xszheng2020/the_stack_dedup_python_hits_3 · Datasets at Hugging Face

8a79c5aa4cc942ec50133c91570519a3c6638f53

208

py

Python

python-hard-way/ex33.py

calebgregory/scraps

cfc0ef608db4520c1a1e22fccdbcae73dfb00e39

[ "MIT" ]

null

python-hard-way/ex33.py

calebgregory/scraps

cfc0ef608db4520c1a1e22fccdbcae73dfb00e39

[ "MIT" ]

null

python-hard-way/ex33.py

calebgregory/scraps

cfc0ef608db4520c1a1e22fccdbcae73dfb00e39

[ "MIT" ]

null

def print_multiples(start, finish, inc): i = start numbers = [] while i < finish: numbers.append(i) i = i + inc print "Numbers now: ", numbers print_multiples(6,100,9)

16

40

0.567308

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208

4.296296

0.518519

0.241379

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0.035211

0.317308

208

12

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0

null

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0

null

1

0

null

0

1

0

3

8a7b65e5bd38986b2df936f442af942a382962b7

420

py

Python

RadioStation/Player/VLCPlayer.py

m-mohiey/AutomaticRadioStation

9ec3935e08ef58302d314387bc107bd1be8a6418

[ "MIT" ]

null

RadioStation/Player/VLCPlayer.py

m-mohiey/AutomaticRadioStation

9ec3935e08ef58302d314387bc107bd1be8a6418

[ "MIT" ]

null

RadioStation/Player/VLCPlayer.py

m-mohiey/AutomaticRadioStation

9ec3935e08ef58302d314387bc107bd1be8a6418

[ "MIT" ]

null

from . import AbstractPlayer import vlc class VLCPlayer(AbstractPlayer): def __init__(self): self.player = vlc.MediaPlayer() self.program = None def open(self, program): self.player.set_mrl(program.media.path) def play(self): self.player.play() def stop(self): self.player.stop() def wait(self): while self.player.is_playing(): pass

18.26087

47

0.609524

50

420

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0.2

0.168

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0.280952

420

22

48

19.090909

0.827815

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1

0.333333

false

0.066667

0.133333

0

0.533333

0

null

0

null

0

1

0

1

0

1

0

3

8a7dafa03dfd357aead512b804e640ce1f6f45ee

737

py

Python

bot1/engine/sysfs_writer.py

dpm76/Bot1

a8e4f6cbc6e4f1d5f1a373a8b3c43811df6446f8

[ "MIT" ]

null

bot1/engine/sysfs_writer.py

dpm76/Bot1

a8e4f6cbc6e4f1d5f1a373a8b3c43811df6446f8

[ "MIT" ]

null

bot1/engine/sysfs_writer.py

dpm76/Bot1

a8e4f6cbc6e4f1d5f1a373a8b3c43811df6446f8

[ "MIT" ]

null

# -*- coding: utf-8 -*- ''' Created on 06/04/2015 @author: david ''' from os import system class SysfsWriter(object): @staticmethod def writeOnce(text, path): ''' writer = SysfsWriter(path) writer.write(text) writer.close() ''' system("echo {0} > {1}".format(text, path)) def __init__(self, path): ''' Constructor ''' self._path = path #self._file = open(path, "a") def write(self, text): #self._file.write(text) #self._file.flush() SysfsWriter.writeOnce(text, self._path) def close(self): #self._file.close() pass

17.139535

51

0.481682

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737

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0.506849

0.092754

0.069565

0

0.02407

0.379919

737

42

52

17.547619

0.730853

0.297151

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0.031532

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0.363636

false

0.090909

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0.545455

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null

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null

0

1

0

1

0

1

0

3

8a82aa98649815d03079e4e5c9ac7d5a804f4112

15,091

py

Python

Detection/AdvancedEAST/label.py

TomHacker/VTD

3009fd53cec8a86493b5f1960e8879e5a0c7345c

[ "Apache-2.0" ]

1

2020-01-01T14:38:44.000Z

Detection/AdvancedEAST/label.py

TomHacker/VTD

3009fd53cec8a86493b5f1960e8879e5a0c7345c

[ "Apache-2.0" ]

null

Detection/AdvancedEAST/label.py

TomHacker/VTD

3009fd53cec8a86493b5f1960e8879e5a0c7345c

[ "Apache-2.0" ]

1

2020-01-07T12:04:33.000Z

import numpy as np import os from PIL import Image, ImageDraw from tqdm import tqdm from Detection.AdvancedEAST import cfg from Detection.AdvancedEAST.preprocess import preprocess_single_image,preprocess_no_cfg def point_inside_of_quad(px, py, quad_xy_list, p_min, p_max): if (p_min[0] <= px <= p_max[0]) and (p_min[1] <= py <= p_max[1]): xy_list = np.zeros((4, 2)) xy_list[:3, :] = quad_xy_list[1:4, :] - quad_xy_list[:3, :] xy_list[3] = quad_xy_list[0, :] - quad_xy_list[3, :] yx_list = np.zeros((4, 2)) yx_list[:, :] = quad_xy_list[:, -1:-3:-1] a = xy_list * ([py, px] - yx_list) b = a[:, 0] - a[:, 1] if np.amin(b) >= 0 or np.amax(b) <= 0: return True else: return False else: return False def point_inside_of_nth_quad(px, py, xy_list, shrink_1, long_edge): nth = -1 vs = [[[0, 0, 3, 3, 0], [1, 1, 2, 2, 1]], [[0, 0, 1, 1, 0], [2, 2, 3, 3, 2]]] for ith in range(2): quad_xy_list = np.concatenate(( np.reshape(xy_list[vs[long_edge][ith][0]], (1, 2)), np.reshape(shrink_1[vs[long_edge][ith][1]], (1, 2)), np.reshape(shrink_1[vs[long_edge][ith][2]], (1, 2)), np.reshape(xy_list[vs[long_edge][ith][3]], (1, 2))), axis=0) p_min = np.amin(quad_xy_list, axis=0) p_max = np.amax(quad_xy_list, axis=0) if point_inside_of_quad(px, py, quad_xy_list, p_min, p_max): if nth == -1: nth = ith else: nth = -1 break return nth def shrink(xy_list, ratio=cfg.shrink_ratio): if ratio == 0.0: return xy_list, xy_list diff_1to3 = xy_list[:3, :] - xy_list[1:4, :] diff_4 = xy_list[3:4, :] - xy_list[0:1, :] diff = np.concatenate((diff_1to3, diff_4), axis=0) dis = np.sqrt(np.sum(np.square(diff), axis=-1)) # determine which are long or short edges long_edge = int(np.argmax(np.sum(np.reshape(dis, (2, 2)), axis=0))) short_edge = 1 - long_edge # cal r length array r = [np.minimum(dis[i], dis[(i + 1) % 4]) for i in range(4)] # cal theta array diff_abs = np.abs(diff) diff_abs[:, 0] += cfg.epsilon theta = np.arctan(diff_abs[:, 1] / diff_abs[:, 0]) # shrink two long edges temp_new_xy_list = np.copy(xy_list) shrink_edge(xy_list, temp_new_xy_list, long_edge, r, theta, ratio) shrink_edge(xy_list, temp_new_xy_list, long_edge + 2, r, theta, ratio) # shrink two short edges new_xy_list = np.copy(temp_new_xy_list) shrink_edge(temp_new_xy_list, new_xy_list, short_edge, r, theta, ratio) shrink_edge(temp_new_xy_list, new_xy_list, short_edge + 2, r, theta, ratio) return temp_new_xy_list, new_xy_list, long_edge def shrink_edge(xy_list, new_xy_list, edge, r, theta, ratio=cfg.shrink_ratio): if ratio == 0.0: return start_point = edge end_point = (edge + 1) % 4 long_start_sign_x = np.sign( xy_list[end_point, 0] - xy_list[start_point, 0]) new_xy_list[start_point, 0] = \ xy_list[start_point, 0] + \ long_start_sign_x * ratio * r[start_point] * np.cos(theta[start_point]) long_start_sign_y = np.sign( xy_list[end_point, 1] - xy_list[start_point, 1]) new_xy_list[start_point, 1] = \ xy_list[start_point, 1] + \ long_start_sign_y * ratio * r[start_point] * np.sin(theta[start_point]) # long edge one, end point long_end_sign_x = -1 * long_start_sign_x new_xy_list[end_point, 0] = \ xy_list[end_point, 0] + \ long_end_sign_x * ratio * r[end_point] * np.cos(theta[start_point]) long_end_sign_y = -1 * long_start_sign_y new_xy_list[end_point, 1] = \ xy_list[end_point, 1] + \ long_end_sign_y * ratio * r[end_point] * np.sin(theta[start_point]) def process_label(data_dir=cfg.data_dir): with open(os.path.join(data_dir, cfg.val_fname), 'r') as f_val: f_list = f_val.readlines() with open(os.path.join(data_dir, cfg.train_fname), 'r') as f_train: f_list.extend(f_train.readlines()) for line, _ in zip(f_list, tqdm(range(len(f_list)))): line_cols = str(line).strip('\n').split(',') img_name, width, height = \ line_cols[0].strip(), int(line_cols[1].strip()), \ int(line_cols[2].strip()) gt = np.zeros((height // cfg.pixel_size, width // cfg.pixel_size, 7)) train_label_dir = os.path.join(data_dir, cfg.train_label_dir_name) xy_list_array = np.load(os.path.join(train_label_dir, img_name.replace('.jpg','.npy'))) train_image_dir = os.path.join(data_dir, cfg.train_image_dir_name) with Image.open(os.path.join(train_image_dir, img_name)) as im: draw = ImageDraw.Draw(im) for xy_list in xy_list_array: _, shrink_xy_list, _ = shrink(xy_list, cfg.shrink_ratio) shrink_1, _, long_edge = shrink(xy_list, cfg.shrink_side_ratio) p_min = np.amin(shrink_xy_list, axis=0) p_max = np.amax(shrink_xy_list, axis=0) # floor of the float ji_min = (p_min / cfg.pixel_size - 0.5).astype(int) - 1 # +1 for ceil of the float and +1 for include the end ji_max = (p_max / cfg.pixel_size - 0.5).astype(int) + 3 imin = np.maximum(0, ji_min[1]) imax = np.minimum(height // cfg.pixel_size, ji_max[1]) jmin = np.maximum(0, ji_min[0]) jmax = np.minimum(width // cfg.pixel_size, ji_max[0]) for i in range(imin, imax): for j in range(jmin, jmax): px = (j + 0.5) * cfg.pixel_size py = (i + 0.5) * cfg.pixel_size if point_inside_of_quad(px, py, shrink_xy_list, p_min, p_max): gt[i, j, 0] = 1 line_width, line_color = 1, 'red' ith = point_inside_of_nth_quad(px, py, xy_list, shrink_1, long_edge) vs = [[[3, 0], [1, 2]], [[0, 1], [2, 3]]] if ith in range(2): gt[i, j, 1] = 1 if ith == 0: line_width, line_color = 2, 'yellow' else: line_width, line_color = 2, 'green' gt[i, j, 2:3] = ith gt[i, j, 3:5] = \ xy_list[vs[long_edge][ith][0]] - [px, py] gt[i, j, 5:] = \ xy_list[vs[long_edge][ith][1]] - [px, py] draw.line([(px - 0.5 * cfg.pixel_size, py - 0.5 * cfg.pixel_size), (px + 0.5 * cfg.pixel_size, py - 0.5 * cfg.pixel_size), (px + 0.5 * cfg.pixel_size, py + 0.5 * cfg.pixel_size), (px - 0.5 * cfg.pixel_size, py + 0.5 * cfg.pixel_size), (px - 0.5 * cfg.pixel_size, py - 0.5 * cfg.pixel_size)], width=line_width, fill=line_color) act_image_dir = os.path.join(cfg.data_dir, cfg.show_act_image_dir_name) if cfg.draw_act_quad: im.save(os.path.join(act_image_dir, img_name)) train_label_dir = os.path.join(data_dir, cfg.train_label_dir_name) np.save(os.path.join(train_label_dir, img_name.replace('.jpg', '_gt.npy')), gt) def process_label_no_cfg(data_dir,shape): print('start preprocessing......') preprocess_no_cfg(data_dir,shape) print('*'*100) print('*' * 100) print('start process labels......') with open(os.path.join(data_dir, cfg.val_fname), 'r') as f_val: f_list = f_val.readlines() with open(os.path.join(data_dir, cfg.train_fname), 'r') as f_train: f_list.extend(f_train.readlines()) for line, _ in zip(f_list, tqdm(range(len(f_list)))): line_cols = str(line).strip('\n').split(',') img_name, width, height = \ line_cols[0].strip(), shape, shape gt = np.zeros((height // cfg.pixel_size, width // cfg.pixel_size, 7)) train_label_dir = os.path.join(data_dir, cfg.train_label_dir_name) xy_list_array = np.load(os.path.join(train_label_dir, img_name.replace('.jpg','.npy'))) train_image_dir = os.path.join(data_dir, cfg.train_image_dir_name) with Image.open(os.path.join(train_image_dir, img_name)) as im: draw = ImageDraw.Draw(im) for xy_list in xy_list_array: _, shrink_xy_list, _ = shrink(xy_list, cfg.shrink_ratio) shrink_1, _, long_edge = shrink(xy_list, cfg.shrink_side_ratio) p_min = np.amin(shrink_xy_list, axis=0) p_max = np.amax(shrink_xy_list, axis=0) # floor of the float ji_min = (p_min / cfg.pixel_size - 0.5).astype(int) - 1 # +1 for ceil of the float and +1 for include the end ji_max = (p_max / cfg.pixel_size - 0.5).astype(int) + 3 imin = np.maximum(0, ji_min[1]) imax = np.minimum(height // cfg.pixel_size, ji_max[1]) jmin = np.maximum(0, ji_min[0]) jmax = np.minimum(width // cfg.pixel_size, ji_max[0]) for i in range(imin, imax): for j in range(jmin, jmax): px = (j + 0.5) * cfg.pixel_size py = (i + 0.5) * cfg.pixel_size if point_inside_of_quad(px, py, shrink_xy_list, p_min, p_max): gt[i, j, 0] = 1 line_width, line_color = 1, 'red' ith = point_inside_of_nth_quad(px, py, xy_list, shrink_1, long_edge) vs = [[[3, 0], [1, 2]], [[0, 1], [2, 3]]] if ith in range(2): gt[i, j, 1] = 1 if ith == 0: line_width, line_color = 2, 'yellow' else: line_width, line_color = 2, 'green' gt[i, j, 2:3] = ith gt[i, j, 3:5] = \ xy_list[vs[long_edge][ith][0]] - [px, py] gt[i, j, 5:] = \ xy_list[vs[long_edge][ith][1]] - [px, py] draw.line([(px - 0.5 * cfg.pixel_size, py - 0.5 * cfg.pixel_size), (px + 0.5 * cfg.pixel_size, py - 0.5 * cfg.pixel_size), (px + 0.5 * cfg.pixel_size, py + 0.5 * cfg.pixel_size), (px - 0.5 * cfg.pixel_size, py + 0.5 * cfg.pixel_size), (px - 0.5 * cfg.pixel_size, py - 0.5 * cfg.pixel_size)], width=line_width, fill=line_color) act_image_dir = os.path.join(cfg.data_dir, cfg.show_act_image_dir_name) if cfg.draw_act_quad: im.save(os.path.join(act_image_dir, img_name)) train_label_dir = os.path.join(data_dir, cfg.train_label_dir_name) np.save(os.path.join(train_label_dir, img_name.replace('.jpg', '_gt.npy')), gt) print(os.path.join(train_label_dir, img_name.replace('.jpg', '_gt.npy'))+' Shape is{} Done!'.format(gt.shape)) def process_label_single_image(img_name,shape): width,height=shape,shape gt = np.zeros((height // cfg.pixel_size, width // cfg.pixel_size, 7)) resized_img,xy_list_array=preprocess_single_image(img_name) for xy_list in xy_list_array: _, shrink_xy_list, _ = shrink(xy_list, cfg.shrink_ratio) shrink_1, _, long_edge = shrink(xy_list, cfg.shrink_side_ratio) p_min = np.amin(shrink_xy_list, axis=0) p_max = np.amax(shrink_xy_list, axis=0) # floor of the float ji_min = (p_min / cfg.pixel_size - 0.5).astype(int) - 1 # +1 for ceil of the float and +1 for include the end ji_max = (p_max / cfg.pixel_size - 0.5).astype(int) + 3 imin = np.maximum(0, ji_min[1]) imax = np.minimum(height // cfg.pixel_size, ji_max[1]) jmin = np.maximum(0, ji_min[0]) jmax = np.minimum(width // cfg.pixel_size, ji_max[0]) for i in range(imin, imax): for j in range(jmin, jmax): px = (j + 0.5) * cfg.pixel_size py = (i + 0.5) * cfg.pixel_size if point_inside_of_quad(px, py, shrink_xy_list, p_min, p_max): gt[i, j, 0] = 1 line_width, line_color = 1, 'red' ith = point_inside_of_nth_quad(px, py, xy_list, shrink_1, long_edge) vs = [[[3, 0], [1, 2]], [[0, 1], [2, 3]]] if ith in range(2): gt[i, j, 1] = 1 if ith == 0: line_width, line_color = 2, 'yellow' else: line_width, line_color = 2, 'green' gt[i, j, 2:3] = ith gt[i, j, 3:5] = \ xy_list[vs[long_edge][ith][0]] - [px, py] gt[i, j, 5:] = \ xy_list[vs[long_edge][ith][1]] - [px, py] return resized_img,gt if __name__ == '__main__': process_label_no_cfg('E:\py_projects\data_new\data_new\data',256)

50.811448

103

0.477238

2,059

15,091

3.226323

0.081107

0.079482

0.039139

0.793467

0.753726

0.729339

0.693964

0.682372

0.672136

0

0.03375

0.401166

15,091

296

104

50.983108

0.701339

0.023656

0

0.667897

0

0.014673

0.002513

0

1

0.02583

false

0

0.02214

0

0.077491

0.01845

0

null

0

1

0

1

0

null

0

3

8a8850dc06a3031c04aec4d9fd3759f0f774b453

157

py

Python

tbot/utils/split.py

thomaserlang/tbot

99cfa204d86ef35cf2cc9482ae5a44abb35b443a

[ "MIT" ]

null

tbot/utils/split.py

thomaserlang/tbot

99cfa204d86ef35cf2cc9482ae5a44abb35b443a

[ "MIT" ]

10

2022-02-14T11:40:20.000Z

2022-03-09T22:44:03.000Z

tbot/utils/split.py

thomaserlang/tbot

99cfa204d86ef35cf2cc9482ae5a44abb35b443a

[ "MIT" ]

1

2020-09-19T16:38:24.000Z

import shlex def split(s): if '"' not in s: return s.split(' ') try: return list(shlex.split(s)) except ValueError: pass

17.444444

35

0.535032

21

157

4

0.666667

0.142857

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0.343949

157

9

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17.444444

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0

0.012658

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false

0.125

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0.5

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null

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8a8995ef6b40809aa8fcabb717f831f30ee25474

11,530

py

Python

Communication/messages_robocup_ssl_detection_pb2.py

MaximeGLegault/UI-Debug

f91e48cb9ffe11e78eafdd2c7a23c525d6cd6e97

[ "MIT" ]

2

2018-03-13T17:22:35.000Z

2019-10-17T11:46:01.000Z

Communication/messages_robocup_ssl_detection_pb2.py

MaximeGLegault/UI-Debug

f91e48cb9ffe11e78eafdd2c7a23c525d6cd6e97

[ "MIT" ]

73

2016-05-30T04:52:41.000Z

2019-06-21T03:11:49.000Z

Communication/messages_robocup_ssl_detection_pb2.py

MaximeGLegault/UI-Debug

f91e48cb9ffe11e78eafdd2c7a23c525d6cd6e97

[ "MIT" ]

11

2016-05-30T04:44:41.000Z

2019-04-13T12:02:14.000Z

# Under MIT License, see LICENSE.txt # Generated by the protocol buffer compiler. DO NOT EDIT! # source: messages_robocup_ssl_detection.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() DESCRIPTOR = _descriptor.FileDescriptor( name='messages_robocup_ssl_detection.proto', package='', serialized_pb=_b('\n$messages_robocup_ssl_detection.proto\"x\n\x11SSL_DetectionBall\x12\x12\n\nconfidence\x18\x01 \x02(\x02\x12\x0c\n\x04\x61rea\x18\x02 \x01(\r\x12\t\n\x01x\x18\x03 \x02(\x02\x12\t\n\x01y\x18\x04 \x02(\x02\x12\t\n\x01z\x18\x05 \x01(\x02\x12\x0f\n\x07pixel_x\x18\x06 \x02(\x02\x12\x0f\n\x07pixel_y\x18\x07 \x02(\x02\"\x97\x01\n\x12SSL_DetectionRobot\x12\x12\n\nconfidence\x18\x01 \x02(\x02\x12\x10\n\x08robot_id\x18\x02 \x01(\r\x12\t\n\x01x\x18\x03 \x02(\x02\x12\t\n\x01y\x18\x04 \x02(\x02\x12\x13\n\x0borientation\x18\x05 \x01(\x02\x12\x0f\n\x07pixel_x\x18\x06 \x02(\x02\x12\x0f\n\x07pixel_y\x18\x07 \x02(\x02\x12\x0e\n\x06height\x18\x08 \x01(\x02\"\xd9\x01\n\x12SSL_DetectionFrame\x12\x14\n\x0c\x66rame_number\x18\x01 \x02(\r\x12\x11\n\tt_capture\x18\x02 \x02(\x01\x12\x0e\n\x06t_sent\x18\x03 \x02(\x01\x12\x11\n\tcamera_id\x18\x04 \x02(\r\x12!\n\x05\x62\x61lls\x18\x05 \x03(\x0b\x32\x12.SSL_DetectionBall\x12*\n\rrobots_yellow\x18\x06 \x03(\x0b\x32\x13.SSL_DetectionRobot\x12(\n\x0brobots_blue\x18\x07 \x03(\x0b\x32\x13.SSL_DetectionRobot') ) _sym_db.RegisterFileDescriptor(DESCRIPTOR) _SSL_DETECTIONBALL = _descriptor.Descriptor( name='SSL_DetectionBall', full_name='SSL_DetectionBall', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='confidence', full_name='SSL_DetectionBall.confidence', index=0, number=1, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='area', full_name='SSL_DetectionBall.area', index=1, number=2, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='x', full_name='SSL_DetectionBall.x', index=2, number=3, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='y', full_name='SSL_DetectionBall.y', index=3, number=4, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='z', full_name='SSL_DetectionBall.z', index=4, number=5, type=2, cpp_type=6, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pixel_x', full_name='SSL_DetectionBall.pixel_x', index=5, number=6, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pixel_y', full_name='SSL_DetectionBall.pixel_y', index=6, number=7, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=40, serialized_end=160, ) _SSL_DETECTIONROBOT = _descriptor.Descriptor( name='SSL_DetectionRobot', full_name='SSL_DetectionRobot', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='confidence', full_name='SSL_DetectionRobot.confidence', index=0, number=1, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='robot_id', full_name='SSL_DetectionRobot.robot_id', index=1, number=2, type=13, cpp_type=3, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='x', full_name='SSL_DetectionRobot.x', index=2, number=3, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='y', full_name='SSL_DetectionRobot.y', index=3, number=4, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='orientation', full_name='SSL_DetectionRobot.orientation', index=4, number=5, type=2, cpp_type=6, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pixel_x', full_name='SSL_DetectionRobot.pixel_x', index=5, number=6, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='pixel_y', full_name='SSL_DetectionRobot.pixel_y', index=6, number=7, type=2, cpp_type=6, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='height', full_name='SSL_DetectionRobot.height', index=7, number=8, type=2, cpp_type=6, label=1, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=163, serialized_end=314, ) _SSL_DETECTIONFRAME = _descriptor.Descriptor( name='SSL_DetectionFrame', full_name='SSL_DetectionFrame', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='frame_number', full_name='SSL_DetectionFrame.frame_number', index=0, number=1, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='t_capture', full_name='SSL_DetectionFrame.t_capture', index=1, number=2, type=1, cpp_type=5, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='t_sent', full_name='SSL_DetectionFrame.t_sent', index=2, number=3, type=1, cpp_type=5, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='camera_id', full_name='SSL_DetectionFrame.camera_id', index=3, number=4, type=13, cpp_type=3, label=2, has_default_value=False, default_value=0, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='balls', full_name='SSL_DetectionFrame.balls', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='robots_yellow', full_name='SSL_DetectionFrame.robots_yellow', index=5, number=6, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), _descriptor.FieldDescriptor( name='robots_blue', full_name='SSL_DetectionFrame.robots_blue', index=6, number=7, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, options=None), ], extensions=[ ], nested_types=[], enum_types=[ ], options=None, is_extendable=False, extension_ranges=[], oneofs=[ ], serialized_start=317, serialized_end=534, ) _SSL_DETECTIONFRAME.fields_by_name['balls'].message_type = _SSL_DETECTIONBALL _SSL_DETECTIONFRAME.fields_by_name['robots_yellow'].message_type = _SSL_DETECTIONROBOT _SSL_DETECTIONFRAME.fields_by_name['robots_blue'].message_type = _SSL_DETECTIONROBOT DESCRIPTOR.message_types_by_name['SSL_DetectionBall'] = _SSL_DETECTIONBALL DESCRIPTOR.message_types_by_name['SSL_DetectionRobot'] = _SSL_DETECTIONROBOT DESCRIPTOR.message_types_by_name['SSL_DetectionFrame'] = _SSL_DETECTIONFRAME SSL_DetectionBall = _reflection.GeneratedProtocolMessageType('SSL_DetectionBall', (_message.Message,), dict( DESCRIPTOR = _SSL_DETECTIONBALL, __module__ = 'messages_robocup_ssl_detection_pb2' # @@protoc_insertion_point(class_scope:SSL_DetectionBall) )) _sym_db.RegisterMessage(SSL_DetectionBall) SSL_DetectionRobot = _reflection.GeneratedProtocolMessageType('SSL_DetectionRobot', (_message.Message,), dict( DESCRIPTOR = _SSL_DETECTIONROBOT, __module__ = 'messages_robocup_ssl_detection_pb2' # @@protoc_insertion_point(class_scope:SSL_DetectionRobot) )) _sym_db.RegisterMessage(SSL_DetectionRobot) SSL_DetectionFrame = _reflection.GeneratedProtocolMessageType('SSL_DetectionFrame', (_message.Message,), dict( DESCRIPTOR = _SSL_DETECTIONFRAME, __module__ = 'messages_robocup_ssl_detection_pb2' # @@protoc_insertion_point(class_scope:SSL_DetectionFrame) )) _sym_db.RegisterMessage(SSL_DetectionFrame) # @@protoc_insertion_point(module_scope)

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8a955ddf4eb8066df9dc120c99da7b52c9ff1b87

152

py

Python

neibor/apps.py

BrendaMwiza/neighborhood

53a4476837324f745470d7aa914214f294be21c6

[ "MIT" ]

null

neibor/apps.py

BrendaMwiza/neighborhood

53a4476837324f745470d7aa914214f294be21c6

[ "MIT" ]

3

2019-11-03T18:33:57.000Z

2021-09-08T01:24:33.000Z

neibor/apps.py

BrendaMwiza/neighborhood

53a4476837324f745470d7aa914214f294be21c6

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import unicode_literals from django.apps import AppConfig class NeiborConfig(AppConfig): name = 'neibor'

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8a9e1f75933d48a36a913ef4cda57e31a8f6cc8e

96

py

Python

src/ttss/Mode.py

tomekzaw/ttss

8c8fdd9e1e3544010bb3d7fe5d9b2ff59e46f61a

[ "MIT" ]

null

src/ttss/Mode.py

tomekzaw/ttss

8c8fdd9e1e3544010bb3d7fe5d9b2ff59e46f61a

[ "MIT" ]

null

src/ttss/Mode.py

tomekzaw/ttss

8c8fdd9e1e3544010bb3d7fe5d9b2ff59e46f61a

[ "MIT" ]

null

from enum import Enum class Mode(Enum): DEPARTURES = 'departure' ARRIVALS = 'arrival'

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8aad5b2d0822def37bd3f501b9c5fe5026ac71f8

52

py

Python

hillfit/__init__.py

bilalshaikh42/hillfit

355413512af17ce123ac2b771e23fe62d878854e

[ "MIT" ]

null

hillfit/__init__.py

bilalshaikh42/hillfit

355413512af17ce123ac2b771e23fe62d878854e

[ "MIT" ]

null

hillfit/__init__.py

bilalshaikh42/hillfit

355413512af17ce123ac2b771e23fe62d878854e

[ "MIT" ]

null

from .fitting import HillFit __version__ = "0.1.3"

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null

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8ab7adb346214653506dd8ae81e7c5a06b55d55b

1,291

py

Python

fragbuilder/basilisk_lib/Mocapy/MocapyExceptions.py

larsbratholm/fragbuilder

e16cbcb190403b5fef49811abd11d16d7ef7fb30

[ "BSD-2-Clause" ]

8

2015-04-11T17:43:13.000Z

2021-12-02T10:18:45.000Z

fragbuilder/basilisk_lib/Mocapy/MocapyExceptions.py

larsbratholm/fragbuilder

e16cbcb190403b5fef49811abd11d16d7ef7fb30

[ "BSD-2-Clause" ]

null

fragbuilder/basilisk_lib/Mocapy/MocapyExceptions.py

larsbratholm/fragbuilder

e16cbcb190403b5fef49811abd11d16d7ef7fb30

[ "BSD-2-Clause" ]

6

2015-04-01T07:18:26.000Z

2021-04-24T11:11:18.000Z

# Mocapy: A parallelized Dynamic Bayesian Network toolkit # # Copyright (C) 2004 Thomas Hamelryck # # This library 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 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 # General Public License for more details. # # You should have received a copy of the GNU General Public License # along with BASILISK. If not, see <http://www.gnu.org/licenses/>. """ Mocapy exception classes. """ class MocapyException(Exception): pass class MocapyVectorException(MocapyException): pass class MocapyDBNException(MocapyException): pass class MocapyVMFException(MocapyException): pass class MocapyGaussianException(MocapyException): pass class MocapyDiscreteException(MocapyException): pass class MocapyDirichletException(MocapyException): pass class MocapyKentException(MocapyException): pass class MocapyEMException(MocapyException): pass class MocapyVMException(MocapyException): pass

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8aba73b8e02feea78d1362cefdd1ed6854478c36

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py

Python

var/spack/repos/builtin/packages/py-filelock/package.py

varioustoxins/spack

cab0e4cb240f34891a6d753f3393e512f9a99e9a

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

null

var/spack/repos/builtin/packages/py-filelock/package.py

varioustoxins/spack

cab0e4cb240f34891a6d753f3393e512f9a99e9a

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

6

2022-01-08T08:41:11.000Z

2022-03-14T19:28:07.000Z

var/spack/repos/builtin/packages/py-filelock/package.py

foeroyingur/spack

5300cbbb2e569190015c72d0970d25425ea38647

[ "ECL-2.0", "Apache-2.0", "MIT-0", "MIT" ]

null

# Copyright 2013-2022 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 PyFilelock(PythonPackage): """A platform-independent file lock for Python. This package contains a single module, which implements a platform independent file lock in Python, which provides a simple way of inter-process communication""" homepage = "https://github.com/benediktschmitt/py-filelock" pypi = "filelock/filelock-3.0.4.tar.gz" version('3.4.0', sha256='93d512b32a23baf4cac44ffd72ccf70732aeff7b8050fcaf6d3ec406d954baf4') version('3.0.12', sha256='18d82244ee114f543149c66a6e0c14e9c4f8a1044b5cdaadd0f82159d6a6ff59') version('3.0.4', sha256='011327d4ed939693a5b28c0fdf2fd9bda1f68614c1d6d0643a89382ce9843a71') version('3.0.3', sha256='7d8a86350736aa0efea0730e6a7f774195cbb1c2d61134c15f6be576399e87ff') version('3.0.0', sha256='b3ad481724adfb2280773edd95ce501e497e88fa4489c6e41e637ab3fd9a456c') version('2.0.13', sha256='d05079e7d7cae7576e192749d3461999ca6b0843d35b0f79f1fa956b0f6fc7d8') version('2.0.12', sha256='eb4314a9a032707a914b037433ce866d4ed363fce8605d45f0c9d2cd6ac52f98') version('2.0.11', sha256='e9e370efe86c30b19a2c8c36dd9fcce8e5ce294ef4ed6ac86664b666eaf852ca') version('2.0.10', sha256='c73bf706d8a0c5722de0b745495fed9cda0e46c0eabb44eb18ee3f00520fa85f') version('2.0.9', sha256='0f91dce339c9f25d6f2e0733a17e4f9a47b139dffda52619a0e61e013e5c6782') version('2.0.8', sha256='7e48e4906de3c9a5d64d8f235eb3ae1050dfefa63fd65eaf318cc915c935212b') depends_on('python@3.6:', when='@3.3:', type=('build', 'run')) depends_on('python@2.7:2,3.5:', when='@3.1:', type=('build', 'run')) depends_on('py-setuptools', type=('build', 'run'))

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0

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8aba9850c786140b6211e9fd7a9163f187300909

199

py

Python

yield_next.py

joshavenue/python_notebook

8d46ba88ef4f05dea6801364bc134edb981df02e

[ "Unlicense" ]

null

yield_next.py

joshavenue/python_notebook

8d46ba88ef4f05dea6801364bc134edb981df02e

[ "Unlicense" ]

null

yield_next.py

joshavenue/python_notebook

8d46ba88ef4f05dea6801364bc134edb981df02e

[ "Unlicense" ]

null

def gen(): yield 3 # Like return but one by one yield 'wow' yield -1 yield 1.2 x = gen() print(next(x)) # Use next() function to go one by one print(next(x)) print(next(x)) print(next(x))

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null

0

3

8abbeaf85fe20109216100fa91b3ee91af6a398d

2,416

py

Python

doc/generate_autodoc_index.py

Lezval/horizon

0e08f4f92bed0a07102c77be12969a095aac5a2a

[ "Apache-2.0" ]

2

2015-05-18T13:50:20.000Z

2015-05-18T14:47:08.000Z

doc/generate_autodoc_index.py

Lezval/horizon

0e08f4f92bed0a07102c77be12969a095aac5a2a

[ "Apache-2.0" ]

null

doc/generate_autodoc_index.py

Lezval/horizon

0e08f4f92bed0a07102c77be12969a095aac5a2a

[ "Apache-2.0" ]

null

#!/usr/bin/env python """Generates files for sphinx documentation using a simple Autodoc based template. To use, just run as a script: $ python doc/generate_autodoc_index.py """ import os base_dir = os.path.dirname(os.path.abspath(__file__)) RSTDIR = os.path.join(base_dir, "source", "sourcecode") SRCS = {'dashboard': os.path.join(base_dir, "..", "openstack-dashboard"), 'django_openstack': os.path.join(base_dir, "..", "django-openstack")} def find_autodoc_modules(module_name, sourcedir): """returns a list of modules in the SOURCE directory""" modlist = [] os.chdir(os.path.join(sourcedir, module_name)) print "SEARCHING %s" % sourcedir for root, dirs, files in os.walk("."): for filename in files: if filename.endswith(".py"): # root = ./dashboard/test/unit # filename = base.py # remove the pieces of the root elements = root.split(os.path.sep) # replace the leading "." with the module name elements[0] = module_name # and get the base module name base, extension = os.path.splitext(filename) if not (base == "__init__"): elements.append(base) result = ".".join(elements) #print result modlist.append(result) return modlist if not(os.path.exists(RSTDIR)): os.mkdir(RSTDIR) INDEXOUT = open("%s/autoindex.rst" % RSTDIR, "w") INDEXOUT.write("Source Code Index\n") INDEXOUT.write("=================\n") INDEXOUT.write(".. toctree::\n") INDEXOUT.write(" :maxdepth: 1\n") INDEXOUT.write("\n") for modulename in SRCS: for module in find_autodoc_modules(modulename, SRCS[modulename]): generated_file = "%s/%s.rst" % (RSTDIR, module) print "Generating %s" % generated_file INDEXOUT.write(" %s\n" % module) FILEOUT = open(generated_file, "w") FILEOUT.write("The :mod:`%s` Module\n" % module) FILEOUT.write("==============================" "==============================" "==============================\n") FILEOUT.write(".. automodule:: %s\n" % module) FILEOUT.write(" :members:\n") FILEOUT.write(" :undoc-members:\n") FILEOUT.write(" :show-inheritance:\n") FILEOUT.close() INDEXOUT.close()

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2,416

4.84

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0.040571

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null

0

1

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1

0

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76e1ac4521176e0f74fc909837b2547afdae25b0

4,268

py

Python

Scripts/simulation/situations/visiting/ungreeted_player_visiting_npc_situation.py

velocist/TS4CheatsInfo

b59ea7e5f4bd01d3b3bd7603843d525a9c179867

[ "Apache-2.0" ]

null

Scripts/simulation/situations/visiting/ungreeted_player_visiting_npc_situation.py

velocist/TS4CheatsInfo

b59ea7e5f4bd01d3b3bd7603843d525a9c179867

[ "Apache-2.0" ]

null

Scripts/simulation/situations/visiting/ungreeted_player_visiting_npc_situation.py

velocist/TS4CheatsInfo

b59ea7e5f4bd01d3b3bd7603843d525a9c179867

[ "Apache-2.0" ]

null

# uncompyle6 version 3.7.4 # Python bytecode 3.7 (3394) # Decompiled from: Python 3.7.9 (tags/v3.7.9:13c94747c7, Aug 17 2020, 18:58:18) [MSC v.1900 64 bit (AMD64)] # Embedded file name: T:\InGame\Gameplay\Scripts\Server\situations\visiting\ungreeted_player_visiting_npc_situation.py # Compiled at: 2016-09-08 04:20:41 # Size of source mod 2**32: 5618 bytes from sims4.tuning.instances import lock_instance_tunables from sims4.tuning.tunable_base import GroupNames from sims4.utils import classproperty from situations.base_situation import _RequestUserData from situations.bouncer.bouncer_request import SelectableSimRequestFactory from situations.situation_complex import SituationStateData from situations.situation_types import SituationCreationUIOption from situations.visiting.visiting_situation_common import VisitingNPCSituation import build_buy, distributor.ops, role.role_state, sims4.tuning.tunable, situations.bouncer.bouncer_types, situations.situation_complex class UngreetedPlayerVisitingNPCSituation(VisitingNPCSituation): INSTANCE_TUNABLES = {'ungreeted_player_sims': sims4.tuning.tunable.TunableTuple(situation_job=situations.situation_job.SituationJob.TunableReference(description='\n The job given to player sims in the ungreeted situation.\n '), role_state=role.role_state.RoleState.TunableReference(description='\n The role state given to player sims in the ungreeted situation.\n '), tuning_group=(GroupNames.ROLES))} @classmethod def _get_greeted_status(cls): return situations.situation_types.GreetedStatus.WAITING_TO_BE_GREETED @classmethod def _states(cls): return (SituationStateData(1, UngreetedPlayerVisitingNPCState),) @classmethod def _get_tuned_job_and_default_role_state_tuples(cls): return [(cls.ungreeted_player_sims.situation_job, cls.ungreeted_player_sims.role_state)] @classmethod def default_job(cls): return cls.ungreeted_player_sims.situation_job @classproperty def distribution_override(cls): return True def start_situation(self): super().start_situation() self._change_state(UngreetedPlayerVisitingNPCState()) build_buy.register_build_buy_enter_callback(self._on_build_buy_enter) build_buy.register_build_buy_exit_callback(self._on_build_buy_exit) def load_situation(self): build_buy.register_build_buy_enter_callback(self._on_build_buy_enter) build_buy.register_build_buy_exit_callback(self._on_build_buy_exit) return super().load_situation() def _destroy(self): build_buy.unregister_build_buy_exit_callback(self._on_build_buy_exit) build_buy.unregister_build_buy_enter_callback(self._on_build_buy_enter) super()._destroy() def _issue_requests(self): request = SelectableSimRequestFactory(self, callback_data=_RequestUserData(role_state_type=(self.ungreeted_player_sims.role_state)), job_type=(self.ungreeted_player_sims.situation_job), exclusivity=(self.exclusivity)) self.manager.bouncer.submit_request(request) def _on_sim_removed_from_situation_prematurely(self, sim, sim_job): if self.num_of_sims > 0: return else: return self.manager.is_player_greeted() or None self._self_destruct() def get_create_op(self, *args, **kwargs): return distributor.ops.SetWallsUpOrDown(True) def get_delete_op(self): return distributor.ops.SetWallsUpOrDown(False) def _on_build_buy_enter(self): op = distributor.ops.SetWallsUpOrDown(False) distributor.system.Distributor.instance().add_op(self, op) def _on_build_buy_exit(self): op = distributor.ops.SetWallsUpOrDown(True) distributor.system.Distributor.instance().add_op(self, op) lock_instance_tunables(UngreetedPlayerVisitingNPCSituation, exclusivity=(situations.bouncer.bouncer_types.BouncerExclusivityCategory.UNGREETED), creation_ui_option=(SituationCreationUIOption.NOT_AVAILABLE), duration=0) class UngreetedPlayerVisitingNPCState(situations.situation_complex.SituationState): pass

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4,268

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0

null

0

null

0

1

0

1

0

3

76e3ac759cb46610e24e4c7d2702c871cceef470

1,129

py

Python

server/user/migrations/0001_initial.py

MetLee/hackergame

571b5407e0644169a2f9b3907a0a1d93138ba436

[ "MIT" ]

48

2018-09-30T11:07:52.000Z

2021-12-07T03:32:59.000Z

server/user/migrations/0001_initial.py

MetLee/hackergame

571b5407e0644169a2f9b3907a0a1d93138ba436

[ "MIT" ]

100

2018-10-13T18:37:25.000Z

2021-11-11T12:14:45.000Z

server/user/migrations/0001_initial.py

MetLee/hackergame

571b5407e0644169a2f9b3907a0a1d93138ba436

[ "MIT" ]

11

2018-10-08T14:59:33.000Z

2022-03-02T03:21:09.000Z

# Generated by Django 2.1.12 on 2019-10-04 09:32 import random from django.db import migrations, models def gen_hash(): return f'{random.randrange(10000):04d}' class Migration(migrations.Migration): initial = True dependencies = [ ] operations = [ migrations.CreateModel( name='User', fields=[ ('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')), ('user', models.IntegerField(unique=True)), ('hash', models.TextField(default=gen_hash)), ('group', models.TextField()), ('nickname', models.TextField(null=True)), ('name', models.TextField(null=True)), ('sno', models.TextField(null=True)), ('tel', models.TextField(null=True)), ('email', models.TextField(null=True)), ('token', models.TextField()), ], options={ 'permissions': [('full', '管理个人信息')], 'default_permissions': (), }, ), ]

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104

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0.196918

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39

115

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0.034483

false

0

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0.275862

0

null

1

0

1

0

1

0

null

0

3

76eed02ced74012c47f21df319d4a40ffb5476f9

89

py

Python

poke_django/trainer/apps.py

XrossFox/Poke-Django-Api-Test

2e272b055fbeb633edb64fb2a3d6a720a50045f8

[ "MIT" ]

2

2016-10-21T21:52:08.000Z

2021-10-19T02:19:43.000Z

poke_django/trainer/apps.py

XrossFox/Poke-Django-Api-Test

2e272b055fbeb633edb64fb2a3d6a720a50045f8

[ "MIT" ]

2

2020-06-05T23:51:09.000Z

2020-10-11T20:12:37.000Z

blackjack_trainer/trainer/apps.py

cberry216/blackjack-strategy-trainer

ec813a3dad9158aaf98f50dd61ab52b122c19382

[ "MIT" ]

4

2016-10-24T19:17:48.000Z

2018-05-11T11:53:12.000Z

from django.apps import AppConfig class TrainerConfig(AppConfig): name = 'trainer'

14.833333

33

0.752809

10

89

6.7

0.9

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0.168539

89

5

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17.8

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1

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false

0

0.333333

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null

0

1

0

null

0

1

0

3

76f27d8974c6c64d388588d2537e66e0ab436004

1,438

py

Python

plynx/base/resource.py

khaxis/plynx

20768470261fc5f29cb660c815c479b49765b2fe

[ "Apache-2.0" ]

137

2018-11-14T07:13:33.000Z

2020-02-03T12:32:35.000Z

plynx/base/resource.py

khaxis/plynx

20768470261fc5f29cb660c815c479b49765b2fe

[ "Apache-2.0" ]

10

2019-01-11T21:51:14.000Z

2020-01-30T01:29:22.000Z

plynx/base/resource.py

khaxis/plynx

20768470261fc5f29cb660c815c479b49765b2fe

[ "Apache-2.0" ]

11

2018-11-14T15:05:54.000Z

2019-09-09T15:45:49.000Z

"""Templates for PLynx Resources and utils.""" from collections import namedtuple from typing import Dict from plynx.constants import NodeResources PreviewObject = namedtuple('PreviewObject', ['fp', 'resource_id']) def _force_decode(byte_array): try: return byte_array.decode("utf-8") except UnicodeDecodeError: return f"# not a UTF-8 sequence:\n{byte_array}" return "Failed to decode the sequence" class BaseResource: """Base Resource class""" DISPLAY_RAW: bool = False def __init__(self): pass @staticmethod def prepare_input(filename: str, preview: bool = False) -> Dict[str, str]: # pylint: disable=unused-argument """Resource preprocessor""" return {NodeResources.INPUT: filename} @staticmethod def prepare_output(filename: str, preview: bool = False) -> Dict[str, str]: """Prepare output""" if not preview: # Create file with open(filename, 'a'): pass return {NodeResources.OUTPUT: filename} @staticmethod def postprocess_output(filename: str) -> str: """Resource postprocessor""" return filename @classmethod def preview(cls, preview_object: PreviewObject) -> str: """Preview Resource""" # TODO escape html code for security reasons data = _force_decode(preview_object.fp.read()) return f"<pre>{data}</pre>"

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158

1,438

5.759494

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0.048352

0.081319

0

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1,438

49

117

29.346939

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0.097458

0.019492

0

0.020408

0

1

0.2

false

0.066667

0.1

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0.6

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null

0

null

0

1

0

1

0

1

0

3

76f625a9aea0ade09d8888d306db58ebdb52aa50

4,866

py

Python

tests/rubrik_polaris/sonar_scan_test.py

crestdatasystems/rubrik-polaris-sdk-for-python

ff0086ab7432db621a8ec89e1b5cba8d0caca7e2

[ "MIT" ]

null

tests/rubrik_polaris/sonar_scan_test.py

crestdatasystems/rubrik-polaris-sdk-for-python

ff0086ab7432db621a8ec89e1b5cba8d0caca7e2

[ "MIT" ]

null

tests/rubrik_polaris/sonar_scan_test.py

crestdatasystems/rubrik-polaris-sdk-for-python

ff0086ab7432db621a8ec89e1b5cba8d0caca7e2

[ "MIT" ]

null

import os import pytest from conftest import util_load_json, BASE_URL from rubrik_polaris.sonar.scan import ERROR_MESSAGES FILE_TYPES = ['ANY', 'HITS', 'STALE', 'OPEN_ACCESS', 'STALE_HITS', 'OPEN_ACCESS_HITS'] @pytest.mark.parametrize("scan_name, resources, analyzer_groups", [ ("", [{"snappableFid": "dummy_id"}], [{"id": "dummy_id"}]), ("scan_name", [], [{"id": "dummy_id"}]), ("scan_name", [{"snappableFid": "dummy_id"}], []) ]) def test_trigger_on_demand_scan_when_invalid_values_are_provided(client, scan_name, resources, analyzer_groups): """ Tests trigger_on_demand_scan method of PolarisClient when invalid values are provided """ from rubrik_polaris.sonar.scan import trigger_on_demand_scan with pytest.raises(ValueError) as e: trigger_on_demand_scan(client, scan_name=scan_name, resources=resources, analyzer_groups=analyzer_groups) assert str(e.value) == ERROR_MESSAGES['MISSING_PARAMETERS_IN_SCAN'] def test_trigger_on_demand_scan_when_valid_values_are_provided(requests_mock, client): """ Tests trigger_on_demand_scan method of PolarisClient when valid values are provided """ from rubrik_polaris.sonar.scan import trigger_on_demand_scan expected_response = util_load_json(os.path.join(os.path.dirname(os.path.realpath(__file__)), "test_data/on_demand_scan.json")) requests_mock.post(BASE_URL + "/graphql", json=expected_response) scan_name = "Scan from SDK" resources = [{"snappableFid": "dummy_id"}] analyzer_groups = [{"id": "dummy_id", "name": "name", "groupType": "group_type", "analyzers": [{}]}] response = trigger_on_demand_scan( client, scan_name=scan_name, resources=resources, analyzer_groups=analyzer_groups) assert response == expected_response def test_get_on_demand_scan_status_when_valid_values_are_provided(requests_mock, client): """ Tests get_on_demand_scan_status method of PolarisClient when valid values are provided """ from rubrik_polaris.sonar.scan import get_on_demand_scan_status expected_response = util_load_json(os.path.join(os.path.dirname(os.path.realpath(__file__)), "test_data/on_demand_scan_status.json")) requests_mock.post(BASE_URL + "/graphql", json=expected_response) response = get_on_demand_scan_status(client, crawl_id="587d147a-add9-4152-b7a0-5a667d99f395") assert response == expected_response @pytest.mark.parametrize("crawl_id", [""]) def test_get_on_demand_scan_status_when_invalid_values_are_provided(client, crawl_id): """ Tests get_on_demand_scan_status method of PolarisClient when invalid values are provided """ from rubrik_polaris.sonar.scan import get_on_demand_scan_status with pytest.raises(ValueError) as e: get_on_demand_scan_status(client, crawl_id=crawl_id) assert str(e.value) == ERROR_MESSAGES['MISSING_PARAMETERS_IN_SCAN_STATUS'] @pytest.mark.parametrize("crawl_id, filters, err_msg", [ ("", {"fileType": "HITS"}, ERROR_MESSAGES['MISSING_PARAMETERS_IN_SCAN_RESULT']), ("scan_name", {}, ERROR_MESSAGES['MISSING_PARAMETERS_IN_SCAN_RESULT']), ("scan_name", {"fileType": "HIT"}, ERROR_MESSAGES['INVALID_FILE_TYPE'].format('HIT', FILE_TYPES)) ]) def test_get_on_demand_scan_result_when_invalid_values_are_provided(client, crawl_id, filters, err_msg, requests_mock): """ Tests get_on_demand_scan_result method of PolarisClient when invalid values are provided """ from rubrik_polaris.sonar.scan import get_on_demand_scan_result expected_response = util_load_json( os.path.join(os.path.dirname(os.path.realpath(__file__)), "test_data/file_type_values.json") ) requests_mock.post(BASE_URL + "/graphql", json=expected_response) with pytest.raises(ValueError) as e: get_on_demand_scan_result(client, crawl_id=crawl_id, filters=filters) assert str(e.value) == err_msg def test_get_on_demand_scan_result_when_valid_values_are_provided(requests_mock, client): """ Tests get_on_demand_scan_result method of PolarisClient when valid values are provided """ from rubrik_polaris.sonar.scan import get_on_demand_scan_result query_response = util_load_json(os.path.join(os.path.dirname(os.path.realpath(__file__)), "test_data/on_demand_scan_result.json")) enum_response = util_load_json( os.path.join(os.path.dirname(os.path.realpath(__file__)), "test_data/file_type_values.json") ) responses = [ {'json': enum_response}, {'json': query_response} ] requests_mock.post(BASE_URL + "/graphql", responses) response = get_on_demand_scan_result(client, crawl_id="dummy_id", filters={"fileType": "HITS"}) assert response == query_response

43.061947

119

0.728935

648

4,866

5.050926

0.143519

0.065995

0.098992

0.073327

0.806599

0.743049

0.70608

0.68897

0.597311

0.53865

0

0.005387

0.160707

4,866

112

120

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0.796033

0.107069

0

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0

0.169723

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0

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1

0.089552

false

0

0.149254

0

0.238806

0

null

0

1

0

null

0

3

76f926951e7b3191305fab755280da429f174f8f

1,403

py

Python

user/migrations/0004_auto_20190705_1454.py

BreakUnrealGod/TanTan

043454a76ee27d61e7d9aede7818f9127e34aaf2

[ "MIT" ]

null

user/migrations/0004_auto_20190705_1454.py

BreakUnrealGod/TanTan

043454a76ee27d61e7d9aede7818f9127e34aaf2

[ "MIT" ]

10

2019-12-04T23:38:04.000Z

2022-02-10T09:53:59.000Z

swiper/user/migrations/0004_auto_20190705_1454.py

lijiaqipy/test1

ab628a794ab67e153b929c819c876c5a676ab068

[ "MIT" ]

null

# Generated by Django 2.2.3 on 2019-07-05 14:54 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('user', '0003_auto_20190704_1547'), ] operations = [ migrations.RenameField( model_name='user', old_name='birth_mohth', new_name='birth_month', ), migrations.RenameField( model_name='user', old_name='birth_yaer', new_name='birth_year', ), migrations.AlterField( model_name='profile', name='dating_sex', field=models.IntegerField(choices=[(0, '全部'), (1, '男'), (2, '女')], default=0), ), migrations.AlterField( model_name='profile', name='location', field=models.CharField(choices=[('bj', '北京'), ('sz', '深圳'), ('sh', '上海'), ('gz', '广州'), ('cd', '成都'), ('dl', '大连')], max_length=64), ), migrations.AlterField( model_name='user', name='location', field=models.CharField(choices=[('bj', '北京'), ('sz', '深圳'), ('sh', '上海'), ('gz', '广州'), ('cd', '成都'), ('dl', '大连')], max_length=64), ), migrations.AlterField( model_name='user', name='sex', field=models.IntegerField(choices=[(0, '全部'), (1, '男'), (2, '女')], default=0), ), ]

31.886364

144

0.496793

146

1,403

4.636986

0.445205

0.079764

0.076809

0.171344

0.711965

0.599705

0.463811

0

0.044284

0.307912

1,403

43

145

32.627907

0.652935

0.032074

0

0.648649

1

0

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0.016962

0

1

0

false

0

0.027027

0

0.108108

0

null

0

1

0

1

0

1

0

null

0

3

0a075be8805805fed40a5a0838052f57b229cf58

238

py

Python

AtCoder/ABC029/C.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

1

2018-11-25T04:15:45.000Z

AtCoder/ABC029/C.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

null

AtCoder/ABC029/C.py

takaaki82/Java-Lessons

c4f11462bf84c091527dde5f25068498bfb2cc49

[ "MIT" ]

2

2018-08-08T13:01:14.000Z

2018-11-25T12:38:36.000Z

N = int(input()) def brute_force(s, remain): if remain == 0: print(s) else: brute_force(s + "a", remain - 1) brute_force(s + "b", remain - 1) brute_force(s + "c", remain - 1) brute_force("", N)

17

40

0.508403

35

238

3.314286

0.457143

0.431034

0.37931

0.439655

0.310345

0

0.024691

0.319328

238

13

41

18.307692

0.691358

0

0.012605

0

1

0.111111

false

0

0.111111

0

null

1

0

null

0

3

0a0766ccdfab40edb3131b5ef4903ea06f8f355a

396

py

Python

dazu/training_data/reader.py

Dazu-io/dazu

064a7fd91961bdf372868e7b0a106102e9fc058b

[ "Apache-2.0" ]

2

2020-03-14T18:17:08.000Z

2020-07-10T01:05:52.000Z

dazu/training_data/reader.py

Dazu-io/dazu

064a7fd91961bdf372868e7b0a106102e9fc058b

[ "Apache-2.0" ]

41

2020-01-20T22:30:08.000Z

2020-02-21T19:46:52.000Z

dazu/training_data/reader.py

Dazu-io/dazu

064a7fd91961bdf372868e7b0a106102e9fc058b

[ "Apache-2.0" ]

3

2019-03-15T17:56:04.000Z

2020-01-17T20:29:37.000Z

from abc import abstractmethod from typing import Dict from dazu.config import DazuConfig from dazu.registry import Module from dazu.typing import TrainingData class Reader(Module): @classmethod @abstractmethod def load(cls, config: DazuConfig) -> TrainingData: pass @classmethod def validate_data(cls, config: DazuConfig, data: Dict) -> bool: return True

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6.12766

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0.131944

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396

17

68

23.294118

0.917197

0

0.153846

0

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0.153846

false

0.076923

0.384615

0.076923

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0

null

0

null

0

1

0

1

0

3

0a14f4c1f0df038c2f10a10238e8e6670db20514

1,388

py

Python

src/ZServer/Zope2/Startup/__init__.py

datakurre/ZServer

9aa87900463229350f691f1c8877c6e8f13538c8

[ "ZPL-2.1" ]

1

2019-06-14T15:39:18.000Z

src/ZServer/Zope2/Startup/__init__.py

datakurre/ZServer

9aa87900463229350f691f1c8877c6e8f13538c8

[ "ZPL-2.1" ]

null

src/ZServer/Zope2/Startup/__init__.py

datakurre/ZServer

9aa87900463229350f691f1c8877c6e8f13538c8

[ "ZPL-2.1" ]

null

############################################################################## # # Copyright (c) 2002 Zope Foundation and Contributors. # All Rights Reserved. # # This software is subject to the provisions of the Zope Public License, # Version 2.1 (ZPL). A copy of the ZPL should accompany this distribution. # THIS SOFTWARE IS PROVIDED "AS IS" AND ANY AND ALL EXPRESS OR IMPLIED # WARRANTIES ARE DISCLAIMED, INCLUDING, BUT NOT LIMITED TO, THE IMPLIED # WARRANTIES OF TITLE, MERCHANTABILITY, AGAINST INFRINGEMENT, AND FITNESS # FOR A PARTICULAR PURPOSE. # ############################################################################## from __future__ import absolute_import import sys # The default async io event loop and twisted reactor can only be # set once. Therefore they must be set as early as possible. try: import uvloop uvloop.install() except ImportError: pass from twisted.internet.error import ReactorAlreadyInstalledError try: import twisted.internet.asyncioreactor twisted.internet.asyncioreactor.install() except (ImportError, ReactorAlreadyInstalledError): pass def get_starter(): if sys.platform[:3].lower() == "win": from ZServer.Zope2.Startup.starter import WindowsZopeStarter return WindowsZopeStarter() else: from ZServer.Zope2.Startup.starter import UnixZopeStarter return UnixZopeStarter()

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0.049837

0.078007

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true

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0

null

0

null

0

1

0

3

0a45e19210e3f8fd15ff3b6f8f8ce4c6ca714738

16

py

Python

chabie/__init__.py

TatchNicolas/chabie

6650da8d34341e181a3ae3d47e76c024bcc0a8dc

[ "MIT" ]

2

2018-12-04T01:40:54.000Z

2019-01-29T05:05:20.000Z

chabie/__init__.py

TatchNicolas/chabie

6650da8d34341e181a3ae3d47e76c024bcc0a8dc

[ "MIT" ]

3

2020-03-24T16:28:22.000Z

2021-02-02T22:06:47.000Z

chabie/__init__.py

TatchNicolas/chabie

6650da8d34341e181a3ae3d47e76c024bcc0a8dc

[ "MIT" ]

null

name = 'chabie'

8

15

0.625

2

16

5

1

0

0.1875

16

1

16

0.769231

0

0.375

0

1

0

false

0

1

0

null

0

1

0

null

0

3

0a49f25c6cb66c0881a569ced7bd0a0345534fa0

329

py

Python

awx/main/routing.py

gitEdouble/awx

5885654405ccaf465f08df4db998a6dafebd9b4d

[ "Apache-2.0" ]

2

2018-11-12T18:52:24.000Z

2020-05-22T18:41:21.000Z

awx/main/routing.py

gitEdouble/awx

5885654405ccaf465f08df4db998a6dafebd9b4d

[ "Apache-2.0" ]

4

2020-04-29T23:03:16.000Z

2022-03-01T23:56:09.000Z

awx/main/routing.py

gitEdouble/awx

5885654405ccaf465f08df4db998a6dafebd9b4d

[ "Apache-2.0" ]

9

2019-05-11T00:03:30.000Z

2021-07-07T16:09:17.000Z

from channels.routing import route channel_routing = [ route("websocket.connect", "awx.main.consumers.ws_connect", path=r'^/websocket/$'), route("websocket.disconnect", "awx.main.consumers.ws_disconnect", path=r'^/websocket/$'), route("websocket.receive", "awx.main.consumers.ws_receive", path=r'^/websocket/$'), ]

36.555556

93

0.711246

40

329

5.75

0.4

0.182609

0.208696

0.234783

0.243478

0

0.094225

329

8

94

41.125

0.771812

0

0.556231

0.273556

0

1

0

false

0

0.166667

0

0.166667

0

null

0

1

0

1

0

null

0

3

0a4a7c2e881ce42dc6e0b95e826eb31368ac6e12

2,232

py

Python

py_client/aidm/aidm_track_closure_classes.py

sma-software/openviriato.algorithm-platform.py-client

73d4cf89aa6f4d02ab15b5504d92107848742325

[ "Apache-2.0" ]

2

2021-06-21T06:50:29.000Z

2021-06-30T15:58:02.000Z

py_client/aidm/aidm_track_closure_classes.py

sma-software/openviriato.algorithm-platform.py-client

73d4cf89aa6f4d02ab15b5504d92107848742325

[ "Apache-2.0" ]

null

py_client/aidm/aidm_track_closure_classes.py

sma-software/openviriato.algorithm-platform.py-client

73d4cf89aa6f4d02ab15b5504d92107848742325

[ "Apache-2.0" ]

null

from py_client.aidm.aidm_base_classes import _HasDebugString from py_client.aidm.aidm_time_window_classes import TimeWindow class AlgorithmNodeTrackClosure(_HasDebugString): __node_id: int __node_track_id: int __closure_time_window: TimeWindow def __init__(self, debug_string: str, node_id: int, node_track_id: int, closure_time_window: TimeWindow): _HasDebugString.__init__(self, debug_string) self.__closure_time_window = closure_time_window self.__node_id = node_id self.__node_track_id = node_track_id @property def node_id(self) -> int: return self.__node_id @property def node_track_id(self) -> int: return self.__node_track_id @property def closure_time_window(self) -> TimeWindow: return self.__closure_time_window class AlgorithmSectionTrackClosure(_HasDebugString): __section_track_id: int __from_node_id: int __to_node_id: int __closure_time_window_from_node: TimeWindow __closure_time_window_to_node: TimeWindow def __init__( self, debug_string: str, section_track_id: int, from_node_id: int, to_node_id: int, closure_time_window_from_node: TimeWindow, closure_time_window_to_node: TimeWindow): _HasDebugString.__init__(self, debug_string) self.__section_track_id = section_track_id self.__from_node_id = from_node_id self.__to_node_id = to_node_id self.__closure_time_window_from_node = closure_time_window_from_node self.__closure_time_window_to_node = closure_time_window_to_node @property def section_track_id(self) -> int: return self.__section_track_id @property def from_node_id(self) -> int: return self.__from_node_id @property def to_node_id(self) -> int: return self.__to_node_id @property def closure_time_window_from_node(self) -> TimeWindow: return self.__closure_time_window_from_node @property def closure_time_window_to_node(self) -> TimeWindow: return self.__closure_time_window_to_node

31.885714

110

0.697133

281

2,232

4.846975

0.103203

0.139501

0.22467

0.092511

0.717327

0.629222

0.420705

0.299559

0.23348

0

0.247312

2,232

69

111

32.347826

0.810714

0

0.181818

0

1

0.181818

false

0

0.036364

0.145455

0.545455

0

null

0

1

0

null

0

1

0

3

0a6077624e8a5eec68b3d6b8f51513c0ebaf50fb

1,280

py

Python

Android/parser/ui/images/encode_bitmaps.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

1

2020-05-31T08:46:45.000Z

Android/parser/ui/images/encode_bitmaps.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

null

Android/parser/ui/images/encode_bitmaps.py

Bravest-Ptt/Useful-Shell

75016ff44f218afce6b885af7b23fb801a7ef2d4

[ "Apache-2.0" ]

null

""" This is a way to save the startup time when running img2py on lots of files... """ import sys from wx.tools import img2py command_lines = [ " -F -n action_clean_history action_clean_history.png images.py", "-a -F -n action_new action_new.png images.py", "-a -F -n app_splash app_splash.png images.py", "-a -F -n web_service_error web_service_error.png images.py", "-a -F -n web_service_info web_service_info.png images.py", "-a -F -n web_service_success web_service_success.png images.py", "-a -F -n task_done task_done.png images.py", "-a -F -n task_process task_process.png images.py", "-a -F -n task_paused task_paused.png images.py", "-a -F -n task_waiting task_waiting.png images.py", "-a -F -n task_generating task_generating.png images.py" ] if __name__ == "__main__": for line in command_lines: args = line.split() img2py.main(args)

42.666667

92

0.489844

156

1,280

3.762821

0.339744

0.037479

0.206133

0.204429

0.32368

0.27598

0.122658

0

0.00406

0.422656

1,280

29

93

44.137931

0.790257

0.060938

0

0.782718

0.057047

0

1

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false

0

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0

0.105263

0

null

0

1

0

1

0

null

0

3

0a6611331aec5272182cb56364fda31f43b05983

11,288

py

Python

sdk/python/pulumi_alicloud/apigateway/vpc_access.py

pulumi/pulumi-alicloud

9c34d84b4588a7c885c6bec1f03b5016e5a41683

[ "ECL-2.0", "Apache-2.0" ]

42

2019-03-18T06:34:37.000Z

2022-03-24T07:08:57.000Z

sdk/python/pulumi_alicloud/apigateway/vpc_access.py

pulumi/pulumi-alicloud

9c34d84b4588a7c885c6bec1f03b5016e5a41683

[ "ECL-2.0", "Apache-2.0" ]

152

2019-04-15T21:03:44.000Z

2022-03-29T18:00:57.000Z

sdk/python/pulumi_alicloud/apigateway/vpc_access.py

pulumi/pulumi-alicloud

9c34d84b4588a7c885c6bec1f03b5016e5a41683

[ "ECL-2.0", "Apache-2.0" ]

3

2020-08-26T17:30:07.000Z

2021-07-05T01:37:45.000Z

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi Terraform Bridge (tfgen) Tool. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** import warnings import pulumi import pulumi.runtime from typing import Any, Mapping, Optional, Sequence, Union, overload from .. import _utilities __all__ = ['VpcAccessArgs', 'VpcAccess'] @pulumi.input_type class VpcAccessArgs: def __init__(__self__, *, instance_id: pulumi.Input[str], port: pulumi.Input[int], vpc_id: pulumi.Input[str], name: Optional[pulumi.Input[str]] = None): """ The set of arguments for constructing a VpcAccess resource. :param pulumi.Input[str] instance_id: ID of the instance in VPC (ECS/Server Load Balance). :param pulumi.Input[int] port: ID of the port corresponding to the instance. :param pulumi.Input[str] vpc_id: The vpc id of the vpc authorization. :param pulumi.Input[str] name: The name of the vpc authorization. """ pulumi.set(__self__, "instance_id", instance_id) pulumi.set(__self__, "port", port) pulumi.set(__self__, "vpc_id", vpc_id) if name is not None: pulumi.set(__self__, "name", name) @property @pulumi.getter(name="instanceId") def instance_id(self) -> pulumi.Input[str]: """ ID of the instance in VPC (ECS/Server Load Balance). """ return pulumi.get(self, "instance_id") @instance_id.setter def instance_id(self, value: pulumi.Input[str]): pulumi.set(self, "instance_id", value) @property @pulumi.getter def port(self) -> pulumi.Input[int]: """ ID of the port corresponding to the instance. """ return pulumi.get(self, "port") @port.setter def port(self, value: pulumi.Input[int]): pulumi.set(self, "port", value) @property @pulumi.getter(name="vpcId") def vpc_id(self) -> pulumi.Input[str]: """ The vpc id of the vpc authorization. """ return pulumi.get(self, "vpc_id") @vpc_id.setter def vpc_id(self, value: pulumi.Input[str]): pulumi.set(self, "vpc_id", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the vpc authorization. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @pulumi.input_type class _VpcAccessState: def __init__(__self__, *, instance_id: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, vpc_id: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering VpcAccess resources. :param pulumi.Input[str] instance_id: ID of the instance in VPC (ECS/Server Load Balance). :param pulumi.Input[str] name: The name of the vpc authorization. :param pulumi.Input[int] port: ID of the port corresponding to the instance. :param pulumi.Input[str] vpc_id: The vpc id of the vpc authorization. """ if instance_id is not None: pulumi.set(__self__, "instance_id", instance_id) if name is not None: pulumi.set(__self__, "name", name) if port is not None: pulumi.set(__self__, "port", port) if vpc_id is not None: pulumi.set(__self__, "vpc_id", vpc_id) @property @pulumi.getter(name="instanceId") def instance_id(self) -> Optional[pulumi.Input[str]]: """ ID of the instance in VPC (ECS/Server Load Balance). """ return pulumi.get(self, "instance_id") @instance_id.setter def instance_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "instance_id", value) @property @pulumi.getter def name(self) -> Optional[pulumi.Input[str]]: """ The name of the vpc authorization. """ return pulumi.get(self, "name") @name.setter def name(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "name", value) @property @pulumi.getter def port(self) -> Optional[pulumi.Input[int]]: """ ID of the port corresponding to the instance. """ return pulumi.get(self, "port") @port.setter def port(self, value: Optional[pulumi.Input[int]]): pulumi.set(self, "port", value) @property @pulumi.getter(name="vpcId") def vpc_id(self) -> Optional[pulumi.Input[str]]: """ The vpc id of the vpc authorization. """ return pulumi.get(self, "vpc_id") @vpc_id.setter def vpc_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "vpc_id", value) class VpcAccess(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, instance_id: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, vpc_id: Optional[pulumi.Input[str]] = None, __props__=None): """ ## Import Api gateway app can be imported using the id, e.g. ```sh $ pulumi import alicloud:apigateway/vpcAccess:VpcAccess example "APiGatewayVpc:vpc-aswcj19ajsz:i-ajdjfsdlf:8080" ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] instance_id: ID of the instance in VPC (ECS/Server Load Balance). :param pulumi.Input[str] name: The name of the vpc authorization. :param pulumi.Input[int] port: ID of the port corresponding to the instance. :param pulumi.Input[str] vpc_id: The vpc id of the vpc authorization. """ ... @overload def __init__(__self__, resource_name: str, args: VpcAccessArgs, opts: Optional[pulumi.ResourceOptions] = None): """ ## Import Api gateway app can be imported using the id, e.g. ```sh $ pulumi import alicloud:apigateway/vpcAccess:VpcAccess example "APiGatewayVpc:vpc-aswcj19ajsz:i-ajdjfsdlf:8080" ``` :param str resource_name: The name of the resource. :param VpcAccessArgs args: The arguments to use to populate this resource's properties. :param pulumi.ResourceOptions opts: Options for the resource. """ ... def __init__(__self__, resource_name: str, *args, **kwargs): resource_args, opts = _utilities.get_resource_args_opts(VpcAccessArgs, pulumi.ResourceOptions, *args, **kwargs) if resource_args is not None: __self__._internal_init(resource_name, opts, **resource_args.__dict__) else: __self__._internal_init(resource_name, *args, **kwargs) def _internal_init(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, instance_id: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, vpc_id: Optional[pulumi.Input[str]] = None, __props__=None): if opts is None: opts = pulumi.ResourceOptions() if not isinstance(opts, pulumi.ResourceOptions): raise TypeError('Expected resource options to be a ResourceOptions instance') if opts.version is None: opts.version = _utilities.get_version() if opts.id is None: if __props__ is not None: raise TypeError('__props__ is only valid when passed in combination with a valid opts.id to get an existing resource') __props__ = VpcAccessArgs.__new__(VpcAccessArgs) if instance_id is None and not opts.urn: raise TypeError("Missing required property 'instance_id'") __props__.__dict__["instance_id"] = instance_id __props__.__dict__["name"] = name if port is None and not opts.urn: raise TypeError("Missing required property 'port'") __props__.__dict__["port"] = port if vpc_id is None and not opts.urn: raise TypeError("Missing required property 'vpc_id'") __props__.__dict__["vpc_id"] = vpc_id super(VpcAccess, __self__).__init__( 'alicloud:apigateway/vpcAccess:VpcAccess', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, instance_id: Optional[pulumi.Input[str]] = None, name: Optional[pulumi.Input[str]] = None, port: Optional[pulumi.Input[int]] = None, vpc_id: Optional[pulumi.Input[str]] = None) -> 'VpcAccess': """ Get an existing VpcAccess resource's state with the given name, id, and optional extra properties used to qualify the lookup. :param str resource_name: The unique name of the resulting resource. :param pulumi.Input[str] id: The unique provider ID of the resource to lookup. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[str] instance_id: ID of the instance in VPC (ECS/Server Load Balance). :param pulumi.Input[str] name: The name of the vpc authorization. :param pulumi.Input[int] port: ID of the port corresponding to the instance. :param pulumi.Input[str] vpc_id: The vpc id of the vpc authorization. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _VpcAccessState.__new__(_VpcAccessState) __props__.__dict__["instance_id"] = instance_id __props__.__dict__["name"] = name __props__.__dict__["port"] = port __props__.__dict__["vpc_id"] = vpc_id return VpcAccess(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="instanceId") def instance_id(self) -> pulumi.Output[str]: """ ID of the instance in VPC (ECS/Server Load Balance). """ return pulumi.get(self, "instance_id") @property @pulumi.getter def name(self) -> pulumi.Output[str]: """ The name of the vpc authorization. """ return pulumi.get(self, "name") @property @pulumi.getter def port(self) -> pulumi.Output[int]: """ ID of the port corresponding to the instance. """ return pulumi.get(self, "port") @property @pulumi.getter(name="vpcId") def vpc_id(self) -> pulumi.Output[str]: """ The vpc id of the vpc authorization. """ return pulumi.get(self, "vpc_id")

37.131579

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11,288

4.84141

0.110132

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0.070064

0.751896

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0.691386

0.648165

0.640431

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0

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0.280829

11,288

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37.254125

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0

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0

1

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false

0.005682

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0.272727

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null

0

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0

1

0

1

0

null

0

3

6a4f45597597bd19a6b6e1eddcb0eec72e2d136f

11,318

py

Python

polygon/library.py

rayeef/polygon

b69d614c8f1d83bc0b07ea705fa781441a70fc9a

[ "Apache-2.0" ]

null

polygon/library.py

rayeef/polygon

b69d614c8f1d83bc0b07ea705fa781441a70fc9a

[ "Apache-2.0" ]

null

polygon/library.py

rayeef/polygon

b69d614c8f1d83bc0b07ea705fa781441a70fc9a

[ "Apache-2.0" ]

null

from definitions import LastTrade from definitions import LastQuote from definitions import HistTrade from definitions import Quote from definitions import Aggregate from definitions import Company from definitions import CompanyV3 from definitions import Address from definitions import Symbol from definitions import SymbolV3 from definitions import Dividend from definitions import News from definitions import NewsV2 from definitions import Publisher from definitions import Earning from definitions import Financial from definitions import Exchange from definitions import Error from definitions import NotFound from definitions import Conflict from definitions import Unauthorized from definitions import MarketStatus from definitions import MarketHoliday from definitions import AnalystRatings from definitions import RatingSection from definitions import CryptoTick from definitions import CryptoTickJson from definitions import CryptoExchange from definitions import CryptoSnapshotTicker from definitions import CryptoSnapshotBookItem from definitions import CryptoSnapshotTickerBook from definitions import CryptoSnapshotAgg from definitions import Forex from definitions import LastForexTrade from definitions import LastForexQuote from definitions import ForexAggregate from definitions import ForexSnapshotTicker from definitions import ForexSnapshotAgg from definitions import Ticker from definitions import Split from definitions import Financials from definitions import Trade from definitions import StocksSnapshotTicker from definitions import StocksSnapshotBookItem from definitions import StocksSnapshotTickerBook from definitions import StocksV2Trade from definitions import StocksV2NBBO from definitions import StocksSnapshotAgg from definitions import StocksSnapshotQuote from definitions import Aggv2 from definitions import AggResponse from definitions import ReferenceTickersApiResponse from definitions import ReferenceTickersV3ApiResponse from definitions import ReferenceTickerTypesApiResponse from definitions import ReferenceTickerDetailsApiResponse from definitions import ReferenceTickerDetailsV3ApiResponse from definitions import ReferenceTickerNewsApiResponse from definitions import ReferenceTickerNewsV2ApiResponse from definitions import ReferenceMarketsApiResponse from definitions import ReferenceLocalesApiResponse from definitions import ReferenceStockSplitsApiResponse from definitions import ReferenceStockDividendsApiResponse from definitions import ReferenceStockFinancialsApiResponse from definitions import ReferenceMarketStatusApiResponse from definitions import ReferenceMarketHolidaysApiResponse from definitions import StocksEquitiesExchangesApiResponse from definitions import StocksEquitiesHistoricTradesApiResponse from definitions import HistoricTradesV2ApiResponse from definitions import StocksEquitiesHistoricQuotesApiResponse from definitions import HistoricNBboQuotesV2ApiResponse from definitions import StocksEquitiesLastTradeForASymbolApiResponse from definitions import StocksEquitiesLastQuoteForASymbolApiResponse from definitions import StocksEquitiesDailyOpenCloseApiResponse from definitions import StocksEquitiesConditionMappingsApiResponse from definitions import StocksEquitiesSnapshotAllTickersApiResponse from definitions import StocksEquitiesSnapshotSingleTickerApiResponse from definitions import StocksEquitiesSnapshotGainersLosersApiResponse from definitions import StocksEquitiesPreviousCloseApiResponse from definitions import StocksEquitiesAggregatesApiResponse from definitions import StocksEquitiesGroupedDailyApiResponse from definitions import ForexCurrenciesHistoricForexTicksApiResponse from definitions import ForexCurrenciesRealTimeCurrencyConversionApiResponse from definitions import ForexCurrenciesLastQuoteForACurrencyPairApiResponse from definitions import ForexCurrenciesGroupedDailyApiResponse from definitions import ForexCurrenciesPreviousCloseApiResponse from definitions import ForexCurrenciesSnapshotAllTickersApiResponse from definitions import ForexCurrenciesSnapshotSingleTickerApiResponse from definitions import ForexCurrenciesSnapshotGainersLosersApiResponse from definitions import CryptoCryptoExchangesApiResponse from definitions import CryptoLastTradeForACryptoPairApiResponse from definitions import CryptoDailyOpenCloseApiResponse from definitions import CryptoHistoricCryptoTradesApiResponse from definitions import CryptoGroupedDailyApiResponse from definitions import CryptoPreviousCloseApiResponse from definitions import CryptoSnapshotAllTickersApiResponse from definitions import CryptoSnapshotSingleTickerApiResponse from definitions import CryptoSnapshotSingleTickerFullBookApiResponse from definitions import CryptoSnapshotGainersLosersApiResponse from definitions import CurrenciesAggregatesApiResponse from definitions import StockSymbol from definitions import ConditionTypeMap from definitions import SymbolTypeMap from definitions import TickerSymbol import typing from definitions import Definition AnyDefinition = typing.TypeVar("AnyDefinition", bound=Definition) # noinspection SpellCheckingInspection name_to_class: typing.Dict[str, typing.Callable[[], typing.Type[AnyDefinition]]] = { "LastTrade": LastTrade, "LastQuote": LastQuote, "HistTrade": HistTrade, "Quote": Quote, "Aggregate": Aggregate, "Company": Company, "CompanyV3": CompanyV3, "Address": Address, "Symbol": Symbol, "Dividend": Dividend, "News": News, "NewsV2": NewsV2, "Publisher": Publisher, "Earning": Earning, "Financial": Financial, "Exchange": Exchange, "Error": Error, "NotFound": NotFound, "Conflict": Conflict, "Unauthorized": Unauthorized, "MarketStatus": MarketStatus, "MarketHoliday": MarketHoliday, "AnalystRatings": AnalystRatings, "RatingSection": RatingSection, "CryptoTick": CryptoTick, "CryptoTickJson": CryptoTickJson, "CryptoExchange": CryptoExchange, "CryptoSnapshotTicker": CryptoSnapshotTicker, "CryptoSnapshotBookItem": CryptoSnapshotBookItem, "CryptoSnapshotTickerBook": CryptoSnapshotTickerBook, "CryptoSnapshotAgg": CryptoSnapshotAgg, "Forex": Forex, "LastForexTrade": LastForexTrade, "LastForexQuote": LastForexQuote, "ForexAggregate": ForexAggregate, "ForexSnapshotTicker": ForexSnapshotTicker, "ForexSnapshotAgg": ForexSnapshotAgg, "Ticker": Ticker, "Split": Split, "Financials": Financials, "Trade": Trade, "StocksSnapshotTicker": StocksSnapshotTicker, "StocksSnapshotBookItem": StocksSnapshotBookItem, "StocksSnapshotTickerBook": StocksSnapshotTickerBook, "StocksV2Trade": StocksV2Trade, "StocksV2NBBO": StocksV2NBBO, "StocksSnapshotAgg": StocksSnapshotAgg, "StocksSnapshotQuote": StocksSnapshotQuote, "Aggv2": Aggv2, "AggResponse": AggResponse, "ReferenceTickersApiResponse": ReferenceTickersApiResponse, "ReferenceTickersV3ApiResponse": ReferenceTickersV3ApiResponse, "ReferenceTickerTypesApiResponse": ReferenceTickerTypesApiResponse, "ReferenceTickerDetailsApiResponse": ReferenceTickerDetailsApiResponse, "ReferenceTickerDetailsV3ApiResponse": ReferenceTickerDetailsV3ApiResponse, "ReferenceTickerNewsApiResponse": ReferenceTickerNewsApiResponse, "ReferenceTickerNewsV2ApiResponse": ReferenceTickerNewsV2ApiResponse, "ReferenceMarketsApiResponse": ReferenceMarketsApiResponse, "ReferenceLocalesApiResponse": ReferenceLocalesApiResponse, "ReferenceStockSplitsApiResponse": ReferenceStockSplitsApiResponse, "ReferenceStockDividendsApiResponse": ReferenceStockDividendsApiResponse, "ReferenceStockFinancialsApiResponse": ReferenceStockFinancialsApiResponse, "ReferenceMarketStatusApiResponse": ReferenceMarketStatusApiResponse, "ReferenceMarketHolidaysApiResponse": ReferenceMarketHolidaysApiResponse, "StocksEquitiesExchangesApiResponse": StocksEquitiesExchangesApiResponse, "StocksEquitiesHistoricTradesApiResponse": StocksEquitiesHistoricTradesApiResponse, "HistoricTradesV2ApiResponse": HistoricTradesV2ApiResponse, "StocksEquitiesHistoricQuotesApiResponse": StocksEquitiesHistoricQuotesApiResponse, "HistoricNBboQuotesV2ApiResponse": HistoricNBboQuotesV2ApiResponse, "StocksEquitiesLastTradeForASymbolApiResponse": StocksEquitiesLastTradeForASymbolApiResponse, "StocksEquitiesLastQuoteForASymbolApiResponse": StocksEquitiesLastQuoteForASymbolApiResponse, "StocksEquitiesDailyOpenCloseApiResponse": StocksEquitiesDailyOpenCloseApiResponse, "StocksEquitiesConditionMappingsApiResponse": StocksEquitiesConditionMappingsApiResponse, "StocksEquitiesSnapshotAllTickersApiResponse": StocksEquitiesSnapshotAllTickersApiResponse, "StocksEquitiesSnapshotSingleTickerApiResponse": StocksEquitiesSnapshotSingleTickerApiResponse, "StocksEquitiesSnapshotGainersLosersApiResponse": StocksEquitiesSnapshotGainersLosersApiResponse, "StocksEquitiesPreviousCloseApiResponse": StocksEquitiesPreviousCloseApiResponse, "StocksEquitiesAggregatesApiResponse": StocksEquitiesAggregatesApiResponse, "StocksEquitiesGroupedDailyApiResponse": StocksEquitiesGroupedDailyApiResponse, "ForexCurrenciesHistoricForexTicksApiResponse": ForexCurrenciesHistoricForexTicksApiResponse, "ForexCurrenciesRealTimeCurrencyConversionApiResponse": ForexCurrenciesRealTimeCurrencyConversionApiResponse, "ForexCurrenciesLastQuoteForACurrencyPairApiResponse": ForexCurrenciesLastQuoteForACurrencyPairApiResponse, "ForexCurrenciesGroupedDailyApiResponse": ForexCurrenciesGroupedDailyApiResponse, "ForexCurrenciesPreviousCloseApiResponse": ForexCurrenciesPreviousCloseApiResponse, "ForexCurrenciesSnapshotAllTickersApiResponse": ForexCurrenciesSnapshotAllTickersApiResponse, "ForexCurrenciesSnapshotSingleTickerApiResponse": ForexCurrenciesSnapshotSingleTickerApiResponse, "ForexCurrenciesSnapshotGainersLosersApiResponse": ForexCurrenciesSnapshotGainersLosersApiResponse, "CryptoCryptoExchangesApiResponse": CryptoCryptoExchangesApiResponse, "CryptoLastTradeForACryptoPairApiResponse": CryptoLastTradeForACryptoPairApiResponse, "CryptoDailyOpenCloseApiResponse": CryptoDailyOpenCloseApiResponse, "CryptoHistoricCryptoTradesApiResponse": CryptoHistoricCryptoTradesApiResponse, "CryptoGroupedDailyApiResponse": CryptoGroupedDailyApiResponse, "CryptoPreviousCloseApiResponse": CryptoPreviousCloseApiResponse, "CryptoSnapshotAllTickersApiResponse": CryptoSnapshotAllTickersApiResponse, "CryptoSnapshotSingleTickerApiResponse": CryptoSnapshotSingleTickerApiResponse, "CryptoSnapshotSingleTickerFullBookApiResponse": CryptoSnapshotSingleTickerFullBookApiResponse, "CryptoSnapshotGainersLosersApiResponse": CryptoSnapshotGainersLosersApiResponse, "CurrenciesAggregatesApiResponse": CurrenciesAggregatesApiResponse, } # noinspection SpellCheckingInspection name_to_type = { "StockSymbol": StockSymbol, "ConditionTypeMap": ConditionTypeMap, "SymbolTypeMap": SymbolTypeMap, "TickerSymbol": TickerSymbol, }

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6a71cd9a3a4a72b42c9c16579ec0689070b5b326

170

py

Python

utils/convert_datetime.py

huynhminhtruong/py

6f90423a62103b2bd28daa0d5a27b4a25bc318c8

[ "MIT" ]

null

utils/convert_datetime.py

huynhminhtruong/py

6f90423a62103b2bd28daa0d5a27b4a25bc318c8

[ "MIT" ]

null

utils/convert_datetime.py

huynhminhtruong/py

6f90423a62103b2bd28daa0d5a27b4a25bc318c8

[ "MIT" ]

null

import datetime as dt date_time_str = '2019-11-04T12:12:51Z' date_time_obj = dt.datetime.strptime(date_time_str, '%Y-%m-%dT%H:%M:%SZ') print(date_time_obj.timestamp())

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6a7c7c04c0b9e8643f9cb05da0c380ed19234a92

370

py

Python

funboost/utils/dependency_packages/mongomq/utils.py

DJMIN/funboost

7570ca2909bb0b44a1080f5f98aa96c86d3da9d4

[ "Apache-2.0" ]

333

2019-08-08T10:25:27.000Z

2022-03-30T07:32:04.000Z

funboost/utils/dependency_packages/mongomq/utils.py

mooti-barry/funboost

2cd9530e2c4e5a52fc921070d243d402adbc3a0e

[ "Apache-2.0" ]

38

2020-04-24T01:47:51.000Z

2021-12-20T07:22:15.000Z

funboost/utils/dependency_packages/mongomq/utils.py

mooti-barry/funboost

2cd9530e2c4e5a52fc921070d243d402adbc3a0e

[ "Apache-2.0" ]

84

2019-08-09T11:51:14.000Z

2022-03-02T06:29:09.000Z

def enum(name, *sequential, **named): values = dict(zip(sequential, range(len(sequential))), **named) # NOTE: Yes, we *really* want to cast using str() here. # On Python 2 type() requires a byte string (which is str() on Python 2). # On Python 3 it does not matter, so we'll use str(), which acts as # a no-op. return type(str(name), (), values)

46.25

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0.076596

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370

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null

0

1

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6a91c867376436aedff1c1b17719fe89d54add01

194

py

Python

resdk/shortcuts/__init__.py

tristanbrown/resolwe-bio-py

c911defde8a5e7e902ad1adf4f9e480f17002c18

[ "Apache-2.0" ]

4

2016-09-28T16:00:05.000Z

2018-08-16T16:14:10.000Z

resdk/shortcuts/__init__.py

tristanbrown/resolwe-bio-py

c911defde8a5e7e902ad1adf4f9e480f17002c18

[ "Apache-2.0" ]

229

2016-03-28T19:41:00.000Z

2022-03-16T15:02:15.000Z

resdk/shortcuts/__init__.py

tristanbrown/resolwe-bio-py

c911defde8a5e7e902ad1adf4f9e480f17002c18

[ "Apache-2.0" ]

18

2016-03-10T16:11:57.000Z

2021-06-01T10:01:49.000Z

""".. Ignore pydocstyle D400. ========= Shortcuts ========= Shortcut mixin classes ====================== .. autoclass:: resdk.shortcuts.collection.CollectionRelationsMixin :members: """

13.857143

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194

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1

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3

6a9a56b22b45a784db590179a8a9211729bf5133

50

py

Python

env/Lib/site-packages/frccontrol/version.py

DiMino-0/Rapid-React-2022-Team810

05c61453fce7d9762b119dce4326bbdb1cb8688b

[ "BSD-3-Clause" ]

null

env/Lib/site-packages/frccontrol/version.py

DiMino-0/Rapid-React-2022-Team810

05c61453fce7d9762b119dce4326bbdb1cb8688b

[ "BSD-3-Clause" ]

5

2022-02-13T14:38:04.000Z

2022-02-15T00:13:07.000Z

env/Lib/site-packages/frccontrol/version.py

DiMino-0/Rapid-React-2022-Team810

05c61453fce7d9762b119dce4326bbdb1cb8688b

[ "BSD-3-Clause" ]

4

2022-02-04T22:58:27.000Z

2022-02-14T19:29:18.000Z

# Autogenerated by setup.py __version__ = "2022.9"

25

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0

1

0

1

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null

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3

6aa102af37c99a906bbbf0f58ec1ef62d9b40076

378

py

Python

src/pyglue/DocStrings/ExceptionMissingFile.py

omenos/OpenColorIO

7316c3be20752278924dd3f213bff297ffb63a14

[ "BSD-3-Clause" ]

7

2015-07-01T03:19:43.000Z

2021-03-27T11:02:16.000Z

src/pyglue/DocStrings/ExceptionMissingFile.py

dictoon/OpenColorIO

64adcad300adfd166280d2e7b1fb5c3ce7dca482

[ "BSD-3-Clause" ]

null

src/pyglue/DocStrings/ExceptionMissingFile.py

dictoon/OpenColorIO

64adcad300adfd166280d2e7b1fb5c3ce7dca482

[ "BSD-3-Clause" ]

2

2019-03-05T20:43:59.000Z

2019-11-11T20:35:55.000Z

class ExceptionMissingFile: """ An exception class for errors detected at runtime, thrown when OCIO cannot find a file that is expected to exist. This is provided as a custom type to distinguish cases where one wants to continue looking for missing files, but wants to properly fail for other error conditions. """ def __init__(self): pass

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1

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1

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3

6aacdfa486708ed8b617784dc9cd04599014bd8e

251

py

Python

WEEKS/CD_Sata-Structures/general/practice/PYTHON/37 - arrayMaxConsecutiveSum.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

WEEKS/CD_Sata-Structures/general/practice/PYTHON/37 - arrayMaxConsecutiveSum.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

WEEKS/CD_Sata-Structures/general/practice/PYTHON/37 - arrayMaxConsecutiveSum.py

webdevhub42/Lambda

b04b84fb5b82fe7c8b12680149e25ae0d27a0960

[ "MIT" ]

null

def arrayMaxConsecutiveSum(inputArray, k): arr = [sum(inputArray[:k])] for i in range(1, len(inputArray) - (k - 1)): arr.append(arr[i - 1] - inputArray[i - 1] + inputArray[i + k - 1]) sort_arr = sorted(arr) return sort_arr[-1]

35.857143

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1

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1

0

1

0

null

0

3

6ad298a145a3e0b10594c4465cca34f885db1f68

147

py

Python

mah_tags/apps.py

mahbd/brur-payment

cb9812e1d2f8c22c7015708ca9bb4fc05bfb1452

[ "MIT" ]

null

mah_tags/apps.py

mahbd/brur-payment

cb9812e1d2f8c22c7015708ca9bb4fc05bfb1452

[ "MIT" ]

null

mah_tags/apps.py

mahbd/brur-payment

cb9812e1d2f8c22c7015708ca9bb4fc05bfb1452

[ "MIT" ]

null

from django.apps import AppConfig class MahTagsConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'mah_tags'

21

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3

6ad58fa69ec62fd766239b79d36be41ba2a0bd77

70,155

py

Python

model/SDE/s.Imp-em-numpy-mp-net v2-average.py

neulbo-187/Cucker-Smale-Model

e77e8d804be440999c0e410a41364a992b8fcc75

[ "MIT" ]

2

2021-03-08T11:23:58.000Z

2021-04-11T11:10:08.000Z

model/SDE/s.Imp-em-numpy-mp-net v2-average.py

neulbo-187/Cucker-Smale-Model

e77e8d804be440999c0e410a41364a992b8fcc75

[ "MIT" ]

null

model/SDE/s.Imp-em-numpy-mp-net v2-average.py

neulbo-187/Cucker-Smale-Model

e77e8d804be440999c0e410a41364a992b8fcc75

[ "MIT" ]

null

#%% import numpy as np from scipy import integrate import matplotlib.pyplot as plt import matplotlib as mpl import time from matplotlib import animation, rc from IPython.display import HTML from matplotlib.ticker import ScalarFormatter import matplotlib.gridspec as gridspec from matplotlib.ticker import MaxNLocator from mpl_toolkits.axes_grid1.inset_locator import inset_axes, mark_inset import matplotlib.patches as mpatches from mpl_toolkits.axes_grid1.inset_locator import (inset_axes, TransformedBbox,BboxPatch, BboxConnector) from matplotlib.ticker import ScalarFormatter, FormatStrFormatter import os import glob import pandas as pd #np 참고 http://taewan.kim/post/numpy_cheat_sheet/ def sto_ratio(start,end,below): if np.min(Vcum[1:,start:end,0,0]) >= below : ratio = abs(np.max(np.max(Vcum[1:,start:end,0,0],axis=0)-np.min(Vcum[1:,start:end,0,0],axis=0))/(np.max(Vcum[1:,start:end,0,0])-np.min(Vcum[1:,start:end,0,0]))) else : ratio=0 return ratio def makeplot(): global fig # fig=plt.figure(constrained_layout=True,figsize=(10,5)) # spec=gridspec.GridSpec(ncols=9,nrows=6,figure=fig) # ax=fig.add_subplot(spec[0:3,0:4]) # bx=fig.add_subplot(spec[0:3,4:8]) # bx_larged=fig.add_subplot(spec[0:3,8]) # dx=fig.add_subplot(spec[3:,6:]) ## plot1 : graph of (v_t^1)_1 ... (v_t^n)_1 on trial =1 fig_size=(5.1,3.4) fig=plt.figure(figsize=fig_size) plt.plot(np.array(range(0,T))*h,[0 for tt in range(T)],linewidth=0.8,c='k') for i in range(N): plt.plot(np.array(range(0,T))*h,Vcum[1,:,i,0],alpha=0.6,linewidth=0.3) axes = plt.axes() axes.set_xlim(right=(T-2)*h,left=0) axes.set_xlabel('t') axes.set_ylabel('velocity',rotation=90) saveplot(1,plotsave) ## plot2 : graph of (v_t^1)_1 on all trial fig=plt.figure(figsize=fig_size) ## plot 안에 그래프 그리기 : inset_axes,mark_inset/https://data-newbie.tistory.com/447 axes=plt.axes() plt.plot(np.array(range(0,T))*h,[0 for tt in range(T)],linewidth=0.8,c='k') for i in range(Trial) : plt.plot(np.array(range(0,T))*h,Vcum[i+1,:,0,0],linewidth=0.3, alpha=0.6) axes.set_xlim(right=(T-2)*h,left=0) ax_max=max(np.max(Vcum[1:,:,0,0]),-1*np.min(Vcum[1:,:,0,0])) if np.max(Vcum[1:,:,0,0]) > (-1)*np.min(Vcum[1:,:,0,0]): # ax_cut=int(np.median(np.argmax(Vcum[1:,:,0,0],axis=1))) cut_sign=1 plotlen=abs(np.min(Vcum[1:,:,0,0]))/(abs(np.max(Vcum[1:,:,0,0]))+abs(np.min(Vcum[1:,:,0,0]))) else : # ax_cut=int(np.median(np.argmin(Vcum[1:,:,0,0],axis=1))) cut_sign=-1 plotlen=abs(np.max(Vcum[1:,:,0,0]))/(abs(np.max(Vcum[1:,:,0,0]))+abs(np.min(Vcum[1:,:,0,0]))) # ax_ycut=np.max(Vcum[1:,ax_cut,0,0]) # ax_ycut2=np.min(Vcum[1:,ax_cut,0,0]) # # print(np.argmax(Vcum[1:,:,0,0],axis=1)) # # print(Vcum[1,:,0,0]) # # print(Vcum[2,:,0,0]) # # print(Vcum[3,:,0,0]) # print("ax_ycut : %f" %ax_ycut) # print("ax_ycut2 : %f" %ax_ycut2) # lar_len=min(12*(ax_ycut-ax_ycut2),abs(ax_ycut)*0.3) # cutunit=3 # print("ax_cut : %d" %ax_cut) # print("lar_len : %.2f" %lar_len) # # select=0 # # bounded_l=ax_cut # # bounded_r=T-1 # # ccut=ax_cut*3+50 # # while select==0 : # # if cut_sign*(ax_ycut-np.mean(Vcum[:,ccut,0,0]))>lar_len : # # bounded_r=ccut # # ccut=int((bounded_l+ccut)/2) # # if cut_sign*(ax_ycut-np.mean(Vcum[:,ccut,0,0]))<lar_len : # # bounded_l=ccut # # ccut=int((bounded_r+ccut)/2) # # if bounded_r-bounded_l<cutunit: # # select=1 # # ax_rightcut=min(int(ax_cut*4),bounded_r+1) # # print("bound l : %d" %bounded_l) # # print("bound r : %d" %bounded_r) # # print("ax_rightcut : %d" %ax_rightcut) # # select=0 # # bounded_l=0 # # bounded_r=ax_cut # # ccut=int(ax_cut*0.5) # # while select==0 : # # if cut_sign*(ax_ycut-np.mean(Vcum[:,ccut,0,0]))>lar_len : # # bounded_l=ccut # # ccut=int((bounded_r+ccut)/2) # # if cut_sign*(ax_ycut-np.mean(Vcum[:,ccut,0,0]))<lar_len : # # bounded_r=ccut # # ccut=int((bounded_l+ccut)/2) # # if bounded_r-bounded_l<cutunit: # # select=1 # # ax_leftcut=max(bounded_l,int(ax_cut-(ax_rightcut-ax_cut)),0) # # print("bound l : %d" %bounded_l) # # print("bound r : %d" %bounded_r) # # print("ax_leftcut : %d" %ax_leftcut) below=0.1 if T>900 : enlarge_len=6 else : enlarge_len=3 I_start=range(0,T-enlarge_len) ratio=np.zeros(T-enlarge_len) for i in I_start: ratio[i] = sto_ratio(i,i+enlarge_len,below*ax_max) ax_leftcut=np.argmax(ratio) ax_rightcut=ax_leftcut+enlarge_len print("ax_leftcut : %d" %ax_leftcut) print("cut_sign : %d" %cut_sign) print("plotlen : %.2f" %plotlen ) ax_larged=inset_axes(axes,"100%","100%",bbox_to_anchor=[0.9-0.35,0.05+(0.1+plotlen)*(1+cut_sign)/2,0.08+0.35,0.8-plotlen+0.02*(cut_sign-1)/2],bbox_transform=axes.transAxes,borderpad=0) #x축 시작 위치, y축 시작 위치, 너비, 높이 for i in range(Trial) : ax_larged.plot(np.array(range(ax_leftcut,ax_rightcut))*h,Vcum[i+1,ax_leftcut:ax_rightcut,0,0],linewidth=0.3, alpha=0.5) # ax_larged.set_xticks([]) ax_larged.set_yticks([]) # ax_larged.set_ylim(bottom=np.max(Vcum[:,ax_leftcut:ax_rightcut,0,0])-lar_len*1.5,top=np.max(Vcum[:,ax_leftcut:ax_rightcut,0,0])+lar_len*0.05) # ax_larged.set_ylim(bottom=np.max(Vcum[:,ax_cut,0,0])-lar_len*1.5,top=np.max(Vcum[:,ax_cut,0,0])+lar_len*0.05) my_mark_inset(axes,ax_larged,loc1a=2,loc1b=1,loc2a=3,loc2b=4,fc="none",ec="0.2",boxlw=0.6,connectlw=0.4) #우상부터 반시계로 1~4 axes.set_xlabel('t') axes.set_ylabel('velocity',rotation=90) saveplot(2,plotsave) # plot3 : graph of E(Vnrm) fig=plt.figure(constrained_layout=True,figsize=fig_size) spec=gridspec.GridSpec(ncols=18,nrows=6,figure=fig) EVnrm=np.mean(Vnrmcum[1:],axis=0) EphE=np.mean(phEcum[1:],axis=0) VVnrmcum=np.sort(Vnrmcum[1:],axis=0) E0=EVnrm[0]+EphE[0] SupVnrm=max(np.max(VVnrmcum[int(Trial*0.9),:]), np.max(EVnrm)) print (EVnrm) scale_const=int(np.log10(E0)) scale=10**(-scale_const) if E0>= SupVnrm: cx_up=fig.add_subplot(spec[:2,:]) cx_down=fig.add_subplot(spec[2:,:]) # cx_down.plot(np.array(range(0,T))*h,[0 for tt in range(T)],linewidth=0.8,c='k') cx_up.plot(np.array(range(0,T))*h,EVnrm*scale,linewidth=0.7,alpha=0.8,label=r'$\mathrm{\mathbb{E}}\Vert {\bf v}_t \Vert$') cx_up.plot(np.array(range(0,T))*h,[E0*scale for tt in range(T)],linewidth=0.5,c='gold',label=r'$E_0$',ls='--') cx_up.plot(np.array(range(0,T))*h,(E0-EphE)*scale, alpha=0.8,linewidth=0.7,c='forestgreen',label=r'$E_0-E^{\phi}_t$',ls='-.') cx_up.plot(np.array(range(0,T))*h,(EphE+EVnrm)*scale, alpha=0.8,linewidth=0.5,c='firebrick',label=r'$E_t$',ls=':') # cx_up.plot(range(0,T),medVnrm,c='paleturquoise',linewidth=0.7,alpha=0.7,label='median of ') # cx_up.plot(range(0,T),VVnrmcum[int(Trial*0.9),:],c='deeppink',linewidth=0.5,alpha=0.7,label='90%') cx_down.plot(np.array(range(0,T))*h,EVnrm*scale,linewidth=0.95,alpha=0.8,label=r'$\mathrm{\mathbb{E}}$') cx_down.plot(np.array(range(0,T))*h,[E0*scale for tt in range(T)],linewidth=0.5,c='gold') cx_down.plot(np.array(range(0,T))*h,(E0-EphE)*scale, alpha=0.8,linewidth=0.7,c='forestgreen',ls='-.') cx_down.plot(np.array(range(0,T))*h,(EphE+EVnrm)*scale, alpha=0.8,linewidth=0.5,c='firebrick',ls=':') # cx_down.plot(range(0,T),medVnrm,c='paleturquoise',linewidth=0.7,alpha=0.7,label='median') # cx_down.plot(range(0,T),VVnrmcum[int(Trial*0.9),:],c='deeppink',linewidth=0.5,alpha=0.7,label='90%') cx_up.set_ylim(0.9*E0*scale,E0*scale*1.01) # cxcut=E0-min(EphE[np.argmax(VVnrmcum[int(Trial*0.9),:])], EphE[np.argmax(EVnrm)]) cx_top=SupVnrm*1.2*scale # cx_bottom=min(np.min(VVnrmcum[0,:])*(-0.5),SupVnrm*(-0.05))*scale cx_bottom=-0.001*2 cx_down.set_ylim(bottom=cx_bottom,top=cx_top) # cx_down.set_ylim(top=cxcut*1.2) cx_up.legend(fontsize=9.5*0.83,loc='best') # cx_down.legend(fontsize=10,loc='best') cx_up.spines['bottom'].set_visible(False) cx_down.spines['top'].set_visible(False) cx_up.xaxis.set_visible(False) cx_down.xaxis.tick_bottom() cx_up.set_xlim(right=(T-2)*h, left=-.01/9) cx_down.set_xlim(right=(T-2)*h,left=-.01/9) axes=cx_down d = .004 # how big to make the diagonal lines in axes coordinates # arguments to pass to plot, just so we don't keep repeating them kwargs = dict(transform=cx_up.transAxes, color='k', clip_on=False,lw=0.8) curvyline_x=np.linspace(-d,1+d,250) curvyline_y=1.5*2*d*np.sin(2*np.pi/d*8*curvyline_x) cx_up.plot(curvyline_x,curvyline_y, **kwargs) # top-left diagonal kwargs.update(transform=cx_down.transAxes) # switch to the bottom axes cx_down.plot(curvyline_x, 1+0.7*curvyline_y, **kwargs) # bottom-right diagonal cx_up.annotate(r'$\times$10$^{%i}$' %(scale_const),xy=(0.003,0.83),xycoords='axes fraction') #축의 가ㅄ 표시 형식 -> 이것 저것 해보다가 결국 수동으로 하기로 #https://stackoverflow.com/questions/39620700//positioning-the-exponent-of-tick-labels-when-using-scientific-notation-in-matplo else : cx=fig.add_subplot(spec[:,:]) # cx.set_title(r'$\mathrm{\mathbb{E}}||v(t)||^2$') # cx.set_xlabel('K=%.2f,M=%.2f, sigma=%.2f' %(K,M,L)) cx.plot(np.array(range(0,T))*h,EVnrm,linewidth=0.7,alpha=0.8,label=r'$\mathrm{\mathbb{E}}||v||$') cx.plot(np.array(range(0,T))*h,[E0 for tt in range(T)],linewidth=0.5,c='gold',label=r'$E_0$') cx.plot(np.array(range(0,T))*h,E0-EphE, alpha=0.8,linewidth=0.5,c='forestgreen',label=r'$E_0-E^{\phi}_t$',ls='-.') cx.plot(np.array(range(0,T))*h,EphE+EVnrm, alpha=0.8,linewidth=0.5,c='firebrick',label=r'$E_t$',ls=':') # cx.plot(range(0,T),medVnrm,c='paleturquoise',linewidth=0.7,alpha=0.7,label='median') # cx.plot(range(0,T),VVnrmcum[int(Trial*0.9),:],c='deeppink',linewidth=0.5,alpha=0.7,label='90%') cx.legend(fontsize=10,loc='best') cx_top=E0 cx_bottom=-0.001 axes=cx plotlen=abs(np.min(EVnrm))/(E0+abs(np.min(EVnrm))) cx_larged=inset_axes(axes,"100%","100%",bbox_to_anchor=[0.7,plotlen+0.15,0.28,0.8-plotlen],bbox_transform=axes.transAxes,borderpad=0) #x축 시작 위치, y축 시작 위치, 너비, 높이 cx_larged.plot(np.array(range(0,T))*h,EVnrm*scale,label=r'$\mathrm{\mathbb{E}}$') cx_larged.plot(np.array(range(0,T))*h,(E0-EphE)*scale, alpha=0.8,linewidth=0.7,c='forestgreen',label=r'$E_0-E_\phi(t)$',ls='-.') # cx_larged.plot(range(0,T),medVnrm,c='paleturquoise',linewidth=0.7,alpha=0.7) # cx_larged.plot(range(0,T),VVnrmcum[int(Trial*0.9),:],c='deeppink',linewidth=0.5,alpha=0.7) # cx_rightcut=np.argmax(EVnrm) cx_rightcut=int(T/250*3) # cx_larged.set_ylim(bottom=min(np.min(VVnrmcum[0,:])*(-0.5),SupVnrm*(-0.01)),top=SupVnrm*1.05) # cx_larged.set_ylim(bottom=min(np.min(VVnrmcum[0:cx_rightcut])*(-0.5),np.max(EVnrm[0:cx_rightcut])*(-0.1)),top=(E0-np.min(EphE[:int(cx_rightcut*1.05)]))*0.65) # cx_larged.set_ylim(bottom=max(cx_bottom,np.max(EVnrm[:int(cx_rightcut*1.05)+1])*(-0.025)*scale),top=min(scale*((E0-np.min(EphE[:int(cx_rightcut*1.05)+1]))*0.35+np.max(EVnrm[0:int(cx_rightcut*1.05)+1])*0.65),cx_top*0.9)) cx_larged.set_ylim(bottom=max(cx_bottom,np.min(EVnrm[:int(cx_rightcut*1.05)+1])*scale),top=min(scale*((E0-np.min(EphE[:int(cx_rightcut*1.05)+1]))*0.35+np.max(EVnrm[0:int(cx_rightcut*1.05)+1])*0.65),cx_top*0.9)) # cx_larged.set_xlim(left=cx_rightcut*(-0.05)*h,right=cx_rightcut*1.05*h) cx_larged.set_xlim(left=0,right=cx_rightcut*1.05*h) # cx_larged.legend(fontsize=5,loc='best') cx_larged.set_yticks([]) my_mark_inset(axes,cx_larged,loc1a=2,loc1b=1,loc2a=3,loc2b=4,fc="none",ec="0.2",boxlw=0.4,connectlw=0.3) #우상부터 반시계로 1~4 axes.set_xlabel('t') saveplot(3,plotsave) ## dx : graph of H(x,v) fig=plt.figure(figsize=fig_size) Hxv=np.mean(Xbnrmcum[1:]+Vnrmcum[1:],axis=0) plt.plot(np.array(range(0,T))*h,Hxv) axes=plt.axes() axes.set_xlim(left=0,right=(T-2)*h) axes.set_ylim(bottom=-0.001*2400) axes.set_xlabel('t') axes.set_yscale('log') saveplot(4,plotsave) #fig.tight_layout() def my_mark_inset(parent_axes, inset_axes, loc1a=1, loc1b=1, loc2a=2, loc2b=2,boxlw=0.5,connectlw=0.5, **kwargs): rect = TransformedBbox(inset_axes.viewLim, parent_axes.transData) pp = BboxPatch(rect, fill=False,lw=boxlw, **kwargs) parent_axes.add_patch(pp) p1 = BboxConnector(inset_axes.bbox, rect, loc1=loc1a, loc2=loc1b,lw=connectlw, **kwargs) inset_axes.add_patch(p1) p1.set_clip_on(False) p2 = BboxConnector(inset_axes.bbox, rect, loc1=loc2a, loc2=loc2b,lw=connectlw, **kwargs) inset_axes.add_patch(p2) p2.set_clip_on(False) return pp, p1, p2 def saveplot(plotnum,save) : if save!=0 : # plt.savefig('graph_k%.2fm%.2fs%.4fnet%d.%d.%dN%dpsLB%.2fphLB%.2ftrial%dh%.5f-%d.pdf' %(K,M,L,nettype[0],nettype[1],nettype[2],N,psLB,phLB,Trial,h,plotnum),dpi=2000,bbox_inches='tight',pad_inches=0.02) if plotnum == 2 : plt.savefig('graph_k%.1fm%.1fs%.5fnet%d.%d.%dN%d-%d.eps' %(K,M,L,nettype[0],nettype[1],nettype[2],N,plotnum),dpi=3000,bbox_inches='tight',pad_inches=0.02) plt.savefig('graph_k%.1fm%.1fs%.5fnet%d.%d.%dN%d-%d.pdf' %(K,M,L,nettype[0],nettype[1],nettype[2],N,plotnum),dpi=3000,bbox_inches='tight',pad_inches=0.02) print("image saved_%d" %plotnum) else : plt.show() def savedata(savemode) : ## savemode==1 : save just outlier data and initial setting ## savemode==2 : save all data and initial setting ## savemode==0 : don't save if savemode==1 : print("data reshaping") selP = Pcum[selI,:,:,:].reshape(-1,T*N*2) selV = Vcum[selI,:,:,:].reshape(-1,T*N*2) selVnrm = Vnrmcum[selI,:] selXbnrm = Xbnrmcum[selI,:] seldB = dBcum[selI,:] selP_df=pd.DataFrame(selP) selV_df=pd.DataFrame(selV) selVnrm_df=pd.DataFrame(selVnrm) selXbnrm_df=pd.DataFrame(selXbnrm) seldB_df=pd.DataFrame(seldB) selcount_df=pd.DataFrame(selcount) print("saving...") selP_df.to_csv('selP_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") selV_df.to_csv('selV_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") selVnrm_df.to_csv('selVnrm_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") selXbnrm_df.to_csv('selXbnrm_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") seldB_df.to_csv('seldB_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") selcount_df.to_csv('selcount_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") elif savemode==2 : print("data reshaping") reP = Pcum.reshape(-1,T*N*2) reV = Vcum.reshape(-1,T*N*2) redB = dBcum.reshape(-1,T*2) P_df=pd.DataFrame(reP) V_df=pd.DataFrame(reV) dBcum_df=pd.DataFrame(redB) Vnrm_df=pd.DataFrame(Vnrmcum) Xbnrm_df=pd.DataFrame(Xbnrmcum) phE_df=pd.DataFrame(phEcum) print("saving...") P_df.to_csv('P_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") V_df.to_csv('V_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") Vnrm_df.to_csv('Vnrm_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") Xbnrm_df.to_csv('Xbnrm_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") phE_df.to_csv('phE_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") dBcum_df.to_csv('dBcum_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") # setting 을 df로 만들어서 입출력 편하게 저장하는 법 확인하기. # dB, Pinit, Vinit, Z, A if savemode!=0 : variables=['N','alpha','beta','psLB','phLB','K','M','L','T','h','Trial','cut','nettype','curvetype','version'] setting={} for index in variables: setting[index]=globals()[index] setting_df = pd.DataFrame(setting) Pinit_df=pd.DataFrame(Pinit) Vinit_df=pd.DataFrame(Vinit) Z_df=pd.DataFrame(Z) A_df=pd.DataFrame(A) setting_df.to_csv('setting_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") Pinit_df.to_csv('Pinit_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") Vinit_df.to_csv('Vinit_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") Z_df.to_csv('Z_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") A_df.to_csv('A_%s_%s.csv' %(set_name,test_name),index=False,sep="\t") def makenet(net_type): A=np.zeros((N,N)) if net_type==0 : A[:,:]=1 for i in range(N) : A[i,i]=0 elif net_type==1 : for i in range(N-1) : A[i,i+1] = 1 A[0,1:N]=1 A[0:int(N/2)-1,int(N/2)-1]=1 A[int(N/2)-1,int(N/2):N]=1 A[:N-1,N-1]=1 A=A+A.T elif net_type==2 : for i in range(N-1) : A[i,i+1] = 1 A=A+A.T elif net_type==3 : if N % 2 != 0 : step=2 elif N % 4 == 0 : step=N/2-1 else : step=N/2-2 for i in range(N) : A[i,int((i+step)%N)]=1 A[i,int((i-step)%N)]=1 elif net_type==4 : for i in range(N-1) : A[i,i+1] = 1 A=A+A.T for i in range(int(N/10)) : A[i*10,:]=1 A[:,i*10]=1 A[i*10,i*10]=0 elif net_type==5 : for i in range(N-1) : A[i,i+1] = 1 A[N-1,0]=1 A=A+A.T return A def phiEest(ssq,b,LB): phE=(np.power(1+ssq,1-b)-1)/(1-b)+ssq*LB return phE def psi(s,b,LB): a = np.power((1+s),-b) + LB return a def csmpf(X,V): Kem=np.zeros((N,2)) for i in range(N): J= A_ps[i,:] == 1 s=(np.power(X[i][0]-X[:,0],2)+np.power(X[i][1]-X[:,1],2))[J] ps=psi(s,alpha,psLB) a=np.sum((V[J]-V[i])*np.array([ps]).T,axis=0) * K #행렬의 각 행별로 array에 저장된 scalar를 곱하려고 하려면 dimension이 같아야함 #즉 여기선 n*2 행렬이 있고 거기에서 각각의 행에 곱할 scalar가 ps에 저장되어 있는데, #1dimension으로 n짜리 array로는 못하고, n*1 사이즈의 2차원 행렬이어야 함. # a/=N J= A_ph[i,:] == 1 u=np.array([0.0,0.0]) ss=(np.power(X[i][0]-Z[i][0]-X[:,0]+Z[:,0],2)+np.power(X[i][1]-Z[i][1]-X[:,1]+Z[:,1],2))[J] pss=psi(ss,beta,phLB) u=np.sum((X[J]-Z[J]-X[i]+Z[i])*np.array([pss]).T,axis=0) * M a+=u Kem[i]=a Kem=np.nan_to_num(Kem) return Kem def brown(V) : W=np.zeros((N,2)) for i in range(N) : J= A_b[i,:]==1 W[i]=np.sum((V[J]-V[i]))*L return W def dW(dt) : return np.random.normal(0,np.sqrt(dt)) def theta(x): a=np.heaviside(x,0) return a def Curve (dom) : num=N if jump==1: num*=2 t=np.linspace(0,dom,num,endpoint=False) if curvename=='circle': X = np.cos(t) Y = np.sin(t) elif curvename=='pi': X = 17/31 *np.sin(235/57 - 32 *t) + 19/17 *np.sin(192/55 - 30 *t) + 47/32 *np.sin(69/25 - 29 *t) + 35/26 *np.sin(75/34 - 27 *t) + 6/31 *np.sin(23/10 - 26 *t) + 35/43 *np.sin(10/33 - 25 *t) + 126/43 *np.sin(421/158 - 24 *t) + 143/57 *np.sin(35/22 - 22 *t) + 106/27 *np.sin(84/29 - 21 *t) + 88/25 *np.sin(23/27 - 20 *t) + 74/27 *np.sin(53/22 - 19 *t) + 44/53 *np.sin(117/25 - 18 *t) + 126/25 *np.sin(88/49 - 17 *t) + 79/11 *np.sin(43/26 - 16 *t) + 43/12 *np.sin(41/17 - 15 *t) + 47/27 *np.sin(244/81 - 14 *t) + 8/5 *np.sin(79/19 - 13 *t) + 373/46 *np.sin(109/38 - 12 *t) + 1200/31 *np.sin(133/74 - 11 *t) + 67/24 *np.sin(157/61 - 10 *t) + 583/28 *np.sin(13/8 - 8 *t) + 772/35 *np.sin(59/16 - 7 *t) + 3705/46 *np.sin(117/50 - 6 *t) + 862/13 *np.sin(19/8 - 5 *t) + 6555/34 *np.sin(157/78 - 3 *t) + 6949/13 *np.sin(83/27 - t) - 6805/54 *np.sin(2 *t + 1/145) - 5207/37 *np.sin(4 *t + 49/74) - 1811/58 *np.sin(9 *t + 55/43) - 63/20 *np.sin(23 *t + 2/23) - 266/177 *np.sin(28 *t + 13/18) - 2/21 *np.sin(31 *t + 7/16) Y = 70/37 *np.sin(65/32 - 32 *t) + 11/12 *np.sin(98/41 - 31 *t) + 26/29 *np.sin(35/12 - 30 *t) + 54/41 *np.sin(18/7 - 29 *t) + 177/71 *np.sin(51/19 - 27 *t) + 59/34 *np.sin(125/33 - 26 *t) + 49/29 *np.sin(18/11 - 25 *t) + 151/75 *np.sin(59/22 - 24 *t) + 52/9 *np.sin(118/45 - 22 *t) + 52/33 *np.sin(133/52 - 21 *t) + 37/45 *np.sin(61/14 - 20 *t) + 143/46 *np.sin(144/41 - 19 *t) + 254/47 *np.sin(19/52 - 18 *t) + 246/35 *np.sin(92/25 - 17 *t) + 722/111 *np.sin(176/67 - 16 *t) + 136/23 *np.sin(3/19 - 15 *t) + 273/25 *np.sin(32/21 - 13 *t) + 229/33 *np.sin(117/28 - 12 *t) + 19/4 *np.sin(43/11 - 11 *t) + 135/8 *np.sin(23/10 - 10 *t) + 205/6 *np.sin(33/23 - 8 *t) + 679/45 *np.sin(55/12 - 7 *t) + 101/8 *np.sin(11/12 - 6 *t) + 2760/59 *np.sin(40/11 - 5 *t) + 1207/18 *np.sin(21/23 - 4 *t) + 8566/27 *np.sin(39/28 - 3 *t) + 12334/29 *np.sin(47/37 - 2 *t) + 15410/39 *np.sin(185/41 - t) - 596/17 *np.sin(9 *t + 3/26) - 247/28 *np.sin(14 *t + 25/21) - 458/131 *np.sin(23 *t + 21/37) - 41/36 *np.sin(28 *t + 7/8) elif curvename=='b.simpson': X = ((-5/37 *np.sin(61/42 - 8 *t) - 112/41 *np.sin(36/23 - 7 *t) - 62/37 *np.sin(14/9 - 6 *t) - 31/7 *np.sin(69/44 - 5 *t) - 275/13 *np.sin(47/30 - 3 *t) - 23/38 *np.sin(48/31 - 2 *t) + 461/10 *np.sin(t + 107/68) + 8/23 *np.sin(4 *t + 179/38) - 2345/18) *np.heaviside(71 *np.pi - t,0.5) *np.heaviside(t - 67 *np.pi,0.5) + (-41/74 *np.sin(112/75 - 17 *t) - 274/37 *np.sin(17/11 - 11 *t) - 907/30 *np.sin(36/23 - 5 *t) + 623/15 *np.sin(t + 47/30) + 684/29 *np.sin(2 *t + 212/45) + 3864/25 *np.sin(3 *t + 63/40) + 1513/78 *np.sin(4 *t + 19/12) + 269/45 *np.sin(6 *t + 14/9) + 66/25 *np.sin(7 *t + 155/33) + 121/35 *np.sin(8 *t + 27/17) + 44/13 *np.sin(9 *t + 35/22) + 71/7 *np.sin(10 *t + 30/19) + 87/40 *np.sin(12 *t + 57/37) + 61/62 *np.sin(13 *t + 47/28) + 43/65 *np.sin(14 *t + 31/20) + 54/37 *np.sin(15 *t + 127/27) + 56/27 *np.sin(16 *t + 30/19) + 11843/35) *np.heaviside(67 *np.pi - t,0.5) *np.heaviside(t - 63 *np.pi,0.5) + (-119/55 *np.sin(65/43 - 13 *t) - 78/11 *np.sin(82/55 - 12 *t) - 25/31 *np.sin(36/23 - 11 *t) - 70/9 *np.sin(31/20 - 9 *t) - 707/65 *np.sin(47/30 - 7 *t) - 953/22 *np.sin(45/29 - 5 *t) + 962/15 *np.sin(t + 113/72) + 1091/30 *np.sin(2 *t + 212/45) + 3177/26 *np.sin(3 *t + 27/17) + 1685/22 *np.sin(4 *t + 43/27) + 143/27 *np.sin(6 *t + 49/32) + 203/27 *np.sin(8 *t + 27/17) + 411/37 *np.sin(10 *t + 50/31) + 65/27 *np.sin(14 *t + 33/20) + 8/19 *np.sin(15 *t + 13/7) + 3/11 *np.sin(16 *t + 43/33) - 11597/35) *np.heaviside(63 *np.pi - t,0.5) *np.heaviside(t - 59 *np.pi,0.5) + (-1/7 *np.sin(41/81 - 30 *t) - 8/27 *np.sin(3/28 - 28 *t) - 10/23 *np.sin(3/26 - 26 *t) + 2377/13 *np.sin(t + 33/28) + 43/15 *np.sin(2 *t + 26/7) + 131/18 *np.sin(3 *t + 3/25) + 45/41 *np.sin(4 *t + 105/32) + 43/14 *np.sin(5 *t + 87/23) + 135/136 *np.sin(6 *t + 51/20) + 51/14 *np.sin(7 *t + 118/43) + 19/18 *np.sin(8 *t + 23/18) + 49/23 *np.sin(9 *t + 25/12) + 14/19 *np.sin(10 *t + 63/55) + 54/49 *np.sin(11 *t + 68/41) + 32/37 *np.sin(12 *t + 30/29) + 5/12 *np.sin(13 *t + 43/24) + 34/45 *np.sin(14 *t + 15/17) + 13/30 *np.sin(15 *t + 67/23) + 21/31 *np.sin(16 *t + 43/60) + 25/62 *np.sin(17 *t + 89/34) + 9/20 *np.sin(18 *t + 11/26) + 4/17 *np.sin(19 *t + 55/28) + 26/51 *np.sin(20 *t + 4/17) + 2/33 *np.sin(21 *t + 247/62) + 14/31 *np.sin(22 *t + 9/44) + 5/26 *np.sin(23 *t + 113/34) + 9/17 *np.sin(24 *t + 3/10) + 4/25 *np.sin(25 *t + 99/32) + 6/23 *np.sin(27 *t + 548/183) + 10/33 *np.sin(29 *t + 129/37) + 5/12 *np.sin(31 *t + 127/39) - 9719/87) *np.heaviside(59 *np.pi - t,0.5) *np.heaviside(t - 55 *np.pi,0.5) + (228/65 *np.sin(t + 116/33) + 353/40 *np.sin(2 *t + 33/19) + 107/24 *np.sin(3 *t + 58/33) + 58/21 *np.sin(4 *t + 519/130) + 19/15 *np.sin(5 *t + 45/37) + 13/12 *np.sin(6 *t + 145/38) + 43/42 *np.sin(7 *t + 25/99) + 11/19 *np.sin(8 *t + 105/44) + 203/19) *np.heaviside(55 *np.pi - t,0.5) *np.heaviside(t - 51 *np.pi,0.5) + (-23/10 *np.sin(22/17 - 4 *t) - 159/17 *np.sin(156/125 - 3 *t) + 523/112 *np.sin(t + 80/21) + 111/23 *np.sin(2 *t + 25/24) + 92/79 *np.sin(5 *t + 57/32) + 58/37 *np.sin(6 *t + 159/35) + 18/31 *np.sin(7 *t + 27/43) - 7563/28) *np.heaviside(51 *np.pi - t,0.5) *np.heaviside(t - 47 *np.pi,0.5) + (-76/17 *np.sin(42/41 - 14 *t) - 154/31 *np.sin(37/38 - 11 *t) + 10820/41 *np.sin(t + 25/34) + 1476/31 *np.sin(2 *t + 36/19) + 595/12 *np.sin(3 *t + 67/43) + 3568/67 *np.sin(4 *t + 282/77) + 974/59 *np.sin(5 *t + 40/19) + 427/18 *np.sin(6 *t + 47/25) + 454/23 *np.sin(7 *t + 20/27) + 41/40 *np.sin(8 *t + 9/2) + 139/22 *np.sin(9 *t + 99/26) + 276/37 *np.sin(10 *t + 37/29) + 113/25 *np.sin(12 *t + 61/30) + 37/29 *np.sin(13 *t + 37/31) + 51/19 *np.sin(15 *t + 127/34) + 115/72 *np.sin(16 *t + 7/38) + 162/43 *np.sin(17 *t + 67/21) + 26/33 *np.sin(18 *t + 194/45) - 3614/99) *np.heaviside(47 *np.pi - t,0.5) *np.heaviside(t - 43 *np.pi,0.5) + (347/17 *np.sin(t + 3/13) + 9951/41) *np.heaviside(43 *np.pi - t,0.5) *np.heaviside(t - 39 *np.pi,0.5) + (760/29 *np.sin(t + 23/25) - 6059/28) *np.heaviside(39 *np.pi - t,0.5) *np.heaviside(t - 35 *np.pi,0.5) + (-106/41 *np.sin(7/13 - 18 *t) - 55/38 *np.sin(13/29 - 16 *t) - 173/19 *np.sin(34/29 - 7 *t) - 484/31 *np.sin(13/16 - 5 *t) - 1193/17 *np.sin(97/83 - 2 *t) + 6885/26 *np.sin(t + 41/48) + 99/5 *np.sin(3 *t + 5/16) + 751/36 *np.sin(4 *t + 73/18) + 129/40 *np.sin(6 *t + 83/18) + 327/31 *np.sin(8 *t + 17/23) + 498/47 *np.sin(9 *t + 123/88) + 298/49 *np.sin(10 *t + 54/25) + 82/15 *np.sin(11 *t + 153/35) + 106/27 *np.sin(12 *t + 3/32) + 171/43 *np.sin(13 *t + 433/173) + 36/11 *np.sin(14 *t + 98/33) + 39/22 *np.sin(15 *t + 97/25) + 68/37 *np.sin(17 *t + 157/34) - 227/29) *np.heaviside(35 *np.pi - t,0.5) *np.heaviside(t - 31 *np.pi,0.5) + (-2/15 *np.sin(66/47 - 14 *t) - 45/23 *np.sin(5/9 - 11 *t) - 151/43 *np.sin(13/32 - 8 *t) - 31/36 *np.sin(24/19 - 7 *t) + 2121/32 *np.sin(t + 45/38) + 2085/47 *np.sin(2 *t + 299/88) + 1321/43 *np.sin(3 *t + 72/25) + 557/37 *np.sin(4 *t + 74/21) + 205/17 *np.sin(5 *t + 27/23) + 13/9 *np.sin(6 *t + 113/32) + 35/17 *np.sin(9 *t + 7/22) + 93/26 *np.sin(10 *t + 112/25) + 11/14 *np.sin(12 *t + 58/17) + 8/15 *np.sin(13 *t + 47/30) + 33/20 *np.sin(15 *t + 32/25) + 31/94 *np.sin(16 *t + 192/59) + 35/31 *np.sin(17 *t + 51/77) + 9473/34) *np.heaviside(31 *np.pi - t,0.5) *np.heaviside(t - 27 *np.pi,0.5) + (-33/29 *np.sin(27/55 - 12 *t) + 388/13 *np.sin(t + 5/13) + 2087/30 *np.sin(2 *t + 193/55) + 1311/49 *np.sin(3 *t + 133/30) + 993/41 *np.sin(4 *t + 134/31) + 175/17 *np.sin(5 *t + 73/29) + 83/23 *np.sin(6 *t + 28/33) + 9/19 *np.sin(7 *t + 73/36) + 101/32 *np.sin(8 *t + 57/28) + 51/25 *np.sin(9 *t + 106/39) + 47/28 *np.sin(10 *t + 129/47) + 17/29 *np.sin(11 *t + 33/17) + 27/22 *np.sin(13 *t + 155/86) + 108/65 *np.sin(14 *t + 8/27) + 9/16 *np.sin(15 *t + 44/13) + 11/14 *np.sin(16 *t + 3/19) + 11/23 *np.sin(17 *t + 106/23) + 9/64 *np.sin(18 *t + 97/22) - 10004/35) *np.heaviside(27 *np.pi - t,0.5) *np.heaviside(t - 23 *np.pi,0.5) + (-18/13 *np.sin(7/50 - 18 *t) - 7/5 *np.sin(1/10 - 16 *t) - 51/25 *np.sin(18/19 - 12 *t) - 219/35 *np.sin(7/30 - 10 *t) - 158/43 *np.sin(40/37 - 6 *t) - 512/25 *np.sin(13/16 - 4 *t) - 289/29 *np.sin(68/67 - 2 *t) + 18315/101 *np.sin(t + 29/18) + 664/31 *np.sin(3 *t + 61/23) + 48/11 *np.sin(5 *t + 84/67) + 489/49 *np.sin(7 *t + 11/25) + 397/33 *np.sin(8 *t + 8/19) + 73/12 *np.sin(9 *t + 9/53) + 194/41 *np.sin(11 *t + 17/14) + 2/3 *np.sin(13 *t + 149/50) + 43/29 *np.sin(14 *t + 91/31) + 61/35 *np.sin(15 *t + 131/56) + 29/37 *np.sin(17 *t + 1/19) + 49/43 *np.sin(19 *t + 65/24) + 15/19 *np.sin(20 *t + 88/21) + 11/38 *np.sin(21 *t + 217/50) + 3917/10) *np.heaviside(23 *np.pi - t,0.5) *np.heaviside(t - 19 *np.pi,0.5) + (-8/9 *np.sin(12/23 - 16 *t) - 504/53 *np.sin(8/29 - 8 *t) - 635/43 *np.sin(32/37 - 4 *t) - 307/41 *np.sin(8/27 - 3 *t) - 20292/91 *np.sin(16/19 - t) + 483/19 *np.sin(2 *t + 41/13) + 108/23 *np.sin(5 *t + 70/29) + 74/35 *np.sin(6 *t + 145/34) + 287/43 *np.sin(7 *t + 69/16) + 254/39 *np.sin(9 *t + 5/27) + 19/4 *np.sin(10 *t + 37/30) + 129/46 *np.sin(11 *t + 75/32) + 24/19 *np.sin(12 *t + 71/46) + 125/52 *np.sin(13 *t + 87/44) + 46/27 *np.sin(14 *t + 40/31) + 26/29 *np.sin(15 *t + 106/27) + 25/63 *np.sin(17 *t + 53/12) + 23/22 *np.sin(18 *t + 9/29) + 3/35 *np.sin(19 *t + 205/103) + 200/201 *np.sin(20 *t + 22/25) + 8/31 *np.sin(21 *t + 77/25) - 15195/29) *np.heaviside(19 *np.pi - t,0.5) *np.heaviside(t - 15 *np.pi,0.5) + (-15/23 *np.sin(22/23 - 35 *t) - 21/26 *np.sin(13/40 - 30 *t) - 71/64 *np.sin(16/19 - 29 *t) - 97/29 *np.sin(15/41 - 23 *t) - 57/17 *np.sin(54/35 - 16 *t) - 79/25 *np.sin(41/39 - 14 *t) - 24/11 *np.sin(3/8 - 13 *t) - 149/17 *np.sin(21/62 - 6 *t) - 613/31 *np.sin(16/17 - 2 *t) + 6033/20 *np.sin(t + 24/17) + 631/16 *np.sin(3 *t + 127/30) + 463/31 *np.sin(4 *t + 71/28) + 94/23 *np.sin(5 *t + 98/25) + 45/11 *np.sin(7 *t + 31/10) + 39/23 *np.sin(8 *t + 163/39) + 23/22 *np.sin(9 *t + 42/17) + 167/44 *np.sin(10 *t + 232/231) + 233/49 *np.sin(11 *t + 29/45) + 194/129 *np.sin(12 *t + 3/5) + 166/37 *np.sin(15 *t + 83/29) + 123/35 *np.sin(17 *t + 136/35) + 47/26 *np.sin(18 *t + 64/25) + 72/35 *np.sin(19 *t + 41/14) + 56/31 *np.sin(20 *t + 48/35) + 63/25 *np.sin(21 *t + 2/5) + 100/37 *np.sin(22 *t + 13/15) + 4/3 *np.sin(24 *t + 59/19) + 17/25 *np.sin(25 *t + 15/38) + 51/19 *np.sin(26 *t + 68/19) + 11/27 *np.sin(27 *t + 228/91) + 19/14 *np.sin(28 *t + 31/9) + 4/13 *np.sin(31 *t + 14/55) + 31/37 *np.sin(32 *t + 2/31) + 150/151 *np.sin(33 *t + 58/21) + 41/32 *np.sin(34 *t + 26/11) + 4/3 *np.sin(36 *t + 25/18) - 6956/53) *np.heaviside(15 *np.pi - t,0.5) *np.heaviside(t - 11 *np.pi,0.5) + (4337/36 *np.sin(t + 45/29) + 265/18) *np.heaviside(11 *np.pi - t,0.5) *np.heaviside(t - 7 *np.pi,0.5) + (-23/21 *np.sin(31/61 - t) - 1152/11) *np.heaviside(7 *np.pi - t,0.5) *np.heaviside(t - 3 *np.pi,0.5) + (3314/27 *np.sin(t + 30/31) + 65/31 *np.sin(2 *t + 26/23) - 1467/5) *np.heaviside(3 *np.pi - t,0.5) *np.heaviside(t + np.pi,0.5)) *np.heaviside(np.sin(t/2),0.0) Y = ((-9/23 *np.sin(38/25 - 6 *t) - 67/38 *np.sin(36/23 - 3 *t) + 31/30 *np.sin(t + 14/9) + 409/9 *np.sin(2 *t + 74/47) + 493/141 *np.sin(4 *t + 85/54) + 14/17 *np.sin(5 *t + 75/16) + 5/46 *np.sin(7 *t + 21/13) + 33/23 *np.sin(8 *t + 74/47) + 14536/41) *np.heaviside(71 *np.pi - t,0.5) *np.heaviside(t - 67 *np.pi,0.5) + (-89/29 *np.sin(59/38 - 17 *t) - 5/11 *np.sin(14/9 - 16 *t) - 99/40 *np.sin(58/37 - 15 *t) - 59/7 *np.sin(25/16 - 11 *t) - 2/35 *np.sin(8/41 - 10 *t) - 381/26 *np.sin(25/16 - 9 *t) - 67/21 *np.sin(17/11 - 8 *t) - 1706/37 *np.sin(36/23 - 5 *t) - 29/9 *np.sin(29/19 - 4 *t) - 851/29 *np.sin(58/37 - 3 *t) + 1991/30 *np.sin(t + 96/61) + 528/17 *np.sin(2 *t + 85/54) + 89/67 *np.sin(6 *t + 37/24) + 102/13 *np.sin(7 *t + 80/17) + 17/16 *np.sin(12 *t + 91/58) + 35/12 *np.sin(13 *t + 37/23) + 127/27 *np.sin(14 *t + 27/17) - 26576/29) *np.heaviside(67 *np.pi - t,0.5) *np.heaviside(t - 63 *np.pi,0.5) + (-29/14 *np.sin(47/33 - 16 *t) - 35/22 *np.sin(75/52 - 15 *t) - 236/63 *np.sin(16/11 - 14 *t) - 41/6 *np.sin(34/23 - 13 *t) - 236/29 *np.sin(46/31 - 12 *t) - 167/28 *np.sin(55/37 - 11 *t) - 259/33 *np.sin(76/51 - 10 *t) - 414/73 *np.sin(56/37 - 9 *t) - 121/28 *np.sin(17/11 - 7 *t) - 177/32 *np.sin(61/41 - 6 *t) - 1499/41 *np.sin(48/31 - 5 *t) - 647/23 *np.sin(25/16 - 3 *t) + 610/13 *np.sin(t + 30/19) + 1474/31 *np.sin(2 *t + 30/19) + 807/41 *np.sin(4 *t + 41/26) + 208/31 *np.sin(8 *t + 43/27) - 16147/17) *np.heaviside(63 *np.pi - t,0.5) *np.heaviside(t - 59 *np.pi,0.5) + (-12/41 *np.sin(1/4 - 28 *t) - 11/43 *np.sin(9/14 - 26 *t) - 17/41 *np.sin(14/13 - 24 *t) - 22/31 *np.sin(17/67 - 22 *t) - 7/10 *np.sin(64/63 - 19 *t) - 69/41 *np.sin(39/31 - 14 *t) - 86/25 *np.sin(22/41 - 12 *t) - 87/52 *np.sin(31/27 - 9 *t) - 23/15 *np.sin(13/33 - 7 *t) - 25/17 *np.sin(22/25 - 3 *t) + 159/28 *np.sin(t + 249/248) + 571/20 *np.sin(2 *t + 23/26) + 109/36 *np.sin(4 *t + 29/18) + 161/58 *np.sin(5 *t + 31/23) + 147/26 *np.sin(6 *t + 31/19) + 199/35 *np.sin(8 *t + 37/42) + 96/19 *np.sin(10 *t + 17/47) + 64/27 *np.sin(11 *t + 337/75) + 15/7 *np.sin(13 *t + 157/44) + np.sin(15 *t + 101/33) + 5/38 *np.sin(16 *t + 1/28) + 11/56 *np.sin(17 *t + 23/37) + 6/11 *np.sin(18 *t + 8/9) + 91/136 *np.sin(20 *t + 3/19) + 55/54 *np.sin(21 *t + 102/25) + 15/16 *np.sin(23 *t + 118/31) + 22/27 *np.sin(25 *t + 49/15) + 3/8 *np.sin(27 *t + 27/8) + 22/43 *np.sin(29 *t + 57/16) + 10/19 *np.sin(30 *t + 50/83) + 5/31 *np.sin(31 *t + 121/38) + 2727/23) *np.heaviside(59 *np.pi - t,0.5) *np.heaviside(t - 55 *np.pi,0.5) + (-41/31 *np.sin(23/21 - 4 *t) - 85/14 *np.sin(17/32 - t) + 407/35 *np.sin(2 *t + 75/22) + 21/10 *np.sin(3 *t + 41/14) + 53/54 *np.sin(5 *t + 54/25) + 31/61 *np.sin(6 *t + 124/27) + 5/36 *np.sin(7 *t + 3/19) + 19/31 *np.sin(8 *t + 144/31) + 10393/23) *np.heaviside(55 *np.pi - t,0.5) *np.heaviside(t - 51 *np.pi,0.5) + (-36/41 *np.sin(5/18 - 6 *t) + 83/35 *np.sin(t + 95/28) + 43/37 *np.sin(2 *t + 66/17) + 165/13 *np.sin(3 *t + 27/53) + 79/19 *np.sin(4 *t + 9/17) + 37/24 *np.sin(5 *t + 190/63) + 57/58 *np.sin(7 *t + 267/100) + 13545/31) *np.heaviside(51 *np.pi - t,0.5) *np.heaviside(t - 47 *np.pi,0.5) + (-123/47 *np.sin(19/15 - 18 *t) - 59/29 *np.sin(1/49 - 16 *t) - 213/37 *np.sin(29/22 - 13 *t) - 381/40 *np.sin(4/29 - 11 *t) - 168/29 *np.sin(6/11 - 10 *t) - 1233/44 *np.sin(3/19 - 3 *t) - 711/7 *np.sin(1/39 - 2 *t) - 5171/26 *np.sin(12/19 - t) + 2965/57 *np.sin(4 *t + 89/28) + 347/21 *np.sin(5 *t + 23/93) + 1087/69 *np.sin(6 *t + 4/31) + 760/37 *np.sin(7 *t + 172/53) + 333/19 *np.sin(8 *t + 7/13) + 325/81 *np.sin(9 *t + 96/55) + 53/17 *np.sin(12 *t + 138/49) + 73/40 *np.sin(14 *t + 92/67) + 47/31 *np.sin(15 *t + 81/19) + 7/11 *np.sin(17 *t + 29/30) - 3017/19) *np.heaviside(47 *np.pi - t,0.5) *np.heaviside(t - 43 *np.pi,0.5) + (-713/27 *np.sin(22/17 - t) - 36840/41) *np.heaviside(43 *np.pi - t,0.5) *np.heaviside(t - 39 *np.pi,0.5) + (-675/23 *np.sin(13/16 - t) - 17750/19) *np.heaviside(39 *np.pi - t,0.5) *np.heaviside(t - 35 *np.pi,0.5) + (-39/29 *np.sin(11/16 - 17 *t) - 102/37 *np.sin(8/49 - 11 *t) - 95/34 *np.sin(4/13 - 9 *t) - 71/22 *np.sin(7/12 - 8 *t) - 194/17 *np.sin(29/23 - 7 *t) - 2531/25 *np.sin(13/36 - t) + 601/19 *np.sin(2 *t + 264/61) + 232/5 *np.sin(3 *t + 53/13) + 309/40 *np.sin(4 *t + 29/10) + 266/39 *np.sin(5 *t + 3/16) + 71/95 *np.sin(6 *t + 50/37) + 281/44 *np.sin(10 *t + 33/43) + 29/15 *np.sin(12 *t + 105/29) + 39/25 *np.sin(13 *t + 109/36) + 24/11 *np.sin(14 *t + 51/38) + 19/9 *np.sin(15 *t + 38/23) + 43/29 *np.sin(16 *t + 4) + 53/74 *np.sin(18 *t + 74/25) - 45956/91) *np.heaviside(35 *np.pi - t,0.5) *np.heaviside(t - 31 *np.pi,0.5) + (-25/32 *np.sin(4/13 - 15 *t) - 40/43 *np.sin(11/19 - 13 *t) - 12727/115 *np.sin(83/84 - t) + 1762/31 *np.sin(2 *t + 66/29) + 905/78 *np.sin(3 *t + 46/25) + 209/25 *np.sin(4 *t + 104/37) + 103/27 *np.sin(5 *t + 32/17) + 121/60 *np.sin(6 *t + 143/37) + 29/7 *np.sin(7 *t + 45/13) + 41/36 *np.sin(8 *t + 271/58) + 125/62 *np.sin(9 *t + 152/33) + 118/79 *np.sin(10 *t + 56/25) + 41/24 *np.sin(11 *t + 108/25) + 22/45 *np.sin(12 *t + 116/41) + 43/35 *np.sin(14 *t + 68/19) + 1/15 *np.sin(16 *t + 26/11) + 13/43 *np.sin(17 *t + 53/25) - 29541/41) *np.heaviside(31 *np.pi - t,0.5) *np.heaviside(t - 27 *np.pi,0.5) + (-235/21 *np.sin(5/46 - 5 *t) - 133/13 *np.sin(3/29 - 4 *t) - 437/37 *np.sin(50/37 - 3 *t) - 2785/19 *np.sin(5/4 - t) + 724/17 *np.sin(2 *t + 68/29) + 211/141 *np.sin(6 *t + 83/44) + 41/14 *np.sin(7 *t + 135/32) + 83/20 *np.sin(8 *t + 135/38) + 123/62 *np.sin(9 *t + 136/33) + 304/203 *np.sin(10 *t + 166/47) + 59/44 *np.sin(11 *t + 5/29) + 25/36 *np.sin(12 *t + 102/49) + 13/12 *np.sin(13 *t + 101/41) + 23/13 *np.sin(14 *t + 73/26) + 5/32 *np.sin(15 *t + 85/27) + 41/61 *np.sin(16 *t + 56/25) + 1/7 *np.sin(17 *t + 10/17) + 7/18 *np.sin(18 *t + 134/51) - 8059/11) *np.heaviside(27 *np.pi - t,0.5) *np.heaviside(t - 23 *np.pi,0.5) + (-32/23 *np.sin(20/27 - 18 *t) - 31/20 *np.sin(19/17 - 17 *t) - 89/38 *np.sin(30/23 - 13 *t) - 529/122 *np.sin(22/15 - 10 *t) - 151/35 *np.sin(2/27 - 8 *t) - 417/28 *np.sin(43/29 - 4 *t) - 851/35 *np.sin(3/14 - 3 *t) - 13229/88 *np.sin(31/52 - t) + 425/12 *np.sin(2 *t + 37/18) + 397/30 *np.sin(5 *t + 37/17) + 299/31 *np.sin(6 *t + 122/41) + 301/38 *np.sin(7 *t + 58/35) + 240/43 *np.sin(9 *t + 118/27) + 39/28 *np.sin(11 *t + 27/34) + 82/165 *np.sin(12 *t + 58/27) + 29/26 *np.sin(14 *t + 77/27) + 47/19 *np.sin(15 *t + 7/4) + 46/17 *np.sin(16 *t + 79/22) + 46/35 *np.sin(19 *t + 43/21) + 23/28 *np.sin(20 *t + 105/31) + 27/23 *np.sin(21 *t + 184/41) - 12036/55) *np.heaviside(23 *np.pi - t,0.5) *np.heaviside(t - 19 *np.pi,0.5) + (-16/37 *np.sin(42/43 - 19 *t) - 21/23 *np.sin(37/26 - 18 *t) - 23/17 *np.sin(25/56 - 17 *t) - 46/61 *np.sin(34/45 - 16 *t) - 161/22 *np.sin(1/2 - 6 *t) - 472/43 *np.sin(15/23 - 5 *t) - 620/29 *np.sin(43/60 - 3 *t) + 2821/25 *np.sin(t + 167/39) + 2605/88 *np.sin(2 *t + 89/30) + 449/43 *np.sin(4 *t + 66/25) + 37/24 *np.sin(7 *t + 37/33) + 107/13 *np.sin(8 *t + 175/52) + 341/128 *np.sin(9 *t + 188/41) + 32/15 *np.sin(10 *t + 12/19) + 208/43 *np.sin(11 *t + 44/73) + 122/53 *np.sin(12 *t + 41/39) + 69/40 *np.sin(13 *t + 9/32) + 34/23 *np.sin(14 *t + 208/45) + 19/11 *np.sin(15 *t + 11/36) + 17/19 *np.sin(20 *t + 111/26) + 4/15 *np.sin(21 *t + 26/25) - 10055/37) *np.heaviside(19 *np.pi - t,0.5) *np.heaviside(t - 15 *np.pi,0.5) + (-59/44 *np.sin(173/172 - 36 *t) - 73/31 *np.sin(21/53 - 30 *t) - 23/11 *np.sin(13/12 - 29 *t) - 133/50 *np.sin(23/19 - 28 *t) - 125/29 *np.sin(108/77 - 24 *t) - 122/33 *np.sin(1/19 - 21 *t) - 238/79 *np.sin(4/7 - 16 *t) - 141/16 *np.sin(34/37 - 9 *t) - 45/8 *np.sin(16/27 - 7 *t) + 11594/23 *np.sin(t + 1768/589) + 1582/37 *np.sin(2 *t + 28/25) + 771/38 *np.sin(3 *t + 107/31) + 863/22 *np.sin(4 *t + 87/22) + 485/29 *np.sin(5 *t + 63/25) + 27/8 *np.sin(6 *t + 75/76) + 106/19 *np.sin(8 *t + 20/23) + 54/17 *np.sin(10 *t + 10/49) + 206/61 *np.sin(11 *t + 106/29) + 65/14 *np.sin(12 *t + 81/29) + 80/11 *np.sin(13 *t + 49/43) + 41/29 *np.sin(14 *t + 1/114) + 17/38 *np.sin(15 *t + 97/43) + 97/20 *np.sin(17 *t + 98/23) + 77/30 *np.sin(18 *t + 49/19) + 44/13 *np.sin(19 *t + 53/16) + 44/19 *np.sin(20 *t + 95/23) + 135/29 *np.sin(22 *t + 27/25) + 243/121 *np.sin(23 *t + 23/17) + 15/4 *np.sin(25 *t + 10/17) + 50/13 *np.sin(26 *t + 75/32) + 308/47 *np.sin(27 *t + 253/76) + 65/19 *np.sin(31 *t + 7/15) + 92/33 *np.sin(32 *t + 26/11) + 17/15 *np.sin(33 *t + 74/23) + 8/15 *np.sin(34 *t + 64/27) + 17/27 *np.sin(35 *t + 215/72) + 16757/30) *np.heaviside(15 *np.pi - t,0.5) *np.heaviside(t - 11 *np.pi,0.5) + (1805/16 *np.sin(t + 1/303) + 19936/43) *np.heaviside(11 *np.pi - t,0.5) *np.heaviside(t - 7 *np.pi,0.5) + (374/65 *np.sin(t + 149/47) + 11537/27) *np.heaviside(7 *np.pi - t,0.5) *np.heaviside(t - 3 *np.pi,0.5) + (-15391/135 *np.sin(35/71 - t) + 112/53 *np.sin(2 *t + 66/29) + 13507/30) *np.heaviside(3 *np.pi - t,0.5) *np.heaviside(t + np.pi,0.5)) *np.heaviside(np.sin(t/2),0.0) elif curvename=='einstein': X = ((-38/9 *np.sin(11/7 - 3 *t) + 156/5 *np.sin(t + 47/10) + 91/16 *np.sin(2 *t + 21/13) + 555/2) *theta(91 *np.pi - t) *theta(t - 87 *np.pi) + (-12/11 *np.sin(35/23 - 11 *t) + 4243/12 *np.sin(t + 11/7) + 678/11 *np.sin(2 *t + 33/7) + 401/6 *np.sin(3 *t + 47/10) + 59/3 *np.sin(4 *t + 11/7) + 238/25 *np.sin(5 *t + 47/10) + 85/11 *np.sin(6 *t + 51/11) + 57/4 *np.sin(7 *t + 61/13) + 28/29 *np.sin(8 *t + 22/5) + 52/9 *np.sin(9 *t + 14/3) + 286/57 *np.sin(10 *t + 11/7) + 19/11 *np.sin(12 *t + 32/7) + 30/11 *np.sin(13 *t + 60/13) + 95/14 *np.sin(14 *t + 89/19) + 32/7 *np.sin(15 *t + 11/7) + 43/10 *np.sin(16 *t + 65/14) + 19/7 *np.sin(17 *t + 32/7) + 13/10 *np.sin(18 *t + 77/17) + 11/9 *np.sin(19 *t + 85/19) + 1/5 *np.sin(20 *t + 4) + 3/11 *np.sin(21 *t + 28/9) + 29/11 *np.sin(22 *t + 60/13) + 80/27 *np.sin(23 *t + 50/11) + 19/12 *np.sin(24 *t + 60/13) + 1/5 *np.sin(25 *t + 12/5) + 82/13 *np.sin(26 *t + 51/11) + 3/11 *np.sin(27 *t + 19/8) + 32/9 *np.sin(28 *t + 10/7) + 41/7 *np.sin(29 *t + 22/15) + 9/11 *np.sin(30 *t + 11/8) + 2881/6) *theta(87 *np.pi - t) *theta(t - 83 *np.pi) + (-46/31 *np.sin(20/13 - 22 *t) - 22/9 *np.sin(14/9 - 6 *t) - 5/4 *np.sin(3/2 - 4 *t) + 399/5 *np.sin(t + 11/7) + 16/9 *np.sin(2 *t + 3/2) + 116/13 *np.sin(3 *t + 14/9) + 8/5 *np.sin(5 *t + 14/9) + 11/7 *np.sin(7 *t + 8/5) + 9/11 *np.sin(8 *t + 14/3) + 28/13 *np.sin(9 *t + 11/7) + 7/8 *np.sin(10 *t + 11/7) + 23/12 *np.sin(11 *t + 17/11) + 11/12 *np.sin(12 *t + 19/13) + 35/23 *np.sin(13 *t + 3/2) + 13/7 *np.sin(14 *t + 20/13) + 19/9 *np.sin(15 *t + 3/2) + 11/5 *np.sin(16 *t + 3/2) + 27/13 *np.sin(17 *t + 34/23) + 3 *np.sin(18 *t + 26/17) + 6/5 *np.sin(19 *t + 7/5) + 19/12 *np.sin(20 *t + 29/19) + 20/13 *np.sin(21 *t + 21/13) + 8/9 *np.sin(23 *t + 32/7) + 22/23 *np.sin(24 *t + 23/5) + 17/11 *np.sin(25 *t + 61/13) + 13021/30) *theta(83 *np.pi - t) *theta(t - 79 *np.pi) + (-15/31 *np.sin(11/7 - 8 *t) + 1/15 *np.sin(t + 11/6) + 55/14 *np.sin(2 *t + 19/12) + 88/13 *np.sin(3 *t + 19/12) + 17/9 *np.sin(4 *t + 8/5) + 1/18 *np.sin(5 *t + 16/9) + 4/7 *np.sin(6 *t + 21/13) + 9/8 *np.sin(7 *t + 8/5) + 8/15 *np.sin(9 *t + 8/5) + 3053/7) *theta(79 *np.pi - t) *theta(t - 75 *np.pi) + (-20/3 *np.sin(11/7 - 4 *t) - 117/8 *np.sin(11/7 - 3 *t) - 647/27 *np.sin(11/7 - 2 *t) + 559/15 *np.sin(t + 11/7) + 2/13 *np.sin(5 *t + 13/8) + 6/17 *np.sin(6 *t + 18/11) + 5/8 *np.sin(7 *t + 8/5) + 22549/41) *theta(75 *np.pi - t) *theta(t - 71 *np.pi) + (-11/9 *np.sin(17/11 - 10 *t) - 40/13 *np.sin(14/9 - 8 *t) - 254/23 *np.sin(11/7 - 4 *t) - 62/7 *np.sin(11/7 - 2 *t) + 11 *np.sin(t + 11/7) + 255/16 *np.sin(3 *t + 11/7) + 137/10 *np.sin(5 *t + 19/12) + 111/8 *np.sin(6 *t + 19/12) + 29/19 *np.sin(7 *t + 8/5) + 2/9 *np.sin(9 *t + 26/17) + 11/12 *np.sin(11 *t + 19/12) + 1/24 *np.sin(12 *t + 41/9) + 8/9 *np.sin(14 *t + 13/8) + 1313/3) *theta(71 *np.pi - t) *theta(t - 67 *np.pi) + (-5/8 *np.sin(14/9 - 8 *t) - 11/13 *np.sin(14/9 - 7 *t) - 12/5 *np.sin(11/7 - 6 *t) - 7/9 *np.sin(14/9 - 3 *t) - 272/13 *np.sin(11/7 - 2 *t) + 7/2 *np.sin(t + 11/7) + 3/4 *np.sin(4 *t + 14/9) + 7/9 *np.sin(5 *t + 11/7) + 3/13 *np.sin(9 *t + 11/7) + 4876/9) *theta(67 *np.pi - t) *theta(t - 63 *np.pi) + (-22/9 *np.sin(11/7 - t) + 177/7 *np.sin(2 *t + 11/7) + 21/10 *np.sin(3 *t + 11/7) + 11/7 *np.sin(4 *t + 11/7) + 1/14 *np.sin(5 *t + 17/10) + 66/19 *np.sin(6 *t + 11/7) + 1/22 *np.sin(7 *t + 12/7) + 20/13 *np.sin(8 *t + 11/7) + 3561/10) *theta(63 *np.pi - t) *theta(t - 59 *np.pi) + (-9/17 *np.sin(25/17 - 11 *t) - 1/2 *np.sin(25/17 - 10 *t) - 1/5 *np.sin(9/7 - 9 *t) - 1/3 *np.sin(4/3 - 8 *t) - 7/3 *np.sin(14/9 - 7 *t) - 208/25 *np.sin(14/9 - 4 *t) + 139/3 *np.sin(t + 11/7) + 186/5 *np.sin(2 *t + 11/7) + 19/6 *np.sin(3 *t + 8/5) + 19/12 *np.sin(5 *t + 8/5) + 3/13 *np.sin(6 *t + 7/4) + 2/5 *np.sin(12 *t + 13/8) + 1/9 *np.sin(13 *t + 65/14) + 6/13 *np.sin(14 *t + 18/11) + 1/8 *np.sin(15 *t + 5/3) + 1/8 *np.sin(16 *t + 7/4) + 1/18 *np.sin(17 *t + 24/11) + 1737/4) *theta(59 *np.pi - t) *theta(t - 55 *np.pi) + (-6/13 *np.sin(23/15 - 21 *t) - 3/10 *np.sin(10/7 - 20 *t) - 7/8 *np.sin(26/17 - 19 *t) - 1/4 *np.sin(19/13 - 18 *t) - 11/17 *np.sin(17/11 - 17 *t) - 1/8 *np.sin(11/9 - 16 *t) - 7/8 *np.sin(17/11 - 15 *t) - 38/39 *np.sin(11/7 - 13 *t) - 57/10 *np.sin(14/9 - 7 *t) - 1/7 *np.sin(3/5 - 6 *t) - 201/10 *np.sin(14/9 - 5 *t) - 28/11 *np.sin(17/11 - 4 *t) - 303/10 *np.sin(14/9 - 3 *t) + 1084/9 *np.sin(t + 11/7) + 39/7 *np.sin(2 *t + 14/9) + 23/14 *np.sin(8 *t + 14/9) + 22/23 *np.sin(9 *t + 47/10) + 8/13 *np.sin(10 *t + 11/7) + 1/8 *np.sin(11 *t + 22/13) + 10/19 *np.sin(12 *t + 11/7) + 9/13 *np.sin(14 *t + 21/13) + 1/8 *np.sin(22 *t + 11/7) + 1319/3) *theta(55 *np.pi - t) *theta(t - 51 *np.pi) + (-3/2 *np.sin(11/7 - 17 *t) - 9/8 *np.sin(14/9 - 15 *t) - 12/7 *np.sin(14/9 - 14 *t) - 8/7 *np.sin(14/9 - 12 *t) - 6/19 *np.sin(3/2 - 11 *t) - 296/11 *np.sin(11/7 - 5 *t) - 163/25 *np.sin(11/7 - 4 *t) - 721/20 *np.sin(11/7 - 3 *t) - 85/4 *np.sin(11/7 - 2 *t) + 1353/7 *np.sin(t + 11/7) + 31/11 *np.sin(6 *t + 8/5) + 113/10 *np.sin(7 *t + 33/7) + 27/7 *np.sin(8 *t + 14/9) + 23/8 *np.sin(9 *t + 33/7) + 7/6 *np.sin(10 *t + 13/8) + 5/12 *np.sin(13 *t + 37/8) + 2/3 *np.sin(16 *t + 51/11) + 3/8 *np.sin(18 *t + 8/5) + 7126/15) *theta(51 *np.pi - t) *theta(t - 47 *np.pi) + (-2/9 *np.sin(1/3 - 4 *t) + 791/5 *np.sin(t + 11/7) + 10/19 *np.sin(2 *t + 9/14) + 118/7 *np.sin(3 *t + 14/9) + 21/4 *np.sin(5 *t + 11/7) + 1/9 *np.sin(6 *t + 117/58) + 30/11 *np.sin(7 *t + 14/9) + 5/13 *np.sin(8 *t + 17/14) + 7/4 *np.sin(9 *t + 28/19) + 3/14 *np.sin(10 *t + 15/16) + 12/13 *np.sin(11 *t + 19/12) + 1/15 *np.sin(12 *t + 43/13) + 11/16 *np.sin(13 *t + 13/8) + 2251/5) *theta(47 *np.pi - t) *theta(t - 43 *np.pi) + (3724/25 *np.sin(t + 11/7) + 1/3 *np.sin(2 *t + 16/9) + 266/17 *np.sin(3 *t + 11/7) + 10/13 *np.sin(4 *t + 19/11) + 34/7 *np.sin(5 *t + 19/12) + 5/12 *np.sin(6 *t + 5/3) + 20/11 *np.sin(7 *t + 8/5) + 1/5 *np.sin(8 *t + 11/7) + 7/5 *np.sin(9 *t + 19/12) + 2/7 *np.sin(10 *t + 5/3) + 7/8 *np.sin(11 *t + 14/9) + 1/51 *np.sin(12 *t + 47/16) + 7/9 *np.sin(13 *t + 13/8) + 1/10 *np.sin(14 *t + 50/11) + 12403/28) *theta(43 *np.pi - t) *theta(t - 39 *np.pi) + (-4/7 *np.sin(5/9 - 19 *t) + 4341/11 *np.sin(t + 17/11) + 595/6 *np.sin(2 *t + 14/3) + 1286/17 *np.sin(3 *t + 37/8) + 314/9 *np.sin(4 *t + 23/15) + 121/3 *np.sin(5 *t + 37/8) + 222/17 *np.sin(6 *t + 21/5) + 103/9 *np.sin(7 *t + 23/5) + 29/5 *np.sin(8 *t + 25/6) + 127/9 *np.sin(9 *t + 49/11) + 11/6 *np.sin(10 *t + 37/19) + 23/3 *np.sin(11 *t + 23/5) + 77/13 *np.sin(12 *t + 23/12) + 97/7 *np.sin(13 *t + 41/9) + 29/7 *np.sin(14 *t + 17/8) + 39/7 *np.sin(15 *t + 49/11) + 5/8 *np.sin(16 *t + 19/11) + 5/11 *np.sin(17 *t + 17/9) + 2/3 *np.sin(18 *t + 27/7) + 19/13 *np.sin(20 *t + 37/12) + 84/13 *np.sin(21 *t + 25/6) + 11/23 *np.sin(22 *t + 41/14) + 45/13 *np.sin(23 *t + 31/32) + 3/14 *np.sin(24 *t + 41/20) + 49/13 *np.sin(25 *t + 41/10) + 16/11 *np.sin(26 *t + 17/11) + 12/7 *np.sin(27 *t + 22/5) + 37/13 *np.sin(28 *t + 48/13) + 4/3 *np.sin(29 *t + 3) + 31/11 *np.sin(30 *t + 3/10) + 79/15 *np.sin(31 *t + 10/11) + 10753/21) *theta(39 *np.pi - t) *theta(t - 35 *np.pi) + (-16/9 *np.sin(13/9 - 8 *t) - 108/19 *np.sin(8/11 - 6 *t) + 17/13 *np.sin(t + 8/7) + 7/3 *np.sin(2 *t + 21/10) + 24/7 *np.sin(3 *t + 20/9) + 26/7 *np.sin(4 *t + 32/7) + 26/11 *np.sin(5 *t + 11/4) + 105/19 *np.sin(7 *t + 30/7) + 6/7 *np.sin(9 *t + 5/11) + 23/15 *np.sin(10 *t + 7/5) + 11/6 *np.sin(11 *t + 11/3) + 12822/23) *theta(35 *np.pi - t) *theta(t - 31 *np.pi) + (-5/8 *np.sin(11/12 - 10 *t) - 64/13 *np.sin(13/14 - 6 *t) + 7/5 *np.sin(t + 45/11) + 74/21 *np.sin(2 *t + 1/7) + 52/15 *np.sin(3 *t + 39/10) + 5/8 *np.sin(4 *t + 3/5) + 17/11 *np.sin(5 *t + 7/6) + 39/8 *np.sin(7 *t + 51/13) + 15/8 *np.sin(8 *t + 29/8) + 16/9 *np.sin(9 *t + 14/3) + 97/48 *np.sin(11 *t + 5/9) + 3401/10) *theta(31 *np.pi - t) *theta(t - 27 *np.pi) + (-12/25 *np.sin(17/13 - 6 *t) - 7/11 *np.sin(4/7 - 4 *t) - 14/27 *np.sin(3/13 - 2 *t) + 351/10 *np.sin(t + 11/8) + 17/6 *np.sin(3 *t + 28/27) + 9/8 *np.sin(5 *t + 10/13) + 3921/7) *theta(27 *np.pi - t) *theta(t - 23 *np.pi) + (431/8 *np.sin(t + 4/5) + 199/25 *np.sin(2 *t + 40/9) + 2328/7) *theta(23 *np.pi - t) *theta(t - 19 *np.pi) + (-2/3 *np.sin(5/4 - 9 *t) - 11/9 *np.sin(4/3 - 5 *t) - 74/21 *np.sin(1/13 - 4 *t) + 107/6 *np.sin(t + 8/17) + 73/10 *np.sin(2 *t + 12/11) + 53/12 *np.sin(3 *t + 48/11) + 4/9 *np.sin(6 *t + 31/13) + 4/11 *np.sin(7 *t + 5/13) + 5/14 *np.sin(8 *t + 127/42) + 5/16 *np.sin(10 *t + 17/9) + 2/5 *np.sin(11 *t + 29/7) + 2378/13) *theta(19 *np.pi - t) *theta(t - 15 *np.pi) + (194/13 *np.sin(t + 51/14) + 93/23 *np.sin(2 *t + 43/12) + 13/8 *np.sin(3 *t + 57/17) + 9/5 *np.sin(4 *t + 32/13) + 14050/21) *theta(15 *np.pi - t) *theta(t - 11 *np.pi) + (-19/18 *np.sin(1/11 - 16 *t) - 8/11 *np.sin(1/6 - 14 *t) - 13/11 *np.sin(1 - 7 *t) - 9/8 *np.sin(7/11 - 5 *t) - 148/9 *np.sin(1/7 - 2 *t) + 19/6 *np.sin(t + 37/8) + 625/11 *np.sin(3 *t + 8/5) + 241/24 *np.sin(4 *t + 1/6) + 16/17 *np.sin(6 *t + 7/5) + 95/47 *np.sin(8 *t + 1/4) + 20/9 *np.sin(9 *t + 12/7) + 11/5 *np.sin(10 *t + 1/4) + 3/7 *np.sin(11 *t + 2/3) + 9/19 *np.sin(12 *t + 28/9) + 3/5 *np.sin(13 *t + 25/6) + 2/11 *np.sin(15 *t + 13/9) + 1/3 *np.sin(17 *t + 1/6) + 3925/7) *theta(11 *np.pi - t) *theta(t - 7 *np.pi) + (-31/12 *np.sin(11/12 - 6 *t) - 244/9 *np.sin(15/11 - 4 *t) - 186/5 *np.sin(7/6 - 2 *t) + 911/26 *np.sin(t + 74/21) + 317/7 *np.sin(3 *t + 1/3) + 28/9 *np.sin(5 *t + 52/15) + 33/17 *np.sin(7 *t + 12/5) + 7/10 *np.sin(8 *t + 13/7) + 6/7 *np.sin(9 *t + 9/5) + 6/7 *np.sin(10 *t + 11/4) + 13/5 *np.sin(11 *t + 4/7) + 2721/8) *theta(7 *np.pi - t) *theta(t - 3 *np.pi) + (-10/7 *np.sin(14/9 - 12 *t) - 11/7 *np.sin(7/9 - 11 *t) - 51/19 *np.sin(3/2 - 4 *t) - 89/4 *np.sin(18/13 - 3 *t) - 81/10 *np.sin(12/25 - 2 *t) + 2029/8 *np.sin(t + 3/2) + 3 *np.sin(5 *t + 3/5) + 23/15 *np.sin(6 *t + 29/10) + 74/15 *np.sin(7 *t + 51/25) + 10/11 *np.sin(8 *t + 32/21) + 13/6 *np.sin(9 *t + 8/5) + 2/7 *np.sin(10 *t + 16/7) + 4407/10) *theta(3 *np.pi - t) *theta(t +np.pi)) *theta(np.sin(t/2)) Y = ((41/2 *np.sin(t + 61/13) + 163/18 *np.sin(2 *t + 14/3) + 1/2 *np.sin(3 *t + 41/9) + 3802/5) *theta(91 *np.pi - t) *theta(t - 87 *np.pi) + (-12/7 *np.sin(7/5 - 17 *t) - 41/11 *np.sin(11/7 - 9 *t) - 3/7 *np.sin(11/8 - 4 *t) + 1175/14 *np.sin(t + 47/10) + 9961/40 *np.sin(2 *t + 33/7) + 555/8 *np.sin(3 *t + 11/7) + 39/5 *np.sin(5 *t + 14/9) + 11/5 *np.sin(6 *t + 3/2) + 25/2 *np.sin(7 *t + 47/10) + 155/12 *np.sin(8 *t + 14/9) + 33/10 *np.sin(10 *t + 19/12) + 14/5 *np.sin(11 *t + 51/11) + 64/7 *np.sin(12 *t + 14/3) + 45/7 *np.sin(13 *t + 11/7) + 1/14 *np.sin(14 *t + 49/13) + 1/2 *np.sin(15 *t + 16/13) + 76/25 *np.sin(16 *t + 19/12) + 23/5 *np.sin(18 *t + 26/17) + 191/38 *np.sin(19 *t + 47/10) + 47/13 *np.sin(20 *t + 23/15) + 62/9 *np.sin(21 *t + 33/7) + 31/9 *np.sin(22 *t + 37/25) + 31/4 *np.sin(23 *t + 16/11) + 18/7 *np.sin(24 *t + 4/3) + 91/15 *np.sin(25 *t + 3/2) + 29/7 *np.sin(26 *t + 14/3) + 49/25 *np.sin(27 *t + 47/10) + 9/4 *np.sin(28 *t + 23/5) + 57/56 *np.sin(29 *t + 6/5) + 83/10 *np.sin(30 *t + 16/11) + 18532/29) *theta(87 *np.pi - t) *theta(t - 83 *np.pi) + (-9/7 *np.sin(4/3 - 25 *t) - 106/11 *np.sin(16/11 - 22 *t) - 11/3 *np.sin(17/11 - 11 *t) - 1/17 *np.sin(1/16 - 9 *t) - 2/9 *np.sin(3/2 - 8 *t) - 2/9 *np.sin(11/9 - 6 *t) + 38/39 *np.sin(t + 14/3) + 9/5 *np.sin(2 *t + 61/13) + 19/7 *np.sin(3 *t + 8/5) + 22/5 *np.sin(4 *t + 33/7) + 8/11 *np.sin(5 *t + 3/2) + 95/94 *np.sin(7 *t + 14/9) + 25/13 *np.sin(10 *t + 13/8) + 3/5 *np.sin(12 *t + 14/3) + 2/11 *np.sin(13 *t + 17/4) + 35/11 *np.sin(14 *t + 14/3) + 17/5 *np.sin(15 *t + 51/11) + 84/13 *np.sin(16 *t + 89/19) + 51/8 *np.sin(17 *t + 51/11) + 5/8 *np.sin(18 *t + 17/5) + 35/6 *np.sin(19 *t + 61/13) + 11/9 *np.sin(20 *t + 9/2) + 21/13 *np.sin(21 *t + 27/16) + 77/12 *np.sin(23 *t + 8/5) + 151/14 *np.sin(24 *t + 21/13) + 2152/7) *theta(83 *np.pi - t) *theta(t - 79 *np.pi) + (-14/11 *np.sin(20/13 - 7 *t) - 47/8 *np.sin(14/9 - 3 *t) - 388/7 *np.sin(11/7 - t) + 18/11 *np.sin(2 *t + 3/2) + 4/3 *np.sin(4 *t + 19/12) + 19/14 *np.sin(5 *t + 47/10) + 3/11 *np.sin(6 *t + 25/17) + 1/24 *np.sin(8 *t + 9/14) + 1/3 *np.sin(9 *t + 47/10) + 5435/13) *theta(79 *np.pi - t) *theta(t - 75 *np.pi) + (-5/2 *np.sin(14/9 - 5 *t) - 42/11 *np.sin(11/7 - 3 *t) - 237/19 *np.sin(11/7 - t) + 86/3 *np.sin(2 *t + 11/7) + 14/15 *np.sin(4 *t + 11/7) + 17/8 *np.sin(6 *t + 11/7) + 15/16 *np.sin(7 *t + 8/5) + 4683/10) *theta(75 *np.pi - t) *theta(t - 71 *np.pi) + (-5/7 *np.sin(14/9 - 13 *t) - 11/16 *np.sin(14/9 - 9 *t) - 13/6 *np.sin(11/7 - 5 *t) - 2/7 *np.sin(20/13 - 4 *t) - np.sin(11/7 - 3 *t) - 341/34 *np.sin(11/7 - t) + 5/3 *np.sin(2 *t + 11/7) + 19/8 *np.sin(6 *t + 19/12) + 1/11 *np.sin(7 *t + 55/12) + 7/6 *np.sin(8 *t + 19/12) + 3/8 *np.sin(10 *t + 11/7) + 1/10 *np.sin(11 *t + 5/3) + 1/2 *np.sin(12 *t + 19/12) + 7/10 *np.sin(14 *t + 8/5) + 469/2) *theta(71 *np.pi - t) *theta(t - 67 *np.pi) + (-3/10 *np.sin(14/9 - 8 *t) + 16/11 *np.sin(t + 75/16) + 63/2 *np.sin(2 *t + 11/7) + 5/7 *np.sin(3 *t + 8/5) + 2/3 *np.sin(4 *t + 13/8) + 1/33 *np.sin(5 *t + 9/2) + 23/7 *np.sin(6 *t + 11/7) + 1/29 *np.sin(7 *t + 14/3) + 1/5 *np.sin(9 *t + 61/13) + 3265/9) *theta(67 *np.pi - t) *theta(t - 63 *np.pi) + (-16/13 *np.sin(11/7 - 4 *t) - 59/12 *np.sin(11/7 - t) + 183/5 *np.sin(2 *t + 11/7) + 5/4 *np.sin(3 *t + 14/9) + 8/7 *np.sin(5 *t + 47/10) + 80/27 *np.sin(6 *t + 11/7) + 14/13 *np.sin(7 *t + 19/12) + 20/19 *np.sin(8 *t + 33/7) + 10934/29) *theta(63 *np.pi - t) *theta(t - 59 *np.pi) + (-7/9 *np.sin(29/19 - 15 *t) - 121/60 *np.sin(17/11 - 5 *t) - 742/11 *np.sin(11/7 - t) + 494/11 *np.sin(2 *t + 19/12) + 74/15 *np.sin(3 *t + 19/12) + 78/7 *np.sin(4 *t + 21/13) + 47/10 *np.sin(6 *t + 13/8) + 35/17 *np.sin(7 *t + 27/16) + 17/7 *np.sin(8 *t + 19/12) + 5/16 *np.sin(9 *t + 19/8) + 22/9 *np.sin(10 *t + 11/7) + 2/11 *np.sin(11 *t + 39/10) + 10/11 *np.sin(12 *t + 19/12) + 5/13 *np.sin(13 *t + 12/7) + 3/7 *np.sin(14 *t + 23/14) + 1/4 *np.sin(16 *t + 18/11) + 1/12 *np.sin(17 *t + 15/7) + 4470/11) *theta(59 *np.pi - t) *theta(t - 55 *np.pi) + (-2/9 *np.sin(17/11 - 21 *t) - 9/7 *np.sin(3/2 - 18 *t) - 3/10 *np.sin(22/15 - 17 *t) - 23/7 *np.sin(14/9 - 8 *t) + 18/11 *np.sin(t + 8/5) + 155/4 *np.sin(2 *t + 11/7) + 9/7 *np.sin(3 *t + 28/17) + 173/10 *np.sin(4 *t + 11/7) + 14/13 *np.sin(5 *t + 75/16) + 22/9 *np.sin(6 *t + 8/5) + 1/7 *np.sin(7 *t + 16/9) + 5/3 *np.sin(9 *t + 8/5) + 9/8 *np.sin(10 *t + 8/5) + 16/9 *np.sin(11 *t + 8/5) + 8/3 *np.sin(12 *t + 8/5) + 3/13 *np.sin(13 *t + 14/3) + 29/30 *np.sin(14 *t + 11/7) + 1/6 *np.sin(15 *t + 16/9) + 7/8 *np.sin(16 *t + 28/17) + 5/16 *np.sin(19 *t + 18/11) + 11/12 *np.sin(20 *t + 18/11) + 1/7 *np.sin(22 *t + 9/7) + 3262/11) *theta(55 *np.pi - t) *theta(t - 51 *np.pi) + (-7/8 *np.sin(17/11 - 18 *t) - 7/6 *np.sin(17/11 - 17 *t) - 3/10 *np.sin(23/15 - 15 *t) - 17/10 *np.sin(11/7 - 10 *t) - 24/7 *np.sin(14/9 - 9 *t) - 24/25 *np.sin(14/9 - 8 *t) - 40/11 *np.sin(11/7 - 7 *t) + 19/10 *np.sin(t + 33/7) + 39/7 *np.sin(2 *t + 11/7) + 162/19 *np.sin(3 *t + 11/7) + 123/8 *np.sin(4 *t + 11/7) + 33/7 *np.sin(5 *t + 11/7) + 77/9 *np.sin(6 *t + 11/7) + 21/22 *np.sin(11 *t + 8/5) + 9/17 *np.sin(12 *t + 21/13) + 31/12 *np.sin(13 *t + 19/12) + 1/20 *np.sin(14 *t + 23/5) + 5/14 *np.sin(16 *t + 8/5) + 16814/23) *theta(51 *np.pi - t) *theta(t - 47 *np.pi) + (-102/11 *np.sin(11/7 - t) + 29/7 *np.sin(2 *t + 33/7) + 27/10 *np.sin(3 *t + 19/12) + 17/7 *np.sin(4 *t + 47/10) + 2/11 *np.sin(5 *t + 13/7) + 37/14 *np.sin(6 *t + 47/10) + 1/13 *np.sin(7 *t + 85/21) + 51/26 *np.sin(8 *t + 47/10) + 5/6 *np.sin(9 *t + 8/5) + 3/5 *np.sin(10 *t + 47/10) + 8/13 *np.sin(11 *t + 8/5) + 9/13 *np.sin(12 *t + 47/10) + 1/10 *np.sin(13 *t + 53/12) + 9028/13) *theta(47 *np.pi - t) *theta(t - 43 *np.pi) + (-1/2 *np.sin(17/11 - 14 *t) - 15/11 *np.sin(14/9 - 10 *t) - 29/11 *np.sin(14/9 - 8 *t) - 29/9 *np.sin(14/9 - 6 *t) - 1/3 *np.sin(13/9 - 5 *t) - 108/13 *np.sin(14/9 - 4 *t) - 12/7 *np.sin(14/9 - t) + 4/13 *np.sin(2 *t + 8/5) + 15/11 *np.sin(3 *t + 11/7) + 7/6 *np.sin(7 *t + 11/7) + 1/15 *np.sin(9 *t + 5/4) + 1/9 *np.sin(11 *t + 16/11) + 1/10 *np.sin(12 *t + 12/7) + 3/8 *np.sin(13 *t + 8/5) + 5872/9) *theta(43 *np.pi - t) *theta(t - 39 *np.pi) + (-6/7 *np.sin(38/25 - 30 *t) - 6/5 *np.sin(1/21 - 28 *t) - 13/8 *np.sin(7/9 - 18 *t) + 275/3 *np.sin(t + 23/5) + 3929/11 *np.sin(2 *t + 14/3) + 219/4 *np.sin(3 *t + 27/16) + 421/11 *np.sin(4 *t + 47/10) + 101/6 *np.sin(5 *t + 26/17) + 242/9 *np.sin(6 *t + 4/3) + 153/13 *np.sin(7 *t + 1) + 73/6 *np.sin(8 *t + 5/4) + 65/9 *np.sin(9 *t + 13/11) + 47/14 *np.sin(10 *t + 9/7) + 51/11 *np.sin(11 *t + 25/6) + 25/7 *np.sin(12 *t + 17/13) + 13/2 *np.sin(13 *t + 9/8) + 40/17 *np.sin(14 *t + 16/17) + 36/7 *np.sin(15 *t + 46/47) + 2 *np.sin(16 *t + 2/7) + 52/21 *np.sin(17 *t + 10/7) + 55/12 *np.sin(19 *t + 6/5) + 17/8 *np.sin(20 *t + 1/3) + 17/6 *np.sin(21 *t + 58/57) + 37/12 *np.sin(22 *t + 35/8) + 3/4 *np.sin(23 *t + 12/13) + 28/13 *np.sin(24 *t + 4/5) + 37/19 *np.sin(25 *t + 19/5) + 7/10 *np.sin(26 *t + 55/13) + 89/14 *np.sin(27 *t + 7/8) + 15/7 *np.sin(29 *t + 23/6) + 7/11 *np.sin(31 *t + 11/14) + 8933/13) *theta(39 *np.pi - t) *theta(t - 35 *np.pi) + (-17/9 *np.sin(9/14 - 11 *t) - 4/3 *np.sin(1/5 - 8 *t) - 29/6 *np.sin(3/8 - 7 *t) + 13/8 *np.sin(t + 11/6) + 6/5 *np.sin(2 *t + 30/7) + 8/7 *np.sin(3 *t + 31/11) + 13/6 *np.sin(4 *t + 1/11) + 4/5 *np.sin(5 *t + 31/7) + 31/9 *np.sin(6 *t + 8/11) + 1/3 *np.sin(9 *t + 39/20) + 9/5 *np.sin(10 *t + 13/4) + 7555/14) *theta(35 *np.pi - t) *theta(t - 31 *np.pi) + (-11/10 *np.sin(10/9 - 8 *t) - 9/2 *np.sin(2/5 - 7 *t) - 18/11 *np.sin(10/11 - 3 *t) + 17/9 *np.sin(t + 32/7) + 6/5 *np.sin(2 *t + 38/13) + 19/14 *np.sin(4 *t + 28/9) + 13/9 *np.sin(5 *t + 3) + 15/4 *np.sin(6 *t + 3/4) + 60/17 *np.sin(9 *t + 1/14) + 10/9 *np.sin(10 *t + 5/4) + 13/7 *np.sin(11 *t + 30/13) + 9899/18) *theta(31 *np.pi - t) *theta(t - 27 *np.pi) + (-2/11 *np.sin(2/9 - 5 *t) + 110/7 *np.sin(t + 35/12) + 16/9 *np.sin(2 *t + 68/15) + 3/14 *np.sin(3 *t + 36/13) + 1/2 *np.sin(4 *t + 7/2) + 1/7 *np.sin(6 *t + 45/13) + 2682/5) *theta(27 *np.pi - t) *theta(t - 23 *np.pi) + (157/9 *np.sin(t + 69/34) + 19/3 *np.sin(2 *t + 20/7) + 2169/4) *theta(23 *np.pi - t) *theta(t - 19 *np.pi) + (-3/2 *np.sin(3/13 - 7 *t) - 13/4 *np.sin(11/12 - 4 *t) - 131/7 *np.sin(5/4 - 2 *t) + 370/7 *np.sin(t + 74/17) + 31/3 *np.sin(3 *t + 47/16) + 11/4 *np.sin(5 *t + 50/11) + 43/11 *np.sin(6 *t + 19/7) + 23/14 *np.sin(8 *t + 33/10) + 3/5 *np.sin(9 *t + 21/11) + 1/10 *np.sin(10 *t + 1/16) + 1/3 *np.sin(11 *t + 62/25) + 5541/11) *theta(19 *np.pi - t) *theta(t - 15 *np.pi) + (171/4 *np.sin(t + 37/8) + 7/9 *np.sin(2 *t + 18/13) + 41/10 *np.sin(3 *t + 40/9) + 6/11 *np.sin(4 *t + 15/11) + 5012/11) *theta(15 *np.pi - t) *theta(t - 11 *np.pi) + (-12/13 *np.sin(7/5 - 12 *t) - 13/8 *np.sin(13/11 - 10 *t) + 43/12 *np.sin(t + 7/9) + 279/35 *np.sin(2 *t + 9/2) + 201/14 *np.sin(3 *t + 2/9) + 23/9 *np.sin(4 *t + 8/7) + 64/9 *np.sin(5 *t + 14/5) + 83/6 *np.sin(6 *t + 14/3) + 103/17 *np.sin(7 *t + 13/4) + 36/13 *np.sin(8 *t + 46/11) + 22/7 *np.sin(9 *t + 2/7) + 8/9 *np.sin(11 *t + 11/4) + 20/11 *np.sin(13 *t + 74/25) + 5/7 *np.sin(14 *t + 42/13) + 7/9 *np.sin(15 *t + 4/7) + 9/11 *np.sin(16 *t + 17/4) + 7/12 *np.sin(17 *t + 36/11) + 3437/6) *theta(11 *np.pi - t) *theta(t - 7 *np.pi) + (-22/7 *np.sin(7/9 - 9 *t) - 36/7 *np.sin(1 - 5 *t) - 181/26 *np.sin(6/5 - 3 *t) + 28/9 *np.sin(t + 5/6) + 131/22 *np.sin(2 *t + 26/7) + 127/13 *np.sin(4 *t + 23/5) + 21/4 *np.sin(6 *t + 1/10) + 40/3 *np.sin(7 *t + 22/23) + 88/13 *np.sin(8 *t + 23/5) + 115/38 *np.sin(10 *t + 3/7) + 11/9 *np.sin(11 *t + 11/8) + 8493/14) *theta(7 *np.pi - t) *theta(t - 3 *np.pi) + (-8/7 *np.sin(16/13 - 10 *t) - 23/10 *np.sin(4/3 - 7 *t) - 3961/12 *np.sin(1/19 - t) + 55/3 *np.sin(2 *t + 13/11) + 9/17 *np.sin(3 *t + 31/13) + 81/7 *np.sin(4 *t + 9/2) + 113/17 *np.sin(5 *t + 13/4) + 40/9 *np.sin(6 *t + 12/11) + 24/23 *np.sin(8 *t + 53/21) + 19/8 *np.sin(9 *t + 3/7) + 3/13 *np.sin(11 *t + 18/5) + 45/44 *np.sin(12 *t + 5/7) + 6798/13) *theta(3 *np.pi - t) *theta(t +np.pi)) *theta(np.sin(t/2)) else : print("error : there is not such curve name") quit() Target = np.array([X,Y]).T if jump==1: Jcheck0=np.zeros(num) for i in range(num-1) : Jcheck0[i]=np .count_nonzero(Target[i+1:] == Target[i]) Jcheck1= Target[:] != [[0,0]] Jcheck = np.logical_and(Jcheck0[:]==0,Jcheck1[:,0]) Target=Target[Jcheck] t=np.linspace(0,dom,Jcheck.sum(),endpoint=False) print(Jcheck.sum()) return Target,t def setPVinit(setting) : global Pinit, Vinit global Xbmean, Vimean if setting==0: Pinitlen=int((np.max(Z)-np.min(Z))) # Pinitlen=20 coeff=0.25 # coeff=0.5 # coeff=1.25 P_range=Pinitlen*coeff print("P_range = %f" %P_range) Pinit=np.random.rand(N,2)*P_range-P_range/2 Pinit-=np.array(np.mean(Pinit[:],axis=0)) Pinit+=np.array(np.mean(Z[:],axis=0)) v_range=50 v_s=np.random.randint(-10,10,size=2) v_s=np.array([0,0]) print("v_s = %.1f,%.1f" %(v_s[0],v_s[1])) Vinit=(np.random.rand(N,2)*v_range)-v_range/2 + v_s #np.array끼리 그냥 곱하면 component 사이의 곱 Vimean=np.array(np.mean(Vinit[:],axis=0)) Vinit-=Vimean else : print(os.getcwd()) Pinit_df=pd.read_csv('./Pinit_%s.csv' %set_name,delimiter='\t') Vinit_df=pd.read_csv('./Vinit_%s.csv' %set_name,delimiter='\t') Pinit=Pinit_df.to_numpy() Vinit=Vinit_df.to_numpy() print(Pinit.shape) Xbimean=np.array(np.mean(Pinit[:]-Z[:],axis=0)) print("\nbarX_i mean={}".format(Xbimean)) Vimean=np.array(np.mean(Vinit[:],axis=0)) print("\nVimean={}".format(Vimean)) def set_dBcum(setting) : global dBcum dBcum=np.zeros((Trial+1,2,T)) if setting == 0 : dBcum[1:,0,:]=np.random.normal(0,np.sqrt(h),(Trial,T)) dBcum[1:,1,:]=np.random.randint(0,1,(Trial,T))*2-1 else : dBcum_df=pd.read_csv('./dBcum.csv',delimiter='\t') dBcum_np=dBcum_df.to_numpy() dBcum=dBcum_np.reshape(-1,2,T) def settings(set_name) : global N global alpha, beta, psLB, phLB global K, M, L, T global curvetype,nettype, h global PVinitset, dBset if set_name=='ein' : ##ein set N=500 alpha=0.25 beta=alpha psLB=0.3 phLB=0.1 K=0.5 M=7 L=0.00001 #L=sigma T=400 #T : number of steps for solving the DE T=180 curvetype=3 # nettype=[0,0,0] nettype=[3,1,0] nettype=[4,4,0] # nettype=[4,3,0] PVinitset=1 #whether making or loading the initial data of P,V h=0.025/2 #h=\Delta t ~ dt dBset=0 elif set_name=='pi' : ##pi set N=30 alpha=0.25 beta=alpha psLB=0.31 phLB=0.1 K=5 M=7 L=0.001 #L=sigma T=400 #T : number of steps for solving the DE T=1400 curvetype=1 # nettype=[0,0,0] nettype=[3,1,0] # nettype=[4,3,0] PVinitset=1 #whether making or loading the initial data of P,V h=0.025 #h=\Delta t ~ dt dBset=0 # cut=100 def make_variables(): global P, V global Pdiff, Vnrmi, Xbave, Xbnrmi, phEi P=np.array([Pinit]) V=np.array([Vinit]) print(P[0]) print(V[0]) print(Vimean) ## Vnrm(t) = Vnrm = sum_i |v_t^i|^2 s=np.power(Vinit[:,0],2)+np.power(Vinit[:,1],2) Vnrmi=np.sum(s)-N*np.sum(np.power(Vimean,2)) ## Xbnrm(t) = sum_i |x*_i-x*_ave|^2 = \sum_{i} |\bar{x}_t^i-\bar{x}_t^ave|^2 Xbave=np.sum(Pinit,axis=0)-np.sum(Z,axis=0) Xbnrmi=np.sum(np.power(Pinit[:,0]-Z[:,0]-Xbave[0],2)+np.power(Pinit[:,1]-Z[:,1]-Xbave[1],2)) ##phE(t)=\sum_{i,j\in\calE} \int_0^|\bar{x}_t^{ij}|^2 \phi(r)dr phEi=0 for i in range(N): J = A_ph[i,:]==1 ssq=(np.power(P[0,i,0]-Z[i,0]-P[0,:,0]+Z[:,0],2)+np.power(P[0,i,1]-Z[i,1]-P[0,:,1]+Z[:,1],2))[J] phEi+=np.sum(phiEest(ssq,beta,phLB)) phEi*=M/2 if __name__ == '__main__': version=2.00 ##inputs and settings set_name='pi' test_name='test' settings(set_name) Trial=5 cut=10 dataset=0 #whether making or loading the solutions of DE ##Setting target pattern. /curvetype #jump==1 then the "curve" is disconnected if curvetype==0: curvename='circle' domain=2*np.pi jump=0 elif curvetype==1: curvename='pi' domain=2*np.pi jump=0 elif curvetype==2: curvename='b.simpson' domain=72*np.pi jump=1 elif curvetype==3: curvename='einstein' domain=92*np.pi jump=1 Z,Domain=Curve(domain) #Set Z as given curve # A : adjacency matrix / nettype zeta=['ps','ph','b'] for ind in range(3): A=makenet(nettype[ind]) globals()['A_{}'.format(zeta[ind])]=np.copy(A) print(A_ps) ##Setting a initial data of P,V / PVinitset # P : positions, V : velocity. i.e. P=\bx, V=\bv setPVinit(PVinitset) ## Making variables : P, V, and Pdiff, Vnrm, nV, Xbnrm, phE, calH make_variables() #이렇게 계속 append 하는 방식 말고 cum 미리 array 만들어 놓는게 빠른지 함 확인 해봐야 + 공간 어떤 방식이 더 많이 확보 가능한가 #-> 속도는 큰 차이 없고 오히려 append하는게 더 빠른 것 같아서 당황 Pcum=np.array([np.zeros((T,N,2))]) Vcum=np.array([np.zeros((T,N,2))]) nVcum=np.array([np.zeros((T,N,2))]) Vnrmcum=np.array([np.zeros(T)]) phEcum=np.array([np.zeros(T)]) Xbnrmcum=np.array([np.zeros(T)]) #dBcum : saving values of dBt set_dBcum(dBset) #지금 수정하기 귀찮다고 대충 했더니 cum ndarray들은 [0]=0 이고 [1]부터 가ㅄ이들어가는 상황 ## Main part if dataset==0: for trial in range (0,Trial): P=np.zeros((T,N,2)) V=np.zeros((T,N,2)) Vnrm=np.zeros(T) Xbnrm=np.zeros(T) phE=np.zeros(T) P[0]=np.array([Pinit]) V[0]=np.array([Vinit]) Vnrm[0]=Vnrmi Xbnrm[0]=Xbnrmi phE[0]=phEi ## Solving DE for each trial for t in range(1,T): # print ("start %dth loop" %t) Pnow=np.copy(P[t-1]) Vnow=np.copy(V[t-1]) ## Stochastic Runge Kutta. ## calculating P[t], V[t] ## P,V_t = P,V_t-1 + (K_1 /2 +K_2 /2) ## K_1 = h * csmpf (P,V_t-1)+ (dBt-1-S*sqrt(h)) * Br(P,V_t-1) ## K_2 = h * csmpf (P,V_t-1 + K_1)+ (dBt-1+S*sqrt(h)) * Br(P,V_t-1 + K_1) ## https://en.wikipedia.org/wiki/Runge%E2%80%93Kutta_method_(SDE) dBt=dBcum[trial+1,0,t] S=dBcum[trial+1,1,t] K_1=np.array([Vnow,csmpf(Pnow,Vnow)])*h+np.array([np.zeros((N,2)),(dBt-S*np.sqrt(h))*brown(Vnow)]) K_2=np.array([Vnow+K_1[1],csmpf(Pnow+K_1[0],Vnow+K_1[1])])*h+np.array([np.zeros((N,2)),(dBt+S*np.sqrt(h))*brown(Vnow+K_1[1])]) Pnext=np.copy(Pnow) Vnext=np.copy(Vnow) Pnext+=(K_1[0]+K_2[0])/2 Vnext+=(K_1[1]+K_2[1])/2 Pnext=np.nan_to_num(Pnext) Vnext=np.nan_to_num(Vnext) ## appending P,V, dB P[t]=np.array([Pnext]) V[t]=np.array([Vnext]) ## calculating and appending Vnrm, Xbnrm, phE s=np.power(Vnext[:,0],2)+np.power(Vnext[:,1],2) Vmean=np.array(np.mean(Vnext[:],axis=0)) Vnrm[t]=np.sum(s)-N*np.sum(np.power(Vmean,2)) Xbmean=np.array(np.mean(Pnext[:]-Z[:],axis=0)) Xbnrm[t]=np.sum(np.power(Pnext[:,0]-Z[:,0]-Xbmean[0],2)+np.power(Pnext[:,1]-Z[:,1]-Xbmean[1],2)) for i in range(N): J = A_ph[i,:]==1 ssq=(np.power(P[t,i,0]-Z[i,0]-P[t,:,0]+Z[:,0],2)+np.power(P[t,i,1]-Z[i,1]-P[t,:,1]+Z[:,1],2))[J] phE[t]+=np.sum(phiEest(ssq,beta,phLB)) phE[t]*=M/2 ##appending to cumulative data array Pcum=np.append(Pcum,np.array([P]),axis=0) Vcum=np.append(Vcum,np.array([V]),axis=0) Vnrmcum=np.append(Vnrmcum,np.array([Vnrm]),axis=0) Xbnrmcum=np.append(Xbnrmcum,np.array([Xbnrm]),axis=0) phEcum=np.append(phEcum,np.array([phE]),axis=0) if trial % 10 ==0 : print("end %d" %trial) elif dataset==1: ## loading data ## Pcum, Vcum, Vnrmcum, Xbnrmcum, phEcum print(os.getcwd()) Pcum_df=pd.read_csv('./Pcum.csv',delimiter='\t') Vcum_df=pd.read_csv('./Vcum.csv',delimiter='\t') Vnrmcum_df=pd.read_csv('./Vnrmcum.csv',delimiter='\t') Xbnrmcum_df=pd.read_csv('./Xbnrmcum.csv',delimiter='\t') phEcum_df=pd.read_csv('./phEcum.csv',delimiter='\t') Pcum_np=Pcum_df.to_numpy() Vcum_np=Vcum_df.to_numpy() Vnrmcum=Vnrmcum_df.to_numpy() Xbnrmcum=Xbnrmcum_df.to_numpy() phEnrmcum=phEcum_df.to_numpy() Pcum=Pcum_np.reshape(-1,T,N,2) Vcum=Vcum_np.reshape(-1,T,N,2) print(Pinit.shape) print ("End\n") medVnrm=np.median(Vnrmcum[1:],axis=0) stdVnrm=np.std(Vnrmcum[1:],axis=0) ##Outlier detection ##find appropriate constant 'cut' ## that the number of trials which is further than 'cut' * std from median ## is larger than 1% but not too large select=0 while select==0: checkI= Vnrmcum-medVnrm > cut*stdVnrm selcount = np.sum(checkI,axis=1) selI = selcount > 0 print ('cut:%.2f select:%d' %(cut,np.sum(selI))) if np.sum(selI)<=Trial*0.01 : cut-=0.25 else : select=1 print('select average') print(np.mean(selcount)) break ##Plotting and saving plot # plotsave=(input("Do you want to save? Yes=else, No=0 ")) plotsave=1 makeplot() #파일 저장은 어떻게 할지. 데이터 P,V,nV : Trial*T*N*2 / Vnrm, Xsnrm, dB : Trial*T #전자 : numpy를 썼을때 data모양 재조합하기 쉬운 방식으로 모양을 바꿔주면 될 듯. ##Saving data # if savemode==1 then save only chosen data(i.e. outliers), # elif savemode==2 then save all data save_mode=2 savedata(save_mode) print("DONE") # 중간에 물결선 넣기 # https://matplotlib.org/3.1.0/gallery/subplots_axes_and_figures/broken_axis.html 물결선 넣기 -> 결국 그래프를 두개로 쪼개야함 # https://matplotlib.org/3.1.0/tutorials/intermediate/gridspec.html ->그래프를 격자 위에 임의로 배치할 수 있음. 조각보처럼 # https://stackoverflow.com/questions/53642861/broken-axis-slash-marks-inside-bar-chart-in-matplotlib # %%

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6ad8a755033ecac454450a7695caf96f0b658d20

478

py

Python

codigo/Live199/exemplo_01.py

z4r4tu5tr4/live-de-quarta

1d12adb83f2afe306faf52e47edacef714c50574

[ "MIT" ]

2

2017-06-05T23:32:00.000Z

2017-06-08T01:01:35.000Z

codigo/Live199/exemplo_01.py

z4r4tu5tr4/live-de-quarta

1d12adb83f2afe306faf52e47edacef714c50574

[ "MIT" ]

null

codigo/Live199/exemplo_01.py

z4r4tu5tr4/live-de-quarta

1d12adb83f2afe306faf52e47edacef714c50574

[ "MIT" ]

null

import os if os.name == 'nt': filename = r'\\files\\pasta_0\\arquivo_1.txt' else: filename = 'files/pasta_0/arquivo_1.txt' with open(filename) as file: print(file.read()) from pathlib import Path path_atual = Path() pasta_0 = path_atual / 'files' / 'pasta_0' arquivo_0 = pasta_0 / 'arquivo_0.txt' arquivo_0.exists() # True arquivo_0.is_file # True arquivo_0.suffix # .txt arquivo_0.stem # arquivo_0 arquivo_0.read_text() # 'files/pasta_0/arquivo_0.txt'

17.703704

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26

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0

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0.125

0.0625

0

null

1

0

null

0

3

6ada06bcfa9bbdada08caf10d98edb9ed5f71ce8

4,514

py

Python

test/tests/augassign.py

jonco3/dynamic

76d10b012a7860595c7d9abbdf542c7d8f2a4d53

[ "MIT" ]

1

2020-11-26T23:37:19.000Z

test/tests/augassign.py

jonco3/dynamic

76d10b012a7860595c7d9abbdf542c7d8f2a4d53

[ "MIT" ]

null

test/tests/augassign.py

jonco3/dynamic

76d10b012a7860595c7d9abbdf542c7d8f2a4d53

[ "MIT" ]

null

# output: ok input = [10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10, 10] expected = [11, 8, 30, 2.5, 2, 4, 10000000, 20, 2, 2, 14, 15] def test(v): v[0] += 1 v[1] -= 2 v[2] *= 3 v[3] /= 4 v[4] //= 5 v[5] %= 6 v[6] **= 7 v[7] <<= 1 v[8] >>= 2 v[9] &= 3 v[10] ^= 4 v[11] |= 5 return v assert test(list(input)) == expected class Wrapped: def __init__(self, initial): self.value = initial def __eq__(self, other): return self.value == other def __iadd__(self, other): self.value += other return self def __isub__(self, other): self.value -= other return self def __imul__(self, other): self.value *= other return self def __itruediv__(self, other): self.value /= other return self def __ifloordiv__(self, other): self.value //= other return self def __imod__(self, other): self.value %= other return self def __ipow__(self, other): self.value **= other return self def __ilshift__(self, other): self.value <<= other return self def __irshift__(self, other): self.value >>= other return self def __ior__(self, other): self.value |= other return self def __iand__(self, other): self.value &= other return self def __ixor__(self, other): self.value ^= other return self assert test(list(map(Wrapped, input))) == expected class Wrapped2: def __init__(self, initial): self.value = initial def __add__(self, other): return Wrapped(self.value + other) def __sub__(self, other): return Wrapped(self.value - other) def __mul__(self, other): return Wrapped(self.value * other) def __truediv__(self, other): return Wrapped(self.value / other) def __floordiv__(self, other): return Wrapped(self.value // other) def __mod__(self, other): return Wrapped(self.value % other) def __pow__(self, other): return Wrapped(self.value ** other) def __lshift__(self, other): return Wrapped(self.value << other) def __rshift__(self, other): return Wrapped(self.value >> other) def __or__(self, other): return Wrapped(self.value | other) def __and__(self, other): return Wrapped(self.value & other) def __xor__(self, other): return Wrapped(self.value ^ other) assert test(list(map(Wrapped2, input))) == expected class C: def __init__(self, value): self.value = value o = C(1) def incValue(self, other): self.value += other return self o.__iadd__ = incValue threw = False try: o += 1 except TypeError as e: if "unsupported operand type" in str(e): threw = True assert threw C.__iadd__ = incValue o += 1 assert o.value == 2 class NonDataDescriptor: def __get__(self, instance, owner): def f(other): o.value -= other return o return f C.__iadd__ = NonDataDescriptor() o += 1 assert o.value == 1 class D: def __init__(self, initial): self.value = initial def __iadd__(self, other): self.value += other return self def __add__(self, other): return F(self.value - other) class E: def __init__(self, initial): self.value = initial def __iadd__(self, other): self.value += other return self def __add__(self, other): return NotImplemented class F: def __init__(self, initial): self.value = initial def __iadd__(self, other): return NotImplemented def __add__(self, other): return F(self.value - other) class G: def __init__(self, initial): self.value = initial def __iadd__(self, other): return NotImplemented def __add__(self, other): return NotImplemented d = D(0); d += 1; assert d.value == 1 e = E(0); e += 1; assert e.value == 1 f = F(0); f += 1; assert f.value == -1 g = G(0); threw = False try: g += 1 except TypeError: threw = True assert threw assert g.value == 0 class H: def __init__(self, initial): self.value = initial def __radd__(self, other): return H(self.value + other) h = 0; h += H(1); assert h.value == 1 # Test builtin stub reverses its arguments when required def opt(a, b): a += b return a assert opt(1, 1.5) == 2.5 assert opt(1, 1.5) == 2.5 print('ok')

23.268041

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4,514

4.02459

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0.176782

0.10998

0.638697

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0.561711

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4,514

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23.388601

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0

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0

null

0

null

0

1

0

1

0

3

6aef32d96b642f7e1027413f538b1e4a32088548

458

py

Python

xmlUtilLib.py

fermi-lat/xmlUtil

b1dc221207394c6e31ce3b91d95a67c0eeb8ab56

[ "BSD-3-Clause" ]

null

xmlUtilLib.py

fermi-lat/xmlUtil

b1dc221207394c6e31ce3b91d95a67c0eeb8ab56

[ "BSD-3-Clause" ]

null

xmlUtilLib.py

fermi-lat/xmlUtil

b1dc221207394c6e31ce3b91d95a67c0eeb8ab56

[ "BSD-3-Clause" ]

null

# $Header: /nfs/slac/g/glast/ground/cvs/GlastRelease-scons/xmlUtil/xmlUtilLib.py,v 1.2 2009/08/06 23:59:48 jrb Exp $ def generate(env, **kw): if not kw.get('depsOnly', 0): env.Tool('addLibrary', library = ['xmlUtil']) if env['PLATFORM'] == 'win32': env.Tool('findPkgPath', package = 'xmlUtil') env.Tool('xmlBaseLib') env.Tool('facilitiesLib') env.Tool('addLibrary', library = env['xercesLibs']) def exists(env): return 1;

35.230769

116

0.646288

64

458

4.625

0.6875

0.118243

0.114865

0.162162

0

0.052083

0.161572

458

12

117

38.166667

0.71875

0.248908

0

1

0

0.289474

0

null

0

null

0

null

0

1

0

1

0

null

0

1

0

3

6af0bb5cfa1c474d50abf3d422c13b8bfda0c5b4

509

py

Python

FenrTech SOLUTION-1/Image2Text/ImToStr1.py

MdNazmul9/PYTHON_CODE_ALL

75046943f1bb6b4a010955b23bfe3f01cd08a473

[ "MIT" ]

null

FenrTech SOLUTION-1/Image2Text/ImToStr1.py

MdNazmul9/PYTHON_CODE_ALL

75046943f1bb6b4a010955b23bfe3f01cd08a473

[ "MIT" ]

null

FenrTech SOLUTION-1/Image2Text/ImToStr1.py

MdNazmul9/PYTHON_CODE_ALL

75046943f1bb6b4a010955b23bfe3f01cd08a473

[ "MIT" ]

null

import cv2 import pytesseract #pytesseract.pytesseract.tesseract_cmd = r'C:\\Program Files\\Tesseract-OCR\\tesseract.exe' #pytesseract.pytesseract.tesseract_cmd = 'C:\\Program Files (x86)\\Tesseract-OCR\\tesseract.exe' pytesseract.pytesseract.tesseract_cmd = r'C:\Users\User\AppData\Local\Tesseract-OCR\tesseract.exe' img = cv2.imread('./BreakingNews.png') text = pytesseract.image_to_string(img) print(text) img = cv2.imread('./BitCoin.jpeg') text = pytesseract.image_to_string(img) print(text)

39.153846

99

0.766208

68

509

5.632353

0.397059

0.229765

0.24282

0.266319

0.610966

0.511749

0

0.01073

0.084479

509

13

100

39.153846

0.811159

0.363458

0

0.444444

0

0.279743

0.176849

0

1

0

false

0

0.222222

0

0.222222

0

null

1

0

null

0

3

0a7b1cd2b2a1d357fd02ba117bde72a44afd1fa3

385

py

Python

moban_tornado/__init__.py

PrajwalM2212/moban-tornado

c5279e7a643d11ff0881496a3b770ef2507d797a

[ "MIT" ]

2

2019-02-24T11:59:19.000Z

moban_tornado/__init__.py

PrajwalM2212/moban-tornado

c5279e7a643d11ff0881496a3b770ef2507d797a

[ "MIT" ]

3

2019-02-24T21:21:41.000Z

2020-05-29T15:01:12.000Z

moban_tornado/__init__.py

moremoban/moban-tornado

c5279e7a643d11ff0881496a3b770ef2507d797a

[ "MIT" ]

null

from lml.plugin import PluginInfo, PluginInfoChain import moban.constants as constants from moban_tornado._version import __version__ from moban_tornado._version import __author__ PluginInfoChain(__name__).add_a_plugin_instance( PluginInfo( constants.TEMPLATE_ENGINE_EXTENSION, "%s.engine.EngineTornado" % __name__, tags=["Tornado", "tornado", ], ) )

27.5

50

0.758442

41

385

6.512195

0.536585

0.067416

0.11985

0.172285

0.217228

0

0.161039

385

13

51

29.615385

0.826625

0

0.096104

0.05974

0

1

0

true

0

0.363636

0

0.363636

0

null

0

1

0

null

0

1

0

1

0

3

0a8a59fbc9f9de431d6267755346bfe6e2daa160

767

py

Python

strikethrough_removal/src/__init__.py

RaphaelaHeil/strikethrough-removal-cyclegans

91555b22cac6b6a379597aa94c23bdf02c9970a7

[ "MIT" ]

3

2021-08-30T12:37:14.000Z

2022-02-09T16:07:14.000Z

strikethrough_removal/src/__init__.py

ektavats/strikethrough-removal-cyclegans

35456619ff87fa010d2c161cff774af02142bae9

[ "MIT" ]

null

strikethrough_removal/src/__init__.py

ektavats/strikethrough-removal-cyclegans

35456619ff87fa010d2c161cff774af02142bae9

[ "MIT" ]

1

2022-01-25T10:30:54.000Z

from .utils import PadToSize, composeTransformations, getDiscriminatorModels, getGeneratorModels, \ getPretrainedAuxiliaryLossModel from .metrics import calculateRmse, calculateF1Score from .dataset import StruckCleanDataset, ValidationStruckCleanDataset, TestDataset from .configuration import StrikeThroughType, ExperimentType, FeatureType, ModelName, Configuration, getConfiguration __all__ = ["PadToSize", "composeTransformations", "getDiscriminatorModels", "getGeneratorModels", "getPretrainedAuxiliaryLossModel", "calculateRmse", "calculateF1Score", "StruckCleanDataset", "ValidationStruckCleanDataset", "TestDataset", "StrikeThroughType", "ExperimentType", "FeatureType", "ModelName", "Configuration", "getConfiguration"]

69.727273

117

0.801825

45

767

13.577778

0.488889

0.101473

0.173486

0.232406

0.595745

0.261866

0

0.002933

0.110821

767

10

118

76.7

0.892962

0

0.349413

0.134289

0

1

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false

0

0.444444

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0.444444

0

1

null

0

1

0

null

0

1

0

3

0a91db1805ccec96b3f71337475826f22f3896b4

283

py

Python

attendees/persons/apps.py

xjlin0/attendees32

25913c75ea8d916dcb065a23f2fa68bea558f77c

[ "MIT" ]

null

attendees/persons/apps.py

xjlin0/attendees32

25913c75ea8d916dcb065a23f2fa68bea558f77c

[ "MIT" ]

5

2022-01-21T03:26:40.000Z

2022-02-04T17:32:16.000Z

attendees/persons/apps.py

xjlin0/attendees32

25913c75ea8d916dcb065a23f2fa68bea558f77c

[ "MIT" ]

null

from django.apps import AppConfig class PersonsConfig(AppConfig): name = "attendees.persons" def ready(self): # importing signal handlers # https://docs.djangoproject.com/en/dev/topics/signals/#preventing-duplicate-signals import attendees.persons.signals

28.3

120

0.738516

32

283

6.53125

0.8125

0.15311

0

0.162544

283

9

121

31.444444

0.881857

0.381625

0

0.099415

0

1

0.2

false

0

0.4

0

1

0

null

0

1

0

null

0

1

0

1

0

3

0a9807c2f3907c5b205e154cd6248dfe4333924f

183

py

Python

update/venv/lib/python3.9/site-packages/fontTools/__init__.py

Imudassir77/material-design-icons

63c5cb306073a9ecdfd3579f0f696746ab6305f6

[ "Apache-2.0" ]

38,667

2015-01-01T00:15:34.000Z

2022-03-31T22:57:03.000Z

update/venv/lib/python3.9/site-packages/fontTools/__init__.py

azizhudai/material-design-icons

63c5cb306073a9ecdfd3579f0f696746ab6305f6

[ "Apache-2.0" ]

1,192

2015-01-03T07:59:34.000Z

2022-03-31T13:22:26.000Z

update/venv/lib/python3.9/site-packages/fontTools/__init__.py

azizhudai/material-design-icons

63c5cb306073a9ecdfd3579f0f696746ab6305f6

[ "Apache-2.0" ]

11,269

2015-01-01T08:41:17.000Z

2022-03-31T16:12:52.000Z

import logging from fontTools.misc.loggingTools import configLogger log = logging.getLogger(__name__) version = __version__ = "4.22.1" __all__ = ["version", "log", "configLogger"]

20.333333

52

0.754098

21

183

6

0.714286

0

0.024845

0.120219

183

8

53

22.875

0.757764

0

0.153005

0

1

0

false

0

0.4

0

0.4

0

1

0

null

0

1

0

null

0

1

0

3

0abc3a801eabf7fb558efa2abc0fd1fd2967300a

185

py

Python

web/__init__.py

aHugues/default-flask

4d6c8c95f9f93b1fccc56aa413f912c86bf99bc3

[ "Apache-2.0" ]

1

2019-04-13T20:13:37.000Z

web/__init__.py

aHugues/default-flask

4d6c8c95f9f93b1fccc56aa413f912c86bf99bc3

[ "Apache-2.0" ]

1

2019-04-14T13:31:10.000Z

web/__init__.py

aHugues/porygon-indexer

8d6c9ca912c95d01a73a36f87e173e2a450441e8

[ "Apache-2.0" ]

null

from flask import Flask from .views import main_views def create_app(debug=False): app = Flask(__name__) app.debug = debug app.register_blueprint(main_views) return app

23.125

38

0.740541

27

185

4.777778

0.518519

0.139535

0

0.189189

185

8

39

23.125

0.86

0

1

0.142857

false

0

0.285714

0

0.571429

0.142857

1

0

null

0

1

0

null

0

1

0

3

0ad29e2d73a653c167863eb5398a68759438da21

123

py

Python

ArchiveddashProblems/Problem_006.py

Utshaan/Archived_Problems

423e8fc5db2dd5ee54a625cf8cbec2a8a271fcf3

[ "MIT" ]

1

2022-03-14T14:57:01.000Z

ArchiveddashProblems/Problem_006.py

Utshaan/Archived_Problems

423e8fc5db2dd5ee54a625cf8cbec2a8a271fcf3

[ "MIT" ]

1

2022-03-13T12:33:07.000Z

2022-03-13T12:50:42.000Z

ArchiveddashProblems/Problem_006.py

Utshaan/Archived_Problems

423e8fc5db2dd5ee54a625cf8cbec2a8a271fcf3

[ "MIT" ]

null

from fpack import SumofSquares, SquareofSum x = int(input("number, now\n")) a = SquareofSum(x) - SumofSquares(x) print(a)

20.5

43

0.723577

18

123

4.944444

0.722222

0.269663

0

0.130081

123

5

44

24.6

0.831776

0

0.105691

0

1

0

false

0

0.25

0

0.25

1

0

null

1

0

1

0

null

0

3

0aec531afb01a71fa2d98ffd998050ce1a051ad6

3,078

py

Python

app/api_v1/endpoints/kafka.py

endocode/fasten_api

a2f5c712fb0f39de664ef98543c21d3eb472d9e9

[ "Apache-2.0" ]

null

app/api_v1/endpoints/kafka.py

endocode/fasten_api

a2f5c712fb0f39de664ef98543c21d3eb472d9e9

[ "Apache-2.0" ]

null

app/api_v1/endpoints/kafka.py

endocode/fasten_api

a2f5c712fb0f39de664ef98543c21d3eb472d9e9

[ "Apache-2.0" ]

null

from fastapi import APIRouter from api_v1.endpoints.utils import connect_kafka router = APIRouter() @router.get("/") async def root(): return {"message": "it's working!"} @router.get("/{pkg_manager}/{product}/deps/{timestamp}") def rebuild_dependency_net(pkg_manager: str, product: str, timestamp: int): """ Given a product and a timestamp, reconstruct its dependency network Return: A set of revisions, along with an adjacency matrix REST examples: GET /api/mvn/org.slf4j:slf4j-api/deps/1233323123 GET /api/pypi/numpy/deps/1233323123?transitive=true """ msg = connect_kafka() # TODO: send a kafka topic requesting a set of revisions # TODO: read the kafka topic with the answer # TODO: transform the data from kafka (if necessary) # TODO: return the set of revisions return msg @router.get("/{pkg_manager}/{product}/cg/{timestamp}") def get_call_graph(): """ Given a product and a timestamp, retrieve its call graph Use case: A user wants to run a custom analysis locally. Return: A JSON-serialized RevisionCallGraph REST examples: GET /api/mvn/org.slf4j:slf4j-api/cg/1233323123 GET /api/pypi/numpy/cg/1233323123?transitive=true """ pass @router.get("/{pkg_manager}/{product}/{version}") def get_metadata(): """ Given a product and a version, retrieve all known metadata Return: All known metadata for a revision REST examples: GET /api/mvn/org.slf4j:slf4j-api/1.7.29 GET /api/pypi/numpy/1.15.2 """ pass @router.get("/{pkg_manager}/{product}/{version}/vulnerabilities") def get_vulnerabilities(): """ Vulnerabilities in the transitive closure of a package version Expected result, in order of detail - Paths of revisions, - Paths of files / compilation units, - Paths of functions REST examples: GET /api/mvn/org.slf4j:slf4j-api/1.7.29/vulnerabilities GET /api/pypi/numpy/1.15.2/vulnerabilities """ pass @router.post("/{pkg_manager}/{product}/{version}/impact") def post_(): """ Impact analysis Use case: the user asks the KB to compute the impact of a semantic change to a function Exapected result: The full set of functions reachable from the provided function REST examples: POST /api/mvn/org.slf4j:slf4j-api/1.7.29/impact POST /api/mvn/org.slf4j:slf4j-api/1.7.29/impact?transitive=true The post body contains a FASTEN URI """ # TODO: need to clarify this use case pass @router.post("/{pkg_manager}/{product}/{version}/cg") def update_cg(): """ Update the static CG of a package version with new edges Use case: A user runs an instrumented test suite locally and decides to update the central call graph with edges that do not exist due to shortcomings in static analysis. Expected result: A list of edges that where added. REST examples: POST /api/mvn/org.slf4j:slf4j-api/1.7.29/cg POST /api/pypi/numpy/1.15.2/cg """ pass

25.229508

77

0.675763

443

3,078

4.654628

0.327314

0.023278

0.030553

0.047527

0.318623

0.260912

0.227934

0.13676

0.100873

0

0.036205

0.219298

3,078

121

78

25.438017

0.821889

0.648798

0

0.2

0

0.310875

0.286052

0

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0

1

0.24

false

0.2

0.08

0

0.4

0

null

0

null

0

1

0

1

0

1

0

3

0aeea2abe861dcfc38b00218cc263c0a631c1760

1,674

py

Python

gmail.py

NH-web/NH-gmail

17ff1eadabca534da8bda8761445418f18f14c30

[ "Apache-2.0" ]

2

2020-10-11T14:53:21.000Z

2022-01-02T12:49:21.000Z

gmail.py

NH-web/NH-gmail

17ff1eadabca534da8bda8761445418f18f14c30

[ "Apache-2.0" ]

null

gmail.py

NH-web/NH-gmail

17ff1eadabca534da8bda8761445418f18f14c30

[ "Apache-2.0" ]

null

import smtplib import time import subprocess from datetime import datetime r = "033[1;91m" g = "033[1;32m" s = g + "+" print (g +'-'*60) print ("") print ('['+s+']starting your tool and updating the programm') print ("") print (g +'-'*60) time.sleep(5) print (g'/...\.....starting the server' + g +'/....//../'*1000) subprocess.call('clear',SHELL=True) while True: print ('play song for more motivation!......') subprocess.call("play-audio 'Eminem_-_Escape_feat._Hopsin_(2019)(360p).mp3'",SHELL=True) print ('now let-us start.....') def usage(): print ('USAGE: python gmail.py <GMAIL> <PASSLIST>') print (' {{{{{ }}}}} ') print (' {{{{ }}}} ') print (' {{{{ NNNNNNNN NNNN HHHH HHHH }}}} ') print (' {{{{ NNNNNNNNN NNNN HHHH HHHH }}}} ') print ('{{{{ NNNNN NNNN NNNN HHHHHHHHHHH }}}} ') print (' {{{{ NNNNN NNNN NNNN HHHHHHHHHHH }}}} ') print (' {{{{ NNNNN NNNNNNNN HHHH HHHH }}}} ') print (' {{{{{ NNNNN NNNNNNN HHHH HHHH }}}} ') print (' {{{{{{ }}}}} ') target = str(sys.argv[1]) passw = str(sys.argv[2]) s = smtplib.SMTP('smtp.gmail.com',587) def start(): for password in passw: try: passww = s.login(target,password) t1 = datetime.now() print ('started at:{0}'.format(t1)) print ('[+]password Found:%s'%passww) except: print ('[-]Attempting password:%s'%password) print (len(sys.argv)) if len(sys.argv) != 3: usage() else: start() t2 = datetime.now() total = t2 - t1 print ('finished in :{0}'.format(total))

27.9

92

0.519713

193

1,674

4.481865

0.466321

0.046243

0.060116

0.039306

0.078613

0

0.034426

0.271207

1,674

59

93

28.372881

0.67459

0

0.16

0

0.449492

0.028093

0

null

0.12

0.08

null

0.46

0

null

0

null

0

1

0

1

0

1

0

3

7c145f3f4175223e4ff7a27b6305b695ba73a77b

136

py

Python

multiplication/multiplication.py

Vino2001-hub/the-creative-vipers

844c20e7f8dc6a69f64c17fba29d385b5dd21868

[ "MIT" ]

null

multiplication/multiplication.py

Vino2001-hub/the-creative-vipers

844c20e7f8dc6a69f64c17fba29d385b5dd21868

[ "MIT" ]

null

multiplication/multiplication.py

Vino2001-hub/the-creative-vipers

844c20e7f8dc6a69f64c17fba29d385b5dd21868

[ "MIT" ]

3

2021-04-18T14:20:45.000Z

2021-04-18T15:12:42.000Z

def domultiplication: a=68 b=10 print("Multiplication of 68*10=",a*b)#multiplication function is invoked domultiplication()

22.666667

76

0.727941

18

136

5.5

0.666667

0

0.070796

0.169118

136

5

77

27.2

0.80531

0.25

0

0.237624

0

null

0

null

0.2

1

0

null

0

1

0

null

0

1

0

3

7c1a4a7821a91fb68ddce6a8ad71199b67b52d2a

47,543

py

Python

neo/test/coretest/test_irregularysampledsignal.py

alafuzof/python-neo

5fae976d1d944bf16285dc51f57d0e7d4c2c62ad

[ "BSD-3-Clause" ]

null

neo/test/coretest/test_irregularysampledsignal.py

alafuzof/python-neo

5fae976d1d944bf16285dc51f57d0e7d4c2c62ad

[ "BSD-3-Clause" ]

null

neo/test/coretest/test_irregularysampledsignal.py

alafuzof/python-neo

5fae976d1d944bf16285dc51f57d0e7d4c2c62ad

[ "BSD-3-Clause" ]

1

2021-07-17T16:24:25.000Z

# -*- coding: utf-8 -*- """ Tests of the neo.core.irregularlysampledsignal.IrregularySampledSignal class """ import unittest import os import pickle import warnings from copy import deepcopy import numpy as np import quantities as pq from numpy.testing import assert_array_equal from neo.core.dataobject import ArrayDict try: from IPython.lib.pretty import pretty except ImportError as err: HAVE_IPYTHON = False else: HAVE_IPYTHON = True from neo.core.irregularlysampledsignal import IrregularlySampledSignal from neo.core import Segment, ChannelIndex from neo.core.baseneo import MergeError from neo.test.tools import (assert_arrays_almost_equal, assert_arrays_equal, assert_neo_object_is_compliant, assert_same_sub_schema, assert_same_attributes, assert_same_annotations, assert_same_array_annotations) from neo.test.generate_datasets import (get_fake_value, get_fake_values, fake_neo, TEST_ANNOTATIONS) class Test__generate_datasets(unittest.TestCase): def setUp(self): np.random.seed(0) self.annotations = dict( [(str(x), TEST_ANNOTATIONS[x]) for x in range(len(TEST_ANNOTATIONS))]) def test__get_fake_values(self): self.annotations['seed'] = 0 times = get_fake_value('times', pq.Quantity, seed=0, dim=1) signal = get_fake_value('signal', pq.Quantity, seed=1, dim=2) name = get_fake_value('name', str, seed=2, obj=IrregularlySampledSignal) description = get_fake_value('description', str, seed=3, obj='IrregularlySampledSignal') file_origin = get_fake_value('file_origin', str) arr_ann = get_fake_value('array_annotations', dict, seed=5, obj=IrregularlySampledSignal, n=1) attrs1 = {'name': name, 'description': description, 'file_origin': file_origin} attrs2 = attrs1.copy() attrs2.update(self.annotations) attrs2['array_annotations'] = arr_ann res11 = get_fake_values(IrregularlySampledSignal, annotate=False, seed=0) res12 = get_fake_values('IrregularlySampledSignal', annotate=False, seed=0) res21 = get_fake_values(IrregularlySampledSignal, annotate=True, seed=0) res22 = get_fake_values('IrregularlySampledSignal', annotate=True, seed=0) assert_array_equal(res11.pop('times'), times) assert_array_equal(res12.pop('times'), times) assert_array_equal(res21.pop('times'), times) assert_array_equal(res22.pop('times'), times) assert_array_equal(res11.pop('signal'), signal) assert_array_equal(res12.pop('signal'), signal) assert_array_equal(res21.pop('signal'), signal) assert_array_equal(res22.pop('signal'), signal) self.assertEqual(res11, attrs1) self.assertEqual(res12, attrs1) # Array annotations need to be compared separately # because numpy arrays define equality differently arr_ann_res21 = res21.pop('array_annotations') arr_ann_attrs2 = attrs2.pop('array_annotations') self.assertEqual(res21, attrs2) assert_arrays_equal(arr_ann_res21['valid'], arr_ann_attrs2['valid']) assert_arrays_equal(arr_ann_res21['number'], arr_ann_attrs2['number']) arr_ann_res22 = res22.pop('array_annotations') self.assertEqual(res22, attrs2) assert_arrays_equal(arr_ann_res22['valid'], arr_ann_attrs2['valid']) assert_arrays_equal(arr_ann_res22['number'], arr_ann_attrs2['number']) def test__fake_neo__cascade(self): self.annotations['seed'] = None obj_type = IrregularlySampledSignal cascade = True res = fake_neo(obj_type=obj_type, cascade=cascade) self.assertTrue(isinstance(res, IrregularlySampledSignal)) assert_neo_object_is_compliant(res) self.assertEqual(res.annotations, self.annotations) def test__fake_neo__nocascade(self): self.annotations['seed'] = None obj_type = 'IrregularlySampledSignal' cascade = False res = fake_neo(obj_type=obj_type, cascade=cascade) self.assertTrue(isinstance(res, IrregularlySampledSignal)) assert_neo_object_is_compliant(res) self.assertEqual(res.annotations, self.annotations) class TestIrregularlySampledSignalConstruction(unittest.TestCase): def test_IrregularlySampledSignal_creation_times_units_signal_units(self): params = {'test2': 'y1', 'test3': True} arr_ann = {'anno1': [23], 'anno2': ['A']} sig = IrregularlySampledSignal([1.1, 1.5, 1.7] * pq.ms, signal=[20., 40., 60.] * pq.mV, name='test', description='tester', file_origin='test.file', test1=1, array_annotations=arr_ann, **params) sig.annotate(test1=1.1, test0=[1, 2]) assert_neo_object_is_compliant(sig) assert_array_equal(sig.times, [1.1, 1.5, 1.7] * pq.ms) assert_array_equal(np.asarray(sig).flatten(), np.array([20., 40., 60.])) self.assertEqual(sig.units, pq.mV) self.assertEqual(sig.name, 'test') self.assertEqual(sig.description, 'tester') self.assertEqual(sig.file_origin, 'test.file') self.assertEqual(sig.annotations['test0'], [1, 2]) self.assertEqual(sig.annotations['test1'], 1.1) self.assertEqual(sig.annotations['test2'], 'y1') self.assertTrue(sig.annotations['test3']) assert_arrays_equal(sig.array_annotations['anno1'], np.array([23])) assert_arrays_equal(sig.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(sig.array_annotations, ArrayDict) def test_IrregularlySampledSignal_creation_units_arg(self): params = {'test2': 'y1', 'test3': True} arr_ann = {'anno1': [23], 'anno2': ['A']} sig = IrregularlySampledSignal([1.1, 1.5, 1.7], signal=[20., 40., 60.], units=pq.V, time_units=pq.s, name='test', description='tester', file_origin='test.file', test1=1, array_annotations=arr_ann, **params) sig.annotate(test1=1.1, test0=[1, 2]) assert_neo_object_is_compliant(sig) assert_array_equal(sig.times, [1.1, 1.5, 1.7] * pq.s) assert_array_equal(np.asarray(sig).flatten(), np.array([20., 40., 60.])) self.assertEqual(sig.units, pq.V) self.assertEqual(sig.name, 'test') self.assertEqual(sig.description, 'tester') self.assertEqual(sig.file_origin, 'test.file') self.assertEqual(sig.annotations['test0'], [1, 2]) self.assertEqual(sig.annotations['test1'], 1.1) self.assertEqual(sig.annotations['test2'], 'y1') self.assertTrue(sig.annotations['test3']) assert_arrays_equal(sig.array_annotations['anno1'], np.array([23])) assert_arrays_equal(sig.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(sig.array_annotations, ArrayDict) def test_IrregularlySampledSignal_creation_units_rescale(self): params = {'test2': 'y1', 'test3': True} arr_ann = {'anno1': [23], 'anno2': ['A']} sig = IrregularlySampledSignal([1.1, 1.5, 1.7] * pq.s, signal=[2., 4., 6.] * pq.V, units=pq.mV, time_units=pq.ms, name='test', description='tester', file_origin='test.file', test1=1, array_annotations=arr_ann, **params) sig.annotate(test1=1.1, test0=[1, 2]) assert_neo_object_is_compliant(sig) assert_array_equal(sig.times, [1100, 1500, 1700] * pq.ms) assert_array_equal(np.asarray(sig).flatten(), np.array([2000., 4000., 6000.])) self.assertEqual(sig.units, pq.mV) self.assertEqual(sig.name, 'test') self.assertEqual(sig.description, 'tester') self.assertEqual(sig.file_origin, 'test.file') self.assertEqual(sig.annotations['test0'], [1, 2]) self.assertEqual(sig.annotations['test1'], 1.1) self.assertEqual(sig.annotations['test2'], 'y1') self.assertTrue(sig.annotations['test3']) assert_arrays_equal(sig.array_annotations['anno1'], np.array([23])) assert_arrays_equal(sig.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(sig.array_annotations, ArrayDict) def test_IrregularlySampledSignal_different_lens_ValueError(self): times = [1.1, 1.5, 1.7] * pq.ms signal = [20., 40., 60., 70.] * pq.mV self.assertRaises(ValueError, IrregularlySampledSignal, times, signal) def test_IrregularlySampledSignal_no_signal_units_ValueError(self): times = [1.1, 1.5, 1.7] * pq.ms signal = [20., 40., 60.] self.assertRaises(ValueError, IrregularlySampledSignal, times, signal) def test_IrregularlySampledSignal_no_time_units_ValueError(self): times = [1.1, 1.5, 1.7] signal = [20., 40., 60.] * pq.mV self.assertRaises(ValueError, IrregularlySampledSignal, times, signal) class TestIrregularlySampledSignalProperties(unittest.TestCase): def setUp(self): self.times = [np.arange(10.0) * pq.s, np.arange(-100.0, 100.0, 10.0) * pq.ms, np.arange(100) * pq.ns] self.data = [np.arange(10.0) * pq.nA, np.arange(-100.0, 100.0, 10.0) * pq.mV, np.random.uniform(size=100) * pq.uV] self.signals = [IrregularlySampledSignal(t, signal=D, testattr='test') for D, t in zip(self.data, self.times)] def test__compliant(self): for signal in self.signals: assert_neo_object_is_compliant(signal) def test__t_start_getter(self): for signal, times in zip(self.signals, self.times): self.assertAlmostEqual(signal.t_start, times[0], delta=1e-15) def test__t_stop_getter(self): for signal, times in zip(self.signals, self.times): self.assertAlmostEqual(signal.t_stop, times[-1], delta=1e-15) def test__duration_getter(self): for signal, times in zip(self.signals, self.times): self.assertAlmostEqual(signal.duration, times[-1] - times[0], delta=1e-15) def test__sampling_intervals_getter(self): for signal, times in zip(self.signals, self.times): assert_arrays_almost_equal(signal.sampling_intervals, np.diff(times), threshold=1e-15) def test_IrregularlySampledSignal_repr(self): sig = IrregularlySampledSignal([1.1, 1.5, 1.7] * pq.s, signal=[2., 4., 6.] * pq.V, name='test', description='tester', file_origin='test.file', test1=1) assert_neo_object_is_compliant(sig) if np.__version__.split(".")[:2] > ['1', '13']: # see https://github.com/numpy/numpy/blob/master/doc/release/1.14.0-notes.rst#many # -changes-to-array-printing-disableable-with-the-new-legacy-printing-mode targ = ( '<IrregularlySampledSignal(array([[2.],\n [4.],\n [6.]]) * V ' '' + 'at times [1.1 1.5 1.7] s)>') else: targ = ( '<IrregularlySampledSignal(array([[ 2.],\n [ 4.],\n [ 6.]]) ' '* V ' + 'at times [ 1.1 1.5 1.7] s)>') res = repr(sig) self.assertEqual(targ, res) class TestIrregularlySampledSignalArrayMethods(unittest.TestCase): def setUp(self): self.data1 = np.arange(10.0) self.data1quant = self.data1 * pq.mV self.time1 = np.logspace(1, 5, 10) self.time1quant = self.time1 * pq.ms self.arr_ann = {'anno1': [23], 'anno2': ['A']} self.signal1 = IrregularlySampledSignal(self.time1quant, signal=self.data1quant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test', array_annotations=self.arr_ann) self.signal1.segment = Segment() self.signal1.channel_index = ChannelIndex([0]) def test__compliant(self): assert_neo_object_is_compliant(self.signal1) self.assertEqual(self.signal1.name, 'spam') self.assertEqual(self.signal1.description, 'eggs') self.assertEqual(self.signal1.file_origin, 'testfile.txt') self.assertEqual(self.signal1.annotations, {'arg1': 'test'}) assert_arrays_equal(self.signal1.array_annotations['anno1'], np.array([23])) assert_arrays_equal(self.signal1.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(self.signal1.array_annotations, ArrayDict) def test__slice_should_return_IrregularlySampledSignal(self): result = self.signal1[3:8] self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) self.assertEqual(result.size, 5) self.assertEqual(result.t_start, self.time1quant[3]) self.assertEqual(result.t_stop, self.time1quant[7]) assert_array_equal(self.time1quant[3:8], result.times) assert_array_equal(self.data1[3:8].reshape(-1, 1), result.magnitude) # Test other attributes were copied over (in this case, defaults) self.assertEqual(result.file_origin, self.signal1.file_origin) self.assertEqual(result.name, self.signal1.name) self.assertEqual(result.description, self.signal1.description) self.assertEqual(result.annotations, self.signal1.annotations) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test__getitem_should_return_single_quantity(self): self.assertEqual(self.signal1[0], 0 * pq.mV) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertRaises(IndexError, self.signal1.__getitem__, 10) def test__getitem_out_of_bounds_IndexError(self): self.assertRaises(IndexError, self.signal1.__getitem__, 10) def test_comparison_operators(self): assert_array_equal(self.signal1 >= 5 * pq.mV, np.array( [[False, False, False, False, False, True, True, True, True, True]]).T) assert_array_equal(self.signal1 == 5 * pq.mV, np.array( [[False, False, False, False, False, True, False, False, False, False]]).T) assert_array_equal(self.signal1 == self.signal1, np.array( [[True, True, True, True, True, True, True, True, True, True]]).T) def test__comparison_as_indexing_single_trace(self): self.assertEqual(self.signal1[self.signal1 == 5], [5 * pq.mV]) def test__comparison_as_indexing_multi_trace(self): signal = IrregularlySampledSignal(self.time1quant, np.arange(20).reshape((-1, 2)) * pq.V) assert_array_equal(signal[signal < 10], np.array([[0, 2, 4, 6, 8], [1, 3, 5, 7, 9]]).T * pq.V) def test__indexing_keeps_order_across_channels(self): # AnalogSignals with 10 traces each having 5 samples (eg. data[0] = [0,10,20,30,40]) data = np.array([range(10), range(10, 20), range(20, 30), range(30, 40), range(40, 50)]) mask = np.full((5, 10), fill_value=False, dtype=bool) # selecting one entry per trace mask[[0, 1, 0, 3, 0, 2, 4, 3, 1, 4], range(10)] = True signal = IrregularlySampledSignal(np.arange(5) * pq.s, np.array(data) * pq.V) assert_array_equal(signal[mask], np.array([[0, 11, 2, 33, 4, 25, 46, 37, 18, 49]]) * pq.V) def test__indexing_keeps_order_across_time(self): # AnalogSignals with 10 traces each having 5 samples (eg. data[0] = [0,10,20,30,40]) data = np.array([range(10), range(10, 20), range(20, 30), range(30, 40), range(40, 50)]) mask = np.full((5, 10), fill_value=False, dtype=bool) # selecting two entries per trace temporal_ids = [0, 1, 0, 3, 1, 2, 4, 2, 1, 4] + [4, 3, 2, 1, 0, 1, 2, 3, 2, 1] mask[temporal_ids, list(range(10)) + list(range(10))] = True signal = IrregularlySampledSignal(np.arange(5) * pq.s, np.array(data) * pq.V) assert_array_equal(signal[mask], np.array([[0, 11, 2, 13, 4, 15, 26, 27, 18, 19], [40, 31, 22, 33, 14, 25, 46, 37, 28, 49]]) * pq.V) def test__comparison_with_inconsistent_units_should_raise_Exception(self): self.assertRaises(ValueError, self.signal1.__gt__, 5 * pq.nA) def test_simple_statistics(self): targmean = self.signal1[:-1] * np.diff(self.time1quant).reshape(-1, 1) targmean = targmean.sum() / (self.time1quant[-1] - self.time1quant[0]) self.assertEqual(self.signal1.max(), 9 * pq.mV) self.assertEqual(self.signal1.min(), 0 * pq.mV) self.assertEqual(self.signal1.mean(), targmean) def test_mean_interpolation_NotImplementedError(self): self.assertRaises(NotImplementedError, self.signal1.mean, True) def test_resample_NotImplementedError(self): self.assertRaises(NotImplementedError, self.signal1.resample, True) def test__rescale_same(self): result = self.signal1.copy() result = result.rescale(pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(result.units, 1 * pq.mV) assert_array_equal(result.magnitude, self.data1.reshape(-1, 1)) assert_array_equal(result.times, self.time1quant) assert_same_sub_schema(result, self.signal1) self.assertIsInstance(result.channel_index, ChannelIndex) self.assertIsInstance(result.segment, Segment) self.assertIs(result.channel_index, self.signal1.channel_index) self.assertIs(result.segment, self.signal1.segment) def test__rescale_new(self): result = self.signal1.copy() result = result.rescale(pq.uV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(result.units, 1 * pq.uV) assert_arrays_almost_equal(np.array(result), self.data1.reshape(-1, 1) * 1000., 1e-10) assert_array_equal(result.times, self.time1quant) self.assertIsInstance(result.channel_index, ChannelIndex) self.assertIsInstance(result.segment, Segment) self.assertIs(result.channel_index, self.signal1.channel_index) self.assertIs(result.segment, self.signal1.segment) def test__rescale_new_incompatible_ValueError(self): self.assertRaises(ValueError, self.signal1.rescale, pq.nA) def test_time_slice(self): targdataquant = [[1.0], [2.0], [3.0]] * pq.mV targtime = np.logspace(1, 5, 10) targtimequant = targtime[1:4] * pq.ms targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = 15 t_stop = 250 result = self.signal1.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test__time_slice_deepcopy_annotations(self): params1 = {'test0': 'y1', 'test1': ['deeptest'], 'test2': True} self.signal1.annotate(**params1) result = self.signal1.time_slice(None, None) # Change annotations of original params2 = {'test0': 'y2', 'test2': False} self.signal1.annotate(**params2) self.signal1.annotations['test1'][0] = 'shallowtest' self.assertNotEqual(self.signal1.annotations['test0'], result.annotations['test0']) self.assertNotEqual(self.signal1.annotations['test1'], result.annotations['test1']) self.assertNotEqual(self.signal1.annotations['test2'], result.annotations['test2']) # Change annotations of result params3 = {'test0': 'y3'} result.annotate(**params3) result.annotations['test1'][0] = 'shallowtest2' self.assertNotEqual(self.signal1.annotations['test0'], result.annotations['test0']) self.assertNotEqual(self.signal1.annotations['test1'], result.annotations['test1']) self.assertNotEqual(self.signal1.annotations['test2'], result.annotations['test2']) def test__time_slice_deepcopy_array_annotations(self): length = self.signal1.shape[-1] params1 = {'test0': ['y{}'.format(i) for i in range(length)], 'test1': ['deeptest' for i in range(length)], 'test2': [(-1)**i > 0 for i in range(length)]} self.signal1.array_annotate(**params1) result = self.signal1.time_slice(None, None) # Change annotations of original params2 = {'test0': ['x{}'.format(i) for i in range(length)], 'test2': [(-1) ** (i + 1) > 0 for i in range(length)]} self.signal1.array_annotate(**params2) self.signal1.array_annotations['test1'][0] = 'shallowtest' self.assertFalse(all(self.signal1.array_annotations['test0'] == result.array_annotations['test0'])) self.assertFalse(all(self.signal1.array_annotations['test1'] == result.array_annotations['test1'])) self.assertFalse(all(self.signal1.array_annotations['test2'] == result.array_annotations['test2'])) # Change annotations of result params3 = {'test0': ['z{}'.format(i) for i in range(1, result.shape[-1]+1)]} result.array_annotate(**params3) result.array_annotations['test1'][0] = 'shallow2' self.assertFalse(all(self.signal1.array_annotations['test0'] == result.array_annotations['test0'])) self.assertFalse(all(self.signal1.array_annotations['test1'] == result.array_annotations['test1'])) self.assertFalse(all(self.signal1.array_annotations['test2'] == result.array_annotations['test2'])) def test__time_slice_deepcopy_data(self): result = self.signal1.time_slice(None, None) # Change values of original array self.signal1[2] = 7.3*self.signal1.units self.assertFalse(all(self.signal1 == result)) # Change values of sliced array result[3] = 9.5*result.units self.assertFalse(all(self.signal1 == result)) def test_time_slice_out_of_boundries(self): targdataquant = self.data1quant targtimequant = self.time1quant targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = 0 t_stop = 2500000 result = self.signal1.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test_time_slice_empty(self): targdataquant = [] * pq.mV targtimequant = [] * pq.ms targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = 15 t_stop = 250 result = targ_signal.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) self.assertEqual(result.array_annotations, {}) self.assertIsInstance(result.array_annotations, ArrayDict) def test_time_slice_none_stop(self): targdataquant = [[1.0], [2.0], [3.0], [4.0], [5.0], [6.0], [7.0], [8.0], [9.0]] * pq.mV targtime = np.logspace(1, 5, 10) targtimequant = targtime[1:10] * pq.ms targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = 15 t_stop = None result = self.signal1.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test_time_slice_none_start(self): targdataquant = [[0.0], [1.0], [2.0], [3.0]] * pq.mV targtime = np.logspace(1, 5, 10) targtimequant = targtime[0:4] * pq.ms targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = None t_stop = 250 result = self.signal1.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test_time_slice_none_both(self): targdataquant = [[0.0], [1.0], [2.0], [3.0], [4.0], [5.0], [6.0], [7.0], [8.0], [9.0]] * pq.mV targtime = np.logspace(1, 5, 10) targtimequant = targtime[0:10] * pq.ms targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = None t_stop = None result = self.signal1.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test_time_slice_differnt_units(self): targdataquant = [[1.0], [2.0], [3.0]] * pq.mV targtime = np.logspace(1, 5, 10) targtimequant = targtime[1:4] * pq.ms targ_signal = IrregularlySampledSignal(targtimequant, signal=targdataquant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test') t_start = 15 t_stop = 250 t_start = 0.015 * pq.s t_stop = .250 * pq.s result = self.signal1.time_slice(t_start, t_stop) assert_array_equal(result, targ_signal) assert_array_equal(result.times, targtimequant) self.assertEqual(result.units, 1 * pq.mV) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) def test__time_slice_should_set_parents_to_None(self): # When timeslicing, a deep copy is made, # thus the reference to parent objects should be destroyed result = self.signal1.time_slice(1 * pq.ms, 3 * pq.ms) self.assertEqual(result.segment, None) self.assertEqual(result.channel_index, None) def test__deepcopy_should_set_parents_objects_to_None(self): # Deepcopy should destroy references to parents result = deepcopy(self.signal1) self.assertEqual(result.segment, None) self.assertEqual(result.channel_index, None) def test__time_shift_same_attributes(self): result = self.signal1.time_shift(1 * pq.ms) assert_same_attributes(result, self.signal1, exclude=['times', 't_start', 't_stop']) def test__time_shift_same_annotations(self): result = self.signal1.time_shift(1 * pq.ms) assert_same_annotations(result, self.signal1) def test__time_shift_same_array_annotations(self): result = self.signal1.time_shift(1 * pq.ms) assert_same_array_annotations(result, self.signal1) def test__time_shift_should_set_parents_to_None(self): # When time-shifting, a deep copy is made, # thus the reference to parent objects should be destroyed result = self.signal1.time_shift(1 * pq.ms) self.assertEqual(result.segment, None) self.assertEqual(result.channel_index, None) def test__time_shift_by_zero(self): shifted = self.signal1.time_shift(0 * pq.ms) assert_arrays_equal(shifted.times, self.signal1.times) def test__time_shift_same_units(self): shifted = self.signal1.time_shift(10 * pq.ms) assert_arrays_equal(shifted.times, self.signal1.times + 10 * pq.ms) def test__time_shift_different_units(self): shifted = self.signal1.time_shift(1 * pq.s) assert_arrays_equal(shifted.times, self.signal1.times + 1000 * pq.ms) def test_as_array(self): sig_as_arr = self.signal1.as_array() self.assertIsInstance(sig_as_arr, np.ndarray) assert_array_equal(self.data1, sig_as_arr.flat) def test_as_quantity(self): sig_as_q = self.signal1.as_quantity() self.assertIsInstance(sig_as_q, pq.Quantity) assert_array_equal(self.data1, sig_as_q.magnitude.flat) def test__copy_should_preserve_parent_objects(self): result = self.signal1.copy() self.assertIs(result.segment, self.signal1.segment) self.assertIs(result.channel_index, self.signal1.channel_index) class TestIrregularlySampledSignalCombination(unittest.TestCase): def setUp(self): self.data1 = np.arange(10.0) self.data1quant = self.data1 * pq.mV self.time1 = np.logspace(1, 5, 10) self.time1quant = self.time1 * pq.ms self.arr_ann = {'anno1': [23], 'anno2': ['A']} self.signal1 = IrregularlySampledSignal(self.time1quant, signal=self.data1quant, name='spam', description='eggs', file_origin='testfile.txt', arg1='test', array_annotations=self.arr_ann) def test__compliant(self): assert_neo_object_is_compliant(self.signal1) self.assertEqual(self.signal1.name, 'spam') self.assertEqual(self.signal1.description, 'eggs') self.assertEqual(self.signal1.file_origin, 'testfile.txt') self.assertEqual(self.signal1.annotations, {'arg1': 'test'}) assert_arrays_equal(self.signal1.array_annotations['anno1'], np.array([23])) assert_arrays_equal(self.signal1.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(self.signal1.array_annotations, ArrayDict) def test__add_const_quantity_should_preserve_data_complement(self): result = self.signal1 + 0.065 * pq.V self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) assert_array_equal(result.magnitude, self.data1.reshape(-1, 1) + 65) assert_array_equal(result.times, self.time1quant) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertEqual(result[9], 74 * pq.mV) def test__add_two_consistent_signals_should_preserve_data_complement(self): data2 = np.arange(10.0, 20.0) data2quant = data2 * pq.mV signal2 = IrregularlySampledSignal(self.time1quant, signal=data2quant) assert_neo_object_is_compliant(signal2) result = self.signal1 + signal2 self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) targ = IrregularlySampledSignal(self.time1quant, signal=np.arange(10.0, 30.0, 2.0), units="mV", name='spam', description='eggs', file_origin='testfile.txt', arg1='test') assert_neo_object_is_compliant(targ) assert_array_equal(result, targ) assert_array_equal(self.time1quant, targ.times) assert_array_equal(result.times, targ.times) assert_same_sub_schema(result, targ) def test__add_signals_with_inconsistent_times_AssertionError(self): signal2 = IrregularlySampledSignal(self.time1quant * 2., signal=np.arange(10.0), units="mV") assert_neo_object_is_compliant(signal2) self.assertRaises(ValueError, self.signal1.__add__, signal2) def test__add_signals_with_inconsistent_dimension_ValueError(self): signal2 = np.arange(20).reshape(2, 10) self.assertRaises(ValueError, self.signal1.__add__, signal2) def test__subtract_const_should_preserve_data_complement(self): result = self.signal1 - 65 * pq.mV self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertEqual(result[9], -56 * pq.mV) assert_array_equal(result.magnitude, (self.data1 - 65).reshape(-1, 1)) assert_array_equal(result.times, self.time1quant) def test__subtract_from_const_should_return_signal(self): result = 10 * pq.mV - self.signal1 self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertEqual(result[9], 1 * pq.mV) assert_array_equal(result.magnitude, (10 - self.data1).reshape(-1, 1)) assert_array_equal(result.times, self.time1quant) def test__mult_signal_by_const_float_should_preserve_data_complement(self): result = self.signal1 * 2. self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertEqual(result[9], 18 * pq.mV) assert_array_equal(result.magnitude, self.data1.reshape(-1, 1) * 2) assert_array_equal(result.times, self.time1quant) def test__mult_signal_by_const_array_should_preserve_data_complement(self): result = self.signal1 * np.array(2.) self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertEqual(result[9], 18 * pq.mV) assert_array_equal(result.magnitude, self.data1.reshape(-1, 1) * 2) assert_array_equal(result.times, self.time1quant) def test__divide_signal_by_const_should_preserve_data_complement(self): result = self.signal1 / 0.5 self.assertIsInstance(result, IrregularlySampledSignal) assert_neo_object_is_compliant(result) self.assertEqual(result.name, 'spam') self.assertEqual(result.description, 'eggs') self.assertEqual(result.file_origin, 'testfile.txt') self.assertEqual(result.annotations, {'arg1': 'test'}) assert_arrays_equal(result.array_annotations['anno1'], np.array([23])) assert_arrays_equal(result.array_annotations['anno2'], np.array(['A'])) self.assertIsInstance(result.array_annotations, ArrayDict) self.assertEqual(self.signal1[9], 9 * pq.mV) self.assertEqual(result[9], 18 * pq.mV) assert_array_equal(result.magnitude, self.data1.reshape(-1, 1) / 0.5) assert_array_equal(result.times, self.time1quant) @unittest.skipUnless(HAVE_IPYTHON, "requires IPython") def test__pretty(self): res = pretty(self.signal1) signal = self.signal1 targ = (("IrregularlySampledSignal with %d channels of length %d; units %s; datatype %s \n" "" % (signal.shape[1], signal.shape[0], signal.units.dimensionality.unicode, signal.dtype)) + ("name: '%s'\ndescription: '%s'\n" % (signal.name, signal.description)) + ("annotations: %s\n" % str(signal.annotations)) + ("sample times: %s" % (signal.times[:10],))) self.assertEqual(res, targ) def test__merge(self): data1 = np.arange(1000.0, 1066.0).reshape((11, 6)) * pq.uV data2 = np.arange(2.0, 2.033, 0.001).reshape((11, 3)) * pq.mV times1 = np.arange(11.0) * pq.ms times2 = np.arange(1.0, 12.0) * pq.ms arr_ann1 = {'anno1': np.arange(6), 'anno2': ['a', 'b', 'c', 'd', 'e', 'f']} arr_ann2 = {'anno1': np.arange(100, 103), 'anno3': []} signal1 = IrregularlySampledSignal(times1, data1, name='signal1', description='test signal', file_origin='testfile.txt', array_annotations=arr_ann1) signal2 = IrregularlySampledSignal(times1, data2, name='signal2', description='test signal', file_origin='testfile.txt', array_annotations=arr_ann2) signal3 = IrregularlySampledSignal(times2, data2, name='signal3', description='test signal', file_origin='testfile.txt') with warnings.catch_warnings(record=True) as w: merged12 = signal1.merge(signal2) self.assertTrue(len(w) == 1) self.assertEqual(w[0].category, UserWarning) self.assertSequenceEqual(str(w[0].message), "The following array annotations were " "omitted, because they were only present" " in one of the merged objects: " "['anno2'] from the one that was merged " "into and ['anno3'] from the one that " "was merged into the other") target_data12 = np.hstack([data1, data2.rescale(pq.uV)]) assert_neo_object_is_compliant(signal1) assert_neo_object_is_compliant(signal2) assert_neo_object_is_compliant(merged12) self.assertAlmostEqual(merged12[5, 0], 1030.0 * pq.uV, 9) self.assertAlmostEqual(merged12[5, 6], 2015.0 * pq.uV, 9) self.assertEqual(merged12.name, 'merge(signal1, signal2)') self.assertEqual(merged12.file_origin, 'testfile.txt') assert_arrays_equal(merged12.array_annotations['anno1'], np.array([0, 1, 2, 3, 4, 5, 100, 101, 102])) self.assertIsInstance(merged12.array_annotations, ArrayDict) assert_arrays_equal(merged12.magnitude, target_data12) self.assertRaises(MergeError, signal1.merge, signal3) class TestAnalogSignalFunctions(unittest.TestCase): def test__pickle(self): signal1 = IrregularlySampledSignal(np.arange(10.0) / 100 * pq.s, np.arange(10.0), units="mV") fobj = open('./pickle', 'wb') pickle.dump(signal1, fobj) fobj.close() fobj = open('./pickle', 'rb') try: signal2 = pickle.load(fobj) except ValueError: signal2 = None assert_array_equal(signal1, signal2) fobj.close() os.remove('./pickle') class TestIrregularlySampledSignalEquality(unittest.TestCase): def test__signals_with_different_times_should_be_not_equal(self): signal1 = IrregularlySampledSignal(np.arange(10.0) / 100 * pq.s, np.arange(10.0), units="mV") signal2 = IrregularlySampledSignal(np.arange(10.0) / 100 * pq.ms, np.arange(10.0), units="mV") self.assertNotEqual(signal1, signal2) if __name__ == "__main__": unittest.main()

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47,543

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0.076101

0.069359

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0.755933

0.72093

0.694338

0.667711

0.637407

0.611836

0

0.037789

0.234104

47,543

968

100

49.114669

0.768764

0.02238

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0.058299

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0

1

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null

0

1

0

3

7c2a8bdac271337f93e880a885f56ed4b95de212

1,345

py

Python

aio_pika/patterns/base.py

homersoft/aio-pika

7438e4ee86b8944d38907d3042c8d5605d68c81e

[ "Apache-2.0" ]

null

aio_pika/patterns/base.py

homersoft/aio-pika

7438e4ee86b8944d38907d3042c8d5605d68c81e

[ "Apache-2.0" ]

null

aio_pika/patterns/base.py

homersoft/aio-pika

7438e4ee86b8944d38907d3042c8d5605d68c81e

[ "Apache-2.0" ]

null

import pickle from typing import Any, Callable class Method: __slots__ = ( "name", "func", ) def __init__(self, name: str, func: Callable[..., Any]): self.name = name self.func = func def __getattr__(self, item: str) -> "Method": return Method(".".join((self.name, item)), func=self.func) def __call__(self, **kwargs: Any) -> Any: return self.func(self.name, kwargs=kwargs) class Proxy: __slots__ = ("func",) def __init__(self, func: Callable[..., Any]): self.func = func def __getattr__(self, item: str) -> Method: return Method(item, self.func) class Base: SERIALIZER = pickle CONTENT_TYPE = "application/python-pickle" def serialize(self, data: Any) -> bytes: """ Serialize data to the bytes. Uses `pickle` by default. You should overlap this method when you want to change serializer :param data: Data which will be serialized """ return self.SERIALIZER.dumps(data) def deserialize(self, data: bytes) -> Any: """ Deserialize data from bytes. Uses `pickle` by default. You should overlap this method when you want to change serializer :param data: Data which will be deserialized """ return self.SERIALIZER.loads(data)

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0.060606

0.027778

0.037879

0.388889

0

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1,345

52

74

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0.814815

0.246097

0

0.074074

0

0.047059

0.026738

0

1

0.259259

false

0

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0.111111

0.777778

0

null

0

null

0

1

0

1

0

3

7c3050e5fc98b66c7e1fa269352e4262de180b09

177

py

Python

test/todo/domain/test_frequency_db_name.py

MarkStefanovic/todo-api

fb6198511712df853e693787839533f0c9956178

[ "MIT" ]

null

test/todo/domain/test_frequency_db_name.py

MarkStefanovic/todo-api

fb6198511712df853e693787839533f0c9956178

[ "MIT" ]

null

test/todo/domain/test_frequency_db_name.py

MarkStefanovic/todo-api

fb6198511712df853e693787839533f0c9956178

[ "MIT" ]

null

from src import core if __name__ == "__main__": n = core.FrequencyDbName.DAILY assert n == "daily" print(n) print(repr(n)) x = core.FrequencyDbName("todo")

19.666667

36

0.632768

23

177

4.521739

0.652174

0.365385

0

0.231638

177

8

37

22.125

0.764706

0

0.096045

0

0.142857

1

0

false

0

0.142857

0

0.142857

0.285714

1

0

null

1

0

1

0

null

0

3

7c33481b6158455cf60525f5ced765bba063e1ba

447

py

Python

codestepbystep/count_to_by.py

aleeper/python_sandbox

2c320e043735f99fac68308fe2692c819cf5a636

[ "MIT" ]

null

codestepbystep/count_to_by.py

aleeper/python_sandbox

2c320e043735f99fac68308fe2692c819cf5a636

[ "MIT" ]

null

codestepbystep/count_to_by.py

aleeper/python_sandbox

2c320e043735f99fac68308fe2692c819cf5a636

[ "MIT" ]

null

def get_string_count_to_by(to, by): if by < 1: raise ValueError("'by' must be > 0") if to < 1: raise ValueError("'to' must be > 0") if to <= by: return str(to) return get_string_count_to_by(to - by, by) + ", " + str(to) def count_to_by(to, by): print(get_string_count_to_by(to, by)) def main(): count_to_by(10,1) count_to_by(34,5) count_to_by(17,3) if __name__ == '__main__': main()

21.285714

63

0.588367

78

447

3.012821

0.294872

0.204255

0.268085

0.187234

0.429787

0.280851

0

0.039514

0.263982

447

20

64

22.35

0.674772

0

0.09396

0

1

0.1875

false

0

0.3125

0.0625

0

null

1

0

null

0

3

7c3c1e943fef73d42bafa5e9c1b474901c314ea9

2,739

py

Python

aliyun-python-sdk-dms-enterprise/aliyunsdkdms_enterprise/request/v20181101/ListInstancesRequest.py

liumihust/aliyun-openapi-python-sdk

c7b5dd4befae4b9c59181654289f9272531207ef

[ "Apache-2.0" ]

null

aliyun-python-sdk-dms-enterprise/aliyunsdkdms_enterprise/request/v20181101/ListInstancesRequest.py

liumihust/aliyun-openapi-python-sdk

c7b5dd4befae4b9c59181654289f9272531207ef

[ "Apache-2.0" ]

1

2020-05-31T14:51:47.000Z

aliyun-python-sdk-dms-enterprise/aliyunsdkdms_enterprise/request/v20181101/ListInstancesRequest.py

liumihust/aliyun-openapi-python-sdk

c7b5dd4befae4b9c59181654289f9272531207ef

[ "Apache-2.0" ]

null

# Licensed to the Apache Software Foundation (ASF) under one # or more contributor license agreements. See the NOTICE file # distributed with this work for additional information # regarding copyright ownership. The ASF licenses this file # to you 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. from aliyunsdkcore.request import RpcRequest from aliyunsdkdms_enterprise.endpoint import endpoint_data class ListInstancesRequest(RpcRequest): def __init__(self): RpcRequest.__init__(self, 'dms-enterprise', '2018-11-01', 'ListInstances','dmsenterprise') if hasattr(self, "endpoint_map"): setattr(self, "endpoint_map", endpoint_data.getEndpointMap()) if hasattr(self, "endpoint_regional"): setattr(self, "endpoint_regional", endpoint_data.getEndpointRegional()) def get_SearchKey(self): return self.get_query_params().get('SearchKey') def set_SearchKey(self,SearchKey): self.add_query_param('SearchKey',SearchKey) def get_Tid(self): return self.get_query_params().get('Tid') def set_Tid(self,Tid): self.add_query_param('Tid',Tid) def get_InstanceState(self): return self.get_query_params().get('InstanceState') def set_InstanceState(self,InstanceState): self.add_query_param('InstanceState',InstanceState) def get_PageNumber(self): return self.get_query_params().get('PageNumber') def set_PageNumber(self,PageNumber): self.add_query_param('PageNumber',PageNumber) def get_NetType(self): return self.get_query_params().get('NetType') def set_NetType(self,NetType): self.add_query_param('NetType',NetType) def get_DbType(self): return self.get_query_params().get('DbType') def set_DbType(self,DbType): self.add_query_param('DbType',DbType) def get_EnvType(self): return self.get_query_params().get('EnvType') def set_EnvType(self,EnvType): self.add_query_param('EnvType',EnvType) def get_InstanceSource(self): return self.get_query_params().get('InstanceSource') def set_InstanceSource(self,InstanceSource): self.add_query_param('InstanceSource',InstanceSource) def get_PageSize(self): return self.get_query_params().get('PageSize') def set_PageSize(self,PageSize): self.add_query_param('PageSize',PageSize)

32.223529

92

0.758306

370

2,739

5.424324

0.310811

0.026906

0.06278

0.076233

0.139013

0

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0.135451

2,739

85

93

32.223529

0.842483

0.275283

0

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0

1

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false

0

0.044444

0.2

0.688889

0

null

0

null

0

1

0

1

0

3

7c4493dcbfca95c195eb7212d69f702245111712

620

py

Python

uds/utilities/__init__.py

mdabrowski1990/uds

1aee0c1de446ee3dd461706949504f2c218db1e8

[ "MIT" ]

18

2021-03-28T22:39:18.000Z

2022-02-13T21:50:37.000Z

uds/utilities/__init__.py

mdabrowski1990/uds

1aee0c1de446ee3dd461706949504f2c218db1e8

[ "MIT" ]

153

2021-02-09T09:27:05.000Z

2022-03-29T06:09:15.000Z

uds/utilities/__init__.py

mdabrowski1990/uds

1aee0c1de446ee3dd461706949504f2c218db1e8

[ "MIT" ]

1

2021-05-13T16:01:46.000Z

"""Various helper functions, classes and variables that are shared and reused within the project.""" from .enums import ValidatedEnum, ExtendableEnum, ByteEnum, NibbleEnum from .common_types import Nibble, RawByte, RawBytes, RawBytesTuple, RawBytesList, RawBytesSet, \ validate_nibble, validate_raw_bytes, validate_raw_byte, \ TimeMilliseconds from .bytes_operations import Endianness, EndiannessAlias, int_to_bytes_list, bytes_list_to_int from .custom_exceptions import ReassignmentError, InconsistentArgumentsError, AmbiguityError, \ UnusedArgumentError from .custom_warnings import UnusedArgumentWarning

56.363636

100

0.835484

67

620

7.507463

0.701493

0.043738

0

0.109677

620

10

101

62

0.911232

0.151613

0

1

0

true

0

0.625

0

0.625

0

null

0

null

0

1

0

1

0

1

0

3

7c45660fbf28183fb31bd82bbfed828e456a6d37

187,644

py

Python

tests/x509/test_x509.py

mattsb42-aws/cryptography

e687b8f7f40e30ef88e9de889c55cd7fdec99762

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause" ]

2

2021-01-30T13:23:54.000Z

2021-06-07T21:35:19.000Z

tests/x509/test_x509.py

mattsb42-aws/cryptography

e687b8f7f40e30ef88e9de889c55cd7fdec99762

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause" ]

7

2019-11-28T21:48:38.000Z

2020-08-02T18:06:40.000Z

tests/x509/test_x509.py

mattsb42-aws/cryptography

e687b8f7f40e30ef88e9de889c55cd7fdec99762

[ "PSF-2.0", "Apache-2.0", "BSD-3-Clause" ]

6

2020-05-29T21:46:30.000Z

2020-12-15T20:32:19.000Z

# -*- coding: utf-8 -*- # This file is dual licensed under the terms of the Apache License, Version # 2.0, and the BSD License. See the LICENSE file in the root of this repository # for complete details. from __future__ import absolute_import, division, print_function import binascii import collections import datetime import ipaddress import os import pytest import pytz import six from cryptography import utils, x509 from cryptography.exceptions import UnsupportedAlgorithm from cryptography.hazmat._der import ( BIT_STRING, CONSTRUCTED, CONTEXT_SPECIFIC, DERReader, GENERALIZED_TIME, INTEGER, OBJECT_IDENTIFIER, PRINTABLE_STRING, SEQUENCE, SET, UTC_TIME ) from cryptography.hazmat.backends.interfaces import ( DSABackend, EllipticCurveBackend, RSABackend, X509Backend ) from cryptography.hazmat.primitives import hashes, serialization from cryptography.hazmat.primitives.asymmetric import ( dsa, ec, ed25519, ed448, padding, rsa ) from cryptography.hazmat.primitives.asymmetric.utils import ( decode_dss_signature ) from cryptography.x509.name import _ASN1Type from cryptography.x509.oid import ( AuthorityInformationAccessOID, ExtendedKeyUsageOID, ExtensionOID, NameOID, SignatureAlgorithmOID ) from ..hazmat.primitives.fixtures_dsa import DSA_KEY_2048 from ..hazmat.primitives.fixtures_ec import EC_KEY_SECP256R1 from ..hazmat.primitives.fixtures_rsa import RSA_KEY_2048, RSA_KEY_512 from ..hazmat.primitives.test_ec import _skip_curve_unsupported from ..utils import load_vectors_from_file @utils.register_interface(x509.ExtensionType) class DummyExtension(object): oid = x509.ObjectIdentifier("1.2.3.4") @utils.register_interface(x509.GeneralName) class FakeGeneralName(object): def __init__(self, value): self._value = value value = utils.read_only_property("_value") def _load_cert(filename, loader, backend): cert = load_vectors_from_file( filename=filename, loader=lambda pemfile: loader(pemfile.read(), backend), mode="rb" ) return cert ParsedCertificate = collections.namedtuple( "ParsedCertificate", ["not_before_tag", "not_after_tag", "issuer", "subject"] ) def _parse_cert(der): # See the Certificate structured, defined in RFC 5280. with DERReader(der).read_single_element(SEQUENCE) as cert: tbs_cert = cert.read_element(SEQUENCE) # Skip outer signature algorithm _ = cert.read_element(SEQUENCE) # Skip signature _ = cert.read_element(BIT_STRING) with tbs_cert: # Skip version _ = tbs_cert.read_optional_element(CONTEXT_SPECIFIC | CONSTRUCTED | 0) # Skip serialNumber _ = tbs_cert.read_element(INTEGER) # Skip inner signature algorithm _ = tbs_cert.read_element(SEQUENCE) issuer = tbs_cert.read_element(SEQUENCE) validity = tbs_cert.read_element(SEQUENCE) subject = tbs_cert.read_element(SEQUENCE) # Skip subjectPublicKeyInfo _ = tbs_cert.read_element(SEQUENCE) # Skip issuerUniqueID _ = tbs_cert.read_optional_element(CONTEXT_SPECIFIC | CONSTRUCTED | 1) # Skip subjectUniqueID _ = tbs_cert.read_optional_element(CONTEXT_SPECIFIC | CONSTRUCTED | 2) # Skip extensions _ = tbs_cert.read_optional_element(CONTEXT_SPECIFIC | CONSTRUCTED | 3) with validity: not_before_tag, _ = validity.read_any_element() not_after_tag, _ = validity.read_any_element() return ParsedCertificate( not_before_tag=not_before_tag, not_after_tag=not_after_tag, issuer=issuer, subject=subject, ) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestCertificateRevocationList(object): def test_load_pem_crl(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) assert isinstance(crl, x509.CertificateRevocationList) fingerprint = binascii.hexlify(crl.fingerprint(hashes.SHA1())) assert fingerprint == b"3234b0cb4c0cedf6423724b736729dcfc9e441ef" assert isinstance(crl.signature_hash_algorithm, hashes.SHA256) assert ( crl.signature_algorithm_oid == SignatureAlgorithmOID.RSA_WITH_SHA256 ) def test_load_der_crl(self, backend): crl = _load_cert( os.path.join("x509", "PKITS_data", "crls", "GoodCACRL.crl"), x509.load_der_x509_crl, backend ) assert isinstance(crl, x509.CertificateRevocationList) fingerprint = binascii.hexlify(crl.fingerprint(hashes.SHA1())) assert fingerprint == b"dd3db63c50f4c4a13e090f14053227cb1011a5ad" assert isinstance(crl.signature_hash_algorithm, hashes.SHA256) def test_invalid_pem(self, backend): with pytest.raises(ValueError): x509.load_pem_x509_crl(b"notacrl", backend) def test_invalid_der(self, backend): with pytest.raises(ValueError): x509.load_der_x509_crl(b"notacrl", backend) def test_unknown_signature_algorithm(self, backend): crl = _load_cert( os.path.join( "x509", "custom", "crl_md2_unknown_crit_entry_ext.pem" ), x509.load_pem_x509_crl, backend ) with pytest.raises(UnsupportedAlgorithm): crl.signature_hash_algorithm() def test_issuer(self, backend): crl = _load_cert( os.path.join("x509", "PKITS_data", "crls", "GoodCACRL.crl"), x509.load_der_x509_crl, backend ) assert isinstance(crl.issuer, x509.Name) assert list(crl.issuer) == [ x509.NameAttribute(x509.OID_COUNTRY_NAME, u'US'), x509.NameAttribute( x509.OID_ORGANIZATION_NAME, u'Test Certificates 2011' ), x509.NameAttribute(x509.OID_COMMON_NAME, u'Good CA') ] assert crl.issuer.get_attributes_for_oid(x509.OID_COMMON_NAME) == [ x509.NameAttribute(x509.OID_COMMON_NAME, u'Good CA') ] def test_equality(self, backend): crl1 = _load_cert( os.path.join("x509", "PKITS_data", "crls", "GoodCACRL.crl"), x509.load_der_x509_crl, backend ) crl2 = _load_cert( os.path.join("x509", "PKITS_data", "crls", "GoodCACRL.crl"), x509.load_der_x509_crl, backend ) crl3 = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) assert crl1 == crl2 assert crl1 != crl3 assert crl1 != object() def test_update_dates(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) assert isinstance(crl.next_update, datetime.datetime) assert isinstance(crl.last_update, datetime.datetime) assert crl.next_update.isoformat() == "2016-01-01T00:00:00" assert crl.last_update.isoformat() == "2015-01-01T00:00:00" def test_revoked_cert_retrieval(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) for r in crl: assert isinstance(r, x509.RevokedCertificate) # Check that len() works for CRLs. assert len(crl) == 12 def test_get_revoked_certificate_by_serial_number(self, backend): crl = _load_cert( os.path.join( "x509", "PKITS_data", "crls", "LongSerialNumberCACRL.crl"), x509.load_der_x509_crl, backend ) serial_number = 725064303890588110203033396814564464046290047507 revoked = crl.get_revoked_certificate_by_serial_number(serial_number) assert revoked.serial_number == serial_number assert crl.get_revoked_certificate_by_serial_number(500) is None def test_revoked_cert_retrieval_retain_only_revoked(self, backend): """ This test attempts to trigger the crash condition described in https://github.com/pyca/cryptography/issues/2557 PyPy does gc at its own pace, so it will only be reliable on CPython. """ revoked = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend )[11] assert revoked.revocation_date == datetime.datetime(2015, 1, 1, 0, 0) assert revoked.serial_number == 11 def test_extensions(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_ian_aia_aki.pem"), x509.load_pem_x509_crl, backend ) crl_number = crl.extensions.get_extension_for_oid( ExtensionOID.CRL_NUMBER ) aki = crl.extensions.get_extension_for_class( x509.AuthorityKeyIdentifier ) aia = crl.extensions.get_extension_for_class( x509.AuthorityInformationAccess ) ian = crl.extensions.get_extension_for_class( x509.IssuerAlternativeName ) assert crl_number.value == x509.CRLNumber(1) assert crl_number.critical is False assert aki.value == x509.AuthorityKeyIdentifier( key_identifier=( b'yu\xbb\x84:\xcb,\xdez\t\xbe1\x1bC\xbc\x1c*MSX' ), authority_cert_issuer=None, authority_cert_serial_number=None ) assert aia.value == x509.AuthorityInformationAccess([ x509.AccessDescription( AuthorityInformationAccessOID.CA_ISSUERS, x509.DNSName(u"cryptography.io") ) ]) assert ian.value == x509.IssuerAlternativeName([ x509.UniformResourceIdentifier(u"https://cryptography.io"), ]) def test_delta_crl_indicator(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_delta_crl_indicator.pem"), x509.load_pem_x509_crl, backend ) dci = crl.extensions.get_extension_for_oid( ExtensionOID.DELTA_CRL_INDICATOR ) assert dci.value == x509.DeltaCRLIndicator(12345678901234567890) assert dci.critical is False def test_signature(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) assert crl.signature == binascii.unhexlify( b"536a5a0794f68267361e7bc2f19167a3e667a2ab141535616855d8deb2ba1af" b"9fd4546b1fe76b454eb436af7b28229fedff4634dfc9dd92254266219ae0ea8" b"75d9ff972e9a2da23d5945f073da18c50a4265bfed9ca16586347800ef49dd1" b"6856d7265f4f3c498a57f04dc04404e2bd2e2ada1f5697057aacef779a18371" b"c621edc9a5c2b8ec1716e8fa22feeb7fcec0ce9156c8d344aa6ae8d1a5d99d0" b"9386df36307df3b63c83908f4a61a0ff604c1e292ad63b349d1082ddd7ae1b7" b"c178bba995523ec6999310c54da5706549797bfb1230f5593ba7b4353dade4f" b"d2be13a57580a6eb20b5c4083f000abac3bf32cd8b75f23e4c8f4b3a79e1e2d" b"58a472b0" ) def test_tbs_certlist_bytes(self, backend): crl = _load_cert( os.path.join("x509", "PKITS_data", "crls", "GoodCACRL.crl"), x509.load_der_x509_crl, backend ) ca_cert = _load_cert( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, backend ) ca_cert.public_key().verify( crl.signature, crl.tbs_certlist_bytes, padding.PKCS1v15(), crl.signature_hash_algorithm ) def test_public_bytes_pem(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_empty.pem"), x509.load_pem_x509_crl, backend ) # Encode it to PEM and load it back. crl = x509.load_pem_x509_crl(crl.public_bytes( encoding=serialization.Encoding.PEM, ), backend) assert len(crl) == 0 assert crl.last_update == datetime.datetime(2015, 12, 20, 23, 44, 47) assert crl.next_update == datetime.datetime(2015, 12, 28, 0, 44, 47) def test_public_bytes_der(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) # Encode it to DER and load it back. crl = x509.load_der_x509_crl(crl.public_bytes( encoding=serialization.Encoding.DER, ), backend) assert len(crl) == 12 assert crl.last_update == datetime.datetime(2015, 1, 1, 0, 0, 0) assert crl.next_update == datetime.datetime(2016, 1, 1, 0, 0, 0) @pytest.mark.parametrize( ("cert_path", "loader_func", "encoding"), [ ( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, serialization.Encoding.PEM, ), ( os.path.join("x509", "PKITS_data", "crls", "GoodCACRL.crl"), x509.load_der_x509_crl, serialization.Encoding.DER, ), ] ) def test_public_bytes_match(self, cert_path, loader_func, encoding, backend): crl_bytes = load_vectors_from_file( cert_path, lambda pemfile: pemfile.read(), mode="rb" ) crl = loader_func(crl_bytes, backend) serialized = crl.public_bytes(encoding) assert serialized == crl_bytes def test_public_bytes_invalid_encoding(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_empty.pem"), x509.load_pem_x509_crl, backend ) with pytest.raises(TypeError): crl.public_bytes('NotAnEncoding') def test_verify_bad(self, backend): crl = _load_cert( os.path.join("x509", "custom", "invalid_signature.pem"), x509.load_pem_x509_crl, backend ) crt = _load_cert( os.path.join("x509", "custom", "invalid_signature.pem"), x509.load_pem_x509_certificate, backend ) assert not crl.is_signature_valid(crt.public_key()) def test_verify_good(self, backend): crl = _load_cert( os.path.join("x509", "custom", "valid_signature.pem"), x509.load_pem_x509_crl, backend ) crt = _load_cert( os.path.join("x509", "custom", "valid_signature.pem"), x509.load_pem_x509_certificate, backend ) assert crl.is_signature_valid(crt.public_key()) def test_verify_argument_must_be_a_public_key(self, backend): crl = _load_cert( os.path.join("x509", "custom", "valid_signature.pem"), x509.load_pem_x509_crl, backend ) with pytest.raises(TypeError): crl.is_signature_valid("not a public key") with pytest.raises(TypeError): crl.is_signature_valid(object) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestRevokedCertificate(object): def test_revoked_basics(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) for i, rev in enumerate(crl): assert isinstance(rev, x509.RevokedCertificate) assert isinstance(rev.serial_number, int) assert isinstance(rev.revocation_date, datetime.datetime) assert isinstance(rev.extensions, x509.Extensions) assert rev.serial_number == i assert rev.revocation_date.isoformat() == "2015-01-01T00:00:00" def test_revoked_extensions(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) exp_issuer = [ x509.DirectoryName(x509.Name([ x509.NameAttribute(x509.OID_COUNTRY_NAME, u"US"), x509.NameAttribute(x509.OID_COMMON_NAME, u"cryptography.io"), ])) ] # First revoked cert doesn't have extensions, test if it is handled # correctly. rev0 = crl[0] # It should return an empty Extensions object. assert isinstance(rev0.extensions, x509.Extensions) assert len(rev0.extensions) == 0 with pytest.raises(x509.ExtensionNotFound): rev0.extensions.get_extension_for_oid(x509.OID_CRL_REASON) with pytest.raises(x509.ExtensionNotFound): rev0.extensions.get_extension_for_oid(x509.OID_CERTIFICATE_ISSUER) with pytest.raises(x509.ExtensionNotFound): rev0.extensions.get_extension_for_oid(x509.OID_INVALIDITY_DATE) # Test manual retrieval of extension values. rev1 = crl[1] assert isinstance(rev1.extensions, x509.Extensions) reason = rev1.extensions.get_extension_for_class( x509.CRLReason).value assert reason == x509.CRLReason(x509.ReasonFlags.unspecified) issuer = rev1.extensions.get_extension_for_class( x509.CertificateIssuer).value assert issuer == x509.CertificateIssuer(exp_issuer) date = rev1.extensions.get_extension_for_class( x509.InvalidityDate).value assert date == x509.InvalidityDate(datetime.datetime(2015, 1, 1, 0, 0)) # Check if all reason flags can be found in the CRL. flags = set(x509.ReasonFlags) for rev in crl: try: r = rev.extensions.get_extension_for_class(x509.CRLReason) except x509.ExtensionNotFound: # Not all revoked certs have a reason extension. pass else: flags.discard(r.value.reason) assert len(flags) == 0 def test_no_revoked_certs(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_empty.pem"), x509.load_pem_x509_crl, backend ) assert len(crl) == 0 def test_duplicate_entry_ext(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_dup_entry_ext.pem"), x509.load_pem_x509_crl, backend ) with pytest.raises(x509.DuplicateExtension): crl[0].extensions def test_unsupported_crit_entry_ext(self, backend): crl = _load_cert( os.path.join( "x509", "custom", "crl_md2_unknown_crit_entry_ext.pem" ), x509.load_pem_x509_crl, backend ) ext = crl[0].extensions.get_extension_for_oid( x509.ObjectIdentifier("1.2.3.4") ) assert ext.value.value == b"\n\x01\x00" def test_unsupported_reason(self, backend): crl = _load_cert( os.path.join( "x509", "custom", "crl_unsupported_reason.pem" ), x509.load_pem_x509_crl, backend ) with pytest.raises(ValueError): crl[0].extensions def test_invalid_cert_issuer_ext(self, backend): crl = _load_cert( os.path.join( "x509", "custom", "crl_inval_cert_issuer_entry_ext.pem" ), x509.load_pem_x509_crl, backend ) with pytest.raises(ValueError): crl[0].extensions def test_indexing(self, backend): crl = _load_cert( os.path.join("x509", "custom", "crl_all_reasons.pem"), x509.load_pem_x509_crl, backend ) with pytest.raises(IndexError): crl[-13] with pytest.raises(IndexError): crl[12] assert crl[-1].serial_number == crl[11].serial_number assert len(crl[2:4]) == 2 assert crl[2:4][0].serial_number == crl[2].serial_number assert crl[2:4][1].serial_number == crl[3].serial_number def test_get_revoked_certificate_doesnt_reorder(self, backend): private_key = RSA_KEY_2048.private_key(backend) last_update = datetime.datetime(2002, 1, 1, 12, 1) next_update = datetime.datetime(2030, 1, 1, 12, 1) builder = x509.CertificateRevocationListBuilder().issuer_name( x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u"cryptography.io CA") ]) ).last_update( last_update ).next_update( next_update ) for i in [2, 500, 3, 49, 7, 1]: revoked_cert = x509.RevokedCertificateBuilder().serial_number( i ).revocation_date( datetime.datetime(2012, 1, 1, 1, 1) ).build(backend) builder = builder.add_revoked_certificate(revoked_cert) crl = builder.sign(private_key, hashes.SHA256(), backend) assert crl[0].serial_number == 2 assert crl[2].serial_number == 3 # make sure get_revoked_certificate_by_serial_number doesn't affect # ordering after being invoked crl.get_revoked_certificate_by_serial_number(500) assert crl[0].serial_number == 2 assert crl[2].serial_number == 3 @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestRSACertificate(object): def test_load_pem_cert(self, backend): cert = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) assert isinstance(cert, x509.Certificate) assert cert.serial_number == 11559813051657483483 fingerprint = binascii.hexlify(cert.fingerprint(hashes.SHA1())) assert fingerprint == b"2b619ed04bfc9c3b08eb677d272192286a0947a8" assert isinstance(cert.signature_hash_algorithm, hashes.SHA1) assert ( cert.signature_algorithm_oid == SignatureAlgorithmOID.RSA_WITH_SHA1 ) def test_negative_serial_number(self, backend): cert = _load_cert( os.path.join("x509", "custom", "negative_serial.pem"), x509.load_pem_x509_certificate, backend, ) assert cert.serial_number == -18008675309 def test_alternate_rsa_with_sha1_oid(self, backend): cert = _load_cert( os.path.join("x509", "alternate-rsa-sha1-oid.pem"), x509.load_pem_x509_certificate, backend ) assert isinstance(cert.signature_hash_algorithm, hashes.SHA1) assert ( cert.signature_algorithm_oid == SignatureAlgorithmOID._RSA_WITH_SHA1 ) def test_load_der_cert(self, backend): cert = _load_cert( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, backend ) assert isinstance(cert, x509.Certificate) assert cert.serial_number == 2 fingerprint = binascii.hexlify(cert.fingerprint(hashes.SHA1())) assert fingerprint == b"6f49779533d565e8b7c1062503eab41492c38e4d" assert isinstance(cert.signature_hash_algorithm, hashes.SHA256) def test_signature(self, backend): cert = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) assert cert.signature == binascii.unhexlify( b"8e0f72fcbebe4755abcaf76c8ce0bae17cde4db16291638e1b1ce04a93cdb4c" b"44a3486070986c5a880c14fdf8497e7d289b2630ccb21d24a3d1aa1b2d87482" b"07f3a1e16ccdf8daa8a7ea1a33d49774f513edf09270bd8e665b6300a10f003" b"66a59076905eb63cf10a81a0ca78a6ef3127f6cb2f6fb7f947fce22a30d8004" b"8c243ba2c1a54c425fe12310e8a737638f4920354d4cce25cbd9dea25e6a2fe" b"0d8579a5c8d929b9275be221975479f3f75075bcacf09526523b5fd67f7683f" b"3cda420fabb1e9e6fc26bc0649cf61bb051d6932fac37066bb16f55903dfe78" b"53dc5e505e2a10fbba4f9e93a0d3b53b7fa34b05d7ba6eef869bfc34b8e514f" b"d5419f75" ) assert len(cert.signature) == cert.public_key().key_size // 8 def test_tbs_certificate_bytes(self, backend): cert = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) assert cert.tbs_certificate_bytes == binascii.unhexlify( b"308202d8a003020102020900a06cb4b955f7f4db300d06092a864886f70d010" b"10505003058310b3009060355040613024155311330110603550408130a536f" b"6d652d53746174653121301f060355040a1318496e7465726e6574205769646" b"769747320507479204c74643111300f0603550403130848656c6c6f20434130" b"1e170d3134313132363231343132305a170d3134313232363231343132305a3" b"058310b3009060355040613024155311330110603550408130a536f6d652d53" b"746174653121301f060355040a1318496e7465726e657420576964676974732" b"0507479204c74643111300f0603550403130848656c6c6f2043413082012230" b"0d06092a864886f70d01010105000382010f003082010a0282010100b03af70" b"2059e27f1e2284b56bbb26c039153bf81f295b73a49132990645ede4d2da0a9" b"13c42e7d38d3589a00d3940d194f6e6d877c2ef812da22a275e83d8be786467" b"48b4e7f23d10e873fd72f57a13dec732fc56ab138b1bb308399bb412cd73921" b"4ef714e1976e09603405e2556299a05522510ac4574db5e9cb2cf5f99e8f48c" b"1696ab3ea2d6d2ddab7d4e1b317188b76a572977f6ece0a4ad396f0150e7d8b" b"1a9986c0cb90527ec26ca56e2914c270d2a198b632fa8a2fda55079d3d39864" b"b6fb96ddbe331cacb3cb8783a8494ccccd886a3525078847ca01ca5f803e892" b"14403e8a4b5499539c0b86f7a0daa45b204a8e079d8a5b03db7ba1ba3d7011a" b"70203010001a381bc3081b9301d0603551d0e04160414d8e89dc777e4472656" b"f1864695a9f66b7b0400ae3081890603551d23048181307f8014d8e89dc777e" b"4472656f1864695a9f66b7b0400aea15ca45a3058310b300906035504061302" b"4155311330110603550408130a536f6d652d53746174653121301f060355040" b"a1318496e7465726e6574205769646769747320507479204c74643111300f06" b"03550403130848656c6c6f204341820900a06cb4b955f7f4db300c0603551d1" b"3040530030101ff" ) cert.public_key().verify( cert.signature, cert.tbs_certificate_bytes, padding.PKCS1v15(), cert.signature_hash_algorithm ) def test_issuer(self, backend): cert = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "Validpre2000UTCnotBeforeDateTest3EE.crt" ), x509.load_der_x509_certificate, backend ) issuer = cert.issuer assert isinstance(issuer, x509.Name) assert list(issuer) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute( NameOID.ORGANIZATION_NAME, u'Test Certificates 2011' ), x509.NameAttribute(NameOID.COMMON_NAME, u'Good CA') ] assert issuer.get_attributes_for_oid(NameOID.COMMON_NAME) == [ x509.NameAttribute(NameOID.COMMON_NAME, u'Good CA') ] def test_all_issuer_name_types(self, backend): cert = _load_cert( os.path.join( "x509", "custom", "all_supported_names.pem" ), x509.load_pem_x509_certificate, backend ) issuer = cert.issuer assert isinstance(issuer, x509.Name) assert list(issuer) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.COUNTRY_NAME, u'CA'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Illinois'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Chicago'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'Zero, LLC'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'One, LLC'), x509.NameAttribute(NameOID.COMMON_NAME, u'common name 0'), x509.NameAttribute(NameOID.COMMON_NAME, u'common name 1'), x509.NameAttribute(NameOID.ORGANIZATIONAL_UNIT_NAME, u'OU 0'), x509.NameAttribute(NameOID.ORGANIZATIONAL_UNIT_NAME, u'OU 1'), x509.NameAttribute(NameOID.DN_QUALIFIER, u'dnQualifier0'), x509.NameAttribute(NameOID.DN_QUALIFIER, u'dnQualifier1'), x509.NameAttribute(NameOID.SERIAL_NUMBER, u'123'), x509.NameAttribute(NameOID.SERIAL_NUMBER, u'456'), x509.NameAttribute(NameOID.TITLE, u'Title 0'), x509.NameAttribute(NameOID.TITLE, u'Title 1'), x509.NameAttribute(NameOID.SURNAME, u'Surname 0'), x509.NameAttribute(NameOID.SURNAME, u'Surname 1'), x509.NameAttribute(NameOID.GIVEN_NAME, u'Given Name 0'), x509.NameAttribute(NameOID.GIVEN_NAME, u'Given Name 1'), x509.NameAttribute(NameOID.PSEUDONYM, u'Incognito 0'), x509.NameAttribute(NameOID.PSEUDONYM, u'Incognito 1'), x509.NameAttribute(NameOID.GENERATION_QUALIFIER, u'Last Gen'), x509.NameAttribute(NameOID.GENERATION_QUALIFIER, u'Next Gen'), x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u'dc0'), x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u'dc1'), x509.NameAttribute(NameOID.EMAIL_ADDRESS, u'test0@test.local'), x509.NameAttribute(NameOID.EMAIL_ADDRESS, u'test1@test.local'), ] def test_subject(self, backend): cert = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "Validpre2000UTCnotBeforeDateTest3EE.crt" ), x509.load_der_x509_certificate, backend ) subject = cert.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute( NameOID.ORGANIZATION_NAME, u'Test Certificates 2011' ), x509.NameAttribute( NameOID.COMMON_NAME, u'Valid pre2000 UTC notBefore Date EE Certificate Test3' ) ] assert subject.get_attributes_for_oid(NameOID.COMMON_NAME) == [ x509.NameAttribute( NameOID.COMMON_NAME, u'Valid pre2000 UTC notBefore Date EE Certificate Test3' ) ] def test_unicode_name(self, backend): cert = _load_cert( os.path.join( "x509", "custom", "utf8_common_name.pem" ), x509.load_pem_x509_certificate, backend ) assert cert.subject.get_attributes_for_oid(NameOID.COMMON_NAME) == [ x509.NameAttribute( NameOID.COMMON_NAME, u'We heart UTF8!\u2122' ) ] assert cert.issuer.get_attributes_for_oid(NameOID.COMMON_NAME) == [ x509.NameAttribute( NameOID.COMMON_NAME, u'We heart UTF8!\u2122' ) ] def test_non_ascii_dns_name(self, backend): cert = _load_cert( os.path.join("x509", "utf8-dnsname.pem"), x509.load_pem_x509_certificate, backend ) san = cert.extensions.get_extension_for_class( x509.SubjectAlternativeName ).value names = san.get_values_for_type(x509.DNSName) assert names == [ u'partner.biztositas.hu', u'biztositas.hu', u'*.biztositas.hu', u'biztos\xedt\xe1s.hu', u'*.biztos\xedt\xe1s.hu', u'xn--biztosts-fza2j.hu', u'*.xn--biztosts-fza2j.hu' ] def test_all_subject_name_types(self, backend): cert = _load_cert( os.path.join( "x509", "custom", "all_supported_names.pem" ), x509.load_pem_x509_certificate, backend ) subject = cert.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'AU'), x509.NameAttribute(NameOID.COUNTRY_NAME, u'DE'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'California'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'New York'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'San Francisco'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Ithaca'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'Org Zero, LLC'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'Org One, LLC'), x509.NameAttribute(NameOID.COMMON_NAME, u'CN 0'), x509.NameAttribute(NameOID.COMMON_NAME, u'CN 1'), x509.NameAttribute( NameOID.ORGANIZATIONAL_UNIT_NAME, u'Engineering 0' ), x509.NameAttribute( NameOID.ORGANIZATIONAL_UNIT_NAME, u'Engineering 1' ), x509.NameAttribute(NameOID.DN_QUALIFIER, u'qualified0'), x509.NameAttribute(NameOID.DN_QUALIFIER, u'qualified1'), x509.NameAttribute(NameOID.SERIAL_NUMBER, u'789'), x509.NameAttribute(NameOID.SERIAL_NUMBER, u'012'), x509.NameAttribute(NameOID.TITLE, u'Title IX'), x509.NameAttribute(NameOID.TITLE, u'Title X'), x509.NameAttribute(NameOID.SURNAME, u'Last 0'), x509.NameAttribute(NameOID.SURNAME, u'Last 1'), x509.NameAttribute(NameOID.GIVEN_NAME, u'First 0'), x509.NameAttribute(NameOID.GIVEN_NAME, u'First 1'), x509.NameAttribute(NameOID.PSEUDONYM, u'Guy Incognito 0'), x509.NameAttribute(NameOID.PSEUDONYM, u'Guy Incognito 1'), x509.NameAttribute(NameOID.GENERATION_QUALIFIER, u'32X'), x509.NameAttribute(NameOID.GENERATION_QUALIFIER, u'Dreamcast'), x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u'dc2'), x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u'dc3'), x509.NameAttribute(NameOID.EMAIL_ADDRESS, u'test2@test.local'), x509.NameAttribute(NameOID.EMAIL_ADDRESS, u'test3@test.local'), ] def test_load_good_ca_cert(self, backend): cert = _load_cert( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, backend ) assert cert.not_valid_before == datetime.datetime(2010, 1, 1, 8, 30) assert cert.not_valid_after == datetime.datetime(2030, 12, 31, 8, 30) assert cert.serial_number == 2 public_key = cert.public_key() assert isinstance(public_key, rsa.RSAPublicKey) assert cert.version is x509.Version.v3 fingerprint = binascii.hexlify(cert.fingerprint(hashes.SHA1())) assert fingerprint == b"6f49779533d565e8b7c1062503eab41492c38e4d" def test_utc_pre_2000_not_before_cert(self, backend): cert = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "Validpre2000UTCnotBeforeDateTest3EE.crt" ), x509.load_der_x509_certificate, backend ) assert cert.not_valid_before == datetime.datetime(1950, 1, 1, 12, 1) def test_pre_2000_utc_not_after_cert(self, backend): cert = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "Invalidpre2000UTCEEnotAfterDateTest7EE.crt" ), x509.load_der_x509_certificate, backend ) assert cert.not_valid_after == datetime.datetime(1999, 1, 1, 12, 1) def test_post_2000_utc_cert(self, backend): cert = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) assert cert.not_valid_before == datetime.datetime( 2014, 11, 26, 21, 41, 20 ) assert cert.not_valid_after == datetime.datetime( 2014, 12, 26, 21, 41, 20 ) def test_generalized_time_not_before_cert(self, backend): cert = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "ValidGeneralizedTimenotBeforeDateTest4EE.crt" ), x509.load_der_x509_certificate, backend ) assert cert.not_valid_before == datetime.datetime(2002, 1, 1, 12, 1) assert cert.not_valid_after == datetime.datetime(2030, 12, 31, 8, 30) assert cert.version is x509.Version.v3 def test_generalized_time_not_after_cert(self, backend): cert = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "ValidGeneralizedTimenotAfterDateTest8EE.crt" ), x509.load_der_x509_certificate, backend ) assert cert.not_valid_before == datetime.datetime(2010, 1, 1, 8, 30) assert cert.not_valid_after == datetime.datetime(2050, 1, 1, 12, 1) assert cert.version is x509.Version.v3 def test_invalid_version_cert(self, backend): cert = _load_cert( os.path.join("x509", "custom", "invalid_version.pem"), x509.load_pem_x509_certificate, backend ) with pytest.raises(x509.InvalidVersion) as exc: cert.version assert exc.value.parsed_version == 7 def test_eq(self, backend): cert = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) cert2 = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) assert cert == cert2 def test_ne(self, backend): cert = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) cert2 = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "ValidGeneralizedTimenotAfterDateTest8EE.crt" ), x509.load_der_x509_certificate, backend ) assert cert != cert2 assert cert != object() def test_hash(self, backend): cert1 = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) cert2 = _load_cert( os.path.join("x509", "custom", "post2000utctime.pem"), x509.load_pem_x509_certificate, backend ) cert3 = _load_cert( os.path.join( "x509", "PKITS_data", "certs", "ValidGeneralizedTimenotAfterDateTest8EE.crt" ), x509.load_der_x509_certificate, backend ) assert hash(cert1) == hash(cert2) assert hash(cert1) != hash(cert3) def test_version_1_cert(self, backend): cert = _load_cert( os.path.join("x509", "v1_cert.pem"), x509.load_pem_x509_certificate, backend ) assert cert.version is x509.Version.v1 def test_invalid_pem(self, backend): with pytest.raises(ValueError): x509.load_pem_x509_certificate(b"notacert", backend) def test_invalid_der(self, backend): with pytest.raises(ValueError): x509.load_der_x509_certificate(b"notacert", backend) def test_unsupported_signature_hash_algorithm_cert(self, backend): cert = _load_cert( os.path.join("x509", "verisign_md2_root.pem"), x509.load_pem_x509_certificate, backend ) with pytest.raises(UnsupportedAlgorithm): cert.signature_hash_algorithm def test_public_bytes_pem(self, backend): # Load an existing certificate. cert = _load_cert( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, backend ) # Encode it to PEM and load it back. cert = x509.load_pem_x509_certificate(cert.public_bytes( encoding=serialization.Encoding.PEM, ), backend) # We should recover what we had to start with. assert cert.not_valid_before == datetime.datetime(2010, 1, 1, 8, 30) assert cert.not_valid_after == datetime.datetime(2030, 12, 31, 8, 30) assert cert.serial_number == 2 public_key = cert.public_key() assert isinstance(public_key, rsa.RSAPublicKey) assert cert.version is x509.Version.v3 fingerprint = binascii.hexlify(cert.fingerprint(hashes.SHA1())) assert fingerprint == b"6f49779533d565e8b7c1062503eab41492c38e4d" def test_public_bytes_der(self, backend): # Load an existing certificate. cert = _load_cert( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, backend ) # Encode it to DER and load it back. cert = x509.load_der_x509_certificate(cert.public_bytes( encoding=serialization.Encoding.DER, ), backend) # We should recover what we had to start with. assert cert.not_valid_before == datetime.datetime(2010, 1, 1, 8, 30) assert cert.not_valid_after == datetime.datetime(2030, 12, 31, 8, 30) assert cert.serial_number == 2 public_key = cert.public_key() assert isinstance(public_key, rsa.RSAPublicKey) assert cert.version is x509.Version.v3 fingerprint = binascii.hexlify(cert.fingerprint(hashes.SHA1())) assert fingerprint == b"6f49779533d565e8b7c1062503eab41492c38e4d" def test_public_bytes_invalid_encoding(self, backend): cert = _load_cert( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, backend ) with pytest.raises(TypeError): cert.public_bytes('NotAnEncoding') @pytest.mark.parametrize( ("cert_path", "loader_func", "encoding"), [ ( os.path.join("x509", "v1_cert.pem"), x509.load_pem_x509_certificate, serialization.Encoding.PEM, ), ( os.path.join("x509", "PKITS_data", "certs", "GoodCACert.crt"), x509.load_der_x509_certificate, serialization.Encoding.DER, ), ] ) def test_public_bytes_match(self, cert_path, loader_func, encoding, backend): cert_bytes = load_vectors_from_file( cert_path, lambda pemfile: pemfile.read(), mode="rb" ) cert = loader_func(cert_bytes, backend) serialized = cert.public_bytes(encoding) assert serialized == cert_bytes def test_certificate_repr(self, backend): cert = _load_cert( os.path.join( "x509", "cryptography.io.pem" ), x509.load_pem_x509_certificate, backend ) assert repr(cert) == ( "<Certificate(subject=<Name(OU=GT48742965,OU=See www.rapidssl.com" "/resources/cps (c)14,OU=Domain Control Validated - RapidSSL(R)," "CN=www.cryptography.io)>, ...)>" ) def test_parse_tls_feature_extension(self, backend): cert = _load_cert( os.path.join("x509", "tls-feature-ocsp-staple.pem"), x509.load_pem_x509_certificate, backend ) ext = cert.extensions.get_extension_for_class(x509.TLSFeature) assert ext.critical is False assert ext.value == x509.TLSFeature( [x509.TLSFeatureType.status_request] ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestRSACertificateRequest(object): @pytest.mark.parametrize( ("path", "loader_func"), [ [ os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr ], [ os.path.join("x509", "requests", "rsa_sha1.der"), x509.load_der_x509_csr ], ] ) def test_load_rsa_certificate_request(self, path, loader_func, backend): request = _load_cert(path, loader_func, backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) assert ( request.signature_algorithm_oid == SignatureAlgorithmOID.RSA_WITH_SHA1 ) public_key = request.public_key() assert isinstance(public_key, rsa.RSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), ] extensions = request.extensions assert isinstance(extensions, x509.Extensions) assert list(extensions) == [] @pytest.mark.parametrize( "loader_func", [x509.load_pem_x509_csr, x509.load_der_x509_csr] ) def test_invalid_certificate_request(self, loader_func, backend): with pytest.raises(ValueError): loader_func(b"notacsr", backend) def test_unsupported_signature_hash_algorithm_request(self, backend): request = _load_cert( os.path.join("x509", "requests", "rsa_md4.pem"), x509.load_pem_x509_csr, backend ) with pytest.raises(UnsupportedAlgorithm): request.signature_hash_algorithm def test_duplicate_extension(self, backend): request = _load_cert( os.path.join( "x509", "requests", "two_basic_constraints.pem" ), x509.load_pem_x509_csr, backend ) with pytest.raises(x509.DuplicateExtension) as exc: request.extensions assert exc.value.oid == ExtensionOID.BASIC_CONSTRAINTS def test_unsupported_critical_extension(self, backend): request = _load_cert( os.path.join( "x509", "requests", "unsupported_extension_critical.pem" ), x509.load_pem_x509_csr, backend ) ext = request.extensions.get_extension_for_oid( x509.ObjectIdentifier('1.2.3.4') ) assert ext.value.value == b"value" def test_unsupported_extension(self, backend): request = _load_cert( os.path.join( "x509", "requests", "unsupported_extension.pem" ), x509.load_pem_x509_csr, backend ) extensions = request.extensions assert len(extensions) == 1 assert extensions[0].oid == x509.ObjectIdentifier("1.2.3.4") assert extensions[0].value == x509.UnrecognizedExtension( x509.ObjectIdentifier("1.2.3.4"), b"value" ) def test_request_basic_constraints(self, backend): request = _load_cert( os.path.join( "x509", "requests", "basic_constraints.pem" ), x509.load_pem_x509_csr, backend ) extensions = request.extensions assert isinstance(extensions, x509.Extensions) assert list(extensions) == [ x509.Extension( ExtensionOID.BASIC_CONSTRAINTS, True, x509.BasicConstraints(ca=True, path_length=1), ), ] def test_subject_alt_name(self, backend): request = _load_cert( os.path.join("x509", "requests", "san_rsa_sha1.pem"), x509.load_pem_x509_csr, backend, ) ext = request.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(ext.value) == [ x509.DNSName(u"cryptography.io"), x509.DNSName(u"sub.cryptography.io"), ] def test_public_bytes_pem(self, backend): # Load an existing CSR. request = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) # Encode it to PEM and load it back. request = x509.load_pem_x509_csr(request.public_bytes( encoding=serialization.Encoding.PEM, ), backend) # We should recover what we had to start with. assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, rsa.RSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), ] def test_public_bytes_der(self, backend): # Load an existing CSR. request = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) # Encode it to DER and load it back. request = x509.load_der_x509_csr(request.public_bytes( encoding=serialization.Encoding.DER, ), backend) # We should recover what we had to start with. assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, rsa.RSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), ] def test_signature(self, backend): request = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert request.signature == binascii.unhexlify( b"8364c86ffbbfe0bfc9a21f831256658ca8989741b80576d36f08a934603a43b1" b"837246d00167a518abb1de7b51a1e5b7ebea14944800818b1a923c804f120a0d" b"624f6310ef79e8612755c2b01dcc7f59dfdbce0db3f2630f185f504b8c17af80" b"cbd364fa5fda68337153930948226cd4638287a0aed6524d3006885c19028a1e" b"e2f5a91d6e77dbaa0b49996ee0a0c60b55b61bd080a08bb34aa7f3e07e91f37f" b"6a11645be2d8654c1570dcda145ed7cc92017f7d53225d7f283f3459ec5bda41" b"cf6dd75d43676c543483385226b7e4fa29c8739f1b0eaf199613593991979862" b"e36181e8c4c270c354b7f52c128db1b70639823324c7ea24791b7bc3d7005f3b" ) def test_tbs_certrequest_bytes(self, backend): request = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert request.tbs_certrequest_bytes == binascii.unhexlify( b"308201840201003057310b3009060355040613025553310e300c060355040813" b"055465786173310f300d0603550407130641757374696e310d300b060355040a" b"130450794341311830160603550403130f63727970746f6772617068792e696f" b"30820122300d06092a864886f70d01010105000382010f003082010a02820101" b"00a840a78460cb861066dfa3045a94ba6cf1b7ab9d24c761cffddcc2cb5e3f1d" b"c3e4be253e7039ef14fe9d6d2304f50d9f2e1584c51530ab75086f357138bff7" b"b854d067d1d5f384f1f2f2c39cc3b15415e2638554ef8402648ae3ef08336f22" b"b7ecc6d4331c2b21c3091a7f7a9518180754a646640b60419e4cc6f5c798110a" b"7f030a639fe87e33b4776dfcd993940ec776ab57a181ad8598857976dc303f9a" b"573ca619ab3fe596328e92806b828683edc17cc256b41948a2bfa8d047d2158d" b"3d8e069aa05fa85b3272abb1c4b4422b6366f3b70e642377b145cd6259e5d3e7" b"db048d51921e50766a37b1b130ee6b11f507d20a834001e8de16a92c14f2e964" b"a30203010001a000" ) request.public_key().verify( request.signature, request.tbs_certrequest_bytes, padding.PKCS1v15(), request.signature_hash_algorithm ) def test_public_bytes_invalid_encoding(self, backend): request = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) with pytest.raises(TypeError): request.public_bytes('NotAnEncoding') def test_signature_invalid(self, backend): request = _load_cert( os.path.join("x509", "requests", "invalid_signature.pem"), x509.load_pem_x509_csr, backend ) assert not request.is_signature_valid def test_signature_valid(self, backend): request = _load_cert( os.path.join("x509", "requests", "rsa_sha256.pem"), x509.load_pem_x509_csr, backend ) assert request.is_signature_valid @pytest.mark.parametrize( ("request_path", "loader_func", "encoding"), [ ( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, serialization.Encoding.PEM, ), ( os.path.join("x509", "requests", "rsa_sha1.der"), x509.load_der_x509_csr, serialization.Encoding.DER, ), ] ) def test_public_bytes_match(self, request_path, loader_func, encoding, backend): request_bytes = load_vectors_from_file( request_path, lambda pemfile: pemfile.read(), mode="rb" ) request = loader_func(request_bytes, backend) serialized = request.public_bytes(encoding) assert serialized == request_bytes def test_eq(self, backend): request1 = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) request2 = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert request1 == request2 def test_ne(self, backend): request1 = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) request2 = _load_cert( os.path.join("x509", "requests", "san_rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert request1 != request2 assert request1 != object() def test_hash(self, backend): request1 = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) request2 = _load_cert( os.path.join("x509", "requests", "rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) request3 = _load_cert( os.path.join("x509", "requests", "san_rsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert hash(request1) == hash(request2) assert hash(request1) != hash(request3) def test_build_cert(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), ])).public_key( subject_private_key.public_key() ).add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA1(), backend) assert cert.version is x509.Version.v3 assert cert.not_valid_before == not_valid_before assert cert.not_valid_after == not_valid_after basic_constraints = cert.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is False assert basic_constraints.value.path_length is None subject_alternative_name = cert.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(subject_alternative_name.value) == [ x509.DNSName(u"cryptography.io"), ] def test_build_cert_private_type_encoding(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) name = x509.Name([ x509.NameAttribute( NameOID.STATE_OR_PROVINCE_NAME, u'Texas', _ASN1Type.PrintableString), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), x509.NameAttribute( NameOID.COMMON_NAME, u'cryptography.io', _ASN1Type.IA5String), ]) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name( name ).subject_name( name ).public_key( subject_private_key.public_key() ).not_valid_before( not_valid_before ).not_valid_after(not_valid_after) cert = builder.sign(issuer_private_key, hashes.SHA256(), backend) for dn in (cert.subject, cert.issuer): assert dn.get_attributes_for_oid( NameOID.STATE_OR_PROVINCE_NAME )[0]._type == _ASN1Type.PrintableString assert dn.get_attributes_for_oid( NameOID.STATE_OR_PROVINCE_NAME )[0]._type == _ASN1Type.PrintableString assert dn.get_attributes_for_oid( NameOID.LOCALITY_NAME )[0]._type == _ASN1Type.UTF8String def test_build_cert_printable_string_country_name(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.JURISDICTION_COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.JURISDICTION_COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ])).public_key( subject_private_key.public_key() ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA256(), backend) parsed = _parse_cert(cert.public_bytes(serialization.Encoding.DER)) subject = parsed.subject issuer = parsed.issuer def read_next_rdn_value_tag(reader): # Assume each RDN has a single attribute. with reader.read_element(SET) as rdn: attribute = rdn.read_element(SEQUENCE) with attribute: _ = attribute.read_element(OBJECT_IDENTIFIER) tag, value = attribute.read_any_element() return tag # Check that each value was encoded as an ASN.1 PRINTABLESTRING. assert read_next_rdn_value_tag(subject) == PRINTABLE_STRING assert read_next_rdn_value_tag(issuer) == PRINTABLE_STRING if ( # This only works correctly in OpenSSL 1.1.0f+ and 1.0.2l+ backend._lib.CRYPTOGRAPHY_OPENSSL_110F_OR_GREATER or ( backend._lib.CRYPTOGRAPHY_OPENSSL_102L_OR_GREATER and not backend._lib.CRYPTOGRAPHY_OPENSSL_110_OR_GREATER ) ): assert read_next_rdn_value_tag(subject) == PRINTABLE_STRING assert read_next_rdn_value_tag(issuer) == PRINTABLE_STRING class TestCertificateBuilder(object): @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_checks_for_unsupported_extensions(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( private_key.public_key() ).serial_number( 777 ).not_valid_before( datetime.datetime(1999, 1, 1) ).not_valid_after( datetime.datetime(2020, 1, 1) ).add_extension( DummyExtension(), False ) with pytest.raises(NotImplementedError): builder.sign(private_key, hashes.SHA1(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_encode_nonstandard_aia(self, backend): private_key = RSA_KEY_2048.private_key(backend) aia = x509.AuthorityInformationAccess([ x509.AccessDescription( x509.ObjectIdentifier("2.999.7"), x509.UniformResourceIdentifier(u"http://example.com") ), ]) builder = x509.CertificateBuilder().subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( private_key.public_key() ).serial_number( 777 ).not_valid_before( datetime.datetime(1999, 1, 1) ).not_valid_after( datetime.datetime(2020, 1, 1) ).add_extension( aia, False ) builder.sign(private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_subject_dn_asn1_types(self, backend): private_key = RSA_KEY_2048.private_key(backend) name = x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u"mysite.com"), x509.NameAttribute(NameOID.COUNTRY_NAME, u"US"), x509.NameAttribute(NameOID.LOCALITY_NAME, u"value"), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u"value"), x509.NameAttribute(NameOID.STREET_ADDRESS, u"value"), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u"value"), x509.NameAttribute(NameOID.ORGANIZATIONAL_UNIT_NAME, u"value"), x509.NameAttribute(NameOID.SERIAL_NUMBER, u"value"), x509.NameAttribute(NameOID.SURNAME, u"value"), x509.NameAttribute(NameOID.GIVEN_NAME, u"value"), x509.NameAttribute(NameOID.TITLE, u"value"), x509.NameAttribute(NameOID.GENERATION_QUALIFIER, u"value"), x509.NameAttribute(NameOID.X500_UNIQUE_IDENTIFIER, u"value"), x509.NameAttribute(NameOID.DN_QUALIFIER, u"value"), x509.NameAttribute(NameOID.PSEUDONYM, u"value"), x509.NameAttribute(NameOID.USER_ID, u"value"), x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u"value"), x509.NameAttribute(NameOID.EMAIL_ADDRESS, u"value"), x509.NameAttribute(NameOID.JURISDICTION_COUNTRY_NAME, u"US"), x509.NameAttribute(NameOID.JURISDICTION_LOCALITY_NAME, u"value"), x509.NameAttribute( NameOID.JURISDICTION_STATE_OR_PROVINCE_NAME, u"value" ), x509.NameAttribute(NameOID.BUSINESS_CATEGORY, u"value"), x509.NameAttribute(NameOID.POSTAL_ADDRESS, u"value"), x509.NameAttribute(NameOID.POSTAL_CODE, u"value"), ]) cert = x509.CertificateBuilder().subject_name( name ).issuer_name( name ).public_key( private_key.public_key() ).serial_number( 777 ).not_valid_before( datetime.datetime(1999, 1, 1) ).not_valid_after( datetime.datetime(2020, 1, 1) ).sign(private_key, hashes.SHA256(), backend) for dn in (cert.subject, cert.issuer): for oid, asn1_type in TestNameAttribute.EXPECTED_TYPES: assert dn.get_attributes_for_oid( oid )[0]._type == asn1_type @pytest.mark.parametrize( ("not_valid_before", "not_valid_after"), [ [datetime.datetime(1970, 2, 1), datetime.datetime(9999, 1, 1)], [datetime.datetime(1970, 2, 1), datetime.datetime(9999, 12, 31)], ] ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_extreme_times(self, not_valid_before, not_valid_after, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( private_key.public_key() ).serial_number( 777 ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(private_key, hashes.SHA256(), backend) assert cert.not_valid_before == not_valid_before assert cert.not_valid_after == not_valid_after parsed = _parse_cert(cert.public_bytes(serialization.Encoding.DER)) assert parsed.not_before_tag == UTC_TIME assert parsed.not_after_tag == GENERALIZED_TIME @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_no_subject_name(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) with pytest.raises(ValueError): builder.sign(subject_private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_no_issuer_name(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( 777 ).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) with pytest.raises(ValueError): builder.sign(subject_private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_no_public_key(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) with pytest.raises(ValueError): builder.sign(subject_private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_no_not_valid_before(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) with pytest.raises(ValueError): builder.sign(subject_private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_no_not_valid_after(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.sign(subject_private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_no_serial_number(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) with pytest.raises(ValueError): builder.sign(subject_private_key, hashes.SHA256(), backend) def test_issuer_name_must_be_a_name_type(self): builder = x509.CertificateBuilder() with pytest.raises(TypeError): builder.issuer_name("subject") with pytest.raises(TypeError): builder.issuer_name(object) def test_issuer_name_may_only_be_set_once(self): name = x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) builder = x509.CertificateBuilder().issuer_name(name) with pytest.raises(ValueError): builder.issuer_name(name) def test_subject_name_must_be_a_name_type(self): builder = x509.CertificateBuilder() with pytest.raises(TypeError): builder.subject_name("subject") with pytest.raises(TypeError): builder.subject_name(object) def test_subject_name_may_only_be_set_once(self): name = x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) builder = x509.CertificateBuilder().subject_name(name) with pytest.raises(ValueError): builder.subject_name(name) def test_not_valid_before_after_not_valid_after(self): builder = x509.CertificateBuilder() builder = builder.not_valid_after( datetime.datetime(2002, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.not_valid_before( datetime.datetime(2003, 1, 1, 12, 1) ) def test_not_valid_after_before_not_valid_before(self): builder = x509.CertificateBuilder() builder = builder.not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.not_valid_after( datetime.datetime(2001, 1, 1, 12, 1) ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_public_key_must_be_public_key(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder() with pytest.raises(TypeError): builder.public_key(private_key) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_public_key_may_only_be_set_once(self, backend): private_key = RSA_KEY_2048.private_key(backend) public_key = private_key.public_key() builder = x509.CertificateBuilder().public_key(public_key) with pytest.raises(ValueError): builder.public_key(public_key) def test_serial_number_must_be_an_integer_type(self): with pytest.raises(TypeError): x509.CertificateBuilder().serial_number(10.0) def test_serial_number_must_be_non_negative(self): with pytest.raises(ValueError): x509.CertificateBuilder().serial_number(-1) def test_serial_number_must_be_positive(self): with pytest.raises(ValueError): x509.CertificateBuilder().serial_number(0) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_minimal_serial_number(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( 1 ).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'RU'), ])).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'RU'), ])).public_key( subject_private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) cert = builder.sign(subject_private_key, hashes.SHA256(), backend) assert cert.serial_number == 1 @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_biggest_serial_number(self, backend): subject_private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder().serial_number( (1 << 159) - 1 ).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'RU'), ])).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'RU'), ])).public_key( subject_private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ) cert = builder.sign(subject_private_key, hashes.SHA256(), backend) assert cert.serial_number == (1 << 159) - 1 def test_serial_number_must_be_less_than_160_bits_long(self): with pytest.raises(ValueError): x509.CertificateBuilder().serial_number(1 << 159) def test_serial_number_may_only_be_set_once(self): builder = x509.CertificateBuilder().serial_number(10) with pytest.raises(ValueError): builder.serial_number(20) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_aware_not_valid_after(self, backend): time = datetime.datetime(2012, 1, 16, 22, 43) tz = pytz.timezone("US/Pacific") time = tz.localize(time) utc_time = datetime.datetime(2012, 1, 17, 6, 43) private_key = RSA_KEY_2048.private_key(backend) cert_builder = x509.CertificateBuilder().not_valid_after(time) cert_builder = cert_builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( utc_time - datetime.timedelta(days=365) ) cert = cert_builder.sign(private_key, hashes.SHA256(), backend) assert cert.not_valid_after == utc_time @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_earliest_time(self, backend): time = datetime.datetime(1950, 1, 1) private_key = RSA_KEY_2048.private_key(backend) cert_builder = x509.CertificateBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( time ).not_valid_after( time ) cert = cert_builder.sign(private_key, hashes.SHA256(), backend) assert cert.not_valid_before == time assert cert.not_valid_after == time parsed = _parse_cert(cert.public_bytes(serialization.Encoding.DER)) assert parsed.not_before_tag == UTC_TIME assert parsed.not_after_tag == UTC_TIME def test_invalid_not_valid_after(self): with pytest.raises(TypeError): x509.CertificateBuilder().not_valid_after(104204304504) with pytest.raises(TypeError): x509.CertificateBuilder().not_valid_after(datetime.time()) with pytest.raises(ValueError): x509.CertificateBuilder().not_valid_after( datetime.datetime(1940, 8, 10) ) def test_not_valid_after_may_only_be_set_once(self): builder = x509.CertificateBuilder().not_valid_after( datetime.datetime.now() ) with pytest.raises(ValueError): builder.not_valid_after( datetime.datetime.now() ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_aware_not_valid_before(self, backend): time = datetime.datetime(2012, 1, 16, 22, 43) tz = pytz.timezone("US/Pacific") time = tz.localize(time) utc_time = datetime.datetime(2012, 1, 17, 6, 43) private_key = RSA_KEY_2048.private_key(backend) cert_builder = x509.CertificateBuilder().not_valid_before(time) cert_builder = cert_builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_after( utc_time + datetime.timedelta(days=366) ) cert = cert_builder.sign(private_key, hashes.SHA256(), backend) assert cert.not_valid_before == utc_time def test_invalid_not_valid_before(self): with pytest.raises(TypeError): x509.CertificateBuilder().not_valid_before(104204304504) with pytest.raises(TypeError): x509.CertificateBuilder().not_valid_before(datetime.time()) with pytest.raises(ValueError): x509.CertificateBuilder().not_valid_before( datetime.datetime(1940, 8, 10) ) def test_not_valid_before_may_only_be_set_once(self): builder = x509.CertificateBuilder().not_valid_before( datetime.datetime.now() ) with pytest.raises(ValueError): builder.not_valid_before( datetime.datetime.now() ) def test_add_extension_checks_for_duplicates(self): builder = x509.CertificateBuilder().add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ) with pytest.raises(ValueError): builder.add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ) def test_add_invalid_extension_type(self): builder = x509.CertificateBuilder() with pytest.raises(TypeError): builder.add_extension(object(), False) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.parametrize( "algorithm", [ object(), None ] ) def test_sign_with_unsupported_hash(self, algorithm, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder() builder = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2032, 1, 1, 12, 1) ) with pytest.raises(TypeError): builder.sign(private_key, algorithm, backend) @pytest.mark.supported( only_if=lambda backend: backend.ed25519_supported(), skip_message="Requires OpenSSL with Ed25519 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_sign_with_unsupported_hash_ed25519(self, backend): private_key = ed25519.Ed25519PrivateKey.generate() builder = x509.CertificateBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2032, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) @pytest.mark.supported( only_if=lambda backend: backend.ed448_supported(), skip_message="Requires OpenSSL with Ed448 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_sign_with_unsupported_hash_ed448(self, backend): private_key = ed448.Ed448PrivateKey.generate() builder = x509.CertificateBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2032, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.supported( only_if=lambda backend: backend.hash_supported(hashes.MD5()), skip_message="Requires OpenSSL with MD5 support" ) def test_sign_rsa_with_md5(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder() builder = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2032, 1, 1, 12, 1) ) cert = builder.sign(private_key, hashes.MD5(), backend) assert isinstance(cert.signature_hash_algorithm, hashes.MD5) @pytest.mark.requires_backend_interface(interface=DSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.supported( only_if=lambda backend: backend.hash_supported(hashes.MD5()), skip_message="Requires OpenSSL with MD5 support" ) def test_sign_dsa_with_md5(self, backend): private_key = DSA_KEY_2048.private_key(backend) builder = x509.CertificateBuilder() builder = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2032, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.MD5(), backend) @pytest.mark.requires_backend_interface(interface=EllipticCurveBackend) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.supported( only_if=lambda backend: backend.hash_supported(hashes.MD5()), skip_message="Requires OpenSSL with MD5 support" ) def test_sign_ec_with_md5(self, backend): _skip_curve_unsupported(backend, ec.SECP256R1()) private_key = EC_KEY_SECP256R1.private_key(backend) builder = x509.CertificateBuilder() builder = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).serial_number( 1 ).public_key( private_key.public_key() ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2032, 1, 1, 12, 1) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.MD5(), backend) @pytest.mark.requires_backend_interface(interface=DSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_dsa_private_key(self, backend): issuer_private_key = DSA_KEY_2048.private_key(backend) subject_private_key = DSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA1(), backend) assert cert.version is x509.Version.v3 assert cert.not_valid_before == not_valid_before assert cert.not_valid_after == not_valid_after basic_constraints = cert.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is False assert basic_constraints.value.path_length is None subject_alternative_name = cert.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(subject_alternative_name.value) == [ x509.DNSName(u"cryptography.io"), ] @pytest.mark.requires_backend_interface(interface=EllipticCurveBackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_ec_private_key(self, backend): _skip_curve_unsupported(backend, ec.SECP256R1()) issuer_private_key = ec.generate_private_key(ec.SECP256R1(), backend) subject_private_key = ec.generate_private_key(ec.SECP256R1(), backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA1(), backend) assert cert.version is x509.Version.v3 assert cert.not_valid_before == not_valid_before assert cert.not_valid_after == not_valid_after basic_constraints = cert.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is False assert basic_constraints.value.path_length is None subject_alternative_name = cert.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(subject_alternative_name.value) == [ x509.DNSName(u"cryptography.io"), ] @pytest.mark.supported( only_if=lambda backend: backend.ed25519_supported(), skip_message="Requires OpenSSL with Ed25519 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_ed25519(self, backend): issuer_private_key = ed25519.Ed25519PrivateKey.generate() subject_private_key = ed25519.Ed25519PrivateKey.generate() not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, None, backend) issuer_private_key.public_key().verify( cert.signature, cert.tbs_certificate_bytes ) assert cert.signature_algorithm_oid == SignatureAlgorithmOID.ED25519 assert cert.signature_hash_algorithm is None assert isinstance(cert.public_key(), ed25519.Ed25519PublicKey) assert cert.version is x509.Version.v3 assert cert.not_valid_before == not_valid_before assert cert.not_valid_after == not_valid_after basic_constraints = cert.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is False assert basic_constraints.value.path_length is None subject_alternative_name = cert.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(subject_alternative_name.value) == [ x509.DNSName(u"cryptography.io"), ] @pytest.mark.supported( only_if=lambda backend: backend.ed25519_supported(), skip_message="Requires OpenSSL with Ed25519 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.requires_backend_interface(interface=RSABackend) def test_build_cert_with_public_ed25519_rsa_sig(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = ed25519.Ed25519PrivateKey.generate() not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA256(), backend) issuer_private_key.public_key().verify( cert.signature, cert.tbs_certificate_bytes, padding.PKCS1v15(), cert.signature_hash_algorithm ) assert cert.signature_algorithm_oid == ( SignatureAlgorithmOID.RSA_WITH_SHA256 ) assert isinstance(cert.signature_hash_algorithm, hashes.SHA256) assert isinstance(cert.public_key(), ed25519.Ed25519PublicKey) @pytest.mark.supported( only_if=lambda backend: backend.ed448_supported(), skip_message="Requires OpenSSL with Ed448 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_ed448(self, backend): issuer_private_key = ed448.Ed448PrivateKey.generate() subject_private_key = ed448.Ed448PrivateKey.generate() not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( x509.BasicConstraints(ca=False, path_length=None), True, ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, None, backend) issuer_private_key.public_key().verify( cert.signature, cert.tbs_certificate_bytes ) assert cert.signature_algorithm_oid == SignatureAlgorithmOID.ED448 assert cert.signature_hash_algorithm is None assert isinstance(cert.public_key(), ed448.Ed448PublicKey) assert cert.version is x509.Version.v3 assert cert.not_valid_before == not_valid_before assert cert.not_valid_after == not_valid_after basic_constraints = cert.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is False assert basic_constraints.value.path_length is None subject_alternative_name = cert.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(subject_alternative_name.value) == [ x509.DNSName(u"cryptography.io"), ] @pytest.mark.supported( only_if=lambda backend: backend.ed448_supported(), skip_message="Requires OpenSSL with Ed448 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.requires_backend_interface(interface=RSABackend) def test_build_cert_with_public_ed448_rsa_sig(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = ed448.Ed448PrivateKey.generate() not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA256(), backend) issuer_private_key.public_key().verify( cert.signature, cert.tbs_certificate_bytes, padding.PKCS1v15(), cert.signature_hash_algorithm ) assert cert.signature_algorithm_oid == ( SignatureAlgorithmOID.RSA_WITH_SHA256 ) assert isinstance(cert.signature_hash_algorithm, hashes.SHA256) assert isinstance(cert.public_key(), ed448.Ed448PublicKey) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_rsa_key_too_small(self, backend): issuer_private_key = RSA_KEY_512.private_key(backend) subject_private_key = RSA_KEY_512.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) with pytest.raises(ValueError): builder.sign(issuer_private_key, hashes.SHA512(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.parametrize( "add_ext", [ x509.SubjectAlternativeName( [ # These examples exist to verify compatibility with # certificates that have utf8 encoded data in the ia5string x509.DNSName._init_without_validation(u'a\xedt\xe1s.test'), x509.RFC822Name._init_without_validation( u'test@a\xedt\xe1s.test' ), x509.UniformResourceIdentifier._init_without_validation( u'http://a\xedt\xe1s.test' ), ] ), x509.CertificatePolicies([ x509.PolicyInformation( x509.ObjectIdentifier("2.16.840.1.12345.1.2.3.4.1"), [u"http://other.com/cps"] ) ]), x509.CertificatePolicies([ x509.PolicyInformation( x509.ObjectIdentifier("2.16.840.1.12345.1.2.3.4.1"), None ) ]), x509.CertificatePolicies([ x509.PolicyInformation( x509.ObjectIdentifier("2.16.840.1.12345.1.2.3.4.1"), [ u"http://example.com/cps", u"http://other.com/cps", x509.UserNotice( x509.NoticeReference(u"my org", [1, 2, 3, 4]), u"thing" ) ] ) ]), x509.CertificatePolicies([ x509.PolicyInformation( x509.ObjectIdentifier("2.16.840.1.12345.1.2.3.4.1"), [ u"http://example.com/cps", x509.UserNotice( x509.NoticeReference(u"UTF8\u2122'", [1, 2, 3, 4]), u"We heart UTF8!\u2122" ) ] ) ]), x509.CertificatePolicies([ x509.PolicyInformation( x509.ObjectIdentifier("2.16.840.1.12345.1.2.3.4.1"), [x509.UserNotice(None, u"thing")] ) ]), x509.CertificatePolicies([ x509.PolicyInformation( x509.ObjectIdentifier("2.16.840.1.12345.1.2.3.4.1"), [ x509.UserNotice( x509.NoticeReference(u"my org", [1, 2, 3, 4]), None ) ] ) ]), x509.IssuerAlternativeName([ x509.DNSName(u"myissuer"), x509.RFC822Name(u"email@domain.com"), ]), x509.ExtendedKeyUsage([ ExtendedKeyUsageOID.CLIENT_AUTH, ExtendedKeyUsageOID.SERVER_AUTH, ExtendedKeyUsageOID.CODE_SIGNING, ]), x509.InhibitAnyPolicy(3), x509.TLSFeature([x509.TLSFeatureType.status_request]), x509.TLSFeature([x509.TLSFeatureType.status_request_v2]), x509.TLSFeature([ x509.TLSFeatureType.status_request, x509.TLSFeatureType.status_request_v2 ]), x509.NameConstraints( permitted_subtrees=[ x509.IPAddress(ipaddress.IPv4Network(u"192.168.0.0/24")), x509.IPAddress(ipaddress.IPv4Network(u"192.168.0.0/29")), x509.IPAddress(ipaddress.IPv4Network(u"127.0.0.1/32")), x509.IPAddress(ipaddress.IPv4Network(u"8.0.0.0/8")), x509.IPAddress(ipaddress.IPv4Network(u"0.0.0.0/0")), x509.IPAddress( ipaddress.IPv6Network(u"FF:0:0:0:0:0:0:0/96") ), x509.IPAddress( ipaddress.IPv6Network(u"FF:FF:0:0:0:0:0:0/128") ), ], excluded_subtrees=[x509.DNSName(u"name.local")] ), x509.NameConstraints( permitted_subtrees=[ x509.IPAddress(ipaddress.IPv4Network(u"0.0.0.0/0")), ], excluded_subtrees=None ), x509.NameConstraints( permitted_subtrees=None, excluded_subtrees=[x509.DNSName(u"name.local")] ), x509.PolicyConstraints( require_explicit_policy=None, inhibit_policy_mapping=1 ), x509.PolicyConstraints( require_explicit_policy=3, inhibit_policy_mapping=1 ), x509.PolicyConstraints( require_explicit_policy=0, inhibit_policy_mapping=None ), x509.CRLDistributionPoints([ x509.DistributionPoint( full_name=None, relative_name=x509.RelativeDistinguishedName([ x509.NameAttribute( NameOID.COMMON_NAME, u"indirect CRL for indirectCRL CA3" ), ]), reasons=None, crl_issuer=[x509.DirectoryName( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u"US"), x509.NameAttribute( NameOID.ORGANIZATION_NAME, u"Test Certificates 2011" ), x509.NameAttribute( NameOID.ORGANIZATIONAL_UNIT_NAME, u"indirectCRL CA3 cRLIssuer" ), ]) )], ) ]), x509.CRLDistributionPoints([ x509.DistributionPoint( full_name=[x509.DirectoryName( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u"US"), ]) )], relative_name=None, reasons=None, crl_issuer=[x509.DirectoryName( x509.Name([ x509.NameAttribute( NameOID.ORGANIZATION_NAME, u"cryptography Testing" ), ]) )], ) ]), x509.CRLDistributionPoints([ x509.DistributionPoint( full_name=[ x509.UniformResourceIdentifier( u"http://myhost.com/myca.crl" ), x509.UniformResourceIdentifier( u"http://backup.myhost.com/myca.crl" ) ], relative_name=None, reasons=frozenset([ x509.ReasonFlags.key_compromise, x509.ReasonFlags.ca_compromise ]), crl_issuer=[x509.DirectoryName( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u"US"), x509.NameAttribute( NameOID.COMMON_NAME, u"cryptography CA" ), ]) )], ) ]), x509.CRLDistributionPoints([ x509.DistributionPoint( full_name=[x509.UniformResourceIdentifier( u"http://domain.com/some.crl" )], relative_name=None, reasons=frozenset([ x509.ReasonFlags.key_compromise, x509.ReasonFlags.ca_compromise, x509.ReasonFlags.affiliation_changed, x509.ReasonFlags.superseded, x509.ReasonFlags.privilege_withdrawn, x509.ReasonFlags.cessation_of_operation, x509.ReasonFlags.aa_compromise, x509.ReasonFlags.certificate_hold, ]), crl_issuer=None ) ]), x509.CRLDistributionPoints([ x509.DistributionPoint( full_name=None, relative_name=None, reasons=None, crl_issuer=[x509.DirectoryName( x509.Name([ x509.NameAttribute( NameOID.COMMON_NAME, u"cryptography CA" ), ]) )], ) ]), x509.CRLDistributionPoints([ x509.DistributionPoint( full_name=[x509.UniformResourceIdentifier( u"http://domain.com/some.crl" )], relative_name=None, reasons=frozenset([x509.ReasonFlags.aa_compromise]), crl_issuer=None ) ]), x509.FreshestCRL([ x509.DistributionPoint( full_name=[x509.UniformResourceIdentifier( u"http://domain.com/some.crl" )], relative_name=None, reasons=frozenset([ x509.ReasonFlags.key_compromise, x509.ReasonFlags.ca_compromise, x509.ReasonFlags.affiliation_changed, x509.ReasonFlags.superseded, x509.ReasonFlags.privilege_withdrawn, x509.ReasonFlags.cessation_of_operation, x509.ReasonFlags.aa_compromise, x509.ReasonFlags.certificate_hold, ]), crl_issuer=None ) ]), x509.FreshestCRL([ x509.DistributionPoint( full_name=None, relative_name=x509.RelativeDistinguishedName([ x509.NameAttribute( NameOID.COMMON_NAME, u"indirect CRL for indirectCRL CA3" ), ]), reasons=None, crl_issuer=None, ) ]), x509.FreshestCRL([ x509.DistributionPoint( full_name=None, relative_name=x509.RelativeDistinguishedName([ x509.NameAttribute( NameOID.COMMON_NAME, u"indirect CRL for indirectCRL CA3" ), x509.NameAttribute( NameOID.COUNTRY_NAME, u"US" ), ]), reasons=None, crl_issuer=None, ) ]), ] ) def test_ext(self, add_ext, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) cert = x509.CertificateBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ).public_key( subject_private_key.public_key() ).serial_number( 123 ).add_extension( add_ext, critical=False ).sign(issuer_private_key, hashes.SHA256(), backend) ext = cert.extensions.get_extension_for_class(type(add_ext)) assert ext.critical is False assert ext.value == add_ext @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_key_usage(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) cert = x509.CertificateBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ).public_key( subject_private_key.public_key() ).serial_number( 123 ).add_extension( x509.KeyUsage( digital_signature=True, content_commitment=True, key_encipherment=False, data_encipherment=False, key_agreement=False, key_cert_sign=True, crl_sign=False, encipher_only=False, decipher_only=False ), critical=False ).sign(issuer_private_key, hashes.SHA256(), backend) ext = cert.extensions.get_extension_for_oid(ExtensionOID.KEY_USAGE) assert ext.critical is False assert ext.value == x509.KeyUsage( digital_signature=True, content_commitment=True, key_encipherment=False, data_encipherment=False, key_agreement=False, key_cert_sign=True, crl_sign=False, encipher_only=False, decipher_only=False ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_ca_request_with_path_length_none(self, backend): private_key = RSA_KEY_2048.private_key(backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=None), critical=True ).sign(private_key, hashes.SHA1(), backend) loaded_request = x509.load_pem_x509_csr( request.public_bytes(encoding=serialization.Encoding.PEM), backend ) subject = loaded_request.subject assert isinstance(subject, x509.Name) basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.path_length is None @pytest.mark.parametrize( "unrecognized", [ x509.UnrecognizedExtension( x509.ObjectIdentifier("1.2.3.4.5"), b"abcdef", ) ] ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_unrecognized_extension(self, backend, unrecognized): private_key = RSA_KEY_2048.private_key(backend) cert = x509.CertificateBuilder().subject_name( x509.Name([x509.NameAttribute(x509.OID_COUNTRY_NAME, u'US')]) ).issuer_name( x509.Name([x509.NameAttribute(x509.OID_COUNTRY_NAME, u'US')]) ).not_valid_before( datetime.datetime(2002, 1, 1, 12, 1) ).not_valid_after( datetime.datetime(2030, 12, 31, 8, 30) ).public_key( private_key.public_key() ).serial_number( 123 ).add_extension( unrecognized, critical=False ).sign(private_key, hashes.SHA256(), backend) ext = cert.extensions.get_extension_for_oid(unrecognized.oid) assert ext.value == unrecognized @pytest.mark.requires_backend_interface(interface=X509Backend) class TestCertificateSigningRequestBuilder(object): @pytest.mark.requires_backend_interface(interface=RSABackend) def test_sign_invalid_hash_algorithm(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([]) ) with pytest.raises(TypeError): builder.sign(private_key, 'NotAHash', backend) @pytest.mark.supported( only_if=lambda backend: backend.ed25519_supported(), skip_message="Requires OpenSSL with Ed25519 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_request_with_unsupported_hash_ed25519(self, backend): private_key = ed25519.Ed25519PrivateKey.generate() builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) @pytest.mark.supported( only_if=lambda backend: backend.ed448_supported(), skip_message="Requires OpenSSL with Ed448 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_request_with_unsupported_hash_ed448(self, backend): private_key = ed448.Ed448PrivateKey.generate() builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.supported( only_if=lambda backend: backend.hash_supported(hashes.MD5()), skip_message="Requires OpenSSL with MD5 support" ) def test_sign_rsa_with_md5(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) ) request = builder.sign(private_key, hashes.MD5(), backend) assert isinstance(request.signature_hash_algorithm, hashes.MD5) @pytest.mark.requires_backend_interface(interface=DSABackend) @pytest.mark.supported( only_if=lambda backend: backend.hash_supported(hashes.MD5()), skip_message="Requires OpenSSL with MD5 support" ) def test_sign_dsa_with_md5(self, backend): private_key = DSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.MD5(), backend) @pytest.mark.requires_backend_interface(interface=EllipticCurveBackend) @pytest.mark.supported( only_if=lambda backend: backend.hash_supported(hashes.MD5()), skip_message="Requires OpenSSL with MD5 support" ) def test_sign_ec_with_md5(self, backend): _skip_curve_unsupported(backend, ec.SECP256R1()) private_key = EC_KEY_SECP256R1.private_key(backend) builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) ) with pytest.raises(ValueError): builder.sign(private_key, hashes.MD5(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) def test_no_subject_name(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder() with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) @pytest.mark.requires_backend_interface(interface=RSABackend) def test_build_ca_request_with_rsa(self, backend): private_key = RSA_KEY_2048.private_key(backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, hashes.SHA1(), backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, rsa.RSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ] basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is True assert basic_constraints.value.path_length == 2 @pytest.mark.requires_backend_interface(interface=RSABackend) def test_build_ca_request_with_unicode(self, backend): private_key = RSA_KEY_2048.private_key(backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA\U0001f37a'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, hashes.SHA1(), backend) loaded_request = x509.load_pem_x509_csr( request.public_bytes(encoding=serialization.Encoding.PEM), backend ) subject = loaded_request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA\U0001f37a'), ] @pytest.mark.requires_backend_interface(interface=RSABackend) def test_subject_dn_asn1_types(self, backend): private_key = RSA_KEY_2048.private_key(backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u"mysite.com"), x509.NameAttribute(NameOID.COUNTRY_NAME, u"US"), x509.NameAttribute(NameOID.LOCALITY_NAME, u"value"), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u"value"), x509.NameAttribute(NameOID.STREET_ADDRESS, u"value"), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u"value"), x509.NameAttribute(NameOID.ORGANIZATIONAL_UNIT_NAME, u"value"), x509.NameAttribute(NameOID.SERIAL_NUMBER, u"value"), x509.NameAttribute(NameOID.SURNAME, u"value"), x509.NameAttribute(NameOID.GIVEN_NAME, u"value"), x509.NameAttribute(NameOID.TITLE, u"value"), x509.NameAttribute(NameOID.GENERATION_QUALIFIER, u"value"), x509.NameAttribute(NameOID.X500_UNIQUE_IDENTIFIER, u"value"), x509.NameAttribute(NameOID.DN_QUALIFIER, u"value"), x509.NameAttribute(NameOID.PSEUDONYM, u"value"), x509.NameAttribute(NameOID.USER_ID, u"value"), x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u"value"), x509.NameAttribute(NameOID.EMAIL_ADDRESS, u"value"), x509.NameAttribute(NameOID.JURISDICTION_COUNTRY_NAME, u"US"), x509.NameAttribute( NameOID.JURISDICTION_LOCALITY_NAME, u"value" ), x509.NameAttribute( NameOID.JURISDICTION_STATE_OR_PROVINCE_NAME, u"value" ), x509.NameAttribute(NameOID.BUSINESS_CATEGORY, u"value"), x509.NameAttribute(NameOID.POSTAL_ADDRESS, u"value"), x509.NameAttribute(NameOID.POSTAL_CODE, u"value"), ]) ).sign(private_key, hashes.SHA256(), backend) for oid, asn1_type in TestNameAttribute.EXPECTED_TYPES: assert request.subject.get_attributes_for_oid( oid )[0]._type == asn1_type @pytest.mark.requires_backend_interface(interface=RSABackend) def test_build_ca_request_with_multivalue_rdns(self, backend): private_key = RSA_KEY_2048.private_key(backend) subject = x509.Name([ x509.RelativeDistinguishedName([ x509.NameAttribute(NameOID.TITLE, u'Test'), x509.NameAttribute(NameOID.COMMON_NAME, u'Multivalue'), x509.NameAttribute(NameOID.SURNAME, u'RDNs'), ]), x509.RelativeDistinguishedName([ x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA') ]), ]) request = x509.CertificateSigningRequestBuilder().subject_name( subject ).sign(private_key, hashes.SHA1(), backend) loaded_request = x509.load_pem_x509_csr( request.public_bytes(encoding=serialization.Encoding.PEM), backend ) assert isinstance(loaded_request.subject, x509.Name) assert loaded_request.subject == subject @pytest.mark.requires_backend_interface(interface=RSABackend) def test_build_nonca_request_with_rsa(self, backend): private_key = RSA_KEY_2048.private_key(backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ).add_extension( x509.BasicConstraints(ca=False, path_length=None), critical=True, ).sign(private_key, hashes.SHA1(), backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, rsa.RSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ] basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is False assert basic_constraints.value.path_length is None @pytest.mark.requires_backend_interface(interface=EllipticCurveBackend) def test_build_ca_request_with_ec(self, backend): _skip_curve_unsupported(backend, ec.SECP256R1()) private_key = ec.generate_private_key(ec.SECP256R1(), backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, hashes.SHA1(), backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, ec.EllipticCurvePublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ] basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is True assert basic_constraints.value.path_length == 2 @pytest.mark.supported( only_if=lambda backend: backend.ed25519_supported(), skip_message="Requires OpenSSL with Ed25519 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_ca_request_with_ed25519(self, backend): private_key = ed25519.Ed25519PrivateKey.generate() request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, None, backend) assert request.signature_hash_algorithm is None public_key = request.public_key() assert isinstance(public_key, ed25519.Ed25519PublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ] basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is True assert basic_constraints.value.path_length == 2 @pytest.mark.supported( only_if=lambda backend: backend.ed448_supported(), skip_message="Requires OpenSSL with Ed448 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_ca_request_with_ed448(self, backend): private_key = ed448.Ed448PrivateKey.generate() request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, None, backend) assert request.signature_hash_algorithm is None public_key = request.public_key() assert isinstance(public_key, ed448.Ed448PublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), ] basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is True assert basic_constraints.value.path_length == 2 @pytest.mark.requires_backend_interface(interface=DSABackend) def test_build_ca_request_with_dsa(self, backend): private_key = DSA_KEY_2048.private_key(backend) request = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, hashes.SHA1(), backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, dsa.DSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ] basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is True assert basic_constraints.value.path_length == 2 def test_add_duplicate_extension(self): builder = x509.CertificateSigningRequestBuilder().add_extension( x509.BasicConstraints(True, 2), critical=True, ) with pytest.raises(ValueError): builder.add_extension( x509.BasicConstraints(True, 2), critical=True, ) def test_set_invalid_subject(self): builder = x509.CertificateSigningRequestBuilder() with pytest.raises(TypeError): builder.subject_name('NotAName') def test_add_invalid_extension_type(self): builder = x509.CertificateSigningRequestBuilder() with pytest.raises(TypeError): builder.add_extension(object(), False) def test_add_unsupported_extension(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder() builder = builder.subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).add_extension( DummyExtension(), False ) with pytest.raises(NotImplementedError): builder.sign(private_key, hashes.SHA256(), backend) def test_key_usage(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder() request = builder.subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ).add_extension( x509.KeyUsage( digital_signature=True, content_commitment=True, key_encipherment=False, data_encipherment=False, key_agreement=False, key_cert_sign=True, crl_sign=False, encipher_only=False, decipher_only=False ), critical=False ).sign(private_key, hashes.SHA256(), backend) assert len(request.extensions) == 1 ext = request.extensions.get_extension_for_oid(ExtensionOID.KEY_USAGE) assert ext.critical is False assert ext.value == x509.KeyUsage( digital_signature=True, content_commitment=True, key_encipherment=False, data_encipherment=False, key_agreement=False, key_cert_sign=True, crl_sign=False, encipher_only=False, decipher_only=False ) def test_key_usage_key_agreement_bit(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder() request = builder.subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ).add_extension( x509.KeyUsage( digital_signature=False, content_commitment=False, key_encipherment=False, data_encipherment=False, key_agreement=True, key_cert_sign=True, crl_sign=False, encipher_only=False, decipher_only=True ), critical=False ).sign(private_key, hashes.SHA256(), backend) assert len(request.extensions) == 1 ext = request.extensions.get_extension_for_oid(ExtensionOID.KEY_USAGE) assert ext.critical is False assert ext.value == x509.KeyUsage( digital_signature=False, content_commitment=False, key_encipherment=False, data_encipherment=False, key_agreement=True, key_cert_sign=True, crl_sign=False, encipher_only=False, decipher_only=True ) def test_add_two_extensions(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder() request = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).add_extension( x509.SubjectAlternativeName([x509.DNSName(u"cryptography.io")]), critical=False, ).add_extension( x509.BasicConstraints(ca=True, path_length=2), critical=True ).sign(private_key, hashes.SHA1(), backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, rsa.RSAPublicKey) basic_constraints = request.extensions.get_extension_for_oid( ExtensionOID.BASIC_CONSTRAINTS ) assert basic_constraints.value.ca is True assert basic_constraints.value.path_length == 2 ext = request.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert list(ext.value) == [x509.DNSName(u"cryptography.io")] def test_set_subject_twice(self): builder = x509.CertificateSigningRequestBuilder() builder = builder.subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ) with pytest.raises(ValueError): builder.subject_name( x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ]) ) def test_subject_alt_names(self, backend): private_key = RSA_KEY_2048.private_key(backend) san = x509.SubjectAlternativeName([ x509.DNSName(u"example.com"), x509.DNSName(u"*.example.com"), x509.RegisteredID(x509.ObjectIdentifier("1.2.3.4.5.6.7")), x509.DirectoryName(x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u'PyCA'), x509.NameAttribute( NameOID.ORGANIZATION_NAME, u'We heart UTF8!\u2122' ) ])), x509.IPAddress(ipaddress.ip_address(u"127.0.0.1")), x509.IPAddress(ipaddress.ip_address(u"ff::")), x509.OtherName( type_id=x509.ObjectIdentifier("1.2.3.3.3.3"), value=b"0\x03\x02\x01\x05" ), x509.RFC822Name(u"test@example.com"), x509.RFC822Name(u"email"), x509.RFC822Name(u"email@xn--eml-vla4c.com"), x509.UniformResourceIdentifier( u"https://xn--80ato2c.cryptography" ), x509.UniformResourceIdentifier( u"gopher://cryptography:70/some/path" ), ]) csr = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u"SAN"), ]) ).add_extension( san, critical=False, ).sign(private_key, hashes.SHA256(), backend) assert len(csr.extensions) == 1 ext = csr.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_ALTERNATIVE_NAME ) assert not ext.critical assert ext.oid == ExtensionOID.SUBJECT_ALTERNATIVE_NAME assert ext.value == san def test_invalid_asn1_othername(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u"SAN"), ]) ).add_extension( x509.SubjectAlternativeName([ x509.OtherName( type_id=x509.ObjectIdentifier("1.2.3.3.3.3"), value=b"\x01\x02\x01\x05" ), ]), critical=False, ) with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) def test_subject_alt_name_unsupported_general_name(self, backend): private_key = RSA_KEY_2048.private_key(backend) builder = x509.CertificateSigningRequestBuilder().subject_name( x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u"SAN"), ]) ).add_extension( x509.SubjectAlternativeName([FakeGeneralName("")]), critical=False, ) with pytest.raises(ValueError): builder.sign(private_key, hashes.SHA256(), backend) def test_extended_key_usage(self, backend): private_key = RSA_KEY_2048.private_key(backend) eku = x509.ExtendedKeyUsage([ ExtendedKeyUsageOID.CLIENT_AUTH, ExtendedKeyUsageOID.SERVER_AUTH, ExtendedKeyUsageOID.CODE_SIGNING, ]) builder = x509.CertificateSigningRequestBuilder() request = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ).add_extension( eku, critical=False ).sign(private_key, hashes.SHA256(), backend) ext = request.extensions.get_extension_for_oid( ExtensionOID.EXTENDED_KEY_USAGE ) assert ext.critical is False assert ext.value == eku @pytest.mark.requires_backend_interface(interface=RSABackend) def test_rsa_key_too_small(self, backend): private_key = RSA_KEY_512.private_key(backend) builder = x509.CertificateSigningRequestBuilder() builder = builder.subject_name( x509.Name([x509.NameAttribute(NameOID.COUNTRY_NAME, u'US')]) ) with pytest.raises(ValueError) as exc: builder.sign(private_key, hashes.SHA512(), backend) assert str(exc.value) == "Digest too big for RSA key" @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_aia(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) aia = x509.AuthorityInformationAccess([ x509.AccessDescription( AuthorityInformationAccessOID.OCSP, x509.UniformResourceIdentifier(u"http://ocsp.domain.com") ), x509.AccessDescription( AuthorityInformationAccessOID.CA_ISSUERS, x509.UniformResourceIdentifier(u"http://domain.com/ca.crt") ) ]) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( aia, critical=False ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA1(), backend) ext = cert.extensions.get_extension_for_oid( ExtensionOID.AUTHORITY_INFORMATION_ACCESS ) assert ext.value == aia @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_ski(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) ski = x509.SubjectKeyIdentifier.from_public_key( subject_private_key.public_key() ) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( ski, critical=False ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA1(), backend) ext = cert.extensions.get_extension_for_oid( ExtensionOID.SUBJECT_KEY_IDENTIFIER ) assert ext.value == ski @pytest.mark.parametrize( "aki", [ x509.AuthorityKeyIdentifier( b"\xc3\x9c\xf3\xfc\xd3F\x084\xbb\xceF\x7f\xa0|[\xf3\xe2\x08" b"\xcbY", None, None ), x509.AuthorityKeyIdentifier( b"\xc3\x9c\xf3\xfc\xd3F\x084\xbb\xceF\x7f\xa0|[\xf3\xe2\x08" b"\xcbY", [ x509.DirectoryName( x509.Name([ x509.NameAttribute( NameOID.ORGANIZATION_NAME, u"PyCA" ), x509.NameAttribute( NameOID.COMMON_NAME, u"cryptography CA" ) ]) ) ], 333 ), x509.AuthorityKeyIdentifier( None, [ x509.DirectoryName( x509.Name([ x509.NameAttribute( NameOID.ORGANIZATION_NAME, u"PyCA" ), x509.NameAttribute( NameOID.COMMON_NAME, u"cryptography CA" ) ]) ) ], 333 ), ] ) @pytest.mark.requires_backend_interface(interface=RSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_build_cert_with_aki(self, aki, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( aki, critical=False ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA256(), backend) ext = cert.extensions.get_extension_for_oid( ExtensionOID.AUTHORITY_KEY_IDENTIFIER ) assert ext.value == aki def test_ocsp_nocheck(self, backend): issuer_private_key = RSA_KEY_2048.private_key(backend) subject_private_key = RSA_KEY_2048.private_key(backend) not_valid_before = datetime.datetime(2002, 1, 1, 12, 1) not_valid_after = datetime.datetime(2030, 12, 31, 8, 30) builder = x509.CertificateBuilder().serial_number( 777 ).issuer_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).subject_name(x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), ])).public_key( subject_private_key.public_key() ).add_extension( x509.OCSPNoCheck(), critical=False ).not_valid_before( not_valid_before ).not_valid_after( not_valid_after ) cert = builder.sign(issuer_private_key, hashes.SHA256(), backend) ext = cert.extensions.get_extension_for_oid( ExtensionOID.OCSP_NO_CHECK ) assert isinstance(ext.value, x509.OCSPNoCheck) @pytest.mark.requires_backend_interface(interface=DSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestDSACertificate(object): def test_load_dsa_cert(self, backend): cert = _load_cert( os.path.join("x509", "custom", "dsa_selfsigned_ca.pem"), x509.load_pem_x509_certificate, backend ) assert isinstance(cert.signature_hash_algorithm, hashes.SHA1) public_key = cert.public_key() assert isinstance(public_key, dsa.DSAPublicKey) num = public_key.public_numbers() assert num.y == int( "4c08bfe5f2d76649c80acf7d431f6ae2124b217abc8c9f6aca776ddfa94" "53b6656f13e543684cd5f6431a314377d2abfa068b7080cb8ddc065afc2" "dea559f0b584c97a2b235b9b69b46bc6de1aed422a6f341832618bcaae2" "198aba388099dafb05ff0b5efecb3b0ae169a62e1c72022af50ae68af3b" "033c18e6eec1f7df4692c456ccafb79cc7e08da0a5786e9816ceda651d6" "1b4bb7b81c2783da97cea62df67af5e85991fdc13aff10fc60e06586386" "b96bb78d65750f542f86951e05a6d81baadbcd35a2e5cad4119923ae6a2" "002091a3d17017f93c52970113cdc119970b9074ca506eac91c3dd37632" "5df4af6b3911ef267d26623a5a1c5df4a6d13f1c", 16 ) assert num.parameter_numbers.g == int( "4b7ced71dc353965ecc10d441a9a06fc24943a32d66429dd5ef44d43e67" "d789d99770aec32c0415dc92970880872da45fef8dd1e115a3e4801387b" "a6d755861f062fd3b6e9ea8e2641152339b828315b1528ee6c7b79458d2" "1f3db973f6fc303f9397174c2799dd2351282aa2d8842c357a73495bbaa" "c4932786414c55e60d73169f5761036fba29e9eebfb049f8a3b1b7cee6f" "3fbfa136205f130bee2cf5b9c38dc1095d4006f2e73335c07352c64130a" "1ab2b89f13b48f628d3cc3868beece9bb7beade9f830eacc6fa241425c0" "b3fcc0df416a0c89f7bf35668d765ec95cdcfbe9caff49cfc156c668c76" "fa6247676a6d3ac945844a083509c6a1b436baca", 16 ) assert num.parameter_numbers.p == int( "bfade6048e373cd4e48b677e878c8e5b08c02102ae04eb2cb5c46a523a3" "af1c73d16b24f34a4964781ae7e50500e21777754a670bd19a7420d6330" "84e5556e33ca2c0e7d547ea5f46a07a01bf8669ae3bdec042d9b2ae5e6e" "cf49f00ba9dac99ab6eff140d2cedf722ee62c2f9736857971444c25d0a" "33d2017dc36d682a1054fe2a9428dda355a851ce6e6d61e03e419fd4ca4" "e703313743d86caa885930f62ed5bf342d8165627681e9cc3244ba72aa2" "2148400a6bbe80154e855d042c9dc2a3405f1e517be9dea50562f56da93" "f6085f844a7e705c1f043e65751c583b80d29103e590ccb26efdaa0893d" "833e36468f3907cfca788a3cb790f0341c8a31bf", 16 ) assert num.parameter_numbers.q == int( "822ff5d234e073b901cf5941f58e1f538e71d40d", 16 ) def test_signature(self, backend): cert = _load_cert( os.path.join("x509", "custom", "dsa_selfsigned_ca.pem"), x509.load_pem_x509_certificate, backend ) assert cert.signature == binascii.unhexlify( b"302c021425c4a84a936ab311ee017d3cbd9a3c650bb3ae4a02145d30c64b4326" b"86bdf925716b4ed059184396bcce" ) r, s = decode_dss_signature(cert.signature) assert r == 215618264820276283222494627481362273536404860490 assert s == 532023851299196869156027211159466197586787351758 def test_tbs_certificate_bytes(self, backend): cert = _load_cert( os.path.join("x509", "custom", "dsa_selfsigned_ca.pem"), x509.load_pem_x509_certificate, backend ) assert cert.tbs_certificate_bytes == binascii.unhexlify( b"3082051aa003020102020900a37352e0b2142f86300906072a8648ce3804033" b"067310b3009060355040613025553310e300c06035504081305546578617331" b"0f300d0603550407130641757374696e3121301f060355040a1318496e74657" b"26e6574205769646769747320507479204c7464311430120603550403130b50" b"79434120445341204341301e170d3134313132373035313431375a170d31343" b"13232373035313431375a3067310b3009060355040613025553310e300c0603" b"55040813055465786173310f300d0603550407130641757374696e3121301f0" b"60355040a1318496e7465726e6574205769646769747320507479204c746431" b"1430120603550403130b50794341204453412043413082033a3082022d06072" b"a8648ce380401308202200282010100bfade6048e373cd4e48b677e878c8e5b" b"08c02102ae04eb2cb5c46a523a3af1c73d16b24f34a4964781ae7e50500e217" b"77754a670bd19a7420d633084e5556e33ca2c0e7d547ea5f46a07a01bf8669a" b"e3bdec042d9b2ae5e6ecf49f00ba9dac99ab6eff140d2cedf722ee62c2f9736" b"857971444c25d0a33d2017dc36d682a1054fe2a9428dda355a851ce6e6d61e0" b"3e419fd4ca4e703313743d86caa885930f62ed5bf342d8165627681e9cc3244" b"ba72aa22148400a6bbe80154e855d042c9dc2a3405f1e517be9dea50562f56d" b"a93f6085f844a7e705c1f043e65751c583b80d29103e590ccb26efdaa0893d8" b"33e36468f3907cfca788a3cb790f0341c8a31bf021500822ff5d234e073b901" b"cf5941f58e1f538e71d40d028201004b7ced71dc353965ecc10d441a9a06fc2" b"4943a32d66429dd5ef44d43e67d789d99770aec32c0415dc92970880872da45" b"fef8dd1e115a3e4801387ba6d755861f062fd3b6e9ea8e2641152339b828315" b"b1528ee6c7b79458d21f3db973f6fc303f9397174c2799dd2351282aa2d8842" b"c357a73495bbaac4932786414c55e60d73169f5761036fba29e9eebfb049f8a" b"3b1b7cee6f3fbfa136205f130bee2cf5b9c38dc1095d4006f2e73335c07352c" b"64130a1ab2b89f13b48f628d3cc3868beece9bb7beade9f830eacc6fa241425" b"c0b3fcc0df416a0c89f7bf35668d765ec95cdcfbe9caff49cfc156c668c76fa" b"6247676a6d3ac945844a083509c6a1b436baca0382010500028201004c08bfe" b"5f2d76649c80acf7d431f6ae2124b217abc8c9f6aca776ddfa9453b6656f13e" b"543684cd5f6431a314377d2abfa068b7080cb8ddc065afc2dea559f0b584c97" b"a2b235b9b69b46bc6de1aed422a6f341832618bcaae2198aba388099dafb05f" b"f0b5efecb3b0ae169a62e1c72022af50ae68af3b033c18e6eec1f7df4692c45" b"6ccafb79cc7e08da0a5786e9816ceda651d61b4bb7b81c2783da97cea62df67" b"af5e85991fdc13aff10fc60e06586386b96bb78d65750f542f86951e05a6d81" b"baadbcd35a2e5cad4119923ae6a2002091a3d17017f93c52970113cdc119970" b"b9074ca506eac91c3dd376325df4af6b3911ef267d26623a5a1c5df4a6d13f1" b"ca381cc3081c9301d0603551d0e04160414a4fb887a13fcdeb303bbae9a1dec" b"a72f125a541b3081990603551d2304819130818e8014a4fb887a13fcdeb303b" b"bae9a1deca72f125a541ba16ba4693067310b3009060355040613025553310e" b"300c060355040813055465786173310f300d0603550407130641757374696e3" b"121301f060355040a1318496e7465726e657420576964676974732050747920" b"4c7464311430120603550403130b5079434120445341204341820900a37352e" b"0b2142f86300c0603551d13040530030101ff" ) cert.public_key().verify( cert.signature, cert.tbs_certificate_bytes, cert.signature_hash_algorithm ) @pytest.mark.requires_backend_interface(interface=DSABackend) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestDSACertificateRequest(object): @pytest.mark.parametrize( ("path", "loader_func"), [ [ os.path.join("x509", "requests", "dsa_sha1.pem"), x509.load_pem_x509_csr ], [ os.path.join("x509", "requests", "dsa_sha1.der"), x509.load_der_x509_csr ], ] ) def test_load_dsa_request(self, path, loader_func, backend): request = _load_cert(path, loader_func, backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA1) public_key = request.public_key() assert isinstance(public_key, dsa.DSAPublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), ] def test_signature(self, backend): request = _load_cert( os.path.join("x509", "requests", "dsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert request.signature == binascii.unhexlify( b"302c021461d58dc028d0110818a7d817d74235727c4acfdf0214097b52e198e" b"ce95de17273f0a924df23ce9d8188" ) def test_tbs_certrequest_bytes(self, backend): request = _load_cert( os.path.join("x509", "requests", "dsa_sha1.pem"), x509.load_pem_x509_csr, backend ) assert request.tbs_certrequest_bytes == binascii.unhexlify( b"3082021802010030573118301606035504030c0f63727970746f677261706879" b"2e696f310d300b060355040a0c0450794341310b300906035504061302555331" b"0e300c06035504080c055465786173310f300d06035504070c0641757374696e" b"308201b63082012b06072a8648ce3804013082011e028181008d7fadbc09e284" b"aafa69154cea24177004909e519f8b35d685cde5b4ecdc9583e74d370a0f88ad" b"a98f026f27762fb3d5da7836f986dfcdb3589e5b925bea114defc03ef81dae30" b"c24bbc6df3d588e93427bba64203d4a5b1687b2b5e3b643d4c614976f89f95a3" b"8d3e4c89065fba97514c22c50adbbf289163a74b54859b35b7021500835de56b" b"d07cf7f82e2032fe78949aed117aa2ef0281801f717b5a07782fc2e4e68e311f" b"ea91a54edd36b86ac634d14f05a68a97eae9d2ef31fb1ef3de42c3d100df9ca6" b"4f5bdc2aec7bfdfb474cf831fea05853b5e059f2d24980a0ac463f1e818af352" b"3e3cb79a39d45fa92731897752842469cf8540b01491024eaafbce6018e8a1f4" b"658c343f4ba7c0b21e5376a21f4beb8491961e038184000281800713f07641f6" b"369bb5a9545274a2d4c01998367fb371bb9e13436363672ed68f82174c2de05c" b"8e839bc6de568dd50ba28d8d9d8719423aaec5557df10d773ab22d6d65cbb878" b"04a697bc8fd965b952f9f7e850edf13c8acdb5d753b6d10e59e0b5732e3c82ba" b"fa140342bc4a3bba16bd0681c8a6a2dbbb7efe6ce2b8463b170ba000" ) request.public_key().verify( request.signature, request.tbs_certrequest_bytes, request.signature_hash_algorithm ) @pytest.mark.requires_backend_interface(interface=EllipticCurveBackend) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestECDSACertificate(object): def test_load_ecdsa_cert(self, backend): _skip_curve_unsupported(backend, ec.SECP384R1()) cert = _load_cert( os.path.join("x509", "ecdsa_root.pem"), x509.load_pem_x509_certificate, backend ) assert isinstance(cert.signature_hash_algorithm, hashes.SHA384) public_key = cert.public_key() assert isinstance(public_key, ec.EllipticCurvePublicKey) num = public_key.public_numbers() assert num.x == int( "dda7d9bb8ab80bfb0b7f21d2f0bebe73f3335d1abc34eadec69bbcd095f" "6f0ccd00bba615b51467e9e2d9fee8e630c17", 16 ) assert num.y == int( "ec0770f5cf842e40839ce83f416d3badd3a4145936789d0343ee10136c7" "2deae88a7a16bb543ce67dc23ff031ca3e23e", 16 ) assert isinstance(num.curve, ec.SECP384R1) def test_signature(self, backend): cert = _load_cert( os.path.join("x509", "ecdsa_root.pem"), x509.load_pem_x509_certificate, backend ) assert cert.signature == binascii.unhexlify( b"3065023100adbcf26c3f124ad12d39c30a099773f488368c8827bbe6888d5085" b"a763f99e32de66930ff1ccb1098fdd6cabfa6b7fa0023039665bc2648db89e50" b"dca8d549a2edc7dcd1497f1701b8c8868f4e8c882ba89aa98ac5d100bdf854e2" b"9ae55b7cb32717" ) r, s = decode_dss_signature(cert.signature) assert r == int( "adbcf26c3f124ad12d39c30a099773f488368c8827bbe6888d5085a763f99e32" "de66930ff1ccb1098fdd6cabfa6b7fa0", 16 ) assert s == int( "39665bc2648db89e50dca8d549a2edc7dcd1497f1701b8c8868f4e8c882ba89a" "a98ac5d100bdf854e29ae55b7cb32717", 16 ) def test_tbs_certificate_bytes(self, backend): _skip_curve_unsupported(backend, ec.SECP384R1()) cert = _load_cert( os.path.join("x509", "ecdsa_root.pem"), x509.load_pem_x509_certificate, backend ) assert cert.tbs_certificate_bytes == binascii.unhexlify( b"308201c5a0030201020210055556bcf25ea43535c3a40fd5ab4572300a06082" b"a8648ce3d0403033061310b300906035504061302555331153013060355040a" b"130c446967694365727420496e6331193017060355040b13107777772e64696" b"769636572742e636f6d3120301e06035504031317446967694365727420476c" b"6f62616c20526f6f74204733301e170d3133303830313132303030305a170d3" b"338303131353132303030305a3061310b300906035504061302555331153013" b"060355040a130c446967694365727420496e6331193017060355040b1310777" b"7772e64696769636572742e636f6d3120301e06035504031317446967694365" b"727420476c6f62616c20526f6f742047333076301006072a8648ce3d0201060" b"52b8104002203620004dda7d9bb8ab80bfb0b7f21d2f0bebe73f3335d1abc34" b"eadec69bbcd095f6f0ccd00bba615b51467e9e2d9fee8e630c17ec0770f5cf8" b"42e40839ce83f416d3badd3a4145936789d0343ee10136c72deae88a7a16bb5" b"43ce67dc23ff031ca3e23ea3423040300f0603551d130101ff040530030101f" b"f300e0603551d0f0101ff040403020186301d0603551d0e04160414b3db48a4" b"f9a1c5d8ae3641cc1163696229bc4bc6" ) cert.public_key().verify( cert.signature, cert.tbs_certificate_bytes, ec.ECDSA(cert.signature_hash_algorithm) ) def test_load_ecdsa_no_named_curve(self, backend): _skip_curve_unsupported(backend, ec.SECP256R1()) cert = _load_cert( os.path.join("x509", "custom", "ec_no_named_curve.pem"), x509.load_pem_x509_certificate, backend ) with pytest.raises(NotImplementedError): cert.public_key() @pytest.mark.requires_backend_interface(interface=X509Backend) @pytest.mark.requires_backend_interface(interface=EllipticCurveBackend) class TestECDSACertificateRequest(object): @pytest.mark.parametrize( ("path", "loader_func"), [ [ os.path.join("x509", "requests", "ec_sha256.pem"), x509.load_pem_x509_csr ], [ os.path.join("x509", "requests", "ec_sha256.der"), x509.load_der_x509_csr ], ] ) def test_load_ecdsa_certificate_request(self, path, loader_func, backend): _skip_curve_unsupported(backend, ec.SECP384R1()) request = _load_cert(path, loader_func, backend) assert isinstance(request.signature_hash_algorithm, hashes.SHA256) public_key = request.public_key() assert isinstance(public_key, ec.EllipticCurvePublicKey) subject = request.subject assert isinstance(subject, x509.Name) assert list(subject) == [ x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'Texas'), x509.NameAttribute(NameOID.LOCALITY_NAME, u'Austin'), ] def test_signature(self, backend): _skip_curve_unsupported(backend, ec.SECP384R1()) request = _load_cert( os.path.join("x509", "requests", "ec_sha256.pem"), x509.load_pem_x509_csr, backend ) assert request.signature == binascii.unhexlify( b"306502302c1a9f7de8c1787332d2307a886b476a59f172b9b0e250262f3238b1" b"b45ee112bb6eb35b0fb56a123b9296eb212dffc302310094cf440c95c52827d5" b"56ae6d76500e3008255d47c29f7ee782ed7558e51bfd76aa45df6d999ed5c463" b"347fe2382d1751" ) def test_tbs_certrequest_bytes(self, backend): _skip_curve_unsupported(backend, ec.SECP384R1()) request = _load_cert( os.path.join("x509", "requests", "ec_sha256.pem"), x509.load_pem_x509_csr, backend ) assert request.tbs_certrequest_bytes == binascii.unhexlify( b"3081d602010030573118301606035504030c0f63727970746f6772617068792" b"e696f310d300b060355040a0c0450794341310b300906035504061302555331" b"0e300c06035504080c055465786173310f300d06035504070c0641757374696" b"e3076301006072a8648ce3d020106052b8104002203620004de19b514c0b3c3" b"ae9b398ea3e26b5e816bdcf9102cad8f12fe02f9e4c9248724b39297ed7582e" b"04d8b32a551038d09086803a6d3fb91a1a1167ec02158b00efad39c9396462f" b"accff0ffaf7155812909d3726bd59fde001cff4bb9b2f5af8cbaa000" ) request.public_key().verify( request.signature, request.tbs_certrequest_bytes, ec.ECDSA(request.signature_hash_algorithm) ) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestOtherCertificate(object): def test_unsupported_subject_public_key_info(self, backend): cert = _load_cert( os.path.join( "x509", "custom", "unsupported_subject_public_key_info.pem" ), x509.load_pem_x509_certificate, backend, ) with pytest.raises(ValueError): cert.public_key() def test_bad_time_in_validity(self, backend): cert = _load_cert( os.path.join( "x509", "badasn1time.pem" ), x509.load_pem_x509_certificate, backend, ) with pytest.raises(ValueError, match='19020701025736Z'): cert.not_valid_after class TestNameAttribute(object): EXPECTED_TYPES = [ (NameOID.COMMON_NAME, _ASN1Type.UTF8String), (NameOID.COUNTRY_NAME, _ASN1Type.PrintableString), (NameOID.LOCALITY_NAME, _ASN1Type.UTF8String), (NameOID.STATE_OR_PROVINCE_NAME, _ASN1Type.UTF8String), (NameOID.STREET_ADDRESS, _ASN1Type.UTF8String), (NameOID.ORGANIZATION_NAME, _ASN1Type.UTF8String), (NameOID.ORGANIZATIONAL_UNIT_NAME, _ASN1Type.UTF8String), (NameOID.SERIAL_NUMBER, _ASN1Type.PrintableString), (NameOID.SURNAME, _ASN1Type.UTF8String), (NameOID.GIVEN_NAME, _ASN1Type.UTF8String), (NameOID.TITLE, _ASN1Type.UTF8String), (NameOID.GENERATION_QUALIFIER, _ASN1Type.UTF8String), (NameOID.X500_UNIQUE_IDENTIFIER, _ASN1Type.UTF8String), (NameOID.DN_QUALIFIER, _ASN1Type.PrintableString), (NameOID.PSEUDONYM, _ASN1Type.UTF8String), (NameOID.USER_ID, _ASN1Type.UTF8String), (NameOID.DOMAIN_COMPONENT, _ASN1Type.IA5String), (NameOID.EMAIL_ADDRESS, _ASN1Type.IA5String), (NameOID.JURISDICTION_COUNTRY_NAME, _ASN1Type.PrintableString), (NameOID.JURISDICTION_LOCALITY_NAME, _ASN1Type.UTF8String), ( NameOID.JURISDICTION_STATE_OR_PROVINCE_NAME, _ASN1Type.UTF8String ), (NameOID.BUSINESS_CATEGORY, _ASN1Type.UTF8String), (NameOID.POSTAL_ADDRESS, _ASN1Type.UTF8String), (NameOID.POSTAL_CODE, _ASN1Type.UTF8String), ] def test_default_types(self): for oid, asn1_type in TestNameAttribute.EXPECTED_TYPES: na = x509.NameAttribute(oid, u"US") assert na._type == asn1_type def test_alternate_type(self): na2 = x509.NameAttribute( NameOID.COMMON_NAME, u"common", _ASN1Type.IA5String ) assert na2._type == _ASN1Type.IA5String def test_init_bad_oid(self): with pytest.raises(TypeError): x509.NameAttribute(None, u'value') def test_init_bad_value(self): with pytest.raises(TypeError): x509.NameAttribute( x509.ObjectIdentifier('2.999.1'), b'bytes' ) def test_init_none_value(self): with pytest.raises(TypeError): x509.NameAttribute(NameOID.ORGANIZATION_NAME, None) def test_init_bad_country_code_value(self): with pytest.raises(ValueError): x509.NameAttribute( NameOID.COUNTRY_NAME, u'United States' ) # unicode string of length 2, but > 2 bytes with pytest.raises(ValueError): x509.NameAttribute( NameOID.COUNTRY_NAME, u'\U0001F37A\U0001F37A' ) def test_invalid_type(self): with pytest.raises(TypeError): x509.NameAttribute(NameOID.COMMON_NAME, u"common", "notanenum") def test_eq(self): assert x509.NameAttribute( x509.ObjectIdentifier('2.999.1'), u'value' ) == x509.NameAttribute( x509.ObjectIdentifier('2.999.1'), u'value' ) def test_ne(self): assert x509.NameAttribute( x509.ObjectIdentifier('2.5.4.3'), u'value' ) != x509.NameAttribute( x509.ObjectIdentifier('2.5.4.5'), u'value' ) assert x509.NameAttribute( x509.ObjectIdentifier('2.999.1'), u'value' ) != x509.NameAttribute( x509.ObjectIdentifier('2.999.1'), u'value2' ) assert x509.NameAttribute( x509.ObjectIdentifier('2.999.2'), u'value' ) != object() def test_repr(self): na = x509.NameAttribute(x509.ObjectIdentifier('2.5.4.3'), u'value') if not six.PY2: assert repr(na) == ( "<NameAttribute(oid=<ObjectIdentifier(oid=2.5.4.3, name=commo" "nName)>, value='value')>" ) else: assert repr(na) == ( "<NameAttribute(oid=<ObjectIdentifier(oid=2.5.4.3, name=commo" "nName)>, value=u'value')>" ) def test_distinugished_name(self): # Escaping na = x509.NameAttribute(NameOID.COMMON_NAME, u'James "Jim" Smith, III') assert na.rfc4514_string() == r'CN=James \"Jim\" Smith\, III' na = x509.NameAttribute(NameOID.USER_ID, u'# escape+,;\0this ') assert na.rfc4514_string() == r'UID=\# escape\+\,\;\00this\ ' # Nonstandard attribute OID na = x509.NameAttribute(NameOID.EMAIL_ADDRESS, u'somebody@example.com') assert (na.rfc4514_string() == '1.2.840.113549.1.9.1=somebody@example.com') def test_empty_value(self): na = x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u'') assert na.rfc4514_string() == r'ST=' class TestRelativeDistinguishedName(object): def test_init_empty(self): with pytest.raises(ValueError): x509.RelativeDistinguishedName([]) def test_init_not_nameattribute(self): with pytest.raises(TypeError): x509.RelativeDistinguishedName(["not-a-NameAttribute"]) def test_init_duplicate_attribute(self): with pytest.raises(ValueError): x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'val1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'val1'), ]) def test_hash(self): rdn1 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2'), ]) rdn2 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2'), x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), ]) rdn3 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value3'), ]) assert hash(rdn1) == hash(rdn2) assert hash(rdn1) != hash(rdn3) def test_eq(self): rdn1 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2'), ]) rdn2 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2'), x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), ]) assert rdn1 == rdn2 def test_ne(self): rdn1 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2'), ]) rdn2 = x509.RelativeDistinguishedName([ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value3'), ]) assert rdn1 != rdn2 assert rdn1 != object() def test_iter_input(self): # Order must be preserved too attrs = [ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1'), x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value2'), x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value3') ] rdn = x509.RelativeDistinguishedName(iter(attrs)) assert list(rdn) == attrs assert list(rdn) == attrs def test_get_attributes_for_oid(self): oid = x509.ObjectIdentifier('2.999.1') attr = x509.NameAttribute(oid, u'value1') rdn = x509.RelativeDistinguishedName([attr]) assert rdn.get_attributes_for_oid(oid) == [attr] assert rdn.get_attributes_for_oid(x509.ObjectIdentifier('1.2.3')) == [] class TestObjectIdentifier(object): def test_eq(self): oid1 = x509.ObjectIdentifier('2.999.1') oid2 = x509.ObjectIdentifier('2.999.1') assert oid1 == oid2 def test_ne(self): oid1 = x509.ObjectIdentifier('2.999.1') assert oid1 != x509.ObjectIdentifier('2.999.2') assert oid1 != object() def test_repr(self): oid = x509.ObjectIdentifier("2.5.4.3") assert repr(oid) == "<ObjectIdentifier(oid=2.5.4.3, name=commonName)>" oid = x509.ObjectIdentifier("2.999.1") assert repr(oid) == "<ObjectIdentifier(oid=2.999.1, name=Unknown OID)>" def test_name_property(self): oid = x509.ObjectIdentifier("2.5.4.3") assert oid._name == 'commonName' oid = x509.ObjectIdentifier("2.999.1") assert oid._name == 'Unknown OID' def test_too_short(self): with pytest.raises(ValueError): x509.ObjectIdentifier("1") def test_invalid_input(self): with pytest.raises(ValueError): x509.ObjectIdentifier("notavalidform") def test_invalid_node1(self): with pytest.raises(ValueError): x509.ObjectIdentifier("7.1.37") def test_invalid_node2(self): with pytest.raises(ValueError): x509.ObjectIdentifier("1.50.200") def test_valid(self): x509.ObjectIdentifier("0.35.200") x509.ObjectIdentifier("1.39.999") x509.ObjectIdentifier("2.5.29.3") x509.ObjectIdentifier("2.999.37.5.22.8") x509.ObjectIdentifier("2.25.305821105408246119474742976030998643995") class TestName(object): def test_eq(self): ava1 = x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1') ava2 = x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2') name1 = x509.Name([ava1, ava2]) name2 = x509.Name([ x509.RelativeDistinguishedName([ava1]), x509.RelativeDistinguishedName([ava2]), ]) name3 = x509.Name([x509.RelativeDistinguishedName([ava1, ava2])]) name4 = x509.Name([x509.RelativeDistinguishedName([ava2, ava1])]) assert name1 == name2 assert name3 == name4 def test_ne(self): ava1 = x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1') ava2 = x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2') name1 = x509.Name([ava1, ava2]) name2 = x509.Name([ava2, ava1]) name3 = x509.Name([x509.RelativeDistinguishedName([ava1, ava2])]) assert name1 != name2 assert name1 != name3 assert name1 != object() def test_hash(self): ava1 = x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1') ava2 = x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2') name1 = x509.Name([ava1, ava2]) name2 = x509.Name([ x509.RelativeDistinguishedName([ava1]), x509.RelativeDistinguishedName([ava2]), ]) name3 = x509.Name([ava2, ava1]) name4 = x509.Name([x509.RelativeDistinguishedName([ava1, ava2])]) name5 = x509.Name([x509.RelativeDistinguishedName([ava2, ava1])]) assert hash(name1) == hash(name2) assert hash(name1) != hash(name3) assert hash(name1) != hash(name4) assert hash(name4) == hash(name5) def test_iter_input(self): attrs = [ x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1') ] name = x509.Name(iter(attrs)) assert list(name) == attrs assert list(name) == attrs def test_rdns(self): rdn1 = x509.NameAttribute(x509.ObjectIdentifier('2.999.1'), u'value1') rdn2 = x509.NameAttribute(x509.ObjectIdentifier('2.999.2'), u'value2') name1 = x509.Name([rdn1, rdn2]) assert name1.rdns == [ x509.RelativeDistinguishedName([rdn1]), x509.RelativeDistinguishedName([rdn2]), ] name2 = x509.Name([x509.RelativeDistinguishedName([rdn1, rdn2])]) assert name2.rdns == [x509.RelativeDistinguishedName([rdn1, rdn2])] @pytest.mark.parametrize( ("common_name", "org_name", "expected_repr"), [ ( u'cryptography.io', u'PyCA', "<Name(CN=cryptography.io,O=PyCA)>", ), ( u'Certificación', u'Certificación', "<Name(CN=Certificación,O=Certificación)>", ), ]) def test_repr(self, common_name, org_name, expected_repr): name = x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, common_name), x509.NameAttribute(NameOID.ORGANIZATION_NAME, org_name), ]) assert repr(name) == expected_repr def test_rfc4514_string(self): n = x509.Name([ x509.RelativeDistinguishedName([ x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u'net'), ]), x509.RelativeDistinguishedName([ x509.NameAttribute(NameOID.DOMAIN_COMPONENT, u'example'), ]), x509.RelativeDistinguishedName([ x509.NameAttribute(NameOID.ORGANIZATIONAL_UNIT_NAME, u'Sales'), x509.NameAttribute(NameOID.COMMON_NAME, u'J. Smith'), ]), ]) assert (n.rfc4514_string() == 'OU=Sales+CN=J. Smith,DC=example,DC=net') def test_rfc4514_string_empty_values(self): n = x509.Name([ x509.NameAttribute(NameOID.COUNTRY_NAME, u'US'), x509.NameAttribute(NameOID.STATE_OR_PROVINCE_NAME, u''), x509.NameAttribute(NameOID.LOCALITY_NAME, u''), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), ]) assert (n.rfc4514_string() == 'CN=cryptography.io,O=PyCA,L=,ST=,C=US') def test_not_nameattribute(self): with pytest.raises(TypeError): x509.Name(["not-a-NameAttribute"]) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_bytes(self, backend): name = x509.Name([ x509.NameAttribute(NameOID.COMMON_NAME, u'cryptography.io'), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) assert name.public_bytes(backend) == binascii.unhexlify( b"30293118301606035504030c0f63727970746f6772617068792e696f310d300" b"b060355040a0c0450794341" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_bmpstring_bytes(self, backend): # For this test we need an odd length string. BMPString is UCS-2 # encoded so it will always be even length and OpenSSL will error if # you pass an odd length string without encoding it properly first. name = x509.Name([ x509.NameAttribute( NameOID.COMMON_NAME, u'cryptography.io', _ASN1Type.BMPString ), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) assert name.public_bytes(backend) == binascii.unhexlify( b"30383127302506035504031e1e00630072007900700074006f00670072006100" b"7000680079002e0069006f310d300b060355040a0c0450794341" ) @pytest.mark.requires_backend_interface(interface=X509Backend) def test_universalstring_bytes(self, backend): # UniversalString is UCS-4 name = x509.Name([ x509.NameAttribute( NameOID.COMMON_NAME, u'cryptography.io', _ASN1Type.UniversalString ), x509.NameAttribute(NameOID.ORGANIZATION_NAME, u'PyCA'), ]) assert name.public_bytes(backend) == binascii.unhexlify( b"30563145304306035504031c3c00000063000000720000007900000070000000" b"740000006f000000670000007200000061000000700000006800000079000000" b"2e000000690000006f310d300b060355040a0c0450794341" ) @pytest.mark.supported( only_if=lambda backend: backend.ed25519_supported(), skip_message="Requires OpenSSL with Ed25519 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestEd25519Certificate(object): def test_load_pem_cert(self, backend): cert = _load_cert( os.path.join("x509", "ed25519", "root-ed25519.pem"), x509.load_pem_x509_certificate, backend ) # self-signed, so this will work cert.public_key().verify(cert.signature, cert.tbs_certificate_bytes) assert isinstance(cert, x509.Certificate) assert cert.serial_number == 9579446940964433301 assert cert.signature_hash_algorithm is None assert cert.signature_algorithm_oid == SignatureAlgorithmOID.ED25519 @pytest.mark.supported( only_if=lambda backend: backend.ed448_supported(), skip_message="Requires OpenSSL with Ed448 support" ) @pytest.mark.requires_backend_interface(interface=X509Backend) class TestEd448Certificate(object): def test_load_pem_cert(self, backend): cert = _load_cert( os.path.join("x509", "ed448", "root-ed448.pem"), x509.load_pem_x509_certificate, backend ) # self-signed, so this will work cert.public_key().verify(cert.signature, cert.tbs_certificate_bytes) assert isinstance(cert, x509.Certificate) assert cert.serial_number == 448 assert cert.signature_hash_algorithm is None assert cert.signature_algorithm_oid == SignatureAlgorithmOID.ED448 def test_random_serial_number(monkeypatch): sample_data = os.urandom(20) def notrandom(size): assert size == len(sample_data) return sample_data monkeypatch.setattr(os, "urandom", notrandom) serial_number = x509.random_serial_number() assert ( serial_number == utils.int_from_bytes(sample_data, "big") >> 1 ) assert serial_number.bit_length() < 160

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null

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null

0

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7c6fb68062cf367ed6e9e36afe007ca0ca5f2f0c

866

py

Python

evewspace/Teamspeak/default_settings.py

gpapaz/eve-wspace

6b46d120c5ca8d27546113f51fd74fd7797dcbfc

[ "Apache-2.0" ]

null

evewspace/Teamspeak/default_settings.py

gpapaz/eve-wspace

6b46d120c5ca8d27546113f51fd74fd7797dcbfc

[ "Apache-2.0" ]

null

evewspace/Teamspeak/default_settings.py

gpapaz/eve-wspace

6b46d120c5ca8d27546113f51fd74fd7797dcbfc

[ "Apache-2.0" ]

null

# Eve W-Space # Copyright 2014 Andrew Austin and contributors # # 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. from core.models import ConfigEntry from Teamspeak.models import TeamspeakServer from core.utils import get_config def load_defaults(): ts3 = TeamspeakServer.create("localhost", "baduser","badpass","10011", "9887") ts3.save()

37.652174

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1

0

1

0

3

7c7361013f3a7b9971368dc2c25a05418213cbf7

29

py

Python

UnitTests/__init__.py

YuriShporhun/YBio

420e1fa8c8d0d56bfb6e56f1afcf277c73f1d968

[ "Apache-2.0" ]

null

UnitTests/__init__.py

YuriShporhun/YBio

420e1fa8c8d0d56bfb6e56f1afcf277c73f1d968

[ "Apache-2.0" ]

null

UnitTests/__init__.py

YuriShporhun/YBio

420e1fa8c8d0d56bfb6e56f1afcf277c73f1d968

[ "Apache-2.0" ]

null

__author__ = 'Yuri Shporhun'

14.5

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1

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null

0

1

0

null

0

3

7c7a35ec575fe9f29dac44ba63baf9dd56d48655

1,057

py

Python

response/core/models/user_external.py

dgzlopes/response

2e8d6d1110cdac302a3552b66f33d439dea37a7b

[ "MIT" ]

8

2020-12-13T09:36:43.000Z

2022-03-31T23:35:31.000Z

response/core/models/user_external.py

dgzlopes/response

2e8d6d1110cdac302a3552b66f33d439dea37a7b

[ "MIT" ]

39

2020-10-02T15:56:55.000Z

2022-01-19T11:58:41.000Z

response/core/models/user_external.py

dgzlopes/response

2e8d6d1110cdac302a3552b66f33d439dea37a7b

[ "MIT" ]

3

2020-10-30T19:46:31.000Z

2021-05-14T04:59:39.000Z

from django.contrib.auth.models import User from django.db import models class ExternalUserManager(models.Manager): def get_or_create_slack(self, *args, **kwargs): return self.get_or_create(app_id="slack", *args, **kwargs) def update_or_create_slack(self, *args, **kwargs): return self.update_or_create(app_id="slack", *args, **kwargs) class ExternalUser(models.Model): class Meta: unique_together = ("owner", "app_id", "external_id") owner = models.ForeignKey(User, on_delete=models.PROTECT, null=True, blank=True) app_id = models.CharField(max_length=50, blank=False, null=False) external_id = models.CharField(max_length=50, blank=False, null=False) display_name = models.CharField(max_length=50, blank=False, null=False) full_name = models.CharField(max_length=50, blank=True, null=True) email = models.CharField(max_length=100, blank=True, null=True) objects = ExternalUserManager() def __str__(self): return f"{self.display_name or self.external_id} ({self.app_id})"

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null

0

1

0

null

0

1

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7c7c81414791a11a686c1db3350b4387ca49624e

512

py

Python

tests/system/test_platform.py

paulocoutinhox/pygemstones

79397ee187670dc78746a3b3f64ca6118cd3a86c

[ "MIT" ]

2

2021-11-28T11:13:07.000Z

2022-02-02T02:26:47.000Z

tests/system/test_platform.py

paulocoutinhox/pygemstones

79397ee187670dc78746a3b3f64ca6118cd3a86c

[ "MIT" ]

4

2022-01-04T22:22:09.000Z

2022-01-21T06:44:03.000Z

tests/system/test_platform.py

paulocoutinhox/pygemstones

79397ee187670dc78746a3b3f64ca6118cd3a86c

[ "MIT" ]

null

import pygemstones.system.platform as p # ----------------------------------------------------------------------------- def test_windows(): ret = p.is_windows() assert isinstance(ret, bool) # ----------------------------------------------------------------------------- def test_linux(): ret = p.is_linux() assert isinstance(ret, bool) # ----------------------------------------------------------------------------- def test_macos(): ret = p.is_macos() assert isinstance(ret, bool)

25.6

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7cb5de8677ae5ad6a1057d991768a49b492ffbc5

519

py

Python

ultron/actions/__init__.py

Prakash2403/ultron

7d1067eb98ef52f6a88299534ea204e7ae45d7a7

[ "MIT" ]

13

2017-08-15T15:50:13.000Z

2019-06-03T10:24:50.000Z

ultron/actions/__init__.py

Prakash2403/ultron

7d1067eb98ef52f6a88299534ea204e7ae45d7a7

[ "MIT" ]

3

2017-08-29T16:35:04.000Z

2021-06-01T23:49:16.000Z

ultron/actions/__init__.py

Prakash2403/ultron

7d1067eb98ef52f6a88299534ea204e7ae45d7a7

[ "MIT" ]

4

2017-08-16T09:33:59.000Z

2019-06-05T07:25:30.000Z

""" The base class for all actions. For defining a new action, inherit this class, then define all the associated methods. """ from abc import abstractmethod, ABC class Action(ABC): @abstractmethod def execute(self, *args, **kwargs): return @abstractmethod def post_execute(self, *args, **kwargs): return @abstractmethod def pre_execute(self, *args, **kwargs): return def run(self): self.pre_execute() self.execute() self.post_execute()

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null

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1

0

3

7cba2cd283da139416a5e9b54e91d7ae58a1f4e5

143,685

py

Python

swotann/nnetwork.py

dighr/swot-webapp

17f738a1e9f0e11b9fe9625ddd8c9533d5f36e8f

[ "MIT" ]

null

swotann/nnetwork.py

dighr/swot-webapp

17f738a1e9f0e11b9fe9625ddd8c9533d5f36e8f

[ "MIT" ]

null

swotann/nnetwork.py

dighr/swot-webapp

17f738a1e9f0e11b9fe9625ddd8c9533d5f36e8f

[ "MIT" ]

null

import base64 import datetime import io import os import matplotlib as mpl import matplotlib.pyplot as plt import numpy as np from xlrd.xldate import xldate_as_datetime from yattag import Doc plt.rcParams.update({"figure.autolayout": True}) import matplotlib.gridspec as gridspec import pandas as pd import scipy.stats import tensorflow as tf from sklearn.model_selection import train_test_split from sklearn.preprocessing import MinMaxScaler import logging """ TF_CPP_MIN_LOG_LEVEL: Defaults to 0, so all logs are shown. Set TF_CPP_MIN_LOG_LEVEL to 1 to filter out INFO logs, 2 to additionally filter out WARNING, 3 to additionally filter out ERROR. """ os.environ["TF_CPP_MIN_LOG_LEVEL"] = "1" from tensorflow import keras class NNetwork(object): def __init__(self, network_count=200, epochs=1000): logging.getLogger().setLevel(logging.INFO) self.xl_dateformat = r"%Y-%m-%dT%H:%M" self.model = None self.pretrained_networks = [] self.software_version = "2.0.1" self.input_filename = None self.today = str(datetime.date.today()) self.avg_time_elapsed = 0 self.predictors_scaler = MinMaxScaler(feature_range=(-1, 1)) self.targets_scaler = MinMaxScaler(feature_range=(-1, 1)) self.history = None self.file = None self.skipped_rows = [] self.ruleset = [] self.layer1_neurons = 12 self.network_count = network_count self.epochs = epochs self.predictors = None self.targets = None self.predictions = None self.avg_case_results_am = None self.avg_case_results_pm = None self.worst_case_results_am = None self.worst_case_results_pm = None self.WB_bandwidth = None self.post_process_check = False # Is post-processed better than raw. If False, uses raw results, if true, uses post-processed results self.optimizer = keras.optimizers.Nadam(lr=0.01, beta_1=0.9, beta_2=0.999) self.model = keras.models.Sequential() self.model.add( keras.layers.Dense(self.layer1_neurons, input_dim=5, activation="tanh") ) self.model.add(keras.layers.Dense(1, activation="linear")) self.model.compile(loss="mse", optimizer=self.optimizer, metrics=["mse"]) def import_data_from_csv(self, filename): """ Imports data to the network by a comma-separated values (CSV) file. Load data to a network that are stored in .csv file format. The data loaded from this method can be used both for training reasons as well as to make predictions. :param filename: String containing the filename of the .csv file containing the input data (e.g "input_data.csv") """ df = pd.read_csv(filename) self.file = df.copy() global FRC_IN global FRC_OUT global WATTEMP global COND # Locate the fields used as inputs/predictors and outputs in the loaded file # and split them if "se1_frc" in self.file.columns: FRC_IN = "se1_frc" WATTEMP = "se1_wattemp" COND = "se1_cond" FRC_OUT = "se4_frc" elif "ts_frc1" in self.file.columns: FRC_IN = "ts_frc1" WATTEMP = "ts_wattemp" COND = "ts_cond" FRC_OUT = "hh_frc1" elif "ts_frc" in self.file.columns: FRC_IN = "ts_frc" WATTEMP = "ts_wattemp" COND = "ts_cond" FRC_OUT = "hh_frc" # Standardize the DataFrame by specifying rules # To add a new rule, call the method execute_rule with the parameters (description, affected_column, query) self.execute_rule("Invalid tapstand FRC", FRC_IN, self.file[FRC_IN].isnull()) self.execute_rule("Invalid household FRC", FRC_OUT, self.file[FRC_OUT].isnull()) self.execute_rule( "Invalid tapstand date/time", "ts_datetime", self.valid_dates(self.file["ts_datetime"]), ) self.execute_rule( "Invalid household date/time", "hh_datetime", self.valid_dates(self.file["hh_datetime"]), ) self.skipped_rows = df.loc[df.index.difference(self.file.index)] self.file.reset_index(drop=True, inplace=True) # fix dropped indices in pandas # Locate the rows of the missing data drop_threshold = 0.90 * len(self.file.loc[:, [FRC_IN]]) nan_rows_watt = self.file.loc[self.file[WATTEMP].isnull()] if len(nan_rows_watt) < drop_threshold: self.execute_rule( "Missing Water Temperature Measurement", WATTEMP, self.file[WATTEMP].isnull(), ) nan_rows_cond = self.file.loc[self.file[COND].isnull()] if len(nan_rows_cond) < drop_threshold: self.execute_rule("Missing EC Measurement", COND, self.file[COND].isnull()) self.skipped_rows = df.loc[df.index.difference(self.file.index)] self.file.reset_index(drop=True, inplace=True) start_date = self.file["ts_datetime"] end_date = self.file["hh_datetime"] durations = [] all_dates = [] collection_time = [] for i in range(len(start_date)): try: # excel type start = float(start_date[i]) end = float(end_date[i]) start = xldate_as_datetime(start, datemode=0) if start.hour > 12: collection_time = np.append(collection_time, 1) else: collection_time = np.append(collection_time, 0) end = xldate_as_datetime(end, datemode=0) except ValueError: # kobo type start = start_date[i][:16].replace("/", "-") end = end_date[i][:16].replace("/", "-") start = datetime.datetime.strptime(start, self.xl_dateformat) if start.hour > 12: collection_time = np.append(collection_time, 1) else: collection_time = np.append(collection_time, 0) end = datetime.datetime.strptime(end, self.xl_dateformat) durations.append((end - start).total_seconds()) all_dates.append(datetime.datetime.strftime(start, self.xl_dateformat)) self.durations = durations self.time_of_collection = collection_time self.avg_time_elapsed = np.mean(durations) # Extract the column of dates for all data and put them in YYYY-MM-DD format self.file["formatted_date"] = all_dates predictors = { FRC_IN: self.file[FRC_IN], "elapsed time": (np.array(self.durations) / 3600), "time of collection (0=AM, 1=PM)": self.time_of_collection, } self.targets = self.file.loc[:, FRC_OUT] self.var_names = [ "Tapstand FRC (mg/L)", "Elapsed Time", "time of collection (0=AM, 1=PM)", ] self.predictors = pd.DataFrame(predictors) if len(nan_rows_watt) < drop_threshold: self.predictors[WATTEMP] = self.file[WATTEMP] self.var_names.append("Water Temperature(" + r"$\degree$" + "C)") self.median_wattemp = np.median(self.file[WATTEMP].dropna().to_numpy()) self.upper95_wattemp = np.percentile( self.file[WATTEMP].dropna().to_numpy(), 95 ) if len(nan_rows_cond) < drop_threshold: self.predictors[COND] = self.file[COND] self.var_names.append("EC (" + r"$\mu$" + "s/cm)") self.median_cond = np.median(self.file[COND].dropna().to_numpy()) self.upper95_cond = np.percentile(self.file[COND].dropna().to_numpy(), 95) self.targets = self.targets.values.reshape(-1, 1) self.datainputs = self.predictors self.dataoutputs = self.targets self.input_filename = filename def set_up_model(self): self.optimizer = keras.optimizers.Nadam(lr=0.01, beta_1=0.9, beta_2=0.999) self.model = keras.models.Sequential() self.model.add( keras.layers.Dense( self.layer1_neurons, input_dim=len(self.datainputs.columns), activation="tanh", ) ) self.model.add(keras.layers.Dense(1, activation="linear")) self.model.compile(loss="mse", optimizer=self.optimizer) def train_SWOT_network(self, directory): """Train the set of 200 neural networks on SWOT data Trains an ensemble of 200 neural networks on se1_frc, water temperature, water conductivity.""" if not os.path.exists(directory): os.makedirs(directory) self.predictors_scaler = self.predictors_scaler.fit(self.predictors) self.targets_scaler = self.targets_scaler.fit(self.targets) x = self.predictors t = self.targets self.calibration_predictions = [] self.trained_models = {} for i in range(self.network_count): logging.info('Training Network ' + str(i)) model_out = self.train_network(x, t, directory) self.trained_models.update({'model_' + str(i): model_out}) def train_network(self, x, t, directory): """ Trains a single Neural Network on imported data. This method trains Neural Network on data that have previously been imported to the network using the import_data_from_csv() method. The network used is a Multilayer Perceptron (MLP). Input and Output data are normalized using MinMax Normalization. The input dataset is split in training and validation datasets, where 80% of the inputs are the training dataset and 20% is the validation dataset. The training history is stored in a variable called self.history (see keras documentation: keras.model.history object) Performance metrics are calculated and stored for evaluating the network performance. """ tf.keras.backend.clear_session() early_stopping_monitor = keras.callbacks.EarlyStopping(monitor='val_loss', min_delta=0, patience=10, restore_best_weights=True) x_norm = self.predictors_scaler.transform(x) t_norm = self.targets_scaler.transform(t) trained_model = keras.models.clone_model(self.model) x_norm_train, x_norm_val, t_norm_train, t_norm_val = train_test_split(x_norm, t_norm, train_size=0.333, shuffle=True) new_weights = [np.random.uniform(-0.05, 0.05, w.shape) for w in trained_model.get_weights()] trained_model.set_weights(new_weights) trained_model.compile(loss='mse', optimizer=self.optimizer) trained_model.fit(x_norm_train, t_norm_train, epochs=self.epochs, validation_data=(x_norm_val, t_norm_val), callbacks=[early_stopping_monitor], verbose=0, batch_size=len(t_norm_train)) self.calibration_predictions.append(self.targets_scaler.inverse_transform(trained_model.predict(x_norm))) return trained_model def calibration_performance_evaluation(self, filename): Y_true = np.array(self.targets) Y_pred = np.array(self.calibration_predictions) FRC_X = self.datainputs[FRC_IN].to_numpy() capture_all = ( np.less_equal(Y_true, np.max(Y_pred, axis=0)) * np.greater_equal(Y_true, np.min(Y_pred, axis=0)) * 1 ) capture_90 = ( np.less_equal(Y_true, np.percentile(Y_pred, 95, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 5, axis=0)) * 1 ) capture_80 = ( np.less_equal(Y_true, np.percentile(Y_pred, 90, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 10, axis=0)) * 1 ) capture_70 = ( np.less_equal(Y_true, np.percentile(Y_pred, 85, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 15, axis=0)) * 1 ) capture_60 = ( np.less_equal(Y_true, np.percentile(Y_pred, 80, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 20, axis=0)) * 1 ) capture_50 = ( np.less_equal(Y_true, np.percentile(Y_pred, 75, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 25, axis=0)) * 1 ) capture_40 = ( np.less_equal(Y_true, np.percentile(Y_pred, 70, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 30, axis=0)) * 1 ) capture_30 = ( np.less_equal(Y_true, np.percentile(Y_pred, 65, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 35, axis=0)) * 1 ) capture_20 = ( np.less_equal(Y_true, np.percentile(Y_pred, 60, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 40, axis=0)) * 1 ) capture_10 = ( np.less_equal(Y_true, np.percentile(Y_pred, 55, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 45, axis=0)) * 1 ) capture_all_20 = capture_all * np.less(Y_true, 0.2) capture_90_20 = capture_90 * np.less(Y_true, 0.2) capture_80_20 = capture_80 * np.less(Y_true, 0.2) capture_70_20 = capture_70 * np.less(Y_true, 0.2) capture_60_20 = capture_60 * np.less(Y_true, 0.2) capture_50_20 = capture_50 * np.less(Y_true, 0.2) capture_40_20 = capture_40 * np.less(Y_true, 0.2) capture_30_20 = capture_30 * np.less(Y_true, 0.2) capture_20_20 = capture_20 * np.less(Y_true, 0.2) capture_10_20 = capture_10 * np.less(Y_true, 0.2) length_20 = np.sum(np.less(Y_true, 0.2)) test_len = len(Y_true) capture_all_sum = np.sum(capture_all) capture_90_sum = np.sum(capture_90) capture_80_sum = np.sum(capture_80) capture_70_sum = np.sum(capture_70) capture_60_sum = np.sum(capture_60) capture_50_sum = np.sum(capture_50) capture_40_sum = np.sum(capture_40) capture_30_sum = np.sum(capture_30) capture_20_sum = np.sum(capture_20) capture_10_sum = np.sum(capture_10) capture_all_20_sum = np.sum(capture_all_20) capture_90_20_sum = np.sum(capture_90_20) capture_80_20_sum = np.sum(capture_80_20) capture_70_20_sum = np.sum(capture_70_20) capture_60_20_sum = np.sum(capture_60_20) capture_50_20_sum = np.sum(capture_50_20) capture_40_20_sum = np.sum(capture_40_20) capture_30_20_sum = np.sum(capture_30_20) capture_20_20_sum = np.sum(capture_20_20) capture_10_20_sum = np.sum(capture_10_20) capture = [ capture_10_sum / test_len, capture_20_sum / test_len, capture_30_sum / test_len, capture_40_sum / test_len, capture_50_sum / test_len, capture_60_sum / test_len, capture_70_sum / test_len, capture_80_sum / test_len, capture_90_sum / test_len, capture_all_sum / test_len, ] capture_20 = [ capture_10_20_sum / length_20, capture_20_20_sum / length_20, capture_30_20_sum / length_20, capture_40_20_sum / length_20, capture_50_20_sum / length_20, capture_60_20_sum / length_20, capture_70_20_sum / length_20, capture_80_20_sum / length_20, capture_90_20_sum / length_20, capture_all_20_sum / length_20, ] self.percent_capture_cal = capture_all_sum / test_len self.percent_capture_02_cal = capture_all_20_sum / length_20 self.CI_reliability_cal = ( (0.1 - capture_10_sum / test_len) ** 2 + (0.2 - capture_20_sum / test_len) ** 2 + (0.3 - capture_30_sum / test_len) ** 2 + (0.4 - capture_40_sum / test_len) ** 2 + (0.5 - capture_50_sum / test_len) ** 2 + (0.6 - capture_60_sum / test_len) ** 2 + (0.7 - capture_70_sum / test_len) ** 2 + (0.8 - capture_80_sum / test_len) ** 2 + (0.9 - capture_90_sum / test_len) ** 2 + (1 - capture_all_sum / test_len) ** 2 ) self.CI_reliability_02_cal = ( (0.1 - capture_10_20_sum / length_20) ** 2 + (0.2 - capture_20_20_sum / length_20) ** 2 + (0.3 - capture_30_20_sum / length_20) ** 2 + (0.4 - capture_40_20_sum / length_20) ** 2 + (0.5 - capture_50_20_sum / length_20) ** 2 + (0.6 - capture_60_20_sum / length_20) ** 2 + (0.7 - capture_70_20_sum / length_20) ** 2 + (0.8 - capture_80_20_sum / length_20) ** 2 + (0.9 - capture_90_20_sum / length_20) ** 2 + (1 - capture_all_20_sum / length_20) ** 2 ) # Rank Histogram rank = [] for a in range(0, len(Y_true)): n_lower = np.sum(np.greater(Y_true[a], Y_pred[:, a])) n_equal = np.sum(np.equal(Y_true[a], Y_pred[:, a])) deviate_rank = np.random.random_integers(0, n_equal) rank = np.append(rank, n_lower + deviate_rank) rank_hist = np.histogram(rank, bins=self.network_count + 1) delta = np.sum((rank_hist[0] - (test_len / ((self.network_count + 1)))) ** 2) delta_0 = self.network_count * test_len / (self.network_count + 1) self.delta_score_cal = delta / delta_0 c = self.network_count alpha = np.zeros((test_len, (c + 1))) beta = np.zeros((test_len, (c + 1))) low_outlier = 0 high_outlier = 0 for a in range(0, test_len): observation = Y_true[a] forecast = np.sort(Y_pred[:, a]) for b in range(1, c): if observation > forecast[b]: alpha[a, b] = forecast[b] - forecast[b - 1] beta[a, b] = 0 elif forecast[b] > observation > forecast[b - 1]: alpha[a, b] = observation - forecast[b - 1] beta[a, b] = forecast[b] - observation else: alpha[a, b] = 0 beta[a, b] = forecast[b] - forecast[b - 1] # overwrite boundaries in case of outliers if observation < forecast[0]: beta[a, 0] = forecast[0] - observation low_outlier += 1 if observation > forecast[c - 1]: alpha[a, c] = observation - forecast[c - 1] high_outlier += 1 alpha_bar = np.mean(alpha, axis=0) beta_bar = np.mean(beta, axis=0) g_bar = alpha_bar + beta_bar o_bar = beta_bar / (alpha_bar + beta_bar) if low_outlier > 0: o_bar[0] = low_outlier / test_len g_bar[0] = beta_bar[0] / o_bar[0] else: o_bar[0] = 0 g_bar[0] = 0 if high_outlier > 0: o_bar[c] = high_outlier / test_len g_bar[c] = alpha_bar[c] / o_bar[c] else: o_bar[c] = 0 g_bar[c] = 0 p_i = np.arange(0 / c, (c + 1) / c, 1 / c) self.CRPS_cal = np.sum( g_bar * ((1 - o_bar) * (p_i**2) + o_bar * ((1 - p_i) ** 2)) ) CI_x = [0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 1.00] fig = plt.figure(figsize=(15, 10), dpi=100) gridspec.GridSpec(2, 3) plt.subplot2grid((2, 3), (0, 0), colspan=2, rowspan=2) plt.axhline(0.2, c="k", ls="--", label="Point-of-consumption FRC = 0.2 mg/L") plt.scatter( FRC_X, Y_true, edgecolors="k", facecolors="None", s=20, label="Observed" ) plt.scatter( FRC_X, np.median(Y_pred, axis=0), facecolors="r", edgecolors="None", s=10, label="Forecast Median", ) plt.vlines( FRC_X, np.min(Y_pred, axis=0), np.max(Y_pred, axis=0), color="r", label="Forecast Range", ) plt.xlabel("Point-of-Distribution FRC (mg/L)") plt.ylabel("Point-of-Consumption FRC (mg/L)") plt.xlim([0, np.max(FRC_X)]) plt.legend( bbox_to_anchor=(0.001, 0.999), shadow=False, labelspacing=0.1, fontsize="small", handletextpad=0.1, loc="upper left", ) ax1 = fig.axes[0] ax1.set_title("(a)", y=0.88, x=0.05) plt.subplot2grid((2, 3), (0, 2), colspan=1, rowspan=1) plt.plot(CI_x, CI_x, c="k") plt.scatter(CI_x, capture, label="All observations") plt.scatter(CI_x, capture_20, label="Point-of-Consumption FRC below 0.2 mg/L") plt.xlabel("Ensemble Confidence Interval") plt.ylabel("Percent Capture") plt.ylim([0, 1]) plt.xlim([0, 1]) plt.legend( bbox_to_anchor=(0.001, 0.999), shadow=False, labelspacing=0.1, fontsize="small", handletextpad=0.1, loc="upper left", ) ax2 = fig.axes[1] ax2.set_title("(b)", y=0.88, x=0.05) plt.subplot2grid((2, 3), (1, 2), colspan=1, rowspan=1) plt.hist(rank, bins=(self.network_count + 1), density=True) plt.xlabel("Rank") plt.ylabel("Probability") ax3 = fig.axes[2] ax3.set_title("(c)", y=0.88, x=0.05) plt.savefig( os.path.splitext(filename)[0] + "_Calibration_Diagnostic_Figs.png", format="png", bbox_inches="tight", ) plt.close() myStringIOBytes = io.BytesIO() plt.savefig(myStringIOBytes, format="png", bbox_inches="tight") myStringIOBytes.seek(0) my_base_64_pngData = base64.b64encode(myStringIOBytes.read()) return my_base_64_pngData def get_bw(self): Y_true = np.array(self.targets) Y_pred = np.array(self.calibration_predictions)[:, :, 0] s2 = [] xt_yt = [] for a in range(0, len(Y_true)): observation = Y_true[a] forecast = np.sort(Y_pred[:, a]) s2 = np.append(s2, np.var(forecast)) xt_yt = np.append(xt_yt, (np.mean(forecast) - observation) ** 2) WB_bw = np.mean(xt_yt) - (1 + 1 / self.network_count) * np.mean(s2) return WB_bw def post_process_performance_eval(self, bandwidth): Y_true = np.squeeze(np.array(self.targets)) Y_pred = np.array(self.calibration_predictions)[:, :, 0] test_len = len(Y_true) min_CI = [] max_CI = [] CI_90_Lower = [] CI_90_Upper = [] CI_80_Lower = [] CI_80_Upper = [] CI_70_Lower = [] CI_70_Upper = [] CI_60_Lower = [] CI_60_Upper = [] CI_50_Lower = [] CI_50_Upper = [] CI_40_Lower = [] CI_40_Upper = [] CI_30_Lower = [] CI_30_Upper = [] CI_20_Lower = [] CI_20_Upper = [] CI_10_Lower = [] CI_10_Upper = [] CI_median = [] CRPS = [] Kernel_Risk = [] evaluation_range = np.arange(-10, 10.001, 0.001) # compute CRPS as well as the confidence intervals of each ensemble forecast for a in range(0, test_len): scipy_kde = scipy.stats.gaussian_kde(Y_pred[:, a], bw_method=bandwidth) scipy_pdf = scipy_kde.evaluate(evaluation_range) * 0.001 scipy_cdf = np.cumsum(scipy_pdf) min_CI = np.append( min_CI, evaluation_range[np.max(np.where(scipy_cdf == 0)[0])] ) max_CI = np.append(max_CI, evaluation_range[np.argmax(scipy_cdf)]) CI_90_Lower = np.append( CI_90_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.05)))] ) CI_90_Upper = np.append( CI_90_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.95)))] ) CI_80_Lower = np.append( CI_80_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.1)))] ) CI_80_Upper = np.append( CI_80_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.9)))] ) CI_70_Lower = np.append( CI_70_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.15)))] ) CI_70_Upper = np.append( CI_70_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.85)))] ) CI_60_Lower = np.append( CI_60_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.2)))] ) CI_60_Upper = np.append( CI_60_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.8)))] ) CI_50_Lower = np.append( CI_50_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.25)))] ) CI_50_Upper = np.append( CI_50_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.75)))] ) CI_40_Lower = np.append( CI_40_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.3)))] ) CI_40_Upper = np.append( CI_40_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.7)))] ) CI_30_Lower = np.append( CI_30_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.35)))] ) CI_30_Upper = np.append( CI_30_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.65)))] ) CI_20_Lower = np.append( CI_20_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.4)))] ) CI_20_Upper = np.append( CI_20_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.6)))] ) CI_10_Lower = np.append( CI_10_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.45)))] ) CI_10_Upper = np.append( CI_10_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.55)))] ) CI_median = np.append( CI_median, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.50)))] ) Kernel_Risk = np.append(Kernel_Risk, scipy_kde.integrate_box_1d(-10, 0.2)) Heaviside = (evaluation_range >= Y_true[a]).astype(int) CRPS_dif = (scipy_cdf - Heaviside) ** 2 CRPS = np.append(CRPS, np.sum(CRPS_dif * 0.001)) mean_CRPS = np.mean(CRPS) capture_all = ( np.less_equal(Y_true, max_CI) * np.greater_equal(Y_true, min_CI) * 1 ) capture_90 = ( np.less_equal(Y_true, CI_90_Upper) * np.greater_equal(Y_true, CI_90_Lower) * 1 ) capture_80 = ( np.less_equal(Y_true, CI_80_Upper) * np.greater_equal(Y_true, CI_80_Lower) * 1 ) capture_70 = ( np.less_equal(Y_true, CI_70_Upper) * np.greater_equal(Y_true, CI_70_Lower) * 1 ) capture_60 = ( np.less_equal(Y_true, CI_60_Upper) * np.greater_equal(Y_true, CI_60_Lower) * 1 ) capture_50 = ( np.less_equal(Y_true, CI_50_Upper) * np.greater_equal(Y_true, CI_50_Lower) * 1 ) capture_40 = ( np.less_equal(Y_true, CI_40_Upper) * np.greater_equal(Y_true, CI_40_Lower) * 1 ) capture_30 = ( np.less_equal(Y_true, CI_30_Upper) * np.greater_equal(Y_true, CI_30_Lower) * 1 ) capture_20 = ( np.less_equal(Y_true, CI_20_Upper) * np.greater_equal(Y_true, CI_20_Lower) * 1 ) capture_10 = ( np.less_equal(Y_true, CI_10_Upper) * np.greater_equal(Y_true, CI_10_Lower) * 1 ) length_20 = np.sum(np.less(Y_true, 0.2)) capture_all_20 = capture_all * np.less(Y_true, 0.2) capture_90_20 = capture_90 * np.less(Y_true, 0.2) capture_80_20 = capture_80 * np.less(Y_true, 0.2) capture_70_20 = capture_70 * np.less(Y_true, 0.2) capture_60_20 = capture_60 * np.less(Y_true, 0.2) capture_50_20 = capture_50 * np.less(Y_true, 0.2) capture_40_20 = capture_40 * np.less(Y_true, 0.2) capture_30_20 = capture_30 * np.less(Y_true, 0.2) capture_20_20 = capture_20 * np.less(Y_true, 0.2) capture_10_20 = capture_10 * np.less(Y_true, 0.2) capture_all_sum = np.sum(capture_all) capture_90_sum = np.sum(capture_90) capture_80_sum = np.sum(capture_80) capture_70_sum = np.sum(capture_70) capture_60_sum = np.sum(capture_60) capture_50_sum = np.sum(capture_50) capture_40_sum = np.sum(capture_40) capture_30_sum = np.sum(capture_30) capture_20_sum = np.sum(capture_20) capture_10_sum = np.sum(capture_10) capture_all_20_sum = np.sum(capture_all_20) capture_90_20_sum = np.sum(capture_90_20) capture_80_20_sum = np.sum(capture_80_20) capture_70_20_sum = np.sum(capture_70_20) capture_60_20_sum = np.sum(capture_60_20) capture_50_20_sum = np.sum(capture_50_20) capture_40_20_sum = np.sum(capture_40_20) capture_30_20_sum = np.sum(capture_30_20) capture_20_20_sum = np.sum(capture_20_20) capture_10_20_sum = np.sum(capture_10_20) capture_sum_squares = ( (0.1 - capture_10_sum / test_len) ** 2 + (0.2 - capture_20_sum / test_len) ** 2 + (0.3 - capture_30_sum / test_len) ** 2 + (0.4 - capture_40_sum / test_len) ** 2 + (0.5 - capture_50_sum / test_len) ** 2 + (0.6 - capture_60_sum / test_len) ** 2 + (0.7 - capture_70_sum / test_len) ** 2 + (0.8 - capture_80_sum / test_len) ** 2 + (0.9 - capture_90_sum / test_len) ** 2 + (1 - capture_all_sum / test_len) ** 2 ) capture_20_sum_squares = ( (0.1 - capture_10_20_sum / length_20) ** 2 + (0.2 - capture_20_20_sum / length_20) ** 2 + (0.3 - capture_30_20_sum / length_20) ** 2 + (0.4 - capture_40_20_sum / length_20) ** 2 + (0.5 - capture_50_20_sum / length_20) ** 2 + (0.6 - capture_60_20_sum / length_20) ** 2 + (0.7 - capture_70_20_sum / length_20) ** 2 + (0.8 - capture_80_20_sum / length_20) ** 2 + (0.9 - capture_90_20_sum / length_20) ** 2 + (1 - capture_all_20_sum / length_20) ** 2 ) return ( mean_CRPS, capture_sum_squares, capture_20_sum_squares, capture_all_sum / test_len, capture_all_20_sum / length_20, ) def post_process_cal(self): self.WB_bandwidth = self.get_bw() ( self.CRPS_post_cal, self.CI_reliability_post_cal, self.CI_reliability_02_post_cal, self.percent_capture_post_cal, self.percent_capture_02_post_cal, ) = self.post_process_performance_eval(self.WB_bandwidth) CRPS_Skill = (self.CRPS_post_cal - self.CRPS_cal) / (0 - self.CRPS_cal) CI_Skill = (self.CI_reliability_post_cal - self.CI_reliability_cal) / ( 0 - self.CI_reliability_cal ) CI_20_Skill = (self.CI_reliability_02_post_cal - self.CI_reliability_02_cal) / ( 0 - self.CI_reliability_02_cal ) PC_Skill = (self.percent_capture_post_cal - self.percent_capture_cal) / ( 1 - self.percent_capture_cal ) PC_20_Skill = ( self.percent_capture_02_post_cal - self.percent_capture_02_cal ) / (1 - self.percent_capture_02_cal) Net_Score = CRPS_Skill + CI_Skill + CI_20_Skill + PC_Skill + PC_20_Skill if Net_Score > 0: self.post_process_check = True else: self.post_process_check = False def full_performance_evaluation(self, directory): x_norm = self.predictors_scaler.transform(self.predictors) t_norm = self.targets_scaler.transform(self.targets) base_model = self.model base_model.save(directory + "\\base_network.h5") x_cal_norm, x_test_norm, t_cal_norm, t_test_norm = train_test_split( x_norm, t_norm, test_size=0.25, shuffle=False, random_state=10 ) self.verifying_observations = self.targets_scaler.inverse_transform(t_test_norm) self.test_x_data = self.predictors_scaler.inverse_transform(x_test_norm) early_stopping_monitor = keras.callbacks.EarlyStopping( monitor="val_loss", min_delta=0, patience=10, restore_best_weights=True ) self.verifying_predictions = [] for i in range(0, self.network_count): tf.keras.backend.clear_session() self.model = keras.models.load_model(directory + "\\base_network.h5") x_norm_train, x_norm_val, t_norm_train, t_norm_val = train_test_split( x_cal_norm, t_cal_norm, train_size=1 / 3, shuffle=True, random_state=i**2, ) new_weights = [ np.random.uniform(-0.05, 0.05, w.shape) for w in self.model.get_weights() ] self.model.set_weights(new_weights) self.model.fit( x_norm_train, t_norm_train, epochs=self.epochs, validation_data=(x_norm_val, t_norm_val), callbacks=[early_stopping_monitor], verbose=0, batch_size=len(t_norm_train), ) self.verifying_predictions.append(self.targets_scaler.inverse_transform(self.model.predict(x_test_norm))) Y_true = np.array(self.verifying_observations) Y_pred = np.array(self.verifying_predictions) FRC_X = self.test_x_data[:, 0] capture_all = ( np.less_equal(Y_true, np.max(Y_pred, axis=0)) * np.greater_equal(Y_true, np.min(Y_pred, axis=0)) * 1 ) capture_90 = ( np.less_equal(Y_true, np.percentile(Y_pred, 95, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 5, axis=0)) * 1 ) capture_80 = ( np.less_equal(Y_true, np.percentile(Y_pred, 90, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 10, axis=0)) * 1 ) capture_70 = ( np.less_equal(Y_true, np.percentile(Y_pred, 85, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 15, axis=0)) * 1 ) capture_60 = ( np.less_equal(Y_true, np.percentile(Y_pred, 80, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 20, axis=0)) * 1 ) capture_50 = ( np.less_equal(Y_true, np.percentile(Y_pred, 75, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 25, axis=0)) * 1 ) capture_40 = ( np.less_equal(Y_true, np.percentile(Y_pred, 70, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 30, axis=0)) * 1 ) capture_30 = ( np.less_equal(Y_true, np.percentile(Y_pred, 65, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 35, axis=0)) * 1 ) capture_20 = ( np.less_equal(Y_true, np.percentile(Y_pred, 60, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 40, axis=0)) * 1 ) capture_10 = ( np.less_equal(Y_true, np.percentile(Y_pred, 55, axis=0)) * np.greater_equal(Y_true, np.percentile(Y_pred, 45, axis=0)) * 1 ) capture_all_20 = capture_all * np.less(Y_true, 0.2) capture_90_20 = capture_90 * np.less(Y_true, 0.2) capture_80_20 = capture_80 * np.less(Y_true, 0.2) capture_70_20 = capture_70 * np.less(Y_true, 0.2) capture_60_20 = capture_60 * np.less(Y_true, 0.2) capture_50_20 = capture_50 * np.less(Y_true, 0.2) capture_40_20 = capture_40 * np.less(Y_true, 0.2) capture_30_20 = capture_30 * np.less(Y_true, 0.2) capture_20_20 = capture_20 * np.less(Y_true, 0.2) capture_10_20 = capture_10 * np.less(Y_true, 0.2) length_20 = np.sum(np.less(Y_true, 0.2)) test_len = len(Y_true) capture_all_sum = np.sum(capture_all) capture_90_sum = np.sum(capture_90) capture_80_sum = np.sum(capture_80) capture_70_sum = np.sum(capture_70) capture_60_sum = np.sum(capture_60) capture_50_sum = np.sum(capture_50) capture_40_sum = np.sum(capture_40) capture_30_sum = np.sum(capture_30) capture_20_sum = np.sum(capture_20) capture_10_sum = np.sum(capture_10) capture_all_20_sum = np.sum(capture_all_20) capture_90_20_sum = np.sum(capture_90_20) capture_80_20_sum = np.sum(capture_80_20) capture_70_20_sum = np.sum(capture_70_20) capture_60_20_sum = np.sum(capture_60_20) capture_50_20_sum = np.sum(capture_50_20) capture_40_20_sum = np.sum(capture_40_20) capture_30_20_sum = np.sum(capture_30_20) capture_20_20_sum = np.sum(capture_20_20) capture_10_20_sum = np.sum(capture_10_20) capture = [ capture_10_sum / test_len, capture_20_sum / test_len, capture_30_sum / test_len, capture_40_sum / test_len, capture_50_sum / test_len, capture_60_sum / test_len, capture_70_sum / test_len, capture_80_sum / test_len, capture_90_sum / test_len, capture_all_sum / test_len, ] capture_20 = [ capture_10_20_sum / length_20, capture_20_20_sum / length_20, capture_30_20_sum / length_20, capture_40_20_sum / length_20, capture_50_20_sum / length_20, capture_60_20_sum / length_20, capture_70_20_sum / length_20, capture_80_20_sum / length_20, capture_90_20_sum / length_20, capture_all_20_sum / length_20, ] self.percent_capture_cal = capture_all_sum / test_len self.percent_capture_02_cal = capture_all_20_sum / length_20 self.CI_reliability_cal = ( (0.1 - capture_10_sum / test_len) ** 2 + (0.2 - capture_20_sum / test_len) ** 2 + (0.3 - capture_30_sum / test_len) ** 2 + (0.4 - capture_40_sum / test_len) ** 2 + (0.5 - capture_50_sum / test_len) ** 2 + (0.6 - capture_60_sum / test_len) ** 2 + (0.7 - capture_70_sum / test_len) ** 2 + (0.8 - capture_80_sum / test_len) ** 2 + (0.9 - capture_90_sum / test_len) ** 2 + (1 - capture_all_sum / test_len) ** 2 ) self.CI_reliability_02_cal = ( (0.1 - capture_10_20_sum / length_20) ** 2 + (0.2 - capture_20_20_sum / length_20) ** 2 + (0.3 - capture_30_20_sum / length_20) ** 2 + (0.4 - capture_40_20_sum / length_20) ** 2 + (0.5 - capture_50_20_sum / length_20) ** 2 + (0.6 - capture_60_20_sum / length_20) ** 2 + (0.7 - capture_70_20_sum / length_20) ** 2 + (0.8 - capture_80_20_sum / length_20) ** 2 + (0.9 - capture_90_20_sum / length_20) ** 2 + (1 - capture_all_20_sum / length_20) ** 2 ) # Rank Histogram rank = [] for a in range(0, len(Y_true)): n_lower = np.sum(np.greater(Y_true[a], Y_pred[:, a])) n_equal = np.sum(np.equal(Y_true[a], Y_pred[:, a])) deviate_rank = np.random.random_integers(0, n_equal) rank = np.append(rank, n_lower + deviate_rank) rank_hist = np.histogram(rank, bins=self.network_count + 1) delta = np.sum((rank_hist[0] - (test_len / ((self.network_count + 1)))) ** 2) delta_0 = self.network_count * test_len / (self.network_count + 1) self.delta_score_cal = delta / delta_0 CI_x = [0.10, 0.20, 0.30, 0.40, 0.50, 0.60, 0.70, 0.80, 0.90, 1.00] fig = plt.figure(figsize=(15, 10), dpi=100) gridspec.GridSpec(2, 3) plt.subplot2grid((2, 3), (0, 0), colspan=2, rowspan=2) plt.axhline(0.2, c="k", ls="--", label="Point-of-consumption FRC = 0.2 mg/L") plt.scatter( FRC_X, Y_true, edgecolors="k", facecolors="None", s=20, label="Observed" ) plt.scatter( FRC_X, np.median(Y_pred, axis=0), facecolors="r", edgecolors="None", s=10, label="Forecast Median", ) plt.vlines( FRC_X, np.min(Y_pred, axis=0), np.max(Y_pred, axis=0), color="r", label="Forecast Range", ) plt.xlabel("Point-of-Distribution FRC (mg/L)") plt.ylabel("Point-of-Consumption FRC (mg/L)") plt.subplot2grid((2, 3), (0, 2), colspan=1, rowspan=1) plt.plot(CI_x, CI_x, c='k') plt.scatter(CI_x, capture) plt.scatter(CI_x, capture_20) plt.xlabel("Ensemble Confidence Interval") plt.ylabel("Percent Capture") plt.ylim([0, 1]) plt.xlim([0, 1]) plt.subplot2grid((2, 3), (1, 2), colspan=1, rowspan=1) plt.hist(rank, bins=(self.network_count + 1), density=True) plt.xlabel('Rank') plt.ylabel('Probability') plt.savefig(directory + "\\Verification_Diagnostic_Figs.png", format='png') plt.close() myStringIOBytes = io.BytesIO() plt.savefig(myStringIOBytes, format='png') myStringIOBytes.seek(0) my_base_64_pngData = base64.b64encode(myStringIOBytes.read()) return my_base_64_pngData def set_inputs_for_table(self, storage_target): frc = np.arange(0.20, 2.05, 0.05) lag_time = [storage_target for i in range(0, len(frc))] am_collect = [0 for i in range(0, len(frc))] pm_collect = [1 for i in range(0, len(frc))] temp_med_am = { "ts_frc": frc, "elapsed time": lag_time, "time of collection (0=AM, 1=PM)": am_collect, } temp_med_pm = { "ts_frc": frc, "elapsed time": lag_time, "time of collection (0=AM, 1=PM)": pm_collect, } temp_95_am = { "ts_frc": frc, "elapsed time": lag_time, "time of collection (0=AM, 1=PM)": am_collect, } temp_95_pm = { "ts_frc": frc, "elapsed time": lag_time, "time of collection (0=AM, 1=PM)": pm_collect, } if WATTEMP in self.datainputs.columns: watt_med = [self.median_wattemp for i in range(0, len(frc))] watt_95 = [self.upper95_wattemp for i in range(0, len(frc))] temp_med_am.update({"ts_wattemp": watt_med}) temp_med_pm.update({"ts_wattemp": watt_med}) temp_95_am.update({"ts_wattemp": watt_95}) temp_95_pm.update({"ts_wattemp": watt_95}) if COND in self.datainputs.columns: cond_med = [self.median_cond for i in range(0, len(frc))] cond_95 = [self.upper95_cond for i in range(0, len(frc))] temp_med_am.update({"ts_cond": cond_med}) temp_med_pm.update({"ts_cond": cond_med}) temp_95_am.update({"ts_cond": cond_95}) temp_95_pm.update({"ts_cond": cond_95}) self.avg_case_predictors_am = pd.DataFrame(temp_med_am) self.avg_case_predictors_pm = pd.DataFrame(temp_med_pm) self.worst_case_predictors_am = pd.DataFrame(temp_95_am) self.worst_case_predictors_pm = pd.DataFrame(temp_95_pm) def post_process_predictions(self, results_table_frc): # results_table_frc=results_table_frc.to_numpy() evaluation_range = np.arange(-10, 10.001, 0.001) test1_frc = np.arange(0.2, 2.05, 0.05) bandwidth = self.WB_bandwidth Max_CI = [] Min_CI = [] CI_99_Upper = [] CI_99_Lower = [] CI_95_Upper = [] CI_95_Lower = [] Median_Results = [] risk_00_kernel_frc = [] risk_20_kernel_frc = [] risk_25_kernel_frc = [] risk_30_kernel_frc = [] for a in range(0, len(test1_frc)): scipy_kde = scipy.stats.gaussian_kde(results_table_frc[a, :], bw_method=bandwidth) risk_00_kernel_frc = np.append(risk_00_kernel_frc, scipy_kde.integrate_box_1d(-10, 0)) risk_20_kernel_frc = np.append(risk_20_kernel_frc, scipy_kde.integrate_box_1d(-10, 0.2)) risk_25_kernel_frc = np.append(risk_25_kernel_frc, scipy_kde.integrate_box_1d(-10, 0.25)) risk_30_kernel_frc = np.append(risk_30_kernel_frc, scipy_kde.integrate_box_1d(-10, 0.3)) scipy_pdf = scipy_kde.evaluate(evaluation_range) * 0.001 scipy_cdf = np.cumsum(scipy_pdf) Min_CI = np.append(Min_CI, evaluation_range[np.max(np.where(scipy_cdf == 0)[0])]) Max_CI = np.append(Max_CI, evaluation_range[np.argmax(scipy_cdf)]) CI_99_Upper = np.append(CI_99_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.995)))]) CI_99_Lower = np.append(CI_99_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.005)))]) CI_95_Upper = np.append(CI_95_Upper, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.975)))]) CI_95_Lower = np.append(CI_95_Lower, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.025)))]) Median_Results = np.append(Median_Results, evaluation_range[np.argmin(np.abs((scipy_cdf - 0.5)))]) temp_key = {"Tapstand FRC":np.arange(0.20,2.05,0.05),"median": Median_Results, "Ensemble Minimum": Min_CI, "Ensemble Maximum": Max_CI, "Lower 99 CI": CI_99_Lower, "Upper 99 CI": CI_99_Upper, "Lower 95 CI": CI_95_Lower, "Upper 95 CI": CI_95_Upper, 'probability==0': risk_00_kernel_frc, "probability<=0.20": risk_20_kernel_frc, "probability<=0.25": risk_25_kernel_frc, "probability<=0.30": risk_30_kernel_frc} post_processed_df = pd.DataFrame(temp_key) return post_processed_df def predict(self): """ To make the predictions, a pretrained model must be loaded using the import_pretrained_model() method. The SWOT ANN uses an ensemble of 200 ANNs. All of the 200 ANNs make a prediction on the inputs and the results are stored. The median of all the 200 predictions is calculated and stored here. The method also calculates the probabilities of the target FRC levels to be less than 0.2, 0.25 and 0.3 mg/L respectively. The predictions are target FRC values in mg/L, and the probability values range from 0 to 1. All of the above results are saved in the self.results class field. V2.0 Notes: If at least 1 WQ variable is provided, we do a scenario analysis, providing targets for the average case (median water quality) and the "worst case" using the upper 95th percentile water quality """ # Initialize empty arrays for the probabilities to be appended in. avg_case_results_am = {} avg_case_results_pm = {} worst_case_results_am = {} worst_case_results_pm = {} # Normalize the inputs using the input scaler loaded input_scaler = self.predictors_scaler avg_case_inputs_norm_am = input_scaler.transform(self.avg_case_predictors_am) avg_case_inputs_norm_pm = input_scaler.transform(self.avg_case_predictors_pm) worst_case_inputs_norm_am = input_scaler.transform(self.worst_case_predictors_am) worst_case_inputs_norm_pm = input_scaler.transform(self.worst_case_predictors_pm) ##AVERAGE CASE TARGET w AM COLLECTION # Iterate through all loaded pretrained networks, make predictions based on the inputs, # calculate the median of the predictions and store everything to self.results for j in range(0, self.network_count): key = "se4_frc_net-" + str(j) predictions = self.targets_scaler.inverse_transform( self.trained_models["model_" + str(j)].predict(avg_case_inputs_norm_am)).tolist() temp = sum(predictions, []) avg_case_results_am.update({key: temp}) self.avg_case_results_am = pd.DataFrame(avg_case_results_am) self.avg_case_results_am["median"] = self.avg_case_results_am.median(axis=1) for i in self.avg_case_predictors_am.keys(): self.avg_case_results_am.update({i: self.avg_case_predictors_am[i].tolist()}) self.avg_case_results_am[i] = self.avg_case_predictors_am[i].tolist() # Include the inputs/predictors in the self.results variable for i in self.avg_case_predictors_am.keys(): self.avg_case_results_am.update({i: self.avg_case_predictors_am[i].tolist()}) self.avg_case_results_am[i] = self.avg_case_predictors_am[i].tolist() if self.post_process_check == False: # Calculate all the probability fields and store them to self.results # results_table_frc_avg = self.results.iloc[:, 0:(self.network_count - 1)] self.avg_case_results_am["probability<=0.20"] = np.sum( np.less_equal(self.avg_case_results_am.iloc[:, 0:(self.network_count - 1)], 0.2), axis=1) / self.network_count self.avg_case_results_am["probability<=0.25"] = np.sum( np.less_equal(self.avg_case_results_am.iloc[:, 0:(self.network_count - 1)], 0.25), axis=1) / self.network_count self.avg_case_results_am["probability<=0.30"] = np.sum( np.less_equal(self.avg_case_results_am.iloc[:, 0:(self.network_count - 1)], 0.3), axis=1) / self.network_count else: self.avg_case_results_am_post = self.post_process_predictions( self.avg_case_results_am.iloc[:, 0:(self.network_count - 1)].to_numpy()) ##AVERAGE CASE TARGET w PM COLLECTION # Iterate through all loaded pretrained networks, make predictions based on the inputs, # calculate the median of the predictions and store everything to self.results for j in range(0, self.network_count): key = "se4_frc_net-" + str(j) predictions = self.targets_scaler.inverse_transform( self.trained_models["model_" + str(j)].predict(avg_case_inputs_norm_pm)).tolist() temp = sum(predictions, []) avg_case_results_pm.update({key: temp}) self.avg_case_results_pm = pd.DataFrame(avg_case_results_pm) self.avg_case_results_pm["median"] = self.avg_case_results_pm.median(axis=1) # Include the inputs/predictors in the self.results variable for i in self.avg_case_predictors_pm.keys(): self.avg_case_results_pm.update({i: self.avg_case_predictors_pm[i].tolist()}) self.avg_case_results_pm[i] = self.avg_case_predictors_pm[i].tolist() if self.post_process_check == False: # Calculate all the probability fields and store them to self.results # results_table_frc_avg = self.results.iloc[:, 0:(self.network_count - 1)] self.avg_case_results_pm["probability<=0.20"] = ( np.sum( np.less( self.avg_case_results_pm.iloc[:, 0 : (self.network_count - 1)], 0.2, ), axis=1, ) / self.network_count ) self.avg_case_results_pm["probability<=0.25"] = ( np.sum( np.less( self.avg_case_results_pm.iloc[:, 0 : (self.network_count - 1)], 0.25, ), axis=1, ) / self.network_count ) self.avg_case_results_pm["probability<=0.30"] = ( np.sum( np.less( self.avg_case_results_pm.iloc[:, 0 : (self.network_count - 1)], 0.3, ), axis=1, ) / self.network_count ) else: self.avg_case_results_pm_post = self.post_process_predictions( self.avg_case_results_pm.iloc[:, 0:(self.network_count - 1)].to_numpy()) if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: ##WORST CASE TARGET w AM COLLECTION for j in range(0, self.network_count): key = "se4_frc_net-" + str(j) predictions = self.targets_scaler.inverse_transform( self.trained_models["model_" + str(j)].predict(worst_case_inputs_norm_am)).tolist() temp = sum(predictions, []) worst_case_results_am.update({key: temp}) self.worst_case_results_am = pd.DataFrame(worst_case_results_am) self.worst_case_results_am["median"] = self.worst_case_results_am.median(axis=1) # Include the inputs/predictors in the self.results variable for i in self.worst_case_predictors_am.keys(): self.worst_case_results_am.update({i: self.worst_case_predictors_am[i].tolist()}) self.worst_case_results_am[i] = self.worst_case_predictors_am[i].tolist() if self.post_process_check == False: # Calculate all the probability fields and store them to self.results # results_table_frc_avg = self.results.iloc[:, 0:(self.network_count - 1)] self.worst_case_results_am["probability<=0.20"] = ( np.sum( np.less( self.worst_case_results_am.iloc[ :, 0 : (self.network_count - 1) ], 0.2, ), axis=1, ) / self.network_count ) self.worst_case_results_am["probability<=0.25"] = ( np.sum( np.less( self.worst_case_results_am.iloc[ :, 0 : (self.network_count - 1) ], 0.25, ), axis=1, ) / self.network_count ) self.worst_case_results_am["probability<=0.30"] = ( np.sum( np.less( self.worst_case_results_am.iloc[ :, 0 : (self.network_count - 1) ], 0.3, ), axis=1, ) / self.network_count ) else: self.worst_case_results_am_post = self.post_process_predictions( self.worst_case_results_am.iloc[:, 0:(self.network_count - 1)].to_numpy()) ##WORST CASE TARGET w PM COLLECTION for j in range(0, self.network_count): key = "se4_frc_net-" + str(j) predictions = self.targets_scaler.inverse_transform( self.trained_models["model_" + str(j)].predict(worst_case_inputs_norm_pm)).tolist() temp = sum(predictions, []) worst_case_results_pm.update({key: temp}) self.worst_case_results_pm = pd.DataFrame(worst_case_results_pm) self.worst_case_results_pm["median"] = self.worst_case_results_pm.median(axis=1) # Include the inputs/predictors in the self.results variable for i in self.worst_case_predictors_pm.keys(): self.worst_case_results_pm.update({i: self.worst_case_predictors_pm[i].tolist()}) self.worst_case_results_pm[i] = self.worst_case_predictors_pm[i].tolist() if self.post_process_check == False: # Calculate all the probability fields and store them to self.results # results_table_frc_avg = self.results.iloc[:, 0:(self.network_count - 1)] self.worst_case_results_pm["probability<=0.20"] = ( np.sum( np.less( self.worst_case_results_pm.iloc[ :, 0 : (self.network_count - 1) ], 0.2, ), axis=1, ) / self.network_count ) self.worst_case_results_pm["probability<=0.25"] = ( np.sum( np.less( self.worst_case_results_pm.iloc[ :, 0 : (self.network_count - 1) ], 0.25, ), axis=1, ) / self.network_count ) self.worst_case_results_pm["probability<=0.30"] = ( np.sum( np.less( self.worst_case_results_pm.iloc[ :, 0 : (self.network_count - 1) ], 0.3, ), axis=1, ) / self.network_count ) else: self.worst_case_results_pm_post = self.post_process_predictions( self.worst_case_results_pm.iloc[:, 0:(self.network_count - 1)].to_numpy()) def results_visualization(self, filename, storage_target): test1_frc = np.arange(0.2, 2.05, 0.05) # Variables to plot - Full range, 95th percentile, 99th percentile, median, the three risks if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: if self.post_process_check == False: results_table_frc_avg_am = self.avg_case_results_am.iloc[ :, 0 : (self.network_count - 1) ] results_table_frc_avg_pm = self.avg_case_results_pm.iloc[ :, 0 : (self.network_count - 1) ] results_table_frc_worst_am = self.worst_case_results_am.iloc[ :, 0 : (self.network_count - 1) ] results_table_frc_worst_pm = self.worst_case_results_pm.iloc[ :, 0 : (self.network_count - 1) ] preds_fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots( 2, 2, figsize=(6.69, 6.69), dpi=300 ) ax1.fill_between( test1_frc, np.percentile(results_table_frc_avg_am, 97.5, axis=1), np.percentile(results_table_frc_avg_am, 2.5, axis=1), facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax1.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax1.plot( test1_frc, np.min(results_table_frc_avg_am, axis=1), "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax1.plot( test1_frc, np.max(results_table_frc_avg_am, axis=1), "#ffa600", linewidth=0.5, ) ax1.plot( test1_frc, np.median(results_table_frc_avg_am, axis=1), "#ffa600", linewidth=1, label="Median Prediction", ) ax1.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax1.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax1.set_xlim([0.19, 2.0]) ax1.set_xticks(np.arange(0.2, 2.2, 0.2)) ax1.set_xlabel("Tap Stand FRC (mg/L)") ax1.set_ylabel("Household FRC (mg/L)") ax1.set_title("Average Case - AM Collection") ax2.fill_between( test1_frc, np.percentile(results_table_frc_avg_pm, 97.5, axis=1), np.percentile(results_table_frc_avg_pm, 2.5, axis=1), facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax2.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax2.plot( test1_frc, np.min(results_table_frc_avg_pm, axis=1), "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax2.plot( test1_frc, np.max(results_table_frc_avg_pm, axis=1), "#ffa600", linewidth=0.5, ) ax2.plot( test1_frc, np.median(results_table_frc_avg_pm, axis=1), "#ffa600", linewidth=1, label="Median Prediction", ) ax2.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax2.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax2.set_xlim([0.19, 2.0]) ax2.set_xticks(np.arange(0.2, 2.2, 0.2)) ax2.set_xlabel("Tap Stand FRC (mg/L)") ax2.set_ylabel("Household FRC (mg/L)") ax2.set_title("Average Case - PM Collection") ax3.fill_between( test1_frc, np.percentile(results_table_frc_worst_am, 97.5, axis=1), np.percentile(results_table_frc_worst_am, 2.5, axis=1), facecolor="#b80000", alpha=0.5, label="95th Percentile Range", ) ax3.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax3.plot( test1_frc, np.min(results_table_frc_worst_am, axis=1), "#b80000", linewidth=0.5, label="Minimum/Maximum", ) ax3.plot( test1_frc, np.max(results_table_frc_worst_am, axis=1), "#b80000", linewidth=0.5, ) ax3.plot( test1_frc, np.median(results_table_frc_worst_am, axis=1), "#b80000", linewidth=1, label="Median Prediction", ) ax3.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax3.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax3.set_xlim([0.19, 2.0]) ax3.set_xticks(np.arange(0.2, 2.2, 0.2)) ax3.set_xlabel("Tap Stand FRC (mg/L)") ax3.set_ylabel("Household FRC (mg/L)") ax3.set_title("Worst Case - AM Collection") ax4.fill_between( test1_frc, np.percentile(results_table_frc_worst_pm, 97.5, axis=1), np.percentile(results_table_frc_worst_pm, 2.5, axis=1), facecolor="#b80000", alpha=0.5, label="95th Percentile Range", ) ax4.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax4.plot( test1_frc, np.min(results_table_frc_worst_pm, axis=1), "#b80000", linewidth=0.5, label="Minimum/Maximum", ) ax4.plot( test1_frc, np.max(results_table_frc_worst_pm, axis=1), "#b80000", linewidth=0.5, ) ax4.plot( test1_frc, np.median(results_table_frc_worst_pm, axis=1), "#b80000", linewidth=1, label="Median Prediction", ) ax4.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax4.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax4.set_xlim([0.19, 2.0]) ax4.set_xticks(np.arange(0.2, 2.2, 0.2)) ax4.set_xlabel("Tap Stand FRC (mg/L)") ax4.set_ylabel("Household FRC (mg/L)") ax4.set_title("Worst Case - PM Collection") plt.subplots_adjust(wspace=0.25) plt.savefig( os.path.splitext(filename)[0] + "_Predictions_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig1.pickle', 'wb')) StringIOBytes_preds = io.BytesIO() plt.savefig(StringIOBytes_preds, format="png", bbox_inches="tight") StringIOBytes_preds.seek(0) preds_base_64_pngData = base64.b64encode(StringIOBytes_preds.read()) plt.close() risk_fig = plt.figure(figsize=(6.69, 3.35), dpi=300) plt.plot( test1_frc, np.sum(np.less(results_table_frc_avg_am, 0.20), axis=1) / self.network_count, c="#ffa600", label="Risk of Household FRC < 0.20 mg/L - Average Case, AM Collection", ) plt.plot( test1_frc, np.sum(np.less(results_table_frc_avg_pm, 0.20), axis=1) / self.network_count, c="#ffa600", ls="--", label="Risk of Household FRC < 0.20 mg/L - Average Case, PM Collection", ) plt.plot( test1_frc, np.sum(np.less(results_table_frc_worst_am, 0.2), axis=1) / self.network_count, c="#b80000", label="Risk of Household FRC < 0.20 mg/L - Worst Case, AM Collection", ) plt.plot( test1_frc, np.sum(np.less(results_table_frc_worst_pm, 0.2), axis=1) / self.network_count, c="#b80000", ls="--", label="Risk of Household FRC < 0.20 mg/L - Worst Case, PM Collection", ) plt.xlim([0.2, 2]) plt.xlabel("Tapstand FRC (mg/L)") plt.ylim([0, 1]) plt.ylabel("Risk of Point-of-Consumption FRC < 0.2 mg/L") plt.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) plt.subplots_adjust(bottom=0.15, right=0.95) plt.savefig( os.path.splitext(filename)[0] + "_Risk_Fig.png", format="png", bbox_inches="tight", ) StringIOBytes_risk = io.BytesIO() plt.savefig(StringIOBytes_risk, format="png", bbox_inches="tight") StringIOBytes_risk.seek(0) risk_base_64_pngData = base64.b64encode(StringIOBytes_risk.read()) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig2.pickle', 'wb')) plt.close() elif self.post_process_check == True: preds_fig, ((ax1, ax2), (ax3, ax4)) = plt.subplots( 2, 2, figsize=(6.69, 6.69), dpi=300 ) ax1.fill_between( test1_frc, self.avg_case_results_am_post["Upper 95 CI"], self.avg_case_results_am_post["Lower 95 CI"], facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax1.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax1.plot( test1_frc, self.avg_case_results_am_post["Ensemble Minimum"], "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax1.plot( test1_frc, self.avg_case_results_am_post["Ensemble Maximum"], "#ffa600", linewidth=0.5, ) ax1.plot( test1_frc, self.avg_case_results_am_post["median"], "#ffa600", linewidth=1, label="Median Prediction", ) ax1.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax1.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax1.set_xlim([0.19, 2.0]) ax1.set_xticks(np.arange(0.2, 2.2, 0.2)) ax1.set_xlabel("Tap Stand FRC (mg/L)") ax1.set_ylabel("Household FRC (mg/L)") ax1.set_title("Average Case - AM Collection") ax2.fill_between( test1_frc, self.avg_case_results_pm_post["Upper 95 CI"], self.avg_case_results_pm_post["Lower 95 CI"], facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax2.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax2.plot( test1_frc, self.avg_case_results_pm_post["Ensemble Minimum"], "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax2.plot( test1_frc, self.avg_case_results_pm_post["Ensemble Maximum"], "#ffa600", linewidth=0.5, ) ax2.plot( test1_frc, self.avg_case_results_pm_post["median"], "#ffa600", linewidth=1, label="median Prediction", ) ax2.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax2.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax2.set_xlim([0.19, 2.0]) ax2.set_xticks(np.arange(0.2, 2.2, 0.2)) ax2.set_xlabel("Tap Stand FRC (mg/L)") ax2.set_ylabel("Household FRC (mg/L)") ax2.set_title("Average Case - PM Collection") ax3.fill_between( test1_frc, self.worst_case_results_am_post["Upper 95 CI"], self.worst_case_results_am_post["Lower 95 CI"], facecolor="#b80000", alpha=0.5, label="95th Percentile Range", ) ax3.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax3.plot( test1_frc, self.worst_case_results_am_post["Ensemble Minimum"], "#b80000", linewidth=0.5, label="Minimum/Maximum", ) ax3.plot( test1_frc, self.worst_case_results_am_post["Ensemble Maximum"], "#b80000", linewidth=0.5, ) ax3.plot( test1_frc, self.worst_case_results_am_post["median"], "#b80000", linewidth=1, label="Median Prediction", ) ax3.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax3.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax3.set_xlim([0.19, 2.0]) ax3.set_xticks(np.arange(0.2, 2.2, 0.2)) ax3.set_xlabel("Tap Stand FRC (mg/L)") ax3.set_ylabel("Household FRC (mg/L)") ax3.set_title("Worst Case - AM Collection") ax4.fill_between( test1_frc, self.worst_case_results_pm_post["Upper 95 CI"], self.worst_case_results_pm_post["Lower 95 CI"], facecolor="#b80000", alpha=0.5, label="95th Percentile Range", ) ax4.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax4.plot( test1_frc, self.worst_case_results_pm_post["Ensemble Minimum"], "#b80000", linewidth=0.5, label="Minimum/Maximum", ) ax4.plot( test1_frc, self.worst_case_results_pm_post["Ensemble Maximum"], "#b80000", linewidth=0.5, ) ax4.plot( test1_frc, self.worst_case_results_pm_post["median"], "#b80000", linewidth=1, label="Median Prediction", ) ax4.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax4.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax4.set_xlim([0.19, 2.0]) ax4.set_xticks(np.arange(0.2, 2.2, 0.2)) ax4.set_xlabel("Tap Stand FRC (mg/L)") ax4.set_ylabel("Household FRC (mg/L)") ax4.set_title("Worst Case - PM Collection") plt.subplots_adjust(wspace=0.25) plt.savefig( os.path.splitext(filename)[0] + "_Predictions_Fig.png", format="png", bbox_inches="tight", ) StringIOBytes_preds = io.BytesIO() plt.savefig(StringIOBytes_preds, format="png", bbox_inches="tight") StringIOBytes_preds.seek(0) preds_base_64_pngData = base64.b64encode(StringIOBytes_preds.read()) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig1.pickle', 'wb')) plt.close() risk_fig = plt.figure(figsize=(6.69, 3.35), dpi=300) plt.plot( test1_frc, self.avg_case_results_am_post["probability<=0.20"], c="#ffa600", label="Risk of Household FRC < 0.20 mg/L - Average Case, AM Collection", ) plt.plot( test1_frc, self.avg_case_results_pm_post["probability<=0.20"], c="#ffa600", ls="--", label="Risk of Household FRC < 0.20 mg/L - Average Case, PM Collection", ) plt.plot( test1_frc, self.worst_case_results_am_post["probability<=0.20"], c="#b80000", label="Risk of Household FRC < 0.20 mg/L - Worst Case, AM Collection", ) plt.plot( test1_frc, self.worst_case_results_pm_post["probability<=0.20"], c="#b80000", ls="--", label="Risk of Household FRC < 0.20 mg/L - Worst Case, PM Collection", ) plt.xlim([0.2, 2]) plt.xlabel("Tapstand FRC (mg/L)") plt.ylim([0, 1]) plt.ylabel("Risk of Point-of-Consumption FRC < 0.2 mg/L") plt.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) plt.savefig( os.path.splitext(filename)[0] + "_Risk_Fig.png", format="png", bbox_inches="tight", ) StringIOBytes_risk = io.BytesIO() plt.savefig(StringIOBytes_risk, format="png", bbox_inches="tight") StringIOBytes_risk.seek(0) risk_base_64_pngData = base64.b64encode(StringIOBytes_risk.read()) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig2.pickle', 'wb')) plt.close() if WATTEMP in self.datainputs.columns and COND in self.datainputs.columns: hist_fig, (ax1, ax2, ax3, ax4, ax5, ax6) = plt.subplots( 6, 1, figsize=(3.35, 6.69), dpi=300 ) ax1.set_ylabel("Frequency") ax1.set_xlabel("Tapstand FRC (mg/L)") ax1.hist(self.datainputs.iloc[:, 0], bins=30, color="grey") ax2.set_ylabel("Frequency") ax2.set_xlabel("Elapsed Time (hours)") ax2.hist(self.datainputs.iloc[:, 1], bins=30, color="grey") ax3.set_ylabel("Frequency") ax3.set_xlabel("Collection Time (0=AM, 1=PM)") ax3.hist(self.datainputs.iloc[:, 2], bins=30, color="grey") ax4.set_ylabel("Frequency") ax4.set_xlabel("Water Temperature(" + r"$\degree$" + "C)") ax4.hist(self.datainputs.iloc[:, 3], bins=30, color="grey") ax4.axvline( self.median_wattemp, c="#ffa600", ls="--", label="Average Case Value Used", ) ax4.axvline( self.upper95_wattemp, c="#b80000", ls="--", label="Worst Case Value Used", ) ax4.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) ax5.set_ylabel("Frequency") ax5.set_xlabel("Electrical Conductivity (" + r"$\mu$" + "s/cm)") ax5.hist(self.datainputs.iloc[:, 4], bins=30, color="grey") ax5.axvline( self.median_cond, c="#ffa600", ls="--", label="Average Case Value Used", ) ax5.axvline( self.upper95_cond, c="#b80000", ls="--", label="Worst Case Value used", ) ax5.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) ax6.set_ylabel("Frequency") ax6.set_xlabel("Household FRC (mg/L)") ax6.hist(self.dataoutputs, bins=30, color="grey") plt.subplots_adjust( left=0.18, hspace=0.60, top=0.99, bottom=0.075, right=0.98 ) plt.savefig( os.path.splitext(filename)[0] + "_Histograms_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig3.pickle', 'wb')) plt.close() StringIOBytes_histogram = io.BytesIO() plt.savefig(StringIOBytes_histogram, format="png", bbox_inches="tight") StringIOBytes_histogram.seek(0) hist_base_64_pngData = base64.b64encode(StringIOBytes_histogram.read()) elif WATTEMP in self.datainputs.columns: hist_fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots( 6, 1, figsize=(3.35, 6.69), dpi=300 ) ax1.set_ylabel("Frequency") ax1.set_xlabel("Tapstand FRC (mg/L)") ax1.hist(self.datainputs.iloc[:, 0], bins=30, color="grey") ax2.set_ylabel("Frequency") ax2.set_xlabel("Elapsed Time (hours)") ax2.hist(self.datainputs.iloc[:, 1], bins=30, color="grey") ax3.set_ylabel("Frequency") ax3.set_xlabel("Collection Time (0=AM, 1=PM)") ax3.hist(self.datainputs.iloc[:, 2], bins=30, color="grey") ax4.set_ylabel("Frequency") ax4.set_xlabel("Water Temperature(" + r"$\degree$" + "C)") ax4.hist(self.datainputs.iloc[:, 3], bins=30, color="grey") ax4.axvline( self.median_wattemp, c="#ffa600", ls="--", label="Average Case Value Used", ) ax4.axvline( self.upper95_wattemp, c="#b80000", ls="--", label="Worst Case Value Used", ) ax4.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) ax5.set_ylabel("Frequency") ax5.set_xlabel("Household FRC (mg/L)") ax5.hist(self.dataoutputs, bins=30, color="grey") plt.subplots_adjust( left=0.18, hspace=0.60, top=0.99, bottom=0.075, right=0.98 ) plt.savefig( os.path.splitext(filename)[0] + "_Histograms_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig3.pickle', 'wb')) plt.close() StringIOBytes_histogram = io.BytesIO() plt.savefig(StringIOBytes_histogram, format="png", bbox_inches="tight") StringIOBytes_histogram.seek(0) hist_base_64_pngData = base64.b64encode(StringIOBytes_histogram.read()) elif COND in self.datainputs.columns: hist_fig, (ax1, ax2, ax3, ax4, ax5) = plt.subplots( 6, 1, figsize=(3.35, 6.69), dpi=300 ) ax1.set_ylabel("Frequency") ax1.set_xlabel("Tapstand FRC (mg/L)") ax1.hist(self.datainputs.iloc[:, 0], bins=30, color="grey") ax2.set_ylabel("Frequency") ax2.set_xlabel("Elapsed Time (hours)") ax2.hist(self.datainputs.iloc[:, 1], bins=30, color="grey") ax3.set_ylabel("Frequency") ax3.set_xlabel("Collection Time (0=AM, 1=PM)") ax3.hist(self.datainputs.iloc[:, 2], bins=30, color="grey") ax4.set_ylabel("Frequency") ax4.set_xlabel("Electrical Conductivity (" + r"$\mu$" + "s/cm)") ax4.hist(self.datainputs.iloc[:, 4], bins=30, color="grey") ax4.axvline( self.median_cond, c="#ffa600", ls="--", label="Average Case Value Used", ) ax4.axvline( self.upper95_cond, c="#b80000", ls="--", label="Worst Case Value used", ) ax4.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) ax5.set_ylabel("Frequency") ax5.set_xlabel("Household FRC (mg/L)") ax5.hist(self.dataoutputs, bins=30, color="grey") plt.subplots_adjust( left=0.18, hspace=0.60, top=0.99, bottom=0.075, right=0.98 ) plt.savefig( os.path.splitext(filename)[0] + "_Histograms_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig3.pickle', 'wb')) plt.close() StringIOBytes_histogram = io.BytesIO() plt.savefig(StringIOBytes_histogram, format="png", bbox_inches="tight") StringIOBytes_histogram.seek(0) hist_base_64_pngData = base64.b64encode(StringIOBytes_histogram.read()) else: if self.post_process_check == False: results_table_frc_avg_am = self.avg_case_results_am.iloc[ :, 0 : (self.network_count - 1) ] results_table_frc_avg_pm = self.avg_case_results_pm.iloc[ :, 0 : (self.network_count - 1) ] preds_fig, (ax1, ax2) = plt.subplots( 1, 2, figsize=(6.69, 3.35), dpi=300 ) ax1.fill_between( test1_frc, np.percentile(results_table_frc_avg_am, 97.5, axis=1), np.percentile(results_table_frc_avg_am, 2.5, axis=1), facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax1.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax1.plot( test1_frc, np.min(results_table_frc_avg_am, axis=1), "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax1.plot( test1_frc, np.max(results_table_frc_avg_am, axis=1), "#ffa600", linewidth=0.5, ) ax1.plot( test1_frc, np.median(results_table_frc_avg_am, axis=1), "#ffa600", linewidth=1, label="Median Prediction", ) ax1.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax1.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax1.set_xlim([0.19, 2.0]) ax1.set_xticks(np.arange(0.2, 2.2, 0.2)) ax1.set_xlabel("Tap Stand FRC (mg/L)") ax1.set_ylabel("Household FRC (mg/L)") ax1.set_title("AM Collection") ax2.fill_between( test1_frc, np.percentile(results_table_frc_avg_pm, 97.5, axis=1), np.percentile(results_table_frc_avg_pm, 2.5, axis=1), facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax2.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax2.plot( test1_frc, np.min(results_table_frc_avg_pm, axis=1), "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax2.plot( test1_frc, np.max(results_table_frc_avg_pm, axis=1), "#ffa600", linewidth=0.5, ) ax2.plot( test1_frc, np.median(results_table_frc_avg_pm, axis=1), "#ffa600", linewidth=1, label="Median Prediction", ) ax2.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax2.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax2.set_xlim([0.19, 2.0]) ax2.set_xticks(np.arange(0.2, 2.2, 0.2)) ax2.set_xlabel("Tap Stand FRC (mg/L)") ax2.set_ylabel("Household FRC (mg/L)") ax2.set_title("PM Collection") plt.subplots_adjust(wspace=0.25) plt.savefig( os.path.splitext(filename)[0] + "_Predictions_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig1.pickle', 'wb')) StringIOBytes_preds = io.BytesIO() plt.savefig(StringIOBytes_preds, format="png", bbox_inches="tight") StringIOBytes_preds.seek(0) preds_base_64_pngData = base64.b64encode(StringIOBytes_preds.read()) plt.close() risk_fig = plt.figure(figsize=(6.69, 3.35), dpi=300) plt.plot( test1_frc, np.sum(np.less(results_table_frc_avg_am, 0.20), axis=1) / self.network_count, c="#ffa600", label="Risk of Household FRC < 0.20 mg/L - Average Case, AM Collection", ) plt.plot( test1_frc, np.sum(np.less(results_table_frc_avg_pm, 0.20), axis=1) / self.network_count, c="#ffa600", ls="--", label="Risk of Household FRC < 0.20 mg/L - Average Case, PM Collection", ) plt.xlim([0.2, 2]) plt.xlabel("Tapstand FRC (mg/L)") plt.ylim([0, 1]) plt.ylabel("Risk of Point-of-Consumption FRC < 0.2 mg/L") plt.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) plt.subplots_adjust(bottom=0.15, right=0.95) plt.savefig( os.path.splitext(filename)[0] + "_Risk_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig2.pickle', 'wb')) StringIOBytes_risk = io.BytesIO() plt.savefig(StringIOBytes_risk, format="png", bbox_inches="tight") StringIOBytes_risk.seek(0) risk_base_64_pngData = base64.b64encode(StringIOBytes_risk.read()) plt.close() elif self.post_process_check == True: preds_fig, (ax1, ax2) = plt.subplots( 1, 2, figsize=(6.69, 3.35), dpi=300 ) ax1.fill_between( test1_frc, self.avg_case_results_am_post["Upper 95 CI"], self.avg_case_results_am_post["Lower 95 CI"], facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax1.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax1.plot( test1_frc, self.avg_case_results_am_post["Ensemble Minimum"], "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax1.plot( test1_frc, self.avg_case_results_am_post["Ensemble Maximum"], "#ffa600", linewidth=0.5, ) ax1.plot( test1_frc, self.avg_case_results_am_post["median"], "#ffa600", linewidth=1, label="Median Prediction", ) ax1.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax1.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax1.set_xlim([0.19, 2.0]) ax1.set_xticks(np.arange(0.2, 2.2, 0.2)) ax1.set_xlabel("Tap Stand FRC (mg/L)") ax1.set_ylabel("Household FRC (mg/L)") ax1.set_title("AM Collection") ax2.fill_between( test1_frc, self.avg_case_results_pm_post["Upper 95 CI"], self.avg_case_results_pm_post["Lower 95 CI"], facecolor="#ffa600", alpha=0.5, label="95th Percentile Range", ) ax2.axhline(0.2, c="k", ls="-.", linewidth=1, label="FRC = 0.2 mg/L") ax2.plot( test1_frc, self.avg_case_results_pm_post["Ensemble Minimum"], "#ffa600", linewidth=0.5, label="Minimum/Maximum", ) ax2.plot( test1_frc, self.avg_case_results_pm_post["Ensemble Maximum"], "#ffa600", linewidth=0.5, ) ax2.plot( test1_frc, self.avg_case_results_pm_post["median"], "#ffa600", linewidth=1, label="median Prediction", ) ax2.scatter( self.datainputs[FRC_IN], self.dataoutputs, c="k", s=10, marker="x", label="Testing Observations", ) ax2.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", loc="upper right", ) ax2.set_xlim([0.19, 2.0]) ax2.set_xticks(np.arange(0.2, 2.2, 0.2)) ax2.set_xlabel("Tap Stand FRC (mg/L)") ax2.set_ylabel("Household FRC (mg/L)") ax2.set_title("PM Collection") plt.subplots_adjust(wspace=0.25) plt.tight_layout() plt.savefig( os.path.splitext(filename)[0] + "_Predictions_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig1.pickle', 'wb')) StringIOBytes_preds = io.BytesIO() plt.savefig(StringIOBytes_preds, format="png", bbox_inches="tight") StringIOBytes_preds.seek(0) preds_base_64_pngData = base64.b64encode(StringIOBytes_preds.read()) plt.close() risk_fig = plt.figure(figsize=(6.69, 3.35), dpi=300) plt.plot( test1_frc, self.avg_case_results_am_post["probability<=0.20"], c="#ffa600", label="Risk of Household FRC < 0.20 mg/L - Average Case, AM Collection", ) plt.plot( test1_frc, self.avg_case_results_pm_post["probability<=0.20"], c="#ffa600", ls="--", label="Risk of Household FRC < 0.20 mg/L - Average Case, PM Collection", ) plt.xlim([0.2, 2]) plt.xlabel("Tapstand FRC (mg/L)") plt.ylim([0, 1]) plt.ylabel("Risk of Point-of-Consumption FRC < 0.2 mg/L") plt.legend( bbox_to_anchor=(0.999, 0.999), shadow=False, fontsize="small", ncol=1, labelspacing=0.1, columnspacing=0.2, handletextpad=0.1, loc="upper right", ) plt.savefig( os.path.splitext(filename)[0] + "_Risk_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig2.pickle', 'wb')) StringIOBytes_risk = io.BytesIO() plt.savefig(StringIOBytes_risk, format="png", bbox_inches="tight") StringIOBytes_risk.seek(0) risk_base_64_pngData = base64.b64encode(StringIOBytes_risk.read()) plt.close() hist_fig, (ax1, ax2, ax3, ax4) = plt.subplots( 4, 1, figsize=(3.35, 6.69), dpi=300 ) ax1.set_ylabel("Frequency") ax1.set_xlabel("Tapstand FRC (mg/L)") ax1.hist(self.datainputs.iloc[:, 0], bins=30, color="grey") ax2.set_ylabel("Frequency") ax2.set_xlabel("Elapsed Time (hours)") ax2.hist(self.datainputs.iloc[:, 1], bins=30, color="grey") ax3.set_ylabel("Frequency") ax3.set_xlabel("Collection Time (0=AM, 1=PM)") ax3.hist(self.datainputs.iloc[:, 2], bins=30, color="grey") ax4.set_ylabel("Frequency") ax4.set_xlabel("Household FRC (mg/L)") ax4.hist(self.dataoutputs, bins=30, color="grey") plt.subplots_adjust( left=0.18, hspace=0.60, top=0.99, bottom=0.075, right=0.98 ) plt.savefig( os.path.splitext(filename)[0] + "_Histograms_Fig.png", format="png", bbox_inches="tight", ) # pl.dump(fig, open(os.path.splitext(filename)[0] + 'Fig3.pickle', 'wb')) plt.close() StringIOBytes_histogram = io.BytesIO() plt.savefig(StringIOBytes_histogram, format="png", bbox_inches="tight") StringIOBytes_histogram.seek(0) hist_base_64_pngData = base64.b64encode(StringIOBytes_histogram.read()) return hist_base_64_pngData, risk_base_64_pngData, preds_base_64_pngData def display_results(self): """ Display the results of the predictions as a console output. Display and return all the contents of the self.results variable which is a pandas Dataframe object :return: A Pandas Dataframe object (self.results) containing all the result of the predictions """ if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: if self.post_process_check == False: logging.info(self.avg_case_results_am) logging.info(self.worst_case_results_am) logging.info(self.avg_case_results_pm) logging.info(self.worst_case_results_pm) return self.avg_case_results_am, self.avg_case_results_pm, self.worst_case_results_am, self.worst_case_results_pm else: logging.info(self.avg_case_results_am_post) logging.info(self.worst_case_results_am_post) logging.info(self.avg_case_results_pm_post) logging.info(self.worst_case_results_pm_post) return self.avg_case_results_am_post, self.avg_case_results_pm_post, self.worst_case_results_am_post, self.worst_case_results_pm_post else: if self.post_process_check == False: logging.info(self.avg_case_results_am) logging.info(self.avg_case_results_pm) return self.avg_case_results_am, self.avg_case_results_pm else: logging.info(self.avg_case_results_am_post) logging.info(self.avg_case_results_pm_post) return self.avg_case_results_am_post, self.avg_case_results_pm_post def export_results_to_csv(self, filename): self.avg_case_results_am.to_csv( os.path.splitext(filename)[0] + "_average_case_am.csv", index=False ) self.avg_case_results_pm.to_csv( os.path.splitext(filename)[0] + "_average_case_pm.csv", index=False ) if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: self.worst_case_results_am.to_csv( os.path.splitext(filename)[0] + "_worst_case_am.csv", index=False ) self.worst_case_results_pm.to_csv( os.path.splitext(filename)[0] + "_worst_case_pm.csv", index=False ) if self.post_process_check == True: self.avg_case_results_am_post.to_csv( os.path.splitext(filename)[0] + "_average_case_am.csv", index=False ) self.avg_case_results_pm_post.to_csv( os.path.splitext(filename)[0] + "_average_case_pm.csv", index=False ) if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: self.worst_case_results_am_post.to_csv( os.path.splitext(filename)[0] + "_worst_case_am.csv", index=False ) self.worst_case_results_pm_post.to_csv( os.path.splitext(filename)[0] + "_worst_case_pm.csv", index=False ) def generate_model_performance(self): """Generates training performance graphs Plots the model performance metrics (MSE and R^2 vs # of epochs) after training and returns a base64 encoded image. The NN has to be trained first otherwise the image will be empty. Returns: Base64 data stream""" fig, axs = plt.subplots(1, 2, sharex=True) ax = axs[0] ax.boxplot( [self.total_mse_train, self.total_mse_val, self.total_mse_test], labels=["Training", "Validation", "Testing"], ) ax.set_title("Mean Squared Error") tr_legend = "Training Avg MSE: {mse:.4f}".format(mse=self.avg_mse_train) val_legend = "Validation Avg MSE: {mse:.4f}".format(mse=self.avg_mse_val) ts_legend = "Testing Avg MSE: {mse:.4f}".format(mse=self.avg_mse_test) ax.legend([tr_legend, val_legend, ts_legend]) ax = axs[1] ax.boxplot( [ self.total_rsquared_train, self.total_rsquared_val, self.total_rsquared_test, ], labels=["Training", "Validation", "Testing"], ) ax.set_title("R^2") tr_legend = "Training Avg. R^2: {rs:.3f}".format(rs=self.avg_rsq_train) val_legend = "Validation Avg. R^2: {rs:.3f}".format(rs=self.avg_rsq_val) ts_legend = "Validation Avg. R^2: {rs:.3f}".format(rs=self.avg_rsq_test) ax.legend([tr_legend, val_legend, ts_legend]) fig.suptitle( "Performance metrics across 100 training runs on " + str(self.epochs) + " epochs, with " + str(self.layer1_neurons) + " neurons on hidden layer." ) fig.set_size_inches(12, 8) # plt.show() # Uncomment the next lines to save the graph to disk # plt.savefig("model_metrics\\" + str(self.epochs) + "_epochs_" + str(self.layer1_neurons) + "_neurons.png", # dpi=100) # plt.close() plt.show() myStringIOBytes = io.BytesIO() plt.savefig(myStringIOBytes, format='png') myStringIOBytes.seek(0) my_base_64_pngData = base64.b64encode(myStringIOBytes.read()) return my_base_64_pngData def generate_2d_scatterplot(self): """Generate a 2d scatterplot of the predictions Plots three, 2-dimensional scatterplots of the predictions as a function of the inputs The 3 scatterplots are plotting: predictions vs se1_frc and water temperature, predictions vs water conductivity and water temperature, and predictions vs se1_frc and water conductivity. A histogram of the prediction set is also generated and plotted. A prediction using the predict() method must be made first. Returns: a base64 data represenation of the image.""" df = self.results # Uncomment the following line to load the results direclty from an csv file # df = pd.read_csv('results.csv') # Filter out outlier values df = df.drop(df[df[FRC_IN] > 2.8].index) frc = df[FRC_IN] watt = df[WATTEMP] cond = df[COND] c = df["median"] # sort data for the cdf sorted_data = np.sort(c) # The following lines of code calculate the width of the histogram bars # and align the range of the histogram and the pdf if min(c) < 0: lo_limit = 0 else: lo_limit = round(min(c), 2) logging.info(lo_limit) if max(c) <= 0.75: divisions = 16 hi_limit = 0.75 elif max(c) < 1: divisions = 21 hi_limit = 1 elif max(c) <= 1.5: divisions = 31 hi_limit = 1.5 elif max(c) <= 2: divisions = 41 hi_limit = 2 divisions = round((hi_limit - lo_limit) / 0.05, 0) + 1 logging.info(divisions) # Get the data between the limits sorted_data = sorted_data[sorted_data > lo_limit] sorted_data = sorted_data[sorted_data < hi_limit] # create a colorbar for the se4_frc and divide it in 0.2 mg/L intervals cmap = plt.cm.jet_r cmaplist = [cmap(i) for i in range(cmap.N)] cmap = mpl.colors.LinearSegmentedColormap.from_list( "Custom cmap", cmaplist, cmap.N ) bounds = np.linspace(0, 1.4, 8) norm = mpl.colors.BoundaryNorm(bounds, cmap.N) fig = plt.figure(figsize=(19.2, 10.8), dpi=100) ax = fig.add_subplot(221) img = ax.scatter(frc, watt, c=c, s=5, cmap=cmap, norm=norm, alpha=1) ax.set_xlabel("FRC at tapstand (mg/L)") ax.set_ylabel("Water Temperature (" + "\u00b0" + "C)") ax.grid(linewidth=0.2) ax = fig.add_subplot(222) img = ax.scatter(frc, cond, c=c, s=5, cmap=cmap, norm=norm, alpha=1) ax.set_xlabel("FRC at tapstand (mg/L)") ax.set_ylabel("Water Conductivity (\u03BCS/cm)") ax.grid(linewidth=0.2) ax = fig.add_subplot(223) img = ax.scatter(watt, cond, c=c, s=5, cmap=cmap, norm=norm, alpha=1) ax.set_xlabel("Water Temperature (" + "\u00b0" + "C)") ax.set_ylabel("Water Conductivity (\u03BCS/cm)") ax.grid(linewidth=0.2) ax = fig.add_subplot(224) img = ax.hist( c, bins=np.linspace(lo_limit, hi_limit, divisions), edgecolor="black", linewidth=0.1, ) ax.grid(linewidth=0.1) line02 = ax.axvline(0.2, color="r", linestyle="dashed", linewidth=2) line03 = ax.axvline(0.3, color="y", linestyle="dashed", linewidth=2) ax.set_xlabel("FRC at household (mg/L)") ax.set_ylabel("# of instances") axcdf = ax.twinx() (cdf,) = axcdf.step(sorted_data, np.arange(sorted_data.size), color="g") ax.legend( (line02, line03, cdf), ("0.2 mg/L", "0.3 mg/L", "CDF"), loc="center right" ) ax2 = fig.add_axes([0.93, 0.1, 0.01, 0.75]) cb = mpl.colorbar.ColorbarBase( ax2, cmap=cmap, norm=norm, spacing="proportional", ticks=bounds, boundaries=bounds, ) cb.ax.set_ylabel("FRC at se4 (mg/L)", rotation=270, labelpad=20) plt.show() myStringIOBytes = io.BytesIO() plt.savefig(myStringIOBytes, format="png") myStringIOBytes.seek(0) my_base_64_pngData = base64.b64encode(myStringIOBytes.read()) return my_base_64_pngData def generate_input_info_plots(self, filename): """Generates histograms of the inputs to the ANN Plots one histogram for each input field on the neural network along with the mean and median values.""" df = self.datainputs # df = df.drop(df[df["se1_frc"] > 2.8].index) frc = df[FRC_IN] watt = df[WATTEMP] cond = df[COND] dfo = self.file dfo = dfo.drop(dfo[dfo[FRC_IN] > 2.8].index) frc4 = dfo[FRC_OUT] fig = plt.figure(figsize=(19.2, 10.8), dpi=100) # fig.suptitle('Total samples: '+ str(len(frc))) # + # "\n" + "SWOT version: " + self.software_version + # "\n" + "Input Filename: " + os.path.basename(self.input_filename) + # "\n" + "Generated on: " + self.today) axInitialFRC = fig.add_subplot(221) axInitialFRC.hist(frc, bins=20, edgecolor="black", linewidth=0.1) axInitialFRC.set_xlabel("Initial FRC (mg/L)") axInitialFRC.set_ylabel("# of instances") mean = round(np.mean(frc), 2) median = np.median(frc) mean_line = axInitialFRC.axvline( mean, color="r", linestyle="dashed", linewidth=2 ) median_line = axInitialFRC.axvline( median, color="y", linestyle="dashed", linewidth=2 ) axInitialFRC.legend( (mean_line, median_line), ("Mean: " + str(mean) + " mg/L", "Median: " + str(median) + " mg/L"), ) ax = fig.add_subplot(222) ax.hist(watt, bins=20, edgecolor="black", linewidth=0.1) ax.set_xlabel("Water Temperature (" + "\u00b0" + "C)") ax.set_ylabel("# of instances") mean = round(np.mean(watt), 2) median = np.median(watt) mean_line = ax.axvline(mean, color="r", linestyle="dashed", linewidth=2) median_line = ax.axvline(median, color="y", linestyle="dashed", linewidth=2) ax.legend( (mean_line, median_line), ( "Mean: " + str(mean) + "\u00b0" + "C", "Median: " + str(median) + "\u00b0" + "C", ), ) ax = fig.add_subplot(223) ax.hist(cond, bins=20, edgecolor="black", linewidth=0.1) ax.set_xlabel("Water Conductivity (\u03BCS/cm)") ax.set_ylabel("# of instances") mean = round(np.mean(cond), 2) median = np.median(cond) mean_line = ax.axvline(mean, color="r", linestyle="dashed", linewidth=2) median_line = ax.axvline(median, color="y", linestyle="dashed", linewidth=2) ax.legend( (mean_line, median_line), ( "Mean: " + str(mean) + " \u03BCS/cm", "Median: " + str(median) + " \u03BCS/cm", ), ) axHouseholdFRC = fig.add_subplot(224) axHouseholdFRC.hist( frc4, bins=np.linspace(0, 2, 41), edgecolor="black", linewidth=0.1 ) axHouseholdFRC.set_xlabel("Household FRC (\u03BCS/cm)") axHouseholdFRC.set_ylabel("# of instances") mean = round(np.mean(frc4), 2) median = np.median(frc4) mean_line = axHouseholdFRC.axvline( mean, color="r", linestyle="dashed", linewidth=2 ) median_line = axHouseholdFRC.axvline( median, color="y", linestyle="dashed", linewidth=2 ) axHouseholdFRC.legend( (mean_line, median_line), ( "Mean: " + str(mean) + " \u03BCS/cm", "Median: " + str(median) + " \u03BCS/cm", ), ) fig.savefig(os.path.splitext(filename)[0] + ".png", format="png") # plt.show() # create figure for initial and household FRC separately in a single image figFRC = plt.figure(figsize=(19.2 / 1.45, 6.4), dpi=100) axInitialFRC = figFRC.add_subplot(211) axInitialFRC.hist(frc, bins=20, edgecolor="black", linewidth=0.1) axInitialFRC.set_xlabel("Initial FRC (mg/L)") axInitialFRC.set_ylabel("# of instances") mean = round(np.mean(frc), 2) median = np.median(frc) mean_line = axInitialFRC.axvline( mean, color="r", linestyle="dashed", linewidth=2 ) median_line = axInitialFRC.axvline( median, color="y", linestyle="dashed", linewidth=2 ) axInitialFRC.legend( (mean_line, median_line), ("Mean: " + str(mean) + " mg/L", "Median: " + str(median) + " mg/L"), ) axHouseholdFRC = figFRC.add_subplot(212) axHouseholdFRC.hist( frc4, bins=np.linspace(0, 2, 41), edgecolor="black", linewidth=0.1 ) axHouseholdFRC.set_xlabel("Household FRC (mg/L)") axHouseholdFRC.set_ylabel("# of instances") mean = round(np.mean(frc4), 2) median = np.median(frc4) mean_line = axHouseholdFRC.axvline( mean, color="r", linestyle="dashed", linewidth=2 ) median_line = axHouseholdFRC.axvline( median, color="y", linestyle="dashed", linewidth=2 ) axHouseholdFRC.legend( (mean_line, median_line), ("Mean: " + str(mean) + " mg/L", "Median: " + str(median) + " mg/L"), ) figFRC.savefig(os.path.splitext(filename)[0] + "-frc.jpg", format="jpg") myStringIOBytes = io.BytesIO() plt.savefig(myStringIOBytes, format="png") myStringIOBytes.seek(0) my_base_64_pngData = base64.b64encode(myStringIOBytes.read()) return my_base_64_pngData def generate_html_report(self, filename, storage_target): """Generates an html report of the SWOT results. The report is saved on disk under the name 'filename'.""" df = self.datainputs frc = df[FRC_IN] # self.generate_input_info_plots(filename).decode('UTF-8') hist, risk, pred = self.results_visualization(filename, storage_target) hist.decode("UTF-8") risk.decode("UTF-8") pred.decode("UTF-8") # scatterplots_b64 = self.generate_2d_scatterplot().decode('UTF-8') if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: avg_html_table, worst_html_table = self.prepare_table_for_html_report( storage_target ) else: avg_html_table = self.prepare_table_for_html_report(storage_target) skipped_rows_table = self.skipped_rows_html() doc, tag, text, line = Doc().ttl() with tag("h1", klass="title"): text("SWOT ARTIFICIAL NEURAL NETWORK REPORT") with tag("p", klass="swot_version"): text("SWOT ANN Code Version: " + self.software_version) with tag("p", klass="input_filename"): text("Input File Name: " + os.path.basename(self.input_filename)) with tag("p", klass="date"): text("Date Generated: " + self.today) with tag("p", klass="time_difference"): text( "Average time between tapstand and household: " + str(int(self.avg_time_elapsed // 3600)) + " hours and " + str(int((self.avg_time_elapsed // 60) % 60)) + " minutes" ) with tag("p"): text("Total Samples: " + str(len(frc))) if self.post_process_check == False: with tag("h2", klass="Header"): text("Predicted Risk - Raw Ensemble:") else: with tag("h2", klass="Header"): text("Predicted Risk - Post-Processed Ensemble:") if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: with tag("p", klass="Predictions Fig Text"): text( "Household FRC forecast from an ensemble of " + str(self.network_count) + " ANN models. The predictions of each model are grouped into a probability density function to predict the risk of FRC below threshold values of 0.20 mg/L using a fixed input variable set for worst case and average case scenarios (shown in the risk tables below). Note that if FRC is collected using pool testers instead of a cholorimeter, the predicted FRC may be disproportionately clustered towards the centre of the observations, resulting in some observations with low FRC to not be captured within the ensemble forecast. In these cases, the predicted risk in the next figure and in the subsequent risk tables may be underpredicted. Average case predictions use median collected values for conductivity and water temperature; worst-case scenario uses 95th percentile values for conductivity and water temeperature" ) with tag("div", id="Predictions Graphs"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Predictions_Fig.png" ), ) # doc.asis('<object data="cid:'+os.path.basename(os.path.splitext(filename)[0]+'.PNG') + '" type="image/jpeg"></object>') # doc.asis( # '<object data="' # + os.path.basename( # os.path.splitext(filename)[0] + "_Predictions_Fig.png" # ) # + '" type="image/jpeg"></object>' # ) with tag("p", klass="Risk Fig Text"): text( "Figure and tables showing predicted risk of household FRC below 0.2 mg/L for average and worst case scenarios for both AM and PM collection. Risk obtained from forecast pdf (above) and taken as cumulative probability of houeshold FRC below 0.2 mg/L. Note that 0% predicted risk of household FRC below 0.2 mg/L does not mean that there is no possibility of household FRC being below 0.2 mg/L, simply that the predicted risk is too low to be measured. The average case target may, in some, cases be more conservative than the worst case targets as the worst case target is derived on the assumption that higher conductivity and water temperature will lead to greater decay (as confirmed by FRC decay chemisty and results at past sites). However, this may not be true in all cases, so the most conservative target is always recommended." ) with tag("div", id="Risk Graphs"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Risk_Fig.png" ), ) # doc.asis('<object data="cid:'+os.path.basename(os.path.splitext(filename)[0]+'.PNG') + '" type="image/jpeg"></object>') # doc.asis( # '<object data="' # + os.path.basename(os.path.splitext(filename)[0] + "_Risk_Fig.png") # + '" type="image/jpeg"></object>' # ) with tag("h2", klass="Header"): text("Average Case Targets Table") with tag("table", id="average case table"): doc.asis(avg_html_table) with tag("h2", klass="Header"): text("Worst Case Targets Table") with tag("table", id="worst case table"): doc.asis(worst_html_table) with tag("p", klass="Histograms Text"): text( "Histograms for the input variables used to generate predictions and risk recommendations above. Average case and worst case conductivity and water temperature are shown for context of values used to generate targets." ) with tag("div", id="Histograms"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Histograms_Fig.png" ), ) # doc.asis('<object data="cid:'+os.path.basename(os.path.splitext(filename)[0]+'.PNG') + '" type="image/jpeg"></object>') # doc.asis( # '<object data="' # + os.path.basename( # os.path.splitext(filename)[0] + "_Histograms_Fig.png" # ) # + '" type="image/jpeg"></object>' # ) else: with tag("p", klass="Predictions Fig Text"): text( "Household FRC forecast from an ensemble of " + str(self.network_count) + " ANN models. The predictions of each model are grouped into a probability density function to predict the risk of FRC below threshold values of 0.20 mg/L using a fixed input variable set(shown in the risk table below). Note that if FRC is collected using pool testers instead of a cholorimeter, the predicted FRC may be disproportionately clustered towards the centre of the observations, resulting in some observations with low FRC to not be captured within the ensemble forecast. In these cases, the predicted risk in the next figure and in the subsequent risk table may be underpredicted." ) with tag("div", id="Predictions Graphs"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Predictions_Fig.png" ), ) # doc.asis('<object data="cid:'+os.path.basename(os.path.splitext(filename)[0]+'.PNG') + '" type="image/jpeg"></object>') # doc.asis( # '<object data="' # + os.path.basename( # os.path.splitext(filename)[0] + "_Predictions_Fig.png" # ) # + '" type="image/jpeg"></object>' # ) with tag("p", klass="Risk Fig Text"): text( "Figure and tables showing predicted risk of household FRC below 0.2 mg/L for both AM and PM collection. Risk obtained from forecast probability density function (above) and taken as cumulative probability of houeshold FRC below 0.2 mg/L. Note that 0% predicted risk of household FRC below 0.2 mg/L does not mean that there is no possibility of household FRC being below 0.2 mg/L, simply that the predicted risk is too low to be measured." ) with tag("div", id="Risk Graphs"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Risk_Fig.png" ), ) # doc.asis('<object data="cid:'+os.path.basename(os.path.splitext(filename)[0]+'.PNG') + '" type="image/jpeg"></object>') # doc.asis( # '<object data="' # + os.path.basename(os.path.splitext(filename)[0] + "_Risk_Fig.png") # + '" type="image/jpeg"></object>' # ) with tag("h2", klass="Header"): text("Targets Table") with tag("table", id="average case table"): doc.asis(avg_html_table) with tag("p", klass="Histograms Text"): text( "Histograms for the input variables used to generate predictions and risk recommendations above." ) with tag("div", id="Histograms"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Histograms_Fig.png" ), ) # doc.asis('<object data="cid:'+os.path.basename(os.path.splitext(filename)[0]+'.PNG') + '" type="image/jpeg"></object>') # doc.asis( # '<object data="' # + os.path.basename( # os.path.splitext(filename)[0] + "_Histograms_Fig.png" # ) # + '" type="image/jpeg"></object>' # ) with tag("h2", klass="Header"): text("Model Diagnostic Figures") with tag("p", klass="Performance Indicator General Text"): text( "These figures evaluate the performance of the ANN ensemble model after training. These figures serve as an indicator of the similarity between the distribution of forecasts produced by the ANN ensembles and the observed data and can be used to evaluate the soundness of the models, and of the confidence we can have in the targets." ) with tag("p", klass="Performance annotation 1"): text( "Subplot A: Household FRC forecasts from an ensemble of" + str(self.network_count) + " neural networks using the full provided dataset." ) with tag("p", klass="Performance annotation 2"): text( "Subplot B: Confidence Interval (CI) reliability diagram. Each point shows the percentage of observations captured within each ensemble CI. An ideal model will have all points on the 1:1 line. If points are below the line, indicates forecast underdispersion (may lead to overly optimistic targets). If points are above the line, indicates overdispersion (may result in overly conservative targets)." ) with tag("p", klass="Performance annotation 3"): text( "Subplot C: Rank Histogram. This creates a histogram of the relative location of all recorded observations relative to each ensemble member. An ideal model has a flat rank histogram. A U-shaped rank histogram indicates forecast underdispersion (may lead to overly optimistic targets). An arch-shaped rank histogram indicates overdispersion (may result in overly conservative targets)." ) with tag("div", id="diagnostic_graphs"): doc.stag( "img", src=os.path.basename( os.path.splitext(filename)[0] + "_Calibration_Diagnostic_Figs.png" ), ) # doc.asis( # '<object data="' # + os.path.basename( # os.path.splitext(filename)[0] + "_Calibration_Diagnostic_Figs.png" # ) # + '" type="image/jpeg"></object>' # ) doc.asis(skipped_rows_table) totalmatches = 0 if len(self.ruleset): with tag("ul", id="ann_ruleset"): for rule in self.ruleset: totalmatches += rule[2] line("li", "%s. Matches: %d" % (rule[0], rule[2])) with tag("div", id="pythonSkipped_count"): text(totalmatches) file = open(filename, "w+") file.write(doc.getvalue()) file.close() return doc.getvalue() def generate_metadata(self): metadata = {} metadata["average_time"] = self.avg_time_elapsed # in seconds return metadata def prepare_table_for_html_report(self, storage_target): """Formats the results into an html table for display.""" avg_table_df = pd.DataFrame() avg_table_df["Input FRC (mg/L)"] = self.avg_case_results_am[FRC_IN] avg_table_df["Storage Duration for Target"] = storage_target if WATTEMP in self.datainputs.columns: avg_table_df["Water Temperature (Degrees C)"] = self.avg_case_results_am[ WATTEMP ] if COND in self.datainputs.columns: avg_table_df[ "Electrical Conductivity (s*10^-6/cm)" ] = self.avg_case_results_am[COND] if self.post_process_check == False: avg_table_df[ "Median Predicted Household FRC Concentration (mg/L) - AM Collection" ] = np.round(self.avg_case_results_am["median"], decimals=3) avg_table_df[ "Median Predicted Household FRC Concentration (mg/L) - PM Collection" ] = np.round(self.avg_case_results_pm["median"], decimals=3) avg_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - AM Collection" ] = np.round(self.avg_case_results_am["probability<=0.20"], decimals=3) avg_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - PM Collection" ] = np.round(self.avg_case_results_pm["probability<=0.20"], decimals=3) # avg_table_df['Predicted Risk of Household FRC below 0.30 mg/L'] = self.avg_case_results['probability<=0.30'] else: avg_table_df[ "Median Predicted Household FRC Concentration (mg/L) - AM Collection" ] = np.round(self.avg_case_results_am_post["median"], decimals=3) avg_table_df[ "Median Predicted Household FRC Concentration (mg/L) - PM Collection" ] = np.round(self.avg_case_results_pm_post["median"], decimals=3) avg_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - AM Collection" ] = np.round(self.avg_case_results_am_post["probability<=0.20"], decimals=3) avg_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - PM Collection" ] = np.round(self.avg_case_results_pm_post["probability<=0.20"], decimals=3) # avg_table_df['Predicted Risk of Household FRC below 0.30 mg/L'] = self.avg_case_results['probability<=0.30'] str_io = io.StringIO() avg_table_df.to_html(buf=str_io, table_id="annTable") avg_html_str = str_io.getvalue() if WATTEMP in self.datainputs.columns or COND in self.datainputs.columns: worst_table_df = pd.DataFrame() worst_table_df["Input FRC (mg/L)"] = self.worst_case_results_am[FRC_IN] worst_table_df["Storage Duration for Target"] = storage_target if WATTEMP in self.datainputs.columns: worst_table_df[ "Water Temperature(" + r"$\degree$" + "C)" ] = self.worst_case_results_am[WATTEMP] if COND in self.datainputs.columns: worst_table_df[ "Electrical Conductivity (" + r"$\mu$" + "s/cm)" ] = self.worst_case_results_am[COND] worst_table_df["Storage Duration for Target"] = storage_target if self.post_process_check == False: worst_table_df[ "Median Predicted FRC level at Household (mg/L) - AM Collection" ] = np.round(self.worst_case_results_am["median"], decimals=3) worst_table_df[ "Median Predicted FRC level at Household (mg/L) - PM Collection" ] = np.round(self.worst_case_results_pm["median"], decimals=3) worst_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - AMM Collection" ] = np.round( self.worst_case_results_am["probability<=0.20"], decimals=3 ) worst_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - PM Collection" ] = np.round( self.worst_case_results_pm["probability<=0.20"], decimals=3 ) else: worst_table_df[ "Median Predicted FRC level at Household (mg/L) - AM Collection" ] = np.round(self.worst_case_results_am_post["median"], decimals=3) worst_table_df[ "Median Predicted FRC level at Household (mg/L) - PM Collection" ] = np.round(self.worst_case_results_pm_post["median"], decimals=3) worst_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - AMM Collection" ] = np.round( self.worst_case_results_am_post["probability<=0.20"], decimals=3 ) worst_table_df[ "Predicted Risk of Household FRC below 0.20 mg/L - PM Collection" ] = np.round( self.worst_case_results_pm_post["probability<=0.20"], decimals=3 ) # worst_table_df['Predicted Risk of Household FRC below 0.30 mg/L'] = self.worst_case_results['probability<=0.30'] str_io = io.StringIO() worst_table_df.to_html(buf=str_io, table_id='annTable') worst_html_str = str_io.getvalue() return avg_html_str, worst_html_str else: return avg_html_str def skipped_rows_html(self): if self.skipped_rows.empty: return "" printable_columns = [ "ts_datetime", FRC_IN, "hh_datetime", FRC_OUT, WATTEMP, COND, ] required_columns = [rule[1] for rule in self.ruleset] doc, tag, text = Doc().tagtext() with tag( "table", klass="table center fill-whitespace", id="pythonSkipped", border="1", ): with tag("thead"): with tag("tr"): for col in printable_columns: with tag("th"): text(col) with tag("tbody"): for (_, row) in self.skipped_rows[printable_columns].iterrows(): with tag("tr"): for col in printable_columns: with tag("td"): # check if required value in cell is nan if col in required_columns and ( not row[col] or row[col] != row[col] ): with tag("div", klass="red-cell"): text("") else: text(row[col]) return doc.getvalue() def valid_dates(self, series): mask = [] for i in series.index.to_numpy(): row = series[i] if row == None: mask.append(True) continue if isinstance(row, str) and not row.replace(".", "", 1).isdigit(): try: datetime.datetime.strptime( row[:16].replace("/", "-"), self.xl_dateformat ) mask.append(False) except: mask.append(True) else: try: start = float(row) start = xldate_as_datetime(start, datemode=0) mask.append(False) except: mask.append(True) return mask def execute_rule(self, description, column, matches): rule = (description, column, sum(matches)) self.ruleset.append(rule) if sum(matches): self.file.drop(self.file.loc[matches].index, inplace=True) def run_swot(self, input_file, results_file, report_file, storage_target): now = datetime.datetime.now() directory = ( "model_retraining" + os.sep + now.strftime("%m%d%Y_%H%M%S") + "_" + os.path.basename(input_file) ) # Uncommentfor Excel processing # file = pd.read_excel(input_file) file = pd.read_csv(input_file) # Support from 3 different input templates se1_frc, ts_frc, and ts frc1 if "se1_frc" in file.columns: FRC_IN = "se1_frc" WATTEMP = "se1_wattemp" COND = "se1_cond" FRC_OUT = "se4_frc" elif "ts_frc1" in file.columns: FRC_IN = "ts_frc1" WATTEMP = "ts_wattemp" COND = "ts_cond" FRC_OUT = "hh_frc1" elif "ts_frc" in file.columns: FRC_IN = "ts_frc" WATTEMP = "ts_wattemp" COND = "ts_cond" FRC_OUT = "hh_frc" self.import_data_from_csv(input_file) self.set_up_model() self.train_SWOT_network(directory) self.calibration_performance_evaluation(report_file) self.post_process_cal() # self.full_performance_evaluation(directory) self.set_inputs_for_table(storage_target) self.predict() self.display_results() self.export_results_to_csv(results_file) self.generate_html_report(report_file, storage_target) metadata = self.generate_metadata() return metadata

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855

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143,685

4.134482

0.053723

0.026256

0.016158

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0.743387

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0.692442

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143,685

3,420

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null

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0

1

0

null

0

3

7cbc1c2cfd82e096e87227121e7b6641e2523065

634

py

Python

desktop_shop/util.py

Alex92rus/desktop_shop

305caf263b56b279e46d5945285189673b868988

[ "MIT" ]

null

desktop_shop/util.py

Alex92rus/desktop_shop

305caf263b56b279e46d5945285189673b868988

[ "MIT" ]

null

desktop_shop/util.py

Alex92rus/desktop_shop

305caf263b56b279e46d5945285189673b868988

[ "MIT" ]

null

# -*- coding: utf-8 -*- """ Created on Sat Nov 14 16:31:46 2020 @author: Korean_Crimson """ import datetime def generate_timestamp() -> str: '''Generates date+timestamp of current time''' return datetime.datetime.now().strftime('%Y%m%d_%H%M%S') def get_current_date() -> str: '''Returns current date''' return datetime.datetime.now().strftime('%Y-%m-%d') def validate_date_string(date_string) -> bool: '''Checks if passed string can be converted to date''' try: datetime.datetime.strptime(date_string, '%Y-%m-%d') valid = True except ValueError: valid = False return valid

24.384615

60

0.648265

87

634

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634

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7cd63e9f63f8e91c04efeef40461ed815c84dfc9

143

py

Python

BasicExerciseAndKnowledge/w3cschool/n26_fibs_RecursiveWay.py

Jonathan1214/learn-python

19d0299b30e953069f19402bff5c464c4d5580be

[ "MIT" ]

null

BasicExerciseAndKnowledge/w3cschool/n26_fibs_RecursiveWay.py

Jonathan1214/learn-python

19d0299b30e953069f19402bff5c464c4d5580be

[ "MIT" ]

null

BasicExerciseAndKnowledge/w3cschool/n26_fibs_RecursiveWay.py

Jonathan1214/learn-python

19d0299b30e953069f19402bff5c464c4d5580be

[ "MIT" ]

null

#coding:utf-8 # 题目：利用递归方法求5!。 def factorial(num): if num in (0,1): return 1 return factorial(num-1) * num print(factorial(5))

15.888889

33

0.615385

23

143

3.826087

0.652174

0.272727

0

0.063636

0.230769

143

9

34

15.888889

0.736364

0.181818

0

1

0.2

false

0

0.6

0.2

1

0

null

1

0

1

0

null

0

3

7cecbc7a83d800700a0bc3e1e1e13789a0d1223c

140

py

Python

aiocloudflare/api/accounts/roles/roles.py

Stewart86/aioCloudflare

341c0941f8f888a8b7e696e64550bce5da4949e6

[ "MIT" ]

2

2021-09-14T13:20:55.000Z

2022-02-24T14:18:24.000Z

aiocloudflare/api/accounts/roles/roles.py

Stewart86/aioCloudflare

341c0941f8f888a8b7e696e64550bce5da4949e6

[ "MIT" ]

46

2021-09-08T08:39:45.000Z

2022-03-29T12:31:05.000Z

aiocloudflare/api/accounts/roles/roles.py

Stewart86/aioCloudflare

341c0941f8f888a8b7e696e64550bce5da4949e6

[ "MIT" ]

1

2021-12-30T23:02:23.000Z

from aiocloudflare.commons.auth import Auth class Roles(Auth): _endpoint1 = "accounts" _endpoint2 = "roles" _endpoint3 = None

17.5

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null

0

1

0

null

0

1

0

3

7ceec091cb6f866e1695e04948d008917f13dd0f

10,228

py

Python

tests/parsers/asl.py

pyllyukko/plaso

7533db2d1035ca71d264d6281ebd5db2d073c587

[ "Apache-2.0" ]

2

2019-10-23T03:37:59.000Z

2020-08-14T17:09:26.000Z

tests/parsers/asl.py

pyllyukko/plaso

7533db2d1035ca71d264d6281ebd5db2d073c587

[ "Apache-2.0" ]

null

tests/parsers/asl.py

pyllyukko/plaso

7533db2d1035ca71d264d6281ebd5db2d073c587

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """Tests for Apple System Log file parser.""" import unittest from plaso.lib import errors from plaso.parsers import asl from tests.parsers import test_lib class ASLParserTest(test_lib.ParserTestCase): """Tests for Apple System Log file parser.""" # pylint: disable=protected-access _TEST_RECORD = bytes(bytearray([ 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x44, 0x61, 0x72, 0x6b, 0x54, 0x65, 0x6d, 0x70, 0x6c, 0x61, 0x72, 0x2d, 0x32, 0x2e, 0x6c, 0x6f, 0x63, 0x61, 0x6c, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0a, 0x6c, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x64, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x14, 0x63, 0x6f, 0x6d, 0x2e, 0x61, 0x70, 0x70, 0x6c, 0x65, 0x2e, 0x6c, 0x6f, 0x63, 0x61, 0x74, 0x69, 0x6f, 0x6e, 0x64, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x43, 0x46, 0x4c, 0x6f, 0x67, 0x20, 0x4c, 0x6f, 0x63, 0x61, 0x6c, 0x20, 0x54, 0x69, 0x6d, 0x65, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x18, 0x32, 0x30, 0x31, 0x33, 0x2d, 0x31, 0x31, 0x2d, 0x32, 0x35, 0x20, 0x30, 0x39, 0x3a, 0x34, 0x35, 0x3a, 0x33, 0x35, 0x2e, 0x37, 0x30, 0x31, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x0d, 0x43, 0x46, 0x4c, 0x6f, 0x67, 0x20, 0x54, 0x68, 0x72, 0x65, 0x61, 0x64, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x96, 0x49, 0x6e, 0x63, 0x6f, 0x72, 0x72, 0x65, 0x63, 0x74, 0x20, 0x4e, 0x53, 0x53, 0x74, 0x72, 0x69, 0x6e, 0x67, 0x45, 0x6e, 0x63, 0x6f, 0x64, 0x69, 0x6e, 0x67, 0x20, 0x76, 0x61, 0x6c, 0x75, 0x65, 0x20, 0x30, 0x78, 0x38, 0x30, 0x30, 0x30, 0x31, 0x30, 0x30, 0x20, 0x64, 0x65, 0x74, 0x65, 0x63, 0x74, 0x65, 0x64, 0x2e, 0x20, 0x41, 0x73, 0x73, 0x75, 0x6d, 0x69, 0x6e, 0x67, 0x20, 0x4e, 0x53, 0x41, 0x53, 0x43, 0x49, 0x49, 0x53, 0x74, 0x72, 0x69, 0x6e, 0x67, 0x45, 0x6e, 0x63, 0x6f, 0x64, 0x69, 0x6e, 0x67, 0x2e, 0x20, 0x57, 0x69, 0x6c, 0x6c, 0x20, 0x73, 0x74, 0x6f, 0x70, 0x20, 0x74, 0x68, 0x69, 0x73, 0x20, 0x63, 0x6f, 0x6d, 0x70, 0x61, 0x74, 0x69, 0x62, 0x6c, 0x69, 0x74, 0x79, 0x20, 0x6d, 0x61, 0x70, 0x70, 0x69, 0x6e, 0x67, 0x20, 0x62, 0x65, 0x68, 0x61, 0x76, 0x69, 0x6f, 0x72, 0x20, 0x69, 0x6e, 0x20, 0x74, 0x68, 0x65, 0x20, 0x6e, 0x65, 0x61, 0x72, 0x20, 0x66, 0x75, 0x74, 0x75, 0x72, 0x65, 0x2e, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x11, 0x53, 0x65, 0x6e, 0x64, 0x65, 0x72, 0x5f, 0x4d, 0x61, 0x63, 0x68, 0x5f, 0x55, 0x55, 0x49, 0x44, 0x00, 0x00, 0x01, 0x00, 0x00, 0x00, 0x25, 0x35, 0x30, 0x45, 0x31, 0x46, 0x37, 0x36, 0x41, 0x2d, 0x36, 0x30, 0x46, 0x46, 0x2d, 0x33, 0x36, 0x38, 0x43, 0x2d, 0x42, 0x37, 0x34, 0x45, 0x2d, 0x45, 0x42, 0x34, 0x38, 0x46, 0x36, 0x44, 0x39, 0x38, 0x43, 0x35, 0x31, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0xa4, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x03, 0xce, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x8c, 0x1e, 0x00, 0x00, 0x00, 0x00, 0x52, 0x93, 0x1c, 0x3f, 0x2a, 0x0c, 0xc9, 0x28, 0x00, 0x04, 0x00, 0x01, 0x00, 0x00, 0x00, 0x45, 0x00, 0x00, 0x00, 0xcd, 0x00, 0x00, 0x00, 0xcd, 0x00, 0x00, 0x00, 0xcd, 0xff, 0xff, 0xff, 0xff, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x06, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x1a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x2a, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x8c, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x44, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x5b, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x79, 0x84, 0x31, 0x30, 0x30, 0x37, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x28, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x01, 0x3f, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00, 0x00])) def testParseRecord(self): """Tests the _ParseRecord function.""" parser = asl.ASLParser() storage_writer = self._CreateStorageWriter() parser_mediator = self._CreateParserMediator(storage_writer) file_object = self._CreateFileObject('asl', self._TEST_RECORD) next_record_offset = parser._ParseRecord(parser_mediator, file_object, 362) self.assertEqual(next_record_offset, 974) # Test with log entry descriptor data too small. file_object = self._CreateFileObject('asl', self._TEST_RECORD[:452]) with self.assertRaises(errors.ParseError): parser._ParseRecord(parser_mediator, file_object, 362) # TODO: test with invalid additional data size. def testParseRecordExtraField(self): """Tests the _ParseRecordExtraField function.""" parser = asl.ASLParser() extra_field_map = parser._GetDataTypeMap('asl_record_extra_field') extra_field = extra_field_map.CreateStructureValues( name_string_offset=10, value_string_offset=20) extra_field_data = extra_field_map.FoldByteStream(extra_field) extra_field_value = parser._ParseRecordExtraField(extra_field_data, 0) self.assertEqual(extra_field_value.name_string_offset, 10) self.assertEqual(extra_field_value.value_string_offset, 20) # Test with extra field data too small. with self.assertRaises(errors.ParseError): parser._ParseRecordExtraField(extra_field_data[:-1], 0) def testParseRecordString(self): """Tests the _ParseRecordString function.""" parser = asl.ASLParser() string_map = parser._GetDataTypeMap('asl_record_string') string = string_map.CreateStructureValues( unknown1=0, string_size=4, string='test') string_data = string_map.FoldByteStream(string) # Prefix the string data with 4 bytes since string offset cannot be 0. string_data = b''.join([b'\x00\x00\x00\x00', string_data]) string_value = parser._ParseRecordString(string_data, 0, 0) self.assertIsNone(string_value) string_value = parser._ParseRecordString(string_data, 0, 4) self.assertEqual(string_value, 'test') # Test with string data too small. with self.assertRaises(errors.ParseError): parser._ParseRecordString(string_data[:-1], 0, 4) # Test with inline string data. string_value = parser._ParseRecordString(b'', 0, 0x8474657374000000) self.assertEqual(string_value, 'test') with self.assertRaises(errors.ParseError): parser._ParseRecordString(b'', 0, 0xf474657374000000) with self.assertRaises(errors.ParseError): parser._ParseRecordString(b'', 0, 0x8f74657374000000) with self.assertRaises(errors.ParseError): parser._ParseRecordString(b'', 0, 0x84ffffffff000000) def testGetFormatSpecification(self): """Tests the GetFormatSpecification function.""" format_specification = asl.ASLParser.GetFormatSpecification() self.assertIsNotNone(format_specification) def _CreateFileHeaderData(self, parser): """Creates file header test data. Args: parser (ASLParser): ASL parser. Returns: bytes: file header test data. """ file_header_map = parser._GetDataTypeMap('asl_file_header') unknown1_data = b'\x00' * 36 file_header = file_header_map.CreateStructureValues( signature=b'ASL DB\x00\x00\x00\x00\x00\x00', format_version=2, first_log_entry_offset=80, creation_time=0, cache_size=0, last_log_entry_offset=0, unknown1=unknown1_data) return file_header_map.FoldByteStream(file_header) def testParseFileObject(self): """Tests the ParseFileObject function.""" parser = asl.ASLParser() file_header_data = self._CreateFileHeaderData(parser) storage_writer = self._CreateStorageWriter() parser_mediator = self._CreateParserMediator(storage_writer) file_object = self._CreateFileObject('asl', file_header_data) parser.ParseFileObject(parser_mediator, file_object) self.assertEqual(storage_writer.number_of_warnings, 0) self.assertEqual(storage_writer.number_of_events, 0) # Test with file header data too small. file_object = self._CreateFileObject('asl', file_header_data[:-1]) with self.assertRaises(errors.UnableToParseFile): parser.ParseFileObject(parser_mediator, file_object) # Test with invalid signature. file_object = self._CreateFileObject( 'asl', b''.join([b'\xff\xff\xff\xff', file_header_data[4:]])) storage_writer = self._CreateStorageWriter() parser_mediator = self._CreateParserMediator(storage_writer) with self.assertRaises(errors.UnableToParseFile): parser.ParseFileObject(parser_mediator, file_object) # Test with first record data too small. file_object = self._CreateFileObject('asl', b''.join([ file_header_data, self._TEST_RECORD[:452]])) parser.ParseFileObject(parser_mediator, file_object) self.assertEqual(storage_writer.number_of_warnings, 1) self.assertEqual(storage_writer.number_of_events, 0) def testParse(self): """Tests the Parse function.""" parser = asl.ASLParser() storage_writer = self._ParseFile(['applesystemlog.asl'], parser) self.assertEqual(storage_writer.number_of_warnings, 0) self.assertEqual(storage_writer.number_of_events, 2) events = list(storage_writer.GetEvents()) # Note that "compatiblity" is spelt incorrectly in the actual message being # tested here. expected_event_values = { 'computer_name': 'DarkTemplar-2.local', 'data_type': 'mac:asl:event', 'extra_information': ( 'CFLog Local Time: 2013-11-25 09:45:35.701, ' 'CFLog Thread: 1007, ' 'Sender_Mach_UUID: 50E1F76A-60FF-368C-B74E-EB48F6D98C51'), 'facility': 'com.apple.locationd', 'group_id': 205, 'level': 4, 'message': ( 'Incorrect NSStringEncoding value 0x8000100 detected. ' 'Assuming NSASCIIStringEncoding. Will stop this compatiblity ' 'mapping behavior in the near future.'), 'message_id': 101406, 'pid': 69, 'read_gid': -1, 'read_uid': 205, 'record_position': 442, 'sender': 'locationd', 'timestamp': '2013-11-25 09:45:35.705481', 'user_sid': '205'} self.CheckEventValues(storage_writer, events[0], expected_event_values) if __name__ == '__main__': unittest.main()

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0

null

0

1

0

1

0

null

0

3

7cef36bc0025f56675335f7db3a0fe2078984246

46

py

Python

Knowledge/Python/variables.py

thealexcesar/Harvard-CS50-Web

f099e7cf3d3c7f081dd4cb564d35ab6f5ff52bdf

[ "MIT" ]

2

2021-04-05T15:29:08.000Z

2022-03-08T11:07:21.000Z

Knowledge/Python/variables.py

thealexcesar/Harvard-CS50-Web

f099e7cf3d3c7f081dd4cb564d35ab6f5ff52bdf

[ "MIT" ]

null

Knowledge/Python/variables.py

thealexcesar/Harvard-CS50-Web

f099e7cf3d3c7f081dd4cb564d35ab6f5ff52bdf

[ "MIT" ]

null

a = 28 b = 1.5 c = "Hello!" d = True e = None

7.666667

12

0.478261

11

46

2

1

0

0.129032

0.326087

46

5

13

9.2

0.580645

0

0.130435

0

1

0

false

0

1

0

null

0

1

0

null

0

3

6b06a0bf4f6d6883c503d6354aadfeff8918c158

210

py

Python

datasets/csqa_new/extract_submission.py

gogowhy/ENet_framework

74e4417a249376e41878c0595518db2481d45ce1

[ "MIT" ]

244

2019-09-06T07:53:57.000Z

2022-03-28T19:32:15.000Z

datasets/csqa_new/extract_submission.py

gogowhy/ENet_framework

74e4417a249376e41878c0595518db2481d45ce1

[ "MIT" ]

null

datasets/csqa_new/extract_submission.py

gogowhy/ENet_framework

74e4417a249376e41878c0595518db2481d45ce1

[ "MIT" ]

61

2019-09-14T07:06:57.000Z

2022-03-16T07:02:52.000Z

import json with open("test_rand_split.jsonl", 'r') as fw: for line in open("test_rand_split.jsonl", 'r').readlines(): data = json.loads(line.strip()) print(data["id"]+','+data["answerKey"])

42

63

0.628571

31

210

4.129032

0.677419

0.125

0.1875

0.265625

0.359375

0

0.166667

210

5

64

42

0.731429

0

0.265403

0.199052

0

1

0

false

0

0.2

0

0.2

0

null

0

1

0

1

0

null

0

3

6b0782a9e582959a13bad44c331bf33e0963ce20

448

py

Python

atomicpress/themes/minimal/helpers.py

marteinn/AtomicPress

b8a0ca9c9c327f062833fc4a401a8ac0baccf6d1

[ "MIT" ]

7

2015-04-10T07:42:53.000Z

2016-01-20T16:46:48.000Z

atomicpress/themes/minimal/helpers.py

marteinn/AtomicPress

b8a0ca9c9c327f062833fc4a401a8ac0baccf6d1

[ "MIT" ]

4

2015-09-01T19:39:43.000Z

2015-09-06T17:57:27.000Z

atomicpress/themes/minimal/helpers.py

marteinn/AtomicPress

b8a0ca9c9c327f062833fc4a401a8ac0baccf6d1

[ "MIT" ]

1

2016-12-05T16:27:59.000Z

from sqlalchemy import or_, and_ from atomicpress.app import app from atomicpress.models import Post, PostStatus def gen_post_status(): """ Show only published posts outside debug. """ if not app.config["DEBUG"]: post_status = and_(Post.status == PostStatus.PUBLISH) else: post_status = or_(Post.status == PostStatus.PUBLISH, Post.status == PostStatus.DRAFT) return post_status

24.888889

61

0.658482

53

448

5.396226

0.490566

0.244755

0.20979

0.188811

0

0.252232

448

17

62

26.352941

0.853731

0.089286

0

0.012755

0

1

0.1

false

0

0.3

0

0.5

0

null

1

0

null

0

3

6b08b63255aa6aef6063d2bb955dc708928c668c

177

py

Python

src/data/helpers.py

martinlarsalbert/roll_decay_damping

5982fae683ee2b4d3b51d07956a1a9544f89d629

[ "MIT" ]

null

src/data/helpers.py

martinlarsalbert/roll_decay_damping

5982fae683ee2b4d3b51d07956a1a9544f89d629

[ "MIT" ]

null

src/data/helpers.py

martinlarsalbert/roll_decay_damping

5982fae683ee2b4d3b51d07956a1a9544f89d629

[ "MIT" ]

null

import pandas as pd import os def load(file_name): file_path = os.path.join('../../data/external/',file_name) data = pd.read_csv(file_path, index_col=0) return data

25.285714

62

0.694915

30

177

3.9

0.633333

0.136752

0

0.006757

0.163842

177

7

63

25.285714

0.783784

0

0.11236

0

1

0.166667

false

0

0.333333

0

0.666667

0

null

0

1

0

null

0

1

0

1

0

3

6b17d5bee29a57e35b7da4ad3f75206d512304bf

44,731

py

Python

pysnmp-with-texts/Nortel-MsCarrier-MscPassport-DataCollectionMIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

8

2019-05-09T17:04:00.000Z

2021-06-09T06:50:51.000Z

pysnmp-with-texts/Nortel-MsCarrier-MscPassport-DataCollectionMIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

4

2019-05-31T16:42:59.000Z

2020-01-31T21:57:17.000Z

pysnmp-with-texts/Nortel-MsCarrier-MscPassport-DataCollectionMIB.py

agustinhenze/mibs.snmplabs.com

1fc5c07860542b89212f4c8ab807057d9a9206c7

[ "Apache-2.0" ]

10

2019-04-30T05:51:36.000Z

2022-02-16T03:33:41.000Z

# # PySNMP MIB module Nortel-MsCarrier-MscPassport-DataCollectionMIB (http://snmplabs.com/pysmi) # ASN.1 source file:///Users/davwang4/Dev/mibs.snmplabs.com/asn1/Nortel-MsCarrier-MscPassport-DataCollectionMIB # Produced by pysmi-0.3.4 at Wed May 1 14:29:37 2019 # On host DAVWANG4-M-1475 platform Darwin version 18.5.0 by user davwang4 # Using Python version 3.7.3 (default, Mar 27 2019, 09:23:15) # ObjectIdentifier, OctetString, Integer = mibBuilder.importSymbols("ASN1", "ObjectIdentifier", "OctetString", "Integer") NamedValues, = mibBuilder.importSymbols("ASN1-ENUMERATION", "NamedValues") ValueRangeConstraint, ValueSizeConstraint, SingleValueConstraint, ConstraintsUnion, ConstraintsIntersection = mibBuilder.importSymbols("ASN1-REFINEMENT", "ValueRangeConstraint", "ValueSizeConstraint", "SingleValueConstraint", "ConstraintsUnion", "ConstraintsIntersection") Unsigned32, RowStatus, Integer32, Gauge32, DisplayString, Counter32, StorageType = mibBuilder.importSymbols("Nortel-MsCarrier-MscPassport-StandardTextualConventionsMIB", "Unsigned32", "RowStatus", "Integer32", "Gauge32", "DisplayString", "Counter32", "StorageType") NonReplicated, EnterpriseDateAndTime, AsciiString = mibBuilder.importSymbols("Nortel-MsCarrier-MscPassport-TextualConventionsMIB", "NonReplicated", "EnterpriseDateAndTime", "AsciiString") mscComponents, mscPassportMIBs = mibBuilder.importSymbols("Nortel-MsCarrier-MscPassport-UsefulDefinitionsMIB", "mscComponents", "mscPassportMIBs") NotificationGroup, ModuleCompliance = mibBuilder.importSymbols("SNMPv2-CONF", "NotificationGroup", "ModuleCompliance") ObjectIdentity, TimeTicks, Counter64, Unsigned32, MibIdentifier, MibScalar, MibTable, MibTableRow, MibTableColumn, Integer32, Bits, Gauge32, IpAddress, Counter32, NotificationType, iso, ModuleIdentity = mibBuilder.importSymbols("SNMPv2-SMI", "ObjectIdentity", "TimeTicks", "Counter64", "Unsigned32", "MibIdentifier", "MibScalar", "MibTable", "MibTableRow", "MibTableColumn", "Integer32", "Bits", "Gauge32", "IpAddress", "Counter32", "NotificationType", "iso", "ModuleIdentity") TextualConvention, DisplayString = mibBuilder.importSymbols("SNMPv2-TC", "TextualConvention", "DisplayString") dataCollectionMIB = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14)) mscCol = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21)) mscColRowStatusTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 1), ) if mibBuilder.loadTexts: mscColRowStatusTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColRowStatusTable.setDescription('This entry controls the addition and deletion of mscCol components.') mscColRowStatusEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 1, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex")) if mibBuilder.loadTexts: mscColRowStatusEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColRowStatusEntry.setDescription('A single entry in the table represents a single mscCol component.') mscColRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 1, 1, 1), RowStatus()).setMaxAccess("readwrite") if mibBuilder.loadTexts: mscColRowStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColRowStatus.setDescription('This variable is used as the basis for SNMP naming of mscCol components. These components can be added.') mscColComponentName = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 1, 1, 2), DisplayString()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColComponentName.setStatus('mandatory') if mibBuilder.loadTexts: mscColComponentName.setDescription("This variable provides the component's string name for use with the ASCII Console Interface") mscColStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 1, 1, 4), StorageType()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColStorageType.setStatus('mandatory') if mibBuilder.loadTexts: mscColStorageType.setDescription('This variable represents the storage type value for the mscCol tables.') mscColIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 1, 1, 10), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 3, 4, 5, 6))).clone(namedValues=NamedValues(("accounting", 0), ("alarm", 1), ("log", 2), ("debug", 3), ("scn", 4), ("trap", 5), ("stats", 6)))) if mibBuilder.loadTexts: mscColIndex.setStatus('mandatory') if mibBuilder.loadTexts: mscColIndex.setDescription('This variable represents the index for the mscCol tables.') mscColProvTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 10), ) if mibBuilder.loadTexts: mscColProvTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColProvTable.setDescription('This group specifies all of the provisioning data for a DCS Collector.') mscColProvEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 10, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex")) if mibBuilder.loadTexts: mscColProvEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColProvEntry.setDescription('An entry in the mscColProvTable.') mscColAgentQueueSize = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 10, 1, 1), Unsigned32().subtype(subtypeSpec=ConstraintsUnion(ValueRangeConstraint(0, 0), ValueRangeConstraint(20, 10000), ))).setMaxAccess("readwrite") if mibBuilder.loadTexts: mscColAgentQueueSize.setStatus('obsolete') if mibBuilder.loadTexts: mscColAgentQueueSize.setDescription("This attribute has been replaced with the agentQueueSize attribute in the Lp Engineering DataStream Ov component. Upon migration, if the existing provisioned value of this attribute is the same as the system default for this type of data, no new components are added because the default is what the DataStream component already would be using. Otherwise, if the value is not the same as the system default, then for each Lp which is provisioned at the time of the migration, a DataStream is provisioned and the Ov's agentQueueSize is set to the non-default value.") mscColStatsTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 11), ) if mibBuilder.loadTexts: mscColStatsTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColStatsTable.setDescription('This group specifies the statistics operational attributes of the DCS Collector, Agent and Spooler components.') mscColStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 11, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex")) if mibBuilder.loadTexts: mscColStatsEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColStatsEntry.setDescription('An entry in the mscColStatsTable.') mscColCurrentQueueSize = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 11, 1, 1), Gauge32().subtype(subtypeSpec=ValueRangeConstraint(0, 4294967295))).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColCurrentQueueSize.setStatus('mandatory') if mibBuilder.loadTexts: mscColCurrentQueueSize.setDescription('This gauge contains the current number of records held by this DCS component.') mscColRecordsRx = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 11, 1, 2), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColRecordsRx.setStatus('mandatory') if mibBuilder.loadTexts: mscColRecordsRx.setDescription('This counter contains the cumulative number of records received by a DCS component, from applications which send data to it, since the processor last restarted. This counter wraps to 0 when the maximum value is exceeded.') mscColRecordsDiscarded = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 11, 1, 3), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColRecordsDiscarded.setStatus('mandatory') if mibBuilder.loadTexts: mscColRecordsDiscarded.setDescription('This is the cumulative number of records discarded by this DCS component since the processor last restarted. This counter wraps to 0 when the maximum value is exceeded.') mscColTimesTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 266), ) if mibBuilder.loadTexts: mscColTimesTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColTimesTable.setDescription('This attribute specifies the scheduled times at which data should be collected. Only accounting applications need the capability to generate data in this way. Setting this attribute for other streams has no effect. The user can enter the times in any order and duplicates are prevented at data entry. There is a limit of 24 entries, which is imposed at semantic check time. The collection times are triggered in chronological order. A semantic check error is issued if any 2 entries are less than 1 hour apart or if any 2 entries are more than 12 hours apart (which implies that if any entries are provided, there must be at least 2 entries). Note that by default (that is, in the absence of a provisioned schedule), a Virtual Circuit (VC) starts its own 12-hour accounting timer. If any collection times are provisioned here, then the Time- Of-Day-Accounting (TODA) method is used in place of 12-hour accounting. This is applicable to both Switched VCs and Permanent VCs.') mscColTimesEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 266, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColTimesValue")) if mibBuilder.loadTexts: mscColTimesEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColTimesEntry.setDescription('An entry in the mscColTimesTable.') mscColTimesValue = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 266, 1, 1), EnterpriseDateAndTime().subtype(subtypeSpec=ValueSizeConstraint(5, 5)).setFixedLength(5)).setMaxAccess("readwrite") if mibBuilder.loadTexts: mscColTimesValue.setStatus('mandatory') if mibBuilder.loadTexts: mscColTimesValue.setDescription('This variable represents both the value and the index for the mscColTimesTable.') mscColTimesRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 266, 1, 2), RowStatus()).setMaxAccess("writeonly") if mibBuilder.loadTexts: mscColTimesRowStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColTimesRowStatus.setDescription('This variable is used to control the addition and deletion of individual values of the mscColTimesTable.') mscColLastTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 275), ) if mibBuilder.loadTexts: mscColLastTable.setStatus('obsolete') if mibBuilder.loadTexts: mscColLastTable.setDescription('Note: This was made obsolete in R4.1 (BD0108A). This attribute is used for Collector/stats and Collector/account. For statistics, when collection is turned off, or prior to the very first probe, the value is the empty list. Otherwise, this is the network time at which the last probe was sent out (that is, the last time that statistics were collected from, or at least reset by, the applications providing them). For accounting, when no entries exist in collectionTimes, or prior to the very first collection time, the value is the empty list. Otherwise, this is the network time at which the last time-of-day changeover occurred.') mscColLastEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 275, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColLastValue")) if mibBuilder.loadTexts: mscColLastEntry.setStatus('obsolete') if mibBuilder.loadTexts: mscColLastEntry.setDescription('An entry in the mscColLastTable.') mscColLastValue = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 275, 1, 1), EnterpriseDateAndTime().subtype(subtypeSpec=ValueSizeConstraint(19, 19)).setFixedLength(19)).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColLastValue.setStatus('obsolete') if mibBuilder.loadTexts: mscColLastValue.setDescription('This variable represents both the value and the index for the mscColLastTable.') mscColPeakTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 279), ) if mibBuilder.loadTexts: mscColPeakTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColPeakTable.setDescription('This attribute specifies the length of the accounting peak water mark interval. It is at least one minute and at most 15 minutes long. An accounting peak water mark within a given accounting interval is the accounting count which occured during a peak water mark interval with the highest traffic. Peak water marks are used to determine traffic bursts. If no value is provisioned for this attribute value of 5 minutes is assumed. Peak water mark is only measured if attribute collectionTimes in Collector/account is provisioned.') mscColPeakEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 279, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColPeakValue")) if mibBuilder.loadTexts: mscColPeakEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColPeakEntry.setDescription('An entry in the mscColPeakTable.') mscColPeakValue = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 279, 1, 1), Integer32().subtype(subtypeSpec=ValueRangeConstraint(1, 15))).setMaxAccess("readwrite") if mibBuilder.loadTexts: mscColPeakValue.setStatus('mandatory') if mibBuilder.loadTexts: mscColPeakValue.setDescription('This variable represents both the value and the index for the mscColPeakTable.') mscColPeakRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 279, 1, 2), RowStatus()).setMaxAccess("writeonly") if mibBuilder.loadTexts: mscColPeakRowStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColPeakRowStatus.setDescription('This variable is used to control the addition and deletion of individual values of the mscColPeakTable.') mscColSp = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2)) mscColSpRowStatusTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 1), ) if mibBuilder.loadTexts: mscColSpRowStatusTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpRowStatusTable.setDescription('This entry controls the addition and deletion of mscColSp components.') mscColSpRowStatusEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 1, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColSpIndex")) if mibBuilder.loadTexts: mscColSpRowStatusEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpRowStatusEntry.setDescription('A single entry in the table represents a single mscColSp component.') mscColSpRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 1, 1, 1), RowStatus()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpRowStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpRowStatus.setDescription('This variable is used as the basis for SNMP naming of mscColSp components. These components cannot be added nor deleted.') mscColSpComponentName = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 1, 1, 2), DisplayString()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpComponentName.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpComponentName.setDescription("This variable provides the component's string name for use with the ASCII Console Interface") mscColSpStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 1, 1, 4), StorageType()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpStorageType.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpStorageType.setDescription('This variable represents the storage type value for the mscColSp tables.') mscColSpIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 1, 1, 10), NonReplicated()) if mibBuilder.loadTexts: mscColSpIndex.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpIndex.setDescription('This variable represents the index for the mscColSp tables.') mscColSpProvTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 10), ) if mibBuilder.loadTexts: mscColSpProvTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpProvTable.setDescription('This group specifies all of the provisioning data for a DCS Spooler.') mscColSpProvEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 10, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColSpIndex")) if mibBuilder.loadTexts: mscColSpProvEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpProvEntry.setDescription('An entry in the mscColSpProvTable.') mscColSpSpooling = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 10, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1))).clone(namedValues=NamedValues(("off", 0), ("on", 1)))).setMaxAccess("readwrite") if mibBuilder.loadTexts: mscColSpSpooling.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpSpooling.setDescription('This attribute specifies whether or not this type of data is spooled to the disk. If set to off, it is roughly equivalent to Locking the Spooler (except this will survive processor restarts). The following defaults are used: - alarm: on - accounting: on - log: on - debug: off - scn: on - trap: off (see Note below) - stats: on Note that SNMP Traps cannot be spooled. A semantic check prevents the user from setting the value to on for the trap stream.') mscColSpMaximumNumberOfFiles = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 10, 1, 2), Unsigned32().subtype(subtypeSpec=ValueRangeConstraint(0, 200))).setMaxAccess("readwrite") if mibBuilder.loadTexts: mscColSpMaximumNumberOfFiles.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpMaximumNumberOfFiles.setDescription("This attribute specifies the maximum number of files that should be kept on the disk in the directory containing the closed files of this type. The value 0 is defined to mean 'unlimited'. A different default for each type of Spooler is defined as follows: - alarm: 30 - accounting: 200 - debug: 2 - log: 10 - scn: 10 - trap: 2 (this value is meaningless and is ignored) - stats: 200") mscColSpStateTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11), ) if mibBuilder.loadTexts: mscColSpStateTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpStateTable.setDescription('This group contains the three OSI State attributes and the six OSI Status attributes. The descriptions generically indicate what each attribute implies about the component. Note that not all the values and state combinations described here are supported by every component which uses this group. For component-specific information and the valid state combinations, refer to NTP 241- 7001-150, Passport Operations and Maintenance Guide.') mscColSpStateEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColSpIndex")) if mibBuilder.loadTexts: mscColSpStateEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpStateEntry.setDescription('An entry in the mscColSpStateTable.') mscColSpAdminState = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 1), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2))).clone(namedValues=NamedValues(("locked", 0), ("unlocked", 1), ("shuttingDown", 2))).clone('unlocked')).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpAdminState.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpAdminState.setDescription('This attribute indicates the OSI Administrative State of the component. The value locked indicates that the component is administratively prohibited from providing services for its users. A Lock or Lock - force command has been previously issued for this component. When the value is locked, the value of usageState must be idle. The value shuttingDown indicates that the component is administratively permitted to provide service to its existing users only. A Lock command was issued against the component and it is in the process of shutting down. The value unlocked indicates that the component is administratively permitted to provide services for its users. To enter this state, issue an Unlock command to this component. The OSI Status attributes, if supported by the component, may provide more details, qualifying the state of the component.') mscColSpOperationalState = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 2), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1))).clone(namedValues=NamedValues(("disabled", 0), ("enabled", 1))).clone('disabled')).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpOperationalState.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpOperationalState.setDescription('This attribute indicates the OSI Operational State of the component. The value enabled indicates that the component is available for operation. Note that if adminState is locked, it would still not be providing service. The value disabled indicates that the component is not available for operation. For example, something is wrong with the component itself, or with another component on which this one depends. If the value is disabled, the usageState must be idle. The OSI Status attributes, if supported by the component, may provide more details, qualifying the state of the component.') mscColSpUsageState = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 3), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2))).clone(namedValues=NamedValues(("idle", 0), ("active", 1), ("busy", 2))).clone('idle')).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpUsageState.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpUsageState.setDescription('This attribute indicates the OSI Usage State of the component. The value idle indicates that the component is not currently in use. The value active indicates that the component is in use and has spare capacity to provide for additional users. The value busy indicates that the component is in use and has no spare operating capacity for additional users at this time. The OSI Status attributes, if supported by the component, may provide more details, qualifying the state of the component.') mscColSpAvailabilityStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 4), OctetString().subtype(subtypeSpec=ValueSizeConstraint(2, 2)).setFixedLength(2)).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpAvailabilityStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpAvailabilityStatus.setDescription('If supported by the component, this attribute indicates the OSI Availability status of the component. Note that, even though it is defined as a multi-valued set, at most one value is shown to the user. When no values are in the set, this indicates that either the attribute is not supported or that none of the status conditions described below are present. The value inTest indicates that the resource is undergoing a test procedure. If adminState is locked or shuttingDown, the normal users are precluded from using the resource and controlStatus is reservedForTest. Tests that do not exclude additional users can be present in any operational or administrative state but the reservedForTest condition should not be present. The value failed indicates that the component has an internal fault that prevents it from operating. The operationalState is disabled. The value dependency indicates that the component cannot operate because some other resource on which it depends is unavailable. The operationalState is disabled. The value powerOff indicates the resource requires power to be applied and it is not powered on. The operationalState is disabled. The value offLine indicates the resource requires a routine operation (either manual, automatic, or both) to be performed to place it on-line and make it available for use. The operationalState is disabled. The value offDuty indicates the resource is inactive in accordance with a predetermined time schedule. In the absence of other disabling conditions, the operationalState is enabled or disabled. The value degraded indicates the service provided by the component is degraded in some way, such as in speed or operating capacity. However, the resource remains available for service. The operationalState is enabled. The value notInstalled indicates the resource is not present. The operationalState is disabled. The value logFull is not used. Description of bits: inTest(0) failed(1) powerOff(2) offLine(3) offDuty(4) dependency(5) degraded(6) notInstalled(7) logFull(8)') mscColSpProceduralStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 5), OctetString().subtype(subtypeSpec=ValueSizeConstraint(1, 1)).setFixedLength(1)).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpProceduralStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpProceduralStatus.setDescription("If supported by the component, this attribute indicates the OSI Procedural status of the component. Note that, even though it is defined as a multi-valued set, at most one value is shown to the user. When no values are in the set, this indicates that either the attribute is not supported or that none of the status conditions described below are present. The value initializationRequired indicates (for a resource which doesn't initialize autonomously) that initialization is required before it can perform its normal functions, and this procedure has not been initiated. The operationalState is disabled. The value notInitialized indicates (for a resource which does initialize autonomously) that initialization is required before it can perform its normal functions, and this procedure has not been initiated. The operationalState may be enabled or disabled. The value initializing indicates that initialization has been initiated but is not yet complete. The operationalState may be enabled or disabled. The value reporting indicates the resource has completed some processing operation and is notifying the results. The operationalState is enabled. The value terminating indicates the component is in a termination phase. If the resource doesn't reinitialize autonomously, operationalState is disabled; otherwise it is enabled or disabled. Description of bits: initializationRequired(0) notInitialized(1) initializing(2) reporting(3) terminating(4)") mscColSpControlStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 6), OctetString().subtype(subtypeSpec=ValueSizeConstraint(1, 1)).setFixedLength(1)).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpControlStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpControlStatus.setDescription('If supported by the component, this attribute indicates the OSI Control status of the component. Note that, even though it is defined as a multi-valued set, at most one value is shown to the user. When no values are in the set, this indicates that either the attribute is not supported or that none of the status conditions described below are present. The value subjectToTest indicates the resource is available but tests may be conducted simultaneously at unpredictable times, which may cause it to exhibit unusual characteristics. The value partOfServicesLocked indicates that part of the service is restricted from users of a resource. The adminState is unlocked. The value reservedForTest indicates that the component is administratively unavailable because it is undergoing a test procedure. The adminState is locked. The value suspended indicates that the service has been administratively suspended. Description of bits: subjectToTest(0) partOfServicesLocked(1) reservedForTest(2) suspended(3)') mscColSpAlarmStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 7), OctetString().subtype(subtypeSpec=ValueSizeConstraint(1, 1)).setFixedLength(1)).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpAlarmStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpAlarmStatus.setDescription('If supported by the component, this attribute indicates the OSI Alarm status of the component. Note that, even though it is defined as a multi-valued set, at most one value is shown to the user. When no values are in the set, this indicates that either the attribute is not supported or that none of the status conditions described below are present. The value underRepair indicates the component is currently being repaired. The operationalState is enabled or disabled. The value critical indicates one or more critical alarms are outstanding against the component. Other, less severe, alarms may also be outstanding. The operationalState is enabled or disabled. The value major indicates one or more major alarms are outstanding against the component. Other, less severe, alarms may also be outstanding. The operationalState is enabled or disabled. The value minor indicates one or more minor alarms are outstanding against the component. Other, less severe, alarms may also be outstanding. The operationalState is enabled or disabled. The value alarmOutstanding generically indicates that an alarm of some severity is outstanding against the component. Description of bits: underRepair(0) critical(1) major(2) minor(3) alarmOutstanding(4)') mscColSpStandbyStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 8), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1, 2, 15))).clone(namedValues=NamedValues(("hotStandby", 0), ("coldStandby", 1), ("providingService", 2), ("notSet", 15))).clone('notSet')).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpStandbyStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpStandbyStatus.setDescription('If supported by the component, this attribute indicates the OSI Standby status of the component. The value notSet indicates that either the attribute is not supported or that none of the status conditions described below are present. Note that this is a non-standard value, used because the original specification indicated this attribute was set-valued and thus, did not provide a value to indicate that none of the other three are applicable. The value hotStandby indicates that the resource is not providing service but will be immediately able to take over the role of the resource to be backed up, without initialization activity, and containing the same information as the resource to be backed up. The value coldStandby indicates the resource is a backup for another resource but will not be immediately able to take over the role of the backed up resource and will require some initialization activity. The value providingService indicates that this component, as a backup resource, is currently backing up another resource.') mscColSpUnknownStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 11, 1, 9), Integer32().subtype(subtypeSpec=ConstraintsUnion(SingleValueConstraint(0, 1))).clone(namedValues=NamedValues(("false", 0), ("true", 1))).clone('false')).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpUnknownStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpUnknownStatus.setDescription('This attribute indicates the OSI Unknown status of the component. The value false indicates that all of the other OSI State and Status attribute values can be considered accurate. The value true indicates that the actual state of the component is not known for sure.') mscColSpOperTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 12), ) if mibBuilder.loadTexts: mscColSpOperTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpOperTable.setDescription('This group contains the operational attributes specific to a DCS Spooler.') mscColSpOperEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 12, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColSpIndex")) if mibBuilder.loadTexts: mscColSpOperEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpOperEntry.setDescription('An entry in the mscColSpOperTable.') mscColSpSpoolingFileName = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 12, 1, 1), AsciiString().subtype(subtypeSpec=ValueSizeConstraint(0, 128))).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpSpoolingFileName.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpSpoolingFileName.setDescription('When spooling is on, this attribute contains the name of the open file into which data is currently being spooled. When spooling is off, the value of this attribute is the empty string.') mscColSpStatsTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 13), ) if mibBuilder.loadTexts: mscColSpStatsTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpStatsTable.setDescription('This group specifies the statistics operational attributes of the DCS Collector, Agent and Spooler components.') mscColSpStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 13, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColSpIndex")) if mibBuilder.loadTexts: mscColSpStatsEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpStatsEntry.setDescription('An entry in the mscColSpStatsTable.') mscColSpCurrentQueueSize = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 13, 1, 1), Gauge32().subtype(subtypeSpec=ValueRangeConstraint(0, 4294967295))).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpCurrentQueueSize.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpCurrentQueueSize.setDescription('This gauge contains the current number of records held by this DCS component.') mscColSpRecordsRx = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 13, 1, 2), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpRecordsRx.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpRecordsRx.setDescription('This counter contains the cumulative number of records received by a DCS component, from applications which send data to it, since the processor last restarted. This counter wraps to 0 when the maximum value is exceeded.') mscColSpRecordsDiscarded = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 2, 13, 1, 3), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColSpRecordsDiscarded.setStatus('mandatory') if mibBuilder.loadTexts: mscColSpRecordsDiscarded.setDescription('This is the cumulative number of records discarded by this DCS component since the processor last restarted. This counter wraps to 0 when the maximum value is exceeded.') mscColAg = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3)) mscColAgRowStatusTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 1), ) if mibBuilder.loadTexts: mscColAgRowStatusTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgRowStatusTable.setDescription('*** THIS TABLE CURRENTLY NOT IMPLEMENTED *** This entry controls the addition and deletion of mscColAg components.') mscColAgRowStatusEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 1, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColAgIndex")) if mibBuilder.loadTexts: mscColAgRowStatusEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgRowStatusEntry.setDescription('A single entry in the table represents a single mscColAg component.') mscColAgRowStatus = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 1, 1, 1), RowStatus()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgRowStatus.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgRowStatus.setDescription('This variable is used as the basis for SNMP naming of mscColAg components. These components cannot be added nor deleted.') mscColAgComponentName = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 1, 1, 2), DisplayString()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgComponentName.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgComponentName.setDescription("This variable provides the component's string name for use with the ASCII Console Interface") mscColAgStorageType = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 1, 1, 4), StorageType()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgStorageType.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgStorageType.setDescription('This variable represents the storage type value for the mscColAg tables.') mscColAgIndex = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 1, 1, 10), Integer32().subtype(subtypeSpec=ValueRangeConstraint(0, 15))) if mibBuilder.loadTexts: mscColAgIndex.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgIndex.setDescription('This variable represents the index for the mscColAg tables.') mscColAgStatsTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 10), ) if mibBuilder.loadTexts: mscColAgStatsTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgStatsTable.setDescription('*** THIS TABLE CURRENTLY NOT IMPLEMENTED *** This group specifies the statistics operational attributes of the DCS Collector, Agent and Spooler components.') mscColAgStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 10, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColAgIndex")) if mibBuilder.loadTexts: mscColAgStatsEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgStatsEntry.setDescription('An entry in the mscColAgStatsTable.') mscColAgCurrentQueueSize = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 10, 1, 1), Gauge32().subtype(subtypeSpec=ValueRangeConstraint(0, 4294967295))).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgCurrentQueueSize.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgCurrentQueueSize.setDescription('This gauge contains the current number of records held by this DCS component.') mscColAgRecordsRx = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 10, 1, 2), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgRecordsRx.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgRecordsRx.setDescription('This counter contains the cumulative number of records received by a DCS component, from applications which send data to it, since the processor last restarted. This counter wraps to 0 when the maximum value is exceeded.') mscColAgRecordsDiscarded = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 10, 1, 3), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgRecordsDiscarded.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgRecordsDiscarded.setDescription('This is the cumulative number of records discarded by this DCS component since the processor last restarted. This counter wraps to 0 when the maximum value is exceeded.') mscColAgAgentStatsTable = MibTable((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 11), ) if mibBuilder.loadTexts: mscColAgAgentStatsTable.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgAgentStatsTable.setDescription('*** THIS TABLE CURRENTLY NOT IMPLEMENTED *** This group contains the statistical attributes specific to the DCS Agent components.') mscColAgAgentStatsEntry = MibTableRow((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 11, 1), ).setIndexNames((0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColIndex"), (0, "Nortel-MsCarrier-MscPassport-DataCollectionMIB", "mscColAgIndex")) if mibBuilder.loadTexts: mscColAgAgentStatsEntry.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgAgentStatsEntry.setDescription('An entry in the mscColAgAgentStatsTable.') mscColAgRecordsNotGenerated = MibTableColumn((1, 3, 6, 1, 4, 1, 562, 36, 2, 1, 21, 3, 11, 1, 1), Counter32()).setMaxAccess("readonly") if mibBuilder.loadTexts: mscColAgRecordsNotGenerated.setStatus('mandatory') if mibBuilder.loadTexts: mscColAgRecordsNotGenerated.setDescription('This attribute counts the records of a particular event type on this Card which could not be generated by some application due to some problem such as insufficient resources. One cannot tell exactly which event could not be generated, nor which application instance tried to generate it, but when this count increases, it is an indicator that some re-engineering may be required and will provide some idea as to why a record is missing. This counter wraps to 0 when the maximum value is exceeded.') dataCollectionGroup = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 1)) dataCollectionGroupCA = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 1, 1)) dataCollectionGroupCA02 = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 1, 1, 3)) dataCollectionGroupCA02A = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 1, 1, 3, 2)) dataCollectionCapabilities = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 3)) dataCollectionCapabilitiesCA = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 3, 1)) dataCollectionCapabilitiesCA02 = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 3, 1, 3)) dataCollectionCapabilitiesCA02A = MibIdentifier((1, 3, 6, 1, 4, 1, 562, 36, 2, 2, 14, 3, 1, 3, 2)) mibBuilder.exportSymbols("Nortel-MsCarrier-MscPassport-DataCollectionMIB", mscColSpComponentName=mscColSpComponentName, dataCollectionCapabilitiesCA02=dataCollectionCapabilitiesCA02, mscColAgCurrentQueueSize=mscColAgCurrentQueueSize, mscColProvEntry=mscColProvEntry, mscColAgRowStatus=mscColAgRowStatus, mscColTimesRowStatus=mscColTimesRowStatus, mscColRowStatusTable=mscColRowStatusTable, mscColStorageType=mscColStorageType, mscColSpStorageType=mscColSpStorageType, mscColSpCurrentQueueSize=mscColSpCurrentQueueSize, mscColSpRowStatusEntry=mscColSpRowStatusEntry, mscColSpRowStatusTable=mscColSpRowStatusTable, mscColStatsEntry=mscColStatsEntry, mscColProvTable=mscColProvTable, mscColRecordsDiscarded=mscColRecordsDiscarded, mscColTimesValue=mscColTimesValue, mscColPeakRowStatus=mscColPeakRowStatus, mscColSpSpoolingFileName=mscColSpSpoolingFileName, mscColRecordsRx=mscColRecordsRx, mscColSpSpooling=mscColSpSpooling, mscColAgStatsTable=mscColAgStatsTable, dataCollectionCapabilitiesCA=dataCollectionCapabilitiesCA, mscColLastEntry=mscColLastEntry, mscColSpRowStatus=mscColSpRowStatus, dataCollectionGroupCA02=dataCollectionGroupCA02, mscColAg=mscColAg, mscColAgentQueueSize=mscColAgentQueueSize, mscColAgComponentName=mscColAgComponentName, mscColAgAgentStatsTable=mscColAgAgentStatsTable, mscColSpStateTable=mscColSpStateTable, mscColSpMaximumNumberOfFiles=mscColSpMaximumNumberOfFiles, mscColSpStatsTable=mscColSpStatsTable, mscColPeakValue=mscColPeakValue, mscColSpOperEntry=mscColSpOperEntry, mscColAgIndex=mscColAgIndex, mscColSpProceduralStatus=mscColSpProceduralStatus, dataCollectionMIB=dataCollectionMIB, dataCollectionGroupCA=dataCollectionGroupCA, mscColSpAvailabilityStatus=mscColSpAvailabilityStatus, mscColTimesTable=mscColTimesTable, mscColSpRecordsRx=mscColSpRecordsRx, mscColRowStatusEntry=mscColRowStatusEntry, mscColSpProvEntry=mscColSpProvEntry, dataCollectionCapabilities=dataCollectionCapabilities, mscColSpIndex=mscColSpIndex, mscColIndex=mscColIndex, mscColSpOperationalState=mscColSpOperationalState, mscColSpStateEntry=mscColSpStateEntry, mscColLastTable=mscColLastTable, mscColAgRecordsRx=mscColAgRecordsRx, mscColAgRowStatusTable=mscColAgRowStatusTable, mscColSp=mscColSp, mscColSpUnknownStatus=mscColSpUnknownStatus, mscColAgStatsEntry=mscColAgStatsEntry, mscColLastValue=mscColLastValue, mscColSpStandbyStatus=mscColSpStandbyStatus, dataCollectionGroup=dataCollectionGroup, mscColAgRowStatusEntry=mscColAgRowStatusEntry, mscColStatsTable=mscColStatsTable, mscColSpProvTable=mscColSpProvTable, mscColAgAgentStatsEntry=mscColAgAgentStatsEntry, mscColSpAdminState=mscColSpAdminState, mscColComponentName=mscColComponentName, mscColCurrentQueueSize=mscColCurrentQueueSize, mscColPeakEntry=mscColPeakEntry, mscColAgRecordsDiscarded=mscColAgRecordsDiscarded, mscColRowStatus=mscColRowStatus, mscColPeakTable=mscColPeakTable, mscColAgRecordsNotGenerated=mscColAgRecordsNotGenerated, dataCollectionCapabilitiesCA02A=dataCollectionCapabilitiesCA02A, mscCol=mscCol, mscColSpStatsEntry=mscColSpStatsEntry, mscColSpRecordsDiscarded=mscColSpRecordsDiscarded, mscColTimesEntry=mscColTimesEntry, mscColSpControlStatus=mscColSpControlStatus, mscColSpUsageState=mscColSpUsageState, dataCollectionGroupCA02A=dataCollectionGroupCA02A, mscColAgStorageType=mscColAgStorageType, mscColSpAlarmStatus=mscColSpAlarmStatus, mscColSpOperTable=mscColSpOperTable)

191.15812

3,370

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null

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3

6b1986265c356937240c8f049e4c27f556e3ad32

203

py

Python

python_web_framework_project_defense/python_web_framework_project_defense/extended_user_auth/apps.py

Xamaneone/Django-Projects

4fac8659680a6448bb55bce008bfd0eac1ad1f6d

[ "MIT" ]

null

python_web_framework_project_defense/python_web_framework_project_defense/extended_user_auth/apps.py

Xamaneone/Django-Projects

4fac8659680a6448bb55bce008bfd0eac1ad1f6d

[ "MIT" ]

null

python_web_framework_project_defense/python_web_framework_project_defense/extended_user_auth/apps.py

Xamaneone/Django-Projects

4fac8659680a6448bb55bce008bfd0eac1ad1f6d

[ "MIT" ]

null

from django.apps import AppConfig class ExtendedUserAuthConfig(AppConfig): default_auto_field = 'django.db.models.BigAutoField' name = 'python_web_framework_project_defense.extended_user_auth'

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68

0.82266

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203

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1

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0

1

0

1

null

0

3

6b2789562eb8efddec5ec7449dee11fe69846fac

1,257

py

Python

cloud_notes/urls.py

kiwiheretic/logos-v2

22739221a6d431322c809b7e17aba54f37eb9617

[ "Apache-2.0" ]

4

2015-02-20T08:11:59.000Z

2019-05-15T23:48:11.000Z

cloud_notes/urls.py

kiwiheretic/logos-v2

22739221a6d431322c809b7e17aba54f37eb9617

[ "Apache-2.0" ]

58

2015-01-11T02:10:09.000Z

2022-03-20T01:20:15.000Z

cloud_notes/urls.py

kiwiheretic/logos-v2

22739221a6d431322c809b7e17aba54f37eb9617

[ "Apache-2.0" ]

1

2016-06-15T00:49:44.000Z

# urls.py from __future__ import absolute_import from django.conf.urls import include, url from haystack.generic_views import SearchView from haystack.forms import SearchForm from .views import MySearchView import cloud_notes.views # required to set an app name to resolve 'url' in templates with namespacing app_name = "cloud_notes" urlpatterns = [ url(r'^$', cloud_notes.views.list), url(r'^new/', cloud_notes.views.new_note), url(r'^preview/(\d+)', cloud_notes.views.preview), url(r'^edit/(\d+)', cloud_notes.views.edit_note), url(r'^trash/(\d+)', cloud_notes.views.trash_note), url(r'^empty_trash/', cloud_notes.views.empty_trash), url(r'^delete/(\d+)', cloud_notes.views.delete_note), url(r'^upload/', cloud_notes.views.upload_note), url(r'^export/', cloud_notes.views.export), url(r'^export_all/', cloud_notes.views.export_all), url(r'^import/', cloud_notes.views.import_file), url(r'^import_all/', cloud_notes.views.import_all), url(r'^folders/', cloud_notes.views.folders), url(r'^hash_tags/', cloud_notes.views.hash_tags), url(r'^download/(\d+)', cloud_notes.views.download), url(r'^search/', cloud_notes.views.MySearchView.as_view(form_class = SearchForm), name='search_view'), ]

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0.32

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1

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null

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1

0

3

6b34b62ff9176d754e62eb3c435d235886456de0

224

py

Python

sync_tests/test_upload.py

Tara-X/mirror-sync

98b86c65a389682df8500085c15ef57dc5309569

[ "MIT" ]

null

sync_tests/test_upload.py

Tara-X/mirror-sync

98b86c65a389682df8500085c15ef57dc5309569

[ "MIT" ]

1

2021-06-01T22:06:38.000Z

sync_tests/test_upload.py

Tara-X/mirror-sync

98b86c65a389682df8500085c15ef57dc5309569

[ "MIT" ]

null

# -*- coding:utf-8 -*- import sys import unittest class TestUpload(unittest.TestCase): def test_upload(self): pass def test_remove(self): pass if __name__ == '__main__': unittest.main()

13.176471

36

0.616071

26

224

4.923077

0.692308

0.109375

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0.006061

0.263393

224

16

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0.769697

0.089286

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1

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null

0

null

0

1

0

1

0

3

6b36941c3ad4d3977e550da048bd026bd39e5196

302

py

Python

venv/Lib/site-packages/pybrain3/rl/environments/twoplayergames/capturegameplayers/randomplayer.py

ishatserka/MachineLearningAndDataAnalysisCoursera

e82e772df2f4aec162cb34ac6127df10d14a625a

[ "MIT" ]

null

venv/Lib/site-packages/pybrain3/rl/environments/twoplayergames/capturegameplayers/randomplayer.py

ishatserka/MachineLearningAndDataAnalysisCoursera

e82e772df2f4aec162cb34ac6127df10d14a625a

[ "MIT" ]

null

venv/Lib/site-packages/pybrain3/rl/environments/twoplayergames/capturegameplayers/randomplayer.py

ishatserka/MachineLearningAndDataAnalysisCoursera

e82e772df2f4aec162cb34ac6127df10d14a625a

[ "MIT" ]

null

__author__ = 'Tom Schaul, tom@idsia.ch' from random import choice from .captureplayer import CapturePlayer class RandomCapturePlayer(CapturePlayer): """ do random moves in the capture game""" def getAction(self): return [self.color, choice(self.game.getLegals(self.color))]

25.166667

68

0.715232

36

302

5.888889

0.666667

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0.18543

302

12

68

25.166667

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0.333333

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0.833333

0

null

0

null

0

1

0

3

6b44f8e8ae27a08bdbd449c05fa181aea67c9352

3,241

py

Python

storeAdjust/serializer.py

FreeGodCode/store

1ea1d6f0d6030fb58bce9a4e2d428342a0c3ad19

[ "MIT" ]

null

storeAdjust/serializer.py

FreeGodCode/store

1ea1d6f0d6030fb58bce9a4e2d428342a0c3ad19

[ "MIT" ]

1

2021-03-05T15:00:38.000Z

storeAdjust/serializer.py

FreeGodCode/store

1ea1d6f0d6030fb58bce9a4e2d428342a0c3ad19

[ "MIT" ]

null

from rest_framework import serializers from . import models class TransferRequestSerializer(serializers.ModelSerializer): org_name = serializers.CharField(source='organization.org_name') class Meta: model = models.TransferRequest fields = ( 'id', 'str_identify', 'org_name', 'str_to_house', 'str_from_house', 'str_date', 'str_department', 'str_status','str_creator', 'str_creator_identify', 'str_created_at' ) class TransferRequestDetailSerializer(serializers.ModelSerializer): str_identify = serializers.CharField(source='transfer_request.str_identify') trd_identify = serializers.CharField(source='material.material_identify') trd_name = serializers.CharField(source='material.material_name') trd_specification = serializers.CharField(source='material.material_specification') trd_model = serializers.CharField(source='material.material_model') trd_measure = serializers.CharField(source='material.measure_name') class Meta: model = models.TransferRequestDetail fields = ( 'id', 'str_identify', 'trd_identify', 'trd_name', 'trd_specification', 'trd_model', 'trd_measure', 'trd_num', 'trd_present_num', 'trd_used', 'trd_remarks' ) class TransferRequestDetailToTransferDetailSerializer(serializers.ModelSerializer): str_identify = serializers.CharField(source='transfer_request.str_identify') td_identify = serializers.CharField(source='material.material_identify') td_name = serializers.CharField(source='material.material_name') td_specification = serializers.CharField(source='material.material_specification') td_model = serializers.CharField(source='material.material_model') td_measure = serializers.CharField(source='material.measure_name') td_apply_num = serializers.CharField(source='trd_num') class Meta: model = models.TransferRequestDetail fields = ( 'id', 'str_identify', 'td_identify', 'td_name', 'td_specification', 'td_model', 'td_measure', 'td_apply_num' ) class TransferSerializer(serializers.ModelSerializer): org_name = serializers.CharField(source='organization.org_name') class Meta: model = models.Transfer fields = ( 'id', 'st_identify', 'org_name', 'st_to_house', 'st_from_house', 'st_date', 'st_status', 'st_creator', 'st_creator_identify', 'st_created_at' ) class TransferDetailSerializer(serializers.ModelSerializer): st_identify = serializers.CharField(source='transfer.st_identify') td_identify = serializers.CharField(source='material.material_identify') td_name = serializers.CharField(source='material.material_name') td_specification = serializers.CharField(source='material.material_specification') td_model = serializers.CharField(source='material.material_model') td_measure = serializers.CharField(source='material.measure_name') class Meta: model = models.TransferDetail fields = ( 'id', 'str_identify', 'st_identify', 'td_identify', 'td_name', 'td_specification', 'td_model', 'td_measure', 'td_apply_num', 'td_real_num ', 'td_present_num', 'td_remarks' )

45.013889

120

0.724468

340

3,241

6.594118

0.144118

0.187333

0.243533

0.227475

0.689563

0.67083

0.569135

0.5281

0

0.161678

3,241

72

121

45.013889

0.825175

0

0.45614

0

0.320481

0.144664

0

1

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false

0

0.035088

0

0.578947

0

null

0

1

0

null

0

1

0

3

860f15449ffd7b916eb81156f97cf4a7427d9bfc

120

py

Python

gym_antnest/__init__.py

unoti/aigym-antnest

6dfcb2ddc2118edd64ba8b474510f2a20a67d6f9

[ "MIT" ]

null

gym_antnest/__init__.py

unoti/aigym-antnest

6dfcb2ddc2118edd64ba8b474510f2a20a67d6f9

[ "MIT" ]

null

gym_antnest/__init__.py

unoti/aigym-antnest

6dfcb2ddc2118edd64ba8b474510f2a20a67d6f9

[ "MIT" ]

null

from gym.envs.registration import register register( id='antnest-v0', entry_point='antnest.envs:AntNestEnv', )

17.142857

42

0.733333

15

120

5.8

0.8

0

0.009709

0.141667

120

6

43

20

0.834951

0

0.275

0.191667

0

1

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true

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0.2

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0.2

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1

0

null

0

1

0

null

0

1

0

3

8612a7432e2a2ecf2a7b2210ba9155777f131c66

473

py

Python

src/visitpy/visit_utils/src/builtin/__init__.py

whophil/visit

4fd83212e20db1177916110ba40eeec6f41f8435

[ "BSD-3-Clause" ]

null

src/visitpy/visit_utils/src/builtin/__init__.py

whophil/visit

4fd83212e20db1177916110ba40eeec6f41f8435

[ "BSD-3-Clause" ]

null

src/visitpy/visit_utils/src/builtin/__init__.py

whophil/visit

4fd83212e20db1177916110ba40eeec6f41f8435

[ "BSD-3-Clause" ]

null

# Copyright (c) Lawrence Livermore National Security, LLC and other VisIt # Project developers. See the top-level LICENSE file for dates and other # details. No copyright assignment is required to contribute to VisIt. """ file: __init__.py author: Cyrus Harrison <cyrush@llnl.gov> created: 7/6/2020 description: Init file for 'visit_utils.builtin' module. """ from .evalfuncs import * from .writescript import WriteScript from .convert2to3 import ConvertPy2to3

31.533333

73

0.769556

64

473

5.609375

0.765625

0.044568

0

0.025063

0.156448

473

15

74

31.533333

0.874687

0.744186

0

1

0

true

0

1

0

1

0

null

0

null

0

1

0

1

0

1

0

3

862b954f750bb811af31e158371b5f4caeac3f34

340

py

Python

jade2/rosetta_jade/flag_util.py

RosettaCommons/jade2

40affc7c4e0f1f6ee07030e72de284e3484946e7

[ "BSD-3-Clause" ]

1

2019-12-23T21:52:23.000Z

jade2/rosetta_jade/flag_util.py

RosettaCommons/jade2

40affc7c4e0f1f6ee07030e72de284e3484946e7

[ "BSD-3-Clause" ]

null

jade2/rosetta_jade/flag_util.py

RosettaCommons/jade2

40affc7c4e0f1f6ee07030e72de284e3484946e7

[ "BSD-3-Clause" ]

2

2021-11-13T01:34:15.000Z

2021-11-13T01:34:34.000Z

from jade2.basic.path import * def get_common_flags_string_for_init(flags_name = "common_flags.flags"): """ Get a string of common flags as specified in the database. :return: str """ return " ".join([ line.strip() for line in open(get_rosetta_flags_path()+'/'+flags_name, 'r') if line and not line.startswith('#')])

30.909091

136

0.685294

51

340

4.352941

0.627451

0.148649

0

0.003571

0.176471

340

10

137

34

0.789286

0.208824

0

0.088353

0

1

0.333333

false

0

0.333333

0

1

0

null

0

null

0

1

0

1

0

1

0

3

86378030ffb7a008ace921889a0f6c81d8965897

1,565

py

Python

future/touchpoint.py

alpinedatalabs/python-alpine-api

2f74e4eeb7cb6d2b4f2d73db90e8c4afc552d1e7

[ "MIT" ]

null

future/touchpoint.py

alpinedatalabs/python-alpine-api

2f74e4eeb7cb6d2b4f2d73db90e8c4afc552d1e7

[ "MIT" ]

8

2017-03-07T01:23:22.000Z

2019-10-24T22:45:46.000Z

future/touchpoint.py

alpinedatalabs/python-alpine-api

2f74e4eeb7cb6d2b4f2d73db90e8c4afc552d1e7

[ "MIT" ]

3

2017-03-13T11:15:19.000Z

2019-03-24T21:47:05.000Z

from api.exception import * from api.alpineobject import AlpineObject class TouchPoint(AlpineObject): def __init__(self, base_url, session, token): super(TouchPoint, self).__init__(base_url, session, token) def add_touchpoint(self, touchpoint_name, workfile_id, workspace_id, touchpoint_description): """ Does nothing :param touchpoint_name: :param workfile_id: :param workspace_id: :param touchpoint_description: :return: """ pass def delete_touchpoint(self, touchpoint_name, workspace_id): """ Does nothing :param touchpoint_name: :param workspace_id: :return: """ pass def publish_touchpoint(self, workspace_id, touchpoint_name): pass def unpublish_touchpoint(self, workspace_id, touchpoint_name): pass def run_touchpoint(self, workspace_id, touchpoint_name, output_table, parameter_list=None): pass def stop_touchpoint(self, workspace_id, touchpoint_name): pass def get_touchpoint_list(self, workspace_id=None): pass def get_touchpoint_info(self, touchpoint_name): pass def get_touchpoint_id(self, touchpoint_name): pass def add_touchpoint_parameter(self, workspace_id, touchpoint_name, variable_name, data_type, variable_label, variable_desc, options, required_val, use_default): pass def get_touchpoint_parameters(self, workspace_id, touchpoint_name): pass

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null

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0

1

0

1

0

3

8639bc81e6a1d5c69c20797cee962de7e7df13c0

1,155

py

Python

py2End/Components/container.py

FuhrerG/PythonAtspi-API

bde1f71cebaa270b6f540562b1896f5bd7ff17cb

[ "MIT" ]

null

py2End/Components/container.py

FuhrerG/PythonAtspi-API

bde1f71cebaa270b6f540562b1896f5bd7ff17cb

[ "MIT" ]

null

py2End/Components/container.py

FuhrerG/PythonAtspi-API

bde1f71cebaa270b6f540562b1896f5bd7ff17cb

[ "MIT" ]

null

from __future__ import annotations from component import * from typing import Dict, Any, List, Tuple from utils import * import gi gi.require_version('Atspi', '2.0') from gi.repository import Atspi class Container(E2eComponent): # Atributes # Constructor def __init__(self: Container, obj: Atspi.Object): super().__init__(obj) # Public Methods def get_childrens(self: Container) -> List[E2eComponent]: childrens = [self.component.get_child_at_index(i) for i in range(self.component.get_child_count())] return Utils.to_e2e_list(childrens) def get_childrens_number(self: Container) -> int: return len(self.get_childrens()) def get_descendants(self: Container) -> List[E2eComponent]: childrens = [] for obj in Utils.tree_walk(self.component): childrens.append(obj) return Utils.to_e2e_list(childrens) def get_descendants_number(self: Container) -> int: return len(self.get_descendants()) def is_parent_of(self: Container, child: E2eComponent) -> bool: return child.component.get_parent() == self.component

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1,155

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null

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null

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1

0

1

0

3

864de2366e0badfd5eaa5e2e35d4298c9984af96

386

py

Python

mriqc/classifier/__init__.py

erramuzpe/mriqc

03eb869b0966cf27fe85db88a970f8ab8640c9e9

[ "BSD-3-Clause" ]

1

2019-08-17T21:20:48.000Z

mriqc/classifier/__init__.py

erramuzpe/mriqc

03eb869b0966cf27fe85db88a970f8ab8640c9e9

[ "BSD-3-Clause" ]

null

mriqc/classifier/__init__.py

erramuzpe/mriqc

03eb869b0966cf27fe85db88a970f8ab8640c9e9

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # emacs: -*- mode: python; py-indent-offset: 4; indent-tabs-mode: nil -*- # vi: set ft=python sts=4 ts=4 sw=4 et: """ Using the classifier -------------------- .. toctree:: :maxdepth: 3 cv/base cv/data cv/helper Cross-validation in MRIQC ------------------------- .. toctree:: :maxdepth: 3 cv/experiments """

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386

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0

null

0

1

0

3

8652e9b06d7a64b3de9ec8c032f891de24bf0135

869

py

Python

fosslint/config.py

udoprog/fosslint

85a9d9d85c747afeee3bbe693a6aa2a021b42b6f

[ "Apache-2.0" ]

1

2016-09-30T13:52:01.000Z

fosslint/config.py

udoprog/fosslint

85a9d9d85c747afeee3bbe693a6aa2a021b42b6f

[ "Apache-2.0" ]

3

2016-09-29T22:10:45.000Z

2016-09-30T14:03:10.000Z

fosslint/config.py

udoprog/fosslint

85a9d9d85c747afeee3bbe693a6aa2a021b42b6f

[ "Apache-2.0" ]

null

import configparser BOOLEAN_TRUE = set(['true']) def unquote(string): """ Unqoute escape sequences in the given string. TODO: implement this """ return string class Config: def __init__(self, config): self.config = config def sections(self): return self.config.sections() def __getitem__(self, section): return Section(self.config[section]) class Section: def __init__(self, section): self.section = section def get(self, key): value = self.section.get(key) if value is None: return None if value.startswith('"') and value.endswith('"'): return unquote(value[1:-1]) return value def getboolean(self, key): value = self.get(key) if value is None: return None return value in BOOLEAN_TRUE

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null

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null

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1

0

1

0

1

0

3

867259bc377f0dc64ef6ea3a154fe7023103a89d

51,739

py

Python

src/sage/combinat/sf/sf.py

drvinceknight/sage

00199fb220aa173d8585b9e90654dafd3247d82d

[ "BSL-1.0" ]

2

2015-08-11T05:05:47.000Z

2019-05-15T17:27:25.000Z

src/sage/combinat/sf/sf.py

kaushik94/sage

00199fb220aa173d8585b9e90654dafd3247d82d

[ "BSL-1.0" ]

null

src/sage/combinat/sf/sf.py

kaushik94/sage

00199fb220aa173d8585b9e90654dafd3247d82d

[ "BSL-1.0" ]

1

2020-07-24T12:04:03.000Z

""" Symmetric functions, with their multiple realizations """ #***************************************************************************** # Copyright (C) 2007 Mike Hansen <mhansen@gmail.com> # 2009-2012 Jason Bandlow <jbandlow@gmail.com> # 2012 Anne Schilling <anne at math.ucdavis.edu> # 2009-2012 Nicolas M. Thiery <nthiery at users.sf.net> # 2012 Mike Zabrocki <mike.zabrocki@gmail.com> # # Distributed under the terms of the GNU General Public License (GPL) # # 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 for more details. # # The full text of the GPL is available at: # # http://www.gnu.org/licenses/ #***************************************************************************** from sage.structure.parent import Parent from sage.structure.unique_representation import UniqueRepresentation from sage.categories.all import Rings, GradedHopfAlgebras from sage.combinat.partition import Partitions from sage.combinat.free_module import CombinatorialFreeModule from sage.rings.rational_field import QQ import schur import monomial import powersum import elementary import homogeneous import hall_littlewood import jack import macdonald import llt class SymmetricFunctions(UniqueRepresentation, Parent): r""" The abstract algebra of commutative symmetric functions .. rubric:: Symmetric Functions in Sage .. MODULEAUTHOR:: Jason Bandlow, Anne Schilling, Nicolas M. Thiery, Mike Zabrocki This document is an introduction to working with symmetric function theory in Sage. It is not intended to be an introduction to the theory of symmetric functions ([MAC]_ and [STA]_, Chapter 7, are two excellent references.) The reader is also expected to be familiar with Sage. .. rubric:: The algebra of symmetric functions The algebra of symmetric functions is the unique free commutative graded connected algebra over the given ring, with one generator in each degree. It can also be thought of as the inverse limit (in the category of graded algebras) of the algebra of symmetric polynomials in `n` variables as `n \rightarrow \infty`. Sage allows us to construct the algebra of symmetric functions over any ring. We will use a base ring of rational numbers in these first examples:: sage: Sym = SymmetricFunctions(QQ) sage: Sym Symmetric Functions over Rational Field Sage knows certain categorical information about this algebra:: sage: Sym.category() Join of Category of hopf algebras over Rational Field and Category of graded algebras over Rational Field and Category of monoids with realizations and Category of coalgebras over Rational Field with realizations Notice that ``Sym`` is an *abstract* algebra. This reflects the fact that there are multiple natural bases. To work with specific elements, we need a *realization* of this algebra. In practice, this means we need to specify a basis. .. rubric:: An example basis - power sums Here is an example of how one might use the power sum realization:: sage: p = Sym.powersum() sage: p Symmetric Functions over Rational Field in the powersum basis ``p`` now represents the realization of the symmetric function algebra on the power sum basis. The basis itself is accessible through:: sage: p.basis() Lazy family (Term map from Partitions to Symmetric Functions over Rational Field in the powersum basis(i))_{i in Partitions} sage: p.basis().keys() Partitions This last line means that ``p.basis()`` is an association between the set of Partitions and the basis elements of the algebra ``p``. To construct a specific element one can therefore do:: sage: p.basis()[Partition([2,1,1])] p[2, 1, 1] As this is rather cumbersome, realizations of the symmetric function algebra allow for the following abuses of notation:: sage: p[Partition([2, 1, 1])] p[2, 1, 1] sage: p[[2, 1, 1]] p[2, 1, 1] sage: p[2, 1, 1] p[2, 1, 1] or even:: sage: p[(i for i in [2, 1, 1])] p[2, 1, 1] In the special case of the empty partition, due to a limitation in Python syntax, one cannot use:: sage: p[] # todo: not implemented Please use instead:: sage: p[[]] p[] .. note:: When elements are constructed using the ``p[something ]`` syntax , an error will be raised if the input cannot be interpreted as a partition. This is *not* the case when ``p.basis()`` is used:: sage: p['something'] Traceback (most recent call last): ... ValueError: ['s', 'o', 'm', 'e', 't', 'h', 'i', 'n', 'g'] is not an element of Partitions sage: p.basis()['something'] p'something' Elements of ``p`` are linear combinations of such compositions:: sage: p.an_element() 2*p[] + 2*p[1] + 3*p[2] .. rubric:: Algebra structure Algebraic combinations of basis elements can be entered in a natural way:: sage: p[2,1,1] + 2 * p[1] * (p[4] + p[2,1]) 3*p[2, 1, 1] + 2*p[4, 1] Let us explore the other operations of ``p``. We can ask for the mathematical properties of ``p``:: sage: p.categories() [Category of bases of Symmetric Functions over Rational Field, Category of graded hopf algebras with basis over Rational Field, ...] To start with, ``p`` is a graded algebra, the grading being induced by the size of the partitions. Due to this, the one is the basis element indexed by the empty partition:: sage: p.one() p[] The ``p`` basis is multiplicative; that is, multiplication is induced by linearity from the (nonincreasingly sorted) concatenation of partitions:: sage: p[3,1] * p[2,1] p[3, 2, 1, 1] sage: (p.one() + 2 * p[3,1]) * p[4, 2] p[4, 2] + 2*p[4, 3, 2, 1] .. rubric:: The classical bases In addition to the power sum basis, the other classical bases of the symmetric function algebra are the elementary, complete homogeneous, monomial, and Schur bases. These can be defined as follows:: sage: e = Sym.elementary() sage: h = Sym.homogeneous() sage: m = Sym.monomial() sage: s = Sym.schur() These can be defined all at once with the single command :: sage: Sym.inject_shorthands() doctest:...: RuntimeWarning: redefining global value `h` doctest:...: RuntimeWarning: redefining global value `s` doctest:...: RuntimeWarning: redefining global value `e` doctest:...: RuntimeWarning: redefining global value `m` doctest:...: RuntimeWarning: redefining global value `p` We can then do conversions from one basis to another:: sage: s(p[2,1]) -s[1, 1, 1] + s[3] sage: m(p[3]) m[3] sage: m(p[3,2]) m[3, 2] + m[5] For computations which mix bases, Sage will return a result with respect to a single (not necessarily predictable) basis:: sage: p[2] * s[2] - m[4] 1/2*p[2, 1, 1] + 1/2*p[2, 2] - p[4] sage: p( m[1] * ( e[3]*s[2] + 1 )) p[1] + 1/12*p[1, 1, 1, 1, 1, 1] - 1/6*p[2, 1, 1, 1, 1] - 1/4*p[2, 2, 1, 1] + 1/6*p[3, 1, 1, 1] + 1/6*p[3, 2, 1] The one for different bases such as the power sum and Schur function is the same:: sage: s.one() == p.one() True .. rubric:: Basic computations In this section, we explore some of the many methods that can be applied to an arbitrary symmetric function:: sage: f = s[2]^2; f s[2, 2] + s[3, 1] + s[4] For more methods than discussed here, create a symmetric function as above, and use ``f.<tab>``. .. _`Representation theory of the symmetric group`: .. rubric:: Representation theory of the symmetric group The Schur functions `s_\lambda` can also be interpreted as irreducible characters of the symmetric group `S_n`, where `n` is the size of the partition `\lambda`. Since the Schur functions of degree `n` form a basis of the symmetric functions of degree `n`, it follows that an arbitrary symmetric function (homogeneous of degree `n`) may be interpreted as a function on the symmetric group. In this interpretation the power sum symmetric function `p_\lambda` is the characteristic function of the conjugacy class with shape `\lambda`, multiplied by the order of the centralizer of an element. Hence the irreducible characters can be computed as follows:: sage: Sym = SymmetricFunctions(QQ) sage: s = Sym.schur() sage: p = Sym.power() sage: P = Partitions(5).list() sage: P = [P[i] for i in range(len(P)-1,-1,-1)] sage: M = matrix([[s[P[i]].scalar(p[P[j]]) for j in range(len(P))] for i in range(len(P))]) sage: M [ 1 -1 1 1 -1 -1 1] [ 4 -2 0 1 1 0 -1] [ 5 -1 1 -1 -1 1 0] [ 6 0 -2 0 0 0 1] [ 5 1 1 -1 1 -1 0] [ 4 2 0 1 -1 0 -1] [ 1 1 1 1 1 1 1] We can indeed check that this agrees with the character table of `S_5`:: sage: SymmetricGroup(5).character_table() == M True In this interpretation of symmetric functions as characters on the symmetric group, the multiplication and comultiplication are interpreted as induction (from `S_n\times S_m` to `S_{n+m}`) and restriction, respectively. The Schur functions can also be interpreted as characters of `GL_n`, see `Partitions and Schur functions`__. __ ../../../../thematic_tutorials/lie/lie_basics.html#partitions-and-schur-polynomials .. rubric:: The omega involution The `\omega` involution is the linear extension of the map which sends `e_\lambda` to `h_{\lambda}`:: sage: h(f) h[2, 2] sage: e(f.omega()) e[2, 2] .. rubric:: The Hall scalar product The Hall scalar product on the algebra of symmetric functions makes the Schur functions into an orthonormal basis:: sage: f.scalar(f) 3 .. rubric:: Skewing *Skewing* is the adjoint operation to multiplication with respect to this scalar product:: sage: f.skew_by(s[1]) 2*s[2, 1] + 2*s[3] In general, ``s[la].skew_by(s[mu])`` is the symmetric function typically denoted `s_{\lambda \setminus \mu}` or `s_{\lambda / \mu}`. .. rubric:: Expanding into variables We can expand a symmetric function into a symmetric polynomial in a specified number of variables:: sage: f.expand(2) x0^4 + 2*x0^3*x1 + 3*x0^2*x1^2 + 2*x0*x1^3 + x1^4 See the documentation for ``expand`` for more examples. .. rubric:: The Kronecker product As in the section on the `Representation theory of the symmetric group`_, a symmetric function may be considered as a class function on the symmetric group where the elements `p_\mu/z_\mu` are the indicators of a permutation having cycle structure `\mu`. The Kronecker product of two symmetric functions corresponds to the pointwise product of these class functions. Since the Schur functions are the irreducible characters of the symmetric group under this identification, the Kronecker product of two Schur functions corresponds to the internal tensor product of two irreducible symmetric group representations. Under this identification, the Kronecker product of `p_\mu/z_\mu` and `p_\nu/z_\nu` is `p_\mu/z_\mu` if `\mu=\nu`, and the result is equal to `0` otherwise. ``internal_product``, ``kronecker_product``, ``inner_tensor`` and ``itensor`` are different names for the same function. :: sage: f.kronecker_product(f) s[1, 1, 1, 1] + 3*s[2, 1, 1] + 4*s[2, 2] + 5*s[3, 1] + 3*s[4] .. rubric:: Plethysm The *plethysm* of symmetric functions is the operation corresponding to composition of representations of the general linear group. See [STA]_ Chapter 7, Appendix 2 for details. :: sage: s[2].plethysm(s[2]) s[2, 2] + s[4] Plethysm can also be written as a composition of functions:: sage: s[2]( s[2] ) s[2, 2] + s[4] If the coefficient ring contains degree 1 elements, these are handled properly by plethysm:: sage: R.<t> = QQ[]; s = SymmetricFunctions(R).schur() sage: s[2]( (1-t)*s[1] ) (t^2-t)*s[1, 1] + (-t+1)*s[2] See the documentation for ``plethysm`` for more information. .. rubric:: Inner plethysm The operation of inner plethysm ``f.inner_plethysm(g)`` models the composition of the `S_n` representation represented by `g` with the `GL_m` representation whose character is `f`. See the documentation of ``inner_plethysm``, [ST94]_ or [STA]_, exercise 7.74 solutions for more information:: sage: s = SymmetricFunctions(QQ).schur() sage: f = s[2]^2 sage: f.inner_plethysm(s[2]) s[2] .. rubric:: Hopf algebra structure The ring of symmetric functions is further endowed with a coalgebra structure. The coproduct is an algebra morphism, and therefore determined by its values on the generators; the power sum generators are primitive:: sage: p[1].coproduct() p[] # p[1] + p[1] # p[] sage: p[2].coproduct() p[] # p[2] + p[2] # p[] The coproduct, being cocommutative on the generators, is cocommutative everywhere:: sage: p[2, 1].coproduct() p[] # p[2, 1] + p[1] # p[2] + p[2] # p[1] + p[2, 1] # p[] This coproduct, along with the counit which sends every symmetric function to its `0`-th homogeneous component, makes the ring of symmetric functions into a graded connected bialgebra. It is known that every graded connected bialgebra has an antipode. For the ring of symmetric functions, the antipode can be characterized explicitly: The antipode is an anti-algebra morphism (thus an algebra morphism, since our algebra is commutative) which sends `p_{\lambda}` to `(-1)^{\mathrm{length}(\lambda)} p_{\lambda}` for every partition `\lambda`. Thus, in particular, it sends the generators on the ``p`` basis to their opposites:: sage: p[3].antipode() -p[3] sage: p[3,2,1].antipode() -p[3, 2, 1] The graded connected bialgebra of symmetric functions over a `\QQ`-algebra has a rather simply-understood structure: It is (isomorphic to) the symmetric algebra of its space of primitives (which is spanned by the power-sum symmetric functions). Here are further examples:: sage: f = s[2]^2 sage: f.antipode() s[1, 1, 1, 1] + s[2, 1, 1] + s[2, 2] sage: f.coproduct() s[] # s[2, 2] + s[] # s[3, 1] + s[] # s[4] + 2*s[1] # s[2, 1] + 2*s[1] # s[3] + s[1, 1] # s[1, 1] + s[1, 1] # s[2] + s[2] # s[1, 1] + 3*s[2] # s[2] + 2*s[2, 1] # s[1] + s[2, 2] # s[] + 2*s[3] # s[1] + s[3, 1] # s[] + s[4] # s[] sage: f.coproduct().apply_multilinear_morphism( lambda x,y: x*y.antipode() ) 0 .. rubric:: Transformations of symmetric functions There are many methods in Sage which make it easy to manipulate symmetric functions. For example, if we have some function which acts on partitions (say, conjugation), it is a simple matter to apply it to the support of a symmetric function. Here is an example:: sage: conj = lambda mu: mu.conjugate() sage: f = h[4] + 2*h[3,1] sage: f.map_support(conj) h[1, 1, 1, 1] + 2*h[2, 1, 1] We can also easily modify the coefficients:: sage: def foo(mu, coeff): return mu.conjugate(), -coeff sage: f.map_item(foo) -h[1, 1, 1, 1] - 2*h[2, 1, 1] See also ``map_coefficients``. There are also methods for building functions directly:: sage: s.sum_of_monomials(mu for mu in Partitions(3)) s[1, 1, 1] + s[2, 1] + s[3] sage: s.sum_of_monomials(Partitions(3)) s[1, 1, 1] + s[2, 1] + s[3] sage: s.sum_of_terms( (mu, mu[0]) for mu in Partitions(3)) s[1, 1, 1] + 2*s[2, 1] + 3*s[3] These are the preferred way to build elements within a program; the result will usually be faster than using :func:`sum`. It also guarantees that empty sums yields the zero of ``s`` (see also ``s.sum``). Note also that it is a good idea to use:: sage: s.one() s[] sage: s.zero() 0 instead of ``s(1)`` and ``s(0)`` within programs where speed is important, in order to prevent unnecessary coercions. .. rubric:: Different base rings Depending on the base ring, the different realizations of the symmetric function algebra may not span the same space:: sage: SZ = SymmetricFunctions(ZZ) sage: p = SZ.power(); s = SZ.schur() sage: p(s[1,1,1]) Traceback (most recent call last): ... TypeError: no conversion of this rational to integer Because of this, some functions may not behave as expected when working over the integers, even though they make mathematical sense:: sage: s[1,1,1].plethysm(s[1,1,1]) Traceback (most recent call last): ... TypeError: no conversion of this rational to integer It is possible to work over different base rings simultaneously:: sage: s = SymmetricFunctions(QQ).schur() sage: p = SymmetricFunctions(QQ).power() sage: sz = SymmetricFunctions(ZZ).schur(); sz._prefix = 'sz' sage: pz = SymmetricFunctions(ZZ).power(); pz._prefix = 'pz' sage: p(sz[1,1,1]) 1/6*p[1, 1, 1] - 1/2*p[2, 1] + 1/3*p[3] sage: sz( 1/6*p[1, 1, 1] - 1/2*p[2, 1] + 1/3*p[3] ) sz[1, 1, 1] As shown in this example, if you are working over multiple base rings simultaneously, it is a good idea to change the prefix in some cases, so that you can tell from the output which realization your result is in. Let us change the notation back for the remainder of this tutorial:: sage: sz._prefix = 's' sage: pz._prefix = 'p' One can also use the Sage standard renaming idiom to get shorter outputs:: sage: Sym = SymmetricFunctions(QQ) sage: Sym.rename("Sym") sage: Sym Sym sage: Sym.rename() And we name it back:: sage: Sym.rename("Symmetric Functions over Rational Field"); Sym Symmetric Functions over Rational Field .. rubric:: Other bases There are two additional basis of the symmetric functions which are not considered as classical bases: * forgotten basis * Witt basis The forgotten basis is the dual basis of the elementary symmetric functions basis with respect to the Hall scalar product. The Witt basis can be constructed by .. MATH:: \prod_{d=1}^{\infty} (1 - w_d t^d)^{-1} = \sum_{n=0}^{\infty} h_n t^n where `t` is a formal variable. There are further bases of the ring of symmetric functions, in general over fields with parameters such as `q` and `t`: * Hall-Littlewood bases * Jack bases * Macdonald bases * `k`-Schur functions We briefly demonstrate how to access these bases. For more information, see the documentation of the individual bases. The *Jack polynomials* can be obtained as:: sage: Sym = SymmetricFunctions(FractionField(QQ['t'])) sage: Jack = Sym.jack() sage: P = Jack.P(); J = Jack.J(); Q = Jack.Q() sage: J(P[2,1]) (1/(t+2))*JackJ[2, 1] The parameter `t` can be specialized as follows:: sage: Sym = SymmetricFunctions(QQ) sage: Jack = Sym.jack(t = 1) sage: P = Jack.P(); J = Jack.J(); Q = Jack.Q() sage: J(P[2,1]) 1/3*JackJ[2, 1] Similarly one can access the Hall-Littlewood and Macdonald polynomials, etc:: sage: Sym = SymmetricFunctions(FractionField(QQ['q','t'])) sage: Mcd = Sym.macdonald() sage: P = Mcd.P(); J = Mcd.J(); Q = Mcd.Q() sage: J(P[2,1]) (1/(-q*t^4+2*q*t^3-q*t^2+t^2-2*t+1))*McdJ[2, 1] .. rubric:: `k`-Schur functions The `k`-Schur functions live in the `k`-bounded subspace of the ring of symmetric functions. It is possible to compute in the `k`-bounded subspace directly:: sage: Sym = SymmetricFunctions(QQ) sage: ks = Sym.kschur(3,1) sage: f = ks[2,1]*ks[2,1]; f ks3[2, 2, 1, 1] + ks3[2, 2, 2] + ks3[3, 1, 1, 1] or to lift to the ring of symmetric functions:: sage: f.lift() s[2, 2, 1, 1] + s[2, 2, 2] + s[3, 1, 1, 1] + 2*s[3, 2, 1] + s[3, 3] + s[4, 1, 1] + s[4, 2] However, it is not always possible to convert a symmetric function to the `k`-bounded subspace:: sage: s = Sym.schur() sage: ks(s[2,1,1]) Traceback (most recent call last): ... ValueError: s[2, 1, 1] is not in the image The `k`-Schur functions are more generally defined with a parameter `t` and they are a basis of the subspace spanned by the Hall-Littlewood ``Qp`` symmetric functions indexed by partitions whose first part is less than or equal to `k`:: sage: Sym = SymmetricFunctions(QQ['t'].fraction_field()) sage: SymS3 = Sym.kBoundedSubspace(3) # default t='t' sage: ks = SymS3.kschur() sage: Qp = Sym.hall_littlewood().Qp() sage: ks(Qp[2,1,1,1]) ks3[2, 1, 1, 1] + (t^2+t)*ks3[2, 2, 1] + (t^3+t^2)*ks3[3, 1, 1] + t^4*ks3[3, 2] The subspace spanned by the `k`-Schur functions with a parameter `t` are not known to form a natural algebra. However it is known that the product of a `k`-Schur function and an `\ell`-Schur function is in the linear span of the `k+\ell`-Schur functions:: sage: ks(ks[2,1]*ks[1,1]) Traceback (most recent call last): ... ValueError: s[2, 1, 1, 1] + s[2, 2, 1] + s[3, 1, 1] + s[3, 2] is not in the image sage: ks[2,1]*ks[1,1] s[2, 1, 1, 1] + s[2, 2, 1] + s[3, 1, 1] + s[3, 2] sage: ks6 = Sym.kBoundedSubspace(6).kschur() sage: ks6(ks[3,1,1]*ks[3]) ks6[3, 3, 1, 1] + ks6[4, 2, 1, 1] + (t+1)*ks6[4, 3, 1] + t*ks6[4, 4] + ks6[5, 1, 1, 1] + ks6[5, 2, 1] + t*ks6[5, 3] + ks6[6, 1, 1] .. rubric:: dual `k`-Schur functions The dual space to the subspace spanned by the `k`-Schur functions is most naturally realized as a quotient of the ring of symmetric functions by an ideal. When `t=1` the ideal is generated by the monomial symmetric functions indexed by partitions whose first part is greater than `k`.:: sage: Sym = SymmetricFunctions(QQ) sage: SymQ3 = Sym.kBoundedQuotient(3,t=1) sage: km = SymQ3.kmonomial() sage: km[2,1]*km[2,1] 4*m3[2, 2, 1, 1] + 6*m3[2, 2, 2] + 2*m3[3, 2, 1] + 2*m3[3, 3] sage: F = SymQ3.affineSchur() sage: F[2,1]*F[2,1] 2*F3[1, 1, 1, 1, 1, 1] + 4*F3[2, 1, 1, 1, 1] + 4*F3[2, 2, 1, 1] + 4*F3[2, 2, 2] + 2*F3[3, 1, 1, 1] + 4*F3[3, 2, 1] + 2*F3[3, 3] When `t` is not equal to `1`, the subspace spanned by the `k`-Schur functions is realized as a quotient of the ring of symmetric functions by the ideal generated by the Hall-Littlewood symmetric functions in the P basis indexed by partitions with first part greater than `k`.:: sage: Sym = SymmetricFunctions(FractionField(QQ['t'])) sage: SymQ3 = Sym.kBoundedQuotient(3) sage: kHLP = SymQ3.kHallLittlewoodP() sage: kHLP[2,1]*kHLP[2,1] (t^2+2*t+1)*HLP3[2, 2, 1, 1] + (t^3+2*t^2+2*t+1)*HLP3[2, 2, 2] + (-t^4-t^3+t+1)*HLP3[3, 1, 1, 1] + (-t^2+t+2)*HLP3[3, 2, 1] + (t+1)*HLP3[3, 3] sage: HLP = Sym.hall_littlewood().P() sage: kHLP(HLP[3,1]) HLP3[3, 1] sage: kHLP(HLP[4]) 0 In this space, the basis which is dual to the `k`-Schur functions conjecturally expands positively in the `k`-bounded Hall-Littlewood functions and has positive structure coefficients.:: sage: dks = SymQ3.dual_k_Schur() sage: kHLP(dks[2,2]) (t^4+t^2)*HLP3[1, 1, 1, 1] + t*HLP3[2, 1, 1] + HLP3[2, 2] sage: dks[2,1]*dks[1,1] (t^2+t)*dks3[1, 1, 1, 1, 1] + (t+1)*dks3[2, 1, 1, 1] + (t+1)*dks3[2, 2, 1] + dks3[3, 1, 1] + dks3[3, 2] At `t=1` the `k`-bounded Hall-Littlewood basis is equal to the `k`-bounded monomial basis and the dual `k`-Schur elements are equal to the affine Schur basis. The `k`-bounded monomial basis and affine Schur functions are faster and should be used instead of the `k`-bounded Hall-Littlewood P basis and dual `k`-Schur functions when `t=1`.:: sage: SymQ3 = Sym.kBoundedQuotient(3,t=1) sage: dks = SymQ3.dual_k_Schur() sage: F = SymQ3.affineSchur() sage: F[3,1]==dks[3,1] True .. rubric:: Implementing new bases .. todo:: to be described .. rubric:: Acknowledgements The design is heavily inspired from the implementation of symmetric functions in MuPAD-Combinat (see [HT04]_ and [FD06]_). REFERENCES: .. [FD06] Francois Descouens, Making research on symmetric functions using MuPAD-Combinat. In Andres Iglesias and Nobuki Takayama, editors, 2nd International Congress on Mathematical Software (ICMS'06), volume 4151 of LNCS, pages 407-418, Castro Urdiales, Spain, September 2006. Springer-Verlag. :arXiv:`0806.1873` .. [HT04] Florent Hivert and Nicolas M. Thiery, MuPAD-Combinat, an open-source package for research in algebraic combinatorics. Sem. Lothar. Combin., 51 :Art. B51z, 70 pp. (electronic), 2004. http://mupad-combinat.sf.net/. .. [MAC] Ian Macdonald, Symmetric Functions and Orthogonal Polynomials, Second edition. With contributions by A. Zelevinsky. Oxford Mathematical Monographs. Oxford Science Publications. The Clarendon Press, Oxford University Press, New York, 1995. x+475 pp. ISBN: 0-19-853489-2 .. [STA] Richard Stanley, Enumerative combinatorics. Vol. 2. With a foreword by Gian-Carlo Rota and appendix 1 by Sergey Fomin. Cambridge Studies in Advanced Mathematics, 62. Cambridge University Press, Cambridge, 1999. xii+581 pp. ISBN: 0-521-56069-1; 0-521-78987-7 .. [ST94] Scharf, Thomas, Thibon, Jean-Yves, A Hopf-algebra approach to inner plethysm. Adv. Math. 104 (1994), no. 1, 30-58. :doi:`10.1006/aima.1994.1019` .. rubric:: Further tests TESTS:: sage: Sym = SymmetricFunctions(QQ) sage: Sym Symmetric Functions over Rational Field sage: h = Sym.h(); e = Sym.e(); s = Sym.s(); m = Sym.m(); p = Sym.p() sage: ( ( h[2,1] * ( 1 + 3 * h[2,1]) ) + s[2]. antipode()) . coproduct() h[] # h[1, 1] - h[] # h[2] + h[] # h[2, 1] + 3*h[] # h[2, 2, 1, 1] + h[1] # h[1] + h[1] # h[1, 1] + h[1] # h[2] + 6*h[1] # h[2, 1, 1, 1] + 6*h[1] # h[2, 2, 1] + h[1, 1] # h[] + h[1, 1] # h[1] + 3*h[1, 1] # h[1, 1, 1, 1] + 12*h[1, 1] # h[2, 1, 1] + 3*h[1, 1] # h[2, 2] + 6*h[1, 1, 1] # h[1, 1, 1] + 6*h[1, 1, 1] # h[2, 1] + 3*h[1, 1, 1, 1] # h[1, 1] - h[2] # h[] + h[2] # h[1] + 6*h[2] # h[2, 1, 1] + h[2, 1] # h[] + 6*h[2, 1] # h[1, 1, 1] + 12*h[2, 1] # h[2, 1] + 12*h[2, 1, 1] # h[1, 1] + 6*h[2, 1, 1] # h[2] + 6*h[2, 1, 1, 1] # h[1] + 3*h[2, 2] # h[1, 1] + 6*h[2, 2, 1] # h[1] + 3*h[2, 2, 1, 1] # h[] .. TODO:: - Introduce fields with degree 1 elements as in MuPAD-Combinat, to get proper plethysm. - Use UniqueRepresentation to get rid of all the manual cache handling for the bases - Devise a mechanism so that pickling bases of symmetric functions pickles the coercions which have a cache. """ def __init__(self, R): r""" Initialization of ``self``. INPUT: - ``R`` -- a ring EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) TESTS:: sage: TestSuite(Sym).run() """ assert(R in Rings()) self._base = R # Won't be needed when CategoryObject won't override anymore base_ring Parent.__init__(self, category = GradedHopfAlgebras(R).WithRealizations()) def a_realization(self): r""" Returns a particular realization of ``self`` (the Schur basis). EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) sage: Sym.a_realization() Symmetric Functions over Rational Field in the Schur basis """ return self.schur() def _repr_(self): # could be taken care of by the category r""" Representation of ``self`` TESTS:: sage: SymmetricFunctions(RR) # indirect doctest Symmetric Functions over Real Field with 53 bits of precision """ return "Symmetric Functions over %s"%self.base_ring() def schur(self): r""" The Schur basis of the Symmetric Functions EXAMPLES:: sage: SymmetricFunctions(QQ).schur() Symmetric Functions over Rational Field in the Schur basis """ return schur.SymmetricFunctionAlgebra_schur(self) s = schur Schur = schur # Currently needed by SymmetricFunctions.__init_extra__ # and sfa.SymmetricFunctionsBases.corresponding_basis_over def powersum(self): r""" The power sum basis of the Symmetric Functions EXAMPLES:: sage: SymmetricFunctions(QQ).powersum() Symmetric Functions over Rational Field in the powersum basis """ return powersum.SymmetricFunctionAlgebra_power(self) p = powersum power = powersum # Todo: get rid of this one when it won't be needed anymore def complete(self): r""" The complete basis of the Symmetric Functions EXAMPLES:: sage: SymmetricFunctions(QQ).complete() Symmetric Functions over Rational Field in the homogeneous basis """ return homogeneous.SymmetricFunctionAlgebra_homogeneous(self) h = complete homogeneous = complete def elementary(self): r""" The elementary basis of the Symmetric Functions EXAMPLES:: sage: SymmetricFunctions(QQ).elementary() Symmetric Functions over Rational Field in the elementary basis """ return elementary.SymmetricFunctionAlgebra_elementary(self) e = elementary def monomial(self): r""" The monomial basis of the Symmetric Functions EXAMPLES:: sage: SymmetricFunctions(QQ).monomial() Symmetric Functions over Rational Field in the monomial basis """ return monomial.SymmetricFunctionAlgebra_monomial(self) m = monomial def witt(self, coerce_h=True, coerce_e=False, coerce_p=False): r""" The Witt basis of the symmetric functions. EXAMPLES:: sage: SymmetricFunctions(QQ).witt() Symmetric Functions over Rational Field in the Witt basis sage: SymmetricFunctions(QQ).witt(coerce_p=True) Symmetric Functions over Rational Field in the Witt basis sage: SymmetricFunctions(QQ).witt(coerce_h=False, coerce_e=True, coerce_p=True) Symmetric Functions over Rational Field in the Witt basis """ import witt return witt.SymmetricFunctionAlgebra_witt(self, coerce_h=coerce_h, coerce_e=coerce_e, coerce_p=coerce_p) w = witt # Currently needed by sfa.SymmetricFunctionsBases.corresponding_basis_over Witt = witt def forgotten(self): r""" The forgotten basis of the Symmetric Functions (or the basis dual to the elementary basis with respect to the Hall scalar product). EXAMPLES:: sage: SymmetricFunctions(QQ).forgotten() Symmetric Functions over Rational Field in the forgotten basis TESTS: Over the rationals:: sage: Sym = SymmetricFunctions(QQ) sage: e = Sym.e() sage: f = Sym.f() sage: h = Sym.h() sage: p = Sym.p() sage: s = Sym.s() sage: m = Sym.m() sage: e(f([2,1])) -2*e[1, 1, 1] + 5*e[2, 1] - 3*e[3] sage: f(e([2,1])) 3*f[1, 1, 1] + 2*f[2, 1] + f[3] sage: h(f([2,1])) h[2, 1] - 3*h[3] sage: f(h([2,1])) 3*f[1, 1, 1] + f[2, 1] sage: p(f([2,1])) -p[2, 1] - p[3] sage: f(p([2,1])) -f[2, 1] - f[3] sage: s(f([2,1])) s[2, 1] - 2*s[3] sage: f(s([2,1])) 2*f[1, 1, 1] + f[2, 1] sage: m(f([2,1])) -m[2, 1] - 2*m[3] sage: f(m([2,1])) -f[2, 1] - 2*f[3] Over the integers:: sage: Sym = SymmetricFunctions(ZZ) sage: e = Sym.e() sage: f = Sym.f() sage: h = Sym.h() sage: p = Sym.p() sage: s = Sym.s() sage: m = Sym.m() sage: e(f([2,1])) -2*e[1, 1, 1] + 5*e[2, 1] - 3*e[3] sage: f(e([2,1])) 3*f[1, 1, 1] + 2*f[2, 1] + f[3] sage: h(f([2,1])) h[2, 1] - 3*h[3] sage: f(h([2,1])) 3*f[1, 1, 1] + f[2, 1] sage: f(p([2,1])) -f[2, 1] - f[3] sage: s(f([2,1])) s[2, 1] - 2*s[3] sage: f(s([2,1])) 2*f[1, 1, 1] + f[2, 1] sage: m(f([2,1])) -m[2, 1] - 2*m[3] sage: f(m([2,1])) -f[2, 1] - 2*f[3] Conversion from the forgotten basis to the power-sum basis over the integers is not well-defined in general, even if the result happens to have integral coefficients:: sage: p(f([2,1])) Traceback (most recent call last): ... TypeError: no conversion of this rational to integer Fun exercise: prove that `p(f_{\lambda})` and `p(m_{\lambda})` have integral coefficients whenever `\lambda` is a strict partition. """ return self.elementary().dual_basis() f = forgotten def macdonald(self, q='q', t='t'): r""" Returns the entry point for the various Macdonald bases. INPUT: - ``q``, ``t`` -- parameters Macdonald symmetric functions including bases `P`, `Q`, `J`, `H`, `Ht`. This also contains the `S` basis which is dual to the Schur basis with respect to the `q,t` scalar product. The parameters `q` and `t` must be in the base_ring of parent. EXAMPLES:: sage: Sym = SymmetricFunctions(FractionField(QQ['q','t'])) sage: P = Sym.macdonald().P(); P Symmetric Functions over Fraction Field of Multivariate Polynomial Ring in q, t over Rational Field in the Macdonald P basis sage: P[2] McdP[2] sage: Q = Sym.macdonald().Q(); Q Symmetric Functions over Fraction Field of Multivariate Polynomial Ring in q, t over Rational Field in the Macdonald Q basis sage: S = Sym.macdonald().S() sage: s = Sym.schur() sage: matrix([[S(la).scalar_qt(s(mu)) for la in Partitions(3)] for mu in Partitions(3)]) [1 0 0] [0 1 0] [0 0 1] sage: H = Sym.macdonald().H() sage: s(H[2,2]) q^2*s[1, 1, 1, 1] + (q^2*t+q*t+q)*s[2, 1, 1] + (q^2*t^2+1)*s[2, 2] + (q*t^2+q*t+t)*s[3, 1] + t^2*s[4] sage: Sym = SymmetricFunctions(QQ['z','q'].fraction_field()) sage: (z,q) = Sym.base_ring().gens() sage: Hzq = Sym.macdonald(q=z,t=q).H() sage: H1z = Sym.macdonald(q=1,t=z).H() sage: s = Sym.schur() sage: s(H1z([2,2])) s[1, 1, 1, 1] + (2*z+1)*s[2, 1, 1] + (z^2+1)*s[2, 2] + (z^2+2*z)*s[3, 1] + z^2*s[4] sage: s(Hzq[2,2]) z^2*s[1, 1, 1, 1] + (z^2*q+z*q+z)*s[2, 1, 1] + (z^2*q^2+1)*s[2, 2] + (z*q^2+z*q+q)*s[3, 1] + q^2*s[4] sage: s(H1z(Hzq[2,2])) z^2*s[1, 1, 1, 1] + (z^2*q+z*q+z)*s[2, 1, 1] + (z^2*q^2+1)*s[2, 2] + (z*q^2+z*q+q)*s[3, 1] + q^2*s[4] """ return macdonald.Macdonald(self, q=q, t=t) def hall_littlewood(self, t='t'): """ Returns the entry point for the various Hall-Littlewood bases. INPUT: - ``t`` -- parameter Hall-Littlewood symmetric functions including bases `P`, `Q`, `Qp`. The Hall-Littlewood `P` and `Q` functions at `t=-1` are the Schur-P and Schur-Q functions when indexed by strict partitions. The parameter `t` must be in the base ring of parent. EXAMPLES:: sage: Sym = SymmetricFunctions(FractionField(QQ['t'])) sage: P = Sym.hall_littlewood().P(); P Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Hall-Littlewood P basis sage: P[2] HLP[2] sage: Q = Sym.hall_littlewood().Q(); Q Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Hall-Littlewood Q basis sage: Q[2] HLQ[2] sage: Qp = Sym.hall_littlewood().Qp(); Qp Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Hall-Littlewood Qp basis sage: Qp[2] HLQp[2] """ return hall_littlewood.HallLittlewood(self, t=t) def jack(self, t='t'): """ Returns the entry point for the various Jack bases. INPUT: - ``t`` -- parameter Jack symmetric functions including bases `P`, `Q`, `Qp`. The parameter `t` must be in the base ring of parent. EXAMPLES:: sage: Sym = SymmetricFunctions(FractionField(QQ['t'])) sage: JP = Sym.jack().P(); JP Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Jack P basis sage: JQ = Sym.jack().Q(); JQ Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Jack Q basis sage: JJ = Sym.jack().J(); JJ Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Jack J basis sage: JQp = Sym.jack().Qp(); JQp Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the Jack Qp basis """ return jack.Jack( self, t=t ) def zonal(self): """ The zonal basis of the Symmetric Functions EXAMPLES:: sage: SymmetricFunctions(QQ).zonal() Symmetric Functions over Rational Field in the zonal basis """ return jack.SymmetricFunctionAlgebra_zonal( self ) def llt(self, k, t='t'): """ The LLT symmetric functions. INPUT: - ``k`` -- a positive integer indicating the level - ``t`` -- a parameter (default: `t`) LLT polynomials in `hspin` and `hcospin` bases. EXAMPLES:: sage: llt3 = SymmetricFunctions(QQ['t'].fraction_field()).llt(3); llt3 level 3 LLT polynomials over Fraction Field of Univariate Polynomial Ring in t over Rational Field sage: llt3.hspin() Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the level 3 LLT spin basis sage: llt3.hcospin() Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the level 3 LLT cospin basis sage: llt3.hcospin() Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field in the level 3 LLT cospin basis """ return llt.LLT_class( self, k, t=t ) def from_polynomial(self, f): """ Converts a symmetric polynomial ``f`` to a symmetric function. INPUT: - ``f`` -- a symmetric polynomial This function converts a symmetric polynomial `f` in a polynomial ring in finitely many variables to a symmetric function in the monomial basis of the ring of symmetric functions over the same base ring. EXAMPLES:: sage: P = PolynomialRing(QQ, 'x', 3) sage: x = P.gens() sage: f = x[0] + x[1] + x[2] sage: S = SymmetricFunctions(QQ) sage: S.from_polynomial(f) m[1] sage: f = x[0] + 2*x[1] + x[2] sage: S.from_polynomial(f) Traceback (most recent call last): ... ValueError: x0 + 2*x1 + x2 is not a symmetric polynomial """ return self.m().from_polynomial(f) def register_isomorphism(self, morphism, only_conversion=False): """ Register an isomorphism between two bases of ``self``, as a canonical coercion (unless the optional keyword ``only_conversion`` is set to ``True``, in which case the isomorphism is registered as conversion only). EXAMPLES: We override the canonical coercion from the Schur basis to the powersum basis by a (stupid!) map `s_\lambda\mapsto 2p_\lambda`. :: sage: Sym = SymmetricFunctions(QQ['zorglub']) # make sure we are not going to screw up later tests sage: s = Sym.s(); p = Sym.p().dual_basis() sage: phi = s.module_morphism(diagonal = lambda t: 2, codomain = p) sage: phi(s[2, 1]) 2*d_p[2, 1] sage: Sym.register_isomorphism(phi) sage: p(s[2,1]) 2*d_p[2, 1] The map is supposed to implement the canonical isomorphism between the two bases. Otherwise, the results will be mathematically wrong, as above. Use with care! """ if only_conversion: morphism.codomain().register_conversion(morphism) else: morphism.codomain().register_coercion(morphism) _shorthands = set(['e', 'h', 'm', 'p', 's']) def inject_shorthands(self, shorthands = _shorthands): """ Imports standard shorthands into the global namespace INPUT: - ``shorthands`` -- a list (or iterable) of strings (default: ['e', 'h', 'm', 'p', 's']) EXAMPLES:: sage: S = SymmetricFunctions(ZZ) sage: S.inject_shorthands() sage: s[1] + e[2] * p[1,1] + 2*h[3] + m[2,1] s[1] - 2*s[1, 1, 1] + s[1, 1, 1, 1] + s[2, 1] + 2*s[2, 1, 1] + s[2, 2] + 2*s[3] + s[3, 1] sage: e Symmetric Functions over Integer Ring in the elementary basis sage: p Symmetric Functions over Integer Ring in the powersum basis sage: s Symmetric Functions over Integer Ring in the Schur basis sage: e == S.e(), h == S.h(), m == S.m(), p == S.p(), s == S.s() (True, True, True, True, True) One can also just import a subset of the shorthands:: sage: S = SymmetricFunctions(QQ) sage: S.inject_shorthands(['p', 's']) sage: p Symmetric Functions over Rational Field in the powersum basis sage: s Symmetric Functions over Rational Field in the Schur basis Note that ``e`` is left unchanged:: sage: e Symmetric Functions over Integer Ring in the elementary basis """ from sage.misc.misc import inject_variable for shorthand in shorthands: assert shorthand in self._shorthands inject_variable(shorthand, getattr(self, shorthand)()) def __init_extra__(self): """ Sets up the coercions between the different bases EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) # indirect doctest sage: s = Sym.s(); p = Sym.p() sage: f = s.coerce_map_from(p); f Generic morphism: From: Symmetric Functions over Rational Field in the powersum basis To: Symmetric Functions over Rational Field in the Schur basis sage: p.an_element() 2*p[] + 2*p[1] + 3*p[2] sage: f(p.an_element()) 2*s[] + 2*s[1] - 3*s[1, 1] + 3*s[2] sage: f(p.an_element()) == p.an_element() True """ #powersum = self.powersum () #complete = self.complete () #elementary = self.elementary() #schur = self.schur () #monomial = self.monomial () iso = self.register_isomorphism from sage.combinat.sf.classical import conversion_functions for (basis1_name, basis2_name) in conversion_functions.keys(): basis1 = getattr(self, basis1_name)() basis2 = getattr(self, basis2_name)() on_basis = SymmetricaConversionOnBasis(t = conversion_functions[basis1_name,basis2_name], domain = basis1, codomain = basis2) from sage.rings.rational_field import RationalField if basis2_name != "powersum" or self._base.has_coerce_map_from(RationalField()): iso(basis1._module_morphism(on_basis, codomain = basis2)) else: # Don't register conversions to powersums as coercions, # unless the base ring is a `\QQ`-algebra # (otherwise the coercion graph loses commutativity). iso(basis1._module_morphism(on_basis, codomain = basis2), only_conversion = True) # Todo: fill in with other conversion functions on the classical bases def kBoundedSubspace(self, k, t='t'): r""" Return the `k`-bounded subspace of the ring of symmetric functions. INPUT: - ``k`` - a positive integer - ``t`` a formal parameter; `t=1` yields a subring The subspace of the ring of symmetric functions spanned by `\{ s_{\lambda}[X/(1-t)] \}_{\lambda_1\le k} = \{ s_{\lambda}^{(k)}[X,t]\}_{\lambda_1 \le k}` over the base ring `\mathbb{Q}[t]`. When `t=1`, this space is in fact a subalgebra of the ring of symmetric functions generated by the complete homogeneous symmetric functions `h_i` for `1\le i \le k`. .. seealso:: :meth:`sage.combinat.sf.new_kschur.KBoundedSubspace` EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) sage: KB = Sym.kBoundedSubspace(3,1); KB 3-bounded Symmetric Functions over Rational Field with t=1 sage: Sym = SymmetricFunctions(QQ['t']) sage: Sym.kBoundedSubspace(3) 3-bounded Symmetric Functions over Univariate Polynomial Ring in t over Rational Field sage: Sym = SymmetricFunctions(QQ['z']) sage: z = Sym.base_ring().gens()[0] sage: Sym.kBoundedSubspace(3,t=z) 3-bounded Symmetric Functions over Univariate Polynomial Ring in z over Rational Field with t=z """ from sage.combinat.sf.new_kschur import KBoundedSubspace return KBoundedSubspace(self, k, t=t) def kschur(self, k, t ='t'): r""" Returns the `k`-Schur functions. EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) sage: ks = Sym.kschur(3,1) sage: ks[2]*ks[2] ks3[2, 2] + ks3[3, 1] sage: ks[2,1,1].lift() s[2, 1, 1] + s[3, 1] sage: Sym = SymmetricFunctions(QQ['t']) sage: ks = Sym.kschur(3) sage: ks[2,2,1].lift() s[2, 2, 1] + t*s[3, 2] """ return self.kBoundedSubspace(k, t=t).kschur() def khomogeneous(self, k): r""" Returns the homogeneous symmetric functions in the `k`-bounded subspace. EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) sage: kh = Sym.khomogeneous(4) sage: kh[3]*kh[4] h4[4, 3] sage: kh[4].lift() h[4] """ return self.kBoundedSubspace(k, t=1).khomogeneous() def kBoundedQuotient(self, k, t='t'): r""" Returns the `k`-bounded quotient space of the ring of symmetric functions. INPUT: - ``k`` - a positive integer The quotient of the ring of symmetric functions ... .. seealso:: :meth:`sage.combinat.sf.k_dual.KBoundedQuotient` EXAMPLES:: sage: Sym = SymmetricFunctions(QQ) sage: KQ = Sym.kBoundedQuotient(3); KQ Traceback (most recent call last): ... TypeError: unable to convert t to a rational sage: KQ = Sym.kBoundedQuotient(3,t=1); KQ 3-Bounded Quotient of Symmetric Functions over Rational Field with t=1 sage: Sym = SymmetricFunctions(QQ['t'].fraction_field()) sage: KQ = Sym.kBoundedQuotient(3); KQ 3-Bounded Quotient of Symmetric Functions over Fraction Field of Univariate Polynomial Ring in t over Rational Field """ from sage.combinat.sf.k_dual import KBoundedQuotient return KBoundedQuotient(self, k, t) class SymmetricaConversionOnBasis: def __init__(self, t, domain, codomain): """ Initialization of ``self``. INPUT: - ``t`` -- a function taking a monomial in CombinatorialFreeModule(QQ, Partitions()), and returning a (partition, coefficient) list. - ``domain``, ``codomain`` -- parents Construct a function mapping a partition to an element of ``codomain``. This is a temporary quick hack to wrap around the existing symmetrica conversions, without changing their specs. EXAMPLES:: sage: Sym = SymmetricFunctions(QQ[x]) sage: p = Sym.p(); s = Sym.s() sage: def t(x) : [(p,c)] = x; return [ (p,2*c), (p.conjugate(), c) ] sage: f = sage.combinat.sf.sf.SymmetricaConversionOnBasis(t, p, s) sage: f(Partition([3,1])) s[2, 1, 1] + 2*s[3, 1] """ self._domain = domain self.fake_sym = CombinatorialFreeModule(QQ, Partitions()) self._codomain = codomain self._t = t def __call__(self, partition): """ sage: Sym = SymmetricFunctions(QQ[x]) sage: p = Sym.p(); s = Sym.s() sage: p[1] + s[1] # indirect doctest 2*p[1] """ # TODO: use self._codomain.sum_of_monomials, when the later # will have an optional optimization for the case when there # is no repetition in the support return self._codomain._from_dict(dict(self._t(self.fake_sym.monomial(partition))), coerce = True)

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null

0

1

0

1

0

3

8675c8c5e86ac10bb03d23826def9bd5917b7d31

91

py

Python

tests/settings.py

Olerdrive/lucyfer

548d122f72f30aa658a8d844e319bd9feab8ae6a

[ "MIT" ]

5

2019-09-02T12:15:17.000Z

2020-03-07T12:54:36.000Z

tests/settings.py

Olerdrive/lucyfer

548d122f72f30aa658a8d844e319bd9feab8ae6a

[ "MIT" ]

19

2019-08-12T12:00:13.000Z

2019-11-11T14:14:38.000Z

tests/settings.py

Olerdrive/lucyfer

548d122f72f30aa658a8d844e319bd9feab8ae6a

[ "MIT" ]

3

2019-10-24T16:45:27.000Z

2020-03-05T09:48:45.000Z

LUCYFER_SETTINGS = { "SAVED_SEARCHES_ENABLE": False, "SAVED_SEARCHES_KEY": None, }

18.2

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5.9

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4

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0.428571

0.230769

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0

1

0

null

1

0

1

0

null

0

3

869a10978a36aa0ec09fb0893830708008c7185c

2,126

py

Python

tests/test_cli_spec.py

rai-project/scope_plot

e7fc1629f89fc48f820a1bce45bcc552d259e290

[ "Apache-2.0" ]

null

tests/test_cli_spec.py

rai-project/scope_plot

e7fc1629f89fc48f820a1bce45bcc552d259e290

[ "Apache-2.0" ]

8

2018-08-13T20:27:48.000Z

2018-08-30T11:40:32.000Z

tests/test_cli_spec.py

c3sr/scope_plot

e7fc1629f89fc48f820a1bce45bcc552d259e290

[ "Apache-2.0" ]

null

import os import pytest from scope_plot import cli pytest_plugins = ["pytester"] FIXTURES_DIR = os.path.join( os.path.dirname(os.path.realpath(__file__)), "..", "__fixtures") @pytest.fixture def run(testdir): def do_run(*args): args = ["scope_plot", "--debug"] + list(args) return testdir._run(*args) return do_run @pytest.fixture def run_spec(testdir): def do_run(spec_file): spec_path = os.path.join(FIXTURES_DIR, spec_file) output_path = os.path.join(FIXTURES_DIR, "test.pdf") args = [ "scope_plot", "--debug", "--include", FIXTURES_DIR, "spec", "--output", output_path, spec_path ] return testdir._run(*args) return do_run @pytest.fixture def run_spec_no_output(testdir): def do_run(spec_file): spec_path = os.path.join(FIXTURES_DIR, spec_file) args = [ "scope_plot", "--debug", "--include", FIXTURES_DIR, "spec", spec_path ] return testdir._run(*args) return do_run def test_spec_missing(tmpdir, run_spec): result = run_spec("matplotlib_bar_missing.yml") assert result.ret == 0 def test_bokeh_bar(tmpdir, run_spec): result = run_spec("bokeh_bar.yml") assert result.ret == 0 def test_bokeh_errorbar(tmpdir, run_spec): result = run_spec("bokeh_errorbar.yml") assert result.ret == 0 def test_bokeh_subplots(tmpdir, run_spec): result = run_spec("bokeh_subplots.yml") assert result.ret == 0 def test_matplotlib_bar(tmpdir, run_spec): result = run_spec("matplotlib_bar.yml") assert result.ret == 0 def test_matplotlib_errorbar(tmpdir, run_spec): result = run_spec("matplotlib_errorbar.yml") assert result.ret == 0 def test_matplotlib_regplot(tmpdir, run_spec): result = run_spec("matplotlib_regplot.yml") assert result.ret == 0 def test_matplotlib_subplots(tmpdir, run_spec): result = run_spec("matplotlib_subplots.yml") assert result.ret == 0 def test_no_output_on_cli(tmpdir, run_spec_no_output): result = run_spec_no_output("errorbar_output.yml") assert result.ret == 0

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0.676388

295

2,126

4.562712

0.152542

0.114413

0.086924

0.120357

0.753343

0.739227

0.720654

0.543091

0.204309

0.169391

0

0.0053

0.201317

2,126

89

82

23.88764

0.787397

0

0.40678

0

0.137818

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0

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1

0.254237

false

0

0.050847

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0.40678

0

null

0

1

0

null

0

1

0

3

86a56bf132ec9905600491082d231a8ff09388f0

265

py

Python

front/utils.py

etalab-ia/pdf_api

adfb1d54d66e794073285b91fcc86f70e33c02ae

[ "MIT" ]

null

front/utils.py

etalab-ia/pdf_api

adfb1d54d66e794073285b91fcc86f70e33c02ae

[ "MIT" ]

null

front/utils.py

etalab-ia/pdf_api

adfb1d54d66e794073285b91fcc86f70e33c02ae

[ "MIT" ]

null

import os import streamlit as st def save_uploaded_file(uploaded_file, path): with open(os.path.join(path, uploaded_file.name), "wb") as f: f.write(uploaded_file.getbuffer()) return st.success("Saved File:{} to {}".format(uploaded_file.name, path))

37.857143

77

0.716981

41

265

4.487805

0.560976

0.326087

0.173913

0

0.143396

265

7

77

37.857143

0.810573

0

0.078947

0

1

0.166667

false

0

0.333333

0

0.666667

0

null

1

0

1

0

null

0

1

0

3

86b83db1a4475c35a6d2678493f7612ed5e4b36c

2,240

py

Python

ldap_peoples/form_fields.py

fx74/django-ldap-academia-ou-manager

c5bffa963e389f970e1a8e257fe107ebbc201b54

[ "BSD-2-Clause" ]

16

2019-01-13T10:37:20.000Z

2021-11-25T09:51:19.000Z

ldap_peoples/form_fields.py

fx74/django-ldap-academia-ou-manager

c5bffa963e389f970e1a8e257fe107ebbc201b54

[ "BSD-2-Clause" ]

1

2020-12-03T11:48:45.000Z

ldap_peoples/form_fields.py

fx74/django-ldap-academia-ou-manager

c5bffa963e389f970e1a8e257fe107ebbc201b54

[ "BSD-2-Clause" ]

4

2019-01-17T14:50:33.000Z

2020-12-03T11:47:05.000Z

from django import forms from django.core import validators from django.utils.translation import ugettext_lazy as _ class ListField(forms.Field): def has_changed(self, initial, data): """Return True if data differs from initial.""" # Always return False if the field is disabled since self.bound_data # always uses the initial value in this case. # print(sorted(initial), sorted(data)) if self.disabled: return False try: data = self.to_python(data) if hasattr(self, '_coerce'): return self._coerce(data) != self._coerce(initial) except ValidationError: return True # For purposes of seeing whether something has changed, None is # the same as an empty string, if the data or initial value we get # is None, replace it with ''. initial_value = initial if initial is not None else '' data_value = data if data is not None else '' return sorted(initial_value) != sorted(data_value) class EmailListField(ListField): pass #def validate_email_list(value): #print('EXEC') #if not isinstance(value, list): #raise ValidationError( #_('%(value)s is not a list'), #params={'value': value}, #) #for item in value: #validation = validators.validate_email(item) #print(validation, item) # TODO #def validate(self, value): #"""Check if value consists only of valid emails.""" #print(value) #super().validate(value) #for email in value: #validate_email(email) #default_validators = [validate_email_list] class ScopedListField(ListField): pass # TODO # class TimeStampField(forms.SplitDateTimeField): # widget = DateTimeInput # input_formats = formats.get_format_lazy('DATETIME_INPUT_FORMATS') # default_error_messages = { # 'invalid': _('Enter a valid date/time.'), # } # def clean(self, value): # value = self.to_python(value) # self.validate(value) # self.run_validators(value) # print(self.__dict__, value) # return value

32.463768

76

0.612946

259

2,240

5.169884

0.397683

0.035848

0.017924

0.019417

0

0.291964

2,240

68

77

32.941176

0.844262

0.507589

0

0.1

0

0.006598

0

0.014706

0

1

0.05

false

0.1

0.15

0

0.55

0

null

0

null

0

1

0

1

0

1

0

3

86c85487bdd6c4b71d56f86b754f528eae27ea0d

99

py

Python

JuneLong19/xortest.py

mayank-kumar-giri/Competitive-Coding

4cd26ede051bad15bf25cfd037317c313b607507

[ "MIT" ]

null

JuneLong19/xortest.py

mayank-kumar-giri/Competitive-Coding

4cd26ede051bad15bf25cfd037317c313b607507

[ "MIT" ]

null

JuneLong19/xortest.py

mayank-kumar-giri/Competitive-Coding

4cd26ede051bad15bf25cfd037317c313b607507

[ "MIT" ]

null

n = 95 for i in range(1,1000): a = n ^ i print(bin(a),a) print(i,bin(n),n) print()

14.142857

23

0.484848

21

99

2.285714

0.52381

0

0.102941

0.313131

99

7

24

14.142857

0.602941

0

1

0

false

0

0.5

1

0

null

0

1

0

null

0

1

0

3

86de7ae33a8de99b470fdd69c5cb0a9fbc95628a

714

py

Python

transition.py

RaghubirChimni/LogGenerator

fc7a52ddad15b0885d9f14ffe2d3f017fac63b01

[ "MIT" ]

1

2019-06-11T20:32:04.000Z

transition.py

GabrielSiq/LogGenerator

c3103059bc9a8088d760d756836f6fd0a0b49cd0

[ "MIT" ]

null

transition.py

GabrielSiq/LogGenerator

c3103059bc9a8088d760d756836f6fd0a0b49cd0

[ "MIT" ]

2

2020-11-16T18:54:15.000Z

2021-01-22T22:18:59.000Z

from typing import Union, Tuple from duration import Duration class Transition: # Initialization and instance variables def __init__(self, source: str, destination: str, sgate: str = None, dgate: str = None, distribution: Union[dict, int] = 0) -> None: self.source = source self.source_gate = sgate self.destination = destination self.destination_gate = dgate self.delay = Duration(distribution) # Public methods def get_next(self) -> Tuple[str, str, int]: return self.destination, self.destination_gate, self.delay.generate() # Private methods def __repr__(self): return ', '.join("%s: %s" % item for item in vars(self).items())

34

136

0.665266

87

714

5.321839

0.482759

0.12959

0.112311

0.12959

0

0.001818

0.229692

714

20

137

35.7

0.84

0.095238

0

0.012461

0

1

0.230769

false

0

0.153846

0.615385

0

null

0

null

0

1

0

1

0

3

86e56f2059cbc90d0370dd853a96bccd5507662e

8,973

py

Python

tests/test_csv_file.py

changrunner/zeppos_csv

5b55619bb3baec4c1a676d904bec4fd573d220a9

[ "Apache-2.0" ]

null

tests/test_csv_file.py

changrunner/zeppos_csv

5b55619bb3baec4c1a676d904bec4fd573d220a9

[ "Apache-2.0" ]

null

tests/test_csv_file.py

changrunner/zeppos_csv

5b55619bb3baec4c1a676d904bec4fd573d220a9

[ "Apache-2.0" ]

null

import unittest from zeppos_csv.csv_file import CsvFile from tests.util_for_testing import UtilForTesting from zeppos_bcpy.sql_configuration import SqlConfiguration import os from zeppos_logging.app_logger import AppLogger import pandas as pd from pandas._testing import assert_frame_equal class TestProjectMethods(unittest.TestCase): def setUp(self): UtilForTesting.file_clean_up() def tearDown(self): UtilForTesting.file_clean_up() def test_constructor_method(self): self.assertEqual(str(type(CsvFile(r"c:\temp\test1.csv"))), "<class 'zeppos_csv.csv_file.CsvFile'>") def test_get_dataframe_windows_encoding_with_header(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c1', content="col1,col2\ntest1,test2") df = CsvFile(full_file_name_list[0]).get_dataframe_windows_encoding_with_header() self.assertEqual(1, df.shape[0]) def test_get_dataframe_windows_encoding_with_header_and_chunking_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c2', content="col1,col2\ntest1,test2") df_chunks = CsvFile(full_file_name_list[0]).get_dataframe_windows_encoding_with_header_and_chunking() self.assertEqual(1, df_chunks.get_chunk().shape[0]) def test_get_dataframe_windows_encoding_without_header(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c3', content="test1,test2") df = CsvFile(full_file_name_list[0]).get_dataframe_windows_encoding_without_header(['col1','col2']) self.assertEqual(1, df.shape[0]) def test_get_dataframe_windows_encoding_without_header_and_chunking_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c4', content="test1,test2\ntest1,test2\n") df_chunks = CsvFile(full_file_name_list[0]).get_dataframe_windows_encoding_without_header_and_chunking(['col1', 'col2']) self.assertEqual(2, df_chunks.get_chunk().shape[0]) def test_get_dataframe_utf8_encoding_with_header_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c5', content="col1|col2\ntest1|test2") df = CsvFile(full_file_name_list[0]).get_dataframe_utf8_encoding_with_header() self.assertEqual(df.shape[0], 1) self.assertEqual(df.columns[0], 'col1') self.assertEqual(df.columns[1], 'col2') def test_get_dataframe_utf8_encoding_without_header_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c6', content="test1,test2") df = CsvFile(full_file_name_list[0]).get_dataframe_utf8_encoding_without_header(['col1', 'col2']) self.assertEqual(df.shape[0], 1) self.assertEqual(df.columns[0], 'col1') self.assertEqual(df.columns[1], 'col2') def test_get_dataframe_utf8_encoding_with_header_and_chunkung_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c7', content="col1,col2\ntest1,test2") df = CsvFile(full_file_name_list[0]).get_dataframe_utf8_encoding_with_header_and_chunking() self.assertEqual(df.get_chunk().shape[0], 1) def test_get_dataframe_utf8_encoding_without_header_and_chunking_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('test_df_c8', content="test1,test2") df = CsvFile(full_file_name_list[0]).get_dataframe_utf8_encoding_without_header_and_chunking(['col1', 'col2']) self.assertEqual(df.get_chunk().shape[0], 1) ################################################# # Test file_manager.file inherited functionality ################################################# def test_file_name_property(self): self.assertEqual(CsvFile("c:\\temp\\test.csv").file_name, "test.csv") def test_full_file_name_property(self): self.assertEqual(CsvFile("c:\\temp\\test.csv").full_file_name, "c:\\temp\\test.csv") def test_full_extension_property(self): self.assertEqual(CsvFile("c:\\temp\\test.csv").extension, "csv") def test_mark_file_as_done_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('done') CsvFile(full_file_name=full_file_name_list[0]).mark_as_done() self.assertEqual(os.path.exists(full_file_name_list[0] + ".done"), True) def test_mark_file_as_fail_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('fail') CsvFile(full_file_name=full_file_name_list[0]).mark_as_fail() self.assertEqual(os.path.exists(full_file_name_list[0] + ".fail"), True) def test_mark_file_as_nodata_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('nodata') CsvFile(full_file_name=full_file_name_list[0]).mark_as_nodata() self.assertEqual(os.path.exists(full_file_name_list[0] + ".nodata"), True) def test_get_total_line_count_for_file_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup(sub_directory="file_info", content="1\n2\n") self.assertEqual( CsvFile(full_file_name_list[0]).get_total_line_count_for_file(), 2 ) def test_mark_file_as_ready_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('ready', '.done') result = CsvFile(full_file_name_list[0]).mark_file_as_ready() self.assertEqual(result, True) self.assertEqual(os.path.exists(os.path.splitext(full_file_name_list[0])[0]), True) def test_to_sql_server_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('ready1', '', content="seconds|minutes\n3600|12\n") return_dict = CsvFile.to_sql_server( pandas_dataframe=CsvFile(full_file_name_list[0]).get_dataframe_utf8_encoding_with_header(), sql_configuration=SqlConfiguration( server_type="microsoft", server_name="localhost\\sqlexpress", database_name="master", schema_name="dbo", table_name="staging_test_to_sql_server" ) ) self.assertEqual(["SECONDS", "MINUTES", 'AUDIT_CREATE_UTC_DATETIME'], return_dict["columns"]) self.assertEqual(None, return_dict["error"]) def test_to_sql_server_with_additional_static_info_method(self): temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('ready1', '', content="seconds|minutes\n3600|12\n") return_dict = CsvFile.to_sql_server( pandas_dataframe=CsvFile(full_file_name_list[0]).get_dataframe_utf8_encoding_with_header(), sql_configuration=SqlConfiguration( server_type="microsoft", server_name="localhost\\sqlexpress", database_name="master", schema_name="dbo", table_name="staging_test_to_sql_server2" ), additional_static_data_dict={'static_field1': 'some info 1', 'static_field2': 'some info 2'} ) self.assertEqual(['SECONDS', 'MINUTES', 'STATIC_FIELD1', 'STATIC_FIELD2', 'AUDIT_CREATE_UTC_DATETIME'], return_dict["columns"]) self.assertEqual(None, return_dict["error"]) def test_to_sql_server_with_chunking_method(self): AppLogger.set_debug_level() temp_dir, file_dir, full_file_name_list = UtilForTesting.file_setup('ready2', '', content="seconds|minutes\n3600|12\n3600|13\n3600|14\n3600|15\n3600|16\n") csv_file = CsvFile(full_file_name_list[0]) return_dict = CsvFile(full_file_name_list[0]).to_sql_server_with_chunking( pandas_dataframe_chunks=csv_file.get_dataframe_windows_encoding_with_header_and_chunking(batch_size=2), sql_configuration=SqlConfiguration( server_type="microsoft", server_name="localhost\\sqlexpress", database_name="master", schema_name="dbo", table_name="staging_test_to_sql_server3", ) ) self.assertEqual(["SECONDS", "MINUTES", 'AUDIT_CREATE_UTC_DATETIME', 'CSV_FILE_NAME'], return_dict["columns"]) self.assertEqual(None, return_dict["error"]) def test_save_dataframe_method(self): csv_file = CsvFile(r"c:\temp\test.csv") df_expected = pd.DataFrame({'seconds': [3600], 'minutes': [10]}, columns=['seconds', 'minutes']) csv_file.save_dataframe(df_expected) df_actual = pd.read_csv(r"c:\temp\test.csv", sep="|") assert_frame_equal(df_actual, df_expected) if __name__ == '__main__': unittest.main()

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null

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1

0

1

0

null

0

3

86eab53612ebaf581b877e4e75d7e2dc2f2e2320

103

py

Python

lib/tx.py

tildecross/tx

c59d5f18f95160d6eaaafaeff0e8f02b132bcc7b

[ "BSD-3-Clause" ]

null

lib/tx.py

tildecross/tx

c59d5f18f95160d6eaaafaeff0e8f02b132bcc7b

[ "BSD-3-Clause" ]

null

lib/tx.py

tildecross/tx

c59d5f18f95160d6eaaafaeff0e8f02b132bcc7b

[ "BSD-3-Clause" ]

null

from core import Core class Tx: def __init__(self): self.core = Core() tx = Tx()

12.875

26

0.543689

14

103

3.714286

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103

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null

0

1

0

null

0

1

0

3

86fd210a10933ec93d4a4b2c057f9647b3353006

459

py

Python

beamer/config.py

beamer-bridge/beamer

79e9c8abdff1e05febf0ac9af0f4308290010604

[ "MIT" ]

2

2022-03-29T16:51:52.000Z

2022-03-30T13:23:23.000Z

beamer/config.py

beamer-bridge/beamer

79e9c8abdff1e05febf0ac9af0f4308290010604

[ "MIT" ]

56

2022-03-25T09:12:42.000Z

2022-03-31T14:01:54.000Z

beamer/config.py

beamer-bridge/beamer

79e9c8abdff1e05febf0ac9af0f4308290010604

[ "MIT" ]

null

from dataclasses import dataclass from pathlib import Path from typing import Optional from eth_account.signers.local import LocalAccount from beamer.contracts import DeploymentInfo from beamer.typing import URL @dataclass class Config: account: LocalAccount deployment_info: DeploymentInfo l1_rpc_url: URL l2a_rpc_url: URL l2b_rpc_url: URL token_match_file: Path fill_wait_time: int prometheus_metrics_port: Optional[int]

21.857143

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null

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0

1

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0

3

8104b4bdce0eba8be4737fc520b6ace52e05d736

5,054

py

Python

panflute/containers.py

robert-shade/panflute

6df0a347b00f361df9b0067cdcf2c6492f479377

[ "BSD-3-Clause" ]

null

panflute/containers.py

robert-shade/panflute

6df0a347b00f361df9b0067cdcf2c6492f479377

[ "BSD-3-Clause" ]

null

panflute/containers.py

robert-shade/panflute

6df0a347b00f361df9b0067cdcf2c6492f479377

[ "BSD-3-Clause" ]

null

""" These containers keep track of the identity of the parent object, and the attribute of the parent object that they correspond to. """ # --------------------------- # Imports # --------------------------- import sys py2 = sys.version_info[0] == 2 if py2: str = basestring if py2: from collections import OrderedDict, MutableSequence, MutableMapping else: from collections import OrderedDict from collections.abc import MutableSequence, MutableMapping from .utils import check_type, encode_dict # check_group # --------------------------- # Container Classes # --------------------------- # These are list and OrderedDict containers that # (a) track the identity of their parents, and # (b) track the parent's property where they are stored # They attach these two to the elements requested through __getattr__ class ListContainer(MutableSequence): """ Wrapper around a list, to track the elements' parents. **This class shouldn't be instantiated directly by users, but by the elements that contain it**. :param args: elements contained in the list--like object :param oktypes: type or tuple of types that are allowed as items :type oktypes: ``type`` | ``tuple`` :param parent: the parent element :type parent: ``Element`` :param container: None, unless the element is not part of its .parent.content (this is the case for table headers for instance, which are not retrieved with table.content but with table.header) :type container: ``str`` | None """ # Based on http://stackoverflow.com/a/3488283 # See also https://docs.python.org/3/library/collections.abc.html __slots__ = ['list', 'oktypes', 'parent', 'location'] def __init__(self, *args, oktypes=object, parent=None): self.oktypes = oktypes self.parent = parent self.location = None # Cannot be set through __init__ self.list = [] self.extend(args) # self.oktypes must be set first def __contains__(self, item): return item in self.list def __len__(self): return len(self.list) def __getitem__(self, i): if isinstance(i, int): return attach(self.list[i], self.parent, self.location) else: newlist = self.list.__getitem__(i) obj = ListContainer(*newlist, oktypes=self.oktypes, parent=self.parent) obj.location = self.location return obj def __delitem__(self, i): del self.list[i] def __setitem__(self, i, v): v = check_type(v, self.oktypes) self.list[i] = v def insert(self, i, v): v = check_type(v, self.oktypes) self.list.insert(i, v) def __str__(self): return self.__repr__() def __repr__(self): return 'ListContainer({})'.format(' '.join(repr(x) for x in self.list)) def to_json(self): return [to_json_wrapper(item) for item in self.list] class DictContainer(MutableMapping): """ Wrapper around a dict, to track the elements' parents. **This class shouldn't be instantiated directly by users, but by the elements that contain it**. :param args: elements contained in the dict--like object :param oktypes: type or tuple of types that are allowed as items :type oktypes: ``type`` | ``tuple`` :param parent: the parent element :type parent: ``Element`` """ __slots__ = ['dict', 'oktypes', 'parent', 'location'] def __init__(self, *args, oktypes=object, parent=None, **kwargs): self.oktypes = oktypes self.parent = parent self.location = None self.dict = OrderedDict() self.update(args) # Must be a sequence of tuples self.update(kwargs) # Order of kwargs is not preserved def __contains__(self, item): return item in self.dict def __len__(self): return len(self.dict) def __getitem__(self, k): return attach(self.dict[k], self.parent, self.location) def __delitem__(self, k): del self.dict[k] def __setitem__(self, k, v): v = check_type(v, self.oktypes) self.dict[k] = v def __str__(self): return self.__repr__() def __repr__(self): return 'DictContainer({})'.format(' '.join(repr(x) for x in self.dict)) def __iter__(self): return self.dict.__iter__() def to_json(self): items = self.dict.items() return OrderedDict((k, to_json_wrapper(v)) for k, v in items) return [item.to_json() for item in self.dict] # --------------------------- # Functions # --------------------------- def attach(element, parent, location): if not isinstance(element, (int, str, bool)): element.parent = parent element.location = location else: print(element, 'has no parent') return element def to_json_wrapper(e): if isinstance(e, str): return e elif isinstance(e, bool): return encode_dict('MetaBool', e) else: return e.to_json()

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null

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null

0

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0

1

0

3

81052ab68524c0862cd11da15370bdda191089a4

140

py

Python

django/CVE-2021-35042/web/vuln/apps.py

nobgr/vulhub

b24a89459fbd98ba76881adb6d4e2fb376792863

[ "MIT" ]

9,681

2017-09-16T12:31:59.000Z

2022-03-31T23:49:31.000Z

django/CVE-2021-35042/web/vuln/apps.py

starkxun/vulhub

e5c1b204a6bf1e27d654569ec963329486f230e6

[ "MIT" ]

180

2017-11-01T08:05:07.000Z

2022-03-31T05:26:33.000Z

django/CVE-2021-35042/web/vuln/apps.py

starkxun/vulhub

e5c1b204a6bf1e27d654569ec963329486f230e6

[ "MIT" ]

3,399

2017-09-16T12:21:54.000Z

2022-03-31T12:28:48.000Z

from django.apps import AppConfig class VulnConfig(AppConfig): name = 'vuln' default_auto_field = 'django.db.models.BigAutoField'

20

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140

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57

23.333333

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0

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0

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1

0

null

0

1

0

null

0

1

0

3

811fb08146675ce608fef97368865a1b0650aaa2

80

py

Python

the-python-standard-library-by-example/calendar/calendar_textcalendar.py

gottaegbert/penter

8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d

[ "MIT" ]

13

2020-01-04T07:37:38.000Z

2021-08-31T05:19:58.000Z

the-python-standard-library-by-example/calendar/calendar_textcalendar.py

gottaegbert/penter

8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d

[ "MIT" ]

3

2020-06-05T22:42:53.000Z

2020-08-24T07:18:54.000Z

the-python-standard-library-by-example/calendar/calendar_textcalendar.py

gottaegbert/penter

8cbb6be3c4bf67c7c69fa70e597bfbc3be4f0a2d

[ "MIT" ]

9

2020-10-19T04:53:06.000Z

2021-08-31T05:20:01.000Z

import calendar c = calendar.TextCalendar(calendar.SUNDAY) c.prmonth(2017, 7)

13.333333

42

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5.636364

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0

0.070423

0.1125

80

5

43

16

0.802817

0

1

0

false

0

0.333333

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0

1

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null

0

1

0

null

0

1

0

3

81330c931de8a17bf78139d00524331d06347cce

936

py

Python

python/ds/heightBinaryTree.py

unhingedporter/DataStructureMustKnow

3c5b3225afa2775d37a2ff90121f73208717640a

[ "MIT" ]

3

2019-11-23T08:43:58.000Z

2019-11-23T08:52:53.000Z

python/ds/heightBinaryTree.py

unhingedpotter/DSMustKnow

64958cbbbb3f4cdb1104c2255e555233554503f9

[ "MIT" ]

null

python/ds/heightBinaryTree.py

unhingedpotter/DSMustKnow

64958cbbbb3f4cdb1104c2255e555233554503f9

[ "MIT" ]

null

# Find height of a given binary tree class Node(): def __init__(self, value): self.left = None self.right = None self.value = value class Tree(): def height(self, node: Node): if node is None or (node.left is None and node.right is None): return 0 else: left_sub_tree_height = self.height(node.left) right_sub_tree_height = self.height(node.right) return max(left_sub_tree_height, right_sub_tree_height) + 1 n = Node(15) n.left = Node(10) n.right = Node(20) n.left.right = Node(12) n.right.left = Node(18) n.right.right = Node(30) # Creating left skewed tree n1 = Node(5) n1.left = Node(0) n1.left.left = Node(0) n1.left.left.left = Node(0) n1.left.left.left.left = Node(0) n1.left.left.left.left.left = Node(0) n1.left.left.left.left.left.left = Node(0) n.left.left = n1 print(f'The height of the tree is {Tree().height(n)}')

21.272727

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160

936

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0.25

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0.207612

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936

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0.035714

0

null

1

0

null

0

3

813df2208329c1eed93b0b636e383fdd4e7a6884

2,077

py

Python

orders/models.py

falconsoft3d/clientportal_shop

bc09eda46cb42bbc490dfc6d958250ec000073b5

[ "MIT" ]

5

2022-03-14T21:15:20.000Z

2022-03-22T10:11:58.000Z

orders/models.py

falconsoft3d/clientportal_shop

bc09eda46cb42bbc490dfc6d958250ec000073b5

[ "MIT" ]

null

orders/models.py

falconsoft3d/clientportal_shop

bc09eda46cb42bbc490dfc6d958250ec000073b5

[ "MIT" ]

null

from django.db import models from accounts.models import Account from store.models import Product class Order(models.Model): STATUS = ( ('New', 'Nuevo'), ('Accepted', 'Aceptado'), ('Completed', 'Completado'), ('Cancel', 'Cancelado'), ) user = models.ForeignKey(Account, on_delete=models.CASCADE, null=True) order_number = models.CharField(max_length=20) first_name = models.CharField(max_length=50) last_name = models.CharField(max_length=50) phone = models.CharField(max_length=50) email = models.CharField(max_length=50) addres_line_1 = models.CharField(max_length=100) addres_line_2 = models.CharField(max_length=100) state = models.CharField(max_length=50) city = models.CharField(max_length=50) country = models.CharField(max_length=50) order_note = models.CharField(max_length=100, blank=True) order_total = models.FloatField() tax = models.FloatField() status = models.CharField(max_length=50, choices=STATUS, default='New') ip = models.CharField(blank=True, max_length=20) is_ordered = models.BooleanField(default=False) created_at = models.DateTimeField(auto_now_add=True) update_at = models.DateTimeField(auto_now=True) def full_name(self): return f'{self.first_name} {self.last_name}' def full_address(self): return f'{self.addres_line_1} {self.addres_line_2}' def __str__(self): return self.first_name class OrderProduct(models.Model): order = models.ForeignKey(Order, on_delete=models.CASCADE) user = models.ForeignKey(Account, on_delete=models.CASCADE) product = models.ForeignKey(Product, on_delete=models.CASCADE) quantity = models.IntegerField() product_price = models.FloatField() ordered = models.BooleanField(default=False) created_at = models.DateTimeField(auto_now_add=True) update_at = models.DateTimeField(auto_now=True) def subtotal(self): return self.product_price * self.quantity def __str__(self): return self.product.product_name

35.20339

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null

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null

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3

d49cd26aa57849731f642d65c31a4c763b7dff77

87

py

Python

rusel/base/dir_forms.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

rusel/base/dir_forms.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

rusel/base/dir_forms.py

ruslan-ok/ruslan

fc402e53d2683581e13f4d6c69a6f21e5c2ca1f8

[ "MIT" ]

null

from django import forms class UploadForm(forms.Form): upload = forms.FileField()

17.4

30

0.747126

11

87

5.909091

0.818182

0

0.16092

87

4

31

21.75

0.890411

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

3

d4a4d2f9c7dcf14b818e14bd146d3520a0c0d7ee

137

py

Python

func/python/bench_mdp.py

J-Heinemann/faasm

6a7472d73ef7cc18e63617c72715c8775afd11a9

[ "Apache-2.0" ]

1

2020-04-21T07:33:42.000Z

func/python/bench_mdp.py

J-Heinemann/faasm

6a7472d73ef7cc18e63617c72715c8775afd11a9

[ "Apache-2.0" ]

4

2020-02-03T18:54:32.000Z

2020-05-13T18:28:28.000Z

func/python/bench_mdp.py

J-Heinemann/faasm

6a7472d73ef7cc18e63617c72715c8775afd11a9

[ "Apache-2.0" ]

null

from pyperformance.benchmarks.bm_mdp import bench_mdp def faasm_main(): bench_mdp(1) if __name__ == "__main__": faasm_main()

13.7

53

0.722628

19

137

4.526316

0.684211

0.186047

0

0.00885

0.175182

137

9

54

15.222222

0.752212

0

0.058394

0

1

0.2

true

0

0.2

0

0.4

0

1

0

null

0

1

0

null

0

1

0

3