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':
    
        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)
            
    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:	1.13
Committed:	Thu Sep 20 14:14:53 2012 UTC (12 years, 7 months ago) by peller
Content type:	text/x-python
Branch:	MAIN
Changes since 1.12:	+1 -1 lines
Log Message:	bin-by-bin statistical treatment in DC
#	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	peller	1.12
53			if type(options[7])==str:
54			cutcut=config.get('Cuts',options[7])
55			elif type(options[7])==list:
56			cutcut=config.get('Cuts',options[7][0])
57			cutcut=cutcut.replace(options[7][1],options[7][2])
58	peller	1.13	#print cutcut
59	peller	1.8	if subsample>-1:
60	peller	1.7	treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample])
61			else:
62			treeCut='%s & EventForTraining == 0'%(cutcut)
63	peller	1.1
64			elif job.type == 'DATA':
65	peller	1.5	cutcut=config.get('Cuts',options[8])
66	peller	1.8	treeCut='%s'%(cutcut)
67	peller	1.5
68	peller	1.1
69	nmohr	1.9	input = TFile.Open(path+'/'+job.getpath(),'read')
70	peller	1.1
71			Tree = input.Get(job.tree)
72			#Tree=tmpTree.CloneTree()
73			#Tree.SetDirectory(0)
74
75			#Tree=tmpTree.Clone()
76	peller	1.11	weightF=config.get('Weights',which_weightF)
77	peller	1.1	#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax)
78			#hTree.SetDirectory(0)
79			#hTree.Sumw2()
80			#print 'drawing...'
81			if job.type != 'DATA':
82			#print treeCut
83			#print job.name
84			if Tree.GetEntries():
85			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'(%s)*(%s)' %(treeCut,weightF), "goff,e")
86			full=True
87			else:
88			full=False
89			elif job.type == 'DATA':
90
91			if len(options)>10:
92			if options[11] == 'blind':
93			treeCut = treeCut + '&'+treeVar+'<0'
94
95
96			Tree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeCut, "goff,e")
97			full = True
98			if full:
99			hTree = ROOT.gDirectory.Get(name)
100			else:
101			hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
102			hTree.Sumw2()
103			#print job.name + ' Sumw2', hTree.GetEntries()
104
105			if job.type != 'DATA':
106	nmohr	1.10	ScaleFactor = getScale(job,path,config,rescale,subsample)
107	peller	1.1	if ScaleFactor != 0:
108			hTree.Scale(ScaleFactor)
109
110			print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
111
112			hTree.SetDirectory(0)
113	peller	1.7	input.Close()
114
115
116
117			return hTree, group
118	peller	1.1
119
120			######################
121
122
123
124			def orderandadd(histos,typs,setup):
125			#ORDER AND ADD TOGETHER
126
127			ordnung=[]
128			ordnungtyp=[]
129			num=[0]*len(setup)
130			for i in range(0,len(setup)):
131			for j in range(0,len(histos)):
132	peller	1.2	if typs[j] in setup[i]:
133	peller	1.1	num[i]+=1
134			ordnung.append(histos[j])
135			ordnungtyp.append(typs[j])
136
137			del histos
138			del typs
139
140			histos=ordnung
141			typs=ordnungtyp
142
143			for k in range(0,len(num)):
144			for m in range(0,num[k]):
145			if m > 0:
146
147			#add
148			histos[k].Add(histos[k+1],1)
149	peller	1.2	printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
150	peller	1.1	del histos[k+1]
151			del typs[k+1]
152
153			del histos[len(setup):]
154			del typs[len(setup):]
155
156			return histos, typs
157
158