text stringlengths 0 1.05M | meta dict |
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from __future__ import absolute_import, division, print_function
import tensorflow as tf
from tensorflow import convert_to_tensor as to_T
from util.cnn import fc_layer as fc, conv_relu_layer as conv_relu
def _get_lstm_cell(num_layers, lstm_dim, apply_dropout):
if isinstance(lstm_dim, list): # Different layers h... | {
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"path": "models_shapes/nmn3_netgen_att.py",
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from __future__ import absolute_import, division, print_function
import tensorflow as tf
from tensorflow_probability.python import distributions as tfd
from tensorflow_probability.python import layers as tfl
from tensorflow_probability.python.internal import \
distribution_util as dist_util
from tensorflow_probabi... | {
"repo_name": "imito/odin",
"path": "odin/bay/distribution_layers/count_layers.py",
"copies": "1",
"size": "21219",
"license": "mit",
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"autogenerated": false,
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"config... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
from tensorflow.python.framework import dtypes
from tensorflow.contrib import learn as tflearn
from tensorflow.contrib import layers as tflayers
def lstm_model(num_units, rnn_layers, dense_layers=None, learning_rate=0.1, optimiz... | {
"repo_name": "irontarkus95/MET-Oracle-lstm-weather-prediction",
"path": "LSTM_RCNN/lstm.py",
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from __future__ import absolute_import, division, print_function
import tensorflow as tf
import polyaxon_lib as plx
from polyaxon_schemas.losses import SoftmaxCrossEntropyConfig
from polyaxon_schemas.metrics import AccuracyConfig
from polyaxon_schemas.optimizers import AdamConfig
def graph_fn(mode, features):
x... | {
"repo_name": "polyaxon/polyaxon-api",
"path": "examples/programatic_examples/imdb_sentiment_lstm.py",
"copies": "1",
"size": "1839",
"license": "mit",
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"line_max": 91,
"alpha_frac": 0.6742794997,
"autogenerated": false,
"ratio": 3.502857142... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
import tensorflow.contrib.layers as layers
from deep_rl.misc import slice_2d, get_vars_from_scope
def create_a3c_graph(input_shape, n_action, model, opt, beta=None, name='a3c'):
"""
Implements Actor Critic Model (A3C)
... | {
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"path": "deep_rl/graphs/a3c.py",
"copies": "1",
"size": "2340",
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"alpha_frac": 0.6666666667,
"autogenerated": false,
"ratio": 3.20109439124487,
"config_test": false,
"has... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
import torch
from tensorflow import nest
from tensorflow.python import keras
from odin import backend as bk
# ===========================================================================
# Base classe
# =========================... | {
"repo_name": "imito/odin",
"path": "odin/networks/attention.py",
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"license": "mit",
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"autogenerated": false,
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"config_test": true,
"has... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
def conv_layer(name, bottom, kernel_size, stride, output_dim, padding='SAME',
bias_term=True, weights_initializer=None, biases_initializer=None, reuse=None):
# input has shape [batch, in_height, in_width, in_ch... | {
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"path": "util/cnn.py",
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"h... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
from deep_rl.misc.utils import get_vars_from_scope, slice_2d
def create_dqn_graph(n_action, model, opt, gamma=0.99):
"""
Implements Deep Q-Learning
if terminal:
y = r
else:
y = r + gamma * max_a... | {
"repo_name": "domluna/deep_rl",
"path": "deep_rl/graphs/dqn.py",
"copies": "1",
"size": "1550",
"license": "mit",
"hash": 6630909429152993000,
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"alpha_frac": 0.5909677419,
"autogenerated": false,
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"config_test": false,
"h... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
from deep_rl.misc.utils import get_vars_from_scope, slice_2d
def create_vpg_graph(n_action, policy_model, value_model, policy_opt, value_opt):
"""
Implements Vanilla Policy Gradient
"""
actions = tf.placeholder(... | {
"repo_name": "domluna/deep_rl",
"path": "deep_rl/graphs/vpg.py",
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"ha... |
from __future__ import absolute_import, division, print_function
import tensorflow as tf
def full_connect(inputs,
weights_shape,
biases_shape,
is_train=True,
FLAGS=None):
"""
Define full-connect layer with reused Variables.
"""
weights ... | {
"repo_name": "tobegit3hub/deep_recommend_system",
"path": "model.py",
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"ratio": 3.3255879059350506,
"config_test"... |
from __future__ import absolute_import, division, print_function
import textwrap
from distutils.version import LooseVersion
from collections import Iterator
import sys
import traceback
from contextlib import contextmanager
import warnings
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from p... | {
"repo_name": "cpcloud/dask",
"path": "dask/dataframe/utils.py",
"copies": "1",
"size": "21108",
"license": "bsd-3-clause",
"hash": -1765535917126917400,
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"line_max": 82,
"alpha_frac": 0.5701629714,
"autogenerated": false,
"ratio": 3.6677671589921808,
"config_test": f... |
from __future__ import absolute_import, division, print_function
import textwrap
from distutils.version import LooseVersion
from collections import Iterator
import sys
import numpy as np
import pandas as pd
import pandas.util.testing as tm
from pandas.core.common import is_datetime64tz_dtype, is_categorical_dtype
im... | {
"repo_name": "cowlicks/dask",
"path": "dask/dataframe/utils.py",
"copies": "1",
"size": "16030",
"license": "bsd-3-clause",
"hash": 8129658437381091000,
"line_mean": 32.7473684211,
"line_max": 79,
"alpha_frac": 0.566625078,
"autogenerated": false,
"ratio": 3.594170403587444,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import tflearn
def textfile_to_seq(file, seq_maxlen=25, redun_step=3):
""" string_to_semi_redundant_sequences.
Vectorize a string and returns parsed sequences and targets, along with
the associated dictionary.
Arguments:
string: ... | {
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from __future__ import absolute_import, division, print_function
import threading
from Queue import Empty
import cloudpickle as cp
import pytest
from mentor.queue import LockingQueue, Queue
def test_queue_put_get(zk):
queue = Queue(zk, '/mentor/putget')
queue.put(cp.dumps(range(5)))
assert cp.loads(queu... | {
"repo_name": "lensacom/satyr",
"path": "mentor/tests/test_queue.py",
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"size": "1905",
"license": "apache-2.0",
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"line_max": 65,
"alpha_frac": 0.6330708661,
"autogenerated": false,
"ratio": 3.0431309904153356,
"config_test": tr... |
from __future__ import absolute_import, division, print_function
import threading
from . import ir, pipeline, transforms
#------------------------------------------------------------------------
# Passes
#------------------------------------------------------------------------
passes = [
transforms.explicit_coe... | {
"repo_name": "zeeshanali/blaze",
"path": "blaze/compute/air/prepare.py",
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"alpha_frac": 0.4063301967,
"autogenerated": false,
"ratio": 5.566666666666666,
"config_te... |
from __future__ import absolute_import, division, print_function
import time
from Queue import Empty
import cloudpickle as cp
from kazoo.client import KazooClient
from kazoo.recipe.queue import LockingQueue as KazooLockingQueue
from kazoo.recipe.queue import Queue as KazooQueue
from .utils import timeout as seconds
... | {
"repo_name": "lensacom/satyr",
"path": "mentor/queue.py",
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"size": "1969",
"license": "apache-2.0",
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"line_max": 70,
"alpha_frac": 0.6109700356,
"autogenerated": false,
"ratio": 3.977777777777778,
"config_test": false,
"h... |
from __future__ import absolute_import, division, print_function
import time
import importlib
import json
import copy
import pdb
import tensorflow as tf
from tensorflow.python.ops import variables
import numpy as np
import tfutils.utils as utils
from tfutils.error import NanLossError, HiLossError, NoChangeError
from... | {
"repo_name": "neuroailab/tfutils",
"path": "tfutils/train.py",
"copies": "1",
"size": "22221",
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"line_max": 119,
"alpha_frac": 0.5507852932,
"autogenerated": false,
"ratio": 4.907464664310954,
"config_test": false,
"h... |
from __future__ import absolute_import, division, print_function
import time
import json
import os
import tempfile
import threading
from collections import defaultdict, Iterable
import numpy as np
from lcm import LCM
from robotlocomotion import viewer2_comms_t
from director.thirdparty import transformations
class Cl... | {
"repo_name": "patmarion/director",
"path": "src/python/director/viewerclient.py",
"copies": "1",
"size": "13512",
"license": "bsd-3-clause",
"hash": -1701496471069745200,
"line_mean": 29.4324324324,
"line_max": 105,
"alpha_frac": 0.5820011841,
"autogenerated": false,
"ratio": 3.9858407079646017,... |
from __future__ import absolute_import, division, print_function
import time
import numpy as np
import os
import glob
import warnings
import json
from PIL import Image
from ..datasets import VOT
from ..utils.metrics import poly_iou
from ..utils.viz import show_frame
class ExperimentVOT(object):
r"""Experiment p... | {
"repo_name": "got-10k/toolkit",
"path": "got10k/experiments/vot.py",
"copies": "1",
"size": "22933",
"license": "mit",
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"line_max": 94,
"alpha_frac": 0.4772162386,
"autogenerated": false,
"ratio": 4.434925546315993,
"config_test": false,... |
from __future__ import absolute_import, division, print_function
import time
import os
import construct
import idna
from tlsenum import hello_constructs
from tlsenum.mappings import (
CipherSuites, ECCurves, ECPointFormat, TLSProtocolVersion
)
class ClientHello(object):
@property
def protocol_version(... | {
"repo_name": "Ayrx/tlsenum",
"path": "tlsenum/parse_hello.py",
"copies": "1",
"size": "8585",
"license": "mit",
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"line_max": 78,
"alpha_frac": 0.5796156086,
"autogenerated": false,
"ratio": 4.1254204709274385,
"config_test": false,
"ha... |
from __future__ import absolute_import, division, print_function
import time
from ..messages import PythonTask
from ..queue import Queue
from ..scheduler import QueueScheduler, Running
from ..utils import timeout
__all__ = ('Pool',
'Queue',
'AsyncResult')
class AsyncResult(object):
def _... | {
"repo_name": "lensacom/satyr",
"path": "mentor/apis/multiprocessing.py",
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"size": "2193",
"license": "apache-2.0",
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"line_max": 79,
"alpha_frac": 0.6019151847,
"autogenerated": false,
"ratio": 4.0686456400742115,
"config_tes... |
from __future__ import absolute_import, division, print_function
import time
from workflows.services.common_service import CommonService
class UtilizationStatistics(object):
'''Generate statistics about the percentage of time spent in different
statuses over a fixed time slice. This class is not thread-safe.'... | {
"repo_name": "xia2/workflows",
"path": "workflows/frontend/utilization.py",
"copies": "1",
"size": "1847",
"license": "bsd-3-clause",
"hash": 2080981114472612000,
"line_mean": 40.9772727273,
"line_max": 99,
"alpha_frac": 0.6599891716,
"autogenerated": false,
"ratio": 4.095343680709535,
"config... |
from __future__ import absolute_import, division, print_function
import time
import appr.models.kv
from appr.exception import ResourceNotFound, UnableToLockResource
from appr.models.kv.filesystem import filesystem_client
from appr.models.kv.models_index_base import ModelsIndexBase
class ModelsIndexFilesystem(Models... | {
"repo_name": "app-registry/appr",
"path": "appr/models/kv/filesystem/models_index.py",
"copies": "2",
"size": "1633",
"license": "apache-2.0",
"hash": 1575734404513044700,
"line_mean": 34.5,
"line_max": 82,
"alpha_frac": 0.6099203919,
"autogenerated": false,
"ratio": 3.6862302483069977,
"confi... |
from __future__ import absolute_import, division, print_function
import time
import appr.models.kv
from appr.exception import ResourceNotFound, UnableToLockResource
from appr.models.kv.models_index_base import ModelsIndexBase
from appr.models.kv.redis import redis_client
class ModelsIndexRedis(ModelsIndexBase):
... | {
"repo_name": "app-registry/appr",
"path": "appr/models/kv/redis/models_index.py",
"copies": "2",
"size": "1638",
"license": "apache-2.0",
"hash": 6950786190620633000,
"line_mean": 34.6086956522,
"line_max": 82,
"alpha_frac": 0.5995115995,
"autogenerated": false,
"ratio": 3.576419213973799,
"co... |
from __future__ import absolute_import, division, print_function
import time
import etcd
import appr.models.kv
from appr.exception import ResourceNotFound, UnableToLockResource
from appr.models.kv.etcd import etcd_client
from appr.models.kv.models_index_base import ModelsIndexBase
class ModelsIndexEtcd(ModelsIndex... | {
"repo_name": "cn-app-registry/cnr-server",
"path": "appr/models/kv/etcd/models_index.py",
"copies": "2",
"size": "1775",
"license": "apache-2.0",
"hash": 5426085283039726000,
"line_mean": 33.1346153846,
"line_max": 85,
"alpha_frac": 0.5949295775,
"autogenerated": false,
"ratio": 3.51485148514851... |
from __future__ import absolute_import, division, print_function
import time
import numpy as np
import tensorflow as tf
import logging
from tensorflow.contrib import layers, learn
import gym
from deep_rl.graphs import create_vpg_graph
from deep_rl.trajectories import compute_vpg_advantage, sample_traj
from deep_rl.m... | {
"repo_name": "domluna/deep_rl",
"path": "examples/run_vpg.py",
"copies": "1",
"size": "5686",
"license": "mit",
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"line_max": 98,
"alpha_frac": 0.5944424903,
"autogenerated": false,
"ratio": 3.630906768837803,
"config_test": false,
"has... |
from __future__ import absolute_import, division, print_function
import time
# TODO: change thrown errors to these
from concurrent.futures import ALL_COMPLETED, CancelledError, TimeoutError
from ..messages import PythonTask
from ..scheduler import QueueScheduler, Running
from ..utils import timeout as seconds
__all... | {
"repo_name": "lensacom/satyr",
"path": "mentor/apis/futures.py",
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"line_max": 74,
"alpha_frac": 0.5873015873,
"autogenerated": false,
"ratio": 4.288956127080182,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import toolz
from datashape import Record, DataShape, dshape
from datashape import coretypes as ct
import datashape
from numpy import inf
from .core import common_subexpression
from .expressions import Expr, ndim
class Reduction(Expr):
""" A colum... | {
"repo_name": "mrocklin/blaze",
"path": "blaze/expr/reductions.py",
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"config_test":... |
from __future__ import absolute_import, division, print_function
import toolz
from toolz import first
import datashape
from datashape import Record, dshape, DataShape
from datashape import coretypes as ct
from datashape.predicates import isscalar, iscollection
from .core import common_subexpression
from .expressions ... | {
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from __future__ import absolute_import, division, print_function
import toolz
from toolz import pipe
import itertools
from datashape import discover, Unit, Tuple, Record, iscollection, isscalar
import sqlalchemy as sa
from ..data.sql import dshape_to_alchemy
from ..dispatch import dispatch
from ..expr import *
from .... | {
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from __future__ import absolute_import, division, print_function
import toolz
import datashape
import functools
from toolz import concat, memoize, partial
import re
from datashape import dshape, DataShape, Record, Var, Mono
from datashape.predicates import isscalar, iscollection, isboolean, isrecord
from ..compatibi... | {
"repo_name": "vitan/blaze",
"path": "blaze/expr/expressions.py",
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"alpha_frac": 0.5669291339,
"autogenerated": false,
"ratio": 3.911638475132542,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import toolz
import datashape
import functools
import keyword
import numpy as np
from toolz import concat, memoize, partial
from toolz.curried import map, filter
import re
from datashape import dshape, DataShape, Record, Var, Mono, Fixed
from datashape... | {
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"path": "blaze/expr/expressions.py",
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"ratio": 3.8933058316144757,
"config_test"... |
from __future__ import absolute_import, division, print_function
import toolz
import datashape
import re
from keyword import iskeyword
import numpy as np
from toolz import concat, memoize, partial, first
from toolz.curried import map, filter
from datashape import dshape, DataShape, Record, Var, Mono, Fixed
from da... | {
"repo_name": "dwillmer/blaze",
"path": "blaze/expr/expressions.py",
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"line_max": 80,
"alpha_frac": 0.5615387967,
"autogenerated": false,
"ratio": 3.830607476635514,
"config_test"... |
from __future__ import absolute_import, division, print_function
import toolz
__all__ = ['Expr', 'Scalar']
def _str(s):
""" Wrap single quotes around strings """
if isinstance(s, str):
return "'%s'" % s
else:
return str(s)
class Expr(object):
@property
def args(self):
... | {
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"hash": 6890287834447016000,
"line_mean": 24.012987013,
"line_max": 80,
"alpha_frac": 0.5301142264,
"autogenerated": false,
"ratio": 3.661596958174905,
"config_test": false,
... |
from __future__ import absolute_import, division, print_function
import traceback
from functools import wraps
from glue.core.session import Session
from glue.core.edit_subset_mode import EditSubsetMode
from glue.core.hub import HubListener
from glue.core import Data, Subset
from glue.core import command
from glue.cor... | {
"repo_name": "saimn/glue",
"path": "glue/core/application_base.py",
"copies": "1",
"size": "13952",
"license": "bsd-3-clause",
"hash": 947870857902747400,
"line_mean": 27.9460580913,
"line_max": 83,
"alpha_frac": 0.5788417431,
"autogenerated": false,
"ratio": 4.41100221308884,
"config_test": f... |
from __future__ import absolute_import, division, print_function
import traceback
import warnings
from .dataarray import DataArray
from .dataset import Dataset
from .pycompat import PY2
class AccessorRegistrationWarning(Warning):
"""Warning for conflicts in accessor registration."""
class _CachedAccessor(obje... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/extensions.py",
"copies": "1",
"size": "3666",
"license": "apache-2.0",
"hash": 2109780267357222700,
"line_mean": 29.8067226891,
"line_max": 79,
"alpha_frac": 0.5927441353,
"autogenerated": false,
"ratio": 4.599749058971142,
"config_test": fa... |
from __future__ import absolute_import, division, print_function
import traceback
__all__ = ['die_on_error', 'avoid_circular']
def die_on_error(msg):
"""
Non-GUI version of the decorator in glue.utils.qt.decorators.
In this case we just let the Python exception terminate the execution.
"""
def ... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/utils/decorators.py",
"copies": "3",
"size": "1050",
"license": "bsd-3-clause",
"hash": -6189258101026877000,
"line_mean": 28.1666666667,
"line_max": 82,
"alpha_frac": 0.5466666667,
"autogenerated": false,
"ratio": 4.251012145748988,
"config_t... |
from __future__ import absolute_import, division, print_function
import types
import logging
from functools import wraps
import numpy as np
# We avoid importing matplotlib up here otherwise Matplotlib and therefore Qt
# get imported as soon as glue.utils is imported.
from glue.external.axescache import AxesCache
fr... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/utils/matplotlib.py",
"copies": "2",
"size": "8258",
"license": "bsd-3-clause",
"hash": -5841126655630998000,
"line_mean": 26.4352159468,
"line_max": 79,
"alpha_frac": 0.6248486316,
"autogenerated": false,
"ratio": 3.726534296028881,
"config_t... |
from __future__ import absolute_import, division, print_function
import types
import re
from datashape.typesets import TypeSet, matches_typeset
from datashape import (from_numba_str, to_numba, broadcastable)
from blaze.py2help import _strtypes, PY2
from .. import llvm_array as lla
from .blaze_kernels import BlazeElem... | {
"repo_name": "zeeshanali/blaze",
"path": "blaze/compute/bkernel/blaze_func.py",
"copies": "2",
"size": "10904",
"license": "bsd-3-clause",
"hash": 6671404794311050000,
"line_mean": 36.9930313589,
"line_max": 88,
"alpha_frac": 0.6161958914,
"autogenerated": false,
"ratio": 4,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import types
import datashape
from datashape import dshape, var, datetime_, float32, int64, bool_
from datashape.util.testing import assert_dshape_equal
import pandas as pd
import pytest
from blaze.compatibility import pickle
from blaze.expr import (
... | {
"repo_name": "ContinuumIO/blaze",
"path": "blaze/expr/tests/test_expr.py",
"copies": "3",
"size": "11527",
"license": "bsd-3-clause",
"hash": 5820691553834571000,
"line_mean": 29.820855615,
"line_max": 81,
"alpha_frac": 0.600242908,
"autogenerated": false,
"ratio": 3.067323044172432,
"config_t... |
from __future__ import absolute_import, division, print_function
import types
import datashape
from datashape import dshape, var, datetime_, float32, int64, bool_
import pandas as pd
import pytest
from blaze.compatibility import pickle
from blaze.expr import symbol, label, Field, Expr, Node
def test_slots():
a... | {
"repo_name": "cpcloud/blaze",
"path": "blaze/expr/tests/test_expr.py",
"copies": "2",
"size": "5714",
"license": "bsd-3-clause",
"hash": -9188664547619333000,
"line_mean": 29.2328042328,
"line_max": 81,
"alpha_frac": 0.5994049702,
"autogenerated": false,
"ratio": 3.1071234366503533,
"config_te... |
from __future__ import absolute_import, division, print_function
import unicodedata
import numpy as np
from .. import Variable, coding
from ..core.pycompat import OrderedDict, basestring, unicode_type
# Special characters that are permitted in netCDF names except in the
# 0th position of the string
_specialchars = ... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/backends/netcdf3.py",
"copies": "1",
"size": "4111",
"license": "apache-2.0",
"hash": -7908629870655553000,
"line_mean": 35.3805309735,
"line_max": 78,
"alpha_frac": 0.6489905133,
"autogenerated": false,
"ratio": 3.7924354243542435,
"config_test":... |
from __future__ import absolute_import, division, print_function
import unittest
from datetime import date, time, datetime
import blaze
from datashape import dshape
from blaze.datadescriptor import ddesc_as_py
class TestDate(unittest.TestCase):
def test_create(self):
a = blaze.array(date(2000, 1, 1))
... | {
"repo_name": "sethkontny/blaze",
"path": "blaze/tests/test_datetime.py",
"copies": "2",
"size": "3637",
"license": "bsd-3-clause",
"hash": 6781223384999112000,
"line_mean": 46.8552631579,
"line_max": 80,
"alpha_frac": 0.5812482816,
"autogenerated": false,
"ratio": 3.0717905405405403,
"config_t... |
from __future__ import absolute_import, division, print_function
import unittest
import ctypes
from datashape import dshape
from blaze.datadescriptor import data_descriptor_from_ctypes, dd_as_py
class TestCTypesMemBufDataDescriptor(unittest.TestCase):
def test_scalar(self):
a = ctypes.c_int(3)
... | {
"repo_name": "aaronmartin0303/blaze",
"path": "blaze/datadescriptor/tests/test_ctypes_membuf_data_descriptor.py",
"copies": "1",
"size": "2747",
"license": "bsd-3-clause",
"hash": -2510047899395444000,
"line_mean": 35.1447368421,
"line_max": 70,
"alpha_frac": 0.552238806,
"autogenerated": false,
... |
from __future__ import absolute_import, division, print_function
import unittest
import ctypes
import blaze
from blaze.datadescriptor import data_descriptor_from_ctypes
class TestArrayStr(unittest.TestCase):
def test_scalar(self):
self.assertEqual(str(blaze.array(100)), '100')
self.assertEqual(s... | {
"repo_name": "aaronmartin0303/blaze",
"path": "blaze/tests/test_array_str.py",
"copies": "1",
"size": "2135",
"license": "bsd-3-clause",
"hash": -5126686716650982000,
"line_mean": 31.8461538462,
"line_max": 77,
"alpha_frac": 0.5489461358,
"autogenerated": false,
"ratio": 3.1913303437967113,
"c... |
from __future__ import absolute_import, division, print_function
import unittest
import math
import blaze
from blaze.datadescriptor import ddesc_as_py
class TestBasic(unittest.TestCase):
def test_add(self):
types = ['int8', 'int16', 'int32', 'int64']
for type_ in types:
a = blaze.ar... | {
"repo_name": "sethkontny/blaze",
"path": "blaze/tests/test_calc.py",
"copies": "1",
"size": "15622",
"license": "bsd-3-clause",
"hash": -8707900961701460000,
"line_mean": 51.9559322034,
"line_max": 109,
"alpha_frac": 0.4357956728,
"autogenerated": false,
"ratio": 3.585494606380537,
"config_tes... |
from __future__ import absolute_import, division, print_function
import unittest
import os
import os.path
from astropy.io import fits
import numpy as np
import desispec.scripts.preproc
from desispec.preproc import preproc, _parse_sec_keyword, _clipped_std_bias
from desispec import io
def xy2hdr(xyslice):
'''
... | {
"repo_name": "gdhungana/desispec",
"path": "py/desispec/test/test_preproc.py",
"copies": "2",
"size": "13446",
"license": "bsd-3-clause",
"hash": 912529586417514100,
"line_mean": 42.3741935484,
"line_max": 101,
"alpha_frac": 0.6002528633,
"autogenerated": false,
"ratio": 3.16153303550435,
"con... |
from __future__ import absolute_import, division, print_function
import unittest
import os
import tempfile
from blaze.datadescriptor import (
JSONDataDescriptor, DyNDDataDescriptor, IDataDescriptor, dd_as_py)
# TODO: This isn't actually being used!
_json_buf = u"""{
"type": "ImageCollection",
"images": [... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/datadescriptor/tests/test_json_data_descriptor.py",
"copies": "2",
"size": "2444",
"license": "bsd-3-clause",
"hash": 937997391621558800,
"line_mean": 26.4606741573,
"line_max": 72,
"alpha_frac": 0.5683306056,
"autogenerated": false,
"ratio": 3.4914285... |
from __future__ import absolute_import, division, print_function
import unittest
import sys
if sys.version_info <= (3, 0):
from mock import patch, Mock
else:
from unittest.mock import patch, Mock
from panoptes_client.subject_set import SubjectSet
class TestSubjectSet(unittest.TestCase):
def test_create... | {
"repo_name": "zooniverse/panoptes-python-client",
"path": "panoptes_client/tests/test_subject_set.py",
"copies": "1",
"size": "1195",
"license": "apache-2.0",
"hash": 6573846257469512000,
"line_mean": 27.4523809524,
"line_max": 64,
"alpha_frac": 0.4343096234,
"autogenerated": false,
"ratio": 4.7... |
from __future__ import absolute_import, division, print_function
import unittest
import tempfile
import os
import csv
import sys
from collections import Iterator
import datashape
from datashape import dshape
from blaze.compatibility import skipIf
from blaze.data.core import DataDescriptor
from blaze.data import CSV
... | {
"repo_name": "aterrel/blaze",
"path": "blaze/data/tests/test_csv.py",
"copies": "1",
"size": "11700",
"license": "bsd-3-clause",
"hash": 5125669127557384000,
"line_mean": 31.4099722992,
"line_max": 85,
"alpha_frac": 0.5537606838,
"autogenerated": false,
"ratio": 3.3883579496090355,
"config_tes... |
from __future__ import absolute_import, division, print_function
import unittest
import tempfile
import os
import csv
import datashape
from blaze.data.core import DataDescriptor
from blaze.data import CSV
from blaze.data.csv import has_header
from blaze.utils import filetext
from dynd import nd
def sanitize(lines)... | {
"repo_name": "sethkontny/blaze",
"path": "blaze/data/tests/test_csv.py",
"copies": "1",
"size": "8543",
"license": "bsd-3-clause",
"hash": 3352021965356333000,
"line_mean": 32.2412451362,
"line_max": 77,
"alpha_frac": 0.5212454641,
"autogenerated": false,
"ratio": 2.9694125825512687,
"config_t... |
from __future__ import absolute_import, division, print_function
import unittest
import tempfile
import os
import datashape
from blaze.datadescriptor import (
CSVDataDescriptor, DyNDDataDescriptor, IDataDescriptor, dd_as_py)
# A CSV toy example
csv_buf = u"""k1,v1,1,False
k2,v2,2,True
k3,v3,3,False
"""
csv_sche... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/datadescriptor/tests/test_csv_data_descriptor.py",
"copies": "2",
"size": "5241",
"license": "bsd-3-clause",
"hash": -4940539992154953000,
"line_mean": 37.2554744526,
"line_max": 76,
"alpha_frac": 0.5601984354,
"autogenerated": false,
"ratio": 2.786283... |
from __future__ import absolute_import, division, print_function
import unittest
from datashape import coercion_cost, dshape, dshapes, error
from datashape.tests import common
from datashape.py2help import skip
class TestCoercion(common.BTestCase):
def test_coerce_ctype(self):
a, b, c = dshapes('float3... | {
"repo_name": "aterrel/datashape",
"path": "datashape/tests/test_coercion.py",
"copies": "2",
"size": "5147",
"license": "bsd-2-clause",
"hash": -6575026463690014000,
"line_mean": 44.5486725664,
"line_max": 76,
"alpha_frac": 0.5731494074,
"autogenerated": false,
"ratio": 3.270012706480305,
"con... |
from __future__ import absolute_import, division, print_function
import unittest
from datashape import coretypes as T
from datashape.type_equation_solver import (matches_datashape_pattern,
match_argtypes_to_signature,
_match_equat... | {
"repo_name": "aterrel/datashape",
"path": "datashape/tests/test_type_equation_solver.py",
"copies": "1",
"size": "12820",
"license": "bsd-2-clause",
"hash": 3002905241598810600,
"line_mean": 51.9752066116,
"line_max": 103,
"alpha_frac": 0.5030421217,
"autogenerated": false,
"ratio": 3.6744052737... |
from __future__ import absolute_import, division, print_function
import unittest
from datashape import dshape
from blaze.compute.air import explicit_coercions
from blaze.compute.air.tests.utils import make_graph
class TestCoercions(unittest.TestCase):
def test_coercions(self):
f, values, graph = make_g... | {
"repo_name": "zeeshanali/blaze",
"path": "blaze/compute/air/tests/test_transforms.py",
"copies": "1",
"size": "1205",
"license": "bsd-3-clause",
"hash": -6411709695848540000,
"line_mean": 34.4411764706,
"line_max": 105,
"alpha_frac": 0.5626556017,
"autogenerated": false,
"ratio": 3.1627296587926... |
from __future__ import absolute_import, division, print_function
import unittest
from datashape import dshape
import blaze
from blaze import array
from blaze.compute.ops.ufuncs import add, mul
import numpy as np
#------------------------------------------------------------------------
# Utils
#---------------------... | {
"repo_name": "XinSong/blaze",
"path": "blaze/compute/air/execution/tests/test_jit_interp.py",
"copies": "2",
"size": "1800",
"license": "bsd-3-clause",
"hash": -4784771157975032000,
"line_mean": 31.7272727273,
"line_max": 73,
"alpha_frac": 0.4972222222,
"autogenerated": false,
"ratio": 3.5856573... |
from __future__ import absolute_import, division, print_function
import unittest
import blaze
from blaze.datadescriptor import dd_as_py
class TestBasic(unittest.TestCase):
def test_add(self):
types = ['int8', 'int16', 'int32', 'int64']
for type_ in types:
a = blaze.array(range(3), d... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/tests/test_calc.py",
"copies": "1",
"size": "13856",
"license": "bsd-3-clause",
"hash": -3796418383526555600,
"line_mean": 52.2923076923,
"line_max": 106,
"alpha_frac": 0.4131062356,
"autogenerated": false,
"ratio": 3.778565584946823,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import unittest
import datashape
import blaze
from blaze.optional_packages import tables_is_here
from blaze.catalog.tests.catalog_harness import CatalogHarness
from blaze.py2help import skipIf
class TestCatalog(unittest.TestCase):
def setUp(self):... | {
"repo_name": "xsixing/blaze",
"path": "blaze/catalog/tests/test_catalog.py",
"copies": "2",
"size": "5754",
"license": "bsd-3-clause",
"hash": 8851084069624317000,
"line_mean": 39.5211267606,
"line_max": 73,
"alpha_frac": 0.5742092457,
"autogenerated": false,
"ratio": 3.289879931389365,
"confi... |
from __future__ import absolute_import, division, print_function
import unittest
import numpy as np
from numpy.testing import assert_array_equal, assert_allclose
from dynd import nd, ndt
import blaze
import unittest
import tempfile
import os, os.path
import glob
import shutil
import blaze
# Useful superclass for ... | {
"repo_name": "talumbau/blaze",
"path": "blaze/compute/tests/test_elwise_eval.py",
"copies": "1",
"size": "15565",
"license": "bsd-3-clause",
"hash": 3863244668738426000,
"line_mean": 35.0300925926,
"line_max": 76,
"alpha_frac": 0.5866366849,
"autogenerated": false,
"ratio": 3.1030701754385963,
... |
from __future__ import absolute_import, division, print_function
import unittest
import numpy as np
import blaze
from blaze.datadescriptor import dd_as_py
from datashape import to_numpy_dtype
class TestBasicTypes(unittest.TestCase):
def test_ints(self):
types = ['int8', 'int16', 'int32', 'int64']
... | {
"repo_name": "xsixing/blaze",
"path": "blaze/tests/test_types.py",
"copies": "2",
"size": "1701",
"license": "bsd-3-clause",
"hash": -7271557337315856000,
"line_mean": 35.1914893617,
"line_max": 64,
"alpha_frac": 0.5661375661,
"autogenerated": false,
"ratio": 3.3029126213592233,
"config_test":... |
from __future__ import absolute_import, division, print_function
import unittest
import numpy as np
import datashape
import blaze
from blaze.datadescriptor import dd_as_py
from blaze.tests.common import MayBeUriTest
from blaze import append
from blaze.py2help import skip
class TestEphemeral(unittest.TestCase):
... | {
"repo_name": "aaronmartin0303/blaze",
"path": "blaze/tests/test_array_creation.py",
"copies": "1",
"size": "6505",
"license": "bsd-3-clause",
"hash": 276563344221429470,
"line_mean": 38.186746988,
"line_max": 77,
"alpha_frac": 0.5949269792,
"autogenerated": false,
"ratio": 3.17626953125,
"conf... |
from __future__ import absolute_import, division, print_function
import unittest
import numpy as np
from datashape import dshape
import blaze
from blaze.compute.function import BlazeFunc
from dynd import nd, _lowlevel
def create_overloaded_add():
# Create an overloaded blaze func, populate it with
# some c... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/tests/test_blaze_functions.py",
"copies": "1",
"size": "4231",
"license": "bsd-3-clause",
"hash": 6340688238991609000,
"line_mean": 39.2952380952,
"line_max": 80,
"alpha_frac": 0.5327345781,
"autogenerated": false,
"ratio": 3.344664031620553,
"config... |
from __future__ import absolute_import, division, print_function
import unittest
import numpy as np
from datashape import dshape
import blaze
from blaze.compute.function import ElementwiseBlazeFunc
from dynd import nd, _lowlevel
def create_overloaded_add():
# Create an overloaded blaze func, populate it with
... | {
"repo_name": "sethkontny/blaze",
"path": "blaze/tests/test_blaze_functions.py",
"copies": "1",
"size": "4180",
"license": "bsd-3-clause",
"hash": 5558677850027961000,
"line_mean": 38.8095238095,
"line_max": 79,
"alpha_frac": 0.5459330144,
"autogenerated": false,
"ratio": 3.365539452495974,
"co... |
from __future__ import absolute_import, division, print_function
import unittest
import numpy as np
from datashape import dshape
import blaze
from blaze.compute.function import function, kernel
from blaze import array, py2help
from dynd import nd, _lowlevel
# f
@function('X, Y, float32 -> X, Y, float32 -> X, Y, fl... | {
"repo_name": "aaronmartin0303/blaze",
"path": "blaze/tests/test_blaze_functions.py",
"copies": "1",
"size": "4654",
"license": "bsd-3-clause",
"hash": 3194633730198116000,
"line_mean": 32.4820143885,
"line_max": 80,
"alpha_frac": 0.5640309411,
"autogenerated": false,
"ratio": 3.0985352862849536,... |
from __future__ import absolute_import, division, print_function
import unittest
try:
# Python 3
from unittest import mock
except ImportError:
# Python 2
import mock
try:
# Python 2
from StringIO import StringIO
except ImportError:
# Python 3
from io import StringIO
import time
from... | {
"repo_name": "gannon93/gkit_utils",
"path": "tests/test_print_utilities.py",
"copies": "1",
"size": "4028",
"license": "mit",
"hash": 4336444804499228000,
"line_mean": 32.2892561983,
"line_max": 81,
"alpha_frac": 0.5757199603,
"autogenerated": false,
"ratio": 3.502608695652174,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import urllib, json
from ... import py2help
if py2help.PY2:
from urllib2 import urlopen
else:
from urllib.request import urlopen
def get_remote_datashape(url):
"""Gets the datashape of a remote array URL."""
response = urlopen(url + '?r... | {
"repo_name": "cezary12/blaze",
"path": "blaze/io/client/requests.py",
"copies": "7",
"size": "2898",
"license": "bsd-3-clause",
"hash": -5464330104047525000,
"line_mean": 33.9156626506,
"line_max": 74,
"alpha_frac": 0.61042098,
"autogenerated": false,
"ratio": 3.7058823529411766,
"config_test"... |
from __future__ import absolute_import, division, print_function
import urllib
import json
from ... import py2help
if py2help.PY2:
from urllib2 import urlopen
else:
from urllib.request import urlopen
def get_remote_datashape(url):
"""Gets the datashape of a remote array URL."""
response = urlopen(ur... | {
"repo_name": "mwiebe/blaze",
"path": "blaze/io/client/requests.py",
"copies": "6",
"size": "2905",
"license": "bsd-3-clause",
"hash": -7200900151490190000,
"line_mean": 33.1764705882,
"line_max": 74,
"alpha_frac": 0.6110154905,
"autogenerated": false,
"ratio": 3.705357142857143,
"config_test":... |
from __future__ import absolute_import, division, print_function
import urwid
TABSTOP = 8
class SourceLine(urwid.FlowWidget):
def __init__(self, dbg_ui, text, line_nr='', attr=None, has_breakpoint=False):
self.dbg_ui = dbg_ui
self.text = text
self.attr = attr
self.line_nr = line... | {
"repo_name": "albfan/pudb",
"path": "pudb/source_view.py",
"copies": "1",
"size": "11598",
"license": "mit",
"hash": -7398406091849711000,
"line_mean": 34.4678899083,
"line_max": 92,
"alpha_frac": 0.5043973099,
"autogenerated": false,
"ratio": 4.551805337519623,
"config_test": false,
"has_no... |
from __future__ import absolute_import, division, print_function
import uuid
import operator
import numbers
from glue.external import six
from glue.core.component_link import BinaryComponentLink
from glue.core.subset import InequalitySubsetState
from glue.core.message import DataRenameComponentMessage
__all__ = ['C... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/core/component_id.py",
"copies": "1",
"size": "5485",
"license": "bsd-3-clause",
"hash": -440545150288055040,
"line_mean": 29.3038674033,
"line_max": 109,
"alpha_frac": 0.6231540565,
"autogenerated": false,
"ratio": 4.108614232209738,
"config_... |
from __future__ import absolute_import, division, print_function
import uuid
import weakref
from matplotlib.colors import ColorConverter
from glue.core.data import Subset, Data
from glue.core.exceptions import IncompatibleAttribute
from glue.utils import broadcast_to
from glue.core.fixed_resolution_buffer import ARR... | {
"repo_name": "astrofrog/glue-vispy-viewers",
"path": "glue_vispy_viewers/volume/layer_artist.py",
"copies": "2",
"size": "8312",
"license": "bsd-2-clause",
"hash": 3228586871450114000,
"line_mean": 32.248,
"line_max": 93,
"alpha_frac": 0.6120067372,
"autogenerated": false,
"ratio": 3.89138576779... |
from __future__ import absolute_import, division, print_function
import uuid
import weakref
import numpy as np
from glue.utils import defer_draw
from glue.viewers.image.state import ImageLayerState, ImageSubsetLayerState
from glue.viewers.matplotlib.layer_artist import MatplotlibLayerArtist
from glue.core.exception... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/viewers/image/layer_artist.py",
"copies": "1",
"size": "13979",
"license": "bsd-3-clause",
"hash": -5157392344947443000,
"line_mean": 34.0350877193,
"line_max": 90,
"alpha_frac": 0.5943200515,
"autogenerated": false,
"ratio": 4.2592931139549055,... |
from __future__ import (absolute_import, division, print_function)
import uuid
from odm2api import serviceBase
from odm2api.models import TimeSeriesResultValues
__author__ = 'sreeder'
class CreateODM2(serviceBase):
# Annotations
def create(self, value):
self._session.add(value)
self._sessi... | {
"repo_name": "ODM2/ODM2PythonAPI",
"path": "odm2api/services/createService.py",
"copies": "2",
"size": "4187",
"license": "bsd-3-clause",
"hash": 2374704380582786600,
"line_mean": 26.1883116883,
"line_max": 83,
"alpha_frac": 0.6166706472,
"autogenerated": false,
"ratio": 4.440084835630965,
"co... |
from __future__ import absolute_import, division, print_function
import uuid
import numpy as np
from glue.core.exceptions import IncompatibleAttribute
from glue.utils import categorical_ndarray
from .multi_scatter import MultiColorScatter
from .layer_state import ScatterLayerState
from ..common.layer_artist import ... | {
"repo_name": "astrofrog/glue-vispy-viewers",
"path": "glue_vispy_viewers/scatter/layer_artist.py",
"copies": "2",
"size": "9420",
"license": "bsd-2-clause",
"hash": 4064415048604583000,
"line_mean": 35.091954023,
"line_max": 100,
"alpha_frac": 0.5847133758,
"autogenerated": false,
"ratio": 3.843... |
from __future__ import absolute_import, division, print_function
import uuid
import numpy as np
from glue.utils import nonpartial
from glue.core.exceptions import IncompatibleAttribute
from .multi_scatter import MultiColorScatter
from .layer_state import ScatterLayerState
from ..common.layer_artist import VispyLaye... | {
"repo_name": "PennyQ/glue-3d-viewer",
"path": "glue_vispy_viewers/scatter/layer_artist.py",
"copies": "1",
"size": "7350",
"license": "bsd-2-clause",
"hash": 2502536197070844000,
"line_mean": 34.6796116505,
"line_max": 100,
"alpha_frac": 0.5783673469,
"autogenerated": false,
"ratio": 3.786707882... |
from __future__ import absolute_import, division, print_function
import warnings
from collections import defaultdict
import numpy as np
import pandas as pd
from .coding import times, strings, variables
from .coding.variables import SerializationWarning
from .core import duck_array_ops, indexing
from .core.pycompat i... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/conventions.py",
"copies": "1",
"size": "20549",
"license": "apache-2.0",
"hash": -7202417387283354000,
"line_mean": 34.5519031142,
"line_max": 79,
"alpha_frac": 0.6239233053,
"autogenerated": false,
"ratio": 4.212587125871258,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import warnings
from distutils.version import LooseVersion
import numpy as np
import pandas as pd
from . import duck_array_ops, dtypes, formatting, ops
from .arithmetic import SupportsArithmetic
from .pycompat import OrderedDict, basestring, dask_array... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/common.py",
"copies": "1",
"size": "36053",
"license": "apache-2.0",
"hash": 8784939485576623000,
"line_mean": 36.3219461698,
"line_max": 90,
"alpha_frac": 0.5509943694,
"autogenerated": false,
"ratio": 4.2696589294173375,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import warnings
from distutils.version import LooseVersion
import numpy as np
from . import dtypes
from .dask_array_ops import dask_rolling_wrapper
from .ops import (
bn, has_bottleneck, inject_bottleneck_rolling_methods,
inject_datasetrolling_... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/rolling.py",
"copies": "1",
"size": "16276",
"license": "apache-2.0",
"hash": 1268512750411181800,
"line_mean": 34.4596949891,
"line_max": 79,
"alpha_frac": 0.5381543377,
"autogenerated": false,
"ratio": 4.412035782054757,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import warnings
from functools import wraps
import pandas as pd
from pandas.core.window import Rolling as pd_Rolling
from ..base import tokenize
from ..utils import M, funcname, derived_from
from .core import _emulate
from .utils import make_meta
def... | {
"repo_name": "gameduell/dask",
"path": "dask/dataframe/rolling.py",
"copies": "3",
"size": "8631",
"license": "bsd-3-clause",
"hash": -9126737527843209000,
"line_mean": 34.2285714286,
"line_max": 81,
"alpha_frac": 0.5871857259,
"autogenerated": false,
"ratio": 3.713855421686747,
"config_test":... |
from __future__ import absolute_import, division, print_function
import warnings
from operator import attrgetter
from hashlib import md5
from functools import partial
from toolz import merge, groupby, curry
from toolz.functoolz import Compose
from .compatibility import bind_method
from .context import _globals
from ... | {
"repo_name": "pombredanne/dask",
"path": "dask/base.py",
"copies": "1",
"size": "6501",
"license": "bsd-3-clause",
"hash": -248236159776766340,
"line_mean": 32.3384615385,
"line_max": 90,
"alpha_frac": 0.5945239194,
"autogenerated": false,
"ratio": 3.8151408450704225,
"config_test": false,
"... |
from __future__ import absolute_import, division, print_function
import warnings
from os.path import basename
from collections import OrderedDict
from glue.core.coordinates import coordinates_from_header, WCSCoordinates
from glue.core.data import Component, Data
from glue.config import data_factory, qglue_parser
__... | {
"repo_name": "saimn/glue",
"path": "glue/core/data_factories/fits.py",
"copies": "3",
"size": "6169",
"license": "bsd-3-clause",
"hash": -8495161455730323000,
"line_mean": 29.5396039604,
"line_max": 112,
"alpha_frac": 0.5882639001,
"autogenerated": false,
"ratio": 3.789312039312039,
"config_te... |
from __future__ import absolute_import, division, print_function
import warnings
import functools
import inspect
import datetime
import tempfile
import os
import shutil
import numpy as np
from contextlib import contextmanager
from multiprocessing.pool import ThreadPool
from multipledispatch import Dispatcher
from d... | {
"repo_name": "ContinuumIO/odo",
"path": "odo/utils.py",
"copies": "4",
"size": "11332",
"license": "bsd-3-clause",
"hash": 6774509659130769000,
"line_mean": 24.4651685393,
"line_max": 80,
"alpha_frac": 0.562919167,
"autogenerated": false,
"ratio": 3.9170411337711717,
"config_test": false,
"h... |
from __future__ import absolute_import, division, print_function
import warnings
from datashape import dshape
import flask
from flask.testing import FlaskClient
from odo import resource
import requests
from requests.packages.urllib3.exceptions import InsecureRequestWarning
from toolz import assoc, keymap
from ..comp... | {
"repo_name": "ContinuumIO/blaze",
"path": "blaze/server/client.py",
"copies": "2",
"size": "8386",
"license": "bsd-3-clause",
"hash": 4445558518802110000,
"line_mean": 30.8859315589,
"line_max": 94,
"alpha_frac": 0.6148342476,
"autogenerated": false,
"ratio": 4.246075949367088,
"config_test": ... |
from __future__ import (absolute_import, division, print_function)
import warnings
from odm2api import serviceBase
from odm2api.models import (
ActionAnnotations, ActionDirectives, ActionExtensionPropertyValues, Actions,
Affiliations, Annotations, AuthorLists, CVActionType, CVAggregationStatistic,
CVAnnot... | {
"repo_name": "ODM2/ODM2PythonAPI",
"path": "odm2api/services/readService.py",
"copies": "1",
"size": "59584",
"license": "bsd-3-clause",
"hash": -4594977475727984600,
"line_mean": 38.6433799069,
"line_max": 158,
"alpha_frac": 0.5968380773,
"autogenerated": false,
"ratio": 4.4211619796690655,
"... |
from __future__ import absolute_import, division, print_function
import warnings
import datashape
from datashape import String, DataShape, Option, bool_
from odo.utils import copydoc
from .expressions import schema_method_list, ElemWise
from .arithmetic import Interp, Repeat, _mkbin, repeat, interp, _add, _radd
from... | {
"repo_name": "ContinuumIO/blaze",
"path": "blaze/expr/strings.py",
"copies": "3",
"size": "10912",
"license": "bsd-3-clause",
"hash": -7644352640154388000,
"line_mean": 29.1436464088,
"line_max": 101,
"alpha_frac": 0.5998900293,
"autogenerated": false,
"ratio": 3.7941585535465925,
"config_test... |
from __future__ import absolute_import, division, print_function
import warnings
import numpy as np
import pandas as pd
import pkg_resources
from ..core.pycompat import basestring
from ..core.utils import is_scalar
ROBUST_PERCENTILE = 2.0
def _load_default_cmap(fname='default_colormap.csv'):
"""
Returns v... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/plot/utils.py",
"copies": "1",
"size": "11666",
"license": "apache-2.0",
"hash": -669678987555741200,
"line_mean": 31.7696629213,
"line_max": 79,
"alpha_frac": 0.6083490485,
"autogenerated": false,
"ratio": 3.8349769888231426,
"config_test": false... |
from __future__ import absolute_import, division, print_function
import warnings
import numpy as np
import pandas as pd
from .core import DataFrame, Series, Index, aca, map_partitions, no_default
from .shuffle import shuffle
from .utils import make_meta, insert_meta_param_description
from ..utils import derived_from... | {
"repo_name": "cowlicks/dask",
"path": "dask/dataframe/groupby.py",
"copies": "1",
"size": "15815",
"license": "bsd-3-clause",
"hash": -371227985008019400,
"line_mean": 33.9116997792,
"line_max": 95,
"alpha_frac": 0.5638318052,
"autogenerated": false,
"ratio": 4.064507838601902,
"config_test": ... |
from __future__ import absolute_import, division, print_function
import warnings
import numpy as np
import pandas as pd
from dask.dataframe.core import (DataFrame, Series, Index,
aca, map_partitions, no_default)
from dask.utils import derived_from
def _maybe_slice(grouped, columns)... | {
"repo_name": "mikegraham/dask",
"path": "dask/dataframe/groupby.py",
"copies": "1",
"size": "14261",
"license": "bsd-3-clause",
"hash": -5082556406472813000,
"line_mean": 31.5593607306,
"line_max": 86,
"alpha_frac": 0.5601991445,
"autogenerated": false,
"ratio": 4.0571834992887625,
"config_tes... |
from __future__ import absolute_import, division, print_function
import warnings
import numpy as np
import pandas as pd
from . import npcompat
def _validate_axis(data, axis):
ndim = data.ndim
if not -ndim <= axis < ndim:
raise IndexError('axis %r out of bounds [-%r, %r)'
% ... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/nputils.py",
"copies": "1",
"size": "6524",
"license": "apache-2.0",
"hash": -4987010971066444000,
"line_mean": 31.783919598,
"line_max": 111,
"alpha_frac": 0.6201716738,
"autogenerated": false,
"ratio": 3.736540664375716,
"config_test": fals... |
from __future__ import absolute_import, division, print_function
import warnings
import pandas as pd
import numpy as np
from pandas.tseries.resample import Resampler as pd_Resampler
from ..core import DataFrame, Series
from ...base import tokenize
from ...utils import derived_from
def getnanos(rule):
try:
... | {
"repo_name": "gameduell/dask",
"path": "dask/dataframe/tseries/resample.py",
"copies": "2",
"size": "5597",
"license": "bsd-3-clause",
"hash": -232735422896459360,
"line_mean": 30.8011363636,
"line_max": 83,
"alpha_frac": 0.5819188851,
"autogenerated": false,
"ratio": 3.558169103623649,
"confi... |
from __future__ import absolute_import, division, print_function
import warnings
import pandas as pd
import numpy as np
from ..core import DataFrame, Series
from ...base import tokenize
def getnanos(rule):
try:
return getattr(rule, 'nanos', None)
except ValueError:
return None
def _resamp... | {
"repo_name": "cowlicks/dask",
"path": "dask/dataframe/tseries/resample.py",
"copies": "2",
"size": "5034",
"license": "bsd-3-clause",
"hash": -5633275493435163000,
"line_mean": 30.4625,
"line_max": 80,
"alpha_frac": 0.568533969,
"autogenerated": false,
"ratio": 3.663755458515284,
"config_test"... |
from __future__ import absolute_import, division, print_function
import warnings
import pandas as pd
import numpy as np
from ..core import DataFrame, Series
from ..utils import PANDAS_VERSION
from ...base import tokenize
from ...utils import derived_from
if PANDAS_VERSION >= '0.20.0':
from pandas.core.resample ... | {
"repo_name": "mraspaud/dask",
"path": "dask/dataframe/tseries/resample.py",
"copies": "2",
"size": "5745",
"license": "bsd-3-clause",
"hash": 5152296525017448000,
"line_mean": 30.7403314917,
"line_max": 85,
"alpha_frac": 0.5857267189,
"autogenerated": false,
"ratio": 3.544108574953732,
"config... |
from __future__ import absolute_import, division, print_function
import warnings
import pandas as pd
from . import utils
from .alignment import align
from .merge import merge
from .pycompat import OrderedDict, basestring, iteritems
from .variable import concat as concat_vars
from .variable import IndexVariable, Vari... | {
"repo_name": "jcmgray/xarray",
"path": "xarray/core/combine.py",
"copies": "1",
"size": "18716",
"license": "apache-2.0",
"hash": -7987946823958506000,
"line_mean": 41.5363636364,
"line_max": 79,
"alpha_frac": 0.5915793973,
"autogenerated": false,
"ratio": 4.659198406771222,
"config_test": fal... |
from __future__ import absolute_import, division, print_function
import weakref
from itertools import chain
from weakref import WeakKeyDictionary
from contextlib import contextmanager
from .callback_container import CallbackContainer
__all__ = ['CallbackProperty', 'callback_property',
'add_callback', 'rem... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/external/echo/core.py",
"copies": "1",
"size": "20093",
"license": "bsd-3-clause",
"hash": 4903858446537994000,
"line_mean": 31.7781402936,
"line_max": 106,
"alpha_frac": 0.6016523167,
"autogenerated": false,
"ratio": 4.59688858384809,
"config... |
from __future__ import absolute_import, division, print_function
import weakref
import logging
from abc import ABCMeta, abstractmethod
from glue.utils import CallbackMixin
from glue.core.data_factories import load_data
from glue.core.edit_subset_mode import EditSubsetMode
MAX_UNDO = 50
"""
The classes in this module... | {
"repo_name": "stscieisenhamer/glue",
"path": "glue/core/command.py",
"copies": "1",
"size": "9078",
"license": "bsd-3-clause",
"hash": 377555847735910500,
"line_mean": 24.716713881,
"line_max": 83,
"alpha_frac": 0.6156642432,
"autogenerated": false,
"ratio": 4.098419864559819,
"config_test": f... |
from __future__ import absolute_import, division, print_function
import workflows.recipe
class RecipeWrapper(object):
'''A wrapper object which contains a recipe and a number of functions to make
life easier for recipe users.
'''
def __init__(self, message=None, transport=None, recipe=None, **kwargs):
... | {
"repo_name": "xia2/workflows",
"path": "workflows/recipe/wrapper.py",
"copies": "1",
"size": "7999",
"license": "bsd-3-clause",
"hash": 1529886499157076000,
"line_mean": 40.0205128205,
"line_max": 82,
"alpha_frac": 0.658832354,
"autogenerated": false,
"ratio": 4.488776655443322,
"config_test":... |
from __future__ import absolute_import, division, print_function
import zipfile
from fsspec import open_files
from fsspec.archive import AbstractArchiveFileSystem
from fsspec.utils import DEFAULT_BLOCK_SIZE
class ZipFileSystem(AbstractArchiveFileSystem):
"""Read contents of ZIP archive as a file-system
Kee... | {
"repo_name": "intake/filesystem_spec",
"path": "fsspec/implementations/zip.py",
"copies": "1",
"size": "3287",
"license": "bsd-3-clause",
"hash": 4395398571788153300,
"line_mean": 30.9126213592,
"line_max": 86,
"alpha_frac": 0.5223608153,
"autogenerated": false,
"ratio": 4.279947916666667,
"co... |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
from abc import ABCMeta, abstractmethod
class AbstractConsumer:
__metaclass__ = ABCMeta
"""
This class provides facilities to create and manage queue consumers. To
create a consumer, subclass this class and override... | {
"repo_name": "veegee/amqpy",
"path": "amqpy/consumer.py",
"copies": "1",
"size": "2942",
"license": "mit",
"hash": 6078707061962467000,
"line_mean": 30.6344086022,
"line_max": 86,
"alpha_frac": 0.6186267845,
"autogenerated": false,
"ratio": 4.4174174174174174,
"config_test": false,
"has_no_k... |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
from collections import namedtuple
queue_declare_ok_t = namedtuple('queue_declare_ok_t', ['queue', 'message_count', 'consumer_count'])
basic_return_t = namedtuple('basic_return_t',
['reply_code', 'reply_... | {
"repo_name": "veegee/amqpy",
"path": "amqpy/spec.py",
"copies": "1",
"size": "3150",
"license": "mit",
"hash": 7623663350077004000,
"line_mean": 24.6097560976,
"line_max": 100,
"alpha_frac": 0.6117460317,
"autogenerated": false,
"ratio": 2.9275092936802976,
"config_test": false,
"has_no_keyw... |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
from datetime import datetime
from decimal import Decimal
import pickle
from .. import Message
class TestBasicMessage:
def check_proplist(self, msg):
"""Check roundtrip processing of a single object
"""
... | {
"repo_name": "veegee/amqpy",
"path": "amqpy/tests/test_basic_message.py",
"copies": "1",
"size": "2475",
"license": "mit",
"hash": -7302332163755806000,
"line_mean": 31.5657894737,
"line_max": 95,
"alpha_frac": 0.5761616162,
"autogenerated": false,
"ratio": 3.9473684210526314,
"config_test": f... |
from __future__ import absolute_import, division, print_function
__metaclass__ = type
from threading import Lock
import sys
from collections import defaultdict, deque
import six
import logging
import socket
import errno
from .utils import get_errno
if six.PY2:
from Queue import Queue
else:
from queue import Q... | {
"repo_name": "veegee/amqpy",
"path": "amqpy/method_io.py",
"copies": "1",
"size": "8751",
"license": "mit",
"hash": -2020871074423022600,
"line_mean": 33.4527559055,
"line_max": 98,
"alpha_frac": 0.6144440635,
"autogenerated": false,
"ratio": 4.390868038133467,
"config_test": false,
"has_no_... |
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