def test_invalid_n_mean(self):
"""Test if function raises a ``ValueError`` when the mean photon number is specified to
be negative."""
g = nx.complete_graph(5)
with pytest.raises(ValueError,
match="Mean photon number must be non-negative"):
similarity.prob_event_exact(g, 2, 2, n_mean=-1)
def test_low_count(self):
"""Test if function raises a ``ValueError`` if ``max_count_per_mode`` is negative."""
g = nx.complete_graph(5)
with pytest.raises(
ValueError,
match="Maximum number of photons per mode must be non-negative"
):
similarity.prob_event_exact(g, 2, max_count_per_mode=-1)
def test_invalid_loss(self):
"""Test if function raises a ``ValueError`` when the loss parameter is specified outside
of range."""
g = nx.complete_graph(5)
with pytest.raises(
ValueError,
match="Loss parameter must take a value between zero and one"):
similarity.prob_event_exact(g, 2, 2, loss=2)
def test_known_result(self):
"""Tests if the probability for known cases is correctly
reproduced."""
graph = nx.complete_graph(4)
p1 = similarity.prob_event_exact(graph, 2, 2, 1)
p2 = similarity.prob_event_exact(graph, 2, 1, 1)
p3 = similarity.prob_orbit_exact(graph, [1, 1], 1)
p4 = similarity.prob_event_exact(graph, 2, 2, 4)
assert np.allclose(p1 - p2, 0)
assert np.allclose(p2, p3)
assert np.allclose(p4, 0.21087781178526066)
def test_correct_result_returned(self, monkeypatch):
"""Tests if the call to _get_state function is performed correctly and probabilities over all
constituent orbits of the given event are summed correctly. The test monkeypatches the fock_prob
function so that the probability is the same for each sample permutation of all constituent orbits
and is equal to 1/8. For a 4-mode graph, an event with ``photon_number = 2``, and
``max_count_per_mode = 1`` contains orbit [1, 1] which has 6 possible sample permutations."""
graph = nx.complete_graph(4)
with monkeypatch.context() as m:
m.setattr(
"strawberryfields.backends.BaseGaussianState.fock_prob",
lambda *args, **kwargs: 1 / 8,
)
assert similarity.prob_event_exact(graph, 2, 1) == 6 / 8
def test_calls_exact_for_zero_samples(self):
"""Test if function calls the exact function for zero samples"""
g = nx.complete_graph(5)
assert similarity.feature_vector_events(
g, [2], 1, samples=0) == similarity.prob_event_exact(g, 2, 1)
def test_odd_photon_numbers(self, k, nmax):
"""Test if function returns zero probability for odd number of total photons."""
graph = nx.complete_graph(10)
assert similarity.prob_event_exact(graph, k, nmax) == 0.0
def test_prob_vacuum_event(self):
"""Tests if the function gives the right probability for an event with zero photons when
the GBS device has been configured to have zero mean photon number."""
graph = nx.complete_graph(5)
assert similarity.prob_event_exact(graph, 0, 0, 0) == 1.0
def test_invalid_photon_number(self):
"""Test if function raises a ``ValueError`` when a photon number below zero is specified"""
g = nx.complete_graph(5)
with pytest.raises(ValueError,
match="Photon number must not be below zero"):
similarity.prob_event_exact(g, -1, 2)
