString(output) except xml.parsers.expat.ExpatError: log.msg("SVNPoller: SVNPoller._determine_prefix_2: ExpatError in '%s'" % output) raise rootnodes = doc.getElementsByTagName("root") if not rootnodes: # this happens if the URL we gave was already the root. In this # case, our prefix is empty. self._prefix = "" return self._prefix rootnode = rootnodes[0] root = "".join([c.data for c in rootnode.childNodes]) # root will be a unicode string if not self.svnurl.startswith(root): log.msg(format="svnurl='%(svnurl)s' doesn't start with <root>='%(root)s'", svnurl=self.svnurl, root=root) raise RuntimeError("Can't handle redirected svn connections!? " "This shouldn't happen.") prefix = self.svnurl[len(root):] if prefix.startswith("/"): prefix = prefix[1:] log.msg("SVNPoller: svnurl=%s, root=%s, so prefix=%s" % (self.svnurl, root, prefix)) return prefix d.addCallback(determine_prefix) return d def get_logs(self, _): args = [] args.extend(["log", "--xml", "--verbose", "--non-interactive"]) if self.svnuser: args.extend(["--username=%s" % self.svnuser]) if self.svnpasswd: args.extend(["--password=%s" % self.svnpasswd]) if self.extra_args: args.extend(self.extra_args) args.extend(["--limit=%d" % (self.histmax), self.svnurl]) d = self.getProcessOutput(args) return d def parse_logs(self, output): # parse the XML output, return a list of <logentry> nodes try: doc = xml.dom.minidom.parseString(output) except xml.parsers.expat.ExpatError: log.msg("SVNPoller: SVNPoller.parse_logs: ExpatError in '%s'" % output) raise logentries = doc.getElementsByTagName("logentry") return logentries def get_new_logentries(self, logentries): last_change = old_last_change = self.last_change # given a list of logentries, calculate new_last_change, and # new_logentries, where new_logentries contains only the ones after # last_change new_last_change = None new_logentries = [] if logentries: new_last_change = int(logentries[0].getAttribute("revision")) if last_change is None: # if this is the first time we've been run, ignore any changes # that occurred before now. This prevents a build at every # startup. log.msg('SVNPoller: starting at change %s' % new_last_change) elif last_change == new_last_change: # an unmodified repository will hit this case log.msg('SVNPoller: no changes') else: for el in logentries: if last_change == int(el.getAttribute("revision")): break new_logentries.append(el) new_logentries.reverse() # return oldest first self.last_change = new_last_change log.msg('SVNPoller: _process_changes %s .. %s' % (old_last_change, new_last_change)) return new_logentries def _get_text(self, element, tag_name): try: child_nodes = element.getElementsByTagName(tag_name)[0].childNodes text = "".join([t.data for t in child_nodes]) except: text = "<unknown>" return text def _transform_path(self, path): if not path.startswith(self._prefix): log.msg(format="SVNPoller: ignoring path '%(path)s' which doesn't" "start with prefix '%(prefix)s'", path=path, prefix=self._prefix) return relative_path = path[len(self._prefix):] if relative_path.startswith("/"): relative_path = relative_path[1:] where = self.split_file(relative_path) # 'where' is either None, (branch, final_path) or a dict if not where: return if isinstance(where, tuple): where = dict(branch=where[0], path=where[1]) return where def create_changes(self, new_logentries): changes = [] for el in new_logentries: revision = str(el.getAttribute("revision")) revlink='' if self.revlinktmpl: if revision: revlink = self.revlinktmpl % urllib.quote_plus(revision) log.msg("Adding change revision %s" % (revision,)) author = self._get_text(el, "author") comments = self._get_text(el, "msg") # there is a "date" field, but it provides localtime in the # repository's timezone, whereas we care about buildmaster's # localtime (since this will get used to position the boxes on # the Waterfall display, etc). So ignore the date field, and # addChange will fill in with the current time branches = {} try: pathlist = el.getElementsByTagName("paths")[0] except IndexError: # weird, we got an empty revision log.msg("ignoring commit with no paths") continue for p in pathlist.getElementsByTagName("path"): kind = p.getAttribute("kind") action = p.getAttribute("action") path = "".join([t.data for t in p.childNodes]) # the rest of buildbot is certaily not yet ready to handle # unicode filenames, because they get put in RemoteCommands # which get sent via PB to the buildslave, and PB doesn't # handle unicode. path = path.encode("ascii") if path.startswith("/"): path = path[1:] if kind == "dir" and not path.endswith("/"): path += "/" where = self._transform_path(path) # if 'where' is None, the file was outside any project that # we care about and we should ignore it if where: branch = where.get("branch", None) filename = where["path"] if not branch in branches: branches[branch] = { 'files': [], 'number_of_directories': 0} if filename == "": # root directory of branch branches[branch]['files'].append(filename) branches[branch]['number_of_directories'] += 1 elif filename.endswith("/"): # subdirectory of branch branches[branch]['files'].append(filename[:-1]) branches[branch]['number_of_directories'] += 1 else: branches[branch]['files'].append(filename) if not branches[branch].has_key('action'): branches[branch]['action'] = action for key in ("repository", "project", "codebase"): if key in where: branches[branch][key] = where[key] for branch in branches.keys(): action = branches[branch]['action'] files = branches[branch]['files'] number_of_directories_changed = branches[branch]['number_of_directories'] number_of_files_changed = len(files) if action == u'D' and number_of_directories_changed == 1 and number_of_files_changed == 1 and files[0] == '': log.msg("Ignoring deletion of branch '%s'" % branch) else: chdict = dict( author=author, files=files, comments=comments, revision=revision, branch=branch, revlink=revlink, category=self.category, repository=branches[branch].get('repository', self.svnurl), project=branches[branch].get('project', self.project), codebase=branches[branch].get('codebase', None)) changes.append(chdict) return changes @defer.inlineCallbacks def submit_changes(self, changes): for chdict in changes: yield self.master.addChange(src='svn', **chdict) def finished_ok(self, res): if self.cachepath: with open(self.cachepath, "w") as f: f.write(str(self.last_change)) log.msg("SVNPoller: finished polling %s" % res) return res

denny820909/builder

lib/python2.7/site-packages/buildbot-0.8.8-py2.7.egg/buildbot/changes/svnpoller.py

Python

mit

17,125

[ "Brian" ]

c6ee6cebb5316101c9122b06b364bf802cc40a90f4ed3ada65b71884900d110d

# Databricks notebook source # MAGIC %md # MAGIC # MAGIC # [SDS-2.2, Scalable Data Science](https://lamastex.github.io/scalable-data-science/sds/2/2/) # MAGIC # MAGIC This is used in a non-profit educational setting with kind permission of [Adam Breindel](https://www.linkedin.com/in/adbreind). # MAGIC This is not licensed by Adam for use in a for-profit setting. Please contact Adam directly at `adbreind@gmail.com` to request or report such use cases or abuses. # MAGIC A few minor modifications and additional mathematical statistical pointers have been added by Raazesh Sainudiin when teaching PhD students in Uppsala University. # COMMAND ---------- # MAGIC %md # MAGIC Archived YouTube video of this live unedited lab-lecture: # MAGIC # MAGIC [![Archived YouTube video of this live unedited lab-lecture](http://img.youtube.com/vi/Vwou20grUD4/0.jpg)](https://www.youtube.com/embed/Vwou20grUD4?start=378&end=2146&autoplay=1) [![Archived YouTube video of this live unedited lab-lecture](http://img.youtube.com/vi/-LLL3MUl9ps/0.jpg)](https://www.youtube.com/embed/-LLL3MUl9ps?start=0&end=2467&autoplay=1) # COMMAND ---------- # MAGIC %md # MAGIC #### We can also implement the model with mini-batches -- this will let us see matrix ops in action: # MAGIC # MAGIC (N.b., feed_dict is intended for small data / experimentation. For more info on ingesting data at scale, see https://www.tensorflow.org/api_guides/python/reading_data) # COMMAND ---------- # we know these params, but we're making TF learn them REAL_SLOPE_X1 = 2 # slope along axis 1 (x-axis) REAL_SLOPE_X2 = 3 # slope along axis 2 (y-axis) REAL_INTERCEPT = 5 # intercept along axis 3 (z-axis), think of (x,y,z) axes in the usual way # COMMAND ---------- import numpy as np # GENERATE a batch of true data, with a little Gaussian noise added def make_mini_batch(size=10): X = np.random.rand(size, 2) # Y = np.matmul(X, [REAL_SLOPE_X1, REAL_SLOPE_X2]) + REAL_INTERCEPT + 0.2 * np.random.randn(size) return X.reshape(size,2), Y.reshape(size,1) # COMMAND ---------- # MAGIC %md # MAGIC To digest what's going on inside the function above, let's take it step by step. # COMMAND ---------- Xex = np.random.rand(10, 2) # Xex is simulating PRNGs from independent Uniform [0,1] RVs Xex # visualize these as 10 orddered pairs of points in the x-y plane that makes up our x-axis and y-axis (or x1 and x2 axes) # COMMAND ---------- Yex = np.matmul(Xex, [REAL_SLOPE_X1, REAL_SLOPE_X2]) # + REAL_INTERCEPT + 0.2 * np.random.randn(size) Yex # COMMAND ---------- # MAGIC %md # MAGIC The first entry in Yex is obtained as follows (change the numbers in the produc below if you reevaluated the cells above) and geometrically it is the location in z-axis of the plane with slopes given by REAL_SLOPE_X1 in the x-axis and REAL_SLOPE_X2 in the y-aixs with intercept 0 at the point in the x-y or x1-x2 plane given by (0.68729439, 0.58462379). # COMMAND ---------- 0.68729439*REAL_SLOPE_X1 + 0.58462379*REAL_SLOPE_X2 # COMMAND ---------- # MAGIC %md # MAGIC The next steps are adding an intercept term to translate the plane in the z-axis and then a scaled (the multiplication by 0.2 here) gaussian noise from independetly drawn pseudo-random samples from the standard normal or Normal(0,1) random variable via `np.random.randn(size)`. # COMMAND ---------- Yex = np.matmul(Xex, [REAL_SLOPE_X1, REAL_SLOPE_X2]) + REAL_INTERCEPT # + 0.2 * np.random.randn(10) Yex # COMMAND ---------- Yex = np.matmul(Xex, [REAL_SLOPE_X1, REAL_SLOPE_X2]) + REAL_INTERCEPT + 0.2 * np.random.randn(10) Yex # note how each entry in Yex is jiggled independently a bit by 0.2 * np.random.randn() # COMMAND ---------- # MAGIC %md # MAGIC Thus we can now fully appreciate what is going on in `make_mini_batch`. This is meant to substitute for pulling random sub-samples of batches of the real data during stochastic gradient descent. # COMMAND ---------- make_mini_batch() # our mini-batch of Xx and Ys # COMMAND ---------- import tensorflow as tf batch = 5 # size of batch tf.reset_default_graph() # this is important to do before you do something new in TF # we will work with single floating point precision and this is specified in the tf.float32 type argument to each tf object/method x = tf.placeholder(tf.float32, shape=(batch, 2)) # placeholder node for the pairs of x variables (predictors) in batches of size batch x_aug = tf.concat( (x, tf.ones((batch, 1))), 1 ) # x_aug is a concatenation of a vector of 1`s along the first dimension y = tf.placeholder(tf.float32, shape=(batch, 1)) # placeholder node for the univariate response y with batch many rows and 1 column model_params = tf.get_variable("model_params", [3,1]) # these are the x1 slope, x2 slope and the intercept (3 rows and 1 column) y_model = tf.matmul(x_aug, model_params) # our two-factor regression model is defined by this matrix multiplication # note that the noise is formally part of the model and what we are actually modeling is the mean response... error = tf.reduce_sum(tf.square(y - y_model))/batch # this is mean square error where the sum is computed by a reduce call on addition train_op = tf.train.GradientDescentOptimizer(0.02).minimize(error) # learning rate is set to 0.02 init = tf.global_variables_initializer() # our way into running the TF session errors = [] # list to track errors over iterations with tf.Session() as session: session.run(init) for i in range(500): x_data, y_data = make_mini_batch(batch) # simulate the mini-batch of data x1,x2 and response y with noise _, error_val = session.run([train_op, error], feed_dict={x: x_data, y: y_data}) errors.append(error_val) out = session.run(model_params) print(out) # COMMAND ---------- REAL_SLOPE_X1, REAL_SLOPE_X2, REAL_INTERCEPT # compare with rue parameter values - it's not too far from the estimates # COMMAND ---------- import matplotlib.pyplot as plt fig, ax = plt.subplots() fig.set_size_inches((4,3)) plt.plot(errors) display(fig)

raazesh-sainudiin/scalable-data-science

db/2/2/054_DLbyABr_03a-BatchTensorFlowWithMatrices.py

Python

unlicense

6,018

[ "Gaussian" ]

92f383182ba078dd5dc208a7c21eb9590de9c853b924891811d41203a89d0556

#! CCSD dipole with user-specified basis set import psi4 psi4.set_output_file("output.dat", False) h2o = psi4.geometry(""" 0 1 H O 1 0.957 H 2 0.957 1 104.5 """) psi4.set_options({'freeze_core': 'false'}) psi4.basis_helper(""" # Sadlej-pVTZ spherical **** H 0 S 4 1.00 33.8650140000 0.0060680000 5.0947880000 0.0453160000 1.1587860000 0.2028460000 0.3258400000 0.5037090000 S 1 1.00 0.1027410000 1.0000000000 S 1 1.00 0.0324000000 1.0000000000 P 2 1.00 1.1588000000 0.1884400000 0.3258000000 0.8824200000 P 2 1.00 0.1027000000 0.1178000000 0.0324000000 0.0042000000 **** C 0 S 5 1.00 5240.6353000000 0.0009370000 782.2048000000 0.0072280000 178.3508300000 0.0363440000 50.8159420000 0.1306000000 16.8235620000 0.3189310000 S 2 1.00 6.1757760000 0.4387420000 2.4180490000 0.2149740000 S 1 1.00 0.5119000000 1.0000000000 S 1 1.00 0.1565900000 1.0000000000 S 1 1.00 0.0479000000 1.0000000000 P 4 1.00 18.8418000000 0.0138870000 4.1592400000 0.0862790000 1.2067100000 0.2887440000 0.3855400000 0.4994110000 P 1 1.00 0.1219400000 1.0000000000 P 1 1.00 0.0385680000 1.0000000000 D 2 1.00 1.2067000000 0.2628500000 0.3855000000 0.8043000000 D 2 1.00 0.1219000000 0.6535000000 0.0386000000 0.8636000000 **** O 0 S 5 1.00 10662.2850000000 0.0007990000 1599.7097000000 0.0061530000 364.7252600000 0.0311570000 103.6517900000 0.1155960000 33.9058050000 0.3015520000 S 2 1.00 12.2874690000 0.4448700000 4.7568050000 0.2431720000 S 1 1.00 1.0042710000 1.0000000000 S 1 1.00 0.3006860000 1.0000000000 S 1 1.00 0.0900300000 1.0000000000 P 4 1.00 34.8564630000 0.0156480000 7.8431310000 0.0981970000 2.3062490000 0.3077680000 0.7231640000 0.4924700000 P 1 1.00 0.2148820000 1.0000000000 P 1 1.00 0.0638500000 1.0000000000 D 2 1.00 2.3062000000 0.2027000000 0.7232000000 0.5791000000 D 2 1.00 0.2149000000 0.7854500000 0.0639000000 0.5338700000 **** """) ccsd_e, wfn = psi4.properties('ccsd',properties=['dipole'],return_wfn=True) psi4.oeprop(wfn,"DIPOLE", "QUADRUPOLE", title="(OEPROP)CC") import warnings #TEST with warnings.catch_warnings(): #TEST warnings.simplefilter("ignore") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC DIPOLE X"), 0.000000000000,6,"CC DIPOLE X") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC DIPOLE Y"), 0.000000000000,6,"CC DIPOLE Y") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC DIPOLE Z"),-1.840334899884,6,"CC DIPOLE Z") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE XX"),-7.864006962064,6,"CC QUADRUPOLE XX") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE XY"), 0.000000000000,6,"CC QUADRUPOLE XY") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE XZ"), 0.000000000000,6,"CC QUADRUPOLE XZ") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE YY"),-4.537386915305,6,"CC QUADRUPOLE YY") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE YZ"), 0.000000000000,6,"CC QUADRUPOLE YZ") #TEST psi4.compare_values(psi4.variable("(OEPROP)CC QUADRUPOLE ZZ"),-6.325836255265,6,"CC QUADRUPOLE ZZ") #TEST psi4.core.print_variables()

ashutoshvt/psi4

tests/python/cc54/input.py

Python

lgpl-3.0

4,053

[ "Psi4" ]

185c8664d8dbe6d1925c118436247e52e717768f8114d504ada7143e2181dfe2

from __future__ import print_function import numpy as np from numpy import zeros, ones, einsum from .constants import tol6, tol8, tol12, Ha2eV, kb_HaK from .mathutil import delta_lorentzian from . import EigFile, Eigr2dFile, FanFile, DdbFile, GkkFile __author__ = "Gabriel Antonius" __all__ = ['QptAnalyzer'] class QptAnalyzer(object): def __init__(self, ddb_fname=None, eigq_fname=None, eigk_fname=None, eigr2d_fname=None, eigr2d0_fname=None, eigi2d_fname=None, fan_fname=None, fan0_fname=None, gkk_fname=None, gkk0_fname=None, wtq=1.0, smearing=0.00367, temperatures=None, omegase=None, asr=True, mu=None, ): # Files self.ddb = DdbFile(ddb_fname, read=False, asr=asr) self.eigq = EigFile(eigq_fname, read=False) self.eigr2d = Eigr2dFile(eigr2d_fname, read=False) self.eigi2d = Eigr2dFile(eigi2d_fname, read=False) self.fan = FanFile(fan_fname, read=False) self.eig0 = EigFile(eigk_fname, read=False) self.eigr2d0 = Eigr2dFile(eigr2d0_fname, read=False) self.fan0 = FanFile(fan0_fname, read=False) self.gkk = GkkFile(gkk_fname, read=False) self.gkk0 = GkkFile(gkk0_fname, read=False) self.wtq = wtq self.smearing = smearing self.omegase = omegase if omegase else list() self.temperatures = temperatures if temperatures else list() self.mu = mu @property def nkpt(self): if self.eigr2d.fname: return self.eigr2d.nkpt elif self.fan.fname: return self.fan.nkpt elif self.gkk.fname: return self.gkk.nkpt else: raise Exception("Don't know nkpt. No files to read.") @property def nband(self): if self.eigr2d.fname: return self.eigr2d.nband elif self.fan.fname: return self.fan.nband elif self.gkk.fname: return self.gkk.nband else: raise Exception("Don't know nband. No files to read.") @property def natom(self): return self.ddb.natom @property def nmode(self): return self.ddb.nmode @property def is_gamma(self): return self.ddb.is_gamma @property def qred(self): return self.ddb.qred @property def omega(self): return self.ddb.omega @property def nomegase(self): return len(self.omegase) @property def ntemp(self): return len(self.temperatures) @property def use_gkk(self): return (bool(self.gkk.fname) and bool(self.gkk0.fname)) @property def has_active(self): return (bool(self.fan.fname) and bool(self.fan0.fname)) or self.use_gkk def read_nonzero_files(self): """Read all nc files that are not specifically related to q=0.""" for f in (self.ddb, self.eigq, self.eigr2d, self.eigi2d, self.fan, self.gkk): if f.fname: f.read_nc() self.ddb.compute_dynmat() def read_ddb(self): """Read the ddb and diagonalize the matrix, setting omega.""" self.ddb.read_nc() self.ddb.compute_dynmat() def read_zero_files(self): """Read all nc files that are not specifically related to q=0.""" for f in (self.eig0, self.eigr2d0, self.fan0, self.gkk0): if f.fname: f.read_nc() def broadcast_zero_files(self): """Broadcast the data related to q=0 from master to all workers.""" if self.eig0.fname: self.eig0.broadcast() self.eig0.get_degen() if self.eigr2d0.fname: self.eigr2d0.broadcast() if self.fan0.fname: self.fan0.broadcast() if self.gkk0.fname: self.gkk0.broadcast() def get_occ_kq_nospin(self): """ Get the occupations, being either 0 or 1, regardless of spinor. Assumes a gapped system, where occupations are the same at all kpts. Returns: occ[nband] """ if self.eigr2d.fname: occ = self.eigr2d.occ[0,0,:] elif self.fan.fname: occ = self.fan.occ[0,0,:] elif self.gkk.fname: occ = self.gkk.occ[0,0,:] else: raise Exception("Don't know nband. No files to read.") if any(occ == 2.0): occ = occ / 2.0 return occ def get_max_val(self): """Get the maximum valence band energy.""" occ0 = self.get_occ_kq_nospin() eig = self.eigq.EIG[0,0,:] E_last = eig[0] for f, E in zip(occ0, eig): if f < 0.5: break E_last = E return E_last def get_min_cond(self): """Get the minimum conduction band energy.""" occ0 = self.get_occ_kq_nospin() eig = self.eigq.EIG[0,0,:] for f, E in zip(occ0, eig): if f <= 0.5: break return E def find_fermi_level(self): """ Find the Fermi level locally, using the eigenvalues at all k+q points available. Assuming a gapped system. """ return (self.get_max_val() + self.get_min_cond()) / 2.0 @staticmethod def reduce_array(arr, mode=False, temperature=False, omega=False): """ Eliminate dimensions from an array of shape (nmode, ntemp, nomegase, nkpt, nband) by summing over any or all of the first three dimension. mode: Keep the first dimension temperature: Keep the second dimension omega: Keep the third dimension """ # Find the final order of final_indices = '' if mode: final_indices += 'o' if temperature: final_indices += 't' if omega: final_indices += 'l' final_indices += 'kn' summation = 'otlkn->' + final_indices return einsum(summation, arr) def get_fan_ddw_sternheimer(self, mode=False, omega=False, temperature=False): """ Compute the fan and ddw contribution to the self-energy obtained from the Sternheimer equation, that is, the contribution of the upper bands. Do not include the q-point weight. Returns: fan, ddw The return arrays vary in dimensions, depending on the input arguments. These arrays are at most of dimension 5, as fan[nmode, ntemp, nomegase, nkpt, nband] ddw[nmode, ntemp, nomegase, nkpt, nband] Depending on the truth value of the input arguments, the dimension nomegase (omega) and ntemp (temperature) will be eliminated. The dimension nmode will be summed over in case mode=False. In the semi-static approximation, these quantities do not actually depend on omega, so the arrays are simply repated along the omega axis. """ nkpt = self.nkpt nband = self.nband natom = self.natom nmode = self.nmode nomegase = self.nomegase ntemp = self.ntemp # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() # FIXME this will not work for nsppol=2 # nmode, nkpt, nband fan = einsum('knabij,objai->okn', self.eigr2d.EIG2D, displ_red_FAN2) ddw = einsum('knabij,objai->okn', self.eigr2d0.EIG2D, displ_red_DDW2) # Temperature dependence factor n_B = self.ddb.get_bose(self.temperatures) tdep = 2 * n_B + 1 if temperature else ones((nmode,1)) # Omega dependence factor odep = ones(nomegase) if omega else ones(1) # nmode, ntemp, nkpt, nband fan = einsum('okn,ot->otkn', fan, tdep) ddw = einsum('okn,ot->otkn', ddw, tdep) # nmode, ntemp, nomega, nkpt, nband fan = einsum('otkn,l->otlkn', fan, odep) ddw = einsum('otkn,l->otlkn', ddw, odep) # Reduce the arrays fan = self.reduce_array(fan, mode=mode, temperature=temperature, omega=omega) ddw = self.reduce_array(ddw, mode=mode, temperature=temperature, omega=omega) return fan, ddw def get_fan_ddw_gkk2_active(self): """ Compute the squared gkk elements for the fan ddw terms. Returns: fan[nkpt, nband, nband, nmode] ddw[nkpt, nband, nband, nmode] """ if not self.has_active: raise Exception('You should provide GKK files or FAN files ' 'to compute active space contribution.') # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() if self.use_gkk: gkk2 = self.gkk.get_gkk_squared() gkk02 = self.gkk0.get_gkk_squared() else: gkk2 = self.fan.FAN gkk02 = self.fan0.FAN # nkpt, nband, nband, nmode fan = einsum('kniajbm,oabij->knmo', gkk2, displ_red_FAN2) ddw = einsum('kniajbm,oabij->knmo', gkk02, displ_red_DDW2) # Enforce the diagonal coupling terms to be zero at Gamma ddw = self.eig0.symmetrize_fan_degen(ddw) if self.is_gamma: fan = self.eig0.symmetrize_fan_degen(fan) return fan, ddw def get_fan_ddw_active(self, mode=False, omega=False, temperature=False, dynamical=True): """ Compute the fan and ddw contributions to the self-energy from the active space, that is, the the lower bands. Do not include the q-point weight. Returns: fan, ddw The return arrays vary in dimensions, depending on the input arguments. These arrays are at most of dimension 5, as fan[nmode, ntemp, nomegase, nkpt, nband] ddw[nmode, ntemp, nomegase, nkpt, nband] Depending on the truth value of the input arguments, the dimension nomegase (omega) and ntemp (temperature) will be eliminated. The dimension nmode will be summed over in case mode=False. The Debye-Waller term does not actually depends on omega, but this dimension is kept anyway. """ nkpt = self.nkpt nband = self.nband nmode = self.nmode if temperature: ntemp = self.ntemp temperatures = self.temperatures # Bose-Enstein occupation number # nmode, ntemp n_B = self.ddb.get_bose(temperatures) else: ntemp = 1 temperatures = zeros(1) n_B = zeros((nmode,1)) if omega: nomegase = self.nomegase omega_se = self.omegase else: # omega_se is measured from the bare eigenvalues nomegase = 1 omega_se = zeros(1) if dynamical: omega_q = self.ddb.omega[:].real else: omega_q = zeros(nmode) # Fermi-Dirac occupation number # nspin, nkpt, nband, ntemp occ = self.eigq.get_fermi_function(self.mu, temperatures) # G^2 # nkpt, nband, nband, nmode fan_g2, ddw_g2 = self.get_fan_ddw_gkk2_active() # DDW term # -------- # nkpt, nband occ0 = self.eig0.get_fermi_function_T0(self.mu)[0,:,:] # nkpt, nband, nband delta_E_ddw = (einsum('kn,m->knm', self.eig0.EIG[0,:,:].real, ones(nband)) - einsum('kn,m->kmn', self.eig0.EIG[0,:,:].real, ones(nband)) - einsum('m,kn->knm', ones(nband), (2*occ0-1)) * self.smearing * 1j) # nmode, nkpt, nband ddw = einsum('knmo,knm->okn', ddw_g2, 1.0 / delta_E_ddw) # nmode, ntemp tdep = 2 * n_B + 1 # FIXME This is not optimal: The mode indices will be summed # so there is no need to create an array this big. # in case omega=True and mode=False # nmode, ntemp, nkpt, nband ddw = einsum('okn,ot->otkn', ddw, tdep) odep = ones(nomegase) if omega else ones(0) # ntemp, nomega, nkpt, nband ddw = einsum('otkn,l->otlkn', ddw, ones(nomegase)) # Reduce the arrays ddw = self.reduce_array(ddw, mode=mode, temperature=temperature, omega=omega) # Fan term # -------- # nmode, ntemp, nomegase, nkpt, nband fan = zeros((nmode, ntemp, nomegase, nkpt, nband), dtype=complex) # n + 1 - f # nkpt, nband, nmode, ntemp num1 = (einsum('ot,kn->knot', n_B, ones((nkpt,nband))) + 1. - einsum('knt,o->knot', occ[0,:,:,:], ones(nmode))) # n + f # nkpt, nband, nmode, ntemp num2 = (einsum('ot,kn->knot', n_B, ones((nkpt,nband))) + einsum('knt,o->knot', occ[0,:,:,:], ones(nmode))) # nkpt, nband eta = (2 * occ0 - 1) * self.smearing * 1j for jband in range(nband): # nkpt, nband delta_E = ( self.eig0.EIG[0,:,:].real - einsum('k,n->kn', self.eigq.EIG[0,:,jband].real, ones(nband)) - eta) # nkpt, nband, nomegase delta_E_omega = (einsum('kn,l->knl', delta_E, ones(nomegase)) + einsum('kn,l->knl', ones((nkpt,nband)), omega_se)) # nkpt, nband, nomegase, nmode deno1 = (einsum('knl,o->knlo', delta_E_omega, ones(nmode)) - einsum('knl,o->knlo', ones((nkpt,nband,nomegase)), omega_q)) # nmode, nkpt, nband, nomegase, ntemp div1 = einsum('kot,knlo->oknlt', num1[:,jband,:,:], 1.0 / deno1) del deno1 # nkpt, nband, nomegase, nmode deno2 = (einsum('knl,o->knlo', delta_E_omega, ones(nmode)) + einsum('knl,o->knlo', ones((nkpt,nband,nomegase)), omega_q)) # nmode, nkpt, nband, nomegase, ntemp div2 = einsum('kot,knlo->oknlt', num2[:,jband,:,:], 1.0 / deno2) del deno2 # FIXME This is not optimal: The mode indices will be summed # so there is no need to create an array this big. # in case omega=True and mode=False # nmode, ntemp, nomegase, nkpt, nband fan += einsum('kno,oknlt->otlkn', fan_g2[:,:,jband,:], div1 + div2) del div1, div2 # Reduce the arrays fan = self.reduce_array(fan, mode=mode, temperature=temperature, omega=omega) return fan, ddw def get_fan_ddw(self, mode=False, temperature=False, omega=False, dynamical=False): kwargs = dict( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) fan_stern, ddw_stern = self.get_fan_ddw_sternheimer( mode=mode, temperature=temperature, omega=omega, ) fan_active, ddw_active = self.get_fan_ddw_active( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) fan = fan_active + fan_stern ddw = ddw_active + ddw_stern return fan, ddw def get_self_energy(self, mode=False, temperature=False, omega=False, dynamical=True, only_sternheimer=False, only_active=False, only_fan=False, only_ddw=False, ): if only_sternheimer and only_active: raise Exception( 'only_sternheimer and only_active cannot be True at the same time') elif only_sternheimer: fan, ddw = self.get_fan_ddw_sternheimer( mode=mode, temperature=temperature, omega=omega, ) elif only_active: fan, ddw = self.get_fan_ddw_active( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) else: fan, ddw = self.get_fan_ddw( mode=mode, temperature=temperature, omega=omega, dynamical=dynamical) if only_fan: se_q = fan elif only_ddw: se_q = - ddw else: se_q = fan - ddw se = self.wtq * se_q se = self.eig0.make_average(se) return se def get_broadening(self, mode=False, temperature=False, omega=False, dynamical=True): """ Compute the zp broadening contribution from one q-point in a dynamical scheme. Only take the active space contribution. """ nkpt = self.nkpt nband = self.nband nmode = self.nmode if temperature: ntemp = self.ntemp temperatures = self.temperatures # Bose-Enstein occupation number # nmode, ntemp n_B = self.ddb.get_bose(temperatures) else: ntemp = 1 temperatures = zeros(1) n_B = zeros((nmode,1)) if omega: nomegase = self.nomegase omega_se = self.omegase else: # omega_se is measured from the bare eigenvalues nomegase = 1 omega_se = zeros(1) if dynamical: omega_q = self.ddb.omega[:].real else: omega_q = zeros(nmode) # Fermi-Dirac occupation number # nspin, nkpt, nband, ntemp occ = self.eigq.get_fermi_function(self.mu, temperatures) # nkpt, nband, ntemp f = occ[0] # nkpt, nband occ0 = self.eig0.get_fermi_function_T0(self.mu)[0,:,:] # nkpt, nband, nband, nmode fan_g2, ddw_g2 = self.get_fan_ddw_gkk2_active() # nmode, ntemp, nkpt n_B = einsum('ot,q->otq', n_B, ones(nkpt)) # nmode, ntemp, nkpt,nband f = einsum('qmt,o->otqm', f, ones(nmode)) # nkpt, nband sign = np.sign(- (2 * occ0 - 1.)) broadening = zeros((nmode,ntemp,nomegase,nkpt,nband)) for jband in range(nband): # nmode, ntemp, nkpt num1 = (n_B + f[...,jband]) num2 = (n_B + 1 - f[...,jband]) # nkpt, nband delta_E = ( self.eig0.EIG[0,:,:].real - einsum('q,n->qn', self.eigq.EIG[0,:,jband].real, ones(nband)) ) # nkpt, nband, nomegase delta_E_omega = (einsum('kn,l->knl', delta_E, ones(nomegase)) + einsum('kn,l->knl', ones((nkpt,nband)), omega_se)) # nmode, nkpt, nband, nomegase deno1 = ( einsum('knl,o->oknl', delta_E_omega, ones(nmode)) + einsum('o,knl->oknl', omega_q, ones((nkpt,nband,nomegase))) ) # nmode, nkpt, nband, nomegase deno2 = ( einsum('knl,o->oknl', delta_E_omega, ones(nmode)) - einsum('o,knl->oknl', omega_q, ones((nkpt,nband,nomegase))) ) # nmode, nkpt, nband, nomegase delta1 = np.pi * delta_lorentzian(deno1, self.smearing) delta2 = np.pi * delta_lorentzian(deno2, self.smearing) # nmode, ntemp, nomegase, nkpt, nband term1 = einsum('otk,oknl->otlkn', num1, delta1) term2 = einsum('otk,oknl->otlkn', num2, delta2) deltas = einsum('kn,otlkn->otlkn', sign, term1 + term2) broadening_j = einsum('kno,otlkn->otlkn', fan_g2[:,:,jband,:], deltas) broadening += broadening_j.real # Reduce the arrays broadening = self.reduce_array(broadening, mode=mode, temperature=temperature, omega=omega) broadening *= self.wtq broadening = self.eig0.make_average(broadening) return broadening def get_zp_self_energy(self): """ Compute the zp frequency-dependent dynamical self-energy from one q-point. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega) = Sigma_kn(omega + E^0_kn) Returns: sigma[nkpt,nband,nomegase] """ self.sigma = self.get_self_energy( mode=False, temperature=False, omega=True, dynamical=True, only_sternheimer=False, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('lkn->knl', self.sigma) # FIXME why?? return self.sigma def get_td_self_energy(self): """ Compute the temperature depended and frequency-dependent dynamical self-energy from one q-point. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega,T) = Sigma_kn(omega + E^0_kn, T) Returns: sigma[nkpt,nband,nomegase,ntemp] """ self.sigma = self.get_self_energy( mode=False, temperature=True, omega=True, dynamical=True, only_sternheimer=False, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('tlkn->knlt', self.sigma) # FIXME why?? return self.sigma def get_zp_self_energy_active(self): """ Compute the zp frequency-dependent dynamical self-energy from one q-point. Only include the active space contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega) = Sigma_kn(omega + E^0_kn) Returns: sigma[nkpt,nband,nomegase] """ self.sigma = self.get_self_energy( mode=False, temperature=False, omega=True, dynamical=True, only_sternheimer=False, only_active=True, ) # nkpt, nband, nomegase, nband self.sigma = einsum('lkn->knl', self.sigma) # FIXME why?? return self.sigma def get_zp_self_energy_sternheimer(self): """ Compute the zp frequency-dependent dynamical self-energy from one q-point. Only include the Sternheimer contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega) = Sigma_kn(omega + E^0_kn) Returns: sigma[nkpt,nband,nomegase] """ self.sigma = self.get_self_energy( mode=False, temperature=False, omega=True, dynamical=True, only_sternheimer=True, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('lkn->knl', self.sigma) # FIXME why?? return self.sigma def get_td_self_energy_active(self): """ Compute the temperature depended and frequency-dependent dynamical self-energy from one q-point. Only include the active space contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega,T) = Sigma_kn(omega + E^0_kn, T) Returns: sigma[nkpt,nband,nomegase,ntemp] """ self.sigma = self.get_self_energy( mode=False, temperature=True, omega=True, dynamical=True, only_sternheimer=False, only_active=True, ) # nkpt, nband, nomegase, nband self.sigma = einsum('tlkn->knlt', self.sigma) # FIXME why?? return self.sigma def get_td_self_energy_sternheimer(self): """ Compute the temperature depended and frequency-dependent dynamical self-energy from one q-point. Only include the Sternheimer contribution. The self-energy is evaluated on a frequency mesh 'omegase' that is shifted by the bare energies, such that, what is retured is Simga'_kn(omega,T) = Sigma_kn(omega + E^0_kn, T) Returns: sigma[nkpt,nband,nomegase,ntemp] """ self.sigma = self.get_self_energy( mode=False, temperature=True, omega=True, dynamical=True, only_sternheimer=True, only_active=False, ) # nkpt, nband, nomegase, nband self.sigma = einsum('tlkn->knlt', self.sigma) # FIXME why?? return self.sigma def get_zpr_static_sternheimer(self): """Compute the q-point zpr contribution in a static scheme.""" self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=False, only_sternheimer=True, only_active=False, ).real return self.zpr def get_zpr_static(self): """ Compute the q-point zpr contribution in a static scheme, with the transitions split between active and sternheimer. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=False, only_sternheimer=False, only_active=False, ).real return self.zpr def get_zpr_dynamical(self): """ Compute the q-point zpr contribution in a static scheme with the transitions split between active and sternheimer. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=True, only_sternheimer=False, only_active=False, ).real return self.zpr def get_tdr_static(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a static scheme, with the transitions split between active and sternheimer. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=False, only_sternheimer=False, only_active=False, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_tdr_dynamical(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a dynamical scheme. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=True, only_sternheimer=False, only_active=False, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_tdr_static_nosplit(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a static scheme. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=False, only_sternheimer=True, only_active=False, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_tdr_dynamical_active(self): """ Compute the q-point contribution to the temperature-dependent renormalization in a dynamical scheme, taking only the active space contribution. """ self.tdr = self.get_self_energy( mode=False, temperature=True, omega=False, dynamical=True, only_sternheimer=False, only_active=True, ).real # nkpt, nband, ntemp self.tdr = einsum('tkn->knt', self.tdr) # FIXME why?? return self.tdr def get_zpr_dynamical_active(self): """ Compute the q-point contribution to the zero point renormalization in a dynamical scheme, taking only the active space contribution. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=True, only_sternheimer=False, only_active=True, ).real # nkpt, nband, ntemp return self.zpr def get_zpr_static_modes(self): """ Compute the q-point zpr contribution in a static scheme, with the transitions split between active and sternheimer. Retain the mode decomposition of the zpr. """ self.zpr = self.get_self_energy( mode=True, temperature=False, omega=False, dynamical=False, only_sternheimer=False, only_active=False, ).real # nmode, nkpt, nband return self.zpr # FIXME use self.zpr_mode? def get_zpb_dynamical(self): """ Compute the zp broadening contribution from one q-point in a dynamical scheme. Only take the active space contribution. Returns: zpb[nkpt,nband] """ self.zpb = self.get_broadening(mode=False, temperature=False, omega=False, dynamical=True) return self.zpb def get_tdb_dynamical(self): """ Compute the td broadening contribution from one q-point in a dynamical scheme. Only take the active space contribution. Returns: zpb[nkpt,nband,ntemp] """ self.tdb = self.get_broadening(mode=False, temperature=True, omega=False, dynamical=True) self.tdb = einsum('tkn->knt', self.tdb) # FIXME why?? return self.tdb def get_zpb_static(self): """ Compute the zp broadening contribution from one q-point in a static scheme. Only take the active space contribution. Returns: zpb[nkpt,nband] """ self.zpb = self.get_broadening(mode=False, temperature=False, omega=False, dynamical=False) return self.zpb def get_tdb_static(self): """ Compute the td broadening contribution from one q-point in a static scheme. Only take the active space contribution. Returns: zpb[nkpt,nband,ntemp] """ self.tdb = self.get_broadening(mode=False, temperature=True, omega=False, dynamical=False) self.tdb = einsum('tkn->knt', self.tdb) # FIXME why?? return self.tdb def get_tdb_static_nosplit(self): """ Compute the q-point contribution to the temperature-dependent broadening in a static scheme from the EIGI2D files. """ nkpt = self.nkpt nband = self.nband natom = self.natom ntemp = self.ntemp # These indicies be swapped at the end self.tdb = zeros((ntemp, nkpt, nband), dtype=complex) # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() bose = self.ddb.get_bose(self.temperatures) fan_corrQ = einsum('ijklmn,olnkm->oij', self.eigi2d.EIG2D, displ_red_FAN2) for imode in np.arange(3*natom): for tt, T in enumerate(self.temperatures): self.tdb[tt,:,:] += np.pi * fan_corrQ[imode,:,:] * (2*bose[imode,tt] + 1.) self.tdb = self.tdb * self.wtq self.tdb = self.eig0.make_average(self.tdb) # nkpt, nband, ntemp self.tdb = np.einsum('tkn->knt', self.tdb) return self.tdb def get_zpb_static_nosplit(self): """ Compute the zp broadening contribution from one q-point in a static scheme from the EIGI2D files. """ nkpt = self.nkpt nband = self.nband natom = self.natom self.zpb = zeros((nkpt, nband), dtype=complex) # Get reduced displacement (scaled with frequency) displ_red_FAN2, displ_red_DDW2 = self.ddb.get_reduced_displ_squared() fan_corrQ = einsum('ijklmn,olnkm->oij', self.eigi2d.EIG2D, displ_red_FAN2) self.zpb += np.pi * np.sum(fan_corrQ, axis=0) self.zpb = self.zpb * self.wtq if np.any(self.zpb[:,:].imag > tol12): warnings.warn("The real part of the broadening is non zero: {}".format(broadening)) self.zpb = self.eig0.make_average(self.zpb) return self.zpb def get_zpr_ddw_active(self): """ Compute the q-point zpr contribution in a static scheme with the transitions split between active and sternheimer. """ self.zpr = self.get_self_energy( mode=False, temperature=False, omega=False, dynamical=False, only_sternheimer=False, only_active=True, only_ddw=True, ).real return self.zpr

jmbeuken/abinit

scripts/post_processing/ElectronPhononCoupling/ElectronPhononCoupling/core/qptanalyzer.py

Python

gpl-3.0

34,212

[ "DIRAC" ]

b0b8dbe6d1c83ea8b9b09f42206c7561554a5156367c4b677ffa30ccc2ff52aa

# # tsne.py # # Implementation of t-SNE in Python. The implementation was tested on Python 2.5.1, and it requires a working # installation of NumPy. The implementation comes with an example on the MNIST dataset. In order to plot the # results of this example, a working installation of matplotlib is required. # The example can be run by executing: ipython tsne.py -pylab # # # Created by Laurens van der Maaten on 20-12-08. # Copyright (c) 2008 Tilburg University. All rights reserved. import numpy as np def Hbeta(D = np.array([]), beta = 1.0): """Compute the perplexity and the P-row for a specific value of the precision of a Gaussian distribution.""" # Compute P-row and corresponding perplexity P = np.exp(-D.copy() * beta); sumP = sum(P); H = np.log(sumP) + beta * np.sum(D * P) / sumP; P = P / sumP; return H, P; def x2p(X = np.array([]), tol = 1e-5, perplexity = 30.0): """Performs a binary search to get P-values in such a way that each conditional Gaussian has the same perplexity.""" # Initialize some variables print "Computing pairwise distances..." (n, d) = X.shape; sum_X = np.sum(np.square(X), 1); D = np.add(np.add(-2 * np.dot(X, X.T), sum_X).T, sum_X); P = np.zeros((n, n)); beta = np.ones((n, 1)); logU = np.log(perplexity); # Loop over all datapoints for i in range(n): # Print progress if i % 500 == 0: print "Computing P-values for point ", i, " of ", n, "..." # Compute the Gaussian kernel and entropy for the current precision betamin = -np.inf; betamax = np.inf; Di = D[i, np.concatenate((np.r_[0:i], np.r_[i+1:n]))]; (H, thisP) = Hbeta(Di, beta[i]); # Evaluate whether the perplexity is within tolerance Hdiff = H - logU; tries = 0; while np.abs(Hdiff) > tol and tries < 50: # If not, increase or decrease precision if Hdiff > 0: betamin = beta[i]; if betamax == np.inf or betamax == -np.inf: beta[i] = beta[i] * 2; else: beta[i] = (beta[i] + betamax) / 2; else: betamax = beta[i]; if betamin == np.inf or betamin == -np.inf: beta[i] = beta[i] / 2; else: beta[i] = (beta[i] + betamin) / 2; # Recompute the values (H, thisP) = Hbeta(Di, beta[i]); Hdiff = H - logU; tries = tries + 1; # Set the final row of P P[i, np.concatenate((np.r_[0:i], np.r_[i+1:n]))] = thisP; # Return final P-matrix print "Mean value of sigma: ", np.mean(np.sqrt(1 / beta)) return P; def pca(X = np.array([]), no_dims = 50): """Runs PCA on the NxD array X in order to reduce its dimensionality to no_dims dimensions.""" print "Preprocessing the data using PCA..." (n, d) = X.shape; X = X - np.tile(np.mean(X, 0), (n, 1)); (l, M) = np.linalg.eig(np.dot(X.T, X)); Y = np.dot(X, M[:,0:no_dims]); np.testing.assert_array_almost_equal(np.imag(Y), np.zeros(Y.shape)) return np.real(Y); def tsne(X = np.array([]), no_dims = 2, initial_dims = 50, perplexity = 30.0): """Runs t-SNE on the dataset in the NxD array X to reduce its dimensionality to no_dims dimensions. The syntaxis of the function is Y = tsne.tsne(X, no_dims, perplexity), where X is an NxD NumPy array.""" # Check inputs if X.dtype != "float64": print "Error: array X should have type float64."; return -1; #if no_dims.__class__ != "<type 'int'>": # doesn't work yet! # print "Error: number of dimensions should be an integer."; # return -1; # Initialize variables X = pca(X, initial_dims); (n, d) = X.shape; max_iter = 1000; initial_momentum = 0.5; final_momentum = 0.8; eta = 500; min_gain = 0.01; Y = np.random.randn(n, no_dims); dY = np.zeros((n, no_dims)); iY = np.zeros((n, no_dims)); gains = np.ones((n, no_dims)); # Compute P-values P = x2p(X, 1e-5, perplexity); P = P + np.transpose(P); P = P / np.sum(P); P = P * 4; # early exaggeration P = np.maximum(P, 1e-12); # Run iterations for iter in range(max_iter): # Compute pairwise affinities sum_Y = np.sum(np.square(Y), 1); num = 1 / (1 + np.add(np.add(-2 * np.dot(Y, Y.T), sum_Y).T, sum_Y)); num[range(n), range(n)] = 0; Q = num / np.sum(num); Q = np.maximum(Q, 1e-12); # Compute gradient PQ = P - Q; for i in range(n): dY[i,:] = np.sum(np.tile(PQ[:,i] * num[:,i], (no_dims, 1)).T * (Y[i,:] - Y), 0); # Perform the update if iter < 20: momentum = initial_momentum else: momentum = final_momentum gains = (gains + 0.2) * ((dY > 0) != (iY > 0)) + (gains * 0.8) * ((dY > 0) == (iY > 0)); gains[gains < min_gain] = min_gain; iY = momentum * iY - eta * (gains * dY); Y = Y + iY; Y = Y - np.tile(np.mean(Y, 0), (n, 1)); # Compute current value of cost function if (iter + 1) % 10 == 0: C = np.sum(P * np.log(P / Q)); print "Iteration ", (iter + 1), ": error is ", C # Stop lying about P-values if iter == 100: P = P / 4; # Return solution return Y; if __name__ == "__main__": import pylab print "Run Y = tsne.tsne(X, no_dims, perplexity) to perform t-SNE on your dataset." print "Running example on 2,500 MNIST digits..." X = np.loadtxt("mnist2500_X.txt"); labels = np.loadtxt("mnist2500_labels.txt"); Y = tsne(X, 2, 50, 20.0); pylab.scatter(Y[:,0], Y[:,1], 20, labels);

afraser/CellProfiler-Analyst

cpa/tsne.py

Python

gpl-2.0

5,205

[ "Gaussian" ]

19443cc85cf3ba62aad79dc3d4331e460883e83ce4333dcc8455d6f9c891d732

# Copyright 2017 Amazon.com, Inc. or its affiliates. All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"). You may not # use this file except in compliance with the License. A copy of the License # is located at # # http://aws.amazon.com/apache2.0/ # # or in the "license" file accompanying this file. This file is distributed on # an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either # express or implied. See the License for the specific language governing # permissions and limitations under the License. import logging import math from typing import Dict, Optional, Tuple, Union import mxnet as mx import numpy as np from . import constants as C from . import utils logger = logging.getLogger(__name__) def activation(data: mx.sym.Symbol, act_type: str) -> mx.sym.Symbol: """ Apply custom or standard activation. Custom activation types include: - Swish-1, also called Sigmoid-Weighted Linear Unit (SiLU): Ramachandran et al. (https://arxiv.org/pdf/1710.05941.pdf), Elfwing et al. (https://arxiv.org/pdf/1702.03118.pdf) - Gaussian Error Linear Unit (GELU): Hendrycks and Gimpel (https://arxiv.org/pdf/1606.08415.pdf) :param data: input Symbol of any shape. :param act_type: Type of activation. :return: output Symbol with same shape as input. """ # TODO: Contribute these to MXNet? For now it appears that registered activation types must be implemented in C++. if act_type == C.SWISH1: return data * mx.sym.Activation(data, act_type="sigmoid") elif act_type == C.GELU: # Approximation of x * gaussian_cdf(x) used by Hendrycks and Gimpel return 0.5 * data * (1 + mx.sym.Activation((math.sqrt(2 / math.pi) * (data + (0.044715 * (data**3)))), act_type="tanh")) else: return mx.sym.Activation(data, act_type=act_type) class LayerNormalization: """ Implements Ba et al, Layer Normalization (https://arxiv.org/abs/1607.06450). :param prefix: Optional prefix of layer name. :param scale: Optional variable for scaling of shape (num_hidden,). Will be created if None. :param shift: Optional variable for shifting of shape (num_hidden,). Will be created if None. :param scale_init: Initial value of scale variable if scale is None. Default 1.0. :param shift_init: Initial value of shift variable if shift is None. Default 0.0. """ def __init__(self, prefix: str = 'layernorm', scale: Optional[mx.sym.Symbol] = None, shift: Optional[mx.sym.Symbol] = None, scale_init: float = 1.0, shift_init: float = 0.0) -> None: self.prefix = prefix self.scale = scale if scale is not None else mx.sym.Variable('%s_gamma' % prefix, init=mx.init.Constant(value=scale_init)) self.shift = shift if shift is not None else mx.sym.Variable('%s_beta' % prefix, init=mx.init.Constant(value=shift_init)) def __call__(self, data: mx.sym.Symbol, eps: float = 1e-06) -> mx.sym.Symbol: """ Normalizes hidden units of data as follows: data = scale * (data - mean) / sqrt(var + eps) + shift Normalization is performed over the last dimension of the input data. :param data: Data to normalize. Shape: (d0, ..., dn, num_hidden). :param eps: Variance epsilon. :return: inputs_norm: Normalized inputs. Shape: (d0, ..., dn, num_hidden). """ return mx.sym.LayerNorm(data=data, gamma=self.scale, beta=self.shift, axis=-1, eps=eps, output_mean_var=False, name=self.prefix) class LHUC: """ Learning Hidden Unit Contribution David Vilar. "Learning Hidden Unit Contribution for Adapting Neural Machine Translation Models" NAACL 2018 :param num_hidden: Number of hidden units of the layer to be modified. :param weight: Optional parameter vector. :param prefix: Optional prefix for created parameters (if not given as weight). """ def __init__(self, num_hidden: int, weight: Optional[mx.sym.Symbol] = None, prefix: str = "") -> None: self.num_hidden = num_hidden self.prefix = prefix if weight is None: self.params = mx.sym.Variable(self.prefix + C.LHUC_NAME, shape=(self.num_hidden,), init=mx.init.Uniform(0.1), dtype="float32") else: self.params = weight def __call__(self, inputs: mx.sym.Symbol, name: Optional[str] = None) -> mx.sym.Symbol: # We use a sigmoid with amplitude 2 for weighting the hidden units. The # activation is dampened when the value of the sigmoid is close to 0, and # strengthened when it's close to 2 (see also original paper) weight_vector = 2 * mx.sym.Activation(data=self.params, act_type="sigmoid") out = mx.sym.broadcast_mul(weight_vector, inputs, name=name) return out class WeightNormalization: """ Implements Weight Normalization, see Salimans & Kingma 2016 (https://arxiv.org/abs/1602.07868). For a given tensor the normalization is done per hidden dimension. :param weight: Weight tensor of shape: (num_hidden, d1, d2, ...). :param num_hidden: Size of the first dimension. :param ndim: The total number of dimensions of the weight tensor. :param prefix: The prefix used for naming. """ def __init__(self, weight, num_hidden, ndim=2, prefix: str = '') -> None: self.prefix = prefix self.weight = weight self.num_hidden = num_hidden self.scale = mx.sym.Variable("%swn_scale" % prefix, shape=tuple([num_hidden] + [1] * (ndim - 1)), init=mx.init.Constant(value=1.0)) def __call__(self, weight: Optional[mx.nd.NDArray] = None, scale: Optional[mx.nd.NDArray] = None) -> mx.sym.Symbol: """ Normalize each hidden dimension and scale afterwards :return: A weight normalized weight tensor. """ if weight is None and scale is None: return mx.sym.broadcast_mul(lhs=mx.sym.L2Normalization(self.weight, mode='instance'), rhs=self.scale, name="%swn_scale" % self.prefix) else: assert isinstance(weight, mx.nd.NDArray) assert isinstance(scale, mx.nd.NDArray) return mx.nd.broadcast_mul(lhs=mx.nd.L2Normalization(weight, mode='instance'), rhs=scale) class OutputLayer: """ Defines the output layer of Sockeye decoders. Supports weight tying and weight normalization. :param hidden_size: Decoder hidden size. :param vocab_size: Target vocabulary size. :param weight_normalization: Whether to apply weight normalization. :param prefix: Prefix used for naming. """ def __init__(self, hidden_size: int, vocab_size: int, weight: Optional[mx.sym.Symbol], weight_normalization: bool, prefix: str = C.DEFAULT_OUTPUT_LAYER_PREFIX) -> None: self.vocab_size = vocab_size self.prefix = prefix if weight is None: self.w = mx.sym.Variable("%sweight" % self.prefix, shape=(vocab_size, hidden_size)) else: self.w = weight self.weight_normalization = weight_normalization if weight_normalization: logger.info("Normalizing output layer weights.") self.weight_norm = WeightNormalization(self.w, num_hidden=vocab_size, ndim=2, prefix=self.prefix) self.w = self.weight_norm() self.b = mx.sym.Variable("%sbias" % self.prefix) def __call__(self, hidden: Union[mx.sym.Symbol, mx.nd.NDArray], weight: Optional[mx.nd.NDArray] = None, bias: Optional[mx.nd.NDArray] = None): """ Linear transformation to vocab size. Returns logits. :param hidden: Decoder representation for n elements. Shape: (n, self.num_hidden). :return: Logits. Shape(n, self.vocab_size). """ if isinstance(hidden, mx.sym.Symbol): # TODO dropout? return mx.sym.FullyConnected(data=hidden, num_hidden=self.vocab_size, weight=self.w, bias=self.b, flatten=False, name=C.LOGITS_NAME) # Equivalent NDArray implementation (requires passed weights/biases) assert isinstance(hidden, mx.nd.NDArray) utils.check_condition(weight is not None and bias is not None, "OutputLayer NDArray implementation requires passing weight and bias NDArrays.") return mx.nd.FullyConnected(data=hidden, num_hidden=bias.shape[0], weight=weight, bias=bias, flatten=False) def split_heads(x: mx.sym.Symbol, depth_per_head: int, heads: int) -> mx.sym.Symbol: """ Returns a symbol with head dimension folded into batch and depth divided by the number of heads. :param x: Symbol of shape (batch, length, depth). :param depth_per_head: Depth per head. :param heads: Number of heads. :return: Symbol of shape (batch * heads, length, depth_per_heads). """ # (batch, length, heads, depth_per_head) x = mx.sym.reshape(data=x, shape=(0, -1, heads, depth_per_head)) # (batch, heads, length, depth/heads) x = mx.sym.transpose(data=x, axes=(0, 2, 1, 3)) # (batch * heads, length, depth/heads) return mx.sym.reshape(data=x, shape=(-3, -1, depth_per_head)) def combine_heads(x: mx.sym.Symbol, depth_per_head: int, heads: int) -> mx.sym.Symbol: """ Returns a symbol with both batch & length, and head & depth dimensions combined. :param x: Symbol of shape (batch * heads, length, depth_per_head). :param depth_per_head: Depth per head. :param heads: Number of heads. :return: Symbol of shape (batch, length, depth). """ # (batch, heads, length, depth_per_head) x = mx.sym.reshape(data=x, shape=(-4, -1, heads, 0, depth_per_head)) # (batch, length, heads, depth_per_head) x = mx.sym.transpose(x, axes=(0, 2, 1, 3)) # (batch, length, depth) return mx.sym.reshape(x, shape=(-1, 0, depth_per_head * heads)) def broadcast_to_heads(x: mx.sym.Symbol, num_heads: int, ndim: int, fold_heads: bool = True) -> mx.sym.Symbol: """ Broadcasts batch-major input of shape (batch, d1 ... dn-1) to (batch*heads, d1 ... dn-1). :param x: Batch-major input. Shape: (batch, d1 ... dn-1). :param num_heads: Number of heads. :param ndim: Number of dimensions in x. :param fold_heads: Whether to fold heads dimension into batch dimension. :return: Tensor with each sample repeated heads-many times. Shape: (batch * heads, d1 ... dn-1) if fold_heads == True, (batch, heads, d1 ... dn-1) else. """ dims = [0] * (ndim - 1) # x: (batch, 1) x = mx.sym.expand_dims(x, axis=1) # x: (batch, heads, dims...) x = mx.sym.broadcast_to(x, shape=[0, num_heads] + dims) if fold_heads: # (batch * heads, dims...) return mx.sym.reshape(x, shape=[-3] + dims) else: # x: (batch, heads, dims...) return x def dot_attention(queries: mx.sym.Symbol, keys: mx.sym.Symbol, values: mx.sym.Symbol, lengths: Optional[mx.sym.Symbol] = None, dropout: float = 0.0, bias: Optional[mx.sym.Symbol] = None, prefix: Optional[str] = ''): """ Computes dot attention for a set of queries, keys, and values. :param queries: Attention queries. Shape: (n, lq, d). :param keys: Attention keys. Shape: (n, lk, d). :param values: Attention values. Shape: (n, lk, dv). :param lengths: Optional sequence lengths of the keys. Shape: (n,). :param dropout: Dropout probability. :param bias: Optional 3d bias tensor. :param prefix: Optional prefix :return: 'Context' vectors for each query. Shape: (n, lq, dv). """ utils.check_condition(lengths is not None or bias is not None, "Must provide either length or bias argument for masking") # (n, lq, lk) logits = mx.sym.batch_dot(lhs=queries, rhs=keys, transpose_b=True, name='%sdot' % prefix) if lengths is not None: # mask lk dimension # (lk, n, lq) logits = mx.sym.transpose(data=logits, axes=(2, 0, 1)) logits = mx.sym.SequenceMask(data=logits, use_sequence_length=True, sequence_length=lengths, value=C.LARGE_NEGATIVE_VALUE) # (n, lq, lk) logits = mx.sym.transpose(data=logits, axes=(1, 2, 0)) if bias is not None: logits = mx.sym.broadcast_add(logits, bias, name='%sbias_add' % prefix) probs = mx.sym.softmax(logits, axis=-1) probs = mx.sym.Dropout(probs, p=dropout) if dropout > 0.0 else probs # (n, lq, lk) x (n, lk, dv) -> (n, lq, dv) return mx.sym.batch_dot(lhs=probs, rhs=values, name='%scontexts' % prefix) class MultiHeadAttentionBase: """ Base class for Multi-head attention. :param prefix: Attention prefix. :param depth_att: Attention depth / number of hidden units. :param heads: Number of attention heads. :param depth_out: Output depth / number of output units. :param dropout: Dropout probability on attention scores """ def __init__(self, prefix: str, depth_att: int = 512, heads: int = 8, depth_out: int = 512, dropout: float = 0.0) -> None: self.prefix = prefix utils.check_condition(depth_att % heads == 0, "Number of heads (%d) must divide attention depth (%d)" % (heads, depth_att)) self.depth = depth_att self.heads = heads self.depth_out = depth_out self.dropout = dropout self.depth_per_head = self.depth // self.heads self.w_h2o = mx.sym.Variable("%sh2o_weight" % prefix) def _attend(self, queries: mx.sym.Symbol, keys: mx.sym.Symbol, values: mx.sym.Symbol, lengths: Optional[mx.sym.Symbol] = None, bias: Optional[mx.sym.Symbol] = None) -> mx.sym.Symbol: """ Returns context vectors of multi-head dot attention. :param queries: Query tensor. Shape: (batch_size, query_max_length, depth). :param keys: Keys. Shape: (batch_size, memory_max_length, depth). :param values: Values. Shape: (batch_size, memory_max_length, depth). :param lengths: Optional lengths of keys. Shape: (batch_size,). :param bias: Optional 3d bias. :return: Context vectors. Shape: (batch_size, query_max_length, output_depth). """ # scale by sqrt(depth_per_head) queries = queries * (self.depth_per_head ** -0.5) # (batch*heads, length, depth/heads) queries = split_heads(queries, self.depth_per_head, self.heads) keys = split_heads(keys, self.depth_per_head, self.heads) values = split_heads(values, self.depth_per_head, self.heads) lengths = broadcast_to_heads(lengths, self.heads, ndim=1, fold_heads=True) if lengths is not None else lengths # (batch*heads, query_max_length, depth_per_head) contexts = dot_attention(queries, keys, values, lengths=lengths, dropout=self.dropout, bias=bias, prefix=self.prefix) # (batch, query_max_length, depth) contexts = combine_heads(contexts, self.depth_per_head, self.heads) # contexts: (batch, query_max_length, output_depth) contexts = mx.sym.FullyConnected(data=contexts, weight=self.w_h2o, no_bias=True, num_hidden=self.depth_out, flatten=False) return contexts class MultiHeadSelfAttention(MultiHeadAttentionBase): """ Multi-head self-attention. Independent linear projections of inputs serve as queries, keys, and values for the attention. :param prefix: Attention prefix. :param depth_att: Attention depth / number of hidden units. :param heads: Number of attention heads. :param depth_out: Output depth / number of output units. :param dropout: Dropout probability on attention scores """ def __init__(self, prefix: str, depth_att: int = 512, heads: int = 8, depth_out: int = 512, dropout: float = 0.0) -> None: super().__init__(prefix, depth_att, heads, depth_out, dropout) self.w_i2h = mx.sym.Variable("%si2h_weight" % prefix) def __call__(self, inputs: mx.sym.Symbol, input_lengths: Optional[mx.sym.Symbol] = None, bias: Optional[mx.sym.Symbol] = None, cache: Optional[Dict[str, Optional[mx.sym.Symbol]]] = None) -> mx.sym.Symbol: """ Computes multi-head attention on a set of inputs, serving as queries, keys, and values. If sequence lengths are provided, they will be used to mask the attention scores. A bias mask may also be used to mask the attention scores. May also use a cache of previously computed inputs. Returns a symbol of shape (batch, max_length, output_depth). :param inputs: Input Data. Shape: (batch, max_length, input_depth). :param input_lengths: Optional lengths of inputs to mask attention scores. Shape: (batch, 1). :param bias: Optional 3d bias tensor to mask attention scores. :param cache: Optional dictionary of previously computed keys and values. :return: Symbol of shape (batch, max_length, output_depth). """ # combined: (batch, max_length, depth * 3) combined = mx.sym.FullyConnected(data=inputs, weight=self.w_i2h, no_bias=True, num_hidden=self.depth * 3, flatten=False, name="%sqkv_transform" % self.prefix) # split into query, keys and values # (batch, max_length, depth) # pylint: disable=unbalanced-tuple-unpacking queries, keys, values = mx.sym.split(data=combined, num_outputs=3, axis=2) if cache is not None: # append new keys & values to cache, update the cache keys = cache['k'] = keys if cache['k'] is None else mx.sym.concat(cache['k'], keys, dim=1) values = cache['v'] = values if cache['v'] is None else mx.sym.concat(cache['v'], values, dim=1) return self._attend(queries, keys, values, lengths=input_lengths, bias=bias) class MultiHeadAttention(MultiHeadAttentionBase): """ Multi-head attention layer for queries independent from keys/values. :param prefix: Attention prefix. :param depth_att: Attention depth / number of hidden units. :param heads: Number of attention heads. :param depth_out: Output depth / number of output units. :param dropout: Dropout probability on attention scores """ def __init__(self, prefix: str, depth_att: int = 512, heads: int = 8, depth_out: int = 512, dropout: float = 0.0) -> None: super().__init__(prefix, depth_att, heads, depth_out, dropout) self.w_q2h = mx.sym.Variable("%sq2h_weight" % prefix) self.w_k2h = mx.sym.Variable("%sk2h_weight" % prefix) self.w_v2h = mx.sym.Variable("%sv2h_weight" % prefix) def __call__(self, queries: mx.sym.Symbol, memory: mx.sym.Symbol, memory_lengths: Optional[mx.sym.Symbol] = None, bias: Optional[mx.sym.Symbol] = None) -> mx.sym.Symbol: """ Computes multi-head attention for queries given a memory tensor. If sequence lengths are provided, they will be used to mask the attention scores. A bias mask may also be used to mask the attention scores. Returns a symbol of shape (batch, max_length, output_depth). :param queries: Query tensor. Shape: (batch, query_max_length, input_depth). :param memory: Memory data to attend to. Shape: (batch, memory_max_length, input_depth). :param memory_lengths: Optional lengths of memory to mask attention scores. Shape: (batch, 1). :param bias: Optional 3d bias tensor to mask attention scores. :return: Symbol of shape (batch, query_seq_len, output_depth). """ # (batch, query_max_length, depth) queries = mx.sym.FullyConnected(data=queries, weight=self.w_q2h, no_bias=True, num_hidden=self.depth, flatten=False, name="%sq_transform" % self.prefix) # (batch, memory_max_length, depth) keys = mx.sym.FullyConnected(data=memory, weight=self.w_k2h, no_bias=True, num_hidden=self.depth, flatten=False, name="%sk_transform" % self.prefix) # (batch, memory_max_length, depth) values = mx.sym.FullyConnected(data=memory, weight=self.w_v2h, no_bias=True, num_hidden=self.depth, flatten=False, name="%sv_transform" % self.prefix) return self._attend(queries, keys, values, bias=bias, lengths=memory_lengths) class ProjectedDotAttention: """ Dot attention layer for queries independent from keys/values. :param prefix: Attention prefix. :param num_hidden: Attention depth / number of hidden units. """ def __init__(self, prefix: str, num_hidden) -> None: self.prefix = prefix self.num_hidden = num_hidden self.w_q2h = mx.sym.Variable("%sq2h_weight" % prefix) self.b_q2h = mx.sym.Variable("%sq2h_bias" % prefix) self.w_kv2h = mx.sym.Variable("%skv2h_weight" % prefix) self.b_kv2h = mx.sym.Variable("%skv2h_bias" % prefix) def __call__(self, queries: mx.sym.Symbol, memory: mx.sym.Symbol, memory_lengths: mx.sym.Symbol) -> mx.sym.Symbol: """ Apply project, apply dot attention and return new context vectors. :param queries: Symbol of shape (batch, queries_max_length, input_num_hidden). :param memory: Symbol of shape (batch, memory_max_length, input_num_hidden). :param memory_lengths: Symbol of shape (batch, 1). :return: Symbol of shape (batch, queries_max_length, num_hidden). """ # (batch, memory_max_length, num_hidden * 2) combined = mx.sym.FullyConnected(data=memory, weight=self.w_kv2h, bias=self.b_kv2h, num_hidden=self.num_hidden * 2, flatten=False, name="%skv_transform" % self.prefix) # split into keys and values # pylint: disable=unbalanced-tuple-unpacking keys, values = mx.sym.split(data=combined, num_outputs=2, axis=2) # (batch, queries_max_length, num_hidden) queries = mx.sym.FullyConnected(data=queries, weight=self.w_q2h, bias=self.b_q2h, num_hidden=self.num_hidden, flatten=False, name="%sq_transform" % self.prefix) # scale by sqrt(num_hidden) queries = queries * (self.num_hidden ** -0.5) # (batch, queries_max_length, num_hidden) contexts = dot_attention(queries, keys, values, memory_lengths) return contexts class PlainDotAttention: """ Dot attention layer for queries independent from keys/values. """ def __call__(self, queries: mx.sym.Symbol, memory: mx.sym.Symbol, memory_lengths: mx.sym.Symbol) -> mx.sym.Symbol: """ Returns a symbol of shape (batch, max_length, output_depth). :param queries: Symbol of shape (batch, queries_max_length, input_depth). :param memory: Symbol of shape (batch, memory_max_length, input_depth). :param memory_lengths: Symbol of shape (batch, 1). :return: Symbol of shape (batch, queries_max_length, output_depth). """ # (batch*heads, queries_max_length, depth_per_head) contexts = dot_attention(queries, memory, memory, memory_lengths) return contexts class PositionalEncodings(mx.operator.CustomOp): """ Returns a symbol of shape (1, max_seq_len, num_embed) with positional encodings as in Vaswani et al, 2017. :param length: Maximum sequence length. :param depth: Embedding size. """ def __init__(self, length: int, depth: int) -> None: super().__init__() self.encodings = self.get_encodings(length, depth) @staticmethod def get_encodings(length, depth) -> np.ndarray: utils.check_condition(depth % 2 == 0, "Positional embeddings require an even embedding size it " "is however %d." % depth) # (1, depth) channels = np.arange(depth // 2).reshape((1, -1)) # (length, 1) positions = np.arange(0, length).reshape((-1, 1)) scaled_positions = positions / np.power(10000, (2 * channels) / depth) # sinusoids: sin = np.sin(scaled_positions) # cosines: cos = np.cos(scaled_positions) # interleave: (1, length, num_embed) encodings = np.hstack([sin, cos]).reshape(1, length, depth) return encodings def forward(self, is_train, req, in_data, out_data, aux): self.assign(out_data[0], req[0], self.encodings) def backward(self, req, out_grad, in_data, out_data, in_grad, aux): pass @mx.operator.register("positional_encodings") class PositionalEncodingsProp(mx.operator.CustomOpProp): def __init__(self, length: str, depth: str) -> None: super().__init__() self.length = int(length) self.depth = int(depth) def list_arguments(self): return [] def list_outputs(self): return ['output'] def infer_shape(self, in_shape): return [], [(1, self.length, self.depth)], [] def infer_type(self, in_type): return [], [np.float32], [] def create_operator(self, ctx, shapes, dtypes): return PositionalEncodings(length=self.length, depth=self.depth)

artemsok/sockeye

sockeye/layers.py

Python

apache-2.0

28,551

[ "Gaussian" ]

9a3f8675dfffca44bf2ab512c14ef444a2c07019fbbd675c1ad0352c1412c641

import copy import hyperchamber as hc import inspect import math import operator import os import re from functools import reduce import pyparsing import hypergan import torch import torch.nn as nn from .gan_component import GANComponent from hypergan.gan_component import ValidationException from hypergan.layer_shape import LayerShape from hypergan.distributions.base_distribution import BaseDistribution from hypergan.modules.adaptive_instance_norm import AdaptiveInstanceNorm from hypergan.modules.attention import Attention from hypergan.modules.const import Const from hypergan.modules.learned_noise import LearnedNoise from hypergan.modules.modulated_conv2d import ModulatedConv2d, Blur, EqualLinear from hypergan.modules.multi_head_attention import MultiHeadAttention from hypergan.modules.reshape import Reshape from hypergan.modules.no_op import NoOp from hypergan.modules.scaled_conv2d import ScaledConv2d from hypergan.modules.variational import Variational from hypergan.modules.pixel_norm import PixelNorm import torchvision import hypergan as hg class ConfigurableComponent(GANComponent): custom_layers = {} def __init__(self, gan, config, input=None, input_shape=None, context_shapes = {}, input_is_latent=False): self.current_size = LayerShape(gan.channels(), gan.height(), gan.width()) if isinstance(input, GANComponent): if hasattr(input, 'current_height'): self.current_size = LayerShape(input.current_channels, input.current_height, input.current_width) elif hasattr(input, 'current_channels'): self.current_size = LayerShape(input.current_channels) else: self.current_size = input.current_size if input_shape is not None: self.current_size = LayerShape(*input_shape) self.layers = [] self.layer_shapes = [] self.untrainable_parameters = set() self.layer_output_sizes = {} self.nn_layers = [] self.layer_options = {} self.parsed_layers = [] self.parser = hypergan.parser.Parser() self.context_shapes = context_shapes for key, shape in self.context_shapes.items(): self.layer_output_sizes[key] = shape if isinstance(input, BaseDistribution): self.is_latent = True else: self.is_latent = False self._latent_parameters = [] self.layer_ops = {**self.activations(), **ConfigurableComponent.custom_layers, "add": hg.layers.Add, "cat": hg.layers.Cat, "channel_attention": hg.layers.ChannelAttention, "efficient_attention": hg.layers.EfficientAttention, "ez_norm": hg.layers.EzNorm, "layer": hg.layers.Layer, "minibatch": hg.layers.Minibatch, "mul": hg.layers.Mul, "multi_head_attention2": hg.layers.MultiHeadAttention, #TODO rename "noise": hg.layers.Noise, "pixel_shuffle": hg.layers.PixelShuffle, "residual": hg.layers.Residual, "resizable_stack": hg.layers.ResizableStack, "segment_softmax": hg.layers.SegmentSoftmax, "upsample": hg.layers.Upsample, #easy to convert "dropout": self.layer_dropout, "identity": self.layer_identity, "flatten": self.layer_flatten, "pretrained": self.layer_pretrained, "avg_pool": self.layer_avg_pool,#TODO handle dims "pad": self.layer_pad, "reshape": self.layer_reshape, "split": self.layer_split, #hard to convert "adaptive_avg_pool": self.layer_adaptive_avg_pool, "adaptive_avg_pool1d": self.layer_adaptive_avg_pool1d, "adaptive_avg_pool3d": self.layer_adaptive_avg_pool3d, "adaptive_instance_norm": self.layer_adaptive_instance_norm, "attention": self.layer_attention, "batch_norm": self.layer_batch_norm, "batch_norm1d": self.layer_batch_norm1d, "blur": self.layer_blur, "const": self.layer_const, "conv": self.layer_conv, "conv1d": self.layer_conv1d, "conv2d": self.layer_conv2d, "conv3d": self.layer_conv3d, "deconv": self.layer_deconv, "equal_linear": self.layer_equal_linear, "instance_norm": self.layer_instance_norm, "instance_norm1d": self.layer_instance_norm1d, "instance_norm3d": self.layer_instance_norm3d, "latent": self.layer_latent, "layer_norm": self.layer_norm, "learned_noise": self.layer_learned_noise, "linear": self.layer_linear, "modulated_conv2d": self.layer_modulated_conv2d, "multi_head_attention": self.layer_multi_head_attention, "pixel_norm": self.layer_pixel_norm, "resize_conv": self.layer_resize_conv, "resize_conv2d": self.layer_resize_conv2d, "resize_conv1d": self.layer_resize_conv1d, "scaled_conv2d": self.layer_scaled_conv2d, "subpixel": self.layer_subpixel, "vae": self.layer_vae #"linear_attention": hg.layers.LinearAttention, #"make2d": self.layer_make2d, #"make3d": self.layer_make3d, # "crop": self.layer_crop, # "dropout": self.layer_dropout, # "noise": self.layer_noise, #TODO #"attention": self.layer_attention, #TODO #"const": self.layer_const, #TODO #"gram_matrix": self.layer_gram_matrix, #TODO #"image_statistics": self.layer_image_statistics, #TODO #"knowledge_base": self.layer_knowledge_base, #TODO #"layer_norm": self.layer_layer_norm,#TODO #"mask": self.layer_mask,#TODO #"match_support": self.layer_match_support,#TODO #"pixel_norm": self.layer_pixel_norm,#TODO #"progressive_replace": self.layer_progressive_replace,#TODO #"reduce_sum": self.layer_reduce_sum,#TODO might want to just do "reduce sum" instead #"relational": self.layer_relational,#TODO #"unpool": self.layer_unpool, #TODO https://arxiv.org/abs/1505.04366 #"squash": self.layer_squash, #TODO #"tensorflowcv": self.layer_tensorflowcv, #TODO layer torchvision instead? #"turing_test": self.layer_turing_test, #TODO #"two_sample_stack": self.layer_two_sample_stack, #TODO #"zeros": self.layer_zeros, #TODO #"zeros_like": self.layer_zeros_like #TODO } self.named_layers = {} if not hasattr(gan, "named_layers"): gan.named_layers = {} self.subnets = hc.Config(hc.Config(config).subnets or {}) GANComponent.__init__(self, gan, config) self.device = self.config.device or "cuda:0" self.const_two = torch.Tensor([2.0]).float()[0].cuda() self.const_one = torch.Tensor([1.0]).float()[0].cuda() def required(self): return "layers".split() def layer(self, name): if name in self.gan.named_layers: return self.gan.named_layers[name] if name in self.named_layers: return self.named_layers[name] return None def create(self): for layer in self.config.layers: net = self.create_parsed_layer(layer) self.nn_layers.append(net) self.net = nn.ModuleList(self.nn_layers) def create_parsed_layer(self, layer_defn): config = self.config parsed, layer = self.parse_layer(layer_defn) self.parsed_layers.append(parsed) self.layer_shapes.append(self.current_size) return layer def parse_layer(self, layer_defn): print("Parsing layer:", layer_defn) parsed = self.parser.parse_string(layer_defn) parsed.parsed_options = hc.Config(parsed.options) parsed.layer_defn = layer_defn print("Parsed layer:", parsed.to_list()) layer = self.build_layer(parsed.layer_name, parsed.args, parsed.parsed_options) return parsed, layer def build_layer(self, op, args, options): if self.layer_ops[op]: try: is_hg_layer = issubclass(self.layer_ops[op], hg.Layer) except TypeError: is_hg_layer = False if is_hg_layer: net = self.layer_ops[op](self, args, options) self.current_size = net.output_size() if self.is_latent: self._latent_parameters += net.latent_parameters() self.is_latent = False elif isinstance(self.layer_ops[op], nn.Module): net = self.layer_ops[op] else: net = self.layer_ops[op](None, args, options) if 'name' in options: self.set_layer(options['name'], net) if options.trainable == False: self.untrainable_parameters = self.untrainable_parameters.union(set(net.parameters())) return net else: print("ConfigurableComponent: Op not defined", op) def set_layer(self, name, net): self.gan.named_layers[name] = net self.named_layers[name] = net self.layer_output_sizes[name] = self.current_size def activations(self): return { "celu": nn.CELU(), "gelu": nn.GELU(), "lrelu": nn.LeakyReLU(0.2), "prelu": nn.PReLU(), "relu": nn.ReLU(), "relu6": nn.ReLU6(), "selu": nn.SELU(), "sigmoid": nn.Sigmoid(), "softplus": nn.Softplus(), "softshrink": nn.Softshrink(), "softsign": nn.Softsign(), "hardsigmoid": nn.Hardsigmoid(), "hardtanh": nn.Hardtanh(), "tanh": nn.Tanh(), "tanhshrink": nn.Tanhshrink() } def layer_dropout(self, net, args, options): return nn.Dropout2d(float(args[0])) def layer_identity(self, net, args, options): return NoOp() def layer_equal_linear(self, net, args, options): lr_mul = 1 if options.lr_mul is not None: lr_mul = options.lr_mul result = EqualLinear(options.input_size or self.current_size.size(), args[0], lr_mul=lr_mul) self.current_size = LayerShape(args[0]) return result def get_device(self): return torch.device(self.device or "cuda:0") def get_same_padding(self, input_rows, filter_rows, stride, dilation): out_rows = (input_rows + stride - 1) // stride return max(0, (out_rows - 1) * stride + (filter_rows - 1) * dilation + 1 - input_rows) // 2 def layer_const(self, net, args, options): return Const(*self.current_size.dims) #from https://discuss.pytorch.org/t/utility-function-for-calculating-the-shape-of-a-conv-output/11173/3 def conv_output_shape(self, h_w, kernel_size=1, stride=1, pad=0, dilation=1): if type(kernel_size) is not tuple: kernel_size = (kernel_size, kernel_size) h = math.floor( ((h_w[0] + (2 * pad) - ( dilation * (kernel_size[0] - 1) ) - 1 )/ stride) + 1) w = math.floor( ((h_w[1] + (2 * pad) - ( dilation * (kernel_size[1] - 1) ) - 1 )/ stride) + 1) return h, w def layer_conv(self, net, args, options): return self.layer_conv2d(net, args, options) def layer_conv2d(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels options = hc.Config(options) stride = 1 if options.stride is not None: stride = options.stride filter = 3 if options.filter is not None: filter = options.filter padding = 1 if options.padding is not None: padding = options.padding dilation = 1 layer = nn.Conv2d(options.input_channels or self.current_size.channels, channels, filter, stride, padding = (padding, padding)) self.nn_init(layer, options.initializer) h, w = self.conv_output_shape((self.current_size.height, self.current_size.width), filter, stride, padding, dilation) self.current_size = LayerShape(channels, h, w) return layer def layer_conv1d(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels print("Options:", options) options = hc.Config(options) stride = options.stride or 1 fltr = options.filter or 3 dilation = 1 padding = 1 if options.padding is not None: padding = options.padding layers = [nn.Conv1d(options.input_channels or self.current_size.channels, channels, fltr, stride, padding = padding)] self.nn_init(layers[-1], options.initializer) h, _ = self.conv_output_shape((self.current_size.height, self.current_size.height), options.filter or 3, stride, padding, 1) self.current_size = LayerShape(channels, h) return nn.Sequential(*layers) def layer_conv3d(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels options = hc.Config(options) stride = options.stride or 1 fltr = options.filter or 3 dilation = 1 padding = options.padding or 1#self.get_same_padding(self.current_width, self.current_width, stride, dilation) if options.padding0: padding = [options.padding0, padding, padding] if options.stride0: stride = [options.stride0, stride, stride] else: stride = [stride, stride, stride] layers = [nn.Conv3d(options.input_channels or self.current_size.channels, channels, fltr, stride, padding = padding)] self.nn_init(layer, options.initializer) self.current_size = LayerShape(frames, channels, self.current_size.height // stride[1], self.current_size.width // stride[2]) #TODO this doesn't work, what is frames? Also chw calculation like conv2d return nn.Sequential(*layers) def layer_linear(self, net, args, options): options = hc.Config(options) shape = [int(x) for x in str(args[0]).split("*")] bias = True if options.bias == False: bias = False output_size = 1 for dim in shape: output_size *= dim layers = [] if len(self.current_size.dims) != 1: layers += [nn.Flatten()] layers += [nn.Linear(options.input_size or self.current_size.size(), output_size, bias=bias)] self.nn_init(layers[-1], options.initializer) self.current_size = LayerShape(*list(reversed(shape))) if len(shape) != 1: layers.append(Reshape(*self.current_size.dims)) if self.is_latent: self._latent_parameters += [layers[0].weight] self.is_latent = False return nn.Sequential(*layers) def layer_modulated_conv2d(self, net, args, options): channels = self.current_size.channels if len(args) > 0: channels = args[0] method = "conv" if len(args) > 1: method = args[1] upsample = method == "upsample" downsample = method == "downsample" demodulate = True if options.demodulate == False: demodulate = False filter = 3 if options.filter: filter = options.filter lr_mul = 1.0 if options.lr_mul: lr_mul = options.lr_mul input_channels = self.current_size.channels if options.input_channels: input_channels = options.input_channels result = ModulatedConv2d(input_channels, channels, filter, self.layer_output_sizes['w'].size(), upsample=upsample, demodulate=demodulate, downsample=downsample, lr_mul=lr_mul) if upsample: self.current_size = LayerShape(channels, self.current_size.height * 2, self.current_size.width * 2) elif downsample: self.current_size = LayerShape(channels, self.current_size.height // 2, self.current_size.width // 2) return result def layer_blur(self, net, args, options): blur_kernel=[1, 3, 3, 1] kernel_size=3 factor = 2 p = (len(blur_kernel) - factor) - (kernel_size - 1) pad0 = (p + 1) // 2 + factor - 1 pad1 = p // 2 + 1 return Blur(blur_kernel, pad=(pad0, pad1), upsample_factor=factor) def layer_reshape(self, net, args, options): dims_args = [int(x) for x in args[0].split("*")] dims = list(reversed(dims_args)) self.current_size = LayerShape(*dims) return Reshape(*dims) def layer_adaptive_avg_pool(self, net, args, options): self.current_size = LayerShape(self.current_size.channels, self.current_size.height // 2, self.current_size.width // 2) return nn.AdaptiveAvgPool2d([self.current_size.height, self.current_size.width]) def layer_adaptive_avg_pool1d (self, net, args, options): self.current_size = LayerShape(self.current_size.channels, self.current_size.height // 2) return nn.AdaptiveAvgPool1d(self.current_size.height) def layer_avg_pool(self, net, args, options): self.current_size = LayerShape(self.current_size.channels, self.current_size.height // 2, self.current_size.width // 2) return nn.AvgPool2d(2, 2) def layer_adaptive_avg_pool3d(self, net, args, options): frames = 4 #TODO self.current_size = LayerShape(frames, self.current_size.channels, self.current_size.height // 2, self.current_size.width // 2) return nn.AdaptiveAvgPool3d([self.current_size.frames, self.current_size.height, self.current_size.width]) #TODO looks wrong def layer_instance_norm(self, net, args, options): options = hc.Config(options) affine = True if options.affine == False: affine = False return nn.InstanceNorm2d(self.current_size.channels, affine=affine) def layer_instance_norm1d(self, net, args, options): options = hc.Config(options) affine = True if options.affine == False: affine = False return nn.InstanceNorm1d(self.current_size.channels, affine=affine) def layer_instance_norm3d(self, net, args, options): options = hc.Config(options) affine = True if options.affine == False: affine = False return nn.InstanceNorm3d(self.current_size.channels, affine=affine) def layer_batch_norm(self, net, args, options): return nn.BatchNorm2d(self.current_size.channels) def layer_batch_norm1d(self, net, args, options): return nn.BatchNorm1d(self.current_size.size()) def get_conv_options(self, config, options): stride = options.stride or self.ops.config_option("stride", [1,1]) fltr = options.filter or self.ops.config_option("filter", [3,3]) avg_pool = options.avg_pool or self.ops.config_option("avg_pool", [1,1]) if type(stride) != type([]): stride = [stride, stride] if type(avg_pool) != type([]): avg_pool = [avg_pool, avg_pool] if type(fltr) != type([]): fltr = [fltr, fltr] return stride, fltr, avg_pool def layer_deconv(self, net, args, options): if len(args) > 0: channels = args[0] else: channels = self.current_size.channels options = hc.Config(options) filter = 4 #TODO if options.filter: filter = options.filter stride = 2 if options.stride: stride = options.stride padding = 1 if options.padding: padding = options.padding layer = nn.ConvTranspose2d(options.input_channels or self.current_size.channels, channels, filter, stride, padding) self.nn_init(layer, options.initializer) self.current_size = LayerShape(channels, self.current_size.height * 2, self.current_size.width * 2) return layer def layer_pad(self, net, args, options): options = hc.Config(options) return nn.ZeroPad2d((args[0], args[1], args[2], args[3])) def layer_pixel_norm(self, net, args, options): return PixelNorm() def layer_pretrained(self, net, args, options): model = getattr(torchvision.models, args[0])(pretrained=True) model.train(True) if options.layer: layers = list(model.children())[:options.layer] if options.sublayer: layers[-1] = nn.Sequential(*layers[-1][:options.sublayer]) else: layers = [model] print("List of pretrained layers:", layers) raise ValidationException("layer=-1 required for pretrained, sublayer=-1 optional. Layers outputted above.") return nn.Sequential(*layers) def layer_resize_conv(self, net, args, options): return self.layer_resize_conv2d(net, args, options) def layer_resize_conv2d(self, net, args, options): options = hc.Config(options) channels = args[0] w = options.w or self.current_size.width * 2 h = options.h or self.current_size.height * 2 layers = [nn.Upsample((h, w), mode="bilinear"), nn.Conv2d(options.input_channels or self.current_size.channels, channels, options.filter or 3, 1, 1)] self.nn_init(layers[-1], options.initializer) self.current_size = LayerShape(channels, h, w) return nn.Sequential(*layers) def layer_resize_conv1d(self, net, args, options): options = hc.Config(options) channels = args[0] h = options.h or self.current_size.height * 2 padding = 1 if options.padding is not None: padding = options.padding layers = [nn.Upsample((h)), nn.Conv1d(options.input_channels or self.current_size.channels, channels, options.filter or 3, 1, padding=padding)] self.nn_init(layers[-1], options.initializer) h, _ = self.conv_output_shape((h, h), options.filter or 3, 1, padding, 1) self.current_size = LayerShape(channels, h) return nn.Sequential(*layers) def layer_scaled_conv2d(self, net, args, options): channels = self.current_size.channels if len(args) > 0: channels = args[0] method = "conv" if len(args) > 1: method = args[1] upsample = method == "upsample" downsample = method == "downsample" demodulate = True if options.demodulate == False: demodulate = False filter = 3 if options.filter: filter = options.filter lr_mul = 1.0 if options.lr_mul: lr_mul = options.lr_mul input_channels = self.current_size.channels if options.input_channels: input_channels = options.input_channels result = ScaledConv2d(input_channels, channels, filter, 0, upsample=upsample, demodulate=demodulate, downsample=downsample, lr_mul=lr_mul) self.nn_init(result, options.initializer) if upsample: self.current_size = LayerShape(channels, self.current_size.height * 2, self.current_size.width * 2) else: self.current_size = LayerShape(channels, self.current_size.height - 2, self.current_size.width - 2) return result def layer_split(self, net, args, options): options = hc.Config(options) split_size = args[0] select = args[1] dim = -1 if options.dim: dim = options.dim #TODO better validation #TODO increase dim options if dim == -1: dims = list(self.current_size.dims).copy() dims[0] = split_size if (select + 1) * split_size > self.current_size.channels: dims[0] = self.current_size.channels % split_size self.current_size = LayerShape(*dims) return NoOp() def layer_subpixel(self, net, args, options): options = hc.Config(options) channels = args[0] layers = [nn.Conv2d(options.input_channels or self.current_size.channels, channels*4, options.filter or 3, 1, 1), nn.PixelShuffle(2)] self.nn_init(layers[0], options.initializer) self.current_size = LayerShape(channels, self.current_size.height * 2, self.current_size.width * 2) return nn.Sequential(*layers) def layer_latent(self, net, args, options): self.current_size = LayerShape(self.gan.latent.current_input_size) self.is_latent = True return NoOp() def layer_linformer(self, net, args, options): model = Linformer( input_size = self.current_size.size(), channels = self.current_size.height # TODO wtf ) return model def layer_vae(self, net, args, options): self.vae = Variational(self.current_size.channels) return self.vae def layer_multi_head_attention(self, net, args, options): output_size = self.current_size.size() if len(args) > 0: output_size = args[0] layer = MultiHeadAttention(self.current_size.size(), output_size, heads=options.heads or 4) self.current_size = LayerShape(output_size) self.nn_init(layer.o, options.initializer) self.nn_init(layer.h, options.initializer) self.nn_init(layer.g, options.initializer) self.nn_init(layer.f, options.initializer) if self.is_latent: self._latent_parameters += [layer.h.weight, layer.g.weight, layer.f.weight] self.is_latent = False return layer def layer_attention(self, net, args, options): layer = Attention(self.current_size.channels) self.nn_init(layer.v, options.initializer) self.nn_init(layer.h, options.initializer) self.nn_init(layer.g, options.initializer) self.nn_init(layer.f, options.initializer) return layer def layer_norm(self, net, args, options): affine = True if options.affine == False: affine = False return nn.LayerNorm(self.current_size.dims, elementwise_affine=affine) def layer_learned_noise(self, net, args, options): return LearnedNoise(*([self.gan.batch_size(), *self.current_size.dims])) def layer_adaptive_instance_norm(self, net, args, options): return AdaptiveInstanceNorm(self.layer_output_sizes['w'].size(), self.current_size.channels, equal_linear=options.equal_linear) def layer_flatten(self, net, args, options): self.current_size = LayerShape(self.current_size.size()) return nn.Flatten() def layer_zeros_like(self, net, args, options): return Zeros(self.gan.latent.sample().shape) def nn_init(self, layer, initializer_option): if initializer_option is None: return if type(initializer_option) == pyparsing.ParseResults and type(initializer_option[0]) == hypergan.parser.Pattern: args = [initializer_option[0].layer_name] + initializer_option[0].args options = hc.Config(initializer_option[0].options) else: args = [initializer_option] options = hc.Config({}) layer_data = layer.weight.data if args[0] == "uniform": a = float(args[1]) b = float(args[2]) nn.init.uniform_(layer_data, a, b) elif args[0] == "normal": mean = float(args[1]) std = float(args[2]) nn.init.normal_(layer_data, mean, std) elif args[0] == "constant": val = float(args[1]) nn.init.constant_(layer_data, val) elif args[0] == "ones": nn.init.ones_(layer_data) elif args[0] == "zeros": nn.init.zeros_(layer_data) elif args[0] == "eye": nn.init.eye_(layer_data) elif args[0] == "dirac": nn.init.dirac_(layer_data) elif args[0] == "xavier_uniform": gain = nn.init.calculate_gain(options.gain or "relu") nn.init.xavier_uniform_(layer_data, gain=gain) elif args[0] == "xavier_normal": gain = nn.init.calculate_gain(options.gain or "relu") nn.init.xavier_normal_(layer_data, gain=gain) elif args[0] == "kaiming_uniform": a = 0 #TODO wrong nn.init.kaiming_uniform_(layer_data, mode=(options.mode or "fan_in"), nonlinearity=options.gain or "relu") elif args[0] == "kaiming_normal": a = 0 #TODO wrong nn.init.kaiming_normal_(layer_data, mode=(options.mode or "fan_in"), nonlinearity=options.gain or "relu") elif args[0] == "orthogonal": if "gain" in options: gain = nn.init.calculate_gain(options["gain"]) else: gain = 1 nn.init.orthogonal_(layer_data, gain=gain) else: print("Warning: No initializer found for " + args[0]) if "gain" in options: layer_data.mul_(nn.init.calculate_gain(options["gain"])) return NoOp() def forward(self, input, context={}): if self.get_device().index != input.device.index: input = input.to(self.get_device()) for module, parsed, layer_shape in zip(self.net, self.parsed_layers, self.layer_shapes): try: options = parsed.parsed_options args = parsed.args layer_name = parsed.layer_name name = options.name if isinstance(module, hg.Layer): input = module(input, context) elif layer_name == "adaptive_instance_norm": input = module(input, context['w']) elif layer_name == "ez_norm": input = module(input, context['w']) elif layer_name == "split": input = torch.split(input, args[0], options.dim or -1)[args[1]] elif layer_name == "latent": input = self.gan.latent.z#sample() elif layer_name == "modulated_conv2d": input = module(input, context['w']) elif layer_name == "pretrained": in_zero_one = (input + self.const_one) / self.const_two mean = torch.as_tensor([0.485, 0.456, 0.406], device='cuda:0').view(1, 3, 1, 1) std = torch.as_tensor([0.229, 0.224, 0.225], device='cuda:0').view(1, 3, 1, 1) input = module(input.clone().sub_(mean).div_(std)) else: input = module(input) if self.gan.steps == 0: size = LayerShape(*list(input.shape[1:])) if size.squeeze_dims() != layer_shape.squeeze_dims(): print("Error: Size error on", layer_name) print("Error: Expected output size", layer_shape.dims) print("Error: Actual output size", size.dims) raise "Layer size error, cannot continue" else: pass if name is not None: context[name] = input except: raise ValidationException("Error on " + parsed.layer_defn + " - input size " + ",".join([str(x) for x in input.shape])) self.sample = input return input def latent_parameters(self): return self._latent_parameters def set_trainable(self, flag): for p in (set(list(self.parameters())) - self.untrainable_parameters): p.requires_grad = flag def layer_shape(self): return self.current_size def __getstate__(self): obj = dict(self.__dict__) del obj["parser"] return obj def __setstate__(self, d): self.__dict__ = d self.parser = hypergan.parser.Parser()

255BITS/HyperGAN

hypergan/configurable_component.py

Python

mit

32,342

[ "DIRAC" ]

57f453c1a9b980ac591391d18e935227cc73f49512d324d5cb70ff70a6a0272e

# ---------------------------------------------------------------------------------------------------- # # Copyright (c) 2020, Oracle and/or its affiliates. All rights reserved. # DO NOT ALTER OR REMOVE COPYRIGHT NOTICES OR THIS FILE HEADER. # # This code is free software; you can redistribute it and/or modify it # under the terms of the GNU General Public License version 2 only, as # published by the Free Software Foundation. # # This code is distributed in the hope that it will be useful, but WITHOUT # ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or # FITNESS FOR A PARTICULAR PURPOSE. See the GNU General Public License # version 2 for more details (a copy is included in the LICENSE file that # accompanied this code). # # You should have received a copy of the GNU General Public License version # 2 along with this work; if not, write to the Free Software Foundation, # Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA. # # Please contact Oracle, 500 Oracle Parkway, Redwood Shores, CA 94065 USA # or visit www.oracle.com if you need additional information or have any # questions. # # ---------------------------------------------------------------------------------------------------- import json import os import re import subprocess from multiprocessing import Lock import mx _bear_version_regex = re.compile(r"bear ([0-9]+).([0-9]+).([0-9]+)", re.IGNORECASE) _bear_version = '<uninitialized>' def _get_bear_version(): global _bear_version if _bear_version == '<uninitialized>': try: output = mx._check_output_str(['bear', '--version'], stderr=subprocess.STDOUT) except OSError: output = '' m = _bear_version_regex.search(output) if m: _bear_version = int(m.group(1)) else: mx.warn("Could not find bear, will not produce compilation database for make projects.") _bear_version = None return _bear_version def gmake_with_bear(out=None, append=False, context=None): v = _get_bear_version() if v is None: return [mx.gmake_cmd(context=context)] else: ret = ['bear'] if append: ret.append('--append' if v >= 3 else '-a') if out is not None: ret.append('--output' if v >= 3 else '-o') ret.append(out) if v >= 3: ret.append('--') ret.append(mx.gmake_cmd(context=context)) return ret _compdb_path = None _compdb_lock = None def _default_compdb_path(): suite = mx.primary_suite() if suite is None: # no primary suite, don't try to enable compdb return None if suite.vc_dir: return os.path.join(os.path.dirname(suite.vc_dir), 'compile_commands.json') else: return os.path.join(suite.dir, 'compile_commands.json') def init(): global _compdb_path global _compdb_lock o = mx.get_opts().compdb if o is None: o = mx.get_env('MX_COMPDB') if o is not None and o != 'none': _compdb_lock = Lock() if o == 'default': _compdb_path = _default_compdb_path() else: _compdb_path = os.path.abspath(o) def enabled(): return _compdb_path is not None def gmake_with_compdb_cmd(context=None): if enabled(): return gmake_with_bear(append=True, context=context) else: return [mx.gmake_cmd(context=context)] class Compdb: def __init__(self): self.content = {} def __enter__(self): _compdb_lock.acquire() if os.path.exists(_compdb_path): self.mergeFile(_compdb_path) return self def __exit__(self, *args): with open(_compdb_path, 'w') as f: json.dump(list(self.content.values()), f, indent=4) _compdb_lock.release() def merge(self, data): for item in data: key = item['file'] if not os.path.isabs(key): key = os.path.normpath(os.path.join(item['directory'], item['file'])) self.content[item['file']] = item def mergeString(self, string): try: self.merge(json.loads(string)) except json.JSONDecodeError: mx.warn("Error decoding JSON compilation database. Ignoring.") def mergeFile(self, path): with open(path, 'r') as f: try: self.merge(json.load(f)) except json.JSONDecodeError: mx.warn("Error decoding JSON compilation database from '%s'. Ignoring." % path) class CompdbCapture: def __init__(self, suite): self.data = "" def __call__(self, data): self.data += data def __enter__(self): if enabled(): return self else: return None def __exit__(self, *args): if enabled(): with Compdb() as db: db.mergeString(self.data) def merge_compdb(subject, path): if enabled(): with Compdb() as db: inFile = os.path.join(path, 'compile_commands.json') if os.path.exists(inFile): db.mergeFile(inFile) else: mx.warn("JSON compilation database for %s not found (expected at %s)." % (subject, inFile))

graalvm/mx

mx_compdb.py

Python

gpl-2.0

5,256

[ "VisIt" ]

318b30996a0bfb1c7510967f8cdff0925a84f2be3ee143d009c6bec87092ec4a

"""Rewrite assertion AST to produce nice error messages""" import ast import _ast import errno import itertools import imp import marshal import os import re import struct import sys import types from fnmatch import fnmatch import py from _pytest.assertion import util # pytest caches rewritten pycs in __pycache__. if hasattr(imp, "get_tag"): PYTEST_TAG = imp.get_tag() + "-PYTEST" else: if hasattr(sys, "pypy_version_info"): impl = "pypy" elif sys.platform == "java": impl = "jython" else: impl = "cpython" ver = sys.version_info PYTEST_TAG = "%s-%s%s-PYTEST" % (impl, ver[0], ver[1]) del ver, impl PYC_EXT = ".py" + (__debug__ and "c" or "o") PYC_TAIL = "." + PYTEST_TAG + PYC_EXT REWRITE_NEWLINES = sys.version_info[:2] != (2, 7) and sys.version_info < (3, 2) ASCII_IS_DEFAULT_ENCODING = sys.version_info[0] < 3 if sys.version_info >= (3,5): ast_Call = ast.Call else: ast_Call = lambda a,b,c: ast.Call(a, b, c, None, None) class AssertionRewritingHook(object): """PEP302 Import hook which rewrites asserts.""" def __init__(self, config): self.config = config self.fnpats = config.getini("python_files") self.session = None self.modules = {} self._rewritten_names = set() self._register_with_pkg_resources() self._must_rewrite = set() def set_session(self, session): self.session = session def find_module(self, name, path=None): state = self.config._assertstate state.trace("find_module called for: %s" % name) names = name.rsplit(".", 1) lastname = names[-1] pth = None if path is not None: # Starting with Python 3.3, path is a _NamespacePath(), which # causes problems if not converted to list. path = list(path) if len(path) == 1: pth = path[0] if pth is None: try: fd, fn, desc = imp.find_module(lastname, path) except ImportError: return None if fd is not None: fd.close() tp = desc[2] if tp == imp.PY_COMPILED: if hasattr(imp, "source_from_cache"): try: fn = imp.source_from_cache(fn) except ValueError: # Python 3 doesn't like orphaned but still-importable # .pyc files. fn = fn[:-1] else: fn = fn[:-1] elif tp != imp.PY_SOURCE: # Don't know what this is. return None else: fn = os.path.join(pth, name.rpartition(".")[2] + ".py") fn_pypath = py.path.local(fn) if not self._should_rewrite(name, fn_pypath, state): return None self._rewritten_names.add(name) # The requested module looks like a test file, so rewrite it. This is # the most magical part of the process: load the source, rewrite the # asserts, and load the rewritten source. We also cache the rewritten # module code in a special pyc. We must be aware of the possibility of # concurrent pytest processes rewriting and loading pycs. To avoid # tricky race conditions, we maintain the following invariant: The # cached pyc is always a complete, valid pyc. Operations on it must be # atomic. POSIX's atomic rename comes in handy. write = not sys.dont_write_bytecode cache_dir = os.path.join(fn_pypath.dirname, "__pycache__") if write: try: os.mkdir(cache_dir) except OSError: e = sys.exc_info()[1].errno if e == errno.EEXIST: # Either the __pycache__ directory already exists (the # common case) or it's blocked by a non-dir node. In the # latter case, we'll ignore it in _write_pyc. pass elif e in [errno.ENOENT, errno.ENOTDIR]: # One of the path components was not a directory, likely # because we're in a zip file. write = False elif e in [errno.EACCES, errno.EROFS, errno.EPERM]: state.trace("read only directory: %r" % fn_pypath.dirname) write = False else: raise cache_name = fn_pypath.basename[:-3] + PYC_TAIL pyc = os.path.join(cache_dir, cache_name) # Notice that even if we're in a read-only directory, I'm going # to check for a cached pyc. This may not be optimal... co = _read_pyc(fn_pypath, pyc, state.trace) if co is None: state.trace("rewriting %r" % (fn,)) source_stat, co = _rewrite_test(self.config, fn_pypath) if co is None: # Probably a SyntaxError in the test. return None if write: _make_rewritten_pyc(state, source_stat, pyc, co) else: state.trace("found cached rewritten pyc for %r" % (fn,)) self.modules[name] = co, pyc return self def _should_rewrite(self, name, fn_pypath, state): # always rewrite conftest files fn = str(fn_pypath) if fn_pypath.basename == 'conftest.py': state.trace("rewriting conftest file: %r" % (fn,)) return True if self.session is not None: if self.session.isinitpath(fn): state.trace("matched test file (was specified on cmdline): %r" % (fn,)) return True # modules not passed explicitly on the command line are only # rewritten if they match the naming convention for test files for pat in self.fnpats: # use fnmatch instead of fn_pypath.fnmatch because the # latter might trigger an import to fnmatch.fnmatch # internally, which would cause this method to be # called recursively if fnmatch(fn_pypath.basename, pat): state.trace("matched test file %r" % (fn,)) return True for marked in self._must_rewrite: if name.startswith(marked): state.trace("matched marked file %r (from %r)" % (name, marked)) return True return False def mark_rewrite(self, *names): """Mark import names as needing to be re-written. The named module or package as well as any nested modules will be re-written on import. """ already_imported = set(names).intersection(set(sys.modules)) if already_imported: for name in already_imported: if name not in self._rewritten_names: self._warn_already_imported(name) self._must_rewrite.update(names) def _warn_already_imported(self, name): self.config.warn( 'P1', 'Module already imported so can not be re-written: %s' % name) def load_module(self, name): # If there is an existing module object named 'fullname' in # sys.modules, the loader must use that existing module. (Otherwise, # the reload() builtin will not work correctly.) if name in sys.modules: return sys.modules[name] co, pyc = self.modules.pop(name) # I wish I could just call imp.load_compiled here, but __file__ has to # be set properly. In Python 3.2+, this all would be handled correctly # by load_compiled. mod = sys.modules[name] = imp.new_module(name) try: mod.__file__ = co.co_filename # Normally, this attribute is 3.2+. mod.__cached__ = pyc mod.__loader__ = self py.builtin.exec_(co, mod.__dict__) except: if name in sys.modules: del sys.modules[name] raise return sys.modules[name] def is_package(self, name): try: fd, fn, desc = imp.find_module(name) except ImportError: return False if fd is not None: fd.close() tp = desc[2] return tp == imp.PKG_DIRECTORY @classmethod def _register_with_pkg_resources(cls): """ Ensure package resources can be loaded from this loader. May be called multiple times, as the operation is idempotent. """ try: import pkg_resources # access an attribute in case a deferred importer is present pkg_resources.__name__ except ImportError: return # Since pytest tests are always located in the file system, the # DefaultProvider is appropriate. pkg_resources.register_loader_type(cls, pkg_resources.DefaultProvider) def get_data(self, pathname): """Optional PEP302 get_data API. """ with open(pathname, 'rb') as f: return f.read() def _write_pyc(state, co, source_stat, pyc): # Technically, we don't have to have the same pyc format as # (C)Python, since these "pycs" should never be seen by builtin # import. However, there's little reason deviate, and I hope # sometime to be able to use imp.load_compiled to load them. (See # the comment in load_module above.) try: fp = open(pyc, "wb") except IOError: err = sys.exc_info()[1].errno state.trace("error writing pyc file at %s: errno=%s" %(pyc, err)) # we ignore any failure to write the cache file # there are many reasons, permission-denied, __pycache__ being a # file etc. return False try: fp.write(imp.get_magic()) mtime = int(source_stat.mtime) size = source_stat.size & 0xFFFFFFFF fp.write(struct.pack("<ll", mtime, size)) marshal.dump(co, fp) finally: fp.close() return True RN = "\r\n".encode("utf-8") N = "\n".encode("utf-8") cookie_re = re.compile(r"^[ \t\f]*#.*coding[:=][ \t]*[-\w.]+") BOM_UTF8 = '\xef\xbb\xbf' def _rewrite_test(config, fn): """Try to read and rewrite *fn* and return the code object.""" state = config._assertstate try: stat = fn.stat() source = fn.read("rb") except EnvironmentError: return None, None if ASCII_IS_DEFAULT_ENCODING: # ASCII is the default encoding in Python 2. Without a coding # declaration, Python 2 will complain about any bytes in the file # outside the ASCII range. Sadly, this behavior does not extend to # compile() or ast.parse(), which prefer to interpret the bytes as # latin-1. (At least they properly handle explicit coding cookies.) To # preserve this error behavior, we could force ast.parse() to use ASCII # as the encoding by inserting a coding cookie. Unfortunately, that # messes up line numbers. Thus, we have to check ourselves if anything # is outside the ASCII range in the case no encoding is explicitly # declared. For more context, see issue #269. Yay for Python 3 which # gets this right. end1 = source.find("\n") end2 = source.find("\n", end1 + 1) if (not source.startswith(BOM_UTF8) and cookie_re.match(source[0:end1]) is None and cookie_re.match(source[end1 + 1:end2]) is None): if hasattr(state, "_indecode"): # encodings imported us again, so don't rewrite. return None, None state._indecode = True try: try: source.decode("ascii") except UnicodeDecodeError: # Let it fail in real import. return None, None finally: del state._indecode # On Python versions which are not 2.7 and less than or equal to 3.1, the # parser expects *nix newlines. if REWRITE_NEWLINES: source = source.replace(RN, N) + N try: tree = ast.parse(source) except SyntaxError: # Let this pop up again in the real import. state.trace("failed to parse: %r" % (fn,)) return None, None rewrite_asserts(tree, fn, config) try: co = compile(tree, fn.strpath, "exec") except SyntaxError: # It's possible that this error is from some bug in the # assertion rewriting, but I don't know of a fast way to tell. state.trace("failed to compile: %r" % (fn,)) return None, None return stat, co def _make_rewritten_pyc(state, source_stat, pyc, co): """Try to dump rewritten code to *pyc*.""" if sys.platform.startswith("win"): # Windows grants exclusive access to open files and doesn't have atomic # rename, so just write into the final file. _write_pyc(state, co, source_stat, pyc) else: # When not on windows, assume rename is atomic. Dump the code object # into a file specific to this process and atomically replace it. proc_pyc = pyc + "." + str(os.getpid()) if _write_pyc(state, co, source_stat, proc_pyc): os.rename(proc_pyc, pyc) def _read_pyc(source, pyc, trace=lambda x: None): """Possibly read a pytest pyc containing rewritten code. Return rewritten code if successful or None if not. """ try: fp = open(pyc, "rb") except IOError: return None with fp: try: mtime = int(source.mtime()) size = source.size() data = fp.read(12) except EnvironmentError as e: trace('_read_pyc(%s): EnvironmentError %s' % (source, e)) return None # Check for invalid or out of date pyc file. if (len(data) != 12 or data[:4] != imp.get_magic() or struct.unpack("<ll", data[4:]) != (mtime, size)): trace('_read_pyc(%s): invalid or out of date pyc' % source) return None try: co = marshal.load(fp) except Exception as e: trace('_read_pyc(%s): marshal.load error %s' % (source, e)) return None if not isinstance(co, types.CodeType): trace('_read_pyc(%s): not a code object' % source) return None return co def rewrite_asserts(mod, module_path=None, config=None): """Rewrite the assert statements in mod.""" AssertionRewriter(module_path, config).run(mod) def _saferepr(obj): """Get a safe repr of an object for assertion error messages. The assertion formatting (util.format_explanation()) requires newlines to be escaped since they are a special character for it. Normally assertion.util.format_explanation() does this but for a custom repr it is possible to contain one of the special escape sequences, especially '\n{' and '\n}' are likely to be present in JSON reprs. """ repr = py.io.saferepr(obj) if py.builtin._istext(repr): t = py.builtin.text else: t = py.builtin.bytes return repr.replace(t("\n"), t("\\n")) from _pytest.assertion.util import format_explanation as _format_explanation # noqa def _format_assertmsg(obj): """Format the custom assertion message given. For strings this simply replaces newlines with '\n~' so that util.format_explanation() will preserve them instead of escaping newlines. For other objects py.io.saferepr() is used first. """ # reprlib appears to have a bug which means that if a string # contains a newline it gets escaped, however if an object has a # .__repr__() which contains newlines it does not get escaped. # However in either case we want to preserve the newline. if py.builtin._istext(obj) or py.builtin._isbytes(obj): s = obj is_repr = False else: s = py.io.saferepr(obj) is_repr = True if py.builtin._istext(s): t = py.builtin.text else: t = py.builtin.bytes s = s.replace(t("\n"), t("\n~")).replace(t("%"), t("%%")) if is_repr: s = s.replace(t("\\n"), t("\n~")) return s def _should_repr_global_name(obj): return not hasattr(obj, "__name__") and not py.builtin.callable(obj) def _format_boolop(explanations, is_or): explanation = "(" + (is_or and " or " or " and ").join(explanations) + ")" if py.builtin._istext(explanation): t = py.builtin.text else: t = py.builtin.bytes return explanation.replace(t('%'), t('%%')) def _call_reprcompare(ops, results, expls, each_obj): for i, res, expl in zip(range(len(ops)), results, expls): try: done = not res except Exception: done = True if done: break if util._reprcompare is not None: custom = util._reprcompare(ops[i], each_obj[i], each_obj[i + 1]) if custom is not None: return custom return expl unary_map = { ast.Not: "not %s", ast.Invert: "~%s", ast.USub: "-%s", ast.UAdd: "+%s" } binop_map = { ast.BitOr: "|", ast.BitXor: "^", ast.BitAnd: "&", ast.LShift: "<<", ast.RShift: ">>", ast.Add: "+", ast.Sub: "-", ast.Mult: "*", ast.Div: "/", ast.FloorDiv: "//", ast.Mod: "%%", # escaped for string formatting ast.Eq: "==", ast.NotEq: "!=", ast.Lt: "<", ast.LtE: "<=", ast.Gt: ">", ast.GtE: ">=", ast.Pow: "**", ast.Is: "is", ast.IsNot: "is not", ast.In: "in", ast.NotIn: "not in" } # Python 3.5+ compatibility try: binop_map[ast.MatMult] = "@" except AttributeError: pass # Python 3.4+ compatibility if hasattr(ast, "NameConstant"): _NameConstant = ast.NameConstant else: def _NameConstant(c): return ast.Name(str(c), ast.Load()) def set_location(node, lineno, col_offset): """Set node location information recursively.""" def _fix(node, lineno, col_offset): if "lineno" in node._attributes: node.lineno = lineno if "col_offset" in node._attributes: node.col_offset = col_offset for child in ast.iter_child_nodes(node): _fix(child, lineno, col_offset) _fix(node, lineno, col_offset) return node class AssertionRewriter(ast.NodeVisitor): """Assertion rewriting implementation. The main entrypoint is to call .run() with an ast.Module instance, this will then find all the assert statements and re-write them to provide intermediate values and a detailed assertion error. See http://pybites.blogspot.be/2011/07/behind-scenes-of-pytests-new-assertion.html for an overview of how this works. The entry point here is .run() which will iterate over all the statements in an ast.Module and for each ast.Assert statement it finds call .visit() with it. Then .visit_Assert() takes over and is responsible for creating new ast statements to replace the original assert statement: it re-writes the test of an assertion to provide intermediate values and replace it with an if statement which raises an assertion error with a detailed explanation in case the expression is false. For this .visit_Assert() uses the visitor pattern to visit all the AST nodes of the ast.Assert.test field, each visit call returning an AST node and the corresponding explanation string. During this state is kept in several instance attributes: :statements: All the AST statements which will replace the assert statement. :variables: This is populated by .variable() with each variable used by the statements so that they can all be set to None at the end of the statements. :variable_counter: Counter to create new unique variables needed by statements. Variables are created using .variable() and have the form of "@py_assert0". :on_failure: The AST statements which will be executed if the assertion test fails. This is the code which will construct the failure message and raises the AssertionError. :explanation_specifiers: A dict filled by .explanation_param() with %-formatting placeholders and their corresponding expressions to use in the building of an assertion message. This is used by .pop_format_context() to build a message. :stack: A stack of the explanation_specifiers dicts maintained by .push_format_context() and .pop_format_context() which allows to build another %-formatted string while already building one. This state is reset on every new assert statement visited and used by the other visitors. """ def __init__(self, module_path, config): super(AssertionRewriter, self).__init__() self.module_path = module_path self.config = config def run(self, mod): """Find all assert statements in *mod* and rewrite them.""" if not mod.body: # Nothing to do. return # Insert some special imports at the top of the module but after any # docstrings and __future__ imports. aliases = [ast.alias(py.builtin.builtins.__name__, "@py_builtins"), ast.alias("_pytest.assertion.rewrite", "@pytest_ar")] expect_docstring = True pos = 0 lineno = 0 for item in mod.body: if (expect_docstring and isinstance(item, ast.Expr) and isinstance(item.value, ast.Str)): doc = item.value.s if "PYTEST_DONT_REWRITE" in doc: # The module has disabled assertion rewriting. return lineno += len(doc) - 1 expect_docstring = False elif (not isinstance(item, ast.ImportFrom) or item.level > 0 or item.module != "__future__"): lineno = item.lineno break pos += 1 imports = [ast.Import([alias], lineno=lineno, col_offset=0) for alias in aliases] mod.body[pos:pos] = imports # Collect asserts. nodes = [mod] while nodes: node = nodes.pop() for name, field in ast.iter_fields(node): if isinstance(field, list): new = [] for i, child in enumerate(field): if isinstance(child, ast.Assert): # Transform assert. new.extend(self.visit(child)) else: new.append(child) if isinstance(child, ast.AST): nodes.append(child) setattr(node, name, new) elif (isinstance(field, ast.AST) and # Don't recurse into expressions as they can't contain # asserts. not isinstance(field, ast.expr)): nodes.append(field) def variable(self): """Get a new variable.""" # Use a character invalid in python identifiers to avoid clashing. name = "@py_assert" + str(next(self.variable_counter)) self.variables.append(name) return name def assign(self, expr): """Give *expr* a name.""" name = self.variable() self.statements.append(ast.Assign([ast.Name(name, ast.Store())], expr)) return ast.Name(name, ast.Load()) def display(self, expr): """Call py.io.saferepr on the expression.""" return self.helper("saferepr", expr) def helper(self, name, *args): """Call a helper in this module.""" py_name = ast.Name("@pytest_ar", ast.Load()) attr = ast.Attribute(py_name, "_" + name, ast.Load()) return ast_Call(attr, list(args), []) def builtin(self, name): """Return the builtin called *name*.""" builtin_name = ast.Name("@py_builtins", ast.Load()) return ast.Attribute(builtin_name, name, ast.Load()) def explanation_param(self, expr): """Return a new named %-formatting placeholder for expr. This creates a %-formatting placeholder for expr in the current formatting context, e.g. ``%(py0)s``. The placeholder and expr are placed in the current format context so that it can be used on the next call to .pop_format_context(). """ specifier = "py" + str(next(self.variable_counter)) self.explanation_specifiers[specifier] = expr return "%(" + specifier + ")s" def push_format_context(self): """Create a new formatting context. The format context is used for when an explanation wants to have a variable value formatted in the assertion message. In this case the value required can be added using .explanation_param(). Finally .pop_format_context() is used to format a string of %-formatted values as added by .explanation_param(). """ self.explanation_specifiers = {} self.stack.append(self.explanation_specifiers) def pop_format_context(self, expl_expr): """Format the %-formatted string with current format context. The expl_expr should be an ast.Str instance constructed from the %-placeholders created by .explanation_param(). This will add the required code to format said string to .on_failure and return the ast.Name instance of the formatted string. """ current = self.stack.pop() if self.stack: self.explanation_specifiers = self.stack[-1] keys = [ast.Str(key) for key in current.keys()] format_dict = ast.Dict(keys, list(current.values())) form = ast.BinOp(expl_expr, ast.Mod(), format_dict) name = "@py_format" + str(next(self.variable_counter)) self.on_failure.append(ast.Assign([ast.Name(name, ast.Store())], form)) return ast.Name(name, ast.Load()) def generic_visit(self, node): """Handle expressions we don't have custom code for.""" assert isinstance(node, ast.expr) res = self.assign(node) return res, self.explanation_param(self.display(res)) def visit_Assert(self, assert_): """Return the AST statements to replace the ast.Assert instance. This re-writes the test of an assertion to provide intermediate values and replace it with an if statement which raises an assertion error with a detailed explanation in case the expression is false. """ if isinstance(assert_.test, ast.Tuple) and self.config is not None: fslocation = (self.module_path, assert_.lineno) self.config.warn('R1', 'assertion is always true, perhaps ' 'remove parentheses?', fslocation=fslocation) self.statements = [] self.variables = [] self.variable_counter = itertools.count() self.stack = [] self.on_failure = [] self.push_format_context() # Rewrite assert into a bunch of statements. top_condition, explanation = self.visit(assert_.test) # Create failure message. body = self.on_failure negation = ast.UnaryOp(ast.Not(), top_condition) self.statements.append(ast.If(negation, body, [])) if assert_.msg: assertmsg = self.helper('format_assertmsg', assert_.msg) explanation = "\n>assert " + explanation else: assertmsg = ast.Str("") explanation = "assert " + explanation template = ast.BinOp(assertmsg, ast.Add(), ast.Str(explanation)) msg = self.pop_format_context(template) fmt = self.helper("format_explanation", msg) err_name = ast.Name("AssertionError", ast.Load()) exc = ast_Call(err_name, [fmt], []) if sys.version_info[0] >= 3: raise_ = ast.Raise(exc, None) else: raise_ = ast.Raise(exc, None, None) body.append(raise_) # Clear temporary variables by setting them to None. if self.variables: variables = [ast.Name(name, ast.Store()) for name in self.variables] clear = ast.Assign(variables, _NameConstant(None)) self.statements.append(clear) # Fix line numbers. for stmt in self.statements: set_location(stmt, assert_.lineno, assert_.col_offset) return self.statements def visit_Name(self, name): # Display the repr of the name if it's a local variable or # _should_repr_global_name() thinks it's acceptable. locs = ast_Call(self.builtin("locals"), [], []) inlocs = ast.Compare(ast.Str(name.id), [ast.In()], [locs]) dorepr = self.helper("should_repr_global_name", name) test = ast.BoolOp(ast.Or(), [inlocs, dorepr]) expr = ast.IfExp(test, self.display(name), ast.Str(name.id)) return name, self.explanation_param(expr) def visit_BoolOp(self, boolop): res_var = self.variable() expl_list = self.assign(ast.List([], ast.Load())) app = ast.Attribute(expl_list, "append", ast.Load()) is_or = int(isinstance(boolop.op, ast.Or)) body = save = self.statements fail_save = self.on_failure levels = len(boolop.values) - 1 self.push_format_context() # Process each operand, short-circuting if needed. for i, v in enumerate(boolop.values): if i: fail_inner = [] # cond is set in a prior loop iteration below self.on_failure.append(ast.If(cond, fail_inner, [])) # noqa self.on_failure = fail_inner self.push_format_context() res, expl = self.visit(v) body.append(ast.Assign([ast.Name(res_var, ast.Store())], res)) expl_format = self.pop_format_context(ast.Str(expl)) call = ast_Call(app, [expl_format], []) self.on_failure.append(ast.Expr(call)) if i < levels: cond = res if is_or: cond = ast.UnaryOp(ast.Not(), cond) inner = [] self.statements.append(ast.If(cond, inner, [])) self.statements = body = inner self.statements = save self.on_failure = fail_save expl_template = self.helper("format_boolop", expl_list, ast.Num(is_or)) expl = self.pop_format_context(expl_template) return ast.Name(res_var, ast.Load()), self.explanation_param(expl) def visit_UnaryOp(self, unary): pattern = unary_map[unary.op.__class__] operand_res, operand_expl = self.visit(unary.operand) res = self.assign(ast.UnaryOp(unary.op, operand_res)) return res, pattern % (operand_expl,) def visit_BinOp(self, binop): symbol = binop_map[binop.op.__class__] left_expr, left_expl = self.visit(binop.left) right_expr, right_expl = self.visit(binop.right) explanation = "(%s %s %s)" % (left_expl, symbol, right_expl) res = self.assign(ast.BinOp(left_expr, binop.op, right_expr)) return res, explanation def visit_Call_35(self, call): """ visit `ast.Call` nodes on Python3.5 and after """ new_func, func_expl = self.visit(call.func) arg_expls = [] new_args = [] new_kwargs = [] for arg in call.args: res, expl = self.visit(arg) arg_expls.append(expl) new_args.append(res) for keyword in call.keywords: res, expl = self.visit(keyword.value) new_kwargs.append(ast.keyword(keyword.arg, res)) if keyword.arg: arg_expls.append(keyword.arg + "=" + expl) else: ## **args have `arg` keywords with an .arg of None arg_expls.append("**" + expl) expl = "%s(%s)" % (func_expl, ', '.join(arg_expls)) new_call = ast.Call(new_func, new_args, new_kwargs) res = self.assign(new_call) res_expl = self.explanation_param(self.display(res)) outer_expl = "%s\n{%s = %s\n}" % (res_expl, res_expl, expl) return res, outer_expl def visit_Starred(self, starred): # From Python 3.5, a Starred node can appear in a function call res, expl = self.visit(starred.value) return starred, '*' + expl def visit_Call_legacy(self, call): """ visit `ast.Call nodes on 3.4 and below` """ new_func, func_expl = self.visit(call.func) arg_expls = [] new_args = [] new_kwargs = [] new_star = new_kwarg = None for arg in call.args: res, expl = self.visit(arg) new_args.append(res) arg_expls.append(expl) for keyword in call.keywords: res, expl = self.visit(keyword.value) new_kwargs.append(ast.keyword(keyword.arg, res)) arg_expls.append(keyword.arg + "=" + expl) if call.starargs: new_star, expl = self.visit(call.starargs) arg_expls.append("*" + expl) if call.kwargs: new_kwarg, expl = self.visit(call.kwargs) arg_expls.append("**" + expl) expl = "%s(%s)" % (func_expl, ', '.join(arg_expls)) new_call = ast.Call(new_func, new_args, new_kwargs, new_star, new_kwarg) res = self.assign(new_call) res_expl = self.explanation_param(self.display(res)) outer_expl = "%s\n{%s = %s\n}" % (res_expl, res_expl, expl) return res, outer_expl # ast.Call signature changed on 3.5, # conditionally change which methods is named # visit_Call depending on Python version if sys.version_info >= (3, 5): visit_Call = visit_Call_35 else: visit_Call = visit_Call_legacy def visit_Attribute(self, attr): if not isinstance(attr.ctx, ast.Load): return self.generic_visit(attr) value, value_expl = self.visit(attr.value) res = self.assign(ast.Attribute(value, attr.attr, ast.Load())) res_expl = self.explanation_param(self.display(res)) pat = "%s\n{%s = %s.%s\n}" expl = pat % (res_expl, res_expl, value_expl, attr.attr) return res, expl def visit_Compare(self, comp): self.push_format_context() left_res, left_expl = self.visit(comp.left) if isinstance(comp.left, (_ast.Compare, _ast.BoolOp)): left_expl = "({0})".format(left_expl) res_variables = [self.variable() for i in range(len(comp.ops))] load_names = [ast.Name(v, ast.Load()) for v in res_variables] store_names = [ast.Name(v, ast.Store()) for v in res_variables] it = zip(range(len(comp.ops)), comp.ops, comp.comparators) expls = [] syms = [] results = [left_res] for i, op, next_operand in it: next_res, next_expl = self.visit(next_operand) if isinstance(next_operand, (_ast.Compare, _ast.BoolOp)): next_expl = "({0})".format(next_expl) results.append(next_res) sym = binop_map[op.__class__] syms.append(ast.Str(sym)) expl = "%s %s %s" % (left_expl, sym, next_expl) expls.append(ast.Str(expl)) res_expr = ast.Compare(left_res, [op], [next_res]) self.statements.append(ast.Assign([store_names[i]], res_expr)) left_res, left_expl = next_res, next_expl # Use pytest.assertion.util._reprcompare if that's available. expl_call = self.helper("call_reprcompare", ast.Tuple(syms, ast.Load()), ast.Tuple(load_names, ast.Load()), ast.Tuple(expls, ast.Load()), ast.Tuple(results, ast.Load())) if len(comp.ops) > 1: res = ast.BoolOp(ast.And(), load_names) else: res = load_names[0] return res, self.explanation_param(self.pop_format_context(expl_call))

jaraco/pytest

_pytest/assertion/rewrite.py

Python

mit

36,408

[ "VisIt" ]

eb323067c6c1fa56007179e82feaebc742ee2ed5bfdff1b103a1e8c0c2e52b69

# -*- coding: utf-8 -*- # Form implementation generated from reading ui file 'ui/ui_semiautomaticclassificationplugin.ui' # # Created by: PyQt5 UI code generator 5.11.3 # # WARNING! All changes made in this file will be lost! from PyQt5 import QtCore, QtGui, QtWidgets class Ui_SemiAutomaticClassificationPlugin(object): def setupUi(self, SemiAutomaticClassificationPlugin): SemiAutomaticClassificationPlugin.setObjectName("SemiAutomaticClassificationPlugin") SemiAutomaticClassificationPlugin.setEnabled(True) SemiAutomaticClassificationPlugin.resize(951, 529) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(SemiAutomaticClassificationPlugin.sizePolicy().hasHeightForWidth()) SemiAutomaticClassificationPlugin.setSizePolicy(sizePolicy) SemiAutomaticClassificationPlugin.setMinimumSize(QtCore.QSize(400, 400)) icon = QtGui.QIcon() icon.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) SemiAutomaticClassificationPlugin.setWindowIcon(icon) SemiAutomaticClassificationPlugin.setSizeGripEnabled(True) self.gridLayout_301 = QtWidgets.QGridLayout(SemiAutomaticClassificationPlugin) self.gridLayout_301.setContentsMargins(2, 2, 2, 2) self.gridLayout_301.setObjectName("gridLayout_301") self.splitter = QtWidgets.QSplitter(SemiAutomaticClassificationPlugin) self.splitter.setFrameShape(QtWidgets.QFrame.NoFrame) self.splitter.setOrientation(QtCore.Qt.Horizontal) self.splitter.setChildrenCollapsible(False) self.splitter.setObjectName("splitter") self.widget = QtWidgets.QWidget(self.splitter) self.widget.setMinimumSize(QtCore.QSize(50, 0)) self.widget.setMaximumSize(QtCore.QSize(250, 16777215)) self.widget.setObjectName("widget") self.gridLayout_193 = QtWidgets.QGridLayout(self.widget) self.gridLayout_193.setContentsMargins(1, 1, 1, 1) self.gridLayout_193.setObjectName("gridLayout_193") self.f_filter_lineEdit = QtWidgets.QLineEdit(self.widget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.f_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.f_filter_lineEdit.setSizePolicy(sizePolicy) self.f_filter_lineEdit.setMinimumSize(QtCore.QSize(100, 0)) self.f_filter_lineEdit.setObjectName("f_filter_lineEdit") self.gridLayout_193.addWidget(self.f_filter_lineEdit, 0, 0, 1, 1) self.menu_treeWidget = QtWidgets.QTreeWidget(self.widget) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.menu_treeWidget.sizePolicy().hasHeightForWidth()) self.menu_treeWidget.setSizePolicy(sizePolicy) self.menu_treeWidget.setMinimumSize(QtCore.QSize(100, 0)) self.menu_treeWidget.setFrameShape(QtWidgets.QFrame.StyledPanel) self.menu_treeWidget.setFrameShadow(QtWidgets.QFrame.Sunken) self.menu_treeWidget.setEditTriggers(QtWidgets.QAbstractItemView.CurrentChanged|QtWidgets.QAbstractItemView.DoubleClicked) self.menu_treeWidget.setProperty("showDropIndicator", False) self.menu_treeWidget.setAlternatingRowColors(True) self.menu_treeWidget.setTextElideMode(QtCore.Qt.ElideNone) self.menu_treeWidget.setIndentation(15) self.menu_treeWidget.setRootIsDecorated(True) self.menu_treeWidget.setHeaderHidden(True) self.menu_treeWidget.setObjectName("menu_treeWidget") item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon1 = QtGui.QIcon() icon1.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandset_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon1) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon2 = QtGui.QIcon() icon2.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_roi_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon2) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon3 = QtGui.QIcon() icon3.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_weight_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon3) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_1.setIcon(0, icon1) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon4 = QtGui.QIcon() icon4.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_export_spectral_library.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon4) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon5 = QtGui.QIcon() icon5.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_import_spectral_library.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon5) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon6 = QtGui.QIcon() icon6.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_LCS_threshold_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon6) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon7 = QtGui.QIcon() icon7.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_roi_multiple.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon7) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon8 = QtGui.QIcon() icon8.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_rgb_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon8) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon9 = QtGui.QIcon() icon9.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_threshold_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon9) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon10 = QtGui.QIcon() icon10.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_arrow.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon10) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon11 = QtGui.QIcon() icon11.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_class_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon11) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon12 = QtGui.QIcon() icon12.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_aster_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon12) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon13 = QtGui.QIcon() icon13.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_goes_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon13) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon14 = QtGui.QIcon() icon14.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_landsat8_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon14) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon15 = QtGui.QIcon() icon15.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_modis_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon15) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon16 = QtGui.QIcon() icon16.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sentinel1_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon16) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon17 = QtGui.QIcon() icon17.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sentinel_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon17) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon18 = QtGui.QIcon() icon18.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sentinel3_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon18) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon19 = QtGui.QIcon() icon19.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_clip_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon19) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon20 = QtGui.QIcon() icon20.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_cloud_masking_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon20) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon21 = QtGui.QIcon() icon21.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_mosaic_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon21) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon22 = QtGui.QIcon() icon22.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_neighbor_pixels.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon22) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon23 = QtGui.QIcon() icon23.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reproject_raster_bands.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon23) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon24 = QtGui.QIcon() icon24.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_split_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon24) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon25 = QtGui.QIcon() icon25.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_stack_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon25) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon26 = QtGui.QIcon() icon26.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_vector_to_raster_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon26) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon27 = QtGui.QIcon() icon27.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_band_processing.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon27) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon28 = QtGui.QIcon() icon28.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_band_combination_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon28) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon29 = QtGui.QIcon() icon29.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon29) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon30 = QtGui.QIcon() icon30.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_kmeans_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon30) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon31 = QtGui.QIcon() icon31.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_pca_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon31) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon32 = QtGui.QIcon() icon32.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_random_forest.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon32) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon33 = QtGui.QIcon() icon33.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_spectral_distance.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon33) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon34 = QtGui.QIcon() icon34.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_post_process.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon34) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon35 = QtGui.QIcon() icon35.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_accuracy_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon35) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon36 = QtGui.QIcon() icon36.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification_dilation.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon36) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon37 = QtGui.QIcon() icon37.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification_erosion.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon37) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon38 = QtGui.QIcon() icon38.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_report_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon38) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon39 = QtGui.QIcon() icon39.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_class_to_vector_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon39) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon40 = QtGui.QIcon() icon40.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_classification_sieve.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon40) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon41 = QtGui.QIcon() icon41.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_class_signature_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon41) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon42 = QtGui.QIcon() icon42.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_cross_classification.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon42) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon43 = QtGui.QIcon() icon43.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_edit_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon43) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon44 = QtGui.QIcon() icon44.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_land_cover_change.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon44) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon45 = QtGui.QIcon() icon45.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reclassification_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon45) item_1 = QtWidgets.QTreeWidgetItem(item_0) icon46 = QtGui.QIcon() icon46.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_zonal_stat_raster_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_1.setIcon(0, icon46) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon47 = QtGui.QIcon() icon47.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandcalc_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon47) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon48 = QtGui.QIcon() icon48.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_batch.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon48) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon49 = QtGui.QIcon() icon49.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_settings_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon49) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_1 = QtWidgets.QTreeWidgetItem(item_0) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) icon50 = QtGui.QIcon() icon50.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/guide.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon50) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) icon51 = QtGui.QIcon() icon51.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/help.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon51) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) item_0.setFont(0, font) icon52 = QtGui.QIcon() icon52.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/fromGIStoRS.png"), QtGui.QIcon.Normal, QtGui.QIcon.Off) item_0.setIcon(0, icon52) item_0 = QtWidgets.QTreeWidgetItem(self.menu_treeWidget) font = QtGui.QFont() font.setBold(True) font.setWeight(75) font.setStrikeOut(False) item_0.setFont(0, font) brush = QtGui.QBrush(QtGui.QColor(92, 184, 92)) brush.setStyle(QtCore.Qt.SolidPattern) item_0.setBackground(0, brush) brush = QtGui.QBrush(QtGui.QColor(255, 255, 255)) brush.setStyle(QtCore.Qt.NoBrush) item_0.setForeground(0, brush) item_0.setIcon(0, icon) self.gridLayout_193.addWidget(self.menu_treeWidget, 1, 0, 1, 1) self.main_tabWidget = QtWidgets.QTabWidget(self.splitter) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.main_tabWidget.sizePolicy().hasHeightForWidth()) self.main_tabWidget.setSizePolicy(sizePolicy) self.main_tabWidget.setMinimumSize(QtCore.QSize(400, 0)) self.main_tabWidget.setTabPosition(QtWidgets.QTabWidget.East) self.main_tabWidget.setTabShape(QtWidgets.QTabWidget.Rounded) self.main_tabWidget.setIconSize(QtCore.QSize(12, 12)) self.main_tabWidget.setDocumentMode(True) self.main_tabWidget.setObjectName("main_tabWidget") self.tool_tab = QtWidgets.QWidget() self.tool_tab.setObjectName("tool_tab") self.gridLayout_262 = QtWidgets.QGridLayout(self.tool_tab) self.gridLayout_262.setObjectName("gridLayout_262") self.SCP_tabs = QtWidgets.QTabWidget(self.tool_tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.SCP_tabs.sizePolicy().hasHeightForWidth()) self.SCP_tabs.setSizePolicy(sizePolicy) self.SCP_tabs.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates)) self.SCP_tabs.setIconSize(QtCore.QSize(20, 20)) self.SCP_tabs.setDocumentMode(True) self.SCP_tabs.setObjectName("SCP_tabs") self.tab_band_set = QtWidgets.QWidget() self.tab_band_set.setObjectName("tab_band_set") self.gridLayout_219 = QtWidgets.QGridLayout(self.tab_band_set) self.gridLayout_219.setObjectName("gridLayout_219") self.gridLayout_52 = QtWidgets.QGridLayout() self.gridLayout_52.setObjectName("gridLayout_52") self.label_59 = QtWidgets.QLabel(self.tab_band_set) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_59.sizePolicy().hasHeightForWidth()) self.label_59.setSizePolicy(sizePolicy) self.label_59.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_59.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_59.setWordWrap(False) self.label_59.setObjectName("label_59") self.gridLayout_52.addWidget(self.label_59, 0, 0, 1, 1) self.wavelength_sat_combo = QtWidgets.QComboBox(self.tab_band_set) self.wavelength_sat_combo.setObjectName("wavelength_sat_combo") self.gridLayout_52.addWidget(self.wavelength_sat_combo, 0, 1, 1, 1) self.gridLayout_50 = QtWidgets.QGridLayout() self.gridLayout_50.setObjectName("gridLayout_50") self.label_60 = QtWidgets.QLabel(self.tab_band_set) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_60.sizePolicy().hasHeightForWidth()) self.label_60.setSizePolicy(sizePolicy) self.label_60.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_60.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_60.setObjectName("label_60") self.gridLayout_50.addWidget(self.label_60, 0, 0, 1, 1) self.unit_combo = QtWidgets.QComboBox(self.tab_band_set) self.unit_combo.setMinimumSize(QtCore.QSize(100, 0)) self.unit_combo.setObjectName("unit_combo") self.gridLayout_50.addWidget(self.unit_combo, 0, 1, 1, 1) self.export_bandset_toolButton = QtWidgets.QToolButton(self.tab_band_set) self.export_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon53 = QtGui.QIcon() icon53.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_export.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.export_bandset_toolButton.setIcon(icon53) self.export_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_bandset_toolButton.setObjectName("export_bandset_toolButton") self.gridLayout_50.addWidget(self.export_bandset_toolButton, 0, 5, 1, 1) self.import_bandset_toolButton = QtWidgets.QToolButton(self.tab_band_set) self.import_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon54 = QtGui.QIcon() icon54.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_import.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.import_bandset_toolButton.setIcon(icon54) self.import_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_bandset_toolButton.setObjectName("import_bandset_toolButton") self.gridLayout_50.addWidget(self.import_bandset_toolButton, 0, 4, 1, 1) self.bandset_dateEdit = QtWidgets.QDateEdit(self.tab_band_set) self.bandset_dateEdit.setDateTime(QtCore.QDateTime(QtCore.QDate(2020, 1, 1), QtCore.QTime(0, 0, 0))) self.bandset_dateEdit.setMaximumDate(QtCore.QDate(2045, 12, 31)) self.bandset_dateEdit.setMinimumDate(QtCore.QDate(1972, 1, 1)) self.bandset_dateEdit.setCalendarPopup(True) self.bandset_dateEdit.setDate(QtCore.QDate(2020, 1, 1)) self.bandset_dateEdit.setObjectName("bandset_dateEdit") self.gridLayout_50.addWidget(self.bandset_dateEdit, 0, 3, 1, 1) self.label_3 = QtWidgets.QLabel(self.tab_band_set) self.label_3.setObjectName("label_3") self.gridLayout_50.addWidget(self.label_3, 0, 2, 1, 1) self.gridLayout_52.addLayout(self.gridLayout_50, 0, 2, 1, 1) self.gridLayout_219.addLayout(self.gridLayout_52, 2, 0, 1, 2) self.splitter_3 = QtWidgets.QSplitter(self.tab_band_set) self.splitter_3.setOrientation(QtCore.Qt.Vertical) self.splitter_3.setChildrenCollapsible(False) self.splitter_3.setObjectName("splitter_3") self.widget_5 = QtWidgets.QWidget(self.splitter_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_5.sizePolicy().hasHeightForWidth()) self.widget_5.setSizePolicy(sizePolicy) self.widget_5.setMinimumSize(QtCore.QSize(0, 50)) self.widget_5.setObjectName("widget_5") self.gridLayout_203 = QtWidgets.QGridLayout(self.widget_5) self.gridLayout_203.setContentsMargins(1, 1, 1, 1) self.gridLayout_203.setObjectName("gridLayout_203") self.gridLayout_59 = QtWidgets.QGridLayout() self.gridLayout_59.setObjectName("gridLayout_59") spacerItem = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_59.addItem(spacerItem, 2, 1, 1, 1) self.label_52 = QtWidgets.QLabel(self.widget_5) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_52.sizePolicy().hasHeightForWidth()) self.label_52.setSizePolicy(sizePolicy) self.label_52.setStyleSheet("background-color : #656565; color : white") self.label_52.setFrameShape(QtWidgets.QFrame.Panel) self.label_52.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_52.setObjectName("label_52") self.gridLayout_59.addWidget(self.label_52, 0, 0, 1, 1) self.bands_filter_lineEdit = QtWidgets.QLineEdit(self.widget_5) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.bands_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.bands_filter_lineEdit.setSizePolicy(sizePolicy) self.bands_filter_lineEdit.setObjectName("bands_filter_lineEdit") self.gridLayout_59.addWidget(self.bands_filter_lineEdit, 0, 1, 1, 1) self.gridLayout_69 = QtWidgets.QGridLayout() self.gridLayout_69.setObjectName("gridLayout_69") self.bands_tableWidget = QtWidgets.QTableWidget(self.widget_5) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.bands_tableWidget.sizePolicy().hasHeightForWidth()) self.bands_tableWidget.setSizePolicy(sizePolicy) self.bands_tableWidget.setMinimumSize(QtCore.QSize(0, 30)) self.bands_tableWidget.setFrameShadow(QtWidgets.QFrame.Sunken) self.bands_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.bands_tableWidget.setTabKeyNavigation(True) self.bands_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.bands_tableWidget.setObjectName("bands_tableWidget") self.bands_tableWidget.setColumnCount(1) self.bands_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.bands_tableWidget.setHorizontalHeaderItem(0, item) self.bands_tableWidget.horizontalHeader().setVisible(False) self.bands_tableWidget.horizontalHeader().setStretchLastSection(True) self.bands_tableWidget.verticalHeader().setVisible(False) self.gridLayout_69.addWidget(self.bands_tableWidget, 0, 0, 1, 1) self.gridLayout_60 = QtWidgets.QGridLayout() self.gridLayout_60.setObjectName("gridLayout_60") self.toolButton_reload_3 = QtWidgets.QToolButton(self.widget_5) self.toolButton_reload_3.setStyleSheet("margin: 0px;padding: 0px") icon55 = QtGui.QIcon() icon55.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reload.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_reload_3.setIcon(icon55) self.toolButton_reload_3.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_3.setObjectName("toolButton_reload_3") self.gridLayout_60.addWidget(self.toolButton_reload_3, 1, 0, 1, 1) self.select_all_bands_Button = QtWidgets.QToolButton(self.widget_5) self.select_all_bands_Button.setStyleSheet("margin: 0px;padding: 0px;") icon56 = QtGui.QIcon() icon56.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_select_all.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.select_all_bands_Button.setIcon(icon56) self.select_all_bands_Button.setIconSize(QtCore.QSize(22, 22)) self.select_all_bands_Button.setObjectName("select_all_bands_Button") self.gridLayout_60.addWidget(self.select_all_bands_Button, 2, 0, 1, 1) self.add_raster_bands_Button = QtWidgets.QToolButton(self.widget_5) self.add_raster_bands_Button.setStyleSheet("margin: 0px;padding: 0px") icon57 = QtGui.QIcon() icon57.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_plus.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.add_raster_bands_Button.setIcon(icon57) self.add_raster_bands_Button.setIconSize(QtCore.QSize(22, 22)) self.add_raster_bands_Button.setObjectName("add_raster_bands_Button") self.gridLayout_60.addWidget(self.add_raster_bands_Button, 3, 0, 1, 1) self.gridLayout_69.addLayout(self.gridLayout_60, 0, 1, 1, 1) self.gridLayout_59.addLayout(self.gridLayout_69, 1, 0, 2, 2) self.gridLayout_203.addLayout(self.gridLayout_59, 0, 0, 1, 1) self.widget_6 = QtWidgets.QWidget(self.splitter_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_6.sizePolicy().hasHeightForWidth()) self.widget_6.setSizePolicy(sizePolicy) self.widget_6.setMinimumSize(QtCore.QSize(0, 50)) self.widget_6.setObjectName("widget_6") self.gridLayout_217 = QtWidgets.QGridLayout(self.widget_6) self.gridLayout_217.setContentsMargins(1, 1, 1, 1) self.gridLayout_217.setObjectName("gridLayout_217") self.gridLayout_11 = QtWidgets.QGridLayout() self.gridLayout_11.setObjectName("gridLayout_11") self.gridLayout_42 = QtWidgets.QGridLayout() self.gridLayout_42.setObjectName("gridLayout_42") self.label_53 = QtWidgets.QLabel(self.widget_6) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_53.sizePolicy().hasHeightForWidth()) self.label_53.setSizePolicy(sizePolicy) self.label_53.setStyleSheet("background-color : #656565; color : white") self.label_53.setFrameShape(QtWidgets.QFrame.Panel) self.label_53.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_53.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_53.setObjectName("label_53") self.gridLayout_42.addWidget(self.label_53, 0, 0, 1, 1) self.gridLayout_11.addLayout(self.gridLayout_42, 0, 0, 1, 2) self.Band_set_tabWidget = QtWidgets.QTabWidget(self.widget_6) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.Band_set_tabWidget.sizePolicy().hasHeightForWidth()) self.Band_set_tabWidget.setSizePolicy(sizePolicy) self.Band_set_tabWidget.setMinimumSize(QtCore.QSize(0, 20)) self.Band_set_tabWidget.setStyleSheet("QTabBar::tab {\n" "min-height: 30px;\n" "min-width: 120px;\n" "}\n" "QTabBar::tab:selected { font: bold; color: green; }") self.Band_set_tabWidget.setTabPosition(QtWidgets.QTabWidget.North) self.Band_set_tabWidget.setDocumentMode(True) self.Band_set_tabWidget.setTabsClosable(True) self.Band_set_tabWidget.setMovable(True) self.Band_set_tabWidget.setObjectName("Band_set_tabWidget") self.gridLayout_11.addWidget(self.Band_set_tabWidget, 1, 0, 1, 1) self.gridLayout_65 = QtWidgets.QGridLayout() self.gridLayout_65.setObjectName("gridLayout_65") self.gridLayout_169 = QtWidgets.QGridLayout() self.gridLayout_169.setObjectName("gridLayout_169") self.remove_toolButton = QtWidgets.QToolButton(self.widget_6) self.remove_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon58 = QtGui.QIcon() icon58.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_remove.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.remove_toolButton.setIcon(icon58) self.remove_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_toolButton.setObjectName("remove_toolButton") self.gridLayout_169.addWidget(self.remove_toolButton, 0, 0, 1, 1) self.clear_bandset_toolButton = QtWidgets.QToolButton(self.widget_6) self.clear_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon59 = QtGui.QIcon() icon59.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_reset.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.clear_bandset_toolButton.setIcon(icon59) self.clear_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_bandset_toolButton.setObjectName("clear_bandset_toolButton") self.gridLayout_169.addWidget(self.clear_bandset_toolButton, 1, 0, 1, 1) self.gridLayout_65.addLayout(self.gridLayout_169, 1, 0, 1, 2) self.gridLayout_127 = QtWidgets.QGridLayout() self.gridLayout_127.setObjectName("gridLayout_127") self.sort_by_name_toolButton = QtWidgets.QToolButton(self.widget_6) self.sort_by_name_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon60 = QtGui.QIcon() icon60.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_order_by_name.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.sort_by_name_toolButton.setIcon(icon60) self.sort_by_name_toolButton.setIconSize(QtCore.QSize(22, 22)) self.sort_by_name_toolButton.setObjectName("sort_by_name_toolButton") self.gridLayout_127.addWidget(self.sort_by_name_toolButton, 3, 0, 1, 1) self.move_up_toolButton = QtWidgets.QToolButton(self.widget_6) self.move_up_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon61 = QtGui.QIcon() icon61.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_move_up.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.move_up_toolButton.setIcon(icon61) self.move_up_toolButton.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton.setObjectName("move_up_toolButton") self.gridLayout_127.addWidget(self.move_up_toolButton, 1, 0, 1, 1) self.move_down_toolButton = QtWidgets.QToolButton(self.widget_6) self.move_down_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon62 = QtGui.QIcon() icon62.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_move_down.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.move_down_toolButton.setIcon(icon62) self.move_down_toolButton.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton.setObjectName("move_down_toolButton") self.gridLayout_127.addWidget(self.move_down_toolButton, 2, 0, 1, 1) self.add_band_set_toolButton = QtWidgets.QToolButton(self.widget_6) self.add_band_set_toolButton.setStyleSheet("margin: 0px;padding: 0px") icon63 = QtGui.QIcon() icon63.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_add_bandset_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.add_band_set_toolButton.setIcon(icon63) self.add_band_set_toolButton.setIconSize(QtCore.QSize(22, 22)) self.add_band_set_toolButton.setObjectName("add_band_set_toolButton") self.gridLayout_127.addWidget(self.add_band_set_toolButton, 0, 0, 1, 1) self.gridLayout_65.addLayout(self.gridLayout_127, 0, 0, 1, 2) self.gridLayout_11.addLayout(self.gridLayout_65, 1, 1, 1, 1) self.gridLayout_217.addLayout(self.gridLayout_11, 0, 0, 1, 1) self.gridLayout_219.addWidget(self.splitter_3, 1, 0, 1, 2) self.gridLayout_53 = QtWidgets.QGridLayout() self.gridLayout_53.setObjectName("gridLayout_53") self.virtual_raster_bandset_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.virtual_raster_bandset_checkBox.setObjectName("virtual_raster_bandset_checkBox") self.gridLayout_53.addWidget(self.virtual_raster_bandset_checkBox, 1, 0, 1, 1) self.band_calc_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.band_calc_checkBox.setObjectName("band_calc_checkBox") self.gridLayout_53.addWidget(self.band_calc_checkBox, 1, 3, 1, 1) self.stack_raster_bandset_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.stack_raster_bandset_checkBox.setObjectName("stack_raster_bandset_checkBox") self.gridLayout_53.addWidget(self.stack_raster_bandset_checkBox, 1, 1, 1, 1) self.overview_raster_bandset_checkBox = QtWidgets.QCheckBox(self.tab_band_set) self.overview_raster_bandset_checkBox.setObjectName("overview_raster_bandset_checkBox") self.gridLayout_53.addWidget(self.overview_raster_bandset_checkBox, 1, 2, 1, 1) self.label_94 = QtWidgets.QLabel(self.tab_band_set) self.label_94.setStyleSheet("background-color : #656565; color : white") self.label_94.setFrameShape(QtWidgets.QFrame.Panel) self.label_94.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_94.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_94.setObjectName("label_94") self.gridLayout_53.addWidget(self.label_94, 0, 0, 1, 7) spacerItem1 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_53.addItem(spacerItem1, 1, 4, 1, 1) self.band_set_process_toolButton = QtWidgets.QToolButton(self.tab_band_set) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.band_set_process_toolButton.setFont(font) self.band_set_process_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.band_set_process_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon64 = QtGui.QIcon() icon64.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_run.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.band_set_process_toolButton.setIcon(icon64) self.band_set_process_toolButton.setIconSize(QtCore.QSize(34, 34)) self.band_set_process_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.band_set_process_toolButton.setObjectName("band_set_process_toolButton") self.gridLayout_53.addWidget(self.band_set_process_toolButton, 1, 5, 1, 1) self.gridLayout_219.addLayout(self.gridLayout_53, 3, 0, 1, 2) self.gridLayout_130 = QtWidgets.QGridLayout() self.gridLayout_130.setObjectName("gridLayout_130") self.toolButton_reload = QtWidgets.QToolButton(self.tab_band_set) self.toolButton_reload.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload.setIcon(icon55) self.toolButton_reload.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload.setObjectName("toolButton_reload") self.gridLayout_130.addWidget(self.toolButton_reload, 1, 4, 1, 1) self.label_39 = QtWidgets.QLabel(self.tab_band_set) self.label_39.setStyleSheet("background-color : #656565; color : white") self.label_39.setFrameShape(QtWidgets.QFrame.Panel) self.label_39.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_39.setObjectName("label_39") self.gridLayout_130.addWidget(self.label_39, 0, 0, 1, 5) self.toolButton_input_raster = QtWidgets.QToolButton(self.tab_band_set) self.toolButton_input_raster.setStyleSheet("margin: 0px;padding: 0px;") icon65 = QtGui.QIcon() icon65.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_open_file.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_input_raster.setIcon(icon65) self.toolButton_input_raster.setIconSize(QtCore.QSize(22, 22)) self.toolButton_input_raster.setObjectName("toolButton_input_raster") self.gridLayout_130.addWidget(self.toolButton_input_raster, 1, 3, 1, 1) self.image_raster_name_combo = QtWidgets.QComboBox(self.tab_band_set) self.image_raster_name_combo.setObjectName("image_raster_name_combo") self.gridLayout_130.addWidget(self.image_raster_name_combo, 1, 0, 1, 3) self.gridLayout_219.addLayout(self.gridLayout_130, 0, 0, 1, 2) self.SCP_tabs.addTab(self.tab_band_set, "") self.tab_basic_tools = QtWidgets.QWidget() self.tab_basic_tools.setObjectName("tab_basic_tools") self.gridLayout_216 = QtWidgets.QGridLayout(self.tab_basic_tools) self.gridLayout_216.setObjectName("gridLayout_216") self.tabWidget_5 = QtWidgets.QTabWidget(self.tab_basic_tools) self.tabWidget_5.setStyleSheet("") self.tabWidget_5.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_5.setDocumentMode(True) self.tabWidget_5.setObjectName("tabWidget_5") self.tab_RGB = QtWidgets.QWidget() self.tab_RGB.setObjectName("tab_RGB") self.gridLayout_213 = QtWidgets.QGridLayout(self.tab_RGB) self.gridLayout_213.setObjectName("gridLayout_213") self.gridLayout_243 = QtWidgets.QGridLayout() self.gridLayout_243.setObjectName("gridLayout_243") self.gridLayout_234 = QtWidgets.QGridLayout() self.gridLayout_234.setObjectName("gridLayout_234") self.label_126 = QtWidgets.QLabel(self.tab_RGB) self.label_126.setStyleSheet("background-color : #656565; color : white") self.label_126.setFrameShape(QtWidgets.QFrame.Panel) self.label_126.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_126.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_126.setObjectName("label_126") self.gridLayout_234.addWidget(self.label_126, 0, 0, 1, 1) self.gridLayout_243.addLayout(self.gridLayout_234, 0, 0, 1, 2) self.gridLayout_244 = QtWidgets.QGridLayout() self.gridLayout_244.setObjectName("gridLayout_244") spacerItem2 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_244.addItem(spacerItem2, 3, 0, 1, 1) self.sort_by_name_toolButton_2 = QtWidgets.QToolButton(self.tab_RGB) self.sort_by_name_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.sort_by_name_toolButton_2.setIcon(icon60) self.sort_by_name_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.sort_by_name_toolButton_2.setObjectName("sort_by_name_toolButton_2") self.gridLayout_244.addWidget(self.sort_by_name_toolButton_2, 2, 0, 1, 1) self.move_down_toolButton_3 = QtWidgets.QToolButton(self.tab_RGB) self.move_down_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") self.move_down_toolButton_3.setIcon(icon62) self.move_down_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton_3.setObjectName("move_down_toolButton_3") self.gridLayout_244.addWidget(self.move_down_toolButton_3, 1, 0, 1, 1) self.move_up_toolButton_3 = QtWidgets.QToolButton(self.tab_RGB) self.move_up_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") self.move_up_toolButton_3.setIcon(icon61) self.move_up_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton_3.setObjectName("move_up_toolButton_3") self.gridLayout_244.addWidget(self.move_up_toolButton_3, 0, 0, 1, 1) self.gridLayout_243.addLayout(self.gridLayout_244, 1, 1, 1, 1) self.gridLayout_245 = QtWidgets.QGridLayout() self.gridLayout_245.setObjectName("gridLayout_245") self.add_RGB_pushButton = QtWidgets.QToolButton(self.tab_RGB) self.add_RGB_pushButton.setStyleSheet("margin: 0px;padding: 0px") icon66 = QtGui.QIcon() icon66.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_add.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.add_RGB_pushButton.setIcon(icon66) self.add_RGB_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_RGB_pushButton.setObjectName("add_RGB_pushButton") self.gridLayout_245.addWidget(self.add_RGB_pushButton, 0, 0, 1, 1) self.export_RGB_List_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.export_RGB_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_RGB_List_toolButton.setIcon(icon53) self.export_RGB_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_RGB_List_toolButton.setObjectName("export_RGB_List_toolButton") self.gridLayout_245.addWidget(self.export_RGB_List_toolButton, 4, 0, 1, 1) self.import_RGB_List_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.import_RGB_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_RGB_List_toolButton.setIcon(icon54) self.import_RGB_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_RGB_List_toolButton.setObjectName("import_RGB_List_toolButton") self.gridLayout_245.addWidget(self.import_RGB_List_toolButton, 5, 0, 1, 1) self.clear_RGB_list_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.clear_RGB_list_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_RGB_list_toolButton.setIcon(icon59) self.clear_RGB_list_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_RGB_list_toolButton.setObjectName("clear_RGB_list_toolButton") self.gridLayout_245.addWidget(self.clear_RGB_list_toolButton, 2, 0, 1, 1) self.remove_RGB_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.remove_RGB_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_RGB_toolButton.setIcon(icon58) self.remove_RGB_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_RGB_toolButton.setObjectName("remove_RGB_toolButton") self.gridLayout_245.addWidget(self.remove_RGB_toolButton, 1, 0, 1, 1) spacerItem3 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_245.addItem(spacerItem3, 3, 0, 1, 1) self.gridLayout_243.addLayout(self.gridLayout_245, 2, 1, 1, 1) self.RGB_tableWidget = QtWidgets.QTableWidget(self.tab_RGB) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.RGB_tableWidget.sizePolicy().hasHeightForWidth()) self.RGB_tableWidget.setSizePolicy(sizePolicy) self.RGB_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.DoubleClicked) self.RGB_tableWidget.setAlternatingRowColors(True) self.RGB_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.MultiSelection) self.RGB_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.RGB_tableWidget.setObjectName("RGB_tableWidget") self.RGB_tableWidget.setColumnCount(1) self.RGB_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.RGB_tableWidget.setHorizontalHeaderItem(0, item) self.RGB_tableWidget.horizontalHeader().setDefaultSectionSize(50) self.RGB_tableWidget.horizontalHeader().setStretchLastSection(True) self.RGB_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_243.addWidget(self.RGB_tableWidget, 1, 0, 2, 1) self.gridLayout_213.addLayout(self.gridLayout_243, 0, 0, 1, 1) self.gridLayout_246 = QtWidgets.QGridLayout() self.gridLayout_246.setObjectName("gridLayout_246") self.label_196 = QtWidgets.QLabel(self.tab_RGB) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_196.sizePolicy().hasHeightForWidth()) self.label_196.setSizePolicy(sizePolicy) self.label_196.setStyleSheet("background-color : #656565; color : white") self.label_196.setFrameShape(QtWidgets.QFrame.Panel) self.label_196.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_196.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_196.setObjectName("label_196") self.gridLayout_246.addWidget(self.label_196, 0, 0, 1, 2) self.horizontalLayout_27 = QtWidgets.QHBoxLayout() self.horizontalLayout_27.setObjectName("horizontalLayout_27") self.label_192 = QtWidgets.QLabel(self.tab_RGB) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_192.sizePolicy().hasHeightForWidth()) self.label_192.setSizePolicy(sizePolicy) self.label_192.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_192.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_192.setObjectName("label_192") self.horizontalLayout_27.addWidget(self.label_192) self.all_RGB_list_toolButton = QtWidgets.QToolButton(self.tab_RGB) self.all_RGB_list_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon67 = QtGui.QIcon() icon67.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_enter.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.all_RGB_list_toolButton.setIcon(icon67) self.all_RGB_list_toolButton.setIconSize(QtCore.QSize(22, 22)) self.all_RGB_list_toolButton.setObjectName("all_RGB_list_toolButton") self.horizontalLayout_27.addWidget(self.all_RGB_list_toolButton) spacerItem4 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_27.addItem(spacerItem4) self.gridLayout_246.addLayout(self.horizontalLayout_27, 1, 0, 1, 2) self.gridLayout_213.addLayout(self.gridLayout_246, 1, 0, 1, 1) self.tabWidget_5.addTab(self.tab_RGB, "") self.tab_band_set_list = QtWidgets.QWidget() self.tab_band_set_list.setObjectName("tab_band_set_list") self.gridLayout_197 = QtWidgets.QGridLayout(self.tab_band_set_list) self.gridLayout_197.setObjectName("gridLayout_197") self.gridLayout_267 = QtWidgets.QGridLayout() self.gridLayout_267.setObjectName("gridLayout_267") self.label_208 = QtWidgets.QLabel(self.tab_band_set_list) self.label_208.setStyleSheet("background-color : #656565; color : white") self.label_208.setFrameShape(QtWidgets.QFrame.Panel) self.label_208.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_208.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_208.setObjectName("label_208") self.gridLayout_267.addWidget(self.label_208, 0, 0, 1, 1) self.band_set_filter_lineEdit = QtWidgets.QLineEdit(self.tab_band_set_list) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.band_set_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.band_set_filter_lineEdit.setSizePolicy(sizePolicy) self.band_set_filter_lineEdit.setObjectName("band_set_filter_lineEdit") self.gridLayout_267.addWidget(self.band_set_filter_lineEdit, 0, 1, 1, 1) self.gridLayout_197.addLayout(self.gridLayout_267, 0, 0, 1, 1) self.band_set_list_tableWidget = QtWidgets.QTableWidget(self.tab_band_set_list) self.band_set_list_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.band_set_list_tableWidget.setAlternatingRowColors(True) self.band_set_list_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.MultiSelection) self.band_set_list_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.band_set_list_tableWidget.setObjectName("band_set_list_tableWidget") self.band_set_list_tableWidget.setColumnCount(3) self.band_set_list_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.band_set_list_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.band_set_list_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.band_set_list_tableWidget.setHorizontalHeaderItem(2, item) self.band_set_list_tableWidget.horizontalHeader().setDefaultSectionSize(68) self.band_set_list_tableWidget.horizontalHeader().setStretchLastSection(True) self.band_set_list_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_197.addWidget(self.band_set_list_tableWidget, 1, 0, 2, 1) self.verticalLayout_2 = QtWidgets.QVBoxLayout() self.verticalLayout_2.setObjectName("verticalLayout_2") self.move_down_toolButton_4 = QtWidgets.QToolButton(self.tab_band_set_list) self.move_down_toolButton_4.setStyleSheet("margin: 0px;padding: 0px;") self.move_down_toolButton_4.setIcon(icon62) self.move_down_toolButton_4.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton_4.setObjectName("move_down_toolButton_4") self.verticalLayout_2.addWidget(self.move_down_toolButton_4) self.move_up_toolButton_4 = QtWidgets.QToolButton(self.tab_band_set_list) self.move_up_toolButton_4.setStyleSheet("margin: 0px;padding: 0px;") self.move_up_toolButton_4.setIcon(icon61) self.move_up_toolButton_4.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton_4.setObjectName("move_up_toolButton_4") self.verticalLayout_2.addWidget(self.move_up_toolButton_4) spacerItem5 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.verticalLayout_2.addItem(spacerItem5) self.rgb_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.rgb_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.rgb_toolButton.setIcon(icon8) self.rgb_toolButton.setIconSize(QtCore.QSize(22, 22)) self.rgb_toolButton.setObjectName("rgb_toolButton") self.verticalLayout_2.addWidget(self.rgb_toolButton) self.gridLayout_197.addLayout(self.verticalLayout_2, 1, 1, 1, 1) self.gridLayout_269 = QtWidgets.QGridLayout() self.gridLayout_269.setObjectName("gridLayout_269") self.add_bandset_pushButton = QtWidgets.QToolButton(self.tab_band_set_list) self.add_bandset_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.add_bandset_pushButton.setIcon(icon66) self.add_bandset_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_bandset_pushButton.setObjectName("add_bandset_pushButton") self.gridLayout_269.addWidget(self.add_bandset_pushButton, 2, 0, 1, 1) self.export_bandset_List_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.export_bandset_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_bandset_List_toolButton.setIcon(icon53) self.export_bandset_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_bandset_List_toolButton.setObjectName("export_bandset_List_toolButton") self.gridLayout_269.addWidget(self.export_bandset_List_toolButton, 5, 0, 1, 1) self.import_bandset_List_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.import_bandset_List_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_bandset_List_toolButton.setIcon(icon54) self.import_bandset_List_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_bandset_List_toolButton.setObjectName("import_bandset_List_toolButton") self.gridLayout_269.addWidget(self.import_bandset_List_toolButton, 6, 0, 1, 1) spacerItem6 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_269.addItem(spacerItem6, 4, 0, 1, 1) self.remove_bandset_toolButton = QtWidgets.QToolButton(self.tab_band_set_list) self.remove_bandset_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_bandset_toolButton.setIcon(icon58) self.remove_bandset_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_bandset_toolButton.setObjectName("remove_bandset_toolButton") self.gridLayout_269.addWidget(self.remove_bandset_toolButton, 3, 0, 1, 1) spacerItem7 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_269.addItem(spacerItem7, 1, 0, 1, 1) self.sort_by_date = QtWidgets.QToolButton(self.tab_band_set_list) self.sort_by_date.setStyleSheet("margin: 0px;padding: 0px;") self.sort_by_date.setIcon(icon60) self.sort_by_date.setIconSize(QtCore.QSize(22, 22)) self.sort_by_date.setObjectName("sort_by_date") self.gridLayout_269.addWidget(self.sort_by_date, 0, 0, 1, 1) self.gridLayout_197.addLayout(self.gridLayout_269, 2, 1, 1, 1) self.tabWidget_5.addTab(self.tab_band_set_list, "") self.tab_algorithm_weight = QtWidgets.QWidget() self.tab_algorithm_weight.setObjectName("tab_algorithm_weight") self.gridLayout_150 = QtWidgets.QGridLayout(self.tab_algorithm_weight) self.gridLayout_150.setObjectName("gridLayout_150") self.gridLayout_100 = QtWidgets.QGridLayout() self.gridLayout_100.setObjectName("gridLayout_100") self.gridLayout_108 = QtWidgets.QGridLayout() self.gridLayout_108.setObjectName("gridLayout_108") self.label_79 = QtWidgets.QLabel(self.tab_algorithm_weight) self.label_79.setStyleSheet("background-color : #656565; color : white") self.label_79.setFrameShape(QtWidgets.QFrame.Panel) self.label_79.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_79.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_79.setObjectName("label_79") self.gridLayout_108.addWidget(self.label_79, 0, 0, 1, 1) self.gridLayout_100.addLayout(self.gridLayout_108, 0, 0, 1, 2) self.gridLayout_101 = QtWidgets.QGridLayout() self.gridLayout_101.setObjectName("gridLayout_101") spacerItem8 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_101.addItem(spacerItem8, 6, 1, 1, 1) self.gridLayout_104 = QtWidgets.QGridLayout() self.gridLayout_104.setObjectName("gridLayout_104") self.gridLayout_102 = QtWidgets.QGridLayout() self.gridLayout_102.setObjectName("gridLayout_102") self.reset_weights_pushButton = QtWidgets.QToolButton(self.tab_algorithm_weight) self.reset_weights_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.reset_weights_pushButton.setIcon(icon59) self.reset_weights_pushButton.setIconSize(QtCore.QSize(22, 22)) self.reset_weights_pushButton.setObjectName("reset_weights_pushButton") self.gridLayout_102.addWidget(self.reset_weights_pushButton, 0, 0, 1, 1) self.gridLayout_104.addLayout(self.gridLayout_102, 0, 0, 1, 1) self.gridLayout_101.addLayout(self.gridLayout_104, 5, 0, 1, 3) spacerItem9 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_101.addItem(spacerItem9, 3, 1, 1, 1) self.gridLayout_100.addLayout(self.gridLayout_101, 1, 1, 1, 1) self.gridLayout_103 = QtWidgets.QGridLayout() self.gridLayout_103.setObjectName("gridLayout_103") self.set_weight_value_pushButton = QtWidgets.QToolButton(self.tab_algorithm_weight) self.set_weight_value_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.set_weight_value_pushButton.setIcon(icon67) self.set_weight_value_pushButton.setIconSize(QtCore.QSize(22, 22)) self.set_weight_value_pushButton.setObjectName("set_weight_value_pushButton") self.gridLayout_103.addWidget(self.set_weight_value_pushButton, 1, 2, 1, 1) self.label_131 = QtWidgets.QLabel(self.tab_algorithm_weight) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_131.sizePolicy().hasHeightForWidth()) self.label_131.setSizePolicy(sizePolicy) self.label_131.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_131.setObjectName("label_131") self.gridLayout_103.addWidget(self.label_131, 1, 0, 1, 1) self.weight_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.tab_algorithm_weight) self.weight_doubleSpinBox.setMaximum(1000.0) self.weight_doubleSpinBox.setProperty("value", 1.0) self.weight_doubleSpinBox.setObjectName("weight_doubleSpinBox") self.gridLayout_103.addWidget(self.weight_doubleSpinBox, 1, 1, 1, 1) spacerItem10 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_103.addItem(spacerItem10, 1, 3, 1, 1) self.label_93 = QtWidgets.QLabel(self.tab_algorithm_weight) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_93.sizePolicy().hasHeightForWidth()) self.label_93.setSizePolicy(sizePolicy) self.label_93.setStyleSheet("background-color : #656565; color : white") self.label_93.setFrameShape(QtWidgets.QFrame.Panel) self.label_93.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_93.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_93.setObjectName("label_93") self.gridLayout_103.addWidget(self.label_93, 0, 0, 1, 4) self.gridLayout_100.addLayout(self.gridLayout_103, 2, 0, 1, 2) self.alg_band_weight_tabWidget = QtWidgets.QTabWidget(self.tab_algorithm_weight) self.alg_band_weight_tabWidget.setTabPosition(QtWidgets.QTabWidget.North) self.alg_band_weight_tabWidget.setObjectName("alg_band_weight_tabWidget") self.gridLayout_100.addWidget(self.alg_band_weight_tabWidget, 1, 0, 1, 1) self.gridLayout_150.addLayout(self.gridLayout_100, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_algorithm_weight, "") self.tab_multiple_ROI = QtWidgets.QWidget() self.tab_multiple_ROI.setObjectName("tab_multiple_ROI") self.gridLayout_247 = QtWidgets.QGridLayout(self.tab_multiple_ROI) self.gridLayout_247.setObjectName("gridLayout_247") self.gridLayout_8 = QtWidgets.QGridLayout() self.gridLayout_8.setObjectName("gridLayout_8") self.point_distance_spinBox = QtWidgets.QSpinBox(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.point_distance_spinBox.sizePolicy().hasHeightForWidth()) self.point_distance_spinBox.setSizePolicy(sizePolicy) self.point_distance_spinBox.setMinimumSize(QtCore.QSize(40, 0)) self.point_distance_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.point_distance_spinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.point_distance_spinBox.setMinimum(1) self.point_distance_spinBox.setMaximum(999999999) self.point_distance_spinBox.setProperty("value", 100) self.point_distance_spinBox.setObjectName("point_distance_spinBox") self.gridLayout_8.addWidget(self.point_distance_spinBox, 1, 5, 1, 1) self.point_grid_spinBox = QtWidgets.QSpinBox(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.point_grid_spinBox.sizePolicy().hasHeightForWidth()) self.point_grid_spinBox.setSizePolicy(sizePolicy) self.point_grid_spinBox.setMinimumSize(QtCore.QSize(40, 0)) self.point_grid_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.point_grid_spinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.point_grid_spinBox.setMinimum(1) self.point_grid_spinBox.setMaximum(999999999) self.point_grid_spinBox.setProperty("value", 10000) self.point_grid_spinBox.setObjectName("point_grid_spinBox") self.gridLayout_8.addWidget(self.point_grid_spinBox, 1, 3, 1, 1) self.label_48 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_48.setStyleSheet("background-color : #656565; color : white") self.label_48.setFrameShape(QtWidgets.QFrame.Panel) self.label_48.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_48.setObjectName("label_48") self.gridLayout_8.addWidget(self.label_48, 0, 0, 1, 9) self.label_139 = QtWidgets.QLabel(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_139.sizePolicy().hasHeightForWidth()) self.label_139.setSizePolicy(sizePolicy) self.label_139.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_139.setObjectName("label_139") self.gridLayout_8.addWidget(self.label_139, 1, 7, 1, 1) self.label_19 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_19.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_19.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_19.setObjectName("label_19") self.gridLayout_8.addWidget(self.label_19, 1, 0, 1, 1) self.point_number_spinBox = QtWidgets.QSpinBox(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.point_number_spinBox.sizePolicy().hasHeightForWidth()) self.point_number_spinBox.setSizePolicy(sizePolicy) self.point_number_spinBox.setMinimumSize(QtCore.QSize(40, 0)) self.point_number_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.point_number_spinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.point_number_spinBox.setMinimum(1) self.point_number_spinBox.setMaximum(999999999) self.point_number_spinBox.setProperty("value", 100) self.point_number_spinBox.setObjectName("point_number_spinBox") self.gridLayout_8.addWidget(self.point_number_spinBox, 1, 1, 1, 1) self.add_random_point_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.add_random_point_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.add_random_point_pushButton.setIcon(icon67) self.add_random_point_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_random_point_pushButton.setObjectName("add_random_point_pushButton") self.gridLayout_8.addWidget(self.add_random_point_pushButton, 1, 8, 1, 1) self.point_distance_checkBox = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.point_distance_checkBox.setObjectName("point_distance_checkBox") self.gridLayout_8.addWidget(self.point_distance_checkBox, 1, 4, 1, 1) self.point_grid_checkBox = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.point_grid_checkBox.setObjectName("point_grid_checkBox") self.gridLayout_8.addWidget(self.point_grid_checkBox, 1, 2, 1, 1) spacerItem11 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_8.addItem(spacerItem11, 1, 6, 1, 1) self.stratified_point_checkBox = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.stratified_point_checkBox.setObjectName("stratified_point_checkBox") self.gridLayout_8.addWidget(self.stratified_point_checkBox, 2, 0, 1, 2) self.stratified_lineEdit = QtWidgets.QLineEdit(self.tab_multiple_ROI) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.stratified_lineEdit.sizePolicy().hasHeightForWidth()) self.stratified_lineEdit.setSizePolicy(sizePolicy) self.stratified_lineEdit.setMinimumSize(QtCore.QSize(400, 0)) self.stratified_lineEdit.setMaxLength(10000) self.stratified_lineEdit.setObjectName("stratified_lineEdit") self.gridLayout_8.addWidget(self.stratified_lineEdit, 2, 2, 1, 4) self.band_set_comb_spinBox_10 = QtWidgets.QSpinBox(self.tab_multiple_ROI) self.band_set_comb_spinBox_10.setMinimum(1) self.band_set_comb_spinBox_10.setMaximum(100000) self.band_set_comb_spinBox_10.setObjectName("band_set_comb_spinBox_10") self.gridLayout_8.addWidget(self.band_set_comb_spinBox_10, 2, 8, 1, 1) self.label_25 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_25.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_25.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_25.setObjectName("label_25") self.gridLayout_8.addWidget(self.label_25, 2, 6, 1, 2) self.gridLayout_247.addLayout(self.gridLayout_8, 0, 0, 1, 1) self.gridLayout_32 = QtWidgets.QGridLayout() self.gridLayout_32.setObjectName("gridLayout_32") self.label_47 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_47.setStyleSheet("background-color : #656565; color : white") self.label_47.setFrameShape(QtWidgets.QFrame.Panel) self.label_47.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_47.setObjectName("label_47") self.gridLayout_32.addWidget(self.label_47, 0, 0, 1, 2) self.point_tableWidget = QtWidgets.QTableWidget(self.tab_multiple_ROI) self.point_tableWidget.setAlternatingRowColors(True) self.point_tableWidget.setObjectName("point_tableWidget") self.point_tableWidget.setColumnCount(10) self.point_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(6, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(7, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(8, item) item = QtWidgets.QTableWidgetItem() self.point_tableWidget.setHorizontalHeaderItem(9, item) self.point_tableWidget.horizontalHeader().setDefaultSectionSize(90) self.point_tableWidget.verticalHeader().setDefaultSectionSize(24) self.gridLayout_32.addWidget(self.point_tableWidget, 1, 0, 1, 1) self.gridLayout_72 = QtWidgets.QGridLayout() self.gridLayout_72.setObjectName("gridLayout_72") self.gridLayout_39 = QtWidgets.QGridLayout() self.gridLayout_39.setObjectName("gridLayout_39") spacerItem12 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_39.addItem(spacerItem12, 3, 0, 1, 1) self.add_point_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.add_point_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.add_point_pushButton.setIcon(icon66) self.add_point_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_point_pushButton.setObjectName("add_point_pushButton") self.gridLayout_39.addWidget(self.add_point_pushButton, 1, 0, 1, 1) self.remove_point_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.remove_point_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_point_pushButton.setIcon(icon58) self.remove_point_pushButton.setIconSize(QtCore.QSize(22, 22)) self.remove_point_pushButton.setObjectName("remove_point_pushButton") self.gridLayout_39.addWidget(self.remove_point_pushButton, 2, 0, 1, 1) self.export_point_list_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.export_point_list_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.export_point_list_pushButton.setIcon(icon53) self.export_point_list_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_point_list_pushButton.setObjectName("export_point_list_pushButton") self.gridLayout_39.addWidget(self.export_point_list_pushButton, 5, 0, 1, 1) spacerItem13 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_39.addItem(spacerItem13, 6, 0, 1, 1) self.import_point_list_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) self.import_point_list_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.import_point_list_pushButton.setIcon(icon54) self.import_point_list_pushButton.setIconSize(QtCore.QSize(22, 22)) self.import_point_list_pushButton.setObjectName("import_point_list_pushButton") self.gridLayout_39.addWidget(self.import_point_list_pushButton, 4, 0, 1, 1) spacerItem14 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_39.addItem(spacerItem14, 0, 0, 1, 1) self.gridLayout_72.addLayout(self.gridLayout_39, 2, 0, 1, 1) self.gridLayout_32.addLayout(self.gridLayout_72, 1, 1, 1, 1) self.gridLayout_73 = QtWidgets.QGridLayout() self.gridLayout_73.setObjectName("gridLayout_73") spacerItem15 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_73.addItem(spacerItem15, 1, 4, 1, 1) self.signature_checkBox2 = QtWidgets.QCheckBox(self.tab_multiple_ROI) self.signature_checkBox2.setChecked(True) self.signature_checkBox2.setObjectName("signature_checkBox2") self.gridLayout_73.addWidget(self.signature_checkBox2, 1, 5, 1, 1) self.label_159 = QtWidgets.QLabel(self.tab_multiple_ROI) self.label_159.setStyleSheet("background-color : #656565; color : white") self.label_159.setFrameShape(QtWidgets.QFrame.Panel) self.label_159.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_159.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_159.setObjectName("label_159") self.gridLayout_73.addWidget(self.label_159, 0, 4, 1, 3) self.save_point_rois_pushButton = QtWidgets.QToolButton(self.tab_multiple_ROI) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.save_point_rois_pushButton.setFont(font) self.save_point_rois_pushButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.save_point_rois_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.save_point_rois_pushButton.setIcon(icon64) self.save_point_rois_pushButton.setIconSize(QtCore.QSize(34, 34)) self.save_point_rois_pushButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.save_point_rois_pushButton.setObjectName("save_point_rois_pushButton") self.gridLayout_73.addWidget(self.save_point_rois_pushButton, 1, 6, 1, 1) self.gridLayout_32.addLayout(self.gridLayout_73, 3, 0, 1, 2) self.gridLayout_247.addLayout(self.gridLayout_32, 1, 0, 1, 1) self.tabWidget_5.addTab(self.tab_multiple_ROI, "") self.tab_Import = QtWidgets.QWidget() self.tab_Import.setObjectName("tab_Import") self.gridLayout_168 = QtWidgets.QGridLayout(self.tab_Import) self.gridLayout_168.setObjectName("gridLayout_168") self.toolBox_4 = QtWidgets.QToolBox(self.tab_Import) self.toolBox_4.setObjectName("toolBox_4") self.page_8 = QtWidgets.QWidget() self.page_8.setGeometry(QtCore.QRect(0, 0, 357, 448)) self.page_8.setObjectName("page_8") self.gridLayout_4 = QtWidgets.QGridLayout(self.page_8) self.gridLayout_4.setObjectName("gridLayout_4") self.gridLayout_31 = QtWidgets.QGridLayout() self.gridLayout_31.setObjectName("gridLayout_31") self.usgs_chapter_comboBox = QtWidgets.QComboBox(self.page_8) self.usgs_chapter_comboBox.setObjectName("usgs_chapter_comboBox") self.gridLayout_31.addWidget(self.usgs_chapter_comboBox, 0, 1, 1, 1) self.usgs_library_comboBox = QtWidgets.QComboBox(self.page_8) self.usgs_library_comboBox.setObjectName("usgs_library_comboBox") self.gridLayout_31.addWidget(self.usgs_library_comboBox, 1, 1, 1, 1) self.gridLayout_14 = QtWidgets.QGridLayout() self.gridLayout_14.setObjectName("gridLayout_14") self.gridLayout_31.addLayout(self.gridLayout_14, 2, 1, 1, 1) self.label_123 = QtWidgets.QLabel(self.page_8) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_123.sizePolicy().hasHeightForWidth()) self.label_123.setSizePolicy(sizePolicy) self.label_123.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_123.setObjectName("label_123") self.gridLayout_31.addWidget(self.label_123, 0, 0, 1, 1) self.label_124 = QtWidgets.QLabel(self.page_8) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_124.sizePolicy().hasHeightForWidth()) self.label_124.setSizePolicy(sizePolicy) self.label_124.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_124.setObjectName("label_124") self.gridLayout_31.addWidget(self.label_124, 1, 0, 1, 1) self.gridLayout_12 = QtWidgets.QGridLayout() self.gridLayout_12.setObjectName("gridLayout_12") spacerItem16 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_12.addItem(spacerItem16, 0, 0, 1, 1) self.label_130 = QtWidgets.QLabel(self.page_8) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_130.sizePolicy().hasHeightForWidth()) self.label_130.setSizePolicy(sizePolicy) self.label_130.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_130.setObjectName("label_130") self.gridLayout_12.addWidget(self.label_130, 0, 1, 1, 1) self.add_usgs_library_pushButton = QtWidgets.QToolButton(self.page_8) self.add_usgs_library_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.add_usgs_library_pushButton.setIcon(icon67) self.add_usgs_library_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_usgs_library_pushButton.setObjectName("add_usgs_library_pushButton") self.gridLayout_12.addWidget(self.add_usgs_library_pushButton, 0, 2, 1, 1) self.gridLayout_31.addLayout(self.gridLayout_12, 3, 0, 1, 2) self.USGS_library_textBrowser = QtWidgets.QTextBrowser(self.page_8) self.USGS_library_textBrowser.setFrameShape(QtWidgets.QFrame.Panel) self.USGS_library_textBrowser.setFrameShadow(QtWidgets.QFrame.Sunken) self.USGS_library_textBrowser.setOpenExternalLinks(True) self.USGS_library_textBrowser.setObjectName("USGS_library_textBrowser") self.gridLayout_31.addWidget(self.USGS_library_textBrowser, 5, 0, 1, 2) self.label = QtWidgets.QLabel(self.page_8) font = QtGui.QFont() font.setPointSize(8) self.label.setFont(font) self.label.setFrameShape(QtWidgets.QFrame.Panel) self.label.setFrameShadow(QtWidgets.QFrame.Sunken) self.label.setWordWrap(True) self.label.setOpenExternalLinks(True) self.label.setObjectName("label") self.gridLayout_31.addWidget(self.label, 6, 0, 1, 2) self.label_129 = QtWidgets.QLabel(self.page_8) self.label_129.setStyleSheet("background-color : #656565; color : white") self.label_129.setFrameShape(QtWidgets.QFrame.Panel) self.label_129.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_129.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_129.setObjectName("label_129") self.gridLayout_31.addWidget(self.label_129, 4, 0, 1, 2) self.gridLayout_4.addLayout(self.gridLayout_31, 0, 1, 1, 1) self.toolBox_4.addItem(self.page_8, "") self.page_6 = QtWidgets.QWidget() self.page_6.setGeometry(QtCore.QRect(0, 0, 604, 53)) self.page_6.setObjectName("page_6") self.gridLayout_175 = QtWidgets.QGridLayout(self.page_6) self.gridLayout_175.setObjectName("gridLayout_175") self.gridLayout_174 = QtWidgets.QGridLayout() self.gridLayout_174.setObjectName("gridLayout_174") self.label_9 = QtWidgets.QLabel(self.page_6) self.label_9.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_9.setObjectName("label_9") self.gridLayout_174.addWidget(self.label_9, 0, 0, 1, 1) self.open_library_pushButton = QtWidgets.QToolButton(self.page_6) self.open_library_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.open_library_pushButton.setIcon(icon65) self.open_library_pushButton.setIconSize(QtCore.QSize(22, 22)) self.open_library_pushButton.setObjectName("open_library_pushButton") self.gridLayout_174.addWidget(self.open_library_pushButton, 0, 1, 1, 1) spacerItem17 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_174.addItem(spacerItem17, 2, 0, 1, 1) self.gridLayout_175.addLayout(self.gridLayout_174, 0, 0, 1, 1) self.toolBox_4.addItem(self.page_6, "") self.page_9 = QtWidgets.QWidget() self.page_9.setGeometry(QtCore.QRect(0, 0, 417, 165)) self.page_9.setObjectName("page_9") self.gridLayout_181 = QtWidgets.QGridLayout(self.page_9) self.gridLayout_181.setObjectName("gridLayout_181") self.gridLayout_178 = QtWidgets.QGridLayout() self.gridLayout_178.setObjectName("gridLayout_178") self.open_shapefile_pushButton = QtWidgets.QToolButton(self.page_9) self.open_shapefile_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.open_shapefile_pushButton.setIcon(icon65) self.open_shapefile_pushButton.setIconSize(QtCore.QSize(20, 20)) self.open_shapefile_pushButton.setObjectName("open_shapefile_pushButton") self.gridLayout_178.addWidget(self.open_shapefile_pushButton, 0, 2, 1, 1) self.label_120 = QtWidgets.QLabel(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_120.sizePolicy().hasHeightForWidth()) self.label_120.setSizePolicy(sizePolicy) self.label_120.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_120.setObjectName("label_120") self.gridLayout_178.addWidget(self.label_120, 0, 0, 1, 1) self.gridLayout_179 = QtWidgets.QGridLayout() self.gridLayout_179.setObjectName("gridLayout_179") self.C_ID_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.C_ID_combo.sizePolicy().hasHeightForWidth()) self.C_ID_combo.setSizePolicy(sizePolicy) self.C_ID_combo.setObjectName("C_ID_combo") self.gridLayout_179.addWidget(self.C_ID_combo, 2, 2, 1, 1) self.MC_ID_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.MC_ID_combo.sizePolicy().hasHeightForWidth()) self.MC_ID_combo.setSizePolicy(sizePolicy) self.MC_ID_combo.setObjectName("MC_ID_combo") self.gridLayout_179.addWidget(self.MC_ID_combo, 2, 0, 1, 1) self.MC_Info_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.MC_Info_combo.sizePolicy().hasHeightForWidth()) self.MC_Info_combo.setSizePolicy(sizePolicy) self.MC_Info_combo.setObjectName("MC_Info_combo") self.gridLayout_179.addWidget(self.MC_Info_combo, 2, 1, 1, 1) self.label_99 = QtWidgets.QLabel(self.page_9) self.label_99.setFrameShape(QtWidgets.QFrame.Panel) self.label_99.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_99.setObjectName("label_99") self.gridLayout_179.addWidget(self.label_99, 1, 3, 1, 1) self.C_Info_combo = QtWidgets.QComboBox(self.page_9) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.C_Info_combo.sizePolicy().hasHeightForWidth()) self.C_Info_combo.setSizePolicy(sizePolicy) self.C_Info_combo.setObjectName("C_Info_combo") self.gridLayout_179.addWidget(self.C_Info_combo, 2, 3, 1, 1) self.label_119 = QtWidgets.QLabel(self.page_9) self.label_119.setStyleSheet("background-color : #656565; color : white") self.label_119.setFrameShape(QtWidgets.QFrame.Panel) self.label_119.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_119.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_119.setObjectName("label_119") self.gridLayout_179.addWidget(self.label_119, 0, 0, 1, 5) self.MC_ID_combo_2 = QtWidgets.QLabel(self.page_9) self.MC_ID_combo_2.setFrameShape(QtWidgets.QFrame.Panel) self.MC_ID_combo_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.MC_ID_combo_2.setObjectName("MC_ID_combo_2") self.gridLayout_179.addWidget(self.MC_ID_combo_2, 1, 2, 1, 1) self.label_121 = QtWidgets.QLabel(self.page_9) self.label_121.setFrameShape(QtWidgets.QFrame.Panel) self.label_121.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_121.setObjectName("label_121") self.gridLayout_179.addWidget(self.label_121, 1, 0, 1, 1) self.label_122 = QtWidgets.QLabel(self.page_9) self.label_122.setFrameShape(QtWidgets.QFrame.Panel) self.label_122.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_122.setObjectName("label_122") self.gridLayout_179.addWidget(self.label_122, 1, 1, 1, 1) self.gridLayout_178.addLayout(self.gridLayout_179, 3, 0, 1, 3) spacerItem18 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_178.addItem(spacerItem18, 5, 0, 1, 1) self.gridLayout_180 = QtWidgets.QGridLayout() self.gridLayout_180.setObjectName("gridLayout_180") self.label_2 = QtWidgets.QLabel(self.page_9) self.label_2.setObjectName("label_2") self.gridLayout_180.addWidget(self.label_2, 0, 2, 1, 1) spacerItem19 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_180.addItem(spacerItem19, 0, 0, 1, 1) self.signature_checkBox_2 = QtWidgets.QCheckBox(self.page_9) self.signature_checkBox_2.setChecked(True) self.signature_checkBox_2.setObjectName("signature_checkBox_2") self.gridLayout_180.addWidget(self.signature_checkBox_2, 0, 1, 1, 1) self.import_shapefile_pushButton = QtWidgets.QToolButton(self.page_9) self.import_shapefile_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.import_shapefile_pushButton.setIcon(icon67) self.import_shapefile_pushButton.setIconSize(QtCore.QSize(22, 22)) self.import_shapefile_pushButton.setObjectName("import_shapefile_pushButton") self.gridLayout_180.addWidget(self.import_shapefile_pushButton, 0, 3, 1, 1) self.gridLayout_178.addLayout(self.gridLayout_180, 4, 0, 1, 3) self.select_shapefile_label = QtWidgets.QLabel(self.page_9) self.select_shapefile_label.setFrameShape(QtWidgets.QFrame.Panel) self.select_shapefile_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.select_shapefile_label.setText("") self.select_shapefile_label.setObjectName("select_shapefile_label") self.gridLayout_178.addWidget(self.select_shapefile_label, 0, 1, 1, 1) self.gridLayout_181.addLayout(self.gridLayout_178, 0, 1, 1, 1) self.toolBox_4.addItem(self.page_9, "") self.gridLayout_168.addWidget(self.toolBox_4, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_Import, "") self.tab_export = QtWidgets.QWidget() self.tab_export.setObjectName("tab_export") self.gridLayout_142 = QtWidgets.QGridLayout(self.tab_export) self.gridLayout_142.setObjectName("gridLayout_142") self.gridLayout_176 = QtWidgets.QGridLayout() self.gridLayout_176.setObjectName("gridLayout_176") self.label_97 = QtWidgets.QLabel(self.tab_export) self.label_97.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_97.setObjectName("label_97") self.gridLayout_176.addWidget(self.label_97, 1, 0, 1, 1) self.export_SCP_pushButton = QtWidgets.QToolButton(self.tab_export) self.export_SCP_pushButton.setStyleSheet("margin: 0px;padding: 0px;") icon68 = QtGui.QIcon() icon68.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_new_file.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.export_SCP_pushButton.setIcon(icon68) self.export_SCP_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_SCP_pushButton.setObjectName("export_SCP_pushButton") self.gridLayout_176.addWidget(self.export_SCP_pushButton, 1, 1, 1, 1) self.export_CSV_library_toolButton = QtWidgets.QToolButton(self.tab_export) self.export_CSV_library_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon69 = QtGui.QIcon() icon69.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_open_dir.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.export_CSV_library_toolButton.setIcon(icon69) self.export_CSV_library_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_CSV_library_toolButton.setObjectName("export_CSV_library_toolButton") self.gridLayout_176.addWidget(self.export_CSV_library_toolButton, 3, 1, 1, 1) self.label_96 = QtWidgets.QLabel(self.tab_export) self.label_96.setStyleSheet("background-color : #656565; color : white") self.label_96.setFrameShape(QtWidgets.QFrame.Panel) self.label_96.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_96.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_96.setObjectName("label_96") self.gridLayout_176.addWidget(self.label_96, 0, 0, 1, 2) self.label_222 = QtWidgets.QLabel(self.tab_export) self.label_222.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_222.setObjectName("label_222") self.gridLayout_176.addWidget(self.label_222, 2, 0, 1, 1) self.label_20 = QtWidgets.QLabel(self.tab_export) self.label_20.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_20.setObjectName("label_20") self.gridLayout_176.addWidget(self.label_20, 3, 0, 1, 1) self.export_SHP_pushButton = QtWidgets.QToolButton(self.tab_export) self.export_SHP_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.export_SHP_pushButton.setIcon(icon68) self.export_SHP_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_SHP_pushButton.setObjectName("export_SHP_pushButton") self.gridLayout_176.addWidget(self.export_SHP_pushButton, 2, 1, 1, 1) spacerItem20 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_176.addItem(spacerItem20, 4, 0, 1, 1) self.gridLayout_142.addLayout(self.gridLayout_176, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_export, "") self.tab_threshold = QtWidgets.QWidget() self.tab_threshold.setObjectName("tab_threshold") self.gridLayout_177 = QtWidgets.QGridLayout(self.tab_threshold) self.gridLayout_177.setObjectName("gridLayout_177") self.gridLayout_110 = QtWidgets.QGridLayout() self.gridLayout_110.setObjectName("gridLayout_110") self.gridLayout_161 = QtWidgets.QGridLayout() self.gridLayout_161.setObjectName("gridLayout_161") self.gridLayout_198 = QtWidgets.QGridLayout() self.gridLayout_198.setObjectName("gridLayout_198") spacerItem21 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_198.addItem(spacerItem21, 0, 0, 1, 1) self.gridLayout_161.addLayout(self.gridLayout_198, 0, 0, 1, 1) spacerItem22 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_161.addItem(spacerItem22, 3, 0, 1, 1) self.gridLayout_129 = QtWidgets.QGridLayout() self.gridLayout_129.setObjectName("gridLayout_129") self.reset_threshold_pushButton = QtWidgets.QToolButton(self.tab_threshold) self.reset_threshold_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.reset_threshold_pushButton.setIcon(icon59) self.reset_threshold_pushButton.setIconSize(QtCore.QSize(22, 22)) self.reset_threshold_pushButton.setObjectName("reset_threshold_pushButton") self.gridLayout_129.addWidget(self.reset_threshold_pushButton, 0, 0, 1, 1) self.gridLayout_161.addLayout(self.gridLayout_129, 1, 0, 1, 1) self.gridLayout_110.addLayout(self.gridLayout_161, 1, 1, 1, 1) self.signature_threshold_tableWidget = QtWidgets.QTableWidget(self.tab_threshold) self.signature_threshold_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.ExtendedSelection) self.signature_threshold_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectItems) self.signature_threshold_tableWidget.setObjectName("signature_threshold_tableWidget") self.signature_threshold_tableWidget.setColumnCount(7) self.signature_threshold_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.signature_threshold_tableWidget.setHorizontalHeaderItem(6, item) self.signature_threshold_tableWidget.horizontalHeader().setDefaultSectionSize(50) self.signature_threshold_tableWidget.horizontalHeader().setStretchLastSection(True) self.signature_threshold_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_110.addWidget(self.signature_threshold_tableWidget, 1, 0, 1, 1) self.gridLayout_109 = QtWidgets.QGridLayout() self.gridLayout_109.setObjectName("gridLayout_109") self.label_80 = QtWidgets.QLabel(self.tab_threshold) self.label_80.setStyleSheet("background-color : #656565; color : white") self.label_80.setFrameShape(QtWidgets.QFrame.Panel) self.label_80.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_80.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_80.setObjectName("label_80") self.gridLayout_109.addWidget(self.label_80, 0, 0, 1, 1) self.gridLayout_110.addLayout(self.gridLayout_109, 0, 0, 1, 2) self.gridLayout_111 = QtWidgets.QGridLayout() self.gridLayout_111.setObjectName("gridLayout_111") self.label_85 = QtWidgets.QLabel(self.tab_threshold) self.label_85.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_85.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_85.setObjectName("label_85") self.gridLayout_111.addWidget(self.label_85, 1, 2, 1, 1) self.multiplicative_threshold_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.tab_threshold) self.multiplicative_threshold_doubleSpinBox.setDecimals(1) self.multiplicative_threshold_doubleSpinBox.setMaximum(10000.0) self.multiplicative_threshold_doubleSpinBox.setProperty("value", 1.0) self.multiplicative_threshold_doubleSpinBox.setObjectName("multiplicative_threshold_doubleSpinBox") self.gridLayout_111.addWidget(self.multiplicative_threshold_doubleSpinBox, 1, 3, 1, 1) self.automatic_threshold_pushButton = QtWidgets.QToolButton(self.tab_threshold) self.automatic_threshold_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.automatic_threshold_pushButton.setIcon(icon67) self.automatic_threshold_pushButton.setIconSize(QtCore.QSize(22, 22)) self.automatic_threshold_pushButton.setObjectName("automatic_threshold_pushButton") self.gridLayout_111.addWidget(self.automatic_threshold_pushButton, 1, 4, 1, 1) self.horizontalLayout_3 = QtWidgets.QHBoxLayout() self.horizontalLayout_3.setObjectName("horizontalLayout_3") self.label_132 = QtWidgets.QLabel(self.tab_threshold) self.label_132.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_132.setObjectName("label_132") self.horizontalLayout_3.addWidget(self.label_132) self.threshold_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.tab_threshold) self.threshold_doubleSpinBox.setDecimals(4) self.threshold_doubleSpinBox.setMaximum(10000.0) self.threshold_doubleSpinBox.setProperty("value", 0.0) self.threshold_doubleSpinBox.setObjectName("threshold_doubleSpinBox") self.horizontalLayout_3.addWidget(self.threshold_doubleSpinBox) self.set_threshold_value_pushButton = QtWidgets.QToolButton(self.tab_threshold) self.set_threshold_value_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.set_threshold_value_pushButton.setIcon(icon67) self.set_threshold_value_pushButton.setIconSize(QtCore.QSize(22, 22)) self.set_threshold_value_pushButton.setObjectName("set_threshold_value_pushButton") self.horizontalLayout_3.addWidget(self.set_threshold_value_pushButton) self.gridLayout_111.addLayout(self.horizontalLayout_3, 1, 0, 1, 1) spacerItem23 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_111.addItem(spacerItem23, 1, 1, 1, 1) spacerItem24 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_111.addItem(spacerItem24, 1, 5, 1, 1) self.label_88 = QtWidgets.QLabel(self.tab_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_88.sizePolicy().hasHeightForWidth()) self.label_88.setSizePolicy(sizePolicy) self.label_88.setStyleSheet("background-color : #656565; color : white") self.label_88.setFrameShape(QtWidgets.QFrame.Panel) self.label_88.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_88.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_88.setObjectName("label_88") self.gridLayout_111.addWidget(self.label_88, 0, 0, 1, 6) self.gridLayout_110.addLayout(self.gridLayout_111, 2, 0, 1, 2) self.gridLayout_177.addLayout(self.gridLayout_110, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_threshold, "") self.tab_LCS_threshold = QtWidgets.QWidget() self.tab_LCS_threshold.setObjectName("tab_LCS_threshold") self.gridLayout_105 = QtWidgets.QGridLayout(self.tab_LCS_threshold) self.gridLayout_105.setObjectName("gridLayout_105") self.gridLayout_137 = QtWidgets.QGridLayout() self.gridLayout_137.setObjectName("gridLayout_137") self.LCS_tableWidget = QtWidgets.QTableWidget(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.LCS_tableWidget.sizePolicy().hasHeightForWidth()) self.LCS_tableWidget.setSizePolicy(sizePolicy) self.LCS_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.SelectedClicked) self.LCS_tableWidget.setAlternatingRowColors(True) self.LCS_tableWidget.setObjectName("LCS_tableWidget") self.LCS_tableWidget.setColumnCount(5) self.LCS_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.LCS_tableWidget.setHorizontalHeaderItem(4, item) self.LCS_tableWidget.horizontalHeader().setDefaultSectionSize(50) self.LCS_tableWidget.horizontalHeader().setStretchLastSection(True) self.LCS_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_137.addWidget(self.LCS_tableWidget, 1, 0, 1, 1) self.gridLayout_138 = QtWidgets.QGridLayout() self.gridLayout_138.setObjectName("gridLayout_138") self.label_86 = QtWidgets.QLabel(self.tab_LCS_threshold) self.label_86.setStyleSheet("background-color : #656565; color : white") self.label_86.setFrameShape(QtWidgets.QFrame.Panel) self.label_86.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_86.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_86.setObjectName("label_86") self.gridLayout_138.addWidget(self.label_86, 0, 0, 1, 1) self.gridLayout_137.addLayout(self.gridLayout_138, 0, 0, 1, 2) self.verticalLayout = QtWidgets.QVBoxLayout() self.verticalLayout.setObjectName("verticalLayout") self.signature_spectral_plot_toolButton_2 = QtWidgets.QToolButton(self.tab_LCS_threshold) self.signature_spectral_plot_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") icon70 = QtGui.QIcon() icon70.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_sign_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.signature_spectral_plot_toolButton_2.setIcon(icon70) self.signature_spectral_plot_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.signature_spectral_plot_toolButton_2.setObjectName("signature_spectral_plot_toolButton_2") self.verticalLayout.addWidget(self.signature_spectral_plot_toolButton_2) self.gridLayout_137.addLayout(self.verticalLayout, 1, 1, 1, 1) self.gridLayout_139 = QtWidgets.QGridLayout() self.gridLayout_139.setObjectName("gridLayout_139") self.horizontalLayout = QtWidgets.QHBoxLayout() self.horizontalLayout.setObjectName("horizontalLayout") self.label_102 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_102.sizePolicy().hasHeightForWidth()) self.label_102.setSizePolicy(sizePolicy) self.label_102.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_102.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_102.setObjectName("label_102") self.horizontalLayout.addWidget(self.label_102) self.set_min_max_Button = QtWidgets.QToolButton(self.tab_LCS_threshold) self.set_min_max_Button.setStyleSheet("margin: 0px;padding: 0px;") self.set_min_max_Button.setIcon(icon67) self.set_min_max_Button.setIconSize(QtCore.QSize(22, 22)) self.set_min_max_Button.setObjectName("set_min_max_Button") self.horizontalLayout.addWidget(self.set_min_max_Button) self.gridLayout_139.addLayout(self.horizontalLayout, 1, 0, 1, 1) self.horizontalLayout_2 = QtWidgets.QHBoxLayout() self.horizontalLayout_2.setObjectName("horizontalLayout_2") spacerItem25 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_2.addItem(spacerItem25) self.label_101 = QtWidgets.QLabel(self.tab_LCS_threshold) self.label_101.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_101.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_101.setObjectName("label_101") self.horizontalLayout_2.addWidget(self.label_101) self.multiplicative_threshold_doubleSpinBox_2 = QtWidgets.QDoubleSpinBox(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.multiplicative_threshold_doubleSpinBox_2.sizePolicy().hasHeightForWidth()) self.multiplicative_threshold_doubleSpinBox_2.setSizePolicy(sizePolicy) self.multiplicative_threshold_doubleSpinBox_2.setDecimals(1) self.multiplicative_threshold_doubleSpinBox_2.setMaximum(10000.0) self.multiplicative_threshold_doubleSpinBox_2.setProperty("value", 1.0) self.multiplicative_threshold_doubleSpinBox_2.setObjectName("multiplicative_threshold_doubleSpinBox_2") self.horizontalLayout_2.addWidget(self.multiplicative_threshold_doubleSpinBox_2) self.automatic_threshold_pushButton_2 = QtWidgets.QToolButton(self.tab_LCS_threshold) self.automatic_threshold_pushButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.automatic_threshold_pushButton_2.setIcon(icon67) self.automatic_threshold_pushButton_2.setIconSize(QtCore.QSize(22, 22)) self.automatic_threshold_pushButton_2.setObjectName("automatic_threshold_pushButton_2") self.horizontalLayout_2.addWidget(self.automatic_threshold_pushButton_2) spacerItem26 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_2.addItem(spacerItem26) self.gridLayout_140 = QtWidgets.QGridLayout() self.gridLayout_140.setObjectName("gridLayout_140") self.label_89 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_89.sizePolicy().hasHeightForWidth()) self.label_89.setSizePolicy(sizePolicy) self.label_89.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_89.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_89.setObjectName("label_89") self.gridLayout_140.addWidget(self.label_89, 0, 2, 1, 3) self.LCS_pointerButton = QtWidgets.QToolButton(self.tab_LCS_threshold) self.LCS_pointerButton.setStyleSheet("margin: 0px;padding: 0px;") icon71 = QtGui.QIcon() icon71.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_LCS_threshold_set_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.LCS_pointerButton.setIcon(icon71) self.LCS_pointerButton.setIconSize(QtCore.QSize(22, 22)) self.LCS_pointerButton.setObjectName("LCS_pointerButton") self.gridLayout_140.addWidget(self.LCS_pointerButton, 0, 5, 1, 1) self.gridLayout_144 = QtWidgets.QGridLayout() self.gridLayout_144.setObjectName("gridLayout_144") self.LCS_include_checkBox = QtWidgets.QCheckBox(self.tab_LCS_threshold) self.LCS_include_checkBox.setText("") self.LCS_include_checkBox.setIcon(icon57) self.LCS_include_checkBox.setChecked(True) self.LCS_include_checkBox.setObjectName("LCS_include_checkBox") self.gridLayout_144.addWidget(self.LCS_include_checkBox, 0, 0, 1, 1) self.LCS_cut_checkBox = QtWidgets.QCheckBox(self.tab_LCS_threshold) self.LCS_cut_checkBox.setText("") icon72 = QtGui.QIcon() icon72.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_minus.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.LCS_cut_checkBox.setIcon(icon72) self.LCS_cut_checkBox.setObjectName("LCS_cut_checkBox") self.gridLayout_144.addWidget(self.LCS_cut_checkBox, 1, 0, 1, 1) self.gridLayout_140.addLayout(self.gridLayout_144, 0, 6, 1, 1) self.label_178 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_178.sizePolicy().hasHeightForWidth()) self.label_178.setSizePolicy(sizePolicy) self.label_178.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_178.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_178.setObjectName("label_178") self.gridLayout_140.addWidget(self.label_178, 0, 0, 1, 1) self.LCS_ROI_button = QtWidgets.QToolButton(self.tab_LCS_threshold) self.LCS_ROI_button.setStyleSheet("margin: 0px;padding: 0px;") icon73 = QtGui.QIcon() icon73.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_LCS_threshold_ROI_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.LCS_ROI_button.setIcon(icon73) self.LCS_ROI_button.setIconSize(QtCore.QSize(22, 22)) self.LCS_ROI_button.setObjectName("LCS_ROI_button") self.gridLayout_140.addWidget(self.LCS_ROI_button, 0, 1, 1, 1) self.horizontalLayout_2.addLayout(self.gridLayout_140) self.gridLayout_139.addLayout(self.horizontalLayout_2, 1, 1, 1, 1) self.label_125 = QtWidgets.QLabel(self.tab_LCS_threshold) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_125.sizePolicy().hasHeightForWidth()) self.label_125.setSizePolicy(sizePolicy) self.label_125.setStyleSheet("background-color : #656565; color : white") self.label_125.setFrameShape(QtWidgets.QFrame.Panel) self.label_125.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_125.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_125.setObjectName("label_125") self.gridLayout_139.addWidget(self.label_125, 0, 0, 1, 2) self.gridLayout_137.addLayout(self.gridLayout_139, 2, 0, 1, 2) self.gridLayout_105.addLayout(self.gridLayout_137, 0, 0, 1, 1) self.tabWidget_5.addTab(self.tab_LCS_threshold, "") self.gridLayout_216.addWidget(self.tabWidget_5, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_basic_tools, "") self.tab_download_products = QtWidgets.QWidget() self.tab_download_products.setObjectName("tab_download_products") self.gridLayout_68 = QtWidgets.QGridLayout(self.tab_download_products) self.gridLayout_68.setObjectName("gridLayout_68") self.gridLayout_113 = QtWidgets.QGridLayout() self.gridLayout_113.setObjectName("gridLayout_113") self.tabWidget_3 = QtWidgets.QTabWidget(self.tab_download_products) self.tabWidget_3.setStyleSheet("QTabBar::tab {\n" "padding: 10px;\n" "min-height: 18px;\n" "}") self.tabWidget_3.setTabPosition(QtWidgets.QTabWidget.North) self.tabWidget_3.setObjectName("tabWidget_3") self.tab_login = QtWidgets.QWidget() self.tab_login.setObjectName("tab_login") self.gridLayout_238 = QtWidgets.QGridLayout(self.tab_login) self.gridLayout_238.setObjectName("gridLayout_238") self.gridLayout_227 = QtWidgets.QGridLayout() self.gridLayout_227.setObjectName("gridLayout_227") self.remember_user_checkBox_2 = QtWidgets.QCheckBox(self.tab_login) self.remember_user_checkBox_2.setChecked(True) self.remember_user_checkBox_2.setObjectName("remember_user_checkBox_2") self.gridLayout_227.addWidget(self.remember_user_checkBox_2, 1, 4, 1, 1) self.password_usgs_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.password_usgs_lineEdit.setObjectName("password_usgs_lineEdit") self.gridLayout_227.addWidget(self.password_usgs_lineEdit, 1, 3, 1, 1) self.password_scihub_label_3 = QtWidgets.QLabel(self.tab_login) self.password_scihub_label_3.setObjectName("password_scihub_label_3") self.gridLayout_227.addWidget(self.password_scihub_label_3, 1, 2, 1, 1) self.label_180 = QtWidgets.QLabel(self.tab_login) self.label_180.setStyleSheet("background-color : #656565; color : white") self.label_180.setFrameShape(QtWidgets.QFrame.Panel) self.label_180.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_180.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_180.setOpenExternalLinks(True) self.label_180.setObjectName("label_180") self.gridLayout_227.addWidget(self.label_180, 0, 0, 1, 6) self.user_usgs_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.user_usgs_lineEdit.setObjectName("user_usgs_lineEdit") self.gridLayout_227.addWidget(self.user_usgs_lineEdit, 1, 1, 1, 1) self.user_scihub_label_2 = QtWidgets.QLabel(self.tab_login) self.user_scihub_label_2.setObjectName("user_scihub_label_2") self.gridLayout_227.addWidget(self.user_scihub_label_2, 1, 0, 1, 1) self.gridLayout_238.addLayout(self.gridLayout_227, 0, 0, 1, 1) self.gridLayout_242 = QtWidgets.QGridLayout() self.gridLayout_242.setObjectName("gridLayout_242") self.remember_user_checkBox_3 = QtWidgets.QCheckBox(self.tab_login) self.remember_user_checkBox_3.setChecked(True) self.remember_user_checkBox_3.setObjectName("remember_user_checkBox_3") self.gridLayout_242.addWidget(self.remember_user_checkBox_3, 1, 4, 1, 1) self.password_usgs_lineEdit_2 = QtWidgets.QLineEdit(self.tab_login) self.password_usgs_lineEdit_2.setObjectName("password_usgs_lineEdit_2") self.gridLayout_242.addWidget(self.password_usgs_lineEdit_2, 1, 3, 1, 1) self.password_scihub_label_4 = QtWidgets.QLabel(self.tab_login) self.password_scihub_label_4.setObjectName("password_scihub_label_4") self.gridLayout_242.addWidget(self.password_scihub_label_4, 1, 2, 1, 1) self.label_191 = QtWidgets.QLabel(self.tab_login) self.label_191.setStyleSheet("background-color : #656565; color : white") self.label_191.setFrameShape(QtWidgets.QFrame.Panel) self.label_191.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_191.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_191.setOpenExternalLinks(True) self.label_191.setObjectName("label_191") self.gridLayout_242.addWidget(self.label_191, 0, 0, 1, 6) self.user_usgs_lineEdit_2 = QtWidgets.QLineEdit(self.tab_login) self.user_usgs_lineEdit_2.setObjectName("user_usgs_lineEdit_2") self.gridLayout_242.addWidget(self.user_usgs_lineEdit_2, 1, 1, 1, 1) self.user_scihub_label_3 = QtWidgets.QLabel(self.tab_login) self.user_scihub_label_3.setObjectName("user_scihub_label_3") self.gridLayout_242.addWidget(self.user_scihub_label_3, 1, 0, 1, 1) self.gridLayout_238.addLayout(self.gridLayout_242, 1, 0, 1, 1) self.gridLayout_159 = QtWidgets.QGridLayout() self.gridLayout_159.setObjectName("gridLayout_159") self.user_scihub_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.user_scihub_lineEdit.setObjectName("user_scihub_lineEdit") self.gridLayout_159.addWidget(self.user_scihub_lineEdit, 2, 1, 1, 1) self.password_scihub_label = QtWidgets.QLabel(self.tab_login) self.password_scihub_label.setObjectName("password_scihub_label") self.gridLayout_159.addWidget(self.password_scihub_label, 2, 2, 1, 1) self.label_147 = QtWidgets.QLabel(self.tab_login) self.label_147.setStyleSheet("background-color : #656565; color : white") self.label_147.setFrameShape(QtWidgets.QFrame.Panel) self.label_147.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_147.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_147.setOpenExternalLinks(True) self.label_147.setObjectName("label_147") self.gridLayout_159.addWidget(self.label_147, 0, 0, 1, 6) self.remember_user_checkBox = QtWidgets.QCheckBox(self.tab_login) self.remember_user_checkBox.setChecked(True) self.remember_user_checkBox.setObjectName("remember_user_checkBox") self.gridLayout_159.addWidget(self.remember_user_checkBox, 2, 4, 1, 1) self.user_scihub_label = QtWidgets.QLabel(self.tab_login) self.user_scihub_label.setObjectName("user_scihub_label") self.gridLayout_159.addWidget(self.user_scihub_label, 2, 0, 1, 1) self.password_scihub_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.password_scihub_lineEdit.setObjectName("password_scihub_lineEdit") self.gridLayout_159.addWidget(self.password_scihub_lineEdit, 2, 3, 1, 1) self.horizontalLayout_10 = QtWidgets.QHBoxLayout() self.horizontalLayout_10.setObjectName("horizontalLayout_10") self.password_scihub_label_2 = QtWidgets.QLabel(self.tab_login) self.password_scihub_label_2.setObjectName("password_scihub_label_2") self.horizontalLayout_10.addWidget(self.password_scihub_label_2) self.sentinel_service_lineEdit = QtWidgets.QLineEdit(self.tab_login) self.sentinel_service_lineEdit.setText("") self.sentinel_service_lineEdit.setObjectName("sentinel_service_lineEdit") self.horizontalLayout_10.addWidget(self.sentinel_service_lineEdit) self.reset_sentinel_service_toolButton = QtWidgets.QToolButton(self.tab_login) self.reset_sentinel_service_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.reset_sentinel_service_toolButton.setIcon(icon59) self.reset_sentinel_service_toolButton.setIconSize(QtCore.QSize(22, 22)) self.reset_sentinel_service_toolButton.setObjectName("reset_sentinel_service_toolButton") self.horizontalLayout_10.addWidget(self.reset_sentinel_service_toolButton) self.gridLayout_159.addLayout(self.horizontalLayout_10, 1, 0, 1, 5) self.sentinel2_alternative_search_checkBox = QtWidgets.QCheckBox(self.tab_login) self.sentinel2_alternative_search_checkBox.setObjectName("sentinel2_alternative_search_checkBox") self.gridLayout_159.addWidget(self.sentinel2_alternative_search_checkBox, 3, 0, 1, 5) self.gridLayout_238.addLayout(self.gridLayout_159, 2, 0, 1, 1) spacerItem27 = QtWidgets.QSpacerItem(20, 251, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_238.addItem(spacerItem27, 3, 0, 1, 1) icon74 = QtGui.QIcon() icon74.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_login.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.tabWidget_3.addTab(self.tab_login, icon74, "") self.tab_search = QtWidgets.QWidget() self.tab_search.setObjectName("tab_search") self.gridLayout_264 = QtWidgets.QGridLayout(self.tab_search) self.gridLayout_264.setObjectName("gridLayout_264") self.gridLayout_search = QtWidgets.QGridLayout() self.gridLayout_search.setObjectName("gridLayout_search") self.gridLayout_132 = QtWidgets.QGridLayout() self.gridLayout_132.setObjectName("gridLayout_132") self.remove_image_toolButton = QtWidgets.QToolButton(self.tab_search) self.remove_image_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.remove_image_toolButton.setIcon(icon58) self.remove_image_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_image_toolButton.setObjectName("remove_image_toolButton") self.gridLayout_132.addWidget(self.remove_image_toolButton, 1, 1, 1, 1) self.toolButton_display = QtWidgets.QToolButton(self.tab_search) self.toolButton_display.setStyleSheet("margin: 0px;padding: 0px;") icon75 = QtGui.QIcon() icon75.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_image_preview.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_display.setIcon(icon75) self.toolButton_display.setIconSize(QtCore.QSize(22, 22)) self.toolButton_display.setObjectName("toolButton_display") self.gridLayout_132.addWidget(self.toolButton_display, 0, 1, 1, 1) self.clear_table_toolButton = QtWidgets.QToolButton(self.tab_search) self.clear_table_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_table_toolButton.setIcon(icon59) self.clear_table_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_table_toolButton.setObjectName("clear_table_toolButton") self.gridLayout_132.addWidget(self.clear_table_toolButton, 2, 1, 1, 1) self.export_table_pushButton = QtWidgets.QToolButton(self.tab_search) self.export_table_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.export_table_pushButton.setIcon(icon53) self.export_table_pushButton.setIconSize(QtCore.QSize(22, 22)) self.export_table_pushButton.setObjectName("export_table_pushButton") self.gridLayout_132.addWidget(self.export_table_pushButton, 4, 1, 1, 1) self.import_table_pushButton = QtWidgets.QToolButton(self.tab_search) self.import_table_pushButton.setStyleSheet("margin: 0px;padding: 0px") self.import_table_pushButton.setIcon(icon54) self.import_table_pushButton.setIconSize(QtCore.QSize(22, 22)) self.import_table_pushButton.setObjectName("import_table_pushButton") self.gridLayout_132.addWidget(self.import_table_pushButton, 3, 1, 1, 1) self.gridLayout_121 = QtWidgets.QGridLayout() self.gridLayout_121.setObjectName("gridLayout_121") self.image_preview_label = QtWidgets.QLabel(self.tab_search) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.image_preview_label.sizePolicy().hasHeightForWidth()) self.image_preview_label.setSizePolicy(sizePolicy) self.image_preview_label.setMinimumSize(QtCore.QSize(300, 300)) self.image_preview_label.setFrameShape(QtWidgets.QFrame.Panel) self.image_preview_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.image_preview_label.setAlignment(QtCore.Qt.AlignCenter) self.image_preview_label.setObjectName("image_preview_label") self.gridLayout_121.addWidget(self.image_preview_label, 0, 0, 1, 1) self.gridLayout_132.addLayout(self.gridLayout_121, 0, 0, 5, 1) self.gridLayout_search.addLayout(self.gridLayout_132, 2, 1, 1, 1) self.download_images_tableWidget = QtWidgets.QTableWidget(self.tab_search) self.download_images_tableWidget.setFrameShadow(QtWidgets.QFrame.Sunken) self.download_images_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.download_images_tableWidget.setTabKeyNavigation(True) self.download_images_tableWidget.setAlternatingRowColors(True) self.download_images_tableWidget.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.download_images_tableWidget.setObjectName("download_images_tableWidget") self.download_images_tableWidget.setColumnCount(14) self.download_images_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(6, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(7, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(8, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(9, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(10, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(11, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(12, item) item = QtWidgets.QTableWidgetItem() self.download_images_tableWidget.setHorizontalHeaderItem(13, item) self.download_images_tableWidget.verticalHeader().setDefaultSectionSize(20) self.gridLayout_search.addWidget(self.download_images_tableWidget, 2, 0, 1, 1) self.label_100 = QtWidgets.QLabel(self.tab_search) self.label_100.setStyleSheet("background-color : #656565; color : white") self.label_100.setFrameShape(QtWidgets.QFrame.Panel) self.label_100.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_100.setObjectName("label_100") self.gridLayout_search.addWidget(self.label_100, 0, 0, 1, 1) self.products_filter_lineEdit = QtWidgets.QLineEdit(self.tab_search) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.products_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.products_filter_lineEdit.setSizePolicy(sizePolicy) self.products_filter_lineEdit.setObjectName("products_filter_lineEdit") self.gridLayout_search.addWidget(self.products_filter_lineEdit, 0, 1, 1, 1) self.gridLayout_264.addLayout(self.gridLayout_search, 1, 0, 1, 1) self.gridLayout_133 = QtWidgets.QGridLayout() self.gridLayout_133.setObjectName("gridLayout_133") self.gridLayout_54 = QtWidgets.QGridLayout() self.gridLayout_54.setObjectName("gridLayout_54") self.toolButton_OSM = QtWidgets.QToolButton(self.tab_search) self.toolButton_OSM.setStyleSheet("margin: 0px;padding: 0px;") icon76 = QtGui.QIcon() icon76.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_osm_add.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.toolButton_OSM.setIcon(icon76) self.toolButton_OSM.setIconSize(QtCore.QSize(22, 22)) self.toolButton_OSM.setObjectName("toolButton_OSM") self.gridLayout_54.addWidget(self.toolButton_OSM, 0, 0, 1, 1) self.label_205 = QtWidgets.QLabel(self.tab_search) self.label_205.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_205.setAlignment(QtCore.Qt.AlignCenter) self.label_205.setOpenExternalLinks(True) self.label_205.setObjectName("label_205") self.gridLayout_54.addWidget(self.label_205, 0, 1, 1, 1) self.label_206 = QtWidgets.QLabel(self.tab_search) self.label_206.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_206.setAlignment(QtCore.Qt.AlignCenter) self.label_206.setOpenExternalLinks(True) self.label_206.setObjectName("label_206") self.gridLayout_54.addWidget(self.label_206, 0, 2, 1, 1) spacerItem28 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_54.addItem(spacerItem28, 0, 3, 1, 2) self.gridLayout_133.addLayout(self.gridLayout_54, 3, 0, 1, 2) self.label_103 = QtWidgets.QLabel(self.tab_search) self.label_103.setStyleSheet("background-color : #656565; color : white") self.label_103.setFrameShape(QtWidgets.QFrame.Panel) self.label_103.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_103.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_103.setObjectName("label_103") self.gridLayout_133.addWidget(self.label_103, 0, 0, 1, 2) self.gridLayout_122 = QtWidgets.QGridLayout() self.gridLayout_122.setObjectName("gridLayout_122") self.selectUL_toolButton_3 = QtWidgets.QToolButton(self.tab_search) self.selectUL_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") icon77 = QtGui.QIcon() icon77.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_pointer_tool.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.selectUL_toolButton_3.setIcon(icon77) self.selectUL_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.selectUL_toolButton_3.setObjectName("selectUL_toolButton_3") self.gridLayout_122.addWidget(self.selectUL_toolButton_3, 0, 7, 1, 1) self.LX_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.LX_lineEdit_3.setText("") self.LX_lineEdit_3.setMaxLength(15) self.LX_lineEdit_3.setObjectName("LX_lineEdit_3") self.gridLayout_122.addWidget(self.LX_lineEdit_3, 0, 4, 1, 1) self.UX_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.UX_lineEdit_3.setMaxLength(15) self.UX_lineEdit_3.setObjectName("UX_lineEdit_3") self.gridLayout_122.addWidget(self.UX_lineEdit_3, 0, 1, 1, 1) self.label_105 = QtWidgets.QLabel(self.tab_search) self.label_105.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_105.setAlignment(QtCore.Qt.AlignCenter) self.label_105.setObjectName("label_105") self.gridLayout_122.addWidget(self.label_105, 0, 3, 1, 1) self.label_107 = QtWidgets.QLabel(self.tab_search) self.label_107.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_107.setAlignment(QtCore.Qt.AlignCenter) self.label_107.setObjectName("label_107") self.gridLayout_122.addWidget(self.label_107, 0, 0, 1, 1) self.LY_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.LY_lineEdit_3.setMaxLength(15) self.LY_lineEdit_3.setObjectName("LY_lineEdit_3") self.gridLayout_122.addWidget(self.LY_lineEdit_3, 0, 5, 1, 1) self.UY_lineEdit_3 = QtWidgets.QLineEdit(self.tab_search) self.UY_lineEdit_3.setMaxLength(15) self.UY_lineEdit_3.setObjectName("UY_lineEdit_3") self.gridLayout_122.addWidget(self.UY_lineEdit_3, 0, 2, 1, 1) self.show_area_radioButton_2 = QtWidgets.QRadioButton(self.tab_search) self.show_area_radioButton_2.setChecked(True) self.show_area_radioButton_2.setAutoExclusive(False) self.show_area_radioButton_2.setObjectName("show_area_radioButton_2") self.gridLayout_122.addWidget(self.show_area_radioButton_2, 0, 6, 1, 1) self.gridLayout_115 = QtWidgets.QGridLayout() self.gridLayout_115.setObjectName("gridLayout_115") self.find_images_toolButton = QtWidgets.QToolButton(self.tab_search) self.find_images_toolButton.setStyleSheet("margin: 0px;padding: 0px;") icon78 = QtGui.QIcon() icon78.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_search_images.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.find_images_toolButton.setIcon(icon78) self.find_images_toolButton.setIconSize(QtCore.QSize(22, 22)) self.find_images_toolButton.setObjectName("find_images_toolButton") self.gridLayout_115.addWidget(self.find_images_toolButton, 1, 8, 1, 1) self.label_35 = QtWidgets.QLabel(self.tab_search) self.label_35.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.label_35.setObjectName("label_35") self.gridLayout_115.addWidget(self.label_35, 1, 7, 1, 1) self.gridLayout_114 = QtWidgets.QGridLayout() self.gridLayout_114.setObjectName("gridLayout_114") self.landsat_satellite_combo = QtWidgets.QComboBox(self.tab_search) self.landsat_satellite_combo.setObjectName("landsat_satellite_combo") self.gridLayout_114.addWidget(self.landsat_satellite_combo, 0, 1, 1, 1) self.dateEdit_from = QtWidgets.QDateEdit(self.tab_search) self.dateEdit_from.setDateTime(QtCore.QDateTime(QtCore.QDate(2016, 1, 1), QtCore.QTime(0, 0, 0))) self.dateEdit_from.setMaximumDate(QtCore.QDate(2045, 12, 31)) self.dateEdit_from.setMinimumDate(QtCore.QDate(1972, 1, 1)) self.dateEdit_from.setCalendarPopup(True) self.dateEdit_from.setDate(QtCore.QDate(2016, 1, 1)) self.dateEdit_from.setObjectName("dateEdit_from") self.gridLayout_114.addWidget(self.dateEdit_from, 0, 4, 1, 1) self.label_110 = QtWidgets.QLabel(self.tab_search) self.label_110.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_110.setAlignment(QtCore.Qt.AlignCenter) self.label_110.setObjectName("label_110") self.gridLayout_114.addWidget(self.label_110, 0, 8, 1, 1) self.dateEdit_to = QtWidgets.QDateEdit(self.tab_search) self.dateEdit_to.setMaximumDate(QtCore.QDate(2045, 12, 31)) self.dateEdit_to.setMinimumDate(QtCore.QDate(1980, 1, 2)) self.dateEdit_to.setCalendarPopup(True) self.dateEdit_to.setDate(QtCore.QDate(2045, 12, 31)) self.dateEdit_to.setObjectName("dateEdit_to") self.gridLayout_114.addWidget(self.dateEdit_to, 0, 6, 1, 1) self.label_112 = QtWidgets.QLabel(self.tab_search) self.label_112.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_112.setAlignment(QtCore.Qt.AlignCenter) self.label_112.setObjectName("label_112") self.gridLayout_114.addWidget(self.label_112, 0, 5, 1, 1) self.label_111 = QtWidgets.QLabel(self.tab_search) self.label_111.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_111.setAlignment(QtCore.Qt.AlignCenter) self.label_111.setObjectName("label_111") self.gridLayout_114.addWidget(self.label_111, 0, 3, 1, 1) self.cloud_cover_spinBox = QtWidgets.QSpinBox(self.tab_search) self.cloud_cover_spinBox.setMinimumSize(QtCore.QSize(50, 0)) self.cloud_cover_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.cloud_cover_spinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.cloud_cover_spinBox.setMinimum(0) self.cloud_cover_spinBox.setMaximum(100) self.cloud_cover_spinBox.setSingleStep(10) self.cloud_cover_spinBox.setProperty("value", 100) self.cloud_cover_spinBox.setObjectName("cloud_cover_spinBox") self.gridLayout_114.addWidget(self.cloud_cover_spinBox, 0, 9, 1, 1) self.label_114 = QtWidgets.QLabel(self.tab_search) self.label_114.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_114.setAlignment(QtCore.Qt.AlignCenter) self.label_114.setObjectName("label_114") self.gridLayout_114.addWidget(self.label_114, 0, 0, 1, 1) spacerItem29 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_114.addItem(spacerItem29, 0, 7, 1, 1) spacerItem30 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_114.addItem(spacerItem30, 0, 2, 1, 1) self.gridLayout_115.addLayout(self.gridLayout_114, 0, 0, 1, 9) self.gridLayout_120 = QtWidgets.QGridLayout() self.gridLayout_120.setObjectName("gridLayout_120") self.label_194 = QtWidgets.QLabel(self.tab_search) self.label_194.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_194.setAlignment(QtCore.Qt.AlignCenter) self.label_194.setObjectName("label_194") self.gridLayout_120.addWidget(self.label_194, 0, 0, 1, 1) self.label_113 = QtWidgets.QLabel(self.tab_search) self.label_113.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_113.setAlignment(QtCore.Qt.AlignCenter) self.label_113.setObjectName("label_113") self.gridLayout_120.addWidget(self.label_113, 0, 2, 1, 1) self.imageID_lineEdit = QtWidgets.QLineEdit(self.tab_search) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.imageID_lineEdit.sizePolicy().hasHeightForWidth()) self.imageID_lineEdit.setSizePolicy(sizePolicy) self.imageID_lineEdit.setMinimumSize(QtCore.QSize(200, 0)) self.imageID_lineEdit.setMaxLength(10000) self.imageID_lineEdit.setObjectName("imageID_lineEdit") self.gridLayout_120.addWidget(self.imageID_lineEdit, 0, 3, 1, 1) self.result_number_spinBox_2 = QtWidgets.QSpinBox(self.tab_search) self.result_number_spinBox_2.setMinimumSize(QtCore.QSize(50, 0)) self.result_number_spinBox_2.setMaximumSize(QtCore.QSize(100, 16777215)) self.result_number_spinBox_2.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.result_number_spinBox_2.setMinimum(5) self.result_number_spinBox_2.setMaximum(2000) self.result_number_spinBox_2.setSingleStep(5) self.result_number_spinBox_2.setProperty("value", 20) self.result_number_spinBox_2.setObjectName("result_number_spinBox_2") self.gridLayout_120.addWidget(self.result_number_spinBox_2, 0, 1, 1, 1) self.gridLayout_115.addLayout(self.gridLayout_120, 1, 0, 1, 7) self.gridLayout_122.addLayout(self.gridLayout_115, 1, 0, 1, 8) self.gridLayout_133.addLayout(self.gridLayout_122, 1, 0, 2, 2) self.gridLayout_264.addLayout(self.gridLayout_133, 0, 0, 1, 1) icon79 = QtGui.QIcon() icon79.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_search.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.tabWidget_3.addTab(self.tab_search, icon79, "") self.tab_options = QtWidgets.QWidget() self.tab_options.setObjectName("tab_options") self.gridLayout_199 = QtWidgets.QGridLayout(self.tab_options) self.gridLayout_199.setObjectName("gridLayout_199") self.gridLayout_116 = QtWidgets.QGridLayout() self.gridLayout_116.setObjectName("gridLayout_116") self.checkBox_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_6.setChecked(True) self.checkBox_band_6.setObjectName("checkBox_band_6") self.gridLayout_116.addWidget(self.checkBox_band_6, 1, 5, 1, 1) self.checkBox_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_4.setChecked(True) self.checkBox_band_4.setObjectName("checkBox_band_4") self.gridLayout_116.addWidget(self.checkBox_band_4, 1, 3, 1, 1) self.checkBox_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_1.setChecked(True) self.checkBox_band_1.setObjectName("checkBox_band_1") self.gridLayout_116.addWidget(self.checkBox_band_1, 1, 0, 1, 1) self.checkBox_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_3.setChecked(True) self.checkBox_band_3.setObjectName("checkBox_band_3") self.gridLayout_116.addWidget(self.checkBox_band_3, 1, 2, 1, 1) self.checkBox_band_12 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_12.setChecked(True) self.checkBox_band_12.setObjectName("checkBox_band_12") self.gridLayout_116.addWidget(self.checkBox_band_12, 2, 5, 1, 1) self.checkBox_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_2.setChecked(True) self.checkBox_band_2.setObjectName("checkBox_band_2") self.gridLayout_116.addWidget(self.checkBox_band_2, 1, 1, 1, 1) self.checkBox_band_11 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_11.setChecked(True) self.checkBox_band_11.setObjectName("checkBox_band_11") self.gridLayout_116.addWidget(self.checkBox_band_11, 2, 4, 1, 1) self.checkBox_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_5.setChecked(True) self.checkBox_band_5.setObjectName("checkBox_band_5") self.gridLayout_116.addWidget(self.checkBox_band_5, 1, 4, 1, 1) self.check_toolButton = QtWidgets.QToolButton(self.tab_options) self.check_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton.setIcon(icon56) self.check_toolButton.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton.setObjectName("check_toolButton") self.gridLayout_116.addWidget(self.check_toolButton, 1, 6, 1, 1) self.label_108 = QtWidgets.QLabel(self.tab_options) self.label_108.setStyleSheet("background-color : #656565; color : white") self.label_108.setFrameShape(QtWidgets.QFrame.Panel) self.label_108.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_108.setObjectName("label_108") self.gridLayout_116.addWidget(self.label_108, 0, 0, 1, 7) self.gridLayout_117 = QtWidgets.QGridLayout() self.gridLayout_117.setObjectName("gridLayout_117") spacerItem31 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_117.addItem(spacerItem31, 3, 1, 1, 1) self.gridLayout_136 = QtWidgets.QGridLayout() self.gridLayout_136.setObjectName("gridLayout_136") self.checkBoxs_band_9 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_9.setChecked(True) self.checkBoxs_band_9.setObjectName("checkBoxs_band_9") self.gridLayout_136.addWidget(self.checkBoxs_band_9, 1, 8, 1, 1) self.checkBoxs_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_1.setChecked(True) self.checkBoxs_band_1.setObjectName("checkBoxs_band_1") self.gridLayout_136.addWidget(self.checkBoxs_band_1, 1, 0, 1, 1) self.check_toolButton_2 = QtWidgets.QToolButton(self.tab_options) self.check_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton_2.setIcon(icon56) self.check_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton_2.setObjectName("check_toolButton_2") self.gridLayout_136.addWidget(self.check_toolButton_2, 1, 14, 1, 1) self.label_118 = QtWidgets.QLabel(self.tab_options) self.label_118.setStyleSheet("background-color : #656565; color : white") self.label_118.setFrameShape(QtWidgets.QFrame.Panel) self.label_118.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_118.setObjectName("label_118") self.gridLayout_136.addWidget(self.label_118, 0, 0, 1, 15) self.checkBoxs_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_2.setChecked(True) self.checkBoxs_band_2.setObjectName("checkBoxs_band_2") self.gridLayout_136.addWidget(self.checkBoxs_band_2, 1, 1, 1, 1) self.checkBoxs_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_3.setChecked(True) self.checkBoxs_band_3.setObjectName("checkBoxs_band_3") self.gridLayout_136.addWidget(self.checkBoxs_band_3, 1, 2, 1, 1) self.checkBoxs_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_4.setChecked(True) self.checkBoxs_band_4.setObjectName("checkBoxs_band_4") self.gridLayout_136.addWidget(self.checkBoxs_band_4, 1, 3, 1, 1) self.checkBoxs_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_5.setChecked(True) self.checkBoxs_band_5.setObjectName("checkBoxs_band_5") self.gridLayout_136.addWidget(self.checkBoxs_band_5, 1, 4, 1, 1) self.checkBoxs_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_6.setChecked(True) self.checkBoxs_band_6.setObjectName("checkBoxs_band_6") self.gridLayout_136.addWidget(self.checkBoxs_band_6, 1, 5, 1, 1) self.checkBoxs_band_7 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_7.setChecked(True) self.checkBoxs_band_7.setObjectName("checkBoxs_band_7") self.gridLayout_136.addWidget(self.checkBoxs_band_7, 1, 6, 1, 1) self.checkBoxs_band_12 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_12.setChecked(True) self.checkBoxs_band_12.setObjectName("checkBoxs_band_12") self.gridLayout_136.addWidget(self.checkBoxs_band_12, 1, 11, 1, 1) self.checkBoxs_band_8 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_8.setChecked(True) self.checkBoxs_band_8.setObjectName("checkBoxs_band_8") self.gridLayout_136.addWidget(self.checkBoxs_band_8, 1, 7, 1, 1) self.checkBoxs_band_10 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_10.setChecked(True) self.checkBoxs_band_10.setObjectName("checkBoxs_band_10") self.gridLayout_136.addWidget(self.checkBoxs_band_10, 1, 9, 1, 1) self.ancillary_data_checkBox = QtWidgets.QCheckBox(self.tab_options) self.ancillary_data_checkBox.setChecked(True) self.ancillary_data_checkBox.setObjectName("ancillary_data_checkBox") self.gridLayout_136.addWidget(self.ancillary_data_checkBox, 1, 13, 1, 1) self.checkBoxs_band_13 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_13.setChecked(True) self.checkBoxs_band_13.setObjectName("checkBoxs_band_13") self.gridLayout_136.addWidget(self.checkBoxs_band_13, 1, 12, 1, 1) self.checkBoxs_band_11 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_band_11.setChecked(True) self.checkBoxs_band_11.setObjectName("checkBoxs_band_11") self.gridLayout_136.addWidget(self.checkBoxs_band_11, 1, 10, 1, 1) self.gridLayout_117.addLayout(self.gridLayout_136, 0, 1, 1, 1) self.gridLayout_160 = QtWidgets.QGridLayout() self.gridLayout_160.setObjectName("gridLayout_160") self.checkBoxs3_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_6.setChecked(True) self.checkBoxs3_band_6.setObjectName("checkBoxs3_band_6") self.gridLayout_160.addWidget(self.checkBoxs3_band_6, 1, 5, 1, 1) self.checkBoxs3_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_2.setChecked(True) self.checkBoxs3_band_2.setObjectName("checkBoxs3_band_2") self.gridLayout_160.addWidget(self.checkBoxs3_band_2, 1, 1, 1, 1) self.checkBoxs3_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_5.setChecked(True) self.checkBoxs3_band_5.setObjectName("checkBoxs3_band_5") self.gridLayout_160.addWidget(self.checkBoxs3_band_5, 1, 4, 1, 1) self.checkBoxs3_band_8 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_8.setChecked(True) self.checkBoxs3_band_8.setObjectName("checkBoxs3_band_8") self.gridLayout_160.addWidget(self.checkBoxs3_band_8, 1, 7, 1, 1) self.checkBoxs3_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_1.setChecked(True) self.checkBoxs3_band_1.setObjectName("checkBoxs3_band_1") self.gridLayout_160.addWidget(self.checkBoxs3_band_1, 1, 0, 1, 1) self.checkBoxs3_band_16 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_16.setChecked(True) self.checkBoxs3_band_16.setObjectName("checkBoxs3_band_16") self.gridLayout_160.addWidget(self.checkBoxs3_band_16, 2, 4, 1, 1) self.checkBoxs3_band_10 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_10.setChecked(True) self.checkBoxs3_band_10.setObjectName("checkBoxs3_band_10") self.gridLayout_160.addWidget(self.checkBoxs3_band_10, 1, 9, 1, 1) self.checkBoxs3_band_12 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_12.setChecked(True) self.checkBoxs3_band_12.setObjectName("checkBoxs3_band_12") self.gridLayout_160.addWidget(self.checkBoxs3_band_12, 2, 0, 1, 1) self.s3_ancillary_data_checkBox = QtWidgets.QCheckBox(self.tab_options) self.s3_ancillary_data_checkBox.setChecked(True) self.s3_ancillary_data_checkBox.setObjectName("s3_ancillary_data_checkBox") self.gridLayout_160.addWidget(self.s3_ancillary_data_checkBox, 2, 10, 1, 1) self.checkBoxs3_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_3.setChecked(True) self.checkBoxs3_band_3.setObjectName("checkBoxs3_band_3") self.gridLayout_160.addWidget(self.checkBoxs3_band_3, 1, 2, 1, 1) self.label_127 = QtWidgets.QLabel(self.tab_options) self.label_127.setStyleSheet("background-color : #656565; color : white") self.label_127.setFrameShape(QtWidgets.QFrame.Panel) self.label_127.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_127.setObjectName("label_127") self.gridLayout_160.addWidget(self.label_127, 0, 0, 1, 12) self.checkBoxs3_band_20 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_20.setChecked(True) self.checkBoxs3_band_20.setObjectName("checkBoxs3_band_20") self.gridLayout_160.addWidget(self.checkBoxs3_band_20, 2, 8, 1, 1) self.checkBoxs3_band_17 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_17.setChecked(True) self.checkBoxs3_band_17.setObjectName("checkBoxs3_band_17") self.gridLayout_160.addWidget(self.checkBoxs3_band_17, 2, 5, 1, 1) self.checkBoxs3_band_14 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_14.setChecked(True) self.checkBoxs3_band_14.setObjectName("checkBoxs3_band_14") self.gridLayout_160.addWidget(self.checkBoxs3_band_14, 2, 2, 1, 1) self.checkBoxs3_band_9 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_9.setChecked(True) self.checkBoxs3_band_9.setObjectName("checkBoxs3_band_9") self.gridLayout_160.addWidget(self.checkBoxs3_band_9, 1, 8, 1, 1) self.checkBoxs3_band_13 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_13.setChecked(True) self.checkBoxs3_band_13.setObjectName("checkBoxs3_band_13") self.gridLayout_160.addWidget(self.checkBoxs3_band_13, 2, 1, 1, 1) self.checkBoxs3_band_19 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_19.setChecked(True) self.checkBoxs3_band_19.setObjectName("checkBoxs3_band_19") self.gridLayout_160.addWidget(self.checkBoxs3_band_19, 2, 7, 1, 1) self.check_toolButton_3 = QtWidgets.QToolButton(self.tab_options) self.check_toolButton_3.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton_3.setIcon(icon56) self.check_toolButton_3.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton_3.setObjectName("check_toolButton_3") self.gridLayout_160.addWidget(self.check_toolButton_3, 1, 11, 1, 1) self.checkBoxs3_band_7 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_7.setChecked(True) self.checkBoxs3_band_7.setObjectName("checkBoxs3_band_7") self.gridLayout_160.addWidget(self.checkBoxs3_band_7, 1, 6, 1, 1) self.checkBoxs3_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_4.setChecked(True) self.checkBoxs3_band_4.setObjectName("checkBoxs3_band_4") self.gridLayout_160.addWidget(self.checkBoxs3_band_4, 1, 3, 1, 1) self.checkBoxs3_band_11 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_11.setChecked(True) self.checkBoxs3_band_11.setObjectName("checkBoxs3_band_11") self.gridLayout_160.addWidget(self.checkBoxs3_band_11, 1, 10, 1, 1) self.checkBoxs3_band_15 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_15.setChecked(True) self.checkBoxs3_band_15.setObjectName("checkBoxs3_band_15") self.gridLayout_160.addWidget(self.checkBoxs3_band_15, 2, 3, 1, 1) self.checkBoxs3_band_21 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_21.setChecked(True) self.checkBoxs3_band_21.setObjectName("checkBoxs3_band_21") self.gridLayout_160.addWidget(self.checkBoxs3_band_21, 2, 9, 1, 1) self.checkBoxs3_band_18 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs3_band_18.setChecked(True) self.checkBoxs3_band_18.setObjectName("checkBoxs3_band_18") self.gridLayout_160.addWidget(self.checkBoxs3_band_18, 2, 6, 1, 1) self.gridLayout_117.addLayout(self.gridLayout_160, 1, 1, 1, 1) self.gridLayout_141 = QtWidgets.QGridLayout() self.gridLayout_141.setObjectName("gridLayout_141") self.checkBoxs_goes_band_1 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_1.setChecked(True) self.checkBoxs_goes_band_1.setObjectName("checkBoxs_goes_band_1") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_1, 1, 0, 1, 1) self.label_272 = QtWidgets.QLabel(self.tab_options) self.label_272.setStyleSheet("background-color : #656565; color : white") self.label_272.setFrameShape(QtWidgets.QFrame.Panel) self.label_272.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_272.setObjectName("label_272") self.gridLayout_141.addWidget(self.label_272, 0, 0, 1, 8) self.checkBoxs_goes_band_5 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_5.setChecked(True) self.checkBoxs_goes_band_5.setObjectName("checkBoxs_goes_band_5") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_5, 1, 4, 1, 1) self.checkBoxs_goes_band_3 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_3.setChecked(True) self.checkBoxs_goes_band_3.setObjectName("checkBoxs_goes_band_3") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_3, 1, 2, 1, 1) self.checkBoxs_goes_band_4 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_4.setChecked(True) self.checkBoxs_goes_band_4.setObjectName("checkBoxs_goes_band_4") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_4, 1, 3, 1, 1) self.checkBoxs_goes_band_2 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_2.setChecked(True) self.checkBoxs_goes_band_2.setObjectName("checkBoxs_goes_band_2") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_2, 1, 1, 1, 1) self.checkBoxs_goes_band_6 = QtWidgets.QCheckBox(self.tab_options) self.checkBoxs_goes_band_6.setChecked(True) self.checkBoxs_goes_band_6.setObjectName("checkBoxs_goes_band_6") self.gridLayout_141.addWidget(self.checkBoxs_goes_band_6, 1, 5, 1, 1) self.check_toolButton_4 = QtWidgets.QToolButton(self.tab_options) self.check_toolButton_4.setStyleSheet("margin: 0px;padding: 0px;") self.check_toolButton_4.setIcon(icon56) self.check_toolButton_4.setIconSize(QtCore.QSize(22, 22)) self.check_toolButton_4.setObjectName("check_toolButton_4") self.gridLayout_141.addWidget(self.check_toolButton_4, 1, 7, 1, 1) spacerItem32 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_141.addItem(spacerItem32, 1, 6, 1, 1) self.gridLayout_117.addLayout(self.gridLayout_141, 2, 1, 1, 1) self.gridLayout_116.addLayout(self.gridLayout_117, 3, 0, 1, 7) self.checkBox_band_8 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_8.setChecked(True) self.checkBox_band_8.setObjectName("checkBox_band_8") self.gridLayout_116.addWidget(self.checkBox_band_8, 2, 1, 1, 1) self.checkBox_band_10 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_10.setChecked(True) self.checkBox_band_10.setObjectName("checkBox_band_10") self.gridLayout_116.addWidget(self.checkBox_band_10, 2, 3, 1, 1) self.checkBox_band_9 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_9.setChecked(True) self.checkBox_band_9.setObjectName("checkBox_band_9") self.gridLayout_116.addWidget(self.checkBox_band_9, 2, 2, 1, 1) self.checkBox_band_7 = QtWidgets.QCheckBox(self.tab_options) self.checkBox_band_7.setChecked(True) self.checkBox_band_7.setObjectName("checkBox_band_7") self.gridLayout_116.addWidget(self.checkBox_band_7, 2, 0, 1, 1) self.gridLayout_199.addLayout(self.gridLayout_116, 0, 0, 1, 1) icon80 = QtGui.QIcon() icon80.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_download_options.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.tabWidget_3.addTab(self.tab_options, icon80, "") self.gridLayout_113.addWidget(self.tabWidget_3, 0, 1, 1, 1) self.gridLayout_68.addLayout(self.gridLayout_113, 0, 0, 1, 1) self.gridLayout_320 = QtWidgets.QGridLayout() self.gridLayout_320.setObjectName("gridLayout_320") self.label_258 = QtWidgets.QLabel(self.tab_download_products) self.label_258.setStyleSheet("background-color : #656565; color : white") self.label_258.setFrameShape(QtWidgets.QFrame.Panel) self.label_258.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_258.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_258.setOpenExternalLinks(True) self.label_258.setObjectName("label_258") self.gridLayout_320.addWidget(self.label_258, 0, 0, 1, 8) self.preprocess_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.preprocess_checkBox.setChecked(True) self.preprocess_checkBox.setObjectName("preprocess_checkBox") self.gridLayout_320.addWidget(self.preprocess_checkBox, 1, 2, 1, 1) self.load_in_QGIS_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.load_in_QGIS_checkBox.setChecked(True) self.load_in_QGIS_checkBox.setObjectName("load_in_QGIS_checkBox") self.gridLayout_320.addWidget(self.load_in_QGIS_checkBox, 1, 3, 1, 1) self.download_if_preview_in_legend_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.download_if_preview_in_legend_checkBox.setChecked(True) self.download_if_preview_in_legend_checkBox.setObjectName("download_if_preview_in_legend_checkBox") self.gridLayout_320.addWidget(self.download_if_preview_in_legend_checkBox, 1, 1, 1, 1) spacerItem33 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_320.addItem(spacerItem33, 1, 5, 1, 1) self.export_links_Button = QtWidgets.QToolButton(self.tab_download_products) self.export_links_Button.setStyleSheet("margin: 0px;padding: 0px;") self.export_links_Button.setIcon(icon53) self.export_links_Button.setIconSize(QtCore.QSize(22, 22)) self.export_links_Button.setObjectName("export_links_Button") self.gridLayout_320.addWidget(self.export_links_Button, 1, 6, 1, 1) self.download_images_Button = QtWidgets.QToolButton(self.tab_download_products) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.download_images_Button.setFont(font) self.download_images_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.download_images_Button.setStyleSheet("margin: 0px;padding: 0px;") self.download_images_Button.setIcon(icon64) self.download_images_Button.setIconSize(QtCore.QSize(34, 34)) self.download_images_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.download_images_Button.setObjectName("download_images_Button") self.gridLayout_320.addWidget(self.download_images_Button, 1, 7, 1, 1) self.virtual_download_checkBox = QtWidgets.QCheckBox(self.tab_download_products) self.virtual_download_checkBox.setObjectName("virtual_download_checkBox") self.gridLayout_320.addWidget(self.virtual_download_checkBox, 1, 4, 1, 1) self.gridLayout_68.addLayout(self.gridLayout_320, 1, 0, 1, 1) self.SCP_tabs.addTab(self.tab_download_products, "") self.tab_preprocessing = QtWidgets.QWidget() self.tab_preprocessing.setStyleSheet("") self.tab_preprocessing.setObjectName("tab_preprocessing") self.gridLayout_6 = QtWidgets.QGridLayout(self.tab_preprocessing) self.gridLayout_6.setObjectName("gridLayout_6") self.tabWidget_preprocessing = QtWidgets.QTabWidget(self.tab_preprocessing) self.tabWidget_preprocessing.setStyleSheet("") self.tabWidget_preprocessing.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_preprocessing.setDocumentMode(True) self.tabWidget_preprocessing.setObjectName("tabWidget_preprocessing") self.tab_Landsat = QtWidgets.QWidget() self.tab_Landsat.setObjectName("tab_Landsat") self.gridLayout_18 = QtWidgets.QGridLayout(self.tab_Landsat) self.gridLayout_18.setObjectName("gridLayout_18") self.gridLayout_37 = QtWidgets.QGridLayout() self.gridLayout_37.setObjectName("gridLayout_37") self.label_36 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_36.sizePolicy().hasHeightForWidth()) self.label_36.setSizePolicy(sizePolicy) self.label_36.setMinimumSize(QtCore.QSize(229, 0)) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_36.setFont(font) self.label_36.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_36.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_36.setObjectName("label_36") self.gridLayout_37.addWidget(self.label_36, 1, 0, 1, 1) self.label_37 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_37.sizePolicy().hasHeightForWidth()) self.label_37.setSizePolicy(sizePolicy) self.label_37.setStyleSheet("background-color : #656565; color : white") self.label_37.setFrameShape(QtWidgets.QFrame.Panel) self.label_37.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_37.setObjectName("label_37") self.gridLayout_37.addWidget(self.label_37, 0, 0, 1, 4) self.celsius_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.celsius_checkBox.setChecked(False) self.celsius_checkBox.setTristate(False) self.celsius_checkBox.setObjectName("celsius_checkBox") self.gridLayout_37.addWidget(self.celsius_checkBox, 3, 0, 1, 1) self.DOS1_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.DOS1_checkBox.setChecked(False) self.DOS1_checkBox.setTristate(False) self.DOS1_checkBox.setObjectName("DOS1_checkBox") self.gridLayout_37.addWidget(self.DOS1_checkBox, 4, 0, 1, 1) self.gridLayout_29 = QtWidgets.QGridLayout() self.gridLayout_29.setObjectName("gridLayout_29") self.nodata_spinBox_3 = QtWidgets.QSpinBox(self.tab_Landsat) self.nodata_spinBox_3.setMinimum(-999) self.nodata_spinBox_3.setMaximum(100000) self.nodata_spinBox_3.setObjectName("nodata_spinBox_3") self.gridLayout_29.addWidget(self.nodata_spinBox_3, 0, 2, 1, 1) self.nodata_checkBox_2 = QtWidgets.QCheckBox(self.tab_Landsat) self.nodata_checkBox_2.setChecked(True) self.nodata_checkBox_2.setObjectName("nodata_checkBox_2") self.gridLayout_29.addWidget(self.nodata_checkBox_2, 0, 1, 1, 1) spacerItem34 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_29.addItem(spacerItem34, 0, 0, 1, 1) self.gridLayout_37.addLayout(self.gridLayout_29, 4, 1, 1, 3) self.label_41 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_41.sizePolicy().hasHeightForWidth()) self.label_41.setSizePolicy(sizePolicy) self.label_41.setMinimumSize(QtCore.QSize(229, 0)) self.label_41.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_41.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_41.setObjectName("label_41") self.gridLayout_37.addWidget(self.label_41, 2, 0, 1, 1) self.toolButton_directoryInput = QtWidgets.QToolButton(self.tab_Landsat) self.toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput.setIcon(icon69) self.toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput.setObjectName("toolButton_directoryInput") self.gridLayout_37.addWidget(self.toolButton_directoryInput, 1, 3, 1, 1) self.label_26 = QtWidgets.QLabel(self.tab_Landsat) self.label_26.setFrameShape(QtWidgets.QFrame.Panel) self.label_26.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_26.setText("") self.label_26.setObjectName("label_26") self.gridLayout_37.addWidget(self.label_26, 1, 1, 1, 2) self.label_27 = QtWidgets.QLabel(self.tab_Landsat) self.label_27.setFrameShape(QtWidgets.QFrame.Panel) self.label_27.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_27.setText("") self.label_27.setObjectName("label_27") self.gridLayout_37.addWidget(self.label_27, 2, 1, 1, 2) self.gridLayout_183 = QtWidgets.QGridLayout() self.gridLayout_183.setObjectName("gridLayout_183") self.pansharpening_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.pansharpening_checkBox.setChecked(False) self.pansharpening_checkBox.setTristate(False) self.pansharpening_checkBox.setObjectName("pansharpening_checkBox") self.gridLayout_183.addWidget(self.pansharpening_checkBox, 0, 0, 1, 1) self.create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Landsat) self.create_bandset_checkBox.setChecked(True) self.create_bandset_checkBox.setTristate(False) self.create_bandset_checkBox.setObjectName("create_bandset_checkBox") self.gridLayout_183.addWidget(self.create_bandset_checkBox, 1, 0, 1, 1) self.add_new_bandset_checkBox_1 = QtWidgets.QCheckBox(self.tab_Landsat) self.add_new_bandset_checkBox_1.setChecked(True) self.add_new_bandset_checkBox_1.setTristate(False) self.add_new_bandset_checkBox_1.setObjectName("add_new_bandset_checkBox_1") self.gridLayout_183.addWidget(self.add_new_bandset_checkBox_1, 1, 1, 1, 1) spacerItem35 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_183.addItem(spacerItem35, 1, 2, 1, 1) self.gridLayout_37.addLayout(self.gridLayout_183, 5, 0, 1, 4) self.toolButton_directoryInput_MTL = QtWidgets.QToolButton(self.tab_Landsat) self.toolButton_directoryInput_MTL.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput_MTL.setIcon(icon65) self.toolButton_directoryInput_MTL.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput_MTL.setObjectName("toolButton_directoryInput_MTL") self.gridLayout_37.addWidget(self.toolButton_directoryInput_MTL, 2, 3, 1, 1) self.gridLayout_18.addLayout(self.gridLayout_37, 0, 0, 1, 1) self.gridLayout_95 = QtWidgets.QGridLayout() self.gridLayout_95.setObjectName("gridLayout_95") self.landsat_tableWidget = QtWidgets.QTableWidget(self.tab_Landsat) self.landsat_tableWidget.setObjectName("landsat_tableWidget") self.landsat_tableWidget.setColumnCount(13) self.landsat_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(2, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(3, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(4, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(5, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(6, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(7, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(8, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(9, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(10, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(11, item) item = QtWidgets.QTableWidgetItem() self.landsat_tableWidget.setHorizontalHeaderItem(12, item) self.landsat_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.gridLayout_95.addWidget(self.landsat_tableWidget, 1, 0, 1, 1) self.gridLayout_15 = QtWidgets.QGridLayout() self.gridLayout_15.setObjectName("gridLayout_15") self.pushButton_remove_band = QtWidgets.QToolButton(self.tab_Landsat) self.pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_remove_band.setIcon(icon58) self.pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.pushButton_remove_band.setObjectName("pushButton_remove_band") self.gridLayout_15.addWidget(self.pushButton_remove_band, 0, 0, 1, 1) self.gridLayout_95.addLayout(self.gridLayout_15, 1, 1, 1, 1) self.gridLayout_98 = QtWidgets.QGridLayout() self.gridLayout_98.setObjectName("gridLayout_98") self.satellite_label = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label.sizePolicy().hasHeightForWidth()) self.satellite_label.setSizePolicy(sizePolicy) self.satellite_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label.setObjectName("satellite_label") self.gridLayout_98.addWidget(self.satellite_label, 1, 0, 1, 1) self.satellite_label_3 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_3.sizePolicy().hasHeightForWidth()) self.satellite_label_3.setSizePolicy(sizePolicy) self.satellite_label_3.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_3.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_3.setObjectName("satellite_label_3") self.gridLayout_98.addWidget(self.satellite_label_3, 1, 4, 1, 1) self.date_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.date_lineEdit.setObjectName("date_lineEdit") self.gridLayout_98.addWidget(self.date_lineEdit, 1, 3, 1, 1) self.satellite_label_2 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_2.sizePolicy().hasHeightForWidth()) self.satellite_label_2.setSizePolicy(sizePolicy) self.satellite_label_2.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_2.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_2.setObjectName("satellite_label_2") self.gridLayout_98.addWidget(self.satellite_label_2, 1, 2, 1, 1) self.satellite_label_4 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_4.sizePolicy().hasHeightForWidth()) self.satellite_label_4.setSizePolicy(sizePolicy) self.satellite_label_4.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_4.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_4.setObjectName("satellite_label_4") self.gridLayout_98.addWidget(self.satellite_label_4, 1, 6, 1, 1) self.sun_elev_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.sun_elev_lineEdit.setObjectName("sun_elev_lineEdit") self.gridLayout_98.addWidget(self.sun_elev_lineEdit, 1, 5, 1, 1) self.earth_sun_dist_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.earth_sun_dist_lineEdit.setObjectName("earth_sun_dist_lineEdit") self.gridLayout_98.addWidget(self.earth_sun_dist_lineEdit, 1, 7, 1, 1) self.label_74 = QtWidgets.QLabel(self.tab_Landsat) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_74.sizePolicy().hasHeightForWidth()) self.label_74.setSizePolicy(sizePolicy) self.label_74.setStyleSheet("background-color : #656565; color : white") self.label_74.setFrameShape(QtWidgets.QFrame.Panel) self.label_74.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_74.setObjectName("label_74") self.gridLayout_98.addWidget(self.label_74, 0, 0, 1, 9) self.satellite_lineEdit = QtWidgets.QLineEdit(self.tab_Landsat) self.satellite_lineEdit.setObjectName("satellite_lineEdit") self.gridLayout_98.addWidget(self.satellite_lineEdit, 1, 1, 1, 1) self.gridLayout_95.addLayout(self.gridLayout_98, 0, 0, 1, 2) self.gridLayout_18.addLayout(self.gridLayout_95, 1, 0, 1, 1) self.gridLayout_97 = QtWidgets.QGridLayout() self.gridLayout_97.setObjectName("gridLayout_97") spacerItem36 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_97.addItem(spacerItem36, 1, 1, 1, 1) self.label_161 = QtWidgets.QLabel(self.tab_Landsat) self.label_161.setStyleSheet("background-color : #656565; color : white") self.label_161.setFrameShape(QtWidgets.QFrame.Panel) self.label_161.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_161.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_161.setObjectName("label_161") self.gridLayout_97.addWidget(self.label_161, 0, 1, 1, 3) self.pushButton_Conversion = QtWidgets.QToolButton(self.tab_Landsat) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion.setFont(font) self.pushButton_Conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion.setIcon(icon64) self.pushButton_Conversion.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion.setObjectName("pushButton_Conversion") self.gridLayout_97.addWidget(self.pushButton_Conversion, 1, 3, 1, 1) self.landsat_conversion = QtWidgets.QToolButton(self.tab_Landsat) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.landsat_conversion.setFont(font) self.landsat_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.landsat_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.landsat_conversion.setIcon(icon48) self.landsat_conversion.setIconSize(QtCore.QSize(34, 34)) self.landsat_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.landsat_conversion.setObjectName("landsat_conversion") self.gridLayout_97.addWidget(self.landsat_conversion, 1, 2, 1, 1) self.gridLayout_18.addLayout(self.gridLayout_97, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Landsat, "") self.tab_Sentinel1 = QtWidgets.QWidget() self.tab_Sentinel1.setObjectName("tab_Sentinel1") self.gridLayout_167 = QtWidgets.QGridLayout(self.tab_Sentinel1) self.gridLayout_167.setObjectName("gridLayout_167") self.gridLayout_265 = QtWidgets.QGridLayout() self.gridLayout_265.setObjectName("gridLayout_265") self.gridLayout_279 = QtWidgets.QGridLayout() self.gridLayout_279.setObjectName("gridLayout_279") self.S1_label_95 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_95.sizePolicy().hasHeightForWidth()) self.S1_label_95.setSizePolicy(sizePolicy) self.S1_label_95.setMinimumSize(QtCore.QSize(229, 0)) self.S1_label_95.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_95.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.S1_label_95.setObjectName("S1_label_95") self.gridLayout_279.addWidget(self.S1_label_95, 0, 0, 1, 1) self.S1_label_96 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_96.sizePolicy().hasHeightForWidth()) self.S1_label_96.setSizePolicy(sizePolicy) self.S1_label_96.setFrameShape(QtWidgets.QFrame.Panel) self.S1_label_96.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_96.setText("") self.S1_label_96.setObjectName("S1_label_96") self.gridLayout_279.addWidget(self.S1_label_96, 0, 1, 1, 1) self.S1_toolButton_directoryInput_xml = QtWidgets.QToolButton(self.tab_Sentinel1) self.S1_toolButton_directoryInput_xml.setStyleSheet("margin: 0px;padding: 0px;") self.S1_toolButton_directoryInput_xml.setIcon(icon65) self.S1_toolButton_directoryInput_xml.setIconSize(QtCore.QSize(22, 22)) self.S1_toolButton_directoryInput_xml.setObjectName("S1_toolButton_directoryInput_xml") self.gridLayout_279.addWidget(self.S1_toolButton_directoryInput_xml, 0, 2, 1, 1) self.horizontalLayout_48 = QtWidgets.QHBoxLayout() self.horizontalLayout_48.setObjectName("horizontalLayout_48") self.S1_label_97 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_97.sizePolicy().hasHeightForWidth()) self.S1_label_97.setSizePolicy(sizePolicy) self.S1_label_97.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_97.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.S1_label_97.setObjectName("S1_label_97") self.horizontalLayout_48.addWidget(self.S1_label_97) self.VH_checkBox_S1 = QtWidgets.QCheckBox(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.VH_checkBox_S1.sizePolicy().hasHeightForWidth()) self.VH_checkBox_S1.setSizePolicy(sizePolicy) self.VH_checkBox_S1.setChecked(True) self.VH_checkBox_S1.setTristate(False) self.VH_checkBox_S1.setObjectName("VH_checkBox_S1") self.horizontalLayout_48.addWidget(self.VH_checkBox_S1) self.VV_checkBox_S1 = QtWidgets.QCheckBox(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.VV_checkBox_S1.sizePolicy().hasHeightForWidth()) self.VV_checkBox_S1.setSizePolicy(sizePolicy) self.VV_checkBox_S1.setChecked(True) self.VV_checkBox_S1.setTristate(False) self.VV_checkBox_S1.setObjectName("VV_checkBox_S1") self.horizontalLayout_48.addWidget(self.VV_checkBox_S1) self.gridLayout_279.addLayout(self.horizontalLayout_48, 1, 0, 1, 1) self.gridLayout_265.addLayout(self.gridLayout_279, 3, 0, 1, 3) self.label_209 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_209.sizePolicy().hasHeightForWidth()) self.label_209.setSizePolicy(sizePolicy) self.label_209.setStyleSheet("background-color : #656565; color : white") self.label_209.setFrameShape(QtWidgets.QFrame.Panel) self.label_209.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_209.setObjectName("label_209") self.gridLayout_265.addWidget(self.label_209, 0, 0, 1, 3) self.S1_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel1) self.S1_create_bandset_checkBox.setChecked(True) self.S1_create_bandset_checkBox.setTristate(False) self.S1_create_bandset_checkBox.setObjectName("S1_create_bandset_checkBox") self.gridLayout_265.addWidget(self.S1_create_bandset_checkBox, 5, 0, 1, 1) self.add_new_bandset_checkBox_6 = QtWidgets.QCheckBox(self.tab_Sentinel1) self.add_new_bandset_checkBox_6.setChecked(True) self.add_new_bandset_checkBox_6.setTristate(False) self.add_new_bandset_checkBox_6.setObjectName("add_new_bandset_checkBox_6") self.gridLayout_265.addWidget(self.add_new_bandset_checkBox_6, 5, 1, 1, 2) self.gridLayout_266 = QtWidgets.QGridLayout() self.gridLayout_266.setObjectName("gridLayout_266") self.S1_label_87 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S1_label_87.sizePolicy().hasHeightForWidth()) self.S1_label_87.setSizePolicy(sizePolicy) self.S1_label_87.setFrameShape(QtWidgets.QFrame.Panel) self.S1_label_87.setFrameShadow(QtWidgets.QFrame.Sunken) self.S1_label_87.setText("") self.S1_label_87.setObjectName("S1_label_87") self.gridLayout_266.addWidget(self.S1_label_87, 0, 1, 1, 1) self.S1_toolButton_fileInput = QtWidgets.QToolButton(self.tab_Sentinel1) self.S1_toolButton_fileInput.setStyleSheet("margin: 0px;padding: 0px;") self.S1_toolButton_fileInput.setIcon(icon65) self.S1_toolButton_fileInput.setIconSize(QtCore.QSize(22, 22)) self.S1_toolButton_fileInput.setObjectName("S1_toolButton_fileInput") self.gridLayout_266.addWidget(self.S1_toolButton_fileInput, 0, 2, 1, 1) self.label_207 = QtWidgets.QLabel(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_207.sizePolicy().hasHeightForWidth()) self.label_207.setSizePolicy(sizePolicy) self.label_207.setMinimumSize(QtCore.QSize(229, 0)) self.label_207.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_207.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_207.setObjectName("label_207") self.gridLayout_266.addWidget(self.label_207, 0, 0, 1, 1) self.gridLayout_265.addLayout(self.gridLayout_266, 2, 0, 1, 3) self.horizontalLayout_46 = QtWidgets.QHBoxLayout() self.horizontalLayout_46.setObjectName("horizontalLayout_46") self.projection_checkBox_S1 = QtWidgets.QCheckBox(self.tab_Sentinel1) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.projection_checkBox_S1.sizePolicy().hasHeightForWidth()) self.projection_checkBox_S1.setSizePolicy(sizePolicy) self.projection_checkBox_S1.setTristate(False) self.projection_checkBox_S1.setObjectName("projection_checkBox_S1") self.horizontalLayout_46.addWidget(self.projection_checkBox_S1) self.band_set_comb_spinBox_11 = QtWidgets.QSpinBox(self.tab_Sentinel1) self.band_set_comb_spinBox_11.setMinimum(1) self.band_set_comb_spinBox_11.setMaximum(100000) self.band_set_comb_spinBox_11.setObjectName("band_set_comb_spinBox_11") self.horizontalLayout_46.addWidget(self.band_set_comb_spinBox_11) spacerItem37 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_46.addItem(spacerItem37) self.convert_to_db_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel1) self.convert_to_db_checkBox.setChecked(True) self.convert_to_db_checkBox.setTristate(False) self.convert_to_db_checkBox.setObjectName("convert_to_db_checkBox") self.horizontalLayout_46.addWidget(self.convert_to_db_checkBox) spacerItem38 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_46.addItem(spacerItem38) self.S1_nodata_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel1) self.S1_nodata_checkBox.setChecked(True) self.S1_nodata_checkBox.setObjectName("S1_nodata_checkBox") self.horizontalLayout_46.addWidget(self.S1_nodata_checkBox) self.S1_nodata_spinBox = QtWidgets.QSpinBox(self.tab_Sentinel1) self.S1_nodata_spinBox.setMinimum(-999) self.S1_nodata_spinBox.setMaximum(100000) self.S1_nodata_spinBox.setObjectName("S1_nodata_spinBox") self.horizontalLayout_46.addWidget(self.S1_nodata_spinBox) self.gridLayout_265.addLayout(self.horizontalLayout_46, 4, 0, 1, 3) self.gridLayout_167.addLayout(self.gridLayout_265, 0, 0, 1, 1) spacerItem39 = QtWidgets.QSpacerItem(20, 296, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_167.addItem(spacerItem39, 1, 0, 1, 1) self.gridLayout_268 = QtWidgets.QGridLayout() self.gridLayout_268.setObjectName("gridLayout_268") self.label_210 = QtWidgets.QLabel(self.tab_Sentinel1) self.label_210.setStyleSheet("background-color : #656565; color : white") self.label_210.setFrameShape(QtWidgets.QFrame.Panel) self.label_210.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_210.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_210.setObjectName("label_210") self.gridLayout_268.addWidget(self.label_210, 0, 0, 1, 3) spacerItem40 = QtWidgets.QSpacerItem(782, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_268.addItem(spacerItem40, 1, 0, 1, 1) self.pushButton_Conversion_6 = QtWidgets.QToolButton(self.tab_Sentinel1) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_6.setFont(font) self.pushButton_Conversion_6.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_6.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_6.setIcon(icon64) self.pushButton_Conversion_6.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_6.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_6.setObjectName("pushButton_Conversion_6") self.gridLayout_268.addWidget(self.pushButton_Conversion_6, 1, 2, 1, 1) self.sentinel1_conversion = QtWidgets.QToolButton(self.tab_Sentinel1) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sentinel1_conversion.setFont(font) self.sentinel1_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.sentinel1_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.sentinel1_conversion.setIcon(icon48) self.sentinel1_conversion.setIconSize(QtCore.QSize(34, 34)) self.sentinel1_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sentinel1_conversion.setObjectName("sentinel1_conversion") self.gridLayout_268.addWidget(self.sentinel1_conversion, 1, 1, 1, 1) self.gridLayout_167.addLayout(self.gridLayout_268, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Sentinel1, "") self.tab_Sentinel2 = QtWidgets.QWidget() self.tab_Sentinel2.setObjectName("tab_Sentinel2") self.gridLayout_164 = QtWidgets.QGridLayout(self.tab_Sentinel2) self.gridLayout_164.setObjectName("gridLayout_164") self.gridLayout_146 = QtWidgets.QGridLayout() self.gridLayout_146.setObjectName("gridLayout_146") self.label_90 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_90.sizePolicy().hasHeightForWidth()) self.label_90.setSizePolicy(sizePolicy) self.label_90.setMinimumSize(QtCore.QSize(229, 0)) self.label_90.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_90.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_90.setObjectName("label_90") self.gridLayout_146.addWidget(self.label_90, 1, 0, 1, 1) self.gridLayout_147 = QtWidgets.QGridLayout() self.gridLayout_147.setObjectName("gridLayout_147") self.S2_toolButton_directoryInput = QtWidgets.QToolButton(self.tab_Sentinel2) self.S2_toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.S2_toolButton_directoryInput.setIcon(icon69) self.S2_toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.S2_toolButton_directoryInput.setObjectName("S2_toolButton_directoryInput") self.gridLayout_147.addWidget(self.S2_toolButton_directoryInput, 0, 1, 1, 1) self.S2_label_86 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S2_label_86.sizePolicy().hasHeightForWidth()) self.S2_label_86.setSizePolicy(sizePolicy) self.S2_label_86.setFrameShape(QtWidgets.QFrame.Panel) self.S2_label_86.setFrameShadow(QtWidgets.QFrame.Sunken) self.S2_label_86.setText("") self.S2_label_86.setObjectName("S2_label_86") self.gridLayout_147.addWidget(self.S2_label_86, 0, 0, 1, 1) self.gridLayout_146.addLayout(self.gridLayout_147, 1, 1, 1, 2) self.DOS1_checkBox_S2 = QtWidgets.QCheckBox(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.DOS1_checkBox_S2.sizePolicy().hasHeightForWidth()) self.DOS1_checkBox_S2.setSizePolicy(sizePolicy) self.DOS1_checkBox_S2.setChecked(False) self.DOS1_checkBox_S2.setTristate(False) self.DOS1_checkBox_S2.setObjectName("DOS1_checkBox_S2") self.gridLayout_146.addWidget(self.DOS1_checkBox_S2, 3, 0, 1, 1) self.gridLayout_148 = QtWidgets.QGridLayout() self.gridLayout_148.setObjectName("gridLayout_148") self.S2_nodata_spinBox = QtWidgets.QSpinBox(self.tab_Sentinel2) self.S2_nodata_spinBox.setMinimum(-999) self.S2_nodata_spinBox.setMaximum(100000) self.S2_nodata_spinBox.setObjectName("S2_nodata_spinBox") self.gridLayout_148.addWidget(self.S2_nodata_spinBox, 0, 2, 1, 1) self.S2_nodata_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel2) self.S2_nodata_checkBox.setChecked(True) self.S2_nodata_checkBox.setObjectName("S2_nodata_checkBox") self.gridLayout_148.addWidget(self.S2_nodata_checkBox, 0, 1, 1, 1) spacerItem41 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_148.addItem(spacerItem41, 0, 0, 1, 1) self.gridLayout_146.addLayout(self.gridLayout_148, 3, 1, 1, 2) self.label_91 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_91.sizePolicy().hasHeightForWidth()) self.label_91.setSizePolicy(sizePolicy) self.label_91.setStyleSheet("background-color : #656565; color : white") self.label_91.setFrameShape(QtWidgets.QFrame.Panel) self.label_91.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_91.setObjectName("label_91") self.gridLayout_146.addWidget(self.label_91, 0, 0, 1, 3) self.S2_label_93 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S2_label_93.sizePolicy().hasHeightForWidth()) self.S2_label_93.setSizePolicy(sizePolicy) self.S2_label_93.setMinimumSize(QtCore.QSize(229, 0)) self.S2_label_93.setFrameShadow(QtWidgets.QFrame.Sunken) self.S2_label_93.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.S2_label_93.setObjectName("S2_label_93") self.gridLayout_146.addWidget(self.S2_label_93, 2, 0, 1, 1) self.gridLayout_156 = QtWidgets.QGridLayout() self.gridLayout_156.setObjectName("gridLayout_156") self.S2_label_94 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S2_label_94.sizePolicy().hasHeightForWidth()) self.S2_label_94.setSizePolicy(sizePolicy) self.S2_label_94.setFrameShape(QtWidgets.QFrame.Panel) self.S2_label_94.setFrameShadow(QtWidgets.QFrame.Sunken) self.S2_label_94.setText("") self.S2_label_94.setObjectName("S2_label_94") self.gridLayout_156.addWidget(self.S2_label_94, 0, 0, 1, 1) self.S2_toolButton_directoryInput_xml2 = QtWidgets.QToolButton(self.tab_Sentinel2) self.S2_toolButton_directoryInput_xml2.setStyleSheet("margin: 0px;padding: 0px;") self.S2_toolButton_directoryInput_xml2.setIcon(icon65) self.S2_toolButton_directoryInput_xml2.setIconSize(QtCore.QSize(22, 22)) self.S2_toolButton_directoryInput_xml2.setObjectName("S2_toolButton_directoryInput_xml2") self.gridLayout_156.addWidget(self.S2_toolButton_directoryInput_xml2, 0, 1, 1, 1) self.gridLayout_146.addLayout(self.gridLayout_156, 2, 1, 1, 2) self.S2_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel2) self.S2_create_bandset_checkBox.setChecked(True) self.S2_create_bandset_checkBox.setTristate(False) self.S2_create_bandset_checkBox.setObjectName("S2_create_bandset_checkBox") self.gridLayout_146.addWidget(self.S2_create_bandset_checkBox, 5, 0, 1, 1) self.add_new_bandset_checkBox_2 = QtWidgets.QCheckBox(self.tab_Sentinel2) self.add_new_bandset_checkBox_2.setChecked(True) self.add_new_bandset_checkBox_2.setTristate(False) self.add_new_bandset_checkBox_2.setObjectName("add_new_bandset_checkBox_2") self.gridLayout_146.addWidget(self.add_new_bandset_checkBox_2, 5, 1, 1, 2) self.preprocess_b_1_9_10_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel2) self.preprocess_b_1_9_10_checkBox.setTristate(False) self.preprocess_b_1_9_10_checkBox.setObjectName("preprocess_b_1_9_10_checkBox") self.gridLayout_146.addWidget(self.preprocess_b_1_9_10_checkBox, 4, 0, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_146, 0, 0, 1, 1) self.gridLayout_166 = QtWidgets.QGridLayout() self.gridLayout_166.setObjectName("gridLayout_166") self.S2_satellite_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel2) self.S2_satellite_lineEdit.setObjectName("S2_satellite_lineEdit") self.gridLayout_166.addWidget(self.S2_satellite_lineEdit, 1, 1, 1, 1) self.satellite_label_5 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_5.sizePolicy().hasHeightForWidth()) self.satellite_label_5.setSizePolicy(sizePolicy) self.satellite_label_5.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_5.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_5.setObjectName("satellite_label_5") self.gridLayout_166.addWidget(self.satellite_label_5, 1, 0, 1, 1) spacerItem42 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_166.addItem(spacerItem42, 1, 2, 1, 1) self.satellite_label_6 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_6.sizePolicy().hasHeightForWidth()) self.satellite_label_6.setSizePolicy(sizePolicy) self.satellite_label_6.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_6.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_6.setObjectName("satellite_label_6") self.gridLayout_166.addWidget(self.satellite_label_6, 1, 7, 1, 1) self.S2_product_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel2) self.S2_product_lineEdit.setObjectName("S2_product_lineEdit") self.gridLayout_166.addWidget(self.S2_product_lineEdit, 1, 8, 1, 1) self.label_92 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_92.sizePolicy().hasHeightForWidth()) self.label_92.setSizePolicy(sizePolicy) self.label_92.setStyleSheet("background-color : #656565; color : white") self.label_92.setFrameShape(QtWidgets.QFrame.Panel) self.label_92.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_92.setObjectName("label_92") self.gridLayout_166.addWidget(self.label_92, 0, 0, 1, 9) self.date_lineEdit_3 = QtWidgets.QLineEdit(self.tab_Sentinel2) self.date_lineEdit_3.setObjectName("date_lineEdit_3") self.gridLayout_166.addWidget(self.date_lineEdit_3, 1, 4, 1, 1) spacerItem43 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_166.addItem(spacerItem43, 1, 6, 1, 1) self.satellite_label_15 = QtWidgets.QLabel(self.tab_Sentinel2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_15.sizePolicy().hasHeightForWidth()) self.satellite_label_15.setSizePolicy(sizePolicy) self.satellite_label_15.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_15.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_15.setObjectName("satellite_label_15") self.gridLayout_166.addWidget(self.satellite_label_15, 1, 3, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_166, 1, 0, 1, 1) self.gridLayout_162 = QtWidgets.QGridLayout() self.gridLayout_162.setObjectName("gridLayout_162") self.sentinel_2_tableWidget = QtWidgets.QTableWidget(self.tab_Sentinel2) self.sentinel_2_tableWidget.setTextElideMode(QtCore.Qt.ElideMiddle) self.sentinel_2_tableWidget.setObjectName("sentinel_2_tableWidget") self.sentinel_2_tableWidget.setColumnCount(3) self.sentinel_2_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.sentinel_2_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.sentinel_2_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.sentinel_2_tableWidget.setHorizontalHeaderItem(2, item) self.sentinel_2_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.sentinel_2_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_162.addWidget(self.sentinel_2_tableWidget, 0, 0, 1, 1) self.S2_pushButton_remove_band = QtWidgets.QToolButton(self.tab_Sentinel2) self.S2_pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.S2_pushButton_remove_band.setIcon(icon58) self.S2_pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.S2_pushButton_remove_band.setObjectName("S2_pushButton_remove_band") self.gridLayout_162.addWidget(self.S2_pushButton_remove_band, 0, 1, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_162, 2, 0, 1, 1) self.gridLayout_165 = QtWidgets.QGridLayout() self.gridLayout_165.setObjectName("gridLayout_165") spacerItem44 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_165.addItem(spacerItem44, 1, 1, 1, 1) self.label_162 = QtWidgets.QLabel(self.tab_Sentinel2) self.label_162.setStyleSheet("background-color : #656565; color : white") self.label_162.setFrameShape(QtWidgets.QFrame.Panel) self.label_162.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_162.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_162.setObjectName("label_162") self.gridLayout_165.addWidget(self.label_162, 0, 1, 1, 3) self.pushButton_Conversion_2 = QtWidgets.QToolButton(self.tab_Sentinel2) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_2.setFont(font) self.pushButton_Conversion_2.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_2.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_2.setIcon(icon64) self.pushButton_Conversion_2.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_2.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_2.setObjectName("pushButton_Conversion_2") self.gridLayout_165.addWidget(self.pushButton_Conversion_2, 1, 3, 1, 1) self.sentinel2_conversion = QtWidgets.QToolButton(self.tab_Sentinel2) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sentinel2_conversion.setFont(font) self.sentinel2_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.sentinel2_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.sentinel2_conversion.setIcon(icon48) self.sentinel2_conversion.setIconSize(QtCore.QSize(34, 34)) self.sentinel2_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sentinel2_conversion.setObjectName("sentinel2_conversion") self.gridLayout_165.addWidget(self.sentinel2_conversion, 1, 2, 1, 1) self.gridLayout_164.addLayout(self.gridLayout_165, 3, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Sentinel2, "") self.tab_Sentinel3 = QtWidgets.QWidget() self.tab_Sentinel3.setObjectName("tab_Sentinel3") self.gridLayout_158 = QtWidgets.QGridLayout(self.tab_Sentinel3) self.gridLayout_158.setObjectName("gridLayout_158") self.gridLayout_153 = QtWidgets.QGridLayout() self.gridLayout_153.setObjectName("gridLayout_153") self.gridLayout_157 = QtWidgets.QGridLayout() self.gridLayout_157.setObjectName("gridLayout_157") self.S2_nodata_spinBox_2 = QtWidgets.QSpinBox(self.tab_Sentinel3) self.S2_nodata_spinBox_2.setMinimum(-999) self.S2_nodata_spinBox_2.setMaximum(100000) self.S2_nodata_spinBox_2.setObjectName("S2_nodata_spinBox_2") self.gridLayout_157.addWidget(self.S2_nodata_spinBox_2, 0, 2, 1, 1) self.S3_nodata_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel3) self.S3_nodata_checkBox.setChecked(True) self.S3_nodata_checkBox.setObjectName("S3_nodata_checkBox") self.gridLayout_157.addWidget(self.S3_nodata_checkBox, 0, 1, 1, 1) spacerItem45 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_157.addItem(spacerItem45, 0, 0, 1, 1) self.gridLayout_153.addLayout(self.gridLayout_157, 3, 1, 1, 2) self.label_109 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_109.sizePolicy().hasHeightForWidth()) self.label_109.setSizePolicy(sizePolicy) self.label_109.setStyleSheet("background-color : #656565; color : white") self.label_109.setFrameShape(QtWidgets.QFrame.Panel) self.label_109.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_109.setObjectName("label_109") self.gridLayout_153.addWidget(self.label_109, 0, 0, 1, 3) self.S3_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_Sentinel3) self.S3_create_bandset_checkBox.setChecked(True) self.S3_create_bandset_checkBox.setTristate(False) self.S3_create_bandset_checkBox.setObjectName("S3_create_bandset_checkBox") self.gridLayout_153.addWidget(self.S3_create_bandset_checkBox, 4, 0, 1, 1) self.label_106 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_106.sizePolicy().hasHeightForWidth()) self.label_106.setSizePolicy(sizePolicy) self.label_106.setMinimumSize(QtCore.QSize(229, 0)) self.label_106.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_106.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_106.setObjectName("label_106") self.gridLayout_153.addWidget(self.label_106, 2, 0, 1, 1) self.gridLayout_155 = QtWidgets.QGridLayout() self.gridLayout_155.setObjectName("gridLayout_155") self.S3_toolButton_directoryInput = QtWidgets.QToolButton(self.tab_Sentinel3) self.S3_toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.S3_toolButton_directoryInput.setIcon(icon69) self.S3_toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.S3_toolButton_directoryInput.setObjectName("S3_toolButton_directoryInput") self.gridLayout_155.addWidget(self.S3_toolButton_directoryInput, 0, 1, 1, 1) self.S3_label_87 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.S3_label_87.sizePolicy().hasHeightForWidth()) self.S3_label_87.setSizePolicy(sizePolicy) self.S3_label_87.setFrameShape(QtWidgets.QFrame.Panel) self.S3_label_87.setFrameShadow(QtWidgets.QFrame.Sunken) self.S3_label_87.setText("") self.S3_label_87.setObjectName("S3_label_87") self.gridLayout_155.addWidget(self.S3_label_87, 0, 0, 1, 1) self.gridLayout_153.addLayout(self.gridLayout_155, 2, 1, 1, 2) self.DOS1_checkBox_S3 = QtWidgets.QCheckBox(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.DOS1_checkBox_S3.sizePolicy().hasHeightForWidth()) self.DOS1_checkBox_S3.setSizePolicy(sizePolicy) self.DOS1_checkBox_S3.setChecked(False) self.DOS1_checkBox_S3.setTristate(False) self.DOS1_checkBox_S3.setObjectName("DOS1_checkBox_S3") self.gridLayout_153.addWidget(self.DOS1_checkBox_S3, 3, 0, 1, 1) self.add_new_bandset_checkBox_3 = QtWidgets.QCheckBox(self.tab_Sentinel3) self.add_new_bandset_checkBox_3.setChecked(True) self.add_new_bandset_checkBox_3.setTristate(False) self.add_new_bandset_checkBox_3.setObjectName("add_new_bandset_checkBox_3") self.gridLayout_153.addWidget(self.add_new_bandset_checkBox_3, 4, 1, 1, 2) self.gridLayout_158.addLayout(self.gridLayout_153, 0, 0, 1, 1) self.gridLayout_212 = QtWidgets.QGridLayout() self.gridLayout_212.setObjectName("gridLayout_212") self.sentinel_3_tableWidget = QtWidgets.QTableWidget(self.tab_Sentinel3) self.sentinel_3_tableWidget.setTextElideMode(QtCore.Qt.ElideMiddle) self.sentinel_3_tableWidget.setObjectName("sentinel_3_tableWidget") self.sentinel_3_tableWidget.setColumnCount(1) self.sentinel_3_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.sentinel_3_tableWidget.setHorizontalHeaderItem(0, item) self.sentinel_3_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.sentinel_3_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_212.addWidget(self.sentinel_3_tableWidget, 1, 0, 1, 1) self.gridLayout_229 = QtWidgets.QGridLayout() self.gridLayout_229.setObjectName("gridLayout_229") self.S3_pushButton_remove_band = QtWidgets.QToolButton(self.tab_Sentinel3) self.S3_pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.S3_pushButton_remove_band.setIcon(icon58) self.S3_pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.S3_pushButton_remove_band.setObjectName("S3_pushButton_remove_band") self.gridLayout_229.addWidget(self.S3_pushButton_remove_band, 0, 0, 1, 1) self.gridLayout_212.addLayout(self.gridLayout_229, 1, 1, 1, 1) self.gridLayout_230 = QtWidgets.QGridLayout() self.gridLayout_230.setObjectName("gridLayout_230") self.S3_satellite_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel3) self.S3_satellite_lineEdit.setObjectName("S3_satellite_lineEdit") self.gridLayout_230.addWidget(self.S3_satellite_lineEdit, 1, 1, 1, 1) self.satellite_label_12 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_12.sizePolicy().hasHeightForWidth()) self.satellite_label_12.setSizePolicy(sizePolicy) self.satellite_label_12.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_12.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_12.setObjectName("satellite_label_12") self.gridLayout_230.addWidget(self.satellite_label_12, 1, 0, 1, 1) spacerItem46 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_230.addItem(spacerItem46, 1, 2, 1, 1) self.satellite_label_14 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_14.sizePolicy().hasHeightForWidth()) self.satellite_label_14.setSizePolicy(sizePolicy) self.satellite_label_14.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_14.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_14.setObjectName("satellite_label_14") self.gridLayout_230.addWidget(self.satellite_label_14, 1, 3, 1, 1) self.S3_product_lineEdit = QtWidgets.QLineEdit(self.tab_Sentinel3) self.S3_product_lineEdit.setObjectName("S3_product_lineEdit") self.gridLayout_230.addWidget(self.S3_product_lineEdit, 1, 4, 1, 1) self.label_115 = QtWidgets.QLabel(self.tab_Sentinel3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_115.sizePolicy().hasHeightForWidth()) self.label_115.setSizePolicy(sizePolicy) self.label_115.setStyleSheet("background-color : #656565; color : white") self.label_115.setFrameShape(QtWidgets.QFrame.Panel) self.label_115.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_115.setObjectName("label_115") self.gridLayout_230.addWidget(self.label_115, 0, 0, 1, 5) self.gridLayout_212.addLayout(self.gridLayout_230, 0, 0, 1, 2) self.gridLayout_232 = QtWidgets.QGridLayout() self.gridLayout_232.setObjectName("gridLayout_232") spacerItem47 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_232.addItem(spacerItem47, 1, 1, 1, 1) self.label_181 = QtWidgets.QLabel(self.tab_Sentinel3) self.label_181.setStyleSheet("background-color : #656565; color : white") self.label_181.setFrameShape(QtWidgets.QFrame.Panel) self.label_181.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_181.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_181.setObjectName("label_181") self.gridLayout_232.addWidget(self.label_181, 0, 1, 1, 3) self.pushButton_Conversion_5 = QtWidgets.QToolButton(self.tab_Sentinel3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_5.setFont(font) self.pushButton_Conversion_5.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_5.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_5.setIcon(icon64) self.pushButton_Conversion_5.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_5.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_5.setObjectName("pushButton_Conversion_5") self.gridLayout_232.addWidget(self.pushButton_Conversion_5, 1, 3, 1, 1) self.sentinel3_conversion = QtWidgets.QToolButton(self.tab_Sentinel3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sentinel3_conversion.setFont(font) self.sentinel3_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.sentinel3_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.sentinel3_conversion.setIcon(icon48) self.sentinel3_conversion.setIconSize(QtCore.QSize(34, 34)) self.sentinel3_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sentinel3_conversion.setObjectName("sentinel3_conversion") self.gridLayout_232.addWidget(self.sentinel3_conversion, 1, 2, 1, 1) self.gridLayout_212.addLayout(self.gridLayout_232, 2, 0, 1, 2) self.gridLayout_158.addLayout(self.gridLayout_212, 1, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_Sentinel3, "") self.tab_ASTER = QtWidgets.QWidget() self.tab_ASTER.setObjectName("tab_ASTER") self.gridLayout_118 = QtWidgets.QGridLayout(self.tab_ASTER) self.gridLayout_118.setObjectName("gridLayout_118") self.gridLayout_92 = QtWidgets.QGridLayout() self.gridLayout_92.setObjectName("gridLayout_92") self.gridLayout_94 = QtWidgets.QGridLayout() self.gridLayout_94.setObjectName("gridLayout_94") self.nodata_spinBox_6 = QtWidgets.QSpinBox(self.tab_ASTER) self.nodata_spinBox_6.setMinimum(-999) self.nodata_spinBox_6.setMaximum(100000) self.nodata_spinBox_6.setObjectName("nodata_spinBox_6") self.gridLayout_94.addWidget(self.nodata_spinBox_6, 0, 2, 1, 1) self.nodata_checkBox_5 = QtWidgets.QCheckBox(self.tab_ASTER) self.nodata_checkBox_5.setChecked(True) self.nodata_checkBox_5.setObjectName("nodata_checkBox_5") self.gridLayout_94.addWidget(self.nodata_checkBox_5, 0, 1, 1, 1) spacerItem48 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_94.addItem(spacerItem48, 0, 0, 1, 1) self.gridLayout_92.addLayout(self.gridLayout_94, 3, 1, 1, 3) self.label_143 = QtWidgets.QLabel(self.tab_ASTER) self.label_143.setFrameShape(QtWidgets.QFrame.Panel) self.label_143.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_143.setText("") self.label_143.setObjectName("label_143") self.gridLayout_92.addWidget(self.label_143, 1, 1, 1, 2) self.toolButton_directoryInput_ASTER = QtWidgets.QToolButton(self.tab_ASTER) self.toolButton_directoryInput_ASTER.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput_ASTER.setIcon(icon65) self.toolButton_directoryInput_ASTER.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput_ASTER.setObjectName("toolButton_directoryInput_ASTER") self.gridLayout_92.addWidget(self.toolButton_directoryInput_ASTER, 1, 3, 1, 1) self.DOS1_checkBox_2 = QtWidgets.QCheckBox(self.tab_ASTER) self.DOS1_checkBox_2.setChecked(False) self.DOS1_checkBox_2.setTristate(False) self.DOS1_checkBox_2.setObjectName("DOS1_checkBox_2") self.gridLayout_92.addWidget(self.DOS1_checkBox_2, 3, 0, 1, 1) self.label_67 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_67.sizePolicy().hasHeightForWidth()) self.label_67.setSizePolicy(sizePolicy) self.label_67.setStyleSheet("background-color : #656565; color : white") self.label_67.setFrameShape(QtWidgets.QFrame.Panel) self.label_67.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_67.setObjectName("label_67") self.gridLayout_92.addWidget(self.label_67, 0, 0, 1, 4) self.label_55 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_55.sizePolicy().hasHeightForWidth()) self.label_55.setSizePolicy(sizePolicy) self.label_55.setMinimumSize(QtCore.QSize(229, 0)) self.label_55.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_55.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_55.setObjectName("label_55") self.gridLayout_92.addWidget(self.label_55, 1, 0, 1, 1) self.gridLayout_221 = QtWidgets.QGridLayout() self.gridLayout_221.setObjectName("gridLayout_221") self.create_bandset_checkBox_2 = QtWidgets.QCheckBox(self.tab_ASTER) self.create_bandset_checkBox_2.setChecked(True) self.create_bandset_checkBox_2.setTristate(False) self.create_bandset_checkBox_2.setObjectName("create_bandset_checkBox_2") self.gridLayout_221.addWidget(self.create_bandset_checkBox_2, 0, 0, 1, 1) self.add_new_bandset_checkBox_4 = QtWidgets.QCheckBox(self.tab_ASTER) self.add_new_bandset_checkBox_4.setChecked(True) self.add_new_bandset_checkBox_4.setTristate(False) self.add_new_bandset_checkBox_4.setObjectName("add_new_bandset_checkBox_4") self.gridLayout_221.addWidget(self.add_new_bandset_checkBox_4, 0, 1, 1, 1) spacerItem49 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_221.addItem(spacerItem49, 0, 2, 1, 1) self.gridLayout_92.addLayout(self.gridLayout_221, 4, 0, 1, 4) self.celsius_checkBox_2 = QtWidgets.QCheckBox(self.tab_ASTER) self.celsius_checkBox_2.setChecked(False) self.celsius_checkBox_2.setTristate(False) self.celsius_checkBox_2.setObjectName("celsius_checkBox_2") self.gridLayout_92.addWidget(self.celsius_checkBox_2, 2, 0, 1, 3) self.gridLayout_118.addLayout(self.gridLayout_92, 0, 0, 1, 1) self.gridLayout_96 = QtWidgets.QGridLayout() self.gridLayout_96.setObjectName("gridLayout_96") self.ASTER_tableWidget = QtWidgets.QTableWidget(self.tab_ASTER) self.ASTER_tableWidget.setObjectName("ASTER_tableWidget") self.ASTER_tableWidget.setColumnCount(3) self.ASTER_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.ASTER_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.ASTER_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.ASTER_tableWidget.setHorizontalHeaderItem(2, item) self.ASTER_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.ASTER_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_96.addWidget(self.ASTER_tableWidget, 1, 0, 1, 1) self.gridLayout_222 = QtWidgets.QGridLayout() self.gridLayout_222.setObjectName("gridLayout_222") self.pushButton_remove_band_2 = QtWidgets.QToolButton(self.tab_ASTER) self.pushButton_remove_band_2.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_remove_band_2.setIcon(icon58) self.pushButton_remove_band_2.setIconSize(QtCore.QSize(22, 22)) self.pushButton_remove_band_2.setObjectName("pushButton_remove_band_2") self.gridLayout_222.addWidget(self.pushButton_remove_band_2, 0, 0, 1, 1) self.gridLayout_96.addLayout(self.gridLayout_222, 1, 1, 1, 1) self.gridLayout_223 = QtWidgets.QGridLayout() self.gridLayout_223.setObjectName("gridLayout_223") self.date_lineEdit_2 = QtWidgets.QLineEdit(self.tab_ASTER) self.date_lineEdit_2.setObjectName("date_lineEdit_2") self.gridLayout_223.addWidget(self.date_lineEdit_2, 1, 2, 1, 1) self.earth_sun_dist_lineEdit_2 = QtWidgets.QLineEdit(self.tab_ASTER) self.earth_sun_dist_lineEdit_2.setObjectName("earth_sun_dist_lineEdit_2") self.gridLayout_223.addWidget(self.earth_sun_dist_lineEdit_2, 1, 6, 1, 1) self.satellite_label_9 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_9.sizePolicy().hasHeightForWidth()) self.satellite_label_9.setSizePolicy(sizePolicy) self.satellite_label_9.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_9.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_9.setObjectName("satellite_label_9") self.gridLayout_223.addWidget(self.satellite_label_9, 1, 5, 1, 1) self.satellite_label_8 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_8.sizePolicy().hasHeightForWidth()) self.satellite_label_8.setSizePolicy(sizePolicy) self.satellite_label_8.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_8.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_8.setObjectName("satellite_label_8") self.gridLayout_223.addWidget(self.satellite_label_8, 1, 1, 1, 1) self.satellite_label_7 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_7.sizePolicy().hasHeightForWidth()) self.satellite_label_7.setSizePolicy(sizePolicy) self.satellite_label_7.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_7.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_7.setObjectName("satellite_label_7") self.gridLayout_223.addWidget(self.satellite_label_7, 1, 3, 1, 1) self.sun_elev_lineEdit_2 = QtWidgets.QLineEdit(self.tab_ASTER) self.sun_elev_lineEdit_2.setObjectName("sun_elev_lineEdit_2") self.gridLayout_223.addWidget(self.sun_elev_lineEdit_2, 1, 4, 1, 1) self.ulm_lineEdit = QtWidgets.QLineEdit(self.tab_ASTER) self.ulm_lineEdit.setObjectName("ulm_lineEdit") self.gridLayout_223.addWidget(self.ulm_lineEdit, 1, 10, 1, 1) self.satellite_label_10 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_10.sizePolicy().hasHeightForWidth()) self.satellite_label_10.setSizePolicy(sizePolicy) self.satellite_label_10.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_10.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_10.setObjectName("satellite_label_10") self.gridLayout_223.addWidget(self.satellite_label_10, 1, 7, 1, 1) self.utm_zone_lineEdit = QtWidgets.QLineEdit(self.tab_ASTER) self.utm_zone_lineEdit.setObjectName("utm_zone_lineEdit") self.gridLayout_223.addWidget(self.utm_zone_lineEdit, 1, 8, 1, 1) self.satellite_label_11 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_11.sizePolicy().hasHeightForWidth()) self.satellite_label_11.setSizePolicy(sizePolicy) self.satellite_label_11.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_11.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_11.setObjectName("satellite_label_11") self.gridLayout_223.addWidget(self.satellite_label_11, 1, 9, 1, 1) self.satellite_label_17 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_17.sizePolicy().hasHeightForWidth()) self.satellite_label_17.setSizePolicy(sizePolicy) self.satellite_label_17.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_17.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_17.setObjectName("satellite_label_17") self.gridLayout_223.addWidget(self.satellite_label_17, 1, 11, 1, 1) self.lrm_lineEdit = QtWidgets.QLineEdit(self.tab_ASTER) self.lrm_lineEdit.setObjectName("lrm_lineEdit") self.gridLayout_223.addWidget(self.lrm_lineEdit, 1, 12, 1, 1) self.label_160 = QtWidgets.QLabel(self.tab_ASTER) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_160.sizePolicy().hasHeightForWidth()) self.label_160.setSizePolicy(sizePolicy) self.label_160.setStyleSheet("background-color : #656565; color : white") self.label_160.setFrameShape(QtWidgets.QFrame.Panel) self.label_160.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_160.setObjectName("label_160") self.gridLayout_223.addWidget(self.label_160, 0, 0, 1, 13) self.gridLayout_96.addLayout(self.gridLayout_223, 0, 0, 1, 2) self.gridLayout_118.addLayout(self.gridLayout_96, 1, 0, 1, 1) self.gridLayout_224 = QtWidgets.QGridLayout() self.gridLayout_224.setObjectName("gridLayout_224") spacerItem50 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_224.addItem(spacerItem50, 1, 1, 1, 1) self.label_163 = QtWidgets.QLabel(self.tab_ASTER) self.label_163.setStyleSheet("background-color : #656565; color : white") self.label_163.setFrameShape(QtWidgets.QFrame.Panel) self.label_163.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_163.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_163.setObjectName("label_163") self.gridLayout_224.addWidget(self.label_163, 0, 1, 1, 3) self.pushButton_Conversion_3 = QtWidgets.QToolButton(self.tab_ASTER) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_3.setFont(font) self.pushButton_Conversion_3.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_3.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_3.setIcon(icon64) self.pushButton_Conversion_3.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_3.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_3.setObjectName("pushButton_Conversion_3") self.gridLayout_224.addWidget(self.pushButton_Conversion_3, 1, 3, 1, 1) self.aster_conversion = QtWidgets.QToolButton(self.tab_ASTER) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.aster_conversion.setFont(font) self.aster_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.aster_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.aster_conversion.setIcon(icon48) self.aster_conversion.setIconSize(QtCore.QSize(34, 34)) self.aster_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.aster_conversion.setObjectName("aster_conversion") self.gridLayout_224.addWidget(self.aster_conversion, 1, 2, 1, 1) self.gridLayout_118.addLayout(self.gridLayout_224, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_ASTER, "") self.tab_MODIS = QtWidgets.QWidget() self.tab_MODIS.setObjectName("tab_MODIS") self.gridLayout_70 = QtWidgets.QGridLayout(self.tab_MODIS) self.gridLayout_70.setObjectName("gridLayout_70") self.gridLayout_270 = QtWidgets.QGridLayout() self.gridLayout_270.setObjectName("gridLayout_270") self.label_218 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_218.sizePolicy().hasHeightForWidth()) self.label_218.setSizePolicy(sizePolicy) self.label_218.setStyleSheet("background-color : #656565; color : white") self.label_218.setFrameShape(QtWidgets.QFrame.Panel) self.label_218.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_218.setObjectName("label_218") self.gridLayout_270.addWidget(self.label_218, 0, 0, 1, 4) self.label_217 = QtWidgets.QLabel(self.tab_MODIS) self.label_217.setFrameShape(QtWidgets.QFrame.Panel) self.label_217.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_217.setText("") self.label_217.setObjectName("label_217") self.gridLayout_270.addWidget(self.label_217, 2, 1, 1, 2) self.gridLayout_272 = QtWidgets.QGridLayout() self.gridLayout_272.setObjectName("gridLayout_272") self.create_bandset_checkBox_3 = QtWidgets.QCheckBox(self.tab_MODIS) self.create_bandset_checkBox_3.setChecked(True) self.create_bandset_checkBox_3.setTristate(False) self.create_bandset_checkBox_3.setObjectName("create_bandset_checkBox_3") self.gridLayout_272.addWidget(self.create_bandset_checkBox_3, 0, 0, 1, 1) self.add_new_bandset_checkBox_5 = QtWidgets.QCheckBox(self.tab_MODIS) self.add_new_bandset_checkBox_5.setChecked(True) self.add_new_bandset_checkBox_5.setTristate(False) self.add_new_bandset_checkBox_5.setObjectName("add_new_bandset_checkBox_5") self.gridLayout_272.addWidget(self.add_new_bandset_checkBox_5, 0, 1, 1, 1) spacerItem51 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_272.addItem(spacerItem51, 0, 2, 1, 1) self.gridLayout_270.addLayout(self.gridLayout_272, 4, 0, 1, 4) self.label_219 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_219.sizePolicy().hasHeightForWidth()) self.label_219.setSizePolicy(sizePolicy) self.label_219.setMinimumSize(QtCore.QSize(229, 0)) self.label_219.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_219.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_219.setObjectName("label_219") self.gridLayout_270.addWidget(self.label_219, 2, 0, 1, 1) self.toolButton_directoryInput_MODIS = QtWidgets.QToolButton(self.tab_MODIS) self.toolButton_directoryInput_MODIS.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_directoryInput_MODIS.setIcon(icon65) self.toolButton_directoryInput_MODIS.setIconSize(QtCore.QSize(22, 22)) self.toolButton_directoryInput_MODIS.setObjectName("toolButton_directoryInput_MODIS") self.gridLayout_270.addWidget(self.toolButton_directoryInput_MODIS, 2, 3, 1, 1) self.gridLayout_271 = QtWidgets.QGridLayout() self.gridLayout_271.setObjectName("gridLayout_271") self.nodata_spinBox_8 = QtWidgets.QSpinBox(self.tab_MODIS) self.nodata_spinBox_8.setMinimum(-100000) self.nodata_spinBox_8.setMaximum(100000) self.nodata_spinBox_8.setProperty("value", -999) self.nodata_spinBox_8.setObjectName("nodata_spinBox_8") self.gridLayout_271.addWidget(self.nodata_spinBox_8, 0, 2, 1, 1) self.nodata_checkBox_7 = QtWidgets.QCheckBox(self.tab_MODIS) self.nodata_checkBox_7.setChecked(True) self.nodata_checkBox_7.setObjectName("nodata_checkBox_7") self.gridLayout_271.addWidget(self.nodata_checkBox_7, 0, 1, 1, 1) spacerItem52 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_271.addItem(spacerItem52, 0, 0, 1, 1) self.gridLayout_270.addLayout(self.gridLayout_271, 3, 1, 1, 3) self.reproject_modis_checkBox = QtWidgets.QCheckBox(self.tab_MODIS) self.reproject_modis_checkBox.setChecked(True) self.reproject_modis_checkBox.setTristate(False) self.reproject_modis_checkBox.setObjectName("reproject_modis_checkBox") self.gridLayout_270.addWidget(self.reproject_modis_checkBox, 3, 0, 1, 1) self.gridLayout_70.addLayout(self.gridLayout_270, 0, 0, 1, 1) self.gridLayout_273 = QtWidgets.QGridLayout() self.gridLayout_273.setObjectName("gridLayout_273") self.MODIS_tableWidget = QtWidgets.QTableWidget(self.tab_MODIS) self.MODIS_tableWidget.setObjectName("MODIS_tableWidget") self.MODIS_tableWidget.setColumnCount(2) self.MODIS_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.MODIS_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.MODIS_tableWidget.setHorizontalHeaderItem(1, item) self.MODIS_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.MODIS_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_273.addWidget(self.MODIS_tableWidget, 1, 0, 1, 1) self.gridLayout_274 = QtWidgets.QGridLayout() self.gridLayout_274.setObjectName("gridLayout_274") self.pushButton_remove_band_3 = QtWidgets.QToolButton(self.tab_MODIS) self.pushButton_remove_band_3.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_remove_band_3.setIcon(icon58) self.pushButton_remove_band_3.setIconSize(QtCore.QSize(22, 22)) self.pushButton_remove_band_3.setObjectName("pushButton_remove_band_3") self.gridLayout_274.addWidget(self.pushButton_remove_band_3, 0, 0, 1, 1) self.gridLayout_273.addLayout(self.gridLayout_274, 1, 1, 1, 1) self.gridLayout_275 = QtWidgets.QGridLayout() self.gridLayout_275.setObjectName("gridLayout_275") self.satellite_label_16 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_16.sizePolicy().hasHeightForWidth()) self.satellite_label_16.setSizePolicy(sizePolicy) self.satellite_label_16.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_16.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_16.setObjectName("satellite_label_16") self.gridLayout_275.addWidget(self.satellite_label_16, 1, 4, 1, 1) self.MODIS_ID_lineEdit = QtWidgets.QLineEdit(self.tab_MODIS) self.MODIS_ID_lineEdit.setObjectName("MODIS_ID_lineEdit") self.gridLayout_275.addWidget(self.MODIS_ID_lineEdit, 1, 2, 1, 1) self.satellite_label_13 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_13.sizePolicy().hasHeightForWidth()) self.satellite_label_13.setSizePolicy(sizePolicy) self.satellite_label_13.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_13.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_13.setObjectName("satellite_label_13") self.gridLayout_275.addWidget(self.satellite_label_13, 1, 1, 1, 1) self.MODIS_date_lineEdit = QtWidgets.QLineEdit(self.tab_MODIS) self.MODIS_date_lineEdit.setObjectName("MODIS_date_lineEdit") self.gridLayout_275.addWidget(self.MODIS_date_lineEdit, 1, 5, 1, 1) self.label_220 = QtWidgets.QLabel(self.tab_MODIS) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_220.sizePolicy().hasHeightForWidth()) self.label_220.setSizePolicy(sizePolicy) self.label_220.setStyleSheet("background-color : #656565; color : white") self.label_220.setFrameShape(QtWidgets.QFrame.Panel) self.label_220.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_220.setObjectName("label_220") self.gridLayout_275.addWidget(self.label_220, 0, 0, 1, 6) spacerItem53 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_275.addItem(spacerItem53, 1, 3, 1, 1) self.gridLayout_273.addLayout(self.gridLayout_275, 0, 0, 1, 2) self.gridLayout_70.addLayout(self.gridLayout_273, 1, 0, 1, 1) self.gridLayout_276 = QtWidgets.QGridLayout() self.gridLayout_276.setObjectName("gridLayout_276") spacerItem54 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_276.addItem(spacerItem54, 1, 1, 1, 1) self.label_221 = QtWidgets.QLabel(self.tab_MODIS) self.label_221.setStyleSheet("background-color : #656565; color : white") self.label_221.setFrameShape(QtWidgets.QFrame.Panel) self.label_221.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_221.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_221.setObjectName("label_221") self.gridLayout_276.addWidget(self.label_221, 0, 1, 1, 3) self.pushButton_Conversion_4 = QtWidgets.QToolButton(self.tab_MODIS) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_4.setFont(font) self.pushButton_Conversion_4.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_4.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_4.setIcon(icon64) self.pushButton_Conversion_4.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_4.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_4.setObjectName("pushButton_Conversion_4") self.gridLayout_276.addWidget(self.pushButton_Conversion_4, 1, 3, 1, 1) self.modis_conversion = QtWidgets.QToolButton(self.tab_MODIS) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.modis_conversion.setFont(font) self.modis_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.modis_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.modis_conversion.setIcon(icon48) self.modis_conversion.setIconSize(QtCore.QSize(34, 34)) self.modis_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.modis_conversion.setObjectName("modis_conversion") self.gridLayout_276.addWidget(self.modis_conversion, 1, 2, 1, 1) self.gridLayout_70.addLayout(self.gridLayout_276, 2, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_MODIS, "") self.tab_spectral_distance = QtWidgets.QWidget() self.tab_spectral_distance.setObjectName("tab_spectral_distance") self.gridLayout_61 = QtWidgets.QGridLayout(self.tab_spectral_distance) self.gridLayout_61.setObjectName("gridLayout_61") self.gridLayout_119 = QtWidgets.QGridLayout() self.gridLayout_119.setObjectName("gridLayout_119") self.label_142 = QtWidgets.QLabel(self.tab_spectral_distance) self.label_142.setStyleSheet("background-color : #656565; color : white") self.label_142.setFrameShape(QtWidgets.QFrame.Panel) self.label_142.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_142.setObjectName("label_142") self.gridLayout_119.addWidget(self.label_142, 0, 0, 1, 1) self.gridLayout_61.addLayout(self.gridLayout_119, 0, 0, 1, 1) self.horizontalLayout_22 = QtWidgets.QHBoxLayout() self.horizontalLayout_22.setObjectName("horizontalLayout_22") self.label_64 = QtWidgets.QLabel(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_64.sizePolicy().hasHeightForWidth()) self.label_64.setSizePolicy(sizePolicy) self.label_64.setMinimumSize(QtCore.QSize(229, 0)) self.label_64.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_64.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_64.setObjectName("label_64") self.horizontalLayout_22.addWidget(self.label_64) self.vector_name_combo = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.vector_name_combo.sizePolicy().hasHeightForWidth()) self.vector_name_combo.setSizePolicy(sizePolicy) self.vector_name_combo.setObjectName("vector_name_combo") self.horizontalLayout_22.addWidget(self.vector_name_combo) self.toolButton_reload_16 = QtWidgets.QToolButton(self.tab_spectral_distance) self.toolButton_reload_16.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_16.setIcon(icon55) self.toolButton_reload_16.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_16.setObjectName("toolButton_reload_16") self.horizontalLayout_22.addWidget(self.toolButton_reload_16) self.gridLayout_61.addLayout(self.horizontalLayout_22, 1, 0, 1, 1) self.horizontalLayout_19 = QtWidgets.QHBoxLayout() self.horizontalLayout_19.setObjectName("horizontalLayout_19") self.field_checkBox = QtWidgets.QCheckBox(self.tab_spectral_distance) self.field_checkBox.setChecked(True) self.field_checkBox.setObjectName("field_checkBox") self.horizontalLayout_19.addWidget(self.field_checkBox) self.field_comboBox = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.field_comboBox.sizePolicy().hasHeightForWidth()) self.field_comboBox.setSizePolicy(sizePolicy) self.field_comboBox.setObjectName("field_comboBox") self.horizontalLayout_19.addWidget(self.field_comboBox) self.gridLayout_61.addLayout(self.horizontalLayout_19, 2, 0, 1, 1) self.horizontalLayout_25 = QtWidgets.QHBoxLayout() self.horizontalLayout_25.setObjectName("horizontalLayout_25") self.constant_value_checkBox = QtWidgets.QCheckBox(self.tab_spectral_distance) self.constant_value_checkBox.setObjectName("constant_value_checkBox") self.horizontalLayout_25.addWidget(self.constant_value_checkBox) self.constant_value_spinBox = QtWidgets.QSpinBox(self.tab_spectral_distance) self.constant_value_spinBox.setMinimum(-100000) self.constant_value_spinBox.setMaximum(100000) self.constant_value_spinBox.setProperty("value", 1) self.constant_value_spinBox.setObjectName("constant_value_spinBox") self.horizontalLayout_25.addWidget(self.constant_value_spinBox) self.gridLayout_61.addLayout(self.horizontalLayout_25, 3, 0, 1, 1) self.horizontalLayout_20 = QtWidgets.QHBoxLayout() self.horizontalLayout_20.setObjectName("horizontalLayout_20") self.label_157 = QtWidgets.QLabel(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_157.sizePolicy().hasHeightForWidth()) self.label_157.setSizePolicy(sizePolicy) self.label_157.setMinimumSize(QtCore.QSize(229, 0)) self.label_157.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_157.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_157.setObjectName("label_157") self.horizontalLayout_20.addWidget(self.label_157) self.conversion_type_combo = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.conversion_type_combo.sizePolicy().hasHeightForWidth()) self.conversion_type_combo.setSizePolicy(sizePolicy) self.conversion_type_combo.setObjectName("conversion_type_combo") self.horizontalLayout_20.addWidget(self.conversion_type_combo) self.gridLayout_61.addLayout(self.horizontalLayout_20, 4, 0, 1, 1) self.gridLayout_194 = QtWidgets.QGridLayout() self.gridLayout_194.setObjectName("gridLayout_194") self.label_156 = QtWidgets.QLabel(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_156.sizePolicy().hasHeightForWidth()) self.label_156.setSizePolicy(sizePolicy) self.label_156.setMinimumSize(QtCore.QSize(229, 0)) self.label_156.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_156.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_156.setObjectName("label_156") self.gridLayout_194.addWidget(self.label_156, 0, 0, 1, 1) self.toolButton_reload_17 = QtWidgets.QToolButton(self.tab_spectral_distance) self.toolButton_reload_17.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_17.setIcon(icon55) self.toolButton_reload_17.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_17.setObjectName("toolButton_reload_17") self.gridLayout_194.addWidget(self.toolButton_reload_17, 0, 2, 1, 1) self.reference_raster_name_combo = QtWidgets.QComboBox(self.tab_spectral_distance) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_raster_name_combo.sizePolicy().hasHeightForWidth()) self.reference_raster_name_combo.setSizePolicy(sizePolicy) self.reference_raster_name_combo.setObjectName("reference_raster_name_combo") self.gridLayout_194.addWidget(self.reference_raster_name_combo, 0, 1, 1, 1) self.gridLayout_61.addLayout(self.gridLayout_194, 5, 0, 1, 1) self.horizontalLayout_47 = QtWidgets.QHBoxLayout() self.horizontalLayout_47.setObjectName("horizontalLayout_47") self.extent_checkBox_2 = QtWidgets.QCheckBox(self.tab_spectral_distance) self.extent_checkBox_2.setObjectName("extent_checkBox_2") self.horizontalLayout_47.addWidget(self.extent_checkBox_2) self.gridLayout_61.addLayout(self.horizontalLayout_47, 6, 0, 1, 1) self.gridLayout_210 = QtWidgets.QGridLayout() self.gridLayout_210.setObjectName("gridLayout_210") spacerItem55 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_210.addItem(spacerItem55, 0, 2, 1, 1) self.label_167 = QtWidgets.QLabel(self.tab_spectral_distance) self.label_167.setStyleSheet("background-color : #656565; color : white") self.label_167.setFrameShape(QtWidgets.QFrame.Panel) self.label_167.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_167.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_167.setObjectName("label_167") self.gridLayout_210.addWidget(self.label_167, 1, 0, 1, 3) spacerItem56 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_210.addItem(spacerItem56, 2, 0, 1, 1) self.convert_vector_toolButton = QtWidgets.QToolButton(self.tab_spectral_distance) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.convert_vector_toolButton.setFont(font) self.convert_vector_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.convert_vector_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.convert_vector_toolButton.setIcon(icon64) self.convert_vector_toolButton.setIconSize(QtCore.QSize(34, 34)) self.convert_vector_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.convert_vector_toolButton.setObjectName("convert_vector_toolButton") self.gridLayout_210.addWidget(self.convert_vector_toolButton, 2, 2, 1, 1) self.vector_to_raster = QtWidgets.QToolButton(self.tab_spectral_distance) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.vector_to_raster.setFont(font) self.vector_to_raster.setLayoutDirection(QtCore.Qt.RightToLeft) self.vector_to_raster.setStyleSheet("margin: 0px;padding: 0px;") self.vector_to_raster.setIcon(icon48) self.vector_to_raster.setIconSize(QtCore.QSize(34, 34)) self.vector_to_raster.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.vector_to_raster.setObjectName("vector_to_raster") self.gridLayout_210.addWidget(self.vector_to_raster, 2, 1, 1, 1) self.gridLayout_61.addLayout(self.gridLayout_210, 7, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_spectral_distance, "") self.tab_clip = QtWidgets.QWidget() self.tab_clip.setObjectName("tab_clip") self.gridLayout_58 = QtWidgets.QGridLayout(self.tab_clip) self.gridLayout_58.setObjectName("gridLayout_58") self.gridLayout_51 = QtWidgets.QGridLayout() self.gridLayout_51.setObjectName("gridLayout_51") self.label_128 = QtWidgets.QLabel(self.tab_clip) self.label_128.setStyleSheet("background-color : #656565; color : white") self.label_128.setFrameShape(QtWidgets.QFrame.Panel) self.label_128.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_128.setObjectName("label_128") self.gridLayout_51.addWidget(self.label_128, 0, 0, 1, 1) self.gridLayout_58.addLayout(self.gridLayout_51, 0, 0, 1, 1) self.gridLayout_24 = QtWidgets.QGridLayout() self.gridLayout_24.setObjectName("gridLayout_24") self.nodata_spinBox = QtWidgets.QSpinBox(self.tab_clip) self.nodata_spinBox.setMinimum(-2147483647) self.nodata_spinBox.setMaximum(2147483647) self.nodata_spinBox.setObjectName("nodata_spinBox") self.gridLayout_24.addWidget(self.nodata_spinBox, 1, 1, 1, 1) self.band_set_comb_spinBox_2 = QtWidgets.QSpinBox(self.tab_clip) self.band_set_comb_spinBox_2.setMinimum(1) self.band_set_comb_spinBox_2.setMaximum(100000) self.band_set_comb_spinBox_2.setObjectName("band_set_comb_spinBox_2") self.gridLayout_24.addWidget(self.band_set_comb_spinBox_2, 0, 1, 1, 1) self.label_251 = QtWidgets.QLabel(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_251.sizePolicy().hasHeightForWidth()) self.label_251.setSizePolicy(sizePolicy) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_251.setFont(font) self.label_251.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_251.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_251.setObjectName("label_251") self.gridLayout_24.addWidget(self.label_251, 0, 0, 1, 1) self.label_62 = QtWidgets.QLabel(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_62.sizePolicy().hasHeightForWidth()) self.label_62.setSizePolicy(sizePolicy) self.label_62.setMinimumSize(QtCore.QSize(150, 0)) self.label_62.setMaximumSize(QtCore.QSize(100, 16777215)) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_62.setFont(font) self.label_62.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_62.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_62.setObjectName("label_62") self.gridLayout_24.addWidget(self.label_62, 2, 0, 1, 1) self.label_16 = QtWidgets.QLabel(self.tab_clip) self.label_16.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_16.setObjectName("label_16") self.gridLayout_24.addWidget(self.label_16, 1, 0, 1, 1) spacerItem57 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_24.addItem(spacerItem57, 1, 2, 1, 1) self.output_clip_name_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.output_clip_name_lineEdit.setMaxLength(10) self.output_clip_name_lineEdit.setObjectName("output_clip_name_lineEdit") self.gridLayout_24.addWidget(self.output_clip_name_lineEdit, 2, 1, 1, 2) self.gridLayout_58.addLayout(self.gridLayout_24, 1, 0, 1, 1) self.gridLayout_20 = QtWidgets.QGridLayout() self.gridLayout_20.setObjectName("gridLayout_20") spacerItem58 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_20.addItem(spacerItem58, 1, 8, 1, 1) self.LX_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.LX_lineEdit.setMaxLength(10) self.LX_lineEdit.setObjectName("LX_lineEdit") self.gridLayout_20.addWidget(self.LX_lineEdit, 1, 6, 1, 1) self.UX_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.UX_lineEdit.setMaxLength(10) self.UX_lineEdit.setObjectName("UX_lineEdit") self.gridLayout_20.addWidget(self.UX_lineEdit, 1, 3, 1, 1) self.UY_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.UY_lineEdit.setMaxLength(10) self.UY_lineEdit.setObjectName("UY_lineEdit") self.gridLayout_20.addWidget(self.UY_lineEdit, 1, 4, 1, 1) self.LY_lineEdit = QtWidgets.QLineEdit(self.tab_clip) self.LY_lineEdit.setMaxLength(10) self.LY_lineEdit.setObjectName("LY_lineEdit") self.gridLayout_20.addWidget(self.LY_lineEdit, 1, 7, 1, 1) self.label_12 = QtWidgets.QLabel(self.tab_clip) self.label_12.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_12.setAlignment(QtCore.Qt.AlignCenter) self.label_12.setObjectName("label_12") self.gridLayout_20.addWidget(self.label_12, 1, 5, 1, 1) self.selectUL_toolButton = QtWidgets.QToolButton(self.tab_clip) self.selectUL_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.selectUL_toolButton.setIcon(icon77) self.selectUL_toolButton.setIconSize(QtCore.QSize(22, 22)) self.selectUL_toolButton.setObjectName("selectUL_toolButton") self.gridLayout_20.addWidget(self.selectUL_toolButton, 1, 10, 1, 1) self.label_29 = QtWidgets.QLabel(self.tab_clip) self.label_29.setStyleSheet("background-color : #656565; color : white") self.label_29.setFrameShape(QtWidgets.QFrame.Panel) self.label_29.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_29.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_29.setObjectName("label_29") self.gridLayout_20.addWidget(self.label_29, 0, 0, 1, 11) self.show_area_radioButton_3 = QtWidgets.QRadioButton(self.tab_clip) self.show_area_radioButton_3.setChecked(True) self.show_area_radioButton_3.setAutoExclusive(False) self.show_area_radioButton_3.setObjectName("show_area_radioButton_3") self.gridLayout_20.addWidget(self.show_area_radioButton_3, 1, 9, 1, 1) self.label_11 = QtWidgets.QLabel(self.tab_clip) self.label_11.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_11.setAlignment(QtCore.Qt.AlignCenter) self.label_11.setObjectName("label_11") self.gridLayout_20.addWidget(self.label_11, 1, 0, 1, 3) self.gridLayout_58.addLayout(self.gridLayout_20, 2, 0, 1, 1) self.gridLayout_22 = QtWidgets.QGridLayout() self.gridLayout_22.setObjectName("gridLayout_22") self.shapefile_comboBox = QtWidgets.QComboBox(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.shapefile_comboBox.sizePolicy().hasHeightForWidth()) self.shapefile_comboBox.setSizePolicy(sizePolicy) self.shapefile_comboBox.setObjectName("shapefile_comboBox") self.gridLayout_22.addWidget(self.shapefile_comboBox, 0, 1, 1, 1) self.shapefile_checkBox = QtWidgets.QCheckBox(self.tab_clip) self.shapefile_checkBox.setObjectName("shapefile_checkBox") self.gridLayout_22.addWidget(self.shapefile_checkBox, 0, 0, 1, 1) self.toolButton_reload_8 = QtWidgets.QToolButton(self.tab_clip) self.toolButton_reload_8.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_8.setIcon(icon55) self.toolButton_reload_8.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_8.setObjectName("toolButton_reload_8") self.gridLayout_22.addWidget(self.toolButton_reload_8, 0, 2, 1, 1) self.temporary_ROI_checkBox = QtWidgets.QCheckBox(self.tab_clip) self.temporary_ROI_checkBox.setObjectName("temporary_ROI_checkBox") self.gridLayout_22.addWidget(self.temporary_ROI_checkBox, 2, 0, 1, 1) self.gridLayout_19 = QtWidgets.QGridLayout() self.gridLayout_19.setObjectName("gridLayout_19") self.vector_field_checkBox = QtWidgets.QCheckBox(self.tab_clip) self.vector_field_checkBox.setObjectName("vector_field_checkBox") self.gridLayout_19.addWidget(self.vector_field_checkBox, 0, 0, 1, 1) self.class_field_comboBox_3 = QtWidgets.QComboBox(self.tab_clip) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox_3.sizePolicy().hasHeightForWidth()) self.class_field_comboBox_3.setSizePolicy(sizePolicy) self.class_field_comboBox_3.setObjectName("class_field_comboBox_3") self.gridLayout_19.addWidget(self.class_field_comboBox_3, 0, 1, 1, 1) self.gridLayout_22.addLayout(self.gridLayout_19, 1, 1, 1, 1) self.gridLayout_58.addLayout(self.gridLayout_22, 3, 0, 1, 1) self.gridLayout_28 = QtWidgets.QGridLayout() self.gridLayout_28.setObjectName("gridLayout_28") spacerItem59 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_28.addItem(spacerItem59, 2, 0, 1, 1) self.label_164 = QtWidgets.QLabel(self.tab_clip) self.label_164.setStyleSheet("background-color : #656565; color : white") self.label_164.setFrameShape(QtWidgets.QFrame.Panel) self.label_164.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_164.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_164.setObjectName("label_164") self.gridLayout_28.addWidget(self.label_164, 1, 0, 1, 3) self.clip_Button = QtWidgets.QToolButton(self.tab_clip) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.clip_Button.setFont(font) self.clip_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.clip_Button.setStyleSheet("margin: 0px;padding: 0px;") self.clip_Button.setIcon(icon64) self.clip_Button.setIconSize(QtCore.QSize(34, 34)) self.clip_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.clip_Button.setObjectName("clip_Button") self.gridLayout_28.addWidget(self.clip_Button, 2, 2, 1, 1) spacerItem60 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_28.addItem(spacerItem60, 0, 0, 1, 1) self.clip_multiple_rasters = QtWidgets.QToolButton(self.tab_clip) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.clip_multiple_rasters.setFont(font) self.clip_multiple_rasters.setLayoutDirection(QtCore.Qt.RightToLeft) self.clip_multiple_rasters.setStyleSheet("margin: 0px;padding: 0px;") self.clip_multiple_rasters.setIcon(icon48) self.clip_multiple_rasters.setIconSize(QtCore.QSize(34, 34)) self.clip_multiple_rasters.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.clip_multiple_rasters.setObjectName("clip_multiple_rasters") self.gridLayout_28.addWidget(self.clip_multiple_rasters, 2, 1, 1, 1) self.gridLayout_58.addLayout(self.gridLayout_28, 4, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_clip, "") self.tab_reproject_bands = QtWidgets.QWidget() self.tab_reproject_bands.setObjectName("tab_reproject_bands") self.gridLayout_295 = QtWidgets.QGridLayout(self.tab_reproject_bands) self.gridLayout_295.setObjectName("gridLayout_295") self.gridLayout_289 = QtWidgets.QGridLayout() self.gridLayout_289.setObjectName("gridLayout_289") self.band_set_comb_spinBox_14 = QtWidgets.QSpinBox(self.tab_reproject_bands) self.band_set_comb_spinBox_14.setMinimum(1) self.band_set_comb_spinBox_14.setMaximum(100000) self.band_set_comb_spinBox_14.setObjectName("band_set_comb_spinBox_14") self.gridLayout_289.addWidget(self.band_set_comb_spinBox_14, 1, 1, 1, 1) self.label_264 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_264.sizePolicy().hasHeightForWidth()) self.label_264.setSizePolicy(sizePolicy) self.label_264.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_264.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_264.setObjectName("label_264") self.gridLayout_289.addWidget(self.label_264, 1, 0, 1, 1) spacerItem61 = QtWidgets.QSpacerItem(605, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_289.addItem(spacerItem61, 1, 2, 1, 1) self.label_249 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_249.sizePolicy().hasHeightForWidth()) self.label_249.setSizePolicy(sizePolicy) self.label_249.setStyleSheet("background-color : #656565; color : white") self.label_249.setFrameShape(QtWidgets.QFrame.Panel) self.label_249.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_249.setObjectName("label_249") self.gridLayout_289.addWidget(self.label_249, 0, 0, 1, 3) self.gridLayout_295.addLayout(self.gridLayout_289, 0, 0, 1, 1) self.gridLayout_291 = QtWidgets.QGridLayout() self.gridLayout_291.setObjectName("gridLayout_291") self.raster_align_comboBox = QtWidgets.QComboBox(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_align_comboBox.sizePolicy().hasHeightForWidth()) self.raster_align_comboBox.setSizePolicy(sizePolicy) self.raster_align_comboBox.setObjectName("raster_align_comboBox") self.gridLayout_291.addWidget(self.raster_align_comboBox, 0, 2, 1, 1) self.use_align_raster_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.use_align_raster_checkBox.setObjectName("use_align_raster_checkBox") self.gridLayout_291.addWidget(self.use_align_raster_checkBox, 0, 0, 1, 1) self.toolButton_reload_25 = QtWidgets.QToolButton(self.tab_reproject_bands) self.toolButton_reload_25.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_25.setIcon(icon55) self.toolButton_reload_25.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_25.setObjectName("toolButton_reload_25") self.gridLayout_291.addWidget(self.toolButton_reload_25, 0, 3, 1, 1) self.same_extent_raster_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.same_extent_raster_checkBox.setObjectName("same_extent_raster_checkBox") self.gridLayout_291.addWidget(self.same_extent_raster_checkBox, 0, 1, 1, 1) self.gridLayout_295.addLayout(self.gridLayout_291, 1, 0, 1, 1) self.gridLayout_292 = QtWidgets.QGridLayout() self.gridLayout_292.setObjectName("gridLayout_292") self.epsg_code_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.epsg_code_lineEdit.setText("") self.epsg_code_lineEdit.setMaxLength(10) self.epsg_code_lineEdit.setObjectName("epsg_code_lineEdit") self.gridLayout_292.addWidget(self.epsg_code_lineEdit, 0, 1, 1, 1) self.use_epsg_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.use_epsg_checkBox.setObjectName("use_epsg_checkBox") self.gridLayout_292.addWidget(self.use_epsg_checkBox, 0, 0, 1, 1) self.label_267 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_267.sizePolicy().hasHeightForWidth()) self.label_267.setSizePolicy(sizePolicy) self.label_267.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_267.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_267.setObjectName("label_267") self.gridLayout_292.addWidget(self.label_267, 0, 6, 1, 1) self.label_266 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_266.sizePolicy().hasHeightForWidth()) self.label_266.setSizePolicy(sizePolicy) self.label_266.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_266.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_266.setObjectName("label_266") self.gridLayout_292.addWidget(self.label_266, 0, 3, 1, 1) self.x_resolution_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.x_resolution_lineEdit.setText("") self.x_resolution_lineEdit.setMaxLength(10) self.x_resolution_lineEdit.setObjectName("x_resolution_lineEdit") self.gridLayout_292.addWidget(self.x_resolution_lineEdit, 0, 4, 1, 1) self.y_resolution_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.y_resolution_lineEdit.setText("") self.y_resolution_lineEdit.setMaxLength(10) self.y_resolution_lineEdit.setObjectName("y_resolution_lineEdit") self.gridLayout_292.addWidget(self.y_resolution_lineEdit, 0, 7, 1, 1) spacerItem62 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_292.addItem(spacerItem62, 0, 2, 1, 1) spacerItem63 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_292.addItem(spacerItem63, 0, 5, 1, 1) self.gridLayout_295.addLayout(self.gridLayout_292, 2, 0, 1, 1) self.horizontalLayout_63 = QtWidgets.QHBoxLayout() self.horizontalLayout_63.setObjectName("horizontalLayout_63") self.resample_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.resample_checkBox.setObjectName("resample_checkBox") self.horizontalLayout_63.addWidget(self.resample_checkBox) self.resample_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.resample_lineEdit.setMaxLength(10) self.resample_lineEdit.setObjectName("resample_lineEdit") self.horizontalLayout_63.addWidget(self.resample_lineEdit) self.gridLayout_295.addLayout(self.horizontalLayout_63, 3, 0, 1, 1) self.horizontalLayout_64 = QtWidgets.QHBoxLayout() self.horizontalLayout_64.setObjectName("horizontalLayout_64") self.label_269 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_269.sizePolicy().hasHeightForWidth()) self.label_269.setSizePolicy(sizePolicy) self.label_269.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_269.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_269.setObjectName("label_269") self.horizontalLayout_64.addWidget(self.label_269) self.resampling_method_comboBox = QtWidgets.QComboBox(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.resampling_method_comboBox.sizePolicy().hasHeightForWidth()) self.resampling_method_comboBox.setSizePolicy(sizePolicy) self.resampling_method_comboBox.setObjectName("resampling_method_comboBox") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.resampling_method_comboBox.addItem("") self.horizontalLayout_64.addWidget(self.resampling_method_comboBox) spacerItem64 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_64.addItem(spacerItem64) self.label_270 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_270.sizePolicy().hasHeightForWidth()) self.label_270.setSizePolicy(sizePolicy) self.label_270.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_270.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_270.setObjectName("label_270") self.horizontalLayout_64.addWidget(self.label_270) self.raster_type_combo_2 = QtWidgets.QComboBox(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_type_combo_2.sizePolicy().hasHeightForWidth()) self.raster_type_combo_2.setSizePolicy(sizePolicy) self.raster_type_combo_2.setObjectName("raster_type_combo_2") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.raster_type_combo_2.addItem("") self.horizontalLayout_64.addWidget(self.raster_type_combo_2) self.gridLayout_295.addLayout(self.horizontalLayout_64, 4, 0, 1, 1) self.horizontalLayout_66 = QtWidgets.QHBoxLayout() self.horizontalLayout_66.setObjectName("horizontalLayout_66") self.change_nodata_checkBox = QtWidgets.QCheckBox(self.tab_reproject_bands) self.change_nodata_checkBox.setObjectName("change_nodata_checkBox") self.horizontalLayout_66.addWidget(self.change_nodata_checkBox) self.nodata_spinBox_14 = QtWidgets.QSpinBox(self.tab_reproject_bands) self.nodata_spinBox_14.setMinimum(-2147483647) self.nodata_spinBox_14.setMaximum(2147483647) self.nodata_spinBox_14.setProperty("value", -32768) self.nodata_spinBox_14.setObjectName("nodata_spinBox_14") self.horizontalLayout_66.addWidget(self.nodata_spinBox_14) spacerItem65 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_66.addItem(spacerItem65) self.gridLayout_295.addLayout(self.horizontalLayout_66, 5, 0, 1, 1) self.horizontalLayout_68 = QtWidgets.QHBoxLayout() self.horizontalLayout_68.setObjectName("horizontalLayout_68") self.label_265 = QtWidgets.QLabel(self.tab_reproject_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_265.sizePolicy().hasHeightForWidth()) self.label_265.setSizePolicy(sizePolicy) self.label_265.setMinimumSize(QtCore.QSize(229, 0)) self.label_265.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_265.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_265.setObjectName("label_265") self.horizontalLayout_68.addWidget(self.label_265) self.reproj_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_reproject_bands) self.reproj_output_name_lineEdit.setMaxLength(10) self.reproj_output_name_lineEdit.setObjectName("reproj_output_name_lineEdit") self.horizontalLayout_68.addWidget(self.reproj_output_name_lineEdit) self.gridLayout_295.addLayout(self.horizontalLayout_68, 6, 0, 1, 1) spacerItem66 = QtWidgets.QSpacerItem(20, 198, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_295.addItem(spacerItem66, 7, 0, 1, 1) self.gridLayout_290 = QtWidgets.QGridLayout() self.gridLayout_290.setObjectName("gridLayout_290") self.label_263 = QtWidgets.QLabel(self.tab_reproject_bands) self.label_263.setStyleSheet("background-color : #656565; color : white") self.label_263.setFrameShape(QtWidgets.QFrame.Panel) self.label_263.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_263.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_263.setObjectName("label_263") self.gridLayout_290.addWidget(self.label_263, 0, 0, 1, 2) self.horizontalLayout_59 = QtWidgets.QHBoxLayout() self.horizontalLayout_59.setObjectName("horizontalLayout_59") spacerItem67 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_59.addItem(spacerItem67) self.reproject_raster_bands = QtWidgets.QToolButton(self.tab_reproject_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reproject_raster_bands.setFont(font) self.reproject_raster_bands.setLayoutDirection(QtCore.Qt.RightToLeft) self.reproject_raster_bands.setStyleSheet("margin: 0px;padding: 0px;") self.reproject_raster_bands.setIcon(icon48) self.reproject_raster_bands.setIconSize(QtCore.QSize(34, 34)) self.reproject_raster_bands.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reproject_raster_bands.setObjectName("reproject_raster_bands") self.horizontalLayout_59.addWidget(self.reproject_raster_bands) self.reproject_Button = QtWidgets.QToolButton(self.tab_reproject_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reproject_Button.setFont(font) self.reproject_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.reproject_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reproject_Button.setIcon(icon64) self.reproject_Button.setIconSize(QtCore.QSize(34, 34)) self.reproject_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reproject_Button.setObjectName("reproject_Button") self.horizontalLayout_59.addWidget(self.reproject_Button) self.gridLayout_290.addLayout(self.horizontalLayout_59, 2, 0, 1, 2) self.gridLayout_295.addLayout(self.gridLayout_290, 8, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_reproject_bands, "") self.tab_split_raster = QtWidgets.QWidget() self.tab_split_raster.setObjectName("tab_split_raster") self.gridLayout_57 = QtWidgets.QGridLayout(self.tab_split_raster) self.gridLayout_57.setObjectName("gridLayout_57") spacerItem68 = QtWidgets.QSpacerItem(20, 302, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_57.addItem(spacerItem68, 3, 1, 1, 1) self.gridLayout_190 = QtWidgets.QGridLayout() self.gridLayout_190.setObjectName("gridLayout_190") self.raster_name_combo = QtWidgets.QComboBox(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_name_combo.sizePolicy().hasHeightForWidth()) self.raster_name_combo.setSizePolicy(sizePolicy) self.raster_name_combo.setObjectName("raster_name_combo") self.gridLayout_190.addWidget(self.raster_name_combo, 1, 1, 1, 1) self.label_57 = QtWidgets.QLabel(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_57.sizePolicy().hasHeightForWidth()) self.label_57.setSizePolicy(sizePolicy) self.label_57.setStyleSheet("background-color : #656565; color : white") self.label_57.setFrameShape(QtWidgets.QFrame.Panel) self.label_57.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_57.setObjectName("label_57") self.gridLayout_190.addWidget(self.label_57, 0, 0, 1, 3) self.label_50 = QtWidgets.QLabel(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_50.sizePolicy().hasHeightForWidth()) self.label_50.setSizePolicy(sizePolicy) self.label_50.setMinimumSize(QtCore.QSize(229, 0)) self.label_50.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_50.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_50.setObjectName("label_50") self.gridLayout_190.addWidget(self.label_50, 1, 0, 1, 1) self.toolButton_reload_9 = QtWidgets.QToolButton(self.tab_split_raster) self.toolButton_reload_9.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_9.setIcon(icon55) self.toolButton_reload_9.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_9.setObjectName("toolButton_reload_9") self.gridLayout_190.addWidget(self.toolButton_reload_9, 1, 2, 1, 1) self.gridLayout_57.addLayout(self.gridLayout_190, 0, 0, 1, 4) self.label_165 = QtWidgets.QLabel(self.tab_split_raster) self.label_165.setStyleSheet("background-color : #656565; color : white") self.label_165.setFrameShape(QtWidgets.QFrame.Panel) self.label_165.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_165.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_165.setObjectName("label_165") self.gridLayout_57.addWidget(self.label_165, 4, 0, 1, 4) self.horizontalLayout_57 = QtWidgets.QHBoxLayout() self.horizontalLayout_57.setObjectName("horizontalLayout_57") self.label_61 = QtWidgets.QLabel(self.tab_split_raster) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_61.sizePolicy().hasHeightForWidth()) self.label_61.setSizePolicy(sizePolicy) self.label_61.setMinimumSize(QtCore.QSize(229, 0)) self.label_61.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_61.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_61.setObjectName("label_61") self.horizontalLayout_57.addWidget(self.label_61) self.output_name_lineEdit = QtWidgets.QLineEdit(self.tab_split_raster) self.output_name_lineEdit.setMaxLength(10) self.output_name_lineEdit.setObjectName("output_name_lineEdit") self.horizontalLayout_57.addWidget(self.output_name_lineEdit) self.gridLayout_57.addLayout(self.horizontalLayout_57, 1, 0, 1, 4) self.horizontalLayout_54 = QtWidgets.QHBoxLayout() self.horizontalLayout_54.setObjectName("horizontalLayout_54") spacerItem69 = QtWidgets.QSpacerItem(667, 38, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_54.addItem(spacerItem69) self.split_raster_bands = QtWidgets.QToolButton(self.tab_split_raster) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.split_raster_bands.setFont(font) self.split_raster_bands.setLayoutDirection(QtCore.Qt.RightToLeft) self.split_raster_bands.setStyleSheet("margin: 0px;padding: 0px;") self.split_raster_bands.setIcon(icon48) self.split_raster_bands.setIconSize(QtCore.QSize(34, 34)) self.split_raster_bands.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.split_raster_bands.setObjectName("split_raster_bands") self.horizontalLayout_54.addWidget(self.split_raster_bands) self.split_Button = QtWidgets.QToolButton(self.tab_split_raster) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.split_Button.setFont(font) self.split_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.split_Button.setStyleSheet("margin: 0px;padding: 0px;") self.split_Button.setIcon(icon64) self.split_Button.setIconSize(QtCore.QSize(34, 34)) self.split_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.split_Button.setObjectName("split_Button") self.horizontalLayout_54.addWidget(self.split_Button) self.gridLayout_57.addLayout(self.horizontalLayout_54, 5, 0, 1, 4) self.tabWidget_preprocessing.addTab(self.tab_split_raster, "") self.tab_stack_bands = QtWidgets.QWidget() self.tab_stack_bands.setObjectName("tab_stack_bands") self.gridLayout_23 = QtWidgets.QGridLayout(self.tab_stack_bands) self.gridLayout_23.setObjectName("gridLayout_23") self.label_252 = QtWidgets.QLabel(self.tab_stack_bands) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_252.sizePolicy().hasHeightForWidth()) self.label_252.setSizePolicy(sizePolicy) self.label_252.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_252.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_252.setObjectName("label_252") self.gridLayout_23.addWidget(self.label_252, 1, 0, 1, 1) self.band_set_comb_spinBox_3 = QtWidgets.QSpinBox(self.tab_stack_bands) self.band_set_comb_spinBox_3.setMinimum(1) self.band_set_comb_spinBox_3.setMaximum(100000) self.band_set_comb_spinBox_3.setObjectName("band_set_comb_spinBox_3") self.gridLayout_23.addWidget(self.band_set_comb_spinBox_3, 1, 1, 1, 1) spacerItem70 = QtWidgets.QSpacerItem(647, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_23.addItem(spacerItem70, 1, 3, 1, 1) spacerItem71 = QtWidgets.QSpacerItem(20, 339, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_23.addItem(spacerItem71, 2, 0, 1, 1) self.horizontalLayout_53 = QtWidgets.QHBoxLayout() self.horizontalLayout_53.setObjectName("horizontalLayout_53") spacerItem72 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_53.addItem(spacerItem72) self.stack_raster_bands = QtWidgets.QToolButton(self.tab_stack_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.stack_raster_bands.setFont(font) self.stack_raster_bands.setLayoutDirection(QtCore.Qt.RightToLeft) self.stack_raster_bands.setStyleSheet("margin: 0px;padding: 0px;") self.stack_raster_bands.setIcon(icon48) self.stack_raster_bands.setIconSize(QtCore.QSize(34, 34)) self.stack_raster_bands.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.stack_raster_bands.setObjectName("stack_raster_bands") self.horizontalLayout_53.addWidget(self.stack_raster_bands) self.stack_Button = QtWidgets.QToolButton(self.tab_stack_bands) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.stack_Button.setFont(font) self.stack_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.stack_Button.setStyleSheet("margin: 0px;padding: 0px;") self.stack_Button.setIcon(icon64) self.stack_Button.setIconSize(QtCore.QSize(34, 34)) self.stack_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.stack_Button.setObjectName("stack_Button") self.horizontalLayout_53.addWidget(self.stack_Button) self.gridLayout_23.addLayout(self.horizontalLayout_53, 4, 0, 1, 4) self.label_223 = QtWidgets.QLabel(self.tab_stack_bands) self.label_223.setStyleSheet("background-color : #656565; color : white") self.label_223.setFrameShape(QtWidgets.QFrame.Panel) self.label_223.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_223.setObjectName("label_223") self.gridLayout_23.addWidget(self.label_223, 0, 0, 1, 4) self.label_226 = QtWidgets.QLabel(self.tab_stack_bands) self.label_226.setStyleSheet("background-color : #656565; color : white") self.label_226.setFrameShape(QtWidgets.QFrame.Panel) self.label_226.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_226.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_226.setObjectName("label_226") self.gridLayout_23.addWidget(self.label_226, 3, 0, 1, 4) self.tabWidget_preprocessing.addTab(self.tab_stack_bands, "") self.tab_mosaic_band_sets = QtWidgets.QWidget() self.tab_mosaic_band_sets.setObjectName("tab_mosaic_band_sets") self.gridLayout_278 = QtWidgets.QGridLayout(self.tab_mosaic_band_sets) self.gridLayout_278.setObjectName("gridLayout_278") self.horizontalLayout_28 = QtWidgets.QHBoxLayout() self.horizontalLayout_28.setObjectName("horizontalLayout_28") self.label_134 = QtWidgets.QLabel(self.tab_mosaic_band_sets) self.label_134.setStyleSheet("background-color : #656565; color : white") self.label_134.setFrameShape(QtWidgets.QFrame.Panel) self.label_134.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_134.setObjectName("label_134") self.horizontalLayout_28.addWidget(self.label_134) self.gridLayout_278.addLayout(self.horizontalLayout_28, 0, 0, 1, 1) self.gridLayout_66 = QtWidgets.QGridLayout() self.gridLayout_66.setObjectName("gridLayout_66") self.label_135 = QtWidgets.QLabel(self.tab_mosaic_band_sets) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_135.sizePolicy().hasHeightForWidth()) self.label_135.setSizePolicy(sizePolicy) self.label_135.setMinimumSize(QtCore.QSize(229, 0)) self.label_135.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_135.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_135.setObjectName("label_135") self.gridLayout_66.addWidget(self.label_135, 3, 0, 1, 1) self.nodata_checkBox_9 = QtWidgets.QCheckBox(self.tab_mosaic_band_sets) self.nodata_checkBox_9.setChecked(True) self.nodata_checkBox_9.setObjectName("nodata_checkBox_9") self.gridLayout_66.addWidget(self.nodata_checkBox_9, 1, 0, 1, 1) self.nodata_spinBox_10 = QtWidgets.QSpinBox(self.tab_mosaic_band_sets) self.nodata_spinBox_10.setMinimum(-2147483647) self.nodata_spinBox_10.setMaximum(2147483647) self.nodata_spinBox_10.setObjectName("nodata_spinBox_10") self.gridLayout_66.addWidget(self.nodata_spinBox_10, 1, 1, 1, 1) spacerItem73 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_66.addItem(spacerItem73, 1, 2, 1, 1) self.mosaic_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_mosaic_band_sets) self.mosaic_output_name_lineEdit.setMaxLength(10) self.mosaic_output_name_lineEdit.setObjectName("mosaic_output_name_lineEdit") self.gridLayout_66.addWidget(self.mosaic_output_name_lineEdit, 3, 1, 1, 2) self.label_144 = QtWidgets.QLabel(self.tab_mosaic_band_sets) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_144.sizePolicy().hasHeightForWidth()) self.label_144.setSizePolicy(sizePolicy) self.label_144.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_144.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_144.setObjectName("label_144") self.gridLayout_66.addWidget(self.label_144, 0, 0, 1, 1) self.mosaic_band_sets_lineEdit = QtWidgets.QLineEdit(self.tab_mosaic_band_sets) self.mosaic_band_sets_lineEdit.setObjectName("mosaic_band_sets_lineEdit") self.gridLayout_66.addWidget(self.mosaic_band_sets_lineEdit, 0, 1, 1, 2) self.mosaic_virtual_checkBox = QtWidgets.QCheckBox(self.tab_mosaic_band_sets) self.mosaic_virtual_checkBox.setObjectName("mosaic_virtual_checkBox") self.gridLayout_66.addWidget(self.mosaic_virtual_checkBox, 2, 0, 1, 1) self.gridLayout_278.addLayout(self.gridLayout_66, 1, 0, 1, 1) spacerItem74 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_278.addItem(spacerItem74, 2, 0, 1, 1) self.gridLayout_228 = QtWidgets.QGridLayout() self.gridLayout_228.setObjectName("gridLayout_228") spacerItem75 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_228.addItem(spacerItem75, 1, 0, 1, 1) self.mosaic_bandsets_toolButton = QtWidgets.QToolButton(self.tab_mosaic_band_sets) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.mosaic_bandsets_toolButton.setFont(font) self.mosaic_bandsets_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.mosaic_bandsets_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.mosaic_bandsets_toolButton.setIcon(icon64) self.mosaic_bandsets_toolButton.setIconSize(QtCore.QSize(34, 34)) self.mosaic_bandsets_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.mosaic_bandsets_toolButton.setObjectName("mosaic_bandsets_toolButton") self.gridLayout_228.addWidget(self.mosaic_bandsets_toolButton, 1, 2, 1, 1) self.mosaic_bandsets = QtWidgets.QToolButton(self.tab_mosaic_band_sets) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.mosaic_bandsets.setFont(font) self.mosaic_bandsets.setLayoutDirection(QtCore.Qt.RightToLeft) self.mosaic_bandsets.setStyleSheet("margin: 0px;padding: 0px;") self.mosaic_bandsets.setIcon(icon48) self.mosaic_bandsets.setIconSize(QtCore.QSize(34, 34)) self.mosaic_bandsets.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.mosaic_bandsets.setObjectName("mosaic_bandsets") self.gridLayout_228.addWidget(self.mosaic_bandsets, 1, 1, 1, 1) self.label_182 = QtWidgets.QLabel(self.tab_mosaic_band_sets) self.label_182.setStyleSheet("background-color : #656565; color : white") self.label_182.setFrameShape(QtWidgets.QFrame.Panel) self.label_182.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_182.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_182.setObjectName("label_182") self.gridLayout_228.addWidget(self.label_182, 0, 0, 1, 3) self.gridLayout_278.addLayout(self.gridLayout_228, 3, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_mosaic_band_sets, "") self.tab_cloud_mask = QtWidgets.QWidget() self.tab_cloud_mask.setObjectName("tab_cloud_mask") self.gridLayout_296 = QtWidgets.QGridLayout(self.tab_cloud_mask) self.gridLayout_296.setObjectName("gridLayout_296") self.gridLayout_261 = QtWidgets.QGridLayout() self.gridLayout_261.setObjectName("gridLayout_261") self.label_260 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_260.sizePolicy().hasHeightForWidth()) self.label_260.setSizePolicy(sizePolicy) self.label_260.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_260.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_260.setObjectName("label_260") self.gridLayout_261.addWidget(self.label_260, 0, 0, 1, 1) spacerItem76 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_261.addItem(spacerItem76, 0, 2, 1, 1) self.band_set_comb_spinBox_9 = QtWidgets.QSpinBox(self.tab_cloud_mask) self.band_set_comb_spinBox_9.setMinimum(1) self.band_set_comb_spinBox_9.setMaximum(100000) self.band_set_comb_spinBox_9.setObjectName("band_set_comb_spinBox_9") self.gridLayout_261.addWidget(self.band_set_comb_spinBox_9, 0, 1, 1, 1) self.gridLayout_296.addLayout(self.gridLayout_261, 1, 0, 1, 2) self.gridLayout_106 = QtWidgets.QGridLayout() self.gridLayout_106.setObjectName("gridLayout_106") self.classification_name_combo_4 = QtWidgets.QComboBox(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_4.sizePolicy().hasHeightForWidth()) self.classification_name_combo_4.setSizePolicy(sizePolicy) self.classification_name_combo_4.setObjectName("classification_name_combo_4") self.gridLayout_106.addWidget(self.classification_name_combo_4, 0, 1, 1, 1) self.cloud_mask_classes_lineEdit = QtWidgets.QLineEdit(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.cloud_mask_classes_lineEdit.sizePolicy().hasHeightForWidth()) self.cloud_mask_classes_lineEdit.setSizePolicy(sizePolicy) self.cloud_mask_classes_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.cloud_mask_classes_lineEdit.setText("") self.cloud_mask_classes_lineEdit.setMaxLength(10000) self.cloud_mask_classes_lineEdit.setObjectName("cloud_mask_classes_lineEdit") self.gridLayout_106.addWidget(self.cloud_mask_classes_lineEdit, 1, 1, 1, 1) self.label_203 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_203.sizePolicy().hasHeightForWidth()) self.label_203.setSizePolicy(sizePolicy) self.label_203.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_203.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_203.setObjectName("label_203") self.gridLayout_106.addWidget(self.label_203, 1, 0, 1, 1) self.label_186 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_186.sizePolicy().hasHeightForWidth()) self.label_186.setSizePolicy(sizePolicy) self.label_186.setMinimumSize(QtCore.QSize(229, 0)) self.label_186.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_186.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_186.setObjectName("label_186") self.gridLayout_106.addWidget(self.label_186, 0, 0, 1, 1) self.toolButton_reload_23 = QtWidgets.QToolButton(self.tab_cloud_mask) self.toolButton_reload_23.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_23.setIcon(icon55) self.toolButton_reload_23.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_23.setObjectName("toolButton_reload_23") self.gridLayout_106.addWidget(self.toolButton_reload_23, 0, 2, 1, 1) self.gridLayout_296.addLayout(self.gridLayout_106, 2, 0, 1, 2) self.gridLayout_143 = QtWidgets.QGridLayout() self.gridLayout_143.setObjectName("gridLayout_143") self.label_140 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_140.sizePolicy().hasHeightForWidth()) self.label_140.setSizePolicy(sizePolicy) self.label_140.setMinimumSize(QtCore.QSize(229, 0)) self.label_140.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_140.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_140.setObjectName("label_140") self.gridLayout_143.addWidget(self.label_140, 1, 0, 1, 1) self.mask_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_cloud_mask) self.mask_output_name_lineEdit.setMaxLength(10) self.mask_output_name_lineEdit.setObjectName("mask_output_name_lineEdit") self.gridLayout_143.addWidget(self.mask_output_name_lineEdit, 1, 1, 1, 1) self.gridLayout_145 = QtWidgets.QGridLayout() self.gridLayout_145.setObjectName("gridLayout_145") self.cloud_buffer_spinBox = QtWidgets.QSpinBox(self.tab_cloud_mask) self.cloud_buffer_spinBox.setMinimum(1) self.cloud_buffer_spinBox.setMaximum(1000) self.cloud_buffer_spinBox.setProperty("value", 1) self.cloud_buffer_spinBox.setObjectName("cloud_buffer_spinBox") self.gridLayout_145.addWidget(self.cloud_buffer_spinBox, 0, 1, 1, 1) spacerItem77 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_145.addItem(spacerItem77, 0, 2, 1, 1) self.cloud_buffer_checkBox = QtWidgets.QCheckBox(self.tab_cloud_mask) self.cloud_buffer_checkBox.setEnabled(True) self.cloud_buffer_checkBox.setObjectName("cloud_buffer_checkBox") self.gridLayout_145.addWidget(self.cloud_buffer_checkBox, 0, 0, 1, 1) self.nodata_spinBox_11 = QtWidgets.QSpinBox(self.tab_cloud_mask) self.nodata_spinBox_11.setMinimum(-2147483647) self.nodata_spinBox_11.setMaximum(2147483647) self.nodata_spinBox_11.setProperty("value", -32768) self.nodata_spinBox_11.setObjectName("nodata_spinBox_11") self.gridLayout_145.addWidget(self.nodata_spinBox_11, 1, 1, 1, 1) self.label_141 = QtWidgets.QLabel(self.tab_cloud_mask) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_141.sizePolicy().hasHeightForWidth()) self.label_141.setSizePolicy(sizePolicy) self.label_141.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_141.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_141.setObjectName("label_141") self.gridLayout_145.addWidget(self.label_141, 1, 0, 1, 1) self.gridLayout_143.addLayout(self.gridLayout_145, 0, 0, 1, 2) self.gridLayout_296.addLayout(self.gridLayout_143, 3, 0, 1, 2) spacerItem78 = QtWidgets.QSpacerItem(20, 173, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_296.addItem(spacerItem78, 4, 1, 1, 1) self.gridLayout_257 = QtWidgets.QGridLayout() self.gridLayout_257.setObjectName("gridLayout_257") self.cloud_mask_toolButton = QtWidgets.QToolButton(self.tab_cloud_mask) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.cloud_mask_toolButton.setFont(font) self.cloud_mask_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.cloud_mask_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.cloud_mask_toolButton.setIcon(icon64) self.cloud_mask_toolButton.setIconSize(QtCore.QSize(34, 34)) self.cloud_mask_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.cloud_mask_toolButton.setObjectName("cloud_mask_toolButton") self.gridLayout_257.addWidget(self.cloud_mask_toolButton, 1, 2, 1, 1) self.cloud_masking = QtWidgets.QToolButton(self.tab_cloud_mask) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.cloud_masking.setFont(font) self.cloud_masking.setLayoutDirection(QtCore.Qt.RightToLeft) self.cloud_masking.setStyleSheet("margin: 0px;padding: 0px;") self.cloud_masking.setIcon(icon48) self.cloud_masking.setIconSize(QtCore.QSize(34, 34)) self.cloud_masking.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.cloud_masking.setObjectName("cloud_masking") self.gridLayout_257.addWidget(self.cloud_masking, 1, 1, 1, 1) spacerItem79 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_257.addItem(spacerItem79, 1, 0, 1, 1) self.label_185 = QtWidgets.QLabel(self.tab_cloud_mask) self.label_185.setStyleSheet("background-color : #656565; color : white") self.label_185.setFrameShape(QtWidgets.QFrame.Panel) self.label_185.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_185.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_185.setObjectName("label_185") self.gridLayout_257.addWidget(self.label_185, 0, 0, 1, 3) self.gridLayout_296.addLayout(self.gridLayout_257, 5, 0, 1, 2) self.horizontalLayout_33 = QtWidgets.QHBoxLayout() self.horizontalLayout_33.setObjectName("horizontalLayout_33") self.label_138 = QtWidgets.QLabel(self.tab_cloud_mask) self.label_138.setStyleSheet("background-color : #656565; color : white") self.label_138.setFrameShape(QtWidgets.QFrame.Panel) self.label_138.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_138.setObjectName("label_138") self.horizontalLayout_33.addWidget(self.label_138) self.gridLayout_296.addLayout(self.horizontalLayout_33, 0, 0, 1, 2) self.tabWidget_preprocessing.addTab(self.tab_cloud_mask, "") self.tab_GOES = QtWidgets.QWidget() self.tab_GOES.setObjectName("tab_GOES") self.gridLayout_308 = QtWidgets.QGridLayout(self.tab_GOES) self.gridLayout_308.setObjectName("gridLayout_308") self.gridLayout_297 = QtWidgets.QGridLayout() self.gridLayout_297.setObjectName("gridLayout_297") self.gridLayout_298 = QtWidgets.QGridLayout() self.gridLayout_298.setObjectName("gridLayout_298") self.GOES_nodata_spinBox = QtWidgets.QSpinBox(self.tab_GOES) self.GOES_nodata_spinBox.setMinimum(-999) self.GOES_nodata_spinBox.setMaximum(100000) self.GOES_nodata_spinBox.setObjectName("GOES_nodata_spinBox") self.gridLayout_298.addWidget(self.GOES_nodata_spinBox, 0, 2, 1, 1) self.GOES_nodata_checkBox = QtWidgets.QCheckBox(self.tab_GOES) self.GOES_nodata_checkBox.setChecked(True) self.GOES_nodata_checkBox.setObjectName("GOES_nodata_checkBox") self.gridLayout_298.addWidget(self.GOES_nodata_checkBox, 0, 1, 1, 1) spacerItem80 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_298.addItem(spacerItem80, 0, 0, 1, 1) self.gridLayout_297.addLayout(self.gridLayout_298, 3, 1, 1, 2) self.label_273 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_273.sizePolicy().hasHeightForWidth()) self.label_273.setSizePolicy(sizePolicy) self.label_273.setStyleSheet("background-color : #656565; color : white") self.label_273.setFrameShape(QtWidgets.QFrame.Panel) self.label_273.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_273.setObjectName("label_273") self.gridLayout_297.addWidget(self.label_273, 0, 0, 1, 3) self.GOES_create_bandset_checkBox = QtWidgets.QCheckBox(self.tab_GOES) self.GOES_create_bandset_checkBox.setChecked(True) self.GOES_create_bandset_checkBox.setTristate(False) self.GOES_create_bandset_checkBox.setObjectName("GOES_create_bandset_checkBox") self.gridLayout_297.addWidget(self.GOES_create_bandset_checkBox, 4, 0, 1, 1) self.label_274 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_274.sizePolicy().hasHeightForWidth()) self.label_274.setSizePolicy(sizePolicy) self.label_274.setMinimumSize(QtCore.QSize(229, 0)) self.label_274.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_274.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_274.setObjectName("label_274") self.gridLayout_297.addWidget(self.label_274, 2, 0, 1, 1) self.gridLayout_299 = QtWidgets.QGridLayout() self.gridLayout_299.setObjectName("gridLayout_299") self.GOES_toolButton_directoryInput = QtWidgets.QToolButton(self.tab_GOES) self.GOES_toolButton_directoryInput.setStyleSheet("margin: 0px;padding: 0px;") self.GOES_toolButton_directoryInput.setIcon(icon69) self.GOES_toolButton_directoryInput.setIconSize(QtCore.QSize(22, 22)) self.GOES_toolButton_directoryInput.setObjectName("GOES_toolButton_directoryInput") self.gridLayout_299.addWidget(self.GOES_toolButton_directoryInput, 0, 1, 1, 1) self.GOES_label = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.GOES_label.sizePolicy().hasHeightForWidth()) self.GOES_label.setSizePolicy(sizePolicy) self.GOES_label.setFrameShape(QtWidgets.QFrame.Panel) self.GOES_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.GOES_label.setText("") self.GOES_label.setObjectName("GOES_label") self.gridLayout_299.addWidget(self.GOES_label, 0, 0, 1, 1) self.gridLayout_297.addLayout(self.gridLayout_299, 2, 1, 1, 2) self.add_new_bandset_checkBox_7 = QtWidgets.QCheckBox(self.tab_GOES) self.add_new_bandset_checkBox_7.setChecked(True) self.add_new_bandset_checkBox_7.setTristate(False) self.add_new_bandset_checkBox_7.setObjectName("add_new_bandset_checkBox_7") self.gridLayout_297.addWidget(self.add_new_bandset_checkBox_7, 4, 1, 1, 2) self.gridLayout_308.addLayout(self.gridLayout_297, 0, 0, 1, 1) self.gridLayout_304 = QtWidgets.QGridLayout() self.gridLayout_304.setObjectName("gridLayout_304") self.GOES_tableWidget = QtWidgets.QTableWidget(self.tab_GOES) self.GOES_tableWidget.setTextElideMode(QtCore.Qt.ElideMiddle) self.GOES_tableWidget.setObjectName("GOES_tableWidget") self.GOES_tableWidget.setColumnCount(1) self.GOES_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.GOES_tableWidget.setHorizontalHeaderItem(0, item) self.GOES_tableWidget.horizontalHeader().setDefaultSectionSize(155) self.GOES_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_304.addWidget(self.GOES_tableWidget, 1, 0, 1, 1) self.gridLayout_305 = QtWidgets.QGridLayout() self.gridLayout_305.setObjectName("gridLayout_305") self.GOES_pushButton_remove_band = QtWidgets.QToolButton(self.tab_GOES) self.GOES_pushButton_remove_band.setStyleSheet("margin: 0px;padding: 0px;") self.GOES_pushButton_remove_band.setIcon(icon58) self.GOES_pushButton_remove_band.setIconSize(QtCore.QSize(22, 22)) self.GOES_pushButton_remove_band.setObjectName("GOES_pushButton_remove_band") self.gridLayout_305.addWidget(self.GOES_pushButton_remove_band, 0, 0, 1, 1) self.gridLayout_304.addLayout(self.gridLayout_305, 1, 1, 1, 1) self.gridLayout_306 = QtWidgets.QGridLayout() self.gridLayout_306.setObjectName("gridLayout_306") self.label_277 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_277.sizePolicy().hasHeightForWidth()) self.label_277.setSizePolicy(sizePolicy) self.label_277.setStyleSheet("background-color : #656565; color : white") self.label_277.setFrameShape(QtWidgets.QFrame.Panel) self.label_277.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_277.setObjectName("label_277") self.gridLayout_306.addWidget(self.label_277, 0, 0, 1, 4) self.satellite_label_20 = QtWidgets.QLabel(self.tab_GOES) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.satellite_label_20.sizePolicy().hasHeightForWidth()) self.satellite_label_20.setSizePolicy(sizePolicy) self.satellite_label_20.setFrameShadow(QtWidgets.QFrame.Sunken) self.satellite_label_20.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.satellite_label_20.setObjectName("satellite_label_20") self.gridLayout_306.addWidget(self.satellite_label_20, 1, 0, 1, 1) self.GOES_satellite_lineEdit = QtWidgets.QLineEdit(self.tab_GOES) self.GOES_satellite_lineEdit.setObjectName("GOES_satellite_lineEdit") self.gridLayout_306.addWidget(self.GOES_satellite_lineEdit, 1, 1, 1, 1) spacerItem81 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_306.addItem(spacerItem81, 1, 2, 1, 1) self.gridLayout_304.addLayout(self.gridLayout_306, 0, 0, 1, 2) self.gridLayout_307 = QtWidgets.QGridLayout() self.gridLayout_307.setObjectName("gridLayout_307") spacerItem82 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_307.addItem(spacerItem82, 1, 1, 1, 1) self.label_278 = QtWidgets.QLabel(self.tab_GOES) self.label_278.setStyleSheet("background-color : #656565; color : white") self.label_278.setFrameShape(QtWidgets.QFrame.Panel) self.label_278.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_278.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_278.setObjectName("label_278") self.gridLayout_307.addWidget(self.label_278, 0, 1, 1, 3) self.pushButton_Conversion_8 = QtWidgets.QToolButton(self.tab_GOES) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pushButton_Conversion_8.setFont(font) self.pushButton_Conversion_8.setLayoutDirection(QtCore.Qt.RightToLeft) self.pushButton_Conversion_8.setStyleSheet("margin: 0px;padding: 0px;") self.pushButton_Conversion_8.setIcon(icon64) self.pushButton_Conversion_8.setIconSize(QtCore.QSize(34, 34)) self.pushButton_Conversion_8.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pushButton_Conversion_8.setObjectName("pushButton_Conversion_8") self.gridLayout_307.addWidget(self.pushButton_Conversion_8, 1, 3, 1, 1) self.goes_conversion = QtWidgets.QToolButton(self.tab_GOES) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.goes_conversion.setFont(font) self.goes_conversion.setLayoutDirection(QtCore.Qt.RightToLeft) self.goes_conversion.setStyleSheet("margin: 0px;padding: 0px;") self.goes_conversion.setIcon(icon48) self.goes_conversion.setIconSize(QtCore.QSize(34, 34)) self.goes_conversion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.goes_conversion.setObjectName("goes_conversion") self.gridLayout_307.addWidget(self.goes_conversion, 1, 2, 1, 1) self.gridLayout_304.addLayout(self.gridLayout_307, 2, 0, 1, 2) self.gridLayout_308.addLayout(self.gridLayout_304, 1, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_GOES, "") self.tab_neighbor_pixels = QtWidgets.QWidget() self.tab_neighbor_pixels.setObjectName("tab_neighbor_pixels") self.gridLayout_310 = QtWidgets.QGridLayout(self.tab_neighbor_pixels) self.gridLayout_310.setObjectName("gridLayout_310") self.gridLayout_240 = QtWidgets.QGridLayout() self.gridLayout_240.setObjectName("gridLayout_240") self.label_283 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_283.setStyleSheet("background-color : #656565; color : white") self.label_283.setFrameShape(QtWidgets.QFrame.Panel) self.label_283.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_283.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_283.setObjectName("label_283") self.gridLayout_240.addWidget(self.label_283, 8, 0, 1, 3) self.gridLayout_309 = QtWidgets.QGridLayout() self.gridLayout_309.setObjectName("gridLayout_309") self.label_287 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_287.sizePolicy().hasHeightForWidth()) self.label_287.setSizePolicy(sizePolicy) self.label_287.setFrameShape(QtWidgets.QFrame.Panel) self.label_287.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_287.setText("") self.label_287.setObjectName("label_287") self.gridLayout_309.addWidget(self.label_287, 0, 1, 1, 1) self.label_281 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_281.sizePolicy().hasHeightForWidth()) self.label_281.setSizePolicy(sizePolicy) self.label_281.setMinimumSize(QtCore.QSize(229, 0)) font = QtGui.QFont() font.setBold(False) font.setWeight(50) self.label_281.setFont(font) self.label_281.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_281.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_281.setObjectName("label_281") self.gridLayout_309.addWidget(self.label_281, 0, 0, 1, 1) self.toolButton_input_matrix = QtWidgets.QToolButton(self.tab_neighbor_pixels) self.toolButton_input_matrix.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_input_matrix.setIcon(icon65) self.toolButton_input_matrix.setIconSize(QtCore.QSize(22, 22)) self.toolButton_input_matrix.setObjectName("toolButton_input_matrix") self.gridLayout_309.addWidget(self.toolButton_input_matrix, 0, 2, 1, 1) self.horizontalLayout_71 = QtWidgets.QHBoxLayout() self.horizontalLayout_71.setObjectName("horizontalLayout_71") self.label_279 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_279.sizePolicy().hasHeightForWidth()) self.label_279.setSizePolicy(sizePolicy) self.label_279.setMinimumSize(QtCore.QSize(229, 0)) self.label_279.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_279.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_279.setObjectName("label_279") self.horizontalLayout_71.addWidget(self.label_279) self.neighbor_output_name_lineEdit = QtWidgets.QLineEdit(self.tab_neighbor_pixels) self.neighbor_output_name_lineEdit.setMaxLength(10) self.neighbor_output_name_lineEdit.setObjectName("neighbor_output_name_lineEdit") self.horizontalLayout_71.addWidget(self.neighbor_output_name_lineEdit) self.gridLayout_309.addLayout(self.horizontalLayout_71, 2, 0, 1, 3) self.neighbor_virtual_checkBox = QtWidgets.QCheckBox(self.tab_neighbor_pixels) self.neighbor_virtual_checkBox.setObjectName("neighbor_virtual_checkBox") self.gridLayout_309.addWidget(self.neighbor_virtual_checkBox, 1, 0, 1, 1) self.gridLayout_240.addLayout(self.gridLayout_309, 2, 0, 1, 3) self.neighbor_pixels = QtWidgets.QToolButton(self.tab_neighbor_pixels) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.neighbor_pixels.setFont(font) self.neighbor_pixels.setLayoutDirection(QtCore.Qt.RightToLeft) self.neighbor_pixels.setStyleSheet("margin: 0px;padding: 0px;") self.neighbor_pixels.setIcon(icon48) self.neighbor_pixels.setIconSize(QtCore.QSize(34, 34)) self.neighbor_pixels.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.neighbor_pixels.setObjectName("neighbor_pixels") self.gridLayout_240.addWidget(self.neighbor_pixels, 9, 1, 1, 1) spacerItem83 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_240.addItem(spacerItem83, 9, 0, 1, 1) self.class_neighbor_toolButton = QtWidgets.QToolButton(self.tab_neighbor_pixels) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_neighbor_toolButton.setFont(font) self.class_neighbor_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_neighbor_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.class_neighbor_toolButton.setIcon(icon64) self.class_neighbor_toolButton.setIconSize(QtCore.QSize(34, 34)) self.class_neighbor_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_neighbor_toolButton.setObjectName("class_neighbor_toolButton") self.gridLayout_240.addWidget(self.class_neighbor_toolButton, 9, 2, 1, 1) spacerItem84 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_240.addItem(spacerItem84, 7, 2, 1, 1) self.horizontalLayout_70 = QtWidgets.QHBoxLayout() self.horizontalLayout_70.setObjectName("horizontalLayout_70") self.label_286 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_286.setStyleSheet("background-color : #656565; color : white") self.label_286.setFrameShape(QtWidgets.QFrame.Panel) self.label_286.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_286.setObjectName("label_286") self.horizontalLayout_70.addWidget(self.label_286) self.gridLayout_240.addLayout(self.horizontalLayout_70, 0, 0, 1, 3) self.gridLayout_277 = QtWidgets.QGridLayout() self.gridLayout_277.setObjectName("gridLayout_277") self.statistic_lineEdit_2 = QtWidgets.QLineEdit(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_lineEdit_2.sizePolicy().hasHeightForWidth()) self.statistic_lineEdit_2.setSizePolicy(sizePolicy) self.statistic_lineEdit_2.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_lineEdit_2.setText("") self.statistic_lineEdit_2.setMaxLength(10000) self.statistic_lineEdit_2.setObjectName("statistic_lineEdit_2") self.gridLayout_277.addWidget(self.statistic_lineEdit_2, 1, 2, 1, 1) self.statistic_name_combobox_2 = QtWidgets.QComboBox(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_name_combobox_2.sizePolicy().hasHeightForWidth()) self.statistic_name_combobox_2.setSizePolicy(sizePolicy) self.statistic_name_combobox_2.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_name_combobox_2.setObjectName("statistic_name_combobox_2") self.gridLayout_277.addWidget(self.statistic_name_combobox_2, 1, 1, 1, 1) self.label_284 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_284.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_284.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_284.setObjectName("label_284") self.gridLayout_277.addWidget(self.label_284, 1, 0, 1, 1) spacerItem85 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_277.addItem(spacerItem85, 1, 3, 1, 1) self.label_285 = QtWidgets.QLabel(self.tab_neighbor_pixels) self.label_285.setStyleSheet("background-color : #656565; color : white") self.label_285.setFrameShape(QtWidgets.QFrame.Panel) self.label_285.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_285.setObjectName("label_285") self.gridLayout_277.addWidget(self.label_285, 0, 0, 1, 4) self.gridLayout_240.addLayout(self.gridLayout_277, 6, 0, 1, 3) self.gridLayout_300 = QtWidgets.QGridLayout() self.gridLayout_300.setObjectName("gridLayout_300") self.label_282 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_282.sizePolicy().hasHeightForWidth()) self.label_282.setSizePolicy(sizePolicy) self.label_282.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_282.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_282.setObjectName("label_282") self.gridLayout_300.addWidget(self.label_282, 0, 0, 1, 1) self.label_280 = QtWidgets.QLabel(self.tab_neighbor_pixels) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_280.sizePolicy().hasHeightForWidth()) self.label_280.setSizePolicy(sizePolicy) self.label_280.setMinimumSize(QtCore.QSize(229, 0)) self.label_280.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_280.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_280.setObjectName("label_280") self.gridLayout_300.addWidget(self.label_280, 1, 0, 1, 1) self.band_set_comb_spinBox_15 = QtWidgets.QSpinBox(self.tab_neighbor_pixels) self.band_set_comb_spinBox_15.setMinimum(1) self.band_set_comb_spinBox_15.setMaximum(100000) self.band_set_comb_spinBox_15.setObjectName("band_set_comb_spinBox_15") self.gridLayout_300.addWidget(self.band_set_comb_spinBox_15, 0, 1, 1, 1) self.class_neighbor_threshold_spinBox = QtWidgets.QSpinBox(self.tab_neighbor_pixels) self.class_neighbor_threshold_spinBox.setMinimum(1) self.class_neighbor_threshold_spinBox.setMaximum(1000) self.class_neighbor_threshold_spinBox.setProperty("value", 1) self.class_neighbor_threshold_spinBox.setObjectName("class_neighbor_threshold_spinBox") self.gridLayout_300.addWidget(self.class_neighbor_threshold_spinBox, 1, 1, 1, 1) spacerItem86 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_300.addItem(spacerItem86, 1, 3, 1, 1) self.circular_structure_checkBox = QtWidgets.QCheckBox(self.tab_neighbor_pixels) self.circular_structure_checkBox.setObjectName("circular_structure_checkBox") self.gridLayout_300.addWidget(self.circular_structure_checkBox, 1, 2, 1, 1) self.gridLayout_240.addLayout(self.gridLayout_300, 1, 0, 1, 3) self.horizontalLayout_72 = QtWidgets.QHBoxLayout() self.horizontalLayout_72.setObjectName("horizontalLayout_72") spacerItem87 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_72.addItem(spacerItem87) self.gridLayout_240.addLayout(self.horizontalLayout_72, 3, 0, 1, 3) self.gridLayout_310.addLayout(self.gridLayout_240, 0, 0, 1, 1) self.tabWidget_preprocessing.addTab(self.tab_neighbor_pixels, "") self.gridLayout_6.addWidget(self.tabWidget_preprocessing, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_preprocessing, "") self.tab_band_processing = QtWidgets.QWidget() self.tab_band_processing.setObjectName("tab_band_processing") self.gridLayout_163 = QtWidgets.QGridLayout(self.tab_band_processing) self.gridLayout_163.setObjectName("gridLayout_163") self.tabWidget_4 = QtWidgets.QTabWidget(self.tab_band_processing) self.tabWidget_4.setStyleSheet("") self.tabWidget_4.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_4.setDocumentMode(True) self.tabWidget_4.setObjectName("tabWidget_4") self.tab_bandset_combination_2 = QtWidgets.QWidget() self.tab_bandset_combination_2.setObjectName("tab_bandset_combination_2") self.gridLayout_62 = QtWidgets.QGridLayout(self.tab_bandset_combination_2) self.gridLayout_62.setObjectName("gridLayout_62") self.toolBox_band_set_combination = QtWidgets.QToolBox(self.tab_bandset_combination_2) self.toolBox_band_set_combination.setObjectName("toolBox_band_set_combination") self.page_29 = QtWidgets.QWidget() self.page_29.setGeometry(QtCore.QRect(0, 0, 723, 351)) self.page_29.setObjectName("page_29") self.gridLayout_330 = QtWidgets.QGridLayout(self.page_29) self.gridLayout_330.setObjectName("gridLayout_330") self.gridLayout_333 = QtWidgets.QGridLayout() self.gridLayout_333.setObjectName("gridLayout_333") spacerItem88 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_333.addItem(spacerItem88, 0, 2, 1, 1) spacerItem89 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_333.addItem(spacerItem89, 2, 0, 1, 1) self.label_253 = QtWidgets.QLabel(self.page_29) self.label_253.setStyleSheet("background-color : #656565; color : white") self.label_253.setFrameShape(QtWidgets.QFrame.Panel) self.label_253.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_253.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_253.setObjectName("label_253") self.gridLayout_333.addWidget(self.label_253, 1, 0, 1, 3) self.calculateBandSetComb_toolButton = QtWidgets.QToolButton(self.page_29) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateBandSetComb_toolButton.setFont(font) self.calculateBandSetComb_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateBandSetComb_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateBandSetComb_toolButton.setIcon(icon64) self.calculateBandSetComb_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateBandSetComb_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateBandSetComb_toolButton.setObjectName("calculateBandSetComb_toolButton") self.gridLayout_333.addWidget(self.calculateBandSetComb_toolButton, 2, 2, 1, 1) self.band_combination = QtWidgets.QToolButton(self.page_29) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.band_combination.setFont(font) self.band_combination.setLayoutDirection(QtCore.Qt.RightToLeft) self.band_combination.setStyleSheet("margin: 0px;padding: 0px;") self.band_combination.setIcon(icon48) self.band_combination.setIconSize(QtCore.QSize(34, 34)) self.band_combination.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.band_combination.setObjectName("band_combination") self.gridLayout_333.addWidget(self.band_combination, 2, 1, 1, 1) self.gridLayout_330.addLayout(self.gridLayout_333, 2, 1, 1, 1) self.gridLayout_331 = QtWidgets.QGridLayout() self.gridLayout_331.setObjectName("gridLayout_331") self.label_250 = QtWidgets.QLabel(self.page_29) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_250.sizePolicy().hasHeightForWidth()) self.label_250.setSizePolicy(sizePolicy) self.label_250.setMinimumSize(QtCore.QSize(229, 0)) self.label_250.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_250.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_250.setWordWrap(True) self.label_250.setObjectName("label_250") self.gridLayout_331.addWidget(self.label_250, 1, 0, 1, 2) self.band_set_comb_spinBox = QtWidgets.QSpinBox(self.page_29) self.band_set_comb_spinBox.setMinimum(1) self.band_set_comb_spinBox.setMaximum(100000) self.band_set_comb_spinBox.setObjectName("band_set_comb_spinBox") self.gridLayout_331.addWidget(self.band_set_comb_spinBox, 1, 2, 1, 1) spacerItem90 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_331.addItem(spacerItem90, 1, 3, 1, 1) self.gridLayout_330.addLayout(self.gridLayout_331, 1, 1, 1, 1) self.horizontalLayout_34 = QtWidgets.QHBoxLayout() self.horizontalLayout_34.setObjectName("horizontalLayout_34") self.label_72 = QtWidgets.QLabel(self.page_29) self.label_72.setStyleSheet("background-color : #656565; color : white") self.label_72.setFrameShape(QtWidgets.QFrame.Panel) self.label_72.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_72.setObjectName("label_72") self.horizontalLayout_34.addWidget(self.label_72) self.gridLayout_330.addLayout(self.horizontalLayout_34, 0, 1, 1, 1) self.toolBox_band_set_combination.addItem(self.page_29, "") self.page_30 = QtWidgets.QWidget() self.page_30.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_30.setObjectName("page_30") self.gridLayout_334 = QtWidgets.QGridLayout(self.page_30) self.gridLayout_334.setObjectName("gridLayout_334") self.gridLayout_335 = QtWidgets.QGridLayout() self.gridLayout_335.setObjectName("gridLayout_335") self.band_set_comb_textBrowser = QtWidgets.QTextBrowser(self.page_30) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.band_set_comb_textBrowser.setFont(font) self.band_set_comb_textBrowser.setTabChangesFocus(True) self.band_set_comb_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.band_set_comb_textBrowser.setTabStopWidth(120) self.band_set_comb_textBrowser.setOpenLinks(False) self.band_set_comb_textBrowser.setObjectName("band_set_comb_textBrowser") self.gridLayout_335.addWidget(self.band_set_comb_textBrowser, 0, 0, 1, 1) self.gridLayout_334.addLayout(self.gridLayout_335, 0, 0, 1, 1) self.toolBox_band_set_combination.addItem(self.page_30, "") self.gridLayout_62.addWidget(self.toolBox_band_set_combination, 0, 0, 1, 1) self.tabWidget_4.addTab(self.tab_bandset_combination_2, "") self.PCA_tab = QtWidgets.QWidget() self.PCA_tab.setObjectName("PCA_tab") self.gridLayout_170 = QtWidgets.QGridLayout(self.PCA_tab) self.gridLayout_170.setObjectName("gridLayout_170") self.toolBox_PCA = QtWidgets.QToolBox(self.PCA_tab) self.toolBox_PCA.setStyleSheet("") self.toolBox_PCA.setObjectName("toolBox_PCA") self.page_16 = QtWidgets.QWidget() self.page_16.setGeometry(QtCore.QRect(0, 0, 459, 196)) self.page_16.setObjectName("page_16") self.gridLayout_182 = QtWidgets.QGridLayout(self.page_16) self.gridLayout_182.setObjectName("gridLayout_182") self.horizontalLayout_5 = QtWidgets.QHBoxLayout() self.horizontalLayout_5.setObjectName("horizontalLayout_5") self.label_58 = QtWidgets.QLabel(self.page_16) self.label_58.setStyleSheet("background-color : #656565; color : white") self.label_58.setFrameShape(QtWidgets.QFrame.Panel) self.label_58.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_58.setObjectName("label_58") self.horizontalLayout_5.addWidget(self.label_58) self.gridLayout_182.addLayout(self.horizontalLayout_5, 0, 0, 1, 1) self.gridLayout_173 = QtWidgets.QGridLayout() self.gridLayout_173.setObjectName("gridLayout_173") self.nodata_checkBox_4 = QtWidgets.QCheckBox(self.page_16) self.nodata_checkBox_4.setObjectName("nodata_checkBox_4") self.gridLayout_173.addWidget(self.nodata_checkBox_4, 2, 0, 1, 1) self.num_comp_checkBox = QtWidgets.QCheckBox(self.page_16) self.num_comp_checkBox.setObjectName("num_comp_checkBox") self.gridLayout_173.addWidget(self.num_comp_checkBox, 1, 0, 1, 1) self.nodata_spinBox_5 = QtWidgets.QSpinBox(self.page_16) self.nodata_spinBox_5.setMinimum(-999999999) self.nodata_spinBox_5.setMaximum(999999999) self.nodata_spinBox_5.setProperty("value", 0) self.nodata_spinBox_5.setObjectName("nodata_spinBox_5") self.gridLayout_173.addWidget(self.nodata_spinBox_5, 2, 1, 1, 1) spacerItem91 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_173.addItem(spacerItem91, 3, 4, 1, 1) self.pca_Button = QtWidgets.QToolButton(self.page_16) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pca_Button.setFont(font) self.pca_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.pca_Button.setStyleSheet("margin: 0px;padding: 0px;") self.pca_Button.setIcon(icon64) self.pca_Button.setIconSize(QtCore.QSize(34, 34)) self.pca_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pca_Button.setObjectName("pca_Button") self.gridLayout_173.addWidget(self.pca_Button, 5, 4, 1, 1) self.label_254 = QtWidgets.QLabel(self.page_16) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_254.sizePolicy().hasHeightForWidth()) self.label_254.setSizePolicy(sizePolicy) self.label_254.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_254.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_254.setObjectName("label_254") self.gridLayout_173.addWidget(self.label_254, 0, 0, 1, 1) self.band_set_comb_spinBox_4 = QtWidgets.QSpinBox(self.page_16) self.band_set_comb_spinBox_4.setMinimum(1) self.band_set_comb_spinBox_4.setMaximum(100000) self.band_set_comb_spinBox_4.setObjectName("band_set_comb_spinBox_4") self.gridLayout_173.addWidget(self.band_set_comb_spinBox_4, 0, 1, 1, 1) self.pca_components_spinBox = QtWidgets.QSpinBox(self.page_16) self.pca_components_spinBox.setMinimum(2) self.pca_components_spinBox.setMaximum(1000) self.pca_components_spinBox.setObjectName("pca_components_spinBox") self.gridLayout_173.addWidget(self.pca_components_spinBox, 1, 1, 1, 1) self.label_166 = QtWidgets.QLabel(self.page_16) self.label_166.setStyleSheet("background-color : #656565; color : white") self.label_166.setFrameShape(QtWidgets.QFrame.Panel) self.label_166.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_166.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_166.setObjectName("label_166") self.gridLayout_173.addWidget(self.label_166, 4, 0, 1, 5) spacerItem92 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_173.addItem(spacerItem92, 5, 2, 1, 1) self.pca = QtWidgets.QToolButton(self.page_16) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.pca.setFont(font) self.pca.setLayoutDirection(QtCore.Qt.RightToLeft) self.pca.setStyleSheet("margin: 0px;padding: 0px;") self.pca.setIcon(icon48) self.pca.setIconSize(QtCore.QSize(34, 34)) self.pca.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.pca.setObjectName("pca") self.gridLayout_173.addWidget(self.pca, 5, 3, 1, 1) self.gridLayout_182.addLayout(self.gridLayout_173, 1, 0, 1, 1) self.toolBox_PCA.addItem(self.page_16, "") self.page_17 = QtWidgets.QWidget() self.page_17.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_17.setObjectName("page_17") self.gridLayout_200 = QtWidgets.QGridLayout(self.page_17) self.gridLayout_200.setObjectName("gridLayout_200") self.gridLayout_201 = QtWidgets.QGridLayout() self.gridLayout_201.setObjectName("gridLayout_201") self.report_textBrowser_2 = QtWidgets.QTextBrowser(self.page_17) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_2.setFont(font) self.report_textBrowser_2.setTabChangesFocus(True) self.report_textBrowser_2.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_2.setTabStopWidth(160) self.report_textBrowser_2.setOpenLinks(False) self.report_textBrowser_2.setObjectName("report_textBrowser_2") self.gridLayout_201.addWidget(self.report_textBrowser_2, 0, 0, 1, 1) self.gridLayout_200.addLayout(self.gridLayout_201, 0, 0, 1, 1) self.toolBox_PCA.addItem(self.page_17, "") self.gridLayout_170.addWidget(self.toolBox_PCA, 0, 0, 1, 1) self.tabWidget_4.addTab(self.PCA_tab, "") self.tab_kmeans = QtWidgets.QWidget() self.tab_kmeans.setObjectName("tab_kmeans") self.gridLayout_208 = QtWidgets.QGridLayout(self.tab_kmeans) self.gridLayout_208.setObjectName("gridLayout_208") self.toolBox_kmeans = QtWidgets.QToolBox(self.tab_kmeans) self.toolBox_kmeans.setStyleSheet("") self.toolBox_kmeans.setObjectName("toolBox_kmeans") self.page_18 = QtWidgets.QWidget() self.page_18.setGeometry(QtCore.QRect(0, 0, 764, 390)) self.page_18.setObjectName("page_18") self.gridLayout_152 = QtWidgets.QGridLayout(self.page_18) self.gridLayout_152.setObjectName("gridLayout_152") self.horizontalLayout_29 = QtWidgets.QHBoxLayout() self.horizontalLayout_29.setObjectName("horizontalLayout_29") self.label_78 = QtWidgets.QLabel(self.page_18) self.label_78.setStyleSheet("background-color : #656565; color : white") self.label_78.setFrameShape(QtWidgets.QFrame.Panel) self.label_78.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_78.setObjectName("label_78") self.horizontalLayout_29.addWidget(self.label_78) self.gridLayout_152.addLayout(self.horizontalLayout_29, 0, 0, 1, 1) self.gridLayout_151 = QtWidgets.QGridLayout() self.gridLayout_151.setObjectName("gridLayout_151") self.isodata_radioButton = QtWidgets.QRadioButton(self.page_18) self.isodata_radioButton.setChecked(False) self.isodata_radioButton.setAutoExclusive(False) self.isodata_radioButton.setObjectName("isodata_radioButton") self.gridLayout_151.addWidget(self.isodata_radioButton, 0, 5, 1, 1) self.band_set_comb_spinBox_5 = QtWidgets.QSpinBox(self.page_18) self.band_set_comb_spinBox_5.setMinimum(1) self.band_set_comb_spinBox_5.setMaximum(100000) self.band_set_comb_spinBox_5.setObjectName("band_set_comb_spinBox_5") self.gridLayout_151.addWidget(self.band_set_comb_spinBox_5, 0, 1, 1, 1) self.label_230 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_230.sizePolicy().hasHeightForWidth()) self.label_230.setSizePolicy(sizePolicy) self.label_230.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_230.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_230.setObjectName("label_230") self.gridLayout_151.addWidget(self.label_230, 0, 3, 1, 1) self.label_255 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_255.sizePolicy().hasHeightForWidth()) self.label_255.setSizePolicy(sizePolicy) self.label_255.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_255.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_255.setObjectName("label_255") self.gridLayout_151.addWidget(self.label_255, 0, 0, 1, 1) self.kmeans_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmeans_radioButton.setChecked(True) self.kmeans_radioButton.setAutoExclusive(False) self.kmeans_radioButton.setObjectName("kmeans_radioButton") self.gridLayout_151.addWidget(self.kmeans_radioButton, 0, 4, 1, 1) spacerItem93 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_151.addItem(spacerItem93, 0, 2, 1, 1) spacerItem94 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_151.addItem(spacerItem94, 0, 6, 1, 1) self.gridLayout_152.addLayout(self.gridLayout_151, 1, 0, 1, 1) self.gridLayout_125 = QtWidgets.QGridLayout() self.gridLayout_125.setObjectName("gridLayout_125") self.label_225 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_225.sizePolicy().hasHeightForWidth()) self.label_225.setSizePolicy(sizePolicy) self.label_225.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_225.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_225.setObjectName("label_225") self.gridLayout_125.addWidget(self.label_225, 1, 0, 1, 1) self.thresh_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.page_18) self.thresh_doubleSpinBox.setDecimals(7) self.thresh_doubleSpinBox.setMinimum(1e-06) self.thresh_doubleSpinBox.setMaximum(10000000.0) self.thresh_doubleSpinBox.setSingleStep(1e-05) self.thresh_doubleSpinBox.setProperty("value", 0.0001) self.thresh_doubleSpinBox.setObjectName("thresh_doubleSpinBox") self.gridLayout_125.addWidget(self.thresh_doubleSpinBox, 0, 1, 1, 1) self.std_dev_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.page_18) self.std_dev_doubleSpinBox.setDecimals(7) self.std_dev_doubleSpinBox.setMinimum(1e-06) self.std_dev_doubleSpinBox.setMaximum(1000000000.0) self.std_dev_doubleSpinBox.setSingleStep(1e-05) self.std_dev_doubleSpinBox.setProperty("value", 0.0001) self.std_dev_doubleSpinBox.setObjectName("std_dev_doubleSpinBox") self.gridLayout_125.addWidget(self.std_dev_doubleSpinBox, 2, 1, 1, 1) self.kmean_threshold_checkBox = QtWidgets.QCheckBox(self.page_18) self.kmean_threshold_checkBox.setChecked(True) self.kmean_threshold_checkBox.setObjectName("kmean_threshold_checkBox") self.gridLayout_125.addWidget(self.kmean_threshold_checkBox, 0, 0, 1, 1) self.nodata_spinBox_9 = QtWidgets.QSpinBox(self.page_18) self.nodata_spinBox_9.setMinimum(-999999999) self.nodata_spinBox_9.setMaximum(999999999) self.nodata_spinBox_9.setProperty("value", 0) self.nodata_spinBox_9.setObjectName("nodata_spinBox_9") self.gridLayout_125.addWidget(self.nodata_spinBox_9, 4, 1, 1, 1) self.kmeans_iter_spinBox = QtWidgets.QSpinBox(self.page_18) self.kmeans_iter_spinBox.setMinimum(1) self.kmeans_iter_spinBox.setMaximum(1000) self.kmeans_iter_spinBox.setProperty("value", 10) self.kmeans_iter_spinBox.setObjectName("kmeans_iter_spinBox") self.gridLayout_125.addWidget(self.kmeans_iter_spinBox, 1, 1, 1, 1) self.label_228 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_228.sizePolicy().hasHeightForWidth()) self.label_228.setSizePolicy(sizePolicy) self.label_228.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_228.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_228.setWordWrap(True) self.label_228.setObjectName("label_228") self.gridLayout_125.addWidget(self.label_228, 2, 0, 1, 1) self.nodata_checkBox_8 = QtWidgets.QCheckBox(self.page_18) self.nodata_checkBox_8.setObjectName("nodata_checkBox_8") self.gridLayout_125.addWidget(self.nodata_checkBox_8, 4, 0, 1, 1) self.kmeans_classes_spinBox = QtWidgets.QSpinBox(self.page_18) self.kmeans_classes_spinBox.setMinimum(1) self.kmeans_classes_spinBox.setMaximum(1000) self.kmeans_classes_spinBox.setProperty("value", 10) self.kmeans_classes_spinBox.setObjectName("kmeans_classes_spinBox") self.gridLayout_125.addWidget(self.kmeans_classes_spinBox, 0, 3, 1, 1) self.label_224 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_224.sizePolicy().hasHeightForWidth()) self.label_224.setSizePolicy(sizePolicy) self.label_224.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_224.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_224.setObjectName("label_224") self.gridLayout_125.addWidget(self.label_224, 0, 2, 1, 1) spacerItem95 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_125.addItem(spacerItem95, 0, 4, 1, 1) self.label_229 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_229.sizePolicy().hasHeightForWidth()) self.label_229.setSizePolicy(sizePolicy) self.label_229.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_229.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_229.setWordWrap(True) self.label_229.setObjectName("label_229") self.gridLayout_125.addWidget(self.label_229, 2, 2, 1, 1) self.min_size_class_spinBox = QtWidgets.QSpinBox(self.page_18) self.min_size_class_spinBox.setMinimum(1) self.min_size_class_spinBox.setMaximum(1000000) self.min_size_class_spinBox.setProperty("value", 10) self.min_size_class_spinBox.setObjectName("min_size_class_spinBox") self.gridLayout_125.addWidget(self.min_size_class_spinBox, 2, 3, 1, 1) self.gridLayout_152.addLayout(self.gridLayout_125, 2, 0, 1, 1) self.gridLayout_231 = QtWidgets.QGridLayout() self.gridLayout_231.setObjectName("gridLayout_231") self.gridLayout_135 = QtWidgets.QGridLayout() self.gridLayout_135.setObjectName("gridLayout_135") self.min_distance_radioButton = QtWidgets.QRadioButton(self.page_18) self.min_distance_radioButton.setChecked(True) self.min_distance_radioButton.setAutoExclusive(False) self.min_distance_radioButton.setObjectName("min_distance_radioButton") self.gridLayout_135.addWidget(self.min_distance_radioButton, 2, 1, 1, 1) self.kmean_save_siglist_checkBox = QtWidgets.QCheckBox(self.page_18) self.kmean_save_siglist_checkBox.setObjectName("kmean_save_siglist_checkBox") self.gridLayout_135.addWidget(self.kmean_save_siglist_checkBox, 3, 0, 1, 4) self.label_227 = QtWidgets.QLabel(self.page_18) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_227.sizePolicy().hasHeightForWidth()) self.label_227.setSizePolicy(sizePolicy) self.label_227.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_227.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_227.setObjectName("label_227") self.gridLayout_135.addWidget(self.label_227, 2, 0, 1, 1) self.horizontalLayout_30 = QtWidgets.QHBoxLayout() self.horizontalLayout_30.setObjectName("horizontalLayout_30") self.label_104 = QtWidgets.QLabel(self.page_18) self.label_104.setStyleSheet("background-color : #656565; color : white") self.label_104.setFrameShape(QtWidgets.QFrame.Panel) self.label_104.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_104.setObjectName("label_104") self.horizontalLayout_30.addWidget(self.label_104) self.gridLayout_135.addLayout(self.horizontalLayout_30, 0, 0, 1, 4) self.gridLayout_10 = QtWidgets.QGridLayout() self.gridLayout_10.setObjectName("gridLayout_10") self.gridLayout_226 = QtWidgets.QGridLayout() self.gridLayout_226.setObjectName("gridLayout_226") self.kmean_siglist_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmean_siglist_radioButton.setChecked(False) self.kmean_siglist_radioButton.setAutoExclusive(False) self.kmean_siglist_radioButton.setObjectName("kmean_siglist_radioButton") self.gridLayout_226.addWidget(self.kmean_siglist_radioButton, 0, 1, 1, 1) self.kmean_randomsiglist_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmean_randomsiglist_radioButton.setChecked(False) self.kmean_randomsiglist_radioButton.setAutoExclusive(False) self.kmean_randomsiglist_radioButton.setObjectName("kmean_randomsiglist_radioButton") self.gridLayout_226.addWidget(self.kmean_randomsiglist_radioButton, 0, 2, 1, 1) self.kmean_minmax_radioButton = QtWidgets.QRadioButton(self.page_18) self.kmean_minmax_radioButton.setChecked(True) self.kmean_minmax_radioButton.setAutoExclusive(False) self.kmean_minmax_radioButton.setObjectName("kmean_minmax_radioButton") self.gridLayout_226.addWidget(self.kmean_minmax_radioButton, 0, 0, 1, 1) self.gridLayout_10.addLayout(self.gridLayout_226, 1, 0, 1, 1) self.gridLayout_135.addLayout(self.gridLayout_10, 1, 0, 1, 4) self.spectral_angle_map_radioButton = QtWidgets.QRadioButton(self.page_18) self.spectral_angle_map_radioButton.setChecked(False) self.spectral_angle_map_radioButton.setAutoExclusive(False) self.spectral_angle_map_radioButton.setObjectName("spectral_angle_map_radioButton") self.gridLayout_135.addWidget(self.spectral_angle_map_radioButton, 2, 2, 1, 1) self.gridLayout_231.addLayout(self.gridLayout_135, 0, 0, 1, 4) self.label_179 = QtWidgets.QLabel(self.page_18) self.label_179.setStyleSheet("background-color : #656565; color : white") self.label_179.setFrameShape(QtWidgets.QFrame.Panel) self.label_179.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_179.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_179.setObjectName("label_179") self.gridLayout_231.addWidget(self.label_179, 2, 0, 1, 4) spacerItem96 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_231.addItem(spacerItem96, 3, 0, 1, 2) self.kmeans_Button = QtWidgets.QToolButton(self.page_18) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.kmeans_Button.setFont(font) self.kmeans_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.kmeans_Button.setStyleSheet("margin: 0px;padding: 0px;") self.kmeans_Button.setIcon(icon64) self.kmeans_Button.setIconSize(QtCore.QSize(34, 34)) self.kmeans_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.kmeans_Button.setObjectName("kmeans_Button") self.gridLayout_231.addWidget(self.kmeans_Button, 3, 3, 1, 1) self.clustering = QtWidgets.QToolButton(self.page_18) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.clustering.setFont(font) self.clustering.setLayoutDirection(QtCore.Qt.RightToLeft) self.clustering.setStyleSheet("margin: 0px;padding: 0px;") self.clustering.setIcon(icon48) self.clustering.setIconSize(QtCore.QSize(34, 34)) self.clustering.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.clustering.setObjectName("clustering") self.gridLayout_231.addWidget(self.clustering, 3, 2, 1, 1) spacerItem97 = QtWidgets.QSpacerItem(38, 0, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_231.addItem(spacerItem97, 1, 3, 1, 1) self.gridLayout_152.addLayout(self.gridLayout_231, 3, 0, 1, 1) self.toolBox_kmeans.addItem(self.page_18, "") self.page_23 = QtWidgets.QWidget() self.page_23.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_23.setObjectName("page_23") self.gridLayout_235 = QtWidgets.QGridLayout(self.page_23) self.gridLayout_235.setObjectName("gridLayout_235") self.gridLayout_236 = QtWidgets.QGridLayout() self.gridLayout_236.setObjectName("gridLayout_236") self.report_textBrowser_3 = QtWidgets.QTextBrowser(self.page_23) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_3.setFont(font) self.report_textBrowser_3.setTabChangesFocus(True) self.report_textBrowser_3.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_3.setTabStopWidth(160) self.report_textBrowser_3.setOpenLinks(False) self.report_textBrowser_3.setObjectName("report_textBrowser_3") self.gridLayout_236.addWidget(self.report_textBrowser_3, 0, 0, 1, 1) self.gridLayout_235.addLayout(self.gridLayout_236, 0, 0, 1, 1) self.toolBox_kmeans.addItem(self.page_23, "") self.gridLayout_208.addWidget(self.toolBox_kmeans, 0, 0, 1, 1) self.tabWidget_4.addTab(self.tab_kmeans, "") self.tab_spectral_dist = QtWidgets.QWidget() self.tab_spectral_dist.setObjectName("tab_spectral_dist") self.gridLayout_154 = QtWidgets.QGridLayout(self.tab_spectral_dist) self.gridLayout_154.setObjectName("gridLayout_154") self.gridLayout_149 = QtWidgets.QGridLayout() self.gridLayout_149.setObjectName("gridLayout_149") self.min_distance_radioButton_2 = QtWidgets.QRadioButton(self.tab_spectral_dist) self.min_distance_radioButton_2.setChecked(True) self.min_distance_radioButton_2.setAutoExclusive(False) self.min_distance_radioButton_2.setObjectName("min_distance_radioButton_2") self.gridLayout_149.addWidget(self.min_distance_radioButton_2, 2, 1, 1, 1) self.label_231 = QtWidgets.QLabel(self.tab_spectral_dist) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_231.sizePolicy().hasHeightForWidth()) self.label_231.setSizePolicy(sizePolicy) self.label_231.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_231.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_231.setObjectName("label_231") self.gridLayout_149.addWidget(self.label_231, 2, 0, 1, 1) self.spectral_angle_map_radioButton_2 = QtWidgets.QRadioButton(self.tab_spectral_dist) self.spectral_angle_map_radioButton_2.setChecked(False) self.spectral_angle_map_radioButton_2.setAutoExclusive(False) self.spectral_angle_map_radioButton_2.setObjectName("spectral_angle_map_radioButton_2") self.gridLayout_149.addWidget(self.spectral_angle_map_radioButton_2, 2, 2, 1, 1) self.horizontalLayout_32 = QtWidgets.QHBoxLayout() self.horizontalLayout_32.setObjectName("horizontalLayout_32") self.horizontalLayout_31 = QtWidgets.QHBoxLayout() self.horizontalLayout_31.setObjectName("horizontalLayout_31") self.label_137 = QtWidgets.QLabel(self.tab_spectral_dist) self.label_137.setStyleSheet("background-color : #656565; color : white") self.label_137.setFrameShape(QtWidgets.QFrame.Panel) self.label_137.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_137.setObjectName("label_137") self.horizontalLayout_31.addWidget(self.label_137) self.horizontalLayout_32.addLayout(self.horizontalLayout_31) self.gridLayout_149.addLayout(self.horizontalLayout_32, 0, 0, 1, 4) self.distance_threshold_checkBox = QtWidgets.QCheckBox(self.tab_spectral_dist) self.distance_threshold_checkBox.setChecked(True) self.distance_threshold_checkBox.setObjectName("distance_threshold_checkBox") self.gridLayout_149.addWidget(self.distance_threshold_checkBox, 3, 0, 1, 1) self.thresh_doubleSpinBox_2 = QtWidgets.QDoubleSpinBox(self.tab_spectral_dist) self.thresh_doubleSpinBox_2.setDecimals(7) self.thresh_doubleSpinBox_2.setMinimum(1e-06) self.thresh_doubleSpinBox_2.setMaximum(1000.0) self.thresh_doubleSpinBox_2.setSingleStep(1.0) self.thresh_doubleSpinBox_2.setProperty("value", 0.1) self.thresh_doubleSpinBox_2.setObjectName("thresh_doubleSpinBox_2") self.gridLayout_149.addWidget(self.thresh_doubleSpinBox_2, 3, 1, 1, 1) self.gridLayout_41 = QtWidgets.QGridLayout() self.gridLayout_41.setObjectName("gridLayout_41") self.label_256 = QtWidgets.QLabel(self.tab_spectral_dist) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_256.sizePolicy().hasHeightForWidth()) self.label_256.setSizePolicy(sizePolicy) self.label_256.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_256.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_256.setObjectName("label_256") self.gridLayout_41.addWidget(self.label_256, 0, 0, 1, 1) self.band_set_comb_spinBox_7 = QtWidgets.QSpinBox(self.tab_spectral_dist) self.band_set_comb_spinBox_7.setMinimum(1) self.band_set_comb_spinBox_7.setMaximum(100000) self.band_set_comb_spinBox_7.setProperty("value", 2) self.band_set_comb_spinBox_7.setObjectName("band_set_comb_spinBox_7") self.gridLayout_41.addWidget(self.band_set_comb_spinBox_7, 1, 1, 1, 1) self.label_257 = QtWidgets.QLabel(self.tab_spectral_dist) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_257.sizePolicy().hasHeightForWidth()) self.label_257.setSizePolicy(sizePolicy) self.label_257.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_257.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_257.setObjectName("label_257") self.gridLayout_41.addWidget(self.label_257, 1, 0, 1, 1) self.band_set_comb_spinBox_6 = QtWidgets.QSpinBox(self.tab_spectral_dist) self.band_set_comb_spinBox_6.setMinimum(1) self.band_set_comb_spinBox_6.setMaximum(100000) self.band_set_comb_spinBox_6.setObjectName("band_set_comb_spinBox_6") self.gridLayout_41.addWidget(self.band_set_comb_spinBox_6, 0, 1, 1, 1) spacerItem98 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_41.addItem(spacerItem98, 1, 2, 1, 1) self.gridLayout_149.addLayout(self.gridLayout_41, 1, 0, 1, 4) self.gridLayout_154.addLayout(self.gridLayout_149, 0, 0, 1, 1) self.gridLayout_233 = QtWidgets.QGridLayout() self.gridLayout_233.setObjectName("gridLayout_233") self.label_183 = QtWidgets.QLabel(self.tab_spectral_dist) self.label_183.setStyleSheet("background-color : #656565; color : white") self.label_183.setFrameShape(QtWidgets.QFrame.Panel) self.label_183.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_183.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_183.setObjectName("label_183") self.gridLayout_233.addWidget(self.label_183, 1, 0, 1, 4) spacerItem99 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_233.addItem(spacerItem99, 2, 0, 1, 2) spacerItem100 = QtWidgets.QSpacerItem(38, 37, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_233.addItem(spacerItem100, 0, 3, 1, 1) self.spectral_distance_bandsets_toolButton = QtWidgets.QToolButton(self.tab_spectral_dist) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.spectral_distance_bandsets_toolButton.setFont(font) self.spectral_distance_bandsets_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.spectral_distance_bandsets_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.spectral_distance_bandsets_toolButton.setIcon(icon64) self.spectral_distance_bandsets_toolButton.setIconSize(QtCore.QSize(34, 34)) self.spectral_distance_bandsets_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.spectral_distance_bandsets_toolButton.setObjectName("spectral_distance_bandsets_toolButton") self.gridLayout_233.addWidget(self.spectral_distance_bandsets_toolButton, 2, 3, 1, 1) self.spectral_distance = QtWidgets.QToolButton(self.tab_spectral_dist) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.spectral_distance.setFont(font) self.spectral_distance.setLayoutDirection(QtCore.Qt.RightToLeft) self.spectral_distance.setStyleSheet("margin: 0px;padding: 0px;") self.spectral_distance.setIcon(icon48) self.spectral_distance.setIconSize(QtCore.QSize(34, 34)) self.spectral_distance.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.spectral_distance.setObjectName("spectral_distance") self.gridLayout_233.addWidget(self.spectral_distance, 2, 2, 1, 1) self.gridLayout_154.addLayout(self.gridLayout_233, 1, 0, 1, 1) self.tabWidget_4.addTab(self.tab_spectral_dist, "") self.tab_classification = QtWidgets.QWidget() self.tab_classification.setObjectName("tab_classification") self.gridLayout_260 = QtWidgets.QGridLayout(self.tab_classification) self.gridLayout_260.setObjectName("gridLayout_260") self.gridLayout_218 = QtWidgets.QGridLayout() self.gridLayout_218.setObjectName("gridLayout_218") self.horizontalLayout_55 = QtWidgets.QHBoxLayout() self.horizontalLayout_55.setObjectName("horizontalLayout_55") self.label_32 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_32.sizePolicy().hasHeightForWidth()) self.label_32.setSizePolicy(sizePolicy) self.label_32.setObjectName("label_32") self.horizontalLayout_55.addWidget(self.label_32) self.macroclass_checkBox = QtWidgets.QCheckBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.macroclass_checkBox.sizePolicy().hasHeightForWidth()) self.macroclass_checkBox.setSizePolicy(sizePolicy) self.macroclass_checkBox.setObjectName("macroclass_checkBox") self.horizontalLayout_55.addWidget(self.macroclass_checkBox) self.class_checkBox = QtWidgets.QCheckBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_checkBox.sizePolicy().hasHeightForWidth()) self.class_checkBox.setSizePolicy(sizePolicy) self.class_checkBox.setObjectName("class_checkBox") self.horizontalLayout_55.addWidget(self.class_checkBox) spacerItem101 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_55.addItem(spacerItem101) self.algorithm_weight_button = QtWidgets.QToolButton(self.tab_classification) self.algorithm_weight_button.setStyleSheet("margin: 0px;padding: 0px;") self.algorithm_weight_button.setIcon(icon3) self.algorithm_weight_button.setIconSize(QtCore.QSize(22, 22)) self.algorithm_weight_button.setObjectName("algorithm_weight_button") self.horizontalLayout_55.addWidget(self.algorithm_weight_button) self.gridLayout_218.addLayout(self.horizontalLayout_55, 2, 0, 1, 4) self.algorithm_combo = QtWidgets.QComboBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.algorithm_combo.sizePolicy().hasHeightForWidth()) self.algorithm_combo.setSizePolicy(sizePolicy) self.algorithm_combo.setMinimumSize(QtCore.QSize(100, 0)) self.algorithm_combo.setObjectName("algorithm_combo") self.algorithm_combo.addItem("") self.algorithm_combo.addItem("") self.algorithm_combo.addItem("") self.gridLayout_218.addWidget(self.algorithm_combo, 4, 0, 1, 3) self.band_set_comb_spinBox_12 = QtWidgets.QSpinBox(self.tab_classification) self.band_set_comb_spinBox_12.setMinimum(1) self.band_set_comb_spinBox_12.setMaximum(100000) self.band_set_comb_spinBox_12.setObjectName("band_set_comb_spinBox_12") self.gridLayout_218.addWidget(self.band_set_comb_spinBox_12, 1, 1, 1, 1) self.label_261 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_261.sizePolicy().hasHeightForWidth()) self.label_261.setSizePolicy(sizePolicy) self.label_261.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_261.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_261.setObjectName("label_261") self.gridLayout_218.addWidget(self.label_261, 1, 0, 1, 1) self.label_240 = QtWidgets.QLabel(self.tab_classification) self.label_240.setStyleSheet("background-color : #656565; color : white") self.label_240.setFrameShape(QtWidgets.QFrame.Panel) self.label_240.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_240.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_240.setObjectName("label_240") self.gridLayout_218.addWidget(self.label_240, 3, 0, 1, 4) self.gridLayout_255 = QtWidgets.QGridLayout() self.gridLayout_255.setObjectName("gridLayout_255") self.alg_threshold_SpinBox = QtWidgets.QDoubleSpinBox(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.alg_threshold_SpinBox.sizePolicy().hasHeightForWidth()) self.alg_threshold_SpinBox.setSizePolicy(sizePolicy) self.alg_threshold_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.alg_threshold_SpinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.alg_threshold_SpinBox.setDecimals(4) self.alg_threshold_SpinBox.setMaximum(10000.0) self.alg_threshold_SpinBox.setObjectName("alg_threshold_SpinBox") self.gridLayout_255.addWidget(self.alg_threshold_SpinBox, 0, 1, 1, 1) self.algorithm_threshold_button = QtWidgets.QToolButton(self.tab_classification) self.algorithm_threshold_button.setStyleSheet("margin: 0px;padding: 0px;") self.algorithm_threshold_button.setIcon(icon9) self.algorithm_threshold_button.setIconSize(QtCore.QSize(22, 22)) self.algorithm_threshold_button.setObjectName("algorithm_threshold_button") self.gridLayout_255.addWidget(self.algorithm_threshold_button, 0, 3, 1, 1) self.label_234 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_234.sizePolicy().hasHeightForWidth()) self.label_234.setSizePolicy(sizePolicy) self.label_234.setMaximumSize(QtCore.QSize(100, 16777215)) self.label_234.setObjectName("label_234") self.gridLayout_255.addWidget(self.label_234, 0, 0, 1, 1) spacerItem102 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_255.addItem(spacerItem102, 0, 2, 1, 1) self.gridLayout_218.addLayout(self.gridLayout_255, 4, 3, 1, 1) self.label_243 = QtWidgets.QLabel(self.tab_classification) self.label_243.setStyleSheet("background-color : #656565; color : white") self.label_243.setFrameShape(QtWidgets.QFrame.Panel) self.label_243.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_243.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_243.setObjectName("label_243") self.gridLayout_218.addWidget(self.label_243, 0, 0, 1, 4) spacerItem103 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_218.addItem(spacerItem103, 1, 3, 1, 1) self.gridLayout_260.addLayout(self.gridLayout_218, 0, 0, 1, 1) self.verticalLayout_4 = QtWidgets.QVBoxLayout() self.verticalLayout_4.setObjectName("verticalLayout_4") self.gridLayout_225 = QtWidgets.QGridLayout() self.gridLayout_225.setObjectName("gridLayout_225") self.LC_signature_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.LC_signature_checkBox.setObjectName("LC_signature_checkBox") self.gridLayout_225.addWidget(self.LC_signature_checkBox, 1, 1, 1, 1) self.label_235 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_235.sizePolicy().hasHeightForWidth()) self.label_235.setSizePolicy(sizePolicy) self.label_235.setObjectName("label_235") self.gridLayout_225.addWidget(self.label_235, 1, 0, 1, 1) self.LC_signature_button = QtWidgets.QToolButton(self.tab_classification) self.LC_signature_button.setStyleSheet("margin: 0px;padding: 0px;") self.LC_signature_button.setText("") self.LC_signature_button.setIcon(icon6) self.LC_signature_button.setIconSize(QtCore.QSize(22, 22)) self.LC_signature_button.setObjectName("LC_signature_button") self.gridLayout_225.addWidget(self.LC_signature_button, 1, 5, 1, 1) self.LCS_leave_unclassified_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.LCS_leave_unclassified_checkBox.setObjectName("LCS_leave_unclassified_checkBox") self.gridLayout_225.addWidget(self.LCS_leave_unclassified_checkBox, 1, 3, 1, 1) self.label_241 = QtWidgets.QLabel(self.tab_classification) self.label_241.setStyleSheet("background-color : #656565; color : white") self.label_241.setFrameShape(QtWidgets.QFrame.Panel) self.label_241.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_241.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_241.setObjectName("label_241") self.gridLayout_225.addWidget(self.label_241, 0, 0, 1, 6) self.LCS_class_algorithm_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.LCS_class_algorithm_checkBox.setObjectName("LCS_class_algorithm_checkBox") self.gridLayout_225.addWidget(self.LCS_class_algorithm_checkBox, 1, 2, 1, 1) self.verticalLayout_4.addLayout(self.gridLayout_225) self.label_242 = QtWidgets.QLabel(self.tab_classification) self.label_242.setStyleSheet("background-color : #656565; color : white") self.label_242.setFrameShape(QtWidgets.QFrame.Panel) self.label_242.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_242.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_242.setObjectName("label_242") self.verticalLayout_4.addWidget(self.label_242) self.gridLayout_239 = QtWidgets.QGridLayout() self.gridLayout_239.setSpacing(4) self.gridLayout_239.setObjectName("gridLayout_239") self.resetQmlButton = QtWidgets.QToolButton(self.tab_classification) self.resetQmlButton.setStyleSheet("margin: 0px;padding: 0px;") self.resetQmlButton.setIcon(icon59) self.resetQmlButton.setIconSize(QtCore.QSize(22, 22)) self.resetQmlButton.setObjectName("resetQmlButton") self.gridLayout_239.addWidget(self.resetQmlButton, 0, 3, 1, 1) self.label_238 = QtWidgets.QLabel(self.tab_classification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_238.sizePolicy().hasHeightForWidth()) self.label_238.setSizePolicy(sizePolicy) self.label_238.setObjectName("label_238") self.gridLayout_239.addWidget(self.label_238, 0, 0, 1, 1) self.qml_Button = QtWidgets.QToolButton(self.tab_classification) self.qml_Button.setStyleSheet("margin: 0px;padding: 0px;") self.qml_Button.setIcon(icon65) self.qml_Button.setIconSize(QtCore.QSize(22, 22)) self.qml_Button.setObjectName("qml_Button") self.gridLayout_239.addWidget(self.qml_Button, 0, 2, 1, 1) self.qml_lineEdit = QtWidgets.QLineEdit(self.tab_classification) self.qml_lineEdit.setEnabled(False) self.qml_lineEdit.setObjectName("qml_lineEdit") self.gridLayout_239.addWidget(self.qml_lineEdit, 0, 1, 1, 1) self.verticalLayout_4.addLayout(self.gridLayout_239) self.gridLayout_241 = QtWidgets.QGridLayout() self.gridLayout_241.setObjectName("gridLayout_241") self.mask_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.mask_checkBox.setObjectName("mask_checkBox") self.gridLayout_241.addWidget(self.mask_checkBox, 0, 0, 1, 1) self.resetMaskButton = QtWidgets.QToolButton(self.tab_classification) self.resetMaskButton.setStyleSheet("margin: 0px;padding: 0px;") self.resetMaskButton.setIcon(icon59) self.resetMaskButton.setIconSize(QtCore.QSize(22, 22)) self.resetMaskButton.setObjectName("resetMaskButton") self.gridLayout_241.addWidget(self.resetMaskButton, 0, 3, 1, 1) self.mask_lineEdit = QtWidgets.QLineEdit(self.tab_classification) self.mask_lineEdit.setEnabled(False) self.mask_lineEdit.setInputMethodHints(QtCore.Qt.ImhUrlCharactersOnly) self.mask_lineEdit.setText("") self.mask_lineEdit.setObjectName("mask_lineEdit") self.gridLayout_241.addWidget(self.mask_lineEdit, 0, 1, 1, 2) self.verticalLayout_4.addLayout(self.gridLayout_241) self.horizontalLayout_56 = QtWidgets.QHBoxLayout() self.horizontalLayout_56.setObjectName("horizontalLayout_56") self.vector_output_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.vector_output_checkBox.setObjectName("vector_output_checkBox") self.horizontalLayout_56.addWidget(self.vector_output_checkBox) self.report_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.report_checkBox.setObjectName("report_checkBox") self.horizontalLayout_56.addWidget(self.report_checkBox) self.alg_files_checkBox = QtWidgets.QCheckBox(self.tab_classification) self.alg_files_checkBox.setObjectName("alg_files_checkBox") self.horizontalLayout_56.addWidget(self.alg_files_checkBox) self.verticalLayout_4.addLayout(self.horizontalLayout_56) self.gridLayout_249 = QtWidgets.QGridLayout() self.gridLayout_249.setObjectName("gridLayout_249") self.button_classification = QtWidgets.QToolButton(self.tab_classification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.button_classification.setFont(font) self.button_classification.setLayoutDirection(QtCore.Qt.RightToLeft) self.button_classification.setStyleSheet("margin: 0px;padding: 0px;") self.button_classification.setIcon(icon64) self.button_classification.setIconSize(QtCore.QSize(34, 34)) self.button_classification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.button_classification.setObjectName("button_classification") self.gridLayout_249.addWidget(self.button_classification, 2, 2, 1, 1) self.label_239 = QtWidgets.QLabel(self.tab_classification) self.label_239.setStyleSheet("background-color : #656565; color : white") self.label_239.setFrameShape(QtWidgets.QFrame.Panel) self.label_239.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_239.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_239.setObjectName("label_239") self.gridLayout_249.addWidget(self.label_239, 1, 0, 1, 3) spacerItem104 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_249.addItem(spacerItem104, 0, 2, 1, 1) spacerItem105 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_249.addItem(spacerItem105, 2, 0, 1, 1) self.classification = QtWidgets.QToolButton(self.tab_classification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification.setFont(font) self.classification.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification.setStyleSheet("margin: 0px;padding: 0px;") self.classification.setIcon(icon48) self.classification.setIconSize(QtCore.QSize(34, 34)) self.classification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification.setObjectName("classification") self.gridLayout_249.addWidget(self.classification, 2, 1, 1, 1) self.verticalLayout_4.addLayout(self.gridLayout_249) self.gridLayout_260.addLayout(self.verticalLayout_4, 1, 0, 1, 1) self.tabWidget_4.addTab(self.tab_classification, "") self.tab_random_forest = QtWidgets.QWidget() self.tab_random_forest.setObjectName("tab_random_forest") self.gridLayout_288 = QtWidgets.QGridLayout(self.tab_random_forest) self.gridLayout_288.setObjectName("gridLayout_288") self.toolBox_random_forest = QtWidgets.QToolBox(self.tab_random_forest) self.toolBox_random_forest.setStyleSheet("") self.toolBox_random_forest.setObjectName("toolBox_random_forest") self.page_21 = QtWidgets.QWidget() self.page_21.setGeometry(QtCore.QRect(0, 0, 634, 327)) self.page_21.setObjectName("page_21") self.gridLayout_287 = QtWidgets.QGridLayout(self.page_21) self.gridLayout_287.setObjectName("gridLayout_287") self.gridLayout_280 = QtWidgets.QGridLayout() self.gridLayout_280.setObjectName("gridLayout_280") self.horizontalLayout_58 = QtWidgets.QHBoxLayout() self.horizontalLayout_58.setObjectName("horizontalLayout_58") self.label_233 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_233.sizePolicy().hasHeightForWidth()) self.label_233.setSizePolicy(sizePolicy) self.label_233.setObjectName("label_233") self.horizontalLayout_58.addWidget(self.label_233) self.macroclass_checkBox_rf = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.macroclass_checkBox_rf.sizePolicy().hasHeightForWidth()) self.macroclass_checkBox_rf.setSizePolicy(sizePolicy) self.macroclass_checkBox_rf.setChecked(True) self.macroclass_checkBox_rf.setObjectName("macroclass_checkBox_rf") self.horizontalLayout_58.addWidget(self.macroclass_checkBox_rf) self.class_checkBox_rf = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_checkBox_rf.sizePolicy().hasHeightForWidth()) self.class_checkBox_rf.setSizePolicy(sizePolicy) self.class_checkBox_rf.setObjectName("class_checkBox_rf") self.horizontalLayout_58.addWidget(self.class_checkBox_rf) spacerItem106 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_58.addItem(spacerItem106) self.gridLayout_280.addLayout(self.horizontalLayout_58, 2, 0, 1, 3) self.band_set_comb_spinBox_13 = QtWidgets.QSpinBox(self.page_21) self.band_set_comb_spinBox_13.setMinimum(1) self.band_set_comb_spinBox_13.setMaximum(100000) self.band_set_comb_spinBox_13.setObjectName("band_set_comb_spinBox_13") self.gridLayout_280.addWidget(self.band_set_comb_spinBox_13, 1, 1, 1, 1) self.label_262 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_262.sizePolicy().hasHeightForWidth()) self.label_262.setSizePolicy(sizePolicy) self.label_262.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_262.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_262.setObjectName("label_262") self.gridLayout_280.addWidget(self.label_262, 1, 0, 1, 1) self.label_245 = QtWidgets.QLabel(self.page_21) self.label_245.setStyleSheet("background-color : #656565; color : white") self.label_245.setFrameShape(QtWidgets.QFrame.Panel) self.label_245.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_245.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_245.setObjectName("label_245") self.gridLayout_280.addWidget(self.label_245, 0, 0, 1, 3) self.gridLayout_284 = QtWidgets.QGridLayout() self.gridLayout_284.setObjectName("gridLayout_284") self.number_trees_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.number_trees_SpinBox.sizePolicy().hasHeightForWidth()) self.number_trees_SpinBox.setSizePolicy(sizePolicy) self.number_trees_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.number_trees_SpinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.number_trees_SpinBox.setDecimals(0) self.number_trees_SpinBox.setMinimum(1.0) self.number_trees_SpinBox.setMaximum(1000000.0) self.number_trees_SpinBox.setSingleStep(1.0) self.number_trees_SpinBox.setProperty("value", 10.0) self.number_trees_SpinBox.setObjectName("number_trees_SpinBox") self.gridLayout_284.addWidget(self.number_trees_SpinBox, 0, 1, 1, 1) self.label_237 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_237.sizePolicy().hasHeightForWidth()) self.label_237.setSizePolicy(sizePolicy) self.label_237.setMaximumSize(QtCore.QSize(150, 16777215)) self.label_237.setObjectName("label_237") self.gridLayout_284.addWidget(self.label_237, 0, 0, 1, 1) spacerItem107 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_284.addItem(spacerItem107, 0, 2, 1, 1) self.gridLayout_280.addLayout(self.gridLayout_284, 4, 0, 1, 3) self.gridLayout_282 = QtWidgets.QGridLayout() self.gridLayout_282.setObjectName("gridLayout_282") self.number_training_samples_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.number_training_samples_SpinBox.sizePolicy().hasHeightForWidth()) self.number_training_samples_SpinBox.setSizePolicy(sizePolicy) self.number_training_samples_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.number_training_samples_SpinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.number_training_samples_SpinBox.setDecimals(0) self.number_training_samples_SpinBox.setMinimum(1.0) self.number_training_samples_SpinBox.setMaximum(1000000.0) self.number_training_samples_SpinBox.setSingleStep(100.0) self.number_training_samples_SpinBox.setProperty("value", 5000.0) self.number_training_samples_SpinBox.setObjectName("number_training_samples_SpinBox") self.gridLayout_282.addWidget(self.number_training_samples_SpinBox, 0, 1, 1, 1) self.label_236 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_236.sizePolicy().hasHeightForWidth()) self.label_236.setSizePolicy(sizePolicy) self.label_236.setMaximumSize(QtCore.QSize(208, 16777215)) self.label_236.setObjectName("label_236") self.gridLayout_282.addWidget(self.label_236, 0, 0, 1, 1) spacerItem108 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_282.addItem(spacerItem108, 0, 2, 1, 1) self.gridLayout_280.addLayout(self.gridLayout_282, 3, 0, 1, 3) spacerItem109 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_280.addItem(spacerItem109, 1, 2, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_280, 0, 0, 1, 1) self.gridLayout_285 = QtWidgets.QGridLayout() self.gridLayout_285.setObjectName("gridLayout_285") self.evaluate_classifier_checkBox = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.evaluate_classifier_checkBox.sizePolicy().hasHeightForWidth()) self.evaluate_classifier_checkBox.setSizePolicy(sizePolicy) self.evaluate_classifier_checkBox.setObjectName("evaluate_classifier_checkBox") self.gridLayout_285.addWidget(self.evaluate_classifier_checkBox, 0, 0, 1, 1) self.evaluate_feature_power_set_checkBox = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.evaluate_feature_power_set_checkBox.sizePolicy().hasHeightForWidth()) self.evaluate_feature_power_set_checkBox.setSizePolicy(sizePolicy) self.evaluate_feature_power_set_checkBox.setObjectName("evaluate_feature_power_set_checkBox") self.gridLayout_285.addWidget(self.evaluate_feature_power_set_checkBox, 0, 1, 1, 1) spacerItem110 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_285.addItem(spacerItem110, 0, 6, 1, 1) self.label_248 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_248.sizePolicy().hasHeightForWidth()) self.label_248.setSizePolicy(sizePolicy) self.label_248.setMaximumSize(QtCore.QSize(100, 16777215)) self.label_248.setObjectName("label_248") self.gridLayout_285.addWidget(self.label_248, 0, 4, 1, 1) self.rf_power_min_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.rf_power_min_SpinBox.sizePolicy().hasHeightForWidth()) self.rf_power_min_SpinBox.setSizePolicy(sizePolicy) self.rf_power_min_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.rf_power_min_SpinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.rf_power_min_SpinBox.setDecimals(0) self.rf_power_min_SpinBox.setMinimum(1.0) self.rf_power_min_SpinBox.setMaximum(1000000.0) self.rf_power_min_SpinBox.setSingleStep(1.0) self.rf_power_min_SpinBox.setProperty("value", 2.0) self.rf_power_min_SpinBox.setObjectName("rf_power_min_SpinBox") self.gridLayout_285.addWidget(self.rf_power_min_SpinBox, 0, 3, 1, 1) self.label_247 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Minimum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_247.sizePolicy().hasHeightForWidth()) self.label_247.setSizePolicy(sizePolicy) self.label_247.setMaximumSize(QtCore.QSize(100, 16777215)) self.label_247.setObjectName("label_247") self.gridLayout_285.addWidget(self.label_247, 0, 2, 1, 1) self.rf_power_max_SpinBox = QtWidgets.QDoubleSpinBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.rf_power_max_SpinBox.sizePolicy().hasHeightForWidth()) self.rf_power_max_SpinBox.setSizePolicy(sizePolicy) self.rf_power_max_SpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.rf_power_max_SpinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.rf_power_max_SpinBox.setDecimals(0) self.rf_power_max_SpinBox.setMinimum(1.0) self.rf_power_max_SpinBox.setMaximum(1000000.0) self.rf_power_max_SpinBox.setSingleStep(1.0) self.rf_power_max_SpinBox.setProperty("value", 7.0) self.rf_power_max_SpinBox.setObjectName("rf_power_max_SpinBox") self.gridLayout_285.addWidget(self.rf_power_max_SpinBox, 0, 5, 1, 1) self.save_classifier_checkBox = QtWidgets.QCheckBox(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.save_classifier_checkBox.sizePolicy().hasHeightForWidth()) self.save_classifier_checkBox.setSizePolicy(sizePolicy) self.save_classifier_checkBox.setObjectName("save_classifier_checkBox") self.gridLayout_285.addWidget(self.save_classifier_checkBox, 1, 0, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_285, 1, 0, 1, 1) self.gridLayout_286 = QtWidgets.QGridLayout() self.gridLayout_286.setObjectName("gridLayout_286") self.label_244 = QtWidgets.QLabel(self.page_21) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_244.sizePolicy().hasHeightForWidth()) self.label_244.setSizePolicy(sizePolicy) self.label_244.setObjectName("label_244") self.gridLayout_286.addWidget(self.label_244, 0, 0, 1, 1) self.classifier_Button = QtWidgets.QToolButton(self.page_21) self.classifier_Button.setStyleSheet("margin: 0px;padding: 0px;") self.classifier_Button.setIcon(icon65) self.classifier_Button.setIconSize(QtCore.QSize(22, 22)) self.classifier_Button.setObjectName("classifier_Button") self.gridLayout_286.addWidget(self.classifier_Button, 0, 2, 1, 1) self.classifier_lineEdit_ = QtWidgets.QLineEdit(self.page_21) self.classifier_lineEdit_.setEnabled(False) self.classifier_lineEdit_.setObjectName("classifier_lineEdit_") self.gridLayout_286.addWidget(self.classifier_lineEdit_, 0, 1, 1, 1) self.resetClassifierButton = QtWidgets.QToolButton(self.page_21) self.resetClassifierButton.setStyleSheet("margin: 0px;padding: 0px;") self.resetClassifierButton.setIcon(icon59) self.resetClassifierButton.setIconSize(QtCore.QSize(22, 22)) self.resetClassifierButton.setObjectName("resetClassifierButton") self.gridLayout_286.addWidget(self.resetClassifierButton, 0, 3, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_286, 2, 0, 1, 1) self.gridLayout_283 = QtWidgets.QGridLayout() self.gridLayout_283.setObjectName("gridLayout_283") self.button_random_forest = QtWidgets.QToolButton(self.page_21) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.button_random_forest.setFont(font) self.button_random_forest.setLayoutDirection(QtCore.Qt.RightToLeft) self.button_random_forest.setStyleSheet("margin: 0px;padding: 0px;") self.button_random_forest.setIcon(icon64) self.button_random_forest.setIconSize(QtCore.QSize(34, 34)) self.button_random_forest.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.button_random_forest.setObjectName("button_random_forest") self.gridLayout_283.addWidget(self.button_random_forest, 2, 2, 1, 1) self.label_246 = QtWidgets.QLabel(self.page_21) self.label_246.setStyleSheet("background-color : #656565; color : white") self.label_246.setFrameShape(QtWidgets.QFrame.Panel) self.label_246.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_246.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_246.setObjectName("label_246") self.gridLayout_283.addWidget(self.label_246, 1, 0, 1, 3) spacerItem111 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_283.addItem(spacerItem111, 0, 2, 1, 1) spacerItem112 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_283.addItem(spacerItem112, 2, 0, 1, 1) self.random_forest = QtWidgets.QToolButton(self.page_21) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.random_forest.setFont(font) self.random_forest.setLayoutDirection(QtCore.Qt.RightToLeft) self.random_forest.setStyleSheet("margin: 0px;padding: 0px;") self.random_forest.setIcon(icon48) self.random_forest.setIconSize(QtCore.QSize(34, 34)) self.random_forest.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.random_forest.setObjectName("random_forest") self.gridLayout_283.addWidget(self.random_forest, 2, 1, 1, 1) self.gridLayout_287.addLayout(self.gridLayout_283, 3, 0, 1, 1) self.toolBox_random_forest.addItem(self.page_21, "") self.page_25 = QtWidgets.QWidget() self.page_25.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_25.setObjectName("page_25") self.gridLayout_293 = QtWidgets.QGridLayout(self.page_25) self.gridLayout_293.setObjectName("gridLayout_293") self.gridLayout_294 = QtWidgets.QGridLayout() self.gridLayout_294.setObjectName("gridLayout_294") self.report_textBrowser_5 = QtWidgets.QTextBrowser(self.page_25) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_5.setFont(font) self.report_textBrowser_5.setTabChangesFocus(True) self.report_textBrowser_5.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_5.setTabStopWidth(160) self.report_textBrowser_5.setOpenLinks(False) self.report_textBrowser_5.setObjectName("report_textBrowser_5") self.gridLayout_294.addWidget(self.report_textBrowser_5, 0, 0, 1, 1) self.gridLayout_293.addLayout(self.gridLayout_294, 0, 0, 1, 1) self.toolBox_random_forest.addItem(self.page_25, "") self.gridLayout_288.addWidget(self.toolBox_random_forest, 0, 0, 1, 1) self.tabWidget_4.addTab(self.tab_random_forest, "") self.gridLayout_163.addWidget(self.tabWidget_4, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_band_processing, "") self.tab_postProcessing = QtWidgets.QWidget() self.tab_postProcessing.setObjectName("tab_postProcessing") self.gridLayout_552 = QtWidgets.QGridLayout(self.tab_postProcessing) self.gridLayout_552.setObjectName("gridLayout_552") self.tabWidget_2 = QtWidgets.QTabWidget(self.tab_postProcessing) self.tabWidget_2.setStyleSheet("") self.tabWidget_2.setIconSize(QtCore.QSize(20, 20)) self.tabWidget_2.setDocumentMode(True) self.tabWidget_2.setObjectName("tabWidget_2") self.tab_accuracy = QtWidgets.QWidget() self.tab_accuracy.setObjectName("tab_accuracy") self.gridLayout_184 = QtWidgets.QGridLayout(self.tab_accuracy) self.gridLayout_184.setObjectName("gridLayout_184") self.toolBox_accuracy = QtWidgets.QToolBox(self.tab_accuracy) self.toolBox_accuracy.setObjectName("toolBox_accuracy") self.page_10 = QtWidgets.QWidget() self.page_10.setGeometry(QtCore.QRect(0, 0, 723, 351)) self.page_10.setObjectName("page_10") self.gridLayout_36 = QtWidgets.QGridLayout(self.page_10) self.gridLayout_36.setObjectName("gridLayout_36") self.gridLayout_33 = QtWidgets.QGridLayout() self.gridLayout_33.setObjectName("gridLayout_33") self.label_33 = QtWidgets.QLabel(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_33.sizePolicy().hasHeightForWidth()) self.label_33.setSizePolicy(sizePolicy) self.label_33.setMinimumSize(QtCore.QSize(229, 0)) self.label_33.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_33.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_33.setObjectName("label_33") self.gridLayout_33.addWidget(self.label_33, 1, 0, 1, 1) self.label_34 = QtWidgets.QLabel(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_34.sizePolicy().hasHeightForWidth()) self.label_34.setSizePolicy(sizePolicy) self.label_34.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_34.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_34.setObjectName("label_34") self.gridLayout_33.addWidget(self.label_34, 2, 0, 1, 1) self.classification_name_combo = QtWidgets.QComboBox(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo.sizePolicy().hasHeightForWidth()) self.classification_name_combo.setSizePolicy(sizePolicy) self.classification_name_combo.setObjectName("classification_name_combo") self.gridLayout_33.addWidget(self.classification_name_combo, 1, 1, 1, 3) self.buttonReload_shape_4 = QtWidgets.QToolButton(self.page_10) self.buttonReload_shape_4.setStyleSheet("margin: 0px;padding: 0px;") self.buttonReload_shape_4.setIcon(icon55) self.buttonReload_shape_4.setIconSize(QtCore.QSize(22, 22)) self.buttonReload_shape_4.setObjectName("buttonReload_shape_4") self.gridLayout_33.addWidget(self.buttonReload_shape_4, 2, 4, 1, 1) self.toolButton_reload_4 = QtWidgets.QToolButton(self.page_10) self.toolButton_reload_4.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_4.setIcon(icon55) self.toolButton_reload_4.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_4.setObjectName("toolButton_reload_4") self.gridLayout_33.addWidget(self.toolButton_reload_4, 1, 4, 1, 1) self.reference_name_combo = QtWidgets.QComboBox(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_name_combo.sizePolicy().hasHeightForWidth()) self.reference_name_combo.setSizePolicy(sizePolicy) self.reference_name_combo.setObjectName("reference_name_combo") self.gridLayout_33.addWidget(self.reference_name_combo, 2, 1, 1, 3) self.horizontalLayout_36 = QtWidgets.QHBoxLayout() self.horizontalLayout_36.setObjectName("horizontalLayout_36") self.label_145 = QtWidgets.QLabel(self.page_10) self.label_145.setStyleSheet("background-color : #656565; color : white") self.label_145.setFrameShape(QtWidgets.QFrame.Panel) self.label_145.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_145.setObjectName("label_145") self.horizontalLayout_36.addWidget(self.label_145) self.gridLayout_33.addLayout(self.horizontalLayout_36, 0, 0, 1, 5) self.label_82 = QtWidgets.QLabel(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_82.sizePolicy().hasHeightForWidth()) self.label_82.setSizePolicy(sizePolicy) self.label_82.setMinimumSize(QtCore.QSize(6, 0)) self.label_82.setMaximumSize(QtCore.QSize(100, 200)) self.label_82.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_82.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_82.setObjectName("label_82") self.gridLayout_33.addWidget(self.label_82, 3, 1, 1, 1) self.class_field_comboBox = QtWidgets.QComboBox(self.page_10) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox.sizePolicy().hasHeightForWidth()) self.class_field_comboBox.setSizePolicy(sizePolicy) self.class_field_comboBox.setObjectName("class_field_comboBox") self.gridLayout_33.addWidget(self.class_field_comboBox, 3, 2, 1, 2) self.horizontalLayout_67 = QtWidgets.QHBoxLayout() self.horizontalLayout_67.setObjectName("horizontalLayout_67") self.nodata_checkBox_11 = QtWidgets.QCheckBox(self.page_10) self.nodata_checkBox_11.setObjectName("nodata_checkBox_11") self.horizontalLayout_67.addWidget(self.nodata_checkBox_11) self.nodata_spinBox_15 = QtWidgets.QSpinBox(self.page_10) self.nodata_spinBox_15.setMinimum(-2147483647) self.nodata_spinBox_15.setMaximum(2147483647) self.nodata_spinBox_15.setProperty("value", 0) self.nodata_spinBox_15.setObjectName("nodata_spinBox_15") self.horizontalLayout_67.addWidget(self.nodata_spinBox_15) spacerItem113 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_67.addItem(spacerItem113) self.gridLayout_33.addLayout(self.horizontalLayout_67, 4, 0, 1, 5) self.gridLayout_36.addLayout(self.gridLayout_33, 0, 0, 1, 1) self.gridLayout_25 = QtWidgets.QGridLayout() self.gridLayout_25.setObjectName("gridLayout_25") spacerItem114 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_25.addItem(spacerItem114, 0, 2, 1, 1) spacerItem115 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_25.addItem(spacerItem115, 2, 0, 1, 1) self.label_168 = QtWidgets.QLabel(self.page_10) self.label_168.setStyleSheet("background-color : #656565; color : white") self.label_168.setFrameShape(QtWidgets.QFrame.Panel) self.label_168.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_168.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_168.setObjectName("label_168") self.gridLayout_25.addWidget(self.label_168, 1, 0, 1, 3) self.calculateMatrix_toolButton = QtWidgets.QToolButton(self.page_10) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateMatrix_toolButton.setFont(font) self.calculateMatrix_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateMatrix_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateMatrix_toolButton.setIcon(icon64) self.calculateMatrix_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateMatrix_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateMatrix_toolButton.setObjectName("calculateMatrix_toolButton") self.gridLayout_25.addWidget(self.calculateMatrix_toolButton, 2, 2, 1, 1) self.accuracy = QtWidgets.QToolButton(self.page_10) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.accuracy.setFont(font) self.accuracy.setLayoutDirection(QtCore.Qt.RightToLeft) self.accuracy.setStyleSheet("margin: 0px;padding: 0px;") self.accuracy.setIcon(icon48) self.accuracy.setIconSize(QtCore.QSize(34, 34)) self.accuracy.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.accuracy.setObjectName("accuracy") self.gridLayout_25.addWidget(self.accuracy, 2, 1, 1, 1) self.gridLayout_36.addLayout(self.gridLayout_25, 1, 0, 1, 1) self.toolBox_accuracy.addItem(self.page_10, "") self.page_11 = QtWidgets.QWidget() self.page_11.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_11.setObjectName("page_11") self.gridLayout_35 = QtWidgets.QGridLayout(self.page_11) self.gridLayout_35.setObjectName("gridLayout_35") self.gridLayout_34 = QtWidgets.QGridLayout() self.gridLayout_34.setObjectName("gridLayout_34") self.error_matrix_textBrowser = QtWidgets.QTextBrowser(self.page_11) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.error_matrix_textBrowser.setFont(font) self.error_matrix_textBrowser.setTabChangesFocus(True) self.error_matrix_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.error_matrix_textBrowser.setTabStopWidth(120) self.error_matrix_textBrowser.setOpenLinks(False) self.error_matrix_textBrowser.setObjectName("error_matrix_textBrowser") self.gridLayout_34.addWidget(self.error_matrix_textBrowser, 0, 0, 1, 1) self.gridLayout_35.addLayout(self.gridLayout_34, 0, 0, 1, 1) self.toolBox_accuracy.addItem(self.page_11, "") self.gridLayout_184.addWidget(self.toolBox_accuracy, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_accuracy, "") self.tab_landCoverChange = QtWidgets.QWidget() self.tab_landCoverChange.setObjectName("tab_landCoverChange") self.gridLayout_187 = QtWidgets.QGridLayout(self.tab_landCoverChange) self.gridLayout_187.setObjectName("gridLayout_187") self.toolBox_landCoverChange = QtWidgets.QToolBox(self.tab_landCoverChange) self.toolBox_landCoverChange.setObjectName("toolBox_landCoverChange") self.page_12 = QtWidgets.QWidget() self.page_12.setGeometry(QtCore.QRect(0, 0, 385, 193)) self.page_12.setObjectName("page_12") self.gridLayout_186 = QtWidgets.QGridLayout(self.page_12) self.gridLayout_186.setObjectName("gridLayout_186") self.gridLayout_44 = QtWidgets.QGridLayout() self.gridLayout_44.setObjectName("gridLayout_44") self.mask_unchanged_checkBox = QtWidgets.QCheckBox(self.page_12) self.mask_unchanged_checkBox.setChecked(True) self.mask_unchanged_checkBox.setObjectName("mask_unchanged_checkBox") self.gridLayout_44.addWidget(self.mask_unchanged_checkBox, 3, 0, 1, 1) self.classification_reference_name_combo = QtWidgets.QComboBox(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_reference_name_combo.sizePolicy().hasHeightForWidth()) self.classification_reference_name_combo.setSizePolicy(sizePolicy) self.classification_reference_name_combo.setObjectName("classification_reference_name_combo") self.gridLayout_44.addWidget(self.classification_reference_name_combo, 1, 1, 1, 1) self.label_40 = QtWidgets.QLabel(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_40.sizePolicy().hasHeightForWidth()) self.label_40.setSizePolicy(sizePolicy) self.label_40.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_40.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_40.setObjectName("label_40") self.gridLayout_44.addWidget(self.label_40, 2, 0, 1, 1) self.label_38 = QtWidgets.QLabel(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_38.sizePolicy().hasHeightForWidth()) self.label_38.setSizePolicy(sizePolicy) self.label_38.setMinimumSize(QtCore.QSize(229, 0)) self.label_38.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_38.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_38.setObjectName("label_38") self.gridLayout_44.addWidget(self.label_38, 1, 0, 1, 1) self.new_classification_name_combo = QtWidgets.QComboBox(self.page_12) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.new_classification_name_combo.sizePolicy().hasHeightForWidth()) self.new_classification_name_combo.setSizePolicy(sizePolicy) self.new_classification_name_combo.setObjectName("new_classification_name_combo") self.gridLayout_44.addWidget(self.new_classification_name_combo, 2, 1, 1, 1) self.toolButton_reload_5 = QtWidgets.QToolButton(self.page_12) self.toolButton_reload_5.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_5.setIcon(icon55) self.toolButton_reload_5.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_5.setObjectName("toolButton_reload_5") self.gridLayout_44.addWidget(self.toolButton_reload_5, 1, 2, 1, 1) self.toolButton_reload_6 = QtWidgets.QToolButton(self.page_12) self.toolButton_reload_6.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_6.setIcon(icon55) self.toolButton_reload_6.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_6.setObjectName("toolButton_reload_6") self.gridLayout_44.addWidget(self.toolButton_reload_6, 2, 2, 1, 1) self.horizontalLayout_35 = QtWidgets.QHBoxLayout() self.horizontalLayout_35.setObjectName("horizontalLayout_35") self.label_116 = QtWidgets.QLabel(self.page_12) self.label_116.setStyleSheet("background-color : #656565; color : white") self.label_116.setFrameShape(QtWidgets.QFrame.Panel) self.label_116.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_116.setObjectName("label_116") self.horizontalLayout_35.addWidget(self.label_116) self.gridLayout_44.addLayout(self.horizontalLayout_35, 0, 0, 1, 3) self.gridLayout_186.addLayout(self.gridLayout_44, 0, 0, 1, 1) self.gridLayout_45 = QtWidgets.QGridLayout() self.gridLayout_45.setObjectName("gridLayout_45") spacerItem116 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_45.addItem(spacerItem116, 2, 0, 1, 1) spacerItem117 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_45.addItem(spacerItem117, 0, 2, 1, 1) self.label_169 = QtWidgets.QLabel(self.page_12) self.label_169.setStyleSheet("background-color : #656565; color : white") self.label_169.setFrameShape(QtWidgets.QFrame.Panel) self.label_169.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_169.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_169.setObjectName("label_169") self.gridLayout_45.addWidget(self.label_169, 1, 0, 1, 3) self.calculateLandCoverChange_toolButton = QtWidgets.QToolButton(self.page_12) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateLandCoverChange_toolButton.setFont(font) self.calculateLandCoverChange_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateLandCoverChange_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateLandCoverChange_toolButton.setIcon(icon64) self.calculateLandCoverChange_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateLandCoverChange_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateLandCoverChange_toolButton.setObjectName("calculateLandCoverChange_toolButton") self.gridLayout_45.addWidget(self.calculateLandCoverChange_toolButton, 2, 2, 1, 1) self.land_cover_change = QtWidgets.QToolButton(self.page_12) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.land_cover_change.setFont(font) self.land_cover_change.setLayoutDirection(QtCore.Qt.RightToLeft) self.land_cover_change.setStyleSheet("margin: 0px;padding: 0px;") self.land_cover_change.setIcon(icon48) self.land_cover_change.setIconSize(QtCore.QSize(34, 34)) self.land_cover_change.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.land_cover_change.setObjectName("land_cover_change") self.gridLayout_45.addWidget(self.land_cover_change, 2, 1, 1, 1) self.gridLayout_186.addLayout(self.gridLayout_45, 1, 0, 1, 1) self.toolBox_landCoverChange.addItem(self.page_12, "") self.page_13 = QtWidgets.QWidget() self.page_13.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_13.setObjectName("page_13") self.gridLayout_185 = QtWidgets.QGridLayout(self.page_13) self.gridLayout_185.setObjectName("gridLayout_185") self.gridLayout_46 = QtWidgets.QGridLayout() self.gridLayout_46.setObjectName("gridLayout_46") self.change_textBrowser = QtWidgets.QTextBrowser(self.page_13) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.change_textBrowser.setFont(font) self.change_textBrowser.setTabChangesFocus(True) self.change_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.change_textBrowser.setTabStopWidth(160) self.change_textBrowser.setOpenLinks(False) self.change_textBrowser.setObjectName("change_textBrowser") self.gridLayout_46.addWidget(self.change_textBrowser, 0, 0, 1, 1) self.gridLayout_185.addLayout(self.gridLayout_46, 0, 0, 1, 1) self.toolBox_landCoverChange.addItem(self.page_13, "") self.gridLayout_187.addWidget(self.toolBox_landCoverChange, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_landCoverChange, "") self.tab_class_report = QtWidgets.QWidget() self.tab_class_report.setObjectName("tab_class_report") self.gridLayout_27 = QtWidgets.QGridLayout(self.tab_class_report) self.gridLayout_27.setObjectName("gridLayout_27") self.toolBox_class_report = QtWidgets.QToolBox(self.tab_class_report) self.toolBox_class_report.setStyleSheet("") self.toolBox_class_report.setObjectName("toolBox_class_report") self.page_14 = QtWidgets.QWidget() self.page_14.setGeometry(QtCore.QRect(0, 0, 444, 167)) self.page_14.setObjectName("page_14") self.gridLayout_48 = QtWidgets.QGridLayout(self.page_14) self.gridLayout_48.setObjectName("gridLayout_48") self.gridLayout_47 = QtWidgets.QGridLayout() self.gridLayout_47.setObjectName("gridLayout_47") self.classification_report_name_combo = QtWidgets.QComboBox(self.page_14) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_report_name_combo.sizePolicy().hasHeightForWidth()) self.classification_report_name_combo.setSizePolicy(sizePolicy) self.classification_report_name_combo.setObjectName("classification_report_name_combo") self.gridLayout_47.addWidget(self.classification_report_name_combo, 1, 1, 1, 1) self.label_44 = QtWidgets.QLabel(self.page_14) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_44.sizePolicy().hasHeightForWidth()) self.label_44.setSizePolicy(sizePolicy) self.label_44.setMinimumSize(QtCore.QSize(229, 0)) self.label_44.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_44.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_44.setObjectName("label_44") self.gridLayout_47.addWidget(self.label_44, 1, 0, 1, 1) self.gridLayout_26 = QtWidgets.QGridLayout() self.gridLayout_26.setObjectName("gridLayout_26") self.nodata_checkBox = QtWidgets.QCheckBox(self.page_14) self.nodata_checkBox.setObjectName("nodata_checkBox") self.gridLayout_26.addWidget(self.nodata_checkBox, 0, 0, 1, 1) self.nodata_spinBox_2 = QtWidgets.QSpinBox(self.page_14) self.nodata_spinBox_2.setMinimum(-2147483647) self.nodata_spinBox_2.setMaximum(2147483647) self.nodata_spinBox_2.setProperty("value", 0) self.nodata_spinBox_2.setObjectName("nodata_spinBox_2") self.gridLayout_26.addWidget(self.nodata_spinBox_2, 0, 1, 1, 1) self.gridLayout_47.addLayout(self.gridLayout_26, 2, 0, 1, 1) self.toolButton_reload_10 = QtWidgets.QToolButton(self.page_14) self.toolButton_reload_10.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_10.setIcon(icon55) self.toolButton_reload_10.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_10.setObjectName("toolButton_reload_10") self.gridLayout_47.addWidget(self.toolButton_reload_10, 1, 2, 1, 1) self.gridLayout_48.addLayout(self.gridLayout_47, 1, 1, 1, 1) self.gridLayout_189 = QtWidgets.QGridLayout() self.gridLayout_189.setObjectName("gridLayout_189") spacerItem118 = QtWidgets.QSpacerItem(358, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_189.addItem(spacerItem118, 2, 1, 1, 1) self.label_170 = QtWidgets.QLabel(self.page_14) self.label_170.setStyleSheet("background-color : #656565; color : white") self.label_170.setFrameShape(QtWidgets.QFrame.Panel) self.label_170.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_170.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_170.setObjectName("label_170") self.gridLayout_189.addWidget(self.label_170, 1, 0, 1, 4) self.calculateReport_toolButton = QtWidgets.QToolButton(self.page_14) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculateReport_toolButton.setFont(font) self.calculateReport_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculateReport_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculateReport_toolButton.setIcon(icon64) self.calculateReport_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculateReport_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculateReport_toolButton.setObjectName("calculateReport_toolButton") self.gridLayout_189.addWidget(self.calculateReport_toolButton, 2, 3, 1, 1) spacerItem119 = QtWidgets.QSpacerItem(20, 82, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_189.addItem(spacerItem119, 0, 0, 1, 2) self.classification_report = QtWidgets.QToolButton(self.page_14) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_report.setFont(font) self.classification_report.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_report.setStyleSheet("margin: 0px;padding: 0px;") self.classification_report.setIcon(icon48) self.classification_report.setIconSize(QtCore.QSize(34, 34)) self.classification_report.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_report.setObjectName("classification_report") self.gridLayout_189.addWidget(self.classification_report, 2, 2, 1, 1) self.gridLayout_48.addLayout(self.gridLayout_189, 2, 1, 1, 1) self.horizontalLayout_37 = QtWidgets.QHBoxLayout() self.horizontalLayout_37.setObjectName("horizontalLayout_37") self.label_148 = QtWidgets.QLabel(self.page_14) self.label_148.setStyleSheet("background-color : #656565; color : white") self.label_148.setFrameShape(QtWidgets.QFrame.Panel) self.label_148.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_148.setObjectName("label_148") self.horizontalLayout_37.addWidget(self.label_148) self.gridLayout_48.addLayout(self.horizontalLayout_37, 0, 1, 1, 1) self.toolBox_class_report.addItem(self.page_14, "") self.page_15 = QtWidgets.QWidget() self.page_15.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_15.setObjectName("page_15") self.gridLayout_188 = QtWidgets.QGridLayout(self.page_15) self.gridLayout_188.setObjectName("gridLayout_188") self.gridLayout_43 = QtWidgets.QGridLayout() self.gridLayout_43.setObjectName("gridLayout_43") self.report_textBrowser = QtWidgets.QTextBrowser(self.page_15) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser.setFont(font) self.report_textBrowser.setTabChangesFocus(True) self.report_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser.setTabStopWidth(160) self.report_textBrowser.setOpenLinks(False) self.report_textBrowser.setObjectName("report_textBrowser") self.gridLayout_43.addWidget(self.report_textBrowser, 0, 0, 1, 1) self.gridLayout_188.addLayout(self.gridLayout_43, 0, 0, 1, 1) self.toolBox_class_report.addItem(self.page_15, "") self.gridLayout_27.addWidget(self.toolBox_class_report, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_class_report, "") self.tab_cross_classification = QtWidgets.QWidget() self.tab_cross_classification.setObjectName("tab_cross_classification") self.gridLayout_254 = QtWidgets.QGridLayout(self.tab_cross_classification) self.gridLayout_254.setObjectName("gridLayout_254") self.toolBox_cross_classification = QtWidgets.QToolBox(self.tab_cross_classification) self.toolBox_cross_classification.setObjectName("toolBox_cross_classification") self.page_19 = QtWidgets.QWidget() self.page_19.setGeometry(QtCore.QRect(0, 0, 456, 229)) self.page_19.setObjectName("page_19") self.gridLayout_192 = QtWidgets.QGridLayout(self.page_19) self.gridLayout_192.setObjectName("gridLayout_192") self.horizontalLayout_38 = QtWidgets.QHBoxLayout() self.horizontalLayout_38.setObjectName("horizontalLayout_38") self.label_187 = QtWidgets.QLabel(self.page_19) self.label_187.setStyleSheet("background-color : #656565; color : white") self.label_187.setFrameShape(QtWidgets.QFrame.Panel) self.label_187.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_187.setObjectName("label_187") self.horizontalLayout_38.addWidget(self.label_187) self.gridLayout_192.addLayout(self.horizontalLayout_38, 0, 0, 1, 1) self.gridLayout_250 = QtWidgets.QGridLayout() self.gridLayout_250.setObjectName("gridLayout_250") self.gridLayout_248 = QtWidgets.QGridLayout() self.gridLayout_248.setObjectName("gridLayout_248") self.nodata_checkBox_6 = QtWidgets.QCheckBox(self.page_19) self.nodata_checkBox_6.setObjectName("nodata_checkBox_6") self.gridLayout_248.addWidget(self.nodata_checkBox_6, 0, 0, 1, 1) self.nodata_spinBox_7 = QtWidgets.QSpinBox(self.page_19) self.nodata_spinBox_7.setMinimum(-2147483647) self.nodata_spinBox_7.setMaximum(2147483647) self.nodata_spinBox_7.setObjectName("nodata_spinBox_7") self.gridLayout_248.addWidget(self.nodata_spinBox_7, 0, 1, 1, 1) self.gridLayout_250.addLayout(self.gridLayout_248, 2, 0, 1, 1) self.label_197 = QtWidgets.QLabel(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_197.sizePolicy().hasHeightForWidth()) self.label_197.setSizePolicy(sizePolicy) self.label_197.setMinimumSize(QtCore.QSize(229, 0)) self.label_197.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_197.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_197.setObjectName("label_197") self.gridLayout_250.addWidget(self.label_197, 1, 0, 1, 1) self.label_199 = QtWidgets.QLabel(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_199.sizePolicy().hasHeightForWidth()) self.label_199.setSizePolicy(sizePolicy) self.label_199.setMinimumSize(QtCore.QSize(6, 0)) self.label_199.setMaximumSize(QtCore.QSize(100, 200)) self.label_199.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_199.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_199.setObjectName("label_199") self.gridLayout_250.addWidget(self.label_199, 4, 1, 1, 1) self.class_field_comboBox_2 = QtWidgets.QComboBox(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox_2.sizePolicy().hasHeightForWidth()) self.class_field_comboBox_2.setSizePolicy(sizePolicy) self.class_field_comboBox_2.setObjectName("class_field_comboBox_2") self.gridLayout_250.addWidget(self.class_field_comboBox_2, 4, 2, 1, 2) self.toolButton_reload_21 = QtWidgets.QToolButton(self.page_19) self.toolButton_reload_21.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_21.setIcon(icon55) self.toolButton_reload_21.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_21.setObjectName("toolButton_reload_21") self.gridLayout_250.addWidget(self.toolButton_reload_21, 1, 4, 1, 1) self.classification_name_combo_2 = QtWidgets.QComboBox(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_2.sizePolicy().hasHeightForWidth()) self.classification_name_combo_2.setSizePolicy(sizePolicy) self.classification_name_combo_2.setObjectName("classification_name_combo_2") self.gridLayout_250.addWidget(self.classification_name_combo_2, 1, 1, 1, 3) self.buttonReload_shape_5 = QtWidgets.QToolButton(self.page_19) self.buttonReload_shape_5.setStyleSheet("margin: 0px;padding: 0px;") self.buttonReload_shape_5.setIcon(icon55) self.buttonReload_shape_5.setIconSize(QtCore.QSize(22, 22)) self.buttonReload_shape_5.setObjectName("buttonReload_shape_5") self.gridLayout_250.addWidget(self.buttonReload_shape_5, 3, 4, 1, 1) self.reference_name_combo_2 = QtWidgets.QComboBox(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_name_combo_2.sizePolicy().hasHeightForWidth()) self.reference_name_combo_2.setSizePolicy(sizePolicy) self.reference_name_combo_2.setObjectName("reference_name_combo_2") self.gridLayout_250.addWidget(self.reference_name_combo_2, 3, 1, 1, 3) self.label_198 = QtWidgets.QLabel(self.page_19) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_198.sizePolicy().hasHeightForWidth()) self.label_198.setSizePolicy(sizePolicy) self.label_198.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_198.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_198.setObjectName("label_198") self.gridLayout_250.addWidget(self.label_198, 3, 0, 1, 1) self.gridLayout_192.addLayout(self.gridLayout_250, 1, 0, 1, 1) self.gridLayout_251 = QtWidgets.QGridLayout() self.gridLayout_251.setObjectName("gridLayout_251") spacerItem120 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_251.addItem(spacerItem120, 0, 2, 1, 1) spacerItem121 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_251.addItem(spacerItem121, 2, 0, 1, 1) self.label_200 = QtWidgets.QLabel(self.page_19) self.label_200.setStyleSheet("background-color : #656565; color : white") self.label_200.setFrameShape(QtWidgets.QFrame.Panel) self.label_200.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_200.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_200.setObjectName("label_200") self.gridLayout_251.addWidget(self.label_200, 1, 0, 1, 3) self.calculatecrossClass_toolButton = QtWidgets.QToolButton(self.page_19) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.calculatecrossClass_toolButton.setFont(font) self.calculatecrossClass_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.calculatecrossClass_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculatecrossClass_toolButton.setIcon(icon64) self.calculatecrossClass_toolButton.setIconSize(QtCore.QSize(34, 34)) self.calculatecrossClass_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.calculatecrossClass_toolButton.setObjectName("calculatecrossClass_toolButton") self.gridLayout_251.addWidget(self.calculatecrossClass_toolButton, 2, 2, 1, 1) self.cross_classification = QtWidgets.QToolButton(self.page_19) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.cross_classification.setFont(font) self.cross_classification.setLayoutDirection(QtCore.Qt.RightToLeft) self.cross_classification.setStyleSheet("margin: 0px;padding: 0px;") self.cross_classification.setIcon(icon48) self.cross_classification.setIconSize(QtCore.QSize(34, 34)) self.cross_classification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.cross_classification.setObjectName("cross_classification") self.gridLayout_251.addWidget(self.cross_classification, 2, 1, 1, 1) self.gridLayout_192.addLayout(self.gridLayout_251, 2, 0, 1, 1) self.toolBox_cross_classification.addItem(self.page_19, "") self.page_22 = QtWidgets.QWidget() self.page_22.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_22.setObjectName("page_22") self.gridLayout_252 = QtWidgets.QGridLayout(self.page_22) self.gridLayout_252.setObjectName("gridLayout_252") self.gridLayout_253 = QtWidgets.QGridLayout() self.gridLayout_253.setObjectName("gridLayout_253") self.cross_matrix_textBrowser = QtWidgets.QTextBrowser(self.page_22) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.cross_matrix_textBrowser.setFont(font) self.cross_matrix_textBrowser.setTabChangesFocus(True) self.cross_matrix_textBrowser.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.cross_matrix_textBrowser.setTabStopWidth(120) self.cross_matrix_textBrowser.setOpenLinks(False) self.cross_matrix_textBrowser.setObjectName("cross_matrix_textBrowser") self.gridLayout_253.addWidget(self.cross_matrix_textBrowser, 0, 0, 1, 1) self.gridLayout_252.addLayout(self.gridLayout_253, 0, 0, 1, 1) self.toolBox_cross_classification.addItem(self.page_22, "") self.gridLayout_254.addWidget(self.toolBox_cross_classification, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_cross_classification, "") self.tab_class_signature = QtWidgets.QWidget() self.tab_class_signature.setObjectName("tab_class_signature") self.gridLayout_123 = QtWidgets.QGridLayout(self.tab_class_signature) self.gridLayout_123.setObjectName("gridLayout_123") self.toolBox_class_signature = QtWidgets.QToolBox(self.tab_class_signature) self.toolBox_class_signature.setStyleSheet("") self.toolBox_class_signature.setObjectName("toolBox_class_signature") self.page_20 = QtWidgets.QWidget() self.page_20.setGeometry(QtCore.QRect(0, 0, 387, 196)) self.page_20.setObjectName("page_20") self.gridLayout_209 = QtWidgets.QGridLayout(self.page_20) self.gridLayout_209.setObjectName("gridLayout_209") self.horizontalLayout_39 = QtWidgets.QHBoxLayout() self.horizontalLayout_39.setObjectName("horizontalLayout_39") self.label_188 = QtWidgets.QLabel(self.page_20) self.label_188.setStyleSheet("background-color : #656565; color : white") self.label_188.setFrameShape(QtWidgets.QFrame.Panel) self.label_188.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_188.setObjectName("label_188") self.horizontalLayout_39.addWidget(self.label_188) self.gridLayout_209.addLayout(self.horizontalLayout_39, 0, 0, 1, 1) self.gridLayout_211 = QtWidgets.QGridLayout() self.gridLayout_211.setObjectName("gridLayout_211") self.gridLayout_112 = QtWidgets.QGridLayout() self.gridLayout_112.setObjectName("gridLayout_112") self.classification_name_combo_3 = QtWidgets.QComboBox(self.page_20) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_3.sizePolicy().hasHeightForWidth()) self.classification_name_combo_3.setSizePolicy(sizePolicy) self.classification_name_combo_3.setObjectName("classification_name_combo_3") self.gridLayout_112.addWidget(self.classification_name_combo_3, 0, 1, 1, 1) self.label_201 = QtWidgets.QLabel(self.page_20) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_201.sizePolicy().hasHeightForWidth()) self.label_201.setSizePolicy(sizePolicy) self.label_201.setMinimumSize(QtCore.QSize(229, 0)) self.label_201.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_201.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_201.setObjectName("label_201") self.gridLayout_112.addWidget(self.label_201, 0, 0, 1, 1) self.toolButton_reload_22 = QtWidgets.QToolButton(self.page_20) self.toolButton_reload_22.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_22.setIcon(icon55) self.toolButton_reload_22.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_22.setObjectName("toolButton_reload_22") self.gridLayout_112.addWidget(self.toolButton_reload_22, 0, 2, 1, 1) self.gridLayout_211.addLayout(self.gridLayout_112, 0, 0, 1, 3) self.label_259 = QtWidgets.QLabel(self.page_20) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_259.sizePolicy().hasHeightForWidth()) self.label_259.setSizePolicy(sizePolicy) self.label_259.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_259.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_259.setObjectName("label_259") self.gridLayout_211.addWidget(self.label_259, 1, 0, 1, 1) self.band_set_comb_spinBox_8 = QtWidgets.QSpinBox(self.page_20) self.band_set_comb_spinBox_8.setMinimum(1) self.band_set_comb_spinBox_8.setMaximum(100000) self.band_set_comb_spinBox_8.setObjectName("band_set_comb_spinBox_8") self.gridLayout_211.addWidget(self.band_set_comb_spinBox_8, 1, 1, 1, 1) spacerItem122 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_211.addItem(spacerItem122, 1, 2, 1, 1) self.gridLayout_209.addLayout(self.gridLayout_211, 1, 0, 1, 1) self.gridLayout_256 = QtWidgets.QGridLayout() self.gridLayout_256.setObjectName("gridLayout_256") self.label_184 = QtWidgets.QLabel(self.page_20) self.label_184.setStyleSheet("background-color : #656565; color : white") self.label_184.setFrameShape(QtWidgets.QFrame.Panel) self.label_184.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_184.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_184.setObjectName("label_184") self.gridLayout_256.addWidget(self.label_184, 2, 0, 1, 4) self.class_signature_Button = QtWidgets.QToolButton(self.page_20) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_signature_Button.setFont(font) self.class_signature_Button.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_signature_Button.setStyleSheet("margin: 0px;padding: 0px;") self.class_signature_Button.setIcon(icon64) self.class_signature_Button.setIconSize(QtCore.QSize(34, 34)) self.class_signature_Button.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_signature_Button.setObjectName("class_signature_Button") self.gridLayout_256.addWidget(self.class_signature_Button, 3, 3, 1, 1) spacerItem123 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_256.addItem(spacerItem123, 3, 0, 1, 2) spacerItem124 = QtWidgets.QSpacerItem(38, 37, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_256.addItem(spacerItem124, 1, 0, 1, 1) self.class_signature_save_siglist_checkBox = QtWidgets.QCheckBox(self.page_20) self.class_signature_save_siglist_checkBox.setChecked(True) self.class_signature_save_siglist_checkBox.setObjectName("class_signature_save_siglist_checkBox") self.gridLayout_256.addWidget(self.class_signature_save_siglist_checkBox, 0, 0, 1, 4) self.class_signature = QtWidgets.QToolButton(self.page_20) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_signature.setFont(font) self.class_signature.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_signature.setStyleSheet("margin: 0px;padding: 0px;") self.class_signature.setIcon(icon48) self.class_signature.setIconSize(QtCore.QSize(34, 34)) self.class_signature.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_signature.setObjectName("class_signature") self.gridLayout_256.addWidget(self.class_signature, 3, 2, 1, 1) self.gridLayout_209.addLayout(self.gridLayout_256, 2, 0, 1, 1) self.toolBox_class_signature.addItem(self.page_20, "") self.page_24 = QtWidgets.QWidget() self.page_24.setGeometry(QtCore.QRect(0, 0, 90, 90)) self.page_24.setObjectName("page_24") self.gridLayout_258 = QtWidgets.QGridLayout(self.page_24) self.gridLayout_258.setObjectName("gridLayout_258") self.gridLayout_259 = QtWidgets.QGridLayout() self.gridLayout_259.setObjectName("gridLayout_259") self.report_textBrowser_4 = QtWidgets.QTextBrowser(self.page_24) font = QtGui.QFont() font.setFamily("Courier 10 Pitch") self.report_textBrowser_4.setFont(font) self.report_textBrowser_4.setTabChangesFocus(True) self.report_textBrowser_4.setLineWrapMode(QtWidgets.QTextEdit.NoWrap) self.report_textBrowser_4.setTabStopWidth(160) self.report_textBrowser_4.setOpenLinks(False) self.report_textBrowser_4.setObjectName("report_textBrowser_4") self.gridLayout_259.addWidget(self.report_textBrowser_4, 0, 0, 1, 1) self.gridLayout_258.addLayout(self.gridLayout_259, 0, 0, 1, 1) self.toolBox_class_signature.addItem(self.page_24, "") self.gridLayout_123.addWidget(self.toolBox_class_signature, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_class_signature, "") self.tab_class_to_vector = QtWidgets.QWidget() self.tab_class_to_vector.setObjectName("tab_class_to_vector") self.gridLayout_49 = QtWidgets.QGridLayout(self.tab_class_to_vector) self.gridLayout_49.setObjectName("gridLayout_49") self.horizontalLayout_40 = QtWidgets.QHBoxLayout() self.horizontalLayout_40.setObjectName("horizontalLayout_40") self.label_189 = QtWidgets.QLabel(self.tab_class_to_vector) self.label_189.setStyleSheet("background-color : #656565; color : white") self.label_189.setFrameShape(QtWidgets.QFrame.Panel) self.label_189.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_189.setObjectName("label_189") self.horizontalLayout_40.addWidget(self.label_189) self.gridLayout_49.addLayout(self.horizontalLayout_40, 0, 0, 1, 1) self.gridLayout_71 = QtWidgets.QGridLayout() self.gridLayout_71.setObjectName("gridLayout_71") self.label_63 = QtWidgets.QLabel(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_63.sizePolicy().hasHeightForWidth()) self.label_63.setSizePolicy(sizePolicy) self.label_63.setMinimumSize(QtCore.QSize(229, 0)) self.label_63.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_63.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_63.setObjectName("label_63") self.gridLayout_71.addWidget(self.label_63, 0, 0, 1, 1) self.classification_vector_name_combo = QtWidgets.QComboBox(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_vector_name_combo.sizePolicy().hasHeightForWidth()) self.classification_vector_name_combo.setSizePolicy(sizePolicy) self.classification_vector_name_combo.setObjectName("classification_vector_name_combo") self.gridLayout_71.addWidget(self.classification_vector_name_combo, 0, 1, 1, 1) self.toolButton_reload_11 = QtWidgets.QToolButton(self.tab_class_to_vector) self.toolButton_reload_11.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_11.setIcon(icon55) self.toolButton_reload_11.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_11.setObjectName("toolButton_reload_11") self.gridLayout_71.addWidget(self.toolButton_reload_11, 0, 2, 1, 1) self.gridLayout_49.addLayout(self.gridLayout_71, 1, 0, 1, 1) self.gridLayout_74 = QtWidgets.QGridLayout() self.gridLayout_74.setObjectName("gridLayout_74") self.class_macroclass_comboBox = QtWidgets.QComboBox(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_macroclass_comboBox.sizePolicy().hasHeightForWidth()) self.class_macroclass_comboBox.setSizePolicy(sizePolicy) self.class_macroclass_comboBox.setObjectName("class_macroclass_comboBox") self.class_macroclass_comboBox.addItem("") self.class_macroclass_comboBox.addItem("") self.gridLayout_74.addWidget(self.class_macroclass_comboBox, 1, 1, 1, 1) self.use_class_code_checkBox = QtWidgets.QCheckBox(self.tab_class_to_vector) self.use_class_code_checkBox.setObjectName("use_class_code_checkBox") self.gridLayout_74.addWidget(self.use_class_code_checkBox, 1, 0, 1, 1) self.label_49 = QtWidgets.QLabel(self.tab_class_to_vector) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_49.sizePolicy().hasHeightForWidth()) self.label_49.setSizePolicy(sizePolicy) self.label_49.setStyleSheet("background-color : #656565; color : white") self.label_49.setFrameShape(QtWidgets.QFrame.Panel) self.label_49.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_49.setObjectName("label_49") self.gridLayout_74.addWidget(self.label_49, 0, 0, 1, 2) self.dissolve_output_checkBox = QtWidgets.QCheckBox(self.tab_class_to_vector) self.dissolve_output_checkBox.setObjectName("dissolve_output_checkBox") self.gridLayout_74.addWidget(self.dissolve_output_checkBox, 2, 0, 1, 1) self.gridLayout_49.addLayout(self.gridLayout_74, 2, 0, 1, 1) self.gridLayout_75 = QtWidgets.QGridLayout() self.gridLayout_75.setObjectName("gridLayout_75") spacerItem125 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_75.addItem(spacerItem125, 0, 1, 1, 1) spacerItem126 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_75.addItem(spacerItem126, 0, 0, 1, 1) self.convert_toolButton = QtWidgets.QToolButton(self.tab_class_to_vector) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.convert_toolButton.setFont(font) self.convert_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.convert_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.convert_toolButton.setIcon(icon64) self.convert_toolButton.setIconSize(QtCore.QSize(34, 34)) self.convert_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.convert_toolButton.setObjectName("convert_toolButton") self.gridLayout_75.addWidget(self.convert_toolButton, 2, 2, 1, 1) self.label_171 = QtWidgets.QLabel(self.tab_class_to_vector) self.label_171.setStyleSheet("background-color : #656565; color : white") self.label_171.setFrameShape(QtWidgets.QFrame.Panel) self.label_171.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_171.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_171.setObjectName("label_171") self.gridLayout_75.addWidget(self.label_171, 1, 0, 1, 3) self.classification_to_vector = QtWidgets.QToolButton(self.tab_class_to_vector) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_to_vector.setFont(font) self.classification_to_vector.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_to_vector.setStyleSheet("margin: 0px;padding: 0px;") self.classification_to_vector.setIcon(icon48) self.classification_to_vector.setIconSize(QtCore.QSize(34, 34)) self.classification_to_vector.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_to_vector.setObjectName("classification_to_vector") self.gridLayout_75.addWidget(self.classification_to_vector, 2, 1, 1, 1) self.gridLayout_49.addLayout(self.gridLayout_75, 3, 0, 1, 1) self.tabWidget_2.addTab(self.tab_class_to_vector, "") self.tab_reclassification = QtWidgets.QWidget() self.tab_reclassification.setObjectName("tab_reclassification") self.gridLayout_191 = QtWidgets.QGridLayout(self.tab_reclassification) self.gridLayout_191.setObjectName("gridLayout_191") self.gridLayout_78 = QtWidgets.QGridLayout() self.gridLayout_78.setObjectName("gridLayout_78") self.label_65 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_65.sizePolicy().hasHeightForWidth()) self.label_65.setSizePolicy(sizePolicy) self.label_65.setMinimumSize(QtCore.QSize(229, 0)) self.label_65.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_65.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_65.setObjectName("label_65") self.gridLayout_78.addWidget(self.label_65, 1, 0, 1, 1) self.reclassification_name_combo = QtWidgets.QComboBox(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reclassification_name_combo.sizePolicy().hasHeightForWidth()) self.reclassification_name_combo.setSizePolicy(sizePolicy) self.reclassification_name_combo.setObjectName("reclassification_name_combo") self.gridLayout_78.addWidget(self.reclassification_name_combo, 1, 1, 1, 1) self.toolButton_reload_12 = QtWidgets.QToolButton(self.tab_reclassification) self.toolButton_reload_12.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_12.setIcon(icon55) self.toolButton_reload_12.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_12.setObjectName("toolButton_reload_12") self.gridLayout_78.addWidget(self.toolButton_reload_12, 1, 2, 1, 1) self.horizontalLayout_41 = QtWidgets.QHBoxLayout() self.horizontalLayout_41.setObjectName("horizontalLayout_41") self.label_190 = QtWidgets.QLabel(self.tab_reclassification) self.label_190.setStyleSheet("background-color : #656565; color : white") self.label_190.setFrameShape(QtWidgets.QFrame.Panel) self.label_190.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_190.setObjectName("label_190") self.horizontalLayout_41.addWidget(self.label_190) self.gridLayout_78.addLayout(self.horizontalLayout_41, 0, 0, 1, 3) self.gridLayout_191.addLayout(self.gridLayout_78, 0, 0, 1, 1) self.gridLayout_79 = QtWidgets.QGridLayout() self.gridLayout_79.setObjectName("gridLayout_79") self.calculate_unique_values_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.calculate_unique_values_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.calculate_unique_values_toolButton.setIcon(icon67) self.calculate_unique_values_toolButton.setIconSize(QtCore.QSize(22, 22)) self.calculate_unique_values_toolButton.setObjectName("calculate_unique_values_toolButton") self.gridLayout_79.addWidget(self.calculate_unique_values_toolButton, 1, 4, 1, 1) self.CID_MCID_code_checkBox = QtWidgets.QCheckBox(self.tab_reclassification) self.CID_MCID_code_checkBox.setObjectName("CID_MCID_code_checkBox") self.gridLayout_79.addWidget(self.CID_MCID_code_checkBox, 1, 2, 1, 1) self.label_98 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_98.sizePolicy().hasHeightForWidth()) self.label_98.setSizePolicy(sizePolicy) self.label_98.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_98.setObjectName("label_98") self.gridLayout_79.addWidget(self.label_98, 1, 3, 1, 1) self.label_54 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_54.sizePolicy().hasHeightForWidth()) self.label_54.setSizePolicy(sizePolicy) self.label_54.setStyleSheet("background-color : #656565; color : white") self.label_54.setFrameShape(QtWidgets.QFrame.Panel) self.label_54.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_54.setObjectName("label_54") self.gridLayout_79.addWidget(self.label_54, 0, 2, 1, 3) self.incremental_new_values_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.incremental_new_values_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.incremental_new_values_toolButton.setIcon(icon67) self.incremental_new_values_toolButton.setIconSize(QtCore.QSize(22, 22)) self.incremental_new_values_toolButton.setObjectName("incremental_new_values_toolButton") self.gridLayout_79.addWidget(self.incremental_new_values_toolButton, 2, 4, 1, 1) self.label_271 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_271.sizePolicy().hasHeightForWidth()) self.label_271.setSizePolicy(sizePolicy) self.label_271.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_271.setObjectName("label_271") self.gridLayout_79.addWidget(self.label_271, 2, 3, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_79, 1, 0, 1, 1) self.gridLayout_77 = QtWidgets.QGridLayout() self.gridLayout_77.setObjectName("gridLayout_77") self.reclass_values_tableWidget = QtWidgets.QTableWidget(self.tab_reclassification) self.reclass_values_tableWidget.setAlternatingRowColors(True) self.reclass_values_tableWidget.setObjectName("reclass_values_tableWidget") self.reclass_values_tableWidget.setColumnCount(2) self.reclass_values_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.reclass_values_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.reclass_values_tableWidget.setHorizontalHeaderItem(1, item) self.reclass_values_tableWidget.horizontalHeader().setStretchLastSection(True) self.reclass_values_tableWidget.verticalHeader().setDefaultSectionSize(24) self.gridLayout_77.addWidget(self.reclass_values_tableWidget, 0, 0, 1, 1) self.gridLayout_81 = QtWidgets.QGridLayout() self.gridLayout_81.setObjectName("gridLayout_81") self.add_value_pushButton = QtWidgets.QToolButton(self.tab_reclassification) self.add_value_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.add_value_pushButton.setIcon(icon66) self.add_value_pushButton.setIconSize(QtCore.QSize(22, 22)) self.add_value_pushButton.setObjectName("add_value_pushButton") self.gridLayout_81.addWidget(self.add_value_pushButton, 1, 0, 1, 1) self.remove_row_pushButton = QtWidgets.QToolButton(self.tab_reclassification) self.remove_row_pushButton.setStyleSheet("margin: 0px;padding: 0px;") self.remove_row_pushButton.setIcon(icon58) self.remove_row_pushButton.setIconSize(QtCore.QSize(22, 22)) self.remove_row_pushButton.setObjectName("remove_row_pushButton") self.gridLayout_81.addWidget(self.remove_row_pushButton, 2, 0, 1, 1) spacerItem127 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_81.addItem(spacerItem127, 0, 0, 1, 1) spacerItem128 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_81.addItem(spacerItem128, 6, 0, 1, 1) self.import_reclass_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.import_reclass_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_reclass_toolButton.setIcon(icon54) self.import_reclass_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_reclass_toolButton.setObjectName("import_reclass_toolButton") self.gridLayout_81.addWidget(self.import_reclass_toolButton, 4, 0, 1, 1) self.export_reclass_toolButton = QtWidgets.QToolButton(self.tab_reclassification) self.export_reclass_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_reclass_toolButton.setIcon(icon53) self.export_reclass_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_reclass_toolButton.setObjectName("export_reclass_toolButton") self.gridLayout_81.addWidget(self.export_reclass_toolButton, 5, 0, 1, 1) spacerItem129 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_81.addItem(spacerItem129, 3, 0, 1, 1) self.gridLayout_77.addLayout(self.gridLayout_81, 0, 1, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_77, 2, 0, 1, 1) self.gridLayout_80 = QtWidgets.QGridLayout() self.gridLayout_80.setObjectName("gridLayout_80") self.gridLayout_82 = QtWidgets.QGridLayout() self.gridLayout_82.setObjectName("gridLayout_82") self.apply_symbology_checkBox = QtWidgets.QCheckBox(self.tab_reclassification) self.apply_symbology_checkBox.setChecked(False) self.apply_symbology_checkBox.setObjectName("apply_symbology_checkBox") self.gridLayout_82.addWidget(self.apply_symbology_checkBox, 1, 0, 1, 1) self.class_macroclass_comboBox_2 = QtWidgets.QComboBox(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_macroclass_comboBox_2.sizePolicy().hasHeightForWidth()) self.class_macroclass_comboBox_2.setSizePolicy(sizePolicy) self.class_macroclass_comboBox_2.setObjectName("class_macroclass_comboBox_2") self.class_macroclass_comboBox_2.addItem("") self.class_macroclass_comboBox_2.addItem("") self.gridLayout_82.addWidget(self.class_macroclass_comboBox_2, 1, 1, 1, 1) self.label_51 = QtWidgets.QLabel(self.tab_reclassification) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_51.sizePolicy().hasHeightForWidth()) self.label_51.setSizePolicy(sizePolicy) self.label_51.setStyleSheet("background-color : #656565; color : white") self.label_51.setFrameShape(QtWidgets.QFrame.Panel) self.label_51.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_51.setObjectName("label_51") self.gridLayout_82.addWidget(self.label_51, 0, 0, 1, 2) self.gridLayout_80.addLayout(self.gridLayout_82, 0, 0, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_80, 3, 0, 1, 1) self.gridLayout_83 = QtWidgets.QGridLayout() self.gridLayout_83.setObjectName("gridLayout_83") spacerItem130 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_83.addItem(spacerItem130, 1, 0, 1, 1) self.label_172 = QtWidgets.QLabel(self.tab_reclassification) self.label_172.setStyleSheet("background-color : #656565; color : white") self.label_172.setFrameShape(QtWidgets.QFrame.Panel) self.label_172.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_172.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_172.setObjectName("label_172") self.gridLayout_83.addWidget(self.label_172, 0, 0, 1, 3) self.reclassify_toolButton = QtWidgets.QToolButton(self.tab_reclassification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reclassify_toolButton.setFont(font) self.reclassify_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.reclassify_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.reclassify_toolButton.setIcon(icon64) self.reclassify_toolButton.setIconSize(QtCore.QSize(34, 34)) self.reclassify_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reclassify_toolButton.setObjectName("reclassify_toolButton") self.gridLayout_83.addWidget(self.reclassify_toolButton, 1, 2, 1, 1) self.reclassification = QtWidgets.QToolButton(self.tab_reclassification) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.reclassification.setFont(font) self.reclassification.setLayoutDirection(QtCore.Qt.RightToLeft) self.reclassification.setStyleSheet("margin: 0px;padding: 0px;") self.reclassification.setIcon(icon48) self.reclassification.setIconSize(QtCore.QSize(34, 34)) self.reclassification.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.reclassification.setObjectName("reclassification") self.gridLayout_83.addWidget(self.reclassification, 1, 1, 1, 1) self.gridLayout_191.addLayout(self.gridLayout_83, 4, 0, 1, 1) self.tabWidget_2.addTab(self.tab_reclassification, "") self.tab = QtWidgets.QWidget() self.tab.setObjectName("tab") self.gridLayout_359 = QtWidgets.QGridLayout(self.tab) self.gridLayout_359.setObjectName("gridLayout_359") self.horizontalLayout_42 = QtWidgets.QHBoxLayout() self.horizontalLayout_42.setObjectName("horizontalLayout_42") self.label_193 = QtWidgets.QLabel(self.tab) self.label_193.setStyleSheet("background-color : #656565; color : white") self.label_193.setFrameShape(QtWidgets.QFrame.Panel) self.label_193.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_193.setObjectName("label_193") self.horizontalLayout_42.addWidget(self.label_193) self.gridLayout_359.addLayout(self.horizontalLayout_42, 0, 0, 1, 1) self.gridLayout_196 = QtWidgets.QGridLayout() self.gridLayout_196.setObjectName("gridLayout_196") self.undo_edit_Button = QtWidgets.QToolButton(self.tab) self.undo_edit_Button.setEnabled(False) self.undo_edit_Button.setStyleSheet("margin: 0px;padding: 0px;") icon81 = QtGui.QIcon() icon81.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_undo_edit_raster.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.undo_edit_Button.setIcon(icon81) self.undo_edit_Button.setIconSize(QtCore.QSize(22, 22)) self.undo_edit_Button.setObjectName("undo_edit_Button") self.gridLayout_196.addWidget(self.undo_edit_Button, 10, 0, 1, 1) self.label_173 = QtWidgets.QLabel(self.tab) self.label_173.setStyleSheet("background-color : #656565; color : white") self.label_173.setFrameShape(QtWidgets.QFrame.Panel) self.label_173.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_173.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_173.setObjectName("label_173") self.gridLayout_196.addWidget(self.label_173, 9, 0, 1, 4) self.horizontalLayout_8 = QtWidgets.QHBoxLayout() self.horizontalLayout_8.setObjectName("horizontalLayout_8") self.label_66 = QtWidgets.QLabel(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_66.sizePolicy().hasHeightForWidth()) self.label_66.setSizePolicy(sizePolicy) self.label_66.setMinimumSize(QtCore.QSize(229, 0)) self.label_66.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_66.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_66.setObjectName("label_66") self.horizontalLayout_8.addWidget(self.label_66) self.edit_raster_name_combo = QtWidgets.QComboBox(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.edit_raster_name_combo.sizePolicy().hasHeightForWidth()) self.edit_raster_name_combo.setSizePolicy(sizePolicy) self.edit_raster_name_combo.setObjectName("edit_raster_name_combo") self.horizontalLayout_8.addWidget(self.edit_raster_name_combo) self.toolButton_reload_14 = QtWidgets.QToolButton(self.tab) self.toolButton_reload_14.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_14.setIcon(icon55) self.toolButton_reload_14.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_14.setObjectName("toolButton_reload_14") self.horizontalLayout_8.addWidget(self.toolButton_reload_14) self.gridLayout_196.addLayout(self.horizontalLayout_8, 0, 0, 1, 4) self.horizontalLayout_6 = QtWidgets.QHBoxLayout() self.horizontalLayout_6.setObjectName("horizontalLayout_6") self.use_constant_val_checkBox = QtWidgets.QCheckBox(self.tab) self.use_constant_val_checkBox.setChecked(True) self.use_constant_val_checkBox.setObjectName("use_constant_val_checkBox") self.horizontalLayout_6.addWidget(self.use_constant_val_checkBox) self.value_spinBox = QtWidgets.QSpinBox(self.tab) self.value_spinBox.setMinimum(-2147483647) self.value_spinBox.setMaximum(2147483647) self.value_spinBox.setObjectName("value_spinBox") self.horizontalLayout_6.addWidget(self.value_spinBox) spacerItem131 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_6.addItem(spacerItem131) self.gridLayout_196.addLayout(self.horizontalLayout_6, 6, 0, 1, 4) self.horizontalLayout_7 = QtWidgets.QHBoxLayout() self.horizontalLayout_7.setObjectName("horizontalLayout_7") self.use_expression_checkBox = QtWidgets.QCheckBox(self.tab) self.use_expression_checkBox.setObjectName("use_expression_checkBox") self.horizontalLayout_7.addWidget(self.use_expression_checkBox) self.expression_lineEdit = QtWidgets.QLineEdit(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.expression_lineEdit.sizePolicy().hasHeightForWidth()) self.expression_lineEdit.setSizePolicy(sizePolicy) self.expression_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.expression_lineEdit.setMaxLength(10000) self.expression_lineEdit.setObjectName("expression_lineEdit") self.horizontalLayout_7.addWidget(self.expression_lineEdit) self.gridLayout_196.addLayout(self.horizontalLayout_7, 7, 0, 1, 4) spacerItem132 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_196.addItem(spacerItem132, 10, 1, 1, 1) spacerItem133 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_196.addItem(spacerItem133, 8, 3, 1, 1) self.horizontalLayout_9 = QtWidgets.QHBoxLayout() self.horizontalLayout_9.setObjectName("horizontalLayout_9") self.label_81 = QtWidgets.QLabel(self.tab) self.label_81.setStyleSheet("background-color : #656565; color : white") self.label_81.setFrameShape(QtWidgets.QFrame.Panel) self.label_81.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_81.setObjectName("label_81") self.horizontalLayout_9.addWidget(self.label_81) self.gridLayout_196.addLayout(self.horizontalLayout_9, 1, 0, 1, 4) self.horizontalLayout_24 = QtWidgets.QHBoxLayout() self.horizontalLayout_24.setObjectName("horizontalLayout_24") self.use_field_vector_checkBox = QtWidgets.QCheckBox(self.tab) self.use_field_vector_checkBox.setObjectName("use_field_vector_checkBox") self.horizontalLayout_24.addWidget(self.use_field_vector_checkBox) self.field_comboBox_2 = QtWidgets.QComboBox(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.field_comboBox_2.sizePolicy().hasHeightForWidth()) self.field_comboBox_2.setSizePolicy(sizePolicy) self.field_comboBox_2.setObjectName("field_comboBox_2") self.horizontalLayout_24.addWidget(self.field_comboBox_2) self.gridLayout_196.addLayout(self.horizontalLayout_24, 5, 0, 1, 4) self.horizontalLayout_21 = QtWidgets.QHBoxLayout() self.horizontalLayout_21.setObjectName("horizontalLayout_21") self.edit_val_use_vector_radioButton = QtWidgets.QRadioButton(self.tab) self.edit_val_use_vector_radioButton.setObjectName("edit_val_use_vector_radioButton") self.horizontalLayout_21.addWidget(self.edit_val_use_vector_radioButton) self.vector_name_combo_2 = QtWidgets.QComboBox(self.tab) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.vector_name_combo_2.sizePolicy().hasHeightForWidth()) self.vector_name_combo_2.setSizePolicy(sizePolicy) self.vector_name_combo_2.setObjectName("vector_name_combo_2") self.horizontalLayout_21.addWidget(self.vector_name_combo_2) self.toolButton_reload_20 = QtWidgets.QToolButton(self.tab) self.toolButton_reload_20.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_20.setIcon(icon55) self.toolButton_reload_20.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_20.setObjectName("toolButton_reload_20") self.horizontalLayout_21.addWidget(self.toolButton_reload_20) self.gridLayout_196.addLayout(self.horizontalLayout_21, 3, 0, 1, 4) self.horizontalLayout_23 = QtWidgets.QHBoxLayout() self.horizontalLayout_23.setObjectName("horizontalLayout_23") self.edit_val_use_ROI_radioButton = QtWidgets.QRadioButton(self.tab) self.edit_val_use_ROI_radioButton.setChecked(True) self.edit_val_use_ROI_radioButton.setObjectName("edit_val_use_ROI_radioButton") self.horizontalLayout_23.addWidget(self.edit_val_use_ROI_radioButton) self.gridLayout_196.addLayout(self.horizontalLayout_23, 2, 0, 1, 4) self.horizontalLayout_26 = QtWidgets.QHBoxLayout() self.horizontalLayout_26.setObjectName("horizontalLayout_26") self.label_158 = QtWidgets.QLabel(self.tab) self.label_158.setStyleSheet("background-color : #656565; color : white") self.label_158.setFrameShape(QtWidgets.QFrame.Panel) self.label_158.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_158.setObjectName("label_158") self.horizontalLayout_26.addWidget(self.label_158) self.gridLayout_196.addLayout(self.horizontalLayout_26, 4, 0, 1, 4) self.raster_set_value_toolButton = QtWidgets.QToolButton(self.tab) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.raster_set_value_toolButton.setFont(font) self.raster_set_value_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.raster_set_value_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.raster_set_value_toolButton.setIcon(icon64) self.raster_set_value_toolButton.setIconSize(QtCore.QSize(34, 34)) self.raster_set_value_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.raster_set_value_toolButton.setObjectName("raster_set_value_toolButton") self.gridLayout_196.addWidget(self.raster_set_value_toolButton, 10, 3, 1, 1) self.edit_raster_using_vector = QtWidgets.QToolButton(self.tab) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.edit_raster_using_vector.setFont(font) self.edit_raster_using_vector.setLayoutDirection(QtCore.Qt.RightToLeft) self.edit_raster_using_vector.setStyleSheet("margin: 0px;padding: 0px;") self.edit_raster_using_vector.setIcon(icon48) self.edit_raster_using_vector.setIconSize(QtCore.QSize(34, 34)) self.edit_raster_using_vector.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.edit_raster_using_vector.setObjectName("edit_raster_using_vector") self.gridLayout_196.addWidget(self.edit_raster_using_vector, 10, 2, 1, 1) self.gridLayout_359.addLayout(self.gridLayout_196, 1, 0, 1, 1) self.tabWidget_2.addTab(self.tab, "") self.tab_sieve = QtWidgets.QWidget() self.tab_sieve.setObjectName("tab_sieve") self.gridLayout_202 = QtWidgets.QGridLayout(self.tab_sieve) self.gridLayout_202.setObjectName("gridLayout_202") self.gridLayout_64 = QtWidgets.QGridLayout() self.gridLayout_64.setObjectName("gridLayout_64") spacerItem134 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_64.addItem(spacerItem134, 2, 2, 1, 1) spacerItem135 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_64.addItem(spacerItem135, 4, 0, 1, 1) self.horizontalLayout_11 = QtWidgets.QHBoxLayout() self.horizontalLayout_11.setObjectName("horizontalLayout_11") self.label_70 = QtWidgets.QLabel(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_70.sizePolicy().hasHeightForWidth()) self.label_70.setSizePolicy(sizePolicy) self.label_70.setMinimumSize(QtCore.QSize(229, 0)) self.label_70.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_70.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_70.setObjectName("label_70") self.horizontalLayout_11.addWidget(self.label_70) self.sieve_raster_name_combo = QtWidgets.QComboBox(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.sieve_raster_name_combo.sizePolicy().hasHeightForWidth()) self.sieve_raster_name_combo.setSizePolicy(sizePolicy) self.sieve_raster_name_combo.setObjectName("sieve_raster_name_combo") self.horizontalLayout_11.addWidget(self.sieve_raster_name_combo) self.toolButton_reload_15 = QtWidgets.QToolButton(self.tab_sieve) self.toolButton_reload_15.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_15.setIcon(icon55) self.toolButton_reload_15.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_15.setObjectName("toolButton_reload_15") self.horizontalLayout_11.addWidget(self.toolButton_reload_15) self.gridLayout_64.addLayout(self.horizontalLayout_11, 0, 0, 1, 3) self.horizontalLayout_12 = QtWidgets.QHBoxLayout() self.horizontalLayout_12.setObjectName("horizontalLayout_12") self.label_133 = QtWidgets.QLabel(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_133.sizePolicy().hasHeightForWidth()) self.label_133.setSizePolicy(sizePolicy) self.label_133.setMinimumSize(QtCore.QSize(229, 0)) self.label_133.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_133.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_133.setObjectName("label_133") self.horizontalLayout_12.addWidget(self.label_133) self.sieve_threshold_spinBox = QtWidgets.QSpinBox(self.tab_sieve) self.sieve_threshold_spinBox.setMinimum(2) self.sieve_threshold_spinBox.setMaximum(10000) self.sieve_threshold_spinBox.setObjectName("sieve_threshold_spinBox") self.horizontalLayout_12.addWidget(self.sieve_threshold_spinBox) spacerItem136 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_12.addItem(spacerItem136) self.label_136 = QtWidgets.QLabel(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_136.sizePolicy().hasHeightForWidth()) self.label_136.setSizePolicy(sizePolicy) self.label_136.setMinimumSize(QtCore.QSize(229, 0)) self.label_136.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_136.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_136.setObjectName("label_136") self.horizontalLayout_12.addWidget(self.label_136) self.sieve_connection_combo = QtWidgets.QComboBox(self.tab_sieve) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.sieve_connection_combo.sizePolicy().hasHeightForWidth()) self.sieve_connection_combo.setSizePolicy(sizePolicy) self.sieve_connection_combo.setMaximumSize(QtCore.QSize(80, 16777215)) self.sieve_connection_combo.setObjectName("sieve_connection_combo") self.sieve_connection_combo.addItem("") self.sieve_connection_combo.addItem("") self.horizontalLayout_12.addWidget(self.sieve_connection_combo) self.gridLayout_64.addLayout(self.horizontalLayout_12, 1, 0, 1, 3) self.label_174 = QtWidgets.QLabel(self.tab_sieve) self.label_174.setStyleSheet("background-color : #656565; color : white") self.label_174.setFrameShape(QtWidgets.QFrame.Panel) self.label_174.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_174.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_174.setObjectName("label_174") self.gridLayout_64.addWidget(self.label_174, 3, 0, 1, 3) self.sieve_toolButton = QtWidgets.QToolButton(self.tab_sieve) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.sieve_toolButton.setFont(font) self.sieve_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.sieve_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.sieve_toolButton.setIcon(icon64) self.sieve_toolButton.setIconSize(QtCore.QSize(34, 34)) self.sieve_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.sieve_toolButton.setObjectName("sieve_toolButton") self.gridLayout_64.addWidget(self.sieve_toolButton, 4, 2, 1, 1) self.classification_sieve = QtWidgets.QToolButton(self.tab_sieve) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_sieve.setFont(font) self.classification_sieve.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_sieve.setStyleSheet("margin: 0px;padding: 0px;") self.classification_sieve.setIcon(icon48) self.classification_sieve.setIconSize(QtCore.QSize(34, 34)) self.classification_sieve.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_sieve.setObjectName("classification_sieve") self.gridLayout_64.addWidget(self.classification_sieve, 4, 1, 1, 1) self.gridLayout_202.addLayout(self.gridLayout_64, 1, 0, 1, 1) self.horizontalLayout_43 = QtWidgets.QHBoxLayout() self.horizontalLayout_43.setObjectName("horizontalLayout_43") self.label_195 = QtWidgets.QLabel(self.tab_sieve) self.label_195.setStyleSheet("background-color : #656565; color : white") self.label_195.setFrameShape(QtWidgets.QFrame.Panel) self.label_195.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_195.setObjectName("label_195") self.horizontalLayout_43.addWidget(self.label_195) self.gridLayout_202.addLayout(self.horizontalLayout_43, 0, 0, 1, 1) self.tabWidget_2.addTab(self.tab_sieve, "") self.tab_erosion = QtWidgets.QWidget() self.tab_erosion.setObjectName("tab_erosion") self.gridLayout_205 = QtWidgets.QGridLayout(self.tab_erosion) self.gridLayout_205.setObjectName("gridLayout_205") self.horizontalLayout_44 = QtWidgets.QHBoxLayout() self.horizontalLayout_44.setObjectName("horizontalLayout_44") self.label_202 = QtWidgets.QLabel(self.tab_erosion) self.label_202.setStyleSheet("background-color : #656565; color : white") self.label_202.setFrameShape(QtWidgets.QFrame.Panel) self.label_202.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_202.setObjectName("label_202") self.horizontalLayout_44.addWidget(self.label_202) self.gridLayout_205.addLayout(self.horizontalLayout_44, 0, 0, 1, 1) self.gridLayout_204 = QtWidgets.QGridLayout() self.gridLayout_204.setObjectName("gridLayout_204") spacerItem137 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_204.addItem(spacerItem137, 3, 2, 1, 1) spacerItem138 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_204.addItem(spacerItem138, 5, 0, 1, 1) self.horizontalLayout_13 = QtWidgets.QHBoxLayout() self.horizontalLayout_13.setObjectName("horizontalLayout_13") self.label_146 = QtWidgets.QLabel(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_146.sizePolicy().hasHeightForWidth()) self.label_146.setSizePolicy(sizePolicy) self.label_146.setMinimumSize(QtCore.QSize(229, 0)) self.label_146.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_146.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_146.setObjectName("label_146") self.horizontalLayout_13.addWidget(self.label_146) self.erosion_raster_name_combo = QtWidgets.QComboBox(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.erosion_raster_name_combo.sizePolicy().hasHeightForWidth()) self.erosion_raster_name_combo.setSizePolicy(sizePolicy) self.erosion_raster_name_combo.setObjectName("erosion_raster_name_combo") self.horizontalLayout_13.addWidget(self.erosion_raster_name_combo) self.toolButton_reload_18 = QtWidgets.QToolButton(self.tab_erosion) self.toolButton_reload_18.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_18.setIcon(icon55) self.toolButton_reload_18.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_18.setObjectName("toolButton_reload_18") self.horizontalLayout_13.addWidget(self.toolButton_reload_18) self.gridLayout_204.addLayout(self.horizontalLayout_13, 0, 0, 1, 3) self.horizontalLayout_14 = QtWidgets.QHBoxLayout() self.horizontalLayout_14.setObjectName("horizontalLayout_14") self.label_149 = QtWidgets.QLabel(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_149.sizePolicy().hasHeightForWidth()) self.label_149.setSizePolicy(sizePolicy) self.label_149.setMinimumSize(QtCore.QSize(229, 0)) self.label_149.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_149.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_149.setObjectName("label_149") self.horizontalLayout_14.addWidget(self.label_149) self.erosion_threshold_spinBox = QtWidgets.QSpinBox(self.tab_erosion) self.erosion_threshold_spinBox.setMinimum(1) self.erosion_threshold_spinBox.setMaximum(1000) self.erosion_threshold_spinBox.setProperty("value", 1) self.erosion_threshold_spinBox.setObjectName("erosion_threshold_spinBox") self.horizontalLayout_14.addWidget(self.erosion_threshold_spinBox) self.circular_structure_checkBox_3 = QtWidgets.QCheckBox(self.tab_erosion) self.circular_structure_checkBox_3.setObjectName("circular_structure_checkBox_3") self.horizontalLayout_14.addWidget(self.circular_structure_checkBox_3) spacerItem139 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_14.addItem(spacerItem139) self.gridLayout_204.addLayout(self.horizontalLayout_14, 2, 0, 1, 3) self.horizontalLayout_15 = QtWidgets.QHBoxLayout() self.horizontalLayout_15.setObjectName("horizontalLayout_15") self.label_151 = QtWidgets.QLabel(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_151.sizePolicy().hasHeightForWidth()) self.label_151.setSizePolicy(sizePolicy) self.label_151.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_151.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_151.setObjectName("label_151") self.horizontalLayout_15.addWidget(self.label_151) self.erosion_classes_lineEdit = QtWidgets.QLineEdit(self.tab_erosion) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.erosion_classes_lineEdit.sizePolicy().hasHeightForWidth()) self.erosion_classes_lineEdit.setSizePolicy(sizePolicy) self.erosion_classes_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.erosion_classes_lineEdit.setText("") self.erosion_classes_lineEdit.setMaxLength(10000) self.erosion_classes_lineEdit.setObjectName("erosion_classes_lineEdit") self.horizontalLayout_15.addWidget(self.erosion_classes_lineEdit) self.gridLayout_204.addLayout(self.horizontalLayout_15, 1, 0, 1, 3) self.label_175 = QtWidgets.QLabel(self.tab_erosion) self.label_175.setStyleSheet("background-color : #656565; color : white") self.label_175.setFrameShape(QtWidgets.QFrame.Panel) self.label_175.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_175.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_175.setObjectName("label_175") self.gridLayout_204.addWidget(self.label_175, 4, 0, 1, 3) self.class_erosion_toolButton = QtWidgets.QToolButton(self.tab_erosion) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_erosion_toolButton.setFont(font) self.class_erosion_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_erosion_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.class_erosion_toolButton.setIcon(icon64) self.class_erosion_toolButton.setIconSize(QtCore.QSize(34, 34)) self.class_erosion_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_erosion_toolButton.setObjectName("class_erosion_toolButton") self.gridLayout_204.addWidget(self.class_erosion_toolButton, 5, 2, 1, 1) self.classification_erosion = QtWidgets.QToolButton(self.tab_erosion) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_erosion.setFont(font) self.classification_erosion.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_erosion.setStyleSheet("margin: 0px;padding: 0px;") self.classification_erosion.setIcon(icon48) self.classification_erosion.setIconSize(QtCore.QSize(34, 34)) self.classification_erosion.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_erosion.setObjectName("classification_erosion") self.gridLayout_204.addWidget(self.classification_erosion, 5, 1, 1, 1) self.gridLayout_205.addLayout(self.gridLayout_204, 1, 0, 1, 1) self.tabWidget_2.addTab(self.tab_erosion, "") self.tab_dilation = QtWidgets.QWidget() self.tab_dilation.setObjectName("tab_dilation") self.gridLayout_207 = QtWidgets.QGridLayout(self.tab_dilation) self.gridLayout_207.setObjectName("gridLayout_207") self.horizontalLayout_45 = QtWidgets.QHBoxLayout() self.horizontalLayout_45.setObjectName("horizontalLayout_45") self.label_204 = QtWidgets.QLabel(self.tab_dilation) self.label_204.setStyleSheet("background-color : #656565; color : white") self.label_204.setFrameShape(QtWidgets.QFrame.Panel) self.label_204.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_204.setObjectName("label_204") self.horizontalLayout_45.addWidget(self.label_204) self.gridLayout_207.addLayout(self.horizontalLayout_45, 0, 0, 1, 1) self.gridLayout_206 = QtWidgets.QGridLayout() self.gridLayout_206.setObjectName("gridLayout_206") spacerItem140 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_206.addItem(spacerItem140, 3, 2, 1, 1) spacerItem141 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_206.addItem(spacerItem141, 5, 0, 1, 1) self.horizontalLayout_16 = QtWidgets.QHBoxLayout() self.horizontalLayout_16.setObjectName("horizontalLayout_16") self.label_152 = QtWidgets.QLabel(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_152.sizePolicy().hasHeightForWidth()) self.label_152.setSizePolicy(sizePolicy) self.label_152.setMinimumSize(QtCore.QSize(229, 0)) self.label_152.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_152.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_152.setObjectName("label_152") self.horizontalLayout_16.addWidget(self.label_152) self.dilation_raster_name_combo = QtWidgets.QComboBox(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.dilation_raster_name_combo.sizePolicy().hasHeightForWidth()) self.dilation_raster_name_combo.setSizePolicy(sizePolicy) self.dilation_raster_name_combo.setObjectName("dilation_raster_name_combo") self.horizontalLayout_16.addWidget(self.dilation_raster_name_combo) self.toolButton_reload_19 = QtWidgets.QToolButton(self.tab_dilation) self.toolButton_reload_19.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_19.setIcon(icon55) self.toolButton_reload_19.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_19.setObjectName("toolButton_reload_19") self.horizontalLayout_16.addWidget(self.toolButton_reload_19) self.gridLayout_206.addLayout(self.horizontalLayout_16, 0, 0, 1, 3) self.horizontalLayout_17 = QtWidgets.QHBoxLayout() self.horizontalLayout_17.setObjectName("horizontalLayout_17") self.label_153 = QtWidgets.QLabel(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_153.sizePolicy().hasHeightForWidth()) self.label_153.setSizePolicy(sizePolicy) self.label_153.setMinimumSize(QtCore.QSize(229, 0)) self.label_153.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_153.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_153.setObjectName("label_153") self.horizontalLayout_17.addWidget(self.label_153) self.dilation_threshold_spinBox = QtWidgets.QSpinBox(self.tab_dilation) self.dilation_threshold_spinBox.setMinimum(1) self.dilation_threshold_spinBox.setMaximum(1000) self.dilation_threshold_spinBox.setProperty("value", 1) self.dilation_threshold_spinBox.setObjectName("dilation_threshold_spinBox") self.horizontalLayout_17.addWidget(self.dilation_threshold_spinBox) self.circular_structure_checkBox_2 = QtWidgets.QCheckBox(self.tab_dilation) self.circular_structure_checkBox_2.setObjectName("circular_structure_checkBox_2") self.horizontalLayout_17.addWidget(self.circular_structure_checkBox_2) spacerItem142 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_17.addItem(spacerItem142) self.gridLayout_206.addLayout(self.horizontalLayout_17, 2, 0, 1, 3) self.horizontalLayout_18 = QtWidgets.QHBoxLayout() self.horizontalLayout_18.setObjectName("horizontalLayout_18") self.label_155 = QtWidgets.QLabel(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_155.sizePolicy().hasHeightForWidth()) self.label_155.setSizePolicy(sizePolicy) self.label_155.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_155.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_155.setObjectName("label_155") self.horizontalLayout_18.addWidget(self.label_155) self.dilation_classes_lineEdit = QtWidgets.QLineEdit(self.tab_dilation) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.dilation_classes_lineEdit.sizePolicy().hasHeightForWidth()) self.dilation_classes_lineEdit.setSizePolicy(sizePolicy) self.dilation_classes_lineEdit.setMinimumSize(QtCore.QSize(400, 26)) self.dilation_classes_lineEdit.setText("") self.dilation_classes_lineEdit.setMaxLength(10000) self.dilation_classes_lineEdit.setObjectName("dilation_classes_lineEdit") self.horizontalLayout_18.addWidget(self.dilation_classes_lineEdit) self.gridLayout_206.addLayout(self.horizontalLayout_18, 1, 0, 1, 3) self.label_176 = QtWidgets.QLabel(self.tab_dilation) self.label_176.setStyleSheet("background-color : #656565; color : white") self.label_176.setFrameShape(QtWidgets.QFrame.Panel) self.label_176.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_176.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_176.setObjectName("label_176") self.gridLayout_206.addWidget(self.label_176, 4, 0, 1, 3) self.class_dilation_toolButton = QtWidgets.QToolButton(self.tab_dilation) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.class_dilation_toolButton.setFont(font) self.class_dilation_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.class_dilation_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.class_dilation_toolButton.setIcon(icon64) self.class_dilation_toolButton.setIconSize(QtCore.QSize(34, 34)) self.class_dilation_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.class_dilation_toolButton.setObjectName("class_dilation_toolButton") self.gridLayout_206.addWidget(self.class_dilation_toolButton, 5, 2, 1, 1) self.classification_dilation = QtWidgets.QToolButton(self.tab_dilation) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.classification_dilation.setFont(font) self.classification_dilation.setLayoutDirection(QtCore.Qt.RightToLeft) self.classification_dilation.setStyleSheet("margin: 0px;padding: 0px;") self.classification_dilation.setIcon(icon48) self.classification_dilation.setIconSize(QtCore.QSize(34, 34)) self.classification_dilation.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.classification_dilation.setObjectName("classification_dilation") self.gridLayout_206.addWidget(self.classification_dilation, 5, 1, 1, 1) self.gridLayout_207.addLayout(self.gridLayout_206, 1, 0, 1, 1) self.tabWidget_2.addTab(self.tab_dilation, "") self.tab_zonal_stats_rasters = QtWidgets.QWidget() self.tab_zonal_stats_rasters.setObjectName("tab_zonal_stats_rasters") self.gridLayout_281 = QtWidgets.QGridLayout(self.tab_zonal_stats_rasters) self.gridLayout_281.setObjectName("gridLayout_281") self.gridLayout_87 = QtWidgets.QGridLayout() self.gridLayout_87.setObjectName("gridLayout_87") self.horizontalLayout_50 = QtWidgets.QHBoxLayout() self.horizontalLayout_50.setObjectName("horizontalLayout_50") self.label_212 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_212.setStyleSheet("background-color : #656565; color : white") self.label_212.setFrameShape(QtWidgets.QFrame.Panel) self.label_212.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_212.setObjectName("label_212") self.horizontalLayout_50.addWidget(self.label_212) self.gridLayout_87.addLayout(self.horizontalLayout_50, 0, 0, 1, 1) self.horizontalLayout_51 = QtWidgets.QHBoxLayout() self.horizontalLayout_51.setObjectName("horizontalLayout_51") self.label_77 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_77.sizePolicy().hasHeightForWidth()) self.label_77.setSizePolicy(sizePolicy) self.label_77.setMinimumSize(QtCore.QSize(229, 0)) self.label_77.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_77.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_77.setObjectName("label_77") self.horizontalLayout_51.addWidget(self.label_77) self.classification_name_combo_5 = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.classification_name_combo_5.sizePolicy().hasHeightForWidth()) self.classification_name_combo_5.setSizePolicy(sizePolicy) self.classification_name_combo_5.setObjectName("classification_name_combo_5") self.horizontalLayout_51.addWidget(self.classification_name_combo_5) self.toolButton_reload_24 = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) self.toolButton_reload_24.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_reload_24.setIcon(icon55) self.toolButton_reload_24.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_24.setObjectName("toolButton_reload_24") self.horizontalLayout_51.addWidget(self.toolButton_reload_24) self.gridLayout_87.addLayout(self.horizontalLayout_51, 1, 0, 1, 1) self.horizontalLayout_52 = QtWidgets.QHBoxLayout() self.horizontalLayout_52.setObjectName("horizontalLayout_52") self.nodata_checkBox_10 = QtWidgets.QCheckBox(self.tab_zonal_stats_rasters) self.nodata_checkBox_10.setObjectName("nodata_checkBox_10") self.horizontalLayout_52.addWidget(self.nodata_checkBox_10) self.nodata_spinBox_12 = QtWidgets.QSpinBox(self.tab_zonal_stats_rasters) self.nodata_spinBox_12.setMinimum(-2147483647) self.nodata_spinBox_12.setMaximum(2147483647) self.nodata_spinBox_12.setObjectName("nodata_spinBox_12") self.horizontalLayout_52.addWidget(self.nodata_spinBox_12) spacerItem143 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_52.addItem(spacerItem143) self.gridLayout_87.addLayout(self.horizontalLayout_52, 2, 0, 1, 1) self.gridLayout_281.addLayout(self.gridLayout_87, 0, 0, 1, 1) self.gridLayout_91 = QtWidgets.QGridLayout() self.gridLayout_91.setObjectName("gridLayout_91") self.class_field_comboBox_4 = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.class_field_comboBox_4.sizePolicy().hasHeightForWidth()) self.class_field_comboBox_4.setSizePolicy(sizePolicy) self.class_field_comboBox_4.setObjectName("class_field_comboBox_4") self.gridLayout_91.addWidget(self.class_field_comboBox_4, 1, 2, 1, 1) self.label_214 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_214.sizePolicy().hasHeightForWidth()) self.label_214.setSizePolicy(sizePolicy) self.label_214.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_214.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_214.setObjectName("label_214") self.gridLayout_91.addWidget(self.label_214, 0, 0, 1, 1) self.buttonReload_shape_6 = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) self.buttonReload_shape_6.setStyleSheet("margin: 0px;padding: 0px;") self.buttonReload_shape_6.setIcon(icon55) self.buttonReload_shape_6.setIconSize(QtCore.QSize(22, 22)) self.buttonReload_shape_6.setObjectName("buttonReload_shape_6") self.gridLayout_91.addWidget(self.buttonReload_shape_6, 0, 3, 1, 1) self.label_213 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_213.sizePolicy().hasHeightForWidth()) self.label_213.setSizePolicy(sizePolicy) self.label_213.setMinimumSize(QtCore.QSize(6, 0)) self.label_213.setMaximumSize(QtCore.QSize(100, 200)) self.label_213.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_213.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_213.setObjectName("label_213") self.gridLayout_91.addWidget(self.label_213, 1, 1, 1, 1) self.reference_name_combo_3 = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.reference_name_combo_3.sizePolicy().hasHeightForWidth()) self.reference_name_combo_3.setSizePolicy(sizePolicy) self.reference_name_combo_3.setObjectName("reference_name_combo_3") self.gridLayout_91.addWidget(self.reference_name_combo_3, 0, 1, 1, 2) self.gridLayout_281.addLayout(self.gridLayout_91, 1, 0, 1, 1) self.gridLayout_131 = QtWidgets.QGridLayout() self.gridLayout_131.setObjectName("gridLayout_131") self.statistic_lineEdit = QtWidgets.QLineEdit(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_lineEdit.sizePolicy().hasHeightForWidth()) self.statistic_lineEdit.setSizePolicy(sizePolicy) self.statistic_lineEdit.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_lineEdit.setText("") self.statistic_lineEdit.setMaxLength(10000) self.statistic_lineEdit.setObjectName("statistic_lineEdit") self.gridLayout_131.addWidget(self.statistic_lineEdit, 1, 2, 1, 1) self.statistic_name_combobox = QtWidgets.QComboBox(self.tab_zonal_stats_rasters) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.statistic_name_combobox.sizePolicy().hasHeightForWidth()) self.statistic_name_combobox.setSizePolicy(sizePolicy) self.statistic_name_combobox.setMaximumSize(QtCore.QSize(200, 16777215)) self.statistic_name_combobox.setObjectName("statistic_name_combobox") self.gridLayout_131.addWidget(self.statistic_name_combobox, 1, 1, 1, 1) self.label_232 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_232.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_232.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_232.setObjectName("label_232") self.gridLayout_131.addWidget(self.label_232, 1, 0, 1, 1) spacerItem144 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_131.addItem(spacerItem144, 1, 3, 1, 1) self.label_216 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_216.setStyleSheet("background-color : #656565; color : white") self.label_216.setFrameShape(QtWidgets.QFrame.Panel) self.label_216.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_216.setObjectName("label_216") self.gridLayout_131.addWidget(self.label_216, 0, 0, 1, 4) self.gridLayout_281.addLayout(self.gridLayout_131, 2, 0, 1, 1) self.gridLayout_128 = QtWidgets.QGridLayout() self.gridLayout_128.setObjectName("gridLayout_128") self.zonal_stat_raster_toolButton = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.zonal_stat_raster_toolButton.setFont(font) self.zonal_stat_raster_toolButton.setLayoutDirection(QtCore.Qt.RightToLeft) self.zonal_stat_raster_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.zonal_stat_raster_toolButton.setIcon(icon64) self.zonal_stat_raster_toolButton.setIconSize(QtCore.QSize(34, 34)) self.zonal_stat_raster_toolButton.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.zonal_stat_raster_toolButton.setObjectName("zonal_stat_raster_toolButton") self.gridLayout_128.addWidget(self.zonal_stat_raster_toolButton, 2, 2, 1, 1) self.label_215 = QtWidgets.QLabel(self.tab_zonal_stats_rasters) self.label_215.setStyleSheet("background-color : #656565; color : white") self.label_215.setFrameShape(QtWidgets.QFrame.Panel) self.label_215.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_215.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_215.setObjectName("label_215") self.gridLayout_128.addWidget(self.label_215, 1, 0, 1, 3) spacerItem145 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_128.addItem(spacerItem145, 2, 0, 1, 1) spacerItem146 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_128.addItem(spacerItem146, 0, 0, 1, 1) self.zonal_stat_raster = QtWidgets.QToolButton(self.tab_zonal_stats_rasters) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.zonal_stat_raster.setFont(font) self.zonal_stat_raster.setLayoutDirection(QtCore.Qt.RightToLeft) self.zonal_stat_raster.setStyleSheet("margin: 0px;padding: 0px;") self.zonal_stat_raster.setIcon(icon48) self.zonal_stat_raster.setIconSize(QtCore.QSize(34, 34)) self.zonal_stat_raster.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.zonal_stat_raster.setObjectName("zonal_stat_raster") self.gridLayout_128.addWidget(self.zonal_stat_raster, 2, 1, 1, 1) self.gridLayout_281.addLayout(self.gridLayout_128, 3, 0, 1, 1) self.tabWidget_2.addTab(self.tab_zonal_stats_rasters, "") self.gridLayout_552.addWidget(self.tabWidget_2, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_postProcessing, "") self.tab_band_calc = QtWidgets.QWidget() self.tab_band_calc.setObjectName("tab_band_calc") self.gridLayout_303 = QtWidgets.QGridLayout(self.tab_band_calc) self.gridLayout_303.setObjectName("gridLayout_303") self.splitter_band_calc = QtWidgets.QSplitter(self.tab_band_calc) self.splitter_band_calc.setOrientation(QtCore.Qt.Vertical) self.splitter_band_calc.setChildrenCollapsible(False) self.splitter_band_calc.setObjectName("splitter_band_calc") self.widget_2 = QtWidgets.QWidget(self.splitter_band_calc) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_2.sizePolicy().hasHeightForWidth()) self.widget_2.setSizePolicy(sizePolicy) self.widget_2.setMinimumSize(QtCore.QSize(0, 150)) self.widget_2.setObjectName("widget_2") self.gridLayout_126 = QtWidgets.QGridLayout(self.widget_2) self.gridLayout_126.setContentsMargins(1, 1, 1, 1) self.gridLayout_126.setObjectName("gridLayout_126") self.gridLayout_86 = QtWidgets.QGridLayout() self.gridLayout_86.setObjectName("gridLayout_86") self.gridLayout_171 = QtWidgets.QGridLayout() self.gridLayout_171.setObjectName("gridLayout_171") self.toolButton_reload_13 = QtWidgets.QToolButton(self.widget_2) self.toolButton_reload_13.setStyleSheet("margin: 0px;padding: 0px") self.toolButton_reload_13.setIcon(icon55) self.toolButton_reload_13.setIconSize(QtCore.QSize(22, 22)) self.toolButton_reload_13.setObjectName("toolButton_reload_13") self.gridLayout_171.addWidget(self.toolButton_reload_13, 0, 0, 1, 1) self.gridLayout_86.addLayout(self.gridLayout_171, 1, 1, 2, 1) self.tableWidget_band_calc = QtWidgets.QTableWidget(self.widget_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.tableWidget_band_calc.sizePolicy().hasHeightForWidth()) self.tableWidget_band_calc.setSizePolicy(sizePolicy) self.tableWidget_band_calc.setFrameShape(QtWidgets.QFrame.WinPanel) self.tableWidget_band_calc.setFrameShadow(QtWidgets.QFrame.Sunken) self.tableWidget_band_calc.setAlternatingRowColors(True) self.tableWidget_band_calc.setSelectionMode(QtWidgets.QAbstractItemView.NoSelection) self.tableWidget_band_calc.setSelectionBehavior(QtWidgets.QAbstractItemView.SelectRows) self.tableWidget_band_calc.setColumnCount(2) self.tableWidget_band_calc.setObjectName("tableWidget_band_calc") self.tableWidget_band_calc.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.tableWidget_band_calc.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.tableWidget_band_calc.setHorizontalHeaderItem(1, item) self.tableWidget_band_calc.horizontalHeader().setDefaultSectionSize(200) self.tableWidget_band_calc.horizontalHeader().setStretchLastSection(True) self.gridLayout_86.addWidget(self.tableWidget_band_calc, 1, 0, 2, 1) self.gridLayout_85 = QtWidgets.QGridLayout() self.gridLayout_85.setObjectName("gridLayout_85") self.bandcalc_filter_lineEdit = QtWidgets.QLineEdit(self.widget_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.bandcalc_filter_lineEdit.sizePolicy().hasHeightForWidth()) self.bandcalc_filter_lineEdit.setSizePolicy(sizePolicy) self.bandcalc_filter_lineEdit.setObjectName("bandcalc_filter_lineEdit") self.gridLayout_85.addWidget(self.bandcalc_filter_lineEdit, 0, 1, 1, 1) self.label_71 = QtWidgets.QLabel(self.widget_2) self.label_71.setStyleSheet("background-color : #656565; color : white") self.label_71.setFrameShape(QtWidgets.QFrame.Panel) self.label_71.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_71.setObjectName("label_71") self.gridLayout_85.addWidget(self.label_71, 0, 0, 1, 1) self.gridLayout_86.addLayout(self.gridLayout_85, 0, 0, 1, 2) self.gridLayout_126.addLayout(self.gridLayout_86, 0, 0, 1, 1) self.widget_3 = QtWidgets.QWidget(self.splitter_band_calc) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_3.sizePolicy().hasHeightForWidth()) self.widget_3.setSizePolicy(sizePolicy) self.widget_3.setMinimumSize(QtCore.QSize(0, 250)) self.widget_3.setObjectName("widget_3") self.gridLayout_40 = QtWidgets.QGridLayout(self.widget_3) self.gridLayout_40.setContentsMargins(0, 0, 0, 0) self.gridLayout_40.setObjectName("gridLayout_40") self.band_calc_tabWidget = QtWidgets.QTabWidget(self.widget_3) self.band_calc_tabWidget.setStyleSheet("QTabBar::tab {\n" "padding: 10px;\n" "min-height: 18px;\n" "}") self.band_calc_tabWidget.setTabPosition(QtWidgets.QTabWidget.North) self.band_calc_tabWidget.setObjectName("band_calc_tabWidget") self.tab_expression = QtWidgets.QWidget() self.tab_expression.setObjectName("tab_expression") self.gridLayout_2 = QtWidgets.QGridLayout(self.tab_expression) self.gridLayout_2.setObjectName("gridLayout_2") self.splitter_2 = QtWidgets.QSplitter(self.tab_expression) self.splitter_2.setOrientation(QtCore.Qt.Horizontal) self.splitter_2.setChildrenCollapsible(False) self.splitter_2.setObjectName("splitter_2") self.plainTextEdit_calc = QtWidgets.QPlainTextEdit(self.splitter_2) self.plainTextEdit_calc.setMinimumSize(QtCore.QSize(100, 0)) self.plainTextEdit_calc.setMaximumSize(QtCore.QSize(16777215, 400)) font = QtGui.QFont() font.setPointSize(11) self.plainTextEdit_calc.setFont(font) self.plainTextEdit_calc.setPlainText("") self.plainTextEdit_calc.setObjectName("plainTextEdit_calc") self.frame = QtWidgets.QFrame(self.splitter_2) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.frame.sizePolicy().hasHeightForWidth()) self.frame.setSizePolicy(sizePolicy) self.frame.setMinimumSize(QtCore.QSize(100, 0)) self.frame.setMaximumSize(QtCore.QSize(300, 16777215)) self.frame.setFrameShape(QtWidgets.QFrame.StyledPanel) self.frame.setFrameShadow(QtWidgets.QFrame.Raised) self.frame.setObjectName("frame") self.gridLayout_67 = QtWidgets.QGridLayout(self.frame) self.gridLayout_67.setContentsMargins(2, 2, 2, 2) self.gridLayout_67.setObjectName("gridLayout_67") self.gridLayout_88 = QtWidgets.QGridLayout() self.gridLayout_88.setObjectName("gridLayout_88") self.gridLayout_90 = QtWidgets.QGridLayout() self.gridLayout_90.setObjectName("gridLayout_90") self.horizontalLayout_49 = QtWidgets.QHBoxLayout() self.horizontalLayout_49.setObjectName("horizontalLayout_49") self.toolButton_less = QtWidgets.QToolButton(self.frame) self.toolButton_less.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_less.setObjectName("toolButton_less") self.horizontalLayout_49.addWidget(self.toolButton_less) self.toolButton_greater = QtWidgets.QToolButton(self.frame) self.toolButton_greater.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_greater.setObjectName("toolButton_greater") self.horizontalLayout_49.addWidget(self.toolButton_greater) self.toolButton_lbracket = QtWidgets.QToolButton(self.frame) self.toolButton_lbracket.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_lbracket.setObjectName("toolButton_lbracket") self.horizontalLayout_49.addWidget(self.toolButton_lbracket) self.toolButton_rbracket = QtWidgets.QToolButton(self.frame) self.toolButton_rbracket.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_rbracket.setObjectName("toolButton_rbracket") self.horizontalLayout_49.addWidget(self.toolButton_rbracket) self.toolButton_power = QtWidgets.QToolButton(self.frame) self.toolButton_power.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_power.setObjectName("toolButton_power") self.horizontalLayout_49.addWidget(self.toolButton_power) self.toolButton_sqrt = QtWidgets.QToolButton(self.frame) self.toolButton_sqrt.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_sqrt.setObjectName("toolButton_sqrt") self.horizontalLayout_49.addWidget(self.toolButton_sqrt) self.gridLayout_90.addLayout(self.horizontalLayout_49, 1, 0, 1, 1) self.horizontalLayout_4 = QtWidgets.QHBoxLayout() self.horizontalLayout_4.setObjectName("horizontalLayout_4") self.toolButton_plus = QtWidgets.QToolButton(self.frame) self.toolButton_plus.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_plus.setObjectName("toolButton_plus") self.horizontalLayout_4.addWidget(self.toolButton_plus) self.toolButton_minus = QtWidgets.QToolButton(self.frame) self.toolButton_minus.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_minus.setObjectName("toolButton_minus") self.horizontalLayout_4.addWidget(self.toolButton_minus) self.toolButton_product = QtWidgets.QToolButton(self.frame) self.toolButton_product.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_product.setObjectName("toolButton_product") self.horizontalLayout_4.addWidget(self.toolButton_product) self.toolButton_ratio = QtWidgets.QToolButton(self.frame) self.toolButton_ratio.setMinimumSize(QtCore.QSize(25, 25)) self.toolButton_ratio.setObjectName("toolButton_ratio") self.horizontalLayout_4.addWidget(self.toolButton_ratio) self.toolButton_equal = QtWidgets.QToolButton(self.frame) self.toolButton_equal.setMinimumSize(QtCore.QSize(45, 25)) self.toolButton_equal.setObjectName("toolButton_equal") self.horizontalLayout_4.addWidget(self.toolButton_equal) self.toolButton_unequal = QtWidgets.QToolButton(self.frame) self.toolButton_unequal.setMinimumSize(QtCore.QSize(45, 25)) self.toolButton_unequal.setObjectName("toolButton_unequal") self.horizontalLayout_4.addWidget(self.toolButton_unequal) self.gridLayout_90.addLayout(self.horizontalLayout_4, 0, 0, 1, 2) self.toolButton_import_expression = QtWidgets.QToolButton(self.frame) self.toolButton_import_expression.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_import_expression.setIcon(icon65) self.toolButton_import_expression.setIconSize(QtCore.QSize(22, 22)) self.toolButton_import_expression.setObjectName("toolButton_import_expression") self.gridLayout_90.addWidget(self.toolButton_import_expression, 1, 1, 1, 1) self.gridLayout_88.addLayout(self.gridLayout_90, 0, 0, 2, 3) self.gridLayout_93 = QtWidgets.QGridLayout() self.gridLayout_93.setObjectName("gridLayout_93") self.gridLayout_38 = QtWidgets.QGridLayout() self.gridLayout_38.setObjectName("gridLayout_38") self.band_calc_function_tableWidget = QtWidgets.QTableWidget(self.frame) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.band_calc_function_tableWidget.sizePolicy().hasHeightForWidth()) self.band_calc_function_tableWidget.setSizePolicy(sizePolicy) self.band_calc_function_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.band_calc_function_tableWidget.setAlternatingRowColors(True) self.band_calc_function_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.SingleSelection) self.band_calc_function_tableWidget.setObjectName("band_calc_function_tableWidget") self.band_calc_function_tableWidget.setColumnCount(1) self.band_calc_function_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.band_calc_function_tableWidget.setHorizontalHeaderItem(0, item) self.band_calc_function_tableWidget.horizontalHeader().setStretchLastSection(True) self.band_calc_function_tableWidget.verticalHeader().setVisible(False) self.gridLayout_38.addWidget(self.band_calc_function_tableWidget, 0, 0, 1, 1) self.gridLayout_93.addLayout(self.gridLayout_38, 0, 0, 1, 2) self.gridLayout_88.addLayout(self.gridLayout_93, 3, 0, 1, 3) self.gridLayout_67.addLayout(self.gridLayout_88, 0, 0, 1, 1) self.gridLayout_2.addWidget(self.splitter_2, 0, 0, 1, 1) icon82 = QtGui.QIcon() icon82.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandcalc_expression.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.band_calc_tabWidget.addTab(self.tab_expression, icon82, "") self.tab_decision_rules = QtWidgets.QWidget() self.tab_decision_rules.setObjectName("tab_decision_rules") self.gridLayout_89 = QtWidgets.QGridLayout(self.tab_decision_rules) self.gridLayout_89.setObjectName("gridLayout_89") self.gridLayout_215 = QtWidgets.QGridLayout() self.gridLayout_215.setObjectName("gridLayout_215") self.decision_rules_tableWidget = QtWidgets.QTableWidget(self.tab_decision_rules) font = QtGui.QFont() font.setPointSize(10) self.decision_rules_tableWidget.setFont(font) self.decision_rules_tableWidget.setObjectName("decision_rules_tableWidget") self.decision_rules_tableWidget.setColumnCount(2) self.decision_rules_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.decision_rules_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.decision_rules_tableWidget.setHorizontalHeaderItem(1, item) self.decision_rules_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_215.addWidget(self.decision_rules_tableWidget, 0, 0, 1, 1) self.gridLayout_89.addLayout(self.gridLayout_215, 0, 0, 1, 1) self.gridLayout_220 = QtWidgets.QGridLayout() self.gridLayout_220.setObjectName("gridLayout_220") spacerItem147 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_220.addItem(spacerItem147, 6, 0, 1, 1) self.remove_rule_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.remove_rule_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.remove_rule_toolButton.setIcon(icon58) self.remove_rule_toolButton.setIconSize(QtCore.QSize(22, 22)) self.remove_rule_toolButton.setObjectName("remove_rule_toolButton") self.gridLayout_220.addWidget(self.remove_rule_toolButton, 4, 0, 1, 1) self.move_up_toolButton_2 = QtWidgets.QToolButton(self.tab_decision_rules) self.move_up_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.move_up_toolButton_2.setIcon(icon61) self.move_up_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.move_up_toolButton_2.setObjectName("move_up_toolButton_2") self.gridLayout_220.addWidget(self.move_up_toolButton_2, 0, 0, 1, 1) self.import_rules_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.import_rules_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_rules_toolButton.setIcon(icon54) self.import_rules_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_rules_toolButton.setObjectName("import_rules_toolButton") self.gridLayout_220.addWidget(self.import_rules_toolButton, 7, 0, 1, 1) self.clear_rules_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.clear_rules_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_rules_toolButton.setIcon(icon59) self.clear_rules_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_rules_toolButton.setObjectName("clear_rules_toolButton") self.gridLayout_220.addWidget(self.clear_rules_toolButton, 5, 0, 1, 1) spacerItem148 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_220.addItem(spacerItem148, 9, 0, 1, 1) self.add_rule_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.add_rule_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.add_rule_toolButton.setIcon(icon66) self.add_rule_toolButton.setIconSize(QtCore.QSize(22, 22)) self.add_rule_toolButton.setObjectName("add_rule_toolButton") self.gridLayout_220.addWidget(self.add_rule_toolButton, 3, 0, 1, 1) spacerItem149 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_220.addItem(spacerItem149, 2, 0, 1, 1) self.move_down_toolButton_2 = QtWidgets.QToolButton(self.tab_decision_rules) self.move_down_toolButton_2.setStyleSheet("margin: 0px;padding: 0px;") self.move_down_toolButton_2.setIcon(icon62) self.move_down_toolButton_2.setIconSize(QtCore.QSize(22, 22)) self.move_down_toolButton_2.setObjectName("move_down_toolButton_2") self.gridLayout_220.addWidget(self.move_down_toolButton_2, 1, 0, 1, 1) self.export_rules_toolButton = QtWidgets.QToolButton(self.tab_decision_rules) self.export_rules_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_rules_toolButton.setIcon(icon53) self.export_rules_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_rules_toolButton.setObjectName("export_rules_toolButton") self.gridLayout_220.addWidget(self.export_rules_toolButton, 8, 0, 1, 1) self.gridLayout_89.addLayout(self.gridLayout_220, 0, 1, 1, 1) icon83 = QtGui.QIcon() icon83.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_bandcalc_rules.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.band_calc_tabWidget.addTab(self.tab_decision_rules, icon83, "") self.gridLayout_40.addWidget(self.band_calc_tabWidget, 0, 0, 1, 1) self.horizontalLayout_73 = QtWidgets.QHBoxLayout() self.horizontalLayout_73.setObjectName("horizontalLayout_73") self.nodata_as_value_checkBox = QtWidgets.QCheckBox(self.widget_3) self.nodata_as_value_checkBox.setObjectName("nodata_as_value_checkBox") self.horizontalLayout_73.addWidget(self.nodata_as_value_checkBox) self.nodata_checkBox_3 = QtWidgets.QCheckBox(self.widget_3) self.nodata_checkBox_3.setObjectName("nodata_checkBox_3") self.horizontalLayout_73.addWidget(self.nodata_checkBox_3) self.nodata_spinBox_13 = QtWidgets.QSpinBox(self.widget_3) self.nodata_spinBox_13.setMinimum(-2147483647) self.nodata_spinBox_13.setMaximum(2147483647) self.nodata_spinBox_13.setObjectName("nodata_spinBox_13") self.horizontalLayout_73.addWidget(self.nodata_spinBox_13) self.label_4 = QtWidgets.QLabel(self.widget_3) self.label_4.setObjectName("label_4") self.horizontalLayout_73.addWidget(self.label_4) self.calc_type_combo = QtWidgets.QComboBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.calc_type_combo.sizePolicy().hasHeightForWidth()) self.calc_type_combo.setSizePolicy(sizePolicy) self.calc_type_combo.setObjectName("calc_type_combo") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.calc_type_combo.addItem("") self.horizontalLayout_73.addWidget(self.calc_type_combo) spacerItem150 = QtWidgets.QSpacerItem(214, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_73.addItem(spacerItem150) self.label_83 = QtWidgets.QLabel(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_83.sizePolicy().hasHeightForWidth()) self.label_83.setSizePolicy(sizePolicy) self.label_83.setMinimumSize(QtCore.QSize(40, 0)) self.label_83.setMaximumSize(QtCore.QSize(120, 16777215)) self.label_83.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_83.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_83.setObjectName("label_83") self.horizontalLayout_73.addWidget(self.label_83) self.intersection_checkBox = QtWidgets.QCheckBox(self.widget_3) self.intersection_checkBox.setChecked(True) self.intersection_checkBox.setObjectName("intersection_checkBox") self.horizontalLayout_73.addWidget(self.intersection_checkBox) self.extent_checkBox = QtWidgets.QCheckBox(self.widget_3) self.extent_checkBox.setObjectName("extent_checkBox") self.horizontalLayout_73.addWidget(self.extent_checkBox) self.raster_extent_combo = QtWidgets.QComboBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_extent_combo.sizePolicy().hasHeightForWidth()) self.raster_extent_combo.setSizePolicy(sizePolicy) self.raster_extent_combo.setObjectName("raster_extent_combo") self.horizontalLayout_73.addWidget(self.raster_extent_combo) self.align_radioButton = QtWidgets.QRadioButton(self.widget_3) self.align_radioButton.setChecked(True) self.align_radioButton.setObjectName("align_radioButton") self.horizontalLayout_73.addWidget(self.align_radioButton) self.gridLayout_40.addLayout(self.horizontalLayout_73, 1, 0, 1, 1) self.label_84 = QtWidgets.QLabel(self.widget_3) self.label_84.setStyleSheet("background-color : #656565; color : white") self.label_84.setFrameShape(QtWidgets.QFrame.Panel) self.label_84.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_84.setObjectName("label_84") self.gridLayout_40.addWidget(self.label_84, 2, 0, 1, 1) self.horizontalLayout_60 = QtWidgets.QHBoxLayout() self.horizontalLayout_60.setObjectName("horizontalLayout_60") self.raster_type_combo = QtWidgets.QComboBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(1) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.raster_type_combo.sizePolicy().hasHeightForWidth()) self.raster_type_combo.setSizePolicy(sizePolicy) self.raster_type_combo.setObjectName("raster_type_combo") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.raster_type_combo.addItem("") self.horizontalLayout_60.addWidget(self.raster_type_combo) self.label_268 = QtWidgets.QLabel(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_268.sizePolicy().hasHeightForWidth()) self.label_268.setSizePolicy(sizePolicy) self.label_268.setMinimumSize(QtCore.QSize(50, 0)) self.label_268.setMaximumSize(QtCore.QSize(130, 16777215)) self.label_268.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_268.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_268.setObjectName("label_268") self.horizontalLayout_60.addWidget(self.label_268) self.nodata_spinBox_4 = QtWidgets.QSpinBox(self.widget_3) self.nodata_spinBox_4.setMinimum(-2147483647) self.nodata_spinBox_4.setMaximum(2147483647) self.nodata_spinBox_4.setProperty("value", -32768) self.nodata_spinBox_4.setObjectName("nodata_spinBox_4") self.horizontalLayout_60.addWidget(self.nodata_spinBox_4) self.nodata_mask_checkBox = QtWidgets.QCheckBox(self.widget_3) self.nodata_mask_checkBox.setChecked(True) self.nodata_mask_checkBox.setObjectName("nodata_mask_checkBox") self.horizontalLayout_60.addWidget(self.nodata_mask_checkBox) self.set_scale_checkBox = QtWidgets.QCheckBox(self.widget_3) self.set_scale_checkBox.setObjectName("set_scale_checkBox") self.horizontalLayout_60.addWidget(self.set_scale_checkBox) self.scale_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.scale_doubleSpinBox.sizePolicy().hasHeightForWidth()) self.scale_doubleSpinBox.setSizePolicy(sizePolicy) self.scale_doubleSpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.scale_doubleSpinBox.setDecimals(7) self.scale_doubleSpinBox.setMinimum(-1e+34) self.scale_doubleSpinBox.setMaximum(1e+34) self.scale_doubleSpinBox.setProperty("value", 1.0) self.scale_doubleSpinBox.setObjectName("scale_doubleSpinBox") self.horizontalLayout_60.addWidget(self.scale_doubleSpinBox) self.set_offset_checkBox = QtWidgets.QCheckBox(self.widget_3) self.set_offset_checkBox.setObjectName("set_offset_checkBox") self.horizontalLayout_60.addWidget(self.set_offset_checkBox) self.offset_doubleSpinBox = QtWidgets.QDoubleSpinBox(self.widget_3) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.offset_doubleSpinBox.sizePolicy().hasHeightForWidth()) self.offset_doubleSpinBox.setSizePolicy(sizePolicy) self.offset_doubleSpinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.offset_doubleSpinBox.setDecimals(7) self.offset_doubleSpinBox.setMinimum(-1e+34) self.offset_doubleSpinBox.setMaximum(1e+34) self.offset_doubleSpinBox.setProperty("value", 0.0) self.offset_doubleSpinBox.setObjectName("offset_doubleSpinBox") self.horizontalLayout_60.addWidget(self.offset_doubleSpinBox) spacerItem151 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_60.addItem(spacerItem151) self.band_calc = QtWidgets.QToolButton(self.widget_3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.band_calc.setFont(font) self.band_calc.setLayoutDirection(QtCore.Qt.RightToLeft) self.band_calc.setStyleSheet("margin: 0px;padding: 0px;") self.band_calc.setIcon(icon48) self.band_calc.setIconSize(QtCore.QSize(34, 34)) self.band_calc.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.band_calc.setObjectName("band_calc") self.horizontalLayout_60.addWidget(self.band_calc) self.toolButton_calculate = QtWidgets.QToolButton(self.widget_3) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.toolButton_calculate.setFont(font) self.toolButton_calculate.setLayoutDirection(QtCore.Qt.RightToLeft) self.toolButton_calculate.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_calculate.setIcon(icon64) self.toolButton_calculate.setIconSize(QtCore.QSize(34, 34)) self.toolButton_calculate.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.toolButton_calculate.setObjectName("toolButton_calculate") self.horizontalLayout_60.addWidget(self.toolButton_calculate) self.gridLayout_40.addLayout(self.horizontalLayout_60, 3, 0, 1, 1) self.gridLayout_303.addWidget(self.splitter_band_calc, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_band_calc, "") self.tab_batch = QtWidgets.QWidget() self.tab_batch.setObjectName("tab_batch") self.verticalLayout_5 = QtWidgets.QVBoxLayout(self.tab_batch) self.verticalLayout_5.setObjectName("verticalLayout_5") self.verticalLayout_3 = QtWidgets.QVBoxLayout() self.verticalLayout_3.setObjectName("verticalLayout_3") self.label_73 = QtWidgets.QLabel(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_73.sizePolicy().hasHeightForWidth()) self.label_73.setSizePolicy(sizePolicy) self.label_73.setStyleSheet("background-color : #656565; color : white") self.label_73.setFrameShape(QtWidgets.QFrame.Panel) self.label_73.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_73.setObjectName("label_73") self.verticalLayout_3.addWidget(self.label_73) self.splitter_batch = QtWidgets.QSplitter(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.MinimumExpanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.splitter_batch.sizePolicy().hasHeightForWidth()) self.splitter_batch.setSizePolicy(sizePolicy) self.splitter_batch.setMinimumSize(QtCore.QSize(100, 0)) self.splitter_batch.setOrientation(QtCore.Qt.Horizontal) self.splitter_batch.setChildrenCollapsible(False) self.splitter_batch.setObjectName("splitter_batch") self.plainTextEdit_batch = QtWidgets.QPlainTextEdit(self.splitter_batch) self.plainTextEdit_batch.setMinimumSize(QtCore.QSize(200, 0)) font = QtGui.QFont() font.setPointSize(11) self.plainTextEdit_batch.setFont(font) self.plainTextEdit_batch.setPlainText("") self.plainTextEdit_batch.setObjectName("plainTextEdit_batch") self.widget_4 = QtWidgets.QWidget(self.splitter_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Ignored) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.widget_4.sizePolicy().hasHeightForWidth()) self.widget_4.setSizePolicy(sizePolicy) self.widget_4.setMinimumSize(QtCore.QSize(100, 400)) self.widget_4.setMaximumSize(QtCore.QSize(250, 16777215)) self.widget_4.setObjectName("widget_4") self.gridLayout_76 = QtWidgets.QGridLayout(self.widget_4) self.gridLayout_76.setContentsMargins(1, 1, 1, 1) self.gridLayout_76.setObjectName("gridLayout_76") self.gridLayout_214 = QtWidgets.QGridLayout() self.gridLayout_214.setObjectName("gridLayout_214") self.export_batch_toolButton = QtWidgets.QToolButton(self.widget_4) self.export_batch_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.export_batch_toolButton.setIcon(icon53) self.export_batch_toolButton.setIconSize(QtCore.QSize(22, 22)) self.export_batch_toolButton.setObjectName("export_batch_toolButton") self.gridLayout_214.addWidget(self.export_batch_toolButton, 0, 2, 1, 1) self.clear_batch_toolButton = QtWidgets.QToolButton(self.widget_4) self.clear_batch_toolButton.setStyleSheet("margin: 0px;padding: 0px;") self.clear_batch_toolButton.setIcon(icon59) self.clear_batch_toolButton.setIconSize(QtCore.QSize(22, 22)) self.clear_batch_toolButton.setObjectName("clear_batch_toolButton") self.gridLayout_214.addWidget(self.clear_batch_toolButton, 0, 0, 1, 1) self.import_batch_toolButton = QtWidgets.QToolButton(self.widget_4) self.import_batch_toolButton.setStyleSheet("margin: 0px;padding: 0px") self.import_batch_toolButton.setIcon(icon54) self.import_batch_toolButton.setIconSize(QtCore.QSize(22, 22)) self.import_batch_toolButton.setObjectName("import_batch_toolButton") self.gridLayout_214.addWidget(self.import_batch_toolButton, 0, 1, 1, 1) self.gridLayout_76.addLayout(self.gridLayout_214, 1, 0, 1, 1) self.batch_tableWidget = QtWidgets.QTableWidget(self.widget_4) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.MinimumExpanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.batch_tableWidget.sizePolicy().hasHeightForWidth()) self.batch_tableWidget.setSizePolicy(sizePolicy) self.batch_tableWidget.setMaximumSize(QtCore.QSize(300, 16777215)) self.batch_tableWidget.setEditTriggers(QtWidgets.QAbstractItemView.NoEditTriggers) self.batch_tableWidget.setAlternatingRowColors(True) self.batch_tableWidget.setSelectionMode(QtWidgets.QAbstractItemView.SingleSelection) self.batch_tableWidget.setObjectName("batch_tableWidget") self.batch_tableWidget.setColumnCount(1) self.batch_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.batch_tableWidget.setHorizontalHeaderItem(0, item) self.batch_tableWidget.horizontalHeader().setStretchLastSection(True) self.batch_tableWidget.verticalHeader().setVisible(False) self.gridLayout_76.addWidget(self.batch_tableWidget, 0, 0, 1, 1) self.verticalLayout_3.addWidget(self.splitter_batch) self.batch_label = QtWidgets.QLabel(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.batch_label.sizePolicy().hasHeightForWidth()) self.batch_label.setSizePolicy(sizePolicy) self.batch_label.setText("") self.batch_label.setObjectName("batch_label") self.verticalLayout_3.addWidget(self.batch_label) self.label_177 = QtWidgets.QLabel(self.tab_batch) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Preferred, QtWidgets.QSizePolicy.Maximum) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_177.sizePolicy().hasHeightForWidth()) self.label_177.setSizePolicy(sizePolicy) self.label_177.setStyleSheet("background-color : #656565; color : white") self.label_177.setFrameShape(QtWidgets.QFrame.Panel) self.label_177.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_177.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_177.setObjectName("label_177") self.verticalLayout_3.addWidget(self.label_177) self.horizontalLayout_69 = QtWidgets.QHBoxLayout() self.horizontalLayout_69.setObjectName("horizontalLayout_69") spacerItem152 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.horizontalLayout_69.addItem(spacerItem152) self.check_batch = QtWidgets.QToolButton(self.tab_batch) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.check_batch.setFont(font) self.check_batch.setLayoutDirection(QtCore.Qt.RightToLeft) self.check_batch.setStyleSheet("margin: 0px;padding: 0px;") icon84 = QtGui.QIcon() icon84.addPixmap(QtGui.QPixmap(":/plugins/semiautomaticclassificationplugin/icons/semiautomaticclassificationplugin_batch_check.svg"), QtGui.QIcon.Normal, QtGui.QIcon.Off) self.check_batch.setIcon(icon84) self.check_batch.setIconSize(QtCore.QSize(34, 34)) self.check_batch.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.check_batch.setObjectName("check_batch") self.horizontalLayout_69.addWidget(self.check_batch) self.toolButton_run_batch = QtWidgets.QToolButton(self.tab_batch) font = QtGui.QFont() font.setBold(True) font.setWeight(75) self.toolButton_run_batch.setFont(font) self.toolButton_run_batch.setLayoutDirection(QtCore.Qt.RightToLeft) self.toolButton_run_batch.setStyleSheet("margin: 0px;padding: 0px;") self.toolButton_run_batch.setIcon(icon64) self.toolButton_run_batch.setIconSize(QtCore.QSize(34, 34)) self.toolButton_run_batch.setToolButtonStyle(QtCore.Qt.ToolButtonTextBesideIcon) self.toolButton_run_batch.setObjectName("toolButton_run_batch") self.horizontalLayout_69.addWidget(self.toolButton_run_batch) self.verticalLayout_3.addLayout(self.horizontalLayout_69) self.verticalLayout_5.addLayout(self.verticalLayout_3) self.SCP_tabs.addTab(self.tab_batch, "") self.tab_Settings = QtWidgets.QWidget() sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.tab_Settings.sizePolicy().hasHeightForWidth()) self.tab_Settings.setSizePolicy(sizePolicy) self.tab_Settings.setMinimumSize(QtCore.QSize(454, 0)) self.tab_Settings.setMaximumSize(QtCore.QSize(16777215, 16777215)) self.tab_Settings.setObjectName("tab_Settings") self.gridLayout_134 = QtWidgets.QGridLayout(self.tab_Settings) self.gridLayout_134.setObjectName("gridLayout_134") self.settings_tabWidget = QtWidgets.QTabWidget(self.tab_Settings) self.settings_tabWidget.setDocumentMode(True) self.settings_tabWidget.setObjectName("settings_tabWidget") self.tabWidgetProcessing = QtWidgets.QWidget() self.tabWidgetProcessing.setObjectName("tabWidgetProcessing") self.gridLayout_195 = QtWidgets.QGridLayout(self.tabWidgetProcessing) self.gridLayout_195.setObjectName("gridLayout_195") self.gridLayout_3 = QtWidgets.QGridLayout() self.gridLayout_3.setObjectName("gridLayout_3") self.label_28 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_28.setStyleSheet("background-color : #656565; color : white") self.label_28.setFrameShape(QtWidgets.QFrame.Panel) self.label_28.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_28.setObjectName("label_28") self.gridLayout_3.addWidget(self.label_28, 0, 0, 1, 1) self.gridLayout = QtWidgets.QGridLayout() self.gridLayout.setObjectName("gridLayout") self.RAM_spinBox = QtWidgets.QSpinBox(self.tabWidgetProcessing) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.RAM_spinBox.sizePolicy().hasHeightForWidth()) self.RAM_spinBox.setSizePolicy(sizePolicy) self.RAM_spinBox.setMinimumSize(QtCore.QSize(50, 0)) self.RAM_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.RAM_spinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.RAM_spinBox.setMinimum(128) self.RAM_spinBox.setMaximum(196608) self.RAM_spinBox.setSingleStep(10) self.RAM_spinBox.setProperty("value", 512) self.RAM_spinBox.setObjectName("RAM_spinBox") self.gridLayout.addWidget(self.RAM_spinBox, 0, 1, 1, 1) self.label_23 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_23.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_23.setObjectName("label_23") self.gridLayout.addWidget(self.label_23, 0, 0, 1, 1) self.label_56 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_56.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_56.setObjectName("label_56") self.gridLayout.addWidget(self.label_56, 1, 0, 1, 1) self.CPU_spinBox = QtWidgets.QSpinBox(self.tabWidgetProcessing) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Fixed, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.CPU_spinBox.sizePolicy().hasHeightForWidth()) self.CPU_spinBox.setSizePolicy(sizePolicy) self.CPU_spinBox.setMinimumSize(QtCore.QSize(50, 0)) self.CPU_spinBox.setMaximumSize(QtCore.QSize(100, 16777215)) self.CPU_spinBox.setAlignment(QtCore.Qt.AlignRight|QtCore.Qt.AlignTrailing|QtCore.Qt.AlignVCenter) self.CPU_spinBox.setMinimum(1) self.CPU_spinBox.setMaximum(1000) self.CPU_spinBox.setSingleStep(1) self.CPU_spinBox.setProperty("value", 1) self.CPU_spinBox.setObjectName("CPU_spinBox") self.gridLayout.addWidget(self.CPU_spinBox, 1, 1, 1, 1) self.gridLayout_3.addLayout(self.gridLayout, 1, 0, 1, 1) self.gridLayout_195.addLayout(self.gridLayout_3, 0, 0, 1, 1) self.gridLayout_237 = QtWidgets.QGridLayout() self.gridLayout_237.setObjectName("gridLayout_237") self.label_13 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_13.setFrameShape(QtWidgets.QFrame.Panel) self.label_13.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_13.setObjectName("label_13") self.gridLayout_237.addWidget(self.label_13, 1, 1, 1, 1) self.label_18 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_18.setFrameShape(QtWidgets.QFrame.Panel) self.label_18.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_18.setObjectName("label_18") self.gridLayout_237.addWidget(self.label_18, 1, 3, 1, 1) self.smtp_user_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.smtp_user_lineEdit.setObjectName("smtp_user_lineEdit") self.gridLayout_237.addWidget(self.smtp_user_lineEdit, 2, 2, 1, 1) self.smtp_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.smtp_checkBox.setChecked(True) self.smtp_checkBox.setTristate(False) self.smtp_checkBox.setObjectName("smtp_checkBox") self.gridLayout_237.addWidget(self.smtp_checkBox, 3, 1, 1, 1) self.label_117 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_117.setStyleSheet("background-color : #656565; color : white") self.label_117.setFrameShape(QtWidgets.QFrame.Panel) self.label_117.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_117.setObjectName("label_117") self.gridLayout_237.addWidget(self.label_117, 0, 0, 1, 5) self.smtp_password_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.smtp_password_lineEdit.setObjectName("smtp_password_lineEdit") self.gridLayout_237.addWidget(self.smtp_password_lineEdit, 2, 3, 1, 1) self.smtp_server_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.smtp_server_lineEdit.setObjectName("smtp_server_lineEdit") self.gridLayout_237.addWidget(self.smtp_server_lineEdit, 2, 1, 1, 1) self.label_14 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_14.setFrameShape(QtWidgets.QFrame.Panel) self.label_14.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_14.setObjectName("label_14") self.gridLayout_237.addWidget(self.label_14, 1, 2, 1, 1) self.to_email_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.to_email_lineEdit.setObjectName("to_email_lineEdit") self.gridLayout_237.addWidget(self.to_email_lineEdit, 3, 2, 1, 3) self.remeber_settings_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.remeber_settings_checkBox.setChecked(True) self.remeber_settings_checkBox.setObjectName("remeber_settings_checkBox") self.gridLayout_237.addWidget(self.remeber_settings_checkBox, 2, 4, 1, 1) self.gridLayout_195.addLayout(self.gridLayout_237, 2, 0, 1, 1) self.gridLayout_124 = QtWidgets.QGridLayout() self.gridLayout_124.setObjectName("gridLayout_124") self.reset_temp_directory_Button = QtWidgets.QToolButton(self.tabWidgetProcessing) self.reset_temp_directory_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_temp_directory_Button.setIcon(icon59) self.reset_temp_directory_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_temp_directory_Button.setObjectName("reset_temp_directory_Button") self.gridLayout_124.addWidget(self.reset_temp_directory_Button, 2, 3, 1, 1) self.temp_directory_Button = QtWidgets.QToolButton(self.tabWidgetProcessing) self.temp_directory_Button.setStyleSheet("margin: 0px;padding: 0px;") self.temp_directory_Button.setIcon(icon69) self.temp_directory_Button.setIconSize(QtCore.QSize(22, 22)) self.temp_directory_Button.setObjectName("temp_directory_Button") self.gridLayout_124.addWidget(self.temp_directory_Button, 2, 0, 1, 1) self.label_87 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_87.setStyleSheet("background-color : #656565; color : white") self.label_87.setFrameShape(QtWidgets.QFrame.Panel) self.label_87.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_87.setObjectName("label_87") self.gridLayout_124.addWidget(self.label_87, 0, 0, 1, 4) self.temp_directory_label = QtWidgets.QLabel(self.tabWidgetProcessing) self.temp_directory_label.setFrameShape(QtWidgets.QFrame.Panel) self.temp_directory_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.temp_directory_label.setText("") self.temp_directory_label.setObjectName("temp_directory_label") self.gridLayout_124.addWidget(self.temp_directory_label, 2, 1, 1, 2) self.gridLayout_195.addLayout(self.gridLayout_124, 3, 0, 1, 1) self.gridLayout_107 = QtWidgets.QGridLayout() self.gridLayout_107.setObjectName("gridLayout_107") self.verticalLayout_6 = QtWidgets.QVBoxLayout() self.verticalLayout_6.setObjectName("verticalLayout_6") self.SNAP_label = QtWidgets.QLabel(self.tabWidgetProcessing) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.SNAP_label.sizePolicy().hasHeightForWidth()) self.SNAP_label.setSizePolicy(sizePolicy) self.SNAP_label.setFrameShadow(QtWidgets.QFrame.Sunken) self.SNAP_label.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.SNAP_label.setObjectName("SNAP_label") self.verticalLayout_6.addWidget(self.SNAP_label) self.label_276 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_276.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_276.setObjectName("label_276") self.verticalLayout_6.addWidget(self.label_276) self.label_288 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_288.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_288.setObjectName("label_288") self.verticalLayout_6.addWidget(self.label_288) self.label_275 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_275.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_275.setObjectName("label_275") self.verticalLayout_6.addWidget(self.label_275) self.gridLayout_107.addLayout(self.verticalLayout_6, 1, 0, 1, 1) self.verticalLayout_7 = QtWidgets.QVBoxLayout() self.verticalLayout_7.setObjectName("verticalLayout_7") self.SNAP_GPT_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.SNAP_GPT_lineEdit.setObjectName("SNAP_GPT_lineEdit") self.verticalLayout_7.addWidget(self.SNAP_GPT_lineEdit) self.python_path_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.python_path_lineEdit.setObjectName("python_path_lineEdit") self.verticalLayout_7.addWidget(self.python_path_lineEdit) self.python_path_lineEdit_2 = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.python_path_lineEdit_2.setObjectName("python_path_lineEdit_2") self.verticalLayout_7.addWidget(self.python_path_lineEdit_2) self.gdal_path_lineEdit = QtWidgets.QLineEdit(self.tabWidgetProcessing) self.gdal_path_lineEdit.setObjectName("gdal_path_lineEdit") self.verticalLayout_7.addWidget(self.gdal_path_lineEdit) self.gridLayout_107.addLayout(self.verticalLayout_7, 1, 1, 1, 1) self.label_211 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_211.setStyleSheet("background-color : #656565; color : white") self.label_211.setFrameShape(QtWidgets.QFrame.Panel) self.label_211.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_211.setObjectName("label_211") self.gridLayout_107.addWidget(self.label_211, 0, 0, 1, 2) self.gridLayout_195.addLayout(self.gridLayout_107, 4, 0, 1, 1) self.gridLayout_30 = QtWidgets.QGridLayout() self.gridLayout_30.setObjectName("gridLayout_30") self.sound_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.sound_checkBox.setChecked(True) self.sound_checkBox.setTristate(False) self.sound_checkBox.setObjectName("sound_checkBox") self.gridLayout_30.addWidget(self.sound_checkBox, 1, 0, 1, 1) self.virtual_raster_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.virtual_raster_checkBox.setChecked(True) self.virtual_raster_checkBox.setObjectName("virtual_raster_checkBox") self.gridLayout_30.addWidget(self.virtual_raster_checkBox, 1, 1, 1, 1) self.label_45 = QtWidgets.QLabel(self.tabWidgetProcessing) self.label_45.setStyleSheet("background-color : #656565; color : white") self.label_45.setFrameShape(QtWidgets.QFrame.Panel) self.label_45.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_45.setObjectName("label_45") self.gridLayout_30.addWidget(self.label_45, 0, 0, 1, 3) self.raster_compression_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.raster_compression_checkBox.setChecked(True) self.raster_compression_checkBox.setObjectName("raster_compression_checkBox") self.gridLayout_30.addWidget(self.raster_compression_checkBox, 1, 2, 1, 1) self.horizontalLayout_65 = QtWidgets.QHBoxLayout() self.horizontalLayout_65.setObjectName("horizontalLayout_65") self.parallel_writing_checkBox = QtWidgets.QCheckBox(self.tabWidgetProcessing) self.parallel_writing_checkBox.setObjectName("parallel_writing_checkBox") self.horizontalLayout_65.addWidget(self.parallel_writing_checkBox) self.gridLayout_30.addLayout(self.horizontalLayout_65, 2, 0, 1, 3) self.gridLayout_195.addLayout(self.gridLayout_30, 1, 0, 1, 1) spacerItem153 = QtWidgets.QSpacerItem(17, 17, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_195.addItem(spacerItem153, 5, 0, 1, 1) self.settings_tabWidget.addTab(self.tabWidgetProcessing, "") self.tabWidgetInterface = QtWidgets.QWidget() self.tabWidgetInterface.setObjectName("tabWidgetInterface") self.gridLayout_63 = QtWidgets.QGridLayout(self.tabWidgetInterface) self.gridLayout_63.setObjectName("gridLayout_63") self.gridLayout_13 = QtWidgets.QGridLayout() self.gridLayout_13.setObjectName("gridLayout_13") self.label_31 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_31.setFrameShape(QtWidgets.QFrame.Panel) self.label_31.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_31.setObjectName("label_31") self.gridLayout_13.addWidget(self.label_31, 1, 3, 1, 1) self.Info_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.Info_field_name_lineEdit.setMaxLength(10) self.Info_field_name_lineEdit.setObjectName("Info_field_name_lineEdit") self.gridLayout_13.addWidget(self.Info_field_name_lineEdit, 2, 3, 1, 1) self.label_24 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_24.setStyleSheet("background-color : #656565; color : white") self.label_24.setFrameShape(QtWidgets.QFrame.Panel) self.label_24.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_24.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_24.setObjectName("label_24") self.gridLayout_13.addWidget(self.label_24, 0, 0, 1, 5) self.ID_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.ID_field_name_lineEdit.setMaxLength(10) self.ID_field_name_lineEdit.setObjectName("ID_field_name_lineEdit") self.gridLayout_13.addWidget(self.ID_field_name_lineEdit, 2, 2, 1, 1) self.MID_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.MID_field_name_lineEdit.setMaxLength(10) self.MID_field_name_lineEdit.setObjectName("MID_field_name_lineEdit") self.gridLayout_13.addWidget(self.MID_field_name_lineEdit, 2, 0, 1, 1) self.label_10 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_10.setFrameShape(QtWidgets.QFrame.Panel) self.label_10.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_10.setObjectName("label_10") self.gridLayout_13.addWidget(self.label_10, 1, 2, 1, 1) self.MCInfo_field_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) self.MCInfo_field_name_lineEdit.setMaxLength(10) self.MCInfo_field_name_lineEdit.setObjectName("MCInfo_field_name_lineEdit") self.gridLayout_13.addWidget(self.MCInfo_field_name_lineEdit, 2, 1, 1, 1) self.label_17 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_17.setFrameShape(QtWidgets.QFrame.Panel) self.label_17.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_17.setObjectName("label_17") self.gridLayout_13.addWidget(self.label_17, 1, 0, 1, 1) self.label_46 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_46.setFrameShape(QtWidgets.QFrame.Panel) self.label_46.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_46.setObjectName("label_46") self.gridLayout_13.addWidget(self.label_46, 1, 1, 1, 1) self.reset_field_names_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_field_names_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_field_names_Button.setIcon(icon59) self.reset_field_names_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_field_names_Button.setObjectName("reset_field_names_Button") self.gridLayout_13.addWidget(self.reset_field_names_Button, 2, 4, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_13, 0, 0, 1, 1) self.gridLayout_21 = QtWidgets.QGridLayout() self.gridLayout_21.setObjectName("gridLayout_21") self.label_21 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_21.setStyleSheet("background-color : #656565; color : white") self.label_21.setFrameShape(QtWidgets.QFrame.Panel) self.label_21.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_21.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_21.setObjectName("label_21") self.gridLayout_21.addWidget(self.label_21, 0, 1, 1, 3) self.gridLayout_172 = QtWidgets.QGridLayout() self.gridLayout_172.setObjectName("gridLayout_172") self.change_color_Button = QtWidgets.QPushButton(self.tabWidgetInterface) self.change_color_Button.setStyleSheet("background-color : #FFAA00") self.change_color_Button.setText("") self.change_color_Button.setObjectName("change_color_Button") self.gridLayout_172.addWidget(self.change_color_Button, 0, 1, 1, 1) self.label_22 = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_22.sizePolicy().hasHeightForWidth()) self.label_22.setSizePolicy(sizePolicy) self.label_22.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_22.setObjectName("label_22") self.gridLayout_172.addWidget(self.label_22, 0, 0, 1, 1) self.transparency_Label = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.transparency_Label.sizePolicy().hasHeightForWidth()) self.transparency_Label.setSizePolicy(sizePolicy) self.transparency_Label.setMinimumSize(QtCore.QSize(100, 0)) self.transparency_Label.setFrameShadow(QtWidgets.QFrame.Sunken) self.transparency_Label.setObjectName("transparency_Label") self.gridLayout_172.addWidget(self.transparency_Label, 0, 2, 1, 1) self.transparency_Slider = QtWidgets.QSlider(self.tabWidgetInterface) self.transparency_Slider.setMaximum(100) self.transparency_Slider.setSingleStep(10) self.transparency_Slider.setProperty("value", 50) self.transparency_Slider.setOrientation(QtCore.Qt.Horizontal) self.transparency_Slider.setTickPosition(QtWidgets.QSlider.TicksBelow) self.transparency_Slider.setTickInterval(10) self.transparency_Slider.setObjectName("transparency_Slider") self.gridLayout_172.addWidget(self.transparency_Slider, 0, 3, 1, 1) self.gridLayout_21.addLayout(self.gridLayout_172, 2, 1, 1, 1) self.reset_color_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_color_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_color_Button.setIcon(icon59) self.reset_color_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_color_Button.setObjectName("reset_color_Button") self.gridLayout_21.addWidget(self.reset_color_Button, 2, 2, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_21, 1, 0, 1, 1) self.gridLayout_84 = QtWidgets.QGridLayout() self.gridLayout_84.setObjectName("gridLayout_84") self.label_68 = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_68.sizePolicy().hasHeightForWidth()) self.label_68.setSizePolicy(sizePolicy) self.label_68.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_68.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_68.setObjectName("label_68") self.gridLayout_84.addWidget(self.label_68, 1, 0, 1, 1) self.variable_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.variable_name_lineEdit.sizePolicy().hasHeightForWidth()) self.variable_name_lineEdit.setSizePolicy(sizePolicy) self.variable_name_lineEdit.setMaxLength(20) self.variable_name_lineEdit.setObjectName("variable_name_lineEdit") self.gridLayout_84.addWidget(self.variable_name_lineEdit, 1, 1, 1, 1) self.label_69 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_69.setStyleSheet("background-color : #656565; color : white") self.label_69.setFrameShape(QtWidgets.QFrame.Panel) self.label_69.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_69.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_69.setObjectName("label_69") self.gridLayout_84.addWidget(self.label_69, 0, 0, 1, 3) self.reset_variable_name_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_variable_name_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_variable_name_Button.setIcon(icon59) self.reset_variable_name_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_variable_name_Button.setObjectName("reset_variable_name_Button") self.gridLayout_84.addWidget(self.reset_variable_name_Button, 1, 2, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_84, 2, 0, 1, 1) self.gridLayout_17 = QtWidgets.QGridLayout() self.gridLayout_17.setObjectName("gridLayout_17") self.label_95 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_95.setStyleSheet("background-color : #656565; color : white") self.label_95.setFrameShape(QtWidgets.QFrame.Panel) self.label_95.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_95.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_95.setObjectName("label_95") self.gridLayout_17.addWidget(self.label_95, 0, 0, 1, 1) spacerItem154 = QtWidgets.QSpacerItem(20, 40, QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) self.gridLayout_17.addItem(spacerItem154, 2, 0, 1, 1) self.download_news_checkBox = QtWidgets.QCheckBox(self.tabWidgetInterface) self.download_news_checkBox.setChecked(True) self.download_news_checkBox.setObjectName("download_news_checkBox") self.gridLayout_17.addWidget(self.download_news_checkBox, 1, 0, 1, 1) self.gridLayout_63.addLayout(self.gridLayout_17, 4, 0, 1, 1) self.gridLayout_99 = QtWidgets.QGridLayout() self.gridLayout_99.setObjectName("gridLayout_99") self.label_76 = QtWidgets.QLabel(self.tabWidgetInterface) self.label_76.setStyleSheet("background-color : #656565; color : white") self.label_76.setFrameShape(QtWidgets.QFrame.Panel) self.label_76.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_76.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_76.setObjectName("label_76") self.gridLayout_99.addWidget(self.label_76, 0, 0, 1, 3) self.reset_group_name_Button = QtWidgets.QToolButton(self.tabWidgetInterface) self.reset_group_name_Button.setStyleSheet("margin: 0px;padding: 0px;") self.reset_group_name_Button.setIcon(icon59) self.reset_group_name_Button.setIconSize(QtCore.QSize(22, 22)) self.reset_group_name_Button.setObjectName("reset_group_name_Button") self.gridLayout_99.addWidget(self.reset_group_name_Button, 1, 2, 1, 1) self.virtual_raster_load_checkBox = QtWidgets.QCheckBox(self.tabWidgetInterface) self.virtual_raster_load_checkBox.setObjectName("virtual_raster_load_checkBox") self.gridLayout_99.addWidget(self.virtual_raster_load_checkBox, 2, 0, 1, 1) self.horizontalLayout_61 = QtWidgets.QHBoxLayout() self.horizontalLayout_61.setObjectName("horizontalLayout_61") self.label_75 = QtWidgets.QLabel(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Maximum, QtWidgets.QSizePolicy.Preferred) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.label_75.sizePolicy().hasHeightForWidth()) self.label_75.setSizePolicy(sizePolicy) self.label_75.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_75.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_75.setObjectName("label_75") self.horizontalLayout_61.addWidget(self.label_75) self.group_name_lineEdit = QtWidgets.QLineEdit(self.tabWidgetInterface) sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Fixed) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.group_name_lineEdit.sizePolicy().hasHeightForWidth()) self.group_name_lineEdit.setSizePolicy(sizePolicy) self.group_name_lineEdit.setMaxLength(20) self.group_name_lineEdit.setObjectName("group_name_lineEdit") self.horizontalLayout_61.addWidget(self.group_name_lineEdit) self.gridLayout_99.addLayout(self.horizontalLayout_61, 1, 0, 1, 2) self.gridLayout_63.addLayout(self.gridLayout_99, 3, 0, 1, 1) self.settings_tabWidget.addTab(self.tabWidgetInterface, "") self.tabWidgetDebug = QtWidgets.QWidget() self.tabWidgetDebug.setObjectName("tabWidgetDebug") self.gridLayout_56 = QtWidgets.QGridLayout(self.tabWidgetDebug) self.gridLayout_56.setObjectName("gridLayout_56") self.gridLayout_7 = QtWidgets.QGridLayout() self.gridLayout_7.setObjectName("gridLayout_7") self.log_checkBox = QtWidgets.QCheckBox(self.tabWidgetDebug) self.log_checkBox.setChecked(False) self.log_checkBox.setTristate(False) self.log_checkBox.setObjectName("log_checkBox") self.gridLayout_7.addWidget(self.log_checkBox, 1, 0, 1, 1) self.exportLog_Button = QtWidgets.QToolButton(self.tabWidgetDebug) self.exportLog_Button.setStyleSheet("margin: 0px;padding: 0px;") self.exportLog_Button.setIcon(icon53) self.exportLog_Button.setIconSize(QtCore.QSize(22, 22)) self.exportLog_Button.setObjectName("exportLog_Button") self.gridLayout_7.addWidget(self.exportLog_Button, 1, 1, 1, 1) self.clearLog_Button = QtWidgets.QToolButton(self.tabWidgetDebug) self.clearLog_Button.setStyleSheet("margin: 0px;padding: 0px;") self.clearLog_Button.setIcon(icon59) self.clearLog_Button.setIconSize(QtCore.QSize(22, 22)) self.clearLog_Button.setObjectName("clearLog_Button") self.gridLayout_7.addWidget(self.clearLog_Button, 1, 2, 1, 1) self.label_30 = QtWidgets.QLabel(self.tabWidgetDebug) self.label_30.setStyleSheet("background-color : #656565; color : white") self.label_30.setFrameShape(QtWidgets.QFrame.Panel) self.label_30.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_30.setObjectName("label_30") self.gridLayout_7.addWidget(self.label_30, 0, 0, 1, 3) self.log_tableWidget = QtWidgets.QTableWidget(self.tabWidgetDebug) self.log_tableWidget.setObjectName("log_tableWidget") self.log_tableWidget.setColumnCount(3) self.log_tableWidget.setRowCount(0) item = QtWidgets.QTableWidgetItem() self.log_tableWidget.setHorizontalHeaderItem(0, item) item = QtWidgets.QTableWidgetItem() self.log_tableWidget.setHorizontalHeaderItem(1, item) item = QtWidgets.QTableWidgetItem() self.log_tableWidget.setHorizontalHeaderItem(2, item) self.log_tableWidget.horizontalHeader().setStretchLastSection(True) self.gridLayout_7.addWidget(self.log_tableWidget, 2, 0, 1, 3) self.gridLayout_56.addLayout(self.gridLayout_7, 0, 0, 1, 1) self.gridLayout_55 = QtWidgets.QGridLayout() self.gridLayout_55.setObjectName("gridLayout_55") self.test_dependencies_Button = QtWidgets.QToolButton(self.tabWidgetDebug) self.test_dependencies_Button.setStyleSheet("margin: 0px;padding: 0px;") self.test_dependencies_Button.setIcon(icon67) self.test_dependencies_Button.setIconSize(QtCore.QSize(22, 22)) self.test_dependencies_Button.setObjectName("test_dependencies_Button") self.gridLayout_55.addWidget(self.test_dependencies_Button, 2, 2, 1, 1) self.label_42 = QtWidgets.QLabel(self.tabWidgetDebug) self.label_42.setAlignment(QtCore.Qt.AlignLeading|QtCore.Qt.AlignLeft|QtCore.Qt.AlignVCenter) self.label_42.setObjectName("label_42") self.gridLayout_55.addWidget(self.label_42, 2, 1, 1, 1) spacerItem155 = QtWidgets.QSpacerItem(40, 20, QtWidgets.QSizePolicy.Expanding, QtWidgets.QSizePolicy.Minimum) self.gridLayout_55.addItem(spacerItem155, 2, 3, 1, 1) self.label_43 = QtWidgets.QLabel(self.tabWidgetDebug) self.label_43.setStyleSheet("background-color : #656565; color : white") self.label_43.setFrameShape(QtWidgets.QFrame.Panel) self.label_43.setFrameShadow(QtWidgets.QFrame.Sunken) self.label_43.setObjectName("label_43") self.gridLayout_55.addWidget(self.label_43, 0, 0, 1, 4) self.gridLayout_56.addLayout(self.gridLayout_55, 1, 0, 1, 1) self.settings_tabWidget.addTab(self.tabWidgetDebug, "") self.gridLayout_134.addWidget(self.settings_tabWidget, 0, 0, 1, 1) self.SCP_tabs.addTab(self.tab_Settings, "") self.tab_About = QtWidgets.QWidget() sizePolicy = QtWidgets.QSizePolicy(QtWidgets.QSizePolicy.Minimum, QtWidgets.QSizePolicy.Expanding) sizePolicy.setHorizontalStretch(0) sizePolicy.setVerticalStretch(0) sizePolicy.setHeightForWidth(self.tab_About.sizePolicy().hasHeightForWidth()) self.tab_About.setSizePolicy(sizePolicy) self.tab_About.setLocale(QtCore.QLocale(QtCore.QLocale.English, QtCore.QLocale.UnitedStates)) self.tab_About.setObjectName("tab_About") self.gridLayout_16 = QtWidgets.QGridLayout(self.tab_About) self.gridLayout_16.setObjectName("gridLayout_16") self.gridLayout_5 = QtWidgets.QGridLayout() self.gridLayout_5.setObjectName("gridLayout_5") self.plugin_version_label = QtWidgets.QLabel(self.tab_About) self.plugin_version_label.setFrameShape(QtWidgets.QFrame.NoFrame) self.plugin_version_label.setFrameShadow(QtWidgets.QFrame.Raised) self.plugin_version_label.setText("") self.plugin_version_label.setTextFormat(QtCore.Qt.PlainText) self.plugin_version_label.setAlignment(QtCore.Qt.AlignCenter) self.plugin_version_label.setObjectName("plugin_version_label") self.gridLayout_5.addWidget(self.plugin_version_label, 1, 0, 1, 1) self.plugin_label = QtWidgets.QLabel(self.tab_About) self.plugin_label.setFrameShape(QtWidgets.QFrame.NoFrame) self.plugin_label.setFrameShadow(QtWidgets.QFrame.Raised) self.plugin_label.setTextFormat(QtCore.Qt.PlainText) self.plugin_label.setAlignment(QtCore.Qt.AlignCenter) self.plugin_label.setObjectName("plugin_label") self.gridLayout_5.addWidget(self.plugin_label, 0, 0, 1, 1) self.gridLayout_16.addLayout(self.gridLayout_5, 0, 0, 1, 1) self.gridLayout_9 = QtWidgets.QGridLayout() self.gridLayout_9.setObjectName("gridLayout_9") self.textBrowser = QtWidgets.QTextBrowser(self.tab_About) self.textBrowser.setFrameShape(QtWidgets.QFrame.Panel) self.textBrowser.setFrameShadow(QtWidgets.QFrame.Sunken) self.textBrowser.setOpenExternalLinks(True) self.textBrowser.setObjectName("textBrowser") self.gridLayout_9.addWidget(self.textBrowser, 0, 0, 1, 1) self.gridLayout_16.addLayout(self.gridLayout_9, 1, 0, 1, 1) self.SCP_tabs.addTab(self.tab_About, "") self.gridLayout_262.addWidget(self.SCP_tabs, 0, 0, 1, 1) self.main_tabWidget.addTab(self.tool_tab, icon, "") self.help_tab = QtWidgets.QWidget() self.help_tab.setObjectName("help_tab") self.gridLayout_263 = QtWidgets.QGridLayout(self.help_tab) self.gridLayout_263.setObjectName("gridLayout_263") self.help_textBrowser = QtWidgets.QTextBrowser(self.help_tab) self.help_textBrowser.setOpenExternalLinks(True) self.help_textBrowser.setOpenLinks(False) self.help_textBrowser.setObjectName("help_textBrowser") self.gridLayout_263.addWidget(self.help_textBrowser, 1, 0, 1, 1) self.main_tabWidget.addTab(self.help_tab, icon51, "") self.gridLayout_301.addWidget(self.splitter, 0, 0, 1, 1) self.retranslateUi(SemiAutomaticClassificationPlugin) self.main_tabWidget.setCurrentIndex(0) self.SCP_tabs.setCurrentIndex(0) self.Band_set_tabWidget.setCurrentIndex(-1) self.tabWidget_5.setCurrentIndex(0) self.alg_band_weight_tabWidget.setCurrentIndex(-1) self.toolBox_4.setCurrentIndex(2) self.tabWidget_3.setCurrentIndex(1) self.tabWidget_preprocessing.setCurrentIndex(0) self.tabWidget_4.setCurrentIndex(0) self.toolBox_band_set_combination.setCurrentIndex(0) self.toolBox_PCA.setCurrentIndex(0) self.toolBox_kmeans.setCurrentIndex(0) self.toolBox_random_forest.setCurrentIndex(0) self.tabWidget_2.setCurrentIndex(0) self.toolBox_accuracy.setCurrentIndex(0) self.toolBox_landCoverChange.setCurrentIndex(0) self.toolBox_class_report.setCurrentIndex(0) self.toolBox_cross_classification.setCurrentIndex(0) self.toolBox_class_signature.setCurrentIndex(0) self.band_calc_tabWidget.setCurrentIndex(0) self.settings_tabWidget.setCurrentIndex(0) QtCore.QMetaObject.connectSlotsByName(SemiAutomaticClassificationPlugin) def retranslateUi(self, SemiAutomaticClassificationPlugin): _translate = QtCore.QCoreApplication.translate SemiAutomaticClassificationPlugin.setWindowTitle(_translate("SemiAutomaticClassificationPlugin", "Semi-Automatic Classification Plugin")) self.f_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) __sortingEnabled = self.menu_treeWidget.isSortingEnabled() self.menu_treeWidget.setSortingEnabled(False) self.menu_treeWidget.topLevelItem(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band set")) self.menu_treeWidget.topLevelItem(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Basic tools")) self.menu_treeWidget.topLevelItem(1).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Algorithm band weight")) self.menu_treeWidget.topLevelItem(1).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band set list")) self.menu_treeWidget.topLevelItem(1).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Export signatures")) self.menu_treeWidget.topLevelItem(1).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "Import signatures")) self.menu_treeWidget.topLevelItem(1).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "LCS threshold")) self.menu_treeWidget.topLevelItem(1).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Multiple ROI creation")) self.menu_treeWidget.topLevelItem(1).child(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "RGB list")) self.menu_treeWidget.topLevelItem(1).child(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Signature threshold")) self.menu_treeWidget.topLevelItem(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Download products")) self.menu_treeWidget.topLevelItem(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "Preprocessing")) self.menu_treeWidget.topLevelItem(3).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "ASTER")) self.menu_treeWidget.topLevelItem(3).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "GOES")) self.menu_treeWidget.topLevelItem(3).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Landsat")) self.menu_treeWidget.topLevelItem(3).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "MODIS")) self.menu_treeWidget.topLevelItem(3).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Sentinel-1")) self.menu_treeWidget.topLevelItem(3).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Sentinel-2")) self.menu_treeWidget.topLevelItem(3).child(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "Sentinel-3")) self.menu_treeWidget.topLevelItem(3).child(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Clip multiple rasters")) self.menu_treeWidget.topLevelItem(3).child(8).setText(0, _translate("SemiAutomaticClassificationPlugin", "Cloud masking")) self.menu_treeWidget.topLevelItem(3).child(9).setText(0, _translate("SemiAutomaticClassificationPlugin", "Mosaic band sets")) self.menu_treeWidget.topLevelItem(3).child(10).setText(0, _translate("SemiAutomaticClassificationPlugin", "Neighbor pixels")) self.menu_treeWidget.topLevelItem(3).child(11).setText(0, _translate("SemiAutomaticClassificationPlugin", "Reproject raster bands")) self.menu_treeWidget.topLevelItem(3).child(12).setText(0, _translate("SemiAutomaticClassificationPlugin", "Split raster bands")) self.menu_treeWidget.topLevelItem(3).child(13).setText(0, _translate("SemiAutomaticClassificationPlugin", "Stack raster bands")) self.menu_treeWidget.topLevelItem(3).child(14).setText(0, _translate("SemiAutomaticClassificationPlugin", "Vector to raster")) self.menu_treeWidget.topLevelItem(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band processing")) self.menu_treeWidget.topLevelItem(4).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band combination")) self.menu_treeWidget.topLevelItem(4).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification")) self.menu_treeWidget.topLevelItem(4).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Clustering")) self.menu_treeWidget.topLevelItem(4).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "PCA")) self.menu_treeWidget.topLevelItem(4).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Random forest")) self.menu_treeWidget.topLevelItem(4).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Spectral distance")) self.menu_treeWidget.topLevelItem(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Postprocessing")) self.menu_treeWidget.topLevelItem(5).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Accuracy")) self.menu_treeWidget.topLevelItem(5).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification dilation")) self.menu_treeWidget.topLevelItem(5).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification erosion")) self.menu_treeWidget.topLevelItem(5).child(3).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification report")) self.menu_treeWidget.topLevelItem(5).child(4).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification to vector")) self.menu_treeWidget.topLevelItem(5).child(5).setText(0, _translate("SemiAutomaticClassificationPlugin", "Classification sieve")) self.menu_treeWidget.topLevelItem(5).child(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "Class signature")) self.menu_treeWidget.topLevelItem(5).child(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Cross classification")) self.menu_treeWidget.topLevelItem(5).child(8).setText(0, _translate("SemiAutomaticClassificationPlugin", "Edit raster")) self.menu_treeWidget.topLevelItem(5).child(9).setText(0, _translate("SemiAutomaticClassificationPlugin", "Land cover change")) self.menu_treeWidget.topLevelItem(5).child(10).setText(0, _translate("SemiAutomaticClassificationPlugin", "Reclassification")) self.menu_treeWidget.topLevelItem(5).child(11).setText(0, _translate("SemiAutomaticClassificationPlugin", "Zonal stat raster")) self.menu_treeWidget.topLevelItem(6).setText(0, _translate("SemiAutomaticClassificationPlugin", "Band calc")) self.menu_treeWidget.topLevelItem(7).setText(0, _translate("SemiAutomaticClassificationPlugin", "Batch")) self.menu_treeWidget.topLevelItem(8).setText(0, _translate("SemiAutomaticClassificationPlugin", "Settings")) self.menu_treeWidget.topLevelItem(8).child(0).setText(0, _translate("SemiAutomaticClassificationPlugin", "Debug")) self.menu_treeWidget.topLevelItem(8).child(1).setText(0, _translate("SemiAutomaticClassificationPlugin", "Interface")) self.menu_treeWidget.topLevelItem(8).child(2).setText(0, _translate("SemiAutomaticClassificationPlugin", "Processing setting")) self.menu_treeWidget.topLevelItem(9).setText(0, _translate("SemiAutomaticClassificationPlugin", "User manual")) self.menu_treeWidget.topLevelItem(10).setText(0, _translate("SemiAutomaticClassificationPlugin", "Help")) self.menu_treeWidget.topLevelItem(11).setText(0, _translate("SemiAutomaticClassificationPlugin", "About")) self.menu_treeWidget.topLevelItem(12).setText(0, _translate("SemiAutomaticClassificationPlugin", "Support the SCP")) self.menu_treeWidget.setSortingEnabled(__sortingEnabled) self.label_59.setText(_translate("SemiAutomaticClassificationPlugin", "Wavelength\n" "quick settings")) self.wavelength_sat_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a configuration for setting band center wavelengths</body></html>")) self.label_60.setText(_translate("SemiAutomaticClassificationPlugin", "Wavelength \n" "unit")) self.unit_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Wavelength unit</body></html>")) self.export_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export band set to text file</body></html>")) self.export_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import band set from text file</body></html>")) self.import_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.bandset_dateEdit.setDisplayFormat(_translate("SemiAutomaticClassificationPlugin", "yyyy-MM-dd")) self.label_3.setText(_translate("SemiAutomaticClassificationPlugin", "Date")) self.label_52.setText(_translate("SemiAutomaticClassificationPlugin", " Single band list")) self.bands_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Filter</body></html>")) self.bands_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) item = self.bands_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) self.toolButton_reload_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_3.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.select_all_bands_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select all / Unselect all</body></html>")) self.select_all_bands_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.add_raster_bands_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add band to Band set</body></html>")) self.add_raster_bands_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_53.setText(_translate("SemiAutomaticClassificationPlugin", " Band set definition")) self.remove_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.clear_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.sort_by_name_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Sort bands by name (priority to ending number)</body></html>")) self.sort_by_name_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_up_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted band up</body></html>")) self.move_up_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_down_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted band down</body></html>")) self.move_down_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_band_set_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add a new band set</body></html>")) self.add_band_set_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.virtual_raster_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a virtual raster of active band set</body></html>")) self.virtual_raster_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create virtual raster of band set")) self.band_calc_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Calculate expression in Band calc</body></html>")) self.band_calc_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Band calc expressions")) self.stack_raster_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a .tif raster stacking the bands of the active band set</body></html>")) self.stack_raster_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create raster of band set \n" "(stack bands)")) self.overview_raster_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Build band overviews (external pyramids) of active band set for faster visualization</body></html>")) self.overview_raster_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Build band overviews")) self.label_94.setText(_translate("SemiAutomaticClassificationPlugin", " Band set tools")) self.band_set_process_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.band_set_process_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.toolButton_reload.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_39.setText(_translate("SemiAutomaticClassificationPlugin", " Multiband image list")) self.toolButton_input_raster.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.image_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a multiband image</body></html>")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_band_set), _translate("SemiAutomaticClassificationPlugin", "Band set")) self.label_126.setText(_translate("SemiAutomaticClassificationPlugin", "RGB list")) self.sort_by_name_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Sort RGB automatically</body></html>")) self.sort_by_name_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_down_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted RGB down</body></html>")) self.move_down_toolButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_up_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted RGB up</body></html>")) self.move_up_toolButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_RGB_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add row</body></html>")) self.add_RGB_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_RGB_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export RGB list to text file</body></html>")) self.export_RGB_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_RGB_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import RGB list from text file</body></html>")) self.import_RGB_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_RGB_list_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.clear_RGB_list_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.remove_RGB_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_RGB_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) item = self.RGB_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "RGB")) self.label_196.setText(_translate("SemiAutomaticClassificationPlugin", "Automatic RGB")) self.label_192.setText(_translate("SemiAutomaticClassificationPlugin", "Band combinations")) self.all_RGB_list_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add all combinations of bands</body></html>")) self.all_RGB_list_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_RGB), _translate("SemiAutomaticClassificationPlugin", "RGB list")) self.label_208.setText(_translate("SemiAutomaticClassificationPlugin", "Band set list")) self.band_set_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Filter</body></html>")) self.band_set_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) item = self.band_set_list_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Number")) item = self.band_set_list_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Bands")) item = self.band_set_list_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "Date")) self.move_down_toolButton_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted Band sets down</body></html>")) self.move_down_toolButton_4.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.move_up_toolButton_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted Band sets up</body></html>")) self.move_up_toolButton_4.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.rgb_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add row</body></html>")) self.rgb_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.add_bandset_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add row</body></html>")) self.add_bandset_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_bandset_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export Band set list to file</body></html>")) self.export_bandset_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_bandset_List_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import Band set list from file</body></html>")) self.import_bandset_List_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.remove_bandset_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_bandset_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.sort_by_date.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Sort band sets by date</body></html>")) self.sort_by_date.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_band_set_list), _translate("SemiAutomaticClassificationPlugin", "Band set list")) self.label_79.setText(_translate("SemiAutomaticClassificationPlugin", "Algorithm band weight")) self.reset_weights_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>\n" "")) self.set_weight_value_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set</body></html>\n" "")) self.label_131.setText(_translate("SemiAutomaticClassificationPlugin", "Set weight")) self.weight_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set a value</body></html>")) self.label_93.setText(_translate("SemiAutomaticClassificationPlugin", "Automatic weight")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_algorithm_weight), _translate("SemiAutomaticClassificationPlugin", "Algorithm band weight")) self.point_distance_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Minimum distance between points</body></html>")) self.point_grid_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Size of a grid cell within points are created randomly</body></html>")) self.label_48.setText(_translate("SemiAutomaticClassificationPlugin", " Create random points")) self.label_139.setText(_translate("SemiAutomaticClassificationPlugin", "Create points")) self.label_19.setText(_translate("SemiAutomaticClassificationPlugin", "Number of points")) self.point_number_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Number of points created randomly</body></html>")) self.add_random_point_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create points</body></html>")) self.point_distance_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create random points with a minimum distance</body></html>")) self.point_distance_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "min distance")) self.point_grid_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create random points inside each cell of a grid with this size</body></html>")) self.point_grid_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "inside grid")) self.stratified_point_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create stratified random points</body></html>")) self.stratified_point_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "stratified for the values")) self.stratified_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter one or more rules separated by semicolon (e.g. raster > 0; raster == 1 )</body></html>")) self.stratified_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "raster > 0")) self.band_set_comb_spinBox_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_25.setText(_translate("SemiAutomaticClassificationPlugin", "of first band of band set")) self.label_47.setText(_translate("SemiAutomaticClassificationPlugin", " Point coordinates and ROI definition")) self.point_tableWidget.setSortingEnabled(False) item = self.point_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "X")) item = self.point_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Y")) item = self.point_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) item = self.point_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name")) item = self.point_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) item = self.point_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "C Name")) item = self.point_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "Min")) item = self.point_tableWidget.horizontalHeaderItem(7) item.setText(_translate("SemiAutomaticClassificationPlugin", "Max")) item = self.point_tableWidget.horizontalHeaderItem(8) item.setText(_translate("SemiAutomaticClassificationPlugin", "Dist")) item = self.point_tableWidget.horizontalHeaderItem(9) item.setText(_translate("SemiAutomaticClassificationPlugin", "Rapid ROI band")) self.add_point_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add row</body></html>")) self.add_point_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.remove_point_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_point_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_point_list_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export point list to text file</body></html>")) self.export_point_list_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_point_list_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import point list from text file</body></html>")) self.import_point_list_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.signature_checkBox2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add ROI spectral signatures to signature list</body></html>")) self.signature_checkBox2.setText(_translate("SemiAutomaticClassificationPlugin", "Calculate sig.")) self.label_159.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.save_point_rois_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.save_point_rois_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_multiple_ROI), _translate("SemiAutomaticClassificationPlugin", "Multiple ROI creation")) self.usgs_chapter_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a chapter</body></html>")) self.usgs_library_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a library</body></html>")) self.label_123.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a chapter</body></html>")) self.label_124.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a library</body></html>")) self.label_130.setText(_translate("SemiAutomaticClassificationPlugin", "Import spectral library")) self.add_usgs_library_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import spectral library</body></html>")) self.USGS_library_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Sans\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" " </body></html>")) self.label.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>USGS Spectral Library Version 7 downloaded from <a href=\"https://crustal.usgs.gov/speclab/QueryAll07a.php\">https://crustal.usgs.gov/speclab/QueryAll07a.php</a>. Reference: Kokaly, R.F., Clark, R.N., Swayze, G.A., Livo, K.E., Hoefen, T.M., Pearson, N.C., Wise, R.A., Benzel, W.M., Lowers, H.A., Driscoll, R.L., and Klein, A.J., 2017, USGS Spectral Library Version 7: U.S. Geological Survey Data Series 1035, 61 p., https://doi.org/10.3133/ds1035.</body></html>")) self.label_129.setText(_translate("SemiAutomaticClassificationPlugin", " Library Description (requires internet connection)")) self.toolBox_4.setItemText(self.toolBox_4.indexOf(self.page_8), _translate("SemiAutomaticClassificationPlugin", "Download USGS Spectral Library")) self.label_9.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a file: SCP file (*.scp) ; USGS library (*.asc) ; ASTER library (*.txt) ; CSV (*.csv)</body></html>")) self.open_library_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.toolBox_4.setItemText(self.toolBox_4.indexOf(self.page_6), _translate("SemiAutomaticClassificationPlugin", "Import library file")) self.open_shapefile_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.label_120.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a vector (*.shp;*.gpkg)</body></html>")) self.C_ID_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>C ID field</body></html>")) self.MC_ID_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>MC ID field</body></html>")) self.MC_Info_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>MC Name field</body></html>")) self.label_99.setText(_translate("SemiAutomaticClassificationPlugin", "C Name field")) self.C_Info_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>C Name field</body></html>")) self.label_119.setText(_translate("SemiAutomaticClassificationPlugin", " Vector fields")) self.MC_ID_combo_2.setText(_translate("SemiAutomaticClassificationPlugin", "C ID field")) self.label_121.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID field")) self.label_122.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name field")) self.label_2.setText(_translate("SemiAutomaticClassificationPlugin", " Import vector")) self.signature_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add ROI spectral signature to signature list</body></html>")) self.signature_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Calculate sig.")) self.import_shapefile_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import vector</body></html>")) self.import_shapefile_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.toolBox_4.setItemText(self.toolBox_4.indexOf(self.page_9), _translate("SemiAutomaticClassificationPlugin", "Import vector")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_Import), _translate("SemiAutomaticClassificationPlugin", "Import signatures")) self.label_97.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export as SCP file (*.scp)</body></html>")) self.export_SCP_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export highlighted spectral signatures</body></html>\n" "")) self.export_CSV_library_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a directory where highlighted spectral signatures are saved as .csv</body></html>")) self.export_CSV_library_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_96.setText(_translate("SemiAutomaticClassificationPlugin", "Export ")) self.label_222.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export as shapefile (*.shp) or geopackage (*.gpkg)</body></html>")) self.label_20.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export as CSV file (.csv)</body></html>")) self.export_SHP_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export highlighted spectral signatures</body></html>\n" "")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_export), _translate("SemiAutomaticClassificationPlugin", "Export signatures")) self.reset_threshold_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>\n" "")) self.signature_threshold_tableWidget.setSortingEnabled(True) item = self.signature_threshold_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "C Name")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "MD Threshold")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "ML Threshold")) item = self.signature_threshold_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "SAM Threshold")) self.label_80.setText(_translate("SemiAutomaticClassificationPlugin", " Signature threshold")) self.label_85.setText(_translate("SemiAutomaticClassificationPlugin", "Set threshold = σ *")) self.multiplicative_threshold_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set a value that will be multiplied by standard deviation</body></html>")) self.automatic_threshold_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set automatic threshold σ</body></html>")) self.label_132.setText(_translate("SemiAutomaticClassificationPlugin", "Set threshold")) self.threshold_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set a value</body></html>")) self.set_threshold_value_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set</body></html>\n" "")) self.label_88.setText(_translate("SemiAutomaticClassificationPlugin", " Automatic thresholds")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_threshold), _translate("SemiAutomaticClassificationPlugin", "Signature threshold")) self.LCS_tableWidget.setSortingEnabled(True) item = self.LCS_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) item = self.LCS_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name")) item = self.LCS_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) item = self.LCS_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "C Name")) item = self.LCS_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "Color [overlap MC_ID-C_ID]")) self.label_86.setText(_translate("SemiAutomaticClassificationPlugin", " LC Signature threshold")) self.signature_spectral_plot_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add highlighted signatures to spectral signature plot</body></html>")) self.signature_spectral_plot_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_102.setText(_translate("SemiAutomaticClassificationPlugin", "Min Max")) self.set_min_max_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set automatic threshold Min Max</body></html>")) self.label_101.setText(_translate("SemiAutomaticClassificationPlugin", "σ *")) self.multiplicative_threshold_doubleSpinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set a value that will be multiplied by standard deviation</body></html>")) self.automatic_threshold_pushButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set automatic threshold σ</body></html>")) self.label_89.setText(_translate("SemiAutomaticClassificationPlugin", "From pixel")) self.LCS_pointerButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Activate pointer for setting thresholds from pixel</body></html>")) self.LCS_include_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, signature threshold is extended to include pixel signature</body></html>")) self.LCS_cut_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, signature threshold is reduced to exclude pixel signature</body></html>")) self.label_178.setText(_translate("SemiAutomaticClassificationPlugin", "From ROI")) self.LCS_ROI_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set thresholds from temporary ROI</body></html>")) self.label_125.setText(_translate("SemiAutomaticClassificationPlugin", "Automatic thresholds")) self.tabWidget_5.setTabText(self.tabWidget_5.indexOf(self.tab_LCS_threshold), _translate("SemiAutomaticClassificationPlugin", "LCS threshold")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_basic_tools), _translate("SemiAutomaticClassificationPlugin", "Basic tools")) self.remember_user_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, remember user name and password locally in QGIS</body></html>")) self.remember_user_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.password_usgs_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Password</body></html>")) self.password_scihub_label_3.setText(_translate("SemiAutomaticClassificationPlugin", "Password")) self.label_180.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Login Landsat (<a href=\"https://ers.cr.usgs.gov\">https://ers.cr.usgs.gov</a>)</body></html>")) self.user_usgs_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>User name</body></html>")) self.user_scihub_label_2.setText(_translate("SemiAutomaticClassificationPlugin", "User")) self.remember_user_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, remember user name and password locally in QGIS</body></html>")) self.remember_user_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.password_usgs_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Password</body></html>")) self.password_scihub_label_4.setText(_translate("SemiAutomaticClassificationPlugin", "Password")) self.label_191.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Login ASTER and MODIS (<a href=\"https://urs.earthdata.nasa.gov\">https://urs.earthdata.nasa.gov</a>)</body></html>")) self.user_usgs_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>User name</body></html>")) self.user_scihub_label_3.setText(_translate("SemiAutomaticClassificationPlugin", "User")) self.user_scihub_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>User name</body></html>")) self.password_scihub_label.setText(_translate("SemiAutomaticClassificationPlugin", "Password")) self.label_147.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Login Sentinels</body></html>")) self.remember_user_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, remember user name and password locally in QGIS</body></html>")) self.remember_user_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.user_scihub_label.setText(_translate("SemiAutomaticClassificationPlugin", "User")) self.password_scihub_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Password</body></html>")) self.password_scihub_label_2.setText(_translate("SemiAutomaticClassificationPlugin", "Service")) self.sentinel_service_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Service</body></html>")) self.reset_sentinel_service_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.reset_sentinel_service_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.sentinel2_alternative_search_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use alternative search for Sentinel-2 (no authentication required)</body></html>")) self.sentinel2_alternative_search_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use alternative search for Sentinel-2 (no authentication required)")) self.tabWidget_3.setTabText(self.tabWidget_3.indexOf(self.tab_login), _translate("SemiAutomaticClassificationPlugin", "Login data")) self.remove_image_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_image_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.toolButton_display.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Display preview of highlighted images in map</body></html>")) self.toolButton_display.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_table_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.clear_table_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.export_table_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export table to text file</body></html>")) self.export_table_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_table_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import table from text file</body></html>")) self.import_table_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.image_preview_label.setText(_translate("SemiAutomaticClassificationPlugin", "Preview")) self.download_images_tableWidget.setSortingEnabled(True) item = self.download_images_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Product")) item = self.download_images_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "ProductID")) item = self.download_images_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "AcquisitionDate")) item = self.download_images_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "CloudCover")) item = self.download_images_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "Zone/Path")) item = self.download_images_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "Row/DayNight")) item = self.download_images_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "min_lat")) item = self.download_images_tableWidget.horizontalHeaderItem(7) item.setText(_translate("SemiAutomaticClassificationPlugin", "min_lon")) item = self.download_images_tableWidget.horizontalHeaderItem(8) item.setText(_translate("SemiAutomaticClassificationPlugin", "max_lat")) item = self.download_images_tableWidget.horizontalHeaderItem(9) item.setText(_translate("SemiAutomaticClassificationPlugin", "max_lon")) item = self.download_images_tableWidget.horizontalHeaderItem(10) item.setText(_translate("SemiAutomaticClassificationPlugin", "Collection/Size")) item = self.download_images_tableWidget.horizontalHeaderItem(11) item.setText(_translate("SemiAutomaticClassificationPlugin", "Preview")) item = self.download_images_tableWidget.horizontalHeaderItem(12) item.setText(_translate("SemiAutomaticClassificationPlugin", "Collection/ID")) item = self.download_images_tableWidget.horizontalHeaderItem(13) item.setText(_translate("SemiAutomaticClassificationPlugin", "Collection/Image")) self.label_100.setText(_translate("SemiAutomaticClassificationPlugin", " Product list")) self.products_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Filter</body></html>")) self.products_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) self.toolButton_OSM.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add OpenStreetMap to the map</body></html>")) self.toolButton_OSM.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_205.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add OpenStreetMap to the map</body></html>")) self.label_206.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>(© <a href=\"http://www.openstreetmap.org/copyright\">OpenStreetMap</a> contributors. The cartography is licensed as CC BY-SA. <a href=\"https://operations.osmfoundation.org/policies/tiles/\">Tile Usage Policy</a>)</body></html>")) self.label_103.setText(_translate("SemiAutomaticClassificationPlugin", " Search parameters")) self.selectUL_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set area in the map</body></html>")) self.LX_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Lower right X</body></html>")) self.LX_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X (Lon)")) self.UX_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Upper left X</body></html>")) self.UX_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X (Lon)")) self.label_105.setText(_translate("SemiAutomaticClassificationPlugin", "LR")) self.label_107.setText(_translate("SemiAutomaticClassificationPlugin", "UL")) self.LY_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Lower right Y</body></html>")) self.LY_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y (Lat)")) self.UY_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Upper left Y</body></html>")) self.UY_lineEdit_3.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y (Lat)")) self.show_area_radioButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Show / hide area</body></html>")) self.show_area_radioButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Show")) self.find_images_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Find images</body></html>")) self.label_35.setText(_translate("SemiAutomaticClassificationPlugin", "Find")) self.landsat_satellite_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a product</body></html>")) self.dateEdit_from.setDisplayFormat(_translate("SemiAutomaticClassificationPlugin", "yyyy-MM-dd")) self.label_110.setText(_translate("SemiAutomaticClassificationPlugin", "Max cloud cover (%)")) self.dateEdit_to.setDisplayFormat(_translate("SemiAutomaticClassificationPlugin", "yyyy-MM-dd")) self.label_112.setText(_translate("SemiAutomaticClassificationPlugin", "to")) self.label_111.setText(_translate("SemiAutomaticClassificationPlugin", "Date from")) self.cloud_cover_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Maximum cloud cover percentage</body></html>")) self.label_114.setText(_translate("SemiAutomaticClassificationPlugin", "Products")) self.label_194.setText(_translate("SemiAutomaticClassificationPlugin", "Results")) self.label_113.setText(_translate("SemiAutomaticClassificationPlugin", "Advanced search")) self.imageID_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Filter images</body></html>")) self.result_number_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Maximum number of results (images)</body></html>")) self.tabWidget_3.setTabText(self.tabWidget_3.indexOf(self.tab_search), _translate("SemiAutomaticClassificationPlugin", "Search")) self.checkBox_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6 (Landsat 1-8)")) self.checkBox_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4 (Landsat 1-8)")) self.checkBox_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1 (Landsat 4-8)")) self.checkBox_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3 (Landsat 4-8)")) self.checkBox_band_12.setText(_translate("SemiAutomaticClassificationPlugin", "Ancillary data")) self.checkBox_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2 (Landsat 4-8)")) self.checkBox_band_11.setText(_translate("SemiAutomaticClassificationPlugin", "11 (Landsat 8)")) self.checkBox_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5 (Landsat 1-8)")) self.check_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select all</body></html>")) self.check_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_108.setText(_translate("SemiAutomaticClassificationPlugin", " Landsat bands")) self.checkBoxs_band_9.setText(_translate("SemiAutomaticClassificationPlugin", "8A")) self.checkBoxs_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.check_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select all</body></html>")) self.check_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_118.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-2 bands")) self.checkBoxs_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2")) self.checkBoxs_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3")) self.checkBoxs_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4")) self.checkBoxs_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5")) self.checkBoxs_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6")) self.checkBoxs_band_7.setText(_translate("SemiAutomaticClassificationPlugin", "7")) self.checkBoxs_band_12.setText(_translate("SemiAutomaticClassificationPlugin", "11")) self.checkBoxs_band_8.setText(_translate("SemiAutomaticClassificationPlugin", "8")) self.checkBoxs_band_10.setText(_translate("SemiAutomaticClassificationPlugin", "9")) self.ancillary_data_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Ancillary data")) self.checkBoxs_band_13.setText(_translate("SemiAutomaticClassificationPlugin", "12")) self.checkBoxs_band_11.setText(_translate("SemiAutomaticClassificationPlugin", "10")) self.checkBoxs3_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6")) self.checkBoxs3_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2")) self.checkBoxs3_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5")) self.checkBoxs3_band_8.setText(_translate("SemiAutomaticClassificationPlugin", "8")) self.checkBoxs3_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.checkBoxs3_band_16.setText(_translate("SemiAutomaticClassificationPlugin", "16")) self.checkBoxs3_band_10.setText(_translate("SemiAutomaticClassificationPlugin", "10")) self.checkBoxs3_band_12.setText(_translate("SemiAutomaticClassificationPlugin", "12")) self.s3_ancillary_data_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Ancillary data")) self.checkBoxs3_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3")) self.label_127.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-3 bands")) self.checkBoxs3_band_20.setText(_translate("SemiAutomaticClassificationPlugin", "20")) self.checkBoxs3_band_17.setText(_translate("SemiAutomaticClassificationPlugin", "17")) self.checkBoxs3_band_14.setText(_translate("SemiAutomaticClassificationPlugin", "14")) self.checkBoxs3_band_9.setText(_translate("SemiAutomaticClassificationPlugin", "9")) self.checkBoxs3_band_13.setText(_translate("SemiAutomaticClassificationPlugin", "13")) self.checkBoxs3_band_19.setText(_translate("SemiAutomaticClassificationPlugin", "19")) self.check_toolButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select all</body></html>")) self.check_toolButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.checkBoxs3_band_7.setText(_translate("SemiAutomaticClassificationPlugin", "7")) self.checkBoxs3_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4")) self.checkBoxs3_band_11.setText(_translate("SemiAutomaticClassificationPlugin", "11")) self.checkBoxs3_band_15.setText(_translate("SemiAutomaticClassificationPlugin", "15")) self.checkBoxs3_band_21.setText(_translate("SemiAutomaticClassificationPlugin", "21")) self.checkBoxs3_band_18.setText(_translate("SemiAutomaticClassificationPlugin", "18")) self.checkBoxs_goes_band_1.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.label_272.setText(_translate("SemiAutomaticClassificationPlugin", " GOES bands")) self.checkBoxs_goes_band_5.setText(_translate("SemiAutomaticClassificationPlugin", "5")) self.checkBoxs_goes_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "3")) self.checkBoxs_goes_band_4.setText(_translate("SemiAutomaticClassificationPlugin", "4")) self.checkBoxs_goes_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "2")) self.checkBoxs_goes_band_6.setText(_translate("SemiAutomaticClassificationPlugin", "6")) self.check_toolButton_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select all</body></html>")) self.check_toolButton_4.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.checkBox_band_8.setText(_translate("SemiAutomaticClassificationPlugin", "8 (Landsat 7, 8)")) self.checkBox_band_10.setText(_translate("SemiAutomaticClassificationPlugin", "10 (Landsat 8)")) self.checkBox_band_9.setText(_translate("SemiAutomaticClassificationPlugin", "9 (Landsat 8)")) self.checkBox_band_7.setText(_translate("SemiAutomaticClassificationPlugin", "7 (Landsat 1-8)")) self.tabWidget_3.setTabText(self.tabWidget_3.indexOf(self.tab_options), _translate("SemiAutomaticClassificationPlugin", "Download options")) self.label_258.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body> Download</body></html>")) self.preprocess_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Preprocess images</body></html>")) self.preprocess_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Preprocess images")) self.load_in_QGIS_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Load images in QGIS after download</body></html>")) self.load_in_QGIS_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Load bands in QGIS")) self.download_if_preview_in_legend_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Download images from list only if the corresponding previews are loaded in QGIS</body></html>")) self.download_if_preview_in_legend_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Only if preview in Layers")) self.export_links_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export download links to a text file</body></html>")) self.export_links_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.download_images_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.download_images_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.virtual_download_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, download as virtual file only the portion of the image defined by search coordinates (does not work for all the sources)</body></html>")) self.virtual_download_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Virtual download")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_download_products), _translate("SemiAutomaticClassificationPlugin", "Download products")) self.label_36.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing Landsat bands")) self.label_37.setText(_translate("SemiAutomaticClassificationPlugin", " Landsat conversion to TOA reflectance and brightness temperature")) self.celsius_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable calculation of temperature in Celsius from thermal band</body></html>")) self.celsius_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", " Brightness temperature in Celsius")) self.DOS1_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the DOS1 atmospheric correction (thermal band is not corrected)</body></html>")) self.DOS1_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.nodata_spinBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.nodata_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_41.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select MTL file (if not in Landsat directory)</body></html>")) self.label_41.setText(_translate("SemiAutomaticClassificationPlugin", "Select MTL file")) self.toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a directory</body></html>")) self.toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.pansharpening_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Perform pan-sharpening (Brovey Transform)</body></html>")) self.pansharpening_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Perform pansharpening (Landsat 7 or 8)")) self.create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_1.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.toolButton_directoryInput_MTL.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.landsat_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit metadata</body></html>")) item = self.landsat_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.landsat_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "RADIANCE_MULT")) item = self.landsat_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "RADIANCE_ADD")) item = self.landsat_tableWidget.horizontalHeaderItem(3) item.setText(_translate("SemiAutomaticClassificationPlugin", "REFLECTANCE_MULT")) item = self.landsat_tableWidget.horizontalHeaderItem(4) item.setText(_translate("SemiAutomaticClassificationPlugin", "REFLECTANCE_ADD")) item = self.landsat_tableWidget.horizontalHeaderItem(5) item.setText(_translate("SemiAutomaticClassificationPlugin", "RADIANCE_MAXIMUM")) item = self.landsat_tableWidget.horizontalHeaderItem(6) item.setText(_translate("SemiAutomaticClassificationPlugin", "REFLECTANCE_MAXIMUM")) item = self.landsat_tableWidget.horizontalHeaderItem(7) item.setText(_translate("SemiAutomaticClassificationPlugin", "K1_CONSTANT")) item = self.landsat_tableWidget.horizontalHeaderItem(8) item.setText(_translate("SemiAutomaticClassificationPlugin", "K2_CONSTANT")) item = self.landsat_tableWidget.horizontalHeaderItem(9) item.setText(_translate("SemiAutomaticClassificationPlugin", "LMAX")) item = self.landsat_tableWidget.horizontalHeaderItem(10) item.setText(_translate("SemiAutomaticClassificationPlugin", "LMIN")) item = self.landsat_tableWidget.horizontalHeaderItem(11) item.setText(_translate("SemiAutomaticClassificationPlugin", "QCALMAX")) item = self.landsat_tableWidget.horizontalHeaderItem(12) item.setText(_translate("SemiAutomaticClassificationPlugin", "QCALMIN")) self.pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.satellite_label.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.satellite_label_3.setText(_translate("SemiAutomaticClassificationPlugin", "Sun elevation")) self.date_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>DATE ACQUIRED</body></html>")) self.satellite_label_2.setText(_translate("SemiAutomaticClassificationPlugin", "Date (YYYY-MM-DD)")) self.satellite_label_4.setText(_translate("SemiAutomaticClassificationPlugin", "Earth sun distance")) self.sun_elev_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>SUN ELEVATION</body></html>")) self.earth_sun_dist_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Earth sun distance</body></html>")) self.label_74.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Satellite (e.g. LANDSAT8)</body></html>")) self.label_161.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.landsat_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.landsat_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Landsat), _translate("SemiAutomaticClassificationPlugin", "Landsat")) self.S1_label_95.setText(_translate("SemiAutomaticClassificationPlugin", "Select SNAP xml graph (optional)")) self.S1_toolButton_directoryInput_xml.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.S1_label_97.setText(_translate("SemiAutomaticClassificationPlugin", "Polarization")) self.VH_checkBox_S1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select VH polarization</body></html>")) self.VH_checkBox_S1.setText(_translate("SemiAutomaticClassificationPlugin", "VH")) self.VV_checkBox_S1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select VV polarization</body></html>")) self.VV_checkBox_S1.setText(_translate("SemiAutomaticClassificationPlugin", "VV")) self.label_209.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-1 conversion (ESA SNAP software required)")) self.S1_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.S1_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_6.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.S1_toolButton_fileInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.label_207.setText(_translate("SemiAutomaticClassificationPlugin", "Sentinel-1 file")) self.projection_checkBox_S1.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, project the output to the same projection as selected Band set</body></html>")) self.projection_checkBox_S1.setText(_translate("SemiAutomaticClassificationPlugin", "Raster projection as Band set")) self.band_set_comb_spinBox_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.convert_to_db_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, convert to dB</body></html>")) self.convert_to_db_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", " convert to dB")) self.S1_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.S1_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.S1_nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.label_210.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion_6.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.sentinel1_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.sentinel1_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Sentinel1), _translate("SemiAutomaticClassificationPlugin", "Sentinel-1")) self.label_90.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing Sentinel-2 bands")) self.S2_toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a directory</body></html>")) self.S2_toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.DOS1_checkBox_S2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the DOS1 atmospheric correction</body></html>")) self.DOS1_checkBox_S2.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.S2_nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.S2_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.S2_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_91.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-2 conversion")) self.S2_label_93.setText(_translate("SemiAutomaticClassificationPlugin", "Select metadata file (MTD_MSI)")) self.S2_toolButton_directoryInput_xml2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.S2_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.S2_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.preprocess_b_1_9_10_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.preprocess_b_1_9_10_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Preprocess bands 1, 9, 10")) self.S2_satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Satellite (e.g. Sentinel-2A)</body></html>")) self.satellite_label_5.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.satellite_label_6.setText(_translate("SemiAutomaticClassificationPlugin", "Product")) self.S2_product_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Satellite (e.g. Sentinel-2A)</body></html>")) self.label_92.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.date_lineEdit_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>DATE ACQUIRED</body></html>")) self.satellite_label_15.setText(_translate("SemiAutomaticClassificationPlugin", "Date (YYYY-MM-DD)")) self.sentinel_2_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit metadata</body></html>")) item = self.sentinel_2_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.sentinel_2_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Quantification value")) item = self.sentinel_2_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "Solar irradiance")) self.S2_pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.S2_pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_162.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion_2.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.sentinel2_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.sentinel2_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Sentinel2), _translate("SemiAutomaticClassificationPlugin", "Sentinel-2")) self.S2_nodata_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.S3_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.S3_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_109.setText(_translate("SemiAutomaticClassificationPlugin", " Sentinel-3 conversion")) self.S3_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.S3_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.label_106.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing Sentinel-3 bands")) self.S3_toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a directory</body></html>")) self.S3_toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.DOS1_checkBox_S3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the DOS1 atmospheric correction</body></html>")) self.DOS1_checkBox_S3.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.add_new_bandset_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.sentinel_3_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit metadata</body></html>")) item = self.sentinel_3_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) self.S3_pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.S3_pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.S3_satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Satellite (e.g. Sentinel-3A)</body></html>")) self.satellite_label_12.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.satellite_label_14.setText(_translate("SemiAutomaticClassificationPlugin", "Product")) self.S3_product_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Satellite (e.g. Sentinel-3A)</body></html>")) self.label_115.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.label_181.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion_5.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.sentinel3_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.sentinel3_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_Sentinel3), _translate("SemiAutomaticClassificationPlugin", "Sentinel-3")) self.nodata_spinBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.nodata_checkBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_5.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.toolButton_directoryInput_ASTER.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.toolButton_directoryInput_ASTER.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.DOS1_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the DOS1 atmospheric correction (thermal band is not corrected)</body></html>")) self.DOS1_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", " Apply DOS1 atmospheric correction")) self.label_67.setText(_translate("SemiAutomaticClassificationPlugin", " ASTER conversion to TOA reflectance and brightness temperature")) self.label_55.setText(_translate("SemiAutomaticClassificationPlugin", "Select file ASTER L1T (.hdf)")) self.create_bandset_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.create_bandset_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_4.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.celsius_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable calculation of temperature in Celsius from thermal band</body></html>")) self.celsius_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", " Brightness temperature in Celsius")) self.ASTER_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit metadata</body></html>")) item = self.ASTER_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.ASTER_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "UnitConversionCoeff")) item = self.ASTER_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "PixelSize")) self.pushButton_remove_band_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.pushButton_remove_band_2.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.date_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>DATE ACQUIRED</body></html>")) self.earth_sun_dist_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Earth sun distance</body></html>")) self.satellite_label_9.setText(_translate("SemiAutomaticClassificationPlugin", "Earth sun \n" "distance")) self.satellite_label_8.setText(_translate("SemiAutomaticClassificationPlugin", "Date\n" " (YYYYMMDD)")) self.satellite_label_7.setText(_translate("SemiAutomaticClassificationPlugin", "Sun elevation")) self.sun_elev_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>SUN ELEVATION</body></html>")) self.ulm_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Upper left</body></html>")) self.satellite_label_10.setText(_translate("SemiAutomaticClassificationPlugin", "UTM zone")) self.utm_zone_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>UTM zone</body></html>")) self.satellite_label_11.setText(_translate("SemiAutomaticClassificationPlugin", "UPPERLEFTM")) self.satellite_label_17.setText(_translate("SemiAutomaticClassificationPlugin", "LOWERRIGHTM")) self.lrm_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Lower right</body></html>")) self.label_160.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.label_163.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion_3.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.aster_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.aster_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_ASTER), _translate("SemiAutomaticClassificationPlugin", "ASTER")) self.label_218.setText(_translate("SemiAutomaticClassificationPlugin", " MODIS conversion")) self.create_bandset_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.create_bandset_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.add_new_bandset_checkBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_5.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.label_219.setText(_translate("SemiAutomaticClassificationPlugin", "Select file MODIS (.hdf)")) self.toolButton_directoryInput_MODIS.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.toolButton_directoryInput_MODIS.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.nodata_spinBox_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.nodata_checkBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_7.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.reproject_modis_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reproject bands to WGS 84</body></html>")) self.reproject_modis_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Reproject to WGS 84")) self.MODIS_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit metadata</body></html>")) item = self.MODIS_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) item = self.MODIS_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "UnitConversionCoeff")) self.pushButton_remove_band_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.pushButton_remove_band_3.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.satellite_label_16.setText(_translate("SemiAutomaticClassificationPlugin", "Date (YYYY-MM-DD)")) self.MODIS_ID_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>DATE ACQUIRED</body></html>")) self.satellite_label_13.setText(_translate("SemiAutomaticClassificationPlugin", "ID")) self.MODIS_date_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>DATE ACQUIRED</body></html>")) self.label_220.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.label_221.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion_4.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.modis_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.modis_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_MODIS), _translate("SemiAutomaticClassificationPlugin", "MODIS")) self.label_142.setText(_translate("SemiAutomaticClassificationPlugin", " Convert vector to raster")) self.label_64.setText(_translate("SemiAutomaticClassificationPlugin", "Select the vector")) self.vector_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the vector</body></html>")) self.toolButton_reload_16.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_16.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.field_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the value field of the vector</body></html>")) self.field_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use the value field of the vector")) self.field_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the value field</body></html>")) self.constant_value_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use constant value</body></html>")) self.constant_value_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use constant value")) self.constant_value_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Value</body></html>")) self.label_157.setText(_translate("SemiAutomaticClassificationPlugin", "Select the type of conversion")) self.conversion_type_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the type of conversion</body></html>")) self.label_156.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference raster")) self.toolButton_reload_17.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_17.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.reference_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the reference raster</body></html>")) self.extent_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the same extent as reference raster</body></html>")) self.extent_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Same extent as reference raster")) self.label_167.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.convert_vector_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.convert_vector_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.vector_to_raster.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.vector_to_raster.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_spectral_distance), _translate("SemiAutomaticClassificationPlugin", "Vector to raster")) self.label_128.setText(_translate("SemiAutomaticClassificationPlugin", " Clip band set")) self.nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.band_set_comb_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_251.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_62.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.label_16.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.output_clip_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Output name prefix</body></html>")) self.output_clip_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "clip")) self.LX_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Lower right X</body></html>")) self.LX_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X")) self.UX_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Upper left X</body></html>")) self.UX_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "X")) self.UY_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Upper left Y</body></html>")) self.UY_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y")) self.LY_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Lower right Y</body></html>")) self.LY_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Y")) self.label_12.setText(_translate("SemiAutomaticClassificationPlugin", "LR")) self.selectUL_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set area in the map</body></html>")) self.label_29.setText(_translate("SemiAutomaticClassificationPlugin", " Clip coordinates")) self.show_area_radioButton_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Show / hide area</body></html>")) self.show_area_radioButton_3.setText(_translate("SemiAutomaticClassificationPlugin", "Show")) self.label_11.setText(_translate("SemiAutomaticClassificationPlugin", "UL")) self.shapefile_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the vector for clipping</body></html>")) self.shapefile_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use vector boundaries for clipping rasters</body></html>")) self.shapefile_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use vector for clipping")) self.toolButton_reload_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_8.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.temporary_ROI_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use temporary ROI boundaries for clipping rasters</body></html>")) self.temporary_ROI_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use temporary ROI for clipping")) self.vector_field_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, clip iterating through each vector polygon and add field value to the output name</body></html>")) self.vector_field_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use vector field for output name")) self.class_field_comboBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the vector field</body></html>")) self.label_164.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.clip_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.clip_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.clip_multiple_rasters.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.clip_multiple_rasters.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_clip), _translate("SemiAutomaticClassificationPlugin", "Clip multiple rasters")) self.band_set_comb_spinBox_14.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_264.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_249.setText(_translate("SemiAutomaticClassificationPlugin", " Reproject raster bands")) self.raster_align_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the reference raster</body></html>")) self.use_align_raster_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Align to raster</body></html>")) self.use_align_raster_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Align to raster")) self.toolButton_reload_25.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_25.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.same_extent_raster_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Keep the same extent as the reference raster</body></html>")) self.same_extent_raster_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "same extent as reference")) self.epsg_code_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>EPSG value</body></html>")) self.use_epsg_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use EPSG value</body></html>")) self.use_epsg_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use EPSG code")) self.label_267.setText(_translate("SemiAutomaticClassificationPlugin", " Y resolution")) self.label_266.setText(_translate("SemiAutomaticClassificationPlugin", " X resolution")) self.x_resolution_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>X resolution</body></html>")) self.y_resolution_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Y resolution</body></html>")) self.resample_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, new pixel size is original pixel size times this factor</body></html>")) self.resample_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Resample pixel factor")) self.resample_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Resample factor</body></html>")) self.resample_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "1")) self.label_269.setText(_translate("SemiAutomaticClassificationPlugin", "Resampling method")) self.resampling_method_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the resampling method</body></html>")) self.resampling_method_comboBox.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "nearest_neighbour")) self.resampling_method_comboBox.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "average")) self.resampling_method_comboBox.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "sum")) self.resampling_method_comboBox.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "maximum")) self.resampling_method_comboBox.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "minimum")) self.resampling_method_comboBox.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "mode")) self.resampling_method_comboBox.setItemText(6, _translate("SemiAutomaticClassificationPlugin", "median")) self.resampling_method_comboBox.setItemText(7, _translate("SemiAutomaticClassificationPlugin", "first_quartile")) self.resampling_method_comboBox.setItemText(8, _translate("SemiAutomaticClassificationPlugin", "third_quartile")) self.label_270.setText(_translate("SemiAutomaticClassificationPlugin", "Output type")) self.raster_type_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a type</body></html>")) self.raster_type_combo_2.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Auto")) self.raster_type_combo_2.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Float32")) self.raster_type_combo_2.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "Int32")) self.raster_type_combo_2.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "UInt32")) self.raster_type_combo_2.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "Int16")) self.raster_type_combo_2.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "UInt16")) self.raster_type_combo_2.setItemText(6, _translate("SemiAutomaticClassificationPlugin", "Byte")) self.change_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, change output NoData value</body></html>")) self.change_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Change output NoData value")) self.nodata_spinBox_14.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value of the output raster</body></html>")) self.label_265.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.reproj_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Output name prefix</body></html>")) self.reproj_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "reproj")) self.label_263.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.reproject_raster_bands.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.reproject_raster_bands.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.reproject_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.reproject_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_reproject_bands), _translate("SemiAutomaticClassificationPlugin", "Reproject raster bands")) self.raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the image to be split</body></html>")) self.label_57.setText(_translate("SemiAutomaticClassificationPlugin", " Split raster bands")) self.label_50.setText(_translate("SemiAutomaticClassificationPlugin", "Select a multiband raster")) self.toolButton_reload_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_9.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_165.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_61.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Output name prefix</body></html>")) self.output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "split")) self.split_raster_bands.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.split_raster_bands.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.split_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.split_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_split_raster), _translate("SemiAutomaticClassificationPlugin", "Split raster bands")) self.label_252.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.stack_raster_bands.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.stack_raster_bands.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.stack_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.stack_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_223.setText(_translate("SemiAutomaticClassificationPlugin", " Stack band set")) self.label_226.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_stack_bands), _translate("SemiAutomaticClassificationPlugin", "Stack raster bands")) self.label_134.setText(_translate("SemiAutomaticClassificationPlugin", " Mosaic of band sets")) self.label_135.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.nodata_checkBox_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_9.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.mosaic_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Output name prefix</body></html>")) self.mosaic_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "mosaic")) self.label_144.setText(_translate("SemiAutomaticClassificationPlugin", "Band set list")) self.mosaic_band_sets_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>List of band set numbers separated by comma , Use * for selecting all the band sets</body></html>")) self.mosaic_band_sets_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "1, 2")) self.mosaic_virtual_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, output bands are virtual rasters</body></html>")) self.mosaic_virtual_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create virtual raster output")) self.mosaic_bandsets_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.mosaic_bandsets_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.mosaic_bandsets.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.mosaic_bandsets.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_182.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_mosaic_band_sets), _translate("SemiAutomaticClassificationPlugin", "Mosaic band sets")) self.label_260.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.classification_name_combo_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification</body></html>")) self.cloud_mask_classes_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter class values separated by , or -</body></html>")) self.label_203.setText(_translate("SemiAutomaticClassificationPlugin", "Mask class values")) self.label_186.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.toolButton_reload_23.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_23.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_140.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.mask_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Output name prefix</body></html>")) self.mask_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "mask")) self.cloud_buffer_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Size in pixels</body></html>")) self.cloud_buffer_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, create a buffer for class values</body></html>")) self.cloud_buffer_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use buffer of pixel size")) self.nodata_spinBox_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.label_141.setText(_translate("SemiAutomaticClassificationPlugin", "Output NoData value")) self.cloud_mask_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.cloud_mask_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.cloud_masking.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.cloud_masking.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_185.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_138.setText(_translate("SemiAutomaticClassificationPlugin", " Mask of band set")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_cloud_mask), _translate("SemiAutomaticClassificationPlugin", "Cloud masking")) self.GOES_nodata_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>No data value</body></html>")) self.GOES_nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.GOES_nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.label_273.setText(_translate("SemiAutomaticClassificationPlugin", " GOES conversion")) self.GOES_create_bandset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create the Band set automatically and use the checked Band set tools</body></html>")) self.GOES_create_bandset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create Band set and use Band set tools")) self.label_274.setText(_translate("SemiAutomaticClassificationPlugin", "Directory containing GOES bands")) self.GOES_toolButton_directoryInput.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a directory</body></html>")) self.GOES_toolButton_directoryInput.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_new_bandset_checkBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a new band set where bands are added</body></html>")) self.add_new_bandset_checkBox_7.setText(_translate("SemiAutomaticClassificationPlugin", "Add bands in a new Band set")) self.GOES_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit metadata</body></html>")) item = self.GOES_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band")) self.GOES_pushButton_remove_band.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.GOES_pushButton_remove_band.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_277.setText(_translate("SemiAutomaticClassificationPlugin", "Metadata")) self.satellite_label_20.setText(_translate("SemiAutomaticClassificationPlugin", "Satellite")) self.GOES_satellite_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Satellite (e.g. Sentinel-3A)</body></html>")) self.label_278.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pushButton_Conversion_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pushButton_Conversion_8.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.goes_conversion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.goes_conversion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_GOES), _translate("SemiAutomaticClassificationPlugin", "GOES")) self.label_283.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_281.setText(_translate("SemiAutomaticClassificationPlugin", "Matrix file (optional)")) self.toolButton_input_matrix.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a file</body></html>")) self.label_279.setText(_translate("SemiAutomaticClassificationPlugin", "Output name prefix")) self.neighbor_output_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Output name prefix</body></html>")) self.neighbor_output_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "neighbor")) self.neighbor_virtual_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, output bands are virtual rasters</body></html>")) self.neighbor_virtual_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create virtual raster output")) self.neighbor_pixels.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.neighbor_pixels.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.class_neighbor_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.class_neighbor_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_286.setText(_translate("SemiAutomaticClassificationPlugin", " Neighbor pixels")) self.statistic_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter a value</body></html>")) self.statistic_name_combobox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a statistic</body></html>")) self.label_284.setText(_translate("SemiAutomaticClassificationPlugin", "Select a statistic")) self.label_285.setText(_translate("SemiAutomaticClassificationPlugin", " Statistic")) self.label_282.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_280.setText(_translate("SemiAutomaticClassificationPlugin", "Neighbor distance in pixels")) self.band_set_comb_spinBox_15.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.class_neighbor_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Distance in pixels</body></html>")) self.circular_structure_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, neighbor pixels are calculated inside a circle of radius equal to the distance in pixels</body></html>")) self.circular_structure_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Circular")) self.tabWidget_preprocessing.setTabText(self.tabWidget_preprocessing.indexOf(self.tab_neighbor_pixels), _translate("SemiAutomaticClassificationPlugin", "Neighbor pixels")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_preprocessing), _translate("SemiAutomaticClassificationPlugin", "Preprocessing")) self.label_253.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateBandSetComb_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.calculateBandSetComb_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.band_combination.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.band_combination.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_250.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set (of classifications)")) self.band_set_comb_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_72.setText(_translate("SemiAutomaticClassificationPlugin", " Combination of band values")) self.toolBox_band_set_combination.setItemText(self.toolBox_band_set_combination.indexOf(self.page_29), _translate("SemiAutomaticClassificationPlugin", "Input")) self.band_set_comb_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Courier 10 Pitch\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" " </body></html>")) self.toolBox_band_set_combination.setItemText(self.toolBox_band_set_combination.indexOf(self.page_30), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_bandset_combination_2), _translate("SemiAutomaticClassificationPlugin", "Band combination")) self.label_58.setText(_translate("SemiAutomaticClassificationPlugin", " Principal Components Analysis of band set")) self.nodata_checkBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_4.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.num_comp_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, calculate this number of components only</body></html>")) self.num_comp_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Number of components")) self.nodata_spinBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.pca_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.pca_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_254.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.pca_components_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Number of components</body></html>")) self.label_166.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.pca.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.pca.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_PCA.setItemText(self.toolBox_PCA.indexOf(self.page_16), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_PCA.setItemText(self.toolBox_PCA.indexOf(self.page_17), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.PCA_tab), _translate("SemiAutomaticClassificationPlugin", "PCA")) self.label_78.setText(_translate("SemiAutomaticClassificationPlugin", " Clustering of band set")) self.isodata_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use ISODATA</body></html>")) self.isodata_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "ISODATA")) self.band_set_comb_spinBox_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_230.setText(_translate("SemiAutomaticClassificationPlugin", "Method ")) self.label_255.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.kmeans_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use K-means</body></html>")) self.kmeans_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "&K-means ")) self.label_225.setText(_translate("SemiAutomaticClassificationPlugin", "Max number of iterations")) self.thresh_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Threshold</body></html>")) self.std_dev_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Threshold</body></html>")) self.kmean_threshold_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, for K-means: iteration is terminated if distance is lower than threshold; for ISODATA: signatures are merged if distance is greater than threshold</body></html>")) self.kmean_threshold_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Distance threshold")) self.nodata_spinBox_9.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.kmeans_iter_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the maximum number of iterations</body></html>")) self.label_228.setText(_translate("SemiAutomaticClassificationPlugin", "ISODATA max standard deviation")) self.nodata_checkBox_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_8.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.kmeans_classes_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Number of classes</body></html>")) self.label_224.setText(_translate("SemiAutomaticClassificationPlugin", "Number of classes")) self.label_229.setText(_translate("SemiAutomaticClassificationPlugin", "ISODATA minimum class size in pixels")) self.min_size_class_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Minimum class size in pixels</body></html>")) self.min_distance_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use Minimum Distance algorithm</body></html>")) self.min_distance_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Minimum Distance")) self.kmean_save_siglist_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, save the resulting signatures to Signature list</body></html>")) self.kmean_save_siglist_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save resulting signatures to Signature list")) self.label_227.setText(_translate("SemiAutomaticClassificationPlugin", "Distance algorithm")) self.label_104.setText(_translate("SemiAutomaticClassificationPlugin", " Seed signatures")) self.kmean_siglist_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use signatures in Signature list as seed signatures</body></html>")) self.kmean_siglist_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Use Signature list as seed signatures")) self.kmean_randomsiglist_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, calculate seed signatures from random pixels</body></html>")) self.kmean_randomsiglist_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Use random seed signatures")) self.kmean_minmax_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, calculate seed signatures from minimum and maximum values of bands</body></html>")) self.kmean_minmax_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Seed signatures from band values")) self.spectral_angle_map_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use Spectral Angle Mapping algorithm (only for K-means)</body></html>")) self.spectral_angle_map_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Spectral Angle Mapping")) self.label_179.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.kmeans_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.kmeans_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.clustering.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.clustering.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_kmeans.setItemText(self.toolBox_kmeans.indexOf(self.page_18), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_kmeans.setItemText(self.toolBox_kmeans.indexOf(self.page_23), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_kmeans), _translate("SemiAutomaticClassificationPlugin", "Clustering")) self.min_distance_radioButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use Minimum Distance algorithm</body></html>")) self.min_distance_radioButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Minimum Distance")) self.label_231.setText(_translate("SemiAutomaticClassificationPlugin", "Distance algorithm")) self.spectral_angle_map_radioButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, use Spectral Angle Mapping algorithm (only for K-means)</body></html>")) self.spectral_angle_map_radioButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Spectral Angle Mapping")) self.label_137.setText(_translate("SemiAutomaticClassificationPlugin", "Spectral distance of band sets")) self.distance_threshold_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, calculate a raster of changes where distance is above threshold</body></html>")) self.distance_threshold_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Distance threshold")) self.thresh_doubleSpinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Threshold</body></html>")) self.label_256.setText(_translate("SemiAutomaticClassificationPlugin", "Select first input band set")) self.band_set_comb_spinBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_257.setText(_translate("SemiAutomaticClassificationPlugin", "Select second input band set")) self.band_set_comb_spinBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_183.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.spectral_distance_bandsets_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.spectral_distance_bandsets_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.spectral_distance.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.spectral_distance.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_spectral_dist), _translate("SemiAutomaticClassificationPlugin", "Spectral distance")) self.label_32.setText(_translate("SemiAutomaticClassificationPlugin", "Use")) self.macroclass_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the ID of macroclasses for the classification</body></html>")) self.macroclass_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) self.class_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the ID of classes for the classification</body></html>")) self.class_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) self.algorithm_weight_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open tab Algorithm band weight</body></html>")) self.algorithm_weight_button.setText(_translate("SemiAutomaticClassificationPlugin", "W")) self.algorithm_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a classification algorithm</body></html>")) self.algorithm_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Minimum Distance")) self.algorithm_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Maximum Likelihood")) self.algorithm_combo.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "Spectral Angle Mapping")) self.band_set_comb_spinBox_12.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_261.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_240.setText(_translate("SemiAutomaticClassificationPlugin", " Algorithm")) self.alg_threshold_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set a classification threshold for all signatures</body></html>")) self.algorithm_threshold_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open tab Signature threshold</body></html>")) self.algorithm_threshold_button.setText(_translate("SemiAutomaticClassificationPlugin", "W")) self.label_234.setText(_translate("SemiAutomaticClassificationPlugin", "Threshold")) self.label_243.setText(_translate("SemiAutomaticClassificationPlugin", "Classification")) self.LC_signature_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the Land Cover Signature Classification is used</body></html>")) self.LC_signature_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "LCS")) self.label_235.setText(_translate("SemiAutomaticClassificationPlugin", "Use")) self.LC_signature_button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open tab LCS threshold</body></html>")) self.LCS_leave_unclassified_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the selected Algorithm is used only for class overlapping pixels of the Land Cover Signature Classification</body></html>")) self.LCS_leave_unclassified_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "only overlap")) self.label_241.setText(_translate("SemiAutomaticClassificationPlugin", " Land Cover Signature Classification")) self.LCS_class_algorithm_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the selected Algorithm is used for unclassified pixels of the Land Cover Signature Classification</body></html>")) self.LCS_class_algorithm_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Algorithm")) self.label_242.setText(_translate("SemiAutomaticClassificationPlugin", " Classification output")) self.resetQmlButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.resetQmlButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_238.setText(_translate("SemiAutomaticClassificationPlugin", "Load qml style")) self.qml_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select qml style</body></html>")) self.qml_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.qml_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Qml file path</body></html>")) self.mask_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select an optional mask vector</body></html>")) self.mask_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Apply mask")) self.resetMaskButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.resetMaskButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.mask_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Path of the optional mask shapefile</body></html>")) self.vector_output_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Create a classification shapefile after the classification process</body></html>")) self.vector_output_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create vector")) self.report_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Calculate a classification report</body></html>")) self.report_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Classification report")) self.alg_files_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If enabled, the rasters calculated by the classification algorithm (one per signature) are saved along with the classification</body></html>")) self.alg_files_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save algorithm files")) self.button_classification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.button_classification.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_239.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.classification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.classification.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_classification), _translate("SemiAutomaticClassificationPlugin", "Classification")) self.label_233.setText(_translate("SemiAutomaticClassificationPlugin", "Use")) self.macroclass_checkBox_rf.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the ID of macroclasses for the classification</body></html>")) self.macroclass_checkBox_rf.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID")) self.class_checkBox_rf.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the ID of classes for the classification</body></html>")) self.class_checkBox_rf.setText(_translate("SemiAutomaticClassificationPlugin", "C ID")) self.band_set_comb_spinBox_13.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_262.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.label_245.setText(_translate("SemiAutomaticClassificationPlugin", "Random Forest classification (ESA SNAP software required)")) self.number_trees_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Number of trees</body></html>")) self.label_237.setText(_translate("SemiAutomaticClassificationPlugin", "Number of trees")) self.number_training_samples_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Number of training samples</body></html>")) self.label_236.setText(_translate("SemiAutomaticClassificationPlugin", "Number of training samples ")) self.evaluate_classifier_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Evaluate classifier</body></html>")) self.evaluate_classifier_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Evaluate classifier")) self.evaluate_feature_power_set_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, evaluate feature power set</body></html>")) self.evaluate_feature_power_set_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Evaluate feature power set")) self.label_248.setText(_translate("SemiAutomaticClassificationPlugin", "Max")) self.rf_power_min_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Minumum power</body></html>")) self.label_247.setText(_translate("SemiAutomaticClassificationPlugin", "Min")) self.rf_power_max_SpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Maximum power</body></html>")) self.save_classifier_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, save classifier</body></html>")) self.save_classifier_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save classifier")) self.label_244.setText(_translate("SemiAutomaticClassificationPlugin", "Load classifier")) self.classifier_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a previosly saved classifier</body></html>")) self.classifier_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.classifier_lineEdit_.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Classifier file path</body></html>")) self.resetClassifierButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.resetClassifierButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.button_random_forest.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.button_random_forest.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_246.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.random_forest.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.random_forest.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_random_forest.setItemText(self.toolBox_random_forest.indexOf(self.page_21), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_random_forest.setItemText(self.toolBox_random_forest.indexOf(self.page_25), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_4.setTabText(self.tabWidget_4.indexOf(self.tab_random_forest), _translate("SemiAutomaticClassificationPlugin", "Random forest")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_band_processing), _translate("SemiAutomaticClassificationPlugin", "Band processing")) self.label_33.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification to assess")) self.label_34.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference vector or raster")) self.classification_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification to assess</body></html>")) self.buttonReload_shape_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.buttonReload_shape_4.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.toolButton_reload_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_4.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.reference_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the reference vector or raster</body></html>")) self.label_145.setText(_translate("SemiAutomaticClassificationPlugin", " Accuracy assessment")) self.label_82.setText(_translate("SemiAutomaticClassificationPlugin", "Vector field")) self.class_field_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the field of the classification code </body></html>")) self.nodata_checkBox_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_11.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_15.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.label_168.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateMatrix_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.calculateMatrix_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.accuracy.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.accuracy.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_accuracy.setItemText(self.toolBox_accuracy.indexOf(self.page_10), _translate("SemiAutomaticClassificationPlugin", "Input")) self.error_matrix_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Courier 10 Pitch\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" " </body></html>")) self.toolBox_accuracy.setItemText(self.toolBox_accuracy.indexOf(self.page_11), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_accuracy), _translate("SemiAutomaticClassificationPlugin", "Accuracy")) self.mask_unchanged_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If enabled, pixels having the same values in both classifications will be reported; if not enabled, 0 value is set for unchanged pixels</body></html>")) self.mask_unchanged_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Report unchanged pixels")) self.classification_reference_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the reference classification raster</body></html>")) self.label_40.setText(_translate("SemiAutomaticClassificationPlugin", "Select the new classification")) self.label_38.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference classification")) self.new_classification_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a new raster to be compared with the reference raster</body></html>")) self.toolButton_reload_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_5.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.toolButton_reload_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_6.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_116.setText(_translate("SemiAutomaticClassificationPlugin", " Land cover change")) self.label_169.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateLandCoverChange_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.calculateLandCoverChange_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.land_cover_change.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.land_cover_change.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_landCoverChange.setItemText(self.toolBox_landCoverChange.indexOf(self.page_12), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_landCoverChange.setItemText(self.toolBox_landCoverChange.indexOf(self.page_13), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_landCoverChange), _translate("SemiAutomaticClassificationPlugin", "Land cover change")) self.classification_report_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification raster</body></html>")) self.label_44.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.nodata_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the report</body></html>")) self.nodata_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.toolButton_reload_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_10.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_170.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculateReport_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.calculateReport_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_report.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.classification_report.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_148.setText(_translate("SemiAutomaticClassificationPlugin", " Classification report")) self.toolBox_class_report.setItemText(self.toolBox_class_report.indexOf(self.page_14), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_class_report.setItemText(self.toolBox_class_report.indexOf(self.page_15), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_class_report), _translate("SemiAutomaticClassificationPlugin", "Classification report")) self.label_187.setText(_translate("SemiAutomaticClassificationPlugin", " Cross classification")) self.nodata_checkBox_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_6.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_7.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.label_197.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.label_199.setText(_translate("SemiAutomaticClassificationPlugin", "Vector field")) self.class_field_comboBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the vector field</body></html>")) self.toolButton_reload_21.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_21.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.classification_name_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification</body></html>")) self.buttonReload_shape_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.buttonReload_shape_5.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.reference_name_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the reference vector or raster</body></html>")) self.label_198.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference vector or raster")) self.label_200.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.calculatecrossClass_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.calculatecrossClass_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.cross_classification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.cross_classification.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_cross_classification.setItemText(self.toolBox_cross_classification.indexOf(self.page_19), _translate("SemiAutomaticClassificationPlugin", "Input")) self.cross_matrix_textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Courier 10 Pitch\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" " </body></html>")) self.toolBox_cross_classification.setItemText(self.toolBox_cross_classification.indexOf(self.page_22), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_cross_classification), _translate("SemiAutomaticClassificationPlugin", "Cross classification")) self.label_188.setText(_translate("SemiAutomaticClassificationPlugin", " Class signature")) self.classification_name_combo_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification</body></html>")) self.label_201.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.toolButton_reload_22.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_22.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_259.setText(_translate("SemiAutomaticClassificationPlugin", "Select input band set")) self.band_set_comb_spinBox_8.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band set number</body></html>")) self.label_184.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.class_signature_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.class_signature_Button.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.class_signature_save_siglist_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, save the resulting signatures to Signature list</body></html>")) self.class_signature_save_siglist_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Save resulting signatures to Signature list")) self.class_signature.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.class_signature.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolBox_class_signature.setItemText(self.toolBox_class_signature.indexOf(self.page_20), _translate("SemiAutomaticClassificationPlugin", "Input")) self.toolBox_class_signature.setItemText(self.toolBox_class_signature.indexOf(self.page_24), _translate("SemiAutomaticClassificationPlugin", "Output")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_class_signature), _translate("SemiAutomaticClassificationPlugin", "Class signature")) self.label_189.setText(_translate("SemiAutomaticClassificationPlugin", " Classification to vector")) self.label_63.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.classification_vector_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification raster</body></html>")) self.toolButton_reload_11.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_11.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.class_macroclass_comboBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the code field</body></html>")) self.class_macroclass_comboBox.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "C_ID")) self.class_macroclass_comboBox.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "MC_ID")) self.use_class_code_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the codes from Signature list table for vector symbology</body></html>")) self.use_class_code_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use code from Signature list")) self.label_49.setText(_translate("SemiAutomaticClassificationPlugin", " Symbology")) self.dissolve_output_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the polygons are dissolved to avoid discontinuity between processed blocks (slower)</body></html>")) self.dissolve_output_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Dissolve output")) self.convert_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.convert_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_171.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.classification_to_vector.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.classification_to_vector.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_class_to_vector), _translate("SemiAutomaticClassificationPlugin", "Classification to vector")) self.label_65.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.reclassification_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification raster</body></html>")) self.toolButton_reload_12.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_12.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_190.setText(_translate("SemiAutomaticClassificationPlugin", " Reclassification")) self.calculate_unique_values_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Calculate unique values</body></html>")) self.CID_MCID_code_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable this for reclassification from C ID to MC ID; if checked, unique values are calculated from the Signature list, setting old value C ID and new value MC ID</body></html>")) self.CID_MCID_code_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "calculate C ID to MC ID values")) self.label_98.setText(_translate("SemiAutomaticClassificationPlugin", "Calculate unique values")) self.label_54.setText(_translate("SemiAutomaticClassificationPlugin", " Values")) self.incremental_new_values_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set incremental new values</body></html>")) self.label_271.setText(_translate("SemiAutomaticClassificationPlugin", "Incremental new values")) self.reclass_values_tableWidget.setSortingEnabled(False) item = self.reclass_values_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Old value")) item = self.reclass_values_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "New value")) self.add_value_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add row</body></html>")) self.add_value_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.remove_row_pushButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_row_pushButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.import_reclass_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import reclassification table from text file</body></html>")) self.import_reclass_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.export_reclass_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export reclassification table to text file</body></html>")) self.export_reclass_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.apply_symbology_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the codes from Signature list table for vector symbology</body></html>")) self.apply_symbology_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use code from Signature list")) self.class_macroclass_comboBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the code field</body></html>")) self.class_macroclass_comboBox_2.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "MC_ID")) self.class_macroclass_comboBox_2.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "C_ID")) self.label_51.setText(_translate("SemiAutomaticClassificationPlugin", " Symbology")) self.label_172.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.reclassify_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.reclassify_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.reclassification.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.reclassification.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_reclassification), _translate("SemiAutomaticClassificationPlugin", "Reclassification")) self.label_193.setText(_translate("SemiAutomaticClassificationPlugin", " Edit raster")) self.undo_edit_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Undo edit (only for ROI polygons)</body></html>")) self.undo_edit_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_173.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.label_66.setText(_translate("SemiAutomaticClassificationPlugin", "Select the input raster")) self.edit_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the raster to edit</body></html>")) self.toolButton_reload_14.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_14.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.use_constant_val_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use constant value</body></html>")) self.use_constant_val_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use constant value")) self.value_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Value</body></html>")) self.use_expression_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use expression</body></html>")) self.use_expression_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use expression")) self.expression_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter expression</body></html>")) self.expression_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "where(raster == 1, 2, raster)")) self.label_81.setText(_translate("SemiAutomaticClassificationPlugin", " Edit raster values")) self.use_field_vector_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Use the value field of the vector</body></html>")) self.use_field_vector_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use the value field of the vector")) self.field_comboBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the value field</body></html>")) self.edit_val_use_vector_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit values using a vector</body></html>")) self.edit_val_use_vector_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", " Edit values using a vector")) self.vector_name_combo_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the vector</body></html>")) self.toolButton_reload_20.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_20.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.edit_val_use_ROI_radioButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Edit values using temporary ROIs</body></html>")) self.edit_val_use_ROI_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", " Edit values using ROI polygons")) self.label_158.setText(_translate("SemiAutomaticClassificationPlugin", " Edit options")) self.raster_set_value_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.raster_set_value_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.edit_raster_using_vector.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.edit_raster_using_vector.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab), _translate("SemiAutomaticClassificationPlugin", "Edit raster")) self.label_70.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.sieve_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification</body></html>")) self.toolButton_reload_15.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_15.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_133.setText(_translate("SemiAutomaticClassificationPlugin", "Size threshold")) self.sieve_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Size threshold in pixels</body></html>")) self.label_136.setText(_translate("SemiAutomaticClassificationPlugin", "Pixel connection")) self.sieve_connection_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Pixel connection</body></html>")) self.sieve_connection_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "4")) self.sieve_connection_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "8")) self.label_174.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.sieve_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.sieve_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_sieve.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.classification_sieve.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.label_195.setText(_translate("SemiAutomaticClassificationPlugin", " Classification sieve")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_sieve), _translate("SemiAutomaticClassificationPlugin", "Classification sieve")) self.label_202.setText(_translate("SemiAutomaticClassificationPlugin", " Classification erosion")) self.label_146.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.erosion_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification</body></html>")) self.toolButton_reload_18.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_18.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_149.setText(_translate("SemiAutomaticClassificationPlugin", "Size in pixels")) self.erosion_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Size in pixels</body></html>")) self.circular_structure_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, neighbor pixels are calculated inside a circle of radius equal to the distance in pixels</body></html>")) self.circular_structure_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Circular")) self.label_151.setText(_translate("SemiAutomaticClassificationPlugin", "Class values")) self.erosion_classes_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter class values separated by , or -</body></html>")) self.label_175.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.class_erosion_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.class_erosion_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_erosion.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.classification_erosion.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_erosion), _translate("SemiAutomaticClassificationPlugin", "Classification erosion")) self.label_204.setText(_translate("SemiAutomaticClassificationPlugin", " Classification dilation")) self.label_152.setText(_translate("SemiAutomaticClassificationPlugin", "Select the classification")) self.dilation_raster_name_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the classification</body></html>")) self.toolButton_reload_19.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_19.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_153.setText(_translate("SemiAutomaticClassificationPlugin", "Size in pixels")) self.dilation_threshold_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Size in pixels</body></html>")) self.circular_structure_checkBox_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, neighbor pixels are calculated inside a circle of radius equal to the distance in pixels</body></html>")) self.circular_structure_checkBox_2.setText(_translate("SemiAutomaticClassificationPlugin", "Circular")) self.label_155.setText(_translate("SemiAutomaticClassificationPlugin", "Class values")) self.dilation_classes_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter class values separated by , or -</body></html>")) self.label_176.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.class_dilation_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.class_dilation_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.classification_dilation.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.classification_dilation.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_dilation), _translate("SemiAutomaticClassificationPlugin", "Classification dilation")) self.label_212.setText(_translate("SemiAutomaticClassificationPlugin", " Zonal stat rasters")) self.label_77.setText(_translate("SemiAutomaticClassificationPlugin", "Select the input raster")) self.classification_name_combo_5.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the raster to edit</body></html>")) self.toolButton_reload_24.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_24.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.nodata_checkBox_10.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_10.setText(_translate("SemiAutomaticClassificationPlugin", "Use value as NoData")) self.nodata_spinBox_12.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.class_field_comboBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the vector field</body></html>")) self.label_214.setText(_translate("SemiAutomaticClassificationPlugin", "Select the reference vector or raster")) self.buttonReload_shape_6.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.buttonReload_shape_6.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.label_213.setText(_translate("SemiAutomaticClassificationPlugin", "Vector field")) self.reference_name_combo_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select the reference vector or raster</body></html>")) self.statistic_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter a value</body></html>")) self.statistic_name_combobox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a statistic</body></html>")) self.label_232.setText(_translate("SemiAutomaticClassificationPlugin", "Select a statistic")) self.label_216.setText(_translate("SemiAutomaticClassificationPlugin", " Statistic")) self.zonal_stat_raster_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.zonal_stat_raster_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.label_215.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.zonal_stat_raster.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.zonal_stat_raster.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.tabWidget_2.setTabText(self.tabWidget_2.indexOf(self.tab_zonal_stats_rasters), _translate("SemiAutomaticClassificationPlugin", " Zonal stat rasters")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_postProcessing), _translate("SemiAutomaticClassificationPlugin", "Postprocessing")) self.toolButton_reload_13.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Refresh list</body></html>")) self.toolButton_reload_13.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.tableWidget_band_calc.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Band list</body></html>")) item = self.tableWidget_band_calc.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Variable")) item = self.tableWidget_band_calc.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Band name")) self.bandcalc_filter_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Filter</body></html>")) self.bandcalc_filter_lineEdit.setPlaceholderText(_translate("SemiAutomaticClassificationPlugin", "Filter")) self.label_71.setText(_translate("SemiAutomaticClassificationPlugin", " Band list")) self.plainTextEdit_calc.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter an expression (e.g. "raster1" + "raster2" )</body></html>")) self.toolButton_less.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Less than</body></html>")) self.toolButton_less.setText(_translate("SemiAutomaticClassificationPlugin", "<")) self.toolButton_greater.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Greater than</body></html>")) self.toolButton_greater.setText(_translate("SemiAutomaticClassificationPlugin", ">")) self.toolButton_lbracket.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open parenthesis</body></html>")) self.toolButton_lbracket.setText(_translate("SemiAutomaticClassificationPlugin", "(")) self.toolButton_rbracket.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Close parenthesis</body></html>")) self.toolButton_rbracket.setText(_translate("SemiAutomaticClassificationPlugin", ")")) self.toolButton_power.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Power</body></html>")) self.toolButton_power.setText(_translate("SemiAutomaticClassificationPlugin", "^")) self.toolButton_sqrt.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Square root</body></html>")) self.toolButton_sqrt.setText(_translate("SemiAutomaticClassificationPlugin", "√")) self.toolButton_plus.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Plus</body></html>")) self.toolButton_plus.setText(_translate("SemiAutomaticClassificationPlugin", "+")) self.toolButton_minus.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Minus</body></html>")) self.toolButton_minus.setText(_translate("SemiAutomaticClassificationPlugin", "-")) self.toolButton_product.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Multiplication</body></html>")) self.toolButton_product.setText(_translate("SemiAutomaticClassificationPlugin", "*")) self.toolButton_ratio.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Division</body></html>")) self.toolButton_ratio.setText(_translate("SemiAutomaticClassificationPlugin", "/")) self.toolButton_equal.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Equals</body></html>")) self.toolButton_equal.setText(_translate("SemiAutomaticClassificationPlugin", "==")) self.toolButton_unequal.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Not equals</body></html>")) self.toolButton_unequal.setText(_translate("SemiAutomaticClassificationPlugin", "!=")) self.toolButton_import_expression.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Open a text file to add custom functions</body></html>")) item = self.band_calc_function_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Functions")) self.band_calc_tabWidget.setTabText(self.band_calc_tabWidget.indexOf(self.tab_expression), _translate("SemiAutomaticClassificationPlugin", "Expression")) self.decision_rules_tableWidget.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter one or more rules separated by semicolon (e.g. "raster1" > 0; "raster2" > 0 )</body></html>")) item = self.decision_rules_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Value")) item = self.decision_rules_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Rule")) self.remove_rule_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Delete row</body></html>")) self.remove_rule_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.move_up_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted rule up</body></html>")) self.move_up_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.import_rules_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import rules from text file</body></html>")) self.import_rules_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_rules_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.clear_rules_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.add_rule_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Add row</body></html>")) self.add_rule_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.move_down_toolButton_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Move highlighted rule down</body></html>")) self.move_down_toolButton_2.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.export_rules_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export rules to text file</body></html>")) self.export_rules_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.band_calc_tabWidget.setTabText(self.band_calc_tabWidget.indexOf(self.tab_decision_rules), _translate("SemiAutomaticClassificationPlugin", "Decision rules")) self.nodata_as_value_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, input NoData pixels will be evaluated as regular values</body></html>")) self.nodata_as_value_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Input NoData \n" " as value")) self.nodata_checkBox_3.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, pixels equal to NoData value will be excluded from the output raster</body></html>")) self.nodata_checkBox_3.setText(_translate("SemiAutomaticClassificationPlugin", "Use value\n" "as NoData")) self.nodata_spinBox_13.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value</body></html>")) self.label_4.setText(_translate("SemiAutomaticClassificationPlugin", "Calculation\n" "data type")) self.calc_type_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a type</body></html>")) self.calc_type_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Float32")) self.calc_type_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Int32")) self.calc_type_combo.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "UInt32")) self.calc_type_combo.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "Int16")) self.calc_type_combo.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "UInt16")) self.calc_type_combo.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "Byte")) self.label_83.setText(_translate("SemiAutomaticClassificationPlugin", "Extent:")) self.intersection_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the extent of raster ouput equals the intersection of input rasters</body></html>")) self.intersection_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Intersection")) self.extent_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the extent of raster ouput equals the extent of selected raster</body></html>")) self.extent_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Same as")) self.raster_extent_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a raster</body></html>")) self.align_radioButton.setText(_translate("SemiAutomaticClassificationPlugin", "Align")) self.label_84.setText(_translate("SemiAutomaticClassificationPlugin", "Output raster")) self.raster_type_combo.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a type</body></html>")) self.raster_type_combo.setItemText(0, _translate("SemiAutomaticClassificationPlugin", "Float32")) self.raster_type_combo.setItemText(1, _translate("SemiAutomaticClassificationPlugin", "Int32")) self.raster_type_combo.setItemText(2, _translate("SemiAutomaticClassificationPlugin", "UInt32")) self.raster_type_combo.setItemText(3, _translate("SemiAutomaticClassificationPlugin", "Int16")) self.raster_type_combo.setItemText(4, _translate("SemiAutomaticClassificationPlugin", "UInt16")) self.raster_type_combo.setItemText(5, _translate("SemiAutomaticClassificationPlugin", "Byte")) self.label_268.setText(_translate("SemiAutomaticClassificationPlugin", "Output \n" "NoData value")) self.nodata_spinBox_4.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>NoData value of the output raster</body></html>")) self.nodata_mask_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, every NoData pixel in input will be NoData pixel in output</body></html>")) self.nodata_mask_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "NoData mask")) self.set_scale_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, set a scale</body></html>")) self.set_scale_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Set \n" "scale")) self.scale_doubleSpinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Scale</body></html>")) self.set_offset_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, set an offset</body></html>")) self.set_offset_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Set \n" "offset")) self.band_calc.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Function to Batch</body></html>")) self.band_calc.setText(_translate("SemiAutomaticClassificationPlugin", " BATCH")) self.toolButton_calculate.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.toolButton_calculate.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_band_calc), _translate("SemiAutomaticClassificationPlugin", "Band calc")) self.label_73.setText(_translate("SemiAutomaticClassificationPlugin", "Batch")) self.plainTextEdit_batch.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enter a batch function</body></html>")) self.export_batch_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export batch to text file</body></html>")) self.export_batch_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) self.clear_batch_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.clear_batch_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.import_batch_toolButton.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Import batch from text file</body></html>")) self.import_batch_toolButton.setText(_translate("SemiAutomaticClassificationPlugin", "Plot")) item = self.batch_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Functions")) self.label_177.setText(_translate("SemiAutomaticClassificationPlugin", " Run")) self.check_batch.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Check batch function</body></html>")) self.check_batch.setText(_translate("SemiAutomaticClassificationPlugin", " CHECK")) self.toolButton_run_batch.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Run</body></html>")) self.toolButton_run_batch.setText(_translate("SemiAutomaticClassificationPlugin", " RUN")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_batch), _translate("SemiAutomaticClassificationPlugin", "Batch")) self.label_28.setText(_translate("SemiAutomaticClassificationPlugin", " System")) self.RAM_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set available RAM for processes</body></html>")) self.label_23.setText(_translate("SemiAutomaticClassificationPlugin", "Available RAM (MB)")) self.label_56.setText(_translate("SemiAutomaticClassificationPlugin", "CPU threads")) self.CPU_spinBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the number of CPU threads </body></html>")) self.label_13.setText(_translate("SemiAutomaticClassificationPlugin", "SMTP server")) self.label_18.setText(_translate("SemiAutomaticClassificationPlugin", "password")) self.smtp_user_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the Class ID field name[max 10 characters]</body></html>")) self.smtp_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the sending of email of completed process</body></html>")) self.smtp_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Send email of completed process to")) self.label_117.setText(_translate("SemiAutomaticClassificationPlugin", "SMTP process notification")) self.smtp_password_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Password</body></html>")) self.smtp_server_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the Class ID field name[max 10 characters]</body></html>")) self.label_14.setText(_translate("SemiAutomaticClassificationPlugin", "user")) self.to_email_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>A list of addresses (separated by comma , ) to send this mail to </body></html>")) self.remeber_settings_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, remember user name and password locally in QGIS</body></html>")) self.remeber_settings_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "remember")) self.reset_temp_directory_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset to default temporary directory</body></html>")) self.reset_temp_directory_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.temp_directory_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select a directory</body></html>")) self.temp_directory_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_87.setText(_translate("SemiAutomaticClassificationPlugin", "Temporary directory")) self.SNAP_label.setText(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body><a href=\"https://step.esa.int/main/download/snap-download/\">ESA SNAP GPT executable</a></body></html>")) self.label_276.setText(_translate("SemiAutomaticClassificationPlugin", "Python executable path")) self.label_288.setText(_translate("SemiAutomaticClassificationPlugin", "Python modules path")) self.label_275.setText(_translate("SemiAutomaticClassificationPlugin", "GDAL installation directory")) self.SNAP_GPT_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Path to the GPT executable (e.g. C:\\Program Files\\snap\\bin\\gpt.exe)</body></html>")) self.python_path_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Path to the Python executable (e.g. /usr/local/bin/python3)</body></html>")) self.python_path_lineEdit_2.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Path to Python modules (e.g. /Applications/QGIS.app/Contents/MacOS/lib/python3.8/site-packages). Multiple paths can be entered separated by ;Restart is required.</body></html>")) self.gdal_path_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Path to the GDAL directory containing tools such as gdal_translate and gdalwarp (e.g. /usr/bin)</body></html>")) self.label_211.setText(_translate("SemiAutomaticClassificationPlugin", "External programs")) self.sound_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the sound when the process is finished</body></html>")) self.sound_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Play sound when finished")) self.virtual_raster_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, create virtual rasters for certain temporary files</body></html>")) self.virtual_raster_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Use virtual raster for temp files")) self.label_45.setText(_translate("SemiAutomaticClassificationPlugin", "Calculation process")) self.raster_compression_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, a lossless compression is applied to rasters in order to save disk space</body></html>")) self.raster_compression_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Raster compression")) self.parallel_writing_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, the output raster is compared to output calculation to avoid writing errors. It could slightly slow the process.</body></html>")) self.parallel_writing_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Enable writing verification")) self.settings_tabWidget.setTabText(self.settings_tabWidget.indexOf(self.tabWidgetProcessing), _translate("SemiAutomaticClassificationPlugin", "Processing")) self.label_31.setText(_translate("SemiAutomaticClassificationPlugin", "C Name field")) self.Info_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the Class name field[max 10 characters]</body></html>")) self.label_24.setText(_translate("SemiAutomaticClassificationPlugin", " Field names of training input")) self.ID_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the Class ID field name[max 10 characters]</body></html>")) self.MID_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the Macroclass ID field name[max 10 characters]</body></html>")) self.label_10.setText(_translate("SemiAutomaticClassificationPlugin", "C ID field")) self.MCInfo_field_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Set the Macroclass name field[max 10 characters]</body></html>")) self.label_17.setText(_translate("SemiAutomaticClassificationPlugin", "MC ID field")) self.label_46.setText(_translate("SemiAutomaticClassificationPlugin", "MC Name field")) self.reset_field_names_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.reset_field_names_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_21.setText(_translate("SemiAutomaticClassificationPlugin", " ROI style")) self.change_color_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Select temporary ROI color</body></html>")) self.label_22.setText(_translate("SemiAutomaticClassificationPlugin", "ROI color")) self.transparency_Label.setText(_translate("SemiAutomaticClassificationPlugin", "Transparency")) self.transparency_Slider.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Change temporary ROI transparency</body></html>")) self.reset_color_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.reset_color_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_68.setText(_translate("SemiAutomaticClassificationPlugin", " Variable name")) self.variable_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Variable name for expressions</body></html>")) self.variable_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "raster")) self.label_69.setText(_translate("SemiAutomaticClassificationPlugin", " Variable name for expressions (tab Reclassification and Edit raster)")) self.reset_variable_name_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.reset_variable_name_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_95.setText(_translate("SemiAutomaticClassificationPlugin", " Dock")) self.download_news_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, news about the SCP are downloaded on startup and displayed in Dock</body></html>")) self.download_news_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Download news on startup")) self.label_76.setText(_translate("SemiAutomaticClassificationPlugin", " Project")) self.reset_group_name_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Reset</body></html>")) self.reset_group_name_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.virtual_raster_load_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>If checked, an RGB composite of the active band set is created when a previous project is loaded</body></html>")) self.virtual_raster_load_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Create RGB composite of band set when a project is loaded")) self.label_75.setText(_translate("SemiAutomaticClassificationPlugin", "Group name")) self.group_name_lineEdit.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Group name</body></html>")) self.group_name_lineEdit.setText(_translate("SemiAutomaticClassificationPlugin", "Class_temp_group")) self.settings_tabWidget.setTabText(self.settings_tabWidget.indexOf(self.tabWidgetInterface), _translate("SemiAutomaticClassificationPlugin", "Interface")) self.log_checkBox.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Enable/Disable the Log of events</body></html>")) self.log_checkBox.setText(_translate("SemiAutomaticClassificationPlugin", "Record events in a Log file")) self.exportLog_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Export the Log file</body></html>")) self.exportLog_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.clearLog_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Clear the Log file content</body></html>")) self.clearLog_Button.setText(_translate("SemiAutomaticClassificationPlugin", "Import library")) self.label_30.setText(_translate("SemiAutomaticClassificationPlugin", " Log file")) item = self.log_tableWidget.horizontalHeaderItem(0) item.setText(_translate("SemiAutomaticClassificationPlugin", "Date")) item = self.log_tableWidget.horizontalHeaderItem(1) item.setText(_translate("SemiAutomaticClassificationPlugin", "Function")) item = self.log_tableWidget.horizontalHeaderItem(2) item.setText(_translate("SemiAutomaticClassificationPlugin", "Message")) self.test_dependencies_Button.setToolTip(_translate("SemiAutomaticClassificationPlugin", "<html><head/><body>Test dependencies</body></html>")) self.label_42.setText(_translate("SemiAutomaticClassificationPlugin", "Test dependencies")) self.label_43.setText(_translate("SemiAutomaticClassificationPlugin", " Test")) self.settings_tabWidget.setTabText(self.settings_tabWidget.indexOf(self.tabWidgetDebug), _translate("SemiAutomaticClassificationPlugin", "Debug")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_Settings), _translate("SemiAutomaticClassificationPlugin", "Settings")) self.plugin_label.setText(_translate("SemiAutomaticClassificationPlugin", "Semi-Automatic Classification Plugin")) self.textBrowser.setHtml(_translate("SemiAutomaticClassificationPlugin", "<!DOCTYPE HTML PUBLIC \"-//W3C//DTD HTML 4.0//EN\" \"http://www.w3.org/TR/REC-html40/strict.dtd\">\n" "<html><head><meta name=\"qrichtext\" content=\"1\" /><style type=\"text/css\">\n" "p, li { white-space: pre-wrap; }\n" "</style></head><body style=\" font-family:\'Sans\'; font-size:10pt; font-weight:400; font-style:normal;\">\n" "Developed by <a href=\"http://www.researchgate.net/profile/Luca_Congedo\">Luca Congedo</a> (ing.congedoluca@gmail.com), the Semi-Automatic Classification Plugin (SCP) is a free open source plugin for QGIS that allows for the semi-automatic classification (also supervised classification) of remote sensing images.\n" "It provides several tools for the download of free images, the preprocessing, the postprocessing, and the raster calculation.\n" "For more information and tutorials visit the official site From GIS to Remote Sensing.\n" "<img src=\":/plugins/semiautomaticclassificationplugin/icons/fromGIStoRS.png\" /><a href=\"https://fromgistors.blogspot.com/p/semi-automatic-classification-plugin.html?spref=sacp\">From GIS to Remote Sensing</a>\n" " Please join the <a href=\"https://www.facebook.com/groups/SemiAutomaticClassificationPlugin\">Semi-Automatic Classification Plugin group on Facebook</a> or <a href=\"https://github.com/semiautomaticgit/SemiAutomaticClassificationPlugin/discussions\">GitHub discussions</a>\n" " \n" "This plugin requires the installation of GDAL, OGR, Numpy, SciPy, and Matplotlib (already bundled with QGIS).\n" "Some tools require the additional installation of: ESA SNAP\n" "<hr />\n" "How to cite:\n" "Congedo, Luca, (2021). Semi-Automatic Classification Plugin: A Python tool for the download and processing of remote sensing images in QGIS. Journal of Open Source Software, 6(64), 3172, <a href=\"https://doi.org/10.21105/joss.03172\">https://doi.org/10.21105/joss.03172</a>\n" "<hr />\n" " The Semi-Automatic Classification Plugin is developed by Luca Congedo.\n" "Translators:\n" "Language: Author \n" "Semi-Automatic Classification Plugin is free software: you can redistribute it and/or modify it under the terms of the GNU General Public License as published by the Free Software Foundation, version 3 of the License.\n" "Semi-Automatic Classification Plugin is distributed in the hope that it will be useful, but WITHOUT ANY WARRANTY; without even the implied warranty of MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.\n" "See the GNU General Public License for more details. You should have received a copy of the GNU General Public License along with Semi-Automatic Classification Plugin. If not, see <<a href=\"http://www.gnu.org/licenses/\">http://www.gnu.org/licenses/</a>>.</body></html>")) self.SCP_tabs.setTabText(self.SCP_tabs.indexOf(self.tab_About), _translate("SemiAutomaticClassificationPlugin", "About")) self.main_tabWidget.setTabText(self.main_tabWidget.indexOf(self.tool_tab), _translate("SemiAutomaticClassificationPlugin", "Tool")) self.main_tabWidget.setTabText(self.main_tabWidget.indexOf(self.help_tab), _translate("SemiAutomaticClassificationPlugin", "Help")) from . import resources_rc

semiautomaticgit/SemiAutomaticClassificationPlugin

ui/ui_semiautomaticclassificationplugin.py

Python

gpl-3.0

841,489

[ "VisIt" ]

67be0e08edb3b7528cc32326b3247b48a02507661e0af18d4a74ce0f927cc464

#!/usr/bin/env python # Author: Andrew Jewett (jewett.aij at g mail) # http://www.chem.ucsb.edu/~sheagroup # License: 3-clause BSD License (See LICENSE.TXT) # Copyright (c) 2011, Regents of the University of California # All rights reserved. man_page_text = """ nbody_by_type.py reads a LAMMPS data file (or an excerpt of a LAMMPS) data file containing bonded many-body interactions by atom type (and bond type), and generates a list of additional interactions in LAMMPS format consistent with those type (to the standard out). Typical Usage: nbody_by_type.py X < old.data > new.data --or-- nbody_by_type.py X \\ -atoms atoms.data \\ -bonds bonds.data \\ -nbody X.data \\ -nbodybytype X_by_type.data \\ > new_X.data In both cases "X" denotes the interaction type, which is either "Angles", "Dihedrals", or "Impropers". (Support for other interaction types can be added by the user. See below.) -------- Example 1 ------- nbody_by_type.py X < old.data > new.data In this example, nbody_by_type.py reads a LAMMPS data file "orig.data", and extracts the relevant section ("Angles", "Dihedrals", or "Impropers"). It also looks a section named "X By Type", (eg. "Angles By type", "Impropers By type", "Impropers By type") which contains a list of criteria for automatically defining additional interactions of that type. For example, this file might contain: Angle By Type 7 1 2 1 * * 8 2 2 * * * 9 3 4 3 * * The first column is an interaction type ID. The next 3 columns are atom type identifiers. The final 2 columns are bond type identifiers. The * is a wildcard symbol indicating there is no preference for bond types in this example. (Optionally, regular expressions can also be used to define a type match, by enclosing the atom or bond type in / slashes.) The first line tells us to that there should be a 3-body "Angle" interaction of type "7" whenever an atom of type 1 is bonded to an atom of type "2", which is bonded to another atom of type "1" again. The second line tells us that an angle is defined whenever three atoms are bonded together and the first two are of type "2". (Redundant angle interactions are filtered.) New interactions are created for every group of bonded atoms which match these criteria if they are bonded together in the relevant way for that interaction type (as determined by nbody_X.py), and printed to the standard output. For example, suppose you are automatically generating 3-body "Angle" interactions using: nbody_by_type Angles < old.data > new.data The file "new.data" will be identical to "old.data", however the "Angles By Type" section will be deleted, and the following lines of text will be added to the "Angles" section: 394 7 5983 5894 5895 395 7 5984 5895 5896 396 7 5985 5896 5897 : : : : : 847 9 14827 14848 14849 The numbers in the first column are counters which assign a ID to every interaction of that type, and start where the original "Angles" data left off (New angle ID numbers do not overlap with old ID numbers). The text in the second column ("7", "9", ...) matches the text from the first column of the "Angle By Type" section of the input file. -------- Example 2 ------- nbody_by_type.py X \\ -atoms atoms.data \\ -bonds bonds.data \\ -nbody X.data \\ -nbodybytype X_by_type.data \\ -prefix "SOMESTRING" -suffix "ANOTHERSTRING" \\ > new_X.data In particular, for Angle interactions: nbody_by_type.py Angles \\ -atoms atoms.data \\ -bonds bonds.data \\ -nbody angles.data \\ -nbodybytype angles_by_type.data \\ > new_Angles.data When run this way, nbody_by_type.py behaves exactly the same way as in Example 1, however only the lines of text corresponding to the new generated interactions are printed, (not the entire data file). Also note, that when run this way, nbody_by_type.py does not read the LAMMPS data from the standard input. Instead, it reads each section of the data file from a different file indicated by the arguments following the "-atoms", "-bonds", "-nbody", and "-nbodybytype" flags. "Angles" is a 3-body interaction style. So when run this way, nbody_by_type.py will create a 5 (=3+2) column file (new_Angles.data). Note: the atom, bond and other IDs/types in need not be integers. Note: This program must be distributed with several python modules, including: nbody_Angles.py, nbody_Dihedrals.py, and nbody_Impropers.py. These contain bond definitions for angular, dihedral, and improper interactions. (In case any new interaction types are ever added to LAMMPS, with only a few lines of python it is easy to edit to define new bonded interaction types by supplying new "nbody_X.py" python module. Refer to the modules listed above for examples.) Note: Optional "-prefix" and "-suffix" arguments can be included to decorate the interaction IDs (first column). For example, -prefix "auto_" and -suffix "_angle", causes "new_Angles.data" to contain the following text: auto_394_angle 7 5983 5894 5895 auto_395_angle 7 5984 5895 5896 auto_396_angle 7 5985 5896 5897 : : : : : auto_847_angle 9 14827 14848 14849 """ g_program_name = __file__.split('/')[-1] # = 'nbody_by_type.py' g_date_str = '2017-2-06' g_version_str = '0.20.0' bond_pattern_module_name = "" import os import sys sys.path.append(os.getcwd()) import importlib if sys.version < '2.6': raise InputError('Error: Using python ' + sys.version + '\n' ' Alas, you must upgrade to a newer version of python (2.6 or later).') elif sys.version < '2.7': sys.stderr.write('--------------------------------------------------------\n' '----------------- WARNING: OLD PYTHON VERSION ----------\n' ' This program is untested on your python version (' + sys.version + ').\n' ' PLEASE LET ME KNOW IF THIS PROGRAM CRASHES (and upgrade python).\n' ' -Andrew 2013-10-25\n' '--------------------------------------------------------\n' '--------------------------------------------------------\n') from ordereddict import OrderedDict else: from collections import OrderedDict try: from .extract_lammps_data import * from .nbody_by_type_lib import GenInteractions_str from .ttree_lex import * from .lttree_styles import AtomStyle2ColNames, ColNames2AidAtypeMolid except (ImportError, SystemError, ValueError): from extract_lammps_data import * from nbody_by_type_lib import GenInteractions_str from ttree_lex import * from lttree_styles import AtomStyle2ColNames, ColNames2AidAtypeMolid def GenInteractions_lines(lines_atoms, lines_bonds, lines_nbody, lines_nbodybytype, atom_style, g_bond_pattern, canonical_order, # function to sort atoms and bonds prefix='', suffix='', report_progress=False, check_undefined=False): column_names = AtomStyle2ColNames(atom_style) i_atomid, i_atomtype, i_molid = ColNames2AidAtypeMolid(column_names) atomids_str = [] atomtypes_str = [] for iv in range(0, len(lines_atoms)): line = lines_atoms[iv].strip() if '#' in line: icomment = line.find('#') line = (line[:icomment]).strip() if len(line) > 0: tokens = SplitQuotedString(line) if ((len(tokens) <= i_atomid) or (len(tokens) <= i_atomtype)): raise(InputError('Error not enough columns on line ' + str(iv + 1) + ' of \"Atoms\" section.')) tokens = SplitQuotedString(line) atomids_str.append(EscCharStrToChar(tokens[i_atomid])) atomtypes_str.append(EscCharStrToChar(tokens[i_atomtype])) bondids_str = [] bondtypes_str = [] bond_pairs = [] for ie in range(0, len(lines_bonds)): line = lines_bonds[ie].strip() if '#' in line: icomment = line.find('#') line = (line[:icomment]).strip() if len(line) > 0: tokens = SplitQuotedString(line) if len(tokens) < 4: raise(InputError('Error not enough columns on line ' + str(ie + 1) + ' of \"Bonds\" section.')) bondids_str.append(EscCharStrToChar(tokens[0])) bondtypes_str.append(EscCharStrToChar(tokens[1])) bond_pairs.append((EscCharStrToChar(tokens[2]), EscCharStrToChar(tokens[3]))) typepattern_to_coefftypes = [] for i in range(0, len(lines_nbodybytype)): line = lines_nbodybytype[i].strip() if '#' in line: icomment = line.find('#') line = (line[:icomment]).strip() if len(line) > 0: tokens = SplitQuotedString(line) if ((len(tokens) != 1 + g_bond_pattern.GetNumVerts()) and (len(tokens) != 1 + g_bond_pattern.GetNumVerts() + g_bond_pattern.GetNumEdges())): raise(InputError('Error: Wrong number of columns in \"By Type\" section of data file.\n' 'Offending line:\n' + '\"' + line + '\"\n' 'Expected either ' + str(1 + g_bond_pattern.GetNumVerts()) + ' or ' + str(1 + g_bond_pattern.GetNumVerts() + g_bond_pattern.GetNumEdges()) + ' colunms.')) coefftype = EscCharStrToChar(tokens[0]) typepattern = [] for typestr in tokens[1:]: if ((len(typestr) >= 2) and (typestr[0] == '/') and (typestr[-1] == '/')): regex_str = typestr[1:-1] typepattern.append(re.compile(regex_str)) else: typepattern.append(EscCharStrToChar(typestr)) # If the user neglected to specify the bond types, assume '*' if len(tokens) == 1 + g_bond_pattern.GetNumVerts(): typepattern += ['*'] * g_bond_pattern.GetNumEdges() typepattern_to_coefftypes.append([typepattern, coefftype]) coefftype_to_atomids_str = GenInteractions_str(bond_pairs, g_bond_pattern, typepattern_to_coefftypes, canonical_order, atomids_str, atomtypes_str, bondids_str, bondtypes_str, report_progress, check_undefined) lines_nbody_new = [] for coefftype, atomids_list in coefftype_to_atomids_str.items(): for atomids_found in atomids_list: n = len(lines_nbody) + len(lines_nbody_new) + 1 line = prefix + str(n) + suffix + ' ' + \ coefftype + ' ' + (' '.join(atomids_found)) + '\n' lines_nbody_new.append(line) return lines_nbody_new def GenInteractions_files(lines_data, src_bond_pattern, fname_atoms, fname_bonds, fname_nbody, fname_nbodybytype, section_name, section_name_bytype, atom_style, prefix='', suffix='', report_progress=False, check_undefined=False): if fname_atoms == None: lines_atoms = [ line for line in ExtractDataSection(lines_data, 'Atoms')] else: try: f = open(fname_atoms, 'r') except: sys.stderr.write('Error: Unable to open file \"' + fname_atoms + '\" for reading.\n') sys.exit(-1) lines_atoms = [line for line in f.readlines() if ((len(line.strip()) > 0) and (line.strip()[0] != '#'))] f.close() if fname_bonds == None: lines_bonds = [ line for line in ExtractDataSection(lines_data, 'Bonds')] else: try: f = open(fname_bonds, 'r') except IOError: sys.stderr.write('Error: Unable to open file \"' + fname_bonds + '\" for reading.\n') sys.exit(-1) lines_bonds = [line for line in f.readlines() if ((len(line.strip()) > 0) and (line.strip()[0] != '#'))] f.close() if fname_nbody == None: lines_nbody = [line for line in ExtractDataSection( lines_data, section_name)] else: try: f = open(fname_nbody, 'r') lines_nbody = [line for line in f.readlines() if ((len(line.strip()) > 0) and (line.strip()[0] != '#'))] f.close() except IOError: #sys.stderr.write(' (omitting optional file \"'+fname_nbody+'\")\n') lines_nbody = [] if fname_nbodybytype == None: lines_nbodybytype = [line for line in ExtractDataSection(lines_data, section_name_bytype)] else: try: f = open(fname_nbodybytype, 'r') except: sys.stderr.write('Error: Unable to open file \"' + fname_nbodybytype + '\" for reading.\n') sys.exit(-1) lines_nbodybytype = [line for line in f.readlines() if((len(line.strip()) > 0)and(line.strip()[0] != '#'))] f.close() # search locations package_opts = [[src_bond_pattern, __package__], ['nbody_alt_symmetry.'+src_bond_pattern, __package__]] if __package__: for i in range(0, len(package_opts)): package_opts[i][0] = '.' + package_opts[i][0] package_opts.append(['.'+src_bond_pattern, __package__+'.nbody_alt_symmetry']) g = None for name, pkg in package_opts: try: g = importlib.import_module(name, pkg) break except (ImportError, SystemError, ValueError): pass if g is None: sys.stderr.write('Error: Unable to locate file \"' + src_bond_pattern + '.py\"\n' ' (Did you mispell the file name?\n' ' Check the \"nbody_alt_symmetry/\" directory.)\n') sys.exit(-1) return GenInteractions_lines(lines_atoms, lines_bonds, lines_nbody, lines_nbodybytype, atom_style, g.bond_pattern, g.canonical_order, prefix, suffix, report_progress, check_undefined) def main(): sys.stderr.write(g_program_name + ' v' + g_version_str + ' ' + g_date_str + ' ') if sys.version < '3': sys.stderr.write(' (python version < 3)\n') else: sys.stderr.write('\n') try: fname_atoms = None fname_bonds = None fname_nbody = None fname_nbodybytype = None atom_style = 'full' prefix = '' suffix = '' check_undefined = False argv = [arg for arg in sys.argv] if len(argv) == 1: raise InputError('Error: Missing argument required.\n' ' The \"' + g_program_name + '\" program requires an argument containing the\n' ' name of a section from a LAMMPS data file storing bonded interactions.\n' ' (For example: "Angles", "Dihedrals", or "Impropers".)\n' #' Note: The first letter of each section is usually capitalized.)\n' '\n' '--------------- general documentation -------------\n' '\n' + man_page_text + '\n') section_name = '' # (This will be replaced later.) section_name_bytype = '' # (This will be replaced later.) # Loop over the remaining arguments not processed yet. # These arguments are specific to the lttree.py program # and are not understood by ttree.py: i = 1 while i < len(argv): #sys.stderr.write('argv['+str(i)+'] = \"'+argv[i]+'\"\n') if ((argv[i].lower() == '-?') or (argv[i].lower() == '--?') or (argv[i].lower() == '-help') or (argv[i].lower() == '-help')): if i + 1 >= len(argv): sys.stdout.write(man_page_text + '\n') sys.exit(0) elif argv[i].lower() == '-atoms': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a file name containing lines of\n' ' text which might appear in the "Atoms" section of a LAMMPS data file.\n') fname_atoms = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-bonds': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a file name containing lines of\n' ' text which might appear in the "Bonds" section of a LAMMPS data file.\n') fname_bonds = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-nbody': if i + 1 >= len(argv): raise InputError( 'Error: ' + argv[i] + ' flag should be followed by a file name\n') # raise InputError('Error: '+argv[i]+' flag should be followed by a file name containing lines of\n' # ' text which might appear in the "'+section_name+' section of a LAMMPS data file.\n') fname_nbody = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-nbodybytype': if i + 1 >= len(argv): raise InputError( 'Error: ' + argv[i] + ' flag should be followed by a file name\n') # raise InputError('Error: '+argv[i]+' flag should be followed by a file name containing\n' # ' text which might appear in the "'+section_name+' By Type" section\n' # ' of a LAMMPS data file.\n') fname_nbodybytype = argv[i + 1] del(argv[i:i + 2]) elif ((argv[i].lower() == '-atom-style') or (argv[i].lower() == '-atom_style')): if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a an atom_style name.\n' ' (Or single quoted string which includes a space-separated\n' ' list of column names.)\n') atom_style = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-prefix': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a prefix string\n' ' (a string you want to appear to the left of the integer\n' ' which counts the bonded interactions you have generated.)\n') prefix = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-suffix': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by a suffix string\n' ' (a string you want to appear to the right of the integer\n' ' which counts the bonded interactions you have generated.)\n') prefix = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-subgraph': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by the name of a python file\n' ' containing the definition of the subgraph you are searching for\n' ' and it\'s symmetry properties.\n' ' (See nbody_Dihedrals.py for example.)\n') bond_pattern_module_name = argv[i + 1] # If the file name ends in ".py", then strip off this suffix. # The next line does not work. Too lazy to care why. # bond_pattern_module_name=bond_pattern_module_name.rstrip('.py') # Do this instead pc = bond_pattern_module_name.rfind('.py') if pc != -1: bond_pattern_module_name = bond_pattern_module_name[0:pc] del(argv[i:i + 2]) elif argv[i].lower() == '-section': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by the name of the LAMMPS\n' ' Data section describing the type of interaction being generated.\n' ' (For example: \"Angles\", \"Dihedrals\", \"Impropers\", etc...)\n') section_name = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-sectionbytype': if i + 1 >= len(argv): raise InputError('Error: ' + argv[i] + ' flag should be followed by the name of the\n' ' write_once(\"???? By Type\") section describing how to create the\n' ' interactions. (For example: \"Angles By Type\", \"Dihedrals By Type\",\n' ' \"Impropers By Type\", etc... Note that this argument\n' ' will contain spaces, so surround it with quotes.)\n') section_name_bytype = argv[i + 1] del(argv[i:i + 2]) elif argv[i].lower() == '-checkff': check_undefined = True del(argv[i:i + 1]) elif argv[i][0] == '-': raise InputError('Error(' + g_program_name + '):\n' 'Unrecogized command line argument \"' + argv[i] + '\"\n') else: i += 1 # if len(argv) == 1: # raise InputError('Error: Missing argument required.\n' # ' The \"'+g_program_name+'\" program requires an argument containing the\n' # ' name of a section from a LAMMPS data file storing bonded interactions.\n' # ' (For example: "Angles", "Dihedrals", or "Impropers".)\n') # #' Note: The first letter of each section is usually capitalized.)\n' if len(argv) == 1: pass elif len(argv) == 2: section_name = argv[1] section_name_bytype = section_name + ' By Type' # default bond_pattern_module name if bond_pattern_module_name == "": # <--if not set by user bond_pattern_module_name = 'nbody_' + section_name del(argv[1:2]) else: # if there are more than 2 remaining arguments, problem_args = ['\"' + arg + '\"' for arg in argv[1:]] raise InputError('Syntax Error(' + g_program_name + '):\n\n' ' Problem with argument list.\n' ' The remaining arguments are:\n\n' ' ' + (' '.join(problem_args)) + '\n\n' ' (The actual problem may be earlier in the argument list.)\n') if ((section_name == '') or (section_name_bytype == '') or (bond_pattern_module_name == '')): raise InputError('Syntax Error(' + g_program_name + '):\n\n' ' You have not defined the following arguments:\n' ' -section name\n' ' -sectionbytype namebytype\n' ' -subgraph pythonfile.py\n') # ------------ Done parsing argument list ---------- if (fname_atoms or fname_bonds or fname_nbody or fname_nbodybytype): output_full_DATA_file = False lines_data = [] else: output_full_DATA_file = True lines_data = sys.stdin.readlines() # Calculate the interactions and generate a list of lines of text lines_new_interactions = \ GenInteractions_files(lines_data, bond_pattern_module_name, fname_atoms, fname_bonds, fname_nbody, fname_nbodybytype, section_name, section_name_bytype, atom_style, prefix, suffix, True, check_undefined) # Print this text to the standard out. # Question: Do we write out the entire DATA file, # or just the portion that was generated by this program? if not output_full_DATA_file: # ...then only print out the interactions which were generated # by this program, omitting any lines from the original data file: # (This is the way I usually run this program.) for line in lines_new_interactions: sys.stdout.write(line) else: # ...then print out the entire data file, deleting the "By Type" # section, and adding the generated lines of text to the # corresponding # If present, update the interaction counter at the beginning # of the LAMMPS data file. (For example, if if 100 new "Angles" # interactions were generated, replace "2 Angles" with "102 Angles") # for i in range(0, len(lines_data)): line = lines_data[i].strip() tokens = SplitQuotedString(line) # updating the interaction counter if ((len(tokens) == 2) and (tokens[1] == (section_name).lower())): tokens[0] = str(int(tokens[0]) + len(lines_new_interactions)) lines_data[i] = ' '.join(tokens) + '\n' # stop when you come to a section header elif line in lammps_data_sections: #"lammps_data_sections" is defined in "extract_lammps_data.py" break # locate the appropriate section of the data file # (storing the type of interactions we just created) i_nbody_a, i_nbody_b = \ FindDataSection(lines_data, section_name) if i_nbody_a == -1: if len(lines_new_interactions) > 0: # If not found, create a new section at the end of the file, # containing a section name followed by the list of lines lines_data += ['\n', section_name + '\n', '\n'] + \ lines_new_interactions + ['\n'] else: # Insert the new lines into the existing section lines_data[i_nbody_b:i_nbody_b] = lines_new_interactions # Figure out where the "By Type" section is located # (so we skip over it) i_bytype_a, i_bytype_b = \ FindDataSection(lines_data, section_name_bytype) in_bytype_section = False for i in range(0, len(lines_data)): line = lines_data[i].strip() # Omit all lines of text in the 'By Type' section (including the # header and commments or blank lines which immediately follow # it.) if line == section_name_bytype: in_bytype_section = True elif i == i_bytype_b: in_bytype_section = False if not in_bytype_section: sys.stdout.write(lines_data[i]) except (ValueError, InputError) as err: sys.stderr.write('\n' + str(err) + '\n') sys.exit(-1) return if __name__ == '__main__': main()

smsaladi/moltemplate

moltemplate/nbody_by_type.py

Python

bsd-3-clause

30,585

[ "LAMMPS" ]

fd6035b4c399d258841e8f670a900cfc9dfd4c7e1e9510eb84222f416d182e67

import os from gpaw import GPAW, restart from ase import Atoms from gpaw.test import equal from math import sqrt import numpy as np modes = ['gpw'] try: import h5py modes.append('hdf5') except ImportError: pass d = 3.0 atoms = Atoms('Na3', positions=[( 0, 0, 0), ( 0, 0, d), ( 0, d*sqrt(3./4.), d/2.)], magmoms=[1.0, 1.0, 1.0], cell=(3.5, 3.5, 4.+2/3.), pbc=True) # Only a short, non-converged calcuation conv = {'eigenstates': 1e-2, 'energy':2e-1, 'density':1e-1} calc = GPAW(h=0.30, nbands=3, convergence=conv) atoms.set_calculator(calc) e0 = atoms.get_potential_energy() niter0 = calc.get_number_of_iterations() f0 = atoms.get_forces() m0 = atoms.get_magnetic_moments() eig00 = calc.get_eigenvalues(spin=0) eig01 = calc.get_eigenvalues(spin=1) # Write the restart file(s) for mode in modes: calc.write('tmp.%s' % mode) del atoms, calc # Try restarting from all the files for mode in modes: atoms, calc = restart('tmp.%s' % mode) e1 = atoms.get_potential_energy() try: # number of iterations needed in restart niter1 = calc.get_number_of_iterations() except: pass f1 = atoms.get_forces() m1 = atoms.get_magnetic_moments() eig10 = calc.get_eigenvalues(spin=0) eig11 = calc.get_eigenvalues(spin=1) print e0, e1 equal(e0, e1, 1e-10) print f0, f1 for ff0, ff1 in zip(f0, f1): err = np.linalg.norm(ff0-ff1) assert err <= 1e-10 print m0, m1 for mm0, mm1 in zip(m0, m1): equal(mm0, mm1, 1e-10) print 'A',eig00, eig10 for eig0, eig1 in zip(eig00, eig10): equal(eig0, eig1, 1e-10) print 'B',eig01, eig11 for eig0, eig1 in zip(eig01, eig11): equal(eig0, eig1, 1e-10) energy_tolerance = 0.0002 niter_tolerance = 0 equal(e0, -0.52198, energy_tolerance) equal(niter0, 6, niter_tolerance) equal(e1, -0.52198, energy_tolerance)

qsnake/gpaw

gpaw/test/restart.py

Python

gpl-3.0

1,993

[ "ASE", "GPAW" ]

17ba3efe1c985142c070950707458a585896b4e2b80e1a0c46c6cea70e9d53a7

#!/usr/bin/env python # -*- coding: utf-8 -*- # (c) 2012 Michal Kalewski <mkalewski at cs.put.poznan.pl> # # This file is a part of the Simple Network Simulator (sim2net) project. # USE, MODIFICATION, COPYING AND DISTRIBUTION OF THIS SOFTWARE IS SUBJECT TO # THE TERMS AND CONDITIONS OF THE MIT LICENSE. YOU SHOULD HAVE RECEIVED A COPY # OF THE MIT LICENSE ALONG WITH THIS SOFTWARE; IF NOT, YOU CAN DOWNLOAD A COPY # FROM HTTP://WWW.OPENSOURCE.ORG/. # # For bug reports, feature and support requests please visit # <https://github.com/mkalewski/sim2net/issues>. """ This package contains miscellaneous utility modules and classes. """ __docformat__ = 'reStructuredText' __all__ = ['logger', 'randomness', 'verification']

mkalewski/sim2net

sim2net/utility/__init__.py

Python

mit

728

[ "VisIt" ]

49b99d9de0234e377c759063a39809ee521f369092b1270de7eb4906e7ba0a9b

#!/usr/bin/python # -*- coding: utf-8 -*- # # --- BEGIN_HEADER --- # # tail - [insert a few words of module description on this line] # Copyright (C) 2003-2009 The MiG Project lead by Brian Vinter # # This file is part of MiG. # # MiG is free software: you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # MiG is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with this program; if not, write to the Free Software # Foundation, Inc., 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301, USA. # # -- END_HEADER --- # import cgi import cgitb cgitb.enable() from shared.functionality.tail import main from shared.cgiscriptstub import run_cgi_script run_cgi_script(main)

heromod/migrid

mig/cgi-bin/tail.py

Python

gpl-2.0

1,096

[ "Brian" ]

35c1a80cdf3cdf2f65ed0b700bce4192ff847f506b471b5e68068faf1a3ab094

# Python standard modules import numpy as np import pandas as pd import matplotlib.pyplot as plt import matplotlib.mlab as mlab from mpl_toolkits.mplot3d import Axes3D import seaborn as sns import statsmodels.api as sm import matplotlib.colors as mcolors import matplotlib as mpl from matplotlib.pylab import * from mpl_toolkits.axes_grid1 import host_subplot resultsdf_plot1 = pd.read_excel('PLR_plots.xlsx', 'plot1') # Results WindLevel = resultsdf_plot1['wind_pen'].tolist() Energycost = resultsdf_plot1['cost_energy'].tolist() EnergycostWind = resultsdf_plot1['cost_wind'].tolist() PLRcost = resultsdf_plot1['cost_plr'].tolist() Fixedcost = resultsdf_plot1['mm_fixedcost'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig = plt.figure(1) width = 0.35 ind = np.arange(len(WindLevel)) p3 = plt.bar(ind, Energycost, width, color=sns.xkcd_rgb["windows blue"], label='$Cost\ of\ Energy$') p2 = plt.bar(ind, EnergycostWind, width, color=sns.xkcd_rgb["medium green"],bottom=Energycost, label='$Cost\ of\ Wind$') new = [x + y for x, y in zip(Energycost, EnergycostWind)] p1 = plt.bar(ind, Fixedcost, width, color=sns.xkcd_rgb["amber"],bottom=new, label='$Variable\ and\ Fixed\ Cost\ Not\ Covered$') new = [x + y for x, y in zip(new, Fixedcost)] p4 = plt.bar(ind, PLRcost, width, color=sns.xkcd_rgb["pale red"],bottom=new, label='$Cost\ of\ PLR$') plt.grid(True, linestyle='-', which='major', color='lightgray', alpha=0.5) plt.axis([-1, 10, 0, 2.5]) plt.ylabel('$Cost\ (M$€$/day)$') plt.xlabel('$Average\ Wind\ Penetration\ Level\ ($%$)$') plt.xticks(ind + width/2., ('0', '9.5', '19', '28', '38', '47', '56', '66','70','77')) plt.yticks(np.arange(0, 3, 0.5)) plt.legend(loc='upper center', bbox_to_anchor=(.5, 1.15), ncol=2, fancybox=True, shadow=True) axes = plt.gca() axes.set_axis_bgcolor('whitesmoke') # plt.savefig('SEpeakloadreserve.pdf') plt.show() resultsdf_plot6 = pd.read_excel('PLR_plots.xlsx', 'plot6') # Results WindLevel = resultsdf_plot6['wind_pen'].tolist() PLR20 = resultsdf_plot6['PLR20'].tolist() PLR15 = resultsdf_plot6['PLR15'].tolist() PLR10 = resultsdf_plot6['PLR10'].tolist() PLR5 = resultsdf_plot6['PLR5'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig = plt.figure(1) plt.plot(WindLevel, PLR5, c=sns.xkcd_rgb["windows blue"],alpha=1, label = r"$5\;$%$\;PLR$") plt.plot(WindLevel, PLR10, c=sns.xkcd_rgb["medium green"],alpha=1, label = r"$10\;$%$\;PLR$") plt.plot(WindLevel, PLR15, c=sns.xkcd_rgb["amber"],alpha=1, label = r"$15\;$%$\;PLR$") plt.plot(WindLevel, PLR20, c=sns.xkcd_rgb["pale red"],alpha=1, label = r"$20\;$%$\;PLR$") plt.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5) plt.axis([0.0, 77, 0, 35]) plt.ylabel('$Number\ of\ Activations$') plt.xlabel('$Average\ Wind\ Penetration\ Level\ ($%$)$') plt.legend(loc='upper center', bbox_to_anchor=(.5, 1.10), ncol=4, fancybox=True, shadow=True) axes = plt.gca() axes.set_axis_bgcolor('whitesmoke') # plt.savefig('peakloadreserveNOA.pdf') plt.show() resultsdf_plot2 = pd.read_excel('PLR_plots.xlsx', 'plot2') resultsdf_plot3 = pd.read_excel('PLR_plots.xlsx', 'plot3') WindLevel = resultsdf_plot2['wind_pen'].tolist() Energycost5 = resultsdf_plot2['CostOfEnergy005'].tolist() Energycost10 = resultsdf_plot2['CostOfEnergy010'].tolist() Energycost15 = resultsdf_plot2['CostOfEnergy015'].tolist() Energycost20 = resultsdf_plot2['CostOfEnergy020'].tolist() MM5 = resultsdf_plot3['mm005'].tolist() MM10 = resultsdf_plot3['mm010'].tolist() MM15 = resultsdf_plot3['mm015'].tolist() MM20 = resultsdf_plot3['mm020'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') f0 = figure(num = 0, figsize = (8, 12))#, dpi = 300) f0.suptitle("$Peak\ Load\ Reserve\ Demand\ Increase$", fontsize=14) ax01 = subplot2grid((2, 2), (0, 0)) ax02 = subplot2grid((2, 2), (0, 1)) ax01.set_ylim(0,4) ax02.set_ylim(0,0.4) ax01.set_xlim(0,77) ax02.set_xlim(0,77) ax01.grid(True) ax02.grid(True) ax01.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax01.set_ylabel("$Total\ Cost\ (M$€$/day)$") ax02.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax02.set_ylabel("$Missing\ Money\ from\ Var.\ and\ Fixed\ Cost\ (M$€$/day)$") ax02.yaxis.tick_right() p011, = ax01.plot(WindLevel, Energycost5, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$5$%$\ PLR$") p012, = ax01.plot(WindLevel, Energycost10, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$10$%$\ PLR$") p013, = ax01.plot(WindLevel, Energycost15, c=sns.xkcd_rgb["amber"],alpha=1, label = "$15$%$\ PLR$") p014, = ax01.plot(WindLevel, Energycost20, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$20$%$\ PLR$") p021, = ax02.plot(WindLevel, MM5, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$5$%$\ PLR$") p022, = ax02.plot(WindLevel, MM10, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$10$%$\ PLR$") p023, = ax02.plot(WindLevel, MM15, c=sns.xkcd_rgb["amber"],alpha=1, label = "$15$%$\ PLR$") p024, = ax02.plot(WindLevel, MM20, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$20$%$\ PLR$") ax01.legend([p011,p012,p013,p014], [p011.get_label(),p012.get_label(),p013.get_label(),p014.get_label()]) legend = ax01.legend(loc='upper center', bbox_to_anchor=(1, 1.15), ncol=4, fancybox=True, shadow=True) ax01.set_axis_bgcolor('whitesmoke') ax02.set_axis_bgcolor('whitesmoke') figure(0) # f0.savefig('PLRdemandincrease.pdf') show() resultsdf_plot7 = pd.read_excel('PLR_plots.xlsx', 'plot7') resultsdf_plot8 = pd.read_excel('PLR_plots.xlsx', 'plot8') WindLevel = resultsdf_plot7['wind_pen'].tolist() MMHB = resultsdf_plot7['HighestBid'].tolist() MM500 = resultsdf_plot7['AP500'].tolist() MM1000 = resultsdf_plot7['AP1000'].tolist() MMHB2 = resultsdf_plot8['wind_pen'].tolist() MM150 = resultsdf_plot8['AP150'].tolist() MM250 = resultsdf_plot8['AP250'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') f0 = figure(num = 0, figsize = (8, 12)) ax01 = subplot2grid((2, 2), (0, 0)) ax02 = subplot2grid((2, 2), (0, 1)) ax01.set_title(r'$PLR\ demand\ 15\ \%$', y=1.12) ax02.set_title(r'$PLR\ demand\ 20\ \%$', y=1.12) ax01.set_ylim(0,0.4) ax02.set_ylim(0,0.3) ax01.set_xlim(0,77) ax02.set_xlim(0,77) ax01.grid(True) ax02.grid(True) ax01.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax01.set_ylabel("$Missing\ Money\ from\ Var.\ and\ Fixed\ Cost\ (M$€$/day)$") ax02.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax02.set_ylabel("$Missing\ Money\ from\ Var.\ and\ Fixed\ Cost\ (M$€$/day)$") p011, = ax01.plot(WindLevel, MMHB, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p012, = ax01.plot(WindLevel, MM500, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$500\ $€$/MWh$") p013, = ax01.plot(WindLevel, MM1000, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$1000\ $€$/MWh$") p021, = ax02.plot(WindLevel, MMHB2, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p022, = ax02.plot(WindLevel, MM150, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$150\ $€$/MWh$") p023, = ax02.plot(WindLevel, MM250, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$250\ $€$/MWh$") ax02.yaxis.tick_right() ax01.legend([p011,p012,p013], [p011.get_label(),p012.get_label(),p013.get_label()]) ax02.legend([p021,p022,p023], [p021.get_label(),p022.get_label(),p023.get_label()]) legend = ax01.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) legend = ax02.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) ax01.set_axis_bgcolor('whitesmoke') ax02.set_axis_bgcolor('whitesmoke') figure(0) # f0.savefig('PLRmissingmoney.pdf') show() resultsdf_plot9 = pd.read_excel('PLR_plots.xlsx', 'plot9') resultsdf_plot10 = pd.read_excel('PLR_plots.xlsx', 'plot10') WindLevel = resultsdf_plot9['wind_pen'].tolist() MMHB = resultsdf_plot9['HighestBid'].tolist() MM500 = resultsdf_plot9['AP500'].tolist() MM1000 = resultsdf_plot9['AP1000'].tolist() MMHB2 = resultsdf_plot10['HighestBid'].tolist() MM150 = resultsdf_plot10['AP150'].tolist() MM250 = resultsdf_plot10['AP250'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') f0 = figure(num = 0, figsize = (8, 12)) ax01 = subplot2grid((2, 2), (0, 0)) ax02 = subplot2grid((2, 2), (0, 1)) ax01.set_title(r'$PLR\ demand\ 15\ \%$', y=1.12) ax02.set_title(r'$PLR\ demand\ 20\ \%$', y=1.12) ax01.set_ylim(0,9) ax02.set_ylim(0,6.5) ax01.set_xlim(0,77) ax02.set_xlim(0,77) ax01.grid(True) ax02.grid(True) ax01.set_xlabel("$Total\ Wind\ Penetration\ Level\ ($%$)$") ax01.set_ylabel("$Total\ Cost\ (M$€$/day)$") ax02.set_xlabel("$Average\ Wind\ Penetration\ Level\ ($%$)$") ax02.set_ylabel("$Total\ Cost\ (M$€$/day)$") p011, = ax01.plot(WindLevel, MMHB, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p012, = ax01.plot(WindLevel, MM500, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$500\ $€$/MWh$") p013, = ax01.plot(WindLevel, MM1000, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$1000\ $€$/MWh$") p021, = ax02.plot(WindLevel, MMHB2, c=sns.xkcd_rgb["windows blue"],alpha=1, label = "$Highest\ Bid$") p022, = ax02.plot(WindLevel, MM150, c=sns.xkcd_rgb["medium green"],alpha=1, label = "$150\ $€$/MWh$") p023, = ax02.plot(WindLevel, MM250, c=sns.xkcd_rgb["pale red"],alpha=1, label = "$250\ $€$/MWh$") ax02.yaxis.tick_right() ax01.legend([p011,p012,p013], [p011.get_label(),p012.get_label(),p013.get_label()]) ax02.legend([p021,p022,p023], [p021.get_label(),p022.get_label(),p023.get_label()]) legend = ax01.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) legend = ax02.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=2, fancybox=True, shadow=True) ax01.set_axis_bgcolor('whitesmoke') ax02.set_axis_bgcolor('whitesmoke') figure(0) # f0.savefig('PLRenergycost.pdf') show() resultsdf_plot1 = pd.read_excel('PLR_plots.xlsx', 'plot11') WindLevel = resultsdf_plot1['wind_pen'].tolist() Energycost = resultsdf_plot1['cost_energy'].tolist() Fixedcost = resultsdf_plot1['relfixedcosts'].tolist() EnergycostPLR = resultsdf_plot1['cost_energyplr'].tolist() EnergycostWindPLR = resultsdf_plot1['cost_wind'].tolist() FixedcostPLR = resultsdf_plot1['relfixedcosts_plr'].tolist() PLRcost = resultsdf_plot1['cost_plr'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig = plt.figure(1) width = 0.35 ind = np.arange(len(WindLevel)) p3 = plt.bar(ind, EnergycostPLR, width, color=sns.xkcd_rgb["windows blue"], label='$Cost\ of\ Energy$') p3 = plt.bar(ind, EnergycostWindPLR, width, color=sns.xkcd_rgb["medium green"], bottom=EnergycostPLR,label='$Cost\ of\ Wind$') new = [x + y for x, y in zip(EnergycostPLR, EnergycostWindPLR)] p5 = plt.bar(ind, FixedcostPLR, width, color=sns.xkcd_rgb["amber"],bottom=new, label='$Variable\ and\ Fixed\ Cost\ Not\ Covered$') new = [x + y for x, y in zip(new, FixedcostPLR)] p4 = plt.bar(ind, PLRcost, width, color=sns.xkcd_rgb["pale red"],bottom=new, label='$Cost\ of\ PLR$') plt.grid(True, linestyle='-', which='major', color='lightgrey', alpha=0.5) plt.axis([-1, 6, 0, 450]) plt.ylabel('$Cost\ (M$€$/day)$') plt.xlabel('$Average\ Wind\ Penetration\ Level\ ($%$)$') plt.xticks(ind + width/2., ('0', '19', '33', '43', '50', '55')) plt.yticks(np.arange(0, 475, 50)) plt.legend(loc='upper center', bbox_to_anchor=(.5, 1.15), ncol=2, fancybox=True, shadow=True) axes = plt.gca() axes.set_axis_bgcolor('whitesmoke') # plt.savefig('EUPLRBARPLOT.pdf') plt.show() resultsdf_plot1 = pd.read_excel('PLR_plots.xlsx', 'plot12') # Results Iteration = resultsdf_plot1['Iterations'].tolist() Nuclear = resultsdf_plot1['NuclearProd'].tolist() Coal = resultsdf_plot1['CoalProd'].tolist() Gas = resultsdf_plot1['GasProd'].tolist() Hydro = resultsdf_plot1['HydroProd'].tolist() Oil = resultsdf_plot1['OilProd'].tolist() CapReq = resultsdf_plot1['CapRequirement'].tolist() sns.set_color_codes("dark") sns.set_style('ticks') fig, ax1 = plt.subplots() width = 0.35 # the width of the bars: can also be len(x) sequence ind = np.arange(len(Iteration)) p3 = ax1.bar(ind, Nuclear, width, color='olive', label='$Nuclear$') p4 = ax1.bar(ind, Coal, width, color='darkgreen',bottom=Nuclear, label='$Coal$') new = [x + y for x, y in zip(Nuclear, Coal)] p5 = ax1.bar(ind, Hydro, width, color='midnightblue',bottom=new, label='$Hydro$') new = [x + y for x, y in zip(new, Hydro)] p6 = ax1.bar(ind, Gas, width, color='blue',bottom=new, label='$Gas$') new = [x + y for x, y in zip(new, Gas)] p7 = ax1.bar(ind, Oil, width, color='silver',bottom=new, label='$Oil$') newxlist = (ind + width/2).tolist() Iteration = newxlist ax1.plot(Iteration, CapReq, linestyle='--', c='darkred',alpha=1, label = '$Cap.\ Req.$') ax1.grid(True, linestyle='-', which='major', color='lightgray', alpha=10000) ax1.set_xlim([-1,5]) ax1.set_ylim([0,4500]) ax1.set_ylabel('$Installed\ Capacity\ (MW)$') ax1.set_xlabel('$Iteration\ Number$') plt.xticks(ind + width/2., ('0', '1', '2', '3', '4')) ax1.legend(loc='upper center', bbox_to_anchor=(.5, 1.1), ncol=6, fancybox=True, shadow=True) ax1.set_axis_bgcolor('whitesmoke') # plt.savefig('PLR24busIteration.pdf') plt.show()

Thomsen22/MissingMoney

Plots/Peak Load Reserve Plots/plotsPLR.py

Python

gpl-3.0

13,539

[ "Amber" ]

8eeba3750c47fb27ad41bc92813e226e75697c0502a966e8b04a30a40259dc9b

import HTSeq import argparse import os.path from CommonFastaFunctions import Create_Blastdb from CommonFastaFunctions import LoadAlelleFasta from CommonFastaFunctions import LoadAlellicProfileGeneric from CommonFastaFunctions import WriteFasta from CommonFastaFunctions import runBlast from CommonFastaFunctions import runBlastParser from Bio.Blast.Applications import NcbiblastnCommandline def main(): parser = argparse.ArgumentParser(description="Given an ffn file, recovers the genes that are not paralogs and have a size bigger than the g parameter provided") parser.add_argument('-i', nargs='?', type=str, help='ffn file', required=True) parser.add_argument('-g', nargs='?', type=int, help='int minimum size', required=True) args = parser.parse_args() genes = args.i sizethresh = args.g gene_fp = HTSeq.FastaReader(genes) geneFile = os.path.abspath( genes ) Gene_Blast_DB_name = Create_Blastdb( geneFile, 1 ) geneF = os.path.splitext( geneFile )[0] blast_out_file = geneF + '.xml' # list of results - the output of the function resultsList = [] # ------------------------------ RUNNING BLAST ------------------------------ # cline = NcbiblastnCommandline(query=geneFile, db=Gene_Blast_DB_name, evalue=0.001, out=blast_out_file, outfmt=5) blast_records = runBlastParser(cline, blast_out_file, geneFile) paralogs=[] for blast_record in blast_records: try: alignment=blast_record.alignments[1] paralogs.append( alignment.hit_def) except: continue pathfiles=os.path.dirname(geneFile) pathfiles=pathfiles+"/" print pathfiles g_fp = HTSeq.FastaReader( genes ) removedparalogs=0 removedsize=0 for contig in g_fp: name = contig.name+" "+contig.descr if name not in paralogs: if int(len(contig.seq))>sizethresh: namefile=contig.name namefile=namefile.replace("|","_") with open(pathfiles+namefile+".fasta", "wb") as f: f.write(">1\n"+contig.seq+"\n") else: removedsize+=1 else: print name removedparalogs+=1 print "Removed %s paralog genes" % str(removedparalogs) print "Removed %s because of size :" % str(removedsize) if __name__ == "__main__": main()

mickaelsilva/pythonscripts

AlleleCalling/ParalogRemove.py

Python

gpl-2.0

2,157

[ "BLAST", "HTSeq" ]

f83585c846b49b185a113d693e3bb14157435f965a52d0696133988828962194

# encoding: utf-8 import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding field 'Indicator.source' db.add_column('profiles_indicator', 'source', self.gf('django.db.models.fields.CharField')(default='U.S. Census Bureau', max_length=300, blank=True), keep_default=False) def backwards(self, orm): # Deleting field 'Indicator.source' db.delete_column('profiles_indicator', 'source') models = { 'auth.group': { 'Meta': {'object_name': 'Group'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, 'auth.permission': { 'Meta': {'ordering': "('content_type__app_label', 'content_type__model', 'codename')", 'unique_together': "(('content_type', 'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['contenttypes.ContentType']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, 'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, 'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, 'profiles.datadomain': { 'Meta': {'ordering': "['weight']", 'object_name': 'DataDomain'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicators': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.Indicator']", 'through': "orm['profiles.IndicatorDomain']", 'symmetrical': 'False'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100', 'db_index': 'True'}), 'subdomain_only': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'subdomains': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.DataDomain']", 'symmetrical': 'False', 'blank': 'True'}), 'weight': ('django.db.models.fields.PositiveIntegerField', [], {'default': '1'}) }, 'profiles.datapoint': { 'Meta': {'unique_together': "(('indicator', 'record', 'time'),)", 'object_name': 'DataPoint'}, 'change_from_time': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'datapoint_as_change_from'", 'null': 'True', 'to': "orm['profiles.Time']"}), 'change_to_time': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'datapoint_as_change_to'", 'null': 'True', 'to': "orm['profiles.Time']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'image': ('sorl.thumbnail.fields.ImageField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'record': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoRecord']"}), 'time': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Time']", 'null': 'True'}) }, 'profiles.datasource': { 'Meta': {'object_name': 'DataSource'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'implementation': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}) }, 'profiles.denominator': { 'Meta': {'object_name': 'Denominator'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'label': ('django.db.models.fields.CharField', [], {'max_length': '50'}), 'multiplier': ('django.db.models.fields.PositiveIntegerField', [], {'null': 'True', 'blank': 'True'}), 'sort': ('django.db.models.fields.PositiveIntegerField', [], {'default': '1'}) }, 'profiles.denominatorpart': { 'Meta': {'object_name': 'DenominatorPart'}, 'data': ('django.db.models.fields.files.FileField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'data_source': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataSource']"}), 'denominator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Denominator']"}), 'formula': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'part': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.IndicatorPart']"}) }, 'profiles.geolevel': { 'Meta': {'object_name': 'GeoLevel'}, 'data_sources': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.DataSource']", 'symmetrical': 'False'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '200'}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoLevel']", 'null': 'True', 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '200', 'db_index': 'True'}) }, 'profiles.georecord': { 'Meta': {'unique_together': "(('slug', 'level'), ('level', 'geo_id', 'custom_name', 'owner'))", 'object_name': 'GeoRecord'}, 'components': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'components_rel_+'", 'blank': 'True', 'to': "orm['profiles.GeoRecord']"}), 'custom_name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'geo_id': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'geom': ('django.contrib.gis.db.models.fields.GeometryField', [], {'null': 'True', 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'level': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoLevel']"}), 'mappings': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'mappings_rel_+'", 'blank': 'True', 'to': "orm['profiles.GeoRecord']"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'notes': ('django.db.models.fields.TextField', [], {'null': 'True', 'blank': 'True'}), 'owner': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['auth.User']", 'null': 'True', 'blank': 'True'}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoRecord']", 'null': 'True', 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'db_index': 'True', 'max_length': '100', 'blank': 'True'}) }, 'profiles.indicator': { 'Meta': {'object_name': 'Indicator'}, 'data_domains': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.DataDomain']", 'through': "orm['profiles.IndicatorDomain']", 'symmetrical': 'False'}), 'data_type': ('django.db.models.fields.CharField', [], {'default': "'COUNT'", 'max_length': '30'}), 'display_change': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'display_distribution': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'display_name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'display_percent': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'levels': ('django.db.models.fields.related.ManyToManyField', [], {'to': "orm['profiles.GeoLevel']", 'symmetrical': 'False'}), 'limitations': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'long_definition': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '100'}), 'notes': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'published': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'purpose': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'routine_use': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'short_definition': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '100', 'db_index': 'True'}), 'source': ('django.db.models.fields.CharField', [], {'default': "'U.S. Census Bureau'", 'max_length': '300', 'blank': 'True'}), 'universe': ('django.db.models.fields.CharField', [], {'max_length': '300', 'blank': 'True'}) }, 'profiles.indicatordomain': { 'Meta': {'object_name': 'IndicatorDomain'}, 'default': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'domain': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataDomain']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}) }, 'profiles.indicatorpart': { 'Meta': {'object_name': 'IndicatorPart'}, 'data': ('django.db.models.fields.files.FileField', [], {'max_length': '100', 'null': 'True', 'blank': 'True'}), 'data_source': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataSource']"}), 'formula': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'indicator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Indicator']"}), 'time': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Time']"}) }, 'profiles.precalculatedvalue': { 'Meta': {'object_name': 'PrecalculatedValue'}, 'data_source': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataSource']"}), 'geo_record': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.GeoRecord']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'notes': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'table': ('django.db.models.fields.TextField', [], {'blank': 'True'}), 'value': ('django.db.models.fields.TextField', [], {'blank': 'True'}) }, 'profiles.time': { 'Meta': {'object_name': 'Time'}, 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '20'}), 'sort': ('django.db.models.fields.DecimalField', [], {'max_digits': '5', 'decimal_places': '1'}) }, 'profiles.value': { 'Meta': {'object_name': 'Value'}, 'datapoint': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.DataPoint']"}), 'denominator': ('django.db.models.fields.related.ForeignKey', [], {'to': "orm['profiles.Denominator']", 'null': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'moe': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'number': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}), 'percent': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '10', 'decimal_places': '2', 'blank': 'True'}) } } complete_apps = ['profiles']

216software/Profiles

communityprofiles/profiles/oldmigrations/0045_auto__add_field_indicator_source.py

Python

mit

15,170

[ "MOE" ]

0501be25706d5ba972b8c72750649f4327d8fc1a03b25d4bad9751e6f62d4086

# Licensed under a 3-clause BSD style license - see LICENSE.rst """ LAMDA Query Tool ---------------- :Author: Brian Svoboda (svobodb@email.arizona.edu) This package is for querying the Leiden Atomic and Molecular Database (LAMDA) hosted at: http://home.strw.leidenuniv.nl/~moldata/. Note: If you use the data files from LAMDA in your research work please refer to the publication by Schoier, F.L., van der Tak, F.F.S., van Dishoeck E.F., Black, J.H. 2005, A&A 432, 369-379. When individual molecules are considered, references to the original papers providing the spectroscopic and collisional data are encouraged. """ from .core import Lamda, parse_lamda_datafile, write_lamda_datafile

ceb8/astroquery

astroquery/lamda/__init__.py

Python

bsd-3-clause

701

[ "Brian" ]

3a2623fb883c350d2543abca0bfee4951d9f0ce1a0980c9277e3bce4f3ae77de

# -*- coding: utf-8 -*- from __future__ import absolute_import from django.conf import settings from django.http import HttpResponse from django.test import TestCase from zilencer.models import Deployment from zerver.views import get_invitee_emails_set, do_change_password from zerver.models import ( get_realm, get_user_profile_by_email, PreregistrationUser, Realm, Recipient, ScheduledJob, UserProfile, UserMessage, ) from zerver.lib.actions import ( create_stream_if_needed, do_add_subscription, set_default_streams, ) from zerver.lib.initial_password import initial_password from zerver.lib.actions import do_set_realm_default_language from zerver.lib.digest import send_digest_email from zerver.lib.notifications import enqueue_welcome_emails, one_click_unsubscribe_link from zerver.lib.test_helpers import ZulipTestCase, find_key_by_email, queries_captured from zerver.lib.test_runner import slow from zerver.lib.session_user import get_session_dict_user import re import ujson from six.moves import urllib from six.moves import range import six from six import text_type class PublicURLTest(ZulipTestCase): """ Account creation URLs are accessible even when not logged in. Authenticated URLs redirect to a page. """ def fetch(self, method, urls, expected_status): # type: (str, List[str], int) -> None for url in urls: response = getattr(self.client, method)(url) # e.g. self.client_post(url) if method is "post" self.assertEqual(response.status_code, expected_status, msg="Expected %d, received %d for %s to %s" % ( expected_status, response.status_code, method, url)) def test_public_urls(self): # type: () -> None """ Test which views are accessible when not logged in. """ # FIXME: We should also test the Tornado URLs -- this codepath # can't do so because this Django test mechanism doesn't go # through Tornado. get_urls = {200: ["/accounts/home/", "/accounts/login/"], 302: ["/"], 401: ["/api/v1/streams/Denmark/members", "/api/v1/users/me/subscriptions", "/api/v1/messages", "/json/messages", "/json/streams", ], } post_urls = {200: ["/accounts/login/"], 302: ["/accounts/logout/"], 401: ["/json/messages", "/json/invite_users", "/json/settings/change", "/json/subscriptions/remove", "/json/subscriptions/exists", "/json/subscriptions/property", "/json/get_subscribers", "/json/fetch_api_key", "/json/users/me/subscriptions", "/api/v1/users/me/subscriptions", ], 400: ["/api/v1/send_message", "/api/v1/external/github", "/api/v1/fetch_api_key", ], } put_urls = {401: ["/json/users/me/pointer"], } for status_code, url_set in six.iteritems(get_urls): self.fetch("get", url_set, status_code) for status_code, url_set in six.iteritems(post_urls): self.fetch("post", url_set, status_code) for status_code, url_set in six.iteritems(put_urls): self.fetch("put", url_set, status_code) def test_get_gcid_when_not_configured(self): # type: () -> None with self.settings(GOOGLE_CLIENT_ID=None): resp = self.client_get("/api/v1/fetch_google_client_id") self.assertEquals(400, resp.status_code, msg="Expected 400, received %d for GET /api/v1/fetch_google_client_id" % resp.status_code, ) data = ujson.loads(resp.content) self.assertEqual('error', data['result']) def test_get_gcid_when_configured(self): # type: () -> None with self.settings(GOOGLE_CLIENT_ID="ABCD"): resp = self.client_get("/api/v1/fetch_google_client_id") self.assertEquals(200, resp.status_code, msg="Expected 200, received %d for GET /api/v1/fetch_google_client_id" % resp.status_code, ) data = ujson.loads(resp.content) self.assertEqual('success', data['result']) self.assertEqual('ABCD', data['google_client_id']) class PasswordResetTest(ZulipTestCase): """ Log in, reset password, log out, log in with new password. """ def test_password_reset(self): # type: () -> None email = 'hamlet@zulip.com' old_password = initial_password(email) self.login(email) # start the password reset process by supplying an email address result = self.client_post('/accounts/password/reset/', {'email': email}) # check the redirect link telling you to check mail for password reset link self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/password/reset/done/")) result = self.client_get(result["Location"]) self.assert_in_response("Check your email to finish the process.", result) # visit password reset link from django.core.mail import outbox for message in reversed(outbox): if email in message.to: password_reset_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)") password_reset_url = password_reset_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a password reset email.") result = self.client_get(password_reset_url) self.assertEquals(result.status_code, 200) # Reset your password result = self.client_post(password_reset_url, {'new_password1': 'new_password', 'new_password2': 'new_password'}) # password reset succeeded self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith("/password/done/")) # log back in with new password self.login(email, password='new_password') user_profile = get_user_profile_by_email('hamlet@zulip.com') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) # make sure old password no longer works self.login(email, password=old_password, fails=True) class LoginTest(ZulipTestCase): """ Logging in, registration, and logging out. """ def test_login(self): # type: () -> None self.login("hamlet@zulip.com") user_profile = get_user_profile_by_email('hamlet@zulip.com') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_login_bad_password(self): # type: () -> None self.login("hamlet@zulip.com", password="wrongpassword", fails=True) self.assertIsNone(get_session_dict_user(self.client.session)) def test_login_nonexist_user(self): # type: () -> None result = self.login_with_return("xxx@zulip.com", "xxx") self.assert_in_response("Please enter a correct email and password", result) def test_register(self): # type: () -> None realm = get_realm("zulip.com") streams = ["stream_%s" % i for i in range(40)] for stream in streams: create_stream_if_needed(realm, stream) set_default_streams(realm, streams) with queries_captured() as queries: self.register("test", "test") # Ensure the number of queries we make is not O(streams) self.assert_length(queries, 67) user_profile = get_user_profile_by_email('test@zulip.com') self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_register_deactivated(self): # type: () -> None """ If you try to register for a deactivated realm, you get a clear error page. """ realm = get_realm("zulip.com") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.register("test", "test") self.assert_in_response("has been deactivated", result) with self.assertRaises(UserProfile.DoesNotExist): get_user_profile_by_email('test@zulip.com') def test_login_deactivated(self): # type: () -> None """ If you try to log in to a deactivated realm, you get a clear error page. """ realm = get_realm("zulip.com") realm.deactivated = True realm.save(update_fields=["deactivated"]) result = self.login_with_return("hamlet@zulip.com") self.assert_in_response("has been deactivated", result) def test_logout(self): # type: () -> None self.login("hamlet@zulip.com") self.client_post('/accounts/logout/') self.assertIsNone(get_session_dict_user(self.client.session)) def test_non_ascii_login(self): # type: () -> None """ You can log in even if your password contain non-ASCII characters. """ email = "test@zulip.com" password = u"hÃ¼mbÃ¼Çµ" # Registering succeeds. self.register("test", password) user_profile = get_user_profile_by_email(email) self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) self.client_post('/accounts/logout/') self.assertIsNone(get_session_dict_user(self.client.session)) # Logging in succeeds. self.client_post('/accounts/logout/') self.login(email, password) self.assertEqual(get_session_dict_user(self.client.session), user_profile.id) def test_register_first_user_with_invites(self): # type: () -> None """ The first user in a realm has a special step in their signup workflow for inviting other users. Do as realistic an end-to-end test as we can without Tornado running. """ username = "user1" password = "test" domain = "test.com" email = "user1@test.com" # Create a new realm to ensure that we're the first user in it. Realm.objects.create(domain=domain, name="Test Inc.") # Start the signup process by supplying an email address. result = self.client_post('/accounts/home/', {'email': email}) # Check the redirect telling you to check your mail for a confirmation # link. self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s@%s" % (username, domain))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url) self.assertEquals(result.status_code, 200) # Pick a password and agree to the ToS. result = self.submit_reg_form_for_user(username, password, domain) self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith("/invite/")) # Invite other users to join you. result = self.client_get(result["Location"]) self.assert_in_response("You're the first one here!", result) # Reset the outbox for our invites. outbox.pop() invitees = ['alice@' + domain, 'bob@' + domain] params = { 'invitee_emails': ujson.dumps(invitees) } result = self.client_post('/json/bulk_invite_users', params) self.assert_json_success(result) # We really did email these users, and they have PreregistrationUser # objects. email_recipients = [message.recipients()[0] for message in outbox] self.assertEqual(len(outbox), len(invitees)) self.assertEqual(sorted(email_recipients), sorted(invitees)) user_profile = get_user_profile_by_email(email) self.assertEqual(len(invitees), PreregistrationUser.objects.filter( referred_by=user_profile).count()) # After this we start manipulating browser information, so stop here. class InviteUserTest(ZulipTestCase): def invite(self, users, streams): # type: (str, List[text_type]) -> HttpResponse """ Invites the specified users to Zulip with the specified streams. users should be a string containing the users to invite, comma or newline separated. streams should be a list of strings. """ return self.client_post("/json/invite_users", {"invitee_emails": users, "stream": streams}) def check_sent_emails(self, correct_recipients): # type: (List[str]) -> None from django.core.mail import outbox self.assertEqual(len(outbox), len(correct_recipients)) email_recipients = [email.recipients()[0] for email in outbox] self.assertEqual(sorted(email_recipients), sorted(correct_recipients)) def test_bulk_invite_users(self): # type: () -> None """The bulk_invite_users code path is for the first user in a realm.""" self.login('hamlet@zulip.com') invitees = ['alice@zulip.com', 'bob@zulip.com'] params = { 'invitee_emails': ujson.dumps(invitees) } result = self.client_post('/json/bulk_invite_users', params) self.assert_json_success(result) self.check_sent_emails(invitees) def test_successful_invite_user(self): # type: () -> None """ A call to /json/invite_users with valid parameters causes an invitation email to be sent. """ self.login("hamlet@zulip.com") invitee = "alice-test@zulip.com" self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(invitee)) self.check_sent_emails([invitee]) def test_successful_invite_user_with_name(self): # type: () -> None """ A call to /json/invite_users with valid parameters causes an invitation email to be sent. """ self.login("hamlet@zulip.com") email = "alice-test@zulip.com" invitee = "Alice Test <{}>".format(email) self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.check_sent_emails([email]) def test_successful_invite_user_with_name_and_normal_one(self): # type: () -> None """ A call to /json/invite_users with valid parameters causes an invitation email to be sent. """ self.login("hamlet@zulip.com") email = "alice-test@zulip.com" email2 = "bob-test@zulip.com" invitee = "Alice Test <{}>, {}".format(email, email2) self.assert_json_success(self.invite(invitee, ["Denmark"])) self.assertTrue(find_key_by_email(email)) self.assertTrue(find_key_by_email(email2)) self.check_sent_emails([email, email2]) def test_invite_user_signup_initial_history(self): # type: () -> None """ Test that a new user invited to a stream receives some initial history but only from public streams. """ self.login("hamlet@zulip.com") user_profile = get_user_profile_by_email("hamlet@zulip.com") private_stream_name = "Secret" (stream, _) = create_stream_if_needed(user_profile.realm, private_stream_name, invite_only=True) do_add_subscription(user_profile, stream) public_msg_id = self.send_message("hamlet@zulip.com", "Denmark", Recipient.STREAM, "Public topic", "Public message") secret_msg_id = self.send_message("hamlet@zulip.com", private_stream_name, Recipient.STREAM, "Secret topic", "Secret message") invitee = "alice-test@zulip.com" self.assert_json_success(self.invite(invitee, [private_stream_name, "Denmark"])) self.assertTrue(find_key_by_email(invitee)) self.submit_reg_form_for_user("alice-test", "password") invitee_profile = get_user_profile_by_email(invitee) invitee_msg_ids = [um.message_id for um in UserMessage.objects.filter(user_profile=invitee_profile)] self.assertTrue(public_msg_id in invitee_msg_ids) self.assertFalse(secret_msg_id in invitee_msg_ids) def test_multi_user_invite(self): # type: () -> None """ Invites multiple users with a variety of delimiters. """ self.login("hamlet@zulip.com") # Intentionally use a weird string. self.assert_json_success(self.invite( """bob-test@zulip.com, carol-test@zulip.com, dave-test@zulip.com earl-test@zulip.com""", ["Denmark"])) for user in ("bob", "carol", "dave", "earl"): self.assertTrue(find_key_by_email("%s-test@zulip.com" % (user,))) self.check_sent_emails(["bob-test@zulip.com", "carol-test@zulip.com", "dave-test@zulip.com", "earl-test@zulip.com"]) def test_missing_or_invalid_params(self): # type: () -> None """ Tests inviting with various missing or invalid parameters. """ self.login("hamlet@zulip.com") self.assert_json_error( self.client_post("/json/invite_users", {"invitee_emails": "foo@zulip.com"}), "You must specify at least one stream for invitees to join.") for address in ("noatsign.com", "outsideyourdomain@example.net"): self.assert_json_error( self.invite(address, ["Denmark"]), "Some emails did not validate, so we didn't send any invitations.") self.check_sent_emails([]) def test_invalid_stream(self): # type: () -> None """ Tests inviting to a non-existent stream. """ self.login("hamlet@zulip.com") self.assert_json_error(self.invite("iago-test@zulip.com", ["NotARealStream"]), "Stream does not exist: NotARealStream. No invites were sent.") self.check_sent_emails([]) def test_invite_existing_user(self): # type: () -> None """ If you invite an address already using Zulip, no invitation is sent. """ self.login("hamlet@zulip.com") self.assert_json_error( self.client_post("/json/invite_users", {"invitee_emails": "hamlet@zulip.com", "stream": ["Denmark"]}), "We weren't able to invite anyone.") self.assertRaises(PreregistrationUser.DoesNotExist, lambda: PreregistrationUser.objects.get( email="hamlet@zulip.com")) self.check_sent_emails([]) def test_invite_some_existing_some_new(self): # type: () -> None """ If you invite a mix of already existing and new users, invitations are only sent to the new users. """ self.login("hamlet@zulip.com") existing = ["hamlet@zulip.com", "othello@zulip.com"] new = ["foo-test@zulip.com", "bar-test@zulip.com"] result = self.client_post("/json/invite_users", {"invitee_emails": "\n".join(existing + new), "stream": ["Denmark"]}) self.assert_json_error(result, "Some of those addresses are already using Zulip, \ so we didn't send them an invitation. We did send invitations to everyone else!") # We only created accounts for the new users. for email in existing: self.assertRaises(PreregistrationUser.DoesNotExist, lambda: PreregistrationUser.objects.get( email=email)) for email in new: self.assertTrue(PreregistrationUser.objects.get(email=email)) # We only sent emails to the new users. self.check_sent_emails(new) def test_invite_outside_domain_in_closed_realm(self): # type: () -> None """ In a realm with `restricted_to_domain = True`, you can't invite people with a different domain from that of the realm or your e-mail address. """ zulip_realm = get_realm("zulip.com") zulip_realm.restricted_to_domain = True zulip_realm.save() self.login("hamlet@zulip.com") external_address = "foo@example.com" self.assert_json_error( self.invite(external_address, ["Denmark"]), "Some emails did not validate, so we didn't send any invitations.") def test_invite_outside_domain_in_open_realm(self): # type: () -> None """ In a realm with `restricted_to_domain = False`, you can invite people with a different domain from that of the realm or your e-mail address. """ zulip_realm = get_realm("zulip.com") zulip_realm.restricted_to_domain = False zulip_realm.save() self.login("hamlet@zulip.com") external_address = "foo@example.com" self.assert_json_success(self.invite(external_address, ["Denmark"])) self.check_sent_emails([external_address]) def test_invite_with_non_ascii_streams(self): # type: () -> None """ Inviting someone to streams with non-ASCII characters succeeds. """ self.login("hamlet@zulip.com") invitee = "alice-test@zulip.com" stream_name = u"hÃ¼mbÃ¼Çµ" realm = get_realm("zulip.com") stream, _ = create_stream_if_needed(realm, stream_name) # Make sure we're subscribed before inviting someone. do_add_subscription( get_user_profile_by_email("hamlet@zulip.com"), stream, no_log=True) self.assert_json_success(self.invite(invitee, [stream_name])) class InviteeEmailsParserTests(TestCase): def setUp(self): # type: () -> None self.email1 = "email1@zulip.com" self.email2 = "email2@zulip.com" self.email3 = "email3@zulip.com" def test_if_emails_separated_by_commas_are_parsed_and_striped_correctly(self): # type: () -> None emails_raw = "{} ,{}, {}".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_separated_by_newlines_are_parsed_and_striped_correctly(self): # type: () -> None emails_raw = "{}\n {}\n {} ".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_from_email_client_separated_by_newlines_are_parsed_correctly(self): # type: () -> None emails_raw = "Email One <{}>\nEmailTwo<{}>\nEmail Three<{}>".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) def test_if_emails_in_mixed_style_are_parsed_correctly(self): # type: () -> None emails_raw = "Email One <{}>,EmailTwo<{}>\n{}".format(self.email1, self.email2, self.email3) expected_set = {self.email1, self.email2, self.email3} self.assertEqual(get_invitee_emails_set(emails_raw), expected_set) class EmailUnsubscribeTests(ZulipTestCase): def test_missedmessage_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in missed message e-mails that you can click even when logged out to update your email notification settings. """ user_profile = get_user_profile_by_email("hamlet@zulip.com") user_profile.enable_offline_email_notifications = True user_profile.save() unsubscribe_link = one_click_unsubscribe_link(user_profile, "missed_messages") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) self.assertEqual(result.status_code, 200) # Circumvent user_profile caching. user_profile = UserProfile.objects.get(email="hamlet@zulip.com") self.assertFalse(user_profile.enable_offline_email_notifications) def test_welcome_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in welcome e-mails that you can click even when logged out to stop receiving them. """ email = "hamlet@zulip.com" user_profile = get_user_profile_by_email("hamlet@zulip.com") # Simulate a new user signing up, which enqueues 2 welcome e-mails. enqueue_welcome_emails(email, "King Hamlet") self.assertEqual(2, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) # Simulate unsubscribing from the welcome e-mails. unsubscribe_link = one_click_unsubscribe_link(user_profile, "welcome") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) # The welcome email jobs are no longer scheduled. self.assertEqual(result.status_code, 200) self.assertEqual(0, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) def test_digest_unsubscribe(self): # type: () -> None """ We provide one-click unsubscribe links in digest e-mails that you can click even when logged out to stop receiving them. Unsubscribing from these emails also dequeues any digest email jobs that have been queued. """ email = "hamlet@zulip.com" user_profile = get_user_profile_by_email("hamlet@zulip.com") self.assertTrue(user_profile.enable_digest_emails) # Enqueue a fake digest email. send_digest_email(user_profile, "", "") self.assertEqual(1, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) # Simulate unsubscribing from digest e-mails. unsubscribe_link = one_click_unsubscribe_link(user_profile, "digest") result = self.client_get(urllib.parse.urlparse(unsubscribe_link).path) # The setting is toggled off, and scheduled jobs have been removed. self.assertEqual(result.status_code, 200) # Circumvent user_profile caching. user_profile = UserProfile.objects.get(email="hamlet@zulip.com") self.assertFalse(user_profile.enable_digest_emails) self.assertEqual(0, len(ScheduledJob.objects.filter( type=ScheduledJob.EMAIL, filter_string__iexact=email))) class RealmCreationTest(ZulipTestCase): def test_create_realm(self): # type: () -> None username = "user1" password = "test" domain = "test.com" email = "user1@test.com" # Make sure the realm does not exist self.assertIsNone(get_realm("test.com")) with self.settings(OPEN_REALM_CREATION=True): # Create new realm with the email result = self.client_post('/create_realm/', {'email': email}) self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s@%s" % (username, domain))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url) self.assertEquals(result.status_code, 200) result = self.submit_reg_form_for_user(username, password, domain) self.assertEquals(result.status_code, 302) # Make sure the realm is created realm = get_realm("test.com") self.assertIsNotNone(realm) self.assertEqual(realm.domain, domain) self.assertEqual(get_user_profile_by_email(email).realm, realm) self.assertTrue(result["Location"].endswith("/invite/")) result = self.client_get(result["Location"]) self.assert_in_response("You're the first one here!", result) class UserSignUpTest(ZulipTestCase): def test_user_default_language(self): # type: () -> None """ Check if the default language of new user is the default language of the realm. """ username = "newguy" email = "newguy@zulip.com" domain = "zulip.com" password = "newpassword" realm = get_realm(domain) do_set_realm_default_language(realm, "de") result = self.client_post('/accounts/home/', {'email': email}) self.assertEquals(result.status_code, 302) self.assertTrue(result["Location"].endswith( "/accounts/send_confirm/%s@%s" % (username, domain))) result = self.client_get(result["Location"]) self.assert_in_response("Check your email so we can get started.", result) # Visit the confirmation link. from django.core.mail import outbox for message in reversed(outbox): if email in message.to: confirmation_link_pattern = re.compile(settings.EXTERNAL_HOST + "(\S+)>") confirmation_url = confirmation_link_pattern.search( message.body).groups()[0] break else: raise ValueError("Couldn't find a confirmation email.") result = self.client_get(confirmation_url) self.assertEquals(result.status_code, 200) # Pick a password and agree to the ToS. result = self.submit_reg_form_for_user(username, password, domain) self.assertEquals(result.status_code, 302) user_profile = get_user_profile_by_email(email) self.assertEqual(user_profile.default_language, realm.default_language) outbox.pop()

ahmadassaf/zulip

zerver/tests/test_signup.py

Python

apache-2.0

31,655

[ "VisIt" ]

ea8c3e7a34939c0b000c13755754e3d1b118bf899c57479e78f62df46521e184

# -*- coding: utf-8 -*- ## begin license ## # # "Meresco Components" are components to build searchengines, repositories # and archives, based on "Meresco Core". # # Copyright (C) 2007-2008 SURF Foundation. http://www.surf.nl # Copyright (C) 2007-2011 Seek You Too (CQ2) http://www.cq2.nl # Copyright (C) 2007-2009 Stichting Kennisnet Ict op school. http://www.kennisnetictopschool.nl # Copyright (C) 2009 Delft University of Technology http://www.tudelft.nl # Copyright (C) 2009 Tilburg University http://www.uvt.nl # Copyright (C) 2011, 2015, 2020 Stichting Kennisnet https://www.kennisnet.nl # Copyright (C) 2012, 2015, 2017-2018, 2020 Seecr (Seek You Too B.V.) https://seecr.nl # Copyright (C) 2017, 2020 SURF https://www.surf.nl # Copyright (C) 2020 Data Archiving and Network Services https://dans.knaw.nl # Copyright (C) 2020 The Netherlands Institute for Sound and Vision https://beeldengeluid.nl # # This file is part of "Meresco Components" # # "Meresco Components" is free software; you can redistribute it and/or modify # it under the terms of the GNU General Public License as published by # the Free Software Foundation; either version 2 of the License, or # (at your option) any later version. # # "Meresco Components" is distributed in the hope that it will be useful, # but WITHOUT ANY WARRANTY; without even the implied warranty of # MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the # GNU General Public License for more details. # # You should have received a copy of the GNU General Public License # along with "Meresco Components"; if not, write to the Free Software # Foundation, Inc., 51 Franklin St, Fifth Floor, Boston, MA 02110-1301 USA # ## end license ## import re UNQUOTED_STRING = r'(?P<unquoted>[\+\-]?[^"\s]+)' QUOTED_STRING = r'(?P<quotedString>[\+\-]?(?P<quot>\")(?P<quoted>.+?)((?<!\\)(?P=quot)))' QUOTED_LABEL_STRING = r'(?P<labelString>[\+\-]?(?P<label>[^"\s]+)=(?P<quot1>\")(?P<quoted1>.+?)((?<!\\)(?P=quot1)))' STRINGS = [QUOTED_LABEL_STRING ,QUOTED_STRING, UNQUOTED_STRING] SPLITTED_STRINGS = re.compile(r'\s*(%s)' % '|'.join(STRINGS)) from cqlparser import parseString, CQLParseException, cql2string, CqlIdentityVisitor, cqlToExpression, CQLTokenizerException, quotTerm from cqlparser.cqlparser import CQL_QUERY, SCOPED_CLAUSE, SEARCH_CLAUSE, SEARCH_TERM, TERM, BOOLEAN, INDEX, RELATION, COMPARITOR DEFAULT_KIND, PLUSMINUS_KIND, BOOLEAN_KIND = list(range(3)) class WebQuery(object): def __init__(self, aString, antiUnaryClause=""): self.original = aString try: plusminus = _feelsLikePlusMinusQuery(aString) boolean = _feelsLikeBooleanQuery(aString) self._needsHelp = boolean and plusminus if plusminus and not boolean: self._kind = PLUSMINUS_KIND self.ast = parseString(_plusminus2Cql(aString, antiUnaryClause)) elif boolean and not plusminus: try: self._kind = BOOLEAN_KIND self.ast = parseString(_boolean2Cql(aString, antiUnaryClause)) except CQLParseException: self._needsHelp = True self._kind = DEFAULT_KIND self.ast = parseString(_default2CqlWithQuotes(aString, antiUnaryClause=antiUnaryClause)) else: self._kind = DEFAULT_KIND try: self.ast = parseString(_default2Cql(aString, antiUnaryClause=antiUnaryClause)) except CQLParseException: self._needsHelp = True self.ast = parseString(_default2CqlWithQuotes(aString, antiUnaryClause=antiUnaryClause)) except (CQLParseException, CQLTokenizerException): self.ast = parseString(quotTerm(self.original)) self.originalAst = self.ast self._filters = [] def addTermFilter(self, term): self._addFilter(SEARCH_CLAUSE( SEARCH_TERM( TERM(term) ) )) @property def query(self): return cqlToExpression(self.ast) def addFilter(self, field, term): self._addFilter(SEARCH_CLAUSE( INDEX(TERM(field)), RELATION(COMPARITOR('exact')), SEARCH_TERM(TERM(term)) )) def _addFilter(self, filterQuery): self._filters.append(filterQuery) insertOriginalAst = SCOPED_CLAUSE(SEARCH_CLAUSE(self.ast)) if len(self._filters) == 1 else self.ast.children[0] self.ast = CQL_QUERY( SCOPED_CLAUSE( insertOriginalAst, BOOLEAN('and'), filterQuery ) ) def replaceTerm(self, oldTerm, newTerm): newAst = CqlReplaceTerm(self.originalAst, oldTerm, newTerm).visit() result = WebQuery(cql2string(newAst)) for f in self._filters: result._addFilter(f) return result def replaceIndex(self, mapping): newAst = CqlReplaceIndex(self.originalAst, mapping).visit() result = WebQuery(cql2string(newAst)) for f in self._filters: result._addFilter(f) return result def asString(self): return cql2string(self.ast) def isBooleanQuery(self): return self._kind == BOOLEAN_KIND def isPlusMinusQuery(self): return self._kind == PLUSMINUS_KIND def isDefaultQuery(self): return self._kind == DEFAULT_KIND def needsBooleanHelp(self): return self._needsHelp def hasFilters(self): return len(self._filters) > 0 class CqlReplaceTerm(CqlIdentityVisitor): def __init__(self, ast, oldTerm, newTerm): CqlIdentityVisitor.__init__(self, ast) self._oldTerm = oldTerm self._newTerm = newTerm def visitTERM(self, node): if node.children[0] == self._oldTerm: return node.__class__(self._newTerm) return CqlIdentityVisitor.visitTERM(self, node) class CqlReplaceIndex(CqlIdentityVisitor): def __init__(self, ast, mapping): CqlIdentityVisitor.__init__(self, ast) self._mapping = mapping def visitINDEX(self, node): indexTerm = node.children[0].children[0] if indexTerm in self._mapping: return INDEX(TERM(self._mapping[indexTerm])) return CqlIdentityVisitor.visitINDEX(self, node) def _feelsLikePlusMinusQuery(aString): for part in (_valueFromGroupdict(m.groupdict()).lower() for m in SPLITTED_STRINGS.finditer(aString)): if part[0] in ['-', '+'] and len(part) > 1: return part[1] not in ['-', '+'] return False def _feelsLikeBooleanQuery(aString): for part in (_valueFromGroupdict(m.groupdict()).lower() for m in SPLITTED_STRINGS.finditer(aString)): if part in ['and', 'or', 'not']: return True elif part[0] == '(' or part[-1] == ')': return True return False def _joinFieldAndTerm(fieldAndTermList): results = [] for field, term in (tuple(fieldAndTerm.split(':', 1)) for fieldAndTerm in fieldAndTermList): if ' ' in term: term = '"%s"' % term results.append('%s exact %s' % (field, term)) if len(results) == 1: return results[0] return ' AND '.join('(%s)' % result for result in results) def _plusminus2Cql(aString, antiUnaryClause): newParts = [] for match in SPLITTED_STRINGS.finditer(aString): part = _valueFromGroupdict(match.groupdict()) if part[0] == '+': newParts.append(part[1:]) elif part[0] == '-': notStatement = 'NOT ' + part[1:] if len(newParts) == 0: newParts.append(antiUnaryClause + " " + notStatement) else: newParts[-1] = newParts[-1] + ' ' + notStatement else: newParts.append(part) return ' AND '.join(newParts) def _boolean2Cql(aString, antiUnaryClause): aString = aString.replace('(', ' ( ').replace(')', ' ) ') newParts = [] for match in SPLITTED_STRINGS.finditer(aString): part = _valueFromGroupdict(match.groupdict()) partAsToken = part.lower() if partAsToken == 'not': if len(newParts) == 0 or newParts[-1] == '(': newParts.append(antiUnaryClause) if partAsToken in ['not', 'and', 'or']: part = part.upper() newParts.append(part) return ' '.join(newParts) def _default2CqlWithQuotes(aString, antiUnaryClause="ignored"): if aString.strip() == '': return antiUnaryClause return ' AND '.join(quot(_valueFromGroupdict(match.groupdict())) for match in SPLITTED_STRINGS.finditer(aString)) def _default2Cql(aString, antiUnaryClause="ignored"): if aString.strip() == '': return antiUnaryClause try: cqlToExpression(aString) return aString except (CQLParseException, CQLTokenizerException): return ' AND '.join(_valueFromGroupdict(match.groupdict()) for match in SPLITTED_STRINGS.finditer(aString)) def quot(aString): if aString[-1] == '"' == aString[0]: return aString return '"%s"' % aString def _valueFromGroupdict(groupdict): return groupdict['unquoted'] or groupdict['quotedString'] or groupdict['labelString']

seecr/meresco-components

meresco/components/web/webquery.py

Python

gpl-2.0

9,266

[ "VisIt" ]

1cc83756ba59b8ce612424796ea1a397539c1b273ed29d9c8d5ed3a8605d799d

from suggestive.util import retry_function, retry from suggestive.error import RetryError import logging import webbrowser import pylastfm logger = logging.getLogger(__name__) logger.addHandler(logging.NullHandler()) def get(data, keys, default=None): if not keys: return data if not isinstance(data, dict): raise TypeError('not a dictionary') key, rest = keys[0], keys[1:] if key not in data: return default return get(data[key], rest, default=default) class LastFM(object): """ Helper class for communicating with Last.FM servers """ def __init__(self, config): self.config = config self.client = self._initialize_client() def _get_user_permission(self, token): """Attempt to open up authorization URL in browser. If this fails, simply display a message in the console asking user to manually open URL""" url = 'http://www.last.fm/api/auth/?api_key={0}&token={1}'.format( self.config.lastfm.api_key, token) try: webbrowser.open_new_tab(url) except Exception: pass message = """\ No LastFM session found; to authorize suggestive, visit this URL and click 'Yes, allow access', then return to this window: {url} Press Enter to continue...""".format(url=url) input(message) def _save_session(self, session_key): """Save session key (in plaintext) to a file""" logger.info('Saving session key to file') with open(self.config.general.session_file, 'w') as handle: handle.write(session_key) def _authorize_application(self, client): """Go through the LastFM desktop application authorization process, saving a session key to a file for future use""" token = retry_function(client.auth.get_token) self._get_user_permission(token) try: session_key = retry_function(client.auth.get_session, token) except pylastfm.AuthenticationError as exc: logger.debug('Unable to get authenticated LastFM session', exc_info=exc) raise self._save_session(session_key) @retry(exceptions=RetryError) def _initialize_client(self): config = self.config client = pylastfm.LastFM(config.lastfm.api_key, config.lastfm.api_secret, username=config.lastfm.user, url=config.lastfm.url, auth_method='session_key_file', session_key=config.general.session_file) try: client.authenticate() return client except pylastfm.FileError: logger.info('Authenticating suggestive with LastFM') self._authorize_application(client) raise RetryError except pylastfm.AuthenticationError as exc: logger.debug('Failed to authenticate', exc_info=exc) raise except pylastfm.LastfmError as exc: logger.error( 'Unable to authenticate to LastFM due to unknown error', exc_info=exc) raise def scrobbles(self, user, start=None, end=None): """Get user scrobbles in the given date range""" return self.client.user.get_recent_tracks(user, start=start, end=end) def loved_tracks(self, user): """Get all of the user's loved tracks""" return self.client.user.get_loved_tracks(user) def love_track(self, artist, track): """Mark the given track loved""" try: self.client.track.love(artist, track) return True except pylastfm.APIError as exc: logger.error('Unable to love track', exc_info=exc) return False def unlove_track(self, artist, track): """Set the track as not loved""" try: self.client.track.unlove(artist, track) return True except pylastfm.APIError as exc: logger.error('Unable to unlove track', exc_info=exc) return False

thesquelched/suggestive

suggestive/lastfm.py

Python

bsd-2-clause

4,198

[ "VisIt" ]

be5fb648a8b05eaf2c9a8451e1de9c123d77d50f527c1c656624b31cbe60fba2