def posterior_sf_compute(prior_flux, sfs):
    """
    Given prior and optimized scale factors, find the posterior scale factors.

    Parameters:
        prior_flux (numpy arr) : processed monthly prior fluxes Mxlonxlat
        sfs        (numpy arr) : obtained scale factors Mxlonxlat

    Returns:
        numpy arr (Mxlonxlat)

    NOTE:
    - keep the dimensions in mind because they can matter when flattening to
      find aggregated errors and things of that sort
    """
    assert prior_flux.shape[0] == sfs.shape[0]
    assert prior_flux.shape[1] == 72
    assert sfs.shape[1] == 72

    return prior_flux * sfs