code stringlengths 2k 1.04M | repo_path stringlengths 5 517 | parsed_code stringlengths 0 1.04M | quality_prob float64 0.02 0.95 | learning_prob float64 0.02 0.93 |
|---|---|---|---|---|
from django.test import TestCase
from rest_framework import serializers
from rest_framework.serializers import ListSerializer
from ai_django_core.drf.fields import RecursiveField
from testapp.models import ModelWithFkToSelf, ModelWithOneToOneToSelf
class TestManyTrueSerializer(serializers.ModelSerializer):
child... | tests/drf/test_fields.py | from django.test import TestCase
from rest_framework import serializers
from rest_framework.serializers import ListSerializer
from ai_django_core.drf.fields import RecursiveField
from testapp.models import ModelWithFkToSelf, ModelWithOneToOneToSelf
class TestManyTrueSerializer(serializers.ModelSerializer):
child... | 0.746324 | 0.388763 |
import logging
import warnings
_logger = logging.getLogger(__name__)
class UserError(Exception):
"""Generic error managed by the client.
Typically when the user tries to do something that has no sense given the current
state of a record. Semantically comparable to the generic 400 HTTP status codes.
... | odoo/exceptions.py | import logging
import warnings
_logger = logging.getLogger(__name__)
class UserError(Exception):
"""Generic error managed by the client.
Typically when the user tries to do something that has no sense given the current
state of a record. Semantically comparable to the generic 400 HTTP status codes.
... | 0.754101 | 0.246035 |
from edparser.utils.io_util import load_pickle, save_pickle
from iwpt2020 import cdroot
import numpy as np
import matplotlib.pyplot as plt
cdroot()
gold_file = 'data/iwpt2020/test-udpipe/en.fixed.conllu'
template = 'data/model/iwpt2020/bert/dep/en.conllu'
def load_conll(path):
with open(path) as src:
t... | iwpt2020/error/oov.py | from edparser.utils.io_util import load_pickle, save_pickle
from iwpt2020 import cdroot
import numpy as np
import matplotlib.pyplot as plt
cdroot()
gold_file = 'data/iwpt2020/test-udpipe/en.fixed.conllu'
template = 'data/model/iwpt2020/bert/dep/en.conllu'
def load_conll(path):
with open(path) as src:
t... | 0.35031 | 0.174129 |
import unittest # Importing unittest Module
from credential import Credential # Importing Credential Class
class TestCredential(unittest.TestCase):
'''
Test class that defines test cases for the credentials class behaviours.
Arg:
unittest.TestCase: TestCase class that helps in creating test cases... | credential_test.py | import unittest # Importing unittest Module
from credential import Credential # Importing Credential Class
class TestCredential(unittest.TestCase):
'''
Test class that defines test cases for the credentials class behaviours.
Arg:
unittest.TestCase: TestCase class that helps in creating test cases... | 0.522446 | 0.48871 |
import numpy as np
import pandas
from ggplot import *
"""
In this question, you need to:
1) implement the compute_cost() and gradient_descent() procedures
2) Select features (in the predictions procedure) and make predictions.
"""
def normalize_features(df):
"""
Normalize the features in the data set.
""... | chapter3/subwayRegress.py | import numpy as np
import pandas
from ggplot import *
"""
In this question, you need to:
1) implement the compute_cost() and gradient_descent() procedures
2) Select features (in the predictions procedure) and make predictions.
"""
def normalize_features(df):
"""
Normalize the features in the data set.
""... | 0.666605 | 0.862525 |
# #### Level-4 data of L1000 gene-expression profiling is calculated as:
#
# Level 4 - Differential Expression (ZSPC):
#
# To obtain a measure of relative gene expression, we use a robust z-scoring procedure to generate differential expression values from normalized profiles (Level-3). We compute the **differential ... | 1.Data-exploration/Profiles_level4/L1000/scripts/nbconverted/L1000_calculate_cpd_median_score.py |
# #### Level-4 data of L1000 gene-expression profiling is calculated as:
#
# Level 4 - Differential Expression (ZSPC):
#
# To obtain a measure of relative gene expression, we use a robust z-scoring procedure to generate differential expression values from normalized profiles (Level-3). We compute the **differential ... | 0.718199 | 0.602062 |
import io
import os
def save_file(fh, path, name):
""" Saves BytesIO stream into path/name """
with io.open(os.path.join(path, name), "wb") as file:
fh.seek(0)
file.write(fh.read())
def prettify_listing(items):
""" Prints file names, one filename per line """
if len(items) > 1:
... | Backup_client/util.py | import io
import os
def save_file(fh, path, name):
""" Saves BytesIO stream into path/name """
with io.open(os.path.join(path, name), "wb") as file:
fh.seek(0)
file.write(fh.read())
def prettify_listing(items):
""" Prints file names, one filename per line """
if len(items) > 1:
... | 0.421433 | 0.244597 |
# # CODI Prevelance Query (PQ) Results Visualization
#
#
# ## Background - PQ algorithm
#
# [CODI-PQ](https://github.com/NORC-UChicago/CODI-PQ) is a program for weight-status-category prevalence based on BMI, and results can be stratified by age, sex, race and geography. PQViz can support the simple output of both ... | PQViz.py |
# # CODI Prevelance Query (PQ) Results Visualization
#
#
# ## Background - PQ algorithm
#
# [CODI-PQ](https://github.com/NORC-UChicago/CODI-PQ) is a program for weight-status-category prevalence based on BMI, and results can be stratified by age, sex, race and geography. PQViz can support the simple output of both ... | 0.768473 | 0.758533 |
import argparse
# TODO: Add any additional required modules
import jinja2
import os
import datetime
# TODO: Think about reusability
def save_to_text_file(fn, data):
with open(fn, "w") as cfgfile:
cfgfile.write(data)
print(f"\nSaved Rendered Configuration to file {fn} in current script directory.")
... | sec09-2_gen_config_from_j2template/config_script.py |
import argparse
# TODO: Add any additional required modules
import jinja2
import os
import datetime
# TODO: Think about reusability
def save_to_text_file(fn, data):
with open(fn, "w") as cfgfile:
cfgfile.write(data)
print(f"\nSaved Rendered Configuration to file {fn} in current script directory.")
... | 0.213295 | 0.376852 |
get_all_qst = '''select
questions.id as question_id,
questions.question_text,
questions.answer_text,
askers.name as asker_name,
experts.name as expert_name
from questions
join users as askers on askers.id = questions.asked_by_id
join ... | Back-End/Python/External Libraries/Flask/Flask_website_examples/05 Question - Answer App/app_query.py | get_all_qst = '''select
questions.id as question_id,
questions.question_text,
questions.answer_text,
askers.name as asker_name,
experts.name as expert_name
from questions
join users as askers on askers.id = questions.asked_by_id
join ... | 0.134691 | 0.089216 |
import os
import numpy as np
import pandas as pd
from mlblocks.discovery import load_pipeline
from orion.core import Orion
class TestOrion:
@classmethod
def setup_class(cls):
cls.clean = pd.DataFrame({
'timestamp': list(range(100)),
'value': [1] * 100,
})
cls... | tests/test_core.py | import os
import numpy as np
import pandas as pd
from mlblocks.discovery import load_pipeline
from orion.core import Orion
class TestOrion:
@classmethod
def setup_class(cls):
cls.clean = pd.DataFrame({
'timestamp': list(range(100)),
'value': [1] * 100,
})
cls... | 0.643105 | 0.512327 |
import sys
import types
import newrelic.packages.six as six
import newrelic.api.transaction
import newrelic.api.object_wrapper
import newrelic.api.external_trace
class capture_external_trace(object):
def __init__(self, wrapped):
newrelic.api.object_wrapper.update_wrapper(self, wrapped)
self._nr_... | venv/lib/python2.7/site-packages/newrelic-2.62.0.47/newrelic/hooks/external_feedparser.py | import sys
import types
import newrelic.packages.six as six
import newrelic.api.transaction
import newrelic.api.object_wrapper
import newrelic.api.external_trace
class capture_external_trace(object):
def __init__(self, wrapped):
newrelic.api.object_wrapper.update_wrapper(self, wrapped)
self._nr_... | 0.320183 | 0.064036 |
from euler_python.utils import eulerlib
def problem090():
"""
Each of the six faces on a cube has a different digit (0 to 9) written on
it; the same is done to a second cube. By placing the two cubes
side-by-side in different positions we can form a variety of 2-digit
numbers.
F... | src/euler_python_package/euler_python/medium/p090.py | from euler_python.utils import eulerlib
def problem090():
"""
Each of the six faces on a cube has a different digit (0 to 9) written on
it; the same is done to a second cube. By placing the two cubes
side-by-side in different positions we can form a variety of 2-digit
numbers.
F... | 0.642769 | 0.848282 |
import numpy as np
def logPPDNA(misfits):
""" Calculate the log-posterior probability density function of model
This routine converts the input data array to a log posterior probability density
function.
For example if the input data for each model is a simple sum of squares of residuals weig... | pyNA/appraise.py | import numpy as np
def logPPDNA(misfits):
""" Calculate the log-posterior probability density function of model
This routine converts the input data array to a log posterior probability density
function.
For example if the input data for each model is a simple sum of squares of residuals weig... | 0.886316 | 0.913252 |
import numpy as np
import cv2
import matplotlib.pyplot as plt
import math
id = 3
# 图像预处理，长宽需要一致，最好都是偶数
fp_read, fp_write = '12.4 stiv images/%d_%d_599.jpg' % (id, 90 + id), '%d_%d_599_filtered.jpg' % (id, 90 + id)
img = plt.imread(fp_read)
img = img[:, 100:400]
height = np.array(img).shape[0]
width = np.array(img).sh... | fuliye.py | import numpy as np
import cv2
import matplotlib.pyplot as plt
import math
id = 3
# 图像预处理，长宽需要一致，最好都是偶数
fp_read, fp_write = '12.4 stiv images/%d_%d_599.jpg' % (id, 90 + id), '%d_%d_599_filtered.jpg' % (id, 90 + id)
img = plt.imread(fp_read)
img = img[:, 100:400]
height = np.array(img).shape[0]
width = np.array(img).sh... | 0.552057 | 0.557243 |
from PyDragonfly import Dragonfly_Module, CMessage, copy_from_msg, copy_to_msg, MT_EXIT
import Dragonfly_config as rc
from dragonfly_utils import respond_to_ping
from argparse import ArgumentParser
from ConfigParser import SafeConfigParser
from PyQt4 import QtGui, QtCore
from PyQt4.Qt import *
import sys
import random... | modules/CursorDisplay/CursorDisplay.py | from PyDragonfly import Dragonfly_Module, CMessage, copy_from_msg, copy_to_msg, MT_EXIT
import Dragonfly_config as rc
from dragonfly_utils import respond_to_ping
from argparse import ArgumentParser
from ConfigParser import SafeConfigParser
from PyQt4 import QtGui, QtCore
from PyQt4.Qt import *
import sys
import random... | 0.214691 | 0.159544 |
import math
import torch
from torch import Tensor
from torch.nn import Parameter
from torch_geometric.nn.conv import MessagePassing, GCNConv
class GCNIIConv(MessagePassing):
"""
The graph convolutional operator with initial residual connections and
identity mapping (GCNII) from the `"Simple and Deep Grap... | gcnii_layer.py | import math
import torch
from torch import Tensor
from torch.nn import Parameter
from torch_geometric.nn.conv import MessagePassing, GCNConv
class GCNIIConv(MessagePassing):
"""
The graph convolutional operator with initial residual connections and
identity mapping (GCNII) from the `"Simple and Deep Grap... | 0.922049 | 0.568775 |
from skopt.space import Categorical, Integer, Real
from src.model import best_models
from src.model.Interface import IContentModel, IBestModel, ICollaborativeModel
import scipy.sparse as sps
# ---------------- CONTENT BASED FILTERING -----------------
class ItemCBF_all(IContentModel):
"""
Item CBF tuned wit... | src/model/new_best_models.py | from skopt.space import Categorical, Integer, Real
from src.model import best_models
from src.model.Interface import IContentModel, IBestModel, ICollaborativeModel
import scipy.sparse as sps
# ---------------- CONTENT BASED FILTERING -----------------
class ItemCBF_all(IContentModel):
"""
Item CBF tuned wit... | 0.797833 | 0.169269 |
from CycleGAN_ls import CycleGAN_LightningSystem
from dataModule import ImageTransform, WatercolorDataset, WatercolorDataModule
from discriminator import CycleGAN_Discriminator
from generator import CycleGAN_Unet_Generator
import os
import glob
import random
import numpy as np
import pandas as pd
import matplotlib.pyp... | train.py | from CycleGAN_ls import CycleGAN_LightningSystem
from dataModule import ImageTransform, WatercolorDataset, WatercolorDataModule
from discriminator import CycleGAN_Discriminator
from generator import CycleGAN_Unet_Generator
import os
import glob
import random
import numpy as np
import pandas as pd
import matplotlib.pyp... | 0.639849 | 0.250414 |
import re
import pytest
from simpy import Interrupt
from simpy.util import start_delayed, subscribe_at
def test_start_delayed(env):
def pem(env):
assert env.now == 5
yield env.timeout(1)
start_delayed(env, pem(env), delay=5)
env.run()
def test_start_delayed_error(env):
"""Check if... | Dessert.Benchmarks/SimPy3/test/test_util.py | import re
import pytest
from simpy import Interrupt
from simpy.util import start_delayed, subscribe_at
def test_start_delayed(env):
def pem(env):
assert env.now == 5
yield env.timeout(1)
start_delayed(env, pem(env), delay=5)
env.run()
def test_start_delayed_error(env):
"""Check if... | 0.599954 | 0.589244 |
from abc import abstractmethod
import warnings
import pandas as pd
from fclib.feature_engineering.utils import is_datetime_like
from fclib.feature_engineering.base_ts_estimators import BaseTSFeaturizer
class BaseTemporalNormalizer(BaseTSFeaturizer):
"""
Base abstract class for creating normalized time feature... | contrib/tsperf/energy_utils/feature_engineering/normalization.py | from abc import abstractmethod
import warnings
import pandas as pd
from fclib.feature_engineering.utils import is_datetime_like
from fclib.feature_engineering.base_ts_estimators import BaseTSFeaturizer
class BaseTemporalNormalizer(BaseTSFeaturizer):
"""
Base abstract class for creating normalized time feature... | 0.94098 | 0.609117 |
import torch
import torch.nn.functional as F
from typing import Optional
from core.modules import LayerNorm
from core.modules import SepConv1d
class VariancePredictor(torch.nn.Module):
def __init__(self, idim: int, n_layers: int=2, n_chans: int=256, out: int=1, kernel_size: int=3,
dropout_rate: f... | core/variance_predictor.py | import torch
import torch.nn.functional as F
from typing import Optional
from core.modules import LayerNorm
from core.modules import SepConv1d
class VariancePredictor(torch.nn.Module):
def __init__(self, idim: int, n_layers: int=2, n_chans: int=256, out: int=1, kernel_size: int=3,
dropout_rate: f... | 0.951278 | 0.544801 |
from django.contrib.auth.signals import user_logged_in, user_logged_out, user_login_failed
from django.db.models.signals import post_save, post_delete, m2m_changed
from django.dispatch import receiver
from .models import ExpectedVariable, MapItem, Runner, Playbook, PlaybookItem, PlaybookMapping, Map, AuditEntry
@rec... | django-backend/app/signals.py | from django.contrib.auth.signals import user_logged_in, user_logged_out, user_login_failed
from django.db.models.signals import post_save, post_delete, m2m_changed
from django.dispatch import receiver
from .models import ExpectedVariable, MapItem, Runner, Playbook, PlaybookItem, PlaybookMapping, Map, AuditEntry
@rec... | 0.424531 | 0.065038 |
import os
import glob
import codecs
import uuid
import string
import random
import re
def remove_substring():
with open ('out.txt', 'w', encoding = 'utf-8') as outfile:
with open('in.txt', 'r') as infile:
summ = 0
count = 0
for line in infile:
line = line.split('acc')[1]
line = line.split(',')[... | exp/easy_string_process.py | import os
import glob
import codecs
import uuid
import string
import random
import re
def remove_substring():
with open ('out.txt', 'w', encoding = 'utf-8') as outfile:
with open('in.txt', 'r') as infile:
summ = 0
count = 0
for line in infile:
line = line.split('acc')[1]
line = line.split(',')[... | 0.042167 | 0.116412 |
from diem import (
identifier,
diem_types,
stdlib,
chain_ids,
txnmetadata,
utils,
)
from diem.testing import create_client, Faucet, XUS
import pytest, time, uuid
@pytest.mark.asyncio
async def test_p2p_under_threshold_by_subaddress():
client = create_client()
faucet = Faucet(client)
... | examples/p2p_transfer.py |
from diem import (
identifier,
diem_types,
stdlib,
chain_ids,
txnmetadata,
utils,
)
from diem.testing import create_client, Faucet, XUS
import pytest, time, uuid
@pytest.mark.asyncio
async def test_p2p_under_threshold_by_subaddress():
client = create_client()
faucet = Faucet(client)
... | 0.555676 | 0.162546 |
from test.matcher import JSPECTestMatcher
class JSPECTestMatcherArrayCapture(JSPECTestMatcher):
"""Class for testing the behaviour when using the ``match`` method for
array captures.
A JSPEC array capture will match a consecutive set of elements, which all
match at least one of the elements in the arr... | test/matcher/arraycapture.py | from test.matcher import JSPECTestMatcher
class JSPECTestMatcherArrayCapture(JSPECTestMatcher):
"""Class for testing the behaviour when using the ``match`` method for
array captures.
A JSPEC array capture will match a consecutive set of elements, which all
match at least one of the elements in the arr... | 0.83602 | 0.773986 |
# Standard lib
import pathlib
import unittest
# Our own imports
from deep_hipsc_tracking import utils
from .. import helpers
# Tests
class TestIsNonemptyDir(helpers.FileSystemTestCase):
def test_returns_false_for_empty_dirs(self):
p1 = self.tempdir / 'foo'
p1.mkdir()
(p1 / '.hidden').... | tests/utils/test_pathdb.py | # Standard lib
import pathlib
import unittest
# Our own imports
from deep_hipsc_tracking import utils
from .. import helpers
# Tests
class TestIsNonemptyDir(helpers.FileSystemTestCase):
def test_returns_false_for_empty_dirs(self):
p1 = self.tempdir / 'foo'
p1.mkdir()
(p1 / '.hidden').... | 0.505859 | 0.355845 |
from bisect import bisect_right
import random
def argmin_dict(d):
return min(d.items(), key=lambda x: x[1])[0]
def add_tuples(tuple_a, tuple_b):
"""
:param tuple_a: ((int), (int))
:param tuple_b: ((int), (int))
:return: vector addition of tuple_a + tuple_b
"""
return tuple([x + y for x, ... | battleground/games/arena/util.py | from bisect import bisect_right
import random
def argmin_dict(d):
return min(d.items(), key=lambda x: x[1])[0]
def add_tuples(tuple_a, tuple_b):
"""
:param tuple_a: ((int), (int))
:param tuple_b: ((int), (int))
:return: vector addition of tuple_a + tuple_b
"""
return tuple([x + y for x, ... | 0.779364 | 0.63542 |
from django.test import tag
from test import cases as case
from test import fixtures as data
@tag('setaside')
class SetAsideTest(case.APITestCase, metaclass = case.MetaAPISchema):
fixtures = data.get_category_fixtures()
schema = {
'object': {
'tags': ('setaside_object',),
... | app/api/tests/test_setaside.py | from django.test import tag
from test import cases as case
from test import fixtures as data
@tag('setaside')
class SetAsideTest(case.APITestCase, metaclass = case.MetaAPISchema):
fixtures = data.get_category_fixtures()
schema = {
'object': {
'tags': ('setaside_object',),
... | 0.333178 | 0.22133 |
import pytest
import asyncio
from hat.drivers import tpkt
@pytest.fixture
def addr(unused_tcp_port):
return tpkt.Address('127.0.0.1', unused_tcp_port)
@pytest.mark.asyncio
async def test_connect_listen(addr):
conn1_future = asyncio.Future()
srv = await tpkt.listen(lambda conn: conn1_future.set_result(c... | test_pytest/test_unit/test_drivers/test_tpkt.py | import pytest
import asyncio
from hat.drivers import tpkt
@pytest.fixture
def addr(unused_tcp_port):
return tpkt.Address('127.0.0.1', unused_tcp_port)
@pytest.mark.asyncio
async def test_connect_listen(addr):
conn1_future = asyncio.Future()
srv = await tpkt.listen(lambda conn: conn1_future.set_result(c... | 0.40157 | 0.583619 |
import logging
from dataclasses import dataclass
import pandas as pd
import torch
from torch import Tensor
from zensols.deeplearn.layer import DeepLinear, DeepLinearNetworkSettings
from zensols.deeplearn.model import BaseNetworkModule
from zensols.deeplearn.batch import (
DataPoint,
Batch,
BatchFeatureMappi... | test/python/iris/model.py | import logging
from dataclasses import dataclass
import pandas as pd
import torch
from torch import Tensor
from zensols.deeplearn.layer import DeepLinear, DeepLinearNetworkSettings
from zensols.deeplearn.model import BaseNetworkModule
from zensols.deeplearn.batch import (
DataPoint,
Batch,
BatchFeatureMappi... | 0.863046 | 0.291781 |
import numpy as np
from neuron import SimpleNeuron
from helpers.diagnostic_helpers import time_measure
class NeuralNetwork(object):
def __init__(self, layer_size=[2, 2, 1], activation_function=None, activation_fun_prime=None):
"""
Default activation function: np.tanh(x)
Default learning fun... | src/neural_networks.py | import numpy as np
from neuron import SimpleNeuron
from helpers.diagnostic_helpers import time_measure
class NeuralNetwork(object):
def __init__(self, layer_size=[2, 2, 1], activation_function=None, activation_fun_prime=None):
"""
Default activation function: np.tanh(x)
Default learning fun... | 0.772959 | 0.532851 |
from __future__ import absolute_import
import struct
import sys
from .common import PY2, BytesIO, string_types
if PY2:
MAX_EXTRACT_VERSION = 63
from zipfile import (
BadZipfile as BadZipFile,
ZipExtFile,
ZipInfo,
_CD_COMMENT_LENGTH,
_CD_EXTRA_FIELD_LENGTH,
_CD_... | Projects/Utilities/zippy/libs/zipfile.py | from __future__ import absolute_import
import struct
import sys
from .common import PY2, BytesIO, string_types
if PY2:
MAX_EXTRACT_VERSION = 63
from zipfile import (
BadZipfile as BadZipFile,
ZipExtFile,
ZipInfo,
_CD_COMMENT_LENGTH,
_CD_EXTRA_FIELD_LENGTH,
_CD_... | 0.447702 | 0.107017 |
import numpy as np
import cv2, os, collections
from scipy.spatial import distance
video = cv2.VideoCapture(0)
hog_desc = cv2.HOGDescriptor()
hog_list = []
# Fonction fancy pour montrer un histogram en couleur (mais vraiment inutile...)
def show_histogram_color(frame):
# Now create a histogram for the frame
h... | project.py | import numpy as np
import cv2, os, collections
from scipy.spatial import distance
video = cv2.VideoCapture(0)
hog_desc = cv2.HOGDescriptor()
hog_list = []
# Fonction fancy pour montrer un histogram en couleur (mais vraiment inutile...)
def show_histogram_color(frame):
# Now create a histogram for the frame
h... | 0.207817 | 0.486149 |
import argparse
import logging
import sys
import time
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import torchvision
from torchvision import datasets, transforms
import os
from wideresnet import WideResNet
from preactresnet i... | AT_AWP/ensemble_model.py | import argparse
import logging
import sys
import time
import math
import numpy as np
import torch
import torch.nn as nn
import torch.nn.functional as F
from torch.autograd import Variable
import torchvision
from torchvision import datasets, transforms
import os
from wideresnet import WideResNet
from preactresnet i... | 0.514888 | 0.245447 |
# Standard Library
import datetime
from typing import Any, Dict, Optional
# Supercell Code
from supercell.breezometer.models.base import BreezoMeterModel
class AirQualityIndex(BreezoMeterModel):
str_fmt = "{class_name} [{timestamp}]: {display_name} = {aqi_display} ({category}) !{dominant_pollutant}"
short_na... | supercell/breezometer/air_quality/models/air_quality_index.py | # Standard Library
import datetime
from typing import Any, Dict, Optional
# Supercell Code
from supercell.breezometer.models.base import BreezoMeterModel
class AirQualityIndex(BreezoMeterModel):
str_fmt = "{class_name} [{timestamp}]: {display_name} = {aqi_display} ({category}) !{dominant_pollutant}"
short_na... | 0.821474 | 0.183758 |
import pytest
import os
import sys
import numpy
import librosa
my_path = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, my_path + '/../')
import dj_feet.song as song
@pytest.fixture
def no_process_base_song(random_song_file):
yield song.Song(random_song_file, process=False)
@pytest.fixture
def ... | tests/test_songs.py | import pytest
import os
import sys
import numpy
import librosa
my_path = os.path.dirname(os.path.abspath(__file__))
sys.path.insert(0, my_path + '/../')
import dj_feet.song as song
@pytest.fixture
def no_process_base_song(random_song_file):
yield song.Song(random_song_file, process=False)
@pytest.fixture
def ... | 0.41561 | 0.423637 |
from __future__ import absolute_import, print_function, unicode_literals
from django.contrib.contenttypes.fields import GenericForeignKey, \
GenericRelation
from django.contrib.contenttypes.models import ContentType
from django.db import models
from django.utils.translation import ugettext_lazy as _
from django_cou... | django_teledex/models.py | from __future__ import absolute_import, print_function, unicode_literals
from django.contrib.contenttypes.fields import GenericForeignKey, \
GenericRelation
from django.contrib.contenttypes.models import ContentType
from django.db import models
from django.utils.translation import ugettext_lazy as _
from django_cou... | 0.407098 | 0.172869 |
import datetime
import numpy
import slycat.web.client
import threading
import time
def generate_model(connection, pid, marking, index):
def random_failure(probability):
if numpy.random.uniform(0, 1) < probability:
connection.update_model(mid, state="finished", result="failed", finished=datetime.datetime.u... | web-client/non-working-examples/slycat-demo-model-progress.py |
import datetime
import numpy
import slycat.web.client
import threading
import time
def generate_model(connection, pid, marking, index):
def random_failure(probability):
if numpy.random.uniform(0, 1) < probability:
connection.update_model(mid, state="finished", result="failed", finished=datetime.datetime.u... | 0.271831 | 0.129678 |
import numpy as np
import pandas as pd
from ..data import cat
ifm_opr_ids = [
'CAR1013',
'CAR1217',
'ACR210',
'ACR288',
'CAR973',
'ACR423',
'ACR281',
'ACR211',
'VCSOPR10',
'CAR1041',
'ACR273',
'ACR425',
'CAR1046',
'ACR280',
'ACR274',
'CAR1070',
'CAR1... | carbonplan_forest_offsets/load/issuance.py | import numpy as np
import pandas as pd
from ..data import cat
ifm_opr_ids = [
'CAR1013',
'CAR1217',
'ACR210',
'ACR288',
'CAR973',
'ACR423',
'ACR281',
'ACR211',
'VCSOPR10',
'CAR1041',
'ACR273',
'ACR425',
'CAR1046',
'ACR280',
'ACR274',
'CAR1070',
'CAR1... | 0.55447 | 0.185523 |
import os
import time
import pickle
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import Select
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions
SLEEP_PAGE = 1
ATCODER_TOP_PAGE = r'https:/... | atcoderContestLoader.py | import os
import time
import pickle
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import Select
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions
SLEEP_PAGE = 1
ATCODER_TOP_PAGE = r'https:/... | 0.163179 | 0.047536 |
from django.views.generic import TemplateView, View
from django.http import Http404, HttpResponse, HttpResponseRedirect
from django.core.urlresolvers import reverse
from django.utils import timezone
from django.contrib.staticfiles.templatetags.staticfiles import static
from django.template.loader import get_template
fr... | attendances/views.py | from django.views.generic import TemplateView, View
from django.http import Http404, HttpResponse, HttpResponseRedirect
from django.core.urlresolvers import reverse
from django.utils import timezone
from django.contrib.staticfiles.templatetags.staticfiles import static
from django.template.loader import get_template
fr... | 0.544559 | 0.096238 |
from unittest import TestCase, mock
from mycroft.util.process_utils import (_update_log_level, bus_logging_status,
create_daemon, ProcessStatus,
StatusCallbackMap)
class TestCreateDaemon(TestCase):
def test_create(self):
"""M... | test/unittests/util/test_process_utils.py | from unittest import TestCase, mock
from mycroft.util.process_utils import (_update_log_level, bus_logging_status,
create_daemon, ProcessStatus,
StatusCallbackMap)
class TestCreateDaemon(TestCase):
def test_create(self):
"""M... | 0.783823 | 0.373676 |
from future.standard_library import install_aliases
install_aliases()
from builtins import str
import os
import sys
import csv
import cssutils
import re
import requests
from urllib.parse import urljoin
from lxml import etree
from lxml.cssselect import CSSSelector, ExpressionError
_url_re = re.compile(r'''url\((['"]?... | inlinestyler/converter.py | from future.standard_library import install_aliases
install_aliases()
from builtins import str
import os
import sys
import csv
import cssutils
import re
import requests
from urllib.parse import urljoin
from lxml import etree
from lxml.cssselect import CSSSelector, ExpressionError
_url_re = re.compile(r'''url\((['"]?... | 0.269806 | 0.07333 |
import logging
from datetime import datetime
import requests
from stati_net.client import Client
import hmac
logger = logging.getLogger('stati')
class HTTPClient(Client):
"""GottWall client to send data via
"""
def __init__(self, project, private_key, public_key,
host='http://127.0.0.1... | stati_net/http.py | import logging
from datetime import datetime
import requests
from stati_net.client import Client
import hmac
logger = logging.getLogger('stati')
class HTTPClient(Client):
"""GottWall client to send data via
"""
def __init__(self, project, private_key, public_key,
host='http://127.0.0.1... | 0.638159 | 0.093885 |
import torch
import os
from collections import Counter
class feature_lib:
def __init__(self,cfg):
self.feature_lib_path= cfg.FEATURELIB.PATH
self.lib = self.load_lib()
# size 2048*n
self.lib_feature = self.lib['feature']
self.lib_label = self.lib['labels']
# 白米饭,... | food_detector/ground_feature.py | import torch
import os
from collections import Counter
class feature_lib:
def __init__(self,cfg):
self.feature_lib_path= cfg.FEATURELIB.PATH
self.lib = self.load_lib()
# size 2048*n
self.lib_feature = self.lib['feature']
self.lib_label = self.lib['labels']
# 白米饭,... | 0.200088 | 0.117344 |
import os.path as osp
from typing import List
import mmcv
import numpy as np
from mmseg.datasets import DATASETS, CustomDataset
from PIL import Image
@DATASETS.register_module()
class BDD100KSemSegDataset(CustomDataset): # type: ignore
"""BDD100K dataset for semantic segmentation."""
CLASSES = (
"... | sem_seg/datasets/bdd100k.py |
import os.path as osp
from typing import List
import mmcv
import numpy as np
from mmseg.datasets import DATASETS, CustomDataset
from PIL import Image
@DATASETS.register_module()
class BDD100KSemSegDataset(CustomDataset): # type: ignore
"""BDD100K dataset for semantic segmentation."""
CLASSES = (
"... | 0.701611 | 0.424412 |
import re
import os
SEC_SETTINGS_DIR = 'web/src/delcien/sec_settings.py'
def configure():
string = ''
email = ''
password = ''
secretKey = ''
emailRegex = r'[a-z,A-Z,.]+@[a-z,A-Z]+\.[a-z,A-Z,.]+[a-z,A-Z]+$'
pattern = re.compile(emailRegex)
while True:
string = input('Enter an email account for the web page ... | configureWebPage.py | import re
import os
SEC_SETTINGS_DIR = 'web/src/delcien/sec_settings.py'
def configure():
string = ''
email = ''
password = ''
secretKey = ''
emailRegex = r'[a-z,A-Z,.]+@[a-z,A-Z]+\.[a-z,A-Z,.]+[a-z,A-Z]+$'
pattern = re.compile(emailRegex)
while True:
string = input('Enter an email account for the web page ... | 0.053564 | 0.091544 |
import argparse
from collections import defaultdict
import json
from nlp2go.cli import Cli
from nlp2go.model import Model
from nlp2go.server import Server
import os
os.environ["PYTHONIOENCODING"] = "utf-8"
def parse_args(args):
parser = argparse.ArgumentParser()
group = parser.add_mutually_exclusive_group(... | nlp2go/main.py | import argparse
from collections import defaultdict
import json
from nlp2go.cli import Cli
from nlp2go.model import Model
from nlp2go.server import Server
import os
os.environ["PYTHONIOENCODING"] = "utf-8"
def parse_args(args):
parser = argparse.ArgumentParser()
group = parser.add_mutually_exclusive_group(... | 0.442396 | 0.08389 |
import math
import torch
from tqdm import tqdm
from torch.nn.functional import mse_loss, l1_loss
from classifier import knn_classification
from utils import Metric
def train(args, classifier, dataloader, epoch, model, rotate, opt, rskel):
model.train()
feature, label = torch.empty(0), torch.empty(0)
# ... | exec.py | import math
import torch
from tqdm import tqdm
from torch.nn.functional import mse_loss, l1_loss
from classifier import knn_classification
from utils import Metric
def train(args, classifier, dataloader, epoch, model, rotate, opt, rskel):
model.train()
feature, label = torch.empty(0), torch.empty(0)
# ... | 0.808786 | 0.456349 |
import logging
import numpy as np
from scipy import stats
from minos import genotyper
class GenotypeConfidenceSimulator:
def __init__(self, mean_depth, depth_variance, error_rate, allele_length=1, iterations=10000):
self.mean_depth = mean_depth
self.depth_variance = depth_variance
self.er... | minos/genotype_confidence_simulator.py | import logging
import numpy as np
from scipy import stats
from minos import genotyper
class GenotypeConfidenceSimulator:
def __init__(self, mean_depth, depth_variance, error_rate, allele_length=1, iterations=10000):
self.mean_depth = mean_depth
self.depth_variance = depth_variance
self.er... | 0.659734 | 0.554531 |
from __future__ import absolute_import
import nnabla as nn
import nnabla.functions as F
import nnabla.parametric_functions as PF
from .helper import create_scale_bias, get_channel_axes
# Small Channel First ResNet
def cf_resblock(x, maps, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
test=False, channe... | python/test/utils/test_graph_converters/ref_graphs/resnets.py |
from __future__ import absolute_import
import nnabla as nn
import nnabla.functions as F
import nnabla.parametric_functions as PF
from .helper import create_scale_bias, get_channel_axes
# Small Channel First ResNet
def cf_resblock(x, maps, kernel=(3, 3), pad=(1, 1), stride=(1, 1),
test=False, channe... | 0.883337 | 0.319957 |
from catboost import CatBoostClassifier, Pool
from sklearn.model_selection import train_test_split
from detector import Preprocess as pp
from sklearn.metrics import roc_auc_score, accuracy_score
import sys
class CatBoostModel:
def __init__(self):
self._preprocess = pp.Preprocess()
self._model = C... | detector/CatBoostModel.py |
from catboost import CatBoostClassifier, Pool
from sklearn.model_selection import train_test_split
from detector import Preprocess as pp
from sklearn.metrics import roc_auc_score, accuracy_score
import sys
class CatBoostModel:
def __init__(self):
self._preprocess = pp.Preprocess()
self._model = C... | 0.752013 | 0.265547 |
from math import trunc
from re import L
import lightbulb
import random
import hikari
import wikipedia
import requests
import asyncio
from hikari.colors import Color
import datetime as dt
from datetime import datetime, time, timedelta
from wikipedia import exceptions
from wikipedia.wikipedia import languages
plugin ... | testbot/bot/extensions/fun.py | from math import trunc
from re import L
import lightbulb
import random
import hikari
import wikipedia
import requests
import asyncio
from hikari.colors import Color
import datetime as dt
from datetime import datetime, time, timedelta
from wikipedia import exceptions
from wikipedia.wikipedia import languages
plugin ... | 0.491944 | 0.317426 |
import numpy as np
from scipy import interpolate
__all__ = ["Material"]
transmission_data = {
"silica": np.array(
[
[200, 87.428395],
[201, 87.777818],
[202, 88.083302],
[203, 88.344465],
[204, 88.634732],
[205, 88.901925],
... | raosi/core/material.py | import numpy as np
from scipy import interpolate
__all__ = ["Material"]
transmission_data = {
"silica": np.array(
[
[200, 87.428395],
[201, 87.777818],
[202, 88.083302],
[203, 88.344465],
[204, 88.634732],
[205, 88.901925],
... | 0.277571 | 0.417628 |
import io
import os
import platform
import research
PlatformName = platform.system()
PlansPath = 'plans/'
OutputPath = 'output/'
markdown_output = OutputPath+"output.md"
word_output = OutputPath+"output.docx"
def md_gen(plan_file):
print("Generating Markdown file...")
plan = io.open(PlansPath+plan_file, "r",... | main.py | import io
import os
import platform
import research
PlatformName = platform.system()
PlansPath = 'plans/'
OutputPath = 'output/'
markdown_output = OutputPath+"output.md"
word_output = OutputPath+"output.docx"
def md_gen(plan_file):
print("Generating Markdown file...")
plan = io.open(PlansPath+plan_file, "r",... | 0.068347 | 0.162679 |
import datetime
import logging
import re
import time
import prettytable
import requests
from pyradiator.common import ColoredString
from pyradiator.common import get_authenticator
LOGGER = logging.getLogger(__name__)
CURRENT_BUILD = 0
LAST_BUILD = 1
COLOR_MAP = {
"UNSTABLE": (255, 255, 0),
"FAILURE": (255,... | pyradiator/content_providers/ask_jenkins_jobs_status.py | import datetime
import logging
import re
import time
import prettytable
import requests
from pyradiator.common import ColoredString
from pyradiator.common import get_authenticator
LOGGER = logging.getLogger(__name__)
CURRENT_BUILD = 0
LAST_BUILD = 1
COLOR_MAP = {
"UNSTABLE": (255, 255, 0),
"FAILURE": (255,... | 0.364438 | 0.069289 |
from statue.cli import statue_cli
from statue.command import Command
from statue.constants import STANDARD
from statue.context import Context
from tests.constants import (
COMMAND1,
COMMAND2,
COMMAND_HELP_STRING1,
COMMAND_HELP_STRING2,
CONTEXT1,
CONTEXT2,
CONTEXT3,
CONTEXT4,
CONTEXT5... | tests/cli/test_context_cli.py | from statue.cli import statue_cli
from statue.command import Command
from statue.constants import STANDARD
from statue.context import Context
from tests.constants import (
COMMAND1,
COMMAND2,
COMMAND_HELP_STRING1,
COMMAND_HELP_STRING2,
CONTEXT1,
CONTEXT2,
CONTEXT3,
CONTEXT4,
CONTEXT5... | 0.461259 | 0.314235 |
import unittest
import os
import shutil
import numpy as np
from sklearn.decomposition import PCA
from pylipid.func import collect_bound_poses, vectorize_poses, write_bound_poses
from pylipid.func import cluster_DBSCAN, cluster_KMeans
from pylipid import LipidInteraction
class TestCluster(unittest.TestCase):
def s... | tests/funcs/test_clusterer.py | import unittest
import os
import shutil
import numpy as np
from sklearn.decomposition import PCA
from pylipid.func import collect_bound_poses, vectorize_poses, write_bound_poses
from pylipid.func import cluster_DBSCAN, cluster_KMeans
from pylipid import LipidInteraction
class TestCluster(unittest.TestCase):
def s... | 0.438064 | 0.273496 |
import itertools
import os
import sys
import geopandas as gpd
import pandas as pd
from shapely.geometry import Polygon
from atra.utils import *
from atra.transport_flow_and_failure_functions import *
from tqdm import tqdm
def create_hazard_attributes_for_network(intersection_dir,climate_scenario,year,sector,hazard_f... | src/atra/analysis/hazards_network_intersections_results_collect.py | import itertools
import os
import sys
import geopandas as gpd
import pandas as pd
from shapely.geometry import Polygon
from atra.utils import *
from atra.transport_flow_and_failure_functions import *
from tqdm import tqdm
def create_hazard_attributes_for_network(intersection_dir,climate_scenario,year,sector,hazard_f... | 0.544075 | 0.353121 |
from zigpy.profiles import zha
from zigpy.quirks import CustomDevice
from zigpy.zcl.clusters.general import Basic, LevelControl, MultistateInput, OnOff, Ota
from zhaquirks import CustomCluster, PowerConfigurationCluster
from zhaquirks.const import (
COMMAND,
COMMAND_DOUBLE,
COMMAND_HOLD,
COMMAND_RELEAS... | zhaquirks/thirdreality/button.py | from zigpy.profiles import zha
from zigpy.quirks import CustomDevice
from zigpy.zcl.clusters.general import Basic, LevelControl, MultistateInput, OnOff, Ota
from zhaquirks import CustomCluster, PowerConfigurationCluster
from zhaquirks.const import (
COMMAND,
COMMAND_DOUBLE,
COMMAND_HOLD,
COMMAND_RELEAS... | 0.698021 | 0.123709 |
from calm.ex import DefinitionError, ArgumentParseError
class ArgumentParser(object):
"""
Extensible default parser for request arguments (path, query).
When specifying request arguments (path, query) types via annotations,
an instance of this class (or subclass) is used to parse the argument
val... | calm/codec.py | from calm.ex import DefinitionError, ArgumentParseError
class ArgumentParser(object):
"""
Extensible default parser for request arguments (path, query).
When specifying request arguments (path, query) types via annotations,
an instance of this class (or subclass) is used to parse the argument
val... | 0.91488 | 0.442637 |
import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import reduce
from base.base_model import BaseModel
from .backbones import mobilenetv2
from .backbones import resnet
class DecoderBlock(nn.Module):
def __init__(self, in_channels, out_channels, block_unit):
super(DecoderBlock, self).... | models/unet.py | import torch
import torch.nn as nn
import torch.nn.functional as F
from functools import reduce
from base.base_model import BaseModel
from .backbones import mobilenetv2
from .backbones import resnet
class DecoderBlock(nn.Module):
def __init__(self, in_channels, out_channels, block_unit):
super(DecoderBlock, self).... | 0.753965 | 0.295154 |
import os
import time
import requests
import ujson as json
from dotenv import load_dotenv
from apscheduler.schedulers.asyncio import AsyncIOScheduler
from discord.ext import commands
from dhooks import Webhook, Embed, File
from utils.global_utils import news_exists, matches_exists
load_dotenv()
vlr_news_webhook = os.g... | cogs/vlr_news.py | import os
import time
import requests
import ujson as json
from dotenv import load_dotenv
from apscheduler.schedulers.asyncio import AsyncIOScheduler
from discord.ext import commands
from dhooks import Webhook, Embed, File
from utils.global_utils import news_exists, matches_exists
load_dotenv()
vlr_news_webhook = os.g... | 0.349755 | 0.06767 |
from pathlib import Path
from denite.base.filter import Base
DEFAULT_ICON = ''
DIR_ICON = ''
FILENAMES = {
'.bash_profile': '',
'.bashrc': '',
'.gitignore': '',
'.vimrc': '',
'dockerfile': '',
'license': '',
}
EXTENSIONS = {
'.bash': '',
'.bat': '',
'.c': '',
'.cc': ... | vim/rplugin/python3/denite/filter/converter/devicons.py | from pathlib import Path
from denite.base.filter import Base
DEFAULT_ICON = ''
DIR_ICON = ''
FILENAMES = {
'.bash_profile': '',
'.bashrc': '',
'.gitignore': '',
'.vimrc': '',
'dockerfile': '',
'license': '',
}
EXTENSIONS = {
'.bash': '',
'.bat': '',
'.c': '',
'.cc': ... | 0.579995 | 0.229578 |
from app import db
# Vamos criar abaixo uma classe, onde poderemos criar usuários apartir dela
class User(db.Model):
'''db.Model é uma classe do sqlalchemy, que traz um modelo de tabela padrão'''
__tablename__ = "users" # users será o nome da minha tabela
id = db.Column(db.Interger, primary_key=True)
... | Aula_flask/app/models/tables.py | from app import db
# Vamos criar abaixo uma classe, onde poderemos criar usuários apartir dela
class User(db.Model):
'''db.Model é uma classe do sqlalchemy, que traz um modelo de tabela padrão'''
__tablename__ = "users" # users será o nome da minha tabela
id = db.Column(db.Interger, primary_key=True)
... | 0.413359 | 0.107719 |
import pytest
from todolist.core.accounts.entities.user import User
from todolist.core.accounts.protocols import UserRepo
from todolist.core.accounts.services import hash_service, user_service
from todolist.core.accounts.services.exceptions import (
EmailNotUniqueError,
UserNotFoundError,
)
@pytest.fixture()... | tests/unit/core/accounts/services/user_service_test.py | import pytest
from todolist.core.accounts.entities.user import User
from todolist.core.accounts.protocols import UserRepo
from todolist.core.accounts.services import hash_service, user_service
from todolist.core.accounts.services.exceptions import (
EmailNotUniqueError,
UserNotFoundError,
)
@pytest.fixture()... | 0.442637 | 0.349449 |
import json
from .base import (BaseStorage, NotFound, BaseDocumentBucket,
BaseBlobBucket, BaseKeyvalBucket)
class BaseMemoryBucket(object):
bucket_type = None # to be overwritten in subclasses
def __init__(self, *a, **kw):
super(BaseMemoryBucket, self).__init__(*a, **kw)
... | harvester/ext/storage/memory.py |
import json
from .base import (BaseStorage, NotFound, BaseDocumentBucket,
BaseBlobBucket, BaseKeyvalBucket)
class BaseMemoryBucket(object):
bucket_type = None # to be overwritten in subclasses
def __init__(self, *a, **kw):
super(BaseMemoryBucket, self).__init__(*a, **kw)
... | 0.531696 | 0.076718 |
import random
from datetime import datetime
import pytz
import requests
from base.views import log
from bs4 import BeautifulSoup
from django.contrib.auth.decorators import login_required
from django.shortcuts import redirect, render
# Create your views here.
def projects(request):
log(request, 'Projects')
p... | projects/views.py | import random
from datetime import datetime
import pytz
import requests
from base.views import log
from bs4 import BeautifulSoup
from django.contrib.auth.decorators import login_required
from django.shortcuts import redirect, render
# Create your views here.
def projects(request):
log(request, 'Projects')
p... | 0.326271 | 0.179782 |
import sys
import json
import argparse
import pytorch_pretrained_bert
sys.path.append('.')
from scripts.data_convert.text_proc import SpacyTextParser
from scripts.data_convert.convert_common import STOPWORD_FILE, BERT_TOK_OPT_HELP, BERT_TOK_OPT, \
FileWrapper, readStopWords, addRetokenizedField
from scripts.confi... | scripts/data_convert/msmarco_adhoc/convert_queries.py | import sys
import json
import argparse
import pytorch_pretrained_bert
sys.path.append('.')
from scripts.data_convert.text_proc import SpacyTextParser
from scripts.data_convert.convert_common import STOPWORD_FILE, BERT_TOK_OPT_HELP, BERT_TOK_OPT, \
FileWrapper, readStopWords, addRetokenizedField
from scripts.confi... | 0.209066 | 0.079926 |
"Code to make variable references plots"
import os
import shutil
import webbrowser
from collections import defaultdict
# pylint:disable=too-many-locals
def referencesplot(model, *, openimmediately=True):
"""Makes a references plot.
1) Creates the JSON file for a d3 references plot
2) Places it and the c... | gpkit/interactive/references.py | "Code to make variable references plots"
import os
import shutil
import webbrowser
from collections import defaultdict
# pylint:disable=too-many-locals
def referencesplot(model, *, openimmediately=True):
"""Makes a references plot.
1) Creates the JSON file for a d3 references plot
2) Places it and the c... | 0.491212 | 0.224927 |
from collections import deque
# 羊 狼 船 羊 狼 船
initial_state = [3, 3, 1, 0, 0, 0] # 初始状态
final_state = [0, 0, 0, 3, 3, 1] # 最终状态
action = [[0, -1, 0], [0, -2, 0], [-1, 0, 0], [-2, 0, 0], [-1, -1, 0], [0, 1, 1], [0, 2, 1], [1, 0, 1], [2, 0, 1],
[1, 1, 1]]
# 利用python的deque队列记录状态转移情况，初始化时加入初始状态。deque是可以从头尾插入和删... | DLS/DLS_WandS_2.py | from collections import deque
# 羊 狼 船 羊 狼 船
initial_state = [3, 3, 1, 0, 0, 0] # 初始状态
final_state = [0, 0, 0, 3, 3, 1] # 最终状态
action = [[0, -1, 0], [0, -2, 0], [-1, 0, 0], [-2, 0, 0], [-1, -1, 0], [0, 1, 1], [0, 2, 1], [1, 0, 1], [2, 0, 1],
[1, 1, 1]]
# 利用python的deque队列记录状态转移情况，初始化时加入初始状态。deque是可以从头尾插入和删... | 0.223377 | 0.593668 |
import logging
import itertools
import struct
import socket
import time
# Packet types
SERVERDATA_AUTH = 3
SERVERDATA_AUTH_RESPONSE = 2
SERVERDATA_EXECCOMMAND = 2
SERVERDATA_RESPONSE_VALUE = 0
__all__ = ['RCONPacket', 'RCONConnection']
rcon_log = logging.getLogger('rcon_lib')
class RCONPacket:
def __init__(sel... | geeksbot_web/rcon/rcon_lib/rcon.py | import logging
import itertools
import struct
import socket
import time
# Packet types
SERVERDATA_AUTH = 3
SERVERDATA_AUTH_RESPONSE = 2
SERVERDATA_EXECCOMMAND = 2
SERVERDATA_RESPONSE_VALUE = 0
__all__ = ['RCONPacket', 'RCONConnection']
rcon_log = logging.getLogger('rcon_lib')
class RCONPacket:
def __init__(sel... | 0.560734 | 0.096877 |
from pytextgears import TextGear
from .utils import *
import os
#API_KEY = os.environ['PYTEXTGEARS_KEY']
def return_error_list(raw_json):
'''Return all json in the error list individually
Args: raw_json (dict): Raw JSON output from grammar checker
Return error_list (list): List of JSON dicts
'''... | pytextgears/json_parser.py |
from pytextgears import TextGear
from .utils import *
import os
#API_KEY = os.environ['PYTEXTGEARS_KEY']
def return_error_list(raw_json):
'''Return all json in the error list individually
Args: raw_json (dict): Raw JSON output from grammar checker
Return error_list (list): List of JSON dicts
'''... | 0.673192 | 0.265035 |
from .entry_point import EntryPoint
from core.entity.corefacility_module import CorefacilityModule
class SynchronizationsEntryPoint(EntryPoint):
"""
Allows to attach different kinds of synchronizations and select an appropriate one
"""
_is_parent_module_root = True
""" The property is used during... | corefacility/core/entity/entry_points/synchronizations.py | from .entry_point import EntryPoint
from core.entity.corefacility_module import CorefacilityModule
class SynchronizationsEntryPoint(EntryPoint):
"""
Allows to attach different kinds of synchronizations and select an appropriate one
"""
_is_parent_module_root = True
""" The property is used during... | 0.833155 | 0.378 |
from jmessage import *
from jmessage import url
import json
class Group(object):
def __init__(self,jmessage):
self.jmessage=jmessage;
def build_group(self, owner_username=None, name=None, members_username=None, desc=None):
group = {}
if owner_username is not None:
group["own... | jmessage/groups/groups.py | from jmessage import *
from jmessage import url
import json
class Group(object):
def __init__(self,jmessage):
self.jmessage=jmessage;
def build_group(self, owner_username=None, name=None, members_username=None, desc=None):
group = {}
if owner_username is not None:
group["own... | 0.067724 | 0.035344 |
from sikuli import Finder
from org.sikuli.android import ADBScreen
from org.sikuli.android import ADBDevice
from pprint import pprint as pp
import json
from glob import glob
from os.path import join, splitext, basename, relpath
tmpdir = join(getBundlePath(), "screencap")
base_img = join(getBundlePath(), "..", "img", "... | create-img-dict.sikuli/create-img-dict.py | from sikuli import Finder
from org.sikuli.android import ADBScreen
from org.sikuli.android import ADBDevice
from pprint import pprint as pp
import json
from glob import glob
from os.path import join, splitext, basename, relpath
tmpdir = join(getBundlePath(), "screencap")
base_img = join(getBundlePath(), "..", "img", "... | 0.159774 | 0.094052 |
import random
import click
from torchvision import ops as tvops
from ... import datautils, utils
from ...defaults import GROZI_ROOT
@click.group()
def grozi():
'''
Commands for GroZi-120 dataset.
This command group contains commands for visualizing various aspects of the GroZi-120 dataset (Merler et al.... | cvpce/cli/datasets/grozi.py | import random
import click
from torchvision import ops as tvops
from ... import datautils, utils
from ...defaults import GROZI_ROOT
@click.group()
def grozi():
'''
Commands for GroZi-120 dataset.
This command group contains commands for visualizing various aspects of the GroZi-120 dataset (Merler et al.... | 0.263505 | 0.352508 |
import pandas as pd
import math
import matplotlib.pyplot as plt
import numpy as np
# COMMAND ----------
# MAGIC %md
# MAGIC #REGRESSION MODEL NOTES
# MAGIC ## We Can Conduct a few different version of this regression model by changing the dependent and independent variables
# MAGIC **Dependent Variable**
# MAGIC We c... | codeSheets/SEAS6401/PGAProject/Regression_Analysis.py | import pandas as pd
import math
import matplotlib.pyplot as plt
import numpy as np
# COMMAND ----------
# MAGIC %md
# MAGIC #REGRESSION MODEL NOTES
# MAGIC ## We Can Conduct a few different version of this regression model by changing the dependent and independent variables
# MAGIC **Dependent Variable**
# MAGIC We c... | 0.581778 | 0.6195 |
from __future__ import print_function
class Cursor(object):
def __init__(self, method, *args, **kwargs):
self.iterator = PageIterator(method, args, kwargs)
def pages(self, limit=0):
if limit > 0:
self.iterator.limit = limit
return self.iterator
def items(self, limit=0... | pixiv/cursor.py | from __future__ import print_function
class Cursor(object):
def __init__(self, method, *args, **kwargs):
self.iterator = PageIterator(method, args, kwargs)
def pages(self, limit=0):
if limit > 0:
self.iterator.limit = limit
return self.iterator
def items(self, limit=0... | 0.617167 | 0.08163 |
"""Classes to represent inputs/outputs/parameters in a Plan."""
import copy
import urllib
from abc import abstractmethod
from pathlib import PurePosixPath
from typing import Any, List, Optional
from uuid import uuid4
from renku.core.errors import ParameterError
from renku.core.utils.urls import get_slug
RANDOM_ID_LE... | renku/core/models/workflow/parameter.py | """Classes to represent inputs/outputs/parameters in a Plan."""
import copy
import urllib
from abc import abstractmethod
from pathlib import PurePosixPath
from typing import Any, List, Optional
from uuid import uuid4
from renku.core.errors import ParameterError
from renku.core.utils.urls import get_slug
RANDOM_ID_LE... | 0.931678 | 0.257753 |
import flatbuffers
from .. import DeferredLightInfo
from .. import DeferredLightResolve
from .. import DeferredShadowLightInfo
class Object:
pass
def convertDeferredLightResolve(convertContext, data):
"""
Converts a DeferredLightResolve. The data map is expected to contain the following elements:
- lightSet: nam... | python/DeepSeaSceneLighting/Convert/DeferredLightResolveConvert.py |
import flatbuffers
from .. import DeferredLightInfo
from .. import DeferredLightResolve
from .. import DeferredShadowLightInfo
class Object:
pass
def convertDeferredLightResolve(convertContext, data):
"""
Converts a DeferredLightResolve. The data map is expected to contain the following elements:
- lightSet: nam... | 0.486088 | 0.584805 |
from django.http import JsonResponse, HttpResponse, HttpResponseBadRequest
from django.views.decorators.csrf import csrf_exempt
from django.contrib.auth import get_user_model
from django.utils import timezone
from todolist.models import Post, TEXT_MAX_LENGTH
from todolist.serializers import post_serializer
from todoli... | todolist/views.py | from django.http import JsonResponse, HttpResponse, HttpResponseBadRequest
from django.views.decorators.csrf import csrf_exempt
from django.contrib.auth import get_user_model
from django.utils import timezone
from todolist.models import Post, TEXT_MAX_LENGTH
from todolist.serializers import post_serializer
from todoli... | 0.658308 | 0.090213 |
import importlib
import pathlib
import shutil
import sys
import tempfile
import textwrap
import unittest
from ops.charm import (
CharmBase,
)
from ops.framework import (
Object,
)
from ops.model import (
ModelError,
)
from ops.testing import Harness
class TestHarness(unittest.TestCase):
def test_ad... | test/test_testing.py |
import importlib
import pathlib
import shutil
import sys
import tempfile
import textwrap
import unittest
from ops.charm import (
CharmBase,
)
from ops.framework import (
Object,
)
from ops.model import (
ModelError,
)
from ops.testing import Harness
class TestHarness(unittest.TestCase):
def test_ad... | 0.385259 | 0.161849 |
import argparse
import sys
import helpers
def preprocess_argv():
# Remove script from argv
argv = sys.argv[1:]
if len(argv):
command_abbreviations = {
'l': 'list',
'u': 'update',
'n': 'new',
'd': 'delete',
'p': 'periods'
}
... | cli.py | import argparse
import sys
import helpers
def preprocess_argv():
# Remove script from argv
argv = sys.argv[1:]
if len(argv):
command_abbreviations = {
'l': 'list',
'u': 'update',
'n': 'new',
'd': 'delete',
'p': 'periods'
}
... | 0.362969 | 0.072308 |
import math
import re
import sys
from voussoirkit import pipeable
def hms_to_seconds(hms) -> float:
'''
Convert hh:mm:ss string to an integer or float of seconds.
'''
parts = hms.split(':')
seconds = 0
if len(parts) > 3:
raise ValueError(f'{hms} doesn\'t match the HH:MM:SS format.')
... | voussoirkit/hms.py | import math
import re
import sys
from voussoirkit import pipeable
def hms_to_seconds(hms) -> float:
'''
Convert hh:mm:ss string to an integer or float of seconds.
'''
parts = hms.split(':')
seconds = 0
if len(parts) > 3:
raise ValueError(f'{hms} doesn\'t match the HH:MM:SS format.')
... | 0.345657 | 0.445771 |
import itertools
import logging
import math
from copy import deepcopy
import numpy as np
import pandas as pd
from scipy.ndimage.filters import uniform_filter1d
import basty.utils.misc as misc
np.seterr(all="ignore")
class SpatioTemporal:
def __init__(self, fps, stft_cfg={}):
self.stft_cfg = deepcopy(st... | basty/feature_extraction/spatiotemporal_features.py | import itertools
import logging
import math
from copy import deepcopy
import numpy as np
import pandas as pd
from scipy.ndimage.filters import uniform_filter1d
import basty.utils.misc as misc
np.seterr(all="ignore")
class SpatioTemporal:
def __init__(self, fps, stft_cfg={}):
self.stft_cfg = deepcopy(st... | 0.692954 | 0.335623 |
import datetime
import unittest
from dawa_facade import DawaFacade
import requests_mock
import os.path
import os
from dawa_facade.responses.replication.street import StreetEvent, StreetData
class StreetTestCase(unittest.TestCase):
"""
:type facade: DawaFacade
"""
facade = None
@classmethod
de... | dawa_facade/tests/replication/test_streets.py | import datetime
import unittest
from dawa_facade import DawaFacade
import requests_mock
import os.path
import os
from dawa_facade.responses.replication.street import StreetEvent, StreetData
class StreetTestCase(unittest.TestCase):
"""
:type facade: DawaFacade
"""
facade = None
@classmethod
de... | 0.648132 | 0.320409 |
import itertools
from oslo_service import service as os_service
from oslo_utils import importutils as utils
from vitrage.common.constants import UpdateMethod
from vitrage.common.utils import opt_exists
from vitrage.datasources.listener_service import ListenerService
from vitrage.datasources.services import ChangesSe... | vitrage/datasources/launcher.py |
import itertools
from oslo_service import service as os_service
from oslo_utils import importutils as utils
from vitrage.common.constants import UpdateMethod
from vitrage.common.utils import opt_exists
from vitrage.datasources.listener_service import ListenerService
from vitrage.datasources.services import ChangesSe... | 0.448909 | 0.091018 |
import collections
import json
import numpy as np
import pandas as pd
import sklearn
def cv_results_to_df(cv_results):
"""
Convert a `sklearn.grid_search.GridSearchCV.cv_results_` attribute to a tidy
pandas DataFrame where each row is a hyperparameter combinatination.
"""
cv_results_df = pd.DataFr... | cognoml/utils.py | import collections
import json
import numpy as np
import pandas as pd
import sklearn
def cv_results_to_df(cv_results):
"""
Convert a `sklearn.grid_search.GridSearchCV.cv_results_` attribute to a tidy
pandas DataFrame where each row is a hyperparameter combinatination.
"""
cv_results_df = pd.DataFr... | 0.793346 | 0.530966 |
import re
import os
from shutil import copy2
import subprocess
from time import time_ns
from pathlib import Path
def time_add_sub(time0, time1, sub=False):
time0 = list(map(int, time0.split(':')))
time1 = list(map(int, time1.split(':')))
time0 = time0[0] * 3600 + time0[1] * 60 + time0[2]
time1 = time1... | connect-dl.py | import re
import os
from shutil import copy2
import subprocess
from time import time_ns
from pathlib import Path
def time_add_sub(time0, time1, sub=False):
time0 = list(map(int, time0.split(':')))
time1 = list(map(int, time1.split(':')))
time0 = time0[0] * 3600 + time0[1] * 60 + time0[2]
time1 = time1... | 0.100508 | 0.13681 |
import unittest
import cellyzer.core as core
import cellyzer.io as io
class TestCallMessageDataSet(unittest.TestCase):
@classmethod
def setUpClass(cls):
# before all the tests
cls.user1 = "3e97992791"
cls.user2 = "265034e175"
cls.user3 = '329233d117'
cls.callDataSet =... | tests/unit_tests/test_CallMessageDataSet.py | import unittest
import cellyzer.core as core
import cellyzer.io as io
class TestCallMessageDataSet(unittest.TestCase):
@classmethod
def setUpClass(cls):
# before all the tests
cls.user1 = "3e97992791"
cls.user2 = "265034e175"
cls.user3 = '329233d117'
cls.callDataSet =... | 0.461259 | 0.321114 |
__author__ = '<EMAIL> (<NAME>)'
import httplib2
import os
import unittest
import urlparse
try:
from urlparse import parse_qs
except ImportError:
from cgi import parse_qs
from apiclient.discovery import build, key2param
from apiclient.http import HttpMock
from apiclient.http import tunnel_patch
from apiclient.... | client/tests/test_discovery.py | __author__ = '<EMAIL> (<NAME>)'
import httplib2
import os
import unittest
import urlparse
try:
from urlparse import parse_qs
except ImportError:
from cgi import parse_qs
from apiclient.discovery import build, key2param
from apiclient.http import HttpMock
from apiclient.http import tunnel_patch
from apiclient.... | 0.437343 | 0.327507 |
from flask import render_template, request, redirect, url_for, flash
from app.src.utils import get_end_path, get_dir_up, get_clean_path
from app.src.utils import get_content_dir, get_pages, is_file
from app.src.format import imgs_type_file
from . import views
@views.route('/storage/<path:path>', methods=['GET', 'POS... | app/views/storage.py | from flask import render_template, request, redirect, url_for, flash
from app.src.utils import get_end_path, get_dir_up, get_clean_path
from app.src.utils import get_content_dir, get_pages, is_file
from app.src.format import imgs_type_file
from . import views
@views.route('/storage/<path:path>', methods=['GET', 'POS... | 0.363308 | 0.082623 |
import engine.db_structure as db_py
import os
filename = "transaction.vdb"
if os.path.isfile(filename):
os.remove(filename)
db = db_py.Database(False, filename)
db.create_table("vadik_table", {"zhenya1": "int", "zhenya2": "str"})
def test_transaction():
id = db.tables[0].start_transaction()
db.tables[0].... | engine_tests/transaction_journal_tests.py | import engine.db_structure as db_py
import os
filename = "transaction.vdb"
if os.path.isfile(filename):
os.remove(filename)
db = db_py.Database(False, filename)
db.create_table("vadik_table", {"zhenya1": "int", "zhenya2": "str"})
def test_transaction():
id = db.tables[0].start_transaction()
db.tables[0].... | 0.311427 | 0.192482 |
from textwrap import dedent
import unittest
from unittest import TestCase
from heconvert.converter import *
class TestKSX5002(TestCase):
def test_all(self):
# h2e test
self.assertEqual('rsef', h2e('ㄱㄴㄷㄹ'))
self.assertEqual('kiju', h2e('ㅏㅑㅓㅕ'))
self.assertEqual('0123', h2e('0123'))... | test/tests.py | from textwrap import dedent
import unittest
from unittest import TestCase
from heconvert.converter import *
class TestKSX5002(TestCase):
def test_all(self):
# h2e test
self.assertEqual('rsef', h2e('ㄱㄴㄷㄹ'))
self.assertEqual('kiju', h2e('ㅏㅑㅓㅕ'))
self.assertEqual('0123', h2e('0123'))... | 0.354768 | 0.353958 |
import requests
import json
import os
import sys
import yaml
from urlparse import urlparse
from docopt import docopt
config = docopt(__doc__)
session_key = ''
session_val = ''
session_token = ''
host = config['--host'] or 'http://datacatalog.worldbank.org'
i = urlparse(host)
if not i.netloc and not i.path:
rais... | dev/ddh-test.py | import requests
import json
import os
import sys
import yaml
from urlparse import urlparse
from docopt import docopt
config = docopt(__doc__)
session_key = ''
session_val = ''
session_token = ''
host = config['--host'] or 'http://datacatalog.worldbank.org'
i = urlparse(host)
if not i.netloc and not i.path:
rais... | 0.126704 | 0.047316 |
import io
import cv2
import base64
import numpy as np
from PIL import Image
from os.path import dirname, join
import tensorflow as tf
from alibi.explainers import AnchorImage
"""
模型解释(改用 alibi )
pip install alibi
alibi 没有针对image regression问题的解释逻辑
"""
# Load TFLite model and allocate tensors.
model_file = join(dirname... | App/beauty/app/src/main/assets/python/report_lite_alibi.py | import io
import cv2
import base64
import numpy as np
from PIL import Image
from os.path import dirname, join
import tensorflow as tf
from alibi.explainers import AnchorImage
"""
模型解释(改用 alibi )
pip install alibi
alibi 没有针对image regression问题的解释逻辑
"""
# Load TFLite model and allocate tensors.
model_file = join(dirname... | 0.601125 | 0.312658 |
import re
from yom.errors import *
from yom.constants import scopes, fields
class YomValidator(object):
is_valid = False
def validate(self):
is_valid = self._validate()
self.is_valid = is_valid
return is_valid
def cleaned_data(self):
if not self.is_valid:
rai... | yom/validators.py | import re
from yom.errors import *
from yom.constants import scopes, fields
class YomValidator(object):
is_valid = False
def validate(self):
is_valid = self._validate()
self.is_valid = is_valid
return is_valid
def cleaned_data(self):
if not self.is_valid:
rai... | 0.674908 | 0.201479 |
import numpy as np
from masp import shoebox_room_sim as srs
import time
import soundfile as sf
import os
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# SETUP
# Room definition
from baseline.cls_feature_class import create_folder
room = np.array([10.2, 7.1, 3.2])
# Desired RT p... | APRI/generate_irs.py | import numpy as np
from masp import shoebox_room_sim as srs
import time
import soundfile as sf
import os
# %%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%%
# SETUP
# Room definition
from baseline.cls_feature_class import create_folder
room = np.array([10.2, 7.1, 3.2])
# Desired RT p... | 0.303216 | 0.238595 |