| 1 |
peller |
1.1 |
#!/usr/bin/env python
|
| 2 |
|
|
from samplesinfo import sample
|
| 3 |
|
|
from printcolor import printc
|
| 4 |
|
|
import pickle
|
| 5 |
|
|
import ROOT
|
| 6 |
|
|
from ROOT import TFile, TTree
|
| 7 |
|
|
import ROOT
|
| 8 |
|
|
from array import array
|
| 9 |
|
|
from ConfigParser import SafeConfigParser
|
| 10 |
|
|
import sys
|
| 11 |
|
|
from mvainfos import mvainfo
|
| 12 |
|
|
|
| 13 |
|
|
#warnings.filterwarnings( action='ignore', category=RuntimeWarning, message='creating converter.*' )
|
| 14 |
|
|
|
| 15 |
|
|
|
| 16 |
|
|
#usage: ./train run gui
|
| 17 |
|
|
|
| 18 |
|
|
|
| 19 |
|
|
#CONFIGURE
|
| 20 |
|
|
|
| 21 |
|
|
#load config
|
| 22 |
|
|
config = SafeConfigParser()
|
| 23 |
|
|
config.read('./config')
|
| 24 |
|
|
|
| 25 |
|
|
#get locations:
|
| 26 |
|
|
Wdir=config.get('Directories','Wdir')
|
| 27 |
|
|
|
| 28 |
|
|
|
| 29 |
|
|
#systematics
|
| 30 |
|
|
systematics=config.get('systematics','systematics')
|
| 31 |
|
|
systematics=systematics.split(' ')
|
| 32 |
|
|
|
| 33 |
|
|
weightF=config.get('Weights','weightF')
|
| 34 |
|
|
|
| 35 |
|
|
|
| 36 |
|
|
def getTree(job,cut):
|
| 37 |
|
|
Tree = ROOT.TChain(job.tree)
|
| 38 |
|
|
Tree.Add(job.getpath())
|
| 39 |
|
|
#Tree.SetDirectory(0)
|
| 40 |
|
|
CuttedTree=Tree.CopyTree(cut)
|
| 41 |
|
|
CuttedTree.SetDirectory(0)
|
| 42 |
|
|
print '\t--> read in %s'%job.name
|
| 43 |
|
|
return CuttedTree
|
| 44 |
|
|
|
| 45 |
|
|
|
| 46 |
|
|
|
| 47 |
|
|
def getScale(job):
|
| 48 |
|
|
input = TFile.Open(job.getpath())
|
| 49 |
|
|
CountWithPU = input.Get("CountWithPU")
|
| 50 |
|
|
CountWithPU2011B = input.Get("CountWithPU2011B")
|
| 51 |
|
|
#print lumi*xsecs[i]/hist.GetBinContent(1)
|
| 52 |
peller |
1.2 |
return float(job.lumi)*float(job.xsec)*float(job.sf)/(0.46502*CountWithPU.GetBinContent(1)+0.53498*CountWithPU2011B.GetBinContent(1))*2/float(job.split)
|
| 53 |
peller |
1.1 |
|
| 54 |
|
|
|
| 55 |
|
|
|
| 56 |
|
|
|
| 57 |
|
|
run=sys.argv[1]
|
| 58 |
|
|
gui=sys.argv[2]
|
| 59 |
|
|
|
| 60 |
|
|
|
| 61 |
|
|
#CONFIG
|
| 62 |
|
|
#factory
|
| 63 |
|
|
factoryname=config.get('factory','factoryname')
|
| 64 |
|
|
factorysettings=config.get('factory','factorysettings')
|
| 65 |
|
|
#MVA
|
| 66 |
|
|
MVAtype=config.get(run,'MVAtype')
|
| 67 |
|
|
MVAname=run
|
| 68 |
|
|
MVAsettings=config.get(run,'MVAsettings')
|
| 69 |
|
|
fnameOutput = Wdir +'/weights/'+factoryname+'_'+MVAname+'.root'
|
| 70 |
|
|
#locations
|
| 71 |
|
|
path=config.get(run,'path')
|
| 72 |
|
|
|
| 73 |
|
|
TCutname=config.get(run, 'treeCut')
|
| 74 |
|
|
TCut=config.get('Cuts',TCutname)
|
| 75 |
peller |
1.3 |
#print TCut
|
| 76 |
peller |
1.1 |
|
| 77 |
|
|
#signals
|
| 78 |
|
|
signals=config.get(run,'signals')
|
| 79 |
|
|
signals=signals.split(' ')
|
| 80 |
|
|
#backgrounds
|
| 81 |
|
|
backgrounds=config.get(run,'backgrounds')
|
| 82 |
|
|
backgrounds=backgrounds.split(' ')
|
| 83 |
|
|
|
| 84 |
|
|
treeVarSet=config.get(run,'treeVarSet')
|
| 85 |
|
|
|
| 86 |
|
|
#variables
|
| 87 |
|
|
#TreeVar Array
|
| 88 |
|
|
MVA_Vars={}
|
| 89 |
|
|
MVA_Vars['Nominal']=config.get(treeVarSet,'Nominal')
|
| 90 |
|
|
MVA_Vars['Nominal']=MVA_Vars['Nominal'].split(' ')
|
| 91 |
|
|
#Spectators:
|
| 92 |
peller |
1.3 |
#spectators=config.get(treeVarSet,'spectators')
|
| 93 |
|
|
#spectators=spectators.split(' ')
|
| 94 |
peller |
1.1 |
|
| 95 |
|
|
#TRAINING samples
|
| 96 |
|
|
infofile = open(path+'/samples.info','r')
|
| 97 |
|
|
info = pickle.load(infofile)
|
| 98 |
|
|
infofile.close()
|
| 99 |
|
|
|
| 100 |
|
|
#Workdir
|
| 101 |
|
|
workdir=ROOT.gDirectory.GetPath()
|
| 102 |
|
|
|
| 103 |
|
|
|
| 104 |
|
|
TrainCut='%s && EventForTraining==1'%TCut
|
| 105 |
|
|
EvalCut='%s && EventForTraining==0'%TCut
|
| 106 |
|
|
|
| 107 |
|
|
#load TRAIN trees
|
| 108 |
|
|
Tbackgrounds = []
|
| 109 |
|
|
TbScales = []
|
| 110 |
|
|
Tsignals = []
|
| 111 |
|
|
TsScales = []
|
| 112 |
|
|
|
| 113 |
|
|
for job in info:
|
| 114 |
|
|
if job.name in signals:
|
| 115 |
|
|
Tsignal = getTree(job,TrainCut)
|
| 116 |
|
|
ROOT.gDirectory.Cd(workdir)
|
| 117 |
|
|
TsScale = getScale(job)
|
| 118 |
|
|
Tsignals.append(Tsignal)
|
| 119 |
|
|
TsScales.append(TsScale)
|
| 120 |
|
|
|
| 121 |
|
|
if job.name in backgrounds:
|
| 122 |
|
|
Tbackground = getTree(job,TrainCut)
|
| 123 |
|
|
ROOT.gDirectory.Cd(workdir)
|
| 124 |
|
|
TbScale = getScale(job)
|
| 125 |
|
|
Tbackgrounds.append(Tbackground)
|
| 126 |
|
|
TbScales.append(TbScale)
|
| 127 |
|
|
|
| 128 |
|
|
#load EVALUATE trees
|
| 129 |
|
|
Ebackgrounds = []
|
| 130 |
|
|
EbScales = []
|
| 131 |
|
|
Esignals = []
|
| 132 |
|
|
EsScales = []
|
| 133 |
|
|
|
| 134 |
|
|
for job in info:
|
| 135 |
|
|
if job.name in signals:
|
| 136 |
|
|
Esignal = getTree(job,EvalCut)
|
| 137 |
|
|
ROOT.gDirectory.Cd(workdir)
|
| 138 |
|
|
EsScale = getScale(job)
|
| 139 |
|
|
Esignals.append(Esignal)
|
| 140 |
|
|
EsScales.append(EsScale)
|
| 141 |
|
|
|
| 142 |
|
|
if job.name in backgrounds:
|
| 143 |
|
|
Ebackground = getTree(job,EvalCut)
|
| 144 |
|
|
ROOT.gDirectory.Cd(workdir)
|
| 145 |
|
|
EbScale = getScale(job)
|
| 146 |
|
|
Ebackgrounds.append(Ebackground)
|
| 147 |
|
|
EbScales.append(EbScale)
|
| 148 |
|
|
|
| 149 |
|
|
output = ROOT.TFile.Open(fnameOutput, "RECREATE")
|
| 150 |
|
|
factory = ROOT.TMVA.Factory(factoryname, output, factorysettings)
|
| 151 |
|
|
|
| 152 |
|
|
#set input trees
|
| 153 |
|
|
for i in range(len(Tsignals)):
|
| 154 |
|
|
|
| 155 |
|
|
factory.AddSignalTree(Tsignals[i], TsScales[i], ROOT.TMVA.Types.kTraining)
|
| 156 |
|
|
factory.AddSignalTree(Esignals[i], EsScales[i], ROOT.TMVA.Types.kTesting)
|
| 157 |
|
|
|
| 158 |
|
|
for i in range(len(Tbackgrounds)):
|
| 159 |
|
|
if (Tbackgrounds[i].GetEntries()>0):
|
| 160 |
|
|
factory.AddBackgroundTree(Tbackgrounds[i], TbScales[i], ROOT.TMVA.Types.kTraining)
|
| 161 |
|
|
|
| 162 |
|
|
if (Ebackgrounds[i].GetEntries()>0):
|
| 163 |
|
|
factory.AddBackgroundTree(Ebackgrounds[i], EbScales[i], ROOT.TMVA.Types.kTesting)
|
| 164 |
|
|
|
| 165 |
|
|
|
| 166 |
|
|
for var in MVA_Vars['Nominal']:
|
| 167 |
|
|
factory.AddVariable(var,'D') # add the variables
|
| 168 |
|
|
#for var in spectators:
|
| 169 |
|
|
# factory.AddSpectator(var,'D') #add specators
|
| 170 |
|
|
|
| 171 |
|
|
#Execute TMVA
|
| 172 |
|
|
factory.SetSignalWeightExpression(weightF)
|
| 173 |
|
|
factory.Verbose()
|
| 174 |
|
|
factory.BookMethod(MVAtype,MVAname,MVAsettings)
|
| 175 |
|
|
factory.TrainAllMethods()
|
| 176 |
|
|
factory.TestAllMethods()
|
| 177 |
|
|
factory.EvaluateAllMethods()
|
| 178 |
|
|
output.Write()
|
| 179 |
|
|
|
| 180 |
|
|
#WRITE INFOFILE
|
| 181 |
|
|
infofile = open(Wdir+'/weights/'+factoryname+'_'+MVAname+'.info','w')
|
| 182 |
|
|
info=mvainfo(MVAname)
|
| 183 |
|
|
info.factoryname=factoryname
|
| 184 |
|
|
info.factorysettings=factorysettings
|
| 185 |
|
|
info.MVAtype=MVAtype
|
| 186 |
|
|
info.MVAsettings=MVAsettings
|
| 187 |
|
|
info.weightfilepath=Wdir+'/weights'
|
| 188 |
|
|
info.path=path
|
| 189 |
|
|
info.varset=treeVarSet
|
| 190 |
|
|
info.vars=MVA_Vars['Nominal']
|
| 191 |
peller |
1.3 |
#info.spectators=spectators
|
| 192 |
peller |
1.1 |
pickle.dump(info,infofile)
|
| 193 |
|
|
infofile.close()
|
| 194 |
|
|
|
| 195 |
|
|
# open the TMVA Gui
|
| 196 |
|
|
if gui == 'gui':
|
| 197 |
|
|
ROOT.gROOT.ProcessLine( ".L TMVAGui.C")
|
| 198 |
|
|
ROOT.gROOT.ProcessLine( "TMVAGui(\"%s\")" % fnameOutput )
|
| 199 |
|
|
ROOT.gApplication.Run()
|
| 200 |
|
|
|
| 201 |
|
|
|
