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.feature_vector_events(g, [2, 4], 2, n_mean=-1)
def test_correct_vector_returned(self, monkeypatch):
"""Test if function correctly constructs the feature vector. The ``prob_event_exact``
and ``prob_event_mc`` function called within ``feature_vector_events`` are
monkeypatched to return hard-coded outputs that depend only on the orbit."""
with monkeypatch.context() as m:
m.setattr(
similarity,
"prob_event_mc",
lambda _graph, photons, max_count, n_mean, samples, loss: 1.0 /
photons,
)
g = nx.complete_graph(8)
assert similarity.feature_vector_events(g, [2, 4, 8], 1,
samples=1) == [
0.5,
0.25,
0.125,
]
with monkeypatch.context() as m:
m.setattr(
similarity,
"prob_event_exact",
lambda _graph, photons, max_count, n_mean, loss: 0.5 *
(1.0 / photons),
)
g = nx.complete_graph(8)
assert similarity.feature_vector_events(
g, [2, 4, 8], 1) == [0.25, 0.125, 0.0625]
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.feature_vector_events(g, [2, 4], max_count_per_mode=-1)
def test_bad_event_photon_numbers(self):
"""Test if function raises a ``ValueError`` when input a minimum photon number that is
below zero."""
with pytest.raises(
ValueError,
match="Cannot request events with photon number below zero"):
graph = nx.complete_graph(5)
similarity.feature_vector_events(graph, [-1, 4], 2)
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.feature_vector_events(g, [2, 4], 2, loss=2)
def test_invalid_event_photon_numbers(self):
"""Test if function raises a ``ValueError`` when the list of event photons numbers
is empty."""
g = nx.complete_graph(5)
with pytest.raises(
ValueError,
match="List of photon numbers must have at least one element"):
similarity.feature_vector_events(g, [], 1)
def test_known_result(self):
"""Tests if the probability for known cases is correctly
reproduced."""
g = nx.complete_graph(4)
p = similarity.feature_vector_events(g, [2, 4], 2, 4)
assert np.allclose(p, [0.21087781178526066, 0.11998024483275889])
graph = nx.complete_graph(20)
assert np.allclose(
similarity.feature_vector_events(graph, [18, 20], 1, 1,
samples=10), [0, 0])
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)
