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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
7559b85519c4553a6f14d8e25fb56c89487b1c17
| 302
|
py
|
Python
|
test/test_jit_cuda_fuser_profiling.py
|
jsun94/nimble
|
e5c899a69677818b1becc58100577441e15ede13
|
[
"BSD-3-Clause"
] | 206
|
2020-11-28T22:56:38.000Z
|
2022-03-27T02:33:04.000Z
|
test/test_jit_cuda_fuser_profiling.py
|
jsun94/nimble
|
e5c899a69677818b1becc58100577441e15ede13
|
[
"BSD-3-Clause"
] | 19
|
2020-12-09T23:13:14.000Z
|
2022-01-24T23:24:08.000Z
|
test/test_jit_cuda_fuser_profiling.py
|
jsun94/nimble
|
e5c899a69677818b1becc58100577441e15ede13
|
[
"BSD-3-Clause"
] | 28
|
2020-11-29T15:25:12.000Z
|
2022-01-20T02:16:27.000Z
|
import sys
sys.argv.append("--ge_config=profiling")
import os
os.environ['PYTORCH_CUDA_FUSER_DISABLE_FALLBACK'] = '1'
os.environ['PYTORCH_CUDA_FUSER_DISABLE_FMA'] = '1'
os.environ['PYTORCH_CUDA_FUSER_JIT_OPT_LEVEL'] = '0'
from test_jit_cuda_fuser import *
if __name__ == '__main__':
run_tests()
| 23.230769
| 55
| 0.764901
| 46
| 302
| 4.456522
| 0.586957
| 0.17561
| 0.234146
| 0.292683
| 0.443902
| 0.443902
| 0
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| 0
| 0
| 0
| 0.011029
| 0.099338
| 302
| 12
| 56
| 25.166667
| 0.742647
| 0
| 0
| 0
| 0
| 0
| 0.427152
| 0.390728
| 0
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| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
f3385e547409e372158c02c380db1b6d59df448b
| 113
|
py
|
Python
|
molecule/default/tests/test_default.py
|
carlosgo13/ansible-role-hello-world
|
e2e823478f250a17b3f2650d7b83a4b5dc251b42
|
[
"MIT"
] | null | null | null |
molecule/default/tests/test_default.py
|
carlosgo13/ansible-role-hello-world
|
e2e823478f250a17b3f2650d7b83a4b5dc251b42
|
[
"MIT"
] | null | null | null |
molecule/default/tests/test_default.py
|
carlosgo13/ansible-role-hello-world
|
e2e823478f250a17b3f2650d7b83a4b5dc251b42
|
[
"MIT"
] | 1
|
2021-02-10T17:11:54.000Z
|
2021-02-10T17:11:54.000Z
|
def test_command(host):
cmd = 'echo "Hello world" | grep "Hello world"'
assert host.command(cmd).rc == 0
| 28.25
| 51
| 0.646018
| 17
| 113
| 4.235294
| 0.705882
| 0.277778
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011111
| 0.20354
| 113
| 3
| 52
| 37.666667
| 0.788889
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| 1
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| false
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| null | 0
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| 0
| 0
|
0
| 4
|
f3a2f90dff4e2027924f2e407ba4c3679bf1d137
| 2,262
|
py
|
Python
|
tests/test_unsupported.py
|
esheppa/aemo-py
|
d168018d5c66e53d7df767dc1d7782a3db1cdcf1
|
[
"MIT"
] | 1
|
2021-06-09T04:55:26.000Z
|
2021-06-09T04:55:26.000Z
|
tests/test_unsupported.py
|
eigenmo-de/aemo-py
|
d168018d5c66e53d7df767dc1d7782a3db1cdcf1
|
[
"MIT"
] | null | null | null |
tests/test_unsupported.py
|
eigenmo-de/aemo-py
|
d168018d5c66e53d7df767dc1d7782a3db1cdcf1
|
[
"MIT"
] | null | null | null |
from context import aemo
def FILE_WITH_UNSUPPORTED():
return """C,SETP.WORLD,SETTLEMENTS,AEMO,TESTCPY,2025/12/31,02:01:00,123456,SETTLEMENTS,123456,,,,,,,,,,,,,,,,,,,,,
I,SETTLEMENTS,NMAS_RECOVERY,2,SETTLEMENTDATE,VERSIONNO,PERIODID,PARTICIPANTID,SERVICE,CONTRACTID,PAYMENTTYPE,REGIONID,RBF,PAYMENT_AMOUNT,PARTICIPANT_ENERGY,REGION_ENERGY,RECOVERY_AMOUNT,LASTCHANGED,PARTICIPANT_GENERATION,REGION_GENERATION,RECOVERY_AMOUNT_CUSTOMER,RECOVERY_AMOUNT_GENERATOR,,,,,,,,,
D,SETTLEMENTS,NMAS_RECOVERY,2,2025/12/31 00:00:00,1,1,TESTCPY,RESTART,XYZ123,AVAILABILITY,TAS1,1.1,1.1,1.1,1.1,1.1,2025/12/31 02:01:00,1.1,1.1,1.1,1.1,,,,,,,,,
I,SETTLEMENTS,CPDATA,5,SETTLEMENTDATE,VERSIONNO,PERIODID,PARTICIPANTID,TCPID,REGIONID,IGENERGY,XGENERGY,INENERGY,XNENERGY,IPOWER,XPOWER,RRP,EEP,TLF,CPRRP,CPEEP,TA,EP,APC,RESC,RESP,METERRUNNO,HOSTDISTRIBUTOR,MDA,LASTCHANGED,METERDATA_SOURCE
D,SETTLEMENTS,CPDATA,5,2025/12/31 00:00:00,1,1,TESTCPY,ABCD,TAS1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,,,,1,,MSATS,2025/12/31 02:01:00,
I,SETTLEMENTS,FCAS_RECOVERY,6,SETTLEMENTDATE,VERSIONNO,PARTICIPANTID,REGIONID,PERIODID,LOWER6SEC_RECOVERY,RAISE6SEC_RECOVERY,LOWER60SEC_RECOVERY,RAISE60SEC_RECOVERY,LOWER5MIN_RECOVERY,RAISE5MIN_RECOVERY,LOWERREG_RECOVERY,RAISEREG_RECOVERY,LASTCHANGED,LOWER6SEC_RECOVERY_GEN,RAISE6SEC_RECOVERY_GEN,LOWER60SEC_RECOVERY_GEN,RAISE60SEC_RECOVERY_GEN,LOWER5MIN_RECOVERY_GEN,RAISE5MIN_RECOVERY_GEN,LOWERREG_RECOVERY_GEN,RAISEREG_RECOVERY_GEN,,,,,
D,SETTLEMENTS,FCAS_RECOVERY,6,2025/12/31 00:00:00,1,TESTCPY,TAS1,1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,2025/12/31 02:01:00,1.1,1.1,1.1,1.1,1.1,1.1,1.1,1.1,,,,,
I,SETTLEMENTS,MARKETFEES,5,SETTLEMENTDATE,RUNNO,PARTICIPANTID,PERIODID,MARKETFEEID,MARKETFEEVALUE,ENERGY,LASTCHANGED,PARTICIPANTCATEGORYID,,,,,,,,,,,,,,,,,,
D,SETTLEMENTS,MARKETFEES,5,2025/12/31 00:00:00,1,TESTCPY,1,V_EST,1.1,1.1,2025/12/31 02:01:00,XYZ,,,,,,,,,,,,,,,,,,
I,SETTLEMENTS,UNSUPPORTED_DATA,3,SETTLEMENTDATE,VERSIONNO
D,SETTLEMENTS,UNSUPPORTED_DATA,3,2025/12/31 00:00:00,1
D,SETTLEMENTS,UNSUPPORTED_DATA,3,2025/12/31 00:01:00,1
D,SETTLEMENTS,UNSUPPORTED_DATA,3,2025/12/31 00:02:00,1
C,END OF REPORT,14,,,,,,,,,,,,,,,,,,,,,,,,,,,,"""
def test_parse_file_with_unsupported():
_ = aemo.NemFile.from_str(FILE_WITH_UNSUPPORTED())
| 98.347826
| 439
| 0.78824
| 384
| 2,262
| 4.502604
| 0.270833
| 0.090226
| 0.121457
| 0.148062
| 0.232504
| 0.232504
| 0.21631
| 0.215153
| 0.188548
| 0.139965
| 0
| 0.139303
| 0.022546
| 2,262
| 22
| 440
| 102.818182
| 0.642696
| 0
| 0
| 0
| 0
| 0.5
| 0.924403
| 0.892573
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| false
| 0
| 0.055556
| 0.055556
| 0.222222
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
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| 0
| 1
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
f3a62cf95395856a6610b4e42afa6e727aeabaf7
| 255
|
py
|
Python
|
pyboard/boot.py
|
jwlauer/CTD
|
af863cb58d9940fa9f5b6d53c91328188c9e9a4e
|
[
"MIT"
] | null | null | null |
pyboard/boot.py
|
jwlauer/CTD
|
af863cb58d9940fa9f5b6d53c91328188c9e9a4e
|
[
"MIT"
] | null | null | null |
pyboard/boot.py
|
jwlauer/CTD
|
af863cb58d9940fa9f5b6d53c91328188c9e9a4e
|
[
"MIT"
] | null | null | null |
"""Imports basic modules at bootup"""
import machine
import pyb
#pyb.main('main.py') # main script to run after this one
#pyb.usb_mode('VCP+MSC') # act as a serial and a storage device
#pyb.usb_mode('VCP+HID') # act as a serial device and a mouse
| 31.875
| 64
| 0.701961
| 46
| 255
| 3.847826
| 0.630435
| 0.067797
| 0.112994
| 0.146893
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.180392
| 255
| 7
| 65
| 36.428571
| 0.84689
| 0.807843
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
f3bc11eb7b7dba721e3d5e50d3cfde3cb66c59ad
| 62
|
py
|
Python
|
src/softframe/rest/service.py
|
pcastanha/frame
|
f3392e3660742db6beb3b6e1702d7aee6acedf62
|
[
"BSD-2-Clause"
] | null | null | null |
src/softframe/rest/service.py
|
pcastanha/frame
|
f3392e3660742db6beb3b6e1702d7aee6acedf62
|
[
"BSD-2-Clause"
] | null | null | null |
src/softframe/rest/service.py
|
pcastanha/frame
|
f3392e3660742db6beb3b6e1702d7aee6acedf62
|
[
"BSD-2-Clause"
] | null | null | null |
from softframe.rest.api import create_app
app = create_app()
| 15.5
| 41
| 0.790323
| 10
| 62
| 4.7
| 0.7
| 0.382979
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.129032
| 62
| 3
| 42
| 20.666667
| 0.87037
| 0
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| 0
| 0
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| 0
| false
| 0
| 0.5
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| 0.5
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| 0
| null | 1
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
45e80e2ed902073bf1be95cc348e8ebcbe8c827c
| 56
|
py
|
Python
|
python/testData/psi/unified/StarParameter.py
|
jnthn/intellij-community
|
8fa7c8a3ace62400c838e0d5926a7be106aa8557
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/psi/unified/StarParameter.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/psi/unified/StarParameter.py
|
Cyril-lamirand/intellij-community
|
60ab6c61b82fc761dd68363eca7d9d69663cfa39
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
def foo(arg1, *, kwarg1):
pass
def bar():
pass
| 9.333333
| 25
| 0.535714
| 8
| 56
| 3.75
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.051282
| 0.303571
| 56
| 6
| 26
| 9.333333
| 0.717949
| 0
| 0
| 0.5
| 0
| 0
| 0
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| 0
| 0
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| 1
| 0.5
| false
| 0.5
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| null | 0
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| null | 0
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| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
34011a1dc40557e76c6b8c64e9110366f55358b0
| 203
|
py
|
Python
|
app/api/serializers/product.py
|
tonyguesswho/jumga
|
fdcfc437578d48489fea2d3ab2f7c8711b6b231c
|
[
"MIT"
] | null | null | null |
app/api/serializers/product.py
|
tonyguesswho/jumga
|
fdcfc437578d48489fea2d3ab2f7c8711b6b231c
|
[
"MIT"
] | null | null | null |
app/api/serializers/product.py
|
tonyguesswho/jumga
|
fdcfc437578d48489fea2d3ab2f7c8711b6b231c
|
[
"MIT"
] | null | null | null |
from rest_framework import serializers
from apps.product.models import Product
class ProductSerilaizer(serializers.ModelSerializer):
class Meta:
model = Product
fields = '__all__'
| 20.3
| 53
| 0.743842
| 21
| 203
| 6.952381
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.20197
| 203
| 9
| 54
| 22.555556
| 0.901235
| 0
| 0
| 0
| 0
| 0
| 0.034483
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
| 4
|
340bf3237d75568b056e7937d4096e9ab2af0198
| 203
|
py
|
Python
|
dcg_playground/main.py
|
boardpack/dcg-playground
|
105f36d65c11706800c6e07af3ef10860f242070
|
[
"MIT"
] | null | null | null |
dcg_playground/main.py
|
boardpack/dcg-playground
|
105f36d65c11706800c6e07af3ef10860f242070
|
[
"MIT"
] | null | null | null |
dcg_playground/main.py
|
boardpack/dcg-playground
|
105f36d65c11706800c6e07af3ef10860f242070
|
[
"MIT"
] | null | null | null |
from starlette.applications import Starlette
from dcg_playground import views
def create_app(debug: bool = False):
application = Starlette(debug=debug, routes=views.routes)
return application
| 22.555556
| 61
| 0.788177
| 25
| 203
| 6.32
| 0.64
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.147783
| 203
| 8
| 62
| 25.375
| 0.913295
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.4
| 0
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
34199085345294dfc2c91add4dde171033b4af07
| 63
|
py
|
Python
|
src/wshop/apps/voucher/__init__.py
|
vituocgia/wshop-core
|
5f6d1ec9e9158f13aab136c5bd901c41e69a1dba
|
[
"BSD-3-Clause"
] | null | null | null |
src/wshop/apps/voucher/__init__.py
|
vituocgia/wshop-core
|
5f6d1ec9e9158f13aab136c5bd901c41e69a1dba
|
[
"BSD-3-Clause"
] | null | null | null |
src/wshop/apps/voucher/__init__.py
|
vituocgia/wshop-core
|
5f6d1ec9e9158f13aab136c5bd901c41e69a1dba
|
[
"BSD-3-Clause"
] | null | null | null |
default_app_config = 'wshop.apps.voucher.config.VoucherConfig'
| 31.5
| 62
| 0.84127
| 8
| 63
| 6.375
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.047619
| 63
| 1
| 63
| 63
| 0.85
| 0
| 0
| 0
| 0
| 0
| 0.619048
| 0.619048
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
34315dd28f88f6d7b6025ecfce8999214e9b706b
| 75
|
py
|
Python
|
db.py
|
AriosJentu/Flaskishe
|
03133e4ea8c53b4da6c5962046fea24f5bcc2a82
|
[
"MIT"
] | null | null | null |
db.py
|
AriosJentu/Flaskishe
|
03133e4ea8c53b4da6c5962046fea24f5bcc2a82
|
[
"MIT"
] | null | null | null |
db.py
|
AriosJentu/Flaskishe
|
03133e4ea8c53b4da6c5962046fea24f5bcc2a82
|
[
"MIT"
] | null | null | null |
import sqlite3 as db
studb = db.connect("studb.db")
cursr = studb.cursor()
| 18.75
| 30
| 0.72
| 12
| 75
| 4.5
| 0.666667
| 0.259259
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015385
| 0.133333
| 75
| 4
| 31
| 18.75
| 0.815385
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
3442805721549a3edd68bc98480954335b240117
| 242
|
py
|
Python
|
main/admin.py
|
abanoub-nasser/short-url
|
0d8f4338f36fc80bd3219a46e811f5c903fe8955
|
[
"MIT"
] | null | null | null |
main/admin.py
|
abanoub-nasser/short-url
|
0d8f4338f36fc80bd3219a46e811f5c903fe8955
|
[
"MIT"
] | null | null | null |
main/admin.py
|
abanoub-nasser/short-url
|
0d8f4338f36fc80bd3219a46e811f5c903fe8955
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from models import Url
class UrlAdmin(admin.ModelAdmin):
list_display = ('id','Lurl','Surl', 'Views', 'Date')
search_fields = ('id','Lurl','Surl','Views', 'Date')
admin.site.register(Url, UrlAdmin)
| 24.2
| 56
| 0.68595
| 32
| 242
| 5.125
| 0.65625
| 0.073171
| 0.121951
| 0.182927
| 0.231707
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132231
| 242
| 9
| 57
| 26.888889
| 0.780952
| 0
| 0
| 0
| 0
| 0
| 0.157025
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.833333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 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
| 1
| 0
|
0
| 4
|
346014f1c19fc41a0ec707bcfeb9759a6f84c7b3
| 285
|
py
|
Python
|
ISMLnextGen/postTest.py
|
Ravenclaw-OIer/ISML_auto_voter
|
9c53bd87530697d374163f571186542c3fc9734b
|
[
"MIT"
] | 128
|
2020-11-16T09:28:17.000Z
|
2022-03-14T10:38:52.000Z
|
ISMLnextGen/postTest.py
|
Ravenclaw-OIer/ISML_auto_voter
|
9c53bd87530697d374163f571186542c3fc9734b
|
[
"MIT"
] | 7
|
2020-11-27T14:45:19.000Z
|
2022-02-15T09:47:12.000Z
|
ISMLnextGen/postTest.py
|
Ravenclaw-OIer/ISML_auto_voter
|
9c53bd87530697d374163f571186542c3fc9734b
|
[
"MIT"
] | 11
|
2020-12-11T12:24:38.000Z
|
2022-02-20T12:42:31.000Z
|
from requests import post
headers={'ipNum':'5'}
payload={'0':'1.1.1.1:8080',
'1':'2.2.2.2:8080',
'2':'2.2.2.2:8080',
'3':'2.2.2.2:8080',
'4':'2.2.2.2:8080',}
response=post(url='http://127.0.0.1:8999/main',headers=headers,json=payload)
pass
| 28.5
| 77
| 0.522807
| 53
| 285
| 2.811321
| 0.415094
| 0.174497
| 0.181208
| 0.134228
| 0.214765
| 0
| 0
| 0
| 0
| 0
| 0
| 0.245614
| 0.2
| 285
| 10
| 78
| 28.5
| 0.407895
| 0
| 0
| 0
| 0
| 0
| 0.350181
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.111111
| 0.111111
| 0
| 0.111111
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
347b9938418d6a9721a42ec91f8ae04cd4cfd836
| 70,622
|
py
|
Python
|
peitho/simulations/cudasim/SBMLParser.py
|
MichaelPHStumpf/Peitho
|
a4daa9a3b2d8960079573d08d5baa019b5ac857e
|
[
"MIT"
] | 1
|
2018-01-05T21:59:49.000Z
|
2018-01-05T21:59:49.000Z
|
peitho/simulations/cudasim/SBMLParser.py
|
MichaelPHStumpf/Peitho
|
a4daa9a3b2d8960079573d08d5baa019b5ac857e
|
[
"MIT"
] | null | null | null |
peitho/simulations/cudasim/SBMLParser.py
|
MichaelPHStumpf/Peitho
|
a4daa9a3b2d8960079573d08d5baa019b5ac857e
|
[
"MIT"
] | 3
|
2018-01-05T22:00:09.000Z
|
2018-12-25T13:32:10.000Z
|
from numpy import *
from libsbml import *
import re
import os
##To call the parser:
## SBMLparse.importSBML(source, integrationType, ModelName=None,method=None)
## All arguments to function must be passed as tuples.
## If there is only one source to parse it must still be passed as a tuple ('source.xml',)
## with an integrationType passed as ('Gillespie',)
## replace the species and parameters recursively
##
## replace
## pq = re.compile(speciesId[q])
## string=pq.sub('y['+repr(q)+']' ,string)
## with
## string = rep(string, speciesId[q],'y['+repr(q)+']')
def rep(str,find,replace):
ex = find+"[^0-9]"
ss = str;
while re.search(ex,ss) != None:
res = re.search(ex,ss)
ss = ss[0:res.start()] + replace + " " + ss[res.end()-1:]
ex = find+"$"
if re.search(ex,ss) != None:
res = re.search(ex,ss)
ss = ss[0:res.start()] + replace + " " + ss[res.end():]
return ss;
######################## CUDA SDE #################################
def write_SDECUDA(stoichiometricMatrix, kineticLaw, species, numSpecies, numGlobalParameters, numReactions, speciesId, listOfParameter, parameterId, parameter, InitValues, name, listOfFunctions, FunctionArgument, FunctionBody, listOfRules, ruleFormula, ruleVariable, listOfEvents, EventCondition, EventVariable, EventFormula, outpath=""):
"""
Write the cuda file with ODE functions using the information taken by the parser
"""
p=re.compile('\s')
#Open the outfile
out_file=open(os.path.join(outpath,name+".cu"),"w")
#Write number of parameters and species
out_file.write("#define NSPECIES " + str(numSpecies) + "\n")
out_file.write("#define NPARAM " + str(numGlobalParameters) + "\n")
out_file.write("#define NREACT " + str(numReactions) + "\n")
out_file.write("\n")
#The user-defined functions used in the model must be written in the file
out_file.write("//Code for texture memory\n")
numEvents = len(listOfEvents)
numRules = len(listOfRules)
num = numEvents+numRules
if num>0:
out_file.write("#define leq(a,b) a<=b\n")
out_file.write("#define neq(a,b) a!=b\n")
out_file.write("#define geq(a,b) a>=b\n")
out_file.write("#define lt(a,b) a<b\n")
out_file.write("#define gt(a,b) a>b\n")
out_file.write("#define eq(a,b) a==b\n")
out_file.write("#define and_(a,b) a&&b\n")
out_file.write("#define or_(a,b) a||b\n")
for i in range(0,len(listOfFunctions)):
out_file.write("__device__ float "+listOfFunctions[i].getId()+"(")
for j in range(0, listOfFunctions[i].getNumArguments()):
out_file.write("float "+FunctionArgument[i][j])
if(j<( listOfFunctions[i].getNumArguments()-1)):
out_file.write(",")
out_file.write("){\n return ")
out_file.write(FunctionBody[i])
out_file.write(";\n}\n")
out_file.write("\n")
out_file.write("\n")
out_file.write("__device__ void step(float *y, float t, unsigned *rngRegs, int tid){\n")
numSpecies = len(species)
#write rules and events
for i in range(0,len(listOfRules)):
if listOfRules[i].isRate() == True:
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = ruleFormula[i]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)',string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
for i in range(0,len(listOfEvents)):
out_file.write(" if( ")
#print EventCondition[i]
out_file.write(mathMLConditionParserCuda(EventCondition[i]))
out_file.write("){\n")
listOfAssignmentRules = listOfEvents[i].getListOfEventAssignments()
for j in range(0, len(listOfAssignmentRules)):
out_file.write(" ")
#out_file.write("float ")
if not(EventVariable[i][j] in speciesId):
out_file.write(EventVariable[i][j])
else:
string = "y["+repr(speciesId.index(EventVariable[i][j]))+"]"
out_file.write(string)
out_file.write("=")
string = EventFormula[i][j]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
out_file.write("}\n")
out_file.write("\n")
for i in range(0, len(listOfRules)):
if listOfRules[i].isAssignment():
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write("float ")
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = mathMLConditionParserCuda(ruleFormula[i])
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub("y["+repr(q)+"]" ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#x = "tex2D(param_tex,"+repr(q)+",tid)"
#string=pq.sub(x,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
out_file.write("")
#Write the derivatives
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False):
out_file.write(" float d_y"+repr(i)+"= DT * (")
if (species[i].isSetCompartment() == True):
out_file.write("(")
reactionWritten = False
for k in range(0,numReactions):
if(not stoichiometricMatrix[i][k]==0.0):
if(reactionWritten and stoichiometricMatrix[i][k]>0.0):
out_file.write("+")
reactionWritten = True
out_file.write(repr(stoichiometricMatrix[i][k]))
out_file.write("*(")
#test if reaction has a positive sign
#if(reactionWritten):
# if(stoichiometricMatrix[i][k]>0.0):
# out_file.write("+")
# else:
# out_file.write("-")
#reactionWritten = True
#test if reaction is 1.0; then omit multiplication term
#if(abs(stoichiometricMatrix[i][k]) == 1.0):
# out_file.write("(")
#else:
# out_file.write(repr(abs(stoichiometricMatrix[i][k])))
# out_file.write("*(")
string = kineticLaw[k]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
string=p.sub('',string)
out_file.write(string)
out_file.write(")")
if (species[i].isSetCompartment() == True):
out_file.write(")/")
mySpeciesCompartment = species[i].getCompartment()
for j in range(0, len(listOfParameter)):
if (listOfParameter[j].getId() == mySpeciesCompartment):
if (not(parameterId[j] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[j] in EventVariable[r]):
flag = True
if flag==False:
out_file.write("tex2D(param_tex,"+repr(j)+",tid)"+");")
break
else:
out_file.write(parameterId[j]+");")
break
else:
out_file.write(");")
out_file.write("\n")
out_file.write("\n")
# check for columns of the stochiometry matrix with more than one entry
randomVariables = ["*randNormal(rngRegs,sqrt(DT))"] * numReactions
for k in range(0,numReactions):
countEntries = 0
for i in range(0,numSpecies):
if(stoichiometricMatrix[i][k] != 0.0): countEntries += 1
# define specific randomVariable
if countEntries > 1:
out_file.write(" float rand"+repr(k)+" = randNormal(rngRegs,sqrt(DT));\n")
randomVariables[k] = "*rand" + repr(k)
out_file.write("\n")
#write noise terms
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False):
out_file.write(" d_y"+repr(i)+" += (")
if (species[i].isSetCompartment() == True):
out_file.write("(")
reactionWritten = False
for k in range(0,numReactions):
if(not stoichiometricMatrix[i][k]==0.0):
if(reactionWritten and stoichiometricMatrix[i][k]>0.0):
out_file.write("+")
reactionWritten = True
out_file.write(repr(stoichiometricMatrix[i][k]))
out_file.write("*sqrt(")
#test if reaction has a positive sign
#if(reactionWritten):
# if(stoichiometricMatrix[i][k]>0.0):
# out_file.write("+")
# else:
# out_file.write("-")
#reactionWritten = True
#test if reaction is 1.0; then omit multiplication term
#if(abs(stoichiometricMatrix[i][k]) == 1.0):
# out_file.write("sqrtf(")
#else:
# out_file.write(repr(abs(stoichiometricMatrix[i][k])))
# out_file.write("*sqrtf(")
string = kineticLaw[k]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
string=p.sub('',string)
out_file.write(string)
#multiply random variable
out_file.write(")")
out_file.write(randomVariables[k])
#out_file.write("*randNormal(rngRegs,sqrt(DT))")
if (species[i].isSetCompartment() == True):
out_file.write(")/")
mySpeciesCompartment = species[i].getCompartment()
for j in range(0, len(listOfParameter)):
if (listOfParameter[j].getId() == mySpeciesCompartment):
if (not(parameterId[j] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[j] in EventVariable[r]):
flag = True
if flag==False:
out_file.write("tex2D(param_tex,"+repr(j)+",tid)"+")")
break
else:
out_file.write(parameterId[j]+")")
break
else:
out_file.write(")")
out_file.write(";\n")
out_file.write("\n")
#add terms
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False ):
out_file.write(" y["+repr(i)+"] += d_y"+repr(i)+";\n")
out_file.write("}\n")
################# same file
p=re.compile('\s')
#The user-defined functions used in the model must be written in the file
out_file.write("//Code for shared memory\n")
numEvents = len(listOfEvents)
numRules = len(listOfRules)
num = numEvents+numRules
if num>0:
out_file.write("#define leq(a,b) a<=b\n")
out_file.write("#define neq(a,b) a!=b\n")
out_file.write("#define geq(a,b) a>=b\n")
out_file.write("#define lt(a,b) a<b\n")
out_file.write("#define gt(a,b) a>b\n")
out_file.write("#define eq(a,b) a==b\n")
out_file.write("#define and_(a,b) a&&b\n")
out_file.write("#define or_(a,b) a||b\n")
for i in range(0,len(listOfFunctions)):
out_file.write("__device__ float "+listOfFunctions[i].getId()+"(")
for j in range(0, listOfFunctions[i].getNumArguments()):
out_file.write("float "+FunctionArgument[i][j])
if(j<( listOfFunctions[i].getNumArguments()-1)):
out_file.write(",")
out_file.write("){\n return ")
out_file.write(FunctionBody[i])
out_file.write(";\n}\n")
out_file.write("\n")
out_file.write("\n")
out_file.write("__device__ void step(float *parameter, float *y, float t, unsigned *rngRegs){\n")
numSpecies = len(species)
#write rules and events
for i in range(0,len(listOfRules)):
if listOfRules[i].isRate() == True:
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = ruleFormula[i]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
pq = re.compile(parameterId[q])
string=pq.sub('parameter['+repr(q)+']' ,string)
out_file.write(string)
out_file.write(";\n")
for i in range(0,len(listOfEvents)):
out_file.write(" if( ")
#print EventCondition[i]
out_file.write(mathMLConditionParserCuda(EventCondition[i]))
out_file.write("){\n")
listOfAssignmentRules = listOfEvents[i].getListOfEventAssignments()
for j in range(0, len(listOfAssignmentRules)):
out_file.write(" ")
#out_file.write("float ")
if not(EventVariable[i][j] in speciesId):
out_file.write(EventVariable[i][j])
else:
string = "y["+repr(speciesId.index(EventVariable[i][j]))+"]"
out_file.write(string)
out_file.write("=")
string = EventFormula[i][j]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
pq = re.compile(parameterId[q])
string=pq.sub('parameter['+repr(q)+']' ,string)
out_file.write(string)
out_file.write(";\n")
out_file.write("}\n")
out_file.write("\n")
for i in range(0, len(listOfRules)):
if listOfRules[i].isAssignment():
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write("float ")
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = mathMLConditionParserCuda(ruleFormula[i])
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub("y["+repr(q)+"]" ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
pq = re.compile(parameterId[q])
x = "parameter["+repr(q)+"]"
string=pq.sub(x,string)
out_file.write(string)
out_file.write(";\n")
#out_file.write("\n\n")
#Write the derivatives
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False):
out_file.write(" float d_y"+repr(i)+"= DT * (")
if (species[i].isSetCompartment() == True):
out_file.write("(")
reactionWritten = False
for k in range(0,numReactions):
if(not stoichiometricMatrix[i][k]==0.0):
if(reactionWritten and stoichiometricMatrix[i][k]>0.0):
out_file.write("+")
reactionWritten = True
out_file.write(repr(stoichiometricMatrix[i][k]))
out_file.write("*(")
#test if reaction has a positive sign
#if(reactionWritten):
# if(stoichiometricMatrix[i][k]>0.0):
# out_file.write("+")
# else:
# out_file.write("-")
#reactionWritten = True
#test if reaction is 1.0; then omit multiplication term
#if(abs(stoichiometricMatrix[i][k]) == 1.0):
# out_file.write("(")
#else:
# out_file.write(repr(abs(stoichiometricMatrix[i][k])))
# out_file.write("*(")
string = kineticLaw[k]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
pq = re.compile(parameterId[q])
string=pq.sub('parameter['+repr(q)+']' ,string)
string=p.sub('',string)
out_file.write(string)
out_file.write(")")
if (species[i].isSetCompartment() == True):
out_file.write(")/")
mySpeciesCompartment = species[i].getCompartment()
for j in range(0, len(listOfParameter)):
if (listOfParameter[j].getId() == mySpeciesCompartment):
if (not(parameterId[j] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[j] in EventVariable[r]):
flag = True
if flag==False:
out_file.write("parameter["+repr(j)+"]"+");")
break
else:
out_file.write(parameterId[j]+");")
break
else:
out_file.write(");")
out_file.write("\n")
out_file.write("\n")
# check for columns of the stochiometry matrix with more than one entry
randomVariables = ["*randNormal(rngRegs,sqrt(DT))"] * numReactions
for k in range(0,numReactions):
countEntries = 0
for i in range(0,numSpecies):
if(stoichiometricMatrix[i][k] != 0.0): countEntries += 1
# define specific randomVariable
if countEntries > 1:
out_file.write(" float rand"+repr(k)+" = randNormal(rngRegs,sqrt(DT));\n")
randomVariables[k] = "*rand" + repr(k)
out_file.write("\n")
#write noise terms
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False):
out_file.write(" d_y"+repr(i)+"+= (")
if (species[i].isSetCompartment() == True):
out_file.write("(")
reactionWritten = False
for k in range(0,numReactions):
if(not stoichiometricMatrix[i][k]==0.0):
if(reactionWritten and stoichiometricMatrix[i][k]>0.0):
out_file.write("+")
reactionWritten = True
out_file.write(repr(stoichiometricMatrix[i][k]))
out_file.write("*sqrt(")
#test if reaction has a positive sign
#if(reactionWritten):
# if(stoichiometricMatrix[i][k]>0.0):
# out_file.write("+")
# else:
# out_file.write("-")
#reactionWritten = True
#test if reaction is 1.0; then omit multiplication term
#if(abs(stoichiometricMatrix[i][k]) == 1.0):
# out_file.write("sqrtf(")
#else:
# out_file.write(repr(abs(stoichiometricMatrix[i][k])))
# out_file.write("*sqrtf(")
string = kineticLaw[k]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
pq = re.compile(parameterId[q])
string=pq.sub('parameter['+repr(q)+']' ,string)
string=p.sub('',string)
out_file.write(string)
#multiply random variable
out_file.write(")")
out_file.write(randomVariables[k])
#out_file.write("*randNormal(rngRegs,sqrt(DT))")
if (species[i].isSetCompartment() == True):
out_file.write(")/")
mySpeciesCompartment = species[i].getCompartment()
for j in range(0, len(listOfParameter)):
if (listOfParameter[j].getId() == mySpeciesCompartment):
if (not(parameterId[j] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[j] in EventVariable[r]):
flag = True
if flag==False:
out_file.write("parameter["+repr(j)+"]"+")")
break
else:
out_file.write(parameterId[j]+")")
break
else:
out_file.write(")")
out_file.write(";\n")
out_file.write("\n")
#add terms
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False):
out_file.write(" y["+repr(i)+"] += d_y"+repr(i)+";\n")
out_file.write("}\n")
######################## CUDA Gillespie #################################
def write_GillespieCUDA(stoichiometricMatrix, kineticLaw, numSpecies, numGlobalParameters, numReactions, species, parameterId, InitValues, speciesId,name, listOfFunctions,FunctionArgument,FunctionBody, listOfRules, ruleFormula, ruleVariable, listOfEvents, EventCondition, EventVariable, EventFormula, outpath=""):
p=re.compile('\s')
#Open the outfile
out_file=open(os.path.join(outpath,name+".cu"),"w")
#Write number of parameters and species
out_file.write("#define NSPECIES " + str(numSpecies) + "\n")
out_file.write("#define NPARAM " + str(numGlobalParameters) + "\n")
out_file.write("#define NREACT " + str(numReactions) + "\n")
out_file.write("\n")
numEvents = len(listOfEvents)
numRules = len(listOfRules)
num = numEvents+numRules
if num>0:
out_file.write("#define leq(a,b) a<=b\n")
out_file.write("#define neq(a,b) a!=b\n")
out_file.write("#define geq(a,b) a>=b\n")
out_file.write("#define lt(a,b) a<b\n")
out_file.write("#define gt(a,b) a>b\n")
out_file.write("#define eq(a,b) a==b\n")
out_file.write("#define and_(a,b) a&&b\n")
out_file.write("#define or_(a,b) a||b\n")
for i in range(0,len(listOfFunctions)):
out_file.write("__device__ float "+listOfFunctions[i].getId()+"(")
for j in range(0, listOfFunctions[i].getNumArguments()):
out_file.write("float "+FunctionArgument[i][j])
if(j<( listOfFunctions[i].getNumArguments()-1)):
out_file.write(",")
out_file.write("){\n return ")
out_file.write(FunctionBody[i])
out_file.write(";\n}\n")
out_file.write("")
out_file.write("\n\n__constant__ int smatrix[]={\n")
for i in range(0,len(stoichiometricMatrix[0])):
for j in range(0,len(stoichiometricMatrix)):
out_file.write(" "+repr(stoichiometricMatrix[j][i]))
if (not(i==(len(stoichiometricMatrix)-1) and (j==(len(stoichiometricMatrix[0])-1)))):
out_file.write(",")
out_file.write("\n")
out_file.write("};\n\n\n")
#stoichiometry function moved to Gillespie.py
#out_file.write("__device__ void stoichiometry(int *y, int r, int tid){\n")
#out_file.write(" for(int i=0; i<"+repr(len(species))+"; i++){\n y[i]+=smatrix[r*"+repr(len(species))+"+ i];\n }\n}\n\n\n")
out_file.write("__device__ void hazards(int *y, float *h, float t, int tid){")
# wirte rules and events
for i in range(0,len(listOfRules)):
if listOfRules[i].isRate() == True:
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = ruleFormula[i]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
for i in range(0,len(listOfEvents)):
out_file.write(" if( ")
out_file.write(mathMLConditionParserCuda(EventCondition[i]))
out_file.write("){\n")
listOfAssignmentRules = listOfEvents[i].getListOfEventAssignments()
for j in range(0, len(listOfAssignmentRules)):
out_file.write(" ")
#out_file.write("float ")
if not(EventVariable[i][j] in speciesId):
out_file.write(EventVariable[i][j])
else:
string = "y["+repr(speciesId.index(EventVariable[i][j]))+"]"
out_file.write(string)
out_file.write("=")
string = EventFormula[i][j]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
out_file.write(" }\n")
out_file.write("\n")
for i in range(0, len(listOfRules)):
if listOfRules[i].isAssignment():
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write("float ")
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = mathMLConditionParserCuda(ruleFormula[i])
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub("y["+repr(q)+"]" ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#x = "tex2D(param_tex,"+repr(q)+",tid)"
#string=pq.sub(x,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
out_file.write("\n")
for i in range(0,numReactions):
out_file.write(" h["+repr(i)+"] = ")
string = kineticLaw[i]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
string=p.sub('',string)
out_file.write(string+";\n")
out_file.write("\n")
out_file.write("}\n\n")
######################## CUDA ODE #################################
def write_ODECUDA(stoichiometricMatrix, kineticLaw, species, numSpecies, numGlobalParameters, numReactions, speciesId, listOfParameter, parameterId,parameter,InitValues,name, listOfFunctions, FunctionArgument, FunctionBody, listOfRules, ruleFormula, ruleVariable, listOfEvents, EventCondition, EventVariable, EventFormula, outpath=""):
"""
Write the cuda file with ODE functions using the information taken by the parser
"""
p=re.compile('\s')
#Open the outfile
out_file=open(os.path.join(outpath,name+".cu"),"w")
#Write number of parameters and species
out_file.write("#define NSPECIES " + str(numSpecies) + "\n")
out_file.write("#define NPARAM " + str(numGlobalParameters) + "\n")
out_file.write("#define NREACT " + str(numReactions) + "\n")
out_file.write("\n")
#The user-defined functions used in the model must be written in the file
numEvents = len(listOfEvents)
numRules = len(listOfRules)
num = numEvents+numRules
if num>0:
out_file.write("#define leq(a,b) a<=b\n")
out_file.write("#define neq(a,b) a!=b\n")
out_file.write("#define geq(a,b) a>=b\n")
out_file.write("#define lt(a,b) a<b\n")
out_file.write("#define gt(a,b) a>b\n")
out_file.write("#define eq(a,b) a==b\n")
out_file.write("#define and_(a,b) a&&b\n")
out_file.write("#define or_(a,b) a||b\n")
for i in range(0,len(listOfFunctions)):
out_file.write("__device__ float "+listOfFunctions[i].getId()+"(")
for j in range(0, listOfFunctions[i].getNumArguments()):
out_file.write("float "+FunctionArgument[i][j])
if(j<( listOfFunctions[i].getNumArguments()-1)):
out_file.write(",")
out_file.write("){\n return ")
out_file.write(FunctionBody[i])
out_file.write(";\n}\n")
out_file.write("\n")
out_file.write("struct myFex{\n __device__ void operator()(int *neq, double *t, double *y, double *ydot/*, void *otherData*/)\n {\n int tid = blockDim.x * blockIdx.x + threadIdx.x;\n")
numSpecies = len(species)
#write rules and events
for i in range(0,len(listOfRules)):
if listOfRules[i].isRate() == True:
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = ruleFormula[i]
for q in range(0,len(speciesId)):
pq = re.compile(speciesId[q])
string=pq.sub('y['+repr(q)+']' ,string)
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
pq = re.compile(parameterId[q])
string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
out_file.write(string)
out_file.write(";\n")
for i in range(0,len(listOfEvents)):
out_file.write(" if( ")
#print EventCondition[i]
out_file.write(mathMLConditionParserCuda(EventCondition[i]))
out_file.write("){\n")
listOfAssignmentRules = listOfEvents[i].getListOfEventAssignments()
for j in range(0, len(listOfAssignmentRules)):
out_file.write(" ")
#out_file.write("float ")
if not(EventVariable[i][j] in speciesId):
out_file.write(EventVariable[i][j])
else:
string = "y["+repr(speciesId.index(EventVariable[i][j]))+"]"
out_file.write(string)
out_file.write("=")
string = EventFormula[i][j]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
out_file.write("}\n")
out_file.write("\n")
for i in range(0, len(listOfRules)):
if listOfRules[i].isAssignment():
out_file.write(" ")
if not(ruleVariable[i] in speciesId):
out_file.write("float ")
out_file.write(ruleVariable[i])
else:
string = "y["+repr(speciesId.index(ruleVariable[i]))+"]"
out_file.write(string)
out_file.write("=")
string = mathMLConditionParserCuda(ruleFormula[i])
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q])
#string=pq.sub("y["+repr(q)+"]" ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#x = "tex2D(param_tex,"+repr(q)+",tid)"
#string=pq.sub(x,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
out_file.write(string)
out_file.write(";\n")
out_file.write("\n\n")
#Write the derivatives
for i in range(0,numSpecies):
if (species[i].getConstant() == False and species[i].getBoundaryCondition() == False):
out_file.write(" ydot["+repr(i)+"]=")
if (species[i].isSetCompartment() == True):
out_file.write("(")
reactionWritten = False
for k in range(0,numReactions):
if(not stoichiometricMatrix[i][k]==0.0):
if(reactionWritten and stoichiometricMatrix[i][k]>0.0):
out_file.write("+")
reactionWritten = True
out_file.write(repr(stoichiometricMatrix[i][k]))
out_file.write("*(")
#test if reaction has a positive sign
#if(reactionWritten):
# if(stoichiometricMatrix[i][k]>0.0):
# out_file.write("+")
# else:
# out_file.write("-")
#reactionWritten = True
#test if reaction is 1.0; then omit multiplication term
#if(abs(stoichiometricMatrix[i][k]) == 1.0):
# out_file.write("(")
#else:
# out_file.write(repr(abs(stoichiometricMatrix[i][k])))
# out_file.write("*(")
string = kineticLaw[k]
for q in range(0,len(speciesId)):
#pq = re.compile(speciesId[q]+'[^0-9]')
#pq = re.compile(speciesId[q]+'[^0-9]')
#pq = re.compile(speciesId[q])
#ret=pq.sub('y['+repr(q)+']' ,string)
string = rep(string, speciesId[q],'y['+repr(q)+']')
##if ret != string:
#if q == 5:
# print speciesId[q], "|", 'y['+repr(q)+']', "\n\t", string, "\n\t", ret
#string = ret;
for q in range(0,len(parameterId)):
if (not(parameterId[q] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[q] in EventVariable[r]):
flag = True
if flag==False:
#pq = re.compile(parameterId[q])
#string=pq.sub('tex2D(param_tex,'+repr(q)+',tid)' ,string)
string = rep(string, parameterId[q],'tex2D(param_tex,'+repr(q)+',tid)')
string=p.sub('',string)
##print string
out_file.write(string)
out_file.write(")")
if (species[i].isSetCompartment() == True):
out_file.write(")/")
mySpeciesCompartment = species[i].getCompartment()
for j in range(0, len(listOfParameter)):
if (listOfParameter[j].getId() == mySpeciesCompartment):
if (not(parameterId[j] in ruleVariable)):
flag = False
for r in range(0,len(EventVariable)):
if (parameterId[j] in EventVariable[r]):
flag = True
if flag==False:
out_file.write("tex2D(param_tex,"+repr(j)+",tid)"+";")
break
else:
out_file.write(parameterId[j]+";")
break
else:
out_file.write(";")
out_file.write("\n")
out_file.write("\n }")
out_file.write("\n};\n\n\n struct myJex{\n __device__ void operator()(int *neq, double *t, double *y, int ml, int mu, double *pd, int nrowpd/*, void *otherData*/){\n return; \n }\n};")
################################################################################
# The parser for logical operations in conditions #
################################################################################
def mathMLConditionParserCuda(mathMLstring):
"""
Replaces and and or with and_ and or_ in a MathML string.
Returns the string with and and or replaced by and_ and or_
***** args *****
mathMLstring:
A mathMLstring
"""
andString = re.compile("and")
orString = re.compile("or")
mathMLstring = andString.sub("and_", mathMLstring)
mathMLstring = orString.sub("or_", mathMLstring)
return mathMLstring
################################################################################
# Function to get initial amount given a species and an algorithm type #
# Need to pass to this a libsbml species object and a type an integration type #
################################################################################
def getSpeciesValue(species, intType):
if species.isSetInitialAmount() and species.isSetInitialConcentration():
if intType==ODE or intType==SDE:
return species.getInitialConcentration()
else: #implies intType = Gillespie
return species.getInitialAmount()
if species.isSetInitialAmount():
return species.getInitialAmount()
else:
return species.getInitialConcentration()
##########################################
#Rename all parameters and species #
##########################################
def rename(node,name,new_name):
typ = node.getType()
if (typ==AST_NAME or typ==AST_NAME_TIME):
nme = node.getName()
if nme == name:
node.setName(new_name)
for n in range(0,node.getNumChildren()):
rename(node.getChild(n),name,new_name)
return node
##############
# The PARSER #
##############
def importSBMLCUDA(source,integrationType,ModelName=None,method=None,outpath=""):
"""
***** args *****
source:
a list of strings.
Each tuple entry describes a SBML file to be parsed.
integrationType:
a list of strings.
The length of this tuple is determined by the number of SBML
files to be parsed. Each entry describes the simulation algorithm.
Possible algorithms are:
ODE --- for deterministic systems; solved with odeint (scipy)
SDE --- for stochastic systems; solved with sdeint (abc)
MJP --- for staochastic systems; solved with GillespieAlgorithm (abc)
***** kwargs *****
ModelName:
a list of strings.
ModelName describes the names of the parsed model files.
method:
an integer number.
Type of noise in a stochastic system.
(Only implemented for stochastic systems solved with sdeint.)
Possible options are:
1 --- default
2 --- Ornstein-Uhlenbeck
3 --- geometric Brownian motion
"""
#regular expressions for detecting integration types
g=re.compile('MJP')
o=re.compile('ODE')
s=re.compile('SDE')
#output general properties
#output = []
#check that you have appropriate lengths of integration types and sources
#(need equal lengths)
if(not(len(source)==len(integrationType))):
print "\nError: Number of sources is not the same as number of integrationTypes!\n"
#check that you have model names,
#if not the models will be named model1, model2, etc
else:
if(ModelName==None):
ModelName=[]
for x in range(0,len(source)):
ModelName.append("model"+repr(x+1))
#if no method is specified and the integrationType is "SDE"
#the method type defaults to 1
for models in range(0,len(source)):
intType = integrationType[models]
if method==None:
if s.match(integrationType[models]):
method=[]
for x in range(0, len(source)):
method.append(1)
#All the below should happen for each model
#Arguments to pass to the writing functions:
#species IDs
#species concentrations (initial values from model)
#reactions in the form of kinetic law list
#stoichiometric matrix
#parameters
#values of parameters
#name of output file
#list of functions if they need to be defined at the top of the written .py file
#I think that we can pass parameters directly to the writing functions, non?
parameterId=[]
parameterId2=[]
parameter=[]
listOfParameter=[]
#Likewise species?
speciesId=[]
speciesId2=[]
species=[]
## r=re.compile('.mod')
## if(r.search(source)):
## old_source=source
## source=r.sub(".xml",old_source)
## call='python mod2sbml.py '+old_source+' > '+ source
## os.system(call)
#Get the model
reader=SBMLReader()
document=reader.readSBML(source[models])
model=document.getModel()
#get basic model properties
numSpeciesTypes=model.getNumSpeciesTypes()
numSpecies=model.getNumSpecies()
numReactions=model.getNumReactions()
numGlobalParameters=model.getNumParameters()
numFunctions=model.getNumFunctionDefinitions()
stoichiometricMatrix=empty([numSpecies, numReactions])
#output.append((numReactions,numGlobalParameters+1,numSpecies))
#################################################################################################
# get compartment volume/size - if it is set, pass as parameter with corresponding Id and value #
#################################################################################################
listOfCompartments = model.getListOfCompartments()
comp=0
for i in range(0, len(listOfCompartments)):
# listOfCompartments[i].setId('compartment'+repr(i+1))
if listOfCompartments[i].isSetVolume():
comp=comp+1
parameterId.append(listOfCompartments[i].getId())
parameterId2.append('compartment'+repr(i+1))
parameter.append(listOfCompartments[i].getVolume())
listOfParameter.append(model.getCompartment(i))
#########################
# get global parameters #
#########################
for i in range(0,numGlobalParameters):
parameterId.append(model.getParameter(i).getId())
if ((len(parameterId2)-comp)<9):
parameterId2.append('parameter0'+repr(i+1))
else:
parameterId2.append('parameter'+repr(i+1))
parameter.append(model.getParameter(i).getValue())
listOfParameter.append(model.getParameter(i))
###############
# get species #
###############
#Empty matrix to hold reactants
reactant=[]
#Empty matrix to hold products
product=[]
#Empty matrix to hold Species Ids
#Empty matrix to hold the InitValues used going forward
InitValues=[]
S1 = []
S2 = []
#Get a list of species
listOfSpecies = model.getListOfSpecies()
#Make the matrices long enough
for k in range(0, len(listOfSpecies)):
species.append(listOfSpecies[k])
speciesId.append(listOfSpecies[k].getId())
if (len(speciesId2)<9):
speciesId2.append('species0'+repr(k+1))
else:
speciesId2.append('species'+repr(k+1))
#get the initial value
#Need to fix this part
#So that it will take getInitialConcentration
#or getInitialValue as appropriate
InitValues.append(getSpeciesValue(listOfSpecies[k],intType))
#I'm not really sure what this part is doing
#Hopefully it will become more clear later
S1.append(0.0)
S2.append(0.0)
#placeholder in reactant matrix for this species
reactant.append(0)
#placeholder in product matrix for this species
product.append(0)
###############################
# analyse the model structure #
###############################
reaction=[]
numReactants=[]
numProducts=[]
kineticLaw=[]
numLocalParameters=[]
#Get the list of reactions
listOfReactions = model.getListOfReactions()
#For every reaction
for i in range(0, len(listOfReactions)):
#What does this part do?
for a in range(0, len(species)):
#what do S1 and S2 represent?
#S1 is something to do with stoichimetry of reactants
#At the moment S1 and S2 are as long as len(species)
S1[a]=0.0
#S2 is something to do with stoichiometry of products
S2[a]=0.0
numReactants.append(listOfReactions[i].getNumReactants())
numProducts.append(listOfReactions[i].getNumProducts())
kineticLaw.append(listOfReactions[i].getKineticLaw().getFormula())
numLocalParameters.append(listOfReactions[i].getKineticLaw().getNumParameters())
for j in range(0, numReactants[i]):
reactant[j]=listOfReactions[i].getReactant(j)
for k in range(0,len(species)):
if (reactant[j].getSpecies()==species[k].getId()):
S1[k]=reactant[j].getStoichiometry()
for l in range(0,numProducts[i]):
product[l]=listOfReactions[i].getProduct(l)
for k in range(0,len(species)):
if (product[l].getSpecies()==species[k].getId()):
S2[k]=product[l].getStoichiometry()
for m in range(0, len(species)):
stoichiometricMatrix[m][i]=-S1[m]+S2[m]
for n in range(0,numLocalParameters[i]):
parameterId.append(listOfReactions[i].getKineticLaw().getParameter(n).getId())
if ((len(parameterId2)-comp)<10):
parameterId2.append('parameter0'+repr(len(parameterId)-comp))
else:
parameterId2.append('parameter'+repr(len(parameterId)-comp))
parameter.append(listOfReactions[i].getKineticLaw().getParameter(n).getValue())
listOfParameter.append(listOfReactions[i].getKineticLaw().getParameter(n))
name=listOfReactions[i].getKineticLaw().getParameter(n).getId()
new_name='parameter'+repr(len(parameterId)-comp)
node=model.getReaction(i).getKineticLaw().getMath()
new_node=rename(node,name,new_name)
kineticLaw[i]=formulaToString(new_node)
for n in range(0,comp):
name=parameterId[n]
new_name='compartment'+repr(n+1)
node=model.getReaction(i).getKineticLaw().getMath()
new_node=rename(node,name,new_name)
kineticLaw[i]=formulaToString(new_node)
#####################
# analyse functions #
#####################
#Get the list of functions
listOfFunctions = model.getListOfFunctionDefinitions()
FunctionArgument=[]
FunctionBody=[]
for fun in range(0,len(listOfFunctions)):
FunctionArgument.append([])
for funArg in range(0, listOfFunctions[fun].getNumArguments()):
FunctionArgument[fun].append(formulaToString(listOfFunctions[fun].getArgument(funArg)))
FunctionBody.append(formulaToString(listOfFunctions[fun].getBody()))
for fun in range(0, len(listOfFunctions)):
for funArg in range(0,listOfFunctions[fun].getNumArguments()):
name=FunctionArgument[fun][funArg]
node=listOfFunctions[fun].getBody()
new_node=rename(node,name,"a"+repr(funArg+1))
FunctionBody[fun]=formulaToString(new_node)
FunctionArgument[fun][funArg]='a'+repr(funArg+1)
#################
# analyse rules #
#################
#Get the list of rules
ruleFormula=[]
ruleVariable=[]
listOfRules = model.getListOfRules()
for ru in range(0,len(listOfRules)):
ruleFormula.append(listOfRules[ru].getFormula())
ruleVariable.append(listOfRules[ru].getVariable())
##################
# analyse events #
##################
listOfEvents = model.getListOfEvents()
EventCondition=[]
EventVariable=[]
EventFormula=[]
# listOfAssignmentRules=[]
for eve in range(0,len(listOfEvents)):
EventCondition.append(formulaToString(listOfEvents[eve].getTrigger().getMath()))
listOfAssignmentRules=listOfEvents[eve].getListOfEventAssignments()
EventVariable.append([])
EventFormula.append([])
for ru in range(0, len(listOfAssignmentRules)):
EventVariable[eve].append(listOfAssignmentRules[ru].getVariable())
EventFormula[eve].append(formulaToString(listOfAssignmentRules[ru].getMath()))
########################################################################
#rename math expressions from python to cuda #
########################################################################
mathPython = []
mathCuda = []
mathPython.append('log10')
mathPython.append('acos')
mathPython.append('asin')
mathPython.append('atan')
mathPython.append('time')
mathPython.append('exp')
mathPython.append('sqrt')
mathPython.append('pow')
mathPython.append('log')
mathPython.append('sin')
mathPython.append('cos')
mathPython.append('ceil')
mathPython.append('floor')
mathPython.append('tan')
mathCuda.append('__log10f')
mathCuda.append('acosf')
mathCuda.append('asinf')
mathCuda.append('atanf')
if o.match(integrationType[models]):
mathCuda.append('t[0]')
if g.match(integrationType[models]):
mathCuda.append('t')
s=re.compile('SDE')
if s.match(integrationType[models]):
mathCuda.append('t')
mathCuda.append('__expf')
mathCuda.append('sqrtf')
mathCuda.append('__powf')
mathCuda.append('__logf')
mathCuda.append('__sinf')
mathCuda.append('__cosf')
mathCuda.append('ceilf')
mathCuda.append('floorf')
mathCuda.append('__tanf')
########################################################################
#rename parameters and species in reactions, events, rules #
########################################################################
NAMES=[[],[]]
NAMES[0].append(parameterId)
NAMES[0].append(parameterId2)
NAMES[1].append(speciesId)
NAMES[1].append(speciesId2)
for nam in range(0,2):
for i in range(0, len(NAMES[nam][0])):
name=NAMES[nam][0][i]
new_name=NAMES[nam][1][i]
for k in range(0, numReactions):
node=model.getReaction(k).getKineticLaw().getMath()
new_node=rename(node,name,new_name)
kineticLaw[k]=formulaToString(new_node)
for k in range(0,len(listOfRules)):
node=listOfRules[k].getMath()
new_node=rename(node,name,new_name)
ruleFormula[k]=formulaToString(new_node)
if ruleVariable[k]==name: ruleVariable[k]=new_name
for k in range(0,len(listOfEvents)):
node=listOfEvents[k].getTrigger().getMath()
new_node=rename(node,name,new_name)
EventCondition[k]=formulaToString(new_node)
listOfAssignmentRules=listOfEvents[k].getListOfEventAssignments()
for cond in range(0, len(listOfAssignmentRules)):
node=listOfAssignmentRules[cond].getMath()
new_node=rename(node,name,new_name)
EventFormula[k][cond]=formulaToString(new_node)
if EventVariable[k][cond]==name: EventVariable[k][cond]=new_name
for nam in range(0,len(mathPython)):
for k in range(0,len(kineticLaw)):
if re.search(mathPython[nam],kineticLaw[k]):
s = kineticLaw[k]
s = re.sub(mathPython[nam],mathCuda[nam],s)
kineticLaw[k]=s
for k in range(0,len(ruleFormula)):
if re.search(mathPython[nam],ruleFormula[k]):
s = ruleFormula[k]
s = re.sub(mathPython[nam],mathCuda[nam],s)
ruleFormula[k]=s
for k in range(0,len(EventFormula)):
for cond in range(0, len(listOfAssignmentRules)):
if re.search(mathPython[nam],EventFormula[k][cond]):
s = EventFormula[k][cond]
s = re.sub(mathPython[nam],mathCuda[nam],s)
EventFormula[k][cond]=s
for k in range(0,len(EventCondition)):
if re.search(mathPython[nam],EventCondition[k]):
s = EventCondition[k]
s = re.sub(mathPython[nam],mathCuda[nam],s)
EventCondition[k]=s
for k in range(0,len(FunctionBody)):
if re.search(mathPython[nam],FunctionBody[k]):
s = FunctionBody[k]
s = re.sub(mathPython[nam],mathCuda[nam],s)
FunctionBody[k]=s
for fun in range(0, len(listOfFunctions)):
for k in range(0,len(FunctionArgument[fun])):
if re.search(mathPython[nam],FunctionArgument[fun][k]):
s = FunctionArgument[fun][k]
s = re.sub(mathPython[nam],mathCuda[nam],s)
FunctionArgument[fun][k]=s
##########################
# call writing functions #
##########################
s=re.compile('SDE')
if o.match(integrationType[models]):
write_ODECUDA(stoichiometricMatrix, kineticLaw, species, numSpecies, numGlobalParameters+1, numReactions, speciesId2, listOfParameter, parameterId2, parameter, InitValues, ModelName[models], listOfFunctions,FunctionArgument, FunctionBody, listOfRules, ruleFormula, ruleVariable, listOfEvents, EventCondition, EventVariable,EventFormula, outpath)
if s.match(integrationType[models]):
write_SDECUDA(stoichiometricMatrix, kineticLaw, species, numSpecies, numGlobalParameters+1, numReactions, speciesId2,listOfParameter, parameterId2, parameter,InitValues,ModelName[models], listOfFunctions, FunctionArgument, FunctionBody, listOfRules, ruleFormula, ruleVariable, listOfEvents, EventCondition, EventVariable, EventFormula, outpath)
if g.match(integrationType[models]):
write_GillespieCUDA(stoichiometricMatrix, kineticLaw, numSpecies, numGlobalParameters+1, numReactions, species, parameterId2, InitValues, speciesId2,ModelName[models], listOfFunctions,FunctionArgument,FunctionBody, listOfRules, ruleFormula, ruleVariable, listOfEvents, EventCondition, EventVariable, EventFormula, outpath)
# output is:
# (numReactions,numGlobalParameters,numSpecies)
# return output
| 43.299816
| 362
| 0.478831
| 6,882
| 70,622
| 4.848736
| 0.07338
| 0.063142
| 0.107165
| 0.03758
| 0.740208
| 0.709521
| 0.682729
| 0.675387
| 0.662381
| 0.657586
| 0
| 0.007903
| 0.380052
| 70,622
| 1,630
| 363
| 43.32638
| 0.75426
| 0.126929
| 0
| 0.726096
| 0
| 0.001992
| 0.056804
| 0.002115
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.00498
| null | null | 0.000996
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
cab010382f312ec62a353e9ea450704175f2f918
| 70
|
py
|
Python
|
How_to_manage_data/pop_quiz.py
|
OscarFM014/IntroCS
|
335b9eb9bd900240c813e137b4290cc7bf32283d
|
[
"MIT"
] | null | null | null |
How_to_manage_data/pop_quiz.py
|
OscarFM014/IntroCS
|
335b9eb9bd900240c813e137b4290cc7bf32283d
|
[
"MIT"
] | null | null | null |
How_to_manage_data/pop_quiz.py
|
OscarFM014/IntroCS
|
335b9eb9bd900240c813e137b4290cc7bf32283d
|
[
"MIT"
] | null | null | null |
p =[1,2,5]
x = p.pop()
#y = p.pop()
#p.append(y)
p.append(x)
print p
| 8.75
| 12
| 0.514286
| 18
| 70
| 2
| 0.5
| 0.222222
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.052632
| 0.185714
| 70
| 7
| 13
| 10
| 0.578947
| 0.314286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0
| null | null | 0.25
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
cab971a0a59b0fb545d0234ae1d7ad226568ed44
| 81
|
py
|
Python
|
tests/fixtures/etc/my_app/settings.d/00_prod1.py
|
peopledoc/django-compose-settings
|
83ce81d3f0de224efcdf632a7ba571759cf8662d
|
[
"MIT"
] | 2
|
2018-05-31T12:46:46.000Z
|
2020-06-30T19:21:02.000Z
|
tests/fixtures/etc/my_app/settings.d/00_prod1.py
|
peopledoc/django-compose-settings
|
83ce81d3f0de224efcdf632a7ba571759cf8662d
|
[
"MIT"
] | null | null | null |
tests/fixtures/etc/my_app/settings.d/00_prod1.py
|
peopledoc/django-compose-settings
|
83ce81d3f0de224efcdf632a7ba571759cf8662d
|
[
"MIT"
] | 2
|
2020-06-01T14:06:15.000Z
|
2021-07-06T11:46:26.000Z
|
from __settings__ import INSTALLED_APPS
INSTALLED_APPS += (
'etc.prod1',
)
| 11.571429
| 39
| 0.716049
| 9
| 81
| 5.777778
| 0.777778
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015152
| 0.185185
| 81
| 6
| 40
| 13.5
| 0.772727
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.25
| 0
| 0.25
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
cace144d6afe93e7acc907b7adcfbf417553922d
| 183
|
py
|
Python
|
tests/test_events.py
|
hemangandhi/lcs
|
9dc96ae51b6389a72ee36cb205b4a2372858df1e
|
[
"MIT"
] | null | null | null |
tests/test_events.py
|
hemangandhi/lcs
|
9dc96ae51b6389a72ee36cb205b4a2372858df1e
|
[
"MIT"
] | null | null | null |
tests/test_events.py
|
hemangandhi/lcs
|
9dc96ae51b6389a72ee36cb205b4a2372858df1e
|
[
"MIT"
] | null | null | null |
from testing_utils import *
import config
from src import event
# we should actually "create_user" to get proper password hashes
from src import authorize
import pytest
import mock
| 18.3
| 64
| 0.814208
| 28
| 183
| 5.25
| 0.714286
| 0.095238
| 0.176871
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.163934
| 183
| 9
| 65
| 20.333333
| 0.960784
| 0.338798
| 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
| 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
| 4
|
cad92f3f3c535fe826c75476d06a4fd638ccf721
| 283
|
py
|
Python
|
src/garage/torch/policies/__init__.py
|
parachutel/garage
|
e9d4301278f5dd31e3cbd20df1422befa2d0b6c4
|
[
"MIT"
] | 1
|
2019-07-31T06:53:38.000Z
|
2019-07-31T06:53:38.000Z
|
src/garage/torch/policies/__init__.py
|
KornbergFresnel/garage
|
f4a6271edd0f9c280c306d1f0bbf4bc1591ab85e
|
[
"MIT"
] | null | null | null |
src/garage/torch/policies/__init__.py
|
KornbergFresnel/garage
|
f4a6271edd0f9c280c306d1f0bbf4bc1591ab85e
|
[
"MIT"
] | null | null | null |
"""PyTorch Policies."""
from garage.torch.policies.base import Policy
from garage.torch.policies.deterministic_policy import DeterministicPolicy
from garage.torch.policies.gaussian_mlp_policy import GaussianMLPPolicy
__all__ = ['DeterministicPolicy', 'GaussianMLPPolicy', 'Policy']
| 40.428571
| 74
| 0.833922
| 30
| 283
| 7.633333
| 0.466667
| 0.131004
| 0.196507
| 0.30131
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.070671
| 283
| 6
| 75
| 47.166667
| 0.870722
| 0.060071
| 0
| 0
| 0
| 0
| 0.161538
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 0
| 0
| 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
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
caf484fbe50613cc4c5e821866fe536ea6c65b87
| 689
|
py
|
Python
|
gym_bot_app/commands/__init__.py
|
wolfranAlpha/GymBot
|
3c5d9976884b6c9073bb524a46981f86e43f5ea8
|
[
"Apache-2.0"
] | 8
|
2018-12-02T10:15:19.000Z
|
2022-01-27T09:03:26.000Z
|
gym_bot_app/commands/__init__.py
|
wolfranAlpha/GymBot
|
3c5d9976884b6c9073bb524a46981f86e43f5ea8
|
[
"Apache-2.0"
] | 4
|
2021-02-10T02:20:38.000Z
|
2021-10-19T20:54:21.000Z
|
gym_bot_app/commands/__init__.py
|
wolfranAlpha/GymBot
|
3c5d9976884b6c9073bb524a46981f86e43f5ea8
|
[
"Apache-2.0"
] | 9
|
2018-07-27T09:05:43.000Z
|
2022-01-24T12:18:38.000Z
|
from gym_bot_app.commands.command import Command
from gym_bot_app.commands.admin import AdminCommand
from gym_bot_app.commands.select_days import SelectDaysCommand
from gym_bot_app.commands.my_days import MyDaysCommand
from gym_bot_app.commands.set_creature import SetCreatureCommand
from gym_bot_app.commands.my_statistics import MyStatisticsCommand
from gym_bot_app.commands.bot_statistics import BotStatisticsCommand
from gym_bot_app.commands.trained import TrainedCommand
from gym_bot_app.commands.all_training_trainees import AllTrainingTraineesCommand
from gym_bot_app.commands.ranking import RankingCommand
from gym_bot_app.commands.motivation_quotes import MotivationQuotesCommand
| 57.416667
| 81
| 0.904209
| 96
| 689
| 6.177083
| 0.322917
| 0.129848
| 0.185497
| 0.241147
| 0.39629
| 0.077572
| 0
| 0
| 0
| 0
| 0
| 0
| 0.063861
| 689
| 11
| 82
| 62.636364
| 0.91938
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1b30c1f6ca94226731ec74647a0bad7ed4f446d6
| 58
|
py
|
Python
|
Stream Tool/Resources/Scripts/RoAUpdatePlayerJson.py
|
Ateozc/RoA-Stream-Tool
|
c2e90d8ac2a6b2604016e11c6bd9210b37f39aa8
|
[
"MIT"
] | null | null | null |
Stream Tool/Resources/Scripts/RoAUpdatePlayerJson.py
|
Ateozc/RoA-Stream-Tool
|
c2e90d8ac2a6b2604016e11c6bd9210b37f39aa8
|
[
"MIT"
] | null | null | null |
Stream Tool/Resources/Scripts/RoAUpdatePlayerJson.py
|
Ateozc/RoA-Stream-Tool
|
c2e90d8ac2a6b2604016e11c6bd9210b37f39aa8
|
[
"MIT"
] | null | null | null |
from RoAScripts import *
update_player_json(sys.argv[1])
| 14.5
| 31
| 0.793103
| 9
| 58
| 4.888889
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.019231
| 0.103448
| 58
| 4
| 31
| 14.5
| 0.826923
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1b4ed80c7618e872a85caf6e76439e54bdb57dff
| 56
|
py
|
Python
|
list 4.py
|
keerthana1502/python_practice
|
8c0499e014826af78f9a88730551ace3fa79686d
|
[
"bzip2-1.0.6"
] | null | null | null |
list 4.py
|
keerthana1502/python_practice
|
8c0499e014826af78f9a88730551ace3fa79686d
|
[
"bzip2-1.0.6"
] | null | null | null |
list 4.py
|
keerthana1502/python_practice
|
8c0499e014826af78f9a88730551ace3fa79686d
|
[
"bzip2-1.0.6"
] | null | null | null |
a=[5,20,15,20,25,50,20]
b=set(a)
b.remove(20)
print(b)
| 9.333333
| 23
| 0.607143
| 16
| 56
| 2.125
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.294118
| 0.089286
| 56
| 5
| 24
| 11.2
| 0.372549
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.25
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
1b57173accf65fbc2ce58e5a17e496b08cec15c5
| 81
|
py
|
Python
|
apps/EHD/gauss/__init__.py
|
rboman/progs
|
c60b4e0487d01ccd007bcba79d1548ebe1685655
|
[
"Apache-2.0"
] | 2
|
2021-12-12T13:26:06.000Z
|
2022-03-03T16:14:53.000Z
|
apps/EHD/gauss/__init__.py
|
rboman/progs
|
c60b4e0487d01ccd007bcba79d1548ebe1685655
|
[
"Apache-2.0"
] | 5
|
2019-03-01T07:08:46.000Z
|
2019-04-28T07:32:42.000Z
|
apps/EHD/gauss/__init__.py
|
rboman/progs
|
c60b4e0487d01ccd007bcba79d1548ebe1685655
|
[
"Apache-2.0"
] | 2
|
2017-12-13T13:13:52.000Z
|
2019-03-13T20:08:15.000Z
|
# -*- coding: utf-8 -*-
# gauss MODULE initialization file
from gaussi import *
| 16.2
| 34
| 0.679012
| 10
| 81
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015152
| 0.185185
| 81
| 4
| 35
| 20.25
| 0.818182
| 0.666667
| 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
| 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
| 4
|
1b6ef4b641ed4a2712597c941f1ec3280245c22f
| 575
|
py
|
Python
|
src/api/pdi/application/operation/GetDataOperationJobExecutionLogList/GetDataOperationJobExecutionLogListQuery.py
|
ahmetcagriakca/pythondataintegrator
|
079b968d6c893008f02c88dbe34909a228ac1c7b
|
[
"MIT"
] | 1
|
2020-12-18T21:37:28.000Z
|
2020-12-18T21:37:28.000Z
|
src/api/pdi/application/operation/GetDataOperationJobExecutionLogList/GetDataOperationJobExecutionLogListQuery.py
|
ahmetcagriakca/pythondataintegrator
|
079b968d6c893008f02c88dbe34909a228ac1c7b
|
[
"MIT"
] | null | null | null |
src/api/pdi/application/operation/GetDataOperationJobExecutionLogList/GetDataOperationJobExecutionLogListQuery.py
|
ahmetcagriakca/pythondataintegrator
|
079b968d6c893008f02c88dbe34909a228ac1c7b
|
[
"MIT"
] | 1
|
2020-12-18T21:37:31.000Z
|
2020-12-18T21:37:31.000Z
|
from dataclasses import dataclass
from pdip.cqrs import IQuery
from pdi.application.operation.GetDataOperationJobExecutionLogList.GetDataOperationJobExecutionLogListRequest import \
GetDataOperationJobExecutionLogListRequest
from pdi.application.operation.GetDataOperationJobExecutionLogList.GetDataOperationJobExecutionLogListResponse import \
GetDataOperationJobExecutionLogListResponse
@dataclass
class GetDataOperationJobExecutionLogListQuery(IQuery[GetDataOperationJobExecutionLogListResponse]):
request: GetDataOperationJobExecutionLogListRequest = None
| 44.230769
| 119
| 0.897391
| 33
| 575
| 15.636364
| 0.515152
| 0.027132
| 0.069767
| 0.104651
| 0.24031
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.069565
| 575
| 12
| 120
| 47.916667
| 0.964486
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.444444
| 0
| 0.666667
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
1b7bb6ce31750ec7d3dfd9c42dfab0ac6a5dde69
| 270
|
py
|
Python
|
website_1/manage.py
|
indoorConstructionMan/Django
|
ebb38a14fbdedd8d064141e3fb1bf52536a9a4f3
|
[
"Apache-2.0"
] | null | null | null |
website_1/manage.py
|
indoorConstructionMan/Django
|
ebb38a14fbdedd8d064141e3fb1bf52536a9a4f3
|
[
"Apache-2.0"
] | null | null | null |
website_1/manage.py
|
indoorConstructionMan/Django
|
ebb38a14fbdedd8d064141e3fb1bf52536a9a4f3
|
[
"Apache-2.0"
] | null | null | null |
#!/usr/bin/env python
#workon myproject
import os
import sys
if __name__ == "__main__":
os.environ.setdefault("DJANGO_SETTINGS_MODULE", "website_1.settings")
from django.core.management import execute_from_command_line
execute_from_command_line(sys.argv)
| 22.5
| 73
| 0.777778
| 37
| 270
| 5.216216
| 0.702703
| 0.11399
| 0.186529
| 0.227979
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004237
| 0.125926
| 270
| 11
| 74
| 24.545455
| 0.813559
| 0.133333
| 0
| 0
| 0
| 0
| 0.206897
| 0.094828
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1b7d660069e5e73f8a8749b68457de22fcfb0b16
| 234
|
py
|
Python
|
dl_lib/modeling/meta_arch/__init__.py
|
AndysonYs/DynamicRouting
|
bc8c43be74bf0c245f236d2303f3c8522d83265a
|
[
"Apache-2.0"
] | 122
|
2020-10-07T14:23:53.000Z
|
2022-03-09T03:56:49.000Z
|
dl_lib/modeling_rooting/meta_arch/__init__.py
|
baiwuchang/CLM_DR
|
6ca572680e1f829f2cb181f192bc30e4fed69e36
|
[
"MIT"
] | 22
|
2020-10-23T14:04:13.000Z
|
2022-03-25T01:39:06.000Z
|
dl_lib/modeling_rooting/meta_arch/__init__.py
|
baiwuchang/CLM_DR
|
6ca572680e1f829f2cb181f192bc30e4fed69e36
|
[
"MIT"
] | 21
|
2020-10-10T02:43:33.000Z
|
2022-03-17T06:52:18.000Z
|
# -*- coding: utf-8 -*-
# Copyright (c) Facebook, Inc. and its affiliates. All Rights Reserved
# import all the meta_arch, so they will be registered
from .semantic_seg import SemanticSegmentor
from .dynamic4seg import DynamicNet4Seg
| 39
| 70
| 0.773504
| 32
| 234
| 5.59375
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.015
| 0.145299
| 234
| 6
| 71
| 39
| 0.88
| 0.611111
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
| 4
|
1b977f88f356c00ab15d387b2cb075136c1b074c
| 29,263
|
py
|
Python
|
tests/snc/environments/test_closed_loop_crw.py
|
dmcnamee/snc
|
c2da8c1e9ecdc42c59b9de73224b3d50ee1c9786
|
[
"Apache-2.0"
] | 5
|
2021-03-24T16:23:10.000Z
|
2021-11-17T12:44:51.000Z
|
tests/snc/environments/test_closed_loop_crw.py
|
dmcnamee/snc
|
c2da8c1e9ecdc42c59b9de73224b3d50ee1c9786
|
[
"Apache-2.0"
] | 3
|
2021-03-26T01:16:08.000Z
|
2021-05-08T22:06:47.000Z
|
tests/snc/environments/test_closed_loop_crw.py
|
dmcnamee/snc
|
c2da8c1e9ecdc42c59b9de73224b3d50ee1c9786
|
[
"Apache-2.0"
] | 2
|
2021-03-24T17:20:06.000Z
|
2021-04-19T09:01:12.000Z
|
from collections import deque, defaultdict
import numpy as np
import pytest
from snc.environments.closed_loop_crw import ClosedLoopCRW
import snc.environments.examples as examples
from snc.environments.job_generators.discrete_review_job_generator import \
DeterministicDiscreteReviewJobGenerator
from snc.environments.job_generators.scaled_bernoulli_services_poisson_arrivals_generator import \
ScaledBernoulliServicesPoissonArrivalsGenerator
from snc.environments.state_initialiser import DeterministicCRWStateInitialiser
def build_closed_loop_env_2_demand_buffers(
demand_to_supplier_routes,
constituency_matrix,
initial_state=np.zeros((5, 1))
):
ind_surplus_buffers = [1, 3]
job_gen_seed = 42
mu = 1.5
mud = 3
mus = 1.5
alpha = 0.95
cost_per_buffer = np.array([[1], [2], [5], [3], [8]])
demand_rate = np.array([[0], [0], [alpha], [0], [alpha]])
buffer_processing_matrix = np.array([[-mu, -mu/3, 0, mus, 0, 0],
[2*mu/3, 0, -mud, 0, 0, 0],
[0, 0, -mud, 0, 0, 0],
[mu/3, mu/3, 0, 0, -mud, mus/3],
[0, 0, 0, 0, -mud, 0]])
job_generator = ScaledBernoulliServicesPoissonArrivalsGenerator(demand_rate,
buffer_processing_matrix,
job_gen_seed=job_gen_seed)
state_initialiser = DeterministicCRWStateInitialiser(initial_state)
cl_env = ClosedLoopCRW(
demand_to_supplier_routes,
ind_surplus_buffers,
cost_per_buffer,
np.ones_like(demand_rate) * np.inf,
constituency_matrix,
job_generator,
state_initialiser
)
return cl_env
def build_closed_loop_single_station_demand_model(initial_state=np.zeros((3, 1)), toa=100):
ind_surplus_buffers = [1]
demand_to_supplier_routes = {2: (2, toa)}
job_gen_seed = 42
mu = 3
mud = 3
mus = 3
alpha = 2
cost_per_buffer = np.array([[1], [2], [5]])
demand_rate = np.array([[0], [0], [alpha]])
buffer_processing_matrix = np.array([[-mu, 0, mus],
[mu, -mud, 0],
[0, -mud, 0]])
job_generator = DeterministicDiscreteReviewJobGenerator(demand_rate,
buffer_processing_matrix,
job_gen_seed,
sim_time_interval=1)
constituency_matrix = np.eye(3)
state_initialiser = DeterministicCRWStateInitialiser(initial_state)
cl_env = ClosedLoopCRW(
demand_to_supplier_routes,
ind_surplus_buffers,
cost_per_buffer,
np.ones_like(demand_rate) * np.inf,
constituency_matrix,
job_generator,
state_initialiser
)
return cl_env
def test_get_supply_and_demand_ids():
demand = (0, 1, 2, 3, 4, 5, 6, 7)
supply = (10, 11, 12, 13, 14, 15, 16, 17)
toa = (20, 21, 22, 23, 24, 25, 26, 27)
demand_to_supplier_routes = {demand[i]: (supply[i], toa[i]) for i in range(8)}
supply_id, demand_id = ClosedLoopCRW.get_supply_and_demand_ids(demand_to_supplier_routes)
assert supply_id == list(supply)
assert demand_id == list(demand)
def test_are_demand_ids_unique():
demand_id = list(range(4))
assert ClosedLoopCRW.are_demand_ids_unique(demand_id)
def test_are_demand_ids_unique_false():
demand_id = [0, 0, 1, 2]
assert not ClosedLoopCRW.are_demand_ids_unique(demand_id)
def test_get_supply_and_demand_ids_repeated_ids():
demand = (0, 1, 2, 3, 4)
supply = (10, 11, 10, 11, 12)
toa = (20, 21, 20, 21, 22)
demand_to_supplier_routes = {demand[i]: (supply[i], toa[i]) for i in range(len(demand))}
supply_id, demand_id = ClosedLoopCRW.get_supply_and_demand_ids(demand_to_supplier_routes)
assert supply_id == [10, 11, 12]
assert demand_id == list(demand)
@pytest.mark.parametrize('supply_ids,demand_ids,env_class', [
([3], [5], examples.double_reentrant_line_with_demand_only_shared_resources_model),
([7, 8], [14, 15], examples.complex_demand_driven_model),
])
def test_is_demand_to_supplier_routes_consistent_with_job_generator_envs(
supply_ids,
demand_ids,
env_class
):
env = env_class()
assert ClosedLoopCRW.is_demand_to_supplier_routes_consistent_with_job_generator(
supply_ids,
demand_ids,
env.constituency_matrix,
env.job_generator.supply_nodes,
env.job_generator.demand_nodes.values()
)
def test_is_supply_ids_consistent_with_job_generator():
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
assert ClosedLoopCRW.is_supply_ids_consistent_with_job_generator(
env.supply_ids,
env.job_generator.supply_nodes,
env.constituency_matrix
)
def test_is_supply_ids_consistent_with_job_generator_false():
supply_ids = [2, 3] # It should be [2, 4]
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
assert not ClosedLoopCRW.is_supply_ids_consistent_with_job_generator(
supply_ids,
env.job_generator.supply_nodes,
env.constituency_matrix
)
def test_initialise_supply_buffers():
supply_id = [0, 11]
supply_buf = ClosedLoopCRW.initialise_supply_buffers(supply_id)
assert supply_buf == {0: 0, 11: 0}
def test_get_activity_supply_resource_association_eye():
supply_nodes = [(0, 1), (1, 2)]
constituency_matrix = np.eye(4)
activity_to_resource, resource_to_activity = \
ClosedLoopCRW.get_activity_supply_resource_association(
supply_nodes,
constituency_matrix
)
assert activity_to_resource == {1: 1, 2: 2}
assert resource_to_activity == {1: [1], 2: [2]}
def test_get_activity_supply_resource_association_only_one_resource():
supply_nodes = [(0, 1), (1, 2)]
constituency_matrix = np.array([[0, 1, 1],
[1, 0, 0]])
activity_to_resource, resource_to_activity = \
ClosedLoopCRW.get_activity_supply_resource_association(
supply_nodes,
constituency_matrix
)
assert activity_to_resource == {1: 0, 2: 0}
assert resource_to_activity == {0: [1, 2]}
def test_get_activity_supply_resource_association_two_resources():
supply_nodes = [(0, 1), (1, 2), (2, 0)]
constituency_matrix = np.array([[1, 1, 0],
[0, 0, 1]])
activity_to_resource, resource_to_activity = \
ClosedLoopCRW.get_activity_supply_resource_association(
supply_nodes,
constituency_matrix
)
assert activity_to_resource == {0: 0, 1: 0, 2: 1}
assert resource_to_activity == {0: [0, 1], 1: [2]}
def test_get_activity_supply_resource_association_action_belongs_to_two_resources():
supply_nodes = [(0, 1)]
constituency_matrix = np.array([[1, 1],
[0, 1]])
with pytest.raises(AssertionError):
_, _ = ClosedLoopCRW.get_activity_supply_resource_association(
supply_nodes,
constituency_matrix
)
def test_get_supply_activity_to_buffer_association_only_one_supply_activity():
supply_nodes = [(0, 2)]
activity_to_buffer = ClosedLoopCRW.get_supply_activity_to_buffer_association(supply_nodes)
assert activity_to_buffer == {2: 0}
def test_get_supply_activity_to_buffer_association_multiple_supply_activities():
supply_nodes = [(0, 2), (1, 3)]
activity_to_buffer = ClosedLoopCRW.get_supply_activity_to_buffer_association(supply_nodes)
assert activity_to_buffer == {2: 0, 3: 1}
@pytest.mark.parametrize(
's1,s2', [(0, 0), (3, 1), (10, 20)]
)
def test_sum_supplier_outbound(s1, s2):
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
routing_matrix = np.zeros_like(env.job_generator.buffer_processing_matrix)
routing_matrix[0, 3] = s1
routing_matrix[3, 5] = s2
sum_outbound = env.sum_supplier_outbound(routing_matrix)
assert sum_outbound == {2: s1, 4: s2}
@pytest.mark.parametrize(
's1,s2', [(0, 0), (3, 1), (10, 20)]
)
def test_sum_supplier_outbound_one_resource_multiple_routes(s1, s2):
demand_to_supplier_routes = {2: (2, 100), 4: (2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 1, 0]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
routing_matrix = np.zeros_like(env.job_generator.buffer_processing_matrix)
routing_matrix[0, 3] = s1
routing_matrix[3, 5] = s2
sum_outbound = env.sum_supplier_outbound(routing_matrix)
assert sum_outbound == {2: s1 + s2}
def get_truncated_val(s, a):
return s if s < a else a
@pytest.mark.parametrize(
's1,s2,a1,a2',
[
(0, 0, 0, 0), # Empty and none available.
(0, 0, 1, 1), # Empty but available.
(3, 2, 0, 0), # Some but none available.
(3, 2, 3, 2), # Exactly what's available.
(3, 2, 2, 1), # More than available.
(3, 2, 4, 3), # Less than available.
]
)
def test_truncate_routing_matrix_supplier(s1, s2, a1, a2):
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
routing_matrix = np.zeros_like(env.job_generator.buffer_processing_matrix)
routing_matrix[0, 3] = s1
routing_matrix[3, 5] = s2
env.supply_buffers[2] = a1
env.supply_buffers[4] = a2
new_routing_matrix = env.truncate_routing_matrix_supplier(2, routing_matrix, a1)
assert new_routing_matrix[0, 3] == get_truncated_val(s1, a1)
new_routing_matrix = env.truncate_routing_matrix_supplier(4, new_routing_matrix, a2)
assert new_routing_matrix[3, 5] == get_truncated_val(s2, a2)
@pytest.mark.parametrize(
's1,s2,a',
[
(0, 0, 0), # Empty and none available.
(0, 0, 1), # Empty but available.
(3, 2, 0), # Some but none available.
(3, 2, 5), # Exactly what's available.
(3, 2, 4), # More than available.
(3, 2, 6), # Less than available.
]
)
def test_truncate_routing_matrix_supplier_one_resource_multiple_routes(s1, s2, a):
demand_to_supplier_routes = {2: (2, 100), 4: (2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 1, 0]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
routing_matrix = np.zeros_like(env.job_generator.buffer_processing_matrix)
routing_matrix[0, 3] = s1
routing_matrix[3, 5] = s2
env.supply_buffers[2] = a
new_routing_matrix = env.truncate_routing_matrix_supplier(2, routing_matrix, a)
assert new_routing_matrix[0, 3] + new_routing_matrix[3, 5] == get_truncated_val(s1 + s2, a)
def get_new_supply_buffers(s, a):
return a - s if s < a else 0
@pytest.mark.parametrize(
's1,s2,a1,a2',
[
(0, 0, 0, 0), # Empty and none available.
(0, 0, 1, 1), # Empty but available.
(3, 2, 0, 0), # Some but none available.
(3, 2, 3, 2), # Exactly what's available.
(3, 2, 2, 1), # More than available.
(3, 2, 4, 3), # Less than available.
]
)
def test_ensure_jobs_conservation(s1, s2, a1, a2):
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
state_plus_arrivals = np.zeros((5, 1))
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
routing_matrix = np.zeros_like(env.job_generator.buffer_processing_matrix)
routing_matrix[0, 3] = s1
routing_matrix[3, 5] = s2
env.supply_buffers[2] = a1
env.supply_buffers[4] = a2
new_routing_matrix = env.ensure_jobs_conservation(routing_matrix, state_plus_arrivals)
assert new_routing_matrix[0, 3] == get_truncated_val(s1, a1)
assert new_routing_matrix[3, 5] == get_truncated_val(s2, a2)
assert env.supply_buffers[2] == get_new_supply_buffers(s1, a1)
assert env.supply_buffers[4] == get_new_supply_buffers(s2, a2)
def test_ensure_jobs_conservation_with_enough_jobs():
state = 3 * np.ones((3, 1))
routing_matrix = np.array([[-3, 0, 3],
[3, -3, 0],
[0, -3, 0]])
env = build_closed_loop_single_station_demand_model()
new_routing_jobs_matrix = env.ensure_jobs_conservation(routing_matrix, state)
assert np.all(new_routing_jobs_matrix == routing_matrix)
def test_ensure_jobs_conservation_with_not_enough_jobs():
state = np.array([[2], [1], [2]])
routing_matrix = np.array([[-3, 0, 3],
[3, -3, 0],
[0, -3, 0]])
env = build_closed_loop_single_station_demand_model()
env.supply_buffers[2] = 1
expected_routing_matrix = np.array([[-2, 0, 1],
[2, -1, 0],
[0, -1, 0]])
new_routing_jobs_matrix = env.ensure_jobs_conservation(routing_matrix, state)
assert np.all(new_routing_jobs_matrix == expected_routing_matrix)
def test_ensure_jobs_conservation_with_zero_jobs():
state = np.zeros((3, 1))
routing_matrix = np.array([[-3, 0, 3],
[3, -3, 0],
[0, -3, 0]])
env = build_closed_loop_single_station_demand_model()
env.supply_buffers[2] = 1
expected_routing_matrix = np.array([[0, 0, 1],
[0, 0, 0],
[0, 0, 0]])
new_routing_jobs_matrix = env.ensure_jobs_conservation(routing_matrix, state)
assert np.all(new_routing_jobs_matrix == expected_routing_matrix)
def test_get_num_items_supply_buff():
demand_to_supplier_routes = {2: (2, 100), 4: (2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 1, 0]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env.supply_buffers[2] = 10
env.supply_buffers[4] = 20
assert env.get_num_items_supply_buff() == 30
def test_get_num_items_supply_buff_init():
demand_to_supplier_routes = {2: (2, 100), 4: (2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 1],
[0, 0, 0, 0, 1, 0]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
assert env.get_num_items_supply_buff() == 0
def test_get_num_items_in_transit_to_suppliers():
supp1 = 2
supp2 = 4
demand_to_supplier_routes = {2: (supp1, 100), 4: (supp2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
toa1 = 10
toa2 = 11
env.in_transit_parcels[toa1].append((supp1, 1))
env.in_transit_parcels[toa2].append((supp2, 7))
assert env.get_num_items_in_transit_to_suppliers() == 8
def test_get_num_items_in_transit_to_suppliers_multiple_in_transit():
supp1 = 2
supp2 = 4
demand_to_supplier_routes = {2: (supp1, 100), 4: (supp2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
toa1 = 10
toa2 = 11
env.in_transit_parcels[toa1].extend([(supp1, 9), (supp1, 1)])
env.in_transit_parcels[toa2].extend([(supp2, 20), (supp1, 10)])
assert env.get_num_items_in_transit_to_suppliers() == 40
def test_get_num_items_in_transit_to_suppliers_init():
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
assert env.get_num_items_in_transit_to_suppliers() == 0
def test_assert_remains_closed_network_empty():
initial_state = np.zeros((5, 1))
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(
demand_to_supplier_routes,
constituency_matrix,
initial_state
)
env.assert_remains_closed_network()
def test_assert_remains_closed_network_false():
initial_state = np.ones((5, 1))
demand_to_supplier_routes = {2: (2, 100), 4: (4, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(
demand_to_supplier_routes,
constituency_matrix,
initial_state
)
env.state[0] = 0 # Remove one item without putting it anywhere else.
with pytest.raises(AssertionError):
env.assert_remains_closed_network()
def test_get_num_items_state_without_demand():
initial_state = 5 * np.ones((5, 1)) # 25 items, 10 in demand buffers.
supp1 = 2
supp2 = 4
demand_to_supplier_routes = {2: (supp1, 100), 4: (supp2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(
demand_to_supplier_routes,
constituency_matrix,
initial_state
)
assert np.all(env.num_initial_items == 15)
def test_assert_remains_closed_network_all_in_transit_and_suppliers():
initial_state = 5 * np.ones((5, 1)) # 25 items, 10 in demand buffers.
supp1 = 2
supp2 = 4
demand_to_supplier_routes = {2: (supp1, 100), 4: (supp2, 300)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(
demand_to_supplier_routes,
constituency_matrix,
initial_state
)
env.state = np.zeros((5, 1))
env.supply_buffers[2] = 1
env.supply_buffers[4] = 2
toa1 = 10
toa2 = 11
env.in_transit_parcels[toa1].extend([(supp1, 3), (supp1, 1)])
env.in_transit_parcels[toa2].extend([(supp2, 2), (supp1, 6)])
env.assert_remains_closed_network()
def test_get_satisfied_demand():
drained_amount = np.array([1, 2, 3, 4, 5])[:, None]
demand_id = [0, 3]
satisfied_demand = ClosedLoopCRW.get_satisfied_demand(drained_amount, demand_id)
assert satisfied_demand == {0: 1, 3: 4}
def test_fill_in_transit_to_suppliers():
initial_state = np.array([10, 4, 3])[:, None]
toa = 200
amount = 7
current_time = 42
env = build_closed_loop_single_station_demand_model(initial_state, toa)
env._t = current_time
satisfied_demand = {2: amount} # From buffer 2, which will be delivered at resource 2.
env.fill_in_transit_to_suppliers(satisfied_demand)
assert env.in_transit_parcels == {current_time + toa: [(2, amount)]}
def test_fill_in_transit_to_suppliers_multiple_parcels():
initial_state = np.array([10, 4, 3])[:, None]
toa = 200
amount1 = 7
amount2 = 14
current_time = 42
env = build_closed_loop_single_station_demand_model(initial_state, toa)
env._t = current_time
env.fill_in_transit_to_suppliers({2: amount1})
env.fill_in_transit_to_suppliers({2: amount2})
assert env.in_transit_parcels == {current_time + toa: [(2, amount1), (2, amount2)]}
def test_fill_in_transit_to_suppliers_multiple_simultaneous_parcels():
toa2 = 100
toa4 = 300
demand_to_supplier_routes = {2: (2, toa2), 4: (4, toa4)}
current_time = 42
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env._t = current_time
env.fill_in_transit_to_suppliers({2: 10, 4: 13})
assert env.in_transit_parcels == {
current_time + toa2: [(2, 10)],
current_time + toa4: [(4, 13)]
}
def test_fill_in_transit_to_suppliers_multiple_resources_multiple_sequential_parcels():
toa2 = 100
toa4 = 300
demand_to_supplier_routes = {2: (2, toa2), 4: (4, toa4)}
current_time = 42
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env._t = current_time
env.fill_in_transit_to_suppliers({2: 10})
env.fill_in_transit_to_suppliers({4: 13})
env._t = current_time + 100
env.fill_in_transit_to_suppliers({2: 14})
assert env.in_transit_parcels == {
current_time + toa2: [(2, 10)],
current_time + toa4: [(4, 13)],
current_time + toa2 + 100: [(2, 14)]
}
def test_fill_supply_buffers_empty_in_transit():
toa2 = 100
toa4 = 300
demand_to_supplier_routes = {2: (2, toa2), 4: (4, toa4)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env.fill_supply_buffers()
assert env.supply_buffers == {2: 0, 4: 0}
assert env.in_transit_parcels == defaultdict(list)
def test_fill_supply_buffers_some_in_transit_but_not_arrived():
amount2 = 10
amount4 = 11
toa2 = 100
toa4 = 300
demand_to_supplier_routes = {2: (2, toa2), 4: (4, toa4)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env.fill_in_transit_to_suppliers({2: amount2, 4: amount4})
env._t = toa2 - 1
env.fill_supply_buffers()
assert env.supply_buffers == {2: 0, 4: 0}
assert env.in_transit_parcels == {toa2: [(2, amount2)], toa4: [(4, amount4)]}
def test_fill_supply_buffers_some_in_transit_only_one_arrived():
toa2 = 100
toa4 = 300
demand_to_supplier_routes = {2: (2, toa2), 4: (4, toa4)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env.fill_in_transit_to_suppliers({2: 10})
env.fill_in_transit_to_suppliers({4: 11})
env._t = toa2
env.fill_supply_buffers()
assert env.supply_buffers == {2: 10, 4: 0}
assert env.in_transit_parcels == {toa4: [(4, 11)]}
def test_fill_supply_buffers_some_in_transit_two_arrived():
toa2 = 100
toa4 = 300
demand_to_supplier_routes = {2: (2, toa2), 4: (4, toa4)}
constituency_matrix = np.array([[1, 1, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0],
[0, 0, 0, 1, 0, 0],
[0, 0, 0, 0, 1, 0],
[0, 0, 0, 0, 0, 1]])
env = build_closed_loop_env_2_demand_buffers(demand_to_supplier_routes, constituency_matrix)
env.fill_in_transit_to_suppliers({4: 11})
env._t = 200
env.fill_in_transit_to_suppliers({2: 10})
env._t = 300
env.fill_supply_buffers()
assert env.supply_buffers == {2: 10, 4: 11}
assert env.in_transit_parcels == defaultdict(list)
def test_step():
env = build_closed_loop_single_station_demand_model(
initial_state=np.array([[10], [5], [3]]),
toa=100
)
action = np.array([[0], [1], [1]])
env.step(action)
# Nothing done in buffer 0. 3 are removed from buffers 1 and 2, but 2 new arrivals at buffer 2.
assert np.all(env.state == np.array([[10], [2], [2]]))
assert env.in_transit_parcels == {101: [(2, 3)]} # Deliver 3 items to resource 2 at time 101.
assert env.supply_buffers == {2: 0}
def test_step_many_steps():
toa = 100
env = build_closed_loop_single_station_demand_model(
initial_state=np.array([[10], [5], [3]]),
toa=toa
)
alpha = env.job_generator.demand_rate[2]
action = np.array([[1], [1], [1]])
env.step(action)
assert np.all(env.state == np.array([[7], [5], [alpha]]))
assert env.in_transit_parcels == {101: [(2, 3)]}
assert env.supply_buffers == {2: 0}
action = np.zeros((3, 1))
for i in range(toa - 1):
env.step(action)
assert np.all(env.state == np.array([[7], [5], [alpha * env.t]]))
assert env.in_transit_parcels == {101: [(2, 3)]}
assert env.supply_buffers == {2: 0}
env.step(action)
assert np.all(env.state == np.array([[7], [5], [env.t * alpha]]))
assert env.in_transit_parcels == defaultdict(list)
assert env.supply_buffers == {2: 3}
| 39.384926
| 99
| 0.568978
| 3,986
| 29,263
| 3.864024
| 0.058204
| 0.059603
| 0.067004
| 0.065446
| 0.840735
| 0.80087
| 0.76516
| 0.729256
| 0.664459
| 0.59713
| 0
| 0.084863
| 0.309401
| 29,263
| 742
| 100
| 39.438005
| 0.677273
| 0.025425
| 0
| 0.597756
| 0
| 0
| 0.002457
| 0.001088
| 0
| 0
| 0
| 0
| 0.110577
| 1
| 0.073718
| false
| 0
| 0.012821
| 0.003205
| 0.092949
| 0
| 0
| 0
| 0
| null | 0
| 0
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| 1
| 1
| 1
| 1
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| null | 0
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
|
0
| 4
|
1b9c3f21614ececcd761077715abfe2491e2c7ba
| 97
|
py
|
Python
|
demo4/module.py
|
HuYuee/python-study
|
28d05b0da0fed210f9da71e179a8894b722b040d
|
[
"MIT"
] | 1
|
2018-05-14T03:45:21.000Z
|
2018-05-14T03:45:21.000Z
|
demo4/module.py
|
HuYuee/python-study
|
28d05b0da0fed210f9da71e179a8894b722b040d
|
[
"MIT"
] | null | null | null |
demo4/module.py
|
HuYuee/python-study
|
28d05b0da0fed210f9da71e179a8894b722b040d
|
[
"MIT"
] | null | null | null |
# 函数，通过注解来告知用户或者开发者
def getValue(word: str='hahha') -> set:
"""哈哈"""
return set(word)
| 12.125
| 39
| 0.587629
| 12
| 97
| 4.75
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.216495
| 97
| 7
| 40
| 13.857143
| 0.75
| 0.216495
| 0
| 0
| 0
| 0
| 0.072464
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
1b9ca382104b94451c43f4fcb3b36c2a6135f166
| 131
|
py
|
Python
|
bb.py
|
sayRequil/kraken-cms
|
be5a175a722f567a7eb6c09ec0fff017d23c0e05
|
[
"Apache-2.0"
] | null | null | null |
bb.py
|
sayRequil/kraken-cms
|
be5a175a722f567a7eb6c09ec0fff017d23c0e05
|
[
"Apache-2.0"
] | null | null | null |
bb.py
|
sayRequil/kraken-cms
|
be5a175a722f567a7eb6c09ec0fff017d23c0e05
|
[
"Apache-2.0"
] | null | null | null |
import version
from mako.template import Template
def run(n):
file = Template(filename=n)
print(file.render(vers=version.vers())
| 21.833333
| 39
| 0.770992
| 20
| 131
| 5.05
| 0.65
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.10687
| 131
| 5
| 40
| 26.2
| 0.863248
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.4
| null | null | 0.2
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1bdae1851b163a8d276e1b1e424c845e690dd96e
| 193
|
py
|
Python
|
cinnamon/cpu_collector.py
|
eladhayun/cinnamon-server
|
559fb2f41c0d1dd22e3170e29900f4df22107b42
|
[
"MIT"
] | 4
|
2019-09-03T04:10:55.000Z
|
2020-10-02T10:14:37.000Z
|
cinnamon/cpu_collector.py
|
eladhayun/activity-monitor
|
559fb2f41c0d1dd22e3170e29900f4df22107b42
|
[
"MIT"
] | null | null | null |
cinnamon/cpu_collector.py
|
eladhayun/activity-monitor
|
559fb2f41c0d1dd22e3170e29900f4df22107b42
|
[
"MIT"
] | null | null | null |
import psutil
class CpuCollector(object):
@staticmethod
def get_usage():
return {
"usage": 100 - psutil.cpu_times_percent(interval=1, percpu=False).idle
}
| 19.3
| 82
| 0.621762
| 21
| 193
| 5.571429
| 0.904762
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.028571
| 0.274611
| 193
| 10
| 83
| 19.3
| 0.807143
| 0
| 0
| 0
| 0
| 0
| 0.025773
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| true
| 0
| 0.142857
| 0.142857
| 0.571429
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
59ed8ff690c0d14d2d3f997f5cc5c234ded3e2d5
| 193
|
py
|
Python
|
runtests.py
|
bartels/satchless
|
4d333014333dc4fd5815f9e0bbea565959919a30
|
[
"BSD-4-Clause"
] | 1
|
2015-11-05T10:26:46.000Z
|
2015-11-05T10:26:46.000Z
|
runtests.py
|
bartels/satchless
|
4d333014333dc4fd5815f9e0bbea565959919a30
|
[
"BSD-4-Clause"
] | null | null | null |
runtests.py
|
bartels/satchless
|
4d333014333dc4fd5815f9e0bbea565959919a30
|
[
"BSD-4-Clause"
] | null | null | null |
#!/usr/bin/env python
import os
from django.core.management import call_command
os.environ['DJANGO_SETTINGS_MODULE'] = 'testing.settings'
if __name__ == "__main__":
call_command('test')
| 19.3
| 57
| 0.751295
| 26
| 193
| 5.115385
| 0.769231
| 0.165414
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.119171
| 193
| 9
| 58
| 21.444444
| 0.782353
| 0.103627
| 0
| 0
| 0
| 0
| 0.290698
| 0.127907
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
59fd3b386f981b42dfead0f02eba42b4b1877e0b
| 160
|
py
|
Python
|
child.py
|
Deric-W/nplayer
|
174040e2e40d69a5d325055fe961f16d02a37a3a
|
[
"MIT"
] | 1
|
2019-05-04T00:28:34.000Z
|
2019-05-04T00:28:34.000Z
|
child.py
|
Deric-W/nplayer
|
174040e2e40d69a5d325055fe961f16d02a37a3a
|
[
"MIT"
] | null | null | null |
child.py
|
Deric-W/nplayer
|
174040e2e40d69a5d325055fe961f16d02a37a3a
|
[
"MIT"
] | null | null | null |
import subprocess,sys
def run(playerpath,file,frames):
NULL = subprocess.run([playerpath,"-n",str(frames),"-q",file],shell=False,check=True)
sys.exit(0)
| 40
| 89
| 0.7125
| 24
| 160
| 4.75
| 0.75
| 0.22807
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006897
| 0.09375
| 160
| 4
| 90
| 40
| 0.77931
| 0
| 0
| 0
| 0
| 0
| 0.024845
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 1
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
941d6cfa25dffa30802c03cc25905a70e7bd4f86
| 91
|
py
|
Python
|
webapp/noobcash/apps.py
|
PanosAntoniadis/noobcash
|
47c9e7aabc010982d841e414c30b9c76cbb84b6d
|
[
"MIT"
] | 7
|
2020-04-11T15:21:53.000Z
|
2022-03-29T21:12:15.000Z
|
webapp/noobcash/apps.py
|
PanosAntoniadis/noobcash
|
47c9e7aabc010982d841e414c30b9c76cbb84b6d
|
[
"MIT"
] | 1
|
2021-06-10T20:32:31.000Z
|
2021-06-10T20:32:31.000Z
|
webapp/noobcash/apps.py
|
PanosAntoniadis/noobcash
|
47c9e7aabc010982d841e414c30b9c76cbb84b6d
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class NoobcashConfig(AppConfig):
name = 'noobcash'
| 15.166667
| 33
| 0.758242
| 10
| 91
| 6.9
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.164835
| 91
| 5
| 34
| 18.2
| 0.907895
| 0
| 0
| 0
| 0
| 0
| 0.087912
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
942360487b92cafe629cc983251b11edb91c41e4
| 165
|
py
|
Python
|
libcity/pipeline/__init__.py
|
moghadas76/test_bigcity
|
607b9602c5b1113b23e1830455e174b0901d7558
|
[
"Apache-2.0"
] | 221
|
2021-09-06T03:33:31.000Z
|
2022-03-28T05:36:49.000Z
|
libcity/pipeline/__init__.py
|
moghadas76/test_bigcity
|
607b9602c5b1113b23e1830455e174b0901d7558
|
[
"Apache-2.0"
] | 43
|
2021-09-19T16:12:28.000Z
|
2022-03-31T16:29:03.000Z
|
libcity/pipeline/__init__.py
|
moghadas76/test_bigcity
|
607b9602c5b1113b23e1830455e174b0901d7558
|
[
"Apache-2.0"
] | 64
|
2021-09-06T07:56:10.000Z
|
2022-03-25T08:48:35.000Z
|
from libcity.pipeline.pipeline import run_model, hyper_parameter, objective_function
__all__ = [
"run_model",
"hyper_parameter",
"objective_function"
]
| 20.625
| 84
| 0.751515
| 18
| 165
| 6.333333
| 0.611111
| 0.140351
| 0.22807
| 0.385965
| 0.684211
| 0.684211
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157576
| 165
| 7
| 85
| 23.571429
| 0.820144
| 0
| 0
| 0
| 0
| 0
| 0.254545
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.166667
| 0
| 0.166667
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
943788f4f9a08422fa690d72cb50280bef5fcda8
| 226
|
py
|
Python
|
biography/serializers/ideology_category.py
|
The-Politico/politico-civic-biography
|
1b4b9dfdb64cfaeee9536c72f8bdfc6882194625
|
[
"MIT"
] | null | null | null |
biography/serializers/ideology_category.py
|
The-Politico/politico-civic-biography
|
1b4b9dfdb64cfaeee9536c72f8bdfc6882194625
|
[
"MIT"
] | 3
|
2020-02-11T23:33:36.000Z
|
2021-06-10T21:06:50.000Z
|
biography/serializers/ideology_category.py
|
The-Politico/politico-civic-biography
|
1b4b9dfdb64cfaeee9536c72f8bdfc6882194625
|
[
"MIT"
] | null | null | null |
from biography.models import IdeologyCategory
from rest_framework import serializers
class IdeologyCategorySerializer(serializers.ModelSerializer):
class Meta:
model = IdeologyCategory
fields = '__all__'
| 25.111111
| 62
| 0.778761
| 20
| 226
| 8.55
| 0.75
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| 0
| 0.176991
| 226
| 8
| 63
| 28.25
| 0.919355
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| 0
| 0.030973
| 0
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| 0
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| 1
| 0
| false
| 0
| 0.333333
| 0
| 0.666667
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| null | 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
944ff85da8388a42c8e0eb2c106d70bd7d155d19
| 178
|
py
|
Python
|
myvenv/bin/django-admin.py
|
vibmat/isqa_demo
|
7f7b829059a4de2e7adff96fb40d061935baf676
|
[
"MIT"
] | null | null | null |
myvenv/bin/django-admin.py
|
vibmat/isqa_demo
|
7f7b829059a4de2e7adff96fb40d061935baf676
|
[
"MIT"
] | 2
|
2020-06-06T00:48:22.000Z
|
2021-06-10T22:14:55.000Z
|
myvenv/bin/django-admin.py
|
vibmat/isqa_demo
|
7f7b829059a4de2e7adff96fb40d061935baf676
|
[
"MIT"
] | null | null | null |
#!/Users/vibhavmathur/logintest/django-auth-tutorial/myvenv/bin/python3
from django.core import management
if __name__ == "__main__":
management.execute_from_command_line()
| 29.666667
| 71
| 0.803371
| 22
| 178
| 6
| 0.863636
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.006135
| 0.08427
| 178
| 5
| 72
| 35.6
| 0.803681
| 0.393258
| 0
| 0
| 0
| 0
| 0.074766
| 0
| 0
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| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
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| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 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
| 4
|
94542443a2d5fcc3301b3ac61d84f0943b776435
| 77
|
py
|
Python
|
zero/process/__init__.py
|
arXiv/arxiv-zero
|
c06f209c92f61e6a1b0d88f0d6d4ad0f89bf6e16
|
[
"MIT"
] | 4
|
2019-05-26T22:57:40.000Z
|
2021-11-05T12:33:16.000Z
|
zero/process/__init__.py
|
arXiv/arxiv-zero
|
c06f209c92f61e6a1b0d88f0d6d4ad0f89bf6e16
|
[
"MIT"
] | 19
|
2017-11-30T20:20:49.000Z
|
2018-08-24T17:27:09.000Z
|
zero/process/__init__.py
|
cul-it/arxiv-zero
|
c06f209c92f61e6a1b0d88f0d6d4ad0f89bf6e16
|
[
"MIT"
] | 5
|
2019-01-10T22:02:11.000Z
|
2021-11-05T12:33:05.000Z
|
"""These modules encapsulate major parts of the service's business logic."""
| 38.5
| 76
| 0.766234
| 11
| 77
| 5.363636
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12987
| 77
| 1
| 77
| 77
| 0.880597
| 0.909091
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
848cc283c9ae93d84bc6cf4a528b566887a34452
| 11,088
|
py
|
Python
|
awswrangler/quicksight/_delete.py
|
isichei/aws-data-wrangler
|
0ce3836000bc5f4b5f7adffdb81392cdcf135b7a
|
[
"Apache-2.0"
] | 2,695
|
2019-03-01T00:38:08.000Z
|
2022-03-31T16:09:38.000Z
|
awswrangler/quicksight/_delete.py
|
isichei/aws-data-wrangler
|
0ce3836000bc5f4b5f7adffdb81392cdcf135b7a
|
[
"Apache-2.0"
] | 977
|
2019-08-15T22:13:37.000Z
|
2022-03-31T15:19:58.000Z
|
awswrangler/quicksight/_delete.py
|
isichei/aws-data-wrangler
|
0ce3836000bc5f4b5f7adffdb81392cdcf135b7a
|
[
"Apache-2.0"
] | 475
|
2019-05-01T04:24:50.000Z
|
2022-03-31T22:08:09.000Z
|
"""Amazon QuickSight Delete Module."""
import logging
from typing import Any, Callable, Dict, Optional
import boto3
from awswrangler import _utils, exceptions, sts
from awswrangler.quicksight._get_list import (
get_dashboard_id,
get_data_source_id,
get_dataset_id,
get_template_id,
list_dashboards,
list_data_sources,
list_datasets,
list_templates,
)
_logger: logging.Logger = logging.getLogger(__name__)
def _delete(
func_name: str, account_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None, **kwargs: Any
) -> None:
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if account_id is None:
account_id = sts.get_account_id(boto3_session=session)
client: boto3.client = _utils.client(service_name="quicksight", session=session)
func: Callable[..., None] = getattr(client, func_name)
func(AwsAccountId=account_id, **kwargs)
def delete_dashboard(
name: Optional[str] = None,
dashboard_id: Optional[str] = None,
version_number: Optional[int] = None,
account_id: Optional[str] = None,
boto3_session: Optional[boto3.Session] = None,
) -> None:
"""Delete a dashboard.
Note
----
You must pass a not None ``name`` or ``dashboard_id`` argument.
Parameters
----------
name : str, optional
Dashboard name.
dashboard_id : str, optional
The ID for the dashboard.
version_number : int, optional
The version number of the dashboard. If the version number property is provided,
only the specified version of the dashboard is deleted.
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_dashboard(name="...")
"""
if (name is None) and (dashboard_id is None):
raise exceptions.InvalidArgument("You must pass a not None name or dashboard_id argument.")
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if (dashboard_id is None) and (name is not None):
dashboard_id = get_dashboard_id(name=name, account_id=account_id, boto3_session=session)
args: Dict[str, Any] = {
"func_name": "delete_dashboard",
"account_id": account_id,
"boto3_session": session,
"DashboardId": dashboard_id,
}
if version_number is not None:
args["VersionNumber"] = version_number
_delete(**args)
def delete_dataset(
name: Optional[str] = None,
dataset_id: Optional[str] = None,
account_id: Optional[str] = None,
boto3_session: Optional[boto3.Session] = None,
) -> None:
"""Delete a dataset.
Note
----
You must pass a not None ``name`` or ``dataset_id`` argument.
Parameters
----------
name : str, optional
Dashboard name.
dataset_id : str, optional
The ID for the dataset.
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_dataset(name="...")
"""
if (name is None) and (dataset_id is None):
raise exceptions.InvalidArgument("You must pass a not None name or dataset_id argument.")
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if (dataset_id is None) and (name is not None):
dataset_id = get_dataset_id(name=name, account_id=account_id, boto3_session=session)
args: Dict[str, Any] = {
"func_name": "delete_data_set",
"account_id": account_id,
"boto3_session": session,
"DataSetId": dataset_id,
}
_delete(**args)
def delete_data_source(
name: Optional[str] = None,
data_source_id: Optional[str] = None,
account_id: Optional[str] = None,
boto3_session: Optional[boto3.Session] = None,
) -> None:
"""Delete a data source.
Note
----
You must pass a not None ``name`` or ``data_source_id`` argument.
Parameters
----------
name : str, optional
Dashboard name.
data_source_id : str, optional
The ID for the data source.
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_data_source(name="...")
"""
if (name is None) and (data_source_id is None):
raise exceptions.InvalidArgument("You must pass a not None name or data_source_id argument.")
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if (data_source_id is None) and (name is not None):
data_source_id = get_data_source_id(name=name, account_id=account_id, boto3_session=session)
args: Dict[str, Any] = {
"func_name": "delete_data_source",
"account_id": account_id,
"boto3_session": session,
"DataSourceId": data_source_id,
}
_delete(**args)
def delete_template(
name: Optional[str] = None,
template_id: Optional[str] = None,
version_number: Optional[int] = None,
account_id: Optional[str] = None,
boto3_session: Optional[boto3.Session] = None,
) -> None:
"""Delete a tamplate.
Note
----
You must pass a not None ``name`` or ``template_id`` argument.
Parameters
----------
name : str, optional
Dashboard name.
template_id : str, optional
The ID for the dashboard.
version_number : int, optional
Specifies the version of the template that you want to delete.
If you don't provide a version number, it deletes all versions of the template.
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_template(name="...")
"""
if (name is None) and (template_id is None):
raise exceptions.InvalidArgument("You must pass a not None name or template_id argument.")
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if (template_id is None) and (name is not None):
template_id = get_template_id(name=name, account_id=account_id, boto3_session=session)
args: Dict[str, Any] = {
"func_name": "delete_template",
"account_id": account_id,
"boto3_session": session,
"TemplateId": template_id,
}
if version_number is not None:
args["VersionNumber"] = version_number
_delete(**args)
def delete_all_dashboards(account_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None) -> None:
"""Delete all dashboards.
Parameters
----------
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_all_dashboards()
"""
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if account_id is None:
account_id = sts.get_account_id(boto3_session=session)
for dashboard in list_dashboards(account_id=account_id, boto3_session=session):
delete_dashboard(dashboard_id=dashboard["DashboardId"], account_id=account_id, boto3_session=session)
def delete_all_datasets(account_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None) -> None:
"""Delete all datasets.
Parameters
----------
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_all_datasets()
"""
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if account_id is None:
account_id = sts.get_account_id(boto3_session=session)
for dataset in list_datasets(account_id=account_id, boto3_session=session):
delete_dataset(dataset_id=dataset["DataSetId"], account_id=account_id, boto3_session=session)
def delete_all_data_sources(account_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None) -> None:
"""Delete all data sources.
Parameters
----------
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_all_data_sources()
"""
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if account_id is None:
account_id = sts.get_account_id(boto3_session=session)
for data_source in list_data_sources(account_id=account_id, boto3_session=session):
delete_data_source(data_source_id=data_source["DataSourceId"], account_id=account_id, boto3_session=session)
def delete_all_templates(account_id: Optional[str] = None, boto3_session: Optional[boto3.Session] = None) -> None:
"""Delete all templates.
Parameters
----------
account_id : str, optional
If None, the account ID will be inferred from your boto3 session.
boto3_session : boto3.Session(), optional
Boto3 Session. The default boto3 session will be used if boto3_session receive None.
Returns
-------
None
None.
Examples
--------
>>> import awswrangler as wr
>>> wr.quicksight.delete_all_templates()
"""
session: boto3.Session = _utils.ensure_session(session=boto3_session)
if account_id is None:
account_id = sts.get_account_id(boto3_session=session)
for template in list_templates(account_id=account_id, boto3_session=session):
delete_template(template_id=template["TemplateId"], account_id=account_id, boto3_session=session)
| 32.611765
| 117
| 0.66811
| 1,404
| 11,088
| 5.07265
| 0.071225
| 0.176917
| 0.090705
| 0.061921
| 0.782645
| 0.769447
| 0.758776
| 0.72606
| 0.667088
| 0.664841
| 0
| 0.012458
| 0.225379
| 11,088
| 339
| 118
| 32.707965
| 0.816742
| 0.384199
| 0
| 0.460317
| 0
| 0
| 0.086229
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.071429
| false
| 0.031746
| 0.039683
| 0
| 0.111111
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
84ab3cc7d88053eeec4827f2d65af163811f9542
| 242
|
py
|
Python
|
js/angular_scroll/__init__.py
|
fanstatic/js.angular_scroll
|
a118c84fba3b3c8ad323f60c70061a923d763d55
|
[
"BSD-3-Clause"
] | null | null | null |
js/angular_scroll/__init__.py
|
fanstatic/js.angular_scroll
|
a118c84fba3b3c8ad323f60c70061a923d763d55
|
[
"BSD-3-Clause"
] | null | null | null |
js/angular_scroll/__init__.py
|
fanstatic/js.angular_scroll
|
a118c84fba3b3c8ad323f60c70061a923d763d55
|
[
"BSD-3-Clause"
] | null | null | null |
from fanstatic import Library, Resource
import js.angular
library = Library('angular-scroll', 'resources')
angular_scroll = Resource(
library, 'angular-scroll.js',
minified='angular-scroll.min.js',
depends=[js.angular.angular])
| 24.2
| 48
| 0.735537
| 29
| 242
| 6.103448
| 0.413793
| 0.293785
| 0.225989
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.132231
| 242
| 9
| 49
| 26.888889
| 0.842857
| 0
| 0
| 0
| 0
| 0
| 0.252066
| 0.086777
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.285714
| 0
| 0.285714
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
84cb38cfaafa40b914eeb56937a152aa563354b7
| 172
|
py
|
Python
|
org/shubhi/general/arithmeticOperator.py
|
shubhdashambhavi/learn-python
|
825b1918457c995ac5e234aaef3bc078bfd7e90c
|
[
"Apache-2.0"
] | null | null | null |
org/shubhi/general/arithmeticOperator.py
|
shubhdashambhavi/learn-python
|
825b1918457c995ac5e234aaef3bc078bfd7e90c
|
[
"Apache-2.0"
] | null | null | null |
org/shubhi/general/arithmeticOperator.py
|
shubhdashambhavi/learn-python
|
825b1918457c995ac5e234aaef3bc078bfd7e90c
|
[
"Apache-2.0"
] | null | null | null |
a=10
b=5
print('Addition:', a+b)
print('Substraction: ', a-b)
print('Multiplication:', a*b)
print('Division: ', a/b)
print('Remainder: ', a%b)
print('Exponential:', a ** b)
| 21.5
| 29
| 0.633721
| 28
| 172
| 3.892857
| 0.392857
| 0.110092
| 0.321101
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.019481
| 0.104651
| 172
| 8
| 30
| 21.5
| 0.688312
| 0
| 0
| 0
| 0
| 0
| 0.410405
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.75
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
84fa9adf475db8e2e6fdf1186a4f25e587766977
| 4,444
|
py
|
Python
|
tests/cases/userChangePassword.py
|
ktphipps/Capstone-ARK
|
335234f874eaab3f3f53ca6d3f122c2826a24e2e
|
[
"MIT"
] | null | null | null |
tests/cases/userChangePassword.py
|
ktphipps/Capstone-ARK
|
335234f874eaab3f3f53ca6d3f122c2826a24e2e
|
[
"MIT"
] | null | null | null |
tests/cases/userChangePassword.py
|
ktphipps/Capstone-ARK
|
335234f874eaab3f3f53ca6d3f122c2826a24e2e
|
[
"MIT"
] | null | null | null |
import pyautogui;
import time;
import unittest
from selenium import webdriver
from selenium.common.exceptions import NoAlertPresentException
from selenium.webdriver.common.keys import Keys
from selenium.webdriver.common.alert import Alert
from selenium.webdriver.support import expected_conditions as EC
# inherit TestCase Class and create a new test class
class userChangePassword(unittest.TestCase):
# initialization of webdriver
def setUp(self):
self.driver = webdriver.Firefox()
self.driver.implicitly_wait(30)
# Test case method.
def test_change_user_password(self):
# get driver
driver = self.driver
# get ractrainer web app using selenium
driver.get("https://ractrainer.web.app/")
# locate element using name
elem = driver.find_element_by_xpath("//a[contains(.,'Login')]")
# send data
elem.click()
# locate element using id
elem = driver.find_element_by_id("Uname")
# send data
elem.send_keys('Temp@test.com')
# locate element using id
elem = driver.find_element_by_id("password")
# send data
elem.send_keys('123456789')
# locate element using name
elem = driver.find_element_by_xpath("//button[contains(.,'Log in')]")
# send data
elem.click()
time.sleep(1)
elem = driver.find_element_by_xpath("//a[contains(.,'User Dashboard')]")
# send data
elem.click()
time.sleep(1)
elem = driver.find_element_by_xpath("//button[contains(.,'Change Password')]")
# send data
elem.click()
time.sleep(1)
# locate element using id
elem = driver.find_element_by_id("password")
# send data
elem.send_keys('987654321')
# locate element using id
elem = driver.find_element_by_id("confirmPassword")
# send data
elem.send_keys('987654321')
time.sleep(1)
# locate element using name
elem = driver.find_element_by_xpath("//button[contains(.,'Change Password')]")
# send data
elem.click()
# give the database time to respond
while (1):
try:
alert = driver.switch_to.alert
alert.accept()
break
except NoAlertPresentException:
continue
time.sleep(1)
# check to make sure we are on the user dashboard
elem = driver.find_element_by_xpath("//a[contains(.,'Logout')]")
# send data
elem.click()
# locate element using id
elem = driver.find_element_by_id("Uname")
# send data
elem.send_keys('Temp@test.com')
# locate element using id
elem = driver.find_element_by_id("password")
# send data
elem.send_keys('123456789')
# locate element using name
elem = driver.find_element_by_xpath("//button[contains(.,'Log in')]")
# send data
elem.click()
# give the database time to respond
while (1):
try:
alert = driver.switch_to.alert
alertText = alert.text
alert.accept()
break
except NoAlertPresentException:
continue
if (alertText != "The password is invalid or the user does not have a password."):
assert False
time.sleep(2)
driver.refresh()
# locate element using id
elem = driver.find_element_by_id("Uname")
# send data
elem.send_keys('Temp@test.com')
# locate element using id
elem = driver.find_element_by_id("password")
# send data
elem.send_keys('987654321')
# locate element using name
elem = driver.find_element_by_xpath("//button[contains(.,'Log in')]")
# send data
elem.click()
time.sleep(1)
elem = driver.find_element_by_xpath("//a[contains(.,'User Dashboard')]")
# send data
elem.click()
#change the password back to the original
elem = driver.find_element_by_xpath("//button[contains(.,'Change Password')]")
# send data
elem.click()
time.sleep(1)
# locate element using id
elem = driver.find_element_by_id("password")
# send data
elem.send_keys('123456789')
# locate element using id
elem = driver.find_element_by_id("confirmPassword")
# send data
elem.send_keys('123456789')
time.sleep(1)
# locate element using name
elem = driver.find_element_by_xpath("//button[contains(.,'Change Password')]")
# send data
elem.click()
# give the database time to respond
while (1):
try:
alert = driver.switch_to.alert
alert.accept()
break
except NoAlertPresentException:
continue
time.sleep(1)
assert True
# cleanup method called after every test performed
def tearDown(self):
self.driver.close()
# execute the script
if __name__ == "__main__":
unittest.main()
| 26.295858
| 84
| 0.694869
| 596
| 4,444
| 5.031879
| 0.196309
| 0.070023
| 0.098033
| 0.147049
| 0.707236
| 0.707236
| 0.683561
| 0.683561
| 0.668223
| 0.668223
| 0
| 0.021679
| 0.190369
| 4,444
| 168
| 85
| 26.452381
| 0.81184
| 0.234248
| 0
| 0.721649
| 0
| 0
| 0.192124
| 0.068317
| 0
| 0
| 0
| 0
| 0.020619
| 1
| 0.030928
| false
| 0.14433
| 0.082474
| 0
| 0.123711
| 0
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| 0
| 0
| null | 0
| 0
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| 1
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| 0
| 0
| 1
| 0
| 0
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| 0
| 0
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| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
84fe53712d4e8b60428bc08d52ea8233d5c319c4
| 492
|
py
|
Python
|
web/handlers.py
|
Tao-Network/shifu
|
079e23af9aeba357a064da7f7eeb1d806f489761
|
[
"MIT"
] | null | null | null |
web/handlers.py
|
Tao-Network/shifu
|
079e23af9aeba357a064da7f7eeb1d806f489761
|
[
"MIT"
] | null | null | null |
web/handlers.py
|
Tao-Network/shifu
|
079e23af9aeba357a064da7f7eeb1d806f489761
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
def handler404(request, exception, template_name="404.html"):
response = render(request,template_name)
response.status_code = 404
return response
def handler500(request, template_name="500.html"):
response = render(request,template_name)
response.status_code = 500
return response
def handler400(request, template_name="400.html"):
response = render(request,template_name)
response.status_code = 400
return response
| 27.333333
| 61
| 0.752033
| 60
| 492
| 6.016667
| 0.35
| 0.199446
| 0.263158
| 0.207756
| 0.457064
| 0.457064
| 0.457064
| 0.457064
| 0.457064
| 0
| 0
| 0.065217
| 0.158537
| 492
| 17
| 62
| 28.941176
| 0.806763
| 0
| 0
| 0.461538
| 0
| 0
| 0.04888
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0
| 0.076923
| 0
| 0.538462
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
ca216ab8e143905d898469195d9a010885593dea
| 269
|
py
|
Python
|
duallife/api.py
|
digitalprizm/duallife
|
a08a2796772d754f61784ecb3d45104c7c153d11
|
[
"MIT"
] | null | null | null |
duallife/api.py
|
digitalprizm/duallife
|
a08a2796772d754f61784ecb3d45104c7c153d11
|
[
"MIT"
] | null | null | null |
duallife/api.py
|
digitalprizm/duallife
|
a08a2796772d754f61784ecb3d45104c7c153d11
|
[
"MIT"
] | null | null | null |
import frappe
from erpnext.controllers.taxes_and_totals import get_itemised_tax_breakup_data
def get_item_wise_tax(self, method):
frappe.flags.country = "UAE"
tax_breakup=get_itemised_tax_breakup_data(self)
import json
self.tax_breakup = json.dumps(tax_breakup[0])
| 33.625
| 78
| 0.840149
| 43
| 269
| 4.883721
| 0.55814
| 0.238095
| 0.133333
| 0.2
| 0.238095
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004049
| 0.081784
| 269
| 7
| 79
| 38.428571
| 0.846154
| 0
| 0
| 0
| 0
| 0
| 0.011152
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.142857
| false
| 0
| 0.428571
| 0
| 0.571429
| 0
| 0
| 0
| 0
| null | 1
| 0
| 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
| 4
|
ca2fa266739e235ea83a9d64a8f675451341c1af
| 153
|
py
|
Python
|
hardware/opentrons_hardware/firmware_bindings/messages/__init__.py
|
anuwrag/opentrons
|
28c8d76a19e367c6bd38f5290faaa32abf378715
|
[
"Apache-2.0"
] | 3
|
2021-09-21T13:20:27.000Z
|
2021-12-02T13:12:32.000Z
|
hardware/opentrons_hardware/firmware_bindings/messages/__init__.py
|
anuwrag/opentrons
|
28c8d76a19e367c6bd38f5290faaa32abf378715
|
[
"Apache-2.0"
] | 36
|
2021-08-10T15:18:09.000Z
|
2022-03-30T19:08:13.000Z
|
hardware/opentrons_hardware/firmware_bindings/messages/__init__.py
|
anuwrag/opentrons
|
28c8d76a19e367c6bd38f5290faaa32abf378715
|
[
"Apache-2.0"
] | null | null | null |
"""Can bus message definitions."""
from .messages import MessageDefinition, get_definition
__all__ = [
"MessageDefinition",
"get_definition",
]
| 19.125
| 55
| 0.72549
| 14
| 153
| 7.5
| 0.785714
| 0.380952
| 0.571429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.156863
| 153
| 7
| 56
| 21.857143
| 0.813953
| 0.183007
| 0
| 0
| 0
| 0
| 0.260504
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
ca3d42eb03f2ca17de7610260c7d474770cbf4c8
| 50
|
py
|
Python
|
connect/asgi.py
|
dixonwhitmire/connect
|
800d821c8f6d6abff6485b43727353b909ef4b76
|
[
"Apache-2.0"
] | 33
|
2020-06-16T11:47:03.000Z
|
2022-03-24T02:41:00.000Z
|
connect/asgi.py
|
dixonwhitmire/connect
|
800d821c8f6d6abff6485b43727353b909ef4b76
|
[
"Apache-2.0"
] | 470
|
2020-06-12T01:18:43.000Z
|
2022-02-20T23:08:00.000Z
|
connect/asgi.py
|
dixonwhitmire/connect
|
800d821c8f6d6abff6485b43727353b909ef4b76
|
[
"Apache-2.0"
] | 30
|
2020-06-12T19:36:09.000Z
|
2022-01-31T15:25:35.000Z
|
from connect.main import get_app
app = get_app()
| 12.5
| 32
| 0.76
| 9
| 50
| 4
| 0.666667
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16
| 50
| 3
| 33
| 16.666667
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 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
| 0
| 0
|
0
| 4
|
ca4c66f6e572ac9382defcececf04929fa065f10
| 49
|
py
|
Python
|
backend/tracim_backend/views/__init__.py
|
lezardrouge/tracim
|
713ff6066767554333e7e0b1de608ec1a7e4229c
|
[
"MIT"
] | null | null | null |
backend/tracim_backend/views/__init__.py
|
lezardrouge/tracim
|
713ff6066767554333e7e0b1de608ec1a7e4229c
|
[
"MIT"
] | null | null | null |
backend/tracim_backend/views/__init__.py
|
lezardrouge/tracim
|
713ff6066767554333e7e0b1de608ec1a7e4229c
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
BASE_API_V2 = "/api/v2/"
| 16.333333
| 24
| 0.530612
| 8
| 49
| 3
| 0.75
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.073171
| 0.163265
| 49
| 2
| 25
| 24.5
| 0.512195
| 0.428571
| 0
| 0
| 0
| 0
| 0.307692
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
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| 1
| 1
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ca5140df217613d2cf961892eae541b355196814
| 208
|
py
|
Python
|
tests/test_ocs_common.py
|
lsst-ts/ts_ocs_common
|
4aa5e78bf8bcc3b466196fee13ab3a33935f58fb
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_ocs_common.py
|
lsst-ts/ts_ocs_common
|
4aa5e78bf8bcc3b466196fee13ab3a33935f58fb
|
[
"BSD-3-Clause"
] | null | null | null |
tests/test_ocs_common.py
|
lsst-ts/ts_ocs_common
|
4aa5e78bf8bcc3b466196fee13ab3a33935f58fb
|
[
"BSD-3-Clause"
] | null | null | null |
#!/usr/bin/env python
# -*- coding: utf-8 -*-
# +
# __doc__ string
# _
__doc__ = """test of ocs_common"""
# +
# function: test_ocs_common() to keep py.test happy
# -
def test_ocs_common():
assert True
| 13.866667
| 51
| 0.625
| 29
| 208
| 4
| 0.724138
| 0.232759
| 0.224138
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005988
| 0.197115
| 208
| 14
| 52
| 14.857143
| 0.688623
| 0.552885
| 0
| 0
| 0
| 0
| 0.211765
| 0
| 0
| 0
| 0
| 0
| 0.333333
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
ca96275c677ad8fc906c965c8a7d52be4c5da4d1
| 213
|
py
|
Python
|
trftools/dictionaries/__init__.py
|
christianbrodbeck/TRF-Tools
|
0d5ee51b4bd2dc33a54bcf167e59cee2b5e11276
|
[
"MIT"
] | null | null | null |
trftools/dictionaries/__init__.py
|
christianbrodbeck/TRF-Tools
|
0d5ee51b4bd2dc33a54bcf167e59cee2b5e11276
|
[
"MIT"
] | 1
|
2021-06-25T16:15:30.000Z
|
2021-06-25T16:15:30.000Z
|
trftools/dictionaries/__init__.py
|
christianbrodbeck/TRF-Tools
|
0d5ee51b4bd2dc33a54bcf167e59cee2b5e11276
|
[
"MIT"
] | 3
|
2020-02-06T19:29:19.000Z
|
2021-11-16T04:06:24.000Z
|
# Author: Christian Brodbeck <christianbrodbeck@nyu.edu>
from ._cmu import read_cmupd
from ._dict import read_dict, combine_dicts, split_apostrophe, write_dict
from ._subtlex import read_subtlex, read_subtlex_pos
| 42.6
| 73
| 0.840376
| 30
| 213
| 5.6
| 0.633333
| 0.178571
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.098592
| 213
| 4
| 74
| 53.25
| 0.875
| 0.253521
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
04607f1db242abc96cc1ca57d5bb954a60575257
| 28
|
py
|
Python
|
src/pytorch_metric_learning/__init__.py
|
JaMesLiMers/pytorch-metric-learning
|
4f45b493914c498fc2a4a948da13590f688aa2fc
|
[
"MIT"
] | 1
|
2020-11-30T08:04:57.000Z
|
2020-11-30T08:04:57.000Z
|
src/pytorch_metric_learning/__init__.py
|
JaMesLiMers/pytorch-metric-learning
|
4f45b493914c498fc2a4a948da13590f688aa2fc
|
[
"MIT"
] | null | null | null |
src/pytorch_metric_learning/__init__.py
|
JaMesLiMers/pytorch-metric-learning
|
4f45b493914c498fc2a4a948da13590f688aa2fc
|
[
"MIT"
] | null | null | null |
__version__ = "0.9.95.dev0"
| 14
| 27
| 0.678571
| 5
| 28
| 3
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.2
| 0.107143
| 28
| 1
| 28
| 28
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0.392857
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
046696ed644ea845a9535b86383218fdc3944431
| 58
|
py
|
Python
|
test/main.py
|
lambdalisue/coc-pyright
|
2ba3debd22b7e070d063c262976dcf5a5f3078af
|
[
"MIT"
] | null | null | null |
test/main.py
|
lambdalisue/coc-pyright
|
2ba3debd22b7e070d063c262976dcf5a5f3078af
|
[
"MIT"
] | null | null | null |
test/main.py
|
lambdalisue/coc-pyright
|
2ba3debd22b7e070d063c262976dcf5a5f3078af
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
from test import m
m.greeting(1)
| 9.666667
| 22
| 0.706897
| 11
| 58
| 3.727273
| 0.909091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.040816
| 0.155172
| 58
| 5
| 23
| 11.6
| 0.795918
| 0.362069
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
047cbc4870c329ce050860fe30806f78e1a2cbb5
| 129
|
py
|
Python
|
api/api/urls.py
|
brendanjamesmulhern/ideaworks-2
|
acff7dfcf38fa22e1a6207e5449659d3d5a53163
|
[
"MIT"
] | null | null | null |
api/api/urls.py
|
brendanjamesmulhern/ideaworks-2
|
acff7dfcf38fa22e1a6207e5449659d3d5a53163
|
[
"MIT"
] | null | null | null |
api/api/urls.py
|
brendanjamesmulhern/ideaworks-2
|
acff7dfcf38fa22e1a6207e5449659d3d5a53163
|
[
"MIT"
] | null | null | null |
from django.contrib import admin
from django.urls import path, include
urlpatterns = [
path('api/', include('app.urls')),
]
| 18.428571
| 38
| 0.705426
| 17
| 129
| 5.352941
| 0.647059
| 0.21978
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.155039
| 129
| 6
| 39
| 21.5
| 0.834862
| 0
| 0
| 0
| 0
| 0
| 0.093023
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
04882f12fef03ec98d38f1c5830a8a46ce9e1ac3
| 101
|
py
|
Python
|
guard/schemas.py
|
long2ice/guard
|
3dc6a86588ec3e97f1873b08d5c581fb2a17bb88
|
[
"Apache-2.0"
] | 1
|
2021-11-05T16:56:59.000Z
|
2021-11-05T16:56:59.000Z
|
guard/schemas.py
|
long2ice/guard
|
3dc6a86588ec3e97f1873b08d5c581fb2a17bb88
|
[
"Apache-2.0"
] | null | null | null |
guard/schemas.py
|
long2ice/guard
|
3dc6a86588ec3e97f1873b08d5c581fb2a17bb88
|
[
"Apache-2.0"
] | null | null | null |
from pydantic import BaseModel
class CreateLogReq(BaseModel):
project_id: int
content: str
| 14.428571
| 30
| 0.752475
| 12
| 101
| 6.25
| 0.916667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.19802
| 101
| 6
| 31
| 16.833333
| 0.925926
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.25
| 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
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
0495bad21eea25f85eaad0e55c2b34cde40e6bca
| 593
|
py
|
Python
|
test.py
|
asm/pymruby
|
295318bb6df8c4dea7d4f08cd728e7bce14c4048
|
[
"MIT"
] | 1
|
2021-11-23T20:23:51.000Z
|
2021-11-23T20:23:51.000Z
|
test.py
|
asm/pymruby
|
295318bb6df8c4dea7d4f08cd728e7bce14c4048
|
[
"MIT"
] | null | null | null |
test.py
|
asm/pymruby
|
295318bb6df8c4dea7d4f08cd728e7bce14c4048
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python
import pymruby
import time
import sys
# TODO: move these over to Nose
foo = pymruby.Pymruby()
print foo.eval("'RUBY_VERSION: ' + RUBY_VERSION")
print foo.eval("n=''; n += 'a' * 10**5; 'hi'")
print foo.eval("__FILE__")
print foo.eval("loop {}")
print foo.eval("while true; end;")
#foo.eval("while 1 do puts 'woah' end")
#foo.eval("def spinner(n); ['|', '\\\\', '-', '/'][n % 4]; end");
#i = 0
#sys.stdout.write("\n")
#while True:
# sys.stdout.write("\033[1G")
# sys.stdout.write(foo.eval("spinner (%s) \r" % i))
# sys.stdout.flush()
# i= i + 1
# time.sleep(0.2)
| 21.962963
| 65
| 0.600337
| 97
| 593
| 3.608247
| 0.484536
| 0.16
| 0.171429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.025743
| 0.148398
| 593
| 26
| 66
| 22.807692
| 0.667327
| 0.53457
| 0
| 0
| 0
| 0
| 0.342205
| 0
| 0
| 0
| 0
| 0.038462
| 0
| 0
| null | null | 0
| 0.333333
| null | null | 0.555556
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 1
|
0
| 4
|
04c737342e201d785084b8266786e7f613d7b9ef
| 131
|
py
|
Python
|
colors.py
|
jrieke/lightshapes
|
0ea8e6443cd45e21d5977ef02f100901b2d0842a
|
[
"MIT"
] | 2
|
2019-01-24T19:12:00.000Z
|
2019-01-24T19:32:23.000Z
|
colors.py
|
jrieke/lightshapes
|
0ea8e6443cd45e21d5977ef02f100901b2d0842a
|
[
"MIT"
] | null | null | null |
colors.py
|
jrieke/lightshapes
|
0ea8e6443cd45e21d5977ef02f100901b2d0842a
|
[
"MIT"
] | null | null | null |
red = (255,0,0)
green = (0,255,0)
blue = (0,0,255)
darkBlue = (0,0,128)
white = (255,255,255)
black = (0,0,0)
pink = (255,200,200)
| 16.375
| 21
| 0.572519
| 28
| 131
| 2.678571
| 0.392857
| 0.133333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.372727
| 0.160305
| 131
| 7
| 22
| 18.714286
| 0.309091
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
04c77729ccfd127a545b81ed84aae6c9d4e2cee0
| 195
|
py
|
Python
|
CAPITULO 3/Exemplos/Exemplo 3.5.py
|
janairacs/aprendendo-a-linguaguem-Python
|
35a39efd97333deba6f70bb9cd97be029b837b24
|
[
"MIT"
] | null | null | null |
CAPITULO 3/Exemplos/Exemplo 3.5.py
|
janairacs/aprendendo-a-linguaguem-Python
|
35a39efd97333deba6f70bb9cd97be029b837b24
|
[
"MIT"
] | null | null | null |
CAPITULO 3/Exemplos/Exemplo 3.5.py
|
janairacs/aprendendo-a-linguaguem-Python
|
35a39efd97333deba6f70bb9cd97be029b837b24
|
[
"MIT"
] | null | null | null |
#Programa 3.1- Exemplo de sequência e tempo
divida = 0
compra = 100
divida = divida + compra
compra = 200
divida = divida + compra
compra = 300
divida = divida + compra
compra = 0
print (divida)
| 17.727273
| 43
| 0.717949
| 29
| 195
| 4.827586
| 0.517241
| 0.257143
| 0.385714
| 0.514286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.083333
| 0.2
| 195
| 10
| 44
| 19.5
| 0.814103
| 0.215385
| 0
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.111111
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
04cc6682a0883d3f192cc9bb34b1faa8adf06144
| 1,323
|
py
|
Python
|
tests/test_politeness.py
|
petarGitNik/reddit-image-downloader
|
e38ddaf225a47d85a0d91785eb22b80c42e886dc
|
[
"MIT"
] | 3
|
2019-03-29T22:09:13.000Z
|
2019-05-24T07:58:52.000Z
|
tests/test_politeness.py
|
petarGitNik/reddit-image-downloader
|
e38ddaf225a47d85a0d91785eb22b80c42e886dc
|
[
"MIT"
] | null | null | null |
tests/test_politeness.py
|
petarGitNik/reddit-image-downloader
|
e38ddaf225a47d85a0d91785eb22b80c42e886dc
|
[
"MIT"
] | 1
|
2020-07-13T14:56:14.000Z
|
2020-07-13T14:56:14.000Z
|
#!/usr/bin/python3
import pytest
from utils.politeness import get_politeness_factor
from domainparsers.common import Domains
__author__ = 'petarGitNik'
__copyright__ = 'Copyright (c) 2017 petarGitNik petargitnik@gmail.com'
__version__ = 'v0.1.0'
__license__ = 'MIT'
__email__ = 'petargitnik@gmail.com'
__status__ = 'Development'
def test_politeness_for_false_inputs():
"""
Test politeness factor for False values.
"""
assert get_politeness_factor(None) == 5
assert get_politeness_factor(0) == 5
assert get_politeness_factor(False) == 5
assert get_politeness_factor([]) == 5
def test_politeness_for_unwknown_domains():
"""
Test politeness factor for unknown domain inputs.
"""
assert get_politeness_factor('flickr') == 5
assert get_politeness_factor('pexels') == 5
assert get_politeness_factor('instagram') == 5
def test_politeness_for_known_domains():
"""
Test politeness factor for known domains.
"""
assert get_politeness_factor(Domains.REDDIT) == 3.88348544015422
assert get_politeness_factor(Domains.IMGUR) == 3.88348544015422
assert get_politeness_factor(Domains.GFYCAT) == 4.436989947253095
assert get_politeness_factor(Domains.TUMBLR) == 3.6724994960588933
assert get_politeness_factor(Domains.BLOGSPOT) == 3.88348544015422
| 30.767442
| 70
| 0.748299
| 157
| 1,323
| 5.910828
| 0.350318
| 0.275862
| 0.266164
| 0.323276
| 0.454741
| 0.101293
| 0.101293
| 0
| 0
| 0
| 0
| 0.084004
| 0.154195
| 1,323
| 42
| 71
| 31.5
| 0.745308
| 0.113379
| 0
| 0
| 0
| 0
| 0.110914
| 0.037267
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0.125
| false
| 0
| 0.125
| 0
| 0.25
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b6cd5581c77828a82945893089a94145caf8db0a
| 62
|
py
|
Python
|
track_actions/__init__.py
|
blackjackgg/drf-history
|
87dd076a30b33d1bc4c1a5cc0542446223a229f7
|
[
"BSD-3-Clause"
] | 11
|
2020-01-25T23:26:56.000Z
|
2021-12-30T14:31:50.000Z
|
track_actions/__init__.py
|
blackjackgg/drf-history
|
87dd076a30b33d1bc4c1a5cc0542446223a229f7
|
[
"BSD-3-Clause"
] | 6
|
2020-03-31T09:03:24.000Z
|
2021-06-27T18:11:11.000Z
|
track_actions/__init__.py
|
blackjackgg/drf-history
|
87dd076a30b33d1bc4c1a5cc0542446223a229f7
|
[
"BSD-3-Clause"
] | 2
|
2020-09-30T06:50:21.000Z
|
2020-09-30T16:48:51.000Z
|
default_app_config = "track_actions.apps.track_actionsConfig"
| 31
| 61
| 0.870968
| 8
| 62
| 6.25
| 0.875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.048387
| 62
| 1
| 62
| 62
| 0.847458
| 0
| 0
| 0
| 0
| 0
| 0.612903
| 0.612903
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
8e1ee149d9e54d7cf55739e5fb4290f66bb2ccf9
| 833
|
py
|
Python
|
ggplot/geoms/__init__.py
|
themiwi/ggplot
|
b6d23c22d52557b983da8ce7a3a6992501dadcd6
|
[
"BSD-2-Clause"
] | 1,133
|
2017-01-10T16:58:15.000Z
|
2022-03-31T14:40:29.000Z
|
ggplot/geoms/__init__.py
|
themiwi/ggplot
|
b6d23c22d52557b983da8ce7a3a6992501dadcd6
|
[
"BSD-2-Clause"
] | 287
|
2015-01-02T18:54:17.000Z
|
2017-01-10T14:48:14.000Z
|
ggplot/geoms/__init__.py
|
themiwi/ggplot
|
b6d23c22d52557b983da8ce7a3a6992501dadcd6
|
[
"BSD-2-Clause"
] | 295
|
2017-01-16T19:16:49.000Z
|
2022-02-18T14:10:58.000Z
|
from .geom_abline import geom_abline
from .geom_area import geom_area
from .geom_bar import geom_bar
from .geom_bin2d import geom_bin2d
from .geom_blank import geom_blank
from .geom_boxplot import geom_boxplot
from .geom_density import geom_density
from .geom_errorbar import geom_errorbar
from .geom_histogram import geom_histogram
from .geom_hline import geom_hline
from .geom_jitter import geom_jitter
from .geom_line import geom_line
from .geom_now_its_art import geom_now_its_art
from .geom_path import geom_path
from .geom_point import geom_point
from .geom_polygon import geom_polygon
from .geom_rect import geom_rect
from .geom_ribbon import geom_ribbon
from .geom_step import geom_step
from .geom_text import geom_text
from .geom_tile import geom_tile
from .geom_violin import geom_violin
from .geom_vline import geom_vline
| 34.708333
| 46
| 0.861945
| 142
| 833
| 4.704225
| 0.197183
| 0.275449
| 0.02994
| 0.038922
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.002699
| 0.110444
| 833
| 23
| 47
| 36.217391
| 0.898785
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
8e220757e7c1bf459299ec289cfcb120f456bd6c
| 3,895
|
py
|
Python
|
server.py
|
goforbroke1006/shapedetectorsvc
|
23df8dfa5593eb10004a034eaa1eda5d67394b49
|
[
"MIT"
] | null | null | null |
server.py
|
goforbroke1006/shapedetectorsvc
|
23df8dfa5593eb10004a034eaa1eda5d67394b49
|
[
"MIT"
] | null | null | null |
server.py
|
goforbroke1006/shapedetectorsvc
|
23df8dfa5593eb10004a034eaa1eda5d67394b49
|
[
"MIT"
] | null | null | null |
import BaseHTTPServer
from urlparse import urlparse
import time
class MainDispatcher(BaseHTTPServer.BaseHTTPRequestHandler):
def _set_headers(self):
self.send_response(200)
self.send_header('Content-type', 'text/html')
self.end_headers()
def do_GET(self):
self._set_headers()
self.wfile.write("<html><body><h1>hi!</h1></body></html>")
query = urlparse(self.path).query
query_components = dict()
for qc in query.split("&"):
if len(qc) == 0:
continue
sp = qc.find('=')
k = qc[0:sp]
v = qc[sp + 1:]
query_components[k] = v
if query_components.has_key("data"):
img_data = query_components["data"]
fh = open("tmp/%d.png" % time.time(), "wb")
fh.write(img_data.decode('base64'))
fh.close()
def do_HEAD(self):
self._set_headers()
def do_POST(self):
# Doesn't do anything with posted data
self._set_headers()
self.wfile.write("<html><body><h1>POST!</h1></body></html>")
server_address = ('', 4401)
httpd = BaseHTTPServer.HTTPServer(server_address, MainDispatcher)
print 'Starting httpd...'
httpd.serve_forever()
# http://localhost:4401/?data=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
| 79.489796
| 2,634
| 0.839024
| 234
| 3,895
| 13.863248
| 0.653846
| 0.01233
| 0.012947
| 0.011097
| 0.023428
| 0.023428
| 0.023428
| 0.023428
| 0.023428
| 0
| 0
| 0.08594
| 0.088832
| 3,895
| 49
| 2,634
| 79.489796
| 0.828121
| 0.685237
| 0
| 0.088235
| 0
| 0
| 0.117647
| 0.063725
| 0
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| null | null | 0
| 0.088235
| null | null | 0.029412
| 0
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| null | 0
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| 0
| 0
| 0
|
0
| 4
|
8e22e80bc5b2efd80656b62e4f5c298f76f02a9d
| 148
|
py
|
Python
|
philips_hue_hooks/action/action.py
|
ChadiEM/philips-hue-motion-hook
|
398a98401654285053cec12209d7ff0bbd211b4f
|
[
"MIT"
] | null | null | null |
philips_hue_hooks/action/action.py
|
ChadiEM/philips-hue-motion-hook
|
398a98401654285053cec12209d7ff0bbd211b4f
|
[
"MIT"
] | 1
|
2020-08-26T07:08:52.000Z
|
2020-09-06T11:47:41.000Z
|
philips_hue_hooks/action/action.py
|
ChadiEM/philips-hue-motion-hook
|
398a98401654285053cec12209d7ff0bbd211b4f
|
[
"MIT"
] | 2
|
2019-01-12T17:14:35.000Z
|
2020-08-17T11:03:39.000Z
|
import abc
class Action:
@abc.abstractmethod
def invoke(self, device_class, device_id, device_name, device_type, new_state):
pass
| 18.5
| 83
| 0.716216
| 20
| 148
| 5.05
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.209459
| 148
| 7
| 84
| 21.142857
| 0.863248
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0.2
| 0.2
| 0
| 0.6
| 0
| 1
| 0
| 0
| null | 0
| 0
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
f3d6fed532bced5a35525a30c429ef5554ede872
| 6,967
|
py
|
Python
|
plugins/classifiers/plugin_ceef/ceef/functions.py
|
mdocekal/ClassMark
|
e6019f9abeb99e9a6b72365a508d5a6dac13c3c7
|
[
"Unlicense"
] | null | null | null |
plugins/classifiers/plugin_ceef/ceef/functions.py
|
mdocekal/ClassMark
|
e6019f9abeb99e9a6b72365a508d5a6dac13c3c7
|
[
"Unlicense"
] | 2
|
2021-01-18T12:29:18.000Z
|
2021-01-18T14:33:31.000Z
|
plugins/classifiers/plugin_ceef/ceef/functions.py
|
windionleaf/ClassMark
|
e6019f9abeb99e9a6b72365a508d5a6dac13c3c7
|
[
"Unlicense"
] | null | null | null |
"""
Created on 19. 3. 2019
This module contains functions that are useful for estimating likelihood that given vector is in a class.
This module could be used for auto importing in a way:
FUNCTIONS=[o for o in getmembers(functions) if isfunction(o[1])]
:author: Martin Dočekal
:contact: xdocek09@stud.fit.vubtr.cz
"""
from scipy.spatial import cKDTree
import numpy as np
def fNearest(samples, samplesVals):
"""
Linear interpolation according to nearest neighbour.
:param samples: Coords for interpolation.
:type samples: np.array
:param samplesVals: Values on class coords.
:type samplesVals: np.array
"""
fnAll=cKDTree(samples)
def res(p):
#check the nearest
_, IA = fnAll.query(p,1)
return samplesVals[IA]
return res
def fNearest2x2FromClassAndOuter(samples, samplesVals):
"""
Finds two nearest from class and two from outer samples and performs weighted average of their values.
As weight is used distance. If distance from some data sample is zero than it's
value is returned. Beware that if there is multiple samples with zero distance
than zero value(outer) haves priority.
Outer class have values that are equal or smaller than 0 (by default) and actual class must have values greater than zero.
:param samples: Coords for interpolation.
:type samples: np.array
:param samplesVals: Values on class coords.
:type samplesVals: np.array
"""
cInd=np.where(samplesVals>0)
classData=samples[cInd]
classVals=samplesVals[cInd]
haveClassData=classData.shape[0]>0
oInd=np.where(samplesVals<=0)
outerData=samples[oInd]
outerVals=samplesVals[oInd]
haveOuterData=outerData.shape[0]>0
#nearest 2x2 (from each class) interpolate
if haveClassData:
fnClass=cKDTree(classData)
fnClassMaxNeigh=1 if classData.shape[0]<2 else 2
if haveOuterData:
fnOuter=cKDTree(outerData)
fnOuterMaxNeigh=1 if outerData.shape[0]<2 else 2
def res(p):
#check the nearest
if haveClassData:
dC, iC=fnClass.query(p,fnClassMaxNeigh)
if fnClassMaxNeigh==1:
#we need col vectors
dC=dC[:, np.newaxis]
iC=iC[:, np.newaxis]
if haveOuterData:
dO, oC=fnOuter.query(p,fnOuterMaxNeigh)
if fnOuterMaxNeigh==1:
#we need col vectors
dO=dO[:, np.newaxis]
oC=oC[:, np.newaxis]
if haveClassData and haveOuterData:
values=np.hstack((classVals[iC],outerVals[oC]))
del iC
del oC
distances=np.hstack((dC,dO))
elif haveClassData:
values=classVals[iC]
del iC
distances=dC
else:
#only outer remains
values=outerVals[oC]
del oC
distances=dO
with np.errstate(divide='ignore',invalid='ignore'):
#we want to detect zero distance values
#this values will show as inf in 1/distances and nans in avg
distances=1./distances
avg=np.average(values, axis=1, weights=distances)
#find problems, if exists
problems=np.where(np.isnan(avg))
if problems[0].shape[0]>0:
problemsCols=(problems[0],np.array(np.argmax(np.isinf(distances[problems]),axis=1))) #we are interested in the first only
#change the nans with values of the problematic points
avg[problems]=values[problemsCols]
return avg
return res
def fNearest2x2FromEachClass2AtAll(samples, samplesVals):
"""
Finds two nearest from each class(outer and act. class), two at all and performs weighted average of their values.
As weight is used distance. If distance from some data sample is zero than it's
value is returned.
Outer class have values that are equal or smaller than 0 (by default) and actual class must have values greater than zero.
:param samples: Coords for interpolation.
:type samples: np.array
:param samplesVals: Values on class coords.
:type samplesVals: np.array
"""
cInd=np.where(samplesVals>0)
classData=samples[cInd]
classVals=samplesVals[cInd]
haveClassData=classData.shape[0]>0
oInd=np.where(samplesVals<=0)
outerData=samples[oInd]
outerVals=samplesVals[oInd]
haveOuterData=outerData.shape[0]>0
fnAll=cKDTree(samples)
fnAllMaxNeigh=1 if samplesVals.shape[0]<2 else 2
if haveClassData:
fnClass=cKDTree(classData)
fnClassMaxNeigh=1 if classData.shape[0]<2 else 2
if haveOuterData:
fnOuter=cKDTree(outerData)
fnOuterMaxNeigh=1 if outerData.shape[0]<2 else 2
def res(p):
#check the nearest
DA, IA = fnAll.query(p,fnAllMaxNeigh)
if fnAllMaxNeigh==1:
#we need col vectors
DA=DA[:, np.newaxis]
IA=IA[:, np.newaxis]
if haveClassData:
dC, iC=fnClass.query(p,fnClassMaxNeigh)
if fnClassMaxNeigh==1:
#we need col vectors
dC=dC[:, np.newaxis]
iC=iC[:, np.newaxis]
if haveOuterData:
dO, oC=fnOuter.query(p,fnOuterMaxNeigh)
if fnOuterMaxNeigh==1:
#we need col vectors
dO=dO[:, np.newaxis]
oC=oC[:, np.newaxis]
#compile data we have
if haveClassData and haveOuterData:
values=np.hstack((samplesVals[IA],classVals[iC],outerVals[oC]))
del iC
del oC
distances=np.hstack((DA,dC,dO))
elif haveClassData:
values=np.hstack((samplesVals[IA],classVals[iC]))
del iC
distances=np.hstack((DA,dC))
else:
#we have just outer not class
values=np.hstack((samplesVals[IA],outerVals[oC]))
del oC
distances=np.hstack((DA,dO))
del IA
with np.errstate(divide='ignore',invalid='ignore'):
#we want to detect zero distance values
#this values will show as inf in 1/distances and nans in avg
distances=1./distances
avg=np.average(values, axis=1, weights=distances)
#find problems, if exists
problems=np.where(np.isnan(avg))
if problems[0].shape[0]>0:
problemsCols=(problems[0],np.array(np.argmax(np.isinf(distances[problems]),axis=1))) #we are interested in the first only
#change the nans with values of the problematic points
avg[problems]=values[problemsCols]
return avg
return res
| 32.70892
| 140
| 0.600402
| 842
| 6,967
| 4.966746
| 0.210214
| 0.015782
| 0.010043
| 0.013152
| 0.794596
| 0.751793
| 0.719751
| 0.686035
| 0.686035
| 0.686035
| 0
| 0.015285
| 0.314483
| 6,967
| 212
| 141
| 32.863208
| 0.860343
| 0.319937
| 0
| 0.774775
| 0
| 0
| 0.005245
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.054054
| false
| 0
| 0.018018
| 0
| 0.126126
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 0
| 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
| 4
|
f3d815396006808d29e207aa1dcfa8bd59a75359
| 473
|
py
|
Python
|
homeapp/forms.py
|
UoW-CPC/cfg-dmproject
|
2d1c7f4412b60f8943f884dc2398c911cf090862
|
[
"Apache-2.0"
] | null | null | null |
homeapp/forms.py
|
UoW-CPC/cfg-dmproject
|
2d1c7f4412b60f8943f884dc2398c911cf090862
|
[
"Apache-2.0"
] | null | null | null |
homeapp/forms.py
|
UoW-CPC/cfg-dmproject
|
2d1c7f4412b60f8943f884dc2398c911cf090862
|
[
"Apache-2.0"
] | null | null | null |
from django import forms
class RegForm(forms.Form):
firstname = forms.CharField(label='First name:', max_length=100)
lastname = forms.CharField(label='Last name:', max_length=100)
email = forms.EmailField() #.CharField(label='Email:', max_length=100)
username = forms.CharField(label='User name:', max_length=100)
password = forms.CharField(widget=forms.PasswordInput()) #forms.CharField(label='Password:', max_length=100)
| 47.3
| 116
| 0.689218
| 57
| 473
| 5.631579
| 0.421053
| 0.218069
| 0.186916
| 0.149533
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.038265
| 0.171247
| 473
| 9
| 117
| 52.555556
| 0.780612
| 0.194503
| 0
| 0
| 0
| 0
| 0.081794
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0.142857
| 0.142857
| 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
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
f3dc08111a8ccaf34220094b60548e65d6768b40
| 9,566
|
py
|
Python
|
src/ensemble.py
|
jasoriya/HackerEarth-DL-3-Challenge
|
b1bd5b3955913327408541ef4b14c260b9014593
|
[
"MIT"
] | 2
|
2018-08-09T19:34:14.000Z
|
2018-08-09T19:34:15.000Z
|
src/ensemble.py
|
jasoriya/HackerEarth-DL-3-Challenge
|
b1bd5b3955913327408541ef4b14c260b9014593
|
[
"MIT"
] | null | null | null |
src/ensemble.py
|
jasoriya/HackerEarth-DL-3-Challenge
|
b1bd5b3955913327408541ef4b14c260b9014593
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
"""
Created on Sat Apr 21 11:51:52 2018
@author: Shreyans
"""
import os
import sys
sys.path.append('../src')
sys.path.append('../data/train_img')
import numpy as np
import pandas as pd
from keras.applications.inception_resnet_v2 import InceptionResNetV2
from keras.applications.inception_v3 import InceptionV3
from keras.applications.vgg16 import VGG16
from keras.models import Model, load_model
from keras.layers import Dense, Input, Flatten, Dropout
from keras.layers.normalization import BatchNormalization
from keras.callbacks import ModelCheckpoint, EarlyStopping, ReduceLROnPlateau, History
from keras.optimizers import Adam
from keras.preprocessing.image import ImageDataGenerator
from keras.preprocessing import image
from sklearn.model_selection import train_test_split
def get_jpeg_data_files_paths():
"""
Returns the input file folders path
:return: list of strings
The input file paths as list [train_jpeg_dir, test_jpeg_dir, train_csv_file]
"""
data_root_folder = os.path.abspath("../data/")
train_jpeg_dir = os.path.join(data_root_folder, 'train_img/')
test_jpeg_dir = os.path.join(data_root_folder, 'test_img/')
train_csv_file = os.path.join(data_root_folder, 'meta-data', 'train.csv')
test_csv_file = os.path.join(data_root_folder, 'meta-data', 'test.csv')
return [train_jpeg_dir, test_jpeg_dir, train_csv_file, test_csv_file]
def get_train_generator(batch_size, filenames, labels_df, train_jpeg_dir):
"""
Returns a batch generator which transforms chunk of raw images into numpy matrices
and then "yield" them for the classifier. Doing so allow to greatly optimize
memory usage as the images are processed then deleted by chunks (defined by batch_size)
instead of preprocessing them all at once and feeding them to the classifier.
:param batch_size: int
The batch size
:param filenames: Series
The list of train image filenames
:param labels_df: DataFrame
Training labels
:param train_jpeg_dir: str
Train directory path
:return: generator
The batch generator
"""
# Image Augmentation
datagen = ImageDataGenerator(
rescale=1./255,
shear_range=0.2,
horizontal_flip=True,
vertical_flip=True) # randomly flip images horizontally
loop_range = len(filenames)
while True:
for i in range(loop_range):
start_offset = batch_size * i
# The last remaining files could be smaller than the batch_size
range_offset = min(batch_size, loop_range - start_offset)
# If we reached the end of the list then we break the loop
if range_offset <= 0:
break
batch_features = np.zeros((range_offset, *img_resize, 3))
batch_labels = np.zeros((range_offset, len(labels_df.columns)))
for j in range(range_offset):
img_path = train_jpeg_dir + filenames.iloc[start_offset + j]
img = image.load_img(img_path, target_size=img_resize)
img = image.img_to_array(img)
img_array = img[:, :, ::-1]
# Zero-center by mean pixel
img_array[:, :, 0] -= 103.939
img_array[:, :, 1] -= 116.779
img_array[:, :, 2] -= 123.68
batch_features[j] = img_array
batch_labels[j] = labels_df.iloc[start_offset + j]
# Augment the images (using Keras allow us to add randomization/shuffle to augmented images)
# Here the next batch of the data generator (and only one for this iteration)
# is taken and returned in the yield statement
yield next(datagen.flow(batch_features, batch_labels, range_offset))
def get_validation_generator(batch_size, filenames, labels_df, train_jpeg_dir):
"""
Returns a batch generator which transforms chunk of raw images into numpy matrices
and then "yield" them for the classifier. Doing so allow to greatly optimize
memory usage as the images are processed then deleted by chunks (defined by batch_size)
instead of preprocessing them all at once and feeding them to the classifier.
:param batch_size: int
The batch size
:param filenames: Series
The list of validation image filenames
:param labels_df: DataFrame
Validation labels
:param train_jpeg_dir: str
Validation directory path
:return: generator
The batch generator
"""
# Image Augmentation
datagen = ImageDataGenerator(rescale=1./255)
loop_range = len(filenames)
while True:
for i in range(loop_range):
start_offset = batch_size * i
# The last remaining files could be smaller than the batch_size
range_offset = min(batch_size, loop_range - start_offset)
# If we reached the end of the list then we break the loop
if range_offset <= 0:
break
batch_features = np.zeros((range_offset, *img_resize, 3))
batch_labels = np.zeros((range_offset, len(labels_df.columns)))
for j in range(range_offset):
img_path = train_jpeg_dir + filenames.iloc[start_offset + j]
img = image.load_img(img_path, target_size=img_resize)
img = image.img_to_array(img)
batch_features[j] = img
batch_labels[j] = labels_df.iloc[start_offset + j]
# Here the next batch of the data generator (and only one for this iteration)
# is taken and returned in the yield statement
yield next(datagen.flow(batch_features, batch_labels, range_offset))
def get_prediction_generator(batch_size, test_filename, test_jpeg_dir):
"""
Returns a batch generator which transforms chunk of raw images into numpy matrices
and then "yield" them for the classifier. Doing so allow to greatly optimize
memory usage as the images are processed then deleted by chunks (defined by batch_size)
instead of preprocessing them all at once and feeding them to the classifier.
:param batch_size: int
The batch size
:param test_filename: Series
The list of test image filenames
:param test_jpeg_dir: str
Test directory path
:return: generator
The batch generator
"""
# NO SHUFFLE HERE as we need our predictions to be in the same order as the inputs
loop_range = len(test_filename)
while True:
for i in range(loop_range):
start_offset = batch_size * i
# The last remaining files could be smaller than the batch_size
range_offset = min(batch_size, loop_range - start_offset)
# If we reached the end of the list then we break the loop
if range_offset <= 0:
break
img_arrays = np.zeros((range_offset, *img_resize, 3))
for j in range(range_offset):
img_path = test_jpeg_dir + test_filename.iloc[start_offset + j]
img = image.load_img(img_path, target_size=img_resize)
img = image.img_to_array(img)
img_array = img[:, :, ::-1]
# Zero-center by mean pixel
img_array[:, :, 0] -= 103.939
img_array[:, :, 1] -= 116.779
img_array[:, :, 2] -= 123.68
img_array = img_array / 255
img_arrays[j] = img_array
yield img_arrays
def create_inception_resnet(img_dim=(139, 139, 3)):
input_tensor = Input(shape=img_dim)
base_model = InceptionResNetV2(include_top=False,
weights='imagenet',
input_shape=img_dim)
for layer in base_model.layers[:8]:
layer.trainable = False
bn = BatchNormalization()(input_tensor)
x = base_model(bn)
x = Flatten()(x)
output = Dense(85, activation='sigmoid')(x)
model = Model(input_tensor, output)
return model
def create_inceptionV3(img_dim=(139, 139, 3)):
input_tensor = Input(shape=img_dim)
base_model = InceptionV3(include_top=False,
weights='imagenet',
input_shape=img_dim)
for layer in base_model.layers[:8]:
layer.trainable = False
bn = BatchNormalization()(input_tensor)
x = base_model(bn)
x = Flatten()(x)
output = Dense(85, activation='sigmoid')(x)
model = Model(input_tensor, output)
return model
def create_vgg16(img_dim=(128, 128, 3)):
input_tensor = Input(shape=img_dim)
base_model = VGG16(include_top=False,
weights='imagenet',
input_shape=img_dim)
for layer in base_model.layers[:8]:
layer.trainable = False
bn = BatchNormalization()(input_tensor)
x = base_model(bn)
x = Flatten()(x)
output = Dense(85, activation='sigmoid')(x)
model = Model(input_tensor, output)
return model
| 39.692946
| 108
| 0.615095
| 1,208
| 9,566
| 4.682947
| 0.190397
| 0.03341
| 0.019091
| 0.021213
| 0.739791
| 0.739791
| 0.717872
| 0.704967
| 0.688881
| 0.657239
| 0
| 0.018088
| 0.312252
| 9,566
| 241
| 109
| 39.692946
| 0.841769
| 0.292808
| 0
| 0.629921
| 0
| 0
| 0.020463
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.055118
| false
| 0
| 0.11811
| 0
| 0.204724
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
6d06d6f2096cab88c3f1a19c13366df33d9e1dd1
| 109
|
py
|
Python
|
new1.py
|
kpmishraindia/wowmeter
|
6e7c681d5fbc0a69e973c241c9fc134f74f64b2d
|
[
"Apache-2.0"
] | null | null | null |
new1.py
|
kpmishraindia/wowmeter
|
6e7c681d5fbc0a69e973c241c9fc134f74f64b2d
|
[
"Apache-2.0"
] | null | null | null |
new1.py
|
kpmishraindia/wowmeter
|
6e7c681d5fbc0a69e973c241c9fc134f74f64b2d
|
[
"Apache-2.0"
] | null | null | null |
#new file as required
print ('ne1')
print ('ne2')
#C:\Users\kpmis\OneDrive\Documents\GitHub\wowmeter\new1.py
| 21.8
| 58
| 0.743119
| 17
| 109
| 4.764706
| 0.941176
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.03
| 0.082569
| 109
| 4
| 59
| 27.25
| 0.78
| 0.706422
| 0
| 0
| 0
| 0
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 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
| 0
| 0
| 0
| 1
|
0
| 4
|
6d1bc8d763567a70c2a54d2261377d336d4be928
| 1,545
|
py
|
Python
|
utils/logging.py
|
bulv1ne/django_utils
|
bf19923dcfdff5c2655500e5b61962c479074d58
|
[
"MIT"
] | 1
|
2017-05-05T11:57:26.000Z
|
2017-05-05T11:57:26.000Z
|
utils/logging.py
|
bulv1ne/django_utils
|
bf19923dcfdff5c2655500e5b61962c479074d58
|
[
"MIT"
] | 2
|
2021-04-06T18:14:52.000Z
|
2021-06-01T22:46:45.000Z
|
utils/logging.py
|
bulv1ne/django-utils
|
bf19923dcfdff5c2655500e5b61962c479074d58
|
[
"MIT"
] | null | null | null |
import logging
class Logger:
def __init__(self, **kwargs):
self.options = kwargs
self.logger = logging.getLogger(kwargs.get("name"))
def copy(self, **kwargs):
options = self.options.copy()
options.update(kwargs)
return Logger(**options)
def construct_msg(self, msg):
return ":".join(
[
"{}={}".format(key, value)
for key, value in self.options.get("fields", {}).items()
]
+ [str(msg)]
)
def name(self, name):
return self.copy(name=name)
def fields(self, **kwargs):
return self.copy(fields=kwargs)
def log(self, level, msg, *args, **kwargs):
self.logger.log(level, self.construct_msg(msg), *args, **kwargs)
def debug(self, msg, *args, **kwargs):
self.logger.debug(self.construct_msg(msg), *args, **kwargs)
def info(self, msg, *args, **kwargs):
self.logger.info(self.construct_msg(msg), *args, **kwargs)
def warning(self, msg, *args, **kwargs):
self.logger.warning(self.construct_msg(msg), *args, **kwargs)
def error(self, msg, *args, **kwargs):
self.logger.error(self.construct_msg(msg), *args, **kwargs)
def critical(self, msg, *args, **kwargs):
self.logger.critical(self.construct_msg(msg), *args, **kwargs)
def exception(self, msg, *args, **kwargs):
self.logger.exception(self.construct_msg(msg), *args, **kwargs)
logger = Logger()
def getLogger(name):
return Logger(name=name)
| 27.589286
| 72
| 0.589644
| 187
| 1,545
| 4.807487
| 0.187166
| 0.10901
| 0.202447
| 0.132369
| 0.451613
| 0.426029
| 0.213571
| 0
| 0
| 0
| 0
| 0
| 0.245955
| 1,545
| 55
| 73
| 28.090909
| 0.771674
| 0
| 0
| 0
| 0
| 0
| 0.010356
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.342105
| false
| 0
| 0.026316
| 0.105263
| 0.526316
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
6d1db2e2a84f59121b73e9f8efcbd5a08c60971d
| 170
|
py
|
Python
|
djmaps/query.py
|
septianpri/djmaps
|
9e2a43e668d4015c9b68a8c69174e0e945f85943
|
[
"MIT"
] | null | null | null |
djmaps/query.py
|
septianpri/djmaps
|
9e2a43e668d4015c9b68a8c69174e0e945f85943
|
[
"MIT"
] | null | null | null |
djmaps/query.py
|
septianpri/djmaps
|
9e2a43e668d4015c9b68a8c69174e0e945f85943
|
[
"MIT"
] | null | null | null |
from pprint import pprint
class poidepok:
def getZoneVolume(req):
return """
select *, st_asgeojson(geom) as geomjson from data.poi
"""
| 18.888889
| 66
| 0.605882
| 19
| 170
| 5.368421
| 0.894737
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.305882
| 170
| 8
| 67
| 21.25
| 0.864407
| 0
| 0
| 0
| 0
| 0
| 0.447059
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.166667
| 0.166667
| 0.666667
| 0.166667
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
6d366950170a3c40a140225c9efb7e0d6db01360
| 17
|
py
|
Python
|
pgnlp/__init__.py
|
porfyriosg/pgnlp
|
d43b104f16dd8ca1fa7a988bcd0ba6f6183f3a4c
|
[
"MIT"
] | 4
|
2020-12-24T16:00:33.000Z
|
2020-12-24T21:46:14.000Z
|
pgnlp/__init__.py
|
porfyriosg/pgnlp
|
d43b104f16dd8ca1fa7a988bcd0ba6f6183f3a4c
|
[
"MIT"
] | null | null | null |
pgnlp/__init__.py
|
porfyriosg/pgnlp
|
d43b104f16dd8ca1fa7a988bcd0ba6f6183f3a4c
|
[
"MIT"
] | null | null | null |
__version__='1.4'
| 17
| 17
| 0.764706
| 3
| 17
| 3
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 0
| 17
| 1
| 17
| 17
| 0.411765
| 0
| 0
| 0
| 0
| 0
| 0.166667
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
6d5b6ee91e297732bd47a195ce4904e5b0d20e97
| 185
|
py
|
Python
|
CursoPython/Python_Mundo_1/Script - Desafio 30.py
|
XiaoNaihe/Python
|
5ba12ae8beff325b069d13210d34116373de2f5d
|
[
"MIT"
] | null | null | null |
CursoPython/Python_Mundo_1/Script - Desafio 30.py
|
XiaoNaihe/Python
|
5ba12ae8beff325b069d13210d34116373de2f5d
|
[
"MIT"
] | null | null | null |
CursoPython/Python_Mundo_1/Script - Desafio 30.py
|
XiaoNaihe/Python
|
5ba12ae8beff325b069d13210d34116373de2f5d
|
[
"MIT"
] | null | null | null |
numero = int(input('Me diga um numero: '))
resultado = numero % 2
if resultado == 0:
print('O numero {} é PAR'.format(numero))
else:
print('O numero {} é IMPAR'.format(numero))
| 26.428571
| 47
| 0.637838
| 28
| 185
| 4.214286
| 0.607143
| 0.101695
| 0.20339
| 0.220339
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.013333
| 0.189189
| 185
| 6
| 48
| 30.833333
| 0.773333
| 0
| 0
| 0
| 0
| 0
| 0.297297
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.333333
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
edbb96804ab98a2491fccec6891be68fbac36fac
| 93
|
py
|
Python
|
Python/Topics/Iterators/Calculating profit/main.py
|
drtierney/hyperskill-problems
|
b74da993f0ac7bcff1cbd5d89a3a1b06b05f33e0
|
[
"MIT"
] | 5
|
2020-08-29T15:15:31.000Z
|
2022-03-01T18:22:34.000Z
|
Python/Topics/Iterators/Calculating profit/main.py
|
drtierney/hyperskill-problems
|
b74da993f0ac7bcff1cbd5d89a3a1b06b05f33e0
|
[
"MIT"
] | null | null | null |
Python/Topics/Iterators/Calculating profit/main.py
|
drtierney/hyperskill-problems
|
b74da993f0ac7bcff1cbd5d89a3a1b06b05f33e0
|
[
"MIT"
] | 1
|
2020-12-02T11:13:14.000Z
|
2020-12-02T11:13:14.000Z
|
for month, cost, revenue in zip(months, costs, revenues):
print(month, (revenue - cost))
| 31
| 57
| 0.688172
| 13
| 93
| 4.923077
| 0.769231
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.172043
| 93
| 2
| 58
| 46.5
| 0.831169
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 0.5
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
edbc9f46ab45d6922b493ddd42ccec3dcc82aee4
| 147
|
py
|
Python
|
src/easy/strings-and-arrows/solutions/python/solution.py
|
rdtsc/codeeval-solutions
|
d5c06baf89125e9e9f4b163ee57e5a8f7e73e717
|
[
"MIT"
] | null | null | null |
src/easy/strings-and-arrows/solutions/python/solution.py
|
rdtsc/codeeval-solutions
|
d5c06baf89125e9e9f4b163ee57e5a8f7e73e717
|
[
"MIT"
] | null | null | null |
src/easy/strings-and-arrows/solutions/python/solution.py
|
rdtsc/codeeval-solutions
|
d5c06baf89125e9e9f4b163ee57e5a8f7e73e717
|
[
"MIT"
] | null | null | null |
#!/usr/bin/env python3
import re
import sys
for line in (line.rstrip() for line in sys.stdin):
print(len(re.findall('(?=<--<<|>>-->)', line)))
| 18.375
| 50
| 0.612245
| 23
| 147
| 3.913043
| 0.652174
| 0.155556
| 0.2
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007874
| 0.136054
| 147
| 7
| 51
| 21
| 0.700787
| 0.142857
| 0
| 0
| 0
| 0
| 0.12
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0.25
| 1
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
ede1b3a15036ced7fce323ab7a545ffe011577fd
| 739
|
py
|
Python
|
pmaf/biome/assembly/_metakit.py
|
mmtechslv/PhyloMAF
|
bab43dd4a4d2812951b1fdf4f1abb83edb79ea88
|
[
"BSD-3-Clause"
] | 1
|
2021-07-02T06:24:17.000Z
|
2021-07-02T06:24:17.000Z
|
pmaf/biome/assembly/_metakit.py
|
mmtechslv/PhyloMAF
|
bab43dd4a4d2812951b1fdf4f1abb83edb79ea88
|
[
"BSD-3-Clause"
] | 1
|
2021-06-28T12:02:46.000Z
|
2021-06-28T12:02:46.000Z
|
pmaf/biome/assembly/_metakit.py
|
mmtechslv/PhyloMAF
|
bab43dd4a4d2812951b1fdf4f1abb83edb79ea88
|
[
"BSD-3-Clause"
] | null | null | null |
from abc import abstractmethod
from pmaf.biome._metakit import BiomeFeatureMetabase, BiomeSampleMetabase
class BiomeAssemblyBackboneMetabase(BiomeFeatureMetabase, BiomeSampleMetabase):
@abstractmethod
def export(self, output_dir, *args, **kwargs):
pass
@abstractmethod
def get_subset(self, *args, **kwargs):
pass
@abstractmethod
def add_essentials(self, *args):
pass
@abstractmethod
def to_otu_table(self, *args, **kwargs):
pass
@abstractmethod
def write_otu_table(self, output_fp, *args, **kwargs):
pass
@property
@abstractmethod
def essentials(self):
pass
@property
@abstractmethod
def controller(self):
pass
| 21.114286
| 79
| 0.67253
| 71
| 739
| 6.873239
| 0.422535
| 0.243852
| 0.114754
| 0.172131
| 0.206967
| 0.143443
| 0
| 0
| 0
| 0
| 0
| 0
| 0.244926
| 739
| 34
| 80
| 21.735294
| 0.874552
| 0
| 0
| 0.615385
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.269231
| false
| 0.269231
| 0.076923
| 0
| 0.384615
| 0
| 0
| 0
| 0
| null | 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
edf6dc384ab4241ba3b72f963c28a82263bab44a
| 155
|
py
|
Python
|
tests/classification/FourClass_500/ws_FourClass_500_GradientBoostingClassifier_sqlite_code_gen.py
|
antoinecarme/sklearn2sql_heroku
|
d680db10683daa419324461eeea851dd8b103ad5
|
[
"BSD-3-Clause"
] | 1
|
2019-07-09T14:45:18.000Z
|
2019-07-09T14:45:18.000Z
|
tests/classification/FourClass_500/ws_FourClass_500_GradientBoostingClassifier_sqlite_code_gen.py
|
antoinecarme/sklearn2sql_heroku
|
d680db10683daa419324461eeea851dd8b103ad5
|
[
"BSD-3-Clause"
] | 5
|
2017-11-13T13:35:37.000Z
|
2021-11-11T12:57:20.000Z
|
tests/classification/FourClass_500/ws_FourClass_500_GradientBoostingClassifier_sqlite_code_gen.py
|
antoinecarme/sklearn2sql_heroku
|
d680db10683daa419324461eeea851dd8b103ad5
|
[
"BSD-3-Clause"
] | 1
|
2021-09-19T15:05:33.000Z
|
2021-09-19T15:05:33.000Z
|
from sklearn2sql_heroku.tests.classification import generic as class_gen
class_gen.test_model("GradientBoostingClassifier" , "FourClass_500" , "sqlite")
| 31
| 79
| 0.832258
| 18
| 155
| 6.888889
| 0.888889
| 0.129032
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.028169
| 0.083871
| 155
| 4
| 80
| 38.75
| 0.84507
| 0
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| 0
| 0
| 0
| 0.290323
| 0.167742
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
610249e451b7060daafdb21b46c93617b1721221
| 1,565
|
py
|
Python
|
tests/test_api_helpers.py
|
KyleKing/Kitsu-Library-Where-Stream
|
10bb6b6de02efa97aac672775d7070c64b098217
|
[
"MIT"
] | 2
|
2019-07-01T09:01:03.000Z
|
2020-02-22T00:51:59.000Z
|
tests/test_api_helpers.py
|
KyleKing/Kitsu-Library-Where-Stream
|
10bb6b6de02efa97aac672775d7070c64b098217
|
[
"MIT"
] | 1
|
2021-04-10T13:06:19.000Z
|
2021-05-26T00:11:33.000Z
|
tests/test_api_helpers.py
|
KyleKing/Kitsu-Library-Where-Stream
|
10bb6b6de02efa97aac672775d7070c64b098217
|
[
"MIT"
] | null | null | null |
"""Test the api_helpers.py file."""
from kitsu_lib.api_helpers import (get_anime, get_data, get_kitsu, get_library, get_streams, get_user, get_user_id,
selective_request)
# def test_get_data():
# """Test get_data with simple smoke test."""
# resp = get_data(url, kwargs=None, debug=False) # act
#
# assert len(resp['data']) == 1
# def test_selective_request():
# """Test selective_request with simple smoke test."""
# resp = selective_request(prefix, url, **get_kwargs) # act
#
# assert len(resp['data']) == 1
# def test_get_kitsu():
# """Test get_kitsu with simple smoke test."""
# resp = get_kitsu(endpoint, prefix='kitsu', **kwargs) # act
#
# assert len(resp['data']) == 1
# def test_get_user():
# """Test get_user with simple smoke test."""
# resp = get_user(username) # act
#
# assert len(resp['data']) == 1
# def test_get_user_id():
# """Test get_user_id with simple smoke test."""
# resp = get_user_id(username) # act
#
# assert len(resp['data']) == 1
# def test_get_library():
# """Test get_library with simple smoke test."""
# resp = get_library(user_id, is_anime=True) # act
#
# assert len(resp['data']) == 1
# def test_get_anime():
# """Test get_anime with simple smoke test."""
# resp = get_anime(anime_link) # act
#
# assert len(resp['data']) == 1
# def test_get_streams():
# """Test get_streams with simple smoke test."""
# resp = get_streams(stream_link) # act
#
# assert len(resp['data']) == 1
| 26.083333
| 115
| 0.614058
| 216
| 1,565
| 4.208333
| 0.185185
| 0.107811
| 0.132013
| 0.167217
| 0.541254
| 0.515952
| 0.372937
| 0.275028
| 0.244224
| 0.176018
| 0
| 0.006601
| 0.225559
| 1,565
| 59
| 116
| 26.525424
| 0.743399
| 0.821086
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
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| 0
| null | 0
| 0
| 1
| 0
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| 0
| 0
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| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
61191aa38181c4f6f0cb6a1b6de99e54051dd1e2
| 219
|
py
|
Python
|
ServicePortal/App/admin.py
|
bubbaayala/Portal
|
424ca12b413fc866a4a3df71051f0308f22f6fb0
|
[
"MIT"
] | null | null | null |
ServicePortal/App/admin.py
|
bubbaayala/Portal
|
424ca12b413fc866a4a3df71051f0308f22f6fb0
|
[
"MIT"
] | null | null | null |
ServicePortal/App/admin.py
|
bubbaayala/Portal
|
424ca12b413fc866a4a3df71051f0308f22f6fb0
|
[
"MIT"
] | null | null | null |
# -*- coding: utf-8 -*-
from __future__ import unicode_literals
from django.contrib import admin
from .models import App, AppDetail
# Register your models here.
admin.site.register(App)
admin.site.register(AppDetail)
| 21.9
| 39
| 0.776256
| 30
| 219
| 5.5
| 0.6
| 0.109091
| 0.206061
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005208
| 0.123288
| 219
| 9
| 40
| 24.333333
| 0.854167
| 0.219178
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.6
| 0
| 0.6
| 0
| 0
| 0
| 0
| null | 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
b6267cf67e859a51151ab60da85917889c881c99
| 151
|
py
|
Python
|
src/actions/utils.py
|
riskfuel/k8s-mig-operator
|
6d4f5b324228f5b2549e1187806ed44d1c4176a2
|
[
"MIT"
] | 9
|
2020-08-24T13:41:35.000Z
|
2021-05-12T09:44:57.000Z
|
src/actions/utils.py
|
riskfuel/k8s-mig-operator
|
6d4f5b324228f5b2549e1187806ed44d1c4176a2
|
[
"MIT"
] | null | null | null |
src/actions/utils.py
|
riskfuel/k8s-mig-operator
|
6d4f5b324228f5b2549e1187806ed44d1c4176a2
|
[
"MIT"
] | 1
|
2021-10-30T07:56:07.000Z
|
2021-10-30T07:56:07.000Z
|
def load_context():
import sys, os
current_path = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, current_path + '/../')
| 30.2
| 61
| 0.649007
| 21
| 151
| 4.333333
| 0.619048
| 0.241758
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.00813
| 0.18543
| 151
| 5
| 62
| 30.2
| 0.731707
| 0
| 0
| 0
| 0
| 0
| 0.026316
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.25
| 0
| 0.5
| 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
| 0
| 0
| 0
|
0
| 4
|
b63ed83916a3d0916bf5bb2ec79a1e104f57793b
| 342
|
py
|
Python
|
b3stockinfo/parsers.py
|
jonathadv/b3-stock-info
|
f2fea4a813797a83dbe9455e5c87970fc9105a3b
|
[
"MIT"
] | null | null | null |
b3stockinfo/parsers.py
|
jonathadv/b3-stock-info
|
f2fea4a813797a83dbe9455e5c87970fc9105a3b
|
[
"MIT"
] | 1
|
2021-03-31T19:53:03.000Z
|
2021-03-31T19:53:03.000Z
|
b3stockinfo/parsers.py
|
jonathadv/b3-stock-info
|
f2fea4a813797a83dbe9455e5c87970fc9105a3b
|
[
"MIT"
] | null | null | null |
import re
def number_parser(value):
regex = r"R\$|%|\."
value = re.sub(regex, "", value)
if "," in value:
value = value.replace(",", ".")
return float(value)
return int(value)
def name_parser(value):
return value.split("-")[1].strip()
def ticker_parser(value):
return value.split("-")[0].strip()
| 18
| 39
| 0.573099
| 44
| 342
| 4.386364
| 0.477273
| 0.170984
| 0.176166
| 0.227979
| 0.279793
| 0
| 0
| 0
| 0
| 0
| 0
| 0.007576
| 0.22807
| 342
| 18
| 40
| 19
| 0.723485
| 0
| 0
| 0
| 0
| 0
| 0.038012
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0.083333
| 0.166667
| 0.666667
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 4
|
b63ff34a48fd46ed65f2dccc0c0942de7d5b1dae
| 89
|
py
|
Python
|
pc/adjustfather.py
|
zy6p/adjust
|
ddcde0a99c6d01038de1f4675ad9409759c03ef0
|
[
"Apache-2.0"
] | 1
|
2020-12-25T13:39:16.000Z
|
2020-12-25T13:39:16.000Z
|
pc/adjustfather.py
|
zy6p/adjust
|
ddcde0a99c6d01038de1f4675ad9409759c03ef0
|
[
"Apache-2.0"
] | null | null | null |
pc/adjustfather.py
|
zy6p/adjust
|
ddcde0a99c6d01038de1f4675ad9409759c03ef0
|
[
"Apache-2.0"
] | null | null | null |
import numpy as np
import pandas as pd
class AdjustFather:
n_num = 1
t_num = 0
| 11.125
| 19
| 0.674157
| 16
| 89
| 3.625
| 0.8125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.031746
| 0.292135
| 89
| 7
| 20
| 12.714286
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 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
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
b658d967ae2ca6e8fa341cfc41ad497af3f55e65
| 195
|
py
|
Python
|
text/_cascade/_typing/image/base.py
|
jedhsu/text
|
8525b602d304ac571a629104c48703443244545c
|
[
"Apache-2.0"
] | null | null | null |
text/_cascade/_typing/image/base.py
|
jedhsu/text
|
8525b602d304ac571a629104c48703443244545c
|
[
"Apache-2.0"
] | null | null | null |
text/_cascade/_typing/image/base.py
|
jedhsu/text
|
8525b602d304ac571a629104c48703443244545c
|
[
"Apache-2.0"
] | null | null | null |
"""
Image base type.
"""
from dataclasses import dataclass
from typing import Callable
class _Image(type):
pass
@dataclass
class Paint:
paint_: Callable
paint_order: property
| 9.75
| 33
| 0.707692
| 23
| 195
| 5.869565
| 0.608696
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.220513
| 195
| 19
| 34
| 10.263158
| 0.888158
| 0.082051
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.125
| 0.25
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 1
| 0
|
0
| 4
|
b673c64b21b7116b730dbf4d4bb25bd807eb531c
| 4,808
|
py
|
Python
|
py3/enecon.py
|
yaoweipeng/dp
|
8cdbc08a89ad3cc7bc452a3d19618ac920f51db4
|
[
"BSD-3-Clause"
] | null | null | null |
py3/enecon.py
|
yaoweipeng/dp
|
8cdbc08a89ad3cc7bc452a3d19618ac920f51db4
|
[
"BSD-3-Clause"
] | null | null | null |
py3/enecon.py
|
yaoweipeng/dp
|
8cdbc08a89ad3cc7bc452a3d19618ac920f51db4
|
[
"BSD-3-Clause"
] | null | null | null |
import sdf
import matplotlib.pyplot as plt
import numpy as np
plt.style.use('seaborn-paper')
plt.rcParams['font.size'] = 24
def cm2inch(value):
return value/2.54
Num = 26
TeS1 = np.ones(Num)
TeS2 = np.ones(Num)
TeS3 = np.ones(Num)
part1 = np.ones(Num)
part2 = np.ones(Num)
pho1 = np.ones(Num)
pho2 = np.ones(Num)
time = np.ones(Num)
file = '/Users/yaowp/code/merge/epoch2d/'
me = 9.1e-31
c = 3e8
# print(e0)
folder = 'Data0'
for i in range(Num):
ii = i
time[i] = ii/10
fname = file+folder+'/'+str(ii).zfill(4)+'.sdf'
datafile = sdf.read(fname)
TeS1[i] = datafile.Total_Particle_Energy_in_Simulation__J_.data
fname = file+folder+'/6'+str(ii).zfill(4)+'.sdf'
datafile = sdf.read(fname)
Gam1 = datafile.Particles_Gamma_subset_part_ele.data
Wgt1 = datafile.Particles_Weight_subset_part_ele.data
Gam2 = datafile.Particles_Gamma_subset_part_ion.data
Wgt2 = datafile.Particles_Weight_subset_part_ion.data
Gam3 = datafile.Particles_Gamma_subset_part_ele0.data
Wgt3 = datafile.Particles_Weight_subset_part_ele0.data
Gam4 = datafile.Particles_Gamma_subset_part_ion0.data
Wgt4 = datafile.Particles_Weight_subset_part_ion0.data
Gam5 = 0
Wgt5 = 0
Gam6 = 0
Wgt6 = 0
Px7 = 0
Py7 = 0
Pz7 = 0
Wgt7 = 0
if i>=1:
Gam5 = datafile.Particles_Gamma_subset_part_eleq.data
Wgt5 = datafile.Particles_Weight_subset_part_eleq.data
Gam6 = datafile.Particles_Gamma_subset_part_ionq.data
Wgt6 = datafile.Particles_Weight_subset_part_ionq.data
Px7 = datafile.Particles_Px_subset_part_pho.data
Py7 = datafile.Particles_Py_subset_part_pho.data
Pz7 = datafile.Particles_Pz_subset_part_pho.data
Wgt7 = datafile.Particles_Weight_subset_part_pho.data
part1[i] = np.sum((Gam1-1)*me*c*c*Wgt1)*10 \
+ np.sum((Gam2-1)*me*c*c*Wgt2)*10 \
+ np.sum((Gam3-1)*me*c*c*Wgt3)*10 \
+ np.sum((Gam4-1)*me*c*c*Wgt4)*10 \
+ np.sum((Gam5-1)*me*c*c*Wgt5)*10 \
+ np.sum((Gam6-1)*me*c*c*Wgt6)*10
pho1[i] = np.sum(np.sqrt(Px7**2+Py7**2+Pz7**2)*c*Wgt7)*10
# folder = 'Data1'
# for i in range(Num):
# time[i] = i*10
# fname = file+folder+'/'+str(i).zfill(4)+'.sdf'
# datafile = sdf.read(fname)
# TeS1[i] = datafile.Total_Field_Energy_in_Simulation__J_.data+datafile.Total_Particle_Energy_in_Simulation__J_.data
folder = 'Data'
for i in range(Num):
ii = i
time[i] = ii/10
fname = file+folder+'/'+str(ii).zfill(4)+'.sdf'
datafile = sdf.read(fname)
TeS2[i] = datafile.Total_Particle_Energy_in_Simulation__J_.data
fname = file+folder+'/6'+str(ii).zfill(4)+'.sdf'
datafile = sdf.read(fname)
Gam1 = datafile.Particles_Gamma_subset_part_ele.data
Wgt1 = datafile.Particles_Weight_subset_part_ele.data
Gam2 = datafile.Particles_Gamma_subset_part_ion.data
Wgt2 = datafile.Particles_Weight_subset_part_ion.data
Gam3 = datafile.Particles_Gamma_subset_part_ele0.data
Wgt3 = datafile.Particles_Weight_subset_part_ele0.data
Gam4 = datafile.Particles_Gamma_subset_part_ion0.data
Wgt4 = datafile.Particles_Weight_subset_part_ion0.data
Gam5 = 0
Wgt5 = 0
Gam6 = 0
Wgt6 = 0
Px7 = 0
Py7 = 0
Pz7 = 0
Wgt7 = 0
if i>=1:
Gam5 = datafile.Particles_Gamma_subset_part_eleq.data
Wgt5 = datafile.Particles_Weight_subset_part_eleq.data
Gam6 = datafile.Particles_Gamma_subset_part_ionq.data
Wgt6 = datafile.Particles_Weight_subset_part_ionq.data
Px7 = datafile.Particles_Px_subset_part_pho.data
Py7 = datafile.Particles_Py_subset_part_pho.data
Pz7 = datafile.Particles_Pz_subset_part_pho.data
Wgt7 = datafile.Particles_Weight_subset_part_pho.data
part2[i] = np.sum((Gam1-1)*me*c*c*Wgt1)*10 \
+ np.sum((Gam2-1)*me*c*c*Wgt2)*10 \
+ np.sum((Gam3-1)*me*c*c*Wgt3)*10 \
+ np.sum((Gam4-1)*me*c*c*Wgt4)*10 \
+ np.sum((Gam5-1)*me*c*c*Wgt5)*10 \
+ np.sum((Gam6-1)*me*c*c*Wgt6)*10
pho2[i] = np.sum(np.sqrt(Px7**2+Py7**2+Pz7**2)*c*Wgt7)*10
# print('TeS1 = ',TeS1)
plt.figure(figsize=(cm2inch(8.5), cm2inch(6)))
ax = plt.subplot()
ax.plot(time, TeS1,'k-', lw=1, label='w/o merge')
ax.plot(time, part1,'b-', lw=1, label='w/o merge')
ax.plot(time, pho1,'r-', lw=1, label='w/o merge')
ax.plot(time, TeS2,'ko', lw=1, markersize=3, markeredgewidth=1, markeredgecolor='k', markerfacecolor='None',label='w merge')
ax.plot(time, part2,'bo', lw=1, markersize=3, markeredgewidth=1, markeredgecolor='b', markerfacecolor='None',label='w merge')
ax.plot(time, pho2,'ro', lw=1, markersize=3, markeredgewidth=1, markeredgecolor='r', markerfacecolor='None',label='w merge')
plt.xlim(0,2.5)
plt.ylim(0,2.5e3)
plt.xlabel('time($\omega_{pe}^{-1}$)')
plt.ylabel('Energy[$J$]')
plt.legend(loc='best', numpoints=1, fancybox=True)
# print(TeS1[0])
# plt.grid(b=True,which='major',axis='both')
# plt.show()
# plt.title('energy conservation',fontsize=32,fontstyle='normal')
plt.savefig('EneCons.pdf',bbox_inches='tight') # n means normalized
plt.close()
| 31.84106
| 126
| 0.71693
| 811
| 4,808
| 4.055487
| 0.202219
| 0.1654
| 0.097902
| 0.123442
| 0.784433
| 0.757981
| 0.757981
| 0.716935
| 0.679234
| 0.656431
| 0
| 0.055634
| 0.121464
| 4,808
| 151
| 127
| 31.84106
| 0.723011
| 0.089226
| 0
| 0.637931
| 0
| 0
| 0.049244
| 0.012826
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008621
| false
| 0
| 0.025862
| 0.008621
| 0.043103
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
b69e2910c790a746963e525f59e028fa36fba54c
| 28
|
py
|
Python
|
specHdl/rawdata/RedundancyPI.py
|
huhub/prototypeTester
|
3ebb1af5afef26c678fad8d36f945ca2fd804b7d
|
[
"Apache-2.0"
] | null | null | null |
specHdl/rawdata/RedundancyPI.py
|
huhub/prototypeTester
|
3ebb1af5afef26c678fad8d36f945ca2fd804b7d
|
[
"Apache-2.0"
] | null | null | null |
specHdl/rawdata/RedundancyPI.py
|
huhub/prototypeTester
|
3ebb1af5afef26c678fad8d36f945ca2fd804b7d
|
[
"Apache-2.0"
] | null | null | null |
Redundancy = ['tsnStreamId']
| 28
| 28
| 0.75
| 2
| 28
| 10.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.071429
| 28
| 1
| 28
| 28
| 0.807692
| 0
| 0
| 0
| 0
| 0
| 0.37931
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 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
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
fcc1d87eda4e9d4ded32e70121f6accf79d65dfe
| 223
|
py
|
Python
|
piccolo/apps/migrations/auto/__init__.py
|
coder3112/piccolo
|
f5f72c6b24782f1b6e04c31549654cd27fd3a148
|
[
"MIT"
] | null | null | null |
piccolo/apps/migrations/auto/__init__.py
|
coder3112/piccolo
|
f5f72c6b24782f1b6e04c31549654cd27fd3a148
|
[
"MIT"
] | null | null | null |
piccolo/apps/migrations/auto/__init__.py
|
coder3112/piccolo
|
f5f72c6b24782f1b6e04c31549654cd27fd3a148
|
[
"MIT"
] | null | null | null |
from .diffable_table import DiffableTable # noqa
from .migration_manager import MigrationManager # noqa
from .schema_differ import AlterStatements, SchemaDiffer # noqa
from .schema_snapshot import SchemaSnapshot # noqa
| 44.6
| 64
| 0.829596
| 25
| 223
| 7.24
| 0.6
| 0.132597
| 0.154696
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.130045
| 223
| 4
| 65
| 55.75
| 0.93299
| 0.085202
| 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
| 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
| 4
|
fcc6d668f013fa0850e572e2fb35109863e4dc22
| 112
|
py
|
Python
|
SRC/Chapter_01-Meet-Python/03_using_input.py
|
archeranimesh/tth-python-basics-3
|
accbc894324d084124ec001817edf4dc3afffa78
|
[
"MIT"
] | null | null | null |
SRC/Chapter_01-Meet-Python/03_using_input.py
|
archeranimesh/tth-python-basics-3
|
accbc894324d084124ec001817edf4dc3afffa78
|
[
"MIT"
] | null | null | null |
SRC/Chapter_01-Meet-Python/03_using_input.py
|
archeranimesh/tth-python-basics-3
|
accbc894324d084124ec001817edf4dc3afffa78
|
[
"MIT"
] | null | null | null |
favorite_color = input("What is your favorite color? ")
print("The color", favorite_color, "is a great color!")
| 37.333333
| 55
| 0.732143
| 17
| 112
| 4.705882
| 0.588235
| 0.4875
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133929
| 112
| 2
| 56
| 56
| 0.824742
| 0
| 0
| 0
| 0
| 0
| 0.491071
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 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
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 4
|
fccc400fb071c130488fdb9d1ee4e4d8004102d3
| 5,008
|
py
|
Python
|
kw_input/interfaces.py
|
alex-kalanis/kw_input
|
ac7beddadc5e766d7b4921352a472abcea6e16cf
|
[
"BSD-3-Clause"
] | null | null | null |
kw_input/interfaces.py
|
alex-kalanis/kw_input
|
ac7beddadc5e766d7b4921352a472abcea6e16cf
|
[
"BSD-3-Clause"
] | null | null | null |
kw_input/interfaces.py
|
alex-kalanis/kw_input
|
ac7beddadc5e766d7b4921352a472abcea6e16cf
|
[
"BSD-3-Clause"
] | null | null | null |
class IEntry:
"""
* Entry interface - this will be shared across the projects
"""
SOURCE_CLI = 'cli'
SOURCE_GET = 'get'
SOURCE_POST = 'post'
SOURCE_FILES = 'files'
SOURCE_COOKIE = 'cookie'
SOURCE_SESSION = 'session'
SOURCE_SERVER = 'server'
SOURCE_ENV = 'environment'
SOURCE_EXTERNAL = 'external'
def get_source(self) -> str:
"""
* Return source of entry
"""
raise NotImplementedError('TBA')
def get_key(self) -> str:
"""
* Return key of entry
"""
raise NotImplementedError('TBA')
def get_value(self):
"""
* Return value of entry
* It could be anything - string, boolean, array - depends on source
"""
raise NotImplementedError('TBA')
class IFileEntry(IEntry):
"""
* File entry interface - how to access uploaded files
* @link https://www.php.net/manual/en/reserved.variables.files.php
"""
def get_mime_type(self) -> str:
"""
* Return what mime is that by browser
* Beware, it is not reliable
"""
raise NotImplementedError('TBA')
def get_temp_name(self) -> str:
"""
* Get name in temp
* Use it for function like move_uploaded_file()
"""
raise NotImplementedError('TBA')
def get_error(self) -> int:
"""
* Get error code from upload
* @link https://www.php.net/manual/en/features.file-upload.errors.php
"""
raise NotImplementedError('TBA')
def get_size(self) -> int:
"""
* Get uploaded file size
"""
raise NotImplementedError('TBA')
class ISource:
"""
* Source of values to parse
"""
def cli(self):
raise NotImplementedError('TBA')
def get(self):
raise NotImplementedError('TBA')
def post(self):
raise NotImplementedError('TBA')
def files(self):
raise NotImplementedError('TBA')
def cookie(self):
raise NotImplementedError('TBA')
def session(self):
raise NotImplementedError('TBA')
def server(self):
raise NotImplementedError('TBA')
def env(self):
raise NotImplementedError('TBA')
def external(self):
raise NotImplementedError('TBA')
class IInputs:
"""
* Basic interface which tells us what actions are by default available by inputs
"""
def set_source(self, source=None):
"""
* Setting the variable sources - from cli (argv), _GET, _POST, _SERVER, ...
"""
raise NotImplementedError('TBA')
def load_entries(self):
"""
* Load entries from source into the local entries which will be accessible
* These two calls came usually in pair
*
* input.set_source(sys.argv).load_entries()
"""
raise NotImplementedError('TBA')
def get_in(self, entry_key: str = None, entry_sources = None):
"""
* Get iterator of local entries, filter them on way
* @param string|null $entry_key
* @param string[] $entry_sources array of constants from Entries.IEntry.SOURCE_*
* @return iterator
* @see Entries.IEntry.SOURCE_CLI
* @see Entries.IEntry.SOURCE_GET
* @see Entries.IEntry.SOURCE_POST
* @see Entries.IEntry.SOURCE_FILES
* @see Entries.IEntry.SOURCE_COOKIE
* @see Entries.IEntry.SOURCE_SESSION
* @see Entries.IEntry.SOURCE_SERVER
* @see Entries.IEntry.SOURCE_ENV
"""
raise NotImplementedError('TBA')
class IVariables:
"""
* Helper interface which allows us access variables from input
"""
def get_in_array(self, entry_key: str = None, entry_sources = None):
"""
* Reformat into array with key as array key and value with the whole entry
* @param string|None entry_key
* @param string[] entry_sources
* @return Entries.IEntry[]
* Also usually came in pair with previous call - but with a different syntax
* Beware - due any dict limitations there is a limitation that only the last entry prevails
*
* entries = variables.get_in_array('example', [Entries.IEntry.SOURCE_GET]);
"""
raise NotImplementedError('TBA')
def get_in_object(self, entry_key: str = None, entry_sources = None):
"""
* Reformat into object with access by key as string key and value with the whole entry
* @param string|None entry_key
* @param string[] entry_sources
* @return Inputs.Input
* Also usually came in pair with previous call - but with a different syntax
* Beware - due any dict limitations there is a limitation that only the last entry prevails
*
* entries_in_object = variables.get_in_object('example', [Entries.IEntry.SOURCE_GET]);
"""
raise NotImplementedError('TBA')
| 29.116279
| 100
| 0.601038
| 566
| 5,008
| 5.210247
| 0.259717
| 0.170905
| 0.192269
| 0.162767
| 0.427603
| 0.30078
| 0.275687
| 0.230926
| 0.181078
| 0.181078
| 0
| 0
| 0.300519
| 5,008
| 171
| 101
| 29.28655
| 0.84185
| 0.457069
| 0
| 0.375
| 0
| 0
| 0.05642
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.375
| false
| 0
| 0
| 0
| 0.625
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
fcde9e8c62cb439bcf824e5857f60dc9c50e4593
| 101
|
py
|
Python
|
setup.py
|
tjkemp/gym-buy-high-sell-low
|
ce7d6acbae7b5f2a032a4dcc95d26f65b0269a06
|
[
"MIT"
] | null | null | null |
setup.py
|
tjkemp/gym-buy-high-sell-low
|
ce7d6acbae7b5f2a032a4dcc95d26f65b0269a06
|
[
"MIT"
] | 1
|
2022-02-20T15:45:03.000Z
|
2022-02-21T13:43:58.000Z
|
setup.py
|
tjkemp/gym-buy-high-sell-low
|
ce7d6acbae7b5f2a032a4dcc95d26f65b0269a06
|
[
"MIT"
] | null | null | null |
from setuptools import setup
setup(name="gym-buy-high-sell-low", install_requires=["gym", "numpy"])
| 25.25
| 70
| 0.742574
| 15
| 101
| 4.933333
| 0.866667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.079208
| 101
| 3
| 71
| 33.666667
| 0.795699
| 0
| 0
| 0
| 0
| 0
| 0.287129
| 0.207921
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
fce086029f853b58617ca7ca04356898d84241b8
| 140
|
py
|
Python
|
jit.py
|
yym064/EMDLoss_PyTorch_cpp_extension
|
0568e67b30c95edb2027d06b0ab5001aa2ee4a98
|
[
"MIT"
] | 2
|
2021-11-04T08:36:00.000Z
|
2022-01-23T14:24:59.000Z
|
jit.py
|
yym064/EMDLoss_PyTorch_cpp_extension
|
0568e67b30c95edb2027d06b0ab5001aa2ee4a98
|
[
"MIT"
] | null | null | null |
jit.py
|
yym064/EMDLoss_PyTorch_cpp_extension
|
0568e67b30c95edb2027d06b0ab5001aa2ee4a98
|
[
"MIT"
] | null | null | null |
from torch.utils.cpp_extension import load
emd_cuda = load(
'emd_cuda', ['emd_cuda.cpp', 'emd_kernel.cu'], verbose=True
)
help(emd_cuda)
| 28
| 63
| 0.735714
| 23
| 140
| 4.217391
| 0.608696
| 0.28866
| 0.226804
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.114286
| 140
| 5
| 64
| 28
| 0.782258
| 0
| 0
| 0
| 0
| 0
| 0.234043
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.2
| 0
| 0.2
| 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
| 0
| 0
| 0
| 0
|
0
| 4
|
1e183db0f6962e3711519d7a0c541d00abc619a6
| 30
|
py
|
Python
|
tests/__init__.py
|
ssichynskyi/SDMX-API-testing-ECB
|
10c2a80180ce6909d1f92b7cde178e9c943ff599
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
ssichynskyi/SDMX-API-testing-ECB
|
10c2a80180ce6909d1f92b7cde178e9c943ff599
|
[
"MIT"
] | null | null | null |
tests/__init__.py
|
ssichynskyi/SDMX-API-testing-ECB
|
10c2a80180ce6909d1f92b7cde178e9c943ff599
|
[
"MIT"
] | null | null | null |
"""Package with AUT tests."""
| 15
| 29
| 0.633333
| 4
| 30
| 4.75
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.133333
| 30
| 1
| 30
| 30
| 0.730769
| 0.766667
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| 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
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
1e1d131fb526342fd59b077b81be664811ec9952
| 92
|
py
|
Python
|
LUH2/GLM/snippets.py
|
ritviksahajpal/LUH2
|
aec79f737aebcaa273de5f8f1aeadd3317d03aa4
|
[
"MIT"
] | null | null | null |
LUH2/GLM/snippets.py
|
ritviksahajpal/LUH2
|
aec79f737aebcaa273de5f8f1aeadd3317d03aa4
|
[
"MIT"
] | null | null | null |
LUH2/GLM/snippets.py
|
ritviksahajpal/LUH2
|
aec79f737aebcaa273de5f8f1aeadd3317d03aa4
|
[
"MIT"
] | null | null | null |
import os, pdb, constants
import pygeoutil.util as util
# Convert ANDREAS NC file to Ascii
| 18.4
| 34
| 0.782609
| 15
| 92
| 4.8
| 0.866667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.173913
| 92
| 4
| 35
| 23
| 0.947368
| 0.347826
| 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
| 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
| 4
|
1e1dad62cf6c1c28415acf7e519e6641c2d16060
| 16,842
|
py
|
Python
|
tests/unit/test_cf.py
|
cloud-gov/external-domain-broker-migrator
|
6f827b3242e6d45e29d3e2404955cbea9ae1a25b
|
[
"CC0-1.0"
] | 1
|
2020-08-14T22:53:03.000Z
|
2020-08-14T22:53:03.000Z
|
tests/unit/test_cf.py
|
cloud-gov/external-domain-broker-migrator
|
6f827b3242e6d45e29d3e2404955cbea9ae1a25b
|
[
"CC0-1.0"
] | 63
|
2020-08-14T20:07:53.000Z
|
2021-12-20T21:39:07.000Z
|
tests/unit/test_cf.py
|
cloud-gov/external-domain-broker-migrator
|
6f827b3242e6d45e29d3e2404955cbea9ae1a25b
|
[
"CC0-1.0"
] | null | null | null |
import json
import pytest
from migrator import cf
from migrator.extensions import config
from migrator.models import CdnRoute
from migrator.migration import Migration
import requests_mock
from tests.lib.fake_cf import get_test_client
def test_get_client(fake_requests):
# this test mostly just validates the test framework
client = get_test_client(fake_requests)
def test_enable_service_plan_2(fake_requests, fake_cf_client):
response_body = """{
"metadata": {
"guid": "new-plan-visibility-guid",
"url": "/v2/service_plan_visibilities/new-plan-visibility-guid",
"created_at": "2016-06-08T16:41:31Z",
"updated_at": "2016-06-08T16:41:26Z"
},
"entity": {
"service_plan_guid": "foo",
"organization_guid": "bar",
"service_plan_url": "/v2/service_plans/foo",
"organization_url": "/v2/organizations/bar"
}
}"""
fake_requests.post(
"http://localhost/v2/service_plan_visibilities", text=response_body
)
res = cf.enable_plan_for_org("foo", "bar", fake_cf_client)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert last_request.url == "http://localhost/v2/service_plan_visibilities"
def test_enable_service_plan_2(fake_requests, fake_cf_client):
response_body = """{
"description": "This combination of ServicePlan and Organization is already taken: organization_id and service_plan_id unique",
"error_code": "CF-ServicePlanVisibilityAlreadyExists",
"code": 260002
}
"""
fake_requests.post(
"http://localhost/v2/service_plan_visibilities",
text=response_body,
status_code=400,
)
# the real test here is that we don't raise an error
res = cf.enable_plan_for_org("foo", "bar", fake_cf_client)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert last_request.url == "http://localhost/v2/service_plan_visibilities"
def test_disable_service_plan_2(fake_requests, fake_cf_client):
response_body = ""
fake_requests.delete(
"http://localhost/v2/service_plan_visibilities/new-plan-visibility-guid",
text=response_body,
)
res = cf.disable_plan_for_org("new-plan-visibility-guid", fake_cf_client)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert (
last_request.url
== "http://localhost/v2/service_plan_visibilities/new-plan-visibility-guid"
)
def test_get_space_for_instance(migration, fake_requests, fake_cf_client):
response_body = """
{
"metadata": {
"guid": "some-instance-id",
"url": "/v2/service_instances/some-instance-id",
"created_at": "2016-06-08T16:41:29Z",
"updated_at": "2016-06-08T16:41:26Z"
},
"entity": {
"name": "name-1508",
"service_guid": "a14baddf-1ccc-5299-0152-ab9s49de4422",
"service_plan_guid": "779d2df0-9cdd-48e8-9781-ea05301cedb1",
"space_guid": "my-space-guid",
"gateway_data": null,
"dashboard_url": null,
"type": "managed_service_instance",
"last_operation": {
"type": "create",
"state": "succeeded",
"description": "service broker-provided description",
"updated_at": "2016-06-08T16:41:29Z",
"created_at": "2016-06-08T16:41:29Z"
},
"tags": [ ],
"maintenance_info": {
"version": "2.1.1",
"description": "OS image update.Expect downtime."
},
"space_url": "/v2/spaces/my-space-guid",
"service_url": "/v2/services/a14baddf-1ccc-5299-0152-ab9s49de4422",
"service_plan_url": "/v2/service_plans/779d2df0-9cdd-48e8-9781-ea05301cedb1",
"service_bindings_url": "/v2/service_instances/some-instance-id/service_bindings",
"service_keys_url": "/v2/service_instances/some-instance-id/service_keys",
"routes_url": "/v2/service_instances/some-instance-id/routes",
"shared_from_url": "/v2/service_instances/some-instance-id/shared_from",
"shared_to_url": "/v2/service_instances/some-instance-id/shared_to",
"service_instance_parameters_url": "/v2/service_instances/some-instance-id/parameters"
}
}
"""
fake_requests.get(
"http://localhost/v2/service_instances/asdf-asdf", text=response_body
)
assert (
cf.get_space_id_for_service_instance_id(migration.instance_id, fake_cf_client)
== "my-space-guid"
)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert last_request.url == "http://localhost/v2/service_instances/asdf-asdf"
def test_get_org_id_for_space_id(fake_cf_client, fake_requests):
response_body = """
{
"guid": "my-space-guid",
"created_at": "2017-02-01T01:33:58Z",
"updated_at": "2017-02-01T01:33:58Z",
"name": "my-space",
"relationships": {
"organization": {
"data": {
"guid": "my-org-guid"
}
},
"quota": {
"data": null
}
},
"links": {
"self": {
"href": "http://localhost/v3/spaces/my-space-guid"
},
"features": {
"href": "http://localhost/v3/spaces/my-space-guid/features"
},
"organization": {
"href": "http://localhost/v3/organizations/my-org-guid"
},
"apply_manifest": {
"href": "http://localhost/v3/spaces/my-space-guid/actions/apply_manifest",
"method": "POST"
}
},
"metadata": {
"labels": {},
"annotations": {}
}
}
"""
fake_requests.get("http://localhost/v3/spaces/my-space-guid", text=response_body)
assert cf.get_org_id_for_space_id("my-space-guid", fake_cf_client) == "my-org-guid"
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert last_request.url == "http://localhost/v3/spaces/my-space-guid"
def test_get_all_space_ids_for_org_3(fake_cf_client, fake_requests):
response_body = """
{
"pagination": {
"total_results": 2,
"total_pages": 1,
"first": {
"href": "https://api.fr.cloud.gov/v3/spaces?organization_guids=my-org-guid&page=1&per_page=50"
},
"last": {
"href": "https://api.fr.cloud.gov/v3/spaces?organization_guids=my-org-guid&page=1&per_page=50"
},
"next": null,
"previous": null
},
"resources": [
{
"guid": "my-space-1-guid",
"created_at": "2021-01-27T20:52:07Z",
"updated_at": "2021-01-27T20:52:07Z",
"name": "space-1",
"relationships": {
"organization": {
"data": {
"guid": "my-org-guid"
}
},
"quota": {
"data": null
}
},
"metadata": {
"labels": {},
"annotations": {}
},
"links": {
"self": {
"href": "https://api.fr.cloud.gov/v3/spaces/my-space-1-guid"
},
"organization": {
"href": "https://api.fr.cloud.gov/v3/organizations/my-org-guid"
},
"features": {
"href": "https://api.fr.cloud.gov/v3/spaces/my-space-1-guid/features"
},
"apply_manifest": {
"href": "https://api.fr.cloud.gov/v3/spaces/my-space-1-guid/actions/apply_manifest",
"method": "POST"
}
}
},
{
"guid": "my-space-2-guid",
"created_at": "2021-02-04T16:26:06Z",
"updated_at": "2021-02-04T16:26:06Z",
"name": "space-2",
"relationships": {
"organization": {
"data": {
"guid": "my-org-guid"
}
},
"quota": {
"data": null
}
},
"metadata": {
"labels": {},
"annotations": {}
},
"links": {
"self": {
"href": "https://api.fr.cloud.gov/v3/spaces/my-space-2-guid"
},
"organization": {
"href": "https://api.fr.cloud.gov/v3/organizations/my-org-guid"
},
"features": {
"href": "https://api.fr.cloud.gov/v3/spaces/my-space-2-guid/features"
},
"apply_manifest": {
"href": "https://api.fr.cloud.gov/v3/spaces/my-space-2-guid/actions/apply_manifest",
"method": "POST"
}
}
}
]
}
"""
fake_requests.get(
"http://localhost/v3/spaces?organization_guids=my-org-guid", text=response_body
)
assert cf.get_all_space_ids_for_org("my-org-guid", fake_cf_client) == [
"my-space-1-guid",
"my-space-2-guid",
]
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert (
last_request.url == "http://localhost/v3/spaces?organization_guids=my-org-guid"
)
def test_create_bare_migrator_service_instance_in_space(fake_cf_client, fake_requests):
response_body = """
{
"metadata": {
"guid": "my-migrator-instance",
"url": "/v2/service_instances/my-migrator-instance",
"created_at": "2016-06-08T16:41:29Z",
"updated_at": "2016-06-08T16:41:26Z"
},
"entity": {
"name": "external-domain-broker-migrator",
"credentials": {
},
"service_plan_guid": "739e78F5-a919-46ef-9193-1293cc086c17",
"space_guid": "my-space-guid",
"gateway_data": null,
"dashboard_url": null,
"type": "managed_service_instance",
"last_operation": {
"type": "create",
"state": "in progress",
"description": "",
"updated_at": "2016-06-08T16:41:26Z",
"created_at": "2016-06-08T16:41:29Z"
},
"space_url": "/v2/spaces/my-space-1-guid",
"service_plan_url": "/v2/service_plans/739e78F5-a919-46ef-9193-1293cc086c17",
"service_bindings_url": "/v2/service_instances/my-migrator-instance/service_bindings",
"service_keys_url": "/v2/service_instances/my-migrator-instance/service_keys",
"routes_url": "/v2/service_instances/my-migrator-instance/routes",
"shared_from_url": "/v2/service_instances/0d632575-bb06-4ea5-bb19-a451a9644d92/shared_from",
"shared_to_url": "/v2/service_instances/0d632575-bb06-4ea5-bb19-a451a9644d92/shared_to"
}
}
"""
def create_param_matcher(request):
domains_in = request.json().get("parameters", {}).get("domains", [])
assert sorted(domains_in) == sorted(["www0.example.gov", "www1.example.gov"])
return True
fake_requests.post(
"http://localhost/v2/service_instances",
text=response_body,
additional_matcher=create_param_matcher,
)
response = cf.create_bare_migrator_service_instance_in_space(
"my-space-guid",
"739e78F5-a919-46ef-9193-1293cc086c17",
"external-domain-broker-migrator",
["www0.example.gov", "www1.example.gov"],
fake_cf_client,
)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert (
last_request.url
== "http://localhost/v2/service_instances?accepts_incomplete=true"
)
assert response["guid"] == "my-migrator-instance"
assert response["state"] == "in progress"
assert response["type"] == "create"
def test_get_migrator_service_instance_status(fake_cf_client, fake_requests):
response_body = """
{
"metadata": {
"guid": "my-migrator-instance",
"url": "/v2/service_instances/my-migrator-instance",
"created_at": "2016-06-08T16:41:29Z",
"updated_at": "2016-06-08T16:41:26Z"
},
"entity": {
"name": "external-domain-broker-migrator",
"credentials": {
},
"service_plan_guid": "739e78F5-a919-46ef-9193-1293cc086c17",
"space_guid": "my-space-guid",
"gateway_data": null,
"dashboard_url": null,
"type": "managed_service_instance",
"last_operation": {
"type": "create",
"state": "succeeded",
"description": "",
"updated_at": "2016-06-08T16:41:26Z",
"created_at": "2016-06-08T16:41:29Z"
},
"space_url": "/v2/spaces/my-space-guid",
"service_plan_url": "/v2/service_plans/739e78F5-a919-46ef-9193-1293cc086c17",
"service_bindings_url": "/v2/service_instances/my-migrator-instance/service_bindings",
"service_keys_url": "/v2/service_instances/my-migrator-instance/service_keys",
"routes_url": "/v2/service_instances/my-migrator-instance/routes",
"shared_from_url": "/v2/service_instances/0d632575-bb06-4ea5-bb19-a451a9644d92/shared_from",
"shared_to_url": "/v2/service_instances/0d632575-bb06-4ea5-bb19-a451a9644d92/shared_to"
}
}
"""
fake_requests.get(
"http://localhost/v2/service_instances/my-migrator-instance", text=response_body
)
assert (
cf.get_migrator_service_instance_status("my-migrator-instance", fake_cf_client)
== "succeeded"
)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert (
last_request.url == "http://localhost/v2/service_instances/my-migrator-instance"
)
def update_existing_cdn_domain_service_instance(fake_cf_client, fake_requests):
response_body = """
{
"metadata": {
"guid": "my-migrator-instance",
"url": "/v2/service_instances/my-migrator-instance",
"created_at": "2016-06-08T16:41:30Z",
"updated_at": "2016-06-08T16:41:26Z"
},
"entity": {
"name": "external-domain-broker-migrator",
"credentials": {
"creds-key-41": "creds-val-41"
},
"service_plan_guid": "739e78F5-a919-46ef-9193-1293cc086c17",
"space_guid": "my-space-guid",
"gateway_data": null,
"dashboard_url": null,
"type": "managed_service_instance",
"last_operation": {
"type": "update",
"state": "in progress",
"description": "",
"updated_at": "2016-06-08T16:41:30Z",
"created_at": "2016-06-08T16:41:30Z"
},
"tags": [
],
"maintenance_info": {
"version": "2.1.0",
"description": "OS image update.\nExpect downtime."
},
"space_url": "/v2/spaces/my-space-guid",
"service_plan_url": "/v2/service_plans/739e78F5-a919-46ef-9193-1293cc086c17",
"service_bindings_url": "/v2/service_instances/my-migrator-instance/service_bindings",
"service_keys_url": "/v2/service_instances/my-migrator-instance/service_keys",
"routes_url": "/v2/service_instances/my-migrator-instance/routes",
"shared_from_url": "/v2/service_instances/0d632575-bb06-4ea5-bb19-a451a9644d92/shared_from",
"shared_to_url": "/v2/service_instances/0d632575-bb06-4ea5-bb19-a451a9644d92/shared_to"
}
}
"""
fake_requests.put(
"http://localhost/v2/service_instances/my-migrator-instance", text=response_body
)
response = cf.update_existing_cdn_domain_service_instance(
"my-space-guid",
"739e78F5-a919-46ef-9193-1293cc086c17",
"external-domain-broker-migrator",
fake_cf_client,
)
assert fake_requests.called
last_request = fake_requests.request_history[-1]
assert (
last_request.url == "http://localhost/v2/service_instances/my-migrator-instance"
)
assert response["guid"] == "my-migrator-instance"
assert response["state"] == "in progress"
assert response["type"] == "update"
def test_purge_service_instance(fake_cf_client, fake_requests):
response_body = """{
"metadata": {
"guid": "my-service-instance",
"url": "/v2/service_instances/my-service-instance",
"created_at": "2016-06-08T16:41:29Z",
"updated_at": "2016-06-08T16:41:26Z"
},
"entity": {
"name": "name-1502",
"credentials": { },
"service_plan_guid": "8ea19d29-2e20-469e-8b91-917a6410e2f2",
"space_guid": "dd68a2ba-04a3-4125-99ea-643b96e07ef6",
"gateway_data": null,
"dashboard_url": null,
"type": "managed_service_instance",
"last_operation": {
"type": "delete",
"state": "complete",
"description": "",
"updated_at": "2016-06-08T16:41:29Z",
"created_at": "2016-06-08T16:41:29Z"
},
"tags": [ ],
"maintenance_info": {},
"space_url": "/v2/spaces/dd68a2ba-04a3-4125-99ea-643b96e07ef6",
"service_plan_url": "/v2/service_plans/8ea19d29-2e20-469e-8b91-917a6410e2f2",
"service_bindings_url": "/v2/service_instances/1aaeb02d-16c3-4405-bc41-80e83d196dff/service_bindings",
"service_keys_url": "/v2/service_instances/1aaeb02d-16c3-4405-bc41-80e83d196dff/service_keys",
"routes_url": "/v2/service_instances/1aaeb02d-16c3-4405-bc41-80e83d196dff/routes",
"shared_from_url": "/v2/service_instances/6da8d173-b409-4094-949f-3c1cc8a68503/shared_from",
"shared_to_url": "/v2/service_instances/6da8d173-b409-4094-949f-3c1cc8a68503/shared_to"
}
} """
fake_requests.delete(
"http://localhost/v2/service_instances/my-service-instance?purge=true",
text=response_body,
)
cf.purge_service_instance("my-service-instance", fake_cf_client)
assert fake_requests.called
| 32.702913
| 135
| 0.635613
| 2,002
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| 5.108891
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0
| 4
|
1e1f60ad3f92cbea49d23ded95791fedb7c54556
| 93
|
py
|
Python
|
runtime/python/Lib/ensurepip/__main__.py
|
hwaipy/InteractionFreeNode
|
88642b68430f57b028fd0f276a5709f89279e30d
|
[
"MIT"
] | 207
|
2018-10-01T08:53:01.000Z
|
2022-03-14T12:15:54.000Z
|
Thonny/Lib/ensurepip/__main__.py
|
Pydiderot/pydiderotIDE
|
a42fcde3ea837ae40c957469f5d87427e8ce46d3
|
[
"MIT"
] | 30
|
2019-01-04T10:14:56.000Z
|
2020-10-12T14:00:31.000Z
|
Thonny/Lib/ensurepip/__main__.py
|
Pydiderot/pydiderotIDE
|
a42fcde3ea837ae40c957469f5d87427e8ce46d3
|
[
"MIT"
] | 76
|
2020-03-16T01:47:46.000Z
|
2022-03-21T16:37:07.000Z
|
import ensurepip
import sys
if __name__ == "__main__":
sys.exit(ensurepip._main())
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0
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1e373b897eb18efe1e4de8ee9231d3fce7bb9416
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|
py
|
Python
|
setup.py
|
alisterburt/tiltstack
|
d8a7c7b633f878560c011fe054e1d9883a18a4f9
|
[
"BSD-3-Clause"
] | 1
|
2022-02-23T02:44:18.000Z
|
2022-02-23T02:44:18.000Z
|
setup.py
|
alisterburt/tiltstack
|
d8a7c7b633f878560c011fe054e1d9883a18a4f9
|
[
"BSD-3-Clause"
] | null | null | null |
setup.py
|
alisterburt/tiltstack
|
d8a7c7b633f878560c011fe054e1d9883a18a4f9
|
[
"BSD-3-Clause"
] | null | null | null |
import setuptools
setuptools.setup(use_scm_version={"write_to": "tiltstack/_version.py"})
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| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| 0
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| 0
| 0
| 0
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| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1e3a51b34dd8f2c988854c62385eb0423ecd26ee
| 73
|
py
|
Python
|
src/ufdl/annotations_plugin/audio/__init__.py
|
waikato-ufdl/ufdl-annotations-plugin
|
9eb3d807e35215ad9cfbd4aa651d7f7142e83efe
|
[
"Apache-2.0"
] | null | null | null |
src/ufdl/annotations_plugin/audio/__init__.py
|
waikato-ufdl/ufdl-annotations-plugin
|
9eb3d807e35215ad9cfbd4aa651d7f7142e83efe
|
[
"Apache-2.0"
] | 4
|
2020-07-29T04:09:13.000Z
|
2020-11-22T20:52:18.000Z
|
src/ufdl/annotations_plugin/audio/__init__.py
|
waikato-ufdl/ufdl-annotations-plugin
|
9eb3d807e35215ad9cfbd4aa651d7f7142e83efe
|
[
"Apache-2.0"
] | null | null | null |
"""
Package for wai.annotations plugins for audio-based data-domains.
"""
| 24.333333
| 65
| 0.753425
| 10
| 73
| 5.5
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.109589
| 73
| 3
| 66
| 24.333333
| 0.846154
| 0.890411
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 0
| null | 1
| null | true
| 0
| 0
| null | null | null | 1
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| null | 0
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| null | 0
| 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
1e431dd0e945208cf9b199695768ccb1dee7918a
| 297
|
py
|
Python
|
src/kulprit/families/__init__.py
|
aloctavodia/kulprit
|
ab017074f7428154b8834515512db259c5f635e8
|
[
"MIT"
] | 4
|
2022-03-08T15:19:26.000Z
|
2022-03-19T05:06:18.000Z
|
src/kulprit/families/__init__.py
|
aloctavodia/kulprit
|
ab017074f7428154b8834515512db259c5f635e8
|
[
"MIT"
] | 2
|
2022-03-17T08:22:30.000Z
|
2022-03-29T08:43:11.000Z
|
src/kulprit/families/__init__.py
|
aloctavodia/kulprit
|
ab017074f7428154b8834515512db259c5f635e8
|
[
"MIT"
] | 2
|
2022-03-16T14:56:57.000Z
|
2022-03-18T14:22:48.000Z
|
"""Distribution families module."""
from abc import ABC, abstractmethod
class BaseFamily(ABC):
"""Base family class."""
@abstractmethod
def solve_analytic(self): # pragma: no cover
pass
@abstractmethod
def solve_dispersion(self): # pragma: no cover
pass
| 18.5625
| 51
| 0.656566
| 32
| 297
| 6.03125
| 0.625
| 0.176166
| 0.227979
| 0.176166
| 0.217617
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.242424
| 297
| 15
| 52
| 19.8
| 0.857778
| 0.279461
| 0
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| 1
| 0.25
| false
| 0.25
| 0.125
| 0
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| 1
| 1
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| null | 0
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| 0
| 1
| 0
| 0
| 0
| 0
|
0
| 4
|
1e5bbd845b6371a4f82f409e369af75f37b6981e
| 143
|
py
|
Python
|
cprint/__init__.py
|
TheTechRobo/install-palc-plus
|
1ee6d32d7e2f0bb1a3ef793d9e32a38e75c1f0fd
|
[
"MIT"
] | null | null | null |
cprint/__init__.py
|
TheTechRobo/install-palc-plus
|
1ee6d32d7e2f0bb1a3ef793d9e32a38e75c1f0fd
|
[
"MIT"
] | null | null | null |
cprint/__init__.py
|
TheTechRobo/install-palc-plus
|
1ee6d32d7e2f0bb1a3ef793d9e32a38e75c1f0fd
|
[
"MIT"
] | null | null | null |
# coding: utf8
#!/usr/bin/env python
from .cprint import *
"""
This module give to possibility to print in color.
"""
__version__ = "1.1"
| 15.888889
| 54
| 0.664336
| 21
| 143
| 4.333333
| 0.904762
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.026087
| 0.195804
| 143
| 9
| 55
| 15.888889
| 0.765217
| 0.223776
| 0
| 0
| 0
| 0
| 0.06383
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0.5
| 1
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| 0
| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
|
0
| 4
|
1e61ca4eaebb4f64b7c640a65ecc7e91d444891c
| 98
|
py
|
Python
|
marketing/apps.py
|
Pythonian/ecomstore
|
d24d20518f784901c553500bcfb83a1dd0063dfa
|
[
"MIT"
] | null | null | null |
marketing/apps.py
|
Pythonian/ecomstore
|
d24d20518f784901c553500bcfb83a1dd0063dfa
|
[
"MIT"
] | null | null | null |
marketing/apps.py
|
Pythonian/ecomstore
|
d24d20518f784901c553500bcfb83a1dd0063dfa
|
[
"MIT"
] | null | null | null |
from django.apps import AppConfig
class MarketingConfig(AppConfig):
name = 'marketing'
| 16.333333
| 34
| 0.72449
| 10
| 98
| 7.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.204082
| 98
| 5
| 35
| 19.6
| 0.910256
| 0
| 0
| 0
| 0
| 0
| 0.096774
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 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
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 4
|
1ebb93cad36245126e4c01afb564c1b5dd66c6e0
| 366
|
py
|
Python
|
inferbeddings/models/__init__.py
|
issca/inferbeddings
|
80492a7aebcdcac21e758514c8af403d77e8594a
|
[
"MIT"
] | 33
|
2017-07-25T14:31:00.000Z
|
2019-03-06T09:18:00.000Z
|
inferbeddings/models/__init__.py
|
issca/inferbeddings
|
80492a7aebcdcac21e758514c8af403d77e8594a
|
[
"MIT"
] | 1
|
2017-08-22T13:49:30.000Z
|
2017-08-22T13:49:30.000Z
|
inferbeddings/models/__init__.py
|
issca/inferbeddings
|
80492a7aebcdcac21e758514c8af403d77e8594a
|
[
"MIT"
] | 9
|
2017-10-05T08:50:45.000Z
|
2019-04-18T12:40:56.000Z
|
# -*- coding: utf-8 -*-
from inferbeddings.models.base import TranslatingModel
from inferbeddings.models.base import BilinearDiagonalModel
from inferbeddings.models.base import BilinearModel
from inferbeddings.models.base import ComplexModel
__all__ = ['TranslatingModel',
'BilinearDiagonalModel',
'BilinearModel',
'ComplexModel']
| 30.5
| 59
| 0.745902
| 32
| 366
| 8.40625
| 0.40625
| 0.252788
| 0.342007
| 0.401487
| 0.490706
| 0
| 0
| 0
| 0
| 0
| 0
| 0.003289
| 0.169399
| 366
| 11
| 60
| 33.272727
| 0.881579
| 0.057377
| 0
| 0
| 0
| 0
| 0.180758
| 0.061224
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1ebe384b12edba8fb2c9dc23dd3058971292bd6b
| 166
|
py
|
Python
|
src/aspire/utils/numeric/__init__.py
|
janden/ASPIRE-Python
|
5bcf831881fd0e42630c3b99671c5ed08de260ea
|
[
"MIT"
] | null | null | null |
src/aspire/utils/numeric/__init__.py
|
janden/ASPIRE-Python
|
5bcf831881fd0e42630c3b99671c5ed08de260ea
|
[
"MIT"
] | null | null | null |
src/aspire/utils/numeric/__init__.py
|
janden/ASPIRE-Python
|
5bcf831881fd0e42630c3b99671c5ed08de260ea
|
[
"MIT"
] | null | null | null |
from aspire import config
if config.common.cupy:
from .cupy import Cupy as NumericClass
else:
from .numpy import Numpy as NumericClass
xp = NumericClass()
| 16.6
| 44
| 0.746988
| 23
| 166
| 5.391304
| 0.521739
| 0.225806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.198795
| 166
| 9
| 45
| 18.444444
| 0.932331
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 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
| 0
| 0
|
0
| 4
|
1ecda3849185865e667a1ff4a117cbc79e536186
| 94
|
py
|
Python
|
bot/__main__.py
|
cytoo/TgGroupScanner
|
528283b438e23b28a5f68c21df94aef366d76654
|
[
"MIT"
] | 12
|
2021-04-15T20:28:32.000Z
|
2022-02-01T09:50:36.000Z
|
bot/__main__.py
|
cytoo/TgGroupScanner
|
528283b438e23b28a5f68c21df94aef366d76654
|
[
"MIT"
] | null | null | null |
bot/__main__.py
|
cytoo/TgGroupScanner
|
528283b438e23b28a5f68c21df94aef366d76654
|
[
"MIT"
] | 6
|
2021-04-16T05:27:41.000Z
|
2021-11-24T03:41:04.000Z
|
from mods.main import client
if __name__ == "__main__":
client.run_until_disconnected()
| 15.666667
| 35
| 0.744681
| 12
| 94
| 5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.159574
| 94
| 5
| 36
| 18.8
| 0.759494
| 0
| 0
| 0
| 0
| 0
| 0.085106
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
1ee2c09bf3c460755d1a6c5432466100a83f9f7b
| 10,436
|
py
|
Python
|
dictdata/dictedit/wordedit.py
|
szatjp/rabbitplan
|
bae942e4673863027fe7f1936e58f2d9d4ebc5c7
|
[
"CC0-1.0"
] | null | null | null |
dictdata/dictedit/wordedit.py
|
szatjp/rabbitplan
|
bae942e4673863027fe7f1936e58f2d9d4ebc5c7
|
[
"CC0-1.0"
] | null | null | null |
dictdata/dictedit/wordedit.py
|
szatjp/rabbitplan
|
bae942e4673863027fe7f1936e58f2d9d4ebc5c7
|
[
"CC0-1.0"
] | null | null | null |
# coding:utf-8
'''
Created on 2018年6月25日
@author: matsui
'''
from django.views.generic import ListView
from django.shortcuts import render,get_object_or_404
from django.contrib.auth.decorators import login_required
from django.http import HttpResponseRedirect
from dictdata.models import JaWord,CnWord,EnWord,Ja2Cn,En2Cn,Ja2En
from dictdata.appcomm.dictedit import funaddword,addtran
from markdown.extensions import fenced_code
class WordList(ListView):
template_name = 'books/books_by_publisher.html'
def get_queryset(self):
self.publisher = get_object_or_404(JaWord, name=self.kwargs['publisher'])
return JaWord.objects.filter(publisher=self.publisher)
def get_context_data(self, **kwargs):
# Call the base implementation first to get a context
context = super().get_context_data(**kwargs)
# Add in the publisher
context['publisher'] = self.publisher
return context
@login_required
def transadd(request,wordno,trantype):
if trantype=='jatocn':
if JaWord.objects.filter(fwordno=wordno).exists():
wordobj = JaWord.objects.get(fwordno=wordno)
if trantype=='cntoja':
if CnWord.objects.filter(fwordno=wordno).exists():
wordobj = CnWord.objects.get(fwordno=wordno)
if trantype in ('entocn','entoja'):
if EnWord.objects.filter(fwordno=wordno).exists():
wordobj = EnWord.objects.get(fwordno=wordno)
if trantype=='cntoen':
if CnWord.objects.filter(fwordno=wordno).exists():
wordobj = CnWord.objects.get(fwordno=wordno)
if request.method == "GET":
return render(request,'dictedit/transedit.html', {"word":wordobj,"trantype":trantype})
if request.method == "POST":
#worddict = {}
word = request.POST.get('fword','')
pronunciation = request.POST.get('fpronunciation','')
if trantype=='jatocn': # 日译中
if JaWord.objects.filter(fwordno=wordno).exists():
wordobj = JaWord.objects.get(fwordno=wordno)
transword = CnWord.objects.filter(fword=word) # 释义的单词是否存在
if len(transword)==0:
# 如果释义的单词不存在，添加该单词
addresult = funaddword('cn',request.user.first_name,{"word":word,"pronunciation":pronunciation})
if addresult['statu']=='Success':
transobj = addresult['wordobj']
ja2cnobj = Ja2Cn(
fjaword = wordobj,
fcnword = transobj,
fuser = request.user.first_name
)
ja2cnobj.save() # 添加翻译表记录
else:
# 如果单词释义存在，但单词翻译不存在，则进入翻译选择页面则添加释义表
#CnWord.objects.filter(fword=word).exclude(fjaword=wordobj,)
if len(transword)==1:
transobj = CnWord.objects.get(fword=word)
if not Ja2Cn.objects.filter(fjaword=wordobj,fcnword=transobj).exists():
ja2cnobj = Ja2Cn(
fjaword = wordobj,
fcnword = transobj,
fuser = request.user.first_name
)
ja2cnobj.save()
return HttpResponseRedirect('/dict/jaword/'+wordobj.fwordno+'/update/')
if trantype=='cntoja': # 中译日
if CnWord.objects.filter(fwordno=wordno).exists():
wordobj = CnWord.objects.get(fwordno=wordno)
transword = JaWord.objects.filter(fword=word) # 释义的单词是否存在
if len(transword)==0:
# 如果释义的单词不存在，添加该单词
addresult = funaddword('ja',request.user.first_name,{"word":word,"pronunciation":pronunciation})
if addresult['statu']=='Success':
transobj = addresult['wordobj']
ja2cnobj = Ja2Cn(
fjaword = transobj,
fcnword = wordobj,
fuser = request.user.first_name
)
ja2cnobj.save() # 添加翻译表记录
else:
# 如果单词释义存在，但单词翻译不存在，则进入翻译选择页面则添加释义表
#CnWord.objects.filter(fword=word).exclude(fjaword=wordobj,)
if len(transword)==1:
transobj = JaWord.objects.get(fword=word)
if not Ja2Cn.objects.filter(fjaword=wordobj,fcnword=transobj).exists():
ja2cnobj = Ja2Cn(
fjaword = transobj,
fcnword = wordobj,
fuser = request.user.first_name
)
ja2cnobj.save()
return HttpResponseRedirect('/dict/cnword/'+wordobj.fwordno+'/update/')
if trantype=='cntoen': # 中译英
if CnWord.objects.filter(fwordno=wordno).exists():
wordobj = CnWord.objects.get(fwordno=wordno)
transword = EnWord.objects.filter(fword=word) # 释义的单词是否存在
if len(transword)==0:
# 如果释义的单词不存在，添加该单词
addresult = funaddword('en',request.user.first_name,{"word":word,"pronunciation":pronunciation})
if addresult['statu']=='Success':
transobj = addresult['wordobj']
lang2lang = En2Cn(
fenword = transobj,
fcnword = wordobj,
fuser = request.user.first_name
)
lang2lang.save() # 添加翻译表记录
else:
# 如果单词释义存在，但单词翻译不存在，则进入翻译选择页面则添加释义表
#CnWord.objects.filter(fword=word).exclude(fjaword=wordobj,)
if len(transword)==1:
transobj = EnWord.objects.get(fword=word)
if not En2Cn.objects.filter(fcnword=wordobj,fenword=transobj).exists():
lang2lang = En2Cn(
fenword = transobj,
fcnword = wordobj,
fuser = request.user.first_name
)
lang2lang.save()
return HttpResponseRedirect('/dict/cnword/'+wordobj.fwordno+'/update/')
if trantype=='entocn': # 英译中
if EnWord.objects.filter(fwordno=wordno).exists():
wordobj = EnWord.objects.get(fwordno=wordno)
transword = CnWord.objects.filter(fword=word) # 释义的单词是否存在
if len(transword)==0:
# 如果释义的单词不存在，添加该单词
addresult = funaddword('cn',request.user.first_name,{"word":word,"pronunciation":pronunciation})
if addresult['statu']=='Success':
transobj = addresult['wordobj']
lang2lang = En2Cn(
fenword = wordobj,
fcnword = transobj,
fuser = request.user.first_name
)
lang2lang.save() # 添加翻译表记录
else:
# 如果单词释义存在，但单词翻译不存在，则进入翻译选择页面则添加释义表
#CnWord.objects.filter(fword=word).exclude(fjaword=wordobj,)
if len(transword)==1:
transobj = CnWord.objects.get(fword=word)
if not En2Cn.objects.filter(fenword=wordobj,fcnword=transobj).exists():
lang2lang = En2Cn(
fenword = wordobj,
fcnword = transobj,
fuser = request.user.first_name
)
lang2lang.save()
return HttpResponseRedirect('/dict/enword/'+wordobj.fwordno+'/update/')
if trantype=='entoja': # 英译日
if EnWord.objects.filter(fwordno=wordno).exists():
wordobj = EnWord.objects.get(fwordno=wordno)
transword = JaWord.objects.filter(fword=word) # 释义的单词是否存在
if len(transword)==0:
# 如果释义的单词不存在，添加该单词
addresult = funaddword('ja',request.user.first_name,{"word":word,"pronunciation":pronunciation})
if addresult['statu']=='Success':
transobj = addresult['wordobj']
lang2lang = Ja2En(
fenword = wordobj,
fjaword = transobj,
fuser = request.user.first_name
)
lang2lang.save() # 添加翻译表记录
else:
# 如果单词释义存在，但单词翻译不存在，则进入翻译选择页面则添加释义表
#CnWord.objects.filter(fword=word).exclude(fjaword=wordobj,)
if len(transword)==1:
transobj = JaWord.objects.get(fword=word)
if not Ja2En.objects.filter(fenword=wordobj,fjaword=transobj).exists():
lang2lang = Ja2En(
fenword = wordobj,
fjaword = transobj,
fuser = request.user.first_name
)
lang2lang.save()
return HttpResponseRedirect('/dict/enword/'+wordobj.fwordno+'/update/')
@login_required
def transdel(request,fid,trantype):
if trantype in ('jatocn','cntoja'):
if Ja2Cn.objects.filter(pk=fid).exists():
Ja2Cn.objects.filter(pk=fid).delete()
if trantype in ('entocn','cntoen'):
if En2Cn.objects.filter(pk=fid).exists():
En2Cn.objects.filter(pk=fid).delete()
if trantype in ('jatoen','entoja'):
if Ja2En.objects.filter(pk=fid).exists():
Ja2En.objects.filter(pk=fid).delete()
# 返回调用的页面
return HttpResponseRedirect(request.META.get('HTTP_REFERER'))
| 50.907317
| 116
| 0.499425
| 863
| 10,436
| 6
| 0.156431
| 0.077829
| 0.04635
| 0.057937
| 0.752414
| 0.714948
| 0.70954
| 0.70954
| 0.695635
| 0.684048
| 0
| 0.010883
| 0.401303
| 10,436
| 205
| 117
| 50.907317
| 0.817862
| 0.077233
| 0
| 0.69186
| 0
| 0
| 0.05329
| 0.005423
| 0
| 0
| 0
| 0
| 0
| 1
| 0.023256
| false
| 0
| 0.040698
| 0
| 0.127907
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 4
|
1ee484740bcadf14e042cf8adbf119345900d4bb
| 97
|
py
|
Python
|
m_kplug/model/criterions/gcn_loss.py
|
WaveLi123/m-kplug
|
9888e67ac85888a16a6ad069d1de4b5877c92bc8
|
[
"Apache-2.0"
] | 2
|
2022-03-15T12:30:03.000Z
|
2022-03-24T09:08:17.000Z
|
m_kplug/model/criterions/gcn_loss.py
|
WaveLi123/m-kplug
|
9888e67ac85888a16a6ad069d1de4b5877c92bc8
|
[
"Apache-2.0"
] | null | null | null |
m_kplug/model/criterions/gcn_loss.py
|
WaveLi123/m-kplug
|
9888e67ac85888a16a6ad069d1de4b5877c92bc8
|
[
"Apache-2.0"
] | null | null | null |
"""
https://github.com/Megvii-Nanjing/ML-GCN/blob/master/models.py
"""
import torch
torch.save()
| 16.166667
| 62
| 0.721649
| 15
| 97
| 4.666667
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.061856
| 97
| 6
| 63
| 16.166667
| 0.769231
| 0.639175
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
949f678741a8de9d3cd2515041d2d96546241fde
| 3,456
|
py
|
Python
|
flopyAdapter/mapping/flopy_package_to_adapter_mapping.py
|
inowas/flopyAdapter
|
19ec295fbe7f45ade949569fef9e30ac64a6c165
|
[
"MIT"
] | null | null | null |
flopyAdapter/mapping/flopy_package_to_adapter_mapping.py
|
inowas/flopyAdapter
|
19ec295fbe7f45ade949569fef9e30ac64a6c165
|
[
"MIT"
] | 1
|
2019-10-30T12:40:38.000Z
|
2019-10-30T12:40:38.000Z
|
flopyAdapter/mapping/flopy_package_to_adapter_mapping.py
|
inowas/flopyAdapter
|
19ec295fbe7f45ade949569fef9e30ac64a6c165
|
[
"MIT"
] | null | null | null |
"""
Mapping of flopy package names to modflow adapters
"""
from flopyAdapter.modflow_package_adapter.basadapter import BasAdapter
from flopyAdapter.modflow_package_adapter.chdadapter import ChdAdapter
from flopyAdapter.modflow_package_adapter.disadapter import DisAdapter
from flopyAdapter.modflow_package_adapter.drnadapter import DrnAdapter
from flopyAdapter.modflow_package_adapter.ghbadapter import GhbAdapter
from flopyAdapter.modflow_package_adapter.hobadapter import HobAdapter
from flopyAdapter.modflow_package_adapter.lpfadapter import LpfAdapter
from flopyAdapter.modflow_package_adapter.mfadapter import MfAdapter
from flopyAdapter.modflow_package_adapter.nwtadapter import NwtAdapter
from flopyAdapter.modflow_package_adapter.ocadapter import OcAdapter
from flopyAdapter.modflow_package_adapter.pcgadapter import PcgAdapter
from flopyAdapter.modflow_package_adapter.rchadapter import RchAdapter
from flopyAdapter.modflow_package_adapter.evtadapter import EvtAdapter
from flopyAdapter.modflow_package_adapter.rivadapter import RivAdapter
from flopyAdapter.modflow_package_adapter.upwadapter import UpwAdapter
from flopyAdapter.modflow_package_adapter.weladapter import WelAdapter
from flopyAdapter.modflow_package_adapter.lmtadapter import LmtAdapter
from flopyAdapter.modflow_package_adapter.mpadapter import MpAdapter
from flopyAdapter.modflow_package_adapter.mpbasadapter import MpBasAdapter
from flopyAdapter.modflow_package_adapter.mpsimadapter import MpSimAdapter
from flopyAdapter.modflow_package_adapter.mtadapter import MtAdapter
from flopyAdapter.modflow_package_adapter.advadapter import AdvAdapter
from flopyAdapter.modflow_package_adapter.btnadapter import BtnAdapter
from flopyAdapter.modflow_package_adapter.dspadapter import DspAdapter
from flopyAdapter.modflow_package_adapter.gcgadapter import GcgAdapter
from flopyAdapter.modflow_package_adapter.lktadapter import LktAdapter
from flopyAdapter.modflow_package_adapter.phcadapter import PhcAdapter
from flopyAdapter.modflow_package_adapter.rctadapter import RctAdapter
from flopyAdapter.modflow_package_adapter.sftadapter import SftAdapter
from flopyAdapter.modflow_package_adapter.ssmadapter import SsmAdapter
from flopyAdapter.modflow_package_adapter.tobadapter import TobAdapter
from flopyAdapter.modflow_package_adapter.uztadapter import UztAdapter
from flopyAdapter.modflow_package_adapter.swtadapter import SwtAdapter
from flopyAdapter.modflow_package_adapter.vdfadapter import VdfAdapter
from flopyAdapter.modflow_package_adapter.vscadapter import VscAdapter
FLOPY_PACKAGE_TO_ADAPTER_MAPPER = {
# Main adapters
"mf": MfAdapter,
"mt": MtAdapter,
"mp": MpAdapter,
"mpbas": MpBasAdapter,
"mpsim": MpSimAdapter,
# Package adapters
"adv": AdvAdapter,
"bas": BasAdapter,
"bas6": BasAdapter,
"btn": BtnAdapter,
"chd": ChdAdapter,
"dis": DisAdapter,
"drn": DrnAdapter,
"dsp": DspAdapter,
"evt": EvtAdapter,
"gcg": GcgAdapter,
"ghb": GhbAdapter,
"hob": HobAdapter,
"lkt": LktAdapter,
"lmt": LmtAdapter,
"lpf": LpfAdapter,
"nwt": NwtAdapter,
"oc": OcAdapter,
"pcg": PcgAdapter,
"phc": PhcAdapter,
"rch": RchAdapter,
"rct": RctAdapter,
"riv": RivAdapter,
"sft": SftAdapter,
"ssm": SsmAdapter,
"swt": SwtAdapter,
"tob": TobAdapter,
"upw": UpwAdapter,
"uzt": UztAdapter,
"vdf": VdfAdapter,
"vsc": VscAdapter,
"wel": WelAdapter
}
| 42.146341
| 74
| 0.823206
| 369
| 3,456
| 7.509485
| 0.230352
| 0.202093
| 0.290509
| 0.378925
| 0.46734
| 0
| 0
| 0
| 0
| 0
| 0
| 0.000326
| 0.111979
| 3,456
| 81
| 75
| 42.666667
| 0.902574
| 0.023727
| 0
| 0
| 0
| 0
| 0.032402
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.479452
| 0
| 0.479452
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
94b184d6c3aef8d6adc783dd0c01264042c85c0c
| 53
|
py
|
Python
|
zof/__main__.py
|
byllyfish/pylibofp
|
8e96caf83f57cab930b45a78eb4a8eaa6d9d0408
|
[
"MIT"
] | 4
|
2017-09-20T19:10:51.000Z
|
2022-01-10T04:02:00.000Z
|
zof/__main__.py
|
byllyfish/pylibofp
|
8e96caf83f57cab930b45a78eb4a8eaa6d9d0408
|
[
"MIT"
] | 2
|
2017-09-02T22:53:03.000Z
|
2018-01-01T03:27:48.000Z
|
zof/__main__.py
|
byllyfish/pylibofp
|
8e96caf83f57cab930b45a78eb4a8eaa6d9d0408
|
[
"MIT"
] | null | null | null |
import zof
if __name__ == '__main__':
zof.run()
| 10.6
| 26
| 0.622642
| 7
| 53
| 3.571429
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.226415
| 53
| 4
| 27
| 13.25
| 0.609756
| 0
| 0
| 0
| 0
| 0
| 0.150943
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 4
|
94dd71250fd2a8c81cc688f002cef70412356ca2
| 230
|
py
|
Python
|
rezarpeds/datastores/engine/defaults.py
|
RezarpeDS/survey-engine
|
4d4cf63e8e73827470147099f1c99f5b25b486a9
|
[
"MIT"
] | null | null | null |
rezarpeds/datastores/engine/defaults.py
|
RezarpeDS/survey-engine
|
4d4cf63e8e73827470147099f1c99f5b25b486a9
|
[
"MIT"
] | null | null | null |
rezarpeds/datastores/engine/defaults.py
|
RezarpeDS/survey-engine
|
4d4cf63e8e73827470147099f1c99f5b25b486a9
|
[
"MIT"
] | null | null | null |
def translate(message):
"""
A dumb translator which does not actually translate anything.
:param message: The message.
:return: A translated message (dummy: actually, the same message).
"""
return message
| 25.555556
| 70
| 0.682609
| 27
| 230
| 5.814815
| 0.62963
| 0.165605
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.230435
| 230
| 8
| 71
| 28.75
| 0.887006
| 0.682609
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 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
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 4
|
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