vectordata indexing tests

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sneakers-the-rat 2024-08-14 00:21:06 -07:00
parent 5780947fe6
commit b610f32c4b
Signed by untrusted user who does not match committer: jonny
GPG key ID: 6DCB96EF1E4D232D

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@ -437,6 +437,37 @@ def dynamictable_assert_equal_length():
_ = MyDT(**cols) _ = MyDT(**cols)
def test_vectordata_indexing():
"""
Vectordata/VectorIndex pairs should know how to index off each other
"""
n_rows = 50
value_array, index_array = _ragged_array(n_rows)
value_array = np.concat(value_array)
data = hdmf.VectorData(value=value_array)
# before we have an index, things should work as normal, indexing a 1D array
assert data[0] == 0
index = hdmf.VectorIndex(value=index_array, target=data)
data._index = index
# after an index, both objects should index raggedly
for i in range(len(index)):
assert all(data[i] == i)
assert all(index[i] == i)
for item in (data, index):
section = item[0:3]
for i, subitem in enumerate(section):
assert all(subitem == i)
# setting uses the same indexing logic
data[0][:] = 5
assert all(data[0] == 5)
def test_vectordata_generic_numpydantic_validation(): def test_vectordata_generic_numpydantic_validation():
""" """
Using VectorData as a generic with a numpydantic array annotation should still validate Using VectorData as a generic with a numpydantic array annotation should still validate