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 |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
daece99b2a82989e1c579f5ed5a84eefc556bf72
| 665
|
py
|
Python
|
lavajato/models.py
|
lolitthax/projeto-topicos-especiaisI
|
c2fa9ba2b8e55063be8e14f7d4012beb7be065dd
|
[
"MIT"
] | null | null | null |
lavajato/models.py
|
lolitthax/projeto-topicos-especiaisI
|
c2fa9ba2b8e55063be8e14f7d4012beb7be065dd
|
[
"MIT"
] | null | null | null |
lavajato/models.py
|
lolitthax/projeto-topicos-especiaisI
|
c2fa9ba2b8e55063be8e14f7d4012beb7be065dd
|
[
"MIT"
] | 1
|
2020-11-03T13:11:40.000Z
|
2020-11-03T13:11:40.000Z
|
from django.db import models
# Create your models here.
class Cliente(models.Model):
nome = models.CharField(max_length=30)
email = models.CharField(max_length=60)
cpf = models.CharField(max_length=11)
telefone = models.CharField(max_length=15)
def __str__(self):
return self.nome
class Veiculo(models.Model):
placa = models.CharField(max_length=7)
ano = models.IntegerField()
modelo = models.CharField(max_length=30)
cor = models.CharField(max_length=30)
descricao = models.CharField(max_length=50)
cliente = models.ForeignKey(Cliente, on_delete=models.CASCADE)
def __str__(self):
return self.placa
| 33.25
| 66
| 0.718797
| 88
| 665
| 5.238636
| 0.443182
| 0.260304
| 0.312364
| 0.416486
| 0.255965
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027372
| 0.17594
| 665
| 20
| 67
| 33.25
| 0.813869
| 0.03609
| 0
| 0.117647
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.117647
| false
| 0
| 0.058824
| 0.117647
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
9718c12608474f2540753bf4235e4e31ef3fb32e
| 224
|
py
|
Python
|
drivers/plot_S21_prot_vs_teff.py
|
lgbouma/gilly
|
b3bc7cf53c28eee6420cd85c3975062d4f46c611
|
[
"MIT"
] | null | null | null |
drivers/plot_S21_prot_vs_teff.py
|
lgbouma/gilly
|
b3bc7cf53c28eee6420cd85c3975062d4f46c611
|
[
"MIT"
] | null | null | null |
drivers/plot_S21_prot_vs_teff.py
|
lgbouma/gilly
|
b3bc7cf53c28eee6420cd85c3975062d4f46c611
|
[
"MIT"
] | null | null | null |
from gilly.plotting import plot_S21_prot_vs_teff
plot_S21_prot_vs_teff(koiflag=[0])
plot_S21_prot_vs_teff(koiflag=[0], ylim=[0.1,20])
plot_S21_prot_vs_teff(koiflag=[0,1])
plot_S21_prot_vs_teff(koiflag=[0,1], ylim=[0.1,20])
| 32
| 51
| 0.794643
| 47
| 224
| 3.361702
| 0.297872
| 0.221519
| 0.348101
| 0.411392
| 0.753165
| 0.64557
| 0.64557
| 0.329114
| 0
| 0
| 0
| 0.112676
| 0.049107
| 224
| 6
| 52
| 37.333333
| 0.629108
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.2
| 0
| 0.2
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
9736a81ef912c8509133559afc8f0df7e70c72ea
| 119
|
py
|
Python
|
coffemachine_project/coffemachine/machine/admin.py
|
Dejna93/django-coffee-machine
|
f7de7b0e5e3009d86b91512db0b5980196d95520
|
[
"MIT"
] | null | null | null |
coffemachine_project/coffemachine/machine/admin.py
|
Dejna93/django-coffee-machine
|
f7de7b0e5e3009d86b91512db0b5980196d95520
|
[
"MIT"
] | null | null | null |
coffemachine_project/coffemachine/machine/admin.py
|
Dejna93/django-coffee-machine
|
f7de7b0e5e3009d86b91512db0b5980196d95520
|
[
"MIT"
] | null | null | null |
# Register your models here.
from django.contrib import admin
from .models import Coffee
admin.site.register(Coffee)
| 17
| 32
| 0.798319
| 17
| 119
| 5.588235
| 0.647059
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.134454
| 119
| 6
| 33
| 19.833333
| 0.92233
| 0.218487
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
973f8dcb0481bff30ed685dd7c09ea8b65409194
| 27
|
py
|
Python
|
scanflow/deploy/__init__.py
|
gusseppe/autodeploy
|
a3caf2eb7db86cd111138a8cb5443d3f1ee4152c
|
[
"MIT"
] | 2
|
2019-11-17T11:24:23.000Z
|
2020-02-07T10:57:54.000Z
|
scanflow/deploy/__init__.py
|
gusseppe/scanflow
|
16321a5380bebaa7ea9fff0bf5903c3bbf108cd2
|
[
"MIT"
] | 6
|
2020-11-13T18:35:12.000Z
|
2022-02-10T01:55:33.000Z
|
scanflow/deploy/__init__.py
|
gusseppe/autodeploy
|
a3caf2eb7db86cd111138a8cb5443d3f1ee4152c
|
[
"MIT"
] | 3
|
2020-11-27T09:29:40.000Z
|
2021-07-27T09:16:40.000Z
|
from .deploy import Deploy
| 13.5
| 26
| 0.814815
| 4
| 27
| 5.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.148148
| 27
| 1
| 27
| 27
| 0.956522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
976654209133ce02df0cad5c79dd454fb1a53907
| 5,294
|
py
|
Python
|
ldklib/docker_models.py
|
lidingke/keras-yolo3
|
38748d814074dd9d311382a2c7b91505f9dceb58
|
[
"MIT"
] | null | null | null |
ldklib/docker_models.py
|
lidingke/keras-yolo3
|
38748d814074dd9d311382a2c7b91505f9dceb58
|
[
"MIT"
] | null | null | null |
ldklib/docker_models.py
|
lidingke/keras-yolo3
|
38748d814074dd9d311382a2c7b91505f9dceb58
|
[
"MIT"
] | null | null | null |
import docker
import grpc
import ctpn_pb2
import ctpn_pb2_grpc
import yolo_pb2
import yolo_pb2_grpc
import crnn_pb2
import crnn_pb2_grpc
import cv2
import json
import numpy as np
class CTPN_Docker(object):
def __init__(self,docker_client = 'unix://var/run/docker.sock',
host_port = 'localhost:50053',run_args=None,run_kwargs=None):
self.client = docker.DockerClient(base_url=docker_client)
channel = grpc.insecure_channel(host_port)
self.stub = ctpn_pb2_grpc.ModelStub(channel)
self.run_args = run_args if run_args else []
self.run_kwargs = {'image': "trnet/ctpn:1.0.1",
'runtime': 'nvidia',
"command" : "python rpc/server.py",
'environment': ["CUDA_VISIBLE_DEVICES=1"],
'ports': {'50051/tcp': '50053'},
'detach': True,
'auto_remove': True}
if run_kwargs:
self.run_kwargs.update(run_kwargs)
# pass
def run(self,img):
assert isinstance(img,np.ndarray), 'img must be a numpy array.'
imgstr = img.tobytes()
shape = json.dumps(img.shape)
# stub = ctpn_pb2_grpc.ModelStub(grpc.insecure_channel('localhost:50051'))
response = self.stub.predict(ctpn_pb2.rect_request(img=imgstr, shape=shape))
return json.loads(response.message)
def __enter__(self):
self.container = self.client.containers.run(*self.run_args,**self.run_kwargs)
for line in self.container.logs(stream=True):
if line.strip().find(b'grpc_server_start') >= 0:
break
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.container.stop()
print('container has stopped.')
class YOLO_Docker(object):
def __init__(self,docker_client = 'unix://var/run/docker.sock',
host_port = 'localhost:50053'):
self.client = docker.DockerClient(base_url=docker_client)
channel = grpc.insecure_channel(host_port)
self.stub = yolo_pb2_grpc.YOLOModelStub(channel)
self.run_args = []
self.run_kwargs = {'image' : "yolo_server",
'runtime':'nvidia',
'environment' : ["CUDA_VISIBLE_DEVICES=1"],
'ports' : {'50051/tcp':'50053'},
'detach':True,
'auto_remove' : True}
def run(self,img):
assert isinstance(img,np.ndarray), 'img must be a numpy array.'
imgstr = img.tobytes()
shape = json.dumps(img.shape)
response = self.stub.predict(yolo_pb2.rect_request(img=imgstr, shape=shape))
return json.loads(response.message)
def __enter__(self):
self.container = self.client.containers.run(*self.run_args,**self.run_kwargs)
for line in self.container.logs(stream=True):
if line.strip() == b'grpc_server_start':
break
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.container.stop()
print('container has stopped.')
class CRNN_Docker(object):
"""
__init__
:param docker_client:unix://var/run/docker.sock
:param host_port:'localhost:50053'
:param run_args:[]
:param run_kwargs:default-
'image': "trnet/crnn:1.0.2",
'runtime': 'nvidia',
"command" : "python server.py",
'environment': ["CUDA_VISIBLE_DEVICES=1"],
'ports': {'50054/tcp': '50054'},
'detach': True,
'auto_remove': True
"""
def __init__(self, docker_client='unix://var/run/docker.sock',
host_port='localhost:50054',run_args=None,run_kwargs=None):
self.client = docker.DockerClient(base_url=docker_client)
channel = grpc.insecure_channel(host_port)
self.stub = crnn_pb2_grpc.GreeterStub(channel)
self.run_args = run_args if run_args else []
self.run_kwargs = {'image': "trnet/crnn:1.0.2",
'runtime': 'nvidia',
"command" : "python server.py",
'environment': ["CUDA_VISIBLE_DEVICES=0"],
'ports': {'50054/tcp': '50054'},
'detach': True,
'auto_remove': True}
if run_kwargs:
self.run_kwargs.update(run_kwargs)
# self.run_kwargs = default_k
def run(self,im):
assert isinstance(im,np.ndarray), 'img must be a numpy array.'
shape = json.dumps(im.shape)
ymax, xmax, _ = im.shape
xmin, ymin = 0, 0
boxline = xmin, ymin, xmax, ymax
box = json.dumps([boxline])
response = self.stub.idc_crnn(crnn_pb2.CrnnRequest(img=im.tobytes(), shape=shape, box_list=box))
return response.message
def __enter__(self):
self.container = self.client.containers.run(*self.run_args,**self.run_kwargs)
for line in self.container.logs(stream=True):
# print(line)
if line.strip().find(b'crnn_serve_start') >= 0:
break
return self
def __exit__(self, exc_type, exc_val, exc_tb):
self.container.stop()
print('container has stopped.')
| 37.020979
| 104
| 0.584624
| 634
| 5,294
| 4.649842
| 0.190852
| 0.048847
| 0.039688
| 0.02578
| 0.760176
| 0.733718
| 0.725577
| 0.714722
| 0.701832
| 0.681479
| 0
| 0.025621
| 0.292218
| 5,294
| 143
| 105
| 37.020979
| 0.761142
| 0.093313
| 0
| 0.596154
| 0
| 0
| 0.141621
| 0.030393
| 0
| 0
| 0
| 0
| 0.028846
| 1
| 0.115385
| false
| 0
| 0.105769
| 0
| 0.307692
| 0.028846
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
97abf2f9413abd54c0d76f68cb6670a25087922a
| 190
|
py
|
Python
|
imsearchtools/__init__.py
|
carandraug/imsearch-tools
|
9e6af18d63ffa43cef033bf5d75d32f62a8efcc7
|
[
"BSD-2-Clause"
] | 7
|
2016-06-18T11:22:43.000Z
|
2019-08-28T23:28:41.000Z
|
imsearchtools/__init__.py
|
carandraug/imsearch-tools
|
9e6af18d63ffa43cef033bf5d75d32f62a8efcc7
|
[
"BSD-2-Clause"
] | null | null | null |
imsearchtools/__init__.py
|
carandraug/imsearch-tools
|
9e6af18d63ffa43cef033bf5d75d32f62a8efcc7
|
[
"BSD-2-Clause"
] | 2
|
2016-12-12T07:40:42.000Z
|
2018-02-19T13:26:07.000Z
|
import engines as query
import process
import utils
import postproc_modules
import http_service_helper
from gevent import monkey
monkey.patch_all(thread=False, select=False, httplib=False)
| 21.111111
| 59
| 0.852632
| 28
| 190
| 5.642857
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105263
| 190
| 8
| 60
| 23.75
| 0.929412
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.857143
| 0
| 0.857143
| 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
| 1
| 0
|
0
| 5
|
97bd4fef8a915af2bee6d4d6ba8247fd48f32e29
| 83
|
py
|
Python
|
interleaving/simulation/__init__.py
|
mpkato/interleaving
|
7907f7dd61bfcad57ad602b5c93e601677025da7
|
[
"MIT"
] | 107
|
2016-10-01T12:49:24.000Z
|
2022-02-23T23:48:26.000Z
|
interleaving/simulation/__init__.py
|
mpkato/interleaving
|
7907f7dd61bfcad57ad602b5c93e601677025da7
|
[
"MIT"
] | 39
|
2016-09-25T01:41:25.000Z
|
2018-10-15T04:38:18.000Z
|
interleaving/simulation/__init__.py
|
mpkato/interleaving
|
7907f7dd61bfcad57ad602b5c93e601677025da7
|
[
"MIT"
] | 20
|
2017-03-13T21:36:11.000Z
|
2022-03-24T17:57:46.000Z
|
from .simulator import Simulator
from .ranker import Ranker
from .user import User
| 20.75
| 32
| 0.819277
| 12
| 83
| 5.666667
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.144578
| 83
| 3
| 33
| 27.666667
| 0.957746
| 0
| 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
| 1
| 0
|
0
| 5
|
97cee469a7e353e93fb3d68746f0e1145a322683
| 103
|
py
|
Python
|
MC/assets/__init__.py
|
Hoyin7123/ByTopicPastPaperCreator
|
083d6d59f634a7f8f6dc4d5b63471e56bd579f8a
|
[
"Apache-2.0"
] | null | null | null |
MC/assets/__init__.py
|
Hoyin7123/ByTopicPastPaperCreator
|
083d6d59f634a7f8f6dc4d5b63471e56bd579f8a
|
[
"Apache-2.0"
] | null | null | null |
MC/assets/__init__.py
|
Hoyin7123/ByTopicPastPaperCreator
|
083d6d59f634a7f8f6dc4d5b63471e56bd579f8a
|
[
"Apache-2.0"
] | null | null | null |
from .pruner import *
from .splitter import *
from .sorter import *
__all__ = ("Pruner", "Splitter")
| 14.714286
| 32
| 0.68932
| 12
| 103
| 5.583333
| 0.5
| 0.298507
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.174757
| 103
| 6
| 33
| 17.166667
| 0.788235
| 0
| 0
| 0
| 0
| 0
| 0.135922
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.75
| 0
| 0.75
| 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
| 1
| 0
|
0
| 5
|
97d0cd2387f29dad74ad0dcc461af6cad505f428
| 15
|
py
|
Python
|
test/integration/ListNewSized/list new sized.py
|
HighSchoolHacking/GLS-Draft
|
9e418b6290e7c8e3f2da87668784bdba1cde5a76
|
[
"MIT"
] | 30
|
2019-10-29T12:47:50.000Z
|
2022-02-12T06:41:39.000Z
|
test/integration/ListNewSized/list new sized.py
|
HighSchoolHacking/GLS-Draft
|
9e418b6290e7c8e3f2da87668784bdba1cde5a76
|
[
"MIT"
] | 247
|
2017-09-21T17:11:18.000Z
|
2019-10-08T12:59:07.000Z
|
test/integration/ListNewSized/list new sized.py
|
HighSchoolHacking/GLS-Draft
|
9e418b6290e7c8e3f2da87668784bdba1cde5a76
|
[
"MIT"
] | 17
|
2017-10-01T16:53:20.000Z
|
2018-11-28T07:20:35.000Z
|
#
[None] * 5
#
| 3.75
| 10
| 0.333333
| 2
| 15
| 2.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 0.333333
| 15
| 3
| 11
| 5
| 0.4
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
8afeb62f39b7504dfb14ac4c1f2d3f19910dd907
| 259
|
py
|
Python
|
keras_xlnet/__init__.py
|
weiyuhan9703/keras-xlnet
|
a50cca33e7948824ca4f392193689ce1a8535c14
|
[
"MIT"
] | 2
|
2021-05-30T11:14:06.000Z
|
2021-05-30T11:18:29.000Z
|
keras_xlnet/__init__.py
|
Rukawa027/keras-xlnet
|
a50cca33e7948824ca4f392193689ce1a8535c14
|
[
"MIT"
] | null | null | null |
keras_xlnet/__init__.py
|
Rukawa027/keras-xlnet
|
a50cca33e7948824ca4f392193689ce1a8535c14
|
[
"MIT"
] | 1
|
2021-05-30T11:14:10.000Z
|
2021-05-30T11:14:10.000Z
|
from .permutation import *
from .mask_embed import *
from .position_embed import *
from .segment_bias import *
from .segment_embed import *
from .attention import *
from .xlnet import *
from .loader import *
from .tokenizer import *
from .pretrained import *
| 23.545455
| 29
| 0.76834
| 34
| 259
| 5.735294
| 0.382353
| 0.461538
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15444
| 259
| 10
| 30
| 25.9
| 0.890411
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 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
| 5
|
c18cbf9b0ab0577e58c7e6a0a069ba62bb4d82bf
| 108
|
py
|
Python
|
setup.py
|
rfgil/quarere
|
1edd56379cb1fc883308f69a4b9bf7b606954d5d
|
[
"MIT"
] | null | null | null |
setup.py
|
rfgil/quarere
|
1edd56379cb1fc883308f69a4b9bf7b606954d5d
|
[
"MIT"
] | null | null | null |
setup.py
|
rfgil/quarere
|
1edd56379cb1fc883308f69a4b9bf7b606954d5d
|
[
"MIT"
] | null | null | null |
from setuptools import setup, find_packages
setup(name='quarere', version='2.0', packages=find_packages())
| 27
| 62
| 0.777778
| 15
| 108
| 5.466667
| 0.733333
| 0.292683
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.020202
| 0.083333
| 108
| 3
| 63
| 36
| 0.808081
| 0
| 0
| 0
| 0
| 0
| 0.092593
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 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
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
c1a74458e4fd09a17299b3c4eee901b64e6d116b
| 92
|
py
|
Python
|
tools/checkkey.py
|
AyoubUmoru/raspi-box
|
e984bcf4cc18dd775cb455e674304c34f162f454
|
[
"MIT"
] | null | null | null |
tools/checkkey.py
|
AyoubUmoru/raspi-box
|
e984bcf4cc18dd775cb455e674304c34f162f454
|
[
"MIT"
] | 1
|
2021-06-02T01:00:19.000Z
|
2021-06-02T01:00:19.000Z
|
tools/checkkey.py
|
AyoubUmoru/raspi-box
|
e984bcf4cc18dd775cb455e674304c34f162f454
|
[
"MIT"
] | null | null | null |
import sys
import tty
tty.setcbreak(sys.stdin)
while True:
print ord(sys.stdin.read(1))
| 15.333333
| 32
| 0.73913
| 16
| 92
| 4.25
| 0.6875
| 0.235294
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.012658
| 0.141304
| 92
| 5
| 33
| 18.4
| 0.848101
| 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 | 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
| 1
| 0
| 0
| 0
|
0
| 5
|
c1d38609937d0ae608227960c01763dacd095f03
| 1,463
|
py
|
Python
|
tests/test_auth.py
|
ionagamed/hexagonal
|
60c0e0839de0d616c50ad87d343a3da3ef6433a6
|
[
"MIT"
] | null | null | null |
tests/test_auth.py
|
ionagamed/hexagonal
|
60c0e0839de0d616c50ad87d343a3da3ef6433a6
|
[
"MIT"
] | 9
|
2018-02-14T07:41:40.000Z
|
2018-03-27T11:24:21.000Z
|
tests/test_auth.py
|
ionagamed/hexagonal
|
60c0e0839de0d616c50ad87d343a3da3ef6433a6
|
[
"MIT"
] | null | null | null |
import pytest
from tests.common import call, root_login, get_login_pair
from hexagonal.auth import decode_token
# decode_token raises an exception when unable to parse
#
#
# def test__root_login__should_not_fail():
# decode_token(root_login())
#
#
# def test__registering_from_root__should_not_fail():
# token = root_login()
# login, password = get_login_pair()
# call('auth.register', {
# 'login': login,
# 'password': password,
# 'role': 'student-patron',
# 'address': '123',
# 'name': 'One Two',
# 'card_number': 123,
# 'phone': 123
# }, token)
#
#
# def test__just_registered_user__should_be_able_to_login():
# token = root_login()
# login, password = get_login_pair()
# call('auth.register', {
# 'login': login,
# 'password': password,
# 'role': 'student-patron',
# 'address': '123',
# 'name': 'One Two',
# 'card_number': 123,
# 'phone': 123
# }, token)
# decode_token(call('auth.login', {
# 'login': login,
# 'password': password
# }))
#ToDo
#def test__creating_new_document_book_is_correct():
#def test__creating_new_document_journal_is_correct():
#def test_creating_new_document_av_file_is_correct():
#def access_of_librariant_to_adding_new_book_to_system_is_correct():
#def access_of_student_to_booking_system_is_correct():
#def access_of_TA_to_booking_system_is_correct():
| 26.125
| 68
| 0.650034
| 179
| 1,463
| 4.832402
| 0.346369
| 0.048555
| 0.104046
| 0.090173
| 0.565318
| 0.473988
| 0.413873
| 0.332948
| 0.332948
| 0.332948
| 0
| 0.015693
| 0.215995
| 1,463
| 55
| 69
| 26.6
| 0.738448
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.018182
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a9b4bc0810aa6a4c89a015b3a571c29fa97a826c
| 170
|
py
|
Python
|
my_project/apps/my_app/views.py
|
wen96/django-boilerplate
|
6e2b208de5730540ca4def28b296938582b8dac5
|
[
"MIT"
] | null | null | null |
my_project/apps/my_app/views.py
|
wen96/django-boilerplate
|
6e2b208de5730540ca4def28b296938582b8dac5
|
[
"MIT"
] | null | null | null |
my_project/apps/my_app/views.py
|
wen96/django-boilerplate
|
6e2b208de5730540ca4def28b296938582b8dac5
|
[
"MIT"
] | null | null | null |
from django.shortcuts import render
from django.views.generic import View
class HomeView(View):
def get(self, request):
return render(request, 'home.html')
| 21.25
| 43
| 0.729412
| 23
| 170
| 5.391304
| 0.73913
| 0.16129
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.176471
| 170
| 7
| 44
| 24.285714
| 0.885714
| 0
| 0
| 0
| 0
| 0
| 0.052941
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.2
| false
| 0
| 0.4
| 0.2
| 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
| 1
| 1
| 0
|
0
| 5
|
a9edf0e974ebe0aba27e58d30254a9ca44fef0f6
| 202
|
py
|
Python
|
api/context_processors.py
|
UQ-UQx/uqx_api
|
54c132ab345fa698be090c3ab4f72c8bd7b42bc3
|
[
"MIT"
] | 3
|
2015-04-13T14:23:39.000Z
|
2018-02-13T15:09:30.000Z
|
api/context_processors.py
|
UQ-UQx/uqx_api
|
54c132ab345fa698be090c3ab4f72c8bd7b42bc3
|
[
"MIT"
] | 7
|
2015-04-20T07:00:09.000Z
|
2021-12-13T19:45:12.000Z
|
api/context_processors.py
|
UQ-UQx/uqx_api
|
54c132ab345fa698be090c3ab4f72c8bd7b42bc3
|
[
"MIT"
] | 3
|
2015-03-26T19:29:18.000Z
|
2016-01-19T23:17:00.000Z
|
import uqx_api.settings
def test_view(request):
extra = {}
extra['settings_brand'] = uqx_api.settings.BRAND
extra['settings_brand_website'] = uqx_api.settings.BRAND_WEBSITE
return extra
| 28.857143
| 68
| 0.742574
| 27
| 202
| 5.259259
| 0.444444
| 0.366197
| 0.295775
| 0.267606
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.153465
| 202
| 7
| 69
| 28.857143
| 0.830409
| 0
| 0
| 0
| 0
| 0
| 0.17734
| 0.108374
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.166667
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e712b95dc49750ca928ac86fa3a26d881979c0e0
| 15,130
|
py
|
Python
|
deeplift/layers/convolutional.py
|
jianwang-ntu/deeplift_tf2.0
|
957511e3e307fdb93f65bf54cc2b5214e5374f49
|
[
"MIT"
] | null | null | null |
deeplift/layers/convolutional.py
|
jianwang-ntu/deeplift_tf2.0
|
957511e3e307fdb93f65bf54cc2b5214e5374f49
|
[
"MIT"
] | null | null | null |
deeplift/layers/convolutional.py
|
jianwang-ntu/deeplift_tf2.0
|
957511e3e307fdb93f65bf54cc2b5214e5374f49
|
[
"MIT"
] | null | null | null |
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
from .core import *
from .helper_functions import conv1d_transpose_via_conv2d
from . import helper_functions as hf
import tensorflow as tf
PoolMode = deeplift.util.enum(max='max', avg='avg')
PaddingMode = deeplift.util.enum(same='SAME', valid='VALID')
DataFormat = deeplift.util.enum(channels_first='channels_first',
channels_last='channels_last')
class Conv(SingleInputMixin, Node):
def __init__(self, conv_mxts_mode, **kwargs):
self.conv_mxts_mode = conv_mxts_mode
super(Conv, self).__init__(**kwargs)
class Conv1D(Conv):
"""
Note: is ACTUALLY a cross-correlation i.e. weights are not 'flipped'
"""
def __init__(self, kernel, bias, stride, padding, **kwargs):
"""
The ordering of the dimensions is assumed to be: length, channels
Note: this is ACTUALLY a cross-correlation,
i.e. the weights are not 'flipped' as for a convolution.
This is the tensorflow behaviour.
"""
super(Conv1D, self).__init__(**kwargs)
#kernel has dimensions:
#length x inp_channels x num output channels
self.kernel = kernel
self.bias = bias
if (hasattr(stride, '__iter__')):
assert len(stride)==1
stride=stride[0]
self.stride = stride
self.padding = padding
def _compute_shape(self, input_shape):
#assuming a theano dimension ordering here...
shape_to_return = [None]
if (input_shape is None or input_shape[1] is None):
shape_to_return += [None]
else:
if (self.padding == PaddingMode.valid):
#overhands are excluded
shape_to_return.append(
1+int((input_shape[1]-self.kernel.shape[0])/self.stride))
elif (self.padding == PaddingMode.same):
shape_to_return.append(
int((input_shape[1]+self.stride-1)/self.stride))
else:
raise RuntimeError("Please implement shape inference for"
" padding mode: "+str(self.padding))
shape_to_return.append(self.kernel.shape[-1]) #num output channels
return shape_to_return
def _build_activation_vars(self, input_act_vars):
conv_without_bias = self._compute_conv_without_bias(
input_act_vars,
kernel=self.kernel)
return conv_without_bias + self.bias[None,None,:]
def _build_pos_and_neg_contribs(self):
if (self.conv_mxts_mode == ConvMxtsMode.Linear):
inp_diff_ref = self._get_input_diff_from_reference_vars()
pos_contribs = (self._compute_conv_without_bias(
x=inp_diff_ref*hf.gt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.gt_mask(self.kernel,0.0))
+self._compute_conv_without_bias(
x=inp_diff_ref*hf.lt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.lt_mask(self.kernel,0.0)))
neg_contribs = (self._compute_conv_without_bias(
x=inp_diff_ref*hf.lt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.gt_mask(self.kernel,0.0))
+self._compute_conv_without_bias(
x=inp_diff_ref*hf.gt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.lt_mask(self.kernel,0.0)))
else:
raise RuntimeError("Unsupported conv_mxts_mode: "+
self.conv_mxts_mode)
return pos_contribs, neg_contribs
def _compute_conv_without_bias(self, x, kernel):
conv_without_bias = tf.nn.conv1d(
input=x,
filters=kernel,
stride=self.stride,
padding=self.padding)
return conv_without_bias
def _get_mxts_increments_for_inputs(self):
pos_mxts = self.get_pos_mxts()
neg_mxts = self.get_neg_mxts()
inp_diff_ref = self._get_input_diff_from_reference_vars()
output_shape = self._get_input_shape()
if (self.conv_mxts_mode == ConvMxtsMode.Linear):
pos_inp_mask = hf.gt_mask(inp_diff_ref,0.0)
neg_inp_mask = hf.lt_mask(inp_diff_ref,0.0)
zero_inp_mask = hf.eq_mask(inp_diff_ref,0.0)
inp_mxts_increments = pos_inp_mask*(
conv1d_transpose_via_conv2d(
value=pos_mxts,
kernel=self.kernel*(hf.gt_mask(self.kernel,0.0)),
tensor_with_output_shape=self.inputs.get_activation_vars(),
padding=self.padding,
stride=self.stride)
+conv1d_transpose_via_conv2d(
value=neg_mxts,
kernel=self.kernel*(hf.lt_mask(self.kernel,0.0)),
tensor_with_output_shape=self.inputs.get_activation_vars(),
padding=self.padding,
stride=self.stride))
inp_mxts_increments += neg_inp_mask*(
conv1d_transpose_via_conv2d(
value=pos_mxts,
kernel=self.kernel*(hf.lt_mask(self.kernel,0.0)),
tensor_with_output_shape=self.inputs.get_activation_vars(),
padding=self.padding,
stride=self.stride)
+conv1d_transpose_via_conv2d(
value=neg_mxts,
kernel=self.kernel*(hf.gt_mask(self.kernel,0.0)),
tensor_with_output_shape=self.inputs.get_activation_vars(),
padding=self.padding,
stride=self.stride))
inp_mxts_increments += zero_inp_mask*(
conv1d_transpose_via_conv2d(
value=0.5*(neg_mxts+pos_mxts),
kernel=self.kernel,
tensor_with_output_shape=self.inputs.get_activation_vars(),
padding=self.padding,
stride=self.stride))
pos_mxts_increments = inp_mxts_increments
neg_mxts_increments = inp_mxts_increments
else:
raise RuntimeError("Unsupported conv mxts mode: "
+str(self.conv_mxts_mode))
return pos_mxts_increments, neg_mxts_increments
class Conv2D(Conv):
"""
Note: is ACTUALLY a cross-correlation i.e. weights are not 'flipped'
"""
def __init__(self, kernel, bias, strides, padding, data_format, **kwargs):
"""
Note: this is ACTUALLY a cross-correlation,
i.e. the weights are not 'flipped' as for a convolution.
This is the tensorflow behaviour.
"""
super(Conv2D, self).__init__(**kwargs)
#kernel has dimensions:
#rows_kern_width x cols_kern_width x inp_channels x num output channels
self.kernel = kernel
self.bias = bias
self.strides = strides
self.padding = padding
self.data_format = data_format
if (data_format not in ['channels_last', 'channels_first']):
raise NotImplementedError(data_format+" data format"
+" not implemented")
def _compute_shape(self, input_shape):
if (self.data_format == DataFormat.channels_first):
input_shape = [input_shape[0], input_shape[2],
input_shape[3], input_shape[1]]
#assuming channels_last dimension ordering here
shape_to_return = [None]
if (input_shape is None):
shape_to_return += [None, None]
else:
if (self.padding == PaddingMode.valid):
for (dim_inp_len, dim_kern_width, dim_stride) in\
zip(input_shape[1:3], self.kernel.shape[:2], self.strides):
#overhangs are excluded
shape_to_return.append(
1+int((dim_inp_len-dim_kern_width)/dim_stride))
elif (self.padding == PaddingMode.same):
for (dim_inp_len, dim_kern_width, dim_stride) in\
zip(input_shape[1:3], self.kernel.shape[:2], self.strides):
shape_to_return.append(
int((dim_inp_len+dim_stride-1)/dim_stride))
else:
raise RuntimeError("Please implement shape inference for"
" border mode: "+str(self.padding))
shape_to_return.append(self.kernel.shape[-1]) #num output channels
if (self.data_format == DataFormat.channels_first):
shape_to_return = [shape_to_return[0], shape_to_return[3],
shape_to_return[1], shape_to_return[2]]
return shape_to_return
def _build_activation_vars(self, input_act_vars):
if (self.data_format == DataFormat.channels_first):
input_act_vars = tf.transpose(a=input_act_vars,
perm=[0,2,3,1])
conv_without_bias = self._compute_conv_without_bias(
x=input_act_vars,
kernel=self.kernel)
to_return = conv_without_bias + self.bias[None,None,None,:]
if (self.data_format == DataFormat.channels_first):
to_return = tf.transpose(a=to_return,
perm=[0,3,1,2])
return to_return
def _build_pos_and_neg_contribs(self):
if (self.conv_mxts_mode == ConvMxtsMode.Linear):
inp_diff_ref = self._get_input_diff_from_reference_vars()
if (self.data_format == DataFormat.channels_first):
inp_diff_ref = tf.transpose(a=inp_diff_ref,
perm=[0,2,3,1])
pos_contribs = (self._compute_conv_without_bias(
x=inp_diff_ref*hf.gt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.gt_mask(self.kernel,0.0))
+self._compute_conv_without_bias(
x=inp_diff_ref*hf.lt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.lt_mask(self.kernel,0.0)))
neg_contribs = (self._compute_conv_without_bias(
x=inp_diff_ref*hf.lt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.gt_mask(self.kernel,0.0))
+self._compute_conv_without_bias(
x=inp_diff_ref*hf.gt_mask(inp_diff_ref,0.0),
kernel=self.kernel*hf.lt_mask(self.kernel,0.0)))
else:
raise RuntimeError("Unsupported conv_mxts_mode: "+
self.conv_mxts_mode)
if (self.data_format == DataFormat.channels_first):
pos_contribs = tf.transpose(a=pos_contribs,
perm=[0,3,1,2])
neg_contribs = tf.transpose(a=neg_contribs,
perm=[0,3,1,2])
return pos_contribs, neg_contribs
def _compute_conv_without_bias(self, x, kernel):
conv_without_bias = tf.nn.conv2d(
input=x,
filters=kernel,
strides=[1]+list(self.strides)+[1],
padding=self.padding)
return conv_without_bias
def _get_mxts_increments_for_inputs(self):
pos_mxts = self.get_pos_mxts()
neg_mxts = self.get_neg_mxts()
inp_diff_ref = self._get_input_diff_from_reference_vars()
inp_act_vars = self.inputs.get_activation_vars()
strides_to_supply = [1]+list(self.strides)+[1]
if (self.data_format == DataFormat.channels_first):
pos_mxts = tf.transpose(a=pos_mxts, perm=(0,2,3,1))
neg_mxts = tf.transpose(a=neg_mxts, perm=(0,2,3,1))
inp_diff_ref = tf.transpose(a=inp_diff_ref, perm=(0,2,3,1))
inp_act_vars = tf.transpose(a=inp_act_vars, perm=(0,2,3,1))
output_shape = tf.shape(input=inp_act_vars)
if (self.conv_mxts_mode == ConvMxtsMode.Linear):
pos_inp_mask = hf.gt_mask(inp_diff_ref,0.0)
neg_inp_mask = hf.lt_mask(inp_diff_ref,0.0)
zero_inp_mask = hf.eq_mask(inp_diff_ref, 0.0)
inp_mxts_increments = pos_inp_mask*(
tf.nn.conv2d_transpose(
input=pos_mxts,
filters=self.kernel*hf.gt_mask(self.kernel, 0.0),
output_shape=output_shape,
padding=self.padding,
strides=strides_to_supply
)
+tf.nn.conv2d_transpose(
input=neg_mxts,
filters=self.kernel*hf.lt_mask(self.kernel, 0.0),
output_shape=output_shape,
padding=self.padding,
strides=strides_to_supply
))
inp_mxts_increments += neg_inp_mask*(
tf.nn.conv2d_transpose(
input=pos_mxts,
filters=self.kernel*hf.lt_mask(self.kernel, 0.0),
output_shape=output_shape,
padding=self.padding,
strides=strides_to_supply
)
+tf.nn.conv2d_transpose(
input=neg_mxts,
filters=self.kernel*hf.gt_mask(self.kernel, 0.0),
output_shape=output_shape,
padding=self.padding,
strides=strides_to_supply
))
inp_mxts_increments += zero_inp_mask*tf.nn.conv2d_transpose(
input=0.5*(pos_mxts+neg_mxts),
filters=self.kernel,
output_shape=output_shape,
padding=self.padding,
strides=strides_to_supply)
pos_mxts_increments = inp_mxts_increments
neg_mxts_increments = inp_mxts_increments
else:
raise RuntimeError("Unsupported conv mxts mode: "
+str(self.conv_mxts_mode))
if (self.data_format == DataFormat.channels_first):
pos_mxts_increments = tf.transpose(a=pos_mxts_increments,
perm=(0,3,1,2))
neg_mxts_increments = tf.transpose(a=neg_mxts_increments,
perm=(0,3,1,2))
return pos_mxts_increments, neg_mxts_increments
| 46.269113
| 79
| 0.548579
| 1,746
| 15,130
| 4.416953
| 0.087056
| 0.058351
| 0.0389
| 0.03112
| 0.82028
| 0.779305
| 0.731587
| 0.682184
| 0.63278
| 0.610996
| 0
| 0.016705
| 0.362987
| 15,130
| 326
| 80
| 46.411043
| 0.783461
| 0.054131
| 0
| 0.710526
| 0
| 0
| 0.022475
| 0
| 0
| 0
| 0
| 0
| 0.003759
| 1
| 0.048872
| false
| 0
| 0.026316
| 0
| 0.12406
| 0.003759
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 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
| 5
|
e727503520b94740decb311593c92fabee4dcda6
| 36
|
py
|
Python
|
static/data/api_key.py
|
KholiswaT/Satellite-Exploration
|
3aa828318457e66a5dd98cc816de09e166307560
|
[
"MIT"
] | 1
|
2021-05-27T07:10:14.000Z
|
2021-05-27T07:10:14.000Z
|
static/data/api_key.py
|
KholiswaT/Satellite-Exploration
|
3aa828318457e66a5dd98cc816de09e166307560
|
[
"MIT"
] | null | null | null |
static/data/api_key.py
|
KholiswaT/Satellite-Exploration
|
3aa828318457e66a5dd98cc816de09e166307560
|
[
"MIT"
] | 1
|
2020-11-24T03:10:05.000Z
|
2020-11-24T03:10:05.000Z
|
API_Key= "RSNS74-FAEMYM-S26ZDF-4LIZ"
| 36
| 36
| 0.805556
| 6
| 36
| 4.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.142857
| 0.027778
| 36
| 1
| 36
| 36
| 0.657143
| 0
| 0
| 0
| 0
| 0
| 0.675676
| 0.675676
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
e764e53d402e8d6e2db6395c2ddfe1d2e3ff11e9
| 95
|
py
|
Python
|
jpn_bpe_tokenizer/__init__.py
|
stsuchi/Japanese-BPE-Tokenizer
|
a7070913dcae5a84f87fb52362fb5ed7e8a55813
|
[
"MIT"
] | null | null | null |
jpn_bpe_tokenizer/__init__.py
|
stsuchi/Japanese-BPE-Tokenizer
|
a7070913dcae5a84f87fb52362fb5ed7e8a55813
|
[
"MIT"
] | null | null | null |
jpn_bpe_tokenizer/__init__.py
|
stsuchi/Japanese-BPE-Tokenizer
|
a7070913dcae5a84f87fb52362fb5ed7e8a55813
|
[
"MIT"
] | null | null | null |
from .mecab_bpe_tokenizer import MecabBPETokenizer
from .trainer import MecabBPETrainTokenizer
| 31.666667
| 50
| 0.894737
| 10
| 95
| 8.3
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.084211
| 95
| 2
| 51
| 47.5
| 0.954023
| 0
| 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
| 1
| 0
|
0
| 5
|
e7a0f23a8beea3d75beb72809aa98f715c7e3f7b
| 50
|
py
|
Python
|
backend/accounts/signals/__init__.py
|
LloydTao/tickexe
|
a0262b4c8f11fdf57b8284d2a6b80dd2a3ad90ff
|
[
"MIT"
] | null | null | null |
backend/accounts/signals/__init__.py
|
LloydTao/tickexe
|
a0262b4c8f11fdf57b8284d2a6b80dd2a3ad90ff
|
[
"MIT"
] | 2
|
2021-10-15T19:28:59.000Z
|
2021-10-15T19:52:00.000Z
|
backend/accounts/signals/__init__.py
|
LloydTao/tickexe
|
a0262b4c8f11fdf57b8284d2a6b80dd2a3ad90ff
|
[
"MIT"
] | null | null | null |
from .profile import create_profile, save_profile
| 25
| 49
| 0.86
| 7
| 50
| 5.857143
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 50
| 1
| 50
| 50
| 0.911111
| 0
| 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
| 1
| 0
|
0
| 5
|
e7d6dda3573072373b2c0ea60c3ecbe2d3d080ea
| 39
|
py
|
Python
|
intro/part01-01_emoticon/src/emoticon.py
|
Hannah-Abi/python-pro-21
|
2ce32c4bf118054329d19afdf83c50561be1ada8
|
[
"MIT"
] | null | null | null |
intro/part01-01_emoticon/src/emoticon.py
|
Hannah-Abi/python-pro-21
|
2ce32c4bf118054329d19afdf83c50561be1ada8
|
[
"MIT"
] | null | null | null |
intro/part01-01_emoticon/src/emoticon.py
|
Hannah-Abi/python-pro-21
|
2ce32c4bf118054329d19afdf83c50561be1ada8
|
[
"MIT"
] | null | null | null |
# Write your solution here
print(":-)")
| 19.5
| 26
| 0.666667
| 5
| 39
| 5.2
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.128205
| 39
| 2
| 27
| 19.5
| 0.764706
| 0.615385
| 0
| 0
| 0
| 0
| 0.214286
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
99dc7ee1d93ec3ee363347a8ca1f50b6c77f6159
| 15,240
|
py
|
Python
|
iotfunctions/ui.py
|
sedgewickmm18/functions
|
69d04a67b122601c4f207ded8e872d31b2ddafc8
|
[
"Apache-2.0"
] | null | null | null |
iotfunctions/ui.py
|
sedgewickmm18/functions
|
69d04a67b122601c4f207ded8e872d31b2ddafc8
|
[
"Apache-2.0"
] | null | null | null |
iotfunctions/ui.py
|
sedgewickmm18/functions
|
69d04a67b122601c4f207ded8e872d31b2ddafc8
|
[
"Apache-2.0"
] | null | null | null |
# *****************************************************************************
# © Copyright IBM Corp. 2018. All Rights Reserved.
#
# This program and the accompanying materials
# are made available under the terms of the Apache V2.0
# which accompanies this distribution, and is available at
# http://www.apache.org/licenses/LICENSE-2.0
#
# *****************************************************************************
import logging
import datetime as dt
logger = logging.getLogger(__name__)
class BaseUIControl(object):
def convert_datatype(self,from_datatype):
conversions = {bool: 'BOOLEAN',
str: 'LITERAL',
float: 'NUMBER',
int: 'NUMBER',
dict: 'JSON',
dt.datetime: 'TIMESTAMP',
None: None
}
try:
return conversions[from_datatype]
except KeyError:
msg = 'couldnt convert type %s ' %from_datatype
raise TypeError(msg)
class UIFunctionOutSingle(BaseUIControl):
'''
Single output item
Parameters
-----------
name : str
Name of function argument
datatype: python datatype object
Used to validate UI input. e.g. str, float, dt.datetime, bool
description: str
Help text to display in UI
tags: list of strs
Optional tags, e.g. ['DIMENSION', 'EVENT', 'ALERT']
'''
def __init__(self,name, datatype=None, description=None, tags = None):
self.name = name
self.datatype = datatype
if description is None:
description = 'Choose an item name for the function output'
self.description = description
if tags is None:
tags = []
self.tags = tags
def to_metadata(self):
meta = {
'name' : self.name,
'dataType' : self.convert_datatype(self.datatype),
'description' : self.description,
'tags' : self.tags
}
return meta
class UIFunctionOutMulti(BaseUIControl):
'''
Array of multiple outputs
Parameters
-----------
name : str
Name of function argument
cardinality_from: str
Name of input argument that defines the number of items to expect from this array output. Specify an array input.
is_datatype_derived: bool
Specify true when the output datatypes are the same as the datatypes of the input array that drives this output array.
datatype: python datatype object
Used to validate UI input. e.g. str, float, dt.datetime, bool
description: str
Help text to display in UI
tags: list of strs
Optional tags, e.g. ['DIMENSION', 'EVENT', 'ALERT']
'''
def __init__(self,name, cardinality_from,
is_datatype_derived = False,
datatype = None,
description=None,
tags = None,
output_item = None):
self.name = name
self.cardinality_from = cardinality_from
self.is_datatype_derived = is_datatype_derived
if description is None:
description = 'Provide names and datatypes for output items'
self.description = description
if datatype is not None:
datatype = self.convert_datatype(datatype)
self.datatype = datatype
if tags is None:
tags = []
self.tags = tags
def to_metadata(self):
if not self.datatype is None:
datatype = [self.datatype]
else:
datatype= None
meta = {
'name' : self.name,
'cardinalityFrom' : self.cardinality_from,
'dataTypeForArray' : datatype,
'description' : self.description,
'tags' : self.tags,
'jsonSchema' : {
"$schema" : "http://json-schema.org/draft-07/schema#",
"type" : "array",
"items" : {"type": "string"}
}
}
if self.is_datatype_derived:
meta['dataTypeFrom'] = self.cardinality_from
return meta
class UISingleItem(BaseUIControl):
'''
Choose a single item as a function argument
Parameters
-----------
name : str
Name of function argument
datatype: python datatype object
Used to validate UI input. e.g. str, float, dt.datetime, bool
required: bool
Specify True when this argument is mandatory
description: str
Help text to display in UI
tags: list of strs
Optional tags, e.g. ['DIMENSION', 'EVENT', 'ALERT']
'''
def __init__(self,name, datatype=None, description=None, required = True,
tags = None):
self.name = name
self.datatype = datatype
self.required = required
if description is None:
description = 'Choose one or more data item to use as a function input'
self.description = description
if tags is None:
tags = []
self.tags = tags
def to_metadata(self):
if self.datatype is None:
datatype = None
else:
datatype = [self.convert_datatype(self.datatype)]
meta = {
'name' : self.name,
'type' : 'DATA_ITEM' ,
'dataType' : datatype,
'required' : self.required,
'description' : self.description,
'tags' : self.tags
}
return meta
class UIMultiItem(BaseUIControl):
'''
Multi-select list of data items
Parameters
-----------
name : str
Name of function argument
datatype: python datatype object
Used to validate UI input. e.g. str, float, dt.datetime, bool
required: bool
Specify True when this argument is mandatory
min_items: int
The minimum number of items that must be selected
max_items: int
The maximum number of items that can be selected
description: str
Help text to display in UI
tags: list of strs
Optional tags, e.g. ['DIMENSION', 'EVENT', 'ALERT']
'''
def __init__(self,name, datatype=None, description=None, required = True,
min_items = None, max_items = None, tags = None,
output_item = None,
is_output_datatype_derived = False,
output_datatype = None
):
self.name = name
self.datatype = datatype
self.required = required
if description is None:
description = 'Choose one or more data item to use as a function input'
self.description = description
if min_items is None:
if self.required:
min_items = 1
else:
min_items = 0
self.min_items = min_items
self.max_items = max_items
if tags is None:
tags = []
self.tags = tags
#the following metadata is optional
#used to create an array output for this input
self.output_item = output_item
self.is_output_datatype_derived = is_output_datatype_derived
self.output_datatype = output_datatype
def to_metadata(self):
if self.datatype is None:
datatype = None
else:
datatype = [self.convert_datatype(self.datatype)]
meta = {
'name' : self.name,
'type' : 'DATA_ITEM' ,
'dataType' : 'ARRAY',
'dataTypeForArray' : datatype,
'required' : self.required,
'description' : self.description,
'tags' : self.tags,
'jsonSchema' : {
"$schema" : "http://json-schema.org/draft-07/schema#",
"type" : "array",
"minItems" : self.min_items,
"maxItems" : self.max_items,
"items" : {"type": "string"}
}
}
return meta
def to_output_metadata(self):
if self.output_item is not None:
if not self.output_datatype is None:
datatype = [self.convert_datatype(self.output_datatype)]
else:
datatype= None
meta = {
'name' : self.output_item,
'cardinalityFrom' : self.name,
'dataTypeForArray' : datatype,
'description' : self.description,
'tags' : self.tags,
'jsonSchema' : {
"$schema" : "http://json-schema.org/draft-07/schema#",
"type" : "array",
"items" : {"type": "string"}
}
}
if self.is_output_datatype_derived:
meta['dataTypeFrom'] = self.name
return meta
else:
return None
class UIMulti(BaseUIControl):
'''
Multi-select list of constants
Parameters
-----------
name : str
Name of function argument
datatype: python datatype object
Used to validate UI input. e.g. str, float, dt.datetime, bool
required: bool
Specify True when this argument is mandatory
min_items: int
The minimum number of values that must be entered/selected
max_items: int
The maximum number of values that can be entered/selected
description: str
Help text to display in UI
tags: list of strs
Optional tags, e.g. ['DIMENSION', 'EVENT', 'ALERT']
values: list
Values to display in UI picklist
'''
def __init__(self,name, datatype, description=None, required = True,
min_items = None, max_items = None, tags = None, values = None,
output_item = None,
is_output_datatype_derived = False,
output_datatype = None):
self.name = name
self.datatype = datatype
self.required = required
if description is None:
description = 'Enter a list of comma separated values'
self.description = description
if min_items is None:
if self.required:
min_items = 1
else:
min_items = 0
self.min_items = min_items
self.max_items = max_items
if tags is None:
tags = []
self.tags = tags
self.values = values
#the following metadata is optional
#used to create an array output for this input
self.output_item = output_item
self.is_output_datatype_derived = is_output_datatype_derived
self.output_datatype = output_datatype
def to_metadata(self):
if self.datatype is None:
msg = 'Datatype is required for multi constant array input %s' %self.name
raise ValueError(msg)
else:
datatype = [self.convert_datatype(self.datatype)]
meta = {
'name' : self.name,
'type' : 'CONSTANT' ,
'dataType' : 'ARRAY',
'dataTypeForArray' : datatype,
'required' : self.required,
'description' : self.description,
'tags' : self.tags,
'values' : self.values,
'jsonSchema' : {
"$schema" : "http://json-schema.org/draft-07/schema#",
"type" : "array",
"minItems" : self.min_items,
"maxItems" : self.max_items,
"items" : {"type": "string"}
}
}
return meta
def to_output_metadata(self):
if self.output_item is not None:
if self.output_datatype is not None:
datatype = [self.convert_datatype(self.output_datatype)]
else:
datatype= None
meta = {
'name' : self.output_item,
'cardinalityFrom' : self.name,
'dataTypeForArray' : datatype,
'description' : self.description,
'tags' : self.tags,
'jsonSchema' : {
"$schema" : "http://json-schema.org/draft-07/schema#",
"type" : "array",
"items" : {"type": "string"}
}
}
if self.is_output_datatype_derived:
meta['dataTypeFrom'] = self.name
return meta
else:
return None
class UISingle(BaseUIControl):
'''
Single valued constant
Parameters
-----------
name : str
Name of function argument
datatype: python datatype object
Used to validate UI input. e.g. str, float, dt.datetime, bool
required: bool
Specify True when this argument is mandatory
description: str
Help text to display in UI
tags: list of strs
Optional tags, e.g. ['DIMENSION', 'EVENT', 'ALERT']
values: list
Values to display in UI picklist
'''
def __init__(self,name, datatype=None, description=None, tags = None,
required = True, values = None, default = None):
self.name = name
self.datatype = datatype
if description is None:
description = 'Enter a constant value'
self.description = description
if tags is None:
tags = []
self.tags = tags
self.required = required
self.values = values
self.default = default
def to_metadata(self):
meta = {
'name' : self.name,
'type' : 'CONSTANT',
'dataType' : self.convert_datatype(self.datatype),
'description' : self.description,
'tags' : self.tags,
'required' : self.required,
'values' : self.values
}
if self.default is not None:
if isinstance(self.default,dict):
meta['value'] = self.default
else:
meta['value'] = {'value':self.default}
return meta
| 33.791574
| 126
| 0.498163
| 1,456
| 15,240
| 5.119505
| 0.120879
| 0.024685
| 0.022538
| 0.013952
| 0.766702
| 0.74242
| 0.735042
| 0.720687
| 0.696002
| 0.690904
| 0
| 0.002452
| 0.41122
| 15,240
| 451
| 127
| 33.791574
| 0.828151
| 0.224344
| 0
| 0.716364
| 0
| 0
| 0.11251
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.054545
| false
| 0
| 0.007273
| 0
| 0.127273
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
99ea14d5a26acfce667a74609393041dacbcf24b
| 46
|
py
|
Python
|
crawlib2/tests/dummy_site/music/controller/__init__.py
|
MacHu-GWU/crawlib2-project
|
618d72522d5b36d40607b53b7de7623976460712
|
[
"MIT"
] | 1
|
2020-06-19T09:45:20.000Z
|
2020-06-19T09:45:20.000Z
|
crawlib2/tests/dummy_site/music/controller/__init__.py
|
MacHu-GWU/crawlib2-project
|
618d72522d5b36d40607b53b7de7623976460712
|
[
"MIT"
] | 1
|
2019-12-27T18:41:21.000Z
|
2019-12-27T18:41:21.000Z
|
crawlib2/tests/dummy_site/music/controller/__init__.py
|
MacHu-GWU/crawlib2-project
|
618d72522d5b36d40607b53b7de7623976460712
|
[
"MIT"
] | 1
|
2021-04-14T22:56:34.000Z
|
2021-04-14T22:56:34.000Z
|
# -*- coding: utf-8 -*-
from .view import bp
| 11.5
| 23
| 0.565217
| 7
| 46
| 3.714286
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.027778
| 0.217391
| 46
| 3
| 24
| 15.333333
| 0.694444
| 0.456522
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
99fcfe3053da0dac86ac5e602bc9ca4a2b36e21a
| 60
|
py
|
Python
|
tests.py
|
gadse/mite-reader
|
a4ee10e2029708c05c104499c0e85049a0e7b10d
|
[
"MIT"
] | null | null | null |
tests.py
|
gadse/mite-reader
|
a4ee10e2029708c05c104499c0e85049a0e7b10d
|
[
"MIT"
] | null | null | null |
tests.py
|
gadse/mite-reader
|
a4ee10e2029708c05c104499c0e85049a0e7b10d
|
[
"MIT"
] | null | null | null |
# TODO: Is there an example mite account we can access here?
| 60
| 60
| 0.766667
| 11
| 60
| 4.181818
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.183333
| 60
| 1
| 60
| 60
| 0.938776
| 0.966667
| 0
| null | 0
| null | 0
| 0
| null | 0
| 0
| 1
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
413e91172426529e257639e2d367bfa5d9c39252
| 293
|
py
|
Python
|
src/songbook/console/_remove.py
|
kipyin/-
|
5d372c7d987e6a1da380197c1b990def0d240298
|
[
"MIT"
] | 1
|
2021-01-03T10:40:28.000Z
|
2021-01-03T10:40:28.000Z
|
src/songbook/console/_remove.py
|
kipyin/-
|
5d372c7d987e6a1da380197c1b990def0d240298
|
[
"MIT"
] | null | null | null |
src/songbook/console/_remove.py
|
kipyin/-
|
5d372c7d987e6a1da380197c1b990def0d240298
|
[
"MIT"
] | 1
|
2021-01-03T10:40:29.000Z
|
2021-01-03T10:40:29.000Z
|
import click
@click.group()
def remove():
pass
@remove.command("song")
def _remove_song():
pass
@remove.command("arrangement")
def _remove_arrangement():
pass
@remove.command("worship")
def _remove_worship():
pass
@remove.command("hymn")
def _remove_hymn():
pass
| 10.851852
| 30
| 0.675768
| 35
| 293
| 5.428571
| 0.314286
| 0.236842
| 0.357895
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.177474
| 293
| 26
| 31
| 11.269231
| 0.788382
| 0
| 0
| 0.3125
| 0
| 0
| 0.088737
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.3125
| true
| 0.3125
| 0.0625
| 0
| 0.375
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
4143d0c8dab45ffb0f2d7668cc74f652d1aa68ad
| 3,185
|
py
|
Python
|
droxi/drox/omcdbase/transc1/models.py
|
andydude/droxtools
|
d608ceb715908fb00398c0d28eee74286fef3750
|
[
"MIT"
] | null | null | null |
droxi/drox/omcdbase/transc1/models.py
|
andydude/droxtools
|
d608ceb715908fb00398c0d28eee74286fef3750
|
[
"MIT"
] | null | null | null |
droxi/drox/omcdbase/transc1/models.py
|
andydude/droxtools
|
d608ceb715908fb00398c0d28eee74286fef3750
|
[
"MIT"
] | null | null | null |
'''
Created on Mar 31, 2014
@author: ajr
'''
from ...models import Number
from ..models import OMSym
import math
# Inverse Trig
@OMSym.called("transc1", "arccos")
class ArcCos(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arccosh")
class ArcCosh(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arccot")
class ArcCot(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arccoth")
class ArcCoth(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arccsc")
class ArcCsc(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arccsch")
class ArcCsch(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arcsec")
class ArcSec(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arcsech")
class ArcSech(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arcsin")
class ArcSin(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arcsinh")
class ArcSinh(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arctan")
class ArcTan(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "arctanh")
class ArcTanh(OMSym):
def __call__(self, arg):
return None
# Forward Trig
@OMSym.called("transc1", "cos")
class Cos(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "cosh")
class Cosh(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "cot")
class Cot(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "coth")
class Coth(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "csc")
class Csc(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "csch")
class Csch(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "sec")
class Sec(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "sech")
class Sech(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "sin")
class Sin(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "sinh")
class Sinh(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "tan")
class Tan(OMSym):
def __call__(self, arg):
return None
@OMSym.called("transc1", "tanh")
class Tanh(OMSym):
def __call__(self, arg):
return None
# Basic
@OMSym.called("transc1", "exp")
class Exp(OMSym):
def __call__(self, arg):
cls = type(arg)
result = math.exp(arg.num)
return cls(result)
@OMSym.called("transc1", "ln")
class Ln(OMSym):
def __call__(self, arg):
cls = type(arg)
result = math.log(arg.num)
return cls(result)
@OMSym.called("transc1", "Log")
class Log(OMSym):
def __call__(self, base, arg):
cls = Number.result_type(base, arg)
result = math.log(arg.num, base.num)
return cls(result)
| 20.158228
| 44
| 0.629513
| 406
| 3,185
| 4.669951
| 0.142857
| 0.156646
| 0.256329
| 0.227848
| 0.671414
| 0.671414
| 0.658228
| 0.627637
| 0.586498
| 0.586498
| 0
| 0.013258
| 0.218524
| 3,185
| 157
| 45
| 20.286624
| 0.748493
| 0.021978
| 0
| 0.470085
| 0
| 0
| 0.102126
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.230769
| false
| 0
| 0.025641
| 0.205128
| 0.717949
| 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
| 1
| 1
| 0
|
0
| 5
|
4182225e976063680c2fe2b96ea88ba059cacec6
| 159
|
py
|
Python
|
openCV/OCR.py
|
untrobotics/IEEE-2019-R5
|
799bffc95b7be1c939d1ad1858b10faabb3cc842
|
[
"MIT"
] | null | null | null |
openCV/OCR.py
|
untrobotics/IEEE-2019-R5
|
799bffc95b7be1c939d1ad1858b10faabb3cc842
|
[
"MIT"
] | 6
|
2019-03-06T01:10:24.000Z
|
2020-06-17T05:04:43.000Z
|
openCV/OCR.py
|
untrobotics/IEEE-2019-R5
|
799bffc95b7be1c939d1ad1858b10faabb3cc842
|
[
"MIT"
] | 3
|
2019-03-01T05:11:39.000Z
|
2019-11-22T15:01:02.000Z
|
try:
from PIL import Image
except ImportError:
import Image
import pytesseract
print(pytesseract.image_to_string(Image.open('testocr.png')))
| 17.666667
| 61
| 0.72956
| 20
| 159
| 5.7
| 0.7
| 0.192982
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.188679
| 159
| 8
| 62
| 19.875
| 0.883721
| 0
| 0
| 0
| 0
| 0
| 0.06962
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.666667
| 0
| 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
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
41902a781a0d8c79f7b55ae174b5f138ba9c49dc
| 5,816
|
py
|
Python
|
pp/components/manhattan_font.py
|
smartalecH/gdsfactory
|
66dfbf740704f1a6155f4812a1d9483ccf5c116c
|
[
"MIT"
] | 16
|
2020-02-03T07:05:31.000Z
|
2021-12-29T18:40:09.000Z
|
pp/components/manhattan_font.py
|
smartalecH/gdsfactory
|
66dfbf740704f1a6155f4812a1d9483ccf5c116c
|
[
"MIT"
] | 2
|
2020-01-31T20:01:40.000Z
|
2020-09-26T17:50:55.000Z
|
pp/components/manhattan_font.py
|
smartalecH/gdsfactory
|
66dfbf740704f1a6155f4812a1d9483ccf5c116c
|
[
"MIT"
] | 7
|
2020-02-09T23:16:18.000Z
|
2020-10-30T03:12:04.000Z
|
import numpy as np
from omegaconf.listconfig import ListConfig
from pp.component import Component
from typing import List, Tuple
import pp
from pp.layers import LAYER
from pp.name import clean_name
"""
A pixel based font, guaranteed to be manhattan, without accute angles
"""
def manhattan_text(
text: str = "abcd",
size: float = 10,
position: Tuple[int, int] = (0, 0),
justify: str = "left",
layer: ListConfig = LAYER.M1,
layers_cladding: List[ListConfig] = [],
cladding_offset: int = 3,
) -> Component:
"""
.. plot::
:include-source:
import pp
c = pp.c.text(text="abcd", size=10, position=(0, 0), justify="left", layer=1)
pp.plotgds(c)
"""
pixel_size = size
xoffset = position[0]
yoffset = position[1]
t = pp.Component(
name=clean_name(text) + "_{}_{}".format(int(position[0]), int(position[1]))
)
for i, line in enumerate(text.split("\n")):
component = pp.Component(name=t.name + "{}".format(i))
for c in line:
try:
if c not in CHARAC_MAP:
c = c.upper()
pixels = CHARAC_MAP[c]
except:
print(
"character {} could not be written (probably not part of dictionnary)".format(
c
)
)
continue
_c = component.add_ref(
pixel_array(pixels=pixels, pixel_size=pixel_size, layer=layer)
)
_c.move((xoffset, yoffset))
component.absorb(_c)
xoffset += pixel_size * 6
t.add_ref(component)
yoffset -= pixel_size * 6
xoffset = position[0]
justify = justify.lower()
for ref in t.references:
if justify == "left":
pass
if justify == "right":
ref.xmax = position[0]
if justify == "center":
ref.move(origin=ref.center, destination=position, axis="x")
points = [
[t.xmin - cladding_offset / 2, t.ymin - cladding_offset],
[t.xmax + cladding_offset / 2, t.ymin - cladding_offset],
[t.xmax + cladding_offset / 2, t.ymax + cladding_offset],
[t.xmin - cladding_offset / 2, t.ymax + cladding_offset],
]
for layer in layers_cladding:
t.add_polygon(points, layer=layer)
return t
@pp.autoname
def pixel_array(
pixels: str = """
XXX
X X
XXXXX
X X
X X
""",
pixel_size: float = 10.0,
layer: ListConfig = LAYER.M1,
) -> Component:
component = pp.Component()
lines = [line for line in pixels.split("\n") if len(line) > 0]
lines.reverse()
j = 0
i = 0
i_max = 0
a = pixel_size
for line in lines:
i = 0
for c in line:
if c in ["X", "1"]:
p0 = np.array([i * a, j * a])
pixel = [p0 + p for p in [(0, 0), (a, 0), (a, a), (0, a)]]
component.add_polygon(pixel, layer=layer)
i += 1
i_max = max(i_max, i)
j += 1
return component
FONT = """\
A
1 1 1 1 1
1 0 0 0 1
1 1 1 0 1
1 0 0 0 1
1 0 0 0 1
B
1 1 1 1 1
1 0 0 0 1
1 0 1 1 1
1 0 0 0 1
1 0 1 1 1
C
1 1 1 1 1
1 0 0 0 1
1 0 0 0 0
1 0 0 0 1
1 1 1 1 1
D
1 1 1 1 1
1 0 0 0 1
1 0 0 0 1
1 0 0 0 1
1 0 1 1 1
E
1 1 1 1 1
1 0 0 0 0
1 0 1 1 0
1 0 0 0 0
1 0 1 1 1
F
1 1 1 1 1
1 0 0 0 0
1 0 1 1 0
1 0 0 0 0
1 0 0 0 0
G
1 1 1 1 1
1 0 0 0 0
1 0 1 1 1
1 0 0 0 1
1 1 1 1 1
H
1 0 0 0 1
1 0 0 0 1
1 1 1 1 1
1 0 0 0 1
1 0 0 0 1
I
1 1 1 1 1
0 0 1 0 0
0 0 1 0 0
0 0 1 0 0
1 1 1 1 1
J
0 0 0 0 1
0 0 0 0 1
0 0 0 0 1
1 0 0 0 1
1 1 1 1 1
K
1 0 0 0 1
1 0 0 1 1
1 1 1 1 0
1 0 0 1 1
1 0 0 0 1
L
1 0 0 0 0
1 0 0 0 0
1 0 0 0 0
1 0 0 0 0
1 1 1 1 1
M
1 1 0 1 1
1 1 1 1 1
1 0 1 0 1
1 0 0 0 1
1 0 0 0 1
N
1 1 1 0 1
1 0 1 0 1
1 0 1 1 1
1 0 0 1 1
1 0 0 0 1
O
1 1 1 1 1
1 0 0 0 1
1 0 0 0 1
1 0 0 0 1
1 1 0 1 1
P
1 1 1 1 1
1 0 0 0 1
1 0 1 1 1
1 0 0 0 0
1 0 0 0 0
Q
1 1 1 1 0
1 0 0 1 0
1 0 0 1 0
1 0 0 1 0
1 1 1 1 1
R
1 1 1 1 0
1 0 0 1 0
1 0 1 1 1
1 0 0 0 1
1 0 0 0 1
S
1 1 1 1 1
1 1 0 0 0
0 1 1 1 0
0 0 0 1 1
1 1 1 1 1
T
1 1 1 1 1
0 0 1 0 0
0 0 1 0 0
0 0 1 0 0
0 0 1 0 0
U
1 0 0 0 1
1 0 0 0 1
1 0 0 0 1
1 0 0 0 1
1 1 1 1 1
V
1 0 0 0 1
1 0 0 0 1
1 0 0 0 1
0 1 0 1 0
0 0 1 0 0
W
1 0 0 0 1
1 0 0 0 1
1 0 1 0 1
1 1 1 1 1
1 1 0 1 1
X
1 1 0 1 1
1 1 1 1 1
0 1 1 1 0
1 1 1 1 1
1 1 0 1 1
Y
1 0 0 0 1
1 0 0 0 1
1 1 1 1 1
0 0 1 0 0
0 0 1 0 0
Z
1 1 1 1 1
0 0 0 1 1
0 0 1 1 0
0 1 1 0 0
1 1 1 1 1
1
0 1 1 0 0
0 0 1 0 0
0 0 1 0 0
0 0 1 0 0
0 1 1 1 0
2
1 1 1 1 1
0 0 0 1 1
1 1 1 1 1
1 1 0 0 0
1 1 1 1 1
3
1 1 1 1 1
0 0 0 1 1
1 1 1 1 1
0 0 0 1 1
1 1 1 1 1
4
1 0 0 1 1
1 0 0 1 1
1 1 1 1 1
0 0 0 1 1
0 0 0 1 1
5
1 1 1 1 1
1 1 0 0 0
1 1 1 1 1
0 0 0 1 1
1 1 1 1 1
6
1 1 1 1 1
1 0 0 0 0
1 1 1 1 1
1 1 0 1 1
1 1 1 1 1
7
1 1 1 1 1
0 0 0 1 1
0 0 0 1 1
0 0 0 1 1
0 0 0 1 1
8
1 1 1 1 1
1 1 0 1 1
1 1 1 1 1
1 1 0 1 1
1 1 1 1 1
9
1 1 1 1 1
1 1 0 1 1
1 1 1 1 1
0 0 0 1 1
0 0 0 1 1
0
0 1 1 1 1
0 1 0 0 1
0 1 0 0 1
0 1 0 0 1
0 1 1 1 1
+
0 0 0 0 0
0 0 1 0 0
0 1 1 1 0
0 0 1 0 0
0 0 0 0 0
-
0 0 0 0 0
0 0 0 0 0
0 1 1 1 0
0 0 0 0 0
0 0 0 0 0
_
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 1 1 1 0
.
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 1 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
0 0 0 0 0
"""
CHARAC_MAP = {}
def load_font() -> None:
lines = FONT.split("\n")
global CHARAC_MAP
while lines:
line = lines.pop(0)
if not line:
break
charac = line[0]
pixels = ""
for i in range(5):
pixels += lines.pop(0).replace("\t", "").replace(" ", "") + "\n"
CHARAC_MAP[charac] = pixels
load_font()
if __name__ == "__main__":
c = manhattan_text(
text="The mask is nearly done. only 12345 drc errors remaining",
layers_cladding=[(33, 44)],
)
pp.show(c)
| 14.686869
| 98
| 0.51685
| 1,524
| 5,816
| 1.937664
| 0.101706
| 0.24382
| 0.244836
| 0.22892
| 0.40061
| 0.40061
| 0.397223
| 0.374534
| 0.369116
| 0.369116
| 0
| 0.312482
| 0.400791
| 5,816
| 395
| 99
| 14.724051
| 0.534864
| 0.023728
| 0
| 0.601671
| 0
| 0
| 0.424645
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.008357
| false
| 0.002786
| 0.019499
| 0
| 0.033426
| 0.002786
| 0
| 0
| 1
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 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
| 5
|
41b18c16b10395f112ebbec8aed3cb28a64d70bf
| 50,977
|
py
|
Python
|
mmhelper/tests/test_detection.py
|
jmetz/momanalysis
|
8d71490c99127568b184784890258e9a6ef876ef
|
[
"MIT"
] | null | null | null |
mmhelper/tests/test_detection.py
|
jmetz/momanalysis
|
8d71490c99127568b184784890258e9a6ef876ef
|
[
"MIT"
] | 3
|
2019-07-25T13:43:15.000Z
|
2019-11-04T12:39:22.000Z
|
mmhelper/tests/test_detection.py
|
jmetz/momanalysis
|
8d71490c99127568b184784890258e9a6ef876ef
|
[
"MIT"
] | 1
|
2021-03-28T03:00:21.000Z
|
2021-03-28T03:00:21.000Z
|
# -*- coding: utf-8 -*-
"""
Created on Fri Nov 1 11:35 2016
@author: as624
"""
import unittest
from mmhelper.detection.bacteria import detect_bacteria_in_all_wells as detbac
from mmhelper.comparison import match_labels, determine_precision_recall
import mmhelper.detection.bacteria as mdet
import mmhelper.detection.wells as mdet_wells
import numpy as np
import skimage.measure as skmeas
class TestSubtractBackground(unittest.TestCase):
"""
class for testing background subtraction
"""
def setUp(self):
self.sz0 = (100, 100)
self.ground_truth = np.zeros(self.sz0)
self.ground_truth_level = 400
# Add some objects
self.ground_truth[10:20, 50:60] = self.ground_truth_level
# Noisy background
self.bg_std = 10
self.bg_offset = 100
self.bg_grad_max = 100
self.bkg = self.bg_std * np.random.randn(*self.sz0) + self.bg_offset
# Add a constant gradient
x0_ = np.meshgrid(np.arange(self.sz0[0]), np.arange(self.sz0[1]))[0]
self.bkg += self.bg_grad_max * x0_ / x0_.max()
self.image = {0: self.ground_truth + self.bkg}
def test_subtract_background(self):
"""
Tests background subtraction
"""
removed = mdet_wells.remove_background(self.image, light_background=False)
# For our current workflow, the background-removed images are inverted
removed = -removed[0]
#import matplotlib.pyplot as plt
# plt.imshow(removed)
# plt.colorbar()
# plt.show()
# Make sure the background is all relatively low now
# NOTE: As background is subtracted, need to go double above reasonable
# statisitcally realy unlikely values of ~4 sigma from normal
# distribution
self.assertTrue(
np.all(removed[self.ground_truth == 0] < 8 * self.bg_std))
# Make sure the foreground is about right
self.assertTrue(
np.all(
np.abs(
removed[self.ground_truth > 0] - self.ground_truth_level) < 8
* self.bg_std))
class DetectBacteria(unittest.TestCase):
"""
Unittests for detecting bacteria
"""
def setUp(self):
self.lbl1 = {1: np.array([[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 211, 1, 1, 1, 1, 1, 1, 1],
[1, 211, 211, 211, 1, 1, 1, 1, 1, 1],
[1, 211, 211, 211, 1, 1, 1, 1, 1, 1],
[1, 1, 211, 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],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])}
self.lbl2 = {2: np.array([[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, 1, 1, 1],
[1, 1, 1, 1, 1, 211, 211, 1, 1, 1],
[1, 1, 1, 1, 211, 211, 211, 211, 1, 1],
[1, 1, 1, 1, 211, 211, 211, 211, 1, 1],
[1, 1, 1, 1, 211, 211, 211, 211, 1, 1],
[1, 1, 1, 1, 1, 211, 211, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]])}
self.lbl_twobac1 = {3: np.array(
[[1, 1, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 185, 185, 1, 1, 1, 1, 1],
[1, 1, 185, 185, 185, 185, 1, 1, 1, 1],
[1, 1, 185, 185, 185, 185, 1, 1, 1, 1],
[1, 1, 185, 185, 185, 185, 1, 1, 1, 1],
[1, 1, 1, 185, 185, 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, 1, 1, 1, 1, 1, 1, 1, 1],
[1, 1, 1, 215, 215, 1, 1, 1, 1, 1],
[1, 1, 215, 215, 215, 215, 1, 1, 1, 1],
[1, 1, 215, 215, 215, 215, 1, 1, 1, 1],
[1, 1, 215, 215, 215, 215, 1, 1, 1, 1],
[1, 1, 1, 215, 215, 1, 1, 1, 1, 1],
[1, 1, 1, 1, 1, 1, 1, 1, 1, 1]]
)}
# self.lbl2 = np.array([[0,0,0,0,0,0,0,0,0,0],
# [0,0,0,0,0,0,0,0,0,0],
# [0,1,1,1,0,0,0,0,0,0],
# [0,1,1,1,0,0,0,0,0,0],
# [0,1,1,1,0,0,0,0,0,0],
# [0,1,1,1,0,0,0,0,0,0],
# [0,0,0,0,0,0,0,0,0,0],
# [0,0,0,0,0,0,0,0,0,0],
# [0,0,0,0,0,0,0,0,0,0]])
# Seems to now remove a border....
self.res1 = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[0, 1, 1, 1, 0, 0, 0, 0, 0, 0],
[0, 0, 1, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
self.res2 = np.array([[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 0, 0, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
self.res_two1 = np.array(
[[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 2, 2, 0, 0, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 0, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 0, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 2, 2, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]
)
self.wellnum1 = [1]
self.wellnum2 = [2]
self.wellnum3 = [3]
self.label_string = {1: '1'}
self.label_string2 = {1: '1', 2: '2'}
def test_detect_small_bacteria1(self):
"""
Test the detection of small bacteria
"""
detected = detbac(self.lbl1,
# maximum area (in pixels) of an object to be
# considered a bacteria
maxsize=1500,
# maximum area (in pixels) of an object to be
# considered a bacteria
minsize=0,
# width (in pixels) at which something is definitely
# a bacteria (can override relativewidth)
absolwidth=0.1,
# ignores anything labeled this distance from the
# bottom of the well (prevents channel border being
# labelled)
)
for k in detected.values():
man_ids, det_ids, man_id_dict, det_id_dict = match_labels(
self.res1, k)
precision_scores, recall_scores = determine_precision_recall(
self.res1, k, man_ids, det_ids, man_id_dict, det_id_dict)
assert np.all(np.array(precision_scores) >= 0.75)
assert np.all(np.array(recall_scores) >= 0.75)
def test_detect_small_bacteria2(self):
"""
A test for detecting small bacteria
"""
detected = detbac(self.lbl2,
# maximum area (in pixels) of an object to be
# considered a bacteria
maxsize=1500,
# maximum area (in pixels) of an object to be
# considered a bacteria
minsize=0,
# width (in pixels) at which something is definitely
# a bacteria (can override relativewidth)
absolwidth=0.1,
)
for k in detected.values():
man_ids, det_ids, man_id_dict, det_id_dict = match_labels(
self.res2, k)
precision_scores, recall_scores = determine_precision_recall(
self.res2, k, man_ids, det_ids, man_id_dict, det_id_dict)
assert np.all(np.array(precision_scores) >= 0.75)
assert np.all(np.array(recall_scores) >= 0.75)
def test_detect_two_bacteria1(self):
"""
Test two detect two bacteria
"""
detected = detbac(self.lbl_twobac1,
# maximum area (in pixels) of an object to be
# considered a bacteria
maxsize=1500,
# maximum area (in pixels) of an object to be
# considered a bacteria
minsize=0,
# width (in pixels) at which something is definitely
# a bacteria (can override relativewidth)
absolwidth=0.1,
)
for k in detected.values():
man_ids, det_ids, man_id_dict, det_id_dict = match_labels(
self.res_two1, k)
precision_scores, recall_scores = determine_precision_recall(
self.res_two1, k, man_ids, det_ids, man_id_dict, det_id_dict)
assert np.all(np.array(precision_scores) >= 0.75)
assert np.all(np.array(recall_scores) >= 0.75)
class TestSplitBacteria(unittest.TestCase):
"""
Class for testing the splitting of bacteria
"""
def setUp(self):
self.wells = {1:
np.array([[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])}
self.wells2 = {2:
np.array([[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
}
self.wells_int = {1:
np.array([[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])}
self.wells2_int = {2:
np.array([[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 400, 400, 400, 400, 400, 400, 0, 0],
[0, 0, 0, 400, 400, 400, 400, 0, 0, 0],
[0, 0, 0, 0, 400, 400, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
}
self.out_wells = [np.array([[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]]), ]
self.out_wells2 = [np.array([[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 1, 1, 1, 1, 1, 1, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 1, 1, 1, 1, 0, 0, 0],
[0, 0, 0, 0, 1, 1, 0, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 2, 2, 2, 2, 2, 2, 0, 0],
[0, 0, 0, 2, 2, 2, 2, 0, 0, 0],
[0, 0, 0, 0, 2, 2, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 3, 3, 0, 0, 0, 0],
[0, 0, 0, 3, 3, 3, 3, 0, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 3, 3, 3, 3, 3, 3, 0, 0],
[0, 0, 0, 3, 3, 3, 3, 0, 0, 0],
[0, 0, 0, 0, 3, 3, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0]])
]
self.out_string = {1: '1', 2: '2'}
self.out_string2 = {1: '1', 2: '2', 3: '3'}
self.wellnum1 = [1]
self.wellnum2 = [2]
def test_bacteria_no_split(self):
"""
Test bacteria that don't need splitting
"""
split = mdet.split_bacteria_in_all_wells(
self.wells,
self.wells_int,
min_skel_length=3,
)
newarrays1 = []
wellnums1 = []
for j, k in split.items():
wellnums1.append(j)
newarrays1.append(k)
np.testing.assert_array_equal(newarrays1, self.out_wells)
self.assertEqual(self.wellnum1, wellnums1)
def test_bacteria_split(self):
"""
Test bacteria that need splitting
"""
split = mdet.split_bacteria_in_all_wells(
self.wells2,
self.wells2_int,
min_skel_length=4,
)
newarrays2 = []
wellnums2 = []
for j, k in split.items():
wellnums2.append(j)
newarrays2.append(k)
np.testing.assert_array_equal(newarrays2, self.out_wells2)
self.assertEqual(self.wellnum2, wellnums2)
class TestExtractWells(unittest.TestCase):
"""
Class for testing the extraction of well profiles
"""
def setUp(self):
# Create test data for the extraction
# Doesn't really matter what the image is
self.image = np.random.rand(10, 10)
self.channel = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 1, 1, 1, 1, 1, 1, 1, 1, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype=bool)
self.wells = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 2, 0, 0, 0, 0, 0, ],
[0, 0, 1, 0, 2, 0, 0, 0, 3, 0, ],
[0, 0, 1, 0, 2, 0, 0, 0, 3, 0, ],
[0, 0, 1, 0, 2, 0, 0, 0, 3, 0, ],
[0, 0, 1, 0, 0, 0, 0, 0, 3, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype='uint16')
self.wellstrue = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[1, 0, 2, 0, 3, 0, 4, 0, 5, 0, ],
[1, 0, 2, 0, 3, 0, 4, 0, 5, 0, ],
[1, 0, 2, 0, 3, 0, 4, 0, 5, 0, ],
[1, 0, 2, 0, 3, 0, 4, 0, 5, 0, ],
[1, 0, 2, 0, 3, 0, 4, 0, 5, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype='uint16')
self.wellwidth = 1
self.coords = {
1: ([6, 5, 4, 3, 2], [0, 0, 0, 0, 0]),
2: ([6, 5, 4, 3, 2], [2, 2, 2, 2, 2]),
3: ([6, 5, 4, 3, 2], [4, 4, 4, 4, 4]),
4: ([6, 5, 4, 3, 2], [6, 6, 6, 6, 6]),
5: ([6, 5, 4, 3, 2], [8, 8, 8, 8, 8]),
}
self.wellimages = {l: self.image[c][:, None]
for l, c in self.coords.items()
}
def test_extract_well_profiles(self):
"""
Tests extract_well_profiles
"""
images, wellimage, coords = mdet_wells.extract_well_profiles(
self.image,
self.wells,
wellwidth=self.wellwidth,
min_well_sep_factor=0.5,
)
self.assertEqual(len(images), len(self.wellimages))
for well1, well2 in zip(images, self.wellimages):
np.testing.assert_array_equal(well1, well2)
#core.assert_array_almost_equal(w1, w2)
np.testing.assert_array_equal(wellimage, self.wellstrue)
self.assertEqual(coords, self.coords)
class TestDetectWells(unittest.TestCase):
"""
Class for testing well detection
"""
def setUp(self):
# Create test data for the detection
self.image = 10 + np.random.randn(30, 30)
self.lbl = np.zeros((30, 30), dtype=int)
self.lbl[6: 9, 6:24] = 1
self.lbl[16: 19, 6:24] = 2
self.image[5:10, 5:25] -= 20
self.image[6: 9, 6:24] += 40
self.image[15:20, 5:25] -= 20
self.image[16: 19, 6:24] += 40
self.scale_range = [1.0, 3.0]
self.maxd = 40
self.mind = 3
self.maxperp = 10
self.minwidth = 0
self.min_outline_area = 0
def test_detect_initial_well_masks(self):
"""
Tests the detect_initial_well_masks function
"""
lblgood = mdet_wells.detect_initial_well_masks(
self.image,
scale_range=self.scale_range,
maxd=self.maxd,
mind=self.mind,
maxperp=self.maxperp,
min_outline_area=self.min_outline_area,
merge_length=0,
debug="",
)[0]
man_ids, det_ids, man_id_dict, det_id_dict = match_labels(
self.lbl, lblgood)
precision_scores, recall_scores = determine_precision_recall(
self.lbl, lblgood, man_ids, det_ids, man_id_dict, det_id_dict)
try:
assert np.all(np.array(precision_scores) > 0.9)
assert np.all(np.array(recall_scores) > 0.9)
#core.assert_array_equal(lblgood, self.lbl)
except BaseException:
import matplotlib.pyplot as plt
plt.figure()
plt.imshow(self.image, cmap='gray')
plt.title("Input image")
plt.savefig("test_detect_initial_well_masks_fail_input_image.jpg")
plt.figure()
plt.imshow(lblgood)
plt.title("Got labels")
plt.savefig("test_detect_initial_well_masks_fail_detected_labels.jpg")
plt.figure()
plt.imshow(self.lbl)
plt.title("Expected labels")
plt.savefig("test_detect_initial_well_masks_fail_expected_labels.jpg")
plt.close("all")
raise
class TestGetWellsAndUnitVectors(unittest.TestCase):
"""
Class for testing get_wells_and_unit_vectors
"""
def setUp(self):
wells_vertical = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 3, 0, 0, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype=int)
self.props_vertical = skmeas.regionprops(wells_vertical)
wells_horizontal = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 1, 1, 1, 1, 1, 1, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 2, 2, 2, 2, 2, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 3, 3, 3, 3, 3, 3, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 4, 4, 4, 4, 4, 4, 4, 4, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype=int)
self.props_horizontal = skmeas.regionprops(wells_horizontal)
wells_vertical_with_outlier = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 5, 5, 5, 5, 5, 5, 5, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 3, 0, 0, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 1, 0, 2, 0, 3, 0, 4, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype=int)
self.props_vertical_with_outlier = skmeas.regionprops(
wells_vertical_with_outlier)
def test_get_wells_vertical(self):
"""
Test for get_wells_and_unit_vectors on vertical wells
"""
coms, oris, uvec_para, uvec_perp = mdet_wells.get_wells_and_unit_vectors(
self.props_vertical)
# Unit vectors can be +-, so make sure by abs-ing
uvec_perp = np.abs(uvec_perp)
uvec_para = np.abs(uvec_para)
np.testing.assert_array_almost_equal(uvec_para, [0, 1])
np.testing.assert_array_almost_equal(uvec_perp, [1, 0])
def test_get_wells_horizontal(self):
"""
Test for get_wells_and_unit_vectors on horizontal wells
"""
coms, oris, uvec_para, uvec_perp = mdet_wells.get_wells_and_unit_vectors(
self.props_horizontal)
# Unit vectors can be +-, so make sure by abs-ing
uvec_perp = np.abs(uvec_perp)
uvec_para = np.abs(uvec_para)
np.testing.assert_array_almost_equal(uvec_para, [1, 0])
np.testing.assert_array_almost_equal(uvec_perp, [0, 1])
def test_get_wells_vertical_outlier(self):
"""
Now added in a horizontal well - if the simple outlier
detection doesn't filter it, the vectors should be off.
"""
coms, oris, uvec_para, uvec_perp = mdet_wells.get_wells_and_unit_vectors(
self.props_vertical_with_outlier)
# Unit vectors can be +-, so make sure by abs-ing
uvec_perp = np.abs(uvec_perp)
uvec_para = np.abs(uvec_para)
np.testing.assert_array_almost_equal(uvec_para, [0, 1])
np.testing.assert_array_almost_equal(uvec_perp, [1, 0])
# Check that one region got rejected
self.assertEqual(len(oris), len(self.props_vertical_with_outlier) - 1)
class TestGetWellSpacingAndSeparations(unittest.TestCase):
"""
Class for testing well_spacing_and_seps
"""
def setUp(self):
# Need, coms (centres of mass), the perpendicular unit vector
# to project the coms along, and wellwidth for filtering
# nearby coms
# Simple case - all uniformly distributed
self.coms_horizontal = [
[2, 5],
[4, 6],
[6, 4],
[8, 5.5],
[10, 5],
]
self.uvec_perp_horizontal = [1, 0]
self.coms_vertical = [
[5, 2],
[6, 4],
[4, 6],
[5.5, 8],
[5, 10],
]
self.uvec_perp_vertical = [0, 1]
self.coms_horizontal_with_gaps = [
[2, 5],
[4, 6],
[6, 4],
[8, 5.5],
[12, 5],
[14, 6.5],
[18, 4.5],
]
self.wellwidth = 0.5
def test_well_spacing_horizontal(self):
"""
Test for the function well_spacing_and_seps on horizontal wells
"""
normseps, posperp_sorted = mdet_wells.well_spacing_and_seps(
self.coms_horizontal,
self.uvec_perp_horizontal,
self.wellwidth,
)
self.assertListEqual(normseps.tolist(), [1, 1, 1, 1])
self.assertListEqual(posperp_sorted.tolist(), [2, 4, 6, 8, 10])
def test_well_spacing_vertical(self):
"""
Test for the function well_spacing_and_seps on vertical wells
"""
normseps, posperp_sorted = mdet_wells.well_spacing_and_seps(
self.coms_vertical,
self.uvec_perp_vertical,
self.wellwidth,
)
self.assertListEqual(normseps.tolist(), [1, 1, 1, 1])
self.assertListEqual(posperp_sorted.tolist(), [2, 4, 6, 8, 10])
def test_well_spacing_horiz_gaps(self):
"""
Test for the function well_spacing_and_seps on horizontal wells with gaps
"""
normseps, posperp_sorted = mdet_wells.well_spacing_and_seps(
self.coms_horizontal_with_gaps,
self.uvec_perp_horizontal,
self.wellwidth,
)
self.assertListEqual(normseps.tolist(), [1, 1, 1, 2, 1, 2])
self.assertListEqual(posperp_sorted.tolist(), [2, 4, 6, 8, 12, 14, 18])
class TestInterpolatePositionsAndExtractProfiles(unittest.TestCase):
"""
Class for testing well interpolation and extracting well profiles
"""
def setUp(self):
self.image = 10 + np.random.randn(10, 22)
self.image += 20 * np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 10, 10, 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, ],
[0, 0, 10, 10, 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, ],
[0, 0, 10, 10, 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, ],
[0, 0, 10, 10, 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, ],
[0, 0, 10, 10, 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, ],
[0, 0, 10, 10, 0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
])
# Means for the regions after extrapolation
self.image_means = {1: 210, 2: 30, 3: 50, 4: 70, 5: 90}
labels = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 4, 4, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 4, 4, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 4, 4, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 4, 4, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 4, 4, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 0, 0, 0, 0, 4, 4, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype=int)
self.finallabel = np.array([
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, 5, 5, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, 5, 5, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, 5, 5, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, 5, 5, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, 5, 5, 0, 0, ],
[0, 0, 1, 1, 0, 0, 2, 2, 0, 0, 3, 3, 0, 0, 4, 4, 0, 0, 5, 5, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
[0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, 0, ],
], dtype=int)
self.normseps = [1, 1, 2]
self.posperp_sorted = [2.5, 6.6, 10.5, 18.5]
self.propsgood = skmeas.regionprops(labels)
self.uvec_para = [0, 1]
self.uvec_perp = [1, 0]
self.wellwidth = 2
def test_interp_pos_extract_profs(self):
"""
Test for interpolate_pos_extract_profs
"""
images, wellimage, coords = mdet_wells.interpolate_pos_extract_profs(
np.array(
self.normseps), np.array(
self.posperp_sorted), self.propsgood, np.array(
self.uvec_para), np.array(
self.uvec_perp), self.wellwidth, self.image, )
# We can check the stats for the regions
for k, im0 in images.items():
# Have normally distributed noise with std 1,
# averaged over 12 values... deviation should
# be well less than 1... but just failed, set to delta=2
self.assertAlmostEqual(
im0.mean(),
self.image_means[k],
delta=2,
)
np.testing.assert_array_equal(wellimage, self.finallabel)
class TestRelabelBacteria(unittest.TestCase):
"""
class for testing bacteria relabelling
"""
def setUp(self):
self.old_labels = {
1 : np.array([[1,0,0,2],]),
2 : np.array([[1,0,0,2],]),
}
self.expected = {
1 : np.array([[1,0,0,2],]),
2 : np.array([[3,0,0,4],]),
}
def test_simple_relabel(self):
"""
Tests relabelling of bacteria
"""
result = mdet.relabel_bacteria(self.old_labels)
self.assertListEqual(list(self.expected.keys()), list(result.keys()))
for k, v in result.items():
np.testing.assert_array_equal(v, self.expected[k])
class TestFilterBacteria(unittest.TestCase):
"""
class for testing bacteria relabelling
"""
def setUp(self):
self.old_labels = np.array([
[0,0,0,0,0,0,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,0,0,0,0,0,0],
])
self.expected = np.array([
[0,0,0,0,0,0,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,1,1,1,1,1,0],
[0,0,0,0,0,0,0],
])
self.expected_nothing = np.array([
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
[0,0,0,0,0,0,0],
])
self.min_av_width = 1
self.minsize = 30
self.maxsize = 50
self.min_width_too_big = 4
self.minsize_too_big = 100
self.maxsize_too_small = 20
def test_simple_filter_nothing(self):
"""
Tests filtering, with nothing to remove
"""
result = mdet.filter_bacteria(
self.old_labels,
self.min_av_width,
self.minsize,
self.maxsize,
)[0]
np.testing.assert_array_equal(result, self.expected)
def test_filter_area_too_small(self):
"""
Tests filter when area is too small
"""
result = mdet.filter_bacteria(
self.old_labels,
self.min_av_width,
self.minsize_too_big,
self.maxsize,
)[0]
np.testing.assert_array_equal(result, self.expected_nothing)
def test_filter_area_too_big(self):
"""
Tests filter when area is too big
"""
result = mdet.filter_bacteria(
self.old_labels,
self.min_av_width,
self.minsize,
self.maxsize_too_small,
)[0]
np.testing.assert_array_equal(result, self.expected_nothing)
def test_filter_too_narrow(self):
"""
Tests filter when bacteria is too narrow
"""
result = mdet.filter_bacteria(
self.old_labels,
self.min_width_too_big,
self.minsize,
self.maxsize,
)[0]
np.testing.assert_array_equal(result, self.expected_nothing)
if __name__ == '__main__':
unittest.main()
| 46.554338
| 83
| 0.343253
| 7,664
| 50,977
| 2.220903
| 0.051409
| 0.341931
| 0.444157
| 0.518418
| 0.698431
| 0.648963
| 0.626403
| 0.613419
| 0.59785
| 0.572352
| 0
| 0.253129
| 0.492242
| 50,977
| 1,094
| 84
| 46.596892
| 0.404458
| 0.075053
| 0
| 0.683662
| 0
| 0
| 0.004993
| 0.003465
| 0
| 0
| 0
| 0
| 0.045191
| 1
| 0.034762
| false
| 0
| 0.00927
| 0
| 0.05562
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
68d68474da3452d1e66846c039d8ff1a4637dd3e
| 724
|
py
|
Python
|
tests/test_calc.py
|
Cymptom-Research/QA_candidate_task
|
2a88dac877a50b6e5f71c205e870abb1bace2757
|
[
"MIT"
] | null | null | null |
tests/test_calc.py
|
Cymptom-Research/QA_candidate_task
|
2a88dac877a50b6e5f71c205e870abb1bace2757
|
[
"MIT"
] | null | null | null |
tests/test_calc.py
|
Cymptom-Research/QA_candidate_task
|
2a88dac877a50b6e5f71c205e870abb1bace2757
|
[
"MIT"
] | 1
|
2022-02-01T14:08:14.000Z
|
2022-02-01T14:08:14.000Z
|
#!/usr/bin/env python3
# ___ _
# / __\ _ _ __ ___ _ __ | |_ ___ _ __ ___
# / / | | | | '_ ` _ \| '_ \| __/ _ \| '_ ` _ \
# / /__| |_| | | | | | | |_) | || (_) | | | | | |
# \____/\__, |_| |_| |_| .__/ \__\___/|_| |_| |_|
# |___/ |_|
#
#
# Author: Ziv Kaspersky <ziv@cymptom.com> on 19/11/2021
from calc import Calculator
def test_add():
# test basic functionality
assert Calculator.add(4, 5) == 9
# test addition with negative numbers
assert Calculator.add(4, -5) == -1
assert Calculator.add(-4, 5) == 1
assert Calculator.add(-56, -47) == -101
# ?
assert Calculator.add(0, 0) == 0
# ?
assert Calculator.add(2 ** 36, 1) == 2 ** 36 + 1
| 26.814815
| 55
| 0.480663
| 68
| 724
| 4.191176
| 0.544118
| 0.336842
| 0.4
| 0.210526
| 0.294737
| 0.221053
| 0.221053
| 0.221053
| 0.221053
| 0
| 0
| 0.072435
| 0.313536
| 724
| 26
| 56
| 27.846154
| 0.501006
| 0.530387
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.75
| 1
| 0.125
| true
| 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
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
68d992a87a5b79d1a9bcc5fea9d86c8e5859ac6b
| 684
|
py
|
Python
|
my-modules/assets/controllers/controllers.py
|
vinit-ww/odoo_app
|
af8458ae1ca125737826eda743a918ed3acd88f2
|
[
"Apache-2.0"
] | null | null | null |
my-modules/assets/controllers/controllers.py
|
vinit-ww/odoo_app
|
af8458ae1ca125737826eda743a918ed3acd88f2
|
[
"Apache-2.0"
] | null | null | null |
my-modules/assets/controllers/controllers.py
|
vinit-ww/odoo_app
|
af8458ae1ca125737826eda743a918ed3acd88f2
|
[
"Apache-2.0"
] | null | null | null |
# -*- coding: utf-8 -*-
from odoo import http
# class Assets(http.Controller):
# @http.route('/assets/assets/', auth='public')
# def index(self, **kw):
# return "Hello, world"
# @http.route('/assets/assets/objects/', auth='public')
# def list(self, **kw):
# return http.request.render('assets.listing', {
# 'root': '/assets/assets',
# 'objects': http.request.env['assets.assets'].search([]),
# })
# @http.route('/assets/assets/objects/<model("assets.assets"):obj>/', auth='public')
# def object(self, obj, **kw):
# return http.request.render('assets.object', {
# 'object': obj
# })
| 34.2
| 88
| 0.549708
| 75
| 684
| 5.013333
| 0.413333
| 0.191489
| 0.119681
| 0.167553
| 0.31383
| 0.164894
| 0
| 0
| 0
| 0
| 0
| 0.001912
| 0.23538
| 684
| 20
| 89
| 34.2
| 0.717017
| 0.916667
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
68dd7173cff844eb49217dd7652b0ba8a13278ba
| 386
|
py
|
Python
|
vendors/__init__.py
|
Globaldots/s3-trigger-purge-edgecast
|
5cc9356858030d4d5b74b0070bcf492ae1972c2d
|
[
"MIT"
] | 2
|
2018-04-08T18:52:41.000Z
|
2018-12-05T15:18:51.000Z
|
vendors/__init__.py
|
Globaldots/s3-trigger-purge-cdn
|
5cc9356858030d4d5b74b0070bcf492ae1972c2d
|
[
"MIT"
] | null | null | null |
vendors/__init__.py
|
Globaldots/s3-trigger-purge-cdn
|
5cc9356858030d4d5b74b0070bcf492ae1972c2d
|
[
"MIT"
] | null | null | null |
from akamai.akamaiclient import Akamai as akamai
from edgecast.edgecastclient import Edgecast as edgecast
from highwinds.highwindsclient import Highwinds as highwinds
from cloudflare.cloudflareclient import Cloudflare as cloudflare
from fastly.fastlyclient import Fastly as fastly
from chinacache.chinacacheclient import Chinacache as chinacache
# TODO complete cloudinary integration
| 42.888889
| 64
| 0.873057
| 46
| 386
| 7.326087
| 0.413043
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.108808
| 386
| 8
| 65
| 48.25
| 0.979651
| 0.093264
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 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
| 1
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
68e3127c47201853f06aa94e672ee9c432ccb052
| 87
|
py
|
Python
|
booked_api_client/exceptions.py
|
abdelkafiahmed/booked-python-api-client
|
6b1995a8ca3f0176d29a8dcdad47b6eddfd707dd
|
[
"BSD-2-Clause"
] | null | null | null |
booked_api_client/exceptions.py
|
abdelkafiahmed/booked-python-api-client
|
6b1995a8ca3f0176d29a8dcdad47b6eddfd707dd
|
[
"BSD-2-Clause"
] | null | null | null |
booked_api_client/exceptions.py
|
abdelkafiahmed/booked-python-api-client
|
6b1995a8ca3f0176d29a8dcdad47b6eddfd707dd
|
[
"BSD-2-Clause"
] | 1
|
2021-06-18T14:06:00.000Z
|
2021-06-18T14:06:00.000Z
|
class AuthenticationError(Exception):
pass
class APICallError(Exception):
pass
| 17.4
| 37
| 0.770115
| 8
| 87
| 8.375
| 0.625
| 0.38806
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16092
| 87
| 5
| 38
| 17.4
| 0.917808
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 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
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
68f84298c453717c3748c6636f036129f173faca
| 89
|
py
|
Python
|
app/main/services/conversions.py
|
pebblecode/cirrus-marketplace-search-api
|
01b643e0c45a6ca9586751f489da09ff8593e8a9
|
[
"MIT"
] | null | null | null |
app/main/services/conversions.py
|
pebblecode/cirrus-marketplace-search-api
|
01b643e0c45a6ca9586751f489da09ff8593e8a9
|
[
"MIT"
] | null | null | null |
app/main/services/conversions.py
|
pebblecode/cirrus-marketplace-search-api
|
01b643e0c45a6ca9586751f489da09ff8593e8a9
|
[
"MIT"
] | null | null | null |
import re
def strip_and_lowercase(value):
return re.sub(r'\W+', '', value).lower()
| 14.833333
| 44
| 0.651685
| 14
| 89
| 4
| 0.857143
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.157303
| 89
| 5
| 45
| 17.8
| 0.746667
| 0
| 0
| 0
| 0
| 0
| 0.033708
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.333333
| 0.333333
| 1
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 0
| 0
|
0
| 5
|
ec1d8ef0b9a82f4b9a9e01206f8b88355f246846
| 4,857
|
py
|
Python
|
src/raport_slotow/tests/test_raport_slotow_autor/test_raport_slotow_autor.py
|
iplweb/django-bpp
|
85f183a99d8d5027ae4772efac1e4a9f21675849
|
[
"BSD-3-Clause"
] | 1
|
2017-04-27T19:50:02.000Z
|
2017-04-27T19:50:02.000Z
|
src/raport_slotow/tests/test_raport_slotow_autor/test_raport_slotow_autor.py
|
mpasternak/django-bpp
|
434338821d5ad1aaee598f6327151aba0af66f5e
|
[
"BSD-3-Clause"
] | 41
|
2019-11-07T00:07:02.000Z
|
2022-02-27T22:09:39.000Z
|
src/raport_slotow/tests/test_raport_slotow_autor/test_raport_slotow_autor.py
|
iplweb/bpp
|
f027415cc3faf1ca79082bf7bacd4be35b1a6fdf
|
[
"BSD-3-Clause"
] | null | null | null |
from io import BytesIO
import PyPDF2
import pytest
from django.urls import reverse
from openpyxl import load_workbook
from raport_slotow import const
from raport_slotow.forms import AutorRaportSlotowForm
from raport_slotow.views import SESSION_KEY
def test_raport_slotow_formularz(admin_client):
res = admin_client.get(reverse("raport_slotow:index"))
assert res.status_code == 200
def test_raport_slotow_autor_brak_danych(admin_client, autor_jan_kowalski, rok):
url = reverse(
"raport_slotow:raport",
)
dane_raportu = {
"obiekt": autor_jan_kowalski.pk,
"od_roku": rok,
"do_roku": rok,
"dzialanie": const.DZIALANIE_WSZYSTKO,
"minimalny_pk": 0,
"slot": None,
"_export": "html",
}
form = AutorRaportSlotowForm(dane_raportu)
assert form.is_valid(), form._errors
s = admin_client.session
s.update({SESSION_KEY: dane_raportu})
s.save()
res = admin_client.get(url)
assert res.status_code == 200
assert "Brak danych" in res.rendered_content
res = admin_client.get(url + "?_export=xlsx")
assert res.status_code == 200
wb = load_workbook(BytesIO(res.content))
assert len(wb.get_sheet_names()) > 0
def test_raport_slotow_autor_sa_dane_eksport_wszystkiego(
admin_client,
autor_jan_kowalski,
rekord_slotu,
rok,
):
url = reverse("raport_slotow:raport")
dane_raportu = {
"obiekt": autor_jan_kowalski.pk,
"od_roku": rok,
"do_roku": rok,
"dzialanie": const.DZIALANIE_WSZYSTKO,
"minimalny_pk": 0,
"slot": None,
"_export": "html",
}
s = admin_client.session
s.update({SESSION_KEY: dane_raportu})
s.save()
res = admin_client.get(url)
assert res.status_code == 200
assert "Brak danych" not in res.rendered_content
res = admin_client.get(url + "?_export=xlsx")
assert res.status_code == 200
wb = load_workbook(BytesIO(res.content))
assert len(wb.get_sheet_names()) > 0
def test_raport_slotow_autor_sa_dane_eksport_wszystkiego_do_pdf(
admin_client,
autor_jan_kowalski,
rekord_slotu,
rok,
):
url = reverse("raport_slotow:raport")
dane_raportu = {
"obiekt": autor_jan_kowalski.pk,
"od_roku": rok,
"do_roku": rok,
"dzialanie": const.DZIALANIE_WSZYSTKO,
"minimalny_pk": 0,
"slot": None,
"_export": "html",
}
s = admin_client.session
s.update({SESSION_KEY: dane_raportu})
s.save()
res = admin_client.get(url + "?_export=pdf")
assert res.status_code == 200
pdfReader = PyPDF2.PdfFileReader(BytesIO(res.content))
assert pdfReader.numPages >= 1
def test_raport_slotow_autor_zbieraj_slot(
admin_client, autor_jan_kowalski, rekord_slotu, rok
):
url = reverse("raport_slotow:raport")
dane_raportu = {
"obiekt": autor_jan_kowalski.pk,
"od_roku": rok,
"do_roku": rok,
"dzialanie": const.DZIALANIE_SLOT,
"minimalny_pk": 0,
"slot": 20,
"_export": "html",
}
s = admin_client.session
s.update({SESSION_KEY: dane_raportu})
s.save()
res = admin_client.get(url)
assert res.status_code == 200
assert "Brak danych" not in res.rendered_content
res = admin_client.get(url + "?_export=xlsx")
assert res.status_code == 200
wb = load_workbook(BytesIO(res.content))
assert len(wb.get_sheet_names()) > 0
def test_raport_slotow_autor_wartosci_poczatkowe(admin_client):
url = reverse("raport_slotow:index")
res = admin_client.get(url, dict(od_roku=5000))
assert b"5000" in res.content
@pytest.mark.parametrize(
"dzialanie,slot", [(const.DZIALANIE_WSZYSTKO, None), (const.DZIALANIE_SLOT, 20)]
)
def test_raport_slotow_autor_sa_dane_minimalny_pk(
admin_client, autor_jan_kowalski, rekord_slotu, rok, dzialanie, slot
):
w = rekord_slotu.rekord
w.punkty_pk = 10
w.save()
url = reverse("raport_slotow:raport")
dane_raportu = {
"obiekt": autor_jan_kowalski.pk,
"od_roku": rok,
"do_roku": rok,
"dzialanie": dzialanie,
"minimalny_pk": 0,
"slot": slot,
"_export": "html",
}
s = admin_client.session
s.update({SESSION_KEY: dane_raportu})
s.save()
res = admin_client.get(url)
assert res.status_code == 200
assert "Brak danych" not in res.rendered_content
dane_raportu = {
"obiekt": autor_jan_kowalski.pk,
"od_roku": rok,
"do_roku": rok,
"dzialanie": dzialanie,
"minimalny_pk": 200,
"slot": slot,
"_export": "html",
}
s = admin_client.session
s.update({SESSION_KEY: dane_raportu})
s.save()
res = admin_client.get(url)
assert res.status_code == 200
assert "Brak danych" in res.rendered_content
| 25.973262
| 84
| 0.654725
| 623
| 4,857
| 4.807384
| 0.147673
| 0.088147
| 0.051419
| 0.062437
| 0.762938
| 0.716528
| 0.714524
| 0.704508
| 0.690818
| 0.690818
| 0
| 0.015529
| 0.231007
| 4,857
| 186
| 85
| 26.112903
| 0.786345
| 0
| 0
| 0.710526
| 0
| 0
| 0.123121
| 0
| 0
| 0
| 0
| 0
| 0.138158
| 1
| 0.046053
| false
| 0
| 0.052632
| 0
| 0.098684
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
ec23453bfe4b1d06d03014a27747bf0f9024512b
| 141
|
py
|
Python
|
metriq/__init__.py
|
unitaryfund/metriq-client
|
7d8831d5015baa490ec77a04ea704d2e9aa9d8d0
|
[
"Apache-2.0"
] | null | null | null |
metriq/__init__.py
|
unitaryfund/metriq-client
|
7d8831d5015baa490ec77a04ea704d2e9aa9d8d0
|
[
"Apache-2.0"
] | null | null | null |
metriq/__init__.py
|
unitaryfund/metriq-client
|
7d8831d5015baa490ec77a04ea704d2e9aa9d8d0
|
[
"Apache-2.0"
] | null | null | null |
__all__ = ["MetriqClient", "version", "__version__"]
from metriq.client import MetriqClient
from metriq.version import version, __version__
| 28.2
| 52
| 0.794326
| 15
| 141
| 6.666667
| 0.466667
| 0.28
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106383
| 141
| 4
| 53
| 35.25
| 0.793651
| 0
| 0
| 0
| 0
| 0
| 0.212766
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 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
| 1
| 0
|
0
| 5
|
ec33984c3e3175f1c43fdbb188ad4d57c58e335c
| 221
|
py
|
Python
|
base/pylib/none.py
|
jpolitz/lambda-py-paper
|
746ef63fc1123714b4adaf78119028afbea7bd76
|
[
"Apache-2.0"
] | 25
|
2015-04-16T04:31:49.000Z
|
2022-03-10T15:53:28.000Z
|
base/pylib/none.py
|
jpolitz/lambda-py-paper
|
746ef63fc1123714b4adaf78119028afbea7bd76
|
[
"Apache-2.0"
] | 1
|
2018-11-21T22:40:02.000Z
|
2018-11-26T17:53:11.000Z
|
base/pylib/none.py
|
jpolitz/lambda-py-paper
|
746ef63fc1123714b4adaf78119028afbea7bd76
|
[
"Apache-2.0"
] | 1
|
2021-03-26T03:36:19.000Z
|
2021-03-26T03:36:19.000Z
|
class NoneType(object):
def __new__(self, *args):
return None
def __init__(self, *args):
pass
def __bool__(self):
return False
def __str__(self):
return "None"
___assign("%NoneType", NoneType)
| 14.733333
| 32
| 0.656109
| 27
| 221
| 4.666667
| 0.555556
| 0.126984
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.221719
| 221
| 14
| 33
| 15.785714
| 0.732558
| 0
| 0
| 0
| 0
| 0
| 0.058824
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0.1
| 0
| 0.3
| 0.8
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
|
0
| 5
|
6b8c8bc201525c06a544583d2122abe2b8024ccb
| 102
|
py
|
Python
|
sqlbucket/__init__.py
|
sp-anna-jones/sqlbucket
|
a9dda3ad0f8594c16e02f7a293b084b809920e92
|
[
"MIT"
] | null | null | null |
sqlbucket/__init__.py
|
sp-anna-jones/sqlbucket
|
a9dda3ad0f8594c16e02f7a293b084b809920e92
|
[
"MIT"
] | null | null | null |
sqlbucket/__init__.py
|
sp-anna-jones/sqlbucket
|
a9dda3ad0f8594c16e02f7a293b084b809920e92
|
[
"MIT"
] | null | null | null |
__version__ = "0.3.0"
from sqlbucket.core import SQLBucket
from sqlbucket.project import Project
| 11.333333
| 37
| 0.77451
| 14
| 102
| 5.357143
| 0.571429
| 0.346667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.034884
| 0.156863
| 102
| 8
| 38
| 12.75
| 0.837209
| 0
| 0
| 0
| 0
| 0
| 0.050505
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 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
| 1
| 0
|
0
| 5
|
6bda686042217cdad58b6e731ee1c83afc300202
| 88
|
py
|
Python
|
iscan/tests/test_modules/relative.py
|
ZhengnanZhao/importscanner
|
75ef3b10383b54a5d318a15d5a85c7fcb4ff762d
|
[
"MIT"
] | 3
|
2021-04-15T14:11:28.000Z
|
2022-02-06T14:28:33.000Z
|
iscan/tests/test_modules/relative.py
|
zzhengnan/iscan
|
75ef3b10383b54a5d318a15d5a85c7fcb4ff762d
|
[
"MIT"
] | null | null | null |
iscan/tests/test_modules/relative.py
|
zzhengnan/iscan
|
75ef3b10383b54a5d318a15d5a85c7fcb4ff762d
|
[
"MIT"
] | null | null | null |
from ..grandparentutils import baz
from ..parentutils import bar
from .utils import foo
| 22
| 34
| 0.806818
| 12
| 88
| 5.916667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.136364
| 88
| 3
| 35
| 29.333333
| 0.934211
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| 1
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| 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
| 5
|
6bf8ed61d9a8d59a0cac9e01d230e8a1e3f93410
| 328
|
py
|
Python
|
tests/test_prepare_data.py
|
ayasyrev/dup_finder
|
f5b9dca06bf183b016ea23c7f7fa1bb3adecac9e
|
[
"Apache-2.0"
] | null | null | null |
tests/test_prepare_data.py
|
ayasyrev/dup_finder
|
f5b9dca06bf183b016ea23c7f7fa1bb3adecac9e
|
[
"Apache-2.0"
] | 1
|
2020-11-13T13:03:55.000Z
|
2020-11-13T13:10:52.000Z
|
tests/test_prepare_data.py
|
ayasyrev/dup_finder
|
f5b9dca06bf183b016ea23c7f7fa1bb3adecac9e
|
[
"Apache-2.0"
] | null | null | null |
import pathlib
from dup_finder.prepare_test_data import TEST_DATA_PATH, TEST_ROOT, PACKAGE_ROOT, LIB_ROOT
def test_path_names():
assert type(TEST_ROOT) == pathlib.PosixPath
assert type(TEST_DATA_PATH) == pathlib.PosixPath
assert type(PACKAGE_ROOT) == pathlib.PosixPath
assert type(LIB_ROOT) == pathlib.PosixPath
| 41
| 90
| 0.786585
| 47
| 328
| 5.170213
| 0.361702
| 0.164609
| 0.246914
| 0.320988
| 0.246914
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.131098
| 328
| 8
| 91
| 41
| 0.852632
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.571429
| 1
| 0.142857
| true
| 0
| 0.285714
| 0
| 0.428571
| 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
| 1
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
d46145f461d9d7deda5700cc4f0bf26477023c4a
| 860
|
py
|
Python
|
tests/integration_tests/foo_tests.py
|
FireXStuff/firex-bundle-foobar
|
e6d27987b880674e50470931c117aadc278e66d8
|
[
"BSD-3-Clause"
] | 2
|
2019-04-05T14:14:34.000Z
|
2019-04-24T19:59:55.000Z
|
tests/integration_tests/foo_tests.py
|
FireXStuff/firex-bundle-foobar
|
e6d27987b880674e50470931c117aadc278e66d8
|
[
"BSD-3-Clause"
] | null | null | null |
tests/integration_tests/foo_tests.py
|
FireXStuff/firex-bundle-foobar
|
e6d27987b880674e50470931c117aadc278e66d8
|
[
"BSD-3-Clause"
] | 1
|
2019-04-05T14:15:10.000Z
|
2019-04-05T14:15:10.000Z
|
from firexapp.testing.config_base import FlowTestConfiguration, assert_is_good_run
class MyFooDefaultTest(FlowTestConfiguration):
def initial_firex_options(self) -> list:
return ["submit", "--chain", "foo,bar"]
def assert_expected_firex_output(self, cmd_output, cmd_err):
assert "defeat No success!!!" in cmd_output
def assert_expected_return_code(self, ret_value):
assert_is_good_run(ret_value)
class DefineMyOwnSuccessTest(FlowTestConfiguration):
def initial_firex_options(self) -> list:
return ["submit", "--chain", "foo,bar", "--define_success", "not likely"]
def assert_expected_firex_output(self, cmd_output, cmd_err):
assert "defeat No not likely" in cmd_output, "Good try... but no"
def assert_expected_return_code(self, ret_value):
assert_is_good_run(ret_value)
| 34.4
| 82
| 0.723256
| 110
| 860
| 5.318182
| 0.372727
| 0.061538
| 0.116239
| 0.076923
| 0.673504
| 0.673504
| 0.673504
| 0.673504
| 0.673504
| 0.673504
| 0
| 0
| 0.174419
| 860
| 24
| 83
| 35.833333
| 0.823944
| 0
| 0
| 0.533333
| 0
| 0
| 0.153667
| 0
| 0
| 0
| 0
| 0
| 0.6
| 1
| 0.4
| false
| 0
| 0.066667
| 0.133333
| 0.733333
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
2e5543171ff5a6308629d1195e29d7f1f007d04b
| 4,366
|
py
|
Python
|
baidu_fy/baidu_fy.py
|
vleij/-
|
2b0f7bb91025b57e370ba4bfe7fe259a3ab78360
|
[
"Apache-2.0"
] | null | null | null |
baidu_fy/baidu_fy.py
|
vleij/-
|
2b0f7bb91025b57e370ba4bfe7fe259a3ab78360
|
[
"Apache-2.0"
] | null | null | null |
baidu_fy/baidu_fy.py
|
vleij/-
|
2b0f7bb91025b57e370ba4bfe7fe259a3ab78360
|
[
"Apache-2.0"
] | null | null | null |
import execjs
import requests
with open('baiodu_fy.js', encoding='utf-8') as f:
js_code = f.read()
node = execjs.get()
#编译js代码
ctx = node.compile(js_code) #compile方法去加载js代码，参数cwd指定本地安装模块所在目录
search = '你好呀'
data1 = ctx.eval('data("'+search+'")') #eval方法中，整个函数调用包含在字符串内
data1['query'] = search
headers = {
'Host':'fanyi.baidu.com',
'User-Agent': 'Mozilla/5.0 (Windows NT 6.1; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/96.0.4664.45 Safari/537.36',
'X-Requested-With':'XMLHttpRequest',
'Origin': 'https://fanyi.baidu.com',
'Referer': 'https://fanyi.baidu.com/translate?aldtype=16047&query=%E4%BD%A0%E5%A5%BD&keyfrom=baidu&smartresult=dict&lang=auto2zh',
'Cookie':'PSTM=1625158021; BAIDUID=226BB1684C9766B09993FCD1A713C35C:FG=1; BIDUPSID=6FE83BD85D2A96B001DAA1FD295A1AA5; __yjs_duid=1_2253a89fdac985131d9133c4a173b2d81625489822668; REALTIME_TRANS_SWITCH=1; FANYI_WORD_SWITCH=1; HISTORY_SWITCH=1; SOUND_SPD_SWITCH=1; SOUND_PREFER_SWITCH=1; BDUSS_BFESS=FpQOEQ3a1dyRXhvY2M2SXlqb21nTUUtUjJ4eVFoeUdoUzZCWjE3V2l5UGVMWVZoRUFBQUFBJCQAAAAAAAAAAAEAAAAGNGeutPPAx7m32K8AAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAAN6gXWHeoF1he; BDSFRCVID=DdAOJeC62lQ-nZ3HcqLwesrXsg0IRInTH6aoO5DD4o1we3OU9p85EG0PKx8g0Kubz7pbogKKLmOTHp-F_2uxOjjg8UtVJeC6EG0Ptf8g0f5; H_BDCLCKID_SF=JJ4eoIKbfIvbfP0k5PoEb-F_hmT22-us0-jR2hcHMPoosIJXXKcCybFqXlO-bbj8LIjiaKJjBMbUotoH2RbEhl5yQh3ianQp52jb_h5TtUJMbb3dLnoMqfAnMMTyKMniBIj9-pnMHlQrh459XP68bTkA5bjZKxtq3mkjbPbDfn028DKuj605D5QyeaRabK6aKC5bL6rJabC3hI3JXU6q2bDeQN3kWIrNWT5B2T6H--oBVb6oyT3JXp0vWq54WbbvLT7johRTWqR4ep6gjUonDh83eMJ33bQJHmJ7BnrO5hvv8b6O3M72qfKmDloOW-TB5bbPLUQF5l8-sq0x0bOte-bQXH_EJ58qJbIJ_DDQ5RbhKCKl-nOoq4tehHRx3R39WDTm_DonBtONoJcSK6OvW-LyKR7kK6OALe5X-pPKKRABVR3XLtPbXTkFyH525M5Q3mkjbUODfn02OP5PetorDt4syPRr2xRnWT4LKfA-b4ncjRcTehoM3xI8LNj405OTbIFO0KJDJCFabKtCjTAKDTPyMMrL2K60aR3Hbx7vWJ5TMCoz2q7ObP4nQPvzJ-Qe-j5-0-5TX-TKShPC-qjM3q0Z3MCDBnoN025Gon0h3l02VMQEe-t2ynLV34QB0PRMW23rWl7mWPtVsxA45J7cM4IseboJLfT-0bc4KKJxbnLWeIJIjjCKjj3QjHD8JTn-5TIX_CjJbnA_Hn7zeUOfLf4pbt-qJt7IHCozohnJ-lRbetO4WbbJDMFwyfTnBT5Ka28tKp-2aKjbeDOO3jr2e5LkQN3TBbkO5bRiLRoLJ-JDDn3oyUvVXp0nK2cly5jtMgOBBJ0yQ4b4OR5JjxonDh83bG7MJPKtfD7H3KChtI0hbf5; BDSFRCVID_BFESS=DdAOJeC62lQ-nZ3HcqLwesrXsg0IRInTH6aoO5DD4o1we3OU9p85EG0PKx8g0Kubz7pbogKKLmOTHp-F_2uxOjjg8UtVJeC6EG0Ptf8g0f5; H_BDCLCKID_SF_BFESS=JJ4eoIKbfIvbfP0k5PoEb-F_hmT22-us0-jR2hcHMPoosIJXXKcCybFqXlO-bbj8LIjiaKJjBMbUotoH2RbEhl5yQh3ianQp52jb_h5TtUJMbb3dLnoMqfAnMMTyKMniBIj9-pnMHlQrh459XP68bTkA5bjZKxtq3mkjbPbDfn028DKuj605D5QyeaRabK6aKC5bL6rJabC3hI3JXU6q2bDeQN3kWIrNWT5B2T6H--oBVb6oyT3JXp0vWq54WbbvLT7johRTWqR4ep6gjUonDh83eMJ33bQJHmJ7BnrO5hvv8b6O3M72qfKmDloOW-TB5bbPLUQF5l8-sq0x0bOte-bQXH_EJ58qJbIJ_DDQ5RbhKCKl-nOoq4tehHRx3R39WDTm_DonBtONoJcSK6OvW-LyKR7kK6OALe5X-pPKKRABVR3XLtPbXTkFyH525M5Q3mkjbUODfn02OP5PetorDt4syPRr2xRnWT4LKfA-b4ncjRcTehoM3xI8LNj405OTbIFO0KJDJCFabKtCjTAKDTPyMMrL2K60aR3Hbx7vWJ5TMCoz2q7ObP4nQPvzJ-Qe-j5-0-5TX-TKShPC-qjM3q0Z3MCDBnoN025Gon0h3l02VMQEe-t2ynLV34QB0PRMW23rWl7mWPtVsxA45J7cM4IseboJLfT-0bc4KKJxbnLWeIJIjjCKjj3QjHD8JTn-5TIX_CjJbnA_Hn7zeUOfLf4pbt-qJt7IHCozohnJ-lRbetO4WbbJDMFwyfTnBT5Ka28tKp-2aKjbeDOO3jr2e5LkQN3TBbkO5bRiLRoLJ-JDDn3oyUvVXp0nK2cly5jtMgOBBJ0yQ4b4OR5JjxonDh83bG7MJPKtfD7H3KChtI0hbf5; BDORZ=B490B5EBF6F3CD402E515D22BCDA1598; ZD_ENTRY=empty; delPer=0; PSINO=7; Hm_lvt_64ecd82404c51e03dc91cb9e8c025574=1641620515; Hm_lpvt_64ecd82404c51e03dc91cb9e8c025574=1641620515; APPGUIDE_10_0_2=1; __yjs_st=2_MzM3MTQ0NGJlZjViZGNmMjhhMTY0NjhkNTg0YWFlY2M3OTJjNGUyZjAwZWFjOGY1MTIwNWI0MzcwOGIzMzZkMGFmOWQxYmRlOWY2NTYyOGY3YTJkMGEwM2YxNTM2ZDFiOTBkY2YzZWNiYTE1NDU1ZGJjZWY5NmY1NWJjZDVmN2IwZmNlNzRlMmNkY2I0Yjg0MmU2ZjAwZTc0MTU5MzExYzM1ZjBiNGNjZGMxM2RhYmZhNjhjNTczY2UxOTEyOTQ3M2E4ZWNiZTNlNGNiNTQzZDM3Zjc3MDdlYmI2OWY5MWFiN2IwMmUxZmZiZjUwMGEzMTQ2NWFkNTI0MzY2OWZlYV83XzllMzRhMjg0; ab_sr=1.0.1_ZTA0MmUwOTlkM2ZhY2JmZTdhM2JmM2UwMDVlZWJmZmJjMGE5NTUxNjVmMTk1ZjFjMDUwM2FhNjM2N2I2NmUwY2FiN2QzNGI2NzRjOTkyMDRhZGVjYTA5MDRmZTc0OTA4YmIyODAzODZlNWYyNjAwMWJiNmRhOGU2YjNiZGQ4YWVjZWFhNzMyNmQ3OTIzYzBlZWFhNGY5NzVhZTI1MWZlZTc5MjIwZGYzNTQ1MGNlMDY2YzAwNzc4MmNkNWRlYTFk; BDRCVFR[feWj1Vr5u3D]=I67x6TjHwwYf0; H_PS_PSSID=35106_31254_35489_35604_35456_34584_35490_35700_34813_35664_35321_26350_22158; BA_HECTOR=8h04850ha501a0aksf1gtid4j0r',
}
r = requests.post("https://fanyi.baidu.com/v2transapi?from=zh&to=en",data=data1,headers=headers)
print(r.text)
| 189.826087
| 3,538
| 0.905405
| 295
| 4,366
| 13.169492
| 0.637288
| 0.009009
| 0.013385
| 0.0139
| 0.494208
| 0.494208
| 0.494208
| 0.435006
| 0.435006
| 0.435006
| 0
| 0.179669
| 0.03115
| 4,366
| 22
| 3,539
| 198.454545
| 0.738771
| 0.013972
| 0
| 0
| 0
| 0.157895
| 0.918906
| 0.788502
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.105263
| 0
| 0.105263
| 0.052632
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
2e80040fac53e82ed710eeb1045512689988b8c3
| 233
|
py
|
Python
|
PEPit/examples/low_dimensional_worst_cases_scenarios/__init__.py
|
PerformanceEstimation/PEPit
|
7005bc9a9da11dea448966437365c897734ec341
|
[
"MIT"
] | 1
|
2022-03-30T11:18:37.000Z
|
2022-03-30T11:18:37.000Z
|
PEPit/examples/low_dimensional_worst_cases_scenarios/__init__.py
|
PerformanceEstimation/PEPit
|
7005bc9a9da11dea448966437365c897734ec341
|
[
"MIT"
] | 1
|
2022-02-23T10:26:38.000Z
|
2022-02-23T10:26:38.000Z
|
PEPit/examples/low_dimensional_worst_cases_scenarios/__init__.py
|
PerformanceEstimation/PEPit
|
7005bc9a9da11dea448966437365c897734ec341
|
[
"MIT"
] | null | null | null |
from .inexact_gradient import wc_inexact_gradient
from .optimized_gradient import wc_optimized_gradient
__all__ = ['inexact_gradient', 'wc_inexact_gradient',
'optimized_gradient.py', 'wc_optimized_gradient',
]
| 33.285714
| 60
| 0.759657
| 26
| 233
| 6.192308
| 0.307692
| 0.372671
| 0.198758
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.16309
| 233
| 6
| 61
| 38.833333
| 0.825641
| 0
| 0
| 0
| 0
| 0
| 0.330472
| 0.180258
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.4
| 0
| 0.4
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
5cf6bf0b3d2c488b0c4a9e08aab9a9fde852eea6
| 530
|
py
|
Python
|
intents/connectors/dialogflow_es/names.py
|
dario-chiappetta/dialogflow_agents
|
ecb03bdce491a3c9d6769816507f3027fd5a60d1
|
[
"Apache-2.0"
] | 6
|
2021-06-24T12:22:21.000Z
|
2021-07-21T21:06:19.000Z
|
intents/connectors/dialogflow_es/names.py
|
dario-chiappetta/dialogflow_agents
|
ecb03bdce491a3c9d6769816507f3027fd5a60d1
|
[
"Apache-2.0"
] | 27
|
2021-06-05T10:41:08.000Z
|
2021-11-01T17:29:38.000Z
|
intents/connectors/dialogflow_es/names.py
|
dariowho/intents
|
ecb03bdce491a3c9d6769816507f3027fd5a60d1
|
[
"Apache-2.0"
] | null | null | null |
from typing import Type
from intents import Intent
from intents.helpers.misc import camel_to_snake_case
def context_name(intent_cls: Type[Intent]) -> str:
return "c_" + camel_to_snake_case(intent_cls.name.replace(".", "_")) # TODO: refine
def event_name(intent_cls: Type[Intent]) -> str:
"""
Generate the default event name that we associate with every intent.
>>> event_name('test.intent_name')
'E_TEST_INTENT_NAME'
"""
return "E_" + camel_to_snake_case(intent_cls.name.replace(".", "_")).upper()
| 31.176471
| 87
| 0.711321
| 76
| 530
| 4.644737
| 0.447368
| 0.101983
| 0.101983
| 0.135977
| 0.351275
| 0.351275
| 0.203966
| 0.203966
| 0
| 0
| 0
| 0
| 0.156604
| 530
| 16
| 88
| 33.125
| 0.789709
| 0.262264
| 0
| 0
| 0
| 0
| 0.021798
| 0
| 0
| 0
| 0
| 0.0625
| 0
| 1
| 0.285714
| false
| 0
| 0.428571
| 0.142857
| 1
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 1
| 1
| 0
|
0
| 5
|
cf3374eb700fea99113bffe97a268a36cf5e84b6
| 68
|
py
|
Python
|
models/segmentation/unet/__init__.py
|
neurips2021vat/Variance-Aware-Training
|
2dcd017ef06e81e299448bdd9da65fa682835127
|
[
"BSD-2-Clause"
] | null | null | null |
models/segmentation/unet/__init__.py
|
neurips2021vat/Variance-Aware-Training
|
2dcd017ef06e81e299448bdd9da65fa682835127
|
[
"BSD-2-Clause"
] | null | null | null |
models/segmentation/unet/__init__.py
|
neurips2021vat/Variance-Aware-Training
|
2dcd017ef06e81e299448bdd9da65fa682835127
|
[
"BSD-2-Clause"
] | null | null | null |
from models.segmentation.unet.model import Model # pyflakes.ignore
| 34
| 67
| 0.823529
| 9
| 68
| 6.222222
| 0.888889
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102941
| 68
| 1
| 68
| 68
| 0.918033
| 0.220588
| 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
| 1
| 0
|
0
| 5
|
cf7c89d4bc4a19c01768bccdde351e1c9b7ad481
| 40
|
py
|
Python
|
tests/databases/__init__.py
|
sethfischer/mundo-flags
|
20e5ad68d760b6c736701f6e43551c738456098d
|
[
"MIT"
] | null | null | null |
tests/databases/__init__.py
|
sethfischer/mundo-flags
|
20e5ad68d760b6c736701f6e43551c738456098d
|
[
"MIT"
] | 1
|
2021-09-06T01:48:18.000Z
|
2021-09-06T08:47:36.000Z
|
tests/databases/__init__.py
|
sethfischer/mundo-flags
|
20e5ad68d760b6c736701f6e43551c738456098d
|
[
"MIT"
] | null | null | null |
"""Tests for manage_flags databases."""
| 20
| 39
| 0.725
| 5
| 40
| 5.6
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| 0.1
| 40
| 1
| 40
| 40
| 0.777778
| 0.825
| 0
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| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
d84270c6cec886ec27e64f92ea306be0fa13d1db
| 250
|
py
|
Python
|
pymarket/conftest.py
|
taqtiqa-mark/pymarket
|
2f8db92010d5f9407a72941788500351e92cbe81
|
[
"MIT"
] | null | null | null |
pymarket/conftest.py
|
taqtiqa-mark/pymarket
|
2f8db92010d5f9407a72941788500351e92cbe81
|
[
"MIT"
] | null | null | null |
pymarket/conftest.py
|
taqtiqa-mark/pymarket
|
2f8db92010d5f9407a72941788500351e92cbe81
|
[
"MIT"
] | null | null | null |
import numpy
import pandas
import pymarket
import pytest
@pytest.fixture(autouse=True)
def add_namespace(doctest_namespace):
doctest_namespace['np'] = numpy
doctest_namespace['pd'] = pandas
doctest_namespace['pm'] = pymarket
| 22.727273
| 42
| 0.728
| 29
| 250
| 6.103448
| 0.517241
| 0.361582
| 0.282486
| 0
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| 0
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| 0
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| 0.18
| 250
| 10
| 43
| 25
| 0.863415
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| false
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| 0
| 1
| 0
|
0
| 5
|
d881fd1c7e59b4bcec3ccbd0b8558e306a842cba
| 252
|
py
|
Python
|
6 kyu/Drunk friend.py
|
mwk0408/codewars_solutions
|
9b4f502b5f159e68024d494e19a96a226acad5e5
|
[
"MIT"
] | 6
|
2020-09-03T09:32:25.000Z
|
2020-12-07T04:10:01.000Z
|
6 kyu/Drunk friend.py
|
mwk0408/codewars_solutions
|
9b4f502b5f159e68024d494e19a96a226acad5e5
|
[
"MIT"
] | 1
|
2021-12-13T15:30:21.000Z
|
2021-12-13T15:30:21.000Z
|
6 kyu/Drunk friend.py
|
mwk0408/codewars_solutions
|
9b4f502b5f159e68024d494e19a96a226acad5e5
|
[
"MIT"
] | null | null | null |
def decode(string_):
if not isinstance(string_, str):
return "Input is not a string"
return string_.translate(str.maketrans("abcdefghijklmnopqrstuvwxyzABCDEFGHIJKLMNOPQRSTUVWXYZ", "zyxwvutsrqponmlkjihgfedcbaZYXWVUTSRQPONMLKJIHGFEDCBA"))
| 63
| 155
| 0.801587
| 21
| 252
| 9.47619
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0.119048
| 252
| 4
| 155
| 63
| 0.896396
| 0
| 0
| 0
| 0
| 0
| 0.494071
| 0.411067
| 0
| 0
| 0
| 0
| 0
| 1
| 0.25
| false
| 0
| 0
| 0
| 0.75
| 0
| 1
| 0
| 0
| null | 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 1
| null | 0
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| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
d8ef151827cad5109913a30783c7723e28a22f0d
| 34
|
py
|
Python
|
unleash/__init__.py
|
SerpentAI/Unleash
|
add22233f5280e462d6410bfc9ccc3f38b7d4a78
|
[
"MIT"
] | 1
|
2020-06-10T06:39:22.000Z
|
2020-06-10T06:39:22.000Z
|
unleash/__init__.py
|
SerpentAI/Unleash
|
add22233f5280e462d6410bfc9ccc3f38b7d4a78
|
[
"MIT"
] | null | null | null |
unleash/__init__.py
|
SerpentAI/Unleash
|
add22233f5280e462d6410bfc9ccc3f38b7d4a78
|
[
"MIT"
] | 3
|
2021-09-05T21:49:40.000Z
|
2021-10-01T12:24:57.000Z
|
from unleash.logger import logger
| 17
| 33
| 0.852941
| 5
| 34
| 5.8
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.117647
| 34
| 1
| 34
| 34
| 0.966667
| 0
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| true
| 0
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| null | 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
d8f0a52563ffa96892286e741539c87ce3599c9f
| 1,239
|
py
|
Python
|
home/models.py
|
StoneMasons4106/clay-cabinet
|
6defd2fcf55d5589777d2e92154668344e923b52
|
[
"MIT"
] | null | null | null |
home/models.py
|
StoneMasons4106/clay-cabinet
|
6defd2fcf55d5589777d2e92154668344e923b52
|
[
"MIT"
] | null | null | null |
home/models.py
|
StoneMasons4106/clay-cabinet
|
6defd2fcf55d5589777d2e92154668344e923b52
|
[
"MIT"
] | null | null | null |
from django.db import models
# Create your models here.
class HomePagePicture(models.Model):
name = models.CharField(max_length=254)
image = models.ImageField(null=True, blank=True)
title = models.CharField(max_length=254, null=True, blank=True)
description = models.CharField(max_length=254, null=True, blank=True)
def __str__(self):
return self.name
class Testimonial(models.Model):
name = models.CharField(max_length=254)
image = models.ImageField(null=True, blank=True)
testimonial = models.TextField(max_length=2048)
date = models.DateField(null=True, blank=True)
def __str__(self):
return self.name
class Content(models.Model):
name = models.CharField(max_length=254)
banner_text = models.CharField(max_length=254)
gallery_title = models.CharField(max_length=254)
gallery_text = models.CharField(max_length=254)
video_title = models.CharField(max_length=254)
video_content = models.CharField(max_length=100000, null=True, blank=True)
video_text = models.CharField(max_length=254)
testimonial_title = models.CharField(max_length=254)
testimonial_text = models.CharField(max_length=254)
def __str__(self):
return self.name
| 33.486486
| 78
| 0.734463
| 164
| 1,239
| 5.341463
| 0.231707
| 0.143836
| 0.267123
| 0.356164
| 0.753425
| 0.753425
| 0.416667
| 0.416667
| 0.368721
| 0.287671
| 0
| 0.044231
| 0.160613
| 1,239
| 37
| 79
| 33.486486
| 0.798077
| 0.01937
| 0
| 0.407407
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| false
| 0
| 0.037037
| 0.111111
| 1
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
2b569f8a7fe3ff47329054fe5a502067ff7a3836
| 223
|
py
|
Python
|
tests/urls.py
|
chewse/rest_condition
|
213e504a930a6c76331df936dbf998efa2450bb3
|
[
"MIT"
] | 250
|
2015-01-07T14:37:32.000Z
|
2022-03-29T15:15:57.000Z
|
tests/urls.py
|
chewse/djangorestframework-signed-permissions
|
b1cc4c57999fc5be8361f60f0ada1d777b27feab
|
[
"MIT"
] | 10
|
2015-04-06T18:38:07.000Z
|
2020-09-10T08:48:26.000Z
|
tests/urls.py
|
chewse/djangorestframework-signed-permissions
|
b1cc4c57999fc5be8361f60f0ada1d777b27feab
|
[
"MIT"
] | 26
|
2015-08-10T14:17:06.000Z
|
2022-03-25T12:31:52.000Z
|
#!/usr/bin/env python
# -*- coding: utf-8 -*-
try:
from django.conf.urls import include, patterns, url
except ImportError:
from django.conf.urls.defaults import include, patterns, url
urlpatterns = patterns('', )
| 22.3
| 64
| 0.699552
| 29
| 223
| 5.37931
| 0.689655
| 0.128205
| 0.179487
| 0.230769
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.005348
| 0.161435
| 223
| 9
| 65
| 24.777778
| 0.828877
| 0.188341
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.6
| 0
| 0.6
| 0
| 1
| 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
| 5
|
2b5b668061af93827be5d4c184e169822aba151e
| 228
|
py
|
Python
|
Python/empire/aws/s3/storage_classes.py
|
Tombmyst/Empire
|
f28782787c5fa9127e353549b73ec90d3c82c003
|
[
"Apache-2.0"
] | null | null | null |
Python/empire/aws/s3/storage_classes.py
|
Tombmyst/Empire
|
f28782787c5fa9127e353549b73ec90d3c82c003
|
[
"Apache-2.0"
] | null | null | null |
Python/empire/aws/s3/storage_classes.py
|
Tombmyst/Empire
|
f28782787c5fa9127e353549b73ec90d3c82c003
|
[
"Apache-2.0"
] | null | null | null |
from empire.python.typings import *
class StorageClasses:
STANDARD: Final[str] = 'STANDARD'
@staticmethod
def values() -> List[str]:
return list(StorageClasses.__dict__['__annotations__'].keys())
| 22.8
| 71
| 0.662281
| 22
| 228
| 6.5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214912
| 228
| 9
| 72
| 25.333333
| 0.798883
| 0
| 0
| 0
| 0
| 0
| 0.105023
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| true
| 0
| 0.166667
| 0.166667
| 0.833333
| 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
| 1
| 1
| 0
|
0
| 5
|
2b5d08180f1f8bddc00238e916e34bcfee23f15c
| 27
|
py
|
Python
|
bin/__init__.py
|
josephmje/datman
|
c18bbbbe11b679d3535d02edb6711c76a891a350
|
[
"Apache-2.0"
] | 17
|
2015-09-08T13:56:40.000Z
|
2022-01-20T19:09:33.000Z
|
bin/__init__.py
|
josephmje/datman
|
c18bbbbe11b679d3535d02edb6711c76a891a350
|
[
"Apache-2.0"
] | 169
|
2015-02-23T23:11:15.000Z
|
2022-03-28T20:32:22.000Z
|
bin/__init__.py
|
josephmje/datman
|
c18bbbbe11b679d3535d02edb6711c76a891a350
|
[
"Apache-2.0"
] | 21
|
2015-09-15T16:22:44.000Z
|
2021-11-05T19:03:02.000Z
|
# Needed for tests to work
| 13.5
| 26
| 0.740741
| 5
| 27
| 4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.222222
| 27
| 1
| 27
| 27
| 0.952381
| 0.888889
| 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
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
2b725d0cb4b8aa42c33bcd24e1c04091070ef136
| 149
|
py
|
Python
|
gpytorch/constraints/__init__.py
|
techshot25/gpytorch
|
b4aee6f81a3428172d4914e7e0fef0e71cd1f519
|
[
"MIT"
] | 2
|
2019-04-19T00:35:49.000Z
|
2019-04-19T02:51:49.000Z
|
gpytorch/constraints/__init__.py
|
VonRosenchild/gpytorch
|
092d523027a844939ba85d7ea8c8c7b7511843d5
|
[
"MIT"
] | null | null | null |
gpytorch/constraints/__init__.py
|
VonRosenchild/gpytorch
|
092d523027a844939ba85d7ea8c8c7b7511843d5
|
[
"MIT"
] | 1
|
2019-04-19T00:42:35.000Z
|
2019-04-19T00:42:35.000Z
|
from .constraints import GreaterThan, Interval, LessThan, Positive
__all__ = [
"GreaterThan",
"Interval",
"LessThan",
"Positive",
]
| 16.555556
| 66
| 0.657718
| 12
| 149
| 7.833333
| 0.666667
| 0.404255
| 0.574468
| 0.744681
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.214765
| 149
| 8
| 67
| 18.625
| 0.803419
| 0
| 0
| 0
| 0
| 0
| 0.234899
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.142857
| 0
| 0.142857
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
9918e8785b560f6c5562e9fc93b33ebba0d19aff
| 46
|
py
|
Python
|
MicroRegEx/PatternSyntaxError.py
|
howl-anderson/MicroRegEx
|
2bfe48f1ac018398e1e77e7f1a6f5c64771399ca
|
[
"MIT"
] | 44
|
2017-04-06T07:41:05.000Z
|
2021-04-02T16:09:29.000Z
|
MicroRegEx/PatternSyntaxError.py
|
howl-anderson/MicroRegEx
|
2bfe48f1ac018398e1e77e7f1a6f5c64771399ca
|
[
"MIT"
] | null | null | null |
MicroRegEx/PatternSyntaxError.py
|
howl-anderson/MicroRegEx
|
2bfe48f1ac018398e1e77e7f1a6f5c64771399ca
|
[
"MIT"
] | 5
|
2018-08-13T11:17:03.000Z
|
2020-09-04T09:11:55.000Z
|
class PatternSyntaxError(Exception):
pass
| 15.333333
| 36
| 0.782609
| 4
| 46
| 9
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.152174
| 46
| 2
| 37
| 23
| 0.923077
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
9941cd5a627a421d97c20763a67dd725597ebc99
| 160
|
py
|
Python
|
heroku.py
|
rooted-cyber/Heroku-CLI
|
980085fb384a8dc4c2b77bc832e34f556a64ee4f
|
[
"Apache-2.0"
] | null | null | null |
heroku.py
|
rooted-cyber/Heroku-CLI
|
980085fb384a8dc4c2b77bc832e34f556a64ee4f
|
[
"Apache-2.0"
] | null | null | null |
heroku.py
|
rooted-cyber/Heroku-CLI
|
980085fb384a8dc4c2b77bc832e34f556a64ee4f
|
[
"Apache-2.0"
] | null | null | null |
import os
def banner():
os.system("toilet -f font -F metal Heroku")
os.system("cd javascript;node menu.js")
os.system("cd bash;bash start.sh")
banner()
| 17.777778
| 45
| 0.68125
| 27
| 160
| 4.037037
| 0.666667
| 0.220183
| 0.183486
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.15625
| 160
| 8
| 46
| 20
| 0.807407
| 0
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| 0.48125
| 0
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| 0
| 1
| 0.166667
| true
| 0
| 0.166667
| 0
| 0.333333
| 0
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| null | 1
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| 0
| 0
| 0
| 0
|
0
| 5
|
9972dfb04979768e7e1f5ad4c5e7b9f7d2beeef7
| 2,094
|
py
|
Python
|
week_7/lab_1.py
|
assassinen/python_openedu
|
50805715f99cdc84fe1dd5d7007a13e37668ab6f
|
[
"Apache-2.0"
] | null | null | null |
week_7/lab_1.py
|
assassinen/python_openedu
|
50805715f99cdc84fe1dd5d7007a13e37668ab6f
|
[
"Apache-2.0"
] | null | null | null |
week_7/lab_1.py
|
assassinen/python_openedu
|
50805715f99cdc84fe1dd5d7007a13e37668ab6f
|
[
"Apache-2.0"
] | null | null | null |
__author__ = 'NovikovII'
#!/usr/bin/env python3
# -*- coding: utf-8 -*-
# import sqlite3
# con = sqlite3.connect('books01.db')
# con.close()
# import sqlite3
# import os
# os.chdir(r'C:\shareFolder\Dropbox\python_openedu\week_7')
# print(os.getcwd())
# con=sqlite3.connect('books01.db')
# con.close()
#
#
# import sqlite3
# import os
# #os.chdir(r'g:\sqlite_opros_6')
# con=sqlite3.connect('books02.db')
# cur=con.cursor()
# sql='''
# CREATE TABLE IF NOT EXISTS author (
# id_author INTEGER PRIMARY KEY AUTOINCREMENT,
# author_name TEXT,
# author_descr TEXT
# );
# '''
# cur.executescript(sql)
# cur.close()
# con.close()
# import sqlite3
# import os
# #os.chdir(r'g:\sqlite_opros_6')
# con=sqlite3.connect('books02.db')
# cur=con.cursor()
# sql='''
# CREATE TABLE IF NOT EXISTS author (
# id_author INTEGER PRIMARY KEY AUTOINCREMENT,
# author_name TEXT,
# author_descr TEXT
# );
# CREATE TABLE IF NOT EXISTS style (
# id_style INTEGER PRIMARY KEY AUTOINCREMENT,
# style_name TEXT
# );
# CREATE TABLE IF NOT EXISTS book (
# id_book INTEGER PRIMARY KEY AUTOINCREMENT,
# id_author INTEGER,
# id_style INTEGER,
# title TEXT,
# description TEXT,
# number_ex INTEGER
# );
# '''
# cur.executescript(sql)
# cur.close()
# con.close()
# import sqlite3
# import os
# #os.chdir(r'g:\sqlite_opros_6')
# con=sqlite3.connect('books02.db')
# cur = con.cursor()
# sql = """\
# INSERT INTO author (author_name, author_descr)
# VALUES ('Chukovskiy', 'Pisatel')
# """
#
# cur.executescript(sql)
# cur.close()
# con.commit()
# con.close()
# import sqlite3
# import os
# #os.chdir(r'g:\sqlite_opros_6')
# con=sqlite3.connect('books02.db')
# cur = con.cursor()
# sql = """\
# select * from author
# """
#
# cur.executescript(sql)
# cur.close()
# con.commit()
# con.close()
import sqlite3
import os
#os.chdir(r'g:\sqlite_opros_6')
con=sqlite3.connect('books02.db')
cur=con.cursor()
sql='''
CREATE TABLE style IF NOT EXISTS (
id_style INTEGER PRIMARY KEY AUTOINCREMENT,
style_name TEXT
);'''
cur.executescript(sql)
cur.close()
con.close()
| 19.570093
| 59
| 0.664279
| 285
| 2,094
| 4.768421
| 0.224561
| 0.066961
| 0.087564
| 0.092715
| 0.772627
| 0.772627
| 0.74025
| 0.74025
| 0.714496
| 0.640912
| 0
| 0.020654
| 0.167622
| 2,094
| 107
| 60
| 19.570093
| 0.759036
| 0.787488
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| false
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| 0.153846
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| 1
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| null | 0
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| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
41e4620427c5012ca8eafdeb5bfc1ded0401e9ec
| 150
|
py
|
Python
|
calculation/gmhazard_calc/gmhazard_calc/scenario/__init__.py
|
ucgmsim/gmhazard
|
d3d90b4c94b3d9605597a3efeccc8523a1e50c0e
|
[
"MIT"
] | null | null | null |
calculation/gmhazard_calc/gmhazard_calc/scenario/__init__.py
|
ucgmsim/gmhazard
|
d3d90b4c94b3d9605597a3efeccc8523a1e50c0e
|
[
"MIT"
] | 8
|
2021-10-13T02:33:23.000Z
|
2022-03-29T21:01:08.000Z
|
calculation/gmhazard_calc/gmhazard_calc/scenario/__init__.py
|
ucgmsim/gmhazard
|
d3d90b4c94b3d9605597a3efeccc8523a1e50c0e
|
[
"MIT"
] | null | null | null |
from .scenario import run_ensemble_scenario, filter_ruptures
from .ScenarioResult import EnsembleScenarioResult, BranchScenarioResult, ScenarioResult
| 50
| 88
| 0.893333
| 14
| 150
| 9.357143
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.073333
| 150
| 2
| 89
| 75
| 0.942446
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
| 0
| 1
| 0
| 0
| null | 0
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| 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
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| 0
| 0
| 0
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| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
513bdaed9c8611de52f39818e6308c92b66efb30
| 119
|
py
|
Python
|
sgnlp/models/lif_3way_ap/__init__.py
|
jonheng/sgnlp
|
aeee85b78de2e449ca1dc6b18686a060cb938d07
|
[
"MIT"
] | null | null | null |
sgnlp/models/lif_3way_ap/__init__.py
|
jonheng/sgnlp
|
aeee85b78de2e449ca1dc6b18686a060cb938d07
|
[
"MIT"
] | null | null | null |
sgnlp/models/lif_3way_ap/__init__.py
|
jonheng/sgnlp
|
aeee85b78de2e449ca1dc6b18686a060cb938d07
|
[
"MIT"
] | null | null | null |
from .config import LIF3WayAPConfig
from .modeling import LIF3WayAPModel
from .preprocess import LIF3WayAPPreprocessor
| 29.75
| 45
| 0.87395
| 12
| 119
| 8.666667
| 0.666667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.028037
| 0.10084
| 119
| 3
| 46
| 39.666667
| 0.943925
| 0
| 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
| 1
| 0
|
0
| 5
|
5a970a4c88c3df8348f5365785d4400dd3e4160e
| 83
|
py
|
Python
|
data_hacking/simple_stats/__init__.py
|
c4pr1c3/data_hacking
|
a2c746375a2b8704eb8f263f6e2b3250ad7ec0ab
|
[
"MIT"
] | 1
|
2022-02-19T11:36:37.000Z
|
2022-02-19T11:36:37.000Z
|
data_hacking/simple_stats/__init__.py
|
c4pr1c3/data_hacking
|
a2c746375a2b8704eb8f263f6e2b3250ad7ec0ab
|
[
"MIT"
] | null | null | null |
data_hacking/simple_stats/__init__.py
|
c4pr1c3/data_hacking
|
a2c746375a2b8704eb8f263f6e2b3250ad7ec0ab
|
[
"MIT"
] | 3
|
2017-09-23T01:17:54.000Z
|
2022-03-23T13:11:37.000Z
|
'''Package for the Simple Statistical Functionality'''
from .simple_stats import *
| 27.666667
| 54
| 0.783133
| 10
| 83
| 6.4
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.120482
| 83
| 2
| 55
| 41.5
| 0.876712
| 0.578313
| 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
| 1
| 0
|
0
| 5
|
5aac7332aa6cf8d07e3b45b4ef14ddbd65244e8f
| 172
|
py
|
Python
|
app/main/__init__.py
|
Bobfrat/sequence-alignment-app
|
64cbd790705ccd5a328da2798445e7b9ce65d647
|
[
"BSD-3-Clause"
] | null | null | null |
app/main/__init__.py
|
Bobfrat/sequence-alignment-app
|
64cbd790705ccd5a328da2798445e7b9ce65d647
|
[
"BSD-3-Clause"
] | null | null | null |
app/main/__init__.py
|
Bobfrat/sequence-alignment-app
|
64cbd790705ccd5a328da2798445e7b9ce65d647
|
[
"BSD-3-Clause"
] | null | null | null |
#!/usr/bin/env python
'''
app/main/__init__.py
'''
from flask import Blueprint
main = Blueprint('main', __name__, static_folder="../ui/build")
from app.main import views
| 17.2
| 63
| 0.715116
| 25
| 172
| 4.56
| 0.72
| 0.122807
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.116279
| 172
| 9
| 64
| 19.111111
| 0.75
| 0.238372
| 0
| 0
| 0
| 0
| 0.121951
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.666667
| 0
| 0.666667
| 0.666667
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 1
|
0
| 5
|
5ac2541df527bc46ac029ad16c61c9d293dbe8d7
| 184
|
py
|
Python
|
src/core/sessions/buffers/buffers/__init__.py
|
Oire/TheQube
|
fcfd8a68b15948e0740642d635db24adef8cc314
|
[
"MIT"
] | 21
|
2015-08-02T21:26:14.000Z
|
2019-12-27T09:57:44.000Z
|
src/core/sessions/buffers/buffers/__init__.py
|
Oire/TheQube
|
fcfd8a68b15948e0740642d635db24adef8cc314
|
[
"MIT"
] | 34
|
2015-01-12T00:38:14.000Z
|
2020-08-31T11:19:37.000Z
|
src/core/sessions/buffers/buffers/__init__.py
|
Oire/TheQube
|
fcfd8a68b15948e0740642d635db24adef8cc314
|
[
"MIT"
] | 15
|
2015-03-24T15:42:30.000Z
|
2020-09-24T20:26:42.000Z
|
# -*- coding: utf-8 -*-
from buffer import Buffer
from dismissable import Dismissable
from updating import Updating
from filtered import Filtered
from messages import Messages
| 23
| 36
| 0.771739
| 23
| 184
| 6.173913
| 0.434783
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.006623
| 0.179348
| 184
| 7
| 37
| 26.285714
| 0.933775
| 0.11413
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
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| 1
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| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
5ae16f89ad51d4da0e6182f2806df670211dceec
| 53
|
py
|
Python
|
src/exceptions/action_not_supported_exception.py
|
mehsoy/jaws
|
b79723c1fc549741494ebf5d948e94a44e971f2a
|
[
"MIT"
] | 1
|
2019-06-17T17:01:17.000Z
|
2019-06-17T17:01:17.000Z
|
src/exceptions/action_not_supported_exception.py
|
mehsoy/jaws
|
b79723c1fc549741494ebf5d948e94a44e971f2a
|
[
"MIT"
] | 7
|
2021-02-08T20:46:15.000Z
|
2021-09-08T02:12:59.000Z
|
src/exceptions/action_not_supported_exception.py
|
mehsoy/jaws
|
b79723c1fc549741494ebf5d948e94a44e971f2a
|
[
"MIT"
] | null | null | null |
class ActionNotSupportedException(Exception):
pass
| 13.25
| 45
| 0.849057
| 4
| 53
| 11.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.09434
| 53
| 3
| 46
| 17.666667
| 0.9375
| 0
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| 0
| 1
| 0
| true
| 0.5
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| 0.5
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| 1
| null | 0
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| 0
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| 0
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| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
5af4788582a4125cb61283099afaef85b9b25989
| 113
|
py
|
Python
|
auto_events/form/__init__.py
|
fedecech/form_automator
|
b20364803b000333b24ce55ef8c01a18d7b47f23
|
[
"MIT"
] | null | null | null |
auto_events/form/__init__.py
|
fedecech/form_automator
|
b20364803b000333b24ce55ef8c01a18d7b47f23
|
[
"MIT"
] | null | null | null |
auto_events/form/__init__.py
|
fedecech/form_automator
|
b20364803b000333b24ce55ef8c01a18d7b47f23
|
[
"MIT"
] | null | null | null |
from .Form import Form
from .FormComponent import FormComponent
from .FormComponentType import FormComponentType
| 28.25
| 48
| 0.867257
| 12
| 113
| 8.166667
| 0.416667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.106195
| 113
| 3
| 49
| 37.666667
| 0.970297
| 0
| 0
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| 0
| 0
| 0
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| 0
| 0
| 0
| 0
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| 0
| true
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| null | 0
| 0
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| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
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| 1
| 0
| 0
| 0
| 0
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| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
8503be01b49daa229fd55657a591f2aa16a62ebd
| 188
|
py
|
Python
|
app/models/__init__.py
|
jattoabdul/vanhack-cms
|
ab2cb054e35765531833afd98051027d891baf10
|
[
"MIT"
] | null | null | null |
app/models/__init__.py
|
jattoabdul/vanhack-cms
|
ab2cb054e35765531833afd98051027d891baf10
|
[
"MIT"
] | null | null | null |
app/models/__init__.py
|
jattoabdul/vanhack-cms
|
ab2cb054e35765531833afd98051027d891baf10
|
[
"MIT"
] | null | null | null |
from .admin import Admin
from .student import Student
from .event import Event
from .lecture import Lecture
from .student_event import StudentEvent
from .lecture_admin import LectureAdmin
| 26.857143
| 39
| 0.840426
| 26
| 188
| 6
| 0.307692
| 0.141026
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12766
| 188
| 6
| 40
| 31.333333
| 0.95122
| 0
| 0
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| 0
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| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
85065a61a919d471077a777cc54e76b7a05a3a5e
| 40
|
py
|
Python
|
modules_imports_names/module.py
|
UWSEDS/lecture-materials
|
42f24ce191efc4a193ac4a84e067519045f7f7c3
|
[
"BSD-2-Clause"
] | null | null | null |
modules_imports_names/module.py
|
UWSEDS/lecture-materials
|
42f24ce191efc4a193ac4a84e067519045f7f7c3
|
[
"BSD-2-Clause"
] | null | null | null |
modules_imports_names/module.py
|
UWSEDS/lecture-materials
|
42f24ce191efc4a193ac4a84e067519045f7f7c3
|
[
"BSD-2-Clause"
] | 4
|
2020-10-09T01:07:19.000Z
|
2020-12-11T23:11:35.000Z
|
print("Inside module.py")
print("hai!")
| 13.333333
| 25
| 0.675
| 6
| 40
| 4.5
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.075
| 40
| 2
| 26
| 20
| 0.72973
| 0
| 0
| 0
| 0
| 0
| 0.5
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
8518659d193d15da1f865318d888cc09f41636db
| 6,680
|
py
|
Python
|
API_Scrapers/apiscraper_gamersclub.py
|
filipefborba/GamersNetwork
|
28f7254293192fb80f7d84b5e936893fa70ec474
|
[
"MIT"
] | null | null | null |
API_Scrapers/apiscraper_gamersclub.py
|
filipefborba/GamersNetwork
|
28f7254293192fb80f7d84b5e936893fa70ec474
|
[
"MIT"
] | null | null | null |
API_Scrapers/apiscraper_gamersclub.py
|
filipefborba/GamersNetwork
|
28f7254293192fb80f7d84b5e936893fa70ec474
|
[
"MIT"
] | null | null | null |
import requests
import json
from bs4 import BeautifulSoup, SoupStrainer
from get_match_html import get_partida_html
#pip install bs4
#pip install lxml
def get_partidas_campeonato(id):
url = "https://gamersclub.com.br/campeonatos/csgo/" + str(id)
querystring = {"pag":"partidas"}
headers = {
'Referer': "https://gamersclub.com.br/campeonatos/csgo/846",
'X-Requested-With': "XMLHttpRequest",
'cache-control': "no-cache"
}
response = requests.request("GET", url, headers=headers, params=querystring)
partidas_html = response.text
camp_partidas = {id: {}}
soup = BeautifulSoup(partidas_html, features="lxml")
for link in soup.find_all('a'):
partida_id = link.get("href").split("/")[-1:][0]
if (partida_id not in camp_partidas[id]) and (partida_id != None) and (not partida_id.startswith("#")) :
camp_partidas[id][partida_id] = {}
return camp_partidas
def get_partida(camp_id, partida_id):
url = "https://gamersclub.com.br/api/ebacon2/stats/scoreboards/{}/{}".format(str(camp_id), str(partida_id))
headers = {
'Referer': "https://gamersclub.com.br/campeonatos/csgo/1257/partida/104124",
'Cookie': "__utma=203582342.232122176.1489463720.1497671483.1497749677.12; _ga=GA1.3.232122176.1489463720; rdtrk=%7B%22id%22%3A%2219e6bdb6-ab8f-4549-bf65-45ff0c86e846%22%7D; intercom-lou-gp4gdmdo=1; __trf.src=encoded_eyJmaXJzdF9zZXNzaW9uIjp7InZhbHVlIjoiMjAzNTgyMzQyLjE0ODk0NjM3MjEuMS4xLnV0bWNzcj0oZGlyZWN0KXx1dG1jY249KGRpcmVjdCl8dXRtY21kPShub25lKSIsImV4dHJhX3BhcmFtcyI6e319LCJjdXJyZW50X3Nlc3Npb24iOnsidmFsdWUiOiJodHRwczovL2dhbWVyc2NsdWIuY29tLmJyLyIsImV4dHJhX3BhcmFtcyI6e319LCJjcmVhdGVkX2F0IjoxNTE4MTM1OTYwMzAwfQ==; __cfduid=dfaae443a782f1d6d0b715bebbb0338321522639930; SL_C_23361dd035530_KEY=a14d3638cda988422792e3613234743b983fdd9e; crisp-client%2Fsession%2F839282a3-c2c1-4fd3-b493-0f2d3c1e2102=session_91c09cdd-f616-4e12-9599-8aad4f09988d; crisp-client%2Fsession%2F839282a3-c2c1-4fd3-b493-0f2d3c1e2102%2Fc3b2fd43f122359ddf0a576a7d4d75ab74b4d92f9feb92c94eeb2406a6d36192=session_91c09cdd-f616-4e12-9599-8aad4f09988d; SL_C_23361dd035530_VID=Nm59QhW-6TYP; SL_C_23361dd035530_SID=hMyy703pm5eY; gclubsess=fe6dc36080d6083b0e1060909e4d5a51218b6dd8; _gid=GA1.3.168545321.1543697640; _fbp=fb.2.1543697640249.576304885",
'cache-control': "no-cache",
}
response = requests.request("GET", url, headers=headers)
resultados_partida = response.json()
return resultados_partida
try:
campeonatos_ids = [846, 881, 915, 957, 1008, 1019, 1039, 1079, 1116, 1164, 1209, 1257]
campeonatos = {}
for str(camp_id) in campeonatos_ids:
camp = get_partidas_campeonato(camp_id)
campeonatos.update(camp)
#campeonatos = {846: {'66817': {}, '66818': {}, '66386': {}, '66819': {}, '66387': {}, '66820': {}, '66385': {}, '66920': {}, '66885': {}, '66884': {}, '66919': {}, '66388': {}, '66917': {}, '66918': {}, '67081': {}, '67082': {}, '66981': {}, '66921': {}, '67083': {}, '67115': {}, '67119': {}, '67117': {}, '67116': {}, '67118': {}, '68711': {}, '68712': {}, '68775': {}}, 881: {'69447': {}, '69448': {}, '69449': {}, '69456': {}, '69455': {}, '69452': {}, '69454': {}, '69451': {}, '69489': {}, '69492': {}, '69490': {}, '69633': {}, '69493': {}, '69494': {}, '69495': {}, '69488': {}, '69634': {}, '69630': {}, '69631': {}, '69632': {}, '70936': {}, '71172': {}, '70935': {}, '70934': {}, '71187': {}, '71188': {}, '71704': {}}, 915: {'73003': {}, '73004': {}, '73007': {}, '73005': {}, '73076': {}, '73008': {}, '73011': {}, '73009': {}, '73010': {}, '73194': {}, '73195': {}, '73197': {}, '73196': {}, '73212': {}, '73213': {}, '73405': {}, '73272': {}, '73273': {}, '73599': {}, '73598': {}, '73406': {}, '73637': {}, '73636': {}, '73634': {}, '73600': {}, '76347': {}, '75972': {}, '76382': {}}, 957: {'76641': {}, '77119': {}, '77117': {}, '77120': {}, '76642': {}, '77121': {}, '76643': {}, '76640': {}, '77245': {}, '77248': {}, '77243': {}, '77242': {}, '77240': {}, '77247': {}, '77241': {}, '77244': {}, '77643': {}, '77611': {}, '77642': {}, '77610': {}, '79525': {}, '79524': {}, '77645': {}, '79597': {}, '79980': {}, '79981': {}, '80325': {}}, 1008: {'80886': {}, '80888': {}, '80889': {}, '80890': {}, '80892': {}, '80893': {}, '80887': {}, '80891': {}, '80960': {}, '80895': {}, '80961': {}, '80894': {}}, 1019: {'81425': {}, '81432': {}, '81430': {}, '81435': {}, '81428': {}, '81436': {}, '81427': {}, '81431': {}, '81429': {}, '81433': {}, '81426': {}, '81434': {}, '82905': {}, '82906': {}, '82908': {}, '82907': {}, '82950': {}, '82951': {}, '83230': {}}, 1039: {'84509': {}, '84510': {}, '84511': {}, '84512': {}, '84513': {}, '84514': {}, '84515': {}, '84516': {}, '84517': {}, '84518': {}, '84519': {}, '84520': {}, '84693': {}, '84696': {}, '84694': {}, '84695': {}, '84698': {}, '84699': {}, '85588': {}}, 1079: {'88339': {}, '88343': {}, '88340': {}, '88348': {}, '88337': {}, '88344': {}, '88342': {}, '88347': {}, '88338': {}, '88345': {}, '88341': {}, '88346': {}, '88494': {}, '88496': {}, '88493': {}, '88495': {}, '88504': {}, '88505': {}, '88628': {}}, 1116: {'91382': {}, '91392': {}, '91385': {}, '91387': {}, '91391': {}, '91381': {}, '91386': {}, '91388': {}, '91383': {}, '91389': {}, '91384': {}, '91390': {}, '91598': {}, '91599': {}, '91607': {}, '91608': {}, '91703': {}}, 1164: {'96587': {}, '96590': {}, '96586': {}, '96595': {}, '96589': {}, '96593': {}, '96584': {}, '96592': {}, '96585': {}, '96588': {}, '96594': {}, '96591': {}, '96985': {}, '96986': {}, '97064': {}, '97065': {}, '97521': {}}, 1209: {'101120': {}, '101117': {}, '101143': {}, '101138': {}, '101119': {}, '101118': {}, '101139': {}, '101142': {}, '101116': {}, '101121': {}, '101140': {}, '101141': {}, '102020': {}, '102019': {}, '102044': {}, '102047': {}, '102261': {}}, 1257: {'104124': {}, '104125': {}, '103994': {}, '103992': {}, '103988': {}, '103986': {}, '104127': {}, '104126': {}, '103993': {}, '103987': {}, '104128': {}, '104129': {}, '105105': {}, '105106': {}, '105235': {}, '105240': {}, '105376': {}}}
for camp_id in campeonatos:
for partida_id in campeonatos[camp_id]:
if camp_id >= 1116:
partida = get_partida(camp_id, partida_id)
else:
partida = get_partida_html(camp_id, partida_id)
campeonatos[camp_id][partida_id] = partida
with open("campeonatos_completo.json", 'w') as fp:
json.dump(campeonatos, fp)
except Exception as e:
print(e)
print("Um erro ocorreu. Salvando o restante...")
with open("campeonatos_incompleto.json", 'w') as fp:
json.dump(campeonatos, fp)
| 99.701493
| 3,344
| 0.564371
| 629
| 6,680
| 5.887122
| 0.653418
| 0.026735
| 0.014853
| 0.021604
| 0.1569
| 0.1569
| 0.10532
| 0.10532
| 0.033486
| 0.033486
| 0
| 0.321498
| 0.152545
| 6,680
| 66
| 3,345
| 101.212121
| 0.332627
| 0.504341
| 0
| 0.078431
| 0
| 0.019608
| 0.460538
| 0.343816
| 0
| 0
| 0
| 0
| 0
| 0
| null | null | 0
| 0.078431
| null | null | 0.039216
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
51a6517a7a2a18e1f5a2996d6a7f6710c0563839
| 30
|
py
|
Python
|
application/services/__init__.py
|
raphaelbh/timezone-api
|
bd273614685065a74df0c577673b43b42bae813c
|
[
"MIT"
] | 2
|
2022-02-14T19:52:34.000Z
|
2022-02-14T19:52:39.000Z
|
application/services/__init__.py
|
raphaelbh/timezone-api
|
bd273614685065a74df0c577673b43b42bae813c
|
[
"MIT"
] | null | null | null |
application/services/__init__.py
|
raphaelbh/timezone-api
|
bd273614685065a74df0c577673b43b42bae813c
|
[
"MIT"
] | null | null | null |
from . import timezone_service
| 30
| 30
| 0.866667
| 4
| 30
| 6.25
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.1
| 30
| 1
| 30
| 30
| 0.925926
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
cfad419ee40a8dc8ac1df4ad10d5679f1daa4135
| 91
|
py
|
Python
|
tests/parser/edbidb.5.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/edbidb.5.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
tests/parser/edbidb.5.test.py
|
veltri/DLV2
|
944aaef803aa75e7ec51d7e0c2b0d964687fdd0e
|
[
"Apache-2.0"
] | null | null | null |
input = """
a(1).
a(2) :- true.
true.
"""
output = """
a(1).
a(2) :- true.
true.
"""
| 8.272727
| 14
| 0.384615
| 14
| 91
| 2.5
| 0.428571
| 0.114286
| 0.171429
| 0.228571
| 0.685714
| 0.685714
| 0
| 0
| 0
| 0
| 0
| 0.059701
| 0.263736
| 91
| 10
| 15
| 9.1
| 0.462687
| 0
| 0
| 0.8
| 0
| 0
| 0.635294
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| 0
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
cfb6aa456d2c2752350fbe4ccb98ce7dd3d89265
| 95
|
py
|
Python
|
torchrecipes/audio/source_separation/conf/__init__.py
|
nateanl/recipes-1
|
3b46a7479508608f73b6f24deffdc8fcffd25ee5
|
[
"BSD-3-Clause"
] | null | null | null |
torchrecipes/audio/source_separation/conf/__init__.py
|
nateanl/recipes-1
|
3b46a7479508608f73b6f24deffdc8fcffd25ee5
|
[
"BSD-3-Clause"
] | null | null | null |
torchrecipes/audio/source_separation/conf/__init__.py
|
nateanl/recipes-1
|
3b46a7479508608f73b6f24deffdc8fcffd25ee5
|
[
"BSD-3-Clause"
] | null | null | null |
#!/usr/bin/env python3
import torchrecipes.audio.source_separation.datamodule.librimix # noqa
| 31.666667
| 71
| 0.821053
| 12
| 95
| 6.416667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.011364
| 0.073684
| 95
| 2
| 72
| 47.5
| 0.863636
| 0.273684
| 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
| 1
| 0
|
0
| 5
|
cfca8c4ad5c1bc9a4f8bb36916d1e68974f19aea
| 32
|
py
|
Python
|
python/testData/inspections/PyUnresolvedReferencesInspection/NamespacePackageNameDoesntMatchFileName/google/protobuf/service.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 2
|
2019-04-28T07:48:50.000Z
|
2020-12-11T14:18:08.000Z
|
python/testData/inspections/PyUnresolvedReferencesInspection/NamespacePackageNameDoesntMatchFileName/google/protobuf/service.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 173
|
2018-07-05T13:59:39.000Z
|
2018-08-09T01:12:03.000Z
|
python/testData/inspections/PyUnresolvedReferencesInspection/NamespacePackageNameDoesntMatchFileName/google/protobuf/service.py
|
truthiswill/intellij-community
|
fff88cfb0dc168eea18ecb745d3e5b93f57b0b95
|
[
"Apache-2.0"
] | 2
|
2020-03-15T08:57:37.000Z
|
2020-04-07T04:48:14.000Z
|
class Service(object):
pass
| 10.666667
| 22
| 0.6875
| 4
| 32
| 5.5
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.21875
| 32
| 2
| 23
| 16
| 0.88
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.5
| 0
| 0
| 0.5
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
|
0
| 5
|
320dd67193a6a4adc37b0b547b4128d8d24fd8b6
| 198
|
py
|
Python
|
components.py
|
Aspect13/scheduling
|
95d133efa49c10ab9d7c543631df9e3ce8e6302b
|
[
"Apache-2.0"
] | null | null | null |
components.py
|
Aspect13/scheduling
|
95d133efa49c10ab9d7c543631df9e3ce8e6302b
|
[
"Apache-2.0"
] | null | null | null |
components.py
|
Aspect13/scheduling
|
95d133efa49c10ab9d7c543631df9e3ce8e6302b
|
[
"Apache-2.0"
] | 1
|
2022-01-20T09:49:33.000Z
|
2022-01-20T09:49:33.000Z
|
from flask import render_template
def render_security_test_create(context, slot, payload):
return render_template(
'scheduling:security_test_create.html',
config=payload
)
| 22
| 56
| 0.737374
| 23
| 198
| 6.043478
| 0.695652
| 0.201439
| 0.258993
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.19697
| 198
| 8
| 57
| 24.75
| 0.874214
| 0
| 0
| 0
| 0
| 0
| 0.181818
| 0.181818
| 0
| 0
| 0
| 0
| 0
| 1
| 0.166667
| false
| 0
| 0.166667
| 0.166667
| 0.5
| 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
| 1
| 0
| 0
|
0
| 5
|
3225b50f657517d6323b186f71d8dfdce19be319
| 6,599
|
py
|
Python
|
modules/dbnd/test_dbnd/tracking/user_commands/test_tracking_datasets.py
|
busunkim96/dbnd
|
0191fdcd4c4fbd35006f1026d1a55b2abab9097b
|
[
"Apache-2.0"
] | 224
|
2020-01-02T10:46:37.000Z
|
2022-03-02T13:54:08.000Z
|
modules/dbnd/test_dbnd/tracking/user_commands/test_tracking_datasets.py
|
busunkim96/dbnd
|
0191fdcd4c4fbd35006f1026d1a55b2abab9097b
|
[
"Apache-2.0"
] | 16
|
2020-03-11T09:37:58.000Z
|
2022-01-26T10:22:08.000Z
|
modules/dbnd/test_dbnd/tracking/user_commands/test_tracking_datasets.py
|
busunkim96/dbnd
|
0191fdcd4c4fbd35006f1026d1a55b2abab9097b
|
[
"Apache-2.0"
] | 24
|
2020-03-24T13:53:50.000Z
|
2022-03-22T11:55:18.000Z
|
import json
import pytest
from more_itertools import one
from dbnd import dataset_op_logger, log_dataset_op, task
from dbnd._core.constants import DbndDatasetOperationType, DbndTargetOperationStatus
from dbnd._core.tracking.schemas.metrics import Metric
from dbnd.testing.helpers_mocks import set_tracking_context
from targets import target
from test_dbnd.tracking.tracking_helpers import (
get_log_datasets,
get_log_metrics,
get_log_targets,
)
@pytest.mark.usefixtures(set_tracking_context.__name__)
class TestTrackingDatasets(object):
def test_log_dataset(self, mock_channel_tracker):
@task()
def task_with_log_datasets():
log_dataset_op(
"location://path/to/value.csv", DbndDatasetOperationType.read
)
task_with_log_datasets()
log_dataset_arg = one(get_log_datasets(mock_channel_tracker))
assert log_dataset_arg.operation_path == "location://path/to/value.csv"
assert log_dataset_arg.operation_type == DbndDatasetOperationType.read
assert log_dataset_arg.operation_status == DbndTargetOperationStatus.OK
assert log_dataset_arg.value_preview == ""
assert log_dataset_arg.data_dimensions is None
assert log_dataset_arg.data_schema is None
# no metrics reported
log_metrics_args = list(get_log_metrics(mock_channel_tracker))
assert len(log_metrics_args) == 0
def test_log_dataset_with_wrapper(self, mock_channel_tracker, pandas_data_frame):
@task()
def task_with_log_dataset_wrapper():
with dataset_op_logger(
op_path=target("/path/to/value.csv"), op_type="read",
) as logger:
ans = 42
logger.set(data=pandas_data_frame)
task_with_log_dataset_wrapper()
log_dataset_arg = one(get_log_datasets(mock_channel_tracker))
assert log_dataset_arg.operation_path == "/path/to/value.csv"
assert log_dataset_arg.operation_type == DbndDatasetOperationType.read
assert log_dataset_arg.operation_status == DbndTargetOperationStatus.OK
assert log_dataset_arg.value_preview is not None
assert log_dataset_arg.data_dimensions == (5, 3)
assert set(json.loads(log_dataset_arg.data_schema).keys()) == {
"columns",
"dtypes",
"shape",
"size.bytes",
"type",
}
def test_failed_target_with_wrapper(self, mock_channel_tracker, pandas_data_frame):
@task()
def task_with_log_dataset_wrapper():
with dataset_op_logger(
op_path=target("/path/to/value.csv"),
data=pandas_data_frame,
op_type="write",
) as logger:
ans = 42
ans / 0
try:
task_with_log_dataset_wrapper()
except Exception:
pass
log_dataset_arg = one(get_log_datasets(mock_channel_tracker))
assert log_dataset_arg.operation_path == "/path/to/value.csv"
assert log_dataset_arg.operation_type == DbndDatasetOperationType.write
assert log_dataset_arg.operation_status == DbndTargetOperationStatus.NOK
assert log_dataset_arg.value_preview is not None
assert log_dataset_arg.data_dimensions == (5, 3)
assert set(json.loads(log_dataset_arg.data_schema).keys()) == {
"columns",
"dtypes",
"shape",
"size.bytes",
"type",
}
def test_failed_target(self, mock_channel_tracker):
@task()
def task_with_log_datasets():
log_dataset_op(
"location://path/to/value.csv",
"read", # Check passing str values too
success=False,
)
task_with_log_datasets()
log_dataset_arg = one(get_log_datasets(mock_channel_tracker))
assert log_dataset_arg.operation_path == "location://path/to/value.csv"
assert log_dataset_arg.operation_type == DbndDatasetOperationType.read
assert log_dataset_arg.operation_status == DbndTargetOperationStatus.NOK
assert log_dataset_arg.value_preview == ""
assert log_dataset_arg.data_dimensions is None
assert log_dataset_arg.data_schema is None
log_metrics_args = get_log_metrics(mock_channel_tracker)
assert len(list(log_metrics_args)) == 0
def test_with_actual_op_path(self, mock_channel_tracker):
@task()
def task_with_log_datasets():
a_target = target("/path/to/value.csv")
log_dataset_op(a_target, DbndDatasetOperationType.read)
task_with_log_datasets()
log_dataset_arg = one(get_log_datasets(mock_channel_tracker))
assert log_dataset_arg.operation_path == "/path/to/value.csv"
assert log_dataset_arg.operation_type == DbndDatasetOperationType.read
assert log_dataset_arg.operation_status == DbndTargetOperationStatus.OK
assert log_dataset_arg.value_preview == ""
assert log_dataset_arg.data_dimensions is None
assert log_dataset_arg.data_schema is None
log_metrics_args = get_log_metrics(mock_channel_tracker)
assert len(list(log_metrics_args)) == 0
def test_path_with_data_meta(self, mock_channel_tracker, pandas_data_frame):
@task()
def task_with_log_datasets():
log_dataset_op(
"/path/to/value.csv",
DbndDatasetOperationType.read,
data=pandas_data_frame,
with_preview=True,
with_schema=True,
)
task_with_log_datasets()
log_dataset_arg = one(get_log_datasets(mock_channel_tracker))
assert log_dataset_arg.operation_path == "/path/to/value.csv"
assert log_dataset_arg.operation_type == DbndDatasetOperationType.read
assert log_dataset_arg.operation_status == DbndTargetOperationStatus.OK
assert log_dataset_arg.value_preview is not None
assert log_dataset_arg.data_dimensions == (5, 3)
assert set(json.loads(log_dataset_arg.data_schema).keys()) == {
"columns",
"dtypes",
"shape",
"size.bytes",
"type",
}
log_metrics_args = get_log_metrics(mock_channel_tracker)
metrics_names = {metric_row["metric"].key for metric_row in log_metrics_args}
assert metrics_names == {
"path.to.schema",
"path.to.shape0",
"path.to.shape1",
"path.to",
}
| 37.925287
| 87
| 0.660858
| 783
| 6,599
| 5.176245
| 0.137931
| 0.130767
| 0.134715
| 0.1547
| 0.779176
| 0.761905
| 0.746114
| 0.746114
| 0.736245
| 0.720207
| 0
| 0.003269
| 0.258372
| 6,599
| 173
| 88
| 38.144509
| 0.824888
| 0.007274
| 0
| 0.62069
| 0
| 0
| 0.064142
| 0.017104
| 0
| 0
| 0
| 0
| 0.275862
| 1
| 0.082759
| false
| 0.006897
| 0.062069
| 0
| 0.151724
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
5c4e773fe46ed33728bf1c32029d239fd38c681d
| 80
|
py
|
Python
|
Starting Out with Python/Chapter 2/2.3 Displaying Output with the print Function/2-2_double_quotes.py
|
jesushilarioh/Python
|
79c8b0d2c4f0ec9cccee26dcd563de0c55ba283e
|
[
"MIT"
] | null | null | null |
Starting Out with Python/Chapter 2/2.3 Displaying Output with the print Function/2-2_double_quotes.py
|
jesushilarioh/Python
|
79c8b0d2c4f0ec9cccee26dcd563de0c55ba283e
|
[
"MIT"
] | null | null | null |
Starting Out with Python/Chapter 2/2.3 Displaying Output with the print Function/2-2_double_quotes.py
|
jesushilarioh/Python
|
79c8b0d2c4f0ec9cccee26dcd563de0c55ba283e
|
[
"MIT"
] | null | null | null |
print("Kate Austen")
print("123 Full Circle Drive")
print("Asheville, NC 28899")
| 26.666667
| 30
| 0.7375
| 12
| 80
| 4.916667
| 0.833333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.111111
| 0.1
| 80
| 3
| 31
| 26.666667
| 0.708333
| 0
| 0
| 0
| 0
| 0
| 0.62963
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
5cd50937db1449f40e90303bb25e195677b58565
| 71
|
py
|
Python
|
datahub/company/admin/constants.py
|
uktrade/data-hub-api-actions-test
|
a72439dfeb34e4179491db42fea290b9c2afadb1
|
[
"MIT"
] | null | null | null |
datahub/company/admin/constants.py
|
uktrade/data-hub-api-actions-test
|
a72439dfeb34e4179491db42fea290b9c2afadb1
|
[
"MIT"
] | 16
|
2020-04-01T15:25:35.000Z
|
2020-04-14T14:07:30.000Z
|
datahub/company/admin/constants.py
|
uktrade/data-hub-api-actions-test
|
a72439dfeb34e4179491db42fea290b9c2afadb1
|
[
"MIT"
] | null | null | null |
ADMIN_ADD_ADVISER_FROM_SSO_FEATURE_FLAG = 'admin-add-adviser-from-sso'
| 35.5
| 70
| 0.859155
| 12
| 71
| 4.583333
| 0.583333
| 0.290909
| 0.545455
| 0.690909
| 0.8
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.042254
| 71
| 1
| 71
| 71
| 0.808824
| 0
| 0
| 0
| 0
| 0
| 0.366197
| 0.366197
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7a2a306c62af325778b965f704dc45193e65081a
| 24,396
|
py
|
Python
|
jupiter/domain/schedules.py
|
horia141/jupiter
|
2c721d1d44e1cd2607ad9936e54a20ea254741dc
|
[
"MIT"
] | 15
|
2019-05-05T14:34:58.000Z
|
2022-02-25T09:57:28.000Z
|
jupiter/domain/schedules.py
|
horia141/jupiter
|
2c721d1d44e1cd2607ad9936e54a20ea254741dc
|
[
"MIT"
] | 3
|
2020-02-22T16:09:39.000Z
|
2021-12-18T21:33:06.000Z
|
jupiter/domain/schedules.py
|
horia141/jupiter
|
2c721d1d44e1cd2607ad9936e54a20ea254741dc
|
[
"MIT"
] | null | null | null |
"""Module for working with schedules."""
import abc
import typing
from typing import Optional
import pendulum
from pendulum import UTC
from pendulum.tz.timezone import Timezone
from jupiter.domain.adate import ADate
from jupiter.domain.entity_name import EntityName
from jupiter.domain.recurring_task_due_at_day import RecurringTaskDueAtDay
from jupiter.domain.recurring_task_due_at_month import RecurringTaskDueAtMonth
from jupiter.domain.recurring_task_due_at_time import RecurringTaskDueAtTime
from jupiter.domain.recurring_task_period import RecurringTaskPeriod
from jupiter.domain.recurring_task_skip_rule import RecurringTaskSkipRule
from jupiter.domain.timezone import Timezone as DomainTimezone
from jupiter.framework.base.timestamp import Timestamp
class Schedule(abc.ABC):
"""The base class for the schedule descriptors class."""
_should_skip: bool
_actionable_date: Optional[pendulum.Date]
_date: pendulum.Date
_due_date: pendulum.Date
_due_time: Optional[pendulum.DateTime]
_full_name: EntityName
_timeline: str
def __str__(self) -> str:
"""String representation."""
return f"Schedule({self.period} {self.first_day} {self.end_day} {self.timeline})"
def __repr__(self) -> str:
"""String representation."""
return f"Schedule({self.period} {self.first_day} {self.end_day} {self.timeline})"
@staticmethod
def year_two_digits(date: Timestamp) -> str:
"""Get the last two digits (decade and year) from a date."""
return str(date.value.year % 100)
@staticmethod
def month_to_quarter_num(date: pendulum.Date) -> int:
"""Map a date to one of the four quarters from the year."""
month_to_quarter_num = {
1: 1,
2: 1,
3: 1,
4: 2,
5: 2,
6: 2,
7: 3,
8: 3,
9: 3,
10: 4,
11: 4,
12: 4
}
return month_to_quarter_num[date.month]
@staticmethod
def month_to_quarter(date: typing.Union[pendulum.Date, Timestamp]) -> str:
"""Map a date to the name of four quarters from the year."""
month_to_quarter = {
1: "Q1",
2: "Q1",
3: "Q1",
4: "Q2",
5: "Q2",
6: "Q2",
7: "Q3",
8: "Q3",
9: "Q3",
10: "Q4",
11: "Q4",
12: "Q4"
}
return month_to_quarter[date.month]
@staticmethod
def month_to_quarter_start(date: typing.Union[pendulum.Date, Timestamp]) -> int:
"""Map a month in a date to the first month of a quarter of which the date belongs."""
month_to_quarter = {
1: 1,
2: 1,
3: 1,
4: 4,
5: 4,
6: 4,
7: 7,
8: 7,
9: 7,
10: 10,
11: 10,
12: 10
}
return month_to_quarter[date.month]
@staticmethod
def month_to_quarter_end(date: typing.Union[pendulum.Date, Timestamp]) -> int:
"""Map a month in a date to the last month of a quarter of which the date belongs."""
month_to_quarter = {
1: 3,
2: 3,
3: 3,
4: 6,
5: 6,
6: 6,
7: 9,
8: 9,
9: 9,
10: 12,
11: 12,
12: 12
}
return month_to_quarter[date.month]
@staticmethod
def month_to_month(date: typing.Union[pendulum.Date, Timestamp]) -> str:
"""Map a month to the name it has."""
month_to_month = {
1: "Jan",
2: "Feb",
3: "Mar",
4: "Apr",
5: "May",
6: "Jun",
7: "Jul",
8: "Aug",
9: "Sep",
10: "Oct",
11: "Nov",
12: "Dec"
}
return month_to_month[date.month]
@property
def should_skip(self) -> bool:
"""Whether the date should be skipped according to the planning rules."""
return self._should_skip
@property
def actionable_date(self) -> Optional[ADate]:
"""The actionable date for the schedule, if any."""
return ADate.from_date(self._actionable_date) if self._actionable_date else None
@property
def due_time(self) -> ADate:
"""The due time of an event according to the schedule."""
if self._due_time:
return ADate.from_date_and_time(self._due_time)
else:
return ADate.from_date(self._due_date)
@property
def full_name(self) -> EntityName:
"""The full name of the event with the schedule info in it."""
return self._full_name
@property
def timeline(self) -> str:
"""The timeline of an event."""
return self._timeline
@staticmethod
def _skip_helper(skip_rule: RecurringTaskSkipRule, param: int) -> bool:
skip_rule_str = str(skip_rule)
if skip_rule_str == "even":
return param % 2 == 0
elif skip_rule_str == "odd":
return param % 2 != 0
else:
# Why don't you write better programs, bro?
return skip_rule_str.find(str(param)) != -1
@property
@abc.abstractmethod
def period(self) -> RecurringTaskPeriod:
"""The period for the schedule."""
@property
@abc.abstractmethod
def first_day(self) -> ADate:
"""The first day of the interval represented by the schedule block."""
@property
@abc.abstractmethod
def end_day(self) -> ADate:
"""The end day of the interval represented by the schedule block."""
def contains_adate(self, adate: ADate) -> bool:
"""Tests whether a particular datetime is in the schedule block."""
first_day_dt = pendulum.DateTime(self.first_day.year, self.first_day.month, self.first_day.day, tzinfo=UTC)
end_day_dt = \
pendulum.DateTime(self.end_day.year, self.end_day.month, self.end_day.day, tzinfo=UTC).end_of("day")
adate_ts = adate.to_timestamp().value.end_of("day")
return typing.cast(bool, first_day_dt <= adate_ts) and typing.cast(bool, adate_ts <= end_day_dt)
def contains_timestamp(self, timestamp: Timestamp) -> bool:
"""Tests whether a particular datetime is in the schedule block."""
first_day_dt = pendulum.DateTime(self.first_day.year, self.first_day.month, self.first_day.day, tzinfo=UTC)
end_day_dt = \
pendulum.DateTime(self.end_day.year, self.end_day.month, self.end_day.day, tzinfo=UTC).end_of("day")
timestamp = timestamp.value.end_of("day")
return typing.cast(bool, first_day_dt <= timestamp) and typing.cast(bool, timestamp <= end_day_dt)
class DailySchedule(Schedule):
"""A daily schedule."""
def __init__(
self, name: EntityName, right_now: Timestamp, timezone: Timezone,
skip_rule: Optional[RecurringTaskSkipRule] = None,
due_at_time: Optional[RecurringTaskDueAtTime] = None) -> None:
"""Construct a schedule."""
self._date = typing.cast(pendulum.Date, right_now.value.date())
self._due_date = typing.cast(pendulum.Date, right_now.value.date())
self._actionable_date = None
if due_at_time:
self._due_time = pendulum.parse(
"{date} {time}".format(date=self._due_date.to_date_string(), time=due_at_time),
tz=timezone)
else:
self._due_time = None
self._full_name = EntityName("{name} {year}:{month}{day}".format(
name=name, year=self.year_two_digits(right_now), month=self.month_to_month(right_now),
day=right_now.value.day))
self._timeline = self._generate_timeline(right_now)
self._should_skip = self._skip_helper(skip_rule, self._due_date.day_of_week) if skip_rule else False
@property
def period(self) -> RecurringTaskPeriod:
"""The period string."""
return RecurringTaskPeriod.DAILY
@property
def first_day(self) -> ADate:
"""The first day of the interval represented by the schedule block."""
return ADate.from_date(self._due_date)
@property
def end_day(self) -> ADate:
"""The end day of the interval represented by the schedule block."""
return ADate.from_date(self._due_date)
def _generate_timeline(self, right_now: Timestamp) -> str:
year = "{year}".format(year=right_now.value.year)
quarter = self.month_to_quarter(right_now)
month = self.month_to_month(right_now)
week = "W{week}".format(week=right_now.value.week_of_year)
day = "D{day}".format(day=right_now.value.day_of_week)
return "{year},{quarter},{month},{week},{day}".format(year=year, quarter=quarter, month=month, week=week,
day=day)
class WeeklySchedule(Schedule):
"""A monthly schedule."""
def __init__(
self, name: EntityName, right_now: Timestamp, timezone: Timezone,
skip_rule: Optional[RecurringTaskSkipRule], actionable_from_day: Optional[RecurringTaskDueAtDay],
due_at_time: Optional[RecurringTaskDueAtTime], due_at_day: Optional[RecurringTaskDueAtDay]) -> None:
"""Construct a schedule."""
super().__init__()
start_of_week = right_now.value.start_of("week")
self._date = typing.cast(pendulum.Date, right_now.value.date())
if actionable_from_day:
self._actionable_date = \
typing.cast(pendulum.Date, start_of_week.add(days=actionable_from_day.as_int() - 1).date())
else:
self._actionable_date = None
if due_at_day:
self._due_date = start_of_week.add(days=due_at_day.as_int() - 1).end_of("day")
else:
self._due_date = start_of_week.end_of("week").end_of("day")
if due_at_time:
self._due_time = pendulum.parse(
"{date} {time}".format(date=self._due_date.to_date_string(), time=due_at_time), tz=timezone)
else:
self._due_time = None
self._full_name = EntityName("{name} {year}:W{week}".format(
name=name, year=self.year_two_digits(right_now), week=start_of_week.week_of_year))
self._timeline = self._generate_timeline(start_of_week)
self._should_skip = self._skip_helper(skip_rule, self._due_date.week_of_year) if skip_rule else False
@property
def period(self) -> RecurringTaskPeriod:
"""The period string."""
return RecurringTaskPeriod.WEEKLY
@property
def first_day(self) -> ADate:
"""The first day of the interval represented by the schedule block."""
return ADate.from_date(self._date.start_of("week"))
@property
def end_day(self) -> ADate:
"""The end day of the interval represented by the schedule block."""
return ADate.from_date(self._date.end_of("week"))
def _generate_timeline(self, right_now: pendulum.DateTime) -> str:
year = "{year}".format(year=right_now.year)
quarter = self.month_to_quarter(right_now)
month = self.month_to_month(right_now)
week = "W{week}".format(week=right_now.week_of_year)
return "{year},{quarter},{month},{week}".format(year=year, quarter=quarter, month=month, week=week)
class MonthlySchedule(Schedule):
"""A monthly schedule."""
def __init__(
self, name: EntityName, right_now: Timestamp, timezone: Timezone,
skip_rule: Optional[RecurringTaskSkipRule], actionable_from_day: Optional[RecurringTaskDueAtDay],
due_at_time: Optional[RecurringTaskDueAtTime], due_at_day: Optional[RecurringTaskDueAtDay]) -> None:
"""Construct a schedule."""
super().__init__()
start_of_month = right_now.value.start_of("month")
self._date = typing.cast(pendulum.Date, right_now.value.date())
if actionable_from_day:
self._actionable_date = \
typing.cast(pendulum.Date, start_of_month.add(days=actionable_from_day.as_int() - 1).date())
else:
self._actionable_date = None
if due_at_day:
self._due_date = start_of_month.add(days=due_at_day.as_int() - 1).end_of("day")
else:
self._due_date = start_of_month.end_of("month").end_of("day")
if due_at_time:
self._due_time = pendulum.parse(
"{date} {time}".format(date=self._due_date.to_date_string(), time=due_at_time), tz=timezone)
else:
self._due_time = None
self._full_name = EntityName("{name} {year}:{month}".format(
name=name, year=self.year_two_digits(right_now), month=self.month_to_month(right_now)))
self._timeline = self._generate_timeline(Timestamp(start_of_month))
self._should_skip = self._skip_helper(skip_rule, self._due_date.month) if skip_rule else False
@property
def period(self) -> RecurringTaskPeriod:
"""The period string."""
return RecurringTaskPeriod.MONTHLY
@property
def first_day(self) -> ADate:
"""The first day of the interval represented by the schedule block."""
return ADate.from_date(self._date.start_of("month"))
@property
def end_day(self) -> ADate:
"""The end day of the interval represented by the schedule block."""
return ADate.from_date(self._date.end_of("month"))
def _generate_timeline(self, right_now: Timestamp) -> str:
year = "{year}".format(year=right_now.value.year)
quarter = self.month_to_quarter(right_now)
month = self.month_to_month(right_now)
return "{year},{quarter},{month}".format(year=year, quarter=quarter, month=month)
class QuarterlySchedule(Schedule):
"""A quarterly schedule."""
def __init__(
self, name: EntityName, right_now: Timestamp, timezone: Timezone,
skip_rule: Optional[RecurringTaskSkipRule], actionable_from_day: Optional[RecurringTaskDueAtDay],
actionable_from_month: Optional[RecurringTaskDueAtMonth], due_at_time: Optional[RecurringTaskDueAtTime],
due_at_day: Optional[RecurringTaskDueAtDay], due_at_month: Optional[RecurringTaskDueAtMonth]) -> None:
"""Construct a schedule."""
super().__init__()
self._date = typing.cast(pendulum.Date, right_now.value.date())
if actionable_from_month:
if actionable_from_day:
self._actionable_date = typing.cast(pendulum.Date, right_now
.value
.on(right_now.value.year, self.month_to_quarter_start(right_now), 1)
.start_of("month")
.add(months=actionable_from_month.as_int() - 1)
.add(days=actionable_from_day.as_int() - 1)
.date())
else:
self._actionable_date = typing.cast(pendulum.Date, right_now
.value
.on(right_now.value.year, self.month_to_quarter_start(right_now), 1)
.start_of("month")
.add(months=actionable_from_month.as_int() - 1)
.date())
elif actionable_from_day:
self._actionable_date = typing.cast(pendulum.Date, right_now
.value
.on(right_now.value.year, self.month_to_quarter_start(right_now), 1)
.start_of("month")
.add(days=actionable_from_day.as_int() - 1)
.date())
else:
self._actionable_date = None
if due_at_month:
if due_at_day:
self._due_date = right_now\
.value\
.on(right_now.value.year, self.month_to_quarter_start(right_now), 1)\
.start_of("month")\
.add(months=due_at_month.as_int() - 1)\
.add(days=due_at_day.as_int() - 1)\
.end_of("day")
else:
self._due_date = right_now\
.value\
.on(right_now.value.year, self.month_to_quarter_start(right_now), 1)\
.start_of("month")\
.add(months=due_at_month.as_int() - 1)\
.end_of("month")\
.end_of("day")
elif due_at_day:
self._due_date = right_now\
.value\
.on(right_now.value.year, self.month_to_quarter_start(right_now), 1)\
.start_of("month")\
.add(days=due_at_day.as_int() - 1)\
.end_of("day")
else:
self._due_date = right_now\
.value\
.on(right_now.value.year, self.month_to_quarter_end(right_now), 1)\
.end_of("month")\
.end_of("day")
if due_at_time:
self._due_time = pendulum.parse(
"{date} {time}".format(date=self._due_date.to_date_string(), time=due_at_time), tz=timezone)
else:
self._due_time = None
self._full_name = EntityName("{name} {year}:{quarter}".format(
name=name, year=self.year_two_digits(right_now), quarter=self.month_to_quarter(right_now)))
self._timeline = self._generate_timeline(right_now)
self._should_skip = \
self._skip_helper(skip_rule, self.month_to_quarter_num(self._due_date)) if skip_rule else False
@property
def period(self) -> RecurringTaskPeriod:
"""The period string."""
return RecurringTaskPeriod.QUARTERLY
@property
def first_day(self) -> ADate:
"""The first day of the interval represented by the schedule block."""
return ADate.from_date_and_time(pendulum\
.DateTime(self._date.year, self.month_to_quarter_start(self._date), self._date.day, tzinfo=UTC)\
.start_of("month"))
@property
def end_day(self) -> ADate:
"""The end day of the interval represented by the scedule block."""
return ADate.from_date_and_time(pendulum\
.DateTime(self._date.year, self.month_to_quarter_end(self._date), self._date.day, tzinfo=UTC)\
.end_of("month"))
def _generate_timeline(self, right_now: Timestamp) -> str:
year = "{year}".format(year=right_now.value.year)
quarter = self.month_to_quarter(right_now)
return "{year},{quarter}".format(year=year, quarter=quarter)
class YearlySchedule(Schedule):
"""A yearly schedule."""
def __init__(
self, name: EntityName, right_now: Timestamp, timezone: Timezone,
actionable_from_day: Optional[RecurringTaskDueAtDay],
actionable_from_month: Optional[RecurringTaskDueAtMonth],
due_at_time: Optional[RecurringTaskDueAtTime], due_at_day: Optional[RecurringTaskDueAtDay],
due_at_month: Optional[RecurringTaskDueAtMonth]) -> None:
"""Construct a schedule."""
super().__init__()
self._date = typing.cast(pendulum.Date, right_now.value.date())
if actionable_from_month:
if actionable_from_day:
self._actionable_date = typing.cast(pendulum.Date, right_now
.value
.start_of("year")
.add(months=actionable_from_month.as_int() - 1)
.add(days=actionable_from_day.as_int() - 1)
.date())
else:
self._actionable_date = typing.cast(pendulum.Date, right_now
.value
.start_of("year")
.add(months=actionable_from_month.as_int() - 1)
.date())
elif actionable_from_day:
self._actionable_date = typing.cast(
pendulum.Date, right_now.value.start_of("year").add(days=actionable_from_day.as_int() - 1).date())
else:
self._actionable_date = None
if due_at_month:
if due_at_day:
self._due_date = right_now\
.value\
.start_of("year")\
.add(months=due_at_month.as_int() - 1)\
.add(days=due_at_day.as_int() - 1)\
.end_of("day")
else:
self._due_date = right_now\
.value\
.start_of("year")\
.add(months=due_at_month.as_int() - 1)\
.end_of("month")\
.end_of("day")
elif due_at_day:
self._due_date = right_now.value.start_of("year").add(days=due_at_day.as_int() - 1).end_of("day")
else:
self._due_date = right_now.value.end_of("year").end_of("day")
if due_at_time:
self._due_time = pendulum.parse(
"{date} {time}".format(date=self._due_date.to_date_string(), time=due_at_time), tz=timezone)
else:
self._due_time = None
self._full_name = EntityName("{name} {year}".format(name=name, year=self.year_two_digits(right_now)))
self._timeline = self._generate_timeline(right_now)
self._should_skip = False
@property
def period(self) -> RecurringTaskPeriod:
"""The period string."""
return RecurringTaskPeriod.YEARLY
@property
def first_day(self) -> ADate:
"""The first day of the interval represented by the schedule block."""
return ADate.from_date(self._date.start_of("year"))
@property
def end_day(self) -> ADate:
"""The end day of the interval represented by the schedule block."""
return ADate.from_date(self._date.end_of("year"))
@staticmethod
def _generate_timeline(right_now: Timestamp) -> str:
year = "{year}".format(year=right_now.value.year)
return year
def get_schedule(
period: RecurringTaskPeriod, name: EntityName, right_now: Timestamp, timezone: DomainTimezone,
skip_rule: Optional[RecurringTaskSkipRule], actionable_from_day: Optional[RecurringTaskDueAtDay],
actionable_from_month: Optional[RecurringTaskDueAtMonth], due_at_time: Optional[RecurringTaskDueAtTime],
due_at_day: Optional[RecurringTaskDueAtDay], due_at_month: Optional[RecurringTaskDueAtMonth]) -> Schedule:
"""Build an appropriate schedule from the given parameters."""
pendulum_timezone = pendulum.timezone(str(timezone))
if period == RecurringTaskPeriod.DAILY:
return DailySchedule(name, right_now, pendulum_timezone, skip_rule, due_at_time)
elif period == RecurringTaskPeriod.WEEKLY:
return WeeklySchedule(
name, right_now, pendulum_timezone, skip_rule, actionable_from_day, due_at_time, due_at_day)
elif period == RecurringTaskPeriod.MONTHLY:
return MonthlySchedule(
name, right_now, pendulum_timezone, skip_rule, actionable_from_day, due_at_time, due_at_day)
elif period == RecurringTaskPeriod.QUARTERLY:
return QuarterlySchedule(
name, right_now, pendulum_timezone, skip_rule, actionable_from_day, actionable_from_month, due_at_time,
due_at_day, due_at_month)
elif period == RecurringTaskPeriod.YEARLY:
return YearlySchedule(
name, right_now, pendulum_timezone, actionable_from_day, actionable_from_month, due_at_time, due_at_day,
due_at_month)
else:
raise Exception(f"Invalid period {period}")
| 41.989673
| 120
| 0.591244
| 2,891
| 24,396
| 4.707022
| 0.066413
| 0.046443
| 0.034392
| 0.024985
| 0.779615
| 0.748236
| 0.736111
| 0.707378
| 0.70194
| 0.685847
| 0
| 0.009627
| 0.30173
| 24,396
| 580
| 121
| 42.062069
| 0.789199
| 0.084481
| 0
| 0.54329
| 0
| 0.004329
| 0.033207
| 0.006153
| 0
| 0
| 0
| 0
| 0
| 1
| 0.097403
| false
| 0
| 0.032468
| 0
| 0.253247
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7a319c61790b7e7d01726f98e57f5651f0b50cd0
| 200
|
py
|
Python
|
wfdb/processing/__init__.py
|
Chirayu-sopho/Sleep_Disorder_Classification
|
1566c26b79ec089943cbeec5e4b9ed41e601477c
|
[
"Apache-2.0"
] | null | null | null |
wfdb/processing/__init__.py
|
Chirayu-sopho/Sleep_Disorder_Classification
|
1566c26b79ec089943cbeec5e4b9ed41e601477c
|
[
"Apache-2.0"
] | null | null | null |
wfdb/processing/__init__.py
|
Chirayu-sopho/Sleep_Disorder_Classification
|
1566c26b79ec089943cbeec5e4b9ed41e601477c
|
[
"Apache-2.0"
] | null | null | null |
from .basic import resample_ann, resample_sig, resample_singlechan, resample_multichan, normalize
from .gqrs import gqrs_detect
from .hr import compute_hr
from .peaks import find_peaks, correct_peaks
| 40
| 97
| 0.85
| 29
| 200
| 5.586207
| 0.551724
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.105
| 200
| 4
| 98
| 50
| 0.905028
| 0
| 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
| 1
| 0
|
0
| 5
|
7a4aaa58cb60c3bf29cc356b0c84992d3ba7402f
| 591
|
py
|
Python
|
src/shared/domain/service/logging/logger.py
|
fdelgados/python-ddd-skeleton
|
9c48588929d82e7cbb0e27bd9717123eb9bd26a0
|
[
"MIT"
] | null | null | null |
src/shared/domain/service/logging/logger.py
|
fdelgados/python-ddd-skeleton
|
9c48588929d82e7cbb0e27bd9717123eb9bd26a0
|
[
"MIT"
] | null | null | null |
src/shared/domain/service/logging/logger.py
|
fdelgados/python-ddd-skeleton
|
9c48588929d82e7cbb0e27bd9717123eb9bd26a0
|
[
"MIT"
] | null | null | null |
import abc
class Logger(metaclass=abc.ABCMeta):
@abc.abstractmethod
def debug(self, message: str, *args) -> None:
raise NotImplementedError
@abc.abstractmethod
def info(self, message: str, *args) -> None:
raise NotImplementedError
@abc.abstractmethod
def warning(self, message: str, *args) -> None:
raise NotImplementedError
@abc.abstractmethod
def error(self, message: str, *args) -> None:
raise NotImplementedError
@abc.abstractmethod
def critical(self, message: str) -> None:
raise NotImplementedError
| 24.625
| 51
| 0.666667
| 61
| 591
| 6.459016
| 0.327869
| 0.215736
| 0.253807
| 0.182741
| 0.670051
| 0.670051
| 0.670051
| 0.670051
| 0.670051
| 0.670051
| 0
| 0
| 0.235195
| 591
| 23
| 52
| 25.695652
| 0.871681
| 0
| 0
| 0.588235
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.294118
| false
| 0
| 0.058824
| 0
| 0.411765
| 0
| 0
| 0
| 0
| null | 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
7a5cde4682269d94cf9876e2ba2d3429c11a847b
| 75
|
py
|
Python
|
boa3_test/example/logical_test/MixedOperations.py
|
jplippi/neo3-boa
|
052be4adebb665113715bb80067d954f7ad85ad5
|
[
"Apache-2.0"
] | null | null | null |
boa3_test/example/logical_test/MixedOperations.py
|
jplippi/neo3-boa
|
052be4adebb665113715bb80067d954f7ad85ad5
|
[
"Apache-2.0"
] | null | null | null |
boa3_test/example/logical_test/MixedOperations.py
|
jplippi/neo3-boa
|
052be4adebb665113715bb80067d954f7ad85ad5
|
[
"Apache-2.0"
] | null | null | null |
def Main(a: bool, b: bool, c: bool) -> bool:
return not a and (b or c)
| 25
| 44
| 0.573333
| 16
| 75
| 2.6875
| 0.625
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.266667
| 75
| 2
| 45
| 37.5
| 0.781818
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.5
| false
| 0
| 0
| 0.5
| 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
| 1
| 1
| 0
|
0
| 5
|
7ab04ee207f871f90c4ce14b558a0f6a0340939e
| 96
|
py
|
Python
|
mongodm/__init__.py
|
tdeni/mongodm
|
e793373a7083d83d3f7f36fd1446844a39cf876e
|
[
"MIT"
] | null | null | null |
mongodm/__init__.py
|
tdeni/mongodm
|
e793373a7083d83d3f7f36fd1446844a39cf876e
|
[
"MIT"
] | 1
|
2021-08-03T07:16:46.000Z
|
2021-08-03T07:16:46.000Z
|
mongodm/__init__.py
|
tdeni/mongodm
|
e793373a7083d83d3f7f36fd1446844a39cf876e
|
[
"MIT"
] | null | null | null |
# flake8: noqa
from .mongo import MongoClient
from .types import Document
from .query import Q
| 16
| 30
| 0.78125
| 14
| 96
| 5.357143
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.0125
| 0.166667
| 96
| 5
| 31
| 19.2
| 0.925
| 0.125
| 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
| 1
| 0
|
0
| 5
|
8f8bd8ce5ba3b27ff15a33109fb1a3fd67e1da3d
| 159
|
py
|
Python
|
tests/strategies/__init__.py
|
lycantropos/voronoi
|
977e0b3e5eff2dd294e2e6ce1a8030c763e86233
|
[
"MIT"
] | null | null | null |
tests/strategies/__init__.py
|
lycantropos/voronoi
|
977e0b3e5eff2dd294e2e6ce1a8030c763e86233
|
[
"MIT"
] | null | null | null |
tests/strategies/__init__.py
|
lycantropos/voronoi
|
977e0b3e5eff2dd294e2e6ce1a8030c763e86233
|
[
"MIT"
] | null | null | null |
from .base import (doubles,
integers_32,
integers_64,
sizes,
unsigned_integers_32)
| 26.5
| 40
| 0.427673
| 12
| 159
| 5.333333
| 0.75
| 0.3125
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.08
| 0.528302
| 159
| 5
| 41
| 31.8
| 0.773333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.2
| 0
| 0.2
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
890df086266af089d02f91fe1b3ab8e36420310f
| 254
|
py
|
Python
|
psaw/exceptions.py
|
LeartS/PSAW
|
fd0faac7205e10cc6fcb3654de8e2b23a0d79bf2
|
[
"MIT"
] | null | null | null |
psaw/exceptions.py
|
LeartS/PSAW
|
fd0faac7205e10cc6fcb3654de8e2b23a0d79bf2
|
[
"MIT"
] | null | null | null |
psaw/exceptions.py
|
LeartS/PSAW
|
fd0faac7205e10cc6fcb3654de8e2b23a0d79bf2
|
[
"MIT"
] | null | null | null |
class SearchaniseException(Exception):
def __init__(self, message):
super(SearchaniseException, self).__init__(message)
class PSAWException(Exception):
def __init__(self, message):
super(PSAWException, self).__init__(message)
| 23.090909
| 59
| 0.732283
| 24
| 254
| 7.083333
| 0.375
| 0.141176
| 0.188235
| 0.235294
| 0.376471
| 0.376471
| 0
| 0
| 0
| 0
| 0
| 0
| 0.165354
| 254
| 10
| 60
| 25.4
| 0.801887
| 0
| 0
| 0.333333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0
| 0
| 0.666667
| 0
| 1
| 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
| 5
|
890f8d821a8e5baaaa4cabbd6a51552f6b111b72
| 177
|
py
|
Python
|
preprocessing/__init__.py
|
costaruan/kaggle-dogs-vs-cats-competition
|
d386e3267a3ab81e17f84c0c260973404b1e6808
|
[
"MIT"
] | null | null | null |
preprocessing/__init__.py
|
costaruan/kaggle-dogs-vs-cats-competition
|
d386e3267a3ab81e17f84c0c260973404b1e6808
|
[
"MIT"
] | null | null | null |
preprocessing/__init__.py
|
costaruan/kaggle-dogs-vs-cats-competition
|
d386e3267a3ab81e17f84c0c260973404b1e6808
|
[
"MIT"
] | null | null | null |
from .image_preprocessing import create_testing_data
from .image_preprocessing import create_training_data
__all__ = ['create_testing_data',
'create_training_data']
| 29.5
| 53
| 0.80791
| 21
| 177
| 6.142857
| 0.428571
| 0.139535
| 0.341085
| 0.434109
| 0.527132
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135593
| 177
| 5
| 54
| 35.4
| 0.843137
| 0
| 0
| 0
| 0
| 0
| 0.220339
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.5
| 0
| 0.5
| 0
| 1
| 0
| 0
| null | 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
891906192ecd0af6d29c3f7ce57aa6aa4a0c05d5
| 501
|
py
|
Python
|
dataset/__init__.py
|
Jueast/VLAE_Pytorch
|
8373390008d611909997e4a3de8396f617d53a49
|
[
"MIT"
] | null | null | null |
dataset/__init__.py
|
Jueast/VLAE_Pytorch
|
8373390008d611909997e4a3de8396f617d53a49
|
[
"MIT"
] | null | null | null |
dataset/__init__.py
|
Jueast/VLAE_Pytorch
|
8373390008d611909997e4a3de8396f617d53a49
|
[
"MIT"
] | null | null | null |
try: # Works for python 3
from dataset.dataset import *
from dataset.dataset_mnist import MnistDataset
from dataset.dataset_SVHN import SVHNDataset
from dataset.dataset_dsprites import DspritesDataset
from dataset.dataset_HEART import HeartDataset
except: # Works for python 2
from dataset import *
from dataset_mnist import MnistDataset
from dataset_SVHN import SVHNDataset
from dataset_dsprites import DspritesDataset
from dataset_HEART import HeartDataset
| 41.75
| 56
| 0.790419
| 61
| 501
| 6.360656
| 0.295082
| 0.283505
| 0.231959
| 0.123711
| 0.618557
| 0.618557
| 0
| 0
| 0
| 0
| 0
| 0.004914
| 0.187625
| 501
| 12
| 57
| 41.75
| 0.948403
| 0.073852
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.833333
| 0
| 0.833333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
56eab0dcd9984691e100ac12be2044e800ca41bf
| 1,180
|
py
|
Python
|
lists_01/list_examples.py
|
YAtOff/vcs-internship
|
bcbd4f54402fd65c6c5f955e16ef50413c8cd7e4
|
[
"Apache-2.0"
] | null | null | null |
lists_01/list_examples.py
|
YAtOff/vcs-internship
|
bcbd4f54402fd65c6c5f955e16ef50413c8cd7e4
|
[
"Apache-2.0"
] | null | null | null |
lists_01/list_examples.py
|
YAtOff/vcs-internship
|
bcbd4f54402fd65c6c5f955e16ef50413c8cd7e4
|
[
"Apache-2.0"
] | 1
|
2018-11-08T13:01:47.000Z
|
2018-11-08T13:01:47.000Z
|
"""
Indexing
========
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> ???
1
Negative indexing
=================
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> ???
10
>>> ???
8
List slices (``a[start:end]``)
==============================
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> ???
[2, 3, 4, 5, 6, 7]
List slices with negative indexing
==================================
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> ???
[7, 8]
List slices with step (``a[start:end:step]``)
=============================================
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> ???
[0, 2, 4, 6, 8, 10]
>>> ???
[0, 3, 6, 9]
>>> ???
[2, 4, 6]
List slices with negative step
==============================
>>> a = [0, 1, 2, 3, 4, 5, 6, 7, 8, 9, 10]
>>> ???
[10, 9, 8, 7, 6, 5, 4, 3, 2, 1, 0]
>>> ???
[10, 8, 6, 4, 2, 0]
List slice assignment
=====================
>>> a = [1, 2, 3, 4, 5]
>>> a[2:3] = [0,0]
>>> a
???
>>> a[1:1], a[4:4], a[4:5] = [8,9], [0], []
>>> a
???
>>> a[1:7] = []
>>> a
???
"""
if __name__ == "__main__":
import doctest
doctest.testmod()
| 14.75
| 47
| 0.29322
| 178
| 1,180
| 1.898876
| 0.157303
| 0.053254
| 0.071006
| 0.094675
| 0.41716
| 0.402367
| 0.384615
| 0.384615
| 0.384615
| 0.384615
| 0
| 0.163876
| 0.291525
| 1,180
| 79
| 48
| 14.936709
| 0.240431
| 0.933051
| 0
| 0
| 0
| 0
| 0.112676
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 0.333333
| 0
| 0.333333
| 0
| 0
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
56fdfb66660db6efff34d8fd14cff0943c9e7cd7
| 1,312
|
py
|
Python
|
Connector/sendData.py
|
katarinagalic/pillow-clock
|
bad4003ded92a3faf2ca4913623f47b4630ac53d
|
[
"MIT"
] | null | null | null |
Connector/sendData.py
|
katarinagalic/pillow-clock
|
bad4003ded92a3faf2ca4913623f47b4630ac53d
|
[
"MIT"
] | null | null | null |
Connector/sendData.py
|
katarinagalic/pillow-clock
|
bad4003ded92a3faf2ca4913623f47b4630ac53d
|
[
"MIT"
] | 1
|
2019-08-07T19:38:05.000Z
|
2019-08-07T19:38:05.000Z
|
import requests
import datetime
class sendData():
def __init__(self, userID, startTime, endTime):
self.__date = datetime.datetime.now().date()
self.__url = "http://127.0.0.1:8000/nights/"
self.__user = userID
self.__start = startTime
self.__end = endTime
self.__data = {
'sleeper': self.__user,
'start_sleep': self.__start,
'end_sleep': self.__end
}
def send (self):
requests.post(url = self.__url, data = self.__data)
if __name__ == "__main__":
pass
# testArray = ["2019-10-31 20:21:01", "2019-10-31 20:22:01"]
# test = sendData ("2", testArray[0], testArray[1])
# test.send()
# test = ("I got: getData"
# "[2019/05/26 14:41:54, 2019/05/26 14:42:02]"
# "[2019/05/26 14:42:03, 2019/05/26 14:42:03]"
# "[2019/05/26 14:42:03, 2019/05/26 14:42:03]"
# "[2019/05/26 14:42:03, 2019/05/26 14:42:03]"
# "[2019/05/26 14:42:03, 2019/05/26 14:42:04]"
# "[2019/05/26 14:42:04, 2019/05/26 14:42:05]"
# "[2019/05/26 14:42:05, 2019/05/26 14:42:05]"
# "[2019/05/26 14:42:05, 2019/05/26 14:42:05]"
# "[2019/05/26 14:42:05, 2019/05/26 14:42:06]"
# "[2019/05/26 14:42:06, 2019/05/26 14:42:13]"
# "[2019/05/26 14:42:14, 2019/05/26 14:42:16]")
# test = test.replace('I got: getData', '')
# test = test.replace('[', '')
# fin = test.split(',')
# print (fin[0])
| 31.238095
| 61
| 0.604421
| 237
| 1,312
| 3.194093
| 0.257384
| 0.174373
| 0.232497
| 0.290621
| 0.377807
| 0.330251
| 0.330251
| 0.330251
| 0.330251
| 0.330251
| 0
| 0.32022
| 0.166921
| 1,312
| 41
| 62
| 32
| 0.37237
| 0.587652
| 0
| 0
| 0
| 0
| 0.122841
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.111111
| false
| 0.055556
| 0.111111
| 0
| 0.277778
| 0
| 0
| 0
| 0
| null | 0
| 1
| 1
| 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
| 5
|
71247fd00182d2a6e325f812cf9fdc8b3d6a0051
| 33
|
py
|
Python
|
LogTelegram/__init__.py
|
xTruog94/LogTelegram
|
1c7ce557a4bb39e97f39e4038f66ac7563ceaa87
|
[
"MIT"
] | null | null | null |
LogTelegram/__init__.py
|
xTruog94/LogTelegram
|
1c7ce557a4bb39e97f39e4038f66ac7563ceaa87
|
[
"MIT"
] | null | null | null |
LogTelegram/__init__.py
|
xTruog94/LogTelegram
|
1c7ce557a4bb39e97f39e4038f66ac7563ceaa87
|
[
"MIT"
] | null | null | null |
from .LogTele import send_message
| 33
| 33
| 0.878788
| 5
| 33
| 5.6
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.090909
| 33
| 1
| 33
| 33
| 0.933333
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
713f4c94b04175a1092ee1b9928125ea67ce203a
| 39
|
py
|
Python
|
py_graph_t/vertex/__init__.py
|
sturmianseq/PyGraph
|
e81c3a0f543f5bfcda1a603c6dcecde13d582c57
|
[
"MIT"
] | 17
|
2019-09-29T22:02:57.000Z
|
2020-04-03T00:04:34.000Z
|
py_graph_t/vertex/__init__.py
|
sturmianseq/PyGraph
|
e81c3a0f543f5bfcda1a603c6dcecde13d582c57
|
[
"MIT"
] | 63
|
2019-10-01T12:13:35.000Z
|
2019-12-11T11:32:21.000Z
|
py_graph_t/vertex/__init__.py
|
sturmianseq/PyGraph
|
e81c3a0f543f5bfcda1a603c6dcecde13d582c57
|
[
"MIT"
] | 24
|
2019-10-01T15:53:37.000Z
|
2020-03-08T13:36:06.000Z
|
from .SimpleVertex import SimpleVertex
| 19.5
| 38
| 0.871795
| 4
| 39
| 8.5
| 0.75
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.102564
| 39
| 1
| 39
| 39
| 0.971429
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
8579181b012eb6f5bd8dcdbfdd73cbc71b0d52fa
| 258
|
py
|
Python
|
Fase 4 - Temas avanzados/Tema 11 - Modulos/Apuntes/Leccion 01 (Apuntes) - Modulos/hola.py
|
ruben69695/python-course
|
a3d3532279510fa0315a7636c373016c7abe4f0a
|
[
"MIT"
] | 1
|
2019-01-27T20:44:53.000Z
|
2019-01-27T20:44:53.000Z
|
Fase 4 - Temas avanzados/Tema 11 - Modulos/Apuntes/Leccion 02 (Apuntes) - Paquetes/paquete/saludos.py
|
ruben69695/python-course
|
a3d3532279510fa0315a7636c373016c7abe4f0a
|
[
"MIT"
] | null | null | null |
Fase 4 - Temas avanzados/Tema 11 - Modulos/Apuntes/Leccion 02 (Apuntes) - Paquetes/paquete/saludos.py
|
ruben69695/python-course
|
a3d3532279510fa0315a7636c373016c7abe4f0a
|
[
"MIT"
] | null | null | null |
# Este es un módulo con funciones que saludan
def saludar():
print("Hola, te estoy saludando desde la función saludar() del módulo saludos")
class Saludo():
def __init__(self):
print("Hola, te estoy saludando desde el __init__ de la clase Saludo")
| 36.857143
| 81
| 0.732558
| 39
| 258
| 4.641026
| 0.692308
| 0.099448
| 0.121547
| 0.176796
| 0.331492
| 0.331492
| 0
| 0
| 0
| 0
| 0
| 0
| 0.182171
| 258
| 7
| 82
| 36.857143
| 0.85782
| 0.166667
| 0
| 0
| 0
| 0
| 0.629808
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.4
| false
| 0
| 0
| 0
| 0.6
| 0.4
| 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
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 1
| 0
|
0
| 5
|
857970a9bbbaacfd684e380db747712f65196f31
| 133
|
py
|
Python
|
cwbbus/__init__.py
|
killertux/cwbbus
|
a57580a72ad2c5ead7b78e9381ccf80fbe8f6e31
|
[
"MIT"
] | null | null | null |
cwbbus/__init__.py
|
killertux/cwbbus
|
a57580a72ad2c5ead7b78e9381ccf80fbe8f6e31
|
[
"MIT"
] | null | null | null |
cwbbus/__init__.py
|
killertux/cwbbus
|
a57580a72ad2c5ead7b78e9381ccf80fbe8f6e31
|
[
"MIT"
] | 1
|
2019-06-16T18:39:07.000Z
|
2019-06-16T18:39:07.000Z
|
from cwbbus.downloader import get_data, get_data_range
from cwbbus.datareader import DataReader
from cwbbus.filetype import FileType
| 33.25
| 54
| 0.87218
| 19
| 133
| 5.947368
| 0.473684
| 0.265487
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.097744
| 133
| 3
| 55
| 44.333333
| 0.941667
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 0
| 0
| null | 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
85817df9c5ffb74dd7b128d64245f8f543c460fb
| 50
|
py
|
Python
|
boofuzz/unit_tests/__init__.py
|
youngcraft/boofuzz-modbus
|
bfeb48345b56797b48079e0620e7b06b27085789
|
[
"Apache-2.0"
] | 23
|
2018-08-11T12:12:33.000Z
|
2022-01-28T10:22:49.000Z
|
boofuzz/unit_tests/__init__.py
|
ctf-fuzzer/boofuzz-modbus
|
bfeb48345b56797b48079e0620e7b06b27085789
|
[
"Apache-2.0"
] | 2
|
2018-07-24T15:15:40.000Z
|
2020-07-12T13:06:56.000Z
|
boofuzz/unit_tests/__init__.py
|
ctf-fuzzer/boofuzz-modbus
|
bfeb48345b56797b48079e0620e7b06b27085789
|
[
"Apache-2.0"
] | 10
|
2018-04-02T13:21:36.000Z
|
2022-01-17T09:20:27.000Z
|
import test_blocks
import legos
import primitives
| 12.5
| 18
| 0.88
| 7
| 50
| 6.142857
| 0.714286
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.12
| 50
| 3
| 19
| 16.666667
| 0.977273
| 0
| 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
| 1
| 0
|
0
| 5
|
85b33a6aee8cbe25a47bbdedfaa5429e9f34bd76
| 6,206
|
py
|
Python
|
rcnn_dff/tools/monitor_log.py
|
tonysy/mx-rcnn-flow
|
b78c3c964c802bb874d673170d7452e7a573a998
|
[
"Apache-2.0"
] | 2
|
2018-01-31T02:47:42.000Z
|
2019-07-05T03:48:54.000Z
|
rcnn_dff/tools/monitor_log.py
|
tonysy/mx-rcnn-flow
|
b78c3c964c802bb874d673170d7452e7a573a998
|
[
"Apache-2.0"
] | null | null | null |
rcnn_dff/tools/monitor_log.py
|
tonysy/mx-rcnn-flow
|
b78c3c964c802bb874d673170d7452e7a573a998
|
[
"Apache-2.0"
] | null | null | null |
# coding:utf-8
import tail
import matplotlib.pyplot as plt
from matplotlib.ticker import MultipleLocator, FormatStrFormatter
import numpy as np
import re
import argparse
parser = argparse.ArgumentParser(description='Parses log file and generates train/val curves')
parser.add_argument('--log_file', type=str,default="log_tr_va",
help='the path of log file')
parser.add_argument('--metric', type=str,default="L1Loss",
help='the path of log file')
parser.add_argument('--ylim_log', type=float,default=1.2,
help='the path of log file')
parser.add_argument('--ylim_l1', type=float,default=1.2,
help='the path of log file')
args = parser.parse_args()
global args
def print_line(txt):
global args
print(txt)
plot_curve(args.metric, args.log_file)
def plot_curve(metric, log_file):
global args
plt.ion()
plt.clf()
plt.style.use('ggplot')
# ax = plt.subplot(1,1,1)
metric_list = ["LogLoss", 'L1Loss']
ylimm_list = [args.ylim_log,args.ylim_l1]
y_size_list = [0.1, 0.1]
linestyle_list = ['-', '--']
for i, item in enumerate(metric_list):
log_rpn, log_rcnn, idx, metric_name = log_parse(item, log_file)
# if i+1 < 3:
# ax = plt.subplot(2,1,i+1)
# else:
# ax = plt.subplot(2,2,i+1)
ax = plt.subplot(1,2,i+1)
plt.xlabel("Epoch")
plt.ylabel(item)
plt.plot(idx, log_rpn, '-', linestyle=linestyle_list[i], color="g",
label=metric_name[0])
plt.plot(idx, log_rcnn, '-', linestyle=linestyle_list[i], color="b",
label=metric_name[1])
plt.legend(loc="best")
# plt.xticks(np.arange(min(idx), max(idx)+1, 100), )
# plt.yticks(np.arange(0, 1.2, 0.2))
plt.ylim([0,ylimm_list[i]])
xmajorLocator = MultipleLocator(1) #将x主刻度标签设置为20的倍数
xmajorFormatter = FormatStrFormatter('%5.1f') #设置x轴标签文本的格式
xminorLocator = MultipleLocator(0.2) #将x轴次刻度标签设置为5的倍数
ymajorLocator = MultipleLocator(0.1) #将y轴主刻度标签设置为0.5的倍数
ymajorFormatter = FormatStrFormatter('%1.1f') #设置y轴标签文本的格式
yminorLocator = MultipleLocator(y_size_list[i]) #将此y轴次刻度标签设置为0.1的倍数
ax.xaxis.set_major_locator(xmajorLocator)
ax.xaxis.set_major_formatter(xmajorFormatter)
ax.yaxis.set_major_locator(ymajorLocator)
ax.yaxis.set_major_formatter(ymajorFormatter)
#显示次刻度标签的位置,没有标签文本
ax.xaxis.set_minor_locator(xminorLocator)
ax.yaxis.set_minor_locator(yminorLocator)
ax.xaxis.grid(True, which='major') #x坐标轴的网格使用主刻度
ax.yaxis.grid(True, which='minor') #y坐标轴的网格使用次刻度
plt.tight_layout()
plt.draw()
plt.pause(0.01)
def log_parse(metric, log_file):
if metric == 'TRAIN_ACC':
metric_name = ['Train-RPNAcc','Train-RCNNAcc']
elif metric == 'ACC':
metric_name = ['RPNAcc', 'RCNNAcc']
elif metric == 'L1Loss':
metric_name = ['RPNL1Loss', 'RCNNL1Loss']
elif metric == 'LogLoss':
metric_name = ['RPNLogLoss', 'RCNNLogLoss']
else:
assert 1==1, 'metric error!'
if metric == 'TRAIN_ACC':
RPN = re.compile('.*?]\s{}=([\d\.]+)'.format(metric_name[0]))
RCNN = re.compile('.*?]\s{}=([\d\.]+)'.format(metric_name[1]))
else:
RPN = re.compile('.*{}=([\d\.]+).*?'.format(metric_name[0]))
RCNN = re.compile('.*{}=([\d\.]+).*?'.format(metric_name[1]))
log = open(log_file).read()
log_rpn = [float(x) for x in RPN.findall(log)]
log_rcnn = [float(x) for x in RCNN.findall(log)]
idx = np.arange(len(log_rpn),dtype='float32')
idx = idx / 186
return log_rpn, log_rcnn, idx, metric_name
t = tail.Tail(args.log_file)
t.register_callback(print_line)
t.follow(s=1)
# plot_curve(args.metric, args.log_file)
# def plot_curve(metric, log_file):
# if metric == 'TRAIN_ACC':
# metric_name = ['Train-RPNAcc','Train-RCNNAcc']
# elif metric == 'ACC':
# metric_name = ['RPNAcc', 'RCNNAcc']
# elif metric == 'L1Loss':
# metric_name = ['RPNL1Loss', 'RCNNL1Loss']
# elif metric == 'LogLoss':
# metric_name = ['RPNLogLoss', 'RCNNLogLoss']
# else:
# assert 1==1, 'metric error!'
#
# if metric == 'TRAIN_ACC':
# RPN = re.compile('.*?]\s{}=([\d\.]+)'.format(metric_name[0]))
# RCNN = re.compile('.*?]\s{}=([\d\.]+)'.format(metric_name[1]))
# else:
# RPN = re.compile('.*{}=([\d\.]+).*?'.format(metric_name[0]))
# RCNN = re.compile('.*{}=([\d\.]+).*?'.format(metric_name[1]))
# log = open(log_file).read()
# log_rpn = [float(x) for x in RPN.findall(log)]
# log_rcnn = [float(x) for x in RCNN.findall(log)]
#
# idx = np.arange(len(log_rpn),dtype='float32')
# idx = idx / 186
#
# # plt.figure(figsize=(8, 6))
# plt.ion()
# plt.clf()
# ax = plt.subplot(111)
# plt.xlabel("Epoch")
# plt.ylabel(metric)
# plt.plot(idx, log_rpn, '-', linestyle='-', color="r",
# label=metric_name[0])
#
# plt.plot(idx, log_rcnn, '-', linestyle='-', color="b",
# label=metric_name[1])
#
# plt.legend(loc="best")
#
# # plt.xticks(np.arange(min(idx), max(idx)+1, 100), )
# # plt.yticks(np.arange(0, 1.2, 0.2))
# plt.ylim([0,1.2])
#
# xmajorLocator = MultipleLocator(1) #将x主刻度标签设置为20的倍数
# xmajorFormatter = FormatStrFormatter('%5.1f') #设置x轴标签文本的格式
# xminorLocator = MultipleLocator(0.2) #将x轴次刻度标签设置为5的倍数
#
#
# ymajorLocator = MultipleLocator(0.1) #将y轴主刻度标签设置为0.5的倍数
# ymajorFormatter = FormatStrFormatter('%1.1f') #设置y轴标签文本的格式
# yminorLocator = MultipleLocator(0.1) #将此y轴次刻度标签设置为0.1的倍数
#
# ax.xaxis.set_major_locator(xmajorLocator)
# ax.xaxis.set_major_formatter(xmajorFormatter)
#
# ax.yaxis.set_major_locator(ymajorLocator)
# ax.yaxis.set_major_formatter(ymajorFormatter)
#
# #显示次刻度标签的位置,没有标签文本
# ax.xaxis.set_minor_locator(xminorLocator)
# ax.yaxis.set_minor_locator(yminorLocator)
#
# ax.xaxis.grid(True, which='major') #x坐标轴的网格使用主刻度
# ax.yaxis.grid(True, which='minor') #y坐标轴的网格使用次刻度
#
# plt.draw()
# plt.pause(0.001)
| 33.010638
| 94
| 0.608605
| 793
| 6,206
| 4.629256
| 0.208071
| 0.059929
| 0.02833
| 0.037047
| 0.789975
| 0.760556
| 0.746935
| 0.73277
| 0.73277
| 0.722691
| 0
| 0.02637
| 0.217854
| 6,206
| 187
| 95
| 33.187166
| 0.729913
| 0.413149
| 0
| 0.130952
| 0
| 0
| 0.122743
| 0
| 0
| 0
| 0
| 0
| 0.011905
| 1
| 0.035714
| false
| 0
| 0.071429
| 0
| 0.119048
| 0.035714
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 1
| 1
| 1
| 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
|
0
| 5
|
a411fedfd58f7de76afb052efd977eb76b07577a
| 123
|
py
|
Python
|
borrowingMoneyManagement/apps.py
|
520MianXiangDuiXiang520/FamilyPropertyManageSystem
|
b4f9d681a96a6547c6755d0229f420b4112076c5
|
[
"MIT"
] | 7
|
2019-11-24T08:24:33.000Z
|
2021-11-07T20:25:51.000Z
|
borrowingMoneyManagement/apps.py
|
520MianXiangDuiXiang520/FamilyPropertyManageSystem
|
b4f9d681a96a6547c6755d0229f420b4112076c5
|
[
"MIT"
] | 6
|
2020-02-12T02:58:28.000Z
|
2022-02-10T08:52:38.000Z
|
borrowingMoneyManagement/apps.py
|
520MianXiangDuiXiang520/FamilyPropertyManageSystem
|
b4f9d681a96a6547c6755d0229f420b4112076c5
|
[
"MIT"
] | 1
|
2019-11-30T03:11:32.000Z
|
2019-11-30T03:11:32.000Z
|
from django.apps import AppConfig
class BorrowingmoneymanagementConfig(AppConfig):
name = 'borrowingMoneyManagement'
| 20.5
| 48
| 0.821138
| 10
| 123
| 10.1
| 0.9
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.121951
| 123
| 5
| 49
| 24.6
| 0.935185
| 0
| 0
| 0
| 0
| 0
| 0.195122
| 0.195122
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.333333
| 0
| 1
| 0
| 1
| 0
| 1
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
|
0
| 5
|
a44ac13aedef01c9d27ae624b2360ccbd994a7f1
| 287
|
py
|
Python
|
Exercicios/exe002.py
|
Isaaquee/Curso-em-Video---Python
|
6d0ed4a9aac2b7a50df9f9d07a5b4de7e0999f88
|
[
"MIT"
] | null | null | null |
Exercicios/exe002.py
|
Isaaquee/Curso-em-Video---Python
|
6d0ed4a9aac2b7a50df9f9d07a5b4de7e0999f88
|
[
"MIT"
] | null | null | null |
Exercicios/exe002.py
|
Isaaquee/Curso-em-Video---Python
|
6d0ed4a9aac2b7a50df9f9d07a5b4de7e0999f88
|
[
"MIT"
] | null | null | null |
print ('=====Crie um programa que pergunte seu nome, e imprima, É um prazer te conhecer====')
nome=input('Qual seu nome?')
#print ('É um prazer te conhecer', nome,'!')
#Metodo do professor,{} - esse bloco sera substituido pelo format
print ('É um prazer te conhecer, {}!'.format(nome))
| 41
| 93
| 0.686411
| 44
| 287
| 4.477273
| 0.568182
| 0.045685
| 0.137056
| 0.167513
| 0.380711
| 0.380711
| 0
| 0
| 0
| 0
| 0
| 0
| 0.149826
| 287
| 6
| 94
| 47.833333
| 0.807377
| 0.372822
| 0
| 0
| 0
| 0
| 0.702247
| 0
| 0
| 0
| 0
| 0.166667
| 0
| 1
| 0
| false
| 0
| 0
| 0
| 0
| 0.666667
| 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
| 1
| 0
| null | 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
|
0
| 5
|
a452e63ad08ea6ae5e58a9d655a09d94d4354074
| 30
|
py
|
Python
|
py/redrock/_version.py
|
michaelJwilson/redrock
|
477c3d231514b1926dca493f8ab121aa194917bb
|
[
"BSD-3-Clause"
] | null | null | null |
py/redrock/_version.py
|
michaelJwilson/redrock
|
477c3d231514b1926dca493f8ab121aa194917bb
|
[
"BSD-3-Clause"
] | null | null | null |
py/redrock/_version.py
|
michaelJwilson/redrock
|
477c3d231514b1926dca493f8ab121aa194917bb
|
[
"BSD-3-Clause"
] | null | null | null |
__version__ = '0.13.2.dev565'
| 15
| 29
| 0.7
| 5
| 30
| 3.4
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.259259
| 0.1
| 30
| 1
| 30
| 30
| 0.37037
| 0
| 0
| 0
| 0
| 0
| 0.433333
| 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
| 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
| 5
|
a46cc92d6fc4969c3b12dfe4a62e7b893b552204
| 29
|
py
|
Python
|
meteoalertapi/__init__.py
|
xbgmsharp/meteoalert-api
|
f6886faa57c3dc69df10630d824e880de96cc7fc
|
[
"MIT"
] | 5
|
2019-05-18T10:39:23.000Z
|
2022-01-17T06:22:13.000Z
|
meteoalertapi/__init__.py
|
xbgmsharp/meteoalert-api
|
f6886faa57c3dc69df10630d824e880de96cc7fc
|
[
"MIT"
] | 12
|
2019-05-18T10:35:46.000Z
|
2022-02-09T12:21:22.000Z
|
meteoalertapi/__init__.py
|
xbgmsharp/meteoalert-api
|
f6886faa57c3dc69df10630d824e880de96cc7fc
|
[
"MIT"
] | 8
|
2019-05-24T20:53:28.000Z
|
2022-02-19T07:01:56.000Z
|
from .meteoalertapi import *
| 14.5
| 28
| 0.793103
| 3
| 29
| 7.666667
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.137931
| 29
| 1
| 29
| 29
| 0.92
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0
| 1
| 0
| 1
| 0
| 1
| 1
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
a46f4b86e8076de73d267180b206a413cd1c6d83
| 71
|
py
|
Python
|
grab/djangoui/grabstat/forms.py
|
subeax/grab
|
55518263c543da214d1f0cb54622bbc4fda66349
|
[
"MIT"
] | 1
|
2021-05-10T16:03:24.000Z
|
2021-05-10T16:03:24.000Z
|
grab/djangoui/grabstat/forms.py
|
subeax/grab
|
55518263c543da214d1f0cb54622bbc4fda66349
|
[
"MIT"
] | null | null | null |
grab/djangoui/grabstat/forms.py
|
subeax/grab
|
55518263c543da214d1f0cb54622bbc4fda66349
|
[
"MIT"
] | null | null | null |
# coding: utf-8
from django import forms
#from grabstat.models import
| 14.2
| 28
| 0.774648
| 11
| 71
| 5
| 0.818182
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.016667
| 0.15493
| 71
| 4
| 29
| 17.75
| 0.9
| 0.56338
| 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
| 1
| 0
|
0
| 5
|
f100dc1ddda289aaf6937ccc63a34af09286b350
| 72
|
py
|
Python
|
wakati/__init__.py
|
DHI-GRAS/wakati
|
eb854464e46eae7b44c5a925b9d035b1bf9d3f82
|
[
"BSD-2-Clause"
] | 2
|
2019-02-15T03:51:27.000Z
|
2021-06-30T12:49:06.000Z
|
wakati/__init__.py
|
DHI-GRAS/wakati
|
eb854464e46eae7b44c5a925b9d035b1bf9d3f82
|
[
"BSD-2-Clause"
] | null | null | null |
wakati/__init__.py
|
DHI-GRAS/wakati
|
eb854464e46eae7b44c5a925b9d035b1bf9d3f82
|
[
"BSD-2-Clause"
] | null | null | null |
from __future__ import absolute_import
from wakati.wakati import Timer
| 18
| 38
| 0.861111
| 10
| 72
| 5.7
| 0.6
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.125
| 72
| 3
| 39
| 24
| 0.904762
| 0
| 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
| 1
| 0
|
0
| 5
|
f17acfbf2c1dd815df82261e781f38461b7df2d5
| 209
|
py
|
Python
|
centermask/__init__.py
|
MiXaiLL76/centermask2
|
612fa5f02b09c4167e14031be50c6e5e4e58ea77
|
[
"Apache-2.0"
] | null | null | null |
centermask/__init__.py
|
MiXaiLL76/centermask2
|
612fa5f02b09c4167e14031be50c6e5e4e58ea77
|
[
"Apache-2.0"
] | null | null | null |
centermask/__init__.py
|
MiXaiLL76/centermask2
|
612fa5f02b09c4167e14031be50c6e5e4e58ea77
|
[
"Apache-2.0"
] | null | null | null |
from centermask import utils
from centermask import layers
from centermask import evaluation
from centermask import config
from centermask import modeling
from centermask import model_zoo
__version__ = "0.1"
| 23.222222
| 33
| 0.84689
| 28
| 209
| 6.142857
| 0.464286
| 0.488372
| 0.697674
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.01105
| 0.133971
| 209
| 8
| 34
| 26.125
| 0.939227
| 0
| 0
| 0
| 0
| 0
| 0.014354
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| false
| 0
| 0.857143
| 0
| 0.857143
| 0
| 1
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
|
0
| 5
|
74de7ef681499a8d3cf74df077ee838c246bf21e
| 206
|
py
|
Python
|
src/python/WMCore/ResourceControl/Oracle/Destroy.py
|
khurtado/WMCore
|
f74e252412e49189a92962945a94f93bec81cd1e
|
[
"Apache-2.0"
] | 21
|
2015-11-19T16:18:45.000Z
|
2021-12-02T18:20:39.000Z
|
src/python/WMCore/ResourceControl/Oracle/Destroy.py
|
khurtado/WMCore
|
f74e252412e49189a92962945a94f93bec81cd1e
|
[
"Apache-2.0"
] | 5,671
|
2015-01-06T14:38:52.000Z
|
2022-03-31T22:11:14.000Z
|
src/python/WMCore/ResourceControl/Oracle/Destroy.py
|
khurtado/WMCore
|
f74e252412e49189a92962945a94f93bec81cd1e
|
[
"Apache-2.0"
] | 67
|
2015-01-21T15:55:38.000Z
|
2022-02-03T19:53:13.000Z
|
#/usr/bin/env python
"""
_Destroy_
Oracle implementation of ResourceControl.Destroy.
"""
from WMCore.ResourceControl.MySQL.Destroy import Destroy as MySQLDestroy
class Destroy(MySQLDestroy):
pass
| 13.733333
| 72
| 0.776699
| 23
| 206
| 6.869565
| 0.73913
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.135922
| 206
| 14
| 73
| 14.714286
| 0.88764
| 0.38835
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0
| true
| 0.333333
| 0.333333
| 0
| 0.666667
| 0
| 1
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 0
| 1
| 1
| 1
| 0
| 1
| 0
|
0
| 5
|
74fd3d43402305d25e3681b0e67143d361009225
| 289
|
py
|
Python
|
src/interface/clients/provider.py
|
sdediego/forex-django-clean-architecture
|
915a8d844a8db5a40c726fe4cf9f6d50f7c95275
|
[
"MIT"
] | 8
|
2021-11-09T16:43:38.000Z
|
2022-03-25T16:04:26.000Z
|
src/interface/clients/provider.py
|
sdediego/forex-django-clean-architecture
|
915a8d844a8db5a40c726fe4cf9f6d50f7c95275
|
[
"MIT"
] | null | null | null |
src/interface/clients/provider.py
|
sdediego/forex-django-clean-architecture
|
915a8d844a8db5a40c726fe4cf9f6d50f7c95275
|
[
"MIT"
] | 2
|
2021-11-16T21:17:31.000Z
|
2022-02-11T11:15:29.000Z
|
# coding: utf-8
from typing import Any
class ProviderClient:
def __init__(self, provider_driver: object):
self.provider_driver = provider_driver
def fetch_data(self, action: str, **kwargs: dict) -> Any:
return self.provider_driver.fetch_data(action, **kwargs)
| 22.230769
| 64
| 0.705882
| 37
| 289
| 5.243243
| 0.594595
| 0.28866
| 0.278351
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0.004292
| 0.193772
| 289
| 12
| 65
| 24.083333
| 0.828326
| 0.044983
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 1
| 0.333333
| false
| 0
| 0.166667
| 0.166667
| 0.833333
| 0
| 0
| 0
| 0
| null | 1
| 1
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| 0
| null | 0
| 0
| 0
| 0
| 0
| 1
| 0
| 0
| 0
| 1
| 1
| 0
|
0
| 5
|
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