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from copy import copy |
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|
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class HistoMaker: |
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< |
def __init__(self, samples, path, config, optionsList): |
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> |
def __init__(self, samples, path, config, optionsList,GroupDict=None): |
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self.path = path |
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self.config = config |
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self.optionsList = optionsList |
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self.cuts = [] |
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for options in optionsList: |
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self.cuts.append(options['cut']) |
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+ |
#print self.cuts |
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#self.tc = TreeCache(self.cuts,samples,path) |
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self.tc = TreeCache(self.cuts,samples,path,config) |
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self._rebin = False |
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self.mybinning = None |
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+ |
self.GroupDict=GroupDict |
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+ |
self.calc_rebin_flag = False |
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|
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def get_histos_from_tree(self,job): |
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if self.lumi == 0: |
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# get all Histos at once |
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for options in self.optionsList: |
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name=job.name |
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< |
group=job.group |
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> |
if self.GroupDict is None: |
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> |
group=job.group |
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> |
else: |
| 49 |
> |
group=self.GroupDict[job.name] |
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treeVar=options['var'] |
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name=options['name'] |
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< |
nBins=self.nBins |
| 53 |
< |
#int(options['nBins']) |
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> |
if self._rebin or self.calc_rebin_flag: |
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> |
nBins = self.nBins |
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> |
else: |
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> |
nBins = int(options['nBins']) |
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xMin=float(options['xMin']) |
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xMax=float(options['xMax']) |
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weightF=options['weight'] |
| 63 |
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|
| 64 |
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if job.type != 'DATA': |
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if CuttedTree.GetEntries(): |
| 58 |
– |
|
| 66 |
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if 'RTight' in treeVar or 'RMed' in treeVar: |
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drawoption = '(%s)*(%s)'%(weightF,BDT_add_cut) |
| 68 |
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else: |
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else: |
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full=False |
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elif job.type == 'DATA': |
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< |
if options['blind']: |
| 75 |
> |
if eval(options['blind']): |
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if treeVar == 'H.mass': |
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CuttedTree.Draw('%s>>%s(%s,%s,%s)' %(treeVar,name,nBins,xMin,xMax),treeVar+'<90. || '+treeVar + '>150.' , "goff,e") |
| 78 |
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else: |
| 90 |
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if 'RTight' in treeVar or 'RMed' in treeVar: |
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if TrainFlag: |
| 92 |
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MC_rescale_factor=2. |
| 93 |
< |
print 'I RESCALE BY 2.0' |
| 93 |
> |
#print 'I RESCALE BY 2.0' |
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else: |
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MC_rescale_factor = 1. |
| 96 |
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ScaleFactor = self.tc.get_scale(job,self.config,self.lumi)*MC_rescale_factor |
| 112 |
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gDict = {} |
| 113 |
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if self._rebin: |
| 114 |
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gDict[group] = self.mybinning.rebin(hTree) |
| 115 |
+ |
del hTree |
| 116 |
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else: |
| 117 |
+ |
#print 'not rebinning %s'%job.name |
| 118 |
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gDict[group] = hTree |
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hTreeList.append(gDict) |
| 120 |
+ |
CuttedTree.IsA().Destructor(CuttedTree) |
| 121 |
+ |
del CuttedTree |
| 122 |
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return hTreeList |
| 123 |
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|
| 124 |
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@property |
| 143 |
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return False |
| 144 |
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|
| 145 |
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def calc_rebin(self, bg_list, nBins_start=1000, tolerance=0.35): |
| 146 |
< |
self.norebin_nBins = self.nBins |
| 146 |
> |
self.calc_rebin_flag = True |
| 147 |
> |
self.norebin_nBins = copy(self.nBins) |
| 148 |
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self.rebin_nBins = nBins_start |
| 149 |
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self.nBins = nBins_start |
| 150 |
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i=0 |
| 151 |
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#add all together: |
| 152 |
+ |
print '\n\t...calculating rebinning...' |
| 153 |
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for job in bg_list: |
| 154 |
+ |
htree = self.get_histos_from_tree(job)[0].values()[0] |
| 155 |
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if not i: |
| 156 |
< |
totalBG = self.get_histos_from_tree(job)[0].values()[0] |
| 156 |
> |
totalBG = copy(htree) |
| 157 |
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else: |
| 158 |
< |
totalBG.Add(self.get_histos_from_tree(job)[0].values()[0],1) |
| 158 |
> |
totalBG.Add(htree,1) |
| 159 |
> |
del htree |
| 160 |
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i+=1 |
| 161 |
|
ErrorR=0 |
| 162 |
|
ErrorL=0 |
| 192 |
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stepsize=int(inbetween)/(int(self.norebin_nBins)-2) |
| 193 |
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modulo = int(inbetween)%(int(self.norebin_nBins)-2) |
| 194 |
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|
| 195 |
< |
#print'stepsize %s'% stepsize |
| 195 |
> |
#print 'stepsize %s'% stepsize |
| 196 |
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#print 'modulo %s'%modulo |
| 197 |
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binlist=[binL] |
| 198 |
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for i in range(0,int(self.norebin_nBins)-3): |
| 200 |
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binlist[-1]+=modulo |
| 201 |
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binlist.append(binR) |
| 202 |
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binlist.append(self.rebin_nBins+1) |
| 203 |
< |
|
| 203 |
> |
#print 'binning set to %s'%binlist |
| 204 |
|
self.mybinning = Rebinner(int(self.norebin_nBins),array('d',[-1.0]+[totalBG.GetBinLowEdge(i) for i in binlist]),True) |
| 205 |
|
self._rebin = True |
| 206 |
< |
|
| 206 |
> |
print '\t > rebinning is set <\n' |
| 207 |
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|
| 208 |
|
@staticmethod |
| 209 |
|
def orderandadd(histo_dicts,setup): |
| 213 |
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for histo_dict in histo_dicts: |
| 214 |
|
if histo_dict.has_key(sample): |
| 215 |
|
if nSample == 0: |
| 216 |
< |
ordered_histo_dict[sample] = histo_dict[sample] |
| 216 |
> |
ordered_histo_dict[sample] = histo_dict[sample].Clone() |
| 217 |
|
else: |
| 218 |
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printc('magenta','','\t--> added %s to %s'%(sample,sample)) |
| 219 |
|
ordered_histo_dict[sample].Add(histo_dict[sample]) |
| 220 |
|
nSample += 1 |
| 221 |
+ |
del histo_dicts |
| 222 |
|
return ordered_histo_dict |
| 223 |
|
|
| 224 |
|
class Rebinner: |
| 228 |
|
self.active=active |
| 229 |
|
def rebin(self, histo): |
| 230 |
|
if not self.active: return histo |
| 215 |
– |
#print 'rebinning' |
| 231 |
|
#print histo.Integral() |
| 232 |
|
ROOT.gDirectory.Delete('hnew') |
| 233 |
|
histo.Rebin(self.nBins,'hnew',self.lowedgearray) |
| 241 |
|
newhisto.SetName(binhisto.GetName()) |
| 242 |
|
newhisto.SetTitle(binhisto.GetTitle()) |
| 243 |
|
#print newhisto.Integral() |
| 244 |
+ |
del histo |
| 245 |
+ |
del binhisto |
| 246 |
|
return copy(newhisto) |
