| 9 |
|
from copy import copy |
| 10 |
|
|
| 11 |
|
class HistoMaker: |
| 12 |
< |
def __init__(self, samples, path, config, optionsList): |
| 12 |
> |
def __init__(self, samples, path, config, optionsList,GroupDict=None): |
| 13 |
|
self.path = path |
| 14 |
|
self.config = config |
| 15 |
|
self.optionsList = optionsList |
| 18 |
|
self.cuts = [] |
| 19 |
|
for options in optionsList: |
| 20 |
|
self.cuts.append(options['cut']) |
| 21 |
+ |
#print self.cuts |
| 22 |
|
#self.tc = TreeCache(self.cuts,samples,path) |
| 23 |
|
self.tc = TreeCache(self.cuts,samples,path,config) |
| 24 |
|
self._rebin = False |
| 25 |
|
self.mybinning = None |
| 26 |
+ |
self.GroupDict=GroupDict |
| 27 |
+ |
self.calc_rebin_flag = False |
| 28 |
|
|
| 29 |
|
def get_histos_from_tree(self,job): |
| 30 |
|
if self.lumi == 0: |
| 43 |
|
# get all Histos at once |
| 44 |
|
for options in self.optionsList: |
| 45 |
|
name=job.name |
| 46 |
< |
group=job.group |
| 46 |
> |
if self.GroupDict is None: |
| 47 |
> |
group=job.group |
| 48 |
> |
else: |
| 49 |
> |
group=self.GroupDict[job.name] |
| 50 |
|
treeVar=options['var'] |
| 51 |
|
name=options['name'] |
| 52 |
< |
nBins=self.nBins |
| 53 |
< |
#int(options['nBins']) |
| 52 |
> |
if self._rebin or self.calc_rebin_flag: |
| 53 |
> |
nBins = self.nBins |
| 54 |
> |
else: |
| 55 |
> |
nBins = int(options['nBins']) |
| 56 |
|
xMin=float(options['xMin']) |
| 57 |
|
xMax=float(options['xMax']) |
| 58 |
|
weightF=options['weight'] |
| 63 |
|
|
| 64 |
|
if job.type != 'DATA': |
| 65 |
|
if CuttedTree.GetEntries(): |
| 58 |
– |
|
| 66 |
|
if 'RTight' in treeVar or 'RMed' in treeVar: |
| 67 |
|
drawoption = '(%s)*(%s)'%(weightF,BDT_add_cut) |
| 68 |
|
else: |
| 90 |
|
if 'RTight' in treeVar or 'RMed' in treeVar: |
| 91 |
|
if TrainFlag: |
| 92 |
|
MC_rescale_factor=2. |
| 93 |
< |
print 'I RESCALE BY 2.0' |
| 93 |
> |
#print 'I RESCALE BY 2.0' |
| 94 |
|
else: |
| 95 |
|
MC_rescale_factor = 1. |
| 96 |
|
ScaleFactor = self.tc.get_scale(job,self.config,self.lumi)*MC_rescale_factor |
| 114 |
|
gDict[group] = self.mybinning.rebin(hTree) |
| 115 |
|
del hTree |
| 116 |
|
else: |
| 117 |
+ |
#print 'not rebinning %s'%job.name |
| 118 |
|
gDict[group] = hTree |
| 119 |
|
hTreeList.append(gDict) |
| 120 |
|
CuttedTree.IsA().Destructor(CuttedTree) |
| 143 |
|
return False |
| 144 |
|
|
| 145 |
|
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 |
|
self.rebin_nBins = nBins_start |
| 149 |
|
self.nBins = nBins_start |
| 150 |
|
i=0 |
| 151 |
|
#add all together: |
| 152 |
+ |
print '\n\t...calculating rebinning...' |
| 153 |
|
for job in bg_list: |
| 144 |
– |
print job |
| 154 |
|
htree = self.get_histos_from_tree(job)[0].values()[0] |
| 155 |
|
if not i: |
| 156 |
|
totalBG = copy(htree) |
| 192 |
|
stepsize=int(inbetween)/(int(self.norebin_nBins)-2) |
| 193 |
|
modulo = int(inbetween)%(int(self.norebin_nBins)-2) |
| 194 |
|
|
| 195 |
< |
#print'stepsize %s'% stepsize |
| 195 |
> |
#print 'stepsize %s'% stepsize |
| 196 |
|
#print 'modulo %s'%modulo |
| 197 |
|
binlist=[binL] |
| 198 |
|
for i in range(0,int(self.norebin_nBins)-3): |
| 200 |
|
binlist[-1]+=modulo |
| 201 |
|
binlist.append(binR) |
| 202 |
|
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 |
|
|
| 208 |
|
@staticmethod |
| 209 |
|
def orderandadd(histo_dicts,setup): |
