extend training range

        The reference parameters and the R-curves.

    """

    # generate the reference parameters

    # NOTE: the n-Trace model is more expressive with relaxed bounds

    parameters_ref = np.column_stack(

        [

            np.random.uniform(5.0, 7.0, n_dataset),  # electolyte_sld,

            np.random.uniform(-1.0, 7.0, n_dataset),  # electolyte_sld, including air and H2O

            np.random.uniform(5, 120, n_dataset),  # electolyte_roughness,

            np.random.uniform(-5.0, 6.5, n_dataset),  # sei_sld,

            np.random.uniform(10, 500, n_dataset),  # sei_thickness,

            np.random.uniform(1, 80, n_dataset),  # sei_roughness,

            np.random.uniform(-2, 6, n_dataset),  # material_sld,

            np.random.uniform(10, 200, n_dataset),  # material_thickness,

            np.random.uniform(1, 35, n_dataset),  # material_roughness,

            np.random.uniform(-2, 7, n_dataset),  # bulk_3_sld,

            np.random.uniform(10, 200, n_dataset),  # bulk_3_thickness,

            np.random.uniform(1, 55, n_dataset),  # bulk_3_roughness,

            np.random.uniform(6, 7, n_dataset),  # cu_sld,

            np.random.uniform(20, 700, n_dataset),  # cu_thickness,

            np.random.uniform(1, 35, n_dataset),  # cu_roughness,

            np.random.uniform(2, 7, n_dataset),  # bulk_2_sld,

            np.random.uniform(20, 700, n_dataset),  # bulk_2_thickness (cu_thickness),

            np.random.uniform(1, 55, n_dataset),  # bulk_2_roughness (cu_roughness),

            np.random.uniform(-3.5, 0, n_dataset),  # ti_sld,

            np.random.uniform(10, 100, n_dataset),  # ti_thickness,

            np.random.uniform(1, 35, n_dataset),  # ti_roughness,

            np.random.uniform(-3.5, 7, n_dataset),  # bulk_1_sld,

            np.random.uniform(10, 200, n_dataset),  # bulk_1_thickness,

            np.random.uniform(1, 55, n_dataset),  # bulk_1_roughness,

            np.random.uniform(1, 4.2, n_dataset),  # oxide_sld,

            np.random.uniform(5, 50, n_dataset),  # oxide_thickness,