def test_view_delitem(attr):
    adata = gen_adata((10, 10))
    getattr(adata, attr)["to_delete"] = np.ones((10, 10))
    # Shouldn’t be a subclass, should be an ndarray
    assert type(getattr(adata, attr)["to_delete"]) is np.ndarray
    view = adata[5:7, :][:, :5]
    adata_hash = joblib.hash(adata)
    view_hash = joblib.hash(view)

    getattr(view, attr).__delitem__("to_delete")

    assert not view.is_view
    assert "to_delete" not in getattr(view, attr)
    assert "to_delete" in getattr(adata, attr)
    assert adata_hash == joblib.hash(adata)
    assert view_hash != joblib.hash(view)
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()