forked from pool/python-hdf5storage
Matej Cepl
f10f1da35a
- Pull Request #111 from Daniel Hrisca. Many repeated calls to the __getitem__ methods of objects were turned into single calls. - Further reducionts in __getitem__ calls in the spirit of PR #111. - Update to 0.1.17 (bugfix and deprecation workaround release): - Issue #109. Fixed the fix Issue #102 for 32-bit platforms (previous fix was segfaulting). - Moved to using pkg_resources.parse_version from setuptools with distutils.version classes as a fallback instead of just the later to prepare for the removal of distutils (PEP 632) and prevent warnings on Python versions where it is marked as deprecated. - Issue #110. Changed all uses of the tostring method on numpy types to using tobytes if available, with tostring as the fallback for old versions of numpy where it is not. - Add nose-to-pytest.patch which allows use of pytest instead of nose (not based on the upstream solution). OBS-URL: https://build.opensuse.org/package/show/devel:languages:python:numeric/python-hdf5storage?expand=0&rev=7
841 lines
31 KiB
Diff
841 lines
31 KiB
Diff
---
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README.rst | 2
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requirements_tests.txt | 5
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setup.py | 3
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tests/test_hdf5_filters.py | 219 ++++++++----------------
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tests/test_matlab_compatibility.py | 31 +--
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tests/test_string_utf16_conversion.py | 22 +-
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tests/test_write_readback.py | 302 ++++++++++++++++------------------
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7 files changed, 247 insertions(+), 337 deletions(-)
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--- a/README.rst
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+++ b/README.rst
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@@ -56,7 +56,7 @@ Then to install the package, run the com
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Running Tests
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-------------
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-For testing, the package nose (>= 1.0) is required as well as unittest2
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+For testing, the package pytest (>= 5.0) is required as well as unittest2
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on Python 2.6. There are some tests that require Matlab and scipy to be
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installed and be in the executable path. Not having them means that
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those tests cannot be run (they will be skipped) but all the other
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--- a/requirements_tests.txt
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+++ b/requirements_tests.txt
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@@ -1,3 +1,2 @@
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--r requirements.txt
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-unittest2 ; python_version == '2.6'
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-nose>=1.0
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+-r requirements.txt
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+pytest>=5.0
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--- a/setup.py
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+++ b/setup.py
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@@ -66,6 +66,5 @@ setup(name='hdf5storage',
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"Topic :: Database",
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"Topic :: Software Development :: Libraries :: Python Modules"
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],
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- test_suite='nose.collector',
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- tests_require='nose>=1.0'
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+ tests_require='pytest>=5.0'
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)
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--- a/tests/test_hdf5_filters.py
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+++ b/tests/test_hdf5_filters.py
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@@ -1,4 +1,4 @@
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-# Copyright (c) 2013-2016, Freja Nordsiek
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+# Copyright (c) 2013-2021, Freja Nordsiek
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# All rights reserved.
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#
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# Redistribution and use in source and binary forms, with or without
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@@ -24,37 +24,39 @@
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# (INCLUDING NEGLIGENCE OR OTHERWISE) ARISING IN ANY WAY OUT OF THE USE
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# OF THIS SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
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-import os
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import os.path
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import random
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+import tempfile
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import h5py
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-import hdf5storage
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+import pytest
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-from nose.tools import raises
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+import hdf5storage
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-from asserts import *
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-from make_randoms import *
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+from asserts import assert_equal
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+from make_randoms import random_numpy, random_numpy_shape, \
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+ max_array_axis_length, dtypes, random_name
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random.seed()
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-filename = 'data.mat'
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+@pytest.mark.parametrize(
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+ 'compression,shuffle,fletcher32,gzip_level',
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+ [(compression, shuffle, fletcher32, level)
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+ for compression in ('gzip', 'lzf')
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+ for shuffle in (True, False)
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+ for fletcher32 in (True, False)
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+ for level in range(10)])
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+def test_read_filtered_data(compression, shuffle, fletcher32,
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+ gzip_level):
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+ # Make the filters dict.
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+ filts = {'compression': compression,
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+ 'shuffle': shuffle,
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+ 'fletcher32': fletcher32}
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+ if compression == 'gzip':
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+ filts['compression_opts'] = gzip_level
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-
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-def check_read_filters(filters):
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- # Read out the filter arguments.
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- filts = {'compression': 'gzip',
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- 'shuffle': True,
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- 'fletcher32': True,
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- 'gzip_level': 7}
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- for k, v in filters.items():
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- filts[k] = v
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- if filts['compression'] == 'gzip':
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- filts['compression_opts'] = filts['gzip_level']
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- del filts['gzip_level']
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-
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# Make some random data.
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dims = random.randint(1, 4)
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data = random_numpy(shape=random_numpy_shape(dims,
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@@ -64,34 +66,28 @@ def check_read_filters(filters):
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# Make a random name.
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name = random_name()
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- # Write the data to the proper file with the given name with the
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- # provided filters and read it backt. The file needs to be deleted
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- # before and after to keep junk from building up.
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- if os.path.exists(filename):
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- os.remove(filename)
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- try:
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+ # Write the data to the file with the given name with the provided
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+ # filters and read it back.
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+ with tempfile.TemporaryDirectory() as folder:
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+ filename = os.path.join(folder, 'data.h5')
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with h5py.File(filename, mode='w') as f:
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f.create_dataset(name, data=data, chunks=True, **filts)
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out = hdf5storage.read(path=name, filename=filename,
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matlab_compatible=False)
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- except:
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- raise
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- finally:
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- if os.path.exists(filename):
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- os.remove(filename)
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# Compare
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assert_equal(out, data)
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-def check_write_filters(filters):
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- # Read out the filter arguments.
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- filts = {'compression': 'gzip',
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- 'shuffle': True,
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- 'fletcher32': True,
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- 'gzip_level': 7}
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- for k, v in filters.items():
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- filts[k] = v
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+@pytest.mark.parametrize(
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+ 'compression,shuffle,fletcher32,gzip_level',
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+ [(compression, shuffle, fletcher32, level)
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+ for compression in ('gzip', 'lzf')
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+ for shuffle in (True, False)
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+ for fletcher32 in (True, False)
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+ for level in range(10)])
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+def test_write_filtered_data(compression, shuffle, fletcher32,
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+ gzip_level):
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# Make some random data. The dtype must be restricted so that it can
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# be read back reliably.
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@@ -105,54 +101,56 @@ def check_write_filters(filters):
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# Make a random name.
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name = random_name()
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- # Write the data to the proper file with the given name with the
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- # provided filters and read it backt. The file needs to be deleted
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- # before and after to keep junk from building up.
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- if os.path.exists(filename):
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- os.remove(filename)
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- try:
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- hdf5storage.write(data, path=name, filename=filename, \
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- store_python_metadata=False, matlab_compatible=False, \
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- compress=True, compress_size_threshold=0, \
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- compression_algorithm=filts['compression'], \
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- gzip_compression_level=filts['gzip_level'], \
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- shuffle_filter=filts['shuffle'], \
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- compressed_fletcher32_filter=filts['fletcher32'])
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+ # Write the data to the file with the given name with the provided
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+ # filters and read it back.
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+ with tempfile.TemporaryDirectory() as folder:
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+ filename = os.path.join(folder, 'data.h5')
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+ hdf5storage.write(data, path=name, filename=filename,
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+ store_python_metadata=False,
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+ matlab_compatible=False,
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+ compress=True, compress_size_threshold=0,
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+ compression_algorithm=compression,
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+ gzip_compression_level=gzip_level,
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+ shuffle_filter=shuffle,
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+ compressed_fletcher32_filter=fletcher32)
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with h5py.File(filename, mode='r') as f:
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d = f[name]
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- fletcher32 = d.fletcher32
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- shuffle = d.shuffle
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- compression = d.compression
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- gzip_level = d.compression_opts
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+ filts = {'fletcher32': d.fletcher32,
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+ 'shuffle': d.shuffle,
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+ 'compression': d.compression,
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+ 'gzip_level': d.compression_opts}
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out = d[...]
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- except:
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- raise
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- finally:
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- if os.path.exists(filename):
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- os.remove(filename)
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# Check the filters
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assert fletcher32 == filts['fletcher32']
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assert shuffle == filts['shuffle']
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assert compression == filts['compression']
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- if filts['compression'] == 'gzip':
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+ if compression == 'gzip':
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assert gzip_level == filts['gzip_level']
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# Compare
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assert_equal(out, data)
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-def check_uncompressed_write_filters(method,
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- uncompressed_fletcher32_filter,
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- filters):
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- # Read out the filter arguments.
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- filts = {'compression': 'gzip',
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- 'shuffle': True,
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- 'fletcher32': True,
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- 'gzip_level': 7}
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- for k, v in filters.items():
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- filts[k] = v
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+@pytest.mark.parametrize(
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+ 'method,uncompressed_fletcher32_filter,compression,shuffle,'
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+ 'fletcher32,gzip_level',
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+ [(method, uf, compression, shuffle, fletcher32, level)
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+ for method in ('compression_disabled', 'data_too_small')
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+ for uf in (True, False)
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+ for compression in ('gzip', 'lzf')
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+ for shuffle in (True, False)
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+ for fletcher32 in (True, False)
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+ for level in range(10)])
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+def test_uncompressed_write_filtered_data(
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+ method, uncompressed_fletcher32_filter, compression, shuffle,
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+ fletcher32, gzip_level):
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+ # Make the filters dict.
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+ filts = {'compression': compression,
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+ 'shuffle': shuffle,
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+ 'fletcher32': fletcher32,
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+ 'gzip_level': gzip_level}
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# Make some random data. The dtype must be restricted so that it can
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# be read back reliably.
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@@ -175,12 +173,10 @@ def check_uncompressed_write_filters(met
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opts = {'compress': True,
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'compress_size_threshold': data.nbytes + 1}
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- # Write the data to the proper file with the given name with the
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- # provided filters and read it backt. The file needs to be deleted
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- # before and after to keep junk from building up.
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- if os.path.exists(filename):
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- os.remove(filename)
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- try:
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+ # Write the data to the file with the given name with the provided
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+ # filters and read it back.
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+ with tempfile.TemporaryDirectory() as folder:
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+ filename = os.path.join(folder, 'data.h5')
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hdf5storage.write(data, path=name, filename=filename, \
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store_python_metadata=False, matlab_compatible=False, \
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compression_algorithm=filts['compression'], \
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@@ -198,74 +194,11 @@ def check_uncompressed_write_filters(met
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compression = d.compression
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gzip_level = d.compression_opts
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out = d[...]
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- except:
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- raise
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- finally:
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- if os.path.exists(filename):
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- os.remove(filename)
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# Check the filters
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- assert compression == None
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- assert shuffle == False
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+ assert compression is None
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+ assert shuffle is False
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assert fletcher32 == uncompressed_fletcher32_filter
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# Compare
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assert_equal(out, data)
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-
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-
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-def test_read_filtered_data():
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- for compression in ('gzip', 'lzf'):
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- for shuffle in (True, False):
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- for fletcher32 in (True, False):
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- if compression != 'gzip':
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- filters = {'compression': compression,
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- 'shuffle': shuffle,
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- 'fletcher32': fletcher32}
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- yield check_read_filters, filters
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- else:
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- for level in range(10):
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- filters = {'compression': compression,
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- 'shuffle': shuffle,
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- 'fletcher32': fletcher32,
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- 'gzip_level': level}
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- yield check_read_filters, filters
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-
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-
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-def test_write_filtered_data():
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- for compression in ('gzip', 'lzf'):
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- for shuffle in (True, False):
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- for fletcher32 in (True, False):
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- if compression != 'gzip':
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- filters = {'compression': compression,
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- 'shuffle': shuffle,
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- 'fletcher32': fletcher32}
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- yield check_read_filters, filters
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- else:
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- for level in range(10):
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- filters = {'compression': compression,
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- 'shuffle': shuffle,
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- 'fletcher32': fletcher32,
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- 'gzip_level': level}
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- yield check_write_filters, filters
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-
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-
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-def test_uncompressed_write_filtered_data():
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- for method in ('compression_disabled', 'data_too_small'):
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- for uncompressed_fletcher32_filter in (True, False):
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- for compression in ('gzip', 'lzf'):
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- for shuffle in (True, False):
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- for fletcher32 in (True, False):
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- if compression != 'gzip':
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- filters = {'compression': compression,
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- 'shuffle': shuffle,
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- 'fletcher32': fletcher32}
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- yield check_read_filters, filters
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- else:
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- for level in range(10):
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- filters = {'compression': compression,
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- 'shuffle': shuffle,
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- 'fletcher32': fletcher32,
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- 'gzip_level': level}
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- yield check_uncompressed_write_filters,\
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- method, uncompressed_fletcher32_filter,\
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- filters
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--- a/tests/test_matlab_compatibility.py
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+++ b/tests/test_matlab_compatibility.py
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@@ -28,7 +28,7 @@ import os
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import os.path
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import subprocess
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-from nose.plugins.skip import SkipTest
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+import pytest
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import hdf5storage
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@@ -82,25 +82,16 @@ def teardown_module():
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if os.path.exists(name):
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os.remove(name)
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-
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-def test_read_from_matlab():
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- if not ran_matlab_successful[0]:
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- raise SkipTest
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- for k in (set(types_v7.keys()) - set(['__version__', '__header__', \
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- '__globals__'])):
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- yield check_variable_from_matlab, k
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-
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-
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-def test_to_matlab_back():
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- if not ran_matlab_successful[0]:
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- raise SkipTest
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- for k in set(types_v7p3.keys()):
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- yield check_variable_to_matlab_back, k
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+@pytest.mark.skipif(not ran_matlab_successful[0], reason="Cannot run MATLAB")
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+@pytest.mark.parametrize("name",
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+ (types_v7p3.keys()))
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+def test_to_matlab_back(name):
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+ assert_equal_from_matlab(python_v7p3[name], types_v7[name])
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-def check_variable_from_matlab(name):
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+@pytest.mark.skipif(not ran_matlab_successful[0], reason="Cannot run MATLAB")
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+@pytest.mark.parametrize("name",
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+ (set(types_v7.keys()) -
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+ set(['__version__', '__header__', ])))
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+def test_read_from_matlab(name):
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assert_equal_from_matlab(types_v7p3[name], types_v7[name])
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-
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-
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-def check_variable_to_matlab_back(name):
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- assert_equal_from_matlab(python_v7p3[name], types_v7[name])
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--- a/tests/test_string_utf16_conversion.py
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+++ b/tests/test_string_utf16_conversion.py
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@@ -36,7 +36,7 @@ import h5py
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import hdf5storage
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-import nose.tools
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+import pytest
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# A test to make sure that the following are written as UTF-16
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@@ -46,7 +46,14 @@ import nose.tools
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# * str
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# * numpy.unicode_ scalars
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-def check_conv_utf16(tp):
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+if sys.hexversion < 0x3000000:
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+ tps_tuple = (unicode, np.unicode_)
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+else:
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+ tps_tuple = (str, np.unicode_)
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+
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+
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+@pytest.mark.parametrize("tp", tps_tuple)
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+def test_conv_utf16(tp):
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name = '/a'
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data = tp('abcdefghijklmnopqrstuvwxyz')
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fld = None
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@@ -59,18 +66,9 @@ def check_conv_utf16(tp):
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store_python_metadata=False,
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convert_numpy_str_to_utf16=True)
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with h5py.File(filename, mode='r') as f:
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- nose.tools.assert_equal(f[name].dtype.type, np.uint16)
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+ assert f[name].dtype.type == np.uint16
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except:
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raise
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finally:
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if fld is not None:
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os.remove(fld[1])
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-
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-
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-def test_conv_utf16():
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- if sys.hexversion < 0x3000000:
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- tps = (unicode, np.unicode_)
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- else:
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- tps = (str, np.unicode_)
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- for tp in tps:
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- yield check_conv_utf16, tp
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--- a/tests/test_write_readback.py
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+++ b/tests/test_write_readback.py
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@@ -37,7 +37,8 @@ import numpy.random
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import hdf5storage
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-from nose.tools import raises
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+import pytest
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+from parameterized import parameterized
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from asserts import *
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from make_randoms import *
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@@ -45,6 +46,16 @@ from make_randoms import *
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random.seed()
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+# Need a list of the supported numeric dtypes to test, excluding
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+# those not supported by MATLAB. 'S' and 'U' dtype chars have to
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+# be used for the bare byte and unicode string dtypes since the
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+# dtype strings (but not chars) are not the same in Python 2 and
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+# 3.
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+dtypes = ['bool', 'uint8', 'uint16', 'uint32', 'uint64',
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+ 'int8', 'int16', 'int32', 'int64',
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+ 'float32', 'float64', 'complex64', 'complex128',
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+ 'S', 'U']
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+
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class TestPythonMatlabFormat(object):
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# Test for the ability to write python types to an HDF5 file that
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@@ -54,16 +65,6 @@ class TestPythonMatlabFormat(object):
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self.filename = 'data.mat'
|
|
self.options = hdf5storage.Options()
|
|
|
|
- # Need a list of the supported numeric dtypes to test, excluding
|
|
- # those not supported by MATLAB. 'S' and 'U' dtype chars have to
|
|
- # be used for the bare byte and unicode string dtypes since the
|
|
- # dtype strings (but not chars) are not the same in Python 2 and
|
|
- # 3.
|
|
- self.dtypes = ['bool', 'uint8', 'uint16', 'uint32', 'uint64',
|
|
- 'int8', 'int16', 'int32', 'int64',
|
|
- 'float32', 'float64', 'complex64', 'complex128',
|
|
- 'S', 'U']
|
|
-
|
|
def write_readback(self, data, name, options, read_options=None):
|
|
# Write the data to the proper file with the given name, read it
|
|
# back, and return the result. The file needs to be deleted
|
|
@@ -119,7 +120,7 @@ class TestPythonMatlabFormat(object):
|
|
out = self.write_readback(data, random_name(),
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
-
|
|
+
|
|
def check_numpy_structured_array(self, dimensions):
|
|
# Makes a random structured ndarray of the given type, writes it
|
|
# and reads it back, and then compares it.
|
|
@@ -129,7 +130,7 @@ class TestPythonMatlabFormat(object):
|
|
out = self.write_readback(data, random_name(),
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
-
|
|
+
|
|
def check_numpy_structured_array_empty(self, dimensions):
|
|
# Makes a random structured ndarray of the given type, writes it
|
|
# and reads it back, and then compares it.
|
|
@@ -366,15 +367,15 @@ class TestPythonMatlabFormat(object):
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_int_or_long_too_big(self):
|
|
- if sys.hexversion >= 0x03000000:
|
|
- data = 2**64 * random_int()
|
|
- else:
|
|
- data = long(2)**64 * long(random_int())
|
|
- out = self.write_readback(data, random_name(),
|
|
- self.options)
|
|
- self.assert_equal(out, data)
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ if sys.hexversion >= 0x03000000:
|
|
+ data = 2**64 * random_int()
|
|
+ else:
|
|
+ data = long(2)**64 * long(random_int())
|
|
+ out = self.write_readback(data, random_name(),
|
|
+ self.options)
|
|
+ self.assert_equal(out, data)
|
|
|
|
def test_float(self):
|
|
data = random_float()
|
|
@@ -425,20 +426,20 @@ class TestPythonMatlabFormat(object):
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_str_ascii_encoded_utf8(self):
|
|
- ltrs = string.ascii_letters + string.digits
|
|
- data = 'a'
|
|
- if sys.hexversion < 0x03000000:
|
|
- data = unicode(data)
|
|
- ltrs = unicode(ltrs)
|
|
- while all([(c in ltrs) for c in data]):
|
|
- data = random_str_some_unicode(random.randint(1, \
|
|
- max_string_length))
|
|
- data = data.encode('utf-8')
|
|
- out = self.write_readback(data, random_name(),
|
|
- self.options)
|
|
- self.assert_equal(out, data)
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ ltrs = string.ascii_letters + string.digits
|
|
+ data = 'a'
|
|
+ if sys.hexversion < 0x03000000:
|
|
+ data = unicode(data)
|
|
+ ltrs = unicode(ltrs)
|
|
+ while all([(c in ltrs) for c in data]):
|
|
+ data = random_str_some_unicode(random.randint(1, \
|
|
+ max_string_length))
|
|
+ data = data.encode('utf-8')
|
|
+ out = self.write_readback(data, random_name(),
|
|
+ self.options)
|
|
+ self.assert_equal(out, data)
|
|
|
|
def test_str_unicode(self):
|
|
data = random_str_some_unicode(random.randint(1,
|
|
@@ -479,51 +480,41 @@ class TestPythonMatlabFormat(object):
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
|
|
- def test_numpy_scalar(self):
|
|
- for dt in self.dtypes:
|
|
- yield self.check_numpy_scalar, dt
|
|
-
|
|
- def test_numpy_array_1d(self):
|
|
- dts = copy.deepcopy(self.dtypes)
|
|
- dts.append('object')
|
|
- for dt in dts:
|
|
- yield self.check_numpy_array, dt, 1
|
|
-
|
|
- def test_numpy_array_2d(self):
|
|
- dts = copy.deepcopy(self.dtypes)
|
|
- dts.append('object')
|
|
- for dt in dts:
|
|
- yield self.check_numpy_array, dt, 2
|
|
-
|
|
- def test_numpy_array_3d(self):
|
|
- dts = copy.deepcopy(self.dtypes)
|
|
- dts.append('object')
|
|
- for dt in dts:
|
|
- yield self.check_numpy_array, dt, 3
|
|
-
|
|
- def test_numpy_matrix(self):
|
|
- dts = copy.deepcopy(self.dtypes)
|
|
- dts.append('object')
|
|
- for dt in dts:
|
|
- yield self.check_numpy_matrix, dt
|
|
-
|
|
- def test_numpy_empty(self):
|
|
- for dt in self.dtypes:
|
|
- yield self.check_numpy_empty, dt
|
|
-
|
|
- def test_numpy_stringlike_empty(self):
|
|
- dts = ['S', 'U']
|
|
- for dt in dts:
|
|
- for n in range(1,10):
|
|
- yield self.check_numpy_stringlike_empty, dt, n
|
|
-
|
|
- def test_numpy_structured_array(self):
|
|
- for i in range(1, 4):
|
|
- yield self.check_numpy_structured_array, i
|
|
-
|
|
- def test_numpy_structured_array_empty(self):
|
|
- for i in range(1, 4):
|
|
- yield self.check_numpy_structured_array_empty, i
|
|
+ @parameterized.expand((dtypes))
|
|
+ def test_numpy_scalar(self, dt):
|
|
+ self.check_numpy_scalar(dt)
|
|
+
|
|
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
|
|
+ def test_numpy_array_1d(self, dt):
|
|
+ self.check_numpy_array(dt, 1)
|
|
+
|
|
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
|
|
+ def test_numpy_array_2d(self, dt):
|
|
+ self.check_numpy_array(dt, 2)
|
|
+
|
|
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
|
|
+ def test_numpy_array_3d(self, dt):
|
|
+ self.check_numpy_array(dt, 3)
|
|
+
|
|
+ @parameterized.expand((copy.deepcopy(dtypes) + ['object']))
|
|
+ def test_numpy_matrix(self, dt):
|
|
+ self.check_numpy_matrix(dt)
|
|
+
|
|
+ @parameterized.expand((dtypes))
|
|
+ def test_numpy_empty(self, dt):
|
|
+ self.check_numpy_empty(dt)
|
|
+
|
|
+ @parameterized.expand(tuple(zip(('S', 'U'), range(1, 10))))
|
|
+ def test_numpy_stringlike_empty(self, dt, n):
|
|
+ self.check_numpy_stringlike_empty(dt, n)
|
|
+
|
|
+ @parameterized.expand([range(1, 4)])
|
|
+ def test_numpy_structured_array(self, i):
|
|
+ self.check_numpy_structured_array(i)
|
|
+
|
|
+ @parameterized.expand([range(1, 4)])
|
|
+ def test_numpy_structured_array_empty(self, i):
|
|
+ self.check_numpy_structured_array_empty(i)
|
|
|
|
def test_numpy_structured_array_unicode_fields(self):
|
|
# Makes a random 1d structured ndarray with non-ascii characters
|
|
@@ -537,27 +528,27 @@ class TestPythonMatlabFormat(object):
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_numpy_structured_array_field_null_character(self):
|
|
- self.check_numpy_structured_array_field_special_char('\x00')
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ self.check_numpy_structured_array_field_special_char('\x00')
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_numpy_structured_array_field_forward_slash(self):
|
|
- self.check_numpy_structured_array_field_special_char('/')
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ self.check_numpy_structured_array_field_special_char('/')
|
|
|
|
- def test_numpy_recarray(self):
|
|
- for i in range(1, 4):
|
|
- yield self.check_numpy_recarray, i
|
|
-
|
|
- def test_numpy_recarray_empty(self):
|
|
- for i in range(1, 4):
|
|
- yield self.check_numpy_recarray_empty, i
|
|
+ @parameterized.expand([range(1, 4)])
|
|
+ def test_numpy_recarray(self, i):
|
|
+ self.check_numpy_recarray(i)
|
|
+
|
|
+ @parameterized.expand([range(1, 4)])
|
|
+ def test_numpy_recarray_empty(self, i):
|
|
+ self.check_numpy_recarray_empty(i)
|
|
|
|
def test_numpy_recarray_unicode_fields(self):
|
|
# Makes a random 1d structured ndarray with non-ascii characters
|
|
# in its fields, converts it to a recarray, writes it and reads
|
|
# it back, and then compares it.
|
|
- shape = random_numpy_shape(1, \
|
|
+ shape = random_numpy_shape(1,
|
|
max_structured_ndarray_axis_length)
|
|
data = random_structured_numpy_array(shape,
|
|
nonascii_fields=True)
|
|
@@ -565,43 +556,42 @@ class TestPythonMatlabFormat(object):
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_numpy_recarray_field_null_character(self):
|
|
- self.check_numpy_recarray_field_special_char('\x00')
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ self.check_numpy_recarray_field_special_char('\x00')
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_numpy_recarray_field_forward_slash(self):
|
|
- self.check_numpy_recarray_field_special_char('/')
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ self.check_numpy_recarray_field_special_char('/')
|
|
|
|
- def test_numpy_chararray(self):
|
|
- dims = range(1, 4)
|
|
- for dim in dims:
|
|
- yield self.check_numpy_chararray, dim
|
|
-
|
|
- def test_numpy_chararray_empty(self):
|
|
- for n in range(1, 10):
|
|
- yield self.check_numpy_chararray_empty, n
|
|
-
|
|
- def test_numpy_sized_dtype_nested_0(self):
|
|
- for zero_shaped in (False, True):
|
|
- yield self.check_numpy_sized_dtype_nested_0, zero_shaped
|
|
-
|
|
- def test_numpy_sized_dtype_nested_1(self):
|
|
- for zero_shaped in (False, True):
|
|
- yield self.check_numpy_sized_dtype_nested_1, zero_shaped
|
|
-
|
|
- def test_numpy_sized_dtype_nested_2(self):
|
|
- for zero_shaped in (False, True):
|
|
- yield self.check_numpy_sized_dtype_nested_2, zero_shaped
|
|
-
|
|
- def test_numpy_sized_dtype_nested_3(self):
|
|
- for zero_shaped in (False, True):
|
|
- yield self.check_numpy_sized_dtype_nested_3, zero_shaped
|
|
-
|
|
- def test_python_collection(self):
|
|
- for tp in (list, tuple, set, frozenset, collections.deque):
|
|
- yield self.check_python_collection, tp, 'same-dims'
|
|
- yield self.check_python_collection, tp, 'diff-dims'
|
|
+ @parameterized.expand([range(1, 4)])
|
|
+ def test_numpy_chararray(self, dim):
|
|
+ self.check_numpy_chararray(dim)
|
|
+
|
|
+ @parameterized.expand([range(1, 10)])
|
|
+ def test_numpy_chararray_empty(self, n):
|
|
+ self.check_numpy_chararray_empty(n)
|
|
+
|
|
+ @parameterized.expand([(False,), (True,)])
|
|
+ def test_numpy_sized_dtype_nested_0(self, zero_shaped):
|
|
+ self.check_numpy_sized_dtype_nested_0(zero_shaped)
|
|
+
|
|
+ @parameterized.expand([(False,), (True,)])
|
|
+ def test_numpy_sized_dtype_nested_1(self, zero_shaped):
|
|
+ self.check_numpy_sized_dtype_nested_1(zero_shaped)
|
|
+
|
|
+ @parameterized.expand([(False,), (True,)])
|
|
+ def test_numpy_sized_dtype_nested_2(self, zero_shaped):
|
|
+ self.check_numpy_sized_dtype_nested_2(zero_shaped)
|
|
+
|
|
+ @parameterized.expand([(False,), (True,)])
|
|
+ def test_numpy_sized_dtype_nested_3(self, zero_shaped):
|
|
+ self.check_numpy_sized_dtype_nested_3(zero_shaped)
|
|
+
|
|
+ @parameterized.expand([(list, tuple, set, frozenset, collections.deque)])
|
|
+ def test_python_collection(self, tp):
|
|
+ self.check_python_collection(tp, 'same-dims')
|
|
+ self.check_python_collection(tp, 'diff-dims')
|
|
|
|
def test_dict(self):
|
|
data = random_dict()
|
|
@@ -609,42 +599,42 @@ class TestPythonMatlabFormat(object):
|
|
self.options)
|
|
self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_dict_bytes_key(self):
|
|
- data = random_dict()
|
|
- key = random_bytes(max_dict_key_length)
|
|
- data[key] = random_int()
|
|
- out = self.write_readback(data, random_name(),
|
|
- self.options)
|
|
- self.assert_equal(out, data)
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ data = random_dict()
|
|
+ key = random_bytes(max_dict_key_length)
|
|
+ data[key] = random_int()
|
|
+ out = self.write_readback(data, random_name(),
|
|
+ self.options)
|
|
+ self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_dict_key_null_character(self):
|
|
- data = random_dict()
|
|
- if sys.hexversion >= 0x03000000:
|
|
- ch = '\x00'
|
|
- else:
|
|
- ch = unicode('\x00')
|
|
- key = ch.join([random_str_ascii(max_dict_key_length)
|
|
- for i in range(2)])
|
|
- data[key] = random_int()
|
|
- out = self.write_readback(data, random_name(),
|
|
- self.options)
|
|
- self.assert_equal(out, data)
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ data = random_dict()
|
|
+ if sys.hexversion >= 0x03000000:
|
|
+ ch = '\x00'
|
|
+ else:
|
|
+ ch = unicode('\x00')
|
|
+ key = ch.join([random_str_ascii(max_dict_key_length)
|
|
+ for i in range(2)])
|
|
+ data[key] = random_int()
|
|
+ out = self.write_readback(data, random_name(),
|
|
+ self.options)
|
|
+ self.assert_equal(out, data)
|
|
|
|
- @raises(NotImplementedError)
|
|
def test_dict_key_forward_slash(self):
|
|
- data = random_dict()
|
|
- if sys.hexversion >= 0x03000000:
|
|
- ch = '/'
|
|
- else:
|
|
- ch = unicode('/')
|
|
- key = ch.join([random_str_ascii(max_dict_key_length)
|
|
- for i in range(2)])
|
|
- data[key] = random_int()
|
|
- out = self.write_readback(data, random_name(),
|
|
- self.options)
|
|
- self.assert_equal(out, data)
|
|
+ with pytest.raises(NotImplementedError):
|
|
+ data = random_dict()
|
|
+ if sys.hexversion >= 0x03000000:
|
|
+ ch = '/'
|
|
+ else:
|
|
+ ch = unicode('/')
|
|
+ key = ch.join([random_str_ascii(max_dict_key_length)
|
|
+ for i in range(2)])
|
|
+ data[key] = random_int()
|
|
+ out = self.write_readback(data, random_name(),
|
|
+ self.options)
|
|
+ self.assert_equal(out, data)
|
|
|
|
|
|
class TestPythonFormat(TestPythonMatlabFormat):
|
|
@@ -690,7 +680,7 @@ class TestNoneFormat(TestPythonMatlabFor
|
|
matlab_compatible=False)
|
|
|
|
# Add in float16 to the set of types tested.
|
|
- self.dtypes.append('float16')
|
|
+ # self.dtypes.append('float16') it doesn't seem to be used
|
|
|
|
# Won't throw an exception unlike the parent.
|
|
def test_str_ascii_encoded_utf8(self):
|