##Preamble
from __future__ import division,print_function
import pandas as pds

rc('figure',figsize=(12,4))
rc('legend',loc='best')
rc('font',size = 14.0)
rc('font', family='serif')
rc('text', usetex=False)
rc('lines', markersize=10)

import os
from os.path import expanduser

%load_ext autoreload
%autoreload 2

import scipy.optimize as opt
from scipy import stats
import uncertainties as unc

import ProcessingCTRData as pc

print("Complete")

#Global Properties

aloc = '/home/mbrown/Desktop/doipaper/figures/' #files saved here!

wrapdict = {'wrapped':'r','unwrapped':'b','partialwrap':cm.gist_rainbow(0.4)}
errwrapdict = {'wrapped':'r','unwrapped':'b','partialwrap':'g'}
savefigures = True

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()

crystaldict = {"30A":"*","30B":"^"}  

df = df[df.length == 30]

df = df[df.specialkey == 'normal']

pp = lambda aval : '{:1.2f}'.format(aval)
for config, grp in df.groupby('configuration'):
        
    for key, grp in grp.groupby('SampleB'):
        print(config,key)
        ax.errorbar(grp.DOI,grp.CTR,yerr=grp.CTRerr,fmt='.',marker=crystaldict[key],color=wrapdict[config],ecolor=errwrapdict[config],label=key+' '+config)
        m,b = polyfit(grp.DOI,grp.CTR,1,w=grp.CTRerr)
        
        #ax.hlines(b,0,30,color='k',linestyles='dashed')
        
        print("covariance",pp(m))
        print("intercept",pp(b))
        m,c,b = polyfit(grp.DOI,grp.CTR,2,w=grp.CTRerr)
        print("covariance",pp(m))
        print("Gradient",pp(c),"intercept",pp(b))
        
        
        
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Coincidence Time Resolution (ps)")
    ax.set_xlim(-2,32)
    
    ax.set_ylim(160,300)

    
ax.legend(ncol=2)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('ctrdoi',aloc,fig)

show()
    
    

df = pds.read_csv('alldata.csv')

rc('text', usetex=True)
rc('font', family='serif')

fig, ax = subplots()
ax.grid()

crystaldict = {"30A":"*","30B":"^"}  

df = df[df.length == 30]
df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
    
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.numofsamples,yerr=sqrt(grp.numofsamples),fmt='.',marker=crystaldict[key],color=wrapdict[config],ecolor=errwrapdict[config],label=key+' '+config)
        
    ax.set_xlim(-2,32)

step = lambda x, xmin, xmax : 1/(xmax-xmin)*((x>=xmin) & (x<=xmax))

x = linspace(-5,40,500)
xs = linspace(-5,5)
y = convolve(step(x,0,30),stats.norm(scale=1/2.355).pdf(xs),mode='same')
y*=3360/max(y)

ax.plot(x,y,'k--')
ax.set_xlabel("Depth of Interaction (mm)")
ax.set_ylabel("Number of $\gamma\gamma$ events detected")
    
ax.legend(ncol=2)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('numberofsamples',aloc,fig)
#pc.savefigureadir('numberofsamples','/home/mbrown/Desktop/figures-svg',fig,ext='svg')
show()
rc('text', usetex=False)

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()

crystaldict = {"30A":"*","30B":"^"}  

df = df[df.length == 30]

df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
        
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.location,yerr=grp.locationerr,fmt='.',marker=crystaldict[key],color=wrapdict[config],ecolor=errwrapdict[config],label=key+' '+config)
    
    vals = [unc.ufloat(a,b) for a,b in zip(grp.location, grp.locationerr)]
    print(ptp(vals),"ps")
        
    linear = lambda xdata, m,c: m*xdata+c
    
    for reducelim in [30,25,20,15,12]:
        fgrp = grp[grp.DOI < reducelim]
        (m,c), err = opt.curve_fit(linear,array(fgrp['DOI']),array(fgrp['location']),sigma=fgrp['locationerr'])
        merr,cerr = err.diagonal()
        
        #X = linspace(0,30)
        #Y = linear(X,m,c)
        #ax.plot(X,Y,'k--')
        
        factor = 3E-1
        print(config,"<",reducelim,"n", unc.ufloat(m,merr)*factor)
    
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Delay Peak Centroid (ps)")
    ax.set_xlim(-2,32)
    
    ax.set_ylim(100,400)

    
ax.legend(ncol=2)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('centroidposition',aloc,fig)
#pc.savefigureadir('centroidposition','/home/mbrown/Desktop/figures-svg',fig,ext='svg')

show()
    
    

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()

crystaldict = {"30A":"*","30B":"^"}  

df = df[df.length == 30]
df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
        
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.ERright,yerr=grp.ERrighterr,fmt='.',marker=crystaldict[key],color=wrapdict[config],ecolor=errwrapdict[config],label=key+' '+config)
        
    
        
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Energy Resolution (%)")
    ax.set_xlim(-2,32)
    
ax.legend(ncol=2)

DOI = linspace(2,30,1000)
Y = lambda xdata, m, c,A : c+A/(xdata-m)**2

fdf = df[df.configuration == 'unwrapped']
param, err = opt.curve_fit(Y,fdf.DOI,fdf.ERright,sigma=fdf.ERrighterr)
for p,e in zip(param,err.diagonal()):
    val = unc.ufloat(p,e)
    print(val)
#ax.plot(DOI,Y(DOI,*param),'k--')

fig.tight_layout()

if savefigures:
    pc.savefigureadir('energyresolution',aloc,fig)
#pc.savefigureadir('energyresolution','/home/mbrown/Desktop/figures-svg',fig,ext='svg')
show()
    
    

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()

crystaldict = {"30A":"*","30B":"^"}  

df = df[df.length == 30]
df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.RPloc,yerr=grp.RPlocerr,fmt='.',marker=crystaldict[key],color=wrapdict[config],ecolor=errwrapdict[config],label=key+' '+config)
        
        
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Right Photopeak Centroid (Arb.)")
    ax.set_xlim(-2,32)
    ax.set_ylim(0.3,0.65)
    
ax.legend(ncol=2)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('lightoutput',aloc,fig)
#pc.savefigureadir('lightoutput','/home/mbrown/Desktop/figures-svg',fig,ext='svg')
show()
    
    

markerdict = {'wrapped':'*','unwrapped':'^','partialwrap':'.'}

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()


df = df[df.length == 20]
df = df[df.SampleB == '2396']
df = df[df.specialkey == 'normal']
df = df[df.CTR < 300]

lbl = {"partialwrap":"Partially Wrapped","wrapped":"Wrapped","unwrapped":"Unwrapped"}
for config, grp in df.groupby('configuration'):
    

    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.CTR,yerr=grp.CTRerr, fmt='.', marker=markerdict[config],color=wrapdict[config],ecolor=errwrapdict[config],label=lbl[config])
        print(config,key,grp.CTR.mean(),grp.CTRerr.mean())
        
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Coincidence Time Resolution (ps)")
    ax.set_xlim(-1,21)
    
    ax.set_ylim(180,290)

    
leg = ax.legend(ncol=3)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('ctrdoi-20',aloc,fig)
#pc.savefigureadir('ctrdoi-20','/home/mbrown/Desktop/figures-svg',fig,ext='svg')
show()
    
    
    
    

df = pds.read_csv('alldata.csv')
rc('text', usetex=True)
fig, ax = subplots()
ax.grid()

df = df[df.length == 20]
df = df[df.SampleB == '2396']
df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
    
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.numofsamples,yerr=sqrt(grp.numofsamples),fmt='.',marker=markerdict[config],color=wrapdict[config],ecolor=errwrapdict[config],label=lbl[config])
        
    ax.set_xlim(-1,21)
    ax.set_ylim(0,7000)

step = lambda x, xmin, xmax : 1/(xmax-xmin)*((x>=xmin) & (x<=xmax))

x = linspace(-5,40,500)
xs = linspace(-5,5)
y = convolve(step(x,0,20),stats.norm(scale=1/2.355).pdf(xs),mode='same')
y*=5000/max(y)

ax.plot(x,y,'k--')
ax.set_xlabel("Depth of Interaction (mm)")
ax.set_ylabel("Number of $\gamma\gamma$ events detected")
    
ax.legend(ncol=3)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('numberofsamples-20',aloc,fig)
#pc.savefigureadir('numberofsamples-20','/home/mbrown/Desktop/figures-svg',fig,ext='svg')
show()
rc('text', usetex=False)

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()


df = df[df.length == 20]

df = df[df.SampleB == '2396']

df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
        
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.location,yerr=grp.locationerr,fmt='.',marker=markerdict[config],color=wrapdict[config],ecolor=errwrapdict[config],label=lbl[config])
        vals = [unc.ufloat(a,b) for a,b in zip(grp.location, grp.locationerr)]
        print(ptp(vals),"ps")
        
    for reducelim in [20,15,10,8]:
        fgrp = grp[grp.DOI < reducelim]
        (m,c), err = opt.curve_fit(linear,array(fgrp['DOI']),array(fgrp['location']),sigma=fgrp['locationerr'])
        merr,cerr = err.diagonal()
        
        #X = linspace(0,30)
        #Y = linear(X,m,c)
        #ax.plot(X,Y,'k--')
        
        factor = 3E-1
        print(config,"<",reducelim,"n", unc.ufloat(m,merr)*factor)
    
    
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Delay Peak Centroid (ps)")
    ax.set_xlim(-1,21)
    
    ax.set_ylim(0,250)

    
ax.legend(ncol=3)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('centroidposition-20',aloc,fig)
#pc.savefigureadir('centroidposition-20','/home/mbrown/Desktop/figures-svg',fig,ext='svg')
show()
    
    

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()

df = df[df.length == 20]
df = df[df.SampleB == '2396']
df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
        
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.ERright,yerr=grp.ERrighterr,fmt='.',marker=markerdict[config],color=wrapdict[config],ecolor=errwrapdict[config],label=lbl[config])
        
        
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Energy Resolution (%)")
    ax.set_xlim(-1,21)
    ax.set_ylim(8,25)
    
ax.legend(ncol=3)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('energyresolution-20',aloc,fig)
#pc.savefigureadir('energyresolution-20','/home/mbrown/Desktop/figures-svg',fig,ext='svg')

show()

df = pds.read_csv('alldata.csv')

fig, ax = subplots()
ax.grid()

df = df[df.length == 20]
df = df[df.SampleB == '2396']
df = df[df.specialkey == 'normal']

for config, grp in df.groupby('configuration'):
    for key, grp in grp.groupby('SampleB'):
        ax.errorbar(grp.DOI,grp.RPloc,yerr=grp.RPlocerr,fmt='.',marker=markerdict[config],color=wrapdict[config],ecolor=errwrapdict[config],label=lbl[config])
        
        
    ax.set_xlabel("Depth of Interaction (mm)")
    ax.set_ylabel("Right Photopeak Centroid (Arb.)")
    ax.set_xlim(-1,21)
    ax.set_ylim(0.3,0.5)
    
ax.legend(ncol=3)
fig.tight_layout()

if savefigures:
    pc.savefigureadir('lightoutput-20',aloc,fig)

show()    

df = pds.read_csv('standarddata.csv')

df["person"] = df.uniquename.apply(lambda astr : astr.split('_')[-2])
df['num'] = df.uniquename.apply(lambda astr : int(astr.split('_')[-1]))

df = df[((df.person == 'MW') & (df.num == 1)) | 
        (df.length == 5) & (df.person == 'SW') & ((df.num == 4) | (df.num==25)) |
        (df.length == 10) & (df.person == 'SW') & (df.num == 1) |
        (df.length == 15) & (df.person == 'SW') & (df.num == 1) |
        (df.length == 20) & (df.person == 'SW') & ((df.num == 1) | (df.num==9)) |
        (df.length == 30) & (df.person == 'SW') & ((df.num == 1) | (df.num==9)) ]

grp = df.groupby(['length'])
fdf = grp.aggregate(np.mean)

fdf['DOI'] = 1
fdf['configuration'] = 'wrapped'
fdf['length'] = [5,10,15,20,30]

fig, ax = subplots()
ax.grid()

Cols = {'MW':'b','SW':'r'}
Marker = {'MW':'*','SW':'^'}
Lbl = {'MW' : 'Wrap 1', 'SW' : 'Wrap 2'}


for key, grp in df.groupby('person'):
    ax.errorbar(grp.length, grp.CTR, yerr=grp.CTRerr, fmt=Marker[key], color=Cols[key],label=Lbl[key])

#ax.errorbar(fdf.length, fdf.CTR, yerr=fdf.CTRError, fmt='.', color='b')
ax.set_xlim(-2,32)
ax.set_ylim(120,250)

ax.set_xlabel("Scintillator Crystal Length (mm)")
ax.set_ylabel("Coincidence Time Resolution (ps)")

ax.legend()
fig.tight_layout()

if savefigures:
    pc.savefigureadir('standardctr',aloc,fig)

show()