def test_invalid_loss(self):
"""Test if function raises a ``ValueError`` when the loss parameter is specified outside
of range."""
with pytest.raises(
ValueError,
match="Loss parameter must take a value between zero and"):
sample.gaussian(*p, 1, loss=2)
def test_loss(self, monkeypatch):
"""Test if function correctly creates the SF program for lossy GBS."""
mock_eng_run = mock.MagicMock()
with monkeypatch.context() as m:
m.setattr(sf.Engine, "run", mock_eng_run)
sample.gaussian(*p, 1, loss=0.5)
p_func = mock_eng_run.call_args[0][0]
assert isinstance(p_func.circuit[-2].op, sf.ops.LossChannel)
def test_no_loss(self, monkeypatch):
"""Test if function correctly creates the SF program for GBS without loss."""
mock_eng_run = mock.MagicMock()
with monkeypatch.context() as m:
m.setattr(sf.Engine, "run", mock_eng_run)
sample.gaussian(*p, 1)
p_func = mock_eng_run.call_args[0][0]
assert not all(
[isinstance(op, sf.ops.LossChannel) for op in p_func.circuit])
def test_all_loss(self, monkeypatch):
"""Test if function samples from the vacuum when maximum loss is applied."""
dim = len(alpha)
mock_eng_run = mock.MagicMock()
with monkeypatch.context() as m:
m.setattr(sf.Engine, "run", mock_eng_run)
sample.gaussian(*p, 1, loss=1)
p_func = mock_eng_run.call_args[0][0]
eng = sf.LocalEngine(backend="gaussian")
state = eng.run(p_func).state
cov = state.cov()
disp = state.displacement()
assert np.allclose(cov, 0.5 * state.hbar * np.eye(2 * dim))
assert np.allclose(disp, np.zeros(dim))
def test_gaussian_integration(integration_sample_number):
"""Integration test for the function ``strawberryfields.gbs.sample.gaussian`` to check if
it returns samples of correct form, i.e., correct number of samples, correct number of
modes, all non-negative integers."""
samples = np.array(sample.gaussian(*p,
n_samples=integration_sample_number))
dims = samples.shape
assert len(dims) == 2
assert dims == (integration_sample_number, len(alpha))
assert samples.dtype == "int"
assert (samples >= 0).all()
def test_invalid_n_samples(self):
"""Test if function raises a ``ValueError`` when a number of samples less than one is
requested."""
with pytest.raises(ValueError,
match="Number of samples must be at least one"):
sample.gaussian(*p, -1)