Gaussian line profile using numeric python

[Geoff Low]

Hi.  

I have an extensive set of xy data that I want to convolute with a gaussian
profile.  Below is my algorithm,  which doesn't work.  Can anyone see where
I'm being dumb?

import Numeric
from MLab import sum
from Numeric import arange,zeros,transpose,shape,exp,power,pi
from TableIO import readTableAsArray,TableFromColumns,writeTable
from math import sqrt

def get_data(filename):
    d = readTableAsArray(filename,'#')
    x = d[:,0]
    y = d[:,1]
    del d
    return x,y

def main(inpfile,outfile='res.out',sfreq=350,efreq=5050,stepf=2,fwhm=2.5):
    fin,iin = get_data(inpfile)
    xpt = arange(sfreq,efreq,stepf,'d')
    ypt = calcspec(fin,iin,xpt,fwhm)
    del fin,iin
    put_data(outfile,xpt,ypt)
    
def put_data(filename,x,y):
    tmp = TableFromColumns([x,y])
    tmp['filename'] = filename
    writeTable(tmp)
    del tmp
    
def calcspec(fin,iin,x,fw):
    norm,expterm = 0.0,0.0
    inten = zeros((len(x)),'d')
    norm = float(1/(sqrt(2.0*pi)*fw))
    expterm = float(1/(2*(fw**2)))
    for i in range(len(x)):
        print "Starting step ",i+1,"of ",len(x)
        print "sum fin: ",sum(fin)," sum iin: ",sum(iin) 
        print "x[",i,"] = ",x[i],"; SUM(x[",i,"] - fin) = ",sum((x[i]-fin[:]),0)
        #inten[i] = sum((norm*iin[:]*exp(-1.0*(power((expterm*(xpts[i]-fin[:])),2)))),0)
        inten[i] = norm*sum(iin[:]*exp(-1.0*(power(((x[i]-fin[:])*expterm),2))))
        #for j in range(len(fin)):
        #inten[i] = inten[i] + float(norm*iin[j]*exp(-1.0*((expterm*(xpts[i]-fin[j]))**2)))
    return inten

P.S.  I'm no math wizard but this is my interpretation of the gaussian lineshape
function
G(v) = 1/(sqrt(2*PI)*FWHM)*exp(-(v-vo)^2/(2*FWHM^2))

Cheers 
Geoff


http://www.zfree.co.nz

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