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 |
|---|---|---|---|---|
"""Tests for functional operations."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.eager import def_function
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import function
from tensorflow.python.fr... | tensorflow/python/ops/functional_ops_test.py | """Tests for functional operations."""
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
from tensorflow.python.eager import def_function
from tensorflow.python.framework import dtypes
from tensorflow.python.framework import function
from tensorflow.python.fr... | 0.87901 | 0.366675 |
import pytest
from convtools import conversion as c
from convtools.base import Breakpoint
def test_base_zip():
meta = {1: "a", 2: "b", 3: "c"}
input_data = {"items": [1, 2, 3], "meta": meta}
converter = (
c.zip(
c.item("items"),
c.repeat(c.item("meta")),
)
... | tests/test_shortcuts.py | import pytest
from convtools import conversion as c
from convtools.base import Breakpoint
def test_base_zip():
meta = {1: "a", 2: "b", 3: "c"}
input_data = {"items": [1, 2, 3], "meta": meta}
converter = (
c.zip(
c.item("items"),
c.repeat(c.item("meta")),
)
... | 0.536556 | 0.632091 |
from config import Names as N
from control.record import Record
from control.html import HtmlElements as H
class AssessmentR(Record):
"""Logic for assessment records.
Assessment records that are part of a workflow have customised titles,
showing the creator and create data of the assessment.
!!! hin... | server/control/cust/assessment_record.py | from config import Names as N
from control.record import Record
from control.html import HtmlElements as H
class AssessmentR(Record):
"""Logic for assessment records.
Assessment records that are part of a workflow have customised titles,
showing the creator and create data of the assessment.
!!! hin... | 0.689724 | 0.459319 |
"""Quadratic DeepOBS dataset."""
import numpy as np
import tensorflow as tf
from . import dataset
class quadratic(dataset.DataSet):
"""DeepOBS data set class to create an n dimensional stochastic quadratic\
testproblem.
This toy data set consists of a fixed number (``train_size``) of iid draws
from ... | deepobs/tensorflow/datasets/quadratic.py | """Quadratic DeepOBS dataset."""
import numpy as np
import tensorflow as tf
from . import dataset
class quadratic(dataset.DataSet):
"""DeepOBS data set class to create an n dimensional stochastic quadratic\
testproblem.
This toy data set consists of a fixed number (``train_size``) of iid draws
from ... | 0.968066 | 0.957278 |
import testtools
class TempestException(Exception):
"""Base Tempest Exception
To correctly use this class, inherit from it and define
a 'message' property. That message will get printf'd
with the keyword arguments provided to the constructor.
"""
message = "An unknown exception occurred"
... | ceilometer/tests/tempest/exceptions.py |
import testtools
class TempestException(Exception):
"""Base Tempest Exception
To correctly use this class, inherit from it and define
a 'message' property. That message will get printf'd
with the keyword arguments provided to the constructor.
"""
message = "An unknown exception occurred"
... | 0.605566 | 0.251883 |
import rosgraph
import rosparam
import rospkg
import rospy
import rosservice
from re import compile
BLACK_LIST_PARAM = ['/rosdistro', '/rosversion', '/run_id']
BLACK_LIST_TOPIC = ["/tf", "/tf_static", "/rosout", "/clock"]
BLACK_LIST_SERV = ["/set_logger_level", "/get_loggers"]
BLACK_LIST_NODE = ["/rosout"]
ACTION_FI... | src/rosgraph_monitor/graph.py | import rosgraph
import rosparam
import rospkg
import rospy
import rosservice
from re import compile
BLACK_LIST_PARAM = ['/rosdistro', '/rosversion', '/run_id']
BLACK_LIST_TOPIC = ["/tf", "/tf_static", "/rosout", "/clock"]
BLACK_LIST_SERV = ["/set_logger_level", "/get_loggers"]
BLACK_LIST_NODE = ["/rosout"]
ACTION_FI... | 0.240061 | 0.093844 |
import olefile
import shutil
import os
import zipfile
import tempfile
import sys
from glob import iglob
from pathlib import Path
def stomp_vba(original_file, stomped_file):
if olefile.isOleFile(original_file):
# Make copy of file to modify.
shutil.copyfile(original_file, stomped_file)
... | internals/stomp_vba.py | import olefile
import shutil
import os
import zipfile
import tempfile
import sys
from glob import iglob
from pathlib import Path
def stomp_vba(original_file, stomped_file):
if olefile.isOleFile(original_file):
# Make copy of file to modify.
shutil.copyfile(original_file, stomped_file)
... | 0.123868 | 0.167083 |
# Copyright (c) 2021-2022 scmanjarrez. All rights reserved.
# This work is licensed under the terms of the MIT license.
import genshinstats.errors as err
import genshinstats as gs
import paimon_gui as gui
import utils as ut
STATE = ut.CMD.NOP
HELP = (
"Hello Traveler, use the following commands to interact with... | paimon_cli.py |
# Copyright (c) 2021-2022 scmanjarrez. All rights reserved.
# This work is licensed under the terms of the MIT license.
import genshinstats.errors as err
import genshinstats as gs
import paimon_gui as gui
import utils as ut
STATE = ut.CMD.NOP
HELP = (
"Hello Traveler, use the following commands to interact with... | 0.52683 | 0.129816 |
from torch.utils.data import DataLoader
import torchvision.datasets as datasets
import torchvision.transforms as transforms
from sotabenchapi.core import BenchmarkResult, check_inputs
from torchbench.utils import send_model_to_device, default_data_to_device
from torchbench.image_classification.utils import evaluate_cl... | torchbench/image_classification/imagenet.py | from torch.utils.data import DataLoader
import torchvision.datasets as datasets
import torchvision.transforms as transforms
from sotabenchapi.core import BenchmarkResult, check_inputs
from torchbench.utils import send_model_to_device, default_data_to_device
from torchbench.image_classification.utils import evaluate_cl... | 0.958895 | 0.626795 |
from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import numpy as np
import os
import sys
from observations.util import maybe_download_and_extract
def paulsen(path):
"""Neurotransmission in Guinea Pig Brains
The `paulsen` data frame has 346 ... | observations/r/paulsen.py | from __future__ import absolute_import
from __future__ import division
from __future__ import print_function
import csv
import numpy as np
import os
import sys
from observations.util import maybe_download_and_extract
def paulsen(path):
"""Neurotransmission in Guinea Pig Brains
The `paulsen` data frame has 346 ... | 0.742328 | 0.504455 |
import datetime
import json
import re
import warnings
import zipfile
from io import BytesIO, StringIO
import numpy as np
import pandas as pd
import requests
from mssdk.futures import cons
from mssdk.futures.requests_fun import requests_link
calendar = cons.get_calendar()
def get_cffex_daily(date: str = "20100401")... | mssdk/futures/futures_daily_bar.py | import datetime
import json
import re
import warnings
import zipfile
from io import BytesIO, StringIO
import numpy as np
import pandas as pd
import requests
from mssdk.futures import cons
from mssdk.futures.requests_fun import requests_link
calendar = cons.get_calendar()
def get_cffex_daily(date: str = "20100401")... | 0.196865 | 0.171304 |
import csv
import itertools
import os
import multiprocessing
import sys
import numpy.random
from typing import Tuple
from matplotlib import pyplot as plt
from tqdm import tqdm
from pandas import DataFrame
from cvrp.aco_cvrp_solver import AntColonyCVRPSolver
from cvrp.augerat_loader import load_augerat_example
from cv... | test.py | import csv
import itertools
import os
import multiprocessing
import sys
import numpy.random
from typing import Tuple
from matplotlib import pyplot as plt
from tqdm import tqdm
from pandas import DataFrame
from cvrp.aco_cvrp_solver import AntColonyCVRPSolver
from cvrp.augerat_loader import load_augerat_example
from cv... | 0.493409 | 0.239911 |
from cmstk.filetypes import TextFile
from typing import Optional, Tuple
class KpointsFile(TextFile):
"""File wrapper for a VASP KPOINTS file.
Args:
filepath: Filepath to a KPOINTS file.
comment: Top line file descriptor.
n_kpoints: Number of K-Points.
mesh_shift: Shift of the ... | cmstk/vasp/kpoints.py | from cmstk.filetypes import TextFile
from typing import Optional, Tuple
class KpointsFile(TextFile):
"""File wrapper for a VASP KPOINTS file.
Args:
filepath: Filepath to a KPOINTS file.
comment: Top line file descriptor.
n_kpoints: Number of K-Points.
mesh_shift: Shift of the ... | 0.9017 | 0.287677 |
from datetime import datetime
from itertools import chain, zip_longest
from pathlib import Path
from typing import Iterable, List, Tuple
import jinja2
from pytestdocgen.object import TestCase, TestDir
here: Path = Path(__file__).parent
# Jinja env with minor tweaks
j_env = jinja2.Environment(
loader=jinja2.FileS... | pytestdocgen/gendoc.py | from datetime import datetime
from itertools import chain, zip_longest
from pathlib import Path
from typing import Iterable, List, Tuple
import jinja2
from pytestdocgen.object import TestCase, TestDir
here: Path = Path(__file__).parent
# Jinja env with minor tweaks
j_env = jinja2.Environment(
loader=jinja2.FileS... | 0.756268 | 0.328853 |
from __future__ import print_function
import sys
import re
import os
import six
input_file = sys.argv[1]
output_dir = sys.argv[2]
sys.argv[:] = []
if not os.path.exists(output_dir):
os.makedirs(output_dir)
import ROOT
ROOT.gROOT.SetBatch(True)
ROOT.gROOT.SetStyle("Plain")
ROOT.gStyle.SetPalette(1)
def get_by... | RecoTauTag/TauTagTools/test/training/training_control_plots.py |
from __future__ import print_function
import sys
import re
import os
import six
input_file = sys.argv[1]
output_dir = sys.argv[2]
sys.argv[:] = []
if not os.path.exists(output_dir):
os.makedirs(output_dir)
import ROOT
ROOT.gROOT.SetBatch(True)
ROOT.gROOT.SetStyle("Plain")
ROOT.gStyle.SetPalette(1)
def get_by... | 0.506103 | 0.145722 |
import numpy as np
import cv2
# Constants
ALPHA = 0.5
FONT = cv2.FONT_HERSHEY_PLAIN
TEXT_SCALE = 1.0
TEXT_THICKNESS = 1
BLACK = (0, 0, 0)
WHITE = (255, 255, 255)
def gen_colors(num_colors):
"""Generate different colors.
# Arguments
num_colors: total number of colors/classes.
# Output
bgrs:... | src/robot_deep_learning/src/utils/visualization.py | import numpy as np
import cv2
# Constants
ALPHA = 0.5
FONT = cv2.FONT_HERSHEY_PLAIN
TEXT_SCALE = 1.0
TEXT_THICKNESS = 1
BLACK = (0, 0, 0)
WHITE = (255, 255, 255)
def gen_colors(num_colors):
"""Generate different colors.
# Arguments
num_colors: total number of colors/classes.
# Output
bgrs:... | 0.60964 | 0.428473 |
import yaml
import os
import re
import dateparser
from unidecode import unidecode
import logging as logger
from collections import OrderedDict
from .plugins import lines
OPTIONS_DEFAULT = {
'remove_whitespace': False,
'remove_accents': False,
'lowercase': False,
'currency': 'EUR',
'date_formats': [... | invoice2data/extract/invoice_template.py | import yaml
import os
import re
import dateparser
from unidecode import unidecode
import logging as logger
from collections import OrderedDict
from .plugins import lines
OPTIONS_DEFAULT = {
'remove_whitespace': False,
'remove_accents': False,
'lowercase': False,
'currency': 'EUR',
'date_formats': [... | 0.619586 | 0.247726 |
from django.db import models
from django.conf import settings
from django.contrib.auth.models import AbstractUser
# кабинет
class Room(models.Model):
room = models.IntegerField()
# ученики
class Student(models.Model):
first_name = models.CharField(max_length=30)
last_name = models.CharField(max_length=30)... | students/K33422/Izmaylova_Anna/web_lab3/lr_3 school/school_app/models.py | from django.db import models
from django.conf import settings
from django.contrib.auth.models import AbstractUser
# кабинет
class Room(models.Model):
room = models.IntegerField()
# ученики
class Student(models.Model):
first_name = models.CharField(max_length=30)
last_name = models.CharField(max_length=30)... | 0.26923 | 0.122628 |
from __future__ import division
import os.path as osp
import cameramodels
import numpy as np
import numpy.ma as ma
import PIL
import scipy.io
import torch
from dense_fusion.datasets.ycb.ycb_utils import get_data_list
from dense_fusion.datasets.ycb.ycb_utils import get_ycb_video_dataset
from dense_fusion.datasets.ycb... | dense_fusion/datasets/ycb/ycb_video_dataset.py | from __future__ import division
import os.path as osp
import cameramodels
import numpy as np
import numpy.ma as ma
import PIL
import scipy.io
import torch
from dense_fusion.datasets.ycb.ycb_utils import get_data_list
from dense_fusion.datasets.ycb.ycb_utils import get_ycb_video_dataset
from dense_fusion.datasets.ycb... | 0.6488 | 0.198511 |
import logging
import traceback
import uuid
from collections import defaultdict
import pymongo
import six
from blitzdb.backends.base import Backend as BaseBackend
from blitzdb.backends.base import NotInTransaction
from blitzdb.backends.mongo.queryset import QuerySet
from blitzdb.document import Document
from blitzdb.... | blitzdb/backends/mongo/backend.py | import logging
import traceback
import uuid
from collections import defaultdict
import pymongo
import six
from blitzdb.backends.base import Backend as BaseBackend
from blitzdb.backends.base import NotInTransaction
from blitzdb.backends.mongo.queryset import QuerySet
from blitzdb.document import Document
from blitzdb.... | 0.571169 | 0.064153 |
# python3
"""Tensorflow-specific implementations of value.FieldSpec."""
from typing import Text, Tuple, Union, Sequence
import edward2 as ed # type: ignore
from gym import spaces
from recsim_ng.core import value
import tensorflow as tf
FieldValue = value.FieldValue
TFInvariant = Union[None, tf.TypeSpec, tf.TensorS... | recsim_ng/lib/tensorflow/field_spec.py |
# python3
"""Tensorflow-specific implementations of value.FieldSpec."""
from typing import Text, Tuple, Union, Sequence
import edward2 as ed # type: ignore
from gym import spaces
from recsim_ng.core import value
import tensorflow as tf
FieldValue = value.FieldValue
TFInvariant = Union[None, tf.TypeSpec, tf.TensorS... | 0.962018 | 0.557243 |
import unittest
import warnings
import mxnet as mx
import numpy as np
def test_print_summary():
data = mx.sym.Variable('data')
bias = mx.sym.Variable('fc1_bias', lr_mult=1.0)
emb1= mx.symbol.Embedding(data = data, name='emb1', input_dim=100, output_dim=28)
conv1= mx.symbol.Convolution(data = emb1, n... | tests/python/unittest/test_viz.py |
import unittest
import warnings
import mxnet as mx
import numpy as np
def test_print_summary():
data = mx.sym.Variable('data')
bias = mx.sym.Variable('fc1_bias', lr_mult=1.0)
emb1= mx.symbol.Embedding(data = data, name='emb1', input_dim=100, output_dim=28)
conv1= mx.symbol.Convolution(data = emb1, n... | 0.398875 | 0.530905 |
import tensorflow as tf
import tensorflow.keras as ks
from kgcnn.layers.conv.dimenet_conv import DimNetInteractionPPBlock, DimNetOutputBlock
from kgcnn.layers.embedding import EmbeddingDimeBlock
from kgcnn.layers.gather import GatherNodes
from kgcnn.layers.geom import SphericalBasisLayer, NodeDistance, EdgeAngle, Bess... | kgcnn/literature/DimeNetPP.py | import tensorflow as tf
import tensorflow.keras as ks
from kgcnn.layers.conv.dimenet_conv import DimNetInteractionPPBlock, DimNetOutputBlock
from kgcnn.layers.embedding import EmbeddingDimeBlock
from kgcnn.layers.gather import GatherNodes
from kgcnn.layers.geom import SphericalBasisLayer, NodeDistance, EdgeAngle, Bess... | 0.935927 | 0.45175 |
from ..HeightContainer import UniformTopographyInterface
def scale_dependent_statistical_property(topography, func, n=1, scale_factor=None, distance=None):
"""
Compute statistical properties of a uniform topography at specific scales.
The scale is specified either by `scale_factors` or `distance`. These
... | SurfaceTopography/Uniform/ScaleDependentStatistics.py |
from ..HeightContainer import UniformTopographyInterface
def scale_dependent_statistical_property(topography, func, n=1, scale_factor=None, distance=None):
"""
Compute statistical properties of a uniform topography at specific scales.
The scale is specified either by `scale_factors` or `distance`. These
... | 0.957606 | 0.795618 |
from tcutils.util import retry,get_random_name
from vnc_api.vnc_api import RouteAggregate, RouteListType, ServiceInterfaceTag
import fixtures
import re
class RouteAggregateFixture(fixtures.Fixture):
def __init__(self, connections, prefix=None):
self.connections = connections
self.inputs = connecti... | fixtures/route_agg.py | from tcutils.util import retry,get_random_name
from vnc_api.vnc_api import RouteAggregate, RouteListType, ServiceInterfaceTag
import fixtures
import re
class RouteAggregateFixture(fixtures.Fixture):
def __init__(self, connections, prefix=None):
self.connections = connections
self.inputs = connecti... | 0.427277 | 0.068444 |
import math
import time
import torch
import torch.nn.functional as F
from tensornet.engine.ops.regularizer import l1
from tensornet.engine.ops.checkpoint import ModelCheckpoint
from tensornet.engine.ops.tensorboard import TensorBoard
from tensornet.data.processing import InfiniteDataLoader
from tensornet.utils.progres... | tensornet/engine/learner.py | import math
import time
import torch
import torch.nn.functional as F
from tensornet.engine.ops.regularizer import l1
from tensornet.engine.ops.checkpoint import ModelCheckpoint
from tensornet.engine.ops.tensorboard import TensorBoard
from tensornet.data.processing import InfiniteDataLoader
from tensornet.utils.progres... | 0.934939 | 0.316739 |
"""Events functions"""
import numpy as np
# From Salamon's code
# https://github.com/justinsalamon/scaper_waspaa2017/blob/master/urban_sed/util.py
def contiguous_regions(act):
act = np.asarray(act)
onsets = np.where(np.diff(act) == 1)[0] + 1
offsets = np.where(np.diff(act) == -1)[0] + 1
# SPECIAL C... | dcase_models/util/events.py | """Events functions"""
import numpy as np
# From Salamon's code
# https://github.com/justinsalamon/scaper_waspaa2017/blob/master/urban_sed/util.py
def contiguous_regions(act):
act = np.asarray(act)
onsets = np.where(np.diff(act) == 1)[0] + 1
offsets = np.where(np.diff(act) == -1)[0] + 1
# SPECIAL C... | 0.888517 | 0.751089 |
from __future__ import print_function
import sys
import os
import argparse
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torchvision.transforms as transforms
from torch.autograd import Variable
from data import VOC_ROOT, VOC_CLASSES as labelmap
from PIL import Image
from data import VOC... | test.py | from __future__ import print_function
import sys
import os
import argparse
import torch
import torch.nn as nn
import torch.backends.cudnn as cudnn
import torchvision.transforms as transforms
from torch.autograd import Variable
from data import VOC_ROOT, VOC_CLASSES as labelmap
from PIL import Image
from data import VOC... | 0.502441 | 0.238622 |
from django.urls import reverse
from rest_framework import status
from rest_framework.test import APITestCase
from CrossData.API.models import *
class EndpointPOSTTestCase(APITestCase):
def setUp(self):
self.url = reverse("games_view")
self.data = [
{
"id_steam": 123,... | CrossData/API/tests.py | from django.urls import reverse
from rest_framework import status
from rest_framework.test import APITestCase
from CrossData.API.models import *
class EndpointPOSTTestCase(APITestCase):
def setUp(self):
self.url = reverse("games_view")
self.data = [
{
"id_steam": 123,... | 0.4917 | 0.339089 |
from time import time
from java.awt import Color
from java.awt.image import BufferedImage
from de.qfs.apps.qftest.shared.extensions.image import ImageRep
global RGBArray
class RGBArray:
"""
Custom implementation of array holding RGB data of image
Basic init/get/set operations defined
"""
def _... | rgb-array.py | from time import time
from java.awt import Color
from java.awt.image import BufferedImage
from de.qfs.apps.qftest.shared.extensions.image import ImageRep
global RGBArray
class RGBArray:
"""
Custom implementation of array holding RGB data of image
Basic init/get/set operations defined
"""
def _... | 0.789558 | 0.303783 |
from __future__ import unicode_literals
import datetime
import re
import six
DATE = re.compile(
r'^(\/Date\((?P<timestamp>-?\d+)((?P<offset_h>[-+]\d\d)(?P<offset_m>\d\d))?\)\/)'
r'|'
r'((?P<year>\d{4})-(?P<month>[0-2]\d)-0?(?P<day>[0-3]\d)'
r'T'
r'(?P<hour>[0-5]\d):(?P<minute>[0-5]\d):(?P<second>... | xero/utils.py | from __future__ import unicode_literals
import datetime
import re
import six
DATE = re.compile(
r'^(\/Date\((?P<timestamp>-?\d+)((?P<offset_h>[-+]\d\d)(?P<offset_m>\d\d))?\)\/)'
r'|'
r'((?P<year>\d{4})-(?P<month>[0-2]\d)-0?(?P<day>[0-3]\d)'
r'T'
r'(?P<hour>[0-5]\d):(?P<minute>[0-5]\d):(?P<second>... | 0.591251 | 0.436262 |
import asyncio
import copy
import itertools
import re
from base64 import b64decode
from datetime import datetime
from app.service.base_service import BaseService
class PlanningService(BaseService):
def __init__(self):
self.log = self.add_service('planning_svc', self)
async def select_links(self, op... | app/service/planning_svc.py | import asyncio
import copy
import itertools
import re
from base64 import b64decode
from datetime import datetime
from app.service.base_service import BaseService
class PlanningService(BaseService):
def __init__(self):
self.log = self.add_service('planning_svc', self)
async def select_links(self, op... | 0.529993 | 0.154217 |
import itertools
import pytest
from opentrons.broker import publish
from opentrons.api import Session
from opentrons.api.session import _accumulate, _get_labware, _dedupe
from tests.opentrons.conftest import state
from functools import partial
state = partial(state, 'session')
@pytest.fixture
def labware_setup():
... | api/tests/opentrons/api/test_session.py | import itertools
import pytest
from opentrons.broker import publish
from opentrons.api import Session
from opentrons.api.session import _accumulate, _get_labware, _dedupe
from tests.opentrons.conftest import state
from functools import partial
state = partial(state, 'session')
@pytest.fixture
def labware_setup():
... | 0.582729 | 0.500244 |
import numpy as np
import torch.nn as nn
from thop import profile
from thop import clever_format
class OpsCounter():
def __init__(self, count_backward=False):
self.verbose = False
self.multiplier=2 if count_backward else 1 # counts foward + backward pass MACs
self.task_mac_counter, self.ta... | utils/ops_counter.py | import numpy as np
import torch.nn as nn
from thop import profile
from thop import clever_format
class OpsCounter():
def __init__(self, count_backward=False):
self.verbose = False
self.multiplier=2 if count_backward else 1 # counts foward + backward pass MACs
self.task_mac_counter, self.ta... | 0.861887 | 0.159643 |
from pyfluminus.api import name, modules, get_announcements, current_term
from pyfluminus.structs import Module
from pyfluminus.fluminus import get_links_for_module
from app import db
from app.models import User, User_Mods
from app.extra_api import get_class_grps
from datetime import datetime
def get_active_mods(auth... | app/util.py | from pyfluminus.api import name, modules, get_announcements, current_term
from pyfluminus.structs import Module
from pyfluminus.fluminus import get_links_for_module
from app import db
from app.models import User, User_Mods
from app.extra_api import get_class_grps
from datetime import datetime
def get_active_mods(auth... | 0.614278 | 0.304882 |
import numpy as np
from .utils_complexity_attractor import _attractor_lorenz
def complexity_simulate(
duration=10, sampling_rate=1000, method="ornstein", hurst_exponent=0.5, **kwargs
):
"""**Simulate chaotic time series**
This function generates a chaotic signal using different algorithms and complex sy... | neurokit2/complexity/utils_complexity_simulate.py | import numpy as np
from .utils_complexity_attractor import _attractor_lorenz
def complexity_simulate(
duration=10, sampling_rate=1000, method="ornstein", hurst_exponent=0.5, **kwargs
):
"""**Simulate chaotic time series**
This function generates a chaotic signal using different algorithms and complex sy... | 0.9243 | 0.659857 |
__version__ = "1.33.0"
__author__ = "AccelByte"
__email__ = "<EMAIL>"
# pylint: disable=line-too-long
from .handlers_get_users_presence_response import HandlersGetUsersPresenceResponse
from .handlers_user_presence import HandlersUserPresence
from .log_app_message_declaration import LogAppMessageDeclaration
from .mod... | accelbyte_py_sdk/api/lobby/models/__init__.py |
__version__ = "1.33.0"
__author__ = "AccelByte"
__email__ = "<EMAIL>"
# pylint: disable=line-too-long
from .handlers_get_users_presence_response import HandlersGetUsersPresenceResponse
from .handlers_user_presence import HandlersUserPresence
from .log_app_message_declaration import LogAppMessageDeclaration
from .mod... | 0.360714 | 0.029987 |
import json
import os
import random
import sys
import time
from typing import Dict, Optional, Callable, Any
import numpy as np
import tensorflow as tf
from tensorflow.python.training.tracking import data_structures as tf_data_structures
from dpu_utils.utils import RichPath
from ..data import DataFold, GraphDataset
fr... | tf2_gnn/cli_utils/training_utils.py | import json
import os
import random
import sys
import time
from typing import Dict, Optional, Callable, Any
import numpy as np
import tensorflow as tf
from tensorflow.python.training.tracking import data_structures as tf_data_structures
from dpu_utils.utils import RichPath
from ..data import DataFold, GraphDataset
fr... | 0.687525 | 0.198433 |
import json
import logging
from . import model
from . import utils
class Security(object):
"""Class to thread hold to sell when the lost in a transaction is
too high."""
def __init__(self, config_dict):
"""Class Initialisation."""
logging.debug('')
config = json.load(open(config_d... | crypto_trading/algo/security.py | import json
import logging
from . import model
from . import utils
class Security(object):
"""Class to thread hold to sell when the lost in a transaction is
too high."""
def __init__(self, config_dict):
"""Class Initialisation."""
logging.debug('')
config = json.load(open(config_d... | 0.804098 | 0.10732 |
from __future__ import unicode_literals
try:
from collections import Counter
except ImportError:
from backport_collections import Counter
import datetime
from operator import attrgetter
from django.db import models
from django.utils.timezone import now
from aldryn_apphooks_config.managers.base import Manag... | js_services/managers.py |
from __future__ import unicode_literals
try:
from collections import Counter
except ImportError:
from backport_collections import Counter
import datetime
from operator import attrgetter
from django.db import models
from django.utils.timezone import now
from aldryn_apphooks_config.managers.base import Manag... | 0.486819 | 0.161783 |
import logging
from django.contrib import messages
from django.contrib.auth.decorators import user_passes_test
from django.urls import reverse
from django.http import HttpResponseRedirect
from django.shortcuts import render
from dojo.utils import add_breadcrumb
from dojo.forms import ToolTypeForm
from dojo.models impo... | dojo/tool_type/views.py | import logging
from django.contrib import messages
from django.contrib.auth.decorators import user_passes_test
from django.urls import reverse
from django.http import HttpResponseRedirect
from django.shortcuts import render
from dojo.utils import add_breadcrumb
from dojo.forms import ToolTypeForm
from dojo.models impo... | 0.389198 | 0.064624 |
from collections import namedtuple
import numpy as np
import scipy.stats
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as cols
from .utils import hollow_matrix
from .utils import observations
from .utils import rgb_is_dark
class MarkovError(Exception):
pass
def regularize... | striplog/markov.py | from collections import namedtuple
import numpy as np
import scipy.stats
import matplotlib.pyplot as plt
import matplotlib.cm as cm
import matplotlib.colors as cols
from .utils import hollow_matrix
from .utils import observations
from .utils import rgb_is_dark
class MarkovError(Exception):
pass
def regularize... | 0.888813 | 0.572783 |
from django.conf.urls.defaults import patterns, url
from django.core.exceptions import ObjectDoesNotExist
import django.db.models
from django.http import HttpResponse, HttpResponseNotFound
from django.shortcuts import get_object_or_404
from django.template.response import TemplateResponse
from ..core.app import Satchl... | satchless/product/app.py | from django.conf.urls.defaults import patterns, url
from django.core.exceptions import ObjectDoesNotExist
import django.db.models
from django.http import HttpResponse, HttpResponseNotFound
from django.shortcuts import get_object_or_404
from django.template.response import TemplateResponse
from ..core.app import Satchl... | 0.572006 | 0.072604 |
from typing import Dict, List, Union, Any
import requests
from e2e.Classes.Merit.Blockchain import Blockchain
from e2e.Meros.RPC import RPC
from e2e.Tests.Errors import TestError
def request(
rpc: RPC,
req: Union[List[Any], Dict[str, Any]],
headers: Dict[str, str] = {}
) -> Union[List[Any], Dict[str, Any]]:
... | e2e/Tests/RPC/BatchTest.py | from typing import Dict, List, Union, Any
import requests
from e2e.Classes.Merit.Blockchain import Blockchain
from e2e.Meros.RPC import RPC
from e2e.Tests.Errors import TestError
def request(
rpc: RPC,
req: Union[List[Any], Dict[str, Any]],
headers: Dict[str, str] = {}
) -> Union[List[Any], Dict[str, Any]]:
... | 0.718693 | 0.315525 |
import math
import argparse
import itertools
import csv
import time
import numpy as np
from astropy import units as u
from astropy.coordinates import SkyCoord
from astroquery.simbad import Simbad
from os.path import splitext
from utils import CatEntry, convertRADEC
def generate_guide_catalog(catalog):
"""Generat... | startrackerpy/server/startracker/catalogs/guide_stars_catalog.py | import math
import argparse
import itertools
import csv
import time
import numpy as np
from astropy import units as u
from astropy.coordinates import SkyCoord
from astroquery.simbad import Simbad
from os.path import splitext
from utils import CatEntry, convertRADEC
def generate_guide_catalog(catalog):
"""Generat... | 0.381565 | 0.285328 |
from __future__ import print_function
import amber_repo
import boot_data
import filecmp
import logging
import os
import re
import subprocess
import sys
import target
import tempfile
import time
import uuid
from common import SDK_ROOT, EnsurePathExists, GetHostToolPathFromPlatform
# The maximum times to attempt mDNS ... | build/fuchsia/device_target.py | from __future__ import print_function
import amber_repo
import boot_data
import filecmp
import logging
import os
import re
import subprocess
import sys
import target
import tempfile
import time
import uuid
from common import SDK_ROOT, EnsurePathExists, GetHostToolPathFromPlatform
# The maximum times to attempt mDNS ... | 0.637595 | 0.134634 |
__version__ = '3.2.4rc2'
import time
import sys
from . import ca
from . import dbr
from . import pv
from . import alarm
from . import device
from . import motor
from . import multiproc
PV = pv.PV
Alarm = alarm.Alarm
Motor = motor.Motor
Device = device.Device
poll = ca.poll
get_pv = pv.get_pv
CAProcess = multipr... | lib/__init__.py | __version__ = '3.2.4rc2'
import time
import sys
from . import ca
from . import dbr
from . import pv
from . import alarm
from . import device
from . import motor
from . import multiproc
PV = pv.PV
Alarm = alarm.Alarm
Motor = motor.Motor
Device = device.Device
poll = ca.poll
get_pv = pv.get_pv
CAProcess = multipr... | 0.405684 | 0.116286 |
from telemetry.page import page as page_module
from telemetry import story
from page_sets import webgl_supported_shared_state
class ToughWebglCasesPage(page_module.Page):
def __init__(self, url, page_set):
super(ToughWebglCasesPage, self).__init__(
url=url, page_set=page_set,
shared_page_stat... | src/tools/perf/page_sets/tough_webgl_cases.py |
from telemetry.page import page as page_module
from telemetry import story
from page_sets import webgl_supported_shared_state
class ToughWebglCasesPage(page_module.Page):
def __init__(self, url, page_set):
super(ToughWebglCasesPage, self).__init__(
url=url, page_set=page_set,
shared_page_stat... | 0.530723 | 0.059265 |
from sys import version_info
if version_info >= (2, 6, 0):
def swig_import_helper():
from os.path import dirname
import imp
fp = None
try:
fp, pathname, description = imp.find_module('_SimController_ZoneControlTemperature_Thermostat', [dirname(__file__)])
exc... | SimModel_Python_API/simmodel_swig/Release/SimController_ZoneControlTemperature_Thermostat.py |
from sys import version_info
if version_info >= (2, 6, 0):
def swig_import_helper():
from os.path import dirname
import imp
fp = None
try:
fp, pathname, description = imp.find_module('_SimController_ZoneControlTemperature_Thermostat', [dirname(__file__)])
exc... | 0.258139 | 0.071916 |
import numpy as np
from pymanopt.manifolds.manifold import Manifold
class PoincareBall(Manifold):
r"""The Poincare ball.
The Poincare ball of dimension ``n``.
Elements are represented as arrays of shape ``(n,)`` if ``k = 1``.
For ``k > 1``, the class represents the product manifold of ``k`` Poincare... | pymanopt/manifolds/hyperbolic.py | import numpy as np
from pymanopt.manifolds.manifold import Manifold
class PoincareBall(Manifold):
r"""The Poincare ball.
The Poincare ball of dimension ``n``.
Elements are represented as arrays of shape ``(n,)`` if ``k = 1``.
For ``k > 1``, the class represents the product manifold of ``k`` Poincare... | 0.949902 | 0.732089 |
import pytest
from pandas import DataFrame
from pandas.testing import assert_frame_equal
from numpy.testing import assert_array_equal
from tidybear import rename
@pytest.fixture
def df():
return DataFrame({"A": [1, 2],"B": [3, 4]})
def test_canary():
pass
def test_rename_no_args(df):
assert_frame_equal... | tests/test_df_functions/test_rename.py | import pytest
from pandas import DataFrame
from pandas.testing import assert_frame_equal
from numpy.testing import assert_array_equal
from tidybear import rename
@pytest.fixture
def df():
return DataFrame({"A": [1, 2],"B": [3, 4]})
def test_canary():
pass
def test_rename_no_args(df):
assert_frame_equal... | 0.536313 | 0.784505 |
import requests
import sys
import logging
logging.captureWarnings(True)
import config
""" Get all the users of the VOMS VO with their detailed information
:return: user dictionary keyed by the user DN
"""
class vomsApi:
def getUsers(self, hostname, port, vo_name):
result = None
url = "https://%... | lib/vomsApi.py | import requests
import sys
import logging
logging.captureWarnings(True)
import config
""" Get all the users of the VOMS VO with their detailed information
:return: user dictionary keyed by the user DN
"""
class vomsApi:
def getUsers(self, hostname, port, vo_name):
result = None
url = "https://%... | 0.16398 | 0.0771 |
import cv2
import numpy as np
from common import HostNode, get_property_value
from PyFlow.Core.Common import *
from PyFlow.Core.NodeBase import NodePinsSuggestionsHelper
from config import DEBUG
def hex_to_rgb(hex_string):
r_hex = hex_string[1:3]
g_hex = hex_string[3:5]
b_hex = hex_string[5:7]
return... | PyFlow/Packages/DepthAI_Host/Nodes/FrameOps/BBoxOverlayNode.py | import cv2
import numpy as np
from common import HostNode, get_property_value
from PyFlow.Core.Common import *
from PyFlow.Core.NodeBase import NodePinsSuggestionsHelper
from config import DEBUG
def hex_to_rgb(hex_string):
r_hex = hex_string[1:3]
g_hex = hex_string[3:5]
b_hex = hex_string[5:7]
return... | 0.592313 | 0.287693 |
from .base import * # noqa
from .base import env
from datetime import timedelta
# GENERAL
# ------------------------------------------------------------------------------
# https://docs.djangoproject.com/en/dev/ref/settings/#debug
DEBUG = False
# https://docs.djangoproject.com/en/dev/ref/settings/#secret-key
SECRET_K... | CritsAndCoffee.Instagram.API/config/settings/test.py | from .base import * # noqa
from .base import env
from datetime import timedelta
# GENERAL
# ------------------------------------------------------------------------------
# https://docs.djangoproject.com/en/dev/ref/settings/#debug
DEBUG = False
# https://docs.djangoproject.com/en/dev/ref/settings/#secret-key
SECRET_K... | 0.384912 | 0.071949 |
from mlmo.utils.constants.checkpoint import MODEL_PARAMS, OPTIMIZER_STATE
from mlmo.interfaces import BaseIModel
from torch.nn import Module
from mlmo.utils.helpers.loading_and_saving import load_embeddings
from torch.optim import Adam
from logging import getLogger
import torch as T
from torch.nn.utils import clip_grad... | mlmo/interfaces/i_torch_model.py | from mlmo.utils.constants.checkpoint import MODEL_PARAMS, OPTIMIZER_STATE
from mlmo.interfaces import BaseIModel
from torch.nn import Module
from mlmo.utils.helpers.loading_and_saving import load_embeddings
from torch.optim import Adam
from logging import getLogger
import torch as T
from torch.nn.utils import clip_grad... | 0.894208 | 0.345547 |
from __future__ import division
import datetime
import logging
import numpy as np
from ...simple import load_result_file
from utils.misc import display_progress
from video.filters import FilterCrop, FilterDropFrames
from video.io import VideoComposer
from video.analysis.shapes import Rectangle
def make_cropped_vi... | mouse_burrows/scripts/functions/cropped_movie.py | from __future__ import division
import datetime
import logging
import numpy as np
from ...simple import load_result_file
from utils.misc import display_progress
from video.filters import FilterCrop, FilterDropFrames
from video.io import VideoComposer
from video.analysis.shapes import Rectangle
def make_cropped_vi... | 0.627267 | 0.295471 |
import ddt
from ggrc.models import all_models
from integration.ggrc.access_control import rbac_factories
from integration.ggrc.access_control.acl_propagation import base
from integration.ggrc.utils import helpers
@ddt.ddt
class TestAuditorsPropagation(base.TestACLPropagation):
"""Test Audit Captains role permissio... | test/integration/ggrc/access_control/acl_propagation/test_audit_captains.py | import ddt
from ggrc.models import all_models
from integration.ggrc.access_control import rbac_factories
from integration.ggrc.access_control.acl_propagation import base
from integration.ggrc.utils import helpers
@ddt.ddt
class TestAuditorsPropagation(base.TestACLPropagation):
"""Test Audit Captains role permissio... | 0.397354 | 0.278574 |
import os
import torch
import torchvision
import cnn_models.conv_forward_model as convForwModel
import cnn_models.help_fun as cnn_hf
import datasets
import model_manager
from cnn_models.wide_resnet_imagenet import Wide_ResNet_imagenet
import cnn_models.resnet_kfilters as resnet_kfilters
import functools
import quantiza... | resnet34_doublefilters.py | import os
import torch
import torchvision
import cnn_models.conv_forward_model as convForwModel
import cnn_models.help_fun as cnn_hf
import datasets
import model_manager
from cnn_models.wide_resnet_imagenet import Wide_ResNet_imagenet
import cnn_models.resnet_kfilters as resnet_kfilters
import functools
import quantiza... | 0.346099 | 0.152253 |
import time
from gaiatest import GaiaTestCase
from gaiatest.apps.messages.app import Messages
from gaiatest.mocks.mock_contact import MockContact
from gaiatest.apps.contacts.regions.contact_form import NewContact
from gaiatest.apps.contacts.app import Contacts
class TestSmsCreateContact(GaiaTestCase):
def setU... | tests/python/gaia-ui-tests/gaiatest/tests/functional/messages/test_add_to_new_contact_from_messages.py |
import time
from gaiatest import GaiaTestCase
from gaiatest.apps.messages.app import Messages
from gaiatest.mocks.mock_contact import MockContact
from gaiatest.apps.contacts.regions.contact_form import NewContact
from gaiatest.apps.contacts.app import Contacts
class TestSmsCreateContact(GaiaTestCase):
def setU... | 0.558688 | 0.117016 |
# # s_shrink_cov_glasso [<img src="https://www.arpm.co/lab/icons/icon_permalink.png" width=30 height=30 style="display: inline;">](https://www.arpm.co/lab/redirect.php?code=s_shrink_cov_glasso&codeLang=Python)
# For details, see [here](https://www.arpm.co/lab/redirect.php?permalink=Glasso_estimate).
# +
import numpy ... | scripts/sources/s_shrink_cov_glasso.py |
# # s_shrink_cov_glasso [<img src="https://www.arpm.co/lab/icons/icon_permalink.png" width=30 height=30 style="display: inline;">](https://www.arpm.co/lab/redirect.php?code=s_shrink_cov_glasso&codeLang=Python)
# For details, see [here](https://www.arpm.co/lab/redirect.php?permalink=Glasso_estimate).
# +
import numpy ... | 0.500244 | 0.567577 |
from numpy.linalg import svd
from numpy import array, sqrt, sum, zeros, trace, dot, transpose,\
divide, square, subtract, shape, any, abs, mean
from numpy import append as numpy_append
__author__ = "<NAME>"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["<NAME>"]
__license__ = "GPL"
__ver... | scripts/venv/lib/python2.7/site-packages/cogent/cluster/procrustes.py | from numpy.linalg import svd
from numpy import array, sqrt, sum, zeros, trace, dot, transpose,\
divide, square, subtract, shape, any, abs, mean
from numpy import append as numpy_append
__author__ = "<NAME>"
__copyright__ = "Copyright 2007-2012, The Cogent Project"
__credits__ = ["<NAME>"]
__license__ = "GPL"
__ver... | 0.871338 | 0.76238 |
# Lint as: python3
"""TODO(tsitsulin): add headers, tests, and improve style."""
from absl import app
from absl import flags
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.metrics import normalized_mutual_info_score
import tensorflow.compat.v2 as tf
from graph_embedding.dmon.models.multila... | graph_embedding/dmon/train_gcn.py |
# Lint as: python3
"""TODO(tsitsulin): add headers, tests, and improve style."""
from absl import app
from absl import flags
import numpy as np
from sklearn.metrics import accuracy_score
from sklearn.metrics import normalized_mutual_info_score
import tensorflow.compat.v2 as tf
from graph_embedding.dmon.models.multila... | 0.544801 | 0.424889 |
import logging
import pytest
from collections import namedtuple
from streamsets.testframework.markers import sdc_min_version
logger = logging.getLogger(__name__)
# Port for SDC RPC stages to exchange error records
SDC_RPC_LISTENING_PORT = 20000
SDC_RPC_ID = 'lifecycle'
@pytest.fixture(scope='module')
def sdc_comm... | pipeline/test_lifecycle_events.py |
import logging
import pytest
from collections import namedtuple
from streamsets.testframework.markers import sdc_min_version
logger = logging.getLogger(__name__)
# Port for SDC RPC stages to exchange error records
SDC_RPC_LISTENING_PORT = 20000
SDC_RPC_ID = 'lifecycle'
@pytest.fixture(scope='module')
def sdc_comm... | 0.650689 | 0.236373 |
import io
import os
import subprocess
from setuptools import setup
here = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(here, "requirements.txt")) as f:
requirements = f.read().splitlines()
def readme():
with open("README.rst") as f:
return f.read()
git_version = "2.3.0"
if _... | setup.py | import io
import os
import subprocess
from setuptools import setup
here = os.path.abspath(os.path.dirname(__file__))
with open(os.path.join(here, "requirements.txt")) as f:
requirements = f.read().splitlines()
def readme():
with open("README.rst") as f:
return f.read()
git_version = "2.3.0"
if _... | 0.359589 | 0.126434 |
import os
import unittest
from dart.client.python.dart_client import Dart
from dart.engine.no_op.metadata import NoOpActionTypes
from dart.model.action import ActionData, Action, ActionState
from dart.model.dataset import Column, DatasetData, Dataset, DataFormat, DataType, FileFormat, RowFormat, LoadType
from dart.mod... | src/python/dart/test/full/test_consume_subscription.py | import os
import unittest
from dart.client.python.dart_client import Dart
from dart.engine.no_op.metadata import NoOpActionTypes
from dart.model.action import ActionData, Action, ActionState
from dart.model.dataset import Column, DatasetData, Dataset, DataFormat, DataType, FileFormat, RowFormat, LoadType
from dart.mod... | 0.394901 | 0.335514 |
"""A function to build an object detection box coder from configuration."""
from tfold.object_detection.box_coders import faster_rcnn_box_coder
from tfold.object_detection.box_coders import keypoint_box_coder
from tfold.object_detection.box_coders import mean_stddev_box_coder
from tfold.object_detection.box_coders imp... | tfold/object_detection/builders/box_coder_builder.py |
"""A function to build an object detection box coder from configuration."""
from tfold.object_detection.box_coders import faster_rcnn_box_coder
from tfold.object_detection.box_coders import keypoint_box_coder
from tfold.object_detection.box_coders import mean_stddev_box_coder
from tfold.object_detection.box_coders imp... | 0.930844 | 0.303474 |
from discord.ext import commands
from config import REDDIT_APP_ID, REDDIT_APP_SECRET, REDDIT_ENABLED_MEME_SUBREDDITS, REDDIT_ADULT, REDDIT_ADULT_GIF, ADULT_NSFW_CHANNEL_ID
import random
import praw
import aiohttp
import discord
class adult(commands.Cog):
def __init__(self, bot):
self.bot = bot
... | BOT-ALTYAPI-PYTHON/Dbot/cogs/nsfw.py | from discord.ext import commands
from config import REDDIT_APP_ID, REDDIT_APP_SECRET, REDDIT_ENABLED_MEME_SUBREDDITS, REDDIT_ADULT, REDDIT_ADULT_GIF, ADULT_NSFW_CHANNEL_ID
import random
import praw
import aiohttp
import discord
class adult(commands.Cog):
def __init__(self, bot):
self.bot = bot
... | 0.121477 | 0.071494 |
import os
import sys
import json
import urllib.parse
import httplib2
import logging
import re
from colorama import Fore, Back, Style
from lib.search.result import SearchResult
from lib.doi import DOI
from lib.fulltexturl import FullTextURL
from lib.helper import Helper
from lib.filter import Filters
class Request(ob... | lib/search/request.py | import os
import sys
import json
import urllib.parse
import httplib2
import logging
import re
from colorama import Fore, Back, Style
from lib.search.result import SearchResult
from lib.doi import DOI
from lib.fulltexturl import FullTextURL
from lib.helper import Helper
from lib.filter import Filters
class Request(ob... | 0.346431 | 0.12817 |
import os
import pandas as pd
from settings import *
"""
Takes as input the dataframe with the raw data collected from the .xar files and transforms it:
- Keyframes to timestamps (keyframe number * 1/fps)
- Joint values to radians from degrees (all joints except LHand, RHand)
- Keyframes shifted forward by 20
- Init... | src/data/transform_raw.py | import os
import pandas as pd
from settings import *
"""
Takes as input the dataframe with the raw data collected from the .xar files and transforms it:
- Keyframes to timestamps (keyframe number * 1/fps)
- Joint values to radians from degrees (all joints except LHand, RHand)
- Keyframes shifted forward by 20
- Init... | 0.586641 | 0.299284 |
import urllib.request
import ssl
import json
from settings import Settings
from urllib.parse import urlparse
class Openapis:
api_listing = []
api_short_words = ["mine", "marble", "mellow", "futuristic", "zippy", "cap", "fragile", "torpid", "debt","exuberant",
"lovely", "subsequent", "a... | openapis.py | import urllib.request
import ssl
import json
from settings import Settings
from urllib.parse import urlparse
class Openapis:
api_listing = []
api_short_words = ["mine", "marble", "mellow", "futuristic", "zippy", "cap", "fragile", "torpid", "debt","exuberant",
"lovely", "subsequent", "a... | 0.202286 | 0.182389 |
class Node(object):
'''A sentinel node or data node of a circular doubly-linked list (CDLL).'''
def __init__(self, sentinel=None, key=None, value=None):
'''Constructs a node and places it in a new or existing CDLL.'''
if sentinel is None: # This is a new CDLL's sentinel node.
assert ... | main/lru-cache-lc/lru-cache-lc.py | class Node(object):
'''A sentinel node or data node of a circular doubly-linked list (CDLL).'''
def __init__(self, sentinel=None, key=None, value=None):
'''Constructs a node and places it in a new or existing CDLL.'''
if sentinel is None: # This is a new CDLL's sentinel node.
assert ... | 0.724481 | 0.356447 |
from .network import Network
import tensorflow as tf
class VisualContext(Network):
"""Visual context feature fusion."""
def _interpolate(self, xy1, xy2, points2):
batch_size = tf.shape(xy1)[0]
ndataset1 = tf.shape(xy1)[1]
eps = 1e-6
dist_mat = tf.matmul(xy1, xy2, transpose_b... | pyslam/thirdparty/contextdesc/models/cnn_wrapper/augdesc.py | from .network import Network
import tensorflow as tf
class VisualContext(Network):
"""Visual context feature fusion."""
def _interpolate(self, xy1, xy2, points2):
batch_size = tf.shape(xy1)[0]
ndataset1 = tf.shape(xy1)[1]
eps = 1e-6
dist_mat = tf.matmul(xy1, xy2, transpose_b... | 0.829871 | 0.376165 |
from parameterized import parameterized
import unittest
from lib import coordinate_calculator as cc
class TransformTest(unittest.TestCase):
def test_transform(self):
origin_val = (1999, 30)
origin_pos = (40, 200)
scale = (10, 3)
data_list = [(1999.1, 33), (2000.4, 44), (2001.8, 56), (2002.8, 79),
... | server/tests/coordinate_calculator_test.py |
from parameterized import parameterized
import unittest
from lib import coordinate_calculator as cc
class TransformTest(unittest.TestCase):
def test_transform(self):
origin_val = (1999, 30)
origin_pos = (40, 200)
scale = (10, 3)
data_list = [(1999.1, 33), (2000.4, 44), (2001.8, 56), (2002.8, 79),
... | 0.658527 | 0.608391 |
import sys
import re
from optparse import OptionParser
import subprocess
import os
import time
#modify /Lustre02/data/hic/highres_human/allsamples/'''+mytissue+'''_forsort/allcisandtrans.hic for your specific case
#modify alltissues=['A1','A2','A3','A4'] for your specific case
class generate:
def __init__ (self,pa... | code/06.prepare_forfinalplot.py |
import sys
import re
from optparse import OptionParser
import subprocess
import os
import time
#modify /Lustre02/data/hic/highres_human/allsamples/'''+mytissue+'''_forsort/allcisandtrans.hic for your specific case
#modify alltissues=['A1','A2','A3','A4'] for your specific case
class generate:
def __init__ (self,pa... | 0.05572 | 0.161122 |
import openmdao.api as om
import numpy as np
class TireODE(om.ExplicitComponent):
def initialize(self):
self.options.declare('num_nodes', types=int)
def setup(self):
nn = self.options['num_nodes']
#constants
self.add_input('M', val=0.0, desc='mass', units='kg')
self.a... | dymos/examples/racecar/tireODE.py | import openmdao.api as om
import numpy as np
class TireODE(om.ExplicitComponent):
def initialize(self):
self.options.declare('num_nodes', types=int)
def setup(self):
nn = self.options['num_nodes']
#constants
self.add_input('M', val=0.0, desc='mass', units='kg')
self.a... | 0.409575 | 0.164382 |
from flask import Flask, render_template
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from io import BytesIO
import base64
from bs4 import BeautifulSoup
import requests
#don't change this
matplotlib.use('Agg')
app = Flask(__name__) #do not change this
#insert the scrapping here
url_get = req... | app.py | from flask import Flask, render_template
import pandas as pd
import matplotlib
import matplotlib.pyplot as plt
from io import BytesIO
import base64
from bs4 import BeautifulSoup
import requests
#don't change this
matplotlib.use('Agg')
app = Flask(__name__) #do not change this
#insert the scrapping here
url_get = req... | 0.264074 | 0.116362 |
r"""
Analytic Acquisition Functions that evaluate the posterior without performing
Monte-Carlo sampling.
"""
from __future__ import annotations
from abc import ABC
from copy import deepcopy
from typing import Dict, Optional, Tuple, Union
import torch
from botorch.acquisition.acquisition import AcquisitionFunction
f... | botorch/acquisition/analytic.py |
r"""
Analytic Acquisition Functions that evaluate the posterior without performing
Monte-Carlo sampling.
"""
from __future__ import annotations
from abc import ABC
from copy import deepcopy
from typing import Dict, Optional, Tuple, Union
import torch
from botorch.acquisition.acquisition import AcquisitionFunction
f... | 0.9842 | 0.702098 |
from ..debian import DebianReleaseSpec
from ..debian import get_spec_from_release_file
from ..debian import parse_dpkgquery_line
from niceman.tests.utils import eq_, assert_is_subset_recur
def test_get_spec_from_release_file(f=None):
content = """\
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
Origin: NeuroDe... | niceman/support/distributions/tests/test_debian.py | from ..debian import DebianReleaseSpec
from ..debian import get_spec_from_release_file
from ..debian import parse_dpkgquery_line
from niceman.tests.utils import eq_, assert_is_subset_recur
def test_get_spec_from_release_file(f=None):
content = """\
-----BEGIN PGP SIGNED MESSAGE-----
Hash: SHA256
Origin: NeuroDe... | 0.368065 | 0.150653 |
import os
import re
from mmpython import mediainfo
import mmpython
from discinfo import DiscInfo
LSDVD_EXE='lsdvd'
class DVDAudio(mediainfo.AudioInfo):
def __init__(self, data):
mediainfo.AudioInfo.__init__(self)
self.number = int(data[1])
if data[3] != 'xx':
self.language ... | app/FileViewer/FileServer/misc/mmpython/disc/lsdvd.py |
import os
import re
from mmpython import mediainfo
import mmpython
from discinfo import DiscInfo
LSDVD_EXE='lsdvd'
class DVDAudio(mediainfo.AudioInfo):
def __init__(self, data):
mediainfo.AudioInfo.__init__(self)
self.number = int(data[1])
if data[3] != 'xx':
self.language ... | 0.26341 | 0.157266 |
import sys
print(sys.version)
from mpi4py import MPI
comm = MPI.COMM_WORLD
num_procs = comm.Get_size()
rank = comm.Get_rank()
run_test=False
rank_i = rank//3
rank_j = rank%3
import gc
import pandas as pd
import numpy as np
import os
from sklearn.model_selection import GridSearchCV, cross_val_score, cross_validate,... | analysis/2-cluster-ml-scripts/cv_bert_drivers.py | import sys
print(sys.version)
from mpi4py import MPI
comm = MPI.COMM_WORLD
num_procs = comm.Get_size()
rank = comm.Get_rank()
run_test=False
rank_i = rank//3
rank_j = rank%3
import gc
import pandas as pd
import numpy as np
import os
from sklearn.model_selection import GridSearchCV, cross_val_score, cross_validate,... | 0.389547 | 0.252747 |
from pandac.PandaModules import *
from toontown.toonbase.ToonBaseGlobal import *
from direct.interval.IntervalGlobal import *
from toontown.toonbase.ToontownGlobals import *
from toontown.distributed.DelayDelete import DelayDelete
from direct.directnotify import DirectNotifyGlobal
from direct.fsm import StateData
from ... | toontown/minigame/CatchGameToonSD.py | from pandac.PandaModules import *
from toontown.toonbase.ToonBaseGlobal import *
from direct.interval.IntervalGlobal import *
from toontown.toonbase.ToontownGlobals import *
from toontown.distributed.DelayDelete import DelayDelete
from direct.directnotify import DirectNotifyGlobal
from direct.fsm import StateData
from ... | 0.439747 | 0.092155 |
__author__ = '<EMAIL> (<NAME>)'
import document
CUSTOM_SERIALIZE_METHOD_NAME = 'Serialize'
def IsListOrDict(inst):
"""Returns whether or not this is a list, tuple, set or dict ."""
return hasattr(inst, '__iter__')
def IsDict(inst):
"""Returns whether or not the specified instance is a dict."""
return ha... | app/waveapi/util.py | __author__ = '<EMAIL> (<NAME>)'
import document
CUSTOM_SERIALIZE_METHOD_NAME = 'Serialize'
def IsListOrDict(inst):
"""Returns whether or not this is a list, tuple, set or dict ."""
return hasattr(inst, '__iter__')
def IsDict(inst):
"""Returns whether or not the specified instance is a dict."""
return ha... | 0.865849 | 0.343975 |
import re
import os
from subprocess import check_call
from setuptools import setup, find_packages, Command
from setuptools.command.sdist import sdist
cmdclass = {}
try:
from pyqt_distutils.build_ui import build_ui
has_build_ui = True
except ImportError:
has_build_ui = False
try:
from sphinx.setu... | setup.py |
import re
import os
from subprocess import check_call
from setuptools import setup, find_packages, Command
from setuptools.command.sdist import sdist
cmdclass = {}
try:
from pyqt_distutils.build_ui import build_ui
has_build_ui = True
except ImportError:
has_build_ui = False
try:
from sphinx.setu... | 0.352648 | 0.076098 |
import logging
import traceback
import sublime
import sublime_plugin
from ..anaconda_lib.worker import Worker
from ..anaconda_lib._typing import Dict, Any
from ..anaconda_lib.progress_bar import ProgressBar
from ..anaconda_lib.helpers import get_settings, is_python, get_window_view
from ..anaconda_lib.jsonclient imp... | sublime/Packages/Anaconda/commands/autoformat.py |
import logging
import traceback
import sublime
import sublime_plugin
from ..anaconda_lib.worker import Worker
from ..anaconda_lib._typing import Dict, Any
from ..anaconda_lib.progress_bar import ProgressBar
from ..anaconda_lib.helpers import get_settings, is_python, get_window_view
from ..anaconda_lib.jsonclient imp... | 0.394318 | 0.069827 |
# Copyright (c) 2021 <NAME>
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# dis... | pytkanim/__init__.py |
# Copyright (c) 2021 <NAME>
# Permission is hereby granted, free of charge, to any person obtaining
# a copy of this software and associated documentation files (the
# "Software"), to deal in the Software without restriction, including
# without limitation the rights to use, copy, modify, merge, publish,
# dis... | 0.577257 | 0.093678 |
import lightgbm
import numpy as np
import pandas as pd
# functions to test are imported from train.py
from train import split_data, train_model, get_model_metrics
"""A set of simple unit tests for protecting against regressions in train.py"""
def test_split_data():
test_data = {
'id': [0, 1, 2, 3, 4],
... | openhackmlops/training/test_train.py | import lightgbm
import numpy as np
import pandas as pd
# functions to test are imported from train.py
from train import split_data, train_model, get_model_metrics
"""A set of simple unit tests for protecting against regressions in train.py"""
def test_split_data():
test_data = {
'id': [0, 1, 2, 3, 4],
... | 0.814422 | 0.751238 |
import pytest
from graphdatascience.graph.graph_object import Graph
from graphdatascience.graph_data_science import GraphDataScience
from graphdatascience.model.link_prediction_model import LPModel
from graphdatascience.model.model import Model
from graphdatascience.model.node_classification_model import NCModel
from... | graphdatascience/tests/unit/test_prediction_models.py | import pytest
from graphdatascience.graph.graph_object import Graph
from graphdatascience.graph_data_science import GraphDataScience
from graphdatascience.model.link_prediction_model import LPModel
from graphdatascience.model.model import Model
from graphdatascience.model.node_classification_model import NCModel
from... | 0.625552 | 0.515559 |
import multiprocessing
import sys
import time
import unittest
import percy
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
TIMEOUT = 20
class IntegrationTests(unittest.... | tests/IntegrationTests.py | import multiprocessing
import sys
import time
import unittest
import percy
from selenium import webdriver
from selenium.webdriver.common.by import By
from selenium.webdriver.support.ui import WebDriverWait
from selenium.webdriver.support import expected_conditions as EC
TIMEOUT = 20
class IntegrationTests(unittest.... | 0.276691 | 0.094887 |
import numpy as np
import unittest
from itertools import permutations
from colour.colorimetry import TVS_ILLUMINANTS_HUNTERLAB
from colour.models import (
XYZ_to_K_ab_HunterLab1966,
XYZ_to_Hunter_Lab,
Hunter_Lab_to_XYZ,
)
from colour.utilities import domain_range_scale, ignore_numpy_errors
__author__ = ... | colour/models/tests/test_hunter_lab.py |
import numpy as np
import unittest
from itertools import permutations
from colour.colorimetry import TVS_ILLUMINANTS_HUNTERLAB
from colour.models import (
XYZ_to_K_ab_HunterLab1966,
XYZ_to_Hunter_Lab,
Hunter_Lab_to_XYZ,
)
from colour.utilities import domain_range_scale, ignore_numpy_errors
__author__ = ... | 0.730866 | 0.411288 |
import os
import sys
import time
import getopt
import signal
import logging
import subprocess
import configparser
try:
import gi
except:
print("no modules named 'gi', please install python-gobject")
sys.exit()
try:
import cairo
except:
print("no modules named 'cairo', please install python-cairo... | src/clearine.py | import os
import sys
import time
import getopt
import signal
import logging
import subprocess
import configparser
try:
import gi
except:
print("no modules named 'gi', please install python-gobject")
sys.exit()
try:
import cairo
except:
print("no modules named 'cairo', please install python-cairo... | 0.150996 | 0.071429 |
import argparse
import os
import sys
import errno
import precision_recall_per_genome
import precision_recall_average
import precision_recall_by_bpcount
import rand_index
import genome_recovery
import plot_by_genome
import matplotlib.pyplot as plt
from utils import exclude_genomes
from utils import load_data
from utils... | evaluate.py |
import argparse
import os
import sys
import errno
import precision_recall_per_genome
import precision_recall_average
import precision_recall_by_bpcount
import rand_index
import genome_recovery
import plot_by_genome
import matplotlib.pyplot as plt
from utils import exclude_genomes
from utils import load_data
from utils... | 0.385259 | 0.128991 |
import json
import sys
import matplotlib
matplotlib.use('Agg')
import mpl_toolkits.mplot3d.axes3d as p3
import pylab as p
import numpy as np
from matplotlib import cm
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
import requests
import cgi
import cgitb
impor... | cgi-bin/graph-endowment.py | import json
import sys
import matplotlib
matplotlib.use('Agg')
import mpl_toolkits.mplot3d.axes3d as p3
import pylab as p
import numpy as np
from matplotlib import cm
import matplotlib.pyplot as plt
from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
import requests
import cgi
import cgitb
impor... | 0.263126 | 0.251475 |
import unittest
from unittest import TestCase
from math import isnan
from pymatgen.core.periodic_table import Specie
from matminer.utils.data import DemlData, MagpieData, PymatgenData, \
MixingEnthalpy, MatscholarElementData, MEGNetElementData, IUCrBondValenceData
from pymatgen import Element
class TestDemlData... | matminer/utils/tests/test_data.py | import unittest
from unittest import TestCase
from math import isnan
from pymatgen.core.periodic_table import Specie
from matminer.utils.data import DemlData, MagpieData, PymatgenData, \
MixingEnthalpy, MatscholarElementData, MEGNetElementData, IUCrBondValenceData
from pymatgen import Element
class TestDemlData... | 0.74055 | 0.678653 |
import os
import csv
from sklearn.datasets import fetch_mldata
from sklearn.cross_validation import train_test_split
from sklearn.naive_bayes import MultinomialNB
from DenoisingAutoencoder import DenoisingAutoencoder
from StackedDenoisingAutoencoders import StackedDenoisingAutoencoders
custom_data_home = os.path.joi... | run_mnist_stacked_ae.py | import os
import csv
from sklearn.datasets import fetch_mldata
from sklearn.cross_validation import train_test_split
from sklearn.naive_bayes import MultinomialNB
from DenoisingAutoencoder import DenoisingAutoencoder
from StackedDenoisingAutoencoders import StackedDenoisingAutoencoders
custom_data_home = os.path.joi... | 0.458349 | 0.385375 |
import mock
"""
result module - Unit tests for Result class
"""
import unittest
from cloudant.error import ResultException
from cloudant.result import Result, ResultByKey
from cloudant.view import View
from nose.plugins.attrib import attr
from requests.exceptions import HTTPError
from .unit_t_db_base import UnitTestD... | tests/unit/result_tests.py | import mock
"""
result module - Unit tests for Result class
"""
import unittest
from cloudant.error import ResultException
from cloudant.result import Result, ResultByKey
from cloudant.view import View
from nose.plugins.attrib import attr
from requests.exceptions import HTTPError
from .unit_t_db_base import UnitTestD... | 0.832169 | 0.545104 |
import os
import sys
import json
from PyQt5 import QtCore, QtWidgets
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
class WindowClassificationTrainUpdateTransformParam(QtWidgets.QWidget):
forward_model_param = QtCore.pyqtSignal();
backward_data_param = QtCore.pyqtSignal();
def __init__(self):... | classification/training/update/WindowClassificationTrainUpdateTransformParam.py | import os
import sys
import json
from PyQt5 import QtCore, QtWidgets
from PyQt5.QtWidgets import *
from PyQt5.QtGui import *
class WindowClassificationTrainUpdateTransformParam(QtWidgets.QWidget):
forward_model_param = QtCore.pyqtSignal();
backward_data_param = QtCore.pyqtSignal();
def __init__(self):... | 0.107965 | 0.095856 |
import asyncio
import discord
import inspect
import traceback
from typing import Any, Dict, List, Union
from inspect import getfullargspec
from discord.ext import commands
slash_cmd_option_types = {
str: 3,
int: 4,
bool: 5,
discord.Member: 6,
discord.TextChannel: 7,
discord.CategoryChannel: 7,
... | handler/app_commands.py | import asyncio
import discord
import inspect
import traceback
from typing import Any, Dict, List, Union
from inspect import getfullargspec
from discord.ext import commands
slash_cmd_option_types = {
str: 3,
int: 4,
bool: 5,
discord.Member: 6,
discord.TextChannel: 7,
discord.CategoryChannel: 7,
... | 0.417153 | 0.122025 |
import enum
from typing import Mapping, MutableSequence, Union
import enumtables
from sqlalchemy import Column, DateTime, ForeignKey, Integer, JSON, Table
from sqlalchemy.orm import backref, relationship
from aspen.database.models.base import base, idbase
from aspen.database.models.entity import _WORKFLOW_TABLENAME, ... | src/backend/aspen/database/models/workflow.py | import enum
from typing import Mapping, MutableSequence, Union
import enumtables
from sqlalchemy import Column, DateTime, ForeignKey, Integer, JSON, Table
from sqlalchemy.orm import backref, relationship
from aspen.database.models.base import base, idbase
from aspen.database.models.entity import _WORKFLOW_TABLENAME, ... | 0.794225 | 0.242996 |
import os
import numpy as np
from OpenGL.GL import *
import lib.easy_shaders as es
import lib.object_handler as oh
import lib.transformations as tr
class Floor():
def __init__(self):
self.GPU = es.toGPUShape(oh.readOBJ2(os.path.join('mod','tex','ground.obj'), os.path.join('mod','tex','ground.png')), GL_... | tarea2c/mod/floor.py | import os
import numpy as np
from OpenGL.GL import *
import lib.easy_shaders as es
import lib.object_handler as oh
import lib.transformations as tr
class Floor():
def __init__(self):
self.GPU = es.toGPUShape(oh.readOBJ2(os.path.join('mod','tex','ground.obj'), os.path.join('mod','tex','ground.png')), GL_... | 0.371137 | 0.430866 |
import os
import pyudev
import psutil
import logging
from arm.ui import db
from arm.config.config import cfg
from flask_login import LoginManager, current_user, login_user, UserMixin # noqa: F401
from prettytable import PrettyTable
hidden_attribs = ("OMDB_API_KEY", "EMBY_USERID", "EMBY_PASSWORD", "EMBY_API_KEY", "PB_... | arm/models/models.py | import os
import pyudev
import psutil
import logging
from arm.ui import db
from arm.config.config import cfg
from flask_login import LoginManager, current_user, login_user, UserMixin # noqa: F401
from prettytable import PrettyTable
hidden_attribs = ("OMDB_API_KEY", "EMBY_USERID", "EMBY_PASSWORD", "EMBY_API_KEY", "PB_... | 0.399226 | 0.053453 |