def test_cosine_sample_shape(seed, allclose):
""""Tests that CosineSimilarity sample has correct shape."""
# sampling (n, d) should be the exact same as sampling (n*d,)
n = 3
d = 4
dist = CosineSimilarity(2)
a = dist.sample(n, d, rng=np.random.RandomState(seed))
b = dist.sample(n * d, rng=np.random.RandomState(seed))
assert allclose(a.flatten(), b)
def test_cosine_similarity(d, rng):
"""Tests CosineSimilarity sampling."""
num_samples = 2500
num_bins = 8
# Check that it gives a single dimension from UniformHypersphere
exp_dist = UniformHypersphere(surface=True)
act_dist = CosineSimilarity(d)
exp = exp_dist.sample(num_samples, d, rng=rng)[:, 0]
act = act_dist.sample(num_samples, rng=rng)
exp_hist, _ = np.histogram(exp, bins=num_bins)
act_hist, _ = np.histogram(act, bins=num_bins)
assert np.all(np.abs(np.asfarray(exp_hist - act_hist) / num_samples) < 0.15)
