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 |
|---|---|---|---|---|
import datetime
from collections import namedtuple
from plynx.utils.db_connector import get_db_connector
from plynx.utils.common import ObjectId
DBObjectField = namedtuple('DBObjectField', ['type', 'default', 'is_list'])
class DBObjectNotFound(Exception):
"""Internal Exception."""
pass
class ClassNotSavabl... | plynx/db/db_object.py | import datetime
from collections import namedtuple
from plynx.utils.db_connector import get_db_connector
from plynx.utils.common import ObjectId
DBObjectField = namedtuple('DBObjectField', ['type', 'default', 'is_list'])
class DBObjectNotFound(Exception):
"""Internal Exception."""
pass
class ClassNotSavabl... | 0.834137 | 0.16388 |
from sklearn.metrics import roc_auc_score
from statsmodels.stats.proportion import proportion_confint
import numpy as np
class Metrics():
"""
Class to calculate metrics over training and testing.
"""
def __init__(self):
"""
init Constructor method.
@param self Cre... | code/metrics.py | from sklearn.metrics import roc_auc_score
from statsmodels.stats.proportion import proportion_confint
import numpy as np
class Metrics():
"""
Class to calculate metrics over training and testing.
"""
def __init__(self):
"""
init Constructor method.
@param self Cre... | 0.809276 | 0.637341 |
import collections
from datetime import timedelta
from gopro_overlay import fake
from gopro_overlay.entry import Entry
from gopro_overlay.framemeta import FrameMeta, Window
from gopro_overlay.point import Point
from gopro_overlay.timeunits import timeunits
from gopro_overlay.units import metres, units
from tests.test_... | tests/test_framemeta.py | import collections
from datetime import timedelta
from gopro_overlay import fake
from gopro_overlay.entry import Entry
from gopro_overlay.framemeta import FrameMeta, Window
from gopro_overlay.point import Point
from gopro_overlay.timeunits import timeunits
from gopro_overlay.units import metres, units
from tests.test_... | 0.758063 | 0.601359 |
from scipy.stats import *
import matplotlib.pyplot as plt
import seaborn as sns
# settings for seaborn plotting style
sns.set(color_codes=True)
# settings for seaborn plot sizes
sns.set(rc={'figure.figsize':(5,5)})
data_binom = binom.rvs(n=10,p=0.3,size=100000) + \
binom.rvs(n=30,p=0.8,size=100000)
data = ... | Probability/distributions.py | from scipy.stats import *
import matplotlib.pyplot as plt
import seaborn as sns
# settings for seaborn plotting style
sns.set(color_codes=True)
# settings for seaborn plot sizes
sns.set(rc={'figure.figsize':(5,5)})
data_binom = binom.rvs(n=10,p=0.3,size=100000) + \
binom.rvs(n=30,p=0.8,size=100000)
data = ... | 0.357119 | 0.441733 |
import modeli
def izberi_moznost(moznosti):
"""
Funkcija, ki izpiše seznam možnosti in vrne indeks izbrane možnosti.
Če na voljo ni nobene možnosti, izpiše opozorilo in vrne None.
Če je na voljo samo ena možnost, vrne 0.
>>> izberi_moznost(['jabolko', 'hruška', 'stol'])
1) jabolko
... | tekstovni_vmesnik.py | import modeli
def izberi_moznost(moznosti):
"""
Funkcija, ki izpiše seznam možnosti in vrne indeks izbrane možnosti.
Če na voljo ni nobene možnosti, izpiše opozorilo in vrne None.
Če je na voljo samo ena možnost, vrne 0.
>>> izberi_moznost(['jabolko', 'hruška', 'stol'])
1) jabolko
... | 0.10826 | 0.248819 |
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import random
from torchvision import datasets, transforms
from base import BaseTrainDataset, BaseInferenceDataset, BaseDataLoader
random.seed(123)
class Landsat8TrainDataLoader(Base... | data_loader/data_loaders.py |
# This source code is licensed under the MIT license found in the
# LICENSE file in the root directory of this source tree.
import os
import random
from torchvision import datasets, transforms
from base import BaseTrainDataset, BaseInferenceDataset, BaseDataLoader
random.seed(123)
class Landsat8TrainDataLoader(Base... | 0.746324 | 0.349144 |
from typing import List
import pytorch_lightning as pl
import torch
import torch.optim
from src.models.BaseAutoEncoder import BaseAutoEncoder
class LitBaseAutoEncoder(pl.LightningModule):
def __init__(
self,
n_layers: int = 3,
features_list: List[int] = [16, 8, 4, 2],
activation_... | src/lit_models/LitBaseAutoEncoder.py | from typing import List
import pytorch_lightning as pl
import torch
import torch.optim
from src.models.BaseAutoEncoder import BaseAutoEncoder
class LitBaseAutoEncoder(pl.LightningModule):
def __init__(
self,
n_layers: int = 3,
features_list: List[int] = [16, 8, 4, 2],
activation_... | 0.956125 | 0.478285 |
import json
from datetime import datetime
import pytest
from fhirpy.base.resource import AbstractResource
from aidbox_python_sdk.main import create_app
from aidbox_python_sdk.sdk import SDK
from aidbox_python_sdk.settings import Settings
from resources.appointment.appointment import Appointment
from resources.service... | tests/api_test.py | import json
from datetime import datetime
import pytest
from fhirpy.base.resource import AbstractResource
from aidbox_python_sdk.main import create_app
from aidbox_python_sdk.sdk import SDK
from aidbox_python_sdk.settings import Settings
from resources.appointment.appointment import Appointment
from resources.service... | 0.392919 | 0.152979 |
from __future__ import print_function
import sys
PY3 = sys.version_info[0] == 3
if PY3:
xrange = range
import numpy as np
import cv2 as cv
def make_image():
img = np.zeros((500, 500), np.uint8)
black, white = 0, 255
for i in xrange(6):
dx = int((i % 2) * 250 - 30)
dy = int((i / 2.) ... | tests/testcv2.py | from __future__ import print_function
import sys
PY3 = sys.version_info[0] == 3
if PY3:
xrange = range
import numpy as np
import cv2 as cv
def make_image():
img = np.zeros((500, 500), np.uint8)
black, white = 0, 255
for i in xrange(6):
dx = int((i % 2) * 250 - 30)
dy = int((i / 2.) ... | 0.30549 | 0.260207 |
import logging
import os
import datetime
import pickle
import traceback
from pathlib import Path
import time
import requests
import schedule
from config import config
from job import jobs_all
def main():
session = make_session()
jobs = [job for job in jobs_all if job.__name__ not in config.jobs_skip]
job... | app/main.py | import logging
import os
import datetime
import pickle
import traceback
from pathlib import Path
import time
import requests
import schedule
from config import config
from job import jobs_all
def main():
session = make_session()
jobs = [job for job in jobs_all if job.__name__ not in config.jobs_skip]
job... | 0.161982 | 0.06489 |
import os
import unittest
import numpy as np
import iris
from catnip.analysis import *
import catnip.config as conf
class TestAnalysis(unittest.TestCase):
"""Unittest class for analysis module"""
@classmethod
def setUpClass(self):
file1 = os.path.join(conf.DATA_DIR, "FGOALS-g2_ua@925_nov.nc")
... | lib/catnip/tests/test_analysis.py |
import os
import unittest
import numpy as np
import iris
from catnip.analysis import *
import catnip.config as conf
class TestAnalysis(unittest.TestCase):
"""Unittest class for analysis module"""
@classmethod
def setUpClass(self):
file1 = os.path.join(conf.DATA_DIR, "FGOALS-g2_ua@925_nov.nc")
... | 0.555194 | 0.361785 |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
from ._enums import *
from ._inputs import *
__all__ = ['TopicArgs', 'Topic']
@pulumi.input_type
class TopicArgs:
def __init__(__self__, *,
... | sdk/python/pulumi_google_native/pubsub/v1/topic.py |
import warnings
import pulumi
import pulumi.runtime
from typing import Any, Mapping, Optional, Sequence, Union, overload
from ... import _utilities
from . import outputs
from ._enums import *
from ._inputs import *
__all__ = ['TopicArgs', 'Topic']
@pulumi.input_type
class TopicArgs:
def __init__(__self__, *,
... | 0.884102 | 0.141578 |
import numpy as np
import itertools as it
from collections.abc import Iterable
import logging
import mulearn.kernel as kernel
logger = logging.getLogger(__name__)
try:
from gurobipy import LinExpr, GRB, Model, Env, QuadExpr, GurobiError
gurobi_ok = True
except ModuleNotFoundError:
logger.warning('gurobi... | mulearn/optimization.py | import numpy as np
import itertools as it
from collections.abc import Iterable
import logging
import mulearn.kernel as kernel
logger = logging.getLogger(__name__)
try:
from gurobipy import LinExpr, GRB, Model, Env, QuadExpr, GurobiError
gurobi_ok = True
except ModuleNotFoundError:
logger.warning('gurobi... | 0.763748 | 0.46563 |
import h5py
from keras import backend as K
def save_opt_weights(model, filepath):
with h5py.File(filepath, 'w') as f:
# Save optimizer weights.
symbolic_weights = getattr(model.optimizer, 'weights')
if symbolic_weights:
optimizer_weights_group = f.create_group('optimizer_weight... | geogan/utils.py | import h5py
from keras import backend as K
def save_opt_weights(model, filepath):
with h5py.File(filepath, 'w') as f:
# Save optimizer weights.
symbolic_weights = getattr(model.optimizer, 'weights')
if symbolic_weights:
optimizer_weights_group = f.create_group('optimizer_weight... | 0.557364 | 0.239883 |
from __future__ import print_function, division, absolute_import, unicode_literals
import re
class KernFeatureWriter(object):
"""Generates a kerning feature based on glyph class definitions.
Uses the kerning rules contained in an UFO's kerning data, as well as glyph
classes from parsed feature text. Cla... | Lib/ufo2ft/kernFeatureWriter.py | from __future__ import print_function, division, absolute_import, unicode_literals
import re
class KernFeatureWriter(object):
"""Generates a kerning feature based on glyph class definitions.
Uses the kerning rules contained in an UFO's kerning data, as well as glyph
classes from parsed feature text. Cla... | 0.824921 | 0.370168 |
from __future__ import annotations
from enum import Enum
from typing import Callable, Optional
class Stitch(Enum):
"""
A single stitch.
"""
CAST_ON = ("CO", 0, 1, lambda: Stitch.CAST_ON)
BIND_OFF = ("BO", 1, 0, lambda: Stitch.BIND_OFF)
KNIT = ("K", 1, 1, lambda: Stitch.PURL)
PURL = ("P", ... | knitscript/stitch.py | from __future__ import annotations
from enum import Enum
from typing import Callable, Optional
class Stitch(Enum):
"""
A single stitch.
"""
CAST_ON = ("CO", 0, 1, lambda: Stitch.CAST_ON)
BIND_OFF = ("BO", 1, 0, lambda: Stitch.BIND_OFF)
KNIT = ("K", 1, 1, lambda: Stitch.PURL)
PURL = ("P", ... | 0.92928 | 0.406685 |
# Compiled with Coconut version 2.0.0-a_dev9 [How Not to Be Seen]
"""
Utilities for use across all of bbopt.
"""
# Coconut Header: -------------------------------------------------------------
from __future__ import print_function, absolute_import, unicode_literals, division
import sys as _coconut_sys, os as _cocon... | bbopt/util.py |
# Compiled with Coconut version 2.0.0-a_dev9 [How Not to Be Seen]
"""
Utilities for use across all of bbopt.
"""
# Coconut Header: -------------------------------------------------------------
from __future__ import print_function, absolute_import, unicode_literals, division
import sys as _coconut_sys, os as _cocon... | 0.602646 | 0.057652 |
from typing import List, Optional
from pmix.spreadsheet.xlstab import Xlstab
from pmix.spreadsheet.workbook import Workbook
class Xlsform(Workbook):
"""Class to represent an Xlsform spreadsheet.
The Xlsform class extends the Workbook class to provide functionality
related specifically to Xlsforms and wo... | pmix/spreadsheet/xlsform.py | from typing import List, Optional
from pmix.spreadsheet.xlstab import Xlstab
from pmix.spreadsheet.workbook import Workbook
class Xlsform(Workbook):
"""Class to represent an Xlsform spreadsheet.
The Xlsform class extends the Workbook class to provide functionality
related specifically to Xlsforms and wo... | 0.943893 | 0.396156 |
from .base import Base
from .mat44 import mat44
from .mesh import Mesh
from .model import Model
class TForm(Base):
def world(self):
# NOTE: TForms cant be reused because they can have exactly one parent
if self.parent is None:
base = mat44.I()
else:
base = self.par... | meshmaker/tform.py | from .base import Base
from .mat44 import mat44
from .mesh import Mesh
from .model import Model
class TForm(Base):
def world(self):
# NOTE: TForms cant be reused because they can have exactly one parent
if self.parent is None:
base = mat44.I()
else:
base = self.par... | 0.663015 | 0.121999 |
from zeit.cms.content.interfaces import WRITEABLE_ON_CHECKIN
import datetime
import functools
import grokcore.component as grok
import logging
import lxml.etree
import pendulum
import re
import six
import sys
import time
import zeit.cms.content.interfaces
import zeit.cms.content.liveproperty
import zeit.cms.content.cac... | core/src/zeit/cms/content/dav.py | from zeit.cms.content.interfaces import WRITEABLE_ON_CHECKIN
import datetime
import functools
import grokcore.component as grok
import logging
import lxml.etree
import pendulum
import re
import six
import sys
import time
import zeit.cms.content.interfaces
import zeit.cms.content.liveproperty
import zeit.cms.content.cac... | 0.593727 | 0.075858 |
from pyob.exceptions import (
InvalidObjectError,
NonExistentKeyError,
UnrelatedObjectsError,
)
from pyob.tools import (
filter_by_key,
filter_by_keys,
is_iterable,
is_pyob,
is_pyob_set,
)
# ┌─────────────────────────────────────────────────────────────────────────────────────
# │ PYO... | pyob/mixins/pyob_set_dunder.py |
from pyob.exceptions import (
InvalidObjectError,
NonExistentKeyError,
UnrelatedObjectsError,
)
from pyob.tools import (
filter_by_key,
filter_by_keys,
is_iterable,
is_pyob,
is_pyob_set,
)
# ┌─────────────────────────────────────────────────────────────────────────────────────
# │ PYO... | 0.697815 | 0.246936 |
import time
from calendar import timegm
from tornado.gen import coroutine
from tornado.web import RequestHandler
from tornado.escape import json_decode
from json.decoder import JSONDecodeError
from commons.errors import Error, MALFORMED_JSON, INVALID_FIELD, MISSING_FIELD
class BaseHandler(RequestHandler):
"""
... | src/server/handlers/base_handler.py | import time
from calendar import timegm
from tornado.gen import coroutine
from tornado.web import RequestHandler
from tornado.escape import json_decode
from json.decoder import JSONDecodeError
from commons.errors import Error, MALFORMED_JSON, INVALID_FIELD, MISSING_FIELD
class BaseHandler(RequestHandler):
"""
... | 0.483648 | 0.08196 |
import numpy as np
from ..signal import signal_filter, signal_interpolate, signal_rate, signal_resample
from .rsp_peaks import rsp_peaks
def rsp_rate(
rsp_cleaned,
troughs=None,
sampling_rate=1000,
window=10,
hop_size=1,
method="trough",
peak_method="khodadad2018",
interpolation_metho... | neurokit2/rsp/rsp_rate.py | import numpy as np
from ..signal import signal_filter, signal_interpolate, signal_rate, signal_resample
from .rsp_peaks import rsp_peaks
def rsp_rate(
rsp_cleaned,
troughs=None,
sampling_rate=1000,
window=10,
hop_size=1,
method="trough",
peak_method="khodadad2018",
interpolation_metho... | 0.911925 | 0.692798 |
import pytest
from dataclasses import dataclass
from typing import Optional
from gemma import Course, PORT, Item, Fallback, Attr, Call, NullNameError
class TestBasicAPI:
def test_init_basic(self, course_basic):
assert str(course_basic) == "a/b/c/d"
def test_repr(self, course_basic):
assert r... | zdevelop/tests/test_course.py | import pytest
from dataclasses import dataclass
from typing import Optional
from gemma import Course, PORT, Item, Fallback, Attr, Call, NullNameError
class TestBasicAPI:
def test_init_basic(self, course_basic):
assert str(course_basic) == "a/b/c/d"
def test_repr(self, course_basic):
assert r... | 0.810104 | 0.512083 |
from sys import argv, exit
from csp import CSP
# Hilfsfunktion: alle Werte einer Zeile oder Spalte ermitteln
def filter_dict_by_key(dict_to_filter, condition):
filtered_list = []
for key in dict_to_filter:
if condition(key):
filtered_list.append(dict_to_filter[key])
return filtered_list... | listings/chapter05/predefined_sudoku.py | from sys import argv, exit
from csp import CSP
# Hilfsfunktion: alle Werte einer Zeile oder Spalte ermitteln
def filter_dict_by_key(dict_to_filter, condition):
filtered_list = []
for key in dict_to_filter:
if condition(key):
filtered_list.append(dict_to_filter[key])
return filtered_list... | 0.063934 | 0.230432 |
from __future__ import annotations
import typing
import zserio
import tutorial.language
class Experience:
def __init__(
self,
years_of_experience_: int = int(),
programming_language_: typing.Union[tutorial.language.Language, None] = None) -> None:
self._years_of_experi... | src/tutorial/experience.py | from __future__ import annotations
import typing
import zserio
import tutorial.language
class Experience:
def __init__(
self,
years_of_experience_: int = int(),
programming_language_: typing.Union[tutorial.language.Language, None] = None) -> None:
self._years_of_experi... | 0.851891 | 0.357259 |
import os
import io
from .. import Renderer, RenderFunctionRegistry
from ...objects import WorldObject
from ...cameras import Camera
from ...linalg import Matrix4, Vector3
registry = RenderFunctionRegistry()
def register_svg_render_function(wobject_cls, material_cls):
"""Decorator to register an SVG render fu... | pygfx/renderers/svg/_svgrenderer.py | import os
import io
from .. import Renderer, RenderFunctionRegistry
from ...objects import WorldObject
from ...cameras import Camera
from ...linalg import Matrix4, Vector3
registry = RenderFunctionRegistry()
def register_svg_render_function(wobject_cls, material_cls):
"""Decorator to register an SVG render fu... | 0.605566 | 0.31488 |
import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import random
from slot_machine import SlotMachine
class Bandit:
def __init__(self, machine_rate, iteration=10000, sample=10000, method=1):
self.epsilon = 0.25
self.total_iteration = iteration
self.to... | multi-armed_bandit_problem.py | import numpy as np
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
import random
from slot_machine import SlotMachine
class Bandit:
def __init__(self, machine_rate, iteration=10000, sample=10000, method=1):
self.epsilon = 0.25
self.total_iteration = iteration
self.to... | 0.297878 | 0.364127 |
import pytest
import unittest
from mock import patch
from copy import deepcopy
from stackstate_checks.base.stubs import topology, aggregator
from stackstate_checks.base import AgentCheck
from stackstate_checks.aws_topology import AwsTopologyCheck, InitConfig
from .conftest import API_RESULTS
SIMPLE_VPN_GATEWAY = {
... | aws_topology/tests/test_ec2_vpn_gateway.py | import pytest
import unittest
from mock import patch
from copy import deepcopy
from stackstate_checks.base.stubs import topology, aggregator
from stackstate_checks.base import AgentCheck
from stackstate_checks.aws_topology import AwsTopologyCheck, InitConfig
from .conftest import API_RESULTS
SIMPLE_VPN_GATEWAY = {
... | 0.660829 | 0.288206 |
import pytest
from testmodels import models as m
from sierra.management import relationtrees
# FIXTURES AND TEST DATA
pytestmark = pytest.mark.django_db
BAD_RELATION_PARAMS = {
'Invalid model': ('invalid', 'fieldname'),
'Invalid fieldname': (m.EndNode, 'invalid'),
'Fieldname is not a relation': (m.EndN... | django/sierra/sierra/tests/test_relationtrees.py | import pytest
from testmodels import models as m
from sierra.management import relationtrees
# FIXTURES AND TEST DATA
pytestmark = pytest.mark.django_db
BAD_RELATION_PARAMS = {
'Invalid model': ('invalid', 'fieldname'),
'Invalid fieldname': (m.EndNode, 'invalid'),
'Fieldname is not a relation': (m.EndN... | 0.322846 | 0.490419 |
from django.db import models
from django.forms.models import model_to_dict
import json
# Abstract Models
class BaseAsset(models.Model):
class Meta:
abstract = True
def __repr__(self):
return json.dumps(model_to_dict(
self,
fields=[field.name for field in self._meta.fiel... | calixis/plan/submodels/asset.py | from django.db import models
from django.forms.models import model_to_dict
import json
# Abstract Models
class BaseAsset(models.Model):
class Meta:
abstract = True
def __repr__(self):
return json.dumps(model_to_dict(
self,
fields=[field.name for field in self._meta.fiel... | 0.583441 | 0.145267 |
from yaml import load, dump
try:
from yaml import CSafeLoader as SafeLoader
except ImportError:
from yaml import SafeLoader
print("Using Python SafeLoader")
import os
import sys
from sqlalchemy import Table
def importyaml(connection,metadata,sourcePath,language='en'):
invTypes = Table('invTypes',metadata)
... | tableloader/tableFunctions/types.py | from yaml import load, dump
try:
from yaml import CSafeLoader as SafeLoader
except ImportError:
from yaml import SafeLoader
print("Using Python SafeLoader")
import os
import sys
from sqlalchemy import Table
def importyaml(connection,metadata,sourcePath,language='en'):
invTypes = Table('invTypes',metadata)
... | 0.14919 | 0.064212 |
import torch
import torch.nn as nn
from dassl.data import DataManager
from dassl.optim import build_optimizer, build_lr_scheduler
from dassl.utils import count_num_param
from dassl.engine import TRAINER_REGISTRY, TrainerX
from dassl.metrics import compute_accuracy
from dassl.engine.trainer import SimpleNet
from dassl.... | dassl/engine/dg/daeldg.py | import torch
import torch.nn as nn
from dassl.data import DataManager
from dassl.optim import build_optimizer, build_lr_scheduler
from dassl.utils import count_num_param
from dassl.engine import TRAINER_REGISTRY, TrainerX
from dassl.metrics import compute_accuracy
from dassl.engine.trainer import SimpleNet
from dassl.... | 0.891593 | 0.42656 |
import re
from data_extraction.scraper import Scraper
class BetterplaceScraper(Scraper):
"""Scrapes the website https://www.betterplace.org."""
base_url = 'https://www.betterplace.org'
debug = True
def parse(self, response, url):
"""Handles the soupified response of a detail page in the pre... | etl/data_extraction/scrapers/betterplace.py | import re
from data_extraction.scraper import Scraper
class BetterplaceScraper(Scraper):
"""Scrapes the website https://www.betterplace.org."""
base_url = 'https://www.betterplace.org'
debug = True
def parse(self, response, url):
"""Handles the soupified response of a detail page in the pre... | 0.459561 | 0.223239 |
import unittest
from mock import patch
from exporters.exporter_config import ExporterConfig
from exporters.persistence.base_persistence import BasePersistence
from exporters.persistence.pickle_persistence import PicklePersistence
from exporters.utils import remove_if_exists
from .utils import valid_config_with_updates... | tests/test_persistence.py | import unittest
from mock import patch
from exporters.exporter_config import ExporterConfig
from exporters.persistence.base_persistence import BasePersistence
from exporters.persistence.pickle_persistence import PicklePersistence
from exporters.utils import remove_if_exists
from .utils import valid_config_with_updates... | 0.368065 | 0.262523 |
import numpy as np
from wheel_sieve.wheel_sieve_byte import PRIME_GEN
# Memory (bytes) used in sieving numpy array
MEM = 8_000_000
def wheel_sieve_count(lbound, ubound, p_list=(2, 3, 5)):
"""Count primes in [lbound, ubound) using wheel sieve.
Args:
lbound (int): lower bound of range.
ubound ... | wheel_sieve/wheel_sieve_bit.py | import numpy as np
from wheel_sieve.wheel_sieve_byte import PRIME_GEN
# Memory (bytes) used in sieving numpy array
MEM = 8_000_000
def wheel_sieve_count(lbound, ubound, p_list=(2, 3, 5)):
"""Count primes in [lbound, ubound) using wheel sieve.
Args:
lbound (int): lower bound of range.
ubound ... | 0.685634 | 0.527073 |
import imp, numpy, glob, shutil
imp.load_source('common_functions','common_functions.py')
import common_functions as cf
def noise_est(config,logger):
"""
Makes an estimate of the theortically expected noise level for each science target.
Input:
config = The parameters read from the configuration ... | moment_zero.py | import imp, numpy, glob, shutil
imp.load_source('common_functions','common_functions.py')
import common_functions as cf
def noise_est(config,logger):
"""
Makes an estimate of the theortically expected noise level for each science target.
Input:
config = The parameters read from the configuration ... | 0.439988 | 0.384046 |
from copy import copy
import logging
import os
import m3u8
from subprocess import Popen
DEFAULT_VIDEO_ARGS = "-f mpegts -acodec libfaac -vcodec libx264".split(' ')
FFMPEG_THREADS_PER_FILE = 4
def transcode_playlist(playlists, modified_playlist, segments, m3u8_path):
output = list(get_audio_outputs(playlists, mod... | hlsclient/transcode.py | from copy import copy
import logging
import os
import m3u8
from subprocess import Popen
DEFAULT_VIDEO_ARGS = "-f mpegts -acodec libfaac -vcodec libx264".split(' ')
FFMPEG_THREADS_PER_FILE = 4
def transcode_playlist(playlists, modified_playlist, segments, m3u8_path):
output = list(get_audio_outputs(playlists, mod... | 0.158793 | 0.145449 |
from Tkinter import *
from tkFileDialog import asksaveasfilename, askopenfilename
from optparse import OptionParser
import shlex
class App:
def __init__(self, master):
"""Set the name, location of each box"""
frame = Frame(master)
frame.grid(column=0, row=0)
s... | soc_gui.py | from Tkinter import *
from tkFileDialog import asksaveasfilename, askopenfilename
from optparse import OptionParser
import shlex
class App:
def __init__(self, master):
"""Set the name, location of each box"""
frame = Frame(master)
frame.grid(column=0, row=0)
s... | 0.357343 | 0.180053 |
import torch.nn.init as init
__all__ = ['Initializer',
'Initialization',
'WeightInitFunction',
'BiasInitFunction',
'TensorInitFunction']
class Initializer(object):
"""
Base class for all initializers.
"""
# TODO Support LSTMs and GRUs
VALID_LAYERS = {... | inferno/extensions/initializers/base.py | import torch.nn.init as init
__all__ = ['Initializer',
'Initialization',
'WeightInitFunction',
'BiasInitFunction',
'TensorInitFunction']
class Initializer(object):
"""
Base class for all initializers.
"""
# TODO Support LSTMs and GRUs
VALID_LAYERS = {... | 0.487307 | 0.312895 |
from copy import deepcopy
from functools import reduce
from collections.abc import Iterable
from typing import List, Tuple
from nncf.torch.nncf_network import NNCFNetwork
from nncf import NNCFConfig
from tests.torch.test_models.synthetic import PartlyNonDifferentialOutputsModel
from tests.torch.test_models.synthetic ... | tests/torch/test_knowledge_distillation.py | from copy import deepcopy
from functools import reduce
from collections.abc import Iterable
from typing import List, Tuple
from nncf.torch.nncf_network import NNCFNetwork
from nncf import NNCFConfig
from tests.torch.test_models.synthetic import PartlyNonDifferentialOutputsModel
from tests.torch.test_models.synthetic ... | 0.880489 | 0.435841 |
from scipy import stats
from collections import namedtuple
import numpy as np
from splitcli.experiment.weights import Weights
Impact = namedtuple('Impact', ['delta','p_value','mean'])
class EventResult(object):
def __init__(self, event_type, properties={}, property_value=None):
super(EventResult, self)._... | splitcli/experiment/event_result.py | from scipy import stats
from collections import namedtuple
import numpy as np
from splitcli.experiment.weights import Weights
Impact = namedtuple('Impact', ['delta','p_value','mean'])
class EventResult(object):
def __init__(self, event_type, properties={}, property_value=None):
super(EventResult, self)._... | 0.763572 | 0.401746 |
# Authors:
# <NAME> (<EMAIL>)
# $Id: udp.py 2240 2010-12-09 02:01:37Z meddingt $
import socket, time,sys
from Peach.publisher import *
import Peach
def Debug(msg):
if Peach.Engine.engine.Engine.debug:
print msg
class Udp(Publisher):
'''
A simple UDP publisher.
'''
def __init__(self, h... | Peach/Publishers/udp.py |
# Authors:
# <NAME> (<EMAIL>)
# $Id: udp.py 2240 2010-12-09 02:01:37Z meddingt $
import socket, time,sys
from Peach.publisher import *
import Peach
def Debug(msg):
if Peach.Engine.engine.Engine.debug:
print msg
class Udp(Publisher):
'''
A simple UDP publisher.
'''
def __init__(self, h... | 0.224565 | 0.061565 |
import argparse
import collections
import csv
import gzip
import logging
import sys
def get_fh(fh):
try:
c = fh.read(1)
fh.seek(0)
if ord(c) == 0x1f:
return gzip.open(fh, 'rt')
else:
return fh
except:
return sys.stdin
def process(fh, cols, exclude, exclude_ends_with, delimiter, uni... | csvtools/csvcols.py | import argparse
import collections
import csv
import gzip
import logging
import sys
def get_fh(fh):
try:
c = fh.read(1)
fh.seek(0)
if ord(c) == 0x1f:
return gzip.open(fh, 'rt')
else:
return fh
except:
return sys.stdin
def process(fh, cols, exclude, exclude_ends_with, delimiter, uni... | 0.163079 | 0.085061 |
import time
from absl import app, flags, logging
from absl.flags import FLAGS
import core.utils as utils
from core.yolov4 import YOLOv4, decode
from PIL import Image
import cv2
import numpy as np
import tensorflow as tf
flags.DEFINE_string('weights', None, 'name of weights file')
flags.DEFINE_string('image_path', None... | image.py | import time
from absl import app, flags, logging
from absl.flags import FLAGS
import core.utils as utils
from core.yolov4 import YOLOv4, decode
from PIL import Image
import cv2
import numpy as np
import tensorflow as tf
flags.DEFINE_string('weights', None, 'name of weights file')
flags.DEFINE_string('image_path', None... | 0.430626 | 0.23444 |
from django.contrib.auth import get_user_model
from django.core.exceptions import ValidationError
from inventory.common.tests.base_tests import BaseTest
from ..models import InventoryType, Project, Membership
UserModel = get_user_model()
class TestInventoryType(BaseTest):
def __init__(self, name):
s... | inventory/projects/tests/test_projects_models.py |
from django.contrib.auth import get_user_model
from django.core.exceptions import ValidationError
from inventory.common.tests.base_tests import BaseTest
from ..models import InventoryType, Project, Membership
UserModel = get_user_model()
class TestInventoryType(BaseTest):
def __init__(self, name):
s... | 0.588653 | 0.207074 |
import torch
from lcp_physics.lcp.lcp import LCPFunction, LCPOptions
class PdipmEngine():
"""Engine that uses the primal dual interior point method LCP solver.
"""
def __init__(self, max_iter, verbose, extend, solver_type):
self.lcp_options = LCPOptions(max_iter=max_iter,
... | lcp_physics/physics/engines.py | import torch
from lcp_physics.lcp.lcp import LCPFunction, LCPOptions
class PdipmEngine():
"""Engine that uses the primal dual interior point method LCP solver.
"""
def __init__(self, max_iter, verbose, extend, solver_type):
self.lcp_options = LCPOptions(max_iter=max_iter,
... | 0.682468 | 0.361024 |
from typing import Dict, Tuple, Union
import cv2
import numpy as np
from torch import Tensor
from ai_engine.utils.np_utils import (
convert_np_for_vis,
)
def apply_single_mask(
image: np.array, mask: np.array, color: tuple, alpha: float = 0.6
) -> np.array:
"""A method to generate visualization of mask... | ai_engine/utils/visualization_utils.py | from typing import Dict, Tuple, Union
import cv2
import numpy as np
from torch import Tensor
from ai_engine.utils.np_utils import (
convert_np_for_vis,
)
def apply_single_mask(
image: np.array, mask: np.array, color: tuple, alpha: float = 0.6
) -> np.array:
"""A method to generate visualization of mask... | 0.948245 | 0.70069 |
# 2/3 compatibility
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
from future.utils import bytes_to_native_str, native_str_to_bytes
from future.builtins import int, bytes
from .characteristic import GATTCharacteristic
from ..util import BLEUUID, UUIDAcce... | bleep/gatt/service.py |
# 2/3 compatibility
from __future__ import division
from __future__ import print_function
from __future__ import absolute_import
from future.utils import bytes_to_native_str, native_str_to_bytes
from future.builtins import int, bytes
from .characteristic import GATTCharacteristic
from ..util import BLEUUID, UUIDAcce... | 0.798344 | 0.141578 |
from datetime import timedelta
import datetime
from django.conf import settings
from django.contrib.auth.models import AbstractBaseUser, BaseUserManager
from django.db import models
from django.utils import timezone
from accounts.models import User
'''
A device has a devicetype
These will be created by admin
'''
c... | src/devices/models.py | from datetime import timedelta
import datetime
from django.conf import settings
from django.contrib.auth.models import AbstractBaseUser, BaseUserManager
from django.db import models
from django.utils import timezone
from accounts.models import User
'''
A device has a devicetype
These will be created by admin
'''
c... | 0.658527 | 0.197116 |
from collections import OrderedDict
from fontTools.misc.xmlWriter import XMLWriter
import fontFeatures
from io import BytesIO
def glyph(x):
"""Helper routine to document that a glyph name goes in a slot."""
assert isinstance(x, str)
return [x]
class GTableUnparser:
"""Base class for reading binary G... | fontFeatures/ttLib/GTableUnparser.py | from collections import OrderedDict
from fontTools.misc.xmlWriter import XMLWriter
import fontFeatures
from io import BytesIO
def glyph(x):
"""Helper routine to document that a glyph name goes in a slot."""
assert isinstance(x, str)
return [x]
class GTableUnparser:
"""Base class for reading binary G... | 0.905001 | 0.357091 |
import sys
import os
os.chdir(os.path.split(__file__)[0])
sys.path.append('../../') # For functions file
sys.path.append('..') # For config file
import pandas as pd
from sof_config import (analysis_dir, deriv_dir, task,
bad_subs)
from functions import get_sub_list
# Make the output directo... | sof_task/analyses/sof_101_organize_behavioral_data.py | import sys
import os
os.chdir(os.path.split(__file__)[0])
sys.path.append('../../') # For functions file
sys.path.append('..') # For config file
import pandas as pd
from sof_config import (analysis_dir, deriv_dir, task,
bad_subs)
from functions import get_sub_list
# Make the output directo... | 0.208582 | 0.112454 |
import os
import sys
import json
import traceback
import six
import yaml
import requests
from scalrctl import click, defaults, settings, commands, utils
__author__ = '<NAME>, <NAME>'
def _get_spec_path(api_level, extension):
return os.path.join(defaults.CONFIG_DIRECTORY,
'{}.{}'.format(... | scalrctl/commands/internal/update.py | import os
import sys
import json
import traceback
import six
import yaml
import requests
from scalrctl import click, defaults, settings, commands, utils
__author__ = '<NAME>, <NAME>'
def _get_spec_path(api_level, extension):
return os.path.join(defaults.CONFIG_DIRECTORY,
'{}.{}'.format(... | 0.261331 | 0.05549 |
import functools
from io import BytesIO
from typing import ( # pylint: disable=unused-import
Optional, Union, IO, List, Dict, Any, Iterable,
TYPE_CHECKING
)
try:
from urllib.parse import urlparse, quote, unquote
except ImportError:
from urlparse import urlparse # type: ignore
from urllib2 import qu... | sdk/storage/azure-storage-file/azure/storage/file/file_client.py |
import functools
from io import BytesIO
from typing import ( # pylint: disable=unused-import
Optional, Union, IO, List, Dict, Any, Iterable,
TYPE_CHECKING
)
try:
from urllib.parse import urlparse, quote, unquote
except ImportError:
from urlparse import urlparse # type: ignore
from urllib2 import qu... | 0.783947 | 0.105441 |
import multiprocessing
from .prefs import get_prefs
from .operator import *
from .operator_islands import *
from .operator_box import *
from .operator_uv import *
from .utils import *
from .presets import *
from .labels import UvpLabels
from .register import UVP2_OT_SelectUvpEngine
import bpy
class UVP2_OT_SetRo... | scripts/addons/uvpackmaster2/panel_base.py |
import multiprocessing
from .prefs import get_prefs
from .operator import *
from .operator_islands import *
from .operator_box import *
from .operator_uv import *
from .utils import *
from .presets import *
from .labels import UvpLabels
from .register import UVP2_OT_SelectUvpEngine
import bpy
class UVP2_OT_SetRo... | 0.350088 | 0.112649 |
__AUTHOR__ = u"<NAME>, <<EMAIL>>"
__COPYRIGHT__ = u"Copyright (c) 2008 <NAME> <<EMAIL>> and Button Down Design, LLC."
__LICENSE__ = u"Released under the MIT License."
import re, time, datetime, StringIO
try:
import elementtree.ElementTree as ElementTree
except ImportError:
import xml.etree.ElementTree as Elem... | gareports_reader.py | __AUTHOR__ = u"<NAME>, <<EMAIL>>"
__COPYRIGHT__ = u"Copyright (c) 2008 <NAME> <<EMAIL>> and Button Down Design, LLC."
__LICENSE__ = u"Released under the MIT License."
import re, time, datetime, StringIO
try:
import elementtree.ElementTree as ElementTree
except ImportError:
import xml.etree.ElementTree as Elem... | 0.551091 | 0.116211 |
import argparse
import os
import os.path
import re
import sys
import time
from cefpython3 import cefpython as cef
player_info_re = re.compile(r"Player name changed to (\w+) Clan: (\w+) AccountId: (\w+)")
mission_name_re = re.compile(r"Mission name: (.+)")
mission_difficulty_re = re.compile(r" difficulty=(.+)")
b... | endscreen.py |
import argparse
import os
import os.path
import re
import sys
import time
from cefpython3 import cefpython as cef
player_info_re = re.compile(r"Player name changed to (\w+) Clan: (\w+) AccountId: (\w+)")
mission_name_re = re.compile(r"Mission name: (.+)")
mission_difficulty_re = re.compile(r" difficulty=(.+)")
b... | 0.150309 | 0.066297 |
from flask import request, url_for
from flask_ipblock.documents import IPNetwork
class IPBlock(object):
def __init__(self, app, read_preference=None, cache_size=None, cache_ttl=None,
blocking_enabled=True, logging_enabled=False):
"""
Initialize IPBlock and set up a before_request... | flask_ipblock/__init__.py | from flask import request, url_for
from flask_ipblock.documents import IPNetwork
class IPBlock(object):
def __init__(self, app, read_preference=None, cache_size=None, cache_ttl=None,
blocking_enabled=True, logging_enabled=False):
"""
Initialize IPBlock and set up a before_request... | 0.747708 | 0.181155 |
import argparse
import json
import os
import threading
import time
from random import random
import numpy as np
import requests
import tensorflow as tf
from sklearn import metrics
from sklearn.metrics import confusion_matrix, accuracy_score, f1_score
import numpy_encoder
#tf.random.set_random_seed(42) # tensorflow ... | mnist/mnist_client.py | import argparse
import json
import os
import threading
import time
from random import random
import numpy as np
import requests
import tensorflow as tf
from sklearn import metrics
from sklearn.metrics import confusion_matrix, accuracy_score, f1_score
import numpy_encoder
#tf.random.set_random_seed(42) # tensorflow ... | 0.517815 | 0.423875 |
import collections
import logging
import selectors
import socket
LOG = logging.getLogger(__name__)
class Mux:
def __init__(self):
self.listeners = {} # addr -> Fakesocket
self.connected = set() # Each end of a socket pair appears here
self.fd_pool = set(range(10, 1000))
self.... | fake_selectors/faux.py | import collections
import logging
import selectors
import socket
LOG = logging.getLogger(__name__)
class Mux:
def __init__(self):
self.listeners = {} # addr -> Fakesocket
self.connected = set() # Each end of a socket pair appears here
self.fd_pool = set(range(10, 1000))
self.... | 0.464659 | 0.178777 |
"""Class for the ogs FLUID PROPERTY file."""
from ogs5py.fileclasses.base import BlockFile
class MFP(BlockFile):
"""
Class for the ogs FLUID PROPERTY file.
Parameters
----------
task_root : str, optional
Path to the destiny model folder.
Default: cwd+"ogs5model"
t... | ogs5py/fileclasses/mfp/core.py | """Class for the ogs FLUID PROPERTY file."""
from ogs5py.fileclasses.base import BlockFile
class MFP(BlockFile):
"""
Class for the ogs FLUID PROPERTY file.
Parameters
----------
task_root : str, optional
Path to the destiny model folder.
Default: cwd+"ogs5model"
t... | 0.654232 | 0.181825 |
from allennlp import predictors
from allennlp_rc import predictors as rc_predictors
from allennlp_hub.pretrained.helpers import _load_predictor
import allennlp.models
# Models in the main repo
def srl_with_elmo_luheng_2018() -> predictors.SemanticRoleLabelerPredictor:
"""
Semantic Role Labeling
Based o... | allennlp_hub/pretrained/allennlp_pretrained.py | from allennlp import predictors
from allennlp_rc import predictors as rc_predictors
from allennlp_hub.pretrained.helpers import _load_predictor
import allennlp.models
# Models in the main repo
def srl_with_elmo_luheng_2018() -> predictors.SemanticRoleLabelerPredictor:
"""
Semantic Role Labeling
Based o... | 0.864253 | 0.439447 |
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import pi
import funcs as f
from importlib import reload
import dataframe_cleaner
reload(radar1_class)
import radar1_class
from radar1_class import Radar1
import unidecode
from unidecode import unidecode
#final list of columns to choose fr... | src/radar_chart.py | import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
from math import pi
import funcs as f
from importlib import reload
import dataframe_cleaner
reload(radar1_class)
import radar1_class
from radar1_class import Radar1
import unidecode
from unidecode import unidecode
#final list of columns to choose fr... | 0.452052 | 0.414958 |
try:
import xml.etree.cElementTree as ET
except ImportError:
import xml.etree.ElementTree as ET
import numpy as np
from titanium import evaluation, activation
SUPPORTED_NS = {
'4.2': 'http://www.dmg.org/PMML-4_2',
'4.2.1': 'http://www.dmg.org/PMML-4_2',
'4.3': 'http://www.dmg.org/PMML-4_3'
}
cla... | titanium/__init__.py | try:
import xml.etree.cElementTree as ET
except ImportError:
import xml.etree.ElementTree as ET
import numpy as np
from titanium import evaluation, activation
SUPPORTED_NS = {
'4.2': 'http://www.dmg.org/PMML-4_2',
'4.2.1': 'http://www.dmg.org/PMML-4_2',
'4.3': 'http://www.dmg.org/PMML-4_3'
}
cla... | 0.464659 | 0.26301 |
import numpy as np
import os
################################################################################
try:
import cairocffi as cairo
except ImportError:
try:
import cairo
except ImportError:
cairo = None
def create_new_surface(file_format, target=None, width=1024, height=... | script/NetworkDrawer.py | import numpy as np
import os
################################################################################
try:
import cairocffi as cairo
except ImportError:
try:
import cairo
except ImportError:
cairo = None
def create_new_surface(file_format, target=None, width=1024, height=... | 0.630457 | 0.337367 |
from hyperopt import hp
from hyperopt import fmin, tpe, space_eval
#%%
class ParamTuner():
def __init__(self, opt_model,
x,y,
decor=None, scale=False,
cv=None, test_size=None):
"""
The parameter tuning class using Hyperopt module.
Parame... | jostar/utils/_hyperparameter_tuner.py | from hyperopt import hp
from hyperopt import fmin, tpe, space_eval
#%%
class ParamTuner():
def __init__(self, opt_model,
x,y,
decor=None, scale=False,
cv=None, test_size=None):
"""
The parameter tuning class using Hyperopt module.
Parame... | 0.790934 | 0.580382 |
import http.client
from tkinter import *
import xml.etree.ElementTree as etree
import socket
import re
import sys
lgtv = {}
dialogMsg =""
headers = {"Content-Type": "application/atom+xml"}
lgtv["pairingKey"] = "DDGWAF"
class MyDialog:
def __init__(self, parent, dialogMsg):
top = self.top = Toplevel(parent... | lgcommander.py |
import http.client
from tkinter import *
import xml.etree.ElementTree as etree
import socket
import re
import sys
lgtv = {}
dialogMsg =""
headers = {"Content-Type": "application/atom+xml"}
lgtv["pairingKey"] = "DDGWAF"
class MyDialog:
def __init__(self, parent, dialogMsg):
top = self.top = Toplevel(parent... | 0.22431 | 0.05715 |
import logging
from math import floor, sqrt
logging.basicConfig(level=logging.DEBUG)
class Message(object):
def __init__(self, text: str = None):
self.logger = logging.getLogger(type(self).__name__)
self.text = text
self.logger.info('Set text value to {}'.format(self.text))
def __re... | easy/disordered_first_contact/disordered_first_contact.py | import logging
from math import floor, sqrt
logging.basicConfig(level=logging.DEBUG)
class Message(object):
def __init__(self, text: str = None):
self.logger = logging.getLogger(type(self).__name__)
self.text = text
self.logger.info('Set text value to {}'.format(self.text))
def __re... | 0.625552 | 0.198258 |
__all__ = ("MDFadeSlideTransition",)
from kivy.animation import Animation, AnimationTransition
from kivy.uix.screenmanager import (
ScreenManager,
ScreenManagerException,
SlideTransition,
)
class MDFadeSlideTransition(SlideTransition):
_direction = "up"
def start(self, instance_screen_manager: S... | kivymd/uix/transition/transition.py | __all__ = ("MDFadeSlideTransition",)
from kivy.animation import Animation, AnimationTransition
from kivy.uix.screenmanager import (
ScreenManager,
ScreenManagerException,
SlideTransition,
)
class MDFadeSlideTransition(SlideTransition):
_direction = "up"
def start(self, instance_screen_manager: S... | 0.70304 | 0.067886 |
import os
import sys
import json
import argparse
import urllib.request
from urllib.error import HTTPError
def get_tenant_id(tenant, token):
headers = {
"Authorization": "APIToken %s" % token
}
try:
url = "https://%s.console.ves.volterra.io/api/web/namespaces/system" % tenant
requ... | modules/volterra/volterra_resource_site_create.py |
import os
import sys
import json
import argparse
import urllib.request
from urllib.error import HTTPError
def get_tenant_id(tenant, token):
headers = {
"Authorization": "APIToken %s" % token
}
try:
url = "https://%s.console.ves.volterra.io/api/web/namespaces/system" % tenant
requ... | 0.240953 | 0.103612 |
import txros
import numpy as np
from hydrophones.msg import ProcessedPing
from geometry_msgs.msg import Point, PoseStamped, Pose
from navigator_alarm import single_alarm, AlarmListener, AlarmBroadcaster
from twisted.internet import defer
import navigator_tools
import tf
from tf import transformations as trans
ping_sub... | perception/navigator_vision/nodes/pinger_locator.py | import txros
import numpy as np
from hydrophones.msg import ProcessedPing
from geometry_msgs.msg import Point, PoseStamped, Pose
from navigator_alarm import single_alarm, AlarmListener, AlarmBroadcaster
from twisted.internet import defer
import navigator_tools
import tf
from tf import transformations as trans
ping_sub... | 0.370681 | 0.085633 |
# python imports
from __future__ import print_function
import os
import sys
import argparse
# Cityscapes imports
# For semantic segmentation task, we directly call cityscape functions
from thirdParty.cityscapesScripts.cityscapesscripts.evaluation import evalPixelLevelSemanticLabeling
from thirdParty.cityscapesScripts... | lane_segmentation/evaluation/evalPixelLevelSemanticLabeling.py |
# python imports
from __future__ import print_function
import os
import sys
import argparse
# Cityscapes imports
# For semantic segmentation task, we directly call cityscape functions
from thirdParty.cityscapesScripts.cityscapesscripts.evaluation import evalPixelLevelSemanticLabeling
from thirdParty.cityscapesScripts... | 0.524395 | 0.214218 |
from torch.utils.data import Dataset
from data_manager.dcase18_taskb import Dcase18TaskbData
from data_manager.taskb_standrizer import TaskbStandarizer
import numpy as np
class TaskbDevSet (Dataset):
def __init__(self, mode='train', device='a', norm_device=None, transform=None):
super(TaskbDevSet, self)._... | data_loader/data_sets.py | from torch.utils.data import Dataset
from data_manager.dcase18_taskb import Dcase18TaskbData
from data_manager.taskb_standrizer import TaskbStandarizer
import numpy as np
class TaskbDevSet (Dataset):
def __init__(self, mode='train', device='a', norm_device=None, transform=None):
super(TaskbDevSet, self)._... | 0.803983 | 0.431524 |
import unittest
from rdlmpy import RDLMContextManager
from httpretty import HTTPretty, httprettified
from rdlmpy import RDLMLockWaitExceededException
class SpecialException(Exception):
pass
class TestContext(unittest.TestCase):
context = None
server = "localhost"
port = 8888
baseurl = None
r... | tests/test_context.py | import unittest
from rdlmpy import RDLMContextManager
from httpretty import HTTPretty, httprettified
from rdlmpy import RDLMLockWaitExceededException
class SpecialException(Exception):
pass
class TestContext(unittest.TestCase):
context = None
server = "localhost"
port = 8888
baseurl = None
r... | 0.301465 | 0.172102 |
from django.http import Http404, HttpResponse, JsonResponse
from django.contrib.auth.decorators import login_required
from django.shortcuts import render, get_object_or_404, redirect
from django.views.generic import ListView, DetailView, CreateView, UpdateView, DeleteView, FormView
from django.views.generic.base import... | wildlifecompliance/views.py | from django.http import Http404, HttpResponse, JsonResponse
from django.contrib.auth.decorators import login_required
from django.shortcuts import render, get_object_or_404, redirect
from django.views.generic import ListView, DetailView, CreateView, UpdateView, DeleteView, FormView
from django.views.generic.base import... | 0.446012 | 0.062674 |
import os
import traceback
import pandas as pd
from igf_data.illumina.basesMask import BasesMask
from igf_data.utils.sequtils import rev_comp
from igf_data.illumina.samplesheet import SampleSheet
from igf_data.utils.fileutils import get_temp_dir,copy_local_file,check_file_path,remove_dir
from igf_data.process.singlecel... | igf_data/utils/samplesheet_utils.py | import os
import traceback
import pandas as pd
from igf_data.illumina.basesMask import BasesMask
from igf_data.utils.sequtils import rev_comp
from igf_data.illumina.samplesheet import SampleSheet
from igf_data.utils.fileutils import get_temp_dir,copy_local_file,check_file_path,remove_dir
from igf_data.process.singlecel... | 0.384103 | 0.227813 |
__author__ = '<NAME>'
import numpy as np
import pandas as pd
from itertools import combinations
import utils.evaluation as ev
def estimate_invar_spce(para, event_count_matrix):
""" Estimate the Invariant Space using SVD decomposition, return the invariant space size r (integer)
Args:
--------
para: the parameter... | models/mining_invariants.py | __author__ = '<NAME>'
import numpy as np
import pandas as pd
from itertools import combinations
import utils.evaluation as ev
def estimate_invar_spce(para, event_count_matrix):
""" Estimate the Invariant Space using SVD decomposition, return the invariant space size r (integer)
Args:
--------
para: the parameter... | 0.683736 | 0.477798 |
from __future__ import unicode_literals
from django.db import models, migrations
import ezidapp.models.validation
class Migration(migrations.Migration):
dependencies = [
('ezidapp', '0007_storegroup_accounttype'),
]
operations = [
migrations.RemoveField(
model_name='newaccou... | ezidapp/migrations/0008_newaccountworksheet.py | from __future__ import unicode_literals
from django.db import models, migrations
import ezidapp.models.validation
class Migration(migrations.Migration):
dependencies = [
('ezidapp', '0007_storegroup_accounttype'),
]
operations = [
migrations.RemoveField(
model_name='newaccou... | 0.617974 | 0.101411 |
import os.path as osp
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from nuscenes import NuScenes
from nuscenes import NuScenesExplorer
from nuscenes.utils.data_classes import LidarPointCloud
from nuscenes.utils.geometry_utils import BoxVis... | others/pcl.py | import os.path as osp
import matplotlib.pyplot as plt
import matplotlib.cm as cm
from mpl_toolkits.mplot3d import Axes3D
import numpy as np
from nuscenes import NuScenes
from nuscenes import NuScenesExplorer
from nuscenes.utils.data_classes import LidarPointCloud
from nuscenes.utils.geometry_utils import BoxVis... | 0.236869 | 0.471041 |
import os
import shutil
import tempfile
from django import forms
from django.conf import settings
from django.core.files.uploadedfile import SimpleUploadedFile
from django.test import Client, TestCase
from django.urls import reverse
from posts.models import Comment, Follow, Group, Post, User
class TemplatesTest(Tes... | posts/tests/test_views.py | import os
import shutil
import tempfile
from django import forms
from django.conf import settings
from django.core.files.uploadedfile import SimpleUploadedFile
from django.test import Client, TestCase
from django.urls import reverse
from posts.models import Comment, Follow, Group, Post, User
class TemplatesTest(Tes... | 0.321353 | 0.256867 |
import random
import chainer
import chainer.functions as F
import chainer.links as L
import numpy as np
# XML-CNN Network
# =========================================================
class CNN(chainer.Chain):
def __init__(self, **params):
self.in_channels = 1
self.out_channels = params["ou... | xml_cnn_model.py | import random
import chainer
import chainer.functions as F
import chainer.links as L
import numpy as np
# XML-CNN Network
# =========================================================
class CNN(chainer.Chain):
def __init__(self, **params):
self.in_channels = 1
self.out_channels = params["ou... | 0.603231 | 0.178454 |
import argparse
from math import exp
import random
import numpy as np
import torch
import pandas as pd
from utils.config import fetch_configs
from datasets.cifar import SplitCIFARHandler
from net.smallconv import MultiHeadNet
from net.wideresnet import WideResNetMultihead
from utils.run_net import train, evaluate
SEE... | multihead_dual_tasks.py | import argparse
from math import exp
import random
import numpy as np
import torch
import pandas as pd
from utils.config import fetch_configs
from datasets.cifar import SplitCIFARHandler
from net.smallconv import MultiHeadNet
from net.wideresnet import WideResNetMultihead
from utils.run_net import train, evaluate
SEE... | 0.408159 | 0.156556 |
import nose.tools
import sys
sys.path.append('..')
import json
import os
from dcase_framework.parameters import ParameterContainer, ParameterFile
import tempfile
def test_hash():
data_hash_target = 'be2ebe4cb85c65e7e679c55595c62446'
data1 = {
'field1': {
'enable': True,
'1': [... | tests/test_ParameterContainer.py |
import nose.tools
import sys
sys.path.append('..')
import json
import os
from dcase_framework.parameters import ParameterContainer, ParameterFile
import tempfile
def test_hash():
data_hash_target = 'be2ebe4cb85c65e7e679c55595c62446'
data1 = {
'field1': {
'enable': True,
'1': [... | 0.311741 | 0.320635 |
import sqlite3
import re
from json import loads, dumps
from flask import redirect, session, request
from functools import wraps
def login_required(f):
"""
Decorate routes to require login.
http://flask.pocoo.org/docs/1.0/patterns/viewdecorators/
"""
@wraps(f)
def decorated_function(*args, **k... | recipes/helpers.py | import sqlite3
import re
from json import loads, dumps
from flask import redirect, session, request
from functools import wraps
def login_required(f):
"""
Decorate routes to require login.
http://flask.pocoo.org/docs/1.0/patterns/viewdecorators/
"""
@wraps(f)
def decorated_function(*args, **k... | 0.598547 | 0.1126 |
import init_paths
import argparse
import os
import time
import sys
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.optim
import torchvision.transforms as transforms
import torchvision.datasets as datasets
from torch.autograd import Variable
import math
import numpy as np
from utils ... | ImageNet/evaluate.py | import init_paths
import argparse
import os
import time
import sys
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torch.optim
import torchvision.transforms as transforms
import torchvision.datasets as datasets
from torch.autograd import Variable
import math
import numpy as np
from utils ... | 0.392919 | 0.106737 |
from bs4 import BeautifulSoup
import os
import sys
import string
import re
BASE_JAVADOC_URL = "https://docs.oracle.com/javase/8/docs/api/index.html?"
BASE_LOCAL_JAVADOC_DIR = "./docs/api/"
def collectDocFilesFrom(dir):
docFiles = []
for (path, dirs, files) in os.walk(dir):
if 'class-use' not in path:
fo... | lib/fathead/java/parse_utils.py | from bs4 import BeautifulSoup
import os
import sys
import string
import re
BASE_JAVADOC_URL = "https://docs.oracle.com/javase/8/docs/api/index.html?"
BASE_LOCAL_JAVADOC_DIR = "./docs/api/"
def collectDocFilesFrom(dir):
docFiles = []
for (path, dirs, files) in os.walk(dir):
if 'class-use' not in path:
fo... | 0.338405 | 0.136637 |
import torch
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import torchtext
from models.pie_model import PIENet
from models.uncertainty_module import UncertaintyModuleText
from utils.tensor_utils import l2_normalize, sample_gaussian_tensors
def get_pad_mask(max_lengt... | models/caption_encoder.py | import torch
import torch.nn as nn
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence
import torchtext
from models.pie_model import PIENet
from models.uncertainty_module import UncertaintyModuleText
from utils.tensor_utils import l2_normalize, sample_gaussian_tensors
def get_pad_mask(max_lengt... | 0.921061 | 0.342489 |
import os
import math
import logging
from pandac.PandaModules import Texture, NodePath, Camera, DisplayRegion
from pandac.PandaModules import TextureAttrib, CullFaceAttrib
from pandac.PandaModules import GeomVertexReader
from pandac.PandaModules import Vec3
from pandac.PandaModules import OrthographicLens
from pandac.... | src/pano/view/Node2DRenderer.py | import os
import math
import logging
from pandac.PandaModules import Texture, NodePath, Camera, DisplayRegion
from pandac.PandaModules import TextureAttrib, CullFaceAttrib
from pandac.PandaModules import GeomVertexReader
from pandac.PandaModules import Vec3
from pandac.PandaModules import OrthographicLens
from pandac.... | 0.563858 | 0.168515 |
import logging
import os
import signal
import sys
from PyQt5.QtCore import pyqtSignal, QSettings
from PyQt5.QtGui import QIcon
from PyQt5.QtWidgets import QMainWindow, QAction, QFileDialog
from database import Database
from misc import getSPMTVersion, printDbg, initLogs, \
clean_v4_migration, saveCacheSettings, r... | src/spmtApp.py | import logging
import os
import signal
import sys
from PyQt5.QtCore import pyqtSignal, QSettings
from PyQt5.QtGui import QIcon
from PyQt5.QtWidgets import QMainWindow, QAction, QFileDialog
from database import Database
from misc import getSPMTVersion, printDbg, initLogs, \
clean_v4_migration, saveCacheSettings, r... | 0.20142 | 0.089375 |
from common import * # NOQA
import pytest
namespace = {"p_client": None, "ns": None, "cluster": None, "project": None}
def test_wl_sidekick():
p_client = namespace["p_client"]
ns = namespace["ns"]
con = [{"name": "test1",
"image": TEST_CLIENT_IMAGE}]
name = random_test_name("sidekick")
... | tests/v3_api/test_workload.py | from common import * # NOQA
import pytest
namespace = {"p_client": None, "ns": None, "cluster": None, "project": None}
def test_wl_sidekick():
p_client = namespace["p_client"]
ns = namespace["ns"]
con = [{"name": "test1",
"image": TEST_CLIENT_IMAGE}]
name = random_test_name("sidekick")
... | 0.396769 | 0.227684 |
import base64
import requests
import json
import random
from urllib.parse import urlencode
from . import conf
class OauthWeChat(object):
"""微信登录工具"""
def get_code_url(self):
"""
获取微信登录的url
返回说明：redirect_uri?code=CODE&state=STATE；
请求成功返回code和state，否则只有state
"""
... | WeChatLogin.py | import base64
import requests
import json
import random
from urllib.parse import urlencode
from . import conf
class OauthWeChat(object):
"""微信登录工具"""
def get_code_url(self):
"""
获取微信登录的url
返回说明：redirect_uri?code=CODE&state=STATE；
请求成功返回code和state，否则只有state
"""
... | 0.208824 | 0.081923 |
import logging
from flask import Flask, g, request, jsonify
from flask_restx import Resource
from flask_limiter import Limiter
from flask_limiter.util import get_remote_address
import sqlite3 as sql
from handlers.files import file, files
from handlers.users import user, users
from apis import api
from apis.user_model... | main.py | import logging
from flask import Flask, g, request, jsonify
from flask_restx import Resource
from flask_limiter import Limiter
from flask_limiter.util import get_remote_address
import sqlite3 as sql
from handlers.files import file, files
from handlers.users import user, users
from apis import api
from apis.user_model... | 0.436862 | 0.091382 |
import py42.sdk
import py42.settings.debug as debug
import pytest
from py42.exceptions import Py42UnauthorizedError
from requests import Response
from requests.exceptions import ConnectionError
from requests.exceptions import RequestException
from .conftest import create_mock_profile
from code42cli.errors import Code4... | tests/test_sdk_client.py | import py42.sdk
import py42.settings.debug as debug
import pytest
from py42.exceptions import Py42UnauthorizedError
from requests import Response
from requests.exceptions import ConnectionError
from requests.exceptions import RequestException
from .conftest import create_mock_profile
from code42cli.errors import Code4... | 0.544801 | 0.176459 |
import unittest
from gremlin_python.structure.graph import Path, Edge, Vertex
from gremlin_python.process.traversal import T
from graph_notebook.network.EventfulNetwork import EVENT_ADD_NODE
from graph_notebook.network.gremlin.GremlinNetwork import GremlinNetwork
class TestGremlinNetwork(unittest.TestCase):
def t... | test/unit/network/gremlin/test_gremlin_network.py | import unittest
from gremlin_python.structure.graph import Path, Edge, Vertex
from gremlin_python.process.traversal import T
from graph_notebook.network.EventfulNetwork import EVENT_ADD_NODE
from graph_notebook.network.gremlin.GremlinNetwork import GremlinNetwork
class TestGremlinNetwork(unittest.TestCase):
def t... | 0.682045 | 0.333313 |
from datetime import datetime, time, date, timedelta
from time import gmtime
class Time:
def __init__(self, hour=None, minute=None, second=None, time_str=None, minutes=None, seconds=None):
self.time2 = None
if hour is not None:
self.time1 = time(hour, minute, second)
elif tim... | ind2.py | from datetime import datetime, time, date, timedelta
from time import gmtime
class Time:
def __init__(self, hour=None, minute=None, second=None, time_str=None, minutes=None, seconds=None):
self.time2 = None
if hour is not None:
self.time1 = time(hour, minute, second)
elif tim... | 0.602997 | 0.198452 |
import pandas as pd
import logging
import os
import django
from django.core.management.base import BaseCommand
class Command(BaseCommand):
help = 'Takes in the authoritative_agencies_list.csv and the broker_agency_list.csv to make' \
'a modified_authoritative_agencies_list.csv'
logger = logging.g... | usaspending_api/references/management/commands/generate_modified_agencies_list.py | import pandas as pd
import logging
import os
import django
from django.core.management.base import BaseCommand
class Command(BaseCommand):
help = 'Takes in the authoritative_agencies_list.csv and the broker_agency_list.csv to make' \
'a modified_authoritative_agencies_list.csv'
logger = logging.g... | 0.218336 | 0.065485 |
from colorama import Fore, Style
from enum import Enum
from functools import total_ordering
class Logger:
indents = 0
indentsFlag = True
@total_ordering
class Levels:
# __order__ = "CRITICAL FATAL ERROR SUCCESS WARNING NOTICE INFO VERBOSE DEBUG SPAM ALL"
NONE = 100
""" No log is printed if level==NONE"""
... | src/dukepy/logger.py | from colorama import Fore, Style
from enum import Enum
from functools import total_ordering
class Logger:
indents = 0
indentsFlag = True
@total_ordering
class Levels:
# __order__ = "CRITICAL FATAL ERROR SUCCESS WARNING NOTICE INFO VERBOSE DEBUG SPAM ALL"
NONE = 100
""" No log is printed if level==NONE"""
... | 0.328853 | 0.094469 |
HIGH = 1
LOW = 0
def and_gate(in_1, in_2):
if in_1 == HIGH and in_2 == HIGH:
return HIGH
return LOW
def or_gate(in_1, in_2):
if in_1 == HIGH or in_2 == HIGH:
return HIGH
return LOW
def not_gate(in_1):
if in_1 == HIGH:
return LOW
return HIGH
def xor_gate(in_1, in_2... | mu0/Gates.py | HIGH = 1
LOW = 0
def and_gate(in_1, in_2):
if in_1 == HIGH and in_2 == HIGH:
return HIGH
return LOW
def or_gate(in_1, in_2):
if in_1 == HIGH or in_2 == HIGH:
return HIGH
return LOW
def not_gate(in_1):
if in_1 == HIGH:
return LOW
return HIGH
def xor_gate(in_1, in_2... | 0.244453 | 0.499512 |
from nose.tools import eq_
from ycm.completers.all import identifier_completer
def GetCursorIdentifier_StartOfLine_test():
eq_( 'foo',
identifier_completer._GetCursorIdentifier(
{
'column_num': 0,
'line_value': 'foo'
} ) )
eq_( 'fooBar',
identifier_completer... | vim/base/YouCompleteMe/python/ycm/completers/all/tests/identifier_completer_test.py |
from nose.tools import eq_
from ycm.completers.all import identifier_completer
def GetCursorIdentifier_StartOfLine_test():
eq_( 'foo',
identifier_completer._GetCursorIdentifier(
{
'column_num': 0,
'line_value': 'foo'
} ) )
eq_( 'fooBar',
identifier_completer... | 0.670608 | 0.181046 |
from copy import deepcopy
from pickle import dumps
from typing import Any
import numpy as np
from frozendict import frozendict
from autoflow.utils.logging_ import get_logger
class DataContainer():
VALID_INSTANCE = None
dataset_type = None
def __init__(self, dataset_source="", dataset_path=None, dataset... | autoflow/data_container/base.py | from copy import deepcopy
from pickle import dumps
from typing import Any
import numpy as np
from frozendict import frozendict
from autoflow.utils.logging_ import get_logger
class DataContainer():
VALID_INSTANCE = None
dataset_type = None
def __init__(self, dataset_source="", dataset_path=None, dataset... | 0.745491 | 0.272505 |