rm weird vectorize method

        return tuple(result) if result is not None else tuple(np.nan for _ in output_names)

    vectorized_calc = np.vectorize(

        cell_calculation, otypes=[np.float64] * len(output_names)

    )

    # TODO: loop over pvalues and save grids with pvalue noted

    # TODO: Maybe save the results as datasets iso dataarrays, and have p value be a dim?

        aquifer_ds[v] = aquifer_ds[v].where(hc_mask)

    results = xr.apply_ufunc(

        vectorized_calc,

        cell_calculation,

        x_coord,

        y_coord,

        1.0E30,

        1.0e30,

        aquifer_ds["thickness"],

        aquifer_ds["transmissivity"],

        aquifer_ds["transmissivity_with_ntg"],

        aquifer_ds["depth"],

        aquifer_ds["porosity"],

        aquifer_ds["temperature"],

        input_core_dims=[[]] * 10,

        output_core_dims=[[] for _ in output_names],

        vectorize=False,

        vectorize=True,

        dask="parallelized",

        output_dtypes=[np.float64] * len(output_names),

    )