5039cf803debf7a859f71f882fa5af46fc18bb5a,tests/test_pca.py,,test_pca_validation,#,356

Before Change

    X = np.array([[0, 1, 0], [1, 0, 0]])
    X = da.from_array(X, chunks=(2, 3))
    smallest_d = 2  // The smallest dimension
    lower_limit = {"randomized": 1, "full": 0, "auto": 0}

    for solver in solver_list:
        // We conduct the same test on X.T so that it is invariant to axis.
        // But dask-ml needs tall and skinny

After Change

            for n_components in [-1, 3]:

                with pytest.raises(ValueError, match="n_components"):
                    dd.PCA(n_components, svd_solver=solver).fit(data)

            if solver == "arpack":

                n_components = smallest_d

Instances