def test_drop_obs_column():
    adata = ad.AnnData(np.array(X_list), obs=obs_dict, dtype="int32")

    subset = adata[:2]
    assert subset.is_view
    # returns a copy of obs
    assert subset.obs.drop(columns=["oanno1"]).columns.tolist() == ["oanno2", "oanno3"]
    assert subset.is_view
    # would modify obs, so it should actualize subset and not modify adata
    subset.obs.drop(columns=["oanno1"], inplace=True)
    assert not subset.is_view
    assert subset.obs.columns.tolist() == ["oanno2", "oanno3"]

    assert adata.obs.columns.tolist() == ["oanno1", "oanno2", "oanno3"]
def update_cost_model(self, x, cost_x):
        """
        Updates the GP used to handle the cost.

        param x: input of the GP for the cost model.
        param x_cost: values of the time cost at the input locations.
        """

        if self.cost_type == 'evaluation_time':
            cost_evals = np.log(np.atleast_2d(np.asarray(cost_x)).T)

            if self.num_updates == 0:
                X_all = x
                costs_all = cost_evals
            else:
                X_all = np.vstack((self.cost_model.model.X,x))
                costs_all = np.vstack((self.cost_model.model.Y,cost_evals))

            self.num_updates += 1
            self.cost_model.updateModel(X_all, costs_all, None, None)