def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
def compute_svm_cv(K, y, C=100.0, n_folds=5,
                   scoring=balanced_accuracy_scoring):
    """Compute cross-validated score of SVM with given precomputed kernel.
    """
    cv = StratifiedKFold(y, n_folds=n_folds)
    clf = SVC(C=C, kernel='precomputed', class_weight='auto')
    scores = cross_val_score(clf, K, y,
                             scoring=scoring, cv=cv)
    return scores.mean()