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tests/test_incremental_pca.py::test_whitening[auto]
❯ pytest -vs tests/test_incremental_pca.py::test_whitening[auto] (base) =============================================================================================================================================================================================== test session starts =============================================================================================================================================================================================== platform darwin -- Python 3.12.8, pytest-8.3.4, pluggy-1.5.0 -- /Users/toaugspurger/gh/dask/.direnv/python-3.12/bin/python3 cachedir: .pytest_cache hypothesis profile 'default' -> database=DirectoryBasedExampleDatabase(PosixPath('/Users/toaugspurger/gh/dask/dask-ml/.hypothesis/examples')) rootdir: /Users/toaugspurger/gh/dask/dask-ml configfile: pyproject.toml plugins: cov-6.0.0, hypothesis-6.124.7, anyio-4.8.0, rerunfailures-15.0, timeout-2.3.1, mock-3.14.0, xdist-3.6.1 collected 1 item tests/test_incremental_pca.py::test_whitening[auto] FAILED ==================================================================================================================================================================================================== FAILURES ===================================================================================================================================================================================================== ______________________________________________________________________________________________________________________________________________________________________________________________ test_whitening[auto] _______________________________________________________________________________________________________________________________________________________________________________________________ svd_solver = 'auto' @pytest.mark.parametrize("svd_solver", ["full", "auto", "randomized"]) @pytest.mark.filterwarnings("ignore:invalid value:RuntimeWarning") def test_whitening(svd_solver): # Test that PCA and IncrementalPCA transforms match to sign flip. X = datasets.make_low_rank_matrix( 1000, 10, tail_strength=0.0, effective_rank=2, random_state=1999 ) X = da.from_array(X, chunks=[200, -1]) prec = 3 n_samples, n_features = X.shape for nc in [None, 9]: pca = PCA(whiten=True, n_components=nc, svd_solver=svd_solver).fit(X.compute()) ipca = IncrementalPCA( whiten=True, n_components=nc, batch_size=250, svd_solver=svd_solver ).fit(X) Xt_pca = pca.transform(X) Xt_ipca = ipca.transform(X) > assert_almost_equal(np.abs(Xt_pca), np.abs(Xt_ipca), decimal=prec) tests/test_incremental_pca.py:454: _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ ../../../miniforge3/lib/python3.12/contextlib.py:81: in inner return func(*args, **kwds) ../../../miniforge3/lib/python3.12/contextlib.py:81: in inner return func(*args, **kwds) ../.direnv/python-3.12/lib/python3.12/site-packages/numpy/_utils/__init__.py:85: in wrapper return fun(*args, **kwargs) _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ args = (<function assert_array_almost_equal.<locals>.compare at 0x131d1ac00>, array([[0.34637469, 0.64285423, 1.28803667, ...... 0.13500149]]), dask.array<absolute, shape=(1000, 10), dtype=float64, chunksize=(200, 10), chunktype=numpy.ndarray>), kwds = {'err_msg': '', 'header': 'Arrays are not almost equal to 3 decimals', 'precision': 3, 'verbose': True} @wraps(func) def inner(*args, **kwds): with self._recreate_cm(): > return func(*args, **kwds) E AssertionError: E Arrays are not almost equal to 3 decimals E E Mismatched elements: 1510 / 10000 (15.1%) E Max absolute difference among violations: 3.30337443 E Max relative difference among violations: 17.32129949 E ACTUAL: array([[0.346, 0.643, 1.288, ..., 0.853, 0.466, 0.18 ], E [0.092, 0.656, 1.029, ..., 0.886, 0.37 , 0.011], E [0.092, 1.329, 1.784, ..., 0.104, 0.396, 0.077],... E DESIRED: array([[0.346, 0.643, 1.288, ..., 0.853, 0.464, 1.238], E [0.092, 0.656, 1.029, ..., 0.886, 0.369, 0.19 ], E [0.092, 1.329, 1.784, ..., 0.104, 0.395, 0.606],... ../../../miniforge3/lib/python3.12/contextlib.py:81: AssertionError ============================================================================================================================================================================================= short test summary info ============================================================================================================================================================================================= FAILED tests/test_incremental_pca.py::test_whitening[auto] - AssertionError: ================================================================================================================================================================================================ 1 failed in 1.02s ================================================================================================================================================================================================
xref scikit-learn/scikit-learn#29534
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xref scikit-learn/scikit-learn#29534
Skipping for now.
The text was updated successfully, but these errors were encountered: