PDL::Fit::Gaussian - routines for fitting gaussians

       This  file  copyright  (C) 1999, Karl Glazebrook (kgb@aaoepp.aao.gov.au), Gaussian fitting code by Alison
       Offer  (aro@aaocbn.aao.gov.au).   All  rights  reserved.  There  is  no  warranty.  You  are  allowed  to
       redistribute this software / documentation under certain conditions. For details, see the file COPYING in
       the PDL distribution. If this file is separated from the PDL distribution, the copyright notice should be
       included in the file.

perl v5.40.1                                       2025-04-12                                      Gaussian(3pm)

       May not converge for weird data, still pretty good!

       This module contains some custom gaussian fitting routines.  These were developed in collaboration with
       Alison Offer, they do a reasonably robust job and are quite useful.

       Gaussian fitting is something I do a lot of, so I figured it was worth putting in my special code.

       Note it is not clear to me that this code is fully debugged. The reason I say that is because I tried
       using the internal linear eqn solving C routines called elsewhere and they were giving erroneous results.
       So steal from this code with caution! However it does give good fits to reasonable looking gaussians and
       tests show correct parameters.

                    KGB 29/Oct/2002

fitgauss1d
       Fit 1D Gassian to data ndarray

         ($cen, $pk, $fwhm, $back, $err, $fit) = fitgauss1d($x, $data);

         ($cen, $pk, $fwhm, $back, $err, $fit) = fitgauss1d($x, $data);

         xval(n); data(n); [o]xcentre();[o]peak_ht(); [o]fwhm();
         [o]background();int [o]err(); [o]datafit(n);
         [t]sig(n); [t]ytmp(n); [t]yytmp(n); [t]rtmp(n);

       Fits a 1D Gaussian robustly free parameters are the centre, peak height, FWHM. The background is NOT fit,
       because I find this is generally unreliable, rather a median is determined in the 'outer' 10% of pixels
       (i.e. those at the start/end of the data ndarray). The initial estimate of the FWHM is the length of the
       ndarray/3, so it might fail if the ndarray is too long. (This is non-robust anyway). Most data does just
       fine and this is a good default gaussian fitter.

       The values of the error code $err correspond to:

       0: successful fit
       1: internal problem with memory allocation
       2: insufficient number of data points
       3: fit did not converge

       SEE ALSO: fitgauss1dr() for fitting radial gaussians

   fitgauss1dr
       Fit 1D Gassian to radial data ndarray

         ($pk, $fwhm2, $back, $err, $fit) = fitgauss1dr($r, $data);

         ($pk, $fwhm2, $back, $err, $fit) = fitgauss1dr($r, $data);

         xval(n); data(n); [o]peak_ht(); [o]fwhm();
         [o]background();int [o]err(); [o]datafit(n);
         [t]sig(n); [t]ytmp(n); [t]yytmp(n); [t]rtmp(n);

       Fits a 1D radial Gaussian robustly free parameters are the peak height, FWHM. Centre is assumed to be X=0
       (i.e.  start of ndarray).  The background is NOT fit, because I find this is generally unreliable, rather
       a median is determined in the 'outer' 10% of pixels (i.e. those at the end  of  the  data  ndarray).  The
       initial estimate of the FWHM is the length of the ndarray/3, so it might fail if the ndarray is too long.
       (This is non-robust anyway). Most data does just fine and this is a good default gaussian fitter.

       The values of the error code $err correspond to:

       0: successful fit
       1: internal problem with memory allocation
       2: insufficient number of data points
       3: fit did not converge

       SEE ALSO: fitgauss1d() to fit centre as well.

       PDL::Fit::Gaussian - routines for fitting gaussians

               use PDL;
               use PDL::Fit::Gaussian;
               ($cen, $pk, $fwhm, $back, $err, $fit) = fitgauss1d($x, $data);
               ($pk, $fwhm, $back, $err, $fit) = fitgauss1dr($r, $data);