def test_passthrough():
node = Pipeline(steps=dummy_classifier, passthrough=True)
streamer = DummyData()
node.i_training.data = streamer.next()
node.i_training_0.data = streamer.next()
node.i_events.data = make_event('foobar')
node.i.data = streamer.next()
node.i_0.data = streamer.next()
node.i_1.data = streamer.next()
node.i.meta = {'foobar': 42}
node.update()
assert len(list(node.iterate('o*'))) == 3
assert node.o.data.equals(node.i.data)
assert node.o_0.data.equals(node.i_0.data)
assert node.o_0.data.equals(node.i_0.data)
assert node.o.meta == node.i.meta
def test_transform_3D_output(random):
pipeline = [
{'module': 'test_ml', 'class': 'Vectorizer'},
{'module': 'test_ml', 'class': 'DummyTransformer'},
{'module': 'test_ml', 'class': 'Shaper', 'args': { 'shape': (2, -1, 5) }}
]
node = Pipeline(steps=pipeline, mode='fit_transform', meta_label=None)
columns = ['A', 'B', 'C', 'D', 'E']
stream = DummyData(start_date=now())
node.i_0.data = stream.next()
node.i_1.data = stream.next()
node.i_0.data.columns = columns
node.i_1.data.columns = columns
node.i_0.meta = {'index': 0}
node.i_1.meta = {'index': 1}
node.update()
assert len(list(node.iterate('o_*'))) == 2
assert np.array_equal(node.i_0.data.index.values, node.o_0.data.index.values)
assert list(node.i_0.data.columns) == columns
assert list(node.i_1.data.columns) == columns
assert node.o_0.meta == node.i_0.meta
assert node.o_1.meta == node.i_1.meta