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Convert data to arrays if possible when creating datasets #48

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Convert data to arrays if possible when creating datasets #48

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acbfa33
Convert data to arrays if possible when creating datasets
simetenn May 11, 2018
eb479a5
Merge branch 'dev' into lists
simetenn May 11, 2018
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11 changes: 7 additions & 4 deletions exdir/core/group.py
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Original file line number Diff line number Diff line change
Expand Up @@ -15,7 +15,7 @@
def _data_to_shape_and_dtype(data, shape, dtype):
if data is not None:
if shape is None:
shape = data.shape
shape = np.shape(data)
if dtype is None:
dtype = data.dtype
return shape, dtype
Expand All @@ -25,10 +25,10 @@ def _data_to_shape_and_dtype(data, shape, dtype):

def _assert_data_shape_dtype_match(data, shape, dtype):
if data is not None:
if shape is not None and np.product(shape) != np.product(data.shape):
if shape is not None and np.product(shape) != np.product(np.shape(data)):
raise ValueError(
"Provided shape and data.shape do not match: {} vs {}".format(
shape, data.shape
shape, np.shape(shape)
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Looks like a typo. Should it be np.shape(data)?

)
)

Expand Down Expand Up @@ -113,12 +113,15 @@ def create_dataset(self, name, shape=None, dtype=None,

prepared_data, attrs, meta = ds._prepare_write(data, self.plugin_manager.dataset_plugins.write_order)

if not isinstance(prepared_data, np.ndarray) and prepared_data is not None:
prepared_data = np.array(prepared_data)
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Which types will be affected by this? I remember something about quantities automatically getting converted the wrong way (i.e. not by the plugin if there was no plugin) because there was some support for conversion that we didn't expect. If this only affects lists (and other types that you'd really expect to get converted to an np.array), I'm all for it. But if this may trigger some unexpected conversion that a plugin should have done when the plugin is not enabled, I think we should only add it for types we already know (such as lists).


_assert_data_shape_dtype_match(prepared_data, shape, dtype)

shape, dtype = _data_to_shape_and_dtype(prepared_data, shape, dtype)

if prepared_data is not None:
if shape is not None and prepared_data.shape != shape:
if shape is not None and np.shape(prepared_data) != shape:
prepared_data = np.reshape(prepared_data, shape)
else:
if shape is None:
Expand Down
11 changes: 11 additions & 0 deletions tests/test_dataset.py
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Expand Up @@ -102,6 +102,17 @@ def test_create_scalar_data(setup_teardown_file):
assert dset.shape == data.shape


def test_create_list_data(setup_teardown_file):
"""Create a scalar dataset from existing array."""
f = setup_teardown_file[3]
grp = f.create_group("test")

data = [1, 2, 3]
dset = grp.create_dataset('foo', data=data)
assert dset.shape == (3,)
assert np.array_equal(dset.data, np.array(data))
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Thanks for adding a test!



def test_create_extended_data(setup_teardown_file):
"""Create an extended dataset from existing data."""
f = setup_teardown_file[3]
Expand Down