MLE Gaussian Example (fixed)

import math
import random
from pylab import hist, show

#FUNCTIONS

def getNormalizerComponent(mu,sigma,dataRange):
#make the resolution on this large.
 n=0.
 for count in range(dataRange[0]*100,dataRange[1]*100):
  #density * volume
  n+=(math.exp((-1.0/2.0)*pow(float(count)*0.01-mu,2)/pow(sigma,2)))*0.01

 return(n)


#MAIN

print "Demonstration of MLE disentangling two mixed, truncated, unnormalized Gaussians"

#DECLARE THE TRUE DATA PARAMETERS (ANSWERS)
trueSig1=0.9
trueSig2=0.9
trueMu1=4.
trueMu2=8.
trueRatio=0.2
dataSize=100.
range1=[-2,7]
range2=[4,12]


#DECLARE THE SEARCH SPACE
 #brute grid
sigma1List=[0.3,0.4,0.5,0.6,0.7,0.8,0.9]
sigma2List=[0.3,0.4,0.5,0.6,0.7,0.8,0.9]
mu1List=[1.,2.,3.,4.,5.,6.,7.,8.,9.,10.]
mu2List=[1.,2.,3.,4.,5.,6.,7.,8.,9.,10.]
ratioList=[0.1,0.2,0.3,0.4,0.5,0.6,0.7,0.8,0.9]

print "Generating Data..."
#CREATE DATA ARRAY X
x=[]
#gauss1
count=0
while count < int(dataSize*trueRatio):
 guess=random.gauss(trueMu1,trueSig1)
 if guess > range1[0] and guess < range1[1]:
  x.append(guess)
  count+=1

#gauss2
count=0
while count < int(dataSize*(1.0-trueRatio)):
 guess=random.gauss(trueMu2,trueSig2)
 if guess > range2[0] and guess < range2[1]:
  x.append(guess)
  count+=1

#hist(x)
#show()
o=open("outfile.csv","w")

#LOOP THROUGH PARAMETERS IN A BRUTE FORCE GRID SEARCH
maxProb=-99999999999
for mu1 in mu1List:
 print "Sanity Counter: "+str(mu1)
 for mu2 in mu2List:
  for sigma1 in sigma1List:
   for sigma2 in sigma2List:
    for ratio in ratioList:
     workingProb=0.

     n1=getNormalizerComponent(mu1,sigma1,range1)
     n2=getNormalizerComponent(mu2,sigma2,range2)

     for item in x:
      prob1=0.; prob2=0.;
      if range1[0] < item < range1[1]:
       prob1=(ratio)*(1./n1)*math.exp((-1.0/2.0)*pow(item-mu1,2)/pow(sigma1,2))
      if range2[0] < item < range2[1]:
       prob2=(1.-ratio)*(1./n2)*math.exp((-1.0/2.0)*pow(item-mu2,2)/pow(sigma2,2))
      workingProb+=math.log((prob1+prob2))

     o.write(str(mu1)+","+str(mu2)+","+str(sigma1)+","+str(sigma2)+","+str(ratio)+","+str(workingProb)+"\n")

     if workingProb > maxProb:
      maxProb = workingProb
      maxSigma1 = sigma1
      maxSigma2 = sigma2
      maxMu1 = mu1
      maxMu2 = mu2
      maxRatio=ratio

o.close()

print "Values (true :: max)"
print "Gaussian 1: ratio ("+str(trueRatio)+":"+str(maxRatio)+") // sigma ("+str(trueSig1)+":"+str(maxSigma1)+") // mu ("+str(trueMu1)+":"+str(maxMu1)+")."
print "Gaussian 2: ratio ("+str(1.0-trueRatio)+":"+str(1.0-maxRatio)+") //sigma ("+str(trueSig2)+":"+str(maxSigma2)+") // mu ("+str(trueMu2)+":"+str(maxMu2)+")."