def condense_node(self,index):
qnode=self.qlist[index]
print qnode.q
#print qnode.th
a3=[]
counts=[]
counts_err=[]
monlist=[]
for mydataitem in qnode.th:
mydata=mydataitem.data
monlist.append(mydata.metadata['count_info']['monitor'])
counts_err.append(N.array(mydata.data['counts_err']))
counts.append(N.array(mydata.data['counts']))
a3.append(N.array(mydata.data['a3']))
a3_out,counts_out,counts_err_out=simple_combine(a3,counts,counts_err,monlist)
#print a3_out.shape
#print counts_out.shape
#print counts_err_out.shape
qnode.th_condensed={}
qnode.th_condensed['a3']=a3_out
qnode.th_condensed['counts']=counts_out
qnode.th_condensed['counts_err']=counts_err_out
print qnode.th_condensed['counts'].std()
print qnode.th_condensed['counts'].mean()
print qnode.th_condensed['counts'].max()
print qnode.th_condensed['counts'].min()
if 0:
pylab.errorbar(a3_out,counts_out,counts_err_out,marker='s',linestyle='None',mfc='black',mec='black',ecolor='black')
pylab.show()
return
def condense_node(self,index):
qnode=self.qlist[index]
print qnode.q
#print qnode.th
a3=[]
counts=[]
counts_err=[]
monlist=[]
for mydataitem in qnode.th:
mydata=mydataitem.data
monlist.append(mydata.metadata['count_info']['monitor'])
counts_err.append(N.array(mydata.data['counts_err']))
counts.append(N.array(mydata.data['counts']))
a3.append(N.array(mydata.data['a3']))
a3_out,counts_out,counts_err_out=simple_combine(a3,counts,counts_err,monlist)
#print a3_out.shape
#print counts_out.shape
#print counts_err_out.shape
qnode.th_condensed={}
qnode.th_condensed['a3']=a3_out
qnode.th_condensed['counts']=counts_out
qnode.th_condensed['counts_err']=counts_err_out
print qnode.th_condensed['counts'].std()
print qnode.th_condensed['counts'].mean()
print qnode.th_condensed['counts'].max()
print qnode.th_condensed['counts'].min()
if 0:
pylab.errorbar(a3_out,counts_out,counts_err_out,marker='s',linestyle='None',mfc='black',mec='black',ecolor='black')
pylab.show()
return
Icalc=orderparameter(p,T)
residual=(I-Icalc)/Ierr
return residual
if __name__=='__main__':
mydirectory=r'c:\camn2sb2\bt9\Feb5_2008'
myfilebase='order*'
myend='bt9'
temp,I,Ierr,monlist=read_order_files(mydirectory,myfilebase,myend)
## print 'read '
## print 'temp ',temp
## print 'I',I
## print Ierr
## print 'monlist ' ,monlist
## print len(I),len(monlist)
T,I,Ierr=simple_combine.simple_combine(temp,I,Ierr,monlist)
#print temp.shape, I.shape, Ierr.shape
#pylab.errorbar(temp,I,Ierr,marker='s',linestyle='None',mfc='red',mec='red',ecolor=None)
p0=[copy.deepcopy(I[0]),84.0,.33333,copy.deepcopy(I[-1])]
tmin=30
tmax=100
Trange=N.intersect1d(N.where(T>tmin)[0],N.where(T<tmax)[0])
oparam=scipy.odr.Model(orderparameter)
mydata=scipy.odr.RealData(T[Trange],I[Trange],sx=None,sy=Ierr)
myodr = scipy.odr.ODR(mydata, oparam, beta0=p0)
myoutput=myodr.run()
myoutput.pprint()
pfit=myoutput.beta
#pfit = leastsq(residuals, p0, args=(T[Trange],I[Trange],Ierr[Trange]))
print 'pfit=',pfit
print 'chisq=',chisq_calc(pfit,T[Trange],I[Trange],Ierr[Trange]).sum()
print 'delta= ',delta a4_high,I_high,Ierr_high,Tstiched_high,mon_stiched_high=get_highT_file() a4_low,I_low,Ierr_low,Tstiched_low,mon_stiched_low=get_lowT_file() a4_high_max=max(a4_high) a4_high_min=min(a4_high) a4_low_max=max(a4_low) a4_low_min=min(a4_low) a4min=max(a4_low_min,a4_high_min) a4max=min(a4_low_max,a4_high_max) a4range_high=N.intersect1d(N.where(a4_high>a4min)[0],N.where(a4_high<a4max)[0]) a4range_low=N.intersect1d(N.where(a4_low>a4min)[0],N.where(a4_low<a4max)[0]) a4list=[a4_low,a4_high+delta] Ilist=[I_low,-I_high] Ierrlist=[Ierr_low,Ierr_high] monlist=[mon_stiched_low,mon_stiched_high] a4out,Iout,Ierrout=simple_combine.simple_combine(a4list,Ilist,Ierrlist,monlist,method='interpolate',step=0.1) print 'done' background=300.0 Iout=Iout+background myfilestr=mydirectory+'\\'+'subtracted.txt' output(a4out,Iout,Ierrout,outputfile=myfilestr) #exit() pylab.subplot(3,1,1) pylab.errorbar(a4_low,I_low,Ierr_low,linestyle='None',marker='s',mfc='blue',markersize=1.0) pylab.subplot(3,1,2) pylab.errorbar(a4_high,I_high,Ierr_high,linestyle='None',marker='s',mfc='red',markersize=2.0) pylab.subplot(3,1,3) #for delta in N.arange(-.1,.1,.01): # print delta pylab.errorbar(a4out,Iout-background,Ierrout,linestyle='None',marker='s',mfc='green',markersize=1.0) pylab.ylim((-30,30))
residual = (I - Icalc) / Ierr
return residual
if __name__ == '__main__':
mydirectory = r'c:\camn2sb2\bt9\Feb5_2008'
myfilebase = 'order*'
myend = 'bt9'
temp, I, Ierr, monlist = read_order_files(mydirectory, myfilebase, myend)
## print 'read '
## print 'temp ',temp
## print 'I',I
## print Ierr
## print 'monlist ' ,monlist
## print len(I),len(monlist)
T, I, Ierr = simple_combine.simple_combine(temp, I, Ierr, monlist)
#print temp.shape, I.shape, Ierr.shape
#pylab.errorbar(temp,I,Ierr,marker='s',linestyle='None',mfc='red',mec='red',ecolor=None)
p0 = [copy.deepcopy(I[0]), 84.0, .33333, copy.deepcopy(I[-1])]
tmin = 5
tmax = 100
#p=[Tn Jt Nf Bk]
p0 = [88.85, .9844, 1975.0, 4068.0]
if 0:
Icalc1 = meanfield.orderparameter(p0, T)
pylab.plot(T, Icalc1, marker='s', linestyle='None')
pylab.show()
Trange = N.intersect1d(N.where(T > tmin)[0], N.where(T < tmax)[0])
oparam = scipy.odr.Model(meanfield.orderparameter)
mydata = scipy.odr.RealData(T[Trange], I[Trange], sx=None, sy=Ierr)
a4_low_min = min(a4_low)
a4min = max(a4_low_min, a4_high_min)
a4max = min(a4_low_max, a4_high_max)
a4range_high = N.intersect1d(
N.where(a4_high > a4min)[0],
N.where(a4_high < a4max)[0])
a4range_low = N.intersect1d(
N.where(a4_low > a4min)[0],
N.where(a4_low < a4max)[0])
a4list = [a4_low, a4_high + delta]
Ilist = [I_low, -I_high]
Ierrlist = [Ierr_low, Ierr_high]
monlist = [mon_stiched_low, mon_stiched_high]
a4out, Iout, Ierrout = simple_combine.simple_combine(a4list,
Ilist,
Ierrlist,
monlist,
method='interpolate',
step=0.1)
print 'done'
background = 300.0
Iout = Iout + background
myfilestr = mydirectory + '\\' + 'subtracted.txt'
output(a4out, Iout, Ierrout, outputfile=myfilestr)
#exit()
pylab.subplot(3, 1, 1)
pylab.errorbar(a4_low,
I_low,
Ierr_low,
linestyle='None',
marker='s',
mfc='blue',
