GaussianSection: User Contributed Perl Documentation (3)Updated: 2004-06-15 |
GaussianSection: User Contributed Perl Documentation (3)Updated: 2004-06-15 |
Gaussian fitting is something I do a lot of, so I figured it was worth putting in my special code.
Note this code is also used in the Karma package.
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
use PDL::Fit::Gaussian;
($cen, $pk, $fwhm, $back, $err, $fit) = fitgauss1d($x, $data);
($pk, $fwhm, $back, $err, $fit) = fitgauss1dr($r, $data);
($cen, $pk, $fwhm2, $back, $err, $fit) = fitgauss1d($x, $data);
($cen, $pk, $fwhm2, $back, $err, $fit) = fitgauss1d($x, $data);
xval(n); data(n); [o]xcentre();[o]peak_ht(); [o]fwhm(); [o]background();int [o]err(); [o]datafit(n); [t]sig(n); [t]xtmp(n); [t]ytmp(n); [t]yytmp(n); [t]rtmp(n);
Fit's a 1D Gaussian robustly free parameters are the centre, peak height, FWHM. The background is NOT fit, because I find this is generally unreliable, rather a median is determined in the 'outer' 10% of pixels (i.e. those at the start/end of the data piddle). The initial estimate of the FWHM is the length of the piddle/3, so it might fail if the piddle is too long. (This is non-robust anyway). Most data does just fine and this is a good default gaussian fitter.
SEE ALSO: fitgauss1dr() for fitting radial gaussians
($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]xtmp(n); [t]ytmp(n); [t]yytmp(n); [t]rtmp(n);
Fit's a 1D radial Gaussian robustly free parameters are the peak height, FWHM. Centre is assumed to be X=0 (i.e. start of piddle). 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 piddle). The initial estimate of the FWHM is the length of the piddle/3, so it might fail if the piddle is too long. (This is non-robust anyway). Most data does just fine and this is a good default gaussian fitter.
SEE ALSO: fitgauss1d() to fit centre as well.