hexsha string | size int64 | ext string | lang string | max_stars_repo_path string | max_stars_repo_name string | max_stars_repo_head_hexsha string | max_stars_repo_licenses list | max_stars_count int64 | max_stars_repo_stars_event_min_datetime string | max_stars_repo_stars_event_max_datetime string | max_issues_repo_path string | max_issues_repo_name string | max_issues_repo_head_hexsha string | max_issues_repo_licenses list | max_issues_count int64 | max_issues_repo_issues_event_min_datetime string | max_issues_repo_issues_event_max_datetime string | max_forks_repo_path string | max_forks_repo_name string | max_forks_repo_head_hexsha string | max_forks_repo_licenses list | max_forks_count int64 | max_forks_repo_forks_event_min_datetime string | max_forks_repo_forks_event_max_datetime string | content string | avg_line_length float64 | max_line_length int64 | alphanum_fraction float64 | qsc_code_num_words_quality_signal int64 | qsc_code_num_chars_quality_signal float64 | qsc_code_mean_word_length_quality_signal float64 | qsc_code_frac_words_unique_quality_signal float64 | qsc_code_frac_chars_top_2grams_quality_signal float64 | qsc_code_frac_chars_top_3grams_quality_signal float64 | qsc_code_frac_chars_top_4grams_quality_signal float64 | qsc_code_frac_chars_dupe_5grams_quality_signal float64 | qsc_code_frac_chars_dupe_6grams_quality_signal float64 | qsc_code_frac_chars_dupe_7grams_quality_signal float64 | qsc_code_frac_chars_dupe_8grams_quality_signal float64 | qsc_code_frac_chars_dupe_9grams_quality_signal float64 | qsc_code_frac_chars_dupe_10grams_quality_signal float64 | qsc_code_frac_chars_replacement_symbols_quality_signal float64 | qsc_code_frac_chars_digital_quality_signal float64 | qsc_code_frac_chars_whitespace_quality_signal float64 | qsc_code_size_file_byte_quality_signal float64 | qsc_code_num_lines_quality_signal float64 | qsc_code_num_chars_line_max_quality_signal float64 | qsc_code_num_chars_line_mean_quality_signal float64 | qsc_code_frac_chars_alphabet_quality_signal float64 | qsc_code_frac_chars_comments_quality_signal float64 | qsc_code_cate_xml_start_quality_signal float64 | qsc_code_frac_lines_dupe_lines_quality_signal float64 | qsc_code_cate_autogen_quality_signal float64 | qsc_code_frac_lines_long_string_quality_signal float64 | qsc_code_frac_chars_string_length_quality_signal float64 | qsc_code_frac_chars_long_word_length_quality_signal float64 | qsc_code_frac_lines_string_concat_quality_signal float64 | qsc_code_cate_encoded_data_quality_signal float64 | qsc_code_frac_chars_hex_words_quality_signal float64 | qsc_code_frac_lines_prompt_comments_quality_signal float64 | qsc_code_frac_lines_assert_quality_signal float64 | qsc_codepython_cate_ast_quality_signal float64 | qsc_codepython_frac_lines_func_ratio_quality_signal float64 | qsc_codepython_cate_var_zero_quality_signal bool | qsc_codepython_frac_lines_pass_quality_signal float64 | qsc_codepython_frac_lines_import_quality_signal float64 | qsc_codepython_frac_lines_simplefunc_quality_signal float64 | qsc_codepython_score_lines_no_logic_quality_signal float64 | qsc_codepython_frac_lines_print_quality_signal float64 | qsc_code_num_words int64 | qsc_code_num_chars int64 | qsc_code_mean_word_length int64 | qsc_code_frac_words_unique null | qsc_code_frac_chars_top_2grams int64 | qsc_code_frac_chars_top_3grams int64 | qsc_code_frac_chars_top_4grams int64 | qsc_code_frac_chars_dupe_5grams int64 | qsc_code_frac_chars_dupe_6grams int64 | qsc_code_frac_chars_dupe_7grams int64 | qsc_code_frac_chars_dupe_8grams int64 | qsc_code_frac_chars_dupe_9grams int64 | qsc_code_frac_chars_dupe_10grams int64 | qsc_code_frac_chars_replacement_symbols int64 | qsc_code_frac_chars_digital int64 | qsc_code_frac_chars_whitespace int64 | qsc_code_size_file_byte int64 | qsc_code_num_lines int64 | qsc_code_num_chars_line_max int64 | qsc_code_num_chars_line_mean int64 | qsc_code_frac_chars_alphabet int64 | qsc_code_frac_chars_comments int64 | qsc_code_cate_xml_start int64 | qsc_code_frac_lines_dupe_lines int64 | qsc_code_cate_autogen int64 | qsc_code_frac_lines_long_string int64 | qsc_code_frac_chars_string_length int64 | qsc_code_frac_chars_long_word_length int64 | qsc_code_frac_lines_string_concat null | qsc_code_cate_encoded_data int64 | qsc_code_frac_chars_hex_words int64 | qsc_code_frac_lines_prompt_comments int64 | qsc_code_frac_lines_assert int64 | qsc_codepython_cate_ast int64 | qsc_codepython_frac_lines_func_ratio int64 | qsc_codepython_cate_var_zero int64 | qsc_codepython_frac_lines_pass int64 | qsc_codepython_frac_lines_import int64 | qsc_codepython_frac_lines_simplefunc int64 | qsc_codepython_score_lines_no_logic int64 | qsc_codepython_frac_lines_print int64 | effective string | hits int64 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
eb9fd0269907f86d115d62e0ea0520c852272710 | 249 | py | Python | source/tools/filetool.py | chopin1993/protocolmaster-20210731 | e23e235ee00b940a4161c606415574d2a52c701c | [
"Apache-2.0"
] | null | null | null | source/tools/filetool.py | chopin1993/protocolmaster-20210731 | e23e235ee00b940a4161c606415574d2a52c701c | [
"Apache-2.0"
] | null | null | null | source/tools/filetool.py | chopin1993/protocolmaster-20210731 | e23e235ee00b940a4161c606415574d2a52c701c | [
"Apache-2.0"
] | null | null | null | import os
def get_file_list(root, key=None):
files = os.listdir(root)
if key is not None:
files.sort(key=key)
return files
def get_config_file(name):
return os.path.join(os.path.dirname(__file__), ".." , "resource", name) | 20.75 | 75 | 0.658635 | 39 | 249 | 4 | 0.564103 | 0.076923 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.204819 | 249 | 12 | 75 | 20.75 | 0.787879 | 0 | 0 | 0 | 0 | 0 | 0.04 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.125 | 0.125 | 0.625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
eba40c7836d02b53113b113f1c42b28c5c259a93 | 404 | py | Python | twitoff/__init__.py | jeffyjkang/DS-Unit-3-Sprint-3-Productization-and-Cloud | d12952dd625c8d282db1946dd50c7f478e90dd7a | [
"MIT"
] | null | null | null | twitoff/__init__.py | jeffyjkang/DS-Unit-3-Sprint-3-Productization-and-Cloud | d12952dd625c8d282db1946dd50c7f478e90dd7a | [
"MIT"
] | null | null | null | twitoff/__init__.py | jeffyjkang/DS-Unit-3-Sprint-3-Productization-and-Cloud | d12952dd625c8d282db1946dd50c7f478e90dd7a | [
"MIT"
] | null | null | null | from .app import create_app
# APP = create_app()
# python commands:
# in app dir
#FLASKAPP=twitoff flask run
# in root dir
# FLASK_APP=twitoff flask shell
'''
Notes for setup:
in root, FLASK_APP=twitoff flask shell
import create_app
init create_app()
import DB
DB.create_all()
creates tables
'''
'''
Other commands
user1 = User.query.filter(User.name == 'nasa')
user1 = user1.one()
user1.tweets
''' | 14.428571 | 46 | 0.725248 | 62 | 404 | 4.612903 | 0.5 | 0.125874 | 0.104895 | 0.13986 | 0.174825 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01173 | 0.155941 | 404 | 28 | 47 | 14.428571 | 0.826979 | 0.282178 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
ebb439a6545138904530c4467b730cf8637621d9 | 391 | py | Python | utils/reduce_data.py | akshatabhat/transformers | 83c6f38b9bf1397f3d2c95c7b0ea8907f709c580 | [
"Apache-2.0"
] | 1 | 2021-03-26T14:06:52.000Z | 2021-03-26T14:06:52.000Z | utils/reduce_data.py | akshatabhat/transformers | 83c6f38b9bf1397f3d2c95c7b0ea8907f709c580 | [
"Apache-2.0"
] | null | null | null | utils/reduce_data.py | akshatabhat/transformers | 83c6f38b9bf1397f3d2c95c7b0ea8907f709c580 | [
"Apache-2.0"
] | null | null | null | import json
def main(file_path, out_len):
with open(file_path, 'r') as f:
data = json.loads(f.read())
print(len(data['data']))
data['data'] = data['data'][:out_len]
with open(file_path, 'w') as f:
print(len(data['data']))
json.dump(data, f)
if __name__ == "__main__":
main('data/train-v1.1.json', 10)
main('data/dev-v1.1.json', 2)
| 23 | 45 | 0.56266 | 62 | 391 | 3.33871 | 0.435484 | 0.231884 | 0.231884 | 0.231884 | 0.328502 | 0.21256 | 0 | 0 | 0 | 0 | 0 | 0.02349 | 0.237852 | 391 | 16 | 46 | 24.4375 | 0.671141 | 0 | 0 | 0.166667 | 0 | 0 | 0.163683 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.083333 | false | 0 | 0.083333 | 0 | 0.166667 | 0.166667 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
ebd48457bf3399a79fee4cd86c9c5e15db08cd7f | 235 | py | Python | Practice/Beginner/Hard Cash(CASH)/solution.py | DipanjanDasIT/CodeChefCodes | f3d6c9ee6598b1c873d614c4aff005c2971a4fc0 | [
"MIT"
] | null | null | null | Practice/Beginner/Hard Cash(CASH)/solution.py | DipanjanDasIT/CodeChefCodes | f3d6c9ee6598b1c873d614c4aff005c2971a4fc0 | [
"MIT"
] | null | null | null | Practice/Beginner/Hard Cash(CASH)/solution.py | DipanjanDasIT/CodeChefCodes | f3d6c9ee6598b1c873d614c4aff005c2971a4fc0 | [
"MIT"
] | null | null | null | testcases = int(input())
for _ in range(testcases):
main_details = list(map(int, input().split()))
coin_details = list(map(lambda x: int(x)%main_details[-1], input().split()))
print(sum(coin_details)%main_details[-1])
| 39.166667 | 81 | 0.659574 | 34 | 235 | 4.382353 | 0.5 | 0.221477 | 0.187919 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.01 | 0.148936 | 235 | 5 | 82 | 47 | 0.735 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.2 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
ccdce89434f75942295d9616fd82c9bb36f9f529 | 27 | py | Python | src/lib/Bcfg2/Server/Reports/reports/__init__.py | amplify-education/bcfg2 | 02d7f574babfeb2da99e2aad3a92b4e8d6494f07 | [
"mpich2"
] | null | null | null | src/lib/Bcfg2/Server/Reports/reports/__init__.py | amplify-education/bcfg2 | 02d7f574babfeb2da99e2aad3a92b4e8d6494f07 | [
"mpich2"
] | null | null | null | src/lib/Bcfg2/Server/Reports/reports/__init__.py | amplify-education/bcfg2 | 02d7f574babfeb2da99e2aad3a92b4e8d6494f07 | [
"mpich2"
] | null | null | null | __all__ = ['templatetags']
| 13.5 | 26 | 0.703704 | 2 | 27 | 7.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 27 | 1 | 27 | 27 | 0.625 | 0 | 0 | 0 | 0 | 0 | 0.444444 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
cce06a46f4f819aee94f70073960cb4bc2718754 | 76 | py | Python | config/prod.py | Cjwpython/WordlessBook | 3426ccf3ab2f8848caef98bbc7635407774d32b2 | [
"MIT"
] | 2 | 2021-05-19T10:53:25.000Z | 2022-01-20T01:20:08.000Z | config/prod.py | Cjwpython/WordlessBook | 3426ccf3ab2f8848caef98bbc7635407774d32b2 | [
"MIT"
] | null | null | null | config/prod.py | Cjwpython/WordlessBook | 3426ccf3ab2f8848caef98bbc7635407774d32b2 | [
"MIT"
] | 1 | 2022-01-20T01:19:56.000Z | 2022-01-20T01:19:56.000Z | # coding: utf-8
from config.base import *
DEBUG = False
SERVER_PORT = 8899
| 12.666667 | 25 | 0.723684 | 12 | 76 | 4.5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.080645 | 0.184211 | 76 | 5 | 26 | 15.2 | 0.790323 | 0.171053 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
ccfbcfc80bfd4176875b1439857777b6f9e25659 | 4,052 | py | Python | Day12/Part2.py | PeterDowdy/AdventOfCode2019 | 93078b5fc2ef78cdb1b860a3535839dc718c9f5f | [
"MIT"
] | null | null | null | Day12/Part2.py | PeterDowdy/AdventOfCode2019 | 93078b5fc2ef78cdb1b860a3535839dc718c9f5f | [
"MIT"
] | null | null | null | Day12/Part2.py | PeterDowdy/AdventOfCode2019 | 93078b5fc2ef78cdb1b860a3535839dc718c9f5f | [
"MIT"
] | null | null | null | from math import gcd
moons = [(-16, -1, -12), (0, -4, -17), (-11, 11, 0), (2, 2, -6)]
velocities = [(0,0,0),(0,0,0),(0,0,0),(0,0,0)]
x_positions = set()
y_positions = set()
z_positions = set()
x_positions.add((moons[0][0],moons[1][0],moons[2][0],moons[3][0],velocities[0][0],velocities[1][0],velocities[2][0],velocities[3][0]))
y_positions.add((moons[0][1],moons[1][1],moons[2][1],moons[3][1],velocities[0][1],velocities[1][2],velocities[2][1],velocities[3][1]))
z_positions.add((moons[0][2],moons[1][2],moons[2][2],moons[3][2],velocities[0][2],velocities[1][0],velocities[2][2],velocities[3][2]))
x_sequences = {(moons[0][0],moons[1][0],moons[2][0],moons[3][0],velocities[0][0],velocities[1][0],velocities[2][0],velocities[3][0]): 0}
y_sequences = {(moons[0][1],moons[1][1],moons[2][1],moons[3][1],velocities[0][1],velocities[1][1],velocities[2][1],velocities[3][1]): 0}
z_sequences = {(moons[0][2],moons[1][2],moons[2][2],moons[3][2],velocities[0][2],velocities[1][2],velocities[2][2],velocities[3][2]): 0}
ctr = 0
def step():
for i in range(0,4):
moon = moons[i]
gravity_delta = (sum([-1 if other_moon[0] < moon[0] else 1 if other_moon[0] > moon[0] else 0 for other_moon in moons]),
sum([-1 if other_moon[1] < moon[1] else 1 if other_moon[1] > moon[1] else 0 for other_moon in moons]),
sum([-1 if other_moon[2] < moon[2] else 1 if other_moon[2] > moon[2] else 0 for other_moon in moons])
)
velocity = velocities[i]
velocities[i] = (velocity[0]+gravity_delta[0],velocity[1]+gravity_delta[1],velocity[2]+gravity_delta[2])
for i in range(0,4):
moon = moons[i]
velocity = velocities[i]
moons[i] = (moon[0]+velocity[0],moon[1]+velocity[1],moon[2]+velocity[2])
x_cycle_length = 0
y_cycle_length = 0
z_cycle_length = 0
while True:
ctr += 1
step()
if (moons[0][0],moons[1][0],moons[2][0],moons[3][0],velocities[0][0],velocities[1][0],velocities[2][0],velocities[3][0]) in x_positions:
x_cycle_length = ctr-x_sequences[(moons[0][0],moons[1][0],moons[2][0],moons[3][0],velocities[0][0],velocities[1][0],velocities[2][0],velocities[3][0])]
pass
if (moons[0][1],moons[1][1],moons[2][1],moons[3][1],velocities[0][1],velocities[1][2],velocities[2][1],velocities[3][1]) in y_positions:
y_cycle_length = ctr-y_sequences[(moons[0][1],moons[1][1],moons[2][1],moons[3][1],velocities[0][1],velocities[1][2],velocities[2][1],velocities[3][1])]
pass
if (moons[0][2],moons[1][2],moons[2][2],moons[3][2],velocities[0][2],velocities[1][0],velocities[2][2],velocities[3][2]) in z_positions:
z_cycle_length = ctr-z_sequences[(moons[0][2],moons[1][2],moons[2][2],moons[3][2],velocities[0][2],velocities[1][0],velocities[2][2],velocities[3][2])]
pass
if x_cycle_length != 0 and y_cycle_length != 0 and z_cycle_length != 0:
break
x_positions.add((moons[0][0],moons[1][0],moons[2][0],moons[3][0],velocities[0][0],velocities[1][0],velocities[2][0],velocities[3][0]))
y_positions.add((moons[0][1],moons[1][1],moons[2][1],moons[3][1],velocities[0][1],velocities[1][2],velocities[2][1],velocities[3][1]))
z_positions.add((moons[0][2],moons[1][2],moons[2][2],moons[3][2],velocities[0][2],velocities[1][0],velocities[2][2],velocities[3][2]))
x_sequences[(moons[0][0],moons[1][0],moons[2][0],moons[3][0],velocities[0][0],velocities[1][0],velocities[2][0],velocities[3][0])] = ctr
y_sequences[(moons[0][1],moons[1][1],moons[2][1],moons[3][1],velocities[0][1],velocities[1][2],velocities[2][1],velocities[3][1])] = ctr
z_sequences[(moons[0][2],moons[1][2],moons[2][2],moons[3][2],velocities[0][2],velocities[1][0],velocities[2][2],velocities[3][2])] = ctr
print('Cycles found:')
print(f'x lasts {x_cycle_length}')
print(f'y lasts {y_cycle_length}')
print(f'z lasts {z_cycle_length}')
print((x_cycle_length,y_cycle_length,z_cycle_length))
def compute_lcm(x, y):
return (x*y)/gcd(x,y)
print(int(compute_lcm(x_cycle_length, int(compute_lcm(y_cycle_length, z_cycle_length)))))
| 57.070423 | 159 | 0.637957 | 764 | 4,052 | 3.287958 | 0.070681 | 0.12699 | 0.052548 | 0.096338 | 0.738057 | 0.736465 | 0.698248 | 0.690287 | 0.650478 | 0.632166 | 0 | 0.100773 | 0.10612 | 4,052 | 70 | 160 | 57.885714 | 0.592766 | 0 | 0 | 0.263158 | 0 | 0 | 0.020977 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.035088 | false | 0.052632 | 0.017544 | 0.017544 | 0.070175 | 0.105263 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
ccfc9563a897ecbadd4690eb294f53f692567173 | 1,834 | py | Python | 03/main.py | cjcbusatto/advent-of-code-2020 | 7868a6dfe9233809e47c27dd2afd2a287fbf4906 | [
"MIT"
] | null | null | null | 03/main.py | cjcbusatto/advent-of-code-2020 | 7868a6dfe9233809e47c27dd2afd2a287fbf4906 | [
"MIT"
] | null | null | null | 03/main.py | cjcbusatto/advent-of-code-2020 | 7868a6dfe9233809e47c27dd2afd2a287fbf4906 | [
"MIT"
] | null | null | null | def get_map_from_input(input_location):
f = open(input_location, 'r')
input_map = f.read().split('\n')
f.close()
lines = len(input_map)
columns = len(input_map[0])
print(f"Original map = {lines} x {columns}")
extended_map = []
for line in input_map:
extended_map.append(line * 200)
print(
f"Extended map = {str(len(extended_map))} x {str(len(extended_map[0]))}")
return extended_map
def traverse_map_counting_trees(extended_map, right, down):
squares = []
i = 0
j = 0
while i < len(extended_map):
if i == 0:
squares.append(extended_map[i][j])
else:
try:
squares.append(extended_map[i][(j * right)])
except:
print("Error")
break
i += down
j+= 1
tree_counter = 0
for char in squares:
if char == '#':
tree_counter += 1
return tree_counter
extended_map = get_map_from_input('input')
number_of_threes = traverse_map_counting_trees(extended_map, 1, 1)
print(f"1x1 => {number_of_threes}")
number_of_threes = traverse_map_counting_trees(extended_map, 3, 1)
print(f"3x1 => {number_of_threes}")
number_of_threes = traverse_map_counting_trees(extended_map, 5, 1)
print(f"5x1 => {number_of_threes}")
number_of_threes = traverse_map_counting_trees(extended_map, 7, 1)
print(f"7x1 => {number_of_threes}")
number_of_threes = traverse_map_counting_trees(extended_map, 1, 2)
print(f"1x2 => {number_of_threes}")
total = traverse_map_counting_trees(extended_map, 1, 1) * traverse_map_counting_trees(extended_map, 3, 1) * traverse_map_counting_trees(
extended_map, 5, 1) * traverse_map_counting_trees(extended_map, 7, 1) * traverse_map_counting_trees(extended_map, 1, 2)
print(f"Numbers multiplied = {total}") | 26.970588 | 136 | 0.657579 | 263 | 1,834 | 4.250951 | 0.235741 | 0.206619 | 0.186941 | 0.236136 | 0.567979 | 0.5322 | 0.454383 | 0.454383 | 0.315742 | 0.315742 | 0 | 0.028691 | 0.220829 | 1,834 | 68 | 137 | 26.970588 | 0.753674 | 0 | 0 | 0 | 0 | 0 | 0.147139 | 0.027793 | 0 | 0 | 0 | 0 | 0 | 1 | 0.042553 | false | 0 | 0 | 0 | 0.085106 | 0.191489 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
6917abd481963fb432ab3aee8ef82db2c9fb0a45 | 104 | py | Python | app/utils/Constants.py | jonzxz/project-piscator | 588c8b1ac9355f9a82ac449fdbeaa1ef7eb441ef | [
"MIT"
] | null | null | null | app/utils/Constants.py | jonzxz/project-piscator | 588c8b1ac9355f9a82ac449fdbeaa1ef7eb441ef | [
"MIT"
] | null | null | null | app/utils/Constants.py | jonzxz/project-piscator | 588c8b1ac9355f9a82ac449fdbeaa1ef7eb441ef | [
"MIT"
] | 1 | 2021-02-18T03:08:21.000Z | 2021-02-18T03:08:21.000Z | IMAP_GMAIL = 'imap.gmail.com'
IMAP_OUTLOOK = 'outlook.office365.com'
IMAP_YAHOO = 'imap.mail.yahoo.com'
| 26 | 38 | 0.759615 | 16 | 104 | 4.75 | 0.4375 | 0.236842 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.031579 | 0.086538 | 104 | 3 | 39 | 34.666667 | 0.768421 | 0 | 0 | 0 | 0 | 0 | 0.519231 | 0.201923 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
6929df2927459d70fbbc2605690e202e9fada472 | 649 | py | Python | MLGame/mlgame/crosslang/exceptions.py | Liuian/1092_INTRODUCTION-TO-MACHINE-LEARNING-AND-ITS-APPLICATION-TO-GAMING | f4a58d0d9f5832a77a4a86352e084065dc7bae50 | [
"MIT"
] | null | null | null | MLGame/mlgame/crosslang/exceptions.py | Liuian/1092_INTRODUCTION-TO-MACHINE-LEARNING-AND-ITS-APPLICATION-TO-GAMING | f4a58d0d9f5832a77a4a86352e084065dc7bae50 | [
"MIT"
] | null | null | null | MLGame/mlgame/crosslang/exceptions.py | Liuian/1092_INTRODUCTION-TO-MACHINE-LEARNING-AND-ITS-APPLICATION-TO-GAMING | f4a58d0d9f5832a77a4a86352e084065dc7bae50 | [
"MIT"
] | null | null | null | """
The exceptions for the crosslang module
"""
class CompilationError(Exception):
"""
Exception raised when failed to compile the user script
"""
def __init__(self, file, reason):
self.file = file
self.reason = reason
def __str__(self):
return "Failed to compile '{}':\n{}".format(self.file, self.reason)
class MLClientExecutionError(Exception):
"""
Exception raised when an error occurred while running non-python ml script
"""
def __init__(self, message):
"""
Constructor
"""
self.message = message
def __str__(self):
return self.message
| 23.178571 | 78 | 0.624037 | 71 | 649 | 5.478873 | 0.492958 | 0.061697 | 0.123393 | 0.143959 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.269646 | 649 | 27 | 79 | 24.037037 | 0.820675 | 0.280431 | 0 | 0.181818 | 0 | 0 | 0.066502 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.363636 | false | 0 | 0 | 0.181818 | 0.727273 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
693467a0acaed0c7690c50885524596a1996895e | 922 | py | Python | TERCEIRO MUNDO - THIRD WORLD/Um print especial - 97.py | MatheusKlebson/Python-Course | c1c5404095601733057bd91a96b5b4c45f0b5b9a | [
"MIT"
] | null | null | null | TERCEIRO MUNDO - THIRD WORLD/Um print especial - 97.py | MatheusKlebson/Python-Course | c1c5404095601733057bd91a96b5b4c45f0b5b9a | [
"MIT"
] | 1 | 2020-11-25T15:47:38.000Z | 2020-11-25T15:47:38.000Z | TERCEIRO MUNDO - THIRD WORLD/Um print especial - 97.py | MatheusKlebson/Python-Course | c1c5404095601733057bd91a96b5b4c45f0b5b9a | [
"MIT"
] | null | null | null | # Exercício Python 097: Faça um programa que tenha uma função chamada escreva(),
# que receba um texto qualquer como parâmetro e mostre uma mensagem com tamanho adaptável.
# Ex:
# escreva(‘Olá, Mundo!’) Saída:
# ~~~~~~~~~
# Olá, Mundo!
# ~~~~~~~~~
def write(text):
size = len(text) + 4
print("="*size)
print(f" {text}")
print("="*size)
write("HELLO WORLD")
write("I AM PROGRAMMER") | 61.466667 | 167 | 0.273319 | 54 | 922 | 4.666667 | 0.740741 | 0.063492 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012308 | 0.647505 | 922 | 15 | 168 | 61.466667 | 0.763077 | 0.817787 | 0 | 0.285714 | 0 | 0 | 0.226415 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0 | 0 | 0 | 0.142857 | 0.428571 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
6938f0e86ee3f8439ad8093f9adb38fd142480f6 | 1,366 | py | Python | ois_api_client/v2_0/dto/AdditionalQueryParams.py | peterkulik/ois_api_client | 51dabcc9f920f89982c4419bb058f5a88193cee0 | [
"MIT"
] | 7 | 2020-10-22T08:15:29.000Z | 2022-01-27T07:59:39.000Z | ois_api_client/v3_0/dto/AdditionalQueryParams.py | peterkulik/ois_api_client | 51dabcc9f920f89982c4419bb058f5a88193cee0 | [
"MIT"
] | null | null | null | ois_api_client/v3_0/dto/AdditionalQueryParams.py | peterkulik/ois_api_client | 51dabcc9f920f89982c4419bb058f5a88193cee0 | [
"MIT"
] | null | null | null | from typing import Optional
from dataclasses import dataclass
from .InvoiceAppearance import InvoiceAppearance
from .InvoiceCategory import InvoiceCategory
from .PaymentMethod import PaymentMethod
from .Source import Source
@dataclass
class AdditionalQueryParams:
"""Additional params of the invoice query
:param tax_number: Tax number of the supplier or the customer of the invoice (the search criteria depends on the value of the invoiceDirection tag)
:param group_member_tax_number: Tax number of group member of the supplier or the customer of the invoice (the search criteria depends on the value of the invoiceDirection tag)
:param name: Query param of the supplier or the customer of the invoice for leading match pattern (the search criteria depends on the value of the invoiceDirection tag)
:param invoice_category: Type of invoice
:param payment_method: Method of payment
:param invoice_appearance: Form of appearance of the invoice
:param source: Data exchange source
:param currency: Currency of the invoice
"""
tax_number: Optional[str]
group_member_tax_number: Optional[str]
name: Optional[str]
invoice_category: Optional[InvoiceCategory]
payment_method: Optional[PaymentMethod]
invoice_appearance: Optional[InvoiceAppearance]
source: Optional[Source]
currency: Optional[str]
| 44.064516 | 180 | 0.786237 | 179 | 1,366 | 5.921788 | 0.268156 | 0.056604 | 0.067925 | 0.042453 | 0.321698 | 0.285849 | 0.285849 | 0.285849 | 0.285849 | 0.25 | 0 | 0 | 0.171303 | 1,366 | 30 | 181 | 45.533333 | 0.936396 | 0.551245 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.375 | 0 | 0.9375 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
695785b2963244eb85ab885b374aa8c222d96191 | 98 | py | Python | ex.047.mostraNumerosPares.py | romulorm/cev-python | b5c6844956c131a9e4e02355459c218739ebf8c5 | [
"MIT"
] | null | null | null | ex.047.mostraNumerosPares.py | romulorm/cev-python | b5c6844956c131a9e4e02355459c218739ebf8c5 | [
"MIT"
] | null | null | null | ex.047.mostraNumerosPares.py | romulorm/cev-python | b5c6844956c131a9e4e02355459c218739ebf8c5 | [
"MIT"
] | null | null | null | # Conta somente números pares
for c in range(2, 51, 2):
print(c, end=' ')
print("Acabou!")
| 14 | 30 | 0.602041 | 16 | 98 | 3.6875 | 0.8125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.052632 | 0.22449 | 98 | 6 | 31 | 16.333333 | 0.723684 | 0.27551 | 0 | 0 | 0 | 0 | 0.119403 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.666667 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
c600a7c769c43dfaa68adc940ed5418cbaa4e03b | 121 | py | Python | treasureisland/Parameters.py | idoerg/GenomicIslandPrediction | c50edd0c280efca3fac90674a9695cb763c27e31 | [
"MIT"
] | null | null | null | treasureisland/Parameters.py | idoerg/GenomicIslandPrediction | c50edd0c280efca3fac90674a9695cb763c27e31 | [
"MIT"
] | null | null | null | treasureisland/Parameters.py | idoerg/GenomicIslandPrediction | c50edd0c280efca3fac90674a9695cb763c27e31 | [
"MIT"
] | null | null | null | WINDOW_SIZE = 8000
KMER_SIZE = 6
UPPER_THRESHOLD = 0.75
LOWER_THRESHOLD = 0.5
TUNE_METRIC = 1000
MINIMUM_GI_SIZE = 10000
| 17.285714 | 23 | 0.785124 | 21 | 121 | 4.190476 | 0.809524 | 0.227273 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.184466 | 0.14876 | 121 | 6 | 24 | 20.166667 | 0.669903 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
c61aff15e6261423fb5fd8677c7a2c1c475568d6 | 785 | py | Python | src/features/migrations/0025_enable_all_remote_config_feature_states.py | augustuswm/flagsmith-api | 6f37947fe3791726a92b4df2cdbded11e77387d3 | [
"BSD-3-Clause"
] | 1,259 | 2021-06-10T11:24:09.000Z | 2022-03-31T10:30:44.000Z | src/features/migrations/0025_enable_all_remote_config_feature_states.py | augustuswm/flagsmith-api | 6f37947fe3791726a92b4df2cdbded11e77387d3 | [
"BSD-3-Clause"
] | 392 | 2021-06-10T11:12:29.000Z | 2022-03-31T10:13:53.000Z | src/features/migrations/0025_enable_all_remote_config_feature_states.py | augustuswm/flagsmith-api | 6f37947fe3791726a92b4df2cdbded11e77387d3 | [
"BSD-3-Clause"
] | 58 | 2021-06-11T03:18:07.000Z | 2022-03-31T14:39:10.000Z | # Generated by Django 2.2.17 on 2021-01-10 12:35
from django.db import migrations
def enable_all_remote_config_feature_states(apps, schema_editor):
FeatureState = apps.get_model('features', 'FeatureState')
# update all existing remote config feature states to maintain current
# functionality when hiding disabled flags since we've now merged flags
# and remote config feature states.
FeatureState.objects.filter(feature__type="CONFIG").update(enabled=True)
def reverse(apps, schema_editor):
pass
class Migration(migrations.Migration):
dependencies = [
('features', '0024_auto_20200917_1032'),
]
operations = [
migrations.RunPython(
enable_all_remote_config_feature_states, reverse_code=reverse
)
]
| 26.166667 | 76 | 0.723567 | 96 | 785 | 5.71875 | 0.645833 | 0.087432 | 0.138434 | 0.182149 | 0.123862 | 0.123862 | 0 | 0 | 0 | 0 | 0 | 0.050713 | 0.196178 | 785 | 29 | 77 | 27.068966 | 0.819334 | 0.278981 | 0 | 0 | 1 | 0 | 0.101604 | 0.040998 | 0 | 0 | 0 | 0 | 0 | 1 | 0.133333 | false | 0.066667 | 0.066667 | 0 | 0.4 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
c61dc702b237c15662d2418ed34215b2b2a25a9f | 1,999 | py | Python | rolling/apply.py | andrewcfreeman/rolling | 7cff8e45bbebaf64a5da1ad6e7d1a7619eebca17 | [
"MIT"
] | 189 | 2018-03-12T00:31:19.000Z | 2022-03-26T00:17:38.000Z | rolling/apply.py | andrewcfreeman/rolling | 7cff8e45bbebaf64a5da1ad6e7d1a7619eebca17 | [
"MIT"
] | 23 | 2017-12-31T17:50:48.000Z | 2021-11-27T15:31:54.000Z | rolling/apply.py | andrewcfreeman/rolling | 7cff8e45bbebaf64a5da1ad6e7d1a7619eebca17 | [
"MIT"
] | 7 | 2019-01-28T02:53:49.000Z | 2021-11-11T18:34:45.000Z | from collections import deque
from itertools import islice
from .base import RollingObject
class Apply(RollingObject):
"""
Iterator object that applies a function to
a rolling window over a Python iterable.
Parameters
----------
iterable : any iterable object
window_size : integer, the size of the rolling
window moving over the iterable
operation : callable, default sum
a function, or class implementing a __call__
method, to be applied to each window
Complexity
----------
Update time: operation dependent
Memory usage: O(k)
where k is the size of the rolling window
Examples
--------
Rolling sum using builtin sum():
>>> import rolling
>>> seq = (8, 1, 1, 3, 6, 5)
>>> r_sum = rolling.Apply(seq, 3, operation=sum)
>>> next(r_sum)
10
>>> next(r_sum)
5
Reverse each window:
>>> r_rev = rolling.Apply(seq, 4, operation=lambda x: list(reversed(x)))
>>> list(r_rev)
[[3, 1, 1, 8],
[6, 3, 1, 1],
[5, 6, 3, 1]]
"""
def _init_fixed(self, iterable, window_size, operation=sum, **kwargs):
head = islice(self._iterator, window_size - 1)
self._buffer = deque(head, maxlen=window_size)
self._operation = operation
def _init_variable(self, iterable, window_size, operation=sum, **kwargs):
self._buffer = deque(maxlen=window_size)
self._operation = operation
@property
def current_value(self):
return self._operation(self._buffer)
def _add_new(self, new):
self._buffer.append(new)
def _remove_old(self):
self._buffer.popleft()
def _update_window(self, new):
self._buffer.append(new)
@property
def _obs(self):
return len(self._buffer)
def __repr__(self):
return "Rolling(operation='{}', window_size={}, window_type='{}')".format(
self._operation.__name__, self.window_size, self.window_type
)
| 24.084337 | 82 | 0.62031 | 253 | 1,999 | 4.699605 | 0.371542 | 0.067283 | 0.035324 | 0.020185 | 0.216989 | 0.216989 | 0.067283 | 0 | 0 | 0 | 0 | 0.016249 | 0.261131 | 1,999 | 82 | 83 | 24.378049 | 0.788761 | 0.405203 | 0 | 0.222222 | 0 | 0 | 0.054183 | 0.021863 | 0 | 0 | 0 | 0 | 0 | 1 | 0.296296 | false | 0 | 0.111111 | 0.111111 | 0.555556 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
c61e07f6e1d7dbddc3e330dbcdac65bf1c316ee7 | 2,166 | py | Python | src/dfd/models/interface.py | cicheck/dfd | b02752f958cfea2f85222e2b4b3ba7e265a6152d | [
"MIT"
] | null | null | null | src/dfd/models/interface.py | cicheck/dfd | b02752f958cfea2f85222e2b4b3ba7e265a6152d | [
"MIT"
] | 2 | 2021-12-31T17:44:20.000Z | 2021-12-31T19:51:11.000Z | src/dfd/models/interface.py | cicheck/dfd | b02752f958cfea2f85222e2b4b3ba7e265a6152d | [
"MIT"
] | null | null | null | from __future__ import annotations
import abc
import enum
import pathlib
import typing as t
class Prediction(enum.Enum):
"""Represents model prediction."""
def _generate_next_value_(name, start, count, last_values):
return name
REAL = enum.auto()
FAKE = enum.auto()
UNCERTAIN = enum.auto()
@classmethod
def from_confidence(cls, confidence: float, threshold: float = 0.5) -> Prediction:
"""Translate model confidence into prediction using given threshold.
Returns:
Model prediction over given threshold.
"""
if confidence >= threshold:
return cls.FAKE
if 1 - confidence >= threshold:
return cls.REAL
return cls.UNCERTAIN
class ModelInterface(abc.ABC):
"""Height level wrapper around actual models used underneath.
The goal of exposed interface is to hide implementation details such as what library
is used to define models. Currently interface operates on paths and handles only data
stored on disk.
"""
@abc.abstractmethod
def train(self, train_ds_path: pathlib.Path, validation_ds_path: pathlib.Path) -> None:
"""Train model using given train and validation data."""
@abc.abstractmethod
def test(self, test_ds_path: pathlib.Path) -> t.Dict[str, float]:
"""Evaluate model over provided test data.
Returns:
dict, metrics of interests mapped to their values
"""
@abc.abstractmethod
def predict(self, sample_path: pathlib.Path) -> t.Dict[pathlib.Path, Prediction]:
"""Make predictions over provided sample of frames."""
@abc.abstractmethod
def save(self, path: pathlib.Path):
"""Save model under given path."""
@classmethod
@abc.abstractmethod
def load(cls, path: pathlib.Path) -> ModelInterface:
"""Load model from given path."""
@abc.abstractmethod
def get_available_metrics_names(self) -> t.List[str]:
"""Get names of metrics supported by model.
Each metric value will be returned by train and test functions.
Returns: names of supported metrics
"""
| 27.769231 | 91 | 0.66205 | 262 | 2,166 | 5.396947 | 0.427481 | 0.054455 | 0.084866 | 0.036068 | 0.028289 | 0 | 0 | 0 | 0 | 0 | 0 | 0.001847 | 0.250231 | 2,166 | 77 | 92 | 28.12987 | 0.868842 | 0.368421 | 0 | 0.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.15625 | 0.03125 | 0.6875 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
c63aa739c17a4e754a25a2ea9c3f099089da52a6 | 350 | py | Python | __init__.py | LLNL/ferdinand | af47b415ea1e9cb21a45b20d1f3854bc7f3a4d70 | [
"Apache-2.0"
] | null | null | null | __init__.py | LLNL/ferdinand | af47b415ea1e9cb21a45b20d1f3854bc7f3a4d70 | [
"Apache-2.0"
] | null | null | null | __init__.py | LLNL/ferdinand | af47b415ea1e9cb21a45b20d1f3854bc7f3a4d70 | [
"Apache-2.0"
] | null | null | null | ##############################################
# #
# Ferdinand 0.40, Ian Thompson, LLNL #
# #
# gnd,endf,fresco,azure,hyrma #
# #
##############################################
__all__ = ["f90nml"]
| 38.888889 | 46 | 0.18 | 13 | 350 | 4.538462 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.028249 | 0.494286 | 350 | 8 | 47 | 43.75 | 0.305085 | 0.328571 | 0 | 0 | 0 | 0 | 0.214286 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
d660266eecc102047200d3452d83cf102a416710 | 497 | py | Python | manokee/timing/timing.py | smiszym/manokee | afb63b8ce5ba3f83bb924965b8d5098a6d28c474 | [
"MIT"
] | null | null | null | manokee/timing/timing.py | smiszym/manokee | afb63b8ce5ba3f83bb924965b8d5098a6d28c474 | [
"MIT"
] | 14 | 2021-03-11T02:05:20.000Z | 2022-03-12T01:05:11.000Z | manokee/timing/timing.py | smiszym/manokee | afb63b8ce5ba3f83bb924965b8d5098a6d28c474 | [
"MIT"
] | null | null | null | class Timing:
def beat_to_seconds(self, beat_number: float) -> float:
"""
Convert beat number to seconds.
:param beat_number: Beat number counted from 0.
:return: Time in seconds.
"""
raise NotImplementedError
def seconds_to_beat(self, time: float) -> float:
"""
Convert seconds to beat number.
:param time: Time in seconds.
:return: Beat number counted from 0.
"""
raise NotImplementedError
| 29.235294 | 59 | 0.597586 | 56 | 497 | 5.196429 | 0.339286 | 0.206186 | 0.116838 | 0.14433 | 0.151203 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005917 | 0.31992 | 497 | 16 | 60 | 31.0625 | 0.85503 | 0.410463 | 0 | 0.4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.4 | false | 0 | 0 | 0 | 0.6 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
d66748bfb42fb82f0c12adab0e031e9250276edd | 2,947 | py | Python | build/lib/WORC/featureprocessing/SelectIndividuals.py | Sikerdebaard/PREDICTFastr | e1f172c3606e6f33edf58008f958dcd1c0ac5b7b | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | build/lib/WORC/featureprocessing/SelectIndividuals.py | Sikerdebaard/PREDICTFastr | e1f172c3606e6f33edf58008f958dcd1c0ac5b7b | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | build/lib/WORC/featureprocessing/SelectIndividuals.py | Sikerdebaard/PREDICTFastr | e1f172c3606e6f33edf58008f958dcd1c0ac5b7b | [
"ECL-2.0",
"Apache-2.0"
] | null | null | null | #!/usr/bin/env python
# Copyright 2016-2019 Biomedical Imaging Group Rotterdam, Departments of
# Medical Informatics and Radiology, Erasmus MC, Rotterdam, The Netherlands
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from sklearn.base import BaseEstimator
from sklearn.feature_selection.base import SelectorMixin
import numpy as np
class SelectIndividuals(BaseEstimator, SelectorMixin):
'''
Object to fit feature selection based on the type group the feature belongs
to. The label for the feature is used for this procedure.
'''
def __init__(self, parameters=['hf_mean', 'sf_compactness']):
'''
Parameters
----------
parameters: dict, mandatory
Contains the settings for the groups to be selected. Should
contain the settings for the following groups:
- histogram_features
- shape_features
- orientation_features
- semantic_features
- patient_features
- coliage_features
- phase_features
- vessel_features
- log_features
- texture_features
'''
self.parameters = parameters
def fit(self, feature_labels):
'''
Select only features specificed by parameters per patient.
Parameters
----------
feature_labels: list, optional
Contains the labels of all features used. The index in this
list will be used in the transform funtion to select features.
'''
# Remove NAN
selectrows = list()
for num, l in enumerate(feature_labels):
if any(x in l for x in self.parameters):
selectrows.append(num)
self.selectrows = selectrows
def transform(self, inputarray):
'''
Transform the inputarray to select only the features based on the
result from the fit function.
Parameters
----------
inputarray: numpy array, mandatory
Array containing the items to use selection on. The type of
item in this list does not matter, e.g. floats, strings etc.
'''
return np.asarray([np.asarray(x)[self.selectrows].tolist() for x in inputarray])
def _get_support_mask(self):
# NOTE: Method is required for the Selector class, but can be empty
pass
| 35.506024 | 88 | 0.635562 | 350 | 2,947 | 5.285714 | 0.497143 | 0.032432 | 0.014054 | 0.017297 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005794 | 0.297251 | 2,947 | 82 | 89 | 35.939024 | 0.887494 | 0.638616 | 0 | 0 | 0 | 0 | 0.027668 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.0625 | 0.1875 | 0 | 0.5625 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
d6690698841bc39fcf328d809c1ae9a9943d7b0f | 1,279 | py | Python | src/entities/relativeentity.py | alisonbento/steering-all | 99797f99180dd64189ea5ed85ff71b66bfd9cf6f | [
"MIT"
] | 3 | 2016-10-10T18:34:55.000Z | 2017-08-02T15:18:28.000Z | src/entities/relativeentity.py | alisonbento/steering-all | 99797f99180dd64189ea5ed85ff71b66bfd9cf6f | [
"MIT"
] | null | null | null | src/entities/relativeentity.py | alisonbento/steering-all | 99797f99180dd64189ea5ed85ff71b66bfd9cf6f | [
"MIT"
] | null | null | null | from entity import Entity
class RelativeEntity(Entity):
def __init__(self, width, height):
Entity.__init__(self, width, height)
self.margin = [0, 0, 0, 0]
def below(self, entity):
self.y = entity.y + entity.height + self.margin[1]
def above(self, entity):
self.y = entity.y - self.height - self.margin[3]
def leftOf(self, entity):
self.x = entity.x - self.width - self.margin[2]
def rightOf(self, entity):
self.x = entity.x + entity.width + self.margin[0]
def margin(self, margin):
self.margin = margin;
def marginLeft(self, margin):
self.margin[0] = margin
def marginRight(self, margin):
self.margin[2] = margin
def marginTop(self, margin):
self.margin[1] = margin
def marginBottom(self, margin):
self.margin[3] = margin
def alignLeft(self):
self.x = 0 + self.margin[0]
def alignRight(self, width):
self.x = width - self.width - self.margin[2]
def alignTop(self):
self.y = 0 + self.margin[1]
def alignBottom(self, height):
self.y = height - self.height - self.margin[3]
def centerRelativeX(self, entity):
self.x = entity.x + (entity.width / 2) - (self.width / 2)
def centerRelativeY(self, entity):
self.y = entity.y + (entity.height / 2) - (self.height / 2)
| 22.839286 | 63 | 0.641908 | 184 | 1,279 | 4.418478 | 0.168478 | 0.233702 | 0.103321 | 0.123001 | 0.334563 | 0.334563 | 0.164822 | 0.164822 | 0 | 0 | 0 | 0.021825 | 0.211884 | 1,279 | 55 | 64 | 23.254545 | 0.784722 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.457143 | false | 0 | 0.028571 | 0 | 0.514286 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
d673caa4093bd3809cb0be9e8da138d53b90b322 | 3,860 | py | Python | test/domain_types/test_polygon.py | covjson/covjson-validator | 97b6ee445bfcc70ad73d731dce3d67aa4aafaf3a | [
"BSD-3-Clause"
] | null | null | null | test/domain_types/test_polygon.py | covjson/covjson-validator | 97b6ee445bfcc70ad73d731dce3d67aa4aafaf3a | [
"BSD-3-Clause"
] | 6 | 2022-02-02T16:52:33.000Z | 2022-02-09T09:40:50.000Z | test/domain_types/test_polygon.py | covjson/covjson-validator | 97b6ee445bfcc70ad73d731dce3d67aa4aafaf3a | [
"BSD-3-Clause"
] | null | null | null | # Pytests to test the Polygon domain type in the domain.json schema file
import pytest
from jsonschema.exceptions import ValidationError
pytestmark = pytest.mark.schema("/schemas/domain")
@pytest.mark.exhaustive
def test_valid_polygon_domain(validator, polygon_domain):
''' Tests an example of a Polygon domain '''
validator.validate(polygon_domain)
def test_missing_composite_axis(validator, polygon_domain):
''' Invalid: Polygon domain with missing 'composite' axis '''
del polygon_domain["axes"]["composite"]
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_empty_composite_axis(validator, polygon_domain):
''' Invalid: Polygon domain with empty 'composite' axis '''
polygon_domain["axes"]["composite"] = { "values" : [] }
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_wrong_composite_axis_type(validator, polygon_domain):
''' Invalid: Polygon domain with primitive instead of polygon axis '''
polygon_domain["axes"]["composite"] = {
"values": [1, 2, 3]
}
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_wrong_composite_axis_type2(validator, polygon_domain):
''' Invalid: Polygon domain with tuple instead of polygon axis (invalid polygons) '''
polygon_domain["axes"]["composite"]["values"] = [ [1, 1], [2, 2], [3, 3] ]
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_composite_axis_with_2_values(validator, polygon_domain):
''' Invalid: Polygon domain with composite axis with two polygons '''
polygon_domain["axes"]["composite"]["values"] = [
[ [ [100.0, 1.0], [101.0, 0.0], [101.0, 2.0], [100.0, 2.0], [100.0, 1.0] ] ],
[ [ [101.0, 1.0], [102.0, 0.0], [102.0, 2.0], [101.0, 2.0], [101.0, 1.0] ] ]
]
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_wrong_composite_axis_coordinates(validator, polygon_domain):
''' Invalid: Polygon domain with invalid coordinates '''
polygon_domain["axes"]["composite"]["coordinates"] = ["y", "x"]
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_wrong_data_type(validator, polygon_domain):
''' Invalid: Polygon domain with wrong data type '''
polygon_domain["axes"]["composite"]["dataType"] = "tuple"
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_extra_axis(validator, polygon_domain):
''' Invalid: Polygon domain with unrecognised extra axis '''
polygon_domain["axes"]["composite2"] = \
polygon_domain["axes"]["composite"]
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_empty_z_axis(validator, polygon_domain):
''' Invalid: Polygon domain with empty 'z' axis '''
polygon_domain["axes"]["z"] = { "values" : [] }
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_multivalued_z_axis(validator, polygon_domain):
''' Invalid: Polygon domain with multi-valued 'z' axis '''
polygon_domain["axes"]["z"] = { "values" : [1, 2] }
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_empty_t_axis(validator, polygon_domain):
''' Invalid: Polygon domain with empty 't' axis '''
polygon_domain["axes"]["t"] = { "values" : [] }
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
def test_multivalued_t_axis(validator, polygon_domain):
''' Invalid: Polygon domain with multi-valued 't' axis '''
polygon_domain["axes"]["t"] = { "values" : ["2008-01-01T04:00:00Z", "2008-01-01T05:00:00Z"] }
with pytest.raises(ValidationError):
validator.validate(polygon_domain)
| 33.275862 | 97 | 0.690933 | 464 | 3,860 | 5.571121 | 0.157328 | 0.271567 | 0.110638 | 0.15087 | 0.759381 | 0.747776 | 0.668472 | 0.574855 | 0.49323 | 0.401547 | 0 | 0.031796 | 0.168912 | 3,860 | 115 | 98 | 33.565217 | 0.774002 | 0.198705 | 0 | 0.416667 | 0 | 0 | 0.088587 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.216667 | false | 0 | 0.033333 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
d6812fee96c936a6d4abcdec5e68b3b5abdd5c3f | 409 | py | Python | api/core/models.py | vrmartins/poc-django-rest-framework | a4914c25c7decbe16f5233233e9da4dce57f64d8 | [
"MIT"
] | null | null | null | api/core/models.py | vrmartins/poc-django-rest-framework | a4914c25c7decbe16f5233233e9da4dce57f64d8 | [
"MIT"
] | 7 | 2020-04-05T14:25:37.000Z | 2021-09-22T18:50:16.000Z | api/core/models.py | vrmartins/poc-django-rest-framework | a4914c25c7decbe16f5233233e9da4dce57f64d8 | [
"MIT"
] | null | null | null | from django.db import models
from core.utils.cnpj_is_valid import cnpj_is_valid
class Customer(models.Model):
name = models.CharField(max_length=50, null=False, blank=False)
address = models.CharField(max_length=50, null=False, blank=False)
cnpj = models.CharField(max_length=14, unique=True, null=False, blank=False, validators=[cnpj_is_valid])
def __str__(self):
return self.name
| 34.083333 | 108 | 0.750611 | 61 | 409 | 4.819672 | 0.491803 | 0.061224 | 0.112245 | 0.244898 | 0.306122 | 0.306122 | 0.306122 | 0.306122 | 0.306122 | 0 | 0 | 0.017094 | 0.141809 | 409 | 11 | 109 | 37.181818 | 0.820513 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.125 | false | 0 | 0.25 | 0.125 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
d6876109b60f86d0c814c99a79b62726595f011e | 167 | py | Python | webapp/campaigns/urls.py | AKarbas/datachef-interview-assignment | 04a69a0daf0ab5378a2e03913ac60818e3fb73d9 | [
"Intel"
] | null | null | null | webapp/campaigns/urls.py | AKarbas/datachef-interview-assignment | 04a69a0daf0ab5378a2e03913ac60818e3fb73d9 | [
"Intel"
] | null | null | null | webapp/campaigns/urls.py | AKarbas/datachef-interview-assignment | 04a69a0daf0ab5378a2e03913ac60818e3fb73d9 | [
"Intel"
] | null | null | null | from django.urls import path
from . import views
app_name = 'campaigns'
urlpatterns = [
path('<int:campaign_id>/', views.Campaign.as_view(), name='campaign'),
]
| 18.555556 | 74 | 0.700599 | 22 | 167 | 5.181818 | 0.681818 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.143713 | 167 | 8 | 75 | 20.875 | 0.797203 | 0 | 0 | 0 | 0 | 0 | 0.209581 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
d687affcc64565d8faf1f33b4994b4b1b73c74f1 | 1,470 | py | Python | src/test/test_imperfect_indicitive.py | shrutiichandra/spanish-conjugator | 2ebf41b92c14c3e47a873c52fdf4ce1d17bff5e0 | [
"MIT"
] | null | null | null | src/test/test_imperfect_indicitive.py | shrutiichandra/spanish-conjugator | 2ebf41b92c14c3e47a873c52fdf4ce1d17bff5e0 | [
"MIT"
] | null | null | null | src/test/test_imperfect_indicitive.py | shrutiichandra/spanish-conjugator | 2ebf41b92c14c3e47a873c52fdf4ce1d17bff5e0 | [
"MIT"
] | null | null | null | # -*- coding: iso-8859-15 -*-
import spanishconjugator
from spanishconjugator.SpanishConjugator import Conjugator
# ----------------------------------- Imperfect Indicative ----------------------------------- #
def test_imperfect_indicative_yo_ar():
expected = "hablaba"
assert Conjugator().conjugate('hablar','imperfect','indicative','yo') == expected
def test_imperfect_indicative_tu_ar():
expected = "hablabas"
assert Conjugator().conjugate('hablar','imperfect','indicative','tu') == expected
def test_imperfect_indicative_usted_ar():
expected = "hablaba"
assert Conjugator().conjugate('hablar','imperfect','indicative','usted') == expected
def test_imperfect_indicative_nosotros_ar():
expected = 'hablábamos'
assert str(Conjugator().conjugate('hablar','imperfect','indicative','nosotros')) == expected
def test_imperfect_indicative_vosotros_ar():
expected = "hablabais"
assert Conjugator().conjugate('hablar','imperfect','indicative','vosotros') == expected
def test_imperfect_indicative_ustedes_ar():
expected = "hablaban"
assert Conjugator().conjugate('hablar','imperfect','indicative','ustedes') == expected
def test_imperfect_indicative_yo_ar_3():
expected = "charlaba"
assert Conjugator().conjugate('charlar','imperfect','indicative','yo') == expected
def test_imperfect_indicative_yo_ar_4():
expected = "era"
assert Conjugator().conjugate('ser','imperfect','indicative','yo') == expected | 39.72973 | 96 | 0.702041 | 144 | 1,470 | 6.930556 | 0.243056 | 0.323647 | 0.128257 | 0.208417 | 0.626253 | 0.445892 | 0.267535 | 0.225451 | 0.134269 | 0 | 0 | 0.006112 | 0.109524 | 1,470 | 37 | 97 | 39.72973 | 0.756303 | 0.081633 | 0 | 0.076923 | 0 | 0 | 0.218425 | 0 | 0 | 0 | 0 | 0 | 0.307692 | 1 | 0.307692 | false | 0 | 0.076923 | 0 | 0.384615 | 0 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
d68b45e4e7a07123f8215b18f29f9f415483134c | 219 | py | Python | list.py | TomckySan/python-training | 7d5214d01e8844a314d4a5aea6a4e35afa19f729 | [
"MIT"
] | null | null | null | list.py | TomckySan/python-training | 7d5214d01e8844a314d4a5aea6a4e35afa19f729 | [
"MIT"
] | null | null | null | list.py | TomckySan/python-training | 7d5214d01e8844a314d4a5aea6a4e35afa19f729 | [
"MIT"
] | null | null | null | # coding: utf-8
sales= [255, 100, 353, 400]
print len(sales)
print sales[2]
sales[2] = 100
print sales[2]
# 含んでいるか否か
print 100 in sales
print 500 in sales
# range
print range(10)
print range(3,10)
print range(3,10,2)
| 13.6875 | 27 | 0.69863 | 42 | 219 | 3.642857 | 0.404762 | 0.117647 | 0.143791 | 0.169935 | 0.183007 | 0 | 0 | 0 | 0 | 0 | 0 | 0.186813 | 0.16895 | 219 | 15 | 28 | 14.6 | 0.653846 | 0.127854 | 0 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.8 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
d6c44db13e9cf80092cf19bc3a381fd343fa5385 | 1,248 | py | Python | events/migrations/0049_auto_20210308_1449.py | horacexd/clist | 9759dfea97b86514bec9825d2430abc36decacf0 | [
"Apache-2.0"
] | 166 | 2019-05-16T23:46:08.000Z | 2022-03-31T05:20:23.000Z | events/migrations/0049_auto_20210308_1449.py | horacexd/clist | 9759dfea97b86514bec9825d2430abc36decacf0 | [
"Apache-2.0"
] | 92 | 2020-01-18T22:51:53.000Z | 2022-03-12T01:23:57.000Z | events/migrations/0049_auto_20210308_1449.py | VadVergasov/clist | 4afcdfe88250d224043b28efa511749347cec71c | [
"Apache-2.0"
] | 23 | 2020-02-09T17:38:43.000Z | 2021-12-09T14:39:07.000Z | # Generated by Django 3.1.7 on 2021-03-08 14:49
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('events', '0048_auto_20210307_1644'),
]
operations = [
migrations.AlterField(
model_name='event',
name='email_conf',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='event',
name='fields_info',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='event',
name='limits',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='event',
name='logins_paths',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='event',
name='standings_urls',
field=models.JSONField(blank=True, default=dict),
),
migrations.AlterField(
model_name='participant',
name='addition_fields',
field=models.JSONField(blank=True, default=dict),
),
]
| 28.363636 | 61 | 0.560897 | 118 | 1,248 | 5.813559 | 0.398305 | 0.174927 | 0.218659 | 0.253644 | 0.669096 | 0.669096 | 0.613703 | 0.555394 | 0.555394 | 0.555394 | 0 | 0.036643 | 0.322115 | 1,248 | 43 | 62 | 29.023256 | 0.774232 | 0.036058 | 0 | 0.621622 | 1 | 0 | 0.110741 | 0.019151 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.027027 | 0 | 0.108108 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
d6c7f2bc5030b6e6a1c3bad3cfc0eb72b6f4212f | 172 | py | Python | iex_parser_test/__init__.py | Cedric-Kram/iex_parser | b5aebe79b2125681ab0606f4f59ec325aadeebb9 | [
"Apache-2.0"
] | 15 | 2019-08-15T07:22:44.000Z | 2022-01-18T20:52:22.000Z | iex_parser_test/__init__.py | Cedric-Kram/iex_parser | b5aebe79b2125681ab0606f4f59ec325aadeebb9 | [
"Apache-2.0"
] | 5 | 2020-05-29T04:58:34.000Z | 2022-01-31T07:27:20.000Z | iex_parser_test/__init__.py | Cedric-Kram/iex_parser | b5aebe79b2125681ab0606f4f59ec325aadeebb9 | [
"Apache-2.0"
] | 4 | 2020-09-08T15:03:20.000Z | 2022-01-18T13:33:56.000Z | """iex_parser"""
from .parser import Parser
from .messages import DEEP_1_0, TOPS_1_6, TOPS_1_5
__all__ = [
'Parser',
'DEEP_1_0',
'TOPS_1_5',
'TOPS_1_6'
]
| 14.333333 | 50 | 0.645349 | 29 | 172 | 3.241379 | 0.413793 | 0.212766 | 0.12766 | 0.212766 | 0.234043 | 0 | 0 | 0 | 0 | 0 | 0 | 0.088889 | 0.215116 | 172 | 11 | 51 | 15.636364 | 0.607407 | 0.05814 | 0 | 0 | 0 | 0 | 0.192308 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 1 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
d6db1b844a289657730452a636a61c698c02aa89 | 1,117 | py | Python | varex/commons/VCFEntry.py | weiyi-bitw/varex | 765e8876c0ced480a47c0e523736bd31b7897644 | [
"MIT"
] | null | null | null | varex/commons/VCFEntry.py | weiyi-bitw/varex | 765e8876c0ced480a47c0e523736bd31b7897644 | [
"MIT"
] | null | null | null | varex/commons/VCFEntry.py | weiyi-bitw/varex | 765e8876c0ced480a47c0e523736bd31b7897644 | [
"MIT"
] | null | null | null |
class VCFEntry(object):
def __init__(self, vkey, ssid, pid, ac, passFilter=1, qual=-1, gq=-1, dp=-1, ad=-1):
self.vkey = vkey
if not ssid:
self.ssid = "UNKNOWN"
else:
self.ssid = ssid
self.pid = pid
self.ac = ac
self.passFilter = passFilter
self.qual = qual
self.gq = gq
self.dp = dp
self.ad = ad
def __repr__(self):
return "VCFEntry: (" + ', '.join([str(x) for x in [self.vkey, self.ssid, self.pid, self.ac, self.passFilter, self.qual, self.gq, self.dp, self.ad]]) + ")"
def __str__(self):
return '\t'.join([str(x) for x in [self.vkey, self.ssid, self.pid, self.ac, self.passFilter, self.qual, self.gq, self.dp, self.ad]])
def __eq__(self, other):
return (isinstance(other, self.__class__) and self.__dict__ == other.__dict__)
def __ne__(self, other):
return not self.__eq__(other)
def sameEntry(self, other):
return (isinstance(other, self.__class__) and self.vkey == other.vkey and self.ssid == other.ssid and self.pid == other.pid)
| 32.852941 | 162 | 0.584602 | 159 | 1,117 | 3.855346 | 0.220126 | 0.065253 | 0.053834 | 0.035889 | 0.430669 | 0.430669 | 0.430669 | 0.430669 | 0.430669 | 0.280587 | 0 | 0.00612 | 0.268577 | 1,117 | 33 | 163 | 33.848485 | 0.744186 | 0 | 0 | 0 | 0 | 0 | 0.020702 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.166667 | 0 | 0.208333 | 0.5 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 3 |
d6e6b0705f1fc5675687010c9694d9720c0c22e7 | 133 | py | Python | app/extensions.py | vatsalag99/mapping_self-harm_risk_twitter | 262c36f994c909714a738686b025633d832bc596 | [
"MIT"
] | null | null | null | app/extensions.py | vatsalag99/mapping_self-harm_risk_twitter | 262c36f994c909714a738686b025633d832bc596 | [
"MIT"
] | 1 | 2021-06-02T01:16:32.000Z | 2021-06-02T01:16:32.000Z | app/extensions.py | vatsalag99/mapping_self-harm_risk_twitter | 262c36f994c909714a738686b025633d832bc596 | [
"MIT"
] | null | null | null | """Extensions module - Set up for additional libraries can go in here."""
from flask_sqlalchemy import SQLAlchemy
db = SQLAlchemy() | 26.6 | 73 | 0.766917 | 18 | 133 | 5.611111 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.150376 | 133 | 5 | 74 | 26.6 | 0.893805 | 0.503759 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
ba334945cd720fa1ed44ce5324c0dde69e532940 | 5,765 | py | Python | src/pnmol/kernels.py | schmidtjonathan/pnmol-experiments | e07396079e2f2038011f3a377022482991090c5a | [
"MIT"
] | 1 | 2022-02-24T18:25:43.000Z | 2022-02-24T18:25:43.000Z | src/pnmol/kernels.py | schmidtjonathan/pnmol-experiments | e07396079e2f2038011f3a377022482991090c5a | [
"MIT"
] | null | null | null | src/pnmol/kernels.py | schmidtjonathan/pnmol-experiments | e07396079e2f2038011f3a377022482991090c5a | [
"MIT"
] | null | null | null | import abc
from functools import cached_property, partial
import jax
import jax.numpy as jnp
class Kernel(abc.ABC):
"""Covariance kernel interface."""
@abc.abstractmethod
def __call__(self, X, Y):
raise NotImplementedError
class _PairwiseKernel(Kernel):
@partial(jax.jit, static_argnums=(0,))
def __call__(self, X, Y):
# Single element of the Gram matrix:
# X.shape=(d,), Y.shape=(d,) -> K.shape = ()
if X.ndim == Y.ndim <= 1:
return self.pairwise(X, Y)
# Diagonal of the Gram matrix:
# X.shape=(N,d), Y.shape=(N,d) -> K.shape = (N,)
if X.shape == Y.shape:
return self._evaluate_inner(X, Y)
# Full Gram matrix:
# X.shape=[N,d), Y.shape=(d,K) -> K.shape = (N,K)
return self._evaluate_outer(X, Y)
@abc.abstractmethod
def pairwise(self, x, y):
raise NotImplementedError
@cached_property
def _evaluate_inner(self):
return jax.jit(jax.vmap(self.pairwise, (0, 0), 0))
@cached_property
def _evaluate_outer(self):
_pairwise_row = jax.jit(jax.vmap(self.pairwise, (0, None), 0))
return jax.jit(jax.vmap(_pairwise_row, (None, 1), 1))
def __str__(self):
return f"{self.__class__.__name__}()"
def __add__(self, other):
@jax.jit
def pairwise_new(x, y):
return self.pairwise(x, y) + other.pairwise(x, y)
return Lambda(pairwise_new)
class Lambda(_PairwiseKernel):
def __init__(self, fun, /):
self._lambda_fun = jax.jit(fun)
@partial(jax.jit, static_argnums=(0,))
def pairwise(self, x, y):
return self._lambda_fun(x, y)
class _RadialKernel(_PairwiseKernel):
r"""Radial kernels.
k(x,y) = output_scale * \varphi(\|x-y\|*input_scale)
"""
def __init__(
self,
*,
output_scale=1.0,
input_scale=1.0,
):
self._output_scale = output_scale
self._input_scale = input_scale
@property
def output_scale(self):
return self._output_scale
@property
def output_scale_squared(self):
return self.output_scale ** 2
@property
def input_scale(self):
return self._input_scale
@property
def input_scale_squared(self):
return self.input_scale ** 2
@abc.abstractmethod
def pairwise(self, X, Y):
raise NotImplementedError
@partial(jax.jit, static_argnums=0)
def _distance_squared_l2(self, X, Y):
return (X - Y).dot(X - Y)
class SquareExponential(_RadialKernel):
@partial(jax.jit, static_argnums=0)
def pairwise(self, x, y):
dist_squared = self._distance_squared_l2(x, y) * self.input_scale_squared
return self.output_scale_squared * jnp.exp(-dist_squared / 2.0)
class Matern52(_RadialKernel):
# Careful! Matern52 is not differentiable at x=y!
# Therefore, it is likely unusable for PNMOL...
@partial(jax.jit, static_argnums=(0,))
def pairwise(self, x, y):
dist_unscaled = self._distance_squared_l2(x, y)
dist_scaled = jnp.sqrt(5.0 * dist_unscaled * self.input_scale_squared)
A = 1 + dist_scaled + dist_scaled ** 2.0 / 3.0
B = jnp.exp(-dist_scaled)
return self.output_scale_squared * A * B
class Polynomial(_PairwiseKernel):
"""k(x,y) = (x.T @ y + c)^d"""
def __init__(self, *, order=2, const=1.0):
self._order = order
self._const = const
@property
def order(self):
return self._order
@property
def const(self):
return self._const
@partial(jax.jit, static_argnums=(0,))
def pairwise(self, x, y):
return (x.dot(y) + self.const) ** self.order
class WhiteNoise(_PairwiseKernel):
def __init__(self, *, output_scale=1.0):
self._output_scale = output_scale
@property
def output_scale(self):
return self._output_scale
@partial(jax.jit, static_argnums=(0,))
def pairwise(self, x, y):
return self.output_scale ** 2 * jnp.all(x == y)
class _StackedKernel(Kernel):
def __init__(self, *, kernel_list):
self.kernel_list = kernel_list
@partial(jax.jit, static_argnums=0)
def __call__(self, X, Y):
gram_matrix_list = [k(X, Y) for k in self.kernel_list]
# Diagonal of the Gram matrix:
# Concatenate the results together
if X.shape == Y.shape:
return jnp.concatenate(gram_matrix_list)
# Full Gram matrix:
# Block diag the gram matrix
return jax.scipy.linalg.block_diag(*gram_matrix_list)
def duplicate(kernel, num):
"""Create a stack of kernels such that the Gram matrix becomes block diagonal.
The blocks are all identical.
"""
return _StackedKernel(kernel_list=[kernel] * num)
def mle_input_scale(*, mesh_points, data, kernel_type, input_scale_trials):
scale_to_log_lklhd = partial(
input_scale_to_log_likelihood,
data=data,
kernel_type=kernel_type,
mesh_points=mesh_points,
)
scale_to_log_lklhd_optimised = jax.jit(jax.vmap(scale_to_log_lklhd))
log_likelihood_values = scale_to_log_lklhd_optimised(input_scale=input_scale_trials)
index_max = jnp.argmax(log_likelihood_values)
return input_scale_trials[index_max]
@partial(jax.jit, static_argnums=3)
def input_scale_to_log_likelihood(input_scale, mesh_points, data, kernel_type):
kernel = kernel_type(input_scale=input_scale)
K = kernel(mesh_points, mesh_points.T)
return log_likelihood(gram_matrix=K, y=data, n=data.shape[0])
@jax.jit
def log_likelihood(gram_matrix, y, n):
a = y @ jnp.linalg.solve(gram_matrix, y)
b = jnp.log(jnp.linalg.det(gram_matrix))
c = n * jnp.log(2 * jnp.pi)
return -0.5 * (a + b + c)
| 27.193396 | 88 | 0.640937 | 802 | 5,765 | 4.337905 | 0.174564 | 0.016097 | 0.018971 | 0.049152 | 0.425122 | 0.28399 | 0.245473 | 0.190572 | 0.159241 | 0.125898 | 0 | 0.01118 | 0.239722 | 5,765 | 211 | 89 | 27.322275 | 0.782569 | 0.113096 | 0 | 0.311111 | 0 | 0 | 0.005333 | 0.005333 | 0 | 0 | 0 | 0 | 0 | 1 | 0.237037 | false | 0 | 0.02963 | 0.103704 | 0.533333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
ba3dee974a940c282171ed9e43e895bc5c1ce3fc | 370 | py | Python | mjpoll/__init__.py | DarkWizarD24/mjpoll | 877eb45ca713a2e03a84deff4765f282b870e635 | [
"MIT"
] | null | null | null | mjpoll/__init__.py | DarkWizarD24/mjpoll | 877eb45ca713a2e03a84deff4765f282b870e635 | [
"MIT"
] | null | null | null | mjpoll/__init__.py | DarkWizarD24/mjpoll | 877eb45ca713a2e03a84deff4765f282b870e635 | [
"MIT"
] | null | null | null | # coding: utf-8
from flask import Flask
from flask_babel import Babel
from flask_bootstrap import Bootstrap
app = Flask(__name__)
app.config.from_pyfile('application.cfg')
app.secret_key = '_\xeb\xaa9\xea\xb9&\xe8\xdfx\xd4oKu\x01\xf3\x94d\x08\xdeGs\x11<' #TODO get if from config
babel = Babel(app)
Bootstrap(app)
import views
import data
from data import init_db
| 19.473684 | 107 | 0.775676 | 61 | 370 | 4.540984 | 0.590164 | 0.097473 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.043077 | 0.121622 | 370 | 18 | 108 | 20.555556 | 0.809231 | 0.097297 | 0 | 0 | 0 | 0.090909 | 0.23565 | 0.190332 | 0 | 0 | 0 | 0.055556 | 0 | 1 | 0 | false | 0 | 0.545455 | 0 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
ba47aae912bab03eeec32d53c9d7b3b8de1668c7 | 54,161 | py | Python | rubikscolorresolver/cube_555.py | jmsutariya/cube-tracker | 2296d68883acbd3430110318420d09f98c186e91 | [
"MIT"
] | 29 | 2017-03-03T23:47:53.000Z | 2021-12-20T19:43:35.000Z | rubikscolorresolver/cube_555.py | jmsutariya/cube-tracker | 2296d68883acbd3430110318420d09f98c186e91 | [
"MIT"
] | 6 | 2017-03-12T05:25:27.000Z | 2022-03-27T08:20:25.000Z | rubikscolorresolver/cube_555.py | jmsutariya/cube-tracker | 2296d68883acbd3430110318420d09f98c186e91 | [
"MIT"
] | 18 | 2017-08-31T13:28:58.000Z | 2021-12-20T19:43:09.000Z | corner_tuples = (
(1, 26, 105),
(5, 101, 80),
(21, 51, 30),
(25, 76, 55),
(126, 50, 71),
(130, 75, 96),
(146, 125, 46),
(150, 100, 121),
)
edge_orbit_id = {
2: 0,
3: 1,
4: 0,
6: 0,
11: 1,
16: 0,
10: 0,
15: 1,
20: 0,
22: 0,
23: 1,
24: 0, # Upper
27: 0,
28: 1,
29: 0,
31: 0,
36: 1,
41: 0,
35: 0,
40: 1,
45: 0,
47: 0,
48: 1,
49: 0, # Left
52: 0,
53: 1,
54: 0,
56: 0,
61: 1,
66: 0,
60: 0,
65: 1,
70: 0,
72: 0,
73: 1,
74: 0, # Front
77: 0,
78: 1,
79: 0,
81: 0,
86: 1,
91: 0,
85: 0,
90: 1,
95: 0,
97: 0,
98: 1,
99: 0, # Right
102: 0,
103: 1,
104: 0,
106: 0,
111: 1,
116: 0,
110: 0,
115: 1,
120: 0,
122: 0,
123: 1,
124: 0, # Back
127: 0,
128: 1,
129: 0,
131: 0,
136: 1,
141: 0,
135: 0,
140: 1,
145: 0,
147: 0,
148: 1,
149: 0, # Down
}
edge_orbit_wing_pairs = (
# orbit 0
(
(2, 104),
(4, 102),
(6, 27),
(16, 29),
(10, 79),
(20, 77),
(22, 52),
(24, 54),
(31, 110),
(41, 120),
(35, 56),
(45, 66),
(81, 60),
(91, 70),
(85, 106),
(95, 116),
(72, 127),
(74, 129),
(131, 49),
(141, 47),
(135, 97),
(145, 99),
(147, 124),
(149, 122),
),
# orbit 1
(
(3, 103),
(11, 28),
(15, 78),
(23, 53),
(36, 115),
(40, 61),
(86, 65),
(90, 111),
(128, 73),
(136, 48),
(140, 98),
(148, 123),
),
)
center_groups = (
("centers", (13, 38, 63, 88, 113, 138)),
(
"x-centers",
(
7,
9,
13,
17,
19, # Upper
32,
34,
38,
42,
44, # Left
57,
59,
63,
67,
69, # Front
82,
84,
88,
92,
94, # Right
107,
109,
113,
117,
119, # Back
132,
134,
138,
142,
144, # Down
),
),
(
"t-centers",
(
8,
12,
13,
14,
18, # Upper
33,
37,
38,
39,
43, # Left
58,
62,
63,
64,
68, # Front
83,
87,
88,
89,
93, # Right
108,
112,
113,
114,
118, # Back
133,
137,
138,
139,
143, # Down
),
),
)
highlow_edge_values = {
(2, 104, "B", "D"): "D",
(2, 104, "B", "L"): "D",
(2, 104, "B", "R"): "D",
(2, 104, "B", "U"): "D",
(2, 104, "D", "B"): "U",
(2, 104, "D", "F"): "U",
(2, 104, "D", "L"): "U",
(2, 104, "D", "R"): "U",
(2, 104, "F", "D"): "D",
(2, 104, "F", "L"): "D",
(2, 104, "F", "R"): "D",
(2, 104, "F", "U"): "D",
(2, 104, "L", "B"): "U",
(2, 104, "L", "D"): "D",
(2, 104, "L", "F"): "U",
(2, 104, "L", "U"): "D",
(2, 104, "R", "B"): "U",
(2, 104, "R", "D"): "D",
(2, 104, "R", "F"): "U",
(2, 104, "R", "U"): "D",
(2, 104, "U", "B"): "U",
(2, 104, "U", "F"): "U",
(2, 104, "U", "L"): "U",
(2, 104, "U", "R"): "U",
(3, 103, "B", "D"): "D",
(3, 103, "B", "L"): "D",
(3, 103, "B", "R"): "D",
(3, 103, "B", "U"): "D",
(3, 103, "D", "B"): "U",
(3, 103, "D", "F"): "U",
(3, 103, "D", "L"): "U",
(3, 103, "D", "R"): "U",
(3, 103, "F", "D"): "D",
(3, 103, "F", "L"): "D",
(3, 103, "F", "R"): "D",
(3, 103, "F", "U"): "D",
(3, 103, "L", "B"): "U",
(3, 103, "L", "D"): "D",
(3, 103, "L", "F"): "U",
(3, 103, "L", "U"): "D",
(3, 103, "R", "B"): "U",
(3, 103, "R", "D"): "D",
(3, 103, "R", "F"): "U",
(3, 103, "R", "U"): "D",
(3, 103, "U", "B"): "U",
(3, 103, "U", "F"): "U",
(3, 103, "U", "L"): "U",
(3, 103, "U", "R"): "U",
(4, 102, "B", "D"): "U",
(4, 102, "B", "L"): "U",
(4, 102, "B", "R"): "U",
(4, 102, "B", "U"): "U",
(4, 102, "D", "B"): "D",
(4, 102, "D", "F"): "D",
(4, 102, "D", "L"): "D",
(4, 102, "D", "R"): "D",
(4, 102, "F", "D"): "U",
(4, 102, "F", "L"): "U",
(4, 102, "F", "R"): "U",
(4, 102, "F", "U"): "U",
(4, 102, "L", "B"): "D",
(4, 102, "L", "D"): "U",
(4, 102, "L", "F"): "D",
(4, 102, "L", "U"): "U",
(4, 102, "R", "B"): "D",
(4, 102, "R", "D"): "U",
(4, 102, "R", "F"): "D",
(4, 102, "R", "U"): "U",
(4, 102, "U", "B"): "D",
(4, 102, "U", "F"): "D",
(4, 102, "U", "L"): "D",
(4, 102, "U", "R"): "D",
(6, 27, "B", "D"): "U",
(6, 27, "B", "L"): "U",
(6, 27, "B", "R"): "U",
(6, 27, "B", "U"): "U",
(6, 27, "D", "B"): "D",
(6, 27, "D", "F"): "D",
(6, 27, "D", "L"): "D",
(6, 27, "D", "R"): "D",
(6, 27, "F", "D"): "U",
(6, 27, "F", "L"): "U",
(6, 27, "F", "R"): "U",
(6, 27, "F", "U"): "U",
(6, 27, "L", "B"): "D",
(6, 27, "L", "D"): "U",
(6, 27, "L", "F"): "D",
(6, 27, "L", "U"): "U",
(6, 27, "R", "B"): "D",
(6, 27, "R", "D"): "U",
(6, 27, "R", "F"): "D",
(6, 27, "R", "U"): "U",
(6, 27, "U", "B"): "D",
(6, 27, "U", "F"): "D",
(6, 27, "U", "L"): "D",
(6, 27, "U", "R"): "D",
(10, 79, "B", "D"): "D",
(10, 79, "B", "L"): "D",
(10, 79, "B", "R"): "D",
(10, 79, "B", "U"): "D",
(10, 79, "D", "B"): "U",
(10, 79, "D", "F"): "U",
(10, 79, "D", "L"): "U",
(10, 79, "D", "R"): "U",
(10, 79, "F", "D"): "D",
(10, 79, "F", "L"): "D",
(10, 79, "F", "R"): "D",
(10, 79, "F", "U"): "D",
(10, 79, "L", "B"): "U",
(10, 79, "L", "D"): "D",
(10, 79, "L", "F"): "U",
(10, 79, "L", "U"): "D",
(10, 79, "R", "B"): "U",
(10, 79, "R", "D"): "D",
(10, 79, "R", "F"): "U",
(10, 79, "R", "U"): "D",
(10, 79, "U", "B"): "U",
(10, 79, "U", "F"): "U",
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(135, 97, "R", "D"): "D",
(135, 97, "R", "F"): "U",
(135, 97, "R", "U"): "D",
(135, 97, "U", "B"): "U",
(135, 97, "U", "F"): "U",
(135, 97, "U", "L"): "U",
(135, 97, "U", "R"): "U",
(136, 48, "B", "D"): "D",
(136, 48, "B", "L"): "D",
(136, 48, "B", "R"): "D",
(136, 48, "B", "U"): "D",
(136, 48, "D", "B"): "U",
(136, 48, "D", "F"): "U",
(136, 48, "D", "L"): "U",
(136, 48, "D", "R"): "U",
(136, 48, "F", "D"): "D",
(136, 48, "F", "L"): "D",
(136, 48, "F", "R"): "D",
(136, 48, "F", "U"): "D",
(136, 48, "L", "B"): "U",
(136, 48, "L", "D"): "D",
(136, 48, "L", "F"): "U",
(136, 48, "L", "U"): "D",
(136, 48, "R", "B"): "U",
(136, 48, "R", "D"): "D",
(136, 48, "R", "F"): "U",
(136, 48, "R", "U"): "D",
(136, 48, "U", "B"): "U",
(136, 48, "U", "F"): "U",
(136, 48, "U", "L"): "U",
(136, 48, "U", "R"): "U",
(140, 98, "B", "D"): "D",
(140, 98, "B", "L"): "D",
(140, 98, "B", "R"): "D",
(140, 98, "B", "U"): "D",
(140, 98, "D", "B"): "U",
(140, 98, "D", "F"): "U",
(140, 98, "D", "L"): "U",
(140, 98, "D", "R"): "U",
(140, 98, "F", "D"): "D",
(140, 98, "F", "L"): "D",
(140, 98, "F", "R"): "D",
(140, 98, "F", "U"): "D",
(140, 98, "L", "B"): "U",
(140, 98, "L", "D"): "D",
(140, 98, "L", "F"): "U",
(140, 98, "L", "U"): "D",
(140, 98, "R", "B"): "U",
(140, 98, "R", "D"): "D",
(140, 98, "R", "F"): "U",
(140, 98, "R", "U"): "D",
(140, 98, "U", "B"): "U",
(140, 98, "U", "F"): "U",
(140, 98, "U", "L"): "U",
(140, 98, "U", "R"): "U",
(141, 47, "B", "D"): "D",
(141, 47, "B", "L"): "D",
(141, 47, "B", "R"): "D",
(141, 47, "B", "U"): "D",
(141, 47, "D", "B"): "U",
(141, 47, "D", "F"): "U",
(141, 47, "D", "L"): "U",
(141, 47, "D", "R"): "U",
(141, 47, "F", "D"): "D",
(141, 47, "F", "L"): "D",
(141, 47, "F", "R"): "D",
(141, 47, "F", "U"): "D",
(141, 47, "L", "B"): "U",
(141, 47, "L", "D"): "D",
(141, 47, "L", "F"): "U",
(141, 47, "L", "U"): "D",
(141, 47, "R", "B"): "U",
(141, 47, "R", "D"): "D",
(141, 47, "R", "F"): "U",
(141, 47, "R", "U"): "D",
(141, 47, "U", "B"): "U",
(141, 47, "U", "F"): "U",
(141, 47, "U", "L"): "U",
(141, 47, "U", "R"): "U",
(145, 99, "B", "D"): "U",
(145, 99, "B", "L"): "U",
(145, 99, "B", "R"): "U",
(145, 99, "B", "U"): "U",
(145, 99, "D", "B"): "D",
(145, 99, "D", "F"): "D",
(145, 99, "D", "L"): "D",
(145, 99, "D", "R"): "D",
(145, 99, "F", "D"): "U",
(145, 99, "F", "L"): "U",
(145, 99, "F", "R"): "U",
(145, 99, "F", "U"): "U",
(145, 99, "L", "B"): "D",
(145, 99, "L", "D"): "U",
(145, 99, "L", "F"): "D",
(145, 99, "L", "U"): "U",
(145, 99, "R", "B"): "D",
(145, 99, "R", "D"): "U",
(145, 99, "R", "F"): "D",
(145, 99, "R", "U"): "U",
(145, 99, "U", "B"): "D",
(145, 99, "U", "F"): "D",
(145, 99, "U", "L"): "D",
(145, 99, "U", "R"): "D",
(147, 124, "B", "D"): "U",
(147, 124, "B", "L"): "U",
(147, 124, "B", "R"): "U",
(147, 124, "B", "U"): "U",
(147, 124, "D", "B"): "D",
(147, 124, "D", "F"): "D",
(147, 124, "D", "L"): "D",
(147, 124, "D", "R"): "D",
(147, 124, "F", "D"): "U",
(147, 124, "F", "L"): "U",
(147, 124, "F", "R"): "U",
(147, 124, "F", "U"): "U",
(147, 124, "L", "B"): "D",
(147, 124, "L", "D"): "U",
(147, 124, "L", "F"): "D",
(147, 124, "L", "U"): "U",
(147, 124, "R", "B"): "D",
(147, 124, "R", "D"): "U",
(147, 124, "R", "F"): "D",
(147, 124, "R", "U"): "U",
(147, 124, "U", "B"): "D",
(147, 124, "U", "F"): "D",
(147, 124, "U", "L"): "D",
(147, 124, "U", "R"): "D",
(148, 123, "B", "D"): "D",
(148, 123, "B", "L"): "D",
(148, 123, "B", "R"): "D",
(148, 123, "B", "U"): "D",
(148, 123, "D", "B"): "U",
(148, 123, "D", "F"): "U",
(148, 123, "D", "L"): "U",
(148, 123, "D", "R"): "U",
(148, 123, "F", "D"): "D",
(148, 123, "F", "L"): "D",
(148, 123, "F", "R"): "D",
(148, 123, "F", "U"): "D",
(148, 123, "L", "B"): "U",
(148, 123, "L", "D"): "D",
(148, 123, "L", "F"): "U",
(148, 123, "L", "U"): "D",
(148, 123, "R", "B"): "U",
(148, 123, "R", "D"): "D",
(148, 123, "R", "F"): "U",
(148, 123, "R", "U"): "D",
(148, 123, "U", "B"): "U",
(148, 123, "U", "F"): "U",
(148, 123, "U", "L"): "U",
(148, 123, "U", "R"): "U",
(149, 122, "B", "D"): "D",
(149, 122, "B", "L"): "D",
(149, 122, "B", "R"): "D",
(149, 122, "B", "U"): "D",
(149, 122, "D", "B"): "U",
(149, 122, "D", "F"): "U",
(149, 122, "D", "L"): "U",
(149, 122, "D", "R"): "U",
(149, 122, "F", "D"): "D",
(149, 122, "F", "L"): "D",
(149, 122, "F", "R"): "D",
(149, 122, "F", "U"): "D",
(149, 122, "L", "B"): "U",
(149, 122, "L", "D"): "D",
(149, 122, "L", "F"): "U",
(149, 122, "L", "U"): "D",
(149, 122, "R", "B"): "U",
(149, 122, "R", "D"): "D",
(149, 122, "R", "F"): "U",
(149, 122, "R", "U"): "D",
(149, 122, "U", "B"): "U",
(149, 122, "U", "F"): "U",
(149, 122, "U", "L"): "U",
(149, 122, "U", "R"): "U",
}
| 27.96128 | 44 | 0.255848 | 8,987 | 54,161 | 1.540892 | 0.019695 | 0.031196 | 0.007799 | 0.001733 | 0.030618 | 0 | 0 | 0 | 0 | 0 | 0 | 0.230541 | 0.320858 | 54,161 | 1,936 | 45 | 27.975723 | 0.145937 | 0.002105 | 0 | 0.009331 | 0 | 0 | 0.096417 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
ba77c3decd45da528d69e289a995dee1a225f06b | 651 | py | Python | Exercicios/ex109 - Formatando moedas em python.py | anderdot/curso-em-video-python | ea295cf0afa914ff9ab9acb87c458d77e3fb62ad | [
"MIT"
] | null | null | null | Exercicios/ex109 - Formatando moedas em python.py | anderdot/curso-em-video-python | ea295cf0afa914ff9ab9acb87c458d77e3fb62ad | [
"MIT"
] | null | null | null | Exercicios/ex109 - Formatando moedas em python.py | anderdot/curso-em-video-python | ea295cf0afa914ff9ab9acb87c458d77e3fb62ad | [
"MIT"
] | null | null | null | # Desafio 109: Modifique as funções que form criadas no desafio 107 para que
# elas aceitem um parâmetro a mais, informando se o valor retornado por elas
# vai ser ou não formatado pela função moeda(), desenvolvida no desafio 108.
from rotinas import titulo
from modulos.ex109 import moeda as m
valor = int(input('Digite um valor: R$ '))
titulo('Análise', 50)
print(f'A metade de {m.moeda(valor)} é {m.metade(valor, True)}.')
print(f'O dobro de {m.moeda(valor)} é {m.dobro(valor, True)}.')
print(f'A taxa de 10% de {m.moeda(valor)} é {m.aumentar(valor, 10, True)}.')
print(f'O desconto de 15% de {m.moeda(valor)} é {m.diminuir(valor, 15, True)}.')
| 50.076923 | 80 | 0.709677 | 117 | 651 | 3.948718 | 0.504274 | 0.051948 | 0.069264 | 0.112554 | 0.12987 | 0.12987 | 0 | 0 | 0 | 0 | 0 | 0.039711 | 0.149002 | 651 | 12 | 81 | 54.25 | 0.794224 | 0.347158 | 0 | 0 | 0 | 0.25 | 0.643705 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0.5 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
ba7d6a9e7d22a756e68ebfce9d1c8d488b047ed1 | 222 | py | Python | String/058. Length of Last Word.py | beckswu/Leetcode | 480e8dc276b1f65961166d66efa5497d7ff0bdfd | [
"MIT"
] | 138 | 2020-02-08T05:25:26.000Z | 2021-11-04T11:59:28.000Z | String/058. Length of Last Word.py | beckswu/Leetcode | 480e8dc276b1f65961166d66efa5497d7ff0bdfd | [
"MIT"
] | null | null | null | String/058. Length of Last Word.py | beckswu/Leetcode | 480e8dc276b1f65961166d66efa5497d7ff0bdfd | [
"MIT"
] | 24 | 2021-01-02T07:18:43.000Z | 2022-03-20T08:17:54.000Z | """
58. Length of Last Word
"""
class Solution:
def lengthOfLastWord(self, s):
"""
:type s: str
:rtype: int
"""
li = s.split()
return len(li[-1]) if li else 0 | 18.5 | 39 | 0.45045 | 27 | 222 | 3.703704 | 0.851852 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.030534 | 0.40991 | 222 | 12 | 39 | 18.5 | 0.732824 | 0.216216 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
ba8cbf1e8f33b4e6ae6ea6fa33a6606299a26211 | 767 | py | Python | util/path.py | cassianobecker/dnn | bb2ea04f77733de9df10f795bb049ac3b9d30478 | [
"MIT"
] | 3 | 2020-02-21T21:35:07.000Z | 2020-09-29T15:20:00.000Z | util/path.py | cassianobecker/dnn | bb2ea04f77733de9df10f795bb049ac3b9d30478 | [
"MIT"
] | 27 | 2020-02-20T21:00:23.000Z | 2020-05-22T15:23:25.000Z | util/path.py | cassianobecker/dnn | bb2ea04f77733de9df10f795bb049ac3b9d30478 | [
"MIT"
] | null | null | null | import os
import shutil
def get_root():
root_dir = os.path.dirname(os.path.abspath(__file__))
return os.path.split(root_dir)[0]
def absolute_path(relative_path):
return os.path.join(get_root(), relative_path)
def append_path(module, relative_path):
return os.path.join(get_dir(module), relative_path)
def get_dir(module):
return os.path.dirname(os.path.abspath(module))
def is_project_in_cbica():
current_file_path = os.path.dirname(os.path.abspath(__file__))
return current_file_path.split('/')[1] == 'cbica'
def copy_folder(src_path, dest_path, delete_src=False):
if os.path.isdir(dest_path):
shutil.rmtree(dest_path)
shutil.copytree(src_path, dest_path)
if delete_src:
shutil.rmtree(src_path)
| 21.305556 | 66 | 0.720991 | 118 | 767 | 4.372881 | 0.29661 | 0.116279 | 0.093023 | 0.087209 | 0.310078 | 0.310078 | 0.25969 | 0.139535 | 0 | 0 | 0 | 0.003082 | 0.153846 | 767 | 35 | 67 | 21.914286 | 0.791988 | 0 | 0 | 0 | 0 | 0 | 0.007823 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.3 | false | 0 | 0.1 | 0.15 | 0.65 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
baa043ba112c1db1f058e902f2a7ddaf2805cded | 254 | py | Python | ui/experimental.py | miguelgarciaarribas/multroaster | eb3a17e8257cd184cb91d53a2a61c6d3481ac206 | [
"MIT"
] | 1 | 2020-04-18T09:13:18.000Z | 2020-04-18T09:13:18.000Z | ui/experimental.py | miguelgarciaarribas/multroaster | eb3a17e8257cd184cb91d53a2a61c6d3481ac206 | [
"MIT"
] | 18 | 2020-04-24T07:22:54.000Z | 2020-08-28T10:33:18.000Z | ui/experimental.py | miguelgarciaarribas/multroaster | eb3a17e8257cd184cb91d53a2a61c6d3481ac206 | [
"MIT"
] | null | null | null | from PyQt5.QtGui import QImage, QPixmap # review
class ExperimentalContent():
def __init__(self, mainWindow):
print("Loading Experimental content")
self.mainWindow = mainWindow
self.mainWindow.expLabel.setText("hello world")
| 31.75 | 55 | 0.716535 | 26 | 254 | 6.846154 | 0.807692 | 0.235955 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.004878 | 0.192913 | 254 | 7 | 56 | 36.285714 | 0.863415 | 0.023622 | 0 | 0 | 0 | 0 | 0.158537 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.166667 | 0 | 0.5 | 0.166667 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
bac96c72212d49906c555e8ee6009e66b8770acd | 420 | py | Python | structural/decorator_example.py | EdiBoba/python_patterns | b3343eed5592beea2996316feb8df4bad107e1fc | [
"MIT"
] | 2 | 2022-02-08T16:30:22.000Z | 2022-03-16T08:20:25.000Z | structural/decorator_example.py | EdiBoba/python_patterns | b3343eed5592beea2996316feb8df4bad107e1fc | [
"MIT"
] | null | null | null | structural/decorator_example.py | EdiBoba/python_patterns | b3343eed5592beea2996316feb8df4bad107e1fc | [
"MIT"
] | 3 | 2021-08-06T15:47:47.000Z | 2021-12-09T18:59:38.000Z | from abc import ABCMeta, abstractmethod
class IOperator(metaclass=ABCMeta):
@abstractmethod
def operator(self):
pass
class Component(IOperator):
def operator(self):
return 10.0
class Wrapper(IOperator):
def __init__(self, obj):
self.obj = obj
def operator(self):
return self.obj.operator() + 5.0
comp = Component()
comp = Wrapper(comp)
print(comp.operator())
| 16.153846 | 40 | 0.657143 | 50 | 420 | 5.44 | 0.44 | 0.121324 | 0.165441 | 0.154412 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015576 | 0.235714 | 420 | 25 | 41 | 16.8 | 0.831776 | 0 | 0 | 0.1875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.0625 | 0.0625 | 0.125 | 0.625 | 0.0625 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 3 |
bacf7bd40e07778d4ffdc5b9e3092f4045164220 | 449 | py | Python | funk/tools.py | mwilliamson/funk | 658ff45b33b90f621104d9776c4b122b84779350 | [
"BSD-2-Clause"
] | 1 | 2016-04-22T08:02:01.000Z | 2016-04-22T08:02:01.000Z | funk/tools.py | mwilliamson/funk | 658ff45b33b90f621104d9776c4b122b84779350 | [
"BSD-2-Clause"
] | null | null | null | funk/tools.py | mwilliamson/funk | 658ff45b33b90f621104d9776c4b122b84779350 | [
"BSD-2-Clause"
] | null | null | null | class Data(object):
def __init__(self, attributes):
self._keys = list(attributes.keys())
for key in attributes:
setattr(self, key, attributes[key])
def __str__(self):
return "Data({0})".format(", ".join(
"{0}={1!r}".format(key, getattr(self, key))
for key in self._keys
))
def __repr__(self):
return str(self)
def data(**kwargs):
return Data(kwargs)
| 24.944444 | 55 | 0.550111 | 54 | 449 | 4.314815 | 0.425926 | 0.06867 | 0.06867 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009554 | 0.300668 | 449 | 17 | 56 | 26.411765 | 0.732484 | 0 | 0 | 0 | 0 | 0 | 0.044543 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0 | 0 | 0.214286 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
bade9c016e086e5bd504bbf7ecd019f9ea2e8e26 | 322 | py | Python | tests/test_client.py | debonzi/celery_crossover | 2da97fe527a357d5c85dfd29b04424d08dbe9b93 | [
"MIT"
] | 10 | 2018-04-06T18:58:18.000Z | 2021-11-05T19:19:03.000Z | tests/test_client.py | debonzi/celery_crossover | 2da97fe527a357d5c85dfd29b04424d08dbe9b93 | [
"MIT"
] | 2 | 2018-08-15T18:15:54.000Z | 2021-03-26T06:58:02.000Z | tests/test_client.py | debonzi/celery_crossover | 2da97fe527a357d5c85dfd29b04424d08dbe9b93 | [
"MIT"
] | 3 | 2018-04-09T03:06:12.000Z | 2019-11-08T17:35:57.000Z | # -*- coding: utf-8 -*-
import types
from crossover import Client
from crossover import _Requester
def test_client_attributes():
client = Client("redis://localhost:6379/0")
assert isinstance(client, Client)
assert isinstance(client.test, _Requester)
assert isinstance(client.call_task, types.MethodType)
| 26.833333 | 57 | 0.748447 | 39 | 322 | 6.051282 | 0.538462 | 0.20339 | 0.279661 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.021818 | 0.145963 | 322 | 11 | 58 | 29.272727 | 0.836364 | 0.065217 | 0 | 0 | 0 | 0 | 0.080268 | 0.080268 | 0 | 0 | 0 | 0 | 0.375 | 1 | 0.125 | false | 0 | 0.375 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
bafe54956d92542ae97bc15168154b2050039241 | 485 | py | Python | mac/pyobjc-framework-Quartz/PyObjCTest/test_PDFAnnotation.py | albertz/music-player | d23586f5bf657cbaea8147223be7814d117ae73d | [
"BSD-2-Clause"
] | 132 | 2015-01-01T10:02:42.000Z | 2022-03-09T12:51:01.000Z | mac/pyobjc-framework-Quartz/PyObjCTest/test_PDFAnnotation.py | mba811/music-player | 7998986b34cfda2244ef622adefb839331b81a81 | [
"BSD-2-Clause"
] | 6 | 2015-01-06T08:23:19.000Z | 2019-03-14T12:22:06.000Z | mac/pyobjc-framework-Quartz/PyObjCTest/test_PDFAnnotation.py | mba811/music-player | 7998986b34cfda2244ef622adefb839331b81a81 | [
"BSD-2-Clause"
] | 27 | 2015-02-23T11:51:43.000Z | 2022-03-07T02:34:18.000Z |
from PyObjCTools.TestSupport import *
from Quartz.PDFKit import *
class TestPDFAnnotation (TestCase):
def testMethods(self):
self.assertResultIsBOOL(PDFAnnotation.shouldDisplay)
self.assertArgIsBOOL(PDFAnnotation.setShouldDisplay_, 0)
self.assertResultIsBOOL(PDFAnnotation.shouldPrint)
self.assertArgIsBOOL(PDFAnnotation.setShouldPrint_, 0)
self.assertResultIsBOOL(PDFAnnotation.hasAppearanceStream)
if __name__ == "__main__":
main()
| 32.333333 | 66 | 0.762887 | 40 | 485 | 9 | 0.6 | 0.183333 | 0.291667 | 0.2 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.00489 | 0.156701 | 485 | 14 | 67 | 34.642857 | 0.875306 | 0 | 0 | 0 | 0 | 0 | 0.016529 | 0 | 0 | 0 | 0 | 0 | 0.454545 | 1 | 0.090909 | false | 0 | 0.181818 | 0 | 0.363636 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
2401ef1bb0cb741cbeac82b95a7eba1326a957b7 | 1,813 | py | Python | backend/ibutsu_server/models/group.py | john-dupuy/ibutsu-server | ae380fc7a72a4898075291bac8fdb86952bfd06a | [
"MIT"
] | null | null | null | backend/ibutsu_server/models/group.py | john-dupuy/ibutsu-server | ae380fc7a72a4898075291bac8fdb86952bfd06a | [
"MIT"
] | null | null | null | backend/ibutsu_server/models/group.py | john-dupuy/ibutsu-server | ae380fc7a72a4898075291bac8fdb86952bfd06a | [
"MIT"
] | null | null | null | # coding: utf-8
from __future__ import absolute_import
from ibutsu_server import util
from ibutsu_server.models.base_model_ import Model
class Group(Model):
"""NOTE: This class is auto generated by OpenAPI Generator (https://openapi-generator.tech).
Do not edit the class manually.
"""
def __init__(self, id=None, name=None):
"""Group - a model defined in OpenAPI
:param id: The id of this Group.
:type id: str
:param name: The name of this Group.
:type name: str
"""
self.openapi_types = {"id": str, "name": str}
self.attribute_map = {"id": "id", "name": "name"}
self._id = id
self._name = name
@classmethod
def from_dict(cls, dikt) -> "Group":
"""Returns the dict as a model
:param dikt: A dict.
:type: dict
:return: The Group of this Group.
:rtype: Group
"""
return util.deserialize_model(dikt, cls)
@property
def id(self):
"""Gets the id of this Group.
Unique ID of the project
:return: The id of this Group.
:rtype: str
"""
return self._id
@id.setter
def id(self, id):
"""Sets the id of this Group.
Unique ID of the project
:param id: The id of this Group.
:type id: str
"""
self._id = id
@property
def name(self):
"""Gets the name of this Group.
The name of the group
:return: The name of this Group.
:rtype: str
"""
return self._name
@name.setter
def name(self, name):
"""Sets the name of this Group.
The name of the group
:param name: The name of this Group.
:type name: str
"""
self._name = name
| 21.329412 | 96 | 0.552675 | 241 | 1,813 | 4.062241 | 0.253112 | 0.067416 | 0.123596 | 0.05618 | 0.367722 | 0.355465 | 0.355465 | 0.296221 | 0.296221 | 0.296221 | 0 | 0.000845 | 0.34749 | 1,813 | 84 | 97 | 21.583333 | 0.826712 | 0.432984 | 0 | 0.25 | 1 | 0 | 0.029909 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.125 | 0 | 0.541667 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
241bc9ceeaf007cf8c3f1adcf1de894a391d7c80 | 325 | py | Python | serving_patterns/src/app/api/_health.py | shibuiwilliam/ml-system-in-action | 0aa9d6bc4a4346236b9c971ec90afad04bcf5cca | [
"MIT"
] | 10 | 2020-08-30T03:19:10.000Z | 2021-08-08T17:38:06.000Z | serving_patterns/src/app/api/_health.py | shibuiwilliam/ml-system-in-action | 0aa9d6bc4a4346236b9c971ec90afad04bcf5cca | [
"MIT"
] | null | null | null | serving_patterns/src/app/api/_health.py | shibuiwilliam/ml-system-in-action | 0aa9d6bc4a4346236b9c971ec90afad04bcf5cca | [
"MIT"
] | 6 | 2020-08-30T03:19:13.000Z | 2021-11-26T23:32:42.000Z | from typing import Dict
import logging
from src.middleware.profiler import do_cprofile
logger = logging.getLogger(__name__)
@do_cprofile
def health() -> Dict[str, str]:
return {"health": "ok"}
def health_sync() -> Dict[str, str]:
return health()
async def health_async() -> Dict[str, str]:
return health()
| 17.105263 | 47 | 0.698462 | 44 | 325 | 4.977273 | 0.454545 | 0.123288 | 0.136986 | 0.219178 | 0.30137 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.172308 | 325 | 18 | 48 | 18.055556 | 0.814126 | 0 | 0 | 0.181818 | 0 | 0 | 0.024615 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.181818 | false | 0 | 0.272727 | 0.181818 | 0.727273 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
2458dac6adb26f8c77b50a1f69f3c2ef18781671 | 2,518 | py | Python | models/deep_factorized_model.py | kundajelab/mpra_minimal | 2799ed87821130fc537836651d37e45a3247382d | [
"MIT"
] | 11 | 2019-05-06T13:13:35.000Z | 2022-03-10T22:24:27.000Z | models/deep_factorized_model.py | mineeme/MPRA-DragoNN | 2799ed87821130fc537836651d37e45a3247382d | [
"MIT"
] | null | null | null | models/deep_factorized_model.py | mineeme/MPRA-DragoNN | 2799ed87821130fc537836651d37e45a3247382d | [
"MIT"
] | 2 | 2019-07-24T20:42:08.000Z | 2020-02-21T02:33:30.000Z | from models.base_model import BaseModel
from keras.models import Sequential
from keras.layers import Input, Dense, Conv1D, MaxPooling1D, Dropout, Flatten, BatchNormalization
from keras.optimizers import Adam
import tensorflow as tf
class DeepFactorizedModel(BaseModel):
def __init__(self, config):
super(DeepFactorizedModel, self).__init__(config)
self.build_model()
def build_model(self):
self.model = Sequential()
# sublayer 1
self.model.add(Conv1D(48, 3, padding='same', activation='relu', input_shape=(self.config.input_sequence_length, 4)))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Conv1D(64, 3, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Conv1D(100, 3, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Conv1D(150, 7, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Conv1D(300, 7, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(MaxPooling1D(3))
# sublayer 2
self.model.add(Conv1D(200, 7, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Conv1D(200, 3, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Conv1D(200, 3, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(MaxPooling1D(4))
# sublayer 3
self.model.add(Conv1D(200, 7, padding='same', activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(MaxPooling1D(4))
self.model.add(Flatten())
self.model.add(Dense(100, activation='relu'))
self.model.add(BatchNormalization())
self.model.add(Dropout(0.1))
self.model.add(Dense(self.config.number_of_outputs, activation='linear'))
self.model.compile(
loss= "mean_squared_error",
optimizer=self.config.optimizer,
# custom metrics in trainer
)
| 34.493151 | 124 | 0.643765 | 309 | 2,518 | 5.187702 | 0.20712 | 0.207736 | 0.262009 | 0.089208 | 0.635683 | 0.607611 | 0.607611 | 0.607611 | 0.607611 | 0.607611 | 0 | 0.039235 | 0.210485 | 2,518 | 72 | 125 | 34.972222 | 0.767103 | 0.023034 | 0 | 0.52 | 0 | 0 | 0.04075 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.04 | false | 0 | 0.1 | 0 | 0.16 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
2459202d8235c994028b62181cbfcd741881a72d | 323 | py | Python | scripts/nengo_os/print_control.py | markplagge/neuro_os | 60b246c0f975d30658628e1caf60cd209e740e6e | [
"BSD-3-Clause"
] | null | null | null | scripts/nengo_os/print_control.py | markplagge/neuro_os | 60b246c0f975d30658628e1caf60cd209e740e6e | [
"BSD-3-Clause"
] | 1 | 2020-07-21T02:25:45.000Z | 2020-07-21T02:27:45.000Z | scripts/nengo_os/print_control.py | markplagge/neuro_os | 60b246c0f975d30658628e1caf60cd209e740e6e | [
"BSD-3-Clause"
] | null | null | null | debug_print = False
has_run_once = False
def d_print(*args, **kwargs):
global debug_print
global has_run_once
if not has_run_once:
m = "enabled" if debug_print else "disabled"
print(f"Debug Print Mode is {m}")
has_run_once = True
if debug_print:
print(*args, **kwargs)
| 17.944444 | 52 | 0.634675 | 48 | 323 | 4 | 0.4375 | 0.260417 | 0.208333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.275542 | 323 | 17 | 53 | 19 | 0.820513 | 0 | 0 | 0 | 0 | 0 | 0.11838 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.090909 | false | 0 | 0 | 0 | 0.090909 | 0.636364 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
24605b6587afbc12049e73b54cb4418582146acb | 37 | py | Python | zhaquirks/bosch/__init__.py | WolfRevo/zha-device-handlers | 0fa4ca1c03c611be0cf2c38c4fec2a197e3dd1d3 | [
"Apache-2.0"
] | 213 | 2020-04-16T10:48:31.000Z | 2022-03-30T20:48:07.000Z | zhaquirks/bosch/__init__.py | WolfRevo/zha-device-handlers | 0fa4ca1c03c611be0cf2c38c4fec2a197e3dd1d3 | [
"Apache-2.0"
] | 1,088 | 2020-04-03T13:23:29.000Z | 2022-03-31T23:55:03.000Z | zhaquirks/bosch/__init__.py | WolfRevo/zha-device-handlers | 0fa4ca1c03c611be0cf2c38c4fec2a197e3dd1d3 | [
"Apache-2.0"
] | 280 | 2020-04-24T08:44:27.000Z | 2022-03-31T12:58:04.000Z | """Bosch quirks."""
BOSCH = "Bosch"
| 9.25 | 19 | 0.567568 | 4 | 37 | 5.25 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.162162 | 37 | 3 | 20 | 12.333333 | 0.677419 | 0.351351 | 0 | 0 | 0 | 0 | 0.277778 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
24669af442e48736ce23de6fe426df216d0af465 | 661 | py | Python | sharedql/schema.py | akaytatsu/sharedql | ceeb3df2909bc90325c72f930fba35de6827ee74 | [
"MIT"
] | null | null | null | sharedql/schema.py | akaytatsu/sharedql | ceeb3df2909bc90325c72f930fba35de6827ee74 | [
"MIT"
] | null | null | null | sharedql/schema.py | akaytatsu/sharedql | ceeb3df2909bc90325c72f930fba35de6827ee74 | [
"MIT"
] | null | null | null | from __future__ import print_function
import sys
import importlib
from django.conf import settings
import graphene
from .base import sharedql
for imports in settings.INSTALLED_APPS:
imports = imports + ".schema"
try:
mod = importlib.import_module(imports + ".schema")
except ImportError:
pass
# print("Failed to load {module}".format(module=imports),file=sys.stderr)
bases = tuple(sharedql.query_classes + [graphene.ObjectType, object])
# for cls in bases:
# print("Including '{}' in global GraphQL Query...".format(cls.__name__))
SharedQuery = type('Query', bases, {})
schema = graphene.Schema(query=SharedQuery) | 25.423077 | 81 | 0.715582 | 80 | 661 | 5.7625 | 0.55 | 0.056399 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.172466 | 661 | 26 | 82 | 25.423077 | 0.842779 | 0.249622 | 0 | 0 | 0 | 0 | 0.03854 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.066667 | 0.666667 | 0 | 0.666667 | 0.066667 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 1 | 0 | 0 | 3 |
03018f2878f299da32e5fb359237991d538d5f69 | 288 | py | Python | services/web/project/adminsettings.py | pwdel/srcflask | 71c91cc9edb2a5e3aa08dbdd819e05feb84175f2 | [
"BSD-Source-Code"
] | null | null | null | services/web/project/adminsettings.py | pwdel/srcflask | 71c91cc9edb2a5e3aa08dbdd819e05feb84175f2 | [
"BSD-Source-Code"
] | null | null | null | services/web/project/adminsettings.py | pwdel/srcflask | 71c91cc9edb2a5e3aa08dbdd819e05feb84175f2 | [
"BSD-Source-Code"
] | null | null | null | # administrative username and password for development
ADMIN_USERNAME = 'admin'
ADMIN_PASSWORD = 'password'
ADMIN_TYPE = 'admin'
# for production
# ADMIN_USERNAME = 'environ.get('ADMIN_USERNAME')
# ADMIN_PASSWORD = 'environ.get('ADMIN_PASSWORD')
# ADMIN_TYPE = 'environ.get('ADMIN_TYPE')
| 32 | 54 | 0.770833 | 35 | 288 | 6.085714 | 0.314286 | 0.183099 | 0.211268 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.107639 | 288 | 8 | 55 | 36 | 0.828794 | 0.704861 | 0 | 0 | 0 | 0 | 0.227848 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.333333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
03094a8fb0cb1c5dd1e571be669375786508c47f | 403 | py | Python | oacensus/exceptions.py | ananelson/oacensus | 87916c92ab1233bcf82a481113017dfb8d7701b9 | [
"Apache-2.0"
] | null | null | null | oacensus/exceptions.py | ananelson/oacensus | 87916c92ab1233bcf82a481113017dfb8d7701b9 | [
"Apache-2.0"
] | 2 | 2016-01-10T20:23:41.000Z | 2016-01-14T16:57:06.000Z | oacensus/exceptions.py | ananelson/oacensus | 87916c92ab1233bcf82a481113017dfb8d7701b9 | [
"Apache-2.0"
] | null | null | null | class OacensusError(Exception):
pass
class UserFeedback(OacensusError):
"""
An exception which was caused by user input or a runtime error and which
should be presented nicely.
"""
class ConfigFileFormatProblem(UserFeedback):
"""
A problem with config files.
"""
pass
class APIError(UserFeedback):
"""
An exception raised by a remote API.
"""
pass
| 19.190476 | 76 | 0.665012 | 45 | 403 | 5.955556 | 0.666667 | 0.067164 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.253102 | 403 | 20 | 77 | 20.15 | 0.890365 | 0.411911 | 0 | 0.428571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.428571 | 0 | 0 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
031c707ec58ef183b7c607c6546f5f047d0e3e8e | 272 | py | Python | scripting/__init__.py | csdms/py-scripting | df8ba070e44a9d8e6ffcb70958f851e6776e2853 | [
"MIT"
] | null | null | null | scripting/__init__.py | csdms/py-scripting | df8ba070e44a9d8e6ffcb70958f851e6776e2853 | [
"MIT"
] | null | null | null | scripting/__init__.py | csdms/py-scripting | df8ba070e44a9d8e6ffcb70958f851e6776e2853 | [
"MIT"
] | null | null | null | from ._version import get_versions
from .contexts import cd
from .prompting import error, prompt, status, success
from .unix import cp, ln_s
__all__ = ["prompt", "status", "success", "error", "cp", "cd", "ln_s"]
__version__ = get_versions()["version"]
del get_versions
| 24.727273 | 70 | 0.724265 | 38 | 272 | 4.815789 | 0.473684 | 0.180328 | 0.20765 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.136029 | 272 | 10 | 71 | 27.2 | 0.778723 | 0 | 0 | 0 | 0 | 0 | 0.143382 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.571429 | 0 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
033bef35de4a5d1c411f88cd89ce77dc04b26d5f | 1,748 | py | Python | src/toil/server/wsgi_app.py | PolusAI/toil | a98acdb5cbe0f850b2c11403d147577d9971f4e1 | [
"Apache-2.0"
] | 516 | 2015-07-30T19:08:55.000Z | 2018-07-03T20:53:42.000Z | src/toil/server/wsgi_app.py | PolusAI/toil | a98acdb5cbe0f850b2c11403d147577d9971f4e1 | [
"Apache-2.0"
] | 1,949 | 2015-07-29T23:38:49.000Z | 2018-07-05T12:42:04.000Z | src/toil/server/wsgi_app.py | gmloose/toil | a82834073b28f66747c5c3ac99d1a678b82d2290 | [
"Apache-2.0"
] | 193 | 2015-07-31T18:52:57.000Z | 2018-07-05T08:54:11.000Z | # Copyright (C) 2015-2021 Regents of the University of California
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
from typing import Any, Optional, Dict
from gunicorn.app.base import BaseApplication # type: ignore
class GunicornApplication(BaseApplication): # type: ignore
"""
An entry point to integrate a Gunicorn WSGI server in Python. To start a
WSGI application with callable `app`, run the following code:
WSGIApplication(app, options={
...
}).run()
For more details, see: https://docs.gunicorn.org/en/latest/custom.html
"""
def __init__(self, app: object, options: Optional[Dict[str, Any]] = None):
self.options = options or {}
self.application = app
super().__init__()
def init(self, *args: Any) -> None:
pass
def load_config(self) -> None:
for key, value in self.options.items():
if key in self.cfg.settings and value is not None:
self.cfg.set(key.lower(), value)
def load(self) -> object:
return self.application
def run_app(app: object, options: Optional[Dict[str, Any]] = None) -> None:
"""
Run a Gunicorn WSGI server.
"""
GunicornApplication(app, options=options).run()
| 34.27451 | 78 | 0.676201 | 239 | 1,748 | 4.903766 | 0.506276 | 0.051195 | 0.022184 | 0.027304 | 0.064846 | 0.064846 | 0.064846 | 0.064846 | 0 | 0 | 0 | 0.008856 | 0.224828 | 1,748 | 50 | 79 | 34.96 | 0.856089 | 0.519451 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.294118 | false | 0.058824 | 0.117647 | 0.058824 | 0.529412 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
033e5296d7002695cb78ba70091a41d8f1afe514 | 102 | py | Python | tests/files/build_flask.py | microservice-tools/pixis | ce5a1ecc70732677518d21a0e876440af1245eac | [
"MIT"
] | null | null | null | tests/files/build_flask.py | microservice-tools/pixis | ce5a1ecc70732677518d21a0e876440af1245eac | [
"MIT"
] | 21 | 2018-04-25T19:07:41.000Z | 2018-07-18T06:04:56.000Z | tests/files/build_flask.py | microservice-tools/pixis | ce5a1ecc70732677518d21a0e876440af1245eac | [
"MIT"
] | 1 | 2018-04-23T14:44:00.000Z | 2018-04-23T14:44:00.000Z | SPEC = 'swagger.yaml'
IMPLEMENTATION = 'flask'
OUTPUT = 'build'
FLASK_SERVER_NAME = 'my_flask_server'
| 20.4 | 37 | 0.754902 | 13 | 102 | 5.615385 | 0.769231 | 0.30137 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.117647 | 102 | 4 | 38 | 25.5 | 0.811111 | 0 | 0 | 0 | 0 | 0 | 0.362745 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
036b561ed932ab60b4b97fb19bd96ddc0a940784 | 246 | py | Python | lab_restful/app/models/Paper.py | afish1001/lab_server | c6a2b09834d73078ab52e2965849cd41ba795b4b | [
"MIT"
] | null | null | null | lab_restful/app/models/Paper.py | afish1001/lab_server | c6a2b09834d73078ab52e2965849cd41ba795b4b | [
"MIT"
] | null | null | null | lab_restful/app/models/Paper.py | afish1001/lab_server | c6a2b09834d73078ab52e2965849cd41ba795b4b | [
"MIT"
] | null | null | null | from .. import utils
from ..config import table
class Paper():
def __init__(self):
self.collection = table.paper
self.conn = utils.mongo.db.get_collection(self.collection)
def list(self):
pass
paper = Paper()
| 16.4 | 66 | 0.642276 | 31 | 246 | 4.935484 | 0.548387 | 0.183007 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.247967 | 246 | 14 | 67 | 17.571429 | 0.827027 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.222222 | false | 0.111111 | 0.222222 | 0 | 0.555556 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
ceed5b9c4d3963ebe8a8bb9c365ef1238097db1b | 390 | py | Python | tests/basics/try_reraise.py | geowor01/micropython | 7fb13eeef4a85f21cae36f1d502bcc53880e1815 | [
"MIT"
] | 7 | 2019-10-18T13:41:39.000Z | 2022-03-15T17:27:57.000Z | tests/basics/try_reraise.py | geowor01/micropython | 7fb13eeef4a85f21cae36f1d502bcc53880e1815 | [
"MIT"
] | null | null | null | tests/basics/try_reraise.py | geowor01/micropython | 7fb13eeef4a85f21cae36f1d502bcc53880e1815 | [
"MIT"
] | 2 | 2020-06-23T09:10:15.000Z | 2020-12-22T06:42:14.000Z | # Reraising last exception with raise w/o args
def f():
try:
raise ValueError("val", 3)
print("FAIL")
raise SystemExit
except:
raise
try:
f()
print("FAIL")
raise SystemExit
except ValueError as e:
pass
# Can reraise only in except block
try:
raise
print("FAIL")
raise SystemExit
except RuntimeError:
print("PASS")
| 15 | 46 | 0.602564 | 48 | 390 | 4.895833 | 0.5625 | 0.114894 | 0.178723 | 0.306383 | 0.382979 | 0 | 0 | 0 | 0 | 0 | 0 | 0.003704 | 0.307692 | 390 | 25 | 47 | 15.6 | 0.866667 | 0.197436 | 0 | 0.578947 | 0 | 0 | 0.06129 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.052632 | true | 0.105263 | 0 | 0 | 0.052632 | 0.210526 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
cef7afd517df5ca0ce5466fa5f955c031bbbb177 | 223 | py | Python | src/projects/tests/factories/package.py | unikubehq/projects | 0df69eafa2a0d2664a22c7a5866d4512ac4d57fe | [
"Apache-2.0"
] | 1 | 2021-10-05T13:17:03.000Z | 2021-10-05T13:17:03.000Z | src/projects/tests/factories/package.py | unikubehq/projects | 0df69eafa2a0d2664a22c7a5866d4512ac4d57fe | [
"Apache-2.0"
] | 48 | 2021-07-06T07:24:36.000Z | 2022-03-24T08:27:30.000Z | src/projects/tests/factories/package.py | unikubehq/projects | 0df69eafa2a0d2664a22c7a5866d4512ac4d57fe | [
"Apache-2.0"
] | null | null | null | import factory
from projects.tests.factories.project import ProjectFactory
class DeckFactory(factory.DjangoModelFactory):
class Meta:
model = "projects.Deck"
project = factory.SubFactory(ProjectFactory)
| 20.272727 | 59 | 0.766816 | 22 | 223 | 7.772727 | 0.681818 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.161435 | 223 | 10 | 60 | 22.3 | 0.914439 | 0 | 0 | 0 | 0 | 0 | 0.058296 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.833333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
cef8e48081ec1240c8d15a802e15c821eaaffb84 | 1,064 | py | Python | cfc_app/migrations/0005_auto_20201024_0139.py | ephyle/Legit-Info | 7f3845563a64299aa64e4fdba75949276ed9a711 | [
"BSD-2-Clause",
"CC-BY-4.0",
"Apache-2.0"
] | 44 | 2020-10-19T13:06:10.000Z | 2022-01-23T10:56:31.000Z | cfc_app/migrations/0005_auto_20201024_0139.py | ephyle/Legit-Info | 7f3845563a64299aa64e4fdba75949276ed9a711 | [
"BSD-2-Clause",
"CC-BY-4.0",
"Apache-2.0"
] | 111 | 2020-10-20T22:12:58.000Z | 2022-03-28T00:25:13.000Z | cfc_app/migrations/0005_auto_20201024_0139.py | ephyle/Legit-Info | 7f3845563a64299aa64e4fdba75949276ed9a711 | [
"BSD-2-Clause",
"CC-BY-4.0",
"Apache-2.0"
] | 31 | 2021-02-08T22:32:37.000Z | 2022-03-11T10:57:29.000Z | # Generated by Django 3.0.8 on 2020-10-24 01:39
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('cfc_app', '0004_auto_20201024_0133'),
]
operations = [
migrations.AlterField(
model_name='hash',
name='fob_method',
field=models.CharField(editable=False, max_length=6),
),
migrations.AlterField(
model_name='hash',
name='generated_date',
field=models.DateField(editable=False),
),
migrations.AlterField(
model_name='hash',
name='hashcode',
field=models.CharField(editable=False, max_length=32),
),
migrations.AlterField(
model_name='hash',
name='item_name',
field=models.CharField(editable=False, max_length=255),
),
migrations.AlterField(
model_name='hash',
name='size',
field=models.PositiveIntegerField(editable=False),
),
]
| 27.282051 | 67 | 0.56391 | 102 | 1,064 | 5.735294 | 0.470588 | 0.17094 | 0.213675 | 0.247863 | 0.531624 | 0.531624 | 0.215385 | 0 | 0 | 0 | 0 | 0.051247 | 0.321429 | 1,064 | 38 | 68 | 28 | 0.759003 | 0.042293 | 0 | 0.46875 | 1 | 0 | 0.093412 | 0.022616 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.03125 | 0 | 0.125 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
cefb3f843b82b1bef9a3afd4b8e0d08adb19182d | 175 | py | Python | code/eda.py | rodriggs/twosigmafinancial | a8ad216a71e4bb3fbfbd606281b101b845eae961 | [
"MIT"
] | null | null | null | code/eda.py | rodriggs/twosigmafinancial | a8ad216a71e4bb3fbfbd606281b101b845eae961 | [
"MIT"
] | null | null | null | code/eda.py | rodriggs/twosigmafinancial | a8ad216a71e4bb3fbfbd606281b101b845eae961 | [
"MIT"
] | null | null | null | import numpy as np
import pandas as pd
import h5py
# docker run -it kagglegym
# python
# >>> import kagglegym
# >>> kagglegym.test()
train = pd.read_hdf("../data/train.h5")
| 15.909091 | 39 | 0.691429 | 26 | 175 | 4.615385 | 0.692308 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.013699 | 0.165714 | 175 | 10 | 40 | 17.5 | 0.808219 | 0.417143 | 0 | 0 | 0 | 0 | 0.164948 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.75 | 0 | 0.75 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
3010ae6e12181dbe483e73b05d5e55639ba72b1f | 240 | py | Python | backend/categories/models.py | cristianemoyano/django-react-webapp | c91d263f58b0d66a8c260e095d0ec6cee66f8afd | [
"MIT"
] | null | null | null | backend/categories/models.py | cristianemoyano/django-react-webapp | c91d263f58b0d66a8c260e095d0ec6cee66f8afd | [
"MIT"
] | null | null | null | backend/categories/models.py | cristianemoyano/django-react-webapp | c91d263f58b0d66a8c260e095d0ec6cee66f8afd | [
"MIT"
] | null | null | null | from django.db import models
class Category(models.Model):
"""Category model."""
name = models.CharField(max_length=100, unique=True)
class Meta:
ordering = ('name',)
def __str__(self):
return self.name
| 17.142857 | 56 | 0.633333 | 29 | 240 | 5.068966 | 0.724138 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016484 | 0.241667 | 240 | 13 | 57 | 18.461538 | 0.791209 | 0.0625 | 0 | 0 | 0 | 0 | 0.018265 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.142857 | false | 0 | 0.142857 | 0.142857 | 0.857143 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
302088ce171e1ce5fee7f69b6466cc5d52936180 | 3,960 | py | Python | dingtalk/python/alibabacloud_dingtalk/workrecord_1_0/client.py | yndu13/dingtalk-sdk | 700fb7bb49c4d3167f84afc5fcb5e7aa5a09735f | [
"Apache-2.0"
] | 15 | 2020-08-27T04:10:26.000Z | 2022-03-07T06:25:42.000Z | dingtalk/python/alibabacloud_dingtalk/workrecord_1_0/client.py | yndu13/dingtalk-sdk | 700fb7bb49c4d3167f84afc5fcb5e7aa5a09735f | [
"Apache-2.0"
] | 1 | 2020-09-27T01:30:46.000Z | 2021-12-29T09:15:34.000Z | dingtalk/python/alibabacloud_dingtalk/workrecord_1_0/client.py | yndu13/dingtalk-sdk | 700fb7bb49c4d3167f84afc5fcb5e7aa5a09735f | [
"Apache-2.0"
] | 5 | 2020-08-27T04:07:44.000Z | 2021-12-03T02:55:20.000Z | # -*- coding: utf-8 -*-
# This file is auto-generated, don't edit it. Thanks.
from Tea.core import TeaCore
from alibabacloud_tea_openapi.client import Client as OpenApiClient
from alibabacloud_tea_openapi import models as open_api_models
from alibabacloud_tea_util.client import Client as UtilClient
from alibabacloud_dingtalk.workrecord_1_0 import models as dingtalkworkrecord__1__0_models
from alibabacloud_tea_util import models as util_models
from alibabacloud_openapi_util.client import Client as OpenApiUtilClient
class Client(OpenApiClient):
"""
*\
"""
def __init__(
self,
config: open_api_models.Config,
):
super().__init__(config)
self._endpoint_rule = ''
if UtilClient.empty(self._endpoint):
self._endpoint = 'api.dingtalk.com'
def count_work_record(
self,
request: dingtalkworkrecord__1__0_models.CountWorkRecordRequest,
) -> dingtalkworkrecord__1__0_models.CountWorkRecordResponse:
runtime = util_models.RuntimeOptions()
headers = dingtalkworkrecord__1__0_models.CountWorkRecordHeaders()
return self.count_work_record_with_options(request, headers, runtime)
async def count_work_record_async(
self,
request: dingtalkworkrecord__1__0_models.CountWorkRecordRequest,
) -> dingtalkworkrecord__1__0_models.CountWorkRecordResponse:
runtime = util_models.RuntimeOptions()
headers = dingtalkworkrecord__1__0_models.CountWorkRecordHeaders()
return await self.count_work_record_with_options_async(request, headers, runtime)
def count_work_record_with_options(
self,
request: dingtalkworkrecord__1__0_models.CountWorkRecordRequest,
headers: dingtalkworkrecord__1__0_models.CountWorkRecordHeaders,
runtime: util_models.RuntimeOptions,
) -> dingtalkworkrecord__1__0_models.CountWorkRecordResponse:
UtilClient.validate_model(request)
query = {}
if not UtilClient.is_unset(request.user_id):
query['userId'] = request.user_id
real_headers = {}
if not UtilClient.is_unset(headers.common_headers):
real_headers = headers.common_headers
if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token):
real_headers['x-acs-dingtalk-access-token'] = headers.x_acs_dingtalk_access_token
req = open_api_models.OpenApiRequest(
headers=real_headers,
query=OpenApiUtilClient.query(query)
)
return TeaCore.from_map(
dingtalkworkrecord__1__0_models.CountWorkRecordResponse(),
self.do_roarequest('CountWorkRecord', 'workrecord_1.0', 'HTTP', 'GET', 'AK', f'/v1.0/workrecord/counts', 'json', req, runtime)
)
async def count_work_record_with_options_async(
self,
request: dingtalkworkrecord__1__0_models.CountWorkRecordRequest,
headers: dingtalkworkrecord__1__0_models.CountWorkRecordHeaders,
runtime: util_models.RuntimeOptions,
) -> dingtalkworkrecord__1__0_models.CountWorkRecordResponse:
UtilClient.validate_model(request)
query = {}
if not UtilClient.is_unset(request.user_id):
query['userId'] = request.user_id
real_headers = {}
if not UtilClient.is_unset(headers.common_headers):
real_headers = headers.common_headers
if not UtilClient.is_unset(headers.x_acs_dingtalk_access_token):
real_headers['x-acs-dingtalk-access-token'] = headers.x_acs_dingtalk_access_token
req = open_api_models.OpenApiRequest(
headers=real_headers,
query=OpenApiUtilClient.query(query)
)
return TeaCore.from_map(
dingtalkworkrecord__1__0_models.CountWorkRecordResponse(),
await self.do_roarequest_async('CountWorkRecord', 'workrecord_1.0', 'HTTP', 'GET', 'AK', f'/v1.0/workrecord/counts', 'json', req, runtime)
)
| 44.494382 | 150 | 0.716162 | 432 | 3,960 | 6.141204 | 0.201389 | 0.01357 | 0.11308 | 0.147003 | 0.785526 | 0.747079 | 0.687524 | 0.687524 | 0.683754 | 0.683754 | 0 | 0.013016 | 0.204545 | 3,960 | 88 | 151 | 45 | 0.829206 | 0.020202 | 0 | 0.644737 | 1 | 0 | 0.054837 | 0.025867 | 0 | 0 | 0 | 0 | 0 | 1 | 0.039474 | false | 0 | 0.092105 | 0 | 0.197368 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
30292b7c2f6979a04692b3c67d475af07d5a822b | 184 | py | Python | modules/moderation/__init__.py | H3xadecimal/Nest | 4422cf5725a71603ff58ccbf9f261b28ff96f70e | [
"MIT"
] | 10 | 2018-04-21T07:29:42.000Z | 2019-02-01T20:46:48.000Z | modules/moderation/__init__.py | H3xadecimal/Nest | 4422cf5725a71603ff58ccbf9f261b28ff96f70e | [
"MIT"
] | 2 | 2018-09-10T00:58:40.000Z | 2019-12-22T11:19:58.000Z | modules/moderation/__init__.py | H3xadecimal/Nest | 4422cf5725a71603ff58ccbf9f261b28ff96f70e | [
"MIT"
] | 2 | 2018-09-09T23:07:56.000Z | 2019-10-19T15:26:56.000Z | """
Basic moderation utilities for Birb.
"""
from .staff import CheckMods
from .actions import ModActions
def setup(bot):
bot.add_cog(CheckMods())
bot.add_cog(ModActions())
| 15.333333 | 36 | 0.717391 | 24 | 184 | 5.416667 | 0.666667 | 0.092308 | 0.138462 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.163043 | 184 | 11 | 37 | 16.727273 | 0.844156 | 0.195652 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.4 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
303842a63bcf998cc97937b86976891ee5b81ac2 | 5,547 | py | Python | lift-learn/metrics/_values.py | smn-ailab/lift-learn | 158b8be554aad49033ee2eacf14fbbeb2418d6f7 | [
"MIT"
] | 1 | 2019-03-12T11:07:16.000Z | 2019-03-12T11:07:16.000Z | lift-learn/metrics/_values.py | smn-ailab/lift-learn | 158b8be554aad49033ee2eacf14fbbeb2418d6f7 | [
"MIT"
] | 1 | 2019-02-15T06:21:33.000Z | 2019-02-20T01:03:54.000Z | lift-learn/metrics/_values.py | smn-ailab/lift-learn | 158b8be554aad49033ee2eacf14fbbeb2418d6f7 | [
"MIT"
] | null | null | null | """Metrics to assess performance on ite prediction task."""
from typing import Optional
import numpy as np
import pandas as pd
def expected_response(y: np.ndarray, w: np.ndarray, policy: np.ndarray,
mu: Optional[np.ndarray]=None, ps: Optional[np.ndarray]=None) -> float:
"""Estimate expected response.
Parameters
----------
y: array-like of shape = (n_samples)
Observed target values.
w: array-like of shape = shape = (n_samples)
Treatment assignment variables.
policy: array-like of shape = (n_samples)
Estimated treatment policy.
mu: array-like of shape = (n_samples, n_trts), optional
Estimated potential outcomes.
ps: array-like of shape = (n_samples, n_trts), optional
Estimated propensity scores.
Returns
-------
expected_response: float
Estimated expected_response.
"""
mu = np.zeros((w.shape[0], np.unique(w).shape[0])) if mu is None else mu
ps = pd.get_dummies(w).mean(axis=0).values if ps is None else ps
indicator = np.array(w == policy, dtype=int)
expected_response = np.mean(mu[np.arange(w.shape[0]), policy]
+ (y - mu[np.arange(w.shape[0]), policy]) * indicator / ps[w])
return expected_response
def ips_value(y: np.ndarray, w: np.ndarray, policy: np.ndarray, ps: Optional[np.ndarray]=None) -> float:
"""Decision Value Estimator based on Inverse Propensity Score Weighting method.
Parameters
----------
y: array-like of shape = (n_samples)
Observed target values.
w: array-like of shape = shape = (n_samples)
Treatment assignment indicators.
policy: array-like of shape = (n_samples)
Estimated decision model.
ps: array-like of shape = (n_samples), optional
Estimated propensity scores.
Returns
-------
decision_value: float
Estimated decision value using Inverse Propensity Score Weighting method.
References
----------
[1] Y. Zhao, X. Fang, D. S. Levi: Uplift modeling with multiple treatments and general response types, 2017.
[2] A. Schuler, M. Baiocchi, R. Tibshirani, N. Shah: A comparison of methods for model selection when estimating individual treatment effects, 2018.
"""
if not isinstance(y, np.ndarray):
raise TypeError("y must be a numpy.ndarray.")
if not isinstance(w, np.ndarray):
raise TypeError("w must be a numpy.ndarray.")
if not isinstance(policy, np.ndarray):
raise TypeError("policy must be a numpy.ndarray.")
if ps is None:
trts_probs = pd.get_dummies(w).mean(axis=0).values
ps = np.ones((w.shape[0], np.unique(w).shape[0])) * np.expand_dims(trts_probs, axis=0)
else:
assert (np.max(ps) < 1) and (np.min(ps) > 0), "ps must be strictly between 0 and 1."
treatment_matrix = pd.get_dummies(w).values
if np.unique(policy).shape[0] == np.unique(w).shape[0]:
policy = pd.get_dummies(policy).values
else:
diff = np.setdiff1d(np.unique(w), np.unique(policy))
policy = pd.get_dummies(policy).values
for _diff in diff:
policy = np.insert(policy, _diff, 0, axis=1)
indicator_matrix = policy * treatment_matrix
outcome_matrix = np.expand_dims(y, axis=1) * treatment_matrix
decision_value = np.mean(np.sum(indicator_matrix * (outcome_matrix / ps), axis=1))
return decision_value
def dr_value(y: np.ndarray, w: np.ndarray, policy: np.ndarray,
mu: np.ndarray, ps: Optional[np.ndarray]=None) -> float:
"""Decision Value Estimator based on Doubly Robust method.
Parameters
----------
y: array-like of shape = (n_samples)
Observed target values.
w: array-like of shape = (n_samples)
Treatment assignment indicators.
policy: array-like of shape = (n_samples)
Estimated decision model.
ps: array-like of shape = (n_samples)
Estimated propensity scores.
mu: array-like of shape = (n_samples, n_treatments), optional
Estimated potential outcome for each treatment.
Returns
-------
decision_value: float
Estimated decision value using Doubly Robust method.
References
----------
[1] A. Schuler, M. Baiocchi, R. Tibshirani, N. Shah: A comparison of methods for model selection when estimating individual treatment effects, 2018.
"""
if not isinstance(y, np.ndarray):
raise TypeError("y must be a numpy.ndarray.")
if not isinstance(w, np.ndarray):
raise TypeError("w must be a numpy.ndarray.")
if not isinstance(policy, np.ndarray):
raise TypeError("policy must be a numpy.ndarray.")
if not isinstance(mu, np.ndarray):
raise TypeError("mu must be a numpy.ndarray.")
if ps is None:
trts_probs = pd.get_dummies(w).mean(axis=0).values
ps = np.ones((w.shape[0], np.unique(w).shape[0])) * np.expand_dims(trts_probs, axis=0)
else:
assert (np.max(ps) < 1) and (np.min(ps) > 0), "ps must be strictly between 0 and 1."
treatment_matrix = pd.get_dummies(w).values
policy = pd.get_dummies(policy).values
diff = np.setdiff1d(np.unique(w), np.unique(policy))
for _diff in diff:
policy = np.insert(policy, _diff, 0, axis=1)
indicator_matrix = policy * treatment_matrix
outcome_matrix = np.expand_dims(y, axis=1) * treatment_matrix
decision_value = np.mean(np.sum(treatment_matrix * mu + indicator_matrix * (outcome_matrix - mu) / ps, axis=1))
return decision_value
| 36.493421 | 152 | 0.650442 | 772 | 5,547 | 4.589378 | 0.176166 | 0.053345 | 0.043466 | 0.063223 | 0.796218 | 0.761219 | 0.713237 | 0.691222 | 0.624894 | 0.603443 | 0 | 0.011233 | 0.229674 | 5,547 | 151 | 153 | 36.735099 | 0.817927 | 0.383991 | 0 | 0.677966 | 0 | 0 | 0.083702 | 0 | 0 | 0 | 0 | 0 | 0.033898 | 1 | 0.050847 | false | 0 | 0.050847 | 0 | 0.152542 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
303aea533163720c626b39e6c0bbce695a86963f | 16,358 | py | Python | tests/cases/matching_graph.py | nilsec/mtrack | 76652c468417c7e3ac9903586c0127b884d6b032 | [
"MIT"
] | null | null | null | tests/cases/matching_graph.py | nilsec/mtrack | 76652c468417c7e3ac9903586c0127b884d6b032 | [
"MIT"
] | null | null | null | tests/cases/matching_graph.py | nilsec/mtrack | 76652c468417c7e3ac9903586c0127b884d6b032 | [
"MIT"
] | null | null | null | import unittest
import numpy as np
from mtrack.graphs import G1
from mtrack.evaluation.matching_graph import MatchingGraph
from mtrack.evaluation.voxel_skeleton import VoxelSkeleton
from comatch import match_components
import json
test_data_dir = "./data"
class ParallelLinesSetUp(unittest.TestCase):
def setUp(self):
"""
o o
| |
| |
| |
| |
| |
o o
| |
| |
| |
| |
o o
| |
| |
. .
. .
. .
"""
self.gt_vertices = 10
self.rec_vertices = 10
self.gt = G1(self.gt_vertices)
self.rec = G1(self.rec_vertices)
z = 0
for v in self.gt.get_vertex_iterator():
self.gt.set_position(v, np.array([100,100,z]))
self.gt.set_orientation(v, np.array([1,0,0]))
z += 5
if int(v)<self.gt_vertices-1:
self.gt.add_edge(int(v), int(v)+1)
self.vs_gt = VoxelSkeleton(self.gt, voxel_size=[1.,1.,1.], verbose=True)
# Different offset:
z = 0
for v in self.rec.get_vertex_iterator():
self.rec.set_position(v, np.array([150,100,z]))
self.rec.set_orientation(v, np.array([1,0,0]))
z += 5
if int(v)<self.rec_vertices-1:
self.rec.add_edge(int(v), int(v)+1)
self.vs_rec = VoxelSkeleton(self.rec, voxel_size=[1.,1.,1.], verbose=True)
self.groundtruth_skeletons = [self.vs_gt]
self.reconstructed_skeletons = [self.vs_rec]
self.skeletons = {"gt": self.vs_gt, "rec": self.vs_rec}
self.distance_threshold = 50.1
self.voxel_size = [1.,1.,1.]
class ErrorTestSetUpSameDistance(unittest.TestCase):
def setUp(self):
self.gt_vertices = 10
self.rec1_vertices = 5
self.rec2_vertices = 5
self.gt = G1(self.gt_vertices)
self.rec1 = G1(self.rec1_vertices)
self.rec2 = G1(self.rec2_vertices)
z = 0
for v in self.gt.get_vertex_iterator():
self.gt.set_position(v, np.array([100,100,z]))
self.gt.set_orientation(v, np.array([1,0,0]))
z += 5
if int(v)<self.gt_vertices-1:
self.gt.add_edge(int(v), int(v)+1)
self.vs_gt = VoxelSkeleton(self.gt, voxel_size=[1.,1.,1.], verbose=True, subsample=5)
z = 0
for v in self.rec1.get_vertex_iterator():
self.rec1.set_position(v, np.array([160,100, z]))
self.rec1.set_orientation(v, np.array([1,0,0]))
z += 5
if int(v)<self.rec1_vertices-1:
self.rec1.add_edge(int(v), int(v)+1)
z = 0
for v in self.rec2.get_vertex_iterator():
self.rec2.set_position(v, np.array([100,150, z]))
self.rec2.set_orientation(v, np.array([1,0,0]))
z += 5
if int(v)<self.rec2_vertices-1:
self.rec2.add_edge(int(v), int(v)+1)
self.vs_rec1 = VoxelSkeleton(self.rec1, voxel_size=[1.,1.,1.], verbose=True, subsample=5)
self.vs_rec2 = VoxelSkeleton(self.rec2, voxel_size=[1.,1.,1.], verbose=True, subsample=5)
self.groundtruth_skeletons = [self.vs_gt]
self.reconstructed_skeletons = [self.vs_rec1, self.vs_rec2]
self.skeletons = {"gt": [self.vs_gt], "rec": [self.vs_rec1, self.vs_rec2]}
self.distance_threshold = 51
self.voxel_size = [1.,1.,1.]
class MatchingGraphNoInitAllTestCase(ParallelLinesSetUp):
def runTest(self):
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=False)
self.assertTrue(mg.total_vertices ==\
self.vs_gt.get_graph().get_number_of_vertices() +\
self.vs_rec.get_graph().get_number_of_vertices())
class MatchingGraphInitializeTestCase(ParallelLinesSetUp):
def runTest(self):
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=False)
# Test private methods too as internals are complex:
matching_graph, mappings, mv_to_v, v_to_mv = mg._MatchingGraph__initialize()
self.assertTrue(matching_graph.get_number_of_vertices() ==\
mg._MatchingGraph__get_total_vertices())
self.assertTrue(matching_graph.get_number_of_edges()==0)
for tag in ["gt", "rec"]:
for graph in mg.graphs[tag]:
for v in graph.get_vertex_iterator():
mv = v_to_mv[(graph, int(v))]
pos_v = np.array(graph.get_position(v))
pos_mv = np.array(matching_graph.get_position(mv))
self.assertTrue(np.all(pos_v == pos_mv))
mv_ids_rec = mappings["rec"]["mv_ids"]
mv_ids_gt = mappings["gt"]["mv_ids"]
self.assertTrue(set(mv_ids_rec) & set(mv_ids_gt) == set([]))
self.assertTrue(sorted(mv_ids_rec + mv_ids_gt) ==\
range(matching_graph.get_number_of_vertices()))
for i in range(len(mv_ids_gt)):
mv_id = mv_ids_gt[i]
graph_pos = np.array(matching_graph.get_position(mv_id))
mapping_pos = mappings["gt"]["positions"][i]
self.assertTrue(np.all(graph_pos == mapping_pos))
for i in range(len(mv_ids_rec)):
mv_id = mv_ids_rec[i]
graph_pos = np.array(matching_graph.get_position(mv_id))
mapping_pos = mappings["rec"]["positions"][i]
self.assertTrue(np.all(graph_pos == mapping_pos))
class MatchingGraphAddSkeletonEdgesTestCase(ParallelLinesSetUp):
def runTest(self):
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=False)
matching_graph, mappings, mv_to_v, v_to_mv = mg._MatchingGraph__initialize()
mg.matching_graph = matching_graph
mg.mappings = mappings
mg.mv_to_v = mv_to_v
mg.v_to_mv = v_to_mv
self.assertTrue(matching_graph.get_number_of_edges() == 0)
mg._MatchingGraph__add_skeleton_edges()
self.assertTrue(matching_graph.get_number_of_edges() ==\
self.vs_gt.get_graph().get_number_of_edges() +\
self.vs_rec.get_graph().get_number_of_edges())
# Check that all edges are attached to the correct vertices:
for e in matching_graph.get_edge_iterator():
mv0 = e.source()
mv1 = e.target()
v0 = mv_to_v[mv0]
v1 = mv_to_v[mv1]
# Compare graphs
self.assertTrue(v0[0] == v1[0])
edge = v0[0].get_edge(v0[1], v1[1]) # Raises value error if not there
pos_v0 = np.array(v0[0].get_position(v0[1]))
pos_v1 = np.array(v0[0].get_position(v1[1]))
pos_mv0 = np.array(matching_graph.get_position(mv0))
pos_mv1 = np.array(matching_graph.get_position(mv1))
self.assertTrue(np.all(pos_v0 == pos_mv0))
self.assertTrue(np.all(pos_v1 == pos_mv1))
class MatchingGraphAddMatchingEdgesTestCase(ParallelLinesSetUp):
def runTest(self):
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=False)
matching_graph, mappings, mv_to_v, v_to_mv = mg._MatchingGraph__initialize()
mg.matching_graph = matching_graph
mg.mappings = mappings
mg.mv_to_v = mv_to_v
mg.v_to_mv = v_to_mv
mg._MatchingGraph__add_skeleton_edges()
edges_pre_add = mg.matching_graph.get_number_of_edges()
mg._MatchingGraph__add_matching_edges(self.distance_threshold, self.voxel_size)
edges_post_add = mg.matching_graph.get_number_of_edges()
self.assertTrue(edges_post_add > edges_pre_add)
mg.mask_skeleton_edges()
edges_post_masking = mg.matching_graph.get_number_of_edges()
self.assertTrue(edges_post_masking == edges_pre_add)
for e in mg.matching_graph.get_edge_iterator():
self.assertTrue(mg.get_edge_type(e) == "skeleton")
mg.clear_edge_masks()
self.assertTrue(edges_post_add == mg.matching_graph.get_number_of_edges())
mg.mask_matching_edges()
self.assertTrue(edges_post_add - edges_pre_add ==\
mg.matching_graph.get_number_of_edges())
for e in mg.matching_graph.get_edge_iterator():
self.assertTrue(mg.get_edge_type(e) == "matching")
v0_gt = mg.is_groundtruth_mv(e.source())
v1_gt = mg.is_groundtruth_mv(e.target())
self.assertTrue(int(v0_gt) != int(v1_gt))
mg.clear_edge_masks()
mg.to_nml(test_data_dir + "/matching_graph.nml")
class MatchingGraphExportToComatch(ParallelLinesSetUp):
def runTest(self):
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=True)
nodes_gt, nodes_rec, edges_gt_rec, labels_gt, labels_rec, edge_costs, edge_conflicts, edge_pairs = mg.export_to_comatch()
for v_gt in nodes_gt:
self.assertTrue(mg.is_groundtruth_mv(v_gt))
for v_rec in nodes_rec:
self.assertFalse(mg.is_groundtruth_mv(v_rec))
mg.mask_matching_edges()
self.assertTrue(len(edges_gt_rec) == mg.get_number_of_edges())
mg.clear_edge_masks()
self.assertTrue(len(nodes_gt) + len(nodes_rec) == mg.get_number_of_vertices())
class MatchingGraphImportMatches(ParallelLinesSetUp):
def runTest(self):
print "Import matches"
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=True)
nodes_gt, nodes_rec, edges_gt_rec, labels_gt, labels_rec, edge_costs, edge_conflicts, edge_pairs = mg.export_to_comatch()
label_matches, node_matches, num_splits, num_merges, num_fps, num_fns = match_components(nodes_gt, nodes_rec, edges_gt_rec, labels_gt, labels_rec)
matches = node_matches
# Everything is matched
self.assertTrue(len(matches) == mg.get_number_of_vertices()/2)
mg.import_matches(matches)
for v in mg.get_vertex_iterator():
self.assertTrue(mg.is_tp(v))
self.assertFalse(mg.is_fp(v))
self.assertFalse(mg.is_fn(v))
for e in mg.get_edge_iterator():
self.assertFalse(mg.is_split(e))
self.assertFalse(mg.is_merge(e))
class MatchingGraphExportToComatch(ParallelLinesSetUp):
def runTest(self):
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
initialize_all=True)
nodes_gt, nodes_rec, edges_gt_rec, labels_gt, labels_rec, edge_costs, edge_conflicts, edge_pairs = mg.export_to_comatch()
for v_gt in nodes_gt:
self.assertTrue(mg.is_groundtruth_mv(v_gt))
for v_rec in nodes_rec:
self.assertFalse(mg.is_groundtruth_mv(v_rec))
mg.mask_matching_edges()
self.assertTrue(len(edges_gt_rec) == mg.get_number_of_edges())
mg.clear_edge_masks()
self.assertTrue(len(nodes_gt) + len(nodes_rec) == mg.get_number_of_vertices())
class TestOneToOne(ErrorTestSetUpSameDistance):
def runTest(self):
print "OneToOne"
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
distance_cost=True,
initialize_all=True)
nodes_gt, nodes_rec, edges_gt_rec, labels_gt, labels_rec, edge_costs, edge_conflicts, edge_pairs = mg.export_to_comatch()
try:
# Quadmatch
label_matches, node_matches, num_splits, num_merges, num_fps, num_fns = match_components(nodes_gt, nodes_rec, edges_gt_rec, labels_gt,
labels_rec, edge_conflicts=edge_conflicts, max_edges=1, edge_costs=edge_costs)
except TypeError:
# Comatch
label_matches, node_matches, num_splits, num_merges, num_fps, num_fns = match_components(nodes_gt, nodes_rec, edges_gt_rec, labels_gt,
labels_rec, allow_many_to_many=False, edge_costs=edge_costs, no_match_costs=1000.)
print "label matches:", label_matches
print "node_matches:", node_matches
comatch_errors = {"splits": num_splits, "num_merges": num_merges, "num_fps": num_fps, "num_fns": num_fns}
print comatch_errors
mg.import_matches(node_matches)
output_dir = test_data_dir + "/MatchingOnetoOne"
mg.export_all(output_dir)
with open(output_dir + "/macro_errors.json", "w+") as f:
json.dump(comatch_errors, f)
class TestManyToMany(ErrorTestSetUpSameDistance):
def runTest(self):
print "ManyToMany"
mg = MatchingGraph(self.groundtruth_skeletons,
self.reconstructed_skeletons,
self.distance_threshold,
self.voxel_size,
verbose=True,
distance_cost=True,
initialize_all=True)
nodes_gt, nodes_rec, edges_gt_rec, labels_gt, labels_rec, edge_costs, edge_conflicts, edge_pairs = mg.export_to_comatch()
try:
# Quadmatch
label_matches, node_matches, num_splits, num_merges, num_fps, num_fns = match_components(nodes_gt, nodes_rec, edges_gt_rec, labels_gt,
labels_rec, edge_conflicts=edge_conflicts, max_edges=10, edge_costs=edge_costs)
except TypeError:
# Comatch
label_matches, node_matches, num_splits, num_merges, num_fps, num_fns = match_components(nodes_gt, nodes_rec, edges_gt_rec, labels_gt,
labels_rec, allow_many_to_many=True, edge_costs=edge_costs, no_match_costs=1000.)
print "label matches:", label_matches
print "node_matches:", node_matches
comatch_errors = {"splits": num_splits, "num_merges": num_merges, "num_fps": num_fps, "num_fns": num_fns}
print comatch_errors
mg.import_matches(node_matches)
output_dir = test_data_dir + "/MatchingManytoMany"
mg.export_all(output_dir)
with open(output_dir + "/macro_errors.json", "w+") as f:
json.dump(comatch_errors, f)
if __name__ == "__main__":
unittest.main()
| 38.399061 | 183 | 0.578127 | 1,950 | 16,358 | 4.528718 | 0.094359 | 0.044389 | 0.023667 | 0.025365 | 0.771487 | 0.720303 | 0.681916 | 0.650323 | 0.632997 | 0.609218 | 0 | 0.016658 | 0.324734 | 16,358 | 425 | 184 | 38.489412 | 0.782817 | 0.014183 | 0 | 0.568493 | 0 | 0 | 0.020643 | 0 | 0 | 0 | 0 | 0 | 0.116438 | 0 | null | null | 0 | 0.041096 | null | null | 0.030822 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
3043145d544f46f022747e55bca435bd3cfd11fa | 133 | py | Python | src/a01/communication.py | mcardosos/adx-automation-client | d657ff85b0f0e408e5c64703c47798d164f49a35 | [
"MIT"
] | 3 | 2018-02-28T06:22:39.000Z | 2020-05-20T12:39:00.000Z | src/a01/communication.py | mcardosos/adx-automation-client | d657ff85b0f0e408e5c64703c47798d164f49a35 | [
"MIT"
] | 19 | 2018-02-26T21:13:43.000Z | 2018-05-02T16:33:35.000Z | src/a01/communication.py | mcardosos/adx-automation-client | d657ff85b0f0e408e5c64703c47798d164f49a35 | [
"MIT"
] | 6 | 2018-02-26T18:10:31.000Z | 2020-12-30T10:21:31.000Z | import requests
from a01.auth import A01Auth
session = requests.Session() # pylint: disable=invalid-name
session.auth = A01Auth()
| 19 | 60 | 0.766917 | 17 | 133 | 6 | 0.647059 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.052174 | 0.135338 | 133 | 6 | 61 | 22.166667 | 0.834783 | 0.210526 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
304caab2fd293dcea3ce7502cec96c166db7a553 | 187 | py | Python | system/widget.py | ywchiao/shot | 4b7c55bdcca44d05e07fffa59fe4e23364032cb5 | [
"MIT"
] | null | null | null | system/widget.py | ywchiao/shot | 4b7c55bdcca44d05e07fffa59fe4e23364032cb5 | [
"MIT"
] | null | null | null | system/widget.py | ywchiao/shot | 4b7c55bdcca44d05e07fffa59fe4e23364032cb5 | [
"MIT"
] | 1 | 2020-03-27T02:07:27.000Z | 2020-03-27T02:07:27.000Z |
from .system import System
from logcat import LogCat
class Widget(System):
def __init__(self):
super().__init__()
self.on("cmd_render", self._render)
# widget.py
| 14.384615 | 43 | 0.663102 | 24 | 187 | 4.75 | 0.583333 | 0.140351 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.224599 | 187 | 12 | 44 | 15.583333 | 0.786207 | 0.048128 | 0 | 0 | 0 | 0 | 0.057143 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.666667 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
305a285236c3e11d999251641ede1bf722d4ce33 | 211 | py | Python | web/app/conf/__init__.py | kvikshaug/btc.kvikshaug.no | a353096db9edf7ef0aa44e77c367c96b73fbfe6f | [
"Unlicense"
] | null | null | null | web/app/conf/__init__.py | kvikshaug/btc.kvikshaug.no | a353096db9edf7ef0aa44e77c367c96b73fbfe6f | [
"Unlicense"
] | null | null | null | web/app/conf/__init__.py | kvikshaug/btc.kvikshaug.no | a353096db9edf7ef0aa44e77c367c96b73fbfe6f | [
"Unlicense"
] | null | null | null | import importlib
import os
conf_module = importlib.import_module("conf.%s" % os.environ['CONFIGURATION'])
settings = {
key: getattr(conf_module, key)
for key in dir(conf_module)
if key.isupper()
}
| 19.181818 | 78 | 0.706161 | 29 | 211 | 5 | 0.551724 | 0.206897 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.170616 | 211 | 10 | 79 | 21.1 | 0.828571 | 0 | 0 | 0 | 0 | 0 | 0.094787 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.375 | 0 | 0.375 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
0630137217338e4305c7a3e00109299b6cd31cc9 | 133 | py | Python | src/rstatmon/session_manager.py | git-ogawa/raspi-statmon | 619d7a8f697cad92437e2f558de2e0a626b5072f | [
"BSD-3-Clause"
] | null | null | null | src/rstatmon/session_manager.py | git-ogawa/raspi-statmon | 619d7a8f697cad92437e2f558de2e0a626b5072f | [
"BSD-3-Clause"
] | null | null | null | src/rstatmon/session_manager.py | git-ogawa/raspi-statmon | 619d7a8f697cad92437e2f558de2e0a626b5072f | [
"BSD-3-Clause"
] | null | null | null | from flask import session
class Session():
@staticmethod
def set_session(key: str, value):
session[key] = value
| 12.090909 | 37 | 0.646617 | 16 | 133 | 5.3125 | 0.6875 | 0.235294 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.263158 | 133 | 10 | 38 | 13.3 | 0.867347 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0.2 | 0 | 0.6 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
063c305a923cd42896c01fbe6e2e8a0cb43f9912 | 452 | py | Python | excript/aulas/aula26_concatena.py | victorers1/anotacoes_curso_python | c4ef56bcfc7e3baa3944fc2962e8217c6d720b0e | [
"MIT"
] | null | null | null | excript/aulas/aula26_concatena.py | victorers1/anotacoes_curso_python | c4ef56bcfc7e3baa3944fc2962e8217c6d720b0e | [
"MIT"
] | null | null | null | excript/aulas/aula26_concatena.py | victorers1/anotacoes_curso_python | c4ef56bcfc7e3baa3944fc2962e8217c6d720b0e | [
"MIT"
] | null | null | null | num_int = 5
num_dec = 7.3
val_str = "texto qualquer "
print("Primeiro número é:", num_int)
print("O poder do Kakaroto é mais de %i mil" %num_dec)
print("Olá mundo " + val_str + str(num_int))
print("Concatenando decimal:", num_dec)
print("Concatenando decimal: %.10f" %num_dec)
print("Concatenando decimal: " + str(num_dec))
print("Concatenando strings:", val_str)
print("Concatenando strings: %s" %val_str)
print("Concatenando strings: " + val_str) | 30.133333 | 55 | 0.721239 | 70 | 452 | 4.471429 | 0.414286 | 0.325879 | 0.140575 | 0.220447 | 0.479233 | 0 | 0 | 0 | 0 | 0 | 0 | 0.012723 | 0.130531 | 452 | 15 | 56 | 30.133333 | 0.783715 | 0 | 0 | 0 | 0 | 0 | 0.476821 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.75 | 0 | 0 | 0 | null | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
066e5fb8233dc5224d22ebf3b89a9a83782274aa | 745 | py | Python | TITADOweb/web/migrations/0005_passwordresetcodes.py | KomeilParseh/TITA-DO | 714685fa18bfd2ef07f5c0d656927039b05d7997 | [
"MIT"
] | 9 | 2020-08-27T10:10:11.000Z | 2021-04-21T04:46:15.000Z | TITADOweb/web/migrations/0005_passwordresetcodes.py | mdk1384/TITA-DO-1 | 714685fa18bfd2ef07f5c0d656927039b05d7997 | [
"MIT"
] | 2 | 2020-08-27T12:09:57.000Z | 2021-01-05T09:29:19.000Z | TITADOweb/web/migrations/0005_passwordresetcodes.py | mdk1384/TITA-DO-1 | 714685fa18bfd2ef07f5c0d656927039b05d7997 | [
"MIT"
] | 2 | 2020-08-27T10:10:18.000Z | 2021-01-01T06:20:20.000Z | # Generated by Django 3.1.4 on 2020-12-27 17:34
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('web', '0004_token'),
]
operations = [
migrations.CreateModel(
name='Passwordresetcodes',
fields=[
('id', models.AutoField(auto_created=True, primary_key=True, serialize=False, verbose_name='ID')),
('code', models.CharField(max_length=32)),
('email', models.CharField(max_length=120)),
('time', models.DateTimeField()),
('username', models.CharField(max_length=50)),
('password', models.CharField(max_length=50)),
],
),
]
| 29.8 | 114 | 0.561074 | 73 | 745 | 5.616438 | 0.684932 | 0.146341 | 0.17561 | 0.234146 | 0.126829 | 0 | 0 | 0 | 0 | 0 | 0 | 0.053537 | 0.297987 | 745 | 24 | 115 | 31.041667 | 0.730402 | 0.060403 | 0 | 0 | 1 | 0 | 0.091691 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.111111 | 0.055556 | 0 | 0.222222 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
069a8d7c6fbb5a8f120cebac621c759b5b2c0718 | 233 | py | Python | article_retrieval/__main__.py | aleph-oh/wikigame-solver | 9a7b0a16df41291890e2bbe5903be55b25cef0f4 | [
"MIT"
] | null | null | null | article_retrieval/__main__.py | aleph-oh/wikigame-solver | 9a7b0a16df41291890e2bbe5903be55b25cef0f4 | [
"MIT"
] | null | null | null | article_retrieval/__main__.py | aleph-oh/wikigame-solver | 9a7b0a16df41291890e2bbe5903be55b25cef0f4 | [
"MIT"
] | null | null | null | #!/usr/bin/env python3
"""Constructs article graph."""
from database import clear_db
from database.constants import engine
from .database_builder import populate_db
if __name__ == "__main__":
clear_db(engine)
populate_db()
| 21.181818 | 41 | 0.759657 | 31 | 233 | 5.290323 | 0.612903 | 0.219512 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005 | 0.141631 | 233 | 10 | 42 | 23.3 | 0.815 | 0.201717 | 0 | 0 | 0 | 0 | 0.044444 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
06a458881d352d1e5bc5252e5c9354f711ebe5e6 | 208 | py | Python | src_old/tests/scripts/core/ex7.py | toddrme2178/pyccel | deec37503ab0c5d0bcca1a035f7909f7ce8ef653 | [
"MIT"
] | null | null | null | src_old/tests/scripts/core/ex7.py | toddrme2178/pyccel | deec37503ab0c5d0bcca1a035f7909f7ce8ef653 | [
"MIT"
] | null | null | null | src_old/tests/scripts/core/ex7.py | toddrme2178/pyccel | deec37503ab0c5d0bcca1a035f7909f7ce8ef653 | [
"MIT"
] | null | null | null | #coding: utf-8
a = zeros((10,10), double)
for i in range(0,10):
a[i,i] = 2.0
for i in range(0,9):
a[i,i+1] = -1.0
for i in range(0,9):
a[i,i+1] = -1.0
n = 5
for i in range(0, n):
x = 1
| 10.947368 | 26 | 0.480769 | 53 | 208 | 1.886792 | 0.339623 | 0.16 | 0.24 | 0.44 | 0.63 | 0.39 | 0.39 | 0.39 | 0.39 | 0.39 | 0 | 0.156463 | 0.293269 | 208 | 18 | 27 | 11.555556 | 0.52381 | 0.0625 | 0 | 0.4 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
06abef330b43336341fe87f19a5bb8dd00ab85db | 252 | py | Python | driver/comtypes_gamry_simulate.py | yul69-cell/HELAO | a39372eb385ee93b711443d9cbd56c5ec737ff70 | [
"CC0-1.0"
] | null | null | null | driver/comtypes_gamry_simulate.py | yul69-cell/HELAO | a39372eb385ee93b711443d9cbd56c5ec737ff70 | [
"CC0-1.0"
] | null | null | null | driver/comtypes_gamry_simulate.py | yul69-cell/HELAO | a39372eb385ee93b711443d9cbd56c5ec737ff70 | [
"CC0-1.0"
] | null | null | null | #create cinet and functions like COMError that simulate Gamry
#dtaq.Cook is defined to return dummy data when called
#import config here and check if a simulation is being run and if so load that simulation .py that overrides functions like dtaq.Cook | 50.4 | 133 | 0.809524 | 43 | 252 | 4.744186 | 0.744186 | 0.127451 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 252 | 5 | 133 | 50.4 | 0.971429 | 0.972222 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 0 | null | 1 | null | true | 0 | 0 | null | null | null | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
06af2b443d404bade0c4526a7994135505c898f7 | 737 | py | Python | kelte/maths/vector.py | brianbruggeman/rl | 6dd8a53da07697ffc87e62aa397be7b3b08f0aa0 | [
"MIT"
] | null | null | null | kelte/maths/vector.py | brianbruggeman/rl | 6dd8a53da07697ffc87e62aa397be7b3b08f0aa0 | [
"MIT"
] | null | null | null | kelte/maths/vector.py | brianbruggeman/rl | 6dd8a53da07697ffc87e62aa397be7b3b08f0aa0 | [
"MIT"
] | null | null | null | from dataclasses import dataclass, field
from .point import Point
@dataclass()
class Direction(Point):
x: int = 0
y: int = 0
NONE: Direction = Direction(0, 0)
NORTH: Direction = Direction(0, -1)
SOUTH: Direction = Direction(0, 1)
EAST: Direction = Direction(1, 0)
WEST: Direction = Direction(-1, 0)
NORTH_EAST: Direction = NORTH + EAST
NORTH_WEST: Direction = NORTH + WEST
SOUTH_EAST: Direction = SOUTH + EAST
SOUTH_WEST: Direction = SOUTH + WEST
UP: Direction = Direction(0, -1)
DOWN: Direction = Direction(0, 1)
RIGHT: Direction = Direction(1, 0)
LEFT: Direction = Direction(-1, 0)
UP_RIGHT: Direction = UP + RIGHT
UP_LEFT: Direction = UP + LEFT
DOWN_RIGHT: Direction = DOWN + RIGHT
DOWN_LEFT: Direction = DOWN + LEFT
| 22.333333 | 40 | 0.708277 | 104 | 737 | 4.942308 | 0.211538 | 0.315175 | 0.184825 | 0.155642 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.032949 | 0.176391 | 737 | 32 | 41 | 23.03125 | 0.813839 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.086957 | 0 | 0.217391 | 0 | 0 | 0 | 0 | null | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
2311235022e84d72f4d0c26645f17bee8edd6070 | 1,615 | py | Python | statzcw/stats.py | xt0fer/Py21-BasicStats | 5e747765e58092d014fb36e66e2c4d623b1dbcba | [
"MIT"
] | null | null | null | statzcw/stats.py | xt0fer/Py21-BasicStats | 5e747765e58092d014fb36e66e2c4d623b1dbcba | [
"MIT"
] | null | null | null | statzcw/stats.py | xt0fer/Py21-BasicStats | 5e747765e58092d014fb36e66e2c4d623b1dbcba | [
"MIT"
] | 1 | 2021-07-11T14:50:21.000Z | 2021-07-11T14:50:21.000Z |
from typing import List
def zcount(list: List[float]) -> float:
return len(list)
# print("stats test")
# print("zcount should be 5 ==", zcount([1.0,2.0,3.0,4.0,5.0]))
def zmean(list: List[float]) -> float:
return sum(list) / zcount(list)
def zmode(list: List[float]) -> float:
return max(set(list), key = list.count)
def zmedian(list: List[float]) -> float:
sortedLst = sorted(list)
lstLen = len(list)
index = (lstLen - 1) // 2
if (lstLen % 2):
return sortedLst[index]
else:
return (sortedLst[index] + sortedLst[index + 1])/2.0
def zvariance(list: List[float]) -> float:
# Number of observations
n = zcount(list) - 1
# Mean of the data
#mean = sum(data) / n
mean = zmean(list)
# Square deviations
deviations = [abs(mean - xi) ** 2 for xi in list]
# Variance
variance = sum(deviations) / n
return variance
def zstddev(list: List[float]) -> float:
return 0.0
def zstderr(list: List[float]) -> float:
return 0.0
def zcov(a, b):
pass
def zcorr(listx: List[float], listy: List[float]) -> float:
return 0.0
def readDataSets(files):
# print("in readDataSets...", files)
data = {}
for file in files:
twoLists = readDataFile(file)
data[file] = twoLists
return data
def readDataFile(file):
x,y = [], []
with open(file) as f:
first_line = f.readline() # consume headers
for l in f:
row = l.split(',')
#print(row, type(row))
x.append(float(row[0]))
y.append(float(row[1]))
return (x,y)
| 23.071429 | 63 | 0.577709 | 224 | 1,615 | 4.160714 | 0.352679 | 0.08691 | 0.120172 | 0.135193 | 0.166309 | 0.089056 | 0.089056 | 0.062232 | 0 | 0 | 0 | 0.022959 | 0.271827 | 1,615 | 69 | 64 | 23.405797 | 0.769558 | 0.150464 | 0 | 0.068182 | 0 | 0 | 0.000735 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0.022727 | 0.022727 | 0.136364 | 0.522727 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
2316d7baa946659edc0058ea0663bc1e4f77f7ab | 14 | py | Python | getv/__init__.py | FUNNYDMAN/getv | b0c495c9c9b9dea8bff86916aee85ecac4f505ab | [
"MIT"
] | 1 | 2018-08-07T18:50:43.000Z | 2018-08-07T18:50:43.000Z | getv/__init__.py | FUNNYDMAN/getv | b0c495c9c9b9dea8bff86916aee85ecac4f505ab | [
"MIT"
] | null | null | null | getv/__init__.py | FUNNYDMAN/getv | b0c495c9c9b9dea8bff86916aee85ecac4f505ab | [
"MIT"
] | null | null | null | name = "getv"
| 7 | 13 | 0.571429 | 2 | 14 | 4 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.214286 | 14 | 1 | 14 | 14 | 0.727273 | 0 | 0 | 0 | 0 | 0 | 0.285714 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
231e10107f5e6e0ebcb3429683ae08fd50e51f90 | 162 | py | Python | collections/employee.py | learning-foundation/python-oo-ds | 58c212da4562f65f99c8df24bff7667744ea552b | [
"MIT"
] | null | null | null | collections/employee.py | learning-foundation/python-oo-ds | 58c212da4562f65f99c8df24bff7667744ea552b | [
"MIT"
] | null | null | null | collections/employee.py | learning-foundation/python-oo-ds | 58c212da4562f65f99c8df24bff7667744ea552b | [
"MIT"
] | null | null | null | class Employee():
def __init__(self, name, doc_number, salary):
self._name = name
self._doc_number = doc_number
self._salary = salary | 27 | 49 | 0.635802 | 20 | 162 | 4.65 | 0.45 | 0.290323 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.271605 | 162 | 6 | 50 | 27 | 0.788136 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | false | 0 | 0 | 0 | 0.4 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
23294fabdcf63ba5d2ca1685c4bb3c0849350f0e | 207 | py | Python | game_test.py | jakub530/PyGame-Neural-Net | 6f592ee97d97470cddc6599203c9a5d9759905c4 | [
"MIT"
] | null | null | null | game_test.py | jakub530/PyGame-Neural-Net | 6f592ee97d97470cddc6599203c9a5d9759905c4 | [
"MIT"
] | null | null | null | game_test.py | jakub530/PyGame-Neural-Net | 6f592ee97d97470cddc6599203c9a5d9759905c4 | [
"MIT"
] | null | null | null | import sys, pygame,math
import numpy as np
from pygame import gfxdraw
import pygame_lib, nn_lib
import pygame.freetype
from pygame_lib import color
import random
import copy
import auto_maze
import node_vis | 20.7 | 28 | 0.845411 | 35 | 207 | 4.857143 | 0.542857 | 0.117647 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.135266 | 207 | 10 | 29 | 20.7 | 0.949721 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
233e938c1235975c31635e57391932a8a3358fab | 692 | py | Python | tests/tf_tests/functional/test_tf_inference.py | Deeplite/deeplite-profiler | 2b21c0dc5948606c47377f786b605baf4fa31bee | [
"Apache-2.0"
] | 17 | 2021-04-13T06:09:52.000Z | 2021-11-24T06:39:41.000Z | tests/tf_tests/functional/test_tf_inference.py | Deeplite/deeplite-profiler | 2b21c0dc5948606c47377f786b605baf4fa31bee | [
"Apache-2.0"
] | 14 | 2021-04-14T13:46:42.000Z | 2021-12-20T21:10:25.000Z | tests/tf_tests/functional/test_tf_inference.py | Deeplite/deeplite-profiler | 2b21c0dc5948606c47377f786b605baf4fa31bee | [
"Apache-2.0"
] | 7 | 2021-04-09T16:47:56.000Z | 2022-03-05T11:04:30.000Z | import pytest
from tests.tf_tests.functional import BaseFunctionalTest, TENSORFLOW_SUPPORTED, TENSORFLOW_AVAILABLE, MODEL, DATA
class TestTFInference(BaseFunctionalTest):
def test_get_acc(self):
from deeplite.tf_profiler.tf_inference import get_accuracy
assert get_accuracy(MODEL, DATA['test']) < 100
def test_get_topk(self):
from deeplite.tf_profiler.tf_inference import get_topk
assert len(get_topk(MODEL, DATA['test'])) == 2
assert len(get_topk(MODEL, DATA['test'], topk=1)) == 1
def test_get_missclass(self):
from deeplite.tf_profiler.tf_inference import get_missclass
assert get_missclass(MODEL, DATA['test']) > 0
| 36.421053 | 113 | 0.728324 | 92 | 692 | 5.23913 | 0.336957 | 0.093361 | 0.107884 | 0.112033 | 0.406639 | 0.406639 | 0.406639 | 0.286307 | 0.286307 | 0 | 0 | 0.012324 | 0.179191 | 692 | 18 | 114 | 38.444444 | 0.836268 | 0 | 0 | 0 | 0 | 0 | 0.023188 | 0 | 0 | 0 | 0 | 0 | 0.307692 | 1 | 0.230769 | false | 0 | 0.384615 | 0 | 0.692308 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
23549dd532a597635dde1ce83730aec62792e9bd | 200 | py | Python | waymo_open_dataset/latency/examples/tensorflow/multiframe/wod_latency_submission/__init__.py | mirtaheri/waymo-open-dataset | 16c6a1a98fa8bb005fdfe798d27e6f3edf98c356 | [
"Apache-2.0"
] | 1,814 | 2019-08-20T18:30:38.000Z | 2022-03-31T04:14:51.000Z | waymo_open_dataset/latency/examples/tensorflow/multiframe/wod_latency_submission/__init__.py | mirtaheri/waymo-open-dataset | 16c6a1a98fa8bb005fdfe798d27e6f3edf98c356 | [
"Apache-2.0"
] | 418 | 2019-08-20T22:38:02.000Z | 2022-03-31T07:51:15.000Z | waymo_open_dataset/latency/examples/tensorflow/multiframe/wod_latency_submission/__init__.py | mirtaheri/waymo-open-dataset | 16c6a1a98fa8bb005fdfe798d27e6f3edf98c356 | [
"Apache-2.0"
] | 420 | 2019-08-21T10:59:06.000Z | 2022-03-31T08:31:44.000Z | """Example __init__.py to wrap the wod_latency_submission module imports."""
from . import model
initialize_model = model.initialize_model
run_model = model.run_model
DATA_FIELDS = model.DATA_FIELDS
| 28.571429 | 76 | 0.815 | 29 | 200 | 5.206897 | 0.62069 | 0.198676 | 0.264901 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.11 | 200 | 6 | 77 | 33.333333 | 0.848315 | 0.35 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.25 | 0 | 0.25 | 0 | 1 | 0 | 0 | null | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
23793e314023b1afee56b5645d0f4bbfd1a679ef | 1,098 | py | Python | jaxvi/models.py | sagar87/jaxvi | 78829552589f8d44082cf8a1a8e02da549d7c298 | [
"MIT"
] | null | null | null | jaxvi/models.py | sagar87/jaxvi | 78829552589f8d44082cf8a1a8e02da549d7c298 | [
"MIT"
] | null | null | null | jaxvi/models.py | sagar87/jaxvi | 78829552589f8d44082cf8a1a8e02da549d7c298 | [
"MIT"
] | null | null | null | from abc import abstractmethod
from jaxvi.abstract import ABCMeta, abstract_attribute
import jax.numpy as jnp
from jax.scipy.stats import norm, gamma
class Model(metaclass=ABCMeta):
@abstract_attribute
def latent_dim(self):
pass
@abstractmethod
def inv_T(self, zeta: jnp.DeviceArray) -> jnp.DeviceArray:
pass
@abstractmethod
def log_joint(self, theta: jnp.DeviceArray) -> jnp.DeviceArray:
pass
class LinearRegression(Model):
def __init__(self, x, y):
self.x = x
self.y = y
self.latent_dim = x.shape[1] + 1
def inv_T(self, zeta: jnp.DeviceArray) -> jnp.DeviceArray:
return jnp.append(zeta[:-1], jnp.exp(zeta[-1]))
def log_joint(self, theta: jnp.DeviceArray) -> jnp.DeviceArray:
betas = theta[:2]
sigma = theta[2]
beta_prior = norm.logpdf(betas, 0, 10).sum()
sigma_prior = gamma.logpdf(sigma, a=1, scale=2).sum()
yhat = jnp.inner(self.x, betas)
likelihood = norm.logpdf(self.y, yhat, sigma).sum()
return beta_prior + sigma_prior + likelihood
| 27.45 | 67 | 0.644809 | 148 | 1,098 | 4.675676 | 0.364865 | 0.16185 | 0.098266 | 0.16185 | 0.274566 | 0.263006 | 0.263006 | 0.263006 | 0.263006 | 0 | 0 | 0.013142 | 0.237705 | 1,098 | 39 | 68 | 28.153846 | 0.81362 | 0 | 0 | 0.310345 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.206897 | false | 0.103448 | 0.137931 | 0.034483 | 0.482759 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 3 |
2381e2b9c699c0ba9541e7eef0d109d8c8508180 | 121 | py | Python | setup.py | m0hithreddy/rpyc-mem | 72e46da34fe2165a89d702a02ec0bb7b6d64775e | [
"MIT"
] | 1 | 2022-03-12T23:29:13.000Z | 2022-03-12T23:29:13.000Z | setup.py | m0hithreddy/rpyc-mem | 72e46da34fe2165a89d702a02ec0bb7b6d64775e | [
"MIT"
] | null | null | null | setup.py | m0hithreddy/rpyc-mem | 72e46da34fe2165a89d702a02ec0bb7b6d64775e | [
"MIT"
] | null | null | null | from setuptools import setup
setup(
version=open("rpyc_mem/_version.py").readlines()[-1].split()[-1].strip("\"'")
)
| 20.166667 | 81 | 0.661157 | 16 | 121 | 4.875 | 0.8125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.018349 | 0.099174 | 121 | 5 | 82 | 24.2 | 0.697248 | 0 | 0 | 0 | 0 | 0 | 0.173554 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.25 | 0 | 0.25 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
88bea4fa9c19bdca4e8c6da218e8d49f1310845f | 240 | py | Python | api_ui/views.py | mihail-ivanov/base-vue-api | a2ef8ae360d3d26425093aefaf521082cf3684c5 | [
"MIT"
] | null | null | null | api_ui/views.py | mihail-ivanov/base-vue-api | a2ef8ae360d3d26425093aefaf521082cf3684c5 | [
"MIT"
] | null | null | null | api_ui/views.py | mihail-ivanov/base-vue-api | a2ef8ae360d3d26425093aefaf521082cf3684c5 | [
"MIT"
] | null | null | null |
from django.contrib.auth.models import User
from rest_framework import generics
from .serializers import UserSerializer
class UserList(generics.ListCreateAPIView):
queryset = User.objects.all()
serializer_class = UserSerializer
| 21.818182 | 43 | 0.808333 | 27 | 240 | 7.111111 | 0.703704 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 240 | 10 | 44 | 24 | 0.923077 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
88e195f25d51cac398d0cfdc139ce3c46cd5aeca | 257 | py | Python | prototype/zlua_prototype/tests/test_debugger.py | Zolo-mario/ZoloLua | 7527a78b12c3f97cb729327d4d0c724f3dba17f9 | [
"MIT"
] | 9 | 2019-03-11T04:43:03.000Z | 2019-05-12T08:33:31.000Z | prototype/zlua_prototype/tests/test_debugger.py | zoloypzuo/ZeloLua | 7527a78b12c3f97cb729327d4d0c724f3dba17f9 | [
"MIT"
] | 2 | 2019-04-10T05:20:45.000Z | 2019-06-02T13:56:39.000Z | prototype/zlua_prototype/tests/test_debugger.py | Zolo-mario/zlua | 7527a78b12c3f97cb729327d4d0c724f3dba17f9 | [
"MIT"
] | 1 | 2021-12-29T03:13:49.000Z | 2021-12-29T03:13:49.000Z | from unittest import TestCase
class TestDebugger(TestCase):
def test_execute(self):
# self.fail()
pass
def test_parse_instr(self):
from zlua_prototype.debugger import _parse_instr
assert _parse_instr('f ')==('f','') | 25.7 | 56 | 0.657588 | 31 | 257 | 5.193548 | 0.612903 | 0.186335 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.237354 | 257 | 10 | 57 | 25.7 | 0.821429 | 0.042802 | 0 | 0 | 0 | 0 | 0.012245 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 1 | 0.285714 | false | 0.142857 | 0.285714 | 0 | 0.714286 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
88ef9a2c09c1a2b19ed7b65cb09a3ea45e5657d4 | 4,023 | py | Python | stubs.min/Rhino/Geometry/__init___parts/Rectangle3d.py | ricardyn/ironpython-stubs | 4d2b405eda3ceed186e8adca55dd97c332c6f49d | [
"MIT"
] | 1 | 2021-02-02T13:39:16.000Z | 2021-02-02T13:39:16.000Z | stubs.min/Rhino/Geometry/__init___parts/Rectangle3d.py | hdm-dt-fb/ironpython-stubs | 4d2b405eda3ceed186e8adca55dd97c332c6f49d | [
"MIT"
] | null | null | null | stubs.min/Rhino/Geometry/__init___parts/Rectangle3d.py | hdm-dt-fb/ironpython-stubs | 4d2b405eda3ceed186e8adca55dd97c332c6f49d | [
"MIT"
] | null | null | null | class Rectangle3d(object,IEpsilonComparable[Rectangle3d]):
"""
Rectangle3d(plane: Plane,width: float,height: float)
Rectangle3d(plane: Plane,width: Interval,height: Interval)
Rectangle3d(plane: Plane,cornerA: Point3d,cornerB: Point3d)
"""
def ClosestPoint(self,point,includeInterior=None):
"""
ClosestPoint(self: Rectangle3d,point: Point3d,includeInterior: bool) -> Point3d
ClosestPoint(self: Rectangle3d,point: Point3d) -> Point3d
"""
pass
def Contains(self,*__args):
"""
Contains(self: Rectangle3d,x: float,y: float) -> PointContainment
Contains(self: Rectangle3d,pt: Point3d) -> PointContainment
"""
pass
def Corner(self,index):
""" Corner(self: Rectangle3d,index: int) -> Point3d """
pass
@staticmethod
def CreateFromPolyline(polyline,deviation=None,angleDeviation=None):
"""
CreateFromPolyline(polyline: IEnumerable[Point3d]) -> (Rectangle3d,float,float)
CreateFromPolyline(polyline: IEnumerable[Point3d]) -> Rectangle3d
"""
pass
def EpsilonEquals(self,other,epsilon):
""" EpsilonEquals(self: Rectangle3d,other: Rectangle3d,epsilon: float) -> bool """
pass
def MakeIncreasing(self):
""" MakeIncreasing(self: Rectangle3d) """
pass
def PointAt(self,*__args):
"""
PointAt(self: Rectangle3d,t: float) -> Point3d
PointAt(self: Rectangle3d,x: float,y: float) -> Point3d
"""
pass
def RecenterPlane(self,*__args):
""" RecenterPlane(self: Rectangle3d,origin: Point3d)RecenterPlane(self: Rectangle3d,index: int) """
pass
def ToNurbsCurve(self):
""" ToNurbsCurve(self: Rectangle3d) -> NurbsCurve """
pass
def ToPolyline(self):
""" ToPolyline(self: Rectangle3d) -> Polyline """
pass
def Transform(self,xform):
""" Transform(self: Rectangle3d,xform: Transform) -> bool """
pass
def __init__(self,*args):
""" x.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signaturex.__init__(...) initializes x; see x.__class__.__doc__ for signature """
pass
@staticmethod
def __new__(self,plane,*__args):
"""
__new__[Rectangle3d]() -> Rectangle3d
__new__(cls: type,plane: Plane,width: float,height: float)
__new__(cls: type,plane: Plane,width: Interval,height: Interval)
__new__(cls: type,plane: Plane,cornerA: Point3d,cornerB: Point3d)
"""
pass
def __reduce_ex__(self,*args):
pass
def __repr__(self,*args):
""" __repr__(self: object) -> str """
pass
def __str__(self,*args):
pass
Area=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Area(self: Rectangle3d) -> float
"""
BoundingBox=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: BoundingBox(self: Rectangle3d) -> BoundingBox
"""
Center=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Center(self: Rectangle3d) -> Point3d
"""
Circumference=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Circumference(self: Rectangle3d) -> float
"""
Height=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Height(self: Rectangle3d) -> float
"""
IsValid=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: IsValid(self: Rectangle3d) -> bool
"""
Plane=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Plane(self: Rectangle3d) -> Plane
Set: Plane(self: Rectangle3d)=value
"""
Width=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Width(self: Rectangle3d) -> float
"""
X=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: X(self: Rectangle3d) -> Interval
Set: X(self: Rectangle3d)=value
"""
Y=property(lambda self: object(),lambda self,v: None,lambda self: None)
"""Get: Y(self: Rectangle3d) -> Interval
Set: Y(self: Rectangle3d)=value
"""
Unset=None
| 31.186047 | 215 | 0.679592 | 457 | 4,023 | 5.796499 | 0.161926 | 0.11325 | 0.06795 | 0.0906 | 0.436769 | 0.362023 | 0.254058 | 0.254058 | 0.254058 | 0.254058 | 0 | 0.015811 | 0.166791 | 4,023 | 128 | 216 | 31.429688 | 0.774463 | 0.387025 | 0 | 0.391304 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.347826 | false | 0.347826 | 0 | 0 | 0.608696 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
00375bfd9ff84622fa3d819bbee6225d14901c17 | 97 | py | Python | Streamlit_DEMO/Text_input.py | ysraell/examples | b41df16ddda3db2cbafc4e4c85ac9bd5d000d375 | [
"BSD-3-Clause"
] | 7 | 2020-06-11T19:15:29.000Z | 2021-01-31T22:04:56.000Z | Streamlit_DEMO/Text_input.py | ysraell/examples | b41df16ddda3db2cbafc4e4c85ac9bd5d000d375 | [
"BSD-3-Clause"
] | 2 | 2019-12-30T13:09:07.000Z | 2020-06-22T03:14:28.000Z | Streamlit_DEMO/Text_input.py | ysraell/examples | b41df16ddda3db2cbafc4e4c85ac9bd5d000d375 | [
"BSD-3-Clause"
] | 3 | 2020-06-15T18:17:53.000Z | 2020-06-22T20:32:33.000Z | import streamlit as st
title = st.text_input("Search:", "")
st.write("You search for: ", title)
| 19.4 | 36 | 0.680412 | 15 | 97 | 4.333333 | 0.733333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.14433 | 97 | 4 | 37 | 24.25 | 0.783133 | 0 | 0 | 0 | 0 | 0 | 0.237113 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
003ca20243cae85d6e1700ea19f81a8feb7a525d | 36 | py | Python | clarity/Alignment/__init__.py | wjguan/phenocell | 80ff7a0b5cc9e1ecedd8fe488b81a3df120096d9 | [
"MIT"
] | null | null | null | clarity/Alignment/__init__.py | wjguan/phenocell | 80ff7a0b5cc9e1ecedd8fe488b81a3df120096d9 | [
"MIT"
] | null | null | null | clarity/Alignment/__init__.py | wjguan/phenocell | 80ff7a0b5cc9e1ecedd8fe488b81a3df120096d9 | [
"MIT"
] | null | null | null | __all__ = ['Elastix', 'Resampling']; | 36 | 36 | 0.666667 | 3 | 36 | 6.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083333 | 36 | 1 | 36 | 36 | 0.606061 | 0 | 0 | 0 | 0 | 0 | 0.459459 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
003dc875c6b6a3c3cf3b1f0f40f7270a5adb32a6 | 225 | py | Python | examples/plugins/dummy/dummy/main.py | mikiec84/gaffer | 8c5d5b5e2ff3fcb1f7cc7c8fbfc623f97dd0da8d | [
"MIT",
"Unlicense"
] | null | null | null | examples/plugins/dummy/dummy/main.py | mikiec84/gaffer | 8c5d5b5e2ff3fcb1f7cc7c8fbfc623f97dd0da8d | [
"MIT",
"Unlicense"
] | null | null | null | examples/plugins/dummy/dummy/main.py | mikiec84/gaffer | 8c5d5b5e2ff3fcb1f7cc7c8fbfc623f97dd0da8d | [
"MIT",
"Unlicense"
] | 1 | 2018-10-28T00:59:17.000Z | 2018-10-28T00:59:17.000Z | from gaffer import Plugin
__all__ = ['DummyPlugin']
from .app import DummyApp
class DummyPlugin(Plugin):
name = "dummy"
version = "1.0"
description = "test"
def app(self, cfg):
return DummyApp()
| 14.0625 | 26 | 0.635556 | 26 | 225 | 5.346154 | 0.769231 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.011905 | 0.253333 | 225 | 15 | 27 | 15 | 0.815476 | 0 | 0 | 0 | 0 | 0 | 0.102222 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.111111 | false | 0 | 0.222222 | 0.111111 | 0.888889 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 3 |
00433726aac3c77abe8b0c9529d3eb24d0cd9286 | 1,074 | py | Python | recipe_app/forms.py | dbobbgit/recipebox | 8e4e5c6f609e2524726954c9382ca37e844721f9 | [
"MIT"
] | null | null | null | recipe_app/forms.py | dbobbgit/recipebox | 8e4e5c6f609e2524726954c9382ca37e844721f9 | [
"MIT"
] | null | null | null | recipe_app/forms.py | dbobbgit/recipebox | 8e4e5c6f609e2524726954c9382ca37e844721f9 | [
"MIT"
] | null | null | null | from django import forms
from recipe_app.models import Author
from django.contrib.auth.forms import UserCreationForm
# Create two forms: RecipeForm & AuthorForm
"""
Author:
- Name: CharField
- Bio: TextField
Recipe:
- Title: CharField
- Author: ForeignKey
- Description: TextField
- Time Required: CharField (for example, "One hour")
- Instructions: TextField
"""
class AddAuthorForm(UserCreationForm):
name = forms.CharField(max_length=100)
bio = forms.CharField(max_length=250)
username = forms.CharField(max_length=150)
password1 = forms.CharField(widget=forms.PasswordInput)
password2 = None
# class Meta:
# model = Author
# fields = [
# 'name',
# 'bio'
# ]
class AddRecipeForm(forms.Form):
title = forms.CharField(max_length=100)
author = forms.ModelChoiceField(queryset=Author.objects.all())
description = forms.CharField(max_length=500)
time_required = forms.CharField(max_length=50)
instructions = forms.CharField(widget=forms.Textarea)
| 26.195122 | 66 | 0.685289 | 115 | 1,074 | 6.330435 | 0.469565 | 0.153846 | 0.14011 | 0.18956 | 0.071429 | 0 | 0 | 0 | 0 | 0 | 0 | 0.022485 | 0.213222 | 1,074 | 40 | 67 | 26.85 | 0.839053 | 0.115456 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.133333 | 0.2 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
cc3b53a3879a2fe4a77aa4a8b7af91545a4857ec | 4,623 | py | Python | stable_baselines/low_dim_analysis/eval_util.py | hugerepo-tianhang/low_dim_update_stable | 565f6cbf886d266d0633bc112ccae28f1d116ee1 | [
"MIT"
] | null | null | null | stable_baselines/low_dim_analysis/eval_util.py | hugerepo-tianhang/low_dim_update_stable | 565f6cbf886d266d0633bc112ccae28f1d116ee1 | [
"MIT"
] | null | null | null | stable_baselines/low_dim_analysis/eval_util.py | hugerepo-tianhang/low_dim_update_stable | 565f6cbf886d266d0633bc112ccae28f1d116ee1 | [
"MIT"
] | null | null | null | # def get_param_traj_file_path(dir_name, net_name, index):
# return f'{dir_name}/{net_name}_{index}.txt'
import os
from datetime import datetime
def get_current_timestamp():
return datetime.now().strftime('%Y-%m-%d-%H:%M:%S')
def get_project_dir():
project_dir = os.path.abspath(os.path.join(os.path.abspath(__file__), '..', '..', '..'))
return project_dir
def get_run_name(args):
if args.additional_notes == "":
add_note = ""
else:
add_note = f'_additional_notes_{args.additional_notes}'
return f'optimizer_{args.optimizer}_env_{args.env}_time_step_{args.num_timesteps}_' \
f'normalize_{args.normalize}_n_steps_{args.n_steps}_nminibatches_{args.nminibatches}_seed_{args.seed}' \
f'_run_{args.run_num}' \
f'{add_note}'
def get_dir_path_for_this_run(args, proj_dir=None):
if proj_dir is not None:
return f'{proj_dir}/stable_baselines/{args.alg}/{get_run_name(args)}'
else:
return f'{get_project_dir()}/stable_baselines/{args.alg}/{get_run_name(args)}'
def get_log_dir(this_run_dir):
return f"{this_run_dir}/the_log_dir"
def get_save_dir(this_run_dir):
return f"{this_run_dir}/the_save_dir"
def get_test_data_dir(this_run_dir):
return f"{this_run_dir}/test_data"
def get_full_params_dir(this_run_dir):
return f"{this_run_dir}/full_params"
def get_aug_plot_dir(this_run_dir):
return f"{this_run_dir}/aug_plot_dir"
def get_intermediate_data_dir(this_run_dir, params_scope="pi"):
return f"{this_run_dir}/{params_scope}_intermediate_data"
def get_eval_losses_file_path(dir_name, total_timesteps):
return f'{dir_name}/eval_loss_{total_timesteps}.hdf5'
def get_full_param_traj_file_path(dir_name, index):
return f'{dir_name}/all_params_{index}.txt'
def get_plot_dir(args):
return f'{get_project_dir()}/plots/{args.alg}/{get_current_timestamp()}_{get_run_name(args)}'
def get_cma_plot_dir(plot_dir, n_comp_to_use, run_num, origin):
return f'{plot_dir}/cma/cma_n_comp_{n_comp_to_use}_origin_{origin}_run_num_{run_num}'
def get_cma_and_then_ppo_plot_dir(plot_dir, pca_indexes, run_num, cma_num_steps, ppo_num_steps, origin):
return f'{plot_dir}/cma_and_then_ppo/cma_and_then_ppo_pca_indexes_{pca_indexes}' \
f'_ppo_num_steps_{ppo_num_steps}_cma_num_steps_{cma_num_steps}_origin_{origin}_run_num_{run_num}'
def get_other_pcs_plane_plot_dir(plot_dir, other_pcs):
return f'{plot_dir}/other_pcs_{other_pcs}'
def get_ppos_plot_dir(plot_dir, n_comp_to_use, cma_run_num):
return f'{plot_dir}/ppos/ppos_n_comp_{n_comp_to_use}_run_num_{cma_run_num}'
def get_first_n_pc1_vs_V_plot_dir(plot_dir, granularity):
return f'{plot_dir}/first_n_pc1_vs_V/first_n_pc1_vs_V_granularity_{granularity}'
def get_plane_angles_vs_final_plane_along_the_way_plot_dir(plot_dir, n_comp_to_use):
return f'{plot_dir}/plane_angles_vs_final_plane/plane_angles_vs_final_plane_n_comp_to_use_{n_comp_to_use}'
def get_pcs_filename(intermediate_dir, n_comp):
return f"{intermediate_dir}/n_comp_{n_comp}_pcs"
def get_mean_param_filename(intermediate_dir):
return f"{intermediate_dir}/mean_param"
def get_explain_ratios_filename(intermediate_dir, n_comp):
return f"{intermediate_dir}/n_comp_{n_comp}_explain_ratios"
def get_projected_full_path_filename(intermediate_dir, n_comp, pca_center, which_components=(1,2)):
return f"{intermediate_dir}/n_comp_{n_comp}_pca_center_{pca_center}_which_components_{which_components}_projected_full_path"
def get_eval_returns_filename(intermediate_dir, eval_string, n_comp, pca_center, which_components=(1,2)):
return f"{intermediate_dir}/{eval_string}_n_comp_{n_comp}_pca_center_{pca_center}_which_components_{which_components}eval_returns"
def get_projected_finals_eval_returns_filename(intermediate_dir, n_comp_start, np_comp_end, pca_center):
return f"{intermediate_dir}/n_comp_start_{n_comp_start}_np_comp_end_{np_comp_end}_pca_center_{pca_center}eval_returns"
def get_cma_returns_dirname(intermediate_dir, n_comp, run_num):
return f"{intermediate_dir}/cma/cma_n_comp_{n_comp}_run_num_{run_num}"
def get_ppos_returns_dirname(intermediate_dir, n_comp, run_num):
return f"{intermediate_dir}/ppos/ppos_n_comp_{n_comp}_run_num_{run_num}"
def get_cma_and_then_ppo_run_dir(intermediate_dir, pca_indexes, run_num, cma_steps):
return f"{intermediate_dir}/cma_and_then_ppo/ctp_pca_index_{pca_indexes}_cma_steps_{cma_steps}_run_num_{run_num}"
def get_ppo_part(this_run_dir):
return f"{this_run_dir}/ppo_part"
if __name__ == '__main__':
print(get_log_dir("a", 1, "s", False, 0)) | 36.401575 | 134 | 0.784123 | 789 | 4,623 | 4.007605 | 0.155894 | 0.056926 | 0.044276 | 0.063251 | 0.558191 | 0.422201 | 0.314674 | 0.297596 | 0.253004 | 0.199874 | 0 | 0.00241 | 0.102531 | 4,623 | 127 | 135 | 36.401575 | 0.759701 | 0.022496 | 0 | 0.027027 | 0 | 0.013514 | 0.43126 | 0.417091 | 0 | 0 | 0 | 0 | 0 | 1 | 0.391892 | false | 0 | 0.027027 | 0.351351 | 0.824324 | 0.013514 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 |
cc3d4f119ef3b88e30b1e9d3c45699b0745cbf05 | 1,038 | py | Python | AntShares/Network/Inventory.py | OTCGO/sync_antshares | 5724a5a820ec5f59e0c886a3c1646db2d07b4d78 | [
"MIT"
] | 10 | 2017-03-28T05:44:35.000Z | 2021-02-17T03:51:39.000Z | AntShares/Network/Inventory.py | OTCGO/sync_antshares | 5724a5a820ec5f59e0c886a3c1646db2d07b4d78 | [
"MIT"
] | 2 | 2017-07-06T10:00:25.000Z | 2017-08-09T10:14:34.000Z | AntShares/Network/Inventory.py | OTCGO/sync_antshares | 5724a5a820ec5f59e0c886a3c1646db2d07b4d78 | [
"MIT"
] | 3 | 2017-03-28T05:44:39.000Z | 2018-02-09T09:56:03.000Z | # -*- coding:utf-8 -*-
"""
Description:
Inventory Class
Usage:
from AntShares.Network.Inventory import Inventory
"""
from AntShares.IO.MemoryStream import MemoryStream
from AntShares.IO.BinaryWriter import BinaryWriter
from AntShares.Cryptography.Helper import *
from AntShares.Helper import *
import binascii
class Inventory(object):
"""docstring for Inventory"""
def __init__(self):
super(Inventory, self).__init__()
self.hash = None
def ensureHash(self):
self.hash = big_or_little(binascii.hexlify(
bin_dbl_sha256(binascii.unhexlify(self.getHashData()))))
return self.hash
def getHashData(self):
ms = MemoryStream()
w = BinaryWriter(ms)
self.serializeUnsigned(w)
return ms.toArray()
def getScriptHashesForVerifying(self):
pass
def serialize(self):
pass
def serializeUnsigned(self):
pass
def deserialize(self):
pass
def deserializeUnsigned(self):
pass
| 21.183673 | 80 | 0.654143 | 106 | 1,038 | 6.292453 | 0.433962 | 0.097451 | 0.065967 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.005155 | 0.252408 | 1,038 | 48 | 81 | 21.625 | 0.854381 | 0.133911 | 0 | 0.178571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.285714 | false | 0.178571 | 0.178571 | 0 | 0.571429 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 0 | 3 |
cc52398a725b3573f2ce15c63cfb703dc5d3fa5f | 2,760 | py | Python | test/Django/05/02/BookManager/Book/views.py | Kingworrior007/lchw001 | e59e6f300123bd98d49e81be16e73a4440ffa85a | [
"MIT"
] | 2 | 2018-03-09T02:13:54.000Z | 2020-12-28T01:47:30.000Z | test/Django/05/02/BookManager/Book/views.py | X-Warrior007/lchw001 | e59e6f300123bd98d49e81be16e73a4440ffa85a | [
"MIT"
] | null | null | null | test/Django/05/02/BookManager/Book/views.py | X-Warrior007/lchw001 | e59e6f300123bd98d49e81be16e73a4440ffa85a | [
"MIT"
] | null | null | null | from django.shortcuts import render
from django.http import HttpResponse,JsonResponse
from django.conf import settings
from Book.models import PictureInfo,AreaInfo
from django.core.paginator import Paginator
# Create your views here.
def sheng(request):
"""获取省级数据,并转JSON字典,响应给ajax"""
# 查询省级数据 sheng_list = [AreaInfo,AreaInfo,AreaInfo,AreaInfo,...]
sheng_list = AreaInfo.objects.filter(parent__isnull=True)
# 构造JSON列表
list = []
for sheng in sheng_list:
list.append([sheng.id, sheng.name])
# 构造JSON字典
sheng_json_dict = {'shenglist':list}
# 响应JSON : ajax收到的也是如此结构如此内容的json字典
return JsonResponse(sheng_json_dict)
"""
{
"shenglist":[
[id, name],
[id, name],
]
}
"""
"""
{
"shenglist":[
{"id":id, "name":name},
{"id":id, "name":name},
]
}
"""
"""
<select id="sheng">
<option value="100000">北京市</option>
</select>
<select id="shi">
<option value="100005">昌平区</option>
</select>
<select id="qu">
<option value="0">请选择</option>
</select>
"""
def area(request):
"""提供省市区三级联动的页面"""
return render(request, 'Book/area.html')
def page(request, page_num):
"""分页"""
# 查询省级信息 sheng_list = [AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,... 33]
sheng_list = AreaInfo.objects.filter(parent__isnull=True)
# 分页的需求: 对sheng_list进行分页,每页10条
# pagenator = [AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,... 33]
paginator = Paginator(sheng_list, 10)
# 为了实现,当用户输入/page/ 也是默认的请求第一页的数据
# print(type(page_num))
if page_num == '':
page_num = '1'
# 度取出某一页数据 page = [AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo,AreaInfo]
page = paginator.page(page_num) # 1 '1'
# 构造上下文
context = {
'page':page
}
# 渲染模板
return render(request, 'Book/page.html', context)
def recv(request):
"""接受上传的图片,内容保存的项目,地址记录到数据库"""
# 获取图片数据
pic = request.FILES.get('pic') # InMemoryUploadF...
# 获取上传的文件的名字
pic_name = pic.name
# 准备文件存储的路径 : '/static/media/Book/mm03.jpeg'
path = '%s/Book/%s' % (settings.MEDIA_ROOT, pic_name)
# 需要将受到的文件内容数据,保存到项目中
with open(path, 'ab') as file:
for c in pic.chunks(): # chunks() 以安全守护的形式去遍历,避免大文件造成内存溢出
file.write(c)
# 还需要将文件保存到项目中的路径,在数据库中记录
pictureInfo = PictureInfo()
# 仅仅是给模型对象的path属性赋值而已
pictureInfo.path = 'Book/%s' % pic_name
# 以下代码才是把path属性里面的数据,写入到数据库表中
pictureInfo.save()
# 响应结果
return HttpResponse('上传成功')
def upload(request):
"""提供图片上传的表单页面"""
return render(request, 'Book/upload.html')
def staticFile(request):
"""加载静态图片"""
return render(request, 'Book/staticfile.html')
| 21.5625 | 113 | 0.63913 | 307 | 2,760 | 5.667752 | 0.403909 | 0.202299 | 0.248276 | 0.257471 | 0.185057 | 0.185057 | 0.156322 | 0.098851 | 0.045977 | 0 | 0 | 0.011965 | 0.212681 | 2,760 | 127 | 114 | 21.732283 | 0.788771 | 0.288768 | 0 | 0.051282 | 0 | 0 | 0.068966 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.153846 | false | 0 | 0.128205 | 0 | 0.435897 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
cc67238765ba95b77b94fefb1d5fa168307525e1 | 1,921 | py | Python | DjangoBlog/articles/migrations/0009_auto_20210815_1840.py | Dimple278/Publication-Repository | ec274bf5822e160b90f0a5bc8559c1d199e12854 | [
"Unlicense",
"MIT"
] | null | null | null | DjangoBlog/articles/migrations/0009_auto_20210815_1840.py | Dimple278/Publication-Repository | ec274bf5822e160b90f0a5bc8559c1d199e12854 | [
"Unlicense",
"MIT"
] | 1 | 2021-08-08T06:46:46.000Z | 2021-08-08T06:46:46.000Z | DjangoBlog/articles/migrations/0009_auto_20210815_1840.py | Dimple278/Publication-Repository | ec274bf5822e160b90f0a5bc8559c1d199e12854 | [
"Unlicense",
"MIT"
] | 2 | 2021-07-03T11:55:11.000Z | 2021-08-09T08:27:52.000Z | # Generated by Django 3.2.4 on 2021-08-15 12:55
from django.db import migrations, models
class Migration(migrations.Migration):
dependencies = [
('articles', '0008_auto_20210808_0801'),
]
operations = [
migrations.AddField(
model_name='article',
name='doi',
field=models.CharField(blank=True, max_length=100),
),
migrations.AddField(
model_name='article',
name='impactFactor',
field=models.FloatField(default=0),
),
migrations.AddField(
model_name='article',
name='journal_type',
field=models.CharField(choices=[('National', 'National'), ('International', 'International')], default='National', max_length=20),
),
migrations.AddField(
model_name='article',
name='peer_reviewed',
field=models.BooleanField(default=False),
),
migrations.AddField(
model_name='article',
name='sjrRating',
field=models.FloatField(default=0),
),
migrations.AddField(
model_name='book',
name='doi',
field=models.CharField(blank=True, max_length=100),
),
migrations.AddField(
model_name='conferencearticle',
name='doi',
field=models.CharField(blank=True, max_length=100),
),
migrations.AlterField(
model_name='article',
name='article_link',
field=models.URLField(blank=True),
),
migrations.AlterField(
model_name='book',
name='book_link',
field=models.URLField(blank=True),
),
migrations.AlterField(
model_name='conferencearticle',
name='conference_link',
field=models.URLField(blank=True),
),
]
| 30.015625 | 142 | 0.548673 | 171 | 1,921 | 6.035088 | 0.345029 | 0.087209 | 0.156008 | 0.18314 | 0.587209 | 0.587209 | 0.428295 | 0.428295 | 0.428295 | 0.319767 | 0 | 0.034135 | 0.328995 | 1,921 | 63 | 143 | 30.492063 | 0.766486 | 0.023425 | 0 | 0.719298 | 1 | 0 | 0.136606 | 0.012273 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.017544 | 0 | 0.070175 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
cc9334543aeeb4519b2ac91825f9b078d9f16ee4 | 94 | py | Python | src6/1/string3.py | pjackson3/cs50 | 4cf8ca67abfc293d4dbb9bf5a1cb742d74ca7a31 | [
"MIT"
] | null | null | null | src6/1/string3.py | pjackson3/cs50 | 4cf8ca67abfc293d4dbb9bf5a1cb742d74ca7a31 | [
"MIT"
] | null | null | null | src6/1/string3.py | pjackson3/cs50 | 4cf8ca67abfc293d4dbb9bf5a1cb742d74ca7a31 | [
"MIT"
] | 1 | 2020-11-24T23:25:26.000Z | 2020-11-24T23:25:26.000Z | # input and print, with format strings
s = input("What's your name?\n")
print(f"hello, {s}")
| 18.8 | 38 | 0.659574 | 17 | 94 | 3.647059 | 0.764706 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.159574 | 94 | 4 | 39 | 23.5 | 0.78481 | 0.382979 | 0 | 0 | 0 | 0 | 0.517857 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 3 |
cc9a005a14d0a98035518428a505d967d10c254e | 101 | py | Python | Section 18/8.Document-function-with-keyword-based-arguments.py | airbornum/-Complete-Python-Scripting-for-Automation | bc053444f8786259086269ca1713bdb10144dd74 | [
"MIT"
] | 18 | 2020-04-13T03:14:06.000Z | 2022-03-09T18:54:41.000Z | Section 18/8.Document-function-with-keyword-based-arguments.py | airbornum/-Complete-Python-Scripting-for-Automation | bc053444f8786259086269ca1713bdb10144dd74 | [
"MIT"
] | null | null | null | Section 18/8.Document-function-with-keyword-based-arguments.py | airbornum/-Complete-Python-Scripting-for-Automation | bc053444f8786259086269ca1713bdb10144dd74 | [
"MIT"
] | 22 | 2020-04-29T21:12:42.000Z | 2022-03-17T18:19:54.000Z | def display(a,b):
print(f'a={a}')
return None
display(3,4)
display(a=3,b=4)
display(b=4,a=3) | 14.428571 | 18 | 0.60396 | 23 | 101 | 2.652174 | 0.434783 | 0.262295 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.070588 | 0.158416 | 101 | 7 | 19 | 14.428571 | 0.647059 | 0 | 0 | 0 | 0 | 0 | 0.052083 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0 | 0 | 0.333333 | 0.166667 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
aea00ef15d75bbb6792d81d979d452ecd7795555 | 754 | py | Python | wfdb/__init__.py | melbourne-cdth/wfdb-python | a36c22e12f8417ff18e57dbe54b7180dd183ec66 | [
"MIT"
] | null | null | null | wfdb/__init__.py | melbourne-cdth/wfdb-python | a36c22e12f8417ff18e57dbe54b7180dd183ec66 | [
"MIT"
] | null | null | null | wfdb/__init__.py | melbourne-cdth/wfdb-python | a36c22e12f8417ff18e57dbe54b7180dd183ec66 | [
"MIT"
] | null | null | null | from wfdb.io.record import (Record, MultiRecord, rdheader, rdrecord, rdsamp,
wrsamp, dl_database, edf2mit, mit2edf, wav2mit,
mit2wav, wfdb2mat, csv2mit, sampfreq, signame,
wfdbdesc, wfdbtime, sigavg)
from wfdb.io.annotation import (Annotation, rdann, wrann, show_ann_labels,
show_ann_classes, ann2rr, rr2ann, csv2ann,
rdedfann, mrgann)
from wfdb.io.download import get_dbs, get_record_list, dl_files, set_db_index_url
from wfdb.plot.plot import plot_items, plot_wfdb, plot_all_records
from wfdb.plot.plot_plotly import plot_items_pl, plot_wfdb_pl, plot_all_records_pl
from wfdb.version import __version__
| 58 | 82 | 0.66313 | 92 | 754 | 5.130435 | 0.554348 | 0.101695 | 0.063559 | 0.067797 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.016423 | 0.27321 | 754 | 12 | 83 | 62.833333 | 0.844891 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.545455 | 0 | 0.545455 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
aec73f93f4747f28f93931758f77133311e3036f | 83 | py | Python | dynasty/__init__.py | LeMinaw/Dynasty | 458685df8051cd11f497222e0cd7b672515cd6aa | [
"MIT"
] | 2 | 2021-04-04T19:31:32.000Z | 2022-02-06T13:38:09.000Z | dynasty/__init__.py | LeMinaw/Dynasty | 458685df8051cd11f497222e0cd7b672515cd6aa | [
"MIT"
] | null | null | null | dynasty/__init__.py | LeMinaw/Dynasty | 458685df8051cd11f497222e0cd7b672515cd6aa | [
"MIT"
] | null | null | null | __version__ = '0.0.2'
from pathlib import Path
APP_DIR = Path(__file__).parent
| 10.375 | 31 | 0.722892 | 13 | 83 | 3.923077 | 0.846154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.043478 | 0.168675 | 83 | 7 | 32 | 11.857143 | 0.695652 | 0 | 0 | 0 | 0 | 0 | 0.060241 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 3 |
aed61ba31c0649cb1a7854a5aa110c70142265a0 | 269 | py | Python | cmd_creator_b.py | azeznassar/JavaScriptToUML | 53cccc1bba635114f03d966fd2f0f2f2d2d74bae | [
"MIT"
] | 5 | 2020-08-16T09:25:42.000Z | 2022-01-19T21:00:48.000Z | cmd_creator_b.py | azeznassar/JavaScriptToUML | 53cccc1bba635114f03d966fd2f0f2f2d2d74bae | [
"MIT"
] | null | null | null | cmd_creator_b.py | azeznassar/JavaScriptToUML | 53cccc1bba635114f03d966fd2f0f2f2d2d74bae | [
"MIT"
] | 4 | 2020-08-19T09:05:13.000Z | 2021-08-03T17:25:53.000Z | # pylint: disable="import-error"
from command_line_creator import CommandLineCreator
from current_cmd_b import CurrentCMD_B
class CmdCreatorB(CommandLineCreator):
def create_cmd(self):
current_cmd = CurrentCMD_B(self.output)
return current_cmd | 29.888889 | 51 | 0.773234 | 33 | 269 | 6.030303 | 0.606061 | 0.150754 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.167286 | 269 | 9 | 52 | 29.888889 | 0.888393 | 0.111524 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.166667 | false | 0 | 0.333333 | 0 | 0.833333 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 0 | 3 |
aee1d165304e92ca3a56f102fa49637d4eb2d084 | 4,637 | py | Python | anyHR/constraint/node/Node.py | figlerg/anyHR | 418742aa10634338c405de87b2ee1cbe08ae8a9e | [
"BSD-3-Clause"
] | 1 | 2021-08-14T17:59:51.000Z | 2021-08-14T17:59:51.000Z | anyHR/constraint/node/Node.py | figlerg/anyHR | 418742aa10634338c405de87b2ee1cbe08ae8a9e | [
"BSD-3-Clause"
] | 2 | 2022-03-27T13:38:19.000Z | 2022-03-31T15:20:26.000Z | anyHR/constraint/node/Node.py | figlerg/anyHR | 418742aa10634338c405de87b2ee1cbe08ae8a9e | [
"BSD-3-Clause"
] | 1 | 2022-03-27T08:31:23.000Z | 2022-03-27T08:31:23.000Z | # from constraint.node.SubstitutorVisitor import SubstitutorVisitor
from enum import Enum
class Node(object):
def __init__(self):
self.children = list()
self.node_type = NodeType.NODE
def get_vars(self, vars = set()):
# recursively crawls tree and writes down all the variables
# stop
if self.node_type == NodeType.VARIABLE:
vars.add(self.name)
# recursion
for child in self.children:
child.get_vars(vars)
return vars
# for visitor class. Using isinstance breaks when importing from outside
class NodeType(Enum):
NODE = 0
LEQ = 1
GEQ = 2
LESS = 3
GREATER = 4
EQ = 5
NEQ = 6
IN = 7
VARIABLE = 8
CONSTANT = 9
ADDITION = 10
SUBTRACTION = 11
MULTIPLICATION = 12
EXPONENTIAL = 13
def __eq__(self, other):
return self.value == other.value
class LEQ(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.LEQ
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' <= ' + str(self.children[1]) + ')'
class GEQ(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.GEQ
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' >= ' + str(self.children[1]) + ')'
class Less(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.LESS
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' < ' + str(self.children[1]) + ')'
class Greater(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.GREATER
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' > ' + str(self.children[1]) + ')'
class EQ(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.EQ
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' = ' + str(self.children[1]) + ')'
class NEQ(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.NEQ
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' != ' + str(self.children[1]) + ')'
class In(Node):
def __init__(self, op, op_low, op_up):
Node.__init__(self)
self.node_type = NodeType.IN
self.children.append(op)
self.children.append(op_low)
self.children.append(op_up)
def __str__(self):
return '(' + str(self.children[0]) + ')' + ' IN ' + '[ ' + str(self.children[1]) + ' , ' + str(self.children[2]) + ' ]'
class Variable(Node):
def __init__(self, name):
Node.__init__(self)
self.node_type = NodeType.VARIABLE
self.name = name
def __str__(self):
return self.name
class Constant(Node):
def __init__(self, value):
Node.__init__(self)
self.node_type = NodeType.CONSTANT
self.value = value
def __str__(self):
return str(self.value)
class Addition(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.ADDITION
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' + ' + str(self.children[1]) + ')'
class Subtraction(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.SUBTRACTION
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' - ' + str(self.children[1]) + ')'
class Multiplication(Node):
def __init__(self, op1, op2):
Node.__init__(self)
self.node_type = NodeType.MULTIPLICATION
self.children.append(op1)
self.children.append(op2)
def __str__(self):
return '(' + str(self.children[0]) + ' * ' + str(self.children[1]) + ')'
class Exponential(Node):
def __init__(self, op1):
Node.__init__(self)
self.node_type = NodeType.EXPONENTIAL
self.children.append(op1)
def __str__(self):
return '(' + 'EXP(' + str(self.children[1]) + ') ' + ')'
| 25.478022 | 128 | 0.587233 | 563 | 4,637 | 4.507993 | 0.14032 | 0.217494 | 0.156028 | 0.118203 | 0.618203 | 0.596927 | 0.587864 | 0.537431 | 0.524823 | 0.524823 | 0 | 0.023104 | 0.271943 | 4,637 | 181 | 129 | 25.618785 | 0.728673 | 0.045072 | 0 | 0.415385 | 0 | 0 | 0.015607 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.223077 | false | 0 | 0.007692 | 0.107692 | 0.569231 | 0 | 0 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 3 |
aee85d757db25a014d88c52b4b892e6e8e5b9803 | 335 | py | Python | TestGetter.py | okiyama/Chess-EEA-Opponent-Modelling | c81f2b5226e3441ed236b3b20c3811e721d412d8 | [
"MIT"
] | null | null | null | TestGetter.py | okiyama/Chess-EEA-Opponent-Modelling | c81f2b5226e3441ed236b3b20c3811e721d412d8 | [
"MIT"
] | null | null | null | TestGetter.py | okiyama/Chess-EEA-Opponent-Modelling | c81f2b5226e3441ed236b3b20c3811e721d412d8 | [
"MIT"
] | null | null | null | class TestGetter:
""" Interface for getting tests. Useful because I'd like to both be able to evolve a next test as well as play a normal game of chess with the user """
#I thought about using abstract base class for this but it feels like overkill
def getNextTest(self, opponents, previousTest): raise NotImplementedError | 67 | 155 | 0.761194 | 53 | 335 | 4.811321 | 0.867925 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.19403 | 335 | 5 | 156 | 67 | 0.944444 | 0.662687 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.5 | false | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
aee9791412aca3b9a70fc201a6a8bbfc83e5a9e9 | 210 | py | Python | SmartTE/Signals/UndoSignals.py | smartboyathome/SmartTE | 373a721f17e9a1f3d1bbe5c9c101c638de3fa96d | [
"BSD-3-Clause"
] | 1 | 2020-07-15T19:53:27.000Z | 2020-07-15T19:53:27.000Z | SmartTE/Signals/UndoSignals.py | smartboyathome/SmartTE | 373a721f17e9a1f3d1bbe5c9c101c638de3fa96d | [
"BSD-3-Clause"
] | null | null | null | SmartTE/Signals/UndoSignals.py | smartboyathome/SmartTE | 373a721f17e9a1f3d1bbe5c9c101c638de3fa96d | [
"BSD-3-Clause"
] | null | null | null | UNDO_EMPTY = 'undostack-empty'
UNDO_NOT_EMPTY = 'undostack-not-empty'
REDO_EMPTY = 'redostack-empty'
REDO_NOT_EMPTY = 'redostack-not-empty'
UNDO_CHANGED = 'undostack-changed'
REDO_CHANGED = 'redostack-changed'
| 30 | 38 | 0.790476 | 28 | 210 | 5.642857 | 0.25 | 0.202532 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.085714 | 210 | 6 | 39 | 35 | 0.822917 | 0 | 0 | 0 | 0 | 0 | 0.485714 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 3 |
aeeff92da6880272b842617fa1cd1119d5a74e02 | 2,534 | py | Python | pyclustering/cluster/tests/integration/it_hsyncnet.py | JosephChataignon/pyclustering | bf4f51a472622292627ec8c294eb205585e50f52 | [
"BSD-3-Clause"
] | 1,013 | 2015-01-26T19:50:14.000Z | 2022-03-31T07:38:48.000Z | pyclustering/cluster/tests/integration/it_hsyncnet.py | peterlau0626/pyclustering | bf4f51a472622292627ec8c294eb205585e50f52 | [
"BSD-3-Clause"
] | 542 | 2015-01-20T16:44:32.000Z | 2022-01-29T14:57:20.000Z | pyclustering/cluster/tests/integration/it_hsyncnet.py | peterlau0626/pyclustering | bf4f51a472622292627ec8c294eb205585e50f52 | [
"BSD-3-Clause"
] | 262 | 2015-03-19T07:28:12.000Z | 2022-03-30T07:28:24.000Z | """!
@brief Integration-tests for Hierarchical Sync (HSyncNet) algorithm.
@authors Andrei Novikov (pyclustering@yandex.ru)
@date 2014-2020
@copyright BSD-3-Clause
"""
import unittest;
import matplotlib;
matplotlib.use('Agg');
from pyclustering.cluster.tests.hsyncnet_templates import HsyncnetTestTemplates;
from pyclustering.nnet import solve_type;
from pyclustering.samples.definitions import SIMPLE_SAMPLES;
from pyclustering.core.tests import remove_library;
class HsyncnetIntegrationTest(unittest.TestCase):
def testClusteringSampleSimple1WithoutCollectingByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, [5, 5], solve_type.FAST, 5, 0.3, False, True);
def testClusteringSampleSimple1ByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, [5, 5], solve_type.FAST, 5, 0.3, True, True);
def testClusteringOneAllocationSampleSimple1ByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 1, [10], solve_type.FAST, 5, 0.3, True, True);
def testClusteringSampleSimple2ByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 3, [10, 5, 8], solve_type.FAST, 5, 0.2, True, True);
def testClusteringOneAllocationSampleSimple2ByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE2, 1, [23], solve_type.FAST, 5, 0.2, True, True);
def testClusteringOneDimensionDataSampleSimple7ByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE7, 2, [10, 10], solve_type.FAST, 5, 0.3, True, True);
def testClusteringTheSameData1ByCore(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE12, 3, [5, 5, 5], solve_type.FAST, 5, 0.3, True, True);
def testDynamicLengthCollectingByCore(self):
HsyncnetTestTemplates.templateDynamicLength(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, None, 5, 0.3, True, True);
def testDynamicLengthWithoutCollectingByCore(self):
HsyncnetTestTemplates.templateDynamicLength(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, None, 5, 0.3, False, True);
def testProcessingWhenLibraryCoreRemoved(self):
self.runRemovedLibraryCoreTest()
@remove_library
def runRemovedLibraryCoreTest(self):
HsyncnetTestTemplates.templateClustering(SIMPLE_SAMPLES.SAMPLE_SIMPLE1, 2, [5, 5], solve_type.FAST, 5, 0.3, False, True)
| 41.540984 | 133 | 0.753749 | 259 | 2,534 | 7.247104 | 0.281853 | 0.076185 | 0.101225 | 0.208844 | 0.50666 | 0.50666 | 0.426745 | 0.316462 | 0.316462 | 0.287693 | 0 | 0.040892 | 0.15075 | 2,534 | 60 | 134 | 42.233333 | 0.83132 | 0.063536 | 0 | 0 | 0 | 0 | 0.001302 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.354839 | false | 0 | 0.193548 | 0 | 0.580645 | 0 | 0 | 0 | 0 | null | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 3 |
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