def fill_graph(g,etadatas,mcetadatas=None):
idx=0
for ptstr,data in etadatas.items():
parts=ptstr[2:].split('to')
avgpt=0
errptlow=0
errpthigh=0
if parts[0]=='':
avgpt=float(parts[1])
elif parts[1]=='':
avgpt=float(parts[0])*1.2
errptlow=float(parts[0])*0.2
else:
avgpt=(float(parts[0])+float(parts[1]))/2
errptlow=errpthigh=(float(parts[1])-float(parts[0]))/2
NA,NB,NC,ND=data
if NA==0 or NB==0 or NC==0 or ND==0: continue
P=1-(ND/NC)*(NA/NB)
print NA,'/',NB,'*',ND,'/',NC,P
Perr=(ND/NC)*(NA/NB)*sqrt(1/NA+1/NB+1/NC+1/ND)
if mcetadatas!=None and ptstr in mcetadatas:
NAsig,NBsig,NCsig,NDsig=mcetadatas[ptstr]
if NAsig==0 or NBsig==0 or NCsig==0 or NDsig==0: continue
# Just MC the statistical error bars, since the expression
# is too messy to do by hand
x=0
xx=0
N=10000
for trail in range(N):
P=ABCDtools.calc_mccorr(NA,NB,NC,ND,NAsig,NBsig,NCsig,NDsig)
x+=P
xx+=P*P
P=x/N
Perr=sqrt(xx/N-(x/N)**2)
# P=(-b-sqrt(b**2-4*a*c))/(2*a*NC) if a>0 else P
# Perr=sqrt(berr**2+derr**2+(b+d)**2*((aerr/a)**2+1/NC))/(2*a*NC)
# print Perr
g.SetPoint(idx,avgpt,P)
g.SetPointError(idx,errptlow,errpthigh,Perr,Perr)
idx+=1
from ROOT import *
import sys
import argparse
import binningtools
import ABCDtools
parser=argparse.ArgumentParser(description='Plot multiple purity curves.')
parser.add_argument('input',metavar='input.txt',type=str,help='Textfile with count in ABCD regions.')
parser.add_argument('mcinput',metavar='mcinput.txt',type=str,help='Textfile with MC count in ABCD regions.')
parser.add_argument('output',metavar='output.txt',type=str,help='Textfile where to save the output.')
args = parser.parse_args()
data=ABCDtools.loadABCD(args.input)
mcdata=ABCDtools.loadABCD(args.mcinput)
output=args.output
# Save
fout=open(output,'w')
for etastr in data:
for ptstr in data[etastr]:
NA,NB,NC,ND=data[etastr][ptstr]
if etastr in mcdata and ptstr in mcdata[etastr]:
NAsig,NBsig,NCsig,NDsig=mcdata[etastr][ptstr]
text='%s\t%s\t%s\n'%(etastr,ptstr,ABCDtools.calc_mccorr(NA,NB,NC,ND,NAsig,NBsig,NCsig,NDsig))
else:
text='%s\t%s\t%s\n'%(etastr,ptstr,ABCDtools.calc(NA,NB,NC,ND))
fout.write(text)
fout.close()
import ptetabinningtools
import ABCDtools
parser=argparse.ArgumentParser(description='Plot multiple purity curves.')
parser.add_argument('input',metavar='input.txt:title:color:mcinput.txt',type=str,nargs='+',help='Textfiles with the counts in ABCD regions.')
args = parser.parse_args()
datas=[]
for input in args.input:
parts=input.split(':')
input=parts[0]
title=parts[1] if len(parts)>=2 else input
color=parts[2] if len(parts)>=3 else 'kBlack'
mcinput=parts[3] if len(parts)>=4 else ''
datas.append((ABCDtools.loadABCD(input),title,eval(color),ABCDtools.loadABCD(mcinput)))
def fill_graph(g,etadatas,mcetadatas=None):
idx=0
for ptstr,data in etadatas.items():
parts=ptstr[2:].split('to')
avgpt=0
errptlow=0
errpthigh=0
if parts[0]=='':
avgpt=float(parts[1])
elif parts[1]=='':
avgpt=float(parts[0])*1.2
errptlow=float(parts[0])*0.2
else:
avgpt=(float(parts[0])+float(parts[1]))/2
