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')
    inputfile = TFile.Open(path+'/'+job.getpath())
    CountWithPU = inputfile.Get("CountWithPU")
    CountWithPU2011B = inputfile.Get("CountWithPU2011B")
    #print lumi*xsecs[i]/hist.GetBinContent(1)
    
    if subsample>-1:
        if type(job.xsec[subsample]) == str: xsec=float(eval(job.xsec[subsample]))
        else: xsec=float(job.xsec[subsample])
        sf=float(job.sf[subsample])
    else:
        if type(job.xsec) == str: xsec=float(eval(job.xsec))
        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)
    inputfile.Close()
    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] == 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:	1.21
Committed:	Wed Dec 5 15:00:20 2012 UTC (12 years, 5 months ago) by peller
Content type:	text/x-python
Branch:	MAIN
Changes since 1.20:	+4 -4 lines
Log Message:	individual BKGd trainings
#	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	peller	1.21	inputfile = TFile.Open(path+'/'+job.getpath())
15			CountWithPU = inputfile.Get("CountWithPU")
16			CountWithPU2011B = inputfile.Get("CountWithPU2011B")
17	peller	1.1	#print lumi*xsecs[i]/hist.GetBinContent(1)
18	peller	1.7
19			if subsample>-1:
20	peller	1.18	if type(job.xsec[subsample]) == str: xsec=float(eval(job.xsec[subsample]))
21			else: xsec=float(job.xsec[subsample])
22	peller	1.7	sf=float(job.sf[subsample])
23			else:
24	peller	1.18	if type(job.xsec) == str: xsec=float(eval(job.xsec))
25			else: xsec=float(job.xsec)
26	peller	1.7	sf=float(job.sf)
27
28
29	nmohr	1.6	theScale = 1.
30			if anaTag == '7TeV':
31	peller	1.7	theScale = float(job.lumi)xsecsf/(0.46502CountWithPU.GetBinContent(1)+0.53498CountWithPU2011B.GetBinContent(1))*rescale/float(job.split)
32	nmohr	1.6	elif anaTag == '8TeV':
33	peller	1.7	theScale = float(job.lumi)xsecsf/(CountWithPU.GetBinContent(1))*rescale/float(job.split)
34	peller	1.21	inputfile.Close()
35	nmohr	1.6	return theScale
36	peller	1.1
37	peller	1.11	def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1,which_weightF='weightF'):
38	peller	1.8
39			#print job.getpath()
40			#print options
41	peller	1.1	treeVar=options[0]
42	peller	1.7	if subsample>-1:
43			name=job.subnames[subsample]
44			group=job.group[subsample]
45			else:
46			name=job.name
47			group=job.group
48
49	peller	1.1	#title=job.plotname()
50			nBins=int(options[3])
51			xMin=float(options[4])
52			xMax=float(options[5])
53	peller	1.16	#addOverFlow=eval(config.get('Plot_general','addOverFlow'))
54			addOverFlow = False
55	peller	1.1
56	peller	1.17	TrainFlag = eval(config.get('Analysis','TrainFlag'))
57			if TrainFlag: traincut = " & EventForTraining == 0"
58			if not TrainFlag: traincut=""
59
60	peller	1.1	if job.type != 'DATA':
61	peller	1.12
62			if type(options[7])==str:
63			cutcut=config.get('Cuts',options[7])
64			elif type(options[7])==list:
65			cutcut=config.get('Cuts',options[7][0])
66			cutcut=cutcut.replace(options[7][1],options[7][2])
67	peller	1.19	#print cutcut
68	peller	1.8	if subsample>-1:
69	peller	1.17	treeCut='%s & %s%s'%(cutcut,job.subcuts[subsample],traincut)
70	peller	1.7	else:
71	peller	1.17	treeCut='%s%s'%(cutcut,traincut)
72	peller	1.1
73			elif job.type == 'DATA':
74	peller	1.5	cutcut=config.get('Cuts',options[8])
75	peller	1.8	treeCut='%s'%(cutcut)
76	peller	1.5
77	peller	1.1
78	nmohr	1.9	input = TFile.Open(path+'/'+job.getpath(),'read')
79	peller	1.1
80			Tree = input.Get(job.tree)
81			#Tree=tmpTree.CloneTree()
82			#Tree.SetDirectory(0)
83
84			#Tree=tmpTree.Clone()
85	peller	1.11	weightF=config.get('Weights',which_weightF)
86	peller	1.1	#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
87			#hTree.SetDirectory(0)
88			#hTree.Sumw2()
89			#print 'drawing...'
90			if job.type != 'DATA':
91			#print treeCut
92			#print job.name
93			if Tree.GetEntries():
94			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
95			full=True
96			else:
97			full=False
98			elif job.type == 'DATA':
99
100			if len(options)>10:
101			if options[11] == 'blind':
102			treeCut = treeCut + '&'+treeVar+'<0'
103
104
105			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
106			full = True
107			if full:
108			hTree = ROOT.gDirectory.Get(name)
109			else:
110			hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
111			hTree.Sumw2()
112			#print job.name + ' Sumw2', hTree.GetEntries()
113
114			if job.type != 'DATA':
115	nmohr	1.10	ScaleFactor = getScale(job,path,config,rescale,subsample)
116	peller	1.1	if ScaleFactor != 0:
117			hTree.Scale(ScaleFactor)
118	nmohr	1.15
119			if addOverFlow:
120			print 'Adding overflow'
121			uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
122			oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
123			uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
124			oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
125			hTree.SetBinContent(1,uFlow)
126			hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
127			hTree.SetBinError(1,uFlowErr)
128			hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
129
130	peller	1.1
131			print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
132
133			hTree.SetDirectory(0)
134	peller	1.7	input.Close()
135
136			return hTree, group
137	peller	1.1
138
139			######################
140
141
142
143			def orderandadd(histos,typs,setup):
144			#ORDER AND ADD TOGETHER
145
146			ordnung=[]
147			ordnungtyp=[]
148			num=[0]*len(setup)
149			for i in range(0,len(setup)):
150			for j in range(0,len(histos)):
151	peller	1.19	if typs[j] == setup[i]:
152	peller	1.1	num[i]+=1
153			ordnung.append(histos[j])
154			ordnungtyp.append(typs[j])
155
156			del histos
157			del typs
158
159			histos=ordnung
160			typs=ordnungtyp
161
162	peller	1.14	print typs
163
164	peller	1.1	for k in range(0,len(num)):
165			for m in range(0,num[k]):
166			if m > 0:
167
168			#add
169			histos[k].Add(histos[k+1],1)
170	peller	1.2	printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
171	peller	1.1	del histos[k+1]
172			del typs[k+1]
173
174			del histos[len(setup):]
175			del typs[len(setup):]
176
177			return histos, typs
178
179