This file is indexed.

/usr/share/pyshared/pandas/util/testing.py is in python-pandas 0.7.0-1.

This file is owned by root:root, with mode 0o644.

The actual contents of the file can be viewed below.

  1
  2
  3
  4
  5
  6
  7
  8
  9
 10
 11
 12
 13
 14
 15
 16
 17
 18
 19
 20
 21
 22
 23
 24
 25
 26
 27
 28
 29
 30
 31
 32
 33
 34
 35
 36
 37
 38
 39
 40
 41
 42
 43
 44
 45
 46
 47
 48
 49
 50
 51
 52
 53
 54
 55
 56
 57
 58
 59
 60
 61
 62
 63
 64
 65
 66
 67
 68
 69
 70
 71
 72
 73
 74
 75
 76
 77
 78
 79
 80
 81
 82
 83
 84
 85
 86
 87
 88
 89
 90
 91
 92
 93
 94
 95
 96
 97
 98
 99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
127
128
129
130
131
132
133
134
135
136
137
138
139
140
141
142
143
144
145
146
147
148
149
150
151
152
153
154
155
156
157
158
159
160
161
162
163
164
165
166
167
168
169
170
171
172
173
174
175
176
177
178
179
180
181
182
183
184
185
186
187
188
189
190
191
192
193
194
195
196
197
198
199
200
201
202
203
204
205
206
207
208
209
210
211
212
213
214
215
216
217
218
219
220
221
222
223
224
225
226
227
228
229
230
231
232
233
234
235
236
237
238
239
240
241
242
243
244
245
246
247
248
249
250
251
252
253
254
255
256
257
258
259
260
261
262
263
264
265
266
267
268
269
270
271
272
273
274
275
276
277
278
279
280
281
282
283
284
285
286
287
288
289
290
291
292
from __future__ import division

# pylint: disable-msg=W0402

from datetime import datetime
import random
import string
import sys

from distutils.version import LooseVersion

from numpy.random import randn
import numpy as np

from pandas.core.common import isnull
import pandas.core.index as index
import pandas.core.daterange as daterange
import pandas.core.series as series
import pandas.core.frame as frame
import pandas.core.panel as panel

# to_reload = ['index', 'daterange', 'series', 'frame', 'matrix', 'panel']
# for mod in to_reload:
#     reload(locals()[mod])

DateRange = daterange.DateRange
Index = index.Index
Series = series.Series
DataFrame = frame.DataFrame
Panel = panel.Panel

N = 30
K = 4

def rands(n):
    choices = string.ascii_letters + string.digits
    return ''.join([random.choice(choices) for _ in xrange(n)])

#-------------------------------------------------------------------------------
# Console debugging tools

def debug(f, *args, **kwargs):
    from pdb import Pdb as OldPdb
    try:
        from IPython.core.debugger import Pdb
        kw = dict(color_scheme='Linux')
    except ImportError:
        Pdb = OldPdb
        kw = {}
    pdb = Pdb(**kw)
    return pdb.runcall(f, *args, **kwargs)

def set_trace():
    from IPython.core.debugger import Pdb
    try:
        Pdb(color_scheme='Linux').set_trace(sys._getframe().f_back)
    except:
        from pdb import Pdb as OldPdb
        OldPdb().set_trace(sys._getframe().f_back)

#-------------------------------------------------------------------------------
# Comparators

def equalContents(arr1, arr2):
    """Checks if the set of unique elements of arr1 and arr2 are equivalent.
    """
    return frozenset(arr1) == frozenset(arr2)

def isiterable(obj):
    return hasattr(obj, '__iter__')

def assert_almost_equal(a, b):
    if isinstance(a, dict) or isinstance(b, dict):
        return assert_dict_equal(a, b)

    if isinstance(a, basestring):
        assert a == b, (a, b)
        return True

    if isiterable(a):
        np.testing.assert_(isiterable(b))
        np.testing.assert_equal(len(a), len(b))
        if np.array_equal(a, b):
            return True
        else:
            for i in xrange(len(a)):
                assert_almost_equal(a[i], b[i])
        return True

    err_msg = lambda a, b: 'expected %.5f but got %.5f' % (a, b)

    if isnull(a):
        np.testing.assert_(isnull(b))
        return

    if isinstance(a, (bool, float, int)):
        # case for zero
        if abs(a) < 1e-5:
            np.testing.assert_almost_equal(
                a, b, decimal=5, err_msg=err_msg(a, b), verbose=False)
        else:
            np.testing.assert_almost_equal(
                1, a/b, decimal=5, err_msg=err_msg(a, b), verbose=False)
    else:
        assert(a == b)

def is_sorted(seq):
    return assert_almost_equal(seq, np.sort(np.array(seq)))

def assert_dict_equal(a, b, compare_keys=True):
    a_keys = frozenset(a.keys())
    b_keys = frozenset(b.keys())

    if compare_keys:
        assert(a_keys == b_keys)

    for k in a_keys:
        assert_almost_equal(a[k], b[k])

def assert_series_equal(left, right, check_dtype=True):
    assert_almost_equal(left.values, right.values)
    if check_dtype:
        assert(left.dtype == right.dtype)
    assert(left.index.equals(right.index))

def assert_frame_equal(left, right):
    assert(isinstance(left, DataFrame))
    assert(isinstance(right, DataFrame))
    for col, series in left.iterkv():
        assert(col in right)
        assert_series_equal(series, right[col])
    for col in right:
        assert(col in left)
    assert(left.index.equals(right.index))
    assert(left.columns.equals(right.columns))

def assert_panel_equal(left, right):
    assert(left.items.equals(right.items))
    assert(left.major_axis.equals(right.major_axis))
    assert(left.minor_axis.equals(right.minor_axis))

    for col, series in left.iterkv():
        assert(col in right)
        assert_frame_equal(series, right[col])

    for col in right:
        assert(col in left)

def assert_contains_all(iterable, dic):
    for k in iterable:
        assert(k in dic)

def getCols(k):
    return string.ascii_uppercase[:k]

def makeStringIndex(k):
    return Index([rands(10) for _ in xrange(k)])

def makeIntIndex(k):
    return Index(range(k))

def makeDateIndex(k):
    dates = list(DateRange(datetime(2000, 1, 1), periods=k))
    return Index(dates)

def makeFloatSeries():
    index = makeStringIndex(N)
    return Series(randn(N), index=index)

def makeStringSeries():
    index = makeStringIndex(N)
    return Series(randn(N), index=index)

def makeObjectSeries():
    dateIndex = makeDateIndex(N)
    index = makeStringIndex(N)
    return Series(dateIndex, index=index)

def makeTimeSeries():
    return Series(randn(N), index=makeDateIndex(N))

def getArangeMat():
    return np.arange(N * K).reshape((N, K))

def getSeriesData():
    index = makeStringIndex(N)

    return dict((c, Series(randn(N), index=index)) for c in getCols(K))

def getTimeSeriesData():
    return dict((c, makeTimeSeries()) for c in getCols(K))

def getMixedTypeDict():
    index = Index(['a', 'b', 'c', 'd', 'e'])

    data = {
        'A' : [0., 1., 2., 3., 4.],
        'B' : [0., 1., 0., 1., 0.],
        'C' : ['foo1', 'foo2', 'foo3', 'foo4', 'foo5'],
        'D' : DateRange('1/1/2009', periods=5)
    }

    return index, data

def makeDataFrame():
    data = getSeriesData()
    return DataFrame(data)

def makeTimeDataFrame():
    data = getTimeSeriesData()
    return DataFrame(data)

def makePanel():
    cols = ['Item' + c for c in string.ascii_uppercase[:K - 1]]
    data = dict((c, makeTimeDataFrame()) for c in cols)
    return Panel.fromDict(data)

def add_nans(panel):
    I, J, N = panel.shape
    for i, item in enumerate(panel.items):
        dm = panel[item]
        for j, col in enumerate(dm.columns):
            dm[col][:i + j] = np.NaN

class TestSubDict(dict):
    def __init__(self, *args, **kwargs):
        dict.__init__(self, *args, **kwargs)


# Dependency checks.  Copied this from Nipy/Nipype (Copyright of
# respective developers, license: BSD-3)
def package_check(pkg_name, version=None, app='pandas', checker=LooseVersion,
                  exc_failed_import=ImportError,
                  exc_failed_check=RuntimeError):
    """Check that the minimal version of the required package is installed.

    Parameters
    ----------
    pkg_name : string
        Name of the required package.
    version : string, optional
        Minimal version number for required package.
    app : string, optional
        Application that is performing the check.  For instance, the
        name of the tutorial being executed that depends on specific
        packages.
    checker : object, optional
        The class that will perform the version checking.  Default is
        distutils.version.LooseVersion.
    exc_failed_import : Exception, optional
        Class of the exception to be thrown if import failed.
    exc_failed_check : Exception, optional
        Class of the exception to be thrown if version check failed.

    Examples
    --------
    package_check('numpy', '1.3')
    package_check('networkx', '1.0', 'tutorial1')

    """

    if app:
        msg = '%s requires %s' % (app, pkg_name)
    else:
        msg = 'module requires %s' % pkg_name
    if version:
      msg += ' with version >= %s' % (version,)
    try:
        mod = __import__(pkg_name)
    except ImportError:
        raise exc_failed_import(msg)
    if not version:
        return
    try:
        have_version = mod.__version__
    except AttributeError:
        raise exc_failed_check('Cannot find version for %s' % pkg_name)
    if checker(have_version) < checker(version):
        raise exc_failed_check(msg)

def skip_if_no_package(*args, **kwargs):
    """Raise SkipTest if package_check fails

    Parameters
    ----------
    *args Positional parameters passed to `package_check`
    *kwargs Keyword parameters passed to `package_check`
    """
    from nose import SkipTest
    package_check(exc_failed_import=SkipTest,
                  exc_failed_check=SkipTest,
                  *args, **kwargs)