def test_kneighbors_classifier(n_samples=40,
                               n_features=5,
                               n_test_pts=10,
                               n_neighbors=5,
                               random_state=0):
    # Test k-neighbors classification
    rng = np.random.RandomState(random_state)
    X = 2 * rng.rand(n_samples, n_features) - 1
    y = (.5 < (X ** 2).sum(axis=1)).astype(np.int)
    y_str = y.astype(str)

    weight_func = _weight_func

    for algorithm in ALGORITHMS:
        for weights in ['uniform', 'distance', weight_func]:
            knn = neighbors.KNeighborsClassifier(n_neighbors=n_neighbors,
                                                 weights=weights,
                                                 algorithm=algorithm)
            knn.fit(X, y)
            epsilon = 1e-5 * (2 * rng.rand(1, n_features) - 1)
            y_pred = knn.predict(X[:n_test_pts] + epsilon)
            assert_array_equal(y_pred, y[:n_test_pts])
            # Test prediction with y_str
            knn.fit(X, y_str)
            y_pred = knn.predict(X[:n_test_pts] + epsilon)
            assert_array_equal(y_pred, y_str[:n_test_pts])
dataset/ETHPy150Open scikit-learn/scikit-learn/sklearn/neighbors/tests/test_neighbors.py/test_kneighbors_classifier/swapped operands of `<`