def test_chain(self):
trafos = TransformationStub(), TransformationStub()
trafo = TransformationStub()
chained = ChainedTransformation(*trafos)
with mock.patch(
'qupulse._program.transformation.chain_transformations',
return_value='asd') as chain_transformations:
self.assertEqual(chained.chain(trafo), 'asd')
chain_transformations.assert_called_once_with(*trafos, trafo)
def test_denesting(self):
trafo = TransformationStub()
chained = ChainedTransformation(TransformationStub(),
TransformationStub())
expected = ChainedTransformation(trafo, *chained.transformations,
trafo)
result = chain_transformations(trafo, chained, trafo)
self.assertEqual(expected, result)
def test_get_output_channels(self):
trafos = TransformationStub(), TransformationStub(
), TransformationStub()
chained = ChainedTransformation(*trafos)
chans = {1}, {2}, {3}
with mock.patch.object(trafos[0], 'get_output_channels', return_value=chans[0]) as get_output_channels_0,\
mock.patch.object(trafos[1], 'get_output_channels', return_value=chans[1]) as get_output_channels_1,\
mock.patch.object(trafos[2], 'get_output_channels', return_value=chans[2]) as get_output_channels_2:
outs = chained.get_output_channels({0})
self.assertIs(outs, chans[2])
get_output_channels_0.assert_called_once_with({0})
get_output_channels_1.assert_called_once_with({1})
get_output_channels_2.assert_called_once_with({2})
def test_call(self):
trafos = TransformationStub(), TransformationStub(
), TransformationStub()
chained = ChainedTransformation(*trafos)
time = np.arange(12)
data = (np.arange(12.) + 1).reshape((3, 4))
data_in = dict(zip('abc', data))
data_0 = dict(zip('abc', data + 42))
data_1 = dict(zip('abc', data + 2 * 42))
data_2 = dict(zip('abc', data + 3 * 42))
with mock.patch(
'tests._program.transformation_tests.TransformationStub.__call__',
side_effect=[data_0, data_1, data_2]) as call:
outs = chained(time, data_in)
self.assertIs(outs, data_2)
self.assertEqual(call.call_count, 3)
for ((time_arg, data_arg),
kwargs), expected_data in zip(call.call_args_list,
[data_in, data_0, data_1]):
self.assertEqual(kwargs, {})
self.assertIs(time, time_arg)
self.assertIs(expected_data, data_arg)
def test_init_and_properties(self):
trafos = TransformationStub(), TransformationStub(
), TransformationStub()
chained = ChainedTransformation(*trafos)
self.assertEqual(chained.transformations, trafos)
self.assertIs(chained.transformations, chained.compare_key)
def test_chaining(self):
trafo = TransformationStub()
expected = ChainedTransformation(trafo, trafo)
result = chain_transformations(trafo, IdentityTransformation(), trafo)
self.assertEqual(result, expected)
def test_constant_propagation(self):
trafo = ChainedTransformation(ScalingTransformation({'a': 1.1}),
OffsetTransformation({'b': 6.6}))
self.assertTrue(trafo.is_constant_invariant())
trafo = ChainedTransformation(ScalingTransformation({'a': 1.1}),
TransformationStub())
self.assertFalse(trafo.is_constant_invariant())
def test_repr(self):
trafo = ChainedTransformation(ScalingTransformation({'a': 1.1}),
OffsetTransformation({'b': 6.6}))
self.assertEqual(trafo, eval(repr(trafo)))
