[SciPy-User] Fitting Gaussian in spectra

[J. David Lee]

Hi,

I know I'm a bit late to the discussion, but I have some experience 
fitting emission lines. Here's what I've found to work:

*) Fit the lines and background together
*) Use the simplest reasonable model for the background: constant, 
linear, etc.
     --> You could measure the background and construct a model using 
linear interpolation
*) Put the characteristics of your detector in your model:
     -> Line-width (fwhm) vs energy
     -> Detector efficiency vs energy
*) If you know the possible lines you'll be looking for, put those in 
your model as well

If you don't know what lines to expect, but know the shape of the peaks 
you're looking for, you might look at using MPOC-MLE, which is described 
reasonably well in the paper "Pileup Correction Algorithms for 
Very-High-Count-Rate Gamma-Ray Spectrometry With NaI(Tl) Detectors" by 
M. Bolic. I've implemented a modified version of the algorithm for 
counting x-rays from detectors in pulse-mode, and it's the most robust 
algorithm I've been able to find for that purpose.

I hope this helps.

David

On 09/30/2012 03:54 AM, Jerome Kieffer wrote:
> On Sat, 29 Sep 2012 00:15:21 +0530
> Joe Philip Ninan<indiajoe at gmail.com>  wrote:
>
>> 1) fit the continuum and subtract it.
>> Or is there any other module in python/scipy which i should give a try?
>> Thanking you.
> Iteratively apply a Savitsky-Golay filter with a large width(>10) and a low order (2).
> at the begining you will only smear out the noise then start removing peaks.
>
> SG filter are really fast to apply.
>