239 lines
7.6 KiB
Python
239 lines
7.6 KiB
Python
# This file is part of h5py, a Python interface to the HDF5 library.
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#
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# http://www.h5py.org
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#
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# Copyright 2008-2013 Andrew Collette and contributors
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#
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# License: Standard 3-clause BSD; see "license.txt" for full license terms
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# and contributor agreement.
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import sys
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import os
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import shutil
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import inspect
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import tempfile
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import subprocess
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from contextlib import contextmanager
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from functools import wraps
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import numpy as np
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from numpy.lib.recfunctions import repack_fields
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import h5py
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import unittest as ut
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# Check if non-ascii filenames are supported
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# Evidently this is the most reliable way to check
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# See also h5py issue #263 and ipython #466
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# To test for this, run the testsuite with LC_ALL=C
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try:
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testfile, fname = tempfile.mkstemp(chr(0x03b7))
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except UnicodeError:
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UNICODE_FILENAMES = False
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else:
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UNICODE_FILENAMES = True
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os.close(testfile)
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os.unlink(fname)
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del fname
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del testfile
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class TestCase(ut.TestCase):
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"""
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Base class for unit tests.
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"""
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@classmethod
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def setUpClass(cls):
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cls.tempdir = tempfile.mkdtemp(prefix='h5py-test_')
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@classmethod
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def tearDownClass(cls):
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shutil.rmtree(cls.tempdir)
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def mktemp(self, suffix='.hdf5', prefix='', dir=None):
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if dir is None:
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dir = self.tempdir
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return tempfile.mktemp(suffix, prefix, dir=dir)
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def mktemp_mpi(self, comm=None, suffix='.hdf5', prefix='', dir=None):
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if comm is None:
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from mpi4py import MPI
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comm = MPI.COMM_WORLD
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fname = None
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if comm.Get_rank() == 0:
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fname = self.mktemp(suffix, prefix, dir)
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fname = comm.bcast(fname, 0)
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return fname
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def setUp(self):
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self.f = h5py.File(self.mktemp(), 'w')
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def tearDown(self):
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try:
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if self.f:
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self.f.close()
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except:
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pass
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def assertSameElements(self, a, b):
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for x in a:
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match = False
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for y in b:
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if x == y:
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match = True
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if not match:
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raise AssertionError("Item '%s' appears in a but not b" % x)
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for x in b:
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match = False
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for y in a:
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if x == y:
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match = True
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if not match:
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raise AssertionError("Item '%s' appears in b but not a" % x)
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def assertArrayEqual(self, dset, arr, message=None, precision=None, check_alignment=True):
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""" Make sure dset and arr have the same shape, dtype and contents, to
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within the given precision, optionally ignoring differences in dtype alignment.
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Note that dset may be a NumPy array or an HDF5 dataset.
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"""
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if precision is None:
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precision = 1e-5
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if message is None:
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message = ''
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else:
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message = ' (%s)' % message
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if np.isscalar(dset) or np.isscalar(arr):
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assert np.isscalar(dset) and np.isscalar(arr), \
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'Scalar/array mismatch ("%r" vs "%r")%s' % (dset, arr, message)
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dset = np.asarray(dset)
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arr = np.asarray(arr)
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assert dset.shape == arr.shape, \
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"Shape mismatch (%s vs %s)%s" % (dset.shape, arr.shape, message)
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if dset.dtype != arr.dtype:
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if check_alignment:
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normalized_dset_dtype = dset.dtype
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normalized_arr_dtype = arr.dtype
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else:
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normalized_dset_dtype = repack_fields(dset.dtype)
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normalized_arr_dtype = repack_fields(arr.dtype)
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assert normalized_dset_dtype == normalized_arr_dtype, \
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"Dtype mismatch (%s vs %s)%s" % (normalized_dset_dtype, normalized_arr_dtype, message)
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if not check_alignment:
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if normalized_dset_dtype != dset.dtype:
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dset = repack_fields(np.asarray(dset))
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if normalized_arr_dtype != arr.dtype:
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arr = repack_fields(np.asarray(arr))
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if arr.dtype.names is not None:
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for n in arr.dtype.names:
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message = '[FIELD %s] %s' % (n, message)
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self.assertArrayEqual(dset[n], arr[n], message=message, precision=precision, check_alignment=check_alignment)
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elif arr.dtype.kind in ('i', 'f'):
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assert np.all(np.abs(dset[...] - arr[...]) < precision), \
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"Arrays differ by more than %.3f%s" % (precision, message)
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elif arr.dtype.kind == 'O':
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for v1, v2 in zip(dset.flat, arr.flat):
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self.assertArrayEqual(v1, v2, message=message, precision=precision, check_alignment=check_alignment)
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else:
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assert np.all(dset[...] == arr[...]), \
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"Arrays are not equal (dtype %s) %s" % (arr.dtype.str, message)
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def assertNumpyBehavior(self, dset, arr, s, skip_fast_reader=False):
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""" Apply slicing arguments "s" to both dset and arr.
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Succeeds if the results of the slicing are identical, or the
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exception raised is of the same type for both.
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"arr" must be a Numpy array; "dset" may be a NumPy array or dataset.
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"""
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exc = None
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try:
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arr_result = arr[s]
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except Exception as e:
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exc = type(e)
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s_fast = s if isinstance(s, tuple) else (s,)
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if exc is None:
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self.assertArrayEqual(dset[s], arr_result)
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if not skip_fast_reader:
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self.assertArrayEqual(
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dset._fast_reader.read(s_fast),
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arr_result,
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)
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else:
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with self.assertRaises(exc):
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dset[s]
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if not skip_fast_reader:
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with self.assertRaises(exc):
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dset._fast_reader.read(s_fast)
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NUMPY_RELEASE_VERSION = tuple([int(i) for i in np.__version__.split(".")[0:2]])
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@contextmanager
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def closed_tempfile(suffix='', text=None):
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"""
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Context manager which yields the path to a closed temporary file with the
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suffix `suffix`. The file will be deleted on exiting the context. An
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additional argument `text` can be provided to have the file contain `text`.
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"""
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with tempfile.NamedTemporaryFile(
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'w+t', suffix=suffix, delete=False
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) as test_file:
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file_name = test_file.name
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if text is not None:
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test_file.write(text)
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test_file.flush()
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yield file_name
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shutil.rmtree(file_name, ignore_errors=True)
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def insubprocess(f):
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"""Runs a test in its own subprocess"""
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@wraps(f)
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def wrapper(request, *args, **kwargs):
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curr_test = inspect.getsourcefile(f) + "::" + request.node.name
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# get block around test name
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insub = "IN_SUBPROCESS_" + curr_test
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for c in "/\\,:.":
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insub = insub.replace(c, "_")
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defined = os.environ.get(insub, None)
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# fork process
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if defined:
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return f(request, *args, **kwargs)
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else:
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os.environ[insub] = '1'
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env = os.environ.copy()
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env[insub] = '1'
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env.update(getattr(f, 'subproc_env', {}))
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with closed_tempfile() as stdout:
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with open(stdout, 'w+t') as fh:
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rtn = subprocess.call([sys.executable, '-m', 'pytest', curr_test],
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stdout=fh, stderr=fh, env=env)
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with open(stdout, 'rt') as fh:
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out = fh.read()
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assert rtn == 0, "\n" + out
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return wrapper
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def subproc_env(d):
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"""Set environment variables for the @insubprocess decorator"""
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def decorator(f):
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f.subproc_env = d
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return f
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return decorator
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