text stringlengths 0 1.05M | meta dict |
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from __future__ import absolute_import, division, print_function
import logging
import sys
from mesos.interface import Executor
from .messages import decode, encode
class ExecutorProxy(Executor):
"""Base class for Mesos executors.
Users' executors should extend this class to get default implementations of... | {
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... |
from __future__ import absolute_import, division, print_function
import logging
import sys
from mesos.interface import Scheduler
from .messages import Filters, decode, encode
class SchedulerProxy(Scheduler):
def __init__(self, scheduler):
self.scheduler = scheduler
def registered(self, driver, fr... | {
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from __future__ import absolute_import, division, print_function
import logging
from functools import wraps
import numpy as np
from matplotlib.backends.backend_agg import FigureCanvasAgg
from .misc import DeferredMethod
__all__ = ['all_artists', 'new_artists', 'remove_artists', 'get_extent',
'view_casca... | {
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from __future__ import absolute_import, division, print_function
import logging
from mentos.connection import Connection
from mentos.exceptions import (BadRequest, BadSubscription,
ConnectionLost, ConnectionRefusedError,
DetectorClosed, FailedRetry, Master... | {
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"path": "mentos/subscription.py",
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from __future__ import absolute_import, division, print_function
import logging
from pymongo import MongoClient
from pymongo.errors import BulkWriteError
from bson.objectid import ObjectId
from concurrent.futures import ThreadPoolExecutor
from tornado.concurrent import run_on_executor
logger = logging.getLogger('mo... | {
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"path": "file_catalog/mongo.py",
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from __future__ import absolute_import, division, print_function
import logging
import cloudpickle
from mesos.interface import mesos_pb2
from .proxies.messages import (CommandInfo, ContainerInfo, Cpus, Disk,
DockerInfo, Environment, ExecutorInfo, Mem,
Tas... | {
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"path": "mentor/messages.py",
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"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import logging
import numpy as np
import os
import time
import joblib
from joblib import Parallel, delayed
from TotalActivation.filters import hrf
from TotalActivation.process.temporal import wiener
from TotalActivation.process.spatial import tikhonov... | {
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"con... |
from __future__ import absolute_import, division, print_function
import logging
import numpy as np
import scipy.io as sio
import time
import joblib
from joblib import Parallel, delayed
from TotalActivation.filters import hrf
from TotalActivation.process.temporal import wiener
from TotalActivation.process.spatial im... | {
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"config_te... |
from __future__ import absolute_import, division, print_function
import logging
import numpy as np
__all__ = ['Coordinates', 'WCSCoordinates']
class Coordinates(object):
'''
Base class for coordinate transformation
'''
def __init__(self):
pass
def pixel2world(self, *args):
re... | {
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"path": "glue/core/coordinates.py",
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from __future__ import absolute_import, division, print_function
import logging
import numpy as np
from glue.utils import unbroadcast, broadcast_to
__all__ = ['Coordinates', 'WCSCoordinates', 'coordinates_from_header', 'coordinates_from_wcs']
class Coordinates(object):
'''
Base class for coordinate tran... | {
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"config_... |
from __future__ import absolute_import, division, print_function
import logging
import numpy as np
__all__ = ['Coordinates', 'WCSCoordinates']
class Coordinates(object):
'''
Base class for coordinate transformation
'''
def __init__(self):
pass
def pixel2world(self, *args):
r... | {
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from __future__ import absolute_import, division, print_function
import logging
import numpy as np
try:
from plotly import plotly
except ImportError:
plotly = None
from glue.core.layout import Rectangle, snap_to_grid
SYM = {'o': 'circle', 's': 'square', '+': 'cross', '^': 'triangle-up',
'*': 'cross'... | {
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from __future__ import absolute_import, division, print_function
import logging
import pytest
logger = logging.getLogger('pytest_catchlog.test.perf')
@pytest.fixture(autouse=True)
def bench_runtest(request, benchmark):
# Using benchmark.weave to patch a runtest hook doesn't seem to work with
# pytest 2.8.... | {
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"path": "tests/perf/bench/test_runtest_hook.py",
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... |
from __future__ import absolute_import, division, print_function
import logging
import workflows
class CommonTransport(object):
'''A common transport class, containing e.g. the logic to manage
subscriptions and transactions.'''
__callback_interceptor = None
__subscriptions = {}
__subscription_id = 0
... | {
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"path": "workflows/transport/common_transport.py",
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"... |
from __future__ import absolute_import, division, print_function
import logging
logger = logging.getLogger(__name__)
def _get_package(package, version_query, media_type, package_class):
"""
Fetch the package data from the datastore
and instantiate a :obj:`appr.models.package_base.PackageModelBase`
... | {
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"path": "appr/api/impl/registry.py",
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"autogenerated": false,
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"config_tes... |
from __future__ import absolute_import, division, print_function
import logging
logging.basicConfig()
logger = logging.getLogger(__name__)
logger.setLevel(logging.WARNING)
# build the blaze namespace with selected functions
from . import catalog
from . import compute, io
from .objects.array import Array
from .object... | {
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"config_test": tr... |
from __future__ import absolute_import, division, print_function
import logging
logging.basicConfig()
logger = logging.getLogger(__name__)
logger.setLevel(logging.WARNING)
inf = float('inf')
nan = float('nan')
__version__ = '0.6.0-dev'
# If IPython is already loaded, register the Blaze catalog magic
# from . impo... | {
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"path": "blaze/__init__.py",
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"h... |
from __future__ import absolute_import, division, print_function
import math
from operator import getitem
import uuid
import numpy as np
import pandas as pd
from pandas.core.categorical import is_categorical_dtype
from toolz import merge
from .core import DataFrame, Series, _Frame, _concat
from ..base import tokeni... | {
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"ratio": 3.81... |
from __future__ import absolute_import, division, print_function
import math
from operator import getitem
import uuid
import numpy as np
import pandas as pd
from toolz import merge
from .methods import drop_columns
from .core import DataFrame, Series, _Frame, _concat, map_partitions
from .hashing import hash_pandas_... | {
"repo_name": "mraspaud/dask",
"path": "dask/dataframe/shuffle.py",
"copies": "1",
"size": "17192",
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"hash": -597147565638344100,
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"line_max": 83,
"alpha_frac": 0.590739879,
"autogenerated": false,
"ratio": 3.7439024390243905,
"config_test": ... |
from __future__ import (absolute_import, division, print_function)
import math
from sympy import Interval
from sympy.calculus.singularities import is_increasing, is_decreasing
from sympy.codegen.rewriting import Optimization
from sympy.core.function import UndefinedFunction
"""
This module collects classes useful for... | {
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from __future__ import absolute_import, division, print_function
import math
import cmath
import unittest
import numpy as np
from numpy import testing
from numpy.testing import assert_
import blaze
import datashape
from blaze.datadescriptor import dd_as_py
from blaze.py2help import skip
def assert_almost_equal(act... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/tests/test_numpy_ufunc_compat.py",
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"line_max": 80,
"alpha_frac": 0.5510593765,
"autogenerated": false,
"ratio": 2.714883860033895,
"co... |
from __future__ import absolute_import, division, print_function
import math
import itertools
import operator
import pytest
from datetime import datetime, date
import datashape
from collections import Iterator, Iterable
import blaze
from blaze.compute.python import (nunique, mean, rrowfunc, rowfunc,
... | {
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"path": "blaze/compute/tests/test_python_compute.py",
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"autogenerated": false,
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... |
from __future__ import absolute_import, division, print_function
import math
import os
import sys
import numpy as np
from numba import unittest_support as unittest
from numba import njit
from numba.compiler import compile_isolated, Flags, types
from numba.runtime import rtsys
from .support import MemoryLeakMixin, Te... | {
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"path": "numba/tests/test_nrt.py",
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"autogenerated": false,
"ratio": 3.740740740740741,
"config_tes... |
from __future__ import absolute_import, division, print_function
import math
import re
from operator import getitem
from .compatibility import unicode
from .context import _globals
from .core import add, inc # noqa: F401
from .core import (istask, get_dependencies, subs, toposort, flatten,
revers... | {
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"path": "dask/optimize.py",
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"line_max": 120,
"alpha_frac": 0.5134077253,
"autogenerated": false,
"ratio": 3.9555887545837294,
"config_test": true,
... |
from __future__ import absolute_import, division, print_function
import math
import pygal
from pygal.style import DefaultStyle
try:
import pygaljs
except ImportError:
opts = {}
else:
opts = {"js": [pygaljs.uri("2.0.x", "pygal-tooltips.js")]}
opts["css"] = [
"file://style.css",
"file://graph.css"... | {
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"path": "tests/perf/plot.py",
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"config_test": fa... |
from __future__ import absolute_import, division, print_function
import matplotlib
matplotlib.use("Agg")
import os
import pylab
import numpy as np
from keras import backend as K
from keras.callbacks import Callback, EarlyStopping, ModelCheckpoint
from keras.layers import Dense, Dropout, Input, GlobalAveragePooling2D
... | {
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... |
from __future__ import absolute_import, division, print_function
import matplotlib.pyplot as plt
from ..core.client import Client
from ..core import Data
from .layer_artist import LayerArtistContainer
__all__ = ['VizClient', 'GenericMplClient']
class VizClient(Client):
"""
The VizClient class provides an i... | {
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from __future__ import absolute_import, division, print_function
import matplotlib.pyplot as plt
from glue.core import Data
from glue.core.message import SettingsChangeMessage
from glue.core.client import Client
from glue.core.layer_artist import LayerArtistContainer
from glue.utils.matplotlib import freeze_margins
... | {
"repo_name": "saimn/glue",
"path": "glue/viewers/common/viz_client.py",
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"line_max": 87,
"alpha_frac": 0.6069098299,
"autogenerated": false,
"ratio": 4.133068081343944,
"config_tes... |
from __future__ import absolute_import, division, print_function
import mimetypes
import uuid
from io import BytesIO
from twisted.internet.interfaces import IProtocol
from twisted.internet.defer import Deferred
from twisted.python.components import proxyForInterface
from twisted.python.compat import _PY3, unicode
fr... | {
"repo_name": "pexip/os-python-treq",
"path": "src/treq/client.py",
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... |
from __future__ import absolute_import, division, print_function
import mock
import pytest
import workflows.contrib.start_service
def test_get_command_line_help(capsys):
'''Running the start_service script with --help should display command line help and exit.'''
with pytest.raises(SystemExit):
workflows.cont... | {
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"conf... |
from __future__ import absolute_import, division, print_function
import mock
import pytest
import workflows
import workflows.recipe
def check_message_handling_via_unwrapper(callback, recipient, transport, rw_mock, allow_non_recipe):
'''Test callback function of a recipe wrapper.'''
# This message does not contai... | {
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from __future__ import absolute_import, division, print_function
import mock
import workflows.contrib.status_monitor as status_monitor
@mock.patch('workflows.contrib.status_monitor.curses')
@mock.patch('workflows.contrib.status_monitor.time')
@mock.patch('workflows.contrib.status_monitor.workflows.transport')
def tes... | {
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from __future__ import absolute_import, division, print_function
import mock
import workflows.frontend.utilization
from workflows.services.common_service import Status
def about(value, tolerance):
'''Create an object that can be compared against a number and allows a tolerance.'''
class Comparator():
'''A hel... | {
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... |
from __future__ import absolute_import, division, print_function
import mock
import workflows.services
import workflows.services.sample_producer
def test_service_can_be_looked_up():
'''Attempt to look up the service by its name'''
service_class = workflows.services.lookup('SampleProducer')
assert service_class ... | {
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"line_mean": 32.5384615385,
"line_max": 76,
"alpha_frac": 0.7377675841,
"autogenerated": false,
"ratio": 3.58356164... |
from __future__ import absolute_import, division, print_function
import mock
import workflows.services
import workflows.services.sample_transaction
def test_services_can_be_looked_up():
'''Attempt to look up the services by their names'''
service_class = workflows.services.lookup('SampleTxn')
assert service_cla... | {
"repo_name": "xia2/workflows",
"path": "workflows/services/test_sample_service_transaction.py",
"copies": "1",
"size": "4644",
"license": "bsd-3-clause",
"hash": 4286979759727570000,
"line_mean": 41.6055045872,
"line_max": 123,
"alpha_frac": 0.7652885444,
"autogenerated": false,
"ratio": 3.53424... |
from __future__ import absolute_import, division, print_function
import multiprocessing as mp
import numpy as np
from numba import cuda
def parent():
arr = np.arange(10)
darr = cuda.to_device(arr)
ipch = darr.get_ipc_handle()
# launch child proc
mpc = mp.get_context('spawn')
queue = mpc.Qu... | {
"repo_name": "cpcloud/numba",
"path": "examples/cuda_ipc.py",
"copies": "2",
"size": "1225",
"license": "bsd-2-clause",
"hash": -5069240495452699000,
"line_mean": 19.4166666667,
"line_max": 64,
"alpha_frac": 0.5991836735,
"autogenerated": false,
"ratio": 3.2666666666666666,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import multiprocessing
import pickle
import sys
from .async import get_async # TODO: get better get
from .context import _globals
from .optimize import fuse, cull
import cloudpickle
from toolz import curry
if sys.version_info.major < 3:
import c... | {
"repo_name": "cowlicks/dask",
"path": "dask/multiprocessing.py",
"copies": "2",
"size": "3838",
"license": "bsd-3-clause",
"hash": 2128479518367291600,
"line_mean": 30.2032520325,
"line_max": 78,
"alpha_frac": 0.6354872329,
"autogenerated": false,
"ratio": 3.8303393213572856,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import multiprocessing
import traceback
import pickle
import sys
from .local import get_async # TODO: get better get
from .context import _globals
from .optimize import fuse, cull
import cloudpickle
if sys.version_info.major < 3:
import copy_reg... | {
"repo_name": "mraspaud/dask",
"path": "dask/multiprocessing.py",
"copies": "2",
"size": "5571",
"license": "bsd-3-clause",
"hash": -1960134324882675700,
"line_mean": 28.015625,
"line_max": 77,
"alpha_frac": 0.6259199426,
"autogenerated": false,
"ratio": 4.105379513633014,
"config_test": false,... |
from __future__ import absolute_import, division, print_function
import multiprocessing
import mock
import pytest
import workflows.frontend
from workflows.services.common_service import CommonService
### Helper classes used in tests ##############################################
class ServiceCrashingOnInit(CommonSe... | {
"repo_name": "xia2/workflows",
"path": "workflows/frontend/test_frontend.py",
"copies": "1",
"size": "18872",
"license": "bsd-3-clause",
"hash": 2740475426110459000,
"line_mean": 42.7865429234,
"line_max": 128,
"alpha_frac": 0.725148368,
"autogenerated": false,
"ratio": 3.8017727639000807,
"co... |
from __future__ import absolute_import, division, print_function
import mxnet as mx
import mxnet.ndarray as nd
import numpy
import copy
from utils import *
class ReplayMemory(object):
def __init__(self, history_length, memory_size=1000000, replay_start_size=100,
state_dim=(), action_dim=(), stat... | {
"repo_name": "danithaca/mxnet",
"path": "example/reinforcement-learning/dqn/replay_memory.py",
"copies": "16",
"size": "11299",
"license": "apache-2.0",
"hash": 7942620694802313000,
"line_mean": 52.5497630332,
"line_max": 105,
"alpha_frac": 0.6053633065,
"autogenerated": false,
"ratio": 3.860266... |
from __future__ import absolute_import, division, print_function
import mxnet as mx
import mxnet.ndarray as nd
import numpy
import os
import pickle
from collections import OrderedDict
import logging
from utils import *
logger = logging.getLogger(__name__)
class Base(object):
"""Basic wrapper for the symbols
... | {
"repo_name": "coder-james/mxnet",
"path": "example/reinforcement-learning/dqn/base.py",
"copies": "15",
"size": "12988",
"license": "apache-2.0",
"hash": -8084616376120728000,
"line_mean": 42.1495016611,
"line_max": 116,
"alpha_frac": 0.5407299045,
"autogenerated": false,
"ratio": 3.755928282244... |
from __future__ import absolute_import, division, print_function
import networkx as nx
from dask.core import istask, get_dependencies
from toolz import first
def make_hashable(x):
try:
hash(x)
return x
except TypeError:
return hash(str(x))
def lower(func):
while hasattr(func, 'f... | {
"repo_name": "PeterDSteinberg/dask",
"path": "dask/dot.py",
"copies": "1",
"size": "2295",
"license": "bsd-3-clause",
"hash": -7085710115613450000,
"line_mean": 26,
"line_max": 83,
"alpha_frac": 0.522875817,
"autogenerated": false,
"ratio": 3.375,
"config_test": false,
"has_no_keywords": fal... |
from __future__ import absolute_import, division, print_function
import networkx as nx
from dask.core import istask, get_dependencies
def make_hashable(x):
try:
hash(x)
return x
except TypeError:
return hash(str(x))
def lower(func):
while hasattr(func, 'func'):
func = fu... | {
"repo_name": "marianotepper/dask",
"path": "dask/dot.py",
"copies": "2",
"size": "2569",
"license": "bsd-3-clause",
"hash": -8990308331645823000,
"line_mean": 26.9239130435,
"line_max": 87,
"alpha_frac": 0.514986376,
"autogenerated": false,
"ratio": 3.4483221476510066,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import networkx as nx
from datashape import discover
from .utils import expand_tuples, cls_name
from contextlib import contextmanager
ooc_types = set() # Out-of-Core types
class NetworkDispatcher(object):
def __init__(self, name):
self.n... | {
"repo_name": "mrocklin/into",
"path": "into/core.py",
"copies": "1",
"size": "3263",
"license": "bsd-3-clause",
"hash": -637591899890687000,
"line_mean": 30.0761904762,
"line_max": 89,
"alpha_frac": 0.5908673,
"autogenerated": false,
"ratio": 3.7548906789413117,
"config_test": false,
"has_no... |
from __future__ import absolute_import, division, print_function
import networkx as nx
from datashape import discover
from .utils import expand_tuples, ignoring
from contextlib import contextmanager
ooc_types = set() # Out-of-Core types
class NetworkDispatcher(object):
def __init__(self, name):
self.n... | {
"repo_name": "alexmojaki/odo",
"path": "odo/core.py",
"copies": "3",
"size": "3228",
"license": "bsd-3-clause",
"hash": 6346366850859720000,
"line_mean": 30.3398058252,
"line_max": 79,
"alpha_frac": 0.5861214374,
"autogenerated": false,
"ratio": 3.7798594847775178,
"config_test": false,
"has... |
from __future__ import absolute_import, division, print_function
import numbers
from datetime import date, datetime
import toolz
from toolz import first, concat, memoize, unique, assoc
import itertools
from collections import Iterator
from ..compatibility import basestring
from ..expr import Expr, Field, Symbol, symb... | {
"repo_name": "scls19fr/blaze",
"path": "blaze/compute/core.py",
"copies": "6",
"size": "14107",
"license": "bsd-3-clause",
"hash": 1879904644053326300,
"line_mean": 28.3284823285,
"line_max": 82,
"alpha_frac": 0.5891401432,
"autogenerated": false,
"ratio": 3.6968029350104823,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import numbers
from datetime import date, datetime
import toolz
from toolz import first, unique, assoc
import itertools
from collections import Iterator
import pandas as pd
from odo import odo
from ..compatibility import basestring
from ..expr import Ex... | {
"repo_name": "cpcloud/blaze",
"path": "blaze/compute/core.py",
"copies": "2",
"size": "12473",
"license": "bsd-3-clause",
"hash": 3165300232817224700,
"line_mean": 28.279342723,
"line_max": 79,
"alpha_frac": 0.583580534,
"autogenerated": false,
"ratio": 3.614314691393799,
"config_test": false,... |
from __future__ import absolute_import, division, print_function
import numbers
import cPickle
import numpy as np
import theano
import theano.tensor as tt
from theano.ifelse import ifelse
from theano.sandbox.rng_mrg import MRG_RandomStreams as RandomStreams
floatX = theano.config.floatX
def cast_floatX(n):
retu... | {
"repo_name": "julian121266/RecurrentHighwayNetworks",
"path": "theano_rhn.py",
"copies": "2",
"size": "10522",
"license": "mit",
"hash": 6387570429273125000,
"line_mean": 42.6597510373,
"line_max": 126,
"alpha_frac": 0.6510169169,
"autogenerated": false,
"ratio": 3.271766169154229,
"config_tes... |
from __future__ import absolute_import, division, print_function
import numbers
import inspect
from pprint import pformat
from functools import reduce, partial
import numpy as np
import toolz
from toolz import unique, concat, first
import pandas as pd
from ..compatibility import _strtypes
from ..dispatch import dis... | {
"repo_name": "cpcloud/blaze",
"path": "blaze/expr/core.py",
"copies": "2",
"size": "12350",
"license": "bsd-3-clause",
"hash": -7920633615569263000,
"line_mean": 24,
"line_max": 79,
"alpha_frac": 0.5337651822,
"autogenerated": false,
"ratio": 3.7572254335260116,
"config_test": false,
"has_no... |
from __future__ import absolute_import, division, print_function
import numbers
import logging
import operator
import numpy as np
from glue.external.six import add_metaclass
from glue.core.contracts import contract, ContractsMeta
from glue.core.subset import InequalitySubsetState
from glue.core.util import join_comp... | {
"repo_name": "saimn/glue",
"path": "glue/core/component_link.py",
"copies": "1",
"size": "12336",
"license": "bsd-3-clause",
"hash": 918570524636241200,
"line_mean": 32.9834710744,
"line_max": 79,
"alpha_frac": 0.6074902724,
"autogenerated": false,
"ratio": 4.052562417871222,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import numbers
import numpy as np
from functools import partial
from itertools import chain
import datashape
from datashape import (
DataShape,
Fixed,
Option,
Record,
Unit,
Var,
dshape,
object_,
promote,
var,
)
fr... | {
"repo_name": "ContinuumIO/blaze",
"path": "blaze/expr/collections.py",
"copies": "3",
"size": "26662",
"license": "bsd-3-clause",
"hash": -4585575986744477000,
"line_mean": 26.8599791014,
"line_max": 104,
"alpha_frac": 0.5506713675,
"autogenerated": false,
"ratio": 3.7509848058525606,
"config_... |
from __future__ import absolute_import, division, print_function
import numbers
import operator
import numpy as np
from glue.external.six import PY3
from glue.core.roi import CategoricalROI
from glue.core.contracts import contract
from glue.core.util import split_component_view
from glue.core.registry import Registr... | {
"repo_name": "saimn/glue",
"path": "glue/core/subset.py",
"copies": "1",
"size": "31839",
"license": "bsd-3-clause",
"hash": -3877208879731483600,
"line_mean": 30.8071928072,
"line_max": 102,
"alpha_frac": 0.585728195,
"autogenerated": false,
"ratio": 4.1408505657432695,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numbers
import os
import re
import subprocess
import sys
import decimal
import warnings
from functools import partial
from operator import attrgetter
from itertools import chain
from collections import Iterator
from datetime import datetime, date... | {
"repo_name": "quantopian/odo",
"path": "odo/backends/sql.py",
"copies": "1",
"size": "34206",
"license": "bsd-3-clause",
"hash": -5080356345547088000,
"line_mean": 32.1774975752,
"line_max": 113,
"alpha_frac": 0.6049231129,
"autogenerated": false,
"ratio": 3.8703326544467074,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import numbers
import toolz
import inspect
from toolz import unique, concat, compose, partial
import toolz
from pprint import pprint
from ..compatibility import StringIO, _strtypes, builtins
from ..dispatch import dispatch
__all__ = ['Node', 'path', '... | {
"repo_name": "dwillmer/blaze",
"path": "blaze/expr/core.py",
"copies": "2",
"size": "10347",
"license": "bsd-3-clause",
"hash": -1437191260974576000,
"line_mean": 23.4033018868,
"line_max": 79,
"alpha_frac": 0.5321349183,
"autogenerated": false,
"ratio": 3.6743607954545454,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import numpy as np
from collections import OrderedDict
import os
import re
from atom.api import Atom, Str, observe, List, Int, Bool, Typed
from skbeam.fluorescence import XrfElement as Element
from skbeam.core.fitting.xrf_model import K_LINE, L_LINE, M... | {
"repo_name": "NSLS-II/PyXRF",
"path": "pyxrf/model/roi_model.py",
"copies": "1",
"size": "13148",
"license": "bsd-3-clause",
"hash": -9179613348779383000,
"line_mean": 32.6265984655,
"line_max": 99,
"alpha_frac": 0.5715698205,
"autogenerated": false,
"ratio": 3.9119309729247247,
"config_test":... |
from __future__ import absolute_import, division, print_function
import numpy as np
from datashape import dshape, DataShape, Option, DateTime, string, TimeDelta
from datashape import Date, to_numpy_dtype, Tuple, String, Decimal
from datashape.predicates import isscalar, isnumeric, isrecord
def unit_to_dtype(ds):
... | {
"repo_name": "cpcloud/odo",
"path": "odo/numpy_dtype.py",
"copies": "1",
"size": "3524",
"license": "bsd-3-clause",
"hash": -3612319085764110300,
"line_mean": 24.9117647059,
"line_max": 78,
"alpha_frac": 0.5428490352,
"autogenerated": false,
"ratio": 3.4925668979187314,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from datashape import *
from datashape.predicates import isscalar, isnumeric
def unit_to_dtype(ds):
"""
>>> unit_to_dtype('int32')
dtype('int32')
>>> unit_to_dtype('float64')
dtype('float64')
>>> unit_to_dtype... | {
"repo_name": "mrocklin/into",
"path": "into/numpy_dtype.py",
"copies": "1",
"size": "2367",
"license": "bsd-3-clause",
"hash": 180450960615548160,
"line_mean": 26.523255814,
"line_max": 78,
"alpha_frac": 0.5449936629,
"autogenerated": false,
"ratio": 3.246913580246914,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from dynd import nd
import datashape
from . import IDataDescriptor, Capabilities
from ..optional_packages import tables_is_here
if tables_is_here:
import tables as tb
from .dynd_data_descriptor import DyNDDataDescriptor
# WARNIN... | {
"repo_name": "aaronmartin0303/blaze",
"path": "blaze/datadescriptor/hdf5_data_descriptor.py",
"copies": "8",
"size": "4450",
"license": "bsd-3-clause",
"hash": -1794576393004862000,
"line_mean": 36.3949579832,
"line_max": 75,
"alpha_frac": 0.6017977528,
"autogenerated": false,
"ratio": 3.6415711... |
from __future__ import absolute_import, division, print_function
import numpy as np
from dynd import nd
import datashape
from . import IDataDescriptor, Capabilities
import blz
from .dynd_data_descriptor import DyNDDataDescriptor
# WARNING! BLZ always return NumPy arrays when doing indexing
# operations. This is w... | {
"repo_name": "XinSong/blaze",
"path": "blaze/datadescriptor/blz_data_descriptor.py",
"copies": "7",
"size": "5451",
"license": "bsd-3-clause",
"hash": 4993300301379388000,
"line_mean": 33.06875,
"line_max": 77,
"alpha_frac": 0.5997064759,
"autogenerated": false,
"ratio": 4.295508274231678,
"co... |
from __future__ import absolute_import, division, print_function
import numpy as np
from functools import partial, wraps
from math import factorial
from toolz import compose
from .core import _concatenate2, Array, atop, sqrt, elemwise
from .slicing import insert_many
from .numpy_compat import divide
from ..core impor... | {
"repo_name": "ssanderson/dask",
"path": "dask/array/reductions.py",
"copies": "10",
"size": "11734",
"license": "bsd-3-clause",
"hash": -6525226603789796000,
"line_mean": 30.5430107527,
"line_max": 85,
"alpha_frac": 0.5996250213,
"autogenerated": false,
"ratio": 3.3240793201133143,
"config_tes... |
from __future__ import absolute_import, division, print_function
import numpy as np
from functools import partial, wraps
from toolz import compose, curry
import inspect
from .core import _concatenate2, Array, atop, sqrt, elemwise
from .slicing import insert_many
from ..core import flatten
from . import chunk
from ..u... | {
"repo_name": "marianotepper/dask",
"path": "dask/array/reductions.py",
"copies": "2",
"size": "10067",
"license": "bsd-3-clause",
"hash": -4484792602106028500,
"line_mean": 29.5987841945,
"line_max": 85,
"alpha_frac": 0.5968014304,
"autogenerated": false,
"ratio": 3.272756827048114,
"config_te... |
from __future__ import absolute_import, division, print_function
import numpy as np
from functools import partial, wraps
from toolz import compose, curry
from .core import _concatenate2, Array, atop, names, sqrt, elemwise
from .slicing import insert_many
from ..core import flatten
from . import chunk
from ..utils imp... | {
"repo_name": "esc/dask",
"path": "dask/array/reductions.py",
"copies": "2",
"size": "9176",
"license": "bsd-3-clause",
"hash": 5805616984707362000,
"line_mean": 29.5866666667,
"line_max": 85,
"alpha_frac": 0.5953574542,
"autogenerated": false,
"ratio": 3.230985915492958,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from functools import partial, wraps
from toolz import compose, curry
from .core import (_concatenate2, insert_many, Array, atop, names, sqrt,
elemwise)
from ..core import flatten
from ..utils import ignoring
def reduction(x... | {
"repo_name": "PeterDSteinberg/dask",
"path": "dask/array/reductions.py",
"copies": "1",
"size": "7266",
"license": "bsd-3-clause",
"hash": -9189050662074939000,
"line_mean": 28.2983870968,
"line_max": 93,
"alpha_frac": 0.6169832095,
"autogenerated": false,
"ratio": 3.036356038445466,
"config_t... |
from __future__ import (absolute_import, division, print_function)
import numpy as np
from .harmonics import ut_E
from .utilities import Bunch
from ._time_conversion import _normalize_time
def reconstruct(t, coef, epoch='python', verbose=True, **opts):
"""
Reconstruct a tidal signal.
Parameters
----... | {
"repo_name": "efiring/UTide",
"path": "utide/_reconstruct.py",
"copies": "1",
"size": "5372",
"license": "mit",
"hash": -7137091002480009000,
"line_mean": 29.6971428571,
"line_max": 79,
"alpha_frac": 0.5147058824,
"autogenerated": false,
"ratio": 3.203339296362552,
"config_test": false,
"has... |
from __future__ import absolute_import, division, print_function
import numpy as np
from itertools import chain
import h5py
from dynd import nd
import datashape
from datashape import var, dshape
from toolz.curried import pipe, concat, map, partial
from ..dispatch import dispatch
from .core import DataDescriptor
from ... | {
"repo_name": "vitan/blaze",
"path": "blaze/data/hdf5.py",
"copies": "1",
"size": "6096",
"license": "bsd-3-clause",
"hash": 3408942459743557600,
"line_mean": 31.0842105263,
"line_max": 78,
"alpha_frac": 0.5508530184,
"autogenerated": false,
"ratio": 3.6634615384615383,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from itertools import chain
import h5py
from dynd import nd
import datashape
from datashape import var
from ..dispatch import dispatch
from .core import DataDescriptor
from ..utils import partition_all, get
from ..compatibility import... | {
"repo_name": "aterrel/blaze",
"path": "blaze/data/hdf5.py",
"copies": "1",
"size": "4820",
"license": "bsd-3-clause",
"hash": -8023342799787459000,
"line_mean": 31.1333333333,
"line_max": 80,
"alpha_frac": 0.5510373444,
"autogenerated": false,
"ratio": 3.786331500392773,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from itertools import chain
import h5py
from dynd import nd
import datashape
from .core import DataDescriptor
from ..utils import partition_all
h5py_attributes = ['chunks', 'compression', 'compression_opts', 'dtype',
... | {
"repo_name": "sethkontny/blaze",
"path": "blaze/data/hdf5.py",
"copies": "1",
"size": "4332",
"license": "bsd-3-clause",
"hash": -6932624940386869000,
"line_mean": 31.5714285714,
"line_max": 85,
"alpha_frac": 0.5466297322,
"autogenerated": false,
"ratio": 3.8336283185840707,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import numpy as np
from itertools import product
from .core import normalize_chunks, Array, names
def doc_wraps(func):
""" Copy docstring from one function to another """
def _(func2):
func2.__doc__ = func.__doc__.replace('>>>', '>>').re... | {
"repo_name": "simudream/dask",
"path": "dask/array/random.py",
"copies": "5",
"size": "12030",
"license": "bsd-3-clause",
"hash": -3960516644082094000,
"line_mean": 36.7115987461,
"line_max": 79,
"alpha_frac": 0.6323358271,
"autogenerated": false,
"ratio": 3.5931899641577063,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import numpy as np
from itertools import product
from .core import normalize_chunks, Array
from ..base import tokenize
def doc_wraps(func):
""" Copy docstring from one function to another """
def _(func2):
func2.__doc__ = func.__doc__.re... | {
"repo_name": "PhE/dask",
"path": "dask/array/random.py",
"copies": "4",
"size": "12156",
"license": "bsd-3-clause",
"hash": 916484420527660000,
"line_mean": 37.1065830721,
"line_max": 82,
"alpha_frac": 0.6349128003,
"autogenerated": false,
"ratio": 3.5773984696880516,
"config_test": false,
"... |
from __future__ import absolute_import, division, print_function
import numpy as np
from matplotlib.colors import ColorConverter
from glue import config
from qtpy import QtCore, QtWidgets, QtGui
from glue.external.echo import add_callback
from glue.utils import nonpartial
from glue.utils.qt.widget_properties import W... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/utils/qt/colors.py",
"copies": "3",
"size": "5669",
"license": "bsd-3-clause",
"hash": -5737210371490865000,
"line_mean": 24.8858447489,
"line_max": 85,
"alpha_frac": 0.6128064914,
"autogenerated": false,
"ratio": 3.6621447028423773,
"config_t... |
from __future__ import absolute_import, division, print_function
import numpy as np
from matplotlib.transforms import blended_transform_factory
from glue.core.callback_property import CallbackProperty, add_callback
PICK_THRESH = 30 # pixel distance threshold for picking
class Grip(object):
def __init__(self... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/plugins/tools/spectrum_tool/qt/profile_viewer.py",
"copies": "4",
"size": "13923",
"license": "bsd-3-clause",
"hash": -7501474625993291000,
"line_mean": 27.2413793103,
"line_max": 76,
"alpha_frac": 0.5493069022,
"autogenerated": false,
"ratio": ... |
from __future__ import absolute_import, division, print_function
import numpy as np
from mock import MagicMock
from glue import core
from ..data_slice_widget import SliceWidget, DataSlice
class TestSliceWidget(object):
def test_slice_center(self):
s = SliceWidget(lo=0, hi=10)
assert s.slice_ce... | {
"repo_name": "saimn/glue",
"path": "glue/viewers/common/qt/tests/test_data_slice_widget.py",
"copies": "2",
"size": "3801",
"license": "bsd-3-clause",
"hash": -5031886545041272000,
"line_mean": 27.5789473684,
"line_max": 64,
"alpha_frac": 0.5356485135,
"autogenerated": false,
"ratio": 3.30521739... |
from __future__ import absolute_import, division, print_function
import numpy as np
from mock import MagicMock, patch
from ...config import settings
from .. import DataCollection, Data, SubsetGroup
from .. import subset
from ..subset import SubsetState
from ..subset_group import coerce_subset_groups
from .test_state ... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/core/tests/test_subset_group.py",
"copies": "2",
"size": "8031",
"license": "bsd-3-clause",
"hash": -4894715166341256000,
"line_mean": 30.1279069767,
"line_max": 83,
"alpha_frac": 0.5968123521,
"autogenerated": false,
"ratio": 3.3532359081419623... |
from __future__ import absolute_import, division, print_function
import numpy as np
from mock import MagicMock, patch
from .. import DataCollection, Data, SubsetGroup
from .. import subset
from ..subset import SubsetState
from ..subset_group import coerce_subset_groups
from .test_state import clone
class TestSubset... | {
"repo_name": "saimn/glue",
"path": "glue/core/tests/test_subset_group.py",
"copies": "2",
"size": "6829",
"license": "bsd-3-clause",
"hash": -6937184065590735000,
"line_mean": 29.6233183857,
"line_max": 74,
"alpha_frac": 0.5929125787,
"autogenerated": false,
"ratio": 3.33447265625,
"config_tes... |
from __future__ import absolute_import, division, print_function
import numpy as np
from numpy import (
sqrt,
minimum,
)
try:
_ = np.use_fastnumpy # Use Enthought MKL optimizations
from numpy.fft import rfft, irfft, rfftfreq
except AttributeError:
try:
import mklfft # MKL FFT optimization... | {
"repo_name": "achabotl/pambox",
"path": "pambox/central/ec.py",
"copies": "1",
"size": "17944",
"license": "bsd-3-clause",
"hash": 4466792650374887000,
"line_mean": 32.7928436911,
"line_max": 85,
"alpha_frac": 0.5207311636,
"autogenerated": false,
"ratio": 4.163341067285383,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import numpy as np
from numpy.lib import NumpyVersion
from .common import Benchmark
class Random(Benchmark):
params = ['normal', 'uniform', 'weibull 1', 'binomial 10 0.5',
'poisson 10']
def setup(self, name):
items = nam... | {
"repo_name": "DailyActie/Surrogate-Model",
"path": "01-codes/numpy-master/benchmarks/benchmarks/bench_random.py",
"copies": "1",
"size": "1645",
"license": "mit",
"hash": 6788555274493448000,
"line_mean": 24.3076923077,
"line_max": 66,
"alpha_frac": 0.5696048632,
"autogenerated": false,
"ratio":... |
from __future__ import absolute_import, division, print_function
import numpy as np
from numpy.lib.stride_tricks import as_strided
import pandas as pd
from glue.external.six import string_types
__all__ = ['unique', 'shape_to_string', 'view_shape', 'stack_view',
'coerce_numeric', 'check_sorted', 'broadca... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/utils/array.py",
"copies": "1",
"size": "4429",
"license": "bsd-3-clause",
"hash": 7107556927421325000,
"line_mean": 24.6011560694,
"line_max": 81,
"alpha_frac": 0.6089410702,
"autogenerated": false,
"ratio": 3.6785714285714284,
"config_test":... |
from __future__ import absolute_import, division, print_function
import numpy as np
from numpy.testing import (assert_allclose,
assert_equal, assert_almost_equal, assert_raises)
from scipy.spatial import procrustes
class TestProcrustes(object):
def setup_method(self):
"""creat... | {
"repo_name": "apbard/scipy",
"path": "scipy/spatial/tests/test__procrustes.py",
"copies": "1",
"size": "5049",
"license": "bsd-3-clause",
"hash": -6663346325361193000,
"line_mean": 41.7881355932,
"line_max": 79,
"alpha_frac": 0.5066349772,
"autogenerated": false,
"ratio": 3.249034749034749,
"c... |
from __future__ import absolute_import, division, print_function
import numpy as np
from numpy.testing import (TestCase, run_module_suite, assert_allclose,
assert_equal, assert_almost_equal, assert_raises)
from scipy.spatial import procrustes
class ProcrustesTests(TestCase):
def setUp(... | {
"repo_name": "DailyActie/Surrogate-Model",
"path": "01-codes/scipy-master/scipy/spatial/tests/test__procrustes.py",
"copies": "1",
"size": "5153",
"license": "mit",
"hash": -4007413244538559000,
"line_mean": 41.9416666667,
"line_max": 79,
"alpha_frac": 0.5063070056,
"autogenerated": false,
"rati... |
from __future__ import absolute_import, division, print_function
import numpy as np
from pandas import DataFrame
import numpy as np
from odo import resource, into
from datashape.predicates import isscalar, iscollection, isrecord
from blaze.expr import symbol, by
from blaze.interactive import Data
from blaze.compute im... | {
"repo_name": "mrocklin/blaze",
"path": "blaze/compute/tests/test_comprehensive.py",
"copies": "1",
"size": "4373",
"license": "bsd-3-clause",
"hash": 8019634906921651000,
"line_mean": 30.0141843972,
"line_max": 92,
"alpha_frac": 0.5314429453,
"autogenerated": false,
"ratio": 3.3003773584905662,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from pandas import DataFrame
import numpy as np
import bcolz
from datashape.predicates import isscalar, iscollection, isrecord
from blaze.expr import Symbol, by
from blaze.api import Data, into
from blaze.compute import compute
from bl... | {
"repo_name": "vitan/blaze",
"path": "blaze/compute/tests/test_comprehensive.py",
"copies": "1",
"size": "3618",
"license": "bsd-3-clause",
"hash": -1023266594592036500,
"line_mean": 29.6610169492,
"line_max": 78,
"alpha_frac": 0.5243228303,
"autogenerated": false,
"ratio": 3.277173913043478,
"... |
from __future__ import absolute_import, division, print_function
import numpy as np
from pandas import DataFrame, Series
from ..expr import Reduction, Field, Projection, Broadcast, Selection
from ..expr import Distinct, Sort, Head, Label, ReLabel, Union, Expr, Slice
from ..expr import std, var, count, nunique
from ..... | {
"repo_name": "vitan/blaze",
"path": "blaze/compute/numpy.py",
"copies": "1",
"size": "3923",
"license": "bsd-3-clause",
"hash": 193463488919735650,
"line_mean": 24.3096774194,
"line_max": 78,
"alpha_frac": 0.6543461637,
"autogenerated": false,
"ratio": 2.978739559605163,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from qtpy import QtGui
from glue.core import roi as roimod
__all__ = ['cmap2pixmap', 'ginga_graphic_to_roi']
def cmap2pixmap(cmap, steps=50):
"""Convert a Ginga colormap into a QtGui.QPixmap
:param cmap: The colormap to use... | {
"repo_name": "saimn/glue",
"path": "glue/plugins/ginga_viewer/qt/utils.py",
"copies": "1",
"size": "1611",
"license": "bsd-3-clause",
"hash": -8977182342137021000,
"line_mean": 31.22,
"line_max": 75,
"alpha_frac": 0.5890751086,
"autogenerated": false,
"ratio": 3.0685714285714285,
"config_test"... |
from __future__ import absolute_import, division, print_function
import numpy as np
from scipy.ndimage import gaussian_filter
from glue.core.data import Subset
from glue.core.exceptions import IncompatibleAttribute
from .layer_state import IsosurfaceLayerState
from ..common.layer_artist import VispyLayerArtist
from... | {
"repo_name": "astrofrog/glue-vispy-viewers",
"path": "glue_vispy_viewers/isosurface/layer_artist.py",
"copies": "2",
"size": "6925",
"license": "bsd-2-clause",
"hash": -837508147351221500,
"line_mean": 30.334841629,
"line_max": 98,
"alpha_frac": 0.5810830325,
"autogenerated": false,
"ratio": 3.4... |
from __future__ import absolute_import, division, print_function
import numpy as np
from scipy.sparse import coo_matrix
from pymor.core.interfaces import inject_sid
from pymor.discretizations import StationaryDiscretization
from pymor.domaindescriptions import TorusDomain, CircleDomain
from pymor.domaindiscretizers i... | {
"repo_name": "sdrave/mfo-tutorial",
"path": "cellproblems.py",
"copies": "1",
"size": "8251",
"license": "bsd-2-clause",
"hash": -2903402919569150500,
"line_mean": 45.3539325843,
"line_max": 120,
"alpha_frac": 0.6299842443,
"autogenerated": false,
"ratio": 3.8163737280296024,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import numpy as np
from six import PY3
from six.moves import range
from .hashfunctions import hash64
if PY3:
long = int
class HyperLogLog(object):
""" Basic Hyperloglog """
def __init__(self, error_rate):
b = int(np.ceil(np.log2... | {
"repo_name": "Parsely/probably",
"path": "probably/hll.py",
"copies": "1",
"size": "2837",
"license": "mit",
"hash": 5403677793959691000,
"line_mean": 30.5222222222,
"line_max": 82,
"alpha_frac": 0.508635883,
"autogenerated": false,
"ratio": 3.4809815950920244,
"config_test": false,
"has_no_... |
from __future__ import absolute_import, division, print_function
import numpy as np
from six.moves import xrange
from .common import Benchmark
class LaplaceInplace(Benchmark):
params = ['inplace', 'normal']
param_names = ['update']
def setup(self, update):
N = 150
Niter = 1000
d... | {
"repo_name": "DailyActie/Surrogate-Model",
"path": "01-codes/numpy-master/benchmarks/benchmarks/bench_app.py",
"copies": "1",
"size": "2745",
"license": "mit",
"hash": -2245241569779055400,
"line_mean": 30.1931818182,
"line_max": 78,
"alpha_frac": 0.4907103825,
"autogenerated": false,
"ratio": 3... |
from __future__ import absolute_import, division, print_function
import numpy as np
from tensorflow.python.keras.callbacks import Callback
from tensorflow.python.platform import tf_logging as logging
class EarlyStopping(Callback):
""" Original implementation from keras, copied here with some
improvement.
Stop... | {
"repo_name": "imito/odin",
"path": "odin/backend/keras_callbacks.py",
"copies": "1",
"size": "5241",
"license": "mit",
"hash": -2785436992071219000,
"line_mean": 33.2549019608,
"line_max": 79,
"alpha_frac": 0.6216370922,
"autogenerated": false,
"ratio": 3.9614512471655328,
"config_test": false... |
from __future__ import absolute_import, division, print_function
import numpy as np
from toolz import concatv, drop, interleave
class SimplexPoint(object):
__slots__ = ('stencil', 'stepsize', 'halvings', 'index', 'is_reflect',
'is_doubled', 'simplex_key', 'point_key', 'point')
def __init__(... | {
"repo_name": "eriknw/dask-patternsearch",
"path": "dask_patternsearch/stencil.py",
"copies": "1",
"size": "7662",
"license": "bsd-3-clause",
"hash": 198489531210578140,
"line_mean": 36.5588235294,
"line_max": 99,
"alpha_frac": 0.5520751762,
"autogenerated": false,
"ratio": 3.6925301204819276,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from toolz import merge, accumulate
from into import discover, convert, append, into
from datashape.dispatch import dispatch
from datashape import DataShape
from operator import add
import itertools
from .core import rec_concatenate, A... | {
"repo_name": "PeterDSteinberg/dask",
"path": "dask/array/into.py",
"copies": "1",
"size": "1846",
"license": "bsd-3-clause",
"hash": -916139720945648400,
"line_mean": 25.3714285714,
"line_max": 71,
"alpha_frac": 0.6803900325,
"autogenerated": false,
"ratio": 3.21602787456446,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import numpy as np
from toolz import merge, partial
from ..base import tokenize
from .. import threaded
def _partial_fit(model, x, y, kwargs=None):
kwargs = kwargs or dict()
model.partial_fit(x, y, **kwargs)
return model
def fit(model, x... | {
"repo_name": "cpcloud/dask",
"path": "dask/array/learn.py",
"copies": "5",
"size": "3248",
"license": "bsd-3-clause",
"hash": -266483141824313950,
"line_mean": 30.2307692308,
"line_max": 79,
"alpha_frac": 0.5914408867,
"autogenerated": false,
"ratio": 3.3903966597077244,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import numpy as np
from .wrap import wrap, wrap_func_size_as_kwarg
"""
Univariate distributions
"""
wrap = wrap(wrap_func_size_as_kwarg)
random = wrap(np.random.random)
beta = wrap(np.random.beta)
binomial = wrap(np.random.binomial)
chisquare = wrap(n... | {
"repo_name": "esc/dask",
"path": "dask/array/random.py",
"copies": "5",
"size": "1570",
"license": "bsd-3-clause",
"hash": 1508854771252968200,
"line_mean": 27.0357142857,
"line_max": 64,
"alpha_frac": 0.7675159236,
"autogenerated": false,
"ratio": 2.9734848484848486,
"config_test": false,
"... |
from __future__ import absolute_import, division, print_function
import numpy as np
import blz
from dynd import nd
import datashape
from . import DDesc, Capabilities
from .dynd_data_descriptor import DyND_DDesc
from shutil import rmtree
# WARNING! BLZ always return NumPy arrays when doing indexing
# operations. T... | {
"repo_name": "talumbau/blaze",
"path": "blaze/datadescriptor/blz_data_descriptor.py",
"copies": "1",
"size": "5763",
"license": "bsd-3-clause",
"hash": 5885715087383946000,
"line_mean": 31.9314285714,
"line_max": 77,
"alpha_frac": 0.5918792296,
"autogenerated": false,
"ratio": 4.234386480529023,... |
from __future__ import absolute_import, division, print_function
import numpy as np
import blz
from dynd import nd
import datashape
from . import IDataDescriptor, Capabilities
from .dynd_data_descriptor import DyNDDataDescriptor
# WARNING! BLZ always return NumPy arrays when doing indexing
# operations. This is w... | {
"repo_name": "aaronmartin0303/blaze",
"path": "blaze/datadescriptor/blz_data_descriptor.py",
"copies": "3",
"size": "5451",
"license": "bsd-3-clause",
"hash": 3651742674395680000,
"line_mean": 33.06875,
"line_max": 77,
"alpha_frac": 0.5997064759,
"autogenerated": false,
"ratio": 4.29550827423167... |
from __future__ import absolute_import, division, print_function
import numpy as np
import dask.array as da
try:
from dask.array import isin
except ImportError: # pragma: no cover
# Copied from dask v0.17.3.
# Used under the terms of Dask's license, see licenses/DASK_LICENSE.
def _isin_kernel(elemen... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/dask_array_compat.py",
"copies": "1",
"size": "1326",
"license": "apache-2.0",
"hash": 8776050326791888000,
"line_mean": 40.4375,
"line_max": 78,
"alpha_frac": 0.5844645551,
"autogenerated": false,
"ratio": 4.105263157894737,
"config_test": t... |
from __future__ import absolute_import, division, print_function
import numpy as np
import datashape as ds
import pytest
tb = pytest.importorskip('tables')
from odo import into
from odo.utils import tmpfile
from odo.backends.pytables import PyTables, discover
import os
try:
f = tb.open_file('import-tables-test.... | {
"repo_name": "ywang007/odo",
"path": "odo/backends/tests/test_pytables.py",
"copies": "1",
"size": "5252",
"license": "bsd-3-clause",
"hash": -5954882680826653000,
"line_mean": 31.825,
"line_max": 78,
"alpha_frac": 0.5158035034,
"autogenerated": false,
"ratio": 3.4758438120450035,
"config_test... |
from __future__ import absolute_import, division, print_function
import numpy as np
import datashape as ds
import pytest
tb = pytest.importorskip('tables')
from odo import into, odo
from odo.utils import tmpfile
from odo.backends.pytables import PyTables, discover
import os
try:
f = tb.open_file('import-tables-... | {
"repo_name": "cpcloud/odo",
"path": "odo/backends/tests/test_pytables.py",
"copies": "4",
"size": "5644",
"license": "bsd-3-clause",
"hash": -6090682938617079000,
"line_mean": 32.0058479532,
"line_max": 78,
"alpha_frac": 0.5157689582,
"autogenerated": false,
"ratio": 3.428918590522479,
"config... |
from __future__ import absolute_import, division, print_function
import numpy as np
import gsd.hoomd
import sklearn
import scipy.optimize as opt
import os
import os.path
import pdb
from sklearn.neighbors import BallTree
from sklearn.neighbors import radius_neighbors_graph
from scipy.spatial.distance import cdist,pdist... | {
"repo_name": "ramansbach/cluster_analysis",
"path": "clustering/clustering.py",
"copies": "1",
"size": "98464",
"license": "mit",
"hash": 4053610474325787000,
"line_mean": 34.5209235209,
"line_max": 138,
"alpha_frac": 0.5095872603,
"autogenerated": false,
"ratio": 4.199249402934152,
"config_te... |
from __future__ import absolute_import, division, print_function
import numpy as np
import gzip
from itertools import zip_longest
def _ascii_to_phred(s, offset):
"""Convert ascii to Phred quality score with specified ASCII offset."""
return np.fromstring(s, dtype='|S1').view(np.int8) - offset
def ascii_to... | {
"repo_name": "eco32i/keds",
"path": "src/parsers.py",
"copies": "1",
"size": "5717",
"license": "mit",
"hash": -5005583466393571000,
"line_mean": 37.3691275168,
"line_max": 79,
"alpha_frac": 0.572677978,
"autogenerated": false,
"ratio": 3.7341606792945785,
"config_test": false,
"has_no_keywo... |
from __future__ import absolute_import, division, print_function
import numpy as np
import h5py
from multipledispatch import MDNotImplementedError
from datashape import DataShape, to_numpy
from toolz import curry
from ..partition import partitions
from ..expr import Reduction, Field, symbol
from ..expr import Expr, S... | {
"repo_name": "dwillmer/blaze",
"path": "blaze/compute/h5py.py",
"copies": "12",
"size": "5533",
"license": "bsd-3-clause",
"hash": 6659819721293256000,
"line_mean": 31.9345238095,
"line_max": 81,
"alpha_frac": 0.672691126,
"autogenerated": false,
"ratio": 3.6281967213114754,
"config_test": fal... |
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