def test_set_var(adata, subset_func):
    init_hash = joblib.hash(adata)

    subset = adata[:, subset_func(adata.var_names)]

    new_var = pd.DataFrame(
        dict(a=np.ones(subset.n_vars), b=np.ones(subset.n_vars)),
        index=subset.var_names,
    )

    assert subset.is_view
    subset.var = new_var
    assert not subset.is_view
    assert np.all(subset.var == new_var)

    assert joblib.hash(adata) == init_hash
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()