/usr/lib/python3/dist-packages/h5py/tests/common.py is in python3-h5py 2.6.0-1.
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 | # This file is part of h5py, a Python interface to the HDF5 library.
#
# http://www.h5py.org
#
# Copyright 2008-2013 Andrew Collette and contributors
#
# License: Standard 3-clause BSD; see "license.txt" for full license terms
# and contributor agreement.
from __future__ import absolute_import
import sys
import os
import shutil
import tempfile
from six import unichr
import numpy as np
import h5py
if sys.version_info >= (2, 7) or sys.version_info >= (3, 2):
import unittest as ut
else:
try:
import unittest2 as ut
except ImportError:
raise ImportError(
'unittest2 is required to run the test suite with python-%d.%d'
% (sys.version_info[:2])
)
# Check if non-ascii filenames are supported
# Evidently this is the most reliable way to check
# See also h5py issue #263 and ipython #466
# To test for this, run the testsuite with LC_ALL=C
try:
testfile, fname = tempfile.mkstemp(unichr(0x03b7))
except UnicodeError:
UNICODE_FILENAMES = False
else:
UNICODE_FILENAMES = True
os.close(testfile)
os.unlink(fname)
del fname
del testfile
class TestCase(ut.TestCase):
"""
Base class for unit tests.
"""
@classmethod
def setUpClass(cls):
cls.tempdir = tempfile.mkdtemp(prefix='h5py-test_')
@classmethod
def tearDownClass(cls):
shutil.rmtree(cls.tempdir)
def mktemp(self, suffix='.hdf5', prefix='', dir=None):
if dir is None:
dir = self.tempdir
return tempfile.mktemp(suffix, prefix, dir=self.tempdir)
def setUp(self):
self.f = h5py.File(self.mktemp(), 'w')
def tearDown(self):
try:
if self.f:
self.f.close()
except:
pass
if not hasattr(ut.TestCase, 'assertSameElements'):
# shim until this is ported into unittest2
def assertSameElements(self, a, b):
for x in a:
match = False
for y in b:
if x == y:
match = True
if not match:
raise AssertionError("Item '%s' appears in a but not b" % x)
for x in b:
match = False
for y in a:
if x == y:
match = True
if not match:
raise AssertionError("Item '%s' appears in b but not a" % x)
def assertArrayEqual(self, dset, arr, message=None, precision=None):
""" Make sure dset and arr have the same shape, dtype and contents, to
within the given precision.
Note that dset may be a NumPy array or an HDF5 dataset.
"""
if precision is None:
precision = 1e-5
if message is None:
message = ''
else:
message = ' (%s)' % message
if np.isscalar(dset) or np.isscalar(arr):
self.assert_(
np.isscalar(dset) and np.isscalar(arr),
'Scalar/array mismatch ("%r" vs "%r")%s' % (dset, arr, message)
)
self.assert_(
dset - arr < precision,
"Scalars differ by more than %.3f%s" % (precision, message)
)
return
self.assert_(
dset.shape == arr.shape,
"Shape mismatch (%s vs %s)%s" % (dset.shape, arr.shape, message)
)
self.assert_(
dset.dtype == arr.dtype,
"Dtype mismatch (%s vs %s)%s" % (dset.dtype, arr.dtype, message)
)
if arr.dtype.names is not None:
for n in arr.dtype.names:
message = '[FIELD %s] %s' % (n, message)
self.assertArrayEqual(dset[n], arr[n], message=message, precision=precision)
elif arr.dtype.kind in ('i', 'f'):
self.assert_(
np.all(np.abs(dset[...] - arr[...]) < precision),
"Arrays differ by more than %.3f%s" % (precision, message)
)
else:
self.assert_(
np.all(dset[...] == arr[...]),
"Arrays are not equal (dtype %s) %s" % (arr.dtype.str, message)
)
def assertNumpyBehavior(self, dset, arr, s):
""" Apply slicing arguments "s" to both dset and arr.
Succeeds if the results of the slicing are identical, or the
exception raised is of the same type for both.
"arr" must be a Numpy array; "dset" may be a NumPy array or dataset.
"""
exc = None
try:
arr_result = arr[s]
except Exception as e:
exc = type(e)
if exc is None:
self.assertArrayEqual(dset[s], arr_result)
else:
with self.assertRaises(exc):
dset[s]
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