[BUG] Test fail with numpy2 for stomp_squared_matrix_profile #2236
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Describe the bug
in the module similarity_searc/matrix_profiles the test function
test_stomp_squared_matrix_profilefails with numpy 2.0 if this parameter isK_VALUES = [1,3]
this is caused by the np.argsort method, which by default uses the unstable quicksort which means occasional differences in ties with the two versions.
The case K_VALUES = [1] is fixed by making this call stable, but not at all sure about case with 3. See #2216 for more details
Steps/Code to reproduce the bug
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Expected results
set K_VALUES = [1,3] and run with numpy <2.0 (passes) and numpy>=2.0 (fails)
Actual results
aeon\similarity_search\matrix_profiles\tests\test_stomp.py:45 (test_stomp_squared_matrix_profile[3-int64]) dtype = 'int64', k = 3 @pytest.mark.parametrize("dtype", DATATYPES) @pytest.mark.parametrize("k", K_VALUES) def test_stomp_squared_matrix_profile(dtype, k): """Test naive series search.""" X = np.asarray( [[[1, 2, 3, 4, 5, 6, 7, 8]], [[1, 2, 4, 4, 5, 6, 5, 4]]], dtype=dtype ) S = np.asarray([[3, 4, 5, 4, 3, 4, 5, 3, 2, 4, 5]], dtype=dtype) L = 3 mask = np.ones((X.shape[0], X.shape[2] - L + 1), dtype=bool) distance = get_distance_function("squared") mp, ip = stomp_squared_matrix_profile(X, S, L, mask, k=k) for i in range(S.shape[-1] - L + 1): q = S[:, i : i + L] expected = np.array( [ [distance(q, X[j, :, _i : _i + L]) for _i in range(X.shape[-1] - L + 1)] for j in range(X.shape[0]) ] ) id_bests = np.vstack( np.unravel_index( np.argsort(expected.ravel(), kind="stable"), expected.shape ) ).T for j in range(k): assert_almost_equal(mp[i][j], expected[id_bests[j, 0], id_bests[j, 1]]) > assert_equal(ip[i][j], id_bests[j]) L = 3 S = array([[3, 4, 5, 4, 3, 4, 5, 3, 2, 4, 5]]) X = array([[[1, 2, 3, 4, 5, 6, 7, 8]], [[1, 2, 4, 4, 5, 6, 5, 4]]]) distance = CPUDispatcher(<function squared_distance at 0x000002D04F561820>) dtype = 'int64' expected = array([[20., 11., 8., 11., 20., 35.], [21., 10., 5., 11., 8., 3.]]) i = 2 id_bests = array([[1, 5], [1, 2], [0, 2], [1, 4], [1, 1], [0, 1], [0, 3], [1, 3], [0, 0], [0, 4], [1, 0], [0, 5]]) ip = array([array([[0, 2], [1, 2], [1, 1]]), array([[1, 2], [0, 2], [1, 4]]), array([[1, 5], [1, 2], [1, 4]]), array([[1, 2], [0, 2], [0, 1]]), array([[0, 2], [1, 2], [1, 1]]), array([[1, 2], [1, 5], [1, 1]]), array([[1, 5], [1, 2], [0, 1]]), array([[0, 1], [1, 0], [0, 0]]), array([[0, 2], [1, 1], [0, 1]])], dtype=object) j = 2 k = 3 mask = array([[ True, True, True, True, True, True], [ True, True, True, True, True, True]]) mp = array([array([0., 1., 2.]), array([2., 3., 3.]), array([3., 5., 8.]), array([2., 3., 4.]), array([0., 1., 2.]), array([5., 5., 6.]), array([ 9., 11., 13.]), array([2., 4., 5.]), array([1., 1., 2.])], dtype=object) q = array([[5, 4, 3]]) test_stomp.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ..\..\..\..\venv2\lib\site-packages\numpy\_utils\__init__.py:85: in wrapper return fun(*args, **kwargs) args = (array([1, 4]), array([0, 2]), '', True) dep_version = '2.0.0' fun = <function assert_array_equal at 0x000002D04D36CD30> kwargs = {'strict': False} new_name = 'desired' new_names = ['actual', 'desired'] old_name = 'y' old_names = ['x', 'y'] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ args = (<built-in function eq>, array([1, 4]), array([0, 2])) kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True} @wraps(func) def inner(*args, **kwds): with self._recreate_cm(): > return func(*args, **kwds) E AssertionError: E Arrays are not equal E E Mismatched elements: 2 / 2 (100%) E Max absolute difference among violations: 2 E Max relative difference among violations: 1. E ACTUAL: array([1, 4]) E DESIRED: array([0, 2]) args = (<built-in function eq>, array([1, 4]), array([0, 2])) func = <function assert_array_compare at 0x000002D04D36CB80> kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True} self = <contextlib._GeneratorContextManager object at 0x000002D04D374220> C:\Users\Tony\AppData\Local\Programs\Python\Python39\lib\contextlib.py:79: AssertionError PASSED [ 73%]PASSED [ 80%]FAILED [ 86%] aeon\similarity_search\matrix_profiles\tests\test_stomp.py:45 (test_stomp_squared_matrix_profile[3-float64]) dtype = 'float64', k = 3 @pytest.mark.parametrize("dtype", DATATYPES) @pytest.mark.parametrize("k", K_VALUES) def test_stomp_squared_matrix_profile(dtype, k): """Test naive series search.""" X = np.asarray( [[[1, 2, 3, 4, 5, 6, 7, 8]], [[1, 2, 4, 4, 5, 6, 5, 4]]], dtype=dtype ) S = np.asarray([[3, 4, 5, 4, 3, 4, 5, 3, 2, 4, 5]], dtype=dtype) L = 3 mask = np.ones((X.shape[0], X.shape[2] - L + 1), dtype=bool) distance = get_distance_function("squared") mp, ip = stomp_squared_matrix_profile(X, S, L, mask, k=k) for i in range(S.shape[-1] - L + 1): q = S[:, i : i + L] expected = np.array( [ [distance(q, X[j, :, _i : _i + L]) for _i in range(X.shape[-1] - L + 1)] for j in range(X.shape[0]) ] ) id_bests = np.vstack( np.unravel_index( np.argsort(expected.ravel(), kind="stable"), expected.shape ) ).T for j in range(k): assert_almost_equal(mp[i][j], expected[id_bests[j, 0], id_bests[j, 1]]) > assert_equal(ip[i][j], id_bests[j]) L = 3 S = array([[3., 4., 5., 4., 3., 4., 5., 3., 2., 4., 5.]]) X = array([[[1., 2., 3., 4., 5., 6., 7., 8.]], [[1., 2., 4., 4., 5., 6., 5., 4.]]]) distance = CPUDispatcher(<function squared_distance at 0x000002D04F561820>) dtype = 'float64' expected = array([[20., 11., 8., 11., 20., 35.], [21., 10., 5., 11., 8., 3.]]) i = 2 id_bests = array([[1, 5], [1, 2], [0, 2], [1, 4], [1, 1], [0, 1], [0, 3], [1, 3], [0, 0], [0, 4], [1, 0], [0, 5]]) ip = array([array([[0, 2], [1, 2], [1, 1]]), array([[1, 2], [0, 2], [1, 4]]), array([[1, 5], [1, 2], [1, 4]]), array([[1, 2], [0, 2], [0, 1]]), array([[0, 2], [1, 2], [1, 1]]), array([[1, 2], [1, 5], [1, 1]]), array([[1, 5], [1, 2], [0, 1]]), array([[0, 1], [1, 0], [0, 0]]), array([[0, 2], [1, 1], [0, 1]])], dtype=object) j = 2 k = 3 mask = array([[ True, True, True, True, True, True], [ True, True, True, True, True, True]]) mp = array([array([0., 1., 2.]), array([2., 3., 3.]), array([3., 5., 8.]), array([2., 3., 4.]), array([0., 1., 2.]), array([5., 5., 6.]), array([ 9., 11., 13.]), array([2., 4., 5.]), array([1., 1., 2.])], dtype=object) q = array([[5., 4., 3.]]) test_stomp.py:76: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ..\..\..\..\venv2\lib\site-packages\numpy\_utils\__init__.py:85: in wrapper return fun(*args, **kwargs) args = (array([1, 4]), array([0, 2]), '', True) dep_version = '2.0.0' fun = <function assert_array_equal at 0x000002D04D36CD30> kwargs = {'strict': False} new_name = 'desired' new_names = ['actual', 'desired'] old_name = 'y' old_names = ['x', 'y'] _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ args = (<built-in function eq>, array([1, 4]), array([0, 2])) kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True} @wraps(func) def inner(*args, **kwds): with self._recreate_cm(): > return func(*args, **kwds) E AssertionError: E Arrays are not equal E E Mismatched elements: 2 / 2 (100%) E Max absolute difference among violations: 2 E Max relative difference among violations: 1. E ACTUAL: array([1, 4]) E DESIRED: array([0, 2]) args = (<built-in function eq>, array([1, 4]), array([0, 2])) func = <function assert_array_compare at 0x000002D04D36CB80> kwds = {'err_msg': '', 'header': 'Arrays are not equal', 'strict': False, 'verbose': True} self = <contextlib._GeneratorContextManager object at 0x000002D04D374220> C:\Users\Tony\AppData\Local\Programs\Python\Python39\lib\contextlib.py:79: AssertionErrorVersions
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