def likelihood_from_chi_squared_and_noise_normalization(chi_squared,
    noise_normalization):
    """Compute the log likelihood of each model data point's fit to the dataset, where:

    Log Likelihood = -0.5*[Chi_Squared_Term + Noise_Term] (see functions above for these definitions)

    Parameters
    ----------
    chi_squared : float
        The chi-squared term for the model-simulator fit to the dataset.
    noise_normalization : float
        The normalization noise_map-term for the dataset's noise map.
    """
    return -0.5 * (chi_squared + noise_normalization)
