|-mask||mask Input mask (from find_mpup)|
|-max||max Intput max (from find_max)|
|-cal||arc Calibration frame|
|-reftable||arc_ref Calibration lambda reference table|
|-fit||1,1 Arc and Continuum fitting flag.|
|-tol||1.e-2 Fitting tolerance|
|-default||Read default configuration (and save it to |
|-blaze||Use blaze function in fitting process (not implemented yet)|
|-nolocal||Do not compute local adjustment to mask|
Implement the blaze option, in order to fit 0th/2nd orders weighted according to the blaze function.
Discard the need for the arc frame or for the max if they are not actually adjusted.
It is probably not a good idea to use a classical minimization scheme on such a noisy ill-conditionned problem. Maybe have a look at ``simulated annealing'' algorithm (cf.
GSL), which could be however computation-time costly.
Compute decent value for arc normalisation factor
glnormmax (arc frame mean? 1st step value?)
Fit_polynom (with automatic adjustment of polynomial degree) instead of
fit_poly_rej_nag_tab in local adjustment. Furthermore, since the sigma=f(lambda) is noisy, the sigma-clipping is not rebost enough, and one should enforce a physical selection over sigma right after pup_get_maxdata