xszheng2020/the_stack_dedup_python_hits_4 · Datasets at Hugging Face

30887643e6689cf6b0d777ea6dc7288adf88b8bd

93

py

Python

displaymanagement/model_descriptors/screen_size.py

evocount/display-management

c4f58f6653f3457396e44b8c6dc97636b18e8d8a

[ "MIT" ]

1

2021-03-28T22:05:10.000Z

displaymanagement/model_descriptors/screen_size.py

evocount/display-management

c4f58f6653f3457396e44b8c6dc97636b18e8d8a

[ "MIT" ]

1

2021-04-05T19:39:56.000Z

displaymanagement/model_descriptors/screen_size.py

evocount/display-management

c4f58f6653f3457396e44b8c6dc97636b18e8d8a

[ "MIT" ]

null

from pydantic import BaseModel class ScreenSize(BaseModel): width: int height: int

13.285714

30

0.731183

11

93

6.181818

0.818182

0

0.215054

93

6

31

15.5

0.931507

0

1

0

true

0

0.25

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

30ad98dd926285ea6ada4a0ce1dd5c6f44f8b7ea

563

py

Python

user_external_data_utils.py

IA-Cardiologia-husa/KoopaML

537b65eb016cfc86b381842928443a2d2badee8f

[ "Apache-2.0" ]

null

user_external_data_utils.py

IA-Cardiologia-husa/KoopaML

537b65eb016cfc86b381842928443a2d2badee8f

[ "Apache-2.0" ]

4

2020-03-24T17:46:02.000Z

2021-08-23T20:22:34.000Z

user_external_data_utils.py

IA-Cardiologia-husa/KoopaML

537b65eb016cfc86b381842928443a2d2badee8f

[ "Apache-2.0" ]

null

#Import libraries from user_data_utils import clean_database, process_database, fillna_database,preprocess_filtered_database import pandas as pd def load_external_database(): # df = pd.read_excel("External Database.xlsx") return df def clean_external_database(df): df = clean_database(df) return df def process_external_database(df): df = process_database(df) return df def fillna_external_database(df): df=fillna_database(df) return df def preprocess_filtered_external_database(df, wf_name): df=preprocess_filtered_database(df, wf_name) return df

23.458333

106

0.817052

83

563

5.228916

0.301205

0.207373

0.138249

0.145161

0

0.110124

563

23

107

24.478261

0.866267

0.108348

0

0.3125

0

1

0.3125

false

0

0.125

0.0625

0.75

0

null

1

0

null

0

1

0

1

0

4

30ba003199a21c7c6ed28692d6642fba39bc60b7

3,646

py

Python

avalanche/training/strategy_callbacks.py

ryanlindeborg/avalanche

32333776e729bad22f369f8923bc32416c9edcf9

[ "MIT" ]

null

avalanche/training/strategy_callbacks.py

ryanlindeborg/avalanche

32333776e729bad22f369f8923bc32416c9edcf9

[ "MIT" ]

null

avalanche/training/strategy_callbacks.py

ryanlindeborg/avalanche

32333776e729bad22f369f8923bc32416c9edcf9

[ "MIT" ]

null

from abc import ABC from typing import TypeVar, Generic CallbackResult = TypeVar('CallbackResult') class StrategyCallbacks(Generic[CallbackResult], ABC): """ Base class for all classes dealing with strategy callbacks. Implements all the callbacks of the BaseStrategy with an empty function. Subclasses must override the desired callbacks. The main two direct subclasses are :class:`StrategyPlugin`, which are used to implement continual strategies, and :class:`StrategyLogger`, which are used for logging. **Training loop** The training loop and its callbacks are organized as follows:: train before_training before_training_exp adapt_train_dataset make_train_dataloader before_training_epoch before_training_iteration before_forward after_forward before_backward after_backward after_training_iteration before_update after_update after_training_epoch after_training_exp after_training **Evaluation loop** The evaluation loop and its callbacks are organized as follows:: eval before_eval adapt_eval_dataset make_eval_dataloader before_eval_exp eval_epoch before_eval_iteration before_eval_forward after_eval_forward after_eval_iteration after_eval_exp after_eval """ def __init__(self): pass def before_training(self, *args, **kwargs) -> CallbackResult: pass def before_training_exp(self, *args, **kwargs) -> CallbackResult: pass def adapt_train_dataset(self, *args, **kwargs) -> CallbackResult: pass def before_training_epoch(self, *args, **kwargs) -> CallbackResult: pass def before_training_iteration(self, *args, **kwargs) -> CallbackResult: pass def before_forward(self, *args, **kwargs) -> CallbackResult: pass def after_forward(self, *args, **kwargs) -> CallbackResult: pass def before_backward(self, *args, **kwargs) -> CallbackResult: pass def after_backward(self, *args, **kwargs) -> CallbackResult: pass def after_training_iteration(self, *args, **kwargs) -> CallbackResult: pass def before_update(self, *args, **kwargs) -> CallbackResult: pass def after_update(self, *args, **kwargs) -> CallbackResult: pass def after_training_epoch(self, *args, **kwargs) -> CallbackResult: pass def after_training_exp(self, *args, **kwargs) -> CallbackResult: pass def after_training(self, *args, **kwargs) -> CallbackResult: pass def before_eval(self, *args, **kwargs) -> CallbackResult: pass def adapt_eval_dataset(self, *args, **kwargs) -> CallbackResult: pass def before_eval_exp(self, *args, **kwargs) -> CallbackResult: pass def after_eval_exp(self, *args, **kwargs) -> CallbackResult: pass def after_eval(self, *args, **kwargs) -> CallbackResult: pass def before_eval_iteration(self, *args, **kwargs) -> CallbackResult: pass def before_eval_forward(self, *args, **kwargs) -> CallbackResult: pass def after_eval_forward(self, *args, **kwargs) -> CallbackResult: pass def after_eval_iteration(self, *args, **kwargs) -> CallbackResult: pass

28.484375

78

0.621503

372

3,646

5.862903

0.185484

0.077029

0.154058

0.308116

0.580468

0.519028

0.146722

0.093535

0

0.299506

3,646

127

79

28.708661

0.853955

0.360669

0

0.462963

0

0.006472

0

1

0.462963

false

0.462963

0.037037

0

0.518519

0

null

0

1

0

null

0

1

0

1

0

1

0

4

30eda6ac0b0ea70a8814aaa935a9b5f10fbf15a4

105

py

Python

run.py

zubrik13/unit_converter

69e5208e37b66e83f1a2c899d924738471ae4e89

[ "MIT" ]

null

run.py

zubrik13/unit_converter

69e5208e37b66e83f1a2c899d924738471ae4e89

[ "MIT" ]

null

run.py

zubrik13/unit_converter

69e5208e37b66e83f1a2c899d924738471ae4e89

[ "MIT" ]

null

#!/bin/bash/python from webapp.app import app if __name__ == '__main__': app.run(use_reloader=True)

17.5

30

0.714286

16

105

4.125

0.875

0

0.142857

105

6

30

17.5

0.733333

0.161905

0

0.090909

0

1

0

true

0

0.333333

0

0.333333

0

1

0

null

0

1

0

null

0

1

0

1

0

4

30f32a6ae436dac92c44a53d3bd7b950f0acbd5e

1,286

py

Python

ex30.py

Kapiszko/Learn-Python

6458ba8a57e7bfbdabc6b58df40161b43caa4122

[ "Apache-2.0" ]

null

ex30.py

Kapiszko/Learn-Python

6458ba8a57e7bfbdabc6b58df40161b43caa4122

[ "Apache-2.0" ]

null

ex30.py

Kapiszko/Learn-Python

6458ba8a57e7bfbdabc6b58df40161b43caa4122

[ "Apache-2.0" ]

null

people = 50 #defines the people variable cars = 10 #defines the cars variable trucks = 35 #defines the trucks variable if cars > people or trucks < cars: #sets up the first branch print("We should take the cars.") #print that runs if the if above is true elif cars < people: #sets up second branch that runs if the first one is not true print("We should not take the cars.") #print that runs if the elif above is true else: #sets up third and last branch that will run if the above ifs are not true print("We can't decide.") #print that runs if the else above is true if trucks > cars:#sets up the first branch print("That's too many trucks.")#print that runs if the if above is true elif trucks < cars:#sets up second branch that runs if the first one is not true print("Maybe we could take the trucks.")#print that runs if the elif above is true else:#sets up third and last branch that will run if the above ifs are not true print("We still can't decide.")#print that runs if the else above is true if people > trucks:#sets up the first branch print("Alright, let's just take the trucks.")#print that runs if the if above is true else: #sets up second and last branch print("Fine, let's stay home then.")#print that runs if the else above is true

53.583333

89

0.729393

242

1,286

3.876033

0.214876

0.063966

0.10661

0.138593

0.738806

0.701493

0.58209

0.546908

0

0.005877

0.206065

1,286

23

90

55.913043

0.912831

0.597978

0

0.157895

0

0.415663

0

1

0

false

0

0.421053

0

null

0

1

0

null

0

1

0

4

ebc1d427ea96a4bc61d0da3f05886374a4b544c3

3,008

py

Python

medico_experts/doctor_app/models.py

jinalladani25/project-Training

affee90c69657ebcd99ae6722f684c37b6b1e21e

[ "bzip2-1.0.6" ]

null

medico_experts/doctor_app/models.py

jinalladani25/project-Training

affee90c69657ebcd99ae6722f684c37b6b1e21e

[ "bzip2-1.0.6" ]

null

medico_experts/doctor_app/models.py

jinalladani25/project-Training

affee90c69657ebcd99ae6722f684c37b6b1e21e

[ "bzip2-1.0.6" ]

null

from django.db import models # Create your models here. class User(models.Model): email = models.EmailField(unique= True) password = models.CharField(max_length = 20) otp = models.IntegerField(default = 459) is_active = models.BooleanField(default=True) is_verfied = models.BooleanField(default=False) role = models.CharField(max_length = 10) created_at= models.DateTimeField(auto_now_add=True,blank=False) updated_at = models.DateTimeField(auto_now = True, blank=False) class Doctor(models.Model): user_id = models.ForeignKey(User, on_delete = models.CASCADE) firstname = models.CharField(max_length=50) lastname = models.CharField(max_length=50) speciality = models.CharField(max_length = 100) mobile = models.CharField(max_length = 10) clinic = models.CharField(max_length= 100,blank = True) address = models.CharField(max_length= 500, blank= True) gender = models.CharField(max_length= 10) location = models.CharField(max_length= 30, blank= True) residency = models.CharField(max_length = 50) about_doc = models.CharField(max_length= 100, blank= True) profilepic=models.FileField(upload_to='doctor_app/assets/images/',default='doc_male.png') hospital_affiliations=models.CharField(max_length= 100,blank=True) medical_school=models.CharField(max_length=100,blank=True) certifications= models.CharField(max_length=100,blank=True) experience=models.CharField(max_length=100,blank=True) internship=models.CharField(max_length=100,blank=True) about=models.CharField(max_length=1024,blank=True) class Patient(models.Model): user_id = models.ForeignKey(User, on_delete = models.CASCADE) firstname = models.CharField(max_length=50) lastname = models.CharField(max_length=50) mobile = models.CharField(max_length = 10) address = models.CharField(max_length= 500, blank = True) city = models.CharField(max_length = 50) state = models.CharField(max_length = 50, blank = True) gender = models.CharField(max_length= 10) occupation= models.CharField(max_length=100,blank=True) phone_no=models.CharField(max_length=10,blank=True) about=models.CharField(max_length=1024,blank=True) age=models.CharField(max_length=10,blank=True) profilepic=models.FileField(upload_to='doctor_app/assets/images/',default='doc_male.png') class availability(models.Model): doctor_id = models.ForeignKey(Doctor, on_delete= models.CASCADE) avail_date = models.DateField() start_time = models.CharField(max_length = 100) status = models.BooleanField(default= False) class Appointment(models.Model): doctor_id = models.ForeignKey(Doctor, on_delete = models.CASCADE) patient_id = models.ForeignKey(Patient, on_delete = models.CASCADE) availability_id = models.ForeignKey(availability, on_delete = models.CASCADE,default = None) appointment_status = models.BooleanField(default = False) payment_status = models.BooleanField(default = False)

49.311475

96

0.751662

390

3,008

5.635897

0.241026

0.204732

0.245678

0.327571

0.685623

0.539126

0.510009

0.363512

0.291174

0

0.030467

0.137965

3,008

60

97

50.133333

0.8172

0.007979

0

0.333333

0

0.024816

0.016767

0

1

0

false

0.018519

0

1

0

null

1

0

null

0

1

0

4

ebd03bacb9c6bde93502764a3e7b882e14ed9b2d

145

py

Python

service-1-frontend/app/forms.py

JackPendlebury1/ProjectDevops2

bf88eecfbc2855a0cb9a503ad0bdba51b14bc057

[ "MIT" ]

null

service-1-frontend/app/forms.py

JackPendlebury1/ProjectDevops2

bf88eecfbc2855a0cb9a503ad0bdba51b14bc057

[ "MIT" ]

null

service-1-frontend/app/forms.py

JackPendlebury1/ProjectDevops2

bf88eecfbc2855a0cb9a503ad0bdba51b14bc057

[ "MIT" ]

1

2021-02-27T20:37:49.000Z

from flask_wtf import FlaskForm from wtforms import SubmitField class IndexForm(FlaskForm): submit = SubmitField('Get Account Number')

24.166667

47

0.772414

17

145

6.529412

0.764706

0

0.172414

145

5

48

29

0.925

0

0.128571

0

1

0

false

0

0.5

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ebe21f64354ae147da603a0b6218309ed196cb1f

320

py

Python

src/config/TrainingConfig.py

OpenNLPhub/MRC_NER

27ca063764aed9eb5f2ac672bb10052acbf374a5

[ "MIT" ]

4

2020-12-28T08:36:21.000Z

2021-09-30T06:54:21.000Z

src/config/TrainingConfig.py

OpenNLPhub/MRC_NER

27ca063764aed9eb5f2ac672bb10052acbf374a5

[ "MIT" ]

1

2021-06-10T00:18:15.000Z

src/config/TrainingConfig.py

OpenNLPhub/MRC_NER

27ca063764aed9eb5f2ac672bb10052acbf374a5

[ "MIT" ]

null

class TrainingConfig(): batch_size=64 lr=0.001 epoches=20 print_step=15 class BertMRCTrainingConfig(TrainingConfig): batch_size=64 lr=1e-5 epoches=5 class TransformerConfig(TrainingConfig): pass class HBTTrainingConfig(TrainingConfig): batch_size=32 lr=1e-5 epoch=20

15.238095

44

0.696875

39

320

5.615385

0.538462

0.260274

0.315068

0.228311

0.246575

0

0.084677

0.225

320

21

45

15.238095

0.798387

0

0.266667

0

1

0

false

0.066667

0

0.933333

0.066667

0

null

1

0

null

0

1

0

4

694fc36dea0e6f615b5b6a7d1fb90b3b9f190e3f

67

py

Python

examples/__init__.py

raztud/dagger

7b394138c139e3b4fdf228e3d34359f1ae6bdd7a

[ "Apache-2.0" ]

9

2021-09-06T14:22:38.000Z

2022-02-08T07:48:39.000Z

examples/__init__.py

raztud/dagger

7b394138c139e3b4fdf228e3d34359f1ae6bdd7a

[ "Apache-2.0" ]

36

2021-09-04T06:20:19.000Z

2021-12-26T17:54:59.000Z

examples/__init__.py

raztud/dagger

7b394138c139e3b4fdf228e3d34359f1ae6bdd7a

[ "Apache-2.0" ]

4

2021-09-06T08:07:19.000Z

2021-10-18T19:13:18.000Z

"""Curated examples showing common and advanced uses of dagger."""

33.5

66

0.761194

9

67

5.666667

1

0

0.134328

67

1

67

0.87931

0.895522

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

696f252e989c000953a7548c71a0f40a5b76b91f

48

py

Python

backend/tutors/__init__.py

ProgrammingLanguageLeader/TutorsApp

f2d5968b5c29ce75f5f634d6076a6e66efc76801

[ "MIT" ]

3

2019-02-24T23:30:19.000Z

2019-03-27T20:06:53.000Z

backend/tutors/__init__.py

ProgrammingLanguageLeader/TutorsApp

f2d5968b5c29ce75f5f634d6076a6e66efc76801

[ "MIT" ]

1

2019-03-30T08:58:06.000Z

backend/tutors/__init__.py

ProgrammingLanguageLeader/TutorsApp

f2d5968b5c29ce75f5f634d6076a6e66efc76801

[ "MIT" ]

1

2019-03-01T20:10:19.000Z

default_app_config = 'tutors.apps.TutorsConfig'

24

47

0.833333

6

48

6.333333

1

0

0.0625

48

1

48

0.844444

0

0.5

0

1

0

false

0

1

0

null

0

1

0

1

null

0

4

15c453708f08ac58c8dc4bc297b4188180b3c200

134

py

Python

tests/bejl/test_load.py

thautwarm/restrain-jit

f76b3e9ae8a34d2eef87a42cc87197153f14634c

[ "MIT" ]

116

2019-09-18T15:43:09.000Z

2022-02-18T15:28:08.000Z

tests/bejl/test_load.py

thautwarm/restrain-jit

f76b3e9ae8a34d2eef87a42cc87197153f14634c

[ "MIT" ]

6

2019-09-18T16:12:49.000Z

2021-02-03T13:01:42.000Z

tests/bejl/test_load.py

thautwarm/restrain-jit

f76b3e9ae8a34d2eef87a42cc87197153f14634c

[ "MIT" ]

8

2019-09-19T07:15:05.000Z

2022-01-19T19:40:10.000Z

import restrain_jit.cpy_compat import test_load as a a.b = 1 print(type(a)) print(a.__py_module__.b) a.b = 2 print(a.__state_ages__)

14.888889

30

0.761194

28

134

3.178571

0.642857

0.044944

0

0.016949

0.119403

134

8

31

16.75

0.737288

0

1

0

true

0

0.285714

0

0.285714

0.428571

1

0

null

0

1

0

null

0

1

0

1

0

4

15e321a5aaf8fca1b5c3f7f817633af1b736ec29

24

py

Python

data/studio21_generated/introductory/3872/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/introductory/3872/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

data/studio21_generated/introductory/3872/starter_code.py

vijaykumawat256/Prompt-Summarization

614f5911e2acd2933440d909de2b4f86653dc214

[ "Apache-2.0" ]

null

def sort_it(list_, n):

12

22

0.666667

5

24

2.8

1

0

0.166667

24

2

23

12

0.7

0

null

0

null

0

1

0

null

0

1

0

null

0

1

0

4

c60a2a1c14728b80b07d8659ffe42e493d9715d3

71

py

Python

yanoama/pilot/core/__init__.py

guthemberg/yanoama

511342a1f4feb09fc3436fb7b7461510d9020b6c

[ "BSD-3-Clause" ]

null

yanoama/pilot/core/__init__.py

guthemberg/yanoama

511342a1f4feb09fc3436fb7b7461510d9020b6c

[ "BSD-3-Clause" ]

null

yanoama/pilot/core/__init__.py

guthemberg/yanoama

511342a1f4feb09fc3436fb7b7461510d9020b6c

[ "BSD-3-Clause" ]

null

from yanoama.pilot.core.settings import Settings settings = Settings()

23.666667

48

0.816901

9

71

6.444444

0.666667

0.551724

0

0.098592

71

3

49

23.666667

0.90625

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

4

c6239f9521ba37cf75b824eb55f7e81353e0ae42

32

py

Python

core/plugins/crowdin/__init__.py

purecloudlabs/translation-process-automation

ea65a5c35a9490bce57e6dc0104b1b86f4fc8ddf

[ "MIT" ]

null

core/plugins/crowdin/__init__.py

purecloudlabs/translation-process-automation

ea65a5c35a9490bce57e6dc0104b1b86f4fc8ddf

[ "MIT" ]

null

core/plugins/crowdin/__init__.py

purecloudlabs/translation-process-automation

ea65a5c35a9490bce57e6dc0104b1b86f4fc8ddf

[ "MIT" ]

null

""" tpa crowdin repository. """

10.666667

27

0.625

3

32

6.666667

1

0

0.15625

32

2

28

16

0.740741

0.71875

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

c6548aefb587750ebaa4df51e1eeaeaabb464474

69

py

Python

packages/vaex-meta/vaex/meta/_version.py

0xflotus/vaex

10bc10417c8b5973360d93c9d6971bcbba82702e

[ "MIT" ]

null

packages/vaex-meta/vaex/meta/_version.py

0xflotus/vaex

10bc10417c8b5973360d93c9d6971bcbba82702e

[ "MIT" ]

null

packages/vaex-meta/vaex/meta/_version.py

0xflotus/vaex

10bc10417c8b5973360d93c9d6971bcbba82702e

[ "MIT" ]

null

__version_tuple__ = (1, 0, 0, 'beta.8') __version__ = '1.0.0-beta.8'

23

39

0.637681

13

69

2.692308

0.461538

0.114286

0.171429

0.4

0.457143

0

0.133333

0.130435

69

2

40

34.5

0.45

0

0.26087

0

1

0

false

0

1

0

null

0

1

0

1

0

1

0

null

0

4

ba5b49f5043db9f8192e6bc0e9d5d59bdbe6bdbb

112

py

Python

Case5.py

ciracheta99/TestLinkPython

563bf24dac6c2309bd5989767c30a2e70e6c0f68

[ "Apache-2.0" ]

1

2022-01-18T07:48:24.000Z

Case5.py

ciracheta99/TestLinkPython

563bf24dac6c2309bd5989767c30a2e70e6c0f68

[ "Apache-2.0" ]

null

Case5.py

ciracheta99/TestLinkPython

563bf24dac6c2309bd5989767c30a2e70e6c0f68

[ "Apache-2.0" ]

null

print ('Inside Case 5') self.logResult("Just checking if a log file gets generated") self.reportTCResults("p")

37.333333

61

0.75

17

112

4.941176

0.941176

0

0.010204

0.125

112

3

62

37.333333

0.846939

0

1

0

0.504505

0

1

0

true

0

0.333333

1

0

null

0

1

0

1

0

null

0

1

0

4

ba93a7493fdcb59320338b405d2c5aa5720c9f5e

214

py

Python

tools/leetcode.125.Valid Palindrome/leetcode.125.Valid Palindrome.submission5.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

4

2015-10-10T00:30:55.000Z

2020-07-27T19:45:54.000Z

tools/leetcode.125.Valid Palindrome/leetcode.125.Valid Palindrome.submission5.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

tools/leetcode.125.Valid Palindrome/leetcode.125.Valid Palindrome.submission5.py

tedye/leetcode

975d7e3b8cb9b6be9e80e07febf4bcf6414acd46

[ "MIT" ]

null

class Solution: # @param {string} s # @return {boolean} def isPalindrome(self, s): # attempt three clean_s = [i.lower() for i in s if i.isalnum()] return clean_s == clean_s[::-1]

214

0.565421

30

214

3.933333

0.666667

0.152542

0

0.006623

0.294393

214

1

214

0.774834

0.228972

0

1

0.25

false

0

0.75

0

null

0

1

0

1

0

null

0

1

0

1

0

4

ba9921760a924476741def5565cdf0864b2b30cf

328

py

Python

zdcode/program.py

zeta-group/ZDCode

900fbc08bc3844bbd4690e65a9ae07d0b2e38629

[ "MIT" ]

4

2020-10-11T01:04:26.000Z

2022-02-24T03:37:49.000Z

zdcode/program.py

zeta-group/ZDCode

900fbc08bc3844bbd4690e65a9ae07d0b2e38629

[ "MIT" ]

1

2020-03-28T19:07:34.000Z

2020-03-31T00:45:52.000Z

zdcode/program.py

zeta-group/ZDCode

900fbc08bc3844bbd4690e65a9ae07d0b2e38629

[ "MIT" ]

null

import argparse import os import sys try: import zdcode import zdcode.zake as zake from zdcode.bundle import Bundle except ImportError: import __init__ as zdcode import zake from bundle import Bundle def main(): return main_zake() def main_zake(): return zake.main(print_status_code=False)

14.909091

45

0.722561

46

328

4.978261

0.434783

0.104803

0.157205

0

0.228659

328

21

46

15.619048

0.905138

0

1

0.133333

true

0

0.666667

0.133333

0.933333

0.066667

0

null

0

null

0

1

0

1

0

4

bab55480d68a1ff936834a498f1ed8834bcbaffd

1,092

py

Python

utils/default_values.py

w568w/backend

25bdf6f890a6c59418d5a184e48bd87d697c4d23

[ "Apache-2.0" ]

null

utils/default_values.py

w568w/backend

25bdf6f890a6c59418d5a184e48bd87d697c4d23

[ "Apache-2.0" ]

null

utils/default_values.py

w568w/backend

25bdf6f890a6c59418d5a184e48bd87d697c4d23

[ "Apache-2.0" ]

null

""" 数据库默认值生成函数 """ from datetime import datetime, timedelta from django.conf import settings from utils.constants import NotifyConfig def now(): return datetime.now(settings.TIMEZONE) def default_active_user_date(): return now() - timedelta(days=1) def default_permission(): """ silent 字典 index：分区id （string） django的JSONField会将字典的int索引转换成str value：禁言解除时间 """ return { 'admin': '1970-01-01T00:00:00+00:00', # 管理员权限：到期时间 'silent': {}, # 禁言 'offense_count': 0 } def default_config(): """ show_folded: 对折叠内容的处理 fold: 折叠 hide: 隐藏 show: 展示 notify: 在以下场景时通知 NotifyConfig.floor_mentioned: 帖子被提及时 NotifyConfig.favored_hole_replied: 收藏的主题帖有新帖时 NotifyConfig.reported: 被举报时通知管理员 NotifyConfig.punished: 被处罚时另外，当用户权限发生变化或所发帖被修改时也会收到通知 """ return { 'show_folded': 'fold', 'notify': [NotifyConfig.floor_mentioned, NotifyConfig.favored_hole_replied, NotifyConfig.punished] }

21.411765

83

0.6163

105

1,092

6.27619

0.619048

0.045524

0.018209

0.091047

0

0.025707

0.287546

1,092

50

84

21.84

0.821337

0.373626

0

0.105263

0

0.116473

0.041597

0

1

0.210526

true

0

0.157895

0.105263

0.578947

0

null

0

null

0

1

0

1

0

4

bad8f7f3c5de50c562816cefe85260b789cacec8

83

py

Python

cert/apps.py

pulsejet/cert-server

89e7baea1c62ca6b4c83f9ff993b58278c45d20b

[ "MIT" ]

1

2022-01-29T23:58:34.000Z

cert/apps.py

pulsejet/cert-server

89e7baea1c62ca6b4c83f9ff993b58278c45d20b

[ "MIT" ]

1

2020-02-11T22:49:27.000Z

cert/apps.py

pulsejet/cert-server

89e7baea1c62ca6b4c83f9ff993b58278c45d20b

[ "MIT" ]

1

2018-06-12T13:52:05.000Z

from django.apps import AppConfig class CertConfig(AppConfig): name = 'cert'

13.833333

33

0.73494

10

83

6.1

0.9

0

0.180723

83

5

34

16.6

0.897059

0

0.048193

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

243516e0b5204a04bf2e1fb9f03e00f1eab823b0

61

py

Python

Term 2/2-5-input.py

theseana/miniatur

eed89de0b1e0b96bb32067d5c049c6fd4ca5f872

[ "MIT" ]

1

2022-01-16T00:30:43.000Z

Term 2/2-5-input.py

theseana/miniatur

eed89de0b1e0b96bb32067d5c049c6fd4ca5f872

[ "MIT" ]

null

Term 2/2-5-input.py

theseana/miniatur

eed89de0b1e0b96bb32067d5c049c6fd4ca5f872

[ "MIT" ]

null

name = input('ENTER YOUR NAME: ') print('Your name is', name)

30.5

33

0.672131

10

61

4.1

0.6

0.390244

0

0.147541

61

2

34

30.5

0.788462

0

0.467742

0

1

0

false

0

0.5

1

0

null

1

0

1

0

null

0

1

0

4

2462462c15ea01b443b9587f9b36ce27e16054c6

136

py

Python

Darlington/phase1/python Basic 1/day 9 solution/qtn2.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

6

2020-05-23T19:53:25.000Z

2021-05-08T20:21:30.000Z

Darlington/phase1/python Basic 1/day 9 solution/qtn2.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

8

2020-05-14T18:53:12.000Z

2020-07-03T00:06:20.000Z

Darlington/phase1/python Basic 1/day 9 solution/qtn2.py

CodedLadiesInnovateTech/-python-challenge-solutions

430cd3eb84a2905a286819eef384ee484d8eb9e7

[ "MIT" ]

39

2020-05-10T20:55:02.000Z

2020-09-12T17:40:59.000Z

#program to get the details of math module. import math #Sets everything to a list of math module math_ls = dir(math) # print(math_ls)

22.666667

43

0.757353

25

136

4.04

0.64

0.118812

0.237624

0

0.176471

136

5

44

27.2

0.901786

0.602941

0

1

0

false

0

0.333333

0

0.333333

1

0

null

0

1

0

1

0

null

0

1

0

4

2467cce351ee3950d6051b279111c2511b02732a

76

py

Python

pytest_harvest/tests_raw/conftest.py

keszybz/python-pytest-harvest

ef11d3addeae51168ab892b7806c2b4c270e2a82

[ "BSD-3-Clause" ]

36

2018-11-07T19:32:08.000Z

2022-03-19T10:24:48.000Z

pytest_harvest/tests_raw/conftest.py

keszybz/python-pytest-harvest

ef11d3addeae51168ab892b7806c2b4c270e2a82

[ "BSD-3-Clause" ]

55

2018-11-13T10:58:30.000Z

2022-01-06T10:32:53.000Z

pytest_harvest/tests_raw/conftest.py

keszybz/python-pytest-harvest

ef11d3addeae51168ab892b7806c2b4c270e2a82

[ "BSD-3-Clause" ]

4

2019-10-05T09:50:09.000Z

2021-03-31T20:33:16.000Z

# This is actually not even needed apparently # pytest_plugins = ["harvest"]

38

45

0.763158

10

76

5.7

1

0

0.144737

76

2

46

38

0.876923

0.947368

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

79e988cb1033b99846361f660cf488ceaa61337f

131

py

Python

cj/crawler/crawl.py

james-garfield/Captain-Japan

8edc63f138f956fe9187b6eda3bffdd871fba839

[ "Unlicense" ]

null

cj/crawler/crawl.py

james-garfield/Captain-Japan

8edc63f138f956fe9187b6eda3bffdd871fba839

[ "Unlicense" ]

null

cj/crawler/crawl.py

james-garfield/Captain-Japan

8edc63f138f956fe9187b6eda3bffdd871fba839

[ "Unlicense" ]

null

class Crawler: """ This class handles the calling of the scraper. """ def __init__(self) -> None: pass

18.714286

50

0.557252

15

131

4.6

0.866667

0

0.343511

131

7

51

18.714286

0.802326

0.351145

0

1

0.333333

false

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

79ef5867bf82b5a0a8c775c674aa9a70bb9db2d1

106

py

Python

test_con.py

chensjtu/poxture

f6abea1216c987f0e4c628b250054d764eaecf2e

[ "Apache-2.0" ]

null

test_con.py

chensjtu/poxture

f6abea1216c987f0e4c628b250054d764eaecf2e

[ "Apache-2.0" ]

null

test_con.py

chensjtu/poxture

f6abea1216c987f0e4c628b250054d764eaecf2e

[ "Apache-2.0" ]

null

import torch import torch.nn as nn import numpy as np import logging import pickle as pkl path = ""

8.153846

21

0.726415

18

106

4.277778

0.555556

0.285714

0

0.235849

106

12

22

8.833333

0.950617

0

1

0

false

0

0.833333

0

0.833333

0

1

0

null

1

0

null

0

1

0

1

0

4

79f6483d1cb04733eaacf1761903ee1ab906ffdc

37

py

Python

pysrc/tests/test_evaluation/__init__.py

Hrle97/Cheap-Statistics

b6b9159f36b1559c81987202bdb329df9faed782

[ "MIT" ]

null

pysrc/tests/test_evaluation/__init__.py

Hrle97/Cheap-Statistics

b6b9159f36b1559c81987202bdb329df9faed782

[ "MIT" ]

1

2019-08-03T17:59:06.000Z

pysrc/tests/test_evaluation/__init__.py

Hrle97/Cheap-Statistics

b6b9159f36b1559c81987202bdb329df9faed782

[ "MIT" ]

null

""" The evaluation test package. """

9.25

28

0.648649

4

37

6

1

0

0.162162

37

3

29

12.333333

0.774194

0.756757

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

030b50c16b5c12beefb4666d40e343515d234cfd

32

py

Python

docs/mydocs.py

fscutti/pyrate

0e974cdaa43e25cfa1a93de4449e5a39f67b1097

[ "BSD-3-Clause" ]

null

docs/mydocs.py

fscutti/pyrate

0e974cdaa43e25cfa1a93de4449e5a39f67b1097

[ "BSD-3-Clause" ]

null

docs/mydocs.py

fscutti/pyrate

0e974cdaa43e25cfa1a93de4449e5a39f67b1097

[ "BSD-3-Clause" ]

null

""" documentation goes here """

16

31

0.65625

3

32

7

1

0

0.15625

32

1

32

0.777778

0.71875

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

03215682893c061a5b9dd75fe7240a653256f39f

1,946

py

Python

pieces/rook.py

nherbert25/chess_test

5cebe4d57c9a1bdc073925079f8530ad900041c9

[ "MIT" ]

null

pieces/rook.py

nherbert25/chess_test

5cebe4d57c9a1bdc073925079f8530ad900041c9

[ "MIT" ]

null

pieces/rook.py

nherbert25/chess_test

5cebe4d57c9a1bdc073925079f8530ad900041c9

[ "MIT" ]

null

from pieces.piece import Piece import pygame class Rook(Piece): name = 'rook' def __init__(self, alliance, position): Piece.__init__(self, alliance) self.alliance = alliance self.position = position #print(self.sprite, self.alliance, self.position) def toString(self): return("R" if self.alliance == "Black" else "r") def movement(self, original_position): potential_legal_moves = [] potential_legal_moves.append([]) test_position = original_position-1 while test_position%8 < original_position % 8: potential_legal_moves[0].append(test_position) test_position -= 1 potential_legal_moves.append([]) test_position = original_position+1 while test_position%8 > original_position % 8: potential_legal_moves[1].append(test_position) test_position += 1 potential_legal_moves.append([]) test_position = original_position-8 while test_position >= 0: potential_legal_moves[2].append(test_position) test_position -= 8 potential_legal_moves.append([]) test_position = original_position+8 while test_position <= 63: potential_legal_moves[3].append(test_position) test_position += 8 return(potential_legal_moves) def movement_old(self, original_position): potential_legal_moves = [] if original_position % 8 != 0: test_position = original_position-1 while test_position%8 != 0: potential_legal_moves.append(test_position) test_position -= 1 potential_legal_moves.append(test_position) test_position = original_position+1 while test_position%8 != 0: potential_legal_moves.append(test_position) test_position += 1 test_position = original_position-8 while test_position >= 0: potential_legal_moves.append(test_position) test_position -= 8 test_position = original_position+8 while test_position < 64: potential_legal_moves.append(test_position) test_position += 8 #return legal squares return(potential_legal_moves)

25.946667

51

0.754368

256

1,946

5.386719

0.148438

0.287165

0.234228

0.163162

0.738216

0.659173

0.627991

0.594634

0.535896

0

0.021858

0.153649

1,946

74

52

26.297297

0.815422

0.034943

0

0.611111

0

0.005864

0

1

0.074074

false

0

0.037037

0.018519

0.148148

0

null

1

0

1

0

null

0

4

03272fb62083ff6c3dcf76d98ecc874dca5001f6

66

py

Python

file_templates/python-enum.py

jt28828/-fontawesome-enum-generator

30b27885f3c3dadb5b17af5033b4c57169dda8f4

[ "Unlicense" ]

null

file_templates/python-enum.py

jt28828/-fontawesome-enum-generator

30b27885f3c3dadb5b17af5033b4c57169dda8f4

[ "Unlicense" ]

null

file_templates/python-enum.py

jt28828/-fontawesome-enum-generator

30b27885f3c3dadb5b17af5033b4c57169dda8f4

[ "Unlicense" ]

null

from enum import Enum class FontAwesomeCodes(Enum): <<Contents>>

13.2

29

0.772727

8

66

6.375

0.75

0

0.121212

66

5

30

13.2

0.87931

0

null

0

0.333333

null

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ceff0b37affb9b4a452372cfbdd73fc68243af5d

186

py

Python

hooks/hook-skimage.io.py

alexander-g/Root-Detector

cc7af00d204a294ed967bbaab55c03e6a9a15bcc

[ "MIT" ]

1

2022-02-17T16:18:00.000Z

hooks/hook-skimage.io.py

ExPlEcoGreifswald/Root-Detector

cc7af00d204a294ed967bbaab55c03e6a9a15bcc

[ "MIT" ]

null

hooks/hook-skimage.io.py

ExPlEcoGreifswald/Root-Detector

cc7af00d204a294ed967bbaab55c03e6a9a15bcc

[ "MIT" ]

null

from PyInstaller.utils.hooks import collect_data_files, collect_submodules datas = collect_data_files("skimage.io._plugins") hiddenimports = collect_submodules('skimage.io._plugins')

46.5

75

0.833333

23

186

6.391304

0.608696

0.14966

0.217687

0

0.075269

186

4

76

46.5

0.854651

0

0.206522

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

0

1

0

1

0

null

0

1

0

4

3018d4c2a8cbaabce02de0279fa6c83b13ce5ea8

2,315

py

Python

apps/st_app/libs/examples.py

m3hrdadfi/zabanshenas

af105f8de5b25ae6f5690845ff74d98f0591daf4

[ "Apache-2.0" ]

16

2021-02-14T14:35:01.000Z

2022-03-10T22:25:51.000Z

apps/st_app/libs/examples.py

m3hrdadfi/zabanshenas

af105f8de5b25ae6f5690845ff74d98f0591daf4

[ "Apache-2.0" ]

1

2021-02-14T17:28:05.000Z

2022-01-16T08:05:10.000Z

apps/st_app/libs/examples.py

m3hrdadfi/zabanshenas

af105f8de5b25ae6f5690845ff74d98f0591daf4

[ "Apache-2.0" ]

1

2021-12-17T07:10:48.000Z

EXAMPLES = { 'Example 1 - Swedish': 'Glochidion gaudichaudii är en emblikaväxtart som först beskrevs av Johannes Müller Argoviensis , och fick sitt nu gällande namn av Jacob Gijsbert Boerlage . Glochidion gaudichaudii ingår i släktet Glochidion och familjen emblikaväxter . Inga underarter finns listade i Catalogue of Life .', 'Example 2 - Ossetian': 'Рагон англисаг æвзаг ( англ . Old English , рагон англ . Englisc sprǣc ) у англисаг æвзаджы фыццагон формæ Англисы æмæ хуссар Шотландийы XII æнусмæ хæлиугонд . Рагон англисаг æвзаг у ныгуылæн гермайнаг æвзаг .', 'Example 3 - Tuvan': 'Черниң болгаш өске - даа планеталарның тыптып келгениниң дугайында эң - не баштайгы эртем - шинчилел ажылдарын 1755 чылда немец философ И . Кант кылган . Ол - ла үеде француз эртемден Лапластың кылган түңнелдери Кантыныы - биле дүгжүп турар . Кант биле Лаплас - Хүн Черге дөмейлешпес , тергиин изиг , хемчээл талазы - биле Черден хөй катап улуг , а Чер болза , Хүн системазының планетазының бирээзи болур деп тодаргайлааннар . Оон ыңай планета бүрүзү бодунуң орбитазы - биле Хүннү чаңгыс аай углуг дескинип турар , бойдуста бүгү - ле чүве үргүлчү өскерлип , хөгжүп , сайзырап турар деп түңнел үндүргеннер .', 'Example 4 - Malayalam': 'നൂഗാ . ( Nougat ) ഒരു മധുരപലഹാരം . പഞ്ചസാരയും തേനും വറുത്തെടുത്ത നട്സുകളും മുട്ടയുടെ വെള്ളയുമെല്ലാം ചേർത്ത് നിർമ്മിക്കുന്നതാണ് ഈ പലഹാരം . അണ്ടിപ്പരിപ്പ് , ബദാം , പിസ്ത , വാൽനട്ട് , ഹസെൽനട്സ് തുടങ്ങിയ വിവിധ നട്സുകൾ ഇതിനായി ഉപയോഗിക്കാറുണ്ട് . പഴങ്ങളുടെ കഷ്ണവും ഇതിനൊപ്പം ചേർക്കാറുണ്ട് . ചോക്ളേറ്റ് ബാറുകളായും സദ്യക്ക് ശേഷമുള്ള ഡെസേട്ടായും ഇത് ഉപയോഗിക്കാറുണ്ട് . സ്പെയിൻ , ഇറ്റലി എന്നിവിടങ്ങളിലെ പ്രാദേശിക ഭാഷയായ ഓസിറ്റാൻ ഭാഷയിലാണ് ഈ വാക്കുള്ളത് . ആൻഡ്രോയിഡിന്റെ പുതിയ പതിപ്പിന് ഈ പലഹാരത്തിന്റെ പേരാണ് നൽകിയിട്ടുള്ളത് .', 'Example 5 - Interlingue': 'Hó - témper , Ipce publica li electronic bulletine Ipce Newsletter e li revue Ipce Magazine . Li gruppe administra anc un website con un vast documental archive de scientific studies , libres e jornalistic articules pri li pedofilie e temas afin , quel include in plu un privat forum pri ti - ci classe de litteratura e pri li maniere de promotionar li academic debatte pri li pedofilie . Annualmen , Ipce celebra reuniones pro discusser pri questiones intern e altri temas , queles eveni in un land diferent chascun annu .'}

330.714286

634

0.715335

609

2,315

3.014778

0.456486

0.007625

0.006536

0.035403

0.028867

0.022331

0.017429

0

0.004663

0.166307

2,315

6

635

385.833333

0.853368

0

0.833333

0.968467

0

1

0

false

0

null

0

1

0

1

0

1

0

null

0

4

3066e19473c66e5104abb12f7d6a56d2b10324f5

211

py

Python

amd64-linux/lib/python/mod_ia64_itanium2_commands.py

qiyancos/Simics-3.0.31

9bd52d5abad023ee87a37306382a338abf7885f1

[ "BSD-4-Clause", "FSFAP" ]

1

2020-06-15T10:41:18.000Z

amd64-linux/lib/python/mod_ia64_itanium2_commands.py

qiyancos/Simics-3.0.31

9bd52d5abad023ee87a37306382a338abf7885f1

[ "BSD-4-Clause", "FSFAP" ]

null

amd64-linux/lib/python/mod_ia64_itanium2_commands.py

qiyancos/Simics-3.0.31

9bd52d5abad023ee87a37306382a338abf7885f1

[ "BSD-4-Clause", "FSFAP" ]

3

2020-08-10T10:25:02.000Z

2021-09-12T01:12:09.000Z

import ia64_commands funcs = { 'print_disassemble_line': ia64_commands.local_print_disassemble_line, 'pregs': ia64_commands.local_pregs } class_funcs = { 'ia64-itanium2': funcs }

23.444444

53

0.682464

23

211

5.826087

0.478261

0.268657

0.298507

0

0.055215

0.227488

211

8

54

26.375

0.766871

0

0.189573

0.104265

0

1

0

false

0

0.166667

0

0.166667

0.333333

1

0

null

1

0

1

0

null

0

4

06313b4e31b272b50ef54b4eeb0488aee1c9e8a3

1,591

py

Python

tests/test_conf_from_url.py

Pytlicek/fastapi-featureflags

bcd39f7942430da6f8ec93e23500f4e34b8d9528

[ "MIT" ]

10

2021-11-30T07:33:02.000Z

2022-03-23T18:33:04.000Z

tests/test_conf_from_url.py

Pytlicek/fastapi-featureflags

bcd39f7942430da6f8ec93e23500f4e34b8d9528

[ "MIT" ]

4

2021-12-01T20:00:32.000Z

2021-12-16T10:16:33.000Z

tests/test_conf_from_url.py

Pytlicek/fastapi-featureflags

bcd39f7942430da6f8ec93e23500f4e34b8d9528

[ "MIT" ]

1

2021-11-30T07:33:16.000Z

from fastapi_featureflags import feature_enabled def test_ff_from_url(featureflags): featureflags.load_conf_from_url("https://pastebin.com/raw/4Ai3j2DC") assert type(featureflags.get_features()) is dict assert featureflags.conf_from_url is not None assert featureflags.get_features() == { "web_only": False, "web_1": True, "web_2": False, "web_3": True, "web_4": False, } def test_enable_feature(featureflags): assert featureflags.get_features()["web_only"] is False action = featureflags.enable_feature("web_only") assert action is True assert featureflags.get_features()["web_only"] is True def test_disable_feature(featureflags): assert featureflags.get_features()["web_1"] is True action = featureflags.disable_feature("web_1") assert action is False assert featureflags.get_features()["web_1"] is False def test_feature_enabled(featureflags): assert featureflags.get_features()["web_4"] is False assert feature_enabled("web_4") is False assert featureflags.is_enabled("web_4") is False featureflags.enable_feature("web_4") assert feature_enabled("web_4") is True assert featureflags.is_enabled("web_4") is True def test_reload_features(featureflags): assert featureflags.get_features()["web_only"] is True assert featureflags.get_features()["web_1"] is False action = featureflags.reload_feature_flags() assert action is True assert featureflags.get_features()["web_only"] is False assert featureflags.get_features()["web_1"] is True

32.469388

72

0.732244

212

1,591

5.216981

0.179245

0.211573

0.228752

0.262206

0.583183

0.559675

0.440326

0.357143

0.175407

0.101266

0

0.013575

0.166562

1,591

48

73

33.145833

0.820513

0

0.277778

0

0.098052

0

0.527778

1

0.138889

false

0

0.027778

0

0.166667

0

null

1

0

null

0

1

0

4

063370e4a24f85c453b3ea244e2196095e1ea2aa

156

py

Python

tinydb_viewer/__init__.py

patarapolw/tinydb-viewer

3ae90469a8d0316f3b8d398bad019cec8a8a9416

[ "MIT" ]

3

2018-09-30T19:51:58.000Z

2019-08-23T14:27:00.000Z

tinydb_viewer/__init__.py

patarapolw/tinydb-viewer

3ae90469a8d0316f3b8d398bad019cec8a8a9416

[ "MIT" ]

null

tinydb_viewer/__init__.py

patarapolw/tinydb-viewer

3ae90469a8d0316f3b8d398bad019cec8a8a9416

[ "MIT" ]

1

2019-12-05T13:26:59.000Z

from flask import Flask app = Flask(__name__) from .main import TinyDB from .views import index from .api import create_table, edit_record, delete_record

19.5

57

0.801282

24

156

4.916667

0.625

0

0.147436

156

7

58

22.285714

0.887218

0

1

0

false

0

0.8

0

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

4

0649b8e51b139dc61878733582fb4bf1317cc3a2

117

py

Python

fast_carpenter/define/__init__.py

bundocka/fast-carpenter

fa90ba6fb28a73c5de4be53daebc7af9889f2478

[ "Apache-2.0" ]

12

2019-05-17T13:02:20.000Z

2020-08-31T08:16:47.000Z

fast_carpenter/define/__init__.py

bundocka/fast-carpenter

fa90ba6fb28a73c5de4be53daebc7af9889f2478

[ "Apache-2.0" ]

104

2019-05-17T16:25:35.000Z

2022-03-28T16:11:10.000Z

fast_carpenter/define/__init__.py

benkrikler/fast-carpenter-github-test

b6f7e1b218d3a1f39fcbe739c8bab19af63aabb8

[ "Apache-2.0" ]

16

2019-05-20T16:57:48.000Z

2020-09-28T16:36:21.000Z

from .variables import Define from .systematics import SystematicWeights __all__ = ["Define", "SystematicWeights"]

19.5

42

0.794872

11

117

8.090909

0.636364

0

0.119658

117

5

43

23.4

0.864078

0

0.196581

0

1

0

false

0

0.666667

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

068d09f564c7648bbd67fd75d52f49763f41a28f

8,201

py

Python

grr/gui/api_plugins/report_plugins/server_report_plugins.py

StanislavParovoy/GRR

7cdf490f9be2ccc0a8160c9b8ae23b73922049d5

[ "Apache-2.0" ]

5

2017-03-17T08:25:09.000Z

2022-02-22T05:28:14.000Z

grr/gui/api_plugins/report_plugins/server_report_plugins.py

StanislavParovoy/GRR

7cdf490f9be2ccc0a8160c9b8ae23b73922049d5

[ "Apache-2.0" ]

null

grr/gui/api_plugins/report_plugins/server_report_plugins.py

StanislavParovoy/GRR

7cdf490f9be2ccc0a8160c9b8ae23b73922049d5

[ "Apache-2.0" ]

3

2018-12-07T07:04:37.000Z

2022-02-22T05:28:16.000Z

#!/usr/bin/env python """UI server report handling classes.""" import operator from grr.gui.api_plugins.report_plugins import rdf_report_plugins from grr.gui.api_plugins.report_plugins import report_plugin_base from grr.gui.api_plugins.report_plugins import report_utils from grr.lib import events from grr.lib import rdfvalue from grr.lib.aff4_objects import users as aff4_users TYPE = rdf_report_plugins.ApiReportDescriptor.ReportType.SERVER class MostActiveUsersReportPlugin(report_plugin_base.ReportPluginBase): """Reports client activity by week.""" TYPE = TYPE TITLE = "User Breakdown" SUMMARY = "Active user actions." REQUIRES_TIME_RANGE = True def GetReportData(self, get_report_args, token): """Filter the last week of user actions.""" ret = rdf_report_plugins.ApiReportData( representation_type=rdf_report_plugins.ApiReportData.RepresentationType. PIE_CHART) try: timerange_offset = get_report_args.duration timerange_end = get_report_args.start_time + timerange_offset counts = {} try: for event in report_utils.GetAuditLogEntries(timerange_offset, timerange_end, token): counts.setdefault(event.user, 0) counts[event.user] += 1 except ValueError: # Couldn't find any logs.. pass ret.pie_chart.data = sorted( (rdf_report_plugins.ApiReportDataPoint1D( x=count, label=user) for user, count in counts.iteritems() if user not in aff4_users.GRRUser.SYSTEM_USERS), key=lambda series: series.label) except IOError: pass return ret class SystemFlowsReportPlugin(report_plugin_base.ReportPluginBase): """Count given timerange's system-created flows by type.""" TYPE = TYPE TITLE = "System Flows" SUMMARY = ("Flows launched by GRR crons and workers over the given timerange" " grouped by type.") REQUIRES_TIME_RANGE = True def UserFilter(self, username): return username in aff4_users.GRRUser.SYSTEM_USERS def GetReportData(self, get_report_args, token): ret = rdf_report_plugins.ApiReportData( representation_type=rdf_report_plugins.ApiReportData.RepresentationType. STACK_CHART, stack_chart=rdf_report_plugins.ApiStackChartReportData(x_ticks=[])) # TODO(user): move the calculation to a cronjob and store results in # AFF4. try: timerange_offset = get_report_args.duration timerange_end = get_report_args.start_time + timerange_offset # Store run count total and per-user counts = {} try: for event in report_utils.GetAuditLogEntries(timerange_offset, timerange_end, token): if (event.action == events.AuditEvent.Action.RUN_FLOW and self.UserFilter(event.user)): counts.setdefault(event.flow_name, {"total": 0, event.user: 0}) counts[event.flow_name]["total"] += 1 counts[event.flow_name].setdefault(event.user, 0) counts[event.flow_name][event.user] += 1 except ValueError: # Couldn't find any logs.. pass for i, (flow, countdict) in enumerate( sorted( counts.iteritems(), key=lambda x: x[1]["total"], reverse=True)): total_count = countdict["total"] countdict.pop("total") topusercounts = sorted( countdict.iteritems(), key=operator.itemgetter(1), reverse=True)[:3] topusers = ", ".join("%s (%s)" % (user, count) for user, count in topusercounts) ret.stack_chart.data.append( rdf_report_plugins.ApiReportDataSeries2D( # \u2003 is an emspace, a long whitespace character. label=u"%s\u2003Run By: %s" % (flow, topusers), points=[ rdf_report_plugins.ApiReportDataPoint2D( x=i, y=total_count) ])) except IOError: pass return ret class UserActivityReportPlugin(report_plugin_base.ReportPluginBase): """Display user activity by week.""" TYPE = TYPE TITLE = "User Activity" SUMMARY = "Number of flows ran by each user over the last few weeks." # TODO(user): Support timerange selection. WEEKS = 10 def GetReportData(self, get_report_args, token): """Filter the last week of user actions.""" ret = rdf_report_plugins.ApiReportData( representation_type=rdf_report_plugins.ApiReportData.RepresentationType. STACK_CHART) try: user_activity = {} week_duration = rdfvalue.Duration("7d") offset = rdfvalue.Duration(7 * 24 * 60 * 60 * self.__class__.WEEKS) now = rdfvalue.RDFDatetime.Now() try: for fd in report_utils.GetAuditLogFiles(offset, now, token): for event in fd.GenerateItems(): for week in xrange(self.__class__.WEEKS): start = now - week * week_duration if start < event.timestamp < (start + week_duration): weekly_activity = user_activity.setdefault( event.user, [[x, 0] for x in xrange(-self.__class__.WEEKS, 0, 1)]) weekly_activity[-week][1] += 1 except ValueError: # Couldn't find any logs.. pass ret.stack_chart.data = sorted( (rdf_report_plugins.ApiReportDataSeries2D( label=user, points=(rdf_report_plugins.ApiReportDataPoint2D( x=x, y=y) for x, y in data)) for user, data in user_activity.iteritems() if user not in aff4_users.GRRUser.SYSTEM_USERS), key=lambda series: series.label) except IOError: pass return ret class UserFlowsReportPlugin(report_plugin_base.ReportPluginBase): """Count given timerange's user-created flows by type.""" TYPE = TYPE TITLE = "User Flows" SUMMARY = ("Flows launched by GRR users over the given timerange grouped by " "type.") REQUIRES_TIME_RANGE = True def UserFilter(self, username): return username not in aff4_users.GRRUser.SYSTEM_USERS def GetReportData(self, get_report_args, token): ret = rdf_report_plugins.ApiReportData( representation_type=rdf_report_plugins.ApiReportData.RepresentationType. STACK_CHART, stack_chart=rdf_report_plugins.ApiStackChartReportData(x_ticks=[])) # TODO(user): move the calculation to a cronjob and store results in # AFF4. try: timerange_offset = get_report_args.duration timerange_end = get_report_args.start_time + timerange_offset # Store run count total and per-user counts = {} try: for event in report_utils.GetAuditLogEntries(timerange_offset, timerange_end, token): if (event.action == events.AuditEvent.Action.RUN_FLOW and self.UserFilter(event.user)): counts.setdefault(event.flow_name, {"total": 0, event.user: 0}) counts[event.flow_name]["total"] += 1 counts[event.flow_name].setdefault(event.user, 0) counts[event.flow_name][event.user] += 1 except ValueError: # Couldn't find any logs.. pass for i, (flow, countdict) in enumerate( sorted( counts.iteritems(), key=lambda x: x[1]["total"], reverse=True)): total_count = countdict["total"] countdict.pop("total") topusercounts = sorted( countdict.iteritems(), key=operator.itemgetter(1), reverse=True)[:3] topusers = ", ".join("%s (%s)" % (user, count) for user, count in topusercounts) ret.stack_chart.data.append( rdf_report_plugins.ApiReportDataSeries2D( # \u2003 is an emspace, a long whitespace character. label=u"%s\u2003Run By: %s" % (flow, topusers), points=[ rdf_report_plugins.ApiReportDataPoint2D( x=i, y=total_count) ])) except IOError: pass return ret

35.812227

80

0.634435

941

8,201

5.356004

0.191286

0.056746

0.060317

0.046032

0.787698

0.774802

0.735913

0.710714

0.682341

0.664484

0

0.010749

0.273991

8,201

228

81

35.969298

0.835741

0.092672

0

0.694611

0

0.051677

0

0.004386

0

1

0.035928

false

0.047904

0.041916

0.011976

0.233533

0

null

0

1

0

1

0

null

0

4

068f587971ddddcda3f2cb71b5cb66522ba34b28

134

py

Python

Lista_modulos/ex05/ex05.py

SpaceTheArcher/LP2_2s2017

6616b3ecfe5838d1cfac1dac1c8e66b1b661486e

[ "Apache-2.0" ]

1

2017-08-27T03:45:37.000Z

Lista_modulos/ex05/ex05.py

SpaceTheArcher/LP2_2s2017

6616b3ecfe5838d1cfac1dac1c8e66b1b661486e

[ "Apache-2.0" ]

null

Lista_modulos/ex05/ex05.py

SpaceTheArcher/LP2_2s2017

6616b3ecfe5838d1cfac1dac1c8e66b1b661486e

[ "Apache-2.0" ]

null

def sum2(nums): if len(nums) >= 2 : return (nums[0] + nums[1]) elif len(nums) == 1 : return nums[0] else : return 0

19.142857

31

0.529851

22

134

3.227273

0.5

0.197183

0.309859

0

0.074468

0.298507

134

7

32

19.142857

0.680851

0

1

0.142857

false

0

0.571429

0

1

0

null

0

1

0

1

0

null

0

1

0

4

06a5ca3e2b9282df645ea52c4406ab27884a808b

41

py

Python

test_preview.py

amiaynara/link_previewer

1207a7062bc29fc6527b9b788e83d768090d38ce

[ "MIT" ]

null

test_preview.py

amiaynara/link_previewer

1207a7062bc29fc6527b9b788e83d768090d38ce

[ "MIT" ]

1

2021-09-15T15:40:10.000Z

2021-09-16T04:27:07.000Z

test_preview.py

amiaynara/link_previewer

1207a7062bc29fc6527b9b788e83d768090d38ce

[ "MIT" ]

null

""" This tests the get the package. """

10.25

32

0.609756

6

41

4.166667

0.833333

0

0.219512

41

3

33

13.666667

0.78125

0.756098

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

231ebf33a105a3bab681624d2b1c2545e4676fc4

615

py

Python

application/__init__.py

UniversidadeDeVassouras/labproginter-2020.2-IgorRamos-t2

9d922c66d2faef32a9c82f137f5a3cbe3b4bfc0f

[ "Apache-2.0" ]

1

2021-03-28T06:00:27.000Z

application/__init__.py

igoramos77/ava2.0

9d922c66d2faef32a9c82f137f5a3cbe3b4bfc0f

[ "Apache-2.0" ]

null

application/__init__.py

igoramos77/ava2.0

9d922c66d2faef32a9c82f137f5a3cbe3b4bfc0f

[ "Apache-2.0" ]

null

from flask import Flask from flask_session import Session import os app = Flask(__name__, static_folder=os.path.abspath("application/view/static"), template_folder=os.path.abspath("application/view/templates")) app.secret_key = '7777777' app.config['SESSION_TYPE'] = 'filesystem' from application.controller import home_controller from application.controller import disciplina_controller from application.controller import professor_controller from application.controller import aula_controller from application.controller import matriz_curricular_controller from application.controller import periodo_controller

41

142

0.856911

76

615

6.723684

0.381579

0.176125

0.293542

0.363992

0.534247

0.133072

0

0.012324

0.076423

615

15

143

41

0.887324

0

0.126623

0.079545

0

1

0

false

0

0.75

0

0.75

0

null

0

1

0

null

0

1

0

1

0

4

2328f3e9f767713565f176722e3bda2f0a8754b7

167

py

Python

src/main.py

zipzou/captcha-recognition

05b43461f37925d7e0f228ca183d2288e007ca0a

[ "MIT" ]

35

2021-04-15T01:40:20.000Z

2022-03-05T12:03:27.000Z

src/main.py

ChenHuaYou/captcha-recognition

d266f71ad2c2743f9e513eab1c6ee82db9371832

[ "MIT" ]

5

2021-08-06T19:27:53.000Z

2022-03-22T02:05:36.000Z

src/main.py

ChenHuaYou/captcha-recognition

d266f71ad2c2743f9e513eab1c6ee82db9371832

[ "MIT" ]

13

2021-04-15T00:57:26.000Z

2022-03-05T12:03:38.000Z

from train import train from data import get_dict if __name__ == '__main__': train('/Users/frank/Downloads/captchas') # label2id = get_dict() # print(label2id)

20.875

42

0.724551

22

167

5.045455

0.681818

0.126126

0

0.014184

0.155689

167

8

43

20.875

0.77305

0.221557

0

0.304688

0.242188

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

4

233fbbd83b94cea3796ed716e65b271961c88549

91

py

Python

Standard Library/traceback/01_app.py

shubhamnag14/Python-Documents

d3fee0ad90232b413f6ac1b562588fb255b79e42

[ "Apache-2.0" ]

2

2020-11-27T13:21:05.000Z

2021-04-19T21:14:21.000Z

Standard Library/traceback/01_app.py

shubhamnag14/Python-Documents

d3fee0ad90232b413f6ac1b562588fb255b79e42

[ "Apache-2.0" ]

null

Standard Library/traceback/01_app.py

shubhamnag14/Python-Documents

d3fee0ad90232b413f6ac1b562588fb255b79e42

[ "Apache-2.0" ]

1

2021-06-27T20:31:42.000Z

try: 1/0 except Exception as e: print('e : ', e) print(f"repr(e) : {repr(e)}")

15.166667

33

0.505495

16

91

2.875

0.625

0.26087

0

0.030303

0.274725

91

5

34

18.2

0.666667

0

0.252747

0

1

0

true

0

0.4

1

0

null

1

0

1

0

null

0

1

0

4

2359c9a3d36c5f8c677d8030e18f5440235a1aa9

39

py

Python

16-to-2.py

webkadiz/olympiad-problems

620912815904c0f95b91ccd193ca3db0ea20e507

[ "MIT" ]

null

16-to-2.py

webkadiz/olympiad-problems

620912815904c0f95b91ccd193ca3db0ea20e507

[ "MIT" ]

null

16-to-2.py

webkadiz/olympiad-problems

620912815904c0f95b91ccd193ca3db0ea20e507

[ "MIT" ]

null

s = input() print(bin(int(s, 16))[2:])

13

26

0.538462

8

39

2.625

0.875

0

0.088235

0.128205

39

3

26

13

0.529412

0

1

0

false

0

0.5

1

0

null

0

1

0

null

0

1

0

4

23822ad51f8134d0b5e7512fe61c4f955570f7bc

144

py

Python

tests/bmds3/run3.py

shapiromatron/bmds

57562858f3c45e9b9ec23e1c229a8a1de0ea4a70

[ "MIT" ]

2

2017-05-01T20:00:26.000Z

2019-07-09T16:42:25.000Z

tests/analysis/run3.py

shapiromatron/bmds-server

0b2b79b521728582fa66100621e9ea03e251f9f1

[ "MIT" ]

103

2016-11-14T15:58:53.000Z

2022-03-07T21:01:03.000Z

tests/bmds3/run3.py

shapiromatron/bmds

57562858f3c45e9b9ec23e1c229a8a1de0ea4a70

[ "MIT" ]

2

2016-06-28T20:32:00.000Z

2017-02-23T20:30:24.000Z

import os # TODO remove when dll released class RunBmds3: should_run = os.getenv("CI") is None skip_reason = "DLLs not present on CI"

18

42

0.701389

23

144

4.304348

0.913043

0

0.008929

0.222222

144

7

43

20.571429

0.875

0.201389

0

0.212389

0

0.142857

0

1

0

false

0

0.25

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

88bf9936de34f94051c8f23cc11dcff3583497bd

139

py

Python

solutions/__init__.py

clarson469/reinforcementLearning

dafded65aa38d5fff037ce59e620a3d32fb13813

[ "MIT" ]

null

solutions/__init__.py

clarson469/reinforcementLearning

dafded65aa38d5fff037ce59e620a3d32fb13813

[ "MIT" ]

null

solutions/__init__.py

clarson469/reinforcementLearning

dafded65aa38d5fff037ce59e620a3d32fb13813

[ "MIT" ]

null

import os __all__ = [f_name[:-3] for f_name in os.listdir(os.path.dirname(__file__)) if f_name != "__init__.py" and f_name[-3:] == '.py']

34.75

127

0.669065

26

139

2.961538

0.615385

0.25974

0.155844

0

0.016529

0.129496

139

3

128

46.333333

0.619835

0

0.100719

0

1

0

false

0

0.5

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

4

88c7d5284c91ad49177fb1ff56b7d68c71b845c7

88

py

Python

Codeforces/1A Theatre Square.py

a3X3k/Competitive-programing-hacktoberfest-2021

bc3997997318af4c5eafad7348abdd9bf5067b4f

[ "Unlicense" ]

12

2021-06-05T09:40:10.000Z

2021-10-07T17:59:51.000Z

Codeforces/1A Theatre Square.py

a3X3k/Competitive-programing-hacktoberfest-2021

bc3997997318af4c5eafad7348abdd9bf5067b4f

[ "Unlicense" ]

21

2020-10-10T10:41:03.000Z

2020-10-31T10:41:23.000Z

Codeforces/1A Theatre Square.py

a3X3k/Competitive-programing-hacktoberfest-2021

bc3997997318af4c5eafad7348abdd9bf5067b4f

[ "Unlicense" ]

67

2021-08-01T10:04:52.000Z

2021-10-10T00:25:04.000Z

n, m, a = list(map(int, input().split())) print(((n + a - 1) // a) * ((m + a - 1) // a))

44

46

0.409091

17

88

2.117647

0.588235

0.111111

0.166667

0

0.029412

0.227273

88

2

46

44

0.5

0

1

0

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

4

88ed008840a9c15fcf66992c479a06cf9946534c

1,324

py

Python

Transcribing_DNA_into_RNA .py

sujitmandal/Boinformatics

56f4116fd5281bf04b694152b1ea9cf219a6d757

[ "MIT" ]

null

Transcribing_DNA_into_RNA .py

sujitmandal/Boinformatics

56f4116fd5281bf04b694152b1ea9cf219a6d757

[ "MIT" ]

null

Transcribing_DNA_into_RNA .py

sujitmandal/Boinformatics

56f4116fd5281bf04b694152b1ea9cf219a6d757

[ "MIT" ]

null

s = 'GTCGAAGCCATTTCGCCGTGGGGTTGCGCGTGATTCTACCATCAGTTCTTTTTACGGTTCATTTAAACCGGTAATCCAGTAGCGTCAACAAATACTACTCTATGGTTGACTGGAGACGGAACGGGCCCATCGGACGTAATTATGTGGTCTTTGCACGAGCCGGCTGATACAAGCACATGCATCGTGACCACACCGACAAAGTTGTATCTTGGTTCCCGATTTATAACGTCTGCAGAATGAGCCTGTGTGACTATTGTAGTAGGTCCGAATGCCATGTCGGGGCTCCCACCTACGCTGCCTGGCGTCTTTTTGTGCGCAGGTTGTCATTTTCTGGCTTCATAACACCCAGTCCTCAACAAGCGGAAGCCGATCTCACCCTTCCAGTACTTCGTCGACAACGCCGCCATTGTCAACCAAAACCTGTCCTTGAACTAGAGTCGTCTTATCGCACTTAGAGCCTAGCAACCTATCCCGCCATAGAGCTCATTGTAGAAGACCGCAACCCGTGGGGGATCCTATGAGCATACTGCCACTGAAGCTATCGCGGCAGCTAACTGGGATGACCACCGTGTGGAGCCACGCCAGTTCTGATCATCATTTACGTCCACTAAATACTTGGGTCGACCGACAATCGTGGGACTACGCGCGTACAAGCCGGTCGTTCAATAAAGTAGTCAGTCACTTTTCTTCCCACAGAGCTAGACTTGTCAAGCCTCCAATAAGTCAGGGGAGGGGCTGGTCAGCTCAACTACGGGACGGCGGCATAAGTATTGTGCGCAGTGACTGGATACAAGGACTAATACGTCGAGCCTCTGGAGTAGCAGTGTAAGTAAGTAAACATGTGCATGATCTCCGTAGCTATCTCAGGCGTAGGGAGCATGGATAGCATAGGCTGCTCGGATCAGCCTT' ''' Author : Sujit Mandal Github: https://github.com/sujitmandal Package : https://pypi.org/project/images-into-array/ LinkedIn : https://www.linkedin.com/in/sujit-mandal-91215013a/ Facebook : https://www.facebook.com/sujit.mandal.33671748 Twitter : https://twitter.com/mandalsujit37 ''' def RNA(rna): transcribed = rna.replace('T', 'U') print(transcribed) if __name__ == "__main__": RNA(s)

73.555556

915

0.905589

55

1,324

21.654545

0.618182

0.027708

0

0.014151

0.039275

1,324

18

916

73.555556

0.92217

0

0.887066

0.877413

0

1

0

1

0.166667

false

0

0.166667

0

1

null

0

1

null

1

0

4

00124136ba63ec382ab518185fa38b4ed64b607a

356

py

Python

src/schemathesis/__init__.py

barrett-schonefeld/schemathesis

f1f7bfd071b4c541b2c553676e4c18ccfec173ac

[ "MIT" ]

null

src/schemathesis/__init__.py

barrett-schonefeld/schemathesis

f1f7bfd071b4c541b2c553676e4c18ccfec173ac

[ "MIT" ]

null

src/schemathesis/__init__.py

barrett-schonefeld/schemathesis

f1f7bfd071b4c541b2c553676e4c18ccfec173ac

[ "MIT" ]

null

from . import fixups, hooks from .cli import register_check from .constants import __version__ from .loaders import from_dict, from_file, from_path, from_pytest_fixture, from_uri, from_wsgi from .models import Case from .specs import graphql from .specs.openapi._hypothesis import init_default_strategies, register_string_format init_default_strategies()

35.6

94

0.845506

51

356

5.529412

0.54902

0.06383

0.148936

0

0.103933

356

9

95

39.555556

0.884013

0

1

0

true

0

0.875

0

0.875

0

null

0

1

0

null

0

1

0

1

0

1

0

4

002852c268c4bced8379d0e29c070944d82fbc8c

2,238

py

Python

etldjango/etldata/tests.py

DavidCastilloAlvarado/opencovid_ETL

0cd7afcb0e7e6247a01c0aced9aab02b8ad1edaf

[ "MIT" ]

5

2021-05-21T20:02:34.000Z

2021-08-04T21:06:19.000Z

etldjango/etldata/tests.py

DavidCastilloAlvarado/opencovid_ETL

0cd7afcb0e7e6247a01c0aced9aab02b8ad1edaf

[ "MIT" ]

1

2021-06-04T06:17:17.000Z

etldjango/etldata/tests.py

DavidCastilloAlvarado/opencovid_ETL

0cd7afcb0e7e6247a01c0aced9aab02b8ad1edaf

[ "MIT" ]

null

from io import StringIO from django.core.management import call_command from django.test import TestCase class CommandETLOpenCovid2(TestCase): def setUp(self): out = StringIO() call_command('worker_extractor', stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_oxistat(self): out = StringIO() args = ["last"] call_command('worker_t_oxistat', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_vacunas(self): out = StringIO() args = ["last"] call_command('worker_t_vacunas', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_uci_geo(self): out = StringIO() args = ["last"] call_command('worker_t_uci_geo', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_sinadef(self): out = StringIO() args = ["last"] call_command('worker_t_sinadef', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_minsa_muertes(self): out = StringIO() args = ["last"] call_command('worker_t_minsamuertes', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_caphosp(self): out = StringIO() args = ["last"] call_command('worker_t_caphosp', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_posit(self): out = StringIO() args = ["last"] call_command('worker_posit', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_pos_rel(self): out = StringIO() args = ["last"] call_command('worker_pos_rel', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_mov(self): out = StringIO() args = ["last"] call_command('worker_mov', *args, stdout=out) self.assertIn('Work Done!', out.getvalue()) def test_command_resume(self): out = StringIO() call_command('worker_t_resumen', stdout=out) self.assertIn('Work Done!', out.getvalue())

31.521127

64

0.613941

265

2,238

4.977358

0.158491

0.100076

0.125095

0.175133

0.793025

0.744503

0.623199

0.436694

0

0.000593

0.247096

2,238

70

65

31.971429

0.782196

0

0.54386

0

0.140814

0.009388

0

0.192982

1

0.192982

false

0

0.052632

0

0.263158

0

null

0

1

0

1

0

null

0

4

002efa5573cdb4a249651799a5dd229e6c7e7355

62,533

py

Python

auvsi_suas/proto/interop_admin_api_pb2.py

huln24/uavcontrol

8b87174cd8dc8f44d1d042e15d4dea4c98fe2de4

[ "BSD-3-Clause" ]

null

auvsi_suas/proto/interop_admin_api_pb2.py

huln24/uavcontrol

8b87174cd8dc8f44d1d042e15d4dea4c98fe2de4

[ "BSD-3-Clause" ]

null

auvsi_suas/proto/interop_admin_api_pb2.py

huln24/uavcontrol

8b87174cd8dc8f44d1d042e15d4dea4c98fe2de4

[ "BSD-3-Clause" ]

null

# Generated by the protocol buffer compiler. DO NOT EDIT! # source: auvsi_suas/proto/interop_admin_api.proto import sys _b=sys.version_info[0]<3 and (lambda x:x) or (lambda x:x.encode('latin1')) from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() from auvsi_suas.proto import interop_api_pb2 as auvsi__suas_dot_proto_dot_interop__api__pb2 DESCRIPTOR = _descriptor.FileDescriptor( name='auvsi_suas/proto/interop_admin_api.proto', package='auvsi_suas.proto', syntax='proto2', serialized_options=None, serialized_pb=_b('\n(auvsi_suas/proto/interop_admin_api.proto\x12\x10\x61uvsi_suas.proto\x1a\"auvsi_suas/proto/interop_api.proto\"\x8d\x01\n\nOdlcReview\x12$\n\x04odlc\x18\x01 \x01(\x0b\x32\x16.auvsi_suas.proto.Odlc\x12\x1f\n\x17last_modified_timestamp\x18\x02 \x01(\t\x12\x1a\n\x12thumbnail_approved\x18\x03 \x01(\x08\x12\x1c\n\x14\x64\x65scription_approved\x18\x04 \x01(\x08\"P\n\x1aMultiUserMissionEvaluation\x12\x32\n\x05teams\x18\x01 \x03(\x0b\x32#.auvsi_suas.proto.MissionEvaluation\"\xc2\x01\n\x11MissionEvaluation\x12\x0f\n\x07mission\x18\x01 \x01(\x05\x12&\n\x04team\x18\x02 \x01(\x0b\x32\x18.auvsi_suas.proto.TeamId\x12\x10\n\x08warnings\x18\x03 \x03(\t\x12\x33\n\x08\x66\x65\x65\x64\x62\x61\x63k\x18\x04 \x01(\x0b\x32!.auvsi_suas.proto.MissionFeedback\x12-\n\x05score\x18\x05 \x01(\x0b\x32\x1e.auvsi_suas.proto.MissionScore\"\xf0\x02\n\x0fMissionFeedback\x12\"\n\x1auas_telemetry_time_max_sec\x18\x01 \x01(\x01\x12\"\n\x1auas_telemetry_time_avg_sec\x18\x02 \x01(\x01\x12\x37\n\twaypoints\x18\x03 \x03(\x0b\x32$.auvsi_suas.proto.WaypointEvaluation\x12\x42\n\x14stationary_obstacles\x18\x04 \x03(\x0b\x32$.auvsi_suas.proto.ObstacleEvaluation\x12\x33\n\x04odlc\x18\x06 \x01(\x0b\x32%.auvsi_suas.proto.MultiOdlcEvaluation\x12,\n\x03map\x18\x07 \x01(\x0b\x32\x1f.auvsi_suas.proto.MapEvaluation\x12\x35\n\x05judge\x18\x08 \x01(\x0b\x32&.auvsi_suas.proto.MissionJudgeFeedback\"\xba\x01\n\x13MultiOdlcEvaluation\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x1b\n\x13matched_score_ratio\x18\x02 \x01(\x01\x12\"\n\x1a\x65xtra_object_penalty_ratio\x18\x03 \x01(\x01\x12\x1c\n\x14unmatched_odlc_count\x18\x04 \x01(\x05\x12/\n\x05odlcs\x18\x05 \x03(\x0b\x32 .auvsi_suas.proto.OdlcEvaluation\"\x8a\x03\n\x0eOdlcEvaluation\x12\x11\n\treal_odlc\x18\x01 \x01(\x03\x12\x16\n\x0esubmitted_odlc\x18\x02 \x01(\x03\x12\x13\n\x0bscore_ratio\x18\x03 \x01(\x01\x12#\n\x1b\x63lassifications_score_ratio\x18\x04 \x01(\x01\x12\x1f\n\x17geolocation_score_ratio\x18\x05 \x01(\x01\x12\x1e\n\x16\x61\x63tionable_score_ratio\x18\x06 \x01(\x01\x12\x1e\n\x16\x61utonomous_score_ratio\x18\x07 \x01(\x01\x12\x16\n\x0eimage_approved\x18\t \x01(\x08\x12\x1c\n\x14\x64\x65scription_approved\x18\n \x01(\x08\x12\x1d\n\x15\x63lassifications_ratio\x18\x0b \x01(\x01\x12\x1f\n\x17geolocation_accuracy_ft\x18\x0c \x01(\x01\x12\x1d\n\x15\x61\x63tionable_submission\x18\r \x01(\x08\x12\x1d\n\x15\x61utonomous_submission\x18\x0e \x01(\x08\"\x82\x01\n\rMapEvaluation\x12;\n\x07quality\x18\x01 \x01(\x0e\x32*.auvsi_suas.proto.MapEvaluation.MapQuality\"4\n\nMapQuality\x12\x10\n\x0cINSUFFICIENT\x10\x00\x12\n\n\x06MEDIUM\x10\x01\x12\x08\n\x04HIGH\x10\x02\"\x93\x04\n\x14MissionJudgeFeedback\x12\x17\n\x0f\x66light_time_sec\x18\x01 \x01(\x01\x12\x1d\n\x15post_process_time_sec\x18\x02 \x01(\x01\x12\x14\n\x0cused_timeout\x18\x03 \x01(\x08\x12\x1c\n\x14min_auto_flight_time\x18\x04 \x01(\x08\x12\x1e\n\x16safety_pilot_takeovers\x18\x05 \x01(\x05\x12\x1a\n\x12waypoints_captured\x18\x06 \x01(\x05\x12\x15\n\rout_of_bounds\x18\x07 \x01(\x05\x12\x1c\n\x14unsafe_out_of_bounds\x18\x08 \x01(\x05\x12\x1b\n\x13things_fell_off_uas\x18\t \x01(\x08\x12\x0f\n\x07\x63rashed\x18\n \x01(\x08\x12Q\n\x11\x61ir_drop_accuracy\x18\x0b \x01(\x0e\x32\x36.auvsi_suas.proto.MissionJudgeFeedback.AirDropAccuracy\x12\x1d\n\x15ugv_drove_to_location\x18\x0c \x01(\x08\x12&\n\x1eoperational_excellence_percent\x18\r \x01(\x01\"V\n\x0f\x41irDropAccuracy\x12\r\n\tNO_POINTS\x10\x00\x12\x10\n\x0cWITHIN_05_FT\x10\x01\x12\x10\n\x0cWITHIN_15_FT\x10\x02\x12\x10\n\x0cWITHIN_40_FT\x10\x03\"}\n\x12WaypointEvaluation\x12\n\n\x02id\x18\x01 \x01(\x03\x12\x13\n\x0bscore_ratio\x18\x02 \x01(\x01\x12&\n\x1e\x63losest_for_scored_approach_ft\x18\x03 \x01(\x01\x12\x1e\n\x16\x63losest_for_mission_ft\x18\x04 \x01(\x01\"-\n\x12ObstacleEvaluation\x12\n\n\x02id\x18\x01 \x01(\x03\x12\x0b\n\x03hit\x18\x02 \x01(\x08\"\xb8\x03\n\x0cMissionScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x31\n\x08timeline\x18\x02 \x01(\x0b\x32\x1f.auvsi_suas.proto.TimelineScore\x12\x42\n\x11\x61utonomous_flight\x18\x03 \x01(\x0b\x32\'.auvsi_suas.proto.AutonomousFlightScore\x12\x44\n\x12obstacle_avoidance\x18\x04 \x01(\x0b\x32(.auvsi_suas.proto.ObstacleAvoidanceScore\x12-\n\x06object\x18\x05 \x01(\x0b\x32\x1d.auvsi_suas.proto.ObjectScore\x12\'\n\x03map\x18\x08 \x01(\x0b\x32\x1a.auvsi_suas.proto.MapScore\x12\x30\n\x08\x61ir_drop\x18\x06 \x01(\x0b\x32\x1e.auvsi_suas.proto.AirDropScore\x12L\n\x16operational_excellence\x18\x07 \x01(\x0b\x32,.auvsi_suas.proto.OperationalExcellenceScore\"d\n\rTimelineScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x14\n\x0cmission_time\x18\x02 \x01(\x01\x12\x17\n\x0fmission_penalty\x18\x03 \x01(\x01\x12\x0f\n\x07timeout\x18\x04 \x01(\x01\"\xe7\x01\n\x15\x41utonomousFlightScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x1e\n\x16telemetry_prerequisite\x18\x02 \x01(\x08\x12\x19\n\x11waypoint_accuracy\x18\x05 \x01(\x01\x12%\n\x1dsafety_pilot_takeover_penalty\x18\x06 \x01(\x01\x12\x1d\n\x15out_of_bounds_penalty\x18\x07 \x01(\x01\x12\x1f\n\x17things_fell_off_penalty\x18\x08 \x01(\x01\x12\x17\n\x0f\x63rashed_penalty\x18\t \x01(\x01\"M\n\x16ObstacleAvoidanceScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x1e\n\x16telemetry_prerequisite\x18\x02 \x01(\x08\"\x94\x01\n\x0bObjectScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x17\n\x0f\x63haracteristics\x18\x02 \x01(\x01\x12\x13\n\x0bgeolocation\x18\x03 \x01(\x01\x12\x12\n\nactionable\x18\x04 \x01(\x01\x12\x10\n\x08\x61utonomy\x18\x05 \x01(\x01\x12\x1c\n\x14\x65xtra_object_penalty\x18\x07 \x01(\x01\"\x1f\n\x08MapScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\"U\n\x0c\x41irDropScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\x12\x15\n\rdrop_accuracy\x18\x02 \x01(\x01\x12\x19\n\x11\x64rive_to_location\x18\x03 \x01(\x01\"1\n\x1aOperationalExcellenceScore\x12\x13\n\x0bscore_ratio\x18\x01 \x01(\x01\";\n\x14GpsConversionRequest\x12\x10\n\x08latitude\x18\x01 \x01(\t\x12\x11\n\tlongitude\x18\x02 \x01(\t\"<\n\x15GpsConversionResponse\x12\x10\n\x08latitude\x18\x01 \x01(\x01\x12\x11\n\tlongitude\x18\x02 \x01(\x01') , dependencies=[auvsi__suas_dot_proto_dot_interop__api__pb2.DESCRIPTOR,]) _MAPEVALUATION_MAPQUALITY = _descriptor.EnumDescriptor( name='MapQuality', full_name='auvsi_suas.proto.MapEvaluation.MapQuality', filename=None, file=DESCRIPTOR, values=[ _descriptor.EnumValueDescriptor( name='INSUFFICIENT', index=0, number=0, serialized_options=None, type=None), _descriptor.EnumValueDescriptor( name='MEDIUM', index=1, number=1, serialized_options=None, type=None), _descriptor.EnumValueDescriptor( name='HIGH', index=2, number=2, serialized_options=None, type=None), ], containing_type=None, serialized_options=None, serialized_start=1557, serialized_end=1609, ) _sym_db.RegisterEnumDescriptor(_MAPEVALUATION_MAPQUALITY) _MISSIONJUDGEFEEDBACK_AIRDROPACCURACY = _descriptor.EnumDescriptor( name='AirDropAccuracy', full_name='auvsi_suas.proto.MissionJudgeFeedback.AirDropAccuracy', filename=None, file=DESCRIPTOR, values=[ _descriptor.EnumValueDescriptor( name='NO_POINTS', index=0, number=0, serialized_options=None, type=None), _descriptor.EnumValueDescriptor( name='WITHIN_05_FT', index=1, number=1, serialized_options=None, type=None), _descriptor.EnumValueDescriptor( name='WITHIN_15_FT', index=2, number=2, serialized_options=None, type=None), _descriptor.EnumValueDescriptor( name='WITHIN_40_FT', index=3, number=3, serialized_options=None, type=None), ], containing_type=None, serialized_options=None, serialized_start=2057, serialized_end=2143, ) _sym_db.RegisterEnumDescriptor(_MISSIONJUDGEFEEDBACK_AIRDROPACCURACY) _ODLCREVIEW = _descriptor.Descriptor( name='OdlcReview', full_name='auvsi_suas.proto.OdlcReview', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='odlc', full_name='auvsi_suas.proto.OdlcReview.odlc', index=0, number=1, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='last_modified_timestamp', full_name='auvsi_suas.proto.OdlcReview.last_modified_timestamp', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='thumbnail_approved', full_name='auvsi_suas.proto.OdlcReview.thumbnail_approved', index=2, number=3, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description_approved', full_name='auvsi_suas.proto.OdlcReview.description_approved', index=3, number=4, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=99, serialized_end=240, ) _MULTIUSERMISSIONEVALUATION = _descriptor.Descriptor( name='MultiUserMissionEvaluation', full_name='auvsi_suas.proto.MultiUserMissionEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='teams', full_name='auvsi_suas.proto.MultiUserMissionEvaluation.teams', index=0, number=1, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=242, serialized_end=322, ) _MISSIONEVALUATION = _descriptor.Descriptor( name='MissionEvaluation', full_name='auvsi_suas.proto.MissionEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='mission', full_name='auvsi_suas.proto.MissionEvaluation.mission', index=0, number=1, type=5, cpp_type=1, label=1, 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), _descriptor.FieldDescriptor( name='team', full_name='auvsi_suas.proto.MissionEvaluation.team', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='warnings', full_name='auvsi_suas.proto.MissionEvaluation.warnings', index=2, number=3, type=9, cpp_type=9, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='feedback', full_name='auvsi_suas.proto.MissionEvaluation.feedback', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='score', full_name='auvsi_suas.proto.MissionEvaluation.score', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=325, serialized_end=519, ) _MISSIONFEEDBACK = _descriptor.Descriptor( name='MissionFeedback', full_name='auvsi_suas.proto.MissionFeedback', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='uas_telemetry_time_max_sec', full_name='auvsi_suas.proto.MissionFeedback.uas_telemetry_time_max_sec', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='uas_telemetry_time_avg_sec', full_name='auvsi_suas.proto.MissionFeedback.uas_telemetry_time_avg_sec', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='waypoints', full_name='auvsi_suas.proto.MissionFeedback.waypoints', index=2, number=3, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='stationary_obstacles', full_name='auvsi_suas.proto.MissionFeedback.stationary_obstacles', index=3, number=4, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='odlc', full_name='auvsi_suas.proto.MissionFeedback.odlc', index=4, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='map', full_name='auvsi_suas.proto.MissionFeedback.map', index=5, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='judge', full_name='auvsi_suas.proto.MissionFeedback.judge', index=6, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=522, serialized_end=890, ) _MULTIODLCEVALUATION = _descriptor.Descriptor( name='MultiOdlcEvaluation', full_name='auvsi_suas.proto.MultiOdlcEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.MultiOdlcEvaluation.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='matched_score_ratio', full_name='auvsi_suas.proto.MultiOdlcEvaluation.matched_score_ratio', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='extra_object_penalty_ratio', full_name='auvsi_suas.proto.MultiOdlcEvaluation.extra_object_penalty_ratio', index=2, number=3, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='unmatched_odlc_count', full_name='auvsi_suas.proto.MultiOdlcEvaluation.unmatched_odlc_count', index=3, number=4, type=5, cpp_type=1, label=1, 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), _descriptor.FieldDescriptor( name='odlcs', full_name='auvsi_suas.proto.MultiOdlcEvaluation.odlcs', index=4, number=5, type=11, cpp_type=10, label=3, has_default_value=False, default_value=[], message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=893, serialized_end=1079, ) _ODLCEVALUATION = _descriptor.Descriptor( name='OdlcEvaluation', full_name='auvsi_suas.proto.OdlcEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='real_odlc', full_name='auvsi_suas.proto.OdlcEvaluation.real_odlc', index=0, number=1, type=3, cpp_type=2, label=1, 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), _descriptor.FieldDescriptor( name='submitted_odlc', full_name='auvsi_suas.proto.OdlcEvaluation.submitted_odlc', index=1, number=2, type=3, cpp_type=2, label=1, 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), _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.OdlcEvaluation.score_ratio', index=2, number=3, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='classifications_score_ratio', full_name='auvsi_suas.proto.OdlcEvaluation.classifications_score_ratio', index=3, number=4, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='geolocation_score_ratio', full_name='auvsi_suas.proto.OdlcEvaluation.geolocation_score_ratio', index=4, number=5, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='actionable_score_ratio', full_name='auvsi_suas.proto.OdlcEvaluation.actionable_score_ratio', index=5, number=6, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='autonomous_score_ratio', full_name='auvsi_suas.proto.OdlcEvaluation.autonomous_score_ratio', index=6, number=7, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='image_approved', full_name='auvsi_suas.proto.OdlcEvaluation.image_approved', index=7, number=9, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='description_approved', full_name='auvsi_suas.proto.OdlcEvaluation.description_approved', index=8, number=10, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='classifications_ratio', full_name='auvsi_suas.proto.OdlcEvaluation.classifications_ratio', index=9, number=11, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='geolocation_accuracy_ft', full_name='auvsi_suas.proto.OdlcEvaluation.geolocation_accuracy_ft', index=10, number=12, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='actionable_submission', full_name='auvsi_suas.proto.OdlcEvaluation.actionable_submission', index=11, number=13, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='autonomous_submission', full_name='auvsi_suas.proto.OdlcEvaluation.autonomous_submission', index=12, number=14, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=1082, serialized_end=1476, ) _MAPEVALUATION = _descriptor.Descriptor( name='MapEvaluation', full_name='auvsi_suas.proto.MapEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='quality', full_name='auvsi_suas.proto.MapEvaluation.quality', index=0, number=1, type=14, cpp_type=8, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ _MAPEVALUATION_MAPQUALITY, ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=1479, serialized_end=1609, ) _MISSIONJUDGEFEEDBACK = _descriptor.Descriptor( name='MissionJudgeFeedback', full_name='auvsi_suas.proto.MissionJudgeFeedback', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='flight_time_sec', full_name='auvsi_suas.proto.MissionJudgeFeedback.flight_time_sec', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='post_process_time_sec', full_name='auvsi_suas.proto.MissionJudgeFeedback.post_process_time_sec', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='used_timeout', full_name='auvsi_suas.proto.MissionJudgeFeedback.used_timeout', index=2, number=3, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='min_auto_flight_time', full_name='auvsi_suas.proto.MissionJudgeFeedback.min_auto_flight_time', index=3, number=4, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='safety_pilot_takeovers', full_name='auvsi_suas.proto.MissionJudgeFeedback.safety_pilot_takeovers', index=4, number=5, type=5, cpp_type=1, label=1, 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), _descriptor.FieldDescriptor( name='waypoints_captured', full_name='auvsi_suas.proto.MissionJudgeFeedback.waypoints_captured', index=5, number=6, type=5, cpp_type=1, label=1, 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), _descriptor.FieldDescriptor( name='out_of_bounds', full_name='auvsi_suas.proto.MissionJudgeFeedback.out_of_bounds', index=6, number=7, type=5, cpp_type=1, label=1, 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), _descriptor.FieldDescriptor( name='unsafe_out_of_bounds', full_name='auvsi_suas.proto.MissionJudgeFeedback.unsafe_out_of_bounds', index=7, number=8, type=5, cpp_type=1, label=1, 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), _descriptor.FieldDescriptor( name='things_fell_off_uas', full_name='auvsi_suas.proto.MissionJudgeFeedback.things_fell_off_uas', index=8, number=9, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='crashed', full_name='auvsi_suas.proto.MissionJudgeFeedback.crashed', index=9, number=10, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='air_drop_accuracy', full_name='auvsi_suas.proto.MissionJudgeFeedback.air_drop_accuracy', index=10, number=11, type=14, cpp_type=8, label=1, 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), _descriptor.FieldDescriptor( name='ugv_drove_to_location', full_name='auvsi_suas.proto.MissionJudgeFeedback.ugv_drove_to_location', index=11, number=12, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='operational_excellence_percent', full_name='auvsi_suas.proto.MissionJudgeFeedback.operational_excellence_percent', index=12, number=13, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ _MISSIONJUDGEFEEDBACK_AIRDROPACCURACY, ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=1612, serialized_end=2143, ) _WAYPOINTEVALUATION = _descriptor.Descriptor( name='WaypointEvaluation', full_name='auvsi_suas.proto.WaypointEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='auvsi_suas.proto.WaypointEvaluation.id', index=0, number=1, type=3, cpp_type=2, label=1, 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), _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.WaypointEvaluation.score_ratio', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='closest_for_scored_approach_ft', full_name='auvsi_suas.proto.WaypointEvaluation.closest_for_scored_approach_ft', index=2, number=3, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='closest_for_mission_ft', full_name='auvsi_suas.proto.WaypointEvaluation.closest_for_mission_ft', index=3, number=4, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=2145, serialized_end=2270, ) _OBSTACLEEVALUATION = _descriptor.Descriptor( name='ObstacleEvaluation', full_name='auvsi_suas.proto.ObstacleEvaluation', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='id', full_name='auvsi_suas.proto.ObstacleEvaluation.id', index=0, number=1, type=3, cpp_type=2, label=1, 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), _descriptor.FieldDescriptor( name='hit', full_name='auvsi_suas.proto.ObstacleEvaluation.hit', index=1, number=2, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=2272, serialized_end=2317, ) _MISSIONSCORE = _descriptor.Descriptor( name='MissionScore', full_name='auvsi_suas.proto.MissionScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.MissionScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='timeline', full_name='auvsi_suas.proto.MissionScore.timeline', index=1, number=2, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='autonomous_flight', full_name='auvsi_suas.proto.MissionScore.autonomous_flight', index=2, number=3, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='obstacle_avoidance', full_name='auvsi_suas.proto.MissionScore.obstacle_avoidance', index=3, number=4, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='object', full_name='auvsi_suas.proto.MissionScore.object', index=4, number=5, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='map', full_name='auvsi_suas.proto.MissionScore.map', index=5, number=8, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='air_drop', full_name='auvsi_suas.proto.MissionScore.air_drop', index=6, number=6, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='operational_excellence', full_name='auvsi_suas.proto.MissionScore.operational_excellence', index=7, number=7, type=11, cpp_type=10, label=1, has_default_value=False, default_value=None, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=2320, serialized_end=2760, ) _TIMELINESCORE = _descriptor.Descriptor( name='TimelineScore', full_name='auvsi_suas.proto.TimelineScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.TimelineScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='mission_time', full_name='auvsi_suas.proto.TimelineScore.mission_time', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='mission_penalty', full_name='auvsi_suas.proto.TimelineScore.mission_penalty', index=2, number=3, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='timeout', full_name='auvsi_suas.proto.TimelineScore.timeout', index=3, number=4, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=2762, serialized_end=2862, ) _AUTONOMOUSFLIGHTSCORE = _descriptor.Descriptor( name='AutonomousFlightScore', full_name='auvsi_suas.proto.AutonomousFlightScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.AutonomousFlightScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='telemetry_prerequisite', full_name='auvsi_suas.proto.AutonomousFlightScore.telemetry_prerequisite', index=1, number=2, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='waypoint_accuracy', full_name='auvsi_suas.proto.AutonomousFlightScore.waypoint_accuracy', index=2, number=5, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='safety_pilot_takeover_penalty', full_name='auvsi_suas.proto.AutonomousFlightScore.safety_pilot_takeover_penalty', index=3, number=6, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='out_of_bounds_penalty', full_name='auvsi_suas.proto.AutonomousFlightScore.out_of_bounds_penalty', index=4, number=7, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='things_fell_off_penalty', full_name='auvsi_suas.proto.AutonomousFlightScore.things_fell_off_penalty', index=5, number=8, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='crashed_penalty', full_name='auvsi_suas.proto.AutonomousFlightScore.crashed_penalty', index=6, number=9, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=2865, serialized_end=3096, ) _OBSTACLEAVOIDANCESCORE = _descriptor.Descriptor( name='ObstacleAvoidanceScore', full_name='auvsi_suas.proto.ObstacleAvoidanceScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.ObstacleAvoidanceScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='telemetry_prerequisite', full_name='auvsi_suas.proto.ObstacleAvoidanceScore.telemetry_prerequisite', index=1, number=2, type=8, cpp_type=7, label=1, has_default_value=False, default_value=False, message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3098, serialized_end=3175, ) _OBJECTSCORE = _descriptor.Descriptor( name='ObjectScore', full_name='auvsi_suas.proto.ObjectScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.ObjectScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='characteristics', full_name='auvsi_suas.proto.ObjectScore.characteristics', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='geolocation', full_name='auvsi_suas.proto.ObjectScore.geolocation', index=2, number=3, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='actionable', full_name='auvsi_suas.proto.ObjectScore.actionable', index=3, number=4, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='autonomy', full_name='auvsi_suas.proto.ObjectScore.autonomy', index=4, number=5, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='extra_object_penalty', full_name='auvsi_suas.proto.ObjectScore.extra_object_penalty', index=5, number=7, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3178, serialized_end=3326, ) _MAPSCORE = _descriptor.Descriptor( name='MapScore', full_name='auvsi_suas.proto.MapScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.MapScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3328, serialized_end=3359, ) _AIRDROPSCORE = _descriptor.Descriptor( name='AirDropScore', full_name='auvsi_suas.proto.AirDropScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.AirDropScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='drop_accuracy', full_name='auvsi_suas.proto.AirDropScore.drop_accuracy', index=1, number=2, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='drive_to_location', full_name='auvsi_suas.proto.AirDropScore.drive_to_location', index=2, number=3, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3361, serialized_end=3446, ) _OPERATIONALEXCELLENCESCORE = _descriptor.Descriptor( name='OperationalExcellenceScore', full_name='auvsi_suas.proto.OperationalExcellenceScore', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='score_ratio', full_name='auvsi_suas.proto.OperationalExcellenceScore.score_ratio', index=0, number=1, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3448, serialized_end=3497, ) _GPSCONVERSIONREQUEST = _descriptor.Descriptor( name='GpsConversionRequest', full_name='auvsi_suas.proto.GpsConversionRequest', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='latitude', full_name='auvsi_suas.proto.GpsConversionRequest.latitude', index=0, number=1, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), _descriptor.FieldDescriptor( name='longitude', full_name='auvsi_suas.proto.GpsConversionRequest.longitude', index=1, number=2, type=9, cpp_type=9, label=1, has_default_value=False, default_value=_b("").decode('utf-8'), message_type=None, enum_type=None, containing_type=None, is_extension=False, extension_scope=None, serialized_options=None, file=DESCRIPTOR), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3499, serialized_end=3558, ) _GPSCONVERSIONRESPONSE = _descriptor.Descriptor( name='GpsConversionResponse', full_name='auvsi_suas.proto.GpsConversionResponse', filename=None, file=DESCRIPTOR, containing_type=None, fields=[ _descriptor.FieldDescriptor( name='latitude', full_name='auvsi_suas.proto.GpsConversionResponse.latitude', index=0, number=1, type=1, cpp_type=5, label=1, 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), _descriptor.FieldDescriptor( name='longitude', full_name='auvsi_suas.proto.GpsConversionResponse.longitude', index=1, number=2, type=1, cpp_type=5, label=1, 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), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto2', extension_ranges=[], oneofs=[ ], serialized_start=3560, serialized_end=3620, ) _ODLCREVIEW.fields_by_name['odlc'].message_type = auvsi__suas_dot_proto_dot_interop__api__pb2._ODLC _MULTIUSERMISSIONEVALUATION.fields_by_name['teams'].message_type = _MISSIONEVALUATION _MISSIONEVALUATION.fields_by_name['team'].message_type = auvsi__suas_dot_proto_dot_interop__api__pb2._TEAMID _MISSIONEVALUATION.fields_by_name['feedback'].message_type = _MISSIONFEEDBACK _MISSIONEVALUATION.fields_by_name['score'].message_type = _MISSIONSCORE _MISSIONFEEDBACK.fields_by_name['waypoints'].message_type = _WAYPOINTEVALUATION _MISSIONFEEDBACK.fields_by_name['stationary_obstacles'].message_type = _OBSTACLEEVALUATION _MISSIONFEEDBACK.fields_by_name['odlc'].message_type = _MULTIODLCEVALUATION _MISSIONFEEDBACK.fields_by_name['map'].message_type = _MAPEVALUATION _MISSIONFEEDBACK.fields_by_name['judge'].message_type = _MISSIONJUDGEFEEDBACK _MULTIODLCEVALUATION.fields_by_name['odlcs'].message_type = _ODLCEVALUATION _MAPEVALUATION.fields_by_name['quality'].enum_type = _MAPEVALUATION_MAPQUALITY _MAPEVALUATION_MAPQUALITY.containing_type = _MAPEVALUATION _MISSIONJUDGEFEEDBACK.fields_by_name['air_drop_accuracy'].enum_type = _MISSIONJUDGEFEEDBACK_AIRDROPACCURACY _MISSIONJUDGEFEEDBACK_AIRDROPACCURACY.containing_type = _MISSIONJUDGEFEEDBACK _MISSIONSCORE.fields_by_name['timeline'].message_type = _TIMELINESCORE _MISSIONSCORE.fields_by_name['autonomous_flight'].message_type = _AUTONOMOUSFLIGHTSCORE _MISSIONSCORE.fields_by_name['obstacle_avoidance'].message_type = _OBSTACLEAVOIDANCESCORE _MISSIONSCORE.fields_by_name['object'].message_type = _OBJECTSCORE _MISSIONSCORE.fields_by_name['map'].message_type = _MAPSCORE _MISSIONSCORE.fields_by_name['air_drop'].message_type = _AIRDROPSCORE _MISSIONSCORE.fields_by_name['operational_excellence'].message_type = _OPERATIONALEXCELLENCESCORE DESCRIPTOR.message_types_by_name['OdlcReview'] = _ODLCREVIEW DESCRIPTOR.message_types_by_name['MultiUserMissionEvaluation'] = _MULTIUSERMISSIONEVALUATION DESCRIPTOR.message_types_by_name['MissionEvaluation'] = _MISSIONEVALUATION DESCRIPTOR.message_types_by_name['MissionFeedback'] = _MISSIONFEEDBACK DESCRIPTOR.message_types_by_name['MultiOdlcEvaluation'] = _MULTIODLCEVALUATION DESCRIPTOR.message_types_by_name['OdlcEvaluation'] = _ODLCEVALUATION DESCRIPTOR.message_types_by_name['MapEvaluation'] = _MAPEVALUATION DESCRIPTOR.message_types_by_name['MissionJudgeFeedback'] = _MISSIONJUDGEFEEDBACK DESCRIPTOR.message_types_by_name['WaypointEvaluation'] = _WAYPOINTEVALUATION DESCRIPTOR.message_types_by_name['ObstacleEvaluation'] = _OBSTACLEEVALUATION DESCRIPTOR.message_types_by_name['MissionScore'] = _MISSIONSCORE DESCRIPTOR.message_types_by_name['TimelineScore'] = _TIMELINESCORE DESCRIPTOR.message_types_by_name['AutonomousFlightScore'] = _AUTONOMOUSFLIGHTSCORE DESCRIPTOR.message_types_by_name['ObstacleAvoidanceScore'] = _OBSTACLEAVOIDANCESCORE DESCRIPTOR.message_types_by_name['ObjectScore'] = _OBJECTSCORE DESCRIPTOR.message_types_by_name['MapScore'] = _MAPSCORE DESCRIPTOR.message_types_by_name['AirDropScore'] = _AIRDROPSCORE DESCRIPTOR.message_types_by_name['OperationalExcellenceScore'] = _OPERATIONALEXCELLENCESCORE DESCRIPTOR.message_types_by_name['GpsConversionRequest'] = _GPSCONVERSIONREQUEST DESCRIPTOR.message_types_by_name['GpsConversionResponse'] = _GPSCONVERSIONRESPONSE _sym_db.RegisterFileDescriptor(DESCRIPTOR) OdlcReview = _reflection.GeneratedProtocolMessageType('OdlcReview', (_message.Message,), dict( DESCRIPTOR = _ODLCREVIEW, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.OdlcReview) )) _sym_db.RegisterMessage(OdlcReview) MultiUserMissionEvaluation = _reflection.GeneratedProtocolMessageType('MultiUserMissionEvaluation', (_message.Message,), dict( DESCRIPTOR = _MULTIUSERMISSIONEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MultiUserMissionEvaluation) )) _sym_db.RegisterMessage(MultiUserMissionEvaluation) MissionEvaluation = _reflection.GeneratedProtocolMessageType('MissionEvaluation', (_message.Message,), dict( DESCRIPTOR = _MISSIONEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MissionEvaluation) )) _sym_db.RegisterMessage(MissionEvaluation) MissionFeedback = _reflection.GeneratedProtocolMessageType('MissionFeedback', (_message.Message,), dict( DESCRIPTOR = _MISSIONFEEDBACK, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MissionFeedback) )) _sym_db.RegisterMessage(MissionFeedback) MultiOdlcEvaluation = _reflection.GeneratedProtocolMessageType('MultiOdlcEvaluation', (_message.Message,), dict( DESCRIPTOR = _MULTIODLCEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MultiOdlcEvaluation) )) _sym_db.RegisterMessage(MultiOdlcEvaluation) OdlcEvaluation = _reflection.GeneratedProtocolMessageType('OdlcEvaluation', (_message.Message,), dict( DESCRIPTOR = _ODLCEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.OdlcEvaluation) )) _sym_db.RegisterMessage(OdlcEvaluation) MapEvaluation = _reflection.GeneratedProtocolMessageType('MapEvaluation', (_message.Message,), dict( DESCRIPTOR = _MAPEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MapEvaluation) )) _sym_db.RegisterMessage(MapEvaluation) MissionJudgeFeedback = _reflection.GeneratedProtocolMessageType('MissionJudgeFeedback', (_message.Message,), dict( DESCRIPTOR = _MISSIONJUDGEFEEDBACK, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MissionJudgeFeedback) )) _sym_db.RegisterMessage(MissionJudgeFeedback) WaypointEvaluation = _reflection.GeneratedProtocolMessageType('WaypointEvaluation', (_message.Message,), dict( DESCRIPTOR = _WAYPOINTEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.WaypointEvaluation) )) _sym_db.RegisterMessage(WaypointEvaluation) ObstacleEvaluation = _reflection.GeneratedProtocolMessageType('ObstacleEvaluation', (_message.Message,), dict( DESCRIPTOR = _OBSTACLEEVALUATION, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.ObstacleEvaluation) )) _sym_db.RegisterMessage(ObstacleEvaluation) MissionScore = _reflection.GeneratedProtocolMessageType('MissionScore', (_message.Message,), dict( DESCRIPTOR = _MISSIONSCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MissionScore) )) _sym_db.RegisterMessage(MissionScore) TimelineScore = _reflection.GeneratedProtocolMessageType('TimelineScore', (_message.Message,), dict( DESCRIPTOR = _TIMELINESCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.TimelineScore) )) _sym_db.RegisterMessage(TimelineScore) AutonomousFlightScore = _reflection.GeneratedProtocolMessageType('AutonomousFlightScore', (_message.Message,), dict( DESCRIPTOR = _AUTONOMOUSFLIGHTSCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.AutonomousFlightScore) )) _sym_db.RegisterMessage(AutonomousFlightScore) ObstacleAvoidanceScore = _reflection.GeneratedProtocolMessageType('ObstacleAvoidanceScore', (_message.Message,), dict( DESCRIPTOR = _OBSTACLEAVOIDANCESCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.ObstacleAvoidanceScore) )) _sym_db.RegisterMessage(ObstacleAvoidanceScore) ObjectScore = _reflection.GeneratedProtocolMessageType('ObjectScore', (_message.Message,), dict( DESCRIPTOR = _OBJECTSCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.ObjectScore) )) _sym_db.RegisterMessage(ObjectScore) MapScore = _reflection.GeneratedProtocolMessageType('MapScore', (_message.Message,), dict( DESCRIPTOR = _MAPSCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.MapScore) )) _sym_db.RegisterMessage(MapScore) AirDropScore = _reflection.GeneratedProtocolMessageType('AirDropScore', (_message.Message,), dict( DESCRIPTOR = _AIRDROPSCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.AirDropScore) )) _sym_db.RegisterMessage(AirDropScore) OperationalExcellenceScore = _reflection.GeneratedProtocolMessageType('OperationalExcellenceScore', (_message.Message,), dict( DESCRIPTOR = _OPERATIONALEXCELLENCESCORE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.OperationalExcellenceScore) )) _sym_db.RegisterMessage(OperationalExcellenceScore) GpsConversionRequest = _reflection.GeneratedProtocolMessageType('GpsConversionRequest', (_message.Message,), dict( DESCRIPTOR = _GPSCONVERSIONREQUEST, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.GpsConversionRequest) )) _sym_db.RegisterMessage(GpsConversionRequest) GpsConversionResponse = _reflection.GeneratedProtocolMessageType('GpsConversionResponse', (_message.Message,), dict( DESCRIPTOR = _GPSCONVERSIONRESPONSE, __module__ = 'auvsi_suas.proto.interop_admin_api_pb2' # @@protoc_insertion_point(class_scope:auvsi_suas.proto.GpsConversionResponse) )) _sym_db.RegisterMessage(GpsConversionResponse) # @@protoc_insertion_point(module_scope)

44.98777

6,035

0.761166

7,882

62,533

5.72951

0.054047

0.053499

0.055492

0.045438

0.737555

0.7095

0.635452

0.608725

0.5938

0.581466

0

0.039615

0.1212

62,533

1,389

6,036

45.020158

0.782163

0.02613

0

0.712074

1

0.001548

0.239084

0.206804

0

1

0

false

0

0.004644

0

0.004644

0

null

0

1

0

1

0

1

0

null

0

4

004a4d0f2e746c789317928f7b89978730f40928

689

py

Python

gym/envs/safety/__init__.py

guilhermeprokisch/openAIGymTest

fe2c15ba30620ae59172ff2d089857fac7cc86d6

[ "MIT" ]

null

gym/envs/safety/__init__.py

guilhermeprokisch/openAIGymTest

fe2c15ba30620ae59172ff2d089857fac7cc86d6

[ "MIT" ]

null

gym/envs/safety/__init__.py

guilhermeprokisch/openAIGymTest

fe2c15ba30620ae59172ff2d089857fac7cc86d6

[ "MIT" ]

null

# interpretability envs from gym.envs.safety.predict_actions_cartpole import PredictActionsCartpoleEnv from gym.envs.safety.predict_obs_cartpole import PredictObsCartpoleEnv # semi_supervised envs # probably the easiest: from gym.envs.safety.semisuper_pendulum_noise import SemisuperPendulumNoiseEnv # somewhat harder because of higher variance: from gym.envs.safety.semisuper_pendulum_random import SemisuperPendulumRandomEnv # probably the hardest because you only get a constant number of rewards in total: from gym.envs.safety.semisuper_pendulum_decay import SemisuperPendulumDecayEnv # off_switch envs from gym.envs.safety.offswitch_cartpole import OffSwitchCartpoleEnv

45.933333

86

0.854862

84

689

6.857143

0.535714

0.072917

0.114583

0.177083

0.303819

0.177083

0

0.105951

689

14

87

49.214286

0.935065

0.297533

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

cc418c974ade252983d4a5b040b796ef6eddf811

512

py

Python

moceansdk/modules/voice/mc_object/play.py

d3no/mocean-sdk-python

cbc215a0eb8aa26c04afb940eab6482f23150c75

[ "MIT" ]

2

2019-10-31T02:37:43.000Z

2021-07-25T02:45:27.000Z

moceansdk/modules/voice/mc_object/play.py

d3no/mocean-sdk-python

cbc215a0eb8aa26c04afb940eab6482f23150c75

[ "MIT" ]

18

2019-05-30T01:09:34.000Z

2022-01-04T07:31:47.000Z

moceansdk/modules/voice/mc_object/play.py

d3no/mocean-sdk-python

cbc215a0eb8aa26c04afb940eab6482f23150c75

[ "MIT" ]

4

2019-04-19T08:34:47.000Z

2021-07-21T02:02:07.000Z

from moceansdk.modules.voice.mc_object import AbstractMc class Play(AbstractMc): def set_files(self, files): self._params['file'] = files return self def set_barge_in(self, barge_in): self._params['barge-in'] = barge_in return self def set_clear_digit_cache(self, clear_digit_cache): self._params['clear-digit-cache'] = clear_digit_cache return self def required_key(self): return ['file'] def action(self): return 'play'

23.272727

61

0.650391

67

512

4.716418

0.373134

0.088608

0.189873

0.101266

0

0.25

512

21

62

24.380952

0.822917

0

0.2

0

0.072266

0

1

0.333333

false

0

0.066667

0.133333

0.8

0

null

0

1

0

null

0

1

0

1

0

4

cc4cbd0b5827a48fbba31d28687fdf7d888a6111

64

py

Python

grab_videos/rub.py

muzi131313/python_reptitle

aa19405710626ee00d5833bca30ad5fe598ad096

[ "MIT" ]

1

2019-03-01T12:48:03.000Z

grab_videos/rub.py

muzi131313/python_reptitle

aa19405710626ee00d5833bca30ad5fe598ad096

[ "MIT" ]

null

grab_videos/rub.py

muzi131313/python_reptitle

aa19405710626ee00d5833bca30ad5fe598ad096

[ "MIT" ]

null

# base github url: https://github.com/Kratosssss/xvideos_spyder

32

63

0.796875

9

64

5.555556

0.888889

0

0.078125

64

1

64

0.847458

0.953125

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

cc55a11875bfbf9368ac57c7c6932e063eb36651

84

py

Python

server/cellcycle/__init__.py

RENCI/CellCycleBrowser

f1e84f7c529dbfb85a0cd36d66eb1c3ebefb93dd

[ "BSD-3-Clause" ]

4

2017-12-15T20:46:50.000Z

2021-09-14T17:23:01.000Z

server/cellcycle/__init__.py

RENCI/CellCycleBrowser

f1e84f7c529dbfb85a0cd36d66eb1c3ebefb93dd

[ "BSD-3-Clause" ]

35

2017-09-21T14:14:50.000Z

2022-01-19T14:02:42.000Z

server/cellcycle/__init__.py

RENCI/CellCycleBrowser

f1e84f7c529dbfb85a0cd36d66eb1c3ebefb93dd

[ "BSD-3-Clause" ]

null

from __future__ import absolute_import from .celery_tasks import app as celery_app

21

43

0.857143

13

84

5

0.615385

0

0.130952

84

3

44

28

0.890411

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

cc866a7aa37e29106487c359d11611c03d751358

1,880

gyp

Python

src/trusted/ripple_ledger_service/ripple_ledger_service.gyp

MicrohexHQ/nacl_contracts

3efab5eecb3cf7ba43f2d61000e65918aa4ba77a

[ "BSD-3-Clause" ]

6

2015-02-06T23:41:01.000Z

2015-10-21T03:08:51.000Z

src/trusted/ripple_ledger_service/ripple_ledger_service.gyp

MicrohexHQ/nacl_contracts

3efab5eecb3cf7ba43f2d61000e65918aa4ba77a

[ "BSD-3-Clause" ]

null

src/trusted/ripple_ledger_service/ripple_ledger_service.gyp

MicrohexHQ/nacl_contracts

3efab5eecb3cf7ba43f2d61000e65918aa4ba77a

[ "BSD-3-Clause" ]

1

2019-10-02T08:41:50.000Z

# -*- python -*- { 'includes': [ '../../../build/common.gypi', ], 'target_defaults': { 'variables':{ 'target_base': 'none', }, 'target_conditions': [ ['target_base=="ripple_ledger_service"', { 'sources': [ 'ripple_ledger_service.h', 'ripple_ledger_service.c', ], 'xcode_settings': { 'WARNING_CFLAGS': [ '-Wno-missing-field-initializers' ] }, }, ]], }, 'conditions': [ ['OS=="win" and target_arch=="ia32"', { 'targets': [ { 'target_name': 'ripple_ledger_service64', 'type': 'static_library', 'variables': { 'target_base': 'ripple_ledger_service', 'win_target': 'x64', }, 'dependencies': [ '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform64', '<(DEPTH)/native_client/src/shared/srpc/srpc.gyp:nonnacl_srpc64', '<(DEPTH)/native_client/src/trusted/threading/threading.gyp:thread_interface64', '<(DEPTH)/native_client/src/trusted/desc/desc.gyp:nrd_xfer64', '<(DEPTH)/native_client/src/trusted/nacl_base/nacl_base.gyp:nacl_base64', ], }, ], }], ], 'targets': [ { 'target_name': 'ripple_ledger_service', 'type': 'static_library', 'variables': { 'target_base': 'ripple_ledger_service', }, 'dependencies': [ '<(DEPTH)/native_client/src/shared/platform/platform.gyp:platform', '<(DEPTH)/native_client/src/shared/srpc/srpc.gyp:nonnacl_srpc', '<(DEPTH)/native_client/src/trusted/threading/threading.gyp:thread_interface', '<(DEPTH)/native_client/src/trusted/desc/desc.gyp:nrd_xfer', '<(DEPTH)/native_client/src/trusted/nacl_base/nacl_base.gyp:nacl_base', ], }, ], }

30.322581

92

0.557979

179

1,880

5.581006

0.335196

0.11011

0.17017

0.2002

0.68969

0.602603

0.1001

0

0.011586

0.265426

1,880

61

93

30.819672

0.711803

0.007447

0

0.3

0

0.629828

0.473712

0

1

0

true

0

null

0

1

0

1

null

0

1

0

4

cc95c4ce375d5cb68aaa4a3554c3b955788df1e2

1,502

py

Python

src/providerhub/azext_providerhub/generated/_client_factory.py

haroonf/azure-cli-extensions

61c044d34c224372f186934fa7c9313f1cd3a525

[ "MIT" ]

207

2017-11-29T06:59:41.000Z

2022-03-31T10:00:53.000Z

src/providerhub/azext_providerhub/generated/_client_factory.py

haroonf/azure-cli-extensions

61c044d34c224372f186934fa7c9313f1cd3a525

[ "MIT" ]

4,061

2017-10-27T23:19:56.000Z

2022-03-31T23:18:30.000Z

src/providerhub/azext_providerhub/generated/_client_factory.py

haroonf/azure-cli-extensions

61c044d34c224372f186934fa7c9313f1cd3a525

[ "MIT" ]

802

2017-10-11T17:36:26.000Z

2022-03-31T22:24:32.000Z

# -------------------------------------------------------------------------- # Copyright (c) Microsoft Corporation. All rights reserved. # Licensed under the MIT License. See License.txt in the project root for # license information. # # Code generated by Microsoft (R) AutoRest Code Generator. # Changes may cause incorrect behavior and will be lost if the code is # regenerated. # -------------------------------------------------------------------------- from azure.cli.core.commands.client_factory import get_mgmt_service_client from azext_providerhub.vendored_sdks.providerhub import ProviderHub def cf_providerhub_cl(cli_ctx, *_): return get_mgmt_service_client(cli_ctx, ProviderHub) def cf_providerhub(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).providerhub_operations def cf_custom_rollout(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).custom_rollouts def cf_default_rollout(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).default_rollouts def cf_notification_registration(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).notification_registrations def cf_operation(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).operations def cf_provider_registration(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).provider_registrations def cf_resource_type_registration(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).resource_type_registrations def cf_sku(cli_ctx, *_): return cf_providerhub_cl(cli_ctx).skus

30.04

76

0.704394

187

1,502

5.256684

0.379679

0.109868

0.137335

0.164802

0.340793

0.31943

0.218718

0

0.131824

1,502

49

77

30.653061

0.753834

0.292277

0

1

0.428571

false

0

0.095238

0.428571

0.952381

0

null

0

1

0

null

0

1

0

1

0

4

ccb2deb913103dd382e70d40b6f72263e1fabe42

196

py

Python

src/npi/training/__init__.py

NancyFulda/towards-neural-programming-interfaces

21b467af56848c4fc8642fb0412f9f8d1b7718a2

[ "Apache-2.0" ]

null

src/npi/training/__init__.py

NancyFulda/towards-neural-programming-interfaces

21b467af56848c4fc8642fb0412f9f8d1b7718a2

[ "Apache-2.0" ]

1

2022-02-01T02:51:51.000Z

src/npi/training/__init__.py

NancyFulda/towards-neural-programming-interfaces

21b467af56848c4fc8642fb0412f9f8d1b7718a2

[ "Apache-2.0" ]

2

2022-02-07T16:39:02.000Z

2022-03-21T16:08:22.000Z

# This package should store scripts to run training and tests on the model from .npi_loss import NPILoss from .npi_trainer import NPITrainer from .style_classifier_trainer import NPIStyleTrainer

32.666667

74

0.841837

29

196

5.551724

0.793103

0.086957

0

0.137755

196

5

75

39.2

0.952663

0.367347

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ccb7436595d29cd327d60ccd8c4a93ce1ce15a61

23

py

Python

tests/ui_tests/app/helpers/__init__.py

arenadata/adcm

a499caa30adc2a53e7b3f46c96a865f9e4079e4e

[ "Apache-2.0" ]

16

2019-11-28T18:05:21.000Z

2021-12-08T18:09:18.000Z

tests/ui_tests/app/helpers/__init__.py

arenadata/adcm

a499caa30adc2a53e7b3f46c96a865f9e4079e4e

[ "Apache-2.0" ]

1,127

2019-11-29T08:57:25.000Z

2022-03-31T20:21:32.000Z

tests/ui_tests/app/helpers/__init__.py

arenadata/adcm

a499caa30adc2a53e7b3f46c96a865f9e4079e4e

[ "Apache-2.0" ]

10

2019-11-28T18:05:06.000Z

2022-01-13T06:16:40.000Z

"""UI tests helpers"""

11.5

22

0.608696

3

23

4.666667

1

0

0.130435

23

1

23

0.7

0.695652

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

null

0

1

0

4

cccbe2dbf5428eddfe57572f8bb06e2988fb78f6

56

py

Python

modules/hello.py

as3nds/pdm

f0f1275c6a4d3d24a89bd3955c10000add41ebc3

[ "MIT" ]

null

modules/hello.py

as3nds/pdm

f0f1275c6a4d3d24a89bd3955c10000add41ebc3

[ "MIT" ]

null

modules/hello.py

as3nds/pdm

f0f1275c6a4d3d24a89bd3955c10000add41ebc3

[ "MIT" ]

null

# -*- encoding: utf-8 -*- def run(): print "hello"

11.2

25

0.5

7

56

4

1

0

0.02381

0.25

56

4

26

14

0.642857

0.410714

0

0.16129

0

null

0

null

0.5

1

0

null

0

1

0

null

0

1

0

1

0

4

cccda63efa62bd5695e606b8935d762feb894cd2

102

py

Python

introduction_to_classic_ciphers/lesson1/task1/intro_and_warmup.py

behzod/pycharm-courses

0ba74ff0ff87e7747173c60cd139c25b8d7f3b0e

[ "Apache-2.0" ]

213

2015-01-03T19:25:02.000Z

2020-02-06T03:08:43.000Z

introduction_to_classic_ciphers/lesson1/task1/intro_and_warmup.py

behzod/pycharm-courses

0ba74ff0ff87e7747173c60cd139c25b8d7f3b0e

[ "Apache-2.0" ]

24

2015-01-01T17:03:09.000Z

2019-12-22T10:28:22.000Z

introduction_to_classic_ciphers/lesson1/task1/intro_and_warmup.py

behzod/pycharm-courses

0ba74ff0ff87e7747173c60cd139c25b8d7f3b0e

[ "Apache-2.0" ]

139

2015-01-03T19:24:22.000Z

2020-01-24T18:05:51.000Z

ENCRYPTED_MESSAGE = 'HIDE ELVES LAST LEFT OPEN' PLAINTEXT_MESSAGE = 'HELLO' print PLAINTEXT_MESSAGE

17

47

0.803922

13

102

6.076923

0.769231

0.405063

0

0.137255

102

5

48

20.4

0.897727

0

0.294118

0

null

0

null

0.333333

1

0

null

1

0

1

0

null

0

1

0

4

aea31525acc711d8f48d6e7f6c573e8a3986354f

150

py

Python

test/test_plot.py

jsta/camels

c890d89fb45cd43abb03eb8564d31c1c328a72cc

[ "MIT" ]

6

2020-12-18T17:19:35.000Z

2021-12-07T22:25:55.000Z

test/test_plot.py

jsta/camels

c890d89fb45cd43abb03eb8564d31c1c328a72cc

[ "MIT" ]

1

2021-12-07T22:42:40.000Z

test/test_plot.py

jsta/camels

c890d89fb45cd43abb03eb8564d31c1c328a72cc

[ "MIT" ]

4

2020-05-21T10:43:13.000Z

2021-12-07T22:33:56.000Z

import pytest import camels import matplotlib.pyplot as plt def test_plot(): plt.ioff() gauge_id = 13331500 camels.plot_basin(gauge_id)

15

31

0.733333

22

150

4.818182

0.681818

0.132075

0

0.066116

0.193333

150

9

32

16.666667

0.809917

0

1

0.142857

false

0

0.428571

0

0.571429

0

1

0

null

0

1

0

null

0

1

0

1

0

4

aea32a5217f1994f2a7562be4220df08371a6042

268

py

Python

system_user_screen.py

tur103/CLOUDED-OPERATION-SYSTEM

d162ed425a215d180155cb1b4c3b63c22740513a

[ "MIT" ]

1

2020-03-17T18:35:02.000Z

system_user_screen.py

tur103/CLOUDED-OPERATION-SYSTEM

d162ed425a215d180155cb1b4c3b63c22740513a

[ "MIT" ]

null

system_user_screen.py

tur103/CLOUDED-OPERATION-SYSTEM

d162ed425a215d180155cb1b4c3b63c22740513a

[ "MIT" ]

null

import threading import subprocess from constants import * class SystemUserScreen(threading.Thread): def __init__(self): threading.Thread.__init__(self) self.start() def run(self): subprocess.call(" ".join([PYTHON, SCREEN_PROGRAM]))

20.615385

59

0.690299

29

268

6.068966

0.62069

0.170455

0

0.201493

268

12

60

22.333333

0.82243

0

0.003731

0

1

0.222222

false

0

0.333333

0

0.666667

0

1

0

null

0

null

0

1

0

1

0

1

0

4

aeb946f60e7eaf85d0402513d25746fe8ea34de2

263

py

Python

qtgui/widgets/__init__.py

Petr-By/qtpyvis

0b9a151ee6b9a56b486c2bece9c1f03414629efc

[ "MIT" ]

3

2017-10-04T14:51:26.000Z

2017-10-22T09:35:50.000Z

qtgui/widgets/__init__.py

CogSciUOS/DeepLearningToolbox

bf07578b9486d8c48e25df357bc4b9963b513b46

[ "MIT" ]

13

2017-11-26T10:05:00.000Z

2018-03-11T14:08:40.000Z

qtgui/widgets/__init__.py

CogSciUOS/DeepLearningToolbox

bf07578b9486d8c48e25df357bc4b9963b513b46

[ "MIT" ]

2

2017-09-24T21:39:42.000Z

2017-10-04T15:29:54.000Z

#from .data import QDataInfoBox #from .activationview import QActivationView #from .image import QImageView #from .matrixview import QMatrixView #from .network import QNetworkBox #from .network import QNetworkComboBox #from .connectionview import QConnectionView

32.875

44

0.840304

28

263

7.892857

0.535714

0.099548

0.153846

0

0.106464

263

7

45

37.571429

0.940426

0.946768

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

aebaba1cc0cf2e4be9957d5f09cddde2a52be5fb

466

py

Python

reusable/functions.py

AwesomeGitHubRepos/reusable

0d12cd016f8b3598f3daab905fa47b019afe81f8

[ "MIT" ]

1

2022-02-05T17:38:28.000Z

reusable/functions.py

AwesomeGitHubRepos/reusable

0d12cd016f8b3598f3daab905fa47b019afe81f8

[ "MIT" ]

2

2020-09-08T18:12:43.000Z

2021-02-18T03:31:43.000Z

reusable/functions.py

AwesomeGitHubRepos/reusable

0d12cd016f8b3598f3daab905fa47b019afe81f8

[ "MIT" ]

1

2020-11-06T14:19:08.000Z

#!/usr/bin/env python # -*- coding: UTF-8 -*- # # Part of reusable package # # Copyright (c) 2020 - Ohidur Rahman Bappy - MIT License """String Related Functions. Contains a handful of string related functions. """ from .datetime_functions import generate_all_datetime_regex from .iterable_functions import groupby_count from .network_functions import * from .string_functions import * from .utility_functions import * from .fake_useragent import random_useragent

25.888889

59

0.783262

61

466

5.803279

0.639344

0.211864

0.161017

0

0.012376

0.133047

466

17

60

27.411765

0.863861

0.422747

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

4

aeced69aff00bb2a28682e7a708887218bb2ebe9

832

py

Python

currency_converter/currencies/apps.py

Silver3310/currency-converter

95e6edc4ecd32aa9296960bc63a9f91518b13782

[ "MIT" ]

null

currency_converter/currencies/apps.py

Silver3310/currency-converter

95e6edc4ecd32aa9296960bc63a9f91518b13782

[ "MIT" ]

null

currency_converter/currencies/apps.py

Silver3310/currency-converter

95e6edc4ecd32aa9296960bc63a9f91518b13782

[ "MIT" ]

null

from django.apps import AppConfig from django.utils.translation import gettext_lazy as _ from django.db.models.signals import post_migrate def load_data_callback(sender, **kwargs): """ Load data at the project startup """ from currency_converter.currencies.models import Currency from currency_converter.currencies.tasks import update_exchange_rates # load exchange rates in case they are not present if not Currency.objects.exists(): update_exchange_rates.delay() class CurrenciesConfig(AppConfig): name = "currency_converter.currencies" verbose_name = _("Currencies") def ready(self): try: import currency_converter.currencies.signals # noqa F401 except ImportError: pass post_migrate.connect(load_data_callback, sender=self)

28.689655

73

0.725962

99

832

5.919192

0.555556

0.116041

0.1843

0.075085

0

0.004545

0.206731

832

28

74

29.714286

0.883333

0.110577

0

0.053942

0.040111

0

1

0.117647

false

0.058824

0.411765

0

0.705882

0

null

0

1

0

null

0

1

0

1

0

4

aef26b7298e9e65a75ff34daddf7601d1c942b0b

222

py

Python

sjtwo-c/site_scons/site_tools/codegen/site_packages/can/interfaces/ixxat/__init__.py

seanlinc/Playmate

077877d172dd6b7beab910c52ec95ee300bc6480

[ "Apache-2.0" ]

2

2020-04-04T21:09:56.000Z

2020-04-08T17:00:58.000Z

sjtwo-c/site_scons/site_tools/codegen/site_packages/can/interfaces/ixxat/__init__.py

seanlinc/Playmate

077877d172dd6b7beab910c52ec95ee300bc6480

[ "Apache-2.0" ]

13

2020-04-11T21:50:57.000Z

2020-04-19T03:19:48.000Z

sjtwo-c/site_scons/site_tools/codegen/site_packages/can/interfaces/ixxat/__init__.py

seanlinc/Playmate

077877d172dd6b7beab910c52ec95ee300bc6480

[ "Apache-2.0" ]

null

# coding: utf-8 """ Ctypes wrapper module for IXXAT Virtual CAN Interface V3 on win32 systems Copyright (C) 2016 Giuseppe Corbelli <giuseppe.corbelli@weightpack.com> """ from can.interfaces.ixxat.canlib import IXXATBus

22.2

73

0.779279

31

222

5.580645

0.870968

0.184971

0

0.041667

0.135135

222

9

74

24.666667

0.859375

0.725225

0

1

0

true

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

4

aefb2e8693151146f5827909d9c580c21254cc36

137

py

Python

test/test_doctest.py

pykit3/k3jobq

a3feca99074d3e476a1ef8c429770497ae305b56

[ "MIT" ]

null

test/test_doctest.py

pykit3/k3jobq

a3feca99074d3e476a1ef8c429770497ae305b56

[ "MIT" ]

null

test/test_doctest.py

pykit3/k3jobq

a3feca99074d3e476a1ef8c429770497ae305b56

[ "MIT" ]

null

import doctest import k3jobq def load_tests(loader, tests, ignore): tests.addTests(doctest.DocTestSuite(k3jobq)) return tests

15.222222

48

0.759124

17

137

6.058824

0.647059

0

0.017391

0.160584

137

8

49

17.125

0.878261

0

1

0.2

false

0

0.4

0

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4e17d2ab8960c92874430445af8a78718441901f

623

py

Python

payroll/calculations.py

Atwinenickson/lendsuphumanresourcemanagement

b46df164d59a4e94300376d679e07bd9a60d6343

[ "MIT", "Unlicense" ]

36

2019-11-26T11:46:32.000Z

2022-02-17T13:18:18.000Z

payroll/calculations.py

Atwinenickson/lendsuphumanresourcemanagement

b46df164d59a4e94300376d679e07bd9a60d6343

[ "MIT", "Unlicense" ]

13

2020-02-14T09:30:16.000Z

2022-03-12T00:58:09.000Z

payroll/calculations.py

Atwinenickson/lendsuphumanresourcemanagement

b46df164d59a4e94300376d679e07bd9a60d6343

[ "MIT", "Unlicense" ]

16

2019-06-14T12:11:29.000Z

2022-02-14T15:16:07.000Z

from django.db.models import QuerySet, Sum from employees.models import Employee from overtime.selectors import get_approved_overtime_applications def calculate_overtime(employee: Employee) -> int: # Get all approved overtime applications for the employee approved_overtime_applications: QuerySet = get_approved_overtime_applications(employee) # If employee has overtime applications continue if not return zero if approved_overtime_applications: # Sum the overtime pay for each overtime application # Return the overtime pay return total_overtime_pay else: return 0

34.611111

91

0.775281

76

623

6.184211

0.421053

0.255319

0.297872

0.131915

0

0.001984

0.191011

623

17

92

36.647059

0.930556

0.314607

0

1

0.111111

false

0

0.333333

0

0.666667

0

null

1

0

null

0

1

0

1

0

4

4e231951fc1f7121e823078fd50fdaba6b8744e5

4,737

py

Python

pyva/tests/TestSizeRules.py

holoyan/python-data-validation

e928c4131072c53cb8ace1fbaa83216f06ab6bfe

[ "MIT" ]

3

2021-03-16T05:47:46.000Z

2021-03-23T17:43:55.000Z

pyva/tests/TestSizeRules.py

holoyan/python-data-validation

e928c4131072c53cb8ace1fbaa83216f06ab6bfe

[ "MIT" ]

null

pyva/tests/TestSizeRules.py

holoyan/python-data-validation

e928c4131072c53cb8ace1fbaa83216f06ab6bfe

[ "MIT" ]

null

import unittest from pyva import Validator class TestSizeRules(unittest.TestCase): def test_size(self): validation = Validator({ 'age': 10, 'bill': -6, 'count': 0 }, { 'age': 'size:10', 'bill': 'size:-6', 'count': 'size:0' }) self.assertTrue(validation.passes()) def test_size_must_fail(self): validation = Validator({ 'age': 5, 'bill': -7, 'count': 0 }, { 'age': 'size:10', 'bill': 'size:-6', 'count': 'size:0' }) self.assertTrue(validation.fails()) def test_between(self): validation = Validator({ 'age': 11, 'bill': -3200 }, { 'age': 'between:10,100', 'bill': 'between:-3200,0' }) self.assertTrue(validation.passes()) def test_between_must_fail(self): validation = Validator({ 'age': 9, 'bill': -3300 }, { 'age': 'between:10,100', 'bill': 'between:-3200,0' }) self.assertTrue(validation.fails()) self.assertTrue('age' in validation.failed_rules) self.assertTrue('bill' in validation.failed_rules) def test_min(self): validation = Validator({ 'age': 9, 'height': 185 }, { 'age': 'min:1', 'height': 'min:1' }) self.assertTrue(validation.passes()) def test_min_fails(self): validation = Validator({ 'age': 2, 'height': -185 }, { 'age': 'min:1', 'height': 'min:1' }) self.assertTrue(validation.fails()) self.assertTrue('height' in validation.failed_rules) def test_max(self): validation = Validator({ 'age': 9, 'height': 185 }, { 'age': 'max:100', 'height': 'max:250' }) self.assertTrue(validation.passes()) def test_max_fails(self): validation = Validator({ 'age': 9, 'height': 251 }, { 'age': 'max:100', 'height': 'max:250' }) self.assertTrue(validation.fails()) self.assertTrue('height' in validation.failed_rules) def test_gt(self): validation = Validator({ 'age': 22, 'height': 185 }, { 'age': 'required', 'height': 'gt:age' }) self.assertTrue(validation.passes()) def test_gt_fail(self): validation = Validator({ 'age': 17, 'height': 10 }, { 'age': 'required', 'height': 'gt:age' }) self.assertTrue(validation.fails()) self.assertTrue('height' in validation.failed_rules) def test_lt(self): validation = Validator({ 'age': 29, 'height': 20 }, { 'age': 'required', 'height': 'lt:age' }) self.assertTrue(validation.passes()) def test_lt_fail(self): validation = Validator({ 'age': 29, 'height': 185 }, { 'age': 'required', 'height': 'lt:age' }) self.assertTrue(validation.fails()) self.assertTrue('height' in validation.failed_rules) def test_gte(self): validation = Validator({ 'age': 10, 'height': 185, 'width': 185 }, { 'age': 'required', 'height': 'gte:age', 'width': 'gte:height', }) self.assertTrue(validation.passes()) def test_gte_fails(self): validation = Validator({ 'age': 9, 'height': 185, 'width': 184, }, { 'age': 'required', 'height': 'gte:age', 'width': 'gte:height' }) self.assertTrue(validation.fails()) self.assertTrue('height' not in validation.failed_rules) def test_lte(self): validation = Validator({ 'age': 90, 'height': 90 }, { 'age': 'required', 'height': 'lte:height' }) self.assertTrue(validation.passes()) def test_lte_fails(self): validation = Validator({ 'age': 184, 'height': 185 }, { 'age': 'required', 'height': 'lte:age' }) self.assertTrue(validation.fails()) self.assertTrue('height' in validation.failed_rules) if __name__ == '__main__': unittest.main()

23.567164

64

0.45704

418

4,737

5.078947

0.141148

0.158267

0.17334

0.195949

0.814414

0.722091

0.608573

0.508714

0.417805

0.386717

0

0.04219

0.394554

4,737

200

65

23.685

0.698047

0

0.721212

0

0.136795

0

0.145455

1

0.09697

false

0.048485

0.012121

0

0.115152

0

null

0

1

0

1

0

null

0

4

4e3cff55551bd3de37f0efcdddad788c6fa412cf

571

py

Python

Mundo-1/desafio-014.py

LeonardoARGR/Desafios-Python-Curso-em-Video

3fb1b0615fce88f968b5ba6e4bac43fcb0e72d98

[ "MIT" ]

2

2020-04-18T21:56:35.000Z

2020-04-23T00:00:08.000Z

Mundo-1/desafio-014.py

LeonardoARGR/Desafios-Python-Curso-em-Video

3fb1b0615fce88f968b5ba6e4bac43fcb0e72d98

[ "MIT" ]

null

Mundo-1/desafio-014.py

LeonardoARGR/Desafios-Python-Curso-em-Video

3fb1b0615fce88f968b5ba6e4bac43fcb0e72d98

[ "MIT" ]

null

cores = {'limpo': '\033[m', 'vermelho': '\033[1;31m', 'verde': '\033[1;32m', 'azul': '\033[1;34m'} C = float(input('Indique a temperatura em °C: ')) F = 9 * C / 5 + 32 if C > 32: print(f'A temperatura {cores["vermelho"]}{C}°C{cores["limpo"]} é igual à {cores["vermelho"]}{F}°F{cores["limpo"]}') if C < 13: print(f'A temperatura {cores["azul"]}{C}°C{cores["limpo"]} é igual à {cores["azul"]}{F}°F{cores["limpo"]}') else: print(f'A temperatura {cores["verde"]}{C}°C{cores["limpo"]} é igual à {cores["verde"]}{F}°F{cores["limpo"]}')

38.066667

119

0.553415

100

571

3.23

0.3

0.216718

0.065015

0.167183

0.566563

0.232198

0

0.061311

0.171629

571

14

120

40.785714

0.606765

0

0.25

0.681898

0.397188

0

1

0

false

0

0.25

0

null

1

0

1

0

1

0

null

0

4

9defd683cf689d273ae00ba8e38657b9816509b8

104

py

Python

BOJ_Solved/BOJ-8710.py

CodingLeeSeungHoon/Python_Algorithm_TeamNote

1e92986999b45aa9951e12e67b23062e410e9b36

[ "MIT" ]

7

2021-11-19T14:50:59.000Z

2022-02-25T20:00:20.000Z

BOJ_Solved/BOJ-8710.py

CodingLeeSeungHoon/Python_Algorithm_TeamNote

1e92986999b45aa9951e12e67b23062e410e9b36

[ "MIT" ]

null

BOJ_Solved/BOJ-8710.py

CodingLeeSeungHoon/Python_Algorithm_TeamNote

1e92986999b45aa9951e12e67b23062e410e9b36

[ "MIT" ]

null

""" 백준 8710번 : Koszykarz """ import math k, w, m = map(int, input().split()) print(math.ceil((w-k) / m))

17.333333

35

0.586538

18

104

3.388889

0.777778

0

0.045455

0.153846

104

6

36

17.333333

0.647727

0.192308

0

1

0

true

0

0.333333

0

0.333333

1

0

null

0

1

0

null

0

1

0

1

0

4

d19fb160da01df3f79458d6577b0640a85f3fd37

187

py

Python

pymatgen/symmetry/__init__.py

exenGT/pymatgen

a8ffb820ab8fc3f60251099e38c8888f45eae618

[ "MIT" ]

1

2021-11-02T21:10:11.000Z

pymatgen/symmetry/__init__.py

exenGT/pymatgen

a8ffb820ab8fc3f60251099e38c8888f45eae618

[ "MIT" ]

5

2018-08-07T23:00:23.000Z

2021-01-05T22:46:23.000Z

pymatgen/symmetry/__init__.py

exenGT/pymatgen

a8ffb820ab8fc3f60251099e38c8888f45eae618

[ "MIT" ]

6

2019-04-26T18:50:41.000Z

2020-03-29T17:58:34.000Z

# Copyright (c) Pymatgen Development Team. # Distributed under the terms of the MIT License. """ The symmetry package implements symmetry tools, e.g., spacegroup determination, etc. """

23.375

79

0.754011

24

187

5.875

0.875

0

0.149733

187

7

80

26.714286

0.886792

0.930481

0

null

0

null

0

null

0

null

1

null

true

0

null

1

0

null

0

1

0

1

0

null

0

1

0

4

d1c6ec8475644bcdcbc7669936d97e42cd364cd7

198

py

Python

tests/test_import.py

umccr-illumina/libiap

14ab8f9f85c8505e37e578daae65d5d5eb971a45

[ "MIT" ]

null

tests/test_import.py

umccr-illumina/libiap

14ab8f9f85c8505e37e578daae65d5d5eb971a45

[ "MIT" ]

null

tests/test_import.py

umccr-illumina/libiap

14ab8f9f85c8505e37e578daae65d5d5eb971a45

[ "MIT" ]

null

import unittest import libica class TestImport(unittest.TestCase): def test_import(self): print("libica.VERSION: ", libica.VERSION) self.assertEqual(libica.VERSION, "0.5.0")

18

49

0.691919

24

198

5.666667

0.583333

0.286765

0

0.018634

0.186869

198

10

50

19.8

0.826087

0

0.106061

0

0.166667

1

0.166667

false

0

0.666667

0

1

0.166667

1

0

null

1

0

null

0

1

0

1

0

4

d1d1cc2236a5c9b4b0719483bcf421be7002a98c

95

py

Python

peter_lists/todo/apps.py

pvize1/peter_lists

77e9f30cfc45f500e059b7b163db541335180332

[ "MIT" ]

null

peter_lists/todo/apps.py

pvize1/peter_lists

77e9f30cfc45f500e059b7b163db541335180332

[ "MIT" ]

8

2021-05-12T05:53:42.000Z

2022-03-31T04:08:18.000Z

peter_lists/todo/apps.py

pvize1/peter_lists

77e9f30cfc45f500e059b7b163db541335180332

[ "MIT" ]

null

from django.apps import AppConfig class TodoConfig(AppConfig): name = 'peter_lists.todo'

15.833333

33

0.757895

12

95

5.916667

0.916667

0

0.157895

95

5

34

19

0.8875

0

0.168421

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

0605747da27699aac0403a728ad179d6091b5bc9

284

py

Python

Django/view.py

JOHNKYON/Data_save

8d6820e2d6923cf5ca038abd39da8f42793d9ad7

[ "MIT" ]

null

Django/view.py

JOHNKYON/Data_save

8d6820e2d6923cf5ca038abd39da8f42793d9ad7

[ "MIT" ]

null

Django/view.py

JOHNKYON/Data_save

8d6820e2d6923cf5ca038abd39da8f42793d9ad7

[ "MIT" ]

null

# -*- coding: utf-8 -*- from __future__ import absolute_import from __future__ import division from __future__ import generators from __future__ import nested_scopes from __future__ import print_function from __future__ import unicode_literals from __future__ import with_statement

25.818182

39

0.84507

36

284

5.75

0.472222

0.338164

0.541063

0

0.004016

0.123239

284

10

40

28.4

0.827309

0.073944

0

1

0

true

0

1

0

1

0.142857

0

null

1

0

null

0

1

0

1

0

4

060d69762b40f53bff960a427d132f51e5259089

2,006

py

Python

python/core/problem_definition.py

stellaraccident/iree-llvm-sandbox

0bc3aa93f47ace46e8a09db6727f5bd3947ae66b

[ "Apache-2.0" ]

null

python/core/problem_definition.py

stellaraccident/iree-llvm-sandbox

0bc3aa93f47ace46e8a09db6727f5bd3947ae66b

[ "Apache-2.0" ]

null

python/core/problem_definition.py

stellaraccident/iree-llvm-sandbox

0bc3aa93f47ace46e8a09db6727f5bd3947ae66b

[ "Apache-2.0" ]

null

from typing import Any, List, Optional, Sequence, Type, Union # Qualified import of only np.dtype for type checking. np = __import__('numpy', fromlist=['dtype']) class ProblemDefinition: """ Generic problem definition interface.""" def shapes_builder(self, *args: int) -> List[List[int]]: """Shape builder function. Given a list of integer dimensions, return the list of lists of shapes of the FuncOp operands. The FuncOp is responsible for distinguishing between input operands and results. """ pass def gflop_count_builder(self, *args: int) -> float: """GFlop builder function. Given a list of integer dimensions, return the number of GFlops computed. """ pass def gbyte_count_builder(self, *args: int) -> float: """GByte builder function. Given a list of integer dimensions, return the number of GBytes read or written. """ pass def tensors_np_builder(self, *args: Union[int, np.dtype]) -> List[np.dtype]: """NP tensors building function. Given a list of integer dimensions followed by per-operand NP elemental types, return constructed NP values of shapes given by `shaped_builder` and specified elemental types. """ pass def check_np(self, *args: np.dtype) -> None: """NP checking function. Given a list of NP values, check the precomputed results matches those of the expected reference implementation. """ pass def types_mlir_builder(self, *args: Union[int, Type]) -> List[Type]: """ MLIR types builder. Given a list of NP values, check the precomputed results matches those of the expected reference implementation. """ pass def build_problem_under_context_manager(self, name: str, *args: Type): # TODO: -> FuncOp """MLIR problem builder. Given a flat list of MLIR types, build and return the MLIR FuncOp that implements the desired computation on those types. """ pass

29.940299

80

0.677468

264

2,006

5.075758

0.356061

0.035821

0.044776

0.053731

0.391045

0.350746

0.308955

0.281343

0

0.237288

2,006

66

81

30.393939

0.875817

0.565304

0

0.411765

0

0.014577

0

0.015152

0

1

0.411765

false

0.411765

0.117647

0

0.588235

0

null

0

null

0

1

0

1

0

1

0

1

0

4

ae14f2d7f5055e970e14faf07febcfd5a7b01121

737

py

Python

models.py

knarfamlap/css-first-repo

f72d53ce3b608b8ffb56800b3bef9402c6ced448

[ "MIT" ]

null

models.py

knarfamlap/css-first-repo

f72d53ce3b608b8ffb56800b3bef9402c6ced448

[ "MIT" ]

null

models.py

knarfamlap/css-first-repo

f72d53ce3b608b8ffb56800b3bef9402c6ced448

[ "MIT" ]

null

from google.appengine.ext import ndb class User(ndb.Model): username = ndb.StringProperty(required=True) first_name = ndb.StringProperty(required=True) last_name = ndb.StringProperty(required=True) class Comment(ndb.Model): comment_owner = ndb.KeyProperty(User) comment_body = ndb.StringProperty(required=True) class Article(ndb.Model): title = ndb.StringProperty(required=True) body = ndb.StringProperty(required=True) category = ndb.StringProperty(required=True) # post_owner = ndb.KeyProperty(User) # comments = ndb.KeyProperty(Comment, repeated=True) class Category(ndb.Model): name_of_category = ndb.StringProperty(required=True) post = ndb.KeyProperty(Article, repeated=True)

29.48

56

0.746269

89

737

6.101124

0.303371

0.25046

0.368324

0.427256

0.412523

0.151013

0

0.145183

737

24

57

30.708333

0.861905

0.115332

0

1

0

false

0

0.066667

0

1

0

null

1

0

null

0

1

0

4

ae1e65794e6ec9b4f364faecd9f4770bfc76f1d6

1,362

py

Python

samEshop/main/migrations/0006_auto_20210923_1422.py

Tedd-console/Django-Ecomm

fd74af3625888b76bb7f8da6b0ae5331c71b15f9

[ "MIT" ]

null

samEshop/main/migrations/0006_auto_20210923_1422.py

Tedd-console/Django-Ecomm

fd74af3625888b76bb7f8da6b0ae5331c71b15f9

[ "MIT" ]

null

samEshop/main/migrations/0006_auto_20210923_1422.py

Tedd-console/Django-Ecomm

fd74af3625888b76bb7f8da6b0ae5331c71b15f9

[ "MIT" ]

null

# Generated by Django 3.2.7 on 2021-09-23 11:22 from django.db import migrations, models class Migration(migrations.Migration): dependencies = [ ('main', '0005_rename_title_banner_image'), ] operations = [ migrations.AlterModelOptions( name='banner', options={'verbose_name_plural': '1. Banners'}, ), migrations.AlterModelOptions( name='brand', options={'verbose_name_plural': '3. Brands'}, ), migrations.AlterModelOptions( name='category', options={'verbose_name_plural': '2. Categories'}, ), migrations.AlterModelOptions( name='color', options={'verbose_name_plural': '4. Colors'}, ), migrations.AlterModelOptions( name='product', options={'verbose_name_plural': '6. Products'}, ), migrations.AlterModelOptions( name='productattribute', options={'verbose_name_plural': '7. Product Attributes'}, ), migrations.AlterModelOptions( name='size', options={'verbose_name_plural': '5. Sizes'}, ), migrations.AddField( model_name='product', name='is_featured', field=models.BooleanField(default=False), ), ]

28.978723

69

0.556535

114

1,362

6.473684

0.5

0.256098

0.294038

0.227642

0

0.028017

0.318649

1,362

46

70

29.608696

0.767241

0.03304

0

0.375

1

0

0.241065

0.022814

0

1

0

false

0

0.025

0

0.1

0

null

1

0

1

0

null

0

4

ae1fba66b545a438cc99fb5b2db417c9df863219

87

py

Python

programs/Dictionary.py

Amrik85/Python

1fe7147e3c900200d7979b9b72b025be9e8546d9

[ "Apache-2.0" ]

null

programs/Dictionary.py

Amrik85/Python

1fe7147e3c900200d7979b9b72b025be9e8546d9

[ "Apache-2.0" ]

null

programs/Dictionary.py

Amrik85/Python

1fe7147e3c900200d7979b9b72b025be9e8546d9

[ "Apache-2.0" ]

2

2020-10-27T06:19:16.000Z

2020-10-27T13:42:08.000Z

Dict = {1:'Amrik', 2: 'Abhi'} print (Dict) ##call print(Dict[1]) print(Dict.get(2))

9.666667

29

0.586207

15

87

3.4

0.533333

0.529412

0

0.054054

0.149425

87

9

30

9.666667

0.635135

0.045977

0

0.109756

0

1

0

false

0

0.75

1

0

null

1

0

1

0

null

0

1

0

4

ae72eb0d916766ba710ac89b39a82f5e94b41c19

89

py

Python

lib/galaxy/webapps/tool_shed/__init__.py

bopopescu/phyG

023f505b705ab953f502cbc55e90612047867583

[ "CC-BY-3.0" ]

2

2016-02-23T00:09:14.000Z

2019-02-11T07:48:44.000Z

lib/galaxy/webapps/tool_shed/__init__.py

bopopescu/phyG

023f505b705ab953f502cbc55e90612047867583

[ "CC-BY-3.0" ]

null

lib/galaxy/webapps/tool_shed/__init__.py

bopopescu/phyG

023f505b705ab953f502cbc55e90612047867583

[ "CC-BY-3.0" ]

6

2015-05-27T13:09:50.000Z

2019-02-11T07:48:46.000Z

"""The Galaxy Tool Shed application.""" from galaxy.web.framework import expose, url_for

29.666667

48

0.775281

13

89

5.230769

0.923077

0

0.11236

89

3

48

29.666667

0.860759

0.370787

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ae7537cd1251eb0871a95bb77ba85ddd2e4e98f8

258

py

Python

tests/test_viz.py

chrinide/pyRiemann

0f5eb0224673976a53e5d2201a13a187c5bc1e8d

[ "BSD-3-Clause" ]

2

2017-03-03T02:09:10.000Z

2021-04-21T06:32:35.000Z

tests/test_viz.py

chrinide/pyRiemann

0f5eb0224673976a53e5d2201a13a187c5bc1e8d

[ "BSD-3-Clause" ]

null

tests/test_viz.py

chrinide/pyRiemann

0f5eb0224673976a53e5d2201a13a187c5bc1e8d

[ "BSD-3-Clause" ]

null

import numpy as np from pyriemann.utils.viz import plot_confusion_matrix def test_confusion_matrix(): """Test confusion_matrix""" target = np.array([0, 1] * 10) preds = np.array([0, 1] * 10) plot_confusion_matrix(target, preds, ['a', 'b'])

25.8

53

0.674419

38

258

4.394737

0.552632

0.359281

0.227545

0.107784

0.131737

0

0.037736

0.178295

258

9

54

28.666667

0.75

0.081395

0

0.008658

0

1

0.166667

false

0

0.333333

0

0.5

0

null

1

0

1

0

null

0

1

0

4

ae75d3177240373c10695c905340f81e019a0e9e

1,034

py

Python

tests/v2/test_permissions_response.py

MichaelTROEHLER/datadog-api-client-python

12c46626622fb1277bb1e172753b342c671348bd

[ "Apache-2.0" ]

null

tests/v2/test_permissions_response.py

MichaelTROEHLER/datadog-api-client-python

12c46626622fb1277bb1e172753b342c671348bd

[ "Apache-2.0" ]

null

tests/v2/test_permissions_response.py

MichaelTROEHLER/datadog-api-client-python

12c46626622fb1277bb1e172753b342c671348bd

[ "Apache-2.0" ]

null

# coding: utf-8 # Unless explicitly stated otherwise all files in this repository are licensed under the Apache-2.0 License. # This product includes software developed at Datadog (https://www.datadoghq.com/). # Copyright 2019-Present Datadog, Inc. from __future__ import absolute_import import sys import unittest import datadog_api_client.v2 try: from datadog_api_client.v2.model import permission except ImportError: permission = sys.modules[ 'datadog_api_client.v2.model.permission'] from datadog_api_client.v2.model.permissions_response import PermissionsResponse class TestPermissionsResponse(unittest.TestCase): """PermissionsResponse unit test stubs""" def setUp(self): pass def tearDown(self): pass def testPermissionsResponse(self): """Test PermissionsResponse""" # FIXME: construct object with mandatory attributes with example values # model = PermissionsResponse() # noqa: E501 pass if __name__ == '__main__': unittest.main()

26.512821

108

0.736944

120

1,034

6.166667

0.633333

0.054054

0.086486

0.097297

0.104054

0.072973

0

0.016647

0.186654

1,034

38

109

27.210526

0.863258

0.400387

0

0.157895

0

0.076285

0.063018

0

0.026316

0

1

0.157895

false

0.157895

0.368421

0

0.578947

0

null

0

null

0

1

0

1

0

1

0

4

88189c0f45f7f0129b0c34b4be91ab4acfe03711

1,843

py

Python

chapter-14/exercise03.py

krastin/pp-cs3.0

502be9aac2d84215db176864e443c219e5e26591

[ "MIT" ]

null

chapter-14/exercise03.py

krastin/pp-cs3.0

502be9aac2d84215db176864e443c219e5e26591

[ "MIT" ]

null

chapter-14/exercise03.py

krastin/pp-cs3.0

502be9aac2d84215db176864e443c219e5e26591

[ "MIT" ]

null

from members import Student, Faculty, Member class Member(Member): """ Adding __repr__ to Member >>> joe = Member('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com') >>> joe Member('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com') >>> [joe] [Member('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com')] """ def __repr__(self) -> str: return "Member('%s', '%s', '%s')" % (self.name, self.address, self.email) class Faculty(Faculty): """ Adding __repr__ to Faculty >>> joe = Faculty('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com', 1234) >>> joe Faculty('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com', 1234) >>> [joe] [Faculty('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com', 1234)] """ def __repr__(self) -> str: return "Faculty('%s', '%s', '%s', %d)" % (self.name, self.address, self.email, self.faculty_number) class Student(Student): """ Adding __repr__ and __str__ to Student >>> joe = Student('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com', 4321) >>> joe Student('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com', 4321) >>> [joe] [Student('Joe Bonamassa', '1 Guitar Ave', 'joe@bona.com', 4321)] """ def __repr__(self) -> str: return "Student('%s', '%s', '%s', %d)" % (self.name, self.address, self.email, self.student_number) def __str__(self) -> str: """ >>> student = Student('Paul', 'Ajax', 'pgries@cs.toronto.edu', '1234') >>> student.__str__() 'Paul\\nAjax\\npgries@cs.toronto.edu\\n1234\\nCourses: ' """ member_string = super().__str__() return '''{}\n{}\nCourses: {}'''.format( member_string, self.student_number, ' '.join(self.courses_taking)) if __name__ == "__main__": import doctest doctest.testmod()

32.333333

107

0.570808

225

1,843

4.435556

0.226667

0.108216

0.117234

0.171343

0.56012

0.5

0.471944

0

0.028853

0.228975

1,843

57

108

32.333333

0.673469

0.475312

0

0.157895

0

0.13431

0

1

0.210526

false

0

0.105263

0.157895

0.684211

0

null

0

1

0

null

0

1

0

1

0

4

8831ed5ffd537c3671986de176e303120ec6aa26

3,238

py

Python

melodic/lib/python2.7/dist-packages/theora_image_transport/cfg/TheoraPublisherConfig.py

Dieptranivsr/Ros_Diep

d790e75e6f5da916701b11a2fdf3e03b6a47086b

[ "MIT" ]

null

melodic/lib/python2.7/dist-packages/theora_image_transport/cfg/TheoraPublisherConfig.py

Dieptranivsr/Ros_Diep

d790e75e6f5da916701b11a2fdf3e03b6a47086b

[ "MIT" ]

1

2021-07-08T10:26:06.000Z

2021-07-08T10:31:11.000Z

melodic/lib/python2.7/dist-packages/theora_image_transport/cfg/TheoraPublisherConfig.py

Dieptranivsr/Ros_Diep

d790e75e6f5da916701b11a2fdf3e03b6a47086b

[ "MIT" ]

null

## ********************************************************* ## ## File autogenerated for the theora_image_transport package ## by the dynamic_reconfigure package. ## Please do not edit. ## ## ********************************************************/ from dynamic_reconfigure.encoding import extract_params inf = float('inf') config_description = {'upper': 'DEFAULT', 'lower': 'groups', 'srcline': 246, 'name': 'Default', 'parent': 0, 'srcfile': '/opt/ros/melodic/lib/python2.7/dist-packages/dynamic_reconfigure/parameter_generator_catkin.py', 'cstate': 'true', 'parentname': 'Default', 'class': 'DEFAULT', 'field': 'default', 'state': True, 'parentclass': '', 'groups': [], 'parameters': [{'srcline': 291, 'description': "Try to achieve either 'target_bitrate' or 'quality'", 'max': 1, 'cconsttype': 'const int', 'ctype': 'int', 'srcfile': '/opt/ros/melodic/lib/python2.7/dist-packages/dynamic_reconfigure/parameter_generator_catkin.py', 'name': 'optimize_for', 'edit_method': "{'enum_description': 'Enum to control whether optimizing for bitrate or quality', 'enum': [{'srcline': 9, 'description': 'Aim for requested bitrate', 'srcfile': '/tmp/binarydeb/ros-melodic-theora-image-transport-1.9.5/cfg/TheoraPublisher.cfg', 'cconsttype': 'const int', 'value': 0, 'ctype': 'int', 'type': 'int', 'name': 'Bitrate'}, {'srcline': 10, 'description': 'Aim for requested quality', 'srcfile': '/tmp/binarydeb/ros-melodic-theora-image-transport-1.9.5/cfg/TheoraPublisher.cfg', 'cconsttype': 'const int', 'value': 1, 'ctype': 'int', 'type': 'int', 'name': 'Quality'}]}", 'default': 1, 'level': 0, 'min': 0, 'type': 'int'}, {'srcline': 291, 'description': 'Target encoding bitrate, bits per second', 'max': 99200000, 'cconsttype': 'const int', 'ctype': 'int', 'srcfile': '/opt/ros/melodic/lib/python2.7/dist-packages/dynamic_reconfigure/parameter_generator_catkin.py', 'name': 'target_bitrate', 'edit_method': '', 'default': 800000, 'level': 0, 'min': 0, 'type': 'int'}, {'srcline': 291, 'description': 'Encoding quality', 'max': 63, 'cconsttype': 'const int', 'ctype': 'int', 'srcfile': '/opt/ros/melodic/lib/python2.7/dist-packages/dynamic_reconfigure/parameter_generator_catkin.py', 'name': 'quality', 'edit_method': '', 'default': 31, 'level': 0, 'min': 0, 'type': 'int'}, {'srcline': 291, 'description': 'Maximum distance between key frames', 'max': 64, 'cconsttype': 'const int', 'ctype': 'int', 'srcfile': '/opt/ros/melodic/lib/python2.7/dist-packages/dynamic_reconfigure/parameter_generator_catkin.py', 'name': 'keyframe_frequency', 'edit_method': '', 'default': 64, 'level': 0, 'min': 1, 'type': 'int'}], 'type': '', 'id': 0} min = {} max = {} defaults = {} level = {} type = {} all_level = 0 #def extract_params(config): # params = [] # params.extend(config['parameters']) # for group in config['groups']: # params.extend(extract_params(group)) # return params for param in extract_params(config_description): min[param['name']] = param['min'] max[param['name']] = param['max'] defaults[param['name']] = param['default'] level[param['name']] = param['level'] type[param['name']] = param['type'] all_level = all_level | param['level'] TheoraPublisher_Bitrate = 0 TheoraPublisher_Quality = 1

83.025641

2,296

0.651946

391

3,238

5.299233

0.286445

0.060811

0.052124

0.048263

0.43388

0.415541

0.360521

0

0.025233

0.106547

3,238

38

2,297

85.210526

0.690978

0.125077

0

1

0.333333

0.640825

0.225462

0

1

0

false

0

0.055556

0

0.055556

0

null

0

1

0

1

0

null

0

4

885f71cfb09805b164cb063923a020bb739f920b

128

py

Python

terrascript/provider/circonus.py

hugovk/python-terrascript

08fe185904a70246822f5cfbdc9e64e9769ec494

[ "BSD-2-Clause" ]

4

2022-02-07T21:08:14.000Z

2022-03-03T04:41:28.000Z

terrascript/provider/circonus.py

hugovk/python-terrascript

08fe185904a70246822f5cfbdc9e64e9769ec494

[ "BSD-2-Clause" ]

null

terrascript/provider/circonus.py

hugovk/python-terrascript

08fe185904a70246822f5cfbdc9e64e9769ec494

[ "BSD-2-Clause" ]

2

2022-02-06T01:49:42.000Z

2022-02-08T14:15:00.000Z

# terrascript/provider/circonus.py import terrascript class circonus(terrascript.Provider): pass __all__ = ["circonus"]

12.8

37

0.757813

13

128

7.153846

0.615385

0.408602

0

0.140625

128

9

38

14.222222

0.845455

0.25

0

0.085106

0

1

0

false

0.25

0

0.5

0

1

0

null

1

0

1

0

null

0

1

0

4

88749dd2476399f09366db10995930d2e84595d7

126

py

Python

BOJ/19000~19999/19900~19999/19964.py

shinkeonkim/today-ps

f3e5e38c5215f19579bb0422f303a9c18c626afa

[ "Apache-2.0" ]

2

2020-01-29T06:54:41.000Z

2021-11-07T13:23:27.000Z

BOJ/19000~19999/19900~19999/19964.py

shinkeonkim/Today_PS

bb0cda0ee1b9c57e1cfa38355e29d0f1c6167a44

[ "Apache-2.0" ]

null

BOJ/19000~19999/19900~19999/19964.py

shinkeonkim/Today_PS

bb0cda0ee1b9c57e1cfa38355e29d0f1c6167a44

[ "Apache-2.0" ]

null

N,M=map(int,input().split()) if M == 1 or M == 2: print("NEWBIE!") elif M<=N: print("OLDBIE!") else: print("TLE!")

18

28

0.52381

22

126

3

0.727273

0

0.02

0.206349

126

7

29

18

0.64

0

0.141732

0

1

0

true

0

0.428571

1

0

null

0

1

0

null

0

1

0

1

0

4

888de2e21bf0d2a062d03a0bdd144104f536801f

267

py

Python

config.py

LooDaHu/net_drive

0e265cef6b70d5e3e4e1b0a6db68d465a8ee2fe8

[ "MIT" ]

2

2019-12-31T07:47:03.000Z

2020-01-17T00:00:38.000Z

config.py

LooDaHu/net_drive

0e265cef6b70d5e3e4e1b0a6db68d465a8ee2fe8

[ "MIT" ]

null

config.py

LooDaHu/net_drive

0e265cef6b70d5e3e4e1b0a6db68d465a8ee2fe8

[ "MIT" ]

null

class AccountSetting: """Class for several configs""" username = 'loodahu' # Set username here password = '123456' # Set password here def get_username(self): return self.username def get_password(self): return self.password

20.538462

45

0.651685

30

267

5.733333

0.5

0.069767

0.162791

0

0.030457

0.262172

267

12

46

22.25

0.84264

0.23221

0

0.065657

0

1

0.285714

false

0.428571

0

0.285714

1

0

null

0

null

0

1

0

1

0

1

0

4

31f0816c8acb25f6356fad9e2fade3eb68fe5d9e

102

py

Python

2_Python Advanced/PyPDF2/1_PyPDF2.py

Arunken/PythonScripts

702d0a3af7a9be3311f9da0afc5285d453f15484

[ "Apache-2.0" ]

null

2_Python Advanced/PyPDF2/1_PyPDF2.py

Arunken/PythonScripts

702d0a3af7a9be3311f9da0afc5285d453f15484

[ "Apache-2.0" ]

1

2021-06-02T00:58:47.000Z

2_Python Advanced/PyPDF2/1_PyPDF2.py

Arunken/PythonScripts

702d0a3af7a9be3311f9da0afc5285d453f15484

[ "Apache-2.0" ]

null

# -*- coding: utf-8 -*- """ Created on Wed Jul 11 17:29:32 2018 @author: SilverDoe """ import PyPDF2

12.75

35

0.627451

16

102

4

1

0

0.168675

0.186275

102

8

36

12.75

0.60241

0.764706

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ee0c4abe0ac612ed733176776a51dbdaf28da931

306

py

Python

pycomlink/__init__.py

jpolz/pycomlink

bd15ed4dd55fb2735578b18194bb3e9966cb40d9

[ "BSD-3-Clause" ]

1

2018-09-24T03:38:38.000Z

pycomlink/__init__.py

jayapudashine/pycomlink

8670e4492d0bf439ea238be2bd6f69df460b8d41

[ "BSD-3-Clause" ]

null

pycomlink/__init__.py

jayapudashine/pycomlink

8670e4492d0bf439ea238be2bd6f69df460b8d41

[ "BSD-3-Clause" ]

null

""" pycomlink subpackage imports """ from __future__ import absolute_import from . import core from .core.comlink import Comlink from .core.comlink_channel import ComlinkChannel from . import processing from . import io from . import vis from . import spatial from . import validation from . import util

19.125

48

0.79085

40

306

5.9

0.425

0.29661

0.127119

0

0.153595

306

15

49

20.4

0.911197

0.091503

0

1

0

true

0

1

0

1

0

null

1

0

null

0

1

0

1

0

1

0

4

ee295605088b9ac51f1ae40d021762d79bde5584

914

py

Python

utils/sampler.py

cclauss/MagnetLoss-PyTorch

266d2755379ad5b7a9d963bc9eb09f21e5275cd2

[ "MIT" ]

222

2018-03-08T03:44:33.000Z

2021-12-01T21:26:17.000Z

utils/sampler.py

liuyuyuil/MagnetLoss-PyTorch

23ac961333bf7e32911eb1dc4ed021e78b893509

[ "MIT" ]

8

2018-03-08T22:27:28.000Z

2020-04-27T08:07:28.000Z

utils/sampler.py

liuyuyuil/MagnetLoss-PyTorch

23ac961333bf7e32911eb1dc4ed021e78b893509

[ "MIT" ]

35

2018-03-14T10:11:50.000Z

2020-12-16T07:30:16.000Z

import torch class Sampler(object): """Base class for all Samplers. Every Sampler subclass has to provide an __iter__ method, providing a way to iterate over indices of dataset elements, and a __len__ method that returns the length of the returned iterators. """ def __init__(self, data_source): pass def __iter__(self): raise NotImplementedError def __len__(self): raise NotImplementedError class SubsetSequentialSampler(Sampler): """Samples elements sequentially from a given list of indices, without replacement. Arguments: indices (list): a list of indices """ def __init__(self, indices, batch_indices): self.indices = indices self.batch_indices = batch_indices def __iter__(self): return (self.indices[i] for i in self.batch_indices) def __len__(self): return len(self.indices)

25.388889

87

0.684902

112

914

5.258929

0.491071

0.074703

0.037351

0

0.247265

914

35

88

26.114286

0.856105

0.384026

0

0.375

0

1

0.375

false

0.0625

0.125

0.6875

0

null

0

null

0

1

0

1

0

1

0

4

ee52ebdafe2e237c29e15659a2cbe5a098b60df3

68

py

Python

pgm/sum.py

Dharani-18/CODEKATA

c9c39a0579d2ee7fd8790d240f50e087708b8050

[ "Apache-2.0" ]

null

pgm/sum.py

Dharani-18/CODEKATA

c9c39a0579d2ee7fd8790d240f50e087708b8050

[ "Apache-2.0" ]

null

pgm/sum.py

Dharani-18/CODEKATA

c9c39a0579d2ee7fd8790d240f50e087708b8050

[ "Apache-2.0" ]

2

2019-05-24T05:26:31.000Z

2019-07-18T06:18:48.000Z

#adding 2 numbers in python a,b=map(int,input().split()) print(a+b)

17

28

0.691176

14

68

3.357143

0.857143

0.085106

0

0.016393

0.102941

68

3

29

22.666667

0.754098

0.382353

0

1

0

true

0

0.5

1

0

null

0

1

0

null

0

1

0

1

0

4

ee7310a6e66987527dd6bdaca74d16d91de4fc16

688

py

Python

tests/conftest.py

skellet0r/CloudToken

cee88400e308111f7d30fd283feb1e0c6d60dd7e

[ "MIT" ]

1

2021-01-01T19:21:02.000Z

tests/conftest.py

skellet0r/CloudToken

cee88400e308111f7d30fd283feb1e0c6d60dd7e

[ "MIT" ]

null

tests/conftest.py

skellet0r/CloudToken

cee88400e308111f7d30fd283feb1e0c6d60dd7e

[ "MIT" ]

null

import pytest @pytest.fixture(scope="module") def adam(accounts): """Account used to deploy the contract""" return accounts[0] @pytest.fixture(scope="module") def beth(accounts): """Secondary account to interact with""" return accounts[1] @pytest.fixture(scope="module") def oracle(adam, PriceFeedOracle): """Deploy a mocked price feed oracle""" return adam.deploy(PriceFeedOracle) @pytest.fixture(scope="module") def token(adam, oracle, CloudToken): """Deploy the contract and return it""" return adam.deploy(CloudToken, 10 ** 21, oracle.address) @pytest.fixture(autouse=True) def isolate(fn_isolation): """Isolate each function""" pass

21.5

60

0.702035

86

688

5.604651

0.488372

0.134855

0.149378

0.19917

0.224066

0

0.010363

0.15843

688

31

61

22.193548

0.822107

0.232558

0

0.25

0

0.047809

0

1

0.3125

false

0.0625

0

0.625

0

null

0

1

0

null

0

1

0

1

0

1

0

4

ee808e5ed28cfc6a0cd40819ee5f9b8a4d049572

186

py

Python

yah/types/room.py

sunsx0/yah

c073015dfa1fb2b5232c3ec4a9b9dbae571f7053

[ "MIT" ]

null

yah/types/room.py

sunsx0/yah

c073015dfa1fb2b5232c3ec4a9b9dbae571f7053

[ "MIT" ]

null

yah/types/room.py

sunsx0/yah

c073015dfa1fb2b5232c3ec4a9b9dbae571f7053

[ "MIT" ]

null

import typing import dataclasses as dc from .device import Device @dc.dataclass class Room: id: str name: str devices: typing.List[Device] = dc.field(default_factory=list)

16.909091

65

0.731183

27

186

5

0.666667

0.118519

0

0.188172

186

10

66

18.6

0.89404

0

1

0

true

0

0.375

0

0.875

0

1

0

null

0

null

0

1

0

1

0

1

0

4

ee8ea7ceba44f5928d927abe7ae7991da1ea36e1

215

py

Python

__init__.py

mtasic85/routingtable

03c581ab3a29b90b780fb1dec0dfcfe7fc77d5d4

[ "MIT" ]

5

2016-01-25T19:14:48.000Z

2020-01-22T14:46:36.000Z

__init__.py

mtasic85/routingtable

03c581ab3a29b90b780fb1dec0dfcfe7fc77d5d4

[ "MIT" ]

null

__init__.py

mtasic85/routingtable

03c581ab3a29b90b780fb1dec0dfcfe7fc77d5d4

[ "MIT" ]

1

2020-12-30T11:35:46.000Z

__all__ = ['PrintColors', 'Contact', 'RoutingTable', 'ProtocolCommand', 'Node'] from contact import Contact from routing_table import RoutingTable from protocol_command import ProtocolCommand from node import Node

30.714286

79

0.809302

24

215

7

0.5

0

0.111628

215

6

80

35.833333

0.879581

0

0.227907

0

1

0

false

0

0.8

0

0.8

0

1

0

null

0

1

0

null

0

1

0

1

0

4

ee91ab0490423b9ca1913f5f4831cd705fd6e912

252

py

Python

tests/test_versionpredicate.py

enterstudio/pypi-legacy

a58283c7bd53c44d0f2227bd56a577edf64406c2

[ "BSD-3-Clause" ]

1

2015-11-08T11:31:07.000Z

tests/test_versionpredicate.py

enterstudio/pypi-legacy

a58283c7bd53c44d0f2227bd56a577edf64406c2

[ "BSD-3-Clause" ]

null

tests/test_versionpredicate.py

enterstudio/pypi-legacy

a58283c7bd53c44d0f2227bd56a577edf64406c2

[ "BSD-3-Clause" ]

null

"""Tests harness for distutils.versionpredicate. """ import doctest import unittest import versionpredicate def test_suite(): return doctest.DocTestSuite(versionpredicate) if __name__ == "__main__": unittest.main(defaultTest="test_suite")

14.823529

48

0.769841

26

252

7.076923

0.653846

0.097826

0

0.130952

252

16

49

15.75

0.840183

0.178571

0

0.090452

0

1

0.142857

true

0

0.428571

0.142857

0.714286

0

1

0

null

0

null

0

1

0

1

0

4

c99caa0b70f277998668a02fbbe19aa7571ce842

102

py

Python

projekt/backend/biljnevrste/biljnevrsteapp/apps.py

vdavid033/biljnevrste_repo

72517f1403b539f152c71a64aab9e1e0d1ab034f

[ "MIT" ]

null

projekt/backend/biljnevrste/biljnevrsteapp/apps.py

vdavid033/biljnevrste_repo

72517f1403b539f152c71a64aab9e1e0d1ab034f

[ "MIT" ]

51

2019-04-01T14:56:31.000Z

2022-03-21T00:35:42.000Z

projekt/backend/biljnevrste/biljnevrsteapp/apps.py

vdavid033/biljnevrste_repo

72517f1403b539f152c71a64aab9e1e0d1ab034f

[ "MIT" ]

14

2019-04-02T15:22:06.000Z

2019-06-09T13:09:40.000Z

from django.apps import AppConfig class BiljnevrsteappConfig(AppConfig): name = 'biljnevrsteapp'

20.4

38

0.794118

10

102

8.1

0.9

0

0.137255

102

5

39

20.4

0.920455

0

0.135922

0

1

0

false

0

0.333333

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

4

c9cfeab54564530f09759421f6cb135cb8f79725

244

py

Python

OctaHomeAppInterface/OctaFiles/menus.py

Tomcuzz/OctaHomeAutomation

4f0c5ea8b3d5b6e67633ae9c4cb95287d2784f5e

[ "MIT" ]

4

2016-08-14T22:07:03.000Z

2020-10-05T14:43:03.000Z

OctaHomeAppInterface/OctaFiles/menus.py

Tomcuzz/OctaHomeAutomation

4f0c5ea8b3d5b6e67633ae9c4cb95287d2784f5e

[ "MIT" ]

null

OctaHomeAppInterface/OctaFiles/menus.py

Tomcuzz/OctaHomeAutomation

4f0c5ea8b3d5b6e67633ae9c4cb95287d2784f5e

[ "MIT" ]

null

from OctaHomeCore.OctaFiles.menus import * class DeviceUsersSettingsNavBarItem(SettingsSideNavBarItem): Priority = 60 DisplayName = "Device Logins" @property def Link(self): return reverse('SettingsPage', kwargs={'page':'DeviceUsers'})

27.111111

63

0.778689

23

244

8.26087

1

0

0.009217

0.110656

244

9

63

27.111111

0.866359

0

0.163265

0

1

0.142857

false

0

0.142857

0.857143

0

1

0

null

0

1

0

null

0

1

0

4

a00102a089148d7c166bc884f2def4624b5cefae

245

py

Python

billiards/billiards/id.py

zxkane/billiards

809a37b111a0fdbf7a2b1176149256b93c43045f

[ "Apache-1.1" ]

null

billiards/billiards/id.py

zxkane/billiards

809a37b111a0fdbf7a2b1176149256b93c43045f

[ "Apache-1.1" ]

null

billiards/billiards/id.py

zxkane/billiards

809a37b111a0fdbf7a2b1176149256b93c43045f

[ "Apache-1.1" ]

1

2021-02-08T13:19:34.000Z

# -*- coding: utf-8 -*- # encoding: utf-8 ''' Created on 2014年3月20日 @author: kane ''' import string import random def generator(size=7, chars=string.ascii_uppercase + string.digits): return ''.join(random.choice(chars) for _ in range(size))

22.272727

68

0.702041

34

245

5

0.764706

0.047059

0

0.047393

0.138776

245

11

69

22.272727

0.758294

0.306122

0

1

0.25

false

0

0.5

0.25

1

0

null

0

null

0

1

0

1

0

4

4e56fa1e3131434b2b16b306d6f9b56be1da78f7

69

py

Python

locale/pot/api/plotting/_autosummary/pyvista-themes-_ColorbarConfig-height-1.py

tkoyama010/pyvista-doc-translations

23bb813387b7f8bfe17e86c2244d5dd2243990db

[ "MIT" ]

4

2020-08-07T08:19:19.000Z

2020-12-04T09:51:11.000Z

locale/pot/api/plotting/_autosummary/pyvista-themes-_ColorbarConfig-height-1.py

tkoyama010/pyvista-doc-translations

23bb813387b7f8bfe17e86c2244d5dd2243990db

[ "MIT" ]

19

2020-08-06T00:24:30.000Z

2022-03-30T19:22:24.000Z

locale/pot/api/plotting/_autosummary/pyvista-themes-_ColorbarConfig-height-1.py

tkoyama010/pyvista-doc-translations

23bb813387b7f8bfe17e86c2244d5dd2243990db

[ "MIT" ]

1

2021-03-09T07:50:40.000Z

import pyvista pyvista.global_theme.colorbar_horizontal.height = 0.2

23

53

0.855072

10

69

5.7

0.9

0

0.03125

0.072464

69

2

54

34.5

0.859375

0

1

0

true

0

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4ea7253f1c907547ec513b397d20a18904e2d82b

159

py

Python

tests/web_platform/CSS2/normal_flow/test_block_in_inline_empty.py

fletchgraham/colosseum

77be4896ee52b8f5956a3d77b5f2ccd2c8608e8f

[ "BSD-3-Clause" ]

null

tests/web_platform/CSS2/normal_flow/test_block_in_inline_empty.py

fletchgraham/colosseum

77be4896ee52b8f5956a3d77b5f2ccd2c8608e8f

[ "BSD-3-Clause" ]

null

tests/web_platform/CSS2/normal_flow/test_block_in_inline_empty.py

fletchgraham/colosseum

77be4896ee52b8f5956a3d77b5f2ccd2c8608e8f

[ "BSD-3-Clause" ]

1

2020-01-16T01:56:41.000Z

from tests.utils import W3CTestCase class TestBlockInInlineEmpty(W3CTestCase): vars().update(W3CTestCase.find_tests(__file__, 'block-in-inline-empty-'))

26.5

77

0.792453

18

159

6.722222

0.833333

0

0.02069

0.08805

159

5

78

31.8

0.813793

0

0.139241

0

1

0

true

0

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

4

4ec0e8369647b2a9f658f3942fec43cca891f967

35,728

py

Python

Preprocessing/Salimi/Core/Log_Reg_Classifier.py

maliha93/Fairness-Analysis-Code

acf13c6e7993704fc627249fe4ada44d8b616264

[ "MIT" ]

null

Preprocessing/Salimi/Core/Log_Reg_Classifier.py

maliha93/Fairness-Analysis-Code

acf13c6e7993704fc627249fe4ada44d8b616264

[ "MIT" ]

null

Preprocessing/Salimi/Core/Log_Reg_Classifier.py

maliha93/Fairness-Analysis-Code

acf13c6e7993704fc627249fe4ada44d8b616264

[ "MIT" ]

null

import numpy as np import numpy as np import pandas as pd from sklearn import preprocessing import pprint from os import chdir from sklearn.ensemble import RandomForestClassifier import sys #sys.path.insert(0, '//Users/babakmac/Documents/HypDB/relational-causal-inference/source/HypDB') #from core.cov_selection import * #from core.explanation import * #import core.query as sql #import modules.statistics.cit as ci_test #from Modules.InformationTheory.info_theo import * from sklearn.metrics import confusion_matrix import copy from sklearn import tree from utils.read_data import read_from_csv from sklearn import model_selection from sklearn.model_selection import cross_val_score import seaborn as sns sns.set(style="white") #white background style for seaborn plots sns.set(style="whitegrid", color_codes=True) from sklearn.linear_model import LogisticRegression from sklearn.feature_selection import RFE from sklearn.model_selection import train_test_split, cross_val_score from sklearn.metrics import accuracy_score, classification_report, precision_score, recall_score from sklearn.metrics import confusion_matrix, precision_recall_curve, roc_curve, auc, log_loss from sklearn.linear_model import LogisticRegression import statsmodels.api as sm from sklearn.preprocessing import LabelEncoder from sklearn.metrics import roc_auc_score from sklearn.metrics import roc_curve import numpy as np from scipy import interp import matplotlib as mpl mpl.use('TkAgg') import matplotlib.pyplot as plt from itertools import cycle from sklearn.linear_model import LogisticRegression from sklearn import svm, datasets from sklearn.metrics import roc_curve, auc from sklearn.model_selection import StratifiedKFold import math from sklearn.model_selection import StratifiedShuffleSplit from sklearn.model_selection import ShuffleSplit from sklearn.preprocessing import StandardScaler def data_split(data,outcome,path,k=5,test_size=0.3): rs = StratifiedShuffleSplit(n_splits=k, test_size=test_size, random_state=2) data_y = pd.DataFrame(data[outcome]) data_X = data.drop([outcome], axis=1) rs.get_n_splits(data_X, data_y) j = 0 for test, train in rs.split(data_X,data_y): cur_test = data.iloc[train] cur_train = data.iloc[test] cur_train = pd.concat([cur_test, cur_train]) cur_train.to_csv(path + 'train_' + str(j) + '.csv', encoding='utf-8', index=False) #print(path + 'train_' + str(j) + '.csv') #cur_test.to_csv(path + 'test_' + str(j) + '.csv', encoding='utf-8', index=False) #print(len(cur_test.index)) #print(path + 'test_' + str(j) + '.csv') j +=1 def cross_valid(data,features,D_features,Y_features,X_features,path,k=5): print('Original Data Size',len(data.index)) train_df = data[features] dft1 = pd.get_dummies(train_df[X_features]) dft2 = pd.get_dummies(train_df[Y_features]) X = dft1.values y = dft2.values y = y.flatten() cv = StratifiedKFold(n_splits=k,shuffle=True) #classifier = LogisticRegression() j = 0 for train, test in cv.split(X, y): cur_train = train_df.iloc[train] cur_test = train_df.iloc[test] cur_train.to_csv(path + 'train_' + str(j) + '.csv', encoding='utf-8', index=False) print(len(cur_train.index)) print(path + 'train_' + str(j) + '.csv') cur_test.to_csv(path + 'test_' + str(j) + '.csv', encoding='utf-8', index=False) print(len(cur_test.index)) print(path + 'test_' + str(j) + '.csv') j +=1 def strr(list): return str(['%.3f' % val for val in list]) def pretty(d, indent=0): for key, value in d.items(): print('\t' * indent + str(key)) if isinstance(value, dict): pretty(value, indent+1) else: print('*****************************************************************************************') print('\t' * (indent+1) + strr(value)) print('mean:', mean(value)) print('variance:', var(value)) print('*****************************************************************************************') def test_rep_str(D_features,Y_features,X_features,path1,path2,k=5,droped=False,classifier='log_reg'): if classifier=='log_reg': classifier = LogisticRegression() elif classifier=='rand_forest': classifier=RandomForestClassifier(max_depth=2, random_state=0) tprs = [] aucs = [] mean_fpr = np.linspace(0, 1, 100) i = 0 MI_inp = dict() MI_out = dict() MI_test=dict() for j in range(0, k): print(path2+str(j)+'.csv') cur_train=read_from_csv(path1+str(j)+'.csv') print(path1+str(j)+'.csv') cur_test=read_from_csv(path2+str(j)+'.csv') #atts=cur_train.columns #atts=atts.tolist() #list=[att.replace('_x','').replace('_y','') for att in atts] #atts for item in D_features: pval, mi = ci_test.ulti_fast_permutation_tst(cur_train, item, Y_features, X_features, pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) rmi = round(mi, 3) print('####################################') print(len(cur_train.index)) print('Mutul information in train data:', item,'pvalue:' , pval, 'MI:', rmi) print('####################################') if item not in MI_inp.keys(): MI_inp[item]= [rmi] else: MI_inp[item] = MI_inp[item] +[rmi] inf = Info(cur_test) for item in D_features: pval, mi = ci_test.ulti_fast_permutation_tst(cur_test, item, Y_features, X_features, pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) mi = round(mi, 3) print('####################################') print('MI in test data:', item,'pvalue:' , pval, 'MI:', mi) print('####################################') if item not in MI_test.keys(): MI_test[item]= [mi] else: MI_test[item] = MI_test[item] +[mi] mi = inf.CMI(D_features+X_features, Y_features) mi = round(mi, 3) print('Predictive Power(traning)', mi) inf = Info(cur_test) mi = inf.CMI(D_features, Y_features,X_features) mi = round(mi, 3) print('Repaied MI test', mi) mi = inf.CMI(D_features+X_features, Y_features) mi = round(mi, 3) print('Predictive Power(test)', mi) cur_train[Y_features[0]] = pd.to_numeric(cur_train[Y_features[0]]) ate = cur_train.groupby([D_features[0]])[Y_features[0]].mean() print(ate) # m = abs(ate.values[0] - ate.values[1]).value #ate0.insert(0, m) #print('Repaied ATE \n', ate) # new=abs(max((ate.values[0] / ate.values[1]) - 1, (ate.values[0] / ate.values[1]) - 1)).value #print('Repaied J \n', new) #J1.insert(0,new) #ate = cur_test.groupby([D_features[0]])[Y_features[0]].mean() #m = abs(ate.values[0] - ate.values[1]).value #ate0.insert(0, m) #print('Repaied ATE test \n', ate) #new=abs(max((ate.values[0] / ate.values[1]) - 1, (ate.values[0] / ate.values[1]) - 1)).value #print('Repaied J test \n', new) #J1.insert(0,new) # print("len",cur_train.columns,len(cur_train.index),cur_train.shape) # print("len",len(cur_test.index),cur_test.shape) j += 1 #inf = Info(cur_train) #MI_inp.insert(0, I) cur_test['W']=1 train_objs_num = len(cur_train) dataset = pd.concat(objs=[cur_train[ D_features+X_features], cur_test[ D_features+X_features]], axis=0) dataset = pd.get_dummies(dataset) dft1 = dataset[:train_objs_num] dft4 = dataset[train_objs_num:] train_X = dft1.values train_y = cur_train[Y_features[0]].values # train_y=train_y.flatten() #if droped: # dft4 = pd.get_dummies(cur_test[X_features]) #else: # dft4 = pd.get_dummies(cur_test[ D_features+X_features]) #print(cur_test[D_features+X_features]) dft5 = pd.get_dummies(cur_test[Y_features]) # logit = sm.Logit(train_df['bscore'], train_df['juv_misd_count']) X = dft4.values y = dft5.values y = y.flatten() #print("#####################",len(train_X),len(train_y),type(train_X),type(train_y),train_X,train_y,X.shape) print(X.shape,train_X.shape) kfold = model_selection.KFold(n_splits=10, random_state=7) modelCV = LogisticRegression() probas_ = classifier.fit(train_X, train_y).predict_proba(X) scoring = 'accuracy' results = model_selection.cross_val_score(modelCV, train_X, train_y, cv=kfold, scoring=scoring) print('@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@@',mean(results)) #logit = sm.Logit(train_X,cur_train[Y_features[0]]) # fit the model #result = logit.fit() #print(probas_) y_pred = classifier.predict(X) cur_test.insert(0,'y',y_pred) # insert the outcome into the test dataset for item in D_features: pval, mi = ci_test.ulti_fast_permutation_tst(cur_test, item, ['y'], X_features, pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) mi = round(mi, 3) print('*************************') print(' MI in output',item,'pvalue:' , pval, 'MI:', mi) print('***************************') if item not in MI_out.keys(): MI_out[item] = [mi] else: MI_out[item] = MI_out[item] + [mi] print(path1 + str(j) + '.csv') for item in D_features: pval, mi = ci_test.ulti_fast_permutation_tst(cur_test, item, ['y'], pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) #mi = round(mi, 3) print('*************************') print(' MI in output (marginal)',item,'pvalue:' , pval, 'MI:', mi) print('***************************') ate = cur_test.groupby([D_features[0]])[['y']].mean() print(ate) # print("ATE on on test labels", '\n averagee:', mean(ate1), "variancee", var(ate1)) # print("ATE on on outcome", '\n averagee:', mean(ate2), "variancee", var(ate2)) # print("J on on input", '\n averagee:', mean(J1), "variancee", var(J1)) # print("J on on outcome", '\n averagee:', mean(J2), "variancee", var(J2)) print('####################################') #ate = cur_test.groupby(D_features)[Y_features[0]].mean() #m = abs(ate.values[0] - ate.values[1]).value #ate1.insert(0, m) ate = cur_test.groupby(D_features)['y'].mean() #m = abs(ate.values[0] - ate.values[1]).value #ate2.insert(0, m) print('ATE on outcome:',ate) #new=abs(max((ate.values[0] / ate.values[1]) - 1, (ate.values[0] / ate.values[1]) - 1)).value #print('Outcome J \n', new) #J2.insert(0,new) fpr, tpr, thresholds = roc_curve(y, probas_[:, 1]) tprs.append(interp(mean_fpr, fpr, tpr)) tprs[-1][0] = 0.0 roc_auc = auc(fpr, tpr) aucs.append(roc_auc) plt.plot(fpr, tpr, lw=1, alpha=0.3, label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc)) cur_test.to_csv(path1 + '_trained.csv') i += 1 plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r', label='Luck', alpha=.8) mean_tpr = np.mean(tprs, axis=0) mean_tpr[-1] = 1.0 mean_auc = auc(mean_fpr, mean_tpr) std_auc = np.std(aucs) plt.plot(mean_fpr, mean_tpr, color='b', label=r'Mean ROC (AUC = %0.2f $\pm$ %0.2f)' % (mean_auc, std_auc), lw=2, alpha=.8) std_tpr = np.std(tprs, axis=0) tprs_upper = np.minimum(mean_tpr + std_tpr, 1) tprs_lower = np.maximum(mean_tpr - std_tpr, 0) plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2, label=r'$\pm$ 1 std. dev.') plt.xlim([-0.05, 1.05]) plt.ylim([-0.05, 1.05]) plt.xlabel('False Positive Rate') plt.ylabel('True Positive Rate') plt.title('Receiver operating characteristic example') plt.legend(loc="lower right") #print("Mutual Information on repaired traning labels", '\n averagee:', mean(rep_MI_inp), "variancee",var(rep_MI_inp)) #print("ATE on repaired traning labels", '\n averagee:', mean(ate0), "variancee", var(ate0)) #print("Mutual Information on test labels", '\n averagee:', mean(MI_inp.values()), "variancee", var(MI_inp.values())) #print("Mutual Information on outcome", '\n avg:', mean(MI_out.values()), "variancee", var(MI_out.values())) print("Mutual Information on train: \n") pretty(MI_inp) plt.show() print("Mutual Information on test: \n") pretty(MI_test) #print(" Mutual Information on repaired data", rep_MI_inp) print("Mutual Information on outcome: \n") pretty(MI_out) plt.show() return MI_out,MI_inp, mean_auc, std_auc def classification(cur_train,cur_test, dependant, dependee, classifier='log_reg'): if classifier=='log_reg': classifier = LogisticRegression() elif classifier=='rand_forest': classifier=RandomForestClassifier(max_depth=2, random_state=0) train_objs_num = len(cur_train) dataset = pd.concat(objs=[cur_train[dependant], cur_test[ dependant]], axis=0) dataset = pd.get_dummies(dataset) dft1 = dataset[:train_objs_num] dft4 = dataset[train_objs_num:] train_X = dft1.values train_y = cur_train[dependee[0]].values dft5 = pd.get_dummies(cur_test[dependee]) X = dft4.values y = dft5.values y = y.flatten() probas_ = classifier.fit(train_X, train_y).predict_proba(X) #coef= classifier.coef_ y_pred = classifier.predict(X) probas_=np.array(probas_) #cur_test.insert(0, 'prob', probas_[:,0]) cur_test.insert(0,'y',y_pred) # insert the outcome into the test dataset #cur_test['FP']=cur_test.loc[(cur_test[Y_features] ==1) & (cur_test.y == 1)] #cur_test['FP'] = cur_test.apply(lambda x: 1 if x[dependee[0]] == 0 and x['y'] == 1 else 0, axis=1) #cur_test['FN'] = cur_test.apply(lambda x: 1 if x[dependee[0]] == 1 and x['y'] == 0 else 0, axis=1) print('accuracy',accuracy_score(cur_test[dependee[0]], y_pred, normalize=True)) print('AUC', roc_auc_score(cur_test[dependee[0]], y_pred)) print(confusion_matrix(cur_test[dependee[0]], y_pred)) fpr, tpr, _ = roc_curve(y_pred, cur_test[dependee[0]], drop_intermediate=False) import matplotlib.pyplot as plt plt.figure() ##Adding the ROC plt.plot(fpr, tpr, color='red', lw=2, label='ROC curve') ##Random FPR and TPR plt.plot([0, 1], [0, 1], color='blue', lw=2, linestyle='--') ##Title and label plt.xlabel('FPR') plt.ylabel('TPR') plt.title('ROC curve') plt.show() return cur_test def old_test_rep_str(indeps, features, protecteds, Y_features, path1, path2, k=5, droped=False, classifier='log_reg',method='original'): classifer_method=classifier if Y_features[0] in features: features.remove(Y_features[0]) D_features=[] X_features=features print("Fetures to learn on",X_features+D_features) if classifier=='log_reg': classifier = LogisticRegression() elif classifier=='rand_forest': classifier=RandomForestClassifier(max_depth=2, random_state=0) tprs = [] aucs = [] mean_fpr = np.linspace(0, 1, 100) for j in range(0, k): print(path2+str(j)+'.csv') cur_train=read_from_csv(path1+str(j)+'.csv') print(path1+str(j)+'.csv') cur_test=read_from_csv(path2+str(j)+'.csv') #atts=cur_train.columns #atts=atts.tolist() #list=[att.replace('_x','').replace('_y','') for att in atts] #atts for att in protecteds: ate = cur_train.groupby([att])[Y_features].mean() print('ATE on train:',att, ate) for att in protecteds: ate = cur_test.groupby([att])[Y_features].mean() print('ATE on test:',att, ate) i=0 for indep in indeps: X=indep[0] Y=indep[1] Z=indep[2] for att in [X,Y,Z]: if 'y' in att: att.remove('y') att.insert(0,Y_features[0]) pval, mi = ci_test.ulti_fast_permutation_tst(cur_train, X, Y, Z, pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) rmi = round(mi, 3) print('####################################') print(len(cur_train.index)) print('MI in train data:', indep,'pvalue:' , pval, 'MI:', rmi) print('####################################') MI_inp[i]= [rmi] i+=1 inf = Info(cur_test) i=0 for indep in indeps: X=indep[0] Y=indep[1] Z=indep[2] for att in [X,Y,Z]: if 'y' in att: att.remove('y') att.insert(0,Y_features[0]) pval, mi = ci_test.ulti_fast_permutation_tst(cur_test, X, Y, Z, pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) rmi = round(mi, 3) print('####################################') print(len(cur_test.index)) print('MI in test data:', indep,'pvalue:' , pval, 'MI:', rmi) print('####################################') MI_test[i]= [rmi] i+=1 mi = inf.CMI(D_features+X_features, Y_features) mi = round(mi, 3) print('Predictive Power(traning)', mi) inf = Info(cur_test) mi = inf.CMI(D_features, Y_features,X_features) mi = round(mi, 3) print('Repaied MI test', mi) mi = inf.CMI(D_features+X_features, Y_features) mi = round(mi, 3) print('Predictive Power(test)', mi) #cur_train[Y_features[0]] = pd.to_numeric(cur_train[Y_features[0]]) #ate = cur_train.groupby([D_features[0]])[Y_features[0]].mean() #print(ate) # m = abs(ate.values[0] - ate.values[1]).value #ate0.insert(0, m) #print('Repaied ATE \n', ate) # new=abs(max((ate.values[0] / ate.values[1]) - 1, (ate.values[0] / ate.values[1]) - 1)).value #print('Repaied J \n', new) #J1.insert(0,new) #ate = cur_test.groupby([D_features[0]])[Y_features[0]].mean() #m = abs(ate.values[0] - ate.values[1]).value #ate0.insert(0, m) #print('Repaied ATE test \n', ate) #new=abs(max((ate.values[0] / ate.values[1]) - 1, (ate.values[0] / ate.values[1]) - 1)).value #print('Repaied J test \n', new) #J1.insert(0,new) # print("len",cur_train.columns,len(cur_train.index),cur_train.shape) # print("len",len(cur_test.index),cur_test.shape) j += 1 #inf = Info(cur_train) #MI_inp.insert(0, I) cur_test['W']=1 train_objs_num = len(cur_train) dataset = pd.concat(objs=[cur_train[ D_features+X_features], cur_test[ D_features+X_features]], axis=0) dataset = pd.get_dummies(dataset) dft1 = dataset[:train_objs_num] dft4 = dataset[train_objs_num:] train_X = dft1.values train_y = cur_train[Y_features[0]].values # train_y=train_y.flatten() #if droped: # dft4 = pd.get_dummies(cur_test[X_features]) #else: # dft4 = pd.get_dummies(cur_test[ D_features+X_features]) #print(cur_test[D_features+X_features]) dft5 = pd.get_dummies(cur_test[Y_features]) # logit = sm.Logit(train_df['bscore'], train_df['juv_misd_count']) X = dft4.values y = dft5.values y = y.flatten() #print("#####################",len(train_X),len(train_y),type(train_X),type(train_y),train_X,train_y,X.shape) print(X.shape,train_X.shape) #logit = sm.Logit(train_X,cur_train[Y_features[0]]) probas_ = classifier.fit(train_X, train_y).predict_proba(X) scoring = 'accuracy' #result = logit.fit() #print(probas_) y_pred = classifier.predict(X) #predicted = cross_validation.cross_val_predict(logreg, X, y, cv=10) cur_test.insert(0,'y',y_pred) # insert the outcome into the test dataset #cur_test['FP']=cur_test.loc[(cur_test[Y_features] ==1) & (cur_test.y == 1)] cur_test['FP'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 0 and x['y'] == 1 else 0, axis=1) cur_test['FN'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 1 and x['y'] == 0 else 0, axis=1) cur_test['TP'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 1 and x['y'] == 1 else 0, axis=1) cur_test['TN'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 0 and x['y'] == 0 else 0, axis=1) i=0 Z=[] #t_indeps=indeps.copy() t_indeps=copy.copy(indeps) for indep in t_indeps: X=indep[0] Y=indep[1] Z=indep[2] for att in [X,Y,Z]: if Y_features[0] in att: att.remove(Y_features[0]) att.insert(0,'y') for p in protecteds: if p in Z: Z.remove(p) pval, mi = ci_test.ulti_fast_permutation_tst(cur_test, X, Y, Z, pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) rmi = round(mi, 3) print('####################################') print(len(cur_test.index)) print('MI in outcome:', indep,'pvalue:' , pval, 'MI:', rmi) print('####################################') MI_test[i]= [rmi] i+=1 print(path1 + str(j) + '.csv') for item in D_features: pval, mi = ci_test.ulti_fast_permutation_tst(cur_test, item, ['y'], pvalue=0.01, debug=False, loc_num_samples=100, num_samples=100, view=False) #mi = round(mi, 3) print('*************************') print(' MI in output (marginal)',item,'pvalue:' , pval, 'MI:', mi) print('***************************') inf=Info(cur_test) for att in protecteds: ate = cur_test.groupby([att])[['y']].mean() print(att, ate) #sql.mplot(ate, att, ['y'], 'Average Outcome', att, # fontsize=20) ate, matcheddata, adj_set, pur = sql.adjusted_groupby(cur_test, [att], ['y'], threshould=10, covariates=Z, mediatpor=[], init=['Male']) print('adjusted', att, X_features, ate) #sql.mplot(ate, [att], ['y'], ' Average Outcome Adjusted by: ' + list2string(Z), # list2string([att]), # fontsize=24) print('*************************') ate = cur_test.groupby([att])[['FP']].mean() print('FP:', att, ate) #sql.mplot(ate, att, ['FP'], 'FP Rate', att, fontsize=24) ate = cur_test.groupby([att])[['FN']].mean() print('FN:', att, ate) #sql.mplot(ate, [att], ['FN'], 'FN Rate', att, fontsize=24) print('***************************') ate, matcheddata, adj_set, pur = sql.adjusted_groupby(cur_test, [att], ['FP'], threshould=0, covariates=Z, mediatpor=[], init=['Male']) #sql.mplot(ate, [att], ['FP'], 'FP Rate Adjusted by: ' + list2string(Z), # list2string([att]), # fontsize=24) print('Adjusted FP:', att, inf.CMI([att], ['FP']), inf.CMI([att], ['FP'], Z)) print('***************************') ate, matcheddata, adj_set, pur = sql.adjusted_groupby(cur_test, [att], ['FN'], threshould=10, covariates=Z, mediatpor=[], init=['Male']) #sql.mplot(ate, [att], ['FN'], 'FN Rate Adjusted by: ' + list2string(Z), # list2string([att]), # fontsize=24) print('Adjusted FN:', att, ate, inf.CMI([att], ['FN']), inf.CMI([att], ['FN'], Z)) print('***************************') '####' #print('Adjusted FP:', att, inf.CMI([att], ['FP']), inf.CMI([att], ['FP'], Z+Y_features)) #print('***************************') #ate, matcheddata, adj_set, pur = sql.adjusted_groupby(cur_test, [att], ['FN'], # threshould=10, # covariates=Z, mediatpor=[], init=['Male']) #sql.mplot(ate, [att], ['FN'], 'FN Rate Adjusted by: ' + list2string(Z), # list2string([att]), # fontsize=24) #print('Adjusted FN:', att, ate, inf.CMI([att], ['FN']), inf.CMI([att], ['FN'], Z+Y_features)) print('***************************') #ate = cur_test.groupby(D_features)[Y_features[0]].mean() #m = abs(ate.values[0] - ate.values[1]).value #ate1.insert(0, m) #ate = cur_test.groupby(D_features)['y'].mean() #m = abs(ate.values[0] - ate.values[1]).value #ate2.insert(0, m) #new=abs(max((ate.values[0] / ate.values[1]) - 1, (ate.values[0] / ate.values[1]) - 1)).value #print('Outcome J \n', new) #J2.insert(0,new) fpr, tpr, thresholds = roc_curve(cur_test[Y_features[0]], probas_[:, 1]) tprs.append(interp(mean_fpr, fpr, tpr)) tprs[-1][0] = 0.0 roc_auc = auc(fpr, tpr) aucs.append(roc_auc) plt.plot(fpr, tpr, lw=1, alpha=0.3, label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc)) #df=cur_test[features+['FP','FN','y']] df=cur_test ##FPs1=df[df['y']==1].index #FPs2 = df[df[Y_features] == 0].index #index=intersect1d(FPs1,FPs2) #df[FP]= #M=confusion_matrix(cur_test['y'], cur_test[Y_features]) #print(M) df.to_csv(path1 + '_'+method+'_'+classifer_method+'_'+str(j)+'.csv') print(path1 + '_'+method+'_'+classifer_method+'_'+str(j)+'.csv') i += 1 plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r', label='Luck', alpha=.8) mean_tpr = np.mean(tprs, axis=0) mean_tpr[-1] = 1.0 mean_auc = auc(mean_fpr, mean_tpr) std_auc = np.std(aucs) plt.plot(mean_fpr, mean_tpr, color='b', label=r'Mean ROC (AUC = %0.2f $\pm$ %0.2f)' % (mean_auc, std_auc), lw=2, alpha=.8) std_tpr = np.std(tprs, axis=0) tprs_upper = np.minimum(mean_tpr + std_tpr, 1) tprs_lower = np.maximum(mean_tpr - std_tpr, 0) plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2, label=r'$\pm$ 1 std. dev.') plt.xlim([-0.05, 1.05]) plt.ylim([-0.05, 1.05]) plt.xlabel('False Positive Rate') plt.ylabel('True Positive Rate') plt.title('Receiver operating characteristic example') plt.legend(loc="lower right") plt.show() #print("Mutual Information on repaired traning labels", '\n averagee:', mean(rep_MI_inp), "variancee",var(rep_MI_inp)) #print("ATE on repaired traning labels", '\n averagee:', mean(ate0), "variancee", var(ate0)) #print("Mutual Information on test labels", '\n averagee:', mean(MI_inp.values()), "variancee", var(MI_inp.values())) #print("Mutual Information on outcome", '\n avg:', mean(MI_out.values()), "variancee", var(MI_out.values())) print("MI on train: \n") pretty(MI_inp) plt.show() print("MI on test: \n") pretty(MI_test) #print(" Mutual Information on repaired data", rep_MI_inp) print("MI on outcome: \n") pretty(MI_out) plt.show() #print('Coeffient', coef) return aucs def new_test_rep_str(indeps, features, protecteds, Y_features, path1, path2, k=5, droped=False, classifier='log_reg',method='original'): clf=classifier if Y_features[0] in features: features.remove(Y_features[0]) D_features=[] X_features=features tprs = [] aucs = [] mean_fpr = np.linspace(0, 1, 100) for j in range(0, k): print(path2+str(j)+'.csv') cur_train=read_from_csv(path1+str(j)+'.csv') print(path1+str(j)+'.csv') cur_test=read_from_csv(path2+str(j)+'.csv') #atts=cur_train.columns #atts=atts.tolist() #list=[att.replace('_x','').replace('_y','') for att in atts] #atts train_objs_num = len(cur_train) dataset = pd.concat(objs=[cur_train[ D_features+X_features], cur_test[ D_features+X_features]], axis=0) dataset = pd.get_dummies(dataset) dft1 = dataset[:train_objs_num] dft4 = dataset[train_objs_num:] train_X = dft1.values train_y = cur_train[Y_features[0]].values # train_y=train_y.flatten() sc = StandardScaler() X_train = sc.fit_transform(X_train) X_test = sc.transform(X_test) #if droped: # dft4 = pd.get_dummies(cur_test[X_features]) #else: # dft4 = pd.get_dummies(cur_test[ D_features+X_features]) #print(cur_test[D_features+X_features]) dft5 = pd.get_dummies(cur_test[Y_features]) # logit = sm.Logit(train_df['bscore'], train_df['juv_misd_count']) X = dft4.values y = dft5.values y = y.flatten() #print("#####################",len(train_X),len(train_y),type(train_X),type(train_y),train_X,train_y,X.shape) print(X.shape,train_X.shape) #logit = sm.Logit(train_X,cur_train[Y_features[0]]) probas_ = classifier.fit(train_X, train_y).predict_proba(X) scoring = 'accuracy' #result = logit.fit() #print(probas_) y_pred = classifier.predict(X) #predicted = cross_validation.cross_val_predict(logreg, X, y, cv=10) cur_test.insert(0,'y',y_pred) # insert the outcome into the test dataset #cur_test['FP']=cur_test.loc[(cur_test[Y_features] ==1) & (cur_test.y == 1)] cur_test['FP'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 0 and x['y'] == 1 else 0, axis=1) cur_test['FN'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 1 and x['y'] == 0 else 0, axis=1) cur_test['TP'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 1 and x['y'] == 1 else 0, axis=1) cur_test['TN'] = cur_test.apply(lambda x: 1 if x[Y_features[0]] == 0 and x['y'] == 0 else 0, axis=1) i=0 Z=[] fpr, tpr, thresholds = roc_curve(cur_test[Y_features[0]], probas_[:, 1]) tprs.append(interp(mean_fpr, fpr, tpr)) tprs[-1][0] = 0.0 roc_auc = auc(fpr, tpr) aucs.append(roc_auc) plt.plot(fpr, tpr, lw=1, alpha=0.3, label='ROC fold %d (AUC = %0.2f)' % (i, roc_auc)) #df=cur_test[features+['FP','FN','y']] df=cur_test ##FPs1=df[df['y']==1].index #FPs2 = df[df[Y_features] == 0].index #index=intersect1d(FPs1,FPs2) #df[FP]= #M=confusion_matrix(cur_test['y'], cur_test[Y_features]) #print(M) df.to_csv(path1 + '_'+method+'_'+clf.__class__.__name__+'_'+str(j)+'.csv') print(path1 + '_'+method+'_'+clf.__class__.__name__+'_'+str(j)+'.csv') i += 1 plt.plot([0, 1], [0, 1], linestyle='--', lw=2, color='r', label='Luck', alpha=.8) mean_tpr = np.mean(tprs, axis=0) mean_tpr[-1] = 1.0 mean_auc = auc(mean_fpr, mean_tpr) std_auc = np.std(aucs) plt.plot(mean_fpr, mean_tpr, color='b', label=r'Mean ROC (AUC = %0.2f $\pm$ %0.2f)' % (mean_auc, std_auc), lw=2, alpha=.8) std_tpr = np.std(tprs, axis=0) tprs_upper = np.minimum(mean_tpr + std_tpr, 1) tprs_lower = np.maximum(mean_tpr - std_tpr, 0) plt.fill_between(mean_fpr, tprs_lower, tprs_upper, color='grey', alpha=.2, label=r'$\pm$ 1 std. dev.') plt.xlim([-0.05, 1.05]) plt.ylim([-0.05, 1.05]) plt.xlabel('False Positive Rate') plt.ylabel('True Positive Rate') plt.title('Receiver operating characteristic example') plt.legend(loc="lower right") plt.show() return aucs if __name__ == "__main__": #train_df = pd.read_csv("/Users/babakmac/Documents/XDBData/ad_data_prep.csv") #train_df = pd.read_csv("../ data / rep_test_df.csv") train_df = pd.read_csv("/Users/babakmac/Documents/XDBData/cmu_compas.csv") #train_df = pd.read_csv("../data/rep_test_df.csv") #features = ['race', 'age_cat', 'c_charge_degree', 'priors_count', 'is_recid'] features = ['education', 'occupation', 'age', 'race', 'sex', 'income', 'maritalstatus'] D2_features = ['race', 'sex', 'age'] Y2_features = ['income', 'maritalstatus'] X2_features = ['hoursperweek', 'education', 'occupation'] D_features = ['race'] Y_features = ['income'] X_features = ['hoursperweek', 'education', 'occupation','sex', 'age','maritalstatus'] #cross_valid(train_df, features, D_features, Y_features, X_features, path, k=10) method = 'sat' smother=1 size = 5000000 smothers = [1] folds=5 #path1 = path + 'train__rep' + method + '_' + str(size) + '_' + str(smother) + '_' D1_features = ['race', 'sex', 'maritalstatus'] Y1_features = ['income'] X1_features = ['hoursperweek', 'education'] D2_features = ['age'] Y2_features = ['income'] X2_features = ['education', 'occupation', 'hoursperweek'] D1 = [D1_features, Y1_features, X1_features] D2 = [D2_features, Y2_features, X2_features] indeps = [D1, D2] protected=['sex'] new_test_rep_str(indeps, features, protected, Y_features, path1, path2, k=3, classifier=classifier,method='original') #train=read_from_csv('/Users/babakmac/Documents/FairDB/data/randomDAG.csv') #test=read_from_csv('/Users/babakmac/Documents/FairDB/data/randomDAGtest.csv') classification(train, test, ['A', 'B'], ['C'], classifier='log_reg')

38.834783

136

0.54747

4,768

35,728

3.92198

0.082844

0.043048

0.019251

0.013904

0.788449

0.758128

0.732834

0.722781

0.697112

0.678075

0

0.024881

0.275554

35,728

919

137

38.87704

0.697601

0.240596

0

0.65704

0

0.104748

0.035052

0

1

0.01444

false

0

0.070397

0.001805

0.093863

0.15704

0

null

0

1

0

1

0

null

0

4