def test_pipeline(data, pipeline):
expected = []
for i in range(8):
d = InputData(np.random.uniform(size=5), {'n': 5})
pipeline.send(d)
expected.append(d[np.newaxis])
expected = concatenate(expected, axis=-1).reshape((-1, 10))
assert len(data) == 1
assert data[0].shape == (4, 10)
assert np.array_equal(expected, data[0])
assert data[0].metadata == {'n': 5, 'block_size': 10}
def test_pipeline_flush(data, pipeline):
expected = []
for i in range(16):
d = InputData(np.random.uniform(size=5), {'n': 5})
pipeline.send(d)
expected.append(d[np.newaxis])
if i == 6:
pipeline.send(Ellipsis)
expected = []
expected = concatenate(expected[:8], axis=-1).reshape((-1, 10))
assert len(data) == 1
assert data[0].shape == (4, 10)
assert np.array_equal(expected, data[0])
assert data[0].metadata == expected.metadata
def test_input_data():
expected_array = np.concatenate((
np.zeros(shape=5),
np.ones(shape=5),
np.random.uniform(size=5),
))
expected_metadata = {'t0': 0}
expected_input = InputData(expected_array, expected_metadata)
input_data = [
InputData(expected_array[0:5], metadata=expected_metadata),
InputData(expected_array[5:10], metadata=expected_metadata),
InputData(expected_array[10:15], metadata=expected_metadata),
]
result = concatenate(input_data)
assert expected_input.metadata == result.metadata
assert np.array_equal(expected_input, result)