コード例 #1
0
def test_hash_numpy_arrays(three_np_arrays):
    arr1, arr2, arr3 = three_np_arrays

    for obj1, obj2 in itertools.product(three_np_arrays, repeat=2):
        are_hashes_equal = hash(obj1) == hash(obj2)
        are_arrays_equal = np.all(obj1 == obj2)
        assert are_hashes_equal == are_arrays_equal

    assert hash(arr1) != hash(arr1.T)
コード例 #2
0
def test_hash_numpy_arrays(three_np_arrays):
    arr1, arr2, arr3 = three_np_arrays

    for obj1, obj2 in itertools.product(three_np_arrays, repeat=2):
        are_hashes_equal = hash(obj1) == hash(obj2)
        are_arrays_equal = np.all(obj1 == obj2)
        assert are_hashes_equal == are_arrays_equal

    assert hash(arr1) != hash(arr1.T)
コード例 #3
0
ファイル: test_numpy_pickle.py プロジェクト: zhaipro/joblib
def test_numpy_persistence():
    filename = env['filename']
    rnd = np.random.RandomState(0)
    a = rnd.random_sample((10, 2))
    for compress, cache_size in ((0, 0), (1, 0), (1, 10)):
        # We use 'a.T' to have a non C-contiguous array.
        for index, obj in enumerate(((a,), (a.T,), (a, a), [a, a, a])):
            # Change the file name to avoid side effects between tests
            this_filename = filename + str(random.randint(0, 1000))
            filenames = numpy_pickle.dump(obj, this_filename,
                                          compress=compress,
                                          cache_size=cache_size)
            # Check that one file was created per array
            if not compress:
                nose.tools.assert_equal(len(filenames), len(obj) + 1)
            # Check that these files do exist
            for file in filenames:
                nose.tools.assert_true(
                    os.path.exists(os.path.join(env['dir'], file)))

            # Unpickle the object
            obj_ = numpy_pickle.load(this_filename)
            # Check that the items are indeed arrays
            for item in obj_:
                nose.tools.assert_true(isinstance(item, np.ndarray))
            # And finally, check that all the values are equal.
            nose.tools.assert_true(np.all(np.array(obj) ==
                                                np.array(obj_)))

        # Now test with array subclasses
        for obj in (
                    np.matrix(np.zeros(10)),
                    np.core.multiarray._reconstruct(np.memmap, (), np.float)
                   ):
            this_filename = filename + str(random.randint(0, 1000))
            filenames = numpy_pickle.dump(obj, this_filename,
                                          compress=compress,
                                          cache_size=cache_size)
            obj_ = numpy_pickle.load(this_filename)
            if (type(obj) is not np.memmap
                        and hasattr(obj, '__array_prepare__')):
                # We don't reconstruct memmaps
                nose.tools.assert_true(isinstance(obj_, type(obj)))

    # Finally smoke test the warning in case of compress + mmap_mode
    this_filename = filename + str(random.randint(0, 1000))
    numpy_pickle.dump(a, this_filename, compress=1)
    numpy_pickle.load(this_filename, mmap_mode='r')
コード例 #4
0
def test_numpy_persistence():
    filename = env['filename']
    rnd = np.random.RandomState(0)
    a = rnd.random_sample((10, 2))
    for compress, cache_size in ((0, 0), (1, 0), (1, 10)):
        # We use 'a.T' to have a non C-contiguous array.
        for index, obj in enumerate(((a,), (a.T,), (a, a), [a, a, a])):
            # Change the file name to avoid side effects between tests
            this_filename = filename + str(random.randint(0, 1000))
            filenames = numpy_pickle.dump(obj, this_filename,
                                          compress=compress,
                                          cache_size=cache_size)
            # Check that one file was created per array
            if not compress:
                nose.tools.assert_equal(len(filenames), len(obj) + 1)
            # Check that these files do exist
            for file in filenames:
                nose.tools.assert_true(
                    os.path.exists(os.path.join(env['dir'], file)))

            # Unpickle the object
            obj_ = numpy_pickle.load(this_filename)
            # Check that the items are indeed arrays
            for item in obj_:
                nose.tools.assert_true(isinstance(item, np.ndarray))
            # And finally, check that all the values are equal.
            nose.tools.assert_true(np.all(np.array(obj) ==
                                                np.array(obj_)))

        # Now test with array subclasses
        for obj in (
                    np.matrix(np.zeros(10)),
                    np.core.multiarray._reconstruct(np.memmap, (), np.float)
                   ):
            this_filename = filename + str(random.randint(0, 1000))
            filenames = numpy_pickle.dump(obj, this_filename,
                                          compress=compress,
                                          cache_size=cache_size)
            obj_ = numpy_pickle.load(this_filename)
            if (type(obj) is not np.memmap
                        and hasattr(obj, '__array_prepare__')):
                # We don't reconstruct memmaps
                nose.tools.assert_true(isinstance(obj_, type(obj)))

    # Finally smoke test the warning in case of compress + mmap_mode
    this_filename = filename + str(random.randint(0, 1000))
    numpy_pickle.dump(a, this_filename, compress=1)
    numpy_pickle.load(this_filename, mmap_mode='r')
コード例 #5
0
def test_memory_numpy(tmpdir, mmap_mode):
    " Test memory with a function with numpy arrays."
    accumulator = list()

    def n(l=None):
        accumulator.append(1)
        return l

    memory = Memory(location=tmpdir.strpath, mmap_mode=mmap_mode, verbose=0)
    cached_n = memory.cache(n)

    rnd = np.random.RandomState(0)
    for i in range(3):
        a = rnd.random_sample((10, 10))
        for _ in range(3):
            assert np.all(cached_n(a) == a)
            assert len(accumulator) == i + 1
コード例 #6
0
ファイル: test_memory.py プロジェクト: joblib/joblib
def test_memory_numpy(tmpdir, mmap_mode):
    " Test memory with a function with numpy arrays."
    accumulator = list()

    def n(l=None):
        accumulator.append(1)
        return l

    memory = Memory(location=tmpdir.strpath, mmap_mode=mmap_mode,
                    verbose=0)
    cached_n = memory.cache(n)

    rnd = np.random.RandomState(0)
    for i in range(3):
        a = rnd.random_sample((10, 10))
        for _ in range(3):
            assert np.all(cached_n(a) == a)
            assert len(accumulator) == i + 1
コード例 #7
0
ファイル: test_memory.py プロジェクト: apetcho/joblib
def test_memory_numpy():
    " Test memory with a function with numpy arrays."
    # Check with memmapping and without.
    for mmap_mode in (None, "r"):
        accumulator = list()

        def n(l=None):
            accumulator.append(1)
            return l

        memory = Memory(cachedir=env["dir"], mmap_mode=mmap_mode, verbose=0)
        memory.clear(warn=False)
        cached_n = memory.cache(n)

        rnd = np.random.RandomState(0)
        for i in range(3):
            a = rnd.random_sample((10, 10))
            for _ in range(3):
                yield nose.tools.assert_true, np.all(cached_n(a) == a)
                yield nose.tools.assert_equal, len(accumulator), i + 1
コード例 #8
0
ファイル: test_memory.py プロジェクト: yxlinaqua/joblib
def test_memory_numpy():
    " Test memory with a function with numpy arrays."
    # Check with memmapping and without.
    for mmap_mode in (None, 'r'):
        accumulator = list()

        def n(l=None):
            accumulator.append(1)
            return l

        memory = Memory(cachedir=env['dir'], mmap_mode=mmap_mode, verbose=0)
        memory.clear(warn=False)
        cached_n = memory.cache(n)

        rnd = np.random.RandomState(0)
        for i in range(3):
            a = rnd.random_sample((10, 10))
            for _ in range(3):
                yield nose.tools.assert_true, np.all(cached_n(a) == a)
                yield nose.tools.assert_equal, len(accumulator), i + 1
コード例 #9
0
def test_hash_numpy():
    """ Test hashing with numpy arrays.
    """
    rnd = np.random.RandomState(0)
    arr1 = rnd.random_sample((10, 10))
    arr2 = arr1.copy()
    arr3 = arr2.copy()
    arr3[0] += 1
    obj_list = (arr1, arr2, arr3)
    for obj1 in obj_list:
        for obj2 in obj_list:
            yield assert_equal, hash(obj1) == hash(obj2), np.all(obj1 == obj2)

    d1 = {1: arr1, 2: arr1}
    d2 = {1: arr2, 2: arr2}
    yield assert_equal, hash(d1), hash(d2)

    d3 = {1: arr2, 2: arr3}
    yield assert_not_equal, hash(d1), hash(d3)

    yield assert_not_equal, hash(arr1), hash(arr1.T)
コード例 #10
0
def test_memory_numpy(tmpdir):
    " Test memory with a function with numpy arrays."
    # Check with memmapping and without.
    for mmap_mode in (None, 'r'):
        accumulator = list()

        def n(l=None):
            accumulator.append(1)
            return l

        memory = Memory(cachedir=tmpdir.strpath, mmap_mode=mmap_mode,
                            verbose=0)
        memory.clear(warn=False)
        cached_n = memory.cache(n)

        rnd = np.random.RandomState(0)
        for i in range(3):
            a = rnd.random_sample((10, 10))
            for _ in range(3):
                assert np.all(cached_n(a) == a)
                assert len(accumulator) == i + 1
コード例 #11
0
ファイル: test_hashing.py プロジェクト: tlevine/joblib
def test_hash_numpy():
    """ Test hashing with numpy arrays.
    """
    rnd = np.random.RandomState(0)
    arr1 = rnd.random_sample((10, 10))
    arr2 = arr1.copy()
    arr3 = arr2.copy()
    arr3[0] += 1
    obj_list = (arr1, arr2, arr3)
    for obj1 in obj_list:
        for obj2 in obj_list:
            yield nose.tools.assert_equal, hash(obj1) == hash(obj2), \
                np.all(obj1 == obj2)

    d1 = {1: arr1, 2: arr1}
    d2 = {1: arr2, 2: arr2}
    yield nose.tools.assert_equal, hash(d1), hash(d2)

    d3 = {1: arr2, 2: arr3}
    yield nose.tools.assert_not_equal, hash(d1), hash(d3)

    yield nose.tools.assert_not_equal, hash(arr1), hash(arr1.T)