def test_dask_gradient(axis, edge_order): import dask.array as da array = np.array(np.random.randn(100, 5, 40)) x = np.exp(np.linspace(0, 1, array.shape[axis])) darray = da.from_array(array, chunks=[(6, 30, 30, 20, 14), 5, 8]) expected = gradient(array, x, axis=axis, edge_order=edge_order) actual = gradient(darray, x, axis=axis, edge_order=edge_order) assert isinstance(actual, da.Array) assert_array_equal(actual, expected)