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)