| 1 |
from samplesclass import sample
|
| 2 |
from printcolor import printc
|
| 3 |
import pickle
|
| 4 |
import ROOT
|
| 5 |
from ROOT import TFile, TTree
|
| 6 |
import ROOT
|
| 7 |
from array import array
|
| 8 |
from ConfigParser import SafeConfigParser
|
| 9 |
import sys
|
| 10 |
|
| 11 |
|
| 12 |
#load config
|
| 13 |
config = SafeConfigParser()
|
| 14 |
config.read('./config')
|
| 15 |
|
| 16 |
#get locations:
|
| 17 |
Wdir=config.get('Directories','Wdir')
|
| 18 |
|
| 19 |
|
| 20 |
|
| 21 |
|
| 22 |
def getScale(job,rescale):
|
| 23 |
input = TFile.Open(job.getpath())
|
| 24 |
CountWithPU = input.Get("CountWithPU")
|
| 25 |
CountWithPU2011B = input.Get("CountWithPU2011B")
|
| 26 |
#print lumi*xsecs[i]/hist.GetBinContent(1)
|
| 27 |
return float(job.lumi)*float(job.xsec)*float(job.sf)/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*rescale/float(job.split)
|
| 28 |
|
| 29 |
|
| 30 |
def getHistoFromTree(job,options,rescale=1):
|
| 31 |
treeVar=options[0]
|
| 32 |
name=job.name
|
| 33 |
#title=job.plotname()
|
| 34 |
nBins=int(options[3])
|
| 35 |
xMin=float(options[4])
|
| 36 |
xMax=float(options[5])
|
| 37 |
|
| 38 |
if job.type != 'DATA':
|
| 39 |
cutcut=config.get('Cuts',options[7])
|
| 40 |
treeCut='%s & EventForTraining == 0'%cutcut
|
| 41 |
|
| 42 |
elif job.type == 'DATA':
|
| 43 |
treeCut=config.get('Cuts',options[8])
|
| 44 |
|
| 45 |
input = TFile.Open(job.getpath(),'read')
|
| 46 |
|
| 47 |
Tree = input.Get(job.tree)
|
| 48 |
#Tree=tmpTree.CloneTree()
|
| 49 |
#Tree.SetDirectory(0)
|
| 50 |
|
| 51 |
#Tree=tmpTree.Clone()
|
| 52 |
weightF=config.get('Weights','weightF')
|
| 53 |
#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
|
| 54 |
#hTree.SetDirectory(0)
|
| 55 |
#hTree.Sumw2()
|
| 56 |
#print 'drawing...'
|
| 57 |
if job.type != 'DATA':
|
| 58 |
#print treeCut
|
| 59 |
#print job.name
|
| 60 |
if Tree.GetEntries():
|
| 61 |
Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
|
| 62 |
full=True
|
| 63 |
else:
|
| 64 |
full=False
|
| 65 |
elif job.type == 'DATA':
|
| 66 |
|
| 67 |
if len(options)>10:
|
| 68 |
if options[11] == 'blind':
|
| 69 |
treeCut = treeCut + '&'+treeVar+'<0'
|
| 70 |
|
| 71 |
|
| 72 |
Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
|
| 73 |
full = True
|
| 74 |
if full:
|
| 75 |
hTree = ROOT.gDirectory.Get(name)
|
| 76 |
else:
|
| 77 |
hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
|
| 78 |
hTree.Sumw2()
|
| 79 |
#print job.name + ' Sumw2', hTree.GetEntries()
|
| 80 |
|
| 81 |
if job.type != 'DATA':
|
| 82 |
ScaleFactor = getScale(job,rescale)
|
| 83 |
if ScaleFactor != 0:
|
| 84 |
hTree.Scale(ScaleFactor)
|
| 85 |
|
| 86 |
print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
|
| 87 |
|
| 88 |
hTree.SetDirectory(0)
|
| 89 |
input.Close()
|
| 90 |
return hTree, job.group
|
| 91 |
|
| 92 |
|
| 93 |
######################
|
| 94 |
|
| 95 |
|
| 96 |
|
| 97 |
def orderandadd(histos,typs,setup):
|
| 98 |
#ORDER AND ADD TOGETHER
|
| 99 |
|
| 100 |
ordnung=[]
|
| 101 |
ordnungtyp=[]
|
| 102 |
num=[0]*len(setup)
|
| 103 |
for i in range(0,len(setup)):
|
| 104 |
for j in range(0,len(histos)):
|
| 105 |
if typs[j] == setup[i]:
|
| 106 |
num[i]+=1
|
| 107 |
ordnung.append(histos[j])
|
| 108 |
ordnungtyp.append(typs[j])
|
| 109 |
|
| 110 |
del histos
|
| 111 |
del typs
|
| 112 |
|
| 113 |
histos=ordnung
|
| 114 |
typs=ordnungtyp
|
| 115 |
|
| 116 |
for k in range(0,len(num)):
|
| 117 |
for m in range(0,num[k]):
|
| 118 |
if m > 0:
|
| 119 |
|
| 120 |
#add
|
| 121 |
histos[k].Add(histos[k+1],1)
|
| 122 |
#printc('red','','\t--> added %s to %s'%(typs[k],typs[k+1]))
|
| 123 |
del histos[k+1]
|
| 124 |
del typs[k+1]
|
| 125 |
|
| 126 |
del histos[len(setup):]
|
| 127 |
del typs[len(setup):]
|
| 128 |
|
| 129 |
return histos, typs
|
| 130 |
|
| 131 |
|
