def test_set_varm_key(adata):
    init_hash = joblib.hash(adata)

    orig_varm_val = adata.varm["o"].copy()
    subset_varm = adata[:, :50]
    assert subset_varm.is_view
    subset_varm.varm["o"] = np.ones((50, 20))
    assert not subset_varm.is_view
    assert np.all(adata.varm["o"] == orig_varm_val)

    assert init_hash == joblib.hash(adata)
def balanced_accuracy_scoring(clf, X, y):
    """Scoring function that computes the balanced accuracy to be used
    internally in the cross-validation procedure.
    """
    y_pred = clf.predict(X)
    conf_mat = confusion_matrix(y, y_pred)
    bal_acc = 0.
    for i in range(len(conf_mat)):
        bal_acc += (float(conf_mat[i, i])) / np.sum(conf_mat[i])

    bal_acc /= len(conf_mat)
    return bal_acc