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from __future__ import (absolute_import, division, print_function,
unicode_literals)
from pyramid.renderers import render
from pyramid_mailer import get_mailer
from pyramid_mailer.message import Message
from mako.exceptions import TopLevelLookupException
from premailer import Premailer
def pr... | {
"repo_name": "storborg/warpworks",
"path": "warpworks/mail.py",
"copies": "1",
"size": "1404",
"license": "mit",
"hash": 9175132279240191000,
"line_mean": 28.25,
"line_max": 70,
"alpha_frac": 0.6203703704,
"autogenerated": false,
"ratio": 3.9773371104815864,
"config_test": false,
"has_no_key... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from pyramid.settings import asbool
from .client import ElasticClient
__version__ = '0.3.2.dev'
def client_from_config(settings, prefix='elastic.'):
"""
Instantiate and configure an Elasticsearch fr... | {
"repo_name": "storborg/pyramid_es",
"path": "pyramid_es/__init__.py",
"copies": "1",
"size": "1488",
"license": "mit",
"hash": 105021976366827100,
"line_mean": 31.347826087,
"line_max": 79,
"alpha_frac": 0.6767473118,
"autogenerated": false,
"ratio": 4.076712328767123,
"config_test": false,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
from matplotlib.pyplot import FuncFormatter
dollar = lambda x, pos: '$%1.2f' % x
currency = dollar
comma = lambda x, pos: '{:0,d}'.format(int(x))
millions... | {
"repo_name": "bitemyapp/ggplot",
"path": "ggplot/scales/scale_y_continuous.py",
"copies": "12",
"size": "1202",
"license": "bsd-2-clause",
"hash": -2603605603936013000,
"line_mean": 30.6315789474,
"line_max": 66,
"alpha_frac": 0.578202995,
"autogenerated": false,
"ratio": 3.357541899441341,
"c... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
import brewer2mpl
def _number_to_palette(ctype, n):
n -= 1
palettes = sorted(brewer2mpl.COLOR_MAPS[ctype].keys())
if n < len(palettes):
re... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/scales/scale_color_brewer.py",
"copies": "1",
"size": "2321",
"license": "bsd-2-clause",
"hash": 4730006391397340000,
"line_mean": 28.3797468354,
"line_max": 78,
"alpha_frac": 0.5721671693,
"autogenerated": false,
"ratio": 3.5435114503816796,
"config... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
import matplotlib.pyplot as plt
from matplotlib.colors import LinearSegmentedColormap, rgb2hex, ColorConverter
def colors_at_breaks(cmap, breaks=[0, 0.25, 0.5... | {
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"path": "ggplot/scales/scale_color_gradient.py",
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"autogenerated": false,
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"config_t... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
CRAYON_COLORS = {
"red": "#ed0a3f",
"maroon": "#c32148",
"scarlet": "#fd0e35",
"brick red": "#c62d42",
"english vermilion": "#cc474b",
... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/scales/scale_color_crayon.py",
"copies": "1",
"size": "10469",
"license": "bsd-2-clause",
"hash": -7495222878609140000,
"line_mean": 28.9114285714,
"line_max": 107,
"alpha_frac": 0.5402617251,
"autogenerated": false,
"ratio": 2.5256936067551266,
"con... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
class scale_color_funfetti(scale):
"""
Make your plots look like funfetti
Parameters
----------
type: string
One of confetti or s... | {
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"path": "ggplot/scales/scale_color_funfetti.py",
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"autogenerated": false,
"ratio": 3.5885558583106265,
"config_test... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
class scale_color_manual(scale):
"""
Specify a list of colors to use manually.
Parameters
----------
values: list of colors/strings
... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/scales/scale_color_manual.py",
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"line_max": 101,
"alpha_frac": 0.5755297334,
"autogenerated": false,
"ratio": 3.713197969543147,
"config_test": ... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
class scale_colour_manual(scale):
"""
Specify a list of colors to use manually.
Parameters
----------
values : list of colors/strings... | {
"repo_name": "udacity/ggplot",
"path": "ggplot/scales/scale_colour_manual.py",
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"autogenerated": false,
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"config... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
class scale_fill_manual(scale):
"""
Specify a list of colors to use manually.
Parameters
----------
values: list of colors/strings
... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/scales/scale_fill_manual.py",
"copies": "1",
"size": "1446",
"license": "bsd-2-clause",
"hash": 7794467174568878000,
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"line_max": 101,
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"autogenerated": false,
"ratio": 3.6982097186700766,
"config... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from .scale import scale
from copy import deepcopy
class scale_y_log(scale):
"""
Make y axis log based
Parameters
----------
base:
log base to use (defaults to 10)
Examples
... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/scales/scale_log.py",
"copies": "1",
"size": "1190",
"license": "bsd-2-clause",
"hash": 4459924831120872000,
"line_mean": 22.3333333333,
"line_max": 88,
"alpha_frac": 0.5327731092,
"autogenerated": false,
"ratio": 3.278236914600551,
"config_test": fa... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from six import string_types
import numpy as np
import scipy.stats
import pandas as pd
from ggplot.utils import make_iterable_ntimes
from .stat import stat
def bootstrap_statistics(series, statistic, n_sampl... | {
"repo_name": "kmather73/ggplot",
"path": "ggplot/stats/stat_summary.py",
"copies": "12",
"size": "5323",
"license": "bsd-2-clause",
"hash": -7371929121938018000,
"line_mean": 29.9476744186,
"line_max": 125,
"alpha_frac": 0.5650948713,
"autogenerated": false,
"ratio": 3.472276581865623,
"config... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from sqlalchemy import MetaData, Table, Column, types, create_engine, select
from .base import BaseBackend
class SQLBackend(BaseBackend):
def __init__(self, url, table_name='gimlet_channels', **engine_kw... | {
"repo_name": "storborg/gimlet",
"path": "gimlet/backends/sql.py",
"copies": "1",
"size": "1568",
"license": "mit",
"hash": 8681673147649421000,
"line_mean": 40.2631578947,
"line_max": 77,
"alpha_frac": 0.5727040816,
"autogenerated": false,
"ratio": 4.126315789473685,
"config_test": false,
"h... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from unittest import TestCase
from ..dotdict import DotDict
class TestDotDict(TestCase):
def test_get(self):
dd = DotDict({'a': 42,
'b': 'hello'})
self.assertEqual(dd... | {
"repo_name": "storborg/pyramid_es",
"path": "pyramid_es/tests/test_dotdict.py",
"copies": "1",
"size": "1553",
"license": "mit",
"hash": 8909887035107215000,
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"line_max": 66,
"alpha_frac": 0.4365743722,
"autogenerated": false,
"ratio": 3.715311004784689,
"config_test... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from unittest import TestCase
from gimlet.backends.sql import SQLBackend
from gimlet.util import asbool, parse_settings
class TestUtil(TestCase):
def test_asbool_true(self):
for val in ('T', 'trU... | {
"repo_name": "storborg/gimlet",
"path": "gimlet/tests/test_util.py",
"copies": "1",
"size": "2125",
"license": "mit",
"hash": 3255154723701884000,
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"line_max": 75,
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"autogenerated": false,
"ratio": 4.009433962264151,
"config_test": true,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from unittest import TestCase
from ..mixin import ElasticMixin, ESMapping, ESString, ESProp
def rgb_to_hex(rgb):
return ('#' + ('%02x' * 3)) % rgb
class ESColor(ESProp):
def __init__(self, name, *ar... | {
"repo_name": "storborg/pyramid_es",
"path": "pyramid_es/tests/test_mixin.py",
"copies": "1",
"size": "3384",
"license": "mit",
"hash": 2345000204255967700,
"line_mean": 29.2142857143,
"line_max": 71,
"alpha_frac": 0.5345744681,
"autogenerated": false,
"ratio": 4.316326530612245,
"config_test":... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from unittest import TestCase
from webob import Request, Response
import webtest
from gimlet.factories import session_factory_factory
class TestSession(TestCase):
def _make_session(self, secret='secret... | {
"repo_name": "storborg/gimlet",
"path": "gimlet/tests/test_session.py",
"copies": "1",
"size": "6083",
"license": "mit",
"hash": -5396812966871902000,
"line_mean": 32.9832402235,
"line_max": 73,
"alpha_frac": 0.6072661516,
"autogenerated": false,
"ratio": 3.7712337259764412,
"config_test": tru... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
from ..utils import date_breaks, date_format
from .scale import scale
from copy import deepcopy
import six
class scale_x_date(scale):
"""
Position scale, date
Parameters
----------
breaks ... | {
"repo_name": "benslice/ggplot",
"path": "ggplot/scales/scale_x_date.py",
"copies": "12",
"size": "1687",
"license": "bsd-2-clause",
"hash": -1079421989471339500,
"line_mean": 34.1458333333,
"line_max": 66,
"alpha_frac": 0.5459395376,
"autogenerated": false,
"ratio": 3.740576496674058,
"config_... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
# geoms
from .geom_abline import geom_abline
from .geom_area import geom_area
from .geom_bar import geom_bar
from .geom_blank import geom_blank
from .geom_boxplot import geom_boxplot
from .geom_density import ge... | {
"repo_name": "andnovar/ggplot",
"path": "ggplot/geoms/__init__.py",
"copies": "12",
"size": "1672",
"license": "bsd-2-clause",
"hash": 6418944250273414000,
"line_mean": 39.7804878049,
"line_max": 91,
"alpha_frac": 0.6889952153,
"autogenerated": false,
"ratio": 3.2153846153846155,
"config_test"... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import binascii
from six.moves import cPickle as pickle
from struct import Struct
from itsdangerous import Serializer, URLSafeSerializerMixin
class CookieSerializer(Serializer):
packer = Struct(str('16s... | {
"repo_name": "storborg/gimlet",
"path": "gimlet/serializer.py",
"copies": "1",
"size": "1529",
"license": "mit",
"hash": -6069088264501437000,
"line_mean": 28.4038461538,
"line_max": 79,
"alpha_frac": 0.6376716808,
"autogenerated": false,
"ratio": 4.088235294117647,
"config_test": false,
"ha... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import binascii
class Crypter(object):
recommended = ("The recommended method for generating the key is "
"hexlify(os.urandom(32)).")
def __init__(self, key):
from Crypto.Ci... | {
"repo_name": "storborg/gimlet",
"path": "gimlet/crypto.py",
"copies": "1",
"size": "1153",
"license": "mit",
"hash": 895385405003146900,
"line_mean": 30.1621621622,
"line_max": 77,
"alpha_frac": 0.5715524718,
"autogenerated": false,
"ratio": 4.103202846975089,
"config_test": false,
"has_no_k... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import enum
import math
import numpy
import logging
try: # pragma: no cover
from collections import abc
except ImportError: # pragma: no cover
import collections as abc
from python_utils import logger... | {
"repo_name": "WoLpH/numpy-stl",
"path": "stl/base.py",
"copies": "1",
"size": "22070",
"license": "bsd-3-clause",
"hash": 6766210410140129000,
"line_mean": 32.5920852359,
"line_max": 80,
"alpha_frac": 0.5338921613,
"autogenerated": false,
"ratio": 3.296982372273678,
"config_test": false,
"ha... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import itertools
from weakref import ref
from matplotlib.externals import six
from datetime import datetime
import numpy as np
from numpy.testing.utils import (assert_array_equal, assert_approx_equal,
... | {
"repo_name": "zrhans/pythonanywhere",
"path": ".virtualenvs/django19/lib/python3.4/site-packages/matplotlib/tests/test_cbook.py",
"copies": "2",
"size": "12932",
"license": "apache-2.0",
"hash": 7866534601494931000,
"line_mean": 30.0119904077,
"line_max": 77,
"alpha_frac": 0.5653417878,
"autogener... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import itertools
import pickle
from weakref import ref
import warnings
import six
from datetime import datetime
import numpy as np
from numpy.testing.utils import (assert_array_equal, assert_approx_equal,
... | {
"repo_name": "louisLouL/pair_trading",
"path": "capstone_env/lib/python3.6/site-packages/matplotlib/tests/test_cbook.py",
"copies": "2",
"size": "17730",
"license": "mit",
"hash": -9085241931884394000,
"line_mean": 31.2363636364,
"line_max": 76,
"alpha_frac": 0.5490693739,
"autogenerated": false,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import logging
from datetime import datetime, timedelta
from formencode import Schema, NestedVariables, validators
from pyramid.view import view_config
from pyramid.httpexceptions import HTTPFound, HTTPBadReq... | {
"repo_name": "storborg/warpworks",
"path": "warpworks/views/auth.py",
"copies": "1",
"size": "7512",
"license": "mit",
"hash": -6939931899803676000,
"line_mean": 32.9909502262,
"line_max": 79,
"alpha_frac": 0.613684771,
"autogenerated": false,
"ratio": 4.258503401360544,
"config_test": true,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import logging
from itertools import chain
from pprint import pformat
from functools import wraps
import six
from elasticsearch import Elasticsearch
from elasticsearch.exceptions import NotFoundError
import ... | {
"repo_name": "storborg/pyramid_es",
"path": "pyramid_es/client.py",
"copies": "1",
"size": "12207",
"license": "mit",
"hash": 6016018524733611000,
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"line_max": 77,
"alpha_frac": 0.5360858524,
"autogenerated": false,
"ratio": 4.272663633181659,
"config_test": false,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import logging
import abc
import itertools
import os
import time
from binascii import hexlify
from datetime import datetime
from collections import MutableMapping
from itsdangerous import BadSignature
from .... | {
"repo_name": "storborg/gimlet",
"path": "gimlet/session.py",
"copies": "1",
"size": "10504",
"license": "mit",
"hash": -782994047468771200,
"line_mean": 31.4197530864,
"line_max": 79,
"alpha_frac": 0.5864432597,
"autogenerated": false,
"ratio": 4.262987012987013,
"config_test": false,
"has_n... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import logging
import copy
from functools import wraps
from collections import OrderedDict
import six
from .result import ElasticResult
log = logging.getLogger(__name__)
ARBITRARILY_LARGE_SIZE = 100000
de... | {
"repo_name": "storborg/pyramid_es",
"path": "pyramid_es/query.py",
"copies": "1",
"size": "8029",
"license": "mit",
"hash": -3244039409924313600,
"line_mean": 26.9756097561,
"line_max": 78,
"alpha_frac": 0.5166272263,
"autogenerated": false,
"ratio": 4.351761517615176,
"config_test": false,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import math
import pprint as pp
from collections import OrderedDict
from .utils import sorted_unique
class Facet(object):
def __init__(self, data, is_wrap, rowvar=None, colvar=None, nrow=None, ncol=None, s... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/facets.py",
"copies": "1",
"size": "5188",
"license": "bsd-2-clause",
"hash": -2323080095445705700,
"line_mean": 31.2236024845,
"line_max": 120,
"alpha_frac": 0.5381649961,
"autogenerated": false,
"ratio": 3.803519061583578,
"config_test": false,
"... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib as mpl
from cycler import cycler
from .theme import theme_base
class theme_gray(theme_base):
"""
Standard theme for ggplot. Gray background w/ white gridlines.
Copied from the the... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/themes/theme_gray.py",
"copies": "1",
"size": "4342",
"license": "bsd-2-clause",
"hash": -8330410893780642000,
"line_mean": 45.688172043,
"line_max": 100,
"alpha_frac": 0.5702441271,
"autogenerated": false,
"ratio": 3.4625199362041466,
"config_test":... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib as mpl
from .geom import geom
import numpy as np
class geom_point(geom):
DEFAULT_AES = {'alpha': 1, 'color': 'black', 'fill': None,
'shape': 'o', 'size': 20}
REQUIRE... | {
"repo_name": "bitemyapp/ggplot",
"path": "ggplot/geoms/geom_point.py",
"copies": "12",
"size": "1296",
"license": "bsd-2-clause",
"hash": 6871380385975002000,
"line_mean": 35,
"line_max": 81,
"alpha_frac": 0.5516975309,
"autogenerated": false,
"ratio": 3.5604395604395602,
"config_test": false,... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib as mpl
import matplotlib.pyplot as plt
from cycler import cycler
class theme(object):
def __init__(self):
self._rcParams = {}
def __radd__(self, other):
if other.__cla... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/themes/themes.py",
"copies": "1",
"size": "2119",
"license": "bsd-2-clause",
"hash": 7144213200170780000,
"line_mean": 29.2714285714,
"line_max": 78,
"alpha_frac": 0.5578102879,
"autogenerated": false,
"ratio": 4.082851637764932,
"config_test": false... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib as mpl
import matplotlib.pyplot as plt
from .theme import theme_base
class theme_xkcd(theme_base):
"""
xkcd theme
The theme internaly uses the settings from pyplot.xkcd().
""... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/themes/theme_xkcd.py",
"copies": "1",
"size": "1582",
"license": "bsd-2-clause",
"hash": -3912748430783926300,
"line_mean": 36.6666666667,
"line_max": 78,
"alpha_frac": 0.5676359039,
"autogenerated": false,
"ratio": 4.152230971128609,
"config_test": ... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.cbook as cbook
import numpy as np
import pandas as pd
import datetime
def format_ticks(ticks):
are_ints = True
for t in ticks:
try:
if int(t)!=t:
a... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/utils.py",
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"size": "2517",
"license": "bsd-2-clause",
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"line_max": 78,
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"autogenerated": false,
"ratio": 3.7069219440353463,
"config_test": false,
"h... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
from copy import deepcopy
from .geom import geom
import pandas as pd
import numpy as np
from ggplot.components import smoothers
class stat_smooth(geom):
VALID_AES = ['x', 'y'... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/stat_smooth.py",
"copies": "1",
"size": "1664",
"license": "bsd-2-clause",
"hash": -7774066151986999000,
"line_mean": 29.8148148148,
"line_max": 109,
"alpha_frac": 0.5030048077,
"autogenerated": false,
"ratio": 3.3821138211382116,
"config_tes... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
from .geom import geom
from scipy.stats import gaussian_kde
import numpy as np
class geom_density(geom):
VALID_AES = ['x', 'color', 'alpha', 'linestyle', 'fill', 'label']
... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/geom_density.py",
"copies": "1",
"size": "1348",
"license": "bsd-2-clause",
"hash": -4577069524395204000,
"line_mean": 32.7,
"line_max": 113,
"alpha_frac": 0.5252225519,
"autogenerated": false,
"ratio": 3.6630434782608696,
"config_test": fals... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
from itertools import groupby
from operator import itemgetter
from .geom import geom
class geom_step(geom):
VALID_AES = ['x', 'y', 'color', 'alpha', 'linestyle', 'label', 's... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/geom_step.py",
"copies": "1",
"size": "1362",
"license": "bsd-2-clause",
"hash": 7677359010303357000,
"line_mean": 33.9230769231,
"line_max": 108,
"alpha_frac": 0.5161527166,
"autogenerated": false,
"ratio": 3.396508728179551,
"config_test": ... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
from matplotlib.patches import Rectangle
import re
import six
def tex_escape(text):
"""
:param text: a plain text message
:return: the message escaped to appe... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/legend.py",
"copies": "1",
"size": "3072",
"license": "bsd-2-clause",
"hash": -5832804939356563000,
"line_mean": 34.3103448276,
"line_max": 126,
"alpha_frac": 0.5807291667,
"autogenerated": false,
"ratio": 3.479048697621744,
"config_test": false,
"... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
import matplotlib as mpl
from matplotlib.colors import Normalize
import numpy as np
from .geom import geom
import numpy as np
class geom_point(geom):
VALID_AES = ['x', 'y', '... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/geom_point.py",
"copies": "1",
"size": "1250",
"license": "bsd-2-clause",
"hash": 1238490531284855000,
"line_mean": 32.7837837838,
"line_max": 81,
"alpha_frac": 0.5632,
"autogenerated": false,
"ratio": 3.787878787878788,
"config_test": false,... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
import matplotlib as mpl
import numpy as np
import pandas as pd
from .geom import geom
class geom_text(geom):
VALID_AES = ['label','x','y','alpha','angle','color','family','f... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/geom_text.py",
"copies": "1",
"size": "2674",
"license": "bsd-2-clause",
"hash": 274904704060330850,
"line_mean": 30.8333333333,
"line_max": 77,
"alpha_frac": 0.5258040389,
"autogenerated": false,
"ratio": 3.82,
"config_test": false,
"has_n... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
from .geom import geom
import pandas as pd
import numpy as np
import scipy.stats as stats
class stat_function(geom):
"""
Superimpose a func... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/stat_function.py",
"copies": "1",
"size": "4266",
"license": "bsd-2-clause",
"hash": -6447286946856201000,
"line_mean": 29.9130434783,
"line_max": 85,
"alpha_frac": 0.5379746835,
"autogenerated": false,
"ratio": 3.5285359801488836,
"config_te... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
import numpy as np
import pandas as pd
from .geom import geom
from pandas.lib import Timestamp
class geom_bar(geom):
VALID_AES = ['x', 'color', 'alpha', 'fill', 'label', 'we... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/geom_bar.py",
"copies": "1",
"size": "2035",
"license": "bsd-2-clause",
"hash": -3544330590642899000,
"line_mean": 33.4915254237,
"line_max": 86,
"alpha_frac": 0.5228501229,
"autogenerated": false,
"ratio": 3.99803536345776,
"config_test": fa... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import matplotlib.pyplot as plt
import sys
from .geom import geom
class geom_histogram(geom):
VALID_AES = ['x', 'color', 'alpha', 'label', 'binwidth']
def __init__(self, *args, **kwargs):
... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/geoms/geom_histogram.py",
"copies": "1",
"size": "1251",
"license": "bsd-2-clause",
"hash": 5875014641859520000,
"line_mean": 35.7941176471,
"line_max": 79,
"alpha_frac": 0.5243804956,
"autogenerated": false,
"ratio": 3.984076433121019,
"config_tes... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from .geom import geom
class geom_text(geom):
DEFAULT_AES = {'alpha': None, 'angle': 0, 'color': 'black', 'family': None,
'fontface': 1, 'hjust': None, 'size': 12, 'vju... | {
"repo_name": "Cophy08/ggplot",
"path": "ggplot/geoms/geom_text.py",
"copies": "12",
"size": "2616",
"license": "bsd-2-clause",
"hash": -655024807016559400,
"line_mean": 33.88,
"line_max": 81,
"alpha_frac": 0.5244648318,
"autogenerated": false,
"ratio": 3.5737704918032787,
"config_test": false,... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from ._overlap import _compute_overlap
__all__ = ['compute_overlap']
def compute_overlap(ilon, ilat, olon, olat):
"""Compute the overlap between two 'pixels' in spherical coordinates.
... | {
"repo_name": "bsipocz/reproject",
"path": "reproject/spherical_intersect/overlap.py",
"copies": "1",
"size": "1255",
"license": "bsd-2-clause",
"hash": -1962850640461981000,
"line_mean": 34.8571428571,
"line_max": 81,
"alpha_frac": 0.6501992032,
"autogenerated": false,
"ratio": 3.702064896755162... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
from pandas.lib import Timestamp
import pandas as pd
import statsmodels.api as sm
from statsmodels.nonparametric.smoothers_lowess import lowess as smlowess
from statsmodels.sandbox.regression.... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/stats/smoothers.py",
"copies": "1",
"size": "2981",
"license": "bsd-2-clause",
"hash": 42093328699704510,
"line_mean": 31.7582417582,
"line_max": 75,
"alpha_frac": 0.6340154311,
"autogenerated": false,
"ratio": 2.9573412698412698,
"config_test": fals... |
from __future__ import absolute_import, division, print_function, \
unicode_literals
import numpy as np
from sklearn.preprocessing import LabelEncoder
def binary_ks_curve(y_true, y_probas):
"""This function generates the points necessary to calculate the KS
Statistic curve.
Args:
y_true (arra... | {
"repo_name": "reiinakano/scikit-plot",
"path": "scikitplot/helpers.py",
"copies": "1",
"size": "7732",
"license": "mit",
"hash": -1560035604005248500,
"line_mean": 35.3004694836,
"line_max": 79,
"alpha_frac": 0.6060527677,
"autogenerated": false,
"ratio": 3.738878143133462,
"config_test": fals... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import math
def drange(start, stop, step):
"""Compute the steps in between start and stop
Only steps which are a multiple of `step` are used.
"""
r = ((start // step) * step... | {
"repo_name": "assad2012/ggplot",
"path": "ggplot/scales/utils.py",
"copies": "12",
"size": "1733",
"license": "bsd-2-clause",
"hash": -5200086375520864000,
"line_mean": 26.078125,
"line_max": 74,
"alpha_frac": 0.5937680323,
"autogenerated": false,
"ratio": 3.695095948827292,
"config_test": fal... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pandas as pd
from scipy.stats import gaussian_kde
from ggplot.utils import make_iterable_ntimes
from ggplot.utils.exceptions import GgplotError
from .stat import stat
# TODO: switch t... | {
"repo_name": "wllmtrng/ggplot",
"path": "ggplot/stats/stat_density.py",
"copies": "12",
"size": "1690",
"license": "bsd-2-clause",
"hash": 2230873071767475000,
"line_mean": 30.8867924528,
"line_max": 74,
"alpha_frac": 0.549112426,
"autogenerated": false,
"ratio": 3.7555555555555555,
"config_te... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pandas as pd
import matplotlib.cbook as cbook
from .geom import geom
from ggplot.utils import is_string
from ggplot.utils import is_categorical
class geom_bar(geom):
DEFAULT_AES ... | {
"repo_name": "benslice/ggplot",
"path": "ggplot/geoms/geom_bar.py",
"copies": "11",
"size": "3061",
"license": "bsd-2-clause",
"hash": 7263265846881768000,
"line_mean": 35.4404761905,
"line_max": 95,
"alpha_frac": 0.5619078732,
"autogenerated": false,
"ratio": 3.7466340269277847,
"config_test"... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pandas as pd
import matplotlib.pyplot as plt
import matplotlib.cbook as cbook
from .geom import geom
from ggplot.utils import is_string
from ggplot.utils import is_categorical
class g... | {
"repo_name": "wllmtrng/ggplot",
"path": "ggplot/geoms/geom_boxplot.py",
"copies": "12",
"size": "1218",
"license": "bsd-2-clause",
"hash": 3821423309244489700,
"line_mean": 28.7073170732,
"line_max": 68,
"alpha_frac": 0.5599343186,
"autogenerated": false,
"ratio": 3.2830188679245285,
"config_t... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pandas as pd
from ggplot.components import smoothers
from ggplot.utils import make_iterable_ntimes
from .stat import stat
class stat_smooth(stat):
REQUIRED_AES = {'x', 'y'}
D... | {
"repo_name": "andnovar/ggplot",
"path": "ggplot/stats/stat_smooth.py",
"copies": "12",
"size": "1774",
"license": "bsd-2-clause",
"hash": 2883677740331013600,
"line_mean": 31.8518518519,
"line_max": 81,
"alpha_frac": 0.5394588501,
"autogenerated": false,
"ratio": 3.4115384615384614,
"config_te... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import pandas as pd
from ggplot.utils import make_iterable_ntimes
from ggplot.utils.exceptions import GgplotError
from .stat import stat
class stat_function(stat):
"""
Superimpose a... | {
"repo_name": "mizzao/ggplot",
"path": "ggplot/stats/stat_function.py",
"copies": "12",
"size": "4439",
"license": "bsd-2-clause",
"hash": -3369415084848312000,
"line_mean": 28.7919463087,
"line_max": 85,
"alpha_frac": 0.548772246,
"autogenerated": false,
"ratio": 3.5512,
"config_test": false,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import scipy
import scipy.stats
# BCES fitting
# ===============
def bces(y1,y1err,y2,y2err,cerr):
"""
Does the entire regression calculation for 4 slopes:
OLS(Y|X), OLS(X|Y), bisector, ... | {
"repo_name": "rsnemmen/BCES",
"path": "bces/bces.py",
"copies": "1",
"size": "10452",
"license": "mit",
"hash": -8815893280019946000,
"line_mean": 29.2080924855,
"line_max": 180,
"alpha_frac": 0.6557596632,
"autogenerated": false,
"ratio": 2.588410104011887,
"config_test": false,
"has_no_key... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import numpy as np
import six
SHAPES = [
'o',#circle
'^',#triangle up
'D',#diamond
'v',#triangle down
'+',#plus
'x',#x
's',#square
'*',#star
'p',#pentagon
'*'#octagon
]
... | {
"repo_name": "eco32i/ggplot",
"path": "ggplot/components/shapes.py",
"copies": "1",
"size": "1379",
"license": "bsd-2-clause",
"hash": 9215212319028130000,
"line_mean": 26.0392156863,
"line_max": 90,
"alpha_frac": 0.5910079768,
"autogenerated": false,
"ratio": 3.757493188010899,
"config_test":... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import functools
import json
from json import encoder
encoder.FLOAT_REPR = lambda o: format(o, '.8f')
from glob import glob
import numpy as np
from astroquery.simbad import Simbad
from astropy.table i... | {
"repo_name": "bmorris3/boyajian_star_arces",
"path": "toolkit/utils.py",
"copies": "1",
"size": "5065",
"license": "mit",
"hash": -3571135596646832600,
"line_mean": 26.8296703297,
"line_max": 86,
"alpha_frac": 0.5855873643,
"autogenerated": false,
"ratio": 3.5394828791055204,
"config_test": fa... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import hashlib
from datetime import timedelta
from cryptacular.bcrypt import BCRYPTPasswordManager
from sqlalchemy import Column, types
from . import utils
from .base import Base
from .image import ... | {
"repo_name": "storborg/warpworks",
"path": "warpworks/model/user.py",
"copies": "1",
"size": "4070",
"license": "mit",
"hash": -2779442904341444600,
"line_mean": 32.6363636364,
"line_max": 79,
"alpha_frac": 0.6253071253,
"autogenerated": false,
"ratio": 4.348290598290598,
"config_test": false,... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import shutil
import subprocess
import sys
import tempfile
from distutils.core import Command
from .compat import _fix_user_options
PY3 = sys.version_info[0] == 3
class AstropyTest(Command, objec... | {
"repo_name": "eteq/astropy-helpers",
"path": "astropy_helpers/test_helpers.py",
"copies": "1",
"size": "8430",
"license": "bsd-3-clause",
"hash": 57216073260580950,
"line_mean": 40.3235294118,
"line_max": 83,
"alpha_frac": 0.534282325,
"autogenerated": false,
"ratio": 4.329738058551618,
"confi... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import sys
import logging
from astropy.io.fits.verify import VerifyError
from ccdproc import ImageFileCollection
from ..core import fix_keywords, identify_technique
class DataClassifier(object):
... | {
"repo_name": "soar-telescope/goodman",
"path": "goodman_pipeline/images/data_classifier.py",
"copies": "1",
"size": "6230",
"license": "bsd-3-clause",
"hash": 8230829663941967000,
"line_mean": 36.987804878,
"line_max": 85,
"alpha_frac": 0.5817014446,
"autogenerated": false,
"ratio": 4.3324061196... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import time
import sys
import desitarget.io
import astropy.io.fits as fits
import numpy as np
from astropy.table import Table
############################################################
def sweep_m... | {
"repo_name": "apcooper/bright_analysis",
"path": "py/bright_analysis/sweeps/io.py",
"copies": "1",
"size": "5761",
"license": "bsd-3-clause",
"hash": -8862720921649169000,
"line_mean": 38.4589041096,
"line_max": 89,
"alpha_frac": 0.5768095817,
"autogenerated": false,
"ratio": 4.03149055283415,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import time
import sys
import healpy as hp
import desiutil.plots as desiplot
import desitarget.io
import astropy.io.fits as fits
import numpy as np
import matplotlib.pyplot as pl
from astropy.table i... | {
"repo_name": "apcooper/bright_analysis",
"path": "py/bright_analysis/plots/distance.py",
"copies": "1",
"size": "15941",
"license": "bsd-3-clause",
"hash": 5249013871630803000,
"line_mean": 36.3325526932,
"line_max": 113,
"alpha_frac": 0.5477699015,
"autogenerated": false,
"ratio": 2.99080675422... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os
import numpy as np
import kplr
from astropy.io import ascii
import h5py
from astropy.utils.console import ProgressBar
from astropy.utils.data import download_file
from astropy.table import Column, uni... | {
"repo_name": "bmorris3/salter",
"path": "salter/cache.py",
"copies": "1",
"size": "5676",
"license": "mit",
"hash": 3054766055242547700,
"line_mean": 31.8092485549,
"line_max": 104,
"alpha_frac": 0.5856236786,
"autogenerated": false,
"ratio": 3.5833333333333335,
"config_test": false,
"has_no... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import os.path
import sys
import transaction
from sqlalchemy import engine_from_config
from pyramid.paster import get_appsettings, setup_logging
from .. import model
def usage(argv):
cmd = os.path.basen... | {
"repo_name": "storborg/warpworks",
"path": "warpworks/scripts/initializedb.py",
"copies": "1",
"size": "1033",
"license": "mit",
"hash": 1671557267108904000,
"line_mean": 25.4871794872,
"line_max": 66,
"alpha_frac": 0.6437560503,
"autogenerated": false,
"ratio": 3.5016949152542374,
"config_tes... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import pandas as pd
import numpy as np
from .geom import geom
from matplotlib.patches import Rectangle
import matplotlib.colors as colors
import matplotlib.colorbar as colorbar
class geom_tile(geom):
DEFAU... | {
"repo_name": "udacity/ggplot",
"path": "ggplot/geoms/geom_tile.py",
"copies": "12",
"size": "3695",
"license": "bsd-2-clause",
"hash": -2008258174221249000,
"line_mean": 36.3232323232,
"line_max": 123,
"alpha_frac": 0.5548037889,
"autogenerated": false,
"ratio": 3.6620416253716552,
"config_tes... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import pandas as pd
import os
import sys
_ROOT = os.path.abspath(os.path.dirname(__file__))
diamonds = pd.read_csv(os.path.join(_ROOT, "diamonds.csv"))
mtcars = pd.read_csv(os.path.join(_ROOT, "mtcars.csv"))
m... | {
"repo_name": "yhat/ggplot",
"path": "ggplot/datasets/__init__.py",
"copies": "1",
"size": "2552",
"license": "bsd-2-clause",
"hash": 8496658385016726000,
"line_mean": 40.8360655738,
"line_max": 83,
"alpha_frac": 0.6195141066,
"autogenerated": false,
"ratio": 2.6694560669456067,
"config_test": ... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import pandas as pd
from ggplot.utils import pop, make_iterable, make_iterable_ntimes
from ggplot.utils.exceptions import GgplotError
from .stat import stat
class stat_hline(stat):
DEFAULT_PARAMS = {'geom... | {
"repo_name": "andnovar/ggplot",
"path": "ggplot/stats/stat_hline.py",
"copies": "12",
"size": "1317",
"license": "bsd-2-clause",
"hash": -8487484122100909000,
"line_mean": 33.6578947368,
"line_max": 71,
"alpha_frac": 0.5854214123,
"autogenerated": false,
"ratio": 3.9788519637462234,
"config_te... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import pandas as pd
from .stat import stat
_MSG_LABELS = """There are more than 30 unique values mapped to x.
If you want a histogram instead, use 'geom_histogram()'.
"""
class stat_bar(stat):
REQUIRE... | {
"repo_name": "benslice/ggplot",
"path": "ggplot/stats/stat_bar.py",
"copies": "12",
"size": "1322",
"license": "bsd-2-clause",
"hash": -834347888771891300,
"line_mean": 32.8974358974,
"line_max": 68,
"alpha_frac": 0.5514372163,
"autogenerated": false,
"ratio": 3.911242603550296,
"config_test":... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from .legend import get_labels
SHAPES = [
'o',#circle
'^',#triangle up
'D',#diamond
'v',#triangle down
'+',#plus
'x',#x
's',#square
'*',#star
'p',#pentagon
'*... | {
"repo_name": "smblance/ggplot",
"path": "ggplot/components/shapes.py",
"copies": "12",
"size": "1576",
"license": "bsd-2-clause",
"hash": 3400730599622733300,
"line_mean": 26.649122807,
"line_max": 90,
"alpha_frac": 0.5742385787,
"autogenerated": false,
"ratio": 3.8627450980392157,
"config_tes... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six import with_metaclass
import numpy as np
import itertools
from slicerator import Slicerator, propagate_attr, index_attr
from .frame import Frame
from abc import ABCMeta, abstractmethod, abstr... | {
"repo_name": "tacaswell/pims",
"path": "pims/base_frames.py",
"copies": "1",
"size": "23446",
"license": "bsd-3-clause",
"hash": 2786667478823571500,
"line_mean": 35.4634525661,
"line_max": 82,
"alpha_frac": 0.5706730359,
"autogenerated": false,
"ratio": 4.092511782160936,
"config_test": false... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from six.moves import zip, range
from copy import copy
import itertools
import functools
from collections import deque
import numpy as np
from scipy.spatial import cKDTree
import pandas as pd
from .... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/linking.py",
"copies": "1",
"size": "60720",
"license": "bsd-3-clause",
"hash": -6796835265020981000,
"line_mean": 38.4798439532,
"line_max": 108,
"alpha_frac": 0.5808465086,
"autogenerated": false,
"ratio": 4.184700206753963,
"config_test": ... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import collections
import functools
import re
import sys
import warnings
from datetime import datetime, timedelta
import pandas as pd
import numpy as np
from scipy import stats
import yaml
def fit_... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/utils.py",
"copies": "1",
"size": "6527",
"license": "bsd-3-clause",
"hash": -3926802136164843500,
"line_mean": 30.080952381,
"line_max": 91,
"alpha_frac": 0.6284663705,
"autogenerated": false,
"ratio": 3.683408577878104,
"config_test": false... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import datetime
import logging
import uuid
from functools import wraps
from mongoengine import connect
#from metadatastore.document import Document
#from metadatastore.commands import (db_connect, db... | {
"repo_name": "cowanml/samplemanager",
"path": "src/samplemanager/db_init.py",
"copies": "1",
"size": "1492",
"license": "bsd-3-clause",
"hash": 9182782875502606000,
"line_mean": 30.0833333333,
"line_max": 95,
"alpha_frac": 0.686997319,
"autogenerated": false,
"ratio": 3.845360824742268,
"confi... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import functools
import unittest
import nose
import warnings
import os
import numpy as np
from numpy.testing import assert_almost_equal, assert_allclose
from numpy.testing.decorators import slow
impo... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/tests/test_feature_saving.py",
"copies": "2",
"size": "6019",
"license": "bsd-3-clause",
"hash": -7410639883974791000,
"line_mean": 33.0056497175,
"line_max": 89,
"alpha_frac": 0.5919587971,
"autogenerated": false,
"ratio": 3.8143219264892267,
... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import logging
from contextlib import contextmanager
from .fs import FileStore
from .conf import connection_config
from .core import DatumNotFound
logger = logging.getLogger(__name__)
_FS_SINGLETO... | {
"repo_name": "stuwilkins/filestore",
"path": "filestore/api.py",
"copies": "1",
"size": "5432",
"license": "bsd-3-clause",
"hash": -1480551365377988900,
"line_mean": 25.1153846154,
"line_max": 79,
"alpha_frac": 0.6491163476,
"autogenerated": false,
"ratio": 4.398380566801619,
"config_test": fa... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from scipy.ndimage.filters import uniform_filter1d
from scipy.ndimage.fourier import fourier_gaussian
from .utils import print_update, validate_tuple
# When loading module, try t... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/preprocessing.py",
"copies": "1",
"size": "3100",
"license": "bsd-3-clause",
"hash": 5275641183007240000,
"line_mean": 33.8314606742,
"line_max": 78,
"alpha_frac": 0.6432258065,
"autogenerated": false,
"ratio": 3.6904761904761907,
"config_tes... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from scipy.ndimage import morphology
from pandas import DataFrame
from .preprocessing import bandpass
from .masks import binary_mask, x_squared_masks
from .utils import memo, valid... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/uncertainty.py",
"copies": "1",
"size": "4763",
"license": "bsd-3-clause",
"hash": 4732848947774414000,
"line_mean": 37.104,
"line_max": 79,
"alpha_frac": 0.6605080831,
"autogenerated": false,
"ratio": 3.920164609053498,
"config_test": false,... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from scipy.spatial import cKDTree
from trackpy.utils import validate_tuple
def draw_point(image, pos, value):
image[tuple(pos)] = value
def feat_gauss(r, rg=0.333):
""" ... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/artificial.py",
"copies": "2",
"size": "7155",
"license": "bsd-3-clause",
"hash": 8591313168840874000,
"line_mean": 38.0983606557,
"line_max": 79,
"alpha_frac": 0.6359189378,
"autogenerated": false,
"ratio": 3.67299794661191,
"config_test": f... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from .try_numba import try_numba_autojit
@try_numba_autojit(nopython=True)
def _numba_refine_2D(raw_image, image, radiusY, radiusX, coords, N,
max_iterations,... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/feature_numba.py",
"copies": "1",
"size": "22424",
"license": "bsd-3-clause",
"hash": -4317465159195806700,
"line_mean": 35.284789644,
"line_max": 88,
"alpha_frac": 0.45932929,
"autogenerated": false,
"ratio": 3.699719518231315,
"config_test"... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from .utils import memo, validate_tuple
__all__ = ['binary_mask', 'r_squared_mask', 'cosmask', 'sinmask',
'theta_mask']
@memo
def binary_mask(radius, ndim):
"Ellip... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/masks.py",
"copies": "1",
"size": "2735",
"license": "bsd-3-clause",
"hash": -8286278224110137000,
"line_mean": 30.4367816092,
"line_max": 79,
"alpha_frac": 0.6449725777,
"autogenerated": false,
"ratio": 3.4059775840597757,
"config_test": fal... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
from .utils import validate_tuple
def get_slice(coords, shape, radius):
"""Returns the slice and origin that belong to ``slice_image``"""
# interpret parameters
ndim =... | {
"repo_name": "caspervdw/circletracking",
"path": "circletracking/masks.py",
"copies": "1",
"size": "3673",
"license": "bsd-3-clause",
"hash": -8459566437243349000,
"line_mean": 33.980952381,
"line_max": 80,
"alpha_frac": 0.6210182412,
"autogenerated": false,
"ratio": 3.882663847780127,
"config... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import matplotlib as mpl
import matplotlib.pyplot as plt
import matplotlib.gridspec as gridspec
from .utils import validate_tuple, guess_pos_columns
from functools import wraps
de... | {
"repo_name": "caspervdw/circletracking",
"path": "circletracking/plot.py",
"copies": "1",
"size": "14778",
"license": "bsd-3-clause",
"hash": -6016786950707281000,
"line_mean": 33.2083333333,
"line_max": 82,
"alpha_frac": 0.5576532684,
"autogenerated": false,
"ratio": 3.0382401315789473,
"conf... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import numpy as np
import pandas as pd
from pandas import DataFrame, Series
from scipy.spatial import cKDTree
def msd(traj, mpp, fps, max_lagtime=100, detail=False, pos_columns=['x', 'y']):
"""Co... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/motion.py",
"copies": "1",
"size": "16740",
"license": "bsd-3-clause",
"hash": 629275954714549200,
"line_mean": 32.75,
"line_max": 87,
"alpha_frac": 0.6287335723,
"autogenerated": false,
"ratio": 3.628874918707999,
"config_test": false,
"ha... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import os
from abc import ABCMeta, abstractmethod, abstractproperty
import warnings
import pandas as pd
from .utils import print_update
class FramewiseData(object):
"Abstract base class defini... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/framewise_data.py",
"copies": "1",
"size": "10185",
"license": "bsd-3-clause",
"hash": -527852623594377700,
"line_mean": 30.0518292683,
"line_max": 84,
"alpha_frac": 0.5862542955,
"autogenerated": false,
"ratio": 4.064245810055866,
"config_te... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import sys
import datetime
from .. import QtCore, QtGui
from xray_vision.qt_widgets.displaydict import RecursiveTreeWidget
from collections import defaultdict
from .control_widgets import DateTimeBox,... | {
"repo_name": "ericdill/xray-vision",
"path": "xray_vision/qt_widgets/query_widget.py",
"copies": "6",
"size": "18742",
"license": "bsd-3-clause",
"hash": 3032589046550332000,
"line_mean": 33.0145190563,
"line_max": 80,
"alpha_frac": 0.5754455234,
"autogenerated": false,
"ratio": 4.61511942871213... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import sys
import importlib
from collections import OrderedDict
from . import try_numba
from . import preprocessing
def performance_report():
"""Display summary of which optional speedups are i... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/diag.py",
"copies": "1",
"size": "1858",
"license": "bsd-3-clause",
"hash": -2284602226967704600,
"line_mean": 32.1785714286,
"line_max": 77,
"alpha_frac": 0.6119483315,
"autogenerated": false,
"ratio": 4.4556354916067145,
"config_test": fals... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import unittest
import nose
import numpy as np
import pandas as pd
from numpy.testing import assert_allclose
from pandas import DataFrame, Series
import trackpy as tp
# Catch attempts to set values... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/tests/test_correlations.py",
"copies": "2",
"size": "1278",
"license": "bsd-3-clause",
"hash": 1775464732556269300,
"line_mean": 30.1707317073,
"line_max": 75,
"alpha_frac": 0.5938967136,
"autogenerated": false,
"ratio": 3.372031662269129,
"c... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import unittest
import nose
import numpy as np
import pandas as pd
from pandas import DataFrame, Series
from numpy.testing import assert_almost_equal, assert_allclose
from numpy.testing.decorators im... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/tests/test_motion.py",
"copies": "1",
"size": "6826",
"license": "bsd-3-clause",
"hash": 5962750244945369000,
"line_mean": 38.4566473988,
"line_max": 77,
"alpha_frac": 0.5627014357,
"autogenerated": false,
"ratio": 3.3658777120315584,
"config... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import warnings
import numpy as np
import pandas as pd
from scipy import ndimage
from scipy.spatial import cKDTree
from pandas import DataFrame
from .preprocessing import bandpass, scale_to_gamut, s... | {
"repo_name": "daniorerio/trackpy",
"path": "trackpy/feature.py",
"copies": "1",
"size": "32400",
"license": "bsd-3-clause",
"hash": -4641691812612571000,
"line_mean": 43.2019099591,
"line_max": 84,
"alpha_frac": 0.6044135802,
"autogenerated": false,
"ratio": 3.983769826632239,
"config_test": f... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
from matplotlib import docstring
from matplotlib.offsetbox import (AnchoredOffsetbox, AuxTransformBox,
DrawingArea, TextArea, VPacker)
from matplotlib.patches import... | {
"repo_name": "louisLouL/pair_trading",
"path": "capstone_env/lib/python3.6/site-packages/mpl_toolkits/axes_grid1/anchored_artists.py",
"copies": "2",
"size": "13214",
"license": "mit",
"hash": 3850674713766062000,
"line_mean": 34.1436170213,
"line_max": 78,
"alpha_frac": 0.5423792947,
"autogenerat... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import functools
import os
import re
import signal
import sys
from six import unichr
import matplotlib
from matplotlib._pylab_helpers import Gcf
from matplotlib.backend_bases import (
_Backend,... | {
"repo_name": "louisLouL/pair_trading",
"path": "capstone_env/lib/python3.6/site-packages/matplotlib/backends/backend_qt5.py",
"copies": "2",
"size": "31226",
"license": "mit",
"hash": 5466092491139902000,
"line_mean": 35.2250580046,
"line_max": 79,
"alpha_frac": 0.5811503234,
"autogenerated": fals... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import logging
import h5py
import numpy as np
import os.path
import pims
from .handlers_base import HandlerBase
from .readers.spe import PrincetonSPEFile
logger = logging.getLogger(__name__)
clas... | {
"repo_name": "danielballan/filestore",
"path": "filestore/handlers.py",
"copies": "1",
"size": "7964",
"license": "bsd-3-clause",
"hash": 701646722810085000,
"line_mean": 27.8550724638,
"line_max": 79,
"alpha_frac": 0.5777247614,
"autogenerated": false,
"ratio": 4.002010050251256,
"config_test... |
from __future__ import (absolute_import, division, print_function,
unicode_literals)
import six
import logging
import h5py
import numpy as np
import os.path
import tifffile
from .handlers_base import HandlerBase
from .readers.spe import PrincetonSPEFile
logger = logging.getLogger(__name__)
f... | {
"repo_name": "tacaswell/filestore",
"path": "filestore/handlers.py",
"copies": "2",
"size": "12679",
"license": "bsd-3-clause",
"hash": 2242047748813485600,
"line_mean": 27.9474885845,
"line_max": 78,
"alpha_frac": 0.5855351368,
"autogenerated": false,
"ratio": 3.964665415884928,
"config_test"... |
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