def test_statistic_matrix_single_pandas():
spatial_weight_matrix = checkerboard_similarity()
known_arrangements = get_spatial_vectors_df()[["A", "B"]]
known_answers = get_known_answers()[0:2, 0:2]
passes = np.allclose(
known_answers,
leesl.statistic_matrix(known_arrangements, spatial_weight_matrix))
assert passes
def test_statistic_matrix_single_numpy():
# Switch from pandas to numpy.
spatial_weight_matrix = checkerboard_similarity().values
known_arrangements_np = get_spatial_vectors_df()[["A", "B"]].values
known_answers = get_known_answers()[0:2, 0:2]
passes = np.allclose(
known_answers,
leesl.statistic_matrix(known_arrangements_np, spatial_weight_matrix))
assert passes
def test_statistic_matrix_many_numpy():
# Switch from pandas to numpy.
spatial_weight_matrix = checkerboard_similarity().values
known_attrs = get_spatial_vectors_df().values
known_answers = get_known_answers()
passes = np.allclose(
known_answers,
leesl.statistic_matrix(known_attrs, spatial_weight_matrix))
assert passes
def test_statistic_matrix_both_sides_np():
spatial_weight_matrix = checkerboard_similarity()
known_arrangements_np = get_spatial_vectors_df().values
known_answers = get_known_answers()
passes = np.allclose(
known_answers,
leesl.statistic_matrix(known_arrangements_np, spatial_weight_matrix,
known_arrangements_np))
assert passes