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'))

    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 & EventForTraining == 0'%(cutcut,job.subcuts[subsample])        
        else:
            treeCut='%s & EventForTraining == 0'%(cutcut)

    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:	1.15
Committed:	Thu Oct 4 13:02:23 2012 UTC (12 years, 7 months ago) by nmohr
Content type:	text/x-python
Branch:	MAIN
Changes since 1.14:	+13 -2 lines
Log Message:	Plotting style
#	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	nmohr	1.15	addOverFlow=eval(config.get('Plot_general','addOverFlow'))
51	peller	1.1
52			if job.type != 'DATA':
53	peller	1.12
54			if type(options[7])==str:
55			cutcut=config.get('Cuts',options[7])
56			elif type(options[7])==list:
57			cutcut=config.get('Cuts',options[7][0])
58			cutcut=cutcut.replace(options[7][1],options[7][2])
59	peller	1.13	#print cutcut
60	peller	1.8	if subsample>-1:
61	peller	1.7	treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample])
62			else:
63			treeCut='%s & EventForTraining == 0'%(cutcut)
64	peller	1.1
65			elif job.type == 'DATA':
66	peller	1.5	cutcut=config.get('Cuts',options[8])
67	peller	1.8	treeCut='%s'%(cutcut)
68	peller	1.5
69	peller	1.1
70	nmohr	1.9	input = TFile.Open(path+'/'+job.getpath(),'read')
71	peller	1.1
72			Tree = input.Get(job.tree)
73			#Tree=tmpTree.CloneTree()
74			#Tree.SetDirectory(0)
75
76			#Tree=tmpTree.Clone()
77	peller	1.11	weightF=config.get('Weights',which_weightF)
78	peller	1.1	#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
79			#hTree.SetDirectory(0)
80			#hTree.Sumw2()
81			#print 'drawing...'
82			if job.type != 'DATA':
83			#print treeCut
84			#print job.name
85			if Tree.GetEntries():
86			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
87			full=True
88			else:
89			full=False
90			elif job.type == 'DATA':
91
92			if len(options)>10:
93			if options[11] == 'blind':
94			treeCut = treeCut + '&'+treeVar+'<0'
95
96
97			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
98			full = True
99			if full:
100			hTree = ROOT.gDirectory.Get(name)
101			else:
102			hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
103			hTree.Sumw2()
104			#print job.name + ' Sumw2', hTree.GetEntries()
105
106			if job.type != 'DATA':
107	nmohr	1.10	ScaleFactor = getScale(job,path,config,rescale,subsample)
108	peller	1.1	if ScaleFactor != 0:
109			hTree.Scale(ScaleFactor)
110	nmohr	1.15
111			if addOverFlow:
112			print 'Adding overflow'
113			uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
114			oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
115			uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
116			oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
117			hTree.SetBinContent(1,uFlow)
118			hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
119			hTree.SetBinError(1,uFlowErr)
120			hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
121
122	peller	1.1
123			print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
124
125			hTree.SetDirectory(0)
126	peller	1.7	input.Close()
127
128			return hTree, group
129	peller	1.1
130
131			######################
132
133
134
135			def orderandadd(histos,typs,setup):
136			#ORDER AND ADD TOGETHER
137
138			ordnung=[]
139			ordnungtyp=[]
140			num=[0]*len(setup)
141			for i in range(0,len(setup)):
142			for j in range(0,len(histos)):
143	peller	1.2	if typs[j] in setup[i]:
144	peller	1.1	num[i]+=1
145			ordnung.append(histos[j])
146			ordnungtyp.append(typs[j])
147
148			del histos
149			del typs
150
151			histos=ordnung
152			typs=ordnungtyp
153
154	peller	1.14	print typs
155
156	peller	1.1	for k in range(0,len(num)):
157			for m in range(0,num[k]):
158			if m > 0:
159
160			#add
161			histos[k].Add(histos[k+1],1)
162	peller	1.2	printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
163	peller	1.1	del histos[k+1]
164			del typs[k+1]
165
166			del histos[len(setup):]
167			del typs[len(setup):]
168
169			return histos, typs
170
171