| 9 |
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import sys |
| 10 |
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| 11 |
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| 12 |
< |
#load config |
| 13 |
< |
config = BetterConfigParser() |
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< |
config.read('./config') |
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< |
|
| 16 |
< |
#get locations: |
| 17 |
< |
Wdir=config.get('Directories','Wdir') |
| 18 |
< |
anaTag=config.get('Analysis','tag') |
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< |
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| 20 |
< |
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| 21 |
< |
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| 22 |
< |
def getScale(job,rescale,subsample=-1): |
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< |
input = TFile.Open(job.getpath()) |
| 12 |
> |
def getScale(job,path,config,rescale,subsample=-1): |
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> |
anaTag=config.get('Analysis','tag') |
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> |
input = TFile.Open(path+'/'+job.getpath()) |
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CountWithPU = input.Get("CountWithPU") |
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CountWithPU2011B = input.Get("CountWithPU2011B") |
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#print lumi*xsecs[i]/hist.GetBinContent(1) |
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theScale = float(job.lumi)*xsec*sf/(CountWithPU.GetBinContent(1))*rescale/float(job.split) |
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return theScale |
| 33 |
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| 34 |
< |
def getHistoFromTree(job,options,rescale=1,subsample=-1): |
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> |
def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1,which_weightF='weightF'): |
| 35 |
> |
|
| 36 |
> |
#print job.getpath() |
| 37 |
> |
#print options |
| 38 |
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treeVar=options[0] |
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if subsample>-1: |
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name=job.subnames[subsample] |
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nBins=int(options[3]) |
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xMin=float(options[4]) |
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xMax=float(options[5]) |
| 50 |
+ |
#addOverFlow=eval(config.get('Plot_general','addOverFlow')) |
| 51 |
+ |
addOverFlow = False |
| 52 |
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|
| 53 |
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if job.type != 'DATA': |
| 54 |
< |
cutcut=config.get('Cuts',options[7]) |
| 55 |
< |
if subsample>0: |
| 54 |
> |
|
| 55 |
> |
if type(options[7])==str: |
| 56 |
> |
cutcut=config.get('Cuts',options[7]) |
| 57 |
> |
elif type(options[7])==list: |
| 58 |
> |
cutcut=config.get('Cuts',options[7][0]) |
| 59 |
> |
cutcut=cutcut.replace(options[7][1],options[7][2]) |
| 60 |
> |
#print cutcut |
| 61 |
> |
if subsample>-1: |
| 62 |
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treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample]) |
| 63 |
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else: |
| 64 |
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treeCut='%s & EventForTraining == 0'%(cutcut) |
| 65 |
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|
| 66 |
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elif job.type == 'DATA': |
| 67 |
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cutcut=config.get('Cuts',options[8]) |
| 68 |
< |
treeCut='%s & EventForTraining == 0'%(cutcut) |
| 68 |
> |
treeCut='%s'%(cutcut) |
| 69 |
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| 70 |
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| 71 |
< |
input = TFile.Open(job.getpath(),'read') |
| 71 |
> |
input = TFile.Open(path+'/'+job.getpath(),'read') |
| 72 |
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| 73 |
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Tree = input.Get(job.tree) |
| 74 |
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#Tree=tmpTree.CloneTree() |
| 75 |
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#Tree.SetDirectory(0) |
| 76 |
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| 77 |
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#Tree=tmpTree.Clone() |
| 78 |
< |
weightF=config.get('Weights','weightF') |
| 78 |
> |
weightF=config.get('Weights',which_weightF) |
| 79 |
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#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax) |
| 80 |
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#hTree.SetDirectory(0) |
| 81 |
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#hTree.Sumw2() |
| 105 |
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#print job.name + ' Sumw2', hTree.GetEntries() |
| 106 |
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| 107 |
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if job.type != 'DATA': |
| 108 |
< |
ScaleFactor = getScale(job,rescale,subsample) |
| 108 |
> |
ScaleFactor = getScale(job,path,config,rescale,subsample) |
| 109 |
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if ScaleFactor != 0: |
| 110 |
|
hTree.Scale(ScaleFactor) |
| 111 |
+ |
|
| 112 |
+ |
if addOverFlow: |
| 113 |
+ |
print 'Adding overflow' |
| 114 |
+ |
uFlow = hTree.GetBinContent(0)+hTree.GetBinContent(1) |
| 115 |
+ |
oFlow = hTree.GetBinContent(hTree.GetNbinsX()+1)+hTree.GetBinContent(hTree.GetNbinsX()) |
| 116 |
+ |
uFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(0),2)+ROOT.TMath.Power(hTree.GetBinError(1),2)) |
| 117 |
+ |
oFlowErr = ROOT.TMath.Sqrt(ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()),2)+ROOT.TMath.Power(hTree.GetBinError(hTree.GetNbinsX()+1),2)) |
| 118 |
+ |
hTree.SetBinContent(1,uFlow) |
| 119 |
+ |
hTree.SetBinContent(hTree.GetNbinsX(),oFlow) |
| 120 |
+ |
hTree.SetBinError(1,uFlowErr) |
| 121 |
+ |
hTree.SetBinError(hTree.GetNbinsX(),oFlowErr) |
| 122 |
+ |
|
| 123 |
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| 124 |
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print '\t-->import %s\t Integral: %s'%(job.name,hTree.Integral()) |
| 125 |
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| 126 |
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hTree.SetDirectory(0) |
| 127 |
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input.Close() |
| 128 |
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|
| 115 |
– |
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| 116 |
– |
|
| 129 |
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return hTree, group |
| 130 |
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| 131 |
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| 152 |
|
histos=ordnung |
| 153 |
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typs=ordnungtyp |
| 154 |
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|
| 155 |
+ |
print typs |
| 156 |
+ |
|
| 157 |
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for k in range(0,len(num)): |
| 158 |
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for m in range(0,num[k]): |
| 159 |
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if m > 0: |
