def test_exp_biases_extreme(temporal_graph):
rw = TemporalRandomWalk(temporal_graph)
large_times = [100000, 100001]
biases = rw._exp_biases(large_times, t_0=0, decay=True)
assert sum(biases) == pytest.approx(1)
small_times = [0.000001, 0.000002]
biases = rw._exp_biases(small_times, t_0=0, decay=True)
assert sum(biases) == pytest.approx(1)
def test_exp_biases(temporal_graph):
rw = TemporalRandomWalk(temporal_graph)
times = np.array([1, 2, 3])
t_0 = 1
expected = np.exp(t_0 - times) / sum(np.exp(t_0 - times))
biases = rw._exp_biases(times, t_0, decay=True)
assert np.allclose(biases, expected)