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
