def METHOD_NAME(path_to_radex='/Users/adam/work/n2hp/',
        fileprefix='1-2_T=5to55_lvg'):
    """
    Create a n2hp fitter using RADEX data cubes.  The following files must exist::
        path_to_radex+fileprefix+'_tex1.fits'
        path_to_radex+fileprefix+'_tau1.fits'
        path_to_radex+fileprefix+'_tex2.fits'
        path_to_radex+fileprefix+'_tau2.fits'
    e.g. `/Users/adam/work/n2hp/1-2_T=5to55_lvg_tau1.fits`
    """
    # create the n2hp Radex fitter
    # This step cannot be easily generalized: the user needs to read in their own grids
    texgrid1 = pyfits.getdata(path_to_radex+fileprefix+'_tex1.fits')
    taugrid1 = pyfits.getdata(path_to_radex+fileprefix+'_tau1.fits')
    texgrid2 = pyfits.getdata(path_to_radex+fileprefix+'_tex2.fits')
    taugrid2 = pyfits.getdata(path_to_radex+fileprefix+'_tau2.fits')
    hdr    = pyfits.getheader(path_to_radex+fileprefix+'_tau2.fits')
    # this deserves a lot of explanation:
    # models.n2hp.n2hp_radex is the MODEL that we are going to fit
    # models.model.SpectralModel is a wrapper to deal with parinfo, multiple peaks,
    # and annotations
    # all of the parameters after the first are passed to the model function 
    n2hp_radex_fitter = models.model.SpectralModel(
            models.n2hp.n2hp_radex, 4,
            parnames=['density','column','center','width'], 
            parvalues=[4,12,0,1],
            parlimited=[(True,True), (True,True), (False,False), (True,False)], 
            parlimits=[(1,8), (11,16), (0,0), (0,0)],
            parsteps=[0.01,0.01,0,0],
            fitunit='Hz',
            texgrid=((4,5,texgrid1),(14,15,texgrid2)), # specify the frequency range over which the grid is valid (in GHz)
            taugrid=((4,5,taugrid1),(14,15,taugrid2)),
            hdr=hdr,
            shortvarnames=("n","N","v","\\sigma"), # specify the parameter names (TeX is OK)
            grid_vwidth_scale=False,
            )
    return n2hp_radex_fitter