def test_distribution_equivalent_implementation(self, num_items,
num_slots):
distribution = np.vstack(
utils.distribute(num_items, num_slots, normalize=False))
other_implementation = _generate_prob_profiles(num_items, num_slots)
np.testing.assert_array_equal(
utils.sort_rows_lexicographically(distribution),
utils.sort_rows_lexicographically(other_implementation))
def test_from_elo_scores(self):
elo_scores = [800, 400, 400]
elo_1 = 10**(800 / 400)
elo_2 = 10**(400 / 400
) # This is also the associated value for player 3.
expected = np.asarray([
[2, 0, 0, 1 / 2, 0, 0],
[0, 2, 0, 0, 1 / 2, 0],
[0, 0, 2, 0, 0, 1 / 2],
[1, 1, 0, elo_1 / (elo_1 + elo_2), elo_2 / (elo_1 + elo_2), 0],
[1, 0, 1, elo_1 / (elo_1 + elo_2), 0, elo_2 / (elo_1 + elo_2)],
[0, 1, 1, 0, 1 / 2, 1 / 2],
])
htp = heuristic_payoff_table.from_elo_scores(elo_scores)
np.testing.assert_array_almost_equal(
utils.sort_rows_lexicographically(expected),
utils.sort_rows_lexicographically(htp()),
verbose=True)
def test_sort_rows_lexicographically(self):
array = np.asarray([
[1, 1, 0],
[1, 2, 0],
[3, 1, 0],
[0, 0, 4],
])
expected = np.asarray([
[0, 0, 4],
[1, 1, 0],
[1, 2, 0],
[3, 1, 0],
])
np.testing.assert_equal(expected,
utils.sort_rows_lexicographically(array))