| 1 |
nmohr |
1.2 |
import sys,os
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| 2 |
peller |
1.1 |
import pickle
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| 3 |
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import ROOT
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| 4 |
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from array import array
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| 5 |
nmohr |
1.2 |
from printcolor import printc
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| 6 |
peller |
1.1 |
from BetterConfigParser import BetterConfigParser
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| 7 |
nmohr |
1.2 |
from TreeCache import TreeCache
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| 8 |
peller |
1.1 |
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| 9 |
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class HistoMaker:
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| 10 |
nmohr |
1.2 |
def __init__(self, samples, path, config, optionsList):
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| 11 |
peller |
1.1 |
self.path = path
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| 12 |
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self.config = config
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| 13 |
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self.optionsList = optionsList
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| 14 |
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self.lumi=0.
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| 15 |
nmohr |
1.2 |
self.cuts = []
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| 16 |
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for options in optionsList:
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| 17 |
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self.cuts.append(options['cut'])
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| 18 |
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self.tc = TreeCache(self.cuts,samples,path)
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| 19 |
peller |
1.1 |
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| 20 |
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| 21 |
nmohr |
1.2 |
def get_histos_from_tree(self,job):
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| 22 |
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if self.lumi == 0:
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| 23 |
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raise Exception("You're trying to plot with no lumi")
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| 24 |
peller |
1.1 |
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| 25 |
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hTreeList=[]
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| 26 |
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groupList=[]
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| 27 |
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| 28 |
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#get the conversion rate in case of BDT plots
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| 29 |
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TrainFlag = eval(self.config.get('Analysis','TrainFlag'))
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| 30 |
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BDT_add_cut='EventForTraining == 0'
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| 31 |
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| 33 |
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plot_path = self.config.get('Directories','plotpath')
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| 34 |
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addOverFlow=eval(self.config.get('Plot_general','addOverFlow'))
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| 35 |
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| 36 |
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# get all Histos at once
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| 37 |
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for options in self.optionsList:
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| 38 |
nmohr |
1.2 |
name=job.name
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| 39 |
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group=job.group
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| 40 |
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treeVar=options['var']
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| 41 |
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name=options['name']
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| 42 |
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nBins=int(options['nBins'])
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| 43 |
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xMin=float(options['xMin'])
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| 44 |
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xMax=float(options['xMax'])
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| 45 |
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weightF=options['weight']
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| 46 |
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treeCut='%s'%(options['cut'])
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| 47 |
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CuttedTree = self.tc.get_tree(job,treeCut)
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| 48 |
peller |
1.1 |
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| 49 |
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#options
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| 50 |
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| 51 |
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if job.type != 'DATA':
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| 52 |
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if CuttedTree.GetEntries():
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| 53 |
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| 54 |
nmohr |
1.2 |
if 'RTight' in treeVar or 'RMed' in treeVar:
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| 55 |
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drawoption = '(%s)*(%s)'%(weightF,BDT_add_cut)
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| 56 |
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else:
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| 57 |
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drawoption = '%s'%(weightF)
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| 58 |
peller |
1.1 |
CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax), drawoption, "goff,e")
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| 59 |
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full=True
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| 60 |
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else:
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| 61 |
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full=False
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| 62 |
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elif job.type == 'DATA':
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| 63 |
nmohr |
1.2 |
if options['blind'] == 'blind':
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| 64 |
peller |
1.1 |
output.cd()
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| 65 |
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if treeVar == 'H.mass':
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| 66 |
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<90. || '+treeVar + '>150.' , "goff,e")
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| 67 |
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else:
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| 68 |
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<0', "goff,e")
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| 69 |
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| 70 |
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else:
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| 71 |
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),'1', "goff,e")
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| 72 |
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full = True
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| 73 |
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if full:
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| 74 |
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hTree = ROOT.gDirectory.Get(name)
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| 75 |
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else:
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| 76 |
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hTree = ROOT.TH1F('%s'%name,'%s'%name,nBins,xMin,xMax)
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| 77 |
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hTree.Sumw2()
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| 78 |
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if job.type != 'DATA':
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| 79 |
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if 'RTight' in treeVar or 'RMed' in treeVar:
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| 80 |
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if TrainFlag:
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| 81 |
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MC_rescale_factor=2.
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| 82 |
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print 'I RESCALE BY 2.0'
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| 83 |
nmohr |
1.2 |
else:
|
| 84 |
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MC_rescale_factor = 1.
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| 85 |
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ScaleFactor = self.tc.get_scale(job,self.config,self.lumi)*MC_rescale_factor
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| 86 |
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else:
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| 87 |
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ScaleFactor = self.tc.get_scale(job,self.config,self.lumi)
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| 88 |
peller |
1.1 |
if ScaleFactor != 0:
|
| 89 |
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hTree.Scale(ScaleFactor)
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| 90 |
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#print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral())
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| 91 |
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if addOverFlow:
|
| 92 |
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uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1)
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| 93 |
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oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX())
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| 94 |
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uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2))
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| 95 |
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oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2))
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| 96 |
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hTree.SetBinContent(1,uFlow)
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| 97 |
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hTree.SetBinContent(hTree.GetNbinsX(),oFlow)
|
| 98 |
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hTree.SetBinError(1,uFlowErr)
|
| 99 |
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hTree.SetBinError(hTree.GetNbinsX(),oFlowErr)
|
| 100 |
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hTree.SetDirectory(0)
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| 101 |
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hTreeList.append(hTree)
|
| 102 |
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groupList.append(group)
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| 103 |
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| 104 |
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return hTreeList, groupList
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| 105 |
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| 106 |
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| 107 |
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######################
|
| 108 |
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def orderandadd(histos,typs,setup):
|
| 109 |
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#ORDER AND ADD TOGETHER
|
| 110 |
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ordnung=[]
|
| 111 |
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ordnungtyp=[]
|
| 112 |
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num=[0]*len(setup)
|
| 113 |
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for i in range(0,len(setup)):
|
| 114 |
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for j in range(0,len(histos)):
|
| 115 |
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if typs[j] in setup[i]:
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| 116 |
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num[i]+=1
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| 117 |
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ordnung.append(histos[j])
|
| 118 |
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ordnungtyp.append(typs[j])
|
| 119 |
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del histos
|
| 120 |
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del typs
|
| 121 |
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histos=ordnung
|
| 122 |
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typs=ordnungtyp
|
| 123 |
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print typs
|
| 124 |
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for k in range(0,len(num)):
|
| 125 |
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for m in range(0,num[k]):
|
| 126 |
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if m > 0:
|
| 127 |
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#add
|
| 128 |
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histos[k].Add(histos[k+1],1)
|
| 129 |
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printc('magenta','','\t--> added %s to %s'%(typs[k],typs[k+1]))
|
| 130 |
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del histos[k+1]
|
| 131 |
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del typs[k+1]
|
| 132 |
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del histos[len(setup):]
|
| 133 |
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del typs[len(setup):]
|
| 134 |
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return histos, typs
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