def test_set_scalar_subset_X(matrix_type, subset_func):
    adata = ad.AnnData(matrix_type(np.zeros((10, 10))))
    orig_X_val = adata.X.copy()
    subset_idx = slice_subset(adata.obs_names)

    adata_subset = adata[subset_idx, :]

    adata_subset.X = 1

    assert adata_subset.is_view
    assert np.all(asarray(adata[subset_idx, :].X) == 1)

    assert asarray((orig_X_val != adata.X)).sum() == mul(*adata_subset.shape)
def __init__(self, cost_withGradients):
        super(CostModel, self).__init__()

        self.cost_type = cost_withGradients

        # --- Set-up evaluation cost
        if self.cost_type is None:
            self.cost_withGradients = constant_cost_withGradients
            self.cost_type = 'Constant cost'

        elif self.cost_type == 'evaluation_time':
            self.cost_model = GPModel()
            self.cost_withGradients = self._cost_gp_withGradients
            self.num_updates = 0
        else:
            self.cost_withGradients = cost_withGradients
            self.cost_type = 'User defined cost'