def test_correct_vector_returned(self, monkeypatch):
"""Test if function correctly constructs the feature vector. The ``prob_orbit_exact``
and ``prob_orbit_mc`` function called within ``feature_vector_orbits`` are
monkeypatched to return hard-coded outputs that depend only on the orbit."""
with monkeypatch.context() as m:
m.setattr(
similarity,
"prob_orbit_mc",
lambda _graph, orbit, n_mean, samples, loss: 1.0 / sum(orbit),
)
graph = nx.complete_graph(8)
assert similarity.feature_vector_orbits(graph, [[1, 1], [2, 1, 1]],
samples=1) == [
0.5,
0.25,
]
with monkeypatch.context() as m:
m.setattr(
similarity,
"prob_orbit_exact",
lambda _graph, orbit, n_mean, loss: 0.5 * (1.0 / sum(orbit)),
)
graph = nx.complete_graph(8)
assert similarity.feature_vector_orbits(
graph, [[1, 1], [2, 1, 1]]) == [0.25, 0.125]
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_orbits(g, [[1, 1], [2]], n_mean=-1)
def test_invalid_orbits_list(self):
"""Test if function raises a ``ValueError`` when the list of orbits is empty."""
g = nx.complete_graph(5)
with pytest.raises(
ValueError,
match="List of orbits must have at least one orbit"):
similarity.feature_vector_orbits(g, list_of_orbits=[])
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_orbits(g, [[1, 1], [2]], loss=2)
def test_bad_orbit_photon_numbers(self):
"""Test if function raises a ``ValueError`` when input is an orbit with numbers
below zero."""
graph = nx.complete_graph(5)
with pytest.raises(
ValueError,
match="Cannot request orbits with photon number below zero"):
similarity.feature_vector_orbits(graph, [[-1, 1]])
def test_known_result(self):
"""Tests if the probability for known cases is correctly
reproduced."""
graph = nx.complete_graph(4)
p = similarity.feature_vector_orbits(graph, [[1, 1], [2, 1, 1]], 2)
assert np.allclose(p, [0.22918531118334962, 0.06509669127495163])
assert np.allclose(
similarity.feature_vector_orbits(graph, [[2], [4]], 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_orbits(
g, [[1, 1]], samples=0) == similarity.prob_orbit_exact(g, [1, 1])