def test_view_retains_ndarray_subclass():
    adata = ad.AnnData(np.zeros((10, 10)))
    adata.obsm["foo"] = np.zeros((10, 5)).view(NDArraySubclass)

    view = adata[:5, :]

    assert isinstance(view.obsm["foo"], NDArraySubclass)
    assert view.obsm["foo"].shape == (5, 5)
def _cost_gp_withGradients(self,x):
        """
        Predicts the time cost and its gradient of evaluating the function at x.
        """
        m, _, dmdx, _= self.cost_model.predict_withGradients(x)
        return np.exp(m), np.exp(m)*dmdx