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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
dba990b3df5ea3b5ba53e372fdb146c4841a3ec2 | 76 | py | Python | test.py | BenjaminBush/rdtscp | 96be4d1d0b5e86d1129df5dece828b220193d7a5 | [
"MIT"
] | null | null | null | test.py | BenjaminBush/rdtscp | 96be4d1d0b5e86d1129df5dece828b220193d7a5 | [
"MIT"
] | null | null | null | test.py | BenjaminBush/rdtscp | 96be4d1d0b5e86d1129df5dece828b220193d7a5 | [
"MIT"
] | null | null | null | import rdtscp_module
print("RDTSCP_READ {}".format(rdtscp_module.rdtscp())) | 25.333333 | 54 | 0.789474 | 10 | 76 | 5.7 | 0.6 | 0.421053 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.052632 | 76 | 3 | 54 | 25.333333 | 0.791667 | 0 | 0 | 0 | 0 | 0 | 0.181818 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.5 | 0 | 0.5 | 0.5 | 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 | 1 | 0 | 1 | 0 | 0 | 1 | 0 | 6 |
dbb28148e5853bdee5e2c21c91e71e54e2d96653 | 2,189 | py | Python | gym_socks/utils/tests/test_grid.py | ajthor/socks | 77063064ceb5a5da3f01733bef0885b00d4b2bed | [
"MIT"
] | null | null | null | gym_socks/utils/tests/test_grid.py | ajthor/socks | 77063064ceb5a5da3f01733bef0885b00d4b2bed | [
"MIT"
] | 1 | 2021-11-09T21:15:26.000Z | 2021-11-09T21:15:26.000Z | gym_socks/utils/tests/test_grid.py | ajthor/socks | 77063064ceb5a5da3f01733bef0885b00d4b2bed | [
"MIT"
] | null | null | null | import unittest
import gym
import gym_socks.utils
import numpy as np
from gym_socks.utils.grid import make_grid_from_ranges
from gym_socks.utils.grid import make_grid_from_space
from gym_socks.utils.grid import grid_size_from_ranges
from gym_socks.utils.grid import grid_size_from_space
class TestGrid(unittest.TestCase):
def test_grid_from_ranges(cls):
"""Should generate proper grid from ranges."""
xi = [np.linspace(-1, 1, 3), np.linspace(-1, 1, 3)]
result = make_grid_from_ranges(xi)
groundTruth = [
[-1.0, -1.0],
[-1.0, 0.0],
[-1.0, 1.0],
[0.0, -1.0],
[0.0, 0.0],
[0.0, 1.0],
[1.0, -1.0],
[1.0, 0.0],
[1.0, 1.0],
]
cls.assertTrue(np.array_equiv(result, groundTruth))
def test_grid_from_space(cls):
"""Should generate proper grid from space."""
sample_space = gym.spaces.Box(low=-1, high=1, shape=(2,), dtype=np.float32)
groundTruth = [
[-1.0, -1.0],
[-1.0, 0.0],
[-1.0, 1.0],
[0.0, -1.0],
[0.0, 0.0],
[0.0, 1.0],
[1.0, -1.0],
[1.0, 0.0],
[1.0, 1.0],
]
result = make_grid_from_space(sample_space=sample_space, resolution=3)
cls.assertTrue(np.array_equiv(result, groundTruth))
result = make_grid_from_space(sample_space=sample_space, resolution=[3, 3])
cls.assertTrue(np.array_equiv(result, groundTruth))
def test_grid_size_from_space(cls):
"""Should generate proper grid size from ranges."""
xi = [np.linspace(-1, 1, 3), np.linspace(-1, 1, 3)]
cls.assertEqual(grid_size_from_ranges(xi), 9)
def test_grid_size_from_space(cls):
"""Should generate proper grid size from space."""
sample_space = gym.spaces.Box(low=-1, high=1, shape=(2,), dtype=np.float32)
cls.assertEqual(
grid_size_from_space(sample_space=sample_space, resolution=3), 9
)
cls.assertEqual(
grid_size_from_space(sample_space=sample_space, resolution=[3, 3]), 9
)
| 28.802632 | 83 | 0.572864 | 317 | 2,189 | 3.760252 | 0.141956 | 0.040268 | 0.055369 | 0.04698 | 0.877517 | 0.848993 | 0.826342 | 0.796141 | 0.750839 | 0.618289 | 0 | 0.065815 | 0.285062 | 2,189 | 75 | 84 | 29.186667 | 0.695847 | 0.078118 | 0 | 0.596154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.115385 | 1 | 0.076923 | false | 0 | 0.153846 | 0 | 0.25 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
dbc91f3cb58ee3d0a6e32ec981aa72b5a2d060a8 | 100 | py | Python | app/moderator/__init__.py | Amukozoberit/Quotes2 | 80795a5208f9442bf954170a0e4b22d71c53eb81 | [
"MIT"
] | null | null | null | app/moderator/__init__.py | Amukozoberit/Quotes2 | 80795a5208f9442bf954170a0e4b22d71c53eb81 | [
"MIT"
] | null | null | null | app/moderator/__init__.py | Amukozoberit/Quotes2 | 80795a5208f9442bf954170a0e4b22d71c53eb81 | [
"MIT"
] | null | null | null | from flask import Blueprint
moderator=Blueprint('moderator',__name__)
from . import views,errors | 14.285714 | 41 | 0.8 | 12 | 100 | 6.333333 | 0.666667 | 0.473684 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.12 | 100 | 7 | 42 | 14.285714 | 0.863636 | 0 | 0 | 0 | 0 | 0 | 0.089109 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0.666667 | 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 | 1 | 0 | 1 | 1 | 0 | 6 |
dbcf5a4dab04b3f2c86d6982f0a8ce486cceed11 | 98 | py | Python | backend/settings.py | triplejay2013/realtime-transcription-playground | fab8c610cce81b63ac120cc81bfe237455e9a84b | [
"MIT"
] | 98 | 2021-07-02T13:41:17.000Z | 2022-03-03T00:27:01.000Z | backend/settings.py | triplejay2013/realtime-transcription-playground | fab8c610cce81b63ac120cc81bfe237455e9a84b | [
"MIT"
] | 4 | 2021-07-02T13:31:51.000Z | 2021-10-04T14:36:23.000Z | backend/settings.py | triplejay2013/realtime-transcription-playground | fab8c610cce81b63ac120cc81bfe237455e9a84b | [
"MIT"
] | 8 | 2021-07-07T17:02:42.000Z | 2022-03-31T15:09:32.000Z | import os
GOOGLE_SERVICE_JSON_FILE = os.environ['GOOGLE_SERVICE_JSON_FILE']
BACKEND_PORT = 10000
| 19.6 | 65 | 0.836735 | 15 | 98 | 5 | 0.666667 | 0.346667 | 0.453333 | 0.56 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.05618 | 0.091837 | 98 | 4 | 66 | 24.5 | 0.786517 | 0 | 0 | 0 | 0 | 0 | 0.244898 | 0.244898 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 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 | 6 |
9162c9d2d18d68744640d3bf80dd65b2aa210f5f | 135 | py | Python | check_value_substring.py | jjtoledo/Treinamento-Data-Science | 5117975109695b1de06ae43b416972e66a4b7773 | [
"MIT"
] | null | null | null | check_value_substring.py | jjtoledo/Treinamento-Data-Science | 5117975109695b1de06ae43b416972e66a4b7773 | [
"MIT"
] | null | null | null | check_value_substring.py | jjtoledo/Treinamento-Data-Science | 5117975109695b1de06ae43b416972e66a4b7773 | [
"MIT"
] | null | null | null | # Which are ALWAYS equivalent to s:
s = '<any string>'
print s[:]
print s + s[0:-1 + 1]
print s[0:]
print s[:-1]
print s[:3] + s[3:]
| 13.5 | 35 | 0.562963 | 28 | 135 | 2.714286 | 0.428571 | 0.394737 | 0.184211 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.066038 | 0.214815 | 135 | 9 | 36 | 15 | 0.650943 | 0.244444 | 0 | 0 | 0 | 0 | 0.12 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0 | null | null | 0.833333 | 1 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
37d41ffdbb3155f1888879cdada685fbcbced342 | 37 | py | Python | PositioningSolver/src/io_manager/import_timeseries/__init__.py | rodrigo-moliveira/PositioningSolver | d3ea60751ee1d7bf1f845e76c31fac95f7c02c43 | [
"MIT"
] | null | null | null | PositioningSolver/src/io_manager/import_timeseries/__init__.py | rodrigo-moliveira/PositioningSolver | d3ea60751ee1d7bf1f845e76c31fac95f7c02c43 | [
"MIT"
] | null | null | null | PositioningSolver/src/io_manager/import_timeseries/__init__.py | rodrigo-moliveira/PositioningSolver | d3ea60751ee1d7bf1f845e76c31fac95f7c02c43 | [
"MIT"
] | null | null | null | from .read_tm import read_timeseries
| 18.5 | 36 | 0.864865 | 6 | 37 | 5 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.108108 | 37 | 1 | 37 | 37 | 0.909091 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
37f5907446469051953203be85752e970d2e5eb1 | 34 | py | Python | RLtoolkit/graph3d.py | AmiiThinks/rltoolkit | cec83cc3d2029861a5a63a6d0aaca5d9a2dbd36d | [
"MIT"
] | 6 | 2017-10-27T22:51:54.000Z | 2021-11-10T02:09:19.000Z | RLtoolkit/graph3d.py | AmiiThinks/rltoolkit | cec83cc3d2029861a5a63a6d0aaca5d9a2dbd36d | [
"MIT"
] | 1 | 2019-08-28T17:27:23.000Z | 2019-08-28T17:27:23.000Z | RLtoolkit/graph3d.py | AmiiThinks/rltoolkit | cec83cc3d2029861a5a63a6d0aaca5d9a2dbd36d | [
"MIT"
] | 3 | 2018-03-26T18:13:29.000Z | 2019-03-05T20:52:06.000Z | from .Quickgraph.graph3d import *
| 17 | 33 | 0.794118 | 4 | 34 | 6.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.033333 | 0.117647 | 34 | 1 | 34 | 34 | 0.866667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
37f5e1bb5dea85c3c478caf06c9d9fa6cf3b8353 | 141 | py | Python | src/www/api/query.py | herondriftwood/human_ppi | b441bc0b02b1f1c566a50ef9597874ff957364da | [
"Apache-2.0"
] | 1 | 2021-05-09T04:51:28.000Z | 2021-05-09T04:51:28.000Z | src/www/api/query.py | greg-k-taylor/human_ppi | b441bc0b02b1f1c566a50ef9597874ff957364da | [
"Apache-2.0"
] | null | null | null | src/www/api/query.py | greg-k-taylor/human_ppi | b441bc0b02b1f1c566a50ef9597874ff957364da | [
"Apache-2.0"
] | 1 | 2018-11-17T08:53:06.000Z | 2018-11-17T08:53:06.000Z | # -*- coding: utf-8 -*-
from biothings.web.api.es.query import ESQuery
class ESQuery(ESQuery):
# Add app specific queries here
pass
| 20.142857 | 46 | 0.687943 | 20 | 141 | 4.85 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.008772 | 0.191489 | 141 | 6 | 47 | 23.5 | 0.842105 | 0.361702 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.333333 | 0.333333 | 0 | 0.666667 | 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 | 1 | 1 | 0 | 1 | 0 | 0 | 6 |
37fc5050b4a367331e2737c4234c901549b17fc0 | 118 | py | Python | slam_recognition/constant_convolutions/center_surround/__init__.py | SimLeek/pySILEnT | feec2d1fb654d7c8dc25f610916f4e9b202a1092 | [
"Apache-2.0",
"MIT"
] | 5 | 2018-11-18T17:35:59.000Z | 2019-02-13T20:25:58.000Z | slam_recognition/constant_convolutions/center_surround/__init__.py | SimLeek/slam_recognition | feec2d1fb654d7c8dc25f610916f4e9b202a1092 | [
"Apache-2.0",
"MIT"
] | 12 | 2018-10-31T01:57:55.000Z | 2019-02-07T05:49:36.000Z | slam_recognition/constant_convolutions/center_surround/__init__.py | SimLeek/pySILEnT | feec2d1fb654d7c8dc25f610916f4e9b202a1092 | [
"Apache-2.0",
"MIT"
] | null | null | null | from .center_surround_tensor import center_surround_tensor
from .rgby import rgby, rgby_3
from .rgc import midget_rgc
| 29.5 | 58 | 0.855932 | 19 | 118 | 5 | 0.473684 | 0.294737 | 0.421053 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.009524 | 0.110169 | 118 | 3 | 59 | 39.333333 | 0.895238 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 6 |
532654aacb1d26432ba7e388473caae4b3303757 | 450 | py | Python | src/researchhub_document/serializers/__init__.py | ResearchHub/ResearchHub-Backend-Open | d36dca33afae2d442690694bb2ab17180d84bcd3 | [
"MIT"
] | 18 | 2021-05-20T13:20:16.000Z | 2022-02-11T02:40:18.000Z | src/researchhub_document/serializers/__init__.py | ResearchHub/ResearchHub-Backend-Open | d36dca33afae2d442690694bb2ab17180d84bcd3 | [
"MIT"
] | 109 | 2021-05-21T20:14:23.000Z | 2022-03-31T20:56:10.000Z | src/researchhub_document/serializers/__init__.py | ResearchHub/ResearchHub-Backend-Open | d36dca33afae2d442690694bb2ab17180d84bcd3 | [
"MIT"
] | 4 | 2021-05-17T13:47:53.000Z | 2022-02-12T10:48:21.000Z | # flake8: noqa
from researchhub_document.serializers.researchhub_post_serializer import ResearchhubPostSerializer
from researchhub_document.serializers.researchhub_post_serializer import DynamicPostSerializer
from researchhub_document.serializers.researchhub_unified_document_serializer import ResearchhubUnifiedDocumentSerializer
from researchhub_document.serializers.researchhub_unified_document_serializer import DynamicUnifiedDocumentSerializer
| 75 | 121 | 0.933333 | 40 | 450 | 10.15 | 0.35 | 0.147783 | 0.226601 | 0.334975 | 0.694581 | 0.694581 | 0.694581 | 0.694581 | 0.374384 | 0 | 0 | 0.002326 | 0.044444 | 450 | 5 | 122 | 90 | 0.94186 | 0.026667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 0 | 0 | 1 | null | 0 | 1 | 1 | 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 | 1 | 0 | 0 | 0 | 0 | 6 |
532b60db10193cfca3220c8a7c0c204b7667e544 | 101,319 | py | Python | flaskwebapp/tests/unit/test_driver.py | NareshKumarHimachalapathi/DevOps-For-AI-Apps-master | acff6649b22ea8f1fcbb009872ac79dee2015988 | [
"MIT"
] | null | null | null | flaskwebapp/tests/unit/test_driver.py | NareshKumarHimachalapathi/DevOps-For-AI-Apps-master | acff6649b22ea8f1fcbb009872ac79dee2015988 | [
"MIT"
] | null | null | null | flaskwebapp/tests/unit/test_driver.py | NareshKumarHimachalapathi/DevOps-For-AI-Apps-master | acff6649b22ea8f1fcbb009872ac79dee2015988 | [
"MIT"
] | 2 | 2018-10-25T16:06:38.000Z | 2018-11-16T10:39:02.000Z | from context import init, run, driver
import numpy as np
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"]'
class MockModel(object):
def __init__(self):
super(MockModel, self).__init__()
self.arguments=['one']
def eval(self, input_dict):
assert 'one' in input_dict
assert isinstance(input_dict['one'][0], np.ndarray)
assert (3, 224, 224) == input_dict['one'][0].shape
return [0, 0, 0, 0, 0, 0, 1, 0.8, 0.7, 0]
def test_init(monkeypatch):
""" Tests model initialisation1
"""
monkeypatch.setattr(driver, 'LABEL_FILE', 'synset.txt')
monkeypatch.setattr(driver, 'MODEL_FILE', 'ResNet_152.model')
init()
assert driver.trainedModel != None
def test_run(monkeypatch):
""" Test the execution of the model
"""
monkeypatch.setattr(driver, 'trainedModel', MockModel())
results , _ = run(input_string)
assert results==[[('n01498041 stingray', 100.0), ('n01514668 cock', 80.0), ('n01514859 hen', 70.0)]] | 3,070.272727 | 100,371 | 0.958409 | 3,580 | 101,319 | 27.118715 | 0.915922 | 0.000103 | 0.000124 | 0.000124 | 0.000062 | 0 | 0 | 0 | 0 | 0 | 0 | 0.157623 | 0.001954 | 101,319 | 33 | 100,372 | 3,070.272727 | 0.802464 | 0.000632 | 0 | 0 | 0 | 0.047619 | 0.992424 | 0.991288 | 0 | 1 | 0 | 0 | 0.238095 | 1 | 0.190476 | false | 0.047619 | 0.095238 | 0 | 0.380952 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
53393761b84782ca4a2fe11645483a607f085a18 | 30 | py | Python | siamese/layers/__init__.py | Benjamin-Etheredge/siamese | 9665d52bb1e8bf329821788332eb38476595a60f | [
"MIT"
] | 1 | 2021-08-07T14:56:57.000Z | 2021-08-07T14:56:57.000Z | siamese/layers/__init__.py | Benjamin-Etheredge/siamese | 9665d52bb1e8bf329821788332eb38476595a60f | [
"MIT"
] | null | null | null | siamese/layers/__init__.py | Benjamin-Etheredge/siamese | 9665d52bb1e8bf329821788332eb38476595a60f | [
"MIT"
] | null | null | null | from .distance_layers import * | 30 | 30 | 0.833333 | 4 | 30 | 6 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.1 | 30 | 1 | 30 | 30 | 0.888889 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
f402cc3fb8dda3acda5250654acb72c57734d512 | 141 | py | Python | src/drstorage/models/f1.py | chelling87/drstorage | 5d69cdd01306c8d890ace1b4277b64f50efa5114 | [
"BSD-3-Clause"
] | null | null | null | src/drstorage/models/f1.py | chelling87/drstorage | 5d69cdd01306c8d890ace1b4277b64f50efa5114 | [
"BSD-3-Clause"
] | 26 | 2020-11-13T03:49:20.000Z | 2022-03-14T19:55:00.000Z | src/drstorage/models/f1.py | chelling87/drstorage | 5d69cdd01306c8d890ace1b4277b64f50efa5114 | [
"BSD-3-Clause"
] | 1 | 2021-11-18T00:00:51.000Z | 2021-11-18T00:00:51.000Z | from .base import DrStorageFactory
F1_600 = DrStorageFactory(model_number=b"\x02\x58")
F1_1200 = DrStorageFactory(model_number=b"\x00\xad")
| 28.2 | 52 | 0.801418 | 20 | 141 | 5.45 | 0.7 | 0.385321 | 0.495413 | 0.513761 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.115385 | 0.078014 | 141 | 4 | 53 | 35.25 | 0.723077 | 0 | 0 | 0 | 0 | 0 | 0.113475 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.333333 | 0 | 0.333333 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 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 | 6 |
f403844b421133becd6de09fcd5862fd420f838d | 61 | py | Python | coder/blueprints/export/__init__.py | mikkokotila/coder-1 | c0462fb63bd23d4367a31f86f9c7f29b1ece93bd | [
"MIT"
] | 1 | 2019-03-11T12:44:33.000Z | 2019-03-11T12:44:33.000Z | coder/blueprints/export/__init__.py | mikkokotila/coder-1 | c0462fb63bd23d4367a31f86f9c7f29b1ece93bd | [
"MIT"
] | 1 | 2019-01-02T09:52:17.000Z | 2019-01-02T09:52:17.000Z | coder/blueprints/export/__init__.py | mikkokotila/coder-1 | c0462fb63bd23d4367a31f86f9c7f29b1ece93bd | [
"MIT"
] | 1 | 2019-01-04T12:44:50.000Z | 2019-01-04T12:44:50.000Z | from coder.blueprints.datahandling.views import datahandling
| 30.5 | 60 | 0.885246 | 7 | 61 | 7.714286 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.065574 | 61 | 1 | 61 | 61 | 0.947368 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 1 | 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 | 1 | 0 | 1 | 1 | 0 | 6 |
f41157fefbc6d65f19d33b6d827711658eaf0f82 | 35 | py | Python | controller/__init__.py | filipefcl/fs-webservice-auth | 1fb5cfe446aaf06c650495b9e8c6862e493304a6 | [
"MIT"
] | 13 | 2021-11-10T13:17:10.000Z | 2022-03-30T22:56:52.000Z | controller/__init__.py | filipefcl/fs-webservice-auth | 1fb5cfe446aaf06c650495b9e8c6862e493304a6 | [
"MIT"
] | 33 | 2022-01-14T14:15:57.000Z | 2022-03-28T22:34:47.000Z | controller/__init__.py | filipefcl/fs-webservice-auth | 1fb5cfe446aaf06c650495b9e8c6862e493304a6 | [
"MIT"
] | 2 | 2022-02-14T22:40:29.000Z | 2022-02-27T04:27:48.000Z | from .controller import Controller
| 17.5 | 34 | 0.857143 | 4 | 35 | 7.5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.114286 | 35 | 1 | 35 | 35 | 0.967742 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
f43595a0783fdc2eaea98f38188f620fb68cd94d | 118 | py | Python | transmutator/api.py | mozilla-services/transmutator | 68894a08d2b97be1010cd8de3c98c06ded17bb92 | [
"BSD-3-Clause"
] | 1 | 2019-05-16T02:16:53.000Z | 2019-05-16T02:16:53.000Z | transmutator/api.py | mozilla-services/transmutator | 68894a08d2b97be1010cd8de3c98c06ded17bb92 | [
"BSD-3-Clause"
] | null | null | null | transmutator/api.py | mozilla-services/transmutator | 68894a08d2b97be1010cd8de3c98c06ded17bb92 | [
"BSD-3-Clause"
] | 2 | 2019-05-16T02:16:39.000Z | 2019-11-03T23:41:06.000Z | from transmutator.mutations import AtomicMutation # NoQA
from transmutator.orchestration import Orchestrator # NoQA
| 39.333333 | 59 | 0.847458 | 12 | 118 | 8.333333 | 0.666667 | 0.32 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.118644 | 118 | 2 | 60 | 59 | 0.961538 | 0.076271 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
f4420e207eabe9238be41adb512f22ae0669edfa | 16,878 | py | Python | DensityClust/densityCluster_3d.py | LiuChvn/LDC-MGM | 0976b3bae1f63e1a096c0adfe8907fc45dce1272 | [
"MIT"
] | null | null | null | DensityClust/densityCluster_3d.py | LiuChvn/LDC-MGM | 0976b3bae1f63e1a096c0adfe8907fc45dce1272 | [
"MIT"
] | null | null | null | DensityClust/densityCluster_3d.py | LiuChvn/LDC-MGM | 0976b3bae1f63e1a096c0adfe8907fc45dce1272 | [
"MIT"
] | null | null | null | from skimage import filters
import numpy as np
from skimage import measure, morphology
from scipy import ndimage
import time
import matplotlib.pyplot as plt
from DensityClust.clustring_subfunc import \
kc_coord_3d, kc_coord_2d, get_xyz
def densityCluster_3d(data, para):
"""
根据决策图得到聚类中心和聚类中心个数
:param data: 3D data
:param para:
para.rhomin: Minimum density
para.deltamin: Minimum delta
para.v_min: Minimum volume
para.rms: The noise level of the data, used for data truncation calculation
para.sigma: Standard deviation of Gaussian filtering
:return:
NCLUST: number of clusters
centInd: centroid index vector
"""
# 参数初始化
gradmin = para["gradmin"]
rhomin = para["rhomin"]
deltamin = para["deltamin"]
v_min = para["v_min"]
rms = para["rms"]
dc = para['dc']
is_plot = para['is_plot']
k1 = 1 # 第1次计算点的邻域大小
k2 = np.ceil(deltamin).astype(np.int) # 第2次计算点的邻域大小
xx = get_xyz(data) # xx: 3D data coordinates 坐标原点是 1
dim = data.ndim
size_x, size_y, size_z = data.shape
maxed = size_x + size_y + size_z
ND = size_x * size_y * size_z
# Initialize the return result: mask and out
mask = np.zeros_like(data, dtype=np.int)
out = np.zeros_like(data, dtype=np.float)
data_filter = filters.gaussian(data, dc)
rho = data_filter.flatten()
rho_Ind = np.argsort(-rho)
rho_sorted = rho[rho_Ind]
delta, IndNearNeigh, Gradient = np.zeros(ND, np.float), np.zeros(ND, np.int), np.zeros(ND, np.float)
delta[rho_Ind[0]] = np.sqrt(size_x ** 2 + size_y ** 2 + size_z ** 2)
# delta 记录距离，
# IndNearNeigh 记录：两个密度点的联系 % index of nearest neighbor with higher density
IndNearNeigh[rho_Ind[0]] = rho_Ind[0]
t0_ = time.time()
# calculating delta and Gradient
for ii in range(1, ND):
# 密度降序排序后，即密度第ii大的索引(在rho中)
ordrho_ii = rho_Ind[ii]
rho_ii = rho_sorted[ii] # 第ii大的密度值
if rho_ii >= rms:
delta[ordrho_ii] = maxed
point_ii_xy = xx[ordrho_ii, :]
get_value = True # 判断是否需要在大循环中继续执行，默认需要，一旦在小循环中赋值成功，就不在大循环中运行
idex, bt = kc_coord_3d(point_ii_xy, size_z, size_y, size_x, k1)
for ordrho_jj, item in zip(idex, bt):
rho_jj = rho[ordrho_jj] # 根据索引在rho里面取值
dist_i_j = np.sqrt(((point_ii_xy - item) ** 2).sum()) # 计算两点间的距离
gradient = (rho_jj - rho_ii) / dist_i_j
if dist_i_j <= delta[ordrho_ii] and gradient >= 0:
delta[ordrho_ii] = dist_i_j
Gradient[ordrho_ii] = gradient
IndNearNeigh[ordrho_ii] = ordrho_jj
get_value = False
if get_value:
# 表明，在(2 * k1 + 1) * (2 * k1 + 1) * (2 * k1 + 1)的邻域中没有找到比该点高，距离最近的点，则在更大的邻域中搜索
idex, bt = kc_coord_3d(point_ii_xy, size_z, size_y, size_x, k2)
for ordrho_jj, item in zip(idex, bt):
rho_jj = rho[ordrho_jj] # 根据索引在rho里面取值
dist_i_j = np.sqrt(((point_ii_xy - item) ** 2).sum()) # 计算两点间的距离
gradient = (rho_jj - rho_ii) / dist_i_j
if dist_i_j <= delta[ordrho_ii] and gradient >= 0:
delta[ordrho_ii] = dist_i_j
Gradient[ordrho_ii] = gradient
IndNearNeigh[ordrho_ii] = ordrho_jj
get_value = False
if get_value:
delta[ordrho_ii] = k2 + 0.0001
Gradient[ordrho_ii] = -1
IndNearNeigh[ordrho_ii] = ND
else:
IndNearNeigh[ordrho_ii] = ND
delta_sorted = np.sort(-delta) * -1
delta[rho_Ind[0]] = delta_sorted[1]
t1_ = time.time()
print('delata, rho and Gradient are calculated, using %.2f seconds' % (t1_ - t0_))
# 根据密度和距离来确定类中心
clusterInd = -1 * np.ones(ND + 1)
clust_index = np.intersect1d(np.where(rho > rhomin), np.where(delta > deltamin))
clust_num = len(clust_index)
# icl是用来记录第i个类中心在xx中的索引值
icl = np.zeros(clust_num, dtype=int)
n_clump = 0
for ii in range(clust_num):
i = clust_index[ii]
icl[n_clump] = i
n_clump += 1
clusterInd[i] = n_clump
# assignation 将其他非类中心分配到离它最近的类中心中去
# clusterInd = -1 表示该点不是类的中心点，属于其他点，等待被分配到某个类中去
# 类的中心点的梯度Gradient被指定为 - 1
if is_plot == 1:
pass
for i in range(ND):
ordrho_i = rho_Ind[i]
if clusterInd[ordrho_i] == -1: # not centroid
clusterInd[ordrho_i] = clusterInd[IndNearNeigh[ordrho_i]]
else:
Gradient[ordrho_i] = -1 # 将类中心点的梯度设置为-1
clump_volume = np.zeros(n_clump)
for i in range(n_clump):
clump_volume[i] = clusterInd.tolist().count(i + 1)
# centInd [类中心点在xx坐标下的索引值，类中心在centInd的索引值: 代表类别编号]
centInd = []
for i, item in enumerate(clump_volume):
if item >= v_min:
centInd.append([icl[i], i])
centInd = np.array(centInd, np.int)
mask_grad = np.where(Gradient > gradmin)[0]
# 通过梯度确定边界后，还需要进一步利用最小体积来排除假核
n_clump = centInd.shape[0]
clump_sum, clump_volume, clump_peak = np.zeros([n_clump, 1]), np.zeros([n_clump, 1]), np.zeros([n_clump, 1])
clump_Cen, clump_size = np.zeros([n_clump, dim]), np.zeros([n_clump, dim])
clump_Peak = np.zeros([n_clump, dim], np.int)
clump_ii = 0
for i, item in enumerate(centInd):
rho_cluster_i = np.zeros(ND)
index_cluster_i = np.where(clusterInd == (item[1] + 1))[0] # centInd[i, 1] --> item[1] 表示第i个类中心的编号
index_cc = np.intersect1d(mask_grad, index_cluster_i)
rho_cluster_i[index_cluster_i] = rho[index_cluster_i]
rho_cc_mean = rho[index_cc].mean() * 0.2
index_cc_rho = np.where(rho_cluster_i > rho_cc_mean)[0]
index_cluster_rho = np.union1d(index_cc, index_cc_rho)
cl_1_index_ = xx[index_cluster_rho, :] - 1 # -1 是为了在data里面用索引取值(从0开始)
# clusterInd 标记的点的编号是从1开始， 没有标记的点的编号为-1
clustNum = cl_1_index_.shape[0]
cl_i = np.zeros(data.shape, np.int)
for j, item in enumerate(cl_1_index_):
cl_i[item[2], item[1], item[0]] = 1
# 形态学处理
# cl_i = morphology.closing(cl_i) # 做开闭运算会对相邻两个云核的掩膜有影响
L = ndimage.binary_fill_holes(cl_i).astype(int)
L = measure.label(L) # Labeled input image. Labels with value 0 are ignored.
STATS = measure.regionprops(L)
Ar_sum = []
for region in STATS:
coords = region.coords # 经过验证，坐标原点为0
temp = 0
for j, item in enumerate(coords):
temp += data[item[0], item[1], item[2]]
Ar_sum.append(temp)
Ar = np.array(Ar_sum)
ind = np.where(Ar == Ar.max())[0]
L[L != ind[0] + 1] = 0
cl_i = L / (ind[0] + 1)
coords = STATS[ind[0]].coords # 最大的连通域对应的坐标
if coords.shape[0] > v_min:
coords = coords[:, [2, 1, 0]]
clump_i_ = np.zeros(coords.shape[0])
for j, item in enumerate(coords):
clump_i_[j] = data[item[2], item[1], item[0]]
clustsum = clump_i_.sum() + 0.0001 # 加一个0.0001 防止分母为0
clump_Cen[clump_ii, :] = np.matmul(clump_i_, coords) / clustsum
clump_volume[clump_ii, 0] = clustNum
clump_sum[clump_ii, 0] = clustsum
x_i = coords - clump_Cen[clump_ii, :]
clump_size[clump_ii, :] = 2.3548 * np.sqrt((np.matmul(clump_i_, x_i ** 2) / clustsum)
- (np.matmul(clump_i_, x_i) / clustsum) ** 2)
clump_i = data * cl_i
out = out + clump_i
mask = mask + cl_i * (clump_ii + 1)
clump_peak[clump_ii, 0] = clump_i.max()
clump_Peak[clump_ii, [2, 1, 0]] = np.argwhere(clump_i == clump_i.max())[0]
clump_ii += 1
else:
pass
clump_Peak = clump_Peak + 1
clump_Cen = clump_Cen + 1 # python坐标原点是从0开始的，在这里整体加1，改为以1为坐标原点
id_clumps = np.array([item + 1 for item in range(n_clump)], np.int).T
id_clumps = id_clumps.reshape([n_clump, 1])
LDC_outcat = np.column_stack((id_clumps, clump_Peak, clump_Cen, clump_size, clump_peak, clump_sum, clump_volume))
LDC_outcat = LDC_outcat[:clump_ii, :]
return LDC_outcat, mask, out
def densityCluster_2d(data, para):
"""
根据决策图得到聚类中心和聚类中心个数
:param data: 2D data
:param para:
para.rhomin: Minimum density
para.deltamin: Minimum delta
para.v_min: Minimum volume
para.rms: The noise level of the data, used for data truncation calculation
para.dc: Standard deviation of Gaussian filtering
:return:
NCLUST: number of clusters
centInd: centroid index vector
"""
# 参数初始化
gradmin = para["gradmin"]
rhomin = para["rhomin"]
deltamin = para["deltamin"]
v_min = para["v_min"]
rms = para["rms"]
sigma = para['dc']
is_plot = para['is_plot']
k = 1 # 计算点的邻域大小
k2 = np.ceil(deltamin).astype(np.int) # 第2次计算点的邻域大小
xx = get_xyz(data) # xx: 2D data coordinates 坐标原点是 1
dim = data.ndim
mask = np.zeros_like(data, dtype=np.int)
out = np.zeros_like(data, dtype=np.float)
data_filter = filters.gaussian(data, sigma)
size_x, size_y = data.shape
rho = data_filter.flatten()
rho_Ind = np.argsort(-rho)
rho_sorted = rho[rho_Ind]
maxd = size_x + size_y
ND = len(rho)
# delta 记录距离， # IndNearNeigh 记录：两个密度点的联系 % index of nearest neighbor with higher density
delta, IndNearNeigh, Gradient = np.zeros(ND, np.float), np.zeros(ND, np.int), np.zeros(ND, np.float)
delta[rho_Ind[0]] = np.sqrt(size_x ** 2 + size_y ** 2)
IndNearNeigh[rho_Ind[0]] = rho_Ind[0]
t0 = time.time()
# 计算 delta, Gradient
for ii in range(1, ND):
# 密度降序排序后，即密度第ii大的索引（在rho中）
ordrho_ii = rho_Ind[ii]
rho_ii = rho_sorted[ii] # 第ii大的密度值
if rho_ii >= rms:
delta[ordrho_ii] = maxd
point_ii_xy = xx[ordrho_ii, :]
get_value = True # 判断是否需要在大循环中继续执行，默认需要，一旦在小循环中赋值成功，就不在大循环中运行
bt = kc_coord_2d(point_ii_xy, size_y, size_x, k)
for item in bt:
rho_jj = data_filter[item[1] - 1, item[0] - 1]
dist_i_j = np.sqrt(((point_ii_xy - item) ** 2).sum()) # 计算两点间的距离
gradient = (rho_jj - rho_ii) / dist_i_j
if dist_i_j <= delta[ordrho_ii] and gradient >= 0:
delta[ordrho_ii] = dist_i_j
Gradient[ordrho_ii] = gradient
IndNearNeigh[ordrho_ii] = (item[1] - 1) * size_y + item[0] - 1
get_value = False
if get_value: # 表明在小领域中没有找到比该点高，距离最近的点，则进行更大领域的搜索
bt = kc_coord_2d(point_ii_xy, size_y, size_x, k2)
for item in bt:
rho_jj = data_filter[item[1] - 1, item[0] - 1]
dist_i_j = np.sqrt(((point_ii_xy - item) ** 2).sum()) # 计算两点间的距离
gradient = (rho_jj - rho_ii) / dist_i_j
if dist_i_j <= delta[ordrho_ii] and gradient >= 0:
delta[ordrho_ii] = dist_i_j
Gradient[ordrho_ii] = gradient
IndNearNeigh[ordrho_ii] = (item[1] - 1) * size_y + item[0] - 1
get_value = False
if get_value:
delta[ordrho_ii] = k2 + 0.0001
Gradient[ordrho_ii] = -1
IndNearNeigh[ordrho_ii] = ND
else:
IndNearNeigh[ordrho_ii] = ND
delta_sorted = np.sort(-delta) * (-1)
delta[rho_Ind[0]] = delta_sorted[1]
t1 = time.time()
print('delata, rho and Gradient are calculated, using %.2f seconds' % (t1-t0))
# 根据密度和距离来确定类中心
NCLUST = 0
clustInd = -1 * np.ones(ND + 1)
clust_index = np.intersect1d(np.where(rho > rhomin), np.where(delta > deltamin))
clust_num = clust_index.shape[0]
print(clust_num)
# icl是用来记录第i个类中心在xx中的索引值
icl = np.zeros(clust_num, dtype=int)
for ii in range(0, clust_num):
i = clust_index[ii]
icl[NCLUST] = i
NCLUST += 1
clustInd[i] = NCLUST
# assignation
# 将其他非类中心分配到离它最近的类中心中去
# clustInd = -1
# 表示该点不是类的中心点，属于其他点，等待被分配到某个类中去
# 类的中心点的梯度Gradient被指定为 - 1
if is_plot == 1:
plt.scatter(rho, delta, marker='.')
plt.show()
for i in range(ND):
ordrho_i = rho_Ind[i]
if clustInd[ordrho_i] == -1: # not centroid
clustInd[ordrho_i] = clustInd[IndNearNeigh[ordrho_i]]
else:
Gradient[ordrho_i] = -1 # 将类中心点的梯度设置为-1
clustVolume = np.zeros(NCLUST)
for i in range(NCLUST):
clustVolume[i] = clustInd.tolist().count(i + 1)
# % centInd [类中心点在xx坐标下的索引值，
# 类中心在centInd的索引值: 代表类别编号]
centInd = []
for i, item in enumerate(clustVolume):
if item >= v_min:
centInd.append([icl[i], i])
centInd = np.array(centInd, np.int)
mask_grad = np.where(Gradient > gradmin)[0]
# 通过梯度确定边界后，还需要进一步利用最小体积来排除假核
NCLUST = centInd.shape[0]
clustSum, clustVolume, clustPeak = np.zeros([NCLUST, 1]), np.zeros([NCLUST, 1]), np.zeros([NCLUST, 1])
clump_Cen, clustSize = np.zeros([NCLUST, dim]), np.zeros([NCLUST, dim])
clump_Peak = np.zeros([NCLUST, dim], np.int)
clump_ii = 0
for i, item in enumerate(centInd): # centInd[i, 1] --> item[1] 表示第i个类中心的编号
rho_clust_i = np.zeros(ND)
index_clust_i = np.where(clustInd == (item[1] + 1))[0]
index_cc = np.intersect1d(mask_grad, index_clust_i)
rho_clust_i[index_clust_i] = rho[index_clust_i]
if len(index_cc) > 0:
rho_cc_mean = rho[index_cc].mean() * 0.2
else:
rho_cc_mean = rms
index_cc_rho = np.where(rho_clust_i > rho_cc_mean)[0]
index_clust_rho = np.union1d(index_cc, index_cc_rho)
cl_1_index_ = xx[index_clust_rho, :] - 1 # -1 是为了在data里面用索引取值(从0开始)
# clustInd 标记的点的编号是从1开始， 没有标记的点的编号为-1
cl_i = np.zeros(data.shape, np.int)
for j, item in enumerate(cl_1_index_):
cl_i[item[1], item[0]] = 1
# 形态学处理
# cl_i = morphology.closing(cl_i) # 做开闭运算会对相邻两个云核的掩膜有影响
L = ndimage.binary_fill_holes(cl_i).astype(int)
L = measure.label(L) # Labeled input image. Labels with value 0 are ignored.
STATS = measure.regionprops(L)
Ar_sum = []
for region in STATS:
coords = region.coords # 经过验证，坐标原点为0
coords = coords[:, [1, 0]]
temp = 0
for j, item in enumerate(coords):
temp += data[item[1], item[0]]
Ar_sum.append(temp)
Ar = np.array(Ar_sum)
ind = np.where(Ar == Ar.max())[0]
L[L != ind[0] + 1] = 0
cl_i = L / (ind[0] + 1)
coords = STATS[ind[0]].coords # 最大的连通域对应的坐标
clustNum = coords.shape[0]
if clustNum > v_min:
coords = coords[:, [1, 0]]
clump_i_ = np.zeros(coords.shape[0])
for j, item in enumerate(coords):
clump_i_[j] = data[item[1], item[0]]
clustsum = sum(clump_i_) + 0.0001 # 加一个0.0001 防止分母为0
clump_Cen[clump_ii, :] = np.matmul(clump_i_, coords) / clustsum
clustVolume[clump_ii, 0] = clustNum
clustSum[clump_ii, 0] = clustsum
x_i = coords - clump_Cen[clump_ii, :]
clustSize[clump_ii, :] = 2.3548 * np.sqrt((np.matmul(clump_i_, x_i ** 2) / clustsum)
- (np.matmul(clump_i_, x_i) / clustsum) ** 2)
clump_i = data * cl_i
out = out + clump_i
mask = mask + cl_i * (clump_ii + 1)
clustPeak[clump_ii, 0] = clump_i.max()
clump_Peak[clump_ii, [1, 0]] = np.argwhere(clump_i == clump_i.max())[0]
clump_ii += 1
else:
pass
clump_Peak = clump_Peak + 1
clump_Cen = clump_Cen + 1 # python坐标原点是从0开始的，在这里整体加1，改为以1为坐标原点
id_clumps = np.array([item + 1 for item in range(NCLUST)], np.int).T
id_clumps = id_clumps.reshape([NCLUST, 1])
LDC_outcat = np.column_stack((id_clumps, clump_Peak, clump_Cen, clustSize, clustPeak, clustSum, clustVolume))
LDC_outcat = LDC_outcat[:clump_ii, :]
return LDC_outcat, mask, out
if __name__ == '__main__':
pass
| 39.251163 | 118 | 0.563278 | 2,248 | 16,878 | 4.013345 | 0.115214 | 0.024828 | 0.010641 | 0.007094 | 0.806916 | 0.775216 | 0.748171 | 0.723565 | 0.70184 | 0.696298 | 0 | 0.025455 | 0.322669 | 16,878 | 429 | 119 | 39.342657 | 0.763733 | 0.149011 | 0 | 0.617089 | 0 | 0 | 0.014761 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.006329 | false | 0.012658 | 0.022152 | 0 | 0.03481 | 0.009494 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
f44e1abfe2049b273cf288d2e6ba2ea659162f6d | 212 | py | Python | gpim/__init__.py | jupyter-papers/GPim | c9af47696ba613f9ce10c938a4e07b7f96e728ea | [
"MIT"
] | 29 | 2020-02-18T21:41:03.000Z | 2022-03-03T12:23:48.000Z | gpim/__init__.py | jupyter-papers/GPim | c9af47696ba613f9ce10c938a4e07b7f96e728ea | [
"MIT"
] | 2 | 2021-04-30T02:55:18.000Z | 2021-10-04T06:13:46.000Z | gpim/__init__.py | jupyter-papers/GPim | c9af47696ba613f9ce10c938a4e07b7f96e728ea | [
"MIT"
] | 7 | 2020-03-10T02:14:50.000Z | 2021-04-29T00:03:43.000Z | from gpim import gprutils as utils
from gpim.gpreg.gpr import reconstructor
from gpim.gpreg.skgpr import skreconstructor
from gpim.gpreg.vgpr import vreconstructor
from gpim.gpbayes.boptim import boptimizer
| 35.333333 | 45 | 0.834906 | 30 | 212 | 5.9 | 0.533333 | 0.225989 | 0.220339 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.127358 | 212 | 5 | 46 | 42.4 | 0.956757 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
f46de4637fb3c38cfd51413578d63c5af3e3e769 | 2,203 | py | Python | tests/core/actions/add_user/test_add_user_request.py | Himon-SYNCRAFT/taskplus | 9e6293840941d0cb4fd7bac0f8ff66f8e72cc62b | [
"BSD-3-Clause"
] | null | null | null | tests/core/actions/add_user/test_add_user_request.py | Himon-SYNCRAFT/taskplus | 9e6293840941d0cb4fd7bac0f8ff66f8e72cc62b | [
"BSD-3-Clause"
] | null | null | null | tests/core/actions/add_user/test_add_user_request.py | Himon-SYNCRAFT/taskplus | 9e6293840941d0cb4fd7bac0f8ff66f8e72cc62b | [
"BSD-3-Clause"
] | null | null | null | from taskplus.core.actions import AddUserRequest
def test_add_user_request():
role_id = 1
name = 'name'
password = 'password'
request = AddUserRequest(name=name, password=password, roles=[role_id])
assert request.is_valid() is True
assert request.name == name
assert request.roles == [role_id]
def test_add_user_bad_request():
role_id = 'abc'
name = 1
password = 1
request = AddUserRequest(name=name, password=password, roles=role_id)
assert request.is_valid() is False
assert len(request.errors) == 3
errors = request.errors
assert any([param == 'roles' and message == "expected list, got str(abc)"
for param, message in errors])
assert any([param == 'name' and message == "expected str, got int(1)"
for param, message in errors])
assert any([param == 'password' and message == "expected str, got int(1)"
for param, message in errors])
def test_add_user_bad_request2():
role_id = 'abc'
name = 1
password = 1
request = AddUserRequest(name=name, password=password, roles=[role_id])
assert request.is_valid() is False
assert len(request.errors) == 3
errors = request.errors
message_roles = "expected all elements to be int, got str(abc) at index 0"
assert any([param == 'roles' and message == message_roles
for param, message in errors])
assert any([param == 'name' and message == "expected str, got int(1)"
for param, message in errors])
assert any([param == 'password' and message == "expected str, got int(1)"
for param, message in errors])
def test_add_user_request_without_data():
request = AddUserRequest(name=None, password=None, roles=None)
assert request.is_valid() is False
assert len(request.errors) == 3
errors = request.errors
assert any([param == 'roles' and message == "is required"
for param, message in errors])
assert any([param == 'name' and message == "is required"
for param, message in errors])
assert any([param == 'password' and message == "is required"
for param, message in errors])
| 35.532258 | 78 | 0.64049 | 289 | 2,203 | 4.782007 | 0.17301 | 0.058611 | 0.091172 | 0.110709 | 0.79233 | 0.757598 | 0.736614 | 0.736614 | 0.736614 | 0.712735 | 0 | 0.008459 | 0.248752 | 2,203 | 61 | 79 | 36.114754 | 0.826586 | 0 | 0 | 0.612245 | 0 | 0 | 0.127553 | 0 | 0 | 0 | 0 | 0 | 0.367347 | 1 | 0.081633 | false | 0.204082 | 0.020408 | 0 | 0.102041 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 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 | 6 |
be4623e9600255e403d6473819d56bf97fd8a23e | 31,990 | py | Python | algorithm/algorithms.py | divergent63/SCII_Bots | d118abfdaf73b4cf891ba47405c38d07ae7c760e | [
"Apache-2.0"
] | null | null | null | algorithm/algorithms.py | divergent63/SCII_Bots | d118abfdaf73b4cf891ba47405c38d07ae7c760e | [
"Apache-2.0"
] | null | null | null | algorithm/algorithms.py | divergent63/SCII_Bots | d118abfdaf73b4cf891ba47405c38d07ae7c760e | [
"Apache-2.0"
] | null | null | null | import random
import numpy as np
import pickle
import pandas as pd
import os, sys
from absl import app, logging
from pysc2.agents import base_agent
from pysc2.lib import actions, features, units
from pysc2.env import sc2_env, run_loop
from pathlib import Path
from matplotlib import pyplot as plt
import torch
from torch.autograd import Variable
from torch import nn
import model.models as models
from model.models import SimpleConvNet_prob, SimpleConvNet_val
sys.path.append('../')
class SupervisedDeepLearning:
def __init__(self, model_path, learning_rate=0.01, reward_decay=0.9):
self.learning_rate = learning_rate
self.reward_decay = reward_decay
self.feature_screen = 27
self.feature_minimap = 11
self.out_action = 12
self.out_point = 4096
# model_p = models.SimpleConvNet_prob(input_size=[self.feature_screen, self.feature_minimap], output_size=[self.out_action, self.out_point])
model_v = models.SimpleConvNet_val(input_size=[self.feature_screen, self.feature_minimap], output_size=[self.out_action, self.out_point])
self.model = model_v.cuda() if torch.cuda.is_available() else model_v
print('model: \n', self.model)
self.criterion = nn.MSELoss()
# model_path = Path(Path(os.getcwd()) / 'save' / 'dqn' / 'Simple64-dqn-best.pt')
if Path(model_path).exists():
self.model.load_state_dict(torch.load(model_path))
self. critic_optim = torch.optim.Adam(self.model.parameters(), lr=0.01)
def learn(self, history_raw, id_from_actions, epochs=3):
batch_size = len(history_raw )//40
critic_network_loss_lst = []
# history_raw: [e, time, state_model, state_model_next, action, actual_action, last_action, point, reward, score, done]
for epoch in range(epochs):
history = random.sample(history_raw, batch_size)
e, time, state_model, state_model_next, action, actual_action, last_action, point, reward, score, done = zip \
(*history)
# for _ in range(len(history)):
# idx = random.randint(0, len(history) - 1)
state_tensor_lst = [[Variable
(torch.Tensor(state_model[b][i]).float()).cuda() if torch.cuda.is_available() else Variable
(torch.Tensor(state_model[b][i]).float()) for i in range(3)] for b in range(len(history))]
state_tensor_batch_lst = [torch.cat([state_tensor_lst[b][i].unsqueeze(0) for b in range(len(history))]) for i in range(3)]
next_state_tensor_lst = [[Variable
(torch.Tensor(state_model_next[b][i]).float()).cuda() if torch.cuda.is_available() else Variable
(torch.Tensor(state_model_next[b][i]).float()) for i in range(3)] for b in range(len(history))]
next_state_tensor_batch_lst = \
[torch.cat([next_state_tensor_lst[b][i].unsqueeze(0) for b in range(len(history))]) for i in range(3)]
q_predict = self.model(state_tensor_batch_lst)
q_predict_lst = [self.model(state_tensor_batch_lst)[i].detach().cpu().numpy() for i in range(2)] # state
q_predict_nxt = self.model(next_state_tensor_batch_lst)
q_predict_nxt_lst = [self.model(next_state_tensor_batch_lst)[i].detach().cpu().numpy() for i in
range(2)] # next_state
r_with_a = np.zeros((batch_size, len(id_from_actions)))
r_with_ap = np.zeros((batch_size, 4096))
for b in range(len(history)):
r_with_a[b][id_from_actions[actual_action[b]]] = reward[b][0]
r_with_ap[b][point[b]] = reward[b][1]
r = r_with_a # reward
rp = r_with_ap
if done is not True: # if done is not True:
# q_target = r + self.reward_decay * max(q_predict_nxt[0].detach().cpu().numpy()[0])
# q_target = r + self.reward_decay * q_predict_nxt[0] * (1-done)
q_target = r + self.reward_decay * q_predict_nxt[0].detach().cpu().numpy() # * (1 - np.array(done))
qp_target = rp + self.reward_decay * q_predict_nxt[1].detach().cpu().numpy()
else:
q_target = r
qp_target = rp
# train value network
# self.critic_optim.zero_grad()
target_values = Variable(torch.Tensor(q_target).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(q_target).float())
target_values_p = Variable(
torch.Tensor(qp_target).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(qp_target).float())
# values = model_critic([states_var_screen, states_var_minimap, states_var_player])
critic_network_loss = self.criterion(q_predict[0], target_values) + self.criterion(q_predict[1],
target_values_p) # + criterion(q_predict[1], target_values)
print('epoch: ', epoch, ' critic_network_loss: \n', critic_network_loss, '\n')
critic_network_loss_lst.append(float(critic_network_loss.detach().cpu().numpy()))
self.critic_optim.zero_grad()
critic_network_loss.backward()
# torch.nn.utils.clip_grad_norm(self.model.parameters(), 0.5)
self.critic_optim.step()
return critic_network_loss_lst
def save(self, name):
if self.model:
torch.save(self.model.state_dict(), name)
class DeepQLearning:
"""
Natural-DQN with self.copy() after 'done == True'
"""
def __init__(self, model_path, learning_rate=0.01, reward_decay=0.9):
self.learning_rate = learning_rate
self.reward_decay = reward_decay
self.feature_screen = 27
self.feature_minimap = 11
self.out_action = 12
self.out_point = 4096
# model_p = models.SimpleConvNet_prob(input_size=[self.feature_screen, self.feature_minimap], output_size=[self.out_action, self.out_point])
model_v = models.SimpleConvNet_val(input_size=[self.feature_screen, self.feature_minimap],
output_size=[self.out_action, self.out_point])
model_v_process = models.SimpleConvNet_val(input_size=[self.feature_screen, self.feature_minimap],
output_size=[self.out_action, self.out_point])
self.model = model_v.cuda() if torch.cuda.is_available() else model_v
self.model_process = model_v_process.cuda() if torch.cuda.is_available() else model_v_process
print('model: \n', self.model)
self.criterion = nn.MSELoss()
# model_path = Path(Path(os.getcwd()) / 'save' / 'dqn' / 'Simple64-dqn-best.pt')
if Path(model_path).exists():
self.model.load_state_dict(torch.load(model_path))
self.critic_optim = torch.optim.Adam(self.model.parameters(), lr=0.01)
def choose_action_p(self, state, init=False, e_greedy=0.2):
ep = np.random.random()
if not init and ep < e_greedy: # TODO: can't understand the probability matrix from uniform distribution --> SOLVED
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1)[0]], np.random.randint(4096)
p1 = Variable(torch.Tensor(
np.random.dirichlet(np.ones(self.out_action),
size=1)).cuda() if torch.cuda.is_available() else torch.Tensor(
np.random.dirichlet(np.ones(self.out_action), size=1)))
p2 = Variable(torch.Tensor(
np.random.dirichlet(np.ones(self.out_point),
size=1)).cuda() if torch.cuda.is_available() else torch.Tensor(
np.random.dirichlet(np.ones(self.out_point), size=1)))
# print("explored actions")
return [p1, p2]
else:
# state.append(np.zeros((1, 1)))
preds = self.model_process(state)
# print("learned actions")
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1, p=preds[1][0])[0]], np.random.choice(len(self.action_from_id), 1, p=preds[2][0])[0]
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1, p=preds[0].cpu().detach().numpy())[0]], np.random.choice(4096, 1, p=preds[1].cpu().detach().numpy())[0]
# return np.random.choice(list(self.action_from_id.values()), 1, p=preds[0].cpu().detach().numpy())[0], \
# np.random.choice(4096, 1, p=preds[1].cpu().detach().numpy())[0]
return preds
def choose_action_v(self, state, init=False, e_greedy=0.2):
ep = np.random.random()
if not init and ep < e_greedy: # TODO: can't understand the probability matrix from uniform distribution --> SOLVED
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1)[0]], np.random.randint(4096)
v1, v2 = np.reshape(np.random.rand(self.out_action), (1, self.out_action)), np.reshape(
np.random.rand(self.out_point), (1, self.out_point))
# print("explored actions")
return [
Variable(torch.Tensor(v1).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(v1).float()),
Variable(torch.Tensor(v2).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(v2).float())
]
else:
# state.append(np.zeros((1, 1)))
v = self.model_process(state)
# print("learned actions")
return v
def learn(self, history_raw, id_from_actions, epochs=3):
batch_size = len(history_raw) // 16
critic_network_loss_lst = []
# history_raw: [e, time, state_model, state_model_next, action, actual_action, last_action, point, reward, score, done]
for epoch in range(epochs):
history = random.sample(history_raw, batch_size)
e, time, state_model, state_model_next, action, actual_action, last_action, point, reward, score, done = zip(
*history)
# for _ in range(len(history)):
# idx = random.randint(0, len(history) - 1)
state_tensor_lst = [[Variable(
torch.Tensor(state_model[b][i]).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(state_model[b][i]).float()) for i in range(3)] for b in range(len(history))]
state_tensor_batch_lst = [torch.cat([state_tensor_lst[b][i].unsqueeze(0) for b in range(len(history))]) for
i in range(3)]
next_state_tensor_lst = [[Variable(
torch.Tensor(state_model_next[b][i]).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(state_model_next[b][i]).float()) for i in range(3)] for b in range(len(history))]
next_state_tensor_batch_lst = [
torch.cat([next_state_tensor_lst[b][i].unsqueeze(0) for b in range(len(history))]) for i in range(3)]
q_predict = self.model(state_tensor_batch_lst)
q_predict_lst = [self.model(state_tensor_batch_lst)[i].detach().cpu().numpy() for i in range(2)] # state
q_predict_nxt = self.model(next_state_tensor_batch_lst)
q_predict_nxt_lst = [self.model(next_state_tensor_batch_lst)[i].detach().cpu().numpy() for i in
range(2)] # next_state
r_with_a = np.zeros((batch_size, len(id_from_actions)))
r_with_ap = np.zeros((batch_size, 4096))
for b in range(len(history)):
r_with_a[b][id_from_actions[actual_action[b]]] = reward[b][0]
r_with_ap[b][point[b]] = reward[b][1]
r = r_with_a # reward
rp = r_with_ap
if done is not True: # if done is not True:
# q_target = r + self.reward_decay * max(q_predict_nxt[0].detach().cpu().numpy()[0])
# q_target = r + self.reward_decay * q_predict_nxt[0] * (1-done)
q_target = r + self.reward_decay * q_predict_nxt[0].detach().cpu().numpy() # * (1 - np.array(done))
qp_target = rp + self.reward_decay * q_predict_nxt[1].detach().cpu().numpy()
else:
q_target = r
qp_target = rp
# train value network
# self.critic_optim.zero_grad()
target_values = Variable(torch.Tensor(q_target).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(q_target).float())
target_values_p = Variable(
torch.Tensor(qp_target).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(qp_target).float())
# values = model_critic([states_var_screen, states_var_minimap, states_var_player])
critic_network_loss = self.criterion(q_predict[0], target_values) + self.criterion(q_predict[1],
target_values_p) # + criterion(q_predict[1], target_values)
# print('epoch: ', epoch, ' critic_network_loss: \n', critic_network_loss, '\n')
critic_network_loss_lst.append(float(critic_network_loss.detach().cpu().numpy()))
self.critic_optim.zero_grad()
critic_network_loss.backward()
torch.nn.utils.clip_grad_norm(self.model.parameters(), 0.5)
self.critic_optim.step()
return critic_network_loss_lst
def save(self, name):
if self.model:
torch.save(self.model.state_dict(), name)
def copy(self):
for target_param, param in zip(self.model.parameters(), self.model_process.parameters()):
param.data.copy_(target_param.data)
class AdvantageActorCritic:
"""
Advantage Actor-Critic
"""
def __init__(self, model_path, learning_rate=0.01, reward_decay=0.9):
self.learning_rate = learning_rate
self.reward_decay = reward_decay
self.feature_screen = 27
self.feature_minimap = 11
self.out_action = 12
self.out_point = 4096
# <obs[0].observation.feature_screen.shape(1) = 27> + <obs[0].observation.feature_screen.shape(1) = 11> = 38
model_actor = models.SimpleConvNet_prob(input_size=[27, 11], output_size=[len(categorical_actions), 4096])
model_actor = model_actor.cuda() if torch.cuda.is_available() else model_actor
model_critic = models.SimpleConvNet_val(input_size=[27, 11], output_size=1)
model_critic = model_critic.cuda() if torch.cuda.is_available() else model_critic
model = [model_actor, model_critic]
# model = None
print(model[0], model[1])
self.criterion = nn.MSELoss()
# model_path = Path(Path(os.getcwd()) / 'save' / 'dqn' / 'Simple64-dqn-best.pt')
if Path(model_path).exists():
self.model.load_state_dict(torch.load(model_path))
self.critic_optim = torch.optim.Adam(self.model.parameters(), lr=0.01)
def choose_action_p(self, state, init=False, e_greedy=0.2):
ep = np.random.random()
if not init and ep < e_greedy: # TODO: can't understand the probability matrix from uniform distribution --> SOLVED
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1)[0]], np.random.randint(4096)
p1 = Variable(torch.Tensor(
np.random.dirichlet(np.ones(self.out_action),
size=1)).cuda() if torch.cuda.is_available() else torch.Tensor(
np.random.dirichlet(np.ones(self.out_action), size=1)))
p2 = Variable(torch.Tensor(
np.random.dirichlet(np.ones(self.out_point),
size=1)).cuda() if torch.cuda.is_available() else torch.Tensor(
np.random.dirichlet(np.ones(self.out_point), size=1)))
# print("explored actions")
return [p1, p2]
else:
# state.append(np.zeros((1, 1)))
preds = self.model_process(state)
return preds
def choose_action_v(self, state, init=False, e_greedy=0.2):
ep = np.random.random()
if not init and ep < e_greedy: # TODO: can't understand the probability matrix from uniform distribution --> SOLVED
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1)[0]], np.random.randint(4096)
v1, v2 = np.reshape(np.random.rand(self.out_action), (1, self.out_action)), np.reshape(
np.random.rand(self.out_point), (1, self.out_point))
# print("explored actions")
return [
Variable(torch.Tensor(v1).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(v1).float()),
Variable(torch.Tensor(v2).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(v2).float())
]
else:
# state.append(np.zeros((1, 1)))
v = self.model_process(state)
# print("learned actions")
return v
def learn(self, history_raw, id_from_actions, epochs=3):
batch_size = len(history_raw) // 16
critic_network_loss_lst = []
# history_raw: [e, time, state_model, state_model_next, action, actual_action, last_action, point, reward, score, done]
for epoch in range(epochs):
history = random.sample(history_raw, batch_size)
e, time, state_model, state_model_next, action, actual_action, last_action, point, reward, score, done = zip(
*history)
# for _ in range(len(history)):
# idx = random.randint(0, len(history) - 1)
state_tensor_lst = [[Variable(
torch.Tensor(state_model[b][i]).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(state_model[b][i]).float()) for i in range(3)] for b in range(len(history))]
state_tensor_batch_lst = [torch.cat([state_tensor_lst[b][i].unsqueeze(0) for b in range(len(history))]) for
i in range(3)]
next_state_tensor_lst = [[Variable(
torch.Tensor(state_model_next[b][i]).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(state_model_next[b][i]).float()) for i in range(3)] for b in range(len(history))]
next_state_tensor_batch_lst = [
torch.cat([next_state_tensor_lst[b][i].unsqueeze(0) for b in range(len(history))]) for i in range(3)]
q_predict = self.model(state_tensor_batch_lst)
q_predict_lst = [self.model(state_tensor_batch_lst)[i].detach().cpu().numpy() for i in range(2)] # state
q_predict_nxt = self.model(next_state_tensor_batch_lst)
q_predict_nxt_lst = [self.model(next_state_tensor_batch_lst)[i].detach().cpu().numpy() for i in
range(2)] # next_state
r_with_a = np.zeros((batch_size, len(id_from_actions)))
r_with_ap = np.zeros((batch_size, 4096))
for b in range(len(history)):
r_with_a[b][id_from_actions[actual_action[b]]] = reward[b][0]
r_with_ap[b][point[b]] = reward[b][1]
r = r_with_a # reward
rp = r_with_ap
if done is not True: # if done is not True:
# q_target = r + self.reward_decay * max(q_predict_nxt[0].detach().cpu().numpy()[0])
# q_target = r + self.reward_decay * q_predict_nxt[0] * (1-done)
q_target = r + self.reward_decay * q_predict_nxt[0].detach().cpu().numpy() # * (1 - np.array(done))
qp_target = rp + self.reward_decay * q_predict_nxt[1].detach().cpu().numpy()
else:
q_target = r
qp_target = rp
# train value network
# self.critic_optim.zero_grad()
target_values = Variable(torch.Tensor(q_target).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(q_target).float())
target_values_p = Variable(
torch.Tensor(qp_target).float()).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(qp_target).float())
# values = model_critic([states_var_screen, states_var_minimap, states_var_player])
critic_network_loss = self.criterion(q_predict[0], target_values) + self.criterion(q_predict[1],
target_values_p) # + criterion(q_predict[1], target_values)
# print('epoch: ', epoch, ' critic_network_loss: \n', critic_network_loss, '\n')
critic_network_loss_lst.append(float(critic_network_loss.detach().cpu().numpy()))
self.critic_optim.zero_grad()
critic_network_loss.backward()
torch.nn.utils.clip_grad_norm(self.model.parameters(), 0.5)
self.critic_optim.step()
return critic_network_loss_lst
def save(self, name):
if self.model:
torch.save(self.model.state_dict(), name)
def copy(self):
for target_param, param in zip(self.model.parameters(), self.model_process.parameters()):
param.data.copy_(target_param.data)
class AdvantageActorCritic_bak:
"""This class implements the random walking agent using the network model"""
def __init__(self, model, categorical_actions, spatial_actions, id_from_actions, action_from_id):
self.states = []
self.next_states = []
self.rewards = []
self.actions = []
self.points = []
self.score = []
# self.policy_predictions=[]
# self.spatial_predictions=[]
self.gamma = 0.95 # discount rate
self.categorical_actions = categorical_actions
self.spatial_actions = spatial_actions
self.model = model[0] # Actor
self.value_model = model[1] # Critic
# self.epsilon = 0.5
self.id_from_actions = id_from_actions
self.action_from_id = action_from_id
def update_epsilon(self):
if self.epsilon > 0.1:
self.epsilon = 0.999 * self.epsilon
def append_sample(self, states, last_actions, actions, rewards, scores):
self.states.append(states)
self.next_states.append(last_actions)
self.actions.append(actions)
self.rewards.append(rewards)
self.score.append(scores)
return [states, last_actions, actions, rewards, scores]
# def discount_rewards(self, rewards):
# discounted_rewards = np.zeros_like(rewards)
# running_add = 0
# for t in reversed(range(0, len(rewards))):
# running_add = running_add * self.gamma + rewards[t]
# discounted_rewards[t] = running_add
# return discounted_rewards
def discount_rewards(self, rewards, final_r):
discounted_r = np.zeros_like(rewards)
running_add = final_r
for t in reversed(range(0, len(rewards))):
running_add = running_add * self.gamma + rewards[t]
discounted_r[t] = running_add
return discounted_r
def act(self, state, init=False, epsilon=0.2):
ep = np.random.random()
if not init and ep < epsilon: # TODO: can't understand the probability matrix from uniform distribution --> SOLVED
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1)[0]], np.random.randint(4096)
p1 = Variable(torch.Tensor(np.random.dirichlet(np.ones(11), size=1)).cuda() if torch.cuda.is_available() else torch.Tensor(np.random.dirichlet(np.ones(11), size=1)))
p2 = Variable(torch.Tensor(np.random.dirichlet(np.ones(4096), size=1)).cuda() if torch.cuda.is_available() else torch.Tensor(np.random.dirichlet(np.ones(4096), size=1)))
print("explored actions")
return [p1, p2]
else:
# state.append(np.zeros((1, 1)))
preds = self.model(state)
print("learned actions")
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1, p=preds[1][0])[0]], np.random.choice(len(self.action_from_id), 1, p=preds[2][0])[0]
# return self.action_from_id[np.random.choice(len(self.action_from_id), 1, p=preds[0].cpu().detach().numpy())[0]], np.random.choice(4096, 1, p=preds[1].cpu().detach().numpy())[0]
# return np.random.choice(list(self.action_from_id.values()), 1, p=preds[0].cpu().detach().numpy())[0], \
# np.random.choice(4096, 1, p=preds[1].cpu().detach().numpy())[0]
return preds
def act_randomly(self):
return self.action_from_id[np.random.choice(
len(self.action_from_id), 1
)[0]], np.random.randint(4096)
def train(self):
episode_length = len(self.states)
discounted_rewards = self.discount_rewards(self.rewards)
# Standardized discounted rewards
"""discounted_rewards -= np.mean(discounted_rewards)
if np.std(discounted_rewards):
discounted_rewards /= np.std(discounted_rewards)
else:
self.states, self.actions, self.rewards = [], [], []
#print ('std = 0!')
return 0"""
update_inputs = [np.zeros((episode_length, 27, 64, 64)),
np.zeros((episode_length, 11, 64, 64)),
np.zeros((episode_length, 11,))
# np.zeros((episode_length, 1))
] # Episode_lengthx64x64x4
# Episode length is like the minibatch size in DQN
for i in range(episode_length):
update_inputs[0][i, :, :, :] = self.states[i][0][0, :, :, :]
update_inputs[1][i, :, :, :] = self.states[i][1][0, :, :, :]
update_inputs[2][i, :] = self.states[i][2][0, :]
r = np.vstack(self.rewards)
update_inputs.append(np.zeros((episode_length, 1)))
values = self.model.predict(update_inputs)[0]
r = r + self.gamma * values
update_inputs[3] = r
advantages_actions = np.zeros((episode_length, len(self.id_from_actions)))
advantages_space = np.zeros((episode_length, 4096))
for i in range(episode_length):
advantages_actions[i][self.actions[i]] = discounted_rewards[i] - float(values[i])
advantages_space[i][self.points[i]] = discounted_rewards[i] - float(values[i])
self.model.fit(update_inputs, [discounted_rewards, advantages_actions, advantages_space], epochs=3, verbose=2)
self.states, self.actions, self.rewards = [], [], []
self.update_epsilon()
def learn(self):
actor_network_losses = []
critic_network_losses = []
# for n in range(len(agent.states)):
# # train
# # out_spatial, out_non_spatial = model(state_model)
# if score > score_pre:
# history_arr = np.array(history)
# np.savez_compressed('./save/history_random.npz', history)
# agent.save("./save/Simple64-rand.pt")
# score_pre = score
# init_state = agent.states[n]
actions_var_action = Variable(
torch.Tensor([agent.actions[i][0] for i in range(len(agent.actions))]).view(-1, len(categorical_actions)))
actions_var_point = Variable(
torch.Tensor([agent.actions[i][1] for i in range(len(agent.actions))]).view(-1, 4096))
states_var_screen = Variable(
torch.Tensor([agent.states[i][0] for i in range(len(agent.states))]).view(-1, 27, 64, 64))
states_var_minimap = Variable(
torch.Tensor([agent.states[i][1] for i in range(len(agent.states))], ).view(-1, 11, 64, 64))
states_var_player = Variable(
torch.Tensor([agent.states[i][2] for i in range(len(agent.states))], ).view(-1, 11))
batch_size = 33
train_dataloader = DataLoader([
states_var_screen, states_var_minimap, states_var_player, actions_var_action, actions_var_point
], batch_size=batch_size, shuffle=False)
train_dataloader_screen = DataLoader(states_var_screen, batch_size=batch_size, shuffle=False)
train_dataloader_map = DataLoader(states_var_minimap, batch_size=batch_size, shuffle=False)
train_dataloader_play = DataLoader(states_var_player, batch_size=batch_size, shuffle=False)
train_dataloader_a = DataLoader(actions_var_point, batch_size=batch_size, shuffle=False)
train_dataloader_p = DataLoader(actions_var_point, batch_size=batch_size, shuffle=False)
qs = DataLoader(Variable(torch.Tensor(
agent.discount_rewards(agent.rewards, reward))).cuda() if torch.cuda.is_available() else Variable(
torch.Tensor(agent.discount_rewards(agent.rewards))), batch_size=batch_size, shuffle=False)
for i in range(train_dataloader.dataset[0].data.shape[0] // batch_size):
# Display image and label.
train_dataloader_screen_var = next(iter(train_dataloader_screen))
train_dataloader_map_var = next(iter(train_dataloader_map))
train_dataloader_player_var = next(iter(train_dataloader_play))
train_dataloader_a_var = next(iter(train_dataloader_a))
train_dataloader_p_var = next(iter(train_dataloader_p))
# img = states_var_screen_batch[0].squeeze()
# plt.imshow(img, cmap="gray")
# plt.show()
# states_var = Variable(torch.Tensor(next_state_model).view(-1, len(38*64*64)))
# train actor network
model_actor.zero_grad()
log_softmax_actions_1, log_softmax_actions_2 = model_actor(
[train_dataloader_screen_var, train_dataloader_map_var, train_dataloader_player_var])
vs = model_critic([train_dataloader_screen_var, train_dataloader_map_var, train_dataloader_player_var])
# calculate qs
qs_var = next(iter(qs))
advantages = qs_var - vs.detach().squeeze(1)
actor_network_loss = - torch.mean(
torch.sum(log_softmax_actions_1.cpu() * train_dataloader_a_var, 1) * advantages.cpu()) - torch.mean(
torch.sum(log_softmax_actions_2.cpu() * train_dataloader_p_var, 1) * advantages.cpu())
actor_network_loss.backward()
torch.nn.utils.clip_grad_norm(model_actor.parameters(), 0.5)
actor_optim.step()
# train value network
critic_optim.zero_grad()
target_values = qs_var
# values = model_critic([states_var_screen, states_var_minimap, states_var_player])
criterion = nn.MSELoss()
critic_network_loss = criterion(vs, target_values)
critic_network_loss.backward()
torch.nn.utils.clip_grad_norm(model_critic.parameters(), 0.5)
critic_optim.step()
actor_network_losses.append(float(actor_network_loss.detach().numpy()))
critic_network_losses.append(float(critic_network_loss.cpu().detach().numpy()))
return [actor_network_losses, critic_network_losses]
def load(self, name):
if self.model and self.value_model:
self.model.load_state_dict(torch.load(name[0]))
self.value_model.load_state_dict(torch.load(name[1]))
def save(self, name):
if self.model and self.value_model:
torch.save(self.model.state_dict(), name[0])
torch.save(self.value_model.state_dict(), name[1])
| 51.680129 | 190 | 0.612691 | 4,229 | 31,990 | 4.398912 | 0.064791 | 0.025157 | 0.046982 | 0.022577 | 0.812772 | 0.788582 | 0.75762 | 0.740257 | 0.722679 | 0.709455 | 0 | 0.01942 | 0.261175 | 31,990 | 618 | 191 | 51.763754 | 0.767675 | 0.192904 | 0 | 0.59952 | 0 | 0 | 0.003547 | 0 | 0 | 0 | 0 | 0.003236 | 0 | 1 | 0.059952 | false | 0 | 0.038369 | 0.002398 | 0.148681 | 0.014388 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
be66c6795f15d7778f05b739c1979167150bc613 | 83,277 | py | Python | Cookie Synchronization/final_cs_analysis.py | vibhor98/Web-Tracking-in-Indian-Partisan-News-Websites | f68c4ae011a499c0519bed0b0cb953a12f438902 | [
"MIT"
] | 1 | 2021-01-31T18:03:51.000Z | 2021-01-31T18:03:51.000Z | Cookie Synchronization/final_cs_analysis.py | vibhor98/Web-Tracking-in-Indian-Partisan-News-Websites | f68c4ae011a499c0519bed0b0cb953a12f438902 | [
"MIT"
] | null | null | null | Cookie Synchronization/final_cs_analysis.py | vibhor98/Web-Tracking-in-Indian-Partisan-News-Websites | f68c4ae011a499c0519bed0b0cb953a12f438902 | [
"MIT"
] | 2 | 2021-01-31T16:48:13.000Z | 2021-05-28T15:33:48.000Z | '''
Finding TP to TP and TP to FP CS Tracking for each website pair by political leaning
'''
import sys
sys.path.append("../Cookie Synchronization Analysis")
import matplotlib.pyplot as plt
import pandas as pd
import requests
import census_util
import classify_domains
import find_site_leaning
import sqlite3 as lite
import seaborn as sns
import os
import re
# Enter path to the folder containing OpenWPM crawls data.
DATA_DIR = os.path.join(os.path.abspath(os.pardir), 'OpenWPM Crawls')
#######################################################
# check if a given domain is present as a url or referrer in any openwpm crawled data in same request-response communication pair.
# If yes, it returns finds whether its a TP or FP and adds it to a list containing unique TP-TP pairs or TP-FP pairs.
def get_sync_cat(tp_domains, fp_domains, url, referrer, cat1, cat2, cat1cat2, flag, u_id_synced, u_tp_tp_synced,
u_tp_fp_synced):
dom1 = dom2 = ""
for abc in sorted(list(set(tp_domains).union(set(fp_domains))), key=len, reverse=True):
for pqr in sorted(list(set(tp_domains).union(set(fp_domains))), key=len, reverse=True):
if abc != pqr and (abc in url and pqr in referrer) or (abc in referrer and pqr in url):
if abc in tp_domains:
cat1 = "TP"
elif abc in fp_domains:
cat1 = "FP"
if pqr in tp_domains:
cat2 = "TP"
elif pqr in fp_domains:
cat2 = "FP"
if cat1 == "TP":
cat1cat2 = cat1 + "-" + cat2
elif cat2 == "TP":
cat1cat2 = cat2 + "-" + cat1
dom1 = abc
dom2 = pqr
flag = 1
break
if flag == 1:
if k not in u_id_synced:
u_id_synced.append(k)
if cat1cat2 == "TP-TP" and ((abc, pqr) not in u_tp_tp_synced) and ((pqr, abc) not in u_tp_tp_synced):
u_tp_tp_synced.append((abc, pqr))
elif cat1cat2 == "TP-FP" and ((abc, pqr) not in u_tp_fp_synced) and ((pqr, abc) not in u_tp_fp_synced):
u_tp_fp_synced.append((abc, pqr))
return cat1cat2, flag, u_id_synced, u_tp_tp_synced, u_tp_fp_synced, dom1, dom2
return "NOSYNC", 0, u_id_synced, u_tp_tp_synced, u_tp_fp_synced, dom1, dom2
#######################################################
# You may select one group at a time for which analysis is to be done.
groups = ["LEFT-CENTRE"] #;, RIGHT-RIGHT, "LEFT-LEFT", "CENTRE-CENTRE", "RIGHT-LEFT", "RIGHT-CENTRE", "LEFT-CENTRE"]
# This dict contains all distinct cookie ids which are discovered to be in sync via other codes leaning-wise for each OpenWPM crawl
crawl_ids = {
"crawl1_ids": {
"RIGHT-RIGHT": ['a673ad84-7edd-49ca-a2e1-03ccf00aaa96', '6808053167511644657', '329D0E19-1672-4B2D-A596-072E15FE7CF7', '7617907292734751231', '8671487845541945540', 'GyCgmtqvUAPMFuncPiOb', '8da8d2db-bd03-4fed-9ee8-04abf9d095ee', '5725302695348478130', '89A02A02-0BCF-432A-9FCE-39EB2CC3DBEF', 'd5483b60-fd4e-45a7-adc8-97fe8608b8ae', 'a558ca7c-fd49-41ad-a633-c35e116b5eeb', '1908763263083725564', 'E8363DB1-821D-4E90-A871-485CD730FD22', 'ewyAhN30HRQS', 'ZDGbZZznqG7iigyLx78R', '177c4d3e-6c85-48a6-aaa2-1bb9ab35927c', '25f1ef08-a5ff-464c-9430-2e653776c189', '97a321c9601c0774ae57bfb1', 'P3VLtGIlzyO2', 'd88HSyLGpnfhVwJYEcbI', '4676880895506688422', 'b8cc991e-05b9-44ec-ba7c-a296a6893ccf', 'vVVLqawhEpTzjpNPhx87', 'd458ec23-d516-43e1-b57a-9c88b6227653', 'IF2o14JGD7mQQPWx80JTXw', '16135553218108422011', '8cf2237c-ad48-4ca7-bd9f-83bbd4c1c558', 'e2b961c8d1b34163a0428b621cb3fa33', 'ea6f6507-4507-4a82-a410-6a74354aae93', '0b44588d-af65-4a82-8140-166e8790cb47', 'kQBeX68KLgovbyK8', '5624553461506080350', 'jjQCRWMK6U9iCV0vE3r1', 'b9df60bd-c012-4396-a86a-60f6dd3c0d5d', '4281579494177528828', 'Ztz51nNRlToJ6rpFc3Fg', 'ae481aaa-8520-46e7-887c-cff1a93a3cd0', '1Ab0595fac-ef4f-11ea-8e15-122c64aa8f2c', 'hVapGCQLQrOGPdjZ2pSE', '1772128271399740894', 'Vh0iSA4CcKeFOGqbgD-miQ'],
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"CENTRE-CENTRE": ['4b67258c-d65f-43c7-ae98-d2ee62fad705', '8888604135129816790', 'a16b7889-36c5-4ab7-a161-890e3c1831b8', '5c9625b8-a925-4802-b19a-cfa2a8a3638f', '3dc93b85-99d6-49c0-b7bd-e65340c399e3', 'F21F3F8B-E907-4941-95AE-E27DF89FBD72', '7856907158dbecb22c20c522', '1fd05e5c084ea6615ecd0e61', 'B5E104E9-7FFF-4647-9680-EEFC990B1308', 'a_9f818729-153e-468d-9588-48a6c8730711', 'e168d5e585ee44cedc063ea6', '88b2e163-727c-476c-a956-e9f74639c346', '6931244666233872498', '157cc78e-905f-4a1f-86eb-adf8d6fbcad3', 'eacf2480-354a-48e6-b1ad-0d5322853b81', '6SOve1-C_syYbQzgWiUK', 'EA74AFC5-B593-4FD1-B81D-6B9224E744C3', '32e092dd-e85c-4989-875a-439ea7b52b10', '6433449470155549948', 'mW95LkPY92ukNiMbgiJc', '9be55c08-3b45-4385-9fa7-8485ed38cd45', '94d14693-57c7-40c3-86a0-e139337853b9-5f79cf6f-494e', '1758649507604313966', 'dee6a72f-fe48-453b-b9d0-eba90b8441e8', 'CB5C4038-8B9B-41CA-AF25-1B4B18778CA9', '76488396-48f2-4666-ae73-870e317babf8', '1314F35E319B471BB3935719CDF7B66D', '8480e6d0-8817-45aa-a5b5-20bcaaf0caba', 'db0bfff9-278e-458e-b2dc-9ff9527e07ae-1sjr1', '07018270-f2cd-4571-8674-29a7ad79ab64', '679eb1a38308f7e2b4730d6a', 'VHhZoikkh0Q0xXa3kSKh', '2919896342356495572', 'E4363484D7664C92996FDAA5316F77E0', '5bY3q3dfjxyB7qmlX1nq', 'pVa2Fv5vzOWd', 'a8a15c69-11fc-4c0d-85a6-3e83f338b17a', 'F7611468-2E90-4BBF-A534-81B577E1170F', 'G-9S9_G48bnQMERKKFkB', '4342197873766201412', '40hUsv9bCSOxiMz1Ast5Xw', '1F9F45D4462F4D82AA74FE0F1A5C6320', '26bcc1cd-8eaf-4a50-9a4c-959268687604', 'u1tFzeNW1Kp3RE5', 'dcdc14bb-7867-4c2e-ace7-77e6daed344d', '1b3e7666-1e89-46d4-a09c-e7908dd645c8', '4910161351172623623', '3013320352939507100', 'K6R13bXZPenr', 'e9eb1393-0e8c-4dd4-925c-9bbf8e17e281', 'UObmjM2iB_Ww8KOjyc15Xw', '25305968802835511720384574414283577852', '6850925465893631592', '5c1d9533-d455-4fe8-8a94-4885b22c824f', 'g7GKSELpBV-BmWwUcM95Xw', '8d8a7ab3-49f5-4a95-bb87-0ac9ac2c3bf9', '9b8409db-dd42-4417-9c89-3492f299eb77', '5f243db5-c5d3-4936-8c5f-3f69d831a2fc', '3954f57587898cae3b7002670e9c251c', '7863544016552467740', '53a1378c-259e-4cc7-b7d5-06a79cc26319', 'CD009EF170804C5D85A5C7831E09254E', 'dKB3aq3KDZiAurkbutB5Xw', 'BtS6kdtCqdYr', 'a_4c75d583-4c9f-49de-ab70-cebb85cbe866', '4434361883005058481', '_9oMM-1TDsOVaKgU_dB5Xw', '201c7bdd-3259-42c0-b957-6c09f9dbd0ce', 'b31757eb-e346-45ad-96d4-4be153296489', 'fc8cd46f-719f-353d-94e2-dc12b4320fed', 'c91b06bcd46eca6e34bc4ff1e580a223', 'ecb95f39-1576-4993-a9b9-9d5462959e1c', '8425755011885875571'],
"RIGHT-LEFT": ['8480e6d0-8817-45aa-a5b5-20bcaaf0caba', 'e8d4ff9d-b871-4dad-b389-1ddcc0d85ba2', '6850925465893631592', '8425755011885875571', '3dc93b85-99d6-49c0-b7bd-e65340c399e3', '4342197873766201412', '4482717769033512994', '07018270-f2cd-4571-8674-29a7ad79ab64', '6196775144215749995', 'a_4e958946-42d6-4023-8124-e8227457485b', '8888604135129816790', '4484454457670204121', '3626929916442947799', '0ba4bb73-756c-437f-b2c7-ab63d9cf3def', '3013320352939507100', 'VHhZoikkh0Q0xXa3kSKh', '9BAC02AD095C449D8F41C79D2C5FBD41', '65B28BAC-0183-472E-99F1-518787F63E4F', 'F83F7F02-95B4-481D-91DE-4A9382C1FA5E', 'Lrm3HtLql6QtsiB1nNbU', 'ukZp7AO3J8lXv6a66K18', '3896911550656110787', '9v5WdGGj1Kp3TP5', 'an1ynVcA1Kp3XK5', 'd4d15f79-cc7b-4000-b1f8-f8f5467bb7cd', '6433449470155549948', 'TDBJJLs2_1b_0pen8_pv', '2956450342226631486', '0bbc68f2-6247-41c4-adc9-5dd26bdc88ca', 'mbkAoInq8jeR', 'l4zbqY7Dk7J0bprO', '09cd53a05def4fbebe88d7c802331882', 'a_849ce75b-f20b-436f-8361-5ef01e31ee5e', 'j3a4289857e67863d751486b', 'QJ0dN9Lpo2v6bLOv', 'fe14d726-2643-4231-8623-f8b2b0b5b80c', '96k6FedNFbsf58GpGOEM', '10527164129786049167', 'BA1DA5DE111F4CE9B135C6017CE4166E', '679eb1a38308f7e2b4730d6a', 'dbb9dd24c332480787df0c4cbf9ddd53', '8dc00b8b-54e8-3b82-bb67-0d4cdfec71e3', '2132a016-8329-403a-b37f-2a269e8d0b48', 'ru66amtV71ih', 'e35b345c-b2ea-4367-a38f-b1f9d08dae82', 'b5301221f66e4325b22b5fee66a8e986', '23e80953-c4f9-497b-886e-303a6c76616e', '36115a7c-e633-4111-be2e-b1d909777a68-1sk25', 'Bypayhl38FHW', '7818fef6-b8d6-4031-bc5e-294f1629b291'],
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"LEFT-CENTRE": ['07018270-f2cd-4571-8674-29a7ad79ab64', '88b2e163-727c-476c-a956-e9f74639c346', '6433449470155549948', '679eb1a38308f7e2b4730d6a', '0ba4bb73-756c-437f-b2c7-ab63d9cf3def', '4910161351172623623', '5c1d9533-d455-4fe8-8a94-4885b22c824f', '879334cb-e6fe-48e9-ba58-d62812624feb', '8D6981EB-D7CA-41D3-9E72-91973A8D12F8', 'j3a4289857e67863d751486b', '3626929916442947799', '9aa891a9fca10de184ae7c3b59c9fb32', '993613e8-45e2-46b5-9763-7f995800b39f', '5AA9BE6D-C1FF-46A2-9874-1D7B5E78D7FD', 'K6R13bXZPenr', '6A36A375-2D8F-47AC-9931-C44B6627C8B4', '47f0d9d7-ce15-4bfb-8f44-6431a25e7c44', '7FD561BB-EE67-4CC0-9E49-0BC3BF80577B', 'F2D083B6-6AE0-4023-97DB-C0EC525D15CA', '3013320352939507100', '8480e6d0-8817-45aa-a5b5-20bcaaf0caba', '8246774277336838138', '3896911550656110787', 'VHhZoikkh0Q0xXa3kSKh', '44BF94279FE34ED29BF10C58FCBDDEB9', '4223993276519957237', '98113cebc6903dbe1173a197', 'Lrm3HtLql6QtsiB1nNbU', 'N6eIRXmCZnu4Y6TjwCqf', '7ED28684726F49D1ACEA356C2A927314', '7b08d8a6cf88d41b079f881704d0cd06', 'ukZp7AO3J8lXv6a66K18', 'an1ynVcA1Kp3XK5', 'WqUN8a27CmqxD5BR1cx5Xw', 'd55a0a7a-b20d-4fab-b6e9-a5a6e507d9d1-1sjfw', 't93lW3e0OuH0s2F3Arsq', '3177457967996845655', '4342197873766201412', '8425755011885875571', 'F83F7F02-95B4-481D-91DE-4A9382C1FA5E', 'F1iVIpSJz8Q5oqPuNvcQ', '5945195233226464033', 'A8pdCwVwCK-b7ucnFsp5Xw', '8bee2599-873a-49a7-88d0-78da00613b67', '7368991501570415873', 'cbf82daf-d7ba-4cd4-b4b9-17be394f7bdd', 'KFV4JO0K-I-9DML', 'ethAHj8r1Kp3NQ5', '6379651239929026368', 'a_de7f15aa-4176-4cee-87fb-8ac0c06230a5', 'a6016223-1978-4779-b387-9aae34f999ec', 'bc0fb744c376429584db8e8cf56381cc', 'KsTItPt3BaeCc0kej8t5Xw', 'dae20f1c-8352-43ab-8c0c-f443b2c0dd00', '9861afb0-b73b-46c5-a3a0-69b75699894e', '1b3e7666-1e89-46d4-a09c-e7908dd645c8', 'e3f4eee8-edc2-4f1b-8c1f-df18dea7724c', 'f3cfe387-2154-4044-a769-9b7c69990497', 'BA1DA5DE111F4CE9B135C6017CE4166E', '191407f9-3ecf-49ae-828c-3688821f19ee', 'JX7axvn94w1ndyv4', 'e8d4ff9d-b871-4dad-b389-1ddcc0d85ba2', '6850925465893631592', 'be577110-077c-4065-a163-decd4d0c9e93', '85wrX5j3dUsk', '80c1f9fe-6f98-4cd9-896f-4bdbaa9f3ec8', 'c91185f3-a35d-4738-b19c-0b26b8463de2', 'f7e64f6f-b37f-4013-a0f1-f295c29b9a44', '328d54fe-eab6-31c1-8cfb-df44c0565c5a', 'd175956a-7b88-44dd-8de0-862163e7ce65-1siz8', '5eb92617-9687-4b51-9800-b04c93d7b937', 'bb731975cdde4b81ad2ac12fee43ded4']
}
}
#######################################################
# Maintains a leaning-wise mapping of FP visit_id's from OpenWPM crawl that are present in a particular crawl.
# For each visit_id, it keeps a dict containing a domain mapped to 2 keys "1" and "2".
# "1" contains the number of times this domain occurs in sync and "2": contains all the unique domains with which it has been syncing
fp_to_known_id_cnts = {
"crawl1_ids": {"RIGHT-RIGHT": {}, "LEFT-LEFT": {}, "CENTRE-CENTRE": {}, "RIGHT-LEFT": {}, "RIGHT-CENTRE": {}, "LEFT-CENTRE": {}},
"crawl2_ids": {"RIGHT-RIGHT": {}, "LEFT-LEFT": {}, "CENTRE-CENTRE": {}, "RIGHT-LEFT": {}, "RIGHT-CENTRE": {}, "LEFT-CENTRE": {}},
"crawl3_ids": {"RIGHT-RIGHT": {}, "LEFT-LEFT": {}, "CENTRE-CENTRE": {}, "RIGHT-LEFT": {}, "RIGHT-CENTRE": {}, "LEFT-CENTRE": {}},
"crawl4_ids": {"RIGHT-RIGHT": {}, "LEFT-LEFT": {}, "CENTRE-CENTRE": {}, "RIGHT-LEFT": {}, "RIGHT-CENTRE": {}, "LEFT-CENTRE": {}},
"crawl5_ids": {"RIGHT-RIGHT": {}, "LEFT-LEFT": {}, "CENTRE-CENTRE": {}, "RIGHT-LEFT": {}, "RIGHT-CENTRE": {}, "LEFT-CENTRE": {}}
}
#######################################################
# List of all unique TP and FP domains
tp_domains = ['1rx.io', '1trust.app', '2mdn.net', '33across.com', '360yield.com', '3lift.com', '4dex.io', '59.160.110.46', '5abnow.com', '91-cdn.com', 'a-mo.net', 'accesstype.com', 'accuweather.com', 'acuityplatform.com', 'ad-m.asia', 'ad-stir.com', 'ad.style', 'addthis.com', 'addthisedge.com', 'addtoany.com', 'adform.net', 'adgebra.co.in', 'adgebra.in', 'adgrx.com', 'adhigh.net', 'adingo.jp', 'adireto.com', 'adition.com', 'adjust.com', 'adkernel.com', 'adlightning.com', 'admanmedia.com', 'admatrix.jp', 'admedia.com', 'admedo.com', 'admeme.net', 'adnxs.com', 'adobedtm.com', 'adotmob.com', 'adpushup.com', 'adrecover.com', 'adroll.com', 'ads-twitter.com', 'adsafeprotected.com', 'adsnative.com', 'adsolut.in', 'adspruce.com', 'adsrvr.org', 'adsymptotic.com', 'adtelligent.com', 'advangelists.com', 'advertising.com', 'adxbid.info', 'adxpremium.services', 'affinity.com', 'agkn.com', 'akamaihd.net', 'akamaized.net', 'akstat.io', 'alexametrics.com', 'amazon-adsystem.com', 'amazonaws.com', 'amcharts.com', 'amgdgt.com', 'amplify.ai', 'ampproject.net', 'ampproject.org', 'andbeyond.media', 'aniview.com', 'app.link', 'appboy.com', 'appboycdn.com', 'appier.net', 'aso1.net', 'assamtribune.com', 'assettype.com', 'atdmt.com', 'atwola.com', 'audiencemanager.de', 'audienceplay.com', 'automatad.com', 'avct.cloud', 'avocet.io', 'ayads.co', 'azioncdn.net', 'azureedge.net', 'b2c.com', 'barcindia.in', 'bbc.co.uk', 'bbci.co.uk', 'betweendigital.com', 'bfmio.com', 'bhaskarassets.com', 'bidr.io', 'bidswitch.net', 'bidtheatre.com', 'bing.com', 'bitsngo.net', 'bkrtx.com', 'blis.com', 'blismedia.com', 'bluekai.com', 'boldsky.com', 'boltdns.net', 'bookcdn.com', 'bootstrapcdn.com', 'boxx.ai', 'branch.io', 'brand-display.com', 'brealtime.com', 'brightcove.com', 'brightcove.net', 'brut.media', 'bttrack.com', 'careerindia.com', 'careers360.mobi', 'casalemedia.com', 'catchmedia.com', 'cauly.co.kr', 'ccgateway.net', 'cedexis-radar.net', 'cedexis.com', 'chartbeat.com', 'chartbeat.net', 'cheqzone.com', 'chimpstatic.com', 'chocolateplatform.com', 'cinarra.com', 'click.in', 'clickagy.com', 'clicktripz.com', 'clmbtech.com', 'clnmde.com', 'cloudflare.com', 'cloudflareinsights.com', 'cloudfront.net', 'cmcd1.com', 'cognitivlabs.com', 'colossusssp.com', 'connexity.net', 'consensu.org', 'contextweb.com', 'cookiepro.com', 'crazyegg.com', 'createjs.com', 'creativecdn.com', 'creativecommons.org', 'criteo.com', 'criteo.net', 'crowdynews.com', 'crwdcntrl.net', 'ctnsnet.com', 'cuberoot.co', 'dailymotion.com', 'daksham.in', 'data.com', 'datadome.co', 'datawrkz.com', 'dc-1.net', 'deepintent.com', 'demand.supply', 'demdex.net', 'digitaleast.mobi', 'digitaloceanspaces.com', 'digitru.st', 'dinamani.com', 'disqus.com', 'disquscdn.com', 'districtm.io', 'dm-event.net', 'dmca.com', 'dmcdn.net', 'dmxleo.com', 'dnacdn.net', 'domdex.com', 'dotomi.com', 'doubleclick.net', 'doubleverify.com', 'drivespark.com', 'dyntrk.com', 'e-volution.ai', 'ebela.in', 'effectivemeasure.net', 'elfsight.com', 'emerse.com', 'emxdgt.com', 'entitysport.com', 'epapr.in', 'eqads.com', 'erne.co', 'etimg.com', 'everestads.net', 'everesttech.net', 'exelator.com', 'exitbee.com', 'exponential.com', 'extend.tv', 'eyeota.net', 'facebook.com', 'facebook.net', 'factchecker.in', 'fameitc.com', 'fastly.net', 'fbcdn.net', 'fbsbx.com', 'feedify.net', 'filmibeat.com', 'fireworktv.com', 'flashtalking.com', 'flickstree.com', 'flourish.studio', 'flowplayer.org', 'fontawesome.com', 'forecast7.com', 'fouanalytics.com', 'fqtag.com', 'freegeoip.app', 'fw-ad.jp', 'fwcdn1.com', 'fwmrm.net', 'fwpixel.com', 'gadgets360.com', 'gadgets360cdn.com', 'gamoshi.io', 'geistm.com', 'gemius.pl', 'genieessp.com', 'genieesspv.jp', 'geoip-db.com', 'geojs.io', 'geolocation-db.com', 'getbootstrap.com', 'ggpht.com', 'githubusercontent.com', 'gizbot.com', 'gleam.io', 'gmdelivery.com', 'go-mpulse.net', 'goodreturns.in', 'google-analytics.com', 'google.co.in', 'google.com', 'googleadservices.com', 'googleapis.com', 'googleoptimize.com', 'googlesyndication.com', 'googletagmanager.com', 'googletagservices.com', 'googleusercontent.com', 'googlevideo.com', 'gravatar.com', 'growthrx.in', 'gsspat.jp', 'gssprt.jp', 'gstatic.com', 'gumgum.com', 'gumlet.com', 'gvt1.com', 'h-cdn.com', 'hariken.co', 'healthshots.com', 'heatmap.it', 'highcharts.com', 'hindirush.com', 'hotjar.com', 'hotjar.io', 'hs-scripts.com', 'htmedia.in', 'hwcdn.net', 'iamgujarat.com', 'iasds01.com', 'ibeat-analytics.com', 'icubesapps.in', 'id5-sync.com', 'idealmedia.io', 'iimg.in', 'im-apps.net', 'imonomy.com', 'impact-ad.jp', 'impdesk.com', 'imrworldwide.com', 'in.com', 'includemodal.com', 'indexww.com', 'innovid.com', 'insightexpressai.com', 'instagram.com', 'ip-api.com', 'ipapi.co', 'ipdata.co', 'ipify.org', 'ipredictive.com', 'itstrendingnow.com', 'izooto.com', 'jagranimages.com', 'jio.com', 'jiosaavn.com', 'jquery.com', 'jsdelivr.net', 'jwpcdn.com', 'jwplayer.com', 'kargo.com', 'kesari.tv', 'kostprice.com', 'krxd.net', 'ladsp.com', 'ladsp.jp', 'langimg.com', 'leagueofindia.com', 'lemmamedia.com', 'lemmatechnologies.com', 'lentainform.com', 'liadm.com', 'licdn.com', 'licensebuttons.net', 'lijit.com', 'linkedin.com', 'lkqd.net', 'loopme.me', 'm2.ai', 'maharashtratimes.com', 'mailchimp.com', 'manychat.com', 'marphezis.com', 'mathtag.com', 'mccdn.me', 'media-amazon.com', 'media.net', 'metype.com', 'mfadsrvr.com', 'mgid.com', 'microad.jp', 'microsoft.com', 'minute.ly', 'ml314.com', 'mmonline.io', 'moatads.com', 'mobileadtrading.com', 'moengage.com', 'mookie1.com', 'motionspots.com', 'mouseflow.com', 'mrpdata.net', 'mts.ru', 'mxptint.net', 'mykhel.com', 'myvisualiq.net', 'nativeplanet.com', 'ndtv1.com', 'ndtvimg.com', 'netacuity.com', 'netcoresmartech.com', 'netmng.com', 'newrelic.com', 'news4masses.com', 'newstracklive.com', 'nex8.net', 'nr-data.net', 'nrich.ai', 'nwtrk.in', 'oath.com', 'omnithrottle.com', 'omtrdc.net', 'onaudience.com', 'onesignal.com', 'onetag-sys.com', 'onthe.io', 'openweathermap.org', 'openx.net', 'optmd.com', 'oswaldlabs.com', 'outbrain.com', 'outbrainimg.com', 'owneriq.net', 'perfectmarket.com', 'pinkvilla.com', 'pippio.com', 'playground.xyz', 'playstream.media', 'plyr.io', 'polldaddy.com', 'polyfill.io', 'popper.ai', 'powerad.ai', 'powerlinks.com', 'prabhatkhabar.com', 'pricee.com', 'pro-market.net', 'pubmatic.com', 'pushengage.com', 'qlitics.com', 'quantcount.com', 'quantserve.com', 'quintype.io', 'quora.com', 'r-ad.ne.jp', 'razorpay.com', 'readwhere.com', 'reemo-ad.jp', 'resetdigital.co', 'responsibletourismindia.com', 'responsivevoice.org', 'rfihub.com', 'rlcdn.com', 'rtbdemand.com', 'rtk.io', 'rubiconproject.com', 'rundsp.com', 'rutarget.ru', 'rvcj.com', 'rwadx.com', 's3xified.com', 'saavn.com', 'saavncdn.com', 'samakalikamalayalam.com', 'scorecardresearch.com', 'sekindo.com', 'sentinelassam.com', 'servenobid.com', 'serverbid.com', 'serving-sys.com', 'sharedid.org', 'sharethis.com', 'sharethrough.com', 'shopify.com', 'simpli.fi', 'sinceindependence.com', 'sitescout.com', 'sixlogics.com', 'skimresources.com', 'smaato.net', 'smadex.com', 'smartadserver.com', 'smrtb.com', 'snack-media.com', 'snack-projects.co.uk', 'snackly.co', 'sniperlog.ru', 'socdm.com', 'socialketchup.in', 'socialsamosa.com', 'sonobi.com', 'sphereup.com', 'sportradarserving.com', 'spotx.tv', 'spotxcdn.com', 'spotxchange.com', 'springserve.com', 'stackadapt.com', 'statcounter.com', 'statetimes.in', 'stickyadstv.com', 'storygize.net', 'survicate.com', 't.co', 'taboola.com', 'tapad.com', 'teads.tv', 'technoratimedia.com', 'telanganatoday.com', 'theabcdn.com', 'thebetterindia.com', 'thelogicalindian.com', 'thesangaiexpress.com', 'thgim.com', 'thrtle.com', 'tidaltv.com', 'timespoints.com', 'toiimg.com', 'topyaps.com', 'tosshub.com', 'traq.li', 'tremorhub.com', 'tribalfusion.com', 'truepush.com', 'turn.com', 'tvid.in', 'twimg.com', 'twitter.com', 'tynt.com', 'typekit.net', 'ubembed.com', 'uncn.jp', 'unpkg.com', 'urbanairship.com', 'uri.sh', 'userreport.com', 'vdo.ai', 'vidazoo.com', 'videogram.com', 'vidgyor.com', 'vidible.tv', 'vijaykarnataka.com', 'visualwebsiteoptimizer.com', 'volvelle.tech', 'vrtzads.com', 'vuukle.com', 'w55c.net', 'walmart.com', 'warw.in', 'wbtrk.net', 'weatherwidget.io', 'webcontentassessor.com', 'webengage.co', 'webengage.com', 'whizzbi.com', 'windows.net', 'wisden.com', 'wp.com', 'wss.com', 'wzrkt.com', 'xspadvertising.com', 'yahoo.com', 'yahooapis.com', 'yahoosandbox.com', 'yieldmo.com', 'yimg.com', 'youtube.com', 'ytimg.com', 'zedo.com', 'zemanta.com', 'zencdn.net', 'zeotap.com', 'zimbea.com', 'zprk.io', 'zqtk.net']
fp_domains = ['dailyo.in', 'india.com', 'news18.com', 'ptinews.com', 'thestatesman.com', 'kashmirlife.net', 'timesnownews.com', 'intoday.in', 'cnbctv18.com', 'patrika.com', 'dainikbhaskar.com', 'dinamalar.com', 'dailythanthi.com', 'deshabhimani.com', 'zeenews.com', 'sandesh.com', 'outlookhindi.com', 'newslivetv.com', 'newsonair.gov.in', 'businesstoday.in', 'timesheadline.com', 'ndtv.com', 'mathrubhumi.com', 'outlookindia.com', 'newdelhitimes.com', 'oneindia.com', 'newsnationtv.com', 'siasat.com', 'huffingtonpost.in', 'moneycontrol.com', 'businessinsider.in', 'indianexpress.com', 'republicworld.com', 'newindianexpress.com', 'eenadu.net', 'lokmat.com', 'thehindu.com', 'theprint.in', 'telegraphindia.com', 'business-standard.com', 'asianage.com', 'scroll.in', 'punjabkesari.in', 'deccanchronicle.com', 'wionews.com', 'nagpurtoday.in', 'abplive.com', 'indiatimes.in', 'gujaratsamachar.com', 'jagran.com', 'deccanherald.com', 'newsonair.com', 'nic.in', 'thewire.in', 'milligazette.com', 'bhaskar.com', 'thequint.com', 'swarajyamag.com', 'amarujala.com', 'bbc.com', 'countercurrents.org', 'dailyexcelsior.com', 'opindia.com', 'huffpost.com', 'aajtak.in', 'anandabazar.com', 'livehindustan.com', 'huffingtonpost.com', 'andhrajyothy.com', 'moneycontrol.co.in', 'indiatimes.com', 'starofmysore.com', 'greatandhra.com', 'fakingnews.com', 'financialexpress.com', 'thehindubusinessline.com', 'scoopwhoop.com', 'dailypioneer.com', 'mid-day.com', 'tribuneindia.com', 'manoramaonline.com', 'freepressjournal.in', 'indiatoday.in', 'dnaindia.com', 'webdunia.com', 'greaterkashmir.com', 'altnews.in', 'youthkiawaaz.com', 'indiatvnews.com', 'newslaundry.com', 'dailyhunt.in', 'firstpost.com', 'livemint.com', 'hindustantimes.com', 'headlinesoftoday.com', 'catchnews.com', 'forbesindia.com', 'kashmirreader.com', 'ians.in', 'risingkashmir.com', 'aninews.in', 'jansatta.com', 'news24online.com', 'thenewsminute.com']
# Output data frame columns
final_data = pd.DataFrame(columns=['Crawl ID', 'Leaning Group', 'Category', 'Unique ID Synced', 'Unique TP-TP Synced', 'Unique TP-FP Synced'])
# Output data at website-pair level
row_cnt = 0
website_data = pd.DataFrame(columns=['Crawl ID', 'Leaning Group', 'Total Website Pairs', 'Visit ID1', 'Visit ID2', 'Unique IDs in Sync',
'Total IDs in Sync', 'Unique TP-TP Syncs', 'Total TP-TP Syncs', 'Unique TP-FP Syncs', 'Total TP-FP Syncs'])
total_row_cnt = 0
visit_id_to_leaning = {}
for leaning_gp in groups:
for crawl_id in range(1, 6):
# Enter path to the crawled sqlite file
Stateful_Crawl = os.path.join(DATA_DIR, 'crawl-data_stateful_homepage' + str(crawl_id) + '.sqlite')
conn = lite.connect(Stateful_Crawl)
cur = conn.cursor()
curtmp = conn.cursor()
# u stands for unique
u_id_synced = []
u_tp_tp_synced = []
u_tp_fp_synced = []
crawl_str = "crawl" + str(crawl_id) + "_ids"
id_list = list(crawl_ids[crawl_str][leaning_gp])
# '''
print(crawl_str)
# Computing leaning of different fp domains
for visit_id, url, referrer in cur.execute('SELECT visit_id, url, referrer FROM http_requests'):
if visit_id not in visit_id_to_leaning.keys():
for res in curtmp.execute('SELECT arguments FROM crawl_history' + ' WHERE visit_id = ' + str(visit_id)):
site_url = str(res[0]).split(',')[0][9:-1]
site_leaning = find_site_leaning.get_leaning(site_url)
break
visit_id_to_leaning[visit_id] = site_leaning
if site_leaning not in list(leaning_gp.split("-")):
continue
z = 0
for k in id_list:
cat1 = cat2 = ""
cat1cat2 = "NOSYNC"
flag = 0
temp = []
if k in url or k in referrer:
if visit_id not in fp_to_known_id_cnts[crawl_str][leaning_gp].keys():
fp_to_known_id_cnts[crawl_str][leaning_gp][visit_id] = {}
if k not in fp_to_known_id_cnts[crawl_str][leaning_gp][visit_id].keys():
fp_to_known_id_cnts[crawl_str][leaning_gp][visit_id][k] = {"1": 0, "2": []}
fp_to_known_id_cnts[crawl_str][leaning_gp][visit_id][k]["1"] += 1
cat1cat2, flag, u_id_synced, u_tp_tp_synced, u_tp_fp_synced, dom1, dom2 = get_sync_cat(tp_domains, fp_domains, url, referrer, cat1, cat2,
cat1cat2, flag, u_id_synced, u_tp_tp_synced,
u_tp_fp_synced)
if flag == 1:
if dom1 != "" and dom2 != "":
fp_to_known_id_cnts[crawl_str][leaning_gp][visit_id][k]["2"].append(dom1)
fp_to_known_id_cnts[crawl_str][leaning_gp][visit_id][k]["2"].append(dom2)
final_data.loc[total_row_cnt] = [crawl_id, leaning_gp, cat1cat2, len(u_id_synced), len(u_tp_tp_synced), len(u_tp_fp_synced)]
total_row_cnt += 1
z = 1
break
else:
continue
# **********************
# cnt_t represent count of total
cnt_t_id_sync = cnt_t_tp_tp_sync = cnt_t_tp_fp_sync = 0
for row in range(len(final_data)):
cid = int(final_data.iloc[row]["Crawl ID"])
lgp = str(final_data.iloc[row]["Leaning Group"])
categ = str(final_data.iloc[row]["Category"])
if cid == crawl_id and leaning_gp == lgp:
if categ == "TP-TP":
cnt_t_tp_tp_sync += 1
elif categ == "TP-FP":
cnt_t_tp_fp_sync += 1
cnt_t_id_sync = cnt_t_tp_fp_sync + cnt_t_tp_tp_sync
print("Crawl", ",", crawl_id)
print("Leaning Group", ",", leaning_gp)
print("Distinct ID Syncs | Total ID Syncs", ",", len(u_id_synced), "|", cnt_t_id_sync)
print("Distinct TP-TP Syncs | Total TP-TP Syncs", ",", len(u_tp_tp_synced), "|", cnt_t_tp_tp_sync)
print("Distinct TP-FP Syncs | Total TP-FP Syncs", ",", len(u_tp_fp_synced), "|", cnt_t_tp_fp_sync)
# **********************
fp_ids = fp_to_known_id_cnts["crawl" + str(crawl_id) + "_ids"][leaning_gp]
# for a given leaning and crawl, fpi represents an FP and fpj represents another FP.
# Following code finds whether 2 different FPs have any TP in common.
# If yes, counts the total and unique user ids exchanged between TP-TP and TP-FP pairs
pair_cnt = 0
for fpi in fp_ids.keys():
for fpj in fp_ids.keys():
if fpi != fpj:
pair_cnt += 1
total_ids_sync = sum([fp_ids[fpi][idi]['1'] for idi in fp_ids[fpi].keys()]) + sum([fp_ids[fpj][idj]['1'] for idj in fp_ids[fpj].keys()])
unique_ids_sync = len(list(set(fp_ids[fpi].keys()).union(set(fp_ids[fpj].keys()))))
u_tptp = []
u_tpfp = []
t_tptp_cnt = 0
t_tpfp_cnt = 0
for id1 in fp_ids[fpi].keys():
for domain1 in list(set(fp_ids[fpi][id1]["2"])):
for domain2 in list(set(fp_ids[fpi][id1]["2"])):
if domain1 != domain2:
l1 = "TP" if (domain1 in tp_domains) else "FP"
l2 = "TP" if (domain2 in tp_domains) else "FP"
if str(l1) + str(l2) == "TPTP":
t_tptp_cnt += 1
if (domain1, domain2) not in u_tptp and (domain2, domain1) not in u_tptp:
u_tptp.append((domain1, domain2))
elif str(l1) + str(l2) == "TPFP" or str(l1) + str(l2) == "FPTP":
t_tpfp_cnt += 1
if (domain1, domain2) not in u_tpfp and (domain2, domain1) not in u_tpfp:
u_tpfp.append((domain1, domain2))
for id2 in fp_ids[fpj].keys():
for domain1 in list(set(fp_ids[fpj][id2]["2"])):
for domain2 in list(set(fp_ids[fpj][id2]["2"])):
if domain1 != domain2:
l1 = "TP" if (domain1 in tp_domains) else "FP"
l2 = "TP" if (domain2 in tp_domains) else "FP"
if str(l1) + str(l2) == "TPTP":
t_tptp_cnt += 1
if (domain1, domain2) not in u_tptp and (domain2, domain1) not in u_tptp:
u_tptp.append((domain1, domain2))
elif str(l1) + str(l2) == "TPFP" or str(l1) + str(l2) == "FPTP":
t_tpfp_cnt += 1
if (domain1, domain2) not in u_tpfp and (domain2, domain1) not in u_tpfp:
u_tpfp.append((domain1, domain2))
for id1 in fp_ids[fpi].keys():
for id2 in fp_ids[fpj].keys():
if id1 == id2:
for domain1 in fp_ids[fpi][id1]["2"]:
for domain2 in fp_ids[fpj][id2]["2"]:
if domain1 != domain2:
l1 = "TP" if (domain1 in tp_domains) else "FP"
l2 = "TP" if (domain2 in tp_domains) else "FP"
if str(l1) + str(l2) == "TPTP":
t_tptp_cnt += 1
if (domain1, domain2) not in u_tptp and (
domain2, domain1) not in u_tptp:
u_tptp.append((domain1, domain2))
elif str(l1) + str(l2) == "TPFP" or str(l1) + str(l2) == "FPTP":
t_tpfp_cnt += 1
if (domain1, domain2) not in u_tpfp and (
domain2, domain1) not in u_tpfp:
u_tpfp.append((domain1, domain2))
website_data.loc[row_cnt] = [crawl_id, leaning_gp, pair_cnt, fpi, fpj, unique_ids_sync, total_ids_sync, str(len(u_tptp)),
str(t_tptp_cnt), str(len(u_tpfp)), str(t_tpfp_cnt)]
row_cnt += 1
cur.close()
# Writing the website-pair level analysis of TP-TP and TP-FP syncs to a file
website_data.to_csv(os.path.join(DATA_DIR, crawl_str + " " + leaning_gp + '.csv'), index='False')
# **************************************************************************
| 266.060703 | 8,519 | 0.735377 | 8,266 | 83,277 | 7.350472 | 0.398742 | 0.001646 | 0.001679 | 0.001991 | 0.521108 | 0.425451 | 0.372406 | 0.328824 | 0.299709 | 0.295857 | 0 | 0.39438 | 0.105131 | 83,277 | 312 | 8,520 | 266.913462 | 0.420936 | 0.020054 | 0 | 0.185022 | 0 | 0 | 0.733252 | 0.465693 | 0 | 0 | 0 | 0 | 0 | 1 | 0.004405 | false | 0 | 0.048458 | 0 | 0.061674 | 0.030837 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
be876ad2ccf9925b7b68e46510e4ea8c28439e11 | 64 | py | Python | src/erpbrasil/febraban/api/__init__.py | erpbrasil/erpbrasil.febraban | a4f6b254d41e18c8883be6243dd27c143ea4e74d | [
"BSD-3-Clause"
] | 1 | 2020-08-27T18:43:01.000Z | 2020-08-27T18:43:01.000Z | src/erpbrasil/febraban/api/__init__.py | erpbrasil/erpbrasil.febraban | a4f6b254d41e18c8883be6243dd27c143ea4e74d | [
"BSD-3-Clause"
] | 1 | 2020-01-13T22:41:53.000Z | 2020-01-13T22:41:53.000Z | src/erpbrasil/febraban/api/__init__.py | erpbrasil/erpbrasil.febraban | a4f6b254d41e18c8883be6243dd27c143ea4e74d | [
"BSD-3-Clause"
] | 4 | 2019-09-06T12:25:25.000Z | 2021-05-17T11:41:45.000Z | # -*- coding: utf-8 -*-
from . import itau
from . import inter
| 12.8 | 23 | 0.609375 | 9 | 64 | 4.333333 | 0.777778 | 0.512821 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.02 | 0.21875 | 64 | 4 | 24 | 16 | 0.76 | 0.328125 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
be88ba1564ee5df9356eff6fd48ca5684a53b994 | 25 | py | Python | trainable/tests/session.py | hiltonjp/trainable | 3b1432c9c816285680f14e292eaef26cdbe213cf | [
"MIT"
] | 1 | 2018-12-17T19:38:00.000Z | 2018-12-17T19:38:00.000Z | trainable/tests/session.py | hiltonjp/trainable | 3b1432c9c816285680f14e292eaef26cdbe213cf | [
"MIT"
] | null | null | null | trainable/tests/session.py | hiltonjp/trainable | 3b1432c9c816285680f14e292eaef26cdbe213cf | [
"MIT"
] | null | null | null | # TODO make session tests | 25 | 25 | 0.8 | 4 | 25 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.16 | 25 | 1 | 25 | 25 | 0.952381 | 0.92 | 0 | null | 0 | null | 0 | 0 | null | 0 | 0 | 1 | null | 1 | null | true | 0 | 0 | null | null | null | 1 | 1 | 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 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
beac188ef0e79ca19485dd7cb30e1eb8c3e524f0 | 7,289 | py | Python | test/test_losses.py | dav009/PyTorch-BigGraph | e933ac681470c18f05541877084fdbf5b41bfcde | [
"BSD-3-Clause"
] | null | null | null | test/test_losses.py | dav009/PyTorch-BigGraph | e933ac681470c18f05541877084fdbf5b41bfcde | [
"BSD-3-Clause"
] | null | null | null | test/test_losses.py | dav009/PyTorch-BigGraph | e933ac681470c18f05541877084fdbf5b41bfcde | [
"BSD-3-Clause"
] | null | null | null | #!/usr/bin/env python3
# Copyright (c) Facebook, Inc. and its affiliates.
# All rights reserved.
#
# This source code is licensed under the BSD-style license found in the
# LICENSE.txt file in the root directory of this source tree.
# In order to keep values visually aligned in matrix form we use double spaces
# and exceed line length. Tell flake8 to tolerate that. Ideally we'd want to
# disable only those two checks but there doesn't seem to be a way to do so.
# flake8: noqa
from unittest import TestCase, main
import torch
from torchbiggraph.losses import (
LogisticLossFunction,
RankingLossFunction,
SoftmaxLossFunction,
)
class TensorTestCase(TestCase):
def assertTensorEqual(self, actual, expected):
if not isinstance(actual, (torch.FloatTensor, torch.cuda.FloatTensor)):
self.fail("Expected FloatTensor, got %s" % type(actual))
if actual.size() != expected.size():
self.fail(
"Expected tensor of size %s, got %s" % (expected.size(), actual.size())
)
if not torch.allclose(
actual, expected, rtol=0.00005, atol=0.00005, equal_nan=True
):
self.fail("Expected\n%r\ngot\n%r" % (expected, actual))
class TestLogisticLossFunction(TensorTestCase):
def test_forward(self):
pos_scores = torch.tensor([0.8181, 0.5700, 0.3506], requires_grad=True)
neg_scores = torch.tensor(
[
[0.4437, 0.6573, 0.9986, 0.2548, 0.0998],
[0.6175, 0.4061, 0.4582, 0.5382, 0.3126],
[0.9869, 0.2028, 0.1667, 0.0044, 0.9934],
],
requires_grad=True,
)
loss_fn = LogisticLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(4.2589))
loss.backward()
self.assertTrue((pos_scores.grad != 0).any())
self.assertTrue((neg_scores.grad != 0).any())
def test_forward_good(self):
pos_scores = torch.full((3,), +1e9, requires_grad=True)
neg_scores = torch.full((3, 5), -1e9, requires_grad=True)
loss_fn = LogisticLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
def test_forward_bad(self):
pos_scores = torch.full((3,), -1e9, requires_grad=True)
neg_scores = torch.full((3, 5), +1e9, requires_grad=True)
loss_fn = LogisticLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(6e9))
loss.backward()
def test_no_neg(self):
pos_scores = torch.zeros((3,), requires_grad=True)
neg_scores = torch.empty((3, 0), requires_grad=True)
loss_fn = LogisticLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(2.0794))
loss.backward()
def test_no_pos(self):
pos_scores = torch.empty((0,), requires_grad=True)
neg_scores = torch.empty((0, 0), requires_grad=True)
loss_fn = LogisticLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
class TestRankingLossFunction(TensorTestCase):
def test_forward(self):
pos_scores = torch.tensor([0.8181, 0.5700, 0.3506], requires_grad=True)
neg_scores = torch.tensor(
[
[0.4437, 0.6573, 0.9986, 0.2548, 0.0998],
[0.6175, 0.4061, 0.4582, 0.5382, 0.3126],
[0.9869, 0.2028, 0.1667, 0.0044, 0.9934],
],
requires_grad=True,
)
loss_fn = RankingLossFunction(1.0)
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(13.4475))
loss.backward()
self.assertTrue((pos_scores.grad != 0).any())
self.assertTrue((neg_scores.grad != 0).any())
def test_forward_good(self):
pos_scores = torch.full((3,), 2, requires_grad=True)
neg_scores = torch.full((3, 5), 1, requires_grad=True)
loss_fn = RankingLossFunction(1.0)
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
def test_forward_bad(self):
pos_scores = torch.full((3,), -1, requires_grad=True)
neg_scores = torch.zeros((3, 5), requires_grad=True)
loss_fn = RankingLossFunction(1.0)
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(30.0))
loss.backward()
def test_no_neg(self):
pos_scores = torch.zeros((3,), requires_grad=True)
neg_scores = torch.empty((3, 0), requires_grad=True)
loss_fn = RankingLossFunction(1.0)
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
def test_no_pos(self):
pos_scores = torch.empty((0,), requires_grad=True)
neg_scores = torch.empty((0, 3), requires_grad=True)
loss_fn = RankingLossFunction(1.0)
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
class TestSoftmaxLossFunction(TensorTestCase):
def test_forward(self):
pos_scores = torch.tensor([0.8181, 0.5700, 0.3506], requires_grad=True)
neg_scores = torch.tensor(
[
[0.4437, 0.6573, 0.9986, 0.2548, 0.0998],
[0.6175, 0.4061, 0.4582, 0.5382, 0.3126],
[0.9869, 0.2028, 0.1667, 0.0044, 0.9934],
],
requires_grad=True,
)
loss_fn = SoftmaxLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(5.2513))
loss.backward()
self.assertTrue((pos_scores.grad != 0).any())
self.assertTrue((neg_scores.grad != 0).any())
def test_forward_good(self):
pos_scores = torch.full((3,), +1e9, requires_grad=True)
neg_scores = torch.full((3, 5), -1e9, requires_grad=True)
loss_fn = SoftmaxLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
def test_forward_bad(self):
pos_scores = torch.full((3,), -1e9, requires_grad=True)
neg_scores = torch.full((3, 5), +1e9, requires_grad=True)
loss_fn = SoftmaxLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.tensor(6e9))
loss.backward()
def test_no_neg(self):
pos_scores = torch.zeros((3,), requires_grad=True)
neg_scores = torch.empty((3, 0), requires_grad=True)
loss_fn = SoftmaxLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
def test_no_pos(self):
pos_scores = torch.empty((0,), requires_grad=True)
neg_scores = torch.empty((0, 3), requires_grad=True)
loss_fn = SoftmaxLossFunction()
loss = loss_fn(pos_scores, neg_scores)
self.assertTensorEqual(loss, torch.zeros(()))
loss.backward()
if __name__ == "__main__":
main()
| 37.766839 | 87 | 0.622033 | 936 | 7,289 | 4.67094 | 0.174145 | 0.067932 | 0.10979 | 0.061757 | 0.78065 | 0.78065 | 0.773788 | 0.773788 | 0.773788 | 0.765554 | 0 | 0.070201 | 0.249554 | 7,289 | 192 | 88 | 37.963542 | 0.729068 | 0.063246 | 0 | 0.74359 | 0 | 0 | 0.013347 | 0.00308 | 0 | 0 | 0 | 0 | 0.141026 | 1 | 0.102564 | false | 0 | 0.019231 | 0 | 0.147436 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
fe34e50aea093d8529e4a5ab5d67f06e5d70a403 | 35 | py | Python | src/Exif/__init__.py | aji-ptn/MoilApp | 9742a28074add23fda1afa534f25a1b8bea68c93 | [
"MIT"
] | null | null | null | src/Exif/__init__.py | aji-ptn/MoilApp | 9742a28074add23fda1afa534f25a1b8bea68c93 | [
"MIT"
] | null | null | null | src/Exif/__init__.py | aji-ptn/MoilApp | 9742a28074add23fda1afa534f25a1b8bea68c93 | [
"MIT"
] | null | null | null | from Exif.exif_lib import MetaImage | 35 | 35 | 0.885714 | 6 | 35 | 5 | 0.833333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.085714 | 35 | 1 | 35 | 35 | 0.9375 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
fe7d9341adc25f7f3cd16612287ec8c6ce2ada38 | 50 | py | Python | app/events/__init__.py | iMokhles/Blog-by-Masonite- | b981c1aa46513bb76d7422e9be9ec95918a8bc42 | [
"MIT"
] | 1 | 2021-03-26T19:47:52.000Z | 2021-03-26T19:47:52.000Z | app/events/__init__.py | iMokhles/Blog-by-Masonite- | b981c1aa46513bb76d7422e9be9ec95918a8bc42 | [
"MIT"
] | null | null | null | app/events/__init__.py | iMokhles/Blog-by-Masonite- | b981c1aa46513bb76d7422e9be9ec95918a8bc42 | [
"MIT"
] | null | null | null | from .SetIsAdminForUsers import SetIsAdminForUsers | 50 | 50 | 0.92 | 4 | 50 | 11.5 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.06 | 50 | 1 | 50 | 50 | 0.978723 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 0 | 6 |
fe983c93c7979bce422cc6056b0a02dedc918f01 | 5,659 | py | Python | calculator.py | atultyagi612/Simple-Calculator-Gui | 6c40f45bff6d8bfdf6e57921493f02a0ddd22dce | [
"Unlicense"
] | 1 | 2021-01-09T05:05:41.000Z | 2021-01-09T05:05:41.000Z | calculator.py | atultyagi612/Simple-Calculator-Gui | 6c40f45bff6d8bfdf6e57921493f02a0ddd22dce | [
"Unlicense"
] | null | null | null | calculator.py | atultyagi612/Simple-Calculator-Gui | 6c40f45bff6d8bfdf6e57921493f02a0ddd22dce | [
"Unlicense"
] | null | null | null | from tkinter import *
def addition():
a=atul.get()
atul.set(a+"+")
def equal():
atul.set("equal")
def change():
try:
sum=eval(atul.get())
atul.set(sum)
except Exception as e:
atul.set("ERROR")
def number():
print("hlo")
frame1= Tk()
frame1.geometry("900x600")
atul=StringVar()
frame2=Frame(frame1)
frame2.pack(side=TOP,fill=X)
label1=Entry(frame2,textvariable=atul,font=("arial",40,"bold")).pack()
atul.set("")
frame3=Frame(frame1, borderwidth=8, relief=SUNKEN,pady=10)
frame3.pack(fill=X,pady=40)
button1=Button(frame3,text="addittion",borderwidth=3,relief=SUNKEN,padx=10,pady=5,command=lambda : atul.set(atul.get()+"+")).pack(side=LEFT,padx=10)
button2=Button(frame3,text="Subtraction",borderwidth=3,padx=5,pady=5,relief=SUNKEN,command=lambda : atul.set(atul.get()+"-")).pack(padx=20,side=LEFT)
button3=Button(frame3,text="Multiplication",borderwidth=3,padx=5,pady=5,relief=SUNKEN,command=lambda : atul.set(atul.get()+"*")).pack(padx=20,side=LEFT)
button4=Button(frame3,text="division",borderwidth=3,padx=5,pady=5,relief=SUNKEN,command=lambda : atul.set(atul.get()+"/")).pack(padx=20,side=LEFT)
button5=Button(frame3,text="Answer",borderwidth=3,padx=5,pady=5,relief=SUNKEN,command=change).pack(padx=20,side=BOTTOM)
frame3=Frame(frame1)
frame3.pack(fill=X,pady=4)
butt1=Button(frame3,text="7",borderwidth=1,relief=SUNKEN,padx=10,pady=5,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"7"))
butt1.pack(side=LEFT,padx=10)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="8",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"8"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="9",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"9"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
#********************************************* second
frame3=Frame(frame1)
frame3.pack(fill=X,pady=4)
butt1=Button(frame3,text="4",borderwidth=1,relief=SUNKEN,padx=10,pady=5,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"4"))
butt1.pack(side=LEFT,padx=10)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="5",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"5"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="6",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"6"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
#*************************************** third
frame3=Frame(frame1)
frame3.pack(fill=X,pady=4)
butt1=Button(frame3,text="1",borderwidth=1,relief=SUNKEN,padx=10,pady=5,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"1"))
butt1.pack(side=LEFT,padx=10)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="2",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"2"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="3",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"3"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
#***************************************** fourth
frame3=Frame(frame1)
frame3.pack(fill=X,pady=4)
butt1=Button(frame3,text=".",borderwidth=1,relief=SUNKEN,padx=10,pady=5,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"."))
butt1.pack(side=LEFT,padx=10)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="0",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(atul.get()+"0"))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
butt1=Button(frame3,text="C",borderwidth=1,padx=15,pady=5,relief=SUNKEN,font=("arial",25,"bold"),
command=lambda : atul.set(""))
butt1.pack(padx=20,side=LEFT)
butt1.bind("<Enter>", lambda event, h=butt1: h.configure(bg="red"))
butt1.bind("<Leave>", lambda event, h=butt1: h.configure(bg="white"))
frame1.mainloop()
| 41.007246 | 153 | 0.649408 | 856 | 5,659 | 4.293224 | 0.107477 | 0.058776 | 0.078367 | 0.11102 | 0.839728 | 0.830748 | 0.82449 | 0.816054 | 0.816054 | 0.804898 | 0 | 0.054871 | 0.11115 | 5,659 | 137 | 154 | 41.306569 | 0.675746 | 0.026683 | 0 | 0.453608 | 0 | 0 | 0.08891 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.041237 | false | 0 | 0.010309 | 0 | 0.051546 | 0.010309 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
fea4da1bd72e82e3a5f67a7525aefde293fa8ec0 | 72 | py | Python | layers/__init__.py | ml9951/ssd.pytorch | 5f40c26500a5fad683868b7fc3d38b5e2b5a0f02 | [
"MIT"
] | null | null | null | layers/__init__.py | ml9951/ssd.pytorch | 5f40c26500a5fad683868b7fc3d38b5e2b5a0f02 | [
"MIT"
] | null | null | null | layers/__init__.py | ml9951/ssd.pytorch | 5f40c26500a5fad683868b7fc3d38b5e2b5a0f02 | [
"MIT"
] | null | null | null | from .functions import *
from .modules import *
from .box_utils import * | 24 | 24 | 0.763889 | 10 | 72 | 5.4 | 0.6 | 0.37037 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.152778 | 72 | 3 | 25 | 24 | 0.885246 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
22a09f699e2432ae8a42090cfbdd660e8ce92a39 | 47 | py | Python | src/strategies/__init__.py | MohammedAljahdali/shrinkbench | f08a0e27d7e1118a46605e5ec9026ecaa931365e | [
"MIT"
] | 345 | 2020-02-29T11:49:23.000Z | 2022-03-31T09:03:33.000Z | src/strategies/__init__.py | MohammedAljahdali/shrinkbench | f08a0e27d7e1118a46605e5ec9026ecaa931365e | [
"MIT"
] | 24 | 2020-03-13T16:54:13.000Z | 2021-12-14T15:35:08.000Z | src/strategies/__init__.py | MohammedAljahdali/shrinkbench | f08a0e27d7e1118a46605e5ec9026ecaa931365e | [
"MIT"
] | 60 | 2020-03-02T20:54:42.000Z | 2022-03-26T11:38:13.000Z | from .magnitude import *
from .random import *
| 15.666667 | 24 | 0.744681 | 6 | 47 | 5.833333 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.170213 | 47 | 2 | 25 | 23.5 | 0.897436 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
22e5abaa33696d295073c062162bb233994ab2c5 | 610 | py | Python | Day 26/solution.py | EufranioDiogo/30-of-code | 4d0cadbf1e89c2792394f0b2aeadc95545d75e23 | [
"Apache-2.0"
] | 2 | 2020-10-09T21:13:59.000Z | 2020-11-14T23:04:15.000Z | Day 26/solution.py | EufranioDiogo/30-Dias-de-Code | 4d0cadbf1e89c2792394f0b2aeadc95545d75e23 | [
"Apache-2.0"
] | null | null | null | Day 26/solution.py | EufranioDiogo/30-Dias-de-Code | 4d0cadbf1e89c2792394f0b2aeadc95545d75e23 | [
"Apache-2.0"
] | null | null | null | return_date = list(map(int, input().split()))
expected_date = list(map(int, input().split()))
if expected_date[2] > return_date[2]:
print('0')
elif return_date[0] <= expected_date[0] and return_date[1] <= expected_date[1] and return_date[2] == expected_date[2]:
print('0')
elif return_date[0] > expected_date[0] and return_date[1] == expected_date[1] and return_date[2] == expected_date[2]:
print(15 * (return_date[0] - expected_date[0]))
elif return_date[1] > expected_date[1] and return_date[2] == expected_date[2]:
print(500 * (return_date[1] - expected_date[1]))
else:
print('10000')
| 40.666667 | 118 | 0.688525 | 100 | 610 | 3.96 | 0.19 | 0.30303 | 0.164141 | 0.191919 | 0.853535 | 0.853535 | 0.611111 | 0.611111 | 0.611111 | 0.611111 | 0 | 0.064151 | 0.131148 | 610 | 14 | 119 | 43.571429 | 0.683019 | 0 | 0 | 0.166667 | 0 | 0 | 0.011475 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0 | 0 | 0 | 0.416667 | 0 | 0 | 0 | null | 1 | 0 | 1 | 1 | 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 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
fe13787374699c0bd290c3d89961fd6584aeb4c0 | 11,817 | py | Python | test/test_nn_emd.py | eggry/nn-emd | 5488e3b0de904415e27c9e9e9af3e1e3c8923025 | [
"MIT"
] | null | null | null | test/test_nn_emd.py | eggry/nn-emd | 5488e3b0de904415e27c9e9e9af3e1e3c8923025 | [
"MIT"
] | null | null | null | test/test_nn_emd.py | eggry/nn-emd | 5488e3b0de904415e27c9e9e9af3e1e3c8923025 | [
"MIT"
] | null | null | null | import datetime
import logging
import numpy as np
import matplotlib.pyplot as plt
from nn.shallow.nn_shallow_cs import CryptoNNClient
from nn.shallow.nn_shallow_cs import CryptoNNServer
from nn.utils import load_mnist
from nn.utils import load_mnist_size
from nn.utils import timer
from nn.smc import Secure2PCClient
from nn.smc import Secure2PCServer
from nn.smc import EnhancedSecure2PCClient
from nn.smc import EnhancedSecure2PCServer
from crypto.utils import load_dlog_table_config
from crypto.sife_dynamic import SIFEDynamicTPA
from crypto.sife_dynamic import SIFEDynamicClient
from crypto.mife_dynamic import MIFEDynamicTPA
from crypto.mife_dynamic import MIFEDynamicClient
t_str = str(datetime.datetime.today())
logging.basicConfig(
level=logging.DEBUG,
format='%(asctime)s %(name)-12s %(levelname)-8s %(message)s',
datefmt='%m-%d %H:%M',
filename="logs/test_nn_shallow_cs-" + '-'.join(t_str.split()[:1] + t_str.split()[1].split(':')[:2]) + '.log',
filemode='w')
logger = logging.getLogger(__name__)
def test_nn_shallow_mnist():
X_train, y_train = load_mnist_size('datasets/mnist', size=600)
X_test, y_test = load_mnist_size('datasets/mnist', size=100, kind='t10k')
# X_train, y_train = load_mnist('datasets/mnist')
# X_test, y_test = load_mnist('datasets/mnist', kind='t10k')
# shuffle
X_data, y_data = X_train.copy(), y_train.copy()
idx = np.random.permutation(X_data.shape[0])
X_data, y_data = X_data[idx], y_data[idx]
total_mini_batches = 10
hidden_layers_lst = [
[256],
[256, 128, 64],
[256, 128, 64, 32, 16]
]
for hidden_layers in hidden_layers_lst:
nn_client = CryptoNNClient(n_output=10, mini_batches=total_mini_batches, n_features=X_data.shape[1], random_seed=520)
nn_server = CryptoNNServer(n_output=10, n_features=X_data.shape[1], hidden_layers=hidden_layers,
l2=0.1, l1=0.0, epochs=1, eta=0.001, alpha=0.001,
decrease_const=0.0001, mini_batches=total_mini_batches)
X_client, y_client = nn_client.pre_process(X_data, y_data)
with timer('training using secure2pc setting - 10 batches-' + str(hidden_layers), logger) as t:
(train_loss_hist,
test_acc_hist,
train_batch_time_hist,
train_time_hist) = nn_server.fit(X_client, y_client, X_test, y_test)
logger.info('train loss: \n' + str(train_loss_hist))
logger.info('test acc: \n' + str(test_acc_hist))
def test_nn_shallow_mnist_smc():
logger.info('test nn shallow mnist with secure 2pc setting')
logger.info('initialize the crypto system ...')
sec_param_config_file = 'config/sec_param.json' # indicate kernel size 5
dlog_table_config_file = 'config/dlog_b8.json'
with timer('load sife config file, cost time', logger) as t:
eta = 1250
sec_param = 256
dlog = load_dlog_table_config(dlog_table_config_file)
sife_tpa = SIFEDynamicTPA(eta, sec_param=sec_param, sec_param_config=sec_param_config_file)
sife_tpa.setup()
sife_enc_client = SIFEDynamicClient(role='enc')
sife_dec_client = SIFEDynamicClient(role='dec', dlog=dlog)
logger.info('the crypto system initialization done!')
precision_data = 0
precision_weight = 3
secure2pc_client = Secure2PCClient(sife=(sife_tpa, sife_enc_client), precision=precision_data)
secure2pc_server = Secure2PCServer(sife=(sife_tpa, sife_dec_client), precision=(precision_data, precision_weight))
X_train, y_train = load_mnist_size('datasets/mnist', size=600)
X_test, y_test = load_mnist_size('datasets/mnist', size=100, kind='t10k')
# X_train, y_train = load_mnist('datasets/mnist')
# X_test, y_test = load_mnist('datasets/mnist', kind='t10k')
# shuffle
X_data, y_data = X_train.copy(), y_train.copy()
idx = np.random.permutation(X_data.shape[0])
X_data, y_data = X_data[idx], y_data[idx]
total_mini_batches = 50
nn_client = CryptoNNClient(n_output=10, mini_batches=total_mini_batches, n_features=X_data.shape[1], smc=secure2pc_client, random_seed=520)
nn_server = CryptoNNServer(n_output=10, n_features=X_data.shape[1], hidden_layers=[64],
l2=0.1, l1=0.0, epochs=1, eta=0.001, alpha=0.001,
decrease_const=0.0001, mini_batches=total_mini_batches, smc=secure2pc_server)
logger.info('client start to encrypt dataset ...')
ct_feedforward_lst, ct_backpropagation_lst, y_onehot_lst = nn_client.pre_process(X_data, y_data)
logger.info('client encrypting DONE')
logger.info('server start to train ...')
with timer('training using secure2pc setting - 10 batches', logger) as t:
(train_loss_hist,
test_acc_hist,
train_batch_time_hist,
train_time_hist) = nn_server.fit((ct_feedforward_lst, ct_backpropagation_lst), y_onehot_lst, X_test, y_test)
logger.info('server training DONE')
logger.info('training loss: \n\r' + str(train_loss_hist))
logger.info('test acc: \n\r' + str(test_acc_hist))
def test_nn_shallow_mnist_smc_enhanced():
logger.info('test nn shallow in mnist using enhanced smc')
logger.info('initialize the crypto system ...')
sec_param_config_file = 'config/sec_param.json' # indicate kernel size 5
dlog_table_config_file = 'config/dlog_b8.json'
with timer('initialize crypto system, cost time', logger) as t:
eta = 1250
sec_param = 256
setup_parties = {
'id_1': 200,
'id_2': 200,
'id_3': 200,
'id_4': 200,
'id_5': 200
}
logger.info('loading dlog configuration ...')
dlog = load_dlog_table_config(dlog_table_config_file)
logger.info('load dlog configuration DONE')
sife_tpa = SIFEDynamicTPA(eta, sec_param=sec_param, sec_param_config=sec_param_config_file)
sife_tpa.setup()
sife_enc_client = SIFEDynamicClient(sec_param=256, role='enc')
sife_dec_client = SIFEDynamicClient(sec_param=256, role='dec', dlog=dlog)
mife_tpa = MIFEDynamicTPA(sec_param=256, parties=setup_parties, sec_param_config=sec_param_config_file)
mife_tpa.setup()
mife_enc_client = MIFEDynamicClient(sec_param=256, role='enc')
mife_dec_client = MIFEDynamicClient(sec_param=256, role='dec', dlog=dlog)
logger.info('the crypto system initialization done!')
precision_data = 0
precision_weight = 4
es2pc_client = EnhancedSecure2PCClient(
sife=(sife_tpa, sife_enc_client),
mife=(mife_tpa, mife_enc_client),
precision=precision_data)
es2pc_server = EnhancedSecure2PCServer(
sife=(sife_tpa, sife_dec_client),
mife=(mife_tpa, mife_dec_client),
precision=(precision_data, precision_weight))
X_train, y_train = load_mnist_size('datasets/mnist', size=600)
X_test, y_test = load_mnist_size('datasets/mnist', size=100, kind='t10k')
# X_train, y_train = load_mnist('datasets/mnist')
# X_test, y_test = load_mnist('datasets/mnist', kind='t10k')
# shuffle
X_data, y_data = X_train.copy(), y_train.copy()
idx = np.random.permutation(X_data.shape[0])
X_data, y_data = X_data[idx], y_data[idx]
features_splits = np.array_split(range(X_data.shape[1]), len(setup_parties))
X_data_lst = [X_data[:, idx] for idx in features_splits]
total_mini_batches = 50
nn_server = CryptoNNServer(n_output=10, n_features=X_data.shape[1], hidden_layers=[64],
l2=0.1, l1=0.0, epochs=50, eta=0.001, alpha=0.001,
decrease_const=0.0001, mini_batches=total_mini_batches, smc=es2pc_server)
logger.info('client start to encrypt dataset ...')
ct_ff_lst_dict = dict()
ct_bp_lst_dict = dict()
x_idx_count = 0
final_y_onehot_lst = None
for id in setup_parties.keys():
if x_idx_count == (len(setup_parties) - 1):
n_features = X_data_lst[x_idx_count].shape[1] + 1
nn_client = CryptoNNClient(n_output=10, mini_batches=total_mini_batches, n_features=n_features,
smc=es2pc_client, random_seed=520, id=id)
nn_server.register(nn_client)
ct_feedforward_lst, ct_backpropagation_lst, y_onehot_lst = nn_client.pre_process(X_data_lst[x_idx_count], y_data)
ct_ff_lst_dict[id] = ct_feedforward_lst
ct_bp_lst_dict[id] = ct_backpropagation_lst
final_y_onehot_lst = y_onehot_lst
else:
n_features = X_data_lst[x_idx_count].shape[1]
nn_client = CryptoNNClient(n_output=10, mini_batches=total_mini_batches, n_features=n_features,
smc=es2pc_client, random_seed=520, id=id)
nn_server.register(nn_client)
ct_feedforward_lst, ct_backpropagation_lst = nn_client.pre_process(X_data_lst[x_idx_count])
ct_ff_lst_dict[id] = ct_feedforward_lst
ct_bp_lst_dict[id] = ct_backpropagation_lst
x_idx_count = x_idx_count + 1
logger.info('client encrypting DONE')
logger.info('server start to train ...')
(train_loss_hist,
test_acc_hist,
train_batch_time_hist,
train_time_hist) = nn_server.fit((ct_ff_lst_dict, ct_bp_lst_dict), final_y_onehot_lst, X_test, y_test)
logger.info('server training DONE')
logger.info('training loss: \n\r' + str(train_loss_hist))
logger.info('test acc: \n\r' + str(test_acc_hist))
def test_nn_shallow_mnist_smc_cryptonn():
logger.info('test nn shallow mnist with secure 2pc setting')
logger.info('initialize the crypto system ...')
eta = 1250
sec_param = 256
sife_tpa = SIFEDynamicTPA(eta, sec_param=sec_param)
sife_tpa.setup()
sife_enc_client = SIFEDynamicClient(role='enc')
sife_dec_client = SIFEDynamicClient(role='dec')
logger.info('the crypto system initialization done!')
precision_data = 0
precision_weight = 4
secure2pc_client = Secure2PCClient(sife=(sife_tpa, sife_enc_client), precision=precision_data)
secure2pc_server = Secure2PCServer(sife=(sife_tpa, sife_dec_client), precision=(precision_data, precision_weight))
X_train, y_train = load_mnist_size('datasets/mnist', size=60)
X_test, y_test = load_mnist_size('datasets/mnist', size=100, kind='t10k')
# X_train, y_train = load_mnist('datasets/mnist')
# X_test, y_test = load_mnist('datasets/mnist', kind='t10k')
# shuffle
X_data, y_data = X_train.copy(), y_train.copy()
idx = np.random.permutation(X_data.shape[0])
X_data, y_data = X_data[idx], y_data[idx]
total_mini_batches = 1
nn_client = CryptoNNClient(n_output=10, mini_batches=total_mini_batches, n_features=X_data.shape[1], smc=secure2pc_client, random_seed=520)
nn_server = CryptoNNServer(n_output=10, n_features=X_data.shape[1], hidden_layers=[64],
l2=0.1, l1=0.0, epochs=50, eta=0.001, alpha=0.001,
decrease_const=0.0001, mini_batches=total_mini_batches, smc=secure2pc_server)
logger.info('client start to encrypt dataset ...')
ct_feedforward_lst, ct_backpropagation_lst, y_onehot_lst = nn_client.pre_process(X_data, y_data)
logger.info('client encrypting DONE')
logger.info('server start to train ...')
with timer('training using secure2pc setting - 1 batches', logger) as t:
(train_loss_hist,
test_acc_hist,
train_batch_time_hist,
train_time_hist) = nn_server.fit((ct_feedforward_lst, ct_backpropagation_lst), y_onehot_lst, X_test, y_test)
logger.info('server training DONE')
logger.info('training loss: \n\r' + str(train_loss_hist))
logger.info('test acc: \n\r' + str(test_acc_hist)) | 45.625483 | 143 | 0.6907 | 1,712 | 11,817 | 4.436916 | 0.109229 | 0.021722 | 0.027383 | 0.015798 | 0.828726 | 0.791338 | 0.76119 | 0.744207 | 0.728805 | 0.707346 | 0 | 0.033136 | 0.200643 | 11,817 | 259 | 144 | 45.625483 | 0.771014 | 0.042735 | 0 | 0.538462 | 0 | 0 | 0.122057 | 0.005842 | 0.004808 | 0 | 0 | 0 | 0 | 1 | 0.019231 | false | 0 | 0.086538 | 0 | 0.105769 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
fe14df0d27b1225b06bdd216b9e46c2709864838 | 3,021 | py | Python | tests/portmirror/test_set_rx_and_tx_mode.py | ararobotique/botblox-manager-software | 64c5c893601ea62a7ac414023455e8c2da04816d | [
"MIT"
] | 6 | 2021-04-18T21:30:17.000Z | 2022-01-13T06:37:43.000Z | tests/portmirror/test_set_rx_and_tx_mode.py | ararobotique/botblox-manager-software | 64c5c893601ea62a7ac414023455e8c2da04816d | [
"MIT"
] | 36 | 2020-12-16T12:29:24.000Z | 2021-09-18T14:52:25.000Z | tests/portmirror/test_set_rx_and_tx_mode.py | ararobotique/botblox-manager-software | 64c5c893601ea62a7ac414023455e8c2da04816d | [
"MIT"
] | 2 | 2021-04-08T20:27:48.000Z | 2021-08-30T17:32:28.000Z | from typing import AnyStr, List
from botblox_config.cli import create_parser
from pytest import CaptureFixture
from ..conftest import assert_ip175g_command_is_correct_type, get_data_from_cli_args, run_command_to_error
class TestSetRxAndTxMode:
package: List[str] = ['botblox']
base_args: List[str] = [
'--device',
'test',
'mirror',
'-m',
'RXandTX',
]
def test_single_tx_and_single_rx_port(
self,
) -> None:
test_args = self.base_args + [
'-M',
'1',
'-tx',
'2',
'-rx',
'3',
]
data = get_data_from_cli_args(parser=create_parser(self.base_args), args=test_args)
assert_ip175g_command_is_correct_type(data=data)
expected_result = [[20, 4, 8, 64], [20, 3, 16, 192]]
assert data == expected_result
def test_same_tx_and_rx_port(
self,
) -> None:
test_args = self.base_args + [
'-M',
'1',
'-tx',
'2',
'-rx',
'2',
]
data = get_data_from_cli_args(parser=create_parser(self.base_args), args=test_args)
assert_ip175g_command_is_correct_type(data=data)
expected_result = [[20, 4, 8, 64], [20, 3, 8, 192]]
assert data == expected_result
def test_rx_port_non_existent(
self,
capfd: CaptureFixture,
) -> None:
test_args = self.base_args + [
'-M',
'1',
'-tx',
'2',
]
run_command_to_error(self.package, test_args)
captured: CaptureFixture[AnyStr] = capfd.readouterr()
assert captured.out == ''
expected_stderr = 'mirror: error: the following arguments are required: -rx/--rx-port'
actual_stderr: str = captured.err
assert actual_stderr.find(expected_stderr) > -1
def test_tx_port_non_existent(
self,
capfd: CaptureFixture,
) -> None:
test_args = self.base_args + [
'-M',
'1',
'-rx',
'2',
]
run_command_to_error(self.package, test_args)
captured: CaptureFixture[AnyStr] = capfd.readouterr()
assert captured.out == ''
expected_stderr = 'mirror: error: the following arguments are required: -tx/--tx-port'
actual_stderr: str = captured.err
assert actual_stderr.find(expected_stderr) > -1
def test_no_rx_or_tx_port(
self,
capfd: CaptureFixture,
) -> None:
test_args = self.base_args + [
'-M',
'1',
]
run_command_to_error(self.package, test_args)
captured: CaptureFixture[AnyStr] = capfd.readouterr()
assert captured.out == ''
expected_stderr = 'mirror: error: the following arguments are required: -rx/--rx-port, -tx/--tx-port'
actual_stderr: str = captured.err
assert actual_stderr.find(expected_stderr) > -1
| 26.269565 | 109 | 0.562066 | 343 | 3,021 | 4.655977 | 0.209913 | 0.050094 | 0.052599 | 0.050094 | 0.832185 | 0.820914 | 0.800877 | 0.758297 | 0.758297 | 0.758297 | 0 | 0.024486 | 0.324065 | 3,021 | 114 | 110 | 26.5 | 0.757591 | 0 | 0 | 0.674157 | 0 | 0.011236 | 0.094671 | 0 | 0 | 0 | 0 | 0 | 0.123596 | 1 | 0.05618 | false | 0 | 0.044944 | 0 | 0.134831 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
a3a8dbcff433b9f526e0ff231ea26a2bc1d663da | 221 | py | Python | presto/Preprocessors/Multiscale/__init__.py | padmec-reservoir/PRESTO | d9ab92f2df020a36d13040ce6157162402b93c8e | [
"MIT"
] | 42 | 2017-05-04T05:29:19.000Z | 2021-09-15T14:03:33.000Z | presto/Preprocessors/Multiscale/__init__.py | jpra2/Presto2 | 71525a8dece2bcc4f16ff4a2120d7627e9ecd776 | [
"CNRI-Python"
] | null | null | null | presto/Preprocessors/Multiscale/__init__.py | jpra2/Presto2 | 71525a8dece2bcc4f16ff4a2120d7627e9ecd776 | [
"CNRI-Python"
] | 15 | 2017-06-19T20:09:06.000Z | 2021-06-02T12:40:42.000Z | """
Multiscale preprocessors for reservoir simulation using PRESTO.
"""
__all__ = ['Structured', 'Structured2D']
from .Structured import Preprocessor as Structured
from .Structured2D import Preprocessor as Structured2D
| 24.555556 | 63 | 0.800905 | 22 | 221 | 7.863636 | 0.636364 | 0.208092 | 0.231214 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.015464 | 0.122172 | 221 | 8 | 64 | 27.625 | 0.876289 | 0.285068 | 0 | 0 | 0 | 0 | 0.146667 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.666667 | 0 | 0.666667 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 0 | 6 |
a3a9a7537046021bc9c17a8cb4ba9bb3f92d292d | 41 | py | Python | explorer/resources/search/__init__.py | shalevy1/gexplorer | 5216a506aace8259bc84495018c4a67dda220403 | [
"Apache-2.0"
] | null | null | null | explorer/resources/search/__init__.py | shalevy1/gexplorer | 5216a506aace8259bc84495018c4a67dda220403 | [
"Apache-2.0"
] | 1 | 2022-03-21T22:21:30.000Z | 2022-03-21T22:21:30.000Z | explorer/resources/search/__init__.py | shalevy1/gexplorer | 5216a506aace8259bc84495018c4a67dda220403 | [
"Apache-2.0"
] | null | null | null | from explorer.resources.search import v0
| 20.5 | 40 | 0.853659 | 6 | 41 | 5.833333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.027027 | 0.097561 | 41 | 1 | 41 | 41 | 0.918919 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
a3a9f1ee23303d5f40863f99a446b2caa7375f0f | 6,261 | py | Python | persistence/repositories/exam_solution_repository_postgres.py | Ubademy-G3/exams.service | c589256181d5490ea0712f1dfbfebb360e21a10a | [
"MIT"
] | null | null | null | persistence/repositories/exam_solution_repository_postgres.py | Ubademy-G3/exams.service | c589256181d5490ea0712f1dfbfebb360e21a10a | [
"MIT"
] | null | null | null | persistence/repositories/exam_solution_repository_postgres.py | Ubademy-G3/exams.service | c589256181d5490ea0712f1dfbfebb360e21a10a | [
"MIT"
] | null | null | null | from infrastructure.db.exam_solution_schema import ExamSolution
import logging
logger = logging.getLogger(__name__)
class ExamSolutionRepositoryPostgres:
def add_exam_solution(self, db, exam_solution):
db.add(exam_solution)
db.commit()
logger.info("New exam solution added")
logger.debug("ID of the new exam solution: %s", exam_solution.id)
def get_exam_solution(self, db, exam_solution_id):
exam_solution = db.query(ExamSolution).filter(ExamSolution.id == exam_solution_id).first()
logger.debug("Getting exam solution %s", exam_solution_id)
return exam_solution
def get_all_exam_solutions_by_exam_template_id(self, db, exam_template_id, graded, approval_state):
query = db.query(ExamSolution).filter(ExamSolution.exam_template_id == exam_template_id)
if graded is not None:
logger.debug("Get solutions of exam template %s with filter graded %s", exam_template_id, graded)
query = query.filter(ExamSolution.graded == graded)
if approval_state is not None:
logger.debug("Get solutions of exam template %s with filter approval_state %s", exam_template_id, approval_state)
query = query.filter(ExamSolution.approval_state == approval_state)
exam_solutions = query.all()
logger.debug("Getting all solutions of exam template %s", exam_template_id)
return exam_solutions
def get_all_exam_solutions_by_user_id(self, db, user_id, graded, approval_state):
query = db.query(ExamSolution).filter(ExamSolution.user_id == user_id)
if graded is not None:
logger.debug("Get solutions of exam for user %s with filter graded %s", user_id, graded)
query = query.filter(ExamSolution.graded == graded)
if approval_state is not None:
logger.debug("Get solutions of exam for user %s with filter approval_state %s", user_id, approval_state)
query = query.filter(ExamSolution.approval_state == approval_state)
exam_solutions = query.all()
logger.debug("Getting all solutions of exam for user %s", user_id)
return exam_solutions
def get_all_exam_solutions_by_user_id_and_exam_template_id(self, db, user_id, exam_template_id):
query = db.query(ExamSolution).filter(ExamSolution.user_id == user_id)
query = query.filter(ExamSolution.exam_template_id == exam_template_id)
exam_solutions = query.all()
logger.debug("Getting all solutions by user %s and exam template %s", user_id, exam_template_id)
return exam_solutions
def get_all_exam_solutions_by_corrector_id(self, db, corrector_id, graded, approval_state):
query = db.query(ExamSolution).filter(ExamSolution.corrector_id == corrector_id)
if graded is not None:
logger.debug("Get solutions of exam for corrector %s with filter graded %s", corrector_id, graded)
query = query.filter(ExamSolution.graded == graded)
if approval_state is not None:
logger.debug("Get solutions of exam for corrector %s with filter approval_state %s", corrector_id, graded)
query = query.filter(ExamSolution.approval_state == approval_state)
exam_solutions = query.all()
logger.debug("Getting all solutions of exam for corrector %s", corrector_id)
return exam_solutions
def get_all_exam_solutions_by_course_id(self, db, course_id, graded, approval_state):
query = db.query(ExamSolution).filter(ExamSolution.course_id == course_id)
if graded is not None:
logger.debug("Get solutions of exam for course %s with filter graded %s", course_id, graded)
query = query.filter(ExamSolution.graded == graded)
if approval_state is not None:
logger.debug("Get solutions of exam for course %s with filter approval_state %s", course_id, graded)
query = query.filter(ExamSolution.approval_state == approval_state)
exam_solutions = query.all()
logger.debug("Getting all solutions of exam for course %s", course_id)
return exam_solutions
def get_all_exam_solutions_by_user_id_and_course_id(self, db, user_id, course_id, graded, approval_state):
query = db.query(ExamSolution).filter(ExamSolution.user_id == user_id)
query = query.filter(ExamSolution.course_id == course_id)
if graded is not None:
logger.debug("Get solutions of exam for course %s and user %s with filter graded %s", course_id, user_id, graded)
query = query.filter(ExamSolution.graded == graded)
if approval_state is not None:
logger.debug(
"Get solutions of exam for course %s and user %s with filter aproval_state %s",
course_id,
user_id,
approval_state,
)
query = query.filter(ExamSolution.approval_state == approval_state)
exam_solutions = query.all()
return exam_solutions
def get_all_exam_solutions_by_corrector_id_and_course_id(self, db, corrector_id, course_id, graded, approval_state):
query = db.query(ExamSolution).filter(ExamSolution.corrector_id == corrector_id)
query = query.filter(ExamSolution.course_id == course_id)
if graded is not None:
logger.debug(
"Get solutions of exam for course %s and corrector %s with filter graded %s", course_id, corrector_id, graded
)
query = query.filter(ExamSolution.graded == graded)
if approval_state is not None:
logger.debug(
"Get solutions of exam for course %s and corrector %s with filter aproval_state %s",
course_id,
corrector_id,
approval_state,
)
query = query.filter(ExamSolution.approval_state == approval_state)
exam_solutions = query.all()
return exam_solutions
def delete_exam_solution(self, db, exam_solution):
db.delete(exam_solution)
db.commit()
logger.debug("Delete exam solution %s", exam_solution.id)
logger.info("Exam solution deleted")
def update_exam_solution(self, db):
db.commit()
| 52.613445 | 125 | 0.68184 | 822 | 6,261 | 4.961071 | 0.064477 | 0.102011 | 0.058852 | 0.102992 | 0.892104 | 0.838646 | 0.776116 | 0.751594 | 0.721923 | 0.709416 | 0 | 0 | 0.237023 | 6,261 | 118 | 126 | 53.059322 | 0.853674 | 0 | 0 | 0.528846 | 0 | 0 | 0.180802 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.105769 | false | 0 | 0.019231 | 0 | 0.211538 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
a3b96dd45bd5a2c41c3a98f25b2bb582cb2ccf0d | 519 | py | Python | Latest/venv/Lib/site-packages/apptools/naming/trait_defs/__init__.py | adamcvj/SatelliteTracker | 49a8f26804422fdad6f330a5548e9f283d84a55d | [
"Apache-2.0"
] | 1 | 2022-01-09T20:04:31.000Z | 2022-01-09T20:04:31.000Z | Latest/venv/Lib/site-packages/apptools/naming/trait_defs/__init__.py | adamcvj/SatelliteTracker | 49a8f26804422fdad6f330a5548e9f283d84a55d | [
"Apache-2.0"
] | 1 | 2022-02-15T12:01:57.000Z | 2022-03-24T19:48:47.000Z | Latest/venv/Lib/site-packages/apptools/naming/trait_defs/__init__.py | adamcvj/SatelliteTracker | 49a8f26804422fdad6f330a5548e9f283d84a55d | [
"Apache-2.0"
] | null | null | null | #------------------------------------------------------------------------------
#
# Define traits useful with Naming.
#
# Written by: David C. Morrill
#
# Date: 08/16/2005
#
# (c) Copyright 2005 by Enthought, Inc.
#
#------------------------------------------------------------------------------
#------------------------------------------------------------------------------
# Imports:
#------------------------------------------------------------------------------
from apptools.naming.trait_defs.api import *
| 28.833333 | 79 | 0.258189 | 28 | 519 | 4.75 | 0.857143 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.025263 | 0.084778 | 519 | 17 | 80 | 30.529412 | 0.254737 | 0.855491 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
431f24dbacc0630b0662c4b214a828473e485702 | 322 | py | Python | strings/tests/test_string_to_integer.py | ahcode0919/python-ds-algorithms | 0d617b78c50b6c18da40d9fa101438749bfc82e1 | [
"MIT"
] | null | null | null | strings/tests/test_string_to_integer.py | ahcode0919/python-ds-algorithms | 0d617b78c50b6c18da40d9fa101438749bfc82e1 | [
"MIT"
] | null | null | null | strings/tests/test_string_to_integer.py | ahcode0919/python-ds-algorithms | 0d617b78c50b6c18da40d9fa101438749bfc82e1 | [
"MIT"
] | 3 | 2020-10-07T20:24:45.000Z | 2020-12-16T04:53:19.000Z | from strings.string_to_integer import string_to_integer
def test_string_to_integer():
assert string_to_integer("34") == 34
assert string_to_integer(" 100abc") == 100
assert string_to_integer(" -12vdsr") == -12
assert string_to_integer("vdsr12") == 0
assert string_to_integer(" -12 vdsr") == -12
| 32.2 | 55 | 0.704969 | 45 | 322 | 4.666667 | 0.377778 | 0.304762 | 0.571429 | 0.5 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.079245 | 0.177019 | 322 | 9 | 56 | 35.777778 | 0.713208 | 0 | 0 | 0.285714 | 0 | 0 | 0.114907 | 0 | 0 | 0 | 0 | 0 | 0.714286 | 1 | 0.142857 | true | 0 | 0.142857 | 0 | 0.285714 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 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 | 1 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
4a2f19ebbdefc82748175c4dd6d8b3924a2bdf99 | 63 | py | Python | autogram/commons/models/__init__.py | ohduran/autogram | e24c7ff40c44cd0eabf8018e61ad5fe0b422a6a1 | [
"MIT"
] | null | null | null | autogram/commons/models/__init__.py | ohduran/autogram | e24c7ff40c44cd0eabf8018e61ad5fe0b422a6a1 | [
"MIT"
] | null | null | null | autogram/commons/models/__init__.py | ohduran/autogram | e24c7ff40c44cd0eabf8018e61ad5fe0b422a6a1 | [
"MIT"
] | null | null | null | from .models import * # noqa
from .querysets import * # noqa
| 21 | 32 | 0.68254 | 8 | 63 | 5.375 | 0.625 | 0.465116 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.222222 | 63 | 2 | 33 | 31.5 | 0.877551 | 0.142857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4a5d466ad698e35ace6f223f5268bf0a61f61d44 | 94 | py | Python | tests/test_version_return.py | moritzkoerber/binary4fun | 0184989c0484754e2597d9944a2a00dc8076bc07 | [
"MIT"
] | null | null | null | tests/test_version_return.py | moritzkoerber/binary4fun | 0184989c0484754e2597d9944a2a00dc8076bc07 | [
"MIT"
] | null | null | null | tests/test_version_return.py | moritzkoerber/binary4fun | 0184989c0484754e2597d9944a2a00dc8076bc07 | [
"MIT"
] | null | null | null | import sh
def test_should_return_version():
assert sh.python(["setup.py", "--version"])
| 15.666667 | 47 | 0.691489 | 13 | 94 | 4.769231 | 0.846154 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.138298 | 94 | 5 | 48 | 18.8 | 0.765432 | 0 | 0 | 0 | 0 | 0 | 0.180851 | 0 | 0 | 0 | 0 | 0 | 0.333333 | 1 | 0.333333 | true | 0 | 0.333333 | 0 | 0.666667 | 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 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4a69a24557392778c39b917ad20be7fdf4f652f9 | 32 | py | Python | Adafruit_CharLCD/__init__.py | maroianenasrellah/Adafruit_Python_CharLCD | bc75cad284766240424f29dc8e7b84d0caceb72e | [
"MIT"
] | 224 | 2015-01-15T20:47:10.000Z | 2022-02-05T18:41:55.000Z | Adafruit_CharLCD/__init__.py | maroianenasrellah/Adafruit_Python_CharLCD | bc75cad284766240424f29dc8e7b84d0caceb72e | [
"MIT"
] | 30 | 2015-01-01T14:59:52.000Z | 2018-11-21T21:08:59.000Z | Adafruit_CharLCD/__init__.py | maroianenasrellah/Adafruit_Python_CharLCD | bc75cad284766240424f29dc8e7b84d0caceb72e | [
"MIT"
] | 156 | 2015-01-01T16:36:43.000Z | 2022-01-06T12:05:50.000Z | from .Adafruit_CharLCD import *
| 16 | 31 | 0.8125 | 4 | 32 | 6.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 32 | 1 | 32 | 32 | 0.892857 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4a77169f90fce8b735a3a35357f3ba61c5f1f6c1 | 13,057 | py | Python | tests/test_elements/test_ui_horizontal_slider.py | ylenard/pygame_gui | 03683215cc6a838ca1c245af9cfa157b29da700b | [
"MIT"
] | null | null | null | tests/test_elements/test_ui_horizontal_slider.py | ylenard/pygame_gui | 03683215cc6a838ca1c245af9cfa157b29da700b | [
"MIT"
] | null | null | null | tests/test_elements/test_ui_horizontal_slider.py | ylenard/pygame_gui | 03683215cc6a838ca1c245af9cfa157b29da700b | [
"MIT"
] | null | null | null | import os
import pytest
import pygame
from tests.shared_fixtures import _init_pygame, default_ui_manager, default_display_surface, _display_surface_return_none
from pygame_gui.ui_manager import UIManager
from pygame_gui.elements.ui_horizontal_slider import UIHorizontalSlider
from pygame_gui.core.ui_container import UIContainer
from pygame_gui.core.interfaces import IUIManagerInterface
class TestUIHorizontalSlider:
def test_creation(self, _init_pygame, default_ui_manager: IUIManagerInterface,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
assert scroll_bar.image is not None
def test_rebuild(self, _init_pygame, default_ui_manager: IUIManagerInterface,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
scroll_bar.rebuild()
assert scroll_bar.image is not None
def test_kill(self, _init_pygame, default_ui_manager: IUIManagerInterface,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
assert len(default_ui_manager.get_root_container().elements) == 2
assert len(default_ui_manager.get_sprite_group().sprites()) == 6
assert default_ui_manager.get_sprite_group().sprites() == [default_ui_manager.get_root_container(),
scroll_bar,
scroll_bar.button_container,
scroll_bar.left_button,
scroll_bar.right_button,
scroll_bar.sliding_button]
scroll_bar.kill()
assert len(default_ui_manager.get_root_container().elements) == 0
assert len(default_ui_manager.get_sprite_group().sprites()) == 1
assert default_ui_manager.get_sprite_group().sprites() == [default_ui_manager.get_root_container()]
def test_check_has_moved_recently(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
# move the scroll bar a bit
scroll_bar.left_button.held = True
scroll_bar.update(0.2)
assert scroll_bar.has_moved_recently is True
def test_check_update_buttons(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
# scroll down a bit then up again to exercise update
scroll_bar.get_current_value() # Clear has moved this turn
scroll_bar.left_button.held = True
scroll_bar.update(0.3)
scroll_bar.left_button.held = False
scroll_bar.right_button.held = True
scroll_bar.update(0.3)
assert scroll_bar.has_moved_recently is True
def test_check_update_sliding_bar(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(0, 0, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
# scroll down a bit then up again to exercise update
default_ui_manager.mouse_position = (100, 15)
scroll_bar.sliding_button.held = True
scroll_bar.update(0.3)
assert scroll_bar.grabbed_slider is True
scroll_bar.sliding_button.held = False
scroll_bar.update(0.3)
assert scroll_bar.grabbed_slider is False
def test_get_current_value(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
assert scroll_bar.get_current_value() == 50
def test_set_current_value_in_range(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
scroll_bar.set_current_value(75)
assert scroll_bar.get_current_value() == 75
def test_set_current_value_out_of_range(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=default_ui_manager)
with pytest.warns(UserWarning, match='value not in range'):
scroll_bar.set_current_value(200)
def test_rebuild_from_theme_data_non_default(self, _init_pygame,
_display_surface_return_none):
manager = UIManager((800, 600), os.path.join("tests", "data",
"themes",
"ui_horizontal_slider_non_default.json"))
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=manager)
assert scroll_bar.image is not None
def test_rebuild_from_theme_data_no_arrow_buttons(self, _init_pygame,
_display_surface_return_none):
manager = UIManager((800, 600), os.path.join("tests",
"data",
"themes",
"ui_horizontal_slider_no_arrows.json"))
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=50,
value_range=(0, 100),
manager=manager)
assert scroll_bar.left_button is None
assert scroll_bar.right_button is None
assert scroll_bar.image is not None
@pytest.mark.filterwarnings("ignore:Invalid value")
@pytest.mark.filterwarnings("ignore:Colour hex code")
def test_rebuild_from_theme_data_bad_values(self, _init_pygame,
_display_surface_return_none):
manager = UIManager((800, 600), os.path.join("tests",
"data",
"themes",
"ui_horizontal_slider_bad_values.json"))
scroll_bar = UIHorizontalSlider(relative_rect=pygame.Rect(100, 100, 200, 30),
start_value=51,
value_range=(0, 100),
manager=manager)
assert scroll_bar.image is not None
def test_set_position(self, _init_pygame, default_ui_manager, _display_surface_return_none):
slider = UIHorizontalSlider(relative_rect=pygame.Rect(300, 400, 150, 40), start_value=50,
value_range=(0, 200), manager=default_ui_manager)
slider.set_position((200, 200))
# try to click on the slider
default_ui_manager.process_events(pygame.event.Event(pygame.MOUSEBUTTONDOWN,
{'button': 1,
'pos': (205, 205)}))
# if we successfully clicked on the moved slider then this button should be True
assert slider.left_button.held is True
def test_set_relative_position(self, _init_pygame, default_ui_manager,
_display_surface_return_none):
test_container = UIContainer(relative_rect=pygame.Rect(100, 100, 300, 60),
manager=default_ui_manager)
slider = UIHorizontalSlider(relative_rect=pygame.Rect(300, 400, 150, 40),
start_value=50,
container=test_container,
value_range=(0, 200), manager=default_ui_manager)
slider.set_relative_position((150.0, 30.0))
# try to click on the slider
default_ui_manager.process_events(pygame.event.Event(pygame.MOUSEBUTTONDOWN,
{'button': 1,
'pos': (260, 150)}))
assert slider.rect.topleft == (250, 130) and slider.left_button.held is True
def test_set_dimensions(self, _init_pygame, default_ui_manager, _display_surface_return_none):
slider = UIHorizontalSlider(relative_rect=pygame.Rect(0, 0, 150, 40), start_value=50,
value_range=(0, 200), manager=default_ui_manager)
slider.set_dimensions((200, 60))
# try to click on the slider
default_ui_manager.process_events(pygame.event.Event(pygame.MOUSEBUTTONDOWN,
{'button': 1,
'pos': (195, 50)}))
# if we successfully clicked on the moved slider then this button should be True
assert slider.right_button.held is True
assert slider.right_button.rect.top == (slider.shadow_width + slider.border_width)
assert slider.right_button.rect.bottom == 60 - (slider.shadow_width + slider.border_width)
assert slider.right_button.rect.right == 200 - (slider.shadow_width + slider.border_width)
slider.set_dimensions((100, 30))
# try to click on the slider
default_ui_manager.process_events(pygame.event.Event(pygame.MOUSEBUTTONDOWN,
{'button': 1,
'pos': (95, 15)}))
# if we successfully clicked on the moved slider then this button should be True
assert slider.right_button.held is True
assert slider.right_button.rect.top == (slider.shadow_width + slider.border_width)
assert slider.right_button.rect.bottom == 30 - (slider.shadow_width + slider.border_width)
assert slider.right_button.rect.right == 100 - (slider.shadow_width + slider.border_width)
slider.set_dimensions((150, 45))
# try to click on the slider
default_ui_manager.process_events(pygame.event.Event(pygame.MOUSEBUTTONDOWN,
{'button': 1,
'pos': (145, 22)}))
# if we successfully clicked on the moved slider then this button should be True
assert slider.right_button.held is True
assert slider.right_button.rect.top == (slider.shadow_width + slider.border_width)
assert slider.right_button.rect.bottom == 45 - (slider.shadow_width + slider.border_width)
assert slider.right_button.rect.right == 150 - (slider.shadow_width + slider.border_width)
| 53.954545 | 121 | 0.544918 | 1,338 | 13,057 | 4.992526 | 0.118834 | 0.063323 | 0.095808 | 0.057485 | 0.842964 | 0.807036 | 0.77515 | 0.77021 | 0.77006 | 0.711377 | 0 | 0.047868 | 0.385617 | 13,057 | 241 | 122 | 54.178423 | 0.784842 | 0.046259 | 0 | 0.543478 | 0 | 0 | 0.020741 | 0.008682 | 0 | 0 | 0 | 0 | 0.179348 | 1 | 0.081522 | false | 0 | 0.043478 | 0 | 0.130435 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
4a86c3cbddf8de38953b094836d48941f905d73b | 48 | py | Python | hotair/__init__.py | serviper/hota | b132d94af7217ce90636bf1af4f207dc01d00116 | [
"MIT"
] | null | null | null | hotair/__init__.py | serviper/hota | b132d94af7217ce90636bf1af4f207dc01d00116 | [
"MIT"
] | null | null | null | hotair/__init__.py | serviper/hota | b132d94af7217ce90636bf1af4f207dc01d00116 | [
"MIT"
] | null | null | null | from .template import *
from .websocket import * | 24 | 24 | 0.770833 | 6 | 48 | 6.166667 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.145833 | 48 | 2 | 24 | 24 | 0.902439 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4ac5e60d8faf58b5e993e22852ca5d786b686eac | 166 | py | Python | xbee/thread/__init__.py | PowerFlex/python-xbee-intercept | 0c07f3a5f16f479ad7c925cd31638598030cf5a7 | [
"MIT"
] | 65 | 2015-12-06T02:38:28.000Z | 2017-09-05T16:46:07.000Z | xbee/thread/__init__.py | PowerFlex/python-xbee-intercept | 0c07f3a5f16f479ad7c925cd31638598030cf5a7 | [
"MIT"
] | 44 | 2015-10-23T15:33:54.000Z | 2017-09-01T06:39:50.000Z | xbee/thread/__init__.py | PowerFlex/python-xbee-intercept | 0c07f3a5f16f479ad7c925cd31638598030cf5a7 | [
"MIT"
] | 43 | 2015-12-15T02:52:21.000Z | 2017-06-24T17:14:53.000Z | """
XBee package initalization file
info@n.io
"""
from xbee.thread.ieee import XBee
from xbee.thread.zigbee import ZigBee
from xbee.thread.digimesh import DigiMesh
| 16.6 | 41 | 0.789157 | 25 | 166 | 5.24 | 0.52 | 0.183206 | 0.320611 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.126506 | 166 | 9 | 42 | 18.444444 | 0.903448 | 0.253012 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4ac65b0aeab78c93d4f39402df78f739a62735eb | 42 | py | Python | pyexphys/equations/cardiovascular/models/__init__.py | dpfens/PyExPhys | 08483993b81e8c6c8ab76219b245508c5fe82df0 | [
"MIT"
] | 2 | 2020-04-15T21:57:10.000Z | 2020-06-22T23:18:28.000Z | pyexphys/equations/cardiovascular/models/__init__.py | dpfens/PyFit | 08483993b81e8c6c8ab76219b245508c5fe82df0 | [
"MIT"
] | null | null | null | pyexphys/equations/cardiovascular/models/__init__.py | dpfens/PyFit | 08483993b81e8c6c8ab76219b245508c5fe82df0 | [
"MIT"
] | 1 | 2020-04-15T22:00:13.000Z | 2020-04-15T22:00:13.000Z | import cameron
import purdy
import riegel
| 10.5 | 14 | 0.857143 | 6 | 42 | 6 | 0.666667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 42 | 3 | 15 | 14 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4383d5521c4874dcffe956e8ed4cb1e741d13e00 | 25,640 | py | Python | tests/test_api_changeset.py | Pauliceia/ws | 8966cfd80299f22468afe9a2a1156740bf237270 | [
"MIT"
] | null | null | null | tests/test_api_changeset.py | Pauliceia/ws | 8966cfd80299f22468afe9a2a1156740bf237270 | [
"MIT"
] | 2 | 2021-02-08T20:26:34.000Z | 2021-04-30T20:43:28.000Z | tests/test_api_changeset.py | Pauliceia/ws | 8966cfd80299f22468afe9a2a1156740bf237270 | [
"MIT"
] | 1 | 2021-09-08T18:10:58.000Z | 2021-09-08T18:10:58.000Z | #!/usr/bin/env python
# -*- coding: utf-8 -*-
from util.tester import RequestTester
class TestAPIChangeset(RequestTester):
def setUp(self):
self.set_urn('/api/changeset')
# changeset - get
def test__get_api_changeset__return_all_changesets(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-01-05 00:00:00', 'user_id_creator': 1001, 'changeset_id': 1001,
'closed_at': '2017-01-05 00:00:00', 'layer_id': 1001,
'description': 'Creating layer_1001'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-03-05 00:00:00', 'user_id_creator': 1004, 'changeset_id': 1002,
'closed_at': '2017-03-05 00:00:00', 'layer_id': 1002,
'description': 'Creating layer_1002'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-04-12 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1003,
'closed_at': '2017-04-12 00:00:00', 'layer_id': 1003,
'description': 'Creating layer_1003'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-06-28 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1004,
'closed_at': '2017-06-28 00:00:00', 'layer_id': 1004,
'description': 'Creating layer_1004'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-08-05 00:00:00', 'user_id_creator': 1007, 'changeset_id': 1005,
'closed_at': '2017-08-05 00:00:00', 'layer_id': 1005,
'description': 'Creating layer_1005'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-09-04 00:00:00', 'user_id_creator': 1007, 'changeset_id': 1006,
'closed_at': '2017-09-04 00:00:00', 'layer_id': 1006,
'description': 'Creating layer_1006'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-01-08 00:00:00', 'user_id_creator': 1001, 'changeset_id': 1011,
'closed_at': None, 'layer_id': 1001, 'description': 'An open changeset'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-04-13 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1013,
'closed_at': None, 'layer_id': 1003, 'description': 'Creating an open changeset'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-01-08 00:00:00', 'user_id_creator': 1004, 'changeset_id': 1014,
'closed_at': None, 'layer_id': 1002, 'description': 'An open changeset'},
'type': 'Changeset'
}
],
'type': 'FeatureCollection'
}
self.get(expected)
def test__get_api_changeset__return_changeset_by_changeset_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-04-12 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1003,
'closed_at': '2017-04-12 00:00:00', 'layer_id': 1003,
'description': 'Creating layer_1003'},
'type': 'Changeset'
}
],
'type': 'FeatureCollection'
}
self.get(expected, changeset_id="1003")
def test__get_api_changeset__return_changeset_by_layer_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-06-28 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1004,
'closed_at': '2017-06-28 00:00:00', 'layer_id': 1004,
'description': 'Creating layer_1004'},
'type': 'Changeset'
},
],
'type': 'FeatureCollection'
}
self.get(expected, layer_id="1004")
def test__get_api_changeset__return_changeset_by_user_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-04-12 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1003,
'closed_at': '2017-04-12 00:00:00', 'layer_id': 1003,
'description': 'Creating layer_1003'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-06-28 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1004,
'closed_at': '2017-06-28 00:00:00', 'layer_id': 1004,
'description': 'Creating layer_1004'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-04-13 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1013,
'closed_at': None, 'layer_id': 1003, 'description': 'Creating an open changeset'},
'type': 'Changeset'
}
],
'type': 'FeatureCollection'
}
self.get(expected, user_id_creator="1005")
def test__get_api_changeset__return_all_open_changesets(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-01-08 00:00:00', 'user_id_creator': 1001, 'changeset_id': 1011,
'closed_at': None, 'layer_id': 1001, 'description': 'An open changeset'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-04-13 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1013,
'closed_at': None, 'layer_id': 1003, 'description': 'Creating an open changeset'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-01-08 00:00:00', 'user_id_creator': 1004, 'changeset_id': 1014,
'closed_at': None, 'layer_id': 1002, 'description': 'An open changeset'},
'type': 'Changeset'
}
],
'type': 'FeatureCollection'
}
self.get(expected, open=True)
def test__get_api_changeset__return_all_closed_changesets(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-01-05 00:00:00', 'user_id_creator': 1001, 'changeset_id': 1001,
'closed_at': '2017-01-05 00:00:00', 'layer_id': 1001,
'description': 'Creating layer_1001'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-03-05 00:00:00', 'user_id_creator': 1004, 'changeset_id': 1002,
'closed_at': '2017-03-05 00:00:00', 'layer_id': 1002,
'description': 'Creating layer_1002'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-04-12 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1003,
'closed_at': '2017-04-12 00:00:00', 'layer_id': 1003,
'description': 'Creating layer_1003'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-06-28 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1004,
'closed_at': '2017-06-28 00:00:00', 'layer_id': 1004,
'description': 'Creating layer_1004'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-08-05 00:00:00', 'user_id_creator': 1007, 'changeset_id': 1005,
'closed_at': '2017-08-05 00:00:00', 'layer_id': 1005,
'description': 'Creating layer_1005'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-09-04 00:00:00', 'user_id_creator': 1007, 'changeset_id': 1006,
'closed_at': '2017-09-04 00:00:00', 'layer_id': 1006,
'description': 'Creating layer_1006'},
'type': 'Changeset'
},
],
'type': 'FeatureCollection'
}
self.get(expected, closed=True)
def test__get_api_changeset__return_all_open_changesets_by_layer_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-04-13 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1013,
'closed_at': None, 'layer_id': 1003, 'description': 'Creating an open changeset'},
'type': 'Changeset'
}
],
'type': 'FeatureCollection'
}
self.get(expected, open=True, layer_id="1003")
def test__get_api_changeset__return_all_closed_changesets_by_layer_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-06-28 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1004,
'closed_at': '2017-06-28 00:00:00', 'layer_id': 1004,
'description': 'Creating layer_1004'},
'type': 'Changeset'
},
],
'type': 'FeatureCollection'
}
self.get(expected, closed=True, layer_id="1004")
def test__get_api_changeset__return_all_open_changesets_by_user_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-01-08 00:00:00', 'user_id_creator': 1001, 'changeset_id': 1011,
'closed_at': None, 'layer_id': 1001, 'description': 'An open changeset'},
'type': 'Changeset'
},
],
'type': 'FeatureCollection'
}
self.get(expected, open=True, user_id_creator="1001")
def test__get_api_changeset__return_all_closed_changesets_by_user_id(self):
expected = {
'features': [
{
'properties': {'created_at': '2017-04-12 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1003,
'closed_at': '2017-04-12 00:00:00', 'layer_id': 1003,
'description': 'Creating layer_1003'},
'type': 'Changeset'
},
{
'properties': {'created_at': '2017-06-28 00:00:00', 'user_id_creator': 1005, 'changeset_id': 1004,
'closed_at': '2017-06-28 00:00:00', 'layer_id': 1004,
'description': 'Creating layer_1004'},
'type': 'Changeset'
},
],
'type': 'FeatureCollection'
}
self.get(expected, closed=True, user_id_creator="1005")
def test__get_api_changeset__return_zero_resources(self):
expected = {'features': [], 'type': 'FeatureCollection'}
self.get(expected, changeset_id="999")
self.get(expected, changeset_id="998")
# changeset - create, close and delete
def test__post_delete_api_changeset_create_and_close__delete_with_admin(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Create the changeset
##################################################
changeset = {
'properties': {'changeset_id': -1, 'layer_id': 1003},
'type': 'Changeset'
}
changeset_id = self.post_create(changeset)
changeset["properties"]["changeset_id"] = changeset_id
##################################################
# Close the changeset
##################################################
self.set_urn('/api/changeset/close')
close_changeset = {
'properties': {'changeset_id': changeset_id, 'description': 'Creating layer_1003'},
'type': 'ChangesetClose'
}
self.post(close_changeset)
self.auth_logout()
##################################################
# Delete the changeset
##################################################
# login with an admin user to delete the changeset
self.auth_login("rodrigo@admin.com", "rodrigo")
self.set_urn('/api/changeset')
self.delete(changeset_id=changeset_id)
##################################################
# Logout
##################################################
self.auth_logout()
def test__post_delete_api_changeset_create_close_and_delete__with_admin(self):
##################################################
# Login
##################################################
self.auth_login("rodrigo@admin.com", "rodrigo")
##################################################
# Create the changeset
##################################################
changeset = {
'properties': {'changeset_id': -1, 'layer_id': 1003},
'type': 'Changeset'
}
changeset_id = self.post_create(changeset)
changeset["properties"]["changeset_id"] = changeset_id
##################################################
# Close the changeset
##################################################
self.set_urn('/api/changeset/close')
close_changeset = {
'properties': {'changeset_id': changeset_id, 'description': 'Creating layer_1003'},
'type': 'ChangesetClose'
}
self.post(close_changeset)
##################################################
# Delete the changeset
##################################################
self.set_urn('/api/changeset')
self.delete(changeset_id=changeset_id)
##################################################
# Logout
##################################################
self.auth_logout()
class TestAPIChangesetErrors(RequestTester):
def setUp(self):
self.set_urn('/api/changeset')
# changeset errors - get
def test__get_api_changeset__400_bad_request(self):
changesets_ids = ["abc", 0, -1, "-1", "0"]
for changeset_id in changesets_ids:
self.get(
status_code=400, text_message="Invalid parameter.",
changeset_id=changeset_id
)
# changeset errors - create
def test__post_api_changeset_create__400_bad_request(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Try to create a changeset without an attribute
##################################################
resource = {
'properties': {'description': 'Creating layer_1003'},
'type': 'Changeset'
}
self.post_create(
resource,
status_code=400,
text_message="Some attribute in the JSON is missing. Look at the documentation! (error: 'layer_id' is missing)"
)
##################################################
# Logout
##################################################
self.auth_logout()
def test__post_api_changeset_create__401_unauthorized(self):
##################################################
# Try to create a changeset without a logged user
##################################################
resource = {
'properties': {'changeset_id': -1, 'layer_id': 1003, 'description': 'Creating layer_1003'},
'type': 'Changeset'
}
self.post_create(
resource,
status_code=401,
text_message="A valid `Authorization` header is necessary!"
)
# changeset errors - delete
def test__delete_api_changeset__400_bad_request(self):
##################################################
# Login
##################################################
self.auth_login("rodrigo@admin.com", "rodrigo")
##################################################
# Try to delete changesets
##################################################
changesets_ids = ["abc", 0, -1, "-1", "0"]
for changeset_id in changesets_ids:
self.delete(
status_code=400,
text_message="Invalid parameter.",
changeset_id=changeset_id
)
##################################################
# Logout
##################################################
self.auth_logout()
def test__delete_api_changeset__401_unauthorized(self):
##################################################
# Try to delete changesets
##################################################
changesets_ids = ["abc", 0, -1, "-1", "0", "1001"]
for changeset_id in changesets_ids:
self.delete(
status_code=401,
text_message="A valid `Authorization` header is necessary!",
changeset_id=changeset_id
)
def test__delete_api_changeset__403_forbidden(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Try to delete changesets
##################################################
changesets_ids = ["abc", 0, -1, "-1", "0", "1001"]
for changeset_id in changesets_ids:
self.delete(
status_code=403,
text_message="The administrator is who can use this resource.",
changeset_id=changeset_id
)
##################################################
# Logout
##################################################
self.auth_logout()
def test__delete_api_changeset__404_not_found(self):
##################################################
# Login
##################################################
self.auth_login("rodrigo@admin.com", "rodrigo")
##################################################
# Try to delete changesets
##################################################
changesets_ids = ["5000", "5001"]
for changeset_id in changesets_ids:
self.delete(
status_code=404,
text_message="Not found any resource.",
changeset_id=changeset_id
)
##################################################
# Logout
##################################################
self.auth_logout()
class TestAPIChangesetCloseErrors(RequestTester):
def setUp(self):
self.set_urn('/api/changeset/close')
# changeset errors - close
def test__post_api_changeset_close__400_bad_request(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Try to close changesets
##################################################
invalid_changesets_ids = ["abc", 0, -1, "-1", "0"]
for invalid_changeset_id in invalid_changesets_ids:
close_changeset = {
'properties': {'changeset_id': invalid_changeset_id, 'description': 'Creating layer_1003'},
'type': 'ChangesetClose'
}
self.post(close_changeset, status_code=400, text_message="Invalid parameter.")
##################################################
# Logout
##################################################
self.auth_logout()
def test__post_api_changeset_close__401_unauthorized(self):
##################################################
# Try to close changesets
##################################################
invalid_changesets_ids = ["abc", 0, -1, "-1", "0", "1001", 1001]
for invalid_changeset_id in invalid_changesets_ids:
close_changeset = {
'properties': {'changeset_id': invalid_changeset_id, 'description': 'Creating layer_1003'},
'type': 'ChangesetClose'
}
self.post(close_changeset,
status_code=401, text_message="A valid `Authorization` header is necessary!")
def test__post_api_changeset_close__404_not_found(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Try to close changesets
##################################################
invalid_changesets_ids = [
{
"changeset_id": "5000",
"error_message": "Not found the changeset `5000`."
},
{
"changeset_id": "5001",
"error_message": "Not found the changeset `5001`."
}
]
for invalid_changeset in invalid_changesets_ids:
close_changeset = {
'properties': {
'changeset_id': invalid_changeset["changeset_id"],
'description': 'Creating layer_1003'
},
'type': 'ChangesetClose'
}
self.post(close_changeset,
status_code=404, text_message=invalid_changeset["error_message"])
##################################################
# Logout
##################################################
self.auth_logout()
def test__post_api_changeset_close__409_conflict__changeset_has_already_been_closed(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Try to close a changeset
##################################################
close_changeset = {
'properties': {'changeset_id': 1002, 'description': 'Creating layer_1003'},
'type': 'ChangesetClose'
}
self.post(close_changeset,
status_code=409,
text_message="Changeset `1002` has already been closed at `2017-03-05 00:00:00`.")
##################################################
# Logout
##################################################
self.auth_logout()
def test__post_api_changeset_close__409_conflict__user_didnt_create_the_changeset(self):
##################################################
# Login
##################################################
self.auth_login("miguel@admin.com", "miguel")
##################################################
# Try to close a changeset
##################################################
close_changeset = {
'properties': {'changeset_id': 1011, 'description': 'Creating layer_1003'},
'type': 'ChangesetClose'
}
self.post(close_changeset,
status_code=409,
text_message="The user `1003` didn't create the changeset `1011`.")
##################################################
# Logout
##################################################
self.auth_logout()
# Putting the unittest main() function here is not necessary,
# because this file will be called by run_tests.py
| 41.155698 | 123 | 0.422621 | 2,094 | 25,640 | 4.885864 | 0.075454 | 0.037533 | 0.02815 | 0.062946 | 0.914182 | 0.894243 | 0.868048 | 0.840192 | 0.821816 | 0.78223 | 0 | 0.077535 | 0.332995 | 25,640 | 622 | 124 | 41.221865 | 0.520699 | 0.036037 | 0 | 0.60049 | 0 | 0.004902 | 0.288153 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.068627 | false | 0 | 0.002451 | 0 | 0.078431 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
43b1a279f1966965073017646f5df03f994e920a | 18 | py | Python | web/__init__.py | carrasquel/SmartHomeApp | e5fb8eda0ddd103ba5366ed892bdce58ab768352 | [
"MIT"
] | null | null | null | web/__init__.py | carrasquel/SmartHomeApp | e5fb8eda0ddd103ba5366ed892bdce58ab768352 | [
"MIT"
] | null | null | null | web/__init__.py | carrasquel/SmartHomeApp | e5fb8eda0ddd103ba5366ed892bdce58ab768352 | [
"MIT"
] | null | null | null | from .hmi import * | 18 | 18 | 0.722222 | 3 | 18 | 4.333333 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.166667 | 18 | 1 | 18 | 18 | 0.866667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
78e5f20394062bf16c502fbaf692a02d49672f39 | 189 | py | Python | __init__.py | stefangolas/olaf | 71eedac8f22cbf3563be795d2a3b65ea55c41bd8 | [
"MIT"
] | null | null | null | __init__.py | stefangolas/olaf | 71eedac8f22cbf3563be795d2a3b65ea55c41bd8 | [
"MIT"
] | null | null | null | __init__.py | stefangolas/olaf | 71eedac8f22cbf3563be795d2a3b65ea55c41bd8 | [
"MIT"
] | null | null | null | from .AgrowPumps.AgPumps import *
from .Celigo.Celigo import *
from .ClarioStar.platereader.platereader.clariostar import *
from .Cytomat.Cytomat import *
from .PyShaker.shaker import * | 37.8 | 61 | 0.78836 | 22 | 189 | 6.772727 | 0.454545 | 0.268456 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.121693 | 189 | 5 | 62 | 37.8 | 0.89759 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
601ebb34cf1e89ec658a0d6769b2a66d628ffb5f | 36 | py | Python | malaya_speech/train/model/rnn/__init__.py | ishine/malaya-speech | fd34afc7107af1656dff4b3201fa51dda54fde18 | [
"MIT"
] | 111 | 2020-08-31T04:58:54.000Z | 2022-03-29T15:44:18.000Z | malaya_speech/train/model/rnn/__init__.py | ishine/malaya-speech | fd34afc7107af1656dff4b3201fa51dda54fde18 | [
"MIT"
] | 14 | 2020-12-16T07:27:22.000Z | 2022-03-15T17:39:01.000Z | malaya_speech/train/model/rnn/__init__.py | ishine/malaya-speech | fd34afc7107af1656dff4b3201fa51dda54fde18 | [
"MIT"
] | 29 | 2021-02-09T08:57:15.000Z | 2022-03-12T14:09:19.000Z | from .model import ResLayerNormLSTM
| 18 | 35 | 0.861111 | 4 | 36 | 7.75 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.111111 | 36 | 1 | 36 | 36 | 0.96875 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
6039394497287124e0dc14b20b5125e2b42f71ee | 5,584 | py | Python | metaopt/tests/integration/core/call/call.py | cigroup-ol/metaopt | 6dfd5105d3c6eaf00f96670175cae16021069514 | [
"BSD-3-Clause"
] | 8 | 2015-02-02T21:42:23.000Z | 2019-06-30T18:12:43.000Z | metaopt/tests/integration/core/call/call.py | cigroup-ol/metaopt | 6dfd5105d3c6eaf00f96670175cae16021069514 | [
"BSD-3-Clause"
] | 4 | 2015-09-24T14:12:38.000Z | 2021-12-08T22:42:52.000Z | metaopt/tests/integration/core/call/call.py | cigroup-ol/metaopt | 6dfd5105d3c6eaf00f96670175cae16021069514 | [
"BSD-3-Clause"
] | 6 | 2015-02-27T12:35:33.000Z | 2020-10-15T21:04:02.000Z | # -*- coding: utf-8 -*-
"""
Tests for the call module.
"""
# Future
from __future__ import absolute_import, division, print_function, \
unicode_literals, with_statement
# Third Party
import nose
from mock import Mock
from nose.tools import raises
# First Party
from metaopt.core.arg.arg import Arg
from metaopt.core.call.call import call
from metaopt.core.call.util.exception import CallNotPossibleError
from metaopt.core.paramspec.paramspec import ParamSpec
from metaopt.core.returnspec.returnspec import ReturnSpec
from metaopt.core.returnspec.util.wrapper import ReturnValuesWrapper
class TestCall(object):
def test_call_func_with_extra_kwargs(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.extra_kwargs = {"b": 1}
param_a = param_spec.params["a"]
arg_a = Arg(param_a, 0)
f_mock = Mock()
def f(a, b): # That's a hack since getargspec doesn't work with mocks
f_mock(a, b)
call(f, [arg_a], param_spec)
f_mock.assert_called_with(arg_a.value, 1)
def test_call_func_with_kwargs_and_extra_kwargs(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.extra_kwargs = {"b": 1}
param_a = param_spec.params["a"]
arg_a = Arg(param_a, 0)
f_mock = Mock()
def f(**kwargs): # That's a hack since getargspec doesn't work with mocks
f_mock(**kwargs)
call(f, [arg_a], param_spec)
f_mock.assert_called_with(a=arg_a.value, b=1)
def test_call_func_with_return_spec(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
return_spec = ReturnSpec()
return_spec.maximize("z")
def f(a):
return a
result = call(f, [Arg(param_spec.params["a"], 1)], param_spec, return_spec)
assert isinstance(result, ReturnValuesWrapper)
def test_call_func_with_return_spec_same_str(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
return_spec = ReturnSpec()
return_spec.maximize("z")
def f(a):
return a
result = call(f, [Arg(param_spec.params["a"], 1)], param_spec, return_spec)
assert str(result) == str(1)
def test_call_func_without_return_spec(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
def f(a):
return a
result = call(f, [Arg(param_spec.params["a"], 1)], param_spec)
assert isinstance(result, ReturnValuesWrapper)
def test_call_func_with_args_works(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.int("b", interval=(1, 2))
param_a = param_spec.params["a"]
param_b = param_spec.params["b"]
arg_a = Arg(param_a, 0)
arg_b = Arg(param_b, 1)
f_mock = Mock()
def f(a, b): # That's a hack since getargspec doesn't work with mocks
f_mock(a, b)
call(f, [arg_a, arg_b], param_spec)
f_mock.assert_called_with(arg_a.value, arg_b.value)
def test_call_func_with_single_arg_works(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_a = param_spec.params["a"]
arg_a = Arg(param_a, 0)
f_mock = Mock()
def f(a): # That's a hack since getargspec doesn't work with mocks
f_mock(a)
call(f, [arg_a], param_spec)
f_mock.assert_called_with(arg_a.value)
def test_call_func_with_kwargs_works(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.int("b", interval=(1, 2))
param_a = param_spec.params["a"]
param_b = param_spec.params["b"]
arg_a = Arg(param_a, 0)
arg_b = Arg(param_b, 1)
f_mock = Mock()
def f(**kwargs):
f_mock(**kwargs)
call(f, [arg_a, arg_b], param_spec)
f_mock.assert_called_with(a=arg_a.value, b=arg_b.value)
def test_call_func_with_args_returns_result(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.int("b", interval=(1, 2))
param_a = param_spec.params["a"]
param_b = param_spec.params["b"]
arg_a = Arg(param_a, 0)
arg_b = Arg(param_b, 1)
def f(a, b): # That's a hack since getargspec doesn't work with mocks
return a + b
assert arg_a.value + arg_b.value == call(f, [arg_a, arg_b], param_spec).raw_values
@raises(CallNotPossibleError)
def test_call_func_with_vargs_raises_error(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.int("b", interval=(1, 2))
param_a = param_spec.params["a"]
param_b = param_spec.params["b"]
arg_a = Arg(param_a, 0)
arg_b = Arg(param_b, 1)
def f(*vargs):
pass
call(f, [arg_a, arg_b], param_spec)
@raises(CallNotPossibleError)
def test_call_func_with_incorrect_number_of_args_raises_error(self):
param_spec = ParamSpec()
param_spec.int("a", interval=(1, 2))
param_spec.int("b", interval=(1, 2))
param_a = param_spec.params["a"]
param_b = param_spec.params["b"]
arg_a = Arg(param_a, 0)
arg_b = Arg(param_b, 1)
def f(a, b, c):
pass
call(f, [arg_a, arg_b], param_spec)
if __name__ == '__main__':
nose.runmodule()
| 26.975845 | 90 | 0.609957 | 823 | 5,584 | 3.855407 | 0.114216 | 0.15884 | 0.060511 | 0.061456 | 0.805232 | 0.794201 | 0.765837 | 0.722975 | 0.698393 | 0.682004 | 0 | 0.013196 | 0.267192 | 5,584 | 206 | 91 | 27.106796 | 0.762219 | 0.063575 | 0 | 0.719697 | 0 | 0 | 0.00844 | 0 | 0 | 0 | 0 | 0 | 0.068182 | 1 | 0.166667 | false | 0.015152 | 0.075758 | 0.030303 | 0.280303 | 0.007576 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
603aba997434bee299919e6eb2db4e695a5fad54 | 88 | py | Python | tests/data/__init__.py | nikitacs16/COMET | 27d6dd38b674a75cb9b84686b35fd75203b0a66d | [
"Apache-2.0"
] | 138 | 2020-09-22T14:59:52.000Z | 2022-03-30T18:43:41.000Z | tests/data/__init__.py | Unbabel/COMET-Telescope | 3aad7dd76a228a8bd17daa317b86715f0b058f5b | [
"Apache-2.0"
] | 58 | 2020-11-19T11:41:21.000Z | 2022-03-31T17:54:46.000Z | tests/data/__init__.py | Unbabel/COMET-Telescope | 3aad7dd76a228a8bd17daa317b86715f0b058f5b | [
"Apache-2.0"
] | 24 | 2020-09-28T02:35:55.000Z | 2022-03-14T12:51:40.000Z | import os
DATA_PATH = os.path.abspath(__file__)
DATA_PATH = os.path.dirname(DATA_PATH)
| 17.6 | 38 | 0.784091 | 15 | 88 | 4.133333 | 0.466667 | 0.387097 | 0.322581 | 0.451613 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.102273 | 88 | 4 | 39 | 22 | 0.78481 | 0 | 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 | 1 | 1 | 1 | 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 | 6 |
606ac6f13e1c8a1f61b6c784269901ce6404ec48 | 575 | gyp | Python | binding.gyp | Azq2/node-html5-dom | e2df36fb7ea7bdfdbbf8060749e784b1e5a7c8ea | [
"MIT"
] | null | null | null | binding.gyp | Azq2/node-html5-dom | e2df36fb7ea7bdfdbbf8060749e784b1e5a7c8ea | [
"MIT"
] | null | null | null | binding.gyp | Azq2/node-html5-dom | e2df36fb7ea7bdfdbbf8060749e784b1e5a7c8ea | [
"MIT"
] | null | null | null | {
"targets": [{
"target_name": "html5-dom",
"sources": [
"src/addon.cpp",
"src/Parser.cpp",
"src/Tree.cpp",
"src/Utils.cpp",
"src/modest/modest_myurl.c",
"src/modest/modest_mycss.c",
"src/modest/modest_config.h",
"src/modest/modest_myencoding.c",
"src/modest/modest_mycore.c",
"src/modest/modest_myfont.c",
"src/modest/modest_modest.c",
"src/modest/modest_myhtml.c",
"src/modest/modest_myport.c"
],
"include_dirs": [
"<!(node -e \"require('nan')\")",
"third_party/modest/include",
"."
]
}]
}
| 21.296296 | 37 | 0.586087 | 73 | 575 | 4.452055 | 0.424658 | 0.369231 | 0.415385 | 0.344615 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.002169 | 0.198261 | 575 | 26 | 38 | 22.115385 | 0.70282 | 0 | 0 | 0 | 0 | 0 | 0.655652 | 0.455652 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 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 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
6076242164d32e28fc759a2b8a40407f20a2c594 | 82,214 | py | Python | pynetdicom/dimse_primitives.py | hkethi002/pynetdicom | d945d13ac22f754a4fc017ecb437bca6d3276589 | [
"MIT"
] | null | null | null | pynetdicom/dimse_primitives.py | hkethi002/pynetdicom | d945d13ac22f754a4fc017ecb437bca6d3276589 | [
"MIT"
] | null | null | null | pynetdicom/dimse_primitives.py | hkethi002/pynetdicom | d945d13ac22f754a4fc017ecb437bca6d3276589 | [
"MIT"
] | null | null | null | """
Define the DIMSE-C and DIMSE-N service parameter primitives.
Notes:
* The class member names must match their corresponding DICOM element keyword
in order for the DIMSE messages/primitives to be created correctly.
"""
from collections.abc import MutableSequence
from io import BytesIO
import logging
from pathlib import Path
from typing import Optional, List, Tuple, Union, TYPE_CHECKING
import warnings
from pydicom.tag import Tag, BaseTag
from pydicom.uid import UID
from pynetdicom._globals import OptionalUIDType
from pynetdicom.utils import set_ae, decode_bytes, set_uid
if TYPE_CHECKING: # pragma: no cover
from typing import Protocol # Python 3.8+
class NTF(Protocol):
# Protocol for a NamedTemporaryFile
name: str
def write(self, data: bytes) -> bytes:
...
def close(self) -> None:
...
LOGGER = logging.getLogger("pynetdicom.dimse_primitives")
DimseServiceType = Union[
"C_ECHO",
"C_FIND",
"C_GET",
"C_MOVE",
"C_STORE",
"N_ACTION",
"N_CREATE",
"N_DELETE",
"N_EVENT_REPORT",
"N_GET",
"N_SET",
]
DimsePrimitiveType = Union["C_CANCEL", DimseServiceType]
# pylint: disable=invalid-name
# pylint: disable=attribute-defined-outside-init
# pylint: disable=too-many-instance-attributes
# pylint: disable=anomalous-backslash-in-string
class DIMSEPrimitive:
"""Base class for the DIMSE primitives."""
STATUS_OPTIONAL_KEYWORDS: Tuple[str, ...] = ()
REQUEST_KEYWORDS: Tuple[str, ...] = ()
RESPONSE_KEYWORDS: Tuple[str, ...] = ("MessageIDBeingRespondedTo", "Status")
_action_type_id: Optional[int] = None
_affected_sop_class_uid: Optional[UID] = None
_affected_sop_instance_uid: Optional[UID] = None
_attribute_identifier_list: Optional[List[BaseTag]] = None
_dataset: Optional[BytesIO] = None
_event_type_id: Optional[int] = None
_message_id: Optional[int] = None
_message_id_being_responded_to: Optional[int] = None
_move_destination: Optional[str] = None
_move_originator_application_entity_title: Optional[str] = None
_move_originator_message_id: Optional[int] = None
_number_of_completed_suboperations: Optional[int] = None
_number_of_failed_suboperations: Optional[int] = None
_number_of_remaining_suboperations: Optional[int] = None
_number_of_warning_suboperations: Optional[int] = None
_priority: int = 0x02
_requested_sop_class_uid: Optional[UID] = None
_requested_sop_instance_uid: Optional[UID] = None
_status: Optional[int] = None
_context_id: Optional[int] = None
# If we are sending a C-STORE service primitive:
# If None then the dataset is encoded as BytesIO
# If not None then the dataset is stored at (path, offset)
# If we are receiving a C-STORE service primitive:
# If None then the dataset is encoded as BytesIO
# If not None then the dataset is stored at _dataset_path
# self._dataset_path = None
# If we are sending a C-STORE service primitive:
# Always None
# If we are receiving a C-STORE service primitive:
# If None then the dataset is encoded as BytesIO
# If not None then _dataset_file backs the dataset stored
# at _dataset_path
# self._dataset_file = None
_dataset_path: Optional[Union[Path, Tuple[Path, int]]] = None
_dataset_file: Optional["NTF"] = None
@property
def AffectedSOPClassUID(self) -> Optional[UID]:
"""Get or set the *Affected SOP Class UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
return self._affected_sop_class_uid
@AffectedSOPClassUID.setter
def AffectedSOPClassUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Class UID*."""
self._affected_sop_class_uid = set_uid(value, "Affected SOP Class UID") or None
@property
def _AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Affected SOP Instance UID* as :class:`~pydicom.uid.UID`."""
return self._affected_sop_instance_uid
@_AffectedSOPInstanceUID.setter
def _AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value for the Affected SOP Class UID
"""
self._affected_sop_instance_uid = (
set_uid(value, "Affected SOP Instance UID") or None
)
@property
def _dataset_variant(self) -> Optional[BytesIO]:
"""Return the Dataset-like parameter value.
Used for EventInformation, EventReply, AttributeList,
ActionInformation, ActionReply, DataSet, Identifier and
ModificationList dataset-like parameter values.
Returns
-------
BytesIO or None
"""
return self._dataset
@_dataset_variant.setter
def _dataset_variant(self, value: Tuple[Optional[BytesIO], str]) -> None:
"""Set the Dataset-like parameter.
Used for EventInformation, EventReply, AttributeList,
ActionInformation, ActionReply, DataSet, Identifier and
ModificationList dataset-like parameter values.
Parameters
----------
value : tuple
The (dataset, variant name) to set, where dataset is either None
or BytesIO and variant name is str.
"""
if value[0] is None:
self._dataset = value[0]
elif isinstance(value[0], BytesIO):
self._dataset = value[0]
else:
raise TypeError(f"'{value[1]}' parameter must be a BytesIO object")
@property
def is_valid_request(self) -> bool:
"""Return ``True`` if the request is valid, ``False`` otherwise."""
for keyword in self.REQUEST_KEYWORDS:
if getattr(self, keyword) is None:
return False
return True
@property
def is_valid_response(self) -> bool:
"""Return ``True`` if the response is valid, ``False`` otherwise."""
for keyword in self.RESPONSE_KEYWORDS:
if getattr(self, keyword) is None:
return False
return True
@property
def MessageID(self) -> Optional[int]:
"""Get or set the *Message ID* value as :class:`int`.
Parameters
----------
int
The value to use for the *Message ID* parameter.
"""
return self._message_id
@MessageID.setter
def MessageID(self, value: Optional[int]) -> None:
"""Set the *Message ID*."""
if isinstance(value, int):
if 0 <= value < 2**16:
self._message_id = value
else:
raise ValueError("Message ID must be between 0 and 65535, inclusive")
elif value is None:
self._message_id = value
else:
raise TypeError("Message ID must be an int")
@property
def MessageIDBeingRespondedTo(self) -> Optional[int]:
"""Get or set the *Message ID Being Responded To* as :class:`int`.
Parameters
----------
int
The value to use for the *Message ID Being Responded To* parameter.
"""
return self._message_id_being_responded_to
@MessageIDBeingRespondedTo.setter
def MessageIDBeingRespondedTo(self, value: Optional[int]) -> None:
"""Set the *Message ID Being Responded To*."""
if isinstance(value, int):
if 0 <= value < 2**16:
self._message_id_being_responded_to = value
else:
raise ValueError(
"Message ID Being Responded To must be "
"between 0 and 65535, inclusive"
)
elif value is None:
self._message_id_being_responded_to = value
else:
raise TypeError("Message ID Being Responded To must be an int")
@property
def _NumberOfCompletedSuboperations(self) -> Optional[int]:
"""Return the *Number of Completed Suboperations*."""
return self._number_of_completed_suboperations
@_NumberOfCompletedSuboperations.setter
def _NumberOfCompletedSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Completed Suboperations*."""
if isinstance(value, int):
if value >= 0:
self._number_of_completed_suboperations = value
else:
raise ValueError(
"Number of Completed Suboperations must be "
"greater than or equal to 0"
)
elif value is None:
self._number_of_completed_suboperations = value
else:
raise TypeError("Number of Completed Suboperations must be an int")
@property
def _NumberOfFailedSuboperations(self) -> Optional[int]:
"""Return the *Number of Failed Suboperations*."""
return self._number_of_failed_suboperations
@_NumberOfFailedSuboperations.setter
def _NumberOfFailedSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Failed Suboperations*."""
if isinstance(value, int):
if value >= 0:
self._number_of_failed_suboperations = value
else:
raise ValueError(
"Number of Failed Suboperations must be "
"greater than or equal to 0"
)
elif value is None:
self._number_of_failed_suboperations = value
else:
raise TypeError("Number of Failed Suboperations must be an int")
@property
def _NumberOfRemainingSuboperations(self) -> Optional[int]:
"""Return the *Number of Remaining Suboperations*."""
return self._number_of_remaining_suboperations
@_NumberOfRemainingSuboperations.setter
def _NumberOfRemainingSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Remaining Suboperations*."""
if isinstance(value, int):
if value >= 0:
self._number_of_remaining_suboperations = value
else:
raise ValueError(
"Number of Remaining Suboperations must be "
"greater than or equal to 0"
)
elif value is None:
self._number_of_remaining_suboperations = value
else:
raise TypeError("Number of Remaining Suboperations must be an int")
@property
def _NumberOfWarningSuboperations(self) -> Optional[int]:
"""Return the *Number of Warning Suboperations*."""
return self._number_of_warning_suboperations
@_NumberOfWarningSuboperations.setter
def _NumberOfWarningSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Warning Suboperations*."""
if isinstance(value, int):
if value >= 0:
self._number_of_warning_suboperations = value
else:
raise ValueError(
"Number of Warning Suboperations must be "
"greater than or equal to 0"
)
elif value is None:
self._number_of_warning_suboperations = value
else:
raise TypeError("Number of Warning Suboperations must be an int")
@property
def _Priority(self) -> int:
"""Return the *Priority* as :class:`int`.
Parameters
----------
int
The value to use for the *Priority* parameter. It shall be one
of the following:
* 0: Medium
* 1: High
* 2: Low (Default)
"""
return self._priority
@_Priority.setter
def _Priority(self, value: int) -> None:
"""Set the *Priority*."""
if value in [0, 1, 2]:
self._priority = value
else:
LOGGER.warning("Attempted to set Priority parameter to an invalid value")
raise ValueError("Priority must be 0, 1, or 2")
@property
def _RequestedSOPClassUID(self) -> Optional[UID]:
"""Return the *Requested SOP Class UID*."""
return self._requested_sop_class_uid
@_RequestedSOPClassUID.setter
def _RequestedSOPClassUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Class UID*.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value for the Requested SOP Class UID
"""
self._requested_sop_class_uid = (
set_uid(value, "Requested SOP Instance UID") or None
)
@property
def _RequestedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Requested SOP Instance UID*."""
return self._requested_sop_instance_uid
@_RequestedSOPInstanceUID.setter
def _RequestedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Instance UID*.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value for the Requested SOP Instance UID
"""
self._requested_sop_instance_uid = (
set_uid(value, "Requested SOP Instance UID") or None
)
@property
def Status(self) -> Optional[int]:
"""Get or set the *Status* as :class:`int`.
Parameters
----------
int
The value to use for the *Status* parameter.
"""
return self._status
@Status.setter
def Status(self, value: Optional[int]) -> None:
"""Set the *Status*"""
if isinstance(value, int) or value is None:
self._status = value
else:
raise TypeError("DIMSE primitive's 'Status' must be an int")
@property
def msg_type(self) -> str:
"""Return the DIMSE message type as :class:`str`."""
return self.__class__.__name__.replace("_", "-")
# DIMSE-C Service Primitives
class C_STORE(DIMSEPrimitive):
r"""Represents a C-STORE primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | U |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | M | U(=) |
+------------------------------------------+---------+----------+
| Priority | M | \- |
+------------------------------------------+---------+----------+
| Move Originator Application Entity Title | U | \- |
+------------------------------------------+---------+----------+
| Move Originator Message ID | U | \- |
+------------------------------------------+---------+----------+
| Data Set | M | \- |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| Offending Element | \- | C |
+------------------------------------------+---------+----------+
| Error Comment | \- | C |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class for
storage. If included in the response/confirmation, it shall be equal
to the value in the request/indication
Status : int
The error or success notification of the operation.
OffendingElement : list of int or None
An optional status related field containing a list of the
elements in which an error was detected.
ErrorComment : str or None
An optional status related field containing a text description
of the error detected. 64 characters maximum.
"""
STATUS_OPTIONAL_KEYWORDS = (
"OffendingElement",
"ErrorComment",
)
REQUEST_KEYWORDS = (
"MessageID",
"AffectedSOPClassUID",
"AffectedSOPInstanceUID",
"Priority",
"DataSet",
)
def __init__(self) -> None:
# Variable names need to match the corresponding DICOM Element keywords
# in order for the DIMSE Message classes to be built correctly.
# Changes to the variable names can be made provided the DIMSEMessage()
# class' message_to_primitive() and primitive_to_message() methods
# are also changed
# self.MessageID: Optional[int] = None
# self.MessageIDBeingRespondedTo: Optional[int] = None
# self.AffectedSOPClassUID: Optional[UID] = None
# self.AffectedSOPInstanceUID: Optional[UID] = None
# self.Priority = 0x02
self.MoveOriginatorApplicationEntityTitle: Optional[str] = None
self.MoveOriginatorMessageID: Optional[int] = None
self.DataSet: Optional[BytesIO] = None
# self.Status: Optional[int] = None
# Optional Command Set elements used with specific Status values
# For Warning statuses 0xB000, 0xB006, 0xB007
# For Failure statuses 0xCxxx, 0xA9xx,
self.OffendingElement = None
# For Warning statuses 0xB000, 0xB006, 0xB007
# For Failure statuses 0xCxxx, 0xA9xx, 0xA7xx, 0x0122, 0x0124
self.ErrorComment = None
# For Failure statuses 0x0117
# self.AffectedSOPInstanceUID
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Get or set the *Affected SOP Instance UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*."""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def DataSet(self) -> Optional[BytesIO]:
"""Get or set the *Data Set* as :class:`io.BytesIO`."""
return self._dataset_variant
@DataSet.setter
def DataSet(self, value: Optional[BytesIO]) -> None:
"""Set the *Data Set*."""
self._dataset_variant = (value, "DataSet") # type: ignore
@property
def MoveOriginatorApplicationEntityTitle(self) -> Optional[str]:
"""Get or set the *Move Originator Application Entity Title* as
:class:`str`.
Parameters
----------
value : str
The value to use for the *Move Originator AE Title* parameter.
Returns
-------
str or None
Th *Move Originator AE Title* value. May be ``None`` if the
value was invalid.
"""
return self._move_originator_application_entity_title
@MoveOriginatorApplicationEntityTitle.setter
def MoveOriginatorApplicationEntityTitle(self, value: Optional[str]) -> None:
"""Set the *Move Originator Application Entity Title*."""
if isinstance(value, bytes):
warnings.warn(
"The use of bytes with 'Move Originator AE "
"Title' is deprecated, use an ASCII str instead",
DeprecationWarning,
)
value = decode_bytes(value).strip()
try:
value = set_ae(value, "Move Originator AE Title")
except ValueError:
LOGGER.error("Invalid 'Move Originator AE Title' in C-STORE request")
value = None
self._move_originator_application_entity_title = value
@property
def MoveOriginatorMessageID(self) -> Optional[int]:
"""Get or set the *Move Originator Message ID* as :class:`int`."""
return self._move_originator_message_id
@MoveOriginatorMessageID.setter
def MoveOriginatorMessageID(self, value: Optional[int]) -> None:
"""Set the *Move Originator Message ID*.
Parameters
----------
int
The value to use for the *Move Originator Message ID* parameter.
"""
# Fix for peers sending a value consisting of nulls
if isinstance(value, int):
if 0 <= value < 2**16:
self._move_originator_message_id = value
else:
raise ValueError(
"Move Originator Message ID To must be "
"between 0 and 65535, inclusive"
)
elif value is None:
self._move_originator_message_id = value
else:
raise TypeError("Move Originator Message ID To must be an int")
@property
def Priority(self) -> int:
"""Get or set the *Priority* as :class:`int`.
Parameters
----------
int
The value to use for the *Priority* parameter. It shall be one
of the following:
* 0: Medium
* 1: High
* 2: Low (Default)
"""
return self._Priority
@Priority.setter
def Priority(self, value: int) -> None:
"""Set the *Priority*."""
self._Priority = value
class C_FIND(DIMSEPrimitive):
r"""Represents a C-FIND primitive.
+-------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+===============================+=========+==========+
| Message ID | M | U |
+-------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+-------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+-------------------------------+---------+----------+
| Priority | M | \- |
+-------------------------------+---------+----------+
| Identifier | M | C |
+-------------------------------+---------+----------+
| Status | \- | M |
+-------------------------------+---------+----------+
| Offending Element | \- | C |
+-------------------------------+---------+----------+
| Error Comment | \- | C |
+-------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which
this response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class
for storage. If included in the response/confirmation, it shall be
equal to the value in the request/indication
Status : int
The error or success notification of the operation.
OffendingElement : list of int or None
An optional status related field containing a list of the
elements in which an error was detected.
ErrorComment : str or None
An optional status related field containing a text
description of the error detected. 64 characters maximum.
"""
STATUS_OPTIONAL_KEYWORDS = (
"OffendingElement",
"ErrorComment",
)
REQUEST_KEYWORDS = ("MessageID", "AffectedSOPClassUID", "Priority", "Identifier")
def __init__(self) -> None:
# Variable names need to match the corresponding DICOM Element keywords
# in order for the DIMSE Message classes to be built correctly.
# Changes to the variable names can be made provided the DIMSEMessage()
# class' message_to_primitive() and primitive_to_message() methods
# are also changed
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.AffectedSOPClassUID = None
# self.Priority = 0x02
self.Identifier = None
# self.Status = None
# Optional Command Set elements used in with specific Status values
# For Failure statuses 0xA900, 0xCxxx
self.OffendingElement = None
# For Failure statuses 0xA900, 0xA700, 0x0122, 0xCxxx
self.ErrorComment = None
@property
def Identifier(self) -> Optional[BytesIO]:
"""Get or set the *Identifier* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Identifier* parameter.
"""
return self._dataset_variant
@Identifier.setter
def Identifier(self, value: Optional[BytesIO]) -> None:
"""Set the *Identifier*."""
self._dataset_variant = (value, "Identifier") # type: ignore
@property
def Priority(self) -> int:
"""Get or set the *Priority* as :class:`int`.
Parameters
----------
int
The value to use for the *Priority* parameter. It shall be one
of the following:
* 0: Medium
* 1: High
* 2: Low (Default)
"""
return self._Priority
@Priority.setter
def Priority(self, value: int) -> None:
"""Set the *Priority*."""
self._Priority = value
class C_GET(DIMSEPrimitive):
r"""Represents a C-GET primitive.
+-------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+===============================+=========+==========+
| Message ID | M | U |
+-------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+-------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+-------------------------------+---------+----------+
| Priority | M | \- |
+-------------------------------+---------+----------+
| Identifier | M | U |
+-------------------------------+---------+----------+
| Status | \- | M |
+-------------------------------+---------+----------+
| Number of Remaining Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Number of Completed Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Number of Failed Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Number of Warning Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Offending Element | \- | C |
+-------------------------------+---------+----------+
| Error Comment | \- | C |
+-------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which
this response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class
for storage. If included in the response/confirmation, it shall be
equal to the value in the request/indication
Status : int
The error or success notification of the operation.
OffendingElement : list of int or None
An optional status related field containing a list of the
elements in which an error was detected.
ErrorComment : str or None
An optional status related field containing a text
description of the error detected. 64 characters maximum.
"""
STATUS_OPTIONAL_KEYWORDS = (
"ErrorComment",
"OffendingElement",
"NumberOfRemainingSuboperations",
"NumberOfCompletedSuboperations",
"NumberOfFailedSuboperations",
"NumberOfWarningSuboperations",
)
REQUEST_KEYWORDS = ("MessageID", "AffectedSOPClassUID", "Priority", "Identifier")
def __init__(self) -> None:
# Variable names need to match the corresponding DICOM Element keywords
# in order for the DIMSE Message classes to be built correctly.
# Changes to the variable names can be made provided the DIMSEMessage()
# class' message_to_primitive() and primitive_to_message() methods
# are also changed
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.AffectedSOPClassUID = None
# self.Priority = 0x02
self.Identifier = None
# self.Status = None
self.NumberOfRemainingSuboperations = None
self.NumberOfCompletedSuboperations = None
self.NumberOfFailedSuboperations = None
self.NumberOfWarningSuboperations = None
# For Failure statuses 0xA701, 0xA900
self.ErrorComment = None
self.OffendingElement = None
# For 0xA702, 0xFE00, 0xB000, 0x0000
# self.NumberOfRemainingSuboperations
# self.NumberOfCompletedSuboperations
# self.NumberOfFailedSuboperations
# self.NumberOfWarningSuboperations
@property
def Identifier(self) -> Optional[BytesIO]:
"""Get or set the *Identifier* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Identifier* parameter.
"""
return self._dataset_variant
@Identifier.setter
def Identifier(self, value: Optional[BytesIO]) -> None:
"""Set the *Identifier*."""
self._dataset_variant = (value, "Identifier") # type: ignore
@property
def NumberOfCompletedSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Completed Suboperations* as :class:`int`."""
return self._NumberOfCompletedSuboperations
@NumberOfCompletedSuboperations.setter
def NumberOfCompletedSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Completed Suboperations*."""
self._NumberOfCompletedSuboperations = value
@property
def NumberOfFailedSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Failed Suboperations* as :class:`int`."""
return self._NumberOfFailedSuboperations
@NumberOfFailedSuboperations.setter
def NumberOfFailedSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Failed Suboperations*."""
self._NumberOfFailedSuboperations = value
@property
def NumberOfRemainingSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Remaining Suboperations* as :class:`int`."""
return self._NumberOfRemainingSuboperations
@NumberOfRemainingSuboperations.setter
def NumberOfRemainingSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Remaining Suboperations*."""
self._NumberOfRemainingSuboperations = value
@property
def NumberOfWarningSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Warning Suboperations* as :class:`int`."""
return self._NumberOfWarningSuboperations
@NumberOfWarningSuboperations.setter
def NumberOfWarningSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Warning Suboperations*.
Parameters
----------
int
The value to use for the *Number of Warning Suboperations*
parameter.
"""
self._NumberOfWarningSuboperations = value
@property
def Priority(self) -> int:
"""Get or set the *Priority* as :class:`int`.
Parameters
----------
int
The value to use for the *Priority* parameter. It shall be one
of the following:
* 0: Medium
* 1: High
* 2: Low (Default)
"""
return self._Priority
@Priority.setter
def Priority(self, value: int) -> None:
"""Set the *Priority*."""
self._Priority = value
class C_MOVE(DIMSEPrimitive):
r"""Represents a C-MOVE primitive.
+-------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+===============================+=========+==========+
| Message ID | M | U |
+-------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+-------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+-------------------------------+---------+----------+
| Priority | M | \- |
+-------------------------------+---------+----------+
| Move Destination | M | \- |
+-------------------------------+---------+----------+
| Identifier | M | U |
+-------------------------------+---------+----------+
| Status | \- | M |
+-------------------------------+---------+----------+
| Number of Remaining Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Number of Completed Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Number of Failed Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Number of Warning Sub-ops | \- | C |
+-------------------------------+---------+----------+
| Offending Element | \- | C |
+-------------------------------+---------+----------+
| Error Comment | \- | C |
+-------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which
this response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class
for storage. If included in the response/confirmation, it shall be
equal to the value in the request/indication
Status : int
The error or success notification of the operation.
OffendingElement : list of int or None
An optional status related field containing a list of the
elements in which an error was detected.
ErrorComment : str or None
An optional status related field containing a text
description of the error detected. 64 characters maximum.
"""
STATUS_OPTIONAL_KEYWORDS = (
"ErrorComment",
"OffendingElement",
"NumberOfRemainingSuboperations",
"NumberOfCompletedSuboperations",
"NumberOfFailedSuboperations",
"NumberOfWarningSuboperations",
)
REQUEST_KEYWORDS = (
"MessageID",
"AffectedSOPClassUID",
"Priority",
"Identifier",
"MoveDestination",
)
def __init__(self) -> None:
# Variable names need to match the corresponding DICOM Element keywords
# in order for the DIMSE Message classes to be built correctly.
# Changes to the variable names can be made provided the DIMSEMessage()
# class' message_to_primitive() and primitive_to_message() methods
# are also changed
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.AffectedSOPClassUID = None
# self.Priority = 0x02
self.MoveDestination = None
self.Identifier = None
# self.Status = None
self.NumberOfRemainingSuboperations = None
self.NumberOfCompletedSuboperations = None
self.NumberOfFailedSuboperations = None
self.NumberOfWarningSuboperations = None
# Optional Command Set elements used in with specific Status values
# For Failure statuses 0xA900
self.OffendingElement = None
# For Failure statuses 0xA801, 0xA701, 0xA702, 0x0122, 0xA900, 0xCxxx
# 0x0124
self.ErrorComment = None
@property
def Identifier(self) -> Optional[BytesIO]:
"""Get or set the *Identifier* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Identifier* parameter.
"""
return self._dataset_variant
@Identifier.setter
def Identifier(self, value: Optional[BytesIO]) -> None:
"""Set the *Identifier*."""
self._dataset_variant = (value, "Identifier") # type: ignore
@property
def MoveDestination(self) -> Optional[str]:
"""Get or set the *Move Destination* as :class:`str`.
Parameters
----------
value : str
The value to use for the *Move Destination* parameter. Cannot
be an empty string.
Returns
-------
str
The *Move Destination* value.
"""
return self._move_destination
@MoveDestination.setter
def MoveDestination(self, value: Optional[Union[str, bytes]]) -> None:
"""Set the *Move Destination*."""
if isinstance(value, bytes):
warnings.warn(
"The use of bytes with 'Move Destination' is deprecated, "
"use an ASCII str instead",
DeprecationWarning,
)
value = decode_bytes(value).strip()
self._move_destination = set_ae(value, "Move Destination", allow_empty=False)
@property
def NumberOfCompletedSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Completed Suboperations* as :class:`int`."""
return self._NumberOfCompletedSuboperations
@NumberOfCompletedSuboperations.setter
def NumberOfCompletedSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Completed Suboperations*."""
self._NumberOfCompletedSuboperations = value
@property
def NumberOfFailedSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Failed Suboperations* as :class:`int`."""
return self._NumberOfFailedSuboperations
@NumberOfFailedSuboperations.setter
def NumberOfFailedSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Failed Suboperations*."""
self._NumberOfFailedSuboperations = value
@property
def NumberOfRemainingSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Remaining Suboperations* as :class:`int`."""
return self._NumberOfRemainingSuboperations
@NumberOfRemainingSuboperations.setter
def NumberOfRemainingSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Remaining Suboperations*."""
self._NumberOfRemainingSuboperations = value
@property
def NumberOfWarningSuboperations(self) -> Optional[int]:
"""Get or set the *Number of Warning Suboperations* as :class:`int`."""
return self._NumberOfWarningSuboperations
@NumberOfWarningSuboperations.setter
def NumberOfWarningSuboperations(self, value: Optional[int]) -> None:
"""Set the *Number of Warning Suboperations*."""
self._NumberOfWarningSuboperations = value
@property
def Priority(self) -> int:
"""Get or set the *Priority* as :class:`int`.
Parameters
----------
int
The value to use for the *Priority* parameter. It shall be one
of the following:
* 0: Medium
* 1: High
* 2: Low (Default)
"""
return self._Priority
@Priority.setter
def Priority(self, value: int) -> None:
"""Set the *Priority*."""
self._Priority = value
class C_ECHO(DIMSEPrimitive):
r"""Represents a C-ECHO primitive.
+-------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+===============================+=========+==========+
| Message ID | M | U |
+-------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+-------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+-------------------------------+---------+----------+
| Status | \- | M |
+-------------------------------+---------+----------+
| Error Comment | \- | C |
+-------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int or None
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int or None
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str or None
For the request/indication this specifies the SOP Class for
storage. If included in the response/confirmation, it shall be equal
to the value in the request/indication
Status : int or None
The error or success notification of the operation.
ErrorComment : str or None
An optional status related field containing a text description
of the error detected. 64 characters maximum.
"""
STATUS_OPTIONAL_KEYWORDS = ("ErrorComment",)
REQUEST_KEYWORDS = ("MessageID", "AffectedSOPClassUID")
def __init__(self) -> None:
# Variable names need to match the corresponding DICOM Element keywords
# in order for the DIMSE Message classes to be built correctly.
# Changes to the variable names can be made provided the DIMSEMessage()
# class' message_to_primitive() and primitive_to_message() methods
# are also changed
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.AffectedSOPClassUID = None
# self.Status = None
# (Optional) for Failure status 0x0122
self.ErrorComment = None
class C_CANCEL:
"""Represents a C-CANCEL primitive.
+-------------------------------+---------+
| Parameter | Req/ind |
+===============================+=========+
| Message ID Being Responded To | M |
+-------------------------------+---------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
References
----------
* DICOM Standard, Part 7, :dcm:`Section 9.3.2.3<part07/sect_9.3.2.3.html>`
"""
def __init__(self) -> None:
"""Initialise the C_CANCEL"""
# Variable names need to match the corresponding DICOM Element keywords
# in order for the DIMSE Message classes to be built correctly.
# Changes to the variable names can be made provided the DIMSEMessage()
# class' message_to_primitive() and primitive_to_message() methods
# are also changed
self._message_id_being_responded_to: Optional[int] = None
self._context_id: Optional[int] = None
self._dataset_path: Optional[Union[Path, Tuple[Path, int]]] = None
self._dataset_file: Optional["NTF"] = None
@property
def MessageIDBeingRespondedTo(self) -> Optional[int]:
"""Get or set the *Message ID Being Responded To* as an :class:`int`.
Parameters
----------
int
The value to use for the *Message ID Being Responded To* parameter.
"""
return self._message_id_being_responded_to
@MessageIDBeingRespondedTo.setter
def MessageIDBeingRespondedTo(self, value: Optional[int]) -> None:
"""Set the *Message ID Being Responded To*."""
if isinstance(value, int):
if 0 <= value < 2**16:
self._message_id_being_responded_to = value
else:
raise ValueError(
"Message ID Being Responded To must be "
"between 0 and 65535, inclusive"
)
elif value is None:
self._message_id_being_responded_to = value
else:
raise TypeError("Message ID Being Responded To must be an int")
# DIMSE-N Service Primitives
class N_EVENT_REPORT(DIMSEPrimitive):
r"""Represents a N-EVENT-REPORT primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | \- |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | M | U(=) |
+------------------------------------------+---------+----------+
| Event Type ID | M | C(=) |
+------------------------------------------+---------+----------+
| Event Information | U | \- |
+------------------------------------------+---------+----------+
| Event Reply | \- | C |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class for
storage. If included in the response/confirmation, it shall be equal
to the value in the request/indication
Status : int
The error or success notification of the operation.
"""
# Optional status element keywords other than 'Status'
STATUS_OPTIONAL_KEYWORDS = (
"AffectedSOPClassUID",
"AffectedSOPInstanceUID",
"EventTypeID",
"ErrorComment",
"ErrorID", # EventInformation
)
REQUEST_KEYWORDS = (
"MessageID",
"AffectedSOPClassUID",
"EventTypeID",
"AffectedSOPInstanceUID",
)
def __init__(self) -> None:
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.AffectedSOPClassUID = None
# self.AffectedSOPInstanceUID = None
self.EventTypeID = None
self.EventInformation = None
self.EventReply = None
# self.Status = None
# Optional status elements
self.ErrorComment = None
self.ErrorID = None
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Get or set the *Affected SOP Instance UID* as
:class:`~pydicom.uid.UID`.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def EventInformation(self) -> Optional[BytesIO]:
"""Get or set the *Event Information* as :class:`io.BytesIO`."""
return self._dataset_variant
@EventInformation.setter
def EventInformation(self, value: Optional[BytesIO]) -> None:
"""Set the *Event Information*.
Parameters
----------
io.BytesIO
The value to use for the *Event Information* parameter.
"""
self._dataset_variant = (value, "EventInformation") # type: ignore
@property
def EventReply(self) -> Optional[BytesIO]:
"""Get or set the *Event Reply* as :class:`io.BytesIO`."""
return self._dataset_variant
@EventReply.setter
def EventReply(self, value: Optional[BytesIO]) -> None:
"""Set the *Event Reply*.
Parameters
----------
io.BytesIO
The value to use for the *Event Reply* parameter.
"""
self._dataset_variant = (value, "EventReply") # type: ignore
@property
def EventTypeID(self) -> Optional[int]:
"""Get or set the *Event Type ID* as :class:`int`."""
return self._event_type_id
@EventTypeID.setter
def EventTypeID(self, value: Optional[int]) -> None:
"""Set the *Event Type ID*.
Parameters
----------
int
The value to use for the *Event Type ID* parameter.
"""
if isinstance(value, int) or value is None:
self._event_type_id = value
else:
raise TypeError("'N_EVENT_REPORT.EventTypeID' must be an int.")
class N_GET(DIMSEPrimitive):
r"""Represents an N-GET primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | \- |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Requested SOP Class UID | M | \- |
+------------------------------------------+---------+----------+
| Requested SOP Instance UID | M | \- |
+------------------------------------------+---------+----------+
| Attribute Identifier List | U | \- |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | \- | U |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | \- | U |
+------------------------------------------+---------+----------+
| Attribute List | \- | C |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
The SOP Class UID of the SOP Instance for which the attributes were
retrieved.
Status : int
The error or success notification of the operation.
"""
STATUS_OPTIONAL_KEYWORDS = (
"AttributeIdentifierList",
"ErrorComment",
"ErrorID",
)
REQUEST_KEYWORDS = ("MessageID", "RequestedSOPClassUID", "RequestedSOPInstanceUID")
def __init__(self) -> None:
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.RequestedSOPClassUID = None
# self.RequestedSOPInstanceUID = None
self.AttributeIdentifierList = None
# self.AffectedSOPClassUID = None
# self.AffectedSOPInstanceUID = None
self.AttributeList = None
# self.Status = None
# (Optional) elements for specific status values
self.ErrorComment = None
self.ErrorID = None
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Get or set the *Affected SOP Instance UID* as
:class:`~pydicom.uid.UID`.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def AttributeIdentifierList(self) -> Optional[List[BaseTag]]:
"""Get or set the *Attribute Identifier List* as a :class:`list` of
:class:`~pydicom.tag.BaseTag`.
Parameters
----------
list of pydicom.tag.BaseTag
The value to use for the *Attribute Identifier List* parameter.
A list of pydicom :class:`pydicom.tag.BaseTag` instances or any
values acceptable for creating them.
"""
return self._attribute_identifier_list
@AttributeIdentifierList.setter
def AttributeIdentifierList(
self, value: Optional[Union[BaseTag, List[BaseTag]]]
) -> None:
"""Set the *Attribute Identifier List*."""
if value is None:
self._attribute_identifier_list = None
return
# Singleton tags get put in a list
if not isinstance(value, (list, MutableSequence)):
value = [value]
# Empty list -> None
if not value:
self._attribute_identifier_list = None
return
try:
# Convert each item in list to pydicom Tag
self._attribute_identifier_list = [Tag(tag) for tag in value]
except (TypeError, ValueError):
raise ValueError("Attribute Identifier List must be a list of pydicom Tags")
@property
def AttributeList(self) -> Optional[BytesIO]:
"""Get or set the *Attribute List* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Attribute List* parameter.
"""
return self._dataset_variant
@AttributeList.setter
def AttributeList(self, value: Optional[BytesIO]) -> None:
"""Set the *Attribute List*."""
self._dataset_variant = (value, "AttributeList") # type: ignore
@property
def RequestedSOPClassUID(self) -> Optional[UID]:
"""Get or set the *Requested SOP Class UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Class UID* parameter.
"""
return self._RequestedSOPClassUID
@RequestedSOPClassUID.setter
def RequestedSOPClassUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Class UID*."""
self._RequestedSOPClassUID = value # type: ignore
@property
def RequestedSOPInstanceUID(self) -> Optional[UID]:
"""Get or set the *Requested SOP Instance UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Instance UID* parameter.
"""
return self._RequestedSOPInstanceUID
@RequestedSOPInstanceUID.setter
def RequestedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Instance UID*."""
self._RequestedSOPInstanceUID = value # type: ignore
class N_SET(DIMSEPrimitive):
r"""Represents a N-SET primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | \- |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Requested SOP Class UID | M | \- |
+------------------------------------------+---------+----------+
| Requested SOP Instance UID | M | \- |
+------------------------------------------+---------+----------+
| Modification List | M | \- |
+------------------------------------------+---------+----------+
| Attribute List | \- | U |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | \- | U |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | \- | U |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
The SOP Class UID of the modified SOP Instance.
Status : int
The error or success notification of the operation.
"""
STATUS_OPTIONAL_KEYWORDS = ("ErrorComment", "ErrorID", "AttributeIdentifierList")
REQUEST_KEYWORDS = (
"MessageID",
"RequestedSOPClassUID",
"RequestedSOPInstanceUID",
"ModificationList",
)
def __init__(self) -> None:
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.RequestedSOPClassUID = None
# self.RequestedSOPInstanceUID = None
self.ModificationList = None
self.AttributeList = None
# self.AffectedSOPClassUID = None
# self.AffectedSOPInstanceUID = None
# self.Status = None
# Optional
self.ErrorComment = None
self.ErrorID = None
self.AttributeIdentifierList = None
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Get or set the *Affected SOP Instance UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*."""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def AttributeList(self) -> Optional[BytesIO]:
"""Return the *Attribute List* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Attribute List* parameter.
"""
return self._dataset_variant
@AttributeList.setter
def AttributeList(self, value: Optional[BytesIO]) -> None:
"""Set the *Attribute List*."""
self._dataset_variant = (value, "AttributeList") # type: ignore
@property
def ModificationList(self) -> Optional[BytesIO]:
"""Return the *Modification List* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Modification List* parameter.
"""
return self._dataset_variant
@ModificationList.setter
def ModificationList(self, value: Optional[BytesIO]) -> None:
"""Set the *Modification List*."""
self._dataset_variant = (value, "ModificationList") # type: ignore
@property
def RequestedSOPClassUID(self) -> Optional[UID]:
"""Return the *Requested SOP Class UID* as :class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Class UID* parameter.
"""
return self._RequestedSOPClassUID
@RequestedSOPClassUID.setter
def RequestedSOPClassUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Class UID*."""
self._RequestedSOPClassUID = value # type: ignore
@property
def RequestedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Requested SOP Instance UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Instance UID* parameter.
"""
return self._RequestedSOPInstanceUID
@RequestedSOPInstanceUID.setter
def RequestedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Instance UID*."""
self._RequestedSOPInstanceUID = value # type: ignore
class N_ACTION(DIMSEPrimitive):
r"""Represents a N-ACTION primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | \- |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Requested SOP Class UID | M | \- |
+------------------------------------------+---------+----------+
| Requested SOP Instance UID | M | \- |
+------------------------------------------+---------+----------+
| Action Type ID | M | C(=) |
+------------------------------------------+---------+----------+
| Action Information | U | \- |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | \- | U |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | \- | U |
+------------------------------------------+---------+----------+
| Action Reply | \- | C |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class for
storage. If included in the response/confirmation, it shall be equal
to the value in the request/indication
Status : int
The error or success notification of the operation.
"""
STATUS_OPTIONAL_KEYWORDS = ("ErrorComment", "ErrorID", "AttributeIdentifierList")
REQUEST_KEYWORDS = (
"MessageID",
"RequestedSOPClassUID",
"RequestedSOPInstanceUID",
"ActionTypeID",
)
def __init__(self) -> None:
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.RequestedSOPClassUID = None
# self.RequestedSOPInstanceUID = None
self.ActionTypeID = None
self.ActionInformation = None
# self.AffectedSOPClassUID = None
# self.AffectedSOPInstanceUID = None
self.ActionReply = None
# self.Status = None
# Optional status elements
self.ErrorComment = None
self.ErrorID = None
@property
def ActionInformation(self) -> Optional[BytesIO]:
"""Return the *Action Information* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Action Information* parameter.
"""
return self._dataset_variant
@ActionInformation.setter
def ActionInformation(self, value: Optional[BytesIO]) -> None:
"""Set the *Action Information*."""
self._dataset_variant = (value, "ActionInformation") # type: ignore
@property
def ActionReply(self) -> Optional[BytesIO]:
"""Return the *Action Reply* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Action Reply* parameter.
"""
return self._dataset_variant
@ActionReply.setter
def ActionReply(self, value: Optional[BytesIO]) -> None:
"""Set the *Action Reply*."""
self._dataset_variant = (value, "ActionReply") # type: ignore
@property
def ActionTypeID(self) -> Optional[int]:
"""Return the *Action Type ID* as :class:`int`.
Parameters
----------
int
The value to use for the *Action Type ID* parameter.
"""
return self._action_type_id
@ActionTypeID.setter
def ActionTypeID(self, value: Optional[int]) -> None:
"""Set the *Action Type ID*."""
if isinstance(value, int) or value is None:
self._action_type_id = value
else:
raise TypeError("'N_ACTION.ActionTypeID' must be an int.")
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Affected SOP Instance UID* as :class:`~pydicom.uid.UID`.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*."""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def RequestedSOPClassUID(self) -> Optional[UID]:
"""Return the *Requested SOP Class UID* as :class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Class UID* parameter.
"""
return self._RequestedSOPClassUID
@RequestedSOPClassUID.setter
def RequestedSOPClassUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Class UID*."""
self._RequestedSOPClassUID = value # type: ignore
@property
def RequestedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Requested SOP Instance UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Instance UID* parameter.
"""
return self._RequestedSOPInstanceUID
@RequestedSOPInstanceUID.setter
def RequestedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Instance UID*."""
self._RequestedSOPInstanceUID = value # type: ignore
class N_CREATE(DIMSEPrimitive):
r"""Represents a N-CREATE primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | \- |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | M | U(=) |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | U | C |
+------------------------------------------+---------+----------+
| Attribute List | U | U |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class for
storage. If included in the response/confirmation, it shall be equal
to the value in the request/indication
Status : int
The error or success notification of the operation. It shall be
one of the following values:
"""
STATUS_OPTIONAL_KEYWORDS = (
"ErrorComment",
"ErrorID",
)
REQUEST_KEYWORDS = ("MessageID", "AffectedSOPClassUID")
def __init__(self) -> None:
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.AffectedSOPClassUID = None
# self.AffectedSOPInstanceUID = None
self.AttributeList = None
# self.Status = None
# Optional elements
self.ErrorComment = None
self.ErrorID = None
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Affected SOP Instance UID* as :class:`~pydicom.uid.UID`.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*."""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def AttributeList(self) -> Optional[BytesIO]:
"""Return the *Attribute List* as :class:`io.BytesIO`.
Parameters
----------
io.BytesIO
The value to use for the *Attribute List* parameter.
"""
return self._dataset_variant
@AttributeList.setter
def AttributeList(self, value: Optional[BytesIO]) -> None:
"""Set the *Attribute List*."""
self._dataset_variant = (value, "AttributeList") # type: ignore
class N_DELETE(DIMSEPrimitive):
r"""Represents a N-DELETE primitive.
+------------------------------------------+---------+----------+
| Parameter | Req/ind | Rsp/conf |
+==========================================+=========+==========+
| Message ID | M | \- |
+------------------------------------------+---------+----------+
| Message ID Being Responded To | \- | M |
+------------------------------------------+---------+----------+
| Requested SOP Class UID | M | \- |
+------------------------------------------+---------+----------+
| Requested SOP Instance UID | M | \- |
+------------------------------------------+---------+----------+
| Affected SOP Class UID | \- | U |
+------------------------------------------+---------+----------+
| Affected SOP Instance UID | \- | U |
+------------------------------------------+---------+----------+
| Status | \- | M |
+------------------------------------------+---------+----------+
| (=) - The value of the parameter is equal to the value of the parameter
in the column to the left
| C - The parameter is conditional.
| M - Mandatory
| MF - Mandatory with a fixed value
| U - The use of this parameter is a DIMSE service user option
| UF - User option with a fixed value
Attributes
----------
MessageID : int
Identifies the operation and is used to distinguish this
operation from other notifications or operations that may be in
progress. No two identical values for the Message ID shall be used for
outstanding operations.
MessageIDBeingRespondedTo : int
The Message ID of the operation request/indication to which this
response/confirmation applies.
AffectedSOPClassUID : pydicom.uid.UID, bytes or str
For the request/indication this specifies the SOP Class for
storage. If included in the response/confirmation, it shall be equal
to the value in the request/indication
Status : int
The error or success notification of the operation.
"""
STATUS_OPTIONAL_KEYWORDS = (
"ErrorComment",
"ErrorID",
)
REQUEST_KEYWORDS = ("MessageID", "RequestedSOPClassUID", "RequestedSOPInstanceUID")
def __init__(self) -> None:
# self.MessageID = None
# self.MessageIDBeingRespondedTo = None
# self.RequestedSOPClassUID = None
# self.RequestedSOPInstanceUID = None
# self.AffectedSOPClassUID = None
# self.AffectedSOPInstanceUID = None
# self.Status = None
# Optional
self.ErrorComment = None
self.ErrorID = None
@property
def AffectedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Affected SOP Instance UID* as :class:`~pydicom.uid.UID`.
Parameters
----------
value : pydicom.uid.UID, bytes or str
The value to use for the *Affected SOP Class UID* parameter.
"""
return self._AffectedSOPInstanceUID
@AffectedSOPInstanceUID.setter
def AffectedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Affected SOP Instance UID*."""
self._AffectedSOPInstanceUID = value # type: ignore
@property
def RequestedSOPClassUID(self) -> Optional[UID]:
"""Return the *Requested SOP Class UID* as :class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Class UID* parameter.
"""
return self._RequestedSOPClassUID
@RequestedSOPClassUID.setter
def RequestedSOPClassUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Class UID*."""
self._RequestedSOPClassUID = value # type: ignore
@property
def RequestedSOPInstanceUID(self) -> Optional[UID]:
"""Return the *Requested SOP Instance UID* as
:class:`~pydicom.uid.UID`.
Parameters
----------
pydicom.uid.UID, bytes or str
The value to use for the *Requested SOP Instance UID* parameter.
"""
return self._RequestedSOPInstanceUID
@RequestedSOPInstanceUID.setter
def RequestedSOPInstanceUID(self, value: OptionalUIDType) -> None:
"""Set the *Requested SOP Instance UID*."""
self._RequestedSOPInstanceUID = value # type: ignore
| 38.525773 | 88 | 0.538704 | 7,755 | 82,214 | 5.63804 | 0.04668 | 0.019212 | 0.013494 | 0.012785 | 0.8512 | 0.818425 | 0.788738 | 0.764472 | 0.734122 | 0.723555 | 0 | 0.004093 | 0.292736 | 82,214 | 2,133 | 89 | 38.543835 | 0.747846 | 0.551159 | 0 | 0.624831 | 0 | 0 | 0.094949 | 0.017777 | 0 | 0 | 0.000127 | 0 | 0 | 1 | 0.182186 | false | 0 | 0.014845 | 0 | 0.369771 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
60e4e2bd260477e121e863216486bf758a15d283 | 136 | py | Python | torvend/meta/__init__.py | stephen-bunn/torvend | 18e8242ff80523b498a5e7c996ef1bcb074da423 | [
"MIT"
] | 1 | 2018-12-17T23:17:49.000Z | 2018-12-17T23:17:49.000Z | torvend/meta/__init__.py | stephen-bunn/torvend | 18e8242ff80523b498a5e7c996ef1bcb074da423 | [
"MIT"
] | null | null | null | torvend/meta/__init__.py | stephen-bunn/torvend | 18e8242ff80523b498a5e7c996ef1bcb074da423 | [
"MIT"
] | null | null | null | # Copyright (c) 2017 Stephen Bunn (stephen@bunn.io)
# MIT License <https://opensource.org/licenses/MIT>
from .loggable import Loggable
| 27.2 | 51 | 0.757353 | 19 | 136 | 5.421053 | 0.789474 | 0.213592 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.033333 | 0.117647 | 136 | 4 | 52 | 34 | 0.825 | 0.727941 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
7156472f4729e3b7bb891f46102d01d2e28ba342 | 7,405 | py | Python | tests/sql/grants.py | labsyspharm/minerva-db | 49c205fc5d9bcc513b4eb21b6493c928ea711fce | [
"MIT"
] | null | null | null | tests/sql/grants.py | labsyspharm/minerva-db | 49c205fc5d9bcc513b4eb21b6493c928ea711fce | [
"MIT"
] | 2 | 2018-06-06T13:29:23.000Z | 2018-07-25T00:36:38.000Z | tests/sql/grants.py | sorgerlab/minerva-db | 49c205fc5d9bcc513b4eb21b6493c928ea711fce | [
"MIT"
] | 1 | 2020-03-06T23:53:42.000Z | 2020-03-06T23:53:42.000Z | import pytest
from src.minerva_db.sql.api.utils import to_jsonapi
from . import sa_obj_to_dict, statement_log
@pytest.mark.parametrize('fixture_name', ['user_granted_read_hierarchy',
'group_granted_read_hierarchy'])
class TestGrants():
def test_repository(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
repository_uuid = hierarchy['repository'].uuid
decision = client.has_permission(user_uuid, 'Repository',
repository_uuid, 'Read')
assert True is decision
def test_repository_insufficent(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
repository_uuid = hierarchy['repository'].uuid
decision = client.has_permission(user_uuid, 'Repository',
repository_uuid, 'Write')
assert False is decision
def test_repository_none(self, client, db_user, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = db_user.uuid
repository_uuid = hierarchy['repository'].uuid
decision = client.has_permission(user_uuid, 'Repository',
repository_uuid, 'Read')
assert False is decision
def test_import(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
import_uuid = hierarchy['import_'].uuid
decision = client.has_permission(user_uuid, 'Import', import_uuid,
'Read')
assert True is decision
def test_import_insufficent(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
import_uuid = hierarchy['import_'].uuid
decision = client.has_permission(user_uuid, 'Import', import_uuid,
'Write')
assert False is decision
def test_import_none(self, client, db_user, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = db_user.uuid
import_uuid = hierarchy['import_'].uuid
decision = client.has_permission(user_uuid, 'Import', import_uuid,
'Read')
assert False is decision
def test_fileset(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
fileset_uuid = hierarchy['fileset'].uuid
decision = client.has_permission(user_uuid, 'Fileset', fileset_uuid,
'Read')
assert True is decision
def test_fileset_insufficent(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
fileset_uuid = hierarchy['fileset'].uuid
decision = client.has_permission(user_uuid, 'Fileset', fileset_uuid,
'Write')
assert False is decision
def test_fileset_none(self, client, db_user, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = db_user.uuid
fileset_uuid = hierarchy['fileset'].uuid
decision = client.has_permission(user_uuid, 'Fileset', fileset_uuid,
'Read')
assert False is decision
def test_image(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
image_uuid = hierarchy['image'].uuid
decision = client.has_permission(user_uuid, 'Image', image_uuid,
'Read')
assert True is decision
def test_image_standalone(self, client, fixture_name, standalone_image_permissions_admin):
user_uuid = standalone_image_permissions_admin['user'].uuid
image_uuid = standalone_image_permissions_admin['image'].uuid
decision = client.has_permission(user_uuid, 'Image', image_uuid,
'Admin')
assert True is decision
def test_image_insufficent(self, client, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = hierarchy['user'].uuid
image_uuid = hierarchy['image'].uuid
decision = client.has_permission(user_uuid, 'Image', image_uuid,
'Write')
assert False is decision
def test_image_none(self, client, db_user, fixture_name, request):
hierarchy = request.getfixturevalue(fixture_name)
user_uuid = db_user.uuid
image_uuid = hierarchy['image'].uuid
decision = client.has_permission(user_uuid, 'Image', image_uuid,
'Read')
assert False is decision
class TestLists():
def test_list_repositories_for_user(self, client,
user_granted_read_hierarchy):
grant_keys = ['subject_uuid', 'repository_uuid', 'permission']
repository_keys = ['uuid', 'name', 'raw_storage']
user_uuid = user_granted_read_hierarchy['user_uuid']
d_grant = sa_obj_to_dict(
user_granted_read_hierarchy['grant'],
grant_keys
)
d_repository = sa_obj_to_dict(
user_granted_read_hierarchy['repository'],
repository_keys
)
assert to_jsonapi(
[d_grant], {
'repositories': [d_repository]
}
) == client.list_repositories_for_user(user_uuid)
@pytest.mark.parametrize('fixture_name', ['user_granted_read_hierarchy',
'group_granted_read_hierarchy'])
def test_list_repositories_for_user_implied(self, client, fixture_name,
request):
hierarchy = request.getfixturevalue(fixture_name)
grant_keys = ['subject_uuid', 'repository_uuid', 'permission']
repository_keys = ['uuid', 'name', 'raw_storage']
user_uuid = hierarchy['user_uuid']
d_grant = sa_obj_to_dict(
hierarchy['grant'],
grant_keys
)
d_repository = sa_obj_to_dict(
hierarchy['repository'],
repository_keys
)
assert to_jsonapi(
[d_grant], {
'repositories': [d_repository]
}
) == client.list_repositories_for_user(user_uuid, implied=True)
def test_list_repositories_for_user_none(self, client, db_user):
assert to_jsonapi(
[], {
'repositories': []
}
) == client.list_repositories_for_user(db_user.uuid, implied=True)
def test_list_repositories_for_user_query_count(self, connection, client,
db_user):
user_uuid = db_user.uuid
with statement_log(connection) as statements:
client.list_repositories_for_user(user_uuid)
assert len(statements) == 1
| 43.052326 | 94 | 0.611614 | 758 | 7,405 | 5.647757 | 0.091029 | 0.091567 | 0.049054 | 0.08199 | 0.923149 | 0.886008 | 0.850269 | 0.824574 | 0.751694 | 0.735809 | 0 | 0.000194 | 0.302633 | 7,405 | 171 | 95 | 43.304094 | 0.828815 | 0 | 0 | 0.662162 | 0 | 0 | 0.081567 | 0.014855 | 0 | 0 | 0 | 0 | 0.114865 | 1 | 0.114865 | false | 0 | 0.081081 | 0 | 0.209459 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
71dfda7f6c8751d5ceaeeee492bddd484943e0ac | 137 | py | Python | src/ram/capture.py | bootforce-dev/ram-framework | b39c43cbe3b6e76db73dfd65c38da4fa578b032f | [
"MIT"
] | 1 | 2019-03-01T10:19:34.000Z | 2019-03-01T10:19:34.000Z | src/ram/capture.py | ram-framework/ram-framework | b39c43cbe3b6e76db73dfd65c38da4fa578b032f | [
"MIT"
] | null | null | null | src/ram/capture.py | ram-framework/ram-framework | b39c43cbe3b6e76db73dfd65c38da4fa578b032f | [
"MIT"
] | null | null | null | import ram.console
class __api__(object):
def __call__(self, *args, **kwargs):
return ram.console.capture(*args, **kwargs)
| 19.571429 | 51 | 0.671533 | 17 | 137 | 4.941176 | 0.764706 | 0.238095 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.182482 | 137 | 6 | 52 | 22.833333 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.25 | 0.25 | 1 | 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 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 6 |
e085f16f7b96052530bcfc60d34754e3fe44b58a | 176 | py | Python | testplan/testing/multitest/entries/stdout/__init__.py | raoyitao/testplan | aae3e9cee597ca3d01b6d64eed2642c421c56cbb | [
"Apache-2.0"
] | 96 | 2018-03-14T13:14:50.000Z | 2021-01-14T08:26:08.000Z | testplan/testing/multitest/entries/stdout/__init__.py | raoyitao/testplan | aae3e9cee597ca3d01b6d64eed2642c421c56cbb | [
"Apache-2.0"
] | 135 | 2018-06-28T02:41:05.000Z | 2021-01-19T02:16:58.000Z | testplan/testing/multitest/entries/stdout/__init__.py | raoyitao/testplan | aae3e9cee597ca3d01b6d64eed2642c421c56cbb | [
"Apache-2.0"
] | 53 | 2018-03-17T14:39:15.000Z | 2021-01-21T10:54:13.000Z | """
This module contains logic for printing out
assertion details as tests run.
"""
from .base import BaseRenderer, registry
from .assertions import AssertionRenderer
| 22 | 47 | 0.761364 | 21 | 176 | 6.380952 | 0.904762 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.181818 | 176 | 7 | 48 | 25.142857 | 0.930556 | 0.426136 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.5 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
e0d0ebce6a894a7613206e76f7529aa53f64f274 | 81 | py | Python | plugins/devo/icon_devo/actions/__init__.py | lukaszlaszuk/insightconnect-plugins | 8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892 | [
"MIT"
] | 46 | 2019-06-05T20:47:58.000Z | 2022-03-29T10:18:01.000Z | plugins/devo/icon_devo/actions/__init__.py | lukaszlaszuk/insightconnect-plugins | 8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892 | [
"MIT"
] | 386 | 2019-06-07T20:20:39.000Z | 2022-03-30T17:35:01.000Z | plugins/devo/icon_devo/actions/__init__.py | lukaszlaszuk/insightconnect-plugins | 8c6ce323bfbb12c55f8b5a9c08975d25eb9f8892 | [
"MIT"
] | 43 | 2019-07-09T14:13:58.000Z | 2022-03-28T12:04:46.000Z | # GENERATED BY KOMAND SDK - DO NOT EDIT
from .query_logs.action import QueryLogs
| 27 | 40 | 0.790123 | 13 | 81 | 4.846154 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.160494 | 81 | 2 | 41 | 40.5 | 0.926471 | 0.45679 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
e0d9640cb1d25e7fa174eb0693f72eb4d76dc3f6 | 275 | py | Python | programs/install.py | calixo888/AutoBot | 1ceeaf6aa5989fbe9e378b2d67f8838acaf8251e | [
"Apache-2.0"
] | null | null | null | programs/install.py | calixo888/AutoBot | 1ceeaf6aa5989fbe9e378b2d67f8838acaf8251e | [
"Apache-2.0"
] | null | null | null | programs/install.py | calixo888/AutoBot | 1ceeaf6aa5989fbe9e378b2d67f8838acaf8251e | [
"Apache-2.0"
] | null | null | null | import subprocess
try:
subprocess.call("curl https://bootstrap.pypa.io/get-pip.py | python",shell=True)
except:
pass
subprocess.call("pip install pyautogui",shell=True)
subprocess.call("pip install pynput",shell=True)
subprocess.call("pip install future",shell=True) | 30.555556 | 84 | 0.763636 | 39 | 275 | 5.384615 | 0.538462 | 0.266667 | 0.242857 | 0.342857 | 0.314286 | 0.314286 | 0 | 0 | 0 | 0 | 0 | 0 | 0.094545 | 275 | 9 | 85 | 30.555556 | 0.843373 | 0 | 0 | 0 | 0 | 0 | 0.387681 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.125 | 0.125 | 0 | 0.125 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 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 | 1 | 0 | 0 | 0 | 0 | 0 | 6 |
e0ee54224391eef9384c92c221cedbc4d41d94fd | 51,727 | py | Python | tests/components/template/test_light.py | JeffersonBledsoe/core | 3825f80a2dd087ae70654079cd9f3071289b8423 | [
"Apache-2.0"
] | 7 | 2019-08-15T13:36:58.000Z | 2020-03-18T10:46:29.000Z | tests/components/template/test_light.py | JeffersonBledsoe/core | 3825f80a2dd087ae70654079cd9f3071289b8423 | [
"Apache-2.0"
] | 87 | 2020-07-06T22:22:54.000Z | 2022-03-31T06:01:46.000Z | tests/components/template/test_light.py | JeffersonBledsoe/core | 3825f80a2dd087ae70654079cd9f3071289b8423 | [
"Apache-2.0"
] | 7 | 2018-10-04T10:12:45.000Z | 2021-12-29T20:55:40.000Z | """The tests for the Template light platform."""
import logging
import pytest
import homeassistant.components.light as light
from homeassistant.components.light import (
ATTR_BRIGHTNESS,
ATTR_COLOR_TEMP,
ATTR_EFFECT,
ATTR_HS_COLOR,
ATTR_TRANSITION,
ATTR_WHITE_VALUE,
SUPPORT_TRANSITION,
)
from homeassistant.const import (
ATTR_ENTITY_ID,
SERVICE_TURN_OFF,
SERVICE_TURN_ON,
STATE_OFF,
STATE_ON,
STATE_UNAVAILABLE,
)
_LOGGER = logging.getLogger(__name__)
# Represent for light's availability
_STATE_AVAILABILITY_BOOLEAN = "availability_boolean.state"
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{states.test['big.fat...']}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_template_state_invalid(hass, start_ha):
"""Test template state with render error."""
assert hass.states.get("light.test_template_light").state == STATE_OFF
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{ states.light.test_state.state }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_template_state_text(hass, start_ha):
"""Test the state text of a template."""
for set_state in [STATE_ON, STATE_OFF]:
hass.states.async_set("light.test_state", set_state)
await hass.async_block_till_done()
assert hass.states.get("light.test_template_light").state == set_state
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config_addon,expected_state",
[
({"replace1": '"{{ 1 == 1 }}"'}, STATE_ON),
({"replace1": '"{{ 1 == 2 }}"'}, STATE_OFF),
],
)
@pytest.mark.parametrize(
"config",
[
"""{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": replace1,
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state"
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state"
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}"
}
}
}
}
}
}""",
],
)
async def test_templatex_state_boolean(hass, expected_state, start_ha):
"""Test the setting of the state with boolean on."""
assert hass.states.get("light.test_template_light").state == expected_state
@pytest.mark.parametrize("count,domain", [(0, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{%- if false -%}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
{
"light": {
"platform": "template",
"lights": {
"bad name here": {
"value_template": "{{ 1== 1}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
{
"light": {
"platform": "template",
"switches": {"test_template_light": "Invalid"},
}
},
],
)
async def test_template_syntax_error(hass, start_ha):
"""Test templating syntax error."""
assert hass.states.async_all("light") == []
SET_VAL1 = '"value_template": "{{ 1== 1}}",'
SET_VAL2 = '"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},'
SET_VAL3 = '"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},'
@pytest.mark.parametrize("domain", [light.DOMAIN])
@pytest.mark.parametrize(
"config_addon, count",
[
({"replace2": f"{SET_VAL2}{SET_VAL3}"}, 1),
({"replace2": f"{SET_VAL1}{SET_VAL2}"}, 0),
({"replace2": f"{SET_VAL2}{SET_VAL3}"}, 1),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template", "lights": {
"light_one": {
replace2
"set_level": {"service": "light.turn_on",
"data_template": {"entity_id": "light.test_state","brightness": "{{brightness}}"
}}}}}}"""
],
)
async def test_missing_key(hass, count, start_ha):
"""Test missing template."""
if count:
assert hass.states.async_all("light") != []
else:
assert hass.states.async_all("light") == []
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{states.light.test_state.state}}",
"turn_on": {"service": "test.automation"},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_on_action(hass, start_ha, calls):
"""Test on action."""
hass.states.async_set("light.test_state", STATE_OFF)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.state == STATE_OFF
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light"},
blocking=True,
)
assert len(calls) == 1
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{states.light.test_state.state}}",
"turn_on": {
"service": "test.automation",
"data_template": {
"transition": "{{transition}}",
},
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"supports_transition_template": "{{true}}",
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
"transition": "{{transition}}",
},
},
}
},
}
},
],
)
async def test_on_action_with_transition(hass, start_ha, calls):
"""Test on action with transition."""
hass.states.async_set("light.test_state", STATE_OFF)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.state == STATE_OFF
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_TRANSITION: 5},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["transition"] == 5
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"turn_on": {"service": "test.automation"},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_on_action_optimistic(hass, start_ha, calls):
"""Test on action with optimistic state."""
hass.states.async_set("light.test_state", STATE_OFF)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.state == STATE_OFF
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light"},
blocking=True,
)
state = hass.states.get("light.test_template_light")
assert len(calls) == 1
assert state.state == STATE_ON
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{states.light.test_state.state}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "test.automation",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_off_action(hass, start_ha, calls):
"""Test off action."""
hass.states.async_set("light.test_state", STATE_ON)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.state == STATE_ON
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_OFF,
{ATTR_ENTITY_ID: "light.test_template_light"},
blocking=True,
)
assert len(calls) == 1
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{states.light.test_state.state}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "test.automation",
"data_template": {
"transition": "{{transition}}",
},
},
"supports_transition_template": "{{true}}",
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
"transition": "{{transition}}",
},
},
}
},
}
},
],
)
async def test_off_action_with_transition(hass, start_ha, calls):
"""Test off action with transition."""
hass.states.async_set("light.test_state", STATE_ON)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.state == STATE_ON
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_OFF,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_TRANSITION: 2},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["transition"] == 2
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {"service": "test.automation"},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_off_action_optimistic(hass, start_ha, calls):
"""Test off action with optimistic state."""
state = hass.states.get("light.test_template_light")
assert state.state == STATE_OFF
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_OFF,
{ATTR_ENTITY_ID: "light.test_template_light"},
blocking=True,
)
assert len(calls) == 1
state = hass.states.get("light.test_template_light")
assert state.state == STATE_OFF
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{1 == 1}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_white_value": {
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"white_value": "{{white_value}}",
},
},
}
},
}
},
],
)
async def test_white_value_action_no_template(hass, start_ha, calls):
"""Test setting white value with optimistic template."""
state = hass.states.get("light.test_template_light")
assert state.attributes.get("white_value") is None
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_WHITE_VALUE: 124},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["white_value"] == 124
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("white_value") == 124
@pytest.mark.parametrize(
"expected_white_value,config_addon",
[
(255, {"replace3": "{{255}}"}),
(None, {"replace3": "{{256}}"}),
(None, {"replace3": "{{x - 12}}"}),
(None, {"replace3": "{{ none }}"}),
(None, {"replace3": ""}),
],
)
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
"""{
"light": {"platform": "template","lights": {
"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_white_value": {"service": "light.turn_on",
"data_template": {"entity_id": "light.test_state",
"white_value": "{{white_value}}"}},
"white_value_template": "replace3"
}}}}""",
],
)
async def test_white_value_template(hass, expected_white_value, start_ha):
"""Test the template for the white value."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("white_value") == expected_white_value
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{1 == 1}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_level_action_no_template(hass, start_ha, calls):
"""Test setting brightness with optimistic template."""
state = hass.states.get("light.test_template_light")
assert state.attributes.get("brightness") is None
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_BRIGHTNESS: 124},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["brightness"] == 124
state = hass.states.get("light.test_template_light")
_LOGGER.info(str(state.attributes))
assert state is not None
assert state.attributes.get("brightness") == 124
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_level,config_addon",
[
(255, {"replace4": '"{{255}}"'}),
(None, {"replace4": '"{{256}}"'}),
(None, {"replace4": '"{{x - 12}}"'}),
(None, {"replace4": '"{{ none }}"'}),
(None, {"replace4": '""'}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template", "lights": {
"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_level": {"service": "light.turn_on","data_template": {
"entity_id": "light.test_state","brightness": "{{brightness}}"}},
"level_template": replace4
}}}}""",
],
)
async def test_level_template(hass, expected_level, start_ha):
"""Test the template for the level."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("brightness") == expected_level
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_temp,config_addon",
[
(500, {"replace5": '"{{500}}"'}),
(None, {"replace5": '"{{501}}"'}),
(None, {"replace5": '"{{x - 12}}"'}),
(None, {"replace5": '"None"'}),
(None, {"replace5": '"{{ none }}"'}),
(None, {"replace5": '""'}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state"
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state"
},
"set_temperature": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"color_temp": "{{color_temp}}"
}
},
"temperature_template": replace5
}
}
}
}"""
],
)
async def test_temperature_template(hass, expected_temp, start_ha):
"""Test the template for the temperature."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("color_temp") == expected_temp
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{1 == 1}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_temperature": {
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"color_temp": "{{color_temp}}",
},
},
}
},
}
},
],
)
async def test_temperature_action_no_template(hass, start_ha, calls):
"""Test setting temperature with optimistic template."""
state = hass.states.get("light.test_template_light")
assert state.attributes.get("color_template") is None
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_COLOR_TEMP: 345},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["color_temp"] == 345
state = hass.states.get("light.test_template_light")
_LOGGER.info(str(state.attributes))
assert state is not None
assert state.attributes.get("color_temp") == 345
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"friendly_name": "Template light",
"value_template": "{{ 1 == 1 }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_friendly_name(hass, start_ha):
"""Test the accessibility of the friendly_name attribute."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("friendly_name") == "Template light"
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"friendly_name": "Template light",
"value_template": "{{ 1 == 1 }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
"icon_template": "{% if states.light.test_state.state %}"
"mdi:check"
"{% endif %}",
}
},
}
},
],
)
async def test_icon_template(hass, start_ha):
"""Test icon template."""
state = hass.states.get("light.test_template_light")
assert state.attributes.get("icon") == ""
state = hass.states.async_set("light.test_state", STATE_ON)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.attributes["icon"] == "mdi:check"
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"friendly_name": "Template light",
"value_template": "{{ 1 == 1 }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
"entity_picture_template": "{% if states.light.test_state.state %}"
"/local/light.png"
"{% endif %}",
}
},
}
},
],
)
async def test_entity_picture_template(hass, start_ha):
"""Test entity_picture template."""
state = hass.states.get("light.test_template_light")
assert state.attributes.get("entity_picture") == ""
state = hass.states.async_set("light.test_state", STATE_ON)
await hass.async_block_till_done()
state = hass.states.get("light.test_template_light")
assert state.attributes["entity_picture"] == "/local/light.png"
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{1 == 1}}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_color": [
{
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"h": "{{h}}",
"s": "{{s}}",
},
},
{
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"s": "{{s}}",
"h": "{{h}}",
},
},
],
}
},
}
},
],
)
async def test_color_action_no_template(hass, start_ha, calls):
"""Test setting color with optimistic template."""
state = hass.states.get("light.test_template_light")
assert state.attributes.get("hs_color") is None
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_HS_COLOR: (40, 50)},
blocking=True,
)
assert len(calls) == 2
assert calls[0].data["h"] == 40
assert calls[0].data["s"] == 50
assert calls[1].data["h"] == 40
assert calls[1].data["s"] == 50
state = hass.states.get("light.test_template_light")
_LOGGER.info(str(state.attributes))
assert state is not None
assert calls[0].data["h"] == 40
assert calls[0].data["s"] == 50
assert calls[1].data["h"] == 40
assert calls[1].data["s"] == 50
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_hs,config_addon",
[
((360, 100), {"replace6": '"{{(360, 100)}}"'}),
((359.9, 99.9), {"replace6": '"{{(359.9, 99.9)}}"'}),
(None, {"replace6": '"{{(361, 100)}}"'}),
(None, {"replace6": '"{{(360, 101)}}"'}),
(None, {"replace6": '"{{x - 12}}"'}),
(None, {"replace6": '""'}),
(None, {"replace6": '"{{ none }}"'}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template","lights": {"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_color": [{"service": "input_number.set_value",
"data_template": {"entity_id": "input_number.h","color_temp": "{{h}}"
}}],
"color_template": replace6
}}}}"""
],
)
async def test_color_template(hass, expected_hs, start_ha):
"""Test the template for the color."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("hs_color") == expected_hs
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{true}}",
"turn_on": {"service": "test.automation"},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
"set_effect": {
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"effect": "{{effect}}",
},
},
"effect_list_template": "{{ ['Disco', 'Police'] }}",
"effect_template": "{{ 'Disco' }}",
}
},
}
},
],
)
async def test_effect_action_valid_effect(hass, start_ha, calls):
"""Test setting valid effect with template."""
state = hass.states.get("light.test_template_light")
assert state is not None
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_EFFECT: "Disco"},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["effect"] == "Disco"
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("effect") == "Disco"
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"value_template": "{{true}}",
"turn_on": {"service": "test.automation"},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
"set_effect": {
"service": "test.automation",
"data_template": {
"entity_id": "test.test_state",
"effect": "{{effect}}",
},
},
"effect_list_template": "{{ ['Disco', 'Police'] }}",
"effect_template": "{{ None }}",
}
},
}
},
],
)
async def test_effect_action_invalid_effect(hass, start_ha, calls):
"""Test setting invalid effect with template."""
state = hass.states.get("light.test_template_light")
assert state is not None
await hass.services.async_call(
light.DOMAIN,
SERVICE_TURN_ON,
{ATTR_ENTITY_ID: "light.test_template_light", ATTR_EFFECT: "RGB"},
blocking=True,
)
assert len(calls) == 1
assert calls[0].data["effect"] == "RGB"
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("effect") is None
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_effect_list,config_addon",
[
(
["Strobe color", "Police", "Christmas", "RGB", "Random Loop"],
{
"replace7": "\"{{ ['Strobe color', 'Police', 'Christmas', 'RGB', 'Random Loop'] }}\""
},
),
(
["Police", "RGB", "Random Loop"],
{"replace7": "\"{{ ['Police', 'RGB', 'Random Loop'] }}\""},
),
(None, {"replace7": '"{{ [] }}"'}),
(None, {"replace7": "\"{{ '[]' }}\""}),
(None, {"replace7": '"{{ 124 }}"'}),
(None, {"replace7": "\"{{ '124' }}\""}),
(None, {"replace7": '"{{ none }}"'}),
(None, {"replace7": '""'}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template","lights": {"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_effect": {"service": "test.automation",
"data_template": {"entity_id": "test.test_state","effect": "{{effect}}"}},
"effect_template": "{{ None }}",
"effect_list_template": replace7
}}}}""",
],
)
async def test_effect_list_template(hass, expected_effect_list, start_ha):
"""Test the template for the effect list."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("effect_list") == expected_effect_list
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_effect,config_addon",
[
(None, {"replace8": '"Disco"'}),
(None, {"replace8": '"None"'}),
(None, {"replace8": '"{{ None }}"'}),
("Police", {"replace8": '"Police"'}),
("Strobe color", {"replace8": "\"{{ 'Strobe color' }}\""}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template","lights": {"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_effect": {"service": "test.automation","data_template": {
"entity_id": "test.test_state","effect": "{{effect}}"}},
"effect_list_template": "{{ ['Strobe color', 'Police', 'Christmas', 'RGB', 'Random Loop'] }}",
"effect_template": replace8
}}}}""",
],
)
async def test_effect_template(hass, expected_effect, start_ha):
"""Test the template for the effect."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("effect") == expected_effect
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_min_mireds,config_addon",
[
(118, {"replace9": '"{{118}}"'}),
(153, {"replace9": '"{{x - 12}}"'}),
(153, {"replace9": '"None"'}),
(153, {"replace9": '"{{ none }}"'}),
(153, {"replace9": '""'}),
(153, {"replace9": "\"{{ 'a' }}\""}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template","lights": {"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_temperature": {"service": "light.turn_on","data_template": {
"entity_id": "light.test_state","color_temp": "{{color_temp}}"}},
"temperature_template": "{{200}}",
"min_mireds_template": replace9
}}}}""",
],
)
async def test_min_mireds_template(hass, expected_min_mireds, start_ha):
"""Test the template for the min mireds."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("min_mireds") == expected_min_mireds
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_max_mireds,config_addon",
[
(488, {"template1": '"{{488}}"'}),
(500, {"template1": '"{{x - 12}}"'}),
(500, {"template1": '"None"'}),
(500, {"template1": '"{{ none }}"'}),
(500, {"template1": '""'}),
(500, {"template1": "\"{{ 'a' }}\""}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template","lights": {"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_temperature": {"service": "light.turn_on","data_template": {
"entity_id": "light.test_state","color_temp": "{{color_temp}}"}},
"temperature_template": "{{200}}",
"max_mireds_template": template1
}}}}""",
],
)
async def test_max_mireds_template(hass, expected_max_mireds, start_ha):
"""Test the template for the max mireds."""
state = hass.states.get("light.test_template_light")
assert state is not None
assert state.attributes.get("max_mireds") == expected_max_mireds
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"expected_supports_transition,config_addon",
[
(True, {"template2": '"{{true}}"'}),
(True, {"template2": '"{{1 == 1}}"'}),
(False, {"template2": '"{{false}}"'}),
(False, {"template2": '"{{ none }}"'}),
(False, {"template2": '""'}),
(False, {"template2": '"None"'}),
],
)
@pytest.mark.parametrize(
"config",
[
"""{"light": {"platform": "template","lights": {"test_template_light": {
"value_template": "{{ 1 == 1 }}",
"turn_on": {"service": "light.turn_on","entity_id": "light.test_state"},
"turn_off": {"service": "light.turn_off","entity_id": "light.test_state"},
"set_temperature": {"service": "light.turn_on","data_template": {
"entity_id": "light.test_state","color_temp": "{{color_temp}}"}},
"supports_transition_template": template2
}}}}""",
],
)
async def test_supports_transition_template(
hass, expected_supports_transition, start_ha
):
"""Test the template for the supports transition."""
state = hass.states.get("light.test_template_light")
expected_value = 1
if expected_supports_transition is True:
expected_value = 0
assert state is not None
assert (
int(state.attributes.get("supported_features")) & SUPPORT_TRANSITION
) != expected_value
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"availability_template": "{{ is_state('availability_boolean.state', 'on') }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_available_template_with_entities(hass, start_ha):
"""Test availability templates with values from other entities."""
# When template returns true..
hass.states.async_set(_STATE_AVAILABILITY_BOOLEAN, STATE_ON)
await hass.async_block_till_done()
# Device State should not be unavailable
assert hass.states.get("light.test_template_light").state != STATE_UNAVAILABLE
# When Availability template returns false
hass.states.async_set(_STATE_AVAILABILITY_BOOLEAN, STATE_OFF)
await hass.async_block_till_done()
# device state should be unavailable
assert hass.states.get("light.test_template_light").state == STATE_UNAVAILABLE
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light": {
"availability_template": "{{ x - 12 }}",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
"set_level": {
"service": "light.turn_on",
"data_template": {
"entity_id": "light.test_state",
"brightness": "{{brightness}}",
},
},
}
},
}
},
],
)
async def test_invalid_availability_template_keeps_component_available(
hass, start_ha, caplog_setup_text
):
"""Test that an invalid availability keeps the device available."""
assert hass.states.get("light.test_template_light").state != STATE_UNAVAILABLE
assert ("UndefinedError: 'x' is undefined") in caplog_setup_text
@pytest.mark.parametrize("count,domain", [(1, light.DOMAIN)])
@pytest.mark.parametrize(
"config",
[
{
"light": {
"platform": "template",
"lights": {
"test_template_light_01": {
"unique_id": "not-so-unique-anymore",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
},
"test_template_light_02": {
"unique_id": "not-so-unique-anymore",
"turn_on": {
"service": "light.turn_on",
"entity_id": "light.test_state",
},
"turn_off": {
"service": "light.turn_off",
"entity_id": "light.test_state",
},
},
},
}
},
],
)
async def test_unique_id(hass, start_ha):
"""Test unique_id option only creates one light per id."""
assert len(hass.states.async_all("light")) == 1
| 35.069153 | 106 | 0.445396 | 4,325 | 51,727 | 5.073988 | 0.046243 | 0.062338 | 0.063796 | 0.075142 | 0.827569 | 0.805696 | 0.793757 | 0.762679 | 0.740852 | 0.720574 | 0 | 0.012145 | 0.406287 | 51,727 | 1,474 | 107 | 35.092944 | 0.702419 | 0.004311 | 0 | 0.562343 | 0 | 0 | 0.251281 | 0.050302 | 0 | 0 | 0 | 0 | 0.072803 | 1 | 0 | false | 0 | 0.004184 | 0 | 0.004184 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
1cca4720272551c22619089867d378cf6f46c54e | 172 | py | Python | src/realm/utils/__init__.py | orlevii/realm | e561ba09df4fbdc3bf60c8678462da4f55033894 | [
"MIT"
] | 3 | 2021-06-17T06:27:16.000Z | 2022-03-14T09:34:42.000Z | src/realm/utils/__init__.py | orlevii/realm | e561ba09df4fbdc3bf60c8678462da4f55033894 | [
"MIT"
] | null | null | null | src/realm/utils/__init__.py | orlevii/realm | e561ba09df4fbdc3bf60c8678462da4f55033894 | [
"MIT"
] | null | null | null | from concurrent.futures import Future
from typing import Iterable
def await_all(futures: Iterable[Future], timeout=None):
return [f.result(timeout) for f in futures]
| 24.571429 | 55 | 0.77907 | 25 | 172 | 5.32 | 0.68 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.139535 | 172 | 6 | 56 | 28.666667 | 0.898649 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.25 | false | 0 | 0.5 | 0.25 | 1 | 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 | 1 | 0 | 0 | 1 | 1 | 1 | 0 | 0 | 6 |
1ce893b14560fb036ffd45e0c1ab2b54f09b6e81 | 1,881 | py | Python | jobsdb/test.py | yc930401/jobsdb_crawler_with_scrapy | 76a1c5a2ea5db0cf6077eba271dc0b454fc0a956 | [
"MIT"
] | null | null | null | jobsdb/test.py | yc930401/jobsdb_crawler_with_scrapy | 76a1c5a2ea5db0cf6077eba271dc0b454fc0a956 | [
"MIT"
] | 1 | 2017-11-14T07:46:19.000Z | 2017-11-14T07:46:19.000Z | jobsdb/test.py | yc930401/jobsdb_crawler_with_scrapy | 76a1c5a2ea5db0cf6077eba271dc0b454fc0a956 | [
"MIT"
] | null | null | null | import requests
headers = {
'Accept':'text/html,application/xhtml+xml,application/xml;q=0.9,image/webp,*/*;q=0.8',
'Accept-Encoding':'gzip, deflate, sdch, br',
'Accept-Language':'en-US,en;q=0.8,fr;q=0.6',
'Cache-Control':'max-age=0',
'Connection':'keep-alive',
'Cookie':'NSC_wjq_kpctec.dpn_ttm2=14b5a3d9e9a059a69d137dda9e61d206db060add87cf365767e907ecf58f41a1dc04ea1d; AB.Key=5867; inLanding=https%3A%2F%2Fsg.jobsdb.com%2Fsg; spUID=15104618386979998c26ca1.a589b97e; ASP.NET_SessionId=tdvxfaaxvuzt1gb5la5p4ofl; JobsDB.IsAssignedDefaultSummaryMode2=0; OAID=794c986bf71181db07686d6a285f3bcf; s_vnum=1513149226337%26vn%3D5; __utmt=1; _gat_UA-2012489-10=1; RecentSearch=%7B%22JobFunction%22%3A%5B%223%22%2C%222%22%5D%7D; SolData.Search.Hash=5ae0df128702e7798456765dd486d8e8; SolData.SearchID=e26ed2fa-86b4-4a87-8c01-c079d841a302; JLP=True; HideShowBulletInfo=%7B%22DontShowPromoAgain%22%3Afalse%2C%22DefaultShow%22%3Anull%2C%22PromoBubbleShowTimes%22%3A2%7D; s_invisit=true; s_cc=true; s_sq=%5B%5BB%5D%5D; s_vi=[CS]v1|2D04A31605036C8E-40001193C0002B01[CE]; _ga=GA1.3.833630475.1510557226; _gid=GA1.3.1792777067.1510557227; JobsDB.IsCookieSupported=true; __utma=17118395.833630475.1510557226.1510567092.1510576396.5; __utmb=17118395.6.10.1510576396; __utmc=17118395; __utmz=17118395.1510557226.1.1.utmcsr=angryangmo.com|utmccn=(referral)|utmcmd=referral|utmcct=/uncategorized/10-top-job-portals-kick-career-singapore/; insdrSV=34; ins-gaSSId=37bf3748-65aa-a5d3-b4e4-617d440566a1_1510579997; current-currency=; scs=%7B%22t%22%3A1%7D',
'Host':'sg.jobsdb.com',
'Upgrade-Insecure-Requests':'1',
'User-Agent':'Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/58.0.3029.110 Safari/537.36'
}
html = requests.get('https://sg.jobsdb.com/sg/job-list/accounting/accountant/1?JSSRC=HPJC', headers=headers).text
print(html) | 117.5625 | 1,270 | 0.785221 | 265 | 1,881 | 5.483019 | 0.690566 | 0.005506 | 0.004129 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.263897 | 0.053163 | 1,881 | 16 | 1,271 | 117.5625 | 0.551937 | 0 | 0 | 0 | 0 | 0.285714 | 0.900106 | 0.652497 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.071429 | 0 | 0.071429 | 0.071429 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 1 | 1 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
1cf727efd31c88cffc120ef9a7c9dd522fb4cab8 | 34 | py | Python | cornac/models/baseline_only/__init__.py | carmanzhang/cornac | 215efd0ffa7b8ee1afe1ac6b5cc650ee6303ace3 | [
"Apache-2.0"
] | 597 | 2018-07-17T10:59:56.000Z | 2022-03-31T07:59:36.000Z | cornac/models/baseline_only/__init__.py | carmanzhang/cornac | 215efd0ffa7b8ee1afe1ac6b5cc650ee6303ace3 | [
"Apache-2.0"
] | 137 | 2018-10-12T10:52:11.000Z | 2022-03-04T15:26:49.000Z | cornac/models/baseline_only/__init__.py | carmanzhang/cornac | 215efd0ffa7b8ee1afe1ac6b5cc650ee6303ace3 | [
"Apache-2.0"
] | 112 | 2018-07-26T04:36:34.000Z | 2022-03-31T02:29:34.000Z | from .recom_bo import BaselineOnly | 34 | 34 | 0.882353 | 5 | 34 | 5.8 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.088235 | 34 | 1 | 34 | 34 | 0.935484 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
e810460fde7ac47d24af4230a96bb9099b8aed4f | 176 | py | Python | tasks/xdtjc/main.py | xmpx/keras-tcn | bc8cd6af9826efdc12b359d70d1e7678bf680269 | [
"MIT"
] | null | null | null | tasks/xdtjc/main.py | xmpx/keras-tcn | bc8cd6af9826efdc12b359d70d1e7678bf680269 | [
"MIT"
] | null | null | null | tasks/xdtjc/main.py | xmpx/keras-tcn | bc8cd6af9826efdc12b359d70d1e7678bf680269 | [
"MIT"
] | null | null | null | import numpy as np
x_train = np.load('/media/clwang/C60EA0300EA01C05/Users/clwang/Downloads/validation_x2.npy')
print(x_train.shape)
print(x_train.shape)
print(x_train.shape) | 25.142857 | 92 | 0.806818 | 29 | 176 | 4.724138 | 0.586207 | 0.175182 | 0.240876 | 0.350365 | 0.350365 | 0.350365 | 0.350365 | 0.350365 | 0 | 0 | 0 | 0.066667 | 0.0625 | 176 | 7 | 93 | 25.142857 | 0.763636 | 0 | 0 | 0.6 | 0 | 0 | 0.40113 | 0.40113 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.2 | 0 | 0.2 | 0.6 | 1 | 0 | 0 | null | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
e81d26dd4e0027c64adb3dec639d0c82ec2a6fbd | 26,939 | py | Python | tests/test_server_20d_client_authn.py | IdentityPython/idpy-oidc | 44f78f5f70d0c5ddc0108fa9a241c460179b53a8 | [
"Apache-2.0"
] | 1 | 2022-03-24T23:39:22.000Z | 2022-03-24T23:39:22.000Z | tests/test_server_20d_client_authn.py | IdentityPython/idpy-oidc | 44f78f5f70d0c5ddc0108fa9a241c460179b53a8 | [
"Apache-2.0"
] | null | null | null | tests/test_server_20d_client_authn.py | IdentityPython/idpy-oidc | 44f78f5f70d0c5ddc0108fa9a241c460179b53a8 | [
"Apache-2.0"
] | null | null | null | import base64
from unittest.mock import MagicMock
import pytest
from cryptojwt.jws.exception import NoSuitableSigningKeys
from cryptojwt.jwt import JWT
from cryptojwt.key_jar import KeyJar
from cryptojwt.key_jar import build_keyjar
from cryptojwt.utils import as_bytes
from cryptojwt.utils import as_unicode
from idpyoidc.defaults import JWT_BEARER
from idpyoidc.server import Server
from idpyoidc.server.client_authn import BearerBody
from idpyoidc.server.client_authn import BearerHeader
from idpyoidc.server.client_authn import ClientSecretBasic
from idpyoidc.server.client_authn import ClientSecretJWT
from idpyoidc.server.client_authn import ClientSecretPost
from idpyoidc.server.client_authn import JWSAuthnMethod
from idpyoidc.server.client_authn import PrivateKeyJWT
from idpyoidc.server.client_authn import basic_authn
from idpyoidc.server.client_authn import verify_client
from idpyoidc.server.exception import ClientAuthenticationError
from idpyoidc.server.exception import InvalidToken
from idpyoidc.server.oidc.authorization import Authorization
from idpyoidc.server.oidc.registration import Registration
from idpyoidc.server.oidc.token import Token
from idpyoidc.server.oidc.userinfo import UserInfo
from tests import SESSION_PARAMS
KEYDEFS = [
{"type": "RSA", "key": "", "use": ["sig"]},
{"type": "EC", "crv": "P-256", "use": ["sig"]},
]
KEYJAR = build_keyjar(KEYDEFS)
CONF = {
"issuer": "https://example.com/",
"grant_expires_in": 300,
"httpc_params": {"verify": False},
"endpoint": {
"token": {
"path": "token",
"class": Token,
"kwargs": {
"client_authn_method": [
"private_key_jwt",
"client_secret_jwt",
"client_secret_post",
"client_secret_basic",
]
},
},
"authorization": {
"path": "auth",
"class": Authorization,
"kwargs": {"client_authn_method": ["bearer_header", "none"]},
},
"registration": {"path": "registration", "class": Registration, "kwargs": {}},
"userinfo": {
"path": "user",
"class": UserInfo,
"kwargs": {"client_authn_method": ["bearer_body"]},
},
},
"template_dir": "template",
"keys": {
"private_path": "own/jwks.json",
"key_defs": KEYDEFS,
"uri_path": "static/jwks.json",
},
"claims_interface": {"class": "idpyoidc.server.session.claims.ClaimsInterface", "kwargs": {}},
"session_params": SESSION_PARAMS,
}
client_id = "client_id"
client_secret = "a_longer_client_secret"
# Need to add the client_secret as a symmetric key bound to the client_id
KEYJAR.add_symmetric(client_id, client_secret, ["sig"])
def get_client_id_from_token(endpoint_context, token, request=None):
if "client_id" in request:
if request["client_id"] == endpoint_context.registration_access_token[token]:
return request["client_id"]
return ""
class TestClientSecretBasic:
@pytest.fixture(autouse=True)
def setup(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.endpoint_context = server.endpoint_context
self.method = ClientSecretBasic(server.server_get)
def test_client_secret_basic(self):
_token = "{}:{}".format(client_id, client_secret)
token = as_unicode(base64.b64encode(as_bytes(_token)))
authz_token = "Basic {}".format(token)
assert self.method.is_usable(authorization_token=authz_token)
authn_info = self.method.verify(authorization_token=authz_token)
assert authn_info["client_id"] == client_id
def test_wrong_type(self):
assert self.method.is_usable(authorization_token="Foppa toffel") is False
def test_csb_wrong_secret(self):
_token = "{}:{}".format(client_id, "pillow")
token = as_unicode(base64.b64encode(as_bytes(_token)))
authz_token = "Basic {}".format(token)
assert self.method.is_usable(authorization_token=authz_token)
with pytest.raises(ClientAuthenticationError):
self.method.verify(authorization_token=authz_token)
class TestClientSecretPost:
@pytest.fixture(autouse=True)
def create_method(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.endpoint_context = server.endpoint_context
self.method = ClientSecretPost(server.server_get)
def test_client_secret_post(self):
request = {"client_id": client_id, "client_secret": client_secret}
assert self.method.is_usable(request=request)
authn_info = self.method.verify(request)
assert authn_info["client_id"] == client_id
def test_client_secret_post_wrong_secret(self):
request = {"client_id": client_id, "client_secret": "pillow"}
assert self.method.is_usable(request=request)
with pytest.raises(ClientAuthenticationError):
self.method.verify(request)
class TestClientSecretJWT:
@pytest.fixture(autouse=True)
def create_method(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.endpoint_context = server.endpoint_context
self.method = ClientSecretJWT(server.server_get)
def test_client_secret_jwt(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
_jwt.with_jti = True
_assertion = _jwt.pack({"aud": [CONF["issuer"]]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
assert self.method.is_usable(request=request)
authn_info = self.method.verify(request=request)
assert authn_info["client_id"] == client_id
assert "jwt" in authn_info
class TestPrivateKeyJWT:
@pytest.fixture(autouse=True)
def create_method(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.server = server
self.endpoint_context = server.endpoint_context
self.method = PrivateKeyJWT(server.server_get)
def test_private_key_jwt(self):
# Own dynamic keys
client_keyjar = build_keyjar(KEYDEFS)
# The servers keys
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
_jwks = client_keyjar.export_jwks()
self.endpoint_context.keyjar.import_jwks(_jwks, client_id)
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="RS256")
_jwt.with_jti = True
_assertion = _jwt.pack({"aud": [CONF["issuer"]]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
assert self.method.is_usable(request=request)
authn_info = self.method.verify(request=request)
assert authn_info["client_id"] == client_id
assert "jwt" in authn_info
def test_private_key_jwt_reusage_other_endpoint(self):
# Own dynamic keys
client_keyjar = build_keyjar(KEYDEFS)
# The servers keys
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
_jwks = client_keyjar.export_jwks()
self.endpoint_context.keyjar.import_jwks(_jwks, client_id)
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="RS256")
_jwt.with_jti = True
_assertion = _jwt.pack({"aud": [self.server.server_get("endpoint", "token").full_path]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
# This should be OK
assert self.method.is_usable(request=request)
self.method.verify(request=request, endpoint=self.server.server_get("endpoint", "token"))
# This should NOT be OK
with pytest.raises(InvalidToken):
self.method.verify(
request=request, endpoint=self.server.server_get("endpoint", "authorization")
)
# This should NOT be OK because this is the second time the token appears
with pytest.raises(InvalidToken):
self.method.verify(
request=request, endpoint=self.server.server_get("endpoint", "token")
)
def test_private_key_jwt_auth_endpoint(self):
# Own dynamic keys
client_keyjar = build_keyjar(KEYDEFS)
# The servers keys
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
_jwks = client_keyjar.export_jwks()
self.endpoint_context.keyjar.import_jwks(_jwks, client_id)
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="RS256")
_jwt.with_jti = True
_assertion = _jwt.pack(
{"aud": [self.server.server_get("endpoint", "authorization").full_path]}
)
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
assert self.method.is_usable(request=request)
authn_info = self.method.verify(
request=request,
endpoint=self.server.server_get("endpoint", "authorization"),
)
assert authn_info["client_id"] == client_id
assert "jwt" in authn_info
class TestBearerHeader:
@pytest.fixture(autouse=True)
def create_method(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.server = server
self.endpoint_context = server.endpoint_context
self.method = BearerHeader(server.server_get)
def test_bearerheader(self):
authorization_info = "Bearer 1234567890"
get_client_id_from_token = lambda *_: "client_id"
assert self.method.verify(
authorization_token=authorization_info,
get_client_id_from_token=get_client_id_from_token,
) == {"token": "1234567890", "method": "bearer_header", "client_id": "client_id"}
def test_bearerheader_wrong_type(self):
authorization_info = "Thrower 1234567890"
assert self.method.is_usable(authorization_token=authorization_info) is False
class TestBearerBody:
@pytest.fixture(autouse=True)
def create_method(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.server = server
self.endpoint_context = server.endpoint_context
self.method = BearerBody(server.server_get)
def test_bearer_body(self):
request = {"access_token": "1234567890"}
assert self.method.verify(request) == {"token": "1234567890", "method": "bearer_body"}
def test_bearer_body_no_token(self):
request = {}
with pytest.raises(ClientAuthenticationError):
self.method.verify(request=request)
class TestJWSAuthnMethod:
@pytest.fixture(autouse=True)
def create_method(self):
server = Server(conf=CONF, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.server = server
self.endpoint_context = server.endpoint_context
self.method = JWSAuthnMethod(server.server_get)
def test_jws_authn_method_wrong_key(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# Fake symmetric key
client_keyjar.add_symmetric("", "client_secret:client_secret", ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
_assertion = _jwt.pack({"aud": [CONF["issuer"]]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
with pytest.raises(NoSuitableSigningKeys):
self.method.verify(request=request, key_type="private_key")
def test_jws_authn_method_aud_iss(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
# Audience is OP issuer ID
aud = CONF["issuer"]
_assertion = _jwt.pack({"aud": [aud]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
assert self.method.verify(request=request, key_type="client_secret")
def test_jws_authn_method_aud_token_endpoint(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
# audience is OP token endpoint - that's OK
aud = "{}token".format(CONF["issuer"])
_assertion = _jwt.pack({"aud": [aud]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
assert self.method.verify(
request=request,
endpoint=self.server.server_get("endpoint", "token"),
key_type="client_secret",
)
def test_jws_authn_method_aud_not_me(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
# Other audiences not OK
aud = "https://example.org"
_assertion = _jwt.pack({"aud": [aud]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
with pytest.raises(InvalidToken):
self.method.verify(request=request, key_type="client_secret")
def test_jws_authn_method_aud_userinfo_endpoint(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
# audience is the OP - not specifically the user info endpoint
_assertion = _jwt.pack({"aud": [CONF["issuer"]]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
assert self.method.verify(
request=request,
endpoint=self.server.server_get("endpoint", "userinfo"),
key_type="client_secret",
)
def test_basic_auth():
_token = "{}:{}".format(client_id, client_secret)
token = as_unicode(base64.b64encode(as_bytes(_token)))
res = basic_authn("Basic {}".format(token))
assert res
def test_basic_auth_wrong_label():
_token = "{}:{}".format(client_id, client_secret)
token = as_unicode(base64.b64encode(as_bytes(_token)))
with pytest.raises(ClientAuthenticationError):
basic_authn("Expanded {}".format(token))
def test_basic_auth_wrong_token():
_token = "{}:{}".format(client_id, client_secret)
with pytest.raises(ValueError):
basic_authn("Basic {}".format(_token))
_token = "{}{}".format(client_id, client_secret)
token = as_unicode(base64.b64encode(as_bytes(_token)))
with pytest.raises(ValueError):
basic_authn("Basic {}".format(token))
class TestVerify:
@pytest.fixture(autouse=True)
def create_method(self):
self.server = Server(conf=CONF, keyjar=KEYJAR)
self.server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.endpoint_context = self.server.server_get("endpoint_context")
def test_verify_per_client(self):
self.server.endpoint_context.cdb[client_id]["client_authn_method"] = ["public"]
request = {"client_id": client_id}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "registration"),
)
assert res == {"method": "public", "client_id": client_id}
def test_verify_per_client_per_endpoint(self):
self.server.endpoint_context.cdb[client_id]["registration_endpoint_client_authn_method"] = [
"public"
]
self.server.endpoint_context.cdb[client_id]["token_endpoint_client_authn_method"] = [
"client_secret_post"
]
request = {"client_id": client_id}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "registration"),
)
assert res == {"method": "public", "client_id": client_id}
with pytest.raises(ClientAuthenticationError) as e:
verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "token"),
)
assert e.value.args[0] == "Failed to verify client"
request = {"client_id": client_id, "client_secret": client_secret}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "token"),
)
assert set(res.keys()) == {"method", "client_id"}
assert res["method"] == "client_secret_post"
def test_verify_client_client_secret_post(self):
request = {"client_id": client_id, "client_secret": client_secret}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "token"),
)
assert set(res.keys()) == {"method", "client_id"}
assert res["method"] == "client_secret_post"
def test_verify_client_jws_authn_method(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
# Audience is OP issuer ID
aud = "{}token".format(CONF["issuer"]) # aud == Token endpoint
_assertion = _jwt.pack({"aud": [aud]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
http_info = {"headers": {}}
res = verify_client(
self.endpoint_context,
request,
http_info=http_info,
endpoint=self.server.server_get("endpoint", "token"),
)
assert res["method"] == "client_secret_jwt"
assert res["client_id"] == "client_id"
def test_verify_client_bearer_body(self):
request = {"access_token": "1234567890", "client_id": client_id}
self.endpoint_context.registration_access_token["1234567890"] = client_id
res = verify_client(
self.endpoint_context,
request,
get_client_id_from_token=get_client_id_from_token,
endpoint=self.server.server_get("endpoint", "userinfo"),
)
assert set(res.keys()) == {"token", "method", "client_id"}
assert res["method"] == "bearer_body"
def test_verify_client_client_secret_post(self):
request = {"client_id": client_id, "client_secret": client_secret}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "token"),
)
assert set(res.keys()) == {"method", "client_id"}
assert res["method"] == "client_secret_post"
def test_verify_client_client_secret_basic(self):
_token = "{}:{}".format(client_id, client_secret)
token = as_unicode(base64.b64encode(as_bytes(_token)))
authz_token = "Basic {}".format(token)
http_info = {"headers": {"authorization": authz_token}}
res = verify_client(
self.endpoint_context,
request={},
http_info=http_info,
endpoint=self.server.server_get("endpoint", "token"),
)
assert set(res.keys()) == {"method", "client_id"}
assert res["method"] == "client_secret_basic"
def test_verify_client_bearer_header(self):
# A prerequisite for the get_client_id_from_token function
self.endpoint_context.registration_access_token["1234567890"] = client_id
token = "Bearer 1234567890"
http_info = {"headers": {"authorization": token}}
request = {"client_id": client_id}
res = verify_client(
self.endpoint_context,
request,
http_info=http_info,
get_client_id_from_token=get_client_id_from_token,
endpoint=self.server.server_get("endpoint", "authorization"),
)
assert set(res.keys()) == {"token", "method", "client_id"}
assert res["method"] == "bearer_header"
class TestVerify2:
@pytest.fixture(autouse=True)
def create_method(self):
self.server = Server(conf=CONF, keyjar=KEYJAR)
self.server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
self.endpoint_context = self.server.server_get("endpoint_context")
def test_verify_client_jws_authn_method(self):
client_keyjar = KeyJar()
client_keyjar.import_jwks(KEYJAR.export_jwks(private=True), CONF["issuer"])
# The only own key the client has a this point
client_keyjar.add_symmetric("", client_secret, ["sig"])
_jwt = JWT(client_keyjar, iss=client_id, sign_alg="HS256")
# Audience is OP issuer ID
aud = CONF["issuer"] + "token"
_assertion = _jwt.pack({"aud": [aud]})
request = {"client_assertion": _assertion, "client_assertion_type": JWT_BEARER}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "token"),
)
assert res["method"] == "client_secret_jwt"
assert res["client_id"] == "client_id"
def test_verify_client_bearer_body(self):
request = {"access_token": "1234567890", "client_id": client_id}
self.endpoint_context.registration_access_token["1234567890"] = client_id
res = verify_client(
self.endpoint_context,
request,
get_client_id_from_token=get_client_id_from_token,
endpoint=self.server.server_get("endpoint", "userinfo"),
)
assert set(res.keys()) == {"token", "method", "client_id"}
assert res["method"] == "bearer_body"
def test_verify_client_client_secret_post(self):
request = {"client_id": client_id, "client_secret": client_secret}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "token"),
)
assert set(res.keys()) == {"method", "client_id"}
assert res["method"] == "client_secret_post"
def test_verify_client_client_secret_basic(self):
_token = "{}:{}".format(client_id, client_secret)
token = as_unicode(base64.b64encode(as_bytes(_token)))
authz_token = "Basic {}".format(token)
http_info = {"headers": {"authorization": authz_token}}
res = verify_client(
self.endpoint_context,
{},
http_info=http_info,
endpoint=self.server.server_get("endpoint", "token"),
)
assert set(res.keys()) == {"method", "client_id"}
assert res["method"] == "client_secret_basic"
def test_verify_client_bearer_header(self):
# A prerequisite for the get_client_id_from_token function
self.endpoint_context.registration_access_token["1234567890"] = client_id
token = "Bearer 1234567890"
http_info = {"headers": {"authorization": token}}
request = {"client_id": client_id}
res = verify_client(
self.endpoint_context,
request,
http_info=http_info,
get_client_id_from_token=get_client_id_from_token,
endpoint=self.server.server_get("endpoint", "authorization"),
)
assert set(res.keys()) == {"token", "method", "client_id"}
assert res["method"] == "bearer_header"
def test_verify_client_authorization_none(self):
# This is when it's explicitly said that no client auth method is allowed
request = {"client_id": client_id}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "authorization"),
)
assert res["method"] == "none"
assert res["client_id"] == "client_id"
def test_verify_client_registration_public(self):
# This is when no special auth method is configured
request = {"redirect_uris": ["https://example.com/cb"], "client_id": "client_id"}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "registration"),
)
assert res == {"client_id": "client_id", "method": "public"}
def test_verify_client_registration_none(self):
# This is when no special auth method is configured
request = {"redirect_uris": ["https://example.com/cb"]}
res = verify_client(
self.endpoint_context,
request,
endpoint=self.server.server_get("endpoint", "registration"),
)
assert res == {"client_id": None, "method": "none"}
def test_client_auth_setup():
class Mock:
is_usable = MagicMock(return_value=True)
verify = MagicMock(return_value={"method": "custom", "client_id": client_id})
mock = Mock()
mock.tag = "mock"
conf = dict(CONF)
conf["client_authn_methods"] = {"custom": MagicMock(return_value=mock)}
conf["endpoint"]["registration"]["kwargs"]["client_authn_method"] = ["custom"]
server = Server(conf=conf, keyjar=KEYJAR)
server.endpoint_context.cdb[client_id] = {"client_secret": client_secret}
request = {"redirect_uris": ["https://example.com/cb"]}
res = verify_client(
server.endpoint_context, request, endpoint=server.server_get("endpoint", "registration")
)
assert res == {"client_id": "client_id", "method": "custom"}
mock.is_usable.assert_called_once()
mock.verify.assert_called_once()
| 38.539342 | 100 | 0.654219 | 3,111 | 26,939 | 5.372228 | 0.067502 | 0.06127 | 0.046072 | 0.027763 | 0.824388 | 0.772453 | 0.742655 | 0.710824 | 0.703345 | 0.683181 | 0 | 0.009658 | 0.22744 | 26,939 | 698 | 101 | 38.594556 | 0.793388 | 0.041872 | 0 | 0.598131 | 0 | 0 | 0.143561 | 0.015555 | 0 | 0 | 0 | 0 | 0.149533 | 1 | 0.08972 | false | 0 | 0.076636 | 0 | 0.192523 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
1c2a47d1801c0ef25460c345b1ab2ba43aef81e3 | 180 | py | Python | tests/test_utils.py | msonderegger/PolyglotDB | 583fd8ec14c2e34807b45b9f15fa19cffa130bfa | [
"MIT"
] | 25 | 2016-01-28T20:47:07.000Z | 2021-11-29T16:13:07.000Z | tests/test_utils.py | msonderegger/PolyglotDB | 583fd8ec14c2e34807b45b9f15fa19cffa130bfa | [
"MIT"
] | 120 | 2016-04-07T17:55:09.000Z | 2022-03-24T18:30:10.000Z | tests/test_utils.py | PhonologicalCorpusTools/PolyglotDB | 7640212c7062cf44ae911081241ce83a26ced2eb | [
"MIT"
] | 10 | 2015-12-03T20:06:58.000Z | 2021-02-11T03:02:48.000Z | from polyglotdb.utils import get_corpora_list
def test_corpora_list(acoustic_config):
corpora_list = get_corpora_list(acoustic_config)
assert 'acoustic' in corpora_list
| 22.5 | 52 | 0.816667 | 25 | 180 | 5.48 | 0.52 | 0.40146 | 0.20438 | 0.364964 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 180 | 7 | 53 | 25.714286 | 0.878205 | 0 | 0 | 0 | 0 | 0 | 0.044693 | 0 | 0 | 0 | 0 | 0 | 0.25 | 1 | 0.25 | false | 0 | 0.25 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 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 | 0 | 0 | 0 | 6 |
1c3c732fd1bf32628655f32cb83e5438752c6640 | 346 | py | Python | specification_data_files/www.amwa.tv_c0f7b64/block/989/artefacts/audio_track_layout.py | AMWA-TV/AS-11_UK_DPP_HD | 12e100a3de2f60592413a0d21f81f343505e0123 | [
"Apache-2.0"
] | 2 | 2020-02-11T12:55:47.000Z | 2021-07-03T07:04:09.000Z | specification_data_files/www.amwa.tv_c0f7b64/block/989/artefacts/audio_track_layout.py | AMWA-TV/AS-11_UK_DPP_HD | 12e100a3de2f60592413a0d21f81f343505e0123 | [
"Apache-2.0"
] | null | null | null | specification_data_files/www.amwa.tv_c0f7b64/block/989/artefacts/audio_track_layout.py | AMWA-TV/AS-11_UK_DPP_HD | 12e100a3de2f60592413a0d21f81f343505e0123 | [
"Apache-2.0"
] | 1 | 2019-07-14T18:26:16.000Z | 2019-07-14T18:26:16.000Z | CHECK( AS_11_Audio_Track_Layout in [Layout_EBU_R_48_2a,
Layout_EBU_R_123_4b,
Layout_EBU_R_123_4c,
Layout_EBU_R_123_16c,
Layout_EBU_R_123_16d,
Layout_EBU_R_123_16f] )
| 49.428571 | 59 | 0.424855 | 37 | 346 | 3.216216 | 0.459459 | 0.453782 | 0.504202 | 0.546218 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.179487 | 0.549133 | 346 | 6 | 60 | 57.666667 | 0.583333 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 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 | 6 |
1c6e5954ebc7844713b091ece04e0ba850fc09c0 | 32 | py | Python | base_astro_bot/utils/__init__.py | Mirdalan/base_astro_bot | 656ebd55c0f57fc18bf95227af9e20a4c1392489 | [
"MIT"
] | 2 | 2018-11-16T11:31:53.000Z | 2019-05-19T03:07:15.000Z | base_astro_bot/utils/__init__.py | Mirdalan/base_astro_bot | 656ebd55c0f57fc18bf95227af9e20a4c1392489 | [
"MIT"
] | null | null | null | base_astro_bot/utils/__init__.py | Mirdalan/base_astro_bot | 656ebd55c0f57fc18bf95227af9e20a4c1392489 | [
"MIT"
] | null | null | null | from .my_logger import MyLogger
| 16 | 31 | 0.84375 | 5 | 32 | 5.2 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.125 | 32 | 1 | 32 | 32 | 0.928571 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
98d7be3748ff7c9deca5f7ced478e02df458c63e | 35,853 | py | Python | sdk/storage/azure-storage-file-share/tests/test_directory_async.py | kazrael2119/azure-sdk-for-python | 485dd7b1b5ac41c1a5b9991e402b4035b55f437a | [
"MIT"
] | 1 | 2022-02-18T01:17:27.000Z | 2022-02-18T01:17:27.000Z | sdk/storage/azure-storage-file-share/tests/test_directory_async.py | kazrael2119/azure-sdk-for-python | 485dd7b1b5ac41c1a5b9991e402b4035b55f437a | [
"MIT"
] | null | null | null | sdk/storage/azure-storage-file-share/tests/test_directory_async.py | kazrael2119/azure-sdk-for-python | 485dd7b1b5ac41c1a5b9991e402b4035b55f437a | [
"MIT"
] | 1 | 2022-03-04T06:21:56.000Z | 2022-03-04T06:21:56.000Z | # coding: utf-8
# -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import unittest
import asyncio
import pytest
from datetime import datetime, timedelta
from azure.core.exceptions import ResourceNotFoundError, ResourceExistsError
from azure.core.pipeline.transport import AioHttpTransport
from multidict import CIMultiDict, CIMultiDictProxy
from azure.storage.fileshare import (
generate_share_sas,
NTFSAttributes,
ShareSasPermissions,
StorageErrorCode
)
from azure.storage.fileshare.aio import ShareDirectoryClient, ShareServiceClient
from settings.testcase import FileSharePreparer
from devtools_testutils.storage.aio import AsyncStorageTestCase
# ------------------------------------------------------------------------------
TEST_FILE_PERMISSIONS = 'O:S-1-5-21-2127521184-1604012920-1887927527-21560751G:S-1-5-21-2127521184-' \
'1604012920-1887927527-513D:AI(A;;FA;;;SY)(A;;FA;;;BA)(A;;0x1200a9;;;' \
'S-1-5-21-397955417-626881126-188441444-3053964)'
class AiohttpTestTransport(AioHttpTransport):
"""Workaround to vcrpy bug: https://github.com/kevin1024/vcrpy/pull/461
"""
async def send(self, request, **config):
response = await super(AiohttpTestTransport, self).send(request, **config)
if not isinstance(response.headers, CIMultiDictProxy):
response.headers = CIMultiDictProxy(CIMultiDict(response.internal_response.headers))
response.content_type = response.headers.get("content-type")
return response
class StorageDirectoryTest(AsyncStorageTestCase):
# --Helpers-----------------------------------------------------------------
async def _setup(self, storage_account_name, storage_account_key):
url = self.account_url(storage_account_name, "file")
credential = storage_account_key
self.fsc = ShareServiceClient(url, credential=credential, transport=AiohttpTestTransport())
self.share_name = self.get_resource_name('utshare')
if not self.is_playback():
try:
await self.fsc.create_share(self.share_name)
except:
pass
def _teardown(self, FILE_PATH):
if os.path.isfile(FILE_PATH):
try:
os.remove(FILE_PATH)
except:
pass
# --Test cases for directories ----------------------------------------------
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_create_directories_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
# Act
created = await share_client.create_directory('dir1')
# Assert
self.assertTrue(created)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_create_directories_with_metadata_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
metadata = {'hello': 'world', 'number': '42'}
# Act
directory = await share_client.create_directory('dir1', metadata=metadata)
# Assert
props = await directory.get_directory_properties()
self.assertDictEqual(props.metadata, metadata)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_create_directories_fail_on_exist_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
# Act
created = await share_client.create_directory('dir1')
with self.assertRaises(ResourceExistsError):
await share_client.create_directory('dir1')
# Assert
self.assertTrue(created)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_create_subdirectories_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
# Act
created = await directory.create_subdirectory('dir2')
# Assert
self.assertTrue(created)
self.assertEqual(created.directory_path, 'dir1/dir2')
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_create_subdirectories_with_metadata_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
metadata = {'hello': 'world', 'number': '42'}
# Act
created = await directory.create_subdirectory('dir2', metadata=metadata)
# Assert
self.assertTrue(created)
self.assertEqual(created.directory_path, 'dir1/dir2')
properties = await created.get_directory_properties()
self.assertEqual(properties.metadata, metadata)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_create_file_in_directory_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
file_data = b'12345678' * 1024
file_name = self.get_resource_name('file')
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
# Act
new_file = await directory.upload_file(file_name, file_data)
# Assert
file_content = await new_file.download_file()
file_content = await file_content.readall()
self.assertEqual(file_content, file_data)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_delete_file_in_directory_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
file_name = self.get_resource_name('file')
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
new_file = await directory.upload_file(file_name, "hello world")
# Act
deleted = await directory.delete_file(file_name)
# Assert
self.assertIsNone(deleted)
with self.assertRaises(ResourceNotFoundError):
await new_file.get_file_properties()
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_delete_subdirectories_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
await directory.create_subdirectory('dir2')
# Act
deleted = await directory.delete_subdirectory('dir2')
# Assert
self.assertIsNone(deleted)
subdir = directory.get_subdirectory_client('dir2')
with self.assertRaises(ResourceNotFoundError):
await subdir.get_directory_properties()
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_get_directory_properties_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
# Act
props = await directory.get_directory_properties()
# Assert
self.assertIsNotNone(props)
self.assertIsNotNone(props.etag)
self.assertIsNotNone(props.last_modified)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_get_directory_properties_with_snapshot_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
metadata = {"test1": "foo", "test2": "bar"}
directory = await share_client.create_directory('dir1', metadata=metadata)
snapshot1 = await share_client.create_snapshot()
metadata2 = {"test100": "foo100", "test200": "bar200"}
await directory.set_directory_metadata(metadata2)
# Act
share_client = self.fsc.get_share_client(self.share_name, snapshot=snapshot1)
snap_dir = share_client.get_directory_client('dir1')
props = await snap_dir.get_directory_properties()
# Assert
self.assertIsNotNone(props)
self.assertIsNotNone(props.etag)
self.assertIsNotNone(props.last_modified)
self.assertDictEqual(metadata, props.metadata)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_get_directory_metadata_with_snapshot_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
metadata = {"test1": "foo", "test2": "bar"}
directory = await share_client.create_directory('dir1', metadata=metadata)
snapshot1 = await share_client.create_snapshot()
metadata2 = {"test100": "foo100", "test200": "bar200"}
await directory.set_directory_metadata(metadata2)
# Act
share_client = self.fsc.get_share_client(self.share_name, snapshot=snapshot1)
snap_dir = share_client.get_directory_client('dir1')
snapshot_props = await snap_dir.get_directory_properties()
# Assert
self.assertIsNotNone(snapshot_props.metadata)
self.assertDictEqual(metadata, snapshot_props.metadata)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_get_directory_properties_with_non_existing_directory_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = share_client.get_directory_client('dir1')
# Act
with self.assertRaises(ResourceNotFoundError):
await directory.get_directory_properties()
# Assert
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_share_directory_exists_async(self, storage_account_name, storage_account_key):
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
directory2 = share_client.get_directory_client("dir2")
exists = await directory.exists()
exists2 = await directory2.exists()
self.assertTrue(exists)
self.assertFalse(exists2)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_directory_exists_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
# Act
exists = await directory.get_directory_properties()
# Assert
self.assertTrue(exists)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_directory_not_exists_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = share_client.get_directory_client('dir1')
# Act
with self.assertRaises(ResourceNotFoundError):
await directory.get_directory_properties()
# Assert
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_directory_parent_not_exists_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = share_client.get_directory_client('missing1/missing2')
# Act
with self.assertRaises(ResourceNotFoundError) as e:
await directory.get_directory_properties()
# Assert
self.assertEqual(e.exception.error_code, StorageErrorCode.parent_not_found)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_directory_exists_with_snapshot_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
snapshot = await share_client.create_snapshot()
await directory.delete_directory()
# Act
share_client = self.fsc.get_share_client(self.share_name, snapshot=snapshot)
snap_dir = share_client.get_directory_client('dir1')
exists = await snap_dir.get_directory_properties()
# Assert
self.assertTrue(exists)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_directory_not_exists_with_snapshot_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
snapshot = await share_client.create_snapshot()
directory = await share_client.create_directory('dir1')
# Act
share_client = self.fsc.get_share_client(self.share_name, snapshot=snapshot)
snap_dir = share_client.get_directory_client('dir1')
with self.assertRaises(ResourceNotFoundError):
await snap_dir.get_directory_properties()
# Assert
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_get_set_directory_metadata_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
metadata = {'hello': 'world', 'number': '43'}
# Act
await directory.set_directory_metadata(metadata)
props = await directory.get_directory_properties()
# Assert
self.assertDictEqual(props.metadata, metadata)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_set_directory_properties_with_empty_smb_properties(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory_client = await share_client.create_directory('dir1')
directory_properties_on_creation = await directory_client.get_directory_properties()
# Act
await directory_client.set_http_headers()
directory_properties = await directory_client.get_directory_properties()
# Assert
# Make sure set empty smb_properties doesn't change smb_properties
self.assertEqual(directory_properties_on_creation.creation_time,
directory_properties.creation_time)
self.assertEqual(directory_properties_on_creation.last_write_time,
directory_properties.last_write_time)
self.assertEqual(directory_properties_on_creation.permission_key,
directory_properties.permission_key)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_set_directory_properties_with_file_permission_key(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory_client = await share_client.create_directory('dir1')
directory_properties_on_creation = await directory_client.get_directory_properties()
permission_key = directory_properties_on_creation.permission_key
last_write_time = directory_properties_on_creation.last_write_time
creation_time = directory_properties_on_creation.creation_time
new_last_write_time = last_write_time + timedelta(hours=1)
new_creation_time = creation_time + timedelta(hours=1)
# Act
await directory_client.set_http_headers(file_attributes='None', file_creation_time=new_creation_time,
file_last_write_time=new_last_write_time,
permission_key=permission_key)
directory_properties = await directory_client.get_directory_properties()
# Assert
self.assertIsNotNone(directory_properties)
self.assertEqual(directory_properties.creation_time, new_creation_time)
self.assertEqual(directory_properties.last_write_time, new_last_write_time)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_list_subdirectories_and_files_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
await asyncio.gather(
directory.create_subdirectory("subdir1"),
directory.create_subdirectory("subdir2"),
directory.create_subdirectory("subdir3"),
directory.upload_file("file1", "data1"),
directory.upload_file("file2", "data2"),
directory.upload_file("file3", "data3"))
# Act
list_dir = []
async for d in directory.list_directories_and_files():
list_dir.append(d)
# Assert
self.assertEqual(len(list_dir), 6)
self.assertEqual(len(list_dir), 6)
self.assertEqual(list_dir[0]['name'], 'subdir1')
self.assertEqual(list_dir[0]['is_directory'], True)
self.assertEqual(list_dir[1]['name'], 'subdir2')
self.assertEqual(list_dir[1]['is_directory'], True)
self.assertEqual(list_dir[2]['name'], 'subdir3')
self.assertEqual(list_dir[2]['is_directory'], True)
self.assertEqual(list_dir[3]['name'], 'file1')
self.assertEqual(list_dir[3]['is_directory'], False)
self.assertEqual(list_dir[3]['size'], 5)
self.assertEqual(list_dir[4]['name'], 'file2')
self.assertEqual(list_dir[4]['is_directory'], False)
self.assertEqual(list_dir[4]['size'], 5)
self.assertEqual(list_dir[5]['name'], 'file3')
self.assertEqual(list_dir[5]['is_directory'], False)
self.assertEqual(list_dir[5]['size'], 5)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_list_subdirectories_and_files_include_other_data_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
await asyncio.gather(
directory.create_subdirectory("subdir1"),
directory.create_subdirectory("subdir2"),
directory.create_subdirectory("subdir3"),
directory.upload_file("file1", "data1"),
directory.upload_file("file2", "data2"),
directory.upload_file("file3", "data3"))
# Act
list_dir = []
async for d in directory.list_directories_and_files(include=["timestamps", "Etag", "Attributes", "PermissionKey"]):
list_dir.append(d)
self.assertEqual(len(list_dir), 6)
self.assertIsNotNone(list_dir[0].etag)
self.assertIsNotNone(list_dir[1].file_attributes)
self.assertIsNotNone(list_dir[1].last_access_time)
self.assertIsNotNone(list_dir[1].last_write_time)
self.assertIsNotNone(list_dir[2].change_time)
self.assertIsNotNone(list_dir[2].creation_time)
self.assertIsNotNone(list_dir[2].file_id)
try:
await share_client.delete_share()
except:
pass
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_list_subdirectories_and_files_include_extended_info_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
await asyncio.gather(
directory.create_subdirectory("subdir1"))
# Act
list_dir = []
async for d in directory.list_directories_and_files(include_extended_info=True):
list_dir.append(d)
self.assertEqual(len(list_dir), 1)
self.assertIsNotNone(list_dir[0].file_id)
self.assertIsNone(list_dir[0].file_attributes)
self.assertIsNone(list_dir[0].last_access_time)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_list_subdirectories_and_files_with_prefix_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
await asyncio.gather(
directory.create_subdirectory("subdir1"),
directory.create_subdirectory("subdir2"),
directory.create_subdirectory("subdir3"),
directory.upload_file("file1", "data1"),
directory.upload_file("file2", "data2"),
directory.upload_file("file3", "data3"))
# Act
list_dir = []
async for d in directory.list_directories_and_files(name_starts_with="sub"):
list_dir.append(d)
# Assert
self.assertEqual(len(list_dir), 3)
self.assertEqual(list_dir[0]['name'], 'subdir1')
self.assertEqual(list_dir[0]['is_directory'], True)
self.assertEqual(list_dir[1]['name'], 'subdir2')
self.assertEqual(list_dir[1]['is_directory'], True)
self.assertEqual(list_dir[2]['name'], 'subdir3')
self.assertEqual(list_dir[2]['is_directory'], True)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_list_subdirectories_and_files_with_snapshot_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
await asyncio.gather(
directory.create_subdirectory("subdir1"),
directory.create_subdirectory("subdir2"),
directory.upload_file("file1", "data1"))
snapshot = await share_client.create_snapshot()
await asyncio.gather(
directory.create_subdirectory("subdir3"),
directory.upload_file("file2", "data2"),
directory.upload_file("file3", "data3"))
share_client = self.fsc.get_share_client(self.share_name, snapshot=snapshot)
snapshot_dir = share_client.get_directory_client('dir1')
# Act
list_dir = []
async for d in snapshot_dir.list_directories_and_files():
list_dir.append(d)
# Assert
self.assertEqual(len(list_dir), 3)
self.assertEqual(list_dir[0]['name'], 'subdir1')
self.assertEqual(list_dir[0]['is_directory'], True)
self.assertEqual(list_dir[1]['name'], 'subdir2')
self.assertEqual(list_dir[1]['is_directory'], True)
self.assertEqual(list_dir[2]['name'], 'file1')
self.assertEqual(list_dir[2]['is_directory'], False)
self.assertEqual(list_dir[2]['size'], 5)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_list_nested_subdirectories_and_files_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
subdir = await directory.create_subdirectory("subdir1")
await subdir.create_subdirectory("subdir2")
await subdir.create_subdirectory("subdir3")
await asyncio.gather(
directory.upload_file("file1", "data1"),
subdir.upload_file("file2", "data2"),
subdir.upload_file("file3", "data3"))
# Act
list_dir = []
async for d in directory.list_directories_and_files():
list_dir.append(d)
# Assert
self.assertEqual(len(list_dir), 2)
self.assertEqual(list_dir[0]['name'], 'subdir1')
self.assertEqual(list_dir[0]['is_directory'], True)
self.assertEqual(list_dir[1]['name'], 'file1')
self.assertEqual(list_dir[1]['is_directory'], False)
self.assertEqual(list_dir[1]['size'], 5)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_delete_directory_with_existing_share_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
# Act
deleted = await directory.delete_directory()
# Assert
self.assertIsNone(deleted)
with self.assertRaises(ResourceNotFoundError):
await directory.get_directory_properties()
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_delete_directory_with_non_existing_directory_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = share_client.get_directory_client('dir1')
# Act
with self.assertRaises(ResourceNotFoundError):
await directory.delete_directory()
# Assert
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_get_directory_properties_server_encryption_async(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
directory = await share_client.create_directory('dir1')
# Act
props = await directory.get_directory_properties()
# Assert
self.assertIsNotNone(props)
self.assertIsNotNone(props.etag)
self.assertIsNotNone(props.last_modified)
self.assertTrue(props.server_encrypted)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
source_directory = await share_client.create_directory('dir1')
# Act
new_directory = await source_directory.rename_directory('dir2')
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_different_directory(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
parent_source_directory = await share_client.create_directory('dir1')
source_directory = await parent_source_directory.create_subdirectory('sub1')
dest_parent_directory = await share_client.create_directory('dir2')
# Act
new_directory_path = dest_parent_directory.directory_path + '/sub2'
new_directory = await source_directory.rename_directory(new_directory_path)
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_ignore_readonly(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
source_directory = await share_client.create_directory('dir1')
dest_directory = await share_client.create_directory('dir2')
dest_file = dest_directory.get_file_client('test')
file_attributes = NTFSAttributes(read_only=True)
await dest_file.create_file(1024, file_attributes=file_attributes)
# Act
new_directory = await source_directory.rename_directory(
dest_directory.directory_path + '/' + dest_file.file_name,
overwrite=True, ignore_read_only=True)
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
self.assertTrue(props.is_directory)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_file_permission(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
file_permission_key = await share_client.create_permission_for_share(TEST_FILE_PERMISSIONS)
source_directory = await share_client.create_directory('dir1')
# Act
new_directory = await source_directory.rename_directory('dir2', file_permission=TEST_FILE_PERMISSIONS)
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
self.assertEqual(file_permission_key, props.permission_key)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_preserve_permission(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
source_directory = await share_client.create_directory('dir1', file_permission=TEST_FILE_PERMISSIONS)
source_props = await source_directory.get_directory_properties()
source_permission_key = source_props.permission_key
# Act
new_directory = await source_directory.rename_directory('dir2', file_permission='preserve')
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
self.assertEqual(source_permission_key, props.permission_key)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_smb_properties(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
source_directory = await share_client.create_directory('dir1')
file_attributes = NTFSAttributes(read_only=True, directory=True)
file_creation_time = datetime(2022, 1, 26, 10, 9, 30, 500000)
file_last_write_time = datetime(2022, 1, 26, 10, 14, 30, 500000)
# Act
new_directory = await source_directory.rename_directory(
'dir2',
file_attributes=file_attributes,
file_creation_time=file_creation_time,
file_last_write_time=file_last_write_time)
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
self.assertTrue(props.is_directory)
self.assertEqual(str(file_attributes), props.file_attributes.replace(' ', ''))
self.assertEqual(file_creation_time, props.creation_time)
self.assertEqual(file_last_write_time, props.last_write_time)
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_dest_lease(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
source_directory = await share_client.create_directory('dir1')
dest_directory = await share_client.create_directory('dir2')
dest_file = await dest_directory.upload_file('test', b'Hello World')
lease = await dest_file.acquire_lease()
# Act
new_directory = await source_directory.rename_directory(
dest_directory.directory_path + '/' + dest_file.file_name,
overwrite=True, lease=lease)
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
self.assertTrue(props.is_directory)
@pytest.mark.live_test_only
@FileSharePreparer()
@AsyncStorageTestCase.await_prepared_test
async def test_rename_directory_share_sas(self, storage_account_name, storage_account_key):
# Arrange
await self._setup(storage_account_name, storage_account_key)
share_client = self.fsc.get_share_client(self.share_name)
token = generate_share_sas(
share_client.account_name,
share_client.share_name,
share_client.credential.account_key,
expiry=datetime.utcnow() + timedelta(hours=1),
permission=ShareSasPermissions(read=True, write=True))
source_directory = ShareDirectoryClient(
self.account_url(storage_account_name, 'file'),
share_client.share_name, 'dir1',
credential=token)
await source_directory.create_directory()
# Act
new_directory = await source_directory.rename_directory('dir2' + '?' + token)
# Assert
props = await new_directory.get_directory_properties()
self.assertIsNotNone(props)
# ------------------------------------------------------------------------------
| 42.937725 | 127 | 0.701392 | 3,982 | 35,853 | 5.954545 | 0.072325 | 0.0927 | 0.054405 | 0.081186 | 0.828814 | 0.793977 | 0.762557 | 0.714352 | 0.703597 | 0.6796 | 0 | 0.014451 | 0.202856 | 35,853 | 834 | 128 | 42.989209 | 0.815185 | 0.040471 | 0 | 0.625219 | 0 | 0.003503 | 0.038568 | 0.005514 | 0 | 0 | 0.000233 | 0 | 0.196147 | 1 | 0.001751 | false | 0.005254 | 0.019264 | 0 | 0.02627 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
98e7466c7a926a61127a8340f7498fb7da797859 | 25 | py | Python | package/subpackage1/__init__.py | jonathanyeh0723/python-tricks | 434665466babe09e7ad1c181b3a7b8e159a035f1 | [
"Apache-2.0"
] | null | null | null | package/subpackage1/__init__.py | jonathanyeh0723/python-tricks | 434665466babe09e7ad1c181b3a7b8e159a035f1 | [
"Apache-2.0"
] | null | null | null | package/subpackage1/__init__.py | jonathanyeh0723/python-tricks | 434665466babe09e7ad1c181b3a7b8e159a035f1 | [
"Apache-2.0"
] | null | null | null | from .moduleX import Cat
| 12.5 | 24 | 0.8 | 4 | 25 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.16 | 25 | 1 | 25 | 25 | 0.952381 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
98ebd37f8be305e2568571bd777552005e914b09 | 28,636 | py | Python | sdk/communication/azure-communication-chat/tests/test_chat_thread_client.py | GoWang/azure-sdk-for-python | f241e3734a50953c2a37c10d2d84eb4c013b3ba0 | [
"MIT"
] | null | null | null | sdk/communication/azure-communication-chat/tests/test_chat_thread_client.py | GoWang/azure-sdk-for-python | f241e3734a50953c2a37c10d2d84eb4c013b3ba0 | [
"MIT"
] | null | null | null | sdk/communication/azure-communication-chat/tests/test_chat_thread_client.py | GoWang/azure-sdk-for-python | f241e3734a50953c2a37c10d2d84eb4c013b3ba0 | [
"MIT"
] | null | null | null | # -------------------------------------------------------------------------
# Copyright (c) Microsoft Corporation. All rights reserved.
# Licensed under the MIT License. See License.txt in the project root for
# license information.
# --------------------------------------------------------------------------
import unittest
import time
from datetime import datetime
from msrest.serialization import TZ_UTC
from azure.core.credentials import AccessToken
from azure.core.exceptions import HttpResponseError
from azure.communication.chat import (
ChatThreadClient,
ChatParticipant,
ChatMessageType
)
from azure.communication.chat._shared.models import(
CommunicationUserIdentifier
)
from unittest_helpers import mock_response
try:
from unittest.mock import Mock, patch
except ImportError: # python < 3.3
from mock import Mock, patch # type: ignore
def _convert_datetime_to_utc_int(input):
epoch = time.mktime(datetime(1970, 1, 1).timetuple())
input_datetime_as_int = epoch - time.mktime(input.timetuple())
return input_datetime_as_int
class TestChatThreadClient(unittest.TestCase):
@classmethod
@patch('azure.communication.identity._shared.user_credential.CommunicationTokenCredential')
def setUpClass(cls, credential):
credential.get_token = Mock(return_value=AccessToken(
"some_token", _convert_datetime_to_utc_int(datetime.now().replace(tzinfo=TZ_UTC))
))
TestChatThreadClient.credential = credential
def test_update_topic(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=204)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
topic = "update topic"
try:
chat_thread_client.update_topic(topic=topic)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
def test_send_message(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
raised = False
def mock_send(*_, **__):
return mock_response(status_code=201, json_payload={"id": message_id})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
create_message_result = None
try:
content='hello world'
sender_display_name='sender name'
create_message_result = chat_thread_client.send_message(
content=content,
sender_display_name=sender_display_name)
create_message_result_id = create_message_result.id
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
assert create_message_result_id == message_id
def test_send_message_w_type(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
raised = False
message_str = "Hi I am Bob."
chat_message_types = [ChatMessageType.TEXT, ChatMessageType.HTML, "text", "html"]
for chat_message_type in chat_message_types:
def mock_send(*_, **__):
return mock_response(status_code=201, json_payload={
"id": message_id,
"type": chat_message_type,
"sequenceId": "3",
"version": message_id,
"content": {
"message": message_str,
"topic": "Lunch Chat thread",
"participants": [
{
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b",
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
],
"initiator": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"
},
"senderDisplayName": "Bob",
"createdOn": "2021-01-27T01:37:33Z",
"senderId": "8:acs:46849534-eb08-4ab7-bde7-c36928cd1547_00000007-e155-1f06-1db7-3a3a0d00004b"
})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id,
transport=Mock(send=mock_send))
try:
content='hello world'
sender_display_name='sender name'
create_message_result = chat_thread_client.send_message(
content=content,
chat_message_type=chat_message_type,
sender_display_name=sender_display_name)
create_message_result_id = create_message_result.id
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
assert create_message_result_id == message_id
def test_send_message_w_invalid_type_throws_error(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
raised = False
message_str = "Hi I am Bob."
# the payload is irrelevant - it'll fail before
def mock_send(*_, **__):
return mock_response(status_code=201, json_payload={
"id": message_id
})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
create_message_result = None
chat_message_types = [ChatMessageType.PARTICIPANT_ADDED, ChatMessageType.PARTICIPANT_REMOVED,
ChatMessageType.TOPIC_UPDATED, "participant_added", "participant_removed", "topic_updated",
"ChatMessageType.TEXT", "ChatMessageType.HTML",
"ChatMessageType.PARTICIPANT_ADDED", "ChatMessageType.PARTICIPANT_REMOVED",
"ChatMessageType.TOPIC_UPDATED"]
for chat_message_type in chat_message_types:
try:
content='hello world'
sender_display_name='sender name'
create_message_result = chat_thread_client.send_message(
content=content,
chat_message_type=chat_message_type,
sender_display_name=sender_display_name)
except:
raised = True
self.assertTrue(raised, 'Expected is excpetion raised')
def test_get_message(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
raised = False
message_str = "Hi I am Bob."
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={
"id": message_id,
"type": "text",
"sequenceId": "3",
"version": message_id,
"content": {
"message": message_str,
"topic": "Lunch Chat thread",
"participants": [
{
"communicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
],
"initiatorCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}}
},
"senderDisplayName": "Bob",
"createdOn": "2021-01-27T01:37:33Z",
"senderCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"deletedOn": "2021-01-27T01:37:33Z",
"editedOn": "2021-01-27T01:37:33Z"
})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
message = None
try:
message = chat_thread_client.get_message(message_id)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
assert message.id == message_id
assert message.content.message == message_str
assert message.type == ChatMessageType.TEXT
assert len(message.content.participants) > 0
def test_list_messages(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
message_str = "Hi I am Bob."
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={"value": [{
"id": message_id,
"type": "text",
"sequenceId": "3",
"version": message_id,
"content": {
"message": message_str,
"topic": "Lunch Chat thread",
"participants": [
{
"communicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
],
"initiatorCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}}
},
"senderDisplayName": "Bob",
"createdOn": "2021-01-27T01:37:33Z",
"senderCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"deletedOn": "2021-01-27T01:37:33Z",
"editedOn": "2021-01-27T01:37:33Z"
}]})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
chat_messages = None
try:
chat_messages = chat_thread_client.list_messages(results_per_page=1)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
for chat_message in chat_messages.by_page():
l = list(chat_message)
assert len(l) == 1
assert l[0].id == message_id
def test_list_messages_with_start_time(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
raised = False
message_id = '1596823919339'
message_str = "Hi I am Bob."
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={
"value": [
{
"id": message_id,
"type": "text",
"sequenceId": "2",
"version": message_id,
"content": {
"message": message_str,
"topic": "Lunch Chat thread",
"participants": [
{
"communicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
],
"initiatorCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}}
},
"senderDisplayName": "Bob",
"createdOn": "2021-01-27T01:37:33Z",
"senderCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"deletedOn": "2021-01-27T01:37:33Z",
"editedOn": "2021-01-27T01:37:33Z"
},
{
"id": message_id,
"type": "text",
"sequenceId": "3",
"version": message_id,
"content": {
"message": message_str,
"topic": "Lunch Chat thread",
"participants": [
{
"communicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
],
"initiatorCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}}
},
"senderDisplayName": "Bob",
"createdOn": "2021-01-27T01:37:33Z",
"senderCommunicationIdentifier": {"rawId": "string", "communicationUser": {
"id": "8:acs:8540c0de-899f-5cce-acb5-3ec493af3800_0e59221d-0c1d-46ae-9544-c963ce56c10b"}},
"deletedOn": "2021-01-27T01:37:33Z",
"editedOn": "2021-01-27T01:37:33Z"
}
]})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
chat_messages = None
try:
chat_messages = chat_thread_client.list_messages(
start_time=datetime(2020, 8, 17, 18, 0, 0)
)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
for chat_message in chat_messages.by_page():
l = list(chat_message)
assert len(l) == 2
def test_update_message(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
raised = False
def mock_send(*_, **__):
return mock_response(status_code=204)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
try:
content = "updated message content"
chat_thread_client.update_message(message_id, content=content)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
def test_delete_message(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id='1596823919339'
raised = False
def mock_send(*_, **__):
return mock_response(status_code=204)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
try:
chat_thread_client.delete_message(message_id)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
def test_list_participants(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
participant_id="8:acs:57b9bac9-df6c-4d39-a73b-26e944adf6ea_9b0110-08007f1041"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={"value": [
{
"communicationIdentifier": {
"rawId": participant_id,
"communicationUser": {
"id": participant_id
}
},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
]})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
chat_thread_participants = None
try:
chat_thread_participants = chat_thread_client.list_participants()
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
for chat_thread_participant_page in chat_thread_participants.by_page():
l = list(chat_thread_participant_page)
assert len(l) == 1
l[0].identifier.properties['id'] = participant_id
def test_list_participants_with_results_per_page(self):
thread_id = "19:81181a8abbf54b5695f87a0042ddcba9@thread.v2"
participant_id_1 = "8:acs:9b665d53-8164-4923-ad5d-5e983b07d2e7_00000006-5399-552c-b274-5a3a0d0000dc"
participant_id_2 = "8:acs:9b665d53-8164-4923-ad5d-5e983b07d2e7_00000006-9d32-35c9-557d-5a3a0d0002f1"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={
"value": [
{
"communicationIdentifier": {
"rawId": participant_id_1,
"communicationUser": {
"id": participant_id_1
}
},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
},
{
"communicationIdentifier": {
"rawId": participant_id_2,
"communicationUser": {
"id": participant_id_2
}
},
"displayName": "Bob",
"shareHistoryTime": "2020-10-30T10:50:50Z"
}
]})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id,
transport=Mock(send=mock_send))
chat_thread_participants = None
try:
chat_thread_participants = chat_thread_client.list_participants(results_per_page=2)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
for chat_thread_participant_page in chat_thread_participants.by_page():
l = list(chat_thread_participant_page)
assert len(l) == 2
def test_add_participants(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
new_participant_id="8:acs:57b9bac9-df6c-4d39-a73b-26e944adf6ea_9b0110-08007f1041"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=201)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
new_participant = ChatParticipant(
identifier=CommunicationUserIdentifier(new_participant_id),
display_name='name',
share_history_time=datetime.utcnow())
participants = [new_participant]
try:
result = chat_thread_client.add_participants(participants)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
self.assertTrue(len(result) == 0)
def test_add_participants_w_failed_participants_returns_nonempty_list(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
new_participant_id="8:acs:57b9bac9-df6c-4d39-a73b-26e944adf6ea_9b0110-08007f1041"
raised = False
error_message = "some error message"
def mock_send(*_, **__):
return mock_response(status_code=201,json_payload={
"invalidParticipants": [
{
"code": "string",
"message": error_message,
"target": new_participant_id,
"details": []
}
]
})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
new_participant = ChatParticipant(
identifier=CommunicationUserIdentifier(new_participant_id),
display_name='name',
share_history_time=datetime.utcnow())
participants = [new_participant]
try:
result = chat_thread_client.add_participants(participants)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
self.assertTrue(len(result) == 1)
failed_participant = result[0][0]
communication_error = result[0][1]
self.assertEqual(new_participant.identifier.properties['id'], failed_participant.identifier.properties['id'])
self.assertEqual(new_participant.display_name, failed_participant.display_name)
self.assertEqual(new_participant.share_history_time, failed_participant.share_history_time)
self.assertEqual(error_message, communication_error.message)
def test_remove_participant(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
participant_id="8:acs:57b9bac9-df6c-4d39-a73b-26e944adf6ea_9b0110-08007f1041"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=204)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
try:
chat_thread_client.remove_participant(identifier=CommunicationUserIdentifier(participant_id))
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
def test_send_typing_notification(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
try:
chat_thread_client.send_typing_notification()
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
def test_send_read_receipt(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id="1596823919339"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200)
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
try:
chat_thread_client.send_read_receipt(message_id)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
def test_list_read_receipts(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id="1596823919339"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={
"value": [
{
"chatMessageId": message_id,
"senderCommunicationIdentifier": {
"rawId": "string",
"communicationUser": {
"id": "string"
}
}
}
]
})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
read_receipts = None
try:
read_receipts = chat_thread_client.list_read_receipts()
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
for read_receipt_page in read_receipts.by_page():
l = list(read_receipt_page)
assert len(l) == 1
def test_list_read_receipts_with_results_per_page(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
message_id_1="1596823919339"
message_id_2="1596823919340"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={
"value": [
{
"chatMessageId": message_id_1,
"senderCommunicationIdentifier": {
"rawId": "string",
"communicationUser": {
"id": "string"
}
}
},
{
"chatMessageId": message_id_2,
"senderCommunicationIdentifier": {
"rawId": "string",
"communicationUser": {
"id": "string"
}
}
}
]})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
read_receipts = None
try:
read_receipts = chat_thread_client.list_read_receipts(results_per_page=2)
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
for read_receipt_page in read_receipts.by_page():
l = list(read_receipt_page)
assert len(l) == 2
def test_get_properties(self):
thread_id = "19:bcaebfba0d314c2aa3e920d38fa3df08@thread.v2"
raised = False
def mock_send(*_, **__):
return mock_response(status_code=200, json_payload={
"id": thread_id,
"topic": "Lunch Chat thread",
"createdOn": "2020-10-30T10:50:50Z",
"deletedOn": "2020-10-30T10:50:50Z",
"createdByCommunicationIdentifier": {"rawId": "string", "communicationUser": {"id": "string"}}
})
chat_thread_client = ChatThreadClient("https://endpoint", TestChatThreadClient.credential, thread_id, transport=Mock(send=mock_send))
get_thread_result = None
try:
get_thread_result = chat_thread_client.get_properties()
except:
raised = True
self.assertFalse(raised, 'Expected is no excpetion raised')
assert get_thread_result.id == thread_id
if __name__ == '__main__':
unittest.main()
| 43.519757 | 141 | 0.552486 | 2,504 | 28,636 | 6.057508 | 0.102636 | 0.030063 | 0.040084 | 0.017537 | 0.800237 | 0.791469 | 0.786392 | 0.785338 | 0.766878 | 0.743803 | 0 | 0.093382 | 0.347814 | 28,636 | 657 | 142 | 43.585997 | 0.718783 | 0.012956 | 0 | 0.685817 | 0 | 0.030521 | 0.231526 | 0.111127 | 0 | 0 | 0 | 0 | 0.070018 | 1 | 0.071813 | false | 0 | 0.021544 | 0.034111 | 0.131059 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
c710ac9f06f33dc09ecafe89d21e3690a1b59b4a | 47 | py | Python | trainer/__init__.py | rioyokotalab/ecl-isvr | ae274b1b81b1d1c10db008140c477f5893a0c1c3 | [
"BSD-4-Clause-UC"
] | null | null | null | trainer/__init__.py | rioyokotalab/ecl-isvr | ae274b1b81b1d1c10db008140c477f5893a0c1c3 | [
"BSD-4-Clause-UC"
] | null | null | null | trainer/__init__.py | rioyokotalab/ecl-isvr | ae274b1b81b1d1c10db008140c477f5893a0c1c3 | [
"BSD-4-Clause-UC"
] | 2 | 2021-09-30T02:13:40.000Z | 2021-12-14T07:33:28.000Z | #! -*- coding: utf-8
from .trainers import *
| 15.666667 | 24 | 0.595745 | 6 | 47 | 4.666667 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.027027 | 0.212766 | 47 | 2 | 25 | 23.5 | 0.72973 | 0.404255 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
c715fb2ee19fc8f93f02932b2b55dcc88292bebe | 41,229 | py | Python | tests/unit/test_instance.py | asthamohta/python-spanner | 321bc7faf364ad423da08ae4e2c0d6f76834dc09 | [
"Apache-2.0"
] | 49 | 2020-02-06T17:36:32.000Z | 2022-03-31T05:32:29.000Z | tests/unit/test_instance.py | asthamohta/python-spanner | 321bc7faf364ad423da08ae4e2c0d6f76834dc09 | [
"Apache-2.0"
] | 417 | 2020-01-31T23:12:28.000Z | 2022-03-30T22:42:11.000Z | tests/unit/test_instance.py | asthamohta/python-spanner | 321bc7faf364ad423da08ae4e2c0d6f76834dc09 | [
"Apache-2.0"
] | 46 | 2020-01-31T22:54:25.000Z | 2022-03-29T12:04:55.000Z | # Copyright 2016 Google LLC All rights reserved.
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import unittest
import mock
class TestInstance(unittest.TestCase):
PROJECT = "project"
PARENT = "projects/" + PROJECT
INSTANCE_ID = "instance-id"
INSTANCE_NAME = PARENT + "/instances/" + INSTANCE_ID
CONFIG_NAME = "configuration-name"
LOCATION = "projects/" + PROJECT + "/locations/" + CONFIG_NAME
DISPLAY_NAME = "display_name"
NODE_COUNT = 5
PROCESSING_UNITS = 5000
OP_ID = 8915
OP_NAME = "operations/projects/%s/instances/%soperations/%d" % (
PROJECT,
INSTANCE_ID,
OP_ID,
)
TABLE_ID = "table_id"
TABLE_NAME = INSTANCE_NAME + "/tables/" + TABLE_ID
TIMEOUT_SECONDS = 1
DATABASE_ID = "database_id"
DATABASE_NAME = "%s/databases/%s" % (INSTANCE_NAME, DATABASE_ID)
LABELS = {"test": "true"}
FIELD_MASK = ["config", "display_name", "processing_units", "labels"]
def _getTargetClass(self):
from google.cloud.spanner_v1.instance import Instance
return Instance
def _make_one(self, *args, **kwargs):
return self._getTargetClass()(*args, **kwargs)
def test_constructor_defaults(self):
from google.cloud.spanner_v1.instance import DEFAULT_NODE_COUNT
client = object()
instance = self._make_one(self.INSTANCE_ID, client)
self.assertEqual(instance.instance_id, self.INSTANCE_ID)
self.assertIs(instance._client, client)
self.assertIs(instance.configuration_name, None)
self.assertEqual(instance.node_count, DEFAULT_NODE_COUNT)
self.assertEqual(instance.display_name, self.INSTANCE_ID)
self.assertEqual(instance.labels, {})
def test_constructor_non_default(self):
DISPLAY_NAME = "display_name"
client = object()
instance = self._make_one(
self.INSTANCE_ID,
client,
configuration_name=self.CONFIG_NAME,
node_count=self.NODE_COUNT,
display_name=DISPLAY_NAME,
labels=self.LABELS,
)
self.assertEqual(instance.instance_id, self.INSTANCE_ID)
self.assertIs(instance._client, client)
self.assertEqual(instance.configuration_name, self.CONFIG_NAME)
self.assertEqual(instance.node_count, self.NODE_COUNT)
self.assertEqual(instance.display_name, DISPLAY_NAME)
self.assertEqual(instance.labels, self.LABELS)
def test_copy(self):
DISPLAY_NAME = "display_name"
client = _Client(self.PROJECT)
instance = self._make_one(
self.INSTANCE_ID, client, self.CONFIG_NAME, display_name=DISPLAY_NAME
)
new_instance = instance.copy()
# Make sure the client copy succeeded.
self.assertIsNot(new_instance._client, client)
self.assertEqual(new_instance._client, client)
# Make sure the client got copied to a new instance.
self.assertIsNot(instance, new_instance)
self.assertEqual(instance, new_instance)
def test__update_from_pb_success(self):
from google.cloud.spanner_admin_instance_v1 import Instance
display_name = "display_name"
instance_pb = Instance(display_name=display_name)
instance = self._make_one(None, None, None, None)
self.assertEqual(instance.display_name, None)
instance._update_from_pb(instance_pb)
self.assertEqual(instance.display_name, display_name)
def test__update_from_pb_no_display_name(self):
from google.cloud.spanner_admin_instance_v1 import Instance
instance_pb = Instance()
instance = self._make_one(None, None, None, None)
self.assertEqual(instance.display_name, None)
with self.assertRaises(ValueError):
instance._update_from_pb(instance_pb)
self.assertEqual(instance.display_name, None)
def test_from_pb_bad_instance_name(self):
from google.cloud.spanner_admin_instance_v1 import Instance
instance_name = "INCORRECT_FORMAT"
instance_pb = Instance(name=instance_name)
klass = self._getTargetClass()
with self.assertRaises(ValueError):
klass.from_pb(instance_pb, None)
def test_from_pb_project_mistmatch(self):
from google.cloud.spanner_admin_instance_v1 import Instance
ALT_PROJECT = "ALT_PROJECT"
client = _Client(project=ALT_PROJECT)
self.assertNotEqual(self.PROJECT, ALT_PROJECT)
instance_pb = Instance(name=self.INSTANCE_NAME)
klass = self._getTargetClass()
with self.assertRaises(ValueError):
klass.from_pb(instance_pb, client)
def test_from_pb_success(self):
from google.cloud.spanner_admin_instance_v1 import Instance
client = _Client(project=self.PROJECT)
instance_pb = Instance(
name=self.INSTANCE_NAME,
config=self.CONFIG_NAME,
display_name=self.INSTANCE_ID,
labels=self.LABELS,
)
klass = self._getTargetClass()
instance = klass.from_pb(instance_pb, client)
self.assertIsInstance(instance, klass)
self.assertEqual(instance._client, client)
self.assertEqual(instance.instance_id, self.INSTANCE_ID)
self.assertEqual(instance.configuration_name, self.CONFIG_NAME)
self.assertEqual(instance.labels, self.LABELS)
def test_name_property(self):
client = _Client(project=self.PROJECT)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
self.assertEqual(instance.name, self.INSTANCE_NAME)
def test_labels_property(self):
client = _Client(project=self.PROJECT)
instance = self._make_one(
self.INSTANCE_ID, client, self.CONFIG_NAME, labels=self.LABELS
)
self.assertEqual(instance.labels, self.LABELS)
def test___eq__(self):
client = object()
instance1 = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
instance2 = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
self.assertEqual(instance1, instance2)
def test___eq__type_differ(self):
client = object()
instance1 = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
instance2 = object()
self.assertNotEqual(instance1, instance2)
def test___ne__same_value(self):
client = object()
instance1 = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
instance2 = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
comparison_val = instance1 != instance2
self.assertFalse(comparison_val)
def test___ne__(self):
instance1 = self._make_one("instance_id1", "client1", self.CONFIG_NAME)
instance2 = self._make_one("instance_id2", "client2", self.CONFIG_NAME)
self.assertNotEqual(instance1, instance2)
def test_create_grpc_error(self):
from google.api_core.exceptions import Unknown
client = _Client(self.PROJECT)
client.instance_admin_api = _FauxInstanceAdminAPI(_rpc_error=True)
instance = self._make_one(
self.INSTANCE_ID, client, configuration_name=self.CONFIG_NAME
)
with self.assertRaises(Unknown):
instance.create()
def test_create_already_exists(self):
from google.cloud.exceptions import Conflict
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_create_instance_conflict=True
)
instance = self._make_one(
self.INSTANCE_ID, client, configuration_name=self.CONFIG_NAME
)
with self.assertRaises(Conflict):
instance.create()
(parent, instance_id, instance, metadata) = api._created_instance
self.assertEqual(parent, self.PARENT)
self.assertEqual(instance_id, self.INSTANCE_ID)
self.assertEqual(instance.name, self.INSTANCE_NAME)
self.assertEqual(instance.config, self.CONFIG_NAME)
self.assertEqual(instance.display_name, self.INSTANCE_ID)
self.assertEqual(instance.processing_units, 1000)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_create_success(self):
op_future = _FauxOperationFuture()
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_create_instance_response=op_future
)
instance = self._make_one(
self.INSTANCE_ID,
client,
configuration_name=self.CONFIG_NAME,
display_name=self.DISPLAY_NAME,
node_count=self.NODE_COUNT,
labels=self.LABELS,
)
future = instance.create()
self.assertIs(future, op_future)
(parent, instance_id, instance, metadata) = api._created_instance
self.assertEqual(parent, self.PARENT)
self.assertEqual(instance_id, self.INSTANCE_ID)
self.assertEqual(instance.name, self.INSTANCE_NAME)
self.assertEqual(instance.config, self.CONFIG_NAME)
self.assertEqual(instance.display_name, self.DISPLAY_NAME)
self.assertEqual(instance.processing_units, self.PROCESSING_UNITS)
self.assertEqual(instance.labels, self.LABELS)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_create_with_processing_units(self):
op_future = _FauxOperationFuture()
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_create_instance_response=op_future
)
instance = self._make_one(
self.INSTANCE_ID,
client,
configuration_name=self.CONFIG_NAME,
display_name=self.DISPLAY_NAME,
processing_units=self.PROCESSING_UNITS,
labels=self.LABELS,
)
future = instance.create()
self.assertIs(future, op_future)
(parent, instance_id, instance, metadata) = api._created_instance
self.assertEqual(parent, self.PARENT)
self.assertEqual(instance_id, self.INSTANCE_ID)
self.assertEqual(instance.name, self.INSTANCE_NAME)
self.assertEqual(instance.config, self.CONFIG_NAME)
self.assertEqual(instance.display_name, self.DISPLAY_NAME)
self.assertEqual(instance.processing_units, self.PROCESSING_UNITS)
self.assertEqual(instance.labels, self.LABELS)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_exists_instance_grpc_error(self):
from google.api_core.exceptions import Unknown
client = _Client(self.PROJECT)
client.instance_admin_api = _FauxInstanceAdminAPI(_rpc_error=True)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
with self.assertRaises(Unknown):
instance.exists()
def test_exists_instance_not_found(self):
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_instance_not_found=True
)
api._instance_not_found = True
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
self.assertFalse(instance.exists())
name, metadata = api._got_instance
self.assertEqual(name, self.INSTANCE_NAME)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_exists_success(self):
from google.cloud.spanner_admin_instance_v1 import Instance
client = _Client(self.PROJECT)
instance_pb = Instance(
name=self.INSTANCE_NAME,
config=self.CONFIG_NAME,
display_name=self.DISPLAY_NAME,
node_count=self.NODE_COUNT,
)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_get_instance_response=instance_pb
)
instance = self._make_one(self.INSTANCE_ID, client)
self.assertTrue(instance.exists())
name, metadata = api._got_instance
self.assertEqual(name, self.INSTANCE_NAME)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_reload_instance_grpc_error(self):
from google.api_core.exceptions import Unknown
client = _Client(self.PROJECT)
client.instance_admin_api = _FauxInstanceAdminAPI(_rpc_error=True)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
with self.assertRaises(Unknown):
instance.reload()
def test_reload_instance_not_found(self):
from google.cloud.exceptions import NotFound
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_instance_not_found=True
)
api._instance_not_found = True
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
with self.assertRaises(NotFound):
instance.reload()
name, metadata = api._got_instance
self.assertEqual(name, self.INSTANCE_NAME)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_reload_success(self):
from google.cloud.spanner_admin_instance_v1 import Instance
client = _Client(self.PROJECT)
instance_pb = Instance(
name=self.INSTANCE_NAME,
config=self.CONFIG_NAME,
display_name=self.DISPLAY_NAME,
node_count=self.NODE_COUNT,
labels=self.LABELS,
)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_get_instance_response=instance_pb
)
instance = self._make_one(self.INSTANCE_ID, client)
instance.reload()
self.assertEqual(instance.configuration_name, self.CONFIG_NAME)
self.assertEqual(instance.node_count, self.NODE_COUNT)
self.assertEqual(instance.display_name, self.DISPLAY_NAME)
self.assertEqual(instance.labels, self.LABELS)
name, metadata = api._got_instance
self.assertEqual(name, self.INSTANCE_NAME)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_update_grpc_error(self):
from google.api_core.exceptions import Unknown
client = _Client(self.PROJECT)
client.instance_admin_api = _FauxInstanceAdminAPI(_rpc_error=True)
instance = self._make_one(
self.INSTANCE_ID, client, configuration_name=self.CONFIG_NAME
)
with self.assertRaises(Unknown):
instance.update()
def test_update_not_found(self):
from google.cloud.exceptions import NotFound
from google.cloud.spanner_v1.instance import DEFAULT_NODE_COUNT
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_instance_not_found=True
)
instance = self._make_one(
self.INSTANCE_ID, client, configuration_name=self.CONFIG_NAME
)
with self.assertRaises(NotFound):
instance.update()
instance, field_mask, metadata = api._updated_instance
self.assertEqual(field_mask.paths, self.FIELD_MASK)
self.assertEqual(instance.name, self.INSTANCE_NAME)
self.assertEqual(instance.config, self.CONFIG_NAME)
self.assertEqual(instance.display_name, self.INSTANCE_ID)
self.assertEqual(instance.node_count, DEFAULT_NODE_COUNT)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_update_success(self):
op_future = _FauxOperationFuture()
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_update_instance_response=op_future
)
instance = self._make_one(
self.INSTANCE_ID,
client,
configuration_name=self.CONFIG_NAME,
node_count=self.NODE_COUNT,
display_name=self.DISPLAY_NAME,
labels=self.LABELS,
)
future = instance.update()
self.assertIs(future, op_future)
instance, field_mask, metadata = api._updated_instance
self.assertEqual(field_mask.paths, self.FIELD_MASK)
self.assertEqual(instance.name, self.INSTANCE_NAME)
self.assertEqual(instance.config, self.CONFIG_NAME)
self.assertEqual(instance.display_name, self.DISPLAY_NAME)
self.assertEqual(instance.node_count, self.NODE_COUNT)
self.assertEqual(instance.labels, self.LABELS)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_update_success_with_processing_units(self):
op_future = _FauxOperationFuture()
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_update_instance_response=op_future
)
instance = self._make_one(
self.INSTANCE_ID,
client,
configuration_name=self.CONFIG_NAME,
processing_units=self.PROCESSING_UNITS,
display_name=self.DISPLAY_NAME,
labels=self.LABELS,
)
future = instance.update()
self.assertIs(future, op_future)
instance, field_mask, metadata = api._updated_instance
self.assertEqual(
field_mask.paths, ["config", "display_name", "processing_units", "labels"]
)
self.assertEqual(instance.name, self.INSTANCE_NAME)
self.assertEqual(instance.config, self.CONFIG_NAME)
self.assertEqual(instance.display_name, self.DISPLAY_NAME)
self.assertEqual(instance.processing_units, self.PROCESSING_UNITS)
self.assertEqual(instance.labels, self.LABELS)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_delete_grpc_error(self):
from google.api_core.exceptions import Unknown
client = _Client(self.PROJECT)
client.instance_admin_api = _FauxInstanceAdminAPI(_rpc_error=True)
instance = self._make_one(self.INSTANCE_ID, client)
with self.assertRaises(Unknown):
instance.delete()
def test_delete_not_found(self):
from google.cloud.exceptions import NotFound
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_instance_not_found=True
)
instance = self._make_one(self.INSTANCE_ID, client)
with self.assertRaises(NotFound):
instance.delete()
name, metadata = api._deleted_instance
self.assertEqual(name, self.INSTANCE_NAME)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_delete_success(self):
from google.protobuf.empty_pb2 import Empty
client = _Client(self.PROJECT)
api = client.instance_admin_api = _FauxInstanceAdminAPI(
_delete_instance_response=Empty()
)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
instance.delete()
name, metadata = api._deleted_instance
self.assertEqual(name, self.INSTANCE_NAME)
self.assertEqual(metadata, [("google-cloud-resource-prefix", instance.name)])
def test_database_factory_defaults(self):
from google.cloud.spanner_v1.database import Database
from google.cloud.spanner_v1.pool import BurstyPool
client = _Client(self.PROJECT)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
DATABASE_ID = "database-id"
database = instance.database(DATABASE_ID)
self.assertIsInstance(database, Database)
self.assertEqual(database.database_id, DATABASE_ID)
self.assertIs(database._instance, instance)
self.assertEqual(list(database.ddl_statements), [])
self.assertIsInstance(database._pool, BurstyPool)
self.assertIsNone(database._logger)
pool = database._pool
self.assertIs(pool._database, database)
def test_database_factory_explicit(self):
from logging import Logger
from google.cloud.spanner_v1.database import Database
from tests._fixtures import DDL_STATEMENTS
client = _Client(self.PROJECT)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
DATABASE_ID = "database-id"
pool = _Pool()
logger = mock.create_autospec(Logger, instance=True)
encryption_config = {"kms_key_name": "kms_key_name"}
database = instance.database(
DATABASE_ID,
ddl_statements=DDL_STATEMENTS,
pool=pool,
logger=logger,
encryption_config=encryption_config,
)
self.assertIsInstance(database, Database)
self.assertEqual(database.database_id, DATABASE_ID)
self.assertIs(database._instance, instance)
self.assertEqual(list(database.ddl_statements), DDL_STATEMENTS)
self.assertIs(database._pool, pool)
self.assertIs(database._logger, logger)
self.assertIs(pool._bound, database)
self.assertIs(database._encryption_config, encryption_config)
def test_list_databases(self):
from google.cloud.spanner_admin_database_v1 import Database as DatabasePB
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListDatabasesRequest
from google.cloud.spanner_admin_database_v1 import ListDatabasesResponse
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
databases_pb = ListDatabasesResponse(
databases=[
DatabasePB(name="{}/databases/aa".format(self.INSTANCE_NAME)),
DatabasePB(name="{}/databases/bb".format(self.INSTANCE_NAME)),
]
)
ld_api = api._transport._wrapped_methods[
api._transport.list_databases
] = mock.Mock(return_value=databases_pb)
response = instance.list_databases()
databases = list(response)
self.assertIsInstance(databases[0], DatabasePB)
self.assertTrue(databases[0].name.endswith("/aa"))
self.assertTrue(databases[1].name.endswith("/bb"))
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ld_api.assert_called_once_with(
ListDatabasesRequest(parent=self.INSTANCE_NAME),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
def test_list_databases_w_options(self):
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListDatabasesRequest
from google.cloud.spanner_admin_database_v1 import ListDatabasesResponse
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
databases_pb = ListDatabasesResponse(databases=[])
ld_api = api._transport._wrapped_methods[
api._transport.list_databases
] = mock.Mock(return_value=databases_pb)
page_size = 42
response = instance.list_databases(page_size=page_size)
databases = list(response)
self.assertEqual(databases, [])
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ld_api.assert_called_once_with(
ListDatabasesRequest(parent=self.INSTANCE_NAME, page_size=page_size),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
def test_backup_factory_defaults(self):
from google.cloud.spanner_v1.backup import Backup
client = _Client(self.PROJECT)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
BACKUP_ID = "backup-id"
backup = instance.backup(BACKUP_ID)
self.assertIsInstance(backup, Backup)
self.assertEqual(backup.backup_id, BACKUP_ID)
self.assertIs(backup._instance, instance)
self.assertEqual(backup._database, "")
self.assertIsNone(backup._expire_time)
def test_backup_factory_explicit(self):
import datetime
from google.cloud._helpers import UTC
from google.cloud.spanner_v1.backup import Backup
from google.cloud.spanner_admin_database_v1 import CreateBackupEncryptionConfig
client = _Client(self.PROJECT)
instance = self._make_one(self.INSTANCE_ID, client, self.CONFIG_NAME)
BACKUP_ID = "backup-id"
DATABASE_NAME = "database-name"
timestamp = datetime.datetime.utcnow().replace(tzinfo=UTC)
encryption_config = CreateBackupEncryptionConfig(
encryption_type=CreateBackupEncryptionConfig.EncryptionType.CUSTOMER_MANAGED_ENCRYPTION,
kms_key_name="kms_key_name",
)
backup = instance.backup(
BACKUP_ID,
database=DATABASE_NAME,
expire_time=timestamp,
encryption_config=encryption_config,
)
self.assertIsInstance(backup, Backup)
self.assertEqual(backup.backup_id, BACKUP_ID)
self.assertIs(backup._instance, instance)
self.assertEqual(backup._database, DATABASE_NAME)
self.assertIs(backup._expire_time, timestamp)
self.assertEqual(backup._encryption_config, encryption_config)
def test_list_backups_defaults(self):
from google.cloud.spanner_admin_database_v1 import Backup as BackupPB
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListBackupsRequest
from google.cloud.spanner_admin_database_v1 import ListBackupsResponse
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
backups_pb = ListBackupsResponse(
backups=[
BackupPB(name=instance.name + "/backups/op1"),
BackupPB(name=instance.name + "/backups/op2"),
BackupPB(name=instance.name + "/backups/op3"),
]
)
lbo_api = api._transport._wrapped_methods[
api._transport.list_backups
] = mock.Mock(return_value=backups_pb)
backups = instance.list_backups()
for backup in backups:
self.assertIsInstance(backup, BackupPB)
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
lbo_api.assert_called_once_with(
ListBackupsRequest(parent=self.INSTANCE_NAME),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
def test_list_backups_w_options(self):
from google.cloud.spanner_admin_database_v1 import Backup as BackupPB
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListBackupsRequest
from google.cloud.spanner_admin_database_v1 import ListBackupsResponse
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
backups_pb = ListBackupsResponse(
backups=[
BackupPB(name=instance.name + "/backups/op1"),
BackupPB(name=instance.name + "/backups/op2"),
BackupPB(name=instance.name + "/backups/op3"),
]
)
ldo_api = api._transport._wrapped_methods[
api._transport.list_backups
] = mock.Mock(return_value=backups_pb)
backups = instance.list_backups(filter_="filter", page_size=10)
for backup in backups:
self.assertIsInstance(backup, BackupPB)
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ldo_api.assert_called_once_with(
ListBackupsRequest(
parent=self.INSTANCE_NAME, filter="filter", page_size=10
),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
def test_list_backup_operations_defaults(self):
from google.api_core.operation import Operation
from google.cloud.spanner_admin_database_v1 import CreateBackupMetadata
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListBackupOperationsRequest
from google.cloud.spanner_admin_database_v1 import ListBackupOperationsResponse
from google.longrunning import operations_pb2
from google.protobuf.any_pb2 import Any
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
create_backup_metadata = Any()
create_backup_metadata.Pack(
CreateBackupMetadata.pb(
CreateBackupMetadata(name="backup", database="database")
)
)
operations_pb = ListBackupOperationsResponse(
operations=[
operations_pb2.Operation(name="op1", metadata=create_backup_metadata)
]
)
ldo_api = api._transport._wrapped_methods[
api._transport.list_backup_operations
] = mock.Mock(return_value=operations_pb)
ops = instance.list_backup_operations()
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ldo_api.assert_called_once_with(
ListBackupOperationsRequest(parent=self.INSTANCE_NAME),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
self.assertTrue(all([type(op) == Operation for op in ops]))
def test_list_backup_operations_w_options(self):
from google.api_core.operation import Operation
from google.cloud.spanner_admin_database_v1 import CreateBackupMetadata
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListBackupOperationsRequest
from google.cloud.spanner_admin_database_v1 import ListBackupOperationsResponse
from google.longrunning import operations_pb2
from google.protobuf.any_pb2 import Any
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
create_backup_metadata = Any()
create_backup_metadata.Pack(
CreateBackupMetadata.pb(
CreateBackupMetadata(name="backup", database="database")
)
)
operations_pb = ListBackupOperationsResponse(
operations=[
operations_pb2.Operation(name="op1", metadata=create_backup_metadata)
]
)
ldo_api = api._transport._wrapped_methods[
api._transport.list_backup_operations
] = mock.Mock(return_value=operations_pb)
ops = instance.list_backup_operations(filter_="filter", page_size=10)
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ldo_api.assert_called_once_with(
ListBackupOperationsRequest(
parent=self.INSTANCE_NAME, filter="filter", page_size=10
),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
self.assertTrue(all([type(op) == Operation for op in ops]))
def test_list_database_operations_defaults(self):
from google.api_core.operation import Operation
from google.cloud.spanner_admin_database_v1 import CreateDatabaseMetadata
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListDatabaseOperationsRequest
from google.cloud.spanner_admin_database_v1 import (
ListDatabaseOperationsResponse,
)
from google.cloud.spanner_admin_database_v1 import (
OptimizeRestoredDatabaseMetadata,
)
from google.longrunning import operations_pb2
from google.protobuf.any_pb2 import Any
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
create_database_metadata = Any()
create_database_metadata.Pack(
CreateDatabaseMetadata.pb(CreateDatabaseMetadata(database="database"))
)
optimize_database_metadata = Any()
optimize_database_metadata.Pack(
OptimizeRestoredDatabaseMetadata.pb(
OptimizeRestoredDatabaseMetadata(name="database")
)
)
databases_pb = ListDatabaseOperationsResponse(
operations=[
operations_pb2.Operation(name="op1", metadata=create_database_metadata),
operations_pb2.Operation(
name="op2", metadata=optimize_database_metadata
),
]
)
ldo_api = api._transport._wrapped_methods[
api._transport.list_database_operations
] = mock.Mock(return_value=databases_pb)
ops = instance.list_database_operations()
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ldo_api.assert_called_once_with(
ListDatabaseOperationsRequest(parent=self.INSTANCE_NAME),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
self.assertTrue(all([type(op) == Operation for op in ops]))
def test_list_database_operations_w_options(self):
from google.api_core.operation import Operation
from google.cloud.spanner_admin_database_v1 import DatabaseAdminClient
from google.cloud.spanner_admin_database_v1 import ListDatabaseOperationsRequest
from google.cloud.spanner_admin_database_v1 import (
ListDatabaseOperationsResponse,
)
from google.cloud.spanner_admin_database_v1 import RestoreDatabaseMetadata
from google.cloud.spanner_admin_database_v1 import RestoreSourceType
from google.cloud.spanner_admin_database_v1 import UpdateDatabaseDdlMetadata
from google.longrunning import operations_pb2
from google.protobuf.any_pb2 import Any
api = DatabaseAdminClient(credentials=mock.Mock())
client = _Client(self.PROJECT)
client.database_admin_api = api
instance = self._make_one(self.INSTANCE_ID, client)
restore_database_metadata = Any()
restore_database_metadata.Pack(
RestoreDatabaseMetadata.pb(
RestoreDatabaseMetadata(
name="database", source_type=RestoreSourceType.BACKUP
)
)
)
update_database_metadata = Any()
update_database_metadata.Pack(
UpdateDatabaseDdlMetadata.pb(
UpdateDatabaseDdlMetadata(
database="database", statements=["statements"]
)
)
)
databases_pb = ListDatabaseOperationsResponse(
operations=[
operations_pb2.Operation(
name="op1", metadata=restore_database_metadata
),
operations_pb2.Operation(name="op2", metadata=update_database_metadata),
]
)
ldo_api = api._transport._wrapped_methods[
api._transport.list_database_operations
] = mock.Mock(return_value=databases_pb)
ops = instance.list_database_operations(filter_="filter", page_size=10)
expected_metadata = (
("google-cloud-resource-prefix", instance.name),
("x-goog-request-params", "parent={}".format(instance.name)),
)
ldo_api.assert_called_once_with(
ListDatabaseOperationsRequest(
parent=self.INSTANCE_NAME, filter="filter", page_size=10
),
metadata=expected_metadata,
retry=mock.ANY,
timeout=mock.ANY,
)
self.assertTrue(all([type(op) == Operation for op in ops]))
def test_type_string_to_type_pb_hit(self):
from google.cloud.spanner_admin_database_v1 import (
OptimizeRestoredDatabaseMetadata,
)
from google.cloud.spanner_v1 import instance
type_string = "type.googleapis.com/google.spanner.admin.database.v1.OptimizeRestoredDatabaseMetadata"
self.assertIn(type_string, instance._OPERATION_METADATA_TYPES)
self.assertEqual(
instance._type_string_to_type_pb(type_string),
OptimizeRestoredDatabaseMetadata,
)
def test_type_string_to_type_pb_miss(self):
from google.cloud.spanner_v1 import instance
from google.protobuf.empty_pb2 import Empty
self.assertEqual(instance._type_string_to_type_pb("invalid_string"), Empty)
class _Client(object):
def __init__(self, project, timeout_seconds=None):
self.project = project
self.project_name = "projects/" + self.project
self.timeout_seconds = timeout_seconds
def copy(self):
from copy import deepcopy
return deepcopy(self)
def __eq__(self, other):
return (
other.project == self.project
and other.project_name == self.project_name
and other.timeout_seconds == self.timeout_seconds
)
class _FauxInstanceAdminAPI(object):
_create_instance_conflict = False
_instance_not_found = False
_rpc_error = False
def __init__(self, **kwargs):
self.__dict__.update(**kwargs)
def create_instance(self, parent, instance_id, instance, metadata=None):
from google.api_core.exceptions import AlreadyExists, Unknown
self._created_instance = (parent, instance_id, instance, metadata)
if self._rpc_error:
raise Unknown("error")
if self._create_instance_conflict:
raise AlreadyExists("conflict")
return self._create_instance_response
def get_instance(self, name, metadata=None):
from google.api_core.exceptions import NotFound, Unknown
self._got_instance = (name, metadata)
if self._rpc_error:
raise Unknown("error")
if self._instance_not_found:
raise NotFound("error")
return self._get_instance_response
def update_instance(self, instance, field_mask, metadata=None):
from google.api_core.exceptions import NotFound, Unknown
self._updated_instance = (instance, field_mask, metadata)
if self._rpc_error:
raise Unknown("error")
if self._instance_not_found:
raise NotFound("error")
return self._update_instance_response
def delete_instance(self, name, metadata=None):
from google.api_core.exceptions import NotFound, Unknown
self._deleted_instance = name, metadata
if self._rpc_error:
raise Unknown("error")
if self._instance_not_found:
raise NotFound("error")
return self._delete_instance_response
class _FauxOperationFuture(object):
pass
class _Pool(object):
_bound = None
def bind(self, database):
self._bound = database
| 37.894301 | 109 | 0.671493 | 4,419 | 41,229 | 5.97556 | 0.068115 | 0.052829 | 0.032947 | 0.044157 | 0.807392 | 0.792017 | 0.769106 | 0.754488 | 0.729115 | 0.718435 | 0 | 0.004523 | 0.243833 | 41,229 | 1,087 | 110 | 37.929163 | 0.842475 | 0.015911 | 0 | 0.616801 | 0 | 0 | 0.040412 | 0.021229 | 0 | 0 | 0 | 0 | 0.179517 | 1 | 0.064442 | false | 0.001151 | 0.100115 | 0.002301 | 0.204833 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
c722ddd05c48d3b85f8301af1cf50d11d6e73988 | 6,407 | py | Python | loldib/getratings/models/NA/na_galio/na_galio_top.py | koliupy/loldib | c9ab94deb07213cdc42b5a7c26467cdafaf81b7f | [
"Apache-2.0"
] | null | null | null | loldib/getratings/models/NA/na_galio/na_galio_top.py | koliupy/loldib | c9ab94deb07213cdc42b5a7c26467cdafaf81b7f | [
"Apache-2.0"
] | null | null | null | loldib/getratings/models/NA/na_galio/na_galio_top.py | koliupy/loldib | c9ab94deb07213cdc42b5a7c26467cdafaf81b7f | [
"Apache-2.0"
] | null | null | null | from getratings.models.ratings import Ratings
class NA_Galio_Top_Aatrox(Ratings):
pass
class NA_Galio_Top_Ahri(Ratings):
pass
class NA_Galio_Top_Akali(Ratings):
pass
class NA_Galio_Top_Alistar(Ratings):
pass
class NA_Galio_Top_Amumu(Ratings):
pass
class NA_Galio_Top_Anivia(Ratings):
pass
class NA_Galio_Top_Annie(Ratings):
pass
class NA_Galio_Top_Ashe(Ratings):
pass
class NA_Galio_Top_AurelionSol(Ratings):
pass
class NA_Galio_Top_Azir(Ratings):
pass
class NA_Galio_Top_Bard(Ratings):
pass
class NA_Galio_Top_Blitzcrank(Ratings):
pass
class NA_Galio_Top_Brand(Ratings):
pass
class NA_Galio_Top_Braum(Ratings):
pass
class NA_Galio_Top_Caitlyn(Ratings):
pass
class NA_Galio_Top_Camille(Ratings):
pass
class NA_Galio_Top_Cassiopeia(Ratings):
pass
class NA_Galio_Top_Chogath(Ratings):
pass
class NA_Galio_Top_Corki(Ratings):
pass
class NA_Galio_Top_Darius(Ratings):
pass
class NA_Galio_Top_Diana(Ratings):
pass
class NA_Galio_Top_Draven(Ratings):
pass
class NA_Galio_Top_DrMundo(Ratings):
pass
class NA_Galio_Top_Ekko(Ratings):
pass
class NA_Galio_Top_Elise(Ratings):
pass
class NA_Galio_Top_Evelynn(Ratings):
pass
class NA_Galio_Top_Ezreal(Ratings):
pass
class NA_Galio_Top_Fiddlesticks(Ratings):
pass
class NA_Galio_Top_Fiora(Ratings):
pass
class NA_Galio_Top_Fizz(Ratings):
pass
class NA_Galio_Top_Galio(Ratings):
pass
class NA_Galio_Top_Gangplank(Ratings):
pass
class NA_Galio_Top_Garen(Ratings):
pass
class NA_Galio_Top_Gnar(Ratings):
pass
class NA_Galio_Top_Gragas(Ratings):
pass
class NA_Galio_Top_Graves(Ratings):
pass
class NA_Galio_Top_Hecarim(Ratings):
pass
class NA_Galio_Top_Heimerdinger(Ratings):
pass
class NA_Galio_Top_Illaoi(Ratings):
pass
class NA_Galio_Top_Irelia(Ratings):
pass
class NA_Galio_Top_Ivern(Ratings):
pass
class NA_Galio_Top_Janna(Ratings):
pass
class NA_Galio_Top_JarvanIV(Ratings):
pass
class NA_Galio_Top_Jax(Ratings):
pass
class NA_Galio_Top_Jayce(Ratings):
pass
class NA_Galio_Top_Jhin(Ratings):
pass
class NA_Galio_Top_Jinx(Ratings):
pass
class NA_Galio_Top_Kalista(Ratings):
pass
class NA_Galio_Top_Karma(Ratings):
pass
class NA_Galio_Top_Karthus(Ratings):
pass
class NA_Galio_Top_Kassadin(Ratings):
pass
class NA_Galio_Top_Katarina(Ratings):
pass
class NA_Galio_Top_Kayle(Ratings):
pass
class NA_Galio_Top_Kayn(Ratings):
pass
class NA_Galio_Top_Kennen(Ratings):
pass
class NA_Galio_Top_Khazix(Ratings):
pass
class NA_Galio_Top_Kindred(Ratings):
pass
class NA_Galio_Top_Kled(Ratings):
pass
class NA_Galio_Top_KogMaw(Ratings):
pass
class NA_Galio_Top_Leblanc(Ratings):
pass
class NA_Galio_Top_LeeSin(Ratings):
pass
class NA_Galio_Top_Leona(Ratings):
pass
class NA_Galio_Top_Lissandra(Ratings):
pass
class NA_Galio_Top_Lucian(Ratings):
pass
class NA_Galio_Top_Lulu(Ratings):
pass
class NA_Galio_Top_Lux(Ratings):
pass
class NA_Galio_Top_Malphite(Ratings):
pass
class NA_Galio_Top_Malzahar(Ratings):
pass
class NA_Galio_Top_Maokai(Ratings):
pass
class NA_Galio_Top_MasterYi(Ratings):
pass
class NA_Galio_Top_MissFortune(Ratings):
pass
class NA_Galio_Top_MonkeyKing(Ratings):
pass
class NA_Galio_Top_Mordekaiser(Ratings):
pass
class NA_Galio_Top_Morgana(Ratings):
pass
class NA_Galio_Top_Nami(Ratings):
pass
class NA_Galio_Top_Nasus(Ratings):
pass
class NA_Galio_Top_Nautilus(Ratings):
pass
class NA_Galio_Top_Nidalee(Ratings):
pass
class NA_Galio_Top_Nocturne(Ratings):
pass
class NA_Galio_Top_Nunu(Ratings):
pass
class NA_Galio_Top_Olaf(Ratings):
pass
class NA_Galio_Top_Orianna(Ratings):
pass
class NA_Galio_Top_Ornn(Ratings):
pass
class NA_Galio_Top_Pantheon(Ratings):
pass
class NA_Galio_Top_Poppy(Ratings):
pass
class NA_Galio_Top_Quinn(Ratings):
pass
class NA_Galio_Top_Rakan(Ratings):
pass
class NA_Galio_Top_Rammus(Ratings):
pass
class NA_Galio_Top_RekSai(Ratings):
pass
class NA_Galio_Top_Renekton(Ratings):
pass
class NA_Galio_Top_Rengar(Ratings):
pass
class NA_Galio_Top_Riven(Ratings):
pass
class NA_Galio_Top_Rumble(Ratings):
pass
class NA_Galio_Top_Ryze(Ratings):
pass
class NA_Galio_Top_Sejuani(Ratings):
pass
class NA_Galio_Top_Shaco(Ratings):
pass
class NA_Galio_Top_Shen(Ratings):
pass
class NA_Galio_Top_Shyvana(Ratings):
pass
class NA_Galio_Top_Singed(Ratings):
pass
class NA_Galio_Top_Sion(Ratings):
pass
class NA_Galio_Top_Sivir(Ratings):
pass
class NA_Galio_Top_Skarner(Ratings):
pass
class NA_Galio_Top_Sona(Ratings):
pass
class NA_Galio_Top_Soraka(Ratings):
pass
class NA_Galio_Top_Swain(Ratings):
pass
class NA_Galio_Top_Syndra(Ratings):
pass
class NA_Galio_Top_TahmKench(Ratings):
pass
class NA_Galio_Top_Taliyah(Ratings):
pass
class NA_Galio_Top_Talon(Ratings):
pass
class NA_Galio_Top_Taric(Ratings):
pass
class NA_Galio_Top_Teemo(Ratings):
pass
class NA_Galio_Top_Thresh(Ratings):
pass
class NA_Galio_Top_Tristana(Ratings):
pass
class NA_Galio_Top_Trundle(Ratings):
pass
class NA_Galio_Top_Tryndamere(Ratings):
pass
class NA_Galio_Top_TwistedFate(Ratings):
pass
class NA_Galio_Top_Twitch(Ratings):
pass
class NA_Galio_Top_Udyr(Ratings):
pass
class NA_Galio_Top_Urgot(Ratings):
pass
class NA_Galio_Top_Varus(Ratings):
pass
class NA_Galio_Top_Vayne(Ratings):
pass
class NA_Galio_Top_Veigar(Ratings):
pass
class NA_Galio_Top_Velkoz(Ratings):
pass
class NA_Galio_Top_Vi(Ratings):
pass
class NA_Galio_Top_Viktor(Ratings):
pass
class NA_Galio_Top_Vladimir(Ratings):
pass
class NA_Galio_Top_Volibear(Ratings):
pass
class NA_Galio_Top_Warwick(Ratings):
pass
class NA_Galio_Top_Xayah(Ratings):
pass
class NA_Galio_Top_Xerath(Ratings):
pass
class NA_Galio_Top_XinZhao(Ratings):
pass
class NA_Galio_Top_Yasuo(Ratings):
pass
class NA_Galio_Top_Yorick(Ratings):
pass
class NA_Galio_Top_Zac(Ratings):
pass
class NA_Galio_Top_Zed(Ratings):
pass
class NA_Galio_Top_Ziggs(Ratings):
pass
class NA_Galio_Top_Zilean(Ratings):
pass
class NA_Galio_Top_Zyra(Ratings):
pass
| 15.364508 | 46 | 0.761667 | 972 | 6,407 | 4.59465 | 0.151235 | 0.216301 | 0.370802 | 0.463502 | 0.797582 | 0.797582 | 0 | 0 | 0 | 0 | 0 | 0 | 0.173404 | 6,407 | 416 | 47 | 15.401442 | 0.843278 | 0 | 0 | 0.498195 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0.498195 | 0.00361 | 0 | 0.501805 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 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 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 6 |
c73ec913ab1b999717311ec54928a13fa9d6a1ed | 128 | py | Python | core/config/__init__.py | YutouTaro/TrianFlow | 295d318a561f9001ed334bce2bcf6a591b6ff9f9 | [
"MIT"
] | 226 | 2020-04-04T00:16:25.000Z | 2022-03-29T18:15:32.000Z | core/config/__init__.py | YutouTaro/TrianFlow | 295d318a561f9001ed334bce2bcf6a591b6ff9f9 | [
"MIT"
] | 29 | 2020-05-22T03:17:06.000Z | 2021-12-23T03:44:49.000Z | core/config/__init__.py | YutouTaro/TrianFlow | 295d318a561f9001ed334bce2bcf6a591b6ff9f9 | [
"MIT"
] | 40 | 2020-04-09T03:46:40.000Z | 2022-01-13T14:46:23.000Z | import os, sys
sys.path.append(os.path.dirname(os.path.abspath(__file__)))
from config_utils import generate_loss_weights_dict
| 25.6 | 59 | 0.828125 | 21 | 128 | 4.666667 | 0.714286 | 0.122449 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.070313 | 128 | 4 | 60 | 32 | 0.823529 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0.666667 | 0 | 0.666667 | 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 | 1 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
c742aa5e6286cff2557fbc8ae07cf1feacda856f | 209 | py | Python | test/test_orders_api.py | leonardodalinky/pywmapi | b9e2650761895eb9a88170497c4d209b5dd6870c | [
"MIT"
] | 4 | 2022-01-27T14:31:38.000Z | 2022-03-25T08:52:01.000Z | test/test_orders_api.py | leonardodalinky/pywmapi | b9e2650761895eb9a88170497c4d209b5dd6870c | [
"MIT"
] | null | null | null | test/test_orders_api.py | leonardodalinky/pywmapi | b9e2650761895eb9a88170497c4d209b5dd6870c | [
"MIT"
] | null | null | null | from pywmapi.common import *
from pywmapi.orders import *
def test_get_orders():
get_orders("mirage_prime_systems", include=IncludeOption.item)
get_orders("heavy_trauma", include=IncludeOption.item)
| 26.125 | 66 | 0.784689 | 27 | 209 | 5.814815 | 0.592593 | 0.171975 | 0.305732 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.114833 | 209 | 7 | 67 | 29.857143 | 0.848649 | 0 | 0 | 0 | 0 | 0 | 0.15311 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.2 | true | 0 | 0.4 | 0 | 0.6 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
c755eeacd2e86afbf03e7c9206b01787fbec67a9 | 5,671 | py | Python | tests/test_endpoints.py | NHSDigital/shared-flow-testing | d253444a8c857444f9b6ec9cecdbed97fdc38992 | [
"MIT"
] | null | null | null | tests/test_endpoints.py | NHSDigital/shared-flow-testing | d253444a8c857444f9b6ec9cecdbed97fdc38992 | [
"MIT"
] | 41 | 2021-04-23T10:52:20.000Z | 2022-02-26T02:11:16.000Z | tests/test_endpoints.py | NHSDigital/shared-flow-testing | d253444a8c857444f9b6ec9cecdbed97fdc38992 | [
"MIT"
] | null | null | null | import pytest
import requests
from api_test_utils.oauth_helper import OauthHelper
from assertpy import assert_that
from .configuration import config
class TestEndpoints:
@pytest.mark.asyncio
async def test_happy_path(self, get_token):
# Given
token = get_token["access_token"]
expected_status_code = 200
# When
response = requests.get(
url=f"https://internal-dev.api.service.nhs.uk/{config.SERVICE_BASE_PATH}/user-role-service",
headers={
"Authorization": f"Bearer {token}",
"NHSD-Session-URID": "555254242102",
},
)
# Then
assert_that(expected_status_code).is_equal_to(response.status_code)
@pytest.mark.asyncio
async def test_default_role(self, get_token):
# Given
token = get_token["access_token"]
expected_status_code = 200
# When
response = requests.get(
url=f"https://internal-dev.api.service.nhs.uk/{config.SERVICE_BASE_PATH}/user-role-service",
headers={"Authorization": f"Bearer {token}"},
)
# Then
assert_that(expected_status_code).is_equal_to(response.status_code)
@pytest.mark.asyncio
async def test_user_invalid_role_in_header(self, get_token, debug):
# Given
token = get_token["access_token"]
expected_status_code = 400
expected_error = "Bad Request"
expected_error_description = "nhsd-session-urid is invalid"
await debug.start_trace()
# When
response = requests.get(
url=f"https://internal-dev.api.service.nhs.uk/{config.SERVICE_BASE_PATH}/user-role-service",
headers={
"Authorization": f"Bearer {token}",
"NHSD-Session-URID": "notAuserRole123",
},
)
isSharedFlowError = await debug.get_apigee_variable_from_trace(name='sharedFlow.userRoleError')
# Then
assert_that(isSharedFlowError).is_equal_to('true')
assert_that(expected_status_code).is_equal_to(response.status_code)
assert_that(expected_error).is_equal_to(response.json()["issue"][0]["details"]["coding"][0]["display"])
assert_that(expected_error_description).is_equal_to(response.json()["issue"][0]["diagnostics"])
@pytest.mark.asyncio
async def test_no_role_provided(self, get_token_client_credentials, debug):
token = get_token_client_credentials["access_token"]
# Given
expected_status_code = 400
expected_error = "Bad Request"
expected_error_description = "selected_roleid is missing in your token"
await debug.start_trace()
# When
response = requests.get(
url=f"https://internal-dev.api.service.nhs.uk/{config.SERVICE_BASE_PATH}/user-role-service",
headers={"Authorization": f"Bearer {token}"},
)
isSharedFlowError = await debug.get_apigee_variable_from_trace(name='sharedFlow.userRoleError')
# Then
assert_that(isSharedFlowError).is_equal_to('true')
assert_that(expected_status_code).is_equal_to(response.status_code)
assert_that(expected_error).is_equal_to(response.json()["issue"][0]["details"]["coding"][0]["display"])
assert_that(expected_error_description).is_equal_to(response.json()["issue"][0]["diagnostics"])
@pytest.mark.asyncio
async def test_nhs_login_exchanged_token_no_role_provided(
self, get_token_nhs_login_token_exchange, debug
):
token = get_token_nhs_login_token_exchange["access_token"]
# Given
expected_status_code = 400
expected_error = "Bad Request"
expected_error_description = "selected_roleid is missing in your token"
await debug.start_trace()
# When
response = requests.get(
url=f"https://internal-dev.api.service.nhs.uk/{config.SERVICE_BASE_PATH}/user-role-service",
headers={"Authorization": f"Bearer {token}"},
)
isSharedFlowError = await debug.get_apigee_variable_from_trace(name='sharedFlow.userRoleError')
# Then
assert_that(isSharedFlowError).is_equal_to('true')
assert_that(expected_status_code).is_equal_to(response.status_code)
assert_that(expected_error).is_equal_to(response.json()["issue"][0]["details"]["coding"][0]["display"])
assert_that(expected_error_description).is_equal_to(response.json()["issue"][0]["diagnostics"])
@pytest.mark.asyncio
async def test_no_role_id_on_id_token(self, test_app_and_product):
"""Call identity server to get an access token"""
# Given
expected_status_code = 400
test_product, test_app = test_app_and_product
oauth = OauthHelper(
client_id=test_app.client_id,
client_secret=test_app.client_secret,
redirect_uri=test_app.callback_url,
)
jwt = oauth.create_jwt(kid="test-1")
token_resp = await oauth.get_token_response(
grant_type="client_credentials", _jwt=jwt
)
# When
response = requests.get(
url=f"https://internal-dev.api.service.nhs.uk/{config.SERVICE_BASE_PATH}/user-role-service",
headers={
"Authorization": f"Bearer {token_resp['body']['access_token']}",
"NHSD-Session-URID": "123456789",
},
)
# Then
assert_that(expected_status_code).is_equal_to(response.status_code)
| 41.698529 | 112 | 0.64098 | 658 | 5,671 | 5.214286 | 0.177812 | 0.052463 | 0.039347 | 0.059458 | 0.805888 | 0.805888 | 0.769455 | 0.758671 | 0.758671 | 0.750219 | 0 | 0.012218 | 0.249515 | 5,671 | 135 | 113 | 42.007407 | 0.793938 | 0.016752 | 0 | 0.60396 | 0 | 0.059406 | 0.225945 | 0.020101 | 0 | 0 | 0 | 0 | 0.158416 | 1 | 0 | false | 0 | 0.049505 | 0 | 0.059406 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
c77de8d368fd0b2b4aaf3f4c2e11cd396daf28b7 | 5,492 | py | Python | tests/test_app.py | HelmUpgradeBot/UpdateDockerTags | ea286b145485d6601f2211ffbf8373d68fa51760 | [
"MIT"
] | null | null | null | tests/test_app.py | HelmUpgradeBot/UpdateDockerTags | ea286b145485d6601f2211ffbf8373d68fa51760 | [
"MIT"
] | null | null | null | tests/test_app.py | HelmUpgradeBot/UpdateDockerTags | ea286b145485d6601f2211ffbf8373d68fa51760 | [
"MIT"
] | null | null | null | # TODO: Write tests for the following functions:
# - update_image_tags()
# - run()
import base64
from unittest.mock import patch
import yaml
from tag_bot.app import compare_image_tags, edit_config
test_url = "http://jsonplaceholder.typicode.com"
test_header = {"Authorization": "token ThIs_Is_A_ToKeN"}
def test_edit_config_singleuser():
input_images_to_update = ["image_owner/image_name"]
input_image_tags = {
"image_owner/image_name": {
"current": "image_tag",
"latest": "new_image_tag",
"is_profileList": False,
}
}
expected_output = {
"singleuser": {
"image": {"name": "image_owner/image_name", "tag": "new_image_tag"},
}
}
expected_output = yaml.safe_dump(expected_output).encode("utf-8")
expected_output = base64.b64encode(expected_output)
expected_output = expected_output.decode("utf-8")
mock_get = patch(
"tag_bot.app.get_request",
return_value="""{
"singleuser": {
"image": {"name": "image_owner/image_name", "tag": "image_tag"}
}
}""",
)
with mock_get as mock:
result = edit_config(
test_url, test_header, input_images_to_update, input_image_tags
)
assert mock.call_count == 1
mock.assert_called_with(
test_url,
headers=test_header,
output="text",
)
assert result == expected_output
def test_edit_config_profileList():
input_images_to_update = ["image_owner/image_name"]
input_image_tags = {
"image_owner/image_name": {
"current": "image_tag",
"latest": "new_image_tag",
"is_profileList": True,
}
}
expected_output = {
"singleuser": {
"profileList": [
{
"kubespawner_override": {
"image": "image_owner/image_name:new_image_tag"
}
}
]
}
}
expected_output = yaml.safe_dump(expected_output).encode("utf-8")
expected_output = base64.b64encode(expected_output)
expected_output = expected_output.decode("utf-8")
mock_get = patch(
"tag_bot.app.get_request",
return_value="""{
"singleuser": {
"profileList": [
{
"kubespawner_override": {
"image": "image_owner/image_name:image_tag"
}
}
]
}
}""",
)
with mock_get as mock:
result = edit_config(
test_url, test_header, input_images_to_update, input_image_tags
)
assert mock.call_count == 1
mock.assert_called_with(
test_url,
headers=test_header,
output="text",
)
assert result == expected_output
def test_edit_config_both():
input_images_to_update = ["image_owner/image_name1", "image_owner/image_name2"]
input_image_tags = {
"image_owner/image_name1": {
"current": "image_tag1",
"latest": "new_image_tag1",
"is_profileList": False,
},
"image_owner/image_name2": {
"current": "image_tag2",
"latest": "new_image_tag2",
"is_profileList": True,
},
}
expected_output = {
"singleuser": {
"image": {"name": "image_owner/image_name1", "tag": "new_image_tag1"},
"profileList": [
{
"kubespawner_override": {
"image": "image_owner/image_name2:new_image_tag2"
}
}
],
}
}
expected_output = yaml.safe_dump(expected_output).encode("utf-8")
expected_output = base64.b64encode(expected_output)
expected_output = expected_output.decode("utf-8")
mock_get = patch(
"tag_bot.app.get_request",
return_value="""{
"singleuser": {
"image": {"name": "image_owner/image_name1", "tag": "image_tag1"},
"profileList": [
{
"kubespawner_override": {
"image": "image_owner/image_name2:image_tag2"
}
}
]
}
}""",
)
with mock_get as mock:
result = edit_config(
test_url, test_header, input_images_to_update, input_image_tags
)
assert mock.call_count == 1
mock.assert_called_with(
test_url,
headers=test_header,
output="text",
)
assert result == expected_output
def test_compare_image_tags_match():
input_image_tags = {
"image_name": {
"current": "image_name",
"latest": "image_name",
}
}
expected_image_names = []
output_image_names = compare_image_tags(input_image_tags)
assert output_image_names == expected_image_names
def test_compare_image_tags_no_match():
input_image_tags = {
"image_name": {
"current": "image_name",
"latest": "new_image_name",
}
}
expected_image_names = ["image_name"]
output_image_names = compare_image_tags(input_image_tags)
assert output_image_names == expected_image_names
| 27.46 | 83 | 0.539876 | 536 | 5,492 | 5.11194 | 0.152985 | 0.122628 | 0.087591 | 0.055474 | 0.836496 | 0.802555 | 0.779197 | 0.766788 | 0.720803 | 0.677737 | 0 | 0.010958 | 0.351967 | 5,492 | 199 | 84 | 27.59799 | 0.758921 | 0.016023 | 0 | 0.545455 | 0 | 0 | 0.322593 | 0.099074 | 0 | 0 | 0 | 0.005025 | 0.066667 | 1 | 0.030303 | false | 0 | 0.024242 | 0 | 0.054545 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
4012d82f7ea10baea60666a3d282f98e0835d33f | 44,312 | py | Python | tensorflow_data_validation/statistics/generators/top_k_uniques_stats_generator_test.py | maxsei/data-validation | 0f581fa022c23133b7a7c62d22090d0ed6b8d6ac | [
"Apache-2.0"
] | 1 | 2020-08-17T21:49:02.000Z | 2020-08-17T21:49:02.000Z | tensorflow_data_validation/statistics/generators/top_k_uniques_stats_generator_test.py | mitakora/tensorflow-data-validation | 8e43d424a6064e9626a00b2ef9db826baa2ab25d | [
"Apache-2.0"
] | null | null | null | tensorflow_data_validation/statistics/generators/top_k_uniques_stats_generator_test.py | mitakora/tensorflow-data-validation | 8e43d424a6064e9626a00b2ef9db826baa2ab25d | [
"Apache-2.0"
] | null | null | null | # Copyright 2019 Google LLC
#
# 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.
"""Tests for TopKUniques statistics generator."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from absl.testing import absltest
import pyarrow as pa
from tensorflow_data_validation import types
from tensorflow_data_validation.statistics.generators import top_k_uniques_stats_generator
from tensorflow_data_validation.utils import test_util
from google.protobuf import text_format
from tensorflow.python.util.protobuf import compare
from tensorflow_metadata.proto.v0 import schema_pb2
from tensorflow_metadata.proto.v0 import statistics_pb2
class MakeFeatureStatsProtoWithTopKStatsTest(absltest.TestCase):
"""Tests for the make_feature_stats_proto_with_topk_stats function."""
def test_make_feature_stats_proto_with_topk_stats(self):
expected_result = text_format.Parse(
"""
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
}
}""", statistics_pb2.FeatureNameStatistics())
value_counts = [('a', 4), ('c', 3), ('d', 2), ('b', 2)]
top_k_value_count_list = [
top_k_uniques_stats_generator.FeatureValueCount(
value_count[0], value_count[1])
for value_count in value_counts
]
result = (
top_k_uniques_stats_generator
.make_feature_stats_proto_with_topk_stats(
types.FeaturePath(['fa']),
top_k_value_count_list, False, False, 3, 1, 2))
compare.assertProtoEqual(self, result, expected_result)
def test_make_feature_stats_proto_with_topk_stats_unsorted_value_counts(self):
expected_result = text_format.Parse(
"""
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
}
}""", statistics_pb2.FeatureNameStatistics())
# 'b' has a lower count than 'c'.
value_counts = [('a', 4), ('b', 2), ('c', 3), ('d', 2)]
top_k_value_count_list = [
top_k_uniques_stats_generator.FeatureValueCount(
value_count[0], value_count[1])
for value_count in value_counts
]
result = (
top_k_uniques_stats_generator
.make_feature_stats_proto_with_topk_stats(
types.FeaturePath(['fa']),
top_k_value_count_list, False, False, 3, 1, 2))
compare.assertProtoEqual(self, result, expected_result)
def test_make_feature_stats_proto_with_topk_stats_categorical_feature(self):
expected_result = text_format.Parse(
"""
path {
step: 'fa'
}
type: INT
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
}
}""", statistics_pb2.FeatureNameStatistics())
value_counts = [('a', 4), ('c', 3), ('d', 2), ('b', 2)]
top_k_value_count_list = [
top_k_uniques_stats_generator.FeatureValueCount(
value_count[0], value_count[1])
for value_count in value_counts
]
result = (
top_k_uniques_stats_generator
.make_feature_stats_proto_with_topk_stats(
types.FeaturePath(['fa']),
top_k_value_count_list, True, False, 3, 1, 2))
compare.assertProtoEqual(self, result, expected_result)
def test_make_feature_stats_proto_with_topk_stats_weighted(self):
expected_result = text_format.Parse(
"""
path {
step: 'fa'
}
type: STRING
string_stats {
weighted_string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
}
}
}""", statistics_pb2.FeatureNameStatistics())
value_counts = [('a', 4), ('c', 3), ('d', 2), ('b', 2)]
top_k_value_count_list = [
top_k_uniques_stats_generator.FeatureValueCount(
value_count[0], value_count[1])
for value_count in value_counts
]
result = (
top_k_uniques_stats_generator
.make_feature_stats_proto_with_topk_stats(
types.FeaturePath(['fa']),
top_k_value_count_list, False, True, 3, 1, 2))
compare.assertProtoEqual(self, result, expected_result)
class TopkUniquesStatsGeneratorTest(test_util.TransformStatsGeneratorTest):
"""Tests for TopkUniquesStatsGenerator."""
def test_topk_uniques_with_single_string_feature(self):
# fa: 4 'a', 2 'b', 3 'c', 2 'd', 1 'e'
examples = [
pa.RecordBatch.from_arrays([
pa.array([
['a', 'b', 'c', 'e'],
['a', 'c', 'd', 'a'],
['a', 'b', 'c', 'd'],
])
], ['fa'])
]
# Note that if two feature values have the same frequency, the one with the
# lexicographically larger feature value will be higher in the order.
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
top_values {
value: 'b'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_weights(self):
# non-weighted ordering
# 3 'a', 2 'e', 2 'd', 2 'c', 1 'b'
# weighted ordering
# fa: 20 'e', 20 'd', 15 'a', 10 'c', 5 'b'
examples = [
pa.RecordBatch.from_arrays([
pa.array([
['a', 'b', 'c', 'e'],
['a', 'c', 'd', 'a'],
['d', 'e'],
]),
pa.array([[5.0], [5.0], [15.0]])
], ['fa', 'w'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 3.0
}
top_values {
value: 'e'
frequency: 2.0
}
top_values {
value: 'd'
frequency: 2.0
}
top_values {
value: 'c'
frequency: 2.0
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 3.0
}
buckets {
low_rank: 1
high_rank: 1
label: "e"
sample_count: 2.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
weighted_string_stats {
top_values {
value: 'e'
frequency: 20.0
}
top_values {
value: 'd'
frequency: 20.0
}
top_values {
value: 'a'
frequency: 15.0
}
top_values {
value: 'c'
frequency: 10.0
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "e"
sample_count: 20.0
}
buckets {
low_rank: 1
high_rank: 1
label: "d"
sample_count: 20.0
}
buckets {
low_rank: 2
high_rank: 2
label: "a"
sample_count: 15.0
}
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
weight_feature='w', num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_single_unicode_feature(self):
# fa: 4 'a', 2 'b', 3 'c', 2 'd', 1 'e'
examples = [
pa.RecordBatch.from_arrays([
pa.array([
[u'a', u'b', u'c', u'e'],
[u'a', u'c', u'd', u'a'],
[u'a', u'b', u'c', u'd'],
])
], ['fa'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
top_values {
value: 'b'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_multiple_features(self):
# fa: 4 'a', 2 'b', 3 'c', 2 'd', 1 'e'
# fb: 1 'a', 2 'b', 3 'c'
examples = [
pa.RecordBatch.from_arrays([
pa.array([['a', 'b', 'c', 'e'], None, ['a', 'c', 'd'],
['a', 'a', 'b', 'c', 'd'], None]),
pa.array([['a', 'c', 'c'], ['b'], None, None, ['b', 'c']])
], ['fa', 'fb'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
top_values {
value: 'b'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'b'
frequency: 2
}
top_values {
value: 'a'
frequency: 1
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 1
high_rank: 1
label: "b"
sample_count: 2.0
}
buckets {
low_rank: 2
high_rank: 2
label: "a"
sample_count: 1.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
unique: 3
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_empty_input(self):
examples = []
expected_result = []
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(examples, generator,
expected_result)
def test_topk_uniques_with_empty_record_batch(self):
examples = [pa.RecordBatch.from_arrays([], [])]
expected_result = []
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_missing_feature(self):
# fa: 4 'a', 2 'b', 3 'c', 2 'd', 1 'e'
# fb: 1 'a', 1 'b', 2 'c'
examples = [
pa.RecordBatch.from_arrays([
pa.array([['a', 'b', 'c', 'e'], None]),
pa.array([
['a', 'c', 'c'],
['b'],
])
], ['fa', 'fb']),
pa.RecordBatch.from_arrays(
[pa.array([['a', 'c', 'd'], ['a', 'a', 'b', 'c', 'd'], None])],
['fa']),
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
top_values {
value: 'b'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
top_values {
value: 'c'
frequency: 2
}
top_values {
value: 'b'
frequency: 1
}
top_values {
value: 'a'
frequency: 1
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "c"
sample_count: 2.0
}
buckets {
low_rank: 1
high_rank: 1
label: "b"
sample_count: 1.0
}
buckets {
low_rank: 2
high_rank: 2
label: "a"
sample_count: 1.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
unique: 3
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_numeric_feature(self):
# fa: 4 'a', 2 'b', 3 'c', 2 'd', 1 'e'
examples = [
pa.RecordBatch.from_arrays([
pa.array([['a', 'b', 'c', 'e'], None, ['a', 'c', 'd'],
['a', 'a', 'b', 'c', 'd']]),
pa.array([[1.0, 2.0, 3.0], [4.0, 5.0], None, None]),
], ['fa', 'fb'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=2, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_bytes_feature(self):
# fa: 4 'a', 2 'b', 3 'c', 2 'd', 1 'e'
# fb: 1 'a', 2 'b', 3 'c'
examples = [
pa.RecordBatch.from_arrays([
pa.array([['a', 'b', 'c', 'e'], None, ['a', 'c', 'd'],
['a', 'a', 'b', 'c', 'd'], None]),
pa.array([['a', 'c', 'c'], ['b'], None, None, ['b', 'c']])
], ['fa', 'fb'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 4
}
top_values {
value: 'c'
frequency: 3
}
top_values {
value: 'd'
frequency: 2
}
top_values {
value: 'b'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "d"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
schema = text_format.Parse(
"""
feature {
name: "fb"
type: BYTES
image_domain { }
}
""", schema_pb2.Schema())
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
schema=schema, num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_categorical_feature(self):
examples = [
pa.RecordBatch.from_arrays(
[pa.array([[12, 23, 34, 12], [45, 23], [12, 12, 34, 45]])], ['fa']),
pa.RecordBatch.from_arrays([pa.array([None, None], type=pa.null())],
['fa'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: INT
string_stats {
top_values {
value: '12'
frequency: 4
}
top_values {
value: '45'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "12"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "45"
sample_count: 2.0
}
buckets {
low_rank: 2
high_rank: 2
label: "34"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: INT
string_stats {
unique: 4
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
schema = text_format.Parse(
"""
feature {
name: "fa"
type: INT
int_domain {
is_categorical: true
}
}
""", schema_pb2.Schema())
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
schema=schema, num_top_values=2, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_frequency_threshold(self):
examples = [
pa.RecordBatch.from_arrays([
pa.array([['a', 'b', 'y', 'b'], ['a', 'x', 'a', 'z']]),
pa.array([[5.0], [15.0]])
], ['fa', 'w'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 3
}
top_values {
value: 'b'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 3.0
}
buckets {
low_rank: 1
high_rank: 1
label: "b"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
weighted_string_stats {
top_values {
value: 'a'
frequency: 35.0
}
top_values {
value: 'z'
frequency: 15.0
}
top_values {
value: 'x'
frequency: 15.0
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 35.0
}
buckets {
low_rank: 1
high_rank: 1
label: "z"
sample_count: 15.0
}
buckets {
low_rank: 2
high_rank: 2
label: "x"
sample_count: 15.0
}
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
weight_feature='w',
num_top_values=5,
frequency_threshold=2,
weighted_frequency_threshold=15,
num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_invalid_utf8_value(self):
examples = [
pa.RecordBatch.from_arrays(
[pa.array([[b'a', b'\x80abc', b'a', b'\x80abc', b'a']])], ['fa'])
]
expected_result = [
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 3
}
top_values {
value: '__BYTES_VALUE__'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 3.0
}
buckets {
low_rank: 1
high_rank: 1
label: "__BYTES_VALUE__"
sample_count: 2.0
}
}
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 2
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=4, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
examples,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
def test_topk_uniques_with_slicing(self):
examples = [
('slice1',
pa.RecordBatch.from_arrays(
[pa.array([['a', 'b', 'c', 'e']]),
pa.array([['1', '1', '0']])], ['fa', 'fb'])),
('slice2',
pa.RecordBatch.from_arrays(
[pa.array([['b', 'a', 'e', 'c']]),
pa.array([['0', '0', '1']])], ['fa', 'fb'])),
('slice1',
pa.RecordBatch.from_arrays([pa.array([['a', 'c', 'd', 'a']])],
['fa'])),
('slice2',
pa.RecordBatch.from_arrays([pa.array([['b', 'e', 'd', 'b']])], ['fa']))
]
# Note that if two feature values have the same frequency, the one with the
# lexicographically larger feature value will be higher in the order.
expected_result = [
('slice1',
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'a'
frequency: 3
}
top_values {
value: 'c'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "a"
sample_count: 3.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 2.0
}
}
}
}
""", statistics_pb2.DatasetFeatureStatistics())),
('slice1',
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
top_values {
value: '1'
frequency: 2
}
top_values {
value: '0'
frequency: 1
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "1"
sample_count: 2.0
}
buckets {
low_rank: 1
high_rank: 1
label: "0"
sample_count: 1.0
}
}
}
}
""", statistics_pb2.DatasetFeatureStatistics())),
('slice1',
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics())),
('slice1',
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
unique: 2
}
}""", statistics_pb2.DatasetFeatureStatistics())),
('slice2',
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
top_values {
value: 'b'
frequency: 3
}
top_values {
value: 'e'
frequency: 2
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "b"
sample_count: 3.0
}
buckets {
low_rank: 1
high_rank: 1
label: "e"
sample_count: 2.0
}
}
}
}
""", statistics_pb2.DatasetFeatureStatistics())),
('slice2',
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
top_values {
value: '0'
frequency: 2
}
top_values {
value: '1'
frequency: 1
}
rank_histogram {
buckets {
low_rank: 0
high_rank: 0
label: "0"
sample_count: 2.0
}
buckets {
low_rank: 1
high_rank: 1
label: "1"
sample_count: 1.0
}
}
}
}
""", statistics_pb2.DatasetFeatureStatistics())),
('slice2',
text_format.Parse(
"""
features {
path {
step: 'fa'
}
type: STRING
string_stats {
unique: 5
}
}""", statistics_pb2.DatasetFeatureStatistics())),
('slice2',
text_format.Parse(
"""
features {
path {
step: 'fb'
}
type: STRING
string_stats {
unique: 2
}
}""", statistics_pb2.DatasetFeatureStatistics())),
]
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
num_top_values=2, num_rank_histogram_buckets=2)
self.assertSlicingAwareTransformOutputEqual(examples, generator,
expected_result)
def test_topk_uniques_with_struct_leaves(self):
inputs = [
pa.RecordBatch.from_arrays([
pa.array([[1.0], [2.0]]),
pa.array([[{
'f1': ['a', 'b'],
'f2': [1, 2]
}, {
'f1': ['b'],
}], [{
'f1': ['c', 'd'],
'f2': [2, 3]
}, {
'f2': [3]
}]]),
], ['w', 'c']),
pa.RecordBatch.from_arrays([
pa.array([[3.0]]),
pa.array([[{
'f1': ['d'],
'f2': [4]
}]]),
], ['w', 'c']),
]
expected_result = [
text_format.Parse(
"""
features{
type: STRING
string_stats {
top_values {
value: "d"
frequency: 2.0
}
top_values {
value: "b"
frequency: 2.0
}
top_values {
value: "c"
frequency: 1.0
}
rank_histogram {
buckets {
label: "d"
sample_count: 2.0
}
buckets {
low_rank: 1
high_rank: 1
label: "b"
sample_count: 2.0
}
buckets {
low_rank: 2
high_rank: 2
label: "c"
sample_count: 1.0
}
}
}
path {
step: "c"
step: "f1"
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse(
"""
features {
string_stats {
top_values {
value: "3"
frequency: 2.0
}
top_values {
value: "2"
frequency: 2.0
}
top_values {
value: "4"
frequency: 1.0
}
rank_histogram {
buckets {
label: "3"
sample_count: 2.0
}
buckets {
low_rank: 1
high_rank: 1
label: "2"
sample_count: 2.0
}
buckets {
low_rank: 2
high_rank: 2
label: "4"
sample_count: 1.0
}
}
}
path {
step: "c"
step: "f2"
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse("""
features {
type: STRING
string_stats {
unique: 4
}
path {
step: "c"
step: "f1"
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse("""
features {
type: INT
string_stats {
unique: 4
}
path {
step: "c"
step: "f2"
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse("""
features {
type: STRING
string_stats {
weighted_string_stats {
top_values {
value: "d"
frequency: 5.0
}
top_values {
value: "c"
frequency: 2.0
}
top_values {
value: "b"
frequency: 2.0
}
rank_histogram {
buckets {
label: "d"
sample_count: 5.0
}
buckets {
low_rank: 1
high_rank: 1
label: "c"
sample_count: 2.0
}
buckets {
low_rank: 2
high_rank: 2
label: "b"
sample_count: 2.0
}
}
}
}
path {
step: "c"
step: "f1"
}
}""", statistics_pb2.DatasetFeatureStatistics()),
text_format.Parse("""
features {
string_stats {
weighted_string_stats {
top_values {
value: "3"
frequency: 4.0
}
top_values {
value: "4"
frequency: 3.0
}
top_values {
value: "2"
frequency: 3.0
}
rank_histogram {
buckets {
label: "3"
sample_count: 4.0
}
buckets {
low_rank: 1
high_rank: 1
label: "4"
sample_count: 3.0
}
buckets {
low_rank: 2
high_rank: 2
label: "2"
sample_count: 3.0
}
}
}
}
path {
step: "c"
step: "f2"
}
}""", statistics_pb2.DatasetFeatureStatistics()),
]
schema = text_format.Parse(
"""
feature {
name: "c"
type: STRUCT
struct_domain {
feature {
name: "f2"
type: INT
int_domain {
is_categorical: true
}
}
}
}
""", schema_pb2.Schema())
generator = top_k_uniques_stats_generator.TopKUniquesStatsGenerator(
schema=schema,
weight_feature='w', num_top_values=3, num_rank_histogram_buckets=3)
self.assertSlicingAwareTransformOutputEqual(
inputs,
generator,
expected_result,
add_default_slice_key_to_input=True,
add_default_slice_key_to_output=True)
if __name__ == '__main__':
absltest.main()
| 26.251185 | 90 | 0.424197 | 3,858 | 44,312 | 4.605495 | 0.058839 | 0.046094 | 0.060671 | 0.035457 | 0.899651 | 0.893235 | 0.860198 | 0.845846 | 0.818213 | 0.793955 | 0 | 0.030182 | 0.479599 | 44,312 | 1,687 | 91 | 26.266746 | 0.74033 | 0.032203 | 0 | 0.697936 | 0 | 0 | 0.157341 | 0.002134 | 0 | 0 | 0 | 0 | 0.033771 | 1 | 0.033771 | false | 0 | 0.022514 | 0 | 0.060038 | 0.001876 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
40298547c06db51ba28a9db42fcecce5d7ed71b8 | 131 | py | Python | basic.py | PacktPublishing/Network-Hacking-Continued---Intermediate-to-Advanced | cd91f5a6d4076ce9603cbff768a740784977f9cc | [
"MIT"
] | 6 | 2020-06-24T11:17:58.000Z | 2021-11-08T13:10:19.000Z | basic.py | PacktPublishing/Network-Hacking-Continued---Intermediate-to-Advanced | cd91f5a6d4076ce9603cbff768a740784977f9cc | [
"MIT"
] | null | null | null | basic.py | PacktPublishing/Network-Hacking-Continued---Intermediate-to-Advanced | cd91f5a6d4076ce9603cbff768a740784977f9cc | [
"MIT"
] | 7 | 2020-01-14T11:53:24.000Z | 2022-03-19T15:13:14.000Z | from mitmproxy import http
def request(flow):
#Code to handle request flows
def response(flow):
#Code to handle response flows | 16.375 | 31 | 0.770992 | 20 | 131 | 5.05 | 0.6 | 0.158416 | 0.19802 | 0.316832 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.167939 | 131 | 8 | 31 | 16.375 | 0.926606 | 0.435115 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | null | 0 | 0.333333 | null | null | 0 | 1 | 0 | 0 | null | 0 | 1 | 1 | 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 | 1 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 6 |
40d831a890abc3078176745ef3a58793ef2ba020 | 106 | py | Python | bot/commands/__init__.py | infin1tyy/cj | f70819a2c6d9c10a5c8fd65c08a151607da18e1f | [
"MIT"
] | 3 | 2019-02-28T21:47:02.000Z | 2019-03-20T08:31:52.000Z | bot/commands/__init__.py | devlexanderxyz/cj | f70819a2c6d9c10a5c8fd65c08a151607da18e1f | [
"MIT"
] | 1 | 2020-07-05T10:27:53.000Z | 2020-07-05T10:27:53.000Z | bot/commands/__init__.py | devlexanderxyz/cj | f70819a2c6d9c10a5c8fd65c08a151607da18e1f | [
"MIT"
] | null | null | null | from .cmd_konesyntees import cmd_konesyntees
from .cmd_wiki import cmd_wiki
from .cmd_help import cmd_help | 35.333333 | 44 | 0.867925 | 18 | 106 | 4.777778 | 0.333333 | 0.244186 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.103774 | 106 | 3 | 45 | 35.333333 | 0.905263 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
40eb4f99f2f79bdde7449fb0bc40fd5d304ebb81 | 126 | py | Python | JABA/model/__init__.py | futotta-risu/JATS | 4f034b56d98731fa6185add1b9d1d353d28a6310 | [
"Apache-2.0"
] | null | null | null | JABA/model/__init__.py | futotta-risu/JATS | 4f034b56d98731fa6185add1b9d1d353d28a6310 | [
"Apache-2.0"
] | 43 | 2021-06-14T20:58:53.000Z | 2021-07-16T06:40:15.000Z | JABA/model/__init__.py | futotta-risu/JATS | 4f034b56d98731fa6185add1b9d1d353d28a6310 | [
"Apache-2.0"
] | null | null | null | from model.social.Tweet import Tweet
from model.bitcoin.Bitcoin import Bitcoin
from model.sentiment.Sentiment import Sentiment | 42 | 47 | 0.865079 | 18 | 126 | 6.055556 | 0.388889 | 0.247706 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.087302 | 126 | 3 | 47 | 42 | 0.947826 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
dc0e35687961aab2b2e6a0eb57dd6c29134f2792 | 20,099 | py | Python | idaes/core/util/tests/test_misc.py | eslickj/idaes-pse | 328ed07ffb0b4d98c03e972675ea32c41dd2531a | [
"RSA-MD"
] | 1 | 2019-02-21T22:03:48.000Z | 2019-02-21T22:03:48.000Z | idaes/core/util/tests/test_misc.py | eslickj/idaes-pse | 328ed07ffb0b4d98c03e972675ea32c41dd2531a | [
"RSA-MD"
] | 1 | 2021-03-01T22:05:06.000Z | 2021-03-01T22:05:06.000Z | idaes/core/util/tests/test_misc.py | eslickj/idaes-pse | 328ed07ffb0b4d98c03e972675ea32c41dd2531a | [
"RSA-MD"
] | 1 | 2021-11-04T14:57:20.000Z | 2021-11-04T14:57:20.000Z | #################################################################################
# The Institute for the Design of Advanced Energy Systems Integrated Platform
# Framework (IDAES IP) was produced under the DOE Institute for the
# Design of Advanced Energy Systems (IDAES), and is copyright (c) 2018-2021
# by the software owners: The Regents of the University of California, through
# Lawrence Berkeley National Laboratory, National Technology & Engineering
# Solutions of Sandia, LLC, Carnegie Mellon University, West Virginia University
# Research Corporation, et al. All rights reserved.
#
# Please see the files COPYRIGHT.md and LICENSE.md for full copyright and
# license information.
#################################################################################
"""
This module contains miscalaneous utility functions for use in IDAES models.
"""
import pytest
from pyomo.environ import ConcreteModel, Expression, Set, Block, Var, units
from pyomo.network import Port, Arc
from pyomo.common.config import ConfigBlock
from pyomo.core.base.units_container import UnitsError
from idaes.core.util.misc import (add_object_reference, copy_port_values,
TagReference, VarLikeExpression,
set_param_from_config)
import idaes.logger as idaeslog
# Author: Andrew Lee
@pytest.mark.unit
def test_add_object_reference():
m = ConcreteModel()
m.s = Set(initialize=[1, 2, 3])
add_object_reference(m, "test_ref", m.s)
assert hasattr(m, "test_ref")
assert m.test_ref == m.s
# Author: Andrew Lee
@pytest.mark.unit
def test_add_object_reference_fail():
m = ConcreteModel()
with pytest.raises(AttributeError):
add_object_reference(m, "test_ref", m.s)
# Author: John Eslick
@pytest.mark.unit
def test_port_copy():
"""DEPRECATED function test"""
m = ConcreteModel()
m.b1 = Block()
m.b2 = Block()
m.b1.x = Var(initialize=3)
m.b1.y = Var([0, 1], initialize={0: 4, 1: 5})
m.b1.z = Var([0, 1], ["A", "B"], initialize={
(0, "A"): 6, (0, "B"): 7, (1, "A"): 8, (1, "B"): 9})
m.b2.x = Var(initialize=1)
m.b2.y = Var([0, 1], initialize=1)
m.b2.z = Var([0, 1], ["A", "B"], initialize=1)
m.b1.port = Port()
m.b2.port = Port()
m.b1.port.add(m.b1.x, "x")
m.b1.port.add(m.b1.y, "y")
m.b1.port.add(m.b1.z, "z")
m.b2.port.add(m.b2.x, "x")
m.b2.port.add(m.b2.y, "y")
m.b2.port.add(m.b2.z, "z")
def assert_copied_right():
assert(m.b2.x.value == 3)
assert(m.b2.y[0].value == 4)
assert(m.b2.y[1].value == 5)
assert(m.b2.z[0, "A"].value == 6)
assert(m.b2.z[0, "B"].value == 7)
assert(m.b2.z[1, "A"].value == 8)
assert(m.b2.z[1, "B"].value == 9)
def reset():
m.b2.x = 0
m.b2.y[0] = 0
m.b2.y[1] = 0
m.b2.z[0, "A"] = 0
m.b2.z[0, "B"] = 0
m.b2.z[1, "A"] = 0
m.b2.z[1, "B"] = 0
m.arc = Arc(source=m.b1.port, dest=m.b2.port)
copy_port_values(m.b2.port, m.b1.port)
assert_copied_right()
reset()
copy_port_values(source=m.b1.port, destination=m.b2.port)
assert_copied_right()
reset()
copy_port_values(m.arc)
assert_copied_right()
reset()
copy_port_values(arc=m.arc)
assert_copied_right()
reset()
with pytest.raises(AttributeError):
copy_port_values(arc=m.b1.port)
with pytest.raises(RuntimeError):
copy_port_values(source=m.b1.port, destination=m.b2.port, arc=m.arc)
with pytest.raises(RuntimeError):
copy_port_values(source=m.b1.port, arc=m.arc)
with pytest.raises(AttributeError):
copy_port_values(source=m.b1.port, destination=m.arc)
# Author: John Eslick
@pytest.mark.unit
def test_tag_reference():
"""DEPRECATED function test"""
m = ConcreteModel()
m.z = Var([0, 1], ["A", "B"], initialize={
(0, "A"): 6, (0, "B"): 7, (1, "A"): 8, (1, "B"): 9})
test_tag = {}
test_tag["MyTag34&@!e.5"] = TagReference(m.z[:, "A"], description="z tag")
assert(len(test_tag["MyTag34&@!e.5"]) == 2)
assert(test_tag["MyTag34&@!e.5"][0].value == 6)
assert(test_tag["MyTag34&@!e.5"][1].value == 8)
assert(test_tag["MyTag34&@!e.5"].description == "z tag")
m.b = Block([0, 1])
m.b[0].y = Var(initialize=1)
m.b[1].y = Var(initialize=2)
test_tag = TagReference(m.b[:].y, description="y tag")
assert(test_tag[0].value == 1)
assert(test_tag[1].value == 2)
assert(test_tag.description == "y tag")
@pytest.mark.unit
def test_SimpleVarLikeExpression():
m = ConcreteModel()
# Need a Var to use in the Expression to avoid being able to set the value
# of a float
m.v = Var(initialize=42)
m.e = VarLikeExpression(expr=m.v)
assert m.e.type() is Expression
assert not m.e.is_indexed()
with pytest.raises(TypeError,
match="e is an Expression and does not have a value "
"attribute. Use the 'value\(\)' method instead."):
assert m.e.value == 42
with pytest.raises(TypeError,
match="e is an Expression and does not have a value "
"which can be set."):
m.e.set_value(10)
with pytest.raises(TypeError,
match="e is an Expression and does not have a value "
"which can be set."):
m.e.value = 10
with pytest.raises(TypeError,
match="e is an Expression and can not have bounds. "
"Use an inequality Constraint instead."):
m.e.setub(10)
with pytest.raises(TypeError,
match="e is an Expression and can not have bounds. "
"Use an inequality Constraint instead."):
m.e.setlb(0)
with pytest.raises(TypeError,
match="e is an Expression and can not be fixed. "
"Use an equality Constraint instead."):
m.e.fix(8)
with pytest.raises(TypeError,
match="e is an Expression and can not be unfixed."):
m.e.unfix()
m.e.set_value(10, force=True)
assert m.e._expr == 10
@pytest.mark.unit
def test_IndexedVarLikeExpression():
m = ConcreteModel()
# Need a Var to use in the Expression to avoid being able to set the value
# of a float
m.v = Var(initialize=42)
m.e = VarLikeExpression([1, 2, 3, 4], expr=m.v)
assert m.e.type() is Expression
assert m.e.is_indexed()
with pytest.raises(TypeError,
match="e is an Expression and can not have bounds. "
"Use inequality Constraints instead."):
m.e.setub(10)
with pytest.raises(TypeError,
match="e is an Expression and can not have bounds. "
"Use inequality Constraints instead."):
m.e.setlb(0)
with pytest.raises(TypeError,
match="e is an Expression and can not be fixed. "
"Use equality Constraints instead."):
m.e.fix(8)
with pytest.raises(TypeError,
match="e is an Expression and can not be unfixed."):
m.e.unfix()
for i in m.e:
with pytest.raises(TypeError,
match=f"e\[{i}\] is an Expression and does not have"
f" a value attribute. Use the 'value\(\)' method "
"instead"):
assert m.e[i].value == 42
with pytest.raises(TypeError,
match=f"e\[{i}\] is an Expression and does not "
f"have a value which can be set."):
m.e[i].set_value(10)
with pytest.raises(TypeError,
match="e\[{}\] is an Expression and does not have "
"a value which can be set.".format(i)):
m.e[i].value = 10
with pytest.raises(TypeError,
match="e\[{}\] is an Expression and can not have "
"bounds. Use an inequality Constraint instead."
.format(i)):
m.e[i].setub(10)
with pytest.raises(TypeError,
match="e\[{}\] is an Expression and can not have "
"bounds. Use an inequality Constraint instead."
.format(i)):
m.e[i].setlb(0)
with pytest.raises(TypeError,
match="e\[{}\] is an Expression and can not be "
"fixed. Use an equality Constraint instead."
.format(i)):
m.e[i].fix(8)
with pytest.raises(TypeError,
match="e\[{}\] is an Expression and can not be "
"unfixed.".format(i)):
m.e[i].unfix()
m.e[i].set_value(i, force=True)
assert m.e[i]._expr == i
@pytest.mark.unit
class TestSetParamFromConfig():
def test_default_config(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": 42}
m.b.test_param = Var(initialize=1)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
assert ("b no units provided for parameter test_param - assuming "
"default units" in caplog.text)
def test_specified_config(self):
m = ConcreteModel()
m.b = Block()
m.b.config2 = ConfigBlock(implicit=True)
m.b.config2.parameter_data = {"test_param": 42}
m.b.test_param = Var(initialize=1)
set_param_from_config(
m.b, "test_param", config=m.b.config2)
assert m.b.test_param.value == 42
def test_no_config(self):
m = ConcreteModel()
m.b = Block()
m.b.test_param = Var(initialize=1)
with pytest.raises(AttributeError,
match="b - set_param_from_config method was "
"not provided with a config argument, but no "
"default Config block exists. Please specify the "
"Config block to use via the config argument."):
set_param_from_config(m.b, "test_param")
def test_invalid_config(self):
m = ConcreteModel()
m.b = Block()
m.b.config = "foo"
m.b.test_param = Var(initialize=1)
with pytest.raises(TypeError,
match="b - set_param_from_config - config argument "
"provided is not an instance of a Config Block."):
set_param_from_config(m.b, "test_param")
def test_no_param(self):
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": 42}
with pytest.raises(AttributeError,
match="b - set_param_from_config method was "
"provided with param argument test_param, but no "
"attribute of that name exists."):
set_param_from_config(m.b, "test_param")
def test_no_parameter_data(self):
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {}
m.b.test_param = Var(initialize=1)
with pytest.raises(KeyError,
match="b - set_param_from_config method was "
"provided with param argument test_param, but the "
"config block does not contain a value for this "
"parameter."):
set_param_from_config(m.b, "test_param")
def test_indexed(self):
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": {"1": 42}}
m.b.test_param_1 = Var(initialize=1)
set_param_from_config(m.b, "test_param", index="1")
assert m.b.test_param_1.value == 42
def test_no_param_indexed(self):
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": {"1": 42}}
m.b.test_param = Var(initialize=1)
with pytest.raises(AttributeError,
match="b - set_param_from_config method was "
"provided with param and index arguments "
"test_param 1, but no attribute with that "
"combination \(test_param_1\) exists."):
set_param_from_config(m.b, "test_param", index="1")
def test_no_parameter_data_indexed(self):
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": {"2": 42}}
m.b.test_param_1 = Var(initialize=1)
with pytest.raises(KeyError,
match="b - set_param_from_config method was "
"provided with param and index arguments "
"test_param 1, but the config block does not "
"contain a value for this parameter and index."):
set_param_from_config(m.b, "test_param", index="1")
def test_dimensionless_default(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": 42}
m.b.test_param = Var(initialize=1, units=units.dimensionless)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
assert ("b no units provided for parameter test_param - assuming "
"default units" in caplog.text)
def test_dimensionless_defined(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.dimensionless)}
m.b.test_param = Var(initialize=1, units=units.dimensionless)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
def test_dimensionless_defined_none(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, None)}
m.b.test_param = Var(initialize=1, units=units.dimensionless)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
def test_none_defined(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, None)}
m.b.test_param = Var(initialize=1, units=None)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
def test_none_defined_dimensionless(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.dimensionless)}
m.b.test_param = Var(initialize=1, units=None)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
def test_consistent_units(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.m)}
m.b.test_param = Var(initialize=1, units=units.m)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
def test_inconsistent_units(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.m)}
m.b.test_param = Var(initialize=1, units=units.s)
with pytest.raises(UnitsError,
match="Cannot convert m to s. Units are not "
"compatible."):
set_param_from_config(m.b, "test_param")
def test_inconsistent_units_dimensionless(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.dimensionless)}
m.b.test_param = Var(initialize=1, units=units.s)
with pytest.raises(UnitsError,
match="Cannot convert dimensionless to s. Units "
"are not compatible."):
set_param_from_config(m.b, "test_param")
def test_inconsistent_units_none(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, None)}
m.b.test_param = Var(initialize=1, units=units.s)
with pytest.raises(UnitsError,
match="Cannot convert None to s. Units "
"are not compatible."):
set_param_from_config(m.b, "test_param")
def test_inconsistent_units_dimensionless_2(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.s)}
m.b.test_param = Var(initialize=1, units=units.dimensionless)
with pytest.raises(UnitsError,
match="Cannot convert s to None. Units "
"are not compatible."):
set_param_from_config(m.b, "test_param")
def test_inconsistent_units_none_2(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": (42, units.s)}
m.b.test_param = Var(initialize=1, units=None)
with pytest.raises(UnitsError,
match="Cannot convert s to None. Units "
"are not compatible."):
set_param_from_config(m.b, "test_param")
def test_unitted_default(self, caplog):
caplog.set_level(
idaeslog.DEBUG,
logger=("idaes.core.util.misc"))
m = ConcreteModel()
m.b = Block()
m.b.config = ConfigBlock(implicit=True)
m.b.config.parameter_data = {"test_param": 42}
m.b.test_param = Var(initialize=1, units=units.m)
set_param_from_config(m.b, "test_param")
assert m.b.test_param.value == 42
assert ("b no units provided for parameter test_param - assuming "
"default units" in caplog.text)
| 33.893761 | 81 | 0.562565 | 2,626 | 20,099 | 4.18393 | 0.089109 | 0.021116 | 0.027851 | 0.05106 | 0.821061 | 0.78784 | 0.762173 | 0.746701 | 0.721216 | 0.700373 | 0 | 0.019887 | 0.30698 | 20,099 | 592 | 82 | 33.951014 | 0.768899 | 0.047913 | 0 | 0.648148 | 0 | 0 | 0.18021 | 0.006653 | 0 | 0 | 0 | 0 | 0.097222 | 1 | 0.06713 | false | 0 | 0.016204 | 0 | 0.085648 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
9079c19208dad321785018128f7c476f13da7e02 | 32 | py | Python | app/di/__init__.py | mbroz/feel-the-streets | 6e21a496f1530b0500ca66e11712f3f31cd857ae | [
"MIT"
] | 9 | 2020-05-14T15:12:59.000Z | 2021-08-28T13:52:22.000Z | flask_version/meta/__init__.py | mbkmbsit/flask_version | a92827b29adce86f8dbec2784df085458201cc03 | [
"MIT"
] | 8 | 2017-10-11T13:26:10.000Z | 2021-12-13T20:27:52.000Z | flask_version/meta/__init__.py | mbkmbsit/flask_version | a92827b29adce86f8dbec2784df085458201cc03 | [
"MIT"
] | 4 | 2017-07-27T12:25:42.000Z | 2018-01-28T02:06:26.000Z | from .singleton import Singleton | 32 | 32 | 0.875 | 4 | 32 | 7 | 0.75 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.09375 | 32 | 1 | 32 | 32 | 0.965517 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
909d241d3446cb5f57c72db878a8d2b69bfe369d | 34,530 | py | Python | conans/test/functional/graph_lock/graph_lock_ci_test.py | sigmunjr/conan | ce173d25640d5c9cdd62b1c67598291be003633d | [
"MIT"
] | 1 | 2020-11-07T21:25:57.000Z | 2020-11-07T21:25:57.000Z | conans/test/functional/graph_lock/graph_lock_ci_test.py | ttencate/conan | 3dc4fb35cc3be9865f0ae480c89e6a58813d5076 | [
"MIT"
] | null | null | null | conans/test/functional/graph_lock/graph_lock_ci_test.py | ttencate/conan | 3dc4fb35cc3be9865f0ae480c89e6a58813d5076 | [
"MIT"
] | null | null | null | import json
import os
import textwrap
import unittest
from parameterized import parameterized
from conans.model.graph_lock import LOCKFILE
from conans.test.utils.genconanfile import GenConanfile
from conans.test.utils.tools import TestClient, TestServer
from conans.util.env_reader import get_env
from conans.util.files import load
conanfile = textwrap.dedent("""
from conans import ConanFile, load
import os
class Pkg(ConanFile):
{requires}
exports_sources = "myfile.txt"
keep_imports = True
def imports(self):
self.copy("myfile.txt", folder=True)
def package(self):
self.copy("*myfile.txt")
def package_info(self):
self.output.info("SELF FILE: %s"
% load(os.path.join(self.package_folder, "myfile.txt")))
for d in os.listdir(self.package_folder):
p = os.path.join(self.package_folder, d, "myfile.txt")
if os.path.isfile(p):
self.output.info("DEP FILE %s: %s" % (d, load(p)))
""")
class GraphLockCITest(unittest.TestCase):
@parameterized.expand([("recipe_revision_mode",), ("package_revision_mode",)])
@unittest.skipUnless(get_env("TESTING_REVISIONS_ENABLED", False), "Only revisions")
def test_revisions(self, package_id_mode):
test_server = TestServer(users={"user": "mypass"})
client = TestClient(servers={"default": test_server},
users={"default": [("user", "mypass")]})
client.run("config set general.default_package_id_mode=%s" % package_id_mode)
client.save({"conanfile.py": conanfile.format(requires=""),
"myfile.txt": "HelloA"})
client.run("create . PkgA/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(
requires='requires = "PkgA/0.1@user/channel"'),
"myfile.txt": "HelloB"})
client.run("create . PkgB/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(
requires='requires = "PkgB/0.1@user/channel"'),
"myfile.txt": "HelloC"})
client.run("create . PkgC/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(
requires='requires = "PkgC/0.1@user/channel"'),
"myfile.txt": "HelloD"})
client.run("create . PkgD/0.1@user/channel")
self.assertIn("PkgD/0.1@user/channel: SELF FILE: HelloD", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgC: HelloC", client.out)
client.run("upload * --all --confirm")
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
initial_lock_file = client.load(LOCKFILE)
# Do a change in B, this will be a new revision
clientb = TestClient(cache_folder=client.cache_folder, servers={"default": test_server})
clientb.save({"conanfile.py": conanfile.format(requires='requires="PkgA/0.1@user/channel"'),
"myfile.txt": "ByeB World!!"})
clientb.run("create . PkgB/0.1@user/channel")
# Go back to main orchestrator
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
client.run("lock build-order conan.lock --json=build_order.json")
master_lockfile = client.load("conan.lock")
build_order = client.load("build_order.json")
to_build = json.loads(build_order)
lock_fileaux = master_lockfile
while to_build:
for ref, _, _, _ in to_build[0]:
client_aux = TestClient(cache_folder=client.cache_folder,
servers={"default": test_server})
client_aux.save({LOCKFILE: lock_fileaux})
client_aux.run("install %s --build=%s --lockfile=conan.lock"
" --lockfile-out=conan.lock" % (ref, ref))
lock_fileaux = load(os.path.join(client_aux.current_folder, LOCKFILE))
client.save({"new_lock/%s" % LOCKFILE: lock_fileaux})
client.run("lock update conan.lock new_lock/conan.lock")
client.run("lock build-order conan.lock --json=bo.json")
lock_fileaux = client.load(LOCKFILE)
to_build = json.loads(client.load("bo.json"))
new_lockfile = client.load(LOCKFILE)
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
client.run("upload * --all --confirm")
client.save({LOCKFILE: initial_lock_file})
client.run("remove * -f")
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
client.save({LOCKFILE: new_lockfile})
client.run("remove * -f")
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
@parameterized.expand([(False,), (True,)])
def test_version_ranges(self, partial_lock):
client = TestClient()
client.run("config set general.default_package_id_mode=full_package_mode")
files = {
"pkga/conanfile.py": conanfile.format(requires=""),
"pkga/myfile.txt": "HelloA",
"pkgb/conanfile.py": conanfile.format(requires='requires="PkgA/[*]@user/channel"'),
"pkgb/myfile.txt": "HelloB",
"pkgc/conanfile.py": conanfile.format(requires='requires="PkgB/[*]@user/channel"'),
"pkgc/myfile.txt": "HelloC",
"pkgd/conanfile.py": conanfile.format(requires='requires="PkgC/[*]@user/channel"'),
"pkgd/myfile.txt": "HelloD",
}
client.save(files)
client.run("create pkga PkgA/0.1@user/channel")
client.run("create pkgb PkgB/0.1@user/channel")
client.run("create pkgc PkgC/0.1@user/channel")
client.run("create pkgd PkgD/0.1@user/channel")
self.assertIn("PkgD/0.1@user/channel: SELF FILE: HelloD", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgC: HelloC", client.out)
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
initial_lockfile = client.load("conan.lock")
# Do a change in B
client.save({"pkgb/myfile.txt": "ByeB World!!"})
if not partial_lock:
client.run("export pkgb PkgB/0.2@user/channel")
# Go back to main orchestrator
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=productd.lock")
# Now it is locked, PkgA can change
client.save({"pkga/myfile.txt": "ByeA World!!"})
client.run("create pkga PkgA/0.2@user/channel")
else:
client.run("lock create pkgb/conanfile.py --name=PkgB --version=0.2 --user=user "
"--channel=channel --lockfile-out=buildb.lock")
self.assertIn("PkgA/0.1", client.out)
self.assertNotIn("PkgA/0.2", client.out)
# Now it is locked, PkgA can change
client.save({"pkga/myfile.txt": "ByeA World!!"})
client.run("create pkga PkgA/0.2@user/channel")
# Package can be created with previous lock, keep PkgA/0.1
client.run("create pkgb PkgB/0.2@user/channel --lockfile=buildb.lock "
"--lockfile-out=buildb.lock")
self.assertIn("PkgA/0.1", client.out)
self.assertNotIn("PkgA/0.2", client.out)
self.assertIn("PkgB/0.2@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertNotIn("ByeA", client.out)
buildblock = client.load("buildb.lock")
# Go back to main orchestrator, buildb.lock can be used to lock PkgA/0.1 too
client.save({"buildb.lock": buildblock})
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile=buildb.lock "
"--lockfile-out=productd.lock")
self.assertIn("PkgA/0.1", client.out)
self.assertNotIn("PkgA/0.2", client.out)
client.run("lock build-order productd.lock --json=build_order.json")
productd_lockfile = client.load("productd.lock")
json_file = client.load("build_order.json")
to_build = json.loads(json_file)
lock_fileaux = productd_lockfile
while to_build:
for ref, _, _, _ in to_build[0]:
client_aux = TestClient(cache_folder=client.cache_folder)
client_aux.save({"productd.lock": lock_fileaux})
client_aux.run("install %s --build=%s --lockfile=productd.lock "
"--lockfile-out=productd.lock" % (ref, ref))
lock_fileaux = client_aux.load("productd.lock")
client.save({"new_lock/productd.lock": lock_fileaux})
client.run("lock update productd.lock new_lock/productd.lock")
client.run("lock build-order productd.lock --json=bo.json")
lock_fileaux = client.load("productd.lock")
to_build = json.loads(client.load("bo.json"))
# Make sure built packages are marked as modified
productd_lockfile = client.load("productd.lock")
productd_lockfile_json = json.loads(productd_lockfile)
nodes = productd_lockfile_json["graph_lock"]["nodes"]
pkgb = nodes["0"] if partial_lock else nodes["3"]
pkgc = nodes["4"] if partial_lock else nodes["2"]
pkgd = nodes["3"] if partial_lock else nodes["1"]
self.assertIn("PkgB/0.2", pkgb["ref"])
self.assertTrue(pkgb["modified"])
self.assertIn("PkgC/0.1", pkgc["ref"])
self.assertTrue(pkgc["modified"])
self.assertIn("PkgD/0.1", pkgd["ref"])
self.assertTrue(pkgd["modified"])
new_lockfile = client.load("productd.lock")
client.run("install PkgD/0.1@user/channel --lockfile=productd.lock")
self.assertIn("HelloA", client.out)
self.assertNotIn("ByeA", client.out)
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
client.save({LOCKFILE: initial_lockfile})
self.assertIn("HelloA", client.out)
self.assertNotIn("ByeA", client.out)
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
client.save({LOCKFILE: new_lockfile})
self.assertIn("HelloA", client.out)
self.assertNotIn("ByeA", client.out)
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: ByeB World!!", client.out)
# Not locked will retrieve newer versions
client.run("install PkgD/0.1@user/channel", assert_error=True)
self.assertIn("PkgA/0.2@user/channel:5ab84d6acfe1f23c4fae0ab88f26e3a396351ac9 - Cache",
client.out)
self.assertIn("PkgB/0.2@user/channel:11b376c6e7a22ec390c215a8584ef9237a6da32f - Missing",
client.out)
def test_version_ranges_diamond(self):
client = TestClient()
client.run("config set general.default_package_id_mode=full_package_mode")
client.save({"conanfile.py": conanfile.format(requires=""),
"myfile.txt": "HelloA"})
client.run("create . PkgA/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(requires='requires="PkgA/[*]@user/channel"'),
"myfile.txt": "HelloB"})
client.run("create . PkgB/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(requires='requires="PkgA/[*]@user/channel"'),
"myfile.txt": "HelloC"})
client.run("create . PkgC/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(requires='requires="PkgB/[*]@user/channel",'
' "PkgC/[*]@user/channel"'),
"myfile.txt": "HelloD"})
client.run("create . PkgD/0.1@user/channel")
self.assertIn("PkgD/0.1@user/channel: SELF FILE: HelloD", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgC: HelloC", client.out)
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
lock_file = client.load(LOCKFILE)
initial_lock_file = lock_file
# Do a change in A
clientb = TestClient(cache_folder=client.cache_folder)
clientb.run("config set general.default_package_id_mode=full_package_mode")
clientb.save({"conanfile.py": conanfile.format(requires=''),
"myfile.txt": "ByeA World!!"})
clientb.run("create . PkgA/0.2@user/channel")
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
client.run("lock build-order conan.lock --json=build_order.json")
master_lockfile = client.load("conan.lock")
json_file = os.path.join(client.current_folder, "build_order.json")
to_build = json.loads(load(json_file))
lock_fileaux = master_lockfile
while to_build:
ref, _, _, _ = to_build[0].pop(0)
client_aux = TestClient(cache_folder=client.cache_folder)
client_aux.run("config set general.default_package_id_mode=full_package_mode")
client_aux.save({LOCKFILE: lock_fileaux})
client_aux.run("install %s --build=%s --lockfile=conan.lock "
"--lockfile-out=conan.lock" % (ref, ref))
lock_fileaux = load(os.path.join(client_aux.current_folder, "conan.lock"))
client.save({"new_lock/conan.lock": lock_fileaux})
client.run("lock update conan.lock new_lock/conan.lock")
client.run("lock build-order conan.lock")
lock_fileaux = client.load("conan.lock")
output = str(client.out).splitlines()[-1]
to_build = eval(output)
new_lockfile = client.load(LOCKFILE)
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgB/0.1@user/channel: DEP FILE PkgA: ByeA World!!", client.out)
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgA: ByeA World!!", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: ByeA World!!", client.out)
client.save({LOCKFILE: initial_lock_file})
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgB/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
client.save({LOCKFILE: new_lockfile})
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgB/0.1@user/channel: DEP FILE PkgA: ByeA World!!", client.out)
self.assertIn("PkgC/0.1@user/channel: DEP FILE PkgA: ByeA World!!", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: ByeA World!!", client.out)
def test_options(self):
conanfile = textwrap.dedent("""
from conans import ConanFile
class Pkg(ConanFile):
{requires}
options = {{"myoption": [1, 2, 3, 4, 5]}}
default_options = {{"myoption": 1}}
def build(self):
self.output.info("BUILDING WITH OPTION: %s!!" % self.options.myoption)
def package_info(self):
self.output.info("PACKAGE_INFO OPTION: %s!!" % self.options.myoption)
""")
client = TestClient()
client.save({"conanfile.py": conanfile.format(requires="")})
client.run("export . PkgA/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(requires='requires="PkgA/0.1@user/channel"')})
client.run("export . PkgB/0.1@user/channel")
client.save({"conanfile.py": conanfile.format(requires='requires="PkgB/0.1@user/channel"')})
client.run("export . PkgC/0.1@user/channel")
conanfiled = conanfile.format(requires='requires="PkgC/0.1@user/channel"')
conanfiled = conanfiled.replace('default_options = {"myoption": 1}',
'default_options = {"myoption": 2, "PkgC:myoption": 3,'
'"PkgB:myoption": 4, "PkgA:myoption": 5}')
client.save({"conanfile.py": conanfiled})
client.run("export . PkgD/0.1@user/channel")
client.run("profile new myprofile")
# To make sure we can provide a profile as input
client.run("lock create --reference=PkgD/0.1@user/channel -pr=myprofile "
"--lockfile-out=conan.lock")
lock_file = client.load(LOCKFILE)
client2 = TestClient(cache_folder=client.cache_folder)
client2.save({"conanfile.py": conanfile.format(requires=""), LOCKFILE: lock_file})
client2.run("create . PkgA/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgA/0.1@user/channel: BUILDING WITH OPTION: 5!!", client2.out)
self.assertIn("PkgA/0.1@user/channel: PACKAGE_INFO OPTION: 5!!", client2.out)
client2.save({"conanfile.py": conanfile.format(
requires='requires="PkgA/0.1@user/channel"')})
client2.run("create . PkgB/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgB/0.1@user/channel: PACKAGE_INFO OPTION: 4!!", client2.out)
self.assertIn("PkgB/0.1@user/channel: BUILDING WITH OPTION: 4!!", client2.out)
self.assertIn("PkgA/0.1@user/channel: PACKAGE_INFO OPTION: 5!!", client2.out)
client2.save({"conanfile.py": conanfile.format(
requires='requires="PkgB/0.1@user/channel"')})
client2.run("create . PkgC/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgC/0.1@user/channel: PACKAGE_INFO OPTION: 3!!", client2.out)
self.assertIn("PkgC/0.1@user/channel: BUILDING WITH OPTION: 3!!", client2.out)
self.assertIn("PkgB/0.1@user/channel: PACKAGE_INFO OPTION: 4!!", client2.out)
self.assertIn("PkgA/0.1@user/channel: PACKAGE_INFO OPTION: 5!!", client2.out)
client2.save({"conanfile.py": conanfiled})
client2.run("create . PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgD/0.1@user/channel: PACKAGE_INFO OPTION: 2!!", client2.out)
self.assertIn("PkgD/0.1@user/channel: BUILDING WITH OPTION: 2!!", client2.out)
self.assertIn("PkgC/0.1@user/channel: PACKAGE_INFO OPTION: 3!!", client2.out)
self.assertIn("PkgB/0.1@user/channel: PACKAGE_INFO OPTION: 4!!", client2.out)
self.assertIn("PkgA/0.1@user/channel: PACKAGE_INFO OPTION: 5!!", client2.out)
class CIPythonRequiresTest(unittest.TestCase):
python_req = textwrap.dedent("""
from conans import ConanFile
def msg(conanfile):
conanfile.output.info("{}")
class Pkg(ConanFile):
pass
""")
consumer = textwrap.dedent("""
from conans import ConanFile, load
import os
class Pkg(ConanFile):
{requires}
python_requires = "pyreq/[*]@user/channel"
def package_info(self):
self.python_requires["pyreq"].module.msg(self)
""")
def setUp(self):
client = TestClient()
client.run("config set general.default_package_id_mode=full_package_mode")
client.save({"conanfile.py": self.python_req.format("HelloPyWorld")})
client.run("export . pyreq/0.1@user/channel")
client.save({"conanfile.py": self.consumer.format(requires="")})
client.run("create . PkgA/0.1@user/channel")
client.save(
{"conanfile.py": self.consumer.format(requires='requires="PkgA/0.1@user/channel"')})
client.run("create . PkgB/0.1@user/channel")
client.save(
{"conanfile.py": self.consumer.format(requires='requires="PkgB/[~0]@user/channel"')})
client.run("create . PkgC/0.1@user/channel")
client.save(
{"conanfile.py": self.consumer.format(requires='requires="PkgC/0.1@user/channel"')})
client.run("create . PkgD/0.1@user/channel")
for pkg in ("PkgA", "PkgB", "PkgC", "PkgD"):
self.assertIn("{}/0.1@user/channel: HelloPyWorld".format(pkg), client.out)
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
self.client = client
def test_version_ranges(self):
client = self.client
initial_lockfile = client.load("conan.lock")
# Do a change in python_require
client.save({"conanfile.py": self.python_req.format("ByePyWorld")})
client.run("export . pyreq/0.2@user/channel")
# Go back to main orchestrator
client.run("lock create --reference=PkgD/0.1@user/channel --lockfile-out=conan.lock")
client.run("lock build-order conan.lock --json=build_order.json")
master_lockfile = client.load("conan.lock")
json_file = client.load("build_order.json")
to_build = json.loads(json_file)
lock_fileaux = master_lockfile
while to_build:
for ref, _, _, _ in to_build[0]:
client_aux = TestClient(cache_folder=client.cache_folder)
client_aux.save({"conan.lock": lock_fileaux})
client_aux.run("install %s --build=%s --lockfile=conan.lock "
"--lockfile-out=conan.lock" % (ref, ref))
lock_fileaux = client_aux.load("conan.lock")
client.save({"new_lock/conan.lock": lock_fileaux})
client.run("lock update conan.lock new_lock/conan.lock")
client.run("lock build-order conan.lock --json=bo.json")
lock_fileaux = client.load("conan.lock")
to_build = json.loads(client.load("bo.json"))
new_lockfile = client.load("conan.lock")
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
for pkg in ("PkgA", "PkgB", "PkgC", "PkgD"):
self.assertIn("{}/0.1@user/channel: ByePyWorld".format(pkg), client.out)
client.save({"conan.lock": initial_lockfile})
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
for pkg in ("PkgA", "PkgB", "PkgC", "PkgD"):
self.assertIn("{}/0.1@user/channel: HelloPyWorld".format(pkg), client.out)
client.save({"conan.lock": new_lockfile})
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
for pkg in ("PkgA", "PkgB", "PkgC", "PkgD"):
self.assertIn("{}/0.1@user/channel: ByePyWorld".format(pkg), client.out)
def test_version_ranges_partial_unused(self):
client = self.client
consumer = self.consumer
# Do a change in B
client.save({"conanfile.py": consumer.format(requires='requires="PkgA/0.1@user/channel"')})
client.run("lock create conanfile.py --name=PkgB --version=1.0 --user=user "
"--channel=channel --lockfile-out=buildb.lock")
# Do a change in python_require
client.save({"conanfile.py": self.python_req.format("ByePyWorld")})
client.run("export . pyreq/0.2@user/channel")
# create the package with the previous version of python_require
client.save({"conanfile.py": consumer.format(requires='requires="PkgA/0.1@user/channel"')})
# It is a new version, it will not be used in the product build!
client.run("create . PkgB/1.0@user/channel --lockfile=buildb.lock")
self.assertIn("pyreq/0.1", client.out)
self.assertNotIn("pyreq/0.2", client.out)
# Go back to main orchestrator
# This should fail, as PkgB/0.2 is not involved in the new resolution
client.run("lock create --reference=PkgD/0.1@user/channel "
"--lockfile=buildb.lock --lockfile-out=conan.lock", assert_error=True)
self.assertIn("ERROR: The provided lockfile was not used, there is no overlap",
client.out)
client.run("lock build-order conan.lock --json=build_order.json")
json_file = client.load("build_order.json")
to_build = json.loads(json_file)
self.assertEqual(to_build, [])
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
for pkg in ("PkgA", "PkgB", "PkgC", "PkgD"):
self.assertIn("{}/0.1@user/channel: HelloPyWorld".format(pkg), client.out)
client.run("install PkgD/0.1@user/channel", assert_error=True)
self.assertIn("ERROR: Missing prebuilt package", client.out)
client.run("install PkgD/0.1@user/channel --build=missing")
for pkg in ("PkgA", "PkgB", "PkgC", "PkgD"):
self.assertIn("{}/0.1@user/channel: ByePyWorld".format(pkg), client.out)
def test_version_ranges_partial(self):
client = self.client
consumer = self.consumer
# Do a change in B
client.save({"conanfile.py": consumer.format(requires='requires="PkgA/0.1@user/channel"')})
client.run("lock create conanfile.py --name=PkgB --version=0.2 --user=user "
"--channel=channel --lockfile-out=buildb.lock")
# Do a change in python_require
client.save({"conanfile.py": self.python_req.format("ByePyWorld")})
client.run("export . pyreq/0.2@user/channel")
# create the package with the previous version of python_require
client.save({"conanfile.py": consumer.format(requires='requires="PkgA/0.1@user/channel"')})
# It is a new version, it will not be used in the product build!
client.run("create . PkgB/0.2@user/channel --lockfile=buildb.lock")
self.assertIn("pyreq/0.1", client.out)
self.assertNotIn("pyreq/0.2", client.out)
# Go back to main orchestrator
client.run("lock create --reference=PkgD/0.1@user/channel "
"--lockfile=buildb.lock --lockfile-out=conan.lock")
client.run("lock build-order conan.lock --json=build_order.json")
json_file = client.load("build_order.json")
to_build = json.loads(json_file)
if client.cache.config.revisions_enabled:
build_order = [[['PkgC/0.1@user/channel#9e5471ca39a16a120b25ee5690539c71',
'bca7337f8d2fde6cdc9dd17cdc56bc0b0a0e352d', 'host', '4']],
[['PkgD/0.1@user/channel#068fd3ce2a88181dff0b44de344a93a4',
'63a3463d4dd4cc8d7bca7a9fe5140abe582f349a', 'host', '3']]]
else:
build_order = [[['PkgC/0.1@user/channel',
'bca7337f8d2fde6cdc9dd17cdc56bc0b0a0e352d', 'host', '4']],
[['PkgD/0.1@user/channel',
'63a3463d4dd4cc8d7bca7a9fe5140abe582f349a', 'host', '3']]]
self.assertEqual(to_build, build_order)
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock --build=missing")
self.assertIn("PkgA/0.1@user/channel: HelloPyWorld", client.out)
self.assertIn("PkgB/0.2@user/channel: HelloPyWorld", client.out)
self.assertIn("PkgC/0.1@user/channel: ByePyWorld", client.out)
self.assertIn("PkgD/0.1@user/channel: ByePyWorld", client.out)
client.run("install PkgD/0.1@user/channel", assert_error=True)
self.assertIn("ERROR: Missing prebuilt package", client.out)
client.run("install PkgD/0.1@user/channel --build=missing")
self.assertIn("PkgA/0.1@user/channel: ByePyWorld", client.out)
self.assertIn("PkgB/0.2@user/channel: ByePyWorld", client.out)
self.assertIn("PkgC/0.1@user/channel: ByePyWorld", client.out)
self.assertIn("PkgD/0.1@user/channel: ByePyWorld", client.out)
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
self.assertIn("PkgA/0.1@user/channel: HelloPyWorld", client.out)
self.assertIn("PkgB/0.2@user/channel: HelloPyWorld", client.out)
self.assertIn("PkgC/0.1@user/channel: ByePyWorld", client.out)
self.assertIn("PkgD/0.1@user/channel: ByePyWorld", client.out)
class CIBuildRequiresTest(unittest.TestCase):
def test_version_ranges(self):
client = TestClient()
client.run("config set general.default_package_id_mode=full_package_mode")
myprofile = textwrap.dedent("""
[build_requires]
br/[>=0.1]@user/channel
""")
files = {
"myprofile": myprofile,
"br/conanfile.py": GenConanfile(),
"pkga/conanfile.py": conanfile.format(requires=""),
"pkga/myfile.txt": "HelloA",
"pkgb/conanfile.py": conanfile.format(requires='requires="PkgA/[*]@user/channel"'),
"pkgb/myfile.txt": "HelloB",
"pkgc/conanfile.py": conanfile.format(requires='requires="PkgB/[*]@user/channel"'),
"pkgc/myfile.txt": "HelloC",
"pkgd/conanfile.py": conanfile.format(requires='requires="PkgC/[*]@user/channel"'),
"pkgd/myfile.txt": "HelloD",
}
client.save(files)
client.run("create br br/0.1@user/channel")
client.run("create pkga PkgA/0.1@user/channel -pr=myprofile")
client.run("create pkgb PkgB/0.1@user/channel -pr=myprofile")
client.run("create pkgc PkgC/0.1@user/channel -pr=myprofile")
client.run("create pkgd PkgD/0.1@user/channel -pr=myprofile")
self.assertIn("PkgD/0.1@user/channel: SELF FILE: HelloD", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgA: HelloA", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgB: HelloB", client.out)
self.assertIn("PkgD/0.1@user/channel: DEP FILE PkgC: HelloC", client.out)
# Go back to main orchestrator
client.run("lock create --reference=PkgD/0.1@user/channel --build -pr=myprofile "
" --lockfile-out=conan.lock")
# Do a change in br
client.run("create br br/0.2@user/channel")
client.run("lock build-order conan.lock --json=build_order.json")
self.assertIn("br/0.1", client.out)
self.assertNotIn("br/0.2", client.out)
master_lockfile = client.load("conan.lock")
json_file = client.load("build_order.json")
to_build = json.loads(json_file)
if client.cache.config.revisions_enabled:
build_order = [[['br/0.1@user/channel#f3367e0e7d170aa12abccb175fee5f97',
'5ab84d6acfe1f23c4fae0ab88f26e3a396351ac9', 'host', '5']],
[['PkgA/0.1@user/channel#189390ce059842ce984e0502c52cf736',
'5ab84d6acfe1f23c4fae0ab88f26e3a396351ac9', 'host', '4']],
[['PkgB/0.1@user/channel#fa97c46bf83849a5db4564327b3cfada',
'096f747d204735584fa0115bcbd7482d424094bc', 'host', '3']],
[['PkgC/0.1@user/channel#c6f95948619d28d9d96b0ae86c46a482',
'f6d5dbb6f309dbf8519278bae8d07d3b739b3dec', 'host', '2']],
[['PkgD/0.1@user/channel#fce78c934bc0de73eeb05eb4060fc2b7',
'de4467a3fa6ef01b09b7464e85553fb4be2d2096', 'host', '1']]]
else:
build_order = [[['br/0.1@user/channel',
'5ab84d6acfe1f23c4fae0ab88f26e3a396351ac9', 'host', '5']],
[['PkgA/0.1@user/channel',
'5ab84d6acfe1f23c4fae0ab88f26e3a396351ac9', 'host', '4']],
[['PkgB/0.1@user/channel',
'096f747d204735584fa0115bcbd7482d424094bc', 'host', '3']],
[['PkgC/0.1@user/channel',
'f6d5dbb6f309dbf8519278bae8d07d3b739b3dec', 'host', '2']],
[['PkgD/0.1@user/channel',
'de4467a3fa6ef01b09b7464e85553fb4be2d2096', 'host', '1']]]
self.assertEqual(to_build, build_order)
lock_fileaux = master_lockfile
while to_build:
for ref, _, _, _ in to_build[0]:
client_aux = TestClient(cache_folder=client.cache_folder)
client_aux.save({LOCKFILE: lock_fileaux})
client_aux.run("install %s --build=%s --lockfile=conan.lock "
"--lockfile-out=conan.lock" % (ref, ref))
self.assertIn("br/0.1", client_aux.out)
self.assertNotIn("br/0.2", client_aux.out)
lock_fileaux = client_aux.load(LOCKFILE)
client.save({"new_lock/%s" % LOCKFILE: lock_fileaux})
client.run("lock update conan.lock new_lock/conan.lock")
client.run("lock build-order conan.lock --json=build_order.json")
lock_fileaux = client.load(LOCKFILE)
to_build = json.loads(client.load("build_order.json"))
client.run("install PkgD/0.1@user/channel --lockfile=conan.lock")
# No build require at all
self.assertNotIn("br/0.", client.out)
client.run("install PkgD/0.1@user/channel --build -pr=myprofile")
self.assertIn("br/0.2", client.out)
self.assertNotIn("br/0.1", client.out)
| 52.397572 | 100 | 0.611932 | 4,279 | 34,530 | 4.865857 | 0.055854 | 0.102493 | 0.046684 | 0.101148 | 0.852649 | 0.825417 | 0.794775 | 0.757216 | 0.704193 | 0.662456 | 0 | 0.037445 | 0.238199 | 34,530 | 658 | 101 | 52.477204 | 0.754077 | 0.031103 | 0 | 0.61326 | 0 | 0.018416 | 0.436174 | 0.220421 | 0 | 0 | 0 | 0 | 0.206262 | 1 | 0.016575 | false | 0.005525 | 0.033149 | 0 | 0.058932 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
90a5d398fd8612441f3545e778252431a91659c1 | 60 | py | Python | docs/Tutorials/Build/src/call-c-from-python/tests/test_A.py | mabrains/ALIGN-public | 9a6c14310de13df369a8340f465911b629f15a3f | [
"BSD-3-Clause"
] | 119 | 2019-05-14T18:44:34.000Z | 2022-03-17T01:01:02.000Z | docs/Tutorials/Build/src/call-c-from-python/tests/test_A.py | mabrains/ALIGN-public | 9a6c14310de13df369a8340f465911b629f15a3f | [
"BSD-3-Clause"
] | 717 | 2019-04-03T15:36:35.000Z | 2022-03-31T21:56:47.000Z | docs/Tutorials/Build/src/call-c-from-python/tests/test_A.py | mabrains/ALIGN-public | 9a6c14310de13df369a8340f465911b629f15a3f | [
"BSD-3-Clause"
] | 34 | 2019-04-01T21:21:27.000Z | 2022-03-21T09:46:57.000Z | import myModule
def test_A():
assert myModule.fib(3) == 2
| 15 | 29 | 0.7 | 10 | 60 | 4.1 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.04 | 0.166667 | 60 | 3 | 30 | 20 | 0.78 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.333333 | 1 | 0.333333 | true | 0 | 0.333333 | 0 | 0.666667 | 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 | 1 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
90f76751712a1fe31dc5dca34902a92af92839e2 | 28 | py | Python | lyalike/__init__.py | Pablo-Lemos/LyaLike | b57cde6cee12355a4c574be27cc090021b224d88 | [
"MIT"
] | null | null | null | lyalike/__init__.py | Pablo-Lemos/LyaLike | b57cde6cee12355a4c574be27cc090021b224d88 | [
"MIT"
] | null | null | null | lyalike/__init__.py | Pablo-Lemos/LyaLike | b57cde6cee12355a4c574be27cc090021b224d88 | [
"MIT"
] | null | null | null | from .lya import Lya, Tester | 28 | 28 | 0.785714 | 5 | 28 | 4.4 | 0.8 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.142857 | 28 | 1 | 28 | 28 | 0.916667 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
293b3d20f50259bb8c9328866508f6b9a503ef94 | 107 | py | Python | example_bot/states/__init__.py | vladpi/ptb-state-handler | ce54747db4521f4eda4401392f1bd5f33bd78838 | [
"Apache-2.0"
] | null | null | null | example_bot/states/__init__.py | vladpi/ptb-state-handler | ce54747db4521f4eda4401392f1bd5f33bd78838 | [
"Apache-2.0"
] | 5 | 2020-10-15T21:10:53.000Z | 2020-10-18T18:49:14.000Z | example_bot/states/__init__.py | vladpi/ptb-state-handler | ce54747db4521f4eda4401392f1bd5f33bd78838 | [
"Apache-2.0"
] | null | null | null | from .about import about_state
from .contacts import contacts_state
from .main_menu import main_menu_state
| 26.75 | 38 | 0.859813 | 17 | 107 | 5.117647 | 0.411765 | 0.206897 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.11215 | 107 | 3 | 39 | 35.666667 | 0.915789 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
2966e852303135015284c9846e7039aa18ccc390 | 194 | py | Python | aidbox_python_fsm/__init__.py | beda-software/aidbox-python-fsm | 916f2a4ac14ff7f8f2c12690836b29fd034acdd3 | [
"MIT"
] | null | null | null | aidbox_python_fsm/__init__.py | beda-software/aidbox-python-fsm | 916f2a4ac14ff7f8f2c12690836b29fd034acdd3 | [
"MIT"
] | 1 | 2022-03-29T15:02:14.000Z | 2022-03-29T15:02:14.000Z | aidbox_python_fsm/__init__.py | beda-software/aidbox-python-fsm | 916f2a4ac14ff7f8f2c12690836b29fd034acdd3 | [
"MIT"
] | null | null | null | from .aidbox_fsm import init_aidbox_fsm, add_aidbox_fsm_operations, aidbox_fsm_middleware, aidbox_fsm_permission
from .fsm import FSM, FSMError, FSMImpossibleTransitionError, FSMPermissionError
| 64.666667 | 112 | 0.886598 | 24 | 194 | 6.75 | 0.5 | 0.277778 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.072165 | 194 | 2 | 113 | 97 | 0.9 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
2986dd37c9f4659b6ae058089ac3f6705858bdb5 | 30 | py | Python | av/audio/__init__.py | philipnbbc/PyAV | 6f9a1561f43e0cedc10c0ee33cd30bded7d34dc0 | [
"BSD-3-Clause"
] | 538 | 2020-05-01T00:55:03.000Z | 2022-03-31T03:06:17.000Z | av/audio/__init__.py | philipnbbc/PyAV | 6f9a1561f43e0cedc10c0ee33cd30bded7d34dc0 | [
"BSD-3-Clause"
] | 301 | 2020-04-30T20:24:37.000Z | 2022-03-31T21:26:59.000Z | av/audio/__init__.py | philipnbbc/PyAV | 6f9a1561f43e0cedc10c0ee33cd30bded7d34dc0 | [
"BSD-3-Clause"
] | 96 | 2020-05-01T23:56:50.000Z | 2022-03-28T22:14:38.000Z | from .frame import AudioFrame
| 15 | 29 | 0.833333 | 4 | 30 | 6.25 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.133333 | 30 | 1 | 30 | 30 | 0.961538 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
46210e477f8945c4df76e7ed25697d51d18b81c4 | 36 | py | Python | loss/__init__.py | gurucharanmk/Fruits-360_Image_Classification | 9d26bba972ed3eca762ff225b33bd70e82edc7f0 | [
"MIT"
] | null | null | null | loss/__init__.py | gurucharanmk/Fruits-360_Image_Classification | 9d26bba972ed3eca762ff225b33bd70e82edc7f0 | [
"MIT"
] | null | null | null | loss/__init__.py | gurucharanmk/Fruits-360_Image_Classification | 9d26bba972ed3eca762ff225b33bd70e82edc7f0 | [
"MIT"
] | null | null | null | from .focalloss import FocalLossFlat | 36 | 36 | 0.888889 | 4 | 36 | 8 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.083333 | 36 | 1 | 36 | 36 | 0.969697 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 1 | 0 | 1 | 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 | 1 | 0 | 1 | 0 | 1 | 0 | 0 | 6 |
4625d52389abd756239d6b1b38a34f188779f5b3 | 27 | py | Python | step2.py | SirLonsevrot/Lesson_20.11.28_Part2 | 6228a601cdaae9889cc85324510bd4eeea5514ee | [
"Apache-2.0"
] | null | null | null | step2.py | SirLonsevrot/Lesson_20.11.28_Part2 | 6228a601cdaae9889cc85324510bd4eeea5514ee | [
"Apache-2.0"
] | null | null | null | step2.py | SirLonsevrot/Lesson_20.11.28_Part2 | 6228a601cdaae9889cc85324510bd4eeea5514ee | [
"Apache-2.0"
] | null | null | null | print('some kind of text')
| 13.5 | 26 | 0.703704 | 5 | 27 | 3.8 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.148148 | 27 | 1 | 27 | 27 | 0.826087 | 0 | 0 | 0 | 0 | 0 | 0.62963 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 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 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
465020b850b02a150036f3c36416305550694b91 | 5,366 | py | Python | tests/test_fabflee.py | jataware/flee | 67c00c4572e71dd2bbfb390d7d7ede13ffb9594e | [
"BSD-3-Clause"
] | 3 | 2021-05-24T14:07:48.000Z | 2022-01-10T03:20:36.000Z | tests/test_fabflee.py | jataware/flee | 67c00c4572e71dd2bbfb390d7d7ede13ffb9594e | [
"BSD-3-Clause"
] | 15 | 2020-06-05T11:42:23.000Z | 2022-03-09T20:17:29.000Z | tests/test_fabflee.py | jataware/flee | 67c00c4572e71dd2bbfb390d7d7ede13ffb9594e | [
"BSD-3-Clause"
] | 3 | 2020-05-29T15:10:28.000Z | 2022-03-09T19:51:41.000Z | import csv
import logging
import os
import subprocess
import sys
import pytest
base = os.path.join(os.path.dirname(os.path.dirname(__file__)), "FabFlee/config_files")
logger = logging.getLogger(__name__)
# GitHub action = 2 cores
def test_mali(run_py):
ret = run_py("mali", "50")
assert ret == "OK"
def test_par_mali(run_par):
logger.addHandler(logging.StreamHandler(sys.stdout))
logger.setLevel(logging.DEBUG)
ret = run_par("mali", "50", "2")
assert ret == "OK"
def test_burundi(run_py):
ret = run_py("burundi", "50")
assert ret == "OK"
def test_par_burundi(run_par):
logger.addHandler(logging.StreamHandler(sys.stdout))
logger.setLevel(logging.DEBUG)
ret = run_par("burundi", "50", "2")
assert ret == "OK"
def test_car(run_py):
ret = run_py("car", "50")
assert ret == "OK"
def test_par_car(run_par):
logger.addHandler(logging.StreamHandler(sys.stdout))
logger.setLevel(logging.DEBUG)
ret = run_par("car", "50", "2")
assert ret == "OK"
def test_ssudan(run_py):
ret = run_py("ssudan", "50")
assert ret == "OK"
def test_par_ssudan(run_par):
logger.addHandler(logging.StreamHandler(sys.stdout))
logger.setLevel(logging.DEBUG)
ret = run_par("ssudan", "50", "2")
assert ret == "OK"
@pytest.fixture
def run_py():
def _run_py(config, simulation_period):
config_path = os.path.join(base, config)
cmd = [
"python3",
"run.py",
"input_csv",
"source_data",
simulation_period,
"simsetting.csv",
"> out.csv",
]
cmd = " ".join([str(x) for x in cmd])
try:
proc = subprocess.Popen(
[cmd],
cwd=config_path,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
)
stdout = proc.communicate()[0].decode("utf-8")
except Exception as e:
raise RuntimeError("Unexpected error: {}".format(e)) from e
acceptable_err_subprocesse_ret_codes = [0]
if proc.returncode not in acceptable_err_subprocesse_ret_codes:
raise RuntimeError(
"\njob execution encountered an error (return code {})"
"while executing \ncmd = {}\nstdout = {}".format(proc.returncode, cmd, stdout)
)
proc.terminate()
# checking out.csv
if os.path.isfile(os.path.join(config_path, "out.csv")):
with open(os.path.join(config_path, "out.csv"), encoding="utf_8") as csvfile:
reader = csv.reader(csvfile)
lines = len(list(reader))
if lines - 1 != int(simulation_period):
raise RuntimeError(
"The generated days in out.csv file is {} which is less than "
"the target simulation_period = {}".format(lines - 1, simulation_period)
)
# clean generated out.csv file
if os.path.isfile(os.path.join(config_path, "out.csv")):
os.remove(os.path.join(config_path, "out.csv"))
return "OK"
# assert(output.find('success') >= 0)
return _run_py
@pytest.fixture
def run_par():
def _run_par(config, simulation_period, cores):
config_path = os.path.join(base, config)
cmd = [
"mpirun",
"-n",
cores,
"python3",
"run_par.py",
"input_csv",
"source_data",
simulation_period,
"simsetting.csv",
"> out.csv",
]
cmd = " ".join([str(x) for x in cmd])
try:
proc = subprocess.Popen(
[cmd],
cwd=config_path,
shell=True,
stdin=subprocess.PIPE,
stdout=subprocess.PIPE,
stderr=subprocess.STDOUT,
)
stdout = proc.communicate()[0].decode("utf-8")
except Exception as e:
raise RuntimeError("Unexpected error: {}".format(e)) from e
acceptable_err_subprocesse_ret_codes = [0]
if proc.returncode not in acceptable_err_subprocesse_ret_codes:
raise RuntimeError(
"\njob execution encountered an error (return code {})"
"while executing \ncmd = {}\nstdout = {}".format(proc.returncode, cmd, stdout)
)
# checking out.csv
if os.path.isfile(os.path.join(config_path, "out.csv")):
with open(os.path.join(config_path, "out.csv"), encoding="utf_8") as csvfile:
reader = csv.reader(csvfile)
lines = len(list(reader))
if lines - 1 != int(simulation_period):
raise RuntimeError(
"The generated days in out.csv file is {} which is less than "
"the target simulation_period = {}".format(lines - 1, simulation_period)
)
proc.terminate()
# clean generated out.csv file
if os.path.isfile(os.path.join(config_path, "out.csv")):
os.remove(os.path.join(config_path, "out.csv"))
return "OK"
# assert(output.find('success') >= 0)
return _run_par
| 29.483516 | 96 | 0.553112 | 619 | 5,366 | 4.646204 | 0.198708 | 0.035466 | 0.038248 | 0.044506 | 0.848748 | 0.8258 | 0.8258 | 0.771905 | 0.748957 | 0.748957 | 0 | 0.010187 | 0.323146 | 5,366 | 181 | 97 | 29.646409 | 0.781663 | 0.034849 | 0 | 0.681481 | 0 | 0 | 0.137691 | 0 | 0 | 0 | 0 | 0 | 0.059259 | 1 | 0.088889 | false | 0 | 0.044444 | 0 | 0.162963 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
465c171ae2ce2f82d3e6cdcc8a6cd32485f9ee7a | 33 | py | Python | a_package/a_sub_package2/__init__.py | codernayeem/python-cheat-sheet | ec6fe9f33e9175251df65899cef89f65219b9cb4 | [
"MIT"
] | null | null | null | a_package/a_sub_package2/__init__.py | codernayeem/python-cheat-sheet | ec6fe9f33e9175251df65899cef89f65219b9cb4 | [
"MIT"
] | null | null | null | a_package/a_sub_package2/__init__.py | codernayeem/python-cheat-sheet | ec6fe9f33e9175251df65899cef89f65219b9cb4 | [
"MIT"
] | null | null | null | print("a_sub_package Initiated")
| 16.5 | 32 | 0.818182 | 5 | 33 | 5 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.060606 | 33 | 1 | 33 | 33 | 0.806452 | 0 | 0 | 0 | 0 | 0 | 0.69697 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | true | 0 | 0 | 0 | 0 | 1 | 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 | 1 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 0 | 6 |
4670d3113d08541209c9f175558b31102318bf1d | 8,346 | py | Python | src/subjectClass.py | TestowanieAutomatyczneUG/projekt-i-Darkstaron123 | fe8c1e74eb73267ebb985bd030714250bb7adf67 | [
"MIT"
] | null | null | null | src/subjectClass.py | TestowanieAutomatyczneUG/projekt-i-Darkstaron123 | fe8c1e74eb73267ebb985bd030714250bb7adf67 | [
"MIT"
] | null | null | null | src/subjectClass.py | TestowanieAutomatyczneUG/projekt-i-Darkstaron123 | fe8c1e74eb73267ebb985bd030714250bb7adf67 | [
"MIT"
] | null | null | null | class SubjectClass:
def addSubject(self,language, discipleId):
import json
from discipleClass import DiscipleClass
if (language == "EN"):
print("You entered process of adding subject to disciple.")
print("Type in new subject\'s name.")
name = str(input())
with open('../data/data.txt') as json_file:
data = json.load(json_file)
with open('../data/data.txt', 'w') as outfile:
data['disciples'][int(discipleId)]['subjects'].append(
{
"id": str(len(data['disciples'][int(discipleId)]['subjects'])),
"name": name,
"marks": []
}
)
json.dump(data, outfile)
return DiscipleClass().editDisciple(language)
if (language == "PL"):
print("Weszles w proces dodawania przedmiotu do ucznia")
print("Wpisz nazwe nowego przedmiotu.")
name = str(input())
with open('../data/data.txt') as json_file:
data = json.load(json_file)
with open('../data/data.txt', 'w') as outfile:
data['disciples'][int(discipleId)]['subjects'].append(
{
"id": str(len(data['disciples'][int(discipleId)]['subjects'])),
"name": name,
"marks": []
}
)
json.dump(data, outfile)
return DiscipleClass().editDisciple(language)
def editSubject(self,language, discipleId):
import json
from discipleClass import DiscipleClass
from markClass import MarkClass
if (language == "EN"):
print("You entered process of editing subject of disciple.")
with open('../data/data.txt') as json_file:
data = json.load(json_file)
print("List of subjects of this disciple.")
for i in data['disciples'][int(discipleId)]['subjects']:
print("Id: " + i['id'] + " Name: " + i['name'])
print("Choose subject to edit by typing in it\'s id.")
typedId = str(input())
print("=>Choosen subject.<=")
print("Name: " + data['disciples'][int(discipleId)]['subjects'][int(typedId)]['name'])
print("Marks: ", end="")
for i in data['disciples'][int(discipleId)]['subjects'][int(typedId)]['marks']:
print(i, end=" ")
print()
print('Pick an option.')
print("0. Go back to menu of editing disciple.")
print("1. Type in disciple\'s subject new name.")
print("2. Add mark to disciple\'s subject.")
print("3. Edit disciple\'s mark.")
print("4. Remove disciple\'s mark.")
choose = str(input())
if (choose == "0"):
return DiscipleClass().editDisciple(language)
elif (choose == "1"):
data['disciples'][int(discipleId)]['subjects'][int(typedId)]['name'] = str(input())
elif (choose == "2"):
MarkClass().addMark(language, discipleId, typedId)
elif (choose == "3"):
MarkClass().editMark(language, discipleId, typedId)
elif (choose == "4"):
MarkClass().removeMark(language, discipleId, typedId)
else:
print('You had a typo. Try again!')
return MarkClass().editSubject(language, discipleId)
with open('../data/data.txt', 'w') as outfile:
json.dump(data, outfile)
return DiscipleClass().editDisciple(language)
if (language == "PL"):
print("Weszles w proces edytowania przedmiotu ucznia.")
with open('../data/data.txt') as json_file:
data = json.load(json_file)
print("Lista przedmiotow wybranego ucznia.")
for i in data['disciples'][int(discipleId)]['subjects']:
print("Id: " + i['id'] + " Name: " + i['name'])
print("Wybierz przedmiot to zedytowania poprzez wpisanie jego id.")
typedId = str(input())
print("=>Wybrany przedmiot.<=")
print("Nazwa: " + data['disciples'][int(discipleId)]['subjects'][int(typedId)]['name'])
print("Oceny: ", end="")
for i in data['disciples'][int(discipleId)]['subjects'][int(typedId)]['marks']:
print(i, end=" ")
print()
print('Wybierz opcje.')
print("0. Wroc do menu edytowania ucznia.")
print("1. Wpisz nowa nazwe dla wybranego przedmiotu.")
print("2. Dodaj ocene do wybranego przedmiotu.")
print("3. Zedytuj ocene w wybranym przedmiocie.")
print("4. Usun ocene w wybranym przedmiocie.")
choose = str(input())
if (choose == "0"):
return DiscipleClass().editDisciple(language)
elif (choose == "1"):
data['disciples'][int(discipleId)]['subjects'][int(typedId)]['name'] = str(input())
elif (choose == "2"):
MarkClass().addMark(language, discipleId, typedId)
elif (choose == "3"):
MarkClass().editMark(language, discipleId, typedId)
elif (choose == "4"):
MarkClass().removeMark(language, discipleId, typedId)
else:
print('Miales literowke. Sproboj ponownie!')
return MarkClass().editSubject(language, discipleId)
with open('../data/data.txt', 'w') as outfile:
json.dump(data, outfile)
return DiscipleClass().editDisciple(language)
def removeSubject(self,language, discipleId):
import json
from discipleClass import DiscipleClass
if (language == "EN"):
print("You entered process of removing subject. Choose subject by typing in his Id from list below.")
with open('../data/data.txt') as json_file:
data = json.load(json_file)
for i in data['disciples'][int(discipleId)]['subjects']:
print("Id: " + i['id'] + " Name: " + i['name'])
typedId = str(input())
try:
if (len(data['disciples'][int(discipleId)]['subjects']) > int(typedId) and int(typedId) >= 0):
with open('../data/data.txt', 'w') as outfile:
del data['disciples'][int(discipleId)]['subjects'][int(typedId)]
number = 0 # reassigning id after deletion
for i in data['disciples'][int(discipleId)]['subjects']:
i['id'] = str(number)
number = number + 1
json.dump(data, outfile)
else:
return DiscipleClass().editDisciple(language)
except:
print("Wrong input.")
return DiscipleClass().editDisciple(language)
if (language == "PL"):
print("Weszles w proces usuwania przedmiotu. Wybierz przedmiot poprzez wpisanie jego Id z listy ponizej,")
with open('../data/data.txt') as json_file:
data = json.load(json_file)
for i in data['disciples'][int(discipleId)]['subjects']:
print("Id: " + i['id'] + " Nazwa: " + i['name'])
typedId = str(input())
try:
if (len(data['disciples'][int(discipleId)]['subjects']) > int(typedId) and int(typedId) >= 0):
with open('../data/data.txt', 'w') as outfile:
del data['disciples'][int(discipleId)]['subjects'][int(typedId)]
number = 0 # reassigning id after deletion
for i in data['disciples'][int(discipleId)]['subjects']:
i['id'] = str(number)
number = number + 1
json.dump(data, outfile)
else:
return DiscipleClass().editDisciple(language)
except:
print("Zly Input.")
return DiscipleClass().editDisciple(language) | 50.581818 | 118 | 0.508387 | 817 | 8,346 | 5.178703 | 0.172583 | 0.061451 | 0.075632 | 0.122902 | 0.768376 | 0.746396 | 0.746396 | 0.746396 | 0.737887 | 0.695344 | 0 | 0.004799 | 0.350827 | 8,346 | 165 | 119 | 50.581818 | 0.776117 | 0.007069 | 0 | 0.714286 | 0 | 0 | 0.221847 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0.018634 | false | 0 | 0.043478 | 0 | 0.142857 | 0.26087 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
d3d8cb41857b64506b8fdc23250a92165b89836c | 149 | py | Python | scrapli_community/paloalto/panos/__init__.py | ikievite/scrapli_community | b160ae6c21177c949a0b8210810ba2584b31861f | [
"MIT"
] | 37 | 2020-11-13T20:50:30.000Z | 2022-03-25T16:15:28.000Z | scrapli_community/paloalto/panos/__init__.py | ikievite/scrapli_community | b160ae6c21177c949a0b8210810ba2584b31861f | [
"MIT"
] | 84 | 2020-08-02T16:20:15.000Z | 2022-03-02T14:38:26.000Z | scrapli_community/paloalto/panos/__init__.py | ikievite/scrapli_community | b160ae6c21177c949a0b8210810ba2584b31861f | [
"MIT"
] | 25 | 2020-08-01T23:51:37.000Z | 2022-02-21T10:06:33.000Z | """scrapli_community.paloalto.panos"""
from scrapli_community.paloalto.panos.paloalto_panos import SCRAPLI_PLATFORM
__all__ = ("SCRAPLI_PLATFORM",)
| 29.8 | 76 | 0.825503 | 17 | 149 | 6.705882 | 0.470588 | 0.342105 | 0.421053 | 0.508772 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.060403 | 149 | 4 | 77 | 37.25 | 0.814286 | 0.214765 | 0 | 0 | 0 | 0 | 0.144144 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0 | 0.5 | 0 | 0.5 | 0 | 1 | 0 | 0 | null | 1 | 1 | 1 | 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 | 6 |
310ff5cb8a829e89c0fd2dcfe1b2d3d7a7e7fcae | 258,306 | py | Python | instances/passenger_demand/pas-20210422-1717-int1/99.py | LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure | bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11 | [
"BSD-3-Clause"
] | null | null | null | instances/passenger_demand/pas-20210422-1717-int1/99.py | LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure | bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11 | [
"BSD-3-Clause"
] | null | null | null | instances/passenger_demand/pas-20210422-1717-int1/99.py | LHcau/scheduling-shared-passenger-and-freight-transport-on-a-fixed-infrastructure | bba1e6af5bc8d9deaa2dc3b83f6fe9ddf15d2a11 | [
"BSD-3-Clause"
] | null | null | null |
"""
PASSENGERS
"""
numPassengers = 18998
passenger_arriving = (
(3, 7, 3, 7, 4, 2, 2, 1, 2, 0, 1, 2, 0, 4, 7, 1, 9, 6, 1, 3, 1, 3, 0, 1, 1, 0), # 0
(7, 9, 6, 3, 6, 1, 1, 0, 1, 0, 1, 0, 0, 4, 8, 8, 1, 3, 6, 4, 3, 2, 1, 2, 1, 0), # 1
(6, 5, 7, 3, 7, 2, 3, 0, 3, 1, 0, 0, 0, 9, 5, 4, 2, 3, 5, 3, 0, 1, 0, 0, 0, 0), # 2
(3, 9, 5, 4, 8, 2, 3, 3, 3, 0, 0, 1, 0, 6, 3, 0, 2, 3, 2, 1, 1, 3, 0, 0, 1, 0), # 3
(4, 2, 5, 11, 9, 1, 4, 1, 6, 0, 0, 0, 0, 5, 3, 3, 5, 2, 1, 4, 1, 3, 3, 0, 0, 0), # 4
(5, 6, 6, 5, 3, 2, 1, 0, 0, 3, 1, 0, 0, 10, 9, 7, 2, 7, 3, 4, 1, 2, 1, 3, 1, 0), # 5
(5, 6, 8, 7, 2, 3, 3, 2, 6, 2, 1, 0, 0, 10, 7, 4, 6, 7, 8, 3, 3, 1, 3, 0, 1, 0), # 6
(14, 9, 6, 6, 4, 2, 1, 2, 1, 1, 0, 0, 0, 11, 6, 4, 9, 5, 6, 1, 1, 2, 0, 3, 1, 0), # 7
(7, 11, 7, 9, 6, 2, 4, 3, 3, 0, 0, 0, 0, 5, 4, 7, 5, 5, 2, 1, 1, 1, 1, 1, 1, 0), # 8
(10, 5, 11, 7, 8, 5, 1, 5, 6, 0, 1, 0, 0, 8, 7, 8, 2, 4, 5, 4, 3, 4, 1, 0, 1, 0), # 9
(5, 11, 8, 5, 8, 1, 4, 3, 1, 1, 3, 0, 0, 6, 10, 1, 8, 8, 4, 2, 1, 1, 5, 2, 0, 0), # 10
(13, 11, 7, 5, 3, 1, 2, 2, 6, 4, 1, 0, 0, 13, 7, 6, 5, 8, 2, 3, 1, 2, 1, 3, 0, 0), # 11
(14, 7, 4, 8, 7, 5, 5, 7, 4, 1, 2, 0, 0, 7, 3, 9, 5, 3, 5, 4, 4, 2, 1, 3, 0, 0), # 12
(13, 11, 6, 9, 6, 6, 2, 1, 2, 2, 2, 2, 0, 18, 11, 4, 5, 2, 5, 4, 2, 2, 2, 2, 1, 0), # 13
(9, 13, 8, 3, 7, 4, 3, 5, 6, 2, 1, 0, 0, 14, 4, 6, 5, 5, 5, 9, 6, 4, 4, 1, 0, 0), # 14
(9, 8, 5, 7, 6, 2, 2, 2, 2, 0, 3, 0, 0, 9, 8, 14, 4, 3, 1, 4, 6, 1, 5, 5, 1, 0), # 15
(6, 6, 11, 2, 7, 1, 4, 3, 4, 3, 2, 1, 0, 7, 5, 8, 6, 4, 6, 2, 1, 0, 1, 0, 0, 0), # 16
(8, 18, 8, 11, 7, 7, 2, 5, 6, 0, 1, 1, 0, 6, 10, 6, 3, 4, 2, 14, 2, 6, 2, 0, 1, 0), # 17
(7, 9, 8, 6, 6, 2, 3, 3, 2, 2, 2, 1, 0, 8, 8, 5, 4, 9, 5, 5, 2, 4, 4, 2, 2, 0), # 18
(7, 6, 6, 4, 2, 5, 4, 3, 2, 4, 0, 2, 0, 8, 4, 10, 7, 10, 4, 3, 3, 8, 2, 1, 0, 0), # 19
(10, 14, 8, 9, 6, 1, 2, 3, 3, 1, 1, 1, 0, 14, 8, 8, 5, 4, 6, 6, 2, 2, 2, 4, 1, 0), # 20
(7, 7, 7, 6, 10, 4, 3, 1, 6, 1, 1, 1, 0, 16, 8, 6, 4, 8, 7, 4, 2, 3, 4, 3, 0, 0), # 21
(8, 12, 8, 13, 7, 7, 5, 6, 2, 2, 0, 2, 0, 9, 11, 8, 8, 6, 4, 2, 5, 4, 5, 2, 2, 0), # 22
(10, 10, 2, 7, 9, 3, 7, 5, 2, 2, 1, 1, 0, 10, 11, 4, 7, 11, 5, 4, 4, 6, 4, 0, 0, 0), # 23
(15, 15, 10, 5, 4, 3, 3, 2, 6, 0, 0, 1, 0, 8, 9, 6, 8, 11, 5, 7, 2, 6, 3, 2, 0, 0), # 24
(11, 5, 10, 9, 7, 2, 7, 3, 3, 3, 0, 0, 0, 11, 15, 7, 9, 10, 3, 2, 4, 5, 3, 2, 0, 0), # 25
(9, 12, 11, 7, 6, 3, 6, 4, 5, 4, 0, 2, 0, 16, 9, 2, 3, 9, 4, 7, 2, 2, 3, 1, 1, 0), # 26
(7, 12, 13, 11, 5, 3, 3, 2, 3, 0, 1, 1, 0, 12, 4, 5, 10, 7, 6, 2, 2, 2, 2, 5, 0, 0), # 27
(7, 10, 4, 15, 8, 2, 5, 3, 4, 1, 2, 2, 0, 12, 11, 5, 4, 2, 7, 4, 2, 1, 0, 1, 0, 0), # 28
(8, 7, 8, 9, 4, 6, 3, 6, 5, 5, 2, 0, 0, 11, 7, 7, 1, 4, 4, 5, 2, 5, 5, 2, 1, 0), # 29
(10, 11, 10, 13, 4, 7, 5, 1, 4, 2, 0, 2, 0, 7, 7, 3, 7, 5, 6, 5, 1, 2, 1, 0, 1, 0), # 30
(7, 11, 8, 11, 9, 1, 3, 4, 3, 1, 2, 0, 0, 10, 7, 6, 7, 6, 5, 3, 3, 5, 4, 1, 0, 0), # 31
(6, 16, 8, 11, 5, 2, 1, 6, 2, 3, 1, 0, 0, 17, 3, 10, 7, 5, 6, 5, 2, 4, 3, 2, 1, 0), # 32
(12, 10, 8, 5, 7, 0, 4, 4, 0, 1, 0, 1, 0, 6, 10, 6, 4, 8, 6, 1, 3, 6, 2, 3, 2, 0), # 33
(10, 12, 6, 12, 8, 1, 4, 4, 5, 5, 0, 0, 0, 9, 10, 7, 12, 7, 6, 6, 4, 3, 7, 3, 2, 0), # 34
(5, 4, 8, 10, 7, 3, 3, 5, 6, 0, 1, 0, 0, 15, 6, 11, 7, 6, 3, 1, 4, 5, 1, 1, 0, 0), # 35
(8, 5, 4, 8, 9, 4, 5, 5, 2, 0, 0, 1, 0, 4, 8, 12, 5, 10, 4, 6, 2, 3, 2, 1, 0, 0), # 36
(6, 5, 7, 8, 11, 2, 7, 7, 6, 0, 1, 0, 0, 11, 13, 7, 6, 8, 5, 3, 2, 4, 7, 2, 2, 0), # 37
(13, 16, 16, 10, 4, 3, 6, 3, 4, 1, 0, 0, 0, 6, 9, 8, 5, 9, 3, 7, 2, 6, 6, 1, 2, 0), # 38
(4, 7, 8, 13, 5, 2, 2, 1, 1, 3, 2, 2, 0, 11, 8, 9, 3, 12, 10, 6, 2, 5, 2, 0, 2, 0), # 39
(13, 7, 5, 5, 5, 2, 6, 3, 3, 5, 1, 0, 0, 9, 5, 6, 3, 9, 3, 6, 2, 2, 3, 3, 1, 0), # 40
(4, 11, 12, 12, 10, 7, 3, 3, 7, 1, 2, 0, 0, 11, 10, 9, 5, 10, 2, 3, 2, 5, 4, 2, 4, 0), # 41
(7, 10, 10, 9, 7, 7, 5, 2, 2, 1, 0, 0, 0, 13, 5, 4, 7, 4, 6, 7, 4, 6, 2, 0, 1, 0), # 42
(10, 9, 10, 8, 6, 3, 0, 1, 3, 5, 1, 1, 0, 12, 13, 7, 3, 7, 8, 2, 5, 3, 4, 2, 1, 0), # 43
(6, 12, 13, 9, 7, 4, 6, 6, 5, 3, 1, 3, 0, 10, 13, 8, 7, 5, 5, 3, 3, 2, 3, 2, 0, 0), # 44
(10, 11, 5, 13, 8, 3, 4, 5, 2, 0, 3, 0, 0, 17, 7, 5, 3, 3, 3, 6, 2, 1, 2, 1, 0, 0), # 45
(9, 6, 4, 10, 7, 3, 6, 5, 7, 3, 2, 0, 0, 12, 4, 7, 6, 7, 3, 5, 2, 4, 3, 0, 1, 0), # 46
(17, 11, 7, 14, 10, 2, 3, 3, 3, 0, 3, 1, 0, 10, 6, 6, 7, 5, 5, 4, 4, 1, 2, 3, 0, 0), # 47
(13, 11, 10, 10, 5, 4, 2, 6, 3, 2, 2, 0, 0, 8, 13, 8, 3, 5, 2, 2, 4, 6, 1, 3, 1, 0), # 48
(8, 6, 9, 12, 11, 4, 4, 4, 3, 4, 2, 0, 0, 9, 9, 4, 9, 11, 3, 6, 5, 3, 5, 2, 1, 0), # 49
(13, 7, 6, 10, 9, 6, 5, 1, 6, 1, 1, 0, 0, 5, 5, 5, 4, 10, 5, 3, 0, 5, 2, 2, 3, 0), # 50
(8, 11, 10, 13, 4, 8, 3, 4, 6, 1, 2, 0, 0, 9, 14, 11, 3, 3, 2, 4, 3, 4, 0, 0, 0, 0), # 51
(6, 5, 11, 16, 9, 5, 6, 4, 1, 0, 0, 0, 0, 14, 10, 4, 4, 8, 3, 4, 5, 2, 4, 2, 0, 0), # 52
(9, 7, 7, 12, 7, 2, 4, 4, 6, 1, 1, 0, 0, 13, 7, 9, 5, 5, 8, 4, 6, 4, 3, 5, 1, 0), # 53
(4, 8, 9, 9, 3, 2, 4, 7, 7, 2, 1, 0, 0, 10, 5, 6, 4, 14, 3, 5, 5, 5, 4, 1, 0, 0), # 54
(14, 6, 9, 8, 4, 1, 2, 3, 1, 2, 0, 0, 0, 9, 11, 3, 6, 3, 5, 6, 1, 3, 3, 3, 2, 0), # 55
(4, 11, 8, 8, 12, 2, 0, 7, 1, 4, 3, 3, 0, 12, 14, 8, 6, 12, 2, 4, 4, 5, 3, 2, 0, 0), # 56
(14, 9, 8, 9, 6, 3, 5, 6, 4, 0, 0, 0, 0, 12, 7, 8, 6, 6, 5, 5, 2, 2, 4, 0, 1, 0), # 57
(10, 9, 9, 13, 5, 7, 5, 7, 1, 2, 2, 1, 0, 9, 10, 9, 7, 13, 2, 4, 2, 6, 2, 0, 2, 0), # 58
(11, 15, 7, 11, 10, 6, 4, 2, 6, 1, 2, 0, 0, 12, 11, 10, 2, 9, 6, 5, 2, 2, 3, 2, 1, 0), # 59
(14, 6, 7, 9, 10, 4, 3, 3, 7, 3, 2, 1, 0, 8, 11, 6, 6, 7, 6, 4, 6, 6, 2, 1, 0, 0), # 60
(11, 5, 7, 8, 7, 1, 2, 3, 2, 1, 1, 1, 0, 13, 4, 8, 5, 8, 4, 4, 3, 4, 2, 2, 3, 0), # 61
(11, 8, 14, 11, 4, 2, 4, 4, 3, 2, 2, 0, 0, 18, 10, 8, 3, 11, 3, 3, 3, 3, 2, 1, 0, 0), # 62
(16, 9, 7, 10, 8, 2, 2, 2, 3, 2, 3, 0, 0, 8, 6, 3, 3, 17, 1, 2, 2, 4, 5, 3, 1, 0), # 63
(18, 9, 7, 12, 7, 5, 1, 3, 6, 1, 1, 1, 0, 6, 11, 9, 3, 7, 4, 4, 2, 2, 5, 2, 1, 0), # 64
(14, 6, 14, 5, 4, 4, 6, 5, 4, 0, 1, 0, 0, 11, 8, 7, 6, 5, 2, 3, 1, 2, 6, 0, 0, 0), # 65
(15, 5, 9, 10, 5, 4, 3, 2, 4, 1, 2, 2, 0, 11, 10, 8, 7, 5, 3, 6, 1, 3, 6, 1, 2, 0), # 66
(11, 5, 15, 10, 4, 0, 2, 3, 6, 1, 3, 0, 0, 9, 6, 7, 6, 10, 2, 5, 3, 5, 3, 1, 1, 0), # 67
(6, 10, 15, 10, 9, 4, 2, 2, 1, 2, 2, 2, 0, 16, 6, 9, 6, 4, 2, 4, 2, 4, 4, 2, 0, 0), # 68
(15, 12, 13, 5, 6, 6, 6, 3, 2, 1, 0, 1, 0, 11, 14, 11, 7, 9, 5, 6, 4, 4, 7, 0, 2, 0), # 69
(9, 13, 2, 10, 8, 6, 4, 1, 4, 1, 2, 2, 0, 11, 11, 7, 6, 8, 2, 4, 4, 2, 4, 1, 2, 0), # 70
(12, 7, 9, 7, 15, 3, 4, 2, 4, 2, 1, 1, 0, 10, 13, 5, 7, 9, 4, 5, 3, 8, 3, 0, 0, 0), # 71
(12, 3, 10, 4, 7, 4, 2, 5, 2, 3, 0, 2, 0, 12, 8, 12, 7, 8, 6, 4, 5, 7, 5, 2, 1, 0), # 72
(9, 9, 11, 5, 10, 2, 5, 0, 4, 1, 0, 0, 0, 6, 6, 8, 3, 5, 2, 6, 1, 2, 4, 0, 1, 0), # 73
(7, 8, 8, 8, 9, 2, 1, 4, 3, 2, 0, 0, 0, 5, 3, 6, 9, 10, 4, 5, 2, 3, 1, 3, 0, 0), # 74
(13, 13, 8, 12, 9, 3, 2, 1, 5, 3, 2, 0, 0, 8, 6, 6, 4, 8, 2, 2, 3, 4, 3, 0, 1, 0), # 75
(8, 2, 7, 6, 8, 3, 4, 0, 5, 1, 0, 1, 0, 13, 13, 12, 8, 9, 3, 1, 7, 3, 2, 3, 3, 0), # 76
(9, 11, 8, 4, 14, 3, 2, 1, 4, 1, 3, 0, 0, 9, 13, 4, 6, 6, 5, 2, 1, 1, 3, 0, 0, 0), # 77
(11, 8, 4, 9, 10, 4, 2, 0, 6, 4, 1, 2, 0, 7, 8, 7, 6, 11, 7, 4, 2, 4, 2, 2, 0, 0), # 78
(11, 7, 7, 8, 11, 6, 0, 5, 5, 2, 0, 0, 0, 10, 8, 6, 7, 7, 6, 5, 5, 5, 4, 1, 0, 0), # 79
(8, 9, 10, 9, 14, 2, 3, 6, 0, 2, 0, 1, 0, 7, 10, 6, 12, 7, 2, 3, 0, 2, 1, 2, 0, 0), # 80
(12, 8, 8, 11, 8, 6, 8, 4, 2, 0, 0, 1, 0, 17, 9, 5, 9, 12, 4, 5, 6, 3, 2, 2, 1, 0), # 81
(12, 6, 8, 12, 7, 2, 5, 3, 3, 1, 1, 1, 0, 10, 7, 8, 7, 6, 2, 2, 3, 5, 2, 1, 0, 0), # 82
(9, 16, 8, 14, 11, 2, 1, 2, 2, 2, 0, 1, 0, 4, 8, 11, 6, 7, 1, 3, 2, 2, 2, 1, 1, 0), # 83
(10, 6, 5, 11, 4, 6, 4, 1, 2, 2, 0, 0, 0, 10, 8, 5, 2, 8, 6, 8, 0, 2, 4, 3, 0, 0), # 84
(11, 11, 9, 8, 4, 2, 5, 2, 1, 0, 1, 1, 0, 17, 10, 6, 8, 12, 3, 4, 1, 2, 2, 0, 1, 0), # 85
(8, 7, 5, 3, 10, 3, 8, 3, 2, 2, 3, 0, 0, 8, 9, 6, 5, 6, 2, 1, 4, 4, 6, 1, 0, 0), # 86
(10, 7, 9, 10, 7, 1, 7, 2, 4, 5, 1, 0, 0, 9, 9, 8, 7, 7, 7, 1, 4, 4, 4, 0, 0, 0), # 87
(8, 6, 11, 19, 4, 1, 3, 2, 6, 1, 1, 2, 0, 8, 12, 10, 8, 5, 4, 3, 4, 1, 1, 4, 1, 0), # 88
(8, 6, 10, 6, 5, 1, 1, 2, 3, 3, 1, 3, 0, 5, 6, 10, 6, 2, 1, 3, 5, 2, 3, 0, 0, 0), # 89
(6, 8, 9, 15, 4, 2, 6, 1, 1, 2, 0, 1, 0, 9, 7, 6, 7, 4, 5, 2, 4, 2, 3, 4, 0, 0), # 90
(8, 9, 7, 9, 12, 4, 4, 3, 6, 3, 1, 0, 0, 12, 6, 6, 7, 5, 6, 6, 1, 7, 4, 2, 0, 0), # 91
(9, 9, 7, 13, 8, 2, 4, 1, 3, 5, 0, 1, 0, 9, 7, 7, 2, 5, 3, 2, 2, 3, 3, 2, 2, 0), # 92
(9, 8, 5, 13, 7, 2, 3, 2, 3, 3, 1, 0, 0, 14, 8, 9, 9, 8, 1, 2, 3, 3, 2, 1, 1, 0), # 93
(6, 9, 8, 4, 6, 2, 1, 0, 11, 1, 0, 2, 0, 4, 14, 6, 6, 4, 4, 1, 5, 3, 1, 2, 1, 0), # 94
(9, 8, 5, 11, 3, 7, 1, 4, 7, 1, 2, 2, 0, 7, 9, 5, 4, 12, 2, 3, 5, 3, 2, 2, 0, 0), # 95
(9, 13, 6, 10, 4, 1, 1, 3, 2, 2, 1, 0, 0, 8, 10, 5, 7, 9, 4, 1, 5, 6, 4, 2, 0, 0), # 96
(7, 7, 6, 9, 4, 5, 5, 1, 3, 3, 1, 2, 0, 17, 9, 9, 5, 7, 4, 3, 1, 7, 3, 1, 0, 0), # 97
(8, 5, 11, 9, 7, 5, 4, 4, 1, 2, 0, 1, 0, 18, 9, 5, 3, 10, 4, 6, 2, 2, 4, 1, 1, 0), # 98
(10, 6, 7, 12, 6, 7, 5, 1, 1, 2, 2, 2, 0, 7, 6, 8, 4, 6, 4, 1, 2, 4, 4, 1, 3, 0), # 99
(8, 10, 6, 5, 5, 4, 5, 3, 6, 0, 1, 1, 0, 18, 3, 5, 3, 8, 1, 6, 2, 2, 2, 1, 3, 0), # 100
(4, 5, 6, 11, 5, 3, 4, 1, 4, 4, 0, 1, 0, 10, 5, 9, 2, 5, 2, 3, 3, 4, 4, 4, 0, 0), # 101
(9, 6, 6, 10, 10, 5, 3, 1, 1, 1, 1, 2, 0, 11, 9, 6, 7, 11, 3, 4, 3, 3, 7, 1, 1, 0), # 102
(6, 7, 6, 6, 7, 6, 2, 3, 5, 1, 2, 0, 0, 12, 12, 6, 4, 5, 4, 3, 2, 7, 5, 3, 1, 0), # 103
(13, 12, 7, 10, 9, 1, 5, 2, 1, 0, 3, 0, 0, 9, 4, 4, 4, 13, 5, 3, 2, 3, 2, 1, 2, 0), # 104
(11, 6, 8, 7, 6, 7, 2, 5, 2, 2, 0, 1, 0, 14, 8, 2, 6, 3, 1, 2, 4, 5, 1, 1, 0, 0), # 105
(6, 6, 6, 10, 8, 4, 9, 2, 2, 1, 1, 0, 0, 4, 5, 10, 5, 8, 3, 0, 3, 4, 3, 1, 2, 0), # 106
(8, 5, 7, 1, 3, 3, 5, 3, 2, 0, 0, 0, 0, 8, 9, 8, 6, 11, 2, 2, 2, 1, 3, 1, 2, 0), # 107
(5, 9, 9, 7, 11, 2, 3, 2, 8, 0, 0, 1, 0, 9, 12, 1, 5, 9, 3, 3, 2, 7, 2, 3, 1, 0), # 108
(12, 10, 8, 5, 12, 3, 0, 4, 9, 0, 0, 2, 0, 6, 11, 8, 5, 13, 0, 1, 1, 7, 1, 2, 1, 0), # 109
(5, 9, 3, 7, 6, 1, 1, 3, 5, 1, 3, 1, 0, 8, 2, 5, 2, 9, 4, 0, 2, 6, 3, 4, 1, 0), # 110
(9, 8, 6, 10, 8, 5, 0, 6, 3, 0, 0, 1, 0, 9, 9, 10, 6, 8, 3, 3, 2, 2, 5, 2, 2, 0), # 111
(11, 9, 13, 3, 4, 4, 7, 1, 3, 0, 1, 1, 0, 8, 9, 5, 6, 5, 3, 3, 2, 6, 7, 0, 1, 0), # 112
(10, 6, 14, 10, 7, 1, 2, 4, 4, 1, 1, 0, 0, 14, 10, 1, 2, 10, 4, 2, 1, 4, 4, 3, 0, 0), # 113
(10, 7, 12, 9, 7, 5, 1, 3, 3, 2, 1, 1, 0, 9, 6, 5, 7, 5, 3, 2, 4, 5, 6, 0, 0, 0), # 114
(15, 8, 8, 8, 6, 4, 1, 1, 10, 3, 2, 2, 0, 5, 12, 10, 6, 8, 6, 2, 4, 5, 7, 2, 2, 0), # 115
(10, 5, 5, 7, 6, 3, 2, 6, 4, 1, 0, 1, 0, 7, 6, 8, 2, 7, 9, 2, 0, 4, 3, 2, 2, 0), # 116
(7, 7, 10, 7, 6, 6, 1, 1, 1, 1, 0, 1, 0, 7, 11, 3, 5, 10, 3, 1, 1, 4, 3, 3, 0, 0), # 117
(8, 7, 7, 8, 7, 6, 0, 3, 4, 1, 0, 0, 0, 10, 6, 7, 8, 8, 3, 1, 4, 4, 1, 4, 0, 0), # 118
(6, 9, 5, 7, 8, 2, 3, 2, 3, 3, 0, 0, 0, 9, 10, 6, 5, 8, 5, 5, 2, 6, 3, 0, 0, 0), # 119
(14, 9, 4, 9, 6, 3, 4, 1, 0, 3, 2, 1, 0, 19, 5, 5, 3, 10, 2, 3, 3, 3, 0, 0, 1, 0), # 120
(9, 9, 6, 12, 7, 4, 1, 2, 3, 1, 2, 2, 0, 7, 3, 3, 4, 11, 5, 3, 2, 5, 0, 0, 1, 0), # 121
(8, 11, 7, 7, 12, 1, 2, 1, 2, 3, 3, 1, 0, 7, 8, 5, 5, 6, 4, 4, 4, 2, 4, 0, 1, 0), # 122
(6, 4, 8, 10, 12, 1, 3, 2, 7, 1, 1, 1, 0, 4, 4, 5, 5, 8, 5, 3, 3, 2, 4, 2, 0, 0), # 123
(9, 10, 9, 7, 4, 3, 1, 7, 2, 1, 2, 1, 0, 8, 9, 5, 6, 6, 3, 5, 2, 4, 3, 1, 1, 0), # 124
(7, 8, 4, 9, 14, 2, 3, 2, 3, 4, 2, 0, 0, 8, 5, 5, 5, 9, 4, 5, 3, 4, 1, 2, 1, 0), # 125
(8, 10, 3, 13, 3, 6, 5, 6, 4, 2, 3, 0, 0, 12, 10, 4, 3, 6, 4, 1, 1, 3, 1, 0, 0, 0), # 126
(8, 4, 3, 9, 9, 3, 1, 2, 6, 0, 0, 1, 0, 4, 17, 4, 2, 6, 6, 0, 2, 4, 5, 1, 0, 0), # 127
(9, 8, 10, 8, 8, 1, 2, 3, 1, 1, 0, 1, 0, 5, 8, 6, 2, 13, 2, 5, 4, 4, 0, 3, 1, 0), # 128
(10, 11, 15, 7, 3, 3, 3, 1, 6, 2, 2, 1, 0, 7, 9, 1, 6, 7, 1, 6, 3, 1, 1, 1, 2, 0), # 129
(5, 6, 15, 6, 10, 0, 4, 0, 3, 2, 1, 0, 0, 6, 4, 7, 7, 7, 4, 3, 0, 4, 2, 0, 0, 0), # 130
(9, 5, 8, 4, 7, 7, 1, 1, 4, 0, 1, 0, 0, 10, 5, 5, 7, 6, 3, 3, 1, 2, 1, 0, 1, 0), # 131
(6, 8, 5, 4, 8, 4, 0, 3, 3, 1, 1, 1, 0, 9, 5, 4, 2, 8, 1, 2, 1, 2, 3, 1, 1, 0), # 132
(7, 7, 6, 9, 7, 6, 2, 5, 1, 3, 1, 0, 0, 5, 7, 3, 5, 6, 6, 5, 0, 5, 3, 0, 1, 0), # 133
(11, 9, 8, 9, 4, 3, 1, 2, 3, 0, 4, 1, 0, 11, 8, 6, 5, 5, 4, 3, 1, 4, 1, 1, 0, 0), # 134
(7, 5, 4, 10, 5, 5, 4, 1, 5, 4, 1, 1, 0, 6, 10, 6, 2, 9, 0, 4, 1, 2, 3, 2, 0, 0), # 135
(7, 7, 11, 13, 5, 4, 2, 3, 1, 3, 1, 0, 0, 3, 4, 3, 5, 8, 3, 3, 3, 4, 3, 0, 0, 0), # 136
(9, 5, 6, 11, 2, 1, 0, 1, 8, 1, 1, 1, 0, 6, 6, 5, 8, 3, 2, 2, 4, 6, 3, 3, 0, 0), # 137
(5, 2, 8, 7, 8, 1, 1, 1, 2, 1, 3, 1, 0, 12, 3, 5, 3, 9, 3, 5, 1, 3, 2, 2, 0, 0), # 138
(11, 9, 9, 7, 3, 1, 5, 3, 2, 1, 2, 0, 0, 8, 9, 4, 2, 6, 7, 0, 1, 7, 3, 3, 0, 0), # 139
(4, 4, 5, 6, 6, 5, 1, 4, 5, 2, 2, 0, 0, 9, 6, 8, 4, 7, 3, 5, 4, 2, 1, 1, 0, 0), # 140
(5, 8, 5, 8, 9, 3, 6, 3, 3, 2, 1, 1, 0, 6, 7, 2, 3, 5, 4, 2, 2, 1, 1, 1, 0, 0), # 141
(8, 5, 7, 6, 7, 4, 3, 1, 5, 2, 1, 0, 0, 3, 5, 8, 3, 6, 1, 0, 1, 1, 0, 2, 0, 0), # 142
(5, 6, 5, 3, 10, 2, 1, 1, 4, 2, 1, 0, 0, 3, 6, 7, 6, 11, 5, 3, 6, 3, 4, 1, 1, 0), # 143
(6, 12, 8, 11, 7, 3, 3, 5, 3, 0, 0, 1, 0, 8, 7, 8, 6, 7, 3, 1, 0, 6, 2, 0, 0, 0), # 144
(10, 6, 7, 8, 11, 3, 2, 2, 5, 2, 1, 1, 0, 11, 10, 6, 6, 4, 2, 2, 2, 6, 1, 4, 1, 0), # 145
(6, 5, 10, 10, 7, 3, 4, 1, 5, 1, 0, 0, 0, 16, 5, 3, 5, 4, 4, 3, 1, 4, 2, 1, 0, 0), # 146
(9, 3, 10, 5, 4, 5, 1, 3, 2, 1, 0, 1, 0, 7, 6, 4, 6, 4, 2, 5, 0, 2, 3, 2, 0, 0), # 147
(4, 8, 10, 9, 5, 5, 2, 1, 3, 3, 1, 2, 0, 15, 9, 7, 9, 4, 2, 3, 2, 2, 1, 5, 0, 0), # 148
(9, 5, 5, 8, 4, 4, 3, 3, 2, 0, 0, 0, 0, 7, 8, 1, 0, 6, 5, 4, 0, 5, 2, 0, 4, 0), # 149
(6, 7, 5, 9, 12, 3, 2, 3, 2, 0, 0, 1, 0, 5, 8, 3, 4, 8, 0, 1, 3, 3, 1, 3, 1, 0), # 150
(8, 5, 11, 7, 6, 5, 0, 7, 2, 1, 0, 1, 0, 12, 5, 6, 3, 6, 2, 0, 2, 2, 1, 1, 0, 0), # 151
(4, 2, 6, 6, 6, 4, 1, 0, 3, 0, 3, 1, 0, 11, 6, 7, 4, 9, 7, 2, 1, 4, 1, 0, 1, 0), # 152
(10, 4, 5, 7, 3, 1, 5, 5, 6, 1, 0, 0, 0, 9, 4, 7, 2, 6, 2, 3, 4, 2, 2, 2, 2, 0), # 153
(6, 6, 9, 9, 5, 5, 4, 2, 7, 2, 0, 1, 0, 9, 5, 4, 3, 5, 3, 2, 1, 5, 1, 0, 1, 0), # 154
(7, 4, 9, 8, 4, 2, 1, 3, 3, 1, 0, 0, 0, 5, 5, 7, 4, 6, 3, 3, 5, 1, 3, 1, 0, 0), # 155
(8, 4, 6, 10, 8, 4, 2, 3, 4, 1, 0, 0, 0, 5, 5, 4, 4, 8, 3, 3, 2, 1, 0, 4, 1, 0), # 156
(14, 6, 11, 8, 7, 6, 3, 2, 1, 2, 1, 0, 0, 6, 3, 3, 4, 11, 2, 1, 2, 1, 1, 1, 1, 0), # 157
(5, 8, 5, 7, 7, 3, 3, 1, 4, 1, 0, 1, 0, 9, 8, 7, 2, 6, 2, 4, 0, 3, 1, 2, 1, 0), # 158
(2, 11, 9, 4, 4, 0, 4, 2, 1, 0, 0, 2, 0, 5, 2, 4, 2, 5, 5, 5, 1, 3, 0, 1, 0, 0), # 159
(11, 5, 6, 7, 5, 5, 2, 2, 3, 0, 0, 0, 0, 7, 6, 6, 2, 7, 3, 5, 2, 2, 1, 1, 1, 0), # 160
(7, 7, 9, 7, 2, 3, 1, 2, 3, 2, 3, 0, 0, 4, 8, 3, 6, 6, 1, 1, 3, 2, 1, 1, 1, 0), # 161
(7, 9, 9, 7, 6, 4, 2, 3, 3, 4, 2, 0, 0, 9, 6, 3, 5, 4, 4, 1, 4, 4, 3, 1, 1, 0), # 162
(6, 2, 12, 4, 9, 0, 4, 1, 3, 1, 0, 0, 0, 11, 11, 3, 7, 3, 6, 5, 2, 3, 6, 1, 0, 0), # 163
(9, 6, 4, 4, 9, 3, 7, 2, 3, 0, 0, 1, 0, 8, 8, 2, 4, 8, 3, 3, 1, 1, 1, 2, 0, 0), # 164
(8, 4, 7, 5, 4, 1, 1, 4, 2, 2, 0, 1, 0, 2, 4, 5, 9, 2, 2, 2, 1, 4, 2, 2, 1, 0), # 165
(3, 3, 7, 7, 5, 4, 0, 2, 3, 1, 1, 1, 0, 8, 6, 6, 3, 5, 2, 1, 2, 1, 0, 1, 0, 0), # 166
(5, 2, 4, 5, 7, 4, 2, 1, 3, 1, 0, 1, 0, 4, 5, 0, 2, 3, 3, 3, 0, 1, 2, 0, 0, 0), # 167
(7, 4, 7, 3, 4, 2, 0, 1, 1, 1, 0, 0, 0, 12, 6, 3, 4, 5, 5, 3, 3, 2, 1, 1, 1, 0), # 168
(5, 5, 2, 9, 6, 1, 3, 3, 1, 0, 2, 1, 0, 4, 11, 3, 3, 5, 6, 3, 2, 3, 1, 0, 1, 0), # 169
(3, 5, 4, 5, 6, 1, 0, 3, 2, 0, 1, 0, 0, 4, 3, 2, 4, 3, 1, 1, 0, 1, 1, 1, 1, 0), # 170
(4, 4, 3, 4, 3, 2, 4, 1, 5, 1, 0, 0, 0, 6, 0, 2, 0, 5, 4, 2, 2, 0, 1, 1, 0, 0), # 171
(6, 2, 6, 1, 6, 3, 0, 2, 0, 0, 0, 1, 0, 10, 5, 6, 2, 6, 2, 2, 1, 4, 2, 3, 0, 0), # 172
(6, 1, 5, 9, 3, 2, 0, 1, 3, 2, 2, 1, 0, 6, 4, 8, 1, 5, 2, 2, 1, 2, 1, 1, 2, 0), # 173
(7, 3, 2, 4, 3, 2, 2, 4, 2, 1, 1, 0, 0, 5, 8, 2, 2, 8, 3, 1, 3, 2, 1, 1, 0, 0), # 174
(8, 2, 4, 4, 3, 1, 1, 1, 4, 1, 1, 0, 0, 6, 9, 2, 3, 6, 4, 3, 1, 2, 2, 1, 1, 0), # 175
(4, 6, 4, 1, 3, 0, 2, 0, 0, 0, 0, 0, 0, 2, 1, 2, 2, 4, 2, 1, 0, 2, 1, 1, 0, 0), # 176
(5, 3, 3, 3, 2, 0, 0, 3, 0, 2, 3, 0, 0, 5, 3, 2, 1, 2, 2, 1, 1, 2, 0, 1, 0, 0), # 177
(6, 0, 3, 6, 4, 0, 1, 0, 0, 0, 0, 0, 0, 6, 4, 4, 2, 2, 0, 0, 2, 2, 3, 1, 1, 0), # 178
(0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0), # 179
)
station_arriving_intensity = (
(5.020865578371768, 5.525288559693166, 5.211283229612507, 6.214667773863432, 5.554685607609612, 3.1386549320373387, 4.146035615373915, 4.653176172979423, 6.090099062168007, 3.9580150155223697, 4.205265163885603, 4.897915078306173, 5.083880212578363), # 0
(5.354327152019974, 5.890060694144759, 5.555346591330152, 6.625144253276616, 5.922490337474237, 3.3459835840425556, 4.419468941263694, 4.959513722905708, 6.492245326332909, 4.21898069227715, 4.483096135956131, 5.221216660814354, 5.419791647439855), # 1
(5.686723008979731, 6.253385170890979, 5.8980422855474135, 7.033987704664794, 6.288962973749744, 3.5524851145124448, 4.691818507960704, 5.264625247904419, 6.892786806877549, 4.478913775020546, 4.759823148776313, 5.543232652053055, 5.75436482820969), # 2
(6.016757793146562, 6.613820501936447, 6.238010869319854, 7.439576407532074, 6.652661676001902, 3.757340622585113, 4.962003641647955, 5.567301157494507, 7.290135160921093, 4.736782698426181, 5.0343484118273825, 5.862685684930461, 6.086272806254225), # 3
(6.343136148415981, 6.9699251992857745, 6.573892899703036, 7.840288641382569, 7.012144603796492, 3.9597312073986677, 5.2289436685084585, 5.866331861194915, 7.682702045582707, 4.991555897167679, 5.305574134590575, 6.178298392354764, 6.414188632939817), # 4
(6.66456271868351, 7.320257774943588, 6.9043289337525175, 8.234502685720393, 7.36596991669928, 4.158837968091214, 5.491557914725224, 6.160507768524592, 8.068899117981559, 5.242201805918663, 5.572402526547132, 6.488793407234148, 6.736785359632827), # 5
(6.979742147844666, 7.663376740914501, 7.227959528523866, 8.620596820049652, 7.712695774276043, 4.353842003800864, 5.7487657064812625, 6.4486192890024885, 8.447138035236815, 5.487688859352758, 5.833735797178282, 6.792893362476808, 7.052736037699606), # 6
(7.2873790797949685, 7.997840609203132, 7.543425241072635, 8.996949323874462, 8.050880336092554, 4.543924413665721, 5.999486369959585, 6.729456832147552, 8.815830454467644, 5.726985492143586, 6.088476155965268, 7.089320890990929, 7.360713718506519), # 7
(7.586178158429934, 8.322207891814099, 7.849366628454396, 9.361938476698928, 8.379081761714586, 4.7282662968238895, 6.2426392313431975, 7.001810807478725, 9.173388032793206, 5.959060138964774, 6.335525812389321, 7.376798625684702, 7.659391453419917), # 8
(7.874844027645085, 8.635037100752022, 8.144424247724704, 9.713942558027169, 8.69585821070791, 4.906048752413484, 6.47714361681512, 7.264471624514963, 9.518222427332674, 6.182881234489941, 6.573786975931678, 7.654049199466313, 7.947442293806162), # 9
(8.152081331335932, 8.934886748021516, 8.427238655939124, 10.051339847363288, 8.9997678426383, 5.076452879572607, 6.701918852558355, 7.516229692775211, 9.848745295205214, 6.397417213392714, 6.802161856073574, 7.919795245243952, 8.22353929103161), # 10
(8.416594713398005, 9.220315345627206, 8.696450410153215, 10.372508624211397, 9.289368817071534, 5.238659777439368, 6.915884264755916, 7.7558754217784145, 10.163368293529993, 6.601636510346719, 7.019552662296249, 8.17275939592581, 8.486355496462611), # 11
(8.667088817726812, 9.489881405573698, 8.95070006742254, 10.675827168075612, 9.563219293573377, 5.391850545151869, 7.1179591795908115, 7.982199221043521, 10.460503079426179, 6.794507560025572, 7.224861604080934, 8.411664284420068, 8.734563961465534), # 12
(8.902268288217876, 9.74214343986562, 9.188628184802662, 10.959673758460044, 9.819877431709601, 5.5352062818482235, 7.307062923246056, 8.193991500089481, 10.738561310012932, 6.974998797102904, 7.416990890908869, 8.63523254363492, 8.966837737406735), # 13
(9.120837768766716, 9.975659960507588, 9.408875319349146, 11.222426674868792, 10.05790139104599, 5.667908086666534, 7.482114821904661, 8.390042668435246, 10.995954642409421, 7.142078656252334, 7.594842732261284, 8.84218680647856, 9.181849875652563), # 14
(9.321501903268855, 10.188989479504217, 9.610082028117542, 11.462464196805985, 10.275849331148308, 5.789137058744912, 7.642034201749626, 8.569143135599756, 11.23109473373482, 7.29471557214749, 7.757319337619419, 9.031249705859171, 9.37827342756938), # 15
(9.5029653356198, 10.380690508860132, 9.790888868163425, 11.678164603775716, 10.472279411582333, 5.898074297221459, 7.785740388963976, 8.73008331110196, 11.442393241108286, 7.431877979461996, 7.9033229164645125, 9.20114387468494, 9.554781444523545), # 16
(9.663932709715075, 10.549321560579946, 9.949936396542352, 11.867906175282112, 10.645749791913838, 5.993900901234285, 7.9121527097307105, 8.871653604460818, 11.628261821648984, 7.552534312869467, 8.031755678277799, 9.350591945864055, 9.710046977881415), # 17
(9.803108669450204, 10.693441146668274, 10.08586517030988, 12.030067190829278, 10.794818631708589, 6.075797969921503, 8.020190490232851, 8.99264442519526, 11.787112132476096, 7.6556530070435365, 8.141519832540508, 9.478316552304715, 9.842743079009345), # 18
(9.919197858720699, 10.811607779129744, 10.197315746521578, 12.163025929921314, 10.918044090532366, 6.142946602421208, 8.108773056653394, 9.091846182824245, 11.917355830708779, 7.740202496657828, 8.231517588733878, 9.583040326915096, 9.951542799273696), # 19
(10.010904921422082, 10.902379969968962, 10.282928682233003, 12.265160672062354, 11.013984327950944, 6.194527897871518, 8.176819735175362, 9.168049286866717, 12.017404573466198, 7.805151216385958, 8.30065115633915, 9.66348590260339, 10.035119190040824), # 20
(10.076934501449866, 10.964316231190558, 10.341344534499719, 12.334849696756486, 11.081197503530088, 6.229722955410535, 8.223249851981759, 9.220044146841623, 12.085670017867521, 7.849467600901555, 8.34782274483756, 9.718375912277793, 10.092145302677078), # 21
(10.115991242699579, 10.995975074799144, 10.371203860377285, 12.370471283507836, 11.118241776835575, 6.247712874176367, 8.2469827332556, 9.246621172267915, 12.120563821031915, 7.872120084878242, 8.37193456371034, 9.74643298884649, 10.121294188548827), # 22
(10.13039336334264, 10.999723593964335, 10.374923182441702, 12.374930812757203, 11.127732056032597, 6.25, 8.249804002259339, 9.249493827160494, 12.124926234567901, 7.874792272519433, 8.37495803716174, 9.749897576588934, 10.125), # 23
(10.141012413034153, 10.997537037037038, 10.374314814814815, 12.374381944444446, 11.133107613614852, 6.25, 8.248253812636166, 9.2455, 12.124341666666666, 7.87315061728395, 8.37462457912458, 9.749086419753086, 10.125), # 24
(10.15140723021158, 10.993227023319616, 10.373113854595337, 12.373296039094651, 11.138364945594503, 6.25, 8.24519890260631, 9.237654320987655, 12.123186728395062, 7.869918838591678, 8.373963399426362, 9.747485139460448, 10.125), # 25
(10.161577019048034, 10.986859396433472, 10.371336762688616, 12.37168544238683, 11.143503868421105, 6.25, 8.240686718308721, 9.226104938271606, 12.1214762345679, 7.865150708733425, 8.372980483850855, 9.745115683584821, 10.125), # 26
(10.171520983716636, 10.978499999999999, 10.369, 12.369562499999999, 11.148524198544214, 6.25, 8.234764705882354, 9.211, 12.119225, 7.858899999999999, 8.371681818181818, 9.742, 10.125), # 27
(10.181238328390501, 10.968214677640603, 10.366120027434842, 12.366939557613168, 11.153425752413401, 6.25, 8.22748031146615, 9.192487654320988, 12.116447839506172, 7.851220484682213, 8.370073388203018, 9.73816003657979, 10.125), # 28
(10.19072825724275, 10.95606927297668, 10.362713305898492, 12.36382896090535, 11.15820834647822, 6.25, 8.218880981199066, 9.170716049382715, 12.113159567901235, 7.842165935070874, 8.368161179698216, 9.733617741197987, 10.125), # 29
(10.199989974446497, 10.94212962962963, 10.358796296296296, 12.360243055555555, 11.162871797188236, 6.25, 8.209014161220043, 9.145833333333332, 12.109375, 7.83179012345679, 8.365951178451178, 9.728395061728394, 10.125), # 30
(10.209022684174858, 10.926461591220852, 10.354385459533608, 12.356194187242798, 11.167415920993008, 6.25, 8.19792729766804, 9.117987654320988, 12.105108950617284, 7.820146822130773, 8.363449370245666, 9.722513946044812, 10.125), # 31
(10.217825590600954, 10.909131001371742, 10.349497256515773, 12.35169470164609, 11.171840534342095, 6.25, 8.185667836681999, 9.087327160493828, 12.100376234567902, 7.807289803383631, 8.360661740865444, 9.715996342021034, 10.125), # 32
(10.226397897897897, 10.890203703703703, 10.344148148148149, 12.346756944444444, 11.176145453685063, 6.25, 8.172283224400871, 9.054, 12.095191666666667, 7.793272839506173, 8.357594276094275, 9.708864197530863, 10.125), # 33
(10.23473881023881, 10.869745541838133, 10.338354595336076, 12.341393261316872, 11.180330495471466, 6.25, 8.15782090696361, 9.018154320987653, 12.089570061728397, 7.778149702789209, 8.354252961715924, 9.701139460448102, 10.125), # 34
(10.242847531796807, 10.847822359396433, 10.332133058984912, 12.335615997942385, 11.18439547615087, 6.25, 8.142328330509159, 8.979938271604938, 12.083526234567902, 7.761974165523548, 8.350643783514153, 9.692844078646548, 10.125), # 35
(10.250723266745005, 10.824499999999999, 10.3255, 12.3294375, 11.188340212172836, 6.25, 8.12585294117647, 8.9395, 12.077074999999999, 7.7448, 8.346772727272727, 9.684000000000001, 10.125), # 36
(10.258365219256524, 10.799844307270233, 10.318471879286694, 12.322870113168724, 11.192164519986921, 6.25, 8.108442185104494, 8.896987654320988, 12.070231172839506, 7.726680978509374, 8.34264577877541, 9.674629172382259, 10.125), # 37
(10.265772593504476, 10.773921124828533, 10.311065157750342, 12.315926183127573, 11.19586821604269, 6.25, 8.09014350843218, 8.85254938271605, 12.063009567901235, 7.707670873342479, 8.33826892380596, 9.664753543667125, 10.125), # 38
(10.272944593661986, 10.746796296296296, 10.303296296296297, 12.308618055555556, 11.199451116789703, 6.25, 8.071004357298476, 8.806333333333333, 12.055425000000001, 7.687823456790124, 8.333648148148148, 9.654395061728394, 10.125), # 39
(10.279880423902163, 10.718535665294924, 10.295181755829903, 12.300958076131687, 11.202913038677519, 6.25, 8.05107217784233, 8.758487654320989, 12.047492283950618, 7.667192501143119, 8.328789437585733, 9.643575674439873, 10.125), # 40
(10.286579288398128, 10.689205075445816, 10.286737997256516, 12.29295859053498, 11.206253798155702, 6.25, 8.030394416202695, 8.709160493827161, 12.0392262345679, 7.645831778692272, 8.323698777902482, 9.632317329675354, 10.125), # 41
(10.293040391323, 10.658870370370371, 10.277981481481483, 12.284631944444445, 11.209473211673808, 6.25, 8.009018518518518, 8.6585, 12.030641666666668, 7.623795061728395, 8.318382154882155, 9.620641975308642, 10.125), # 42
(10.299262936849892, 10.627597393689987, 10.268928669410151, 12.275990483539095, 11.212571095681403, 6.25, 7.98699193092875, 8.606654320987655, 12.021753395061728, 7.601136122542296, 8.312845554308517, 9.608571559213535, 10.125), # 43
(10.305246129151927, 10.595451989026063, 10.259596021947875, 12.267046553497943, 11.215547266628045, 6.25, 7.964362099572339, 8.553771604938273, 12.0125762345679, 7.577908733424783, 8.307094961965332, 9.596128029263832, 10.125), # 44
(10.310989172402216, 10.5625, 10.25, 12.2578125, 11.218401540963296, 6.25, 7.9411764705882355, 8.5, 12.003124999999999, 7.554166666666667, 8.301136363636363, 9.583333333333332, 10.125), # 45
(10.31649127077388, 10.528807270233196, 10.240157064471878, 12.24830066872428, 11.221133735136716, 6.25, 7.917482490115388, 8.445487654320988, 11.993414506172838, 7.529963694558756, 8.294975745105374, 9.57020941929584, 10.125), # 46
(10.321751628440035, 10.49443964334705, 10.230083676268862, 12.238523405349794, 11.223743665597867, 6.25, 7.893327604292747, 8.390382716049382, 11.983459567901235, 7.505353589391861, 8.288619092156129, 9.55677823502515, 10.125), # 47
(10.326769449573796, 10.459462962962963, 10.219796296296296, 12.228493055555557, 11.22623114879631, 6.25, 7.868759259259259, 8.334833333333334, 11.973275000000001, 7.4803901234567896, 8.28207239057239, 9.543061728395061, 10.125), # 48
(10.331543938348286, 10.42394307270233, 10.209311385459534, 12.218221965020577, 11.228596001181607, 6.25, 7.8438249011538765, 8.278987654320987, 11.96287561728395, 7.455127069044353, 8.275341626137923, 9.529081847279379, 10.125), # 49
(10.336074298936616, 10.387945816186559, 10.198645404663925, 12.207722479423868, 11.230838039203315, 6.25, 7.81857197611555, 8.222993827160494, 11.9522762345679, 7.429618198445358, 8.268432784636488, 9.514860539551899, 10.125), # 50
(10.34035973551191, 10.351537037037037, 10.187814814814814, 12.197006944444444, 11.232957079310998, 6.25, 7.793047930283224, 8.167, 11.941491666666668, 7.403917283950617, 8.261351851851853, 9.50041975308642, 10.125), # 51
(10.344399452247279, 10.314782578875173, 10.176836076817558, 12.186087705761317, 11.234952937954214, 6.25, 7.767300209795852, 8.111154320987653, 11.930536728395062, 7.3780780978509375, 8.254104813567777, 9.485781435756746, 10.125), # 52
(10.348192653315843, 10.27774828532236, 10.165725651577505, 12.174977109053497, 11.23682543158253, 6.25, 7.741376260792383, 8.055604938271605, 11.919426234567903, 7.3521544124371285, 8.246697655568026, 9.470967535436671, 10.125), # 53
(10.351738542890716, 10.2405, 10.154499999999999, 12.1636875, 11.238574376645502, 6.25, 7.715323529411765, 8.000499999999999, 11.908175, 7.3262, 8.239136363636362, 9.456, 10.125), # 54
(10.355036325145022, 10.203103566529492, 10.143175582990398, 12.152231224279834, 11.24019958959269, 6.25, 7.689189461792948, 7.945987654320987, 11.896797839506172, 7.300268632830361, 8.231426923556553, 9.44090077732053, 10.125), # 55
(10.358085204251871, 10.165624828532236, 10.131768861454047, 12.140620627572016, 11.241700886873659, 6.25, 7.663021504074881, 7.892216049382716, 11.885309567901235, 7.274414083219022, 8.223575321112358, 9.425691815272062, 10.125), # 56
(10.360884384384383, 10.12812962962963, 10.120296296296297, 12.128868055555555, 11.243078084937967, 6.25, 7.636867102396514, 7.839333333333334, 11.873725, 7.24869012345679, 8.215587542087542, 9.410395061728394, 10.125), # 57
(10.36343306971568, 10.090683813443073, 10.108774348422497, 12.116985853909464, 11.244331000235174, 6.25, 7.610773702896797, 7.787487654320987, 11.862058950617284, 7.223150525834477, 8.20746957226587, 9.395032464563329, 10.125), # 58
(10.36573046441887, 10.053353223593964, 10.097219478737998, 12.104986368312757, 11.245459449214845, 6.25, 7.584788751714678, 7.736827160493827, 11.850326234567902, 7.197849062642891, 8.1992273974311, 9.379625971650663, 10.125), # 59
(10.367775772667077, 10.016203703703704, 10.085648148148147, 12.092881944444445, 11.246463248326537, 6.25, 7.558959694989106, 7.6875, 11.838541666666668, 7.172839506172839, 8.190867003367003, 9.364197530864198, 10.125), # 60
(10.369568198633415, 9.97930109739369, 10.0740768175583, 12.080684927983539, 11.247342214019811, 6.25, 7.533333978859033, 7.639654320987654, 11.826720061728395, 7.148175628715135, 8.182394375857339, 9.348769090077733, 10.125), # 61
(10.371106946491004, 9.942711248285322, 10.062521947873801, 12.068407664609055, 11.248096162744234, 6.25, 7.507959049463406, 7.5934382716049384, 11.814876234567901, 7.123911202560586, 8.17381550068587, 9.333362597165067, 10.125), # 62
(10.37239122041296, 9.9065, 10.051, 12.056062500000001, 11.248724910949356, 6.25, 7.482882352941176, 7.549, 11.803025, 7.100099999999999, 8.165136363636364, 9.318, 10.125), # 63
(10.373420224572397, 9.870733196159122, 10.039527434842249, 12.043661779835391, 11.249228275084748, 6.25, 7.458151335431292, 7.506487654320988, 11.791181172839506, 7.076795793324188, 8.156362950492579, 9.302703246456334, 10.125), # 64
(10.374193163142438, 9.835476680384087, 10.0281207133059, 12.031217849794238, 11.249606071599967, 6.25, 7.433813443072703, 7.466049382716049, 11.779359567901235, 7.054052354823959, 8.147501247038285, 9.287494284407863, 10.125), # 65
(10.374709240296196, 9.800796296296298, 10.016796296296297, 12.018743055555555, 11.249858116944573, 6.25, 7.409916122004357, 7.427833333333334, 11.767575, 7.031923456790123, 8.138557239057238, 9.272395061728396, 10.125), # 66
(10.374967660206792, 9.766757887517146, 10.005570644718793, 12.006249742798353, 11.24998422756813, 6.25, 7.386506818365206, 7.391987654320989, 11.755842283950617, 7.010462871513489, 8.12953691233321, 9.257427526291723, 10.125), # 67
(10.374791614480825, 9.733248639320323, 9.994405949931412, 11.993641740472357, 11.249877955297345, 6.2498840115836, 7.363515194829646, 7.358343850022862, 11.744087848651121, 6.989620441647166, 8.120285988540376, 9.242530021899743, 10.124875150034294), # 68
(10.373141706924315, 9.699245519713262, 9.982988425925925, 11.980283514492752, 11.248910675381262, 6.248967078189301, 7.340268181346613, 7.325098765432099, 11.731797839506173, 6.968806390704429, 8.10986283891547, 9.227218973359324, 10.12388599537037), # 69
(10.369885787558895, 9.664592459843355, 9.971268432784635, 11.966087124261943, 11.246999314128942, 6.247161255906112, 7.31666013456137, 7.291952446273434, 11.718902892089622, 6.947919524462734, 8.09814888652608, 9.211422761292809, 10.121932334533609), # 70
(10.365069660642929, 9.62931016859153, 9.959250085733881, 11.951073503757382, 11.244168078754136, 6.244495808565767, 7.292701659538988, 7.258915866483768, 11.705422210791038, 6.926960359342639, 8.085187370783862, 9.195152937212715, 10.119039887688615), # 71
(10.358739130434783, 9.593419354838709, 9.946937499999999, 11.935263586956522, 11.240441176470588, 6.2410000000000005, 7.268403361344538, 7.226, 11.691375, 6.905929411764705, 8.07102153110048, 9.17842105263158, 10.115234375), # 72
(10.35094000119282, 9.556940727465816, 9.934334790809327, 11.918678307836823, 11.23584281449205, 6.236703094040542, 7.243775845043092, 7.193215820759031, 11.676780464106082, 6.884827198149493, 8.055694606887588, 9.161238659061919, 10.110541516632374), # 73
(10.341718077175404, 9.519894995353777, 9.921446073388202, 11.901338600375738, 11.230397200032275, 6.231634354519128, 7.218829715699722, 7.160574302697759, 11.661657807498857, 6.863654234917561, 8.039249837556856, 9.143617308016267, 10.104987032750344), # 74
(10.331119162640901, 9.482302867383511, 9.908275462962962, 11.883265398550725, 11.224128540305012, 6.22582304526749, 7.1935755783795, 7.128086419753086, 11.6460262345679, 6.84241103848947, 8.021730462519935, 9.125568551007147, 10.098596643518519), # 75
(10.319189061847677, 9.44418505243595, 9.894827074759945, 11.864479636339238, 11.217061042524005, 6.219298430117361, 7.168024038147495, 7.095763145861912, 11.629904949702789, 6.821098125285779, 8.003179721188491, 9.107103939547082, 10.091396069101508), # 76
(10.305973579054093, 9.40556225939201, 9.881105024005485, 11.845002247718732, 11.209218913903008, 6.212089772900472, 7.142185700068779, 7.063615454961135, 11.613313157293096, 6.7997160117270505, 7.983640852974187, 9.088235025148606, 10.083411029663925), # 77
(10.291518518518519, 9.366455197132618, 9.867113425925925, 11.824854166666666, 11.200626361655774, 6.204226337448559, 7.116071169208425, 7.031654320987655, 11.596270061728394, 6.7782652142338415, 7.9631570972886765, 9.068973359324238, 10.074667245370371), # 78
(10.275869684499314, 9.326884574538697, 9.8528563957476, 11.804056327160493, 11.191307592996047, 6.195737387593354, 7.089691050631501, 6.9998907178783725, 11.578794867398262, 6.756746249226714, 7.941771693543622, 9.049330493586504, 10.065190436385459), # 79
(10.259072881254847, 9.286871100491172, 9.838338048696844, 11.782629663177671, 11.181286815137579, 6.18665218716659, 7.063055949403081, 6.968335619570188, 11.560906778692273, 6.7351596331262265, 7.919527881150688, 9.029317979447935, 10.0550063228738), # 80
(10.241173913043479, 9.246435483870968, 9.8235625, 11.760595108695654, 11.170588235294117, 6.177, 7.036176470588235, 6.937, 11.542625, 6.713505882352941, 7.8964688995215315, 9.008947368421053, 10.044140624999999), # 81
(10.222218584123576, 9.205598433559008, 9.808533864883403, 11.737973597691894, 11.159236060679415, 6.166810089925317, 7.009063219252036, 6.90589483310471, 11.52396873571102, 6.691785513327416, 7.872637988067813, 8.988230212018387, 10.03261906292867), # 82
(10.202252698753504, 9.164380658436214, 9.793256258573388, 11.714786064143853, 11.147254498507221, 6.156111720774272, 6.981726800459553, 6.875031092821216, 11.504957190214906, 6.669999042470211, 7.848078386201194, 8.967178061752461, 10.020467356824417), # 83
(10.181322061191626, 9.122802867383513, 9.777733796296296, 11.691053442028986, 11.134667755991286, 6.144934156378601, 6.954177819275858, 6.844419753086419, 11.485609567901234, 6.648146986201889, 7.822833333333333, 8.945802469135803, 10.007711226851852), # 84
(10.159472475696308, 9.080885769281826, 9.761970593278463, 11.666796665324746, 11.121500040345357, 6.133306660570035, 6.926426880766024, 6.814071787837221, 11.465945073159578, 6.626229860943005, 7.796946068875894, 8.924114985680937, 9.994376393175584), # 85
(10.136749746525913, 9.03865007301208, 9.745970764746229, 11.64203666800859, 11.107775558783183, 6.121258497180309, 6.89848458999512, 6.783998171010516, 11.445982910379517, 6.604248183114124, 7.770459832240534, 8.902127162900394, 9.98048857596022), # 86
(10.113199677938807, 8.996116487455197, 9.729738425925925, 11.61679438405797, 11.09351851851852, 6.108818930041152, 6.870361552028219, 6.75420987654321, 11.425742283950619, 6.582202469135802, 7.743417862838915, 8.879850552306692, 9.96607349537037), # 87
(10.088868074193357, 8.9533057214921, 9.713277692043896, 11.59109074745035, 11.07875312676511, 6.096017222984301, 6.842068371930391, 6.724717878372199, 11.40524239826246, 6.560093235428601, 7.715863400082698, 8.857296705412365, 9.951156871570646), # 88
(10.063800739547922, 8.910238484003717, 9.696592678326475, 11.564946692163177, 11.063503590736707, 6.082882639841488, 6.813615654766708, 6.695533150434385, 11.384502457704619, 6.537920998413083, 7.687839683383544, 8.834477173729935, 9.935764424725651), # 89
(10.03804347826087, 8.866935483870968, 9.6796875, 11.538383152173914, 11.04779411764706, 6.069444444444445, 6.785014005602241, 6.666666666666666, 11.363541666666668, 6.515686274509804, 7.65938995215311, 8.81140350877193, 9.919921875), # 90
(10.011642094590563, 8.823417429974777, 9.662566272290809, 11.511421061460013, 11.031648914709915, 6.055731900624904, 6.756274029502062, 6.638129401005944, 11.342379229538182, 6.4933895801393255, 7.63055744580306, 8.788087262050874, 9.903654942558298), # 91
(9.984642392795372, 8.779705031196071, 9.64523311042524, 11.484081353998926, 11.015092189139029, 6.041774272214601, 6.727406331531242, 6.609932327389118, 11.321034350708734, 6.471031431722209, 7.601385403745053, 8.764539985079297, 9.886989347565157), # 92
(9.957090177133654, 8.735818996415771, 9.62769212962963, 11.456384963768118, 10.998148148148148, 6.027600823045267, 6.69842151675485, 6.582086419753087, 11.299526234567901, 6.448612345679011, 7.57191706539075, 8.74077322936972, 9.869950810185184), # 93
(9.92903125186378, 8.691780034514801, 9.609947445130317, 11.428352824745035, 10.98084099895102, 6.0132408169486355, 6.669330190237961, 6.554602652034752, 11.277874085505259, 6.426132838430297, 7.54219567015181, 8.716798546434674, 9.85256505058299), # 94
(9.90051142124411, 8.647608854374088, 9.592003172153635, 11.400005870907139, 10.963194948761398, 5.9987235177564395, 6.640142957045644, 6.527491998171011, 11.25609710791038, 6.403593426396621, 7.512264457439896, 8.69262748778668, 9.834857788923182), # 95
(9.871576489533012, 8.603326164874554, 9.573863425925927, 11.371365036231884, 10.945234204793028, 5.984078189300411, 6.610870422242971, 6.500765432098766, 11.234214506172838, 6.3809946259985475, 7.482166666666667, 8.668271604938273, 9.816854745370371), # 96
(9.842272260988848, 8.558952674897121, 9.555532321673525, 11.342451254696725, 10.926982974259664, 5.969334095412284, 6.581523190895013, 6.474433927754916, 11.212245484682214, 6.358336953656634, 7.451945537243782, 8.64374244940197, 9.798581640089164), # 97
(9.812644539869984, 8.514509093322713, 9.53701397462277, 11.31328546027912, 10.908465464375052, 5.954520499923793, 6.552111868066842, 6.44850845907636, 11.190209247828074, 6.335620925791441, 7.421644308582906, 8.619051572690298, 9.78006419324417), # 98
(9.782739130434782, 8.470016129032258, 9.5183125, 11.283888586956522, 10.889705882352942, 5.939666666666667, 6.52264705882353, 6.423, 11.168125, 6.312847058823529, 7.391306220095694, 8.59421052631579, 9.761328125), # 99
(9.752601836941611, 8.425494490906676, 9.49943201303155, 11.254281568706388, 10.870728435407084, 5.924801859472641, 6.493139368230145, 6.3979195244627345, 11.146011945587563, 6.290015869173458, 7.36097451119381, 8.569230861790967, 9.742399155521262), # 100
(9.722278463648834, 8.380964887826895, 9.480376628943759, 11.224485339506174, 10.85155733075123, 5.909955342173449, 6.463599401351762, 6.3732780064014625, 11.123889288980338, 6.267127873261788, 7.330692421288912, 8.544124130628353, 9.723303004972564), # 101
(9.691814814814816, 8.336448028673836, 9.461150462962962, 11.194520833333334, 10.832216775599129, 5.895156378600824, 6.43403776325345, 6.349086419753086, 11.1017762345679, 6.244183587509078, 7.300503189792663, 8.518901884340481, 9.704065393518519), # 102
(9.661256694697919, 8.291964622328422, 9.4417576303155, 11.164408984165325, 10.812730977164529, 5.880434232586496, 6.40446505900028, 6.325355738454504, 11.079691986739826, 6.221183528335889, 7.270450056116723, 8.493575674439873, 9.68471204132373), # 103
(9.63064990755651, 8.247535377671579, 9.422202246227709, 11.134170725979603, 10.79312414266118, 5.865818167962201, 6.374891893657326, 6.302096936442616, 11.057655749885688, 6.19812821216278, 7.24057625967275, 8.468157052439054, 9.665268668552812), # 104
(9.600040257648953, 8.203181003584229, 9.402488425925926, 11.103826992753623, 10.773420479302832, 5.851337448559671, 6.345328872289658, 6.279320987654321, 11.035686728395062, 6.175018155410313, 7.210925039872408, 8.442657569850553, 9.64576099537037), # 105
(9.569473549233614, 8.158922208947299, 9.382620284636488, 11.073398718464842, 10.753644194303236, 5.837021338210638, 6.315786599962345, 6.25703886602652, 11.01380412665752, 6.151853874499045, 7.181539636127355, 8.417088778186894, 9.626214741941014), # 106
(9.538995586568856, 8.11477970264171, 9.362601937585735, 11.042906837090714, 10.733819494876139, 5.822899100746838, 6.286275681740461, 6.235261545496114, 10.992027149062643, 6.128635885849539, 7.152463287849252, 8.391462228960604, 9.606655628429355), # 107
(9.508652173913044, 8.070774193548388, 9.3424375, 11.012372282608696, 10.713970588235293, 5.809, 6.256806722689075, 6.214, 10.970375, 6.105364705882353, 7.1237392344497605, 8.365789473684211, 9.587109375), # 108
(9.478489115524543, 8.026926390548255, 9.322131087105625, 10.98181598899624, 10.69412168159445, 5.795353299801859, 6.227390327873262, 6.193265203475081, 10.948866883859168, 6.082040851018047, 7.09541071534054, 8.340082063870238, 9.567601701817559), # 109
(9.448552215661715, 7.983257002522237, 9.301686814128946, 10.951258890230811, 10.674296982167354, 5.7819882639841484, 6.198037102358089, 6.173068129858253, 10.92752200502972, 6.058664837677183, 7.06752096993325, 8.314351551031214, 9.54815832904664), # 110
(9.41888727858293, 7.9397867383512555, 9.281108796296298, 10.920721920289855, 10.654520697167756, 5.768934156378601, 6.168757651208631, 6.153419753086419, 10.906359567901236, 6.035237182280319, 7.040113237639553, 8.288609486679663, 9.528804976851852), # 111
(9.38954010854655, 7.896536306916234, 9.26040114883402, 10.890226013150832, 10.634817033809409, 5.756220240816949, 6.139562579489958, 6.134331047096479, 10.885398776863282, 6.011758401248016, 7.013230757871109, 8.26286742232811, 9.509567365397805), # 112
(9.360504223703044, 7.853598618785952, 9.239617828252069, 10.85983388249204, 10.615175680173705, 5.7438697692145135, 6.1105259636567695, 6.115852568780606, 10.86471281125862, 5.988304736612729, 6.9869239061528665, 8.237192936504428, 9.490443900843221), # 113
(9.331480897900065, 7.811397183525536, 9.219045675021619, 10.829789421277336, 10.595393354566326, 5.731854608529901, 6.082018208410579, 6.09821125950512, 10.84461903571306, 5.965315167912783, 6.961244337113197, 8.211912172112974, 9.471275414160035), # 114
(9.302384903003995, 7.769947198683046, 9.198696932707318, 10.800084505181779, 10.5754076778886, 5.7201435124987645, 6.054059650191562, 6.081402654278709, 10.82512497866879, 5.942825327988077, 6.936154511427094, 8.187037582558851, 9.452006631660376), # 115
(9.273179873237634, 7.729188281291702, 9.178532189983873, 10.770666150266404, 10.555188526383779, 5.708708877287098, 6.026604817527893, 6.065380312898993, 10.80618133922783, 5.920793358449547, 6.911605931271481, 8.162523197487346, 9.43260725975589), # 116
(9.243829442823772, 7.689060048384721, 9.158512035525986, 10.741481372592244, 10.53470577629511, 5.6975230990608905, 5.9996082389477525, 6.050097795163585, 10.787738816492203, 5.899177400908129, 6.887550098823283, 8.13832304654375, 9.413047004858225), # 117
(9.214297245985211, 7.649502116995324, 9.138597058008367, 10.712477188220333, 10.513929303865842, 5.686558573986138, 5.973024442979315, 6.0355086608700965, 10.769748109563935, 5.877935596974759, 6.863938516259424, 8.11439115937335, 9.393295573379024), # 118
(9.184546916944742, 7.610454104156729, 9.118747846105723, 10.683600613211706, 10.492828985339221, 5.675787698228833, 5.946807958150756, 6.021566469816145, 10.752159917545043, 5.857026088260372, 6.840722685756828, 8.090681565621434, 9.373322671729932), # 119
(9.154542089925162, 7.571855626902158, 9.098924988492762, 10.654798663627394, 10.471374696958497, 5.665182867954965, 5.920913312990253, 6.008224781799343, 10.734924939537558, 5.836407016375905, 6.817854109492416, 8.067148294933297, 9.353098006322597), # 120
(9.124246399149268, 7.533646302264829, 9.079089073844187, 10.626018355528434, 10.449536314966918, 5.6547164793305305, 5.89529503602598, 5.995437156617307, 10.717993874643499, 5.816036522932296, 6.795284289643116, 8.043745376954222, 9.33259128356866), # 121
(9.093623478839854, 7.495765747277961, 9.059200690834711, 10.597206704975855, 10.427283715607734, 5.644360928521519, 5.869907655786117, 5.983157154067649, 10.70131742196489, 5.795872749540477, 6.772964728385851, 8.0204268413295, 9.31177220987977), # 122
(9.062636963219719, 7.458153578974774, 9.039220428139036, 10.568310728030694, 10.40458677512419, 5.634088611693925, 5.844705700798839, 5.971338333947983, 10.684846280603754, 5.775873837811387, 6.750846927897544, 7.997146717704421, 9.290610491667572), # 123
(9.031250486511654, 7.420749414388487, 9.01910887443187, 10.539277440753986, 10.381415369759537, 5.623871925013739, 5.819643699592319, 5.959934256055926, 10.668531149662115, 5.755997929355961, 6.728882390355119, 7.973859035724275, 9.269075835343711), # 124
(8.999427682938459, 7.38349287055232, 8.998826618387923, 10.51005385920676, 10.357739375757022, 5.613683264646956, 5.794676180694739, 5.948898480189091, 10.652322728241993, 5.736203165785134, 6.707022617935501, 7.950517825034348, 9.247137947319828), # 125
(8.967132186722928, 7.346323564499494, 8.978334248681898, 10.480586999450054, 10.333528669359893, 5.603495026759568, 5.76975767263427, 5.938184566145092, 10.636171715445418, 5.7164476887098425, 6.685219112815613, 7.927077115279934, 9.224766534007578), # 126
(8.93432763208786, 7.309181113263224, 8.957592353988504, 10.450823877544899, 10.308753126811398, 5.593279607517565, 5.744842703939094, 5.927746073721545, 10.620028810374407, 5.696689639741024, 6.6634233771723785, 7.903490936106316, 9.201931301818599), # 127
(8.900977653256046, 7.272005133876735, 8.93656152298245, 10.420711509552332, 10.28338262435479, 5.583009403086944, 5.719885803137382, 5.917536562716062, 10.603844712130984, 5.6768871604896125, 6.641586913182724, 7.879713317158788, 9.178601957164537), # 128
(8.867045884450281, 7.234735243373241, 8.91520234433844, 10.390196911533382, 10.257387038233311, 5.572656809633695, 5.694841498757313, 5.90750959292626, 10.587570119817174, 5.656998392566545, 6.619661223023571, 7.855698288082636, 9.154748206457038), # 129
(8.832495959893366, 7.197311058785966, 8.893475406731179, 10.359227099549086, 10.230736244690213, 5.562194223323808, 5.669664319327063, 5.89761872414975, 10.571155732535, 5.636981477582757, 6.5975978088718445, 7.831399878523152, 9.130339756107748), # 130
(8.797291513808094, 7.159672197148127, 8.87134129883538, 10.327749089660475, 10.203400119968745, 5.55159404032328, 5.644308793374809, 5.88781751618415, 10.554552249386486, 5.616794557149185, 6.575348172904468, 7.806772118125624, 9.105346312528312), # 131
(8.76139618041726, 7.121758275492944, 8.848760609325746, 10.295709897928587, 10.175348540312154, 5.540828656798102, 5.618729449428725, 5.878059528827073, 10.537710369473654, 5.596395772876765, 6.552863817298364, 7.781769036535342, 9.079737582130376), # 132
(8.724773593943663, 7.083508910853635, 8.825693926876983, 10.263056540414452, 10.146551381963686, 5.529870468914266, 5.592880816016989, 5.868298321876132, 10.520580791898526, 5.575743266376432, 6.53009624423046, 7.756344663397592, 9.053483271325586), # 133
(8.687387388610095, 7.044863720263423, 8.802101840163804, 10.229736033179103, 10.116978521166592, 5.518691872837765, 5.566717421667779, 5.858487455128944, 10.503114215763128, 5.5547951792591235, 6.506996955877678, 7.730453028357666, 9.026553086525583), # 134
(8.649201198639354, 7.005762320755524, 8.777944937860909, 10.195695392283579, 10.08659983416412, 5.507265264734592, 5.540193794909268, 5.84858048838312, 10.48526134016948, 5.533509653135776, 6.483517454416942, 7.704048161060852, 8.99891673414202), # 135
(8.610178658254235, 6.966144329363159, 8.753183808643008, 10.160881633788906, 10.055385197199517, 5.495563040770739, 5.513264464269635, 5.838530981436277, 10.466972864219606, 5.511844829617322, 6.459609242025177, 7.677084091152441, 8.970543920586536), # 136
(8.570283401677534, 6.925949363119547, 8.72777904118481, 10.125241773756125, 10.023304486516034, 5.483557597112198, 5.485883958277055, 5.828292494086029, 10.448199487015533, 5.4897588503147015, 6.435223820879306, 7.649514848277719, 8.941404352270776), # 137
(8.529479063132047, 6.885117039057908, 8.701691224161017, 10.088722828246263, 9.990327578356919, 5.471221329924964, 5.458006805459704, 5.81781858612999, 10.428891907659281, 5.4672098568388465, 6.410312693156252, 7.621294462081978, 8.91146773560639), # 138
(8.487729276840568, 6.843586974211461, 8.67488094624634, 10.051271813320358, 9.956424348965415, 5.458526635375026, 5.429587534345759, 5.807062817365774, 10.409000825252871, 5.444155990800697, 6.38482736103294, 7.592376962210506, 8.880703777005019), # 139
(8.444997677025897, 6.801298785613425, 8.647308796115487, 10.012835745039444, 9.92156467458478, 5.445445909628379, 5.400580673463397, 5.795978747590996, 10.388476938898332, 5.420555393811186, 6.358719326686294, 7.562716378308592, 8.849082182878314), # 140
(8.40124789791083, 6.758192090297021, 8.61893536244316, 9.973361639464553, 9.885718431458253, 5.431951548851015, 5.370940751340795, 5.78451993660327, 10.36727094769768, 5.396366207481251, 6.331940092293238, 7.532266740021525, 8.816572659637913), # 141
(8.356443573718156, 6.714206505295466, 8.58972123390407, 9.93279651265672, 9.848855495829087, 5.418015949208927, 5.340622296506126, 5.772639944200211, 10.345333550752942, 5.371546573421828, 6.304441160030697, 7.500982076994594, 8.783144913695466), # 142
(8.310548338670674, 6.669281647641981, 8.559626999172925, 9.891087380676975, 9.810945743940529, 5.403611506868106, 5.3095798374875685, 5.760292330179432, 10.322615447166147, 5.3460546332438525, 6.276174032075593, 7.4688164188730894, 8.748768651462617), # 143
(8.263525826991184, 6.623357134369786, 8.528613246924428, 9.848181259586356, 9.771959052035829, 5.388710617994547, 5.277767902813299, 5.747430654338549, 10.29906733603931, 5.31984852855826, 6.247090210604851, 7.435723795302299, 8.713413579351014), # 144
(8.215339672902477, 6.576372582512099, 8.496640565833289, 9.804025165445895, 9.731865296358233, 5.3732856787542405, 5.245141021011493, 5.734008476475176, 10.274639916474454, 5.292886400975988, 6.217141197795395, 7.401658235927513, 8.6770494037723), # 145
(8.16595351062735, 6.528267609102142, 8.463669544574216, 9.758566114316626, 9.690634353150992, 5.35730908531318, 5.21165372061033, 5.719979356386927, 10.249283887573606, 5.2651263921079705, 6.186278495824149, 7.3665737703940195, 8.639645831138118), # 146
(8.1153309743886, 6.47898183117313, 8.42966077182191, 9.71175112225958, 9.648236098657351, 5.340753233837358, 5.177260530137981, 5.705296853871415, 10.22294994843879, 5.236526643565146, 6.154453606868036, 7.3304244283471105, 8.601172567860118), # 147
(8.063435698409021, 6.428454865758288, 8.394574836251083, 9.663527205335797, 9.604640409120561, 5.323590520492767, 5.1419159781226265, 5.689914528726257, 10.195588798172029, 5.207045296958447, 6.1216180331039824, 7.29316423943207, 8.561599320349941), # 148
(8.010231316911412, 6.37662632989083, 8.358372326536443, 9.613841379606303, 9.55981716078387, 5.3057933414453995, 5.105574593092441, 5.673785940749067, 10.167151135875338, 5.176640493898813, 6.08772327670891, 7.254747233294191, 8.520895795019237), # 149
(7.955681464118564, 6.323435840603979, 8.321013831352694, 9.562640661132138, 9.513736229890526, 5.287334092861249, 5.0681909035756005, 5.656864649737456, 10.137587660650752, 5.1452703759971765, 6.0527208398597425, 7.215127439578763, 8.479031698279647), # 150
(7.899749774253275, 6.268823014930954, 8.282459939374542, 9.50987206597433, 9.466367492683776, 5.268185170906305, 5.029719438100283, 5.639104215489043, 10.106849071600289, 5.112893084864478, 6.016562224733405, 7.174258887931072, 8.435976736542818), # 151
(7.842399881538343, 6.212727469904973, 8.242671239276701, 9.455482610193918, 9.417680825406869, 5.2483189717465635, 4.9901147251946645, 5.620458197801441, 10.07488606782597, 5.079466762111649, 5.979198933506821, 7.132095607996409, 8.391700616220398), # 152
(7.78359542019656, 6.155088822559256, 8.201608319733868, 9.399419309851933, 9.367646104303056, 5.2277078915480155, 4.949331293386919, 5.600880156472262, 10.041649348429823, 5.044949549349629, 5.940582468356916, 7.088591629420064, 8.346173043724027), # 153
(7.723300024450729, 6.095846689927024, 8.159231769420758, 9.34162918100941, 9.31623320561558, 5.206324326476654, 4.907323671205228, 5.580323651299123, 10.007089612513866, 5.009299588189353, 5.900664331460612, 7.043700981847325, 8.299363725465357), # 154
(7.6614773285236355, 6.034940689041495, 8.115502177012075, 9.282059239727378, 9.263412005587696, 5.184140672698471, 4.864046387177761, 5.558742242079636, 9.971157559180128, 4.972475020241754, 5.859396024994833, 6.997377694923482, 8.251242367856026), # 155
(7.598090966638081, 5.972310436935888, 8.070380131182526, 9.220656502066875, 9.209152380462648, 5.161129326379461, 4.8194539698327, 5.5360894886114185, 9.933803887530626, 4.934433987117773, 5.816729051136504, 6.949575798293822, 8.201778677307685), # 156
(7.533104573016862, 5.907895550643423, 8.023826220606818, 9.157367984088937, 9.153424206483685, 5.137262683685614, 4.773500947698219, 5.512318950692082, 9.894979296667389, 4.895134630428341, 5.772614912062549, 6.900249321603637, 8.150942360231976), # 157
(7.464680946405239, 5.840453120772258, 7.973591953902355, 9.089769581651243, 9.093681105870997, 5.11102447631711, 4.725106720927857, 5.485796952349372, 9.851662091599097, 4.8533659162911436, 5.7255957525389425, 6.847599564194339, 8.096485859415345), # 158
(7.382286766978402, 5.763065319599478, 7.906737818402988, 9.003977158788453, 9.015191309781628, 5.073689648007103, 4.668212763385716, 5.4472135327643825, 9.786427261222144, 4.802280994098745, 5.667416935618994, 6.781362523683108, 8.025427646920194), # 159
(7.284872094904309, 5.675096728540714, 7.821920957955888, 8.89857751040886, 8.916420131346795, 5.024341296047684, 4.602243748383784, 5.3955991895273465, 9.697425227228651, 4.741205651862893, 5.59725950860954, 6.700501948887847, 7.93642060889358), # 160
(7.17322205458596, 5.577120868080469, 7.720046971910309, 8.774572503756728, 8.798393124282113, 4.963577241570314, 4.527681446006876, 5.33160053310978, 9.585829766999018, 4.6706581931709374, 5.515741654599707, 6.605767468907571, 7.830374044819097), # 161
(7.048121770426357, 5.469711258703239, 7.602021459615496, 8.632964006076326, 8.662135842303204, 4.891995305706455, 4.445007626339809, 5.255864173983202, 9.452814657913637, 4.5911569216102315, 5.42348155667862, 6.497908712841293, 7.708197254180333), # 162
(6.9103563668284975, 5.353441420893524, 7.468750020420702, 8.474753884611934, 8.508673839125688, 4.810193309587572, 4.354704059467401, 5.169036722619125, 9.299553677352906, 4.503220140768125, 5.321097397935408, 6.3776753097880325, 7.570799536460879), # 163
(6.760710968195384, 5.228884875135821, 7.321138253675176, 8.300944006607818, 8.339032668465189, 4.718769074345129, 4.257252515474466, 5.071764789489069, 9.127220602697223, 4.407366154231968, 5.209207361459196, 6.245816888846803, 7.419090191144328), # 164
(6.599970698930017, 5.096615141914632, 7.160091758728169, 8.112536239308252, 8.154237884037324, 4.618320421110586, 4.153134764445822, 4.964694985064546, 8.93698921132698, 4.3041132655891134, 5.088429630339111, 6.10308307911662, 7.25397851771427), # 165
(6.428920683435397, 4.957205741714454, 6.9865161349289275, 7.910532449957501, 7.955315039557714, 4.509445171015408, 4.042832576466286, 4.848473919817077, 8.730033280622573, 4.193979778426912, 4.959382387664279, 5.950223509696501, 7.0763738156542955), # 166
(6.248346046114523, 4.811230195019787, 6.801316981626704, 7.695934505799843, 7.74328968874198, 4.392741145191058, 3.9268277216206746, 4.723748204218176, 8.5075265879644, 4.077483996332714, 4.822683816523827, 5.7879878096854585, 6.887185384447996), # 167
(6.059031911370395, 4.659262022315128, 6.605399898170748, 7.469744274079546, 7.519187385305742, 4.268806164768999, 3.805601969993804, 4.5911644487393595, 8.270642910732855, 3.955144222893872, 4.678952100006881, 5.617125608182511, 6.6873225235789615), # 168
(5.861763403606015, 4.501874744084979, 6.399670483910309, 7.232963622040883, 7.28403368296462, 4.138238050880695, 3.6796370916704917, 4.451369263852145, 8.020556026308338, 3.8274787616977366, 4.528805421202568, 5.438386534286672, 6.477694532530785), # 169
(5.657325647224384, 4.339641880813837, 6.185034338194635, 6.98659441692812, 7.038854135434233, 4.001634624657607, 3.549414856735553, 4.305009260028047, 7.7584397120712385, 3.6950059163316578, 4.372861963200016, 5.252520217096959, 6.259210710787055), # 170
(5.4465037666285, 4.173136952986201, 5.962397060372978, 6.731638525985535, 6.784674296430206, 3.8595937072311983, 3.4154170352738054, 4.152731047738583, 7.485467745401956, 3.5582439903829886, 4.211739909088348, 5.060276285712386, 6.032780357831365), # 171
(5.230082886221365, 4.002933481086569, 5.7326642497945866, 6.4690978164573965, 6.5225197196681535, 3.7127131197329337, 3.2781253973700655, 3.9951812374552707, 7.202813903680886, 3.41771128743908, 4.046057441956694, 4.862404369231971, 5.799312773147303), # 172
(5.00884813040598, 3.8296049855994423, 5.4967415058087115, 6.1999741555879755, 6.253415958863702, 3.5615906832942748, 3.1380217131091497, 3.8330064396496235, 6.911651964288422, 3.2739261110872815, 3.8764327448941778, 4.659654096754725, 5.5597172562184625), # 173
(4.783584623585344, 3.653724987009318, 5.2555344277646014, 5.9252694106215404, 5.978388567732466, 3.406824219046685, 2.9955877525758754, 3.6668532647931604, 6.613155704604964, 3.1274067649149466, 3.7034840009899277, 4.452775097379668, 5.314903106528433), # 174
(4.555077490162455, 3.4758670058006946, 5.009948615011508, 5.645985448802367, 5.698463099990069, 3.2490115481216284, 2.851305285855058, 3.497368323357396, 6.308498902010905, 2.9786715525094243, 3.5278293933330693, 4.242517000205814, 5.0657796235608075), # 175
(4.324111854540319, 3.296604562458073, 4.760889666898678, 5.363124137374725, 5.41466510935213, 3.0887504916505666, 2.705656083031515, 3.325198225813849, 5.998855333886642, 2.828238777458067, 3.35008710501273, 4.029629434332179, 4.813256106799174), # 176
(4.0914728411219325, 3.1165111774659513, 4.5092631827753635, 5.077687343582883, 5.128020149534273, 2.9266388707649633, 2.5591219141900625, 3.1509895826340326, 5.68539877761257, 2.6766267433482245, 3.1708753191180357, 3.8148620288577786, 4.5582418557271245), # 177
(3.8579455743102966, 2.9361603713088282, 4.255974761990814, 4.790676934671116, 4.8395537742521135, 2.7632745065962827, 2.4121845494155174, 2.9753890042894655, 5.3693030105690855, 2.52435375376725, 2.9908122187381125, 3.598964412881627, 4.301646169828252), # 178
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179
)
passenger_arriving_acc = (
(3, 7, 3, 7, 4, 2, 2, 1, 2, 0, 1, 2, 0, 4, 7, 1, 9, 6, 1, 3, 1, 3, 0, 1, 1, 0), # 0
(10, 16, 9, 10, 10, 3, 3, 1, 3, 0, 2, 2, 0, 8, 15, 9, 10, 9, 7, 7, 4, 5, 1, 3, 2, 0), # 1
(16, 21, 16, 13, 17, 5, 6, 1, 6, 1, 2, 2, 0, 17, 20, 13, 12, 12, 12, 10, 4, 6, 1, 3, 2, 0), # 2
(19, 30, 21, 17, 25, 7, 9, 4, 9, 1, 2, 3, 0, 23, 23, 13, 14, 15, 14, 11, 5, 9, 1, 3, 3, 0), # 3
(23, 32, 26, 28, 34, 8, 13, 5, 15, 1, 2, 3, 0, 28, 26, 16, 19, 17, 15, 15, 6, 12, 4, 3, 3, 0), # 4
(28, 38, 32, 33, 37, 10, 14, 5, 15, 4, 3, 3, 0, 38, 35, 23, 21, 24, 18, 19, 7, 14, 5, 6, 4, 0), # 5
(33, 44, 40, 40, 39, 13, 17, 7, 21, 6, 4, 3, 0, 48, 42, 27, 27, 31, 26, 22, 10, 15, 8, 6, 5, 0), # 6
(47, 53, 46, 46, 43, 15, 18, 9, 22, 7, 4, 3, 0, 59, 48, 31, 36, 36, 32, 23, 11, 17, 8, 9, 6, 0), # 7
(54, 64, 53, 55, 49, 17, 22, 12, 25, 7, 4, 3, 0, 64, 52, 38, 41, 41, 34, 24, 12, 18, 9, 10, 7, 0), # 8
(64, 69, 64, 62, 57, 22, 23, 17, 31, 7, 5, 3, 0, 72, 59, 46, 43, 45, 39, 28, 15, 22, 10, 10, 8, 0), # 9
(69, 80, 72, 67, 65, 23, 27, 20, 32, 8, 8, 3, 0, 78, 69, 47, 51, 53, 43, 30, 16, 23, 15, 12, 8, 0), # 10
(82, 91, 79, 72, 68, 24, 29, 22, 38, 12, 9, 3, 0, 91, 76, 53, 56, 61, 45, 33, 17, 25, 16, 15, 8, 0), # 11
(96, 98, 83, 80, 75, 29, 34, 29, 42, 13, 11, 3, 0, 98, 79, 62, 61, 64, 50, 37, 21, 27, 17, 18, 8, 0), # 12
(109, 109, 89, 89, 81, 35, 36, 30, 44, 15, 13, 5, 0, 116, 90, 66, 66, 66, 55, 41, 23, 29, 19, 20, 9, 0), # 13
(118, 122, 97, 92, 88, 39, 39, 35, 50, 17, 14, 5, 0, 130, 94, 72, 71, 71, 60, 50, 29, 33, 23, 21, 9, 0), # 14
(127, 130, 102, 99, 94, 41, 41, 37, 52, 17, 17, 5, 0, 139, 102, 86, 75, 74, 61, 54, 35, 34, 28, 26, 10, 0), # 15
(133, 136, 113, 101, 101, 42, 45, 40, 56, 20, 19, 6, 0, 146, 107, 94, 81, 78, 67, 56, 36, 34, 29, 26, 10, 0), # 16
(141, 154, 121, 112, 108, 49, 47, 45, 62, 20, 20, 7, 0, 152, 117, 100, 84, 82, 69, 70, 38, 40, 31, 26, 11, 0), # 17
(148, 163, 129, 118, 114, 51, 50, 48, 64, 22, 22, 8, 0, 160, 125, 105, 88, 91, 74, 75, 40, 44, 35, 28, 13, 0), # 18
(155, 169, 135, 122, 116, 56, 54, 51, 66, 26, 22, 10, 0, 168, 129, 115, 95, 101, 78, 78, 43, 52, 37, 29, 13, 0), # 19
(165, 183, 143, 131, 122, 57, 56, 54, 69, 27, 23, 11, 0, 182, 137, 123, 100, 105, 84, 84, 45, 54, 39, 33, 14, 0), # 20
(172, 190, 150, 137, 132, 61, 59, 55, 75, 28, 24, 12, 0, 198, 145, 129, 104, 113, 91, 88, 47, 57, 43, 36, 14, 0), # 21
(180, 202, 158, 150, 139, 68, 64, 61, 77, 30, 24, 14, 0, 207, 156, 137, 112, 119, 95, 90, 52, 61, 48, 38, 16, 0), # 22
(190, 212, 160, 157, 148, 71, 71, 66, 79, 32, 25, 15, 0, 217, 167, 141, 119, 130, 100, 94, 56, 67, 52, 38, 16, 0), # 23
(205, 227, 170, 162, 152, 74, 74, 68, 85, 32, 25, 16, 0, 225, 176, 147, 127, 141, 105, 101, 58, 73, 55, 40, 16, 0), # 24
(216, 232, 180, 171, 159, 76, 81, 71, 88, 35, 25, 16, 0, 236, 191, 154, 136, 151, 108, 103, 62, 78, 58, 42, 16, 0), # 25
(225, 244, 191, 178, 165, 79, 87, 75, 93, 39, 25, 18, 0, 252, 200, 156, 139, 160, 112, 110, 64, 80, 61, 43, 17, 0), # 26
(232, 256, 204, 189, 170, 82, 90, 77, 96, 39, 26, 19, 0, 264, 204, 161, 149, 167, 118, 112, 66, 82, 63, 48, 17, 0), # 27
(239, 266, 208, 204, 178, 84, 95, 80, 100, 40, 28, 21, 0, 276, 215, 166, 153, 169, 125, 116, 68, 83, 63, 49, 17, 0), # 28
(247, 273, 216, 213, 182, 90, 98, 86, 105, 45, 30, 21, 0, 287, 222, 173, 154, 173, 129, 121, 70, 88, 68, 51, 18, 0), # 29
(257, 284, 226, 226, 186, 97, 103, 87, 109, 47, 30, 23, 0, 294, 229, 176, 161, 178, 135, 126, 71, 90, 69, 51, 19, 0), # 30
(264, 295, 234, 237, 195, 98, 106, 91, 112, 48, 32, 23, 0, 304, 236, 182, 168, 184, 140, 129, 74, 95, 73, 52, 19, 0), # 31
(270, 311, 242, 248, 200, 100, 107, 97, 114, 51, 33, 23, 0, 321, 239, 192, 175, 189, 146, 134, 76, 99, 76, 54, 20, 0), # 32
(282, 321, 250, 253, 207, 100, 111, 101, 114, 52, 33, 24, 0, 327, 249, 198, 179, 197, 152, 135, 79, 105, 78, 57, 22, 0), # 33
(292, 333, 256, 265, 215, 101, 115, 105, 119, 57, 33, 24, 0, 336, 259, 205, 191, 204, 158, 141, 83, 108, 85, 60, 24, 0), # 34
(297, 337, 264, 275, 222, 104, 118, 110, 125, 57, 34, 24, 0, 351, 265, 216, 198, 210, 161, 142, 87, 113, 86, 61, 24, 0), # 35
(305, 342, 268, 283, 231, 108, 123, 115, 127, 57, 34, 25, 0, 355, 273, 228, 203, 220, 165, 148, 89, 116, 88, 62, 24, 0), # 36
(311, 347, 275, 291, 242, 110, 130, 122, 133, 57, 35, 25, 0, 366, 286, 235, 209, 228, 170, 151, 91, 120, 95, 64, 26, 0), # 37
(324, 363, 291, 301, 246, 113, 136, 125, 137, 58, 35, 25, 0, 372, 295, 243, 214, 237, 173, 158, 93, 126, 101, 65, 28, 0), # 38
(328, 370, 299, 314, 251, 115, 138, 126, 138, 61, 37, 27, 0, 383, 303, 252, 217, 249, 183, 164, 95, 131, 103, 65, 30, 0), # 39
(341, 377, 304, 319, 256, 117, 144, 129, 141, 66, 38, 27, 0, 392, 308, 258, 220, 258, 186, 170, 97, 133, 106, 68, 31, 0), # 40
(345, 388, 316, 331, 266, 124, 147, 132, 148, 67, 40, 27, 0, 403, 318, 267, 225, 268, 188, 173, 99, 138, 110, 70, 35, 0), # 41
(352, 398, 326, 340, 273, 131, 152, 134, 150, 68, 40, 27, 0, 416, 323, 271, 232, 272, 194, 180, 103, 144, 112, 70, 36, 0), # 42
(362, 407, 336, 348, 279, 134, 152, 135, 153, 73, 41, 28, 0, 428, 336, 278, 235, 279, 202, 182, 108, 147, 116, 72, 37, 0), # 43
(368, 419, 349, 357, 286, 138, 158, 141, 158, 76, 42, 31, 0, 438, 349, 286, 242, 284, 207, 185, 111, 149, 119, 74, 37, 0), # 44
(378, 430, 354, 370, 294, 141, 162, 146, 160, 76, 45, 31, 0, 455, 356, 291, 245, 287, 210, 191, 113, 150, 121, 75, 37, 0), # 45
(387, 436, 358, 380, 301, 144, 168, 151, 167, 79, 47, 31, 0, 467, 360, 298, 251, 294, 213, 196, 115, 154, 124, 75, 38, 0), # 46
(404, 447, 365, 394, 311, 146, 171, 154, 170, 79, 50, 32, 0, 477, 366, 304, 258, 299, 218, 200, 119, 155, 126, 78, 38, 0), # 47
(417, 458, 375, 404, 316, 150, 173, 160, 173, 81, 52, 32, 0, 485, 379, 312, 261, 304, 220, 202, 123, 161, 127, 81, 39, 0), # 48
(425, 464, 384, 416, 327, 154, 177, 164, 176, 85, 54, 32, 0, 494, 388, 316, 270, 315, 223, 208, 128, 164, 132, 83, 40, 0), # 49
(438, 471, 390, 426, 336, 160, 182, 165, 182, 86, 55, 32, 0, 499, 393, 321, 274, 325, 228, 211, 128, 169, 134, 85, 43, 0), # 50
(446, 482, 400, 439, 340, 168, 185, 169, 188, 87, 57, 32, 0, 508, 407, 332, 277, 328, 230, 215, 131, 173, 134, 85, 43, 0), # 51
(452, 487, 411, 455, 349, 173, 191, 173, 189, 87, 57, 32, 0, 522, 417, 336, 281, 336, 233, 219, 136, 175, 138, 87, 43, 0), # 52
(461, 494, 418, 467, 356, 175, 195, 177, 195, 88, 58, 32, 0, 535, 424, 345, 286, 341, 241, 223, 142, 179, 141, 92, 44, 0), # 53
(465, 502, 427, 476, 359, 177, 199, 184, 202, 90, 59, 32, 0, 545, 429, 351, 290, 355, 244, 228, 147, 184, 145, 93, 44, 0), # 54
(479, 508, 436, 484, 363, 178, 201, 187, 203, 92, 59, 32, 0, 554, 440, 354, 296, 358, 249, 234, 148, 187, 148, 96, 46, 0), # 55
(483, 519, 444, 492, 375, 180, 201, 194, 204, 96, 62, 35, 0, 566, 454, 362, 302, 370, 251, 238, 152, 192, 151, 98, 46, 0), # 56
(497, 528, 452, 501, 381, 183, 206, 200, 208, 96, 62, 35, 0, 578, 461, 370, 308, 376, 256, 243, 154, 194, 155, 98, 47, 0), # 57
(507, 537, 461, 514, 386, 190, 211, 207, 209, 98, 64, 36, 0, 587, 471, 379, 315, 389, 258, 247, 156, 200, 157, 98, 49, 0), # 58
(518, 552, 468, 525, 396, 196, 215, 209, 215, 99, 66, 36, 0, 599, 482, 389, 317, 398, 264, 252, 158, 202, 160, 100, 50, 0), # 59
(532, 558, 475, 534, 406, 200, 218, 212, 222, 102, 68, 37, 0, 607, 493, 395, 323, 405, 270, 256, 164, 208, 162, 101, 50, 0), # 60
(543, 563, 482, 542, 413, 201, 220, 215, 224, 103, 69, 38, 0, 620, 497, 403, 328, 413, 274, 260, 167, 212, 164, 103, 53, 0), # 61
(554, 571, 496, 553, 417, 203, 224, 219, 227, 105, 71, 38, 0, 638, 507, 411, 331, 424, 277, 263, 170, 215, 166, 104, 53, 0), # 62
(570, 580, 503, 563, 425, 205, 226, 221, 230, 107, 74, 38, 0, 646, 513, 414, 334, 441, 278, 265, 172, 219, 171, 107, 54, 0), # 63
(588, 589, 510, 575, 432, 210, 227, 224, 236, 108, 75, 39, 0, 652, 524, 423, 337, 448, 282, 269, 174, 221, 176, 109, 55, 0), # 64
(602, 595, 524, 580, 436, 214, 233, 229, 240, 108, 76, 39, 0, 663, 532, 430, 343, 453, 284, 272, 175, 223, 182, 109, 55, 0), # 65
(617, 600, 533, 590, 441, 218, 236, 231, 244, 109, 78, 41, 0, 674, 542, 438, 350, 458, 287, 278, 176, 226, 188, 110, 57, 0), # 66
(628, 605, 548, 600, 445, 218, 238, 234, 250, 110, 81, 41, 0, 683, 548, 445, 356, 468, 289, 283, 179, 231, 191, 111, 58, 0), # 67
(634, 615, 563, 610, 454, 222, 240, 236, 251, 112, 83, 43, 0, 699, 554, 454, 362, 472, 291, 287, 181, 235, 195, 113, 58, 0), # 68
(649, 627, 576, 615, 460, 228, 246, 239, 253, 113, 83, 44, 0, 710, 568, 465, 369, 481, 296, 293, 185, 239, 202, 113, 60, 0), # 69
(658, 640, 578, 625, 468, 234, 250, 240, 257, 114, 85, 46, 0, 721, 579, 472, 375, 489, 298, 297, 189, 241, 206, 114, 62, 0), # 70
(670, 647, 587, 632, 483, 237, 254, 242, 261, 116, 86, 47, 0, 731, 592, 477, 382, 498, 302, 302, 192, 249, 209, 114, 62, 0), # 71
(682, 650, 597, 636, 490, 241, 256, 247, 263, 119, 86, 49, 0, 743, 600, 489, 389, 506, 308, 306, 197, 256, 214, 116, 63, 0), # 72
(691, 659, 608, 641, 500, 243, 261, 247, 267, 120, 86, 49, 0, 749, 606, 497, 392, 511, 310, 312, 198, 258, 218, 116, 64, 0), # 73
(698, 667, 616, 649, 509, 245, 262, 251, 270, 122, 86, 49, 0, 754, 609, 503, 401, 521, 314, 317, 200, 261, 219, 119, 64, 0), # 74
(711, 680, 624, 661, 518, 248, 264, 252, 275, 125, 88, 49, 0, 762, 615, 509, 405, 529, 316, 319, 203, 265, 222, 119, 65, 0), # 75
(719, 682, 631, 667, 526, 251, 268, 252, 280, 126, 88, 50, 0, 775, 628, 521, 413, 538, 319, 320, 210, 268, 224, 122, 68, 0), # 76
(728, 693, 639, 671, 540, 254, 270, 253, 284, 127, 91, 50, 0, 784, 641, 525, 419, 544, 324, 322, 211, 269, 227, 122, 68, 0), # 77
(739, 701, 643, 680, 550, 258, 272, 253, 290, 131, 92, 52, 0, 791, 649, 532, 425, 555, 331, 326, 213, 273, 229, 124, 68, 0), # 78
(750, 708, 650, 688, 561, 264, 272, 258, 295, 133, 92, 52, 0, 801, 657, 538, 432, 562, 337, 331, 218, 278, 233, 125, 68, 0), # 79
(758, 717, 660, 697, 575, 266, 275, 264, 295, 135, 92, 53, 0, 808, 667, 544, 444, 569, 339, 334, 218, 280, 234, 127, 68, 0), # 80
(770, 725, 668, 708, 583, 272, 283, 268, 297, 135, 92, 54, 0, 825, 676, 549, 453, 581, 343, 339, 224, 283, 236, 129, 69, 0), # 81
(782, 731, 676, 720, 590, 274, 288, 271, 300, 136, 93, 55, 0, 835, 683, 557, 460, 587, 345, 341, 227, 288, 238, 130, 69, 0), # 82
(791, 747, 684, 734, 601, 276, 289, 273, 302, 138, 93, 56, 0, 839, 691, 568, 466, 594, 346, 344, 229, 290, 240, 131, 70, 0), # 83
(801, 753, 689, 745, 605, 282, 293, 274, 304, 140, 93, 56, 0, 849, 699, 573, 468, 602, 352, 352, 229, 292, 244, 134, 70, 0), # 84
(812, 764, 698, 753, 609, 284, 298, 276, 305, 140, 94, 57, 0, 866, 709, 579, 476, 614, 355, 356, 230, 294, 246, 134, 71, 0), # 85
(820, 771, 703, 756, 619, 287, 306, 279, 307, 142, 97, 57, 0, 874, 718, 585, 481, 620, 357, 357, 234, 298, 252, 135, 71, 0), # 86
(830, 778, 712, 766, 626, 288, 313, 281, 311, 147, 98, 57, 0, 883, 727, 593, 488, 627, 364, 358, 238, 302, 256, 135, 71, 0), # 87
(838, 784, 723, 785, 630, 289, 316, 283, 317, 148, 99, 59, 0, 891, 739, 603, 496, 632, 368, 361, 242, 303, 257, 139, 72, 0), # 88
(846, 790, 733, 791, 635, 290, 317, 285, 320, 151, 100, 62, 0, 896, 745, 613, 502, 634, 369, 364, 247, 305, 260, 139, 72, 0), # 89
(852, 798, 742, 806, 639, 292, 323, 286, 321, 153, 100, 63, 0, 905, 752, 619, 509, 638, 374, 366, 251, 307, 263, 143, 72, 0), # 90
(860, 807, 749, 815, 651, 296, 327, 289, 327, 156, 101, 63, 0, 917, 758, 625, 516, 643, 380, 372, 252, 314, 267, 145, 72, 0), # 91
(869, 816, 756, 828, 659, 298, 331, 290, 330, 161, 101, 64, 0, 926, 765, 632, 518, 648, 383, 374, 254, 317, 270, 147, 74, 0), # 92
(878, 824, 761, 841, 666, 300, 334, 292, 333, 164, 102, 64, 0, 940, 773, 641, 527, 656, 384, 376, 257, 320, 272, 148, 75, 0), # 93
(884, 833, 769, 845, 672, 302, 335, 292, 344, 165, 102, 66, 0, 944, 787, 647, 533, 660, 388, 377, 262, 323, 273, 150, 76, 0), # 94
(893, 841, 774, 856, 675, 309, 336, 296, 351, 166, 104, 68, 0, 951, 796, 652, 537, 672, 390, 380, 267, 326, 275, 152, 76, 0), # 95
(902, 854, 780, 866, 679, 310, 337, 299, 353, 168, 105, 68, 0, 959, 806, 657, 544, 681, 394, 381, 272, 332, 279, 154, 76, 0), # 96
(909, 861, 786, 875, 683, 315, 342, 300, 356, 171, 106, 70, 0, 976, 815, 666, 549, 688, 398, 384, 273, 339, 282, 155, 76, 0), # 97
(917, 866, 797, 884, 690, 320, 346, 304, 357, 173, 106, 71, 0, 994, 824, 671, 552, 698, 402, 390, 275, 341, 286, 156, 77, 0), # 98
(927, 872, 804, 896, 696, 327, 351, 305, 358, 175, 108, 73, 0, 1001, 830, 679, 556, 704, 406, 391, 277, 345, 290, 157, 80, 0), # 99
(935, 882, 810, 901, 701, 331, 356, 308, 364, 175, 109, 74, 0, 1019, 833, 684, 559, 712, 407, 397, 279, 347, 292, 158, 83, 0), # 100
(939, 887, 816, 912, 706, 334, 360, 309, 368, 179, 109, 75, 0, 1029, 838, 693, 561, 717, 409, 400, 282, 351, 296, 162, 83, 0), # 101
(948, 893, 822, 922, 716, 339, 363, 310, 369, 180, 110, 77, 0, 1040, 847, 699, 568, 728, 412, 404, 285, 354, 303, 163, 84, 0), # 102
(954, 900, 828, 928, 723, 345, 365, 313, 374, 181, 112, 77, 0, 1052, 859, 705, 572, 733, 416, 407, 287, 361, 308, 166, 85, 0), # 103
(967, 912, 835, 938, 732, 346, 370, 315, 375, 181, 115, 77, 0, 1061, 863, 709, 576, 746, 421, 410, 289, 364, 310, 167, 87, 0), # 104
(978, 918, 843, 945, 738, 353, 372, 320, 377, 183, 115, 78, 0, 1075, 871, 711, 582, 749, 422, 412, 293, 369, 311, 168, 87, 0), # 105
(984, 924, 849, 955, 746, 357, 381, 322, 379, 184, 116, 78, 0, 1079, 876, 721, 587, 757, 425, 412, 296, 373, 314, 169, 89, 0), # 106
(992, 929, 856, 956, 749, 360, 386, 325, 381, 184, 116, 78, 0, 1087, 885, 729, 593, 768, 427, 414, 298, 374, 317, 170, 91, 0), # 107
(997, 938, 865, 963, 760, 362, 389, 327, 389, 184, 116, 79, 0, 1096, 897, 730, 598, 777, 430, 417, 300, 381, 319, 173, 92, 0), # 108
(1009, 948, 873, 968, 772, 365, 389, 331, 398, 184, 116, 81, 0, 1102, 908, 738, 603, 790, 430, 418, 301, 388, 320, 175, 93, 0), # 109
(1014, 957, 876, 975, 778, 366, 390, 334, 403, 185, 119, 82, 0, 1110, 910, 743, 605, 799, 434, 418, 303, 394, 323, 179, 94, 0), # 110
(1023, 965, 882, 985, 786, 371, 390, 340, 406, 185, 119, 83, 0, 1119, 919, 753, 611, 807, 437, 421, 305, 396, 328, 181, 96, 0), # 111
(1034, 974, 895, 988, 790, 375, 397, 341, 409, 185, 120, 84, 0, 1127, 928, 758, 617, 812, 440, 424, 307, 402, 335, 181, 97, 0), # 112
(1044, 980, 909, 998, 797, 376, 399, 345, 413, 186, 121, 84, 0, 1141, 938, 759, 619, 822, 444, 426, 308, 406, 339, 184, 97, 0), # 113
(1054, 987, 921, 1007, 804, 381, 400, 348, 416, 188, 122, 85, 0, 1150, 944, 764, 626, 827, 447, 428, 312, 411, 345, 184, 97, 0), # 114
(1069, 995, 929, 1015, 810, 385, 401, 349, 426, 191, 124, 87, 0, 1155, 956, 774, 632, 835, 453, 430, 316, 416, 352, 186, 99, 0), # 115
(1079, 1000, 934, 1022, 816, 388, 403, 355, 430, 192, 124, 88, 0, 1162, 962, 782, 634, 842, 462, 432, 316, 420, 355, 188, 101, 0), # 116
(1086, 1007, 944, 1029, 822, 394, 404, 356, 431, 193, 124, 89, 0, 1169, 973, 785, 639, 852, 465, 433, 317, 424, 358, 191, 101, 0), # 117
(1094, 1014, 951, 1037, 829, 400, 404, 359, 435, 194, 124, 89, 0, 1179, 979, 792, 647, 860, 468, 434, 321, 428, 359, 195, 101, 0), # 118
(1100, 1023, 956, 1044, 837, 402, 407, 361, 438, 197, 124, 89, 0, 1188, 989, 798, 652, 868, 473, 439, 323, 434, 362, 195, 101, 0), # 119
(1114, 1032, 960, 1053, 843, 405, 411, 362, 438, 200, 126, 90, 0, 1207, 994, 803, 655, 878, 475, 442, 326, 437, 362, 195, 102, 0), # 120
(1123, 1041, 966, 1065, 850, 409, 412, 364, 441, 201, 128, 92, 0, 1214, 997, 806, 659, 889, 480, 445, 328, 442, 362, 195, 103, 0), # 121
(1131, 1052, 973, 1072, 862, 410, 414, 365, 443, 204, 131, 93, 0, 1221, 1005, 811, 664, 895, 484, 449, 332, 444, 366, 195, 104, 0), # 122
(1137, 1056, 981, 1082, 874, 411, 417, 367, 450, 205, 132, 94, 0, 1225, 1009, 816, 669, 903, 489, 452, 335, 446, 370, 197, 104, 0), # 123
(1146, 1066, 990, 1089, 878, 414, 418, 374, 452, 206, 134, 95, 0, 1233, 1018, 821, 675, 909, 492, 457, 337, 450, 373, 198, 105, 0), # 124
(1153, 1074, 994, 1098, 892, 416, 421, 376, 455, 210, 136, 95, 0, 1241, 1023, 826, 680, 918, 496, 462, 340, 454, 374, 200, 106, 0), # 125
(1161, 1084, 997, 1111, 895, 422, 426, 382, 459, 212, 139, 95, 0, 1253, 1033, 830, 683, 924, 500, 463, 341, 457, 375, 200, 106, 0), # 126
(1169, 1088, 1000, 1120, 904, 425, 427, 384, 465, 212, 139, 96, 0, 1257, 1050, 834, 685, 930, 506, 463, 343, 461, 380, 201, 106, 0), # 127
(1178, 1096, 1010, 1128, 912, 426, 429, 387, 466, 213, 139, 97, 0, 1262, 1058, 840, 687, 943, 508, 468, 347, 465, 380, 204, 107, 0), # 128
(1188, 1107, 1025, 1135, 915, 429, 432, 388, 472, 215, 141, 98, 0, 1269, 1067, 841, 693, 950, 509, 474, 350, 466, 381, 205, 109, 0), # 129
(1193, 1113, 1040, 1141, 925, 429, 436, 388, 475, 217, 142, 98, 0, 1275, 1071, 848, 700, 957, 513, 477, 350, 470, 383, 205, 109, 0), # 130
(1202, 1118, 1048, 1145, 932, 436, 437, 389, 479, 217, 143, 98, 0, 1285, 1076, 853, 707, 963, 516, 480, 351, 472, 384, 205, 110, 0), # 131
(1208, 1126, 1053, 1149, 940, 440, 437, 392, 482, 218, 144, 99, 0, 1294, 1081, 857, 709, 971, 517, 482, 352, 474, 387, 206, 111, 0), # 132
(1215, 1133, 1059, 1158, 947, 446, 439, 397, 483, 221, 145, 99, 0, 1299, 1088, 860, 714, 977, 523, 487, 352, 479, 390, 206, 112, 0), # 133
(1226, 1142, 1067, 1167, 951, 449, 440, 399, 486, 221, 149, 100, 0, 1310, 1096, 866, 719, 982, 527, 490, 353, 483, 391, 207, 112, 0), # 134
(1233, 1147, 1071, 1177, 956, 454, 444, 400, 491, 225, 150, 101, 0, 1316, 1106, 872, 721, 991, 527, 494, 354, 485, 394, 209, 112, 0), # 135
(1240, 1154, 1082, 1190, 961, 458, 446, 403, 492, 228, 151, 101, 0, 1319, 1110, 875, 726, 999, 530, 497, 357, 489, 397, 209, 112, 0), # 136
(1249, 1159, 1088, 1201, 963, 459, 446, 404, 500, 229, 152, 102, 0, 1325, 1116, 880, 734, 1002, 532, 499, 361, 495, 400, 212, 112, 0), # 137
(1254, 1161, 1096, 1208, 971, 460, 447, 405, 502, 230, 155, 103, 0, 1337, 1119, 885, 737, 1011, 535, 504, 362, 498, 402, 214, 112, 0), # 138
(1265, 1170, 1105, 1215, 974, 461, 452, 408, 504, 231, 157, 103, 0, 1345, 1128, 889, 739, 1017, 542, 504, 363, 505, 405, 217, 112, 0), # 139
(1269, 1174, 1110, 1221, 980, 466, 453, 412, 509, 233, 159, 103, 0, 1354, 1134, 897, 743, 1024, 545, 509, 367, 507, 406, 218, 112, 0), # 140
(1274, 1182, 1115, 1229, 989, 469, 459, 415, 512, 235, 160, 104, 0, 1360, 1141, 899, 746, 1029, 549, 511, 369, 508, 407, 219, 112, 0), # 141
(1282, 1187, 1122, 1235, 996, 473, 462, 416, 517, 237, 161, 104, 0, 1363, 1146, 907, 749, 1035, 550, 511, 370, 509, 407, 221, 112, 0), # 142
(1287, 1193, 1127, 1238, 1006, 475, 463, 417, 521, 239, 162, 104, 0, 1366, 1152, 914, 755, 1046, 555, 514, 376, 512, 411, 222, 113, 0), # 143
(1293, 1205, 1135, 1249, 1013, 478, 466, 422, 524, 239, 162, 105, 0, 1374, 1159, 922, 761, 1053, 558, 515, 376, 518, 413, 222, 113, 0), # 144
(1303, 1211, 1142, 1257, 1024, 481, 468, 424, 529, 241, 163, 106, 0, 1385, 1169, 928, 767, 1057, 560, 517, 378, 524, 414, 226, 114, 0), # 145
(1309, 1216, 1152, 1267, 1031, 484, 472, 425, 534, 242, 163, 106, 0, 1401, 1174, 931, 772, 1061, 564, 520, 379, 528, 416, 227, 114, 0), # 146
(1318, 1219, 1162, 1272, 1035, 489, 473, 428, 536, 243, 163, 107, 0, 1408, 1180, 935, 778, 1065, 566, 525, 379, 530, 419, 229, 114, 0), # 147
(1322, 1227, 1172, 1281, 1040, 494, 475, 429, 539, 246, 164, 109, 0, 1423, 1189, 942, 787, 1069, 568, 528, 381, 532, 420, 234, 114, 0), # 148
(1331, 1232, 1177, 1289, 1044, 498, 478, 432, 541, 246, 164, 109, 0, 1430, 1197, 943, 787, 1075, 573, 532, 381, 537, 422, 234, 118, 0), # 149
(1337, 1239, 1182, 1298, 1056, 501, 480, 435, 543, 246, 164, 110, 0, 1435, 1205, 946, 791, 1083, 573, 533, 384, 540, 423, 237, 119, 0), # 150
(1345, 1244, 1193, 1305, 1062, 506, 480, 442, 545, 247, 164, 111, 0, 1447, 1210, 952, 794, 1089, 575, 533, 386, 542, 424, 238, 119, 0), # 151
(1349, 1246, 1199, 1311, 1068, 510, 481, 442, 548, 247, 167, 112, 0, 1458, 1216, 959, 798, 1098, 582, 535, 387, 546, 425, 238, 120, 0), # 152
(1359, 1250, 1204, 1318, 1071, 511, 486, 447, 554, 248, 167, 112, 0, 1467, 1220, 966, 800, 1104, 584, 538, 391, 548, 427, 240, 122, 0), # 153
(1365, 1256, 1213, 1327, 1076, 516, 490, 449, 561, 250, 167, 113, 0, 1476, 1225, 970, 803, 1109, 587, 540, 392, 553, 428, 240, 123, 0), # 154
(1372, 1260, 1222, 1335, 1080, 518, 491, 452, 564, 251, 167, 113, 0, 1481, 1230, 977, 807, 1115, 590, 543, 397, 554, 431, 241, 123, 0), # 155
(1380, 1264, 1228, 1345, 1088, 522, 493, 455, 568, 252, 167, 113, 0, 1486, 1235, 981, 811, 1123, 593, 546, 399, 555, 431, 245, 124, 0), # 156
(1394, 1270, 1239, 1353, 1095, 528, 496, 457, 569, 254, 168, 113, 0, 1492, 1238, 984, 815, 1134, 595, 547, 401, 556, 432, 246, 125, 0), # 157
(1399, 1278, 1244, 1360, 1102, 531, 499, 458, 573, 255, 168, 114, 0, 1501, 1246, 991, 817, 1140, 597, 551, 401, 559, 433, 248, 126, 0), # 158
(1401, 1289, 1253, 1364, 1106, 531, 503, 460, 574, 255, 168, 116, 0, 1506, 1248, 995, 819, 1145, 602, 556, 402, 562, 433, 249, 126, 0), # 159
(1412, 1294, 1259, 1371, 1111, 536, 505, 462, 577, 255, 168, 116, 0, 1513, 1254, 1001, 821, 1152, 605, 561, 404, 564, 434, 250, 127, 0), # 160
(1419, 1301, 1268, 1378, 1113, 539, 506, 464, 580, 257, 171, 116, 0, 1517, 1262, 1004, 827, 1158, 606, 562, 407, 566, 435, 251, 128, 0), # 161
(1426, 1310, 1277, 1385, 1119, 543, 508, 467, 583, 261, 173, 116, 0, 1526, 1268, 1007, 832, 1162, 610, 563, 411, 570, 438, 252, 129, 0), # 162
(1432, 1312, 1289, 1389, 1128, 543, 512, 468, 586, 262, 173, 116, 0, 1537, 1279, 1010, 839, 1165, 616, 568, 413, 573, 444, 253, 129, 0), # 163
(1441, 1318, 1293, 1393, 1137, 546, 519, 470, 589, 262, 173, 117, 0, 1545, 1287, 1012, 843, 1173, 619, 571, 414, 574, 445, 255, 129, 0), # 164
(1449, 1322, 1300, 1398, 1141, 547, 520, 474, 591, 264, 173, 118, 0, 1547, 1291, 1017, 852, 1175, 621, 573, 415, 578, 447, 257, 130, 0), # 165
(1452, 1325, 1307, 1405, 1146, 551, 520, 476, 594, 265, 174, 119, 0, 1555, 1297, 1023, 855, 1180, 623, 574, 417, 579, 447, 258, 130, 0), # 166
(1457, 1327, 1311, 1410, 1153, 555, 522, 477, 597, 266, 174, 120, 0, 1559, 1302, 1023, 857, 1183, 626, 577, 417, 580, 449, 258, 130, 0), # 167
(1464, 1331, 1318, 1413, 1157, 557, 522, 478, 598, 267, 174, 120, 0, 1571, 1308, 1026, 861, 1188, 631, 580, 420, 582, 450, 259, 131, 0), # 168
(1469, 1336, 1320, 1422, 1163, 558, 525, 481, 599, 267, 176, 121, 0, 1575, 1319, 1029, 864, 1193, 637, 583, 422, 585, 451, 259, 132, 0), # 169
(1472, 1341, 1324, 1427, 1169, 559, 525, 484, 601, 267, 177, 121, 0, 1579, 1322, 1031, 868, 1196, 638, 584, 422, 586, 452, 260, 133, 0), # 170
(1476, 1345, 1327, 1431, 1172, 561, 529, 485, 606, 268, 177, 121, 0, 1585, 1322, 1033, 868, 1201, 642, 586, 424, 586, 453, 261, 133, 0), # 171
(1482, 1347, 1333, 1432, 1178, 564, 529, 487, 606, 268, 177, 122, 0, 1595, 1327, 1039, 870, 1207, 644, 588, 425, 590, 455, 264, 133, 0), # 172
(1488, 1348, 1338, 1441, 1181, 566, 529, 488, 609, 270, 179, 123, 0, 1601, 1331, 1047, 871, 1212, 646, 590, 426, 592, 456, 265, 135, 0), # 173
(1495, 1351, 1340, 1445, 1184, 568, 531, 492, 611, 271, 180, 123, 0, 1606, 1339, 1049, 873, 1220, 649, 591, 429, 594, 457, 266, 135, 0), # 174
(1503, 1353, 1344, 1449, 1187, 569, 532, 493, 615, 272, 181, 123, 0, 1612, 1348, 1051, 876, 1226, 653, 594, 430, 596, 459, 267, 136, 0), # 175
(1507, 1359, 1348, 1450, 1190, 569, 534, 493, 615, 272, 181, 123, 0, 1614, 1349, 1053, 878, 1230, 655, 595, 430, 598, 460, 268, 136, 0), # 176
(1512, 1362, 1351, 1453, 1192, 569, 534, 496, 615, 274, 184, 123, 0, 1619, 1352, 1055, 879, 1232, 657, 596, 431, 600, 460, 269, 136, 0), # 177
(1518, 1362, 1354, 1459, 1196, 569, 535, 496, 615, 274, 184, 123, 0, 1625, 1356, 1059, 881, 1234, 657, 596, 433, 602, 463, 270, 137, 0), # 178
(1518, 1362, 1354, 1459, 1196, 569, 535, 496, 615, 274, 184, 123, 0, 1625, 1356, 1059, 881, 1234, 657, 596, 433, 602, 463, 270, 137, 0), # 179
)
passenger_arriving_rate = (
(5.020865578371768, 5.064847846385402, 4.342736024677089, 4.661000830397574, 3.7031237384064077, 1.8308820436884476, 2.0730178076869574, 1.938823405408093, 2.030033020722669, 0.9895037538805926, 0.7008775273142672, 0.4081595898588478, 0.0, 5.083880212578363, 4.489755488447325, 3.5043876365713356, 2.968511261641777, 4.060066041445338, 2.7143527675713304, 2.0730178076869574, 1.3077728883488913, 1.8515618692032039, 1.5536669434658585, 0.8685472049354179, 0.4604407133077639, 0.0), # 0
(5.354327152019974, 5.399222302966028, 4.629455492775127, 4.968858189957462, 3.948326891649491, 1.9518237573581576, 2.209734470631847, 2.066464051210712, 2.164081775444303, 1.0547451730692876, 0.7471826893260219, 0.4351013884011963, 0.0, 5.419791647439855, 4.786115272413158, 3.73591344663011, 3.164235519207862, 4.328163550888606, 2.8930496716949965, 2.209734470631847, 1.3941598266843982, 1.9741634458247455, 1.6562860633191545, 0.9258910985550255, 0.49083839117872996, 0.0), # 1
(5.686723008979731, 5.732269739983398, 4.915035237956178, 5.275490778498595, 4.192641982499829, 2.072282983465593, 2.345909253980352, 2.193593853293508, 2.297595602292516, 1.1197284437551367, 0.7933038581293855, 0.46193605433775464, 0.0, 5.75436482820969, 5.0812965977153, 3.9665192906469278, 3.3591853312654094, 4.595191204585032, 3.0710313946109116, 2.345909253980352, 1.480202131046852, 2.0963209912499146, 1.758496926166199, 0.9830070475912357, 0.5211154309075817, 0.0), # 2
(6.016757793146562, 6.062668793441743, 5.198342391099879, 5.579682305649055, 4.435107784001268, 2.191782029841316, 2.4810018208239777, 2.3197088156227115, 2.430045053640364, 1.1841956746065454, 0.8390580686378972, 0.4885571404108718, 0.0, 6.086272806254225, 5.374128544519589, 4.195290343189486, 3.5525870238196355, 4.860090107280728, 3.247592341871796, 2.4810018208239777, 1.5655585927437972, 2.217553892000634, 1.8598941018830188, 1.0396684782199759, 0.551151708494704, 0.0), # 3
(6.343136148415981, 6.389098099345293, 5.478244083085864, 5.880216481036927, 4.674763069197661, 2.3098432043158894, 2.6144718342542292, 2.444304942164548, 2.560900681860902, 1.24788897429192, 0.8842623557650959, 0.514858199362897, 0.0, 6.414188632939817, 5.6634401929918665, 4.42131177882548, 3.743666922875759, 5.121801363721804, 3.422026919030367, 2.6144718342542292, 1.6498880030827783, 2.3373815345988307, 1.9600721603456428, 1.095648816617173, 0.5808270999404813, 0.0), # 4
(6.66456271868351, 6.710236293698289, 5.753607444793765, 6.175877014290295, 4.910646611132853, 2.4259888147198754, 2.745778957362612, 2.566878236885247, 2.689633039327186, 1.310550451479666, 0.9287337544245222, 0.5407327839361791, 0.0, 6.736785359632827, 5.948060623297969, 4.64366877212261, 3.9316513544389973, 5.379266078654372, 3.593629531639346, 2.745778957362612, 1.7328491533713395, 2.4553233055664263, 2.058625671430099, 1.1507214889587531, 0.6100214812452991, 0.0), # 5
(6.979742147844666, 7.024762012504959, 6.023299607103222, 6.465447615037239, 5.141797182850695, 2.5397411688838374, 2.8743828532406313, 2.686924703751037, 2.8157126784122717, 1.3719222148381898, 0.9722892995297139, 0.5660744468730674, 0.0, 7.052736037699606, 6.22681891560374, 4.8614464976485685, 4.115766644514569, 5.631425356824543, 3.761694585251452, 2.8743828532406313, 1.8141008349170267, 2.5708985914253475, 2.1551492050124135, 1.2046599214206444, 0.6386147284095418, 0.0), # 6
(7.2873790797949685, 7.331353891769537, 6.286187700893863, 6.747711992905847, 5.367253557395036, 2.650622574638337, 2.9997431849797924, 2.8039403467281465, 2.9386101514892147, 1.4317463730358968, 1.0147460259942116, 0.5907767409159108, 0.0, 7.360713718506519, 6.498544150075018, 5.073730129971057, 4.2952391191076895, 5.877220302978429, 3.9255164854194056, 2.9997431849797924, 1.8933018390273837, 2.683626778697518, 2.249237330968616, 1.2572375401787725, 0.6664867174335943, 0.0), # 7
(7.586178158429934, 7.628690567496257, 6.54113885704533, 7.021453857524196, 5.586054507809724, 2.7581553398139356, 3.1213196156715988, 2.917421169782802, 3.0577960109310682, 1.4897650347411937, 1.0559209687315536, 0.6147332188070586, 0.0, 7.659391453419917, 6.762065406877643, 5.279604843657768, 4.469295104223581, 6.1155920218621365, 4.084389637695923, 3.1213196156715988, 1.970110957009954, 2.793027253904862, 2.3404846191747324, 1.3082277714090662, 0.6935173243178416, 0.0), # 8
(7.874844027645085, 7.915450675689353, 6.787020206437253, 7.285456918520376, 5.797238807138606, 2.861861772241199, 3.23857180840756, 3.0268631768812346, 3.1727408091108913, 1.5457203086224858, 1.0956311626552797, 0.6378374332888596, 0.0, 7.947442293806162, 7.016211766177453, 5.478155813276398, 4.637160925867456, 6.345481618221783, 4.237608447633728, 3.23857180840756, 2.044186980172285, 2.898619403569303, 2.4284856395067926, 1.3574040412874508, 0.7195864250626686, 0.0), # 9
(8.152081331335932, 8.190312852353056, 7.022698879949271, 7.538504885522466, 5.999845228425533, 2.961264179750688, 3.3509594262791773, 3.1317623719896712, 3.282915098401738, 1.599354303348179, 1.133693642678929, 0.6599829371036627, 0.0, 8.22353929103161, 7.259812308140289, 5.668468213394645, 4.798062910044536, 6.565830196803476, 4.384467320785539, 3.3509594262791773, 2.11518869982192, 2.9999226142127666, 2.5128349618408223, 1.4045397759898541, 0.7445738956684597, 0.0), # 10
(8.416594713398005, 8.451955733491605, 7.247042008461013, 7.779381468158547, 6.192912544714355, 3.055884870172965, 3.457942132377958, 3.2316147590743394, 3.3877894311766643, 1.6504091275866801, 1.1699254437160416, 0.6810632829938176, 0.0, 8.486355496462611, 7.491696112931993, 5.849627218580208, 4.951227382760039, 6.775578862353329, 4.524260662704076, 3.457942132377958, 2.1827749072664036, 3.0964562723571776, 2.5931271560528497, 1.4494084016922026, 0.7683596121356006, 0.0), # 11
(8.667088817726812, 8.699057955109222, 7.458916722852117, 8.006870376056709, 6.375479529048918, 3.1452461513385908, 3.5589795897954057, 3.325916342101467, 3.486834359808726, 1.6986268900063934, 1.2041436006801558, 0.7009720237016724, 0.0, 8.734563961465534, 7.710692260718395, 6.020718003400779, 5.095880670019179, 6.973668719617452, 4.656282878942054, 3.5589795897954057, 2.246604393813279, 3.187739764524459, 2.6689567920189035, 1.4917833445704234, 0.7908234504644749, 0.0), # 12
(8.902268288217876, 8.93029815321015, 7.657190154002218, 8.219755318845033, 6.546584954473067, 3.2288703310781304, 3.653531461623028, 3.414163125037284, 3.579520436670977, 1.7437496992757264, 1.2361651484848115, 0.7196027119695768, 0.0, 8.966837737406735, 7.915629831665344, 6.180825742424058, 5.2312490978271775, 7.159040873341954, 4.7798283750521975, 3.653531461623028, 2.306335950770093, 3.2732924772365335, 2.7399184396150114, 1.5314380308004438, 0.8118452866554684, 0.0), # 13
(9.120837768766716, 9.144354963798623, 7.840729432790956, 8.416820006151594, 6.705267594030659, 3.306279717222145, 3.7410574109523305, 3.4958511118480193, 3.6653182141364735, 1.785519664063084, 1.2658071220435476, 0.7368489005398801, 0.0, 9.181849875652563, 8.10533790593868, 6.329035610217737, 5.3565589921892505, 7.330636428272947, 4.894191556587227, 3.7410574109523305, 2.3616283694443894, 3.3526337970153297, 2.8056066687171985, 1.5681458865581912, 0.8313049967089657, 0.0), # 14
(9.321501903268855, 9.339907022878865, 8.008401690097953, 8.59684814760449, 6.850566220765538, 3.376996617601199, 3.821017100874813, 3.5704763064998986, 3.743698244578273, 1.823678893036873, 1.2928865562699035, 0.752604142154931, 0.0, 9.37827342756938, 8.27864556370424, 6.464432781349516, 5.471036679110618, 7.487396489156546, 4.998666829099858, 3.821017100874813, 2.4121404411437135, 3.425283110382769, 2.865616049201497, 1.6016803380195905, 0.8490824566253515, 0.0), # 15
(9.5029653356198, 9.51563296645512, 8.159074056802854, 8.758623452831788, 6.981519607721555, 3.4405433400458514, 3.892870194481988, 3.6375347129591504, 3.8141310803694286, 1.8579694948654994, 1.3172204860774188, 0.7667619895570784, 0.0, 9.554781444523545, 8.434381885127861, 6.586102430387094, 5.5739084845964975, 7.628262160738857, 5.092548598142811, 3.892870194481988, 2.4575309571756083, 3.4907598038607777, 2.9195411509439295, 1.6318148113605708, 0.8650575424050111, 0.0), # 16
(9.663932709715075, 9.670211430531618, 8.291613663785293, 8.900929631461583, 7.097166527942559, 3.4964421923866666, 3.9560763548653552, 3.6965223351920073, 3.8760872738829946, 1.8881335782173672, 1.3386259463796333, 0.7792159954886714, 0.0, 9.710046977881415, 8.571375950375383, 6.693129731898166, 5.6644007346521, 7.752174547765989, 5.17513126926881, 3.9560763548653552, 2.4974587088476192, 3.5485832639712793, 2.9669765438205284, 1.6583227327570589, 0.8791101300483289, 0.0), # 17
(9.803108669450204, 9.802321051112584, 8.404887641924901, 9.022550393121959, 7.1965457544723925, 3.5442154824542103, 4.010095245116426, 3.746935177164692, 3.929037377492032, 1.9139132517608846, 1.3569199720900849, 0.7898597126920597, 0.0, 9.842743079009345, 8.688456839612655, 6.784599860450424, 5.741739755282652, 7.858074754984064, 5.245709248030569, 4.010095245116426, 2.531582487467293, 3.5982728772361963, 3.0075167977073205, 1.6809775283849802, 0.8911200955556896, 0.0), # 18
(9.919197858720699, 9.910640464202265, 8.497763122101317, 9.122269447440985, 7.2786960603549105, 3.5833855180790386, 4.054386528326697, 3.7882692428434357, 3.9724519435695926, 1.9350506241644574, 1.3719195981223131, 0.7985866939095915, 0.0, 9.951542799273696, 8.784453633005505, 6.859597990611565, 5.80515187249337, 7.944903887139185, 5.30357693998081, 4.054386528326697, 2.55956108434217, 3.6393480301774552, 3.0407564824803295, 1.6995526244202632, 0.9009673149274788, 0.0), # 19
(10.010904921422082, 9.993848305804882, 8.569107235194169, 9.198870504046766, 7.342656218633962, 3.613474607091719, 4.088409867587681, 3.8200205361944657, 4.005801524488732, 1.95128780409649, 1.3834418593898585, 0.805290491883616, 0.0, 10.035119190040824, 8.858195410719775, 6.9172092969492915, 5.853863412289469, 8.011603048977465, 5.348028750672252, 4.088409867587681, 2.5810532907797996, 3.671328109316981, 3.0662901680155894, 1.713821447038834, 0.9085316641640803, 0.0), # 20
(10.076934501449866, 10.050623211924679, 8.6177871120831, 9.251137272567364, 7.387465002353392, 3.6340050573228124, 4.1116249259908795, 3.84168506118401, 4.028556672622507, 1.9623669002253892, 1.39130379080626, 0.8098646593564828, 0.0, 10.092145302677078, 8.90851125292131, 6.9565189540313, 5.887100700676166, 8.057113345245014, 5.378359085657614, 4.1116249259908795, 2.5957178980877234, 3.693732501176696, 3.0837124241891223, 1.72355742241662, 0.91369301926588, 0.0), # 21
(10.115991242699579, 10.079643818565883, 8.642669883647738, 9.277853462630876, 7.41216118455705, 3.644499176602881, 4.1234913666278, 3.852758821778298, 4.040187940343971, 1.968030021219561, 1.3953224272850568, 0.8122027490705409, 0.0, 10.121294188548827, 8.934230239775948, 6.976612136425284, 5.904090063658682, 8.080375880687942, 5.393862350489617, 4.1234913666278, 2.6032136975734863, 3.706080592278525, 3.09261782087696, 1.7285339767295478, 0.9163312562332622, 0.0), # 22
(10.13039336334264, 10.083079961133974, 8.645769318701419, 9.281198109567903, 7.418488037355065, 3.6458333333333335, 4.124902001129669, 3.8539557613168727, 4.0416420781893, 1.9686980681298587, 1.3958263395269568, 0.8124914647157445, 0.0, 10.125, 8.93740611187319, 6.9791316976347835, 5.906094204389575, 8.0832841563786, 5.395538065843622, 4.124902001129669, 2.604166666666667, 3.7092440186775324, 3.0937327031893016, 1.729153863740284, 0.9166436328303613, 0.0), # 23
(10.141012413034153, 10.08107561728395, 8.645262345679013, 9.280786458333335, 7.422071742409901, 3.6458333333333335, 4.124126906318083, 3.852291666666667, 4.041447222222222, 1.968287654320988, 1.39577076318743, 0.8124238683127573, 0.0, 10.125, 8.936662551440328, 6.978853815937151, 5.904862962962962, 8.082894444444443, 5.393208333333334, 4.124126906318083, 2.604166666666667, 3.7110358712049507, 3.0935954861111123, 1.7290524691358027, 0.9164614197530866, 0.0), # 24
(10.15140723021158, 10.077124771376313, 8.644261545496114, 9.279972029320987, 7.4255766303963355, 3.6458333333333335, 4.122599451303155, 3.8490226337448563, 4.041062242798354, 1.96747970964792, 1.3956605665710604, 0.8122904282883707, 0.0, 10.125, 8.935194711172077, 6.978302832855302, 5.902439128943758, 8.082124485596708, 5.388631687242799, 4.122599451303155, 2.604166666666667, 3.7127883151981678, 3.0933240097736636, 1.728852309099223, 0.9161022519433014, 0.0), # 25
(10.161577019048034, 10.071287780064015, 8.642780635573846, 9.278764081790122, 7.429002578947403, 3.6458333333333335, 4.120343359154361, 3.8442103909465026, 4.0404920781893, 1.9662876771833566, 1.3954967473084758, 0.8120929736320684, 0.0, 10.125, 8.933022709952752, 6.977483736542379, 5.898863031550069, 8.0809841563786, 5.381894547325103, 4.120343359154361, 2.604166666666667, 3.7145012894737013, 3.0929213605967085, 1.7285561271147696, 0.915571616369456, 0.0), # 26
(10.171520983716636, 10.063624999999998, 8.640833333333333, 9.277171874999999, 7.432349465696142, 3.6458333333333335, 4.117382352941177, 3.837916666666667, 4.039741666666666, 1.9647250000000003, 1.3952803030303031, 0.8118333333333335, 0.0, 10.125, 8.930166666666667, 6.976401515151515, 5.894175, 8.079483333333332, 5.373083333333334, 4.117382352941177, 2.604166666666667, 3.716174732848071, 3.0923906250000006, 1.7281666666666669, 0.914875, 0.0), # 27
(10.181238328390501, 10.054196787837219, 8.638433356195703, 9.275204668209877, 7.4356171682756, 3.6458333333333335, 4.113740155733075, 3.830203189300412, 4.038815946502057, 1.9628051211705537, 1.3950122313671698, 0.8115133363816492, 0.0, 10.125, 8.926646700198141, 6.9750611568358485, 5.88841536351166, 8.077631893004114, 5.3622844650205765, 4.113740155733075, 2.604166666666667, 3.7178085841378, 3.091734889403293, 1.7276866712391405, 0.9140178898033837, 0.0), # 28
(10.19072825724275, 10.043063500228623, 8.635594421582077, 9.272871720679012, 7.438805564318813, 3.6458333333333335, 4.109440490599533, 3.821131687242798, 4.037719855967078, 1.9605414837677189, 1.3946935299497027, 0.811134811766499, 0.0, 10.125, 8.922482929431489, 6.973467649748514, 5.881624451303155, 8.075439711934155, 5.349584362139917, 4.109440490599533, 2.604166666666667, 3.7194027821594067, 3.0909572402263383, 1.7271188843164156, 0.9130057727480568, 0.0), # 29
(10.199989974446497, 10.03028549382716, 8.63233024691358, 9.270182291666666, 7.441914531458824, 3.6458333333333335, 4.104507080610022, 3.8107638888888884, 4.036458333333333, 1.957947530864198, 1.39432519640853, 0.8106995884773662, 0.0, 10.125, 8.917695473251028, 6.9716259820426485, 5.873842592592593, 8.072916666666666, 5.335069444444444, 4.104507080610022, 2.604166666666667, 3.720957265729412, 3.0900607638888897, 1.7264660493827162, 0.9118441358024693, 0.0), # 30
(10.209022684174858, 10.01592312528578, 8.62865454961134, 9.267145640432098, 7.444943947328672, 3.6458333333333335, 4.09896364883402, 3.799161522633745, 4.035036316872428, 1.9550367055326936, 1.3939082283742779, 0.8102094955037343, 0.0, 10.125, 8.912304450541077, 6.969541141871389, 5.865110116598079, 8.070072633744855, 5.318826131687243, 4.09896364883402, 2.604166666666667, 3.722471973664336, 3.0890485468107003, 1.7257309099222682, 0.910538465935071, 0.0), # 31
(10.217825590600954, 10.00003675125743, 8.624581047096479, 9.263771026234568, 7.447893689561397, 3.6458333333333335, 4.092833918340999, 3.7863863168724285, 4.033458744855967, 1.951822450845908, 1.3934436234775742, 0.8096663618350862, 0.0, 10.125, 8.906329980185948, 6.96721811738787, 5.8554673525377225, 8.066917489711933, 5.3009408436214, 4.092833918340999, 2.604166666666667, 3.7239468447806985, 3.0879236754115236, 1.7249162094192958, 0.909094250114312, 0.0), # 32
(10.226397897897897, 9.98268672839506, 8.620123456790123, 9.260067708333333, 7.450763635790041, 3.6458333333333335, 4.086141612200436, 3.7725000000000004, 4.031730555555555, 1.9483182098765437, 1.392932379349046, 0.8090720164609053, 0.0, 10.125, 8.899792181069957, 6.96466189674523, 5.84495462962963, 8.06346111111111, 5.2815, 4.086141612200436, 2.604166666666667, 3.7253818178950207, 3.086689236111112, 1.724024691358025, 0.9075169753086421, 0.0), # 33
(10.23473881023881, 9.963933413351622, 8.615295496113397, 9.256044945987654, 7.453553663647644, 3.6458333333333335, 4.078910453481805, 3.7575643004115222, 4.029856687242798, 1.9445374256973027, 1.3923754936193207, 0.8084282883706753, 0.0, 10.125, 8.892711172077426, 6.961877468096604, 5.833612277091907, 8.059713374485597, 5.260590020576132, 4.078910453481805, 2.604166666666667, 3.726776831823822, 3.085348315329219, 1.7230590992226795, 0.9058121284865113, 0.0), # 34
(10.242847531796807, 9.943837162780063, 8.610110882487428, 9.25171199845679, 7.456263650767246, 3.6458333333333335, 4.071164165254579, 3.741640946502058, 4.0278420781893, 1.9404935413808875, 1.3917739639190256, 0.807737006553879, 0.0, 10.125, 8.88510707209267, 6.958869819595128, 5.821480624142661, 8.0556841563786, 5.238297325102881, 4.071164165254579, 2.604166666666667, 3.728131825383623, 3.0839039994855972, 1.7220221764974855, 0.9039851966163696, 0.0), # 35
(10.250723266745005, 9.922458333333331, 8.604583333333334, 9.247078125, 7.45889347478189, 3.6458333333333335, 4.062926470588235, 3.724791666666667, 4.025691666666666, 1.9362000000000004, 1.391128787878788, 0.8070000000000002, 0.0, 10.125, 8.877, 6.95564393939394, 5.8086, 8.051383333333332, 5.214708333333334, 4.062926470588235, 2.604166666666667, 3.729446737390945, 3.0823593750000007, 1.7209166666666669, 0.9020416666666666, 0.0), # 36
(10.258365219256524, 9.89985728166438, 8.598726566072246, 9.242152584876543, 7.4614430133246135, 3.6458333333333335, 4.054221092552247, 3.707078189300412, 4.023410390946502, 1.931670244627344, 1.3904409631292352, 0.8062190976985216, 0.0, 10.125, 8.868410074683737, 6.952204815646175, 5.79501073388203, 8.046820781893004, 5.189909465020577, 4.054221092552247, 2.604166666666667, 3.7307215066623067, 3.080717528292182, 1.7197453132144491, 0.8999870256058529, 0.0), # 37
(10.265772593504476, 9.876094364426155, 8.592554298125286, 9.23694463734568, 7.46391214402846, 3.6458333333333335, 4.04507175421609, 3.6885622427983544, 4.021003189300411, 1.92691771833562, 1.3897114873009937, 0.8053961286389272, 0.0, 10.125, 8.859357415028198, 6.948557436504967, 5.780753155006859, 8.042006378600822, 5.163987139917697, 4.04507175421609, 2.604166666666667, 3.73195607201423, 3.078981545781894, 1.7185108596250571, 0.8978267604023779, 0.0), # 38
(10.272944593661986, 9.851229938271604, 8.586080246913582, 9.231463541666667, 7.466300744526468, 3.6458333333333335, 4.035502178649238, 3.6693055555555554, 4.0184750000000005, 1.9219558641975314, 1.3889413580246914, 0.8045329218106996, 0.0, 10.125, 8.849862139917693, 6.944706790123457, 5.765867592592593, 8.036950000000001, 5.137027777777778, 4.035502178649238, 2.604166666666667, 3.733150372263234, 3.07715451388889, 1.7172160493827164, 0.8955663580246914, 0.0), # 39
(10.279880423902163, 9.82532435985368, 8.579318129858253, 9.225718557098766, 7.468608692451679, 3.6458333333333335, 4.025536088921165, 3.649369855967079, 4.015830761316872, 1.9167981252857802, 1.3881315729309558, 0.8036313062033228, 0.0, 10.125, 8.83994436823655, 6.940657864654778, 5.750394375857339, 8.031661522633744, 5.1091177983539104, 4.025536088921165, 2.604166666666667, 3.7343043462258394, 3.0752395190329227, 1.7158636259716507, 0.8932113054412438, 0.0), # 40
(10.286579288398128, 9.79843798582533, 8.57228166438043, 9.219718942901235, 7.4708358654371345, 3.6458333333333335, 4.015197208101347, 3.628816872427984, 4.0130754115226335, 1.9114579446730684, 1.3872831296504138, 0.8026931108062796, 0.0, 10.125, 8.829624218869075, 6.936415648252069, 5.734373834019204, 8.026150823045267, 5.0803436213991775, 4.015197208101347, 2.604166666666667, 3.7354179327185673, 3.073239647633746, 1.7144563328760862, 0.8907670896204848, 0.0), # 41
(10.293040391323, 9.770631172839506, 8.564984567901236, 9.213473958333335, 7.472982141115872, 3.6458333333333335, 4.004509259259259, 3.6077083333333335, 4.010213888888889, 1.9059487654320992, 1.3863970258136926, 0.8017201646090536, 0.0, 10.125, 8.818921810699589, 6.931985129068463, 5.717846296296297, 8.020427777777778, 5.050791666666667, 4.004509259259259, 2.604166666666667, 3.736491070557936, 3.0711579861111122, 1.7129969135802474, 0.8882391975308643, 0.0), # 42
(10.299262936849892, 9.741964277549155, 8.557440557841794, 9.206992862654321, 7.475047397120935, 3.6458333333333335, 3.993495965464375, 3.58610596707819, 4.007251131687243, 1.9002840306355744, 1.3854742590514195, 0.800714296601128, 0.0, 10.125, 8.807857262612407, 6.927371295257098, 5.700852091906722, 8.014502263374485, 5.020548353909466, 3.993495965464375, 2.604166666666667, 3.7375236985604676, 3.0689976208847747, 1.7114881115683587, 0.8856331161408324, 0.0), # 43
(10.305246129151927, 9.712497656607225, 8.549663351623229, 9.200284915123458, 7.477031511085363, 3.6458333333333335, 3.9821810497861696, 3.564071502057614, 4.0041920781893, 1.8944771833561962, 1.3845158269942222, 0.7996773357719861, 0.0, 10.125, 8.796450693491845, 6.92257913497111, 5.683431550068587, 8.0083841563786, 4.98970010288066, 3.9821810497861696, 2.604166666666667, 3.7385157555426813, 3.0667616383744867, 1.709932670324646, 0.8829543324188387, 0.0), # 44
(10.310989172402216, 9.682291666666666, 8.541666666666668, 9.193359375, 7.478934360642197, 3.6458333333333335, 3.9705882352941178, 3.541666666666667, 4.001041666666666, 1.8885416666666672, 1.3835227272727273, 0.798611111111111, 0.0, 10.125, 8.784722222222221, 6.917613636363637, 5.665625, 8.002083333333331, 4.958333333333334, 3.9705882352941178, 2.604166666666667, 3.7394671803210984, 3.064453125000001, 1.7083333333333335, 0.8802083333333335, 0.0), # 45
(10.31649127077388, 9.65140666438043, 8.533464220393233, 9.186225501543209, 7.480755823424477, 3.6458333333333335, 3.958741245057694, 3.518953189300412, 3.997804835390946, 1.8824909236396894, 1.3824959575175624, 0.7975174516079867, 0.0, 10.125, 8.772691967687852, 6.912479787587812, 5.647472770919067, 7.995609670781892, 4.926534465020577, 3.958741245057694, 2.604166666666667, 3.7403779117122387, 3.062075167181071, 1.7066928440786466, 0.8774006058527665, 0.0), # 46
(10.321751628440035, 9.619903006401461, 8.525069730224052, 9.178892554012345, 7.482495777065244, 3.6458333333333335, 3.9466638021463734, 3.4959927983539094, 3.994486522633745, 1.8763383973479657, 1.3814365153593549, 0.7963981862520958, 0.0, 10.125, 8.760380048773053, 6.9071825767967745, 5.629015192043896, 7.98897304526749, 4.894389917695474, 3.9466638021463734, 2.604166666666667, 3.741247888532622, 3.0596308513374493, 1.7050139460448106, 0.8745366369455876, 0.0), # 47
(10.326769449573796, 9.587841049382716, 8.516496913580248, 9.171369791666667, 7.48415409919754, 3.6458333333333335, 3.9343796296296296, 3.4728472222222226, 3.9910916666666667, 1.8700975308641978, 1.3803453984287317, 0.7952551440329219, 0.0, 10.125, 8.74780658436214, 6.901726992143659, 5.610292592592592, 7.982183333333333, 4.861986111111112, 3.9343796296296296, 2.604166666666667, 3.74207704959877, 3.05712326388889, 1.7032993827160496, 0.871621913580247, 0.0), # 48
(10.331543938348286, 9.555281149977136, 8.507759487882945, 9.163666473765433, 7.485730667454405, 3.6458333333333335, 3.9219124505769383, 3.4495781893004116, 3.987625205761317, 1.8637817672610888, 1.3792236043563206, 0.7940901539399483, 0.0, 10.125, 8.73499169333943, 6.896118021781603, 5.5913453017832655, 7.975250411522634, 4.829409465020577, 3.9219124505769383, 2.604166666666667, 3.7428653337272024, 3.054555491255145, 1.7015518975765893, 0.8686619227251944, 0.0), # 49
(10.336074298936616, 9.522283664837678, 8.49887117055327, 9.155791859567902, 7.4872253594688765, 3.6458333333333335, 3.909285988057775, 3.4262474279835393, 3.9840920781893, 1.85740454961134, 1.3780721307727481, 0.7929050449626583, 0.0, 10.125, 8.72195549458924, 6.89036065386374, 5.572213648834019, 7.9681841563786, 4.796746399176955, 3.909285988057775, 2.604166666666667, 3.7436126797344382, 3.051930619855968, 1.6997742341106543, 0.86566215134888, 0.0), # 50
(10.34035973551191, 9.488908950617283, 8.489845679012346, 9.147755208333333, 7.488638052873998, 3.6458333333333335, 3.896523965141612, 3.4029166666666666, 3.9804972222222226, 1.8509793209876546, 1.3768919753086422, 0.7917016460905352, 0.0, 10.125, 8.708718106995885, 6.884459876543211, 5.552937962962963, 7.960994444444445, 4.764083333333334, 3.896523965141612, 2.604166666666667, 3.744319026436999, 3.049251736111112, 1.6979691358024693, 0.8626280864197532, 0.0), # 51
(10.344399452247279, 9.455217363968908, 8.480696730681299, 9.139565779320987, 7.489968625302809, 3.6458333333333335, 3.883650104897926, 3.3796476337448556, 3.976845576131687, 1.8445195244627348, 1.3756841355946297, 0.7904817863130622, 0.0, 10.125, 8.695299649443683, 6.878420677973147, 5.533558573388203, 7.953691152263374, 4.731506687242798, 3.883650104897926, 2.604166666666667, 3.7449843126514044, 3.04652192644033, 1.69613934613626, 0.8595652149062645, 0.0), # 52
(10.348192653315843, 9.421269261545497, 8.471438042981255, 9.131232831790122, 7.491216954388353, 3.6458333333333335, 3.8706881303961915, 3.3565020576131688, 3.9731420781893005, 1.8380386031092826, 1.3744496092613379, 0.7892472946197227, 0.0, 10.125, 8.681720240816947, 6.872248046306688, 5.514115809327846, 7.946284156378601, 4.699102880658437, 3.8706881303961915, 2.604166666666667, 3.7456084771941764, 3.043744277263375, 1.694287608596251, 0.8564790237768635, 0.0), # 53
(10.351738542890716, 9.387125000000001, 8.462083333333332, 9.122765625, 7.492382917763668, 3.6458333333333335, 3.8576617647058824, 3.333541666666666, 3.9693916666666667, 1.8315500000000005, 1.3731893939393938, 0.788, 0.0, 10.125, 8.668, 6.865946969696969, 5.49465, 7.938783333333333, 4.666958333333333, 3.8576617647058824, 2.604166666666667, 3.746191458881834, 3.040921875000001, 1.6924166666666667, 0.8533750000000002, 0.0), # 54
(10.355036325145022, 9.352844935985367, 8.452646319158665, 9.114173418209877, 7.493466393061793, 3.6458333333333335, 3.844594730896474, 3.3108281893004117, 3.9655992798353905, 1.8250671582075908, 1.3719044872594257, 0.7867417314433777, 0.0, 10.125, 8.654159045877153, 6.859522436297127, 5.4752014746227715, 7.931198559670781, 4.6351594650205765, 3.844594730896474, 2.604166666666667, 3.7467331965308963, 3.0380578060699595, 1.6905292638317333, 0.8502586305441244, 0.0), # 55
(10.358085204251871, 9.31848942615455, 8.443140717878373, 9.105465470679011, 7.4944672579157725, 3.6458333333333335, 3.8315107520374405, 3.288423353909465, 3.961769855967078, 1.818603520804756, 1.3705958868520598, 0.7854743179393385, 0.0, 10.125, 8.640217497332722, 6.852979434260299, 5.455810562414267, 7.923539711934156, 4.603792695473251, 3.8315107520374405, 2.604166666666667, 3.7472336289578863, 3.035155156893005, 1.6886281435756747, 0.8471354023776865, 0.0), # 56
(10.360884384384383, 9.284118827160494, 8.433580246913582, 9.096651041666666, 7.495385389958644, 3.6458333333333335, 3.818433551198257, 3.2663888888888892, 3.957908333333333, 1.812172530864198, 1.369264590347924, 0.7841995884773663, 0.0, 10.125, 8.626195473251027, 6.8463229517396185, 5.436517592592593, 7.915816666666666, 4.572944444444445, 3.818433551198257, 2.604166666666667, 3.747692694979322, 3.0322170138888898, 1.6867160493827165, 0.844010802469136, 0.0), # 57
(10.36343306971568, 9.24979349565615, 8.423978623685414, 9.087739390432098, 7.496220666823449, 3.6458333333333335, 3.8053868514483984, 3.2447865226337447, 3.954019650205761, 1.8057876314586196, 1.367911595377645, 0.7829193720469442, 0.0, 10.125, 8.612113092516385, 6.8395579768882255, 5.417362894375858, 7.908039300411522, 4.5427011316872425, 3.8053868514483984, 2.604166666666667, 3.7481103334117245, 3.029246463477367, 1.684795724737083, 0.8408903177869229, 0.0), # 58
(10.36573046441887, 9.215573788294467, 8.414349565614998, 9.078739776234567, 7.49697296614323, 3.6458333333333335, 3.792394375857339, 3.2236779835390945, 3.9501087448559673, 1.799462265660723, 1.3665378995718502, 0.7816354976375554, 0.0, 10.125, 8.597990474013107, 6.83268949785925, 5.398386796982168, 7.900217489711935, 4.513149176954733, 3.792394375857339, 2.604166666666667, 3.748486483071615, 3.02624659207819, 1.6828699131229998, 0.8377794352994972, 0.0), # 59
(10.367775772667077, 9.181520061728396, 8.404706790123456, 9.069661458333334, 7.497642165551024, 3.6458333333333335, 3.779479847494553, 3.203125, 3.946180555555556, 1.7932098765432103, 1.3651445005611673, 0.7803497942386832, 0.0, 10.125, 8.583847736625515, 6.825722502805837, 5.37962962962963, 7.892361111111112, 4.484375, 3.779479847494553, 2.604166666666667, 3.748821082775512, 3.023220486111112, 1.6809413580246915, 0.8346836419753088, 0.0), # 60
(10.369568198633415, 9.147692672610884, 8.395064014631917, 9.060513695987654, 7.498228142679874, 3.6458333333333335, 3.7666669894295164, 3.183189300411523, 3.9422400205761314, 1.7870439071787843, 1.3637323959762233, 0.7790640908398111, 0.0, 10.125, 8.56970499923792, 6.818661979881115, 5.361131721536351, 7.884480041152263, 4.456465020576132, 3.7666669894295164, 2.604166666666667, 3.749114071339937, 3.0201712319958856, 1.6790128029263836, 0.8316084247828076, 0.0), # 61
(10.371106946491004, 9.114151977594878, 8.385434956561502, 9.051305748456791, 7.498730775162823, 3.6458333333333335, 3.753979524731703, 3.1639326131687247, 3.9382920781893, 1.7809778006401469, 1.3623025834476452, 0.7777802164304223, 0.0, 10.125, 8.555582380734645, 6.811512917238226, 5.3429334019204395, 7.8765841563786, 4.429505658436215, 3.753979524731703, 2.604166666666667, 3.7493653875814115, 3.0171019161522645, 1.6770869913123003, 0.8285592706904436, 0.0), # 62
(10.37239122041296, 9.080958333333333, 8.375833333333334, 9.042046875, 7.499149940632904, 3.6458333333333335, 3.741441176470588, 3.1454166666666667, 3.9343416666666666, 1.7750250000000003, 1.360856060606061, 0.7765000000000001, 0.0, 10.125, 8.5415, 6.804280303030303, 5.325075, 7.868683333333333, 4.403583333333334, 3.741441176470588, 2.604166666666667, 3.749574970316452, 3.014015625000001, 1.675166666666667, 0.8255416666666667, 0.0), # 63
(10.373420224572397, 9.048172096479195, 8.366272862368541, 9.032746334876544, 7.4994855167231655, 3.6458333333333335, 3.729075667715646, 3.127703189300412, 3.9303937242798352, 1.7691989483310475, 1.3593938250820965, 0.7752252705380279, 0.0, 10.125, 8.527477975918305, 6.796969125410483, 5.307596844993141, 7.8607874485596705, 4.378784465020577, 3.729075667715646, 2.604166666666667, 3.7497427583615828, 3.0109154449588487, 1.6732545724737085, 0.822561099679927, 0.0), # 64
(10.374193163142438, 9.015853623685413, 8.35676726108825, 9.023413387345679, 7.499737381066645, 3.6458333333333335, 3.7169067215363514, 3.1108539094650207, 3.9264531893004113, 1.7635130887059902, 1.357916874506381, 0.7739578570339887, 0.0, 10.125, 8.513536427373873, 6.7895843725319045, 5.290539266117969, 7.852906378600823, 4.355195473251029, 3.7169067215363514, 2.604166666666667, 3.7498686905333223, 3.0078044624485605, 1.67135345221765, 0.819623056698674, 0.0), # 65
(10.374709240296196, 8.984063271604938, 8.34733024691358, 9.014057291666667, 7.499905411296382, 3.6458333333333335, 3.7049580610021784, 3.094930555555556, 3.9225250000000003, 1.7579808641975312, 1.3564262065095398, 0.7726995884773664, 0.0, 10.125, 8.499695473251029, 6.782131032547699, 5.273942592592592, 7.8450500000000005, 4.332902777777778, 3.7049580610021784, 2.604166666666667, 3.749952705648191, 3.0046857638888897, 1.6694660493827165, 0.8167330246913582, 0.0), # 66
(10.374967660206792, 8.952861396890716, 8.337975537265661, 9.004687307098765, 7.499989485045419, 3.6458333333333335, 3.693253409182603, 3.0799948559670787, 3.9186140946502057, 1.7526157178783728, 1.3549228187222018, 0.7714522938576437, 0.0, 10.125, 8.485975232434079, 6.774614093611008, 5.257847153635117, 7.837228189300411, 4.31199279835391, 3.693253409182603, 2.604166666666667, 3.7499947425227096, 3.001562435699589, 1.6675951074531323, 0.8138964906264289, 0.0), # 67
(10.374791614480825, 8.922144586043629, 8.328671624942844, 8.995231305354269, 7.499918636864896, 3.645765673423767, 3.681757597414823, 3.0659766041761927, 3.9146959495503735, 1.747405110411792, 1.3533809980900628, 0.770210835158312, 0.0, 10.124875150034294, 8.47231918674143, 6.766904990450313, 5.242215331235375, 7.829391899100747, 4.29236724584667, 3.681757597414823, 2.604118338159833, 3.749959318432448, 2.99841043511809, 1.6657343249885688, 0.8111040532766937, 0.0), # 68
(10.373141706924315, 8.890975059737157, 8.319157021604937, 8.985212635869564, 7.499273783587508, 3.6452307956104257, 3.6701340906733066, 3.052124485596708, 3.910599279835391, 1.7422015976761076, 1.3516438064859118, 0.7689349144466104, 0.0, 10.12388599537037, 8.458284058912714, 6.758219032429559, 5.226604793028321, 7.821198559670782, 4.272974279835391, 3.6701340906733066, 2.6037362825788755, 3.749636891793754, 2.9950708786231885, 1.6638314043209876, 0.8082704599761052, 0.0), # 69
(10.369885787558895, 8.859209754856408, 8.309390360653863, 8.974565343196456, 7.497999542752628, 3.6441773992785653, 3.658330067280685, 3.0383135192805977, 3.9063009640298736, 1.736979881115684, 1.3496914810876801, 0.7676185634410675, 0.0, 10.121932334533609, 8.44380419785174, 6.7484574054383994, 5.210939643347051, 7.812601928059747, 4.253638926992837, 3.658330067280685, 2.6029838566275467, 3.748999771376314, 2.991521781065486, 1.6618780721307727, 0.8053827049869463, 0.0), # 70
(10.365069660642929, 8.826867654542236, 8.299375071444901, 8.963305127818035, 7.496112052502757, 3.6426225549966977, 3.646350829769494, 3.0245482777015704, 3.9018074035970125, 1.7317400898356603, 1.347531228463977, 0.7662627447677263, 0.0, 10.119039887688615, 8.428890192444989, 6.737656142319885, 5.195220269506979, 7.803614807194025, 4.234367588782199, 3.646350829769494, 2.6018732535690696, 3.7480560262513785, 2.987768375939346, 1.6598750142889804, 0.8024425140492942, 0.0), # 71
(10.358739130434783, 8.793967741935482, 8.289114583333333, 8.95144769021739, 7.493627450980392, 3.6405833333333337, 3.634201680672269, 3.0108333333333333, 3.897125, 1.7264823529411768, 1.3451702551834133, 0.7648684210526316, 0.0, 10.115234375, 8.413552631578947, 6.7258512759170666, 5.179447058823529, 7.79425, 4.215166666666667, 3.634201680672269, 2.600416666666667, 3.746813725490196, 2.983815896739131, 1.6578229166666667, 0.7994516129032258, 0.0), # 72
(10.35094000119282, 8.760529000176998, 8.27861232567444, 8.939008730877617, 7.490561876328034, 3.638076804856983, 3.621887922521546, 2.9971732586495965, 3.8922601547020275, 1.7212067995373737, 1.3426157678145982, 0.7634365549218266, 0.0, 10.110541516632374, 8.397802104140093, 6.71307883907299, 5.163620398612119, 7.784520309404055, 4.196042562109435, 3.621887922521546, 2.598626289183559, 3.745280938164017, 2.979669576959206, 1.655722465134888, 0.7964117272888181, 0.0), # 73
(10.341718077175404, 8.726570412407629, 8.267871727823502, 8.926003950281803, 7.486931466688183, 3.6351200401361585, 3.609414857849861, 2.9835726261240665, 3.8872192691662857, 1.7159135587293908, 1.3398749729261428, 0.7619681090013557, 0.0, 10.104987032750344, 8.38164919901491, 6.699374864630713, 5.147740676188171, 7.774438538332571, 4.177001676573693, 3.609414857849861, 2.5965143143829703, 3.7434657333440917, 2.975334650093935, 1.6535743455647005, 0.7933245829461482, 0.0), # 74
(10.331119162640901, 8.692110961768218, 8.256896219135802, 8.912449048913043, 7.482752360203341, 3.6317301097393697, 3.59678778918975, 2.9700360082304527, 3.8820087448559666, 1.7106027596223679, 1.336955077086656, 0.7604640459172624, 0.0, 10.098596643518519, 8.365104505089885, 6.684775385433279, 5.131808278867102, 7.764017489711933, 4.158050411522634, 3.59678778918975, 2.594092935528121, 3.7413761801016703, 2.9708163496376816, 1.6513792438271604, 0.7901919056152927, 0.0), # 75
(10.319189061847677, 8.65716963139962, 8.245689228966622, 8.898359727254428, 7.478040695016003, 3.6279240842351275, 3.5840120190737474, 2.956567977442463, 3.876634983234263, 1.7052745313214452, 1.3338632868647486, 0.7589253282955902, 0.0, 10.091396069101508, 8.348178611251491, 6.669316434323743, 5.115823593964334, 7.753269966468526, 4.139195168419449, 3.5840120190737474, 2.5913743458822336, 3.7390203475080015, 2.96611990908481, 1.6491378457933243, 0.7870154210363293, 0.0), # 76
(10.305973579054093, 8.621765404442675, 8.234254186671238, 8.883751685789049, 7.472812609268672, 3.6237190341919425, 3.5710928500343897, 2.9431731062338065, 3.871104385764365, 1.699929002931763, 1.3306068088290313, 0.7573529187623839, 0.0, 10.083411029663925, 8.330882106386222, 6.653034044145156, 5.099787008795288, 7.74220877152873, 4.120442348727329, 3.5710928500343897, 2.58837073870853, 3.736406304634336, 2.9612505619296834, 1.6468508373342476, 0.7837968549493343, 0.0), # 77
(10.291518518518519, 8.585917264038233, 8.222594521604938, 8.868640625, 7.467084241103849, 3.6191320301783265, 3.5580355846042124, 2.9298559670781894, 3.8654233539094642, 1.6945663035584608, 1.327192849548113, 0.7557477799436866, 0.0, 10.074667245370371, 8.313225579380552, 6.635964247740564, 5.083698910675381, 7.7308467078189285, 4.101798353909466, 3.5580355846042124, 2.585094307270233, 3.7335421205519244, 2.956213541666667, 1.6445189043209878, 0.7805379330943849, 0.0), # 78
(10.275869684499314, 8.549644193327138, 8.210713663123, 8.85304224537037, 7.460871728664031, 3.61418014276279, 3.5448455253157505, 2.916621132449322, 3.859598289132754, 1.6891865623066789, 1.3236286155906039, 0.7541108744655421, 0.0, 10.065190436385459, 8.295219619120962, 6.618143077953018, 5.067559686920035, 7.719196578265508, 4.083269585429051, 3.5448455253157505, 2.5815572448305644, 3.7304358643320157, 2.951014081790124, 1.6421427326246, 0.7772403812115581, 0.0), # 79
(10.259072881254847, 8.51296517545024, 8.198615040580703, 8.836972247383253, 7.454191210091719, 3.6088804425138448, 3.5315279747015405, 2.9034731748209115, 3.853635592897424, 1.683789908281557, 1.3199213135251149, 0.7524431649539947, 0.0, 10.0550063228738, 8.27687481449394, 6.599606567625574, 5.05136972484467, 7.707271185794848, 4.064862444749276, 3.5315279747015405, 2.577771744652746, 3.7270956050458595, 2.945657415794418, 1.639723008116141, 0.7739059250409311, 0.0), # 80
(10.241173913043479, 8.475899193548386, 8.186302083333333, 8.82044633152174, 7.447058823529411, 3.60325, 3.5180882352941176, 2.890416666666667, 3.8475416666666664, 1.6783764705882358, 1.3160781499202554, 0.7507456140350878, 0.0, 10.044140624999999, 8.258201754385965, 6.580390749601277, 5.035129411764706, 7.695083333333333, 4.046583333333333, 3.5180882352941176, 2.57375, 3.7235294117647055, 2.940148777173914, 1.6372604166666667, 0.7705362903225808, 0.0), # 81
(10.222218584123576, 8.438465230762423, 8.17377822073617, 8.803480198268922, 7.43949070711961, 3.5973058857897686, 3.504531609626018, 2.8774561804602956, 3.841322911903673, 1.6729463783318543, 1.3121063313446355, 0.7490191843348656, 0.0, 10.03261906292867, 8.23921102768352, 6.560531656723177, 5.018839134995561, 7.682645823807346, 4.0284386526444145, 3.504531609626018, 2.5695042041355487, 3.719745353559805, 2.934493399422974, 1.634755644147234, 0.767133202796584, 0.0), # 82
(10.202252698753504, 8.400682270233196, 8.16104688214449, 8.78608954810789, 7.431502999004814, 3.591065170451659, 3.4908634002297765, 2.8645962886755068, 3.8349857300716352, 1.6674997606175532, 1.3080130643668657, 0.7472648384793719, 0.0, 10.020467356824417, 8.219913223273089, 6.540065321834328, 5.002499281852659, 7.6699714601432705, 4.01043480414571, 3.4908634002297765, 2.5650465503226134, 3.715751499502407, 2.9286965160359637, 1.632209376428898, 0.7636983882030178, 0.0), # 83
(10.181322061191626, 8.362569295101553, 8.14811149691358, 8.768290081521739, 7.423111837327523, 3.584544924554184, 3.477088909637929, 2.851841563786008, 3.8285365226337444, 1.6620367465504726, 1.3038055555555557, 0.7454835390946503, 0.0, 10.007711226851852, 8.200318930041153, 6.519027777777778, 4.986110239651417, 7.657073045267489, 3.9925781893004113, 3.477088909637929, 2.5603892318244172, 3.7115559186637617, 2.922763360507247, 1.629622299382716, 0.7602335722819594, 0.0), # 84
(10.159472475696308, 8.32414528850834, 8.13497549439872, 8.75009749899356, 7.414333360230238, 3.577762218665854, 3.463213440383012, 2.8391965782655086, 3.8219816910531925, 1.6565574652357518, 1.2994910114793157, 0.7436762488067449, 0.0, 9.994376393175584, 8.180438736874192, 6.497455057396579, 4.969672395707254, 7.643963382106385, 3.9748752095717124, 3.463213440383012, 2.5555444419041815, 3.707166680115119, 2.916699166331187, 1.626995098879744, 0.7567404807734855, 0.0), # 85
(10.136749746525913, 8.285429233594407, 8.121642303955191, 8.731527501006443, 7.405183705855455, 3.57073412335518, 3.44924229499756, 2.826665904587715, 3.815327636793172, 1.6510620457785314, 1.2950766387067558, 0.7418439302416996, 0.0, 9.98048857596022, 8.160283232658694, 6.475383193533778, 4.953186137335593, 7.630655273586344, 3.9573322664228017, 3.44924229499756, 2.550524373825129, 3.7025918529277275, 2.910509167002148, 1.6243284607910382, 0.7532208394176735, 0.0), # 86
(10.113199677938807, 8.246440113500597, 8.10811535493827, 8.712595788043478, 7.3956790123456795, 3.563477709190672, 3.4351807760141093, 2.8142541152263374, 3.8085807613168727, 1.645550617283951, 1.290569643806486, 0.7399875460255577, 0.0, 9.96607349537037, 8.139863006281134, 6.452848219032429, 4.936651851851852, 7.6171615226337455, 3.9399557613168725, 3.4351807760141093, 2.54534122085048, 3.6978395061728397, 2.904198596014493, 1.6216230709876542, 0.7496763739545999, 0.0), # 87
(10.088868074193357, 8.207196911367758, 8.094398076703246, 8.693318060587762, 7.385835417843406, 3.5560100467408424, 3.4210341859651954, 2.801965782655083, 3.8017474660874866, 1.6400233088571508, 1.2859772333471164, 0.7381080587843638, 0.0, 9.951156871570646, 8.119188646628, 6.429886166735582, 4.9200699265714505, 7.603494932174973, 3.9227520957171165, 3.4210341859651954, 2.540007176243459, 3.692917708921703, 2.897772686862588, 1.6188796153406495, 0.7461088101243417, 0.0), # 88
(10.063800739547922, 8.16771861033674, 8.080493898605397, 8.673710019122383, 7.375669060491138, 3.5483482065742016, 3.406807827383354, 2.7898054793476605, 3.794834152568206, 1.634480249603271, 1.2813066138972575, 0.7362064311441613, 0.0, 9.935764424725651, 8.098270742585774, 6.4065330694862865, 4.903440748809812, 7.589668305136412, 3.905727671086725, 3.406807827383354, 2.534534433267287, 3.687834530245569, 2.891236673040795, 1.6160987797210793, 0.7425198736669765, 0.0), # 89
(10.03804347826087, 8.128024193548386, 8.06640625, 8.653787364130435, 7.365196078431373, 3.5405092592592595, 3.3925070028011204, 2.7777777777777777, 3.7878472222222226, 1.6289215686274514, 1.2765649920255184, 0.7342836257309943, 0.0, 9.919921875, 8.077119883040936, 6.382824960127592, 4.886764705882353, 7.575694444444445, 3.888888888888889, 3.3925070028011204, 2.5289351851851856, 3.6825980392156863, 2.884595788043479, 1.6132812500000002, 0.7389112903225807, 0.0), # 90
(10.011642094590563, 8.088132644143545, 8.05213856024234, 8.63356579609501, 7.35443260980661, 3.532510275364528, 3.378137014751031, 2.7658872504191434, 3.780793076512727, 1.6233473950348318, 1.2717595743005101, 0.7323406051709063, 0.0, 9.903654942558298, 8.055746656879968, 6.35879787150255, 4.870042185104494, 7.561586153025454, 3.872242150586801, 3.378137014751031, 2.5232216252603767, 3.677216304903305, 2.8778552653650036, 1.6104277120484682, 0.7352847858312315, 0.0), # 91
(9.984642392795372, 8.048062945263066, 8.0376942586877, 8.613061015499195, 7.343394792759352, 3.524368325458518, 3.363703165765621, 2.754138469745466, 3.773678116902911, 1.6177578579305527, 1.2668975672908422, 0.7303783320899415, 0.0, 9.886989347565157, 8.034161652989356, 6.334487836454211, 4.853273573791657, 7.547356233805822, 3.8557938576436523, 3.363703165765621, 2.517405946756084, 3.671697396379676, 2.871020338499732, 1.6075388517375402, 0.7316420859330061, 0.0), # 92
(9.957090177133654, 8.00783408004779, 8.023076774691358, 8.592288722826089, 7.332098765432098, 3.5161004801097393, 3.349210758377425, 2.742536008230453, 3.766508744855967, 1.6121530864197533, 1.261986177565125, 0.7283977691141434, 0.0, 9.869950810185184, 8.012375460255576, 6.309930887825625, 4.836459259259259, 7.533017489711934, 3.839550411522634, 3.349210758377425, 2.5115003429355283, 3.666049382716049, 2.86409624094203, 1.6046153549382718, 0.727984916367981, 0.0), # 93
(9.92903125186378, 7.967465031638567, 8.008289537608597, 8.571264618558777, 7.320560665967347, 3.5077238098867043, 3.3346650951189805, 2.7310844383478132, 3.759291361835086, 1.6065332096075746, 1.2570326116919686, 0.7263998788695563, 0.0, 9.85256505058299, 7.990398667565118, 6.285163058459842, 4.819599628822722, 7.518582723670172, 3.823518213686939, 3.3346650951189805, 2.5055170070619317, 3.6602803329836733, 2.8570882061862592, 1.6016579075217197, 0.7243150028762335, 0.0), # 94
(9.90051142124411, 7.926974783176247, 7.993335976794697, 8.550004403180354, 7.308796632507598, 3.499255385357923, 3.320071478522822, 2.719788332571255, 3.7520323693034596, 1.6008983565991557, 1.2520440762399827, 0.7243856239822234, 0.0, 9.834857788923182, 7.968241863804456, 6.260220381199914, 4.8026950697974655, 7.504064738606919, 3.8077036655997567, 3.320071478522822, 2.4994681323985164, 3.654398316253799, 2.850001467726785, 1.5986671953589393, 0.7206340711978407, 0.0), # 95
(9.871576489533012, 7.886382317801674, 7.978219521604939, 8.528523777173913, 7.296822803195352, 3.4907122770919066, 3.3054352111214853, 2.708652263374486, 3.7447381687242793, 1.5952486564996373, 1.247027777777778, 0.7223559670781895, 0.0, 9.816854745370371, 7.945915637860083, 6.23513888888889, 4.785745969498911, 7.489476337448559, 3.7921131687242804, 3.3054352111214853, 2.4933659122085046, 3.648411401597676, 2.8428412590579715, 1.595643904320988, 0.7169438470728796, 0.0), # 96
(9.842272260988848, 7.845706618655694, 7.962943601394604, 8.506838441022543, 7.284655316173109, 3.482111555657166, 3.2907615954475067, 2.697680803231215, 3.7374151615607376, 1.589584238414159, 1.2419909228739638, 0.7203118707834976, 0.0, 9.798581640089164, 7.923430578618472, 6.209954614369819, 4.768752715242476, 7.474830323121475, 3.7767531245237014, 3.2907615954475067, 2.4872225397551184, 3.6423276580865545, 2.8356128136741816, 1.5925887202789208, 0.7132460562414268, 0.0), # 97
(9.812644539869984, 7.804966668879153, 7.947511645518976, 8.48496409520934, 7.272310309583368, 3.4734702916222124, 3.276055934033421, 2.68687852461515, 3.7300697492760246, 1.5839052314478608, 1.236940718097151, 0.7182542977241916, 0.0, 9.78006419324417, 7.900797274966106, 6.184703590485755, 4.751715694343581, 7.460139498552049, 3.7616299344612103, 3.276055934033421, 2.48105020830158, 3.636155154791684, 2.8283213650697805, 1.589502329103795, 0.7095424244435595, 0.0), # 98
(9.782739130434782, 7.764181451612902, 7.931927083333334, 8.462916440217391, 7.259803921568627, 3.464805555555556, 3.261323529411765, 2.67625, 3.7227083333333333, 1.5782117647058826, 1.2318843700159492, 0.7161842105263159, 0.0, 9.761328125, 7.878026315789473, 6.159421850079745, 4.734635294117647, 7.445416666666667, 3.7467500000000005, 3.261323529411765, 2.474861111111111, 3.6299019607843137, 2.820972146739131, 1.5863854166666669, 0.7058346774193549, 0.0), # 99
(9.752601836941611, 7.723369949997786, 7.916193344192958, 8.44071117652979, 7.247152290271389, 3.4561344180257074, 3.2465696841150726, 2.665799801859473, 3.715337315195854, 1.572503967293365, 1.2268290851989685, 0.714102571815914, 0.0, 9.742399155521262, 7.8551282899750525, 6.134145425994841, 4.717511901880093, 7.430674630391708, 3.732119722603262, 3.2465696841150726, 2.468667441446934, 3.6235761451356945, 2.8135703921765973, 1.5832386688385918, 0.7021245409088898, 0.0), # 100
(9.722278463648834, 7.682551147174654, 7.900313857453133, 8.41836400462963, 7.234371553834153, 3.4474739496011786, 3.231799700675881, 2.6555325026672763, 3.7079630963267793, 1.5667819683154474, 1.2217820702148188, 0.7120103442190294, 0.0, 9.723303004972564, 7.832113786409323, 6.108910351074094, 4.7003459049463405, 7.415926192653559, 3.7177455037341867, 3.231799700675881, 2.4624813925722706, 3.6171857769170765, 2.806121334876544, 1.5800627714906266, 0.6984137406522414, 0.0), # 101
(9.691814814814816, 7.641744026284349, 7.884292052469135, 8.395890625, 7.221477850399419, 3.4388412208504806, 3.217018881626725, 2.645452674897119, 3.7005920781893, 1.56104589687727, 1.2167505316321108, 0.7099084903617069, 0.0, 9.704065393518519, 7.808993393978774, 6.083752658160553, 4.683137690631809, 7.4011841563786, 3.703633744855967, 3.217018881626725, 2.4563151577503435, 3.6107389251997093, 2.798630208333334, 1.5768584104938272, 0.6947040023894864, 0.0), # 102
(9.661256694697919, 7.60096757046772, 7.8681313585962505, 8.373306738123993, 7.208487318109686, 3.430253302342123, 3.20223252950014, 2.63556489102271, 3.6932306622466085, 1.5552958820839726, 1.211741676019454, 0.7077979728699895, 0.0, 9.68471204132373, 7.785777701569883, 6.058708380097269, 4.6658876462519165, 7.386461324493217, 3.689790847431794, 3.20223252950014, 2.4501809302443736, 3.604243659054843, 2.7911022460413317, 1.5736262717192502, 0.6909970518607019, 0.0), # 103
(9.63064990755651, 7.560240762865614, 7.851835205189758, 8.350628044484703, 7.195416095107452, 3.421727264644617, 3.187445946828663, 2.6258737235177567, 3.685885249961896, 1.5495320530406955, 1.2067627099454585, 0.7056797543699213, 0.0, 9.665268668552812, 7.762477298069133, 6.033813549727292, 4.648596159122086, 7.371770499923792, 3.6762232129248593, 3.187445946828663, 2.4440909033175835, 3.597708047553726, 2.783542681494901, 1.5703670410379515, 0.687294614805965, 0.0), # 104
(9.600040257648953, 7.519582586618876, 7.835407021604938, 8.327870244565217, 7.182280319535221, 3.4132801783264752, 3.172664436144829, 2.6163837448559675, 3.6785622427983538, 1.5437545388525786, 1.201820839978735, 0.7035547974875461, 0.0, 9.64576099537037, 7.739102772363006, 6.009104199893674, 4.631263616557734, 7.3571244855967075, 3.662937242798354, 3.172664436144829, 2.4380572702331964, 3.5911401597676105, 2.775956748188406, 1.5670814043209877, 0.6835984169653525, 0.0), # 105
(9.569473549233614, 7.479012024868357, 7.818850237197074, 8.305049038848631, 7.1690961295354905, 3.404929113956206, 3.1578932999811724, 2.6070995275110502, 3.6712680422191735, 1.5379634686247616, 1.1969232726878927, 0.701424064848908, 0.0, 9.626214741941014, 7.715664713337986, 5.9846163634394625, 4.613890405874283, 7.342536084438347, 3.6499393385154706, 3.1578932999811724, 2.4320922242544327, 3.5845480647677452, 2.768349679616211, 1.5637700474394147, 0.6799101840789417, 0.0), # 106
(9.538995586568856, 7.438548060754901, 7.802168281321446, 8.282180127818036, 7.155879663250759, 3.3966911421023225, 3.1431378408702306, 2.5980256439567144, 3.6640090496875475, 1.532158971462385, 1.1920772146415421, 0.6992885190800504, 0.0, 9.606655628429355, 7.692173709880553, 5.96038607320771, 4.596476914387154, 7.328018099375095, 3.6372359015394005, 3.1431378408702306, 2.426207958644516, 3.5779398316253794, 2.760726709272679, 1.5604336562642893, 0.6762316418868093, 0.0), # 107
(9.508652173913044, 7.398209677419356, 7.785364583333334, 8.259279211956523, 7.1426470588235285, 3.3885833333333335, 3.1284033613445374, 2.589166666666667, 3.656791666666667, 1.5263411764705888, 1.1872898724082936, 0.6971491228070177, 0.0, 9.587109375, 7.668640350877193, 5.936449362041468, 4.579023529411765, 7.313583333333334, 3.624833333333334, 3.1284033613445374, 2.4204166666666667, 3.5713235294117642, 2.7530930706521746, 1.557072916666667, 0.6725645161290325, 0.0), # 108
(9.478489115524543, 7.358015858002567, 7.768442572588021, 8.23636199174718, 7.129414454396299, 3.3806227582177515, 3.113695163936631, 2.580527168114617, 3.6496222946197223, 1.5205102127545123, 1.1825684525567568, 0.6950068386558532, 0.0, 9.567601701817559, 7.645075225214384, 5.9128422627837836, 4.561530638263536, 7.299244589239445, 3.612738035360464, 3.113695163936631, 2.4147305415841083, 3.5647072271981495, 2.7454539972490606, 1.5536885145176043, 0.668910532545688, 0.0), # 109
(9.448552215661715, 7.317985585645383, 7.751405678440788, 8.213444167673108, 7.116197988111569, 3.3728264873240867, 3.0990185511790447, 2.5721117207742723, 3.6425073350099066, 1.5146662094192962, 1.177920161655542, 0.6928626292526012, 0.0, 9.54815832904664, 7.621488921778612, 5.8896008082777085, 4.543998628257887, 7.285014670019813, 3.600956409083981, 3.0990185511790447, 2.409161776660062, 3.5580989940557846, 2.737814722557703, 1.5502811356881578, 0.6652714168768531, 0.0), # 110
(9.41888727858293, 7.278137843488651, 7.7342573302469155, 8.190541440217391, 7.103013798111837, 3.365211591220851, 3.0843788256043156, 2.5639248971193416, 3.635453189300412, 1.5088092955700803, 1.173352206273259, 0.6907174572233054, 0.0, 9.528804976851852, 7.597892029456357, 5.866761031366295, 4.526427886710239, 7.270906378600824, 3.5894948559670783, 3.0843788256043156, 2.4037225651577505, 3.5515068990559184, 2.7301804800724643, 1.546851466049383, 0.6616488948626047, 0.0), # 111
(9.38954010854655, 7.238491614673214, 7.717000957361684, 8.167669509863124, 7.089878022539605, 3.357795140476554, 3.069781289744979, 2.5559712696235333, 3.628466258954427, 1.5029396003120044, 1.1688717929785184, 0.6885722851940093, 0.0, 9.509567365397805, 7.574295137134101, 5.844358964892591, 4.5088188009360115, 7.256932517908854, 3.5783597774729463, 3.069781289744979, 2.3984251003403956, 3.5449390112698027, 2.7225565032877084, 1.543400191472337, 0.6580446922430195, 0.0), # 112
(9.360504223703044, 7.1991320672204555, 7.699681523543391, 8.14487541186903, 7.076783786782469, 3.3505906987084666, 3.0552629818283847, 2.548271903658586, 3.6215709370862066, 1.4970761841531826, 1.1644873176921446, 0.6864327447087024, 0.0, 9.490443900843221, 7.550760191795725, 5.8224365884607225, 4.491228552459547, 7.243141874172413, 3.5675806651220205, 3.0552629818283847, 2.3932790705060474, 3.5383918933912346, 2.7149584706230105, 1.5399363047086783, 0.654466551565496, 0.0), # 113
(9.331480897900065, 7.16044741823174, 7.682538062518016, 8.122342065958001, 7.063595569710884, 3.343581854975776, 3.0410091042052896, 2.5409213581271333, 3.6148730119043533, 1.491328791978196, 1.1602073895188663, 0.684326014342748, 0.0, 9.471275414160035, 7.5275861577702265, 5.801036947594331, 4.473986375934587, 7.229746023808707, 3.557289901377987, 3.0410091042052896, 2.3882727535541255, 3.531797784855442, 2.7074473553193346, 1.5365076125036032, 0.6509497652937947, 0.0), # 114
(9.302384903003995, 7.122451598792792, 7.665580777256098, 8.100063378886334, 7.050271785259067, 3.3367503822909463, 3.027029825095781, 2.533917772616129, 3.6083749928895963, 1.4857063319970194, 1.1560257519045158, 0.6822531318799043, 0.0, 9.452006631660376, 7.5047844506789465, 5.7801287595225785, 4.457118995991058, 7.216749985779193, 3.5474848816625806, 3.027029825095781, 2.3833931302078186, 3.5251358926295335, 2.700021126295445, 1.5331161554512198, 0.647495599890254, 0.0), # 115
(9.273179873237634, 7.0850892578507265, 7.648776824986561, 8.077999612699802, 7.036792350922519, 3.330080178417474, 3.0133024087639466, 2.5272417970412473, 3.6020604464092765, 1.480198339612387, 1.1519343218785802, 0.6802102664572789, 0.0, 9.43260725975589, 7.482312931030067, 5.7596716093929015, 4.44059501883716, 7.204120892818553, 3.5381385158577463, 3.0133024087639466, 2.3786286988696244, 3.5183961754612594, 2.6926665375666015, 1.5297553649973124, 0.6440990234409752, 0.0), # 116
(9.243829442823772, 7.04830504435266, 7.632093362938321, 8.056111029444182, 7.02313718419674, 3.323555141118853, 2.9998041194738763, 2.5208740813181603, 3.5959129388307343, 1.4747943502270324, 1.1479250164705472, 0.6781935872119792, 0.0, 9.413047004858225, 7.46012945933177, 5.739625082352736, 4.424383050681096, 7.1918258776614685, 3.5292237138454245, 2.9998041194738763, 2.3739679579420376, 3.51156859209837, 2.6853703431480613, 1.5264186725876645, 0.6407550040320601, 0.0), # 117
(9.214297245985211, 7.0120436072457135, 7.615497548340306, 8.03435789116525, 7.009286202577227, 3.317159168158581, 2.9865122214896576, 2.51479527536254, 3.5899160365213114, 1.46948389924369, 1.143989752709904, 0.6761992632811126, 0.0, 9.393295573379024, 7.438191896092237, 5.71994876354952, 4.40845169773107, 7.179832073042623, 3.5207133855075567, 2.9865122214896576, 2.369399405827558, 3.5046431012886137, 2.678119297055084, 1.5230995096680613, 0.6374585097496104, 0.0), # 118
(9.184546916944742, 6.976249595477001, 7.598956538421437, 8.012700459908778, 6.99521932355948, 3.3108761573001524, 2.973403979075378, 2.5089860290900607, 3.5840533058483475, 1.4642565220650932, 1.1401204476261382, 0.6742234638017862, 0.0, 9.373322671729932, 7.416458101819647, 5.70060223813069, 4.392769566195279, 7.168106611696695, 3.5125804407260848, 2.973403979075378, 2.3649115409286803, 3.49760966177974, 2.670900153302927, 1.5197913076842873, 0.6342045086797276, 0.0), # 119
(9.154542089925162, 6.940867657993644, 7.582437490410635, 7.991098997720545, 6.980916464638998, 3.304690006307063, 2.9604566564951265, 2.5034269924163928, 3.578308313179186, 1.4591017540939766, 1.136309018248736, 0.6722623579111081, 0.0, 9.353098006322597, 7.394885937022188, 5.68154509124368, 4.377305262281929, 7.156616626358372, 3.50479778938295, 2.9604566564951265, 2.360492861647902, 3.490458232319499, 2.663699665906849, 1.516487498082127, 0.6309879689085133, 0.0), # 120
(9.124246399149268, 6.90584244374276, 7.565907561536823, 7.969513766646325, 6.966357543311279, 3.29858461294281, 2.94764751801299, 2.4980988152572112, 3.572664624881166, 1.4540091307330743, 1.1325473816071863, 0.6703121147461852, 0.0, 9.33259128356866, 7.373433262208036, 5.662736908035931, 4.362027392199222, 7.145329249762332, 3.497338341360096, 2.94764751801299, 2.356131866387721, 3.4831787716556395, 2.656504588882109, 1.5131815123073646, 0.6278038585220692, 0.0), # 121
(9.093623478839854, 6.871118601671464, 7.549333909028926, 7.947905028731892, 6.951522477071823, 3.292543874970886, 2.9349538278930587, 2.492982147528187, 3.5671058073216297, 1.4489681873851195, 1.1288274547309753, 0.6683689034441251, 0.0, 9.31177220987977, 7.352057937885375, 5.644137273654876, 4.346904562155357, 7.1342116146432595, 3.490175006539462, 2.9349538278930587, 2.351817053550633, 3.4757612385359113, 2.6493016762439643, 1.5098667818057854, 0.6246471456064968, 0.0), # 122
(9.062636963219719, 6.836640780726876, 7.532683690115864, 7.92623304602302, 6.936391183416127, 3.28655169015479, 2.9223528503994194, 2.4880576391449933, 3.5616154268679177, 1.443968459452847, 1.1251411546495909, 0.6664288931420351, 0.0, 9.290610491667572, 7.330717824562385, 5.625705773247954, 4.33190537835854, 7.123230853735835, 3.4832806948029904, 2.9223528503994194, 2.3475369215391355, 3.4681955917080636, 2.642077682007674, 1.5065367380231727, 0.621512798247898, 0.0), # 123
(9.031250486511654, 6.802353629856113, 7.515924062026559, 7.90445808056549, 6.920943579839691, 3.2805919562580144, 2.9098218497961597, 2.483305940023303, 3.5561770498873715, 1.4389994823389904, 1.1214803983925201, 0.664488252977023, 0.0, 9.269075835343711, 7.309370782747252, 5.6074019919625995, 4.316998447016971, 7.112354099774743, 3.476628316032624, 2.9098218497961597, 2.3432799687557244, 3.4604717899198456, 2.634819360188497, 1.5031848124053118, 0.618395784532374, 0.0), # 124
(8.999427682938459, 6.768201798006293, 7.499022181989936, 7.88254039440507, 6.905159583838015, 3.274648571044058, 2.8973380903473696, 2.478707700078788, 3.5507742427473308, 1.4340507914462837, 1.1178371029892504, 0.6625431520861957, 0.0, 9.247137947319828, 7.2879746729481525, 5.5891855149462515, 4.30215237433885, 7.1015484854946616, 3.470190780110303, 2.8973380903473696, 2.3390346936028985, 3.4525797919190073, 2.6275134648016905, 1.4998044363979874, 0.6152910725460268, 0.0), # 125
(8.967132186722928, 6.734129934124536, 7.481945207234916, 7.8604402495875405, 6.889019112906595, 3.2687054322764144, 2.884878836317135, 2.474243569227122, 3.545390571815139, 1.4291119221774609, 1.1142031854692689, 0.6605897596066612, 0.0, 9.224766534007578, 7.266487355673273, 5.571015927346345, 4.287335766532382, 7.090781143630278, 3.463940996917971, 2.884878836317135, 2.334789594483153, 3.4445095564532977, 2.620146749862514, 1.4963890414469831, 0.6121936303749579, 0.0), # 126
(8.93432763208786, 6.7000826871579555, 7.464660294990421, 7.838117908158674, 6.8725020845409315, 3.26274643771858, 2.872421351969547, 2.469894197383977, 3.5400096034581354, 1.4241724099352562, 1.1105705628620632, 0.6586242446755264, 0.0, 9.201931301818599, 7.244866691430789, 5.552852814310316, 4.272517229805768, 7.080019206916271, 3.457851876337568, 2.872421351969547, 2.3305331697989855, 3.4362510422704657, 2.612705969386225, 1.4929320589980841, 0.6090984261052688, 0.0), # 127
(8.900977653256046, 6.666004706053673, 7.447134602485375, 7.815533632164248, 6.855588416236526, 3.2567554851340508, 2.859942901568691, 2.465640234465026, 3.534614904043661, 1.4192217901224033, 1.1069311521971208, 0.6566427764298991, 0.0, 9.178601957164537, 7.223070540728888, 5.534655760985604, 4.257665370367209, 7.069229808087322, 3.4518963282510366, 2.859942901568691, 2.3262539179528936, 3.427794208118263, 2.6051778773880834, 1.4894269204970751, 0.6060004278230613, 0.0), # 128
(8.867045884450281, 6.631840639758805, 7.4293352869486995, 7.792647683650037, 6.838258025488874, 3.250716472286322, 2.8474207493786565, 2.4614623303859418, 3.529190039939058, 1.4142495981416365, 1.1032768705039286, 0.6546415240068865, 0.0, 9.154748206457038, 7.20105676407575, 5.516384352519642, 4.242748794424909, 7.058380079878116, 3.4460472625403185, 2.8474207493786565, 2.321940337347373, 3.419129012744437, 2.597549227883346, 1.4858670573897401, 0.6028946036144368, 0.0), # 129
(8.832495959893366, 6.5975351372204685, 7.411229505609316, 7.769420324661814, 6.820490829793475, 3.2446132969388883, 2.8348321596635313, 2.457341135062396, 3.5237185775116666, 1.4092453693956895, 1.0995996348119743, 0.6526166565435961, 0.0, 9.130339756107748, 7.178783221979556, 5.4979981740598705, 4.2277361081870675, 7.047437155023333, 3.4402775890873545, 2.8348321596635313, 2.3175809263849203, 3.4102454148967376, 2.589806774887272, 1.4822459011218634, 0.5997759215654973, 0.0), # 130
(8.797291513808094, 6.563032847385783, 7.392784415696151, 7.7458118172453565, 6.802266746645829, 3.238429856855247, 2.8221543966874045, 2.4532572984100627, 3.5181840831288285, 1.4041986392872965, 1.0958913621507447, 0.6505643431771354, 0.0, 9.105346312528312, 7.156207774948489, 5.479456810753724, 4.212595917861889, 7.036368166257657, 3.4345602177740875, 2.8221543966874045, 2.3131641834680337, 3.4011333733229145, 2.5819372724151193, 1.4785568831392302, 0.596639349762344, 0.0), # 131
(8.76139618041726, 6.528278419201865, 7.373967174438122, 7.72178242344644, 6.783565693541435, 3.2321500497988933, 2.8093647247143627, 2.449191470344614, 3.5125701231578845, 1.3990989432191914, 1.0921439695497275, 0.6484807530446118, 0.0, 9.079737582130376, 7.13328828349073, 5.460719847748638, 4.1972968296575734, 7.025140246315769, 3.4288680584824593, 2.8093647247143627, 2.3086786069992096, 3.3917828467707176, 2.573927474482147, 1.4747934348876244, 0.5934798562910787, 0.0), # 132
(8.724773593943663, 6.493216501615832, 7.354744939064153, 7.697292405310838, 6.764367587975791, 3.225757773533322, 2.7964404080084946, 2.445124300781722, 3.5068602639661752, 1.3939358165941083, 1.0883493740384103, 0.6463620552831327, 0.0, 9.053483271325586, 7.10998260811446, 5.44174687019205, 4.181807449782324, 7.0137205279323505, 3.4231740210944106, 2.7964404080084946, 2.3041126953809443, 3.3821837939878954, 2.5657641351036133, 1.4709489878128308, 0.590292409237803, 0.0), # 133
(8.687387388610095, 6.457791743574804, 7.33508486680317, 7.672302024884328, 6.7446523474443945, 3.2192369258220297, 2.7833587108338893, 2.44103643963706, 3.5010380719210428, 1.388698794814781, 1.0844994926462799, 0.6442044190298056, 0.0, 9.026553086525583, 7.0862486093278605, 5.422497463231399, 4.166096384444343, 7.0020761438420855, 3.417451015491884, 2.7833587108338893, 2.2994549470157355, 3.3723261737221972, 2.557434008294776, 1.4670169733606342, 0.5870719766886187, 0.0), # 134
(8.649201198639354, 6.421948794025897, 7.314954114884091, 7.646771544212684, 6.724399889442747, 3.212571404428512, 2.770096897454634, 2.4369085368263, 3.4950871133898262, 1.3833774132839443, 1.0805862424028239, 0.6420040134217377, 0.0, 8.99891673414202, 7.0620441476391145, 5.402931212014119, 4.150132239851832, 6.9901742267796525, 3.41167195155682, 2.770096897454634, 2.2946938603060802, 3.3621999447213735, 2.548923848070895, 1.4629908229768183, 0.583813526729627, 0.0), # 135
(8.610178658254235, 6.385632301916229, 7.294319840535841, 7.62066122534168, 6.703590131466344, 3.205745107116265, 2.7566322321348173, 2.4327212422651154, 3.4889909547398688, 1.3779612074043308, 1.0766015403375297, 0.6397570075960368, 0.0, 8.970543920586536, 7.037327083556404, 5.383007701687648, 4.133883622212991, 6.9779819094797375, 3.4058097391711617, 2.7566322321348173, 2.289817933654475, 3.351795065733172, 2.540220408447227, 1.4588639681071682, 0.58051202744693, 0.0), # 136
(8.570283401677534, 6.348786916192918, 7.273149200987342, 7.593931330317094, 6.682202991010689, 3.1987419316487826, 2.7429419791385277, 2.428455205869179, 3.4827331623385107, 1.3724397125786756, 1.0725373034798844, 0.63745957068981, 0.0, 8.941404352270776, 7.012055277587909, 5.362686517399421, 4.117319137736026, 6.965466324677021, 3.3998372882168506, 2.7429419791385277, 2.284815665463416, 3.3411014955053444, 2.5313104434390317, 1.4546298401974684, 0.577162446926629, 0.0), # 137
(8.529479063132047, 6.311357285803083, 7.251409353467515, 7.566542121184698, 6.660218385571278, 3.1915457757895624, 2.729003402729852, 2.4240910775541624, 3.4762973025530934, 1.3668024642097119, 1.0683854488593754, 0.6351078718401649, 0.0, 8.91146773560639, 6.986186590241813, 5.341927244296877, 4.100407392629135, 6.952594605106187, 3.3937275085758274, 2.729003402729852, 2.2796755541354017, 3.330109192785639, 2.5221807070615663, 1.450281870693503, 0.5737597532548258, 0.0), # 138
(8.487729276840568, 6.273288059693839, 7.229067455205284, 7.538453859990269, 6.63761623264361, 3.184140537302099, 2.7147937671728797, 2.4196095072357395, 3.469666941750957, 1.3610389977001744, 1.0641378935054902, 0.6326980801842089, 0.0, 8.880703777005019, 6.959678882026297, 5.32068946752745, 4.083116993100523, 6.939333883501914, 3.3874533101300353, 2.7147937671728797, 2.274386098072928, 3.318808116321805, 2.51281795333009, 1.4458134910410567, 0.5702989145176218, 0.0), # 139
(8.444997677025897, 6.234523886812306, 7.206090663429573, 7.509626808779583, 6.614376449723186, 3.176510113949888, 2.7002903367316984, 2.4149911448295818, 3.462825646299444, 1.3551388484527966, 1.0597865544477159, 0.6302263648590494, 0.0, 8.849082182878314, 6.932490013449542, 5.298932772238579, 4.0654165453583895, 6.925651292598888, 3.3809876027614147, 2.7002903367316984, 2.2689357956784915, 3.307188224861593, 2.5032089362598615, 1.4412181326859146, 0.5667748988011189, 0.0), # 140
(8.40124789791083, 6.195009416105602, 7.1824461353693, 7.480021229598415, 6.590478954305501, 3.1686384034964257, 2.6854703756703975, 2.4102166402513627, 3.455756982565893, 1.349091551870313, 1.0553233487155398, 0.6276888950017938, 0.0, 8.816572659637913, 6.904577845019731, 5.276616743577699, 4.047274655610939, 6.911513965131786, 3.3743032963519077, 2.6854703756703975, 2.26331314535459, 3.2952394771527507, 2.4933404098661387, 1.4364892270738603, 0.5631826741914184, 0.0), # 141
(8.356443573718156, 6.154689296520844, 7.158101028253392, 7.44959738449254, 6.565903663886058, 3.1605093037052074, 2.670311148253063, 2.4052666434167547, 3.448444516917647, 1.3428866433554572, 1.0507401933384497, 0.6250818397495496, 0.0, 8.783144913695466, 6.875900237245045, 5.253700966692247, 4.028659930066371, 6.896889033835294, 3.3673733007834565, 2.670311148253063, 2.2575066455037196, 3.282951831943029, 2.4831991281641805, 1.4316202056506786, 0.5595172087746222, 0.0), # 142
(8.310548338670674, 6.113508177005149, 7.133022499310772, 7.418315535507731, 6.540630495960352, 3.152106712339729, 2.6547899187437842, 2.4001218042414303, 3.4408718157220486, 1.3365136583109634, 1.0460290053459322, 0.6224013682394242, 0.0, 8.748768651462617, 6.846415050633665, 5.230145026729661, 4.009540974932889, 6.881743631444097, 3.360170525938002, 2.6547899187437842, 2.251504794528378, 3.270315247980176, 2.472771845169244, 1.4266044998621543, 0.5557734706368318, 0.0), # 143
(8.263525826991184, 6.071410706505636, 7.107177705770357, 7.386135944689768, 6.514639368023886, 3.1434145271634857, 2.6388839514066493, 2.3947627726410623, 3.4330224453464364, 1.3299621321395652, 1.0411817017674754, 0.619643649608525, 0.0, 8.713413579351014, 6.816080145693774, 5.205908508837376, 3.9898863964186946, 6.866044890692873, 3.3526678816974873, 2.6388839514066493, 2.245296090831061, 3.257319684011943, 2.4620453148965895, 1.4214355411540713, 0.5519464278641489, 0.0), # 144
(8.215339672902477, 6.0283415339694235, 7.080533804861075, 7.353018874084421, 6.487910197572155, 3.134416645939974, 2.6225705105057466, 2.3891701985313234, 3.424879972158151, 1.3232216002439972, 1.036190199632566, 0.6168048529939595, 0.0, 8.6770494037723, 6.784853382933553, 5.180950998162829, 3.969664800731991, 6.849759944316302, 3.344838277943853, 2.6225705105057466, 2.238869032814267, 3.2439550987860777, 2.451006291361474, 1.4161067609722149, 0.548031048542675, 0.0), # 145
(8.16595351062735, 5.984245308343629, 7.053057953811847, 7.318924585737469, 6.460422902100661, 3.1250969664326886, 2.605826860305165, 2.3833247318278863, 3.4164279625245353, 1.3162815980269928, 1.0310464159706916, 0.6138811475328351, 0.0, 8.639645831138118, 6.7526926228611845, 5.155232079853457, 3.948844794080978, 6.832855925049071, 3.3366546245590407, 2.605826860305165, 2.2322121188804918, 3.2302114510503306, 2.439641528579157, 1.4106115907623695, 0.5440223007585119, 0.0), # 146
(8.1153309743886, 5.93906667857537, 7.024717309851591, 7.283813341694685, 6.4321573991049, 3.1154393864051255, 2.5886302650689905, 2.3772070224464232, 3.40764998281293, 1.3091316608912866, 1.0257422678113395, 0.6108687023622593, 0.0, 8.601172567860118, 6.719555725984851, 5.1287113390566965, 3.9273949826738592, 6.81529996562586, 3.3280898314249923, 2.5886302650689905, 2.2253138474322327, 3.21607869955245, 2.4279377805648954, 1.4049434619703185, 0.5399151525977609, 0.0), # 147
(8.063435698409021, 5.892750293611764, 6.9954790302092364, 7.247645404001847, 6.403093606080374, 3.105427803620781, 2.5709579890613132, 2.3707977203026074, 3.398529599390676, 1.301761324239612, 1.0202696721839972, 0.6077636866193392, 0.0, 8.561599320349941, 6.68540055281273, 5.101348360919985, 3.905283972718835, 6.797059198781352, 3.3191168084236504, 2.5709579890613132, 2.2181627168719866, 3.201546803040187, 2.4158818013339496, 1.3990958060418472, 0.535704572146524, 0.0), # 148
(8.010231316911412, 5.845240802399927, 6.965310272113703, 7.210381034704727, 6.37321144052258, 3.0950461158431497, 2.5527872965462204, 2.3640774753121114, 3.3890503786251127, 1.2941601234747035, 1.0146205461181517, 0.6045622694411826, 0.0, 8.520895795019237, 6.650184963853008, 5.073102730590758, 3.88248037042411, 6.778100757250225, 3.3097084654369557, 2.5527872965462204, 2.21074722560225, 3.18660572026129, 2.403460344901576, 1.3930620544227408, 0.5313855274909026, 0.0), # 149
(7.955681464118564, 5.796482853886981, 6.934178192793912, 7.171980495849104, 6.342490819927017, 3.0842782208357287, 2.5340954517878003, 2.3570269373906068, 3.3791958868835836, 1.2863175939992944, 1.0087868066432906, 0.601260619964897, 0.0, 8.479031698279647, 6.6138668196138655, 5.043934033216452, 3.8589527819978824, 6.758391773767167, 3.2998377123468496, 2.5340954517878003, 2.2030558720255207, 3.1712454099635083, 2.390660165283035, 1.3868356385587826, 0.5269529867169983, 0.0), # 150
(7.899749774253275, 5.746421097020041, 6.902049949478785, 7.132404049480748, 6.310911661789184, 3.0731080163620113, 2.5148597190501416, 2.3496267564537683, 3.3689496905334293, 1.2782232712161197, 1.002760370788901, 0.5978549073275894, 0.0, 8.435976736542818, 6.576403980603482, 5.013801853944504, 3.8346698136483583, 6.737899381066859, 3.2894774590352753, 2.5148597190501416, 2.1950771545442938, 3.155455830894592, 2.377468016493583, 1.3804099898957571, 0.5224019179109128, 0.0), # 151
(7.842399881538343, 5.6950001807462245, 6.868892699397251, 7.091611957645439, 6.278453883604579, 3.0615194001854955, 2.4950573625973322, 2.3418575824172674, 3.3582953559419897, 1.2698666905279126, 0.9965331555844703, 0.5943413006663675, 0.0, 8.391700616220398, 6.537754307330042, 4.982665777922351, 3.809600071583737, 6.716590711883979, 3.2786006153841742, 2.4950573625973322, 2.1867995715610684, 3.1392269418022893, 2.36387065254848, 1.3737785398794504, 0.5177272891587478, 0.0), # 152
(7.78359542019656, 5.642164754012652, 6.834673599778224, 7.049564482388949, 6.245097402868703, 3.049496270069676, 2.4746656466934596, 2.333700065196776, 3.3472164494766075, 1.2612373873374074, 0.9900970780594861, 0.5907159691183387, 0.0, 8.346173043724027, 6.497875660301725, 4.95048539029743, 3.783712162012222, 6.694432898953215, 3.2671800912754865, 2.4746656466934596, 2.17821162147834, 3.1225487014343516, 2.3498548274629836, 1.3669347199556448, 0.5129240685466048, 0.0), # 153
(7.723300024450729, 5.587859465766439, 6.7993598078506325, 7.006221885757057, 6.210822137077053, 3.0370225237780484, 2.453661835602614, 2.325134854707968, 3.3356965375046217, 1.2523248970473384, 0.9834440552434354, 0.5869750818206104, 0.0, 8.299363725465357, 6.456725900026714, 4.917220276217177, 3.7569746911420143, 6.671393075009243, 3.2551887965911552, 2.453661835602614, 2.169301802698606, 3.1054110685385266, 2.335407295252353, 1.3598719615701265, 0.5079872241605854, 0.0), # 154
(7.6614773285236355, 5.532028964954703, 6.762918480843396, 6.961544429795533, 6.175608003725131, 3.0240820590741087, 2.4320231935888805, 2.316142600866515, 3.323719186393376, 1.2431187550604388, 0.9765660041658056, 0.5831148079102902, 0.0, 8.251242367856026, 6.414262887013191, 4.882830020829028, 3.7293562651813157, 6.647438372786752, 3.242599641213121, 2.4320231935888805, 2.160058613624363, 3.0878040018625654, 2.320514809931845, 1.3525836961686795, 0.5029117240867913, 0.0), # 155
(7.598090966638081, 5.474617900524564, 6.725316775985439, 6.915492376550157, 6.139434920308432, 3.0106587737213526, 2.40972698491635, 2.3067039535880913, 3.3112679625102084, 1.2336084967794434, 0.9694548418560842, 0.5791313165244852, 0.0, 8.201778677307685, 6.370444481769337, 4.84727420928042, 3.7008254903383295, 6.622535925020417, 3.2293855350233276, 2.40972698491635, 2.150470552658109, 3.069717460154216, 2.3051641255167192, 1.3450633551970879, 0.49769253641132405, 0.0), # 156
(7.533104573016862, 5.415570921423138, 6.686521850505682, 6.868025988066703, 6.102282804322456, 2.9967365654832747, 2.3867504738491094, 2.2967995627883675, 3.2983264322224626, 1.2237836576070855, 0.9621024853437583, 0.5750207768003032, 0.0, 8.150942360231976, 6.325228544803333, 4.810512426718791, 3.671350972821256, 6.596652864444925, 3.2155193879037145, 2.3867504738491094, 2.140526118202339, 3.051141402161228, 2.2893419960222348, 1.3373043701011365, 0.4923246292202853, 0.0), # 157
(7.464680946405239, 5.353748694041236, 6.644659961585297, 6.817327186238432, 6.062454070580665, 2.9814309445183143, 2.3625533604639286, 2.285748730145572, 3.2838873638663655, 1.213341479072786, 0.9542659587564906, 0.570633297016195, 0.0, 8.096485859415345, 6.276966267178143, 4.771329793782452, 3.640024437218358, 6.567774727732731, 3.200048222203801, 2.3625533604639286, 2.129593531798796, 3.0312270352903323, 2.2724423954128112, 1.3289319923170593, 0.48670442673102154, 0.0), # 158
(7.382286766978402, 5.282809876299521, 6.58894818200249, 6.7529828690913405, 6.010127539854418, 2.95965229467081, 2.334106381692858, 2.2696723053184926, 3.2621424204073812, 1.2005702485246865, 0.9445694892698324, 0.5651135436402591, 0.0, 8.025427646920194, 6.216248980042849, 4.722847446349162, 3.601710745574059, 6.5242848408147625, 3.17754122744589, 2.334106381692858, 2.114037353336293, 3.005063769927209, 2.250994289697114, 1.3177896364004982, 0.4802554432999565, 0.0), # 159
(7.284872094904309, 5.202172001162321, 6.51826746496324, 6.673933132806645, 5.94428008756453, 2.9308657560278157, 2.301121874191892, 2.248166328969728, 3.2324750757428835, 1.1853014129657236, 0.9328765847682567, 0.5583751624073207, 0.0, 7.93642060889358, 6.142126786480525, 4.664382923841283, 3.55590423889717, 6.464950151485767, 3.147432860557619, 2.301121874191892, 2.0934755400198686, 2.972140043782265, 2.2246443776022153, 1.3036534929926482, 0.47292472737839286, 0.0), # 160
(7.17322205458596, 5.11236079574043, 6.4333724765919245, 6.5809293778175455, 5.865595416188075, 2.895420057582683, 2.263840723003438, 2.2215002221290754, 3.1952765889996724, 1.1676645482927346, 0.9192902757666179, 0.5504806224089643, 0.0, 7.830374044819097, 6.055286846498606, 4.596451378833089, 3.5029936448782033, 6.390553177999345, 3.1101003109807053, 2.263840723003438, 2.0681571839876307, 2.9327977080940375, 2.1936431259391824, 1.2866744953183848, 0.46476007234003913, 0.0), # 161
(7.048121770426357, 5.013901987144635, 6.335017883012913, 6.474723004557244, 5.7747572282021356, 2.853663928328766, 2.2225038131699044, 2.1899434058263343, 3.150938219304545, 1.147789230402558, 0.9039135927797701, 0.5414923927367745, 0.0, 7.708197254180333, 5.956416320104519, 4.519567963898851, 3.4433676912076736, 6.30187643860909, 3.065920768156868, 2.2225038131699044, 2.03833137737769, 2.8873786141010678, 2.158241001519082, 1.2670035766025827, 0.4558092715586033, 0.0), # 162
(6.9103563668284975, 4.90732130248573, 6.223958350350585, 6.35606541345895, 5.672449226083792, 2.8059460972594175, 2.1773520297337003, 2.153765301091302, 3.0998512257843016, 1.1258050351920315, 0.8868495663225682, 0.5314729424823361, 0.0, 7.570799536460879, 5.846202367305696, 4.43424783161284, 3.3774151055760937, 6.199702451568603, 3.015271421527823, 2.1773520297337003, 2.0042472123281554, 2.836224613041896, 2.118688471152984, 1.2447916700701172, 0.4461201184077937, 0.0), # 163
(6.760710968195384, 4.793144468874502, 6.100948544729314, 6.225708004955863, 5.559355112310126, 2.752615293367992, 2.128626257737233, 2.113235328953779, 3.0424068675657407, 1.1018415385579923, 0.8682012269098661, 0.5204847407372336, 0.0, 7.419090191144328, 5.725332148109569, 4.34100613454933, 3.305524615673976, 6.0848137351314815, 2.9585294605352903, 2.128626257737233, 1.9661537809771372, 2.779677556155063, 2.075236001651955, 1.2201897089458629, 0.43574040626131844, 0.0), # 164
(6.599970698930017, 4.671897213421746, 5.966743132273474, 6.084402179481189, 5.436158589358215, 2.694020245647842, 2.076567382222911, 2.068622910443561, 2.9789964037756596, 1.0760283163972786, 0.8480716050565187, 0.5085902565930517, 0.0, 7.25397851771427, 5.594492822523568, 4.2403580252825925, 3.2280849491918353, 5.957992807551319, 2.8960720746209856, 2.076567382222911, 1.9243001754627442, 2.7180792946791077, 2.0281340598270634, 1.1933486264546949, 0.42471792849288603, 0.0), # 165
(6.428920683435397, 4.54410526323825, 5.82209677910744, 5.932899337468126, 5.3035433597051425, 2.630509683092322, 2.021416288233143, 2.020197466590449, 2.9100110935408576, 1.0484949446067282, 0.8265637312773799, 0.49585195914137514, 0.0, 7.0763738156542955, 5.454371550555126, 4.1328186563869, 3.145484833820184, 5.820022187081715, 2.8282764532266285, 2.021416288233143, 1.8789354879230868, 2.6517716798525712, 1.9776331124893758, 1.1644193558214881, 0.41310047847620457, 0.0), # 166
(6.248346046114523, 4.410294345434805, 5.667764151355587, 5.771950879349882, 5.1621931258279865, 2.562432334694784, 1.9634138608103373, 1.9682284184242402, 2.835842195988133, 1.0193709990831787, 0.8037806360873045, 0.48233231747378824, 0.0, 6.887185384447996, 5.30565549221167, 4.0189031804365225, 3.058112997249536, 5.671684391976266, 2.755519785793936, 1.9634138608103373, 1.8303088104962744, 2.5810965629139933, 1.9239836264499612, 1.1335528302711175, 0.4009358495849823, 0.0), # 167
(6.059031911370395, 4.270990187122201, 5.50449991514229, 5.60230820555966, 5.012791590203827, 2.490136929448583, 1.902800984996902, 1.9129851869747332, 2.7568809702442847, 0.9887860557234682, 0.7798253500011468, 0.468093800681876, 0.0, 6.6873225235789615, 5.149031807500635, 3.8991267500057343, 2.9663581671704042, 5.513761940488569, 2.6781792617646265, 1.902800984996902, 1.7786692353204163, 2.5063957951019136, 1.867436068519887, 1.100899983028458, 0.3882718351929274, 0.0), # 168
(5.861763403606015, 4.1267185154112305, 5.333058736591924, 5.4247227165306615, 4.856022455309747, 2.413972196347072, 1.8398185458352458, 1.8547371932717271, 2.6735186754361124, 0.9568696904244344, 0.7548009035337614, 0.45319887785722274, 0.0, 6.477694532530785, 4.985187656429449, 3.774004517668807, 2.8706090712733023, 5.347037350872225, 2.596632070580418, 1.8398185458352458, 1.724265854533623, 2.4280112276548733, 1.808240905510221, 1.066611747318385, 0.3751562286737483, 0.0), # 169
(5.657325647224384, 3.978005057412684, 5.154195281828863, 5.23994581269609, 4.692569423622822, 2.334286864383604, 1.7747074283677764, 1.7937538583450197, 2.5861465706904125, 0.9237514790829147, 0.7288103272000027, 0.4377100180914133, 0.0, 6.259210710787055, 4.814810199005545, 3.6440516360000137, 2.7712544372487433, 5.172293141380825, 2.5112554016830275, 1.7747074283677764, 1.6673477602740028, 2.346284711811411, 1.7466486042320304, 1.0308390563657726, 0.36163682340115316, 0.0), # 170
(5.4465037666285, 3.82537554023735, 4.968664216977482, 5.048728894489152, 4.523116197620137, 2.2514296625515327, 1.7077085176369027, 1.7303046032244096, 2.495155915133985, 0.8895609975957474, 0.7019566515147247, 0.4216896904760322, 0.0, 6.032780357831365, 4.638586595236354, 3.509783257573624, 2.6686829927872413, 4.99031183026797, 2.4224264445141737, 1.7077085176369027, 1.6081640446796661, 2.2615580988100685, 1.6829096314963843, 0.9937328433954964, 0.3477614127488501, 0.0), # 171
(5.230082886221365, 3.6693556909960217, 4.777220208162156, 4.851823362343048, 4.348346479778769, 2.1657493198442115, 1.6390626986850327, 1.664658848939696, 2.4009379678936282, 0.8544278218597702, 0.6743429069927823, 0.4052003641026643, 0.0, 5.799312773147303, 4.457204005129307, 3.3717145349639117, 2.56328346557931, 4.8018759357872565, 2.3305223885155746, 1.6390626986850327, 1.5469637998887225, 2.1741732398893845, 1.6172744541143496, 0.9554440416324312, 0.3335777900905475, 0.0), # 172
(5.00884813040598, 3.510471236799489, 4.58061792150726, 4.649980616690982, 4.168943972575801, 2.077594565254994, 1.5690108565545748, 1.5970860165206766, 2.303883988096141, 0.8184815277718206, 0.6460721241490297, 0.3883045080628938, 0.0, 5.5597172562184625, 4.271349588691831, 3.2303606207451483, 2.4554445833154612, 4.607767976192282, 2.235920423128947, 1.5690108565545748, 1.483996118039281, 2.0844719862879004, 1.5499935388969943, 0.916123584301452, 0.31913374879995354, 0.0), # 173
(4.783584623585344, 3.349247904758541, 4.3796120231371685, 4.443952057966156, 3.9855923784883105, 1.987314127777233, 1.4977938762879377, 1.5278555269971503, 2.204385234868321, 0.7818516912287369, 0.6172473334983214, 0.37106459144830567, 0.0, 5.314903106528433, 4.081710505931362, 3.0862366674916064, 2.34555507368621, 4.408770469736642, 2.1389977377960103, 1.4977938762879377, 1.4195100912694523, 1.9927961892441552, 1.4813173526553853, 0.8759224046274336, 0.3044770822507765, 0.0), # 174
(4.555077490162455, 3.18621142198397, 4.174957179176257, 4.2344890866017755, 3.7989753999933793, 1.8952567364042834, 1.425652642927529, 1.457236801398915, 2.102832967336968, 0.7446678881273562, 0.5879715655555117, 0.35354308335048457, 0.0, 5.0657796235608075, 3.8889739168553294, 2.939857827777558, 2.234003664382068, 4.205665934673936, 2.040131521958481, 1.425652642927529, 1.3537548117173452, 1.8994876999966896, 1.411496362200592, 0.8349914358352515, 0.28965558381672457, 0.0), # 175
(4.324111854540319, 3.0218875155865668, 3.9674080557488987, 4.0223431030310435, 3.609776739568087, 1.8017711201294973, 1.3528280415157574, 1.3854992607557703, 1.9996184446288805, 0.7070596943645169, 0.558347850835455, 0.33580245286101496, 0.0, 4.813256106799174, 3.693826981471164, 2.791739254177275, 2.1211790830935504, 3.999236889257761, 1.9396989650580787, 1.3528280415157574, 1.2869793715210696, 1.8048883697840434, 1.3407810343436815, 0.7934816111497798, 0.2747170468715061, 0.0), # 176
(4.0914728411219325, 2.856801912677122, 3.7577193189794698, 3.808265507687162, 3.4186800996895155, 1.7072060079462288, 1.2795609570950313, 1.3129123260975137, 1.8951329258708567, 0.6691566858370562, 0.528479219853006, 0.3179051690714816, 0.0, 4.5582418557271245, 3.496956859786297, 2.6423960992650297, 2.0074700575111684, 3.7902658517417134, 1.838077256536519, 1.2795609570950313, 1.2194328628187348, 1.7093400498447577, 1.269421835895721, 0.751543863795894, 0.25970926478882933, 0.0), # 177
(3.8579455743102966, 2.6914803403664256, 3.5466456349923448, 3.593007701003337, 3.226369182834742, 1.6119101288478317, 1.2060922747077587, 1.239745418453944, 1.7897676701896952, 0.6310884384418126, 0.49846870312301883, 0.299913701073469, 0.0, 4.301646169828252, 3.299050711808158, 2.4923435156150937, 1.8932653153254375, 3.5795353403793904, 1.7356435858355217, 1.2060922747077587, 1.1513643777484512, 1.613184591417371, 1.1976692336677792, 0.7093291269984691, 0.24468003094240237, 0.0), # 178
(0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0, 0.0), # 179
)
passenger_allighting_rate = (
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 0
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 1
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 2
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 3
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 4
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 5
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 6
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 7
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 8
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 9
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 10
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 11
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 12
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 13
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 14
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 15
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 16
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 17
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 18
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 19
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 20
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 21
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 22
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 23
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 24
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 25
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 26
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 27
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 28
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 29
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 30
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 31
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 32
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 33
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 34
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 35
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 36
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 37
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 38
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 39
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 40
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 41
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 42
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 43
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 44
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 45
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 46
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 47
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 48
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 49
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 50
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 51
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 52
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 53
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 54
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 55
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 56
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 57
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 58
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 59
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 60
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 61
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 62
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 63
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 64
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 65
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 66
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 67
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 68
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 69
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 70
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 71
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 72
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 73
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 74
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 75
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 76
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 77
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 78
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 79
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 80
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 81
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 82
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 83
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 84
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 85
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 86
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 87
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 88
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 89
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 90
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 91
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 92
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 93
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 94
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 95
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 96
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 97
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 98
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 99
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 100
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 101
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 102
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 103
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 104
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 105
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 106
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 107
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 108
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 109
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 110
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 111
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 112
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 113
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 114
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 115
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 116
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 117
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 118
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 119
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 120
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 121
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 122
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(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 153
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 154
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 155
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 156
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 157
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 158
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 159
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 160
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 161
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 162
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 163
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 164
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 165
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 166
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 167
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 168
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 169
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 170
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 171
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 172
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 173
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 174
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 175
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 176
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 177
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 178
(0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1, 0, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 0.07692307692307693, 1), # 179
)
"""
parameters for reproducibiliy. More information: https://numpy.org/doc/stable/reference/random/parallel.html
"""
#initial entropy
entropy = 8991598675325360468762009371570610170
#index for seed sequence child
child_seed_index = (
1, # 0
98, # 1
)
| 276.263102 | 494 | 0.76956 | 32,987 | 258,306 | 6.025737 | 0.217389 | 0.358604 | 0.344115 | 0.652007 | 0.376609 | 0.368057 | 0.364278 | 0.364138 | 0.364057 | 0.364057 | 0 | 0.849811 | 0.095755 | 258,306 | 934 | 495 | 276.558887 | 0.001194 | 0.015528 | 0 | 0.200873 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | false | 0.005459 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 1 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 1 | 0 | 0 | 0 | 0 | 1 | 1 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 6 |
3127ca68fbed48bb8071f535f286d3771588dddd | 1,282 | py | Python | 7term/TT/compiler/lab2/NodeType.py | nik-sergeson/bsuir-informatics-labs | 14805fb83b8e2324580b6253158565068595e804 | [
"Apache-2.0"
] | null | null | null | 7term/TT/compiler/lab2/NodeType.py | nik-sergeson/bsuir-informatics-labs | 14805fb83b8e2324580b6253158565068595e804 | [
"Apache-2.0"
] | null | null | null | 7term/TT/compiler/lab2/NodeType.py | nik-sergeson/bsuir-informatics-labs | 14805fb83b8e2324580b6253158565068595e804 | [
"Apache-2.0"
] | null | null | null | class NodeType(object):
PROGRAM, STATEMENT, CONST_DEF, EXPRESSION, CONST_ASSIGNMENT, VAR_DECL, IDENTIFIER_LIST, COLON, HEADING, \
SEQUENCE, ASSIGNMENT, RELATION_EQUAl, RELATION_NON_EQUAL, RELATION_LESS, RELATION_LESS_EQUAL, RELATION_GREATER, \
RELATION_GREATER_EQUAL, OPERATOR_UNARY_PLUS, OPERATOR_UNARY_MINUS, OPERATOR_PLUS, OPERATOR_MINUS, OPERATOR_OR, \
OPERATOR_MULTIPLY, OPERATOR_DIVISION, OPERATOR_DIV, OPERATOR_MOD, OPERATOR_AND, IF, WHILE, OPERATOR_NOT, \
COMPOSED = range(31)
_type_names = ["PROGRAM", "STATEMENT", "CONST_DEF", "EXPRESSION", "CONST_ASSIGNMENT", "VAR_DECL", "IDENTIFIER_LIST",
"COLON",
"HEADING", "SEQUENCE", "ASSIGNMENT", "RELATION_EQUAl", "RELATION_NON_EQUAL", "RELATION_LESS",
"RELATION_LESS_EQUAL",
"RELATION_GREATER", "RELATION_GREATER_EQUAL", "OPERATOR_UNARY_PLUS", "OPERATOR_UNARY_MINUS",
"OPERATOR_PLUS",
"OPERATOR_MINUS", "OPERATOR_OR", "OPERATOR_MULTIPLY", "OPERATOR_DIVISION", "OPERATOR_DIV",
"OPERATOR_MOD", "OPERATOR_AND",
"IF", "WHILE", "OPERATOR_NOT", "COMPOSED"]
@classmethod
def get_type_name(cls, tree_node):
return cls._type_names[tree_node.node_type]
| 61.047619 | 120 | 0.681747 | 137 | 1,282 | 5.934307 | 0.335766 | 0.095941 | 0.051661 | 0.059041 | 0.870849 | 0.870849 | 0.870849 | 0.870849 | 0.870849 | 0.870849 | 0 | 0.001965 | 0.205928 | 1,282 | 20 | 121 | 64.1 | 0.79666 | 0 | 0 | 0 | 0 | 0 | 0.296412 | 0.017161 | 0 | 0 | 0 | 0 | 0 | 1 | 0.055556 | false | 0 | 0 | 0.055556 | 0.222222 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
3149cb85efb586f38f0493664f767114cbae7e50 | 2,193 | py | Python | mag2exp/tests/test_magnetisation.py | ubermag/exsim | 35e7a88716a9ed2c9a34f4c93c628560a597b57f | [
"BSD-3-Clause"
] | null | null | null | mag2exp/tests/test_magnetisation.py | ubermag/exsim | 35e7a88716a9ed2c9a34f4c93c628560a597b57f | [
"BSD-3-Clause"
] | 6 | 2021-06-10T13:42:08.000Z | 2021-07-21T08:57:50.000Z | mag2exp/tests/test_magnetisation.py | ubermag/exsim | 35e7a88716a9ed2c9a34f4c93c628560a597b57f | [
"BSD-3-Clause"
] | null | null | null | # import pytest
import discretisedfield as df
import numpy as np
import micromagneticmodel as mm
import mag2exp
def test_magnetisation_analytical():
mesh = df.Mesh(p1=(0, 0, 0), p2=(6e-9, 4e-9, 1e-9),
cell=(2e-9, 1e-9, 0.5e-9))
field = df.Field(mesh, dim=3, value=(1, 1, 1))
mag = mag2exp.magnetometry.magnetisation(field)
assert np.isclose(mag, 1).all()
def test_torque_analytical_nodemag():
mesh = df.Mesh(p1=(0, 0, 0), p2=(6e-9, 4e-9, 1e-9),
cell=(2e-9, 1e-9, 0.5e-9))
field = df.Field(mesh, dim=3, value=(0, 0, 1))
system = mm.System(name='Box2')
system.energy = mm.Demag() + mm.Zeeman(H=(0, 1, 0))
system.m = field
torque = mag2exp.magnetometry.torque(system, use_demag=False)
assert np.isclose(torque[0], -mm.consts.mu0)
assert np.isclose(torque[1], 0)
assert np.isclose(torque[2], 0)
def test_torque_analytical_parallel_nodemag():
mesh = df.Mesh(p1=(0, 0, 0), p2=(6e-9, 4e-9, 1e-9),
cell=(2e-9, 1e-9, 0.5e-9))
field = df.Field(mesh, dim=3, value=(0, 0, 1))
system = mm.System(name='Box2')
system.energy = mm.Demag() + mm.Zeeman(H=(0, 0, 1))
system.m = field
torque = mag2exp.magnetometry.torque(system, use_demag=False)
assert np.isclose(torque, 0).all()
def test_torque_analytical_demag():
mesh = df.Mesh(p1=(0, 0, 0), p2=(6e-9, 4e-9, 1e-9),
cell=(2e-9, 1e-9, 0.5e-9))
field = df.Field(mesh, dim=3, value=(0, 1e5, 0))
system = mm.System(name='Box2')
system.energy = mm.Demag() + mm.Zeeman(H=(0, 0, 1e5))
system.m = field
torque = mag2exp.magnetometry.torque(system)
assert np.isclose(torque[0], mm.consts.mu0*1e10)
assert np.isclose(torque[1], 0)
assert np.isclose(torque[2], 0)
def test_torque_analytical__parallel_demag():
mesh = df.Mesh(p1=(0, 0, 0), p2=(6e-9, 4e-9, 1e-9),
cell=(2e-9, 1e-9, 0.5e-9))
field = df.Field(mesh, dim=3, value=(0, 1e5, 0))
system = mm.System(name='Box2')
system.energy = mm.Demag() + mm.Zeeman(H=(0, 1e5, 0))
system.m = field
torque = mag2exp.magnetometry.torque(system)
assert np.isclose(torque, 0).all()
| 35.370968 | 65 | 0.606931 | 364 | 2,193 | 3.604396 | 0.145604 | 0.021341 | 0.030488 | 0.128049 | 0.849085 | 0.811738 | 0.807165 | 0.807165 | 0.790396 | 0.788872 | 0 | 0.088966 | 0.21067 | 2,193 | 61 | 66 | 35.95082 | 0.668977 | 0.005928 | 0 | 0.64 | 0 | 0 | 0.007346 | 0 | 0 | 0 | 0 | 0 | 0.18 | 1 | 0.1 | false | 0 | 0.08 | 0 | 0.18 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
314f5772d7061112e5cf78083ec087f87db1427d | 4,688 | py | Python | tests/test_curves.py | PlasmaControl/DESC | 9f1427cbfc6df9e6dfb2407258996dadc6882d1b | [
"MIT"
] | 9 | 2021-07-27T13:12:46.000Z | 2022-03-30T12:28:07.000Z | tests/test_curves.py | PlasmaControl/DESC | 9f1427cbfc6df9e6dfb2407258996dadc6882d1b | [
"MIT"
] | 97 | 2021-06-20T02:42:12.000Z | 2022-03-29T20:54:14.000Z | tests/test_curves.py | ddudt/DESC | 73327a87d60a38c9a74555428da3b8ccace2e92b | [
"MIT"
] | 3 | 2020-11-14T23:25:39.000Z | 2021-05-13T20:05:36.000Z | import numpy as np
import unittest
import pytest
from desc.geometry import FourierRZCurve, FourierXYZCurve, FourierPlanarCurve
from desc.grid import LinearGrid
class TestRZCurve(unittest.TestCase):
def test_length(self):
c = FourierRZCurve()
np.testing.assert_allclose(c.compute_length(grid=20), 10 * 2 * np.pi)
def test_curvature(self):
c = FourierRZCurve()
np.testing.assert_allclose(c.compute_curvature(grid=20), 1 / 10)
def test_torsion(self):
c = FourierRZCurve()
np.testing.assert_allclose(c.compute_torsion(grid=20), 0)
def test_frenet(self):
c = FourierRZCurve()
T, N, B = c.compute_frenet_frame(grid=np.array([[0.0, 0.0, 0.0]]))
np.testing.assert_allclose(T, np.array([[0, 1, 0]]), atol=1e-12)
np.testing.assert_allclose(N, np.array([[-1, 0, 0]]), atol=1e-12)
np.testing.assert_allclose(B, np.array([[0, 0, 1]]), atol=1e-12)
def test_misc(self):
c = FourierRZCurve()
grid = LinearGrid(L=1, M=4, N=4)
c.grid = grid
assert grid.eq(c.grid)
R, Z = c.get_coeffs(0)
np.testing.assert_allclose(R, 10)
np.testing.assert_allclose(Z, 0)
c.set_coeffs(0, 5, 0)
np.testing.assert_allclose(
c.R_n,
[
5,
],
)
np.testing.assert_allclose(c.Z_n, [])
s = c.copy()
assert s.eq(c)
c.change_resolution(5)
with pytest.raises(ValueError):
c.R_n = s.R_n
with pytest.raises(ValueError):
c.Z_n = s.Z_n
class TestXYZCurve(unittest.TestCase):
def test_length(self):
c = FourierXYZCurve()
np.testing.assert_allclose(c.compute_length(grid=20), 2 * 2 * np.pi)
def test_curvature(self):
c = FourierXYZCurve()
np.testing.assert_allclose(c.compute_curvature(grid=20), 1 / 2)
def test_torsion(self):
c = FourierXYZCurve()
np.testing.assert_allclose(c.compute_torsion(grid=20), 0)
def test_frenet(self):
c = FourierXYZCurve()
T, N, B = c.compute_frenet_frame(grid=np.array([[0.0, 0.0, 0.0]]))
np.testing.assert_allclose(T, np.array([[0, 0, 1]]), atol=1e-12)
np.testing.assert_allclose(N, np.array([[-1, 0, 0]]), atol=1e-12)
np.testing.assert_allclose(B, np.array([[0, -1, 0]]), atol=1e-12)
def test_misc(self):
c = FourierXYZCurve()
grid = LinearGrid(L=1, M=4, N=4)
c.grid = grid
assert grid.eq(c.grid)
X, Y, Z = c.get_coeffs(0)
np.testing.assert_allclose(X, 10)
np.testing.assert_allclose(Y, 0)
np.testing.assert_allclose(Z, 0)
c.set_coeffs(0, 5, 2, 3)
np.testing.assert_allclose(c.X_n, [0, 5, 2])
np.testing.assert_allclose(c.Y_n, [0, 2, 0])
np.testing.assert_allclose(c.Z_n, [2, 3, 0])
s = c.copy()
assert s.eq(c)
c.change_resolution(5)
with pytest.raises(ValueError):
c.X_n = s.X_n
with pytest.raises(ValueError):
c.Y_n = s.Y_n
with pytest.raises(ValueError):
c.Z_n = s.Z_n
class TestPlanarCurve(unittest.TestCase):
def test_length(self):
c = FourierPlanarCurve()
np.testing.assert_allclose(c.compute_length(grid=20), 2 * 2 * np.pi)
def test_curvature(self):
c = FourierPlanarCurve()
np.testing.assert_allclose(c.compute_curvature(grid=20), 1 / 2)
def test_torsion(self):
c = FourierPlanarCurve()
np.testing.assert_allclose(c.compute_torsion(grid=20), 0)
def test_frenet(self):
c = FourierPlanarCurve()
T, N, B = c.compute_frenet_frame(grid=np.array([[0.0, 0.0, 0.0]]))
np.testing.assert_allclose(T, np.array([[0, 0, -1]]), atol=1e-12)
np.testing.assert_allclose(N, np.array([[-1, 0, 0]]), atol=1e-12)
np.testing.assert_allclose(B, np.array([[0, 1, 0]]), atol=1e-12)
def test_misc(self):
c = FourierPlanarCurve()
grid = LinearGrid(L=1, M=4, N=4)
c.grid = grid
assert grid.eq(c.grid)
r = c.get_coeffs(0)
np.testing.assert_allclose(r, 2)
c.set_coeffs(0, 3)
np.testing.assert_allclose(
c.r_n,
[
3,
],
)
c.normal = [1, 2, 3]
c.center = [3, 2, 1]
np.testing.assert_allclose(np.linalg.norm(c.normal), 1)
np.testing.assert_allclose(c.normal * np.linalg.norm(c.center), c.center[::-1])
s = c.copy()
assert s.eq(c)
c.change_resolution(5)
with pytest.raises(ValueError):
c.r_n = s.r_n
| 31.046358 | 87 | 0.578285 | 689 | 4,688 | 3.805515 | 0.101597 | 0.10984 | 0.183066 | 0.280702 | 0.85164 | 0.80778 | 0.786423 | 0.713577 | 0.694889 | 0.574752 | 0 | 0.046512 | 0.275384 | 4,688 | 150 | 88 | 31.253333 | 0.725346 | 0 | 0 | 0.619835 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.31405 | 1 | 0.123967 | false | 0 | 0.041322 | 0 | 0.190083 | 0 | 0 | 0 | 0 | null | 0 | 1 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
31771f021b9ad8a3609418ab6f7d13cea73df02a | 1,030 | py | Python | tests/test_stationary.py | drvinceknight/HierarchicalPromotion | 8fce38c4dc9b21f50a8ef769482fd6a82cf0e6a3 | [
"MIT"
] | null | null | null | tests/test_stationary.py | drvinceknight/HierarchicalPromotion | 8fce38c4dc9b21f50a8ef769482fd6a82cf0e6a3 | [
"MIT"
] | 7 | 2019-10-01T06:47:05.000Z | 2020-11-18T13:10:20.000Z | tests/test_stationary.py | drvinceknight/HierarchicalPromotion | 8fce38c4dc9b21f50a8ef769482fd6a82cf0e6a3 | [
"MIT"
] | null | null | null | import numpy as np
import hierarchy as hrcy
def test_stationary():
capacities = [2, 1]
r = 1.1
lmbda = [2, 3]
mu = [[0.2, 0.1], [1.2, 1.1]]
matrix = hrcy.transitions.get_transition_matrix(
capacities=capacities, r=r, lmbda=lmbda, mu=mu
)
pi = hrcy.get_stationary_distribution(
capacities=capacities, r=r, lmbda=lmbda, mu=mu
)
assert np.allclose(pi @ matrix, 0)
assert len(pi) == matrix.shape[0]
assert np.min(pi) >= 0
assert np.isclose(np.sum(pi), 1)
def test_stationary_example_two():
capacities = [4, 2, 1]
r = 1.1
lmbda = [2, 3]
mu = [[0.2, 0.1], [1.2, 1.1], [1.5, 1.7]]
matrix = hrcy.transitions.get_transition_matrix(
capacities=capacities, r=r, lmbda=lmbda, mu=mu
)
pi = hrcy.get_stationary_distribution(
capacities=capacities, r=r, lmbda=lmbda, mu=mu
)
assert np.allclose(pi @ matrix, 0)
assert len(pi) == matrix.shape[0]
assert np.min(pi) >= -10 ** -7
assert np.isclose(np.sum(pi), 1)
| 24.52381 | 54 | 0.600971 | 160 | 1,030 | 3.79375 | 0.225 | 0.023064 | 0.138386 | 0.144975 | 0.820428 | 0.820428 | 0.820428 | 0.744646 | 0.744646 | 0.744646 | 0 | 0.05527 | 0.24466 | 1,030 | 41 | 55 | 25.121951 | 0.724936 | 0 | 0 | 0.5625 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0.25 | 1 | 0.0625 | false | 0 | 0.0625 | 0 | 0.125 | 0 | 0 | 0 | 0 | null | 0 | 0 | 0 | 1 | 1 | 1 | 1 | 1 | 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 | 6 |
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