def log_refl_curve(q, *prep_labels):
    generator = ReflectivityGenerator(q_values, sample)
    restored_labels = output_preprocessor.restore_labels(np.atleast_2d(prep_labels))
    model = generator.simulate_reflectivity(restored_labels, progress_bar=False)[0]
    return np.log10(model)
def log_refl_curve(q, *prep_labels):
    generator = ReflectivityGenerator(q_values, sample)
    restored_labels = output_preprocessor.restore_labels(np.atleast_2d(prep_labels))
    model = generator.simulate_reflectivity(restored_labels, progress_bar=False)[0]
    return np.log10(model)