import numpy as np
import matplotlib.pyplot as plt
import matplotlib.mlab as mlab
import sys
import os
broaden=float(sys.argv[1])
rawdata=open(sys.argv[2],'r').readlines()
mymin=100000.0
mymax=-100000.0
iy=0.0
peakcent=[]
peakintens=[]
for lines in range(0,len(rawdata)):
   freq=float(rawdata[lines].split()[0])
   if freq < mymin:
     mymin=freq
   if freq > mymax:
     mymax=freq
   peakcent.append(freq)
   peakintens.append(float(rawdata[lines].split()[1].strip('\n')))
if mymin < 0.0:
   mymin=0.0
points=mymax-mymin+100.0
#determines the x axis of the spectrum, and number of grid points
ix = np.linspace(mymin-50.0,mymax+50.0,points)
#peak center positions
for peaks in range(0,len(peakcent)):
    iy+=2.51225*broaden*peakintens[peaks]*mlab.normpdf(ix,peakcent[peaks],broaden)
newout1=sys.argv[2].replace('raw','fin1')
newout2=sys.argv[2].replace('raw','fin2')
np.savetxt(newout2, iy, delimiter=" ") 
np.savetxt(newout1, ix, delimiter=" ") 
var1=open(newout1,'r').readlines()
var2=open(newout2,'r').readlines()
finout=sys.argv[2].replace('raw','fin')
finwrite=open(finout,'w')
for lines in range(0,len(var1)):
   finwrite.write('%s %s\n' %(var1[lines].strip('\n'),var2[lines].strip('\n')))
os.system('rm %s\n' %(newout1))
os.system('rm %s\n' %(newout2))

#fig,ax = plt.subplots()
#ax.spines['right'].set_visible(False)
#ax.spines['top'].set_visible(False)
#ax.xaxis.set_ticks_position('bottom')
#ax.yaxis.set_ticks_position('left')
#plt.xlabel('cm-1')
#plt.ylabel('Intensity')
#plt.ylim(-0.05, 1.05)
#ax.plot(ix,iy)
#plt.show()