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#!/usr/bin/env python
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import pickle
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import ROOT
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from array import array
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import sys, os
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from optparse import OptionParser
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from copy import copy,deepcopy
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from math import sqrt
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ROOT.gROOT.SetBatch(True)
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#CONFIGURE
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argv = sys.argv
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parser = OptionParser()
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parser.add_option("-R", "--region", dest="region", default="",
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help="region to plot")
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parser.add_option("-C", "--config", dest="config", default=[], action="append",
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help="configuration file")
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(opts, args) = parser.parse_args(argv)
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if opts.config =="":
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opts.config = "config"
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from myutils import BetterConfigParser, printc, ParseInfo, mvainfo, StackMaker, HistoMaker
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print opts.config
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opts.config.append('8TeVconfig/vhbbPlotDef.ini')
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config = BetterConfigParser()
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config.read(opts.config)
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#path = opts.path
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region = opts.region
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# additional blinding cut:
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addBlindingCut = None
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if config.has_option('Plot_general','addBlindingCut'):
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addBlindingCut = config.get('Plot_general','addBlindingCut')
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print 'adding add. blinding cut'
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#get locations:
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Wdir=config.get('Directories','Wdir')
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samplesinfo=config.get('Directories','samplesinfo')
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path = config.get('Directories','plottingSamples')
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section='Plot:%s'%region
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info = ParseInfo(samplesinfo,path)
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#----------Histo from trees------------
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def doPlot():
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vars = (config.get(section, 'vars')).split(',')
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data = config.get(section,'Datas')
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mc = eval(config.get('Plot_general','samples'))
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SignalRegion = False
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if config.has_option(section,'Signal'):
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mc.append(config.get(section,'Signal'))
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SignalRegion = True
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datasamples = info.get_samples(data)
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mcsamples = info.get_samples(mc)
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GroupDict = eval(config.get('Plot_general','Group'))
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#GETALL AT ONCE
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options = []
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Stacks = []
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for i in range(len(vars)):
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Stacks.append(StackMaker(config,vars[i],region,SignalRegion))
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options.append(Stacks[i].options)
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print options
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Plotter=HistoMaker(mcsamples+datasamples,path,config,options,GroupDict)
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#print '\nProducing Plot of %s\n'%vars[v]
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Lhistos = [[] for _ in range(0,len(vars))]
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Ltyps = [[] for _ in range(0,len(vars))]
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Ldatas = [[] for _ in range(0,len(vars))]
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Ldatatyps = [[] for _ in range(0,len(vars))]
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Ldatanames = [[] for _ in range(0,len(vars))]
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#Find out Lumi:
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lumicounter=0.
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lumi=0.
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for job in datasamples:
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lumi+=float(job.lumi)
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lumicounter+=1.
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if lumicounter > 0:
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lumi=lumi/lumicounter
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Plotter.lumi=lumi
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mass = Stacks[0].mass
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for job in mcsamples:
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#hTempList, typList = Plotter.get_histos_from_tree(job)
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if addBlindingCut:
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hDictList = Plotter.get_histos_from_tree(job,config.get('Cuts',region)+' & ' + addBlindingCut)
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else:
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hDictList = Plotter.get_histos_from_tree(job)
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if job.name == mass:
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print job.name
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Overlaylist= deepcopy([hDictList[v].values()[0] for v in range(0,len(vars))])
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for v in range(0,len(vars)):
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Lhistos[v].append(hDictList[v].values()[0])
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Ltyps[v].append(hDictList[v].keys()[0])
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for job in datasamples:
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#hTemp, typ = Plotter.get_histos_from_tree(job)
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if addBlindingCut:
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dDictList = Plotter.get_histos_from_tree(job,config.get('Cuts',region)+' & ' + addBlindingCut)
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else:
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dDictList = Plotter.get_histos_from_tree(job)
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for v in range(0,len(vars)):
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Ldatas[v].append(dDictList[v].values()[0])
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Ldatatyps[v].append(dDictList[v].keys()[0])
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Ldatanames[v].append(job.name)
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for v in range(0,len(vars)):
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histos = Lhistos[v]
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typs = Ltyps[v]
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Stacks[v].histos = Lhistos[v]
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Stacks[v].typs = Ltyps[v]
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Stacks[v].datas = Ldatas[v]
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Stacks[v].datatyps = Ldatatyps[v]
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Stacks[v].datanames= Ldatanames[v]
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if SignalRegion:
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Stacks[v].overlay = Overlaylist[v]
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Stacks[v].lumi = lumi
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Stacks[v].doPlot()
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Stacks[v].histos = Lhistos[v]
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Stacks[v].typs = Ltyps[v]
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Stacks[v].datas = Ldatas[v]
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Stacks[v].datatyps = Ldatatyps[v]
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Stacks[v].datanames= Ldatanames[v]
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Stacks[v].normalize = True
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Stacks[v].options['pdfName'] = Stacks[v].options['pdfName'].replace('.pdf','_norm.pdf')
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Stacks[v].doPlot()
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print 'i am done!\n'
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#----------------------------------------------------
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doPlot()
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sys.exit(0)
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