xszheng2020/the_stack_dedup_python_hits_6 · Datasets at Hugging Face

15ed9202ca042f9e6fb5d67850a74b8dda5d3886

129

py

Python

routes/socketio.py

knowsWhereHisTowelIs/pi-pyth-serv-socketio

91f85439ac7a33dc723e0614d7ebdfd3c8260ad4

[ "MIT" ]

null

routes/socketio.py

knowsWhereHisTowelIs/pi-pyth-serv-socketio

91f85439ac7a33dc723e0614d7ebdfd3c8260ad4

[ "MIT" ]

null

routes/socketio.py

knowsWhereHisTowelIs/pi-pyth-serv-socketio

91f85439ac7a33dc723e0614d7ebdfd3c8260ad4

[ "MIT" ]

null

import include.WebServer as WebServer @WebServer.addRoute('/sio') def socketio(): return WebServer.render('sio-test.html')

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15f16e80187d53d23cebdaa3a32819e1d3d6fccb

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py

Python

t4k/utils/__init__.py

Yoshiki-Takahashi/tools4kaggle

eb2779687867e876f6beec1351140cfec046b152

[ "MIT" ]

null

t4k/utils/__init__.py

Yoshiki-Takahashi/tools4kaggle

eb2779687867e876f6beec1351140cfec046b152

[ "MIT" ]

null

t4k/utils/__init__.py

Yoshiki-Takahashi/tools4kaggle

eb2779687867e876f6beec1351140cfec046b152

[ "MIT" ]

null

from t4k.utils.mem_reduction import to_lowerbit

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c6459eb87134062b5d42f41b462d35c26182e9e1

194

py

Python

x-frame-options/support/redirect.py

meyerweb/wpt

f04261533819893c71289614c03434c06856c13e

[ "BSD-3-Clause" ]

14,668

2015-01-01T01:57:10.000Z

2022-03-31T23:33:32.000Z

x-frame-options/support/redirect.py

meyerweb/wpt

f04261533819893c71289614c03434c06856c13e

[ "BSD-3-Clause" ]

7,642

2018-05-28T09:38:03.000Z

2022-03-31T20:55:48.000Z

x-frame-options/support/redirect.py

meyerweb/wpt

f04261533819893c71289614c03434c06856c13e

[ "BSD-3-Clause" ]

5,941

2015-01-02T11:32:21.000Z

2022-03-31T16:35:46.000Z

def main(request, response): response.status = 302 response.headers.set(b"X-Frame-Options", request.GET.first(b"value")) response.headers.set(b"Location", request.GET.first(b"url"))

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c655e5f115a927c6e006a3f9c3f56c17b8ca6033

131

py

Python

src/constants.py

rahmanmd86/mntn_challenge

3c909d2fbdb2c9304eda7e27198ffdd497f5e1f9

[ "Unlicense" ]

null

src/constants.py

rahmanmd86/mntn_challenge

3c909d2fbdb2c9304eda7e27198ffdd497f5e1f9

[ "Unlicense" ]

null

src/constants.py

rahmanmd86/mntn_challenge

3c909d2fbdb2c9304eda7e27198ffdd497f5e1f9

[ "Unlicense" ]

null

GET_POSTS_RESPONSE_SCHEMA = 'get_posts_response_schema.json' GET_POSTS_ALL_RESPONSE_SCHEMA = 'get_posts_all_response_schema.json'

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c658bc31b2015b7f5456c0db3699c73a495fc15a

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py

Python

Chapter 01/ch1_38.py

bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE

f6a4194684515495d00aa38347a725dd08f39a0c

[ "MIT" ]

null

Chapter 01/ch1_38.py

bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE

f6a4194684515495d00aa38347a725dd08f39a0c

[ "MIT" ]

null

Chapter 01/ch1_38.py

bpbpublications/TEST-YOUR-SKILLS-IN-PYTHON-LANGUAGE

f6a4194684515495d00aa38347a725dd08f39a0c

[ "MIT" ]

null

import sys print(sys.maxsize)

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py

Python

tascii.py

VyomaanDave0711/tascii

0b6c81921f9b642f77af606e0406bcb0e18ba2ce

[ "Apache-2.0" ]

1

2021-09-20T00:21:29.000Z

tascii.py

VyomaanDave0711/tascii

0b6c81921f9b642f77af606e0406bcb0e18ba2ce

[ "Apache-2.0" ]

null

tascii.py

VyomaanDave0711/tascii

0b6c81921f9b642f77af606e0406bcb0e18ba2ce

[ "Apache-2.0" ]

1

2020-10-02T05:19:42.000Z

# ! FUNCTIONS # ! LETTERS a = """ /\\ / \\ / /\\ \\ / ____ \\ /_/ \\_\\ """ b = """ ____ | _ \\ | |_) | | _ < | |_) | |____/ """ c = """ _____ / ____| | | | | | |____ \_____| """ d = """ _____ | __ \ | | | | | | | | | |__| | |_____/ """ e = """ ______ | ____| | |__ | __| | |____ |______| """ f = """ ______ | ____| | |__ | __| | | |_| """ g = """ _____ / ____| | | __ | | |_ | | |__| | \_____| """ h = """ _ _ | | | | | |__| | | __ | | | | | |_| |_| """ i = """ _____ |_ _| | | | | _| |_ |_____| """ j = """ _ | | | | _ | | | |__| | \____/ """ k = """ _ __ | |/ / | ' / | < | . \ |_|\_\ """ l = """ _ | | | | | | | |____ |______| """ m = """ __ __ | \/ | | \ / | | |\/| | | | | | |_| |_| """ n = """ _ _ | \ | | | \| | | . ` | | |\ | |_| \_| """ o = """ ____ / __ \ | | | | | | | | | |__| | \____/ """ p = """ _____ | __ \ | |__) | | ___/ | | |_| """ q = """ ____ / __ \ | | | | | | | | | |__| | \___\_\ """ r = """ _____ | __ \ | |__) | | _ / | | \ \ |_| \_\ """ s = """ _____ / ____| | (___ \___ \ ____) | |_____/ """ t = """ _______ |__ __| | | | | | | |_| """ u = """ _ _ | | | | | | | | | | | | | |__| | \____/ """ v = """ __ __ \ \ / / \ \ / / \ \/ / \ / \/ """ w = """ __ __ \ \ / / \ \ /\ / / \ \/ \/ / \ /\ / \/ \/ """ x = """ __ __ \ \ / / \ V / > < / . \ /_/ \_\ """ y = """ __ __ \ \ / / \ \_/ / \ / | | |_| """ z = """ ______ |___ / / / / / / /__ /_____| """ # ! NUMEBRS 0 = """ ___ / _ \ | | | | | | | | | |_| | \___/ """ 1 = """ __ /_ | | | | | | | |_| """ 2 = """ ___ |__ \ ) | / / / /_ |____| """ 3 = """ ____ |___ \ __) | |__ < ___) | |____/ """ 4 = """ _ _ | || | | || |_ |__ _| | | |_| """ 5 = """ _____ | ____| | |__ |___ \ ___) | |____/ """ 6 = """ __ / / / /_ | '_ \ | (_) | \___/ """ 7 = """ ______ |____ | / / / / / / /_/ """ 8 = """ ___ / _ \ | (_) | > _ < | (_) | \___/ """ 9 = """ ___ / _ \ | (_) | \__, | / / /_/ """

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py

Python

klap4/config/config.py

griffin962/backendbois

ae35fd772d096ce88a8eceb25de81e6bc4ef14e0

[ "MIT" ]

1

2020-02-12T20:45:41.000Z

klap4/config/config.py

griffin962/backendbois

ae35fd772d096ce88a8eceb25de81e6bc4ef14e0

[ "MIT" ]

null

klap4/config/config.py

griffin962/backendbois

ae35fd772d096ce88a8eceb25de81e6bc4ef14e0

[ "MIT" ]

1

2020-04-04T20:02:49.000Z

from datetime import timedelta def config(): return { "clientOrigin": "http://localhost:8080", "accessExpiration": timedelta(hours=6), "refreshExpiration": timedelta(hours=6) }

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d6c1f0dcf2c0a56724de4ab249133a50e75c33a8

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py

Python

tests/test_hf.py

hongzhouye/sigma-SCF

62e2dce538d1e68c4dc3c72fdf27beb1911e544f

[ "BSD-3-Clause" ]

4

2016-07-30T22:02:50.000Z

2018-08-02T23:46:15.000Z

tests/test_hf.py

hongzhouye/sigma-SCF

62e2dce538d1e68c4dc3c72fdf27beb1911e544f

[ "BSD-3-Clause" ]

11

2017-08-04T20:34:04.000Z

2017-08-08T23:07:42.000Z

tests/test_hf.py

hongzhouye/sigma-SCF

62e2dce538d1e68c4dc3c72fdf27beb1911e544f

[ "BSD-3-Clause" ]

null

""" This is a test. """ def test(): pass

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d6e952f0e218b750755111fc87bbaa5aed3e24e0

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py

Python

priceprop/__init__.py

felixpatzelt/priceprop

038832b5e89b8559c6162e39f1b446f4446fe7f2

[ "MIT" ]

17

2018-01-17T13:19:42.000Z

2022-01-25T14:02:10.000Z

priceprop/__init__.py

felixpatzelt/priceprop

038832b5e89b8559c6162e39f1b446f4446fe7f2

[ "MIT" ]

null

priceprop/__init__.py

felixpatzelt/priceprop

038832b5e89b8559c6162e39f1b446f4446fe7f2

[ "MIT" ]

7

2018-07-14T06:17:05.000Z

2021-05-16T13:59:47.000Z

from propagator import * def __reload_submodules__(): reload(propagator)

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py

Python

lang.py

rohan2546/TechArmy

c086157c7db8ec7eb137b81e7854e31f7dfb678b

[ "MIT" ]

1

2020-03-12T06:21:09.000Z

lang.py

rohan2546/TechArmy

c086157c7db8ec7eb137b81e7854e31f7dfb678b

[ "MIT" ]

null

lang.py

rohan2546/TechArmy

c086157c7db8ec7eb137b81e7854e31f7dfb678b

[ "MIT" ]

null

from subprocess import Popen, PIPE import time from multiprocessing.pool import ThreadPool from multiprocessing import Pool import os import signal # Getting JAVA class name def get_class_name(program_path): fptr = open(program_path+'.txt',"r") contents = tuple(fptr) fptr.close() contents =[x.strip() for x in contents] for lines in contents: words = [] if 'class' in lines: words = lines.split(' ') for i in range(len(words)): if words[i] == 'class': return words[i+1] break class languages: def __init__(self, student_id, problem_id, contest_id, time_out): self.student_id = student_id self.problem_id = problem_id self.contest_id = contest_id self.student_path = contest_id+"/temp_"+student_id self.code_path = self.student_path+"/temp" self.time_out = time_out def processes_py(self, p): code_path = self.code_path+".py" pid = os.getpid() fp = open("problems/"+self.problem_id+"/in"+str(p)+".txt", "r") contents = fp.read() fp.close() def signal_handler(signum, frame): raise Exception("Timed out!") timeout = False #signal.signal(signal.SIGALRM, signal_handler) # signal.alarm(self.time_out) # timeout seconds stdout = '' stderr = 'e' #t = 2 # try: start_time = time.time() op = Popen(["timeout", "2s", "python", code_path], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate(contents.encode("utf-8")) t = (time.time() - start_time) stdout = stdout.decode() stderr = stderr.decode() # try: # os.kill(op.pid, signal.SIGKILL) # except: # pass # except Exception as i: # timeout = True # return(stdout, stderr, t, pid) # write code to compare output with test_case_op file and update value of status # fp = open("problems/"+self.problem_id+"/op"+str(p)+".txt", "r") # contents = fp.read() # fp.close() # status = (stdout == contents) return(stdout, stderr, t, pid) def get_number_of_testcases(self): fp = open("problems/"+self.problem_id+"/number_cases.txt", "r") contents = fp.read() return (int(contents)) def py_lang(self): code_path = self.code_path+".py" # to check for compilation error; dont proceed into threading if compilation error #op = Popen(["python", code_path], stdin=PIPE, stdout=PIPE, stderr=PIPE) #stdout, stderr = op.communicate() #stdout = stdout.decode() #stderr = stderr.decode() stderr = '' try: os.kill(op.pid, signal.SIGKILL) except: pass if(stderr == ''): testcases = self.get_number_of_testcases() #p = Pool(processes=testcases) p = ThreadPool() results = p.map(self.processes_py, list(range(testcases))) p.close() # for stdout, stderr, t, pid in results: # try: # os.kill(op.pid, signal.SIGKILL) # except: # pass # p.terminate() # p.join() return results, 1 else: return stderr, 0 def processes_C(self, p): fp = open("problems/"+self.problem_id+"/in"+str(p)+".txt", "r") contents = fp.read() fp.close() # def signal_handler(signum, frame): # raise Exception("Timed out!") # timeout = False # signal.signal(signal.SIGALRM, signal_handler) # signal.alarm(self.time_out) # timeout seconds # try: start_time = time.time() op = Popen(["timeout","2s",self.student_path+"/./a.out"], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate(contents.encode("utf-8")) t = (time.time() - start_time) stdout = stdout.decode() stderr = stderr.decode() # except Exception as i: # timeout = True # return(timeout) # write code to compare output with test_case_op file and update value of status fp = open("problems/"+self.problem_id+"/op"+str(p)+".txt", "r") contents = fp.read() fp.close() status = (stdout == contents) return(stdout, stderr, status, t) def C_lang(self): code_path = self.code_path+".c" def get_number_of_testcases(): fp = open("problems/"+self.problem_id+"/number_cases.txt", "r") contents = fp.read() return (int(contents)) op = Popen(["gcc", "-w", code_path], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate() stdout = stdout.decode() stderr = stderr.decode() if(stderr == ''): testcases = self.get_number_of_testcases() p = ThreadPool() results = p.map(self.processes_C, list(range(testcases))) p.close() return results, 1 else: return stderr, 0 def processes_cpp(self, p): fp = open("problems/"+self.problem_id+"/in"+str(p)+".txt", "r") contents = fp.read() fp.close() # def signal_handler(signum, frame): # raise Exception("Timed out!") # timeout = False # signal.signal(signal.SIGALRM, signal_handler) # signal.alarm(self.time_out) # timeout seconds # try: start_time = time.time() op = Popen(["timeout","2s",self.student_path+"/./a.out"], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate(contents.encode("utf-8")) t = (time.time() - start_time) stdout = stdout.decode() stderr = stderr.decode() # except Exception as i: # timeout = True # return(timeout) # write code to compare output with test_case_op file and update value of status fp = open("problems/"+self.problem_id+"/op"+str(p)+".txt", "r") contents = fp.read() fp.close() status = (stdout == contents) return(stdout, stderr, status, t) def Cpp_lang(self): code_path = self.code_path+".cpp" op = Popen(["g++", "-w", code_path], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate() stdout = stdout.decode() stderr = stderr.decode() if(stderr == ''): testcases = self.get_number_of_testcases() p = ThreadPool() results = p.map(self.processes_cpp, list(range(testcases))) p.close() return results, 1 else: return stderr, 0 def processes_java(self, p): fp = open("problems/"+self.problem_id+"/in"+str(p)+".txt", "r") contents = fp.read() fp.close() def signal_handler(signum, frame): raise Exception("Timed out!") timeout = False signal.signal(signal.SIGALRM, signal_handler) signal.alarm(self.time_out) # timeout seconds # try: start_time = time.time() op = Popen(["timeout","2s","java", self.student_path+"/temp"], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate(contents.encode("utf-8")) t = (time.time() - start_time) stdout = stdout.decode() stderr = stderr.decode() # except Exception as i: # timeout = True # return(timeout) # write code to compare output with test_case_op file and update value of status fp = open("problems/"+self.problem_id+"/op"+str(p)+".txt", "r") contents = fp.read() fp.close() status = (stdout == contents) return(stdout, stderr, status, t) def java_lang(self): new_code_path = get_class_name(self.code_path) code_path = new_code_path+".java" op = Popen(["javac", code_path], stdin=PIPE, stdout=PIPE, stderr=PIPE) stdout, stderr = op.communicate() stdout = stdout.decode() stderr = stderr.decode() if(stderr != ''): testcases = get_number_of_testcases() p = ThreadPool() results = p.map(self.processes_java, list(range(testcases))) p.close() return results, 1 else: return stderr, 0

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py

Python

utokenize/testdata/basic.py

MaxTurchin/pycopy-lib

d7a69fc2a28031e2ca475c29239f715c1809d8cc

[ "PSF-2.0" ]

126

2019-07-19T14:42:41.000Z

2022-03-21T22:22:19.000Z

utokenize/testdata/basic.py

MaxTurchin/pycopy-lib

d7a69fc2a28031e2ca475c29239f715c1809d8cc

[ "PSF-2.0" ]

38

2019-08-28T01:46:31.000Z

2022-03-17T05:46:51.000Z

utokenize/testdata/basic.py

MaxTurchin/pycopy-lib

d7a69fc2a28031e2ca475c29239f715c1809d8cc

[ "PSF-2.0" ]

55

2019-08-02T09:32:33.000Z

2021-12-22T11:25:51.000Z

def foo(): print(1) print(2) foo()

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py

Python

main.py

Itsmemythic/Web-dev

82ad67ea157b42f17dad1ae6403b85bfeeb15c35

[ "Apache-2.0" ]

null

main.py

Itsmemythic/Web-dev

82ad67ea157b42f17dad1ae6403b85bfeeb15c35

[ "Apache-2.0" ]

null

main.py

Itsmemythic/Web-dev

82ad67ea157b42f17dad1ae6403b85bfeeb15c35

[ "Apache-2.0" ]

null

import time import os import random

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031efcd9cfcaabc5f4c77c86e3aa024a7760d477

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py

Python

conan/tools/intel/__init__.py

Wonders11/conan

28ec09f6cbf1d7e27ec27393fd7bbc74891e74a8

[ "MIT" ]

6,205

2015-12-01T13:40:05.000Z

2022-03-31T07:30:25.000Z

conan/tools/intel/__init__.py

Wonders11/conan

28ec09f6cbf1d7e27ec27393fd7bbc74891e74a8

[ "MIT" ]

8,747

2015-12-01T16:28:48.000Z

2022-03-31T23:34:53.000Z

conan/tools/intel/__init__.py

Mattlk13/conan

005fc53485557b0a570bb71670f2ca9c66082165

[ "MIT" ]

961

2015-12-01T16:56:43.000Z

2022-03-31T13:50:52.000Z

from conan.tools.intel.intel_cc import IntelCC

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0325162ac3f7f5c6b275a36da04091463fc4598c

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py

Python

commands/__init__.py

izhx/allennlpadd

0907f1285121c6d02f5aacb326870ddb90342d31

[ "Apache-2.0" ]

null

commands/__init__.py

izhx/allennlpadd

0907f1285121c6d02f5aacb326870ddb90342d31

[ "Apache-2.0" ]

null

commands/__init__.py

izhx/allennlpadd

0907f1285121c6d02f5aacb326870ddb90342d31

[ "Apache-2.0" ]

null

from .tune import tune # noqa

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py

Python

app.py

kabutokungzz/Smartcam

8a031206ac7decc00554ba1f53c2dd2dbbaa0118

[ "MIT" ]

null

app.py

kabutokungzz/Smartcam

8a031206ac7decc00554ba1f53c2dd2dbbaa0118

[ "MIT" ]

null

app.py

kabutokungzz/Smartcam

8a031206ac7decc00554ba1f53c2dd2dbbaa0118

[ "MIT" ]

null

import datetime import main as app app.main()

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6

03519f277b323b1bb86047784d46b5f5c705217c

219

py

Python

api/__init__.py

PeterYang21/plastering

7c7a21b2f18df78a9d8ec29f3d1d9f47d82c658f

[ "MIT" ]

null

api/__init__.py

PeterYang21/plastering

7c7a21b2f18df78a9d8ec29f3d1d9f47d82c658f

[ "MIT" ]

null

api/__init__.py

PeterYang21/plastering

7c7a21b2f18df78a9d8ec29f3d1d9f47d82c658f

[ "MIT" ]

null

from flask import Flask def create_app(): app = Flask(__name__) register_blueprints(app) return app def register_blueprints(app): from api import api_blueprint app.register_blueprint(api_blueprint)

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035b6530b460a3398ba474362472f30bf635c091

76

py

Python

tests/test_attribute/output.py

waadnakhleh/pythonformatter

5f622986aa4e2fcdf03e49041a7ddc14e66d1a2f

[ "MIT" ]

null

tests/test_attribute/output.py

waadnakhleh/pythonformatter

5f622986aa4e2fcdf03e49041a7ddc14e66d1a2f

[ "MIT" ]

19

2020-12-28T17:17:12.000Z

2021-12-22T20:44:42.000Z

tests/test_attribute/output.py

waadnakhleh/pythonformatter

5f622986aa4e2fcdf03e49041a7ddc14e66d1a2f

[ "MIT" ]

1

2021-03-20T17:41:14.000Z

def foo(): print("this is foo") print(foo.__name__, foo.__qualname__)

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6

0373d15edcc321e87f9a20ab0d46f30fdc174fc6

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py

Python

haversine_distance/__init__.py

dkerrgis/HaverRaster

2f4edb6e59ca78526104873074fe1b6dbea58d8e

[ "MIT" ]

null

haversine_distance/__init__.py

dkerrgis/HaverRaster

2f4edb6e59ca78526104873074fe1b6dbea58d8e

[ "MIT" ]

null

haversine_distance/__init__.py

dkerrgis/HaverRaster

2f4edb6e59ca78526104873074fe1b6dbea58d8e

[ "MIT" ]

null

from .haver_raster import * from .utils import * from .distance_to_edge import *

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py

Python

tests/test_data_patterns.py

DeNederlandscheBank/data-patterns

bfef347c7580764eb0f11e5592e5f13343df5c4a

[ "MIT" ]

7

2019-11-08T20:35:12.000Z

2022-02-01T18:53:47.000Z

tests/test_data_patterns.py

DeNederlandscheBank/data-patterns

bfef347c7580764eb0f11e5592e5f13343df5c4a

[ "MIT" ]

1

2021-01-08T16:26:22.000Z

2021-01-17T16:05:10.000Z

tests/test_data_patterns.py

DeNederlandscheBank/data-patterns

bfef347c7580764eb0f11e5592e5f13343df5c4a

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- """Tests for `data_patterns` package.""" import unittest import os from data_patterns import data_patterns import pandas as pd class TestData_patterns(unittest.TestCase): """Tests for `data_patterns` package.""" def test_pattern1(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) pattern = {'name' : 'Pattern 1', 'pattern' : '-->', 'P_columns': ['Type'], 'Q_columns': ['Assets', 'TV-life', 'TV-nonlife', 'Own funds'], 'encode' : {'Assets': 'reported', 'TV-life': 'reported', 'TV-nonlife': 'reported', 'Own funds': 'reported'}} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 0, 'IF ({"Type"} = "life insurer") THEN ({"Assets"} = "reported") & ({"TV-life"} = "reported") & ({"TV-nonlife"} = "not reported") & ({"Own funds"} = "reported")', 5, 0, 1], [1,'Pattern 1', 0, 'IF ({"Type"} = "non-life insurer") THEN ({"Assets"} = "reported") & ({"TV-life"} = "not reported") & ({"TV-nonlife"} = "reported") & ({"Own funds"} = "reported")', 4, 1, 0.8]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(pattern) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 1: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern2(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) pattern = {'name' : 'Pattern 1', 'pattern' : '-->', 'P_columns': ['TV-life', 'Assets'], 'P_values' : [100,0], 'Q_values' : [0,0], 'Q_columns': ['TV-nonlife', 'Own funds'], 'parameters' : {"min_confidence" : 0, "min_support" : 1, 'Q_operators': ['>', '>'], 'P_operators':['<','>'], 'Q_logics':['|'], 'both_ways':False}} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 0, 'IF ({"TV-life"} < 100) & ({"Assets"} > 0) THEN ({"TV-nonlife"} > 0) | ({"Own funds"} > 0)', 4, 0, 1.0]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(pattern) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 2: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern3(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) pattern = {'name' : 'equal values', 'pattern' : '=', 'value' : 0, 'parameters': {"min_confidence": 0.5, "min_support" : 2}} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'equal values', 0, '({"TV-nonlife"} = 0)', 6, 4, .6]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(pattern) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 3: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern4(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) pattern = {'name' : 'Pattern 1', 'pattern' : '-->', 'P_columns': ['TV-life'], 'P_values' : [0], 'Q_columns': ['TV-nonlife'], 'Q_values' : [8800], 'parameters' : {"min_confidence" : 0, "min_support" : 1, 'both_ways':True}} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 0, 'IF ({"TV-life"} = 0) THEN ({"TV-nonlife"} = 8800) AND IF ~({"TV-life"} = 0) THEN ~({"TV-nonlife"} = 8800)', 7, 3, 0.7]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(pattern) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 4: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern5(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) pattern ={'name' : 'sum pattern', 'pattern' : 'sum', 'parameters': {"min_confidence": 0.5, "min_support" : 1, "nonzero" : True }} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'sum pattern', 0, '({"TV-life"} + {"Own funds"} = {"Assets"})', 6, 0, 1.0], [1,'sum pattern', 0, '({"TV-life"} + {"Excess"} = {"Assets"})', 6, 0, 1.0], [2,'sum pattern', 0, '({"TV-nonlife"} + {"Own funds"} = {"Assets"})', 3, 1, 0.75], [3,'sum pattern', 0, '({"TV-nonlife"} + {"Excess"} = {"Assets"})', 3, 1, 0.75]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(pattern) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 5: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern6(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) parameters = {'min_confidence': 0.5,'min_support' : 2} p2 = {'name' : 'Pattern 1', 'expression' : 'IF ({.*TV-life.*} = 0) THEN ({.*TV-nonlife.*} = 8800) AND IF ~({.*TV-life.*} = 0) THEN ~({.*TV-nonlife.*} = 8800)', 'parameters' : parameters } # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 0, 'IF ({"TV-life"} = 0) THEN ({"TV-nonlife"} = 8800) AND IF ~({"TV-life"} = 0) THEN ~({"TV-nonlife"} = 8800)', 7, 3, 0.7]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(p2) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 4: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern7(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) p2 = {'name' : 'Pattern 1', 'expression' : 'IF ({.*Ty.*} = [@]) THEN ({.*.*} = [@])'} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 0, 'IF ({"Type"} = "non-life insurer") THEN ({"TV-life"} = 0)', 4, 1, 0.8], [1,'Pattern 1', 0, 'IF ({"Type"} = "life insurer") THEN ({"TV-nonlife"} = 0)', 5, 0, 1.0], [2,'Pattern 1', 0, 'IF ({"Type"} = "life insurer") THEN ({"Own funds"} = 200)', 4, 1, 0.8], [3,'Pattern 1', 0, 'IF ({"Type"} = "life insurer") THEN ({"Excess"} = 200.0)', 4, 1, 0.8]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(p2) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 7: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern8(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) parameters = {'min_confidence': 0.3,'min_support' : 1, 'percentile' : 90} p2 = {'name' : 'Pattern 1', 'pattern' : 'percentile', 'columns' : [ 'TV-nonlife', 'Own funds'], 'parameters':parameters} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 0, '({"TV-nonlife"} >= 0.0) & ({"TV-nonlife"} <= 6280.0)', 9, 1, 0.9], [1,'Pattern 1', 0, '({"Own funds"} >= 145.0) & ({"Own funds"} <= 755.0)', 8, 2, 0.8]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(p2) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 8: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern9(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'non-life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) p2 = {'name' : 'Pattern 1', 'cluster':'Type', 'pattern' : '='} # Expected output expected = pd.DataFrame(columns = ['index','pattern_id', 'cluster', 'pattern_def', 'support', 'exceptions', 'confidence'], data = [[0,'Pattern 1', 'life insurer', '({"Own funds"} = {"Excess"})', 5,0,1.0], [1,'Pattern 1', 'non-life insurer', '({"Own funds"} = {"Excess"})', 5,0,1.0]]) expected.set_index('index', inplace = True) expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(p2) actual = data_patterns.PatternDataFrame(actual.loc[:, 'pattern_id': 'confidence']) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 9: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern10(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurerx', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) df.set_index('Name', inplace = True) p2 = {'name' : 'Pattern 1', 'expression':'IF {.*TV-l.*} =[@] THEN {.*Typ.*}= [@]'} # Expected output expected = pd.DataFrame(columns = ['Name', 'Type', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 'life insurer', 1000, 800, 0, 200, 200], ['Insurer 2', 'non-life insurer', 4000, 0, 3200, 800, 800], ['Insurer 3', 'non-life insurer', 800, 0, 700, 100, 100], ['Insurer 4', 'life insurer', 2500, 1800, 0, 700, 700], ['Insurer 5', 'non-life insurer', 2100, 0, 2200, 200, 200], ['Insurer 6', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 7', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 8', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 9', 'life insurer', 9000, 8800, 0, 200, 200], ['Insurer 10', 'non-life insurer', 9000, 0, 8800, 200, 199.99]]) expected.set_index('Name', inplace = True) # expected = data_patterns.PatternDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(p2) df_ana = p.analyze() actual = p.correct_data() # Assert self.assertEqual(type(actual[0]), type(expected), "Pattern test 10: types do not match") pd.testing.assert_frame_equal(actual[0], expected) def test_pattern11(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'periode', 'Assets' ], data = [['Insurer 1', 2018, 1000 ], ['Insurer 2', 2018, 4000 ], ['Insurer 1', 2019, 800 ], ['Insurer 2', 2019, 2500]]) miner = data_patterns.PatternMiner(df) df_patterns = miner.convert_columns_to_time('Name','periode') actual = df_patterns.reset_index() # Expected output expected = pd.DataFrame(columns = ['Name', 'Datapoint', '2018', '2019'], data = [['Insurer 1', 'Assets' ,1000 ,800], ['Insurer 2', 'Assets', 4000 ,2500]]) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 11: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern12(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'periode', 'Assets', 'TV-life', 'TV-nonlife' , 'Own funds', 'Excess'], data = [['Insurer 1', 2018, 1000, 800, 0, 200, 200], ['Insurer 2', 2018, 4000, 0, 3200, 800, 800], ['Insurer 1', 2019, 800, 0, 700, 100, 100], ['Insurer 2', 2019, 2500, 1800, 0, 700, 700]]) df['periode'] = pd.to_datetime(df['periode'],format='%Y') miner = data_patterns.PatternMiner(df) df_patterns = miner.convert_to_time(['Name'],'periode') actual = df_patterns.reset_index() # Expected output expected = pd.DataFrame(columns = ['periode', 'Name','Assets (t-1)', 'TV-life (t-1)', 'TV-nonlife (t-1)', 'Own funds (t-1)', 'Excess (t-1)', 'Assets (t)', 'TV-life (t)', 'TV-nonlife (t)', 'Own funds (t)', 'Excess (t)'], data = [['2018 - 2019', 'Insurer 1', 1000 ,800 ,0 ,200 ,200, 800, 0 ,700, 100 ,100], ['2018 - 2019' ,'Insurer 2' ,4000 ,0 ,3200 ,800 ,800 ,2500, 1800, 0 ,700 ,700]]) # Assert self.assertEqual(type(actual), type(expected), "Pattern test 12: types do not match") pd.testing.assert_frame_equal(actual, expected) def test_pattern13(self): """Test of read input date function""" # Input df = pd.DataFrame(columns = ['Name', 'periode', 'Assets' ], data = [['Insurer 1', 2018, 0 ], ['Insurer 2', 2018, 10 ], ['Insurer 1', 2019, 0 ], ['Insurer 2', 2019, 10]]) p2 = {'name' : 'Pattern 1', 'expression':'IF {.*Name.*} =[@] THEN {.*As.*}= [@]'} # Expected output expected = pd.DataFrame(columns = ['index','result_type', 'pattern_id', 'cluster', 'support', 'exceptions', 'confidence', 'pattern_def', 'P values', 'Q values'], data = [[0,True, 'Pattern 1', 0 ,2 ,0, 1.0, 'IF {"Name"} ="Insurer 1" THEN {"Assets"}= 0' ,'Insurer 1', 0], [1,True ,'Pattern 1', 0, 2 ,0 ,1.0, 'IF {"Name"} ="Insurer 2" THEN {"Assets"}= 10' ,'Insurer 2', 10], [2,True ,'Pattern 1', 0 ,2 ,0, 1.0, 'IF {"Name"} ="Insurer 1" THEN {"Assets"}= 0' ,'Insurer 1', 0], [3,True, 'Pattern 1' ,0 ,2, 0, 1.0, 'IF {"Name"} ="Insurer 2" THEN {"Assets"}= 10', 'Insurer 2', 10]]) expected.set_index('index', inplace = True) expected = data_patterns.ResultDataFrame(expected) # Actual output p = data_patterns.PatternMiner(df) actual = p.find(p2) actual = p.analyze() # Assert self.assertEqual(type(actual), type(expected), "Pattern test 9: types do not match") pd.testing.assert_frame_equal(actual, expected)

67.908142

223

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32,528

4.34324

0.0516

0.096774

0.065494

0.058952

0.902023

0.878036

0.869163

0.838183

0.826679

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0.127468

0.440943

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478

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0.048387

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null

0

1

0

null

0

6

3075c21684cca8ce2353c39521986d6f6a14ff36

5,197

py

Python

opendis/misc.py

DMOC-C/DIS-PDU

af5c93b2081298e0c453592f62c8cc9484e3ded0

[ "BSD-2-Clause" ]

null

opendis/misc.py

DMOC-C/DIS-PDU

af5c93b2081298e0c453592f62c8cc9484e3ded0

[ "BSD-2-Clause" ]

null

opendis/misc.py

DMOC-C/DIS-PDU

af5c93b2081298e0c453592f62c8cc9484e3ded0

[ "BSD-2-Clause" ]

null

# Maybe remove these. Not really used anymore. class PduContainer( object ): """Used for XML compatability. A container that holds PDUs""" def __init__(self): """ Initializer for PduContainer""" self.numberOfPdus = 0 """ Number of PDUs in the container list""" self.pdus = [] """ record sets""" def serialize(self, outputStream): """serialize the class """ outputStream.write_int( len(self.pdus)); for anObj in self.pdus: anObj.serialize(outputStream) def parse(self, inputStream): """"Parse a message. This may recursively call embedded objects.""" self.numberOfPdus = inputStream.read_int(); for idx in range(0, self.numberOfPdus): element = null() element.parse(inputStream) self.pdus.append(element) class PduStream( object ): """Non-DIS class, used to describe streams of PDUS when logging data to a SQL database. This is not in the DIS standard but can be helpful when logging to a Hibernate sql database""" def __init__(self): """ Initializer for PduStream""" self.description = [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] """ Longish description of this PDU stream""" self.name = [ 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0] """ short description of this PDU stream""" self.startTime = 0 """ Start time of recording, in Unix time (seconds since epoch)""" self.stopTime = 0 """ stop time of recording, in Unix time (seconds since epoch)""" self.pduCount = 0 """ how many PDUs in this stream""" self.pdusInStream = [] """ variable length list of PDUs""" def serialize(self, outputStream): """serialize the class """ for idx in range(0, 512): outputStream.write_byte( self.description[ idx ] ); for idx in range(0, 256): outputStream.write_byte( self.name[ idx ] ); outputStream.write_long(self.startTime); outputStream.write_long(self.stopTime); outputStream.write_unsigned_int( len(self.pdusInStream)); for anObj in self.pdusInStream: anObj.serialize(outputStream) def parse(self, inputStream): """"Parse a message. This may recursively call embedded objects.""" self.description = [0]*512 for idx in range(0, 512): val = inputStream.read_byte() self.description[ idx ] = val self.name = [0]*256 for idx in range(0, 256): val = inputStream.read_byte() self.name[ idx ] = val self.startTime = inputStream.read_long(); self.stopTime = inputStream.read_long(); self.pduCount = inputStream.read_unsigned_int(); for idx in range(0, self.pduCount): element = null() element.parse(inputStream) self.pdusInStream.append(element)

57.744444

1,565

0.482971

1,100

5,197

2.261818

0.089091

0.615756

0.921222

1.22508

0.604502

0.563505

0.481511

0.428457

0

0.22247

0.309794

5,197

89

1,566

58.393258

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0.125

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null

1

0

1

0

1

0

1

0

null

0

6

062a241ff9c87897b86745d5dfb1554ce9ff90d3

115

py

Python

pesto/backend/utils/utils.py

saromanov/pesto

b14e92ac8295400fb56d84d7d05d5450e7dc7d61

[ "MIT" ]

null

pesto/backend/utils/utils.py

saromanov/pesto

b14e92ac8295400fb56d84d7d05d5450e7dc7d61

[ "MIT" ]

15

2021-01-09T18:54:03.000Z

2022-03-12T00:21:09.000Z

pesto/backend/utils/utils.py

saromanov/pesto

b14e92ac8295400fb56d84d7d05d5450e7dc7d61

[ "MIT" ]

null

import datetime def time_now_formatted(title): return datetime.datetime.now().strftime(f'{title}:%Y:%m:%d:%H')

28.75

67

0.721739

18

115

4.5

0.777778

0

0.086957

115

4

67

28.75

0.771429

0

0.163793

0

1

0.333333

false

0

0.333333

1

0

1

0

null

0

1

0

null

0

1

0

1

0

6

ebec2f6ce6373eb48b860c020ed743f8f695a6f3

31

py

Python

models/__init__.py

alarca94/senti-transfer

da83a072c8d471bc74aa25b237b5e301502db869

[ "MIT" ]

null

models/__init__.py

alarca94/senti-transfer

da83a072c8d471bc74aa25b237b5e301502db869

[ "MIT" ]

null

models/__init__.py

alarca94/senti-transfer

da83a072c8d471bc74aa25b237b5e301502db869

[ "MIT" ]

null

from .transformers import BETO

15.5

30

0.83871

4

31

6.5

1

0

0.129032

31

1

31

0.962963

0

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true

0

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0

1

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1

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null

0

1

0

null

0

1

0

1

0

1

0

6

230fff0372659e7e279ca5a94a8f9d12b57998c6

85

py

Python

warehouse_management/warehouse_management/doctype/warehouse_receipt/warehouse_receipt.py

mohsinalimat/warehouse_management

691e9e465a75cd06f551d802e5c20a8b6b332df4

[ "MIT" ]

2

2021-08-04T07:31:27.000Z

2021-12-27T21:59:50.000Z

warehouse_management/warehouse_management/doctype/warehouse_receipt/warehouse_receipt.py

mohsinalimat/warehouse_management

691e9e465a75cd06f551d802e5c20a8b6b332df4

[ "MIT" ]

null

warehouse_management/warehouse_management/doctype/warehouse_receipt/warehouse_receipt.py

mohsinalimat/warehouse_management

691e9e465a75cd06f551d802e5c20a8b6b332df4

[ "MIT" ]

3

2021-08-04T07:31:28.000Z

2021-11-03T13:41:49.000Z

from frappe.model.document import Document class WarehouseReceipt(Document): pass

14.166667

42

0.823529

10

85

7

0.8

0

0.117647

85

5

43

17

0.933333

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1

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true

0.333333

0

0.666667

0

1

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null

0

1

0

null

0

1

0

1

0

6

235c17dc3c7fd7cced9e87a94f4721f8b8ec9ac7

134

py

Python

AdvancedSimulator/__init__.py

dan1510123/stock-history-simulator

a970531f650513a4c76c250796aeecc4d7e4c39b

[ "MIT" ]

1

2021-12-25T21:06:50.000Z

AdvancedSimulator/__init__.py

dan1510123/stock-history-simulator

a970531f650513a4c76c250796aeecc4d7e4c39b

[ "MIT" ]

null

AdvancedSimulator/__init__.py

dan1510123/stock-history-simulator

a970531f650513a4c76c250796aeecc4d7e4c39b

[ "MIT" ]

null

print(f'Invoking __init__.py for {__name__}') import AdvancedSimulator.SimulatorSetupGUI import AdvancedSimulator.AdvancedSimulatorGUI

44.666667

45

0.880597

13

134

8.461538

0.846154

0.418182

0

0.052239

134

3

46

44.666667

0.866142

0

0.259259

0

1

0

true

0

0.666667

0

0.666667

0.333333

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

88c710e8ffab8672cb0227fd295be88493198e6e

146

py

Python

dvats/all.py

vrodriguezf/deepvats

56f95b7d05e014ac0aefc87fc16627a38d1ebbf9

[ "Apache-2.0" ]

2

2022-02-07T17:48:55.000Z

2022-02-07T17:48:57.000Z

dvats/all.py

pacmel/timecluster_hub

252cc8ef28af50501c6eba2d2c26dd5e8235bed6

[ "Apache-2.0" ]

38

2021-09-24T08:53:58.000Z

2021-11-24T09:54:49.000Z

dvats/all.py

pacmel/timecluster_hub

252cc8ef28af50501c6eba2d2c26dd5e8235bed6

[ "Apache-2.0" ]

null

import dvats from .imports import * from .load import * from .utils import * from .dr import * from .encoder import * from .visualization import *

20.857143

28

0.746575

20

146

5.45

0.45

0.458716

0

0.171233

146

7

28

20.857143

0.900826

0

1

0

true

0

1

0

1

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1

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null

1

0

1

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null

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1

0

1

0

6

88ee5cda71b3b5b1bad30ead900aaa4aa14bf8dd

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py

Python

vae/src/models/__init__.py

ioangatop/GenerativeModels

c6924e91de475be36253f9f20b687d1e1c8b0dde

[ "MIT" ]

4

2019-12-04T06:10:23.000Z

2021-09-14T06:17:24.000Z

vae/src/models/__init__.py

ioangatop/GenerativeModels

c6924e91de475be36253f9f20b687d1e1c8b0dde

[ "MIT" ]

null

vae/src/models/__init__.py

ioangatop/GenerativeModels

c6924e91de475be36253f9f20b687d1e1c8b0dde

[ "MIT" ]

1

2021-09-16T21:10:12.000Z

from .model import VAE

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py

Python

hylium/__init__.py

kpavao84/hylium

8778091d5b8fc0d7819e2237c2bb2f324e3911ec

[ "MIT" ]

1

2021-06-08T22:15:53.000Z

hylium/__init__.py

kpavao84/hylium

8778091d5b8fc0d7819e2237c2bb2f324e3911ec

[ "MIT" ]

1

2021-06-01T22:46:31.000Z

hylium/__init__.py

kwpav/hylium

8778091d5b8fc0d7819e2237c2bb2f324e3911ec

[ "MIT" ]

null

import hy import hylium

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null

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1

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1

0

6

88ffbbd758a3d3a7dc02c68869744837506941dc

20

py

Python

tests/test_cache.py

groutr/conda-tools

f421fd324f306a713c0cb1a3845306758ff981f4

[ "BSD-3-Clause" ]

11

2016-07-07T00:27:01.000Z

2019-12-02T08:47:16.000Z

tests/test_cache.py

groutr/conda-tools

f421fd324f306a713c0cb1a3845306758ff981f4

[ "BSD-3-Clause" ]

8

2016-07-15T14:59:27.000Z

2019-07-03T18:05:34.000Z

tests/test_cache.py

groutr/conda-tools

f421fd324f306a713c0cb1a3845306758ff981f4

[ "BSD-3-Clause" ]

2

2016-07-13T22:24:51.000Z

2016-11-16T18:03:46.000Z

from .. import cache

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cc35208e2e1aed04cfc61463ff4a100140dc637a

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py

Python

src/python/packages/wgne/__init__.py

susburrows/uvcmetrics

5a3c1266f3e5e97398a7671b01fa2816fb307c38

[ "X11", "MIT" ]

null

src/python/packages/wgne/__init__.py

susburrows/uvcmetrics

5a3c1266f3e5e97398a7671b01fa2816fb307c38

[ "X11", "MIT" ]

null

src/python/packages/wgne/__init__.py

susburrows/uvcmetrics

5a3c1266f3e5e97398a7671b01fa2816fb307c38

[ "X11", "MIT" ]

null

import io from mean_climate_metrics_calculations import compute_metrics import rms_xyt,cor_xyt,bias,rms_xy,annual_mean import git pass

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cc5f65d19406e9854c53137ff9185eb7ea70ba1c

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py

Python

pyinjective/proto/exchange/injective_spot_exchange_rpc_pb2.py

CtheSky/sdk-python

c1b1ae931f4970832466a004eb193027bdc1dea5

[ "Apache-2.0" ]

10

2021-09-07T08:03:52.000Z

2022-03-08T08:39:30.000Z

pyinjective/proto/exchange/injective_spot_exchange_rpc_pb2.py

CtheSky/sdk-python

c1b1ae931f4970832466a004eb193027bdc1dea5

[ "Apache-2.0" ]

39

2021-08-19T20:09:35.000Z

2022-03-22T19:51:59.000Z

pyinjective/proto/exchange/injective_spot_exchange_rpc_pb2.py

CtheSky/sdk-python

c1b1ae931f4970832466a004eb193027bdc1dea5

[ "Apache-2.0" ]

5

2021-11-02T16:23:48.000Z

2022-01-20T22:30:05.000Z

# -*- coding: utf-8 -*- # Generated by the protocol buffer compiler. DO NOT EDIT! # source: exchange/injective_spot_exchange_rpc.proto """Generated protocol buffer code.""" from google.protobuf import descriptor as _descriptor from google.protobuf import message as _message from google.protobuf import reflection as _reflection from google.protobuf import symbol_database as _symbol_database # @@protoc_insertion_point(imports) _sym_db = _symbol_database.Default() DESCRIPTOR = _descriptor.FileDescriptor( name='exchange/injective_spot_exchange_rpc.proto', package='injective_spot_exchange_rpc', syntax='proto3', serialized_options=b'Z\036/injective_spot_exchange_rpcpb', create_key=_descriptor._internal_create_key, serialized_pb=b'\n*exchange/injective_spot_exchange_rpc.proto\x12\x1binjective_spot_exchange_rpc\"P\n\x0eMarketsRequest\x12\x15\n\rmarket_status\x18\x01 \x01(\t\x12\x12\n\nbase_denom\x18\x02 \x01(\t\x12\x13\n\x0bquote_denom\x18\x03 \x01(\t\"O\n\x0fMarketsResponse\x12<\n\x07markets\x18\x01 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Z\x1e/injective_spot_exchange_rpcpbb\x06proto3' ) _MARKETSREQUEST = _descriptor.Descriptor( name='MarketsRequest', full_name='injective_spot_exchange_rpc.MarketsRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_status', full_name='injective_spot_exchange_rpc.MarketsRequest.market_status', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='base_denom', full_name='injective_spot_exchange_rpc.MarketsRequest.base_denom', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quote_denom', full_name='injective_spot_exchange_rpc.MarketsRequest.quote_denom', index=2, number=3, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=75, serialized_end=155, ) _MARKETSRESPONSE = _descriptor.Descriptor( name='MarketsResponse', full_name='injective_spot_exchange_rpc.MarketsResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='markets', full_name='injective_spot_exchange_rpc.MarketsResponse.markets', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=157, serialized_end=236, ) _SPOTMARKETINFO = _descriptor.Descriptor( name='SpotMarketInfo', full_name='injective_spot_exchange_rpc.SpotMarketInfo', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.SpotMarketInfo.market_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='market_status', full_name='injective_spot_exchange_rpc.SpotMarketInfo.market_status', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='ticker', full_name='injective_spot_exchange_rpc.SpotMarketInfo.ticker', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='base_denom', full_name='injective_spot_exchange_rpc.SpotMarketInfo.base_denom', index=3, number=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='base_token_meta', full_name='injective_spot_exchange_rpc.SpotMarketInfo.base_token_meta', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quote_denom', full_name='injective_spot_exchange_rpc.SpotMarketInfo.quote_denom', index=5, number=6, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quote_token_meta', full_name='injective_spot_exchange_rpc.SpotMarketInfo.quote_token_meta', index=6, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='maker_fee_rate', full_name='injective_spot_exchange_rpc.SpotMarketInfo.maker_fee_rate', index=7, number=8, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='taker_fee_rate', full_name='injective_spot_exchange_rpc.SpotMarketInfo.taker_fee_rate', index=8, number=9, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='service_provider_fee', full_name='injective_spot_exchange_rpc.SpotMarketInfo.service_provider_fee', index=9, number=10, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='min_price_tick_size', full_name='injective_spot_exchange_rpc.SpotMarketInfo.min_price_tick_size', index=10, number=11, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='min_quantity_tick_size', full_name='injective_spot_exchange_rpc.SpotMarketInfo.min_quantity_tick_size', index=11, number=12, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=239, serialized_end=624, ) _TOKENMETA = _descriptor.Descriptor( name='TokenMeta', full_name='injective_spot_exchange_rpc.TokenMeta', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='name', full_name='injective_spot_exchange_rpc.TokenMeta.name', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='address', full_name='injective_spot_exchange_rpc.TokenMeta.address', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='symbol', full_name='injective_spot_exchange_rpc.TokenMeta.symbol', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='logo', full_name='injective_spot_exchange_rpc.TokenMeta.logo', index=3, number=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='decimals', full_name='injective_spot_exchange_rpc.TokenMeta.decimals', index=4, number=5, type=17, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='updated_at', full_name='injective_spot_exchange_rpc.TokenMeta.updated_at', index=5, number=6, type=18, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=626, serialized_end=736, ) _MARKETREQUEST = _descriptor.Descriptor( name='MarketRequest', full_name='injective_spot_exchange_rpc.MarketRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.MarketRequest.market_id', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=738, serialized_end=772, ) _MARKETRESPONSE = _descriptor.Descriptor( name='MarketResponse', full_name='injective_spot_exchange_rpc.MarketResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market', full_name='injective_spot_exchange_rpc.MarketResponse.market', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=774, serialized_end=851, ) _STREAMMARKETSREQUEST = _descriptor.Descriptor( name='StreamMarketsRequest', full_name='injective_spot_exchange_rpc.StreamMarketsRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_ids', full_name='injective_spot_exchange_rpc.StreamMarketsRequest.market_ids', index=0, number=1, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=853, serialized_end=895, ) _STREAMMARKETSRESPONSE = _descriptor.Descriptor( name='StreamMarketsResponse', full_name='injective_spot_exchange_rpc.StreamMarketsResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market', full_name='injective_spot_exchange_rpc.StreamMarketsResponse.market', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='operation_type', full_name='injective_spot_exchange_rpc.StreamMarketsResponse.operation_type', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='injective_spot_exchange_rpc.StreamMarketsResponse.timestamp', index=2, number=3, type=18, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=897, serialized_end=1024, ) _ORDERBOOKREQUEST = _descriptor.Descriptor( name='OrderbookRequest', full_name='injective_spot_exchange_rpc.OrderbookRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.OrderbookRequest.market_id', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1026, serialized_end=1063, ) _ORDERBOOKRESPONSE = _descriptor.Descriptor( name='OrderbookResponse', full_name='injective_spot_exchange_rpc.OrderbookResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='orderbook', full_name='injective_spot_exchange_rpc.OrderbookResponse.orderbook', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1065, serialized_end=1152, ) _SPOTLIMITORDERBOOK = _descriptor.Descriptor( name='SpotLimitOrderbook', full_name='injective_spot_exchange_rpc.SpotLimitOrderbook', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='buys', full_name='injective_spot_exchange_rpc.SpotLimitOrderbook.buys', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='sells', full_name='injective_spot_exchange_rpc.SpotLimitOrderbook.sells', index=1, number=2, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1155, serialized_end=1286, ) _PRICELEVEL = _descriptor.Descriptor( name='PriceLevel', full_name='injective_spot_exchange_rpc.PriceLevel', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='price', full_name='injective_spot_exchange_rpc.PriceLevel.price', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quantity', full_name='injective_spot_exchange_rpc.PriceLevel.quantity', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='injective_spot_exchange_rpc.PriceLevel.timestamp', index=2, number=3, type=18, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1288, serialized_end=1352, ) _STREAMORDERBOOKREQUEST = _descriptor.Descriptor( name='StreamOrderbookRequest', full_name='injective_spot_exchange_rpc.StreamOrderbookRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_ids', full_name='injective_spot_exchange_rpc.StreamOrderbookRequest.market_ids', index=0, number=1, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1354, serialized_end=1398, ) _STREAMORDERBOOKRESPONSE = _descriptor.Descriptor( name='StreamOrderbookResponse', full_name='injective_spot_exchange_rpc.StreamOrderbookResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='orderbook', full_name='injective_spot_exchange_rpc.StreamOrderbookResponse.orderbook', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='operation_type', full_name='injective_spot_exchange_rpc.StreamOrderbookResponse.operation_type', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='injective_spot_exchange_rpc.StreamOrderbookResponse.timestamp', index=2, number=3, type=18, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.StreamOrderbookResponse.market_id', index=3, number=4, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1401, serialized_end=1556, ) _ORDERSREQUEST = _descriptor.Descriptor( name='OrdersRequest', full_name='injective_spot_exchange_rpc.OrdersRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.OrdersRequest.market_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='order_side', full_name='injective_spot_exchange_rpc.OrdersRequest.order_side', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.OrdersRequest.subaccount_id', index=2, number=3, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1558, serialized_end=1635, ) _ORDERSRESPONSE = _descriptor.Descriptor( name='OrdersResponse', full_name='injective_spot_exchange_rpc.OrdersResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='orders', full_name='injective_spot_exchange_rpc.OrdersResponse.orders', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1637, serialized_end=1714, ) _SPOTLIMITORDER = _descriptor.Descriptor( name='SpotLimitOrder', full_name='injective_spot_exchange_rpc.SpotLimitOrder', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='order_hash', full_name='injective_spot_exchange_rpc.SpotLimitOrder.order_hash', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='order_side', full_name='injective_spot_exchange_rpc.SpotLimitOrder.order_side', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.SpotLimitOrder.market_id', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.SpotLimitOrder.subaccount_id', index=3, number=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='price', full_name='injective_spot_exchange_rpc.SpotLimitOrder.price', index=4, number=5, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='quantity', full_name='injective_spot_exchange_rpc.SpotLimitOrder.quantity', index=5, number=6, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='unfilled_quantity', full_name='injective_spot_exchange_rpc.SpotLimitOrder.unfilled_quantity', index=6, number=7, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='trigger_price', full_name='injective_spot_exchange_rpc.SpotLimitOrder.trigger_price', index=7, number=8, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='fee_recipient', full_name='injective_spot_exchange_rpc.SpotLimitOrder.fee_recipient', index=8, number=9, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='state', full_name='injective_spot_exchange_rpc.SpotLimitOrder.state', index=9, number=10, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='created_at', full_name='injective_spot_exchange_rpc.SpotLimitOrder.created_at', index=10, number=11, type=18, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='updated_at', full_name='injective_spot_exchange_rpc.SpotLimitOrder.updated_at', index=11, number=12, type=18, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1717, serialized_end=1976, ) _STREAMORDERSREQUEST = _descriptor.Descriptor( name='StreamOrdersRequest', full_name='injective_spot_exchange_rpc.StreamOrdersRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.StreamOrdersRequest.market_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='order_side', full_name='injective_spot_exchange_rpc.StreamOrdersRequest.order_side', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.StreamOrdersRequest.subaccount_id', index=2, number=3, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=1978, serialized_end=2061, ) _STREAMORDERSRESPONSE = _descriptor.Descriptor( name='StreamOrdersResponse', full_name='injective_spot_exchange_rpc.StreamOrdersResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='order', full_name='injective_spot_exchange_rpc.StreamOrdersResponse.order', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='operation_type', full_name='injective_spot_exchange_rpc.StreamOrdersResponse.operation_type', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='injective_spot_exchange_rpc.StreamOrdersResponse.timestamp', index=2, number=3, type=18, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2063, serialized_end=2188, ) _TRADESREQUEST = _descriptor.Descriptor( name='TradesRequest', full_name='injective_spot_exchange_rpc.TradesRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.TradesRequest.market_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='execution_side', full_name='injective_spot_exchange_rpc.TradesRequest.execution_side', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='direction', full_name='injective_spot_exchange_rpc.TradesRequest.direction', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.TradesRequest.subaccount_id', index=3, number=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='skip', full_name='injective_spot_exchange_rpc.TradesRequest.skip', index=4, number=5, type=4, cpp_type=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='limit', full_name='injective_spot_exchange_rpc.TradesRequest.limit', index=5, number=6, type=17, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2191, serialized_end=2320, ) _TRADESRESPONSE = _descriptor.Descriptor( name='TradesResponse', full_name='injective_spot_exchange_rpc.TradesResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='trades', full_name='injective_spot_exchange_rpc.TradesResponse.trades', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2322, serialized_end=2394, ) _SPOTTRADE = _descriptor.Descriptor( name='SpotTrade', full_name='injective_spot_exchange_rpc.SpotTrade', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='order_hash', full_name='injective_spot_exchange_rpc.SpotTrade.order_hash', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.SpotTrade.subaccount_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.SpotTrade.market_id', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='trade_execution_type', full_name='injective_spot_exchange_rpc.SpotTrade.trade_execution_type', index=3, number=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='trade_direction', full_name='injective_spot_exchange_rpc.SpotTrade.trade_direction', index=4, number=5, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='price', full_name='injective_spot_exchange_rpc.SpotTrade.price', index=5, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='fee', full_name='injective_spot_exchange_rpc.SpotTrade.fee', index=6, number=7, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='executed_at', full_name='injective_spot_exchange_rpc.SpotTrade.executed_at', index=7, number=8, type=18, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='fee_recipient', full_name='injective_spot_exchange_rpc.SpotTrade.fee_recipient', index=8, number=9, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2397, serialized_end=2638, ) _STREAMTRADESREQUEST = _descriptor.Descriptor( name='StreamTradesRequest', full_name='injective_spot_exchange_rpc.StreamTradesRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.StreamTradesRequest.market_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='execution_side', full_name='injective_spot_exchange_rpc.StreamTradesRequest.execution_side', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='direction', full_name='injective_spot_exchange_rpc.StreamTradesRequest.direction', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.StreamTradesRequest.subaccount_id', index=3, number=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='skip', full_name='injective_spot_exchange_rpc.StreamTradesRequest.skip', index=4, number=5, type=4, cpp_type=4, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='limit', full_name='injective_spot_exchange_rpc.StreamTradesRequest.limit', index=5, number=6, type=17, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2641, serialized_end=2776, ) _STREAMTRADESRESPONSE = _descriptor.Descriptor( name='StreamTradesResponse', full_name='injective_spot_exchange_rpc.StreamTradesResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='trade', full_name='injective_spot_exchange_rpc.StreamTradesResponse.trade', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='operation_type', full_name='injective_spot_exchange_rpc.StreamTradesResponse.operation_type', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='timestamp', full_name='injective_spot_exchange_rpc.StreamTradesResponse.timestamp', index=2, number=3, type=18, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2778, serialized_end=2898, ) _SUBACCOUNTORDERSLISTREQUEST = _descriptor.Descriptor( name='SubaccountOrdersListRequest', full_name='injective_spot_exchange_rpc.SubaccountOrdersListRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.SubaccountOrdersListRequest.subaccount_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.SubaccountOrdersListRequest.market_id', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2900, serialized_end=2971, ) _SUBACCOUNTORDERSLISTRESPONSE = _descriptor.Descriptor( name='SubaccountOrdersListResponse', full_name='injective_spot_exchange_rpc.SubaccountOrdersListResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='orders', full_name='injective_spot_exchange_rpc.SubaccountOrdersListResponse.orders', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=2973, serialized_end=3064, ) _SUBACCOUNTTRADESLISTREQUEST = _descriptor.Descriptor( name='SubaccountTradesListRequest', full_name='injective_spot_exchange_rpc.SubaccountTradesListRequest', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='subaccount_id', full_name='injective_spot_exchange_rpc.SubaccountTradesListRequest.subaccount_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='market_id', full_name='injective_spot_exchange_rpc.SubaccountTradesListRequest.market_id', 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='execution_type', full_name='injective_spot_exchange_rpc.SubaccountTradesListRequest.execution_type', index=2, number=3, 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, create_key=_descriptor._internal_create_key), _descriptor.FieldDescriptor( name='direction', full_name='injective_spot_exchange_rpc.SubaccountTradesListRequest.direction', index=3, number=4, 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3066, serialized_end=3180, ) _SUBACCOUNTTRADESLISTRESPONSE = _descriptor.Descriptor( name='SubaccountTradesListResponse', full_name='injective_spot_exchange_rpc.SubaccountTradesListResponse', filename=None, file=DESCRIPTOR, containing_type=None, create_key=_descriptor._internal_create_key, fields=[ _descriptor.FieldDescriptor( name='trades', full_name='injective_spot_exchange_rpc.SubaccountTradesListResponse.trades', 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, create_key=_descriptor._internal_create_key), ], extensions=[ ], nested_types=[], enum_types=[ ], serialized_options=None, is_extendable=False, syntax='proto3', extension_ranges=[], oneofs=[ ], serialized_start=3182, serialized_end=3268, ) _MARKETSRESPONSE.fields_by_name['markets'].message_type = _SPOTMARKETINFO _SPOTMARKETINFO.fields_by_name['base_token_meta'].message_type = _TOKENMETA _SPOTMARKETINFO.fields_by_name['quote_token_meta'].message_type = _TOKENMETA _MARKETRESPONSE.fields_by_name['market'].message_type = _SPOTMARKETINFO _STREAMMARKETSRESPONSE.fields_by_name['market'].message_type = _SPOTMARKETINFO _ORDERBOOKRESPONSE.fields_by_name['orderbook'].message_type = _SPOTLIMITORDERBOOK _SPOTLIMITORDERBOOK.fields_by_name['buys'].message_type = _PRICELEVEL _SPOTLIMITORDERBOOK.fields_by_name['sells'].message_type = _PRICELEVEL _STREAMORDERBOOKRESPONSE.fields_by_name['orderbook'].message_type = _SPOTLIMITORDERBOOK _ORDERSRESPONSE.fields_by_name['orders'].message_type = _SPOTLIMITORDER _STREAMORDERSRESPONSE.fields_by_name['order'].message_type = _SPOTLIMITORDER _TRADESRESPONSE.fields_by_name['trades'].message_type = _SPOTTRADE _SPOTTRADE.fields_by_name['price'].message_type = _PRICELEVEL _STREAMTRADESRESPONSE.fields_by_name['trade'].message_type = _SPOTTRADE _SUBACCOUNTORDERSLISTRESPONSE.fields_by_name['orders'].message_type = _SPOTLIMITORDER _SUBACCOUNTTRADESLISTRESPONSE.fields_by_name['trades'].message_type = _SPOTTRADE DESCRIPTOR.message_types_by_name['MarketsRequest'] = _MARKETSREQUEST DESCRIPTOR.message_types_by_name['MarketsResponse'] = _MARKETSRESPONSE DESCRIPTOR.message_types_by_name['SpotMarketInfo'] = _SPOTMARKETINFO DESCRIPTOR.message_types_by_name['TokenMeta'] = _TOKENMETA DESCRIPTOR.message_types_by_name['MarketRequest'] = _MARKETREQUEST DESCRIPTOR.message_types_by_name['MarketResponse'] = _MARKETRESPONSE DESCRIPTOR.message_types_by_name['StreamMarketsRequest'] = _STREAMMARKETSREQUEST DESCRIPTOR.message_types_by_name['StreamMarketsResponse'] = _STREAMMARKETSRESPONSE DESCRIPTOR.message_types_by_name['OrderbookRequest'] = _ORDERBOOKREQUEST DESCRIPTOR.message_types_by_name['OrderbookResponse'] = _ORDERBOOKRESPONSE DESCRIPTOR.message_types_by_name['SpotLimitOrderbook'] = _SPOTLIMITORDERBOOK DESCRIPTOR.message_types_by_name['PriceLevel'] = _PRICELEVEL DESCRIPTOR.message_types_by_name['StreamOrderbookRequest'] = _STREAMORDERBOOKREQUEST DESCRIPTOR.message_types_by_name['StreamOrderbookResponse'] = _STREAMORDERBOOKRESPONSE DESCRIPTOR.message_types_by_name['OrdersRequest'] = _ORDERSREQUEST DESCRIPTOR.message_types_by_name['OrdersResponse'] = _ORDERSRESPONSE DESCRIPTOR.message_types_by_name['SpotLimitOrder'] = _SPOTLIMITORDER DESCRIPTOR.message_types_by_name['StreamOrdersRequest'] = _STREAMORDERSREQUEST DESCRIPTOR.message_types_by_name['StreamOrdersResponse'] = _STREAMORDERSRESPONSE DESCRIPTOR.message_types_by_name['TradesRequest'] = _TRADESREQUEST DESCRIPTOR.message_types_by_name['TradesResponse'] = _TRADESRESPONSE DESCRIPTOR.message_types_by_name['SpotTrade'] = _SPOTTRADE DESCRIPTOR.message_types_by_name['StreamTradesRequest'] = _STREAMTRADESREQUEST DESCRIPTOR.message_types_by_name['StreamTradesResponse'] = _STREAMTRADESRESPONSE DESCRIPTOR.message_types_by_name['SubaccountOrdersListRequest'] = _SUBACCOUNTORDERSLISTREQUEST DESCRIPTOR.message_types_by_name['SubaccountOrdersListResponse'] = _SUBACCOUNTORDERSLISTRESPONSE DESCRIPTOR.message_types_by_name['SubaccountTradesListRequest'] = _SUBACCOUNTTRADESLISTREQUEST DESCRIPTOR.message_types_by_name['SubaccountTradesListResponse'] = _SUBACCOUNTTRADESLISTRESPONSE _sym_db.RegisterFileDescriptor(DESCRIPTOR) MarketsRequest = _reflection.GeneratedProtocolMessageType('MarketsRequest', (_message.Message,), { 'DESCRIPTOR' : _MARKETSREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.MarketsRequest) }) _sym_db.RegisterMessage(MarketsRequest) MarketsResponse = _reflection.GeneratedProtocolMessageType('MarketsResponse', (_message.Message,), { 'DESCRIPTOR' : _MARKETSRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.MarketsResponse) }) _sym_db.RegisterMessage(MarketsResponse) SpotMarketInfo = _reflection.GeneratedProtocolMessageType('SpotMarketInfo', (_message.Message,), { 'DESCRIPTOR' : _SPOTMARKETINFO, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SpotMarketInfo) }) _sym_db.RegisterMessage(SpotMarketInfo) TokenMeta = _reflection.GeneratedProtocolMessageType('TokenMeta', (_message.Message,), { 'DESCRIPTOR' : _TOKENMETA, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.TokenMeta) }) _sym_db.RegisterMessage(TokenMeta) MarketRequest = _reflection.GeneratedProtocolMessageType('MarketRequest', (_message.Message,), { 'DESCRIPTOR' : _MARKETREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.MarketRequest) }) _sym_db.RegisterMessage(MarketRequest) MarketResponse = _reflection.GeneratedProtocolMessageType('MarketResponse', (_message.Message,), { 'DESCRIPTOR' : _MARKETRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.MarketResponse) }) _sym_db.RegisterMessage(MarketResponse) StreamMarketsRequest = _reflection.GeneratedProtocolMessageType('StreamMarketsRequest', (_message.Message,), { 'DESCRIPTOR' : _STREAMMARKETSREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamMarketsRequest) }) _sym_db.RegisterMessage(StreamMarketsRequest) StreamMarketsResponse = _reflection.GeneratedProtocolMessageType('StreamMarketsResponse', (_message.Message,), { 'DESCRIPTOR' : _STREAMMARKETSRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamMarketsResponse) }) _sym_db.RegisterMessage(StreamMarketsResponse) OrderbookRequest = _reflection.GeneratedProtocolMessageType('OrderbookRequest', (_message.Message,), { 'DESCRIPTOR' : _ORDERBOOKREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.OrderbookRequest) }) _sym_db.RegisterMessage(OrderbookRequest) OrderbookResponse = _reflection.GeneratedProtocolMessageType('OrderbookResponse', (_message.Message,), { 'DESCRIPTOR' : _ORDERBOOKRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.OrderbookResponse) }) _sym_db.RegisterMessage(OrderbookResponse) SpotLimitOrderbook = _reflection.GeneratedProtocolMessageType('SpotLimitOrderbook', (_message.Message,), { 'DESCRIPTOR' : _SPOTLIMITORDERBOOK, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SpotLimitOrderbook) }) _sym_db.RegisterMessage(SpotLimitOrderbook) PriceLevel = _reflection.GeneratedProtocolMessageType('PriceLevel', (_message.Message,), { 'DESCRIPTOR' : _PRICELEVEL, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.PriceLevel) }) _sym_db.RegisterMessage(PriceLevel) StreamOrderbookRequest = _reflection.GeneratedProtocolMessageType('StreamOrderbookRequest', (_message.Message,), { 'DESCRIPTOR' : _STREAMORDERBOOKREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamOrderbookRequest) }) _sym_db.RegisterMessage(StreamOrderbookRequest) StreamOrderbookResponse = _reflection.GeneratedProtocolMessageType('StreamOrderbookResponse', (_message.Message,), { 'DESCRIPTOR' : _STREAMORDERBOOKRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamOrderbookResponse) }) _sym_db.RegisterMessage(StreamOrderbookResponse) OrdersRequest = _reflection.GeneratedProtocolMessageType('OrdersRequest', (_message.Message,), { 'DESCRIPTOR' : _ORDERSREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.OrdersRequest) }) _sym_db.RegisterMessage(OrdersRequest) OrdersResponse = _reflection.GeneratedProtocolMessageType('OrdersResponse', (_message.Message,), { 'DESCRIPTOR' : _ORDERSRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.OrdersResponse) }) _sym_db.RegisterMessage(OrdersResponse) SpotLimitOrder = _reflection.GeneratedProtocolMessageType('SpotLimitOrder', (_message.Message,), { 'DESCRIPTOR' : _SPOTLIMITORDER, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SpotLimitOrder) }) _sym_db.RegisterMessage(SpotLimitOrder) StreamOrdersRequest = _reflection.GeneratedProtocolMessageType('StreamOrdersRequest', (_message.Message,), { 'DESCRIPTOR' : _STREAMORDERSREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamOrdersRequest) }) _sym_db.RegisterMessage(StreamOrdersRequest) StreamOrdersResponse = _reflection.GeneratedProtocolMessageType('StreamOrdersResponse', (_message.Message,), { 'DESCRIPTOR' : _STREAMORDERSRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamOrdersResponse) }) _sym_db.RegisterMessage(StreamOrdersResponse) TradesRequest = _reflection.GeneratedProtocolMessageType('TradesRequest', (_message.Message,), { 'DESCRIPTOR' : _TRADESREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.TradesRequest) }) _sym_db.RegisterMessage(TradesRequest) TradesResponse = _reflection.GeneratedProtocolMessageType('TradesResponse', (_message.Message,), { 'DESCRIPTOR' : _TRADESRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.TradesResponse) }) _sym_db.RegisterMessage(TradesResponse) SpotTrade = _reflection.GeneratedProtocolMessageType('SpotTrade', (_message.Message,), { 'DESCRIPTOR' : _SPOTTRADE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SpotTrade) }) _sym_db.RegisterMessage(SpotTrade) StreamTradesRequest = _reflection.GeneratedProtocolMessageType('StreamTradesRequest', (_message.Message,), { 'DESCRIPTOR' : _STREAMTRADESREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamTradesRequest) }) _sym_db.RegisterMessage(StreamTradesRequest) StreamTradesResponse = _reflection.GeneratedProtocolMessageType('StreamTradesResponse', (_message.Message,), { 'DESCRIPTOR' : _STREAMTRADESRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.StreamTradesResponse) }) _sym_db.RegisterMessage(StreamTradesResponse) SubaccountOrdersListRequest = _reflection.GeneratedProtocolMessageType('SubaccountOrdersListRequest', (_message.Message,), { 'DESCRIPTOR' : _SUBACCOUNTORDERSLISTREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SubaccountOrdersListRequest) }) _sym_db.RegisterMessage(SubaccountOrdersListRequest) SubaccountOrdersListResponse = _reflection.GeneratedProtocolMessageType('SubaccountOrdersListResponse', (_message.Message,), { 'DESCRIPTOR' : _SUBACCOUNTORDERSLISTRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SubaccountOrdersListResponse) }) _sym_db.RegisterMessage(SubaccountOrdersListResponse) SubaccountTradesListRequest = _reflection.GeneratedProtocolMessageType('SubaccountTradesListRequest', (_message.Message,), { 'DESCRIPTOR' : _SUBACCOUNTTRADESLISTREQUEST, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SubaccountTradesListRequest) }) _sym_db.RegisterMessage(SubaccountTradesListRequest) SubaccountTradesListResponse = _reflection.GeneratedProtocolMessageType('SubaccountTradesListResponse', (_message.Message,), { 'DESCRIPTOR' : _SUBACCOUNTTRADESLISTRESPONSE, '__module__' : 'exchange.injective_spot_exchange_rpc_pb2' # @@protoc_insertion_point(class_scope:injective_spot_exchange_rpc.SubaccountTradesListResponse) }) _sym_db.RegisterMessage(SubaccountTradesListResponse) DESCRIPTOR._options = None _INJECTIVESPOTEXCHANGERPC = _descriptor.ServiceDescriptor( name='InjectiveSpotExchangeRPC', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC', file=DESCRIPTOR, index=0, serialized_options=None, create_key=_descriptor._internal_create_key, serialized_start=3271, serialized_end=4576, methods=[ _descriptor.MethodDescriptor( name='Markets', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.Markets', index=0, containing_service=None, input_type=_MARKETSREQUEST, output_type=_MARKETSRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='Market', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.Market', index=1, containing_service=None, input_type=_MARKETREQUEST, output_type=_MARKETRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='StreamMarkets', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.StreamMarkets', index=2, containing_service=None, input_type=_STREAMMARKETSREQUEST, output_type=_STREAMMARKETSRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='Orderbook', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.Orderbook', index=3, containing_service=None, input_type=_ORDERBOOKREQUEST, output_type=_ORDERBOOKRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='StreamOrderbook', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.StreamOrderbook', index=4, containing_service=None, input_type=_STREAMORDERBOOKREQUEST, output_type=_STREAMORDERBOOKRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='Orders', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.Orders', index=5, containing_service=None, input_type=_ORDERSREQUEST, output_type=_ORDERSRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='StreamOrders', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.StreamOrders', index=6, containing_service=None, input_type=_STREAMORDERSREQUEST, output_type=_STREAMORDERSRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='Trades', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.Trades', index=7, containing_service=None, input_type=_TRADESREQUEST, output_type=_TRADESRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='StreamTrades', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.StreamTrades', index=8, containing_service=None, input_type=_STREAMTRADESREQUEST, output_type=_STREAMTRADESRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='SubaccountOrdersList', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.SubaccountOrdersList', index=9, containing_service=None, input_type=_SUBACCOUNTORDERSLISTREQUEST, output_type=_SUBACCOUNTORDERSLISTRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), _descriptor.MethodDescriptor( name='SubaccountTradesList', full_name='injective_spot_exchange_rpc.InjectiveSpotExchangeRPC.SubaccountTradesList', index=10, containing_service=None, input_type=_SUBACCOUNTTRADESLISTREQUEST, output_type=_SUBACCOUNTTRADESLISTRESPONSE, serialized_options=None, create_key=_descriptor._internal_create_key, ), ]) _sym_db.RegisterServiceDescriptor(_INJECTIVESPOTEXCHANGERPC) DESCRIPTOR.services_by_name['InjectiveSpotExchangeRPC'] = _INJECTIVESPOTEXCHANGERPC # @@protoc_insertion_point(module_scope)

45.833239

6,964

0.774021

9,848

80,804

5.973396

0.040719

0.042566

0.083891

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0.753017

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80,804

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6,965

45.859251

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0.003066

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false

0

0.002452

0

0.002452

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null

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1

0

1

0

1

0

1

0

null

0

6

cc853d2b679d302ecfa29b743b6bf2b8b6578b25

50

py

Python

ExerciciosPython/ex001.py

LucasBalbinoSS/Exercicios-Python

2e9d3a8ec4ab24a2732c461a84f51bde54902a24

[ "MIT" ]

null

ExerciciosPython/ex001.py

LucasBalbinoSS/Exercicios-Python

2e9d3a8ec4ab24a2732c461a84f51bde54902a24

[ "MIT" ]

null

ExerciciosPython/ex001.py

LucasBalbinoSS/Exercicios-Python

2e9d3a8ec4ab24a2732c461a84f51bde54902a24

[ "MIT" ]

null

msg = '\033[1;31mOlá Mundo\033[1;32m!' print(msg)

16.666667

38

0.66

10

50

3.3

0.7

0.242424

0

0.266667

0.1

50

2

39

25

0.466667

0

0.6

0

1

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false

0

0.5

1

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null

1

0

1

0

1

0

1

0

null

0

1

0

6

ccd153ed89bef21c57f482532bdb27dbfd333b9b

86

py

Python

solver/__init__.py

SeongSuKim95/Re-ID-baseline

b145bba712492f7a93cd3771e007fa694b1c44b6

[ "MIT" ]

297

2021-03-26T14:29:47.000Z

2021-09-10T11:33:56.000Z

PASS_transreid/solver/__init__.py

CASIA-IVA-Lab/PASS-reID

46dc6d25f4396e35ac1a766ad2dcaa580beccf15

[ "Apache-2.0" ]

31

2019-06-13T02:03:22.000Z

2021-12-30T03:55:46.000Z

PASS_transreid/solver/__init__.py

CASIA-IVA-Lab/PASS-reID

46dc6d25f4396e35ac1a766ad2dcaa580beccf15

[ "Apache-2.0" ]

71

2019-06-17T01:10:08.000Z

2022-03-03T06:51:48.000Z

from .lr_scheduler import WarmupMultiStepLR from .make_optimizer import make_optimizer

43

0.895349

11

86

6.727273

0.636364

0.351351

0

0.081395

86

2

44

43

0.936709

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

aeb3b066939678ceaaedbef801437ee31c23e283

2,783

py

Python

epytope/Data/pssms/smmpmbec/mat/A_68_02_11.py

christopher-mohr/epytope

8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd

[ "BSD-3-Clause" ]

7

2021-02-01T18:11:28.000Z

2022-01-31T19:14:07.000Z

epytope/Data/pssms/smmpmbec/mat/A_68_02_11.py

christopher-mohr/epytope

8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd

[ "BSD-3-Clause" ]

22

2021-01-02T15:25:23.000Z

2022-03-14T11:32:53.000Z

epytope/Data/pssms/smmpmbec/mat/A_68_02_11.py

christopher-mohr/epytope

8ac9fe52c0b263bdb03235a5a6dffcb72012a4fd

[ "BSD-3-Clause" ]

4

2021-05-28T08:50:38.000Z

2022-03-14T11:45:32.000Z

A_68_02_11 = {0: {'A': 0.114, 'C': 0.028, 'E': -0.075, 'D': -0.01, 'G': 0.003, 'F': 0.041, 'I': 0.176, 'H': -0.078, 'K': -0.107, 'M': -0.028, 'L': -0.108, 'N': -0.021, 'Q': -0.12, 'P': 0.149, 'S': -0.061, 'R': -0.029, 'T': -0.017, 'W': 0.021, 'V': 0.112, 'Y': 0.009}, 1: {'A': -0.018, 'C': 0.039, 'E': 0.112, 'D': 0.111, 'G': 0.046, 'F': -0.114, 'I': -0.103, 'H': 0.055, 'K': -0.006, 'M': 0.063, 'L': -0.105, 'N': 0.081, 'Q': 0.212, 'P': -0.169, 'S': 0.093, 'R': 0.092, 'T': -0.05, 'W': 0.031, 'V': -0.269, 'Y': -0.101}, 2: {'A': -0.007, 'C': -0.001, 'E': -0.001, 'D': 0.0, 'G': -0.001, 'F': -0.003, 'I': -0.003, 'H': 0.004, 'K': 0.005, 'M': -0.001, 'L': -0.001, 'N': 0.002, 'Q': 0.0, 'P': -0.001, 'S': 0.0, 'R': 0.006, 'T': -0.001, 'W': 0.001, 'V': -0.003, 'Y': 0.002}, 3: {'A': 0.0, 'C': -0.001, 'E': -0.003, 'D': -0.004, 'G': 0.001, 'F': -0.003, 'I': -0.001, 'H': 0.001, 'K': 0.003, 'M': 0.0, 'L': -0.001, 'N': 0.0, 'Q': 0.002, 'P': -0.002, 'S': 0.002, 'R': 0.004, 'T': 0.002, 'W': -0.001, 'V': 0.001, 'Y': -0.0}, 4: {'A': 0.014, 'C': -0.007, 'E': 0.01, 'D': 0.005, 'G': 0.003, 'F': -0.055, 'I': -0.0, 'H': 0.001, 'K': 0.025, 'M': 0.006, 'L': 0.01, 'N': -0.005, 'Q': 0.034, 'P': 0.069, 'S': -0.011, 'R': 0.005, 'T': -0.016, 'W': -0.034, 'V': -0.024, 'Y': -0.03}, 5: {'A': -0.003, 'C': -0.001, 'E': -0.006, 'D': -0.005, 'G': -0.002, 'F': -0.002, 'I': -0.007, 'H': 0.007, 'K': 0.012, 'M': -0.004, 'L': -0.01, 'N': -0.0, 'Q': 0.001, 'P': 0.001, 'S': 0.005, 'R': 0.018, 'T': 0.0, 'W': 0.0, 'V': -0.006, 'Y': 0.002}, 6: {'A': 0.005, 'C': 0.002, 'E': 0.001, 'D': 0.005, 'G': 0.002, 'F': -0.001, 'I': 0.002, 'H': -0.004, 'K': -0.001, 'M': -0.0, 'L': -0.0, 'N': -0.0, 'Q': -0.001, 'P': 0.013, 'S': -0.006, 'R': -0.002, 'T': -0.002, 'W': -0.003, 'V': 0.001, 'Y': -0.009}, 7: {'A': -0.003, 'C': 0.0, 'E': 0.001, 'D': 0.001, 'G': -0.0, 'F': -0.0, 'I': -0.001, 'H': 0.0, 'K': -0.003, 'M': -0.001, 'L': -0.002, 'N': 0.001, 'Q': 0.001, 'P': 0.0, 'S': 0.002, 'R': 0.001, 'T': 0.001, 'W': 0.002, 'V': -0.002, 'Y': 0.0}, 8: {'A': 0.009, 'C': -0.007, 'E': 0.006, 'D': 0.017, 'G': -0.009, 'F': -0.041, 'I': -0.007, 'H': 0.003, 'K': 0.032, 'M': -0.014, 'L': -0.015, 'N': -0.015, 'Q': 0.01, 'P': 0.032, 'S': 0.003, 'R': 0.039, 'T': 0.001, 'W': -0.019, 'V': -0.012, 'Y': -0.013}, 9: {'A': 0.179, 'C': -0.096, 'E': -0.148, 'D': -0.038, 'G': -0.138, 'F': -0.186, 'I': 0.261, 'H': 0.052, 'K': 0.23, 'M': 0.078, 'L': 0.014, 'N': 0.093, 'Q': -0.149, 'P': -1.165, 'S': 0.112, 'R': 0.067, 'T': 0.35, 'W': 0.121, 'V': 0.331, 'Y': 0.03}, 10: {'A': -0.129, 'C': 0.027, 'E': 0.017, 'D': 0.069, 'G': 0.028, 'F': -0.054, 'I': -0.46, 'H': 0.231, 'K': 0.195, 'M': -0.108, 'L': -0.251, 'N': 0.095, 'Q': 0.096, 'P': 0.044, 'S': 0.077, 'R': 0.379, 'T': -0.028, 'W': 0.091, 'V': -0.394, 'Y': 0.076}, -1: {'con': 4.32633}}

2,783

0.38807

679

2,783

1.586156

0.173785

0.122563

0.013928

0.016713

0.339833

0.063138

0

0.366409

0.163493

2,783

1

2,783

0.09622

0

0.080101

0

1

0

false

0

1

null

0

1

0

1

0

null

0

6

aef551682eafbd0ebd3da47804c4eed0165e8cea

281

py

Python

deformable_convolution/modules/__init__.py

Andyflying/LightNet-plusplus

24a76792ab4c1bf8f94fb1457539ded86ed2112e

[ "Apache-2.0" ]

null

deformable_convolution/modules/__init__.py

Andyflying/LightNet-plusplus

24a76792ab4c1bf8f94fb1457539ded86ed2112e

[ "Apache-2.0" ]

null

deformable_convolution/modules/__init__.py

Andyflying/LightNet-plusplus

24a76792ab4c1bf8f94fb1457539ded86ed2112e

[ "Apache-2.0" ]

null

from .deform_conv import DeformConv, _DeformConv, DeformConvPack from .modulated_deform_conv import ModulatedDeformConv, _ModulatedDeformConv, ModulatedDeformConvPack, ModulatedDeformConvTM from .deform_psroi_pooling import DeformRoIPooling, _DeformRoIPooling, DeformRoIPoolingPack

93.666667

124

0.900356

24

281

10.208333

0.583333

0.081633

0.130612

0

0.064057

281

3

125

93.666667

0.931559

0

1

0

true

0

1

0

1

0

1

0

1

null

0

1

0

null

0

1

0

1

0

1

0

6

4e0edc1db2e148fc3539ad6974367bc52803bc95

925

py

Python

people/regex.py

ChrisWaites/human

cf7085ade64aed33ee942b96a5f4d0a6977ba187

[ "MIT" ]

1

2020-03-30T10:05:58.000Z

people/regex.py

ChrisWaites/human

cf7085ade64aed33ee942b96a5f4d0a6977ba187

[ "MIT" ]

1

2018-04-26T04:41:22.000Z

people/regex.py

ChrisWaites/people

cf7085ade64aed33ee942b96a5f4d0a6977ba187

[ "MIT" ]

null

any = r'.*' nonneg_int = r'\d+' neg_int = r'-\d+' int = r'-?\d+' nonneg_float = r'\d*\.?\d+' neg_float = r'-\d*\.?\d+' float = r'-?\d*\.?\d+' float_zero_to_one = r'0(\.\d+)?|1\.0' url = r'((https?|ftp|file):\/\/)?([\da-z\.-]+)\.([a-z\.]{2,6})([\/\w \.-]*)*\/?' email = r'.+@.+' phone = r'\+?(\d.*){3,}' date = r'(0?[1-9]|[12][0-9]|3[01])([ \/\-])(0?[1-9]|1[012])\2([0-9][0-9][0-9][0-9])(([ -])([0-1]?[0-9]|2[0-3]):[0-5]?[0-9]:[0-5]?[0-9])?' time = r'([01]?[0-9]|2[0-3]):[0-5][0-9]' iso8601 = r'(?![+-]?\d{4,5}-?(?:\d{2}|W\d{2})T)(?:|(\d{4}|[+-]\d{5})-?(?:|(0\d|1[0-2])(?:|-?([0-2]\d|3[0-1]))|([0-2]\d{2}|3[0-5]\d|36[0-6])|W([0-4]\d|5[0-3])(?:|-?([1-7])))(?:(?!\d)|T(?=\d)))(?:|([01]\d|2[0-4])(?:|:?([0-5]\d)(?:|:?([0-5]\d)(?:|\.(\d{3})))(?:|[zZ]|([+-](?:[01]\d|2[0-4]))(?:|:?([0-5]\d)))))' def union(*choices): return r'({})'.format('|'.join(choices)) def csv(*choices): return r'{}'.format(' *, *'.join(choices))

42.045455

307

0.371892

192

925

1.755208

0.234375

0.059347

0.04451

0.071217

0.379822

0.317507

0.133531

0.106825

0.053412

0

0.12922

0.071351

925

21

308

44.047619

0.263097

0

0.222222

0.660173

0.550866

0

1

0.111111

false

0

0.111111

0.222222

0

1

null

0

1

0

1

null

0

1

0

6

9d818c19e44f542f0a3a24081f66f939c5318c4b

5,345

py

Python

sdk/python/pulumi_azure_native/resources/__init__.py

polivbr/pulumi-azure-native

09571f3bf6bdc4f3621aabefd1ba6c0d4ecfb0e7

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/resources/__init__.py

polivbr/pulumi-azure-native

09571f3bf6bdc4f3621aabefd1ba6c0d4ecfb0e7

[ "Apache-2.0" ]

null

sdk/python/pulumi_azure_native/resources/__init__.py

polivbr/pulumi-azure-native

09571f3bf6bdc4f3621aabefd1ba6c0d4ecfb0e7

[ "Apache-2.0" ]

null

# coding=utf-8 # *** WARNING: this file was generated by the Pulumi SDK Generator. *** # *** Do not edit by hand unless you're certain you know what you are doing! *** from .. import _utilities import typing # Export this package's modules as members: from ._enums import * from .azure_cli_script import * from .azure_power_shell_script import * from .deployment import * from .deployment_at_management_group_scope import * from .deployment_at_scope import * from .deployment_at_subscription_scope import * from .deployment_at_tenant_scope import * from .deployment_script import * from .get_azure_cli_script import * from .get_azure_power_shell_script import * from .get_deployment import * from .get_deployment_at_management_group_scope import * from .get_deployment_at_scope import * from .get_deployment_at_subscription_scope import * from .get_deployment_at_tenant_scope import * from .get_deployment_script import * from .get_resource import * from .get_resource_group import * from .get_tag_at_scope import * from .get_template_spec import * from .get_template_spec_version import * from .resource import * from .resource_group import * from .tag_at_scope import * from .template_spec import * from .template_spec_version import * from ._inputs import * from . import outputs # Make subpackages available: if typing.TYPE_CHECKING: import pulumi_azure_native.resources.v20151101 as __v20151101 v20151101 = __v20151101 import pulumi_azure_native.resources.v20160201 as __v20160201 v20160201 = __v20160201 import pulumi_azure_native.resources.v20160701 as __v20160701 v20160701 = __v20160701 import pulumi_azure_native.resources.v20160901 as __v20160901 v20160901 = __v20160901 import pulumi_azure_native.resources.v20170510 as __v20170510 v20170510 = __v20170510 import pulumi_azure_native.resources.v20180201 as __v20180201 v20180201 = __v20180201 import pulumi_azure_native.resources.v20180501 as __v20180501 v20180501 = __v20180501 import pulumi_azure_native.resources.v20190301 as __v20190301 v20190301 = __v20190301 import pulumi_azure_native.resources.v20190501 as __v20190501 v20190501 = __v20190501 import pulumi_azure_native.resources.v20190510 as __v20190510 v20190510 = __v20190510 import pulumi_azure_native.resources.v20190601preview as __v20190601preview v20190601preview = __v20190601preview import pulumi_azure_native.resources.v20190701 as __v20190701 v20190701 = __v20190701 import pulumi_azure_native.resources.v20190801 as __v20190801 v20190801 = __v20190801 import pulumi_azure_native.resources.v20191001 as __v20191001 v20191001 = __v20191001 import pulumi_azure_native.resources.v20191001preview as __v20191001preview v20191001preview = __v20191001preview import pulumi_azure_native.resources.v20200601 as __v20200601 v20200601 = __v20200601 import pulumi_azure_native.resources.v20200801 as __v20200801 v20200801 = __v20200801 import pulumi_azure_native.resources.v20201001 as __v20201001 v20201001 = __v20201001 import pulumi_azure_native.resources.v20210101 as __v20210101 v20210101 = __v20210101 import pulumi_azure_native.resources.v20210301preview as __v20210301preview v20210301preview = __v20210301preview import pulumi_azure_native.resources.v20210401 as __v20210401 v20210401 = __v20210401 import pulumi_azure_native.resources.v20210501 as __v20210501 v20210501 = __v20210501 else: v20151101 = _utilities.lazy_import('pulumi_azure_native.resources.v20151101') v20160201 = _utilities.lazy_import('pulumi_azure_native.resources.v20160201') v20160701 = _utilities.lazy_import('pulumi_azure_native.resources.v20160701') v20160901 = _utilities.lazy_import('pulumi_azure_native.resources.v20160901') v20170510 = _utilities.lazy_import('pulumi_azure_native.resources.v20170510') v20180201 = _utilities.lazy_import('pulumi_azure_native.resources.v20180201') v20180501 = _utilities.lazy_import('pulumi_azure_native.resources.v20180501') v20190301 = _utilities.lazy_import('pulumi_azure_native.resources.v20190301') v20190501 = _utilities.lazy_import('pulumi_azure_native.resources.v20190501') v20190510 = _utilities.lazy_import('pulumi_azure_native.resources.v20190510') v20190601preview = _utilities.lazy_import('pulumi_azure_native.resources.v20190601preview') v20190701 = _utilities.lazy_import('pulumi_azure_native.resources.v20190701') v20190801 = _utilities.lazy_import('pulumi_azure_native.resources.v20190801') v20191001 = _utilities.lazy_import('pulumi_azure_native.resources.v20191001') v20191001preview = _utilities.lazy_import('pulumi_azure_native.resources.v20191001preview') v20200601 = _utilities.lazy_import('pulumi_azure_native.resources.v20200601') v20200801 = _utilities.lazy_import('pulumi_azure_native.resources.v20200801') v20201001 = _utilities.lazy_import('pulumi_azure_native.resources.v20201001') v20210101 = _utilities.lazy_import('pulumi_azure_native.resources.v20210101') v20210301preview = _utilities.lazy_import('pulumi_azure_native.resources.v20210301preview') v20210401 = _utilities.lazy_import('pulumi_azure_native.resources.v20210401') v20210501 = _utilities.lazy_import('pulumi_azure_native.resources.v20210501')

49.490741

95

0.815716

614

5,345

6.636808

0.143322

0.129571

0.183558

0.248344

0.671411

0.60319

0.263558

0

0.225373

0.122544

5,345

107

96

49.953271

0.643497

0.043218

0

1

0

0.172117

0

1

0

false

0

0.757576

0

0.757576

0

null

0

1

0

1

0

1

0

null

0

1

0

1

0

6

9dd5b07afcda55724558ef9e31ee76303b61e3fe

209

py

Python

RecoBTag/Skimming/python/btagElecInJet_SkimPaths_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

852

2015-01-11T21:03:51.000Z

2022-03-25T21:14:00.000Z

RecoBTag/Skimming/python/btagElecInJet_SkimPaths_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

30,371

2015-01-02T00:14:40.000Z

2022-03-31T23:26:05.000Z

RecoBTag/Skimming/python/btagElecInJet_SkimPaths_cff.py

ckamtsikis/cmssw

ea19fe642bb7537cbf58451dcf73aa5fd1b66250

[ "Apache-2.0" ]

3,240

2015-01-02T05:53:18.000Z

2022-03-31T17:24:21.000Z

import FWCore.ParameterSet.Config as cms from RecoBTag.Skimming.btagElecInJet_HLT_cfi import * from RecoBTag.Skimming.btagElecInJet_cfi import * btagElecInJetPath = cms.Path(btagElecInJet_HLT*btagElecInJet)

29.857143

61

0.856459

25

209

7

0.56

0.137143

0.228571

0.377143

0

0.08134

209

6

62

34.833333

0.911458

0

1

0

false

0

0.75

0

0.75

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

d1c0bb2dc6786531d6dcb602157eff0e14d5c858

29

py

Python

vnpy/api/femas/__init__.py

xiumingxu/vnpy-xx

8b2d9ecdabcb7931d46fd92fad2d3701b7e66975

[ "MIT" ]

null

vnpy/api/femas/__init__.py

xiumingxu/vnpy-xx

8b2d9ecdabcb7931d46fd92fad2d3701b7e66975

[ "MIT" ]

null

vnpy/api/femas/__init__.py

xiumingxu/vnpy-xx

8b2d9ecdabcb7931d46fd92fad2d3701b7e66975

[ "MIT" ]

null

from .femas_constant import *

29

0.827586

4

29

5.75

1

0

0.103448

29

1

29

0.884615

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

d1c3b7893325a2330caef82e57fc6e99aaa855f1

120

py

Python

src/models/logistic_test_model.py

pkiage/credit-risk-modelling-tool

74f6cdb27c8333c9cae5b08b91b5521af8e444e0

[ "MIT" ]

1

2022-03-03T10:27:23.000Z

src/models/logistic_test_model.py

pkiage/credit-risk-modelling-tool

74f6cdb27c8333c9cae5b08b91b5521af8e444e0

[ "MIT" ]

null

src/models/logistic_test_model.py

pkiage/credit-risk-modelling-tool

74f6cdb27c8333c9cae5b08b91b5521af8e444e0

[ "MIT" ]

1

2022-03-29T14:40:20.000Z

from models.util_test import make_tests_view logistic_test_model = make_tests_view( "Logistic", "Logistic Model")

24

45

0.791667

17

120

5.176471

0.588235

0.204545

0.295455

0.477273

0

0.133333

120

4

46

30

0.846154

0

0.183333

0

1

0

false

0

0.333333

0

0.333333

0

1

0

null

1

0

1

0

null

0

1

0

6

ae2c0d7ddbca17e29543aebb7881d212e0d13199

46

py

Python

src/visualization/__init__.py

blotspot/expanse-book-analysis

03288e34d01eb9465205c764b8ba5d7062ddd5ab

[ "MIT" ]

null

src/visualization/__init__.py

blotspot/expanse-book-analysis

03288e34d01eb9465205c764b8ba5d7062ddd5ab

[ "MIT" ]

null

src/visualization/__init__.py

blotspot/expanse-book-analysis

03288e34d01eb9465205c764b8ba5d7062ddd5ab

[ "MIT" ]

null

from .image import * from .visualize import *

15.333333

24

0.73913

6

46

5.666667

0.666667

0

0.173913

46

2

25

23

0.894737

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ae4575a8354cb779ebe9eed7c8ed676549952c32

4,556

py

Python

eop/special_numeric.py

redhog/EmbarrassmentOfPandas

e0c5c38bfaa79c04424f0d8ecde2c83b7da64908

[ "MIT" ]

null

eop/special_numeric.py

redhog/EmbarrassmentOfPandas

e0c5c38bfaa79c04424f0d8ecde2c83b7da64908

[ "MIT" ]

null

eop/special_numeric.py

redhog/EmbarrassmentOfPandas

e0c5c38bfaa79c04424f0d8ecde2c83b7da64908

[ "MIT" ]

1

2021-04-28T22:03:09.000Z

class SpecialNumeric(object): def __add__(self, *arg, **kw): return self.__getattr__("__add__")(*arg, **kw) def __sub__(self, *arg, **kw): return self.__getattr__("__sub__")(*arg, **kw) def __mul__(self, *arg, **kw): return self.__getattr__("__mul__")(*arg, **kw) def __floordiv__(self, *arg, **kw): return self.__getattr__("__floordiv__")(*arg, **kw) def __mod__(self, *arg, **kw): return self.__getattr__("__mod__")(*arg, **kw) def __divmod__(self, *arg, **kw): return self.__getattr__("__divmod__")(*arg, **kw) def __pow__(self, *arg, **kw): return self.__getattr__("__pow__")(*arg, **kw) def __lshift__(self, *arg, **kw): return self.__getattr__("__lshift__")(*arg, **kw) def __rshift__(self, *arg, **kw): return self.__getattr__("__rshift__")(*arg, **kw) def __and__(self, *arg, **kw): return self.__getattr__("__and__")(*arg, **kw) def __xor__(self, *arg, **kw): return self.__getattr__("__xor__")(*arg, **kw) def __or__(self, *arg, **kw): return self.__getattr__("__or__")(*arg, **kw) def __div__(self, *arg, **kw): return self.__getattr__("__div__")(*arg, **kw) def __truediv__(self, *arg, **kw): return self.__getattr__("__truediv__")(*arg, **kw) def __radd__(self, *arg, **kw): return self.__getattr__("__radd__")(*arg, **kw) def __rsub__(self, *arg, **kw): return self.__getattr__("__rsub__")(*arg, **kw) def __rmul__(self, *arg, **kw): return self.__getattr__("__rmul__")(*arg, **kw) def __rdiv__(self, *arg, **kw): return self.__getattr__("__rdiv__")(*arg, **kw) def __rtruediv__(self, *arg, **kw): return self.__getattr__("__rtruediv__")(*arg, **kw) def __rfloordiv__(self, *arg, **kw): return self.__getattr__("__rfloordiv__")(*arg, **kw) def __rmod__(self, *arg, **kw): return self.__getattr__("__rmod__")(*arg, **kw) def __rdivmod__(self, *arg, **kw): return self.__getattr__("__rdivmod__")(*arg, **kw) def __rpow__(self, *arg, **kw): return self.__getattr__("__rpow__")(*arg, **kw) def __rlshift__(self, *arg, **kw): return self.__getattr__("__rlshift__")(*arg, **kw) def __rrshift__(self, *arg, **kw): return self.__getattr__("__rrshift__")(*arg, **kw) def __rand__(self, *arg, **kw): return self.__getattr__("__rand__")(*arg, **kw) def __rxor__(self, *arg, **kw): return self.__getattr__("__rxor__")(*arg, **kw) def __ror__(self, *arg, **kw): return self.__getattr__("__ror__")(*arg, **kw) def __iadd__(self, *arg, **kw): return self.__getattr__("__iadd__")(*arg, **kw) def __isub__(self, *arg, **kw): return self.__getattr__("__isub__")(*arg, **kw) def __imul__(self, *arg, **kw): return self.__getattr__("__imul__")(*arg, **kw) def __idiv__(self, *arg, **kw): return self.__getattr__("__idiv__")(*arg, **kw) def __itruediv__(self, *arg, **kw): return self.__getattr__("__itruediv__")(*arg, **kw) def __ifloordiv__(self, *arg, **kw): return self.__getattr__("__ifloordiv__")(*arg, **kw) def __imod__(self, *arg, **kw): return self.__getattr__("__imod__")(*arg, **kw) def __ipow__(self, *arg, **kw): return self.__getattr__("__ipow__")(*arg, **kw) def __ilshift__(self, *arg, **kw): return self.__getattr__("__ilshift__")(*arg, **kw) def __irshift__(self, *arg, **kw): return self.__getattr__("__irshift__")(*arg, **kw) def __iand__(self, *arg, **kw): return self.__getattr__("__iand__")(*arg, **kw) def __ixor__(self, *arg, **kw): return self.__getattr__("__ixor__")(*arg, **kw) def __ior__(self, *arg, **kw): return self.__getattr__("__ior__")(*arg, **kw) def __neg__(self, *arg, **kw): return self.__getattr__("__neg__")(*arg, **kw) def __pos__(self, *arg, **kw): return self.__getattr__("__pos__")(*arg, **kw) def __abs__(self, *arg, **kw): return self.__getattr__("__abs__")(*arg, **kw) def __invert__(self, *arg, **kw): return self.__getattr__("__invert__")(*arg, **kw) def __complex__(self, *arg, **kw): return self.__getattr__("__complex__")(*arg, **kw) def __int__(self, *arg, **kw): return self.__getattr__("__int__")(*arg, **kw) def __long__(self, *arg, **kw): return self.__getattr__("__long__")(*arg, **kw) def __float__(self, *arg, **kw): return self.__getattr__("__float__")(*arg, **kw) def __oct__(self, *arg, **kw): return self.__getattr__("__oct__")(*arg, **kw) def __hex__(self, *arg, **kw): return self.__getattr__("__hex__")(*arg, **kw) def __index__(self, *arg, **kw): return self.__getattr__("__index__")(*arg, **kw) def __coerce__(self, *arg, **kw): return self.__getattr__("__coerce__")(*arg, **kw)

82.836364

93

0.649912

586

4,556

3.967577

0.105802

0.227957

0.205161

0.341935

0.592688

0

0.128402

4,556

54

94

84.37037

0.585495

0

0.101185

0

1

0.981481

false

0

0.981481

1

0

null

1

0

null

0

1

0

1

0

6

ae5b09be59ffe0a325947d3778ffaacb6b7bec38

22

py

Python

Blup.py

janaobsteter/Genotype_CODES

8adf70660ebff4dd106c666db02cdba8b8ce4f97

[ "Apache-2.0" ]

1

2021-10-07T18:55:03.000Z

Blup.py

janaobsteter/Genotype_CODES

8adf70660ebff4dd106c666db02cdba8b8ce4f97

[ "Apache-2.0" ]

null

Blup.py

janaobsteter/Genotype_CODES

8adf70660ebff4dd106c666db02cdba8b8ce4f97

[ "Apache-2.0" ]

1

2017-04-13T09:07:41.000Z

from PyPedal import *

11

21

0.772727

3

22

5.666667

1

0

0.181818

22

1

22

0.944444

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

ae625190cb1bcf2697aa3b2d14b4f4406dc644bb

167

py

Python

inclearn/lib/losses/__init__.py

sajjadahmadish/incremental_learning.pytorch

f01c1cf9cbafc930687a89dbdf7c1937d1ca2749

[ "MIT" ]

null

inclearn/lib/losses/__init__.py

sajjadahmadish/incremental_learning.pytorch

f01c1cf9cbafc930687a89dbdf7c1937d1ca2749

[ "MIT" ]

null

inclearn/lib/losses/__init__.py

sajjadahmadish/incremental_learning.pytorch

f01c1cf9cbafc930687a89dbdf7c1937d1ca2749

[ "MIT" ]

null

# flake8: noqa from .base import * from .distillation import * from .metrics import * from .regularizations import * from .unsupervised import * from .losses import *

20.875

30

0.754491

20

167

6.3

0.5

0.396825

0

0.007143

0.161677

167

7

31

23.857143

0.892857

0.071856

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

884466422d02e33a14b7a4d1fd0b18ccc89c7331

49

py

Python

TOPSIS_Aneesh_101853025/__init__.py

aj8101/TOPSIS-Aneesh-101853025

153921e4bc88d16ec0d5ed7108b2ec71934ebfc2

[ "MIT" ]

null

TOPSIS_Aneesh_101853025/__init__.py

aj8101/TOPSIS-Aneesh-101853025

153921e4bc88d16ec0d5ed7108b2ec71934ebfc2

[ "MIT" ]

null

TOPSIS_Aneesh_101853025/__init__.py

aj8101/TOPSIS-Aneesh-101853025

153921e4bc88d16ec0d5ed7108b2ec71934ebfc2

[ "MIT" ]

null

from TOPSIS_Aneesh_101853025.topsis import topsis

49

0.918367

7

49

6.142857

0.714286

0

0.195652

0.061224

49

1

49

0.73913

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

88689311e5b0b853e499d326f2d99a42e06a76de

128

py

Python

poroto/none/c_wrapper.py

TANGO-Project/poroto

380c0ab9f33bead70ed71c78493e682924d7f997

[ "BSD-3-Clause" ]

1

2018-05-22T22:53:31.000Z

poroto/none/c_wrapper.py

TANGO-Project/poroto

380c0ab9f33bead70ed71c78493e682924d7f997

[ "BSD-3-Clause" ]

null

poroto/none/c_wrapper.py

TANGO-Project/poroto

380c0ab9f33bead70ed71c78493e682924d7f997

[ "BSD-3-Clause" ]

null

class CWrapper: def __init__(self, functions, mmap, streams_map, debug): pass def generate(self): pass

18.285714

60

0.625

15

128

5

0.8

0

0.289063

128

6

61

21.333333

0.824176

0

0.4

1

0

1

0.4

false

0.4

0

0.6

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

1

0

6

88b820401e89d270297e8cfe3beb4bd1dbbcc427

167

py

Python

app/screens/mobility.py

zshanahmed/mobileinsight-mobile

ae466c72d17655609539dfec2318b2de5c6786a8

[ "Apache-2.0" ]

63

2017-06-30T15:04:15.000Z

2021-11-15T09:58:45.000Z

app/screens/mobility.py

zshanahmed/mobileinsight-mobile

ae466c72d17655609539dfec2318b2de5c6786a8

[ "Apache-2.0" ]

28

2017-07-24T15:51:50.000Z

2022-03-13T21:13:09.000Z

app/screens/mobility.py

zshanahmed/mobileinsight-mobile

ae466c72d17655609539dfec2318b2de5c6786a8

[ "Apache-2.0" ]

45

2017-07-02T13:16:37.000Z

2022-03-22T07:26:13.000Z

from . import MobileInsightScreenBase from kivy.lang import Builder Builder.load_file('screens/mobility.kv') class MobilityScreen(MobileInsightScreenBase): pass

20.875

46

0.820359

18

167

7.555556

0.777778

0

0.107784

167

7

47

23.857143

0.912752

0

0.113772

0

1

0

true

0.2

0.4

0

0.6

0

1

0

null

0

1

0

null

0

1

0

1

0

6

ee5bfef06a448fdfb9a09c1d6aba79220bc5f783

539

py

Python

src/keras/keras/applications/vgg16.py

lu791019/iii_HA_Image_Recognition_DL

d5f56d62af6d3aac1c216ca4ff309db08a8c9072

[ "Apache-2.0" ]

null

src/keras/keras/applications/vgg16.py

lu791019/iii_HA_Image_Recognition_DL

d5f56d62af6d3aac1c216ca4ff309db08a8c9072

[ "Apache-2.0" ]

null

src/keras/keras/applications/vgg16.py

lu791019/iii_HA_Image_Recognition_DL

d5f56d62af6d3aac1c216ca4ff309db08a8c9072

[ "Apache-2.0" ]

null

from __future__ import absolute_import from __future__ import division from __future__ import print_function from keras_applications import vgg16 from . import keras_modules_injection @keras_modules_injection def VGG16(*args, **kwargs): return vgg16.VGG16(*args, **kwargs) @keras_modules_injection def decode_predictions(*args, **kwargs): return vgg16.decode_predictions(*args, **kwargs) @keras_modules_injection def preprocess_input(*args, **kwargs): return vgg16.preprocess_input(*args, **kwargs)

24.5

53

0.764378

64

539

6.015625

0.3125

0.155844

0.218182

0.187013

0.176623

0

0.026201

0.150278

539

21

54

25.666667

0.81441

0

0.214286

0

1

0.214286

true

0

0.357143

0.214286

0.785714

0.071429

0

null

0

1

0

null

0

1

0

1

0

6

ee5f24272f22941cf917702694ba932755cc640a

24

py

Python

apps/DuelingBanditsPureExploration/algs/BR_Random/__init__.py

sumeetsk/NEXT-1

c42badbcaeb0ab79ab1f74b6303ecc3864b1c7ee

[ "Apache-2.0" ]

null

apps/DuelingBanditsPureExploration/algs/BR_Random/__init__.py

sumeetsk/NEXT-1

c42badbcaeb0ab79ab1f74b6303ecc3864b1c7ee

[ "Apache-2.0" ]

null

apps/DuelingBanditsPureExploration/algs/BR_Random/__init__.py

sumeetsk/NEXT-1

c42badbcaeb0ab79ab1f74b6303ecc3864b1c7ee

[ "Apache-2.0" ]

null

from .BR_Random import *

24

0.791667

4

24

4.5

1

0

0.125

24

1

24

0.857143

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

c99479f3007824b49a0ee91c88b7841a29e1b837

17

py

Python

algorithms/dvr.py

alv16106/RoutingLab

20e49d98290ef36dab78baeef7bc99fa4d36af4d

[ "MIT" ]

null

algorithms/dvr.py

alv16106/RoutingLab

20e49d98290ef36dab78baeef7bc99fa4d36af4d

[ "MIT" ]

null

algorithms/dvr.py

alv16106/RoutingLab

20e49d98290ef36dab78baeef7bc99fa4d36af4d

[ "MIT" ]

null

def dvr(): pass

8.5

10

0.588235

3

17

3.333333

1

0

0.235294

17

2

11

8.5

0.769231

0

1

0.5

true

0.5

0

0.5

0

1

0

null

0

1

0

null

0

1

0

6

4e5f0ba7fb5a685dc84790ed098cc4eb30d50712

57

py

Python

li_hang/knn/__init__.py

LucienShui/HelloMachineLearning

b00a4b3791808ace3b1e45112350c2b3c539995e

[ "Apache-2.0" ]

2

2019-07-28T08:25:40.000Z

2019-07-29T05:29:10.000Z

li_hang/knn/__init__.py

LucienShui/HelloMachineLearning

b00a4b3791808ace3b1e45112350c2b3c539995e

[ "Apache-2.0" ]

null

li_hang/knn/__init__.py

LucienShui/HelloMachineLearning

b00a4b3791808ace3b1e45112350c2b3c539995e

[ "Apache-2.0" ]

null

from knn.base_knn import BaseKNN from knn.knn import KNN

19

32

0.824561

11

57

4.181818

0.454545

0.304348

0

0.140351

57

2

33

28.5

0.938776

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

4e6b445586321bcc44b39541ac44d8498d7d10eb

4,847

py

Python

tests/test_get_super_records_from_interval_tree.py

leoisl/vcf_consensus_builder

1e2f0312810b183edf368b33086475318a779b87

[ "MIT" ]

null

tests/test_get_super_records_from_interval_tree.py

leoisl/vcf_consensus_builder

1e2f0312810b183edf368b33086475318a779b87

[ "MIT" ]

null

tests/test_get_super_records_from_interval_tree.py

leoisl/vcf_consensus_builder

1e2f0312810b183edf368b33086475318a779b87

[ "MIT" ]

null

import unittest from io import StringIO from vcf_consensus_builder.vcf_io import read_vcf from vcf_consensus_builder.vcf_consensus_builder_core import get_super_records_from_interval_tree, InconsistentVCFException from intervaltree import Interval, IntervalTree class Test_get_gt_from_sample_info(unittest.TestCase): def test_get_super_records_from_interval_tree___no_overlaps___everything_is_a_super_record(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) expected = get_super_records_from_interval_tree(interval_tree) actual = interval_tree self.assertEqual(actual, expected) def test_get_super_records_from_interval_tree___several_overlaps(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(3, 4, ('A', 'C')), Interval(3, 5, ('AC', 'CC')), Interval(3, 6, ('ACC', 'CCC')), Interval(3, 7, ('ACCG', 'CCC')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) expected = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) actual = get_super_records_from_interval_tree(interval_tree) self.assertEqual(actual, expected) def test_get_super_records_from_interval_tree___one_overlap_begin_match(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(3, 10, ('ACCGTGG', 'CCCCA')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) expected = IntervalTree( [Interval(2, 3, ('G', 'A')), Interval(3, 10, ('ACCGTGG', 'CCCCA')), Interval(10, 13, ('GGA', 'TTT'))]) actual = get_super_records_from_interval_tree(interval_tree) self.assertEqual(actual, expected) def test_get_super_records_from_interval_tree___one_overlap_totally_inside(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(4, 7, ('CCG', 'CC')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) expected = IntervalTree( [Interval(2, 3, ('G', 'A')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) actual = get_super_records_from_interval_tree(interval_tree) self.assertEqual(actual, expected) def test_get_super_records_from_interval_tree___one_overlap_end_match(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(6, 8, ('GT', 'CC')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) expected = IntervalTree( [Interval(2, 3, ('G', 'A')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) actual = get_super_records_from_interval_tree(interval_tree) self.assertEqual(actual, expected) def test_get_super_records_from_interval_tree___one_overlap_ref_not_consistent_in_the_begin(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(3, 5, ('AG', 'CC')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) self.assertRaises(InconsistentVCFException, get_super_records_from_interval_tree, interval_tree) def test_get_super_records_from_interval_tree___one_overlap_ref_not_consistent_in_the_middle(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(5, 6, ('A', 'C')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) self.assertRaises(InconsistentVCFException, get_super_records_from_interval_tree, interval_tree) def test_get_super_records_from_interval_tree___one_overlap_ref_not_consistent_in_the_end(self): interval_tree = IntervalTree([Interval(2, 3, ('G', 'A')), Interval(7, 8, ('A', 'C')), Interval(3, 8, ('ACCGT', 'CCCC')), Interval(10, 13, ('GGA', 'TTT'))]) self.assertRaises(InconsistentVCFException, get_super_records_from_interval_tree, interval_tree)

62.141026

135

0.552919

525

4,847

4.748571

0.139048

0.163658

0.102286

0.129563

0.863217

0.842359

0.829924

0.797433

0

0.035088

0.306169

4,847

77

136

62.948052

0.706215

0

0.567164

0

0.05261

0

0.119403

1

0.119403

false

0

0.074627

0

0.208955

0

null

0

1

0

null

0

6

4e77e2636e8bae731b5a29b01f700bfd6f96998b

38

py

Python

qflow/samplers/__init__.py

johanere/qflow

5453cd5c3230ad7f082adf9ec1aea63ab0a4312a

[ "MIT" ]

5

2019-07-24T21:46:24.000Z

2021-06-11T18:18:24.000Z

qflow/samplers/__init__.py

johanere/qflow

5453cd5c3230ad7f082adf9ec1aea63ab0a4312a

[ "MIT" ]

22

2019-02-19T10:49:26.000Z

2019-07-18T09:42:13.000Z

qflow/samplers/__init__.py

bsamseth/FYS4411

72b879e7978364498c48fc855b5df676c205f211

[ "MIT" ]

2

2020-11-04T15:17:24.000Z

2021-11-03T16:37:38.000Z

from _qflow_backend.samplers import *

19

37

0.842105

5

38

6

1

0

0.105263

38

1

38

0.882353

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

4e846701f3ef6faca608f8391ba8b6e5c5efaa48

26

py

Python

env/Lib/site-packages/win32/trace/__init__.py

Daniel-Key/HearStone-Python

981584d2b9502319393bd92b48f0ec8d906b4d44

[ "MIT" ]

null

env/Lib/site-packages/win32/trace/__init__.py

Daniel-Key/HearStone-Python

981584d2b9502319393bd92b48f0ec8d906b4d44

[ "MIT" ]

1

2020-10-27T14:44:08.000Z

env/Lib/site-packages/win32/trace/__init__.py

Daniel-Key/HearStone-Python

981584d2b9502319393bd92b48f0ec8d906b4d44

[ "MIT" ]

null

from win32._trace import *

26

0.807692

4

26

5

1

0

0.086957

0.115385

26

1

26

0.782609

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

4eaacb9a993cb7937382b6a8c692577be97599c2

48

py

Python

ex.py

MayZinThwe/python-exercises

7a7bcd7b0a967efb8e5140ab2486036a1defa551

[ "MIT" ]

null

ex.py

MayZinThwe/python-exercises

7a7bcd7b0a967efb8e5140ab2486036a1defa551

[ "MIT" ]

null

ex.py

MayZinThwe/python-exercises

7a7bcd7b0a967efb8e5140ab2486036a1defa551

[ "MIT" ]

null

print("Hello ! Welcome to my python exercises")

24

47

0.75

7

48

5.142857

1

0

0.145833

48

1

48

0.878049

0

0.791667

0

1

0

true

0

1

0

null

0

1

0

1

0

null

0

1

0

1

0

6

14d074f25c20677fce7cfabae54b6f08dabd5e8c

41

py

Python

apiai_assistant/__init__.py

toasterco/apiaiassistant

7f3f0693c4c5aa9f1fd4486f85ebe05080505dc8

[ "MIT" ]

6

2017-08-10T16:08:03.000Z

2018-08-03T23:36:20.000Z

apiai_assistant/__init__.py

toasterco/apiaiassistant

7f3f0693c4c5aa9f1fd4486f85ebe05080505dc8

[ "MIT" ]

1

2018-03-23T14:12:36.000Z

2018-03-23T15:40:33.000Z

apiai_assistant/__init__.py

toasterco/apiaiassistant

7f3f0693c4c5aa9f1fd4486f85ebe05080505dc8

[ "MIT" ]

null

from .assistant import Assistant # NOQA

20.5

40

0.780488

5

41

6.4

0.8

0

0.170732

41

1

41

0.941176

0.097561

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

093c834f97c9fe7e18631ccb68fcd91e27eaaaa6

29

py

Python

Configuration/__init__.py

olmedoluis/pix

872fc75a3cef0d8cb152b1565a831874b9fd3fb5

[ "MIT" ]

null

Configuration/__init__.py

olmedoluis/pix

872fc75a3cef0d8cb152b1565a831874b9fd3fb5

[ "MIT" ]

null

Configuration/__init__.py

olmedoluis/pix

872fc75a3cef0d8cb152b1565a831874b9fd3fb5

[ "MIT" ]

null

from .Aliases import ALIASES

14.5

28

0.827586

4

29

6

0.75

0

0.137931

29

1

29

0.96

0

1

0

true

0

1

0

1

0

1

0

null

0

1

0

null

0

1

0

1

0

1

0

6

093c91e7862f4bc40d6e3817aae211a2aa97b756

151

py

Python

src/artifice/paper/routes/about/views.py

artifice-project/artifice-paper

c20e863ced5364fbdd9142d4e336067504c8341c

[ "MIT" ]

null

src/artifice/paper/routes/about/views.py

artifice-project/artifice-paper

c20e863ced5364fbdd9142d4e336067504c8341c

[ "MIT" ]

null

src/artifice/paper/routes/about/views.py

artifice-project/artifice-paper

c20e863ced5364fbdd9142d4e336067504c8341c

[ "MIT" ]

null

from flask import Blueprint about_blueprint = Blueprint('about', __name__) @about_blueprint.route('/') def index(): return '<h1>about page</h1>'

18.875

46

0.715232

19

151

5.368421

0.631579

0.27451

0

0.015267

0.13245

151

7

47

21.571429

0.763359

0

0.165563

0

1

0.2

false

0

0.2

0.6

1

0

null

1

0

1

0

null

0

1

0

6

1198fa49430f402b6046690066983f8f6c69ea77

218

py

Python

src/sqlalchemy_fp/setup_with_session.py

jackfirth/sqlalchemy-fp

d095f644431ebaa3c698e3aa37e28189d4772772

[ "MIT" ]

null

src/sqlalchemy_fp/setup_with_session.py

jackfirth/sqlalchemy-fp

d095f644431ebaa3c698e3aa37e28189d4772772

[ "MIT" ]

null

src/sqlalchemy_fp/setup_with_session.py

jackfirth/sqlalchemy-fp

d095f644431ebaa3c698e3aa37e28189d4772772

[ "MIT" ]

null

from __future__ import absolute_import from sqlalchemy.orm import sessionmaker from .with_session_from import with_session_from def setup_with_session(engine): return with_session_from(sessionmaker(bind=engine))

27.25

55

0.853211

30

218

5.766667

0.466667

0.254335

0.260116

0

0.100917

218

7

56

31.142857

0.882653

0

1

0.2

false

0

0.6

0.2

1

0

null

1

0

1

0

null

0

1

0

6

11c4cefd849149465abe5ce78f36bd7bdac9dab7

71

py

Python

src/tests/TestFlexioFlowConfig.py

flexiooss/flexio-flow

47491c7e5b49a02dc859028de0d486edc0014b26

[ "Apache-2.0" ]

null

src/tests/TestFlexioFlowConfig.py

flexiooss/flexio-flow

47491c7e5b49a02dc859028de0d486edc0014b26

[ "Apache-2.0" ]

44

2019-04-05T06:08:15.000Z

2021-09-13T19:37:49.000Z

src/tests/TestFlexioFlowConfig.py

flexiooss/flexio-flow

47491c7e5b49a02dc859028de0d486edc0014b26

[ "Apache-2.0" ]

null

import unittest class TestFlexioFlowConfig(unittest.TestCase): pass

14.2

46

0.830986

7

71

8.428571

0.857143

0

0.112676

71

5

47

14.2

0.936508

0

1

0

true

0.333333

0

0.666667

0

1

0

null

0

1

0

null

0

1

0

1

0

6

eef9a7e394a497907d65359f804d4d824d647dea

134

py

Python

gsfarc/gptool/parameter/templates/floatarray.py

geospatial-services-framework/gsfpyarc

5ef69299fbc0b763ad4c1857ceac3ff087c0dc14

[ "MIT" ]

1

2021-11-06T18:36:28.000Z

gsfarc/gptool/parameter/templates/floatarray.py

geospatial-services-framework/gsfpyarc

5ef69299fbc0b763ad4c1857ceac3ff087c0dc14

[ "MIT" ]

null

gsfarc/gptool/parameter/templates/floatarray.py

geospatial-services-framework/gsfpyarc

5ef69299fbc0b763ad4c1857ceac3ff087c0dc14

[ "MIT" ]

null

""" """ from .basicarray import BASICARRAY class FLOATARRAY(BASICARRAY): pass def template(): return FLOATARRAY('GPDouble')

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py

Python

libsaas/services/stripe/__init__.py

MidtownFellowship/libsaas

541bb731b996b08ede1d91a235cb82895765c38a

[ "MIT" ]

155

2015-01-27T15:17:59.000Z

2022-02-20T00:14:08.000Z

libsaas/services/stripe/__init__.py

MidtownFellowship/libsaas

541bb731b996b08ede1d91a235cb82895765c38a

[ "MIT" ]

14

2015-01-12T08:22:37.000Z

2021-06-16T19:49:31.000Z

libsaas/services/stripe/__init__.py

MidtownFellowship/libsaas

541bb731b996b08ede1d91a235cb82895765c38a

[ "MIT" ]

43

2015-01-28T22:41:45.000Z

2021-09-21T04:44:26.000Z

from .service import Stripe

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017d813ce598faf8267045475d05bc2ecd51a224

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py

Python

Voltron/unit_tests/Algorithms/test_binary_search.py

ernestyalumni/HrdwCCppCUDA

17ed937dea06431a4d5ca103f993ea69a6918734

[ "MIT" ]

1

2018-02-09T19:44:51.000Z

Voltron/unit_tests/Algorithms/test_binary_search.py

ernestyalumni/HrdwCCppCUDA

17ed937dea06431a4d5ca103f993ea69a6918734

[ "MIT" ]

null

Voltron/unit_tests/Algorithms/test_binary_search.py

ernestyalumni/HrdwCCppCUDA

17ed937dea06431a4d5ca103f993ea69a6918734

[ "MIT" ]

null

from Voltron.Algorithms.binary_search import ( binary_search, binary_search_iterative, binary_search_recursive, calculate_midpoint, quick_calculate_midpoint_index) import pytest def test_calculate_midpoint_works_for_odd_number_of_elements(): x = calculate_midpoint(0, 4) assert x == 2 x = calculate_midpoint(0, 6) assert x == 3 x = calculate_midpoint(1, 5) assert x == 3 x = calculate_midpoint(1, 7) assert x == 4 x = calculate_midpoint(2, 6) assert x == 4 x = calculate_midpoint(2, 8) assert x == 5 def test_calculate_midpoint_gets_left_index_for_even_number_of_elements(): x = calculate_midpoint(0, 3) assert x == 1 x = calculate_midpoint(0, 5) assert x == 2 x = calculate_midpoint(1, 6) assert x == 3 x = calculate_midpoint(1, 8) assert x == 4 x = calculate_midpoint(2, 7) assert x == 4 x = calculate_midpoint(2, 9) assert x == 5 def test_quick_calculate_midpoint_index_for_odd_number_of_elements(): x = quick_calculate_midpoint_index(0, 4) assert x == 2 x = quick_calculate_midpoint_index(0, 6) assert x == 3 x = quick_calculate_midpoint_index(1, 5) assert x == 3 x = quick_calculate_midpoint_index(1, 7) assert x == 4 x = quick_calculate_midpoint_index(2, 6) assert x == 4 x = quick_calculate_midpoint_index(2, 8) assert x == 5 def test_quick_calculate_midpoint_index_for_even_number_of_elements(): x = quick_calculate_midpoint_index(0, 3) assert x == 1 x = quick_calculate_midpoint_index(0, 5) assert x == 2 x = quick_calculate_midpoint_index(1, 6) assert x == 3 x = quick_calculate_midpoint_index(1, 8) assert x == 4 x = quick_calculate_midpoint_index(2, 7) assert x == 4 x = quick_calculate_midpoint_index(2, 9) assert x == 5 def test_binary_search_recursive_works(): element = 18 array = [1, 2, 5, 7, 13, 15, 16, 18, 24, 28, 29] result = binary_search_recursive(array, element, 0, len(array) - 1) assert result == 7 # Another example. element = 20 array = [4, 14, 16, 17, 19, 21, 24, 28, 30, 35, 36, 38, 39, 40, 41, 43] result = binary_search_recursive(array, element, 0, len(array) - 1) assert result == None def test_binary_search_iterative_works(): element = 18 array = [1, 2, 5, 7, 13, 15, 16, 18, 24, 28, 29] result = binary_search_iterative(array, element) assert result == 7 # Another example. element = 20 array = [4, 14, 16, 17, 19, 21, 24, 28, 30, 35, 36, 38, 39, 40, 41, 43] result = binary_search_iterative(array, element) assert result == None

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6d85fb203936a09fec60dbccfd35255608e5ecac

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py

Python

src/tso/tsocli/command/__init__.py

elijah-ward/TSO

610565a32284cab23e9262c3431ce6d34116bfcf

[ "MIT" ]

4

2018-11-05T21:36:08.000Z

2019-04-15T13:05:39.000Z

src/tso/tsocli/command/__init__.py

elijah-ward/TSO

610565a32284cab23e9262c3431ce6d34116bfcf

[ "MIT" ]

2

2019-02-23T07:13:40.000Z

2019-04-07T17:50:44.000Z

src/tso/tsocli/command/__init__.py

elijah-ward/TSO

610565a32284cab23e9262c3431ce6d34116bfcf

[ "MIT" ]

2

2020-12-09T07:03:09.000Z

2021-07-17T02:32:46.000Z

from .pipeline import cli_pipeline

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6d9447fc40311c76af67867565bd9d30f8ca2d3f

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py

Python

maha/parsers/functions/__init__.py

saedx1/Maha

6158b07cd0d4ff3dcb529c9c49757f8271dc776e

[ "BSD-3-Clause" ]

152

2021-09-18T08:18:47.000Z

2022-03-14T13:23:17.000Z

maha/parsers/functions/__init__.py

saedx1/Maha

6158b07cd0d4ff3dcb529c9c49757f8271dc776e

[ "BSD-3-Clause" ]

65

2021-09-20T06:00:41.000Z

2022-03-20T22:44:39.000Z

maha/parsers/functions/__init__.py

saedx1/Maha

6158b07cd0d4ff3dcb529c9c49757f8271dc776e

[ "BSD-3-Clause" ]

10

2021-09-18T11:56:57.000Z

2021-11-20T09:05:16.000Z

from .parse_dimensions import * from .parse_fn import *

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6db1ace45f02c1eed6ed534d5be30ab9f13fb813

258

py

Python

pystibmvib/__init__.py

helldog136/pystibmvib

390f58c13bec3b1b868955cde1d88fb99d649808

[ "MIT" ]

4

2020-02-28T00:28:54.000Z

2021-03-03T17:13:53.000Z

pystibmvib/__init__.py

helldog136/pystibmvib

390f58c13bec3b1b868955cde1d88fb99d649808

[ "MIT" ]

3

2020-03-05T09:03:36.000Z

2020-05-25T19:59:12.000Z

pystibmvib/__init__.py

helldog136/pystibmvib

390f58c13bec3b1b868955cde1d88fb99d649808

[ "MIT" ]

3

2020-03-26T16:56:28.000Z

2021-03-03T15:01:35.000Z

"""Initialize the package.""" from pystibmvib.client import AbstractSTIBAPIClient, STIBAPIClient from pystibmvib.service import STIBService, InvalidLineFilterException from pystibmvib.service import ShapefileService from .domain import * NAME = "pystibmvib"

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6

6db6657ac576abbe50f872b403fdf4609693666f

155

py

Python

exercicios/ex097 - um print especial.py

ErisonSandro/Exercicios-Python

7fd391fa87a25635cf85921b303f87d9f46854ee

[ "MIT" ]

null

exercicios/ex097 - um print especial.py

ErisonSandro/Exercicios-Python

7fd391fa87a25635cf85921b303f87d9f46854ee

[ "MIT" ]

null

exercicios/ex097 - um print especial.py

ErisonSandro/Exercicios-Python

7fd391fa87a25635cf85921b303f87d9f46854ee

[ "MIT" ]

null

def escreva(tam): print('='*len(tam)) print(tam) print('='*len(tam)) escreva('Nene Sandro') escreva('Curso python do youtube') escreva('CeV')

17.222222

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155

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null

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1

0

6

6dc793dbceaaa7c94a1de5db2221d1c7637d04e6

33

py

Python

sepc/self_mmdet/ops/dcn/__init__.py

implus/SEPC

51e24ace1653cba6d3bc0ab536c6adb3b956c8dd

[ "Apache-2.0" ]

2

2020-04-27T06:30:32.000Z

2020-04-27T06:30:34.000Z

sepc/self_mmdet/ops/dcn/__init__.py

yhl41001/SEPC

51e24ace1653cba6d3bc0ab536c6adb3b956c8dd

[ "Apache-2.0" ]

null

sepc/self_mmdet/ops/dcn/__init__.py

yhl41001/SEPC

51e24ace1653cba6d3bc0ab536c6adb3b956c8dd

[ "Apache-2.0" ]

1

2021-03-23T01:39:30.000Z

from .sepc_dconv import sepc_conv

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1

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1

0

1

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6

6ddcebed8ed47e00da600032d6bb96cc07e6662a

118

py

Python

data/__all_models.py

k-shnyrev/Mos-Quest

c48b05433f493fa95af98d9ae837583f4d28af94

[ "MIT" ]

null

data/__all_models.py

k-shnyrev/Mos-Quest

c48b05433f493fa95af98d9ae837583f4d28af94

[ "MIT" ]

null

data/__all_models.py

k-shnyrev/Mos-Quest

c48b05433f493fa95af98d9ae837583f4d28af94

[ "MIT" ]

null

""" Подключает модели для работы с базой данных """ from . import users from . import questions from . import answers

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a304eaa2bcff84ca69e7d91c6856dd68f1a294bc

21

py

Python

tests/workflowtests/test_files/workflow_manager/wf_instances_prepared/instance1/t1.py

soerenray/MatFlow

db0c8311262738264f1c525b8266a2bf52a7b7e6

[ "MIT" ]

null

tests/workflowtests/test_files/workflow_manager/wf_instances_prepared/instance1/t1.py

soerenray/MatFlow

db0c8311262738264f1c525b8266a2bf52a7b7e6

[ "MIT" ]

null

tests/workflowtests/test_files/workflow_manager/wf_instances_prepared/instance1/t1.py

soerenray/MatFlow

db0c8311262738264f1c525b8266a2bf52a7b7e6

[ "MIT" ]

null

"im a dag def file!"

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0.8125

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0

null

0

1

0

6

0967a8aa3a6e383b321020d6670d35cc747826b5

2,031

py

Python

gameComponents/gameComparison.py

Ty-Allen/Allen_T_RPS_Fall2020

ed955896504af65c55829095d05a0599e7284631

[ "MIT" ]

null

gameComponents/gameComparison.py

Ty-Allen/Allen_T_RPS_Fall2020

ed955896504af65c55829095d05a0599e7284631

[ "MIT" ]

null

gameComponents/gameComparison.py

Ty-Allen/Allen_T_RPS_Fall2020

ed955896504af65c55829095d05a0599e7284631

[ "MIT" ]

null

from gameComponents import gameVars from random import randint # # this will be the AI choice -> a random pick from the choices array # computer_choice = gameVars.choices[randint(0, 2)] # # just validating that I can make a choice # # print outputs whatever is inside the brackets # # check to see what the user input # print("user chose: " + gameVars.user_choice) # # validate that the random choice worked for the AI # print("AI chose: " + computer_choice) def comparison(user_choice): # this will be the AI choice -> a random pick from the choices array computer_choice = gameVars.choices[randint(0, 2)] # just validating that I can make a choice # print outputs whatever is inside the brackets # check to see what the user input print("user chose: " + gameVars.user_choice) # validate that the random choice worked for the AI print("AI chose: " + computer_choice) if (computer_choice == gameVars.user_choice): print("tie") elif (computer_choice == "rock"): if (gameVars.user_choice == "scissors"): gameVars.user_lives -= 1 print("You lose! player lives:", gameVars.user_lives) else: print(""" _______ ---' ____)____ ______) _______) _______) ---.__________) You win! """) gameVars.computer_lives -= 1 elif (computer_choice == "paper"): if (gameVars.user_choice == "scissors"): print(""" _______ ---' ____)____ ______) __________) (____) ---.__(___) You win! """) gameVars.computer_lives -= 1 else: gameVars.user_lives -= 1 print("You lose! player lives:", gameVars.user_lives) elif (computer_choice == "scissors"): if (gameVars.user_choice == "paper"): gameVars.user_lives -= 1 print("You lose! player lives:", gameVars.user_lives) else: print(""" _______ ---' ____) (_____) (_____) (____) ---.__(___) You win! """) gameVars.computer_lives -= 1

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0981df23baad1e3539b52fe250ded26d372793bc

31

py

Python

dttpy/__init__.py

neouniverse/dttpy

c5ff8870d796d84b39c4e6f82ec4eefe523cc3e7

[ "MIT" ]

null

dttpy/__init__.py

neouniverse/dttpy

c5ff8870d796d84b39c4e6f82ec4eefe523cc3e7

[ "MIT" ]

null

dttpy/__init__.py

neouniverse/dttpy

c5ff8870d796d84b39c4e6f82ec4eefe523cc3e7

[ "MIT" ]

null

# from .dttdata import DttData

10.333333

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1

0

1

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6

0994a1d7e4bb4b426765a910c6895428b3f3c6ec

22

py

Python

projecc/__init__.py

logan-pearce/projecc

b75005124493309402e7102f43acab360c994f14

[ "MIT" ]

null

projecc/__init__.py

logan-pearce/projecc

b75005124493309402e7102f43acab360c994f14

[ "MIT" ]

null

projecc/__init__.py

logan-pearce/projecc

b75005124493309402e7102f43acab360c994f14

[ "MIT" ]

null

from .projecc import *

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null

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1

0

1

0

1

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6

099e8cb176868b56924e1749e8be87b8a43b305a

31

py

Python

streamsvg/__init__.py

ysig/streamsvg

ee906fadacf0b016e519548cb2fea21c27748f51

[ "MIT" ]

null

streamsvg/__init__.py

ysig/streamsvg

ee906fadacf0b016e519548cb2fea21c27748f51

[ "MIT" ]

null

streamsvg/__init__.py

ysig/streamsvg

ee906fadacf0b016e519548cb2fea21c27748f51

[ "MIT" ]

null

from .StreamSVG import Drawing

15.5

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1

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1

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09f43206a23393dc138c5147013c4fe0a841a1a1

189

py

Python

iris_sdk/models/data/listing_name.py

NumberAI/python-bandwidth-iris

0e05f79d68b244812afb97e00fd65b3f46d00aa3

[ "MIT" ]

2

2020-04-13T13:47:59.000Z

2022-02-23T20:32:41.000Z

iris_sdk/models/data/listing_name.py

bandwidthcom/python-bandwidth-iris

dbcb30569631395041b92917252d913166f7d3c9

[ "MIT" ]

5

2020-09-18T20:59:24.000Z

2021-08-25T16:51:42.000Z

iris_sdk/models/data/listing_name.py

bandwidthcom/python-bandwidth-iris

dbcb30569631395041b92917252d913166f7d3c9

[ "MIT" ]

5

2018-12-12T14:39:50.000Z

2020-11-17T21:42:29.000Z

#!/usr/bin/env python from iris_sdk.models.base_resource import BaseData from iris_sdk.models.maps.listing_name import ListingNameMap class ListingName(ListingNameMap, BaseData): pass

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6

1129b3d57efab1e8a920d2384648783ef2ad4acd

272

py

Python

neuralcorefres/feature_extraction/__init__.py

RyanElliott10/NeuralCorefRes

a0ca5c614cc1638ab7bd230fcfefbd26120ed800

[ "MIT" ]

2

2020-02-23T01:00:22.000Z

2020-06-17T21:39:57.000Z

neuralcorefres/feature_extraction/__init__.py

RyanElliott10/NeuralCorefRes

a0ca5c614cc1638ab7bd230fcfefbd26120ed800

[ "MIT" ]

9

2020-02-27T01:08:55.000Z

2022-03-12T00:16:12.000Z

neuralcorefres/feature_extraction/__init__.py

RyanElliott10/NeuralCorefRes

a0ca5c614cc1638ab7bd230fcfefbd26120ed800

[ "MIT" ]

null

from neuralcorefres.feature_extraction.gender_classifier import * from neuralcorefres.feature_extraction.stanford_parse_api import * from neuralcorefres.feature_extraction.util import * __all__ = [ "GenderClassifier", "StanfordParseAPI", "findall_entities" ]

27.2

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3a0886451e0c34d2a759ea54b7b873f34baba340

3,211

py

Python

tests/test_find.py

arup-group/mc

50b8faa8b9d40dece88e0a27f911edd427ebc064

[ "MIT" ]

null

tests/test_find.py

arup-group/mc

50b8faa8b9d40dece88e0a27f911edd427ebc064

[ "MIT" ]

12

2021-12-14T15:10:43.000Z

2022-03-31T13:39:25.000Z

tests/test_find.py

arup-group/mc

50b8faa8b9d40dece88e0a27f911edd427ebc064

[ "MIT" ]

null

""" Find method tests. """ import pytest import env env.set_module() from mc.base import BaseConfig def test_test_env_paths(): assert env.test_xml_path.exists() @pytest.fixture def config(): return BaseConfig(path=env.test_xml_path) def test_find_nothing(config): assert config.find('') == [] def test_find_module(config): assert config.find("controler")[0].class_type == 'module' def test_find_param_at_module_level(config): params = config.find("transitModes") assert len(params) == 1 assert params[0].value == 'bus,train' def test_find_param_at_paramset_level(config): params = config.find("earlyDeparture") assert len(params) == 2 assert params[0].value == '-0.0' def test_find_module_param_at_module_level(config): params = config.find("transit/transitModes") assert len(params) == 1 assert params[0].value == 'bus,train' def test_find_all_param_at_module_level(config): params = config.find("*/transitModes") assert len(params) == 1 assert params[0].value == 'bus,train' def test_find_paramset_at_module_level(config): paramsets = config.find("scoringParameters:default") assert len(paramsets) == 1 assert paramsets[0].class_type == 'paramset' def test_find_paramsets_at_module_level(config): paramsets = config.find("scoringParameters:*") assert len(paramsets) == 2 assert paramsets[0].class_type == 'paramset' def test_find_module_paramset_at_module_level(config): paramsets = config.find("planCalcScore/scoringParameters:default") assert len(paramsets) == 1 assert paramsets[0].class_type == 'paramset' def test_find_module_paramsets_at_module_level(config): paramsets = config.find("planCalcScore/scoringParameters:*") assert len(paramsets) == 2 assert paramsets[0].class_type == 'paramset' def test_find_all_paramset_at_module_level(config): paramsets = config.find("*/scoringParameters:default") assert len(paramsets) == 1 assert paramsets[0].class_type == 'paramset' def test_find_all_paramsets_at_module_level(config): paramsets = config.find("*/scoringParameters:*") assert len(paramsets) == 2 assert paramsets[0].class_type == 'paramset' def test_find_paramsets_at_paramsets_level(config): paramsets = config.find("scoringParameters:*/activityParams:*") assert len(paramsets) == 6 assert paramsets[0].class_type == 'paramset' def test_find_paramset_at_paramsets_level(config): paramsets = config.find("scoringParameters:default/activityParams:*") assert len(paramsets) == 3 assert paramsets[0].class_type == 'paramset' def test_find_param_at_paramsets_level(config): paramsets = config.find("scoringParameters:default/activityParams:work/priority") assert len(paramsets) == 1 assert paramsets[0].value == '1.0' def test_find_params_at_paramsets_level(config): paramsets = config.find("activityParams:work/priority") assert len(paramsets) == 2 assert paramsets[0].value == '1.0' def test_find_params_at_nested_paramsets_level(config): paramsets = config.find("scoringParameters:default/priority") assert len(paramsets) == 3 assert paramsets[0].value == '1.0'

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py

Python

odin/visual/__init__.py

trungnt13/odin_old

e5f44f9b6c483d6498767899315ae56e06fe36c4

[ "MIT" ]

2

2016-02-24T20:41:08.000Z

2016-02-29T02:25:16.000Z

odin/visual/__init__.py

trungnt13/odin

e5f44f9b6c483d6498767899315ae56e06fe36c4

[ "MIT" ]

null

odin/visual/__init__.py

trungnt13/odin

e5f44f9b6c483d6498767899315ae56e06fe36c4

[ "MIT" ]

null

from .bashplot import * from .figures import * from .graph import *

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py

Python

theano/sandbox/cuda/tests/test_vector_matrix_dot.py

josharian/Theano

724a25692090fee26eebf72f5d046ca8662089c1

[ "BSD-3-Clause" ]

1

2016-05-07T14:52:38.000Z

theano/sandbox/cuda/tests/test_vector_matrix_dot.py

josharian/Theano

724a25692090fee26eebf72f5d046ca8662089c1

[ "BSD-3-Clause" ]

null

theano/sandbox/cuda/tests/test_vector_matrix_dot.py

josharian/Theano

724a25692090fee26eebf72f5d046ca8662089c1

[ "BSD-3-Clause" ]

null

import numpy import theano # Skip test if cuda_ndarray is not available. from nose.plugins.skip import SkipTest import theano.sandbox.cuda as cuda_ndarray if cuda_ndarray.cuda_available == False: raise SkipTest('Optional package cuda disabled') import theano.sandbox.cuda as cuda import theano.sandbox.cuda.blas as blasop ### Tolerance factor used in this tests !!! atol = 1e-6 ########################## if theano.config.mode=='FAST_COMPILE': mode_with_gpu = theano.compile.mode.get_mode('FAST_RUN').including('gpu') mode_without_gpu = theano.compile.mode.get_mode('FAST_RUN').excluding('gpu') else: mode_with_gpu = theano.compile.mode.get_default_mode().including('gpu') mode_without_gpu = theano.compile.mode.get_default_mode().excluding('gpu') def test_dot_vm(): ''' Test vector dot matrix ''' v = theano.shared( numpy.array(numpy.random.rand(2), dtype='float32')) m = theano.shared( numpy.array(numpy.random.rand(2,5), dtype='float32')) no_gpu_f = theano.function([], theano.dot(v,m), mode = mode_without_gpu) gpu_f = theano.function([], theano.dot(v,m), mode = mode_with_gpu) #gpu_f2 is needed to test the case when the input is not on the gpu #but the output is moved to the gpu. gpu_f2 = theano.function([], cuda.gpu_from_host(theano.dot(v,m)), mode = mode_with_gpu) # Assert they produce the same output assert numpy.allclose(no_gpu_f(), gpu_f(), atol = atol) assert numpy.allclose(no_gpu_f(), gpu_f2(), atol = atol) # Assert that the gpu version actually uses gpu assert sum([isinstance(node.op, blasop.GpuDot22) for node in gpu_f.maker.env.toposort() ]) == 1 assert sum([isinstance(node.op, blasop.GpuDot22) for node in gpu_f2.maker.env.toposort() ]) == 1 def test_dot_mv(): ''' Test matrix dot vector ''' v = theano.shared( numpy.array(numpy.random.rand(2), dtype='float32')) m = theano.shared( numpy.array(numpy.random.rand(5,2), dtype='float32')) no_gpu_f = theano.function([], theano.dot(m,v), mode = mode_without_gpu) gpu_f = theano.function([], theano.dot(m,v), mode = mode_with_gpu) #gpu_f2 is needed to test the case when the input is not on the gpu #but the output is moved to the gpu. gpu_f2 = theano.function([], cuda.gpu_from_host(theano.dot(m,v)), mode = mode_with_gpu) # Assert they produce the same output assert numpy.allclose(no_gpu_f(), gpu_f(), atol = atol) assert numpy.allclose(no_gpu_f(), gpu_f2(), atol = atol) # Assert that the gpu version actually uses gpu assert sum([isinstance(node.op, blasop.GpuDot22) for node in gpu_f.maker.env.toposort() ]) == 1 assert sum([isinstance(node.op, blasop.GpuDot22) for node in gpu_f2.maker.env.toposort() ]) == 1 def test_gemv1(): ''' test vector1+dot(matrix,vector2) ''' v1 = theano.tensor._shared( numpy.array(numpy.random.rand(2) , dtype='float32')) v2 = theano.tensor._shared( numpy.array(numpy.random.rand(5) , dtype='float32')) m = theano.tensor._shared( numpy.array(numpy.random.rand(5,2), dtype='float32')) no_gpu_f = theano.function([], v2+theano.dot(m,v1), mode = mode_without_gpu) gpu_f = theano.function([], v2+theano.dot(m,v1), mode = mode_with_gpu) #gpu_f2 is needed to test the case when the input is not on the gpu #but the output is moved to the gpu. gpu_f2 = theano.function([], cuda.gpu_from_host(v2+theano.dot(m,v1)), mode = mode_with_gpu) # Assert they produce the same output assert numpy.allclose(no_gpu_f(), gpu_f(), atol = atol) assert numpy.allclose(no_gpu_f(), gpu_f2(), atol = atol) # Assert that the gpu version actually uses gpu assert sum([node.op is cuda.blas.gpu_gemm_inplace for node in gpu_f2.maker.env.toposort()]) == 1 assert sum([node.op is cuda.blas.gpu_gemm_inplace for node in gpu_f.maker.env.toposort()]) == 1 def test_gemv2(): ''' test vector1+dot(vector2,matrix) ''' v1 = theano.shared( numpy.array(numpy.random.rand(5) , dtype='float32')) v2 = theano.shared( numpy.array(numpy.random.rand(2) , dtype='float32')) m = theano.shared( numpy.array(numpy.random.rand(5,2), dtype='float32')) no_gpu_f = theano.function([], v2+theano.dot(v1,m), mode = mode_without_gpu) gpu_f = theano.function([], v2+theano.dot(v1,m), mode = mode_with_gpu) #gpu_f2 is needed to test the case when the input is not on the gpu #but the output is moved to the gpu. gpu_f2 = theano.function([], cuda.gpu_from_host(v2+theano.dot(v1,m)), mode = mode_with_gpu) # Assert they produce the same output assert numpy.allclose(no_gpu_f(), gpu_f(), atol = atol) assert numpy.allclose(no_gpu_f(), gpu_f2(), atol = atol) # Assert that the gpu version actually uses gpu assert sum([node.op is cuda.blas.gpu_gemm_inplace for node in gpu_f2.maker.env.toposort()]) == 1 assert sum([node.op is cuda.blas.gpu_gemm_inplace for node in gpu_f.maker.env.toposort()]) == 1 if __name__=='__main__': test_dot_vm() test_dot_mv() test_gemv1() test_gemv2()

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py

Python

holobot/discord/sdk/commands/enums/__init__.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

1

2021-05-24T00:17:46.000Z

holobot/discord/sdk/commands/enums/__init__.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

41

2021-03-24T22:50:09.000Z

2021-12-17T12:15:13.000Z

holobot/discord/sdk/commands/enums/__init__.py

rexor12/holobot

89b7b416403d13ccfeee117ef942426b08d3651d

[ "MIT" ]

null

from .option_type import OptionType

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6

28e47cdbdd9a4e8b4f31132283ecb593b8cd4329

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py

Python

pylangacq/__init__.py

terrykwon/pylangacq

edd94e72e84976992d5bbef4b1232bafc6558820

[ "MIT" ]

null

pylangacq/__init__.py

terrykwon/pylangacq

edd94e72e84976992d5bbef4b1232bafc6558820

[ "MIT" ]

null

pylangacq/__init__.py

terrykwon/pylangacq

edd94e72e84976992d5bbef4b1232bafc6558820

[ "MIT" ]

null

from pylangacq.chat import read_chat, Reader from pylangacq._version import __version__ __all__ = ["__version__", "read_chat", "Reader"]

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1

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6

28f566d5e261ebe50f186052f69726a9f605fc79

21

py

Python

dist/micropy-cli/frozen/random.py

kevindawson/Pico-Stub

6f9112779d4d81f821a3af273a450b9329ccdbab

[ "Apache-2.0" ]

19

2021-01-25T23:56:09.000Z

2022-02-21T13:55:16.000Z

dist/micropy-cli/frozen/random.py

kevindawson/Pico-Stub

6f9112779d4d81f821a3af273a450b9329ccdbab

[ "Apache-2.0" ]

18

2021-02-06T09:03:09.000Z

2021-10-04T16:36:35.000Z

dist/micropy-cli/frozen/random.py

kevindawson/Pico-Stub

6f9112779d4d81f821a3af273a450b9329ccdbab

[ "Apache-2.0" ]

6

2021-01-26T08:41:47.000Z

2021-04-27T11:33:33.000Z

from urandom import *

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0.809524

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6

3a6d86034bb15256a65842b761c119d5b60d213e

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py

Python

ding/framework/middleware/__init__.py

Hcnaeg/DI-engine

aba0c629f87649854091e9e59d948f83962e3e1e

[ "Apache-2.0" ]

null

ding/framework/middleware/__init__.py

Hcnaeg/DI-engine

aba0c629f87649854091e9e59d948f83962e3e1e

[ "Apache-2.0" ]

null

ding/framework/middleware/__init__.py

Hcnaeg/DI-engine

aba0c629f87649854091e9e59d948f83962e3e1e

[ "Apache-2.0" ]

null

from .league_collector import league_collector from .league_dispatcher import league_dispatcher from .league_evaluator import league_evaluator from .league_learner import league_learner

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3a806423128b6794e90ae8e23560afc1d1c061f5

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py

Python

pack/__init__.py

translationalneurosurgery/teach-pypackaging

442d54490c9e54b2e650f504811d9b8eee6d8163

[ "MIT" ]

null

pack/__init__.py

translationalneurosurgery/teach-pypackaging

442d54490c9e54b2e650f504811d9b8eee6d8163

[ "MIT" ]

null

pack/__init__.py

translationalneurosurgery/teach-pypackaging

442d54490c9e54b2e650f504811d9b8eee6d8163

[ "MIT" ]

null

from pathlib import Path print("Importing from", Path(__file__))

16.5

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6

3a8e2a5a14b3f53ded0be857f20f503c306ef977

115

py

Python

mmcq/color.py

kanghyojun/mmcq.py

76c898a1717f3e8c985baa3d66758e0586e0979f

[ "MIT" ]

17

2019-01-17T19:03:18.000Z

2021-12-05T23:23:02.000Z

mmcq/color.py

admire93/mmcq.py

76c898a1717f3e8c985baa3d66758e0586e0979f

[ "MIT" ]

7

2015-03-14T06:42:49.000Z

2017-07-11T07:51:37.000Z

mmcq/color.py

admire93/mmcq.py

76c898a1717f3e8c985baa3d66758e0586e0979f

[ "MIT" ]

7

2015-02-06T21:52:46.000Z

2017-07-11T09:18:50.000Z

from .constant import SIGBITS def get_color_index(r, g, b): return (r << (2 * SIGBITS)) + (g << SIGBITS) + b

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py

Python

venv/lib/python3.8/site-packages/aiohttp/client_proto.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

null

venv/lib/python3.8/site-packages/aiohttp/client_proto.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

null

venv/lib/python3.8/site-packages/aiohttp/client_proto.py

Retraces/UkraineBot

3d5d7f8aaa58fa0cb8b98733b8808e5dfbdb8b71

[ "MIT" ]

null

/home/runner/.cache/pip/pool/21/e9/3f/66e4ebff6c45a0ab77d33bde381875c58b7a89713b5d957050f8825d3b

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3ad604b2a85c05426bea159b69c4870072ae5776

139

py

Python

apps/main/context_processors.py

wowkin2/django-template

7fc6b8ba6123b629c6242edf41f98fc35a81c672

[ "MIT" ]

null

apps/main/context_processors.py

wowkin2/django-template

7fc6b8ba6123b629c6242edf41f98fc35a81c672

[ "MIT" ]

null

apps/main/context_processors.py

wowkin2/django-template

7fc6b8ba6123b629c6242edf41f98fc35a81c672

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- from django.conf import settings def debug(context): return {'DEBUG': settings.DEBUG}

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3aeda6fb01c15aef433e4777929db98c19553540

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py

Python

xitorch/interpolate/__init__.py

mfkasim91/lintorch

7a7da4b960e83c07e45ddb999da99510d3c9e909

[ "MIT" ]

4

2020-10-15T15:07:54.000Z

2022-01-29T23:01:10.000Z

xitorch/interpolate/__init__.py

mfkasim91/lintorch

7a7da4b960e83c07e45ddb999da99510d3c9e909

[ "MIT" ]

7

2020-09-16T11:44:34.000Z

2020-09-24T13:17:19.000Z

xitorch/interpolate/__init__.py

mfkasim91/lintorch

7a7da4b960e83c07e45ddb999da99510d3c9e909

[ "MIT" ]

2

2020-09-17T09:41:33.000Z

2020-09-17T10:00:40.000Z

from xitorch.interpolate.interp1 import *

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aafb5a0b80ebf1847a0d3ea04407d381c52e1429

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py

Python

tests/tests.py

MCXA/PhenotypeCV

5e0bc86682aa7ab85bbdb5d5981f7e67a4f71b64

[ "MIT" ]

null

tests/tests.py

MCXA/PhenotypeCV

5e0bc86682aa7ab85bbdb5d5981f7e67a4f71b64

[ "MIT" ]

null

tests/tests.py

MCXA/PhenotypeCV

5e0bc86682aa7ab85bbdb5d5981f7e67a4f71b64

[ "MIT" ]

1

2020-01-17T04:52:54.000Z

#!/usr/bin/env python import pytest import os import shutil import numpy as np import cv2 from plantcv import plantcv as pcv import plantcv.learn # Import matplotlib and use a null Template to block plotting to screen # This will let us test debug = "plot" import matplotlib matplotlib.use('Template', warn=False) TEST_DATA = os.path.join(os.path.dirname(os.path.abspath(__file__)), "data") TEST_TMPDIR = os.path.join(os.path.dirname(os.path.abspath(__file__)), "..", ".cache") TEST_COLOR_DIM = (2056, 2454, 3) TEST_GRAY_DIM = (2056, 2454) TEST_BINARY_DIM = TEST_GRAY_DIM TEST_INPUT_COLOR = "input_color_img.jpg" TEST_INPUT_GRAY = "input_gray_img.jpg" TEST_INPUT_GRAY_SMALL = "input_gray_img_small.jpg" TEST_INPUT_BINARY = "input_binary_img.png" TEST_INPUT_BAYER = "bayer_img.png" TEST_INPUT_ROI = "input_roi.npz" TEST_INPUT_CONTOURS = "input_contours.npz" TEST_INPUT_CONTOURS1 = "input_contours1.npz" TEST_VIS = "VIS_SV_0_z300_h1_g0_e85_v500_93054.png" TEST_NIR = "NIR_SV_0_z300_h1_g0_e15000_v500_93059.png" TEST_VIS_TV = "VIS_TV_0_z300_h1_g0_e85_v500_93054.png" TEST_NIR_TV = "NIR_TV_0_z300_h1_g0_e15000_v500_93059.png" TEST_INPUT_MASK = "input_mask.png" TEST_INPUT_MASK_RESIZE = "input_mask_resize.png" TEST_INPUT_NIR_MASK = "input_nir.png" TEST_INPUT_FDARK = "FLUO_TV_dark.png" TEST_INPUT_FDARK_LARGE = "FLUO_TV_DARK_large" TEST_INPUT_FMIN = "FLUO_TV_min.png" TEST_INPUT_FMAX = "FLUO_TV_max.png" TEST_INPUT_FMASK = "FLUO_TV_MASK.png" TEST_INTPUT_GREENMAG = "input_green-magenta.jpg" TEST_INTPUT_MULTI = "multi_ori_image.jpg" TEST_INPUT_MULTI_OBJECT = "roi_objects.npz" TEST_INPUT_MULTI_CONTOUR = "multi_contours.npz" TEST_INPUT_ClUSTER_CONTOUR = "clusters_i.npz" TEST_INPUT_MULTI_HIERARCHY = "multi_hierarchy.npz" TEST_INPUT_GENOTXT = "cluster_names.txt" TEST_INPUT_GENOTXT_TOO_MANY = "cluster_names_too_many.txt" TEST_INPUT_CROPPED = 'cropped_img.jpg' TEST_INPUT_CROPPED_MASK = 'cropped-mask.png' TEST_INPUT_MARKER = 'seed-image.jpg' TEST_FOREGROUND = "TEST_FOREGROUND.jpg" TEST_BACKGROUND = "TEST_BACKGROUND.jpg" TEST_PDFS = "naive_bayes_pdfs.txt" TEST_PDFS_BAD = "naive_bayes_pdfs_bad.txt" TEST_VIS_SMALL = "setaria_small_vis.png" TEST_MASK_SMALL = "setaria_small_mask.png" TEST_VIS_COMP_CONTOUR = "setaria_composed_contours.npz" TEST_ACUTE_RESULT = np.asarray([[[119, 285]], [[151, 280]], [[168, 267]], [[168, 262]], [[171, 261]], [[224, 269]], [[246, 271]], [[260, 277]], [[141, 248]], [[183, 194]], [[188, 237]], [[173, 240]], [[186, 260]], [[147, 244]], [[163, 246]], [[173, 268]], [[170, 272]], [[151, 320]], [[195, 289]], [[228, 272]], [[210, 272]], [[209, 247]], [[210, 232]]]) TEST_VIS_SMALL_PLANT = "setaria_small_plant_vis.png" TEST_MASK_SMALL_PLANT = "setaria_small_plant_mask.png" TEST_VIS_COMP_CONTOUR_SMALL_PLANT = "setaria_small_plant_composed_contours.npz" TEST_SAMPLED_RGB_POINTS = "sampled_rgb_points.txt" TEST_TARGET_IMG = "target_img.png" TEST_TARGET_IMG_WITH_HEXAGON = "target_img_w_hexagon.png" TEST_TARGET_IMG_TRIANGLE = "target_img copy.png" TEST_SOURCE1_IMG = "source1_img.png" TEST_SOURCE2_IMG = "source2_img.png" TEST_TARGET_MASK = "mask_img.png" TEST_TARGET_IMG_COLOR_CARD = "color_card_target.png" TEST_SOURCE2_MASK = "mask2_img.png" TEST_TARGET_MATRIX = "target_matrix.npz" TEST_SOURCE1_MATRIX = "source1_matrix.npz" TEST_SOURCE2_MATRIX = "source2_matrix.npz" TEST_MATRIX_B1 = "matrix_b1.npz" TEST_MATRIX_B2 = "matrix_b2.npz" TEST_TRANSFORM1 = "transformation_matrix1.npz" TEST_MATRIX_M1 = "matrix_m1.npz" TEST_MATRIX_M2 = "matrix_m2.npz" TEST_S1_CORRECTED = "source_corrected.png" # ########################## # Tests setup function # ########################## def setup_function(): if not os.path.exists(TEST_TMPDIR): os.mkdir(TEST_TMPDIR) # ########################## # Tests for the main package # ########################## def test_plantcv_acute(): # Read in test data mask = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR), encoding="latin1") obj_contour = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.acute(obj=obj_contour, win=5, thresh=15, mask=mask) _ = pcv.acute(obj=obj_contour, win=0, thresh=15, mask=mask) _ = pcv.acute(obj=np.array(([[213,190]],[[83,61]],[[149,246]])), win=84, thresh=192, mask=mask) _ = pcv.acute(obj=np.array(([[3, 29]], [[31, 102]], [[161, 63]])), win = 148, thresh = 56, mask = mask) _ = pcv.acute(obj=np.array(([[103, 154]], [[27, 227]], [[152, 83]])), win = 35, thresh = 0, mask = mask) # Test with debug = None pcv.params.debug = None _ = pcv.acute(obj=np.array(([[103, 154]], [[27, 227]], [[152, 83]])), win=35, thresh=0, mask=mask) _ = pcv.acute(obj=obj_contour, win=0, thresh=15, mask=mask) homology_pts = pcv.acute(obj=obj_contour, win=5, thresh=15, mask=mask) assert all([i == j] for i, j in zip(np.shape(homology_pts), (29, 1, 2))) def test_plantcv_acute_vertex(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_acute_vertex") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL)) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR), encoding="latin1") obj_contour = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.acute_vertex(obj=obj_contour, win=5, thresh=15, sep=5, img=img) _ = pcv.acute_vertex(obj=[], win=5, thresh=15, sep=5, img=img) _ = pcv.acute_vertex(obj=[], win=.01, thresh=.01, sep=1, img=img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.acute_vertex(obj=obj_contour, win=5, thresh=15, sep=5, img=img) # Test with debug = None pcv.params.debug = None acute = pcv.acute_vertex(obj=obj_contour, win=5, thresh=15, sep=5, img=img) assert all([i == j] for i, j in zip(np.shape(acute), np.shape(TEST_ACUTE_RESULT))) def test_plantcv_acute_vertex_bad_obj(): img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL)) obj_contour = np.array([]) pcv.params.debug = None result = pcv.acute_vertex(obj=obj_contour, win=5, thresh=15, sep=5, img=img) assert all([i == j] for i, j in zip(result, [0, ("NA", "NA")])) def test_plantcv_analyze_bound_horizontal(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_bound_horizontal") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) img_above_bound_only = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL_PLANT)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=300) _ = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=100) _ = pcv.analyze_bound_horizontal(img=img_above_bound_only, obj=object_contours, mask=mask, line_position=1756) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=1756) # Test with debug = None pcv.params.debug = None boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=1756) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert boundary_data[3] == 62555 def test_plantcv_analyze_bound_horizontal_grayscale_image(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with a grayscale reference image and debug="plot" pcv.params.debug = "plot" boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=1756) assert boundary_data[3] == 62555 def test_plantcv_analyze_bound_horizontal_neg_y(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with debug=None, line position that will trigger -y pcv.params.debug = "plot" _ = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=(-1000)) _ = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=(0)) boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_horizontal(img=img, obj=object_contours, mask=mask, line_position=2056) assert boundary_data[3] == 63632 def test_plantcv_analyze_bound_vertical(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_bound_vertical") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.analyze_bound_vertical(img=img, obj=object_contours, mask=mask, line_position=1000) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.analyze_bound_vertical(img=img, obj=object_contours, mask=mask, line_position=1000) # Test with debug = None pcv.params.debug = None boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_vertical(img=img, obj=object_contours, mask=mask, line_position=1000) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert boundary_data[3] == 5016 def test_plantcv_analyze_bound_vertical_grayscale_image(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with a grayscale reference image and debug="plot" pcv.params.debug = "plot" boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_vertical(img=img, obj=object_contours, mask=mask, line_position=1000) assert boundary_data[3] == 5016 def test_plantcv_analyze_bound_vertical_neg_x(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with debug="plot", line position that will trigger -x pcv.params.debug = "plot" boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_vertical(img=img, obj=object_contours, mask=mask, line_position=2454) assert boundary_data[3] == 63632 def test_plantcv_analyze_bound_vertical_small_x(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") object_contours = contours_npz['arr_0'] # Test with debug='plot', line position that will trigger -x, and two channel object pcv.params.debug = "plot" boundary_header, boundary_data, boundary_img1 = pcv.analyze_bound_vertical(img=img, obj=object_contours, mask=mask, line_position=1) assert boundary_data[3] == 0 def test_plantcv_analyze_color(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_color") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type="all") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type='rgb') _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type='lab') _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type='hsv') # Test with debug = None pcv.params.debug = None color_header, color_data, analysis_images = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type=None) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert np.sum(color_data[3]) != 0 def test_plantcv_analyze_color_incorrect_image(): img_binary = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) with pytest.raises(RuntimeError): _ = pcv.analyze_color(rgb_img=img_binary, mask=mask, bins=256, hist_plot_type=None) def test_plantcv_analyze_color_bad_hist_type(): img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) pcv.params.debug = "plot" with pytest.raises(RuntimeError): _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type='bgr') # def test_plantcv_analyze_color_incorrect_pseudo_channel(): # img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # with pytest.raises(RuntimeError): # pcv.params.debug = "plot" # _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type=None, pseudo_channel="x", # pseudo_bkg="white", filename=False) # # # def test_plantcv_analyze_color_incorrect_pseudo_background(): # img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # with pytest.raises(RuntimeError): # pcv.params.debug = "plot" # _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type=None, pseudo_channel="v", # pseudo_bkg="black", filename=False) def test_plantcv_analyze_color_incorrect_hist_plot_type(): img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) with pytest.raises(RuntimeError): pcv.params.debug = "plot" _ = pcv.analyze_color(rgb_img=img, mask=mask, bins=256, hist_plot_type="bgr") def test_plantcv_analyze_nir(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_nir") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), 0) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.analyze_nir_intensity(gray_img=np.uint16(img), mask=mask, bins=256, histplot=True) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.analyze_nir_intensity(gray_img=img, mask=mask, bins=256, histplot=False) # Test with debug = "plot" _ = pcv.analyze_nir_intensity(gray_img=img, mask=mask, bins=256, histplot=True) # Test with debug = None pcv.params.debug = None hist_header, hist_data, h_norm = pcv.analyze_nir_intensity(gray_img=img, mask=mask, bins=256, histplot=False) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert np.sum(hist_data[3]) == 63632 def test_plantcv_analyze_object(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_object") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") obj_contour = contours_npz['arr_0'] # max_obj = max(obj_contour, key=len) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) # Test with debug = None pcv.params.debug = None obj_header, obj_data, obj_images = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert obj_data[1] != 0 def test_plantcv_analyze_object_grayscale_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_object_grayscale_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), 0) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") obj_contour = contours_npz['arr_0'] # max_obj = max(obj_contour, key=len) # Test with debug = "plot" pcv.params.debug = "plot" obj_header, obj_data, obj_images = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) assert obj_data[1] != 0 def test_plantcv_analyze_object_zero_slope(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_object_zero_slope") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Create a test image img = np.zeros((50, 50, 3), dtype=np.uint8) img[10:11, 10:40, 0] = 255 mask = img[:, :, 0] obj_contour = np.array([[[10, 10]], [[11, 10]], [[12, 10]], [[13, 10]], [[14, 10]], [[15, 10]], [[16, 10]], [[17, 10]], [[18, 10]], [[19, 10]], [[20, 10]], [[21, 10]], [[22, 10]], [[23, 10]], [[24, 10]], [[25, 10]], [[26, 10]], [[27, 10]], [[28, 10]], [[29, 10]], [[30, 10]], [[31, 10]], [[32, 10]], [[33, 10]], [[34, 10]], [[35, 10]], [[36, 10]], [[37, 10]], [[38, 10]], [[39, 10]], [[38, 10]], [[37, 10]], [[36, 10]], [[35, 10]], [[34, 10]], [[33, 10]], [[32, 10]], [[31, 10]], [[30, 10]], [[29, 10]], [[28, 10]], [[27, 10]], [[26, 10]], [[25, 10]], [[24, 10]], [[23, 10]], [[22, 10]], [[21, 10]], [[20, 10]], [[19, 10]], [[18, 10]], [[17, 10]], [[16, 10]], [[15, 10]], [[14, 10]], [[13, 10]], [[12, 10]], [[11, 10]]], dtype=np.int32) # Test with debug = None pcv.params.debug = None obj_header, obj_data, obj_images = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) assert obj_data[7] == 30 def test_plantcv_analyze_object_longest_axis_2d(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_object_longest_axis_2d") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Create a test image img = np.zeros((50, 50, 3), dtype=np.uint8) img[0:5, 45:49, 0] = 255 img[0:5, 0:5, 0] = 255 mask = img[:, :, 0] obj_contour = np.array([[[45, 1]], [[45, 2]], [[45, 3]], [[45, 4]], [[46, 4]], [[47, 4]], [[48, 4]], [[48, 3]], [[48, 2]], [[48, 1]], [[47, 1]], [[46, 1]], [[1, 1]], [[1, 2]], [[1, 3]], [[1, 4]], [[2, 4]], [[3, 4]], [[4, 4]], [[4, 3]], [[4, 2]], [[4, 1]], [[3, 1]], [[2, 1]]], dtype=np.int32) # Test with debug = None pcv.params.debug = None obj_header, obj_data, obj_images = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) assert obj_data[7] == 186 def test_plantcv_analyze_object_longest_axis_2e(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_object_longest_axis_2e") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Create a test image img = np.zeros((50, 50, 3), dtype=np.uint8) img[10:15, 10:40, 0] = 255 mask = img[:, :, 0] obj_contour = np.array([[[10, 10]], [[10, 11]], [[10, 12]], [[10, 13]], [[10, 14]], [[11, 14]], [[12, 14]], [[13, 14]], [[14, 14]], [[15, 14]], [[16, 14]], [[17, 14]], [[18, 14]], [[19, 14]], [[20, 14]], [[21, 14]], [[22, 14]], [[23, 14]], [[24, 14]], [[25, 14]], [[26, 14]], [[27, 14]], [[28, 14]], [[29, 14]], [[30, 14]], [[31, 14]], [[32, 14]], [[33, 14]], [[34, 14]], [[35, 14]], [[36, 14]], [[37, 14]], [[38, 14]], [[39, 14]], [[39, 13]], [[39, 12]], [[39, 11]], [[39, 10]], [[38, 10]], [[37, 10]], [[36, 10]], [[35, 10]], [[34, 10]], [[33, 10]], [[32, 10]], [[31, 10]], [[30, 10]], [[29, 10]], [[28, 10]], [[27, 10]], [[26, 10]], [[25, 10]], [[24, 10]], [[23, 10]], [[22, 10]], [[21, 10]], [[20, 10]], [[19, 10]], [[18, 10]], [[17, 10]], [[16, 10]], [[15, 10]], [[14, 10]], [[13, 10]], [[12, 10]], [[11, 10]]], dtype=np.int32) # Test with debug = None pcv.params.debug = None obj_header, obj_data, obj_images = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) assert obj_data[7] == 141 def test_plantcv_analyze_object_small_contour(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_analyze_object_small_contour") os.mkdir(cache_dir) # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) obj_contour = [np.array([[[0, 0]], [[0, 50]], [[50, 50]], [[50, 0]]], dtype=np.int32)] # Test with debug = None pcv.params.debug = None obj_header, obj_data, obj_images = pcv.analyze_object(img=img, obj=obj_contour, mask=mask) assert obj_data is None def test_plantcv_apply_mask_white(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_apply_mask_white") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="white") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="white") # Test with debug = None pcv.params.debug = None masked_img = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="white") assert all([i == j] for i, j in zip(np.shape(masked_img), TEST_COLOR_DIM)) def test_plantcv_apply_mask_black(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_apply_mask_black") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="black") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="black") # Test with debug = None pcv.params.debug = None masked_img = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="black") assert all([i == j] for i, j in zip(np.shape(masked_img), TEST_COLOR_DIM)) def test_plantcv_apply_mask_bad_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) with pytest.raises(RuntimeError): pcv.params.debug = "plot" _ = pcv.apply_mask(rgb_img=img, mask=mask, mask_color="wite") def test_plantcv_auto_crop(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_auto_crop") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_MULTI), -1) contours = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_OBJECT), encoding="latin1") roi_contours = contours['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.auto_crop(img=img1, obj=roi_contours[1], padding_x=20, padding_y=20, color='black') # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.auto_crop(img=img1, obj=roi_contours[1], padding_x=20, padding_y=20, color='image') # Test with debug = None pcv.params.debug = None cropped = pcv.auto_crop(img=img1, obj=roi_contours[1], padding_x=20, padding_y=20, color='black') x, y, z = np.shape(img1) x1, y1, z1 = np.shape(cropped) assert x > x1 def test_plantcv_auto_crop_grayscale_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_auto_crop_grayscale_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_MULTI), -1) gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY) contours = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_OBJECT), encoding="latin1") roi_contours = contours['arr_0'] # Test with debug = "plot" pcv.params.debug = "plot" cropped = pcv.auto_crop(img=gray_img, obj=roi_contours[1], padding_x=20, padding_y=20, color='white') x, y = np.shape(gray_img) x1, y1 = np.shape(cropped) assert x > x1 def test_plantcv_auto_crop_bad_input(): # Read in test data rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_MULTI), -1) gray_img = cv2.cvtColor(rgb_img, cv2.COLOR_BGR2GRAY) contours = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_OBJECT), encoding="latin1") roi_contours = contours['arr_0'] with pytest.raises(RuntimeError): pcv.params.debug = "plot" _ = pcv.auto_crop(img=gray_img, obj=roi_contours[1], padding_x=20, padding_y=20, color='wite') def test_plantcv_canny_edge_detect(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_canny_edge_detect") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.canny_edge_detect(img=rgb_img, mask=mask, mask_color='white') _ = pcv.canny_edge_detect(img=img, mask=mask, mask_color='black') # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.canny_edge_detect(img=img, thickness=2) _ = pcv.canny_edge_detect(img=img) # Test with debug = None pcv.params.debug = None edge_img = pcv.canny_edge_detect(img=img) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(edge_img), TEST_BINARY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(edge_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_canny_edge_detect_bad_input(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_canny_edge_detect") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) with pytest.raises(RuntimeError): edge_img = pcv.canny_edge_detect(img=img, mask=mask, mask_color="gray") def test_plantcv_cluster_contours(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_cluster_contours") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_MULTI), -1) roi_objects = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_OBJECT), encoding="latin1") hierachy = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_HIERARCHY), encoding="latin1") objs = roi_objects['arr_0'] obj_hierarchy = hierachy['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, nrow=4, ncol=6) _ = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, show_grid=True) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, nrow=4, ncol=6) # Test with debug = None pcv.params.debug = None clusters_i, contours, hierachy = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, nrow=4, ncol=6) lenori = len(objs) lenclust = len(clusters_i) assert lenori > lenclust def test_plantcv_cluster_contours_grayscale_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_cluster_contours_grayscale_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_MULTI), 0) roi_objects = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_OBJECT), encoding="latin1") hierachy = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_HIERARCHY), encoding="latin1") objs = roi_objects['arr_0'] obj_hierarchy = hierachy['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, nrow=4, ncol=6) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, nrow=4, ncol=6) # Test with debug = None pcv.params.debug = None clusters_i, contours, hierachy = pcv.cluster_contours(img=img1, roi_objects=objs, roi_obj_hierarchy=obj_hierarchy, nrow=4, ncol=6) lenori = len(objs) lenclust = len(clusters_i) assert lenori > lenclust def test_plantcv_cluster_contours_splitimg(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_cluster_contours_splitimg") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_MULTI), -1) contours = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_CONTOUR), encoding="latin1") clusters = np.load(os.path.join(TEST_DATA, TEST_INPUT_ClUSTER_CONTOUR), encoding="latin1") hierachy = np.load(os.path.join(TEST_DATA, TEST_INPUT_MULTI_HIERARCHY), encoding="latin1") cluster_names = os.path.join(TEST_DATA, TEST_INPUT_GENOTXT) cluster_names_too_many = os.path.join(TEST_DATA, TEST_INPUT_GENOTXT_TOO_MANY) roi_contours = contours['arr_0'] cluster_contours = clusters['arr_0'] obj_hierarchy = hierachy['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.cluster_contour_splitimg(rgb_img=img1, grouped_contour_indexes=cluster_contours, contours=roi_contours, hierarchy=obj_hierarchy, outdir=cache_dir, file=None, filenames=None) _ = pcv.cluster_contour_splitimg(rgb_img=img1, grouped_contour_indexes=[[0]], contours=[], hierarchy=np.array([[[ 1, -1, -1, -1]]])) _ = pcv.cluster_contour_splitimg(rgb_img=img1, grouped_contour_indexes=cluster_contours, contours=roi_contours, hierarchy=obj_hierarchy, outdir=cache_dir, file='multi', filenames=None) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.cluster_contour_splitimg(rgb_img=img1, grouped_contour_indexes=cluster_contours, contours=roi_contours, hierarchy=obj_hierarchy, outdir=None, file=None, filenames=cluster_names) _ = pcv.cluster_contour_splitimg(rgb_img=img1, grouped_contour_indexes=cluster_contours, contours=roi_contours, hierarchy=obj_hierarchy, outdir=None, file=None, filenames=cluster_names_too_many) # Test with debug = None pcv.params.debug = None output_path = pcv.cluster_contour_splitimg(rgb_img=img1, grouped_contour_indexes=cluster_contours, contours=roi_contours, hierarchy=obj_hierarchy, outdir=None, file=None, filenames=None) assert len(output_path) != 0 def test_plantcv_color_palette(): # Collect assertions truths = [] # Return one random color colors = pcv.color_palette(1) # Colors should be a list of length 1, containing a tuple of length 3 truths.append(len(colors) == 1) truths.append(len(colors[0]) == 3) # Return ten random colors colors = pcv.color_palette(10) # Colors should be a list of length 10 truths.append(len(colors) == 10) # All of these should be true for the function to pass testing. assert (all(truths)) def test_plantcv_crop_position_mask(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_crop_position_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data nir, path1, filename1 = pcv.readimage(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK), -1) mask_three_channel = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK)) mask_resize = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK_RESIZE), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="right") _ = pcv.crop_position_mask(nir, mask_resize, x=40, y=3, v_pos="top", h_pos="right") _ = pcv.crop_position_mask(nir, mask_three_channel, x=40, y=3, v_pos="top", h_pos="right") # Test with debug = "print" with bottom _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="bottom", h_pos="left") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="right") # Test with debug = "plot" with bottom _ = pcv.crop_position_mask(nir, mask, x=45, y=2, v_pos="bottom", h_pos="left") # Test with debug = None pcv.params.debug = None newmask = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="right") assert np.sum(newmask) == 641517 def test_plantcv_crop_position_mask_color(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_crop_position_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data nir, path1, filename1 = pcv.readimage(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK), -1) mask_resize = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK_RESIZE)) mask_non_binary = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="right") # Test with debug = "print" with bottom _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="bottom", h_pos="left") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="right") # Test with debug = "plot" with bottom _ = pcv.crop_position_mask(nir, mask, x=45, y=2, v_pos="bottom", h_pos="left") _ = pcv.crop_position_mask(nir, mask_non_binary, x=45, y=2, v_pos="bottom", h_pos="left") _ = pcv.crop_position_mask(nir, mask_non_binary, x=45, y=2, v_pos="top", h_pos="left") _ = pcv.crop_position_mask(nir, mask_non_binary, x=45, y=2, v_pos="bottom", h_pos="right") _ = pcv.crop_position_mask(nir, mask_resize, x=45, y=2, v_pos="top", h_pos="left") # Test with debug = None pcv.params.debug = None newmask = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="right") assert np.sum(newmask) == 641517 def test_plantcv_crop_position_mask_bad_input_x(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_crop_position_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK), -1) # Read in test data nir, path1, filename1 = pcv.readimage(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.crop_position_mask(nir, mask, x=-1, y=-1, v_pos="top", h_pos="right") def test_plantcv_crop_position_mask_bad_input_vpos(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_crop_position_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK), -1) # Read in test data nir, path1, filename1 = pcv.readimage(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="below", h_pos="right") def test_plantcv_crop_position_mask_bad_input_hpos(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_crop_position_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MASK), -1) # Read in test data nir, path1, filename1 = pcv.readimage(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.crop_position_mask(nir, mask, x=40, y=3, v_pos="top", h_pos="starboard") def test_plantcv_dilate(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_dilate") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.dilate(gray_img=img, ksize=5, i=1) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.dilate(gray_img=img, ksize=5, i=1) # Test with debug = None pcv.params.debug = None dilate_img = pcv.dilate(gray_img=img, ksize=5, i=1) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(dilate_img), TEST_BINARY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(dilate_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_dilate_small_k(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = None pcv.params.debug = None with pytest.raises(ValueError): _ = pcv.dilate(img, 1, 1) def test_plantcv_erode(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_erode") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.erode(gray_img=img, ksize=5, i=1) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.erode(gray_img=img, ksize=5, i=1) # Test with debug = None pcv.params.debug = None erode_img = pcv.erode(gray_img=img, ksize=5, i=1) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(erode_img), TEST_BINARY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(erode_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_erode_small_k(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = None pcv.params.debug = None with pytest.raises(ValueError): _ = pcv.erode(img, 1, 1) def test_plantcv_distance_transform(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_distance_transform") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_CROPPED_MASK), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.distance_transform(bin_img=mask, distance_type=1, mask_size=3) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.distance_transform(bin_img=mask, distance_type=1, mask_size=3) # Test with debug = None pcv.params.debug = None distance_transform_img = pcv.distance_transform(bin_img=mask, distance_type=1, mask_size=3) # Assert that the output image has the dimensions of the input image assert all([i == j] for i, j in zip(np.shape(distance_transform_img), np.shape(mask))) def test_plantcv_fatal_error(): # Verify that the fatal_error function raises a RuntimeError with pytest.raises(RuntimeError): pcv.fatal_error("Test error") def test_plantcv_fill(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_fill") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.fill(bin_img=img, size=63632) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.fill(bin_img=img, size=63632) # Test with debug = None pcv.params.debug = None fill_img = pcv.fill(bin_img=img, size=63632) # Assert that the output image has the dimensions of the input image # assert all([i == j] for i, j in zip(np.shape(fill_img), TEST_BINARY_DIM)) assert np.sum(fill_img) == 0 def test_plantcv_fill_bad_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_fill_bad_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): _ = pcv.fill(bin_img=img, size=1) def test_plantcv_find_objects(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_find_objects") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.find_objects(img=img, mask=mask) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.find_objects(img=img, mask=mask) # Test with debug = None pcv.params.debug = None contours, hierarchy = pcv.find_objects(img=img, mask=mask) # Assert the correct number of contours are found if cv2.__version__[0] == '2': assert len(contours) == 2 else: assert len(contours) == 2 def test_plantcv_find_objects_grayscale_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_find_objects_grayscale_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), 0) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "plot" pcv.params.debug = "plot" contours, hierarchy = pcv.find_objects(img=img, mask=mask) # Assert the correct number of contours are found if cv2.__version__[0] == '2': assert len(contours) == 2 else: assert len(contours) == 2 def test_plantcv_flip(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_flip") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) img_binary = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.flip(img=img, direction="horizontal") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.flip(img=img, direction="vertical") _ = pcv.flip(img=img_binary, direction="vertical") # Test with debug = None pcv.params.debug = None flipped_img = pcv.flip(img=img, direction="horizontal") assert all([i == j] for i, j in zip(np.shape(flipped_img), TEST_COLOR_DIM)) def test_plantcv_flip_bad_input(): img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.flip(img=img, direction="vert") def test_plantcv_fluor_fvfm(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_fluor_fvfm") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir filename = os.path.join(cache_dir, 'plantcv_fvfm_hist.jpg') # Read in test data fdark = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FDARK), -1) fmin = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FMIN), -1) fmax = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FMAX), -1) fmask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FMASK), -1) # Test with debug = "print" pcv.params.debug = "print" outfile = os.path.join(cache_dir, TEST_INPUT_FMAX) _ = pcv.fluor_fvfm(fdark=fdark, fmin=fmin, fmax=fmax, mask=fmask, bins=1000) _, _, analysis_images = pcv.fluor_fvfm(fdark=fdark+3000, fmin=fmin, fmax=fmax, mask=fmask, bins=1000) # Test under updated print and plot function hist_img = analysis_images[1] pcv.print_image(hist_img, filename) pcv.plot_image(hist_img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.fluor_fvfm(fdark=fdark, fmin=fmin, fmax=fmax, mask=fmask, bins=1000) # Test with debug = None pcv.params.debug = None fvfm_header, fvfm_data, fvfm_images = pcv.fluor_fvfm(fdark=fdark, fmin=fmin, fmax=fmax, mask=fmask, bins=1000) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert fvfm_data[4] > 0.66 def test_plantcv_fluor_fvfm_bad_input(): fdark = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) fmin = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FMIN), -1) fmax = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FMAX), -1) fmask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_FMASK), -1) with pytest.raises(RuntimeError): _ = pcv.fluor_fvfm(fdark=fdark, fmin=fmin, fmax=fmax, mask=fmask, bins=1000) def test_plantcv_gaussian_blur(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_gaussian_blur") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img_color = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.gaussian_blur(img=img, ksize=(51, 51), sigma_x=0, sigma_y=None) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.gaussian_blur(img=img, ksize=(51, 51), sigma_x=0, sigma_y=None) _ = pcv.gaussian_blur(img=img_color, ksize=(51, 51), sigma_x=0, sigma_y=None) # Test with debug = None pcv.params.debug = None gaussian_img = pcv.gaussian_blur(img=img, ksize=(51, 51), sigma_x=0, sigma_y=None) imgavg = np.average(img) gavg = np.average(gaussian_img) assert gavg != imgavg def test_plantcv_get_nir_sv(): nirpath = pcv.get_nir(TEST_DATA, TEST_VIS) nirpath1 = os.path.join(TEST_DATA, TEST_NIR) assert nirpath == nirpath1 def test_plantcv_get_nir_tv(): nirpath = pcv.get_nir(TEST_DATA, TEST_VIS_TV) nirpath1 = os.path.join(TEST_DATA, TEST_NIR_TV) assert nirpath == nirpath1 def test_plantcv_hist_equalization(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_hist_equalization") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.hist_equalization(gray_img=img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.hist_equalization(gray_img=img) # Test with debug = None pcv.params.debug = None hist = pcv.hist_equalization(gray_img=img) histavg = np.average(hist) imgavg = np.average(img) assert histavg != imgavg def test_plantcv_hist_equalization_bad_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_hist_equalization_bad_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), 1) # Test with debug = None pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.hist_equalization(gray_img=img) def test_plantcv_image_add(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_image_add") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img2 = np.copy(img1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.image_add(gray_img1=img1, gray_img2=img2) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.image_add(gray_img1=img1, gray_img2=img2) # Test with debug = None pcv.params.debug = None added_img = pcv.image_add(gray_img1=img1, gray_img2=img2) assert all([i == j] for i, j in zip(np.shape(added_img), TEST_BINARY_DIM)) def test_plantcv_image_subtract(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_image_sub") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # read in images img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img2 = np.copy(img1) # Test with debug = "print" pcv.params.debug = 'print' _ = pcv.image_subtract(img1, img2) # Test with debug = "plot" pcv.params.debug = 'plot' _ = pcv.image_subtract(img1, img2) # Test with debug = None pcv.params.debug = None new_img = pcv.image_subtract(img1, img2) assert np.array_equal(new_img, np.zeros(np.shape(new_img), np.uint8)) def test_plantcv_image_subtract_fail(): # read in images img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img2 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY)) # test with pytest.raises(RuntimeError): _ = pcv.image_subtract(img1, img2) def test_plantcv_invert(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_invert") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.invert(gray_img=img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.invert(gray_img=img) # Test with debug = None pcv.params.debug = None inverted_img = pcv.invert(gray_img=img) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(inverted_img), TEST_BINARY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(inverted_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_landmark_reference_pt_dist(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_landmark_reference") os.mkdir(cache_dir) points_rescaled = [(0.0139, 0.2569), (0.2361, 0.2917), (0.3542, 0.3819), (0.3542, 0.4167), (0.375, 0.4236), (0.7431, 0.3681), (0.8958, 0.3542), (0.9931, 0.3125), (0.1667, 0.5139), (0.4583, 0.8889), (0.4931, 0.5903), (0.3889, 0.5694), (0.4792, 0.4306), (0.2083, 0.5417), (0.3194, 0.5278), (0.3889, 0.375), (0.3681, 0.3472), (0.2361, 0.0139), (0.5417, 0.2292), (0.7708, 0.3472), (0.6458, 0.3472), (0.6389, 0.5208), (0.6458, 0.625)] centroid_rescaled = (0.4685, 0.4945) bottomline_rescaled = (0.4685, 0.2569) _ = pcv.landmark_reference_pt_dist(points_r=[], centroid_r=('a', 'b'), bline_r=(0, 0)) _ = pcv.landmark_reference_pt_dist(points_r=[(10, 1000)], centroid_r=(10, 10), bline_r=(10, 10)) _ = pcv.landmark_reference_pt_dist(points_r=[], centroid_r=(0, 0), bline_r=(0, 0)) header, landmark_data = pcv.landmark_reference_pt_dist(points_r=points_rescaled, centroid_r=centroid_rescaled, bline_r=bottomline_rescaled) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert len(landmark_data) == 9 def test_plantcv_laplace_filter(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_laplace_filter") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.laplace_filter(gray_img=img, ksize=1, scale=1) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.laplace_filter(gray_img=img, ksize=1, scale=1) # Test with debug = None pcv.params.debug = None lp_img = pcv.laplace_filter(gray_img=img, ksize=1, scale=1) # Assert that the output image has the dimensions of the input image assert all([i == j] for i, j in zip(np.shape(lp_img), TEST_GRAY_DIM)) def test_plantcv_logical_and(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_logical_and") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img2 = np.copy(img1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.logical_and(bin_img1=img1, bin_img2=img2) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.logical_and(bin_img1=img1, bin_img2=img2) # Test with debug = None pcv.params.debug = None and_img = pcv.logical_and(bin_img1=img1, bin_img2=img2) assert all([i == j] for i, j in zip(np.shape(and_img), TEST_BINARY_DIM)) def test_plantcv_logical_or(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_logical_or") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img2 = np.copy(img1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.logical_or(bin_img1=img1, bin_img2=img2) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.logical_or(bin_img1=img1, bin_img2=img2) # Test with debug = None pcv.params.debug = None or_img = pcv.logical_or(bin_img1=img1, bin_img2=img2) assert all([i == j] for i, j in zip(np.shape(or_img), TEST_BINARY_DIM)) def test_plantcv_logical_xor(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_logical_xor") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img1 = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) img2 = np.copy(img1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.logical_xor(bin_img1=img1, bin_img2=img2) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.logical_xor(bin_img1=img1, bin_img2=img2) # Test with debug = None pcv.params.debug = None xor_img = pcv.logical_xor(bin_img1=img1, bin_img2=img2) assert all([i == j] for i, j in zip(np.shape(xor_img), TEST_BINARY_DIM)) def test_plantcv_median_blur(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_median_blur") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.median_blur(gray_img=img, ksize=5) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.median_blur(gray_img=img, ksize=5) # Test with debug = None pcv.params.debug = None blur_img = pcv.median_blur(gray_img=img, ksize=5) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(blur_img), TEST_BINARY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(blur_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_median_blur_bad_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_median_blur_bad_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): _ = pcv.median_blur(img, 5.) def test_plantcv_naive_bayes_classifier(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_naive_bayes_classifier") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.naive_bayes_classifier(rgb_img=img, pdf_file=os.path.join(TEST_DATA, TEST_PDFS)) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.naive_bayes_classifier(rgb_img=img, pdf_file=os.path.join(TEST_DATA, TEST_PDFS)) # Test with debug = None pcv.params.debug = None mask = pcv.naive_bayes_classifier(rgb_img=img, pdf_file=os.path.join(TEST_DATA, TEST_PDFS)) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(mask), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(mask), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_naive_bayes_classifier_bad_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.naive_bayes_classifier(rgb_img=img, pdf_file=os.path.join(TEST_DATA, TEST_PDFS_BAD)) def test_plantcv_object_composition(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_object_composition") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS1), encoding="latin1") object_contours = contours_npz['arr_0'] object_hierarchy = contours_npz['arr_1'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.object_composition(img=img, contours=object_contours, hierarchy=object_hierarchy) _ = pcv.object_composition(img=img, contours=[], hierarchy=object_hierarchy) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.object_composition(img=img, contours=object_contours, hierarchy=object_hierarchy) # Test with debug = None pcv.params.debug = None contours, mask = pcv.object_composition(img=img, contours=object_contours, hierarchy=object_hierarchy) # Assert that the objects have been combined contour_shape = np.shape(contours) # type: tuple assert contour_shape[1] == 1 def test_plantcv_object_composition_grayscale_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_object_composition_grayscale_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), 0) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS1), encoding="latin1") object_contours = contours_npz['arr_0'] object_hierarchy = contours_npz['arr_1'] # Test with debug = "plot" pcv.params.debug = "plot" contours, mask = pcv.object_composition(img=img, contours=object_contours, hierarchy=object_hierarchy) # Assert that the objects have been combined contour_shape = np.shape(contours) # type: tuple assert contour_shape[1] == 1 def test_plantcv_output_mask(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_output_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) img_color = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.output_mask(img=img, mask=mask, filename='test.png', outdir=cache_dir, mask_only=False) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.output_mask(img=img, mask=mask, filename='test.png', outdir=cache_dir, mask_only=False) _ = pcv.output_mask(img=img_color, mask=mask, filename='test.png', outdir=cache_dir, mask_only=False) # Test with debug = None pcv.params.debug = None imgpath, maskpath, analysis_images = pcv.output_mask(img=img, mask=mask, filename='test.png', mask_only=False) assert all([os.path.exists(imgpath) is True, os.path.exists(maskpath) is True]) def test_plantcv_output_mask_true(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_output_mask") pcv.params.debug_outdir = cache_dir os.mkdir(cache_dir) # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) img_color = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.output_mask(img=img, mask=mask, filename='test.png', outdir=cache_dir, mask_only=True) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.output_mask(img=img_color, mask=mask, filename='test.png', outdir=cache_dir, mask_only=True) pcv.params.debug = None imgpath, maskpath, analysis_images = pcv.output_mask(img=img, mask=mask, filename='test.png', outdir=cache_dir, mask_only=False) assert all([os.path.exists(imgpath) is True, os.path.exists(maskpath) is True]) def test_plantcv_plot_hist(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_plot_hist") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Test in print mode pcv.params.debug = "print" img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) _ = pcv.plot_hist(gray_img=np.uint16(img), mask=mask, bins=200) # Test in plot mode pcv.params.debug = "plot" hist_header, hist_data, fig_hist = pcv.plot_hist(gray_img=img) assert np.sum(hist_data[3]) != 0 def test_plantcv_plot_image_matplotlib_input(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_pseudocolor") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) pimg = pcv.pseudocolor(gray_img=img, mask=mask, min_value=10, max_value=200) with pytest.raises(RuntimeError): pcv.plot_image(pimg) def test_plantcv_print_image(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_print_image") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img, path, img_name = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_COLOR)) filename = os.path.join(cache_dir, 'plantcv_print_image.jpg') pcv.print_image(img=img, filename=filename) # Assert that the file was created assert os.path.exists(filename) is True def test_plantcv_print_image_bad_type(): with pytest.raises(RuntimeError): pcv.print_image(img=[], filename="/dev/null") def test_plantcv_pseudocolor(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_pseudocolor") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS), encoding="latin1") obj_contour = contours_npz['arr_0'] filename = os.path.join(cache_dir, 'plantcv_pseudo_image.jpg') # Test with debug = "print" pcv.params.debug = "print" _ = pcv.pseudocolor(gray_img=img, mask=None) _ = pcv.pseudocolor(gray_img=img, mask=None) pimg = pcv.pseudocolor(gray_img=img, mask=mask, min_value=10, max_value=200) pcv.print_image(pimg, filename) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.pseudocolor(gray_img=img, mask=mask, background="image") _ = pcv.pseudocolor(gray_img=img, mask=None) _ = pcv.pseudocolor(gray_img=img, mask=mask, background="black", obj=obj_contour, axes=False, colorbar=False) _ = pcv.pseudocolor(gray_img=img, mask=mask, background="image", obj=obj_contour) _ = pcv.pseudocolor(gray_img=img, mask=None, axes=False, colorbar=False) # Test with debug = None pcv.params.debug = None _ = pcv.pseudocolor(gray_img=img, mask=None) pseudo_img = pcv.pseudocolor(gray_img=img, mask=mask, background="white") # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(pseudo_img), TEST_BINARY_DIM)): assert 1 else: assert 0 def test_plantcv_pseudocolor_bad_input(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_pseudocolor") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) with pytest.raises(RuntimeError): _ = pcv.pseudocolor(gray_img=img) def test_plantcv_pseudocolor_bad_background(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_pseudocolor_bad_background") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) with pytest.raises(RuntimeError): _ = pcv.pseudocolor(gray_img=img, mask=mask, background="pink") def test_plantcv_readimage_native(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_readimage") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Test with debug = "print" pcv.params.debug = "print" _ = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_COLOR)) pcv.params.debug = None img, path, img_name = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Assert that the image name returned equals the name of the input image # Assert that the path of the image returned equals the path of the input image # Assert that the dimensions of the returned image equals the expected dimensions if img_name == TEST_INPUT_COLOR and path == TEST_DATA: if all([i == j] for i, j in zip(np.shape(img), TEST_COLOR_DIM)): assert 1 else: assert 0 else: assert 0 def test_plantcv_readimage_grayscale(): pcv.params.debug = None img, path, img_name = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_GRAY), mode="grey") img, path, img_name = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_GRAY), mode="gray") assert len(np.shape(img)) == 2 def test_plantcv_readimage_rgb(): pcv.params.debug = None img, path, img_name = pcv.readimage(filename=os.path.join(TEST_DATA, TEST_INPUT_GRAY), mode="rgb") assert len(np.shape(img)) == 3 def test_plantcv_readimage_bad_file(): with pytest.raises(RuntimeError): _ = pcv.readimage(filename=TEST_INPUT_COLOR) def test_plantcv_readbayer_default_bg(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_readbayer_default_bg") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Test with debug = "print" pcv.params.debug = "print" _, _, _ = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="BG", alg="default") # Test with debug = "plot" pcv.params.debug = "plot" img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="BG", alg="default") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_default_gb(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="GB", alg="default") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_default_rg(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="RG", alg="default") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_default_gr(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="GR", alg="default") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_edgeaware_bg(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="BG", alg="edgeaware") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_edgeaware_gb(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="GB", alg="edgeaware") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_edgeaware_rg(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="RG", alg="edgeaware") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_edgeaware_gr(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="GR", alg="edgeaware") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_variablenumbergradients_bg(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="BG", alg="variablenumbergradients") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_variablenumbergradients_gb(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="GB", alg="variablenumbergradients") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_variablenumbergradients_rg(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="RG", alg="variablenumbergradients") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_variablenumbergradients_gr(): # Test with debug = None pcv.params.debug = None img, path, img_name = pcv.readbayer(filename=os.path.join(TEST_DATA, TEST_INPUT_BAYER), bayerpattern="GR", alg="variablenumbergradients") assert all([i == j] for i, j in zip(np.shape(img), (335, 400, 3))) def test_plantcv_readbayer_default_bad_input(): # Test with debug = None pcv.params.debug = None with pytest.raises(RuntimeError): _, _, _ = pcv.readbayer(filename=os.path.join(TEST_DATA, "no-image.png"), bayerpattern="GR", alg="default") def test_plantcv_rectangle_mask(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_rectangle_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) img_color = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.rectangle_mask(img=img, p1=(0, 0), p2=(2454, 2056), color="white") _ = pcv.rectangle_mask(img=img, p1=(0, 0), p2=(2454, 2056), color="white") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.rectangle_mask(img=img_color, p1=(0, 0), p2=(2454, 2056), color="gray") # Test with debug = None pcv.params.debug = None masked, hist, contour, heir = pcv.rectangle_mask(img=img, p1=(0, 0), p2=(2454, 2056), color="black") maskedsum = np.sum(masked) imgsum = np.sum(img) assert maskedsum < imgsum def test_plantcv_rectangle_mask_bad_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_rectangle_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) img_color = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = None pcv.params.debug = None with pytest.raises(RuntimeError): masked, hist, contour, hier = pcv.rectangle_mask(img=img, p1=(0, 0), p2=(2454, 2056), color="whit") def test_plantcv_report_size_marker_detect(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_report_size_marker_detect") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MARKER), -1) # ROI contour roi_contour = [np.array([[[3550, 850]], [[3550, 1349]], [[4049, 1349]], [[4049, 850]]], dtype=np.int32)] roi_hierarchy = np.array([[[-1, -1, -1, -1]]], dtype=np.int32) # Test with debug = "print" pcv.params.debug = "print" outfile = os.path.join(cache_dir, TEST_INPUT_MARKER) _ = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='detect', objcolor='light', thresh_channel='s', thresh=120) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='detect', objcolor='light', thresh_channel='s', thresh=120) # Test with debug = None pcv.params.debug = None marker_header, marker_data, images = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='detect', objcolor='light', thresh_channel='s', thresh=120) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert marker_data[1] > 100 def test_plantcv_report_size_marker_define(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MARKER), -1) # ROI contour roi_contour = [np.array([[[3550, 850]], [[3550, 1349]], [[4049, 1349]], [[4049, 850]]], dtype=np.int32)] roi_hierarchy = np.array([[[-1, -1, -1, -1]]], dtype=np.int32) # Test with debug = None pcv.params.debug = None marker_header, marker_data, images = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='define', objcolor='light', thresh_channel='s', thresh=120) assert marker_data[1] == 250000 def test_plantcv_report_size_marker_grayscale_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # ROI contour roi_contour = [np.array([[[0, 0]], [[0, 49]], [[49, 49]], [[49, 0]]], dtype=np.int32)] roi_hierarchy = np.array([[[-1, -1, -1, -1]]], dtype=np.int32) # Test with debug = None pcv.params.debug = None marker_header, marker_data, images = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='define', objcolor='light', thresh_channel='s', thresh=120) if cv2.__version__[0] == '2': assert int(marker_data[1]) == 2401 else: assert marker_data[1] == 2500 def test_plantcv_report_size_marker_bad_marker_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MARKER), -1) # ROI contour roi_contour = [np.array([[[3550, 850]], [[3550, 1349]], [[4049, 1349]], [[4049, 850]]], dtype=np.int32)] roi_hierarchy = np.array([[[-1, -1, -1, -1]]], dtype=np.int32) with pytest.raises(RuntimeError): _ = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='none', objcolor='light', thresh_channel='s', thresh=120) def test_plantcv_report_size_marker_bad_threshold_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MARKER), -1) # ROI contour roi_contour = [np.array([[[3550, 850]], [[3550, 1349]], [[4049, 1349]], [[4049, 850]]], dtype=np.int32)] roi_hierarchy = np.array([[[-1, -1, -1, -1]]], dtype=np.int32) with pytest.raises(RuntimeError): _ = pcv.report_size_marker_area(img=img, roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, marker='detect', objcolor='light', thresh_channel=None, thresh=120) def test_plantcv_resize(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_resize") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.resize(img=img, resize_x=0.5, resize_y=0.5) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.resize(img=img, resize_x=0.5, resize_y=0.5) # Test with debug = None pcv.params.debug = None resized_img = pcv.resize(img=img, resize_x=0.5, resize_y=0.5) ix, iy, iz = np.shape(img) rx, ry, rz = np.shape(resized_img) assert ix > rx def test_plantcv_resize_bad_inputs(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test for fatal error caused by two negative resize values pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.resize(img=img, resize_x=-1, resize_y=-1) def test_plantcv_rgb2gray_hsv(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_rgb2gray_hsv") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.rgb2gray_hsv(rgb_img=img, channel="s") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.rgb2gray_hsv(rgb_img=img, channel="s") # Test with debug = None pcv.params.debug = None s = pcv.rgb2gray_hsv(rgb_img=img, channel="s") # Assert that the output image has the dimensions of the input image but is only a single channel assert all([i == j] for i, j in zip(np.shape(s), TEST_GRAY_DIM)) def test_plantcv_rgb2gray_hsv_bad_input(): img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.rgb2gray_hsv(rgb_img=img, channel="l") def test_plantcv_rgb2gray_lab(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_rgb2gray_lab") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.rgb2gray_lab(rgb_img=img, channel='b') # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.rgb2gray_lab(rgb_img=img, channel='b') # Test with debug = None pcv.params.debug = None b = pcv.rgb2gray_lab(rgb_img=img, channel='b') # Assert that the output image has the dimensions of the input image but is only a single channel assert all([i == j] for i, j in zip(np.shape(b), TEST_GRAY_DIM)) def test_plantcv_rgb2gray_lab_bad_input(): img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.rgb2gray_lab(rgb_img=img, channel="v") def test_plantcv_rgb2gray(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_rgb2gray") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.rgb2gray(rgb_img=img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.rgb2gray(rgb_img=img) # Test with debug = None pcv.params.debug = None gray = pcv.rgb2gray(rgb_img=img) # Assert that the output image has the dimensions of the input image but is only a single channel assert all([i == j] for i, j in zip(np.shape(gray), TEST_GRAY_DIM)) def test_plantcv_roi_objects(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_roi_objects") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) roi_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_ROI), encoding="latin1") roi_contour = roi_npz['arr_0'] roi_hierarchy = roi_npz['arr_1'] contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS1), encoding="latin1") object_contours = contours_npz['arr_0'] object_hierarchy = contours_npz['arr_1'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.roi_objects(img=img, roi_type="largest", roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, object_contour=object_contours, obj_hierarchy=object_hierarchy) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.roi_objects(img=img, roi_type="partial", roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, object_contour=object_contours, obj_hierarchy=object_hierarchy) # Test with debug = None and roi_type = cutto pcv.params.debug = None _ = pcv.roi_objects(img=img, roi_type="cutto", roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, object_contour=object_contours, obj_hierarchy=object_hierarchy) # Test with debug = None kept_contours, kept_hierarchy, mask, area = pcv.roi_objects(img=img, roi_type="partial", roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, object_contour=object_contours, obj_hierarchy=object_hierarchy) # Assert that the contours were filtered as expected assert len(kept_contours) == 1046 def test_plantcv_roi_objects_bad_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) roi_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_ROI), encoding="latin1") roi_contour = roi_npz['arr_0'] roi_hierarchy = roi_npz['arr_1'] contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS1), encoding="latin1") object_contours = contours_npz['arr_0'] object_hierarchy = contours_npz['arr_1'] pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.roi_objects(img=img, roi_type="cut", roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, object_contour=object_contours, obj_hierarchy=object_hierarchy) def test_plantcv_roi_objects_grayscale_input(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_roi_objects_grayscale_input") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR), 0) roi_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_ROI), encoding="latin1") roi_contour = roi_npz['arr_0'] roi_hierarchy = roi_npz['arr_1'] contours_npz = np.load(os.path.join(TEST_DATA, TEST_INPUT_CONTOURS1), encoding="latin1") object_contours = contours_npz['arr_0'] object_hierarchy = contours_npz['arr_1'] # Test with debug = "plot" pcv.params.debug = "plot" kept_contours, kept_hierarchy, mask, area = pcv.roi_objects(img=img, roi_type="partial", roi_contour=roi_contour, roi_hierarchy=roi_hierarchy, object_contour=object_contours, obj_hierarchy=object_hierarchy) # Assert that the contours were filtered as expected assert len(kept_contours) == 1046 def test_plantcv_rotate(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_rotate_img") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.rotate(img=img, rotation_deg=45, crop=True) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.rotate(img=img, rotation_deg=45, crop=True) # Test with debug = None pcv.params.debug = None rotated = pcv.rotate(img=img, rotation_deg=45, crop=True) imgavg = np.average(img) rotateavg = np.average(rotated) assert rotateavg != imgavg def test_plantcv_rotate_gray(): img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.rotate(img=img, rotation_deg=45, crop=False) # Test with debug = None pcv.params.debug = None rotated = pcv.rotate(img=img, rotation_deg=45, crop=False) imgavg = np.average(img) rotateavg = np.average(rotated) assert rotateavg != imgavg def test_plantcv_scale_features(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_scale_features") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data mask = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR), encoding="latin1") obj_contour = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _ = pcv.scale_features(obj=obj_contour, mask=mask, points=TEST_ACUTE_RESULT, line_position=50) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.scale_features(obj=obj_contour, mask=mask, points=TEST_ACUTE_RESULT, line_position='NA') # Test with debug = None pcv.params.debug = None points_rescaled, centroid_rescaled, bottomline_rescaled = pcv.scale_features(obj=obj_contour, mask=mask, points=TEST_ACUTE_RESULT, line_position=50) assert len(points_rescaled) == 23 def test_plantcv_scale_features_bad_input(): mask = np.array([]) obj_contour = np.array([]) pcv.params.debug = None result = pcv.scale_features(obj=obj_contour, mask=mask, points=TEST_ACUTE_RESULT, line_position=50) assert all([i == j] for i, j in zip(result, [("NA", "NA"), ("NA", "NA"), ("NA", "NA")])) def test_plantcv_scharr_filter(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_scharr_filter") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) pcv.params.debug = "print" # Test with debug = "print" _ = pcv.scharr_filter(img=img, dx=1, dy=0, scale=1) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.scharr_filter(img=img, dx=1, dy=0, scale=1) # Test with debug = None pcv.params.debug = None scharr_img = pcv.scharr_filter(img=img, dx=1, dy=0, scale=1) # Assert that the output image has the dimensions of the input image assert all([i == j] for i, j in zip(np.shape(scharr_img), TEST_GRAY_DIM)) def test_plantcv_shift_img(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_shift_img") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_BINARY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.shift_img(img=img, number=300, side="top") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.shift_img(img=img, number=300, side="top") # Test with debug = "plot" _ = pcv.shift_img(img=img, number=300, side="bottom") # Test with debug = "plot" _ = pcv.shift_img(img=img, number=300, side="right") # Test with debug = "plot" _ = pcv.shift_img(img=mask, number=300, side="left") # Test with debug = None pcv.params.debug = None rotated = pcv.shift_img(img=img, number=300, side="top") imgavg = np.average(img) shiftavg = np.average(rotated) assert shiftavg != imgavg def test_plantcv_shift_img_bad_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.shift_img(img=img, number=-300, side="top") def test_plantcv_shift_img_bad_side_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.shift_img(img=img, number=300, side="starboard") def test_plantcv_sobel_filter(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_sobel_filter") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.sobel_filter(gray_img=img, dx=1, dy=0, ksize=1) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.sobel_filter(gray_img=img, dx=1, dy=0, ksize=1) # Test with debug = None pcv.params.debug = None sobel_img = pcv.sobel_filter(gray_img=img, dx=1, dy=0, ksize=1) # Assert that the output image has the dimensions of the input image assert all([i == j] for i, j in zip(np.shape(sobel_img), TEST_GRAY_DIM)) def test_plantcv_watershed_segmentation(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_watershed_segmentation") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_CROPPED)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_CROPPED_MASK), -1) # Test with debug = "print" pcv.params.debug = "print" outfile = os.path.join(cache_dir, TEST_INPUT_CROPPED) _ = pcv.watershed_segmentation(rgb_img=img, mask=mask, distance=10) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.watershed_segmentation(rgb_img=img, mask=mask, distance=10) # Test with debug = None pcv.params.debug = None watershed_header, watershed_data, images = pcv.watershed_segmentation(rgb_img=img, mask=mask, distance=10) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() if cv2.__version__[0] == '2': assert watershed_data[1] > 9 else: assert watershed_data[1] > 9 def test_plantcv_white_balance_gray_16bit(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_white_balance_gray_16bit") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.white_balance(img=img, mode='hist', roi=(5, 5, 80, 80)) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.white_balance(img=img, mode='max', roi=(5, 5, 80, 80)) # Test without an ROI pcv.params.debug = None _ = pcv.white_balance(img=img, mode='hist', roi=None) # Test with debug = None white_balanced = pcv.white_balance(img=img, roi=(5, 5, 80, 80)) imgavg = np.average(img) balancedavg = np.average(white_balanced) assert balancedavg != imgavg def test_plantcv_white_balance_gray_8bit(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_white_balance_gray_8bit") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK)) img = cv2.cvtColor(img, cv2.COLOR_BGR2GRAY) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.white_balance(img=img, mode='hist', roi=(5, 5, 80, 80)) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.white_balance(img=img, mode='max', roi=(5, 5, 80, 80)) # Test without an ROI pcv.params.debug = None _ = pcv.white_balance(img=img, mode='hist', roi=None) # Test with debug = None white_balanced = pcv.white_balance(img=img, roi=(5, 5, 80, 80)) imgavg = np.average(img) balancedavg = np.average(white_balanced) assert balancedavg != imgavg def test_plantcv_white_balance_rgb(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_white_balance_rgb") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MARKER)) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.white_balance(img=img, mode='hist', roi=(5, 5, 80, 80)) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.white_balance(img=img, mode='max', roi=(5, 5, 80, 80)) # Test without an ROI pcv.params.debug = None _ = pcv.white_balance(img=img, mode='hist', roi=None) # Test with debug = None white_balanced = pcv.white_balance(img=img, roi=(5, 5, 80, 80)) imgavg = np.average(img) balancedavg = np.average(white_balanced) assert balancedavg != imgavg def test_plantcv_white_balance_bad_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK), -1) # Test with debug = None with pytest.raises(RuntimeError): pcv.params.debug = "plot" _ = pcv.white_balance(img=img, mode='hist', roi=(5, 5, 5, 5, 5)) def test_plantcv_white_balance_bad_mode_input(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_MARKER)) # Test with debug = None with pytest.raises(RuntimeError): pcv.params.debug = "plot" _ = pcv.white_balance(img=img, mode='histogram', roi=(5, 5, 80, 80)) def test_plantcv_white_balance_bad_input_int(): # Read in test data img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_NIR_MASK), -1) # Test with debug = None with pytest.raises(RuntimeError): pcv.params.debug = "plot" _ = pcv.white_balance(img=img, mode='hist', roi=(5., 5, 5, 5)) def test_plantcv_x_axis_pseudolandmarks(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_x_axis_pseudolandmarks_debug") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR), encoding="latin1") obj_contour = contours_npz['arr_0'] pcv.params.debug = "print" _ = pcv.x_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.x_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) _ = pcv.x_axis_pseudolandmarks(obj=np.array([[0, 0], [0, 0]]), mask=np.array([[0, 0], [0, 0]]), img=img) _ = pcv.x_axis_pseudolandmarks(obj = np.array(([[89,222]],[[252,39]],[[89,207]])), mask = np.array(([[42, 161]], [[2, 47]], [[211, 222]])), img=img) _ = pcv.x_axis_pseudolandmarks(obj=(), mask=mask, img=img) # Test with debug = None pcv.params.debug = None top, bottom, center_v = pcv.x_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert all([all([i == j] for i, j in zip(np.shape(top), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(bottom), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(center_v), (20, 1, 2)))]) def test_plantcv_x_axis_pseudolandmarks_small_obj(): img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL_PLANT)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL_PLANT), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR_SMALL_PLANT), encoding="latin1") obj_contour = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _, _, _ = pcv.x_axis_pseudolandmarks(obj=[], mask=mask, img=img) _, _, _ = pcv.x_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) # Test with debug = "plot" pcv.params.debug = "plot" _, _, _ = pcv.x_axis_pseudolandmarks(obj=[], mask=mask, img=img) top, bottom, center_v = pcv.x_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) assert all([all([i == j] for i, j in zip(np.shape(top), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(bottom), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(center_v), (20, 1, 2)))]) def test_plantcv_x_axis_pseudolandmarks_bad_input(): img = np.array([]) mask = np.array([]) obj_contour = np.array([]) pcv.params.debug = None result = pcv.x_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) assert all([i == j] for i, j in zip(result, [("NA", "NA"), ("NA", "NA"), ("NA", "NA")])) def test_plantcv_x_axis_pseudolandmarks_bad_obj_input(): img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL_PLANT)) with pytest.raises(RuntimeError): _ = pcv.x_axis_pseudolandmarks(obj=np.array([[-2, -2], [-2, -2]]), mask=np.array([[-2, -2], [-2, -2]]), img=img) def test_plantcv_y_axis_pseudolandmarks(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_y_axis_pseudolandmarks_debug") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR), encoding="latin1") obj_contour = contours_npz['arr_0'] pcv.params.debug = "print" _ = pcv.y_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.y_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) pcv.outputs.clear() _ = pcv.y_axis_pseudolandmarks(obj=[], mask=mask, img=img) _ = pcv.y_axis_pseudolandmarks(obj=(), mask=mask, img=img) _ = pcv.y_axis_pseudolandmarks(obj=np.array(([[89, 222]], [[252, 39]], [[89, 207]])), mask=np.array(([[42, 161]], [[2, 47]], [[211, 222]])), img=img) _ = pcv.y_axis_pseudolandmarks(obj=np.array(([[21, 11]], [[159, 155]], [[237, 11]])), mask=np.array(([[38, 54]], [[144, 169]], [[81, 137]])), img=img) # Test with debug = None pcv.params.debug = None left, right, center_h = pcv.y_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert all([all([i == j] for i, j in zip(np.shape(left), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(right), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(center_h), (20, 1, 2)))]) def test_plantcv_y_axis_pseudolandmarks_small_obj(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_y_axis_pseudolandmarks_debug") os.mkdir(cache_dir) img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL_PLANT)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_MASK_SMALL_PLANT), -1) contours_npz = np.load(os.path.join(TEST_DATA, TEST_VIS_COMP_CONTOUR_SMALL_PLANT), encoding="latin1") obj_contour = contours_npz['arr_0'] # Test with debug = "print" pcv.params.debug = "print" _, _, _ = pcv.y_axis_pseudolandmarks(obj=[], mask=mask, img=img) _, _, _ = pcv.y_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) # Test with debug = "plot" pcv.params.debug = "plot" pcv.outputs.clear() left, right, center_h = pcv.y_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert all([all([i == j] for i, j in zip(np.shape(left), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(right), (20, 1, 2))), all([i == j] for i, j in zip(np.shape(center_h), (20, 1, 2)))]) def test_plantcv_y_axis_pseudolandmarks_bad_input(): cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_y_axis_pseudolandmarks_debug") os.mkdir(cache_dir) img = np.array([]) mask = np.array([]) obj_contour = np.array([]) pcv.params.debug = None result = pcv.y_axis_pseudolandmarks(obj=obj_contour, mask=mask, img=img) pcv.print_results(os.path.join(cache_dir, "results.txt")) pcv.outputs.clear() assert all([i == j] for i, j in zip(result, [("NA", "NA"), ("NA", "NA"), ("NA", "NA")])) def test_plantcv_y_axis_pseudolandmarks_bad_obj_input(): img = cv2.imread(os.path.join(TEST_DATA, TEST_VIS_SMALL_PLANT)) with pytest.raises(RuntimeError): _ = pcv.y_axis_pseudolandmarks(obj=np.array([[-2, -2], [-2, -2]]), mask=np.array([[-2, -2], [-2, -2]]), img=img) def test_plantcv_background_subtraction(): # List to hold result of all tests. truths = [] fg_img = cv2.imread(os.path.join(TEST_DATA, TEST_FOREGROUND)) bg_img = cv2.imread(os.path.join(TEST_DATA, TEST_BACKGROUND)) big_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Testing if background subtraction is actually still working. # This should return an array whose sum is greater than one pcv.params.debug = None fgmask = pcv.background_subtraction(background_image=bg_img, foreground_image=fg_img) truths.append(np.sum(fgmask) > 0) fgmask = pcv.background_subtraction(background_image=big_img, foreground_image=bg_img) truths.append(np.sum(fgmask) > 0) # The same foreground subtracted from itself should be 0 fgmask = pcv.background_subtraction(background_image=fg_img, foreground_image=fg_img) truths.append(np.sum(fgmask) == 0) # The same background subtracted from itself should be 0 fgmask = pcv.background_subtraction(background_image=bg_img, foreground_image=bg_img) truths.append(np.sum(fgmask) == 0) # All of these should be true for the function to pass testing. if cv2.__version__[0] == '2': assert (all(truths)) else: assert (all(truths)) def test_plantcv_background_subtraction_debug(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_background_subtraction_debug") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # List to hold result of all tests. truths = [] fg_img = cv2.imread(os.path.join(TEST_DATA, TEST_FOREGROUND)) bg_img = cv2.imread(os.path.join(TEST_DATA, TEST_BACKGROUND)) # Test with debug = "print" pcv.params.debug = "print" fgmask = pcv.background_subtraction(background_image=bg_img, foreground_image=fg_img) truths.append(np.sum(fgmask) > 0) # Test with debug = "plot" pcv.params.debug = "plot" fgmask = pcv.background_subtraction(background_image=bg_img, foreground_image=fg_img) truths.append(np.sum(fgmask) > 0) # All of these should be true for the function to pass testing. assert (all(truths)) def test_plantcv_background_subtraction_bad_img_type(): fg_color = cv2.imread(os.path.join(TEST_DATA, TEST_FOREGROUND)) bg_gray = cv2.imread(os.path.join(TEST_DATA, TEST_BACKGROUND), 0) pcv.params.debug = None with pytest.raises(RuntimeError): _ = pcv.background_subtraction(background_image=bg_gray, foreground_image=fg_color) def test_plantcv_background_subtraction_different_sizes(): fg_img = cv2.imread(os.path.join(TEST_DATA, TEST_FOREGROUND)) bg_img = cv2.imread(os.path.join(TEST_DATA, TEST_BACKGROUND)) bg_shp = np.shape(bg_img) # type: tuple bg_img_resized = cv2.resize(bg_img, (int(bg_shp[0] / 2), int(bg_shp[1] / 2)), interpolation=cv2.INTER_AREA) pcv.params.debug = None fgmask = pcv.background_subtraction(background_image=bg_img_resized, foreground_image=fg_img) assert np.sum(fgmask) > 0 # ############################## # Tests for the learn subpackage # ############################## def test_plantcv_learn_naive_bayes(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_learn_naive_bayes") os.mkdir(cache_dir) # Make image and mask directories in the cache directory imgdir = os.path.join(cache_dir, "images") maskdir = os.path.join(cache_dir, "masks") if not os.path.exists(imgdir): os.mkdir(imgdir) if not os.path.exists(maskdir): os.mkdir(maskdir) # Copy and image and mask to the image/mask directories shutil.copyfile(os.path.join(TEST_DATA, TEST_VIS_SMALL), os.path.join(imgdir, "image.png")) shutil.copyfile(os.path.join(TEST_DATA, TEST_MASK_SMALL), os.path.join(maskdir, "image.png")) # Run the naive Bayes training module outfile = os.path.join(cache_dir, "naive_bayes_pdfs.txt") plantcv.learn.naive_bayes(imgdir=imgdir, maskdir=maskdir, outfile=outfile, mkplots=True) assert os.path.exists(outfile) def test_plantcv_learn_naive_bayes_multiclass(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_learn_naive_bayes_multiclass") os.mkdir(cache_dir) # Run the naive Bayes multiclass training module outfile = os.path.join(cache_dir, "naive_bayes_multiclass_pdfs.txt") plantcv.learn.naive_bayes_multiclass(samples_file=os.path.join(TEST_DATA, TEST_SAMPLED_RGB_POINTS), outfile=outfile, mkplots=True) assert os.path.exists(outfile) # ############################## # Tests for the roi subpackage # ############################## def test_plantcv_roi_from_binary_image(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_roi_from_binary_image") os.mkdir(cache_dir) # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Create a binary image bin_img = np.zeros(np.shape(rgb_img)[0:2], dtype=np.uint8) cv2.rectangle(bin_img, (100, 100), (1000, 1000), 255, -1) # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = cache_dir _, _ = pcv.roi.from_binary_image(bin_img=bin_img, img=rgb_img) # Test with debug = "plot" pcv.params.debug = "plot" _, _ = pcv.roi.from_binary_image(bin_img=bin_img, img=rgb_img) # Test with debug = None pcv.params.debug = None roi_contour, roi_hierarchy = pcv.roi.from_binary_image(bin_img=bin_img, img=rgb_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 3600, 1, 2) def test_plantcv_roi_from_binary_image_grayscale_input(): # Read in a test grayscale image gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Create a binary image bin_img = np.zeros(np.shape(gray_img)[0:2], dtype=np.uint8) cv2.rectangle(bin_img, (100, 100), (1000, 1000), 255, -1) # Test with debug = "plot" pcv.params.debug = "plot" roi_contour, roi_hierarchy = pcv.roi.from_binary_image(bin_img=bin_img, img=gray_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 3600, 1, 2) def test_plantcv_roi_from_binary_image_bad_binary_input(): # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Binary input is required but an RGB input is provided with pytest.raises(RuntimeError): _, _ = pcv.roi.from_binary_image(bin_img=rgb_img, img=rgb_img) def test_plantcv_roi_rectangle(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_roi_rectangle") os.mkdir(cache_dir) # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = cache_dir _, _ = pcv.roi.rectangle(x=100, y=100, h=500, w=500, img=rgb_img) # Test with debug = "plot" pcv.params.debug = "plot" _, _ = pcv.roi.rectangle(x=100, y=100, h=500, w=500, img=rgb_img) # Test with debug = None pcv.params.debug = None roi_contour, roi_hierarchy = pcv.roi.rectangle(x=100, y=100, h=500, w=500, img=rgb_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 4, 1, 2) def test_plantcv_roi_rectangle_grayscale_input(): # Read in a test grayscale image gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "plot" pcv.params.debug = "plot" roi_contour, roi_hierarchy = pcv.roi.rectangle(x=100, y=100, h=500, w=500, img=gray_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 4, 1, 2) def test_plantcv_roi_rectangle_out_of_frame(): # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # The resulting rectangle needs to be within the dimensions of the image with pytest.raises(RuntimeError): _, _ = pcv.roi.rectangle(x=100, y=100, h=500, w=3000, img=rgb_img) def test_plantcv_roi_circle(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_roi_circle") os.mkdir(cache_dir) # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = cache_dir _, _ = pcv.roi.circle(x=100, y=100, r=50, img=rgb_img) # Test with debug = "plot" pcv.params.debug = "plot" _, _ = pcv.roi.circle(x=100, y=100, r=50, img=rgb_img) # Test with debug = None pcv.params.debug = None roi_contour, roi_hierarchy = pcv.roi.circle(x=200, y=225, r=75, img=rgb_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 424, 1, 2) def test_plantcv_roi_circle_grayscale_input(): # Read in a test grayscale image gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "plot" pcv.params.debug = "plot" roi_contour, roi_hierarchy = pcv.roi.circle(x=200, y=225, r=75, img=gray_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 424, 1, 2) def test_plantcv_roi_circle_out_of_frame(): # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # The resulting rectangle needs to be within the dimensions of the image with pytest.raises(RuntimeError): _, _ = pcv.roi.circle(x=50, y=225, r=75, img=rgb_img) def test_plantcv_roi_ellipse(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_roi_ellipse") os.mkdir(cache_dir) # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = cache_dir _, _ = pcv.roi.ellipse(x=200, y=200, r1=75, r2=50, angle=0, img=rgb_img) # Test with debug = "plot" pcv.params.debug = "plot" _, _ = pcv.roi.ellipse(x=200, y=200, r1=75, r2=50, angle=0, img=rgb_img) # Test with debug = None pcv.params.debug = None roi_contour, roi_hierarchy = pcv.roi.ellipse(x=200, y=200, r1=75, r2=50, angle=0, img=rgb_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 360, 1, 2) def test_plantcv_roi_ellipse_grayscale_input(): # Read in a test grayscale image gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "plot" pcv.params.debug = "plot" roi_contour, roi_hierarchy = pcv.roi.ellipse(x=200, y=200, r1=75, r2=50, angle=0, img=gray_img) # Assert the contours and hierarchy lists contain only the ROI assert np.shape(roi_contour) == (1, 360, 1, 2) def test_plantcv_roi_ellipse_out_of_frame(): # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # The resulting rectangle needs to be within the dimensions of the image with pytest.raises(RuntimeError): _, _ = pcv.roi.ellipse(x=50, y=225, r1=75, r2=50, angle=0, img=rgb_img) def test_plantcv_roi_multi(): # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.roi.multi(rgb_img, coord=[(25, 120), (100, 100)], radius=20) # Test with debug = None pcv.params.debug = None rois1, roi_hierarchy1 = pcv.roi.multi(rgb_img, coord=(25, 120), radius=20, spacing=(10, 10), nrows=3, ncols=6) # Assert the contours has 18 ROIs assert len(rois1)==18 def test_plantcv_roi_multi_bad_input(): # Read in test RGB image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_COLOR)) # The user must input a list of custom coordinates OR inputs to make a grid. Not both with pytest.raises(RuntimeError): _, _ = pcv.roi.multi(rgb_img, coord=[(25, 120), (100, 100)], radius=20, spacing=(10, 10), nrows=3, ncols=6) # ############################## # Tests for the transform subpackage # ############################## def test_plantcv_transform_get_color_matrix(): # load in target_matrix matrix_file = np.load(os.path.join(TEST_DATA, TEST_TARGET_MATRIX), encoding="latin1") matrix_compare = matrix_file['arr_0'] # Read in rgb_img and gray-scale mask rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK), -1) # The result should be a len(np.unique(mask))-1 x 4 matrix headers, matrix = pcv.transform.get_color_matrix(rgb_img, mask) assert np.array_equal(matrix, matrix_compare) def test_plantcv_transform_get_color_matrix_img(): # Read in two gray-scale images rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK), -1) mask = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK), -1) # The input for rgb_img needs to be an RGB image with pytest.raises(RuntimeError): _, _ = pcv.transform.get_color_matrix(rgb_img, mask) def test_plantcv_transform_get_color_matrix_mask(): # Read in two gray-scale images rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK)) # The input for rgb_img needs to be an RGB image with pytest.raises(RuntimeError): _, _ = pcv.transform.get_color_matrix(rgb_img, mask) def test_plantcv_transform_get_matrix_m(): # load in comparison matrices matrix_m_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_M1), encoding="latin1") matrix_compare_m = matrix_m_file['arr_0'] matrix_b_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B1), encoding="latin1") matrix_compare_b = matrix_b_file['arr_0'] # read in matrices t_matrix_file = np.load(os.path.join(TEST_DATA, TEST_TARGET_MATRIX), encoding="latin1") t_matrix = t_matrix_file['arr_0'] s_matrix_file = np.load(os.path.join(TEST_DATA, TEST_SOURCE1_MATRIX), encoding="latin1") s_matrix = s_matrix_file['arr_0'] # apply matrices to function matrix_a, matrix_m, matrix_b = pcv.transform.get_matrix_m(t_matrix, s_matrix) matrix_compare_m = np.rint(matrix_compare_m) matrix_compare_b = np.rint(matrix_compare_b) matrix_m = np.rint(matrix_m) matrix_b = np.rint(matrix_b) assert np.array_equal(matrix_m, matrix_compare_m) and np.array_equal(matrix_b, matrix_compare_b) def test_plantcv_transform_get_matrix_m_unequal_data(): # load in comparison matrices matrix_m_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_M2), encoding="latin1") matrix_compare_m = matrix_m_file['arr_0'] matrix_b_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B2), encoding="latin1") matrix_compare_b = matrix_b_file['arr_0'] # read in matrices t_matrix_file = np.load(os.path.join(TEST_DATA, TEST_TARGET_MATRIX), encoding="latin1") t_matrix = t_matrix_file['arr_0'] s_matrix_file = np.load(os.path.join(TEST_DATA, TEST_SOURCE2_MATRIX), encoding="latin1") s_matrix = s_matrix_file['arr_0'] # apply matrices to function matrix_a, matrix_m, matrix_b = pcv.transform.get_matrix_m(t_matrix, s_matrix) matrix_compare_m = np.rint(matrix_compare_m) matrix_compare_b = np.rint(matrix_compare_b) matrix_m = np.rint(matrix_m) matrix_b = np.rint(matrix_b) assert np.array_equal(matrix_m, matrix_compare_m) and np.array_equal(matrix_b, matrix_compare_b) def test_plantcv_transform_calc_transformation_matrix(): # load in comparison matrices matrix_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_compare = matrix_file['arr_0'] # read in matrices matrix_m_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_M1), encoding="latin1") matrix_m = matrix_m_file['arr_0'] matrix_b_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B1), encoding="latin1") matrix_b = matrix_b_file['arr_0'] # apply to function _, matrix_t = pcv.transform.calc_transformation_matrix(matrix_m, matrix_b) matrix_t = np.rint(matrix_t) matrix_compare = np.rint(matrix_compare) assert np.array_equal(matrix_t, matrix_compare) def test_plantcv_transform_calc_transformation_matrix_b_incorrect(): # read in matrices matrix_m_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_M1), encoding="latin1") matrix_m = matrix_m_file['arr_0'] matrix_b_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B1), encoding="latin1") matrix_b = matrix_b_file['arr_0'] matrix_b = np.asmatrix(matrix_b, float) with pytest.raises(RuntimeError): _, _ = pcv.transform.calc_transformation_matrix(matrix_m, matrix_b.T) def test_plantcv_transform_calc_transformation_matrix_not_mult(): # read in matrices matrix_m_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_M1), encoding="latin1") matrix_m = matrix_m_file['arr_0'] matrix_b_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B1), encoding="latin1") matrix_b = matrix_b_file['arr_0'] with pytest.raises(RuntimeError): _, _ = pcv.transform.calc_transformation_matrix(matrix_m, matrix_b[:3]) def test_plantcv_transform_calc_transformation_matrix_not_mat(): # read in matrices matrix_m_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_M1), encoding="latin1") matrix_m = matrix_m_file['arr_0'] matrix_b_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B1), encoding="latin1") matrix_b = matrix_b_file['arr_0'] with pytest.raises(RuntimeError): _, _ = pcv.transform.calc_transformation_matrix(matrix_m[:, 1], matrix_b[:, 1]) def test_plantcv_transform_apply_transformation(): # load corrected image to compare corrected_compare = cv2.imread(os.path.join(TEST_DATA, TEST_S1_CORRECTED)) # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform") os.mkdir(cache_dir) # Make image and mask directories in the cache directory imgdir = os.path.join(cache_dir, "images") # read in matrices matrix_t_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_t = matrix_t_file['arr_0'] # read in images target_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) source_img = cv2.imread(os.path.join(TEST_DATA, TEST_SOURCE1_IMG)) # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = imgdir _ = pcv.transform.apply_transformation_matrix(source_img, target_img, matrix_t) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.transform.apply_transformation_matrix(source_img, target_img, matrix_t) # Test with debug = None pcv.params.debug = None corrected_img = pcv.transform.apply_transformation_matrix(source_img, target_img, matrix_t) # assert source and corrected have same shape assert np.array_equal(corrected_img, corrected_compare) def test_plantcv_transform_apply_transformation_incorrect_t(): # read in matrices matrix_t_file = np.load(os.path.join(TEST_DATA, TEST_MATRIX_B1), encoding="latin1") matrix_t = matrix_t_file['arr_0'] # read in images target_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) source_img = cv2.imread(os.path.join(TEST_DATA, TEST_SOURCE1_IMG)) with pytest.raises(RuntimeError): _ = pcv.transform.apply_transformation_matrix(source_img, target_img, matrix_t) def test_plantcv_transform_apply_transformation_incorrect_img(): # read in matrices matrix_t_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_t = matrix_t_file['arr_0'] # read in images target_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) source_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK), -1) with pytest.raises(RuntimeError): _ = pcv.transform.apply_transformation_matrix(source_img, target_img, matrix_t) def test_plantcv_transform_save_matrix(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform") os.mkdir(cache_dir) # read in matrix matrix_t_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_t = matrix_t_file['arr_0'] # .npz filename filename = os.path.join(cache_dir, 'test.npz') pcv.transform.save_matrix(matrix_t, filename) assert os.path.exists(filename) is True def test_plantcv_transform_save_matrix_incorrect_filename(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform") os.mkdir(cache_dir) # read in matrix matrix_t_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_t = matrix_t_file['arr_0'] # .npz filename filename = "test" with pytest.raises(RuntimeError): pcv.transform.save_matrix(matrix_t, filename) def test_plantcv_transform_load_matrix(): # read in matrix_t matrix_t_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_t = matrix_t_file['arr_0'] # test load function with matrix_t matrix_t_loaded = pcv.transform.load_matrix(os.path.join(TEST_DATA, TEST_TRANSFORM1)) assert np.array_equal(matrix_t, matrix_t_loaded) def test_plantcv_transform_correct_color(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform") os.mkdir(cache_dir) # load corrected image to compare corrected_compare = cv2.imread(os.path.join(TEST_DATA, TEST_S1_CORRECTED)) # load in comparison matrices matrix_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_compare = matrix_file['arr_0'] # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform_correct_color") os.mkdir(cache_dir) # Make image and mask directories in the cache directory imgdir = os.path.join(cache_dir, "images") matdir = os.path.join(cache_dir, "saved_matrices") # Read in target, source, and gray-scale mask target_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) source_img = cv2.imread(os.path.join(TEST_DATA, TEST_SOURCE1_IMG)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK), -1) output_path = os.path.join(matdir) # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = imgdir _, _, _, _ = pcv.transform.correct_color(target_img, mask, source_img, mask, cache_dir) # Test with debug = "plot" pcv.params.debug = "plot" _, _, _, _ = pcv.transform.correct_color(target_img, mask, source_img, mask, output_path) # Test with debug = None pcv.params.debug = None _, _, matrix_t, corrected_img = pcv.transform.correct_color(target_img, mask, source_img, mask, output_path) # assert source and corrected have same shape assert np.array_equal(corrected_img, corrected_compare) and \ os.path.exists(os.path.join(output_path, "target_matrix.npz")) is True and \ os.path.exists(os.path.join(output_path, "source_matrix.npz")) is True and \ os.path.exists(os.path.join(output_path, "transformation_matrix.npz")) is True def test_plantcv_transform_correct_color_output_dne(): # load corrected image to compare corrected_compare = cv2.imread(os.path.join(TEST_DATA, TEST_S1_CORRECTED)) # load in comparison matrices matrix_file = np.load(os.path.join(TEST_DATA, TEST_TRANSFORM1), encoding="latin1") matrix_compare = matrix_file['arr_0'] # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform_correct_color_output_dne") os.mkdir(cache_dir) # Make image and mask directories in the cache directory imgdir = os.path.join(cache_dir, "images") # Read in target, source, and gray-scale mask target_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) source_img = cv2.imread(os.path.join(TEST_DATA, TEST_SOURCE1_IMG)) mask = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_MASK), -1) output_path = os.path.join(cache_dir, "saved_matrices_1") # output_directory that does not currently exist # Test with debug = "print" pcv.params.debug = "print" pcv.params.debug_outdir = imgdir _, _, _, _ = pcv.transform.correct_color(target_img, mask, source_img, mask, output_path) # Test with debug = "plot" pcv.params.debug = "plot" _, _, _, _ = pcv.transform.correct_color(target_img, mask, source_img, mask, output_path) # Test with debug = None pcv.params.debug = None _, _, matrix_t, corrected_img = pcv.transform.correct_color(target_img, mask, source_img, mask, output_path) # assert source and corrected have same shape assert np.array_equal(corrected_img, corrected_compare) and \ os.path.exists(os.path.join(output_path, "target_matrix.npz")) is True and \ os.path.exists(os.path.join(output_path, "source_matrix.npz")) is True and \ os.path.exists(os.path.join(output_path, "transformation_matrix.npz")) is True def test_plantcv_transform_create_color_card_mask(): # Load target image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform_create_color_card_mask") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Test with debug = "print" pcv.params.debug = "print" _ = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=(166, 166), spacing=(21, 21), nrows=6, ncols=4, exclude=[20, 0]) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=(166, 166), spacing=(21, 21), nrows=6, ncols=4, exclude=[20, 0]) # Test with debug = None pcv.params.debug = None mask = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=(166, 166), spacing=(21, 21), nrows=6, ncols=4, exclude=[20, 0]) assert all([i == j] for i, j in zip(np.unique(mask), np.array([0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220], dtype=np.uint8))) def test_plantcv_transform_quick_color_check(): # Load target image t_matrix = np.load(os.path.join(TEST_DATA, TEST_TARGET_MATRIX), encoding="latin1") target_matrix = t_matrix['arr_0'] s_matrix = np.load(os.path.join(TEST_DATA, TEST_SOURCE1_MATRIX), encoding="latin1") source_matrix = s_matrix['arr_0'] # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform_quick_color_check") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Test with debug = "print" pcv.params.debug = "print" pcv.transform.quick_color_check(target_matrix, source_matrix, num_chips=22) # Test with debug = "plot" pcv.params.debug = "plot" pcv.transform.quick_color_check(target_matrix, source_matrix, num_chips=22) #Test with debug = None pcv.params.debug = None pcv.transform.quick_color_check(target_matrix, source_matrix, num_chips=22) assert os.path.exists(os.path.join(cache_dir, "color_quick_check.png")) def test_plantcv_transform_find_color_card(): # Load rgb image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform_find_color_card") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir df, start, space = pcv.transform.find_color_card(rgb_img=rgb_img, threshold='adaptgauss', blurry=False) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=start, spacing=space, nrows=6, ncols=4, exclude=[20, 0]) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=start, spacing=space, nrows=6, ncols=4, exclude=[20, 0]) # Test with debug = None pcv.params.debug = None mask = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=start, spacing=space, nrows=6, ncols=4, exclude=[20, 0]) assert all([i == j] for i, j in zip(np.unique(mask), np.array([0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220], dtype=np.uint8))) def test_plantcv_transform_find_color_card_optional_parameters(): # Load rgb image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG_COLOR_CARD)) # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_transform_find_color_card") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Test with threshold ='normal' df1, start1, space1 = pcv.transform.find_color_card(rgb_img=rgb_img, threshold='normal', blurry=True, background='light') _ = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=start1, spacing=space1, nrows=6, ncols=4, exclude=[20, 0]) # Test with threshold='otsu' df2, start2, space2 = pcv.transform.find_color_card(rgb_img=rgb_img, threshold='otsu', blurry=True) _ = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=start2, spacing=space2, nrows=6, ncols=4, exclude=[20, 0]) # Test with debug = None pcv.params.debug = None mask = pcv.transform.create_color_card_mask(rgb_img=rgb_img, radius=6, start_coord=start2, spacing=space2, nrows=6, ncols=4, exclude=[20, 0]) assert all([i == j] for i, j in zip(np.unique(mask), np.array([0, 10, 20, 30, 40, 50, 60, 70, 80, 90, 100, 110, 120, 130, 140, 150, 160, 170, 180, 190, 200, 210, 220], dtype=np.uint8))) def test_plantcv_transform_find_color_card_bad_thresh_input(): # Load rgb image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) with pytest.raises(RuntimeError): pcv.params.debug = None _, _, _ = pcv.transform.find_color_card(rgb_img=rgb_img, threshold='gaussian') def test_plantcv_transform_find_color_card_bad_background_input(): # Load rgb image rgb_img = cv2.imread(os.path.join(TEST_DATA, TEST_TARGET_IMG)) with pytest.raises(RuntimeError): pcv.params.debug = None _, _, _ = pcv.transform.find_color_card(rgb_img=rgb_img, background='lite') # ############################## # Tests for the threshold subpackage # ############################## def test_plantcv_threshold_binary(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_threshold_binary") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with object type = dark pcv.params.debug = None _ = pcv.threshold.binary(gray_img=gray_img, threshold=25, max_value=255, object_type="dark") # Test with debug = "print" pcv.params.debug = "print" _ = pcv.threshold.binary(gray_img=gray_img, threshold=25, max_value=255, object_type="light") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.threshold.binary(gray_img=gray_img, threshold=25, max_value=255, object_type="light") # Test with debug = None pcv.params.debug = None binary_img = pcv.threshold.binary(gray_img=gray_img, threshold=25, max_value=255, object_type="light") # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(binary_img), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(binary_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_threshold_binary_incorrect_object_type(): gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.threshold.binary(gray_img=gray_img, threshold=25, max_value=255, object_type="lite") def test_plantcv_threshold_gaussian(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_threshold_gaussian") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with object type = dark pcv.params.debug = None _ = pcv.threshold.gaussian(gray_img=gray_img, max_value=255, object_type="dark") # Test with debug = "print" pcv.params.debug = "print" _ = pcv.threshold.gaussian(gray_img=gray_img, max_value=255, object_type="light") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.threshold.gaussian(gray_img=gray_img, max_value=255, object_type="light") # Test with debug = None pcv.params.debug = None binary_img = pcv.threshold.gaussian(gray_img=gray_img, max_value=255, object_type="light") # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(binary_img), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(binary_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_threshold_gaussian_incorrect_object_type(): gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.threshold.gaussian(gray_img=gray_img, max_value=255, object_type="lite") def test_plantcv_threshold_mean(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_threshold_mean") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with object type = dark pcv.params.debug = None _ = pcv.threshold.mean(gray_img=gray_img, max_value=255, object_type="dark") # Test with debug = "print" pcv.params.debug = "print" _ = pcv.threshold.mean(gray_img=gray_img, max_value=255, object_type="light") # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.threshold.mean(gray_img=gray_img, max_value=255, object_type="light") # Test with debug = None pcv.params.debug = None binary_img = pcv.threshold.mean(gray_img=gray_img, max_value=255, object_type="light") # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(binary_img), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(binary_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_threshold_mean_incorrect_object_type(): gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.threshold.mean(gray_img=gray_img, max_value=255, object_type="lite") def test_plantcv_threshold_otsu(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_threshold_otsu") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INTPUT_GREENMAG), -1) # Test with object set to light pcv.params.debug = None _ = pcv.threshold.otsu(gray_img=gray_img, max_value=255, object_type="light") # Test with debug = "print" pcv.params.debug = "print" _ = pcv.threshold.otsu(gray_img=gray_img, max_value=255, object_type='dark') # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.threshold.otsu(gray_img=gray_img, max_value=255, object_type='dark') # Test with debug = None pcv.params.debug = None binary_img = pcv.threshold.otsu(gray_img=gray_img, max_value=255, object_type='dark') # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(binary_img), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(binary_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_threshold_otsu_incorrect_object_type(): gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.threshold.otsu(gray_img=gray_img, max_value=255, object_type="lite") def test_plantcv_threshold_triangle(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_threshold_triangle") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir # Read in test data gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) # Test with debug = "print" pcv.params.debug = "print" _ = pcv.threshold.triangle(gray_img=gray_img, max_value=255, object_type="dark", xstep=10) # Test with debug = "plot" pcv.params.debug = "plot" _ = pcv.threshold.triangle(gray_img=gray_img, max_value=255, object_type="light", xstep=10) # Test with debug = None pcv.params.debug = None binary_img = pcv.threshold.triangle(gray_img=gray_img, max_value=255, object_type="light", xstep=10) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(binary_img), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(binary_img), [0, 255])): assert 1 else: assert 0 else: assert 0 def test_plantcv_threshold_triangle_incorrect_object_type(): gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY), -1) with pytest.raises(RuntimeError): pcv.params.debug = None _ = pcv.threshold.triangle(gray_img=gray_img, max_value=255, object_type="lite", xstep=10) def test_plantcv_threshold_texture(): # Test cache directory cache_dir = os.path.join(TEST_TMPDIR, "test_plantcv_threshold_texture") os.mkdir(cache_dir) pcv.params.debug_outdir = cache_dir gray_img = cv2.imread(os.path.join(TEST_DATA, TEST_INPUT_GRAY_SMALL), -1) binary_img = pcv.threshold.texture(gray_img, ksize=6, threshold=7, offset=3, texture_method='dissimilarity', borders='nearest', max_value=255) # Assert that the output image has the dimensions of the input image if all([i == j] for i, j in zip(np.shape(binary_img), TEST_GRAY_DIM)): # Assert that the image is binary if all([i == j] for i, j in zip(np.unique(binary_img), [0, 255])): assert 1 else: assert 0 else: assert 0 # ############################## # Clean up test files # ############################## def teardown_function(): shutil.rmtree(TEST_TMPDIR)

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pycachecleaner/__init__.py

mikk357/pycachecleaner

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[ "MIT" ]

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2021-01-20T05:47:08.000Z

pycachecleaner/__init__.py

mikk357/pycachecleaner

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pycachecleaner/__init__.py

mikk357/pycachecleaner

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tests/tests/__init__.py

aptivate/django-organizations

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tests/tests/__init__.py

philippeowagner/django-organizations

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tests/tests/__init__.py

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microproxy/event/__init__.py

mike820324/microProxy

64c7c5add4759c6e105b9438cd18c0f8c930c7a3

[ "MIT" ]

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microproxy/event/__init__.py

mike820324/microProxy

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[ "MIT" ]

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microproxy/event/__init__.py

mike820324/microProxy

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[ "MIT" ]

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from manager import EventManager from client import EventClient from manager import start_events_server from types import REPLAY

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tests/legacy_unittest/test_fee_engine.py

bayeshack2016/icon-service

36cab484d2e41548d7f2f74526f127ee3a4423fc

[ "Apache-2.0" ]

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tests/legacy_unittest/test_fee_engine.py

bayeshack2016/icon-service

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2018-09-17T06:59:16.000Z

2021-12-15T06:02:51.000Z

tests/legacy_unittest/test_fee_engine.py

bayeshack2016/icon-service

36cab484d2e41548d7f2f74526f127ee3a4423fc

[ "Apache-2.0" ]

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2018-09-14T02:42:10.000Z

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# -*- coding: utf-8 -*- # Copyright 2019 ICON Foundation # # Licensed under the Apache License, Version 2.0 (the "License"); # you may not use this file except in compliance with the License. # You may obtain a copy of the License at # # http://www.apache.org/licenses/LICENSE-2.0 # # Unless required by applicable law or agreed to in writing, software # distributed under the License is distributed on an "AS IS" BASIS, # WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. # See the License for the specific language governing permissions and # limitations under the License. import os import unittest from random import randrange from unittest.mock import Mock from iconservice.base.address import AddressPrefix, Address from iconservice.base.block import Block from iconservice.base.exception import InvalidRequestException, OutOfBalanceException from iconservice.base.transaction import Transaction from iconservice.database.db import ContextDatabase from iconservice.deploy import DeployStorage from iconservice.deploy.storage import IconScoreDeployInfo from iconservice.fee import FeeEngine, FeeStorage from iconservice.fee.engine import VirtualStepCalculator, FIXED_TERM from iconservice.icon_constant import IconScoreContextType, DeployState from iconservice.iconscore.icon_score_context import IconScoreContext from iconservice.iconscore.context.context import ContextContainer from iconservice.iconscore.icon_score_step import IconScoreStepCounter from iconservice.icx import IcxEngine from iconservice.icx import IcxStorage from iconservice.icx.coin_part import CoinPartType from iconservice.utils import ContextStorage, ContextEngine from tests.legacy_unittest.mock_generator import clear_inner_task def create_context_db(): """ Create memory db for ContextDatabase :return: ContextDatabase """ memory_db = {} # noinspection PyUnusedLocal def put(context, key, value): memory_db[key] = value # noinspection PyUnusedLocal def get(context, key): return memory_db.get(key) # noinspection PyUnusedLocal def delete(context, key): del memory_db[key] context_db = Mock(spec=ContextDatabase) context_db.get = get context_db.put = put context_db.delete = delete return context_db def patch_fee_storage(fee_storage: FeeStorage): memory_db = {} # noinspection PyUnusedLocal def put(context, key, value): memory_db[key] = value # noinspection PyUnusedLocal def put_deposit(context, deposit): memory_db[deposit.id] = deposit # noinspection PyUnusedLocal def get(context, key): return memory_db[key] if key in memory_db else None # noinspection PyUnusedLocal def delete(context, key): del memory_db[key] fee_storage.put_deposit_meta = put fee_storage.get_deposit_meta = get fee_storage.delete_deposit_meta = delete fee_storage.put_deposit = put_deposit fee_storage.get_deposit = get fee_storage.delete_deposit = delete def get_rand_term(): if FIXED_TERM: return FeeEngine._MIN_DEPOSIT_TERM else: return randrange(FeeEngine._MIN_DEPOSIT_TERM, FeeEngine._MAX_DEPOSIT_TERM) calculate_virtual_step = VirtualStepCalculator.calculate_virtual_step class TestFeeEngine(unittest.TestCase): def setUp(self): context = IconScoreContext(IconScoreContextType.DIRECT) block = Mock(spec=Block) block.attach_mock(Mock(return_value=0), 'height') context.block = block self._sender = Address.from_data(AddressPrefix.EOA, os.urandom(20)) self._score_address = Address.from_data(AddressPrefix.CONTRACT, os.urandom(20)) context_db = create_context_db() self.deploy_storage = DeployStorage(context_db) deploy_info = IconScoreDeployInfo(self._score_address, DeployState.ACTIVE, self._sender, os.urandom(32), os.urandom(32)) self.icx_storage = IcxStorage(context_db) self._icx_engine = IcxEngine() self.fee_storage = FeeStorage(context_db) patch_fee_storage(self.fee_storage) self.deploy_storage.put_deploy_info(context, deploy_info) context.storage = ContextStorage(deploy=self.deploy_storage, fee=self.fee_storage, icx=self.icx_storage, iiss=None, prep=None, issue=None, rc=None, meta=None) context.engine = ContextEngine(deploy=None, fee=None, icx=self._icx_engine, iiss=None, prep=None, issue=None) self._icx_engine.open(self.icx_storage) self.icx_storage._put_genesis_data_account(context, CoinPartType.GENERAL, self._sender, 100000000 * 10 ** 18) self.icx_storage._put_genesis_data_account(context, CoinPartType.TREASURY, Address.from_data(AddressPrefix.EOA, os.urandom(20)), 0) self._engine = FeeEngine() def tearDown(self): ContextContainer._clear_context() clear_inner_task() VirtualStepCalculator.calculate_virtual_step = calculate_virtual_step def get_context(self): context = IconScoreContext(IconScoreContextType.INVOKE) context.step_counter = Mock(spec=IconScoreStepCounter) context.step_counter.step_price = 10 ** 10 context.tx = Mock(spec=Transaction) context.tx.to = self._score_address block = Mock(spec=Block) block.attach_mock(Mock(return_value=0), 'height') context.block = block context.storage = ContextStorage(deploy=self.deploy_storage,fee=self.fee_storage, icx=self.icx_storage, iiss=None, prep=None, issue=None, rc=None, meta=None) context.engine = ContextEngine(deploy=None, fee=None, icx=self._icx_engine, iiss=None, prep=None, issue=None) return context def _deposit_bulk(self, count): self.context = self.get_context() self.block_height = 0 input_params = [] for i in range(count): tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() before_sender_balance = self._icx_engine.get_balance(self.context, self._sender) self._engine.add_deposit( self.context, tx_hash, self._sender, self._score_address, amount, block_height, term) after_sender_balance = self._icx_engine.get_balance(self.context, self._sender) self.assertEqual(amount, before_sender_balance - after_sender_balance) input_params.append((tx_hash, amount, block_height, term)) return input_params def test_deposit_fee(self): context = self.get_context() block_height = 0 size = randrange(10, 100) input_param = self._deposit_bulk(size) deposit_info = self._engine.get_deposit_info(context, self._score_address, block_height) self.assertEqual(size, len(deposit_info.deposits)) for i in range(size): tx_hash, amount, block_height, term = input_param[i] deposit = deposit_info.deposits[i] self.assertEqual(tx_hash, deposit.id) self.assertEqual(self._sender, deposit.sender) self.assertEqual(self._score_address, deposit.score_address) self.assertEqual(amount, deposit.deposit_amount) self.assertEqual(block_height, deposit.created) self.assertEqual(block_height + term, deposit.expires) def test_deposit_append_and_delete(self): size = randrange(10, 100) deposit_list = self._deposit_bulk(size) for i in range(size): index = randrange(0, size) size -= 1 withdrawal_deposit_id = deposit_list.pop(index)[0] self._engine.withdraw_deposit(self.context, self._sender, withdrawal_deposit_id, 1) deposit_info = self._engine.get_deposit_info(self.context, self._score_address, 1) for j in range(size): deposit = deposit_info.deposits[j] self.assertEqual(deposit.id, deposit_list[j][0]) self.assertEqual(self._sender, deposit.sender) self.assertEqual(self._score_address, deposit.score_address) self.assertEqual(deposit.deposit_amount, deposit_list[j][1]) self.assertEqual(deposit.created, deposit_list[j][2]) self.assertEqual(deposit.expires, deposit_list[j][2] + deposit_list[j][3]) input_param = self._deposit_bulk(100) deposit_info = self._engine.get_deposit_info(self.context, self._score_address, self.block_height) self.assertEqual(100, len(deposit_info.deposits)) for i in range(size): tx_hash, amount, block_height, term = input_param[i] deposit = deposit_info.deposits[i] self.assertEqual(tx_hash, deposit.id) self.assertEqual(self._sender, deposit.sender) self.assertEqual(self._score_address, deposit.score_address) self.assertEqual(amount, deposit.deposit_amount) self.assertEqual(block_height, deposit.created) self.assertEqual(block_height + term, deposit.expires) def test_deposit_fee_invalid_param(self): context = self.get_context() tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() # invalid amount (underflow) # noinspection PyTypeChecker with self.assertRaises(InvalidRequestException) as e: inv_amount = randrange(0, FeeEngine._MIN_DEPOSIT_AMOUNT - 1) self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, inv_amount, block_height, term) # noinspection PyUnresolvedReferences self.assertEqual('Invalid deposit amount', e.exception.message) # invalid amount (overflow) # noinspection PyTypeChecker with self.assertRaises(InvalidRequestException) as e: inv_amount = \ randrange(FeeEngine._MAX_DEPOSIT_AMOUNT + 1, FeeEngine._MAX_DEPOSIT_AMOUNT * 10) self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, inv_amount, block_height, term) # noinspection PyUnresolvedReferences self.assertEqual('Invalid deposit amount', e.exception.message) # invalid term (underflow) # noinspection PyTypeChecker with self.assertRaises(InvalidRequestException) as e: inv_term = randrange(0, FeeEngine._MIN_DEPOSIT_TERM - 1) self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, amount, block_height, inv_term) # noinspection PyUnresolvedReferences self.assertEqual('Invalid deposit term', e.exception.message) # invalid term (overflow) # noinspection PyTypeChecker with self.assertRaises(InvalidRequestException) as e: inv_term = \ randrange(FeeEngine._MAX_DEPOSIT_TERM + 1, FeeEngine._MAX_DEPOSIT_TERM * 10) self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, amount, block_height, inv_term) # noinspection PyUnresolvedReferences self.assertEqual('Invalid deposit term', e.exception.message) # invalid owner # noinspection PyTypeChecker with self.assertRaises(InvalidRequestException) as e: inv_sender = Address.from_data(AddressPrefix.EOA, os.urandom(20)) self._engine.add_deposit(context, tx_hash, inv_sender, self._score_address, amount, block_height, term) # noinspection PyUnresolvedReferences self.assertEqual('Invalid SCORE owner', e.exception.message) def test_deposit_fee_out_of_balance(self): context = self.get_context() self.icx_storage._put_genesis_data_account( context, CoinPartType.GENERAL, self._sender, 10000 * 10 ** 18) tx_hash = os.urandom(32) amount = 10001 * 10 ** 18 block_height = randrange(100, 10000) term = get_rand_term() # out of balance # noinspection PyTypeChecker with self.assertRaises(OutOfBalanceException) as e: self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, amount, block_height, term) # noinspection PyUnresolvedReferences self.assertEqual('Out of balance', e.exception.message) def test_deposit_fee_available_head_ids(self): context = self.get_context() tx_hash = os.urandom(32) amount = 10000 * 10 ** 18 block_height = 1000 self.icx_storage._put_genesis_data_account(context, CoinPartType.GENERAL, self._sender, amount) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_virtual_step, None) self.assertEqual(deposit_meta.available_head_id_of_deposit, None) self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, amount, block_height, FeeEngine._MIN_DEPOSIT_TERM) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_virtual_step, tx_hash) self.assertEqual(deposit_meta.available_head_id_of_deposit, tx_hash) def test_deposit_fee_expires_updated(self): context = self.get_context() tx_hash = os.urandom(32) amount = 10000 * 10 ** 18 block_height = 1000 term = FeeEngine._MIN_DEPOSIT_TERM self.icx_storage._put_genesis_data_account(context, CoinPartType.GENERAL, self._sender, amount) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.expires_of_virtual_step, -1) self.assertEqual(deposit_meta.expires_of_deposit, -1) self._engine.add_deposit(context, tx_hash, self._sender, self._score_address, amount, block_height, term) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.expires_of_virtual_step, block_height + term) self.assertEqual(deposit_meta.expires_of_deposit, block_height + term) def test_withdraw_fee_without_penalty(self): context = self.get_context() tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() self._engine.add_deposit( context, tx_hash, self._sender, self._score_address, amount, block_height, term) before_sender_balance = self._icx_engine.get_balance(context, self._sender) self._engine.withdraw_deposit(context, self._sender, tx_hash, block_height + term + 1) after_sender_balance = self._icx_engine.get_balance(context, self._sender) deposit_info = self._engine.get_deposit_info(context, self._score_address, block_height) self.assertIsNone(deposit_info) self.assertEqual(amount, after_sender_balance - before_sender_balance) def test_withdraw_fee_with_penalty(self): context = self.get_context() tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() self._engine.add_deposit( context, tx_hash, self._sender, self._score_address, amount, block_height, term) before_sender_balance = self._icx_engine.get_balance(context, self._sender) self._engine.withdraw_deposit(context, self._sender, tx_hash, block_height + term - 1) after_sender_balance = self._icx_engine.get_balance(context, self._sender) deposit_info = self._engine.get_deposit_info(context, self._score_address, block_height) self.assertIsNone(deposit_info) self.assertGreater(after_sender_balance - before_sender_balance, 0) self.assertLessEqual(after_sender_balance - before_sender_balance, amount) def test_withdraw_fee_and_updates_previous_and_next_link_ascending(self): """ Given: There are four deposits. When : Withdraws all of them sequentially(ascending). Then : Checks if the previous and next link update correctly. """ context = self.get_context() cnt_deposit = 4 block_height = randrange(100, 10000) arr_tx_hash = [] for i in range(cnt_deposit): arr_tx_hash.append(os.urandom(32)) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) term = get_rand_term() block_height += 1 self._engine.add_deposit( context, arr_tx_hash[i], self._sender, self._score_address, amount, block_height, term) for i in range(cnt_deposit): target_deposit = self._engine.get_deposit(context, arr_tx_hash[i]) self._engine.withdraw_deposit(context, self._sender, arr_tx_hash[i], block_height + term // 2) if cnt_deposit - 1 == i: self.assertIsNone(target_deposit.next_id) break next_deposit = self._engine.get_deposit(context, target_deposit.next_id) self.assertEqual(next_deposit.prev_id, None) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(next_deposit.id, deposit_meta.head_id) def test_withdraw_fee_and_updates_previous_and_next_link_descending(self): """ Given: There are four deposits. When : Withdraws all of them sequentially(descending). Then : Checks if the previous and next link update correctly. """ context = self.get_context() cnt_deposit = 4 block_height = randrange(100, 10000) arr_tx_hash = [] for i in range(cnt_deposit): arr_tx_hash.append(os.urandom(32)) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) term = get_rand_term() block_height += 1 self._engine.add_deposit( context, arr_tx_hash[i], self._sender, self._score_address, amount, block_height, term) for i in range(cnt_deposit - 1, -1, -1): target_deposit = self._engine.get_deposit(context, arr_tx_hash[i]) self._engine.withdraw_deposit(context, self._sender, arr_tx_hash[i], block_height + term // 2) if i == 0: self.assertIsNone(target_deposit.prev_id) break prev_deposit = self._engine.get_deposit(context, target_deposit.prev_id) self.assertEqual(prev_deposit.next_id, None) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(prev_deposit.id, deposit_meta.tail_id) @unittest.skipIf(FIXED_TERM is True, "FIXED_TERM is true") def test_withdraw_fee_when_available_head_id_of_virtual_step_is_same_as_deposit_id(self): """ Given: There are four deposits. Only the last deposit has enough to long term. When : Available head id of the virtual step is same as deposit id. Then : Searches for next deposit id which is available to use virtual step and where expires of the deposit is more than current block height. In the test, only the last deposit is available. """ context = self.get_context() cnt_deposit = 4 block_height = randrange(100, 10000) arr_tx_hash = [] for i in range(cnt_deposit): arr_tx_hash.append(os.urandom(32)) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height += 1 if i != cnt_deposit - 1: term = FeeEngine._MIN_DEPOSIT_TERM else: term = FeeEngine._MAX_DEPOSIT_TERM self._engine.add_deposit( context, arr_tx_hash[i], self._sender, self._score_address, amount, block_height, term) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_virtual_step, arr_tx_hash[0]) self._engine.withdraw_deposit(context, self._sender, arr_tx_hash[0], block_height + FeeEngine._MAX_DEPOSIT_TERM // 2) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_virtual_step, arr_tx_hash[len(arr_tx_hash) - 1]) @unittest.skipIf(FIXED_TERM is True, "FIXED_TERM is true") def test_withdraw_fee_when_available_head_id_of_deposit_is_same_as_deposit_id(self): """ Given: There are four deposits. Only the third deposit has enough long term. When : Available head id of deposit is same as deposit id. Then : Searches for next deposit id which is available to use deposit and where expires of the deposit is more than current block height. In the test, only the third deposit is available. """ context = self.get_context() cnt_deposit = 4 block_height = randrange(100, 10000) arr_tx_hash = [] for i in range(cnt_deposit): arr_tx_hash.append(os.urandom(32)) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height += 1 if i != cnt_deposit - 2: term = FeeEngine._MIN_DEPOSIT_TERM else: term = FeeEngine._MAX_DEPOSIT_TERM self._engine.add_deposit( context, arr_tx_hash[i], self._sender, self._score_address, amount, block_height, term) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_deposit, arr_tx_hash[0]) self._engine.withdraw_deposit(context, self._sender, arr_tx_hash[0], block_height + FeeEngine._MAX_DEPOSIT_TERM // 2) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_deposit, arr_tx_hash[len(arr_tx_hash) - 2]) @unittest.skipIf(FIXED_TERM is True, "FIXED_TERM is true") def test_withdraw_fee_to_check_setting_on_next_max_expires(self): """ Given: There are four deposits. When : Expires of the withdrawal deposit is same as expires. Then : Searches for max expires which is more than current block height. """ context = self.get_context() cnt_deposit = 4 block_height = randrange(100, 10000) arr_tx_hash = [] last_expires = 0 org_last_expires = 0 for i in range(cnt_deposit): arr_tx_hash.append(os.urandom(32)) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height += 1 if i != 0: term = FeeEngine._MIN_DEPOSIT_TERM if block_height + term > last_expires: last_expires = block_height + term else: term = FeeEngine._MAX_DEPOSIT_TERM org_last_expires = block_height + term self._engine.add_deposit( context, arr_tx_hash[i], self._sender, self._score_address, amount, block_height, term) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_virtual_step, arr_tx_hash[0]) self.assertEqual(deposit_meta.expires_of_virtual_step, org_last_expires) self.assertEqual(deposit_meta.expires_of_deposit, org_last_expires) self._engine.withdraw_deposit(context, self._sender, arr_tx_hash[0], block_height + FeeEngine._MIN_DEPOSIT_TERM // 2) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.expires_of_virtual_step, last_expires) self.assertEqual(deposit_meta.expires_of_deposit, last_expires) @unittest.skipIf(FIXED_TERM is True, "FIXED_TERM is true") def test_withdraw_fee_of_last_deposit_to_check_setting_on_next_max_expires(self): """ Given: There are four deposits. When : Expires of the withdrawal deposit which is the last one is same as expires. Then : Searches for max expires which is more than current block height. """ context = self.get_context() cnt_deposit = 4 block_height = randrange(100, 10000) arr_tx_hash = [] last_expires = 0 org_last_expires = 0 for i in range(cnt_deposit): arr_tx_hash.append(os.urandom(32)) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height += 1 if i != cnt_deposit-1: term = FeeEngine._MIN_DEPOSIT_TERM if block_height + term > last_expires: last_expires = block_height + term else: term = FeeEngine._MAX_DEPOSIT_TERM org_last_expires = block_height + term self._engine.add_deposit( context, arr_tx_hash[i], self._sender, self._score_address, amount, block_height, term) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.available_head_id_of_virtual_step, arr_tx_hash[0]) self.assertEqual(deposit_meta.available_head_id_of_deposit, arr_tx_hash[0]) self.assertEqual(deposit_meta.expires_of_virtual_step, org_last_expires) self.assertEqual(deposit_meta.expires_of_deposit, org_last_expires) # Withdraws the last one self._engine.withdraw_deposit(context, self._sender, arr_tx_hash[cnt_deposit - 1], block_height + FeeEngine._MIN_DEPOSIT_TERM // 2) deposit_meta = self._engine._get_or_create_deposit_meta(context, self._score_address) self.assertEqual(deposit_meta.expires_of_virtual_step, last_expires) self.assertEqual(deposit_meta.expires_of_deposit, last_expires) def test_get_deposit_info(self): context = self.get_context() tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() before_sender_balance = self._icx_engine.get_balance(context, self._sender) self._engine.add_deposit( context, tx_hash, self._sender, self._score_address, amount, block_height, term) after_sender_balance = self._icx_engine.get_balance(context, self._sender) self.assertEqual(amount, before_sender_balance - after_sender_balance) deposit = self._engine.get_deposit(context, tx_hash) self.assertEqual(tx_hash, deposit.id) self.assertEqual(self._score_address, deposit.score_address) self.assertEqual(self._sender, deposit.sender) self.assertEqual(amount, deposit.deposit_amount) self.assertEqual(block_height, deposit.created) self.assertEqual(block_height + term, deposit.expires) def test_charge_transaction_fee_without_sharing(self): context = self.get_context() step_price = 10 ** 10 used_step = 10 ** 10 tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() self._engine.add_deposit( context, tx_hash, self._sender, self._score_address, amount, block_height, term) before_sender_balance = self._icx_engine.get_balance(context, self._sender) self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, block_height) after_sender_balance = self._icx_engine.get_balance(context, self._sender) self.assertEqual(step_price * used_step, before_sender_balance - after_sender_balance) def test_charge_transaction_fee_sharing_deposit(self): context = self.get_context() step_price = 10 ** 10 used_step = 10 ** 10 tx_hash = os.urandom(32) amount = randrange(FeeEngine._MIN_DEPOSIT_AMOUNT, FeeEngine._MAX_DEPOSIT_AMOUNT) block_height = randrange(100, 10000) term = get_rand_term() self._engine.add_deposit( context, tx_hash, self._sender, self._score_address, amount, block_height, term) ratio = 50 context.fee_sharing_proportion = ratio before_sender_balance = self._icx_engine.get_balance(context, self._sender) self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, block_height) after_sender_balance = self._icx_engine.get_balance(context, self._sender) score_charging_step = used_step * ratio // 100 sender_charging_step = used_step - score_charging_step self.assertEqual( step_price * sender_charging_step, before_sender_balance - after_sender_balance) def test_charge_fee_from_score_by_virtual_step_single_deposit(self): """ Given: Five deposits. The fourth deposit is the max expire. When : Current block is 120 so 1st deposit is unavailable Then : Pays fee by virtual step of 2nd. update indices to 2nd """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 100), (os.urandom(32), 50, 180, 100, 100), (os.urandom(32), 70, 150, 100, 100), (os.urandom(32), 90, 250, 100, 100), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 120 used_step = 80 deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) before_virtual_step = deposit_info.available_virtual_step self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(used_step, before_virtual_step - after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(deposits[1][0], deposit_meta.available_head_id_of_virtual_step) def test_charge_fee_from_score_by_virtual_step_single_deposit_next_head(self): """ Given: Five deposits. The fourth deposit is the max expire. When : Current block is 120 so 1st deposit is unavailable Then : Pays fee by virtual step of 2nd. the virtual steps in 2nd are fully consumed update indices to 3rd """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 100), (os.urandom(32), 50, 180, 100, 100), (os.urandom(32), 70, 150, 100, 100), (os.urandom(32), 90, 250, 100, 100), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 120 used_step = 100 deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) before_virtual_step = deposit_info.available_virtual_step self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(used_step, before_virtual_step - after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(deposits[2][0], deposit_meta.available_head_id_of_virtual_step) def test_charge_fee_from_score_by_virtual_step__single_deposit_next_head_next_expire(self): """ Given: Five deposits. The fourth deposit is the max expire. When : Current block is 190 so 4th, 5th deposits are available Then : Pays fee by virtual step of 4th. the virtual steps in 4th are fully consumed update indices to 5th """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 100), (os.urandom(32), 50, 180, 100, 100), (os.urandom(32), 70, 150, 100, 100), (os.urandom(32), 90, 250, 100, 100), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 190 used_step = 100 deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) before_virtual_step = deposit_info.available_virtual_step self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(used_step, before_virtual_step - after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(deposits[4][0], deposit_meta.available_head_id_of_virtual_step) self.assertEqual(deposits[4][2], deposit_meta.expires_of_virtual_step) def test_charge_fee_from_score_by_virtual_step__single_deposit_next_head_next_expire_none(self): """ Given: Five deposits. The fourth deposit is the max expire. When : Current block is 210 so only 4th deposit is available Then : Pays fee by virtual step of 4th. the virtual steps in 4th are fully consumed should update indices but there are no more available deposits """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 100), (os.urandom(32), 50, 180, 100, 100), (os.urandom(32), 70, 150, 100, 100), (os.urandom(32), 90, 250, 100, 100), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 210 used_step = 100 deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) before_virtual_step = deposit_info.available_virtual_step self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(used_step, before_virtual_step - after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) def test_charge_fee_from_score_by_virtual_step_multiple_deposit(self): """ Given: Five deposits. The fourth deposit is the max expire. When : Current block is 120 so 1st deposit is unavailable Then : Pays fee by virtual step through 2nd, 3rd, 4th. the virtual steps in 2nd, 3rd are fully consumed update indices to 4th """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 100), (os.urandom(32), 50, 180, 100, 100), (os.urandom(32), 70, 150, 100, 100), (os.urandom(32), 90, 250, 100, 100), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 120 used_step = 250 deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) before_virtual_step = deposit_info.available_virtual_step self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(used_step, before_virtual_step - after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(deposits[3][0], deposit_meta.available_head_id_of_virtual_step) def test_charge_fee_from_score_by_combine_by_single_deposit(self): """ Given: Five deposits. The fourth deposit is the max expire. Remaining virtual steps are in 5th deposit When : Current block is 120 so 1st deposit is unavailable Remaining virtual steps are not enough to pay fees Then : Pays fee by virtual step first. Pays remaining fee by deposit of 2nd update indices to 2nd """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 0), (os.urandom(32), 50, 180, 100, 0), (os.urandom(32), 70, 150, 100, 0), (os.urandom(32), 90, 250, 100, 0), (os.urandom(32), 110, 200, 100, 50) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 120 used_step = 70 self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(0, after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) self.assertEqual(deposits[1][0], deposit_meta.available_head_id_of_deposit) def test_charge_fee_from_score_by_combine_next_head(self): """ Given: Five deposits. The fourth deposit is the max expire. Remaining virtual steps are in 5th deposit When : Current block is 120 so 1st deposit is unavailable Remaining virtual steps are not enough to pay fees Then : Pays fee by virtual step first. Pays remaining fee by deposit of 2nd 2nd deposit is fully consumed so update indices to 3rd """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 0), (os.urandom(32), 50, 180, 100, 0), (os.urandom(32), 70, 150, 100, 0), (os.urandom(32), 90, 250, 100, 0), (os.urandom(32), 110, 200, 100, 50) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 120 used_step = 140 self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(0, after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) self.assertEqual(deposits[2][0], deposit_meta.available_head_id_of_deposit) def test_charge_fee_from_score_by_combine_next_head_next_expire(self): """ Given: Five deposits. The fourth deposit is the max expire. Remaining virtual steps are in 5th deposit When : Current block is 190 so 1st, 2nd, 3rd deposits are unavailable Remaining virtual steps are not enough to pay fees Then : Pays fee by virtual step first. Pays remaining fee by deposit of 4th 4th deposit is fully consumed so update indices to 5th """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 0), (os.urandom(32), 50, 180, 100, 0), (os.urandom(32), 70, 150, 100, 0), (os.urandom(32), 90, 250, 100, 0), (os.urandom(32), 110, 200, 100, 50) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 190 used_step = 140 self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(0, after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) self.assertEqual(deposits[4][0], deposit_meta.available_head_id_of_deposit) self.assertEqual(deposits[4][2], deposit_meta.expires_of_deposit) def test_charge_fee_from_score_by_combine_next_head_next_expire_none(self): """ Given: Five deposits. The fourth deposit is the max expire. Remaining virtual steps are in 4th and 5th deposit When : Current block is 220 so 5th deposit is unavailable Remaining virtual steps are not enough to pay fees Then : Pays fee by virtual step first. Pays remaining fee by deposit of 4th All available deposits are consumed so make the SCORE disabled """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 0), (os.urandom(32), 50, 180, 100, 0), (os.urandom(32), 70, 150, 100, 0), (os.urandom(32), 90, 250, 100, 50), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 220 used_step = 140 self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(0, after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) self.assertEqual(None, deposit_meta.available_head_id_of_deposit) self.assertEqual(-1, deposit_meta.expires_of_deposit) def test_charge_fee_from_score_by_combine_multiple_deposit(self): """ Given: Five deposits. The fourth deposit is the max expire. Remaining virtual steps are in 5th deposit When : Current block is 120 so 1st deposit is unavailable Remaining virtual steps are not enough to pay fees Then : Pays fee by virtual step first. Pays remaining fee by deposit through 2nd and 3rd deposit. """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 0), (os.urandom(32), 50, 180, 100, 0), (os.urandom(32), 70, 150, 100, 0), (os.urandom(32), 90, 250, 100, 0), (os.urandom(32), 110, 200, 100, 50) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 120 used_step = 230 self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(0, after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) # Asserts indices are updated self.assertEqual(deposits[3][0], deposit_meta.available_head_id_of_deposit) self.assertEqual(deposits[3][2], deposit_meta.expires_of_deposit) def test_charge_fee_from_score_by_combine_additional_pay(self): """ Given: Five deposits. The fourth deposit is the max expire. Remaining virtual steps are in 4th and 5th deposit When : Current block is 220 so 5th deposit is unavailable Remaining virtual steps are not enough to pay fees Available deposits are also not enough to pay fees Then : Pays fees regardless minimum remaining amount and make the SCORE disabled """ context = self.get_context() # tx_hash, from_block, to_block, deposit_amount, virtual_step_amount deposits = [ (os.urandom(32), 10, 100, 100, 0), (os.urandom(32), 50, 180, 100, 0), (os.urandom(32), 70, 150, 100, 0), (os.urandom(32), 90, 250, 100, 50), (os.urandom(32), 110, 200, 100, 100) ] self._set_up_deposits(context, deposits) step_price = 1 current_block = 220 used_step = 150 self._engine.charge_transaction_fee( context, self._sender, self._score_address, step_price, used_step, current_block) deposit_info = self._engine.get_deposit_info(context, self._score_address, current_block) after_virtual_step = deposit_info.available_virtual_step self.assertEqual(0, after_virtual_step) deposit_meta = self.fee_storage.get_deposit_meta(context, self._score_address) # Asserts virtual step disabled self.assertEqual(None, deposit_meta.available_head_id_of_virtual_step) self.assertEqual(-1, deposit_meta.expires_of_virtual_step) # Asserts deposit disabled self.assertEqual(None, deposit_meta.available_head_id_of_deposit) self.assertEqual(-1, deposit_meta.expires_of_deposit) def _set_up_deposits(self, context, deposits): context.fee_sharing_proportion = 100 self._engine._MIN_DEPOSIT_TERM = 50 self._engine._MIN_DEPOSIT_AMOUNT = 10 for deposit in deposits: tx_hash = deposit[0] amount = deposit[3] block_height = deposit[1] term = deposit[2] - block_height # self._engine._calculate_virtual_step_issuance = Mock(return_value=deposit[4]) VirtualStepCalculator.calculate_virtual_step = Mock(return_value=deposit[4]) self._engine.add_deposit( context, tx_hash, self._sender, self._score_address, amount, block_height, term)

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117

0.666759

6,251

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5.029755

0.053271

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0.03365

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50,318

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118

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0

null

0

1

0

null

0

6

a35cbc9a1ccb3c1724b95083e1001a7a1ddf7fe8

6,563

py

Python

identify_shapes/tests/center_of_shape.py

SPLAYER-HD/ImageDetect-Colors-Shapes

eddea8189760b7326a2989cb4a90fa1b183ff2ee

[ "MIT" ]

null

identify_shapes/tests/center_of_shape.py

SPLAYER-HD/ImageDetect-Colors-Shapes

eddea8189760b7326a2989cb4a90fa1b183ff2ee

[ "MIT" ]

1

2020-02-17T10:34:05.000Z

identify_shapes/tests/center_of_shape.py

SPLAYER-HD/ImageDetect-Colors-Shapes

eddea8189760b7326a2989cb4a90fa1b183ff2ee

[ "MIT" ]

null

# import the necessary packages import argparse import imutils import cv2 from PIL import Image import numpy as np from random import randint # construct the argument parse and parse the arguments ap = argparse.ArgumentParser() ap.add_argument("-i", "--image", required=True, help="path to the input image") args = vars(ap.parse_args()) print ('cv2.__version__') print (cv2.__version__) # load the image, convert it to grayscale, blur it slightly, # and threshold it image = cv2.imread(args["image"]) img = Image.open(args["image"]) array = np.array(img) gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) invimg = Image.fromarray(gray) invimg.save('shades-of-grey_gray.png') blurred = cv2.GaussianBlur(gray, (5, 5), 0) invimg = Image.fromarray(blurred) invimg.save('shades-of-grey_blurred.png') thresh = cv2.threshold(gray, 60, 80, cv2.THRESH_BINARY_INV)[1] invimg = Image.fromarray(thresh) invimg.save('shades-of-grey_thresh.png') # find contours in the thresholded image (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) #(_, cnts, _) = imutils.grab_contours(cnts) print('cnts') print(len(cnts)) print(len(cnts[0])) #cv2.drawContours(image, cnts, -1, (240, 0, 159), 3) #cv2.imshow("Image", image) #cv2.waitKey(0) for c in cnts: # compute the center of the contour M = cv2.moments(c) print('M') #print(M) cX = int(M["m10"] / M["m00"]) cY = int(M["m01"] / M["m00"]) # draw the contour and center of the shape on the image cv2.drawContours(image, [c], -1, (0, 255, 0), 2) cv2.circle(image, (cX, cY), 7, (255, 255, 255), -1) cv2.putText(image, "center", (cX - 20, cY - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2) # show the image #cv2.imshow("Image", image) #cv2.waitKey(0) #invimg = Image.fromarray(dst) #invimg.save('shades-of-grey_border.png') #image = cv2.imread("shades-of-grey_border.png") #img = Image.open('shades-of-grey_border.png') array = np.array(img) ''' for row_index, line in enumerate(array): #print (line) for column_index, pixel in enumerate(line): if(pixel[0] ==200): array[row_index][column_index]=[0, 0, 0] #21, 214, 234 ''' for row_index, line in enumerate(array): #print (line) for column_index, pixel in enumerate(line): if(pixel[0] ==255): array[row_index][column_index]=[21, 214, 234] for row_index, line in enumerate(array): #print (line) for column_index, pixel in enumerate(line): if((row_index ==0 or row_index == len(array)-1)and (column_index == 1 or len(array[0])-1)): #print('entro0') array[row_index][column_index]=[255, 255, 255] if((row_index ==0 or row_index == len(array)-1)and (column_index == 0 or len(array[0])-1)): #print('entro') array[row_index][column_index]=[255, 255, 255] if((row_index ==1 or row_index == len(array)-2) and (column_index == 1 or len(array[0])-2)): #print('entro2') array[row_index][column_index]=[255, 255, 255] if(row_index == len(array)-3 and len(array[0])-3): #print('entro3') array[row_index][column_index]=[255, 255, 255] invimg = Image.fromarray(array) invimg.save('shades-of-grey_red.png') image = cv2.imread('shades-of-grey_red.png') gray = cv2.cvtColor(image, cv2.COLOR_BGR2GRAY) invimg.save('shades-of-grey_gray.png') blurred = cv2.GaussianBlur(gray, (5, 5), 0) invimg = Image.fromarray(blurred) invimg.save('shades-of-grey_blurred.png') ##################444 ''' thresh = cv2.threshold(gray, 60, 80, cv2.THRESH_BINARY_INV)[1] invimg = Image.fromarray(thresh) invimg.save('shades-of-grey_thresh.png') # find contours in the thresholded image (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_EXTERNAL,cv2.CHAIN_APPROX_SIMPLE) #(_, cnts, _) = imutils.grab_contours(cnts) print('cnts') print(len(cnts)) print(len(cnts[0])) #cv2.drawContours(image, cnts, -1, (240, 0, 159), 3) #cv2.imshow("Image", image) #cv2.waitKey(0) for c in cnts: # compute the center of the contour M = cv2.moments(c) print('M') #print(M) cX = int(M["m10"] / M["m00"]) cY = int(M["m01"] / M["m00"]) # draw the contour and center of the shape on the image cv2.drawContours(image, [c], -1, (0, 255, 0), 2) cv2.circle(image, (cX, cY), 7, (255, 255, 255), -1) cv2.putText(image, "center", (cX - 20, cY - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2) # show the image cv2.imshow("Image", image) cv2.waitKey(0) ''' ######################444 thresh = cv2.threshold(gray, 210, 255, cv2.RETR_FLOODFILL)[1] invimg = Image.fromarray(thresh) invimg.save('shades-of-grey_thresh.png') # find contours in the thresholded image (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_LIST,cv2.CHAIN_APPROX_NONE) #(_, cnts, _) = imutils.grab_contours(cnts) print('cnts') print(len(cnts)) #print(len(cnts[0])) #print(cnts) #cv2.drawContours(image, cnts, -1, (240, 0, 159), 3) #cv2.imshow("Image", image) #cv2.waitKey(0) print(len(cnts)) #print(len(cnts[0])) # loop over the contours for c in cnts: # compute the center of the contour M = cv2.moments(c) print('M') #print(M) cX = int(M["m10"] / M["m00"]) cY = int(M["m01"] / M["m00"]) # draw the contour and center of the shape on the image cv2.drawContours(image, [c], -1, (0, 255, 0), 2) cv2.circle(image, (cX, cY), 7, (255, 255, 255), -1) cv2.putText(image, "center", (cX - 20, cY - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2) # show the image cv2.imshow("Image", image) cv2.waitKey(0) #################################### thresh = cv2.threshold(gray, 255, 0, cv2.THRESH_TRUNC)[1] invimg = Image.fromarray(thresh) invimg.save('shades-of-grey_thresh.png') # find contours in the thresholded image (cnts, _) = cv2.findContours(thresh.copy(), cv2.RETR_TREE,cv2.CHAIN_APPROX_NONE) #(_, cnts, _) = imutils.grab_contours(cnts) print('cnts') print(len(cnts)) #print(len(cnts[0])) #print(cnts) #cv2.drawContours(image, cnts, -1, (240, 0, 159), 3) #cv2.imshow("Image", image) #cv2.waitKey(0) print(len(cnts)) #print(len(cnts[0])) # loop over the contours for c in cnts: # compute the center of the contour M = cv2.moments(c) print('M') #print(M) cX = int(M["m10"] / M["m00"]) cY = int(M["m01"] / M["m00"]) # draw the contour and center of the shape on the image cv2.drawContours(image, [c], -1, (0, 255, 0), 2) cv2.circle(image, (cX, cY), 7, (255, 255, 255), -1) cv2.putText(image, "center", (cX - 20, cY - 20), cv2.FONT_HERSHEY_SIMPLEX, 0.5, (255, 255, 255), 2) # show the image cv2.imshow("Image", image) cv2.waitKey(0)

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100

0.655341

1,043

6,563

4.032598

0.134228

0.034237

0.03709

0.042796

0.847836

0.804327

0.798859

0.785069

0.749643

0

0.073874

0.15435

6,563

211

101

31.104265

0.683964

0.219564

0

0.677083

0

0.092408

0.056806

0

1

0

false

0

0.0625

0

0.0625

0.145833

0

null

0

1

0

null

0

6

a36e74443a1e748ceabf1db23e8b7644ebc230db

81

py

Python

destructify/parsing/__init__.py

mvdnes/destructify

eb37ee3465da429685a8301ec00b4a63cd375561

[ "MIT" ]

7

2018-06-04T13:47:59.000Z

2021-01-13T19:40:32.000Z

destructify/parsing/__init__.py

mvdnes/destructify

eb37ee3465da429685a8301ec00b4a63cd375561

[ "MIT" ]

1

2021-02-08T10:35:14.000Z

destructify/parsing/__init__.py

mvdnes/destructify

eb37ee3465da429685a8301ec00b4a63cd375561

[ "MIT" ]

2

2020-11-30T22:00:16.000Z

2021-07-10T09:45:49.000Z

from .context import * from .streams import * from .expression import this, len_

20.25

34

0.765432

11

81

5.545455

0.636364

0.327869

0

0.160494

81

3

35

27

0.897059

0

1

0

true

0

1

0

1

0

1

0

null

1

0

1

0

null

0

1

0

1

0

1

0

6

a383c5af1a3c373717d86976e54e385145c82f87

93

py

Python

pwlf/__init__.py

alexlib/piecewise_linear_fit_py

cb32e331690e668b374a54f890eac549d884b2fe

[ "MIT" ]

199

2017-10-31T10:26:15.000Z

2022-03-30T09:16:52.000Z

pwlf/__init__.py

alexlib/piecewise_linear_fit_py

cb32e331690e668b374a54f890eac549d884b2fe

[ "MIT" ]

79

2017-10-31T10:26:12.000Z

2022-03-31T18:46:24.000Z

pwlf/__init__.py

alexlib/piecewise_linear_fit_py

cb32e331690e668b374a54f890eac549d884b2fe

[ "MIT" ]

54

2017-11-09T06:50:34.000Z

2022-03-09T06:15:54.000Z

from .pwlf import PiecewiseLinFit # noqa F401 from .version import __version__ # noqa F401

31

46

0.784946

12

93

5.75

0.583333

0.231884

0

0.077922

0.172043

93

2

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0.818182

0.204301

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true

0

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null

1

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null

0

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6

6ea411ff7d905a647821002b7f1011156a384d50

38,085

py

Python

instances/passenger_demand/pas-20210421-2109-int16e/96.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210421-2109-int16e/96.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

instances/passenger_demand/pas-20210421-2109-int16e/96.py

LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure

bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11

[ "BSD-3-Clause" ]

null

""" PASSENGERS """ numPassengers = 3683 passenger_arriving = ( (3, 11, 2, 7, 3, 0, 6, 8, 4, 4, 1, 0), # 0 (4, 9, 10, 6, 2, 0, 13, 9, 4, 6, 2, 0), # 1 (7, 8, 11, 3, 5, 0, 6, 4, 8, 9, 6, 0), # 2 (7, 7, 10, 2, 2, 0, 9, 7, 7, 5, 2, 0), # 3 (1, 8, 8, 4, 3, 0, 13, 7, 6, 4, 2, 0), # 4 (3, 4, 9, 2, 0, 0, 5, 9, 6, 1, 0, 0), # 5 (4, 11, 14, 2, 1, 0, 9, 9, 10, 8, 3, 0), # 6 (7, 9, 11, 3, 0, 0, 12, 10, 6, 8, 0, 0), # 7 (6, 11, 11, 6, 1, 0, 5, 11, 6, 2, 5, 0), # 8 (5, 7, 9, 9, 0, 0, 8, 13, 8, 2, 3, 0), # 9 (4, 12, 7, 7, 2, 0, 6, 10, 7, 5, 3, 0), # 10 (4, 8, 9, 7, 1, 0, 6, 10, 9, 8, 2, 0), # 11 (4, 7, 8, 8, 4, 0, 6, 13, 13, 1, 3, 0), # 12 (4, 6, 5, 4, 1, 0, 9, 13, 10, 4, 3, 0), # 13 (3, 5, 8, 4, 1, 0, 9, 12, 5, 10, 3, 0), # 14 (5, 9, 12, 2, 4, 0, 8, 9, 6, 7, 2, 0), # 15 (7, 7, 6, 7, 2, 0, 7, 15, 8, 3, 3, 0), # 16 (5, 11, 13, 2, 5, 0, 11, 9, 8, 6, 3, 0), # 17 (3, 16, 11, 3, 4, 0, 8, 13, 6, 3, 2, 0), # 18 (5, 12, 15, 4, 0, 0, 10, 10, 11, 4, 3, 0), # 19 (3, 9, 15, 11, 3, 0, 8, 12, 4, 4, 2, 0), # 20 (3, 7, 6, 4, 2, 0, 7, 8, 12, 6, 2, 0), # 21 (6, 12, 10, 2, 2, 0, 10, 6, 8, 8, 3, 0), # 22 (4, 9, 6, 4, 1, 0, 4, 10, 7, 8, 1, 0), # 23 (2, 10, 13, 7, 1, 0, 12, 8, 7, 4, 3, 0), # 24 (6, 9, 14, 4, 3, 0, 5, 15, 4, 5, 1, 0), # 25 (5, 17, 6, 5, 2, 0, 6, 10, 8, 9, 3, 0), # 26 (5, 8, 13, 6, 3, 0, 5, 11, 5, 6, 3, 0), # 27 (3, 13, 9, 7, 2, 0, 10, 14, 4, 2, 3, 0), # 28 (6, 12, 4, 3, 3, 0, 9, 8, 6, 9, 2, 0), # 29 (4, 15, 6, 6, 5, 0, 10, 8, 4, 5, 0, 0), # 30 (2, 9, 5, 1, 1, 0, 8, 15, 7, 3, 3, 0), # 31 (3, 9, 7, 6, 4, 0, 8, 9, 7, 4, 2, 0), # 32 (6, 18, 6, 3, 3, 0, 5, 11, 3, 5, 1, 0), # 33 (4, 6, 7, 3, 2, 0, 14, 11, 7, 6, 3, 0), # 34 (6, 8, 13, 6, 3, 0, 5, 7, 4, 2, 3, 0), # 35 (4, 8, 5, 2, 2, 0, 7, 9, 6, 6, 3, 0), # 36 (8, 7, 6, 2, 4, 0, 16, 13, 6, 4, 3, 0), # 37 (6, 13, 4, 6, 1, 0, 11, 9, 10, 4, 3, 0), # 38 (2, 14, 10, 5, 3, 0, 6, 11, 10, 6, 2, 0), # 39 (6, 9, 9, 7, 1, 0, 7, 9, 8, 4, 0, 0), # 40 (5, 9, 9, 2, 5, 0, 8, 4, 9, 4, 0, 0), # 41 (2, 17, 5, 1, 1, 0, 6, 13, 6, 9, 1, 0), # 42 (7, 16, 8, 3, 4, 0, 4, 10, 5, 9, 2, 0), # 43 (2, 14, 13, 2, 0, 0, 11, 13, 2, 3, 3, 0), # 44 (8, 11, 13, 3, 2, 0, 4, 12, 6, 9, 2, 0), # 45 (10, 12, 8, 6, 2, 0, 6, 7, 4, 3, 2, 0), # 46 (3, 8, 11, 6, 0, 0, 9, 4, 7, 7, 4, 0), # 47 (6, 11, 11, 5, 2, 0, 8, 9, 8, 6, 2, 0), # 48 (1, 9, 10, 6, 1, 0, 6, 13, 8, 9, 3, 0), # 49 (2, 9, 6, 1, 4, 0, 6, 10, 3, 3, 1, 0), # 50 (7, 16, 8, 7, 2, 0, 4, 6, 6, 6, 5, 0), # 51 (3, 10, 11, 3, 2, 0, 6, 7, 10, 4, 2, 0), # 52 (5, 13, 8, 3, 2, 0, 8, 9, 7, 3, 3, 0), # 53 (6, 13, 6, 8, 3, 0, 6, 9, 11, 6, 2, 0), # 54 (1, 16, 5, 7, 1, 0, 8, 8, 5, 4, 4, 0), # 55 (7, 5, 15, 5, 2, 0, 4, 10, 4, 4, 3, 0), # 56 (8, 16, 5, 4, 0, 0, 3, 6, 10, 6, 3, 0), # 57 (1, 6, 8, 1, 2, 0, 10, 11, 5, 8, 3, 0), # 58 (0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 59 ) station_arriving_intensity = ( (4.239442493415277, 10.874337121212122, 12.79077763496144, 10.138043478260869, 11.428846153846154, 7.610869565217392), # 0 (4.27923521607648, 10.995266557940518, 12.859864860039991, 10.194503019323673, 11.51450641025641, 7.608275422705315), # 1 (4.318573563554774, 11.114402244668911, 12.927312196515281, 10.249719806763286, 11.598358974358975, 7.60560193236715), # 2 (4.357424143985952, 11.231615625000002, 12.993070372750644, 10.303646739130434, 11.680326923076926, 7.60284945652174), # 3 (4.395753565505805, 11.346778142536477, 13.057090117109396, 10.356236714975847, 11.760333333333335, 7.600018357487922), # 4 (4.433528436250122, 11.459761240881035, 13.11932215795487, 10.407442632850241, 11.838301282051281, 7.597108997584541), # 5 (4.470715364354698, 11.570436363636365, 13.179717223650389, 10.457217391304349, 11.914153846153846, 7.594121739130435), # 6 (4.507280957955322, 11.678674954405162, 13.238226042559269, 10.50551388888889, 11.987814102564105, 7.591056944444445), # 7 (4.543191825187787, 11.784348456790122, 13.294799343044847, 10.552285024154589, 12.059205128205129, 7.587914975845411), # 8 (4.578414574187884, 11.88732831439394, 13.34938785347044, 10.597483695652175, 12.12825, 7.584696195652175), # 9 (4.612915813091406, 11.987485970819305, 13.401942302199371, 10.64106280193237, 12.194871794871796, 7.581400966183574), # 10 (4.646662150034143, 12.084692869668913, 13.452413417594972, 10.682975241545895, 12.25899358974359, 7.578029649758455), # 11 (4.679620193151888, 12.178820454545454, 13.500751928020566, 10.723173913043478, 12.320538461538462, 7.574582608695652), # 12 (4.71175655058043, 12.26974016905163, 13.546908561839473, 10.761611714975846, 12.37942948717949, 7.5710602053140095), # 13 (4.743037830455566, 12.357323456790127, 13.590834047415022, 10.798241545893719, 12.435589743589743, 7.567462801932367), # 14 (4.773430640913081, 12.441441761363635, 13.632479113110538, 10.833016304347826, 12.488942307692309, 7.563790760869566), # 15 (4.802901590088772, 12.521966526374861, 13.671794487289347, 10.86588888888889, 12.539410256410257, 7.560044444444445), # 16 (4.831417286118428, 12.598769195426486, 13.708730898314768, 10.896812198067634, 12.586916666666667, 7.556224214975846), # 17 (4.8589443371378405, 12.671721212121213, 13.74323907455013, 10.925739130434785, 12.631384615384619, 7.552330434782609), # 18 (4.8854493512828014, 12.740694020061728, 13.775269744358756, 10.952622584541063, 12.67273717948718, 7.5483634661835755), # 19 (4.910898936689104, 12.805559062850728, 13.804773636103969, 10.9774154589372, 12.710897435897436, 7.544323671497584), # 20 (4.935259701492538, 12.866187784090906, 13.831701478149103, 11.000070652173914, 12.74578846153846, 7.540211413043479), # 21 (4.958498253828894, 12.922451627384962, 13.856003998857469, 11.020541062801932, 12.777333333333331, 7.5360270531400975), # 22 (4.980581201833967, 12.97422203633558, 13.877631926592404, 11.038779589371982, 12.805455128205129, 7.531770954106282), # 23 (5.001475153643547, 13.021370454545455, 13.896535989717222, 11.054739130434783, 12.830076923076923, 7.52744347826087), # 24 (5.0211467173934246, 13.063768325617284, 13.91266691659526, 11.068372584541065, 12.851121794871794, 7.523044987922706), # 25 (5.039562501219393, 13.101287093153758, 13.925975435589832, 11.079632850241545, 12.86851282051282, 7.518575845410628), # 26 (5.056689113257243, 13.133798200757575, 13.936412275064265, 11.088472826086958, 12.88217307692308, 7.514036413043479), # 27 (5.072493161642767, 13.161173092031426, 13.943928163381893, 11.09484541062802, 12.89202564102564, 7.509427053140097), # 28 (5.086941254511755, 13.183283210578004, 13.948473828906026, 11.09870350241546, 12.89799358974359, 7.504748128019324), # 29 (5.1000000000000005, 13.200000000000001, 13.950000000000001, 11.100000000000001, 12.9, 7.5), # 30 (5.112219245524297, 13.213886079545453, 13.948855917874395, 11.099765849673204, 12.89926985815603, 7.4934020156588375), # 31 (5.124174680306906, 13.227588636363638, 13.945456038647343, 11.099067973856208, 12.897095035460993, 7.483239613526571), # 32 (5.135871675191815, 13.241105965909092, 13.93984891304348, 11.097913235294119, 12.893498936170213, 7.469612293853072), # 33 (5.147315601023018, 13.254436363636366, 13.93208309178744, 11.096308496732028, 12.888504964539008, 7.452619556888223), # 34 (5.158511828644501, 13.267578124999998, 13.922207125603865, 11.094260620915033, 12.882136524822696, 7.432360902881893), # 35 (5.169465728900256, 13.280529545454549, 13.91026956521739, 11.091776470588236, 12.874417021276598, 7.408935832083959), # 36 (5.180182672634271, 13.293288920454547, 13.896318961352657, 11.088862908496733, 12.865369858156027, 7.382443844744294), # 37 (5.190668030690537, 13.305854545454546, 13.8804038647343, 11.08552679738562, 12.855018439716313, 7.352984441112776), # 38 (5.200927173913044, 13.318224715909091, 13.862572826086955, 11.081775, 12.843386170212765, 7.32065712143928), # 39 (5.21096547314578, 13.330397727272729, 13.842874396135267, 11.077614379084968, 12.830496453900707, 7.285561385973679), # 40 (5.220788299232737, 13.342371874999998, 13.821357125603866, 11.073051797385622, 12.816372695035462, 7.247796734965852), # 41 (5.230401023017903, 13.354145454545458, 13.798069565217393, 11.068094117647059, 12.801038297872342, 7.207462668665667), # 42 (5.239809015345269, 13.365716761363636, 13.773060265700483, 11.06274820261438, 12.784516666666667, 7.164658687323005), # 43 (5.249017647058824, 13.377084090909092, 13.746377777777779, 11.05702091503268, 12.76683120567376, 7.119484291187739), # 44 (5.258032289002557, 13.388245738636364, 13.718070652173916, 11.050919117647059, 12.748005319148938, 7.072038980509745), # 45 (5.266858312020461, 13.399200000000002, 13.688187439613529, 11.044449673202614, 12.72806241134752, 7.022422255538898), # 46 (5.275501086956522, 13.409945170454547, 13.656776690821255, 11.037619444444445, 12.707025886524825, 6.970733616525071), # 47 (5.283965984654732, 13.420479545454548, 13.623886956521739, 11.030435294117646, 12.68491914893617, 6.9170725637181425), # 48 (5.292258375959079, 13.430801420454543, 13.589566787439615, 11.022904084967323, 12.66176560283688, 6.861538597367982), # 49 (5.300383631713555, 13.440909090909088, 13.553864734299518, 11.015032679738564, 12.63758865248227, 6.804231217724471), # 50 (5.308347122762149, 13.450800852272728, 13.516829347826087, 11.006827941176471, 12.612411702127659, 6.7452499250374816), # 51 (5.316154219948849, 13.460475, 13.47850917874396, 10.998296732026144, 12.58625815602837, 6.684694219556889), # 52 (5.3238102941176475, 13.469929829545457, 13.438952777777779, 10.98944591503268, 12.559151418439718, 6.622663601532567), # 53 (5.331320716112533, 13.479163636363635, 13.398208695652173, 10.980282352941177, 12.531114893617023, 6.559257571214393), # 54 (5.338690856777493, 13.488174715909091, 13.356325483091787, 10.970812908496733, 12.502171985815604, 6.494575628852241), # 55 (5.3459260869565215, 13.496961363636363, 13.313351690821257, 10.961044444444445, 12.472346099290782, 6.428717274695986), # 56 (5.353031777493607, 13.505521875000003, 13.269335869565218, 10.950983823529413, 12.441660638297872, 6.361782008995502), # 57 (5.360013299232737, 13.513854545454544, 13.224326570048309, 10.940637908496733, 12.410139007092198, 6.293869332000667), # 58 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59 ) passenger_arriving_acc = ( (3, 11, 2, 7, 3, 0, 6, 8, 4, 4, 1, 0), # 0 (7, 20, 12, 13, 5, 0, 19, 17, 8, 10, 3, 0), # 1 (14, 28, 23, 16, 10, 0, 25, 21, 16, 19, 9, 0), # 2 (21, 35, 33, 18, 12, 0, 34, 28, 23, 24, 11, 0), # 3 (22, 43, 41, 22, 15, 0, 47, 35, 29, 28, 13, 0), # 4 (25, 47, 50, 24, 15, 0, 52, 44, 35, 29, 13, 0), # 5 (29, 58, 64, 26, 16, 0, 61, 53, 45, 37, 16, 0), # 6 (36, 67, 75, 29, 16, 0, 73, 63, 51, 45, 16, 0), # 7 (42, 78, 86, 35, 17, 0, 78, 74, 57, 47, 21, 0), # 8 (47, 85, 95, 44, 17, 0, 86, 87, 65, 49, 24, 0), # 9 (51, 97, 102, 51, 19, 0, 92, 97, 72, 54, 27, 0), # 10 (55, 105, 111, 58, 20, 0, 98, 107, 81, 62, 29, 0), # 11 (59, 112, 119, 66, 24, 0, 104, 120, 94, 63, 32, 0), # 12 (63, 118, 124, 70, 25, 0, 113, 133, 104, 67, 35, 0), # 13 (66, 123, 132, 74, 26, 0, 122, 145, 109, 77, 38, 0), # 14 (71, 132, 144, 76, 30, 0, 130, 154, 115, 84, 40, 0), # 15 (78, 139, 150, 83, 32, 0, 137, 169, 123, 87, 43, 0), # 16 (83, 150, 163, 85, 37, 0, 148, 178, 131, 93, 46, 0), # 17 (86, 166, 174, 88, 41, 0, 156, 191, 137, 96, 48, 0), # 18 (91, 178, 189, 92, 41, 0, 166, 201, 148, 100, 51, 0), # 19 (94, 187, 204, 103, 44, 0, 174, 213, 152, 104, 53, 0), # 20 (97, 194, 210, 107, 46, 0, 181, 221, 164, 110, 55, 0), # 21 (103, 206, 220, 109, 48, 0, 191, 227, 172, 118, 58, 0), # 22 (107, 215, 226, 113, 49, 0, 195, 237, 179, 126, 59, 0), # 23 (109, 225, 239, 120, 50, 0, 207, 245, 186, 130, 62, 0), # 24 (115, 234, 253, 124, 53, 0, 212, 260, 190, 135, 63, 0), # 25 (120, 251, 259, 129, 55, 0, 218, 270, 198, 144, 66, 0), # 26 (125, 259, 272, 135, 58, 0, 223, 281, 203, 150, 69, 0), # 27 (128, 272, 281, 142, 60, 0, 233, 295, 207, 152, 72, 0), # 28 (134, 284, 285, 145, 63, 0, 242, 303, 213, 161, 74, 0), # 29 (138, 299, 291, 151, 68, 0, 252, 311, 217, 166, 74, 0), # 30 (140, 308, 296, 152, 69, 0, 260, 326, 224, 169, 77, 0), # 31 (143, 317, 303, 158, 73, 0, 268, 335, 231, 173, 79, 0), # 32 (149, 335, 309, 161, 76, 0, 273, 346, 234, 178, 80, 0), # 33 (153, 341, 316, 164, 78, 0, 287, 357, 241, 184, 83, 0), # 34 (159, 349, 329, 170, 81, 0, 292, 364, 245, 186, 86, 0), # 35 (163, 357, 334, 172, 83, 0, 299, 373, 251, 192, 89, 0), # 36 (171, 364, 340, 174, 87, 0, 315, 386, 257, 196, 92, 0), # 37 (177, 377, 344, 180, 88, 0, 326, 395, 267, 200, 95, 0), # 38 (179, 391, 354, 185, 91, 0, 332, 406, 277, 206, 97, 0), # 39 (185, 400, 363, 192, 92, 0, 339, 415, 285, 210, 97, 0), # 40 (190, 409, 372, 194, 97, 0, 347, 419, 294, 214, 97, 0), # 41 (192, 426, 377, 195, 98, 0, 353, 432, 300, 223, 98, 0), # 42 (199, 442, 385, 198, 102, 0, 357, 442, 305, 232, 100, 0), # 43 (201, 456, 398, 200, 102, 0, 368, 455, 307, 235, 103, 0), # 44 (209, 467, 411, 203, 104, 0, 372, 467, 313, 244, 105, 0), # 45 (219, 479, 419, 209, 106, 0, 378, 474, 317, 247, 107, 0), # 46 (222, 487, 430, 215, 106, 0, 387, 478, 324, 254, 111, 0), # 47 (228, 498, 441, 220, 108, 0, 395, 487, 332, 260, 113, 0), # 48 (229, 507, 451, 226, 109, 0, 401, 500, 340, 269, 116, 0), # 49 (231, 516, 457, 227, 113, 0, 407, 510, 343, 272, 117, 0), # 50 (238, 532, 465, 234, 115, 0, 411, 516, 349, 278, 122, 0), # 51 (241, 542, 476, 237, 117, 0, 417, 523, 359, 282, 124, 0), # 52 (246, 555, 484, 240, 119, 0, 425, 532, 366, 285, 127, 0), # 53 (252, 568, 490, 248, 122, 0, 431, 541, 377, 291, 129, 0), # 54 (253, 584, 495, 255, 123, 0, 439, 549, 382, 295, 133, 0), # 55 (260, 589, 510, 260, 125, 0, 443, 559, 386, 299, 136, 0), # 56 (268, 605, 515, 264, 125, 0, 446, 565, 396, 305, 139, 0), # 57 (269, 611, 523, 265, 127, 0, 456, 576, 401, 313, 142, 0), # 58 (269, 611, 523, 265, 127, 0, 456, 576, 401, 313, 142, 0), # 59 ) passenger_arriving_rate = ( (4.239442493415277, 8.699469696969697, 7.674466580976864, 4.055217391304347, 2.2857692307692306, 0.0, 7.610869565217392, 9.143076923076922, 6.082826086956521, 5.1163110539845755, 2.174867424242424, 0.0), # 0 (4.27923521607648, 8.796213246352414, 7.715918916023995, 4.077801207729468, 2.3029012820512818, 0.0, 7.608275422705315, 9.211605128205127, 6.116701811594203, 5.1439459440159965, 2.1990533115881035, 0.0), # 1 (4.318573563554774, 8.891521795735128, 7.7563873179091685, 4.099887922705314, 2.3196717948717946, 0.0, 7.60560193236715, 9.278687179487179, 6.1498318840579715, 5.170924878606112, 2.222880448933782, 0.0), # 2 (4.357424143985952, 8.9852925, 7.795842223650386, 4.121458695652173, 2.336065384615385, 0.0, 7.60284945652174, 9.34426153846154, 6.18218804347826, 5.197228149100257, 2.246323125, 0.0), # 3 (4.395753565505805, 9.07742251402918, 7.834254070265637, 4.142494685990338, 2.352066666666667, 0.0, 7.600018357487922, 9.408266666666668, 6.213742028985508, 5.222836046843758, 2.269355628507295, 0.0), # 4 (4.433528436250122, 9.167808992704828, 7.8715932947729215, 4.1629770531400965, 2.367660256410256, 0.0, 7.597108997584541, 9.470641025641024, 6.244465579710145, 5.247728863181948, 2.291952248176207, 0.0), # 5 (4.470715364354698, 9.25634909090909, 7.907830334190233, 4.182886956521739, 2.382830769230769, 0.0, 7.594121739130435, 9.531323076923076, 6.274330434782609, 5.271886889460156, 2.3140872727272725, 0.0), # 6 (4.507280957955322, 9.34293996352413, 7.942935625535561, 4.2022055555555555, 2.397562820512821, 0.0, 7.591056944444445, 9.590251282051284, 6.303308333333334, 5.295290417023708, 2.3357349908810323, 0.0), # 7 (4.543191825187787, 9.427478765432097, 7.976879605826908, 4.220914009661835, 2.4118410256410256, 0.0, 7.587914975845411, 9.647364102564103, 6.3313710144927535, 5.317919737217938, 2.3568696913580243, 0.0), # 8 (4.578414574187884, 9.509862651515151, 8.009632712082263, 4.23899347826087, 2.4256499999999996, 0.0, 7.584696195652175, 9.702599999999999, 6.358490217391305, 5.339755141388175, 2.377465662878788, 0.0), # 9 (4.612915813091406, 9.589988776655444, 8.041165381319622, 4.256425120772947, 2.438974358974359, 0.0, 7.581400966183574, 9.755897435897436, 6.384637681159421, 5.360776920879748, 2.397497194163861, 0.0), # 10 (4.646662150034143, 9.66775429573513, 8.071448050556983, 4.273190096618357, 2.4517987179487175, 0.0, 7.578029649758455, 9.80719487179487, 6.409785144927537, 5.380965367037988, 2.4169385739337823, 0.0), # 11 (4.679620193151888, 9.743056363636363, 8.100451156812339, 4.289269565217391, 2.4641076923076923, 0.0, 7.574582608695652, 9.85643076923077, 6.433904347826087, 5.400300771208226, 2.4357640909090907, 0.0), # 12 (4.71175655058043, 9.815792135241303, 8.128145137103683, 4.304644685990338, 2.475885897435898, 0.0, 7.5710602053140095, 9.903543589743592, 6.456967028985507, 5.418763424735789, 2.4539480338103257, 0.0), # 13 (4.743037830455566, 9.8858587654321, 8.154500428449014, 4.3192966183574875, 2.4871179487179482, 0.0, 7.567462801932367, 9.948471794871793, 6.478944927536231, 5.4363336189660085, 2.471464691358025, 0.0), # 14 (4.773430640913081, 9.953153409090907, 8.179487467866322, 4.33320652173913, 2.4977884615384616, 0.0, 7.563790760869566, 9.991153846153846, 6.499809782608695, 5.452991645244214, 2.488288352272727, 0.0), # 15 (4.802901590088772, 10.017573221099887, 8.203076692373608, 4.346355555555555, 2.507882051282051, 0.0, 7.560044444444445, 10.031528205128204, 6.519533333333333, 5.468717794915738, 2.504393305274972, 0.0), # 16 (4.831417286118428, 10.079015356341188, 8.22523853898886, 4.358724879227053, 2.517383333333333, 0.0, 7.556224214975846, 10.069533333333332, 6.538087318840581, 5.483492359325907, 2.519753839085297, 0.0), # 17 (4.8589443371378405, 10.13737696969697, 8.245943444730077, 4.370295652173914, 2.5262769230769235, 0.0, 7.552330434782609, 10.105107692307694, 6.55544347826087, 5.4972956298200515, 2.5343442424242424, 0.0), # 18 (4.8854493512828014, 10.192555216049382, 8.265161846615253, 4.381049033816424, 2.534547435897436, 0.0, 7.5483634661835755, 10.138189743589743, 6.571573550724637, 5.510107897743501, 2.5481388040123454, 0.0), # 19 (4.910898936689104, 10.244447250280581, 8.282864181662381, 4.3909661835748794, 2.542179487179487, 0.0, 7.544323671497584, 10.168717948717948, 6.58644927536232, 5.5219094544415865, 2.5611118125701453, 0.0), # 20 (4.935259701492538, 10.292950227272724, 8.299020886889462, 4.400028260869565, 2.5491576923076917, 0.0, 7.540211413043479, 10.196630769230767, 6.600042391304348, 5.53268059125964, 2.573237556818181, 0.0), # 21 (4.958498253828894, 10.337961301907969, 8.313602399314481, 4.408216425120773, 2.555466666666666, 0.0, 7.5360270531400975, 10.221866666666664, 6.6123246376811595, 5.542401599542987, 2.584490325476992, 0.0), # 22 (4.980581201833967, 10.379377629068463, 8.326579155955441, 4.415511835748792, 2.5610910256410255, 0.0, 7.531770954106282, 10.244364102564102, 6.623267753623189, 5.551052770636961, 2.5948444072671157, 0.0), # 23 (5.001475153643547, 10.417096363636363, 8.337921593830332, 4.421895652173912, 2.5660153846153846, 0.0, 7.52744347826087, 10.264061538461538, 6.632843478260869, 5.558614395886888, 2.6042740909090907, 0.0), # 24 (5.0211467173934246, 10.451014660493826, 8.347600149957156, 4.427349033816426, 2.5702243589743587, 0.0, 7.523044987922706, 10.280897435897435, 6.641023550724639, 5.565066766638103, 2.6127536651234564, 0.0), # 25 (5.039562501219393, 10.481029674523006, 8.355585261353898, 4.431853140096617, 2.5737025641025637, 0.0, 7.518575845410628, 10.294810256410255, 6.647779710144927, 5.570390174235932, 2.6202574186307515, 0.0), # 26 (5.056689113257243, 10.507038560606059, 8.361847365038559, 4.435389130434783, 2.5764346153846156, 0.0, 7.514036413043479, 10.305738461538462, 6.653083695652175, 5.574564910025706, 2.6267596401515148, 0.0), # 27 (5.072493161642767, 10.52893847362514, 8.366356898029135, 4.437938164251207, 2.578405128205128, 0.0, 7.509427053140097, 10.313620512820512, 6.656907246376812, 5.5775712653527565, 2.632234618406285, 0.0), # 28 (5.086941254511755, 10.546626568462402, 8.369084297343615, 4.439481400966184, 2.579598717948718, 0.0, 7.504748128019324, 10.318394871794872, 6.659222101449276, 5.57938953156241, 2.6366566421156006, 0.0), # 29 (5.1000000000000005, 10.56, 8.370000000000001, 4.44, 2.58, 0.0, 7.5, 10.32, 6.660000000000001, 5.58, 2.64, 0.0), # 30 (5.112219245524297, 10.571108863636361, 8.369313550724637, 4.439906339869282, 2.5798539716312057, 0.0, 7.4934020156588375, 10.319415886524823, 6.659859509803923, 5.579542367149758, 2.6427772159090903, 0.0), # 31 (5.124174680306906, 10.582070909090909, 8.367273623188405, 4.439627189542483, 2.5794190070921985, 0.0, 7.483239613526571, 10.317676028368794, 6.659440784313724, 5.578182415458937, 2.6455177272727273, 0.0), # 32 (5.135871675191815, 10.592884772727274, 8.363909347826088, 4.439165294117647, 2.5786997872340423, 0.0, 7.469612293853072, 10.314799148936169, 6.658747941176471, 5.575939565217392, 2.6482211931818185, 0.0), # 33 (5.147315601023018, 10.603549090909091, 8.359249855072465, 4.438523398692811, 2.5777009929078014, 0.0, 7.452619556888223, 10.310803971631206, 6.657785098039217, 5.572833236714976, 2.6508872727272728, 0.0), # 34 (5.158511828644501, 10.614062499999998, 8.353324275362318, 4.437704248366013, 2.576427304964539, 0.0, 7.432360902881893, 10.305709219858157, 6.65655637254902, 5.568882850241546, 2.6535156249999994, 0.0), # 35 (5.169465728900256, 10.624423636363638, 8.346161739130434, 4.436710588235294, 2.5748834042553193, 0.0, 7.408935832083959, 10.299533617021277, 6.655065882352941, 5.564107826086956, 2.6561059090909094, 0.0), # 36 (5.180182672634271, 10.634631136363637, 8.337791376811595, 4.435545163398693, 2.573073971631205, 0.0, 7.382443844744294, 10.29229588652482, 6.65331774509804, 5.558527584541062, 2.6586577840909094, 0.0), # 37 (5.190668030690537, 10.644683636363636, 8.32824231884058, 4.4342107189542475, 2.5710036879432625, 0.0, 7.352984441112776, 10.28401475177305, 6.651316078431372, 5.5521615458937195, 2.661170909090909, 0.0), # 38 (5.200927173913044, 10.654579772727272, 8.317543695652173, 4.43271, 2.568677234042553, 0.0, 7.32065712143928, 10.274708936170212, 6.649065, 5.545029130434782, 2.663644943181818, 0.0), # 39 (5.21096547314578, 10.664318181818182, 8.305724637681159, 4.431045751633987, 2.566099290780141, 0.0, 7.285561385973679, 10.264397163120565, 6.646568627450981, 5.537149758454106, 2.6660795454545454, 0.0), # 40 (5.220788299232737, 10.673897499999997, 8.29281427536232, 4.429220718954248, 2.563274539007092, 0.0, 7.247796734965852, 10.253098156028368, 6.643831078431373, 5.5285428502415455, 2.6684743749999993, 0.0), # 41 (5.230401023017903, 10.683316363636365, 8.278841739130435, 4.427237647058823, 2.560207659574468, 0.0, 7.207462668665667, 10.240830638297872, 6.640856470588235, 5.519227826086957, 2.6708290909090913, 0.0), # 42 (5.239809015345269, 10.692573409090908, 8.26383615942029, 4.4250992810457515, 2.556903333333333, 0.0, 7.164658687323005, 10.227613333333332, 6.637648921568627, 5.509224106280192, 2.673143352272727, 0.0), # 43 (5.249017647058824, 10.701667272727272, 8.247826666666667, 4.422808366013072, 2.5533662411347517, 0.0, 7.119484291187739, 10.213464964539007, 6.634212549019608, 5.498551111111111, 2.675416818181818, 0.0), # 44 (5.258032289002557, 10.71059659090909, 8.23084239130435, 4.420367647058823, 2.5496010638297872, 0.0, 7.072038980509745, 10.198404255319149, 6.630551470588235, 5.487228260869566, 2.6776491477272724, 0.0), # 45 (5.266858312020461, 10.71936, 8.212912463768117, 4.417779869281045, 2.5456124822695037, 0.0, 7.022422255538898, 10.182449929078015, 6.626669803921568, 5.475274975845411, 2.67984, 0.0), # 46 (5.275501086956522, 10.727956136363636, 8.194066014492753, 4.415047777777778, 2.5414051773049646, 0.0, 6.970733616525071, 10.165620709219858, 6.6225716666666665, 5.462710676328501, 2.681989034090909, 0.0), # 47 (5.283965984654732, 10.736383636363637, 8.174332173913044, 4.412174117647059, 2.536983829787234, 0.0, 6.9170725637181425, 10.147935319148935, 6.618261176470588, 5.449554782608695, 2.6840959090909093, 0.0), # 48 (5.292258375959079, 10.744641136363633, 8.15374007246377, 4.409161633986929, 2.5323531205673757, 0.0, 6.861538597367982, 10.129412482269503, 6.613742450980394, 5.435826714975845, 2.6861602840909082, 0.0), # 49 (5.300383631713555, 10.752727272727268, 8.13231884057971, 4.406013071895425, 2.527517730496454, 0.0, 6.804231217724471, 10.110070921985816, 6.6090196078431385, 5.421545893719807, 2.688181818181817, 0.0), # 50 (5.308347122762149, 10.760640681818181, 8.110097608695652, 4.4027311764705885, 2.5224823404255314, 0.0, 6.7452499250374816, 10.089929361702126, 6.604096764705883, 5.406731739130435, 2.6901601704545453, 0.0), # 51 (5.316154219948849, 10.768379999999999, 8.087105507246376, 4.399318692810457, 2.517251631205674, 0.0, 6.684694219556889, 10.069006524822695, 6.5989780392156865, 5.391403671497584, 2.6920949999999997, 0.0), # 52 (5.3238102941176475, 10.775943863636364, 8.063371666666667, 4.395778366013072, 2.5118302836879436, 0.0, 6.622663601532567, 10.047321134751774, 6.593667549019608, 5.375581111111111, 2.693985965909091, 0.0), # 53 (5.331320716112533, 10.783330909090907, 8.038925217391304, 4.392112941176471, 2.5062229787234043, 0.0, 6.559257571214393, 10.024891914893617, 6.5881694117647065, 5.359283478260869, 2.6958327272727267, 0.0), # 54 (5.338690856777493, 10.790539772727271, 8.013795289855072, 4.388325163398693, 2.5004343971631204, 0.0, 6.494575628852241, 10.001737588652482, 6.58248774509804, 5.342530193236715, 2.697634943181818, 0.0), # 55 (5.3459260869565215, 10.79756909090909, 7.988011014492754, 4.384417777777777, 2.494469219858156, 0.0, 6.428717274695986, 9.977876879432625, 6.576626666666667, 5.325340676328502, 2.6993922727272723, 0.0), # 56 (5.353031777493607, 10.804417500000001, 7.96160152173913, 4.380393529411765, 2.4883321276595742, 0.0, 6.361782008995502, 9.953328510638297, 6.570590294117648, 5.307734347826087, 2.7011043750000003, 0.0), # 57 (5.360013299232737, 10.811083636363634, 7.934595942028984, 4.376255163398692, 2.4820278014184396, 0.0, 6.293869332000667, 9.928111205673758, 6.564382745098039, 5.289730628019323, 2.7027709090909084, 0.0), # 58 (0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 59 ) passenger_allighting_rate = ( (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 0 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 1 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 2 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 3 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 4 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 5 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 6 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 7 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 8 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 9 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 10 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 11 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 12 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 13 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 14 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 15 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 16 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 17 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 18 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 19 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 20 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 21 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 22 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 23 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 24 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 25 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 26 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 27 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 28 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 29 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 30 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 31 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 32 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 33 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 34 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 35 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 36 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 37 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 38 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 39 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 40 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 41 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 42 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 43 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 44 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 45 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 46 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 47 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 48 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 49 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 50 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 51 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 52 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 53 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 54 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 55 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 56 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 57 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 58 (0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1, 0, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 0.16666666666666666, 1), # 59 ) """ parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html """ #initial entropy entropy = 258194110137029475889902652135037600173 #index for seed sequence child child_seed_index = ( 1, # 0 95, # 1 )

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6e324a51b72b07457cd62a406e2c7a294aeca1af

188

py

Python

cge/output/trash/output.py

cadms/resfinder

f75c5205ca82ca825c2bef5494060d5169788135

[ "Apache-2.0" ]

null

cge/output/trash/output.py

cadms/resfinder

f75c5205ca82ca825c2bef5494060d5169788135

[ "Apache-2.0" ]

null

cge/output/trash/output.py

cadms/resfinder

f75c5205ca82ca825c2bef5494060d5169788135

[ "Apache-2.0" ]

null

#!/usr/bin/env python3 from .exceptions import DuplicateKeyError from .exceptions import LockedObjectError class Write(): """ """ def txt_table(tableresult): pass

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py

Python

datastructures/arrays/array_from_permutation/__init__.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

3

2017-05-02T10:28:13.000Z

2019-02-06T09:10:11.000Z

datastructures/arrays/array_from_permutation/__init__.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

2

2017-06-21T20:39:14.000Z

2020-02-25T10:28:57.000Z

datastructures/arrays/array_from_permutation/__init__.py

JASTYN/pythonmaster

46638ab09d28b65ce5431cd0759fe6df272fb85d

[ "Apache-2.0", "MIT" ]

2

2016-07-29T04:35:22.000Z

2017-01-18T17:05:36.000Z

from typing import List def build_array(nums: List[int]) -> List[int]: return [nums[nums[x]] for x in range(len(nums))]

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py

Python

scripts/create_experiments/create_json_experiments.py

rvalienter90/rl-agents

ad6be08f9a7e2f0ec0daf6f557bd9f476bb9e4da

[ "MIT" ]

null

scripts/create_experiments/create_json_experiments.py

rvalienter90/rl-agents

ad6be08f9a7e2f0ec0daf6f557bd9f476bb9e4da

[ "MIT" ]

null

scripts/create_experiments/create_json_experiments.py

rvalienter90/rl-agents

ad6be08f9a7e2f0ec0daf6f557bd9f476bb9e4da

[ "MIT" ]

null

import json import numpy as np from pathlib import Path import os def get_project_root() -> Path: return Path(__file__).parent.parent root_folder = get_project_root() data = { "info": "", "additional_folder_name": "", "base_config": "", "observation": { "observation_config":{} }, "reward": {}, "scenario": {}, "merging_vehicle": {}, "exit_vehicle": {}, "agent_config": { "exploration": {}, "model": {}, "optimizer":{} }, "cruising_vehicle": {}, "action": { "action_config": {}, } } # ini_folder="./scripts/rl_agents_scripts/configs/experiments/IEEE_Access/" # ini_folder = "./scripts/rl_agents_scripts/configs/experiments/IROS/" ini_folder = "./scripts/rl_agents_scripts/configs/experiments/Behavior/" # base_name_json = "exp_merge_IROS_" base_name_json = "exp_behavior_" start_num =110 play_with_rewards = False play_with_merging_position = False play_with_coop = False play_with_mission_is_controlled = False play_with_randomness = False ablation_action_history = False ablation_state_representation_f1 = False ablation_state_representation_f2 = False complex_scenario = False state_representation_conv = False IROS_exp2000 = False IROS_exp3000 = False IROS_exp4000 = False IROS_exp5000 = False IROS_exp9100 = False complex_100 = False Behavior_100s = False behavior_400s_sensitivity = False behavior_500s_sensitivity = False behavior_900s_sensitivity = False generalization_100s = False generalization_120s = False generalization_200s = False generalization_250s = False generalization_300s = True if generalization_100s: ini_folder = os.path.join(root_folder,'configs/experiments/Multienv/') base_name_json = "exp_generalization_" base_config_folder = "configs/experiments/Multienv/" # start_num = 400 start_num = 100 for base_config in ["exp_base_multi_sa_latent.json", "exp_multi_Grid_DQN_sa_latent.json","exp_base_multi_Image_sa_latent.json"]: # for base_config in ["exp_agressive_DQN.json","exp_neutral_DQN.json","exp_conservative_DQN.json"]: data["base_config"] = base_config_folder + base_config for latent_dimention in [16,32,64]: data['latent_dimention']=latent_dimention name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if generalization_120s: ini_folder = os.path.join(root_folder,'configs/experiments/Multienv/') base_name_json = "exp_generalization_" base_config_folder = "configs/experiments/Multienv/" # start_num = 400 start_num = 120 for base_config in ["exp_base_multi_sa.json", "exp_multi_Grid_DQN_sa.json","exp_base_multi_Image_sa.json"]: # for base_config in ["exp_agressive_DQN.json","exp_neutral_DQN.json","exp_conservative_DQN.json"]: data["base_config"] = base_config_folder + base_config name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if generalization_200s: ini_folder = os.path.join(root_folder,'configs/experiments/Multienv/') base_name_json = "exp_generalization_" base_config_folder = "configs/experiments/Multienv/" # start_num = 400 start_num = 200 for scenario in ["intersection", "roundabout","road_merge","road_exit"]: for base_config in ["exp_base_multi_sa_latent.json", "exp_multi_Grid_DQN_sa_latent.json","exp_base_multi_Image_sa_latent.json"]: # for base_config in ["exp_agressive_DQN.json","exp_neutral_DQN.json","exp_conservative_DQN.json"]: data['scenario']['road_types']=[scenario] data["base_config"] = base_config_folder + base_config for latent_dimention in [16,32,64]: data['latent_dimention']=latent_dimention name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if generalization_250s: ini_folder = os.path.join(root_folder,'configs/experiments/Multienv/') base_name_json = "exp_generalization_" base_config_folder = "configs/experiments/Multienv/" start_num = 250 for scenario in ["intersection", "roundabout","road_merge","road_exit"]: for base_config in ["exp_base_multi_sa.json", "exp_multi_Grid_DQN_sa.json","exp_base_multi_Image_sa.json"]: # for base_config in ["exp_agressive_DQN.json","exp_neutral_DQN.json","exp_conservative_DQN.json"]: data['scenario']['road_types']=[scenario] data["base_config"] = base_config_folder + base_config name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if generalization_300s: ini_folder = os.path.join(root_folder,'configs/experiments/Multienv/') base_name_json = "exp_generalization_" base_config_folder = "configs/experiments/Multienv/" start_num = 350 allenv = ["intersection", "roundabout","road_merge","road_exit"] for base_config in ["exp_generalization_120.json", "exp_generalization_250.json","exp_generalization_253.json","exp_generalization_256.json","exp_generalization_259.json"]: # for base_config in ["exp_generalization_100.json", "exp_generalization_200.json","exp_generalization_209.json","exp_generalization_218.json","exp_generalization_227.json"]: for scenario in ["intersection", "roundabout", "road_merge", "road_exit", allenv]: # for base_config in ["exp_agressive_DQN.json","exp_neutral_DQN.json","exp_conservative_DQN.json"]: if isinstance(scenario,list): data['scenario']['road_types'] = scenario else: data['scenario']['road_types']=[scenario] data["base_config"] = base_config_folder + base_config name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if behavior_400s_sensitivity: base_config_folder = "configs/experiments/Behavior/" # start_num = 400 start_num = 420 for controlled_vehicle in [True, False]: # for base_config in ["exp_agressive_DQN.json","exp_neutral_DQN.json","exp_conservative_DQN.json"]: for base_config in ["exp_agressive_DQN_exit.json", "exp_neutral_DQN_exit.json", "exp_conservative_DQN_exit.json"]: # for base_config in ["exp_agressive_DQN.json", "exp_conservative_DQN.json", "exp_neutral_DQN.json"]: # for base_config in ["exp_agressive_MLP.json", "exp_conservative_MLP.json", "exp_neutral_MLP.json"]: data["base_config"] = base_config_folder + base_config for cooperative_flag, sympathy_flag in [(True, True), (False, False)]: # for type in ["highway_env.vehicle.behavior.CustomVehicle" , "highway_env.vehicle.behavior.CustomVehicleAggressive"]: for type in ["highway_env.vehicle.behavior.CustomVehicle"]: data["reward"]["cooperative_flag"] = cooperative_flag data["reward"]["sympathy_flag"] = sympathy_flag # data["observation"]["cooperative_perception"] = True data["additional_folder_name"] = "exp_merge_" + str(start_num) data["merging_vehicle"]['vehicles_type'] = type data["merging_vehicle"]['controlled_vehicle'] = controlled_vehicle # True # data["merging_vehicle"]['max_speed'] = 25 data["tracker_logging"] = True if controlled_vehicle: data['action']['action_config']['lateral'] = True else: data['action']['action_config']['lateral'] = False info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + \ " controlled_vehicle " + str(data["merging_vehicle"]['controlled_vehicle']) data['info'] = info name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if behavior_500s_sensitivity: start_num = 300 n = 4 distance_wantedn = np.linspace(7, 0.5, n) time_wantedn = np.linspace(2, 0.5, n) comfort_acc_maxn = np.linspace(2, 9, n) comfort_acc_minn = np.linspace(-4, -12, n) longitudinal = [] for i in range(0,n): longitudinal.append((distance_wantedn[i], time_wantedn[i], comfort_acc_maxn[i], comfort_acc_minn[i])) politenessn = np.linspace(0.7, 0, n) lane_change_min_acc_gainn = np.linspace(0.4, 0, n) lane_change_max_braking_imposedn = np.linspace(2, 12, n) lateral = [] for i in range(0, n): lateral.append((politenessn[i], lane_change_min_acc_gainn[i], lane_change_max_braking_imposedn[i])) base_config_folder = "configs/experiments/Behavior/" # start_num = 400 for controlled_vehicle in [False]: for base_config in ["exp_behavior_highway_base.json"]: # for base_config in ["exp_agressive_complex_DQN.json"]: # for base_config in ["exp_agressive_DQN_exit.json"]: # for base_config in ["exp_agressive_DQN.json"]: for distance_wanted, time_wanted, comfort_acc_max, comfort_acc_min in longitudinal: for politeness, lane_change_min_acc_gain, lane_change_max_braking_imposed in lateral: data["cruising_vehicle"]['distance_wanted'] = distance_wanted data["cruising_vehicle"]['time_wanted'] = time_wanted data["cruising_vehicle"]['comfort_acc_max'] = comfort_acc_max data["cruising_vehicle"]['comfort_acc_min'] = comfort_acc_min data["cruising_vehicle"]['politeness'] = politeness data["cruising_vehicle"]['lane_change_min_acc_gain'] = lane_change_min_acc_gain data["cruising_vehicle"]['lane_change_max_braking_imposed'] = lane_change_max_braking_imposed data["base_config"] = base_config_folder + base_config for cooperative_flag, sympathy_flag in [(True, True), (False, False)]: # for type in ["highway_env.vehicle.behavior.CustomVehicle" , "highway_env.vehicle.behavior.CustomVehicleAggressive"]: for type in ["highway_env.vehicle.behavior.CustomVehicle"]: data["reward"]["cooperative_flag"] = cooperative_flag data["reward"]["sympathy_flag"] = sympathy_flag # data["observation"]["cooperative_perception"] = True data["additional_folder_name"] = "exp_merge_" + str(start_num) data["merging_vehicle"]['vehicles_type'] = type data["merging_vehicle"]['controlled_vehicle'] = controlled_vehicle # True # data["merging_vehicle"]['max_speed'] = 25 data["tracker_logging"] = True if controlled_vehicle: data['action']['action_config']['lateral'] = True else: data['action']['action_config']['lateral'] = True info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + \ " controlled_vehicle " + str(data["merging_vehicle"]['controlled_vehicle']) data['info'] = info name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if behavior_900s_sensitivity: start_num = 900 n = 2 distance_wantedn = np.linspace(7, 0.5, n) time_wantedn = np.linspace(2, 0.5, n) comfort_acc_maxn = np.linspace(2, 9, n) comfort_acc_minn = np.linspace(-4, -12, n) longitudinal = [] for i in range(0,n): longitudinal.append((distance_wantedn[i], time_wantedn[i], comfort_acc_maxn[i], comfort_acc_minn[i])) politenessn = np.linspace(0.7, 0, n) lane_change_min_acc_gainn = np.linspace(0.4, 0, n) lane_change_max_braking_imposedn = np.linspace(2, 12, n) lateral = [] for i in range(0, n): lateral.append((politenessn[i], lane_change_min_acc_gainn[i], lane_change_max_braking_imposedn[i])) base_config_folder = "configs/experiments/Behavior/" # start_num = 400 for controlled_vehicle in [False]: # for base_config in ["exp_behavior_highway_base.json"]: # for base_config in ["exp_agressive_complex_DQN.json"]: for base_config in ["exp_agressive_DQN_exit.json"]: # for base_config in ["exp_agressive_DQN.json"]: for distance_wanted, time_wanted, comfort_acc_max, comfort_acc_min in longitudinal: for politeness, lane_change_min_acc_gain, lane_change_max_braking_imposed in lateral: data["cruising_vehicle"]['distance_wanted'] = distance_wanted data["cruising_vehicle"]['time_wanted'] = time_wanted data["cruising_vehicle"]['comfort_acc_max'] = comfort_acc_max data["cruising_vehicle"]['comfort_acc_min'] = comfort_acc_min data["cruising_vehicle"]['politeness'] = politeness data["cruising_vehicle"]['lane_change_min_acc_gain'] = lane_change_min_acc_gain data["cruising_vehicle"]['lane_change_max_braking_imposed'] = lane_change_max_braking_imposed data["base_config"] = base_config_folder + base_config for vals in [10,15,20,25,30]: data["exit_vehicle"]['random_offset_exit'] = [vals, vals] data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if Behavior_100s: base_config_folder = "configs/experiments/Behavior/" start_num = 220 for base_config in ["exp_agressive_Conv3D.json","exp_conservative_Conv3D.json","exp_neutral_Conv3D.json"]: # for base_config in ["exp_agressive_DQN.json", "exp_conservative_DQN.json", "exp_neutral_DQN.json"]: # for base_config in ["exp_agressive_MLP.json", "exp_conservative_MLP.json", "exp_neutral_MLP.json"]: data["base_config"] = base_config_folder + base_config for cooperative_flag, sympathy_flag in [(True, True)]: # for type in ["highway_env.vehicle.behavior.CustomVehicle" , "highway_env.vehicle.behavior.CustomVehicleAggressive"]: for controlled_vehicle in [True, False]: for type in ["highway_env.vehicle.behavior.CustomVehicle"]: data["reward"]["cooperative_flag"] = cooperative_flag data["reward"]["sympathy_flag"] = sympathy_flag # data["observation"]["cooperative_perception"] = True data["additional_folder_name"] = "exp_merge_" + str(start_num) data["merging_vehicle"]['vehicles_type'] = type data["merging_vehicle"]['controlled_vehicle'] = controlled_vehicle # True # data["merging_vehicle"]['max_speed'] = 25 data["tracker_logging"] = True info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + \ " controlled_vehicle " + str(data["merging_vehicle"]['controlled_vehicle']) data['info'] = info name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if complex_100: base_config_folder = "configs/experiments/complex/" start_num = 100 for base_config in ["exp_merge_complex_100base-1.json","exp_merge_complex_100base-2.json", "exp_merge_complex_100base-3.json", "exp_merge_complex_100base-3-2.json"]: for controlled_vehicle in [True, False]: data["base_config"] = base_config_folder + base_config data["merging_vehicle"]["controlled_vehicle"] = controlled_vehicle info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " controlled_vehicle " + str(controlled_vehicle) data["additional_folder_name"] = "exp_merge_complex" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if IROS_exp9100: base_config_folder = "configs/experiments/IROS/" for base_config in ["exp_merge_IROS_9000base-1.json", "exp_merge_IROS_9000base-2.json", "exp_merge_IROS_9000base-2-1.json","exp_merge_IROS_9000base-3.json", "exp_merge_IROS_9000base-3-1.json","exp_merge_IROS_9000base-3-2.json"]: for random_offset_merging in [20]: data["base_config"] = base_config_folder + base_config data["merging_vehicle"]["random_offset_merging"] = [-random_offset_merging , random_offset_merging] info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " random_offset_merging " + str(random_offset_merging) data["additional_folder_name"] = "exp_merge_IROS" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if IROS_exp2000: base_config_folder = "configs/experiments/IROS/" for network in ["ConvNetStanfordMARLNoRes"]: for base_config in ["exp_merge_IROS_2000_base-1.json", "exp_merge_IROS_2000_base-2.json", "exp_merge_IROS_2000_base-3.json"]: for gama in [0.8, 0.99]: for memory_capacity in [20000]: for target_update in [50, 500]: for tau in [10000]: data["base_config"] = base_config_folder + base_config data["agent_config"]["gamma"] = gama data["agent_config"]["memory_capacity"] = memory_capacity data["agent_config"]["target_update"] = target_update data["agent_config"]["exploration"]["tau"] = tau data["agent_config"]["model"]["type"] = network info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " model " + str(network) + \ " tau " + str(tau) + \ " target_update " + str(target_update) + \ " memory_capacity " + str(memory_capacity) + \ " gama " + str(gama) data["additional_folder_name"] = "exp_merge_IROS" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if IROS_exp3000: base_config_folder = "configs/experiments/IROS/" for network in ["ConvNet3Layer"]: for base_config in ["exp_merge_IROS_3000base-1.json", "exp_merge_IROS_3000base-2.json", "exp_merge_IROS_3000base-3.json","exp_merge_IROS_3000base-4.json"]: for double in [False]: for optimizer in ["ADAM", "RMS_PROP"]: for policy_frequency in [1, 5]: data["agent_config"]["model"]["type"] = network data["base_config"] = base_config_folder + base_config data["agent_config"]["double"] = double data["agent_config"]["optimizer"]["type"] = optimizer data["policy_frequency"] = policy_frequency info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " double " + str(double) + \ " optimizer " + str(optimizer) + \ " network " + str(network) + \ " policy_frequency " + str(policy_frequency) data["additional_folder_name"] = "exp_merge_IROS" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if IROS_exp4000: base_config_folder = "configs/experiments/IROS/" for network in ["ConvNetStanfordMARLNoRes", "ConvNetStanfordMARLRes"]: for base_config in ["exp_merge_IROS_4000base-1.json", "exp_merge_IROS_4000base-2.json", "exp_merge_IROS_4000base-3.json","exp_merge_IROS_4000base-4.json"]: for tau in [20000]: for exploration in ["EpsilonGreedyLinear"]: # for exploration in ["EpsilonGreedy", "EpsilonGreedyLinear"]: # for observation_shape in [[500, 64], [200, 64]]: for observation_shape in [[200,64]]: data["agent_config"]["model"]["type"] = network data["base_config"] = base_config_folder + base_config # data["agent_config"]["double"] = double # data["agent_config"]["optimizer"]["type"] = optimizer # data["policy_frequency"] = policy_frequency data["agent_config"]["exploration"]["method"] = exploration data["agent_config"]["exploration"]["tau"] = tau data["observation"]["observation_config"]["observation_shape"] = observation_shape data["observation"]["observation_config"]["observation_shape"] = observation_shape info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " exploration " + str(exploration) + \ " tau " + str(tau) + \ " observation_shape " + str(observation_shape) + \ " network " + str(network) data["additional_folder_name"] = "exp_merge_IROS" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if IROS_exp5000: base_config_folder = "configs/experiments/IROS/" for network in ["ConvNet3D", "ConvNet3DResidual"]: for base_config in ["exp_merge_IROS_5000base-1.json", "exp_merge_IROS_5000base-2.json" ]: for tau in [20000]: for exploration in ["EpsilonGreedyLinear"]: # for exploration in ["EpsilonGreedy", "EpsilonGreedyLinear"]: for observation_shape in [[500, 64], [200, 64]]: # for observation_shape in [[200,64]]: for history_stack_size in [5,10,15]: data["agent_config"]["model"]["type"] = network data["base_config"] = base_config_folder + base_config # data["agent_config"]["double"] = double # data["agent_config"]["optimizer"]["type"] = optimizer # data["policy_frequency"] = policy_frequency data["agent_config"]["exploration"]["method"] = exploration data["agent_config"]["exploration"]["tau"] = tau data["observation"]["observation_config"]["observation_shape"] = observation_shape data["observation"]["observation_config"]["observation_shape"] = observation_shape data["observation"]["observation_config"]["history_stack_size"] = history_stack_size info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " exploration " + str(exploration) + \ " tau " + str(tau) + \ " observation_shape " + str(observation_shape) + \ " history_stack_size " + str(history_stack_size) + \ " network " + str(network) data["additional_folder_name"] = "exp_merge_IROS" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if play_with_rewards: for collision_reward in [0, -2]: for successful_merging_reward in [0,10]: for high_speed_reward in [1]: for cooperative_reward in [4]: data["reward"]["cooperative_flag"] = True data["reward"]["sympathy_flag"] = True if successful_merging_reward == 0: data["reward"]["sympathy_flag"] = False info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " collision_reward= " + str(collision_reward) + " and " + \ "successful_merging_reward= " + str(successful_merging_reward) + " and " + \ "high_speed_reward= " + str(high_speed_reward) + " and " + \ "cooperative_reward= " + str(cooperative_reward) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["reward"]['collision_reward'] = collision_reward data["reward"]['successful_merging_reward'] = successful_merging_reward data["reward"]['high_speed_reward'] = high_speed_reward data["reward"]['cooperative_reward'] = cooperative_reward data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if complex_scenario: for on_desired_lane_reward in [2, 5, 10]: data["reward"]["cooperative_flag"] = True data["reward"]["sympathy_flag"] = False data["additional_folder_name"] = "exp_merge_" + str(start_num) data["reward"]['on_desired_lane_reward'] = on_desired_lane_reward data["tracker_logging"] = True info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " on_desired_lane_reward= " + str(on_desired_lane_reward) data['info'] = info name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if play_with_merging_position: for initial_position in [90, 95, 100]: for speed in [23, 25, 27]: data["reward"]["cooperative_flag"] = True data["reward"]["sympathy_flag"] = False info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ "initial_position= " + str(initial_position) + " and " + \ "speed= " + str(speed) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["merging_vehicle"]['initial_position'] = [initial_position, 0] data["merging_vehicle"]['speed'] = speed data["tracker_logging"] = True name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if play_with_coop: base_config_folder = "configs/experiments/complex/" start_num = 300 for base_config in ["exp_merge_complex_100base-1.json"]: data["base_config"] = base_config_folder + base_config for cooperative_flag, sympathy_flag in [(True, True), (True, False), (False, False)]: # for type in ["highway_env.vehicle.behavior.CustomVehicle" , "highway_env.vehicle.behavior.CustomVehicleAggressive"]: for controlled_vehicle in [True, False]: for type in ["highway_env.vehicle.behavior.CustomVehicle"]: data["reward"]["cooperative_flag"] = cooperative_flag data["reward"]["sympathy_flag"] = sympathy_flag # data["observation"]["cooperative_perception"] = True data["additional_folder_name"] = "exp_merge_" + str(start_num) data["merging_vehicle"]['vehicles_type'] = type data["merging_vehicle"]['controlled_vehicle'] = controlled_vehicle # True # data["merging_vehicle"]['max_speed'] = 25 data["tracker_logging"] = True info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + \ " controlled_vehicle " + str(data["merging_vehicle"]['controlled_vehicle']) data['info'] = info name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if play_with_randomness: for cooperative_flag, sympathy_flag in [(True, True), (True, False), (False, False)]: # for type in ["highway_env.vehicle.behavior.CustomVehicle" , "highway_env.vehicle.behavior.CustomVehicleAggressive"]: for type in ["highway_env.vehicle.behavior.CustomVehicle"]: for random_offset_merging, randomize_speed_offset in zip([2, 10, 15], [0, 4, 6]): data["reward"]["cooperative_flag"] = cooperative_flag data["reward"]["sympathy_flag"] = sympathy_flag data["observation"]["cooperative_perception"] = True data["additional_folder_name"] = "exp_merge_" + str(start_num) data["merging_vehicle"]['vehicles_type'] = type data["merging_vehicle"]['controlled_vehicle'] = True data["merging_vehicle"]['random_offset_merging'] = [-random_offset_merging, random_offset_merging] data["scenario"]['randomize_speed_offset'] = [-randomize_speed_offset, randomize_speed_offset] data["tracker_logging"] = True info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + \ " cooperative_perception " + str(data["observation"]["cooperative_perception"]) + \ " controlled_vehicle" + str(data["merging_vehicle"]['controlled_vehicle']) + \ " random_offset_merging" + str(data["merging_vehicle"]['random_offset_merging']) + \ " randomize_speed_offset" + str(data["scenario"]['randomize_speed_offset']) data['info'] = info name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) # for type in ["highway_env.vehicle.behavior.CustomVehicle", "highway_env.vehicle.behavior.CustomVehicleAggressive"]: # data["reward"]["cooperative_flag"] = False # data["reward"]["sympathy_flag"] = False # data["observation"]["cooperative_perception"] = False # # info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ # " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ # " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ # " type= " + str(type) + " cooperative_perception " + str(data["observation"]["cooperative_perception"]) # # data["additional_folder_name"] = "exp_merge_" + str(start_num) # data['info'] = info # data["merging_vehicle"]['vehicles_type'] = type # data["tracker_logging"] = True # # name = ini_folder + "exp_merge_" + str(start_num) + '.json' # start_num += 1 # with open(name, 'w') as outfile: # json.dump(data, outfile) if play_with_mission_is_controlled: type = "ControlledVehicle" for cooperative_flag, sympathy_flag in [(True, True), (True, False), (False, False)]: data["reward"]["cooperative_flag"] = cooperative_flag data["reward"]["sympathy_flag"] = sympathy_flag data["observation"]["cooperative_perception"] = True info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + " cooperative_perception " + str(data["observation"]["cooperative_perception"]) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["merging_vehicle"]['vehicles_type'] = type data["tracker_logging"] = True name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) data["reward"]["cooperative_flag"] = False data["reward"]["sympathy_flag"] = False data["observation"]["cooperative_perception"] = False info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_base " + \ " cooperative_flag " + str(data["reward"]["cooperative_flag"]) + \ " sympathy_flag " + str(data["reward"]["sympathy_flag"]) + \ " type= " + str(type) + " cooperative_perception " + str(data["observation"]["cooperative_perception"]) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["merging_vehicle"]['vehicles_type'] = type data["tracker_logging"] = True name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if ablation_action_history: for action_history_type in ["discrete", "xy_discrete", "binary"]: for action_history_count in [0, 2, 5, 10, 15]: data["observation"]["action_history_type"] = action_history_type data["observation"]["action_history_count"] = action_history_count info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_merge_300 " + \ " action_history_type " + str(data["observation"]["action_history_type"]) + \ " action_history_count " + str(data["observation"]["action_history_count"]) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if ablation_state_representation_f1: for mission_vehicle_observation in [True, False]: for features in [["presence", "x", "y", "vx", "vy", "is_controlled"], ["presence", "x", "y", "vx", "vy"], ["x", "y", "vx", "vy", "is_controlled"]]: for order in ["sorted", "sorted_by_id", "shuffled"]: # wrong shuffled sorted_by_x data["observation"]["mission_vehicle_observation"] = mission_vehicle_observation data["observation"]["features"] = features data["observation"]["order"] = order info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_merge_300 " + \ " mission_vehicle_observation " + str(data["observation"]["mission_vehicle_observation"]) + \ " features " + str(data["observation"]["features"]) + \ " order " + str(data["observation"]["order"]) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if ablation_state_representation_f2: for absolute in [True, False]: for see_behind in [True, False]: for normalize in [True, False]: for cooperative_perception in [True, False]: data["observation"]["absolute"] = absolute data["observation"]["see_behind"] = see_behind data["observation"]["normalize"] = normalize data["observation"]["cooperative_perception"] = cooperative_perception info = "exp_merge_" + str(start_num) + " similar to IEEE_Access/exp_merge_300 " + \ " absolute " + str(data["observation"]["absolute"]) + \ " see_behind " + str(data["observation"]["see_behind"]) + \ " normalize " + str(data["observation"]["normalize"]) + \ " cooperative_perception " + str(data["observation"]["cooperative_perception"]) data["additional_folder_name"] = "exp_merge_" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + "exp_merge_" + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) if state_representation_conv: base_config_folder = "configs/experiments/IROS/" for cruising_vehicles_front, lanes_count in [(False, 1), (False, 3), (True, 3)]: for base_config in ["exp_base_conv_multiagent_grid.json", "exp_base_conv_multiagent_heatmap.json", "exp_base_conv_multiagent_image.json"]: data["cruising_vehicles_front"] = cruising_vehicles_front data["cruising_vehicles_front_random_everywhere"] = cruising_vehicles_front data["lanes_count"] = lanes_count data["base_config"] = base_config_folder + base_config info = "exp_merge_" + str(start_num) + " similar to " + data["base_config"] + \ " cruising_vehicles_front " + str(data["cruising_vehicles_front"]) + \ " lanes_count " + str(data["lanes_count"]) data["additional_folder_name"] = "exp_merge_IROS" + str(start_num) data['info'] = info data["tracker_logging"] = True name = ini_folder + base_name_json + str(start_num) + '.json' start_num += 1 with open(name, 'w') as outfile: json.dump(data, outfile) print("End")

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templates/template.py

tildeSlashAi/nldenet

953f947bd82eb577fa44f7e86ca5b660c78f885e

[ "MIT" ]

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templates/template.py

tildeSlashAi/nldenet

953f947bd82eb577fa44f7e86ca5b660c78f885e

[ "MIT" ]

null

templates/template.py

tildeSlashAi/nldenet

953f947bd82eb577fa44f7e86ca5b660c78f885e

[ "MIT" ]

null

#!/usr/bin/env python # -*- coding: utf-8 -*- # ---------------------------------------------------- # (c) 2020 tildeSlashAi Team, All Rights Reserved. # Licensed under the MIT License # # tildeSlashAi Team: # - Dominique F. Garmier # ----------------------------------------------------

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