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May8.py
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May8.py
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# -*- coding: utf-8 -*-
"""
Created on Sun May 10 20:32:31 2015
@author: chris
"""
from ramanTools.RamanSpectrum import *
def May8():
os.chdir('/home/chris/Documents/DataWeiss/150508')
x = RamanSpectrum('150508_01.txt')
cl = RamanSpectrum('150508_02.txt')
cl.values[:]*=2
h = RamanSpectrum('150508_04.txt')
c8 = RamanSpectrum('150508_05.txt')
ome = RamanSpectrum('150508_07.txt')
br = RamanSpectrum('150508_08.txt')
py = RamanSpectrum('150508_09.txt')
brwash = RamanSpectrum('150508_10.txt')
me = RamanSpectrum('150508_11.txt')
clf()
ax1 = subplot(121)
for i in (cl,h,ome,br,me):
i.smooth()
i.autobaseline((70,450),leaveout=(70,340),order = 4)
i.autobaseline((450,1650),order = 2, join='start')
i.plot()
legend([ 'cl', 'h', 'ome','br','me'])
ax2 = subplot(122)
for i in (x,py,c8):
i.smooth()
i.autobaseline((50,400),leaveout=(70,340),order = 4)
i.autobaseline((400,1650),order = 3, join='start')
i.plot()
legend(['x','py','c8'])
return 0
def May14():
clf()
s = RamanSpectrum('/home/chris/Documents/DataWeiss/150514/150514_12.txt')
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150514/150514_13.txt')
b = RamanSpectrum('/home/chris/Documents/DataWeiss/150514/150514_14.txt')
c = add_RamanSpectra(a,b)
# c = add_RamanSpectra(s,c)
d = RamanSpectrum('/home/chris/Documents/DataWeiss/150514/150514_15.txt')
v = RamanSpectrum('/home/chris/Documents/DataWeiss/150514/150514_16.txt')
z=0.15
e = subtract_RamanSpectra(c, d*z)
#e.smooth()
l = subtract_RamanSpectra(c,v*z)
#l.smooth()
e = RamanSpectrum(e.append(l))
e = autobaseline(e,(180,277),order = 4)
e = autobaseline(e,(277,1700),order = 4,join='start')
#j = subtract_RamanSpectra(c,RamanSpectrum(pandas.Series(f[2],f[1])))
e.plot()
#d.plot()
#v.plot()
# CdMeOTPRef.index = array(CdMeOTPRef.index)-5
(CdMeOTPRef/120).plot()
(MeOTPRef/240).plot()
return 0
def May15():
clf()
#s = RamanSpectrum('/home/chris/Documents/DataWeiss/150515/150515_02.txt')
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150515/150515_03.txt')
b = RamanSpectrum('/home/chris/Documents/DataWeiss/150515/150515_04.txt')
c = add_RamanSpectra(a,b)
c = autobaseline(c,(300,1700),order = 4)
c.smooth()
c.plot(label='Cd-enriched',color = 'k')
a= fitspectrum(c,(900,1150),'SixGaussian', [200,200,200,200,200,200,950,990,1026,1064,1087,1115,10,10,10,10,10,10,1,-100])
plot(a[1],a[2],linewidth =3,color = 'k')
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150515/150515_07.txt')
b = RamanSpectrum('/home/chris/Documents/DataWeiss/150515/150515_08.txt')
c = add_RamanSpectra(a,b)
c = autobaseline(c,(300,1700),order = 4)
c.smooth()
c.plot(label='stoichiometric',color = 'r')
# CdMeOTPRef.index = array(CdMeOTPRef.index)-5
# (CdMeOTPRef/120).plot()
# (MeOTPRef/240).plot()
(RamanSpectrum('/home/chris/Documents/DataWeiss/150511/150511_01.txt')/4).plot()
(CdODPARef/10-100).plot()
# ics('/home/chris/Orca/Successful/CdMeOTP/CdMeOTP.out')
# ics('/home/chris/Orca/CdTP_bridge/CdTP_bridgeDFT.out',color='r')
a= fitspectrum(c,(900,1150),'SixGaussian', [200,200,200,200,200,200,950,990,1026,1064,1087,1115,10,10,10,10,10,10,1,-100])
plot(a[1],a[2],linewidth =3,color = 'r')
return 0
def May16():
c = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_08.txt')
c.values[:]*=3
c = autobaseline(c,(300,1700),order =6)
c.smooth()
c.plot(label='Cd-enriched')
a= fitspectrum(c,(900,1150),'SixGaussian', [200,200,200,200,200,200,950,990,1026,1064,1087,1115,10,10,10,10,10,10,1,-100])
plot(a[1],a[2],linewidth =3,label='Cdenriched fit')
# a = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_08.txt')
# b = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_07.txt')
# c = add_RamanSpectra(a,b)
#
# c = autobaseline(c,(300,1700),order = 4)
# c.smooth()
# c.plot(label='stoichiometric')
#
# CdMeOTPRef.index = array(CdMeOTPRef.index)-5
# (CdMeOTPRef/120).plot()
# (MeOTPRef/240).plot()
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_01.txt')
b = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_02.txt')
c = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_03.txt')*4
d = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_05.txt')
e = RamanSpectrum('/home/chris/Documents/DataWeiss/150516/150516_06.txt')
a = add_RamanSpectra(a,b)
a = add_RamanSpectra(a,c)
a = add_RamanSpectra(a,d)
a = add_RamanSpectra(a,e)
a.values[:]/=10
a.plot(label='pieces')
# ics('/home/chris/Orca/Successful/CdMeOTP/CdMeOTP.out')
# ics('/home/chris/Orca/CdTP_bridge/CdTP_bridgeDFT.out',color='r')
#a= fitspectrum(a,(900,1150),'SixGaussian', [200,200,200,200,200,200,950,990,1026,1064,1087,1115,10,10,10,10,10,10,1,-100])
# plot(a[1],a[2],linewidth =3,label= 'piecesfit')
return 0
def Voigt(x,A,w0,G,g):
return A*exp(-(x-w0)**2/G)/(3.14159*((x-w0)**2+g**2))
def May18():
r = RamanSpectrum('/home/chris/Documents/DataWeiss/150518/150518_03b.txt')
r.autobaseline((100,763),order =3)
r.autobaseline((763,836),order =1,join='start')
r.autobaseline((836,1600),order =3,join='start')
r.plot()
r = RamanSpectrum('/home/chris/Documents/DataWeiss/150518/150518_05b.txt')
r.autobaseline((100,763),order =3)
r.autobaseline((763,836),order =1,join='start')
r.autobaseline((836,1650),order =3,join='start')
r.plot()
return 0
def today():
a = '/home/chris/Documents/DataWeiss/150518/'
for i in range(1,9):
r = RamanSpectrum(a+'150517_0'+str(i)+'.txt')
v = 10**7/array(r.index)-10**7/785
r = RamanSpectrum(pandas.Series(r.values,-1*v))
r.to_csv(a+'150518_0'+str(i)+'b.txt')
return 0
def May20():
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150520/150520_02.txt')
# def xGaussian(x,*guess):
# numpeaks = (len(guess)-2)/3
# y = guess[-2]*x/1000+guess[-1]
# for i in range(numpeaks):
# y+= guess[i]*exp(-(x-guess[i+numpeaks])**2/guess[i+2*numpeaks])
# return y
n_guess = [100,100,100,100,100,100,100,100,720,790,785,811,820,848,865,885,10,10,10,10,10,10,10,10,0,600]
a.plot()
b = fitspectrum(a,(700,908),'xGaussian',n_guess)
plot(b[1],b[2])
return 0
def May21():
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150521/150521stoic_dots.CSV')
a[:]-=0.2
n_guess = [0.05,0.05,0.05,0.1,0.05,0.05,0.05,0.05,0.05,0.05,
1015, 1048,1075,1100,1159,1169,1184,1204,1221,1246,
20,20,20,40,20,40,20,20,20,20,
0,0.0]
a.plot(color = 'k')
print a.nearest(1100)
print a.nearest(1300)
b = fitspectrum(a,(1000,1260),'xGaussian',n_guess)
print b.params[0]
plot(b.x,b.y,'r')
print len(b.x)
print len(b.peaks)
#plot(b.x,b.peaks[0])
for p in b.peaks:
plot(b.x,p,'b')
#pass
b = ((RamanSpectrum('/home/chris/Documents/DataWeiss/150520/150520_02.txt')-500)/10000)
b.plot()
return 0
def May21b():
clf()
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150520/150520_02.txt')
a[:]-=0.2
n_guess = [0.05,0.05,0.05,0.05,0.05,0.05,0.05,
1068,1100,1169,1184,1204,1221,1246,
20,20,20,20,20,20,20,
0,0.21]
a.plot(color = 'k')
CdODPARef.autobaseline((200,1700),order = 1)
CdODPARef.plot()
# b = RamanSpectrum('/home/chris/Documents/DataWeiss/150408/150408_02.txt')
# b = autobaseline(b,(200,1700),leaveout=(200,300), order = 4)
#b.plot()
return 0
def May27():
clf()
ax1 = subplot(121)
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150527/150527CdOPA2_from_May8_heated.CSV')
# p = [892,915,929,945,962,970,989,1005,1030,1046,1038,1061,1072,1095,1108,1135,1122]
# n_guess = [0.5]*len(p)+[0.2] + p+[1075] + [25]*len(p)+[10000] +[0,0]
#
#
# a.plot(color = 'k',marker = '.')
#
# b = fitspectrum(a,(860,1150),'xGaussian',n_guess)
# print b.params[0]
# plot(b.x,b.y,'r')
#
#
# for p in b.peaks:
# plot(b.x,p,'b')
# #pass)
p = [915,929,945,955,964,968,989,1005,1030]
n_guess = [0.5]*len(p) + p + [25]*len(p) +[0,0]
a.plot(color = 'k',marker = '.')
b = fitspectrum(a,(923,1011),'xGaussian',n_guess)
print b.params[0]
plot(b.x,b.y,'r')
for p in b.peaks:
plot(b.x,p,'b')
#pass)
ax2 = subplot(122)
a = RamanSpectrum('/home/chris/Documents/DataWeiss/150527/150527CdOPA_ala_Cao_heated.CSV')
p = [890,916,955,965]#,983,990,1008,1030,1049,1061,1071,1090,1098,1110,1120]
A = [0.2,0.05,0.4,0.1]#,0.2,0.2,0.1,0.1,0.4,0.12,0.3,0.3,0.4,0.2,0.2]
n_guess = A + p + [25]*len(p) +[0,0.03]
a.plot(color = 'k',marker = '.')
b = fitspectrum(a,(860,930),'xGaussian',n_guess)
print b.params[0]
plot(b.x,b.y,'r')
for p in b.peaks:
plot(b.x,p,'b')
#pass)
p = [965,983,990,1008,1030]#,1049,1061,1071,1090,1098,1110,1120]
A = [0.1,0.2,0.2,0.1,0.1]#0.4,0.12,0.3,0.3,0.4,0.2,0.2]
n_guess = A + p + [25]*len(p) +[0,0.03]
a.plot(color = 'k',marker = '.')
b = fitspectrum(a,(860,1017),'xGaussian',n_guess)
print b.params[0]
plot(b.x,b.y,'r')
for p in b.peaks:
plot(b.x,p,'b')
#pass)
p = [1049,1061,1071,1090,1098,1110,1120]
A = [0.4,0.12,0.3,0.3,0.4,0.2,0.2]
n_guess = A + p + [25]*len(p) +[0,0.03]
a.plot(color = 'k',marker = '.')
b = fitspectrum(a,(1017,1150),'xGaussian',n_guess)
print b.params[0]
plot(b.x,b.y,'r')
for p in b.peaks:
plot(b.x,p,'b')
#pass)
return 0