VHbb/python/gethistofromtree.py

from samplesclass import sample
from printcolor import printc
import pickle
import ROOT 
from ROOT import TFile, TTree
import ROOT
from array import array
from BetterConfigParser import BetterConfigParser
import sys


def getScale(job,path,config,rescale,subsample=-1):
    anaTag=config.get('Analysis','tag')
    input = TFile.Open(path+'/'+job.getpath())
    CountWithPU = input.Get("CountWithPU")
    CountWithPU2011B = input.Get("CountWithPU2011B")
    #print lumi*xsecs[i]/hist.GetBinContent(1)
    
    if subsample>-1:
        xsec=float(job.xsec[subsample])
        sf=float(job.sf[subsample])
    else:
        xsec=float(job.xsec)
        sf=float(job.sf)
    
    
    theScale = 1.
    if anaTag == '7TeV':
        theScale = float(job.lumi)*xsec*sf/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*rescale/float(job.split)
    elif anaTag == '8TeV':
        theScale = float(job.lumi)*xsec*sf/(CountWithPU.GetBinContent(1))*rescale/float(job.split)
    return theScale 

def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1,which_weightF='weightF'):

    #print job.getpath()
    #print options
    treeVar=options[0]
    if subsample>-1:
        name=job.subnames[subsample]
        group=job.group[subsample]
    else:
        name=job.name
        group=job.group

    #title=job.plotname()
    nBins=int(options[3])
    xMin=float(options[4])
    xMax=float(options[5])
    #addOverFlow=eval(config.get('Plot_general','addOverFlow'))
    addOverFlow = False

    TrainFlag = eval(config.get('Analysis','TrainFlag'))
    if TrainFlag: traincut = " & EventForTraining == 0"
    if not TrainFlag: traincut=""

    if job.type != 'DATA':
    
        if type(options[7])==str:
            cutcut=config.get('Cuts',options[7])
        elif type(options[7])==list:
            cutcut=config.get('Cuts',options[7][0])
            cutcut=cutcut.replace(options[7][1],options[7][2])
            #print cutcut
        if subsample>-1:
            treeCut='%s & %s%s'%(cutcut,job.subcuts[subsample],traincut)        
        else:
            treeCut='%s%s'%(cutcut,traincut)

    elif job.type == 'DATA':
        cutcut=config.get('Cuts',options[8])
        treeCut='%s'%(cutcut)


    input = TFile.Open(path+'/'+job.getpath(),'read')

    Tree = input.Get(job.tree)
    #Tree=tmpTree.CloneTree()
    #Tree.SetDirectory(0)
    
    #Tree=tmpTree.Clone()
    weightF=config.get('Weights',which_weightF)
    #hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
    #hTree.SetDirectory(0)
    #hTree.Sumw2()
    #print 'drawing...'
    if job.type != 'DATA':
        #print treeCut
        #print job.name
        if Tree.GetEntries():
            Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
            full=True
        else:
            full=False
    elif job.type == 'DATA':
    
        if len(options)>10:
            if options[11] == 'blind':
                treeCut = treeCut + '&'+treeVar+'<0'
    
    
        Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
        full = True
    if full:
        hTree = ROOT.gDirectory.Get(name)
    else:
        hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
        hTree.Sumw2()
    #print job.name + ' Sumw2', hTree.GetEntries()

    if job.type != 'DATA':
        ScaleFactor = getScale(job,path,config,rescale,subsample)
        if ScaleFactor != 0:
            hTree.Scale(ScaleFactor)
    
    if addOverFlow:
            print 'Adding overflow'
            uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
            oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
            uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
            oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
            hTree.SetBinContent(1,uFlow)
            hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
            hTree.SetBinError(1,uFlowErr)
            hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
              
            
    print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
            
    hTree.SetDirectory(0)
    input.Close()  
    
    return hTree, group
    

######################


def orderandadd(histos,typs,setup):
#ORDER AND ADD TOGETHER

    ordnung=[]
    ordnungtyp=[]
    num=[0]*len(setup)
    for i in range(0,len(setup)):
        for j in range(0,len(histos)):
            if typs[j] in setup[i]:
                num[i]+=1
                ordnung.append(histos[j])
                ordnungtyp.append(typs[j])

    del histos
    del typs

    histos=ordnung
    typs=ordnungtyp

    print typs

    for k in range(0,len(num)):
        for m in range(0,num[k]):
            if m > 0:
            
                #add
                histos[k].Add(histos[k+1],1)
                printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
                del histos[k+1]
                del typs[k+1]

    del histos[len(setup):]
    del typs[len(setup):]

    return histos, typs


Revision:	1.17
Committed:	Sun Oct 14 09:53:49 2012 UTC (12 years, 7 months ago) by peller
Content type:	text/x-python
Branch:	MAIN
CVS Tags:	hcpPreApp
Changes since 1.16:	+6 -2 lines
Log Message:	Mjj
#	User	Rev	Content
1	peller	1.1	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	nmohr	1.3	from BetterConfigParser import BetterConfigParser
9	peller	1.1	import sys
10
11
12	nmohr	1.10	def getScale(job,path,config,rescale,subsample=-1):
13			anaTag=config.get('Analysis','tag')
14	nmohr	1.9	input = TFile.Open(path+'/'+job.getpath())
15	peller	1.1	CountWithPU = input.Get("CountWithPU")
16			CountWithPU2011B = input.Get("CountWithPU2011B")
17			#print lumi*xsecs[i]/hist.GetBinContent(1)
18	peller	1.7
19			if subsample>-1:
20			xsec=float(job.xsec[subsample])
21			sf=float(job.sf[subsample])
22			else:
23			xsec=float(job.xsec)
24			sf=float(job.sf)
25
26
27	nmohr	1.6	theScale = 1.
28			if anaTag == '7TeV':
29	peller	1.7	theScale = float(job.lumi)xsecsf/(0.46502CountWithPU.GetBinContent(1)+0.53498CountWithPU2011B.GetBinContent(1))*rescale/float(job.split)
30	nmohr	1.6	elif anaTag == '8TeV':
31	peller	1.7	theScale = float(job.lumi)xsecsf/(CountWithPU.GetBinContent(1))*rescale/float(job.split)
32	nmohr	1.6	return theScale
33	peller	1.1
34	peller	1.11	def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1,which_weightF='weightF'):
35	peller	1.8
36			#print job.getpath()
37			#print options
38	peller	1.1	treeVar=options[0]
39	peller	1.7	if subsample>-1:
40			name=job.subnames[subsample]
41			group=job.group[subsample]
42			else:
43			name=job.name
44			group=job.group
45
46	peller	1.1	#title=job.plotname()
47			nBins=int(options[3])
48			xMin=float(options[4])
49			xMax=float(options[5])
50	peller	1.16	#addOverFlow=eval(config.get('Plot_general','addOverFlow'))
51			addOverFlow = False
52	peller	1.1
53	peller	1.17	TrainFlag = eval(config.get('Analysis','TrainFlag'))
54			if TrainFlag: traincut = " & EventForTraining == 0"
55			if not TrainFlag: traincut=""
56
57	peller	1.1	if job.type != 'DATA':
58	peller	1.12
59			if type(options[7])==str:
60			cutcut=config.get('Cuts',options[7])
61			elif type(options[7])==list:
62			cutcut=config.get('Cuts',options[7][0])
63			cutcut=cutcut.replace(options[7][1],options[7][2])
64	peller	1.13	#print cutcut
65	peller	1.8	if subsample>-1:
66	peller	1.17	treeCut='%s & %s%s'%(cutcut,job.subcuts[subsample],traincut)
67	peller	1.7	else:
68	peller	1.17	treeCut='%s%s'%(cutcut,traincut)
69	peller	1.1
70			elif job.type == 'DATA':
71	peller	1.5	cutcut=config.get('Cuts',options[8])
72	peller	1.8	treeCut='%s'%(cutcut)
73	peller	1.5
74	peller	1.1
75	nmohr	1.9	input = TFile.Open(path+'/'+job.getpath(),'read')
76	peller	1.1
77			Tree = input.Get(job.tree)
78			#Tree=tmpTree.CloneTree()
79			#Tree.SetDirectory(0)
80
81			#Tree=tmpTree.Clone()
82	peller	1.11	weightF=config.get('Weights',which_weightF)
83	peller	1.1	#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
84			#hTree.SetDirectory(0)
85			#hTree.Sumw2()
86			#print 'drawing...'
87			if job.type != 'DATA':
88			#print treeCut
89			#print job.name
90			if Tree.GetEntries():
91			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
92			full=True
93			else:
94			full=False
95			elif job.type == 'DATA':
96
97			if len(options)>10:
98			if options[11] == 'blind':
99			treeCut = treeCut + '&'+treeVar+'<0'
100
101
102			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
103			full = True
104			if full:
105			hTree = ROOT.gDirectory.Get(name)
106			else:
107			hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
108			hTree.Sumw2()
109			#print job.name + ' Sumw2', hTree.GetEntries()
110
111			if job.type != 'DATA':
112	nmohr	1.10	ScaleFactor = getScale(job,path,config,rescale,subsample)
113	peller	1.1	if ScaleFactor != 0:
114			hTree.Scale(ScaleFactor)
115	nmohr	1.15
116			if addOverFlow:
117			print 'Adding overflow'
118			uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
119			oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
120			uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
121			oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
122			hTree.SetBinContent(1,uFlow)
123			hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
124			hTree.SetBinError(1,uFlowErr)
125			hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
126
127	peller	1.1
128			print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
129
130			hTree.SetDirectory(0)
131	peller	1.7	input.Close()
132
133			return hTree, group
134	peller	1.1
135
136			######################
137
138
139
140			def orderandadd(histos,typs,setup):
141			#ORDER AND ADD TOGETHER
142
143			ordnung=[]
144			ordnungtyp=[]
145			num=[0]*len(setup)
146			for i in range(0,len(setup)):
147			for j in range(0,len(histos)):
148	peller	1.2	if typs[j] in setup[i]:
149	peller	1.1	num[i]+=1
150			ordnung.append(histos[j])
151			ordnungtyp.append(typs[j])
152
153			del histos
154			del typs
155
156			histos=ordnung
157			typs=ordnungtyp
158
159	peller	1.14	print typs
160
161	peller	1.1	for k in range(0,len(num)):
162			for m in range(0,num[k]):
163			if m > 0:
164
165			#add
166			histos[k].Add(histos[k+1],1)
167	peller	1.2	printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
168	peller	1.1	del histos[k+1]
169			del typs[k+1]
170
171			del histos[len(setup):]
172			del typs[len(setup):]
173
174			return histos, typs
175
176