def test_layers_view():
    X = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]])
    L = np.array([[10, 11, 12], [13, 14, 15], [16, 17, 18]])
    real_adata = ad.AnnData(X)
    real_adata.layers["L"] = L
    view_adata = real_adata[1:, 1:]
    real_hash = joblib.hash(real_adata)
    view_hash = joblib.hash(view_adata)

    assert view_adata.is_view

    with pytest.raises(ValueError):
        view_adata.layers["L2"] = L + 2

    assert view_adata.is_view  # Failing to set layer item makes adata not view
    assert real_hash == joblib.hash(real_adata)
    assert view_hash == joblib.hash(view_adata)

    view_adata.layers["L2"] = L[1:, 1:] + 2

    assert not view_adata.is_view
    assert real_hash == joblib.hash(real_adata)
    assert view_hash != joblib.hash(view_adata)
def compute_svm_subjects(K, y, n_folds=5):
    """
    """
    cv = KFold(len(K)/2, n_folds)
    scores = np.zeros(n_folds)
    for i, (train, test) in enumerate(cv):
        train_ids = np.concatenate((train, len(K)/2+train))
        test_ids = np.concatenate((test, len(K)/2+test))
        clf = SVC(kernel='precomputed')
        clf.fit(K[train_ids, :][:, train_ids], y[train_ids])
        scores[i] = clf.score(K[test_ids, :][:, train_ids], y[test_ids])

    return scores.mean()