| 31 |
|
theScale = float(job.lumi)*xsec*sf/(CountWithPU.GetBinContent(1))*rescale/float(job.split) |
| 32 |
|
return theScale |
| 33 |
|
|
| 34 |
< |
def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1): |
| 34 |
> |
def getHistoFromTree(job,path,config,options,rescale=1,subsample=-1,which_weightF='weightF'): |
| 35 |
|
|
| 36 |
|
#print job.getpath() |
| 37 |
|
#print options |
| 49 |
|
xMax=float(options[5]) |
| 50 |
|
|
| 51 |
|
if job.type != 'DATA': |
| 52 |
< |
cutcut=config.get('Cuts',options[7]) |
| 52 |
> |
|
| 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: |
| 60 |
|
treeCut='%s & %s & EventForTraining == 0'%(cutcut,job.subcuts[subsample]) |
| 61 |
|
else: |
| 73 |
|
#Tree.SetDirectory(0) |
| 74 |
|
|
| 75 |
|
#Tree=tmpTree.Clone() |
| 76 |
< |
weightF=config.get('Weights','weightF') |
| 76 |
> |
weightF=config.get('Weights',which_weightF) |
| 77 |
|
#hTree = ROOT.TH1F('%s'%name,'%s'%title,nBins,xMin,xMax) |
| 78 |
|
#hTree.SetDirectory(0) |
| 79 |
|
#hTree.Sumw2() |
