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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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< |
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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): |
| 13 |
> |
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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| 34 |
< |
def getHistoFromTree(job,options,rescale=1,subsample=-1): |
| 34 |
> |
def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1): |
| 35 |
> |
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| 36 |
> |
#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] |
| 50 |
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if job.type != 'DATA': |
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cutcut=config.get('Cuts',options[7]) |
| 53 |
< |
if subsample>0: |
| 53 |
> |
if subsample>-1: |
| 54 |
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treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample]) |
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else: |
| 56 |
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treeCut='%s & EventForTraining == 0'%(cutcut) |
| 57 |
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| 58 |
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elif job.type == 'DATA': |
| 59 |
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cutcut=config.get('Cuts',options[8]) |
| 60 |
< |
treeCut='%s & EventForTraining == 0'%(cutcut) |
| 60 |
> |
treeCut='%s'%(cutcut) |
| 61 |
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| 62 |
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| 63 |
< |
input = TFile.Open(job.getpath(),'read') |
| 63 |
> |
input = TFile.Open(path+'/'+job.getpath(),'read') |
| 64 |
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| 65 |
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Tree = input.Get(job.tree) |
| 66 |
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#Tree=tmpTree.CloneTree() |
| 97 |
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#print job.name + ' Sumw2', hTree.GetEntries() |
| 98 |
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| 99 |
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if job.type != 'DATA': |
| 100 |
< |
ScaleFactor = getScale(job,rescale,subsample) |
| 100 |
> |
ScaleFactor = getScale(job,path,config,rescale,subsample) |
| 101 |
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if ScaleFactor != 0: |
| 102 |
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hTree.Scale(ScaleFactor) |
| 103 |
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