def test_lower_bounds_inequalities():
"""Test that the expected inequalities are verified."""
# Toy dataset
rng = np.random.RandomState(42)
n_samples_train, n_samples_test, n_timestamps = 20, 30, 60
window_size = 0.1
X_train = rng.randn(n_samples_train, n_timestamps)
X_test = rng.randn(n_samples_test, n_timestamps)
# DTW
X_dtw = pairwise_distances(X_test, X_train, dtw)
region = sakoe_chiba_band(n_timestamps, window_size=window_size)
X_dtw_window = pairwise_distances(X_test,
X_train,
dtw_sakoechiba,
window_size=window_size)
# Lower bounds
lb_yi = lower_bound_yi(X_train, X_test)
lb_kim = lower_bound_kim(X_train, X_test)
lb_keogh = lower_bound_keogh(X_train, X_test, region)
lb_improved = lower_bound_improved(X_train, X_test, region)
# Sanity check
EPS = 1e-8
np.testing.assert_array_less(lb_yi, X_dtw + EPS)
np.testing.assert_array_less(lb_kim, X_dtw + EPS)
np.testing.assert_array_less(lb_keogh, X_dtw_window + EPS)
np.testing.assert_array_less(lb_improved, X_dtw_window + EPS)
np.testing.assert_array_less(lb_keogh, lb_improved + EPS)
def test_actual_results_lower_bound_yi(X_train, X_test, arr_desired):
"""Test that the actual results are the expected ones."""
arr_actual = lower_bound_yi(X_train, X_test)
np.testing.assert_allclose(arr_actual, arr_desired, atol=1e-5, rtol=0)
def test_check_consistent_lengths(X, Y, err_msg):
"""Test 'lower_bound_yi' parameter validation."""
with pytest.raises(ValueError, match=re.escape(err_msg)):
lower_bound_yi(X, Y)