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Nov6.py
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Nov6.py
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# -*- coding: utf-8 -*-
"""
Spyder Editor
This temporary script file is located here:
/home/chris/.spyder2/.temp.py
"""
from ramanTools.RamanSpectrum import *
from UVVistools import *
from scipy.special import erf
from numpy.polynomial.polynomial import polyder,polyval
from numpy.polynomial.polynomial import polyfit as pf
import weissdatavariables
def findderivative(x,y,derivorder=1):
window_len=25
# if spectrum.ndim != 1:
# raise ValueError, "smooth only accepts 1 dimension arrays."
#
# if spectrum.size < window_len:
# raise ValueError, "Input vector needs to be bigger than window size."
retval = numpy.ndarray(y.shape)
for i in range(y.size):
i_min = max(0,i-window_len/2)
i_max = min( i+window_len/2-1, y.size)
fit = pf(x[i_min:i_max+1],y[i_min:i_max+1],min(5,window_len))
retval[i] = polyval(x[i],polyder(fit,derivorder),tensor=False)
return retval
def Nov6TCSPC(guess):
"""TCSPC results from PPA capped CdS dots"""
# os.chdir('/media/cybertron_box/Chris Thompson/TCSPC Data')
os.chdir('151106/TCSPC Data')
files = ['11-6-15-chris-cds-exchanged-pH10-375exc-100psbin---433nm_em_621p83t',
'11-6-15-chris-cds-375exc-50psbin--run2-423nm_em_3797p62t',
'11-6-15-scattercell-375ex-750em-213p43t',
'11-6-15-scattercell-375ex-750em-68p68t',
'11-6-1--5-chris-cds-375exc-50psbin-423nm_em_1265p45t',
'11-6-15-chris-cds-exchanged-pH10-375exc-100psbin---433nm_em_171p27t',
'11-6-15-chris-cds-exchanged-375exc-100psbin---430nm_em_841p41t']
pH10_1 = loadtxt(files[0],unpack = True,)
oleate_2 = loadtxt(files[1],unpack = True)
IRF_1 = loadtxt(files[2],unpack = True)
IRF_2 = loadtxt(files[3],unpack = True)
oleate_1 = loadtxt(files[4],unpack = True)
pH7 = loadtxt(files[5],unpack = True)
pH10_2 = loadtxt(files[6],unpack = True)
pH10_1[1]+=pH10_2[1]
oleate_1[1]+=oleate_2[1]
IRF_1[1]+=IRF_2[1]
for i in [oleate_1, pH7, pH10_1,IRF_1]:
zero = numpy.mean(i[1,10:argmax(i[1])-10],axis = 0)
i[1]-=zero
i[1]/=max(i[1])
# t0x = argmax(IRF_1[1])
# t0 = IRF_1[0,t0x]
def gaussian(x,A,w,x0):return (A/sqrt(2*pi)/w)*exp(-(x-x0)**2/(2*w**2))
fitIRF = scipy.optimize.curve_fit(gaussian, IRF_1[0], IRF_1[1],[1,1,45])[0]
fixt0=fitIRF[2]
w = fitIRF[1]
w0 =w# w/(2*sqrt(2*log(2)))
print w0, fixt0
def fitfunction(x,*args):
y = numpy.zeros(x.shape)
t0=args[0]
for z in range((len(args)-1)/2):
A1 = args[z*2+1]
tau1 = args[z*2+2]
# y =(A1/2)*exp(w0^2/(2*tau1^2) - (t-t0)/tau1) * (1 - erf((w0^2-tau1*(t-t0))/(w0*tau1*sqrt(2))));
y+=(A1/2)*exp(w0**2/(2*tau1**2) - (x-t0)/tau1)* (1 - erf((w0**2-tau1*(x-t0))/(w0*tau1*sqrt(2)))) # / (exp(w0**2/(2*tau1**2))* (1 - erf((w0)/(tau1*sqrt(2)))))
return y
#
legend(['oleate','PPA pH7','PPA pH10', 'IRF'])
for i in [IRF_1]:
# plot(i[0],fitfunction(i[0],*guess))
fit = scipy.optimize.curve_fit(fitfunction, i[0], i[1],[44,1,0.1])[0]
print fit
plot(i[0],fitfunction(i[0],*fit),linewidth=3)
figure()
for r in range(1,4):
subplot(310+r)
i = list([oleate_1, pH7, pH10_1])[r-1]
print numpy.mean(numpy.diff(i[0]))
plot(i[0],i[1],'.')
# plot(i[0],fitfunction(i[0],*guess))
fit = scipy.optimize.curve_fit(fitfunction, i[0], i[1],guess,maxfev=3000)[0]
xlim(40,60)
ylim(-0.05,1.05)
print list(("%.2f" % i for i in fit))
plot(i[0],fitfunction(i[0],*fit),linewidth=3)
l = list([fit[0],fit[1],fit[2]])
plot(i[0],fitfunction(i[0],*l),linewidth=1)
l = list([fit[0],fit[3],fit[4]])
plot(i[0],fitfunction(i[0],*l),linewidth=1)
if len(fit)>6:
l = list([fit[0],fit[5],fit[6]])
plot(i[0],fitfunction(i[0],*l),linewidth=1)
tau = array(fit[2::2])
A = array(fit[1::2])
tau_ave = (sum(A*tau**2)/sum(A*tau))
print 'tau ave', tau_ave
annotate(['oleate','PPA pH7','PPA pH10'][r-1],(0.8,0.8),xycoords='axes fraction')
xlabel('time (ns)')
return 0
#fixt0=0
#def fitfunction(x,*args):
# y = numpy.zeros(x.shape)
# t0=fixt0
# for z in range((len(args))/2):
# print A1,tau1
# A1 = args[z*2+0]
# tau1 = args[z*2+1]
# # y =(A1/2)*exp(w0^2/(2*tau1^2) - (t-t0)/tau1) * (1 - erf((w0^2-tau1*(t-t0))/(w0*tau1*sqrt(2))));
# y+=(A1/2)*exp(w0**2/(2*tau1**2) - (x-t0)/tau1)* (1 - erf((w0**2-tau1*(x-t0))/(w0*tau1*sqrt(2))))
# return y
def Nov18():
a =loadtxt('/home/chris/Dropbox/DataWeiss/151118/Dots with untreated alumina.csv', unpack = True, delimiter = ',', skiprows = 1,usecols = (0,1,7,9,11))
s = pf(a[0][0:150],a[4][0:150],1)
a[4]-=polyval(a[0],s)
for i in a[array([1,3,4])]:#[1:]:
i-=i[150]
r = findpeak(a[0],i,(405,420))
print r
i-=i[150]
i/=r[1]
plot(a[0], i)
legend(['as prep', 'alumina 4 mg', 'alumina 5.8 mg'])
ylabel('absorbance')
xlabel('wavelength')
return 0
def Nov23():
figure()
a = loadtxt('/home/chris/Dropbox/DataWeiss/151110/ExchangeYieldforPPAexchange.csv', unpack = True, delimiter = ',', skiprows = 2,usecols = (0,1))
for i in a[1:]:
i[:]-=i[0]
r = findpeak(a[0],i,(405,420))
x = argmin(abs(a[1,0:190]-r[1]/2))
print 'FWHM', a[0,x]-r[0]
print r
print CdSconc(r),'M'
plot(a[0],i)
print '---------------'
figure()
a =loadtxt('/home/chris/Dropbox/DataWeiss/151123/151123PPAdots_forICP.csv', unpack = True, delimiter = ',', skiprows = 1,usecols = (0,1,2,3,17,18,19,21,22,23))
x = argmin(abs(a[0]-450))
for i in a[1:]:
i[:]-=i[x]
r = findpeak(a[0],i,(405,420))
print r
# print CdSconc(r)*5,'M'
plot(a[0],i)
print 'subractiing from 450'
print 'using fixed epsilon---------------'
eps = 476708.893203
# for i in a[1:]:
# i[:]-=i[x]
# r = findpeak(a[0],i,(405,420))
# conc = r[1]/eps/0.2
# #print conc,'M'
# plot(a[0],i)
return 0
def Nov25UVVis():
figure()
a = loadtxt('/home/chris/Dropbox/DataWeiss/151125/151125ppatitratin.csv', unpack = True, delimiter = ',', skiprows = 2)
for i in a[1:]:
x = argmin(abs(a[0]-450))
i[:]-=i[x]
r = findpeak(a[0],i,(405,420))
i[:]/=r[1]
print r
plot(a[0],i)
with open ('/home/chris/Dropbox/DataWeiss/151125/151125ppatitratin.csv','rb') as f:
r = f.readline().split(',')[1:]
f.close()
legend(r)
return 0