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])

    if job.type != 'DATA':
        cutcut=config.get('Cuts',options[7])
        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)
            
    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

    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:	1.11
Committed:	Thu Sep 20 10:19:57 2012 UTC (12 years, 7 months ago) by peller
Content type:	text/x-python
Branch:	MAIN
Changes since 1.10:	+2 -2 lines
Log Message:	weightF option for DC writer
#	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
51			if job.type != 'DATA':
52			cutcut=config.get('Cuts',options[7])
53	peller	1.8	if subsample>-1:
54	peller	1.7	treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample])
55			else:
56			treeCut='%s & EventForTraining == 0'%(cutcut)
57	peller	1.1
58			elif job.type == 'DATA':
59	peller	1.5	cutcut=config.get('Cuts',options[8])
60	peller	1.8	treeCut='%s'%(cutcut)
61	peller	1.5
62	peller	1.1
63	nmohr	1.9	input = TFile.Open(path+'/'+job.getpath(),'read')
64	peller	1.1
65			Tree = input.Get(job.tree)
66			#Tree=tmpTree.CloneTree()
67			#Tree.SetDirectory(0)
68
69			#Tree=tmpTree.Clone()
70	peller	1.11	weightF=config.get('Weights',which_weightF)
71	peller	1.1	#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
72			#hTree.SetDirectory(0)
73			#hTree.Sumw2()
74			#print 'drawing...'
75			if job.type != 'DATA':
76			#print treeCut
77			#print job.name
78			if Tree.GetEntries():
79			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
80			full=True
81			else:
82			full=False
83			elif job.type == 'DATA':
84
85			if len(options)>10:
86			if options[11] == 'blind':
87			treeCut = treeCut + '&'+treeVar+'<0'
88
89
90			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
91			full = True
92			if full:
93			hTree = ROOT.gDirectory.Get(name)
94			else:
95			hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
96			hTree.Sumw2()
97			#print job.name + ' Sumw2', hTree.GetEntries()
98
99			if job.type != 'DATA':
100	nmohr	1.10	ScaleFactor = getScale(job,path,config,rescale,subsample)
101	peller	1.1	if ScaleFactor != 0:
102			hTree.Scale(ScaleFactor)
103
104			print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
105
106			hTree.SetDirectory(0)
107	peller	1.7	input.Close()
108
109
110
111			return hTree, group
112	peller	1.1
113
114			######################
115
116
117
118			def orderandadd(histos,typs,setup):
119			#ORDER AND ADD TOGETHER
120
121			ordnung=[]
122			ordnungtyp=[]
123			num=[0]*len(setup)
124			for i in range(0,len(setup)):
125			for j in range(0,len(histos)):
126	peller	1.2	if typs[j] in setup[i]:
127	peller	1.1	num[i]+=1
128			ordnung.append(histos[j])
129			ordnungtyp.append(typs[j])
130
131			del histos
132			del typs
133
134			histos=ordnung
135			typs=ordnungtyp
136
137			for k in range(0,len(num)):
138			for m in range(0,num[k]):
139			if m > 0:
140
141			#add
142			histos[k].Add(histos[k+1],1)
143	peller	1.2	printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
144	peller	1.1	del histos[k+1]
145			del typs[k+1]
146
147			del histos[len(setup):]
148			del typs[len(setup):]
149
150			return histos, typs
151
152