def main(args, opt): trees = {} for filename in os.listdir(args[0]): if not os.path.splitext(filename)[1] == '.root': continue isdata, pname, splitno = resolveFilename(filename) treefile = os.path.join(args[0], filename) tfile = ROOT.TFile.Open(treefile, 'READ') trees[pname] = tfile.Get(TREENAME) try: cachefile = open('genmlbhists.pck', 'r') hists = pickle.load(cachefile) print '>>> Read syst histos from cache (.svlsysthistos.pck)' cachefile.close() except IOError: hists = {} for tag, sel in MLBSELECTIONS: for pname in trees.keys(): print '... processing', pname, tag hists[(pname, tag)] = getHistoFromTree(trees[pname], sel=sel, var='GenMlb', hname="GenMlb_%s_%s" % (pname, tag), nbins=100, xmin=0, xmax=200, titlex=MLBAXISTITLE) cachefile = open('genmlbhists.pck', 'w') pickle.dump(hists, cachefile, pickle.HIGHEST_PROTOCOL) print '>>> Dumped histos to cachefile (genmlbhists.pck)' cachefile.close() ROOT.gStyle.SetOptTitle(0) ROOT.gStyle.SetOptStat(0) ROOT.gROOT.SetBatch(1) for tag, _ in MLBSELECTIONS: plot = RatioPlot('genmlb') plot.normalized = False plot.add(hists[('TTJets_MSDecays_172v5', tag)], 'Nominal') plot.add(hists[('TTJets_MSDecays_scaleup', tag)], 'Q^{2} scale up') plot.add(hists[('TTJets_MSDecays_scaledown', tag)], 'Q^{2} scale down') plot.tag = "Generator level m_{lb} shape" if tag == 'cor': plot.subtag = "Correct combinations" else: plot.subtag = "Wrong combinations" plot.ratiotitle = 'Ratio wrt nominal' plot.titlex = MLBAXISTITLE plot.tagpos = (0.22, 0.85) plot.subtagpos = (0.22, 0.78) plot.legpos = (0.20, 0.55) plot.ratiorange = (0.85, 1.15) plot.colors = [ROOT.kBlue - 3, ROOT.kRed - 4, ROOT.kOrange - 3] plot.show("genmlb_scale_%s" % tag, opt.outDir) return 0
def main(args, opt): trees = {} for filename in os.listdir(args[0]): if not os.path.splitext(filename)[1] == '.root': continue isdata, pname, splitno = resolveFilename(filename) treefile = os.path.join(args[0], filename) tfile = ROOT.TFile.Open(treefile,'READ') trees[pname] = tfile.Get(TREENAME) try: cachefile = open('genmlbhists.pck', 'r') hists = pickle.load(cachefile) print '>>> Read syst histos from cache (.svlsysthistos.pck)' cachefile.close() except IOError: hists = {} for tag,sel in MLBSELECTIONS: for pname in trees.keys(): print '... processing', pname, tag hists[(pname,tag)] = getHistoFromTree(trees[pname], sel=sel, var='GenMlb', hname="GenMlb_%s_%s"%(pname,tag), nbins=100,xmin=0,xmax=200, titlex=MLBAXISTITLE) cachefile = open('genmlbhists.pck', 'w') pickle.dump(hists, cachefile, pickle.HIGHEST_PROTOCOL) print '>>> Dumped histos to cachefile (genmlbhists.pck)' cachefile.close() ROOT.gStyle.SetOptTitle(0) ROOT.gStyle.SetOptStat(0) ROOT.gROOT.SetBatch(1) for tag,_ in MLBSELECTIONS: plot = RatioPlot('genmlb') plot.normalized = False plot.add(hists[('TTJets_MSDecays_172v5', tag)], 'Nominal') plot.add(hists[('TTJets_MSDecays_scaleup', tag)], 'Q^{2} scale up') plot.add(hists[('TTJets_MSDecays_scaledown', tag)], 'Q^{2} scale down') plot.tag = "Generator level m_{lb} shape" if tag == 'cor': plot.subtag = "Correct combinations" else: plot.subtag = "Wrong combinations" plot.ratiotitle = 'Ratio wrt nominal' plot.titlex = MLBAXISTITLE plot.tagpos = (0.22, 0.85) plot.subtagpos = (0.22, 0.78) plot.legpos = (0.20, 0.55) plot.ratiorange = (0.85, 1.15) plot.colors = [ROOT.kBlue-3, ROOT.kRed-4, ROOT.kOrange-3] plot.show("genmlb_scale_%s"%tag, opt.outDir) return 0
def makeHistos((url, name)): print "... processing", url tree = ROOT.TFile.Open(url,'READ').Get(TREENAME) histos = {} # selection = "SVMassWeight*(SVLCombRank>0 && %s)"%INCSEL selection = "(SVLCombRank>0 && %s)"%INCSEL # selection = "(SVLCombRank>0 && %s)"%EMSEL for varname, nbins, xmin, xmax, titlex in VARS: for ntk1,ntk2 in NTRKBINS: tksel = "(SVNtrk>=%d && SVNtrk<%d)"%(ntk1,ntk2) finalsel = "%s*%s" %(selection,tksel) histos[(varname, ntk1)] = getHistoFromTree( tree, sel=finalsel, var=varname, hname='%s_%s_%d'%(name, varname, ntk1), nbins=nbins, xmin=xmin, xmax=xmax, titlex=titlex) return name,histos
def makeHistos((url, name)): print "... processing", url tree = ROOT.TFile.Open(url, 'READ').Get(TREENAME) histos = {} # selection = "SVMassWeight*(SVLCombRank>0 && %s)"%INCSEL selection = "(SVLCombRank>0 && %s)" % INCSEL # selection = "(SVLCombRank>0 && %s)"%EMSEL for varname, nbins, xmin, xmax, titlex in VARS: for ntk1, ntk2 in NTRKBINS: tksel = "(SVNtrk>=%d && SVNtrk<%d)" % (ntk1, ntk2) finalsel = "%s*%s" % (selection, tksel) histos[(varname, ntk1)] = getHistoFromTree(tree, sel=finalsel, var=varname, hname='%s_%s_%d' % (name, varname, ntk1), nbins=nbins, xmin=xmin, xmax=xmax, titlex=titlex) return name, histos
def main(args, options): os.system('mkdir -p %s'%options.outDir) try: treefiles = {} # procname -> filename for filename in os.listdir(args[0]): if not os.path.splitext(filename)[1] == '.root': continue procname = filename.split('_',1)[1][:-5] treefiles[procname] = os.path.join(args[0],filename) except OSError: print "Not a valid input directory: %s" % args[0] return -1 except IndexError: print "Need to provide an input directory" return -1 ## Collect all the trees svltrees = {} # proc -> tree for proc in treefiles.keys(): tfile = ROOT.TFile.Open(treefiles[proc], 'READ') if not filterUseless(treefiles[proc]): continue svltrees[proc] = tfile.Get(TREENAME) ## Produce all the relevant histograms if not options.cached: masshistos = {} # (selection tag, process) -> histo methistos = {} # (selection tag, process) -> histo fittertkhistos = {} # (selection tag, process) -> [h_ntk1, h_ntk2, ...] for tag,sel,_ in SELECTIONS: for proc, tree in svltrees.iteritems(): if not filterUseless(treefiles[proc], sel): continue htag = ("%s_%s"%(tag, proc)).replace('.','') print ' ... processing %-30s %s htag=%s' % (proc, sel, htag) masshistos[(tag, proc)] = getHistoFromTree(tree, sel=sel, var='SVLMass', hname="SVLMass_%s"%(htag), titlex=MASSXAXISTITLE) methistos[(tag, proc)] = getHistoFromTree(tree, sel=sel, var='MET', hname="MET_%s"%(htag), xmin=0,xmax=200, titlex="Missing E_{T} [GeV]") fittertkhistos[(tag,proc)] = getNTrkHistos(tree, sel=sel, tag=htag, var='SVLMass', titlex=MASSXAXISTITLE) cachefile = open(".svlqcdmasshistos.pck", 'w') pickle.dump(masshistos, cachefile, pickle.HIGHEST_PROTOCOL) pickle.dump(methistos, cachefile, pickle.HIGHEST_PROTOCOL) pickle.dump(fittertkhistos, cachefile, pickle.HIGHEST_PROTOCOL) cachefile.close() else: cachefile = open(".svlqcdmasshistos.pck", 'r') masshistos = pickle.load(cachefile) methistos = pickle.load(cachefile) fittertkhistos = pickle.load(cachefile) cachefile.close() ######################################################### ## Write out the histograms, make data/mc plots outputFileName = os.path.join(options.outDir,'qcd_DataMCHists.root') ofi = ROOT.TFile(outputFileName, 'recreate') ofi.cd() for hist in [h for h in masshistos.values() + methistos.values()]: hist.Write(hist.GetName()) for hist in [h for hists in fittertkhistos.values() for h in hists]: hist.Write(hist.GetName()) ofi.Write() ofi.Close() ## Run the plotter to get scaled MET plots ## Can then use those to subtract non-QCD backgrounds from data template ## Overwrite some of the options options.filter = 'SVLMass,MET' ## only run SVLMass and MET plots # options.excludeProcesses = 'QCD' options.outFile = 'scaled_met_inputs.root' options.cutUnderOverFlow = True os.system('rm %s' % os.path.join(options.outDir, options.outFile)) runPlotter(outputFileName, options) ######################################################### ## Build the actual templates from the single histograms templates = {} # selection tag -> template histo inputfile = openTFile(os.path.join(options.outDir, options.outFile)) for tag,sel,_ in SELECTIONS: categories = ['MET', 'SVLMass'] for x,_ in NTRKBINS: categories.append('SVLMass_tot_%d'%int(x)) for category in categories: plotdirname = '%s_%s'%(category,tag) plotdir = inputfile.Get(plotdirname) h_bg = None h_data = None for tkey in plotdir.GetListOfKeys(): key = tkey.GetName() if key.startswith('Graph_from'): continue if key.startswith('MC8TeV_QCD'): continue hist = inputfile.Get('%s/%s'%(plotdirname,key)) if key.startswith('MC8TeV'): if not h_bg: h_bg = hist.Clone("%s_BGs" % tag) else: h_bg.Add(hist) if key.startswith('Data8TeV'): h_data = hist.Clone("%s_Data" % tag) ## Determine a suitable output name histname = '%s_template'%tag if category == 'MET': histname = "%s_%s" % ('met',histname) if 'tot' in category: tkbin = int(category.split('_')[2]) histname = "%s_%d" % (histname, tkbin) h_data_subtr = h_data.Clone(histname) ## Now subtract the combined MC from the data h_data_subtr.Add(h_bg, -1) dicttag = tag if category == 'MET': dicttag = 'met_%s'%tag if '_tot_' in category: dicttag = '%s_%d' % (tag, tkbin) templates[dicttag] = h_data_subtr ofi = ROOT.TFile(os.path.join(options.outDir,'qcd_templates.root'), 'recreate') ofi.cd() for hist in templates.values(): hist.Write(hist.GetName()) ofi.Write() ofi.Close() for key,hist in sorted(templates.iteritems()): print key ######################################################### ## Make a plot comparing the templates for tag,_,seltag in SELECTIONS: if not tag.endswith('_qcd'): continue templateplot = RatioPlot('qcdtemplates_%s'%tag) for key,hist in sorted(templates.iteritems()): if not tag in key: continue if key.startswith('met'): continue if key == tag: templateplot.add(hist, 'Inclusive') templateplot.reference = hist else: ntrkbin = int(key.rsplit('_',1)[1]) templateplot.add(hist, 'N_{track} = %d'%ntrkbin) templateplot.tag = 'QCD templates' templateplot.subtag = seltag templateplot.tagpos = (0.90, 0.85) templateplot.subtagpos = (0.90, 0.78) templateplot.legpos = (0.75, 0.25) templateplot.ratiotitle = 'Ratio wrt Inclusive' templateplot.extratext = '' #Work in Progress' templateplot.ratiorange = (0.2, 2.2) templateplot.colors = [ROOT.kBlack, ROOT.kBlue-8, ROOT.kAzure-2, ROOT.kCyan-3] templateplot.show("qcdtemplates_%s"%tag, options.outDir) templateplot.reset() return 0
def main(args, options): os.system('mkdir -p %s' % options.outDir) try: treefiles = {} # procname -> filename for filename in os.listdir(args[0]): if not os.path.splitext(filename)[1] == '.root': continue procname = filename.split('_', 1)[1][:-5] treefiles[procname] = os.path.join(args[0], filename) except OSError: print "Not a valid input directory: %s" % args[0] return -1 except IndexError: print "Need to provide an input directory" return -1 ## Collect all the trees svltrees = {} # proc -> tree for proc in treefiles.keys(): tfile = ROOT.TFile.Open(treefiles[proc], 'READ') if not filterUseless(treefiles[proc]): continue svltrees[proc] = tfile.Get(TREENAME) ## Produce all the relevant histograms if not options.cached: masshistos = {} # (selection tag, process) -> histo methistos = {} # (selection tag, process) -> histo fittertkhistos = { } # (selection tag, process) -> [h_ntk1, h_ntk2, ...] for tag, sel, _ in SELECTIONS: for proc, tree in svltrees.iteritems(): if not filterUseless(treefiles[proc], sel): continue htag = ("%s_%s" % (tag, proc)).replace('.', '') print ' ... processing %-30s %s htag=%s' % (proc, sel, htag) masshistos[(tag, proc)] = getHistoFromTree( tree, sel=sel, var='SVLMass', hname="SVLMass_%s" % (htag), titlex=MASSXAXISTITLE) methistos[(tag, proc)] = getHistoFromTree( tree, sel=sel, var='MET', hname="MET_%s" % (htag), xmin=0, xmax=200, titlex="Missing E_{T} [GeV]") fittertkhistos[(tag, proc)] = getNTrkHistos(tree, sel=sel, tag=htag, var='SVLMass', titlex=MASSXAXISTITLE) cachefile = open(".svlqcdmasshistos.pck", 'w') pickle.dump(masshistos, cachefile, pickle.HIGHEST_PROTOCOL) pickle.dump(methistos, cachefile, pickle.HIGHEST_PROTOCOL) pickle.dump(fittertkhistos, cachefile, pickle.HIGHEST_PROTOCOL) cachefile.close() else: cachefile = open(".svlqcdmasshistos.pck", 'r') masshistos = pickle.load(cachefile) methistos = pickle.load(cachefile) fittertkhistos = pickle.load(cachefile) cachefile.close() ######################################################### ## Write out the histograms, make data/mc plots outputFileName = os.path.join(options.outDir, 'qcd_DataMCHists.root') ofi = ROOT.TFile(outputFileName, 'recreate') ofi.cd() for hist in [h for h in masshistos.values() + methistos.values()]: hist.Write(hist.GetName()) for hist in [h for hists in fittertkhistos.values() for h in hists]: hist.Write(hist.GetName()) ofi.Write() ofi.Close() ## Run the plotter to get scaled MET plots ## Can then use those to subtract non-QCD backgrounds from data template ## Overwrite some of the options options.filter = 'SVLMass,MET' ## only run SVLMass and MET plots # options.excludeProcesses = 'QCD' options.outFile = 'scaled_met_inputs.root' options.cutUnderOverFlow = True os.system('rm %s' % os.path.join(options.outDir, options.outFile)) runPlotter(outputFileName, options) ######################################################### ## Build the actual templates from the single histograms templates = {} # selection tag -> template histo inputfile = openTFile(os.path.join(options.outDir, options.outFile)) for tag, sel, _ in SELECTIONS: categories = ['MET', 'SVLMass'] for x, _ in NTRKBINS: categories.append('SVLMass_tot_%d' % int(x)) for category in categories: plotdirname = '%s_%s' % (category, tag) plotdir = inputfile.Get(plotdirname) h_bg = None h_data = None for tkey in plotdir.GetListOfKeys(): key = tkey.GetName() if key.startswith('Graph_from'): continue if key.startswith('MC8TeV_QCD'): continue hist = inputfile.Get('%s/%s' % (plotdirname, key)) if key.startswith('MC8TeV'): if not h_bg: h_bg = hist.Clone("%s_BGs" % tag) else: h_bg.Add(hist) if key.startswith('Data8TeV'): h_data = hist.Clone("%s_Data" % tag) ## Determine a suitable output name histname = '%s_template' % tag if category == 'MET': histname = "%s_%s" % ('met', histname) if 'tot' in category: tkbin = int(category.split('_')[2]) histname = "%s_%d" % (histname, tkbin) h_data_subtr = h_data.Clone(histname) ## Now subtract the combined MC from the data h_data_subtr.Add(h_bg, -1) dicttag = tag if category == 'MET': dicttag = 'met_%s' % tag if '_tot_' in category: dicttag = '%s_%d' % (tag, tkbin) templates[dicttag] = h_data_subtr ofi = ROOT.TFile(os.path.join(options.outDir, 'qcd_templates.root'), 'recreate') ofi.cd() for hist in templates.values(): hist.Write(hist.GetName()) ofi.Write() ofi.Close() for key, hist in sorted(templates.iteritems()): print key ######################################################### ## Make a plot comparing the templates for tag, _, seltag in SELECTIONS: if not tag.endswith('_qcd'): continue templateplot = RatioPlot('qcdtemplates_%s' % tag) for key, hist in sorted(templates.iteritems()): if not tag in key: continue if key.startswith('met'): continue if key == tag: templateplot.add(hist, 'Inclusive') templateplot.reference = hist else: ntrkbin = int(key.rsplit('_', 1)[1]) templateplot.add(hist, 'N_{track} = %d' % ntrkbin) templateplot.tag = 'QCD templates' templateplot.subtag = seltag templateplot.tagpos = (0.90, 0.85) templateplot.subtagpos = (0.90, 0.78) templateplot.legpos = (0.75, 0.25) templateplot.ratiotitle = 'Ratio wrt Inclusive' templateplot.extratext = '' #Work in Progress' templateplot.ratiorange = (0.2, 2.2) templateplot.colors = [ ROOT.kBlack, ROOT.kBlue - 8, ROOT.kAzure - 2, ROOT.kCyan - 3 ] templateplot.show("qcdtemplates_%s" % tag, options.outDir) templateplot.reset() return 0