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import sys |
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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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< |
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| 16 |
< |
#get locations: |
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< |
Wdir=config.get('Directories','Wdir') |
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< |
anaTag=config.get('Analysis','tag') |
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< |
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< |
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< |
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< |
def getScale(job,rescale,subsample=-1): |
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< |
input = TFile.Open(job.getpath()) |
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> |
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 |
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< |
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'): |
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> |
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> |
#print job.getpath() |
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> |
#print options |
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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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xMax=float(options[5]) |
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if job.type != 'DATA': |
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< |
cutcut=config.get('Cuts',options[7]) |
| 53 |
< |
if subsample>0: |
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> |
|
| 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 |
> |
#print cutcut |
| 59 |
> |
if subsample>-1: |
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treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample]) |
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else: |
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treeCut='%s & EventForTraining == 0'%(cutcut) |
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| 64 |
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elif job.type == 'DATA': |
| 65 |
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cutcut=config.get('Cuts',options[8]) |
| 66 |
< |
treeCut='%s & EventForTraining == 0'%(cutcut) |
| 66 |
> |
treeCut='%s'%(cutcut) |
| 67 |
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| 68 |
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|
| 69 |
< |
input = TFile.Open(job.getpath(),'read') |
| 69 |
> |
input = TFile.Open(path+'/'+job.getpath(),'read') |
| 70 |
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| 71 |
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Tree = input.Get(job.tree) |
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#Tree=tmpTree.CloneTree() |
| 73 |
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#Tree.SetDirectory(0) |
| 74 |
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| 75 |
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#Tree=tmpTree.Clone() |
| 76 |
< |
weightF=config.get('Weights','weightF') |
| 76 |
> |
weightF=config.get('Weights',which_weightF) |
| 77 |
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#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax) |
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#hTree.SetDirectory(0) |
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#hTree.Sumw2() |
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#print job.name + ' Sumw2', hTree.GetEntries() |
| 104 |
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| 105 |
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if job.type != 'DATA': |
| 106 |
< |
ScaleFactor = getScale(job,rescale,subsample) |
| 106 |
> |
ScaleFactor = getScale(job,path,config,rescale,subsample) |
| 107 |
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if ScaleFactor != 0: |
| 108 |
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hTree.Scale(ScaleFactor) |
| 109 |
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| 140 |
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histos=ordnung |
| 141 |
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typs=ordnungtyp |
| 142 |
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| 143 |
+ |
print typs |
| 144 |
+ |
|
| 145 |
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for k in range(0,len(num)): |
| 146 |
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for m in range(0,num[k]): |
| 147 |
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if m > 0: |
