def test_write_dset_under_root(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(5, 7)
attrs = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3'],
'labels': {'even_rows': (slice(0, None, 2), slice(None)),
'odd_rows': (slice(1, None, 2), slice(None))}
}
micro_dset = VirtualDataset('test', data)
micro_dset.attrs = attrs.copy()
[h5_dset] = writer.write(micro_dset)
self.assertIsInstance(h5_dset, h5py.Dataset)
reg_ref = attrs.pop('labels')
self.assertEqual(len(h5_dset.attrs), len(attrs) + 1 + len(reg_ref))
for key, expected_val in attrs.items():
self.assertTrue(np.all(get_attr(h5_dset, key) == expected_val))
self.assertTrue(np.all([x in list(reg_ref.keys()) for x in get_attr(h5_dset, 'labels')]))
expected_data = [data[:None:2], data[1:None:2]]
written_data = [h5_dset[h5_dset.attrs['even_rows']], h5_dset[h5_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
os.remove(file_path)
def test_print(self):
group_name = 'indexed_group_'
group = VirtualGroup(group_name)
dset_name_1 = 'dset_1'
data_1 = np.arange(3)
dset_1 = VirtualDataset(dset_name_1, data_1)
dset_name_2 = 'dset_2'
data_2 = np.random.rand(2, 3)
dset_2 = VirtualDataset(dset_name_2, data_2)
inner_grp_name = 'other_indexed_group_'
inner_group = VirtualGroup(inner_grp_name)
inner_group.add_children(dset_2)
group.add_children([dset_1, inner_group])
# http://pragmaticpython.com/2017/03/23/unittesting-print-statements/
stdout_org = sys.stdout
my_stdout = MyOutput()
try:
sys.stdout = my_stdout
group.show_tree()
finally:
sys.stdout = stdout_org
self.assertEqual(str(my_stdout), "/indexed_group_/dset_1\n/indexed_group_/other_indexed_group_\n/indexed_group_"
"/other_indexed_group_/dset_2\n")
def test_write_dset_under_root(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(5, 7)
attrs = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3'],
'labels': {'even_rows': (slice(0, None, 2), slice(None)),
'odd_rows': (slice(1, None, 2), slice(None))}
}
micro_dset = VirtualDataset('test', data)
micro_dset.attrs = attrs.copy()
[h5_dset] = writer.write(micro_dset)
self.assertIsInstance(h5_dset, h5py.Dataset)
reg_ref = attrs.pop('labels')
self.assertEqual(len(h5_dset.attrs), len(attrs) + 1 + len(reg_ref))
for key, expected_val in attrs.items():
self.assertTrue(np.all(get_attr(h5_dset, key) == expected_val))
self.assertTrue(np.all([x in list(reg_ref.keys()) for x in get_attr(h5_dset, 'labels')]))
expected_data = [data[:None:2], data[1:None:2]]
written_data = [h5_dset[h5_dset.attrs['even_rows']], h5_dset[h5_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
os.remove(file_path)
def test_add_children_legal_01(self):
group_name = 'indexed_group_'
group = VirtualGroup(group_name)
dset_name_1 = 'dset_1'
data_1 = np.arange(3)
dset_1 = VirtualDataset(dset_name_1, data_1)
dset_name_2 = 'dset_2'
data_2 = np.random.rand(2, 3)
dset_2 = VirtualDataset(dset_name_2, data_2)
group.add_children([dset_1, dset_2])
self.assertEqual(len(group.children), 2)
def test_simple_dset_write_success_more_options_03(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
dset_name = 'test'
data = np.random.rand(16, 1024)
dtype = np.float16
compression = 'gzip'
chunking = (1, 1024)
microdset = VirtualDataset(dset_name,
data,
dtype=dtype,
compression=compression,
chunking=chunking)
writer = HDFwriter(h5_f)
h5_d = writer._create_simple_dset(h5_f, microdset)
self.assertIsInstance(h5_d, h5py.Dataset)
self.assertEqual(h5_d.parent, h5_f)
self.assertEqual(h5_d.name, '/' + dset_name)
self.assertEqual(h5_d.shape, data.shape)
self.assertEqual(h5_d.dtype, dtype)
self.assertEqual(h5_d.compression, compression)
self.assertEqual(h5_d.chunks, chunking)
self.assertTrue(np.all(h5_d[()] - data < 1E-3))
os.remove(file_path)
def test_incompatible_maxshape_chunking_01(self):
name = 'test'
chunking = (3, 128)
maxshape = (1,129)
data = np.random.rand(5, 128)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, chunking=chunking, maxshape=maxshape)
def test_write_reg_ref_slice_dim_larger_than_data(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(5, 7)
h5_dset = writer._create_simple_dset(h5_f, VirtualDataset('test', data))
self.assertIsInstance(h5_dset, h5py.Dataset)
attrs = {'labels': {'even_rows': (slice(0, 15, 2), slice(None)),
'odd_rows': (slice(1, 15, 2), slice(None))}}
writer._write_dset_attributes(h5_dset, attrs.copy())
h5_f.flush()
# two atts point to region references. one for labels
self.assertEqual(len(h5_dset.attrs), 1 + len(attrs['labels']))
# check if the labels attribute was written:
self.assertTrue(np.all([x in list(attrs['labels'].keys()) for x in get_attr(h5_dset, 'labels')]))
expected_data = [data[:None:2], data[1:None:2]]
written_data = [h5_dset[h5_dset.attrs['even_rows']], h5_dset[h5_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
os.remove(file_path)
def test_generate_and_write_reg_ref_legal(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(2, 7)
h5_dset = writer._create_simple_dset(h5_f, VirtualDataset('test', data))
self.assertIsInstance(h5_dset, h5py.Dataset)
attrs = {'labels': ['row_1', 'row_2']}
if sys.version_info.major == 3:
with self.assertWarns(UserWarning):
writer._write_dset_attributes(h5_dset, attrs.copy())
else:
writer._write_dset_attributes(h5_dset, attrs.copy())
h5_f.flush()
# two atts point to region references. one for labels
self.assertEqual(len(h5_dset.attrs), 1 + len(attrs['labels']))
# check if the labels attribute was written:
self.assertTrue(np.all([x in list(attrs['labels']) for x in get_attr(h5_dset, 'labels')]))
expected_data = [data[0], data[1]]
written_data = [h5_dset[h5_dset.attrs['row_1']], h5_dset[h5_dset.attrs['row_2']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(np.squeeze(exp), np.squeeze(act)))
os.remove(file_path)
def test_empty_dset_write_success_w_options_02(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
dset_name = 'test'
maxshape = (16, 1024)
chunking = (1, 1024)
compression = 'gzip'
dtype = np.float16
microdset = VirtualDataset(dset_name, None, maxshape=maxshape,
dtype=dtype, compression=compression, chunking=chunking)
writer = HDFwriter(h5_f)
h5_d = writer._create_empty_dset(h5_f, microdset)
self.assertIsInstance(h5_d, h5py.Dataset)
self.assertEqual(h5_d.parent, h5_f)
self.assertEqual(h5_d.name, '/' + dset_name)
self.assertEqual(h5_d.dtype, dtype)
self.assertEqual(h5_d.compression, compression)
self.assertEqual(h5_d.chunks, chunking)
self.assertEqual(h5_d.shape, maxshape)
self.assertEqual(h5_d.maxshape, maxshape)
os.remove(file_path)
def test_simple_correct_01(self):
data = np.arange(5)
name = 'test'
dset = VirtualDataset(name, data)
self.assertTrue(np.all(np.equal(dset.data, data)))
self.assertEqual(dset.name, name)
self.assertEqual(dset.resizable, False)
self.assertEqual(dset.maxshape, None)
def test_large_empty_correct_01(self):
data = None
name = 'test'
maxshape = (1024, 16384)
dset = VirtualDataset(name, data, maxshape=maxshape)
self.assertEqual(dset.data, data)
self.assertEqual(dset.name, name)
self.assertEqual(dset.resizable, False)
self.assertEqual(dset.maxshape, maxshape)
def test_resizable_correct_01(self):
dtype = np.uint16
data = np.zeros(shape=(1, 7), dtype=dtype)
name = 'test'
resizable = True
dset = VirtualDataset(name, data, resizable=resizable)
self.assertTrue(np.all(np.equal(dset.data, data)))
self.assertEqual(dset.name, name)
self.assertEqual(dset.resizable, resizable)
self.assertEqual(dset.maxshape, None)
def test_simple_dset_str_dtype_valid(self):
data = np.arange(5, dtype=np.complex64)
name = 'test'
dtype = 'uint8'
dset = VirtualDataset(name, data, dtype=dtype)
self.assertTrue(np.all(np.equal(dset.data, data)))
self.assertEqual(dset.name, name)
self.assertEqual(dset.resizable, False)
self.assertEqual(dset.maxshape, None)
self.assertEqual(dset.dtype, np.dtype(dtype))
def test_correct_compression_simple_dset(self):
data = np.arange(5)
name = 'test'
compression = 'gzip'
dset = VirtualDataset(name, data, compression=compression)
self.assertTrue(np.all(np.equal(dset.data, data)))
self.assertEqual(dset.name, name)
self.assertEqual(dset.resizable, False)
self.assertEqual(dset.maxshape, None)
self.assertEqual(dset.compression, compression)
def test_write_dset_under_invalid_group(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
with self.assertRaises(KeyError):
_ = writer.write(VirtualDataset('test', np.random.rand(5, 7), parent='/does_not_exist'))
os.remove(file_path)
def test_add_single_child_legal_01(self):
dset_name_1 = 'dset_1'
data_1 = np.arange(3)
dset_1 = VirtualDataset(dset_name_1, data_1)
group_name = 'indexed_group_'
group = VirtualGroup(group_name)
group.add_children(dset_1)
group.show_tree()
self.assertEqual(len(group.children), 1)
in_dset = group.children[0]
self.assertIsInstance(in_dset, VirtualDataset)
self.assertEqual(in_dset.name, dset_name_1)
self.assertTrue(np.all(np.equal(in_dset.data, data_1)))
def test_generate_and_write_reg_ref_illegal(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(2, 7)
h5_dset = writer._create_simple_dset(h5_f, VirtualDataset('test', data))
self.assertIsInstance(h5_dset, h5py.Dataset)
# with self.assertWarns(UserWarning):
with self.assertRaises(TypeError):
writer._write_dset_attributes(h5_dset, {'labels': [1, np.arange(3)]})
os.remove(file_path)
def test_write_illegal_reg_ref_not_slice_objs(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(5, 7)
h5_dset = writer._create_simple_dset(h5_f, VirtualDataset('test', data))
self.assertIsInstance(h5_dset, h5py.Dataset)
attrs = {'labels': {'even_rows': (slice(0, None, 2), 15),
'odd_rows': (slice(1, None, 2), 'hello')}}
with self.assertRaises(TypeError):
writer._write_dset_attributes(h5_dset, attrs.copy())
os.remove(file_path)
def test_generate_and_write_reg_ref_illegal(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
writer = HDFwriter(h5_f)
data = np.random.rand(3, 7)
h5_dset = writer._create_simple_dset(h5_f, VirtualDataset('test', data))
self.assertIsInstance(h5_dset, h5py.Dataset)
# with self.assertWarns(UserWarning):
writer._write_dset_attributes(h5_dset, {'labels': ['row_1', 'row_2']})
self.assertEqual(len(h5_dset.attrs), 0)
h5_f.flush()
os.remove(file_path)
def test_empty_dset_write_success_01(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
dset_name = 'test'
maxshape = (16, 1024)
microdset = VirtualDataset(dset_name, None, maxshape=maxshape)
writer = HDFwriter(h5_f)
h5_d = writer._create_empty_dset(h5_f, microdset)
self.assertIsInstance(h5_d, h5py.Dataset)
self.assertEqual(h5_d.parent, h5_f)
self.assertEqual(h5_d.name, '/' + dset_name)
self.assertEqual(h5_d.shape, maxshape)
self.assertEqual(h5_d.maxshape, maxshape)
# dtype is assigned automatically by h5py. Not to be tested here
os.remove(file_path)
def test_simple_dset_write_success_01(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
dtype = np.uint16
dset_name = 'test'
data = np.random.randint(0, high=15, size=5, dtype=dtype)
microdset = VirtualDataset(dset_name, data)
writer = HDFwriter(h5_f)
h5_d = writer._create_simple_dset(h5_f, microdset)
self.assertIsInstance(h5_d, h5py.Dataset)
self.assertEqual(h5_d.parent, h5_f)
self.assertEqual(h5_d.name, '/' + dset_name)
self.assertEqual(h5_d.shape, data.shape)
self.assertTrue(np.allclose(h5_d[()], data))
self.assertEqual(h5_d.dtype, dtype)
os.remove(file_path)
def test_expandable_dset_write_success_01(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
dset_name = 'test'
maxshape = (None, 1024)
data = np.random.rand(1, 1024)
microdset = VirtualDataset(dset_name, data, maxshape=maxshape)
writer = HDFwriter(h5_f)
h5_d = writer._create_resizeable_dset(h5_f, microdset)
self.assertIsInstance(h5_d, h5py.Dataset)
self.assertEqual(h5_d.parent, h5_f)
self.assertEqual(h5_d.name, '/' + dset_name)
self.assertEqual(h5_d.shape, data.shape)
self.assertEqual(h5_d.maxshape, maxshape)
self.assertTrue(np.allclose(h5_d[()], data))
# Now test to make sure that the dataset can be expanded:
# TODO: add this to the example!
expansion_axis = 0
h5_d.resize(h5_d.shape[expansion_axis] + 1, axis=expansion_axis)
self.assertEqual(h5_d.shape, (data.shape[0]+1, data.shape[1]))
self.assertEqual(h5_d.maxshape, maxshape)
# Finally try checking to see if this new data is also present in the file
new_data = np.random.rand(1024)
h5_d[1] = new_data
data = np.vstack((np.squeeze(data), new_data))
self.assertTrue(np.allclose(h5_d[()], data))
os.remove(file_path)
def test_invalid_chunking_argument_02(self):
name = 'test'
chunking = ('a', range(5))
data = np.random.rand(2, 128)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, chunking=chunking)
def test_write_simple_tree(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
inner_dset_data = np.random.rand(5, 7)
inner_dset_attrs = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3'],
'labels': {'even_rows': (slice(0, None, 2), slice(None)),
'odd_rows': (slice(1, None, 2), slice(None))}
}
inner_dset = VirtualDataset('inner_dset', inner_dset_data)
inner_dset.attrs = inner_dset_attrs.copy()
attrs_inner_grp = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3']}
inner_group = VirtualGroup('indexed_inner_group_')
inner_group.attrs = attrs_inner_grp
inner_group.add_children(inner_dset)
outer_dset_data = np.random.rand(5, 7)
outer_dset_attrs = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3'],
'labels': {'even_rows': (slice(0, None, 2), slice(None)),
'odd_rows': (slice(1, None, 2), slice(None))}
}
outer_dset = VirtualDataset('test', outer_dset_data, parent='/test_group')
outer_dset.attrs = outer_dset_attrs.copy()
attrs_outer_grp = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3']}
outer_group = VirtualGroup('unindexed_outer_group')
outer_group.attrs = attrs_outer_grp
outer_group.add_children([inner_group, outer_dset])
writer = HDFwriter(h5_f)
h5_refs_list = writer.write(outer_group)
# I don't know of a more elegant way to do this:
[h5_outer_dset] = get_h5_obj_refs([outer_dset.name], h5_refs_list)
[h5_inner_dset] = get_h5_obj_refs([inner_dset.name], h5_refs_list)
[h5_outer_group] = get_h5_obj_refs([outer_group.name], h5_refs_list)
[h5_inner_group] = get_h5_obj_refs(['indexed_inner_group_000'], h5_refs_list)
self.assertIsInstance(h5_outer_dset, h5py.Dataset)
self.assertIsInstance(h5_inner_dset, h5py.Dataset)
self.assertIsInstance(h5_outer_group, h5py.Group)
self.assertIsInstance(h5_inner_group, h5py.Group)
# check assertions for the inner dataset first
self.assertEqual(h5_inner_dset.parent, h5_inner_group)
reg_ref = inner_dset_attrs.pop('labels')
self.assertEqual(len(h5_inner_dset.attrs), len(inner_dset_attrs) + 1 + len(reg_ref))
for key, expected_val in inner_dset_attrs.items():
self.assertTrue(np.all(get_attr(h5_inner_dset, key) == expected_val))
self.assertTrue(np.all([x in list(reg_ref.keys()) for x in get_attr(h5_inner_dset, 'labels')]))
expected_data = [inner_dset_data[:None:2], inner_dset_data[1:None:2]]
written_data = [h5_inner_dset[h5_inner_dset.attrs['even_rows']], h5_inner_dset[h5_inner_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
# check assertions for the inner data group next:
self.assertEqual(h5_inner_group.parent, h5_outer_group)
for key, expected_val in attrs_inner_grp.items():
self.assertTrue(np.all(get_attr(h5_inner_group, key) == expected_val))
# check the outer dataset next:
self.assertEqual(h5_outer_dset.parent, h5_outer_group)
reg_ref = outer_dset_attrs.pop('labels')
self.assertEqual(len(h5_outer_dset.attrs), len(outer_dset_attrs) + 1 + len(reg_ref))
for key, expected_val in outer_dset_attrs.items():
self.assertTrue(np.all(get_attr(h5_outer_dset, key) == expected_val))
self.assertTrue(np.all([x in list(reg_ref.keys()) for x in get_attr(h5_outer_dset, 'labels')]))
expected_data = [outer_dset_data[:None:2], outer_dset_data[1:None:2]]
written_data = [h5_outer_dset[h5_outer_dset.attrs['even_rows']],
h5_outer_dset[h5_outer_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
# Finally check the outer group:
self.assertEqual(h5_outer_group.parent, h5_f)
for key, expected_val in attrs_outer_grp.items():
self.assertTrue(np.all(get_attr(h5_outer_group, key) == expected_val))
os.remove(file_path)
def test_chunking_w_none(self):
name = 'test'
chunking = (None, 128)
data = np.random.rand(2, 128)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, chunking=chunking)
def test_incompatible_maxshape_data_shapes(self):
name = 'test'
maxshape = 128
data = np.random.rand(2, 128)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, maxshape=maxshape)
def test_incorrect_compression_simple_dset(self):
data = np.arange(5)
name = 'test'
compression = 'blah'
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, compression=compression)
def test_empty_incorrect_01(self):
data = None
name = 'test'
maxshape = (None, 16384)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, maxshape=maxshape)
def test_insufficient_inputs(self):
name = 'test'
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data=None)
def test_write_simple_tree(self):
file_path = 'test.h5'
self.__delete_existing_file(file_path)
with h5py.File(file_path) as h5_f:
inner_dset_data = np.random.rand(5, 7)
inner_dset_attrs = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3'],
'labels': {'even_rows': (slice(0, None, 2), slice(None)),
'odd_rows': (slice(1, None, 2), slice(None))}
}
inner_dset = VirtualDataset('inner_dset', inner_dset_data)
inner_dset.attrs = inner_dset_attrs.copy()
attrs_inner_grp = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3']}
inner_group = VirtualGroup('indexed_inner_group_')
inner_group.attrs = attrs_inner_grp
inner_group.add_children(inner_dset)
outer_dset_data = np.random.rand(5, 7)
outer_dset_attrs = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3'],
'labels': {'even_rows': (slice(0, None, 2), slice(None)),
'odd_rows': (slice(1, None, 2), slice(None))}
}
outer_dset = VirtualDataset('test', outer_dset_data, parent='/test_group')
outer_dset.attrs = outer_dset_attrs.copy()
attrs_outer_grp = {'att_1': 'string_val',
'att_2': 1.2345,
'att_3': [1, 2, 3, 4],
'att_4': ['str_1', 'str_2', 'str_3']}
outer_group = VirtualGroup('unindexed_outer_group')
outer_group.attrs = attrs_outer_grp
outer_group.add_children([inner_group, outer_dset])
writer = HDFwriter(h5_f)
h5_refs_list = writer.write(outer_group)
# I don't know of a more elegant way to do this:
[h5_outer_dset] = get_h5_obj_refs([outer_dset.name], h5_refs_list)
[h5_inner_dset] = get_h5_obj_refs([inner_dset.name], h5_refs_list)
[h5_outer_group] = get_h5_obj_refs([outer_group.name], h5_refs_list)
[h5_inner_group] = get_h5_obj_refs(['indexed_inner_group_000'], h5_refs_list)
self.assertIsInstance(h5_outer_dset, h5py.Dataset)
self.assertIsInstance(h5_inner_dset, h5py.Dataset)
self.assertIsInstance(h5_outer_group, h5py.Group)
self.assertIsInstance(h5_inner_group, h5py.Group)
# check assertions for the inner dataset first
self.assertEqual(h5_inner_dset.parent, h5_inner_group)
reg_ref = inner_dset_attrs.pop('labels')
self.assertEqual(len(h5_inner_dset.attrs), len(inner_dset_attrs) + 1 + len(reg_ref))
for key, expected_val in inner_dset_attrs.items():
self.assertTrue(np.all(get_attr(h5_inner_dset, key) == expected_val))
self.assertTrue(np.all([x in list(reg_ref.keys()) for x in get_attr(h5_inner_dset, 'labels')]))
expected_data = [inner_dset_data[:None:2], inner_dset_data[1:None:2]]
written_data = [h5_inner_dset[h5_inner_dset.attrs['even_rows']], h5_inner_dset[h5_inner_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
# check assertions for the inner data group next:
self.assertEqual(h5_inner_group.parent, h5_outer_group)
for key, expected_val in attrs_inner_grp.items():
self.assertTrue(np.all(get_attr(h5_inner_group, key) == expected_val))
# check the outer dataset next:
self.assertEqual(h5_outer_dset.parent, h5_outer_group)
reg_ref = outer_dset_attrs.pop('labels')
self.assertEqual(len(h5_outer_dset.attrs), len(outer_dset_attrs) + 1 + len(reg_ref))
for key, expected_val in outer_dset_attrs.items():
self.assertTrue(np.all(get_attr(h5_outer_dset, key) == expected_val))
self.assertTrue(np.all([x in list(reg_ref.keys()) for x in get_attr(h5_outer_dset, 'labels')]))
expected_data = [outer_dset_data[:None:2], outer_dset_data[1:None:2]]
written_data = [h5_outer_dset[h5_outer_dset.attrs['even_rows']],
h5_outer_dset[h5_outer_dset.attrs['odd_rows']]]
for exp, act in zip(expected_data, written_data):
self.assertTrue(np.allclose(exp, act))
# Finally check the outer group:
self.assertEqual(h5_outer_group.parent, h5_f)
for key, expected_val in attrs_outer_grp.items():
self.assertTrue(np.all(get_attr(h5_outer_group, key) == expected_val))
os.remove(file_path)
def test_incompatible_chunking_data(self):
name = 'test'
chunking = (4, 128)
data = np.random.rand(2, 128)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, data, chunking=chunking)
def test_incompatible_chunking_data_03(self):
name = 'test'
chunking = (4, 128)
maxshape = (None, 128)
with self.assertRaises(ValueError):
_ = VirtualDataset(name, None, maxshape=maxshape, chunking=chunking)
