id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 51 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
251,000 | ANTsX/ANTsPy | ants/contrib/sampling/transforms.py | LocallyBlurIntensity.transform | def transform(self, X, y=None):
"""
Locally blur an image by applying a gradient anisotropic diffusion filter.
Arguments
---------
X : ANTsImage
image to transform
y : ANTsImage (optional)
another image to transform.
Example
----... | python | def transform(self, X, y=None):
#if X.pixeltype != 'float':
# raise ValueError('image.pixeltype must be float ... use TypeCast transform or clone to float')
insuffix = X._libsuffix
cast_fn = utils.get_lib_fn('locallyBlurAntsImage%s' % (insuffix))
casted_ptr = cast_fn(X.pointer... | [
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Arguments
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X : ANTsImage
image to transform
y : ANTsImage (optional)
another image to transform.
Example
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>>> import ants
>>> blur = ants.... | [
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251,001 | ANTsX/ANTsPy | ants/utils/get_ants_data.py | get_data | def get_data(name=None):
"""
Get ANTsPy test data filename
ANTsR function: `getANTsRData`
Arguments
---------
name : string
name of test image tag to retrieve
Options:
- 'r16'
- 'r27'
- 'r64'
- 'r85'
- 'ch2'
... | python | def get_data(name=None):
if name is None:
files = []
for fname in os.listdir(data_path):
if (fname.endswith('.nii.gz')) or (fname.endswith('.jpg') or (fname.endswith('.csv'))):
fname = os.path.join(data_path, fname)
files.append(fname)
return files... | [
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ANTsR function: `getANTsRData`
Arguments
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name : string
name of test image tag to retrieve
Options:
- 'r16'
- 'r27'
- 'r64'
- 'r85'
- 'ch2'
- 'mni'
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251,002 | ANTsX/ANTsPy | ants/utils/invariant_image_similarity.py | convolve_image | def convolve_image(image, kernel_image, crop=True):
"""
Convolve one image with another
ANTsR function: `convolveImage`
Arguments
---------
image : ANTsImage
image to convolve
kernel_image : ANTsImage
image acting as kernel
crop : boolean
whether to automatica... | python | def convolve_image(image, kernel_image, crop=True):
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if not isinstance(kernel_image, iio.ANTsImage):
raise ValueError('kernel must be ANTsImage type')
orig_ptype = image.pixeltype
if image.pixel... | [
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ANTsR function: `convolveImage`
Arguments
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image : ANTsImage
image to convolve
kernel_image : ANTsImage
image acting as kernel
crop : boolean
whether to automatically crop kernel_image
Returns
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251,003 | ANTsX/ANTsPy | ants/utils/ndimage_to_list.py | ndimage_to_list | def ndimage_to_list(image):
"""
Split a n dimensional ANTsImage into a list
of n-1 dimensional ANTsImages
Arguments
---------
image : ANTsImage
n-dimensional image to split
Returns
-------
list of ANTsImage types
Example
-------
>>> import ants
>>> image = ... | python | def ndimage_to_list(image):
inpixeltype = image.pixeltype
dimension = image.dimension
components = 1
imageShape = image.shape
nSections = imageShape[ dimension - 1 ]
subdimension = dimension - 1
suborigin = iio.get_origin( image )[0:subdimension]
subspacing = iio.get_spacing( image )[0:s... | [
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of n-1 dimensional ANTsImages
Arguments
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image : ANTsImage
n-dimensional image to split
Returns
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list of ANTsImage types
Example
-------
>>> import ants
>>> image = ants.image_read(ants.get_ants_data('r16'... | [
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251,004 | ANTsX/ANTsPy | ants/utils/process_args.py | _int_antsProcessArguments | def _int_antsProcessArguments(args):
"""
Needs to be better validated.
"""
p_args = []
if isinstance(args, dict):
for argname, argval in args.items():
if '-MULTINAME-' in argname:
# have this little hack because python doesnt support
# multiple dic... | python | def _int_antsProcessArguments(args):
p_args = []
if isinstance(args, dict):
for argname, argval in args.items():
if '-MULTINAME-' in argname:
# have this little hack because python doesnt support
# multiple dict entries w/ the same key like R lists
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251,005 | ANTsX/ANTsPy | ants/learn/decomposition.py | initialize_eigenanatomy | def initialize_eigenanatomy(initmat, mask=None, initlabels=None, nreps=1, smoothing=0):
"""
InitializeEigenanatomy is a helper function to initialize sparseDecom
and sparseDecom2. Can be used to estimate sparseness parameters per
eigenvector. The user then only chooses nvecs and optional
regularizat... | python | def initialize_eigenanatomy(initmat, mask=None, initlabels=None, nreps=1, smoothing=0):
if isinstance(initmat, iio.ANTsImage):
# create initmat from each of the unique labels
if mask is not None:
selectvec = mask > 0
else:
selectvec = initmat > 0
initmatvec = ... | [
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initmat : np.ndarray or ANTsImage
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251,006 | ANTsX/ANTsPy | ants/learn/decomposition.py | eig_seg | def eig_seg(mask, img_list, apply_segmentation_to_images=False, cthresh=0, smooth=1):
"""
Segment a mask into regions based on the max value in an image list.
At a given voxel the segmentation label will contain the index to the image
that has the largest value. If the 3rd image has the greatest value,
... | python | def eig_seg(mask, img_list, apply_segmentation_to_images=False, cthresh=0, smooth=1):
maskvox = mask > 0
maskseg = mask.clone()
maskseg[maskvox] = 0
if isinstance(img_list, np.ndarray):
mydata = img_list
elif isinstance(img_list, (tuple, list)):
mydata = core.image_list_to_matrix(img... | [
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Arguments
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251,007 | ANTsX/ANTsPy | ants/utils/label_stats.py | label_stats | def label_stats(image, label_image):
"""
Get label statistics from image
ANTsR function: `labelStats`
Arguments
---------
image : ANTsImage
Image from which statistics will be calculated
label_image : ANTsImage
Label image
Returns
-------
ndarray ?
... | python | def label_stats(image, label_image):
image_float = image.clone('float')
label_image_int = label_image.clone('unsigned int')
libfn = utils.get_lib_fn('labelStats%iD' % image.dimension)
df = libfn(image_float.pointer, label_image_int.pointer)
#df = df[order(df$LabelValue), ]
return pd.DataFrame(d... | [
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ANTsR function: `labelStats`
Arguments
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image : ANTsImage
Image from which statistics will be calculated
label_image : ANTsImage
Label image
Returns
-------
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Example
-------
>>> import ants
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251,008 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.spacing | def spacing(self):
"""
Get image spacing
Returns
-------
tuple
"""
libfn = utils.get_lib_fn('getSpacing%s'%self._libsuffix)
return libfn(self.pointer) | python | def spacing(self):
libfn = utils.get_lib_fn('getSpacing%s'%self._libsuffix)
return libfn(self.pointer) | [
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Returns
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251,009 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.set_spacing | def set_spacing(self, new_spacing):
"""
Set image spacing
Arguments
---------
new_spacing : tuple or list
updated spacing for the image.
should have one value for each dimension
Returns
-------
None
"""
if not isin... | python | def set_spacing(self, new_spacing):
if not isinstance(new_spacing, (tuple, list)):
raise ValueError('arg must be tuple or list')
if len(new_spacing) != self.dimension:
raise ValueError('must give a spacing value for each dimension (%i)' % self.dimension)
libfn = utils.ge... | [
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251,010 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.origin | def origin(self):
"""
Get image origin
Returns
-------
tuple
"""
libfn = utils.get_lib_fn('getOrigin%s'%self._libsuffix)
return libfn(self.pointer) | python | def origin(self):
libfn = utils.get_lib_fn('getOrigin%s'%self._libsuffix)
return libfn(self.pointer) | [
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251,011 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.set_origin | def set_origin(self, new_origin):
"""
Set image origin
Arguments
---------
new_origin : tuple or list
updated origin for the image.
should have one value for each dimension
Returns
-------
None
"""
if not isinstanc... | python | def set_origin(self, new_origin):
if not isinstance(new_origin, (tuple, list)):
raise ValueError('arg must be tuple or list')
if len(new_origin) != self.dimension:
raise ValueError('must give a origin value for each dimension (%i)' % self.dimension)
libfn = utils.get_lib... | [
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new_origin : tuple or list
updated origin for the image.
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Returns
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251,012 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.direction | def direction(self):
"""
Get image direction
Returns
-------
tuple
"""
libfn = utils.get_lib_fn('getDirection%s'%self._libsuffix)
return libfn(self.pointer) | python | def direction(self):
libfn = utils.get_lib_fn('getDirection%s'%self._libsuffix)
return libfn(self.pointer) | [
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Returns
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251,013 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.set_direction | def set_direction(self, new_direction):
"""
Set image direction
Arguments
---------
new_direction : numpy.ndarray or tuple or list
updated direction for the image.
should have one value for each dimension
Returns
-------
None
... | python | def set_direction(self, new_direction):
if isinstance(new_direction, (tuple,list)):
new_direction = np.asarray(new_direction)
if not isinstance(new_direction, np.ndarray):
raise ValueError('arg must be np.ndarray or tuple or list')
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updated direction for the image.
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251,014 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.astype | def astype(self, dtype):
"""
Cast & clone an ANTsImage to a given numpy datatype.
Map:
uint8 : unsigned char
uint32 : unsigned int
float32 : float
float64 : double
"""
if dtype not in _supported_dtypes:
raise ValueEr... | python | def astype(self, dtype):
if dtype not in _supported_dtypes:
raise ValueError('Datatype %s not supported. Supported types are %s' % (dtype, _supported_dtypes))
pixeltype = _npy_to_itk_map[dtype]
return self.clone(pixeltype) | [
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251,015 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.new_image_like | def new_image_like(self, data):
"""
Create a new ANTsImage with the same header information, but with
a new image array.
Arguments
---------
data : ndarray or py::capsule
New array or pointer for the image.
It must have the same shape as the cur... | python | def new_image_like(self, data):
if not isinstance(data, np.ndarray):
raise ValueError('data must be a numpy array')
if not self.has_components:
if data.shape != self.shape:
raise ValueError('given array shape (%s) and image array shape (%s) do not match' % (data.s... | [
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251,016 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.to_file | def to_file(self, filename):
"""
Write the ANTsImage to file
Args
----
filename : string
filepath to which the image will be written
"""
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('toFile%s'%self._libsuffix)
libfn... | python | def to_file(self, filename):
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('toFile%s'%self._libsuffix)
libfn(self.pointer, filename) | [
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251,017 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.apply | def apply(self, fn):
"""
Apply an arbitrary function to ANTsImage.
Args
----
fn : python function or lambda
function to apply to ENTIRE image at once
Returns
-------
ANTsImage
image with function applied to it
"""
... | python | def apply(self, fn):
this_array = self.numpy()
new_array = fn(this_array)
return self.new_image_like(new_array) | [
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251,018 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.sum | def sum(self, axis=None, keepdims=False):
""" Return sum along specified axis """
return self.numpy().sum(axis=axis, keepdims=keepdims) | python | def sum(self, axis=None, keepdims=False):
return self.numpy().sum(axis=axis, keepdims=keepdims) | [
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251,019 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.range | def range(self, axis=None):
""" Return range tuple along specified axis """
return (self.min(axis=axis), self.max(axis=axis)) | python | def range(self, axis=None):
return (self.min(axis=axis), self.max(axis=axis)) | [
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251,020 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.argrange | def argrange(self, axis=None):
""" Return argrange along specified axis """
amin = self.argmin(axis=axis)
amax = self.argmax(axis=axis)
if axis is None:
return (amin, amax)
else:
return np.stack([amin, amax]).T | python | def argrange(self, axis=None):
amin = self.argmin(axis=axis)
amax = self.argmax(axis=axis)
if axis is None:
return (amin, amax)
else:
return np.stack([amin, amax]).T | [
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251,021 | ANTsX/ANTsPy | ants/core/ants_image.py | ANTsImage.unique | def unique(self, sort=False):
""" Return unique set of values in image """
unique_vals = np.unique(self.numpy())
if sort:
unique_vals = np.sort(unique_vals)
return unique_vals | python | def unique(self, sort=False):
unique_vals = np.unique(self.numpy())
if sort:
unique_vals = np.sort(unique_vals)
return unique_vals | [
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251,022 | ANTsX/ANTsPy | ants/core/ants_image.py | LabelImage.uniquekeys | def uniquekeys(self, metakey=None):
"""
Get keys for a given metakey
"""
if metakey is None:
return self._uniquekeys
else:
if metakey not in self.metakeys():
raise ValueError('metakey %s does not exist' % metakey)
return self._u... | python | def uniquekeys(self, metakey=None):
if metakey is None:
return self._uniquekeys
else:
if metakey not in self.metakeys():
raise ValueError('metakey %s does not exist' % metakey)
return self._uniquekeys[metakey] | [
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251,023 | ANTsX/ANTsPy | ants/utils/label_clusters.py | label_clusters | def label_clusters(image, min_cluster_size=50, min_thresh=1e-6, max_thresh=1, fully_connected=False):
"""
This will give a unique ID to each connected
component 1 through N of size > min_cluster_size
ANTsR function: `labelClusters`
Arguments
---------
image : ANTsImage
input imag... | python | def label_clusters(image, min_cluster_size=50, min_thresh=1e-6, max_thresh=1, fully_connected=False):
dim = image.dimension
clust = threshold_image(image, min_thresh, max_thresh)
temp = int(fully_connected)
args = [dim, clust, clust, min_cluster_size, temp]
processed_args = _int_antsProcessArguments... | [
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ANTsR function: `labelClusters`
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251,024 | ANTsX/ANTsPy | ants/registration/make_points_image.py | make_points_image | def make_points_image(pts, mask, radius=5):
"""
Create label image from physical space points
Creates spherical points in the coordinate space of the target image based
on the n-dimensional matrix of points that the user supplies. The image
defines the dimensionality of the data so if the input ima... | python | def make_points_image(pts, mask, radius=5):
powers_lblimg = mask * 0
npts = len(pts)
dim = mask.dimension
if pts.shape[1] != dim:
raise ValueError('points dimensionality should match that of images')
for r in range(npts):
pt = pts[r,:]
idx = tio.transform_physical_point_to_i... | [
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251,025 | ANTsX/ANTsPy | ants/utils/weingarten_image_curvature.py | weingarten_image_curvature | def weingarten_image_curvature(image, sigma=1.0, opt='mean'):
"""
Uses the weingarten map to estimate image mean or gaussian curvature
ANTsR function: `weingartenImageCurvature`
Arguments
---------
image : ANTsImage
image from which curvature is calculated
sigma : scalar
... | python | def weingarten_image_curvature(image, sigma=1.0, opt='mean'):
if image.dimension not in {2,3}:
raise ValueError('image must be 2D or 3D')
if image.dimension == 2:
d = image.shape
temp = np.zeros(list(d)+[10])
for k in range(1,7):
voxvals = image[:d[0],:d[1]]
... | [
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ANTsR function: `weingartenImageCurvature`
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image : ANTsImage
image from which curvature is calculated
sigma : scalar
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opt : string
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251,026 | ANTsX/ANTsPy | ants/core/ants_image_io.py | from_numpy | def from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
"""
Create an ANTsImage object from a numpy array
ANTsR function: `as.antsImage`
Arguments
---------
data : ndarray
image data array
origin : tuple/list
image origin
s... | python | def from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
data = data.astype('float32') if data.dtype.name == 'float64' else data
img = _from_numpy(data.T.copy(), origin, spacing, direction, has_components, is_rgb)
return img | [
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251,027 | ANTsX/ANTsPy | ants/core/ants_image_io.py | _from_numpy | def _from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
"""
Internal function for creating an ANTsImage
"""
if is_rgb: has_components = True
ndim = data.ndim
if has_components:
ndim -= 1
dtype = data.dtype.name
ptype = _npy_to_itk_map... | python | def _from_numpy(data, origin=None, spacing=None, direction=None, has_components=False, is_rgb=False):
if is_rgb: has_components = True
ndim = data.ndim
if has_components:
ndim -= 1
dtype = data.dtype.name
ptype = _npy_to_itk_map[dtype]
data = np.array(data)
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251,028 | ANTsX/ANTsPy | ants/core/ants_image_io.py | make_image | def make_image(imagesize, voxval=0, spacing=None, origin=None, direction=None, has_components=False, pixeltype='float'):
"""
Make an image with given size and voxel value or given a mask and vector
ANTsR function: `makeImage`
Arguments
---------
shape : tuple/ANTsImage
input image size... | python | def make_image(imagesize, voxval=0, spacing=None, origin=None, direction=None, has_components=False, pixeltype='float'):
if isinstance(imagesize, iio.ANTsImage):
img = imagesize.clone()
sel = imagesize > 0
if voxval.ndim > 1:
voxval = voxval.flatten()
if (len(voxval) ... | [
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251,029 | ANTsX/ANTsPy | ants/core/ants_image_io.py | matrix_to_images | def matrix_to_images(data_matrix, mask):
"""
Unmasks rows of a matrix and writes as images
ANTsR function: `matrixToImages`
Arguments
---------
data_matrix : numpy.ndarray
each row corresponds to an image
array should have number of columns equal to non-zero voxels in the mask
... | python | def matrix_to_images(data_matrix, mask):
if data_matrix.ndim > 2:
data_matrix = data_matrix.reshape(data_matrix.shape[0], -1)
numimages = len(data_matrix)
numVoxelsInMatrix = data_matrix.shape[1]
numVoxelsInMask = (mask >= 0.5).sum()
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251,030 | ANTsX/ANTsPy | ants/core/ants_image_io.py | images_to_matrix | def images_to_matrix(image_list, mask=None, sigma=None, epsilon=0.5 ):
"""
Read images into rows of a matrix, given a mask - much faster for
large datasets as it is based on C++ implementations.
ANTsR function: `imagesToMatrix`
Arguments
---------
image_list : list of ANTsImage types
... | python | def images_to_matrix(image_list, mask=None, sigma=None, epsilon=0.5 ):
def listfunc(x):
if np.sum(np.array(x.shape) - np.array(mask.shape)) != 0:
x = reg.resample_image_to_target(x, mask, 2)
return x[mask]
if mask is None:
mask = utils.get_mask(image_list[0])
num_images... | [
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ANTsR function: `imagesToMatrix`
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image_list : list of ANTsImage types
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251,031 | ANTsX/ANTsPy | ants/core/ants_image_io.py | timeseries_to_matrix | def timeseries_to_matrix( image, mask=None ):
"""
Convert a timeseries image into a matrix.
ANTsR function: `timeseries2matrix`
Arguments
---------
image : image whose slices we convert to a matrix. E.g. a 3D image of size
x by y by z will convert to a z by x*y sized matrix
mas... | python | def timeseries_to_matrix( image, mask=None ):
temp = utils.ndimage_to_list( image )
if mask is None:
mask = temp[0]*0 + 1
return image_list_to_matrix( temp, mask ) | [
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251,032 | ANTsX/ANTsPy | ants/core/ants_image_io.py | matrix_to_timeseries | def matrix_to_timeseries( image, matrix, mask=None ):
"""
converts a matrix to a ND image.
ANTsR function: `matrix2timeseries`
Arguments
---------
image: reference ND image
matrix: matrix to convert to image
mask: mask image defining voxels of interest
Returns
-------
... | python | def matrix_to_timeseries( image, matrix, mask=None ):
if mask is None:
mask = temp[0]*0 + 1
temp = matrix_to_images( matrix, mask )
newImage = utils.list_to_ndimage( image, temp)
iio.copy_image_info( image, newImage)
return(newImage) | [
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251,033 | ANTsX/ANTsPy | ants/core/ants_image_io.py | image_header_info | def image_header_info(filename):
"""
Read file info from image header
ANTsR function: `antsImageHeaderInfo`
Arguments
---------
filename : string
name of image file from which info will be read
Returns
-------
dict
"""
if not os.path.exists(filename):
raise... | python | def image_header_info(filename):
if not os.path.exists(filename):
raise Exception('filename does not exist')
libfn = utils.get_lib_fn('antsImageHeaderInfo')
retval = libfn(filename)
retval['dimensions'] = tuple(retval['dimensions'])
retval['origin'] = tuple([round(o,4) for o in retval['orig... | [
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ANTsR function: `antsImageHeaderInfo`
Arguments
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filename : string
name of image file from which info will be read
Returns
-------
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251,034 | ANTsX/ANTsPy | ants/core/ants_image_io.py | image_read | def image_read(filename, dimension=None, pixeltype='float', reorient=False):
"""
Read an ANTsImage from file
ANTsR function: `antsImageRead`
Arguments
---------
filename : string
Name of the file to read the image from.
dimension : int
Number of dimensions of the image rea... | python | def image_read(filename, dimension=None, pixeltype='float', reorient=False):
if filename.endswith('.npy'):
filename = os.path.expanduser(filename)
img_array = np.load(filename)
if os.path.exists(filename.replace('.npy', '.json')):
with open(filename.replace('.npy', '.json')) as j... | [
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ANTsR function: `antsImageRead`
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251,035 | ANTsX/ANTsPy | ants/core/ants_image_io.py | dicom_read | def dicom_read(directory, pixeltype='float'):
"""
Read a set of dicom files in a directory into a single ANTsImage.
The origin of the resulting 3D image will be the origin of the
first dicom image read.
Arguments
---------
directory : string
folder in which all the dicom images exis... | python | def dicom_read(directory, pixeltype='float'):
slices = []
imgidx = 0
for imgpath in os.listdir(directory):
if imgpath.endswith('.dcm'):
if imgidx == 0:
tmp = image_read(os.path.join(directory,imgpath), dimension=3, pixeltype=pixeltype)
origin = tmp.origin
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folder in which all the dicom images exist
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251,036 | ANTsX/ANTsPy | ants/core/ants_image_io.py | image_write | def image_write(image, filename, ri=False):
"""
Write an ANTsImage to file
ANTsR function: `antsImageWrite`
Arguments
---------
image : ANTsImage
image to save to file
filename : string
name of file to which image will be saved
ri : boolean
if True, return ima... | python | def image_write(image, filename, ri=False):
if filename.endswith('.npy'):
img_array = image.numpy()
img_header = {'origin': image.origin,'spacing': image.spacing,
'direction': image.direction.tolist(), 'components': image.components}
np.save(filename, img_array)
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image : ANTsImage
image to save to file
filename : string
name of file to which image will be saved
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251,037 | ANTsX/ANTsPy | ants/segmentation/otsu.py | otsu_segmentation | def otsu_segmentation(image, k, mask=None):
"""
Otsu image segmentation
This is a very fast segmentation algorithm good for quick explortation,
but does not return probability maps.
ANTsR function: `thresholdImage(image, 'Otsu', k)`
Arguments
---------
image : ANTsImage
... | python | def otsu_segmentation(image, k, mask=None):
if mask is not None:
image = image.mask_image(mask)
seg = image.threshold_image('Otsu', k)
return seg | [
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ANTsR function: `thresholdImage(image, 'Otsu', k)`
Arguments
---------
image : ANTsImage
input image
k : integer
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251,038 | ANTsX/ANTsPy | ants/utils/crop_image.py | crop_image | def crop_image(image, label_image=None, label=1):
"""
Use a label image to crop a smaller ANTsImage from within a larger ANTsImage
ANTsR function: `cropImage`
Arguments
---------
image : ANTsImage
image to crop
label_image : ANTsImage
image with label values. If ... | python | def crop_image(image, label_image=None, label=1):
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
if label_image is None:
label_image = get_mask(image)
if label_image.pixeltype != 'float':
label_image = label_... | [
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ANTsR function: `cropImage`
Arguments
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image : ANTsImage
image to crop
label_image : ANTsImage
image with label values. If not supplied, estimated from data.
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251,039 | ANTsX/ANTsPy | ants/utils/crop_image.py | decrop_image | def decrop_image(cropped_image, full_image):
"""
The inverse function for `ants.crop_image`
ANTsR function: `decropImage`
Arguments
---------
cropped_image : ANTsImage
cropped image
full_image : ANTsImage
image in which the cropped image will be put back
Returns
... | python | def decrop_image(cropped_image, full_image):
inpixeltype = 'float'
if cropped_image.pixeltype != 'float':
inpixeltype= cropped_image.pixeltype
cropped_image = cropped_image.clone('float')
if full_image.pixeltype != 'float':
full_image = full_image.clone('float')
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ANTsR function: `decropImage`
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cropped image
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ANTsImage
Example
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251,040 | ANTsX/ANTsPy | ants/segmentation/kmeans.py | kmeans_segmentation | def kmeans_segmentation(image, k, kmask=None, mrf=0.1):
"""
K-means image segmentation that is a wrapper around `ants.atropos`
ANTsR function: `kmeansSegmentation`
Arguments
---------
image : ANTsImage
input image
k : integer
integer number of classes
kmask : ANTsImag... | python | def kmeans_segmentation(image, k, kmask=None, mrf=0.1):
dim = image.dimension
kmimage = utils.iMath(image, 'Normalize')
if kmask is None:
kmask = utils.get_mask(kmimage, 0.01, 1, cleanup=2)
kmask = utils.iMath(kmask, 'FillHoles').threshold_image(1,2)
nhood = 'x'.join(['1']*dim)
mrf = '[%... | [
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ANTsR function: `kmeansSegmentation`
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segment inside this mask
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251,041 | ANTsX/ANTsPy | ants/registration/reorient_image.py | reorient_image2 | def reorient_image2(image, orientation='RAS'):
"""
Reorient an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = mni.reorient_image2()
"""
if image.dimension != 3:
raise ValueError('image must have 3 dimensions')
inpixelt... | python | def reorient_image2(image, orientation='RAS'):
if image.dimension != 3:
raise ValueError('image must have 3 dimensions')
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('reorientImage2')
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>>> import ants
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251,042 | ANTsX/ANTsPy | ants/registration/reorient_image.py | reorient_image | def reorient_image(image, axis1, axis2=None, doreflection=False, doscale=0, txfn=None):
"""
Align image along a specified axis
ANTsR function: `reorientImage`
Arguments
---------
image : ANTsImage
image to reorient
axis1 : list/tuple of integers
vector of size dim,... | python | def reorient_image(image, axis1, axis2=None, doreflection=False, doscale=0, txfn=None):
inpixeltype = image.pixeltype
if image.pixeltype != 'float':
image = image.clone('float')
axis_was_none = False
if axis2 is None:
axis_was_none = True
axis2 = [0]*image.dimension
axis1 =... | [
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251,043 | ANTsX/ANTsPy | ants/registration/reorient_image.py | get_center_of_mass | def get_center_of_mass(image):
"""
Compute an image center of mass in physical space which is defined
as the mean of the intensity weighted voxel coordinate system.
ANTsR function: `getCenterOfMass`
Arguments
---------
image : ANTsImage
image from which center of mass will be ... | python | def get_center_of_mass(image):
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('centerOfMass%s' % image._libsuffix)
com = libfn(image.pointer)
return tuple(com) | [
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ANTsR function: `getCenterOfMass`
Arguments
---------
image : ANTsImage
image from which center of mass will be computed
Returns
-------
scala... | [
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251,044 | ANTsX/ANTsPy | ants/utils/convert_nibabel.py | to_nibabel | def to_nibabel(image):
"""
Convert an ANTsImage to a Nibabel image
"""
if image.dimension != 3:
raise ValueError('Only 3D images currently supported')
import nibabel as nib
array_data = image.numpy()
affine = np.hstack([image.direction*np.diag(image.spacing),np.array(image.origin).r... | python | def to_nibabel(image):
if image.dimension != 3:
raise ValueError('Only 3D images currently supported')
import nibabel as nib
array_data = image.numpy()
affine = np.hstack([image.direction*np.diag(image.spacing),np.array(image.origin).reshape(3,1)])
affine = np.vstack([affine, np.array([0,0,... | [
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251,045 | ANTsX/ANTsPy | ants/utils/convert_nibabel.py | from_nibabel | def from_nibabel(nib_image):
"""
Convert a nibabel image to an ANTsImage
"""
tmpfile = mktemp(suffix='.nii.gz')
nib_image.to_filename(tmpfile)
new_img = iio2.image_read(tmpfile)
os.remove(tmpfile)
return new_img | python | def from_nibabel(nib_image):
tmpfile = mktemp(suffix='.nii.gz')
nib_image.to_filename(tmpfile)
new_img = iio2.image_read(tmpfile)
os.remove(tmpfile)
return new_img | [
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251,046 | ANTsX/ANTsPy | ants/contrib/sampling/affine3d.py | RandomShear3D.transform | def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
shear parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
... | python | def transform(self, X=None, y=None):
# random draw in shear range
shear_x = random.gauss(self.shear_range[0], self.shear_range[1])
shear_y = random.gauss(self.shear_range[0], self.shear_range[1])
shear_z = random.gauss(self.shear_range[0], self.shear_range[1])
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251,047 | ANTsX/ANTsPy | ants/contrib/sampling/affine3d.py | RandomZoom3D.transform | def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
zoom parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
... | python | def transform(self, X=None, y=None):
# random draw in zoom range
zoom_x = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
zoom_y = np.exp( random.gauss(
np.log( self.zoom_range[0] ),
np.log( self.zoom_range[1] ) ) )
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251,048 | ANTsX/ANTsPy | ants/contrib/sampling/affine2d.py | Translate2D.transform | def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
translation parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
An... | python | def transform(self, X=None, y=None):
# convert to radians and unpack
translation_x, translation_y = self.translation
translation_matrix = np.array([[1, 0, translation_x],
[0, 1, translation_y]])
self.tx.set_parameters(translation_matrix)
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251,049 | ANTsX/ANTsPy | ants/contrib/sampling/affine2d.py | RandomTranslate2D.transform | def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with
translation parameters randomly generated from the user-specified
range. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
... | python | def transform(self, X=None, y=None):
# random draw in translation range
translation_x = random.gauss(self.translation_range[0], self.translation_range[1])
translation_y = random.gauss(self.translation_range[0], self.translation_range[1])
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251,050 | ANTsX/ANTsPy | ants/contrib/sampling/affine2d.py | Shear2D.transform | def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
shear parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another... | python | def transform(self, X=None, y=None):
# convert to radians and unpack
shear = [math.pi / 180 * s for s in self.shear]
shear_x, shear_y = shear
shear_matrix = np.array([[1, shear_x, 0],
[shear_y, 1, 0]])
self.tx.set_parameters(shear_matrix)
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251,051 | ANTsX/ANTsPy | ants/contrib/sampling/affine2d.py | Zoom2D.transform | def transform(self, X=None, y=None):
"""
Transform an image using an Affine transform with the given
zoom parameters. Return the transform if X=None.
Arguments
---------
X : ANTsImage
Image to transform
y : ANTsImage (optional)
Another ... | python | def transform(self, X=None, y=None):
# unpack zoom range
zoom_x, zoom_y= self.zoom
self.params = (zoom_x, zoom_y)
zoom_matrix = np.array([[zoom_x, 0, 0],
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self.tx.set_parameters(zoom_matrix)
if self.lazy or X is None:
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251,052 | ANTsX/ANTsPy | ants/segmentation/kelly_kapowski.py | kelly_kapowski | def kelly_kapowski(s, g, w, its=50, r=0.025, m=1.5, **kwargs):
"""
Compute cortical thickness using the DiReCT algorithm.
Diffeomorphic registration-based cortical thickness based on probabilistic
segmentation of an image. This is an optimization algorithm.
Arguments
---------
s : AN... | python | def kelly_kapowski(s, g, w, its=50, r=0.025, m=1.5, **kwargs):
if isinstance(s, iio.ANTsImage):
s = s.clone('unsigned int')
d = s.dimension
outimg = g.clone()
kellargs = {'d': d,
's': s,
'g': g,
'w': w,
'c': its,
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251,053 | ANTsX/ANTsPy | ants/core/ants_transform_io.py | new_ants_transform | def new_ants_transform(precision='float', dimension=3, transform_type='AffineTransform', parameters=None):
"""
Create a new ANTsTransform
ANTsR function: None
Example
-------
>>> import ants
>>> tx = ants.new_ants_transform()
"""
libfn = utils.get_lib_fn('newAntsTransform%s%i' % (u... | python | def new_ants_transform(precision='float', dimension=3, transform_type='AffineTransform', parameters=None):
libfn = utils.get_lib_fn('newAntsTransform%s%i' % (utils.short_ptype(precision), dimension))
itk_tx = libfn(precision, dimension, transform_type)
ants_tx = tio.ANTsTransform(precision=precision, dimens... | [
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251,054 | ANTsX/ANTsPy | ants/core/ants_transform_io.py | create_ants_transform | def create_ants_transform(transform_type='AffineTransform',
precision='float',
dimension=3,
matrix=None,
offset=None,
center=None,
translation=None,
... | python | def create_ants_transform(transform_type='AffineTransform',
precision='float',
dimension=3,
matrix=None,
offset=None,
center=None,
translation=None,
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251,055 | ANTsX/ANTsPy | ants/core/ants_transform_io.py | read_transform | def read_transform(filename, dimension=2, precision='float'):
"""
Read a transform from file
ANTsR function: `readAntsrTransform`
Arguments
---------
filename : string
filename of transform
dimension : integer
spatial dimension of transform
precision : string
... | python | def read_transform(filename, dimension=2, precision='float'):
filename = os.path.expanduser(filename)
if not os.path.exists(filename):
raise ValueError('filename does not exist!')
libfn1 = utils.get_lib_fn('getTransformDimensionFromFile')
dimension = libfn1(filename)
libfn2 = utils.get_lib... | [
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251,056 | ANTsX/ANTsPy | ants/core/ants_transform_io.py | write_transform | def write_transform(transform, filename):
"""
Write ANTsTransform to file
ANTsR function: `writeAntsrTransform`
Arguments
---------
transform : ANTsTransform
transform to save
filename : string
filename of transform (file extension is ".mat" for affine transforms)
... | python | def write_transform(transform, filename):
filename = os.path.expanduser(filename)
libfn = utils.get_lib_fn('writeTransform%s' % (transform._libsuffix))
libfn(transform.pointer, filename) | [
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251,057 | ANTsX/ANTsPy | ants/registration/reflect_image.py | reflect_image | def reflect_image(image, axis=None, tx=None, metric='mattes'):
"""
Reflect an image along an axis
ANTsR function: `reflectImage`
Arguments
---------
image : ANTsImage
image to reflect
axis : integer (optional)
which dimension to reflect across, numbered from 0 to image... | python | def reflect_image(image, axis=None, tx=None, metric='mattes'):
if axis is None:
axis = image.dimension - 1
if (axis > image.dimension) or (axis < 0):
axis = image.dimension - 1
rflct = mktemp(suffix='.mat')
libfn = utils.get_lib_fn('reflectionMatrix%s'%image._libsuffix)
libfn(imag... | [
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ANTsR function: `reflectImage`
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image : ANTsImage
image to reflect
axis : integer (optional)
which dimension to reflect across, numbered from 0 to imageDimension-1
tx : string (optional)
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251,058 | ANTsX/ANTsPy | ants/contrib/bids/cohort.py | BIDSCohort.create_sampler | def create_sampler(self, inputs, targets, input_reader=None, target_reader=None,
input_transform=None, target_transform=None, co_transform=None,
input_return_processor=None, target_return_processor=None, co_return_processor=None):
"""
Create a BIDSSampler that can be used to generate in... | python | def create_sampler(self, inputs, targets, input_reader=None, target_reader=None,
input_transform=None, target_transform=None, co_transform=None,
input_return_processor=None, target_return_processor=None, co_return_processor=None):
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251,059 | ANTsX/ANTsPy | ants/utils/slice_image.py | slice_image | def slice_image(image, axis=None, idx=None):
"""
Slice an image.
Example
-------
>>> import ants
>>> mni = ants.image_read(ants.get_data('mni'))
>>> mni2 = ants.slice_image(mni, axis=1, idx=100)
"""
if image.dimension < 3:
raise ValueError('image must have at least 3 dimensi... | python | def slice_image(image, axis=None, idx=None):
if image.dimension < 3:
raise ValueError('image must have at least 3 dimensions')
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
libfn = utils.get_lib_fn('sliceImageF%i' %... | [
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>>> import ants
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251,060 | ANTsX/ANTsPy | ants/utils/pad_image.py | pad_image | def pad_image(image, shape=None, pad_width=None, value=0.0, return_padvals=False):
"""
Pad an image to have the given shape or to be isotropic.
Arguments
---------
image : ANTsImage
image to pad
shape : tuple
- if shape is given, the image will be padded in each dimension
... | python | def pad_image(image, shape=None, pad_width=None, value=0.0, return_padvals=False):
inpixeltype = image.pixeltype
ndim = image.dimension
if image.pixeltype != 'float':
image = image.clone('float')
if pad_width is None:
if shape is None:
shape = [max(image.shape)] * image.dime... | [
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251,061 | ANTsX/ANTsPy | ants/core/ants_metric.py | ANTsImageToImageMetric.set_fixed_image | def set_fixed_image(self, image):
"""
Set Fixed ANTsImage for metric
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric... | python | def set_fixed_image(self, image):
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric dim (%i)' % (image.dimension, self.dimension))
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251,062 | ANTsX/ANTsPy | ants/core/ants_metric.py | ANTsImageToImageMetric.set_moving_image | def set_moving_image(self, image):
"""
Set Moving ANTsImage for metric
"""
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metr... | python | def set_moving_image(self, image):
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
if image.dimension != self.dimension:
raise ValueError('image dim (%i) does not match metric dim (%i)' % (image.dimension, self.dimension))
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251,063 | ANTsX/ANTsPy | ants/utils/image_to_cluster_images.py | image_to_cluster_images | def image_to_cluster_images(image, min_cluster_size=50, min_thresh=1e-06, max_thresh=1):
"""
Converts an image to several independent images.
Produces a unique image for each connected
component 1 through N of size > min_cluster_size
ANTsR function: `image2ClusterImages`
Arguments
------... | python | def image_to_cluster_images(image, min_cluster_size=50, min_thresh=1e-06, max_thresh=1):
if not isinstance(image, iio.ANTsImage):
raise ValueError('image must be ANTsImage type')
clust = label_clusters(image, min_cluster_size, min_thresh, max_thresh)
labs = np.unique(clust[clust > 0])
clustlis... | [
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ANTsR function: `image2ClusterImages`
Arguments
---------
image : ANTsImage
input image
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251,064 | ANTsX/ANTsPy | ants/utils/threshold_image.py | threshold_image | def threshold_image(image, low_thresh=None, high_thresh=None, inval=1, outval=0, binary=True):
"""
Converts a scalar image into a binary image by thresholding operations
ANTsR function: `thresholdImage`
Arguments
---------
image : ANTsImage
Input image to operate on
low_thresh... | python | def threshold_image(image, low_thresh=None, high_thresh=None, inval=1, outval=0, binary=True):
if high_thresh is None:
high_thresh = image.max() + 0.01
if low_thresh is None:
low_thresh = image.min() - 0.01
dim = image.dimension
outimage = image.clone()
args = [dim, image, outimage, ... | [
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ANTsR function: `thresholdImage`
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image : ANTsImage
Input image to operate on
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251,065 | ANTsX/ANTsPy | ants/registration/symmetrize_image.py | symmetrize_image | def symmetrize_image(image):
"""
Use registration and reflection to make an image symmetric
ANTsR function: N/A
Arguments
---------
image : ANTsImage
image to make symmetric
Returns
-------
ANTsImage
Example
-------
>>> import ants
>>> image = ants.image_r... | python | def symmetrize_image(image):
imager = reflect_image(image, axis=0)
imageavg = imager * 0.5 + image
for i in range(5):
w1 = registration(imageavg, image, type_of_transform='SyN')
w2 = registration(imageavg, imager, type_of_transform='SyN')
xavg = w1['warpedmovout']*0.5 + w2['... | [
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ANTsR function: N/A
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image : ANTsImage
image to make symmetric
Returns
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Example
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>>> import ants
>>> image = ants.image_read( ants.get_ants_data('r16') , 'float')... | [
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251,066 | freakboy3742/pyxero | xero/basemanager.py | BaseManager._get_attachments | def _get_attachments(self, id):
"""Retrieve a list of attachments associated with this Xero object."""
uri = '/'.join([self.base_url, self.name, id, 'Attachments']) + '/'
return uri, {}, 'get', None, None, False | python | def _get_attachments(self, id):
uri = '/'.join([self.base_url, self.name, id, 'Attachments']) + '/'
return uri, {}, 'get', None, None, False | [
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251,067 | freakboy3742/pyxero | xero/basemanager.py | BaseManager._put_attachment_data | def _put_attachment_data(self, id, filename, data, content_type, include_online=False):
"""Upload an attachment to the Xero object."""
uri = '/'.join([self.base_url, self.name, id, 'Attachments', filename])
params = {'IncludeOnline': 'true'} if include_online else {}
headers = {'Content-... | python | def _put_attachment_data(self, id, filename, data, content_type, include_online=False):
uri = '/'.join([self.base_url, self.name, id, 'Attachments', filename])
params = {'IncludeOnline': 'true'} if include_online else {}
headers = {'Content-Type': content_type, 'Content-Length': str(len(data))}
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251,068 | freakboy3742/pyxero | examples/partner_oauth_flow/runserver.py | PartnerCredentialsHandler.page_response | def page_response(self, title='', body=''):
"""
Helper to render an html page with dynamic content
"""
f = StringIO()
f.write('<!DOCTYPE html>\n')
f.write('<html>\n')
f.write('<head><title>{}</title><head>\n'.format(title))
f.write('<body>\n<h2>{}</h2>\n'.... | python | def page_response(self, title='', body=''):
f = StringIO()
f.write('<!DOCTYPE html>\n')
f.write('<html>\n')
f.write('<head><title>{}</title><head>\n'.format(title))
f.write('<body>\n<h2>{}</h2>\n'.format(title))
f.write('<div class="content">{}</div>\n'.format(body))
... | [
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251,069 | freakboy3742/pyxero | examples/partner_oauth_flow/runserver.py | PartnerCredentialsHandler.redirect_response | def redirect_response(self, url, permanent=False):
"""
Generate redirect response
"""
if permanent:
self.send_response(301)
else:
self.send_response(302)
self.send_header("Location", url)
self.end_headers() | python | def redirect_response(self, url, permanent=False):
if permanent:
self.send_response(301)
else:
self.send_response(302)
self.send_header("Location", url)
self.end_headers() | [
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251,070 | freakboy3742/pyxero | xero/auth.py | PublicCredentials._init_credentials | def _init_credentials(self, oauth_token, oauth_token_secret):
"Depending on the state passed in, get self._oauth up and running"
if oauth_token and oauth_token_secret:
if self.verified:
# If provided, this is a fully verified set of
# credentials. Store the oa... | python | def _init_credentials(self, oauth_token, oauth_token_secret):
"Depending on the state passed in, get self._oauth up and running"
if oauth_token and oauth_token_secret:
if self.verified:
# If provided, this is a fully verified set of
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251,071 | freakboy3742/pyxero | xero/auth.py | PublicCredentials._init_oauth | def _init_oauth(self, oauth_token, oauth_token_secret):
"Store and initialize a verified set of OAuth credentials"
self.oauth_token = oauth_token
self.oauth_token_secret = oauth_token_secret
self._oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_sec... | python | def _init_oauth(self, oauth_token, oauth_token_secret):
"Store and initialize a verified set of OAuth credentials"
self.oauth_token = oauth_token
self.oauth_token_secret = oauth_token_secret
self._oauth = OAuth1(
self.consumer_key,
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251,072 | freakboy3742/pyxero | xero/auth.py | PublicCredentials._process_oauth_response | def _process_oauth_response(self, response):
"Extracts the fields from an oauth response"
if response.status_code == 200:
credentials = parse_qs(response.text)
# Initialize the oauth credentials
self._init_oauth(
credentials.get('oauth_token')[0],
... | python | def _process_oauth_response(self, response):
"Extracts the fields from an oauth response"
if response.status_code == 200:
credentials = parse_qs(response.text)
# Initialize the oauth credentials
self._init_oauth(
credentials.get('oauth_token')[0],
... | [
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251,073 | freakboy3742/pyxero | xero/auth.py | PublicCredentials.state | def state(self):
"""Obtain the useful state of this credentials object so that
we can reconstruct it independently.
"""
return dict(
(attr, getattr(self, attr))
for attr in (
'consumer_key', 'consumer_secret', 'callback_uri',
'verif... | python | def state(self):
return dict(
(attr, getattr(self, attr))
for attr in (
'consumer_key', 'consumer_secret', 'callback_uri',
'verified', 'oauth_token', 'oauth_token_secret',
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251,074 | freakboy3742/pyxero | xero/auth.py | PublicCredentials.verify | def verify(self, verifier):
"Verify an OAuth token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oau... | python | def verify(self, verifier):
"Verify an OAuth token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oau... | [
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251,075 | freakboy3742/pyxero | xero/auth.py | PublicCredentials.url | def url(self):
"Returns the URL that can be visited to obtain a verifier code"
# The authorize url is always api.xero.com
query_string = {'oauth_token': self.oauth_token}
if self.scope:
query_string['scope'] = self.scope
url = XERO_BASE_URL + AUTHORIZE_URL + '?' + \... | python | def url(self):
"Returns the URL that can be visited to obtain a verifier code"
# The authorize url is always api.xero.com
query_string = {'oauth_token': self.oauth_token}
if self.scope:
query_string['scope'] = self.scope
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251,076 | freakboy3742/pyxero | xero/auth.py | PartnerCredentials.refresh | def refresh(self):
"Refresh an expired token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
resource_owner_secret=self.oauth_tok... | python | def refresh(self):
"Refresh an expired token"
# Construct the credentials for the verification request
oauth = OAuth1(
self.consumer_key,
client_secret=self.consumer_secret,
resource_owner_key=self.oauth_token,
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251,077 | freakboy3742/pyxero | xero/filesmanager.py | FilesManager._get_files | def _get_files(self, folderId):
"""Retrieve the list of files contained in a folder"""
uri = '/'.join([self.base_url, self.name, folderId, 'Files'])
return uri, {}, 'get', None, None, False, None | python | def _get_files(self, folderId):
uri = '/'.join([self.base_url, self.name, folderId, 'Files'])
return uri, {}, 'get', None, None, False, None | [
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251,078 | dmulcahey/zha-device-handlers | zhaquirks/hivehome/__init__.py | MotionCluster.handle_cluster_request | def handle_cluster_request(self, tsn, command_id, args):
"""Handle the cluster command."""
if command_id == 0:
if self._timer_handle:
self._timer_handle.cancel()
loop = asyncio.get_event_loop()
self._timer_handle = loop.call_later(30, self._turn_off) | python | def handle_cluster_request(self, tsn, command_id, args):
if command_id == 0:
if self._timer_handle:
self._timer_handle.cancel()
loop = asyncio.get_event_loop()
self._timer_handle = loop.call_later(30, self._turn_off) | [
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251,079 | dmulcahey/zha-device-handlers | zhaquirks/xiaomi/__init__.py | BasicCluster._parse_attributes | def _parse_attributes(self, value):
"""Parse non standard atrributes."""
from zigpy.zcl import foundation as f
attributes = {}
attribute_names = {
1: BATTERY_VOLTAGE_MV,
3: TEMPERATURE,
4: XIAOMI_ATTR_4,
5: XIAOMI_ATTR_5,
6: XIA... | python | def _parse_attributes(self, value):
from zigpy.zcl import foundation as f
attributes = {}
attribute_names = {
1: BATTERY_VOLTAGE_MV,
3: TEMPERATURE,
4: XIAOMI_ATTR_4,
5: XIAOMI_ATTR_5,
6: XIAOMI_ATTR_6,
10: PATH
}
... | [
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251,080 | dmulcahey/zha-device-handlers | zhaquirks/xiaomi/__init__.py | BasicCluster._calculate_remaining_battery_percentage | def _calculate_remaining_battery_percentage(self, voltage):
"""Calculate percentage."""
min_voltage = 2500
max_voltage = 3000
percent = (voltage - min_voltage) / (max_voltage - min_voltage) * 200
return min(200, percent) | python | def _calculate_remaining_battery_percentage(self, voltage):
min_voltage = 2500
max_voltage = 3000
percent = (voltage - min_voltage) / (max_voltage - min_voltage) * 200
return min(200, percent) | [
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251,081 | dmulcahey/zha-device-handlers | zhaquirks/xiaomi/__init__.py | PowerConfigurationCluster.battery_reported | def battery_reported(self, voltage, rawVoltage):
"""Battery reported."""
self._update_attribute(BATTERY_PERCENTAGE_REMAINING, voltage)
self._update_attribute(self.BATTERY_VOLTAGE_ATTR,
int(rawVoltage / 100)) | python | def battery_reported(self, voltage, rawVoltage):
self._update_attribute(BATTERY_PERCENTAGE_REMAINING, voltage)
self._update_attribute(self.BATTERY_VOLTAGE_ATTR,
int(rawVoltage / 100)) | [
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251,082 | dmulcahey/zha-device-handlers | zhaquirks/smartthings/tag_v4.py | FastPollingPowerConfigurationCluster.configure_reporting | async def configure_reporting(self, attribute, min_interval,
max_interval, reportable_change):
"""Configure reporting."""
result = await super().configure_reporting(
PowerConfigurationCluster.BATTERY_VOLTAGE_ATTR,
self.FREQUENCY,
self... | python | async def configure_reporting(self, attribute, min_interval,
max_interval, reportable_change):
result = await super().configure_reporting(
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self.FREQUENCY,
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251,083 | F5Networks/f5-common-python | f5/bigip/tm/sys/folder.py | Folder.update | def update(self, **kwargs):
'''Update the object, removing device group if inherited
If inheritedDevicegroup is the string "true" we need to remove
deviceGroup from the args before we update or we get the
following error:
The floating traffic-group: /Common/traffic-group-1 can ... | python | def update(self, **kwargs):
'''Update the object, removing device group if inherited
If inheritedDevicegroup is the string "true" we need to remove
deviceGroup from the args before we update or we get the
following error:
The floating traffic-group: /Common/traffic-group-1 can ... | [
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251,084 | F5Networks/f5-common-python | f5/bigip/tm/cm/device_group.py | Device_Group.sync_to | def sync_to(self):
"""Wrapper method that synchronizes configuration to DG.
Executes the containing object's cm :meth:`~f5.bigip.cm.Cm.exec_cmd`
method to sync the configuration TO the device-group.
:note:: Both sync_to, and sync_from methods are convenience
methods wh... | python | def sync_to(self):
device_group_collection = self._meta_data['container']
cm = device_group_collection._meta_data['container']
sync_cmd = 'config-sync to-group %s' % self.name
cm.exec_cmd('run', utilCmdArgs=sync_cmd) | [
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251,085 | F5Networks/f5-common-python | f5/bigip/tm/sys/application.py | Service._create | def _create(self, **kwargs):
'''Create service on device and create accompanying Python object.
:params kwargs: keyword arguments passed in from create call
:raises: HTTPError
:returns: Python Service object
'''
try:
return super(Service, self)._create(**kwa... | python | def _create(self, **kwargs):
'''Create service on device and create accompanying Python object.
:params kwargs: keyword arguments passed in from create call
:raises: HTTPError
:returns: Python Service object
'''
try:
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251,086 | F5Networks/f5-common-python | f5/bigip/tm/sys/application.py | Service._build_service_uri | def _build_service_uri(self, base_uri, partition, name):
'''Build the proper uri for a service resource.
This follows the scheme:
<base_uri>/~<partition>~<<name>.app>~<name>
:param base_uri: str -- base uri for container
:param partition: str -- partition for this service
... | python | def _build_service_uri(self, base_uri, partition, name):
'''Build the proper uri for a service resource.
This follows the scheme:
<base_uri>/~<partition>~<<name>.app>~<name>
:param base_uri: str -- base uri for container
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251,087 | F5Networks/f5-common-python | f5/bigiq/cm/device/licensing/pool/utility.py | Members.delete | def delete(self, **kwargs):
"""Deletes a member from a license pool
You need to be careful with this method. When you use it, and it
succeeds on the remote BIG-IP, the configuration of the BIG-IP
will be reloaded. During this process, you will not be able to
access the REST inte... | python | def delete(self, **kwargs):
if 'id' not in kwargs:
# BIG-IQ requires that you provide the ID of the members to revoke
# a license from. This ID is already part of the deletion URL though.
# Therefore, if you do not provide it, we enumerate it for you.
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"# a license from. This ID is already part of the deletion URL though.",
"# Therefore, if you do not pr... | Deletes a member from a license pool
You need to be careful with this method. When you use it, and it
succeeds on the remote BIG-IP, the configuration of the BIG-IP
will be reloaded. During this process, you will not be able to
access the REST interface.
This method overrides t... | [
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] | 7e67d5acd757a60e3d5f8c88c534bd72208f5494 | https://github.com/F5Networks/f5-common-python/blob/7e67d5acd757a60e3d5f8c88c534bd72208f5494/f5/bigiq/cm/device/licensing/pool/utility.py#L137-L187 |
251,088 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._set_attributes | def _set_attributes(self, **kwargs):
'''Set attributes for instance in one place
:param kwargs: dict -- dictionary of keyword arguments
'''
self.devices = kwargs['devices'][:]
self.partition = kwargs['partition']
self.device_group_name = 'device_trust_group'
sel... | python | def _set_attributes(self, **kwargs):
'''Set attributes for instance in one place
:param kwargs: dict -- dictionary of keyword arguments
'''
self.devices = kwargs['devices'][:]
self.partition = kwargs['partition']
self.device_group_name = 'device_trust_group'
sel... | [
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251,089 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain.validate | def validate(self):
'''Validate that devices are each trusted by one another
:param kwargs: dict -- keyword args for devices and partition
:raises: DeviceNotTrusted
'''
self._populate_domain()
missing = []
for domain_device in self.domain:
for truste... | python | def validate(self):
'''Validate that devices are each trusted by one another
:param kwargs: dict -- keyword args for devices and partition
:raises: DeviceNotTrusted
'''
self._populate_domain()
missing = []
for domain_device in self.domain:
for truste... | [
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251,090 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._populate_domain | def _populate_domain(self):
'''Populate TrustDomain's domain attribute.
This entails an inspection of each device's certificate-authority
devices in its trust domain and recording them. After which, we
get a dictionary of who trusts who in the domain.
'''
self.domain = ... | python | def _populate_domain(self):
'''Populate TrustDomain's domain attribute.
This entails an inspection of each device's certificate-authority
devices in its trust domain and recording them. After which, we
get a dictionary of who trusts who in the domain.
'''
self.domain = ... | [
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251,091 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain.create | def create(self, **kwargs):
'''Add trusted peers to the root bigip device.
When adding a trusted device to a device, the trust is reflexive. That
is, the truster trusts the trustee and the trustee trusts the truster.
So we only need to add the trusted devices to one device.
:pa... | python | def create(self, **kwargs):
'''Add trusted peers to the root bigip device.
When adding a trusted device to a device, the trust is reflexive. That
is, the truster trusts the trustee and the trustee trusts the truster.
So we only need to add the trusted devices to one device.
:pa... | [
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251,092 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain.teardown | def teardown(self):
'''Teardown trust domain by removing trusted devices.'''
for device in self.devices:
self._remove_trustee(device)
self._populate_domain()
self.domain = {} | python | def teardown(self):
'''Teardown trust domain by removing trusted devices.'''
for device in self.devices:
self._remove_trustee(device)
self._populate_domain()
self.domain = {} | [
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251,093 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._add_trustee | def _add_trustee(self, device):
'''Add a single trusted device to the trust domain.
:param device: ManagementRoot object -- device to add to trust domain
'''
device_name = get_device_info(device).name
if device_name in self.domain:
msg = 'Device: %r is already in th... | python | def _add_trustee(self, device):
'''Add a single trusted device to the trust domain.
:param device: ManagementRoot object -- device to add to trust domain
'''
device_name = get_device_info(device).name
if device_name in self.domain:
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251,094 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._remove_trustee | def _remove_trustee(self, device):
'''Remove a trustee from the trust domain.
:param device: MangementRoot object -- device to remove
'''
trustee_name = get_device_info(device).name
name_object_map = get_device_names_to_objects(self.devices)
delete_func = self._get_dele... | python | def _remove_trustee(self, device):
'''Remove a trustee from the trust domain.
:param device: MangementRoot object -- device to remove
'''
trustee_name = get_device_info(device).name
name_object_map = get_device_names_to_objects(self.devices)
delete_func = self._get_dele... | [
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251,095 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._modify_trust | def _modify_trust(self, truster, mod_peer_func, trustee):
'''Modify a trusted peer device by deploying an iapp.
:param truster: ManagementRoot object -- device on which to perform
commands
:param mod_peer_func: function -- function to call to modify peer
:param ... | python | def _modify_trust(self, truster, mod_peer_func, trustee):
'''Modify a trusted peer device by deploying an iapp.
:param truster: ManagementRoot object -- device on which to perform
commands
:param mod_peer_func: function -- function to call to modify peer
:param ... | [
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251,096 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._delete_iapp | def _delete_iapp(self, iapp_name, deploying_device):
'''Delete an iapp service and template on the root device.
:param iapp_name: str -- name of iapp
:param deploying_device: ManagementRoot object -- device where the
iapp will be deleted
'''
iap... | python | def _delete_iapp(self, iapp_name, deploying_device):
'''Delete an iapp service and template on the root device.
:param iapp_name: str -- name of iapp
:param deploying_device: ManagementRoot object -- device where the
iapp will be deleted
'''
iap... | [
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:param iapp_name: str -- name of iapp
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251,097 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._deploy_iapp | def _deploy_iapp(self, iapp_name, actions, deploying_device):
'''Deploy iapp to add trusted device
:param iapp_name: str -- name of iapp
:param actions: dict -- actions definition of iapp sections
:param deploying_device: ManagementRoot object -- device where the
... | python | def _deploy_iapp(self, iapp_name, actions, deploying_device):
'''Deploy iapp to add trusted device
:param iapp_name: str -- name of iapp
:param actions: dict -- actions definition of iapp sections
:param deploying_device: ManagementRoot object -- device where the
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251,098 | F5Networks/f5-common-python | f5/multi_device/trust_domain.py | TrustDomain._get_add_trustee_cmd | def _get_add_trustee_cmd(self, trustee):
'''Get tmsh command to add a trusted device.
:param trustee: ManagementRoot object -- device to add as trusted
:returns: str -- tmsh command to add trustee
'''
trustee_info = pollster(get_device_info)(trustee)
username = trustee.... | python | def _get_add_trustee_cmd(self, trustee):
'''Get tmsh command to add a trusted device.
:param trustee: ManagementRoot object -- device to add as trusted
:returns: str -- tmsh command to add trustee
'''
trustee_info = pollster(get_device_info)(trustee)
username = trustee.... | [
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251,099 | F5Networks/f5-common-python | f5/bigip/tm/vcmp/virtual_disk.py | Virtual_Disk.load | def load(self, **kwargs):
"""Loads a given resource
Loads a given resource provided a 'name' and an optional 'slot'
parameter. The 'slot' parameter is not a required load parameter
because it is provided as an optional way of constructing the
correct 'name' of the vCMP resource.... | python | def load(self, **kwargs):
kwargs['transform_name'] = True
kwargs = self._mutate_name(kwargs)
return self._load(**kwargs) | [
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