xszheng2020/the_stack_dedup_python_hits_7 · Datasets at Hugging Face

ddcbfbd04d424120fba564125c159a2a41070598

2,589

py

Python

scripts/hsv_shit.py

skyelong/Insight_Project_clean

19ea003e5c5f4013a66ec244e886036b2b78212b

[ "MIT" ]

1

2020-06-14T02:59:27.000Z

scripts/hsv_shit.py

skyelong/Insight_Project_clean

19ea003e5c5f4013a66ec244e886036b2b78212b

[ "MIT" ]

null

scripts/hsv_shit.py

skyelong/Insight_Project_clean

19ea003e5c5f4013a66ec244e886036b2b78212b

[ "MIT" ]

null

#!/usr/bin/env python3 # -*- coding: utf-8 -*- """ Created on Sat Jun 13 20:54:43 2020 @author: macbook """ import cv2 import pandas as pd def shift_h(array, v_thresh, s_thresh): """Produces shifted H values for color segmentation Chroma h is returned from 0 - 179, neutral h are returned 200-255 Inputs: data - array of pixel H, S, V values one entry per pixel Outputs: H, H120, H240 """ shifted_colors = [] for i in range(0,len(data)): H = data[i][0] s = data[i][1] v = data[i][2] V_thres = 255*v_thresh S_thres = 255*s_thresh if (v > V_thres and s > S_thres): if H >= 120: H120 = H - 120 else: H120 = H + 60 if H >= 60: H240 = H - 60 else: H240 = H + 120 else: H = 200 + ((v/255)*55) H120 = H H240 = H shifted_colors.append([H,H120,H240]) return shifted_colors def shift_h_df(data, v_thresh, s_thresh): """Produces shifted H values for color segmentation Inputs: data - dataframe of pixel H, S, V values one entry per pixel Outputs: H, H120, H240 """ shifted_colors = [] for i in range(0,len(data)): H = data["h"][i] s = data["s"][i] v = data["v"][i] V_thres = 255*v_thresh S_thres = 255*s_thresh if (v > V_thres and s > S_thres): if H >= 120: H120 = H - 120 else: H120 = H + 60 if H >= 60: H240 = H - 60 else: H240 = H + 120 else: H = 200 + ((v/255)*55) H120 = H H240 = H shifted_colors.append([H,H120,H240]) return shifted_colors def shift_h_df_remove(data, v_thresh, s_thresh): """Produces shifted H values for color segmentation Inputs: data - list of pixel H, S, V values one entry per pixel Outputs: H, H120, H240 """ shifted_colors = [] for i in range(0,len(data)): H = data["h"][i] s = data["s"][i] v = data["v"][i] V_thres = 255*v_thresh S_thres = 255*s_thresh if (v > V_thres and s > S_thres): if H >= 120: H120 = H - 120 else: H120 = H + 60 if H >= 60: H240 = H - 60 else: H240 = H + 120 shifted_colors.append([H,H120,H240]) else: pass return shifted_colors

27.542553

72

0.481267

362

2,589

3.334254

0.212707

0.096935

0.039768

0.034797

0.807788

0.78459

0

0.126797

0.409038

2,589

94

73

27.542553

0.662092

0.222866

0

0.869565

0

0.003083

0

1

0.043478

false

0.014493

0.028986

0

0.115942

0

null

0

1

0

1

0

null

0

7

9b398f18d9054d135af6f6456e8316b116bc2730

2,156

py

Python

testsim15.py

shurkova/currentVers

25027f3f4faa9033b69041459f0785c1436c3f31

[ "CECILL-B" ]

1

2020-09-09T15:30:38.000Z

testsim15.py

shurkova/currentVers

25027f3f4faa9033b69041459f0785c1436c3f31

[ "CECILL-B" ]

null

testsim15.py

shurkova/currentVers

25027f3f4faa9033b69041459f0785c1436c3f31

[ "CECILL-B" ]

11

2020-05-01T09:03:14.000Z

2022-02-09T14:17:41.000Z

simType='sym_file' symProps = [{'name': 'lovesMaryTom', 'RBs': [{'pred_name': 'lover', 'pred_sem': ['lover1', 'lover2', 'lover3'], 'higher_order': False, 'object_name': 'Mary', 'object_sem': ['mary1', 'mary2', 'mary3'], 'P': 'non_exist'}, {'pred_name': 'beloved', 'pred_sem': ['beloved1', 'beloved2', 'beloved3'], 'higher_order': False, 'object_name': 'Tom', 'object_sem': ['tom1', 'tom2', 'tome3'], 'P': 'non_exist'}], 'set': 'driver', 'analog': 0}, {'name': 'lovesTomJane', 'RBs': [{'pred_name': 'lover', 'pred_sem': ['lover1', 'lover2', 'lover3'], 'higher_order': False, 'object_name': 'Tom', 'object_sem': ['tom1', 'tom2', 'tome3'], 'P': 'non_exist'}, {'pred_name': 'beloved', 'pred_sem': ['beloved1', 'beloved2', 'beloved3'], 'higher_order': False, 'object_name': 'Jane', 'object_sem': ['jane1', 'jane2', 'mary2'], 'P': 'non_exist'}], 'set': 'driver', 'analog': 0}, {'name': 'jealousMaryJane', 'RBs': [{'pred_name': 'jealous_act', 'pred_sem': ['jel1', 'jel2', 'jel3'], 'higher_order': False, 'object_name': 'Mary', 'object_sem': ['mary1', 'mary2', 'mary3'], 'P': 'non_exist'}, {'pred_name': 'jealous_pat', 'pred_sem': ['jel4', 'jel5', 'jel6'], 'higher_order': False, 'object_name': 'Jane', 'object_sem': ['jane1', 'jane2', 'mary2'], 'P': 'non_exist'}], 'set': 'driver', 'analog': 0}, {'name': 'lovesJohnKathy', 'RBs': [{'pred_name': 'lover', 'pred_sem': ['lover1', 'lover2', 'lover3'], 'higher_order': False, 'object_name': 'John', 'object_sem': ['john1', 'john2', 'john3'], 'P': 'non_exist'}, {'pred_name': 'beloved', 'pred_sem': ['beloved1', 'beloved2', 'beloved3'], 'higher_order': False, 'object_name': 'Kathy', 'object_sem': ['kathy1', 'kathy2', 'kathy3'], 'P': 'non_exist'}], 'set': 'recipient', 'analog': 0}, {'name': 'lovesKathySam', 'RBs': [{'pred_name': 'lover', 'pred_sem': ['lover1', 'lover2', 'lover3'], 'higher_order': False, 'object_name': 'Kathy', 'object_sem': ['kathy1', 'kathy2', 'kathy3'], 'P': 'non_exist'}, {'pred_name': 'beloved', 'pred_sem': ['beloved1', 'beloved2', 'beloved3'], 'higher_order': False, 'object_name': 'Sam', 'object_sem': ['sam1', 'sam2', 'sam3'], 'P': 'non_exist'}], 'set': 'recipient', 'analog': 0}]

165.846154

432

0.607607

261

2,156

4.777778

0.249042

0.064154

0.128308

0.176423

0.825982

0.788292

0.772253

0

0.033333

0.095547

2,156

12

433

179.666667

0.606154

0

0.575673

0

1

0

false

0

null

0

1

0

1

0

null

0

8

9b3f76fa1d35675a07fbb0103b68bfc50da25ffc

201

py

Python

assets/code/src/test_integer_division.py

drtrome/rsd

5fdc0edd2733319d1c8c2e7dbbd8e21af1b0606c

[ "MIT" ]

null

assets/code/src/test_integer_division.py

drtrome/rsd

5fdc0edd2733319d1c8c2e7dbbd8e21af1b0606c

[ "MIT" ]

92

2017-10-01T14:00:05.000Z

2020-04-20T13:06:40.000Z

assets/code/src/test_integer_division.py

drtrome/rsd

5fdc0edd2733319d1c8c2e7dbbd8e21af1b0606c

[ "MIT" ]

24

2017-12-11T16:46:31.000Z

2020-01-08T11:54:10.000Z

import integer_division assert integer_division.get_exponent_of_factor(45, 5) == 1 assert integer_division.get_exponent_of_factor(45, 7) == 0 assert integer_division.get_exponent_of_factor(9, 9) == 1

33.5

58

0.820896

33

201

4.606061

0.424242

0.394737

0.414474

0.473684

0.815789

0.552632

0

0.060109

0.089552

201

5

59

40.2

0.770492

0

0.75

1

0

true

0

0.25

0

0.25

0

null

1

0

1

0

null

0

1

0

1

0

9

9b9193eb4c9f1666c2b28aaa8298556db3418728

201

py

Python

Codewars/7kyu/password-hashes/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

7

2017-09-20T16:40:39.000Z

2021-08-31T18:15:08.000Z

Codewars/7kyu/password-hashes/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

Codewars/7kyu/password-hashes/Python/test.py

RevansChen/online-judge

ad1b07fee7bd3c49418becccda904e17505f3018

[ "MIT" ]

null

# Python - 3.6.0 Test.describe('Basic tests') Test.assert_equals(pass_hash('password'), '5f4dcc3b5aa765d61d8327deb882cf99') Test.assert_equals(pass_hash('abc123'), 'e99a18c428cb38d5f260853678922e03')

33.5

77

0.800995

22

201

7.136364

0.727273

0.127389

0.203822

0.254777

0.305732

0

0.252632

0.054726

201

5

78

40.2

0.573684

0.069652

0

0.481081

0.345946

0

0.666667

1

0

true

0.666667

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

8

32d44e2cda15c81583b684ffc016731ccac03212

13,068

py

Python

tests/rst/test_opt_list.py

LudditeLabs/autodoc-tool

b4ae7e3b61907e7e9c3a1b534fce055e5860ffab

[ "Apache-2.0" ]

null

tests/rst/test_opt_list.py

LudditeLabs/autodoc-tool

b4ae7e3b61907e7e9c3a1b534fce055e5860ffab

[ "Apache-2.0" ]

null

tests/rst/test_opt_list.py

LudditeLabs/autodoc-tool

b4ae7e3b61907e7e9c3a1b534fce055e5860ffab

[ "Apache-2.0" ]

null

# Copyright 2018 Luddite Labs Inc. # # 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. # Test: options list. class TesOptList: # Test: if we don't pass source lines info and width. # * Left side option width must be 15 # * Options with long descriptions have 1 blank line margin # * Long options have 1 blank line margin and description on next line. # * Other options have no margins. def test_no_src(self, assert_py_doc): assert_py_doc( settings=dict(line_width=None), text=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, expected=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, pass_lines=False ) # Test: if we pass no source lines info but set width. # * Left side option width must be width / 4 # * Options with long descriptions have 1 blank line margin # * Long options have 1 blank line margin and description on next line. # * Other options have no margins. def test_no_src_width(self, assert_py_doc): assert_py_doc( settings=dict(line_width=66), text=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, expected=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, pass_lines=False ) # Test: if we pass source lines info but no width. # * Left side option width must be the same as in orig text. # * Options with long descriptions have 1 blank line margin # * Long options have 1 blank line margin and description on next line. # * Other options have no margins. def test_src(self, assert_py_doc): assert_py_doc( text=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, expected=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, pass_lines=True ) # Test: if we pass source lines info and width. # * Left side option width must be the same as in orig text. # * Options with long descriptions have 1 blank line margin # * Long options have 1 blank line margin and description on next line. # * Other options have no margins. def test_src_width(self, assert_py_doc): assert_py_doc( settings=dict(line_width=66), text=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, expected=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, pass_lines=True ) # Test: if we pass all info + force margin between options. def test_margin(self, assert_py_doc): assert_py_doc( settings=dict(opt_margin=True, line_width=66), text=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, expected=""" Top text. -a, --ax Output all. -b Output both (this description is quite long). -c arg Output just arg. --long Output all day long. -p This option has two paragraphs in the description. This is the first. This is the second. Blank lines may be omitted between options (as above) or left in (as here and below). --very-long-option A VMS-style option. Note the adjustment for the required two spaces. --an-even-longer-option The description can also start on the next line. -2, --two This option has two variants. -f FILE, --file=FILE These two options are synonyms; both have arguments. /V A VMS/DOS-style option. Bottom text. """, pass_lines=True )

35.034853

82

0.496021

1,512

13,068

4.261243

0.105159

0.027937

0.040354

0.049666

0.909514

0.90253

0.898494

0.892597

0

0.00482

0.444368

13,068

372

83

35.129032

0.882523

0.127717

0

0.920502

0

0.901258

0.020241

0

0.041841

1

0.020921

false

0.020921

0

0.025105

0

null

0

1

0

1

0

1

0

null

0

8

fd17c9d24f779e07c3a9537db132f4ed960d54d4

101

py

Python

rkd/util.py

iro-upgto/rkd

7823781ddc81a9dac18fed55080205e8ed68b57b

[ "MIT" ]

null

rkd/util.py

iro-upgto/rkd

7823781ddc81a9dac18fed55080205e8ed68b57b

[ "MIT" ]

null

rkd/util.py

iro-upgto/rkd

7823781ddc81a9dac18fed55080205e8ed68b57b

[ "MIT" ]

null

from numpy import * def deg2rad(x): return ((x*pi)/180) def rad2deg(x): return ((x*180)/pi)

14.428571

23

0.60396

17

101

3.588235

0.588235

0.229508

0.262295

0

0.1

0.207921

101

7

24

14.428571

0.6625

0

1

0.4

false

0

0.2

0.4

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

fd1e1c6ec4ff50c811ca0ba7f6cd5449de3d665f

235

py

Python

backend/models/__init__.py

riftadi/trashexplorer

fed8ed83c277d56a548ff6036af57d776db3bb9e

[ "Apache-2.0" ]

null

backend/models/__init__.py

riftadi/trashexplorer

fed8ed83c277d56a548ff6036af57d776db3bb9e

[ "Apache-2.0" ]

3

2018-06-14T11:08:52.000Z

2022-03-02T08:08:34.000Z

backend/models/__init__.py

riftadi/trashure

fed8ed83c277d56a548ff6036af57d776db3bb9e

[ "Apache-2.0" ]

null

from models.areamodel import * from models.basedb import * from models.gamemodel import * from models.revokedtokenmodel import * from models.trashbinmodel import * from models.trashbinimagemodel import * from models.usermodel import *

29.375

39

0.821277

28

235

6.892857

0.357143

0.362694

0.497409

0

0.119149

235

7

40

33.571429

0.932367

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

fd3e4cc167ea1ff675c1e1a64a0442080413812e

169

py

Python

baedin/chat/views.py

braedinmgregoire/DndWebsite

19b55117cba39b524ed2cd74b22f33587733fb58

[ "MIT" ]

null

baedin/chat/views.py

braedinmgregoire/DndWebsite

19b55117cba39b524ed2cd74b22f33587733fb58

[ "MIT" ]

null

baedin/chat/views.py

braedinmgregoire/DndWebsite

19b55117cba39b524ed2cd74b22f33587733fb58

[ "MIT" ]

null

from django.shortcuts import render # Create your views here. from django.shortcuts import render def tavern(request): return render(request, 'chat/tavern.html')

18.777778

46

0.769231

23

169

5.652174

0.652174

0.153846

0.292308

0.384615

0.476923

0

0.147929

169

8

47

21.125

0.902778

0.136095

0

0.5

0

0.111111

0

1

0.25

false

0

0.5

0.25

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

8

fd4b935d395704d55d505fcc6d63bd3199b0d576

92

py

Python

parameters_443.py

droptables/Battle-Dex

279b43bb2027e4a54050c9cccddc399c0b96da13

[ "BSD-3-Clause" ]

null

parameters_443.py

droptables/Battle-Dex

279b43bb2027e4a54050c9cccddc399c0b96da13

[ "BSD-3-Clause" ]

null

parameters_443.py

droptables/Battle-Dex

279b43bb2027e4a54050c9cccddc399c0b96da13

[ "BSD-3-Clause" ]

null

password="pbkdf2(1000,20,sha512)$a85a47dcd18825d8$3656c81d1b8497c50ecdb08566babf1e68e8c17b"

46

91

0.891304

7

92

11.714286

1

0

0.483516

0.01087

92

1

92

0.417582

0

0.869565

0

1

0

false

1

0

1

0

1

null

0

1

0

1

0

1

0

1

null

0

1

0

8

b5d3037577f7e53e0de912c8b594fc1d59a629be

13,861

py

Python

mmtfPyspark/tests/utils/test_MmtfSubstructure.py

sbliven/mmtf-pyspark

3d444178bdc0d5128aafdb1326fec12b5d7634b5

[ "Apache-2.0" ]

59

2018-01-28T06:50:56.000Z

2022-02-10T06:07:12.000Z

mmtfPyspark/tests/utils/test_MmtfSubstructure.py

sbliven/mmtf-pyspark

3d444178bdc0d5128aafdb1326fec12b5d7634b5

[ "Apache-2.0" ]

101

2018-02-01T20:51:10.000Z

2022-01-24T00:50:29.000Z

mmtfPyspark/tests/utils/test_MmtfSubstructure.py

sbliven/mmtf-pyspark

3d444178bdc0d5128aafdb1326fec12b5d7634b5

[ "Apache-2.0" ]

29

2018-01-29T10:09:51.000Z

2022-01-23T18:53:28.000Z

#!/usr/bin/env python ''' Authorship information: __author__ = "Peter Rose" __maintainer__ = "Peter Rose" __status__ = "Warning" ''' import unittest import numpy as np from pyspark.sql import SparkSession from mmtfPyspark.io import mmtfReader from mmtfPyspark.utils import MmtfSubstructure class TestMmtfSubstructure(unittest.TestCase): def setUp(self): self.spark = SparkSession.builder.master("local[1]") \ .appName("TestMmtfSubstructure") \ .getOrCreate() def test_4HHB_polychain(self): print('test_4HHB_polychain') path = '../../../resources/files/' pdb = mmtfReader.read_mmtf_files(path) pdb = pdb.filter(lambda t: t[0] == '4HHB') structure = pdb.values().first() chain = MmtfSubstructure(structure, 'A', chain_names=['A'], entity_types=['polymer']) self.assertEqual(1069, chain.num_atoms) self.assertEqual(141, chain.num_groups) self.assertEqual(1, chain.num_chains) self.assertEqual(1, chain.num_models) self.assertEqual(np.testing.assert_allclose([6.204, 6.913, 8.504], chain.x_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([16.869, 17.759, 17.378], chain.y_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([4.854, 4.607, 4.797], chain.z_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([49.05, 43.14, 24.80], chain.b_factor_list[0:3], atol=0.01), None) self.assertEqual(np.testing.assert_allclose([1.0, 1.0, 1.0], chain.occupancy_list[0:3], atol=0.01), None) self.assertListEqual([1, 2, 3], chain.atom_id_list[0:3].tolist()) self.assertListEqual(['', '', ''], chain.alt_loc_list[0:3].tolist()) self.assertListEqual(['A', 'A', 'A'], chain.chain_names[0:3].tolist()) self.assertListEqual(['A', 'A', 'A'], chain.chain_ids[0:3].tolist()) self.assertListEqual(['1', '1', '1'], chain.group_numbers[0:3].tolist()) self.assertListEqual(['VAL', 'VAL', 'VAL'], chain.group_names[0:3].tolist()) self.assertListEqual(['N', 'CA', 'C'], chain.atom_names[0:3].tolist()) self.assertListEqual(['N', 'C', 'C'], chain.elements[0:3].tolist()) self.assertListEqual(['L-PEPTIDE LINKING', 'L-PEPTIDE LINKING'], chain.chem_comp_types[0:2].tolist()) self.assertListEqual([True, True, True], chain.polymer[0:3].tolist()) self.assertListEqual([0, 0, 0], chain.entity_indices[0:3].tolist()) self.assertListEqual([0, 0, 0], chain.sequence_positions[0:3].tolist()) chain = MmtfSubstructure(structure, 'B', chain_names=['B'], entity_types=['polymer']) self.assertEqual(1123, chain.num_atoms) self.assertEqual(146, chain.num_groups) self.assertEqual(1, chain.num_chains) self.assertEqual(1, chain.num_models) self.assertEqual(np.testing.assert_allclose([9.223, 8.694, 9.668], chain.x_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([-20.614, -20.026, -21.068], chain.y_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([1.365, -0.123, -1.645], chain.z_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([46.08, 70.96, 69.74], chain.b_factor_list[0:3], atol=0.01), None) self.assertEqual(np.testing.assert_allclose([1.0, 1.0, 1.0], chain.occupancy_list[0:3], atol=0.01), None) self.assertListEqual([1070, 1071, 1072], chain.atom_id_list[0:3].tolist()) self.assertListEqual(['', '', ''], chain.alt_loc_list[0:3].tolist()) self.assertListEqual(['B', 'B', 'B'], chain.chain_names[0:3].tolist()) self.assertListEqual(['B', 'B', 'B'], chain.chain_ids[0:3].tolist()) self.assertListEqual(['1', '1', '1'], chain.group_numbers[0:3].tolist()) self.assertListEqual(['VAL', 'VAL', 'VAL'], chain.group_names[0:3].tolist()) self.assertListEqual(['N', 'CA', 'C'], chain.atom_names[0:3].tolist()) self.assertListEqual(['N', 'C', 'C'], chain.elements[0:3].tolist()) self.assertListEqual(['L-PEPTIDE LINKING', 'L-PEPTIDE LINKING'], chain.chem_comp_types[0:2].tolist()) self.assertListEqual([True, True, True], chain.polymer[0:3].tolist()) self.assertListEqual([1, 1, 1], chain.entity_indices[0:3].tolist()) self.assertListEqual([0, 0, 0], chain.sequence_positions[0:3].tolist()) def test_4HHB_polychains(self): print('test_4HHB_polychains') path = '../../../resources/files/' pdb = mmtfReader.read_mmtf_files(path) pdb = pdb.filter(lambda t: t[0] == '4HHB') structure = pdb.values().first() chain = MmtfSubstructure(structure, 'A+B', chain_names=['A', 'B'], entity_types=['polymer']) self.assertEqual(1069+1123, chain.num_atoms) self.assertEqual(141+146, chain.num_groups) self.assertEqual(1+1, chain.num_chains) self.assertEqual(1, chain.num_models) def test_4HHB_chain_ids(self): print('test_4HHB_chain_ids') path = '../../../resources/files/' pdb = mmtfReader.read_mmtf_files(path) pdb = pdb.filter(lambda t: t[0] == '4HHB') structure = pdb.values().first() chain = MmtfSubstructure(structure, 'A', chain_ids=['A']) self.assertEqual(1069, chain.num_atoms) np.set_printoptions(threshold=np.inf) print(chain.group_serial) self.assertEqual(141, chain.num_groups) self.assertEqual(1, chain.num_chains) self.assertEqual(1, chain.num_models) self.assertEqual(np.testing.assert_allclose([6.204, 6.913, 8.504], chain.x_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([16.869, 17.759, 17.378], chain.y_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([4.854, 4.607, 4.797], chain.z_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([49.05, 43.14, 24.80], chain.b_factor_list[0:3], atol=0.01), None) self.assertEqual(np.testing.assert_allclose([1.0, 1.0, 1.0], chain.occupancy_list[0:3], atol=0.01), None) self.assertListEqual([1, 2, 3], chain.atom_id_list[0:3].tolist()) self.assertListEqual(['', '', ''], chain.alt_loc_list[0:3].tolist()) self.assertListEqual(['A', 'A', 'A'], chain.chain_names[0:3].tolist()) self.assertListEqual(['A', 'A', 'A'], chain.chain_ids[0:3].tolist()) self.assertListEqual(['1', '1', '1'], chain.group_numbers[0:3].tolist()) self.assertListEqual(['VAL', 'VAL', 'VAL'], chain.group_names[0:3].tolist()) self.assertListEqual(['N', 'CA', 'C'], chain.atom_names[0:3].tolist()) self.assertListEqual(['N', 'C', 'C'], chain.elements[0:3].tolist()) self.assertListEqual(['L-PEPTIDE LINKING', 'L-PEPTIDE LINKING'], chain.chem_comp_types[0:2].tolist()) self.assertListEqual([True, True, True], chain.polymer[0:3].tolist()) self.assertListEqual([0, 0, 0], chain.entity_indices[0:3].tolist()) self.assertListEqual([0, 0, 0], chain.sequence_positions[0:3].tolist()) chain = MmtfSubstructure(structure, 'B', chain_names=['B'], entity_types=['polymer']) self.assertEqual(1123, chain.num_atoms) self.assertEqual(146, chain.num_groups) self.assertEqual(1, chain.num_chains) self.assertEqual(1, chain.num_models) self.assertEqual(np.testing.assert_allclose([9.223, 8.694, 9.668], chain.x_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([-20.614, -20.026, -21.068], chain.y_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([1.365, -0.123, -1.645], chain.z_coord_list[0:3], atol=0.001), None) self.assertEqual(np.testing.assert_allclose([46.08, 70.96, 69.74], chain.b_factor_list[0:3], atol=0.01), None) self.assertEqual(np.testing.assert_allclose([1.0, 1.0, 1.0], chain.occupancy_list[0:3], atol=0.01), None) self.assertListEqual([1070, 1071, 1072], chain.atom_id_list[0:3].tolist()) self.assertListEqual(['', '', ''], chain.alt_loc_list[0:3].tolist()) self.assertListEqual(['B', 'B', 'B'], chain.chain_names[0:3].tolist()) self.assertListEqual(['B', 'B', 'B'], chain.chain_ids[0:3].tolist()) self.assertListEqual(['1', '1', '1'], chain.group_numbers[0:3].tolist()) self.assertListEqual(['VAL', 'VAL', 'VAL'], chain.group_names[0:3].tolist()) self.assertListEqual(['N', 'CA', 'C'], chain.atom_names[0:3].tolist()) self.assertListEqual(['N', 'C', 'C'], chain.elements[0:3].tolist()) self.assertListEqual(['L-PEPTIDE LINKING', 'L-PEPTIDE LINKING'], chain.chem_comp_types[0:2].tolist()) self.assertListEqual([True, True, True], chain.polymer[0:3].tolist()) self.assertListEqual([1, 1, 1], chain.entity_indices[0:3].tolist()) self.assertListEqual([0, 0, 0], chain.sequence_positions[0:3].tolist()) def test_4HHB_group_names(self): print('test_4HHB_chain_ids') path = '../../../resources/files/' pdb = mmtfReader.read_mmtf_files(path) pdb = pdb.filter(lambda t: t[0] == '4HHB') structure = pdb.values().first() chain = MmtfSubstructure(structure, 'HEM', chain_names=['A'], group_names=['HEM']) self.assertEqual(43, chain.num_atoms) self.assertEqual(1, chain.num_groups) self.assertEqual(1, chain.num_chains) self.assertEqual(1, chain.num_models) chain = MmtfSubstructure(structure, 'HEM', group_names=['HEM']) self.assertEqual(43*4, chain.num_atoms) self.assertEqual(1*4, chain.num_groups) self.assertEqual(1*4, chain.num_chains) self.assertEqual(1, chain.num_models) def test_4HHB_group_numbers(self): print('test_4HHB_chain_ids') path = '../../../resources/files/' pdb = mmtfReader.read_mmtf_files(path) pdb = pdb.filter(lambda t: t[0] == '4HHB') structure = pdb.values().first() chain = MmtfSubstructure(structure, 'HEM', chain_names=['A'], group_numbers=['1', '10']) self.assertEqual(43, chain.num_atoms) self.assertEqual(1, chain.num_groups) self.assertEqual(1, chain.num_chains) self.assertEqual(1, chain.num_models) chain = MmtfSubstructure(structure, 'HEM', group_names=['HEM']) self.assertEqual(43*4, chain.num_atoms) self.assertEqual(1*4, chain.num_groups) self.assertEqual(1*4, chain.num_chains) self.assertEqual(1, chain.num_models) # def test_4HHB_chains(self): # print('test_4HHB_chains') # path = '../../../resources/files/' # pdb = mmtfReader.read_mmtf_files(path) # pdb = pdb.filter(lambda t: t[0] == '4HHB') # structure = pdb.values().first() # chains = structure.get_chains() # self.assertEqual(4, len(chains)) # def test_4HHB_chains_first_model(self): # print('test_4HHB_chains_first_model') # path = '../../../resources/files/' # pdb = mmtfReader.read_mmtf_files(path, first_model=True) # pdb = pdb.filter(lambda t: t[0] == '4HHB') # structure = pdb.values().first() # chains = structure.get_chains() # self.assertEqual(4, len(chains)) # # def test_1J6T_chains_first_model(self): # print('test_1J6T_chains_first_model') # path = '../../../resources/files/' # pdb = mmtfReader.read_mmtf_files(path, first_model=True) # pdb = pdb.filter(lambda t: t[0] == '1J6T') # structure = pdb.values().first() # chains = structure.get_chains() # self.assertEqual(2, len(chains)) # def test_4HHB_multiple_chains(self): # print('test_4HHB_multiple_chains') # path = '../../../resources/files/' # pdb = mmtfReader.read_mmtf_files(path) # pdb = pdb.filter(lambda t: t[0] == '4HHB') # structure = pdb.values().first() # chain_list = ['A'] # chains = structure.get_multiple_chains(chain_list) # self.assertEqual(1168, chains.x_coord_list.size) # chain_list = ['A', 'B'] # chains = structure.get_multiple_chains(chain_list) # self.assertEqual(2392, chains.x_coord_list.shape[0]) # chain_list = ['A', 'B', 'C'] # chains = structure.get_multiple_chains(chain_list) # self.assertEqual(3563, chains.x_coord_list.shape[0]) # chain_list = ['A', 'B', 'C', 'D'] # chains = structure.get_multiple_chains(chain_list) # self.assertEqual(4779, chains.x_coord_list.shape[0]) def tearDown(self): self.spark.stop() if __name__ == '__main__': unittest.main()

55.444

109

0.587043

1,750

13,861

4.489714

0.101714

0.016291

0.044801

0.061092

0.914598

0.904162

0.873234

0.869034

0.840524

0

0.061659

0.244138

13,861

249

110

55.666667

0.68827

0.137508

0

0.826816

0

0.048727

0.010502

0

0.581006

1

0.039106

false

0

0.027933

0

0.072626

0.039106

0

null

0

1

0

1

0

null

0

1

0

8

b5d640dc16a26f13ad722f56edb3ce2634e75ee6

4,689

py

Python

mannord/spam_detection_mixins.py

mshavlovsky/mannord

a7bd066e1d8c57bcf220f7234fdf071e19013b49

[ "BSD-2-Clause" ]

null

mannord/spam_detection_mixins.py

mshavlovsky/mannord

a7bd066e1d8c57bcf220f7234fdf071e19013b49

[ "BSD-2-Clause" ]

null

mannord/spam_detection_mixins.py

mshavlovsky/mannord

a7bd066e1d8c57bcf220f7234fdf071e19013b49

[ "BSD-2-Clause" ]

null

from sqlalchemy.ext.declarative import declared_attr from sqlalchemy import (Column, Integer, Float, String, Boolean, ForeignKey, DateTime, Sequence, and_) class UserDirichletMixin(object): """ Field of this class contains information necessary for spam detection according to dirichlet method.""" @declared_attr def sd_base_u_n(cls): return Column(Float, default=0) @declared_attr def sd_base_u_p(cls): return Column(Float, default=0) @declared_attr def sd_reliab(cls): """ Spam detection reliability is computed based on u_n and u_p.""" return Column(Float, default=0) @declared_attr def sd_u_n(cls): return Column(Float, default=0) @declared_attr def sd_u_p(cls): return Column(Float, default=0) @declared_attr def sd_karma_user_base_u_n(cls): return Column(Float, default=0) @declared_attr def sd_karma_user_base_u_p(cls): return Column(Float, default=0) @declared_attr def sd_karma_user_reliab(cls): """ Spam detection reliability""" return Column(Float, default=0) @declared_attr def sd_karma_user_u_n(cls): return Column(Float, default=0) @declared_attr def sd_karma_user_u_p(cls): return Column(Float, default=0) class ItemDirichletMixin(object): """ Item fields which contains information necessary for spam detection according to Dirichlet algorithm.""" @declared_attr def sd_c_n(cls): """ 'Number' of negative votes for the item""" return Column(Float, default=0) @declared_attr def sd_c_p(cls): """ 'Number' of positive votes for the item""" return Column(Float, default=0) @declared_attr def sd_weight(cls): """ weight_spam_k is a weight of an item wich computed in Karger's algorithm. Negative weight indicates spam. """ return Column(Float) @declared_attr def sd_frozen(cls): return Column(Boolean, default=False) @classmethod def sd_get_items_offline_spam_detect(cls, session): items = session.query(cls).filter( cls.sd_frozen == False).all() return items class ActionDirichletMixin(object): @declared_attr def sd_frozen(cls): """ If the field is true, then the action participate in offline spam detection.""" return Column(Boolean, default=False) @classmethod def sd_get_actions_offline_spam_detect(cls, session): actions = session.query(cls).filter( cls.sd_frozen == False).all() return actions class UserKargerMixin(object): """ Fileds of this class contains information necessary for spam detection according to the algorithm by Karger.""" @declared_attr def sk_base_reliab(cls): """ This field is a base raliability of a user for spam detection task. """ return Column(Float, default=0) @declared_attr def sk_reliab(cls): """ Spam detection reliability""" return Column(Float, default=0) @declared_attr def sk_reliab_raw(cls): """ Raw reliability is user's reliability before applying asymptotic function or normalization. We need it to perform online update. """ return Column(Float, default=0) @declared_attr def sk_karma_user_base_reliab(cls): """ This field is a base reliability for a karma user ("null" user) who always votes positively for the user's annotation.""" return Column(Float, default=0) @declared_attr def sk_karma_user_reliab(cls): return Column(Float, default=0) class ItemKargerMixin(object): @declared_attr def sk_weight(cls): """ weight_spam_k is a weight of an item wich computed in Karger's algorithm. Negative weight indicates spam. """ return Column(Float, default=0) @declared_attr def sk_frozen(cls): return Column(Boolean, default=False) @classmethod def sk_get_items_offline_spam_detect(cls, session): items = session.query(cls).filter( cls.sk_frozen == False).all() return items class ActionKargerMixin(object): @declared_attr def sk_frozen(cls): """ If the field is true, then the action does not participate in offline spam detection.""" return Column(Boolean, default=False) @classmethod def sk_get_actions_offline_spam_detect(cls, session): actions = session.query(cls).filter( cls.sk_frozen == False).all() return actions

28.766871

79

0.653231

601

4,689

4.915141

0.193012

0.097495

0.116791

0.146242

0.780975

0.748815

0.719025

0.706161

0.67671

0.604265

0

0.005195

0.261036

4,689

162

80

28.944444

0.84733

0.257198

0

0.663265

0

1

0.27551

false

0

0.020408

0.112245

0.632653

0

null

0

1

0

1

0

null

0

1

0

1

0

7

b5ed9e092a526c71953066be3205defd79154b2b

8,086

py

Python

src/VDrone/nanopb/ahrs_pb2.py

brandonbraun653/VirtualDrone

b779167ef3328340015aec46f1e2623c39ee4c0c

[ "MIT" ]

null

src/VDrone/nanopb/ahrs_pb2.py

brandonbraun653/VirtualDrone

b779167ef3328340015aec46f1e2623c39ee4c0c

[ "MIT" ]

null

src/VDrone/nanopb/ahrs_pb2.py

brandonbraun653/VirtualDrone

b779167ef3328340015aec46f1e2623c39ee4c0c

[ "MIT" ]

null

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: ahrs.proto """Generated protocol buffer code.""" 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='ahrs.proto', package='', syntax='proto2', serialized_options=None, create_key=_descriptor._internal_create_key, serialized_pb=b'\n\nahrs.proto\"A\n\x0b\x41\x63\x63\x65lSample\x12\t\n\x01x\x18\x01 \x02(\x02\x12\t\n\x01y\x18\x02 \x02(\x02\x12\t\n\x01z\x18\x03 \x02(\x02\x12\x11\n\ttimestamp\x18\x04 \x02(\r\"@\n\nGyroSample\x12\t\n\x01x\x18\x01 \x02(\x02\x12\t\n\x01y\x18\x02 \x02(\x02\x12\t\n\x01z\x18\x03 \x02(\x02\x12\x11\n\ttimestamp\x18\x04 \x02(\r\"?\n\tMagSample\x12\t\n\x01x\x18\x01 \x02(\x02\x12\t\n\x01y\x18\x02 \x02(\x02\x12\t\n\x01z\x18\x03 \x02(\x02\x12\x11\n\ttimestamp\x18\x04 \x02(\r' ) _ACCELSAMPLE = _descriptor.Descriptor( name='AccelSample', full_name='AccelSample', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='x', full_name='AccelSample.x', index=0, number=1, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='y', full_name='AccelSample.y', index=1, number=2, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='z', full_name='AccelSample.z', index=2, number=3, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='AccelSample.timestamp', 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, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=14, serialized_end=79, ) _GYROSAMPLE = _descriptor.Descriptor( name='GyroSample', full_name='GyroSample', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='x', full_name='GyroSample.x', index=0, number=1, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='y', full_name='GyroSample.y', index=1, number=2, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='z', full_name='GyroSample.z', index=2, number=3, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='GyroSample.timestamp', 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, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=81, serialized_end=145, ) _MAGSAMPLE = _descriptor.Descriptor( name='MagSample', full_name='MagSample', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='x', full_name='MagSample.x', index=0, number=1, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='y', full_name='MagSample.y', index=1, number=2, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='z', full_name='MagSample.z', index=2, number=3, type=2, cpp_type=6, label=2, has_default_value=False, default_value=float(0), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='MagSample.timestamp', 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, serialized_options=None, file=DESCRIPTOR, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=147, serialized_end=210, ) DESCRIPTOR.message_types_by_name['AccelSample'] = _ACCELSAMPLE DESCRIPTOR.message_types_by_name['GyroSample'] = _GYROSAMPLE DESCRIPTOR.message_types_by_name['MagSample'] = _MAGSAMPLE _sym_db.RegisterFileDescriptor(DESCRIPTOR) AccelSample = _reflection.GeneratedProtocolMessageType('AccelSample', (_message.Message,), { 'DESCRIPTOR' : _ACCELSAMPLE, '__module__' : 'ahrs_pb2' # @@protoc_insertion_point(class_scope:AccelSample) }) _sym_db.RegisterMessage(AccelSample) GyroSample = _reflection.GeneratedProtocolMessageType('GyroSample', (_message.Message,), { 'DESCRIPTOR' : _GYROSAMPLE, '__module__' : 'ahrs_pb2' # @@protoc_insertion_point(class_scope:GyroSample) }) _sym_db.RegisterMessage(GyroSample) MagSample = _reflection.GeneratedProtocolMessageType('MagSample', (_message.Message,), { 'DESCRIPTOR' : _MAGSAMPLE, '__module__' : 'ahrs_pb2' # @@protoc_insertion_point(class_scope:MagSample) }) _sym_db.RegisterMessage(MagSample) # @@protoc_insertion_point(module_scope)

37.785047

488

0.738931

1,047

8,086

5.393505

0.115568

0.055251

0.084115

0.076501

0.757039

0.742164

0.735081

0.712237

0

0.035045

0.135419

8,086

213

489

37.962441

0.772708

0.043285

0

0.713514

1

0.005405

0.117959

0.060987

0

1

0

false

0

0.021622

0

0.021622

0

null

0

1

0

1

0

null

0

7

bd17ea3443a966419ddced7f8488b3f8ed0cb321

156

py

Python

app/api/__init__.py

najens/item_catalog

1d5a3d6d2edc1b65bfab72c6a3a6644729ecf79d

[ "MIT" ]

null

app/api/__init__.py

najens/item_catalog

1d5a3d6d2edc1b65bfab72c6a3a6644729ecf79d

[ "MIT" ]

null

app/api/__init__.py

najens/item_catalog

1d5a3d6d2edc1b65bfab72c6a3a6644729ecf79d

[ "MIT" ]

null

from flask import Blueprint # Setup api blueprint api = Blueprint('api', __name__) # Import blueprint views from .views import categories, items # noqa

17.333333

44

0.75641

20

156

5.7

0.55

0.263158

0

0.173077

156

8

45

19.5

0.883721

0.301282

0

0.028571

0

1

0

false

0

0.666667

0

0.666667

1

0

null

1

0

1

0

null

0

1

0

1

0

7

951755bb41c5dd031feec0bdeaac7ded927d7cea

3,125

py

Python

tests/test_event_handler.py

begor/follower_maze

d76315e5085d4566f5730d70b51559b2262bc827

[ "MIT" ]

null

tests/test_event_handler.py

begor/follower_maze

d76315e5085d4566f5730d70b51559b2262bc827

[ "MIT" ]

null

tests/test_event_handler.py

begor/follower_maze

d76315e5085d4566f5730d70b51559b2262bc827

[ "MIT" ]

null

import unittest from follower_maze import events from tests import factories from tests.helpers import async_test class TestEventHandler(unittest.TestCase): """ Test case for EventHandler. Mostly test correct ordering of events. Client notifies are tested in test_pipeline. """ @async_test async def tearDown(self): await events.handler.EventHandler.reset() @async_test async def test_one_event_in_order(self): event = factories.get_broadcast_event(1) await events.handler.EventHandler.new(event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 1) @async_test async def test_two_events_in_order(self): first_event = factories.get_broadcast_event(1) await events.handler.EventHandler.new(first_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 1) second_event = factories.get_broadcast_event(2) await events.handler.EventHandler.new(second_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 2) @async_test async def test_one_event_out_order(self): event = factories.get_broadcast_event(2) await events.handler.EventHandler.new(event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 0) @async_test async def test_two_events_out_order(self): second_event = factories.get_broadcast_event(2) await events.handler.EventHandler.new(second_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 0) first_event = factories.get_broadcast_event(3) await events.handler.EventHandler.new(first_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 0) @async_test async def test_two_events_mixed_order(self): second_event = factories.get_broadcast_event(2) await events.handler.EventHandler.new(second_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 0) first_event = factories.get_broadcast_event(1) await events.handler.EventHandler.new(first_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 2) @async_test async def test_four_events_mixed_order(self): fourth_event = factories.get_broadcast_event(4) await events.handler.EventHandler.new(fourth_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 0) second_event = factories.get_broadcast_event(2) await events.handler.EventHandler.new(second_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 0) first_event = factories.get_broadcast_event(1) await events.handler.EventHandler.new(first_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 2) third_event = factories.get_broadcast_event(3) await events.handler.EventHandler.new(third_event) self.assertEqual(await events.handler.EventHandler.get_seq_no(), 4) if __name__ == '__main__': unittest.main()

34.340659

75

0.72768

398

3,125

5.437186

0.145729

0.127079

0.207948

0.34658

0.822089

0.792514

0.753235

0

0.00943

0.1856

3,125

90

76

34.722222

0.840864

0.03616

0

0.603448

0

0.002688

0

0.206897

1

0

false

0

0.068966

0

0.086207

0

null

0

1

0

null

0

8

20fa7c51432920af387ab79f17e647054a42c628

286

py

Python

avionix/chart/__init__.py

Maxiimeeb/avionix

c149e4319c8c8c00d50450ec1644545340ff7322

[ "BSD-3-Clause" ]

51

2020-07-17T11:42:44.000Z

2022-03-17T23:51:28.000Z

avionix/chart/__init__.py

Maxiimeeb/avionix

c149e4319c8c8c00d50450ec1644545340ff7322

[ "BSD-3-Clause" ]

55

2020-07-14T21:21:14.000Z

2022-03-04T22:43:10.000Z

avionix/chart/__init__.py

Maxiimeeb/avionix

c149e4319c8c8c00d50450ec1644545340ff7322

[ "BSD-3-Clause" ]

9

2021-01-05T01:52:14.000Z

2022-02-16T12:42:18.000Z

# flake8: noqa from avionix.chart.chart_builder import ChartBuilder from avionix.chart.chart_dependency import ChartDependency from avionix.chart.chart_info import ChartInfo from avionix.chart.chart_maintainer import ChartMaintainer from avionix.chart.values_yaml import Value, Values

35.75

58

0.867133

38

286

6.394737

0.447368

0.226337

0.329218

0.345679

0

0.003831

0.087413

286

7

59

40.857143

0.927203

0.041958

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

2f1d83b8039eedbbe91d800cb7c7788ac6a89ee4

1,191

py

Python

Beepitett_teszt.py

balcsi32/OpenNRE-1

63f2662228b37a38af78ced864a38e0238511d26

[ "MIT" ]

null

Beepitett_teszt.py

balcsi32/OpenNRE-1

63f2662228b37a38af78ced864a38e0238511d26

[ "MIT" ]

null

Beepitett_teszt.py

balcsi32/OpenNRE-1

63f2662228b37a38af78ced864a38e0238511d26

[ "MIT" ]

null

import opennre model = opennre.get_model('wiki80_cnn_softmax') print(model.infer({'text': 'He was the son of Máel Dúin mac Máele Fithrich, and grandson of the high king Áed Uaridnach (died 612).', 'h': {'pos': (18, 46)}, 't': {'pos': (78, 91)}})) model = opennre.get_model('wiki80_bert_softmax') print(model.infer({'text': 'He was the son of Máel Dúin mac Máele Fithrich, and grandson of the high king Áed Uaridnach (died 612).', 'h': {'pos': (18, 46)}, 't': {'pos': (78, 91)}})) model = opennre.get_model('wiki80_bertentity_softmax') print(model.infer({'text': 'He was the son of Máel Dúin mac Máele Fithrich, and grandson of the high king Áed Uaridnach (died 612).', 'h': {'pos': (18, 46)}, 't': {'pos': (78, 91)}})) model = opennre.get_model('tacred_bert_softmax') print(model.infer({'text': 'He was the son of Máel Dúin mac Máele Fithrich, and grandson of the high king Áed Uaridnach (died 612).', 'h': {'pos': (18, 46)}, 't': {'pos': (78, 91)}})) model = opennre.get_model('tacred_bertentity_softmax') print(model.infer({'text': 'He was the son of Máel Dúin mac Máele Fithrich, and grandson of the high king Áed Uaridnach (died 612).', 'h': {'pos': (18, 46)}, 't': {'pos': (78, 91)}}))

99.25

183

0.670865

197

1,191

3.979695

0.192893

0.076531

0.095663

0.127551

0.979592

0.946429

0

0.059281

0.13602

1,191

11

184

108.272727

0.702624

0

0.454545

0

0.454545

0.571788

0.041982

0

1

0

false

0

0.090909

0

0.090909

0.454545

0

null

0

1

0

1

0

1

0

null

0

1

0

9

2f21c5ea86c3499fe0a93827deea60dab3ab1b0a

9,903

py

Python

test/test_cases__yb_chunk_dml_by_integer.py

eloemosynator/YbEasyCli

b35ebe03da07898cfa06ff687cba29cd83268c31

[ "MIT" ]

null

test/test_cases__yb_chunk_dml_by_integer.py

eloemosynator/YbEasyCli

b35ebe03da07898cfa06ff687cba29cd83268c31

[ "MIT" ]

4

2020-06-03T18:11:29.000Z

2022-03-07T20:41:16.000Z

test/test_cases__yb_chunk_dml_by_integer.py

eloemosynator/YbEasyCli

b35ebe03da07898cfa06ff687cba29cd83268c31

[ "MIT" ]

2

2020-05-27T23:43:03.000Z

2022-03-03T23:16:15.000Z

map_out = { r'\d{4}-\d{2}-\d{2} \d{2}:\d{2}:\d{2}.\d{1,6}(-|\+)\d{2}' : 'YYYY-MM-DD HH:MM:SS.FFFFFF-TZ' , r'\d{2}:\d{2}:\d{2}.\d{1,6}' : 'HH:MM:SS.FFFFFF' , r'\d{4}-\d{2}-\d{2}' : 'YYYY-MM-DD'} test_cases = [ test_case( cmd=('yb_chunk_dml_by_integer.py @{argsdir}/yb_chunk_dml_by_integer__args1 ' '--column col4 --execute_chunk_dml') , exit_code=0 , stdout="""-- Running DML chunking. --2020-08-22 18:19:38.201736-06: Starting Integer Chunking, first calculating group counts --2020-08-22 18:19:38.301736-06: Build Chunk Groupings, first pass --2020-08-22 18:19:39.431422-06: Build Chunk DMLs --2020-08-22 18:19:39.522147-06: Chunk: 1, Rows: 100000, Range 1000000 <= col4 < 47500950000 --2020-08-22 18:19:39.822828-06: Chunk: 2, Rows: 100000, Range 47500950000 <= col4 < 90000900000 --2020-08-22 18:19:40.154894-06: Chunk: 3, Rows: 100000, Range 90000900000 <= col4 < 127500850000 --2020-08-22 18:19:40.462646-06: Chunk: 4, Rows: 100000, Range 127500850000 <= col4 < 160000800000 --2020-08-22 18:19:40.781904-06: Chunk: 5, Rows: 100000, Range 160000800000 <= col4 < 187500750000 --2020-08-22 18:19:41.121436-06: Chunk: 6, Rows: 100000, Range 187500750000 <= col4 < 210000700000 --2020-08-22 18:19:41.398286-06: Chunk: 7, Rows: 100000, Range 210000700000 <= col4 < 227500650000 --2020-08-22 18:19:41.758007-06: Chunk: 8, Rows: 100000, Range 227500650000 <= col4 < 240000600000 --2020-08-22 18:19:42.12159-06: Chunk: 9, Rows: 100000, Range 240000600000 <= col4 < 247500550000 --2020-08-22 18:19:42.432212-06: Chunk: 10, Rows: 100000, Range 247500550000 <= col4 < 250000500001 --2020-08-22 18:19:42.672871-06: Chunk: 11, Rows: 0, col4 IS NULL --2020-08-22 18:19:42.916537-06: Completed Integer Chunked DML --Total Rows : 1000000 --IS NULL Rows : 0 --Running total check: PASSED --Duration : 00:00:04.71574 --Overhead duration : 00:00:02.176085 --Total Chunks : 11 --Min chunk size : 100000 --Largest chunk size : 100000 --Average chunk size : 90909 -- Completed DML chunking.""" , stderr='' , map_out=map_out) , test_case( cmd=('yb_chunk_dml_by_integer.py @{argsdir}/yb_chunk_dml_by_integer__args1 ' '--column col4 --print_chunk_dml --null_chunk_off --verbose_chunk_off') , exit_code=0 , stdout="""-- Running DML chunking. INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 1, size: 100000) >>>*/ 1000000 <= col4 AND col4 < 47500950000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 2, size: 100000) >>>*/ 47500950000 <= col4 AND col4 < 90000900000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 3, size: 100000) >>>*/ 90000900000 <= col4 AND col4 < 127500850000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 4, size: 100000) >>>*/ 127500850000 <= col4 AND col4 < 160000800000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 5, size: 100000) >>>*/ 160000800000 <= col4 AND col4 < 187500750000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 6, size: 100000) >>>*/ 187500750000 <= col4 AND col4 < 210000700000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 7, size: 100000) >>>*/ 210000700000 <= col4 AND col4 < 227500650000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 8, size: 100000) >>>*/ 227500650000 <= col4 AND col4 < 240000600000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 9, size: 100000) >>>*/ 240000600000 <= col4 AND col4 < 247500550000 /*<<< chunk_clause */; INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 10, size: 100000) >>>*/ 247500550000 <= col4 AND col4 < 250000500001 /*<<< chunk_clause */; -- Completed DML chunking.""" , stderr='') , test_case( cmd=('yb_chunk_dml_by_integer.py @{argsdir}/yb_chunk_dml_by_integer__args1 ' '--column col4 --print_chunk_dml') , exit_code=0 , stdout="""-- Running DML chunking. --2020-08-22 19:26:27.672082-06: Starting Integer Chunking, first calculating group counts --2020-08-22 19:26:27.801736-06: Build Chunk Groupings, first pass --2020-08-22 19:26:28.922245-06: Build Chunk DMLs --2020-08-22 19:26:29.010727-06: Chunk: 1, Rows: 100000, Range 1000000 <= col4 < 47500950000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 1, size: 100000) >>>*/ 1000000 <= col4 AND col4 < 47500950000 /*<<< chunk_clause */; --2020-08-22 19:26:29.321661-06: Chunk: 2, Rows: 100000, Range 47500950000 <= col4 < 90000900000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 2, size: 100000) >>>*/ 47500950000 <= col4 AND col4 < 90000900000 /*<<< chunk_clause */; --2020-08-22 19:26:29.615457-06: Chunk: 3, Rows: 100000, Range 90000900000 <= col4 < 127500850000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 3, size: 100000) >>>*/ 90000900000 <= col4 AND col4 < 127500850000 /*<<< chunk_clause */; --2020-08-22 19:26:29.913853-06: Chunk: 4, Rows: 100000, Range 127500850000 <= col4 < 160000800000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 4, size: 100000) >>>*/ 127500850000 <= col4 AND col4 < 160000800000 /*<<< chunk_clause */; --2020-08-22 19:26:30.260152-06: Chunk: 5, Rows: 100000, Range 160000800000 <= col4 < 187500750000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 5, size: 100000) >>>*/ 160000800000 <= col4 AND col4 < 187500750000 /*<<< chunk_clause */; --2020-08-22 19:26:30.536624-06: Chunk: 6, Rows: 100000, Range 187500750000 <= col4 < 210000700000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 6, size: 100000) >>>*/ 187500750000 <= col4 AND col4 < 210000700000 /*<<< chunk_clause */; --2020-08-22 19:26:30.822253-06: Chunk: 7, Rows: 100000, Range 210000700000 <= col4 < 227500650000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 7, size: 100000) >>>*/ 210000700000 <= col4 AND col4 < 227500650000 /*<<< chunk_clause */; --2020-08-22 19:26:31.15679-06: Chunk: 8, Rows: 100000, Range 227500650000 <= col4 < 240000600000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 8, size: 100000) >>>*/ 227500650000 <= col4 AND col4 < 240000600000 /*<<< chunk_clause */; --2020-08-22 19:26:31.447927-06: Chunk: 9, Rows: 100000, Range 240000600000 <= col4 < 247500550000 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 9, size: 100000) >>>*/ 240000600000 <= col4 AND col4 < 247500550000 /*<<< chunk_clause */; --2020-08-22 19:26:31.791157-06: Chunk: 10, Rows: 100000, Range 247500550000 <= col4 < 250000500001 INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE /* chunk_clause(chunk: 10, size: 100000) >>>*/ 247500550000 <= col4 AND col4 < 250000500001 /*<<< chunk_clause */; --2020-08-22 19:26:32.112984-06: Chunk: 11, Rows: 0, col4 IS NULL INSERT INTO new_chunked_table SELECT * FROM {db1}.dev.data_types_t WHERE col4 IS NULL; --2020-08-22 19:26:32.349486-06: Completed Integer Chunked DML --Total Rows : 1000000 --IS NULL Rows : 0 --Running total check: PASSED --Duration : 00:00:04.678549 --Overhead duration : 00:00:02.19171 --Total Chunks : 11 --Min chunk size : 100000 --Largest chunk size : 100000 --Average chunk size : 90909 -- Completed DML chunking.""" , stderr='' , map_out=map_out) , test_case( cmd=('yb_chunk_dml_by_integer.py @{argsdir}/yb_chunk_dml_by_integer__args1 ' '--column col1 --column_cardinality high') , exit_code=0 , stdout="""-- Running DML chunking. --2020-12-25 21:16:02.899221-08: Starting Integer Chunking, first calculating group counts --2020-12-25 21:16:03.053718-08: Build Chunk Groupings, first pass --2020-12-25 21:16:03.278257-08: Build Chunk DMLs --2020-12-25 21:16:03.280744-08: Chunk: 1, Rows: 100095, Range 1 <= col1 < 100096 --2020-12-25 21:16:03.283273-08: Chunk: 2, Rows: 100096, Range 100096 <= col1 < 200192 --2020-12-25 21:16:03.285346-08: Chunk: 3, Rows: 100096, Range 200192 <= col1 < 300288 --2020-12-25 21:16:03.287403-08: Chunk: 4, Rows: 100096, Range 300288 <= col1 < 400384 --2020-12-25 21:16:03.289469-08: Chunk: 5, Rows: 100096, Range 400384 <= col1 < 500480 --2020-12-25 21:16:03.291527-08: Chunk: 6, Rows: 100096, Range 500480 <= col1 < 600576 --2020-12-25 21:16:03.293583-08: Chunk: 7, Rows: 100096, Range 600576 <= col1 < 700672 --2020-12-25 21:16:03.295636-08: Chunk: 8, Rows: 100096, Range 700672 <= col1 < 800768 --2020-12-25 21:16:03.297689-08: Chunk: 9, Rows: 100096, Range 800768 <= col1 < 900864 --2020-12-25 21:16:03.299731-08: Chunk: 10, Rows: 99137, Range 900864 <= col1 < 1000001 --2020-12-25 21:16:03.300263-08: Chunk: 11, Rows: 0, col1 IS NULL --2020-12-25 21:16:03.300573-08: Completed Integer Chunked DML --Total Rows : 1000000 --IS NULL Rows : 0 --Running total check: PASSED --Duration : 00:00:00.402947 --Overhead duration : 00:00:00.403053 --Total Chunks : 11 --Min chunk size : 100000 --Largest chunk size : 100096 --Average chunk size : 90909 -- Completed DML chunking. """ , stderr='' , map_out=map_out) ]

73.355556

187

0.688478

1,525

9,903

4.345574

0.125246

0.066395

0.036215

0.063377

0.864946

0.85378

0.787083

0.771541

0.731553

0.565263

0

0.318214

0.153994

9,903

135

188

73.355556

0.472786

0

0.48855

0

0.458015

0.937702

0.079867

0

1

0

false

0.045802

0

0.015267

0

null

0

1

0

1

0

1

0

1

0

null

0

9

2f38da4010203c5618069cf92343e044bc51381a

3,035

py

Python

tests/test_state.py

tulth/gcode_gen

d6e276f2074d4fe66755b2ae06c5b4d85583c563

[ "BSD-3-Clause" ]

null

tests/test_state.py

tulth/gcode_gen

d6e276f2074d4fe66755b2ae06c5b4d85583c563

[ "BSD-3-Clause" ]

null

tests/test_state.py

tulth/gcode_gen

d6e276f2074d4fe66755b2ae06c5b4d85583c563

[ "BSD-3-Clause" ]

null

#!/usr/bin/env python # Sample Test passing with nose and pytest import unittest import numpy as np from gcode_gen.tool import Carbide3D_101 from gcode_gen.state import State, CncState, DEFAULT_START class TestState(unittest.TestCase): def test_create(self): state = State(z_safe=40, position=DEFAULT_START) self.assertEqual(state['z_safe'], 40) actual = state['position'].arr expect = DEFAULT_START.arr self.assertTrue(np.allclose(actual, expect), 'actual: {}\nexpect:{}'.format(actual, expect)) def test_let(self): state = State(z_safe=45, feed_rate=40) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) with state.let(feed_rate=15, z_safe=10): self.assertEqual(state['feed_rate'], 15) self.assertEqual(state['z_safe'], 10) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) def test_excursion(self): state = State(z_safe=45, feed_rate=40) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) with state.excursion(): state['z_safe'] = -12 state['feed_rate'] = 100 self.assertEqual(state['feed_rate'], 100) self.assertEqual(state['z_safe'], -12) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) def test_excursion_nosave(self): state = State(z_safe=45, feed_rate=40) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) with state.excursion(nosave=('z_safe', )): state['z_safe'] = -12 state['feed_rate'] = 100 self.assertEqual(state['feed_rate'], 100) self.assertEqual(state['z_safe'], -12) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], -12) class TestCncState(unittest.TestCase): def test_create(self): tool = Carbide3D_101() state = CncState(tool=tool, z_safe=40) self.assertEqual(state['tool'], tool) self.assertEqual(state['z_safe'], 40) actual = state['position'].arr expect = DEFAULT_START.arr self.assertTrue(np.allclose(actual, expect), 'actual: {}\nexpect:{}'.format(actual, expect)) def test_let(self): tool = Carbide3D_101() state = CncState(tool=tool, z_safe=45, feed_rate=40) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) with state.let(feed_rate=15, z_safe=10): self.assertEqual(state['feed_rate'], 15) self.assertEqual(state['z_safe'], 10) self.assertEqual(state['feed_rate'], 40) self.assertEqual(state['z_safe'], 45) def test_copy(self): tool = Carbide3D_101() state = CncState(milling_feed_rate=40) self.assertEqual(state['milling_feed_rate'], 40) self.assertEqual(state.copy()['milling_feed_rate'], 40)

37.9375

100

0.627348

391

3,035

4.693095

0.14578

0.237057

0.316076

0.179837

0.844687

0.836512

0.783651

0.743324

0

0.048718

0.228995

3,035

79

101

38.417722

0.73547

0.020099

0

0.727273

0

0.109018

0

0.469697

1

0.106061

false

0

0.060606

0

0.19697

0

null

1

0

1

0

null

0

1

0

11

85de22e455744b19d39cd570d4793e152800e526

37

py

Python

CSES-Problemset/introductory/bit_strings.py

rranjan14/cp-solutions

9614508efbed1e4ee8b970b5eed535d782a5783f

[ "MIT" ]

null

CSES-Problemset/introductory/bit_strings.py

rranjan14/cp-solutions

9614508efbed1e4ee8b970b5eed535d782a5783f

[ "MIT" ]

null

CSES-Problemset/introductory/bit_strings.py

rranjan14/cp-solutions

9614508efbed1e4ee8b970b5eed535d782a5783f

[ "MIT" ]

null

print((1<<(int(input())))%1000000007)

37

0.648649

5

37

4.8

1

0

0.297297

0

37

1

37

0.351351

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

7

85e05eb0d9ef2433d7fc89cda418d8fb1813c0d8

2,194

py

Python

products/tests/test_resources.py

jszafran/w84it

62ce3160dcc0e188f2e9d4d7df1f7abe12bd14f7

[ "MIT" ]

1

2019-04-14T10:08:46.000Z

products/tests/test_resources.py

jszafran/w84it

62ce3160dcc0e188f2e9d4d7df1f7abe12bd14f7

[ "MIT" ]

14

2019-01-30T16:22:30.000Z

2020-06-05T20:02:51.000Z

products/tests/test_resources.py

jszafran/w84it

62ce3160dcc0e188f2e9d4d7df1f7abe12bd14f7

[ "MIT" ]

null

datasets = { 'full_valid_data': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my-product.com', 'price': 23.5, 'currency': 'USD', 'work_start_date': '2018-12-01', 'launch_date': '2019-05-25' }, 'invalid_data_url': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my pro_duct.com', 'price': 23.5, 'currency': 'USD', 'work_start_date': '2018-12-01', 'launch_date': '2019-05-25' }, 'invalid_data_price_too_many_decimals': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my-product.com', 'price': 23.523342, 'currency': 'USD', 'work_start_date': '2018-12-01', 'launch_date': '2019-05-25' }, 'invalid_data_price_too_many_digits': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my-product.com', 'price': 1234571233223.52, 'currency': 'USD', 'work_start_date': '2018-12-01', 'launch_date': '2019-05-25' }, 'invalid_data_price_too_manay_digits_and_decimals': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my-product.com', 'price': 1234571233223.52233, 'currency': 'USD', 'work_start_date': '2018-12-01', 'launch_date': '2019-05-25' }, 'invalid_data_price_with_no_currency': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my-product.com', 'price': 125.99, 'currency': '-', 'work_start_date': '2018-12-01', 'launch_date': '2019-05-25' }, 'invalid_data_wrong_dates': {'name': 'test_product', 'description': 'Its going to be awesome!', 'url': 'http://my-product.com', 'price': 125.99, 'currency': '-', 'work_start_date': '2018-14-01', 'launch_date': '2019-17-32' } }

33.242424

55

0.514585

246

2,194

4.353659

0.219512

0.052288

0.098039

0.169935

0.897292

0

0.110892

0.305378

2,194

65

56

33.753846

0.591864

0

0.661538

0

0.530538

0.080675

0

1

0

false

0

null

0

1

0

null

0

7

c82d3bae716464df96943ff0245f82c02d42a86e

99

py

Python

src/eztao/ts/__init__.py

ywx649999311/EzTao

d4d27ac17c675b585e0443f822240df88fcdef57

[ "MIT" ]

11

2020-12-10T13:11:37.000Z

2022-03-28T21:00:19.000Z

src/eztao/ts/__init__.py

ywx649999311/EzTao

d4d27ac17c675b585e0443f822240df88fcdef57

[ "MIT" ]

33

2020-12-09T02:01:43.000Z

2022-03-21T19:53:00.000Z

src/eztao/ts/__init__.py

ywx649999311/EzTao

d4d27ac17c675b585e0443f822240df88fcdef57

[ "MIT" ]

3

2020-12-10T17:27:12.000Z

2021-11-12T05:55:33.000Z

from .utils import * from .carma_fit import * from .carma_sim import * from .carma_mcmc import mcmc

24.75

28

0.777778

16

99

4.625

0.4375

0.405405

0.608108

0

0.151515

99

4

28

24.75

0.880952

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

c85c0f638aea1efcb267a4be5aebb81e515f0ccc

1,680

py

Python

home/migrations/0037_auto_20220126_1535.py

ianshulx/egiportal

3a147a4a61e58f2a6229e08a5a4c256d7b674b81

[ "MIT" ]

1

2022-02-17T10:34:21.000Z

home/migrations/0037_auto_20220126_1535.py

ianshulx/egiportal

3a147a4a61e58f2a6229e08a5a4c256d7b674b81

[ "MIT" ]

null

home/migrations/0037_auto_20220126_1535.py

ianshulx/egiportal

3a147a4a61e58f2a6229e08a5a4c256d7b674b81

[ "MIT" ]

null

# Generated by Django 3.1.14 on 2022-01-26 10:05 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('home', '0036_auto_20211226_1358'), ] operations = [ migrations.AlterField( model_name='book', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), migrations.AlterField( model_name='event1', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), migrations.AlterField( model_name='image', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), migrations.AlterField( model_name='main_event', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), migrations.AlterField( model_name='notice', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), migrations.AlterField( model_name='notice1', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), migrations.AlterField( model_name='quiz', name='id', field=models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID'), ), ]

34.285714

108

0.594048

177

1,680

5.457627

0.265537

0.086957

0.181159

0.210145

0.774327

0

0.028192

0.282143

1,680

48

109

35

0.772803

0.027381

0

0.666667

1

0

0.059436

0.014093

0

1

0

false

0

0.02381

0

0.095238

0

null

0

1

0

1

0

1

0

null

0

8

8d02c02c656b0fbcc39368efcf9f923d45d7db16

25,118

py

Python

forest/binary_trees/single_threaded_binary_trees.py

shunsvineyard/forest-python

729c2980fbb9f90b056cb92ca5eb0ad6091a2dc5

[ "MIT" ]

8

2021-03-17T21:31:10.000Z

2022-01-26T17:07:59.000Z

forest/binary_trees/single_threaded_binary_trees.py

shunsvineyard/forest-python

729c2980fbb9f90b056cb92ca5eb0ad6091a2dc5

[ "MIT" ]

20

2021-03-09T07:23:53.000Z

2022-01-29T22:10:24.000Z

forest/binary_trees/single_threaded_binary_trees.py

shunsvineyard/forest-python

729c2980fbb9f90b056cb92ca5eb0ad6091a2dc5

[ "MIT" ]

null

# Copyright © 2021 by Shun Huang. All rights reserved. # Licensed under MIT License. # See LICENSE in the project root for license information. """Single Threaded Binary Search Trees.""" import dataclasses from typing import Any, Optional from forest.binary_trees import traversal from forest import tree_exceptions @dataclasses.dataclass class Node: """Single Threaded Tree node definition.""" key: Any data: Any left: Optional["Node"] = None right: Optional["Node"] = None parent: Optional["Node"] = None is_thread: bool = False class RightThreadedBinaryTree: """Right Threaded Binary Tree. Attributes ---------- root: `Optional[Node]` The root node of the right threaded binary search tree. empty: `bool` `True` if the tree is empty; `False` otherwise. Methods ------- Core Functions search(key: `Any`) Look for a node based on the given key. insert(key: `Any`, data: `Any`) Insert a (key, data) pair into a binary tree. delete(key: `Any`) Delete a node based on the given key from the binary tree. Auxiliary Functions get_leftmost(node: `Node`) Return the node whose key is the smallest from the given subtree. get_rightmost(node: `Node` = `None`) Return the node whose key is the biggest from the given subtree. get_successor(node: `Node`) Return the successor node in the in-order order. get_predecessor(node: `Node`) Return the predecessor node in the in-order order. get_height(node: `Optional[Node]`) Return the height of the given node. Traversal Functions inorder_traverse() In-order traversal by using the right threads. preorder_traverse() Pre-order traversal by using the right threads. """ def __init__(self) -> None: self.root: Optional[Node] = None def __repr__(self) -> str: """Provie the tree representation to visualize its layout.""" if self.root: return ( f"{type(self)}, root={self.root}, " f"tree_height={str(self.get_height(self.root))}" ) return "empty tree" @property def empty(self) -> bool: """bool: `True` if the tree is empty; `False` otherwise. Notes ----- The property, `empty`, is read-only. """ return self.root is None def search(self, key: Any) -> Optional[Node]: """Look for a node by a given key. Parameters ---------- key: `Any` The key associated with the node. Returns ------- `Optional[Node]` The node found by the given key. If the key does not exist, return `None`. """ current = self.root while current: if key == current.key: return current elif key < current.key: current = current.left else: # key > current.key if current.is_thread: break current = current.right return None def insert(self, key: Any, data: Any) -> None: """Insert a (key, data) pair into the binary search tree. Parameters ---------- key: `Any` The key associated with the data. data: `Any` The data to be inserted. Raises ------ `DuplicateKeyError` Raised if the key to be insted has existed in the tree. """ new_node = Node(key=key, data=data) parent: Optional[Node] = None current: Optional[Node] = self.root while current: parent = current if new_node.key < current.key: current = current.left elif new_node.key > current.key: # If the node is thread, meaning it's a leaf node. if current.is_thread: current = None else: current = current.right else: raise tree_exceptions.DuplicateKeyError(key=new_node.key) new_node.parent = parent # If the tree is empty if parent is None: self.root = new_node elif new_node.key < parent.key: parent.left = new_node # Update thread new_node.right = parent new_node.is_thread = True else: # Update thread new_node.is_thread = parent.is_thread new_node.right = parent.right parent.is_thread = False # Parent's right must be set after thread update parent.right = new_node def delete(self, key: Any) -> None: """Delete a node according to the given key. Parameters ---------- key: `Any` The key of the node to be deleted. """ if self.root and (deleting_node := self.search(key=key)): # Case 1: no child if deleting_node.left is None and ( deleting_node.right is None or deleting_node.is_thread ): self._transplant(deleting_node=deleting_node, replacing_node=None) # Case 2a: only one left child elif deleting_node.left and ( deleting_node.is_thread or deleting_node.right is None # deleting_node.right is None means the deleting node is the root. ): predecessor = self.get_predecessor(node=deleting_node) if predecessor: predecessor.right = deleting_node.right self._transplant( deleting_node=deleting_node, replacing_node=deleting_node.left ) # Case 2b: only one right child elif deleting_node.left is None and deleting_node.is_thread is False: self._transplant( deleting_node=deleting_node, replacing_node=deleting_node.right ) # Case 3: two children elif ( deleting_node.left and deleting_node.right and deleting_node.is_thread is False ): predecessor = self.get_predecessor(node=deleting_node) replacing_node: Node = self.get_leftmost(node=deleting_node.right) # the leftmost node is not the direct child of the deleting node if replacing_node.parent != deleting_node: if replacing_node.is_thread: self._transplant( deleting_node=replacing_node, replacing_node=None ) else: self._transplant( deleting_node=replacing_node, replacing_node=replacing_node.right, ) replacing_node.right = deleting_node.right replacing_node.right.parent = replacing_node replacing_node.is_thread = False self._transplant( deleting_node=deleting_node, replacing_node=replacing_node ) replacing_node.left = deleting_node.left replacing_node.left.parent = replacing_node if predecessor and predecessor.is_thread: predecessor.right = replacing_node else: raise RuntimeError("Invalid case. Should never happened") @staticmethod def get_leftmost(node: Node) -> Node: """Return the leftmost node from a given subtree. The key of the leftmost node is the smallest key in the given subtree. Parameters ---------- node: `Node` The root of the subtree. Returns ------- `Node` The node whose key is the smallest from the subtree of the given node. """ current_node = node while current_node.left: current_node = current_node.left return current_node @staticmethod def get_rightmost(node: Node) -> Node: """Return the rightmost node from a given subtree. The key of the rightmost node is the biggest key in the given subtree. Parameters ---------- node: `Node` The root of the subtree. Returns ------- `Node` The node whose key is the biggest from the subtree of the given node. """ current_node = node while current_node.is_thread is False and current_node.right: current_node = current_node.right return current_node @staticmethod def get_successor(node: Node) -> Optional[Node]: """Return the successor in the in-order order. Parameters ---------- node: `Node` The node to get its successor. Returns ------- `Optional[Node]` The successor node. """ if node.is_thread: return node.right else: if node.right: return RightThreadedBinaryTree.get_leftmost(node=node.right) # if node.right is None, it means no successor of the given node. return None @staticmethod def get_predecessor(node: Node) -> Optional[Node]: """Return the predecessor in the in-order order. Parameters ---------- node: `Node` The node to get its predecessor. Returns ------- `Optional[Node]` The predecessor node. """ if node.left: return RightThreadedBinaryTree.get_rightmost(node=node.left) parent = node.parent while parent and node == parent.left: node = parent parent = parent.parent return parent @staticmethod def get_height(node: Optional[Node]) -> int: """Get the height of the given subtree. Parameters ---------- node: `Optional[Node]` The root of the subtree to get its height. Returns ------- `int` The height of the given subtree. 0 if the subtree has only one node. """ if node: if node.left and node.is_thread is False: return ( max( RightThreadedBinaryTree.get_height(node.left), RightThreadedBinaryTree.get_height(node.right), ) + 1 ) if node.left: return RightThreadedBinaryTree.get_height(node=node.left) + 1 if node.is_thread is False: return RightThreadedBinaryTree.get_height(node=node.right) + 1 return 0 def inorder_traverse(self) -> traversal.Pairs: """Use the right threads to traverse the tree in in-order order. Yields ------ `Pairs` The next (key, data) pair in the tree in-order traversal. """ if self.root: current: Optional[Node] = self.get_leftmost(node=self.root) while current: yield (current.key, current.data) if current.is_thread: current = current.right else: if current.right is None: break current = self.get_leftmost(current.right) def preorder_traverse(self) -> traversal.Pairs: """Use the right threads to traverse the tree in pre-order order. Yields ------ `Pairs` The next (key, data) pair in the tree pre-order traversal. """ current = self.root while current: yield (current.key, current.data) if current.is_thread: # If a node is thread, it must have a right child. current = current.right.right # type: ignore else: current = current.left def _transplant(self, deleting_node: Node, replacing_node: Optional[Node]) -> None: if deleting_node.parent is None: self.root = replacing_node if self.root: self.root.is_thread = False elif deleting_node == deleting_node.parent.left: deleting_node.parent.left = replacing_node if replacing_node: if deleting_node.is_thread: if replacing_node.is_thread: replacing_node.right = replacing_node.right else: # deleting_node == deleting_node.parent.right deleting_node.parent.right = replacing_node if replacing_node: if deleting_node.is_thread: if replacing_node.is_thread: replacing_node.right = replacing_node.right else: deleting_node.parent.right = deleting_node.right deleting_node.parent.is_thread = True if replacing_node: replacing_node.parent = deleting_node.parent class LeftThreadedBinaryTree: """Left Threaded Binary Tree. Attributes ---------- root: `Optional[Node]` The root node of the left threaded binary search tree. empty: `bool` `True` if the tree is empty; `False` otherwise. Methods ------- Core Functions search(key: `Any`) Look for a node based on the given key. insert(key: `Any`, data: `Any`) Insert a (key, data) pair into a binary tree. delete(key: `Any`) Delete a node based on the given key from the binary tree. Auxiliary Functions get_leftmost(node: `Node`) Return the node whose key is the smallest from the given subtree. get_rightmost(node: `Node` = `None`) Return the node whose key is the biggest from the given subtree. get_successor(node: `Node`) Return the successor node in the in-order order. get_predecessor(node: `Node`) Return the predecessor node in the in-order order. get_height(node: `Optional[Node]`) Return the height of the given node. Traversal Function reverse_inorder_traverse() Reversed In-order traversal by using the left threads. """ def __init__(self) -> None: self.root: Optional[Node] = None def __repr__(self) -> str: """Provie the tree representation to visualize its layout.""" if self.root: return ( f"{type(self)}, root={self.root}, " f"tree_height={str(self.get_height(self.root))}" ) return "empty tree" @property def empty(self) -> bool: """bool: `True` if the tree is empty; `False` otherwise. Notes ----- The property, `empty`, is read-only. """ return self.root is None def search(self, key: Any) -> Optional[Node]: """Look for a node by a given key. Parameters ---------- key: `Any` The key associated with the node. Returns ------- `Optional[Node]` The node found by the given key. If the key does not exist, return `None`. """ current = self.root while current: if key == current.key: return current elif key < current.key: if current.is_thread is False: current = current.left else: break else: # key > current.key: current = current.right return None def insert(self, key: Any, data: Any) -> None: """Insert a (key, data) pair into the binary search tree. Parameters ---------- key: `Any` The key associated with the data. data: `Any` The data to be inserted. Raises ------ `DuplicateKeyError` Raised if the key to be insted has existed in the tree. """ new_node = Node(key=key, data=data) parent: Optional[Node] = None current: Optional[Node] = self.root while current: parent = current if new_node.key < current.key: # If the node is thread, meaning it's a leaf node. if current.is_thread: current = None else: current = current.left elif new_node.key > current.key: current = current.right else: raise tree_exceptions.DuplicateKeyError(key=new_node.key) new_node.parent = parent # If the tree is empty if parent is None: self.root = new_node elif new_node.key > parent.key: parent.right = new_node # Update thread new_node.left = parent new_node.is_thread = True else: # Update thread new_node.is_thread = parent.is_thread new_node.left = parent.left parent.is_thread = False # Parent's left must be set after thread update parent.left = new_node def delete(self, key: Any) -> None: """Delete a node according to the given key. Parameters ---------- key: `Any` The key of the node to be deleted. """ if self.root and (deleting_node := self.search(key=key)): # Case 1: no child if deleting_node.right is None and ( deleting_node.left is None or deleting_node.is_thread ): self._transplant(deleting_node=deleting_node, replacing_node=None) # Case 2a: only one left child elif (deleting_node.right is None) and (deleting_node.is_thread is False): self._transplant( deleting_node=deleting_node, replacing_node=deleting_node.left ) # Case 2b: only one right child elif deleting_node.right and ( deleting_node.is_thread or deleting_node.left is None # deleting_node.left is None means the deleting node is the root. ): successor = self.get_successor(node=deleting_node) if successor: successor.left = deleting_node.left self._transplant( deleting_node=deleting_node, replacing_node=deleting_node.right ) # Case 3: two children elif deleting_node.right and deleting_node.left: replacing_node: Node = self.get_leftmost(node=deleting_node.right) successor = self.get_successor(node=replacing_node) # the leftmost node is not the direct child of the deleting node if replacing_node.parent != deleting_node: self._transplant( deleting_node=replacing_node, replacing_node=replacing_node.right, ) replacing_node.right = deleting_node.right replacing_node.right.parent = replacing_node self._transplant( deleting_node=deleting_node, replacing_node=replacing_node ) replacing_node.left = deleting_node.left replacing_node.left.parent = replacing_node replacing_node.is_thread = False if successor and successor.is_thread: successor.left = replacing_node else: raise RuntimeError("Invalid case. Should never happened") @staticmethod def get_leftmost(node: Node) -> Node: """Return the leftmost node from a given subtree. The key of the leftmost node is the smallest key in the given subtree. Parameters ---------- node: `Node` The root of the subtree. Returns ------- `Node` The node whose key is the smallest from the subtree of the given node. """ current_node = node while current_node.left and current_node.is_thread is False: current_node = current_node.left return current_node @staticmethod def get_rightmost(node: Node) -> Node: """Return the rightmost node from a given subtree. The key of the rightmost node is the biggest key in the given subtree. Parameters ---------- node: `Node` The root of the subtree. Returns ------- `Node` The node whose key is the biggest from the subtree of the given node. """ current_node = node while current_node.right: current_node = current_node.right return current_node @staticmethod def get_successor(node: Node) -> Optional[Node]: """Return the successor in the in-order order. Parameters ---------- node: `Node` The node to get its successor. Returns ------- `Optional[Node]` The successor node. """ if node.right: return LeftThreadedBinaryTree.get_leftmost(node=node.right) parent = node.parent while parent and node == parent.right: node = parent parent = parent.parent return parent @staticmethod def get_predecessor(node: Node) -> Optional[Node]: """Return the predecessor in the in-order order. Parameters ---------- node: `Node` The node to get its predecessor. Returns ------- `Optional[Node]` The predecessor node. """ if node.is_thread: return node.left else: if node.left: return LeftThreadedBinaryTree.get_rightmost(node=node.left) # if node.left is None, it means no predecessor of the given node. return None @staticmethod def get_height(node: Optional[Node]) -> int: """Get the height of the given subtree. Parameters ---------- node: `Optional[Node]` The root of the subtree to get its height. Returns ------- `int` The height of the given subtree. 0 if the subtree has only one node. """ if node: if node.right and node.is_thread is False: return ( max( LeftThreadedBinaryTree.get_height(node.left), LeftThreadedBinaryTree.get_height(node.right), ) + 1 ) if node.right: return LeftThreadedBinaryTree.get_height(node=node.right) + 1 if node.is_thread is False: return LeftThreadedBinaryTree.get_height(node=node.left) + 1 return 0 def reverse_inorder_traverse(self) -> traversal.Pairs: """Use the left threads to traverse the tree in reversed in-order. Yields ------ `Pairs` The next (key, data) pair in the tree reversed in-order traversal. """ if self.root: current: Optional[Node] = self.get_rightmost(node=self.root) while current: yield (current.key, current.data) if current.is_thread: current = current.left else: if current.left is None: break current = self.get_rightmost(current.left) def _transplant(self, deleting_node: Node, replacing_node: Optional[Node]) -> None: if deleting_node.parent is None: self.root = replacing_node if self.root: self.root.is_thread = False elif deleting_node == deleting_node.parent.left: deleting_node.parent.left = replacing_node if replacing_node: if deleting_node.is_thread: if replacing_node.is_thread: replacing_node.left = deleting_node.left else: deleting_node.parent.left = deleting_node.left deleting_node.parent.is_thread = True else: # deleting_node == deleting_node.parent.right deleting_node.parent.right = replacing_node if replacing_node: if deleting_node.is_thread: if replacing_node.is_thread: replacing_node.left = deleting_node.left if replacing_node: replacing_node.parent = deleting_node.parent

32.326898

87

0.54654

2,775

25,118

4.824865

0.062703

0.085145

0.029577

0.025245

0.896183

0.872657

0.822765

0.789305

0.753753

0.733064

0

0.001401

0.374672

25,118

776

88

32.368557

0.850958

0.304722

0

0.740541

0

0.016367

0.005754

0

1

0.072973

false

0

0.010811

0

0.194595

0

null

0

1

0

1

0

null

0

7

23c2c853b1909952905413106beeb47782455d4e

6,451

py

Python

tests/test_ttt_computer.py

larryworm1127/tic-tac-toe-python

327b43d36948fc41ef9c902f40c7f67fab793b89

[ "MIT" ]

null

tests/test_ttt_computer.py

larryworm1127/tic-tac-toe-python

327b43d36948fc41ef9c902f40c7f67fab793b89

[ "MIT" ]

null

tests/test_ttt_computer.py

larryworm1127/tic-tac-toe-python

327b43d36948fc41ef9c902f40c7f67fab793b89

[ "MIT" ]

null

""" Test module for ttt_computer.py """ from ttt_game.ttt_computer import * from ttt_game.ttt_board import * def test_minimax_win_row() -> None: """ x x o | x o x | o o x x | o o | x x o o o | x x | x Test if computer can win the game with win case on a row of the board. """ game_board = [[PLAYERX, PLAYERX, PLAYERO], [EMPTY, PLAYERX, PLAYERX], [PLAYERO, EMPTY, PLAYERO]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 1, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERX, PLAYERO, PLAYERX], [EMPTY, PLAYERO, PLAYERO], [PLAYERX, EMPTY, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 1, "Bad Move X: " + str(move[0]) assert move[1] == 0, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERO, EMPTY], [PLAYERX, PLAYERX, PLAYERO], [PLAYERX, EMPTY, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 0, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) def test_minimax_win_col() -> None: """ x | x o o | o o x o o x | o | o x x o x | x o x | x Test if computer can win the game with win case on a column of the board. """ game_board = [[PLAYERX, EMPTY, EMPTY], [PLAYERO, PLAYERO, PLAYERX], [PLAYERX, PLAYERO, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERX) assert move[0] == 0, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERX, PLAYERO, PLAYERO], [EMPTY, EMPTY, PLAYERO], [PLAYERX, PLAYERO, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERX) assert move[0] == 1, "Bad Move X: " + str(move[0]) assert move[1] == 0, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERO, PLAYERX], [EMPTY, PLAYERO, PLAYERX], [PLAYERX, EMPTY, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERX) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) def test_minimax_win_diag() -> None: """ x x | o x x o o x | x o o | o Test if computer can win the game with win case on a diagonal of the board. """ game_board = [[PLAYERX, PLAYERX, EMPTY], [PLAYERO, PLAYERO, PLAYERX], [PLAYERO, EMPTY, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 0, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERX, PLAYERX], [PLAYERX, PLAYERO, EMPTY], [PLAYERO, EMPTY, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) def test_minimax_def_row() -> None: """ x x | o x | x o x o | x x | o o o x | o o x | x x Test if computer can defend with a opponent win case on a row of the board. """ game_board = [[PLAYERX, PLAYERX, EMPTY], [PLAYERX, PLAYERO, EMPTY], [PLAYERO, PLAYERO, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 0, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERX, EMPTY], [PLAYERX, PLAYERX, EMPTY], [PLAYERO, PLAYERO, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 1, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERX, PLAYERO, EMPTY], [PLAYERO, EMPTY, EMPTY], [PLAYERX, PLAYERX, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) def test_minimax_def_col() -> None: """ x o x | o x o | o o x x x o | x x o | x o x o | x | x Test if computer can defend with a opponent win case on a column of the board. """ game_board = [[PLAYERX, PLAYERO, PLAYERX], [PLAYERX, PLAYERX, PLAYERO], [EMPTY, EMPTY, PLAYERO]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 0, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERX, PLAYERO], [PLAYERX, PLAYERX, PLAYERO], [EMPTY, EMPTY, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 1, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERO, PLAYERX], [PLAYERX, PLAYERO, PLAYERX], [EMPTY, PLAYERX, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) def test_minimax_def_diag() -> None: """ x o x | o o x x x o | x x o o | x Check if computer can defend with opponent win case on a diagonal of the board. """ game_board = [[PLAYERX, PLAYERO, PLAYERX], [PLAYERX, PLAYERX, PLAYERO], [PLAYERO, EMPTY, EMPTY]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 2, "Bad Move Y: " + str(move[1]) game_board = [[PLAYERO, PLAYERO, PLAYERX], [PLAYERX, PLAYERX, PLAYERO], [EMPTY, EMPTY, PLAYERX]] board = TTTBoard(3, _custom_board=game_board) move = get_move(board, PLAYERO) assert move[0] == 2, "Bad Move X: " + str(move[0]) assert move[1] == 0, "Bad Move Y: " + str(move[1]) if __name__ == '__main__': import pytest pytest.main(['test_ttt_computer.py'])

35.838889

79

0.578515

954

6,451

3.793501

0.052411

0.07958

0.085106

0.088422

0.934512

0.891406

0.856038

0.843051

0.836419

0.827024

0

0.023881

0.272981

6,451

179

80

36.039106

0.747761

0.126337

0

0.719626

0

0.075486

0

0.299065

1

0.056075

false

0

0.028037

0

0.084112

0

null

0

1

0

1

0

null

0

7

f1975bb62e6d07bcb094be5904e32d28b229ac24

217

py

Python

src/elastic/fortex/elastic/__init__.py

Piyush13y/forte-wrappers

250df428a8705f769d53eb070f89c3f66e713015

[ "Apache-2.0" ]

3

2021-06-17T18:52:00.000Z

2022-01-11T19:15:21.000Z

src/elastic/fortex/elastic/__init__.py

Piyush13y/forte-wrappers

250df428a8705f769d53eb070f89c3f66e713015

[ "Apache-2.0" ]

66

2021-03-30T15:04:11.000Z

2022-03-24T04:35:11.000Z

src/elastic/fortex/elastic/__init__.py

Piyush13y/forte-wrappers

250df428a8705f769d53eb070f89c3f66e713015

[ "Apache-2.0" ]

10

2021-03-16T19:48:31.000Z

2022-03-01T05:48:17.000Z

from fortex.elastic.elastic_search_processor import * from fortex.elastic.elastic_indexer import * from fortex.elastic.elastic_search_index_processor import * from fortex.elastic.elastic_search_query_creator import *

43.4

59

0.870968

29

217

6.206897

0.344828

0.222222

0.377778

0.533333

0.833333

0.666667

0

0.073733

217

4

60

54.25

0.895522

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

9

f1b198cb8ef82f1b30561e725dbb35523ecdd446

26,360

py

Python

XKT/SKT/net.py

bigdata-ustc/XKT

b3ac07541b92001b62d7cff4e8fe7e5a69c5c93c

[ "MIT" ]

17

2019-09-11T12:00:05.000Z

2022-03-30T04:41:05.000Z

XKT/SKT/net.py

bigdata-ustc/XKT

b3ac07541b92001b62d7cff4e8fe7e5a69c5c93c

[ "MIT" ]

1

2021-10-24T01:13:33.000Z

2021-10-24T02:03:26.000Z

XKT/SKT/net.py

bigdata-ustc/XKT

b3ac07541b92001b62d7cff4e8fe7e5a69c5c93c

[ "MIT" ]

6

2019-09-13T07:50:07.000Z

2022-03-12T00:22:11.000Z

# coding: utf-8 # 2021/8/22 @ tongshiwei from baize.mxnet.utils import format_sequence, mask_sequence_variable_length from mxnet import gluon import mxnet as mx from XKT.utils.nn import GRUCell, begin_states, get_states, expand_tensor from .utils import Graph def get_net(ku_num, graph_params=None, net_type="SKT", k=2, **kwargs): if net_type == "SKT": return SKT(ku_num, graph_params, **kwargs) elif net_type == "SKT_TE": return SKT_TE(ku_num, **kwargs) elif net_type == "SKTPart": return SKTPart(ku_num, graph_params, **kwargs) elif net_type == "SKTSync": return SKTSync(ku_num, graph_params, **kwargs) else: raise NotImplementedError class SKT(gluon.Block): def __init__(self, ku_num, graph_params=None, alpha=0.5, latent_dim=None, activation=None, hidden_num=90, concept_dim=None, # dropout=0.5, self_dropout=0.0, dropout=0.0, self_dropout=0.5, # dropout=0.0, self_dropout=0.0, sync_activation="relu", sync_dropout=0.0, prop_activation="relu", prop_dropout=0.0, agg_activation="relu", agg_dropout=0.0, prefix=None, params=None): super(SKT, self).__init__(prefix=prefix, params=params) self.ku_num = int(ku_num) self.hidden_num = self.ku_num if hidden_num is None else int(hidden_num) self.latent_dim = self.hidden_num if latent_dim is None else int(latent_dim) self.concept_dim = self.hidden_num if concept_dim is None else int(concept_dim) graph_params = graph_params if graph_params is not None else [] self.graph = Graph.from_file(ku_num, graph_params) self.alpha = alpha sync_activation = sync_activation if activation is None else activation prop_activation = prop_activation if activation is None else activation agg_activation = agg_activation if activation is None else activation with self.name_scope(): self.rnn = GRUCell(self.hidden_num) self.response_embedding = gluon.nn.Embedding(2 * self.ku_num, self.latent_dim) self.concept_embedding = gluon.nn.Embedding(self.ku_num, self.concept_dim) self.f_self = gluon.rnn.GRUCell(self.hidden_num) # self.f_self = gluon.nn.Sequential() # self.f_self.add( # gluon.nn.Dense(self.hidden_num), # gluon.nn.Activation("relu") # ) self.self_dropout = gluon.nn.Dropout(self_dropout) self.f_prop = gluon.nn.Sequential() self.f_prop.add( gluon.nn.Dense(self.hidden_num, flatten=False), gluon.nn.Activation(prop_activation), gluon.nn.Dropout(prop_dropout), ) self.f_sync = gluon.nn.Sequential() self.f_sync.add( gluon.nn.Dense(self.hidden_num, flatten=False), gluon.nn.Activation(sync_activation), gluon.nn.Dropout(sync_dropout), ) self.f_agg = gluon.nn.Sequential() self.f_agg.add( gluon.nn.Dense(self.hidden_num, flatten=False), # gluon.nn.InstanceNorm(), # gluon.nn.LayerNorm(), # gluon.nn.BatchNorm(), gluon.nn.Activation(agg_activation), gluon.nn.Dropout(agg_dropout), ) self.dropout = gluon.nn.Dropout(dropout) self.out = gluon.nn.Dense(1, flatten=False) def neighbors(self, x, ordinal=True): return self.graph.neighbors(x, ordinal) def successors(self, x, ordinal=True): return self.graph.successors(x, ordinal) def forward(self, questions, answers, valid_length=None, states=None, layout='NTC', compressed_out=True, *args, **kwargs): ctx = questions.context length = questions.shape[1] inputs, axis, F, batch_size = format_sequence(length, questions, layout, False) answers, _, _, _ = format_sequence(length, answers, layout, False) if states is None: states = begin_states([(batch_size, self.ku_num, self.hidden_num)], self.prefix)[0] states = states.as_in_context(ctx) outputs = [] all_states = [] for i in range(length): # self - influence _self_state = get_states(inputs[i], states) # fc # _next_self_state = self.f_self(mx.nd.concat(_self_state, self.response_embedding(answers[i]), dim=-1)) # gru _next_self_state, _ = self.f_self(self.response_embedding(answers[i]), [_self_state]) # _next_self_state = self.f_self(mx.nd.concat(_self_hidden_states, _self_state)) # _next_self_state, _ = self.f_self(_self_hidden_states, [_self_state]) _next_self_state = self.self_dropout(_next_self_state) # get self mask _self_mask = mx.nd.expand_dims(mx.nd.one_hot(inputs[i], self.ku_num), -1) _self_mask = mx.nd.broadcast_to(_self_mask, (0, 0, self.hidden_num)) # find neighbors _neighbors = self.neighbors(inputs[i]) _neighbors_mask = mx.nd.expand_dims(mx.nd.array(_neighbors, ctx=ctx), -1) _neighbors_mask = mx.nd.broadcast_to(_neighbors_mask, (0, 0, self.hidden_num)) # synchronization _broadcast_next_self_states = mx.nd.expand_dims(_next_self_state, 1) _broadcast_next_self_states = mx.nd.broadcast_to(_broadcast_next_self_states, (0, self.ku_num, 0)) # _sync_diff = mx.nd.concat(states, _broadcast_next_self_states, concept_embeddings, dim=-1) _sync_diff = mx.nd.concat(states, _broadcast_next_self_states, dim=-1) _sync_inf = _neighbors_mask * self.f_sync(_sync_diff) # reflection on current vertex _reflec_inf = mx.nd.sum(_sync_inf, axis=1) _reflec_inf = mx.nd.broadcast_to(mx.nd.expand_dims(_reflec_inf, 1), (0, self.ku_num, 0)) _sync_inf = _sync_inf + _self_mask * _reflec_inf # find successors _successors = self.successors(inputs[i]) _successors_mask = mx.nd.expand_dims(mx.nd.array(_successors, ctx=ctx), -1) _successors_mask = mx.nd.broadcast_to(_successors_mask, (0, 0, self.hidden_num)) # propagation # _prop_diff = mx.nd.concat(_next_self_state - _self_state, self.concept_embedding(inputs[i]), dim=-1) _prop_diff = _next_self_state - _self_state # 1 _prop_inf = self.f_prop(_prop_diff) _prop_inf = _successors_mask * mx.nd.broadcast_to(mx.nd.expand_dims(_prop_inf, axis=1), (0, self.ku_num, 0)) # 2 # _broadcast_diff = mx.nd.broadcast_to(mx.nd.expand_dims(_prop_diff, axis=1), (0, self.ku_num, 0)) # _pro_inf = _successors_mask * self.f_prop( # mx.nd.concat(_broadcast_diff, concept_embeddings, dim=-1) # ) # _pro_inf = _successors_mask * self.f_prop( # _broadcast_diff # ) # concept embedding concept_embeddings = self.concept_embedding.weight.data(ctx) concept_embeddings = expand_tensor(concept_embeddings, 0, batch_size) # concept_embeddings = (_self_mask + _successors_mask + _neighbors_mask) * concept_embeddings # aggregate _inf = self.f_agg(self.alpha * _sync_inf + (1 - self.alpha) * _prop_inf) # next_states, _ = self.rnn(_inf, [states]) next_states, _ = self.rnn(mx.nd.concat(_inf, concept_embeddings, dim=-1), [states]) # states = (1 - _self_mask) * next_states + _self_mask * _broadcast_next_self_states states = next_states output = mx.nd.sigmoid(mx.nd.squeeze(self.out(self.dropout(states)), axis=-1)) outputs.append(output) if valid_length is not None and not compressed_out: all_states.append([states]) if valid_length is not None: if compressed_out: states = None else: states = [mx.nd.SequenceLast(mx.nd.stack(*ele_list, axis=0), sequence_length=valid_length, use_sequence_length=True, axis=0) for ele_list in zip(*all_states)] outputs = mask_sequence_variable_length(mx.nd, outputs, length, valid_length, axis, True) outputs, _, _, _ = format_sequence(length, outputs, layout, merge=True) return outputs, states class SKTPart(SKT): def __init__(self, ku_num, graph_params=None, latent_dim=None, activation=None, hidden_num=90, concept_dim=None, dropout=0.0, self_dropout=0.0, prop_activation="relu", prop_dropout=0.0, prefix=None, params=None): super(SKT, self).__init__(prefix=prefix, params=params) self.ku_num = int(ku_num) self.hidden_num = self.ku_num if hidden_num is None else int(hidden_num) self.latent_dim = self.hidden_num if latent_dim is None else int(latent_dim) self.concept_dim = self.hidden_num if concept_dim is None else int(concept_dim) graph_params = graph_params if graph_params is not None else [] self.graph = Graph.from_file(ku_num, graph_params) prop_activation = prop_activation if activation is None else activation with self.name_scope(): self.rnn = GRUCell(self.hidden_num) self.response_embedding = gluon.nn.Embedding(2 * self.ku_num, self.latent_dim) self.concept_embedding = gluon.nn.Embedding(self.ku_num, self.concept_dim) self.f_self = gluon.rnn.GRUCell(self.hidden_num) # self.f_self = gluon.nn.Sequential() # self.f_self.add( # gluon.nn.Dense(self.hidden_num), # gluon.nn.Activation("relu") # ) self.self_dropout = gluon.nn.Dropout(self_dropout) self.f_prop = gluon.nn.Sequential() self.f_prop.add( gluon.nn.Dense(self.hidden_num, flatten=False), gluon.nn.Activation(prop_activation), gluon.nn.Dropout(prop_dropout), ) # self.f_sync = gluon.nn.Sequential() # self.f_sync.add( # gluon.nn.Dense(self.hidden_num, flatten=False), # gluon.nn.Activation(sync_activation), # gluon.nn.Dropout(sync_dropout), # ) # self.f_reflec = gluon.nn.Sequential() # self.f_reflec.add( # gluon.nn.Dense(self.hidden_num, flatten=False), # gluon.nn.Activation(sync_activation), # gluon.nn.Dropout(sync_dropout), # ) # self.f_agg = gluon.nn.Sequential() # self.f_agg.add( # gluon.nn.Dense(self.hidden_num, flatten=False), # # gluon.nn.InstanceNorm(), # # gluon.nn.LayerNorm(), # # gluon.nn.BatchNorm(), # gluon.nn.Activation(agg_activation), # gluon.nn.Dropout(agg_dropout), # ) self.dropout = gluon.nn.Dropout(dropout) self.out = gluon.nn.Dense(1, flatten=False) def forward(self, questions, answers, valid_length=None, states=None, layout='NTC', compressed_out=True, *args, **kwargs): ctx = questions.context length = questions.shape[1] inputs, axis, F, batch_size = format_sequence(length, questions, layout, False) answers, _, _, _ = format_sequence(length, answers, layout, False) if states is None: states = begin_states([(batch_size, self.ku_num, self.hidden_num)], self.prefix)[0] states = states.as_in_context(ctx) outputs = [] all_states = [] for i in range(length): # self - influence _self_state = get_states(inputs[i], states) # fc # _next_self_state = self.f_self(mx.nd.concat(_self_state, self.response_embedding(answers[i]), dim=-1)) # gru _next_self_state, _ = self.f_self(self.response_embedding(answers[i]), [_self_state]) # _next_self_state = self.f_self(mx.nd.concat(_self_hidden_states, _self_state)) # _next_self_state, _ = self.f_self(_self_hidden_states, [_self_state]) _next_self_state = self.self_dropout(_next_self_state) # get self mask _self_mask = mx.nd.expand_dims(mx.nd.one_hot(inputs[i], self.ku_num), -1) _self_mask = mx.nd.broadcast_to(_self_mask, (0, 0, self.hidden_num)) # self-concept embedding # _self_concept_embedding = self.concept_embedding(inputs[i]) # _broadcast_self_concept_embedding = mx.nd.expand_dims(_self_concept_embedding, dim=1) # _broadcast_self_concept_embedding = mx.nd.broadcast_to(_broadcast_self_concept_embedding, # (0, self.ku_num, 0)) # concept embedding concept_embeddings = self.concept_embedding.weight.data(ctx) concept_embeddings = expand_tensor(concept_embeddings, 0, batch_size) # concept_embeddings = (_self_mask + _successors_mask + _neighbors_mask) * concept_embeddings # find successors _successors = self.successors(inputs[i]) _successors_mask = mx.nd.expand_dims(mx.nd.array(_successors, ctx=ctx), -1) _successors_mask = mx.nd.broadcast_to(_successors_mask, (0, 0, self.hidden_num)) _broadcast_next_self_states = mx.nd.expand_dims(_next_self_state, 1) _broadcast_next_self_states = mx.nd.broadcast_to(_broadcast_next_self_states, (0, self.ku_num, 0)) # propagation # _prop_diff = mx.nd.concat(_next_self_state - _self_state, self.concept_embedding(inputs[i]), dim=-1) _prop_diff = _next_self_state - _self_state # 1 _prop_inf = self.f_prop( mx.nd.concat(mx.nd.broadcast_to(mx.nd.expand_dims(_prop_diff, axis=1), (0, self.ku_num, 0)), concept_embeddings, dim=-1)) _prop_inf = _successors_mask * _prop_inf # aggregate # _inf = self.f_agg(_prop_inf) _inf = _prop_inf # next_states, _ = self.rnn(_inf, [states]) next_states, _ = self.rnn(_inf, [states]) updated = _successors_mask * next_states + _self_mask * _broadcast_next_self_states states = updated + (1 - _successors_mask - _self_mask) * states # states = next_states output = mx.nd.sigmoid(mx.nd.squeeze(self.out(self.dropout(states)), axis=-1)) outputs.append(output) if valid_length is not None and not compressed_out: all_states.append([states]) if valid_length is not None: if compressed_out: states = None else: states = [mx.nd.SequenceLast(mx.nd.stack(*ele_list, axis=0), sequence_length=valid_length, use_sequence_length=True, axis=0) for ele_list in zip(*all_states)] outputs = mask_sequence_variable_length(mx.nd, outputs, length, valid_length, axis, True) outputs, _, _, _ = format_sequence(length, outputs, layout, merge=True) return outputs, states class SKT_TE(gluon.Block): def __init__(self, ku_num, latent_dim=None, hidden_num=90, concept_dim=None, dropout=0.0, self_dropout=0.5, prefix=None, params=None): super(SKT_TE, self).__init__(prefix=prefix, params=params) self.ku_num = int(ku_num) self.hidden_num = self.ku_num if hidden_num is None else int(hidden_num) self.latent_dim = self.hidden_num if latent_dim is None else int(latent_dim) self.concept_dim = self.hidden_num if concept_dim is None else int(concept_dim) with self.name_scope(): self.response_embedding = gluon.nn.Embedding(2 * self.ku_num, self.latent_dim) self.f_self = gluon.rnn.GRUCell(self.hidden_num) self.self_dropout = gluon.nn.Dropout(self_dropout) self.dropout = gluon.nn.Dropout(dropout) self.out = gluon.nn.Dense(1, flatten=False) def forward(self, questions, answers, valid_length=None, states=None, layout='NTC', compressed_out=True, *args, **kwargs): ctx = questions.context length = questions.shape[1] inputs, axis, F, batch_size = format_sequence(length, questions, layout, False) answers, _, _, _ = format_sequence(length, answers, layout, False) if states is None: states = begin_states([(batch_size, self.ku_num, self.hidden_num)], self.prefix)[0] states = states.as_in_context(ctx) outputs = [] all_states = [] for i in range(length): # self - influence _self_state = get_states(inputs[i], states) # fc # _next_self_state = self.f_self(mx.nd.concat(_self_state, self.response_embedding(answers[i]), dim=-1)) # gru _next_self_state, _ = self.f_self(self.response_embedding(answers[i]), [_self_state]) # _next_self_state = self.f_self(mx.nd.concat(_self_hidden_states, _self_state)) # _next_self_state, _ = self.f_self(_self_hidden_states, [_self_state]) _next_self_state = self.self_dropout(_next_self_state) # get self mask _self_mask = mx.nd.expand_dims(mx.nd.one_hot(inputs[i], self.ku_num), -1) _self_mask = mx.nd.broadcast_to(_self_mask, (0, 0, self.hidden_num)) _broadcast_next_self_states = mx.nd.expand_dims(_next_self_state, 1) _broadcast_next_self_states = mx.nd.broadcast_to(_broadcast_next_self_states, (0, self.ku_num, 0)) states = (1 - _self_mask) * states + _self_mask * _broadcast_next_self_states output = mx.nd.sigmoid(mx.nd.squeeze(self.out(self.dropout(states)), axis=-1)) outputs.append(output) if valid_length is not None and not compressed_out: all_states.append([states]) if valid_length is not None: if compressed_out: states = None else: states = [mx.nd.SequenceLast(mx.nd.stack(*ele_list, axis=0), sequence_length=valid_length, use_sequence_length=True, axis=0) for ele_list in zip(*all_states)] outputs = mask_sequence_variable_length(mx.nd, outputs, length, valid_length, axis, True) outputs, _, _, _ = format_sequence(length, outputs, layout, merge=True) return outputs, states class SKTSync(SKT): def __init__(self, ku_num, graph_params=None, alpha=0.5, latent_dim=None, activation=None, hidden_num=90, concept_dim=None, dropout=0.0, self_dropout=0.0, sync_activation="relu", sync_dropout=0.0, prop_activation="relu", prop_dropout=0.0, agg_activation="relu", agg_dropout=0.0, prefix=None, params=None): super(SKT, self).__init__(prefix=prefix, params=params) self.ku_num = int(ku_num) self.hidden_num = self.ku_num if hidden_num is None else int(hidden_num) self.latent_dim = self.hidden_num if latent_dim is None else int(latent_dim) self.concept_dim = self.hidden_num if concept_dim is None else int(concept_dim) graph_params = graph_params if graph_params is not None else [] self.graph = Graph.from_file(ku_num, graph_params) self.alpha = alpha sync_activation = sync_activation if activation is None else activation with self.name_scope(): self.rnn = GRUCell(self.hidden_num) self.response_embedding = gluon.nn.Embedding(2 * self.ku_num, self.latent_dim) self.concept_embedding = gluon.nn.Embedding(self.ku_num, self.concept_dim) self.f_self = gluon.rnn.GRUCell(self.hidden_num) # self.f_self = gluon.nn.Sequential() # self.f_self.add( # gluon.nn.Dense(self.hidden_num), # gluon.nn.Activation("relu") # ) self.self_dropout = gluon.nn.Dropout(self_dropout) self.f_sync = gluon.nn.Sequential() self.f_sync.add( gluon.nn.Dense(self.hidden_num, flatten=False), gluon.nn.Activation(sync_activation), gluon.nn.Dropout(sync_dropout), ) self.f_reflec = gluon.nn.Sequential() self.f_reflec.add( gluon.nn.Dense(self.hidden_num, flatten=False), gluon.nn.Activation(sync_activation), gluon.nn.Dropout(sync_dropout), ) self.dropout = gluon.nn.Dropout(dropout) self.out = gluon.nn.Dense(1, flatten=False) def forward(self, questions, answers, valid_length=None, states=None, layout='NTC', compressed_out=True, *args, **kwargs): ctx = questions.context length = questions.shape[1] inputs, axis, F, batch_size = format_sequence(length, questions, layout, False) answers, _, _, _ = format_sequence(length, answers, layout, False) if states is None: states = begin_states([(batch_size, self.ku_num, self.hidden_num)], self.prefix)[0] states = states.as_in_context(ctx) outputs = [] all_states = [] for i in range(length): # self - influence _self_state = get_states(inputs[i], states) # fc # _next_self_state = self.f_self(mx.nd.concat(_self_state, self.response_embedding(answers[i]), dim=-1)) # gru _next_self_state, _ = self.f_self(self.response_embedding(answers[i]), [_self_state]) # _next_self_state = self.f_self(mx.nd.concat(_self_hidden_states, _self_state)) # _next_self_state, _ = self.f_self(_self_hidden_states, [_self_state]) _next_self_state = self.self_dropout(_next_self_state) # get self mask _self_mask = mx.nd.expand_dims(mx.nd.one_hot(inputs[i], self.ku_num), -1) _self_mask = mx.nd.broadcast_to(_self_mask, (0, 0, self.hidden_num)) # self-concept embedding _self_concept_embedding = self.concept_embedding(inputs[i]) # _broadcast_self_concept_embedding = mx.nd.expand_dims(_self_concept_embedding, dim=1) # _broadcast_self_concept_embedding = mx.nd.broadcast_to(_broadcast_self_concept_embedding, # (0, self.ku_num, 0)) # concept embedding concept_embeddings = self.concept_embedding.weight.data(ctx) concept_embeddings = expand_tensor(concept_embeddings, 0, batch_size) # concept_embeddings = (_self_mask + _successors_mask + _neighbors_mask) * concept_embeddings # find neighbors _neighbors = self.neighbors(inputs[i]) _neighbors_mask = mx.nd.expand_dims(mx.nd.array(_neighbors, ctx=ctx), -1) _neighbors_mask = mx.nd.broadcast_to(_neighbors_mask, (0, 0, self.hidden_num)) # synchronization _broadcast_next_self_states = mx.nd.expand_dims(_next_self_state, 1) _broadcast_next_self_states = mx.nd.broadcast_to(_broadcast_next_self_states, (0, self.ku_num, 0)) # _sync_diff = mx.nd.concat(states, _broadcast_next_self_states, concept_embeddings, dim=-1) _sync_diff = mx.nd.concat(states, _broadcast_next_self_states, dim=-1) _sync_inf = _neighbors_mask * self.f_sync( mx.nd.concat(_sync_diff, concept_embeddings, dim=-1) ) # reflection on current vertex _reflec_diff = mx.nd.concat(mx.nd.sum(_neighbors_mask * states, axis=1) + _next_self_state, _self_concept_embedding, dim=-1) # _reflec_diff = mx.nd.concat(mx.nd.sum(_neighbors_mask * states, axis=1), _next_self_state, # _self_concept_embedding, dim=-1) _reflec_inf = self.f_reflec(_reflec_diff) _reflec_inf = mx.nd.broadcast_to(mx.nd.expand_dims(_reflec_inf, 1), (0, self.ku_num, 0)) _sync_inf = _sync_inf + _self_mask * _reflec_inf # aggregate _inf = _sync_inf next_states, _ = self.rnn(_inf, [states]) states = (_neighbors_mask + _self_mask) * next_states + (1 - _neighbors_mask - _self_mask) * states # states = next_states output = mx.nd.sigmoid(mx.nd.squeeze(self.out(self.dropout(states)), axis=-1)) outputs.append(output) if valid_length is not None and not compressed_out: all_states.append([states]) if valid_length is not None: if compressed_out: states = None else: states = [mx.nd.SequenceLast(mx.nd.stack(*ele_list, axis=0), sequence_length=valid_length, use_sequence_length=True, axis=0) for ele_list in zip(*all_states)] outputs = mask_sequence_variable_length(mx.nd, outputs, length, valid_length, axis, True) outputs, _, _, _ = format_sequence(length, outputs, layout, merge=True) return outputs, states

50.40153

120

0.600948

3,266

26,360

4.514697

0.048071

0.024144

0.037911

0.029976

0.942421

0.928518

0.923228

0.905934

0.901458

0.894744

0

0.009399

0.297724

26,360

522

121

50.498084

0.787111

0.171965

0

0.81686

0

0.003041

0

1

0.031977

false

0

0.014535

0.005814

0.087209

0

null

0

1

0

1

0

null

0

7

f1d5fa9e9f93ced1bd2634dfa6e734849ffc9cf4

7,537

py

Python

muon.py

avain/DeepLearningTutorial

423de3f4595a357167e01e9145b5147c611976bc

[ "MIT" ]

1

2018-07-03T08:30:24.000Z

muon.py

avain/DeepLearningTutorial

423de3f4595a357167e01e9145b5147c611976bc

[ "MIT" ]

null

muon.py

avain/DeepLearningTutorial

423de3f4595a357167e01e9145b5147c611976bc

[ "MIT" ]

null

from mxnet import gluon,nd,autograd,metric import matplotlib.pyplot as plt import numpy as np class CreateModel(gluon.nn.Block): def __init__(self,layer,ctx,precision, **kwargs): super(CreateModel, self).__init__(**kwargs) self.layer=layer self.precision=precision self.ctx=ctx self.layer.cast(self.precision) def grad_check_first_layer(self): print( self.layer[0].weight ) print( self.layer[0].weight.grad().sum() ) def forward(self,x): #print(x) return self.layer(x) def fit(self,train_gen,test_gen,epochs,print_every, loss_with_softmax,optimizer): trainer=gluon.Trainer(params=self.collect_params(), optimizer=optimizer) # Initialize some objects for the metrics acc=metric.Accuracy() train_acc_records=[] test_acc_records=[] loss_records=[] for e in range(epochs): for i,(data,label) in enumerate(train_gen): data=data.as_in_context(self.ctx).astype(self.precision) label=label.as_in_context(self.ctx).astype(np.float32) with autograd.record(): label_linear=self.layer(data) label_linear=label_linear.astype(np.float32) # Improve accuracy, as suggested in nVIDIA's SDK. loss=loss_with_softmax(label_linear,label) loss.backward() trainer.step(batch_size=128) # Print the metrics every several iterations. if (i%print_every==0): # print metrics for train (current batch) & test data. label_pred = nd.argmax( nd.softmax(label_linear ), axis=1) acc.reset() acc.update(preds=label_pred, labels=label) train_acc=acc.get()[1] test_acc =self.evaluate_accuracy(test_gen, self.layer) train_acc_records.append(train_acc) test_acc_records.append(test_acc) curr_loss = nd.mean(loss).asscalar() loss_records.append(curr_loss) print("epoch=%2s, iter=%5d, loss=%10f, train acc=%10f, test_acc=%10f"%(e,i,curr_loss,train_acc,test_acc)) # Visialize the calculated metrics of accuracy during of training. self.viz_training(train_acc_records,test_acc_records,loss_records) def evaluate_accuracy(self,data_iterator, net): '''Given model and data, the model accuracy will be calculated.''' acc = metric.Accuracy() for i, (data, label) in enumerate(data_iterator): data = data.as_in_context(self.ctx).astype(self.precision) label = label.as_in_context(self.ctx).astype(self.precision) output = net(data) predictions = nd.argmax(output, axis=1) acc.update(preds=predictions, labels=label) return acc.get()[1] def viz_training(self,train_acc_records,test_acc_records,loss_records): """show how the metrics such as loss and model accuracy varies in the progress of training""" fig,axes=plt.subplots(1,2,figsize=(18,6),dpi=120) axes[0].plot(train_acc_records,ms=5,marker='o',label='train acc',ls='--') axes[0].plot(test_acc_records,ms=5,marker='o',label='val acc',ls='--') axes[0].legend() axes[1].plot(loss_records,ms=5,marker='o',label='train loss',ls='--') axes[1].legend() for idx,ax in enumerate(axes): ax.set_xlabel('Epoch') if idx==0: ax.set_ylabel('Accuracy') else: ax.set_ylabel('Loss') plt.show() class CreateHybridModel(gluon.nn.HybridBlock): def __init__(self,layer,ctx,precision, **kwargs): super(CreateHybridModel, self).__init__(**kwargs) self.layer=layer self.precision=precision self.ctx=ctx self.layer.cast(self.precision) def grad_check_first_layer(self): print( self.layer[0].weight ) print( self.layer[0].weight.grad().sum() ) def hybrid_forward(self,F,x): #print(x) return self.layer(x) def fit(self,train_gen,test_gen,epochs,print_every, loss_with_softmax,optimizer): trainer=gluon.Trainer(params=self.collect_params(), optimizer=optimizer) # Initialize some objects for the metrics acc=metric.Accuracy() train_acc_records=[] test_acc_records=[] loss_records=[] for e in range(epochs): for i,(data,label) in enumerate(train_gen): data=data.as_in_context(self.ctx).astype(self.precision) label=label.as_in_context(self.ctx).astype(np.float32) with autograd.record(): label_linear=self.layer(data) label_linear=label_linear.astype(np.float32) # Improve accuracy, as suggested in nVIDIA's SDK. loss=loss_with_softmax(label_linear,label) loss.backward() trainer.step(batch_size=128) # Print the metrics every several iterations. if (i%print_every==0): # print metrics for train (current batch) & test data. label_pred = nd.argmax( nd.softmax(label_linear ), axis=1) acc.reset() acc.update(preds=label_pred, labels=label) train_acc=acc.get()[1] test_acc =self.evaluate_accuracy(test_gen, self.layer) train_acc_records.append(train_acc) test_acc_records.append(test_acc) curr_loss = nd.mean(loss).asscalar() loss_records.append(curr_loss) print("epoch=%2s, iter=%5d, loss=%10f, train acc=%10f, test_acc=%10f"%(e,i,curr_loss,train_acc,test_acc)) # Visialize the calculated metrics of accuracy during of training. self.viz_training(train_acc_records,test_acc_records,loss_records) def evaluate_accuracy(self,data_iterator, net): '''Given model and data, the model accuracy will be calculated.''' acc = metric.Accuracy() for i, (data, label) in enumerate(data_iterator): data = data.as_in_context(self.ctx).astype(self.precision) label = label.as_in_context(self.ctx).astype(self.precision) output = net(data) predictions = nd.argmax(output, axis=1) acc.update(preds=predictions, labels=label) return acc.get()[1] def viz_training(self,train_acc_records,test_acc_records,loss_records): """show how the metrics such as loss and model accuracy varies in the progress of training""" fig,axes=plt.subplots(1,2,figsize=(18,6),dpi=120) axes[0].plot(train_acc_records,ms=5,marker='o',label='train acc',ls='--') axes[0].plot(test_acc_records,ms=5,marker='o',label='val acc',ls='--') axes[0].legend() axes[1].plot(loss_records,ms=5,marker='o',label='train loss',ls='--') axes[1].legend() for idx,ax in enumerate(axes): ax.set_xlabel('Epoch') if idx==0: ax.set_ylabel('Accuracy') else: ax.set_ylabel('Loss') plt.show()

40.521505

125

0.587502

942

7,537

4.525478

0.159236

0.037532

0.035186

0.028149

0.952381

0.934084

0

0.014736

0.297731

7,537

186

126

40.521505

0.790667

0.108001

0

0.932331

0

0.033772

0

1

0.090226

false

0

0.022556

0.015038

0.157895

0.075188

0

null

0

1

0

1

0

null

0

7

7b25b32d34f39e82f502f67be69100c1ed37da03

2,619

py

Python

tests/parser/choice.48.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/choice.48.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/choice.48.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

input = """ % This is a synthetic example documenting a bug in an early version of DLV's % backjumping algorithm. % The abstract computation tree looks as follows (choice order should be fixed % by disabling heuristics with -OH-): % % o % a / \ -a % / \_..._ % o \ % b / \ -b {-a,-b,f} % / \ % o o % incons incons based on a and b % based % only % on b % % The backjumping algorithm wrongly determined that in the bottom left % subtree both inconsistencies are based only on the choice of b and % therefore stopped the entire search, missing the model on the right. a | -a. b | -b. % taking b causes inconsistency x :- b. y :- b. :- x,y. % taking -b causes m1 to be false, but only with a % taking -b unconditionally causes d to be false :- -b, a, m1. :- -b, d. % falsity of m1 and d causes violation of the following constraint % the reasons are obviously the choice for b and the choice for a :- not m1, not d. % give m1 a chance to be true % if not allow a model with g (which does not exist as m1 will be false there % but together with -b it causes inconsistency, and taking b also entails % inconsistency) m1 | g. % avoid d to be always false % and allow a model with f d | f. """ output = """ % This is a synthetic example documenting a bug in an early version of DLV's % backjumping algorithm. % The abstract computation tree looks as follows (choice order should be fixed % by disabling heuristics with -OH-): % % o % a / \ -a % / \_..._ % o \ % b / \ -b {-a,-b,f} % / \ % o o % incons incons based on a and b % based % only % on b % % The backjumping algorithm wrongly determined that in the bottom left % subtree both inconsistencies are based only on the choice of b and % therefore stopped the entire search, missing the model on the right. a | -a. b | -b. % taking b causes inconsistency x :- b. y :- b. :- x,y. % taking -b causes m1 to be false, but only with a % taking -b unconditionally causes d to be false :- -b, a, m1. :- -b, d. % falsity of m1 and d causes violation of the following constraint % the reasons are obviously the choice for b and the choice for a :- not m1, not d. % give m1 a chance to be true % if not allow a model with g (which does not exist as m1 will be false there % but together with -b it causes inconsistency, and taking b also entails % inconsistency) m1 | g. % avoid d to be always false % and allow a model with f d | f. """

24.942857

79

0.626575

418

2,619

3.916268

0.227273

0.034209

0.026878

0.036652

0.99328

0

0.007531

0.290187

2,619

104

80

25.182692

0.87305

0

0.930233

0

0.987694

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

8

9e61263f3416959aa32c25a1d8c393ed8fa31248

2,488

py

Python

unit_tests_evolutionary.py

CLAHRCWessex/SymmetricTSP

2cfce4146ece0c784aa62f1b0e2ac1cb2e91b6c4

[ "MIT" ]

1

2020-06-01T22:56:11.000Z

unit_tests_evolutionary.py

CLAHRCWessex/SymmetricTSP

2cfce4146ece0c784aa62f1b0e2ac1cb2e91b6c4

[ "MIT" ]

null

unit_tests_evolutionary.py

CLAHRCWessex/SymmetricTSP

2cfce4146ece0c784aa62f1b0e2ac1cb2e91b6c4

[ "MIT" ]

null

''' Unit tests for evolutionary algorithms module 'evolutionary.py' Work in progress! ''' import numpy as np import pytest from evolutionary import PartiallyMappedCrossover def test_pmx_child_a(): test_seed = 101 np.random.seed(seed=test_seed) #sets up swap between index 1 and 3 for child a #sets up swap between index 3 and 5 for child b parent_a = np.array([1, 2, 3, 4, 5, 12]) parent_b = np.array([2, 5, 12, 3, 4, 1]) #expected answer c_a: #0: c_a = [1, 2, 3, 4, 5, 12] #1: c_a = [1, 5, 3, 4, 2, 12] #2: c_a = [1, 5, 12, 4, 2, 3] #3: c_a = [1, 5, 12, 3, 2, 4] #expected answer c_b: #0: c_a = [2, 5, 12, 3, 4, 1] #1: c_a = [2, 5, 12, 4, 3, 1] #2: c_a = [2, 3, 12, 4, 5, 1] #3: c_a = [2, 3, 1, 4, 5, 12] expected_c_a = np.array([1, 5, 12, 3, 2, 4]) expected_c_b = np.array([2, 3, 1, 4, 5, 12]) print(np.sort(np.random.randint(0, len(parent_a), size = 2))) print('before: {0} {1}'.format(parent_a, parent_b)) np.random.seed(seed=test_seed) x_operator = PartiallyMappedCrossover() c_a, c_b = x_operator.crossover(parent_a, parent_b) print('children: {0} {1}'.format(c_a, c_b)) print('after: {0} {1}'.format(parent_a, parent_b)) assert np.array_equal(expected_c_a, c_a) def test_pmx_child_b(): test_seed = 101 np.random.seed(seed=test_seed) #sets up swap between index 1 and 3 for child a #sets up swap between index 3 and 5 for child b parent_a = np.array([1, 2, 3, 4, 5, 12]) parent_b = np.array([2, 5, 12, 3, 4, 1]) #expected answer c_a: #0: c_a = [1, 2, 3, 4, 5, 12] #1: c_a = [1, 5, 3, 4, 2, 12] #2: c_a = [1, 5, 12, 4, 2, 3] #3: c_a = [1, 5, 12, 3, 2, 4] #expected answer c_b: #0: c_a = [2, 5, 12, 3, 4, 1] #1: c_a = [2, 5, 12, 4, 3, 1] #2: c_a = [2, 3, 12, 4, 5, 1] #3: c_a = [2, 3, 1, 4, 5, 12] expected_c_a = np.array([1, 5, 12, 3, 2, 4]) expected_c_b = np.array([2, 3, 1, 4, 5, 12]) print(np.sort(np.random.randint(0, len(parent_a), size = 2))) print('before: {0} {1}'.format(parent_a, parent_b)) np.random.seed(seed=test_seed) x_operator = PartiallyMappedCrossover() c_a, c_b = x_operator.crossover(parent_a, parent_b) print('children: {0} {1}'.format(c_a, c_b)) print('after: {0} {1}'.format(parent_a, parent_b)) assert np.array_equal(expected_c_b, c_b) if __name__ == '__main__': test_pmx_child_a() test_pmx_child_b()

26.189474

65

0.574357

484

2,488

2.762397

0.126033

0.038893

0.023934

0.017951

0.861631

0.839192

0

0.114561

0.249196

2,488

95

66

26.189474

0.601178

0.319534

0

0.722222

0

0.060132

0

0.055556

1

0.055556

false

0

0.083333

0

0.138889

0.222222

0

null

0

1

0

1

0

null

0

7

9e75fd895b35ad1bffe6960d3a4dd10f7527caae

92

py

Python

retropie_game_editor/routes/__init__.py

alanquillin/retropie_game_editor

6bfced066394ea3dc3504cf50af4dd25eb2366bf

[ "Apache-2.0" ]

null

retropie_game_editor/routes/__init__.py

alanquillin/retropie_game_editor

6bfced066394ea3dc3504cf50af4dd25eb2366bf

[ "Apache-2.0" ]

null

retropie_game_editor/routes/__init__.py

alanquillin/retropie_game_editor

6bfced066394ea3dc3504cf50af4dd25eb2366bf

[ "Apache-2.0" ]

null

from retropie_game_editor.routes import games from retropie_game_editor.routes import tools

30.666667

45

0.891304

14

92

5.571429

0.571429

0.307692

0.410256

0.564103

0.871795

0

0.086957

92

2

46

0.928571

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

10

7b9fd930435734590eb3454ea7fc8f2a9a5a804b

1,280

py

Python

tql/utils/config/set_plot.py

Jie-Yuan/1_DataMining

f5338388b4f883233f350d4fb9c5903180883430

[ "Apache-2.0" ]

14

2019-06-25T13:46:32.000Z

2020-10-27T02:04:59.000Z

tql/utils/config/set_plot.py

Jie-Yuan/2_DataMining

f5338388b4f883233f350d4fb9c5903180883430

[ "Apache-2.0" ]

null

tql/utils/config/set_plot.py

Jie-Yuan/2_DataMining

f5338388b4f883233f350d4fb9c5903180883430

[ "Apache-2.0" ]

7

2019-06-25T13:26:16.000Z

2020-10-27T02:05:03.000Z

#!/usr/bin/env python # -*- coding: utf-8 -*- # @Project : tql-Python. # @File : plot_set # @Time : 2019-06-20 11:28 # @Author : yuanjie # @Email : yuanjie@xiaomi.com # @Software : PyCharm # @Description : import matplotlib.pyplot as plt def set_plot(): """ plt.rcParams['font.sans-serif'] = ['Simhei'] # 中文乱码的处理 plt.rcParams['font.family'] = 'sans-serif' plt.rcParams['axes.unicode_minus'] = False # 负号 plt.rcParams["text.usetex"] = False plt.rcParams["legend.numpoints"] = 1 plt.rcParams["figure.figsize"] = (18, 9) # (12, 6) plt.rcParams["figure.dpi"] = 128 plt.rcParams["savefig.dpi"] = plt.rcParams["figure.dpi"] plt.rcParams["font.size"] = 12 plt.rcParams["pdf.fonttype"] = 42 """ plt.rcParams['font.sans-serif'] = ['Simhei'] # 中文乱码的处理 plt.rcParams['font.family'] = 'sans-serif' plt.rcParams['axes.unicode_minus'] = False # 负号 plt.rcParams["text.usetex"] = False plt.rcParams["legend.numpoints"] = 1 plt.rcParams["figure.figsize"] = (18, 9) # (12, 6) plt.rcParams["figure.dpi"] = 128 plt.rcParams["savefig.dpi"] = plt.rcParams["figure.dpi"] plt.rcParams["font.size"] = 12 plt.rcParams["pdf.fonttype"] = 42 print('Setting Success!')

32.820513

60

0.604688

161

1,280

4.782609

0.403727

0.314286

0.116883

0.103896

0.761039

0

0.040315

0.205469

1,280

38

61

33.684211

0.716814

0.527344

0

0.311808

0

1

0.076923

true

0

0.076923

0

0.153846

0.076923

0

null

1

0

1

0

null

0

1

0

7

7bc9513107ffa9240546f89db0e06b2bf7aad8a1

7,981

py

Python

configs/doom.py

joel99/midlevel-reps

f0b4a4d8ccf09a0488cd18af24723172aff99446

[ "MIT" ]

120

2019-04-22T04:45:28.000Z

2022-03-23T01:53:17.000Z

configs/doom.py

joel99/midlevel-reps

f0b4a4d8ccf09a0488cd18af24723172aff99446

[ "MIT" ]

14

2019-06-12T08:21:21.000Z

2021-08-25T15:36:58.000Z

configs/doom.py

joel99/midlevel-reps

f0b4a4d8ccf09a0488cd18af24723172aff99446

[ "MIT" ]

19

2019-06-19T07:00:36.000Z

2022-03-24T07:18:30.000Z

# Doom configs # This should be sourced by the training script, # which must save a sacred experiment in the variable "ex" # For descriptions of all fields, see configs/core.py @ex.named_config def cfg_doom_navigation(): uuid = 'doom_visualnavigation' cfg = {} cfg['learner'] = { 'algo': 'ppo', # Learning algorithm for RL agent. Currently only PPO 'clip_param': 0.1, # Clip param for trust region in PPO 'entropy_coef': 0.01, # Weighting of the entropy term in PPO 'eps': 1e-5, # Small epsilon to prevent divide-by-zero 'gamma': 0.99, # Gamma to use if env.observation_space.shape = 1 'internal_state_size': 512, # If using a recurrent policy, what state size to use 'lr': 0.0001, # Learning rate for algorithm 'num_steps': 200, # Length of each rollout 'num_mini_batch': 16, # Size of PPO minibatch 'num_stack': 4, # Frames that each cell (CNN) can see 'max_grad_norm': 0.5, # Clip grads 'ppo_epoch': 4, # Number of times PPO goes over the buffer 'recurrent_policy': False, # Use a recurrent version with the cell as the standard model 'tau': 0.95, # When using GAE 'use_gae': True, # Whether to use GAE 'value_loss_coef': 0.0001, # Weighting of value_loss in PPO 'perception_network': 'AtariNet', 'test':False, 'use_replay':False, 'replay_buffer_size': 1000, 'on_policy_epoch': 4, 'off_policy_epoch': 0, } image_dim = 84 cfg['env'] = { 'add_timestep': False, # Add timestep to the observation 'env_name': 'Doom_VizdoomMultiGoalWithClutterEnv.room-v0', "env_specific_args": { # "episode_timeout": 1000, "episode_timeout": 100, "n_clutter_objects": 8, "n_goal_objects": 1 }, 'sensors': { 'rgb_filled': None, 'taskonomy': None, 'map': None, 'target': None }, 'transform_fn_pre_aggregation': None, 'transform_fn_post_aggregation': None, 'num_processes': 1, 'additional_repeat_count': 3, } cfg['saving'] = { 'port': 8097, 'log_dir': LOG_DIR, 'log_interval': 1, 'save_interval': 100, 'save_dir': 'checkpoints', 'visdom_log_file': os.path.join(LOG_DIR, 'visdom_logs.json'), 'results_log_file': os.path.join(LOG_DIR, 'result_log.pkl'), 'reward_log_file': os.path.join(LOG_DIR, 'rewards.pkl'), 'vis': False, 'vis_interval': 200, 'launcher_script': None, 'visdom_server': 'localhost', 'visdom_port': '8097', 'checkpoint': None, 'checkpoint_configs': False, # copy the metadata of the checkpoint. YMMV. } cfg['training'] = { 'cuda': True, 'seed': random.randint(0,1000), 'num_frames': 5e6, 'resumable': True, } @ex.named_config def scratch_doom(): # scratch is not compatible with collate because we need to perform Image operations (resize) to go from # 256 to 84. This is not implemented with collate code uuid = 'doom_scratch' cfg = {} cfg['learner'] = { 'perception_network': 'AtariNet', 'perception_network_kwargs': { 'n_map_channels': 0, 'use_target': False, } } cfg['env'] = { 'env_specific_kwargs': { "episode_timeout": 1000, "n_clutter_objects": 8, "n_goal_objects": 1 }, 'transform_fn_pre_aggregation': """ TransformFactory.splitting( { 'color': { 'rgb_filled':rescale_centercrop_resize((3,84,84)) } }, keep_unnamed=False) """.translate(remove_whitespace), 'transform_fn_post_aggregation': None, } @ex.named_config def cfg_doom_exploration(): uuid = 'doom_myopicexploration' cfg = {} cfg['learner'] = { 'algo': 'ppo', # Learning algorithm for RL agent. Currently only PPO 'clip_param': 0.1, # Clip param for trust region in PPO 'entropy_coef': 0.01, # Weighting of the entropy term in PPO 'eps': 1e-5, # Small epsilon to prevent divide-by-zero 'gamma': 0.99, # Gamma to use if env.observation_space.shape = 1 'internal_state_size': 512, # If using a recurrent policy, what state size to use 'lr': 0.0001, # Learning rate for algorithm 'num_steps': 200, # Length of each rollout 'num_mini_batch': 16, # Size of PPO minibatch 'num_stack': 4, # Frames that each cell (CNN) can see 'max_grad_norm': 0.5, # Clip grads 'ppo_epoch': 4, # Number of times PPO goes over the buffer 'recurrent_policy': False, # Use a recurrent version with the cell as the standard model 'tau': 0.95, # When using GAE 'use_gae': True, # Whether to use GAE 'value_loss_coef': 0.0001, # Weighting of value_loss in PPO 'perception_network': 'AtariNet', 'test':False, 'use_replay':False, 'replay_buffer_size': 1000, 'on_policy_epoch': 4, 'off_policy_epoch': 0, } image_dim = 84 cfg['env'] = { 'add_timestep': False, # Add timestep to the observation 'env_name': 'Doom_VizdoomExplorationEnv.room-v0', "env_specific_args": { "episode_timeout": 2000, }, 'sensors': { 'rgb_filled': None, 'taskonomy': None, 'map': None, 'occupancy': None }, 'transform_fn_pre_aggregation': None, 'transform_fn_post_aggregation': None, 'num_processes': 1, 'additional_repeat_count': 3, } cfg['saving'] = { 'port': 8097, 'log_dir': LOG_DIR, 'log_interval': 1, 'save_interval': 100, 'save_dir': 'checkpoints', 'visdom_log_file': os.path.join(LOG_DIR, 'visdom_logs.json'), 'results_log_file': os.path.join(LOG_DIR, 'result_log.pkl'), 'reward_log_file': os.path.join(LOG_DIR, 'rewards.pkl'), 'vis': False, 'vis_interval': 200, 'launcher_script': None, 'visdom_server': 'localhost', 'visdom_port': '8097', 'checkpoint': None, 'checkpoint_configs': False, # copy the metadata of the checkpoint. YMMV. } cfg['training'] = { 'cuda': True, 'seed': random.randint(0,1000), 'num_frames': 5e5, 'resumable': True, } @ex.named_config def scratch_doom_exploration(): # scratch is not compatible with collate because we need to perform Image operations (resize) to go from # 256 to 84. This is not implemented with collate code uuid = 'doom_scratch_exploration' cfg = {} cfg['learner'] = { 'perception_network': 'AtariNet', 'perception_network_kwargs': { 'n_map_channels': 1, 'use_target': False, } } cfg['env'] = { 'env_specific_kwargs': { }, 'transform_fn_pre_aggregation': """ TransformFactory.splitting( { 'color': { 'rgb_filled':rescale_centercrop_resize((3,84,84)) }, 'occupancy': { 'map': rescale_centercrop_resize((1,84,84))} }, keep_unnamed=False) """.translate(remove_whitespace), 'transform_fn_post_aggregation': None, }

35.95045

108

0.543165

887

7,981

4.668546

0.263811

0.014489

0.01304

0.018836

0.907993

0.896885

0.879981

0.809466

0

0.035081

0.342814

7,981

221

109

36.113122

0.754433

0.222153

0

0.756477

0

0.413961

0.106656

0

1

0.020725

false

0

0.020725

0

null

0

1

0

1

0

null

0

7

cdddac10d0b1294b8cb1c1a263ccf4d553be9181

127

py

Python

reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/cameras/handlers/__init__.py

jpmarques19/tensorflwo-test

0ff8b06e0415075c7269820d080284a42595bb2e

[ "Apache-2.0" ]

2,610

2020-10-01T14:14:53.000Z

2022-03-31T18:02:31.000Z

reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/cameras/handlers/__init__.py

jpmarques19/tensorflwo-test

0ff8b06e0415075c7269820d080284a42595bb2e

[ "Apache-2.0" ]

1,959

2020-09-30T20:22:42.000Z

2022-03-31T23:58:37.000Z

reinforcement_learning/rl_deepracer_robomaker_coach_gazebo/src/markov/cameras/handlers/__init__.py

jpmarques19/tensorflwo-test

0ff8b06e0415075c7269820d080284a42595bb2e

[ "Apache-2.0" ]

2,052

2020-09-30T22:11:46.000Z

2022-03-31T23:02:51.000Z

from markov.cameras.handlers.follow_car_camera import FollowCarCamera from markov.cameras.handlers.top_camera import TopCamera

42.333333

69

0.889764

17

127

6.470588

0.647059

0.181818

0.309091

0.454545

0

0.062992

127

2

70

63.5

0.92437

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

7

b527389e9755e0e06ed6a8d47350d6bc82028163

132

py

Python

orders/admin.py

SiddhantNaik17/TheBashTeam_website

a4c3e023599fa9f1b0afa6485346b5b7b883e7f5

[ "MIT" ]

null

orders/admin.py

SiddhantNaik17/TheBashTeam_website

a4c3e023599fa9f1b0afa6485346b5b7b883e7f5

[ "MIT" ]

null

orders/admin.py

SiddhantNaik17/TheBashTeam_website

a4c3e023599fa9f1b0afa6485346b5b7b883e7f5

[ "MIT" ]

1

2020-11-21T16:03:30.000Z

from django.contrib import admin from orders.models import Order, Address admin.site.register(Address) admin.site.register(Order)

18.857143

40

0.818182

19

132

5.684211

0.578947

0.222222

0.296296

0.444444

0

0.098485

132

6

41

22

0.907563

0

1

0

true

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

b5950d02b8c0955813471e397905fbe2511da694

327

py

Python

tests/parser/checker.4.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/checker.4.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

tests/parser/checker.4.test.py

veltri/DLV2

944aaef803aa75e7ec51d7e0c2b0d964687fdd0e

[ "Apache-2.0" ]

null

input = """ a | c :- d, e. d :- a. d :- b. b :- a. e :- f, g, i. f :- g, e, i. i :- e, f, h. g :- f, h, e, i. c :- h, g. h :- i. a | e. """ output = """ a | c :- d, e. d :- a. d :- b. b :- a. e :- f, g, i. f :- g, e, i. i :- e, f, h. g :- f, h, e, i. c :- h, g. h :- i. a | e. """

8.384615

17

0.24159

70

327

1.128571

0.157143

0.101266

0.075949

0.101266

0.860759

0

0.446483

327

38

18

8.605263

0.436464

0

0.923077

0

0.894198

0

1

0

false

0

1

null

0

1

0

1

0

1

0

1

0

null

0

10

a9257a52b380103eed67330a699b4aeda41fa151

175

py

Python

pydeploy/tests/__init__.py

yukinotenshi/pydeploy

e3ddf907b293c9da28503b3d72414a303c5dfbed

[ "MIT" ]

2

2018-12-08T16:18:13.000Z

2020-04-05T11:13:01.000Z

pydeploy/tests/__init__.py

yukinotenshi/pydeploy

e3ddf907b293c9da28503b3d72414a303c5dfbed

[ "MIT" ]

2

2021-06-01T23:08:24.000Z

2021-11-27T06:13:41.000Z

pydeploy/tests/__init__.py

yukinotenshi/pydeploy

e3ddf907b293c9da28503b3d72414a303c5dfbed

[ "MIT" ]

1

2020-01-25T10:51:41.000Z

from pydeploy.tests.test_command import * from pydeploy.tests.test_command_chain import * from pydeploy.tests.test_notifier import * from pydeploy.tests.test_webhook import *

35

47

0.84

25

175

5.68

0.36

0.338028

0.478873

0.591549

0.816901

0

0.091429

175

4

48

43.75

0.893082

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

8

a9329e5f794ac7ff89bdca36f5443f64d702e232

10,357

py

Python

tests/test_namespace/test_include_directive.py

encodis/mokuwiki

e0f25a676ed3d53fc63a760dd4f1c87442306334

[ "MIT" ]

null

tests/test_namespace/test_include_directive.py

encodis/mokuwiki

e0f25a676ed3d53fc63a760dd4f1c87442306334

[ "MIT" ]

null

tests/test_namespace/test_include_directive.py

encodis/mokuwiki

e0f25a676ed3d53fc63a760dd4f1c87442306334

[ "MIT" ]

null

import os from mokuwiki.wiki import Wiki from utils import create_wiki_config, create_markdown_file, create_markdown_string, compare_markdown_content def test_process_file_includes(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "file2.md")}>>') create_markdown_file(source_dir.join('ns1', 'file2.md'), {'title': 'Page Two'}, 'Included Text') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''Included Text''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_globbing(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "fileX*.md")}>>') create_markdown_file(source_dir.join('ns1', 'fileX2.md'), {'title': 'Page Two'}, 'Included Text 2') create_markdown_file(source_dir.join('ns1', 'fileX3.md'), {'title': 'Page Three'}, 'Included Text 3') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''Included Text 2 Included Text 3''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_separator(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "fileX*.md|* * *")}>>') create_markdown_file(source_dir.join('ns1', 'fileX2.md'), {'title': 'Page Two'}, 'Included Text 2') create_markdown_file(source_dir.join('ns1', 'fileX3.md'), {'title': 'Page Three'}, 'Included Text 3') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''Included Text 2 * * * Included Text 3''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_line_prefix(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "file2.md")}||> >>') create_markdown_file(source_dir.join('ns1', 'file2.md'), {'title': 'Page Two'}, '''Included Text''') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''> Included Text''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_separator_and_line_prefix(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "fileX*.md")}|* * *|> >>') create_markdown_file(source_dir.join('ns1', 'fileX2.md'), {'title': 'Page Two'}, 'Included Text 2') create_markdown_file(source_dir.join('ns1', 'fileX3.md'), {'title': 'Page Three'}, 'Included Text 3') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''> Included Text 2 * * * > Included Text 3''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_prefix_and_suffix(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "file2.md")}>>') create_markdown_file(source_dir.join('ns1', 'file2.md'), {'title': 'Page Two', 'prefix': '"The prefix line\n\n"', 'suffix': '"\n\nThe suffix line"'}, 'Included Text') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''The prefix line Included Text The suffix line''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_metadata_replace(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "file2.md")}>>') create_markdown_file(source_dir.join('ns1', 'file2.md'), {'title': 'Page Two'}, 'Included page is ?{title}') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''Included page is Page Two''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1) def test_process_file_includes_metadata_replace_multi(tmpdir): source_dir = tmpdir.mkdir('source') source_dir.mkdir('ns1') target_dir = tmpdir.mkdir('target') create_markdown_file(source_dir.join('ns1', 'file1.md'), {'title': 'Page One'}, f'<<{source_dir.join("ns1", "file2.md")}>>') create_markdown_file(source_dir.join('ns1', 'file2.md'), {'title': 'Page Two', 'subtitle': 'Second Page'}, 'Included page is ?{title} with subtitle ?{subtitle}') create_wiki_config(str(source_dir.join('test.cfg')), None, {'name': 'ns1', 'path': f'{source_dir.join("ns1")}', 'target': str(target_dir)}) wiki = Wiki(source_dir.join('test.cfg')) wiki.process_namespaces() expect1 = create_markdown_string({'title': 'Page One'}, '''Included page is Page Two with subtitle Second Page''') assert os.path.exists(target_dir.join('ns1', 'page_one.md')) with open(target_dir.join('ns1', 'page_one.md'), 'r', encoding='utf8') as fh: actual1 = fh.read() assert compare_markdown_content(expect1, actual1)

33.089457

108

0.534518

1,159

10,357

4.554789

0.062985

0.114226

0.125592

0.106081

0.938246

0.933321

0

0.02

0.309646

10,357

312

109

33.195513

0.718322

0

0.854271

0

0.201356

0.039094

0

0.080402

1

0.040201

false

0

0.015075

0

0.055276

0

null

0

1

0

1

0

null

0

7

a94898877044a8e5124a5b94c784274af147dab3

28

py

Python

Chapter-1-Introduction/ex1.py

ramyaburgula/spring2022

a312e12efb4ea02f2fbdd273601e32135b2269c2

[ "MIT" ]

null

Chapter-1-Introduction/ex1.py

ramyaburgula/spring2022

a312e12efb4ea02f2fbdd273601e32135b2269c2

[ "MIT" ]

null

Chapter-1-Introduction/ex1.py

ramyaburgula/spring2022

a312e12efb4ea02f2fbdd273601e32135b2269c2

[ "MIT" ]

null

print("CIS5755 Fall 2021")

14

27

0.714286

4

28

5

1

0

0.333333

0.142857

28

1

28

0.5

0

0.607143

0

1

0

true

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

7

a949120d99392178854d311ef7b3978b827d7acb

1,653

py

Python

src/mappings.py

AminKaram/BipolarABASolver

3b858d8ea21ad9f39a393afbd5000932060d48a1

[ "MIT" ]

1

2021-08-09T10:48:36.000Z

src/mappings.py

AminKaram/BipolarABASolver

3b858d8ea21ad9f39a393afbd5000932060d48a1

[ "MIT" ]

1

2020-03-30T03:23:33.000Z

2020-03-30T10:23:47.000Z

src/mappings.py

AminKaram/FYP

3b858d8ea21ad9f39a393afbd5000932060d48a1

[ "MIT" ]

2

2019-10-07T12:14:24.000Z

2021-02-26T08:32:28.000Z

from src.bipolar_aba import BipolarABA, Rule def map_baf_to_naba_framework(baf_framework): ''' :param baf_framework: A BAF object. :return: A BipolarABA object corresponding to the n-ABA framework of BAF in the spirit of [CST17] ''' assumptions = set() contraries = set() rules = set() assumptions_contrary_mapping = {} for arg in baf_framework.arguments: contraries.add(arg + '_contrary') assumptions.add(arg) assumptions_contrary_mapping[arg] = arg + '_contrary' language = assumptions.union(contraries) for attack in baf_framework.attacks: rules.add(Rule(attack[0], attack[1] + '_contrary')) for support in baf_framework.supports: rules.add(Rule(support[1], support[0])) return BipolarABA(language, rules, assumptions, assumptions_contrary_mapping) def map_baf_to_daba_framework(baf_framework): ''' :param baf_framework: A BAF object. :return: A BipolarABA object corresponding to the d-ABA framework of BAF in the spirit of [CST17] ''' assumptions = set() contraries = set() rules = set() assumptions_contrary_mapping = {} for arg in baf_framework.arguments: contraries.add(arg + '_contrary') assumptions.add(arg) assumptions_contrary_mapping[arg] = arg + '_contrary' language = assumptions.union(contraries) for attack in baf_framework.attacks: rules.add(Rule(attack[0], attack[1] + '_contrary')) for support in baf_framework.supports: rules.add(Rule(support[0], support[1])) return BipolarABA(language, rules, assumptions, assumptions_contrary_mapping)

33.06

101

0.692075

203

1,653

5.453202

0.216749

0.108401

0.140921

0.019874

0.921409

0.802168

0

0.00916

0.207502

1,653

49

102

33.734694

0.835878

0.161525

0

0.83871

0

0.040089

0

1

0.064516

false

0

0.032258

0

0.16129

0

null

0

1

0

1

0

null

0

7

8d6817e978f1952573c042ff3f00623123e33bcc

8,575

py

Python

lab-taxi/agent.py

dragonoken/deep-reinforcement-learning

c2b791ddf486dbe762ccde6938deba6b291e9aa7

[ "MIT" ]

1

2019-07-07T02:19:27.000Z

lab-taxi/agent.py

dragonoken/deep-reinforcement-learning

c2b791ddf486dbe762ccde6938deba6b291e9aa7

[ "MIT" ]

null

lab-taxi/agent.py

dragonoken/deep-reinforcement-learning

c2b791ddf486dbe762ccde6938deba6b291e9aa7

[ "MIT" ]

1

2019-07-07T02:09:47.000Z

import numpy as np import sys from collections import defaultdict class Agent_A: def __init__(self, nA=6): """ Initialize agent. Params ====== - nA: number of actions available to the agent """ self.nA = nA self.Q = defaultdict(lambda: np.zeros(self.nA)) self.mode = ['zero', 'max', 'expected'][2] self.initial_alpha = 0.2 self.alpha = self.initial_alpha self.min_alpha = 0.0001 self.final_alpha = None self.alpha_decay_mode = ['linear', 'exponential'][0] self.alpha_decay_duration = 100000 if self.alpha_decay_mode == 'linear': self.alpha_decay_rate = (self.min_alpha - self.initial_alpha) / self.alpha_decay_duration else: self.alpha_decay_factor = (self.min_alpha / self.initial_alpha) ** (1 / self.alpha_decay_duration) self.initial_epsilon = 1.0 self.epsilon = self.initial_epsilon self.min_epsilon = 0.000001 self.final_epsilon = None self.epsilon_decay_mode = ['linear', 'exponential'][1] self.epsilon_decay_duration = 100000 if self.epsilon_decay_mode == 'linear': self.epsilon_decay_rate = (self.min_epsilon - self.initial_epsilon) / self.epsilon_decay_duration else: self.epsilon_decay_factor = (self.min_epsilon / self.initial_epsilon) ** (1 / self.epsilon_decay_duration) self.reached_min_alpha = (self.alpha <= self.min_alpha) self.reached_min_epsilon = (self.epsilon <= self.min_epsilon) self.gamma = 1.0 def select_action(self, state): """ Given the state, select an action. Params ====== - state: the current state of the environment Returns ======= - action: an integer, compatible with the task's action space """ action_values = self.Q[state] is_max = np.equal(action_values, action_values.max()) probs = np.full(self.nA, self.epsilon / self.nA) + is_max * (1 - self.epsilon) / sum(is_max) action = np.random.choice(self.nA, p=probs) return action def step(self, state, action, reward, next_state, done): """ Update the agent's knowledge, using the most recently sampled tuple. Params ====== - state: the previous state of the environment - action: the agent's previous choice of action - reward: last reward received - next_state: the current state of the environment - done: whether the episode is complete (True or False) """ action_values = self.Q[next_state] is_max = np.equal(action_values, action_values.max()) probs = np.full(self.nA, self.epsilon / self.nA) + is_max * (1 - self.epsilon) / sum(is_max) if self.mode == 'zero': expected_return = np.random.choice(action_values, p=probs) elif self.mode == 'max': expected_return = np.max(action_values) else: expected_return = np.sum(np.multiply(probs, action_values)) self.Q[state][action] += self.alpha * (reward + self.gamma * expected_return - self.Q[state][action]) if done: if not self.reached_min_alpha: if self.alpha_decay_mode == 'linear': self.alpha += self.alpha_decay_rate elif self.alpha_decay_mode == 'exponential': self.alpha *= self.alpha_decay_factor else: raise RuntimeError("Invalid Mode: {}".format(self.alpha_decay_mode)) if self.alpha <= self.min_alpha: self.reached_min_alpha = True if self.final_alpha is None: self.alpha = self.min_alpha else: self.alpha = self.final_alpha if not self.reached_min_epsilon: if self.epsilon_decay_mode == 'linear': self.epsilon += self.epsilon_decay_rate elif self.epsilon_decay_mode == 'exponential': self.epsilon *= self.epsilon_decay_factor else: raise RuntimeError("Invalid Mode: {}".format(self.epsilon_decay_mode)) if self.epsilon <= self.min_epsilon: self.reached_min_epsilon = True if self.final_epsilon is None: self.epsilon = self.min_epsilon else: self.epsilon = self.final_epsilon class Agent_B: def __init__(self, nA=6): """ Initialize agent. Params ====== - nA: number of actions available to the agent """ self.nA = nA self.Q = defaultdict(lambda: np.zeros(self.nA)) self.initial_alpha = 0.3 self.alpha = self.initial_alpha self.min_alpha = 0.001 self.alpha_decay_mode = ['linear', 'exponential'][0] self.alpha_decay_duration = 20000 if self.alpha_decay_mode == 'linear': self.alpha_decay_rate = (self.min_alpha - self.initial_alpha) / self.alpha_decay_duration else: self.alpha_decay_factor = (self.min_alpha / self.initial_alpha) ** (1 / self.alpha_decay_duration) self.initial_epsilon = 1.0 self.epsilon = self.initial_alpha self.min_epsilon = 0.00001 self.epsilon_decay_mode = ['linear', 'exponential'][1] self.epsilon_decay_duration = 20000 if self.epsilon_decay_mode == 'linear': self.epsilon_decay_rate = (self.min_epsilon - self.initial_epsilon) / self.epsilon_decay_duration else: self.epsilon_decay_factor = (self.min_epsilon / self.initial_epsilon) ** (1 / self.epsilon_decay_duration) self.reached_min_alpha = (self.alpha <= self.min_alpha) self.reached_min_epsilon = (self.epsilon <= self.min_epsilon) def select_action(self, state): """ Given the state, select an action. Params ====== - state: the current state of the environment Returns ======= - action: an integer, compatible with the task's action space """ action_values = self.Q[state] is_max = np.equal(action_values, action_values.max()) probs = np.full(self.nA, self.epsilon / self.nA) + is_max * (1 - self.epsilon) / sum(is_max) action = np.random.choice(self.nA, p=probs) return action def step(self, state, action, reward, next_state, done): """ Update the agent's knowledge, using the most recently sampled tuple. Params ====== - state: the previous state of the environment - action: the agent's previous choice of action - reward: last reward received - next_state: the current state of the environment - done: whether the episode is complete (True or False) """ action_values = self.Q[next_state] is_max = np.equal(action_values, action_values.max()) probs = np.full(self.nA, self.epsilon / self.nA) + is_max * (1 - self.epsilon) / sum(is_max) self.Q[state][action] += self.alpha * (reward + np.sum(probs * action_values) - self.Q[state][action]) if done: if not self.reached_min_alpha: if self.alpha_decay_mode == 'linear': self.alpha += self.alpha_decay_rate elif self.alpha_decay_mode == 'exponential': self.alpha *= self.alpha_decay_factor else: raise RuntimeError("Invalid Mode: {}".format(self.alpha_decay_mode)) if self.alpha <= self.min_alpha: self.reached_min_alpha = True self.alpha = self.min_alpha if not self.reached_min_epsilon: if self.epsilon_decay_mode == 'linear': self.epsilon += self.epsilon_decay_rate elif self.epsilon_decay_mode == 'exponential': self.epsilon *= self.epsilon_decay_factor else: raise RuntimeError("Invalid Mode: {}".format(self.epsilon_decay_mode)) if self.epsilon <= self.min_epsilon: self.reached_min_epsilon = True self.epsilon = self.min_epsilon Agent = Agent_A

40.258216

118

0.578192

1,015

8,575

4.670936

0.107389

0.104408

0.070871

0.037967

0.896857

0.869015

0.868171

0.847922

0.831892

0

0.011868

0.321983

8,575

212

119

40.448113

0.803578

0.133294

0

0.75

0

0.034721

0

1

0.045455

false

0

0.022727

0

0.098485

0

null

0

1

0

1

0

null

0

7

8da7fcb89cb9b5afcf8637d3035d7e33dcba8274

2,401

py

Python

tests/test_agents_common_is_result_better.py

InesVogel/Connect4

9528115515fb33d107ebc26d4141a1d3effdca5e

[ "MIT" ]

null

tests/test_agents_common_is_result_better.py

InesVogel/Connect4

9528115515fb33d107ebc26d4141a1d3effdca5e

[ "MIT" ]

null

tests/test_agents_common_is_result_better.py

InesVogel/Connect4

9528115515fb33d107ebc26d4141a1d3effdca5e

[ "MIT" ]

null

import math from agents.common import PLAYER1, PLAYER2, DEPTH, is_result_better def test_is_result_better_PLAYER1_true(): best_score = -math.inf best_num_moves = DEPTH tmp_score = 1000 tmp_num_moves = DEPTH assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER1) == True assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER2) == False def test_is_result_better_PLAYER2_true(): best_score = math.inf best_num_moves = DEPTH tmp_score = -1000 tmp_num_moves = DEPTH assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER2) == True assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER1) == False def test_is_result_better_PLAYER1_tmpScoreLower_numMovesEqual_false(): best_score = 1000 best_num_moves = DEPTH tmp_score = 999 tmp_num_moves = DEPTH assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER1) == False def test_is_result_better_PLAYER2_tmpScoreHigher_numMovesEqual_false(): best_score = 999 best_num_moves = DEPTH tmp_score = 1000 tmp_num_moves = DEPTH assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER2) == False def test_is_result_better_scoresEqual_numMovesEqual_false(): best_score = 1000 best_num_moves = DEPTH tmp_score = 1000 tmp_num_moves = DEPTH assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER1) == False assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER2) == False # TODO: figure out if needed def test_is_result_better_scoresEqual_numMovesLower_true(): best_score = 1000 best_num_moves = 4 tmp_score = 1000 tmp_num_moves = 3 assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER1) == True assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER2) == True def test_is_result_better_scoresEqual_numMovesHigher_false(): best_score = 1000 best_num_moves = 4 tmp_score = 1000 tmp_num_moves = 5 assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER1) == False assert is_result_better(best_score, best_num_moves, tmp_score, tmp_num_moves, PLAYER2) == False

32.890411

99

0.772595

365

2,401

4.583562

0.10411

0.18171

0.167364

0.143455

0.893007

0.827256

0.8159

0

0.033831

0.162849

2,401

72

100

33.347222

0.798507

0.010829

0

0.673469

0

0.013889

0.244898

1

0.142857

false

0

0.040816

0

0.183673

0

null

0

1

0

null

0

1

0

7

a5deee6566dcbb865222cdb20269547218779cc2

1,895

py

Python

state_formatters/output_formatters.py

oserikov/dream

109ba2df799025dcdada1fddbb7380e1c03100eb

[ "Apache-2.0" ]

34

2021-08-18T14:51:44.000Z

2022-03-10T14:14:48.000Z

state_formatters/output_formatters.py

oserikov/dream

109ba2df799025dcdada1fddbb7380e1c03100eb

[ "Apache-2.0" ]

27

2021-08-30T14:42:09.000Z

2022-03-17T22:11:45.000Z

state_formatters/output_formatters.py

oserikov/dream

109ba2df799025dcdada1fddbb7380e1c03100eb

[ "Apache-2.0" ]

40

2021-08-22T07:13:32.000Z

2022-03-29T11:45:32.000Z

from typing import Dict import logging import difflib logger = logging.getLogger(__name__) logger.setLevel(logging.INFO) def http_api_output_formatter(payload: Dict): response = payload["utterances"][-1]["text"] active_skill = payload["utterances"][-1]["active_skill"] ssml_tagged_response = [] for hyp in payload["utterances"][-2]["hypotheses"]: if hyp.get("skill_name") == active_skill and hyp.get("ssml_tagged_text"): if difflib.SequenceMatcher(None, hyp.get("text", "").split(), response.split()).ratio() > 0.9: ssml_tagged_response.append(hyp["ssml_tagged_text"]) ssml_tagged_response = ssml_tagged_response[-1] if ssml_tagged_response else "" ret_val = { "user_id": payload["human"]["user_telegram_id"], "response": response, "ssml_tagged_response": ssml_tagged_response, "active_skill": active_skill, } logger.info(f"http api output {ret_val}") return ret_val def http_debug_output_formatter(payload: Dict): response = payload["utterances"][-1]["text"] active_skill = payload["utterances"][-1]["active_skill"] ssml_tagged_response = [] for hyp in payload["utterances"][-2]["hypotheses"]: if hyp.get("skill_name") == active_skill and hyp.get("ssml_tagged_text"): if difflib.SequenceMatcher(None, hyp.get("text", "").split(), response.split()).ratio() > 0.9: ssml_tagged_response.append(hyp["ssml_tagged_text"]) ssml_tagged_response = ssml_tagged_response[-1] if ssml_tagged_response else "" ret_val = { "user_id": payload["human"]["user_telegram_id"], "response": response, "active_skill": active_skill, "ssml_tagged_response": ssml_tagged_response, "debug_output": payload["utterances"][-2]["hypotheses"], } logger.info(f"http api output {ret_val}") return ret_val

39.479167

106

0.669657

236

1,895

5.076271

0.211864

0.15025

0.210351

0.108514

0.868114

0.831386

0.771285

0

0.008398

0.183113

1,895

47

107

40.319149

0.765504

0

0.75

0

0.222691

0

1

0.05

false

0

0.075

0

0.175

0

null

0

1

0

1

0

1

0

null

0

8

a5ecae9a8751653dda4ffc416bfeb54fab1fa0f4

16,621

py

Python

sdk/python/pulumi_gcp/organizations/iam_audit_config.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

121

2018-06-18T19:16:42.000Z

2022-03-31T06:06:48.000Z

sdk/python/pulumi_gcp/organizations/iam_audit_config.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

492

2018-06-22T19:41:03.000Z

2022-03-31T15:33:53.000Z

sdk/python/pulumi_gcp/organizations/iam_audit_config.py

sisisin/pulumi-gcp

af6681d70ea457843409110c1324817fe55f68ad

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

43

2018-06-19T01:43:13.000Z

2022-03-23T22:43:37.000Z

# 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 from . import outputs from ._inputs import * __all__ = ['IamAuditConfigArgs', 'IamAuditConfig'] @pulumi.input_type class IamAuditConfigArgs: def __init__(__self__, *, audit_log_configs: pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]], org_id: pulumi.Input[str], service: pulumi.Input[str]): """ The set of arguments for constructing a IamAuditConfig resource. :param pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]] audit_log_configs: The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. :param pulumi.Input[str] org_id: The numeric ID of the organization in which you want to manage the audit logging config. :param pulumi.Input[str] service: Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ pulumi.set(__self__, "audit_log_configs", audit_log_configs) pulumi.set(__self__, "org_id", org_id) pulumi.set(__self__, "service", service) @property @pulumi.getter(name="auditLogConfigs") def audit_log_configs(self) -> pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]]: """ The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. """ return pulumi.get(self, "audit_log_configs") @audit_log_configs.setter def audit_log_configs(self, value: pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]]): pulumi.set(self, "audit_log_configs", value) @property @pulumi.getter(name="orgId") def org_id(self) -> pulumi.Input[str]: """ The numeric ID of the organization in which you want to manage the audit logging config. """ return pulumi.get(self, "org_id") @org_id.setter def org_id(self, value: pulumi.Input[str]): pulumi.set(self, "org_id", value) @property @pulumi.getter def service(self) -> pulumi.Input[str]: """ Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ return pulumi.get(self, "service") @service.setter def service(self, value: pulumi.Input[str]): pulumi.set(self, "service", value) @pulumi.input_type class _IamAuditConfigState: def __init__(__self__, *, audit_log_configs: Optional[pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]]] = None, etag: Optional[pulumi.Input[str]] = None, org_id: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None): """ Input properties used for looking up and filtering IamAuditConfig resources. :param pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]] audit_log_configs: The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. :param pulumi.Input[str] etag: The etag of iam policy :param pulumi.Input[str] org_id: The numeric ID of the organization in which you want to manage the audit logging config. :param pulumi.Input[str] service: Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ if audit_log_configs is not None: pulumi.set(__self__, "audit_log_configs", audit_log_configs) if etag is not None: pulumi.set(__self__, "etag", etag) if org_id is not None: pulumi.set(__self__, "org_id", org_id) if service is not None: pulumi.set(__self__, "service", service) @property @pulumi.getter(name="auditLogConfigs") def audit_log_configs(self) -> Optional[pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]]]: """ The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. """ return pulumi.get(self, "audit_log_configs") @audit_log_configs.setter def audit_log_configs(self, value: Optional[pulumi.Input[Sequence[pulumi.Input['IamAuditConfigAuditLogConfigArgs']]]]): pulumi.set(self, "audit_log_configs", value) @property @pulumi.getter def etag(self) -> Optional[pulumi.Input[str]]: """ The etag of iam policy """ return pulumi.get(self, "etag") @etag.setter def etag(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "etag", value) @property @pulumi.getter(name="orgId") def org_id(self) -> Optional[pulumi.Input[str]]: """ The numeric ID of the organization in which you want to manage the audit logging config. """ return pulumi.get(self, "org_id") @org_id.setter def org_id(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "org_id", value) @property @pulumi.getter def service(self) -> Optional[pulumi.Input[str]]: """ Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ return pulumi.get(self, "service") @service.setter def service(self, value: Optional[pulumi.Input[str]]): pulumi.set(self, "service", value) class IamAuditConfig(pulumi.CustomResource): @overload def __init__(__self__, resource_name: str, opts: Optional[pulumi.ResourceOptions] = None, audit_log_configs: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['IamAuditConfigAuditLogConfigArgs']]]]] = None, org_id: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None, __props__=None): """ Allows management of audit logging config for a given service for a Google Cloud Platform Organization. ## Example Usage ```python import pulumi import pulumi_gcp as gcp config = gcp.organizations.IamAuditConfig("config", audit_log_configs=[gcp.organizations.IamAuditConfigAuditLogConfigArgs( exempted_members=["user:joebloggs@hashicorp.com"], log_type="DATA_READ", )], org_id="your-organization-id", service="allServices") ``` ## Import IAM audit config imports use the identifier of the resource in question and the service, e.g. ```sh $ pulumi import gcp:organizations/iamAuditConfig:IamAuditConfig config "your-organization-id foo.googleapis.com" ``` :param str resource_name: The name of the resource. :param pulumi.ResourceOptions opts: Options for the resource. :param pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['IamAuditConfigAuditLogConfigArgs']]]] audit_log_configs: The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. :param pulumi.Input[str] org_id: The numeric ID of the organization in which you want to manage the audit logging config. :param pulumi.Input[str] service: Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ ... @overload def __init__(__self__, resource_name: str, args: IamAuditConfigArgs, opts: Optional[pulumi.ResourceOptions] = None): """ Allows management of audit logging config for a given service for a Google Cloud Platform Organization. ## Example Usage ```python import pulumi import pulumi_gcp as gcp config = gcp.organizations.IamAuditConfig("config", audit_log_configs=[gcp.organizations.IamAuditConfigAuditLogConfigArgs( exempted_members=["user:joebloggs@hashicorp.com"], log_type="DATA_READ", )], org_id="your-organization-id", service="allServices") ``` ## Import IAM audit config imports use the identifier of the resource in question and the service, e.g. ```sh $ pulumi import gcp:organizations/iamAuditConfig:IamAuditConfig config "your-organization-id foo.googleapis.com" ``` :param str resource_name: The name of the resource. :param IamAuditConfigArgs 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(IamAuditConfigArgs, 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, audit_log_configs: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['IamAuditConfigAuditLogConfigArgs']]]]] = None, org_id: Optional[pulumi.Input[str]] = None, service: 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__ = IamAuditConfigArgs.__new__(IamAuditConfigArgs) if audit_log_configs is None and not opts.urn: raise TypeError("Missing required property 'audit_log_configs'") __props__.__dict__["audit_log_configs"] = audit_log_configs if org_id is None and not opts.urn: raise TypeError("Missing required property 'org_id'") __props__.__dict__["org_id"] = org_id if service is None and not opts.urn: raise TypeError("Missing required property 'service'") __props__.__dict__["service"] = service __props__.__dict__["etag"] = None super(IamAuditConfig, __self__).__init__( 'gcp:organizations/iamAuditConfig:IamAuditConfig', resource_name, __props__, opts) @staticmethod def get(resource_name: str, id: pulumi.Input[str], opts: Optional[pulumi.ResourceOptions] = None, audit_log_configs: Optional[pulumi.Input[Sequence[pulumi.Input[pulumi.InputType['IamAuditConfigAuditLogConfigArgs']]]]] = None, etag: Optional[pulumi.Input[str]] = None, org_id: Optional[pulumi.Input[str]] = None, service: Optional[pulumi.Input[str]] = None) -> 'IamAuditConfig': """ Get an existing IamAuditConfig 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[Sequence[pulumi.Input[pulumi.InputType['IamAuditConfigAuditLogConfigArgs']]]] audit_log_configs: The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. :param pulumi.Input[str] etag: The etag of iam policy :param pulumi.Input[str] org_id: The numeric ID of the organization in which you want to manage the audit logging config. :param pulumi.Input[str] service: Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ opts = pulumi.ResourceOptions.merge(opts, pulumi.ResourceOptions(id=id)) __props__ = _IamAuditConfigState.__new__(_IamAuditConfigState) __props__.__dict__["audit_log_configs"] = audit_log_configs __props__.__dict__["etag"] = etag __props__.__dict__["org_id"] = org_id __props__.__dict__["service"] = service return IamAuditConfig(resource_name, opts=opts, __props__=__props__) @property @pulumi.getter(name="auditLogConfigs") def audit_log_configs(self) -> pulumi.Output[Sequence['outputs.IamAuditConfigAuditLogConfig']]: """ The configuration for logging of each type of permission. This can be specified multiple times. Structure is documented below. """ return pulumi.get(self, "audit_log_configs") @property @pulumi.getter def etag(self) -> pulumi.Output[str]: """ The etag of iam policy """ return pulumi.get(self, "etag") @property @pulumi.getter(name="orgId") def org_id(self) -> pulumi.Output[str]: """ The numeric ID of the organization in which you want to manage the audit logging config. """ return pulumi.get(self, "org_id") @property @pulumi.getter def service(self) -> pulumi.Output[str]: """ Service which will be enabled for audit logging. The special value `allServices` covers all services. Note that if there are google\_organization\_iam\_audit\_config resources covering both `allServices` and a specific service then the union of the two AuditConfigs is used for that service: the `log_types` specified in each `audit_log_config` are enabled, and the `exempted_members` in each `audit_log_config` are exempted. """ return pulumi.get(self, "service")

51.778816

469

0.681307

2,020

16,621

5.39901

0.09802

0.062534

0.046763

0.032276

0.826976

0.809004

0.786723

0.766275

0.749771

0.729048

0

0.000078

0.230552

16,621

320

470

51.940625

0.852686

0.466217

0

0.518072

1

0

0.129538

0.046121

0

1

0.150602

false

0.006024

0.042169

0

0.283133

0

null

0

1

0

1

0

null

0

7

573a2d0a47dfb91ab469b1b58b576760bdd862fd

2,571

py

Python

bayesian_optimization/fully_train_ENAS.py

jojker/D-VAE

2ff77caae4078bbb7ac9c5e0a506d32d0180507d

[ "MIT" ]

95

2019-05-14T20:55:26.000Z

2022-03-26T13:32:42.000Z

bayesian_optimization/fully_train_ENAS.py

jojker/D-VAE

2ff77caae4078bbb7ac9c5e0a506d32d0180507d

[ "MIT" ]

7

2019-11-25T08:24:47.000Z

2021-09-12T13:29:14.000Z

bayesian_optimization/fully_train_ENAS.py

jojker/D-VAE

2ff77caae4078bbb7ac9c5e0a506d32d0180507d

[ "MIT" ]

24

2019-05-14T20:55:38.000Z

2022-01-16T11:29:39.000Z

import os import pdb import numpy as np gpu_id = 0 # S-VAE arcs_scores = ''' 5 4 0 5 0 0 5 0 0 1 5 1 0 0 0 5 0 0 1 1 0 0.7502 5 5 0 4 0 0 5 0 0 1 2 1 0 0 0 4 0 0 1 1 0 0.7502 5 4 0 5 0 0 4 0 0 1 5 1 0 0 0 5 0 0 1 1 0 0.7502 4 5 0 5 0 0 2 0 0 1 5 1 0 0 0 5 0 0 1 1 0 0.7502 5 4 0 5 0 0 1 0 0 1 5 1 0 0 0 4 0 0 1 1 0 0.7502 4 4 0 5 0 0 4 0 0 1 5 1 0 0 0 4 0 0 1 1 0 0.7502 4 5 0 5 0 0 2 0 0 1 2 1 0 0 0 2 0 0 1 1 0 0.7502 4 2 0 1 0 0 4 0 0 1 2 1 0 0 0 5 1 1 1 1 0 0.75 4 5 0 1 0 0 5 1 0 1 5 0 1 0 0 3 1 0 0 1 0 0.75 5 4 0 4 0 0 2 0 0 1 2 1 0 0 0 2 0 0 0 1 0 0.7498 5 5 0 4 0 0 2 0 0 1 5 1 0 0 0 4 0 0 0 1 0 0.7498 4 5 0 5 0 0 0 0 0 1 4 0 0 0 0 4 1 0 0 1 0 0.7498 5 4 0 5 0 0 5 0 0 1 5 1 0 0 0 4 0 0 0 1 0 0.7498 5 5 0 4 0 0 2 0 0 1 4 0 0 0 0 4 1 0 0 1 0 0.7498 5 5 0 4 0 0 5 0 0 1 5 0 0 0 0 5 1 0 0 1 0 0.7498 ''' # D-VAE arcs_scores = ''' 5 4 0 2 0 1 5 1 0 0 5 1 0 1 0 2 0 0 0 1 0 0.7516 4 1 0 2 0 1 2 1 0 0 5 1 0 1 0 2 0 0 0 1 0 0.7516 5 4 0 0 0 1 5 1 0 0 2 1 0 1 0 2 0 0 0 1 0 0.7516 3 4 0 5 0 0 4 1 0 1 2 0 0 0 0 0 1 0 0 0 0 0.7502 3 4 0 5 0 0 5 1 0 1 2 0 0 0 0 2 1 0 0 0 0 0.7502 3 0 0 2 0 0 5 1 0 1 0 0 0 0 0 2 1 0 0 0 0 0.7502 3 2 0 5 0 0 4 1 0 1 0 0 0 0 0 2 1 0 0 0 0 0.7502 1 5 0 5 0 0 4 1 0 1 0 0 0 0 0 2 1 0 0 0 0 0.7502 0 3 0 2 0 0 1 1 0 1 0 0 0 0 0 5 1 0 0 0 0 0.7502 5 5 0 3 0 0 1 0 0 1 5 1 0 0 0 5 0 0 1 1 0 0.7502 1 5 0 2 0 0 5 1 0 1 0 0 0 0 0 2 1 0 0 0 0 0.7502 3 1 0 2 0 0 2 1 0 1 2 0 0 0 0 2 1 0 0 0 0 0.7502 0 2 0 5 0 0 5 1 0 1 0 0 0 0 0 2 1 0 0 0 0 0.7502 0 0 0 2 0 0 4 1 0 1 2 0 0 0 0 2 1 0 0 0 0 0.7502 3 0 0 4 0 0 0 1 0 1 0 0 0 0 0 2 1 0 0 0 0 0.7502 ''' enas_pos = '../software/enas/' arcs = [x.split('.')[0][:-2] for x in arcs_scores.strip().split('\n')] print(arcs) scores = [] for arc in arcs: print('Fully training ENAS architecture ' + arc) save_appendix = ''.join(arc.split()) if not os.path.exists(enas_pos + 'outputs_' + save_appendix): pwd = os.getcwd() os.chdir(enas_pos) os.system('CUDA_VISABLE_DEVICES={} ./scripts/custom_cifar10_macro_final_6.sh'.format(gpu_id) + ' "' + arc + '" ' + save_appendix) os.chdir(pwd) with open(enas_pos + 'outputs_' + save_appendix + '/stdout', 'r') as f: last_line = f.readlines()[-1] scores.append(last_line) new_arcs_scores = [x+' '+y for x, y in zip(arcs_scores.strip().split('\n'), scores)] new_arcs_scores = ''.join(new_arcs_scores) print() print('Fully trained architecture, WS acc, and test acc:') print(new_arcs_scores) print('Average score is {}'.format(np.mean([float(x.split()[1]) for x in scores]))) pdb.set_trace()

33.828947

137

0.576429

857

2,571

1.690782

0.098016

0.298137

0.192547

0.126984

0.601794

0.52588

0.478951

0.454796

0.410628

0

0.457944

0.334111

2,571

75

138

34.28

0.388435

0.004278

0

0.066667

0

0.5

0.658975

0.025029

0

1

0

false

0

0.05

0

0.05

0.1

0

1

null

1

0

1

0

1

0

1

0

null

0

7

575a316cf01a5089aa362a824cd0d0ae8abdf3ee

2,184

py

Python

test/test_util.py

afourney/pyra

245f9d4ce5db8810f4a2456afc64e7ba208484a1

[ "BSD-2-Clause" ]

null

test/test_util.py

afourney/pyra

245f9d4ce5db8810f4a2456afc64e7ba208484a1

[ "BSD-2-Clause" ]

null

test/test_util.py

afourney/pyra

245f9d4ce5db8810f4a2456afc64e7ba208484a1

[ "BSD-2-Clause" ]

1

2020-01-02T19:06:20.000Z

# Load what we actually need to run the tests import unittest import pyra.util as util class TestUtils(unittest.TestCase): def setUp(self): pass def test_binary_search(self): s = range(1,100,2) # Extermities self.assertEqual( util.binary_search(s, -1), 0 ) self.assertEqual( util.binary_search(s, 0), 0 ) self.assertEqual( util.binary_search(s, 1), 0 ) self.assertEqual( util.binary_search(s, 2), 1 ) l = len(s) self.assertEqual( util.binary_search(s, 101), l ) self.assertEqual( util.binary_search(s, 100), l ) self.assertEqual( util.binary_search(s, 99), l-1 ) self.assertEqual( util.binary_search(s, 98), l-1 ) # Inside for i in range(0,len(s)): # Things that are found self.assertEqual( util.binary_search(s, s[i]), i ) # Things that are not found self.assertEqual( util.binary_search(s, s[i]-1), i ) def test_galloping_search(self): s = range(1,100,2) # Extermities self.assertEqual( util.galloping_search(s, -1), 0 ) self.assertEqual( util.galloping_search(s, 0), 0 ) self.assertEqual( util.galloping_search(s, 1), 0 ) self.assertEqual( util.galloping_search(s, 2), 1 ) l = len(s) self.assertEqual( util.galloping_search(s, 101), l ) self.assertEqual( util.galloping_search(s, 100), l ) self.assertEqual( util.galloping_search(s, 99), l-1 ) self.assertEqual( util.galloping_search(s, 98), l-1 ) # Inside for i in range(0,len(s)): # Things that are found self.assertEqual( util.galloping_search(s, s[i]), i ) # Things that are not found self.assertEqual( util.galloping_search(s, s[i]-1), i ) # Hints for i in range(0,len(s)): for j in range(0,len(s)): # Things that are found self.assertEqual( util.galloping_search(s, s[i]), i, j ) # Things that are not found self.assertEqual( util.galloping_search(s, s[i]-1), i, j )

33.090909

74

0.573718

301

2,184

4.076412

0.162791

0.268949

0.340668

0.273839

0.873676

0.847596

0.709046

0.660147

0.643032

0

0.037549

0.304945

2,184

65

75

33.6

0.770751

0.105769

0

0.189189

0

0.594595

1

0.081081

false

0.027027

0.054054

0

0.162162

0

null

1

0

1

0

null

0

1

0

9

f51cb84743214c2f45bc804e995161b357beacc0

113

py

Python

netbox_plugin_extensions/forms/model.py

DanSheps/netbox-plugin-extensions

282f314fd301271f8bfa6620f4b9b15d4c93f59c

[ "Apache-2.0" ]

6

2021-09-22T05:41:24.000Z

2022-03-15T16:11:46.000Z

netbox_plugin_extensions/forms/model.py

DanSheps/netbox-plugin-extensions

282f314fd301271f8bfa6620f4b9b15d4c93f59c

[ "Apache-2.0" ]

3

2021-09-30T16:36:09.000Z

2022-01-13T15:54:53.000Z

netbox_plugin_extensions/forms/model.py

DanSheps/netbox-plugin-extensions

282f314fd301271f8bfa6620f4b9b15d4c93f59c

[ "Apache-2.0" ]

3

2021-09-30T15:32:00.000Z

2022-01-19T12:35:24.000Z

from extras.forms import CustomFieldModelForm class PluginCustomFieldModelForm(CustomFieldModelForm): pass

18.833333

55

0.849558

9

113

10.666667

0.888889

0

0.115044

113

5

56

22.6

0.96

0

1

0

true

0.333333

0

0.666667

0

1

0

1

null

0

1

0

null

0

1

0

1

0

7

f572c9af3e6754201c4e36324e1095604edfab5e

5,052

py

Python

S.py

mrzomby/Tool-s

9a335feedbdc292ca866db63801f56493edc2084

[ "Apache-2.0" ]

null

S.py

mrzomby/Tool-s

9a335feedbdc292ca866db63801f56493edc2084

[ "Apache-2.0" ]

null

S.py

mrzomby/Tool-s

9a335feedbdc292ca866db63801f56493edc2084

[ "Apache-2.0" ]

null

# Obfuscated by Py Compile # Created by Mr.ZOMBY (https://github.com/mrzomby) import marshal,zlib,base64 exec(marshal.loads(zlib.decompress(base64.b32decode("PCOELGGJSLW3Q4MGVNN53HSWPYEC7NGGXCYR3RQMAIQENAQEWFV2S36YKK2EEDW55OG3O7SBX6IZ2FJB3FTWAHNSDACJDSH474X7TW4PH67X5AHPX7APO24EZXH7B6PO4OLY7D75P673766Y3766L57XD757XDZPD4P3776VY6L66PT677B4PF7PH57P7Y6HZ7PX77GXO5775QDJH5GNRDC774FK555376AVP7X2357774KRKXE6QUNJTQOROU24SSF5DNE62PIGLXZRMVWOJMJR3ZTXZS6JJVKF2USG3IZ3A6WQY3DTVH6YCG3G7PF2OBD7F3TV4UKZCD3TKZU7NS3Q4VDF3V56HBUYWHLL3GYTH5P2PST5EJNSUVFNQ3IFEFLRJBLVXRCJC5IIWPTOBQSVKOETWDB5XRSHE5PJM55U3C2F6Y7AJ3GXEHNUDPBLZX4TWVRPJMOTLCGU3LNKNNSRCQYTPO4VDGU43NNFLHBZLM3K72NMLNUQK3ASJQVUCHHPBL2YYORSGIIVM7RX4VNMYTPDPGO2SHJK7DMZO2TSFZDIQG36ZK5EYRYYCDVTKIHBOZXCT33TIFNG3HHBNFUQMUHSTA7X5YXFIUVDE27K4UHTIEWZSKHBAB3UV7JAFC6QGRVUYUUCGEYZWQ42OJF4WV43NC74JBD6HL3MLMW5GU3W3RUKMTSXFDWC3N7V5T23LT5WGPCFL4VIQ7BQ2PLQXRI3QZF5ZIUIRKSVCRSUOVRVRXTVNFS6U3PXLEFQJ2J3ZOL4B4CPFAHQ4XQNFGG3JPDQXEMNGYXWJHHYMHKWC5A6TKFXNBRGFXDOVFJXP765Q37BMVS2PSHV7KJJ3RK4WUR6DWE7IXOJ3FEW7K6OL4LZ4M3POGFYMG5XWVWJ4RECJJ3MZ5DJCZBZ2UODLO7VCHOUKB2OXYYWW243UULJSJM5UOJPQUE7FCVXTW3FOTON26AU4N5YRPCCG3YZREXZK2VGIDEOO2VK7HLNYASXPNCDHXDESXKIKS3LDHMJERYWUVVYCCCKHU6D6Y5DVVUST5VHXXVC4KYZ7HDBG2VLK272K7ND2GAVQ7SGELUWV2WA2OSKH6Z5VO5TYGVDVKBZPSF5MRYRWYM62KKB7PZKZXX42NVFZ7FVVI2XDKHTOJNXAKEGFKHTKAUXUOPKM3KKQWY2H2LD7HVV3T5YTPY4JR4LURZ5LWE4DVH4IGCLC2CSU4UJFOCIASJRVVZNOYTMIGJJCA6UBCHW7RVCB3DF6BIRSBL7PYNFKHRXOFHM34322KIRRLLHTEXJJYT4JDFLC6VFEPZPOV6EP3ZUVKB5HAHHFRB2H5NSJ3QH3RB3TKC43KTNOUIUEWSXPJWELN7LW2TY3T4FY7GLY3DVXYG7OZFICSOEQRJRXKR3R6ZYHJ5YLHQXZTFK3Z6QVIGZDY6SEGOMQLVVV4CQWWKQMRHQ4UN5SAB3QVO2PA263IAZVFUVRI3DU2XLX2XLXFMHZONGEP5HHUXWLHEHAAMP3654BCXETV4FA5XEUQ4FFTJ64SDEZHKL345MOZFPZCNJFIVN3SFFHAUEVHKDUDHXT3RGY7GKZTFUM33XHORQUVRWTFFUNRFUBJDCGNF4OO5MPSNTXSY7IZCKRXPHYUIIJ24KSPSG2YME3BPJPIE2SFLSIHSLU55EJ3ODOLBSH7FUHTIYDPD6GFRTXOWW54Z4XYPOMIQRASBD2I4TCDI2RHEE4OSPHAWSEHECYUEMTXKNQVWSWHS3JQXX635OPMFYKO2472YIWKTPHTMBLT6TYHRTT52M35TUOVJKSVSXY5YTKGYEPGNRUHDHK36EIMLVI7JXMNUK5MO6Z3TAA66UU5Y6G7V2KC36RVGTIIJ6VQ3A2TEJTP3SSQ5CJVVXMYWXIJP7V3S4JZLI2VP4BDTHGYLXVL3LLMI7RRTX4WK7Y3VJNUDDU2IKWIM4G2CV4PVWMLOT4TGWKDLTVLBL3S7B526PBTU6XOWRXMF46TZIVP434NRGZ4OJNT622IU3OPESHIJXQVJ57OARTSZBTWNNWMZZAQ4X7D43XTSFGJ7MF2JXJ7PKG6ZVSGQESMSH2ENGFR4SQLAAPPB5GQ5D2EOFG6PMDEKE3HFPY3FR33GOM7YC3YGAMJ47KPNQHVBSE3QPNKQ6VURFKM4LZPSWSTUX5GZEYKMGRGB37QWHU3WNEJHESVLD2DHKBHYPLBV5JKTMYKZMY5HNOC2ONRJYAO5X3JJONID4TC26VJXZXHK3BK2IKQKFGATUID2JORU65FILUOGGEKJXIKD2UT3ZZNOBQHBZLDVBECONTSWE263I6AX5L4PVTFLSVJ3MD6KLFIIIUGKBF5OPBA2GWOZR6UYHQMJXEJXG4BEZ5CZEIQ4ZDKMPGNNLENYW2XCD2Y63TEOXTXU4BR65JZOQRZUOGQIMUXV36YBWPTWU4PLCEUXUE4ZVAKPNFXJTSXJGRACVFKQ2VCZQZ4SROIFXOCZNQQBNLI2C26TJLUDH2NPORVFUNEZAUCOY6GCLHHKT333HV2NNDJL6RWCDICQKUREHTSRO3V2OPM5BUU4LUZZXO2WPB4OAU5JICTZDFB5X4XB3332CXEFODI4UDW75TSNT36X4JTYS32RPOOC7CHHAIEYX2IEMTA5YRI4KOKEP5XVD46SXZQ3NBIPZWJWC4WGOI6MFWADNMQIKL3EWWCDSUIG7DLASYHAMOXFRPAQHK4C7HJTNHRDCDF3OZVNBKGF4O2DXCHTVK4KICP2UEBHBZL5SPGTH3VZXQC37S4M5T2H3PCQXFGD3RZS3LKUQSP7VDO4MPFKVN4NAGMOYRYPMOKXAADLF4A6KWGALCCGAW2ES5GKH43NAOJK62BHX4SQQJOHY6PDM4RCWAQBD5M3GQBAYKN7HE6LKL4ZGA6IZQ6PTP3AHXOPHAR35NIO64F5ZDNKG5XYPTTFQLOFZWTEG3V3USTXX4CPSV3PSDI7SDYAEXBAV7UOAIQMUNHXHXP7RT2EIFSOUGP5YQCRLYAFBDWAL7SI2YRY7JZCSYEAWBTVXZJLGBJJHYM7A2KVD3IFKZMVU54J4O62T2FWM2Z6SEEA5FA6OMD3NKF54S5TI56YVGWLPJBNAVOTAI6I7YPHWDBL2EGW76LBBOIFEIJ5U4YUNXIPXTNTYA52MHOFHE5NEODLZDTZRYZ4WMCB3URRUN7NF6ZFSTMK4PJA4A4IYECDVDQEKQRVOL2FUP3T5XJ5CD4DKCTCAHUTXPGKAJHV2CVQEYJZCQNIAZEDI5SONZJ262KBSGAVCSXJDXKYLSMFLUAJFTUXDAWK7RZJQSL2IRSQOD7ON5LOBNETJH53IOGOXOE4ABMRY7B4R5JLWJDUXGL4LYDOFAO4YHOMXFGS43GTUMIKT5KNJHDNCN6DEDCKZ3E653DBH4TNCNSPYPROWEHPVETFR4TNOLWFESJ5EKIAG7X34H7TOSLR6MAE7IBUSDAPEA4V4U5G2CTF6GBELZA53A6QEXOKX7WMVMVROWQ67HUI6GW3XLAKRZHPGM4TVV2ZROCEPHABQLCSTZMZDUIDPVWOJTGVUFAO2ZHZXAN7IZR3B57VXDF2FCKSGIXPDQKWPECFU6OCQXS46GTMFFQZ4HUENFSKTT4VRALF7LZYI5E2UY6BNO7OFXXUZ5IC4Q5EGD5NZVOZSXDN6QFJLZ3OXKLY5BOOCSCGNOBUGKILBT5PFTQTNIT4BEFVXZDGTDN7FZBBSS4NQYXBY3KHLPNYYZKRSHG47PGCNZIRXHW3UJVZUU56AAWEWIHFNZ7RU6KW3CVAIWS3J7LAJBZ23YXVQIEVGH52TEYTK6OU7E52NMTQOFNDCTL4L33GTO4ZIA62K2ZUL3THGETQOPGK2JWHGA3NL7ZZVQK3AYWUKNUW2LZLG4UZCG3TCDD2DZNSCDMQS6IATKAYAJHKZ4UKMJF3ZT3EIW44GHEXD2LS4KZ4CMU46XSI3ZK2XB6KZVTWSUFYTUNSZE6PLBNHCXHYIDTNLI7L3RAIORLYCZSNHJLEFNRPKXVXKANBG36OCB4WPZRSWO2BOY2ZQDBJMWA3N6FHANUV3H5VDGQZJH4XLMER4YDTSH2N6H3ZZMSYVBDTW65ZABDBJNC7A4QLDLWRGNGIEHJI6PSUG25CKADLAHN3QEVK6B6MFAO6FOE7GL6MR27BRITXLWO2ZBPJEP43PCYWIKTGYMNCXQIHCZP4WBICS4AUEDYPZYKIQSOOKPW4VFKML6J6VY3ZIJMKAWE6YXCJWOKYNNCOOJVFRQT3KVYYTBI4HYVMQWW3REA6G26BSUTZW3FOKUNOHHFF5QFHKMO7L5GQ5TUG3PF2EGMPLYDAUZTR4FMILHYRJPHOAO67GAFFNSYD6TAPTGBV5T6VG5PNA3KPUWN3IRTBKVIUSU6O7QPGAVFXQ6VCHEG4ADFWW4YYQ6KQRW7MYFEZ7PAVTIQXNZQBUUFEFCU3TIXSP6GCIB4MGJ3XDTZSV2QYNOVI22RBHTI57NBKQEX4AAWBBYSDIMKQXT37MXKPEHAOVOEGRM4HKHUM6RLWCHLI3VSOGO2F5WQ4DAV5NI5RLUGZADOFWZXTA6LZZFUOYTA462SNLYON2KLDAAGHWEDJQKAKNB32RETPWAAKQH2R2WBOSFIOF3YAH6F3WAPE5ENIY57TTGAVYPNB33YF6VXZCNS2SZX2EKHNVP75PKX35PR6HZ63L3D6ODJZ7PX63PH367H3PSJHFH577TXLPXZ675ZZXH5673QWIW4P6DZZPP76OTZ5P377O547RZKL577XRB7775JZPL67X5663Z5ZTB6R46LZZOX37H2EPT76N27XT7T7525XX6A3773YQ67747E7X56PSZ4775ZPYH56PPPZ2RXY34==="))))

1,010.4

4,946

0.991884

24

5,052

208.791667

0.833333

0

0.191903

0.002573

5,052

5

4,946

1,010.4

0.80254

0.01445

0

0.982118

0

1

0

1

0

true

0

0.5

0

0.5

0

1

0

1

null

0

1

0

1

null

1

0

1

0

1

0

10

1984b5af18543c4335539af782a71696dd12d5ef

800

py

Python

tests/fixtures/defxmlschema/chapter03/__init__.py

nimish/xsdata

7afe2781b66982428cc1731f53c065086acd35c1

[ "MIT" ]

null

tests/fixtures/defxmlschema/chapter03/__init__.py

nimish/xsdata

7afe2781b66982428cc1731f53c065086acd35c1

[ "MIT" ]

null

tests/fixtures/defxmlschema/chapter03/__init__.py

nimish/xsdata

7afe2781b66982428cc1731f53c065086acd35c1

[ "MIT" ]

null

from tests.fixtures.defxmlschema.chapter03.chapter03prod2 import ColorType from tests.fixtures.defxmlschema.chapter03.chapter03 import EnvelopeType from tests.fixtures.defxmlschema.chapter03.chapter03ord import ItemsType from tests.fixtures.defxmlschema.chapter03.chapter03ord import OrderType from tests.fixtures.defxmlschema.chapter03.chapter03prod import ProdNumType from tests.fixtures.defxmlschema.chapter03.chapter03prod import ProductType from tests.fixtures.defxmlschema.chapter03.chapter03prod import SizeType from tests.fixtures.defxmlschema.chapter03.chapter03prod2 import Color from tests.fixtures.defxmlschema.chapter03.chapter03 import Envelope from tests.fixtures.defxmlschema.chapter03.chapter03ord import Order from tests.fixtures.defxmlschema.chapter03.chapter03prod import Product

66.666667

75

0.89

88

800

8.090909

0.227273

0.139045

0.26264

0.448034

0.867978

0

0.060847

0.055

800

11

76

72.727273

0.880952

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

8

199b0c6194c48bb463776419c6f03852b1121647

81,167

py

Python

7_stg/model/visualization/viz_samples.py

mackelab/IdentifyMechanisticModels_2020

b93c90ec6156ae5f8afee6aaac7317373e9caf5e

[ "MIT" ]

3

2020-10-23T02:53:11.000Z

2021-03-12T11:04:37.000Z

7_stg/model/visualization/viz_samples.py

mackelab/IdentifyMechanisticModels_2020

b93c90ec6156ae5f8afee6aaac7317373e9caf5e

[ "MIT" ]

null

7_stg/model/visualization/viz_samples.py

mackelab/IdentifyMechanisticModels_2020

b93c90ec6156ae5f8afee6aaac7317373e9caf5e

[ "MIT" ]

1

2021-07-28T08:38:05.000Z

import numpy as np import matplotlib.pyplot as plt import matplotlib.colors as mcolors from print_helper import conductance_to_value_exp, build_string, build_string_gen import seaborn as sns from matplotlib import lines import matplotlib.gridspec as gridspec import prinzdb from print_helper import get_summ_stat_name, get_summ_stat_name_text, get_synapse_name, get_summ_stat_name_asterisk, scale_to_experimental import sys sys.path.append("../visualization") import viz from copy import deepcopy import matplotlib.ticker import matplotlib.patheffects as pe def vis_sample(m, s, sample, hyperparams, t_on=None, t_off=None, with_ss=True, with_params=True, mem_dimensions=None,mode2=None, voltage_trace=None, time_len=None, fontscale=1.0, linescale=1.0, offset=0.0, test_idx=None, case=None, title=None, date_today=None, counter=0, offset_labels=0.0, legend=True, multiplier_cond_shift = 0.0, vis_legend=True, scale_bar=True, ss_names=True, param_names=True, save_fig=False): """ Function of Kaan, modified by Michael. Used for plotting fig 5b Prinz. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ font_size = 15.0 if voltage_trace is None: data = m.gen_single(sample) else: data = voltage_trace Vx = data['data'] params = data['params'] stats = s.calc([data])[0] stats_nan = deepcopy(stats) stats[np.isnan(stats)] = 0.0 if hyperparams.include_plateau: stats = stats[:-4] stats = scale_to_experimental(stats) bar_scaling_factors = [1.0, 10, 100, 10, 100, 1, 10000, 10000] bar_scaling_factors = np.reshape(np.tile(bar_scaling_factors, 3), (3, 8)) bar_vals = bar_scaling_factors[np.asarray(hyperparams.use_membrane)] if mem_dimensions is not None: params_trunc = params[mem_dimensions].tolist() params_trunc += params[-7:].tolist() bar_vals = bar_vals[mem_dimensions] params = np.asarray(params_trunc) if with_params and with_ss: fig = plt.figure(figsize=(11.3, 6)) gs = gridspec.GridSpec(2, 3, width_ratios=[len(stats), len(params[:-7]), len(params[-7:])], wspace=0.25, height_ratios=[0.7, 0.3]) axV = plt.subplot(gs[0, :]) axss = plt.subplot(gs[1, 0]) axmemparams = plt.subplot(gs[1, 1]) axsynparams = plt.subplot(gs[1, 2]) elif with_params: fig = plt.figure(figsize=(6, 7.5)) gs = gridspec.GridSpec(2, 2, width_ratios=[len(params[:-7]), len(params[-7:])], hspace=0.1, wspace=0.38, height_ratios=[0.65, 0.35]) axV = plt.subplot(gs[0, :]) axmemparams = plt.subplot(gs[1, 0]) axsynparams = plt.subplot(gs[1, 1]) elif with_ss: fig, (axV, axss) = plt.subplots(2, figsize=(14, 6)) else: fig, axV = plt.subplots(1, figsize=(14, 3)) cols = ['#034e7b', '#0570b0', '#3690c0'] #cols = ['k', 'k', 'k'] current_col = 0 scale_bar_breadth = 1000.0 scale_bar_voltage_breadth = 50.0 if time_len is not None: m.t = m.t * len(m.t) / time_len scale_bar_breadth = scale_bar_breadth * len(m.t) / time_len for j in range(len(prinzdb.neutypes)): if time_len is not None: axV.plot(m.t[10000+offset:10000+offset+time_len], Vx[j, 10000+offset:10000+offset+time_len] + 120.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.75, c='k', rasterized=True) else: axV.plot(m.t, Vx[j] + 120.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.75, c='k') current_col += 1 if scale_bar: if mode2 == 'small': axV.plot(10860 + np.arange(scale_bar_breadth), 318 * np.ones_like(np.arange(scale_bar_breadth)), lw=1.0, color='k', zorder=5, rasterized=True) axV.text(10905, 324, '1 sec', fontsize=font_size) import matplotlib.patches as patches rect = patches.Rectangle((11890, 234), 2000, 100, linewidth=1, facecolor='w', zorder=3) axV.add_patch(rect) axV.plot(13490 * np.ones_like(np.arange(scale_bar_voltage_breadth)), 318 - scale_bar_voltage_breadth + np.arange(scale_bar_voltage_breadth), lw=1.0, color='k', zorder=6, rasterized=True) axV.text(11770, 270, '50 mV', fontsize=font_size) else: axV.plot(10860 + np.arange(scale_bar_breadth), 318 * np.ones_like(np.arange(scale_bar_breadth)), lw=1.0, color='k', rasterized=True) axV.text(10905, 324, '1 sec', fontsize=font_size) import matplotlib.patches as patches rect = patches.Rectangle((10900, 264), 700, 50, linewidth=1, facecolor='w', zorder=3) axV.add_patch(rect) axV.plot(11860 * np.ones_like(np.arange(scale_bar_voltage_breadth)), 318 - scale_bar_voltage_breadth + np.arange(scale_bar_voltage_breadth), lw=1.0, color='k') axV.text(10930, 270, '50 mV', fontsize=font_size) if not legend and vis_legend: if mode2=='small': axV.text(-0.15, 0.75, 'AB/PD', fontsize=font_size, transform=axV.transAxes) axV.text(-0.1, 0.45, 'LP', fontsize=font_size, transform=axV.transAxes) axV.text(-0.1, 0.15, 'PY', fontsize=font_size, transform=axV.transAxes) else: axV.text(-1540+offset_labels, 220, 'AB/PD', fontsize=font_size) axV.text(-1050+offset_labels, 95, 'LP', fontsize=font_size) axV.text(-1080+offset_labels, -30, 'PY', fontsize=font_size) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) if legend: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), ncol=len(prinzdb.neutypes), fontsize=font_size*fontscale) axV.xaxis.set_tick_params(labelsize=font_size*fontscale) axV.yaxis.set_tick_params(labelsize=font_size*fontscale) axV.spines['left'].set_linewidth(2.0 * linescale) axV.spines['bottom'].set_linewidth(2.0 * linescale) col1 = 'r' col2 = 'r' col3 = 'r' if with_params: lticks = np.arange(len(params[:-7])) width = 0.35*linescale # the width of the bars axmemparams.bar(lticks + width / 2, bar_vals * params[:-7] / 0.628e-3, width, bottom=min(1e-8, np.min(params[:-7])), color='k') names = viz.get_labels(hyperparams, mathmode=True, include_q10=False)[:-7] if mem_dimensions is not None: names = names[mem_dimensions] axmemparams.set_ylim((0, 700)) # axmemparams.set_ylabel('Membrane', fontsize=font_size) axmemparams.set_xticks(lticks + width / 2) if param_names: axmemparams.set_xticklabels(names, rotation='vertical', fontsize=font_size*fontscale) else: axmemparams.axes.get_xaxis().set_visible(False) axmemparams.axes.get_yaxis().set_visible(False) axmemparams.xaxis.set_tick_params(labelsize=font_size*fontscale) axmemparams.yaxis.set_tick_params(labelsize=font_size*fontscale) small_offset = [0.00, -0.0, -0.0, 0.0, -0.00, 0.0] font_decrease = 1.7 mode = '13D' if mode == '13D': if mode2 == 'small': for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -360, 'x', fontsize=font_size / 2) axmemparams.set_ylim((0, 700)) # 850 small_offset = [0.15, -0.04, -0.1, 0.0, -0.02, 0.0] for i in range(6): if i == 2 or i == 3 or i == 4 or i == 5: # -620 axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -410, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]), include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -410, r'$%s$' % str(int(bar_vals[i])), fontsize=font_size / font_decrease) axmemparams.text(0.11, -0.73, r'Membrane $\mathregular{\bar g}$', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.22, -0.85, '[mS/cm' + chr(0x00b0 + 2) + ']', fontsize=font_size, transform=axmemparams.transAxes) else: for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -390, 'x', fontsize=font_size / 2) axmemparams.set_ylim((0, 600)) # 850 small_offset = [0.15, -0.04, -0.1, 0.0, -0.02, 0.0] for i in range(6): if i == 2 or i == 3 or i == 4 or i == 5: # -620 axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -450, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]), include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -450, r'$%s$' % str(int(bar_vals[i])), fontsize=font_size / font_decrease) axmemparams.text(0.11, -0.95, r'Membrane $\mathregular{\bar g}$', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.22, -1.12, '[mS/cm' + chr(0x00b0 + 2) + ']', fontsize=font_size, transform=axmemparams.transAxes) else: for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -470, 'x', fontsize=font_size / 2) for i in range(6): if i == 0 or i == 1 or i == 2 or i == 3 or i == 4 or i == 5: # -620 axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -530, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]), include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -530, r'$%s$' % str(int(bar_vals[i])), fontsize=font_size / font_decrease) lticks = np.arange(len(params[-7:])) axsynparams.bar(lticks + width / 2, params[-7:] * 1e-3, width, bottom=min(1e-8 * 1e-3, np.min(params[-7:] * 1e-3)), color='k') if mode2 == 'small': axsynparams.text(0.22, -0.73, r'Synaptic $\mathregular{\bar g}$', fontsize=font_size, transform=axsynparams.transAxes) axsynparams.text(0.4, -0.85, '[nS]', fontsize=font_size, transform=axsynparams.transAxes) else: axsynparams.text(0.22, -0.95, r'Synaptic $\mathregular{\bar g}$', fontsize=font_size, transform=axsynparams.transAxes) axsynparams.text(0.4, -1.12, '[nS]', fontsize=font_size, transform=axsynparams.transAxes) names = viz.get_labels(hyperparams, include_q10=False)[-7:] # axsynparams.set_ylabel('Synapses', fontsize=font_size) axsynparams.set_yscale('log') axsynparams.set_ylim((1e-8 * 1e-3, 1e-3 * 1e-3)) axsynparams.set_xticks(lticks + width / 2) axsynparams.set_yticks([1e-11, 1e-9, 1e-7]) if param_names: axsynparams.set_xticklabels(names, rotation='vertical', fontsize=font_size*fontscale) else: axsynparams.axes.get_xaxis().set_visible(False) axsynparams.axes.get_yaxis().set_visible(False) axsynparams.xaxis.set_tick_params(labelsize=font_size*fontscale) axsynparams.yaxis.set_tick_params(labelsize=font_size*fontscale) axsynparams.spines['left'].set_linewidth(2.0 * linescale) axsynparams.spines['bottom'].set_linewidth(2.0 * linescale) axmemparams.spines['left'].set_linewidth(2.0 * linescale) axmemparams.spines['bottom'].set_linewidth(2.0 * linescale) if with_ss: lticks = np.arange(len(stats)) width = 0.35 # the width of the bars #stats[8:] *= 2000 axss.bar(lticks + width / 2, stats, width, color='k') nan_pos = np.where(np.isnan(stats_nan))[0] axss.scatter(nan_pos + width / 2, 50 * np.ones_like(nan_pos), c='b', s=70.0, zorder=2, marker='x') # add some text for labels, title and axes ticks names = [] for num in range(15): names.append(get_summ_stat_name(num)) # axss.set_ylabel('Summary Statistics', fontsize=font_size) axss.set_xticks(lticks + width / 2) if ss_names: axss.set_xticklabels(names, rotation='vertical', fontsize=font_size*fontscale) else: axss.axes.get_xaxis().set_visible(False) axss.axes.get_yaxis().set_visible(False) axss.xaxis.set_tick_params(labelsize=font_size*fontscale) axss.yaxis.set_tick_params(labelsize=font_size*fontscale) axss.set_ylim([-4, 4]) axss.set_yticks([-4, -2, 0, 2, 4]) axss.set_yticklabels([r'$-4 \sigma$', r'$-2 \sigma$', '0', '$2 \sigma$', '$4 \sigma$']) axss.text(0.27, -0.95, 'Summary statistics', fontsize=font_size, transform=axss.transAxes) axss.text(0.145, -1.12, '[st. dev. of samples]', fontsize=font_size, transform=axss.transAxes) axss.spines['right'].set_visible(False) axss.spines['top'].set_visible(False) #axss.axes.get_yaxis().set_ticks([]) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) axsynparams.spines['right'].set_visible(False) axsynparams.spines['top'].set_visible(False) axmemparams.spines['right'].set_visible(False) axmemparams.spines['top'].set_visible(False) sns.set(style="ticks", font_scale=1) sns.despine() axV.set_title('') if save_fig: plt.savefig( 'png/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight', dpi=500) plt.savefig( 'svg/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') return fig def vis_sample_plain(m, s, sample, axV=None, t_on=None, t_off=None, col=['k', 'k', 'k'], print_label=False, voltage_trace=None, time_len=None, fontscale=1.0, linescale=1.0, offset=0, scale_bar=True, test_idx=None, case=None, title=None, date_today=None, counter=0, legend=True, save_fig=False): """ Function of Kaan, modified by Michael. Used for plotting fig 5b Prinz. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ if axV is None: _, ax = plt.subplots(1, len(sample), figsize=(6*len(sample),6)) font_size = 15.0 current_counter = 0 dt = m.t[1] - m.t[0] scale_bar_breadth = 500 scale_bar_voltage_breadth = 50 offscale = 100 offvolt = -50 if scale_bar: scale_col = 'k' else: scale_col = 'w' for current_sample in sample: if axV is None: axV = ax[current_counter] if voltage_trace is None: data = m.gen_single(current_sample) else: data = voltage_trace Vx = data['data'] params = data['params'] current_col = 0 for j in range(len(prinzdb.neutypes)): if time_len is not None: axV.plot(m.t[10000+offset:10000+offset+time_len:5], Vx[j, 10000+offset:10000+offset+time_len:5] + 140.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.3, c=col) else: axV.plot(m.t, Vx[j] + 120.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.3, c=col[current_col]) current_col += 1 if print_label: axV.plot([1100.0 + (offset - 26500) * (m.t[1] - m.t[0])], [300], color=col, marker='o', markeredgecolor='w', ms=8, markeredgewidth=1.0, path_effects=[pe.Stroke(linewidth=1.3, foreground='k'), pe.Normal()]) if scale_bar: # time bar axV.plot((offset+5500)*dt+offscale + np.arange(scale_bar_breadth)[::scale_bar_breadth - 1], (-40+offvolt) * np.ones_like(np.arange(scale_bar_breadth))[::scale_bar_breadth - 1], lw=1.0, color='w') # voltage bar axV.plot( (2850 + offset*dt + offscale) * np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth - 1], 275 + np.arange(scale_bar_voltage_breadth)[::scale_bar_voltage_breadth - 1], lw=1.0, color=scale_col, zorder=10) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) #if legend: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), # ncol=len(prinzdb.neutypes), fontsize=font_size*fontscale) #axV.xaxis.set_tick_params(labelsize=font_size*fontscale) #axV.yaxis.set_tick_params(labelsize=font_size*fontscale) #axV.spines['left'].set_linewidth(2.0 * linescale) #axV.spines['bottom'].set_linewidth(2.0 * linescale) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) axV.spines['bottom'].set_visible(False) axV.spines['left'].set_visible(False) #sns.set(style="ticks", font_scale=1) #sns.despine() if save_fig: plt.savefig( '../../thesis_results/pdf/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/png/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/svg/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') current_counter += 1 def vis_sample_plain_31DSynthetic(m, s, sample, axV=None, t_on=None, t_off=None, col=['k', 'k', 'k'], print_label=False, voltage_trace=None, time_len=None, fontscale=1.0, linescale=1.0, offset=0, scale_bar=True, test_idx=None, case=None, title=None, date_today=None, counter=0, legend=True, draw_patch=False, save_fig=False): """ Function of Kaan, modified by Michael. Used for plotting fig 5b Prinz. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ if axV is None: _, ax = plt.subplots(1, len(sample), figsize=(6*len(sample),6)) font_size = 15.0 current_counter = 0 dt = m.t[1] - m.t[0] scale_bar_breadth = 500 scale_bar_voltage_breadth = 50 offscale = 100 offvolt = -50 if scale_bar: scale_col = 'k' else: scale_col = 'w' for current_sample in sample: if axV is None: axV = ax[current_counter] if voltage_trace is None: data = m.gen_single(current_sample) else: data = voltage_trace Vx = data['data'] params = data['params'] current_col = 0 for j in range(len(prinzdb.neutypes)): if time_len is not None: axV.plot(m.t[10000+offset:10000+offset+time_len:5], Vx[j, 10000+offset:10000+offset+time_len:5] + 140.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.3, c=col) else: axV.plot(m.t, Vx[j] + 120.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.3, c=col[current_col]) current_col += 1 if print_label: axV.plot([1100.0 + (offset - 26500) * (m.t[1] - m.t[0])], [300], color=col, marker='o', markeredgecolor='w', ms=8, markeredgewidth=1.0, path_effects=[pe.Stroke(linewidth=1.3, foreground='k'), pe.Normal()]) if draw_patch: import matplotlib.patches as patches rect = patches.Rectangle((1650 + offscale, 266), 200, 65, linewidth=1, facecolor='w', zorder=3) axV.add_patch(rect) if scale_bar: # time bar axV.plot((offset+5500)*dt+offscale + np.arange(scale_bar_breadth)[::scale_bar_breadth - 1], (-40+offvolt) * np.ones_like(np.arange(scale_bar_breadth))[::scale_bar_breadth - 1], lw=1.0, color='w') # voltage bar axV.plot( (2850 + offset*dt + offscale) * np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth - 1], 275 + np.arange(scale_bar_voltage_breadth)[::scale_bar_voltage_breadth - 1], lw=1.0, color=scale_col, zorder=10) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) #if legend: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), # ncol=len(prinzdb.neutypes), fontsize=font_size*fontscale) #axV.xaxis.set_tick_params(labelsize=font_size*fontscale) #axV.yaxis.set_tick_params(labelsize=font_size*fontscale) #axV.spines['left'].set_linewidth(2.0 * linescale) #axV.spines['bottom'].set_linewidth(2.0 * linescale) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) axV.spines['bottom'].set_visible(False) axV.spines['left'].set_visible(False) #sns.set(style="ticks", font_scale=1) #sns.despine() if save_fig: plt.savefig( '../../thesis_results/pdf/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/png/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/svg/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') current_counter += 1 def vis_sample_plain_bit_more(m, s, sample, axV=None, t_on=None, t_off=None, col=['k', 'k', 'k'], voltage_trace=None, time_len=None, fontscale=1.0, linescale=1.0, offset=0, scale_bar=False, test_idx=None, case=None, title=None, date_today=None, counter=0, legend=True, save_fig=False): """ Function of Kaan, modified by Michael. Used for plotting fig 5b Prinz. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ if axV is None: _, ax = plt.subplots(1, len(sample), figsize=(6*len(sample),6)) font_size = 8.0 current_counter = 0 dt = m.t[1] - m.t[0] for current_sample in sample: if axV is None: axV = ax[current_counter] if voltage_trace is None: data = m.gen_single(current_sample) else: data = voltage_trace Vx = data['data'] params = data['params'] current_col = 0 for j in range(len(prinzdb.neutypes)): if time_len is not None: axV.plot(m.t[10000+offset:10000+offset+time_len], Vx[j, 10000+offset:10000+offset+time_len] + 140.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.3, c=col[current_col]) else: axV.plot(m.t, Vx[j] + 120.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.1, c=col[current_col], rasterized=True) current_col += 1 label_col = 'w' axV.text(-0.035, 0.75, 'AB/PD', fontsize=font_size, c=label_col, transform=axV.transAxes) axV.text(-0.028, 0.45, 'LP', fontsize=font_size, c=label_col, transform=axV.transAxes) axV.text(-0.03, 0.15, 'PY', fontsize=font_size, c=label_col, transform=axV.transAxes) axV.plot([1000.0+(offset-26500)*(m.t[1]-m.t[0])], [314], color=col[0], marker='o', markeredgecolor='w', ms=8, markeredgewidth=1.0, path_effects=[pe.Stroke(linewidth=1.3, foreground='k'), pe.Normal()]) scale_bar_breadth = 500 scale_bar_voltage_breadth = 50 offscale=100 offvolt =-50 if scale_bar: # time bar axV.plot((offset+5500)*dt+offscale + np.arange(scale_bar_breadth)[::scale_bar_breadth - 1], (-40+offvolt) * np.ones_like(np.arange(scale_bar_breadth))[::scale_bar_breadth - 1], lw=1.0, color='k') axV.text((offset+5500)*dt+offscale, -125, '500 ms', c=label_col, fontsize=font_size) import matplotlib.patches as patches rect = patches.Rectangle((4400+offscale, 296+offvolt), 500, 50, linewidth=1, facecolor='w', zorder=3) axV.add_patch(rect) # voltage bar axV.plot((4810+offscale) * np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth - 1], -70 + np.arange(scale_bar_voltage_breadth)[ ::scale_bar_voltage_breadth - 1] , lw=1.0, color='w', zorder=10) axV.plot( (4710 + offscale) * np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth - 1], 275 + np.arange(scale_bar_voltage_breadth)[ ::scale_bar_voltage_breadth - 1] , lw=1.0, color='k', zorder=10) axV.text(5000, -70, '50 mV', c=label_col, fontsize=8.0) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) if legend: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), ncol=len(prinzdb.neutypes), fontsize=font_size*fontscale) axV.xaxis.set_tick_params(labelsize=font_size*fontscale) axV.yaxis.set_tick_params(labelsize=font_size*fontscale) axV.spines['left'].set_linewidth(2.0 * linescale) axV.spines['bottom'].set_linewidth(2.0 * linescale) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) axV.spines['bottom'].set_visible(False) axV.spines['left'].set_visible(False) axV.set_title('') if save_fig: plt.savefig( '../../thesis_results/pdf/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/png/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/svg/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') current_counter += 1 def vis_sample_plain_bit_more_31DSynthetic(m, s, sample, axV=None, t_on=None, t_off=None, col=['k', 'k', 'k'], voltage_trace=None, time_len=None, fontscale=1.0, linescale=1.0, offset=0, scale_bar=False, test_idx=None, case=None, title=None, date_today=None, counter=0, legend=True, save_fig=False): """ Function of Kaan, modified by Michael. Used for plotting fig 5b Prinz. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ if axV is None: _, ax = plt.subplots(1, len(sample), figsize=(6*len(sample),6)) font_size = 8.0 current_counter = 0 dt = m.t[1] - m.t[0] for current_sample in sample: if axV is None: axV = ax[current_counter] if voltage_trace is None: data = m.gen_single(current_sample) else: data = voltage_trace Vx = data['data'] params = data['params'] current_col = 0 for j in range(len(prinzdb.neutypes)): if time_len is not None: axV.plot(m.t[10000+offset:10000+offset+time_len], Vx[j, 10000+offset:10000+offset+time_len] + 140.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.3, c=col[current_col]) else: axV.plot(m.t, Vx[j] + 120.0 * (2 - j), label=prinzdb.neutypes[j], lw=0.1, c=col[current_col], rasterized=True) current_col += 1 label_col = 'w' #axV.text(-0.035, 0.75, 'AB/PD', fontsize=font_size, c=label_col, transform=axV.transAxes) #axV.text(-0.028, 0.45, 'LP', fontsize=font_size, c=label_col, transform=axV.transAxes) #axV.text(-0.03, 0.15, 'PY', fontsize=font_size, c=label_col, transform=axV.transAxes) #axV.plot([1000.0+(offset-26500)*(m.t[1]-m.t[0])], [314], color=col[0], marker='o', markeredgecolor='w', ms=8, # markeredgewidth=1.0, path_effects=[pe.Stroke(linewidth=1.3, foreground='k'), pe.Normal()]) scale_bar_breadth = 500 scale_bar_voltage_breadth = 50 offscale=100 offvolt =-50 if scale_bar: draw_col = 'k' else: draw_col = 'w' # time bar axV.plot((offset+5500)*dt+offscale + np.arange(scale_bar_breadth)[::scale_bar_breadth - 1], (-40+offvolt) * np.ones_like(np.arange(scale_bar_breadth))[::scale_bar_breadth - 1], lw=1.0, color=draw_col) # voltage bar axV.plot((offset*dt)+(3100+offscale) * np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth - 1], -70 + np.arange(scale_bar_voltage_breadth)[ ::scale_bar_voltage_breadth - 1] , lw=1.0, color='w', zorder=10) axV.plot((offset*dt)+(3100 + offscale) * np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth - 1], 275 + np.arange(scale_bar_voltage_breadth)[ ::scale_bar_voltage_breadth - 1] , lw=1.0, color=draw_col, zorder=10) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) if legend: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), ncol=len(prinzdb.neutypes), fontsize=font_size*fontscale) axV.xaxis.set_tick_params(labelsize=font_size*fontscale) axV.yaxis.set_tick_params(labelsize=font_size*fontscale) axV.spines['left'].set_linewidth(2.0 * linescale) axV.spines['bottom'].set_linewidth(2.0 * linescale) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) axV.spines['bottom'].set_visible(False) axV.spines['left'].set_visible(False) axV.set_title('') if save_fig: plt.savefig( '../../thesis_results/pdf/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/png/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig( '../../thesis_results/svg/' + date_today + '_sample_prinz_plain_' + case + '_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') current_counter += 1 def vis_sample_subfig(m, s, sample, hyperparams, stats=None, t_on=None, t_off=None, with_ss=True, with_params=True, voltage_trace=None, test_idx=None, case=None, title=None, date_today=None, counter=0, save_fig=False, legend_offset=0.0, axV=None, axss=None, axmemparams=None, axsynparams=None, max_stats=None, min_stats=None, mem_dimensions=None, mode='13D', mode_for_membrane_height=None, stat_mean=None, stat_std=None, scale_bar=True, stat_scale=None, current_col='g', max_conds=None, min_conds=None, legend=True, ss_names=True, param_names=True): """ Based on vis_sample. Is called when the pdf should be shown next ot the sample. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ # Hyperparameters for plotting font_size=15.0 # fontsize of the labels col_bar = 'k' # color of the bars for summstats and conductances col_minmax = 'k' # color of the horizontal line indicating the max and min value of summstats and conds col_shade = 'k' # color of the shade between the max and min values values_each = 100 # not so important. How many values we evaluate for the max and min values indicator_fraction = 0.8 # breath of the horizontal bars for max and min, should be within [0,1] opacity = 0.5 # opacity of the shade width = 0.35 # the width of the bars neuron_labels = ['AB/PD', 'LP', 'PY'] # labels for the legends scale_bar_breadth = 1000 scale_bar_voltage_breadth = 50 if voltage_trace is None: data = m.gen_single(sample) else: data = voltage_trace Vx = data['data'] params = data['params'] #stats = s.calc([data])[0] stats_nan = deepcopy(stats) #stats[np.isnan(stats)]=0.0 #stats = scale_to_experimental(stats) bar_scaling_factors = [1.0, 10, 100, 10, 100, 1, 10000, 10000] bar_scaling_factors = np.asarray([[1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000]]) bar_vals = bar_scaling_factors[np.asarray(hyperparams.use_membrane)] if mem_dimensions is not None: params_trunc = params[mem_dimensions].tolist() params_trunc += params[-7:].tolist() bar_vals = bar_vals[mem_dimensions] params = np.asarray(params_trunc) step_Vtrace = 10 if legend: for j in range(len(prinzdb.neutypes)): axV.plot(m.t[25500:25500+200000:step_Vtrace], Vx[j,25500:25500+200000:step_Vtrace]+140.0*(2-j), label=neuron_labels[j]) else: for j in range(len(prinzdb.neutypes)): axV.plot(m.t[25500:25500+200000:step_Vtrace], Vx[j,25500:25500+200000:step_Vtrace]+140.0*(2-j), label=neuron_labels[j], c='k', lw=0.6) if scale_bar: axV.plot(4810+np.arange(scale_bar_breadth)[::scale_bar_breadth-1], 358*np.ones_like(np.arange(scale_bar_breadth))[::scale_bar_breadth-1], lw=1.0, color='k') axV.text(4845, 364, '1 sec', fontsize=font_size) import matplotlib.patches as patches rect = patches.Rectangle((5400, 296), 500, 50, linewidth=1, facecolor='w', zorder=3) axV.add_patch(rect) axV.plot(5810*np.ones_like(np.arange(scale_bar_voltage_breadth))[::scale_bar_voltage_breadth-1], 358-scale_bar_voltage_breadth+np.arange(scale_bar_voltage_breadth)[::scale_bar_voltage_breadth-1] , lw=1.0, color='k',zorder=10) axV.text(5430, 310, '50 mV', fontsize=font_size) axV.plot(m.t[22500]+20, 325, color=current_col, marker='o', markeredgecolor='w', ms=22, markeredgewidth=0.5) if not legend: axV.text(-0.08, 0.75, 'AB/PD', fontsize=font_size, transform=axV.transAxes) axV.text(-0.04, 0.45, 'LP', fontsize=font_size, transform=axV.transAxes) axV.text(-0.045, 0.15, 'PY', fontsize=font_size, transform=axV.transAxes) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) if legend: if scale_bar: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=len(prinzdb.neutypes), fontsize=font_size) else: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), ncol=len(prinzdb.neutypes), fontsize=font_size) axV.xaxis.set_tick_params(labelsize=font_size) axV.yaxis.set_tick_params(labelsize=font_size) #axV.set_xlim((m.t[25500] - 400, 11500)) axV.set_xlim((m.t[25500] - 200, m.t[25500+200000]+200)) if scale_bar: axV.set_ylim((-95, 360)) if with_params: lticks = np.arange(len(params[:-7])) end_of_time_axis = len(params[:-7]) - 1 + width full_time = np.linspace(width/2-0.5, end_of_time_axis+0.5-width/2, values_each * len(params[:-7])) full_min_conds = np.tile(bar_vals * min_conds[:-7] / 0.628e-3, (values_each, 1)) full_min_conds = full_min_conds.flatten(order='F') full_max_conds = np.tile(bar_vals * max_conds[:-7] / 0.628e-3, (values_each, 1)) full_max_conds = full_max_conds.flatten(order='F') axmemparams.bar(lticks + width / 2, bar_vals * params[:-7] / 0.628e-3, width, bottom=min(1e-8, np.min(params[:-7])), color=col_bar) #min_conds_scaled = bar_vals * deepcopy(min_conds[:-7]) / 0.628e-3 #max_conds_scaled = bar_vals * deepcopy(max_conds[:-7]) / 0.628e-3 #axmemparams.plot(width / 2+np.arange(len(min_conds_scaled)), min_conds_scaled, col1) #axmemparams.plot(width / 2+np.arange(len(min_conds_scaled)), max_conds_scaled, col2) #axmemparams.fill_between(width / 2+np.arange(len(max_conds_scaled)), min_conds_scaled, max_conds_scaled, # facecolor=col3, alpha=0.5) for k in range(len(params[:-7])): start_t = int(values_each*k+(1-indicator_fraction)/2*values_each) end_t = int(values_each*(k+1)-(1-indicator_fraction)/2*values_each) time_diff = end_t - start_t axmemparams.plot(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], col_minmax) axmemparams.plot(full_time[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], col_minmax) axmemparams.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) names = viz.get_labels(hyperparams, mathmode=True, include_q10=False)[:-7] if mem_dimensions is not None: names = names[mem_dimensions] axmemparams.set_ylim((0, 700)) # 850 axmemparams.set_xticks(lticks + width / 2) if param_names: axmemparams.set_xticklabels(names, rotation='vertical', fontsize=font_size) else: axmemparams.axes.get_xaxis().set_visible(False) axmemparams.axes.get_yaxis().set_visible(False) axmemparams.xaxis.set_tick_params(labelsize=font_size) axmemparams.yaxis.set_tick_params(labelsize=font_size) small_offset = [0.00, -0.0, -0.0, 0.0, -0.00, 0.0] font_decrease = 1.7 if mode == '13D': for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -390, 'x', fontsize=font_size / 2) axmemparams.set_ylim((0, 600)) # 850 small_offset = [0.15, -0.04, -0.1, 0.0, -0.02, 0.0] for i in range(6): if i == 2 or i == 3 or i == 4 or i == 5: # -620 axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -450, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]), include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: axmemparams.text(-0.2 + i * 1.0 + small_offset[i], -450, r'$%s$' % str(int(bar_vals[i])), fontsize=font_size / font_decrease) axmemparams.text(0.11, -0.95, r'Membrane $\mathregular{\bar g}$', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.22, -1.12, '[mS/cm'+chr(0x00b0 + 2)+']', fontsize=font_size, transform=axmemparams.transAxes) else: if mode_for_membrane_height == 'high': axmemparams.set_ylim((0, 1000)) for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -650, 'x', fontsize=font_size / 2) for i in range(6): if bar_vals[i] == 1: axmemparams.text(-0.2 + i * 1.02 + 0.18, -750, r'$1$', fontsize=font_size / font_decrease) elif bar_vals[i] == 10: axmemparams.text(-0.2 + i * 1.0 + 0.05, -750, r'$10$', fontsize=font_size / font_decrease) else: axmemparams.text(-0.2 + i * 1.0, -750, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]), include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -470, 'x', fontsize=font_size / 2) for i in range(6): if i==0 or i==1 or i == 2 or i == 3 or i == 4 or i == 5: #-620 axmemparams.text(-0.2+i*1.0+small_offset[i], -530, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]),include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: axmemparams.text(-0.2+i*1.0+small_offset[i], -530, r'$%s$' % str(int(bar_vals[i])), fontsize=font_size/font_decrease) axmemparams.text(0.11, -0.95, r'Membrane $\mathregular{\bar g}$', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.22, -1.12, '[mS/cm' + chr(0x00b0 + 2) + ']', fontsize=font_size, transform=axmemparams.transAxes) lticks = np.arange(len(params[-7:])) end_of_time_axis = len(params[-7:])-1+width full_time = np.linspace(width/2-0.5, end_of_time_axis+0.5-width/2, values_each * len(params[-7:])) full_min_conds = np.tile(min_conds[-7:] * 1e-3, (values_each,1)) full_min_conds = full_min_conds.flatten(order='F') full_max_conds = np.tile(max_conds[-7:] * 1e-3, (values_each, 1)) full_max_conds = full_max_conds.flatten(order='F') axsynparams.bar(lticks + width / 2, params[-7:]*1e-3, width, color=col_bar) #axsynparams.plot(width / 2+np.arange(len(min_conds[-7:])), min_conds[-7:]*0.628e-3, col1) #axsynparams.plot(width / 2+np.arange(len(min_conds[-7:])), max_conds[-7:]*0.628e-3, col2) #axsynparams.fill_between(width / 2 + np.arange(len(min_conds[-7:])), min_conds[-7:] * 0.628e-3, # max_conds[-7:] * 0.628e-3, facecolor=col3, alpha=0.5) for k in range(len(params[-7:])): start_t = int(values_each * k + (1 - indicator_fraction) / 2 * values_each) end_t = int(values_each * (k + 1) - (1 - indicator_fraction) / 2 * values_each) time_diff = end_t - start_t axsynparams.plot(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], col_minmax) axsynparams.plot(full_time[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], col_minmax) axsynparams.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) axsynparams.text(0.22, -0.95, r'Synaptic $\mathregular{\bar g}$', fontsize=font_size, transform=axsynparams.transAxes) axsynparams.text(0.4, -1.12, '[nS]', fontsize=font_size, transform=axsynparams.transAxes) names = viz.get_labels(hyperparams, include_q10=False)[-7:] #axsynparams.set_ylabel('Synapses', fontsize=font_size) axsynparams.set_yscale('log') axsynparams.set_ylim((1e-8*1e-3, 1.3*1e-3*1e-3)) axsynparams.set_xticks(lticks + width / 2) axsynparams.set_yticks([1e-11, 1e-9, 1e-7]) #locmin = matplotlib.ticker.LogLocator(base=10.0, subs=(0.2, 0.4, 0.6, 0.8), numticks=12) #axsynparams.yaxis.set_minor_locator(locmin) #axsynparams.yaxis.set_minor_formatter(matplotlib.ticker.NullFormatter()) if param_names: axsynparams.set_xticklabels(names, rotation='vertical', fontsize=font_size) else: axsynparams.axes.get_xaxis().set_visible(False) axsynparams.axes.get_yaxis().set_visible(False) axsynparams.xaxis.set_tick_params(labelsize=font_size) axsynparams.yaxis.set_tick_params(labelsize=font_size) axsynparams.spines['right'].set_visible(False) axsynparams.spines['top'].set_visible(False) axmemparams.spines['right'].set_visible(False) axmemparams.spines['top'].set_visible(False) if with_ss: lticks = np.arange(len(stats)) if stat_scale is None: stats[8:] *= 2000 min_stats_scaled = deepcopy(min_stats) max_stats_scaled = deepcopy(max_stats) if stat_scale is None: min_stats_scaled[8:] = min_stats_scaled[8:] * 2000 max_stats_scaled[8:] = max_stats_scaled[8:] * 2000 axss.bar(lticks + width / 2, stats, width, color=col_bar) #axss.plot(width / 2+np.arange(len(min_stats_scaled)), min_stats_scaled, col1) #axss.plot(width / 2+np.arange(len(min_stats_scaled)), max_stats_scaled, col2) #axss.fill_between(width / 2+np.arange(len(min_stats_scaled)), min_stats_scaled, max_stats_scaled, # facecolor=col3, alpha=0.5) end_of_time_axis = len(stats) - 1 + width full_time = np.linspace(width / 2 - 0.5, end_of_time_axis + 0.5 - width / 2, values_each * len(stats)) full_min_ss = np.tile(min_stats_scaled, (values_each, 1)) full_min_ss = full_min_ss.flatten(order='F') full_max_ss = np.tile(max_stats_scaled, (values_each, 1)) full_max_ss = full_max_ss.flatten(order='F') for k in range(len(stats)): start_t = int(values_each * k + (1 - indicator_fraction) / 2 * values_each) end_t = int(values_each * (k + 1) - (1 - indicator_fraction) / 2 * values_each) time_diff = end_t - start_t axss.plot(full_time[start_t:end_t][::time_diff-1], full_min_ss[start_t:end_t][::time_diff-1], col_minmax) axss.plot(full_time[start_t:end_t][::time_diff-1], full_max_ss[start_t:end_t][::time_diff-1], col_minmax) axss.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_ss[start_t:end_t][::time_diff-1], full_max_ss[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) axss.text(0.27, -0.95, 'Summary statistics', fontsize=font_size, transform=axss.transAxes) axss.text(0.145, -1.12, '[st. dev. of experimental data]', fontsize=font_size, transform=axss.transAxes) nan_pos = np.where(np.isnan(stats_nan))[0] if stat_scale is not None: axss.scatter(nan_pos+width/2, 3.5*np.ones_like(nan_pos), c='k', s=70.0, zorder=2, marker='x') else: axss.scatter(nan_pos + width / 2, 1900 * np.ones_like(nan_pos), c='k', s=70.0, zorder=2, marker='x') # add some text for labels, title and axes ticks names = [] for num in range(15): names.append(get_summ_stat_name(num)) #axss.set_ylabel('Summary Statistics', fontsize=font_size) axss.set_yticks([-4, -2, 0, 2, 4]) axss.set_yticklabels([r'$-4 \sigma$', '$-2 \sigma$', '0', '$2 \sigma$', '$4 \sigma$']) #axss.axes.get_yaxis().set_ticks([]) axss.set_xticks(lticks + width / 2) if ss_names: axss.set_xticklabels(names, rotation='vertical', fontsize=font_size) else: axss.axes.get_xaxis().set_visible(False) axss.axes.get_yaxis().set_visible(False) axss.xaxis.set_tick_params(labelsize=font_size) axss.yaxis.set_tick_params(labelsize=font_size) if stat_scale is not None: axss.set_ylim([-4.0, 4.0]) else: axss.set_ylim([-450, 2100]) axss.spines['right'].set_visible(False) axss.spines['top'].set_visible(False) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) sns.set(style="ticks", font_scale=1) sns.despine() axV.set_title('') if save_fig: plt.savefig('../../thesis_results/pdf/'+date_today+'_sample_prinz_'+case+'_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/png/'+date_today+'_sample_prinz_'+case+'_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/svg/'+date_today+'_sample_prinz_'+case+'_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') return axV, axss, axmemparams, axsynparams def vis_sample_subfig_twitter(m, s, sample, hyperparams, stats=None, t_on=None, t_off=None, with_ss=False, with_params=False, voltage_trace=None, test_idx=None, case=None, title=None, date_today=None, counter=0, save_fig=False, legend_offset=0.0, axV=None, axss=None, axmemparams=None, axsynparams=None, max_stats=None, min_stats=None, mem_dimensions=None, mode='13D', mode_for_membrane_height=None, offset=0, stat_mean=None, stat_std=None, scale_bar=True, stat_scale=None, current_col='g', max_conds=None, min_conds=None, legend=True, ss_names=True, param_names=True): """ Based on vis_sample. Is called when the pdf should be shown next ot the sample. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ # Hyperparameters for plotting font_size=15.0 # fontsize of the labels col_bar = 'k' # color of the bars for summstats and conductances col_minmax = 'k' # color of the horizontal line indicating the max and min value of summstats and conds col_shade = 'k' # color of the shade between the max and min values values_each = 100 # not so important. How many values we evaluate for the max and min values indicator_fraction = 0.8 # breath of the horizontal bars for max and min, should be within [0,1] opacity = 0.5 # opacity of the shade width = 0.35 # the width of the bars neuron_labels = ['AB/PD', 'LP', 'PY'] # labels for the legends scale_bar_breadth = 1000 scale_bar_voltage_breadth = 50 if voltage_trace is None: data = m.gen_single(sample) else: data = voltage_trace Vx = data['data'] params = data['params'] #stats = s.calc([data])[0] stats_nan = deepcopy(stats) #stats[np.isnan(stats)]=0.0 #stats = scale_to_experimental(stats) bar_scaling_factors = [1.0, 10, 100, 10, 100, 1, 10000, 10000] bar_scaling_factors = np.asarray([[1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000]]) bar_vals = bar_scaling_factors[np.asarray(hyperparams.use_membrane)] if mem_dimensions is not None: params_trunc = params[mem_dimensions].tolist() params_trunc += params[-7:].tolist() bar_vals = bar_vals[mem_dimensions] params = np.asarray(params_trunc) step_Vtrace = 5 for j in range(len(prinzdb.neutypes)): axV.plot(m.t[25500+offset:25500+115000+offset:step_Vtrace], Vx[j,25500+offset:25500+115000+offset:step_Vtrace]+140.0*(2-j), label=neuron_labels[j], c='k', lw=0.6) box = axV.get_position() if t_on is not None: axV.axvline(t_on, c='r', ls='--') if t_on is not None: axV.axvline(t_off, c='r', ls='--') axV.set_position([box.x0, box.y0, box.width, box.height]) axV.axes.get_yaxis().set_ticks([]) axV.axes.get_xaxis().set_ticks([]) if legend: if scale_bar: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.15), ncol=len(prinzdb.neutypes), fontsize=font_size) else: axV.legend(loc='upper center', bbox_to_anchor=(0.5, 1.18), ncol=len(prinzdb.neutypes), fontsize=font_size) axV.xaxis.set_tick_params(labelsize=font_size) axV.yaxis.set_tick_params(labelsize=font_size) axV.spines['right'].set_visible(False) axV.spines['top'].set_visible(False) axV.spines['bottom'].set_visible(False) axV.spines['left'].set_visible(False) sns.set(style="ticks", font_scale=1) sns.despine() axV.set_title('') if save_fig: plt.savefig('../../thesis_results/pdf/'+date_today+'_sample_prinz_'+case+'_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/png/'+date_today+'_sample_prinz_'+case+'_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/svg/'+date_today+'_sample_prinz_'+case+'_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') return axV def vis_sample_subfig_no_voltage(m, s, sample, hyperparams, stats=None, t_on=None, t_off=None, with_ss=True, with_params=True, voltage_trace=None, test_idx=None, case=None, title=None, date_today=None, counter=0, save_fig=False, legend_offset=0.0, axss=None, axmemparams=None, axsynparams=None, max_stats=None, min_stats=None, mem_dimensions=None, mode='13D', mode_for_membrane_height=None, labels_=True, color_input='k', stat_mean=None, stat_std=None, scale_bar=True, stat_scale=None, current_col='g', max_conds=None, min_conds=None, legend=True, ss_names=True, param_names=True): """ Based on vis_sample. Is called when the pdf should be shown next ot the sample. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ # Hyperparameters for plotting font_size=8.0 # fontsize of the labels col_bar = color_input # color of the bars for summstats and conductances col_minmax = color_input # color of the horizontal line indicating the max and min value of summstats and conds col_shade = color_input # color of the shade between the max and min values values_each = 100 # not so important. How many values we evaluate for the max and min values indicator_fraction = 0.8 # breath of the horizontal bars for max and min, should be within [0,1] opacity = 0.5 # opacity of the shade width = 0.35 # the width of the bars neuron_labels = ['AB/PD', 'LP', 'PY'] # labels for the legends scale_bar_breadth = 1000 scale_bar_voltage_breadth = 50 plot_bars=False if voltage_trace is None: data = m.gen_single(sample) else: data = voltage_trace params = sample stats_nan = deepcopy(stats) bar_scaling_factors = np.asarray([[1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000]]) bar_vals = bar_scaling_factors[np.asarray(hyperparams.use_membrane)] if mem_dimensions is not None: params_trunc = params[mem_dimensions].tolist() params_trunc += params[-7:].tolist() bar_vals = bar_vals[mem_dimensions] params = np.asarray(params_trunc) if with_params: lticks = np.arange(len(params[:-7])) end_of_time_axis = len(params[:-7]) - 1 + width full_time = np.linspace(width/2-0.5, end_of_time_axis+0.5-width/2, values_each * len(params[:-7])) full_min_conds = np.tile(bar_vals * min_conds[:-7] / 0.628e-3, (values_each, 1)) full_min_conds = full_min_conds.flatten(order='F') full_max_conds = np.tile(bar_vals * max_conds[:-7] / 0.628e-3, (values_each, 1)) full_max_conds = full_max_conds.flatten(order='F') if plot_bars: axmemparams.bar(lticks + width / 2, bar_vals * params[:-7] / 0.628e-3, width, bottom=min(1e-8, np.min(params[:-7])), color=col_bar) for k in range(len(params[:-7])): start_t = int(values_each*k+(1-indicator_fraction)/2*values_each) end_t = int(values_each*(k+1)-(1-indicator_fraction)/2*values_each) time_diff = end_t - start_t axmemparams.plot(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], c=col_minmax) axmemparams.plot(full_time[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], c=col_minmax) axmemparams.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) names = viz.get_labels_8pt(hyperparams, include_q10=False)[:-7] if mem_dimensions is not None: names = names[mem_dimensions] axmemparams.set_ylim((0, 1000)) # 850 axmemparams.set_xticks(lticks + width / 2) new_names = [] count = 0 for n in names: #if int(bar_vals[count]): # new_names.append(str(int(bar_vals[count])) + ' ' + 'x ' + n) #else: new_names.append(str(int(bar_vals[count]))+' '+'x '+n) count += 1 if param_names: axmemparams.set_xticklabels(new_names, rotation='vertical', fontsize=font_size) else: axmemparams.axes.get_xaxis().set_visible(False) #axmemparams.axes.get_yaxis().set_visible(False) axmemparams.xaxis.set_tick_params(labelsize=font_size) axmemparams.yaxis.set_tick_params(labelsize=font_size) small_offset = [0.00, -0.0, -0.0, 0.0, -0.00, 0.0] font_decrease = 1.7 if labels_: if mode == '13D': axmemparams.set_ylim((0, 1000)) # 850 axmemparams.text(0.36, -1.04, 'Membrane conductances', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.43, -1.20, r'$\mathdefault{[mS/cm}^2\mathdefault{]}$', fontsize=font_size, transform=axmemparams.transAxes) else: if mode_for_membrane_height == 'high': axmemparams.set_ylim((0, 1000)) for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -650, 'x', fontsize=font_size / 2) for i in range(6): if bar_vals[i] == 1: axmemparams.text(-0.2 + i * 1.02 + 0.18, -750, r'$1$', fontsize=font_size / font_decrease) elif bar_vals[i] == 10: axmemparams.text(-0.2 + i * 1.0 + 0.05, -750, r'$10$', fontsize=font_size / font_decrease) else: axmemparams.text(-0.2 + i * 1.0, -750, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]), include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: for i in range(6): # 520 or so axmemparams.text(-0.0 + i * 1.03, -470, 'x', fontsize=font_size / 2) for i in range(6): if i==0 or i==1 or i == 2 or i == 3 or i == 4 or i == 5: #-620 axmemparams.text(-0.2+i*1.0+small_offset[i], -530, r'$%s$' % build_string(conductance_to_value_exp([bar_vals[i]]),include_multiplier=False, negative_num=False), fontsize=font_size / font_decrease) else: axmemparams.text(-0.2+i*1.0+small_offset[i], -530, r'$%s$' % str(int(bar_vals[i])), fontsize=font_size/font_decrease) #axmemparams.text(0.11, -1.50, r'Membrane $\mathregular{\bar g}$', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.11, -1.60, r'Membrane $\mathregular{\bar g}$', fontsize=font_size, transform=axmemparams.transAxes) axmemparams.text(0.22, -1.77, '[mS/cm' + chr(0x00b0 + 2) + ']', fontsize=font_size, transform=axmemparams.transAxes) lticks = np.arange(len(params[-7:])) end_of_time_axis = len(params[-7:])-1+width full_time = np.linspace(width/2-0.5, end_of_time_axis+0.5-width/2, values_each * len(params[-7:])) full_min_conds = np.tile(min_conds[-7:] * 1e-3, (values_each,1)) full_min_conds = full_min_conds.flatten(order='F') full_max_conds = np.tile(max_conds[-7:] * 1e-3, (values_each, 1)) full_max_conds = full_max_conds.flatten(order='F') full_min_conds *= 1e9 full_max_conds *= 1e9 if plot_bars: axsynparams.bar(lticks + width / 2, params[-7:]*1e-3, width, color=col_bar) for k in range(len(params[-7:])): start_t = int(values_each * k + (1 - indicator_fraction) / 2 * values_each) end_t = int(values_each * (k + 1) - (1 - indicator_fraction) / 2 * values_each) time_diff = end_t - start_t axsynparams.plot(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], c=col_minmax) axsynparams.plot(full_time[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], c=col_minmax) axsynparams.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_conds[start_t:end_t][::time_diff-1], full_max_conds[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) if labels_: #axsynparams.text(0.27, -0.85, r'Synaptic $\mathregular{\bar g}$', fontsize=font_size, transform=axsynparams.transAxes) axsynparams.text(0.09, -1.04, 'Synaptic conductances', fontsize=font_size, transform=axsynparams.transAxes) axsynparams.text(0.37, -1.19, '[nS]', fontsize=font_size, transform=axsynparams.transAxes) names = viz.get_labels_8pt(hyperparams, mathmode=True, include_q10=False)[-7:] axsynparams.set_yscale('log') # axsynparams.set_ylim((1e-8*1e-3*1e9, 1.3*1e-3*1e-3*1e9)) axsynparams.set_xticks(lticks + width / 2) #axsynparams.set_yticks([0.01, 1.0, 100]) axsynparams.set_ylim([0.01, 1000]) if param_names: axsynparams.set_xticklabels(names, rotation='vertical', fontsize=font_size) else: axsynparams.axes.get_xaxis().set_visible(False) axsynparams.xaxis.set_tick_params(labelsize=font_size) axsynparams.yaxis.set_tick_params(labelsize=font_size) axsynparams.spines['right'].set_visible(False) axsynparams.spines['top'].set_visible(False) axmemparams.spines['right'].set_visible(False) axmemparams.spines['top'].set_visible(False) axmemparams.tick_params(width=2.0 * 0.666, length=5.0 * 0.666) axsynparams.tick_params(width=2.0 * 0.666, length=5.0 * 0.666) axmemparams.tick_params(width=2.0 * 0.4, length=5.0 * 0.4, which='minor') axsynparams.tick_params(width=2.0 * 0.4, length=5.0 * 0.4, which='minor') if with_ss: lticks = np.arange(len(stats)) if stat_scale is None: stats[8:] *= 2000 min_stats_scaled = deepcopy(min_stats) max_stats_scaled = deepcopy(max_stats) if stat_scale is None: min_stats_scaled[8:] = min_stats_scaled[8:] * 2000 max_stats_scaled[8:] = max_stats_scaled[8:] * 2000 if plot_bars: axss.bar(lticks + width / 2, stats, width, color=col_bar) end_of_time_axis = len(stats) - 1 + width full_time = np.linspace(width / 2 - 0.5, end_of_time_axis + 0.5 - width / 2, values_each * len(stats)) full_min_ss = np.tile(min_stats_scaled, (values_each, 1)) full_min_ss = full_min_ss.flatten(order='F') full_max_ss = np.tile(max_stats_scaled, (values_each, 1)) full_max_ss = full_max_ss.flatten(order='F') for k in range(len(stats)): start_t = int(values_each * k + (1 - indicator_fraction) / 2 * values_each) end_t = int(values_each * (k + 1) - (1 - indicator_fraction) / 2 * values_each) time_diff = end_t - start_t axss.plot(full_time[start_t:end_t][::time_diff-1], full_min_ss[start_t:end_t][::time_diff-1], c=col_minmax) axss.plot(full_time[start_t:end_t][::time_diff-1], full_max_ss[start_t:end_t][::time_diff-1], c=col_minmax) axss.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_ss[start_t:end_t][::time_diff-1], full_max_ss[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) if labels_: axss.text(0.33, -0.68, 'Summary statistics', fontsize=font_size, transform=axss.transAxes) axss.text(0.322, -0.80, '[st. dev. of samples]', fontsize=font_size, transform=axss.transAxes) nan_pos = np.where(np.isnan(stats_nan))[0] if stat_scale is not None: axss.scatter(nan_pos+width/2, 1.7*np.ones_like(nan_pos), c=col_minmax, s=25.0, zorder=2, marker='x') else: axss.scatter(nan_pos + width / 2, 1900 * np.ones_like(nan_pos), c=col_minmax, s=25.0, zorder=2, marker='x') # add some text for labels, title and axes ticks names = [] for num in range(15): names.append(get_summ_stat_name_text(num)) #axss.set_yticks([-4, -2, 0, 2, 4]) axss.set_yticks([-2, -1, 0, 1, 2]) #axss.set_yticklabels([r'$-4 \sigma$', '$-2 \sigma$', '0', '$2 \sigma$', '$4 \sigma$']) axss.set_yticklabels(['$\mathdefault{-2} \sigma$', '$\mathdefault{-}\sigma$', '0', '$\sigma$', '$\mathdefault{2} \sigma$']) axss.set_xticks(lticks + width / 2) if ss_names: axss.set_xticklabels(names, rotation='vertical', fontsize=font_size) else: axss.axes.get_xaxis().set_visible(False) #axss.axes.get_yaxis().set_visible(False) axss.xaxis.set_tick_params(labelsize=font_size) axss.yaxis.set_tick_params(labelsize=font_size) if stat_scale is not None: axss.set_ylim([-2.0, 2.0]) else: axss.set_ylim([-450, 2100]) axss.spines['right'].set_visible(False) axss.spines['top'].set_visible(False) axss.tick_params(width=2.0 * 0.666, length=5.0 * 0.666) #axss.get_xaxis().set_tick_params( # which='both', direction='out', labelsize=font_size*3) sns.set(style="ticks", font_scale=1) sns.despine() if save_fig: plt.savefig('../../thesis_results/pdf/'+date_today+'_sample_prinz_'+case+'_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/png/'+date_today+'_sample_prinz_'+case+'_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/svg/'+date_today+'_sample_prinz_'+case+'_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') if axmemparams is not None and axss is not None: return axss, axmemparams, axsynparams elif axss is not None: return axss elif axmemparams is not None: return axmemparams, axsynparams def vis_ss_barplot(m, s, sample, hyperparams, stats=None, t_on=None, t_off=None, with_ss=True, with_params=True, voltage_trace=None, test_idx=None, case=None, title=None, date_today=None, counter=0, save_fig=False, legend_offset=0.0, axss=None, axmemparams=None, axsynparams=None, max_stats=None, min_stats=None, mem_dimensions=None, mode='13D', mode_for_membrane_height=None, labels_=True, color_input='k', stat_mean=None, stat_std=None, scale_bar=True, stat_scale=None, current_col='g', max_conds=None, min_conds=None, legend=True, ss_names=True, param_names=True): """ Based on vis_sample. Is called when the pdf should be shown next ot the sample. :param m: generator object, from m = netio.create_simulators(params)[0] :param s: summstat object, from s = netio.create_summstats(params) :param sample: membrane/synaptic conductances :param t_on: :param t_off: :param with_ss: bool, True if bars for summary stats are wanted :param with_params: bool, True if bars for parameters are wanted :return: figure object """ # Hyperparameters for plotting font_size=8.0 # fontsize of the labels col_bar = color_input # color of the bars for summstats and conductances col_minmax = color_input # color of the horizontal line indicating the max and min value of summstats and conds col_shade = color_input # color of the shade between the max and min values values_each = 100 # not so important. How many values we evaluate for the max and min values indicator_fraction = 0.8 # breath of the horizontal bars for max and min, should be within [0,1] opacity = 0.5 # opacity of the shade width = 0.35 # the width of the bars neuron_labels = ['AB/PD', 'LP', 'PY'] # labels for the legends scale_bar_breadth = 1000 scale_bar_voltage_breadth = 50 plot_bars=False params = sample stats_nan = deepcopy(stats) bar_scaling_factors = np.asarray([[1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000], [1.0, 100.0, 100.0, 10.0, 100.0, 1.0, 10000, 10000]]) bar_vals = bar_scaling_factors[np.asarray(hyperparams.use_membrane)] if mem_dimensions is not None: params_trunc = params[mem_dimensions].tolist() params_trunc += params[-7:].tolist() bar_vals = bar_vals[mem_dimensions] params = np.asarray(params_trunc) if with_ss: lticks = np.arange(len(stats)) if stat_scale is None: stats[8:] *= 2000 min_stats_scaled = deepcopy(min_stats) max_stats_scaled = deepcopy(max_stats) if stat_scale is None: min_stats_scaled[8:] = min_stats_scaled[8:] * 2000 max_stats_scaled[8:] = max_stats_scaled[8:] * 2000 if plot_bars: axss.bar(lticks + width / 2, stats, width, color=col_bar) end_of_time_axis = len(stats) - 1 + width full_time = np.linspace(width / 2 - 0.5, end_of_time_axis + 0.5 - width / 2, values_each * len(stats)) full_min_ss = np.tile(min_stats_scaled, (values_each, 1)) full_min_ss = full_min_ss.flatten(order='F') full_max_ss = np.tile(max_stats_scaled, (values_each, 1)) full_max_ss = full_max_ss.flatten(order='F') for k in range(len(stats)): start_t = int(values_each * k + (1 - indicator_fraction) / 2 * values_each) end_t = int(values_each * (k + 1) - (1 - indicator_fraction) / 2 * values_each) time_diff = end_t - start_t axss.plot(full_time[start_t:end_t][::time_diff-1], full_min_ss[start_t:end_t][::time_diff-1], c=col_minmax) axss.plot(full_time[start_t:end_t][::time_diff-1], full_max_ss[start_t:end_t][::time_diff-1], c=col_minmax) axss.fill_between(full_time[start_t:end_t][::time_diff-1], full_min_ss[start_t:end_t][::time_diff-1], full_max_ss[start_t:end_t][::time_diff-1], facecolor=col_shade, alpha=opacity) if labels_: axss.text(0.33, -0.68, 'Summary statistics', fontsize=font_size, transform=axss.transAxes) axss.text(0.322, -0.80, '[st. dev. of samples]', fontsize=font_size, transform=axss.transAxes) nan_pos = np.where(np.isnan(stats_nan))[0] if stat_scale is not None: axss.scatter(nan_pos+width/2, 1.7*np.ones_like(nan_pos), c=col_minmax, s=25.0, zorder=2, marker='x') else: axss.scatter(nan_pos + width / 2, 1900 * np.ones_like(nan_pos), c=col_minmax, s=25.0, zorder=2, marker='x') # add some text for labels, title and axes ticks names = [] for num in range(15): names.append(get_summ_stat_name_text(num)) #axss.set_yticks([-4, -2, 0, 2, 4]) axss.set_yticks([-2, -1, 0, 1, 2]) #axss.set_yticklabels([r'$-4 \sigma$', '$-2 \sigma$', '0', '$2 \sigma$', '$4 \sigma$']) axss.set_yticklabels(['$\mathdefault{-2} \sigma$', '$\mathdefault{-}\sigma$', '0', '$\sigma$', '$\mathdefault{2} \sigma$']) axss.set_xticks(lticks + width / 2) if ss_names: axss.set_xticklabels(names, rotation='vertical', fontsize=font_size) else: axss.axes.get_xaxis().set_visible(False) #axss.axes.get_yaxis().set_visible(False) axss.xaxis.set_tick_params(labelsize=font_size) axss.yaxis.set_tick_params(labelsize=font_size) if stat_scale is not None: axss.set_ylim([-2.0, 2.0]) else: axss.set_ylim([-450, 2100]) axss.spines['right'].set_visible(False) axss.spines['top'].set_visible(False) axss.tick_params(width=2.0 * 0.666, length=5.0 * 0.666) #axss.get_xaxis().set_tick_params( # which='both', direction='out', labelsize=font_size*3) sns.set(style="ticks", font_scale=1) sns.despine() if save_fig: plt.savefig('../../thesis_results/pdf/'+date_today+'_sample_prinz_'+case+'_{}_{}.pdf'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/png/'+date_today+'_sample_prinz_'+case+'_{}_{}.png'.format(test_idx[0], counter), bbox_inches='tight') plt.savefig('../../thesis_results/svg/'+date_today+'_sample_prinz_'+case+'_{}_{}.svg'.format(test_idx[0], counter), bbox_inches='tight') if axmemparams is not None and axss is not None: return axss, axmemparams, axsynparams elif axss is not None: return axss elif axmemparams is not None: return axmemparams, axsynparams

49.073156

224

0.588293

11,289

81,167

4.023297

0.043937

0.025892

0.035932

0.010788

0.946388

0.937625

0.925802

0.914793

0.905876

0.897114

0

0.053277

0.27526

81,167

1,653

225

49.102843

0.718827

0.12765

0

0.830938

0

0.045176

0.009753

0

0.000427

0

1

0.007608

false

0

0.016061

0

0.031276

0.005072

0

null

0

1

0

1

0

null

0

7

19aba72551d2a2fafcdd1e66e724fbe8c7260961

28,563

py

Python

data/dataloader.py

DLWK/EANet

3680e099dd815117d4a54f928fb8247aa2f0b71a

[ "MIT" ]

14

2021-04-17T14:28:58.000Z

2022-03-28T09:38:24.000Z

data/dataloader.py

DLWK/EANet

3680e099dd815117d4a54f928fb8247aa2f0b71a

[ "MIT" ]

2

2021-12-13T14:12:45.000Z

2022-03-31T14:37:33.000Z

data/dataloader.py

DLWK/EANet

3680e099dd815117d4a54f928fb8247aa2f0b71a

[ "MIT" ]

3

2021-07-14T14:15:53.000Z

2022-03-31T12:14:34.000Z

import torch import cv2 import os import glob from torch.utils.data import Dataset import random import torch.nn.functional as F # class ISBI_Loader(Dataset): # def __init__(self, data_path,transform): # # 初始化函数，读取所有data_path下的图片 # self.data_path = data_path # self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.jpg')) # self.transform=transform # def augment(self, image, flipCode): # # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 # flip = cv2.flip(image, flipCode) # return flip # def __getitem__(self, index): # # 根据index读取图片 # image_path = self.imgs_path[index] # # 根据image_path生成label_path # label_path = image_path.replace('image', 'label').split('.')[0]+"_mask.png" # edge_path = image_path.replace('image', 'label').split('.')[0]+"_edge.jpg" # # 读取训练图片和标签图片 # image = cv2.imread(image_path, 0) # label = cv2.imread(label_path, 0) # edge = cv2.imread(edge_path, 0) # # 将数据转为单通道的图片 # # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) # image = image.reshape(1, image.shape[0], image.shape[1]) # label = label.reshape(1, label.shape[0], label.shape[1]) # edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # # 处理标签，将像素值为255的改为1 # if label.max() > 1: # label = label / 255 # if edge.max() > 1: # edge = edge / 255 # # 随机进行数据增强，为2时不做处理 # flipCode = random.choice([-1, 0, 1, 2]) # if flipCode != 2: # image = self.augment(image, flipCode) # label = self.augment(label, flipCode) # edge = self.augment(edge, flipCode) # return image, label, edge # def __len__(self): # # 返回训练集大小 # return len(self.imgs_path) class ISBI_Loader(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.png')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] # 根据image_path生成label_path label_path = image_path.replace('image', 'label').split('.')[0]+"_mask.png" edge_path = image_path.replace('image', 'label').split('.')[0]+"_edge.png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 if edge.max() > 1: edge = edge / 255 # 随机进行数据增强，为2时不做处理 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): # 返回训练集大小 return len(self.imgs_path) class ISBI_Loadertest(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.png')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] # 根据image_path生成label_path label_path = image_path.replace('image', 'label').split('.')[0]+"_mask.png" edge_path = image_path.replace('image', 'label').split('.')[0]+"_edge.png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 if edge.max() > 1: edge = edge / 255 # 随机进行数据增强，为2时不做处理 # flipCode = random.choice([-1, 0, 1, 2]) # if flipCode != 2: # image = self.augment(image, flipCode) # label = self.augment(label, flipCode) # edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): # 返回训练集大小 return len(self.imgs_path) class liver_Loader(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, '*.png')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] path = os.path.dirname(image_path) name =image_path.split('/')[-1][0:3] image_path = path +'/'+ name +'.png' # 根据image_path生成label_path label_path =path +'/'+ name+"_mask.png" edge_path = path +'/'+name+"_edge.png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 if edge.max() > 1: edge = edge / 255 # 随机进行数据增强，为2时不做处理 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): # 返回训练集大小 return len(self.imgs_path) class liver_Loadertest(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, '*.png')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] path = os.path.dirname(image_path) name =image_path.split('/')[-1][0:3] image_path = path +'/'+ name +'.png' # 根据image_path生成label_path label_path =path +'/'+ name+"_mask.png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 # 随机进行数据增强，为2时不做处理 # flipCode = random.choice([-1, 0, 1, 2]) # if flipCode != 2: # image = self.augment(image, flipCode) # label = self.augment(label, flipCode) # edge = self.augment(edge, flipCode) return image, label def __len__(self): # 返回训练集大小 return len(self.imgs_path) class ISIC_Loader(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.jpg')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('image', 'label').split('.')[0]+"_Segmentation.png" edge_path = image_path.replace('image', 'label').split('.')[0]+"_Segmentation_edge.png" image = cv2.imread(image_path) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) image = image.reshape(3, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) label = label / 255 edge = edge / 255 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): return len(self.imgs_path) class ISIC_Loadertest(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.jpg')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('image', 'label').split('.')[0]+"_Segmentation.png" edge_path = image_path.replace('image', 'label').split('.')[0]+"_Segmentation_edge.png" image = cv2.imread(image_path) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) image = image.reshape(3, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) label = label / 255 return image, label def __len__(self): return len(self.imgs_path) class Lung_Loader(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'images/*.tif')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('images', 'masks').split('.')[0]+".tif" edge_path = image_path.replace('images', 'edge').split('.')[0]+"_edge.png" image = cv2.imread(image_path,0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 if edge.max() > 1: edge = edge / 255 # 随机进行数据增强，为2时不做处理 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): return len(self.imgs_path) class Lung_Loadertest(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'images/*.tif')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('images', 'masks').split('.')[0]+".tif" image = cv2.imread(image_path,0) label = cv2.imread(label_path, 0) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) if label.max() > 1: label = label / 255 return image, label def __len__(self): return len(self.imgs_path) class CXR(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.png')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('image', 'mask').split('.')[0]+".png" edge_path = image_path.replace('image', 'Edge').split('.')[0]+".png" image = cv2.imread(image_path,0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 if edge.max() > 1: edge = edge / 255 # 随机进行数据增强，为2时不做处理 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): return len(self.imgs_path) class CXRtest(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.png')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('image', 'mask').split('.')[0]+".png" image = cv2.imread(image_path,0) label = cv2.imread(label_path, 0) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) if label.max() > 1: label = label / 255 return image, label def __len__(self): return len(self.imgs_path) class JZX_Loader(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.bmp')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('image', 'GT').split('.')[0]+".bmp" edge_path = image_path.replace('image', 'Edge').split('.')[0]+"_edge.png" image = cv2.imread(image_path,0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) label = label / 255 edge = edge / 255 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): return len(self.imgs_path) class JZX_Loaderval(Dataset): def __init__(self, data_path): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.bmp')) def augment(self, image, flipCode): flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('image', 'GT').split('.')[0]+".bmp" image = cv2.imread(image_path,0) label = cv2.imread(label_path, 0) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) label = label / 255 return image, label def __len__(self): return len(self.imgs_path) class COVD(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'Imgs/*.jpg')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] # 根据image_path生成label_path label_path = image_path.replace('Imgs', 'GT').split('.')[0]+".png" edge_path = image_path.replace('Imgs', 'Edge').split('.')[0]+".png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 if edge.max() > 1: edge = edge / 255 # 随机进行数据增强，为2时不做处理 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) edge = self.augment(edge, flipCode) return image, label, edge def __len__(self): # 返回训练集大小 return len(self.imgs_path) class COVDtest(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'Imgs/*.jpg')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] # 根据image_path生成label_path label_path = image_path.replace('Imgs', 'GT').split('.')[0]+".png" edge_path = image_path.replace('Imgs', 'Edge').split('.')[0]+".png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) # edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) # edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 # if edge.max() > 1: # edge = edge / 255 # 随机进行数据增强，为2时不做处理 # flipCode = random.choice([-1, 0, 1, 2]) # if flipCode != 2: # image = self.augment(image, flipCode) # label = self.augment(label, flipCode) # edge = self.augment(edge, flipCode) return image, label def __len__(self): # 返回训练集大小 return len(self.imgs_path) ###########################一个标准的的写法############# import torch.utils.data as data import PIL.Image as Image import os def make_dataset(root): imgs = [] n = len(os.listdir(root)) // 2 #因为数据集中一套训练数据包含有训练图和mask图，所以要除2 for i in range(n): img = os.path.join(root, "%03d.png" % i) mask = os.path.join(root, "%03d_mask.png" % i) imgs.append((img, mask)) return imgs class LiverDataset(data.Dataset): def __init__(self, root, transform=None, target_transform=None): imgs = make_dataset(root) self.imgs = imgs self.transform = transform self.target_transform = target_transform def __getitem__(self, index): x_path, y_path = self.imgs[index] origin_x = Image.open(x_path) origin_y = Image.open(y_path) if self.transform is not None: img_x = self.transform(origin_x) if self.target_transform is not None: img_y = self.target_transform(origin_y) return img_x, img_y def __len__(self): return len(self.imgs) class Lung1_Loader(Dataset): def __init__(self, data_path, transform=None, target_transform=None): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'images/*.tif')) self.transform =transform self.target_transform =target_transform def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('images', 'masks').split('.')[0]+".tif" edge_path = image_path.replace('images', 'edge').split('.')[0]+"_edge.png" image = Image.open(image_path) label = Image.open(label_path) edge =Image.open(edge_path) if self.transform is not None: image = self.transform(image) if self.target_transform is not None: label = self.target_transform(label) edge = self.target_transform(edge) return image, label, edge def __len__(self): return len(self.imgs_path) class Lung1_Loadertest(Dataset): def __init__(self, data_path, transform=None, target_transform=None): self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'images/*.tif')) self.transform =transform self.target_transform =target_transform def __getitem__(self, index): image_path = self.imgs_path[index] label_path = image_path.replace('images', 'masks').split('.')[0]+".tif" image = Image.open(image_path) label = Image.open(label_path) if self.transform is not None: image = self.transform(image) if self.target_transform is not None: label = self.target_transform(label) return image, label def __len__(self): return len(self.imgs_path) class FJJ_Loader(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.png')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] # 根据image_path生成label_path label_path = image_path.replace('image', 'label').split('.')[0]+"_mask.png" label_path1 = image_path.replace('image', 'body-origin').split('.')[0]+"_mask.png" label_path2 = image_path.replace('image', 'detail-origin').split('.')[0]+"_mask.png" # edge_path = image_path.replace('image', 'label').split('.')[0]+"_edge.png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) label1 = cv2.imread(label_path1, 0) label2 = cv2.imread(label_path2, 0) # edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) label1 = label1.reshape(1, label1.shape[0], label1.shape[1]) label2 = label2.reshape(1, label2.shape[0], label2.shape[1]) # edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 label1 = label1 / 255 label2 = label2 / 255 # if edge.max() > 1: # edge = edge / 255 # 随机进行数据增强，为2时不做处理 flipCode = random.choice([-1, 0, 1, 2]) if flipCode != 2: image = self.augment(image, flipCode) label = self.augment(label, flipCode) label1 = self.augment(label1, flipCode) label2 = self.augment(label2, flipCode) # edge = self.augment(edge, flipCode) return image, label, label1, label2 def __len__(self): # 返回训练集大小 return len(self.imgs_path) class FJJ_Loadertest(Dataset): def __init__(self, data_path): # 初始化函数，读取所有data_path下的图片 self.data_path = data_path self.imgs_path = glob.glob(os.path.join(data_path, 'image/*.png')) def augment(self, image, flipCode): # 使用cv2.flip进行数据增强，filpCode为1水平翻转，0垂直翻转，-1水平+垂直翻转 flip = cv2.flip(image, flipCode) return flip def __getitem__(self, index): # 根据index读取图片 image_path = self.imgs_path[index] # 根据image_path生成label_path label_path = image_path.replace('image', 'label').split('.')[0]+"_mask.png" # label_path1 = image_path.replace('image', 'body-origin').split('.')[0]+"_mask.png" # label_path2 = image_path.replace('image', 'detail-origin').split('.')[0]+"_mask.png" # edge_path = image_path.replace('image', 'label').split('.')[0]+"_edge.png" # 读取训练图片和标签图片 image = cv2.imread(image_path, 0) label = cv2.imread(label_path, 0) # label1 = cv2.imread(label_path1, 0) # label2 = cv2.imread(label_path2, 0) # edge = cv2.imread(edge_path, 0) # 将数据转为单通道的图片 # image = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) # label = cv2.cvtColor(label, cv2.COLOR_BGR2GRAY) image = image.reshape(1, image.shape[0], image.shape[1]) label = label.reshape(1, label.shape[0], label.shape[1]) # label1 = label1.reshape(1, label1.shape[0], label1.shape[1]) # label2 = label2.reshape(1, label2.shape[0], label2.shape[1]) # edge = edge.reshape(1, edge.shape[0], edge.shape[1]) # 处理标签，将像素值为255的改为1 if label.max() > 1: label = label / 255 # label1 = label1 / 255 # label2 = label2 / 255 # if edge.max() > 1: # edge = edge / 255 # 随机进行数据增强，为2时不做处理 # flipCode = random.choice([-1, 0, 1, 2]) # if flipCode != 2: # image = self.augment(image, flipCode) # label = self.augment(label, flipCode) # label1 = self.augment(label1, flipCode) # label2 = self.augment(label2, flipCode) # edge = self.augment(edge, flipCode) return image, label def __len__(self): # 返回训练集大小 return len(self.imgs_path) if __name__ == "__main__": isbi_dataset = ISBI_Loader("/home/wangkun/data/train_96") print("数据个数：", len(isbi_dataset)) train_loader = torch.utils.data.DataLoader(dataset=isbi_dataset, batch_size=4, shuffle=True) for image, label, edge in train_loader: print(image.shape)

32.0213

95

0.57648

3,489

28,563

4.530811

0.038693

0.044408

0.043269

0.038462

0.947368

0.942814

0.935919

0.93497

0.928454

0

0.034423

0.291111

28,563

892

96

32.0213

0.746296

0.201064

0

0.855649

0

0.036476

0.003143

0

1

0.154812

false

0

0.020921

0.039749

0.330544

0.004184

0

null

0

1

0

1

0

null

0

7

273cdaee85fd54b52f7398082c212eaa97d51248

1,133

py

Python

extra_credit/test_parenthetics.py

dave5801/data-structures

b23b7d6e2201325fe94c6fa5d6c0a33ea53be3cc

[ "MIT" ]

null

extra_credit/test_parenthetics.py

dave5801/data-structures

b23b7d6e2201325fe94c6fa5d6c0a33ea53be3cc

[ "MIT" ]

null

extra_credit/test_parenthetics.py

dave5801/data-structures

b23b7d6e2201325fe94c6fa5d6c0a33ea53be3cc

[ "MIT" ]

null

"""Test valid parenthesis""" def test_is_balanced(): """Test is Balanced.""" from balanced_parens import is_balanced assert is_balanced("()") == "balanced" def test_broken(): """Test if broken.""" from balanced_parens import is_balanced assert is_balanced("))") == "broken" def test_is_open(): """Test is open.""" from balanced_parens import is_balanced assert is_balanced("((") == "open" def test_string_1(): """Test from CodeWars.""" from balanced_parens import is_balanced assert is_balanced(" (") == "open" def test_string_2(): """Test from CodeWars.""" from balanced_parens import is_balanced assert is_balanced(")test") == "broken" def test_string_3(): """Test from CodeWars.""" from balanced_parens import is_balanced assert is_balanced("") == "balanced" def test_string_4(): """Test from CodeWars.""" from balanced_parens import is_balanced assert is_balanced("hi())(") == "broken" def test_string_5(): """Test from CodeWars.""" from balanced_parens import is_balanced assert is_balanced("hi(hi)()") == "balanced"

23.122449

48

0.660194

142

1,133

4.992958

0.147887

0.253879

0.203103

0.270804

0.77292

0.702398

0

0.00547

0.193292

1,133

49

48

23.122449

0.770241

0.150044

0

0.333333

0

0.083878

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

null

1

0

1

0

null

0

1

0

1

0

1

0

12

27778576b5961ea5513004a86ed0929f0b0c65fc

115

py

Python

class1-intro-to-python/my_module.py

spu-bigdataanalytics/materials

d95be1cf1d656a49527823df9c4d1fa302a95cc1

[ "MIT" ]

null

class1-intro-to-python/my_module.py

spu-bigdataanalytics/materials

d95be1cf1d656a49527823df9c4d1fa302a95cc1

[ "MIT" ]

4

2020-03-24T18:03:37.000Z

2021-08-23T20:31:59.000Z

class1-intro-to-python/my_module.py

spu-bigdataanalytics-193/materials

d95be1cf1d656a49527823df9c4d1fa302a95cc1

[ "MIT" ]

null

def multipy(a, b): return a * b def divide(a, b, rounding_points=0): return round(a / b, rounding_points)

19.166667

40

0.652174

20

115

3.65

0.5

0.109589

0.273973

0.438356

0

0.011111

0.217391

115

6

40

19.166667

0.8

0

1

0.5

false

0

0.5

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

27a4d5e3f736a39204ceb8674631c1b592891076

219

py

Python

controller/beverage_controller.py

WestHamster/VendingMachine

3aa4b38af2a16810b8cabd6b1187498b92fbbc67

[ "MIT" ]

null

controller/beverage_controller.py

WestHamster/VendingMachine

3aa4b38af2a16810b8cabd6b1187498b92fbbc67

[ "MIT" ]

null

controller/beverage_controller.py

WestHamster/VendingMachine

3aa4b38af2a16810b8cabd6b1187498b92fbbc67

[ "MIT" ]

null

class BeverageController(object): def __init__(self,BeverageService): self.BeverageService = BeverageService def addBeverage(self,id,name,ingredients): return self.BeverageService.addBeverage(id,name,ingredients)

36.5

62

0.826484

23

219

7.695652

0.521739

0.322034

0.19209

0

0.077626

219

6

62

36.5

0.876238

0

1

0.4

false

0

0.2

0.8

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

fdc66d37d5e74b978e92e618d36a9306a2c6d59c

20,677

py

Python

src/stackuchin/__init__.py

Rungutan/stackuchin

03f5cef9f0fe383341f6a59ce7d14ce2e05b28eb

[ "MIT" ]

2

2020-10-06T13:30:40.000Z

2020-10-11T22:48:21.000Z

src/stackuchin/__init__.py

Rungutan/stackuchin

03f5cef9f0fe383341f6a59ce7d14ce2e05b28eb

[ "MIT" ]

null

src/stackuchin/__init__.py

Rungutan/stackuchin

03f5cef9f0fe383341f6a59ce7d14ce2e05b28eb

[ "MIT" ]

1

2020-06-07T02:16:26.000Z

import argparse from argparse import RawTextHelpFormatter import sys import os import yaml PACKAGE_PARENT = '..' SCRIPT_DIR = os.path.dirname(os.path.realpath(os.path.join(os.getcwd(), os.path.expanduser(__file__)))) sys.path.append(os.path.normpath(os.path.join(SCRIPT_DIR, PACKAGE_PARENT))) from stackuchin.create import create from stackuchin.delete import delete from stackuchin.update import update from stackuchin.start_pipeline import start_pipeline class StackuchinCLI(object): def __init__(self): parser = argparse.ArgumentParser( description='CLI tool to automatically create, update and delete AWS CloudFormation ' 'stacks in multiple AWS accounts and regions at the same time', usage='''stackuchin <command> [<args>] To see help text, you can run: stackuchin help stackuchin version stackuchin create --help stackuchin delete --help stackuchin update --help stackuchin pipeline --help ''') parser.add_argument('command', help='Command to run') # parse_args defaults to [1:] for args, but you need to # exclude the rest of the args too, or validation will fail args = parser.parse_args(sys.argv[1:2]) if not hasattr(self, args.command): parser.print_help() exit(1) # use dispatch pattern to invoke method with same name getattr(self, args.command)() # noinspection PyMethodMayBeStatic def version(self): print("1.6.0") # noinspection PyMethodMayBeStatic def create(self): parser = argparse.ArgumentParser( description='Create command system', formatter_class=RawTextHelpFormatter ) parser.add_argument('--stack_file', dest="stack_file" , default='./cloudformation-stacks.yaml' , help="The YAML file which contains your stack definitions.\n" "Defaults to \"./cloudformation-stacks.yaml\" if not specified.") parser.add_argument('--stack_name', dest="stack_name", required=True , help="The stack that you wish to create") parser.add_argument('--secret', dest="secret", required=False, default=None , action='append', metavar='Parameter=Value' , help='Argument used to specify values for NoEcho parameters in your stack') parser.add_argument('--slack_webhook', dest="slack_webhook", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_SLACK.\n' 'If argument is specified, any notifications will be sent to this URL.\n' 'If not specified, the script will check for env var STACKUCHIN_SLACK.\n' 'If neither argument nor environment variable is specified, then no notifications ' 'will be sent.') parser.add_argument('--s3_bucket', dest="s3_bucket", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_BUCKET_NAME.\n' 'If argument is specified, then the template is first uploaded here before ' 'used in the stack.\n' 'If not specified, the script will check for env var STACKUCHIN_BUCKET_NAME.\n' 'If neither argument nor environment variable is specified, then the script will ' 'attempt to feed the template directly to the AWS API call, however, due to ' 'AWS CloudFormation API call limitations, you might end up with a bigger template ' 'in byte size than the max value allowed by AWS.\n' 'Details here -> https://docs.aws.amazon.com/AWSCloudFormation/latest/' 'UserGuide/cloudformation-limits.html') parser.add_argument('--s3_prefix', dest="s3_prefix", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_BUCKET_PREFIX.\n' 'The bucket prefix path to be used when the S3 bucket is defined.') parser.add_argument('--only_errors', dest="only_errors", required=False, default=False, action="store_true" , help='By default, all notifications are sent to Slack if slack_webhook is defined.\n' 'By running this command you ensure that only errors are getting pushed.\n' 'This is useful in case you don\'t want to see COMPLETE and START notifications.') parser.add_argument('-p', '--profile', dest='profile', default=None , help='The AWS profile you\'ll be using.\n' 'If not specified, the "default" profile will be used. \n' 'If no profiles are defined, then the default AWS credential mechanism starts.\n') args = parser.parse_args(sys.argv[2:]) slack_webhook_url = None if args.slack_webhook is not None: slack_webhook_url = args.slack_webhook else: if "STACKUCHIN_SLACK" in os.environ: slack_webhook_url = os.environ.get('STACKUCHIN_SLACK') s3_bucket = None if args.s3_bucket is not None: s3_bucket = args.s3_bucket else: if "STACKUCHIN_BUCKET_NAME" in os.environ: s3_bucket = os.environ.get('STACKUCHIN_BUCKET_NAME') s3_prefix = None if args.s3_prefix is not None: s3_prefix = args.s3_prefix else: if "STACKUCHIN_BUCKET_PREFIX" in os.environ: s3_prefix = os.environ.get('STACKUCHIN_BUCKET_PREFIX') create(args.profile, args.stack_file, args.stack_name, args.secret, slack_webhook_url, s3_bucket, s3_prefix, args.only_errors) # noinspection PyMethodMayBeStatic def delete(self): parser = argparse.ArgumentParser( description='Delete command system', formatter_class=RawTextHelpFormatter ) parser.add_argument('--stack_file', dest="stack_file" , default='./cloudformation-stacks.yaml' , help="The YAML file which contains your stack definitions.\n" "Defaults to \"./cloudformation-stacks.yaml\" if not specified.") parser.add_argument('--stack_name', dest="stack_name", required=True , help="The stack that you wish to create") parser.add_argument('--slack_webhook', dest="slack_webhook", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_SLACK.\n' 'If argument is specified, any notifications will be sent to this URL.\n' 'If not specified, the script will check for env var STACKUCHIN_SLACK.\n' 'If neither argument nor environment variable is specified, then no notifications ' 'will be sent.') parser.add_argument('--only_errors', dest="only_errors", required=False, default=False, action="store_true" , help='By default, all notifications are sent to Slack if slack_webhook is defined.\n' 'By running this command you ensure that only errors are getting pushed.\n' 'This is useful in case you don\'t want to see COMPLETE and START notifications.') parser.add_argument('-p', '--profile', dest='profile', default=None , help='The AWS profile you\'ll be using.\n' 'If not specified, the "default" profile will be used. \n' 'If no profiles are defined, then the default AWS credential mechanism starts.\n') args = parser.parse_args(sys.argv[2:]) slack_webhook_url = None if args.slack_webhook is not None: slack_webhook_url = args.slack_webhook else: if "STACKUCHIN_SLACK" in os.environ: slack_webhook_url = os.environ.get('STACKUCHIN_SLACK') delete(args.profile, args.stack_file, args.stack_name, slack_webhook_url, args.only_errors) # noinspection PyMethodMayBeStatic def update(self): parser = argparse.ArgumentParser( description='Update command system', formatter_class=RawTextHelpFormatter ) parser.add_argument('--stack_file', dest="stack_file" , default='./cloudformation-stacks.yaml' , help="The YAML file which contains your stack definitions.\n" "Defaults to \"./cloudformation-stacks.yaml\" if not specified.") parser.add_argument('--stack_name', dest="stack_name", required=True , help="The stack that you wish to update") parser.add_argument('--secret', dest="secret", required=False, default=None , action='append', metavar='Parameter=Value' , help='Argument used to specify values for NoEcho parameters in your stack') parser.add_argument('--slack_webhook', dest="slack_webhook", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_SLACK.\n' 'If argument is specified, any notifications will be sent to this URL.\n' 'If not specified, the script will check for env var STACKUCHIN_SLACK.\n' 'If neither argument nor environment variable is specified, then no notifications ' 'will be sent.') parser.add_argument('--s3_bucket', dest="s3_bucket", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_BUCKET_NAME.\n' 'If argument is specified, then the template is first uploaded here before ' 'used in the stack.\n' 'If not specified, the script will check for env var STACKUCHIN_BUCKET_NAME.\n' 'If neither argument nor environment variable is specified, then the script will ' 'attempt to feed the template directly to the AWS API call, however, due to ' 'AWS CloudFormation API call limitations, you might end up with a bigger template ' 'in byte size than the max value allowed by AWS.\n' 'Details here -> https://docs.aws.amazon.com/AWSCloudFormation/latest/' 'UserGuide/cloudformation-limits.html') parser.add_argument('--s3_prefix', dest="s3_prefix", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_BUCKET_PREFIX.\n' 'The bucket prefix path to be used when the S3 bucket is defined.') parser.add_argument('--only_errors', dest="only_errors", required=False, default=False, action="store_true" , help='By default, all notifications are sent to Slack if slack_webhook is defined.\n' 'By running this command you ensure that only errors are getting pushed.\n' 'This is useful in case you don\'t want to see COMPLETE and START notifications.') parser.add_argument('-p', '--profile', dest='profile', default=None , help='The AWS profile you\'ll be using.\n' 'If not specified, the "default" profile will be used. \n' 'If no profiles are defined, then the default AWS credential mechanism starts.\n') args = parser.parse_args(sys.argv[2:]) slack_webhook_url = None if args.slack_webhook is not None: slack_webhook_url = args.slack_webhook else: if "STACKUCHIN_SLACK" in os.environ: slack_webhook_url = os.environ.get('STACKUCHIN_SLACK') s3_bucket = None if args.s3_bucket is not None: s3_bucket = args.s3_bucket else: if "STACKUCHIN_BUCKET_NAME" in os.environ: s3_bucket = os.environ.get('STACKUCHIN_BUCKET_NAME') s3_prefix = None if args.s3_prefix is not None: s3_prefix = args.s3_prefix else: if "STACKUCHIN_BUCKET_PREFIX" in os.environ: s3_prefix = os.environ.get('STACKUCHIN_BUCKET_PREFIX') update(args.profile, args.stack_file, args.stack_name, args.secret, slack_webhook_url, s3_bucket, s3_prefix, args.only_errors) # noinspection PyMethodMayBeStatic def pipeline(self): parser = argparse.ArgumentParser( description='Create command system', formatter_class=RawTextHelpFormatter ) parser.add_argument('--stack_file', dest="stack_file" , default='./cloudformation-stacks.yaml' , help="The YAML file which contains your stack definitions.\n" "Defaults to \"./cloudformation-stacks.yaml\" if not specified.") parser.add_argument('--pipeline_file', dest="pipeline_file", required=True , help="The pipeline definition file to run your deployments.") parser.add_argument('--slack_webhook', dest="slack_webhook", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_SLACK.\n' 'If argument is specified, any notifications will be sent to this URL.\n' 'If not specified, the script will check for env var STACKUCHIN_SLACK.\n' 'If neither argument nor environment variable is specified, then no notifications ' 'will be sent.') parser.add_argument('--s3_bucket', dest="s3_bucket", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_BUCKET_NAME.\n' 'If argument is specified, then the template is first uploaded here before ' 'used in the stack.\n' 'If not specified, the script will check for env var STACKUCHIN_BUCKET_NAME.\n' 'If neither argument nor environment variable is specified, then the script will ' 'attempt to feed the template directly to the AWS API call, however, due to ' 'AWS CloudFormation API call limitations, you might end up with a bigger template ' 'in byte size than the max value allowed by AWS.\n' 'Details here -> https://docs.aws.amazon.com/AWSCloudFormation/latest/' 'UserGuide/cloudformation-limits.html') parser.add_argument('--s3_prefix', dest="s3_prefix", required=False, default=None , help='Argument used to overwrite environment variable STACKUCHIN_BUCKET_PREFIX.\n' 'The bucket prefix path to be used when the S3 bucket is defined.') parser.add_argument('--only_errors', dest="only_errors", required=False, default=False, action="store_true" , help='By default, all notifications are sent to Slack if slack_webhook is defined.\n' 'By running this command you ensure that only errors are getting pushed.\n' 'This is useful in case you don\'t want to see COMPLETE and START notifications.') parser.add_argument('-p', '--profile', dest='profile', default=None , help='The AWS profile you\'ll be using.\n' 'If not specified, the "default" profile will be used. \n' 'If no profiles are defined, then the default AWS credential mechanism starts.\n') args = parser.parse_args(sys.argv[2:]) stacks = None try: with open(args.stack_file, 'r') as stack_stream: stacks = yaml.safe_load(stack_stream) except yaml.YAMLError as exc: print(exc) exit(1) pipeline = None try: with open(args.pipeline_file, 'r') as pipeline_stream: pipeline = yaml.safe_load(pipeline_stream) except yaml.YAMLError as exc: print(exc) exit(1) if 'pipeline' not in pipeline: print("The pipeline_file {} must contain a top-level object called \"pipeline\".".format( args.pipeline_file)) exit(1) if 'pipeline_type' in pipeline['pipeline']: if str(pipeline['pipeline']['pipeline_type']).lower() not in ['parallel', 'sequential']: print("The value for \"pipeline_type\" can be either \"parallel\" or \"sequential\".") print("If not specified, the default value is \"sequential\".") exit(1) if 'update' not in pipeline['pipeline'] and \ 'delete' not in pipeline['pipeline'] and \ 'create' not in pipeline['pipeline']: print("An action type of either \"update\", \"create\", or \"delete\" must be defined " "in the \"pipeline\" object definition.") exit(1) for action in ["update", "create", "delete"]: if action in pipeline["pipeline"]: if type(pipeline["pipeline"][action]) is not list: print("Expected a list of inputs for the command {}.".format(action)) exit(1) for item in pipeline["pipeline"][action]: if "stack_name" not in item: print("A property with key \"stack_name\" must be present in each item " "for the {} command.".format(action)) exit(1) if "no_echo" in item: if type(item["no_echo"]) is not list: print("If you want to specify \"secrets\", make sure they " "are a list of Name/Value objects.") exit(1) for secret in item["no_echo"]: if "Name" not in secret or "Value" not in secret: print("You must specify a combination of Name/Value objects " "for each item in your secrets") exit(1) slack_webhook_url = None if args.slack_webhook is not None: slack_webhook_url = args.slack_webhook else: if "STACKUCHIN_SLACK" in os.environ: slack_webhook_url = os.environ.get('STACKUCHIN_SLACK') s3_bucket = None if args.s3_bucket is not None: s3_bucket = args.s3_bucket else: if "STACKUCHIN_BUCKET_NAME" in os.environ: s3_bucket = os.environ.get('STACKUCHIN_BUCKET_NAME') s3_prefix = None if args.s3_prefix is not None: s3_prefix = args.s3_prefix else: if "STACKUCHIN_BUCKET_PREFIX" in os.environ: s3_prefix = os.environ.get('STACKUCHIN_BUCKET_PREFIX') start_pipeline(args.profile, args.stack_file, args.pipeline_file, slack_webhook_url, s3_bucket, s3_prefix, args.only_errors) def main(): StackuchinCLI() if __name__ == '__main__': StackuchinCLI()

58.908832

118

0.569715

2,316

20,677

4.965889

0.107081

0.037562

0.042866

0.025041

0.805495

0.784714

0.775846

0.770629

0.767412

0

0.005269

0.34831

20,677

350

119

59.077143

0.848237

0.015911

0

0.718954

0

0.386991

0.035744

0

1

0.022876

false

0

0.029412

0

0.055556

0.039216

0

null

0

1

0

1

0

null

0

7

fddfb4376fee417763810ae32b3a4e06e66b1b2c

70,761

py

Python

ximpia/xpsite/migrations/0001_initial.py

Ximpia/ximpia

ed2ad22faa42ceca2bde782a47624e5a6ef60e3b

[ "Apache-2.0" ]

1

2020-09-11T01:54:24.000Z

ximpia/xpsite/migrations/0001_initial.py

Ximpia/ximpia

ed2ad22faa42ceca2bde782a47624e5a6ef60e3b

[ "Apache-2.0" ]

null

ximpia/xpsite/migrations/0001_initial.py

Ximpia/ximpia

ed2ad22faa42ceca2bde782a47624e5a6ef60e3b

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- import datetime from south.db import db from south.v2 import SchemaMigration from django.db import models class Migration(SchemaMigration): def forwards(self, orm): # Adding model 'Param' db.create_table('SITE_PARAMETER', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_PARAMETER')), ('mode', self.gf('django.db.models.fields.CharField')(max_length=20, null=True, db_column='MODE', blank=True)), ('name', self.gf('django.db.models.fields.CharField')(max_length=20, db_column='NAME')), ('value', self.gf('django.db.models.fields.CharField')(max_length=100, null=True, db_column='VALUE', blank=True)), ('paramType', self.gf('django.db.models.fields.CharField')(default='string', max_length=10, db_column='PARAM_TYPE')), )) db.send_create_signal(u'xpsite', ['Param']) # Adding model 'MetaKey' db.create_table('SITE_META_KEY', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_META_KEY')), ('name', self.gf('django.db.models.fields.CharField')(max_length=100, db_column='NAME')), ('keyType', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Param'], db_column='ID_SITE_PARAMETER')), )) db.send_create_signal(u'xpsite', ['MetaKey']) # Adding model 'TagMode' db.create_table('SITE_TAG_MODE', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_TAG_MODE')), ('mode', self.gf('django.db.models.fields.CharField')(max_length=30, db_column='MODE')), ('isPublic', self.gf('django.db.models.fields.BooleanField')(default=True, db_column='IS_PUBLIC')), )) db.send_create_signal(u'xpsite', ['TagMode']) # Adding model 'Tag' db.create_table('SITE_TAG', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_TAG')), ('name', self.gf('django.db.models.fields.CharField')(max_length=30, db_column='NAME')), ('mode', self.gf('django.db.models.fields.related.ForeignKey')(related_name='tag_mode', db_column='ID_MODE', to=orm['xpsite.TagMode'])), ('popularity', self.gf('django.db.models.fields.IntegerField')(default=1, null=True, db_column='POPULARITY', blank=True)), ('isPublic', self.gf('django.db.models.fields.BooleanField')(default=True, db_column='IS_PUBLIC')), )) db.send_create_signal(u'xpsite', ['Tag']) # Adding model 'Address' db.create_table('SITE_ADDRESS', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_ADDRESS')), ('street', self.gf('django.db.models.fields.CharField')(max_length=50, null=True, db_column='STREET', blank=True)), ('city', self.gf('django.db.models.fields.CharField')(max_length=20, db_column='CITY')), ('region', self.gf('django.db.models.fields.CharField')(max_length=20, null=True, db_column='REGION', blank=True)), ('zipCode', self.gf('django.db.models.fields.CharField')(max_length=20, null=True, db_column='ZIP_CODE', blank=True)), ('country', self.gf('django.db.models.fields.CharField')(max_length=2, db_column='COUNTRY')), ('long', self.gf('django.db.models.fields.DecimalField')(null=True, max_digits=18, decimal_places=12, blank=True)), ('lat', self.gf('django.db.models.fields.DecimalField')(null=True, max_digits=18, decimal_places=12, blank=True)), )) db.send_create_signal(u'xpsite', ['Address']) # Adding model 'UserChannel' db.create_table('SITE_USER', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_USER')), ('user', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.User'], db_column='ID_USER')), ('title', self.gf('django.db.models.fields.CharField')(max_length=20, db_column='TITLE')), ('name', self.gf('django.db.models.fields.CharField')(default='user', max_length=20, db_column='NAME')), ('tag', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Tag'], null=True, db_column='ID_TAG', blank=True)), )) db.send_create_signal(u'xpsite', ['UserChannel']) # Adding unique constraint on 'UserChannel', fields ['user', 'name'] db.create_unique('SITE_USER', ['ID_USER', 'NAME']) # Adding model 'Category' db.create_table('SITE_CATEGORY', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_CATEGORY')), ('name', self.gf('django.db.models.fields.CharField')(max_length=55, db_column='NAME')), ('slug', self.gf('django.db.models.fields.SlugField')(max_length=200, db_column='SLUG')), ('description', self.gf('django.db.models.fields.CharField')(max_length=255, null=True, db_column='DESCRIPTION', blank=True)), ('parent', self.gf('django.db.models.fields.related.ForeignKey')(blank=True, related_name='category_parent', null=True, db_column='ID_PARENT', to=orm['xpsite.Category'])), ('image', self.gf('filebrowser.fields.FileBrowseField')(max_length=200, null=True, db_column='IMAGE', blank=True)), ('type', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Param'], db_column='ID_SITE_PARAMETER')), ('isPublished', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_PUBLISHED')), ('isPublic', self.gf('django.db.models.fields.BooleanField')(default=True, db_column='IS_PUBLIC')), ('popularity', self.gf('django.db.models.fields.IntegerField')(default=1, null=True, db_column='POPULARITY', blank=True)), ('menuOrder', self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=1, db_column='MENU_ORDER')), )) db.send_create_signal(u'xpsite', ['Category']) # Adding model 'SocialNetworkUser' db.create_table('SITE_SOCIAL_NETWORK_USER', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_SOCIAL_NETWORK_USER')), ('user', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.User'], db_column='ID_USER')), ('socialNetwork', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpcore.CoreParam'], db_column='ID_CORE_PARAMETER')), ('socialId', self.gf('django.db.models.fields.BigIntegerField')(db_column='SOCIAL_ID')), ('token', self.gf('django.db.models.fields.CharField')(max_length=255, db_column='TOKEN')), ('tokenSecret', self.gf('django.db.models.fields.CharField')(max_length=255, null=True, db_column='TOKEN_SECRET', blank=True)), )) db.send_create_signal(u'xpsite', ['SocialNetworkUser']) # Adding unique constraint on 'SocialNetworkUser', fields ['user', 'socialNetwork'] db.create_unique('SITE_SOCIAL_NETWORK_USER', ['ID_USER', 'ID_CORE_PARAMETER']) # Adding model 'Setting' db.create_table('SITE_SETTING', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_SETTING')), ('application', self.gf('django.db.models.fields.related.ForeignKey')(blank=True, related_name='site_setting_app', null=True, db_column='ID_CORE_APPLICATION', to=orm['xpcore.Application'])), ('name', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.MetaKey'], db_column='ID_META')), ('value', self.gf('django.db.models.fields.TextField')(db_column='VALUE')), ('description', self.gf('django.db.models.fields.CharField')(max_length=255, db_column='DESCRIPTION')), ('mustAutoload', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='MUST_AUTOLOAD')), )) db.send_create_signal(u'xpsite', ['Setting']) # Adding model 'UserMeta' db.create_table('SITE_USER_META', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_USER_PROFILE')), ('user', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.User'], db_column='ID_USER')), ('meta', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.MetaKey'], db_column='ID_META')), ('value', self.gf('django.db.models.fields.TextField')(db_column='VALUE')), )) db.send_create_signal(u'xpsite', ['UserMeta']) # Adding model 'UserProfile' db.create_table('SITE_USER_PROFILE', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_USER_PROFILE')), ('user', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.User'], db_column='ID_USER')), ('image', self.gf('filebrowser.fields.FileBrowseField')(max_length=200, null=True, db_column='IMAGE', blank=True)), ('status', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Param'], db_column='ID_SITE_PARAMETER')), )) db.send_create_signal(u'xpsite', ['UserProfile']) # Adding model 'UserAddress' db.create_table('SITE_USER_ADDRESS', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_USER_ADDRESS')), ('userProfile', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.UserProfile'], db_column='ID_SITE_USER_PROFILE')), ('address', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Address'], db_column='ID_ADDRESS')), ('type', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Param'], db_column='ID_SITE_PARAMETER')), )) db.send_create_signal(u'xpsite', ['UserAddress']) # Adding model 'Group' db.create_table('SITE_GROUP', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_GROUP')), ('group', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.Group'], unique=True, db_column='ID_GROUP_SYS')), ('parent', self.gf('django.db.models.fields.related.ForeignKey')(blank=True, related_name='groupchannel_parent', null=True, db_column='ID_PARENT', to=orm['xpsite.Group'])), ('groupNameId', self.gf('django.db.models.fields.CharField')(max_length=20, null=True, db_column='GROUP_NAME_ID', blank=True)), ('isPublic', self.gf('django.db.models.fields.BooleanField')(default=True, db_column='IS_PUBLIC')), ('category', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Category'], db_column='ID_CATEGORY')), )) db.send_create_signal(u'xpsite', ['Group']) # Adding model 'GroupAccess' db.create_table('SITE_GROUP_ACCESS', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_GROUP_ACCESS')), ('groupFrom', self.gf('django.db.models.fields.related.ForeignKey')(related_name='groupaccess_from', db_column='ID_GROUP_FROM', to=orm['xpsite.Group'])), ('groupTo', self.gf('django.db.models.fields.related.ForeignKey')(related_name='groupaccess_to', db_column='ID_GROUP_TO', to=orm['xpsite.Group'])), )) db.send_create_signal(u'xpsite', ['GroupAccess']) # Adding model 'UserChannelGroup' db.create_table('SITE_USER_GROUP', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_USER_GROUP')), ('group', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Group'], db_column='ID_GROUP')), ('userChannel', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.UserChannel'], db_column='ID_USER_CHANNEL')), )) db.send_create_signal(u'xpsite', ['UserChannelGroup']) # Adding model 'GroupTag' db.create_table('SITE_GROUP_TAG', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_GROUP_TAG')), ('group', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Group'], db_column='ID_GROUP')), ('tag', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Tag'], db_column='ID_TAG')), )) db.send_create_signal(u'xpsite', ['GroupTag']) # Adding model 'SignupData' db.create_table('SITE_SIGNUP_DATA', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_SIGNUP_DATA')), ('user', self.gf('django.db.models.fields.CharField')(unique=True, max_length=30, db_column='USER')), ('activationCode', self.gf('django.db.models.fields.PositiveSmallIntegerField')(db_column='ACTIVATION_CODE')), ('data', self.gf('django.db.models.fields.TextField')(db_column='DATA')), )) db.send_create_signal(u'xpsite', ['SignupData']) # Adding model 'Invitation' db.create_table('SITE_INVITATION', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_INVITATION')), ('fromUser', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['auth.User'], db_column='ID_USER')), ('invitationCode', self.gf('django.db.models.fields.CharField')(unique=True, max_length=10, db_column='INVITATION_CODE')), ('email', self.gf('django.db.models.fields.EmailField')(unique=True, max_length=75, db_column='EMAIL')), ('status', self.gf('django.db.models.fields.CharField')(default='pending', max_length=10, db_column='STATUS')), ('number', self.gf('django.db.models.fields.PositiveSmallIntegerField')(default=1, db_column='NUMBER')), ('message', self.gf('django.db.models.fields.TextField')(null=True, db_column='MESSAGE', blank=True)), )) db.send_create_signal(u'xpsite', ['Invitation']) # Adding model 'InvitationMeta' db.create_table('SITE_INVITATION_META', ( ('dateCreate', self.gf('django.db.models.fields.DateTimeField')(auto_now_add=True, null=True, db_column='DATE_CREATE', blank=True)), ('dateModify', self.gf('django.db.models.fields.DateTimeField')(auto_now=True, null=True, db_column='DATE_MODIFY', blank=True)), ('userCreateId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_CREATE_ID', blank=True)), ('userModifyId', self.gf('django.db.models.fields.IntegerField')(null=True, db_column='USER_MODIFY_ID', blank=True)), ('isDeleted', self.gf('django.db.models.fields.BooleanField')(default=False, db_column='IS_DELETED')), ('id', self.gf('django.db.models.fields.AutoField')(primary_key=True, db_column='ID_SITE_USER_PROFILE')), ('invitation', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.Invitation'], db_column='ID_INVITATION')), ('meta', self.gf('django.db.models.fields.related.ForeignKey')(to=orm['xpsite.MetaKey'], db_column='ID_META')), ('value', self.gf('django.db.models.fields.TextField')(db_column='VALUE')), )) db.send_create_signal(u'xpsite', ['InvitationMeta']) def backwards(self, orm): # Removing unique constraint on 'SocialNetworkUser', fields ['user', 'socialNetwork'] db.delete_unique('SITE_SOCIAL_NETWORK_USER', ['ID_USER', 'ID_CORE_PARAMETER']) # Removing unique constraint on 'UserChannel', fields ['user', 'name'] db.delete_unique('SITE_USER', ['ID_USER', 'NAME']) # Deleting model 'Param' db.delete_table('SITE_PARAMETER') # Deleting model 'MetaKey' db.delete_table('SITE_META_KEY') # Deleting model 'TagMode' db.delete_table('SITE_TAG_MODE') # Deleting model 'Tag' db.delete_table('SITE_TAG') # Deleting model 'Address' db.delete_table('SITE_ADDRESS') # Deleting model 'UserChannel' db.delete_table('SITE_USER') # Deleting model 'Category' db.delete_table('SITE_CATEGORY') # Deleting model 'SocialNetworkUser' db.delete_table('SITE_SOCIAL_NETWORK_USER') # Deleting model 'Setting' db.delete_table('SITE_SETTING') # Deleting model 'UserMeta' db.delete_table('SITE_USER_META') # Deleting model 'UserProfile' db.delete_table('SITE_USER_PROFILE') # Deleting model 'UserAddress' db.delete_table('SITE_USER_ADDRESS') # Deleting model 'Group' db.delete_table('SITE_GROUP') # Deleting model 'GroupAccess' db.delete_table('SITE_GROUP_ACCESS') # Deleting model 'UserChannelGroup' db.delete_table('SITE_USER_GROUP') # Deleting model 'GroupTag' db.delete_table('SITE_GROUP_TAG') # Deleting model 'SignupData' db.delete_table('SITE_SIGNUP_DATA') # Deleting model 'Invitation' db.delete_table('SITE_INVITATION') # Deleting model 'InvitationMeta' db.delete_table('SITE_INVITATION_META') models = { u'auth.group': { 'Meta': {'object_name': 'Group'}, u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '80'}), 'permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}) }, u'auth.permission': { 'Meta': {'ordering': "(u'content_type__app_label', u'content_type__model', u'codename')", 'unique_together': "((u'content_type', u'codename'),)", 'object_name': 'Permission'}, 'codename': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'content_type': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['contenttypes.ContentType']"}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '50'}) }, u'auth.user': { 'Meta': {'object_name': 'User'}, 'date_joined': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'email': ('django.db.models.fields.EmailField', [], {'max_length': '75', 'blank': 'True'}), 'first_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Group']", 'symmetrical': 'False', 'blank': 'True'}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'is_active': ('django.db.models.fields.BooleanField', [], {'default': 'True'}), 'is_staff': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'is_superuser': ('django.db.models.fields.BooleanField', [], {'default': 'False'}), 'last_login': ('django.db.models.fields.DateTimeField', [], {'default': 'datetime.datetime.now'}), 'last_name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'blank': 'True'}), 'password': ('django.db.models.fields.CharField', [], {'max_length': '128'}), 'user_permissions': ('django.db.models.fields.related.ManyToManyField', [], {'to': u"orm['auth.Permission']", 'symmetrical': 'False', 'blank': 'True'}), 'username': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30'}) }, u'contenttypes.contenttype': { 'Meta': {'ordering': "('name',)", 'unique_together': "(('app_label', 'model'),)", 'object_name': 'ContentType', 'db_table': "'django_content_type'"}, 'app_label': ('django.db.models.fields.CharField', [], {'max_length': '100'}), u'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True'}), 'model': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}) }, u'xpcore.application': { 'Meta': {'object_name': 'Application', 'db_table': "'CORE_APPLICATION'"}, 'accessGroup': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'app_access'", 'db_column': "'ID_GROUP'", 'to': u"orm['xpsite.Group']"}), 'category': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Category']", 'null': 'True', 'db_column': "'ID_CATEGORY'", 'blank': 'True'}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'developer': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'null': 'True', 'db_column': "'ID_DEVELOPER'", 'blank': 'True'}), 'developerOrg': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'app_dev_org'", 'null': 'True', 'db_column': "'ID_DEVELOPER_ORG'", 'to': u"orm['xpsite.Group']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_CORE_APPLICATION'"}), 'isAdmin': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_ADMIN'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'isPrivate': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_PRIVATE'"}), 'isSubscription': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_SUBSCRIPTION'"}), 'meta': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'app_meta'", 'symmetrical': 'False', 'through': u"orm['xpcore.ApplicationMeta']", 'to': u"orm['xpcore.MetaKey']"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100'}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpcore.Application']", 'null': 'True', 'db_column': "'ID_PARENT'", 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'unique': 'True', 'max_length': '30', 'db_column': "'SLUG'"}), 'tags': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'application_tags'", 'to': u"orm['xpsite.Tag']", 'through': u"orm['xpcore.ApplicationTag']", 'blank': 'True', 'symmetrical': 'False', 'null': 'True'}), 'title': ('django.db.models.fields.CharField', [], {'max_length': '30', 'db_column': "'TITLE'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpcore.applicationmeta': { 'Meta': {'object_name': 'ApplicationMeta', 'db_table': "'CORE_APPLICATION_META'"}, 'application': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpcore.Application']", 'db_column': "'ID_APPLICATION'"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_CORE_APPLICATION_META'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'meta': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpcore.MetaKey']", 'db_column': "'ID_META'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'value': ('django.db.models.fields.TextField', [], {'db_column': "'VALUE'"}) }, u'xpcore.applicationtag': { 'Meta': {'object_name': 'ApplicationTag', 'db_table': "'CORE_APPLICATION_TAG'"}, 'application': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpcore.Application']", 'db_column': "'ID_VIEW'"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_CORE_APPLICATION_TAG'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'tag': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Tag']", 'db_column': "'ID_TAG'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpcore.coreparam': { 'Meta': {'object_name': 'CoreParam', 'db_table': "'CORE_PARAMETER'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_CORE_PARAMETER'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'mode': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'db_column': "'MODE'", 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '20', 'db_column': "'NAME'"}), 'paramType': ('django.db.models.fields.CharField', [], {'default': "'string'", 'max_length': '10', 'db_column': "'PARAM_TYPE'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'value': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'db_column': "'VALUE'", 'blank': 'True'}) }, u'xpcore.metakey': { 'Meta': {'ordering': "['name']", 'object_name': 'MetaKey', 'db_table': "'CORE_META_KEY'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_CORE_META_KEY'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'keyType': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpcore.CoreParam']", 'db_column': "'ID_META_TYPE'"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'db_column': "'NAME'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.address': { 'Meta': {'object_name': 'Address', 'db_table': "'SITE_ADDRESS'"}, 'city': ('django.db.models.fields.CharField', [], {'max_length': '20', 'db_column': "'CITY'"}), 'country': ('django.db.models.fields.CharField', [], {'max_length': '2', 'db_column': "'COUNTRY'"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_ADDRESS'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'lat': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '18', 'decimal_places': '12', 'blank': 'True'}), 'long': ('django.db.models.fields.DecimalField', [], {'null': 'True', 'max_digits': '18', 'decimal_places': '12', 'blank': 'True'}), 'region': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'db_column': "'REGION'", 'blank': 'True'}), 'street': ('django.db.models.fields.CharField', [], {'max_length': '50', 'null': 'True', 'db_column': "'STREET'", 'blank': 'True'}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'zipCode': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'db_column': "'ZIP_CODE'", 'blank': 'True'}) }, u'xpsite.category': { 'Meta': {'object_name': 'Category', 'db_table': "'SITE_CATEGORY'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'description': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'db_column': "'DESCRIPTION'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_CATEGORY'"}), 'image': ('filebrowser.fields.FileBrowseField', [], {'max_length': '200', 'null': 'True', 'db_column': "'IMAGE'", 'blank': 'True'}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'isPublic': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_column': "'IS_PUBLIC'"}), 'isPublished': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_PUBLISHED'"}), 'menuOrder': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'db_column': "'MENU_ORDER'"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '55', 'db_column': "'NAME'"}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'category_parent'", 'null': 'True', 'db_column': "'ID_PARENT'", 'to': u"orm['xpsite.Category']"}), 'popularity': ('django.db.models.fields.IntegerField', [], {'default': '1', 'null': 'True', 'db_column': "'POPULARITY'", 'blank': 'True'}), 'slug': ('django.db.models.fields.SlugField', [], {'max_length': '200', 'db_column': "'SLUG'"}), 'type': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Param']", 'db_column': "'ID_SITE_PARAMETER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.group': { 'Meta': {'object_name': 'Group', 'db_table': "'SITE_GROUP'"}, 'accessGroups': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'group_access'", 'symmetrical': 'False', 'through': u"orm['xpsite.GroupAccess']", 'to': u"orm['xpsite.Group']"}), 'category': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Category']", 'db_column': "'ID_CATEGORY'"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'group': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.Group']", 'unique': 'True', 'db_column': "'ID_GROUP_SYS'"}), 'groupNameId': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'db_column': "'GROUP_NAME_ID'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_GROUP'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'isPublic': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_column': "'IS_PUBLIC'"}), 'parent': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'groupchannel_parent'", 'null': 'True', 'db_column': "'ID_PARENT'", 'to': u"orm['xpsite.Group']"}), 'tags': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'groupchannel_tags'", 'to': u"orm['xpsite.Tag']", 'through': u"orm['xpsite.GroupTag']", 'blank': 'True', 'symmetrical': 'False', 'null': 'True'}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.groupaccess': { 'Meta': {'object_name': 'GroupAccess', 'db_table': "'SITE_GROUP_ACCESS'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'groupFrom': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'groupaccess_from'", 'db_column': "'ID_GROUP_FROM'", 'to': u"orm['xpsite.Group']"}), 'groupTo': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'groupaccess_to'", 'db_column': "'ID_GROUP_TO'", 'to': u"orm['xpsite.Group']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_GROUP_ACCESS'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.grouptag': { 'Meta': {'object_name': 'GroupTag', 'db_table': "'SITE_GROUP_TAG'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'group': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Group']", 'db_column': "'ID_GROUP'"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_GROUP_TAG'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'tag': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Tag']", 'db_column': "'ID_TAG'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.invitation': { 'Meta': {'object_name': 'Invitation', 'db_table': "'SITE_INVITATION'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'email': ('django.db.models.fields.EmailField', [], {'unique': 'True', 'max_length': '75', 'db_column': "'EMAIL'"}), 'fromUser': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'db_column': "'ID_USER'"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_INVITATION'"}), 'invitationCode': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '10', 'db_column': "'INVITATION_CODE'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'message': ('django.db.models.fields.TextField', [], {'null': 'True', 'db_column': "'MESSAGE'", 'blank': 'True'}), 'meta': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'invitation_meta'", 'symmetrical': 'False', 'through': u"orm['xpsite.InvitationMeta']", 'to': u"orm['xpsite.MetaKey']"}), 'number': ('django.db.models.fields.PositiveSmallIntegerField', [], {'default': '1', 'db_column': "'NUMBER'"}), 'status': ('django.db.models.fields.CharField', [], {'default': "'pending'", 'max_length': '10', 'db_column': "'STATUS'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.invitationmeta': { 'Meta': {'object_name': 'InvitationMeta', 'db_table': "'SITE_INVITATION_META'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_USER_PROFILE'"}), 'invitation': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Invitation']", 'db_column': "'ID_INVITATION'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'meta': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.MetaKey']", 'db_column': "'ID_META'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'value': ('django.db.models.fields.TextField', [], {'db_column': "'VALUE'"}) }, u'xpsite.metakey': { 'Meta': {'ordering': "['name']", 'object_name': 'MetaKey', 'db_table': "'SITE_META_KEY'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_META_KEY'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'keyType': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Param']", 'db_column': "'ID_SITE_PARAMETER'"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '100', 'db_column': "'NAME'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.param': { 'Meta': {'object_name': 'Param', 'db_table': "'SITE_PARAMETER'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_PARAMETER'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'mode': ('django.db.models.fields.CharField', [], {'max_length': '20', 'null': 'True', 'db_column': "'MODE'", 'blank': 'True'}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '20', 'db_column': "'NAME'"}), 'paramType': ('django.db.models.fields.CharField', [], {'default': "'string'", 'max_length': '10', 'db_column': "'PARAM_TYPE'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'value': ('django.db.models.fields.CharField', [], {'max_length': '100', 'null': 'True', 'db_column': "'VALUE'", 'blank': 'True'}) }, u'xpsite.setting': { 'Meta': {'object_name': 'Setting', 'db_table': "'SITE_SETTING'"}, 'application': ('django.db.models.fields.related.ForeignKey', [], {'blank': 'True', 'related_name': "'site_setting_app'", 'null': 'True', 'db_column': "'ID_CORE_APPLICATION'", 'to': u"orm['xpcore.Application']"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'description': ('django.db.models.fields.CharField', [], {'max_length': '255', 'db_column': "'DESCRIPTION'"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_SETTING'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'mustAutoload': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'MUST_AUTOLOAD'"}), 'name': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.MetaKey']", 'db_column': "'ID_META'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'value': ('django.db.models.fields.TextField', [], {'db_column': "'VALUE'"}) }, u'xpsite.signupdata': { 'Meta': {'object_name': 'SignupData', 'db_table': "'SITE_SIGNUP_DATA'"}, 'activationCode': ('django.db.models.fields.PositiveSmallIntegerField', [], {'db_column': "'ACTIVATION_CODE'"}), 'data': ('django.db.models.fields.TextField', [], {'db_column': "'DATA'"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_SIGNUP_DATA'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'user': ('django.db.models.fields.CharField', [], {'unique': 'True', 'max_length': '30', 'db_column': "'USER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.socialnetworkuser': { 'Meta': {'unique_together': "(('user', 'socialNetwork'),)", 'object_name': 'SocialNetworkUser', 'db_table': "'SITE_SOCIAL_NETWORK_USER'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_SOCIAL_NETWORK_USER'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'socialId': ('django.db.models.fields.BigIntegerField', [], {'db_column': "'SOCIAL_ID'"}), 'socialNetwork': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpcore.CoreParam']", 'db_column': "'ID_CORE_PARAMETER'"}), 'token': ('django.db.models.fields.CharField', [], {'max_length': '255', 'db_column': "'TOKEN'"}), 'tokenSecret': ('django.db.models.fields.CharField', [], {'max_length': '255', 'null': 'True', 'db_column': "'TOKEN_SECRET'", 'blank': 'True'}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'db_column': "'ID_USER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.tag': { 'Meta': {'ordering': "['-popularity']", 'object_name': 'Tag', 'db_table': "'SITE_TAG'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_TAG'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'isPublic': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_column': "'IS_PUBLIC'"}), 'mode': ('django.db.models.fields.related.ForeignKey', [], {'related_name': "'tag_mode'", 'db_column': "'ID_MODE'", 'to': u"orm['xpsite.TagMode']"}), 'name': ('django.db.models.fields.CharField', [], {'max_length': '30', 'db_column': "'NAME'"}), 'popularity': ('django.db.models.fields.IntegerField', [], {'default': '1', 'null': 'True', 'db_column': "'POPULARITY'", 'blank': 'True'}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.tagmode': { 'Meta': {'object_name': 'TagMode', 'db_table': "'SITE_TAG_MODE'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_TAG_MODE'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'isPublic': ('django.db.models.fields.BooleanField', [], {'default': 'True', 'db_column': "'IS_PUBLIC'"}), 'mode': ('django.db.models.fields.CharField', [], {'max_length': '30', 'db_column': "'MODE'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.useraddress': { 'Meta': {'object_name': 'UserAddress', 'db_table': "'SITE_USER_ADDRESS'"}, 'address': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Address']", 'db_column': "'ID_ADDRESS'"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_USER_ADDRESS'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'type': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Param']", 'db_column': "'ID_SITE_PARAMETER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'userProfile': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.UserProfile']", 'db_column': "'ID_SITE_USER_PROFILE'"}) }, u'xpsite.userchannel': { 'Meta': {'unique_together': "(('user', 'name'),)", 'object_name': 'UserChannel', 'db_table': "'SITE_USER'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'groups': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'user_groups'", 'symmetrical': 'False', 'through': u"orm['xpsite.UserChannelGroup']", 'to': u"orm['xpsite.Group']"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_USER'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'name': ('django.db.models.fields.CharField', [], {'default': "'user'", 'max_length': '20', 'db_column': "'NAME'"}), 'tag': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Tag']", 'null': 'True', 'db_column': "'ID_TAG'", 'blank': 'True'}), 'title': ('django.db.models.fields.CharField', [], {'max_length': '20', 'db_column': "'TITLE'"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'db_column': "'ID_USER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.userchannelgroup': { 'Meta': {'object_name': 'UserChannelGroup', 'db_table': "'SITE_USER_GROUP'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'group': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Group']", 'db_column': "'ID_GROUP'"}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_USER_GROUP'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'userChannel': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.UserChannel']", 'db_column': "'ID_USER_CHANNEL'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) }, u'xpsite.usermeta': { 'Meta': {'object_name': 'UserMeta', 'db_table': "'SITE_USER_META'"}, 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_USER_PROFILE'"}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'meta': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.MetaKey']", 'db_column': "'ID_META'"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'db_column': "'ID_USER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}), 'value': ('django.db.models.fields.TextField', [], {'db_column': "'VALUE'"}) }, u'xpsite.userprofile': { 'Meta': {'object_name': 'UserProfile', 'db_table': "'SITE_USER_PROFILE'"}, 'addresses': ('django.db.models.fields.related.ManyToManyField', [], {'related_name': "'userprofile_addresses'", 'symmetrical': 'False', 'through': u"orm['xpsite.UserAddress']", 'to': u"orm['xpsite.Address']"}), 'dateCreate': ('django.db.models.fields.DateTimeField', [], {'auto_now_add': 'True', 'null': 'True', 'db_column': "'DATE_CREATE'", 'blank': 'True'}), 'dateModify': ('django.db.models.fields.DateTimeField', [], {'auto_now': 'True', 'null': 'True', 'db_column': "'DATE_MODIFY'", 'blank': 'True'}), 'id': ('django.db.models.fields.AutoField', [], {'primary_key': 'True', 'db_column': "'ID_SITE_USER_PROFILE'"}), 'image': ('filebrowser.fields.FileBrowseField', [], {'max_length': '200', 'null': 'True', 'db_column': "'IMAGE'", 'blank': 'True'}), 'isDeleted': ('django.db.models.fields.BooleanField', [], {'default': 'False', 'db_column': "'IS_DELETED'"}), 'status': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['xpsite.Param']", 'db_column': "'ID_SITE_PARAMETER'"}), 'user': ('django.db.models.fields.related.ForeignKey', [], {'to': u"orm['auth.User']", 'db_column': "'ID_USER'"}), 'userCreateId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_CREATE_ID'", 'blank': 'True'}), 'userModifyId': ('django.db.models.fields.IntegerField', [], {'null': 'True', 'db_column': "'USER_MODIFY_ID'", 'blank': 'True'}) } } complete_apps = ['xpsite']

97.466942

245

0.616964

8,225

70,761

5.12

0.026869

0.087006

0.151928

0.21704

0.905229

0.883667

0.868066

0.858425

0.839642

0.816822

0

0.003279

0.15534

70,761

726

246

97.466942

0.7013

0.018668

0

0.470866

0

0.547733

0.26553

0

1

0.00315

false

0.001575

0.006299

0

0.014173

0

null

0

1

0

null

0

7

a906ffa136322d08731cd3a5538fffeeb7adcea8

6,487

py

Python

point/point/tests/trainer/test_model.py

RobertDurfee/VehicleSimulation

567025e195539094393342a266973c148767330e

[ "MIT" ]

null

point/point/tests/trainer/test_model.py

RobertDurfee/VehicleSimulation

567025e195539094393342a266973c148767330e

[ "MIT" ]

null

point/point/tests/trainer/test_model.py

RobertDurfee/VehicleSimulation

567025e195539094393342a266973c148767330e

[ "MIT" ]

null

from unittest import TestCase import numpy as np from point.trainer.model import batch_generator, create_model, compile_model import sys from keras.models import Sequential from keras.layers import InputLayer, Dense, LSTM, TimeDistributed from keras.optimizers import Adam class TestBatchGeneratorDivisible(TestCase): def setUp(self): self.n_samples = 6 self.in_features = 3 self.out_features = 2 self.X = np.array([[-3., 0., -8.], [ 0., -2., 3.], [ 3., -3., -1.], [-1., 6., 1.], [-7., 8., -9.], [ 2., 5., 7.]]) self.Y = np.array([[-3., -8.], [ 0., 1.], [ 3., 2.], [-1., 0.], [-7., -9.], [ 2., 9.]]) self.batch_size = 2 def test_shapes(self): generator = batch_generator(self.X, self.Y, self.batch_size) for _ in range(3): X_batch, Y_batch = next(generator) self.assertEqual(X_batch.shape, (self.batch_size, self.in_features)) self.assertEqual(Y_batch.shape, (self.batch_size, self.out_features)) def test_values(self): generator = batch_generator(self.X, self.Y, self.batch_size) for i in range(3): X_batch, Y_batch = next(generator) self.assertTrue(np.allclose(X_batch, self.X[i*self.batch_size:(i+1)*self.batch_size, :])) self.assertTrue(np.allclose(Y_batch, self.Y[i*self.batch_size:(i+1)*self.batch_size, :])) def test_shapes_repeat_after_epoch(self): generator = batch_generator(self.X, self.Y, self.batch_size) for _ in range(3): next(generator) for _ in range(3): X_batch, Y_batch = next(generator) self.assertEqual(X_batch.shape, (self.batch_size, self.in_features)) self.assertEqual(Y_batch.shape, (self.batch_size, self.out_features)) def test_values_repeat_after_epoch(self): generator = batch_generator(self.X, self.Y, self.batch_size) for _ in range(3): next(generator) for i in range(3): X_batch, Y_batch = next(generator) self.assertTrue(np.allclose(X_batch, self.X[i*self.batch_size:(i+1)*self.batch_size, :])) self.assertTrue(np.allclose(Y_batch, self.Y[i*self.batch_size:(i+1)*self.batch_size, :])) class TestBatchGeneratorNotDivisible(TestCase): def setUp(self): self.n_samples = 6 self.in_features = 3 self.out_features = 2 self.X = np.array([[-3., 0., -8.], [ 0., -2., 3.], [ 3., -3., -1.], [-1., 6., 1.], [-7., 8., -9.], [ 2., 5., 7.]]) self.Y = np.array([[-3., -8.], [ 0., 1.], [ 3., 2.], [-1., 0.], [-7., -9.], [ 2., 9.]]) self.batch_size = 4 def test_shapes(self): generator = batch_generator(self.X, self.Y, self.batch_size) # Complete batch X_batch, Y_batch = next(generator) self.assertEqual(X_batch.shape, (self.batch_size, self.in_features)) self.assertEqual(Y_batch.shape, (self.batch_size, self.out_features)) # Incomplete batch X_batch, Y_batch = next(generator) self.assertEqual(X_batch.shape, (2, self.in_features)) self.assertEqual(Y_batch.shape, (2, self.out_features)) def test_values(self): generator = batch_generator(self.X, self.Y, self.batch_size) # Complete batch X_batch, Y_batch = next(generator) self.assertTrue(np.allclose(X_batch, self.X[:self.batch_size, :])) self.assertTrue(np.allclose(Y_batch, self.Y[:self.batch_size, :])) # Incomplete batch X_batch, Y_batch = next(generator) self.assertTrue(np.allclose(X_batch, self.X[self.batch_size:, :])) self.assertTrue(np.allclose(Y_batch, self.Y[self.batch_size:, :])) def test_shapes_repeat_after_epoch(self): generator = batch_generator(self.X, self.Y, self.batch_size) # First epoch for _ in range(2): next(generator) # Second epoch # Complete batch X_batch, Y_batch = next(generator) self.assertEqual(X_batch.shape, (self.batch_size, self.in_features)) self.assertEqual(Y_batch.shape, (self.batch_size, self.out_features)) # Incomplete batch X_batch, Y_batch = next(generator) self.assertEqual(X_batch.shape, (2, self.in_features)) self.assertEqual(Y_batch.shape, (2, self.out_features)) def test_values_repeat_after_epoch(self): generator = batch_generator(self.X, self.Y, self.batch_size) # First epoch for _ in range(2): next(generator) # Second epoch # Complete batch X_batch, Y_batch = next(generator) self.assertTrue(np.allclose(X_batch, self.X[:self.batch_size, :])) self.assertTrue(np.allclose(Y_batch, self.Y[:self.batch_size, :])) # Incomplete batch X_batch, Y_batch = next(generator) self.assertTrue(np.allclose(X_batch, self.X[self.batch_size:, :])) self.assertTrue(np.allclose(Y_batch, self.Y[self.batch_size:, :])) class TestCreateModel(TestCase): def setUp(self): self.in_features = 2 self.hidden_units = [256, 64, 16, 4] self.out_features = 1 def test_no_exception(self): try: create_model(self.in_features, self.hidden_units, self.out_features) except: self.fail('Unexpected error: ' + str(sys.exc_info())) class TestCompileModel(TestCase): def setUp(self): self.model = Sequential([ InputLayer(input_shape=(10,)), Dense(256), Dense(10) ]) self.optimizer = 'Adam' self.learning_rate = 0.001 self.loss = 'mean_squared_error' def test_no_exception(self): try: compile_model(self.model, self.optimizer, self.learning_rate, self.loss) except: self.fail('Unexpected error: ' + str(sys.exc_info()))

29.621005

101

0.55696

804

6,487

4.299751

0.116915

0.088516

0.127857

0.068846

0.8221

0.808215

0.793752

0.769453

0

0.023548

0.312625

6,487

218

102

29.756881

0.751738

0.027285

0

0.80303

0

0.009211

0

0.181818

1

0.106061

false

0

0.05303

0

0.189394

0

null

0

1

0

1

0

null

0

7

e33ced9a783f745326969d3b24742fc594648ffb

1,597

py

Python

python/testData/inspections/PyArgumentListInspection/collectionsNamedTupleReplace.py

fduminy/intellij-community

fe13dc9ddb7f0f65397325ded25ecb239675eb59

[ "Apache-2.0" ]

2

2018-12-29T09:53:39.000Z

2018-12-29T09:53:42.000Z

python/testData/inspections/PyArgumentListInspection/collectionsNamedTupleReplace.py

tnorbye/intellij-community

f01cf262fc196bf4dbb99e20cd937dee3705a7b6

[ "Apache-2.0" ]

null

python/testData/inspections/PyArgumentListInspection/collectionsNamedTupleReplace.py

tnorbye/intellij-community

f01cf262fc196bf4dbb99e20cd937dee3705a7b6

[ "Apache-2.0" ]

1

2018-10-03T12:35:06.000Z

from collections import namedtuple MyTup1 = namedtuple("MyTup1", "bar baz") mt1 = MyTup1(1, 2) # empty mt1._replace() # one mt1._replace(bar=2) mt1._replace(baz=1) mt1._replace(<warning descr="Unexpected argument">foo=1</warning>) mt1._replace(<warning descr="Unexpected argument">1</warning>) # two mt1._replace(bar=1, baz=2) mt1._replace(baz=2, bar=1) mt1._replace(baz=2, <warning descr="Unexpected argument">foo=1</warning>) mt1._replace(<warning descr="Unexpected argument">2</warning>, <warning descr="Unexpected argument">1</warning>) # two mt1._replace(bar=1, baz=2, <warning descr="Unexpected argument">foo=3</warning>) mt1._replace(<warning descr="Unexpected argument">1</warning>, <warning descr="Unexpected argument">2</warning>, <warning descr="Unexpected argument">3</warning>) class MyTup2(namedtuple("MyTup2", "bar baz")): pass mt2 = MyTup2(1, 2) # empty mt2._replace() # one mt2._replace(bar=2) mt2._replace(baz=1) mt2._replace(<warning descr="Unexpected argument">foo=1</warning>) mt2._replace(<warning descr="Unexpected argument">1</warning>) # two mt2._replace(bar=1, baz=2) mt2._replace(baz=2, bar=1) mt2._replace(baz=2, <warning descr="Unexpected argument">foo=1</warning>) mt2._replace(<warning descr="Unexpected argument">2</warning>, <warning descr="Unexpected argument">1</warning>) # two mt2._replace(bar=1, baz=2, <warning descr="Unexpected argument">foo=3</warning>) mt2._replace(<warning descr="Unexpected argument">1</warning>, <warning descr="Unexpected argument">2</warning>, <warning descr="Unexpected argument">3</warning>)

33.270833

164

0.727614

226

1,597

5.044248

0.106195

0.189474

0.347368

0.473684

0.805263

0.778947

0.773684

0.761404

0.75614

0

0.048409

0.094552

1,597

48

165

33.270833

0.739972

0.021916

0

0.236808

0

null

0.035714

null

0

null

0

1

0

null

0

1

0

9

e35e7c61f1cce1428e31d341d2652fe88733e5a6

167

py

Python

1-100/29/29.py

Thomaw/Project-Euler

bcad5d8a1fd3ebaa06fa52d92d286607e9372a8d

[ "MIT" ]

null

1-100/29/29.py

Thomaw/Project-Euler

bcad5d8a1fd3ebaa06fa52d92d286607e9372a8d

[ "MIT" ]

null

1-100/29/29.py

Thomaw/Project-Euler

bcad5d8a1fd3ebaa06fa52d92d286607e9372a8d

[ "MIT" ]

null

l = [] for a in range(2,101): for b in range (2,101): c = a**b if c not in l: l.append(c) print len(l)

20.875

35

0.359281

27

167

2.222222

0.518519

0.233333

0.266667

0.366667

0

0.1

0.520958

167

7

36

23.857143

0.65

0

null

0

null

0.142857

1

0

null

1

0

1

0

1

0

null

0

1

0

7

e36a75e4d73a8df0eb908f466a697ab447447fde

140

py

Python

reqlog/dbschema/shared.py

JFF-Bohdan/reqlog

a7ba7b6e12609d736b3cd8cd8bc2913d511848ee

[ "MIT" ]

null

reqlog/dbschema/shared.py

JFF-Bohdan/reqlog

a7ba7b6e12609d736b3cd8cd8bc2913d511848ee

[ "MIT" ]

null

reqlog/dbschema/shared.py

JFF-Bohdan/reqlog

a7ba7b6e12609d736b3cd8cd8bc2913d511848ee

[ "MIT" ]

null

import ksuid def get_string_ksuid(): return str(ksuid.ksuid()) def get_base62_ksuid(): return ksuid.ksuid().toBase62()

14

36

0.657143

18

140

4.888889

0.5

0.181818

0.25

0

0.036697

0.221429

140

9

37

15.555556

0.770642

0

1

0.4

true

0

0.2

0.4

1

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

7

e36b00f522d3fc1f91ad397215fe2c5d1e58c15e

128

py

Python

tests/test_pool_tr.py

ffreemt/pool-translate-free

b3554f78edab1a733a975c712cae6e78aa3a365b

[ "MIT" ]

null

tests/test_pool_tr.py

ffreemt/pool-translate-free

b3554f78edab1a733a975c712cae6e78aa3a365b

[ "MIT" ]

null

tests/test_pool_tr.py

ffreemt/pool-translate-free

b3554f78edab1a733a975c712cae6e78aa3a365b

[ "MIT" ]

null

from pool_tr import __version__ from pool_tr.pool_tr import pool_tr def test_version(): assert __version__[:3] in "0.1.0"

18.285714

37

0.757813

23

128

3.652174

0.521739

0.285714

0.238095

0

0.037037

0.15625

128

6

38

21.333333

0.740741

0

0.039063

0

0.25

1

0.25

true

0

0.5

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

e38998e033de8db9f720b66e6107874f13b38fd2

4,442

py

Python

app/tests/api/api_v1/test_currency.py

germainlefebvre4/cryptobot-api

6b8f10554bbb50ac669c8f8a87414c9292fc9d7b

[ "MIT" ]

null

app/tests/api/api_v1/test_currency.py

germainlefebvre4/cryptobot-api

6b8f10554bbb50ac669c8f8a87414c9292fc9d7b

[ "MIT" ]

8

2021-09-28T12:55:38.000Z

2022-01-05T22:45:20.000Z

app/tests/api/api_v1/test_currency.py

germainlefebvre4/cryptobot-api

6b8f10554bbb50ac669c8f8a87414c9292fc9d7b

[ "MIT" ]

null

# from datetime import date, datetime # from dateutil.relativedelta import relativedelta # # from fastapi import status # from fastapi.testclient import TestClient # from sqlalchemy.orm import Session # from app.core.config import settings # from app.tests.utils.utils import random_lower_string, random_weekdays # from app.tests.utils.user import create_random_user # from app.tests.utils.currency import get_random_exchange_currency # def test_create_currency( # client: TestClient, normal_user_token_headers: dict, # ) -> None: # r = client.get(f"{settings.API_V1_STR}/users/me", headers=normal_user_token_headers) # user_id = r.json()["id"] # base_currency, quote_currency = get_random_exchange_currency() # data = { # "base_currency": base_currency, # "quote_currency": quote_currency, # } # response = client.post( # f"{settings.API_V1_STR}/margin/currencies/?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # json=data, # ) # content = response.json() # assert response.status_code == 200 # assert "id" in content # assert content["base_currency"] == base_currency # assert content["quote_currency"] == quote_currency # def test_read_currencies_by_user( # client: TestClient, normal_user_token_headers: dict, # ) -> None: # r = client.get(f"{settings.API_V1_STR}/users/me", headers=normal_user_token_headers) # user_id = r.json()["id"] # response = client.get( # f"{settings.API_V1_STR}/margin/currencies/?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # ) # content = response.json() # assert response.status_code == 200 # assert isinstance(content, list) # def test_read_currency_by_id_by_user( # client: TestClient, normal_user_token_headers: dict, # ) -> None: # r = client.get(f"{settings.API_V1_STR}/users/me", headers=normal_user_token_headers) # user_id = r.json()["id"] # base_currency, quote_currency = get_random_exchange_currency() # data = { # "base_currency": base_currency, # "quote_currency": quote_currency, # } # response = client.post( # f"{settings.API_V1_STR}/margin/currencies/?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # json=data, # ) # content = response.json() # assert response.status_code == 200 # currency_id = content['id'] # response = client.get( # f"{settings.API_V1_STR}/margin/currencies/{currency_id}?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # ) # content = response.json() # assert response.status_code == 200 # assert "id" in content # assert content["base_currency"] == base_currency # assert content["quote_currency"] == quote_currency # def test_delete_currency_by_id_by_user( # client: TestClient, normal_user_token_headers: dict, # ) -> None: # r = client.get(f"{settings.API_V1_STR}/users/me", headers=normal_user_token_headers) # user_id = r.json()["id"] # base_currency, quote_currency = get_random_exchange_currency() # data = { # "base_currency": base_currency, # "quote_currency": quote_currency, # } # response = client.post( # f"{settings.API_V1_STR}/margin/currencies/?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # json=data, # ) # content = response.json() # assert response.status_code == 200 # currency_id = content['id'] # response = client.get( # f"{settings.API_V1_STR}/margin/currencies/{currency_id}?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # ) # content = response.json() # assert response.status_code == 200 # response = client.delete( # f"{settings.API_V1_STR}/margin/currencies/{currency_id}?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # ) # content = response.json() # assert response.status_code == 200 # currency_id = content['id'] # response = client.get( # f"{settings.API_V1_STR}/margin/currencies/{currency_id}?" + \ # f"&user_id={user_id}", # headers=normal_user_token_headers, # ) # content = response.json() # assert response.status_code == 404

31.503546

90

0.646781

535

4,442

5.056075

0.115888

0.044362

0.088725

0.130129

0.834011

0

0.010357

0.21747

4,442

140

91

31.728571

0.767837

0.941693

0

null

0

null

0

null

0

null

1

null

true

0

null

0

null

0

1

0

1

0

null

0

1

0

8

8b6ed41f900a7002b2f19561cffe2f4610bbb025

113

py

Python

First Steps/test_HelloWorld.py

zeltyr/learning_python

785262786c6c7a7879aeec8dfde071e77774a0d4

[ "MIT" ]

null

First Steps/test_HelloWorld.py

zeltyr/learning_python

785262786c6c7a7879aeec8dfde071e77774a0d4

[ "MIT" ]

null

First Steps/test_HelloWorld.py

zeltyr/learning_python

785262786c6c7a7879aeec8dfde071e77774a0d4

[ "MIT" ]

null

import HelloWorld def test_get_text_hello_world(): assert HelloWorld.get_text_hello_world() == "Hello world"

28.25

61

0.79646

16

113

5.1875

0.5625

0.361446

0.289157

0.409639

0

0.115044

113

4

61

28.25

0.83

0

0.096491

0

0.333333

1

0.333333

true

0

0.333333

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

9

8b91915f11171cc19d4a187a59270d952c7ff875

3,937

py

Python

tests/test_models.py

fabianmoss/pkspell

f61f468b512210e5a78cc4c1e30617847e2cf6ef

[ "MIT" ]

7

2021-08-06T08:00:11.000Z

2022-03-10T01:56:27.000Z

tests/test_models.py

fabianmoss/pkspell

f61f468b512210e5a78cc4c1e30617847e2cf6ef

[ "MIT" ]

null

tests/test_models.py

fabianmoss/pkspell

f61f468b512210e5a78cc4c1e30617847e2cf6ef

[ "MIT" ]

1

2021-08-30T09:38:36.000Z

import pytest import numpy as np import torch from src.models.models import PKSpell, PKSpell_single from src.data.pytorch_datasets import pitch_to_ix, ks_to_ix from pathlib import Path def test_PKSpell_single(): n_features = 12 piece_len = [20, 9, 8, 5] batch_size = 4 model = PKSpell_single( n_features, 12, pitch_to_ix, ks_to_ix, rnn_depth=1, cell_type="GRU", dropout=None, bidirectional=True, mode="both", ) dummy_input_midi = np.random.randint( 0, 12, size=(max(piece_len), batch_size, n_features) ) dummy_pitch = np.random.randint( 0, len(pitch_to_ix), size=(max(piece_len), batch_size) ) dummy_ks = np.random.randint(0, len(ks_to_ix), size=(max(piece_len), batch_size)) # try a training loss = model( torch.Tensor(dummy_input_midi), torch.Tensor(dummy_pitch).long(), torch.Tensor(dummy_ks).long(), torch.Tensor(piece_len), ) assert loss.shape == torch.Size([]) # try a prediction prediction = model.predict( torch.Tensor(dummy_input_midi), torch.Tensor([20, 9, 8, 5]) ) assert type(prediction) == tuple assert len(prediction[0]) == batch_size assert len(prediction[1]) == batch_size for i, l in enumerate(piece_len): assert len(prediction[0][i]) == l assert len(prediction[1][i]) == l def test_PKSpell(): n_features = 12 piece_len = [20, 9, 8, 5] batch_size = 4 model = PKSpell( n_features, 12, pitch_to_ix, ks_to_ix, rnn_depth=1, cell_type="GRU", dropout=None, bidirectional=True, mode="both", ) dummy_input_midi = np.random.randint( 0, 12, size=(max(piece_len), batch_size, n_features) ) dummy_pitch = np.random.randint( 0, len(pitch_to_ix), size=(max(piece_len), batch_size) ) dummy_ks = np.random.randint(0, len(ks_to_ix), size=(max(piece_len), batch_size)) # try a training loss = model( torch.Tensor(dummy_input_midi), torch.Tensor(dummy_pitch).long(), torch.Tensor(dummy_ks).long(), torch.Tensor(piece_len), ) assert loss.shape == torch.Size([]) # try a prediction prediction = model.predict( torch.Tensor(dummy_input_midi), torch.Tensor([20, 9, 8, 5]) ) assert type(prediction) == tuple assert len(prediction[0]) == batch_size assert len(prediction[1]) == batch_size for i, l in enumerate(piece_len): assert len(prediction[0][i]) == l assert len(prediction[1][i]) == l def test_PKSpell_odd_hidden_dim(): hidden_dim = 11 hidden_dim2 = 7 with pytest.raises(ValueError): model = PKSpell( 5, hidden_dim, pitch_to_ix, ks_to_ix, rnn_depth=1, cell_type="GRU", dropout=None, bidirectional=True, mode="both", ) with pytest.raises(ValueError): model = PKSpell( 5, 10, pitch_to_ix, ks_to_ix, rnn_depth=1, cell_type="GRU", dropout=None, bidirectional=True, mode="both", hidden_dim2=hidden_dim2, ) def test_import_model(): # import pkspell model = torch.load(Path("models/pkspell.pt")) # import pkspell_single model = torch.load(Path("models/pkspell_single.pt")) assert True def test_import_pretrained_state_dict(): # import pkspell model = PKSpell(17, 300, pitch_to_ix, ks_to_ix, hidden_dim2=24) model.load_state_dict(torch.load(Path("models/pkspell_statedict.pt"))) # import pkspell_single model = PKSpell_single(17, 300, pitch_to_ix, ks_to_ix) model.load_state_dict(torch.load(Path("models/pkspell_single_statedict.pt"))) assert True

26.601351

85

0.602235

523

3,937

4.290631

0.170172

0.032086

0.036096

0.034314

0.838235

0.808824

0.769162

0.734403

0.716578

0.677362

0

0.026521

0.281687

3,937

147

86

26.782313

0.766973

0.034798

0

0.708333

0

0.034292

0.022422

0

0.116667

1

0.041667

false

0

0.066667

0

0.108333

0

null

0

1

0

1

0

null

0

7

8bb9d8bf6abc609e430393ecbb34c8daa6941a53

99

py

Python

vibora/request/__init__.py

mnxzyw/vibora

445bf5bf50dcb27f1415a874fe53d67a8004a2b9

[ "MIT" ]

6,238

2018-06-14T19:29:47.000Z

2022-03-29T21:42:03.000Z

vibora/request/__init__.py

LL816/vibora

4cda888f89aec6bfb2541ee53548ae1bf50fbf1b

[ "MIT" ]

213

2018-06-13T20:13:59.000Z

2022-03-26T07:46:49.000Z

vibora/request/__init__.py

LL816/vibora

4cda888f89aec6bfb2541ee53548ae1bf50fbf1b

[ "MIT" ]

422

2018-06-20T01:29:41.000Z

2022-02-27T16:45:29.000Z

from typing import TYPE_CHECKING from .request import * if TYPE_CHECKING: from .hints import *

19.8

32

0.767677

14

99

5.285714

0.571429

0.324324

0.432432

0

0.181818

99

4

33

24.75

0.91358

0

1

0

true

0

0.75

0

0.75

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

8bcec850a38824a38caad1b88a7683554af31a36

1,619

py

Python

tools/dataset_converters/icdar2013_bbox_2_segmentation.py

vansin/tabnet

2403c8134c23a704940522ace92a75b0fc6f5d99

[ "Apache-2.0" ]

2

2021-10-18T02:52:18.000Z

2022-01-21T08:54:18.000Z

tools/dataset_converters/icdar2013_bbox_2_segmentation.py

vansin/tabnet

2403c8134c23a704940522ace92a75b0fc6f5d99

[ "Apache-2.0" ]

null

tools/dataset_converters/icdar2013_bbox_2_segmentation.py

vansin/tabnet

2403c8134c23a704940522ace92a75b0fc6f5d99

[ "Apache-2.0" ]

null

import json train_in = open('data/icdar2013/annotations/table_ICDAR2013_train.json') test_in = open('data/icdar2013/annotations/table_ICDAR2013_test.json') data_train = json.load(train_in) data_test = json.load(test_in) for annotation in data_train['annotations']: bbox = annotation['bbox'] segmentation = [] # left_top segmentation.append(int(bbox[0])) segmentation.append(int(bbox[1])) # left_bottom segmentation.append(int(bbox[0])) segmentation.append(int(bbox[1] + bbox[3])) # right_bottom segmentation.append(int(bbox[0] + bbox[2])) segmentation.append(int(bbox[1] + bbox[3])) # right_top segmentation.append(int(bbox[0] + bbox[2])) segmentation.append(int(bbox[1])) annotation['segmentation'].append(segmentation) for annotation in data_test['annotations']: bbox = annotation['bbox'] segmentation = [] # left_top segmentation.append(int(bbox[0])) segmentation.append(int(bbox[1])) # left_bottom segmentation.append(int(bbox[0])) segmentation.append(int(bbox[1] + bbox[3])) # right_bottom segmentation.append(int(bbox[0] + bbox[2])) segmentation.append(int(bbox[1] + bbox[3])) # right_top segmentation.append(int(bbox[0] + bbox[2])) segmentation.append(int(bbox[1])) annotation['segmentation'].append(segmentation) with open('data/icdar2013/annotations/table_ICDAR2013_segm_train.json', 'w') as outfile: json.dump(data_train, outfile) with open('data/icdar2013/annotations/table_ICDAR2013_segm_test.json', 'w') as outfile1: json.dump(data_test, outfile1)

29.981481

72

0.692403

210

1,619

5.204762

0.152381

0.296432

0.307411

0.365965

0.803294

0.722781

0.63129

0

0.042553

0.158122

1,619

53

73

30.54717

0.759354

0.053737

0

0.628571

0

0.181221

0.144452

0

1

0

false

0

0.028571

0

0.028571

0

null

1

0

1

0

null

0

8

473e6fdc7dec5d3c88b1c975d3122b2a63e99166

40,645

py

Python

mmseg/datasets/voc.py

giladcohen/mmsegmentation

04eb42b06628cb96a028801c981918741d192529

[ "Apache-2.0" ]

null

mmseg/datasets/voc.py

giladcohen/mmsegmentation

04eb42b06628cb96a028801c981918741d192529

[ "Apache-2.0" ]

null

mmseg/datasets/voc.py

giladcohen/mmsegmentation

04eb42b06628cb96a028801c981918741d192529

[ "Apache-2.0" ]

null

# Copyright (c) OpenMMLab. All rights reserved. import os.path as osp import numpy as np import os from .builder import DATASETS from .custom import CustomDataset from research.utils import generate_farthest_vecs @DATASETS.register_module() class PascalVOCDataset(CustomDataset): """Pascal VOC dataset. Args: split (str): Split txt file for Pascal VOC. """ EMB_DIM = 200 CLASSES = ('background', 'aeroplane', 'bicycle', 'bird', 'boat', 'bottle', 'bus', 'car', 'cat', 'chair', 'cow', 'diningtable', 'dog', 'horse', 'motorbike', 'person', 'pottedplant', 'sheep', 'sofa', 'train', 'tvmonitor') PALETTE = [[0, 0, 0], [128, 0, 0], [0, 128, 0], [128, 128, 0], [0, 0, 128], [128, 0, 128], [0, 128, 128], [128, 128, 128], [64, 0, 0], [192, 0, 0], [64, 128, 0], [192, 128, 0], [64, 0, 128], [192, 0, 128], [64, 128, 128], [192, 128, 128], [0, 64, 0], [128, 64, 0], [0, 192, 0], [128, 192, 0], [0, 64, 128]] def __init__(self, split, **kwargs): self.emb = kwargs.pop('emb', None) super(PascalVOCDataset, self).__init__( img_suffix='.jpg', seg_map_suffix='.png', split=split, **kwargs) assert osp.exists(self.img_dir) and self.split is not None if self.emb is not None: if os.path.exists(self.emb['emb_path']): print('emb path {} exist. reading content to self.idx_to_class_emb_vec'.format(self.emb['emb_path'])) self.idx_to_class_emb_vec = np.load(self.emb['emb_path']) else: print('Generating emb map for {} and dumping it to {}'.format(self.emb['emb_selection'], self.emb['emb_path'])) self.idx_to_class_emb_vec = self.set_emb_vecs(self.emb['emb_selection']) os.makedirs(os.path.dirname(self.emb['emb_path']), exist_ok=True) np.save(self.emb['emb_path'], self.idx_to_class_emb_vec) @staticmethod def parse_vec(s: str): return np.asarray(list(map(float, s.split()))) def set_glove(self): gloves = np.zeros((len(self.CLASSES), self.EMB_DIM), dtype=np.float32) # background gloves[0] = self.parse_vec('0.18118 -0.40912 -0.62699 0.66349 0.52609 0.22725 1.0126 -0.59382 0.10862 -0.57365 -0.37711 -0.13031 -0.26549 -0.60595 -0.30474 0.37288 0.59625 -0.42375 0.37377 -0.25376 -0.50042 0.22405 0.060972 0.4461 -0.43079 0.82193 0.32821 0.074003 -0.38279 0.34623 -0.018477 0.12097 -0.30397 -0.2223 0.34332 -0.53648 0.4261 -0.46458 0.26739 -0.43006 0.36895 0.085638 -0.24012 0.23693 -0.32983 0.03293 -0.18042 -0.48865 -0.46444 -0.33425 0.12641 0.38959 0.27181 0.41119 -0.21471 -0.17354 -0.26007 -0.19764 0.35169 -0.2575 0.30232 -0.54958 0.84861 -0.035018 0.19377 -0.30884 -0.4549 0.27329 0.24261 0.064083 -0.043068 -0.097231 -0.4867 -0.16006 -0.44754 0.16983 -0.071483 0.23399 -0.071736 -0.10345 0.091824 0.37589 -0.11695 -0.69112 0.0019069 -1.0029 0.76611 0.53357 -0.16726 0.045585 -0.35476 0.42482 -0.42188 -0.90294 0.35648 -0.053211 0.20893 0.24375 -0.044005 0.25183 -0.14815 -0.45803 0.0016516 0.14754 -0.84007 -0.075739 -0.25731 0.07955 -0.29573 -0.033395 -0.052914 0.21006 -0.78917 -0.10985 0.19122 0.35997 0.45986 0.46184 -0.20671 -0.34638 0.23701 -0.17631 0.68373 0.19996 0.44723 0.46754 -0.011539 -0.50926 -0.092837 0.62416 0.50671 0.30946 0.080026 0.68015 -0.38421 0.19975 0.21836 0.26643 -0.36207 0.37803 0.039925 -0.29145 0.33588 0.0147 -0.50419 -0.014059 -0.3277 -0.18551 0.11956 0.24942 0.45746 -0.33681 -3.1694 -0.60703 -0.37267 0.7583 0.7298 -0.26974 -0.42411 0.30439 0.10229 0.034068 -0.2953 0.45362 -0.29974 0.19263 -0.053222 -0.57162 0.20615 0.22706 0.21614 -0.25294 0.26947 -0.13109 -0.13436 0.19612 0.019767 0.23358 0.089522 0.12016 -0.20462 0.18511 -0.014861 0.036399 0.063346 0.31004 -0.50888 0.19682 0.3836 -0.62704 0.18202 -0.0037371 0.36821 -0.46103 -0.4889 0.021669 0.25197 0.11028 -0.54431 0.09691') # airplane (instead of aeroplane) gloves[1] = self.parse_vec('-0.42252 -0.72499 0.3823 -0.28675 -0.070732 1.082 0.61925 -0.51744 -0.24192 0.36525 -0.10519 0.68813 -0.82839 0.0121 -0.30335 0.057322 0.077832 0.11161 0.46033 -0.21916 -0.049768 -0.24293 0.12415 -0.40696 0.32383 1.0217 0.62564 -0.75066 -0.41027 -0.0758 -0.1808 -0.027986 0.21466 -1.1386 0.20759 0.67844 -0.60843 0.28039 1.0015 0.014468 0.2675 -0.10874 -0.23052 -0.83247 0.2413 -0.11418 -0.31517 -0.28662 0.067465 0.17122 0.16358 -0.38727 -0.33752 0.15207 0.071406 -0.23285 -0.39292 0.79661 -0.01181 -0.61611 0.42596 -0.024823 0.51229 -0.1942 -0.31514 -0.9923 0.26809 -0.16498 0.20328 -0.21459 -0.70433 -0.0017985 -0.65342 -0.85474 0.161 -0.71959 -0.50075 -0.18926 0.31129 0.90581 0.58413 0.87044 -0.056666 -0.26441 0.29036 0.07847 0.026343 0.3536 -1.1024 0.4081 0.26188 -0.20925 -0.728 -0.04421 -0.21305 -0.2336 -0.33843 -0.27006 -0.81843 -0.19834 0.58124 0.039614 -0.90533 0.39462 -0.35865 -0.47045 0.22981 -0.044953 0.28625 -0.14308 -0.31557 -0.015199 -0.28968 -0.28257 -0.72873 -0.13707 -0.0014256 -0.44722 -0.14099 -0.062103 0.53414 -0.18197 -0.13406 -0.41105 -0.39153 0.73264 0.031486 0.3796 0.40439 0.37544 0.49086 0.38665 0.095826 0.2573 -0.47709 -0.5425 0.19142 0.66534 -0.26036 0.044465 -0.1965 0.21443 0.090587 0.48187 0.063059 0.10099 0.23694 -0.16066 -0.39295 -0.62392 1.2988 -0.2949 -1.8037 0.32934 -0.11134 0.0236 0.29623 -0.39351 0.058452 -0.37467 -0.029277 0.073365 0.3801 0.67572 0.10034 -0.27386 -0.58898 0.18683 0.029444 0.20757 0.01653 -0.4761 0.15124 -0.24604 0.064738 0.22999 -0.80299 0.20186 -0.012943 0.80957 0.25185 -0.28367 -0.0093086 0.2747 -0.91049 0.24138 0.31127 -0.084327 0.15578 -0.23792 0.74639 -0.24335 -0.084517 -0.072658 0.027183 0.083656 0.10962 0.025677 0.26856 0.049582') # bicycle gloves[2] = self.parse_vec('-0.20953 0.71027 0.20456 0.030102 -0.15586 -0.0017965 0.64207 -0.7232 0.6517 -0.50303 0.46756 0.38291 -1.0521 -0.35768 -0.093636 -0.026939 -0.15788 -0.079467 0.56652 0.34809 0.92798 -0.26454 0.89587 -0.18168 -0.2479 1.0151 0.1562 0.29677 -0.24759 -0.32084 0.18955 -0.15548 0.54911 -0.67806 0.47885 0.027665 -0.26085 0.22484 0.48099 0.058068 0.55766 0.084012 -0.051574 0.40012 0.31149 -0.34196 0.091012 0.32463 0.48642 0.49414 0.16418 -0.62328 -0.41107 -0.56187 0.57129 0.045219 0.095414 0.12472 0.19763 0.10691 -0.12217 0.10911 0.094954 -0.20152 -0.17483 -0.42543 0.16613 0.58936 -0.095105 -0.44676 -0.36252 0.10529 -0.36694 0.103 0.21666 0.17183 -0.45817 0.25464 -0.066484 -0.39853 0.59684 0.24154 -0.46958 -0.42001 0.19729 0.45703 0.9437 0.19471 -0.28348 0.26896 0.17337 -0.28803 -0.21938 -0.04655 -0.45331 0.21835 -0.11856 0.13973 0.085915 0.59576 0.83806 0.44316 0.061283 -0.023769 -0.54969 -1.5631 -0.30484 -0.5664 0.17964 0.29822 0.67106 0.29276 0.32477 0.35384 0.12617 0.65192 -0.64218 -0.38125 -0.52421 0.66719 0.61863 -0.29273 -0.2346 0.22393 -0.29474 -0.44579 -0.025123 1.3639 -0.09371 0.4203 1.0943 0.54408 0.28939 -0.42816 -0.44594 0.49912 -0.24159 0.27606 -0.14985 0.13104 -0.39032 0.26478 0.03135 0.18696 -0.39013 -0.0049679 0.50424 -0.36814 0.17211 0.68211 0.6758 -0.56006 -1.8271 0.35589 0.007275 -0.056845 -0.12371 0.62302 0.25987 -0.27712 0.66312 0.49514 0.3868 0.20792 -0.24442 -0.03075 -0.042747 -0.099471 0.076467 0.0563 0.81152 -0.2869 -0.53929 -0.16035 0.71853 0.59261 0.050601 -0.62398 0.25599 0.37793 0.56556 0.24721 0.32267 -0.34488 0.035321 -0.45666 0.083282 -0.74305 0.25377 0.26414 0.53079 -0.27572 0.12793 0.22571 0.028646 -0.22586 0.5593 0.15792 0.002043 0.15446') # bird gloves[3] = self.parse_vec('0.050286 -0.40342 -0.085693 -0.11261 -0.40626 0.27764 0.28587 -0.036815 0.29082 0.53717 -0.096179 0.20294 -0.52494 -0.42556 -0.020042 0.59147 0.60556 -0.096592 0.078125 -1.009 -0.48508 0.26272 -0.36493 -0.72437 0.044094 0.46839 0.22695 0.080163 -0.18623 0.49568 -0.067437 0.29948 -0.36965 -0.73587 -0.033697 0.35647 -0.13801 0.42026 -0.064175 -0.35642 -0.40864 0.081728 0.1202 -0.45304 0.35192 -0.16238 -0.40587 0.28837 0.72754 0.5276 -0.12201 -0.18372 0.36878 0.46526 0.32681 -0.56752 -0.50191 0.60814 0.57881 0.0227 0.23608 0.035366 0.16645 -0.028746 -0.13858 -0.42193 0.42848 -0.011398 0.32289 0.204 -0.34057 0.30971 -0.5685 -0.85169 -0.12805 -0.3842 -0.11821 0.050055 0.50502 0.58767 1.0039 0.3996 -0.027687 0.17466 -0.22844 0.12718 -0.51194 -0.45218 -0.20525 0.055035 0.27 -1.0207 -1.1003 -0.51314 -0.35455 -0.13669 -0.17903 0.10799 -0.24093 0.66859 -0.13704 0.50379 -0.065461 0.15555 -0.51893 0.62364 -0.52682 0.16933 -0.44093 -0.090353 -0.84958 0.42558 -0.31874 -0.38313 0.39895 -0.067433 1.0144 -0.17431 -0.063368 -0.60363 0.20053 0.13679 -0.024741 0.47469 -0.77892 -0.28663 -0.27192 -0.67562 0.28207 0.1935 0.063162 0.73112 0.072682 0.51456 -0.55077 -0.25402 -0.077662 0.035238 -0.32021 -0.33759 -0.24357 0.035842 0.81423 -0.3508 0.18006 -0.049245 0.12888 -0.16803 -0.3665 0.63389 -0.13232 -0.54769 -3.4213 -0.38828 -0.24938 -0.41294 -0.2727 -0.3304 0.23315 -0.52551 0.21471 -0.38583 -0.30177 0.30061 -0.33541 -0.60107 0.23551 -0.80369 -0.13737 -0.1429 0.16166 0.32293 -0.12294 0.16138 -0.093296 0.14234 0.27728 0.036312 -0.19796 0.1936 -0.46891 0.82351 -0.53899 -0.24703 0.049887 0.54725 0.009746 0.57974 -0.0091502 -0.34196 0.026213 0.19177 0.5079 0.16918 0.6699 0.4473 -0.61384 -0.015805 -0.42108 -0.087537') # boat gloves[4] = self.parse_vec('-0.39539 -0.25468 0.043564 0.36511 0.18522 0.329 0.19064 -0.11648 0.31226 -0.040298 -0.0062365 0.30342 -0.42173 0.77493 -0.03998 -0.067118 0.13732 0.95702 0.40353 -0.33322 -0.59533 -0.12267 0.12258 -0.042508 -0.14386 1.1716 0.39072 -0.047285 -0.0033427 -0.81392 0.72796 0.052686 -0.049161 -0.71438 -0.086344 0.33522 0.14088 0.70827 0.2561 0.16326 -0.006642 0.090248 0.16412 0.17618 0.47049 0.018178 0.77729 -0.39745 0.71365 0.64572 0.26825 -0.00055794 -0.76011 -0.37583 -0.20395 -0.083587 -0.49212 0.35199 -0.091585 -0.42059 0.166 1.0091 0.11889 -1.0233 -0.25455 -0.0037728 -0.31496 -0.0079189 -0.00569 -0.94841 -0.24254 0.00080959 0.65628 -0.54486 0.6096 -0.38037 -0.78455 0.12337 0.72398 -0.31379 1.1729 -0.18303 0.10475 -0.04287 -0.27979 -0.10889 0.3874 0.11326 -0.15383 0.32006 -0.11064 -0.1193 -0.33176 -0.31274 -0.11912 0.16069 -0.037982 0.23802 -0.91678 0.30449 0.60797 0.073835 -0.26335 -0.029634 -1.05 0.20826 -0.21924 0.13652 0.40489 0.25212 -0.22705 0.26812 -0.1994 -0.53777 -0.4988 -0.47727 -0.66004 -0.83413 0.047445 0.15756 0.23355 0.21463 -0.056451 0.080833 -0.044144 -0.046193 0.020127 0.61713 0.23021 0.46089 0.45184 -0.053696 -0.29686 0.065724 -0.2795 0.38674 0.10408 0.34197 -0.55379 -0.67967 -0.47101 0.35917 0.1974 -0.043696 -0.052605 -0.73159 0.16067 -0.3786 0.2434 0.61161 0.48916 -0.57555 -3.0066 -0.3901 0.38596 -0.048683 0.39269 0.6831 0.64456 0.87903 0.21022 0.17747 0.017671 0.60079 -0.41003 -0.26996 -0.0044936 0.14928 -0.40555 -0.16593 -0.85092 0.027109 -0.40114 -0.038453 0.17137 -0.17077 -0.17581 0.11836 0.223 0.59717 0.36317 -0.035388 0.30407 0.53003 -0.090254 -0.50943 0.28771 -0.1125 -0.35207 -0.07374 0.57425 -0.60225 -0.19009 0.43454 0.64101 -0.081903 0.529 0.15899 0.021136 -0.016624') # bottle gloves[5] = self.parse_vec('-0.79897 0.12251 0.15633 -0.023137 0.20395 -0.40863 0.11329 -0.26234 -0.04337 -0.28863 0.32162 0.80217 -0.69404 0.072699 0.032425 0.081859 0.49708 0.44474 -0.20787 0.10049 -0.36369 -0.020898 -0.0027382 -0.61522 0.38828 1.4885 -0.031765 0.27525 0.4149 0.13678 0.032849 0.094527 -1.2946 -0.14829 -0.75905 0.21244 0.11954 -0.25734 0.21472 0.11741 0.23785 0.23741 -0.32102 -0.16134 0.21676 0.05692 0.3519 0.57165 -0.13035 0.25762 -0.13437 0.048592 0.069208 -0.12793 0.08571 -0.17723 0.75061 0.074342 -0.63924 -0.046564 0.18867 -0.22023 -0.12546 -0.53414 0.21347 -1.2106 -0.14119 -0.62831 0.80332 -0.020454 0.21436 -0.5496 0.38633 0.36767 0.26217 -0.33457 0.10184 0.025629 0.01278 -0.0032671 1.1778 0.25938 -0.15306 -0.96678 0.5922 0.69536 -0.28397 0.082051 -0.4951 1.5883 -0.47416 0.017795 -0.041617 -0.5739 0.10164 -0.25656 -0.37935 -0.0095207 -0.29664 0.33145 -0.20419 -0.18354 -0.066054 0.56563 -0.8608 -0.54741 0.14342 -0.7112 -0.76279 -0.50002 -0.69331 0.75902 0.05013 -0.75578 0.058621 -0.36132 -0.57238 -0.18413 -0.10716 0.1963 -0.28295 0.13177 0.37334 -0.49856 0.085692 0.14263 0.040408 0.46739 0.47784 -0.35338 0.032038 -0.31784 -0.53549 -0.49545 -0.24752 0.082921 -0.22467 -0.093533 0.20728 0.49855 -0.056853 0.15364 -0.11297 -0.5746 0.33484 -0.55111 0.74624 0.21023 -0.20434 0.19723 0.6313 -0.2206 -3.2973 0.40132 -0.045925 0.031596 -0.19902 0.52396 0.18297 0.2443 0.30136 -0.26096 0.4531 -0.36779 -0.019241 0.17294 -0.69498 0.31856 0.10471 0.47494 0.11335 0.68598 -0.37452 0.053953 -0.72787 -0.50056 -0.33375 0.64967 0.29411 0.48564 0.034691 -0.04236 -0.02612 -0.10335 -0.27702 0.018744 -0.021129 -0.73097 -0.15203 -0.11875 -0.15249 -0.15179 -0.53379 0.75922 0.92714 -0.14741 0.26636 -0.23923 0.84491 -0.7012') # bus gloves[6] = self.parse_vec('0.36878 -0.040716 0.14877 -0.16091 0.25884 0.42093 -0.08497 -0.20741 -0.24405 0.16025 0.18248 0.27653 0.17274 -0.15511 0.1832 -0.59696 0.35511 0.21179 -0.88778 -0.14127 0.27427 -0.22426 -0.49829 -0.2489 -0.64608 -0.51976 0.029963 -0.39474 -0.3698 -0.45758 -0.26379 0.0055427 0.072394 -0.4574 0.13783 0.41553 -0.71718 0.36648 0.80797 0.11551 -0.44923 0.33793 -0.38741 -0.55758 0.064246 0.040185 -0.13671 0.15378 0.41823 0.33495 0.265 -0.18855 -0.20561 -0.56125 -0.49499 -0.29046 -0.38711 -0.040435 -0.60069 -0.37021 0.40149 -0.15775 0.64168 -0.027062 0.43667 -0.3754 0.2332 0.4121 -0.3158 -0.1494 -0.23384 -0.013539 0.25869 -0.56107 -0.29731 0.56592 -0.13422 0.012458 0.19112 0.35151 0.3017 -0.63447 -0.020045 -0.027795 -0.0084391 0.27444 -0.13512 -0.70592 0.64869 -0.32654 0.13714 -0.43252 -0.1321 0.32763 0.043845 0.2212 0.18353 -0.15674 -0.50952 0.15471 0.60796 -0.63089 0.29242 -0.37111 -0.31205 -0.91168 0.4415 -0.25655 0.36425 0.097246 -0.55528 0.29396 0.45414 -0.10683 -0.17456 -0.3311 -0.10974 -0.32565 0.10095 0.74103 0.3077 -0.60567 -0.34343 -0.08782 -0.36266 0.63673 0.17799 0.61259 -0.18688 0.80418 0.42218 -0.20539 0.14961 -0.30303 -0.79753 0.10696 -0.35002 0.23048 0.15042 0.061245 -0.59652 0.0026576 0.05751 0.034295 0.024454 0.097094 -0.0058212 -0.79352 -0.43982 -0.45078 0.33703 -0.081068 -4.0471 0.21823 0.20914 -0.66168 -0.010194 0.86391 0.31894 0.0099252 0.69654 0.4219 0.68502 0.26832 -0.31542 -0.60462 -0.89089 -0.27853 -0.28233 -0.22141 -0.31363 -0.045722 -0.78919 -0.42835 0.90955 -0.49916 0.20697 0.036049 -0.38361 0.69864 0.58477 -0.12021 -0.14528 0.61904 -0.39795 0.042507 -0.04765 0.37876 0.54698 0.26489 0.6039 -0.48082 0.017844 0.4663 -0.35059 -0.098496 -0.5092 0.43729 -0.3703 0.73458') # car gloves[7] = self.parse_vec('-0.023756 -0.6095 -0.64204 0.21877 0.46728 0.18328 -0.017327 -0.1671 0.15519 -0.19869 0.58117 0.40394 -0.39322 -0.14633 -0.14179 0.015474 0.11165 -0.10333 -0.20328 -0.071406 0.12644 -0.26139 -0.36218 -0.67246 -0.34604 0.59822 -0.17553 -0.031497 0.11128 -0.3225 0.061777 0.38997 -0.33846 -0.1767 -0.082802 0.41319 -0.47078 0.48865 0.74484 0.24344 0.43444 0.34383 -0.63643 0.41448 -0.38013 -0.16224 0.41776 -0.045915 0.76219 0.055854 0.80065 0.22815 -0.95708 -0.064152 -0.25136 0.030722 -0.56599 0.13781 0.093393 -0.83462 0.32205 -0.065024 0.86411 -0.054507 0.19187 -0.39785 0.16377 0.57524 -0.37361 -0.72036 -0.48547 0.18768 -0.2428 -0.0031741 -0.43129 0.21333 -0.36452 0.15536 -0.18761 0.43804 0.66989 0.1977 -0.48026 0.17955 -0.26623 0.3866 0.37762 0.33181 -0.29401 0.089559 -0.1417 0.090185 0.23631 0.05726 0.49807 0.5556 0.0085019 -0.19751 -0.99868 -0.12837 0.72538 -0.21058 -0.17776 0.54406 -0.51257 -0.30398 0.5172 -0.4982 0.72498 -0.13728 -0.15657 0.48735 -0.12313 -0.44957 0.10629 0.13345 -0.71389 -0.41793 -0.77205 0.70404 0.35033 -0.33719 -0.23397 -0.18326 -0.36967 0.76203 0.23946 0.85417 0.069386 -0.19864 0.38917 -0.12225 -0.34538 0.062926 -0.31898 0.17836 -0.4046 0.38409 -0.20409 0.35095 -0.42669 -0.06645 0.2125 0.14951 -0.23864 0.1338 0.11083 0.21279 -0.0037618 -0.13022 0.21465 -0.51508 -4.7217 0.15789 0.26162 -0.15878 0.012484 -0.13879 0.40189 -0.49206 0.35261 0.62121 0.37681 0.54427 0.06366 -0.3226 -0.47194 -0.6409 -0.16708 -0.067091 0.21019 0.52271 -0.51378 -0.45009 0.77929 -0.033527 0.34275 0.15728 0.22613 1.0059 0.091323 0.025024 0.1937 0.17346 0.35938 -0.59598 0.52244 -0.32664 0.23388 0.29734 -0.1782 -0.58709 0.58139 -0.39022 -0.17797 0.02756 -0.2737 0.00032772 0.3212 0.31734') # cat gloves[8] = self.parse_vec('0.14557 -0.47214 0.045594 -0.11133 -0.44561 0.016502 0.46724 -0.18545 0.41239 -0.67263 -0.48698 0.72586 -0.22125 -0.20023 0.1779 0.67062 0.41636 0.065783 0.48212 -0.035627 -0.47048 0.077485 -0.28296 -0.49671 0.337 0.71805 0.22005 0.12718 0.067862 0.40265 -0.01821 0.78379 -0.52571 -0.39359 -0.56827 -0.15662 -0.084099 -0.20918 -0.066157 0.25114 -0.40015 0.1593 0.17887 -0.3211 0.09951 0.52923 0.48289 0.14505 0.44368 0.17365 0.3635 -0.51496 -0.12889 -0.19713 0.18096 -0.011301 0.84409 0.98606 0.83535 0.3541 -0.23395 0.3551 0.41899 -0.054763 0.22902 -0.19593 -0.57777 0.29728 0.33972 -0.31119 -0.32498 -0.42557 -0.70302 -0.72515 -0.29349 0.49964 -0.32889 0.24359 0.13243 0.31164 1.2156 0.31241 -0.23794 0.38422 -0.321 -0.28756 -0.20047 0.34454 -0.64929 0.28021 0.060203 0.053618 -0.13341 0.2451 0.18639 -0.0016346 -0.066883 0.077845 -0.085217 0.75257 0.76264 -0.053318 0.071056 0.30552 -0.43411 -0.19361 -0.10493 -0.53732 -0.239 -0.47298 -0.029825 -0.20206 -0.48945 -0.13616 0.49622 0.20743 -0.077396 -0.34304 0.0062387 -0.0065902 -0.24729 -0.013859 -0.079919 0.43452 0.23415 0.17995 0.13236 -0.22717 -0.55278 0.042005 0.21937 0.42042 0.43639 -0.58305 -0.118 0.15379 -0.29596 -0.46251 0.52593 0.10471 -0.19973 -0.028228 0.49974 -0.58053 -0.51416 0.21325 -0.38394 -0.00059821 0.16525 -0.055993 -0.4008 -0.05483 -3.8842 -0.022136 -0.46989 0.23502 0.081298 0.83091 0.47251 0.074057 0.15737 0.065809 -0.26756 0.1947 -0.63597 -0.59914 -0.21369 0.011718 -0.25464 -0.19629 0.18017 0.59031 0.0062176 0.51122 0.36601 -0.27381 -0.11342 0.21195 0.43099 -0.43837 0.12842 0.39312 -0.19492 0.056414 0.54343 0.13678 -0.71087 0.38758 -0.0078956 -0.32383 0.064193 -0.22329 0.071366 -0.30966 -0.46142 0.29545 -0.49186 0.24053 -0.46081 -0.077296') # chair gloves[9] = self.parse_vec('0.083778 -0.31358 0.44036 -0.19852 0.43794 0.51642 0.53045 0.38768 -0.25435 -0.13987 -0.087003 0.52748 -1.0245 0.26502 0.39768 -0.080842 -0.22176 0.25287 -0.22036 0.19245 0.31503 0.24298 -0.31244 -0.5538 -0.065636 1.1332 0.59765 -0.044034 -0.78153 -0.86698 0.28703 -0.76905 -0.084277 -0.22998 -0.15668 -0.3007 0.3213 0.056273 0.28742 0.2602 0.84825 -0.0071684 0.37892 -0.012884 0.00038517 0.17809 0.63603 0.89252 0.3586 0.20689 0.46894 -0.53883 0.0010013 -0.040398 0.0050846 -0.088845 0.40522 -0.00066163 0.40549 0.078797 0.22208 0.28788 0.7882 -0.70755 -0.39356 -0.29528 0.40909 -0.36923 0.72393 -0.17285 0.097639 -0.028392 -0.028554 -0.18386 -0.21958 0.41438 0.12902 0.29108 -0.49385 0.30497 0.020471 0.10858 -0.44766 -0.072593 0.50049 -0.34468 0.45321 0.1845 -0.35328 0.43199 -0.11018 0.26425 -0.63166 0.11634 0.67827 -0.57504 0.16556 -0.88157 -0.94127 0.35106 0.15176 -0.13839 0.12987 -0.33697 -1.1608 -0.14715 -0.054598 -0.32148 0.070592 -0.30956 -0.07437 0.76935 0.19682 -0.59907 -0.10843 0.39593 0.11362 -0.85316 0.10575 0.25386 -0.0021121 0.47077 -0.11135 0.35682 -0.13714 0.21096 0.058276 0.55903 0.25444 0.32109 0.35921 0.66993 -0.59417 -0.043362 -0.12672 -0.66172 -0.0062734 0.6619 0.13831 0.63765 -0.42123 -0.26323 0.13225 -0.62235 0.42746 -0.32953 0.17725 -0.2127 -0.13381 0.39902 -0.24999 -0.28896 -2.8864 0.3831 0.091285 0.35551 0.3535 0.061948 0.35884 -0.020577 0.19219 -0.018047 0.88794 0.11279 0.25829 0.14008 -0.00049045 0.33372 0.10877 -0.20534 0.49567 0.18442 -0.51278 0.39767 0.95853 -0.38023 -0.01555 0.52021 -0.40211 0.38038 0.25662 0.11418 0.833 -0.039078 0.19066 0.15591 -0.45687 -0.12533 0.96457 -0.77102 0.42057 -0.37074 0.20668 0.32806 -0.12334 -0.38058 0.66554 0.10284 -0.38228 -0.26866') # cow gloves[10] = self.parse_vec('-0.50022 -0.36807 0.67852 0.73902 -0.265 0.2138 0.80012 -0.32307 -0.022903 -0.095265 -0.049275 0.85775 -0.1414 -0.23757 0.53613 0.76321 0.63271 -0.98486 0.21919 -0.45295 0.63721 0.11644 -0.6411 -0.14992 0.22396 1.0825 -0.09032 0.063134 0.09663 0.39048 0.12483 0.52111 -0.30639 -0.11429 -0.36173 0.20997 -0.32267 0.3406 0.095895 -0.046656 0.34377 -0.12895 -0.6377 0.35499 0.095412 0.26032 0.11898 0.32955 1.1196 0.10973 0.15534 -0.12486 -0.35955 -0.013375 0.41262 -0.37091 0.62772 0.44115 0.11786 0.5494 -0.79519 0.58553 0.09613 0.076929 -0.19485 -0.094721 -0.40216 0.47339 0.031281 0.56596 -0.096632 -0.28741 -0.058642 -0.60075 -0.258 0.11909 -0.31724 0.21365 -0.036304 0.40186 0.28296 0.60792 -0.64312 0.25329 -0.82223 0.64957 -0.15475 -0.057517 -0.048461 0.31191 -0.46918 -0.29295 0.2265 0.15877 0.21139 -0.077235 0.37437 -0.14858 0.30027 0.48047 -0.098092 0.46117 -0.21483 0.13998 -0.83095 -0.45552 -0.11837 -0.11443 -0.31663 -0.79722 0.058454 -0.23475 0.066028 0.22309 0.14601 -0.044701 -0.33712 0.63045 -0.16638 -0.67182 -0.2189 -0.14132 -0.043728 0.54265 -0.37985 0.059618 0.075789 -0.55127 -0.27159 0.11659 0.3785 0.16998 0.66348 0.20145 -0.097833 0.18527 -0.097937 0.64232 -0.40563 -0.21788 -0.35083 0.52864 -0.20921 -0.98088 0.066697 0.42067 0.13533 0.10734 -0.22574 -0.052797 0.041153 0.14589 -2.7129 -0.13888 0.10586 -0.37203 -0.043385 0.59728 0.34913 0.2266 0.094155 -0.23491 0.20874 0.063022 -0.13774 -0.61335 -0.55479 -0.032523 -0.35708 2.6989e-05 0.29623 0.44281 -0.29544 0.40348 0.030594 -0.48329 -0.44488 0.29776 0.19371 -0.068755 -0.53631 0.31017 -0.086424 0.11114 -0.055969 0.33717 0.077037 -0.062266 -0.19782 0.3087 -0.011787 -0.092054 0.49202 0.9067 -0.3875 -0.38298 -0.51466 0.27193 -0.46579 0.39654') # table (instead of diningtable) gloves[11] = self.parse_vec('-0.134 -0.33646 0.54234 -0.38614 0.35032 -0.042428 0.65948 0.50268 -0.23358 0.065875 -0.2383 0.3261 -0.88971 0.1316 0.1286 0.54411 -0.060063 -0.58494 -0.87027 0.068012 0.23148 0.060188 -0.34582 -0.5468 0.10941 0.51938 0.082787 0.22915 -0.0094834 0.040299 0.24899 -0.306 -0.22724 -0.58301 0.20897 -0.29863 0.61531 0.20226 0.88812 0.25077 0.37314 -0.081076 0.21412 0.23626 0.20637 0.13475 0.38395 0.23572 0.19801 0.34831 -0.29573 0.057377 0.22969 0.20866 0.67706 -0.3422 0.19446 -0.048101 0.062835 -0.35476 0.36633 0.26445 0.38393 -0.2259 -0.35441 -0.17699 0.49916 -0.39928 1.2351 0.087057 -0.12733 -0.17771 -0.33468 0.35263 -0.012405 0.030928 0.52244 0.058012 0.042316 0.65819 0.056759 -0.4262 0.022662 -0.933 0.60916 -0.12176 0.42021 -0.393 -0.23767 0.074235 -0.073421 0.88081 -0.72143 -0.38029 0.50629 0.0015509 0.10175 -0.53257 -0.56345 0.93009 0.02815 -0.13692 -0.15743 0.22503 -0.64667 -0.28772 -0.68087 -0.41039 0.070034 0.022488 -0.42095 -0.02085 0.0089226 -0.49268 0.20415 0.20063 0.47755 -0.47341 -0.070567 0.35511 -0.19021 0.55616 0.071037 0.48354 0.053282 0.194 0.64685 0.70101 -0.051358 -0.15977 0.54975 0.0050765 -0.088246 -0.20462 -0.68097 -0.36608 -0.45045 0.098466 0.039217 0.79404 -0.26734 -0.16116 -0.20512 -0.80283 0.52077 -0.27359 0.61654 -0.25623 -0.29343 0.20662 -0.60995 -0.48954 -3.5513 0.20977 0.37195 0.41746 0.24383 -0.25487 0.17495 0.085444 0.23693 -0.12911 0.040175 -0.15206 0.15921 0.2538 -0.092471 0.21385 0.81152 0.22078 0.36054 0.2941 -0.45904 0.12069 0.71867 -0.17193 0.25481 0.63885 -0.34664 0.58897 -0.23721 -0.15426 0.35082 -0.58878 -0.0075455 -0.20697 -0.38027 -0.53076 0.060267 -0.59977 0.16978 -0.18702 0.27114 -0.44326 0.171 0.067128 0.218 -0.10632 0.33975 -0.32446') # dog gloves[12] = self.parse_vec('-0.49586 -0.59369 -0.107 0.05593 -0.24633 -0.14021 0.63707 0.024992 0.25119 -0.55602 -0.37298 0.60131 -0.35971 -0.096752 0.18511 0.58992 0.47578 -0.16833 0.67079 -0.29472 0.069403 0.05334 -0.36154 -0.12883 0.27814 0.87467 0.12119 0.78215 -0.50617 0.28794 0.14213 0.83281 -0.27079 -0.28813 -0.67607 0.17991 -0.11046 -0.063062 -0.56297 0.36639 0.11009 0.2965 -0.12457 -0.11112 -0.24293 0.53344 0.75589 0.078154 0.91641 0.20878 0.01236 -0.71199 0.19085 -0.5199 -0.14181 0.078136 0.44157 1.0958 0.59009 0.35117 0.021684 0.1073 0.19942 -0.26355 0.084024 -0.32073 -0.24306 0.44821 0.14432 -0.063988 -0.15013 -0.33644 -0.67873 -0.64554 0.10706 0.64709 -0.20094 0.064682 0.035356 0.029288 0.99793 0.34343 -0.019469 0.70635 -0.54329 -0.057843 0.12624 -0.18132 0.099001 0.4478 -0.2641 -0.37506 -0.11238 -0.011805 0.33187 0.45295 0.1682 0.18379 0.29457 0.98963 0.5394 -0.0025833 -0.10989 0.30163 0.34495 -0.2275 -0.21093 -0.79685 0.29833 -0.64644 -0.18653 0.31771 0.061874 -0.44503 0.34052 0.5552 0.017743 -0.33609 0.18478 0.392 -0.44685 -0.2591 -0.4929 0.61712 -0.24546 0.15348 0.19796 0.041105 0.030167 0.13735 0.29154 0.079533 0.53594 -0.61848 0.082946 -0.43806 -0.16041 -0.44336 0.065162 0.29823 -0.13321 0.55445 0.29978 -0.63209 -0.45078 0.1534 -0.31124 0.258 0.062033 0.047879 0.37758 -0.007643 -4.328 0.65362 -0.45488 -0.4565 0.23566 1.0171 0.53344 -0.025861 0.067191 0.60342 -0.56511 0.57175 -0.47311 -0.43066 -0.13385 0.011506 -0.32674 -0.47726 0.010775 0.49053 -0.11302 0.23358 0.098286 -0.55746 0.096976 0.036503 0.41838 -0.22967 0.12346 0.23573 -0.17653 0.03863 0.62339 -0.083598 -0.62161 0.11059 0.11316 -0.26833 0.023406 -0.018887 -0.63446 -0.16513 -0.16886 0.087242 -0.10353 0.06788 -0.20546 0.17962') # horse gloves[13] = self.parse_vec('-0.8107 -0.2135 0.57229 0.38901 -0.53731 0.076275 0.80555 -0.64481 0.58122 -0.003714 0.15482 0.5188 -0.73224 -0.17708 0.37883 1.0903 0.39686 -0.38992 0.45664 -0.31646 0.49369 -0.16371 -0.45948 -0.21822 0.34105 0.96526 0.25932 0.12078 0.012586 0.084278 0.50996 0.27742 -0.15154 -0.13721 -0.098856 0.12999 -0.41539 0.21986 -0.27817 -0.1278 0.1805 -0.71333 0.3577 0.42558 0.25589 0.443 0.36289 0.17151 1.0117 0.74856 0.26782 -0.029225 -0.36808 -0.13197 0.51501 0.13333 0.0058557 0.80578 -0.0721 0.70669 -0.50893 1.2565 0.20282 -0.13758 -0.5108 -0.34195 -0.24551 0.53538 0.2398 -0.30907 -0.20728 -0.82592 -0.34368 0.017876 0.092939 0.049257 -0.43085 -0.13684 0.019521 -0.20954 0.58053 -0.18977 -0.28645 0.44486 -0.5442 0.708 0.46365 0.086484 -0.042811 0.04067 -0.26089 -0.4174 -0.35112 -0.45257 0.27432 0.42729 0.4371 0.31975 0.017235 0.42254 -0.053444 -0.16006 -0.31785 0.33874 -0.23682 -0.34646 -0.30786 -0.55616 -0.045204 0.012021 -0.63051 0.3996 -0.29002 0.0079054 0.047329 0.5004 0.060087 -0.2037 0.12378 0.24339 -0.38377 -0.50928 -0.1049 0.14504 -0.39883 -0.24158 -0.33095 0.20819 0.81785 -0.34484 0.25812 0.017235 0.25583 -0.096405 0.16331 0.12816 -0.1257 0.11052 -0.19591 0.26462 -0.093251 0.74641 0.37195 -0.19395 -0.26052 -0.36437 0.46078 0.22374 -0.15367 0.3202 0.19659 -0.18048 -3.2003 0.24416 -0.36079 -0.022701 -0.10411 0.57065 0.20385 0.020388 0.78644 0.55647 -0.1408 -0.11196 -0.50173 -0.38527 -0.2307 0.062547 -0.54328 -0.56776 0.38209 0.10156 -0.16395 0.35198 0.55722 -0.34555 0.017989 -0.040839 0.28383 -0.049434 0.11944 0.086508 0.4774 0.073957 -0.23412 0.29014 -0.14949 -0.2585 -0.29038 1.0173 0.59803 -0.083486 0.30558 0.47593 0.026809 0.090965 0.052627 0.074359 -0.36702 0.20615') # motorbike gloves[14] = self.parse_vec('-0.71389 0.24032 0.18202 -0.088098 -0.0221 0.40635 -0.052222 -0.7371 0.10113 -0.53055 0.31645 0.038549 -0.19491 -0.32697 0.19943 -0.57279 0.37553 -0.032514 0.38359 0.17835 0.15913 -0.35313 0.02973 -0.23569 -0.43549 1.1884 0.14985 -0.16452 -0.40016 -0.56127 -0.33039 0.52782 0.3549 -0.20633 0.083044 0.2831 0.11659 0.30438 0.10226 0.10078 0.028741 0.47505 -0.20491 0.85168 0.27381 -0.36575 -0.10471 -0.12137 0.57409 0.20199 0.67158 0.24407 -0.37533 -0.47886 0.14464 0.39224 -0.0092274 0.1721 -0.1426 0.2096 0.29686 0.29672 0.51776 -0.47219 -0.47362 0.11739 -0.63042 0.49884 -0.23614 -0.24633 -0.70232 -0.25878 0.030875 -0.16369 0.46182 0.5136 -0.38601 -0.047488 -0.094195 0.13135 0.8398 0.36724 -0.71488 0.37607 -0.48174 0.091225 0.75595 0.025951 -0.53061 0.067239 -0.096866 -0.017189 -0.41604 -0.25577 0.062865 0.72158 0.40743 0.30805 -0.090951 0.41967 0.65751 -0.40103 -0.63055 0.71519 -0.21426 -0.93983 -0.062673 -0.26543 0.57424 -0.18904 -0.048883 0.16076 0.17014 0.066801 -0.33529 0.49848 -0.36642 -0.39713 -0.024494 0.20383 0.27226 -0.77433 0.30171 0.57367 -0.043116 0.079159 0.11836 0.44143 0.38227 0.052925 0.42209 0.25846 0.22436 0.099898 -0.56815 0.5277 0.045656 0.26299 -0.28591 -0.083705 -0.15414 0.31572 -0.33542 0.55337 -0.41729 0.14364 0.27906 0.25342 0.21754 0.048804 0.49028 0.074632 -0.86813 0.46902 0.071533 0.19098 0.034001 0.085827 0.53565 -0.41446 0.89643 0.55033 0.12035 0.35773 0.46279 -0.32748 -0.19938 -0.19853 -0.67121 -0.28168 0.062604 -0.08126 0.18431 -0.20818 0.5847 0.28582 0.29446 -0.4769 -0.039078 0.049103 0.16808 0.10381 0.10851 -0.38339 -0.52841 -0.53238 0.19347 -0.58147 -0.075303 0.94578 0.027874 0.1047 -0.28123 0.39113 -0.014863 -0.14572 0.27597 0.57036 0.051002 0.5199') # person gloves[15] = self.parse_vec('-0.0050341 0.43759 -0.10728 -0.12754 0.14574 0.44772 0.95882 -0.064739 -0.50419 0.33734 -0.023299 -0.16157 -0.50659 -0.19574 0.11752 0.45953 0.59953 0.52383 0.30061 -0.1844 0.13675 0.65594 -0.074337 -0.3523 -0.052698 1.6318 -0.0046084 -0.25087 0.089844 -0.18572 -0.22642 -0.10869 0.048051 -0.17346 -0.43151 0.046666 -0.17714 0.088511 0.2762 0.63112 0.41748 0.0931 0.13658 0.28507 -0.32909 0.089497 0.83896 0.098229 -0.059272 0.2835 -0.27827 0.19624 -0.049926 -0.69574 0.05352 0.060065 -0.068556 0.35591 -0.33751 -0.29361 -0.20059 -0.70989 0.46549 -0.44908 0.39502 0.49783 0.11653 0.54268 -0.48819 0.33826 -0.19704 -0.25727 0.26366 -0.22318 0.89299 -0.31712 0.10259 0.22438 -0.3718 -0.40868 0.38256 0.42004 -0.45121 -0.21513 0.014042 -0.049652 -0.11214 0.011164 -0.3606 -0.22827 -0.29906 0.53176 -0.054389 0.4932 -0.0052785 -0.086764 0.018286 -0.37717 0.51306 0.02191 0.014376 -0.40826 -0.054018 -0.92469 0.62715 -0.089945 0.20125 0.35328 -0.11475 0.15953 -0.26962 0.32959 0.060915 -0.14037 -0.20202 -0.2143 -0.034605 -0.011244 -0.59668 -0.091056 -0.71178 0.042869 -0.57287 -0.32826 -0.067884 -0.17087 -0.19935 -0.1571 0.044163 -0.31392 -0.23472 0.22923 -0.014186 0.6537 0.30681 -0.13804 0.021964 0.024048 0.47967 -0.3507 0.086764 0.68457 0.05042 -0.058323 0.59401 0.44433 -0.26444 -0.29732 0.031588 -0.43998 -0.16777 0.069608 -5.1022 0.47442 -0.27831 -0.10934 0.46917 -0.083847 0.25815 0.17722 0.39479 0.17018 -0.44708 -0.1237 -0.26057 -0.73399 -0.6979 0.36218 0.16067 -0.19531 0.13494 -0.14111 -0.2051 0.29239 -0.053072 0.0051988 -0.062671 -0.45236 0.38349 0.13699 -0.041298 0.29428 -0.23263 -0.032635 0.18313 0.23076 -0.62433 0.53785 0.33477 -0.2688 0.41107 -0.079753 0.32565 -0.42345 -0.12034 0.55607 -0.030407 0.2565 0.057437 -0.43445') # plant (instead of pottedplant) gloves[16] = self.parse_vec('-0.11111 0.057649 0.10509 -0.20679 -0.6105 0.31852 0.42001 -0.17437 0.082972 -0.54518 -0.39878 0.39278 -1.3354 -0.074956 -0.084963 0.30613 0.2464 -0.30133 -0.01795 -0.66445 -0.36118 -0.070666 -0.55449 0.11218 -0.2291 0.86695 -0.22428 0.14198 0.17671 -0.037329 0.037456 0.35369 0.29038 -0.65732 -0.20003 -0.2671 -0.053406 1.121 -0.17424 0.14477 -0.072602 -0.033538 -0.50043 0.23116 0.28005 0.62388 0.32728 -0.51442 0.1267 -0.31332 0.73642 0.3247 0.35872 -0.032586 0.022577 -0.04257 0.86809 0.13627 0.36609 0.28022 0.52616 0.79906 0.087693 -0.21913 0.024632 -0.053635 0.51211 0.17806 -0.40947 -0.079995 -0.56075 0.51136 0.77576 0.16721 0.19856 -0.00095677 -0.20017 -0.23092 0.37044 -0.58672 1.1888 0.084034 0.25076 0.077527 0.42798 0.18191 -0.15721 0.49148 -0.51208 0.1111 0.15223 0.25601 0.22023 -0.39595 -0.2301 0.51021 0.28086 0.5029 0.28635 0.40141 0.62646 0.091801 0.62058 -0.043011 -0.49427 -0.70087 -0.30576 -0.36211 -0.34107 0.57102 -0.8341 -0.070333 0.089223 -0.080423 -0.18906 -0.64046 -0.40274 0.22003 -1.3558 0.25769 -0.9221 0.25875 0.35121 -0.2247 0.10865 -0.44573 0.020137 0.42043 0.613 0.12949 0.36586 0.38093 -0.090628 0.62279 -0.20802 -1.1409 -0.07417 -0.103 -0.041084 -0.5689 -0.84172 -0.085305 -0.13616 -0.35128 -0.25108 -0.30743 -0.13205 0.0080276 0.17393 0.36135 0.18384 0.39011 -2.4754 -0.78184 -0.3437 0.1192 0.16951 0.10794 0.11712 -0.45028 -0.090958 0.19695 0.40981 -0.017894 0.36176 -0.23603 -0.38903 -0.1323 0.45368 -0.47899 -0.039468 -0.42611 0.72573 -0.39974 -0.44137 -0.30683 0.32104 0.75202 0.088467 -0.33332 -0.33403 -0.021241 -0.57665 -0.29877 0.86615 0.055897 0.44669 0.093072 0.36417 0.13264 0.26142 0.21439 1.0113 0.45556 -0.17741 0.63894 0.50394 -0.096641 0.093821 -0.37366') # sheep gloves[17] = self.parse_vec('-0.48883 -0.20854 0.19 0.47514 -0.51317 0.93146 0.39056 -0.063723 0.37478 -0.51601 0.17559 -0.43622 -0.43426 0.47602 0.37163 0.29038 -0.13016 -0.43486 0.46872 -0.37762 -0.27845 0.18054 0.19341 -0.34921 0.46227 1.0573 0.34446 -0.54068 0.025835 0.27329 0.0035218 0.72711 0.15759 0.23173 0.47177 0.091373 -0.33239 0.64459 0.2321 0.53376 0.77982 0.25495 0.32031 1.3828 0.32023 -0.28634 -0.034268 -0.29433 1.1474 0.54237 -0.6161 -0.40534 0.14573 -0.27524 0.19085 -0.27628 0.04799 0.4885 0.39575 0.36233 0.0032923 0.65519 -0.1076 0.089766 -0.4876 0.26514 -0.58268 0.032213 -0.090252 0.52496 0.10102 0.11129 -0.44439 -0.13691 -0.26121 0.0056128 -0.29664 -0.37598 0.39873 0.66627 0.97159 0.82369 -0.28087 1.0091 -0.50606 0.43705 0.14394 -0.11277 -0.11075 0.049597 0.11112 0.033074 -0.42926 -0.18468 -0.57982 -0.31848 0.59124 0.38171 0.18173 0.24726 0.33712 0.70201 -0.10992 0.79551 -0.34354 -0.32717 0.030538 0.24604 -0.16857 -0.77267 -0.45843 -0.0060385 -0.33472 -0.26437 -0.21247 0.24241 -0.46285 0.32434 0.077569 0.28511 -0.38589 -0.0041081 -0.19887 -0.50601 0.54081 -0.33611 -0.10492 -0.55035 0.66215 0.056054 0.0033579 0.51826 0.1167 0.49053 0.012476 -0.024986 -0.099266 0.069926 -0.50376 -0.26692 -0.52158 0.74391 -0.29793 -0.74214 0.13901 0.32073 -0.30176 0.19213 -0.071006 -0.47931 -0.045606 0.083413 -2.2626 -0.62771 0.18383 -0.20006 0.20747 0.93842 0.039725 -0.073622 0.95418 0.13252 0.27428 0.020871 -0.99478 -0.60409 0.17769 0.30552 -1.1167 0.1562 0.042333 0.60667 0.31924 0.026862 -0.10894 -0.059597 -0.37697 -0.12174 0.6681 -0.45187 -0.65058 0.26808 0.014851 0.25176 0.15575 0.14464 -0.050168 -0.16096 -0.52247 -0.58604 0.2535 -0.62094 -0.24828 0.26319 -0.77109 -0.49111 -0.56805 -0.14462 -1.0704 -0.44761') # sofa gloves[18] = self.parse_vec('-0.55126 -0.25437 0.40944 -0.37035 0.15619 0.74781 -0.11626 -0.089062 0.32154 -0.44794 -0.79694 0.2678 -0.28714 -0.18248 -0.099868 0.0044547 0.14694 -0.35398 -0.27681 0.50209 -0.69361 -0.18524 -0.24016 0.065474 -0.12418 -0.62691 0.10098 0.40514 -0.49283 -0.2973 -0.15004 -0.3799 0.16639 -0.27232 0.012692 -0.57008 0.71212 0.014504 -0.32036 0.36146 -0.24907 0.0045155 0.60505 0.10751 -0.012905 -0.7139 -0.0033347 0.49277 0.20195 0.24275 -0.4409 -0.85957 0.20849 -0.15209 -0.14172 0.089232 -0.01787 0.43873 0.50058 0.22154 -0.033405 0.13686 0.7646 -0.69327 -0.26288 -0.23971 -0.17341 -0.23787 0.43504 0.11938 0.11955 0.34672 -0.71679 -0.29109 -0.10691 0.68078 0.40884 0.11318 -0.57474 0.75584 1.0335 -0.2474 -0.15966 -0.012803 0.54782 0.057099 0.4468 -0.71945 0.045912 0.4424 0.12564 0.35803 -0.0099155 0.31759 0.24738 -0.64752 0.25505 -0.67181 -1.0412 1.119 0.64015 -0.11319 0.046755 -0.47351 -0.98552 -0.17908 -0.49623 -0.41556 -0.20261 -0.69094 -0.47285 0.26574 0.7891 -0.069767 -0.03166 -0.41765 0.44728 -0.89895 0.077562 0.1578 0.19055 0.31422 -0.034844 -0.0092608 0.52623 0.92685 0.31479 0.097895 -0.46618 -0.029873 0.22965 0.29097 -0.12395 -0.33712 -0.54815 -0.35642 0.058376 0.47008 0.11739 0.64565 0.26692 0.43143 -0.14349 -0.63512 0.016551 0.35399 -0.43784 -0.15109 0.20562 0.51676 0.31307 0.10661 -2.6111 0.43525 0.29244 0.30252 0.44164 -0.086565 0.36163 -0.42814 0.39952 0.6095 0.37047 0.41566 -0.097301 0.16248 0.10507 0.59692 0.20441 0.14534 0.3668 0.76102 -0.086382 0.24676 0.84287 -0.22111 -0.34975 0.40324 -0.2311 0.21589 0.12531 -0.19429 0.36596 0.18071 -0.090265 0.02224 -0.63616 0.52052 0.49612 0.082192 0.79162 -0.90827 0.53091 -0.42354 0.48783 -0.71943 -0.2491 0.33456 -0.13367 0.41854') # train gloves[19] = self.parse_vec('0.37548 -0.16669 0.20334 -0.1707 0.057389 0.63362 0.098189 0.17951 0.094536 0.61758 -0.012194 0.03028 -0.59888 -0.46359 -0.86279 0.16698 0.17168 0.33183 -0.34339 0.28135 0.25715 -0.61989 0.25431 -0.3545 -0.23358 0.82254 -0.19874 -0.59826 0.41849 -0.2918 -0.010124 0.035356 -0.22821 -0.024697 0.29794 -0.19534 -0.57675 0.1217 1.1021 -0.36827 -0.20924 -0.33711 -0.043826 -0.59845 0.2646 -0.51695 -0.33889 -0.12732 0.15502 -0.07516 0.34644 -0.75462 0.068238 -0.13422 -0.76469 0.37285 -0.052013 0.65885 -0.042933 -0.28987 -0.11953 0.083422 0.32609 -0.17798 -0.41476 -0.65127 0.44529 0.89459 -0.020621 -0.2502 -0.098399 0.38612 -0.090363 -0.42287 -0.031872 0.56521 -0.2458 0.25975 -0.40278 -0.15071 0.2289 -0.61254 -0.10832 0.045791 -0.082635 0.85964 -0.099326 0.072384 0.61234 -0.067309 0.44315 0.37082 -0.70074 1.0807 0.071388 0.44729 0.30407 0.2371 -0.085221 0.15809 0.75598 -0.35196 0.044777 -0.12434 -0.24014 -0.53403 0.24857 -0.171 1.1383 0.13646 -0.097531 -0.21034 0.08839 -0.52547 0.48343 -0.34049 0.08137 -0.54899 0.11817 1.1512 -0.078584 -0.3733 -0.15421 0.30997 -0.79899 -0.029586 -0.018026 -0.0035351 0.18488 1.0739 -0.055238 -0.14807 0.61702 -0.25605 -0.14685 -0.061761 -0.37885 0.479 -0.3825 -0.061271 -1.0717 0.37763 -0.74767 -0.40958 0.76752 -0.43954 0.2279 -0.42838 -0.80615 -1.0569 0.36154 -0.6756 -3.9798 0.43417 0.058424 -0.25163 0.017483 -0.03925 0.078241 0.47291 0.21551 0.32782 -0.19112 0.47168 -0.48036 -0.62983 -0.23916 -0.078116 -0.99057 -0.31946 -0.040178 -0.061123 -0.5638 -1.2017 1.0233 -0.81923 0.70827 0.47827 0.090528 0.32272 0.44516 0.26923 0.19288 0.69647 0.22837 -0.64528 0.13395 0.5601 0.58335 -0.065198 -0.016235 -0.18649 0.47786 0.54648 0.61327 0.14863 -0.098438 -0.33517 0.48419 0.22443') # monitor (instead of tvmonitor) gloves[20] = self.parse_vec('0.39506 0.57035 -0.34469 -0.2418 -0.085844 0.076654 -0.101 -0.043672 0.35994 -0.068255 0.2001 -0.18981 -0.807 -0.10697 -0.49271 -0.62257 0.033404 0.043097 -0.16137 0.037069 -0.092297 0.71918 -0.33535 0.99444 -0.23735 -0.18001 -0.3563 -0.035004 -0.42524 0.020921 0.59765 -0.68987 0.42215 -0.039423 0.81596 -1.0068 0.056338 -0.28865 -0.3757 0.41928 0.026622 0.43745 -0.34303 -0.038377 -0.74057 -0.060697 -0.25378 0.020666 -0.29184 -0.3001 0.0055599 0.24966 -0.58941 -0.46169 -0.14104 0.056481 -0.22584 -0.093435 0.50993 0.079872 0.085146 -0.030725 0.92953 0.31664 0.45899 -0.16236 0.18509 -0.3883 0.36874 -0.094179 0.080235 0.3334 -0.55517 -0.52172 0.035944 0.14773 0.20172 -0.43234 0.26623 -0.18526 0.447 0.72035 0.45101 -0.44633 0.42394 -0.31974 0.26068 0.39124 0.30794 0.27531 -0.74552 0.38866 0.24196 -0.015859 0.10625 -0.27747 0.19079 -0.52362 -0.65494 0.78146 0.40401 0.28761 0.43292 -0.73568 -0.43771 -0.6939 -0.48592 0.055997 0.086118 -0.63828 -0.23677 -0.0023004 0.41527 -0.12113 0.76192 0.55498 -0.13573 0.069332 -0.56071 0.57345 0.1751 0.061245 -0.19107 0.35412 0.44524 0.52874 -0.067264 0.26821 0.12174 0.060287 -0.47326 0.10187 0.044595 0.60027 -0.22113 -0.63658 -0.36007 -0.14078 -0.15648 -0.064581 0.19529 -0.47165 0.1875 -0.20738 0.49041 -0.15263 -0.18486 -0.62451 -0.065947 -0.18168 0.55734 -0.3354 -2.1831 0.073034 -0.55689 0.20047 0.48988 -0.25795 0.16526 0.13197 -0.0024545 0.0057711 0.74506 0.007249 -0.53246 0.045723 -0.45975 -0.96999 0.74073 0.1641 0.49533 -0.030726 0.11014 -0.36607 0.04882 -0.26971 0.52963 0.40551 -0.31313 0.26866 0.19646 0.71257 0.22745 -0.50536 0.34653 0.51053 0.014612 -0.1723 0.056945 0.66266 0.71526 0.03419 0.17104 -0.049182 -0.27842 -0.29963 0.41816 0.16741 0.34322 0.25798') return gloves def set_emb_vecs(self, emb_selection): if emb_selection == 'glove': embs = self.set_glove() elif emb_selection == 'random': embs = np.random.randn(len(self.CLASSES), self.EMB_DIM) elif emb_selection == 'farthest_points': pts = np.random.randn(100 * len(self.CLASSES), self.EMB_DIM) inds = generate_farthest_vecs(pts, len(self.CLASSES)) embs = pts[inds] elif emb_selection == 'orthogonal': pts = np.random.randn(self.EMB_DIM, self.EMB_DIM) q, _ = np.linalg.qr(pts, 'complete') embs = q.T[:len(self.CLASSES)] else: raise AssertionError('Unknown emb_selection: {}'.format(emb_selection)) embs = embs.astype(np.float32) return embs def prepare_test_img(self, idx): img_info = self.img_infos[idx] ann_info = self.get_ann_info(idx) results = dict(img_info=img_info, ann_info=ann_info) self.pre_pipeline(results) seg_map = self.gt_seg_map_loader(results) results = self.pipeline(results) results['gt_semantic_seg'] = seg_map['gt_semantic_seg'] return results

325.16

1,777

0.693935

9,002

40,645

3.121417

0.472895

0.006264

0.008968

0.009716

0.011353

0.007687

0.00363

0

0.732884

0.135761

40,645

124

1,778

327.782258

0.067042

0.008562

0

0.023529

1

0.247059

0.903942

0.000621

0

0.023529

1

0.058824

false

0

0.070588

0.011765

0.223529

0.023529

0

null

0

1

0

1

0

1

0

null

0

7

47f3ffa35ff6bef996b55bed30381d8d8da1530a

43

py

Python

example_pkg/example.py

IoC-Sunderland/Example-Package-Structure

3664c780a52d73ac93cb6bab83c1506c0a9c08c9

[ "MIT" ]

null

example_pkg/example.py

IoC-Sunderland/Example-Package-Structure

3664c780a52d73ac93cb6bab83c1506c0a9c08c9

[ "MIT" ]

null

example_pkg/example.py

IoC-Sunderland/Example-Package-Structure

3664c780a52d73ac93cb6bab83c1506c0a9c08c9

[ "MIT" ]

null

def my_func(): return 'Hi, we made it'

10.75

25

0.604651

8

43

3.125

1

0

0.255814

43

3

26

14.333333

0.78125

0

0.325581

0

1

0.5

true

0

0.5

1

0

1

0

null

0

1

0

null

0

1

0

1

0

7

9a127315b31fdad49a3649f080bf9aa672bf0683

269,731

py

Python

sdks/python/appcenter_sdk/api/distribute_api.py

Brantone/appcenter-sdks

eeb063ecf79908b6e341fb00196d2cd9dc8f3262

[ "MIT" ]

null

sdks/python/appcenter_sdk/api/distribute_api.py

Brantone/appcenter-sdks

eeb063ecf79908b6e341fb00196d2cd9dc8f3262

[ "MIT" ]

6

2019-10-23T06:38:53.000Z

2022-01-22T07:57:58.000Z

sdks/python/appcenter_sdk/api/distribute_api.py

Brantone/appcenter-sdks

eeb063ecf79908b6e341fb00196d2cd9dc8f3262

[ "MIT" ]

2

2019-10-23T06:31:05.000Z

2021-08-21T17:32:47.000Z

# coding: utf-8 """ App Center Client Microsoft Visual Studio App Center API # noqa: E501 OpenAPI spec version: preview Contact: benedetto.abbenanti@gmail.com Project Repository: https://github.com/b3nab/appcenter-sdks """ from __future__ import absolute_import import re # noqa: F401 # python 2 and python 3 compatibility library import six from appcenter_sdk.api_client import ApiClient class distributeApi(object): """NOTE: This class is auto generated by the swagger code generator program. Do not edit the class manually. Ref: https://github.com/swagger-api/swagger-codegen """ def __init__(self, api_client=None): if api_client is None: api_client = ApiClient() self.api_client = api_client def devices_registerUserForDevice(self, user_id, body, **kwargs): # noqa: E501 """devices_registerUserForDevice # noqa: E501 Registers a user for an existing device # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_registerUserForDevice(user_id, body, async=True) >>> result = thread.get() :param async bool :param string user_id: The ID of the user (required) :param object body: The device info. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_registerUserForDevice_with_http_info(user_id, body, **kwargs) # noqa: E501 else: (data) = self.devices_registerUserForDevice_with_http_info(user_id, body, **kwargs) # noqa: E501 return data def devices_registerUserForDevice_with_http_info(self, user_id, body, **kwargs): # noqa: E501 """devices_registerUserForDevice # noqa: E501 Registers a user for an existing device # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_registerUserForDevice_with_http_info(user_id, body, async=True) >>> result = thread.get() :param async bool :param string user_id: The ID of the user (required) :param object body: The device info. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['user_id', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_registerUserForDevice" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'user_id' is set if ('user_id' not in params or params['user_id'] is None): raise ValueError("Missing the required parameter `user_id` when calling `devices_registerUserForDevice`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `devices_registerUserForDevice`") # noqa: E501 collection_formats = {} path_params = {} if 'user_id' in params: path_params['user_id'] = params['user_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/users/{user_id}/devices/register', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def devices_deviceDetails(self, device_udid, **kwargs): # noqa: E501 """devices_deviceDetails # noqa: E501 Returns the device details. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_deviceDetails(device_udid, async=True) >>> result = thread.get() :param async bool :param string device_udid: The UDID of the device (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_deviceDetails_with_http_info(device_udid, **kwargs) # noqa: E501 else: (data) = self.devices_deviceDetails_with_http_info(device_udid, **kwargs) # noqa: E501 return data def devices_deviceDetails_with_http_info(self, device_udid, **kwargs): # noqa: E501 """devices_deviceDetails # noqa: E501 Returns the device details. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_deviceDetails_with_http_info(device_udid, async=True) >>> result = thread.get() :param async bool :param string device_udid: The UDID of the device (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['device_udid'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_deviceDetails" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'device_udid' is set if ('device_udid' not in params or params['device_udid'] is None): raise ValueError("Missing the required parameter `device_udid` when calling `devices_deviceDetails`") # noqa: E501 collection_formats = {} path_params = {} if 'device_udid' in params: path_params['device_udid'] = params['device_udid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/user/devices/{device_udid}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def devices_removeUserDevice(self, device_udid, **kwargs): # noqa: E501 """devices_removeUserDevice # noqa: E501 Removes an existing device from a user # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_removeUserDevice(device_udid, async=True) >>> result = thread.get() :param async bool :param string device_udid: The UDID of the device (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_removeUserDevice_with_http_info(device_udid, **kwargs) # noqa: E501 else: (data) = self.devices_removeUserDevice_with_http_info(device_udid, **kwargs) # noqa: E501 return data def devices_removeUserDevice_with_http_info(self, device_udid, **kwargs): # noqa: E501 """devices_removeUserDevice # noqa: E501 Removes an existing device from a user # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_removeUserDevice_with_http_info(device_udid, async=True) >>> result = thread.get() :param async bool :param string device_udid: The UDID of the device (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['device_udid'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_removeUserDevice" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'device_udid' is set if ('device_udid' not in params or params['device_udid'] is None): raise ValueError("Missing the required parameter `device_udid` when calling `devices_removeUserDevice`") # noqa: E501 collection_formats = {} path_params = {} if 'device_udid' in params: path_params['device_udid'] = params['device_udid'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/user/devices/{device_udid}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def devices_userDevicesList(self, **kwargs): # noqa: E501 """devices_userDevicesList # noqa: E501 Returns all devices associated with the given user. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_userDevicesList(async=True) >>> result = thread.get() :param async bool :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_userDevicesList_with_http_info(**kwargs) # noqa: E501 else: (data) = self.devices_userDevicesList_with_http_info(**kwargs) # noqa: E501 return data def devices_userDevicesList_with_http_info(self, **kwargs): # noqa: E501 """devices_userDevicesList # noqa: E501 Returns all devices associated with the given user. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_userDevicesList_with_http_info(async=True) >>> result = thread.get() :param async bool :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = [] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_userDevicesList" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/user/devices', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_listTesterApps(self, **kwargs): # noqa: E501 """releases_listTesterApps # noqa: E501 Return a list of applications that the user has tester permission to with the latest release for each. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_listTesterApps(async=True) >>> result = thread.get() :param async bool :return: array If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_listTesterApps_with_http_info(**kwargs) # noqa: E501 else: (data) = self.releases_listTesterApps_with_http_info(**kwargs) # noqa: E501 return data def releases_listTesterApps_with_http_info(self, **kwargs): # noqa: E501 """releases_listTesterApps # noqa: E501 Return a list of applications that the user has tester permission to with the latest release for each. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_listTesterApps_with_http_info(async=True) >>> result = thread.get() :param async bool :return: array If the method is called asynchronously, returns the request thread. """ all_params = [] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_listTesterApps" % key ) params[key] = val del params['kwargs'] collection_formats = {} path_params = {} query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/tester/apps', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='array', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_getLatestByHash(self, app_secret, release_hash, **kwargs): # noqa: E501 """releases_getLatestByHash # noqa: E501 Get a release with hash 'release_hash' or the 'latest' from all the distribution groups assigned to the current user. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByHash(app_secret, release_hash, async=True) >>> result = thread.get() :param async bool :param string app_secret: The secret of the target application (required) :param string release_hash: The hash of the release or 'latest' to get the latest release from all the distribution groups assigned to the current user. (required) :param string udid: When passing `udid` in the query string, a provisioning check for the given device ID will be done. Will be ignored for non-iOS platforms.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_getLatestByHash_with_http_info(app_secret, release_hash, **kwargs) # noqa: E501 else: (data) = self.releases_getLatestByHash_with_http_info(app_secret, release_hash, **kwargs) # noqa: E501 return data def releases_getLatestByHash_with_http_info(self, app_secret, release_hash, **kwargs): # noqa: E501 """releases_getLatestByHash # noqa: E501 Get a release with hash 'release_hash' or the 'latest' from all the distribution groups assigned to the current user. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByHash_with_http_info(app_secret, release_hash, async=True) >>> result = thread.get() :param async bool :param string app_secret: The secret of the target application (required) :param string release_hash: The hash of the release or 'latest' to get the latest release from all the distribution groups assigned to the current user. (required) :param string udid: When passing `udid` in the query string, a provisioning check for the given device ID will be done. Will be ignored for non-iOS platforms.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['app_secret', 'release_hash', 'udid'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_getLatestByHash" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'app_secret' is set if ('app_secret' not in params or params['app_secret'] is None): raise ValueError("Missing the required parameter `app_secret` when calling `releases_getLatestByHash`") # noqa: E501 # verify the required parameter 'release_hash' is set if ('release_hash' not in params or params['release_hash'] is None): raise ValueError("Missing the required parameter `release_hash` when calling `releases_getLatestByHash`") # noqa: E501 collection_formats = {} path_params = {} if 'app_secret' in params: path_params['app_secret'] = params['app_secret'] # noqa: E501 if 'release_hash' in params: path_params['release_hash'] = params['release_hash'] # noqa: E501 query_params = [] if 'udid' in params: query_params.append(('udid', params['udid'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/sdk/apps/{app_secret}/releases/{release_hash}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_getLatestByPublicDistributionGroup(self, app_secret, distribution_group_id, **kwargs): # noqa: E501 """releases_getLatestByPublicDistributionGroup # noqa: E501 Get a release with 'latest' for the given public group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByPublicDistributionGroup(app_secret, distribution_group_id, async=True) >>> result = thread.get() :param async bool :param string app_secret: The secret of the target application (required) :param string distribution_group_id: the id for destination (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_getLatestByPublicDistributionGroup_with_http_info(app_secret, distribution_group_id, **kwargs) # noqa: E501 else: (data) = self.releases_getLatestByPublicDistributionGroup_with_http_info(app_secret, distribution_group_id, **kwargs) # noqa: E501 return data def releases_getLatestByPublicDistributionGroup_with_http_info(self, app_secret, distribution_group_id, **kwargs): # noqa: E501 """releases_getLatestByPublicDistributionGroup # noqa: E501 Get a release with 'latest' for the given public group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByPublicDistributionGroup_with_http_info(app_secret, distribution_group_id, async=True) >>> result = thread.get() :param async bool :param string app_secret: The secret of the target application (required) :param string distribution_group_id: the id for destination (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['app_secret', 'distribution_group_id'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_getLatestByPublicDistributionGroup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'app_secret' is set if ('app_secret' not in params or params['app_secret'] is None): raise ValueError("Missing the required parameter `app_secret` when calling `releases_getLatestByPublicDistributionGroup`") # noqa: E501 # verify the required parameter 'distribution_group_id' is set if ('distribution_group_id' not in params or params['distribution_group_id'] is None): raise ValueError("Missing the required parameter `distribution_group_id` when calling `releases_getLatestByPublicDistributionGroup`") # noqa: E501 collection_formats = {} path_params = {} if 'app_secret' in params: path_params['app_secret'] = params['app_secret'] # noqa: E501 if 'distribution_group_id' in params: path_params['distribution_group_id'] = params['distribution_group_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/v0.1/public/sdk/apps/{app_secret}/distribution_groups/{distribution_group_id}/releases/latest', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def distibutionReleases_installAnalytics(self, owner_name, app_name, body, **kwargs): # noqa: E501 """distibutionReleases_installAnalytics # noqa: E501 Notify download(s) for the provided distribution release(s). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.distibutionReleases_installAnalytics(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the app owner (required) :param string app_name: The name of the app (required) :param object body: The install analytics request payload (required) :return: None If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.distibutionReleases_installAnalytics_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.distibutionReleases_installAnalytics_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 return data def distibutionReleases_installAnalytics_with_http_info(self, owner_name, app_name, body, **kwargs): # noqa: E501 """distibutionReleases_installAnalytics # noqa: E501 Notify download(s) for the provided distribution release(s). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.distibutionReleases_installAnalytics_with_http_info(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the app owner (required) :param string app_name: The name of the app (required) :param object body: The install analytics request payload (required) :return: None If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method distibutionReleases_installAnalytics" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `distibutionReleases_installAnalytics`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `distibutionReleases_installAnalytics`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `distibutionReleases_installAnalytics`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'text/csv', 'text/plain']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/v0.1/public/apps/{owner_name}/{app_name}/install_analytics', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type=None, # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_getIosManifest(self, app_id, release_id, token, **kwargs): # noqa: E501 """releases_getIosManifest # noqa: E501 Returns the manifest.plist in XML format for installing the release on a device. Only available for iOS. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getIosManifest(app_id, release_id, token, async=True) >>> result = thread.get() :param async bool :param string app_id: The ID of the application (required) :param integer release_id: The release_id (required) :param string token: A hash that authorizes the download if it matches the release info. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_getIosManifest_with_http_info(app_id, release_id, token, **kwargs) # noqa: E501 else: (data) = self.releases_getIosManifest_with_http_info(app_id, release_id, token, **kwargs) # noqa: E501 return data def releases_getIosManifest_with_http_info(self, app_id, release_id, token, **kwargs): # noqa: E501 """releases_getIosManifest # noqa: E501 Returns the manifest.plist in XML format for installing the release on a device. Only available for iOS. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getIosManifest_with_http_info(app_id, release_id, token, async=True) >>> result = thread.get() :param async bool :param string app_id: The ID of the application (required) :param integer release_id: The release_id (required) :param string token: A hash that authorizes the download if it matches the release info. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['app_id', 'release_id', 'token'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_getIosManifest" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'app_id' is set if ('app_id' not in params or params['app_id'] is None): raise ValueError("Missing the required parameter `app_id` when calling `releases_getIosManifest`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_getIosManifest`") # noqa: E501 # verify the required parameter 'token' is set if ('token' not in params or params['token'] is None): raise ValueError("Missing the required parameter `token` when calling `releases_getIosManifest`") # noqa: E501 collection_formats = {} path_params = {} if 'app_id' in params: path_params['app_id'] = params['app_id'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 query_params = [] if 'token' in params: query_params.append(('token', params['token'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = [] # noqa: E501 return self.api_client.call_api( '/v0.1/public/apps/{app_id}/releases/{release_id}/ios_manifest', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeNotifications_getNotificationByAppId(self, owner_name, app_name, **kwargs): # noqa: E501 """storeNotifications_getNotificationByAppId # noqa: E501 Application specific store service status # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeNotifications_getNotificationByAppId(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeNotifications_getNotificationByAppId_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeNotifications_getNotificationByAppId_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def storeNotifications_getNotificationByAppId_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """storeNotifications_getNotificationByAppId # noqa: E501 Application specific store service status # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeNotifications_getNotificationByAppId_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeNotifications_getNotificationByAppId" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeNotifications_getNotificationByAppId`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeNotifications_getNotificationByAppId`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/store_service_status', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def devices_getReleaseUpdateDevicesStatus(self, release_id, resign_id, owner_name, app_name, **kwargs): # noqa: E501 """devices_getReleaseUpdateDevicesStatus # noqa: E501 Returns the resign status to the caller # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_getReleaseUpdateDevicesStatus(release_id, resign_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string release_id: The ID of the release. (required) :param string resign_id: The ID of the resign operation. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean include_provisioning_profile: A boolean value that indicates if the provisioning profile should be return in addition to the status. When set to true, the provisioning profile will be returned only when status is 'complete' or 'preparing_for_testers'.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_getReleaseUpdateDevicesStatus_with_http_info(release_id, resign_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.devices_getReleaseUpdateDevicesStatus_with_http_info(release_id, resign_id, owner_name, app_name, **kwargs) # noqa: E501 return data def devices_getReleaseUpdateDevicesStatus_with_http_info(self, release_id, resign_id, owner_name, app_name, **kwargs): # noqa: E501 """devices_getReleaseUpdateDevicesStatus # noqa: E501 Returns the resign status to the caller # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_getReleaseUpdateDevicesStatus_with_http_info(release_id, resign_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string release_id: The ID of the release. (required) :param string resign_id: The ID of the resign operation. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean include_provisioning_profile: A boolean value that indicates if the provisioning profile should be return in addition to the status. When set to true, the provisioning profile will be returned only when status is 'complete' or 'preparing_for_testers'.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'resign_id', 'owner_name', 'app_name', 'include_provisioning_profile'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_getReleaseUpdateDevicesStatus" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `devices_getReleaseUpdateDevicesStatus`") # noqa: E501 # verify the required parameter 'resign_id' is set if ('resign_id' not in params or params['resign_id'] is None): raise ValueError("Missing the required parameter `resign_id` when calling `devices_getReleaseUpdateDevicesStatus`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `devices_getReleaseUpdateDevicesStatus`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `devices_getReleaseUpdateDevicesStatus`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'resign_id' in params: path_params['resign_id'] = params['resign_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] if 'include_provisioning_profile' in params: query_params.append(('include_provisioning_profile', params['include_provisioning_profile'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/update_devices/{resign_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_putDistributionTester(self, release_id, tester_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_putDistributionTester # noqa: E501 Update details about the specified tester associated with the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_putDistributionTester(release_id, tester_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string tester_id: The id of the tester (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body:(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_putDistributionTester_with_http_info(release_id, tester_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_putDistributionTester_with_http_info(release_id, tester_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_putDistributionTester_with_http_info(self, release_id, tester_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_putDistributionTester # noqa: E501 Update details about the specified tester associated with the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_putDistributionTester_with_http_info(release_id, tester_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string tester_id: The id of the tester (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body:(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'tester_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_putDistributionTester" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_putDistributionTester`") # noqa: E501 # verify the required parameter 'tester_id' is set if ('tester_id' not in params or params['tester_id'] is None): raise ValueError("Missing the required parameter `tester_id` when calling `releases_putDistributionTester`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_putDistributionTester`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_putDistributionTester`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'tester_id' in params: path_params['tester_id'] = params['tester_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/testers/{tester_id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_deleteDistributionTester(self, release_id, tester_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_deleteDistributionTester # noqa: E501 Delete the given tester from the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteDistributionTester(release_id, tester_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string tester_id: The id of the tester (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_deleteDistributionTester_with_http_info(release_id, tester_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_deleteDistributionTester_with_http_info(release_id, tester_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_deleteDistributionTester_with_http_info(self, release_id, tester_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_deleteDistributionTester # noqa: E501 Delete the given tester from the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteDistributionTester_with_http_info(release_id, tester_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string tester_id: The id of the tester (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'tester_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_deleteDistributionTester" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_deleteDistributionTester`") # noqa: E501 # verify the required parameter 'tester_id' is set if ('tester_id' not in params or params['tester_id'] is None): raise ValueError("Missing the required parameter `tester_id` when calling `releases_deleteDistributionTester`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_deleteDistributionTester`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_deleteDistributionTester`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'tester_id' in params: path_params['tester_id'] = params['tester_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/testers/{tester_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_addTesters(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_addTesters # noqa: E501 Distributes a release to a user # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_addTesters(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_addTesters_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releases_addTesters_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 return data def releases_addTesters_with_http_info(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_addTesters # noqa: E501 Distributes a release to a user # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_addTesters_with_http_info(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_addTesters" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_addTesters`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_addTesters`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_addTesters`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releases_addTesters`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/testers', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_deleteDistributionStore(self, release_id, store_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_deleteDistributionStore # noqa: E501 Delete the given distribution store from the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteDistributionStore(release_id, store_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string store_id: The id of the distribution store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_deleteDistributionStore_with_http_info(release_id, store_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_deleteDistributionStore_with_http_info(release_id, store_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_deleteDistributionStore_with_http_info(self, release_id, store_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_deleteDistributionStore # noqa: E501 Delete the given distribution store from the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteDistributionStore_with_http_info(release_id, store_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string store_id: The id of the distribution store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'store_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_deleteDistributionStore" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_deleteDistributionStore`") # noqa: E501 # verify the required parameter 'store_id' is set if ('store_id' not in params or params['store_id'] is None): raise ValueError("Missing the required parameter `store_id` when calling `releases_deleteDistributionStore`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_deleteDistributionStore`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_deleteDistributionStore`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'store_id' in params: path_params['store_id'] = params['store_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/stores/{store_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_addStore(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_addStore # noqa: E501 Distributes a release to a store # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_addStore(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_addStore_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releases_addStore_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 return data def releases_addStore_with_http_info(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_addStore # noqa: E501 Distributes a release to a store # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_addStore_with_http_info(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_addStore" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_addStore`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_addStore`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_addStore`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releases_addStore`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/stores', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def provisioning_profile(self, release_id, owner_name, app_name, **kwargs): # noqa: E501 """provisioning_profile # noqa: E501 Return information about the provisioning profile. Only available for iOS. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.provisioning_profile(release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The release_id (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.provisioning_profile_with_http_info(release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.provisioning_profile_with_http_info(release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def provisioning_profile_with_http_info(self, release_id, owner_name, app_name, **kwargs): # noqa: E501 """provisioning_profile # noqa: E501 Return information about the provisioning profile. Only available for iOS. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.provisioning_profile_with_http_info(release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The release_id (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method provisioning_profile" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `provisioning_profile`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `provisioning_profile`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `provisioning_profile`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/provisioning_profile', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_putDistributionGroup(self, release_id, group_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_putDistributionGroup # noqa: E501 Update details about the specified distribution group associated with the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_putDistributionGroup(release_id, group_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string group_id: The id of the releases destination (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body:(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_putDistributionGroup_with_http_info(release_id, group_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_putDistributionGroup_with_http_info(release_id, group_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_putDistributionGroup_with_http_info(self, release_id, group_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_putDistributionGroup # noqa: E501 Update details about the specified distribution group associated with the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_putDistributionGroup_with_http_info(release_id, group_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string group_id: The id of the releases destination (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body:(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'group_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_putDistributionGroup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_putDistributionGroup`") # noqa: E501 # verify the required parameter 'group_id' is set if ('group_id' not in params or params['group_id'] is None): raise ValueError("Missing the required parameter `group_id` when calling `releases_putDistributionGroup`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_putDistributionGroup`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_putDistributionGroup`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'group_id' in params: path_params['group_id'] = params['group_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/groups/{group_id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_deleteDistributionGroup(self, release_id, group_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_deleteDistributionGroup # noqa: E501 Delete the given distribution group from the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteDistributionGroup(release_id, group_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string group_id: The id of the distribution group (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_deleteDistributionGroup_with_http_info(release_id, group_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_deleteDistributionGroup_with_http_info(release_id, group_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_deleteDistributionGroup_with_http_info(self, release_id, group_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_deleteDistributionGroup # noqa: E501 Delete the given distribution group from the release # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteDistributionGroup_with_http_info(release_id, group_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string group_id: The id of the distribution group (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'group_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_deleteDistributionGroup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_deleteDistributionGroup`") # noqa: E501 # verify the required parameter 'group_id' is set if ('group_id' not in params or params['group_id'] is None): raise ValueError("Missing the required parameter `group_id` when calling `releases_deleteDistributionGroup`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_deleteDistributionGroup`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_deleteDistributionGroup`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'group_id' in params: path_params['group_id'] = params['group_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/groups/{group_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_addDistributionGroup(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_addDistributionGroup # noqa: E501 Distributes a release to a group # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_addDistributionGroup(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_addDistributionGroup_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releases_addDistributionGroup_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 return data def releases_addDistributionGroup_with_http_info(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_addDistributionGroup # noqa: E501 Distributes a release to a group # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_addDistributionGroup_with_http_info(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_addDistributionGroup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_addDistributionGroup`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_addDistributionGroup`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_addDistributionGroup`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releases_addDistributionGroup`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}/groups', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_getLatestByUser(self, release_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_getLatestByUser # noqa: E501 Get a release with id `release_id`. If `release_id` is `latest`, return the latest release that was distributed to the current user (from all the distribution groups). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByUser(release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string release_id: The ID of the release, or `latest` to get the latest release from all the distribution groups assigned to the current user. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param string udid: when supplied, this call will also check if the given UDID is provisioned. Will be ignored for non-iOS platforms. The value will be returned in the property is_udid_provisioned.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_getLatestByUser_with_http_info(release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_getLatestByUser_with_http_info(release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_getLatestByUser_with_http_info(self, release_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_getLatestByUser # noqa: E501 Get a release with id `release_id`. If `release_id` is `latest`, return the latest release that was distributed to the current user (from all the distribution groups). # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByUser_with_http_info(release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string release_id: The ID of the release, or `latest` to get the latest release from all the distribution groups assigned to the current user. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param string udid: when supplied, this call will also check if the given UDID is provisioned. Will be ignored for non-iOS platforms. The value will be returned in the property is_udid_provisioned.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name', 'udid'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_getLatestByUser" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_getLatestByUser`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_getLatestByUser`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_getLatestByUser`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] if 'udid' in params: query_params.append(('udid', params['udid'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_updateDetails(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_updateDetails # noqa: E501 Update details of a release. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_updateDetails(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_updateDetails_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releases_updateDetails_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 return data def releases_updateDetails_with_http_info(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_updateDetails # noqa: E501 Update details of a release. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_updateDetails_with_http_info(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_updateDetails" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_updateDetails`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_updateDetails`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_updateDetails`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releases_updateDetails`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}', 'PUT', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_update(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_update # noqa: E501 Updates a release. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_update(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_update_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releases_update_with_http_info(release_id, owner_name, app_name, body, **kwargs) # noqa: E501 return data def releases_update_with_http_info(self, release_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releases_update # noqa: E501 Updates a release. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_update_with_http_info(release_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_update" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_update`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_update`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_update`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releases_update`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_delete(self, release_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_delete # noqa: E501 Deletes a release. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_delete(release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_delete_with_http_info(release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_delete_with_http_info(release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_delete_with_http_info(self, release_id, owner_name, app_name, **kwargs): # noqa: E501 """releases_delete # noqa: E501 Deletes a release. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_delete_with_http_info(release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param integer release_id: The ID of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_delete`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_delete`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/{release_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_availableToTester(self, owner_name, app_name, **kwargs): # noqa: E501 """releases_availableToTester # noqa: E501 Return detailed information about releases avaiable to a tester. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_availableToTester(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean published_only: when *true*, filters out releases that were uploaded but were never distributed. Releases that under deleted distribution groups will not be filtered out.(optional) :return: array If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_availableToTester_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_availableToTester_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def releases_availableToTester_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """releases_availableToTester # noqa: E501 Return detailed information about releases avaiable to a tester. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_availableToTester_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean published_only: when *true*, filters out releases that were uploaded but were never distributed. Releases that under deleted distribution groups will not be filtered out.(optional) :return: array If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'published_only'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_availableToTester" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_availableToTester`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_availableToTester`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] if 'published_only' in params: query_params.append(('published_only', params['published_only'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases/filter_by_tester', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='array', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_list(self, owner_name, app_name, **kwargs): # noqa: E501 """releases_list # noqa: E501 Return basic information about releases. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_list(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean published_only: When *true*, filters out releases that were uploaded but were never distributed. Releases that under deleted distribution groups will not be filtered out.(optional) :param string scope: When the scope is 'tester', only includes releases that have been distributed to groups that the user belongs to.(optional) :return: array If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_list_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_list_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def releases_list_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """releases_list # noqa: E501 Return basic information about releases. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_list_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean published_only: When *true*, filters out releases that were uploaded but were never distributed. Releases that under deleted distribution groups will not be filtered out.(optional) :param string scope: When the scope is 'tester', only includes releases that have been distributed to groups that the user belongs to.(optional) :return: array If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'published_only', 'scope'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_list" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_list`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_list`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] if 'published_only' in params: query_params.append(('published_only', params['published_only'])) # noqa: E501 if 'scope' in params: query_params.append(('scope', params['scope'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/releases', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='array', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releaseUploads_complete(self, upload_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releaseUploads_complete # noqa: E501 Commits or aborts the upload process for a release for the specified application # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releaseUploads_complete(upload_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string upload_id: The ID of the upload (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information (required) :return: ReleaseUploadEndResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releaseUploads_complete_with_http_info(upload_id, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releaseUploads_complete_with_http_info(upload_id, owner_name, app_name, body, **kwargs) # noqa: E501 return data def releaseUploads_complete_with_http_info(self, upload_id, owner_name, app_name, body, **kwargs): # noqa: E501 """releaseUploads_complete # noqa: E501 Commits or aborts the upload process for a release for the specified application # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releaseUploads_complete_with_http_info(upload_id, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string upload_id: The ID of the upload (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information (required) :return: ReleaseUploadEndResponse If the method is called asynchronously, returns the request thread. """ all_params = ['upload_id', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releaseUploads_complete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'upload_id' is set if ('upload_id' not in params or params['upload_id'] is None): raise ValueError("Missing the required parameter `upload_id` when calling `releaseUploads_complete`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releaseUploads_complete`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releaseUploads_complete`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releaseUploads_complete`") # noqa: E501 collection_formats = {} path_params = {} if 'upload_id' in params: path_params['upload_id'] = params['upload_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/release_uploads/{upload_id}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ReleaseUploadEndResponse', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releaseUploads_create(self, owner_name, app_name, body, **kwargs): # noqa: E501 """releaseUploads_create # noqa: E501 Begins the upload process for a new release for the specified application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releaseUploads_create(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information (required) :return: ReleaseUploadBeginResponse If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releaseUploads_create_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.releaseUploads_create_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 return data def releaseUploads_create_with_http_info(self, owner_name, app_name, body, **kwargs): # noqa: E501 """releaseUploads_create # noqa: E501 Begins the upload process for a new release for the specified application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releaseUploads_create_with_http_info(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The release information (required) :return: ReleaseUploadBeginResponse If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releaseUploads_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releaseUploads_create`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releaseUploads_create`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `releaseUploads_create`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/release_uploads', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ReleaseUploadBeginResponse', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_listLatest(self, owner_name, app_name, **kwargs): # noqa: E501 """releases_listLatest # noqa: E501 Get the latest release from every distribution group associated with an application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_listLatest(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: array If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_listLatest_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_listLatest_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def releases_listLatest_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """releases_listLatest # noqa: E501 Get the latest release from every distribution group associated with an application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_listLatest_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: array If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_listLatest" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_listLatest`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_listLatest`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/recent_releases', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='array', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleases_getRealTimeStatusByReleaseId(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_getRealTimeStatusByReleaseId # noqa: E501 Return the Real time Status publishing of release from store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_getRealTimeStatusByReleaseId(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param number release_id: The id of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleases_getRealTimeStatusByReleaseId_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleases_getRealTimeStatusByReleaseId_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleases_getRealTimeStatusByReleaseId_with_http_info(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_getRealTimeStatusByReleaseId # noqa: E501 Return the Real time Status publishing of release from store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_getRealTimeStatusByReleaseId_with_http_info(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param number release_id: The id of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleases_getRealTimeStatusByReleaseId" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleases_getRealTimeStatusByReleaseId`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `storeReleases_getRealTimeStatusByReleaseId`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleases_getRealTimeStatusByReleaseId`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleases_getRealTimeStatusByReleaseId`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/releases/{release_id}/realtimestatus', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleasePublishLogs_get(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleasePublishLogs_get # noqa: E501 Returns publish logs for a particular release published to a particular store # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleasePublishLogs_get(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string release_id: The ID of the realease (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleasePublishLogs_get_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleasePublishLogs_get_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleasePublishLogs_get_with_http_info(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleasePublishLogs_get # noqa: E501 Returns publish logs for a particular release published to a particular store # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleasePublishLogs_get_with_http_info(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string release_id: The ID of the realease (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleasePublishLogs_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleasePublishLogs_get`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `storeReleasePublishLogs_get`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleasePublishLogs_get`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleasePublishLogs_get`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/releases/{release_id}/publish_logs', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleases_getPublishError(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_getPublishError # noqa: E501 Return the Error Details of release which failed in publishing. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_getPublishError(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param number release_id: The id of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleases_getPublishError_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleases_getPublishError_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleases_getPublishError_with_http_info(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_getPublishError # noqa: E501 Return the Error Details of release which failed in publishing. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_getPublishError_with_http_info(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param number release_id: The id of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleases_getPublishError" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleases_getPublishError`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `storeReleases_getPublishError`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleases_getPublishError`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleases_getPublishError`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/releases/{release_id}/publish_error_details', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleases_get(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_get # noqa: E501 Return releases published in a store for releaseId and storeId # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_get(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string release_id: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleases_get_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleases_get_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleases_get_with_http_info(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_get # noqa: E501 Return releases published in a store for releaseId and storeId # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_get_with_http_info(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string release_id: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleases_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleases_get`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `storeReleases_get`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleases_get`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleases_get`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/releases/{release_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleases_delete(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_delete # noqa: E501 delete the release with release Id # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_delete(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string release_id: The id of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleases_delete_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleases_delete_with_http_info(store_name, release_id, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleases_delete_with_http_info(self, store_name, release_id, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_delete # noqa: E501 delete the release with release Id # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_delete_with_http_info(store_name, release_id, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string release_id: The id of the release (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'release_id', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleases_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleases_delete`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `storeReleases_delete`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleases_delete`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleases_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/releases/{release_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleases_list(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_list # noqa: E501 Return all releases published in a store # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_list(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleases_list_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleases_list_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleases_list_with_http_info(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_list # noqa: E501 Return all releases published in a store # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_list_with_http_info(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleases_list" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleases_list`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleases_list`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleases_list`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/releases', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def storeReleases_getLatest(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_getLatest # noqa: E501 Returns the latest release published in a store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_getLatest(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.storeReleases_getLatest_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.storeReleases_getLatest_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 return data def storeReleases_getLatest_with_http_info(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """storeReleases_getLatest # noqa: E501 Returns the latest release published in a store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.storeReleases_getLatest_with_http_info(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method storeReleases_getLatest" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `storeReleases_getLatest`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `storeReleases_getLatest`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `storeReleases_getLatest`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}/latest_release', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def stores_get(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """stores_get # noqa: E501 Return the store details for specified store name. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_get(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.stores_get_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.stores_get_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 return data def stores_get_with_http_info(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """stores_get # noqa: E501 Return the store details for specified store name. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_get_with_http_info(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method stores_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `stores_get`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `stores_get`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `stores_get`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def stores_patch(self, store_name, owner_name, app_name, body, **kwargs): # noqa: E501 """stores_patch # noqa: E501 Update the store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_patch(store_name, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: Store update request (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.stores_patch_with_http_info(store_name, owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.stores_patch_with_http_info(store_name, owner_name, app_name, body, **kwargs) # noqa: E501 return data def stores_patch_with_http_info(self, store_name, owner_name, app_name, body, **kwargs): # noqa: E501 """stores_patch # noqa: E501 Update the store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_patch_with_http_info(store_name, owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: Store update request (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method stores_patch" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `stores_patch`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `stores_patch`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `stores_patch`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `stores_patch`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}', 'PATCH', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def stores_delete(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """stores_delete # noqa: E501 delete the store based on specific store name. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_delete(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.stores_delete_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.stores_delete_with_http_info(store_name, owner_name, app_name, **kwargs) # noqa: E501 return data def stores_delete_with_http_info(self, store_name, owner_name, app_name, **kwargs): # noqa: E501 """stores_delete # noqa: E501 delete the store based on specific store name. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_delete_with_http_info(store_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string store_name: The name of the store (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['store_name', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method stores_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'store_name' is set if ('store_name' not in params or params['store_name'] is None): raise ValueError("Missing the required parameter `store_name` when calling `stores_delete`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `stores_delete`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `stores_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'store_name' in params: path_params['store_name'] = params['store_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores/{store_name}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def stores_create(self, owner_name, app_name, body, **kwargs): # noqa: E501 """stores_create # noqa: E501 Create a new external store for the specified application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_create(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The store request (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.stores_create_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.stores_create_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 return data def stores_create_with_http_info(self, owner_name, app_name, body, **kwargs): # noqa: E501 """stores_create # noqa: E501 Create a new external store for the specified application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_create_with_http_info(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The store request (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method stores_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `stores_create`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `stores_create`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `stores_create`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def stores_list(self, owner_name, app_name, **kwargs): # noqa: E501 """stores_list # noqa: E501 Get all the store details from Storage store table for a particular application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_list(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: array If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.stores_list_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.stores_list_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def stores_list_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """stores_list # noqa: E501 Get all the store details from Storage store table for a particular application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.stores_list_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: array If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method stores_list" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `stores_list`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `stores_list`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_stores', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='array', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_getLatestByDistributionGroup(self, owner_name, app_name, distribution_group_name, release_id, **kwargs): # noqa: E501 """releases_getLatestByDistributionGroup # noqa: E501 Return detailed information about a distributed release in a given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByDistributionGroup(owner_name, app_name, distribution_group_name, release_id, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the app owner (required) :param string app_name: The name of the app (required) :param string distribution_group_name: The name of the distribution group. (required) :param string release_id: Only supports the constant `latest`, specific IDs are not supported. `latest` will return the latest release in the distribution group. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_getLatestByDistributionGroup_with_http_info(owner_name, app_name, distribution_group_name, release_id, **kwargs) # noqa: E501 else: (data) = self.releases_getLatestByDistributionGroup_with_http_info(owner_name, app_name, distribution_group_name, release_id, **kwargs) # noqa: E501 return data def releases_getLatestByDistributionGroup_with_http_info(self, owner_name, app_name, distribution_group_name, release_id, **kwargs): # noqa: E501 """releases_getLatestByDistributionGroup # noqa: E501 Return detailed information about a distributed release in a given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_getLatestByDistributionGroup_with_http_info(owner_name, app_name, distribution_group_name, release_id, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the app owner (required) :param string app_name: The name of the app (required) :param string distribution_group_name: The name of the distribution group. (required) :param string release_id: Only supports the constant `latest`, specific IDs are not supported. `latest` will return the latest release in the distribution group. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'distribution_group_name', 'release_id'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_getLatestByDistributionGroup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_getLatestByDistributionGroup`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_getLatestByDistributionGroup`") # noqa: E501 # verify the required parameter 'distribution_group_name' is set if ('distribution_group_name' not in params or params['distribution_group_name'] is None): raise ValueError("Missing the required parameter `distribution_group_name` when calling `releases_getLatestByDistributionGroup`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_getLatestByDistributionGroup`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 if 'distribution_group_name' in params: path_params['distribution_group_name'] = params['distribution_group_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_groups/{distribution_group_name}/releases/{release_id}', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_deleteWithDistributionGroupId(self, owner_name, app_name, distribution_group_name, release_id, **kwargs): # noqa: E501 """releases_deleteWithDistributionGroupId # noqa: E501 Deletes a release with id 'release_id' in a given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteWithDistributionGroupId(owner_name, app_name, distribution_group_name, release_id, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the app owner (required) :param string app_name: The name of the app (required) :param string distribution_group_name: The name of the distribution group. (required) :param integer release_id: The ID identifying the unique release. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_deleteWithDistributionGroupId_with_http_info(owner_name, app_name, distribution_group_name, release_id, **kwargs) # noqa: E501 else: (data) = self.releases_deleteWithDistributionGroupId_with_http_info(owner_name, app_name, distribution_group_name, release_id, **kwargs) # noqa: E501 return data def releases_deleteWithDistributionGroupId_with_http_info(self, owner_name, app_name, distribution_group_name, release_id, **kwargs): # noqa: E501 """releases_deleteWithDistributionGroupId # noqa: E501 Deletes a release with id 'release_id' in a given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_deleteWithDistributionGroupId_with_http_info(owner_name, app_name, distribution_group_name, release_id, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the app owner (required) :param string app_name: The name of the app (required) :param string distribution_group_name: The name of the distribution group. (required) :param integer release_id: The ID identifying the unique release. (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'distribution_group_name', 'release_id'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_deleteWithDistributionGroupId" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_deleteWithDistributionGroupId`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_deleteWithDistributionGroupId`") # noqa: E501 # verify the required parameter 'distribution_group_name' is set if ('distribution_group_name' not in params or params['distribution_group_name'] is None): raise ValueError("Missing the required parameter `distribution_group_name` when calling `releases_deleteWithDistributionGroupId`") # noqa: E501 # verify the required parameter 'release_id' is set if ('release_id' not in params or params['release_id'] is None): raise ValueError("Missing the required parameter `release_id` when calling `releases_deleteWithDistributionGroupId`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 if 'distribution_group_name' in params: path_params['distribution_group_name'] = params['distribution_group_name'] # noqa: E501 if 'release_id' in params: path_params['release_id'] = params['release_id'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_groups/{distribution_group_name}/releases/{release_id}', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def releases_listByDistributionGroup(self, distribution_group_name, owner_name, app_name, **kwargs): # noqa: E501 """releases_listByDistributionGroup # noqa: E501 Return basic information about distributed releases in a given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_listByDistributionGroup(distribution_group_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string distribution_group_name: The name of the distribution group. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.releases_listByDistributionGroup_with_http_info(distribution_group_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.releases_listByDistributionGroup_with_http_info(distribution_group_name, owner_name, app_name, **kwargs) # noqa: E501 return data def releases_listByDistributionGroup_with_http_info(self, distribution_group_name, owner_name, app_name, **kwargs): # noqa: E501 """releases_listByDistributionGroup # noqa: E501 Return basic information about distributed releases in a given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.releases_listByDistributionGroup_with_http_info(distribution_group_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string distribution_group_name: The name of the distribution group. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['distribution_group_name', 'owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method releases_listByDistributionGroup" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'distribution_group_name' is set if ('distribution_group_name' not in params or params['distribution_group_name'] is None): raise ValueError("Missing the required parameter `distribution_group_name` when calling `releases_listByDistributionGroup`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `releases_listByDistributionGroup`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `releases_listByDistributionGroup`") # noqa: E501 collection_formats = {} path_params = {} if 'distribution_group_name' in params: path_params['distribution_group_name'] = params['distribution_group_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_groups/{distribution_group_name}/releases', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def devices_listCsvFormat(self, distribution_group_name, owner_name, app_name, **kwargs): # noqa: E501 """devices_listCsvFormat # noqa: E501 Returns all devices associated with the given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_listCsvFormat(distribution_group_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string distribution_group_name: The name of the distribution group. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean unprovisioned_only: when true, filters out provisioned devices(optional) :param array udids: multiple UDIDs which should be part of the resulting CSV.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_listCsvFormat_with_http_info(distribution_group_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.devices_listCsvFormat_with_http_info(distribution_group_name, owner_name, app_name, **kwargs) # noqa: E501 return data def devices_listCsvFormat_with_http_info(self, distribution_group_name, owner_name, app_name, **kwargs): # noqa: E501 """devices_listCsvFormat # noqa: E501 Returns all devices associated with the given distribution group. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_listCsvFormat_with_http_info(distribution_group_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string distribution_group_name: The name of the distribution group. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param boolean unprovisioned_only: when true, filters out provisioned devices(optional) :param array udids: multiple UDIDs which should be part of the resulting CSV.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['distribution_group_name', 'owner_name', 'app_name', 'unprovisioned_only', 'udids'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_listCsvFormat" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'distribution_group_name' is set if ('distribution_group_name' not in params or params['distribution_group_name'] is None): raise ValueError("Missing the required parameter `distribution_group_name` when calling `devices_listCsvFormat`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `devices_listCsvFormat`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `devices_listCsvFormat`") # noqa: E501 collection_formats = {} path_params = {} if 'distribution_group_name' in params: path_params['distribution_group_name'] = params['distribution_group_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] if 'unprovisioned_only' in params: query_params.append(('unprovisioned_only', params['unprovisioned_only'])) # noqa: E501 if 'udids' in params: query_params.append(('udids', params['udids'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['text/csv', 'text/csv', 'text/csv']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_groups/{distribution_group_name}/devices/download_devices_list', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def devices_list(self, distribution_group_name, owner_name, app_name, **kwargs): # noqa: E501 """devices_list # noqa: E501 Returns all devices associated with the given distribution group # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_list(distribution_group_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string distribution_group_name: The name of the distribution group. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param number release_id: when provided, gets the provisioning state of the devices owned by users of this distribution group when compared to the provided release.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.devices_list_with_http_info(distribution_group_name, owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.devices_list_with_http_info(distribution_group_name, owner_name, app_name, **kwargs) # noqa: E501 return data def devices_list_with_http_info(self, distribution_group_name, owner_name, app_name, **kwargs): # noqa: E501 """devices_list # noqa: E501 Returns all devices associated with the given distribution group # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.devices_list_with_http_info(distribution_group_name, owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string distribution_group_name: The name of the distribution group. (required) :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param number release_id: when provided, gets the provisioning state of the devices owned by users of this distribution group when compared to the provided release.(optional) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['distribution_group_name', 'owner_name', 'app_name', 'release_id'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method devices_list" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'distribution_group_name' is set if ('distribution_group_name' not in params or params['distribution_group_name'] is None): raise ValueError("Missing the required parameter `distribution_group_name` when calling `devices_list`") # noqa: E501 # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `devices_list`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `devices_list`") # noqa: E501 collection_formats = {} path_params = {} if 'distribution_group_name' in params: path_params['distribution_group_name'] = params['distribution_group_name'] # noqa: E501 if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] if 'release_id' in params: query_params.append(('release_id', params['release_id'])) # noqa: E501 header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/distribution_groups/{distribution_group_name}/devices', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def appleMapping_TestFlightGroups(self, owner_name, app_name, **kwargs): # noqa: E501 """appleMapping_TestFlightGroups # noqa: E501 Fetch all apple test flight groups # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_TestFlightGroups(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.appleMapping_TestFlightGroups_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.appleMapping_TestFlightGroups_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def appleMapping_TestFlightGroups_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """appleMapping_TestFlightGroups # noqa: E501 Fetch all apple test flight groups # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_TestFlightGroups_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method appleMapping_TestFlightGroups" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `appleMapping_TestFlightGroups`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `appleMapping_TestFlightGroups`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/apple_test_flight_groups', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def appleMapping_get(self, owner_name, app_name, **kwargs): # noqa: E501 """appleMapping_get # noqa: E501 Get mapping of apple app to an existing app in apple store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_get(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.appleMapping_get_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.appleMapping_get_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def appleMapping_get_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """appleMapping_get # noqa: E501 Get mapping of apple app to an existing app in apple store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_get_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method appleMapping_get" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `appleMapping_get`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `appleMapping_get`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/apple_mapping', 'GET', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def appleMapping_delete(self, owner_name, app_name, **kwargs): # noqa: E501 """appleMapping_delete # noqa: E501 Delete mapping of apple app to an existing app in apple store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_delete(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.appleMapping_delete_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 else: (data) = self.appleMapping_delete_with_http_info(owner_name, app_name, **kwargs) # noqa: E501 return data def appleMapping_delete_with_http_info(self, owner_name, app_name, **kwargs): # noqa: E501 """appleMapping_delete # noqa: E501 Delete mapping of apple app to an existing app in apple store. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_delete_with_http_info(owner_name, app_name, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method appleMapping_delete" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `appleMapping_delete`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `appleMapping_delete`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json', 'multipart/form-data', 'application/json-patch+json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/apple_mapping', 'DELETE', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats) def appleMapping_create(self, owner_name, app_name, body, **kwargs): # noqa: E501 """appleMapping_create # noqa: E501 Create a mapping for an existing app in apple store for the specified application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_create(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The apple app mapping object (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ kwargs['_return_http_data_only'] = True if kwargs.get('async'): return self.appleMapping_create_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 else: (data) = self.appleMapping_create_with_http_info(owner_name, app_name, body, **kwargs) # noqa: E501 return data def appleMapping_create_with_http_info(self, owner_name, app_name, body, **kwargs): # noqa: E501 """appleMapping_create # noqa: E501 Create a mapping for an existing app in apple store for the specified application. # noqa: E501 This method makes a synchronous HTTP request by default. To make an asynchronous HTTP request, please pass async=True >>> thread = api.appleMapping_create_with_http_info(owner_name, app_name, body, async=True) >>> result = thread.get() :param async bool :param string owner_name: The name of the owner (required) :param string app_name: The name of the application (required) :param object body: The apple app mapping object (required) :return: ErrorDetails If the method is called asynchronously, returns the request thread. """ all_params = ['owner_name', 'app_name', 'body'] # noqa: E501 all_params.append('async') all_params.append('_return_http_data_only') all_params.append('_preload_content') all_params.append('_request_timeout') params = locals() for key, val in six.iteritems(params['kwargs']): if key not in all_params: raise TypeError( "Got an unexpected keyword argument '%s'" " to method appleMapping_create" % key ) params[key] = val del params['kwargs'] # verify the required parameter 'owner_name' is set if ('owner_name' not in params or params['owner_name'] is None): raise ValueError("Missing the required parameter `owner_name` when calling `appleMapping_create`") # noqa: E501 # verify the required parameter 'app_name' is set if ('app_name' not in params or params['app_name'] is None): raise ValueError("Missing the required parameter `app_name` when calling `appleMapping_create`") # noqa: E501 # verify the required parameter 'body' is set if ('body' not in params or params['body'] is None): raise ValueError("Missing the required parameter `body` when calling `appleMapping_create`") # noqa: E501 collection_formats = {} path_params = {} if 'owner_name' in params: path_params['owner_name'] = params['owner_name'] # noqa: E501 if 'app_name' in params: path_params['app_name'] = params['app_name'] # noqa: E501 query_params = [] header_params = {} form_params = [] local_var_files = {} body_params = None if 'body' in params: body_params = params['body'] # HTTP header `Accept` header_params['Accept'] = self.api_client.select_header_accept( ['application/json', 'application/json']) # noqa: E501 # HTTP header `Content-Type` header_params['Content-Type'] = self.api_client.select_header_content_type( # noqa: E501 ['application/json']) # noqa: E501 # Authentication setting auth_settings = ['APIToken'] # noqa: E501 return self.api_client.call_api( '/v0.1/apps/{owner_name}/{app_name}/apple_mapping', 'POST', path_params, query_params, header_params, body=body_params, post_params=form_params, files=local_var_files, response_type='ErrorDetails', # noqa: E501 auth_settings=auth_settings, async=params.get('async'), _return_http_data_only=params.get('_return_http_data_only'), _preload_content=params.get('_preload_content', True), _request_timeout=params.get('_request_timeout'), collection_formats=collection_formats)

46.345533

284

0.631941

31,520

269,731

5.178236

0.011643

0.048818

0.024703

0.032938

0.982251

0.974837

0.970616

0.9658

0.964379

0.960948

0

0.0159

0.27834

269,731

5,819

285

46.353497

0.822603

0.073091

0

0.822691

0

0.25125

0.0771

0

null

0

0.00124

null

0

null

0

1

0

1

0

null

0

1

0

8

9a484625217b2e19f2b921f43140968c07ba23eb

84

py

Python

examples/get_appeal_status_example.py

KristN1/cube_appeals

f81503ee665d6a69f3a5b06a69bddb020194f713

[ "MIT" ]

null

examples/get_appeal_status_example.py

KristN1/cube_appeals

f81503ee665d6a69f3a5b06a69bddb020194f713

[ "MIT" ]

null

examples/get_appeal_status_example.py

KristN1/cube_appeals

f81503ee665d6a69f3a5b06a69bddb020194f713

[ "MIT" ]

null

from cube_appeals import get_appeal_status print(get_appeal_status.java("Jukaido"))

28

42

0.857143

13

84

5.153846

0.769231

0.268657

0.447761

0

0.059524

84

3

43

28

0.848101

0

0.082353

0

1

0

true

0

0.5

0

0.5

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

7beef99b61677bcc7028eebfa0f76c49efa1e5cd

7,984

py

Python

src/system_of_equations/factorization.py

jestra52/supor-numerical-analysis-api

3cebc86cf2bba95789de1cb45232aaad182f332f

[ "MIT" ]

1

2020-06-09T17:18:01.000Z

src/system_of_equations/factorization.py

jestra52/supor-numerical-analysis-api

3cebc86cf2bba95789de1cb45232aaad182f332f

[ "MIT" ]

null

src/system_of_equations/factorization.py

jestra52/supor-numerical-analysis-api

3cebc86cf2bba95789de1cb45232aaad182f332f

[ "MIT" ]

null

import copy as cp import math as mt import numpy as np import threading class Factorization: def cholesky(self, A, b): result = { 'aMatrix': None, 'bMatrix': None, 'lMatrix': None, 'uMatrix': None, 'xMatrix': None, 'iterations': None, 'hasInfiniteSolutions': False, 'resultMessage': None, 'solutionFailed': False, 'error': False, 'errorMessage': None } n = len(A) L = np.zeros((n, n)) U = np.zeros((n, n)) phases = list() def diagonal_operation_async(k): incr = 0 for p in range(0, k): incr += L[k][p] * U[p][k] L[k][k] = mt.sqrt(A[k][k] - incr) U[k][k] = L[k][k] def row_operation_async(k, i): incr = 0 for r in range(0, k): incr += L[i][r] * U[r][k] L[i][k] = (A[i][k] - incr) / L[k][k] def column_operation_async(k, j): incr = 0 for s in range(0, k): incr += L[k][s] * U[s][j] U[k][j] = (A[k][j] - incr) / L[k][k] for k in range(0, n): thread = threading.Thread(target=diagonal_operation_async, args=([k])) thread.start() thread.join() if L[k][k] == 0: raise ZeroDivisionError threads = list() for i in range(k+1, n): thread = threading.Thread(target=row_operation_async, args=(k, i)) threads.append(thread) thread.start() for thread in threads: thread.join() threads.clear() for j in range(k+1, n): thread = threading.Thread(target=column_operation_async, args=(k, j)) threads.append(thread) thread.start() for thread in threads: thread.join() if k < n - 1: iteration = { 'lMatrix': list(map(lambda l: list(l), cp.deepcopy(L))), 'uMatrix': list(map(lambda u: list(u), cp.deepcopy(U))), } phases.append(cp.deepcopy(iteration)) if not result['error']: result['aMatrix'] = A result['bMatrix'] = b result['lMatrix'] = L result['uMatrix'] = U result['xMatrix'] = self.solve_x(L, U, b) result['iterations'] = phases return result def doolittle(self, A, b): result = { 'aMatrix': None, 'bMatrix': None, 'lMatrix': None, 'uMatrix': None, 'xMatrix': None, 'iterations': None, 'hasInfiniteSolutions': False, 'resultMessage': None, 'solutionFailed': False, 'error': False, 'errorMessage': None } n = len(A) L = np.zeros((n, n)) U = np.zeros((n, n)) phases = list() def column_operation_async(k, j): incr = 0 for p in range(k): incr += L[k][p] * U[p][j] U[k][j] = (A[k][j] - incr) def row_operation_async(k, i): incr = 0 for r in range(k): incr += L[i][r] * U[r][k] L[i][k] = (A[i][k] - incr) / U[k][k] for k in range(0,n): threads = list() for j in range(k, n): thread = threading.Thread(target=column_operation_async, args=(k, j)) threads.append(thread) thread.start() for thread in threads: thread.join() if U[k][k] == 0: raise ZeroDivisionError threads.clear() for i in range(k, n): thread = threading.Thread(target=row_operation_async, args=(k, i)) threads.append(thread) thread.start() for thread in threads: thread.join() if k < n - 1: iteration = { 'lMatrix': list(map(lambda l: list(l), cp.deepcopy(L))), 'uMatrix': list(map(lambda u: list(u), cp.deepcopy(U))), } phases.append(cp.deepcopy(iteration)) if not result['error']: result['aMatrix'] = A result['bMatrix'] = b result['lMatrix'] = L result['uMatrix'] = U result['xMatrix'] = self.solve_x(L, U, b) result['iterations'] = phases return result def crout(self, A, b): result = { 'aMatrix': None, 'bMatrix': None, 'lMatrix': None, 'uMatrix': None, 'xMatrix': None, 'iterations': None, 'hasInfiniteSolutions': False, 'resultMessage': None, 'solutionFailed': False, 'error': False, 'errorMessage': None } n = len(A) L = np.zeros((n, n)) U = np.zeros((n, n)) phases = list() def row_operation_async(k, i): incr = 0 for p in range(0,k): incr += L[i][p] * U[p][k] L[i][k] = A[i][k] - incr def column_operation_async(k, j): incr = 0 for p in range(0,k): incr += L[k][p] * U[p][j] U[k][j] = (A[k][j] - incr) / L[k][k] for k in range(0, n): threads = list() for i in range(k, n): thread = threading.Thread(target=row_operation_async, args=(k, i)) threads.append(thread) thread.start() for thread in threads: thread.join() if L[k][k] == 0: raise ZeroDivisionError threads.clear() for j in range(k, n): thread = threading.Thread(target=column_operation_async, args=(k, j)) threads.append(thread) thread.start() for thread in threads: thread.join() if k < n - 1: iteration = { 'lMatrix': list(map(lambda l: list(l), cp.deepcopy(L))), 'uMatrix': list(map(lambda u: list(u), cp.deepcopy(U))), } phases.append(cp.deepcopy(iteration)) if not result['error']: result['aMatrix'] = A result['bMatrix'] = b result['lMatrix'] = L result['uMatrix'] = U result['xMatrix'] = self.solve_x(L, U, b) result['iterations'] = phases return result def solve_z(self, L, b): n = len(b) Z = [] for i in range(n): Z.append(0) for i in range(0, n): incr = 0 for p in range(0, i): incr += L[i][p] * Z[p] if L[i][i] == 0: raise ZeroDivisionError Z[i] = (b[i] - incr) / L[i][i] return Z def solve_x(self, L, U, b): n = len(b) Z = self.solve_z(L, b) X = [] for i in range(n): X.append(0) i = n - 1 while i >= 0: incr = 0 for p in range(i+1, n): incr += U[i][p] * X[p] if U[i][i] == 0: raise ZeroDivisionError X[i] = (Z[i] - incr) / U[i][i] i -= 1 return X def get_invertible_matrix(self, L, U): n = len(L) invertible_a = [] for i in range(0, n): b = [] for j in range(0, n): if j == i: b.append(1) else: b.append(0) invertible_a.append(self.solve_x(L, U, b)) return invertible_a

28.312057

85

0.423096

930

7,984

3.589247

0.088172

0.048232

0.02876

0.046135

0.87118

0.832534

0.816058

0.798682

0.782804

0.761833

0

0.008742

0.441258

7,984

281

86

28.412811

0.73952

0

0.732456

0

0.065005

0

1

0.057018

false

0

0.017544

0

0.105263

0

null

0

1

0

1

0

null

0

7

d0004c8e3eb27ae16c6eb46700d72b25a103fcf9

16,124

py

Python

analyze_foldamers/tests/test_rmsd_clustering.py

shirtsgroup/analyze_foldamers

17a7b948d1d0d4fbfb1d84d58753289404fb99a9

[ "MIT" ]

null

analyze_foldamers/tests/test_rmsd_clustering.py

shirtsgroup/analyze_foldamers

17a7b948d1d0d4fbfb1d84d58753289404fb99a9

[ "MIT" ]

33

2020-08-05T23:00:56.000Z

2022-03-21T22:37:03.000Z

analyze_foldamers/tests/test_rmsd_clustering.py

shirtsgroup/analyze_foldamers

17a7b948d1d0d4fbfb1d84d58753289404fb99a9

[ "MIT" ]

null

""" Unit and regression test for the analyze_foldamers package. """ # Import package, test suite, and other packages as needed import analyze_foldamers import pytest import sys import os import pickle from cg_openmm.cg_model.cgmodel import CGModel from analyze_foldamers.ensembles.cluster import * current_path = os.path.dirname(os.path.abspath(__file__)) data_path = os.path.join(current_path, 'test_data') def test_clustering_kmedoids_pdb(tmpdir): """Test Kmeans clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters n_clusters=2 frame_start=10 frame_stride=1 frame_end=-1 # Run KMeans clustering medoid_positions, cluster_size, cluster_rmsd, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_KMedoids( pdb_file_list, cgmodel, n_clusters=n_clusters, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(cluster_rmsd) == n_clusters assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_1.pdb") assert os.path.isfile(f"{output_directory}/silhouette_kmedoids_ncluster_{n_clusters}.pdf") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_kmedoids_pdb_no_cgmodel(tmpdir): """Test Kmeans clustering without a cgmodel""" output_directory = tmpdir.mkdir("output") # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters n_clusters=2 frame_start=10 frame_stride=1 frame_end=-1 # Run KMeans clustering medoid_positions, cluster_size, cluster_rmsd, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_KMedoids( pdb_file_list, cgmodel=None, n_clusters=n_clusters, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(cluster_rmsd) == n_clusters assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_1.pdb") assert os.path.isfile(f"{output_directory}/silhouette_kmedoids_ncluster_{n_clusters}.pdf") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_kmedoids_dcd(tmpdir): """Test KMedoids clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 dcd_file_list = [] for i in range(number_replicas): dcd_file_list.append(f"{data_path}/replica_%s.dcd" %(i+1)) # Set clustering parameters n_clusters=2 frame_start=10 frame_stride=1 frame_end=-1 # Run KMeans clustering medoid_positions, cluster_size, cluster_rmsd, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_KMedoids( dcd_file_list, cgmodel, n_clusters=n_clusters, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_format="dcd", output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(cluster_rmsd) == n_clusters assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_1.dcd") assert os.path.isfile(f"{output_directory}/silhouette_kmedoids_ncluster_{n_clusters}.pdf") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_dbscan_pdb(tmpdir): """Test DBSCAN clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters min_samples=3 eps=0.5 frame_start=10 frame_stride=1 frame_end=-1 # Run DBSCAN density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_DBSCAN( pdb_file_list, cgmodel, min_samples=min_samples, eps=eps, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, core_points_only=False, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.pdb") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_dbscan_pdb_core_medoids(tmpdir): """Test DBSCAN clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters min_samples=3 eps=0.5 frame_start=10 frame_stride=1 frame_end=-1 # Run DBSCAN density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_DBSCAN( pdb_file_list, cgmodel, min_samples=min_samples, eps=eps, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, core_points_only=True, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.pdb") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_dbscan_pdb_no_cgmodel(tmpdir): """Test DBSCAN clustering without cgmodel object""" output_directory = tmpdir.mkdir("output") # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters min_samples=3 eps=0.5 frame_start=10 frame_stride=1 frame_end=-1 # Run DBSCAN density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_DBSCAN( pdb_file_list, cgmodel = None, min_samples=min_samples, eps=eps, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, core_points_only=False, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.pdb") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_dbscan_dcd(tmpdir): """Test DBSCAN clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 dcd_file_list = [] for i in range(number_replicas): dcd_file_list.append(f"{data_path}/replica_%s.dcd" %(i+1)) # Set clustering parameters min_samples=3 eps=0.5 frame_start=10 frame_stride=1 frame_end=-1 # Run OPTICS density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_DBSCAN( dcd_file_list, cgmodel, min_samples=min_samples, eps=eps, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_format="dcd", output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, core_points_only=False, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.dcd") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_optics_pdb(tmpdir): """Test OPTICS clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters min_samples=5 frame_start=10 frame_stride=1 frame_end=-1 # Run OPTICS density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_OPTICS( pdb_file_list, cgmodel, min_samples=min_samples, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.pdb") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_optics_pdb_no_cgmodel(tmpdir): """Test OPTICS clustering without a cgmodel object""" output_directory = tmpdir.mkdir("output") # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters min_samples=5 frame_start=10 frame_stride=1 frame_end=-1 # Run OPTICS density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_OPTICS( pdb_file_list, cgmodel = None, min_samples=min_samples, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.pdb") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_optics_dcd(tmpdir): """Test OPTICS clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 dcd_file_list = [] for i in range(number_replicas): dcd_file_list.append(f"{data_path}/replica_%s.dcd" %(i+1)) # Set clustering parameters min_samples=5 frame_start=10 frame_stride=1 frame_end=-1 # Run OPTICS density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_OPTICS( dcd_file_list, cgmodel, min_samples=min_samples, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_format="dcd", output_dir=output_directory, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.dcd") assert os.path.isfile(f"{output_directory}/distances_rmsd_hist.pdf") def test_clustering_dbscan_pdb_output_clusters(tmpdir): """Test DBSCAN clustering""" output_directory = tmpdir.mkdir("output") # Load in cgmodel cgmodel_path = os.path.join(data_path, "stored_cgmodel.pkl") cgmodel = pickle.load(open(cgmodel_path, "rb")) # Create list of trajectory files for clustering analysis number_replicas = 12 pdb_file_list = [] for i in range(number_replicas): pdb_file_list.append(f"{data_path}/replica_%s.pdb" %(i+1)) # Set clustering parameters min_samples=3 eps=0.5 frame_start=10 frame_stride=1 frame_end=-1 # Run DBSCAN density-based clustering medoid_positions, cluster_sizes, cluster_rmsd, n_noise, silhouette_avg, labels, original_indices = \ get_cluster_medoid_positions_DBSCAN( pdb_file_list, cgmodel, min_samples=min_samples, eps=eps, frame_start=frame_start, frame_stride=frame_stride, frame_end=-1, output_dir=output_directory, output_cluster_traj=True, plot_silhouette=True, plot_rmsd_hist=True, filter=True, filter_ratio=0.20, ) assert len(labels) == len(original_indices) assert os.path.isfile(f"{output_directory}/medoid_0.pdb") assert os.path.isfile(f"{output_directory}/cluster_0.pdb")

33.52183

105

0.636691

1,959

16,124

4.933129

0.062787

0.072951

0.031043

0.046565

0.947951

0.938431

0.9375

0.936672

0

0.013196

0.276234

16,124

480

106

33.591667

0.81491

0.112999

0

0.898844

0

0.110439

0.092652

0

0.112717

1

0.031792

false

0

0.020231

0

0.052023

0

null

0

1

0

1

0

null

0

7

d0df66dbd41f4ab625950abf8c91982c9557edad

237

py

Python

Homework_1.py

maximilianriesterer/friendster

46b9a170eba3f3e05d56eadd6739b186ecf17939

[ "Apache-2.0" ]

null

Homework_1.py

maximilianriesterer/friendster

46b9a170eba3f3e05d56eadd6739b186ecf17939

[ "Apache-2.0" ]

null

Homework_1.py

maximilianriesterer/friendster

46b9a170eba3f3e05d56eadd6739b186ecf17939

[ "Apache-2.0" ]

null

# 'hello world' print("hello world") print("hello \nworld") #task 3 print("#########"'\n\n'"#", "#"'\n\n'"#","#"'\n\n'"#", "#"'\n\n'"#########"'\n\n'"#", "#"'\n\n'"#", "#"'\n\n'"#########"'\n\n'"#", "#"'\n\n'"#", "#", sep = " ")

29.625

166

0.303797

30

237

2.4

0.266667

0.472222

0.666667

0.833333

0.25

0

0.004785

0.118143

237

7

167

33.857143

0.339713

0.080169

0

0.502326

0

1

0

true

0

1

0

null

1

0

1

0

1

0

null

0

1

0

1

0

7

d0eb6b0c32e036bf7fc8b7dcba367f2a471bf8f2

6,545

py

Python

loldib/getratings/models/NA/na_twitch/na_twitch_top.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_twitch/na_twitch_top.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

loldib/getratings/models/NA/na_twitch/na_twitch_top.py

koliupy/loldib

c9ab94deb07213cdc42b5a7c26467cdafaf81b7f

[ "Apache-2.0" ]

null

from getratings.models.ratings import Ratings class NA_Twitch_Top_Aatrox(Ratings): pass class NA_Twitch_Top_Ahri(Ratings): pass class NA_Twitch_Top_Akali(Ratings): pass class NA_Twitch_Top_Alistar(Ratings): pass class NA_Twitch_Top_Amumu(Ratings): pass class NA_Twitch_Top_Anivia(Ratings): pass class NA_Twitch_Top_Annie(Ratings): pass class NA_Twitch_Top_Ashe(Ratings): pass class NA_Twitch_Top_AurelionSol(Ratings): pass class NA_Twitch_Top_Azir(Ratings): pass class NA_Twitch_Top_Bard(Ratings): pass class NA_Twitch_Top_Blitzcrank(Ratings): pass class NA_Twitch_Top_Brand(Ratings): pass class NA_Twitch_Top_Braum(Ratings): pass class NA_Twitch_Top_Caitlyn(Ratings): pass class NA_Twitch_Top_Camille(Ratings): pass class NA_Twitch_Top_Cassiopeia(Ratings): pass class NA_Twitch_Top_Chogath(Ratings): pass class NA_Twitch_Top_Corki(Ratings): pass class NA_Twitch_Top_Darius(Ratings): pass class NA_Twitch_Top_Diana(Ratings): pass class NA_Twitch_Top_Draven(Ratings): pass class NA_Twitch_Top_DrMundo(Ratings): pass class NA_Twitch_Top_Ekko(Ratings): pass class NA_Twitch_Top_Elise(Ratings): pass class NA_Twitch_Top_Evelynn(Ratings): pass class NA_Twitch_Top_Ezreal(Ratings): pass class NA_Twitch_Top_Fiddlesticks(Ratings): pass class NA_Twitch_Top_Fiora(Ratings): pass class NA_Twitch_Top_Fizz(Ratings): pass class NA_Twitch_Top_Galio(Ratings): pass class NA_Twitch_Top_Gangplank(Ratings): pass class NA_Twitch_Top_Garen(Ratings): pass class NA_Twitch_Top_Gnar(Ratings): pass class NA_Twitch_Top_Gragas(Ratings): pass class NA_Twitch_Top_Graves(Ratings): pass class NA_Twitch_Top_Hecarim(Ratings): pass class NA_Twitch_Top_Heimerdinger(Ratings): pass class NA_Twitch_Top_Illaoi(Ratings): pass class NA_Twitch_Top_Irelia(Ratings): pass class NA_Twitch_Top_Ivern(Ratings): pass class NA_Twitch_Top_Janna(Ratings): pass class NA_Twitch_Top_JarvanIV(Ratings): pass class NA_Twitch_Top_Jax(Ratings): pass class NA_Twitch_Top_Jayce(Ratings): pass class NA_Twitch_Top_Jhin(Ratings): pass class NA_Twitch_Top_Jinx(Ratings): pass class NA_Twitch_Top_Kalista(Ratings): pass class NA_Twitch_Top_Karma(Ratings): pass class NA_Twitch_Top_Karthus(Ratings): pass class NA_Twitch_Top_Kassadin(Ratings): pass class NA_Twitch_Top_Katarina(Ratings): pass class NA_Twitch_Top_Kayle(Ratings): pass class NA_Twitch_Top_Kayn(Ratings): pass class NA_Twitch_Top_Kennen(Ratings): pass class NA_Twitch_Top_Khazix(Ratings): pass class NA_Twitch_Top_Kindred(Ratings): pass class NA_Twitch_Top_Kled(Ratings): pass class NA_Twitch_Top_KogMaw(Ratings): pass class NA_Twitch_Top_Leblanc(Ratings): pass class NA_Twitch_Top_LeeSin(Ratings): pass class NA_Twitch_Top_Leona(Ratings): pass class NA_Twitch_Top_Lissandra(Ratings): pass class NA_Twitch_Top_Lucian(Ratings): pass class NA_Twitch_Top_Lulu(Ratings): pass class NA_Twitch_Top_Lux(Ratings): pass class NA_Twitch_Top_Malphite(Ratings): pass class NA_Twitch_Top_Malzahar(Ratings): pass class NA_Twitch_Top_Maokai(Ratings): pass class NA_Twitch_Top_MasterYi(Ratings): pass class NA_Twitch_Top_MissFortune(Ratings): pass class NA_Twitch_Top_MonkeyKing(Ratings): pass class NA_Twitch_Top_Mordekaiser(Ratings): pass class NA_Twitch_Top_Morgana(Ratings): pass class NA_Twitch_Top_Nami(Ratings): pass class NA_Twitch_Top_Nasus(Ratings): pass class NA_Twitch_Top_Nautilus(Ratings): pass class NA_Twitch_Top_Nidalee(Ratings): pass class NA_Twitch_Top_Nocturne(Ratings): pass class NA_Twitch_Top_Nunu(Ratings): pass class NA_Twitch_Top_Olaf(Ratings): pass class NA_Twitch_Top_Orianna(Ratings): pass class NA_Twitch_Top_Ornn(Ratings): pass class NA_Twitch_Top_Pantheon(Ratings): pass class NA_Twitch_Top_Poppy(Ratings): pass class NA_Twitch_Top_Quinn(Ratings): pass class NA_Twitch_Top_Rakan(Ratings): pass class NA_Twitch_Top_Rammus(Ratings): pass class NA_Twitch_Top_RekSai(Ratings): pass class NA_Twitch_Top_Renekton(Ratings): pass class NA_Twitch_Top_Rengar(Ratings): pass class NA_Twitch_Top_Riven(Ratings): pass class NA_Twitch_Top_Rumble(Ratings): pass class NA_Twitch_Top_Ryze(Ratings): pass class NA_Twitch_Top_Sejuani(Ratings): pass class NA_Twitch_Top_Shaco(Ratings): pass class NA_Twitch_Top_Shen(Ratings): pass class NA_Twitch_Top_Shyvana(Ratings): pass class NA_Twitch_Top_Singed(Ratings): pass class NA_Twitch_Top_Sion(Ratings): pass class NA_Twitch_Top_Sivir(Ratings): pass class NA_Twitch_Top_Skarner(Ratings): pass class NA_Twitch_Top_Sona(Ratings): pass class NA_Twitch_Top_Soraka(Ratings): pass class NA_Twitch_Top_Swain(Ratings): pass class NA_Twitch_Top_Syndra(Ratings): pass class NA_Twitch_Top_TahmKench(Ratings): pass class NA_Twitch_Top_Taliyah(Ratings): pass class NA_Twitch_Top_Talon(Ratings): pass class NA_Twitch_Top_Taric(Ratings): pass class NA_Twitch_Top_Teemo(Ratings): pass class NA_Twitch_Top_Thresh(Ratings): pass class NA_Twitch_Top_Tristana(Ratings): pass class NA_Twitch_Top_Trundle(Ratings): pass class NA_Twitch_Top_Tryndamere(Ratings): pass class NA_Twitch_Top_TwistedFate(Ratings): pass class NA_Twitch_Top_Twitch(Ratings): pass class NA_Twitch_Top_Udyr(Ratings): pass class NA_Twitch_Top_Urgot(Ratings): pass class NA_Twitch_Top_Varus(Ratings): pass class NA_Twitch_Top_Vayne(Ratings): pass class NA_Twitch_Top_Veigar(Ratings): pass class NA_Twitch_Top_Velkoz(Ratings): pass class NA_Twitch_Top_Vi(Ratings): pass class NA_Twitch_Top_Viktor(Ratings): pass class NA_Twitch_Top_Vladimir(Ratings): pass class NA_Twitch_Top_Volibear(Ratings): pass class NA_Twitch_Top_Warwick(Ratings): pass class NA_Twitch_Top_Xayah(Ratings): pass class NA_Twitch_Top_Xerath(Ratings): pass class NA_Twitch_Top_XinZhao(Ratings): pass class NA_Twitch_Top_Yasuo(Ratings): pass class NA_Twitch_Top_Yorick(Ratings): pass class NA_Twitch_Top_Zac(Ratings): pass class NA_Twitch_Top_Zed(Ratings): pass class NA_Twitch_Top_Ziggs(Ratings): pass class NA_Twitch_Top_Zilean(Ratings): pass class NA_Twitch_Top_Zyra(Ratings): pass

15.695444

46

0.766692

972

6,545

4.736626

0.151235

0.209818

0.389661

0.479583

0.803432

0

0.169748

6,545

416

47

15.733173

0.847258

0

0.498195

0

1

0

true

0.498195

0.00361

0

0.501805

0

null

1

0

null

0

1

0

1

0

8

4be2c0ed62bf6ee4e5e780a10df446d3ce5503a7

14,567

py

Python

kmip/core/policy.py

vbnmmnbv/PyKMIP

4617ae528006178c466fe3945a477f568b596940

[ "Apache-2.0" ]

12

2016-09-14T21:59:10.000Z

2020-03-11T07:37:25.000Z

kmip/core/policy.py

vbnmmnbv/PyKMIP

4617ae528006178c466fe3945a477f568b596940

[ "Apache-2.0" ]

1

2021-06-25T15:43:48.000Z

kmip/core/policy.py

vbnmmnbv/PyKMIP

4617ae528006178c466fe3945a477f568b596940

[ "Apache-2.0" ]

null

# Copyright (c) 2016 The Johns Hopkins University/Applied Physics Laboratory # All Rights Reserved. # # Licensed under the Apache License, Version 2.0 (the "License"); you may # not use this file except in compliance with the License. You may obtain # a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, WITHOUT # WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the # License for the specific language governing permissions and limitations # under the License. import json import six from kmip.core import enums def read_policy_from_file(path): with open(path, 'r') as f: try: policy_blob = json.loads(f.read()) except Exception as e: raise ValueError( "An error occurred while attempting to parse the JSON " "file. {0}".format(e) ) policies = dict() for name, object_policies in six.iteritems(policy_blob): processed_object_policies = dict() for object_type, operation_policies in six.iteritems(object_policies): processed_operation_policies = dict() for operation, permission in six.iteritems(operation_policies): try: enum_operation = enums.Operation[operation] except Exception: raise ValueError( "'{0}' is not a valid Operation value.".format( operation ) ) try: enum_policy = enums.Policy[permission] except Exception: raise ValueError( "'{0}' is not a valid Policy value.".format( permission ) ) processed_operation_policies.update([ (enum_operation, enum_policy) ]) try: enum_type = enums.ObjectType[object_type] except Exception: raise ValueError( "'{0}' is not a valid ObjectType value.".format( object_type ) ) processed_object_policies.update([ (enum_type, processed_operation_policies) ]) policies.update([(name, processed_object_policies)]) return policies policies = { 'default': { enums.ObjectType.CERTIFICATE: { enums.Operation.LOCATE: enums.Policy.ALLOW_ALL, enums.Operation.CHECK: enums.Policy.ALLOW_ALL, enums.Operation.GET: enums.Policy.ALLOW_ALL, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_ALL, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_ALL, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_ALL, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.SYMMETRIC_KEY: { enums.Operation.REKEY: enums.Policy.ALLOW_OWNER, enums.Operation.REKEY_KEY_PAIR: enums.Policy.ALLOW_OWNER, enums.Operation.DERIVE_KEY: enums.Policy.ALLOW_OWNER, enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.CHECK: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_OWNER, enums.Operation.GET_USAGE_ALLOCATION: enums.Policy.ALLOW_OWNER, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.PUBLIC_KEY: { enums.Operation.LOCATE: enums.Policy.ALLOW_ALL, enums.Operation.CHECK: enums.Policy.ALLOW_ALL, enums.Operation.GET: enums.Policy.ALLOW_ALL, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_ALL, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_ALL, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_ALL, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.PRIVATE_KEY: { enums.Operation.REKEY: enums.Policy.ALLOW_OWNER, enums.Operation.REKEY_KEY_PAIR: enums.Policy.ALLOW_OWNER, enums.Operation.DERIVE_KEY: enums.Policy.ALLOW_OWNER, enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.CHECK: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_OWNER, enums.Operation.GET_USAGE_ALLOCATION: enums.Policy.ALLOW_OWNER, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.SPLIT_KEY: { enums.Operation.REKEY: enums.Policy.ALLOW_OWNER, enums.Operation.REKEY_KEY_PAIR: enums.Policy.ALLOW_OWNER, enums.Operation.DERIVE_KEY: enums.Policy.ALLOW_OWNER, enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.CHECK: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_OWNER, enums.Operation.GET_USAGE_ALLOCATION: enums.Policy.ALLOW_OWNER, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.TEMPLATE: { enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER }, enums.ObjectType.SECRET_DATA: { enums.Operation.REKEY: enums.Policy.ALLOW_OWNER, enums.Operation.REKEY_KEY_PAIR: enums.Policy.ALLOW_OWNER, enums.Operation.DERIVE_KEY: enums.Policy.ALLOW_OWNER, enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.CHECK: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_OWNER, enums.Operation.GET_USAGE_ALLOCATION: enums.Policy.ALLOW_OWNER, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.OPAQUE_DATA: { enums.Operation.REKEY: enums.Policy.ALLOW_OWNER, enums.Operation.REKEY_KEY_PAIR: enums.Policy.ALLOW_OWNER, enums.Operation.DERIVE_KEY: enums.Policy.ALLOW_OWNER, enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.CHECK: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_OWNER, enums.Operation.GET_USAGE_ALLOCATION: enums.Policy.ALLOW_OWNER, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER }, enums.ObjectType.PGP_KEY: { enums.Operation.REKEY: enums.Policy.ALLOW_OWNER, enums.Operation.REKEY_KEY_PAIR: enums.Policy.ALLOW_OWNER, enums.Operation.DERIVE_KEY: enums.Policy.ALLOW_OWNER, enums.Operation.LOCATE: enums.Policy.ALLOW_OWNER, enums.Operation.CHECK: enums.Policy.ALLOW_OWNER, enums.Operation.GET: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_OWNER, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_OWNER, enums.Operation.ADD_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.ALLOW_OWNER, enums.Operation.OBTAIN_LEASE: enums.Policy.ALLOW_OWNER, enums.Operation.GET_USAGE_ALLOCATION: enums.Policy.ALLOW_OWNER, enums.Operation.ACTIVATE: enums.Policy.ALLOW_OWNER, enums.Operation.REVOKE: enums.Policy.ALLOW_OWNER, enums.Operation.DESTROY: enums.Policy.ALLOW_OWNER, enums.Operation.ARCHIVE: enums.Policy.ALLOW_OWNER, enums.Operation.RECOVER: enums.Policy.ALLOW_OWNER } }, 'public': { enums.ObjectType.TEMPLATE: { enums.Operation.LOCATE: enums.Policy.ALLOW_ALL, enums.Operation.GET: enums.Policy.ALLOW_ALL, enums.Operation.GET_ATTRIBUTES: enums.Policy.ALLOW_ALL, enums.Operation.GET_ATTRIBUTE_LIST: enums.Policy.ALLOW_ALL, enums.Operation.ADD_ATTRIBUTE: enums.Policy.DISALLOW_ALL, enums.Operation.MODIFY_ATTRIBUTE: enums.Policy.DISALLOW_ALL, enums.Operation.DELETE_ATTRIBUTE: enums.Policy.DISALLOW_ALL, enums.Operation.DESTROY: enums.Policy.DISALLOW_ALL } } }

56.243243

78

0.600192

1,469

14,567

5.756297

0.100749

0.253311

0.280038

0.327815

0.835383

0.833254

0.830653

0.817053

0.793756

0

0.001213

0.320931

14,567

258

79

56.46124

0.853619

0.042287

0

0.710526

0

0.013275

0

1

0.004386

false

0

0.013158

0

0.02193

0

null

1

0

1

0

null

0

10

4be395efd242dfddb071fb767e62b0f60185f97e

13,689

py

Python

code/vggnet.py

statisticszhang/Image-classification-caffe-model

33084ca0841e768dae84db582e15bb29ffeeaaec

[ "MIT" ]

1

2020-06-03T12:53:43.000Z

code/vggnet.py

statisticszhang/Image-classification-caffe-model

33084ca0841e768dae84db582e15bb29ffeeaaec

[ "MIT" ]

null

code/vggnet.py

statisticszhang/Image-classification-caffe-model

33084ca0841e768dae84db582e15bb29ffeeaaec

[ "MIT" ]

null

from caffe import layers as L from caffe import params as P import caffe def conv_relu(bottom, num_output=64, kernel_size=3, stride=1, pad=1): conv = L.Convolution(bottom, num_output=num_output, kernel_size=kernel_size, stride=stride, pad=pad, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0)) relu = L.ReLU(conv, in_place=True) return conv, relu def fc_relu_drop(bottom, fc_num_output=4096, dropout_ratio=0.5): fc = L.InnerProduct(bottom, num_output=fc_num_output, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0) ) relu = L.ReLU(fc, in_place=True) drop = L.Dropout(fc, in_place=True, dropout_param=dict(dropout_ratio=dropout_ratio)) return fc, relu, drop def conv_bn_scale_relu(bottom, num_output=64, kernel_size=3, stride=1, pad=1): conv = L.Convolution(bottom, num_output=num_output, kernel_size=kernel_size, stride=stride, pad=pad, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0)) bn = L.BatchNorm(conv, use_global_stats=False, in_place=True) scale = L.Scale(conv, scale_param=dict(bias_term=True), in_place=True) relu = L.ReLU(conv, in_place=True) return conv, bn, scale, relu def accuracy_top1_top5(bottom, label): accuracy_top1 = L.Accuracy(bottom, label, include=dict(phase=1)) accuracy_top5 = L.Accuracy(bottom, label, include=dict(phase=1), accuracy_param=dict(top_k=5)) return accuracy_top1, accuracy_top5 class VggNet(object): def __init__(self, lmdb_train, lmdb_test, num_output): self.train_data = lmdb_train self.test_data = lmdb_test self.classifier_num = num_output def vgg_16_proto(self, batch_size, phase='TRAIN'): n = caffe.NetSpec() if phase == 'TRAIN': source_data = self.train_data mirror = True else: source_data = self.test_data mirror = False n.data, n.label = L.Data(source=source_data, backend=P.Data.LMDB, batch_size=batch_size, ntop=2, transform_param=dict(crop_size=224, mean_value=[104, 117, 123], mirror=mirror)) n.conv1_1, n.relu1_1 = conv_relu(n.data, num_output=64) n.conv1_2, n.relu1_2 = conv_relu(n.conv1_1, num_output=64) n.pool1 = L.Pooling(n.conv1_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) # 64x112x112 n.conv2_1, n.relu2_1 = conv_relu(n.pool1, num_output=128) n.conv2_2, n.relu2_2 = conv_relu(n.conv2_1, num_output=128) n.pool2 = L.Pooling(n.conv2_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) # 128x56x56 n.conv3_1, n.relu3_1 = conv_relu(n.pool2, num_output=256) n.conv3_2, n.relu3_2 = conv_relu(n.conv3_1, num_output=256) n.conv3_3, n.relu3_3 = conv_relu(n.conv3_2, num_output=256) n.pool3 = L.Pooling(n.conv3_3, pool=P.Pooling.MAX, kernel_size=2, stride=2) # 256x28x28 n.conv4_1, n.relu4_1 = conv_relu(n.pool3, num_output=512) n.conv4_2, n.relu4_2 = conv_relu(n.conv4_1, num_output=512) n.conv4_3, n.relu4_3 = conv_relu(n.conv4_2, num_output=512) n.pool4 = L.Pooling(n.conv4_3, pool=P.Pooling.MAX, kernel_size=2, stride=2) # 512x14x14 n.conv5_1, n.relu5_1 = conv_relu(n.pool4, num_output=512) n.conv5_2, n.relu5_2 = conv_relu(n.conv5_1, num_output=512) n.conv5_3, n.relu5_3 = conv_relu(n.conv5_2, num_output=512) n.pool5 = L.Pooling(n.conv5_3, pool=P.Pooling.MAX, kernel_size=2, stride=2) # 512x7x7 n.fc6, n.relu6, n.drop6 = fc_relu_drop(n.pool5, fc_num_output=4096, dropout_ratio=0.5) n.fc7, n.relu7, n.drop7 = fc_relu_drop(n.fc6, fc_num_output=4096, dropout_ratio=0.5) n.fc8 = L.InnerProduct(n.fc7, num_output=self.classifier_num, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0) ) n.loss = L.SoftmaxWithLoss(n.fc8, n.label) if phase == 'TRAIN': pass else: n.accuracy_top1, n.accuracy_top5 = accuracy_top1_top5(n.fc8, n.label) return n.to_proto() def vgg_16_bn_proto(self, batch_size, phase='TRAIN'): n = caffe.NetSpec() if phase == 'TRAIN': source_data = self.train_data mirror = True else: source_data = self.test_data mirror = False n.data, n.label = L.Data(source=source_data, backend=P.Data.LMDB, batch_size=batch_size, ntop=2, transform_param=dict(crop_size=224, mean_value=[104, 117, 123], mirror=mirror)) n.conv1_1, n.bn1_1, n.scale1_1, n.relu1_1 = conv_bn_scale_relu(n.data, num_output=64) n.conv1_2, n.bn1_2, n.scale1_2, n.relu1_2 = conv_bn_scale_relu(n.conv1_1, num_output=64) n.pool1 = L.Pooling(n.conv1_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv2_1, n.bn2_1, n.scale2_1, n.relu2_1 = conv_bn_scale_relu(n.pool1, num_output=128) n.conv2_2, n.bn2_2, n.scale2_2, n.relu2_2 = conv_bn_scale_relu(n.conv2_1, num_output=128) n.pool2 = L.Pooling(n.conv2_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv3_1, n.bn3_1, n.scale3_1, n.relu3_1 = conv_bn_scale_relu(n.pool2, num_output=256) n.conv3_2, n.bn3_2, n.scale3_2, n.relu3_2 = conv_bn_scale_relu(n.conv3_1, num_output=256) n.conv3_3, n.bn3_3, n.scale3_3, n.relu3_3 = conv_bn_scale_relu(n.conv3_2, num_output=256) n.pool3 = L.Pooling(n.conv3_3, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv4_1, n.bn4_1, n.scale4_1, n.relu4_1 = conv_bn_scale_relu(n.pool3, num_output=512) n.conv4_2, n.bn4_2, n.scale4_2, n.relu4_2 = conv_bn_scale_relu(n.conv4_1, num_output=512) n.conv4_3, n.bn4_3, n.scale4_3, n.relu4_3 = conv_bn_scale_relu(n.conv4_2, num_output=512) n.pool4 = L.Pooling(n.conv4_3, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv5_1, n.bn5_1, n.scale5_1, n.relu5_1 = conv_bn_scale_relu(n.pool4, num_output=512) n.conv5_2, n.bn5_2, n.scale5_2, n.relu5_2 = conv_bn_scale_relu(n.conv5_1, num_output=512) n.conv5_3, n.bn5_3, n.scale5_3, n.relu5_3 = conv_bn_scale_relu(n.conv5_2, num_output=512) n.pool5 = L.Pooling(n.conv5_3, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.fc6, n.relu6, n.drop6 = fc_relu_drop(n.pool5, fc_num_output=4096, dropout_ratio=0.5) n.fc7, n.relu7, n.drop7 = fc_relu_drop(n.fc6, fc_num_output=4096, dropout_ratio=0.5) n.fc8 = L.InnerProduct(n.fc7, num_output=self.classifier_num, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0) ) n.loss = L.SoftmaxWithLoss(n.fc8, n.label) if phase == 'TRAIN': pass else: n.accuracy_top1, n.accuracy_top5 = accuracy_top1_top5(n.fc8, n.label) return n.to_proto() def vgg_19_proto(self, batch_size, phase='TRAIN'): n = caffe.NetSpec() if phase == 'TRAIN': source_data = self.train_data mirror = True else: source_data = self.test_data mirror = False n.data, n.label = L.Data(source=source_data, backend=P.Data.LMDB, batch_size=batch_size, ntop=2, transform_param=dict(crop_size=224, mean_value=[104, 117, 123], mirror=mirror)) n.conv1_1, n.relu1_1 = conv_relu(n.data, num_output=64) n.conv1_2, n.relu1_2 = conv_relu(n.conv1_1, num_output=64) n.pool1 = L.Pooling(n.conv1_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv2_1, n.relu2_1 = conv_relu(n.pool1, num_output=128) n.conv2_2, n.relu2_2 = conv_relu(n.conv2_1, num_output=128) n.pool2 = L.Pooling(n.conv2_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv3_1, n.relu3_1 = conv_relu(n.pool2, num_output=256) n.conv3_2, n.relu3_2 = conv_relu(n.conv3_1, num_output=256) n.conv3_3, n.relu3_3 = conv_relu(n.conv3_2, num_output=256) n.conv3_4, n.relu3_4 = conv_relu(n.conv3_3, num_output=256) n.pool3 = L.Pooling(n.conv3_4, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv4_1, n.relu4_1 = conv_relu(n.pool3, num_output=512) n.conv4_2, n.relu4_2 = conv_relu(n.conv4_1, num_output=512) n.conv4_3, n.relu4_3 = conv_relu(n.conv4_2, num_output=512) n.conv4_4, n.relu4_4 = conv_relu(n.conv4_3, num_output=512) n.pool4 = L.Pooling(n.conv4_4, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv5_1, n.relu5_1 = conv_relu(n.pool4, num_output=512) n.conv5_2, n.relu5_2 = conv_relu(n.conv5_1, num_output=512) n.conv5_3, n.relu5_3 = conv_relu(n.conv5_2, num_output=512) n.conv5_4, n.relu5_4 = conv_relu(n.conv5_3, num_output=512) n.pool5 = L.Pooling(n.conv5_4, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.fc6, n.relu6, n.drop6 = fc_relu_drop(n.pool5, fc_num_output=4096, dropout_ratio=0.5) n.fc7, n.relu7, n.drop7 = fc_relu_drop(n.fc6, fc_num_output=4096, dropout_ratio=0.5) n.fc8 = L.InnerProduct(n.fc7, num_output=self.classifier_num, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0) ) n.loss = L.SoftmaxWithLoss(n.fc8, n.label) if phase == 'TRAIN': pass else: n.accuracy_top1, n.accuracy_top5 = accuracy_top1_top5(n.fc8, n.label) return n.to_proto() def vgg_19_bn_proto(self, batch_size, phase='TRAIN'): n = caffe.NetSpec() if phase == 'TRAIN': source_data = self.train_data mirror = True else: source_data = self.test_data mirror = False n.data, n.label = L.Data(source=source_data, backend=P.Data.LMDB, batch_size=batch_size, ntop=2, transform_param=dict(crop_size=224, mean_value=[104, 117, 123], mirror=mirror)) n.conv1_1, n.bn1_1, n.scale1_1, n.relu1_1 = conv_bn_scale_relu(n.data, num_output=64) n.conv1_2, n.bn1_2, n.scale1_2, n.relu1_2 = conv_bn_scale_relu(n.conv1_1, num_output=64) n.pool1 = L.Pooling(n.conv1_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv2_1, n.bn2_1, n.scale2_1, n.relu2_1 = conv_bn_scale_relu(n.pool1, num_output=128) n.conv2_2, n.bn2_2, n.scale2_2, n.relu2_2 = conv_bn_scale_relu(n.conv2_1, num_output=128) n.pool2 = L.Pooling(n.conv2_2, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv3_1, n.bn3_1, n.scale3_1, n.relu3_1 = conv_bn_scale_relu(n.pool2, num_output=256) n.conv3_2, n.bn3_2, n.scale3_2, n.relu3_2 = conv_bn_scale_relu(n.conv3_1, num_output=256) n.conv3_3, n.bn3_3, n.scale3_3, n.relu3_3 = conv_bn_scale_relu(n.conv3_2, num_output=256) n.conv3_4, n.bn3_4, n.scale3_4, n.relu3_4 = conv_bn_scale_relu(n.conv3_3, num_output=256) n.pool3 = L.Pooling(n.conv3_4, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv4_1, n.bn4_1, n.scale4_1, n.relu4_1 = conv_bn_scale_relu(n.pool3, num_output=512) n.conv4_2, n.bn4_2, n.scale4_2, n.relu4_2 = conv_bn_scale_relu(n.conv4_1, num_output=512) n.conv4_3, n.bn4_3, n.scale4_3, n.relu4_3 = conv_bn_scale_relu(n.conv4_2, num_output=512) n.conv4_4, n.bn4_4, n.scale4_4, n.relu4_4 = conv_bn_scale_relu(n.conv4_3, num_output=512) n.pool4 = L.Pooling(n.conv4_4, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.conv5_1, n.bn5_1, n.scale5_1, n.relu5_1 = conv_bn_scale_relu(n.pool4, num_output=512) n.conv5_2, n.bn5_2, n.scale5_2, n.relu5_2 = conv_bn_scale_relu(n.conv5_1, num_output=512) n.conv5_3, n.bn5_3, n.scale5_3, n.relu5_3 = conv_bn_scale_relu(n.conv5_2, num_output=512) n.conv5_4, n.bn5_4, n.scale5_4, n.relu5_4 = conv_bn_scale_relu(n.conv5_3, num_output=512) n.pool5 = L.Pooling(n.conv5_4, pool=P.Pooling.MAX, kernel_size=2, stride=2) n.fc6, n.relu6, n.drop6 = fc_relu_drop(n.pool5, fc_num_output=4096, dropout_ratio=0.5) n.fc7, n.relu7, n.drop7 = fc_relu_drop(n.fc6, fc_num_output=4096, dropout_ratio=0.5) n.fc8 = L.InnerProduct(n.fc7, num_output=self.classifier_num, param=[dict(lr_mult=1, decay_mult=1), dict(lr_mult=2, decay_mult=0)], weight_filler=dict(type='gaussian', std=0.01), bias_filler=dict(type='constant', value=0) ) n.loss = L.SoftmaxWithLoss(n.fc8, n.label) if phase == 'TRAIN': pass else: n.accuracy_top1, n.accuracy_top5 = accuracy_top1_top5(n.fc8, n.label) return n.to_proto()

54.106719

112

0.633355

2,358

13,689

3.402036

0.060645

0.090875

0.042508

0.057966

0.919471

0.913114

0.908626

0.905011

0.886437

0

0.094988

0.236321

13,689

252

113

54.321429

0.672374

0.003506

0

0.816425

0

0.012615

0

1

0.043478

false

0.019324

0.014493

0

0.101449

0

null

0

1

0

1

0

null

0

7

ef260c705a0104abd786285bdaab70dc8221bcbb

330

py

Python

backend/__init__.py

Lorioux/donatecare

cce4e40e4859a7fde0f1afa800b1080af728b230

[ "Apache-2.0" ]

null

backend/__init__.py

Lorioux/donatecare

cce4e40e4859a7fde0f1afa800b1080af728b230

[ "Apache-2.0" ]

15

2021-07-09T09:32:23.000Z

2021-07-21T07:45:33.000Z

backend/__init__.py

Lorioux/donatecare

cce4e40e4859a7fde0f1afa800b1080af728b230

[ "Apache-2.0" ]

null

from __future__ import absolute_import from backend.databases.config import * from backend.booking.models import * from backend.registration.models import * from backend.scheduling.models import * from backend.authentication.models import * from backend.authentication import token_required from backend import settings

33

50

0.824242

40

330

6.65

0.375

0.289474

0.383459

0.345865

0.278195

0

0.127273

330

9

51

36.666667

0.923611

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

32482dc21506e4ccbcb07378aaf4ebf05b9a1b2f

1,291

py

Python

dev/google-submit.py

broxeph/ameryn

e1289c280ca865ec84625b712adc52c536b4b174

[ "MIT" ]

null

dev/google-submit.py

broxeph/ameryn

e1289c280ca865ec84625b712adc52c536b4b174

[ "MIT" ]

null

dev/google-submit.py

broxeph/ameryn

e1289c280ca865ec84625b712adc52c536b4b174

[ "MIT" ]

null

def answer(n): def convert_base(in_num, out_base): output = [] for i in range(40): if out_base**(i + 1) > in_num: output.append(str(in_num / out_base**i)) in_num = in_num % out_base**i for j in range(i - 1, -1, -1): if out_base**j <= in_num: output.append(str(in_num / out_base**j)) else: output.append('0') in_num = in_num % out_base**j return ''.join(output) for i in range(2, 40): if str(convert_base(n, i)) == str(convert_base(n, i))[::-1]: return i def convert_base(in_num, out_base): output = [] for i in range(40): if out_base**(i + 1) > in_num: output.append(str(in_num / out_base**i)) in_num = in_num % out_base**i for j in range(i - 1, -1, -1): if out_base**j <= in_num: output.append(str(in_num / out_base**j)) else: output.append('0') in_num = in_num % out_base**j return ''.join(output) n = 111 print answer(n) print '{0} is {1} in base {2}.'.format(n, convert_base(n, answer(n)), answer(n))

35.861111

80

0.464756

186

1,291

3.026882

0.145161

0.159858

0.142096

0.213144

0.843694

0.767318

0

0.030809

0.396592

1,291

36

80

35.861111

0.691913

0

0.787879

0

0.01935

0

null

0

null

0.060606

0

null

0

1

0

1

0

null

0

1

0

9

088bfa9a4e6a04d183737c39a6d131e2cb00a284

17,035

py

Python

restApp/models.py

ibamacsr/painelmma_api

a11a6cd63e312f09f445b139fcff8c11ab383764

[ "MIT" ]

null

restApp/models.py

ibamacsr/painelmma_api

a11a6cd63e312f09f445b139fcff8c11ab383764

[ "MIT" ]

null

restApp/models.py

ibamacsr/painelmma_api

a11a6cd63e312f09f445b139fcff8c11ab383764

[ "MIT" ]

null

# This is an auto-generated Django model module. # You'll have to do the following manually to clean this up: # * Rearrange models' order # * Make sure each model has one field with primary_key=True # * Remove `managed = False` lines if you wish to allow Django to create, modify, and delete the table # Feel free to rename the models, but don't rename db_table values or field names. # # Also note: You'll have to insert the output of 'django-admin sqlcustom [app_label]' # into your database. from __future__ import unicode_literals from django.contrib.gis.db import models from django.conf import settings from .utils import get_reverse_month class DailyAlertaAwifs(models.Model): objectid = models.AutoField(primary_key=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) area_km2 = models.DecimalField(max_digits=38, decimal_places=2, blank=True, null=True) dominio = models.CharField(max_length=200, blank=True, null=True) tipo = models.CharField(max_length=15, blank=True, null=True) uf = models.SmallIntegerField(blank=True, null=True) estado = models.CharField(max_length=2, blank=True, null=True) data_imagem = models.DateTimeField(blank=True, null=True) geom = models.GeometryField(blank=True, null=True) centroide = models.GeometryField(blank=True, null=True) mesid = models.TextField(blank=True, null=True) estagio = models.CharField(max_length=50, blank=True, null=True) periodo_prodes = models.CharField(max_length=10, blank=True, null=True) dominio_pi = models.CharField(max_length=255, blank=True, null=True) dominio_us = models.CharField(max_length=255, blank=True, null=True) dominio_ti = models.CharField(max_length=255, blank=True, null=True) dominio_ap = models.CharField(max_length=255, blank=True, null=True) dominio_as = models.CharField(max_length=255, blank=True, null=True) dominio_fp = models.CharField(max_length=255, blank=True, null=True) class Meta: try: db_table = '%s\".\"vw_alerta_awifs' % settings.SCHEMA managed = False except AttributeError: pass class DailyAlertaDeter(models.Model): objectid = models.AutoField(primary_key=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) area_km2 = models.DecimalField(max_digits=38, decimal_places=2, blank=True, null=True) dominio = models.CharField(max_length=200, blank=True, null=True) tipo = models.CharField(max_length=15, blank=True, null=True) uf = models.SmallIntegerField(blank=True, null=True) estado = models.CharField(max_length=2, blank=True, null=True) data_imagem = models.DateTimeField(blank=True, null=True) geom = models.GeometryField(blank=True, null=True) centroide = models.GeometryField(blank=True, null=True) mesid = models.TextField(blank=True, null=True) estagio = models.CharField(max_length=50, blank=True, null=True) periodo_prodes = models.CharField(max_length=10, blank=True, null=True) dominio_pi = models.CharField(max_length=255, blank=True, null=True) dominio_us = models.CharField(max_length=255, blank=True, null=True) dominio_ti = models.CharField(max_length=255, blank=True, null=True) dominio_ap = models.CharField(max_length=255, blank=True, null=True) dominio_as = models.CharField(max_length=255, blank=True, null=True) dominio_fp = models.CharField(max_length=255, blank=True, null=True) class Meta: try: db_table = '%s\".\"vw_alerta_deter' % settings.SCHEMA managed = False except AttributeError: pass def __str__(self): return "mes: %s, ano: %s, mesid: %s" % (self.mes, self.ano, self.mesid) class DailyAlertaLandsat(models.Model): objectid = models.AutoField(primary_key=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) area_km2 = models.DecimalField(max_digits=38, decimal_places=2, blank=True, null=True) dominio = models.CharField(max_length=200, blank=True, null=True) tipo = models.CharField(max_length=15, blank=True, null=True) uf = models.SmallIntegerField(blank=True, null=True) estado = models.CharField(max_length=2, blank=True, null=True) data_imagem = models.DateTimeField(blank=True, null=True) geom = models.GeometryField(blank=True, null=True) centroide = models.GeometryField(blank=True, null=True) mesid = models.TextField(blank=True, null=True) estagio = models.CharField(max_length=50, blank=True, null=True) periodo_prodes = models.CharField(max_length=10, blank=True, null=True) class Meta: try: db_table = '%s\".\"vw_alerta_indicar' % settings.SCHEMA managed = False except AttributeError: pass class DailyAlertaDeterQualif(models.Model): objectid = models.AutoField(primary_key=True) periodo_prodes = models.CharField(max_length=10, blank=True, null=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) mes_ano = models.CharField(max_length=6, blank=True, null=True) cicatriz_fogo = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) corte_raso_deter = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) degradacao_deter = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) alta = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) leve = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) moderada = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) falso_positivo = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) nao_avaliado = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) deter_total = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) total_avaliado = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) porc_area_avaliada = models.SmallIntegerField(blank=True, null=True) mesid = models.TextField(blank=True, null=True) class Meta: try: db_table = '%s\".\"vw_deter_qualificado' % settings.SCHEMA managed = False except AttributeError: pass def __str__(self): return str(self.mes) + "/" + str(self.ano) class PublicAlertaDeterQualif(models.Model): objectid = models.AutoField(primary_key=True) periodo_prodes = models.CharField(max_length=10, blank=True, null=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) mes_ano = models.CharField(max_length=6, blank=True, null=True) cicatriz_fogo = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) corte_raso_deter = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) degradacao_deter = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) alta = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) leve = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) moderada = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) falso_positivo = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) nao_avaliado = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) deter_total = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) total_avaliado = models.DecimalField(max_digits=6, decimal_places=2, blank=True, null=True) porc_area_avaliada = models.SmallIntegerField(blank=True, null=True) mesid = models.TextField(blank=True, null=True) class Meta: try: db_table = '%s\".\"vw_publica_deter_qualificado' % settings.SCHEMA managed = False except AttributeError: pass def __str__(self): return str(self.mes) + '/' + str(self.ano) class PublicAlertaDeter(models.Model): objectid = models.AutoField(primary_key=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) area_km2 = models.DecimalField(max_digits=38, decimal_places=8, blank=True, null=True) area_ha = models.DecimalField(max_digits=38, decimal_places=8, blank=True, null=True) municipio = models.CharField(max_length=200, blank=True, null=True) dominio = models.CharField(max_length=200, blank=True, null=True) tipo = models.CharField(max_length=15, blank=True, null=True) quinzena = models.CharField(max_length=5, blank=True, null=True) id_des = models.CharField(unique=True, max_length=16, blank=True, null=True) ai = models.IntegerField(blank=True, null=True) tei = models.IntegerField(blank=True, null=True) processo = models.CharField(max_length=20, blank=True, null=True) url = models.CharField(max_length=200, blank=True, null=True) vistoria = models.CharField(max_length=100, blank=True, null=True) resp_vistoria = models.CharField(max_length=150, blank=True, null=True) longitude = models.CharField(max_length=17, blank=True, null=True) latitude = models.CharField(max_length=17, blank=True, null=True) uf = models.SmallIntegerField(blank=True, null=True) estado = models.CharField(max_length=2, blank=True, null=True) obs = models.CharField(max_length=250, blank=True, null=True) id_tablet = models.CharField(max_length=10, blank=True, null=True) data_vist = models.CharField(max_length=50, blank=True, null=True) globalid = models.CharField(max_length=50, blank=True, null=True) dado_final = models.CharField(max_length=1, blank=True, null=True) estagio = models.CharField(max_length=50, blank=True, null=True) data_imagem = models.DateTimeField(blank=True, null=True) geom = models.GeometryField(blank=True, null=True) veg_sec = models.CharField(max_length=100, blank=True, null=True) periodo_prodes = models.CharField(max_length=10, blank=True, null=True) mesid = models.TextField(blank=True, null=True) dominio_pi = models.CharField(max_length=255, blank=True, null=True) dominio_us = models.CharField(max_length=255, blank=True, null=True) dominio_ti = models.CharField(max_length=255, blank=True, null=True) dominio_ap = models.CharField(max_length=255, blank=True, null=True) dominio_as = models.CharField(max_length=255, blank=True, null=True) dominio_fp = models.CharField(max_length=255, blank=True, null=True) class Meta: try: db_table = '%s\".\"vw_publica_alerta_deter_por_periodo' % settings.SCHEMA managed = False except AttributeError: pass class TaxaProdes(models.Model): ano_prodes = models.CharField(max_length=9, blank=True, null=False, primary_key=True) ac = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) am = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) ap = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) ma = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) mt = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) pa = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) ro = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) rr = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) to = models.DecimalField(max_digits=7, decimal_places=2, blank=True, null=False) class Meta: managed = False db_table = 'public\".\"taxa_prodes' def total(self): return self.ac + self.am + self.ap + self.ma + self.mt + self.pa + self.ro + self.rr + self.to def attributes(self): return [p for p in dir(self) if len(p) == 2 and not p == 'pk'] def __str__(self): return self.ano_prodes class TaxaNuvens(models.Model): objectid = models.AutoField(primary_key=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) uf = models.CharField(max_length=2, blank=True, null=True) area_km2 = models.DecimalField(max_digits=10, decimal_places=2, blank=True, null=True) porc_area_km2 = models.DecimalField(max_digits=2, decimal_places=0, blank=True, null=True) dat_cadastro = models.DateTimeField(blank=True, null=True) class Meta: try: db_table = '%s\".\"taxa_nuvem' % settings.SCHEMA managed = False except AttributeError: pass def periodo_prodes(self): if get_reverse_month(self.mes) > 7: return str(self.ano) + "-" + str(int(self.ano) + 1) else: return str(int(self.ano) - 1) + "-" + str(self.ano) def __str__(self): return str(self.mes) + "/" + str(self.ano) + "('" + str(self.porc_area_km2) + "')" class TaxaNuvensAml(models.Model): objectid = models.AutoField(primary_key=True) data_src = models.DateTimeField(blank=True, null=True) f_area = models.DecimalField(max_digits=38, decimal_places=8, blank=True, null=True) porc_area_km2 = models.DecimalField(max_digits=38, decimal_places=8, blank=True, null=True, db_column='percent') mes = models.TextField(blank=True, null=True, db_column='mes_maiusc') ano = models.SmallIntegerField(blank=True, null=True) # mes_convert = get_reverse_month(str(mes)) class Meta: try: db_table = '%s\".\"vw_taxa_nuvem_aml' % settings.SCHEMA managed = False except AttributeError: pass # def mes(self): # return get_reverse_month(self.mes_maiusc) # def porc_area_km2(self): # return round(self.percent * 100) def prodes_filter(queryset, year, month): monthList = ['01','02','03','04','05','06','07','08','09','10','11','12'] if month > 7: return queryset.filter(ano__gte=year - 1, ano__lte=year + 1) class CruzamentoAlerta(models.Model): objectid = models.AutoField(primary_key=True) mes = models.CharField(max_length=10, blank=True, null=True) ano = models.SmallIntegerField(blank=True, null=True) area_km2 = models.DecimalField(max_digits=38, decimal_places=8, blank=True, null=True) area_ha = models.DecimalField(max_digits=38, decimal_places=8, blank=True, null=True) municipio = models.CharField(max_length=200, blank=True, null=True) dominio = models.CharField(max_length=200, blank=True, null=True) tipo = models.CharField(max_length=15, blank=True, null=True) quinzena = models.CharField(max_length=5, blank=True, null=True) id_des = models.CharField(unique=True, max_length=16, blank=True, null=True) ai = models.IntegerField(blank=True, null=True) tei = models.IntegerField(blank=True, null=True) processo = models.CharField(max_length=20, blank=True, null=True) url = models.CharField(max_length=200, blank=True, null=True) vistoria = models.CharField(max_length=100, blank=True, null=True) resp_vistoria = models.CharField(max_length=150, blank=True, null=True) longitude = models.CharField(max_length=17, blank=True, null=True) latitude = models.CharField(max_length=17, blank=True, null=True) uf = models.SmallIntegerField(blank=True, null=True) estado = models.CharField(max_length=2, blank=True, null=True) obs = models.CharField(max_length=250, blank=True, null=True) id_tablet = models.CharField(max_length=10, blank=True, null=True) data_vist = models.CharField(max_length=50, blank=True, null=True) globalid = models.CharField(max_length=50, blank=True, null=True) dado_final = models.CharField(max_length=1, blank=True, null=True) estagio = models.CharField(max_length=50, blank=True, null=True) data_imagem = models.DateTimeField(blank=True, null=True) geom = models.GeometryField(blank=True, null=True) veg_sec = models.CharField(max_length=100, blank=True, null=True) dominio_pi = models.CharField(max_length=255, blank=True, null=True) dominio_us = models.CharField(max_length=255, blank=True, null=True) dominio_ti = models.CharField(max_length=255, blank=True, null=True) dominio_ap = models.CharField(max_length=255, blank=True, null=True) dominio_as = models.CharField(max_length=255, blank=True, null=True) dominio_fp = models.CharField(max_length=255, blank=True, null=True) class Meta: try: db_table = '%s\".\"alerta' % settings.SCHEMA managed = False except AttributeError: pass

50.850746

117

0.715057

2,378

17,035

4.975189

0.10513

0.132364

0.191193

0.235652

0.881836

0.873214

0.864339

0.858254

0.827403

0.824106

0

0.024272

0.163193

17,035

335

118

50.850746

0.805682

0.037981

0

0.783394

1

0

0.019971

0.013314

0

1

0.032491

false

0.032491

0.01444

0.025271

0.815884

0

null

0

1

0

1

0

null

0

10

08b6644228af778db9585bcca30c4666626baf3d

418

py

Python

terrascript/provider/fakewebservices.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

507

2017-07-26T02:58:38.000Z

2022-01-21T12:35:13.000Z

terrascript/provider/fakewebservices.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

135

2017-07-20T12:01:59.000Z

2021-10-04T22:25:40.000Z

terrascript/provider/fakewebservices.py

mjuenema/python-terrascript

6d8bb0273a14bfeb8ff8e950fe36f97f7c6e7b1d

[ "BSD-2-Clause" ]

81

2018-02-20T17:55:28.000Z

2022-01-31T07:08:40.000Z

# terrascript/provider/fakewebservices.py # Automatically generated by tools/makecode.py (24-Sep-2021 15:16:12 UTC) # # For imports without namespace, e.g. # # >>> import terrascript.provider.fakewebservices # # instead of # # >>> import terrascript.provider.hashicorp.fakewebservices # # This is only available for 'official' and 'partner' providers. from terrascript.provider.hashicorp.fakewebservices import *

27.866667

73

0.767943

49

418

6.55102

0.714286

0.23676

0.211838

0.267913

0

0.032698

0.12201

418

14

74

29.857143

0.841962

0.791866

0

1

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

3ebf2201c30fbf06d422b2f7840bac93bee8c3bf

293

py

Python

python3/arr-mathematics/sol.py

wahoyuz/HackerRank

f342de4b95c97458b11dfa1fe3dca52f176f627e

[ "MIT" ]

null

python3/arr-mathematics/sol.py

wahoyuz/HackerRank

f342de4b95c97458b11dfa1fe3dca52f176f627e

[ "MIT" ]

null

python3/arr-mathematics/sol.py

wahoyuz/HackerRank

f342de4b95c97458b11dfa1fe3dca52f176f627e

[ "MIT" ]

null

import numpy if __name__=="__main__": N,M=map(int, input().split()) A=numpy.array([list(map(int, input().split())) for n in range(N)]) B=numpy.array([list(map(int, input().split())) for n in range(N)]) print(A + B) print(A - B) print(A * B) print(A // B) print(A % B) print(A ** B)

20.928571

67

0.59727

55

293

3.036364

0.345455

0.215569

0.251497

0.359281

0.754491

0

0.16041

293

14

68

20.928571

0.678862

0

0.027211

0

1

0

false

0

0.090909

0

0.090909

0.545455

0

null

1

0

1

0

null

0

1

0

9

f5cd2e8e8a32ca9b09ded0821d84218d80b4b94f

160

py

Python

chinese/admin.py

DiegoBrian/Flashcards

1d80dbe2943ce33964095ea856f251ab5c1725d2

[ "MIT" ]

1

2018-11-21T11:17:51.000Z

chinese/admin.py

DiegoBrian/Flashcards

1d80dbe2943ce33964095ea856f251ab5c1725d2

[ "MIT" ]

15

2018-12-07T10:50:14.000Z

2022-03-11T23:33:32.000Z

chinese/admin.py

DiegoBrian/Flashcards

1d80dbe2943ce33964095ea856f251ab5c1725d2

[ "MIT" ]

null

from django.contrib import admin from .models import * admin.site.register(Sentence) admin.site.register(User_Sentence) admin.site.register(User_TimeSettings)

22.857143

38

0.83125

22

160

5.954545

0.5

0.206107

0.389313

0.381679

0.442748

0

0.075

160

7

38

22.857143

0.885135

0

1

0

true

0

0.4

0

0.4

0

1

0

null

1

0

1

0

null

0

1

0

1

0

7

eb190c811a6551b0e7f3f91852c72fc8296bbfdb

9,320

py

Python

ubelt/tests/test_format.py

russelldj/ubelt

c82ae8c8ead66f0c406d28d680430f7df00bb32b

[ "Apache-2.0" ]

null

ubelt/tests/test_format.py

russelldj/ubelt

c82ae8c8ead66f0c406d28d680430f7df00bb32b

[ "Apache-2.0" ]

null

ubelt/tests/test_format.py

russelldj/ubelt

c82ae8c8ead66f0c406d28d680430f7df00bb32b

[ "Apache-2.0" ]

null

import ubelt as ub def test_newlines(): import ubelt as ub dict_ = { 'k1': [[1, 2, 3], [4, 5, 6]], 'k2': [[1, 2, 3], [4, 5, 6]], } assert ub.repr2(dict_, nl=1) != ub.repr2(dict_, nl=2) assert ub.repr2(dict_, nl=2) != ub.repr2(dict_, nl=3) assert ub.repr2(dict_, nl=3) == ub.repr2(dict_, nl=4) assert ub.repr2(dict_, nl=1) == ub.codeblock( ''' { 'k1': [[1, 2, 3], [4, 5, 6]], 'k2': [[1, 2, 3], [4, 5, 6]], } ''') assert ub.repr2(dict_, nl=2) == ub.codeblock( ''' { 'k1': [ [1, 2, 3], [4, 5, 6], ], 'k2': [ [1, 2, 3], [4, 5, 6], ], } ''') def test_compact_brace(): import ubelt as ub def _nest(d, w): if d == 0: return {} else: return {'n{}'.format(d): _nest(d - 1, w + 1), 'mm{}'.format(d): _nest(d - 1, w + 1)} dict_ = _nest(d=3, w=1) result = ub.repr2(dict_, nl=4, precision=2, compact_brace=0) print(result) assert result == ub.codeblock( ''' { 'mm3': { 'mm2': { 'mm1': {}, 'n1': {}, }, 'n2': { 'mm1': {}, 'n1': {}, }, }, 'n3': { 'mm2': { 'mm1': {}, 'n1': {}, }, 'n2': { 'mm1': {}, 'n1': {}, }, }, } ''') result = ub.repr2(dict_, nl=4, precision=2, compact_brace=1) print(result) assert result == ub.codeblock( ''' {'mm3': {'mm2': {'mm1': {}, 'n1': {},}, 'n2': {'mm1': {}, 'n1': {},},}, 'n3': {'mm2': {'mm1': {}, 'n1': {},}, 'n2': {'mm1': {}, 'n1': {},},},} ''') def test_empty(): import ubelt as ub assert ub.repr2(list()) == '[]' assert ub.repr2(dict()) == '{}' assert ub.repr2(set()) == '{}' assert ub.repr2(tuple()) == '()' assert ub.repr2(dict(), explicit=1) == 'dict()' # Even when no braces are no, still include them when input is empty assert ub.repr2(list(), nobr=1) == '[]' assert ub.repr2(dict(), nobr=1) == '{}' assert ub.repr2(set(), nobr=1) == '{}' assert ub.repr2(tuple(), nobr=1) == '()' assert ub.repr2(dict(), nobr=1, explicit=1) == 'dict()' def test_list_of_numpy(): import numpy as np import ubelt as ub data = [ np.zeros((3, 3), dtype=np.int32), np.zeros((3, 10), dtype=np.int32), np.zeros((3, 20), dtype=np.int32), np.zeros((3, 30), dtype=np.int32), ] string = ub.repr2(data, nl=2) print(string) assert repr(data) == repr(eval(string)), 'should produce eval-able code' assert string == ub.codeblock( ''' [ np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), ] ''') string = ub.repr2(data, max_line_width=10000, nl=2) print(string) assert string == ub.codeblock( ''' [ np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), ] ''') string = ub.repr2(data, nl=1) print(string) assert string == ub.codeblock( ''' [ np.array([[0, 0, 0],[0, 0, 0],[0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), ] ''' ) string = ub.repr2(data, nl=0) print(string) assert string == ub.codeblock( ''' [np.array([[0, 0, 0],[0, 0, 0],[0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0],[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0,0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32)] ''' ) def test_dict_of_numpy(): import numpy as np data = ub.odict(zip( ['one', 'two', 'three', 'four'], [ np.zeros((3, 3), dtype=np.int32), np.zeros((3, 10), dtype=np.int32), np.zeros((3, 20), dtype=np.int32), np.zeros((3, 30), dtype=np.int32), ])) string = ub.repr2(data, nl=2) print(string) assert string == ub.codeblock( ''' { 'one': np.array([[0, 0, 0], [0, 0, 0], [0, 0, 0]], dtype=np.int32), 'two': np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), 'three': np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), 'four': np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0], [0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0]], dtype=np.int32), } ''') def test_numpy_scalar_precision(): import numpy as np text = ub.repr2(np.float32(3.333333), precision=2) assert text == '3.33' def test_repr2_tuple_keys(): data = { ('one', 'two'): 100, ('three', 'four'): 200, } string = ub.repr2(data) print(string) string == ub.codeblock( ''' { ( 'one', 'two', ): 100, ( 'three', 'four', ): 200, } ''') data = { ('one', 'two'): 100, ('three', 'four'): 200, } string = ub.repr2(data, sk=1) print(string) string == ub.codeblock( ''' { ('one', 'two'): 100, ('three', 'four'): 200, } ''')

37.131474

700

0.342918

1,565

9,320

2.019169

0.060064

0.585443

0.859177

1.120253

0.822152

0.782595

0.768671

0.74462

0.721203

0

0.223174

0.424034

9,320

250

701

37.28

0.365499

0.007082

0

0.403846

0

0.037049

0

0.230769

1

0.076923

false

0

0.076923

0

0.173077

0.086538

0

null

1

0

1

0

1

0

null

0

11

eb3adceb9ae1eda4fa45afab96b1823e9f19f47f

235

py

Python

descriptive_fruit/generator.py

cncplyr/descriptive_fruit

5893087899141d96dbc1b79f7ebd270f906dcce8

[ "Apache-2.0" ]

1

2017-11-06T14:00:29.000Z

descriptive_fruit/generator.py

cncplyr/descriptive_fruit

5893087899141d96dbc1b79f7ebd270f906dcce8

[ "Apache-2.0" ]

1

2017-11-30T09:50:57.000Z

descriptive_fruit/generator.py

cncplyr/descriptive_fruit

5893087899141d96dbc1b79f7ebd270f906dcce8

[ "Apache-2.0" ]

null

from random import choice from descriptive_fruit.adjective import ADJECTIVES from descriptive_fruit.fruit import FRUITS def generate(separator=' '): return choice(ADJECTIVES) + separator + choice(FRUITS).replace(' ', separator)

26.111111

82

0.787234

27

235

6.777778

0.518519

0.163934

0.218579

0

0.12766

235

8

83

29.375

0.892683

0

1

0

0.008511

0

1

0.2

false

0

0.6

0.2

1

0

1

0

null

0

1

0

1

0

1

0

null

0

1

0

7

de1d9a9e45a9503e323fb6214edee1143b1ed62e

31,760

py

Python

sagan/layers.py

DeepTrickLab/Self-Attention-GAN

a6fa4f0d7916e0721c9797adec1ab5d9c6b76636

[ "MIT" ]

2

2020-09-18T03:45:24.000Z

2021-11-18T11:01:52.000Z

sagan/layers.py

DeepTrickLab/Self-Attention-GAN

a6fa4f0d7916e0721c9797adec1ab5d9c6b76636

[ "MIT" ]

null

sagan/layers.py

DeepTrickLab/Self-Attention-GAN

a6fa4f0d7916e0721c9797adec1ab5d9c6b76636

[ "MIT" ]

null

import tensorflow as tf from tensorflow.keras import layers class SpectralNormalization(tf.keras.layers.Wrapper): """This wrapper reparameterizes a layer by decoupling the weight's magnitude and direction. This speeds up convergence by improving the conditioning of the optimization problem. Weight Normalization: A Simple Reparameterization to Accelerate Training of Deep Neural Networks: https://arxiv.org/abs/1602.07868 Tim Salimans, Diederik P. Kingma (2016) WeightNormalization wrapper works for keras and tf layers. ```python net = WeightNormalization( tf.keras.layers.Conv2D(2, 2, activation='relu'), input_shape=(32, 32, 3), data_init=True)(x) net = WeightNormalization( tf.keras.layers.Conv2D(16, 5, activation='relu'), data_init=True)(net) net = WeightNormalization( tf.keras.layers.Dense(120, activation='relu'), data_init=True)(net) net = WeightNormalization( tf.keras.layers.Dense(n_classes), data_init=True)(net) ``` Arguments: layer: a layer instance. data_init: If `True` use data dependent variable initialization Raises: ValueError: If not initialized with a `Layer` instance. ValueError: If `Layer` does not contain a `kernel` of weights NotImplementedError: If `data_init` is True and running graph execution """ def __init__(self, layer, data_init=True, **kwargs): super(SpectralNormalization, self).__init__(layer, **kwargs) self.data_init = data_init self._track_trackable(layer, name='layer') self._init_critical_section = tf.CriticalSection(name='init_mutex') self.is_rnn = isinstance(self.layer, tf.keras.layers.RNN) if self.data_init and self.is_rnn: logging.warning( "WeightNormalization: Using `data_init=True` with RNNs " "is advised against by the paper. Use `data_init=False`.") def build(self, input_shape): """Build `Layer`""" input_shape = tf.TensorShape(input_shape) self.input_spec = tf.keras.layers.InputSpec( shape=[None] + input_shape[1:]) if not self.layer.built: self.layer.build(input_shape) kernel_layer = self.layer.cell if self.is_rnn else self.layer if not hasattr(kernel_layer, 'kernel'): raise ValueError('`WeightNormalization` must wrap a layer that' ' contains a `kernel` for weights') if self.is_rnn: kernel = kernel_layer.recurrent_kernel else: kernel = kernel_layer.kernel # The kernel's filter or unit dimension is -1 self.layer_depth = int(kernel.shape[-1]) self.kernel_norm_axes = list(range(kernel.shape.rank - 1)) self.g = self.add_weight( name='g', shape=(self.layer_depth,), initializer='ones', dtype=kernel.dtype, trainable=True, synchronization=tf.VariableSynchronization.AUTO, aggregation=tf.compat.v1.VariableAggregation.MEAN ) self.v = kernel self._initialized = self.add_weight( name='initialized', shape=None, initializer='zeros', dtype=tf.dtypes.bool, trainable=False) if self.data_init: # Used for data initialization in self._data_dep_init. with tf.name_scope('data_dep_init'): layer_config = tf.keras.layers.serialize(self.layer) layer_config['config']['trainable'] = False self._naked_clone_layer = tf.keras.layers.deserialize( layer_config) self._naked_clone_layer.build(input_shape) self._naked_clone_layer.set_weights(self.layer.get_weights()) if not self.is_rnn: self._naked_clone_layer.activation = None self.built = True def call(self, inputs): """Call `Layer`""" def _do_nothing(): return tf.identity(self.g) def _update_weights(): # Ensure we read `self.g` after _update_weights. with tf.control_dependencies(self._initialize_weights(inputs)): return tf.identity(self.g) g = self._init_critical_section.execute(lambda: tf.cond( self._initialized, _do_nothing, _update_weights)) with tf.name_scope('compute_weights'): # Replace kernel by normalized weight variable. kernel = tf.nn.l2_normalize(self.v, axis=self.kernel_norm_axes) * g if self.is_rnn: self.layer.cell.recurrent_kernel = kernel update_kernel = tf.identity(self.layer.cell.recurrent_kernel) else: self.layer.kernel = kernel update_kernel = tf.identity(self.layer.kernel) # Ensure we calculate result after updating kernel. with tf.control_dependencies([update_kernel]): outputs = self.layer(inputs) return outputs def compute_output_shape(self, input_shape): return tf.TensorShape( self.layer.compute_output_shape(input_shape).as_list()) def _initialize_weights(self, inputs): """Initialize weight g. The initial value of g could either from the initial value in v, or by the input value if self.data_init is True. """ with tf.control_dependencies([ tf.debugging.assert_equal( # pylint: disable=bad-continuation self._initialized, False, message='The layer has been initialized.') ]): if self.data_init: assign_tensors = self._data_dep_init(inputs) else: assign_tensors = self._init_norm() assign_tensors.append(self._initialized.assign(True)) return assign_tensors def _init_norm(self): """Set the weight g with the norm of the weight vector.""" with tf.name_scope('init_norm'): v_flat = tf.reshape(self.v, [-1, self.layer_depth]) v_norm = tf.linalg.norm(v_flat, axis=0) g_tensor = self.g.assign(tf.reshape(v_norm, (self.layer_depth,))) return [g_tensor] def _data_dep_init(self, inputs): """Data dependent initialization.""" with tf.name_scope('data_dep_init'): #print(type(self.g)) #print(dir(self.g)) #print(self.g.__class__) #print(self.g.__name__) # Generate data dependent init values x_init = self._naked_clone_layer(inputs) data_norm_axes = list(range(x_init.shape.rank - 1)) m_init, v_init = tf.nn.moments(x_init, data_norm_axes) scale_init = 1. / tf.math.sqrt(v_init + 1e-10) # RNNs have fused kernels that are tiled # Repeat scale_init to match the shape of fused kernel # Note: This is only to support the operation, # the paper advises against RNN+data_dep_init if scale_init.shape[0] != self.g.shape[0]: rep = int(self.g.shape[0] / scale_init.shape[0]) scale_init = tf.tile(scale_init, [rep]) # Assign data dependent init values g_tensor = self.g.assign(self.g * scale_init) if hasattr(self.layer, 'bias') and self.layer.bias is not None: bias_tensor = self.layer.bias.assign(-m_init * scale_init) return [g_tensor, bias_tensor] else: return [g_tensor] def get_config(self): config = {'data_init': self.data_init} base_config = super(WeightNormalization, self).get_config() return dict(list(base_config.items()) + list(config.items())) def remove(self): kernel = tf.Variable( tf.nn.l2_normalize(self.v, axis=self.kernel_norm_axes) * self.g, name='recurrent_kernel' if self.is_rnn else 'kernel') if self.is_rnn: self.layer.cell.recurrent_kernel = kernel else: self.layer.kernel = kernel return self.layer """class SpectralNormalization(tf.keras.layers.Wrapper): \"""This wrapper is modified from https://github.com/tensorflow/addons/blob/v0.7.1/tensorflow_addons/layers/wrappers.py Arguments: layer: a layer instance. data_init: If `True` use data dependent variable initialization Raises: ValueError: If not initialized with a `Layer` instance. ValueError: If `Layer` does not contain a `kernel` of weights NotImplementedError: If `data_init` is True and running graph execution \""" def __init__(self, layer, data_init=True, **kwargs): super(SpectralNormalization, self).__init__(layer, **kwargs) self.data_init = data_init self._track_trackable(layer, name='layer') self._init_critical_section = tf.CriticalSection(name='init_mutex') self.is_rnn = isinstance(self.layer, tf.keras.layers.RNN) if self.data_init and self.is_rnn: logging.warning( "WeightNormalization: Using `data_init=True` with RNNs " "is advised against by the paper. Use `data_init=False`.") def build(self, input_shape): \"""Build `Layer`\""" input_shape = tf.TensorShape(input_shape) self.input_spec = tf.keras.layers.InputSpec( shape=[None] + input_shape[1:]) if not self.layer.built: self.layer.build(input_shape) kernel_layer = self.layer.cell if self.is_rnn else self.layer if not hasattr(kernel_layer, 'kernel'): raise ValueError('`WeightNormalization` must wrap a layer that' ' contains a `kernel` for weights') if self.is_rnn: kernel = kernel_layer.recurrent_kernel else: kernel = kernel_layer.kernel # The kernel's filter or unit dimension is -1 self.layer_depth = int(kernel.shape[-1]) self.temporal_dim = int(tf.reshape(kernel, [-1, self.layer_depth]).shape[0]) self.kernel_norm_axes = list(range(kernel.shape.rank - 1)) self._u = self.add_weight( name='u', shape=(1,self.layer_depth), initializer=tf.keras.initializers.GlorotNormal, dtype=kernel.dtype, trainable=True) self._v = self.add_weight( name='g', shape=(1,self.temporal_dim), initializer=tf.keras.initializers.GlorotNormal, dtype=kernel.dtype, trainable=True) self._u = tf.math.l2_normalize(self._u, axis=1) self._v = tf.math.l2_normalize(self._v, axis=1) self.v = kernel \"""self.g = self.add_weight( name='g', shape=(self.layer_depth,), initializer='ones', dtype=kernel.dtype, trainable=True) self._initialized = self.add_weight( name='initialized', shape=None, initializer='zeros', dtype=tf.dtypes.bool, trainable=False) if self.data_init: # Used for data initialization in self._data_dep_init. with tf.name_scope('data_dep_init'): layer_config = tf.keras.layers.serialize(self.layer) layer_config['config']['trainable'] = False self._naked_clone_layer = tf.keras.layers.deserialize( layer_config) self._naked_clone_layer.build(input_shape) self._naked_clone_layer.set_weights(self.layer.get_weights()) if not self.is_rnn: self._naked_clone_layer.activation = None\""" self.built = True def call(self, inputs): \"""Call `Layer`\""" \"""def _do_nothing(): return tf.identity(self.g) def _update_weights(): # Ensure we read `self.g` after _update_weights. with tf.control_dependencies(self._initialize_weights(inputs)): return tf.identity(self.g) g = self._init_critical_section.execute(lambda: tf.cond( self._initialized, _do_nothing, _update_weights))\""" with tf.name_scope('compute_weights'): # Replace kernel by spectrally normalized weight. #with tf.init_scope(): kernel = self.spectral_normalize() if self.is_rnn: self.layer.cell.recurrent_kernel = kernel update_kernel = tf.identity(self.layer.cell.recurrent_kernel) else: self.layer.kernel = kernel update_kernel = tf.identity(self.layer.kernel) # Ensure we calculate result after updating kernel. with tf.control_dependencies([update_kernel]): outputs = self.layer(inputs) return outputs def spectral_normalize(self): kernel_mat = tf.reshape(self.v, [self.layer_depth, self.temporal_dim]) self._v = tf.math.l2_normalize(tf.matmul(self._u, kernel_mat), axis=1) update_v = tf.identity(self._v) with tf.control_dependencies([update_v]): self._u = tf.math.l2_normalize(tf.matmul(self._v, tf.transpose(kernel_mat)), axis=1) update_u = tf.identity(self._u) with tf.control_dependencies([update_u]): sigma = tf.reduce_sum(tf.matmul(self._u, kernel_mat) * self._v) return self.v / sigma def compute_output_shape(self, input_shape): return tf.TensorShape( self.layer.compute_output_shape(input_shape).as_list()) \"""def _initialize_weights(self, inputs): #Initialize weight g. #The initial value of g could either from the initial value in v, #or by the input value if self.data_init is True. with tf.control_dependencies([ tf.debugging.assert_equal( # pylint: disable=bad-continuation self._initialized, False, message='The layer has been initialized.') ]): if self.data_init: assign_tensors = self._data_dep_init(inputs) else: assign_tensors = self._init_norm() assign_tensors.append(self._initialized.assign(True)) return assign_tensors def _init_norm(self): #Set the weight g with the norm of the weight vector. with tf.name_scope('init_norm'): v_flat = tf.reshape(self.v, [-1, self.layer_depth]) v_norm = tf.linalg.norm(v_flat, axis=0) g_tensor = self.g.assign(tf.reshape(v_norm, (self.layer_depth,))) return [g_tensor] def _data_dep_init(self, inputs): #Data dependent initialization. with tf.name_scope('data_dep_init'): # Generate data dependent init values x_init = self._naked_clone_layer(inputs) data_norm_axes = list(range(x_init.shape.rank - 1)) m_init, v_init = tf.nn.moments(x_init, data_norm_axes) scale_init = 1. / tf.math.sqrt(v_init + 1e-10) # RNNs have fused kernels that are tiled # Repeat scale_init to match the shape of fused kernel # Note: This is only to support the operation, # the paper advises against RNN+data_dep_init if scale_init.shape[0] != self.g.shape[0]: rep = int(self.g.shape[0] / scale_init.shape[0]) scale_init = tf.tile(scale_init, [rep]) # Assign data dependent init values g_tensor = self.g.assign(self.g * scale_init) if hasattr(self.layer, 'bias') and self.layer.bias is not None: bias_tensor = self.layer.bias.assign(-m_init * scale_init) return [g_tensor, bias_tensor] else: return [g_tensor]\""" def get_config(self): config = {'data_init': self.data_init} base_config = super(WeightNormalization, self).get_config() return dict(list(base_config.items()) + list(config.items())) def remove(self): kernel = tf.Variable( tf.nn.l2_normalize(self.v, axis=self.kernel_norm_axes) * self.g, name='recurrent_kernel' if self.is_rnn else 'kernel') if self.is_rnn: self.layer.cell.recurrent_kernel = kernel else: self.layer.kernel = kernel return self.layer \""" def l2normalize(v, eps=1e-12): return tf.math.divide(v,(tf.norm(v) + eps)) class SpectralNormalization(layers.Layer): \""" Paper: https://openreview.net/forum?id=B1QRgziT- source: https://github.com/pfnet-research/sngan_projection \""" def __init__(self, module, name="weights", Ip=1, factor=None): super(SpectralNormalization, self).__init__() self.module = module self.weight_name = name if not Ip >= 1: raise ValueError("The number of power iterations should be positive integer") self.Ip = Ip self.factor = factor def _check_param(self): try: u = getattr(self, "u") v = getattr(self, "v") return True except AttributeError: return False def _make_param(self): W = getattr(self.module, self.weight_name)[0] height = W.shape[-1] width = tf.reshape(W, shape=(height, -1)).shape[1] u = tf.random.normal(shape=[1, height]) v = tf.random.normal(shape=[1, width]) self.u = l2normalize(u) self.v = l2normalize(v) def build(self, input_shape): self.module.build(input_shape) if not self._check_param(): self._make_param() def call(self, x, training=None): if training: self.update_uv() return self.module.call(x) # # @tf.function def update_uv(self): \""" Spectrally Normalized Weight \""" W = getattr(self.module, self.weight_name)[0] with tf.init_scope(): W_mat = tf.reshape(W, [W.shape[-1], -1]) for _ in range(self.Ip): self.v = l2normalize(tf.matmul(self.u, W_mat)) self.u = l2normalize(tf.matmul(self.v, tf.transpose(W_mat))) sigma = tf.reduce_sum(tf.matmul(self.u, W_mat) * self.v) if self.factor: sigma = sigma / self.factor W.assign(W / sigma) """ class SNConv2D(tf.keras.layers.Conv2D): """Paper: https://openreview.net/forum?id=B1QRgziT- source: https://github.com/pfnet-research/sngan_projection """ def __init__(self, filters, kernel_size, strides=(1, 1), padding='valid', data_format=None, dilation_rate=(1, 1), activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, Ip=1, factor=None, input_shape=None, **kwargs): super(SNConv2D, self).__init__( filters, kernel_size, strides=strides, padding=padding, data_format=data_format, dilation_rate=dilation_rate, activation=activation, use_bias=use_bias, kernel_initializer=kernel_initializer, bias_initializer=bias_initializer, kernel_regularizer=kernel_regularizer, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, kernel_constraint=kernel_constraint, bias_constraint=bias_constraint, **kwargs) self.training = None self.Ip = Ip self.factor = factor def _check_param(self): try: u = getattr(self, "u") v = getattr(self, "v") return True except AttributeError: return False def _make_param(self): height = self.w.shape[-1] width = tf.reshape(self.w, shape=(height, -1)).shape[1] u = tf.random.normal(shape=[1, height]) v = tf.random.normal(shape=[1, width]) self.u = l2normalize(u) self.v = l2normalize(v) def build(self, input_shape): super(SNConv2D, self).build(input_shape) self.w = self.add_weight( name='sn_conv2d_kernel', shape=self.kernel.shape, dtype=tf.float32, initializer='glorot_uniform', #regularizer=None, trainable=True, #constraint=None, #partitioner=None, #use_resource=None, synchronization=tf.VariableSynchronization.AUTO, aggregation=tf.compat.v1.VariableAggregation.MEAN) if not self._check_param(): self._make_param() # @tf.function def call(self, x, training=None): """Applies the convolution layer. Args: x (tensor): Input image. Returns: tensor: Output of the convolution. """ if training: self.update_wuv() out = tf.nn.conv2d( x, self.w, strides=self.strides, padding='SAME') if self.bias is not None: out += self.bias return out #@tf.function def update_wuv(self): with tf.init_scope(): W_mat = tf.reshape(self.w, [self.w.shape[-1], -1]) for _ in range(self.Ip): self.v = l2normalize(tf.matmul(self.u, W_mat)) self.u = l2normalize(tf.matmul(self.v, tf.transpose(W_mat))) sigma = tf.reduce_sum(tf.matmul(self.u, W_mat) * self.v) if self.factor: sigma = sigma / self.factor self.w.assign(self.w / sigma) class SNConv2DTranspose(tf.keras.layers.Conv2DTranspose): """Paper: https://openreview.net/forum?id=B1QRgziT- source: https://github.com/pfnet-research/sngan_projection """ def __init__(self, filters, kernel_size, strides=(1, 1), padding='valid', output_padding=None, data_format=None, dilation_rate=(1, 1), activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, Ip=1, factor=None, input_shape=None, **kwargs): super(SNConv2DTranspose, self).__init__( filters, kernel_size, strides=strides, output_padding=output_padding, padding=padding, data_format=data_format, dilation_rate=dilation_rate, activation=activation, use_bias=use_bias, kernel_initializer=kernel_initializer, bias_initializer=bias_initializer, kernel_regularizer=kernel_regularizer, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, kernel_constraint=kernel_constraint, bias_constraint=bias_constraint, **kwargs) self.Ip = Ip self.factor = factor self.training = None def _check_param(self): try: u = getattr(self, "u") v = getattr(self, "v") return True except AttributeError: return False def _make_param(self): height = self.w.shape[-1] width = tf.reshape(self.w, shape=(height, -1)).shape[1] u = tf.random.normal(shape=[1, height]) v = tf.random.normal(shape=[1, width]) self.u = l2normalize(u) self.v = l2normalize(v) def build(self, input_shape): super(SNConv2DTranspose, self).build(input_shape) self.w = self.add_weight( name='sn_conv2dTranspose_kernel', shape=self.kernel.shape, dtype=tf.float32, initializer='glorot_uniform', #regularizer=None, trainable=True, #constraint=None, #partitioner=None, #use_resource=None, synchronization=tf.VariableSynchronization.AUTO, aggregation=tf.compat.v1.VariableAggregation.MEAN) if not self._check_param(): self._make_param() # @tf.function def call(self, x, training=None): b, h, w, c = x.get_shape().as_list() if training: self.update_wuv() if self.padding.lower() == 'same': nh = h * self.strides[0] nw = w * self.strides[1] else: nh = h + (h - 1) * self.strides[0] + self.w.shape[0] - 1 nw = w + (w - 1) * self.strides[1] + self.w.shape[1] - 1 out = tf.nn.conv2d_transpose(x, self.w, output_shape=[b, nh, nw, self.w.shape[-2]], strides=self.strides, padding=self.padding.upper()) if self.bias is not None: out += self.bias return out def update_wuv(self): """ Spectrally Normalized Weight """ with tf.init_scope(): W_mat = tf.reshape(self.w, [self.w.shape[-1], -1]) for _ in range(self.Ip): self.v = l2normalize(tf.matmul(self.u, W_mat)) self.u = l2normalize(tf.matmul(self.v, tf.transpose(W_mat))) sigma = tf.reduce_sum(tf.matmul(self.u, W_mat) * self.v) if self.factor: sigma = sigma / self.factor self.w.assign(self.w / sigma) class SNDense(tf.keras.layers.Dense): """Paper: https://openreview.net/forum?id=B1QRgziT- source: https://github.com/pfnet-research/sngan_projection """ def __init__(self, units, activation=None, use_bias=True, kernel_initializer='glorot_uniform', bias_initializer='zeros', kernel_regularizer=None, bias_regularizer=None, activity_regularizer=None, kernel_constraint=None, bias_constraint=None, Ip=1, factor=None, **kwargs): super(SNDense, self).__init__(units, activation=activation, use_bias=use_bias, kernel_initializer=kernel_initializer, bias_initializer=bias_initializer, kernel_regularizer=kernel_regularizer, bias_regularizer=bias_regularizer, activity_regularizer=activity_regularizer, kernel_constraint=kernel_constraint, bias_constraint=bias_constraint, **kwargs) self.Ip = Ip self.factor = factor def _check_param(self): try: u = getattr(self, "u") v = getattr(self, "v") return True except AttributeError: return False def _make_param(self): self.w = self.add_weight( name='sn_dense_kernel', shape=self.weights[0].shape, dtype=tf.float32, initializer='glorot_uniform', #regularizer=None, trainable=True, #constraint=None, #partitioner=None, #use_resource=None, synchronization=tf.VariableSynchronization.AUTO, aggregation=tf.compat.v1.VariableAggregation.MEAN) W = self.weights[0] height = W.shape[-1] width = tf.reshape(W, shape=(height, -1)).shape[1] u = tf.random.normal(shape=[1, height]) v = tf.random.normal(shape=[1, width]) self.u = l2normalize(u) self.v = l2normalize(v) def build(self, input_shape): super(SNDense, self).build(input_shape) if not self._check_param(): self._make_param() # @tf.function def call(self, x, training=None): if training: with tf.init_scope(): self.update_wuv() out = tf.matmul(x, self.w) if self.use_bias: out += self.bias return out def update_wuv(self): W_mat = tf.reshape(self.w, [self.w.shape[-1], -1]) for _ in range(self.Ip): self.v = l2normalize(tf.matmul(self.u, W_mat)) self.u = l2normalize(tf.matmul(self.v, tf.transpose(W_mat))) sigma = tf.reduce_sum(tf.matmul(self.u, W_mat) * self.v) if self.factor: sigma = sigma / self.factor self.w.assign(self.w / sigma) class AttentionLayer(layers.Layer): def __init__(self): super(AttentionLayer, self).__init__() def build(self, input_shape): # to scale attention self.sigma = self.add_weight(shape=(), initializer='zero', trainable=True, name='sigma') b, w, h, c = input_shape.as_list() self.conv = [] self.conv.append(layers.Conv2D(c//8, 1, 1)) self.conv.append(layers.Conv2D(c//8, 1, 1)) # self.conv.append(layers.Conv2D(c//2, 1, 1)) self.conv.append(layers.Conv2D(c, 1, 1)) for i, conv in enumerate(self.conv): #if i==len(self.conv)-1: # conv.build([b,w,h,c//2]) #else: conv.build(input_shape) def call(self, inputs, training=None): b, w, h, c = inputs.shape.as_list() location_num = w * h downsample_num = location_num // 4 query = self.conv[0](inputs) query = tf.reshape(query, [-1, location_num, c//8]) key = self.conv[1](inputs) key = layers.MaxPool2D(2,2)(key) key = tf.reshape(key, [-1, downsample_num, c//8]) key = tf.transpose(key, [0, 2, 1]) atten = tf.matmul(query, key) atten = tf.nn.softmax(atten, axis=-1) # [location_num, downsample_num] value = self.conv[2](inputs) value = layers.MaxPool2D(2,2)(value) value = tf.reshape(value, [-1, downsample_num, c]) atten_g = tf.matmul(atten, value) # [location_num, c] atten_g = tf.reshape(atten_g, [-1, w, h, c]) # atten_g = self.conv[3](atten_g) # return layers.add([(1-self.sigma) * inputs, self.sigma * atten_g]) return layers.add([inputs, self.sigma * atten_g])

36.380298

96

0.564893

3,671

31,760

4.702261

0.100245

0.02659

0.012803

0.006372

0.843877

0.824296

0.813521

0.800371

0.78247

0.779458

0

0.010201

0.330195

31,760

872

97

36.422018

0.80125

0.09556

0

0.773228

0

0.022047

0.179908

0.050388

0

0.00315

1

0.050394

false

0

0.00315

0.116535

0

null

0

1

0

1

0

null

0

7

de348776d36fb77294e59b9465e3801d9072da8f

12,972

py

Python

simulator/simulator-topologies-fault-tolerance/latency/latency.py

giordano-lucas/DeAI

d389010e371473d0e1262176d30ceb36acef7c5a

[ "Apache-2.0" ]

44

2020-06-25T07:35:39.000Z

2022-02-18T12:29:45.000Z

simulator/simulator-topologies-fault-tolerance/latency/latency.py

giordano-lucas/DeAI

d389010e371473d0e1262176d30ceb36acef7c5a

[ "Apache-2.0" ]

152

2020-06-23T23:30:15.000Z

2022-02-25T10:22:30.000Z

simulator/simulator-topologies-fault-tolerance/latency/latency.py

giordano-lucas/DeAI

d389010e371473d0e1262176d30ceb36acef7c5a

[ "Apache-2.0" ]

11

2020-08-11T21:19:49.000Z

2022-01-30T17:15:31.000Z

import numpy as np import torch import sys sys.path.append('..') from utils import model_init, optimizer_init, client_update, diffuse_params, average_models, evaluate, create_mixing_matrix def run_latency(train_loader, test_loader, comm_matrix, num_rounds, epochs, num_clients, latency_nodes, net='net', optimizer='sgd', lr=0.1): """ Runs a decentralized optimization algorithm for the given learning rate for a number of rounds, over some network. Some nodes send their weights with a one-rounds latency, for the entire execution. Outputs the accuracies and returns them. Params: train_loader (array): the list of all train datasets, one per client test_loader (array): the list of test datasets, one per client comm_matrix (numpy.array): the communication matric modeling the network num_rounds (int): the number of data exchanges between nodes epochs (int): the number of optimization steps between each communication (minimum 1) num_clients (int): the number of clients in the network latency_nodes (array): the list of delayed nodes net (string): the neural network framework we use optimizer (string): the chosen optimizer, SGD by default lr (double): the learning rate for the optimizaion algorithm Returns: global_model (nn.Module): the final global neural network averaging all the clients client_models (array of Net): the list of all the final client neural networks accs (array): the corresponding accuracies, with the same shape as lrs """ accs = [] global_model, client_models = model_init(num_clients, net) opt = optimizer_init(client_models, lr, optimizer) loss, test_loss, acc = 0.0, 0.0, 0.0 for r in range(num_rounds): old_client_models = client_models # client update for i in range(num_clients): loss += client_update(client_models[i], opt[i], train_loader[i], epoch=epochs) # diffuse params diffuse_params_latency(client_models, comm_matrix, latency_nodes) if (r > 0): diffuse_params_latency(old_client_models, comm_matrix, np.setdiff1d(np.array(range(num_clients)), latency_nodes)) average_models(global_model, client_models) test_loss, acc = evaluate(global_model, test_loader) print('%d-th round' % r) print('average train loss %0.3g | test loss %0.3g | test acc: %0.3f' % (loss / num_clients, test_loss, acc)) accs.append(acc) return global_model, client_models, accs def run_latency_changing_topo(train_loader, test_loader, num_rounds, epochs, num_clients, latency_nodes, net='net', optimizer='sgd', lr=0.1): """ Runs a decentralized optimization algorithm for the given learning rate for a number of rounds, over some network. Some nodes send their weights with a one-rounds latency, for the entire execution. The network topology evolves over time. Outputs the accuracies and returns them. Params: train_loader (array): the list of all train datasets, one per client test_loader (array): the list of test datasets, one per client comm_matrix (numpy.array): the communication matric modeling the network num_rounds (int): the number of data exchanges between nodes epochs (int): the number of optimization steps between each communication (minimum 1) num_clients (int): the number of clients in the network latency_nodes (array): the list of delayed nodes net (string): the neural network framework we use optimizer (string): the chosen optimizer, SGD by default lr (double): the learning rate for the optimizaion algorithm Returns: global_model (nn.Module): the final global neural network averaging all the clients client_models (array of Net): the list of all the final client neural networks accs (array): the corresponding accuracies, with the same shape as lrs """ accs = [] global_model, client_models = model_init(num_clients, net) opt = optimizer_init(client_models, lr, optimizer) topos = ['centralized', 'ring', 'grid'] topo = np.random.choice(topos) comm_matrix = create_mixing_matrix(topo, num_clients) loss, test_loss, acc = 0.0, 0.0, 0.0 for r in range(num_rounds): old_client_models = client_models old_topo = topo old_comm_matrix = comm_matrix topo = np.random.choice(topos) # client update for i in range(num_clients): loss += client_update(client_models[i], opt[i], train_loader[i], epoch=epochs) # diffuse params diffuse_params_latency(client_models, comm_matrix, latency_nodes) if (r > 0): diffuse_params_latency(old_client_models, old_comm_matrix, np.setdiff1d(np.array(range(num_clients)), latency_nodes)) print("old topo: {}, new topo: {}".format(old_topo, topo)) average_models(global_model, client_models) test_loss, acc = evaluate(global_model, test_loader) print('%d-th round' % r) print('average train loss %0.3g | test loss %0.3g | test acc: %0.3f' % (loss / num_clients, test_loss, acc)) accs.append(acc) return global_model, client_models, accs def run_latency_per_round(train_loader, test_loader, comm_matrix, num_rounds, epochs, num_clients, latency_nodes, latency_rounds, net='net', optimizer='sgd', lr=0.1): """ Runs a decentralized optimization algorithm for the given learning rate for a number of rounds, over some network. Some nodes send their weights with a one-rounds latency, only during specific rounds. Outputs the accuracies and returns them. Params: train_loader (array): the list of all train datasets, one per client test_loader (array): the list of test datasets, one per client comm_matrix (numpy.array): the communication matric modeling the network num_rounds (int): the number of data exchanges between nodes epochs (int): the number of optimization steps between each communication (minimum 1) num_clients (int): the number of clients in the network latency_nodes (array): the list of delayed nodes latency_rounds (array): the rounds at which latency will occur across the network net (string): the neural network framework we use optimizer (string): the chosen optimizer, SGD by default lr (double): the learning rate for the optimizaion algorithm Returns: global_model (nn.Module): the final global neural network averaging all the clients client_models (array of Net): the list of all the final client neural networks accs (array): the corresponding accuracies, with the same shape as lrs """ accs = [] global_model, client_models = model_init(num_clients, net) opt = optimizer_init(client_models, lr, optimizer) loss, test_loss, acc = 0.0, 0.0, 0.0 for r in range(num_rounds): old_client_models = client_models # client update for i in range(num_clients): loss += client_update(client_models[i], opt[i], train_loader[i], epoch=epochs) # diffuse params if (r in latency_rounds): diffuse_params_latency(client_models, comm_matrix, latency_nodes) print("round {}, delay".format(r)) elif (r in latency_rounds + 1): diffuse_params(client_models, comm_matrix) diffuse_params_latency(old_client_models, comm_matrix, np.setdiff1d(np.array(range(num_clients)), latency_nodes)) print("round {}, delay recovery".format(r)) else: diffuse_params(client_models, comm_matrix) print("round {}, normal".format(r)) average_models(global_model, client_models) test_loss, acc = evaluate(global_model, test_loader) print('%d-th round' % r) print('average train loss %0.3g | test loss %0.3g | test acc: %0.3f' % (loss / num_clients, test_loss, acc)) accs.append(acc) return global_model, client_models, accs def run_latency_per_round_changing_topo(train_loader, test_loader, num_rounds, epochs, num_clients, latency_nodes, latency_rounds, net='net', optimizer='sgd', lr=0.1): """ Runs a decentralized optimization algorithm for the given learning rate for a number of rounds, over some network. Some nodes send their weights with a one-rounds latency, only during specific rounds. Outputs the accuracies and returns them. Params: train_loader (array): the list of all train datasets, one per client test_loader (array): the list of test datasets, one per client num_rounds (int): the number of data exchanges between nodes epochs (int): the number of optimization steps between each communication (minimum 1) num_clients (int): the number of clients in the network latency_nodes (array): the list of delayed nodes latency_rounds (array): the rounds at which latency will occur across the network net (string): the neural network framework we use optimizer (string): the chosen optimizer, SGD by default lr (double): the learning rate for the optimizaion algorithm Returns: global_model (nn.Module): the final global neural network averaging all the clients client_models (array of Net): the list of all the final client neural networks accs (array): the corresponding accuracies, with the same shape as lrs """ accs = [] global_model, client_models = model_init(num_clients, net) opt = optimizer_init(client_models, lr, optimizer) topos = ['centralized', 'ring', 'grid'] topo = np.random.choice(topos) comm_matrix = create_mixing_matrix(topo, num_clients) loss, test_loss, acc = 0.0, 0.0, 0.0 for r in range(num_rounds): old_client_models = client_models old_topo = topo old_comm_matrix = comm_matrix topo = np.random.choice(topos) # client update for i in range(num_clients): loss += client_update(client_models[i], opt[i], train_loader[i], epoch=epochs) # diffuse params if (r in latency_rounds): diffuse_params_latency(client_models, comm_matrix, latency_nodes) print("round {}, delay".format(r)) elif (r in latency_rounds + 1): diffuse_params(client_models, comm_matrix) diffuse_params_latency(old_client_models, old_comm_matrix, np.setdiff1d(np.array(range(num_clients)), latency_nodes)) print("round {}, delay recovery".format(r)) else: diffuse_params(client_models, comm_matrix) print("round {}, normal".format(r)) print("old topo: {}, new topo: {}".format(old_topo, topo)) average_models(global_model, client_models) test_loss, acc = evaluate(global_model, test_loader) print('%d-th round' % r) print('average train loss %0.3g | test loss %0.3g | test acc: %0.3f' % (loss / num_clients, test_loss, acc)) accs.append(acc) return global_model, client_models, accs def diffuse_params_latency(client_models, communication_matrix, latency_nodes): """ Diffuses the client models to their neighbours except if the node has latency. Such a node doesn't diffuse its weights now. Params: client_models (array): the list of all the client neural networks communication_matrix (numpy.array): the weighted matrix defining the links between clients latency_nodes (array): the list of nodes with latency """ if client_models: client_state_dicts = [model.state_dict() for model in client_models] keys = client_state_dicts[0].keys() for model, weights in zip(client_models, communication_matrix): neighbors = np.nonzero(weights)[0] working_neigh = np.setdiff1d(neighbors, latency_nodes) if len(working_neigh) != 0: model.load_state_dict( { key: torch.stack( [weights[j]*client_state_dicts[j][key] for j in working_neigh], dim=0, ).sum(0) / weights.sum() for key in keys } ) def nodes_latency(num_nodes, num_delay): """ Chooses a number of nodes among the set of clients. The chosen ones now have latency, i.e. their weights are transmitted with some delay. Params: num_nodes (int): the number of clients num_delay (int): the number of latency nodes to choose Returns: lat_nodes (array): the list of latency nodes """ assert num_delay < num_nodes lat_nodes = [] for i in range(num_delay): k = np.random.choice(num_nodes) while (k in lat_nodes): k = np.random.choice(num_nodes) lat_nodes.append(k) return lat_nodes

46.163701

129

0.68062

1,796

12,972

4.748886

0.106347

0.070348

0.020049

0.024622

0.872083

0.859655

0.851214

0

0.007485

0.237897

12,972

280

130

46.328571

0.85525

0.431468

0

0.755556

0

0.02963

0.073181

0

0.007407

1

0.044444

false

0

0.02963

0

0.111111

0.118519

0

null

0

1

0

1

0

null

0

7

de42a4745b9f9fa1208d30a412a288871079d383

62

py

Python

setu_viewer/models/__init__.py

chenx6/setu-server

4119fd1c7a19c96158174d8c37c376082ad19222

[ "MIT" ]

null

setu_viewer/models/__init__.py

chenx6/setu-server

4119fd1c7a19c96158174d8c37c376082ad19222

[ "MIT" ]

null

setu_viewer/models/__init__.py

chenx6/setu-server

4119fd1c7a19c96158174d8c37c376082ad19222

[ "MIT" ]

null

from .base import db def init_app(app): db.init_app(app)

12.4

20

0.693548

12

62

3.416667

0.583333

0.341463

0.487805

0

0.193548

62

5

21

12.4

0.82

0

1

0.333333

false

0

0.333333

0

0.666667

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

ded3695ff95ec50a38893c062bd0cfc32470b66e

32,666

py

Python

src/blind/02_longest_substring_without_repeating_characters/02_longest_substring_without_repeating_characters.py

ihabbou/blind-must-do

19ee182a2e0692e2501a717d47f155ec7d859f7a

[ "MIT" ]

null

src/blind/02_longest_substring_without_repeating_characters/02_longest_substring_without_repeating_characters.py

ihabbou/blind-must-do

19ee182a2e0692e2501a717d47f155ec7d859f7a

[ "MIT" ]

null

src/blind/02_longest_substring_without_repeating_characters/02_longest_substring_without_repeating_characters.py

ihabbou/blind-must-do

19ee182a2e0692e2501a717d47f155ec7d859f7a

[ "MIT" ]

null

# %% def lengthOfLongestSubstring(s: str) -> int: longest = 0 left = right = 0 lastSeen = dict() for right, char in enumerate(s): loc = lastSeen.get(char, -1) if loc >= left: left = loc lastSeen[char] = right newlen = right - left longest = max(longest, newlen) return longest slen = len(s)-1 def unique_chars_str(ss): return len(ss) == len(set(ss)) while (slen > 1): sub_set = set() for start in range(len(s) - slen + 1): sub = s[start: start + slen] sub_set.add(sub) if len(list(filter(unique_chars_str, sub_set))) != 0: return slen slen -= 1 return min(1, len(s)) # %% test inputs = [ "abcabcbb", "bbbbb", "pwwkew", "abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ0123456789!\"#$%&'()*+,-./:;<=>?@[\\]^_`{|}~ abcdefghijklmnopqrstuvwxyzABCD" ] outputs = [ 3, 1, 3, 95 ] for (s), expected in zip(inputs, outputs): print(expected) result = lengthOfLongestSubstring(s) assert result == expected, f"Expected {expected}, got {result}"

593.927273

31,658

0.646299

454

32,666

45.768722

0.11674

1.939458

2.900236

3.855046

0.972713

0

0.10229

0.020174

32,666

54

31,659

604.925926

0.546912

0.000306

0

0.641534

0.633296

0

0.027778

1

0.055556

false

0

0.027778

0.138889

0.027778

0

1

null

1

0

1

0

1

null

0

14

9d11829672a1cf793563275dee88fb8e9bc06906

170

py

Python

osp/wrappers/simple_simulation/__init__.py

simphony/wrapper-development

1d310ca782feb3b8acc2a8c275cbfb3eb8646071

[ "BSD-3-Clause" ]

null

osp/wrappers/simple_simulation/__init__.py

simphony/wrapper-development

1d310ca782feb3b8acc2a8c275cbfb3eb8646071

[ "BSD-3-Clause" ]

1

2020-11-30T10:44:09.000Z

2021-04-06T09:17:50.000Z

osp/wrappers/simple_simulation/__init__.py

simphony/wrapper-development

1d310ca782feb3b8acc2a8c275cbfb3eb8646071

[ "BSD-3-Clause" ]

1

2021-08-10T13:32:05.000Z

from osp.wrappers.simple_simulation.simulation_engine import SimulationEngine from osp.wrappers.simple_simulation.simple_simulation_session import SimpleSimulationSession

85

92

0.923529

19

170

8

0.526316

0.315789

0.197368

0.276316

0.407895

0

0.041176

170

2

92

85

0.932515

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

9d17a2bfc7b420f14812d41b24f05ed9fd7961b8

112

py

Python

metasearch/tests/unit_test/__init__.py

suzanagi/materials-researchactivity-uoa-2020-public-metasearch-mosaicsearch_publication

37553698e6f778b313922dca23c4ed40530d8f31

[ "MIT" ]

null

metasearch/tests/unit_test/__init__.py

suzanagi/materials-researchactivity-uoa-2020-public-metasearch-mosaicsearch_publication

37553698e6f778b313922dca23c4ed40530d8f31

[ "MIT" ]

null

metasearch/tests/unit_test/__init__.py

suzanagi/materials-researchactivity-uoa-2020-public-metasearch-mosaicsearch_publication

37553698e6f778b313922dca23c4ed40530d8f31

[ "MIT" ]

null

from metasearch.tests.unit_test.model import ResultItemModelTests from metasearch.tests.unit_test.view import *

37.333333

65

0.866071

15

112

6.333333

0.6

0.294737

0.4

0.484211

0.568421

0

0.071429

112

2

66

56

0.913462

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

9d1c27db305f53ca9c02ba62906d4103c206e87f

20,248

py

Python

gym-control/plot.py

AI-secure/rl-perturbed-reward

c894ca5dcdeadd0a0907770bb093b703092e1da1

[ "MIT" ]

19

2020-01-18T02:27:23.000Z

2022-02-17T03:40:43.000Z

gym-control/plot.py

AI-secure/rl-perturbed-reward

c894ca5dcdeadd0a0907770bb093b703092e1da1

[ "MIT" ]

null

gym-control/plot.py

AI-secure/rl-perturbed-reward

c894ca5dcdeadd0a0907770bb093b703092e1da1

[ "MIT" ]

1

2021-04-27T05:25:22.000Z

import argparse import pandas import os import numpy as np import matplotlib.pyplot as plt import seaborn as sns sns.set() sns.set_color_codes() parser = argparse.ArgumentParser() parser.add_argument('--log_dir', type=str, default="logs/dqn_cartpole", help='The path of log directory [default: logs/dqn_cartpole') parser.add_argument('--all', type=bool, default=False, help='Plot all the curves (diff errs) [default: False]') parser.add_argument('--weight', type=float, default=0.2, help='Weight of noise [default: 0.2]') FLAGS = parser.parse_args() LOG_DIR = FLAGS.log_dir WEIGHT = FLAGS.weight def smooth(y, weight=0.6): last = y[0] smoothed = [] for point in y: smoothed_val = last * weight + (1 - weight) * point smoothed.append(smoothed_val) last = smoothed_val return smoothed def plot_qlearn_cartpole_all(): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv"))['0'] plt.plot(smooth(list(history_normal)), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) cnt = 0 for err in [0.2, 0.4, 0.6, 0.8]: history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "noisy.csv"))['0'] history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "surrogate.csv"))['0'] plt.plot(smooth(list(history_noisy)), linewidth=1.5, c=sns.color_palette()[cnt+1], label="noisy (" + str(err) + ")") plt.plot(list(history_noisy), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+1]) plt.plot(smooth(list(history_surrogate)), linewidth=1.5, c=sns.color_palette()[cnt+2], label="surrogate (" + str(err) + ")") plt.plot(list(history_surrogate), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+2]) cnt += 2 plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps)') plt.legend(loc='best') plt.savefig(os.path.join(LOG_DIR, "CartPole-v0-reward-all (Q-Learning).png")) def plot_qlearn_cartpole(weight=0.2): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv"))['0'] history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "noisy.csv"))['0'] history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "surrogate.csv"))['0'] plt.plot(smooth(list(history_normal)), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy)), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate)), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='best') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-steps-" + str(weight) + " (Q-Learning).png")) def plot_dqn_cartpole_all(): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) cnt = 0 for err in [0.2, 0.4, 0.5]: history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "noisy.csv")) history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "surrogate.csv")) plt.plot(smooth(list(history_noisy['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[cnt+1], label="noisy (" + str(err) + ")") plt.plot(list(history_noisy['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+1]) plt.plot(smooth(list(history_surrogate['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[cnt+2], label="surrogate (" + str(err) + ")") plt.plot(list(history_surrogate['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+2]) cnt += 2 plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps)') plt.legend(loc='best') plt.savefig(os.path.join(LOG_DIR, "CartPole-v0-reward-all (DQN).png")) def plot_dqn_cartpole(weight=0.2): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "noisy.csv")) history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "surrogate.csv")) plt.plot(smooth(list(history_normal['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='best') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-steps-" + str(weight) + " (DQN).png")) plt.clf() plt.plot(smooth(list(history_normal['episode_reward'])), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy['episode_reward'])), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate['episode_reward'])), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('CartPole-v0 (reward-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='upper right') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-reward-" + str(weight) + " (DQN).png")) def plot_sarsa_cartpole_all(): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) cnt = 0 for err in [0.2, 0.4, 0.5]: history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "noisy.csv")) history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "surrogate.csv")) plt.plot(smooth(list(history_noisy['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[cnt+1], label="noisy (" + str(err) + ")") plt.plot(list(history_noisy['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+1]) plt.plot(smooth(list(history_surrogate['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[cnt+2], label="surrogate (" + str(err) + ")") plt.plot(list(history_surrogate['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+2]) cnt += 2 plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps)') plt.legend(loc='best') plt.savefig(os.path.join(LOG_DIR, "CartPole-v0-steps-all (SARSA).png")) def plot_sarsa_cartpole(weight=0.2): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "noisy.csv")) history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "surrogate.csv")) plt.plot(smooth(list(history_normal['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='best') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-steps-" + str(weight) + " (SARSA).png")) plt.clf() plt.plot(smooth(list(history_normal['episode_reward'])), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy['episode_reward'])), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate['episode_reward'])), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('CartPole-v0 (reward-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='upper right') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-reward-" + str(weight) + " (SARSA).png")) def plot_cem_cartpole_all(): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) cnt = 0 for err in [0.2, 0.4, 0.5]: history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "noisy.csv")) history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(err)), "surrogate.csv")) plt.plot(smooth(list(history_noisy['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[cnt+1], label="noisy (" + str(err) + ")") plt.plot(list(history_noisy['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+1]) plt.plot(smooth(list(history_surrogate['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[cnt+2], label="surrogate (" + str(err) + ")") plt.plot(list(history_surrogate['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+2]) cnt += 2 plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps)') plt.legend(loc='best') plt.savefig(os.path.join(LOG_DIR, "CartPole-v0-reward-all (CEM).png")) def plot_cem_cartpole(weight=0.2): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) history_noisy = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "noisy.csv")) history_surrogate = pandas.read_csv(os.path.join(os.path.join(LOG_DIR, str(weight)), "surrogate.csv")) plt.plot(smooth(list(history_normal['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate['nb_episode_steps'])), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate['nb_episode_steps']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('steps per episode') plt.xlabel('episode') plt.title('CartPole-v0 (steps-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='best') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-steps-" + str(weight) + " (CEM).png")) plt.clf() plt.plot(smooth(list(history_normal['episode_reward'])), linewidth=1.5, c=sns.color_palette()[0]) plt.plot(smooth(list(history_noisy['episode_reward'])), linewidth=1.5, c=sns.color_palette()[1]) plt.plot(smooth(list(history_surrogate['episode_reward'])), linewidth=1.5, c=sns.color_palette()[2]) plt.plot(list(history_normal['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) plt.plot(list(history_noisy['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(list(history_surrogate['episode_reward']), alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('CartPole-v0 (reward-' + str(weight) + ")") plt.legend(['normal', 'noisy', 'surrogate'], loc='upper right') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "CartPole-v0-reward-" + str(weight) + " (CEM).png")) def plot_ddpg_pendulum_all(): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['episode_reward'] / 200.0)), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['episode_reward'] / 200.0), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) cnt = 0 for err in [0.2, 0.4, 0.5]: reward_noisy = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(err)), "noisy_reward"))) reward_surrogate = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(err)), "surrogate_reward"))) plt.plot(smooth(reward_noisy), linewidth=1.5, c=sns.color_palette()[cnt+1], label="noisy (" + str(err) + ")") plt.plot(reward_noisy, alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+1]) plt.plot(smooth(reward_surrogate), linewidth=1.5, c=sns.color_palette()[cnt+2], label="surrogate (" + str(err) + ")") plt.plot(reward_surrogate, alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+2]) cnt += 2 plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('Pendulum-v0 (reward)') plt.legend(loc='best') # plt.show() plt.savefig(os.path.join(LOG_DIR, "Pendulum-v0-reward-all (DDPG).png")) def plot_ddpg_pendulum(weight=0.2): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['episode_reward'] / 200.0)), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['episode_reward'] / 200.0), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) reward_noisy = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(weight)), "noisy_reward"))) reward_surrogate = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(weight)), "surrogate_reward"))) plt.plot(smooth(reward_noisy), linewidth=1.5, c=sns.color_palette()[1], label="noisy") plt.plot(reward_noisy, alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(smooth(reward_surrogate), linewidth=1.5, c=sns.color_palette()[2], label="surrogate") plt.plot(reward_surrogate, alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('Pendulum-v0 (reward-' + str(weight) + ")") plt.legend(loc='best') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "Pendulum-v0-reward-" + str(weight) + " (DDPG).png")) def plot_naf_pendulum_all(): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['episode_reward'] / 2.0)), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['episode_reward'] / 2.0), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) cnt = 0 for err in [0.2, 0.4, 0.5]: reward_noisy = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(err)), "noisy_reward"))) reward_surrogate = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(err)), "surrogate_reward"))) plt.plot(smooth(reward_noisy), linewidth=1.5, c=sns.color_palette()[cnt+1], label="noisy (" + str(err) + ")") plt.plot(reward_noisy, alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+1]) plt.plot(smooth(reward_surrogate), linewidth=1.5, c=sns.color_palette()[cnt+2], label="surrogate (" + str(err) + ")") plt.plot(reward_surrogate, alpha=0.4, linewidth=0.8, c=sns.color_palette()[cnt+2]) cnt += 2 plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('Pendulum-v0 (reward)') plt.legend(loc='best') # plt.show() plt.savefig(os.path.join(LOG_DIR, "Pendulum-v0-reward-all (NAF).png")) def plot_naf_pendulum(weight=0.2): history_normal = pandas.read_csv(os.path.join(LOG_DIR, "normal.csv")) plt.plot(smooth(list(history_normal['episode_reward'] / 2.0)), linewidth=1.5, c=sns.color_palette()[0], label="normal") plt.plot(list(history_normal['episode_reward'] / 2.0), alpha=0.4, linewidth=0.8, c=sns.color_palette()[0]) reward_noisy = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(weight)), "noisy_reward"))) reward_surrogate = list(np.loadtxt(os.path.join(os.path.join(LOG_DIR, str(weight)), "surrogate_reward"))) plt.plot(smooth(reward_noisy), linewidth=1.5, c=sns.color_palette()[1], label="noisy") plt.plot(reward_noisy, alpha=0.4, linewidth=0.8, c=sns.color_palette()[1]) plt.plot(smooth(reward_surrogate), linewidth=1.5, c=sns.color_palette()[2], label="surrogate") plt.plot(reward_surrogate, alpha=0.4, linewidth=0.8, c=sns.color_palette()[2]) plt.ylabel('reward per episode') plt.xlabel('episode') plt.title('Pendulum-v0 (reward-' + str(weight) + ")") plt.legend(loc='best') # plt.show() plt.savefig(os.path.join(os.path.join(LOG_DIR, str(weight)), "Pendulum-v0-reward-" + str(weight) + " (NAF).png")) def plot(): if "qlearn" in LOG_DIR and "cartpole" in LOG_DIR: plot_qlearn_cartpole(weight=WEIGHT) elif "dqn" in LOG_DIR and "cartpole" in LOG_DIR: plot_dqn_cartpole(weight=WEIGHT) elif "sarsa" in LOG_DIR and "cartpole" in LOG_DIR: plot_sarsa_cartpole(weight=WEIGHT) elif "cem" in LOG_DIR and "cartpole" in LOG_DIR: plot_cem_cartpole(weight=WEIGHT) elif "ddpg" in LOG_DIR and "pendulum" in LOG_DIR: plot_ddpg_pendulum(weight=WEIGHT) elif "naf" in LOG_DIR and "pendulum" in LOG_DIR: plot_naf_pendulum(weight=WEIGHT) else: raise NotImplementedError def plot_all(): if "qlearn" in LOG_DIR and "cartpole" in LOG_DIR: plot_qlearn_cartpole_all() elif "dqn" in LOG_DIR and "cartpole" in LOG_DIR: plot_dqn_cartpole_all() elif "sarsa" in LOG_DIR and "cartpole" in LOG_DIR: plot_sarsa_cartpole_all() elif "cem" in LOG_DIR and "cartpole" in LOG_DIR: plot_cem_cartpole_all() elif "ddpg" in LOG_DIR and "pendulum" in LOG_DIR: plot_ddpg_pendulum_all() elif "naf" in LOG_DIR and "pendulum" in LOG_DIR: plot_naf_pendulum_all() else: raise NotImplementedError if __name__ == "__main__": if FLAGS.all: plot_all() else: plot()

54.724324

152

0.6774

3,211

20,248

4.113049

0.035503

0.047702

0.061331

0.109033

0.935489

0.923071

0

0.02782

0.130136

20,248

369

153

54.872629

0.722024

0.005927

0

0.708475

0

0.160618

0.006512

0

1

0.050847

false

0

0.020339

0

0.074576

0

null

0

1

0

1

0

null

0

7

9d22fc0b20574ed690587203238d9851d4ea7aa2

175

py

Python

django_backend/forms/__init__.py

holg/django_backend

6cef76a378664e6621619862e6db476788a58992

[ "BSD-3-Clause" ]

3

2015-09-10T07:10:49.000Z

2021-03-16T07:17:58.000Z

django_backend/forms/__init__.py

holg/django_backend

6cef76a378664e6621619862e6db476788a58992

[ "BSD-3-Clause" ]

10

2015-09-09T13:40:24.000Z

2021-02-27T09:12:23.000Z

django_backend/forms/__init__.py

holg/django_backend

6cef76a378664e6621619862e6db476788a58992

[ "BSD-3-Clause" ]

5

2016-06-12T08:20:38.000Z

2021-02-27T09:02:30.000Z

from .fields import * # noqa from .filterforms import * # noqa from .forms import * # noqa from .relation_list_fields import * # noqa from .selectrelated import * # noqa

29.166667

43

0.714286

22

175

5.590909

0.409091

0.406504

0.455285

0.325203

0

0.2

175

5

44

35

0.878571

0.137143

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

df9dc8ab4cac73880d49af00d03973097c99a46a

44,783

py

Python

tests/unit/dns/rackspace/test_services.py

satroutr/poppy

27417f86854d9e0a04726acc263ef0a2ce9f8f6e

[ "Apache-2.0" ]

3

2017-07-05T20:09:59.000Z

2018-11-27T22:02:57.000Z

tests/unit/dns/rackspace/test_services.py

satroutr/poppy

27417f86854d9e0a04726acc263ef0a2ce9f8f6e

[ "Apache-2.0" ]

24

2017-04-18T15:14:04.000Z

2019-03-20T19:09:07.000Z

tests/unit/dns/rackspace/test_services.py

satroutr/poppy

27417f86854d9e0a04726acc263ef0a2ce9f8f6e

[ "Apache-2.0" ]

8

2017-04-03T13:24:27.000Z

2021-11-08T20:28:10.000Z

# Copyright (c) 2014 Rackspace, Inc. # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or # implied. # See the License for the specific language governing permissions and # limitations under the License. import uuid import ddt import mock from oslo_config import cfg import pyrax.exceptions as exc from poppy.dns.rackspace import driver from poppy.model.helpers import domain from poppy.model import log_delivery from poppy.model import service from tests.unit import base RACKSPACE_OPTIONS = [ cfg.StrOpt('username', default='', help='Keystone Username'), cfg.StrOpt('api_key', default='', help='Keystone API Key'), cfg.BoolOpt('sharding_enabled', default=True, help='Enable Sharding?'), cfg.IntOpt('num_shards', default=500, help='Number of Shards to use'), cfg.IntOpt('records_limit', default=400, help='Number of records per domain.'), cfg.StrOpt('shard_prefix', default='cdn', help='The shard prefix to use'), cfg.StrOpt('url', default='mycdn.com', help='The url for customers to CNAME to'), cfg.StrOpt('email', help='The email to be provided to Rackspace DNS for' 'creating subdomains'), cfg.StrOpt('auth_endpoint', default='', help='Authentication end point for DNS'), cfg.IntOpt('timeout', default=30, help='DNS response timeout'), cfg.IntOpt('delay', default=1, help='DNS retry delay'), ] RACKSPACE_GROUP = 'drivers:dns:rackspace' @ddt.ddt class TestServicesCreate(base.TestCase): def setUp(self): super(TestServicesCreate, self).setUp() pyrax_cloud_dns_patcher = mock.patch('pyrax.cloud_dns') pyrax_cloud_dns_patcher.start() self.addCleanup(pyrax_cloud_dns_patcher.stop) pyrax_set_credentials_patcher = mock.patch('pyrax.set_credentials') pyrax_set_credentials_patcher.start() self.addCleanup(pyrax_set_credentials_patcher.stop) pyrax_set_setting_patcher = mock.patch('pyrax.set_setting') pyrax_set_setting_patcher.start() self.addCleanup(pyrax_set_setting_patcher.stop) rs_options_patcher = mock.patch.object( driver, 'RACKSPACE_OPTIONS', new=RACKSPACE_OPTIONS ) rs_options_patcher.start() self.addCleanup(rs_options_patcher.stop) provider = driver.DNSProvider(self.conf) self.client = mock.Mock() self.controller = provider.services_controller self.controller.client = self.client def test_create_with_no_links(self): responders = [{ 'Akamai': { 'id': str(uuid.uuid4()), 'links': [] }, 'Fastly': { 'id': str(uuid.uuid4()), 'links': [] } }] subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) dns_details = self.controller.create(responders) for responder in responders: for provider_name in responder: self.assertEqual([], dns_details[provider_name]['access_urls']) def test_create_with_provider_error(self): responders = [{ 'Akamai': { 'error': 'Create service failed with Akamai', 'error_detail': 'Error details' }, 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'blog.mocksite.com', 'href': u'blog.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'test.mocksite.com', 'href': u'test.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) dns_details = self.controller.create(responders) for responder in responders: for provider_name in responder: self.assertIsNotNone(dns_details[provider_name]['error']) self.assertIsNotNone( dns_details[provider_name]['error_detail']) def test_create_with_subdomain_not_found_exception(self): domain_names = [u'blog.mocksite.com', u'test.mocksite.com'] responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'blog.mocksite.com', 'href': u'blog.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'test.mocksite.com', 'href': u'test.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] self.client.find = mock.Mock( side_effect=exc.NotFound('Subdomain not found')) dns_details = self.controller.create(responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_name in domain_names: self.assertIsNotNone( access_urls_map[provider_name][domain_name]) def test_create_with_generic_exception(self): responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'blog.mocksite.com', 'href': u'blog.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'test.mocksite.com', 'href': u'test.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] subdomain = mock.Mock() subdomain.add_records = mock.Mock( side_effect=exc.NotFound('Subdomain not found')) self.client.find = mock.Mock(return_value=subdomain) dns_details = self.controller.create(responders) for responder in responders: for provider_name in responder: self.assertIsNotNone(dns_details[provider_name]['error']) self.assertIsNotNone( dns_details[provider_name]['error_detail']) def test_create(self): domain_names = [u'blog.mocksite.com', u'test.mocksite.com'] responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'blog.mocksite.com', 'href': u'blog.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'test.mocksite.com', 'href': u'test.mocksite.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'href': 'https://cloudfiles.rackspace/CONTAINER/OBJ', 'rel': 'log_delivery' }, { 'domain': u'shared.mocksite.com', 'href': u'test.mocksite.com.global.prod.fastly.net', 'certificate': 'shared', 'rel': 'access_url' }, ]} }] subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) dns_details = self.controller.create(responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_name in domain_names: self.assertIsNotNone( access_urls_map[provider_name][domain_name]) @ddt.ddt class TestServicesDelete(base.TestCase): def setUp(self): super(TestServicesDelete, self).setUp() pyrax_cloud_dns_patcher = mock.patch('pyrax.cloud_dns') pyrax_cloud_dns_patcher.start() self.addCleanup(pyrax_cloud_dns_patcher.stop) pyrax_set_credentials_patcher = mock.patch('pyrax.set_credentials') pyrax_set_credentials_patcher.start() self.addCleanup(pyrax_set_credentials_patcher.stop) pyrax_set_setting_patcher = mock.patch('pyrax.set_setting') pyrax_set_setting_patcher.start() self.addCleanup(pyrax_set_setting_patcher.stop) rs_options_patcher = mock.patch.object( driver, 'RACKSPACE_OPTIONS', new=RACKSPACE_OPTIONS ) rs_options_patcher.start() self.addCleanup(rs_options_patcher.stop) provider = driver.DNSProvider(self.conf) self.client = mock.Mock() self.controller = provider.services_controller self.controller.client = self.client def test_delete_with_exception_subdomain_not_found(self): akamai_access_urls = [ { u'provider_url': u'mycdn.com.v2.mdc.edgesuite.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.com.cdn80.mycdn.com' } ] fastly_access_urls = [ { u'provider_url': u'mocksite.com.global.fastly.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.cdn80.mycdn.com' } ] akamai_details = mock.Mock() akamai_details.access_urls = akamai_access_urls fastly_details = mock.Mock() fastly_details.access_urls = fastly_access_urls provider_details = { 'Akamai': akamai_details, 'Fastly': fastly_details } self.client.find = mock.Mock( side_effect=exc.NotFound('Subdomain not found')) dns_responder = self.controller.delete(provider_details) for provider_name in provider_details: self.assertIsNotNone(dns_responder[provider_name]['error']) self.assertIsNotNone(dns_responder[provider_name]['error_detail']) self.assertIsNotNone( dns_responder[provider_name]['error_class'] ) def test_delete_with_generic_exception(self): akamai_access_urls = [ { u'provider_url': u'mycdn.com.v2.mdc.edgesuite.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.com.cdn80.mycdn.com' } ] fastly_access_urls = [ { u'provider_url': u'mocksite.com.global.fastly.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.cdn80.mycdn.com' } ] akamai_details = mock.Mock() akamai_details.access_urls = akamai_access_urls fastly_details = mock.Mock() fastly_details.access_urls = fastly_access_urls provider_details = { 'Akamai': akamai_details, 'Fastly': fastly_details } subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) self.client.search_records = mock.Mock( side_effect=Exception('Generic exception')) dns_responder = self.controller.delete(provider_details) for provider_name in provider_details: self.assertIsNotNone(dns_responder[provider_name]['error']) self.assertIsNotNone(dns_responder[provider_name]['error_detail']) self.assertIsNotNone( dns_responder[provider_name]['error_class'] ) def test_delete_no_records_found(self): akamai_access_urls = [ { u'provider_url': u'mycdn.com.v2.mdc.edgesuite.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.com.cdn80.mycdn.com' } ] fastly_access_urls = [ { u'provider_url': u'mocksite.com.global.fastly.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.cdn80.mycdn.com' } ] akamai_details = mock.Mock() akamai_details.access_urls = akamai_access_urls fastly_details = mock.Mock() fastly_details.access_urls = fastly_access_urls provider_details = { 'Akamai': akamai_details, 'Fastly': fastly_details } subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) self.client.search_records = mock.Mock(return_value=[]) dns_responder = self.controller.delete(provider_details) for provider_name in provider_details: self.assertEqual({}, dns_responder[provider_name]) def test_delete_with_more_than_one_record_found(self): akamai_access_urls = [ { u'provider_url': u'mycdn.com.v2.mdc.edgesuite.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.com.cdn80.mycdn.com' } ] fastly_access_urls = [ { u'provider_url': u'mocksite.com.global.fastly.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.cdn80.mycdn.com' }, { u'provider_url': u'test.com.global.fastly.net', u'domain': u'mocksite.com' } ] akamai_details = mock.Mock() akamai_details.access_urls = akamai_access_urls fastly_details = mock.Mock() fastly_details.access_urls = fastly_access_urls provider_details = { 'Akamai': akamai_details, 'Fastly': fastly_details } subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) records = [mock.Mock(), mock.Mock()] self.client.search_records = mock.Mock(return_value=records) dns_responder = self.controller.delete(provider_details) for provider_name in provider_details: self.assertIsNotNone(dns_responder[provider_name]['error']) self.assertIsNotNone(dns_responder[provider_name]['error_detail']) def test_delete_with_delete_exception(self): akamai_access_urls = [ { u'provider_url': u'mycdn.com.v2.mdc.edgesuite.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.com.cdn80.mycdn.com' } ] fastly_access_urls = [ { u'provider_url': u'mocksite.com.global.fastly.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.cdn80.mycdn.com' } ] akamai_details = mock.Mock() akamai_details.access_urls = akamai_access_urls fastly_details = mock.Mock() fastly_details.access_urls = fastly_access_urls provider_details = { 'Akamai': akamai_details, 'Fastly': fastly_details } subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) record = mock.Mock() record.delete = mock.Mock( side_effect=exc.NotFound('Generic exception')) self.client.search_records = mock.Mock(return_value=[record]) dns_responder = self.controller.delete(provider_details) for provider_name in provider_details: self.assertIsNotNone(dns_responder[provider_name]['error']) self.assertIsNotNone(dns_responder[provider_name]['error_detail']) self.assertIsNotNone( dns_responder[provider_name]['error_class'] ) def test_delete(self): akamai_access_urls = [ { u'provider_url': u'mycdn.com.v2.mdc.edgesuite.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.com.cdn80.mycdn.com' } ] fastly_access_urls = [ { u'provider_url': u'mocksite.com.global.fastly.net', u'domain': u'mocksite.com', u'operator_url': u'mocksite.cdn80.mycdn.com' } ] akamai_details = mock.Mock() akamai_details.access_urls = akamai_access_urls fastly_details = mock.Mock() fastly_details.access_urls = fastly_access_urls provider_details = { 'Akamai': akamai_details, 'Fastly': fastly_details } subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) record = mock.Mock() self.client.search_records = mock.Mock(return_value=[record]) dns_responder = self.controller.delete(provider_details) for provider_name in provider_details: self.assertEqual({}, dns_responder[provider_name]) @ddt.ddt class TestServicesUpdate(base.TestCase): def setUp(self): super(TestServicesUpdate, self).setUp() pyrax_cloud_dns_patcher = mock.patch('pyrax.cloud_dns') pyrax_cloud_dns_patcher.start() self.addCleanup(pyrax_cloud_dns_patcher.stop) pyrax_set_credentials_patcher = mock.patch('pyrax.set_credentials') pyrax_set_credentials_patcher.start() self.addCleanup(pyrax_set_credentials_patcher.stop) pyrax_set_setting_patcher = mock.patch('pyrax.set_setting') pyrax_set_setting_patcher.start() self.addCleanup(pyrax_set_setting_patcher.stop) rs_options_patcher = mock.patch.object( driver, 'RACKSPACE_OPTIONS', new=RACKSPACE_OPTIONS ) rs_options_patcher.start() self.addCleanup(rs_options_patcher.stop) self.client = mock.Mock() provider = driver.DNSProvider(self.conf) self.controller = provider.services_controller self.controller.client = self.client self.domains_old = [domain.Domain('test.domain.com'), domain.Domain('blog.domain.com')] self.origins_old = [] fastly_access_urls_old = [ { u'provider_url': u'test.domain.com.global.prod.fastly.net', u'domain': u'test.domain.com', u'operator_url': u'test.domain.com.cdn80.mycdn.com' }, { u'provider_url': u'blog.domain.com.global.prod.fastly.net', u'domain': u'blog.domain.com', u'operator_url': u'blog.domain.com.cdn80.mycdn.com' }, { "log_delivery": [ { "internalURL": "https://internal.storage.com", "publicURL": "https://external.storage.com" } ] } ] fastly_provider_details_old = mock.Mock() fastly_provider_details_old.access_urls = fastly_access_urls_old provider_details_old = { 'Fastly': fastly_provider_details_old } self.service_old = service.Service(service_id=uuid.uuid4(), name='myservice', domains=self.domains_old, origins=self.origins_old, flavor_id='standard') self.service_old.provider_details = provider_details_old def test_update_add_domains_with_dns_exception(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() client = mock.Mock() client.find = mock.Mock( side_effect=Exception('DNS Exception')) self.controller.client = client domains_new = [domain.Domain('test.domain.com'), domain.Domain('blog.domain.com'), domain.Domain('pictures.domain.com')] service_updates = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'pictures.domain.com', 'href': u'pictures.domain.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] dns_details = self.controller.update(self.service_old, service_updates, responders) for responder in responders: for provider_name in responder: self.assertIsNotNone(dns_details[provider_name]['error']) self.assertIsNotNone( dns_details[provider_name]['error_detail']) self.assertIsNotNone( dns_details[provider_name]['error_class'] ) def test_update_add_domains_with_no_domains_in_update(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() client = mock.Mock() self.controller.client = client service_updates = service.Service( service_id=self.service_old.service_id, name='myservice', domains=[], origins=[], flavor_id='standard' ) responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'pictures.domain.com', 'href': u'pictures.domain.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] dns_details = self.controller.update( self.service_old, service_updates, responders ) access_urls_map = {} for provider_name in self.service_old.provider_details: provider_detail = self.service_old.provider_details[provider_name] access_urls = provider_detail.access_urls access_urls_map[provider_name] = {'access_urls': access_urls} self.assertEqual(access_urls_map, dns_details) def test_update_remove_domains_provider_error(self): domains_new = [domain.Domain('test.domain.com'), domain.Domain('blog.domain.com'), domain.Domain('pictures.domain.com')] service_new = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'error': 'Create service failed' } }] dns_details = self.controller.update(self.service_old, service_new, responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: if 'operator_url' in access_urls: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_old in self.domains_old: self.assertIsNotNone( access_urls_map[provider_name][domain_old.domain]) def test_update_remove_domains_with_subdomain_not_found_exception(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() client = mock.Mock() client.find = mock.Mock( side_effect=exc.NotFound('Subdomain not found')) records = [mock.Mock(), mock.Mock()] client.search_records = mock.Mock(return_value=records) self.controller.client = client domains_new = [domain.Domain('test.domain.com'), domain.Domain('blog.domain.com')] service_updates = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] dns_details = self.controller.update(self.service_old, service_updates, responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: if 'operator_url' in access_urls: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_new in domains_new: self.assertIsNotNone( access_urls_map[provider_name][domain_new.domain]) def test_update_remove_domains(self): domains_new = [domain.Domain('test.domain.com')] service_updates = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] dns_details = self.controller.update(self.service_old, service_updates, responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_new in domains_new: self.assertIsNotNone( access_urls_map[provider_name][domain_new.domain]) def test_update_same_domains(self): service_updates = service.Service( service_id=self.service_old.service_id, name='myservice', domains=self.domains_old, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] dns_details = self.controller.update(self.service_old, service_updates, responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: if 'operator_url' in access_urls: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_old in self.domains_old: self.assertIsNotNone( access_urls_map[provider_name][domain_old.domain]) def test_update_add_domains(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) domains_new = [domain.Domain('test.domain.com'), domain.Domain('blog.domain.com'), domain.Domain('pictures.domain.com')] service_new = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'pictures.domain.com', 'href': u'pictures.domain.com.global.prod.fastly.net', 'rel': 'access_url', 'certificate': 'san', 'old_operator_url': 'old.operator.url.cdn99.mycdn.com' } ]} }] dns_details = self.controller.update(self.service_old, service_new, responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_new in domains_new: self.assertIsNotNone( access_urls_map[provider_name][domain_new.domain]) def test_update_add_domains_http_to_https_upgrade(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) domains_new = [ domain.Domain('test.domain.com'), domain.Domain('blog.domain.com') ] self.service_old.domains = domains_new service_new = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url', 'certificate': 'san', 'old_operator_url': 'old.operator.url.cdn99.mycdn.com' } ]} }] dns_details = self.controller.update( self.service_old, service_new, responders ) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_new in domains_new: self.assertIsNotNone( access_urls_map[provider_name][domain_new.domain]) @mock.patch('re.match') def test_update_add_domains_https_upgrade_regex_exception(self, re_mock): re_mock.return_value.groups.return_value = (None,) subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) domains_new = [ domain.Domain('test.domain.com'), domain.Domain('blog.domain.com') ] self.service_old.domains = domains_new service_new = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url', 'certificate': 'san', 'old_operator_url': 'old.operator.url.cdn99.mycdn.com' } ]} }] dns_details = self.controller.update( self.service_old, service_new, responders ) self.assertTrue('error' in dns_details['Fastly']) self.assertTrue('error_detail' in dns_details['Fastly']) self.assertTrue('error_class' in dns_details['Fastly']) self.assertTrue('ValueError' in dns_details['Fastly']['error_class']) def test_update_add_domains_https_upgrade_create_cname_record(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() subdomain.find_record.side_effect = exc.DomainRecordNotFound( "Mock -- couldn't find cname record." ) self.client.find = mock.Mock(return_value=subdomain) domains_new = [ domain.Domain('test.domain.com'), domain.Domain('blog.domain.com') ] self.service_old.domains = domains_new service_new = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard') responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url', 'certificate': 'san', 'old_operator_url': 'old.operator.url.cdn99.mycdn.com' } ]} }] dns_details = self.controller.update( self.service_old, service_new, responders ) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) for responder in responders: for provider_name in responder: for domain_new in domains_new: self.assertIsNotNone( access_urls_map[provider_name][domain_new.domain]) def test_update_add_domains_keeps_log_delivery(self): subdomain = mock.Mock() subdomain.add_records = mock.Mock() self.client.find = mock.Mock(return_value=subdomain) domains_new = [domain.Domain('test.domain.com'), domain.Domain('blog.domain.com'), domain.Domain('pictures.domain.com')] service_new = service.Service( service_id=self.service_old.service_id, name='myservice', domains=domains_new, origins=[], flavor_id='standard', log_delivery=log_delivery.LogDelivery(enabled=True) ) self.service_old.log_delivery = log_delivery.LogDelivery(enabled=True) responders = [{ 'Fastly': { 'id': str(uuid.uuid4()), 'links': [ { 'domain': u'test.domain.com', 'href': u'test.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'blog.domain.com', 'href': u'blog.domain.com.global.prod.fastly.net', 'rel': 'access_url' }, { 'domain': u'pictures.domain.com', 'href': u'pictures.domain.com.global.prod.fastly.net', 'rel': 'access_url' } ]} }] dns_details = self.controller.update(self.service_old, service_new, responders) access_urls_map = {} for provider_name in dns_details: access_urls_map[provider_name] = {} access_urls_list = dns_details[provider_name]['access_urls'] for access_urls in access_urls_list: if 'operator_url' in access_urls: access_urls_map[provider_name][access_urls['domain']] = ( access_urls['operator_url']) if 'log_delivery' in access_urls: for ld_url in access_urls['log_delivery']: self.assertIsNotNone(ld_url['internalURL']) self.assertIsNotNone(ld_url['publicURL']) for responder in responders: for provider_name in responder: for domain_new in domains_new: self.assertIsNotNone( access_urls_map[provider_name][domain_new.domain]) def test_gather_cname_links_positive(self): cname_links = self.controller.gather_cname_links(self.service_old) # TODO(isaacm): Add assertions on the returned object self.assertIsNotNone(cname_links) def test_enable_positive(self): responder_enable = self.controller.enable(self.service_old) # TODO(isaacm): Add assertions on the returned object self.assertIsNotNone(responder_enable) def test_disable_positive(self): responder_disable = self.controller.disable(self.service_old) # TODO(isaacm): Add assertions on the returned object self.assertIsNotNone(responder_disable) def test_is_shard_full_shard_not_found(self): self.client.find.side_effect = exc.NotFound(404) self.assertTrue(self.controller.is_shard_full('shard_name')) def test_is_shard_full_false(self): find_mock = mock.Mock() find_mock.list_records.return_value = range(100) self.client.find.return_value = find_mock self.client.list_records_next_page.side_effect = exc.NoMoreResults self.assertFalse(self.controller.is_shard_full('shard_name')) def test_is_shard_full_true(self): find_mock = mock.Mock() find_mock.list_records.return_value = range(600) self.client.find.return_value = find_mock self.client.list_records_next_page.side_effect = exc.NoMoreResults self.assertTrue(self.controller.is_shard_full('shard_name')) def test_is_shard_full_paginate_true(self): find_mock = mock.Mock() find_mock.list_records.return_value = range(300) self.client.find.return_value = find_mock self.client.list_records_next_page.side_effect = [ range(300), exc.NoMoreResults, ] self.assertTrue(self.controller.is_shard_full('shard_name'))

37.44398

79

0.533305

4,446

44,783

5.123482

0.061404

0.067167

0.02454

0.028359

0.86549

0.854691

0.83195

0.813995

0.809298

0.798894

0

0.003234

0.364692

44,783

1,195

80

37.475314

0.797406

0.015877

0

0.720976

0

0.156036

0.052163

0

0.000837

0.043902

1

0.03122

false

0

0.009756

0

0.043902

0

null

0

1

0

1

0

null

0

7

5f27f43884fce687470a5e727a23465a2a2a3ef2

147

py

Python

examples/hex/ex3.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/hex/ex3.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

examples/hex/ex3.py

mcorne/python-by-example

15339c0909c84b51075587a6a66391100971c033

[ "MIT" ]

null

print('%#x' % 255, '%x' % 255, '%X' % 255) print(format(255, '#x'), format(255, 'x'), format(255, 'X')) print(f'{255:#x}', f'{255:x}', f'{255:X}')

36.75

60

0.489796

27

147

2.666667

0.185185

0.444444

0.416667

0.222222

0.625

0

0.209302

0.122449

147

3

61

49

0.348837

0

0.22449

0

1

0

true

0

1

0

null

1

0

1

0

1

0

1

0

null

0

1

0

1

0

9

a065ee8b24c553119b40cb3d0cce2fc958533eb0

2,261

py

Python

src/profiles/models.py

salemzii/ChopFast

95ea88387ecfdb56bd643970b69425b1a1c6f388

[ "MIT" ]

null

src/profiles/models.py

salemzii/ChopFast

95ea88387ecfdb56bd643970b69425b1a1c6f388

[ "MIT" ]

null

src/profiles/models.py

salemzii/ChopFast

95ea88387ecfdb56bd643970b69425b1a1c6f388

[ "MIT" ]

null

from django.db import models from PIL import Image from django.contrib.auth.models import User import uuid class Customer(models.Model): id = models.UUIDField( default=uuid.uuid4, primary_key=True, editable=False ) user = models.OneToOneField(User, on_delete=models.CASCADE) image= models.ImageField(default = 'default.jpg', blank=True, upload_to='profile_pics') address = models.CharField(max_length=75) phone_number = models.IntegerField(default=0000, null=True, blank=True) def __str__(self): template = f"{self.user.username}'s profile." return template.format(self) class Rider(models.Model): id = models.UUIDField( default=uuid.uuid4, primary_key= True, editable=False ) user = models.OneToOneField(User, on_delete=models.CASCADE) image = models.ImageField(default= 'default.jpg', upload_to='profile_pics') address = models.CharField(max_length=75) is_active = models.BooleanField(default=False) phone_number = models.IntegerField(default=0000, null=True, blank=True) def __str__(self): template = f"{self.user.username}'s profile." return template.format(self) class Staff(models.Model): id = models.UUIDField( default=uuid.uuid4, primary_key=True, editable=False ) user = models.OneToOneField(User, on_delete=models.CASCADE) image = models.ImageField(default='default.jpg', upload_to='profile_pics') address = models.CharField(max_length=75) is_active = models.BooleanField(default=False) phone_number = models.IntegerField(default=0000, null=True, blank=True) def __str__(self): template = f"{self.user.username}'s profile." return template.format(self) class Supplier(models.Model): user = models.OneToOneField(User, on_delete=models.CASCADE) name = models.CharField(max_length=120, unique=True) address = models.CharField(max_length=220) phone_number = models.IntegerField(default=0000, null=True, blank=True) created_date = models.DateField(auto_now_add=True) def __str__(self): template = f"{self.user.username}'s profile." return template.format(self) # Create your models here.

31.84507

91

0.698806

283

2,261

5.431095

0.254417

0.029278

0.058556

0.078074

0.843852

0.823683

0.792453

0

0.016885

0.18797

2,261

70

92

32.3

0.820261

0.010615

0

0.722222

0

0.086353

0.039374

0

1

0.074074

false

0

0.074074

0

0.703704

0

null

0

1

0

1

0

null

0

1

0

8

264b0ecae9b9970237b7924c1887171bc8093929

8,319

py

Python

tracklib/filter/eof.py

xueyuelei/tracklib

d33912baf1bebd1605d5e9c8dfc31484c96628cc

[ "MIT" ]

5

2020-03-04T11:36:19.000Z

2020-06-21T16:49:45.000Z

tracklib/filter/eof.py

xueyuelei/tracklib

d33912baf1bebd1605d5e9c8dfc31484c96628cc

[ "MIT" ]

null

tracklib/filter/eof.py

xueyuelei/tracklib

d33912baf1bebd1605d5e9c8dfc31484c96628cc

[ "MIT" ]

null

# -*- coding: utf-8 -*- ''' Extended object tracker REFERENCE: [1]. ''' from __future__ import division, absolute_import, print_function __all__ = ['KochEOFilter', 'FeldmannEOFilter', 'LanEOFilter'] import numpy as np import scipy.linalg as lg from .base import EOFilterBase class KochEOFilter(EOFilterBase): ''' Extended object particle filter using Koch approach ''' def __init__(self, F, H, D, interval, tau, dim=2): self._F = F.copy() self._H = H.copy() self._D = D.copy() self._at = np.exp(-interval / tau) # attenuation factor self._dim = dim def init(self, state, cov, df, extension): self._df = df self._scale = extension * (df - self._dim - 1) self._single_cov = cov.copy() self._state = state.copy() self._cov = np.kron(extension, cov) self._ext = extension.copy() self._init = True def predict(self): if self._init == False: raise RuntimeError('filter must be initialized with init() before use') # predict inverse wishart parameters df = self._df self._df = self._at * self._df w = (self._df - self._dim - 1) / (df - self._dim - 1) self._scale = w * self._scale # predict joint state self._ext = self._scale / (self._df - self._dim - 1) * 2 self._single_cov = self._F @ self._single_cov @ self._F.T + self._D self._single_cov = (self._single_cov + self._single_cov.T) / 2 df_tilde = self._df + len(self._state) // self._dim + len(self._state) self._cov = np.kron(self._ext, self._single_cov) / (df_tilde - 2) F_tilde = np.kron(np.eye(self._dim), self._F) self._state = np.dot(F_tilde, self._state) return self._state, self._cov, self._ext def correct(self, zs): if self._init == False: raise RuntimeError('filter must be initialized with init() before use') n = len(zs) z_mean = np.mean(zs, axis=0) eps = z_mean - np.dot(np.kron(np.eye(self._dim), self._H), self._state) z_center = zs - z_mean Z = np.dot(z_center.T, z_center) S = self._H @ self._single_cov @ self._H.T + 1 / n S = (S + S.T) / 2 S_inv = lg.inv(S) K = self._single_cov @ self._H.T @ S_inv N = S_inv * np.outer(eps, eps) # correct inverse wishart parameters self._df += n self._scale += N + Z # correct joint state self._ext = self._scale / (self._df - self._dim - 1) * 2 self._single_cov -= K @ S @ K.T self._single_cov = (self._single_cov + self._single_cov.T) / 2 df_tilde = self._df + len(self._state) // self._dim + len(self._state) self._cov = np.kron(self._ext, self._single_cov) / (df_tilde - 2) K_tilde = np.kron(np.eye(self._dim), K) self._state += np.dot(K_tilde, eps) return self._state, self._cov, self._ext def distance(self, zs, **kwargs): return super().distance(zs, **kwargs) def likelihood(self, zs, **kwargs): return super().likelihood(zs, **kwargs) class FeldmannEOFilter(EOFilterBase): ''' Extended object particle filter using Feldmann approach ''' def __init__(self, F, H, Q, R, interval, tau, dim=2): self._F = F.copy() self._H = H.copy() self._Q = Q.copy() self._R = R.copy() self._at = np.exp(-interval / tau) # attenuation self._dim = dim def init(self, state, cov, df, extension): self._df = df - self._dim - 1 self._state = state.copy() self._cov = cov.copy() self._ext = extension.copy() self._init = True def predict(self): if self._init == False: raise RuntimeError('filter must be initialized with init() before use') self._state = np.dot(self._F, self._state) self._cov = self._F @ self._cov @ self._F.T + self._Q self._cov = (self._cov + self._cov.T) / 2 self._ext = self._ext self._df = 2 + self._at * (self._df - 2) return self._state, self._cov, self._ext def correct(self, zs): if self._init == False: raise RuntimeError('filter must be initialized with init() before use') n = len(zs) z_mean = np.mean(zs, axis=0) eps = z_mean - np.dot(self._H, self._state) z_center = zs - z_mean Z = np.dot(z_center.T, z_center) Y = self._ext / 4 + self._R S = self._H @ self._cov @ self._H.T + Y / n S = (S + S.T) / 2 X_chol = lg.cholesky(self._ext, lower=True) S_chol = lg.inv(lg.cholesky(S, lower=True)) Y_chol = lg.inv(lg.cholesky(Y, lower=True)) N = np.outer(eps, eps) N_hat = X_chol @ S_chol @ N @ S_chol.T @ X_chol.T Z_hat = X_chol @ Y_chol @ Z @ Y_chol.T @ X_chol.T df = self._df self._df += n self._ext = (df * self._ext + N_hat + Z_hat) / self._df K = self._cov @ self._H.T @ lg.inv(S) self._state += K @ eps self._cov -= K @ S @ K.T self._cov = (self._cov + self._cov.T) / 2 return self._state, self._cov, self._ext def distance(self, zs, **kwargs): return super().distance(zs, **kwargs) def likelihood(self, zs, **kwargs): return super().likelihood(zs, **kwargs) class LanEOFilter(EOFilterBase): ''' Extended object particle filter using Lan approach ''' def __init__(self, F, H, D, R, delta, dim=2): self._F = F.copy() self._H = H.copy() self._D = D.copy() self._R = R.copy() self._delta = delta self._dim = dim def init(self, state, cov, df, extension): self._df = df self._scale = extension * (df - 2 * self._dim - 2) self._single_cov = cov.copy() self._state = state.copy() self._cov = np.kron(extension, cov) self._ext = extension.copy() self._init = True def predict(self): if self._init == False: raise RuntimeError('filter must be initialized with init() before use') # predict inverse wishart parameters lamb = self._df - 2 * self._dim - 2 self._df = 2 * self._delta * (lamb + 1) * (lamb - 1) * (lamb - 2) / lamb**2 / (lamb + self._delta) + 2 * self._dim + 4 self._scale = (self._df - 2 * self._dim - 2) / lamb * self._scale # predict joint state self._ext = self._scale / (self._df - 2 * self._dim - 2) self._single_cov = self._F @ self._single_cov @ self._F.T + self._D self._single_cov = (self._single_cov + self._single_cov.T) / 2 self._cov = np.kron(self._ext, self._single_cov) F_tilde = np.kron(np.eye(self._dim), self._F) self._state = np.dot(F_tilde, self._state) return self._state, self._cov, self._ext def correct(self, zs): if self._init == False: raise RuntimeError('filter must be initialized with init() before use') n = len(zs) z_mean = np.mean(zs, axis=0) eps = z_mean - np.dot(np.kron(np.eye(self._dim), self._H), self._state) z_center = zs - z_mean Z = np.dot(z_center.T, z_center) B = lg.cholesky(self._ext / 4 + self._R, lower=True) @ lg.inv(lg.cholesky(self._ext, lower=True)) B_inv = lg.inv(B) S = self._H @ self._single_cov @ self._H.T + lg.det(B)**(2 / self._dim) / n S = (S + S.T) / 2 S_inv = lg.inv(S) K = self._single_cov @ self._H.T @ S_inv N = S_inv * np.outer(eps, eps) # correct inverse wishart parameters self._df += n self._scale += N + B_inv @ Z @ B_inv.T # correct joint state self._ext = self._scale / (self._df - 2 * self._dim - 2) self._single_cov -= K @ S @ K.T self._single_cov = (self._single_cov + self._single_cov.T) / 2 self._cov = np.kron(self._ext, self._single_cov) K_tilde = np.kron(np.eye(self._dim), K) self._state += np.dot(K_tilde, eps) return self._state, self._cov, self._ext def distance(self, zs, **kwargs): return super().distance(zs, **kwargs) def likelihood(self, zs, **kwargs): return super().likelihood(zs, **kwargs)

34.094262

126

0.57002

1,217

8,319

3.635168

0.091208

0.050633

0.082278

0.061483

0.859855

0.810805

0.750678

0.736438

0.703888

0.688969

0

0.008482

0.291381

8,319

244

127

34.094262

0.741985

0.056978

0

0.730994

0

0.042786

0

1

0.105263

false

0

0.023392

0.035088

0.216374

0.005848

0

null

0

1

0

1

0

null

0

7

cd8e57ac75b8fc835d98e3e37b98001007a129ed

64

py

Python

far_ws/src/follow_ahead_rl/gym-gazeboros_ac/gym_gazeboros_ac/envs/__init__.py

Evoiis/Robot-Follow-Ahead-with-Obstacle-Avoidance

72a407eafc7cdebf0639314c4f4ad0dd6902e6e8

[ "Unlicense" ]

null

far_ws/src/follow_ahead_rl/gym-gazeboros_ac/gym_gazeboros_ac/envs/__init__.py

Evoiis/Robot-Follow-Ahead-with-Obstacle-Avoidance

72a407eafc7cdebf0639314c4f4ad0dd6902e6e8

[ "Unlicense" ]

5

2021-03-26T01:30:13.000Z

2021-04-22T22:19:03.000Z

far_ws/src/follow_ahead_rl/gym-gazeboros_ac/gym_gazeboros_ac/envs/__init__.py

Evoiis/Robot-Follow-Ahead-with-Obstacle-Avoidance

72a407eafc7cdebf0639314c4f4ad0dd6902e6e8

[ "Unlicense" ]

1

2021-05-05T00:57:43.000Z

from gym_gazeboros_ac.envs.gym_gazeboros_ac import GazeborosEnv

32

63

0.90625

10

64

5.4

0.7

0.444444

0.518519

0

0.0625

64

1

64

0.9

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

26d5e1ed72788d66763e45cc45bd38bc17536e23

204

py

Python

cfpq_data/grammars/__init__.py

viabzalov/CFPQ_Data

67239c876897d04ba2f4ef88a75fd4a38a494efa

[ "Apache-2.0" ]

8

2020-03-30T17:47:31.000Z

2022-01-27T13:36:39.000Z

cfpq_data/grammars/__init__.py

viabzalov/CFPQ_Data

67239c876897d04ba2f4ef88a75fd4a38a494efa

[ "Apache-2.0" ]

27

2019-10-21T09:31:08.000Z

2021-11-07T03:19:15.000Z

cfpq_data/grammars/__init__.py

viabzalov/CFPQ_Data

67239c876897d04ba2f4ef88a75fd4a38a494efa

[ "Apache-2.0" ]

14

2019-10-18T12:49:47.000Z

2021-08-03T14:20:17.000Z

from cfpq_data.grammars.rsm import * from cfpq_data.grammars.converters import * from cfpq_data.grammars.readwrite import * from cfpq_data.grammars.utils import * from cfpq_data.grammars.samples import *

34

43

0.828431

30

204

5.466667

0.333333

0.243902

0.365854

0.609756

0.634146

0

0.098039

204

5

44

40.8

0.891304

0

1

0

true

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

7

f808b8c639083159139ce82f99d8c0d34a5eed1c

90

py

Python

irl/common/utils/__init__.py

uidilr/deepirl_chainer

45f6134fe457bdae1484e4847ab0701f39940faa

[ "MIT" ]

16

2019-06-25T11:54:38.000Z

2022-02-13T15:14:40.000Z

irl/common/utils/__init__.py

uidilr/deepirl_chainer

45f6134fe457bdae1484e4847ab0701f39940faa

[ "MIT" ]

4

2019-07-17T15:17:25.000Z

2020-09-03T12:12:16.000Z

irl/common/utils/__init__.py

uidilr/deepirl_chainer

45f6134fe457bdae1484e4847ab0701f39940faa

[ "MIT" ]

3

2019-07-17T16:45:07.000Z

2020-12-15T16:52:26.000Z

from irl.common.utils.get_states_actions_next_states import get_states_actions_next_states

90

0.933333

15

90

5.066667

0.6

0.236842

0.421053

0.526316

0.684211

0

0.033333

90

1

90

0.873563

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

8

f854c848f0ceea8af78f78036033e62f2cd92a68

8,157

py

Python

tools/97_addons/webhook-python/webhook/webhookapp/functions.py

niklaushirt/aiops-install-awx-33

a062656b39ffa6c37b4aa510e79a811de2d0a3c0

[ "IBM-pibs" ]

null

tools/97_addons/webhook-python/webhook/webhookapp/functions.py

niklaushirt/aiops-install-awx-33

a062656b39ffa6c37b4aa510e79a811de2d0a3c0

[ "IBM-pibs" ]

null

tools/97_addons/webhook-python/webhook/webhookapp/functions.py

niklaushirt/aiops-install-awx-33

a062656b39ffa6c37b4aa510e79a811de2d0a3c0

[ "IBM-pibs" ]

null

import requests from requests.auth import HTTPBasicAuth import json import datetime import random import os ITERATE_ELEMENT=os.environ.get('ITERATE_ELEMENT') DEBUG=os.environ.get('WEBHOOK_DEBUG') EVENT_MAPPING=os.environ.get('EVENT_MAPPING') EVENT_TEMPLATE=os.environ.get('EVENT_TEMPLATE') print (' ------------------------------------------------------------------------------------------------') print (' 📛 TEST') # ---------------------------------------------------------------------------------------------------------------------------------------------------- # INJECT EVENTS IN ARRAY # ---------------------------------------------------------------------------------------------------------------------------------------------------- def injectEvents(DATALAYER_ROUTE,DATALAYER_USER,DATALAYER_PWD,REQUEST,DEBUG): print('') print (' ------------------------------------------------------------------------------------------------') print (' 📛 Inject Events') body_unicode = REQUEST.body.decode('utf-8') body = json.loads(body_unicode) if DEBUG=='true': print('**************************************************************************************') print('**************************************************************************************') print('DEBUG PAYLOAD') print('') print(str(body)) print('**************************************************************************************') print('DEBUG EVENT_TEMPLATE') print('') print(str(EVENT_TEMPLATE)) print('**************************************************************************************') print('DEBUG EVENT_MAPPING') print('') print(str(EVENT_MAPPING)) print('**************************************************************************************') print('**************************************************************************************') events = body[ITERATE_ELEMENT] for event in events: payload=EVENT_TEMPLATE mappingelements=EVENT_MAPPING.split(';') for line in mappingelements: line=line.strip() elements=line.split(',') if DEBUG=='true': print('Mapping Line:'+str(line)) actInputKey = elements[0].strip() actOutputKey = elements[1].strip() if actInputKey in event: actValue = str(event[actInputKey]).strip() if DEBUG=='true': print(' 📥 actInputKey:'+str(actInputKey)) print(' 💾 actOutputKey:'+str(actOutputKey)) print(' ✅ actValue:'+str(actValue)) payload=payload.replace('@@'+str(actOutputKey),actValue) else: if DEBUG=='true': print(' ❗ Input field missing - Setting empty:'+str(actOutputKey)) if 'EXPIRY' in actOutputKey: payload=payload.replace('@@'+str(actOutputKey),'600000') elif'override_with_date' in actInputKey: timestamp = datetime.datetime.now() MY_TIMESTAMP_FORMATTED = timestamp.strftime("%Y-%m-%dT%H:%M:%S.000Z") payload=payload.replace('@@'+str(actOutputKey),str(MY_TIMESTAMP_FORMATTED)) else: payload=payload.replace('@@'+str(actOutputKey),'') if DEBUG=='true': print ('PAYLOAD FINAL'+str(payload)) #timestamp = str(datetime.datetime.now()) #+%Y-%m-%dT%H:%M:%S url = 'https://'+DATALAYER_ROUTE+'/irdatalayer.aiops.io/active/v1/events' auth=HTTPBasicAuth(DATALAYER_USER, DATALAYER_PWD) headers = {'Content-Type': 'application/json', 'Accept-Charset': 'UTF-8', 'x-username' : 'admin', 'x-subscription-id' : 'cfd95b7e-3bc7-4006-a4a8-a73a79c71255'} response = requests.post(url, data=str(payload), headers=headers, auth=auth)#, verify=False) print (' RESULT:'+str(response.content)) print ('') print ('') print ('') #print(events) print (' ✅ Inject Events') print (' ------------------------------------------------------------------------------------------------') print ('') print ('') print ('') return 'OK' # ---------------------------------------------------------------------------------------------------------------------------------------------------- # INJECT SingleEVENTS # ---------------------------------------------------------------------------------------------------------------------------------------------------- def injectEventsSingle(DATALAYER_ROUTE,DATALAYER_USER,DATALAYER_PWD,REQUEST,DEBUG): print('') print (' ------------------------------------------------------------------------------------------------') print (' 📛 Inject Events Single') body_unicode = REQUEST.body.decode('utf-8') body = json.loads(body_unicode) if DEBUG=='true': print('**************************************************************************************') print('**************************************************************************************') print('DEBUG PAYLOAD') print('') print(str(body)) print('**************************************************************************************') print('DEBUG EVENT_TEMPLATE') print('') print(str(EVENT_TEMPLATE)) print('**************************************************************************************') print('DEBUG EVENT_MAPPING') print('') print(str(EVENT_MAPPING)) print('**************************************************************************************') print('**************************************************************************************') payload=EVENT_TEMPLATE event = body mappingelements=EVENT_MAPPING.split(';') for line in mappingelements: line=line.strip() elements=line.split(',') if DEBUG=='true': print('Mapping Line:'+str(line)) actInputKey = elements[0].strip() actOutputKey = elements[1].strip() if actInputKey in event: actValue = str(event[actInputKey]).strip() if DEBUG=='true': print(' 📥 actInputKey:'+str(actInputKey)) print(' 💾 actOutputKey:'+str(actOutputKey)) print(' ✅ actValue:'+str(actValue)) payload=payload.replace('@@'+str(actOutputKey),actValue) else: if DEBUG=='true': print(' ❗ Input field missing - Setting empty:'+str(actOutputKey)) if 'EXPIRY' in actOutputKey: payload=payload.replace('@@'+str(actOutputKey),'600000') elif'override_with_date' in actInputKey: timestamp = datetime.datetime.now() MY_TIMESTAMP_FORMATTED = timestamp.strftime("%Y-%m-%dT%H:%M:%S.000Z") payload=payload.replace('@@'+str(actOutputKey),str(MY_TIMESTAMP_FORMATTED)) else: payload=payload.replace('@@'+str(actOutputKey),'') if DEBUG=='true': print ('PAYLOAD FINAL'+str(payload)) #timestamp = str(datetime.datetime.now()) #+%Y-%m-%dT%H:%M:%S url = 'https://'+DATALAYER_ROUTE+'/irdatalayer.aiops.io/active/v1/events' auth=HTTPBasicAuth(DATALAYER_USER, DATALAYER_PWD) headers = {'Content-Type': 'application/json', 'Accept-Charset': 'UTF-8', 'x-username' : 'admin', 'x-subscription-id' : 'cfd95b7e-3bc7-4006-a4a8-a73a79c71255'} response = requests.post(url, data=str(payload), headers=headers, auth=auth)#, verify=False) print (' RESULT:'+str(response.content)) print ('') print ('') print ('') #print(events) print (' ✅ Inject Events') print (' ------------------------------------------------------------------------------------------------') print ('') print ('') print ('') return 'OK'

39.597087

167

0.414613

615

8,157

5.442276

0.188618

0.098596

0.05378

0.047804

0.874813

0

0.01062

0.21503

8,157

205

168

39.790244

0.510073

0.099301

0

0.875862

0

0.345891

0.232596

0

1

0.013793

false

0

0.041379

0

0.068966

0.468966

0

null

0

1

0

1

0

null

0

1

0

8

f8b684072e405127024e3106ddedd40820aee116

13,581

py

Python

backend/tests/test_validation.py

ScilifelabDataCentre/project_portal

a274e9e8ac2f92972a240154afd73e6137bec9db

[ "BSD-3-Clause" ]

2

2021-03-26T11:50:27.000Z

2022-02-24T20:18:44.000Z

backend/tests/test_validation.py

ScilifelabDataCentre/project_portal

a274e9e8ac2f92972a240154afd73e6137bec9db

[ "BSD-3-Clause" ]

120

2020-03-19T21:35:57.000Z

2022-03-11T19:06:58.000Z

backend/tests/test_validation.py

ScilifelabDataCentre/Data-Tracker

978f518ff91e0d7689b63d18fc280b8ef283c294

[ "BSD-3-Clause" ]

null

"""Tests for validation functions.""" import uuid import pytest # avoid pylint errors because of fixtures # pylint: disable = redefined-outer-name, unused-import from helpers import mdb import validate def test_validate_affiliation(): """Confirm that only valid strings are accepted.""" validator = validate.VALIDATION_MAPPER["affiliation"] assert validator("Test") assert validator("") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_auth_ids(): """Confirm that only valid lists of strings are accepted.""" validator = validate.VALIDATION_MAPPER["auth_ids"] assert validator([]) assert validator(["Test"]) assert validator(["Test", "Test 2"]) with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator("asd") with pytest.raises(ValueError): validator([1, 2, 3, 4]) with pytest.raises(ValueError): validator(4.5) def test_validate_authors(mdb): """Confirm that only valid users are accepted.""" validator = validate.VALIDATION_MAPPER["authors"] test_users = [str(entry["_id"]) for entry in mdb["users"].aggregate([{"$sample": {"size": 5}}])] assert validator([], db=mdb) assert validator(test_users, db=mdb) assert validator(test_users[:1], db=mdb) with pytest.raises(ValueError): validator(test_users[0], db=mdb) with pytest.raises(ValueError): validator([str(uuid.uuid4()) for _ in range(4)], db=mdb) with pytest.raises(ValueError): validator(5, db=mdb) with pytest.raises(ValueError): validator("asd", db=mdb) with pytest.raises(ValueError): validator([1, 2, 3, 4], db=mdb) with pytest.raises(ValueError): validator(4.5, db=mdb) def test_validate_contact(): """Confirm that only valid strings are accepted.""" validator = validate.VALIDATION_MAPPER["contact"] assert validator("Test") assert validator("") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_datasets(mdb): """Confirm that only valid users are accepted.""" validator = validate.VALIDATION_MAPPER["datasets"] test_datasets = [ str(entry["_id"]) for entry in mdb["datasets"].aggregate([{"$sample": {"size": 5}}]) ] assert validator([], db=mdb) assert validator(test_datasets, db=mdb) assert validator(test_datasets[:1], db=mdb) with pytest.raises(ValueError): validator(test_datasets[0], db=mdb) with pytest.raises(ValueError): validator([str(uuid.uuid4()) for _ in range(4)], db=mdb) with pytest.raises(ValueError): validator(["not_an_uuid"], db=mdb) with pytest.raises(ValueError): validator(5, db=mdb) with pytest.raises(ValueError): validator("asd", db=mdb) with pytest.raises(ValueError): validator([1, 2, 3, 4], db=mdb) with pytest.raises(ValueError): validator(4.5, db=mdb) def test_validate_description(): """Confirm that only valid strings are accepted.""" validator = validate.VALIDATION_MAPPER["description"] assert validator("Test") assert validator("") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_editors(mdb): """Confirm that only valid users are accepted.""" validator = validate.VALIDATION_MAPPER["editors"] test_users = [str(entry["_id"]) for entry in mdb["users"].aggregate([{"$sample": {"size": 5}}])] assert validator(test_users, db=mdb) assert validator(test_users[:1], db=mdb) with pytest.raises(ValueError): validator(test_users[0], db=mdb) with pytest.raises(ValueError): validator([str(uuid.uuid4()) for _ in range(4)], db=mdb) with pytest.raises(ValueError): validator(["invalid_uuid"], db=mdb) with pytest.raises(ValueError): validator(5, db=mdb) with pytest.raises(ValueError): validator("asd", db=mdb) with pytest.raises(ValueError): validator([1, 2, 3, 4], db=mdb) with pytest.raises(ValueError): validator(4.5, db=mdb) def test_validate_email(): """Confirm that "only" valid emails are accepted.""" validator = validate.VALIDATION_MAPPER["email"] assert validator("") assert validator("test@example.com") assert validator("test.name@sub.example.com") with pytest.raises(ValueError): validator("test@localhost") with pytest.raises(ValueError): validator("test@localhost@localhost.com") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator("asd") with pytest.raises(ValueError): validator([1, 2, 3, 4]) with pytest.raises(ValueError): validator(4.5) def test_validate_field(): """Confirm that the correct validation is run.""" validator = validate.validate_field assert validator("permissions", ["DATA_EDIT"], testing=True) assert validator("name", "Test", testing=True) assert not validator("permissions", "DATA_EDIT", testing=True) assert not validator("bad_key", [], testing=True) def test_validate_generators(mdb): """Confirm that only valid users are accepted.""" validator = validate.VALIDATION_MAPPER["editors"] test_users = [str(entry["_id"]) for entry in mdb["users"].aggregate([{"$sample": {"size": 5}}])] assert validator([], db=mdb) assert validator(test_users, db=mdb) assert validator(test_users[:1], db=mdb) with pytest.raises(ValueError): validator(test_users[0], db=mdb) with pytest.raises(ValueError): validator([str(uuid.uuid4()) for _ in range(4)], db=mdb) with pytest.raises(ValueError): validator(["invalid_uuid"], db=mdb) with pytest.raises(ValueError): validator(5, db=mdb) with pytest.raises(ValueError): validator("asd", db=mdb) with pytest.raises(ValueError): validator([1, 2, 3, 4], db=mdb) with pytest.raises(ValueError): validator(4.5, db=mdb) def test_validate_name(): """Confirm that only valid strings are accepted.""" validator = validate.VALIDATION_MAPPER["name"] assert validator("Test") assert validator("Test Name") with pytest.raises(ValueError): assert validator("") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_orcid(): """Confirm that only valid orcids are accepted.""" validator = validate.VALIDATION_MAPPER["orcid"] assert validator("0123-4567-8901-2345") assert validator("9999-9999-9999-9999") with pytest.raises(ValueError): validator({}) with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) with pytest.raises(ValueError): validator("999F-9999-9999-9999") with pytest.raises(ValueError): validator("1234-") with pytest.raises(ValueError): validator("1234-6789") def test_validate_organisation(mdb): """Confirm that only valid users are accepted.""" validator = validate.VALIDATION_MAPPER["organisation"] test_users = [str(entry["_id"]) for entry in mdb["users"].aggregate([{"$sample": {"size": 5}}])] assert validator("", db=mdb) assert validator(test_users[0], db=mdb) assert validator(test_users[4], db=mdb) with pytest.raises(ValueError): validator(test_users, db=mdb) with pytest.raises(ValueError): validator(test_users[:1], db=mdb) with pytest.raises(ValueError): validator([str(uuid.uuid4()) for _ in range(4)], db=mdb) with pytest.raises(ValueError): validator(str(uuid.uuid4()), db=mdb) with pytest.raises(ValueError): validator(5, db=mdb) with pytest.raises(ValueError): validator("asd", db=mdb) with pytest.raises(ValueError): validator([1, 2, 3, 4], db=mdb) with pytest.raises(ValueError): validator(4.5, db=mdb) def test_validate_permissions(): """Confirm that only valid permission lists are accepted.""" validator = validate.VALIDATION_MAPPER["permissions"] assert validator(["DATA_EDIT"]) assert validator(["DATA_EDIT", "USER_MANAGEMENT"]) assert validator([]) with pytest.raises(ValueError): validator(["DATA_EDIT", "USER_MANAGEMENT", "DATA_EDIT"]) with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator([1, 2, 3]) with pytest.raises(ValueError): validator(["DATA_EDIT", 2, 3]) with pytest.raises(ValueError): validator("DATA_EDIT") with pytest.raises(ValueError): validator({}) with pytest.raises(ValueError): validator(["BAD_PERMISSION"]) with pytest.raises(ValueError): validator(("DATA_EDIT",)) with pytest.raises(ValueError): validator(4.5) def test_validate_properties(): """Confirm that only valid key:value pairs are accepted.""" validator = validate.VALIDATION_MAPPER["properties"] assert validator({}) assert validator({"key": "value"}) assert validator({"long key": "long value"}) assert validator( { "key": "value", "key2": "value2", "key3": "value3", "key4": "value4", "long key": "long value", } ) with pytest.raises(ValueError): assert validator({"ke": "value"}) with pytest.raises(ValueError): assert validator({"key": "va"}) with pytest.raises(ValueError): assert validator({"key": " value"}) with pytest.raises(ValueError): assert validator({"key": "value "}) with pytest.raises(ValueError): assert validator({" key": "value"}) with pytest.raises(ValueError): assert validator({"key ": "value"}) with pytest.raises(ValueError): assert validator({1: "value"}) with pytest.raises(ValueError): assert validator({"key": 1}) with pytest.raises(ValueError): assert validator(["tag"]) with pytest.raises(ValueError): assert validator("") with pytest.raises(ValueError): assert validator([]) with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_tags(): """Confirm that only valid tags are accepted.""" validator = validate.VALIDATION_MAPPER["tags"] assert validator([]) assert validator(["test"]) assert validator(["test", "test2"]) with pytest.raises(ValueError): assert validator({}) with pytest.raises(ValueError): assert validator([""]) with pytest.raises(ValueError): assert validator([" tag"]) with pytest.raises(ValueError): assert validator(["tag "]) with pytest.raises(ValueError): assert validator(["ta"]) with pytest.raises(ValueError): assert validator([0]) with pytest.raises(ValueError): assert validator([0, 1, 2, 3]) with pytest.raises(ValueError): assert validator("") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_title(): """Confirm that only valid strings are accepted.""" validator = validate.VALIDATION_MAPPER["title"] assert validator("Test") assert validator("Test With more WORdS") with pytest.raises(ValueError): assert validator("") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5) def test_validate_url(): """Confirm that urls start with http(s)://.""" validator = validate.VALIDATION_MAPPER["url"] assert validator("") assert validator("https://www.example.com/folder") assert validator("http://www.example.com/folder") assert validator("http://localhost") with pytest.raises(ValueError): validator("RandomTexthttps://www.example.com/folder") with pytest.raises(ValueError): validator("http:/") with pytest.raises(ValueError): validator("https:/") with pytest.raises(ValueError): validator("ftp://localhost") with pytest.raises(ValueError): validator("Test With more WORdS") with pytest.raises(ValueError): validator(5) with pytest.raises(ValueError): validator(["asd"]) with pytest.raises(ValueError): validator(("asd",)) with pytest.raises(ValueError): validator(4.5)

31.4375

100

0.646123

1,555

13,581

5.576206

0.082958

0.136086

0.217737

0.353823

0.8608

0.83589

0.780417

0.714681

0.684119

0.658286

0

0.017259

0.210736

13,581

431

101

31.510441

0.791678

0.070687

0

0.695015

0

0.082482

0.004232

0

0.208211

1

0.052786

false

0

0.01173

0

0.064516

0

null

0

1

0

1

0

null

0

7