def stackedPlot(self, var, logy = False, pdfName = None, Silent = False): if not pdfName: pdfName = 'total' xvar = self.ws.var(var) nbins = xvar.getBins() # if hasattr(self.pars, 'plotRanges') and not xvar.hasRange('plotRange'): # xvar.setRange('plotRange', self.pars.plotRanges[var][1], # self.pars.plotRanges[var][2]) # xvar.setBins(self.pars.plotRanges[var][0], 'plotBins') # elif not xvar.hasRange('plotRange'): # xvar.setRange('plotRange', xvar.getMin(), xvar.getMax()) # xvar.setBins(nbins, 'plotBins') sframe = xvar.frame(RooFit.Range('plotRange'), RooFit.Bins(xvar.getBins('plotBins'))) sframe.SetName("%s_stacked" % var) pdf = self.ws.pdf(pdfName) if isinstance(pdf, RooAddPdf): compList = RooArgList(pdf.pdfList()) else: compList = None data = self.ws.data('data_obs') nexp = pdf.expectedEvents(self.ws.set('obsSet')) if not Silent: print pdf.GetName(),'expected: %.0f' % (nexp) print 'data events: %.0f' % (data.sumEntries()) if nexp < 1: nexp = data.sumEntries() theComponents = [] if self.pars.includeSignal: theComponents += self.pars.signals theComponents += self.pars.backgrounds data.plotOn(sframe, RooFit.Invisible(), RooFit.Binning('plotBins')) # dataHist = RooAbsData.createHistogram(data,'dataHist_%s' % var, xvar, # RooFit.Binning('%sBinning' % var)) # #dataHist.Scale(1., 'width') # invData = RooHist(dataHist, 1., 1, RooAbsData.SumW2, 1.0, False) # #invData.Print('v') # sframe.addPlotable(invData, 'pe', True, True) for (idx,component) in enumerate(theComponents): if not Silent: print 'plotting',component,'...', if hasattr(self.pars, '%sPlotting' % (component)): plotCharacteristics = getattr(self.pars, '%sPlotting' % \ (component)) else: plotCharacteristics = {'color' : colorwheel[idx%6], 'title' : component } compCmd = RooCmdArg.none() if compList: compSet = RooArgSet(compList) if compSet.getSize() > 0: compCmd = RooFit.Components(compSet) removals = compList.selectByName('%s*' % component) compList.remove(removals) if not Silent: print 'events', self.ws.function('f_%s_norm' % component).getVal() sys.stdout.flush() if abs(self.ws.function('f_%s_norm' % component).getVal()) >= 1.: pdf.plotOn(sframe, #RooFit.ProjWData(data), RooFit.DrawOption('LF'), RooFit.FillStyle(1001), RooFit.FillColor(plotCharacteristics['color']), RooFit.LineColor(plotCharacteristics['color']), RooFit.VLines(), RooFit.Range('plotRange'), RooFit.NormRange('plotRange'), RooFit.Normalization(nexp, RooAbsReal.NumEvent), compCmd ) tmpCurve = sframe.getCurve() tmpCurve.SetName(component) tmpCurve.SetTitle(plotCharacteristics['title']) if 'visible' in plotCharacteristics: sframe.setInvisible(component, plotCharacteristics['visible']) data.plotOn(sframe, RooFit.Name('theData'), RooFit.Binning('plotBins')) sframe.getHist('theData').SetTitle('data') # theData = RooHist(dataHist, 1., 1, RooAbsData.SumW2, 1.0, True) # theData.SetName('theData') # theData.SetTitle('data') # sframe.addPlotable(theData, 'pe') if (logy): sframe.SetMinimum(0.01) sframe.SetMaximum(1.0e6) else: sframe.SetMaximum(sframe.GetMaximum()*1.35) pass excluded = (var in self.pars.exclude) bname = var if not excluded: for v in self.pars.exclude: if hasattr(self.pars, 'varNames') and \ (self.pars.varNames[v] == var): excluded = True bname = v if excluded: blinder = TBox(self.pars.exclude[bname][0], sframe.GetMinimum(), self.pars.exclude[bname][1], sframe.GetMaximum()) # blinder.SetName('blinder') # blinder.SetTitle('signal region') blinder.SetFillColor(kBlack) if self.pars.blind: blinder.SetFillStyle(1001) else: blinder.SetFillStyle(0) blinder.SetLineStyle(2) sframe.addObject(blinder) elif self.pars.blind: if not Silent: print "blind but can't find exclusion region for", var print 'excluded',excluded,self.pars.exclude print 'hiding data points' sframe.setInvisible('theData', True) else: sframe.setInvisible('theData', False) #sframe.GetYaxis().SetTitle('Events / GeV') # dataHist.IsA().Destructor(dataHist) if not Silent: print xvar.setBins(nbins) return sframe
def findOnePe(hist, ws, name='x', Npe=1): fitPed(hist, ws, name) x = ws.var(name) ped = ws.pdf('ped') pedWidth = ws.var('pedWidth') pdfs = RooArgList(ped) pdfList = [] fped = RooRealVar('fped', 'f_{ped}', 0.8, 0., 1.) fractions = RooArgList(fped) fList = [] peList = [] peMean = RooRealVar('peMean', 'mean_{pe}', 6., 0., 20.) peWidth = RooRealVar('peWidth', 'width_{pe}', pedWidth.getVal(), 0., 10.) for i in range(0, Npe): pem = RooFormulaVar('pem{0}'.format(i + 1), '@0+{0}*@1'.format(i + 1), RooArgList(ws.var('pedMean'), peMean)) peList.append(pem) npepdf = RooGaussian('pe{0}pdf'.format(i + 1), 'pe{0}pdf'.format(i + 1), x, pem, pedWidth) pdfs.add(npepdf) pdfList.append(npepdf) fnpe = RooRealVar('fpe{0}'.format(i + 1), 'fpe{0}'.format(i + 1), 0.5, -0.1, 1.0) fractions.add(fnpe) fList.append(fnpe) #bgMean = RooRealVar("bgMean", "bgMean", 6.0, x.getMin(), x.getMax()) bgScale = RooRealVar("bgScale", "bgScale", 0.5, -1.0, Npe + 1.0) bgMean = RooFormulaVar("bgMean", "@1+@0*@2", RooArgList(peMean, ws.var('pedMean'), bgScale)) bgWidthL = RooRealVar("bgWidthL", "bgWidthL", pedWidth.getVal() * 2, 0., 25.) bgWidthR = RooRealVar("bgWidthR", "bgWidthR", pedWidth.getVal() * 7, 0., 25.) bgGauss = RooBifurGauss("bgGauss", "bgGauss", x, bgMean, bgWidthR, bgWidthR) if (Npe > 1): pdfs.add(bgGauss) else: fractions.remove(fractions.at(fractions.getSize() - 1)) ## pem = RooFormulaVar('pem', '@0+@1', RooArgList(peMean, ws.var('pedMean'))) ## firstPe = RooGaussian('firstPe', 'firstPe', x, pem, peWidth) ## pdfs.Print("v") ## fractions.Print("v") pedPlusOne = RooAddPdf('pedPlusOne', 'pedPlusOne', pdfs, fractions, True) ## pedWidth = ped.GetParameter(2) ## pedMean = ped.GetParameter(1) ## pedA = ped.GetParameter(0) secondMax = hist.GetMaximumBin() + 1 goingDown = True maxVal = hist.GetBinContent(secondMax) foundMax = False while (not foundMax) and (secondMax < hist.GetNbinsX()): tmpVal = hist.GetBinContent(secondMax + 1) if (tmpVal < maxVal): if not goingDown: foundMax = True else: goingDown = True maxVal = tmpVal secondMax += 1 elif (tmpVal > maxVal): goingDown = False maxVal = tmpVal secondMax += 1 else: maxVal = tmpVal secondMax += 1 secondMaxx = hist.GetBinCenter(secondMax) print 'found 2nd maximum in bin', secondMax, 'value', secondMaxx ## peMean.setVal(secondMaxx) ## bgMean.setVal(secondMaxx*0.6) x.setRange('pedPlus_fit', x.getMin(), ws.var('pedMean').getVal() + pedWidth.getVal() * 6. * (Npe + 0)) pedPlusOne.fitTo(ws.data('ds'), RooFit.Minos(False), RooFit.Range('pedPlus_fit'), RooFit.PrintLevel(1)) getattr(ws, 'import')(pedPlusOne)
def findOnePe(hist, ws, name='x', Npe = 1): fitPed(hist, ws, name) x = ws.var(name) ped = ws.pdf('ped') pedWidth = ws.var('pedWidth') pdfs = RooArgList(ped) pdfList = [] fped = RooRealVar('fped', 'f_{ped}', 0.8, 0., 1.) fractions = RooArgList(fped) fList = [] peList = [] peMean = RooRealVar('peMean', 'mean_{pe}', 6., 0., 20.) peWidth = RooRealVar('peWidth', 'width_{pe}', pedWidth.getVal(), 0., 10.) for i in range(0, Npe): pem = RooFormulaVar('pem{0}'.format(i+1), '@0+{0}*@1'.format(i+1), RooArgList(ws.var('pedMean'), peMean)) peList.append(pem) npepdf = RooGaussian('pe{0}pdf'.format(i+1), 'pe{0}pdf'.format(i+1), x, pem, pedWidth) pdfs.add(npepdf) pdfList.append(npepdf) fnpe = RooRealVar('fpe{0}'.format(i+1), 'fpe{0}'.format(i+1), 0.5, -0.1, 1.0) fractions.add(fnpe) fList.append(fnpe) #bgMean = RooRealVar("bgMean", "bgMean", 6.0, x.getMin(), x.getMax()) bgScale = RooRealVar("bgScale", "bgScale", 0.5, -1.0, Npe + 1.0) bgMean = RooFormulaVar("bgMean", "@1+@0*@2", RooArgList(peMean, ws.var('pedMean'), bgScale)) bgWidthL = RooRealVar("bgWidthL", "bgWidthL", pedWidth.getVal()*2, 0., 25.) bgWidthR = RooRealVar("bgWidthR", "bgWidthR", pedWidth.getVal()*7, 0., 25.) bgGauss = RooBifurGauss("bgGauss", "bgGauss", x, bgMean, bgWidthR, bgWidthR) if (Npe > 1): pdfs.add(bgGauss) else: fractions.remove(fractions.at(fractions.getSize()-1)) ## pem = RooFormulaVar('pem', '@0+@1', RooArgList(peMean, ws.var('pedMean'))) ## firstPe = RooGaussian('firstPe', 'firstPe', x, pem, peWidth) ## pdfs.Print("v") ## fractions.Print("v") pedPlusOne = RooAddPdf('pedPlusOne', 'pedPlusOne', pdfs, fractions, True) ## pedWidth = ped.GetParameter(2) ## pedMean = ped.GetParameter(1) ## pedA = ped.GetParameter(0) secondMax = hist.GetMaximumBin() + 1 goingDown = True maxVal = hist.GetBinContent(secondMax) foundMax = False while (not foundMax) and (secondMax < hist.GetNbinsX()): tmpVal = hist.GetBinContent(secondMax+1) if (tmpVal < maxVal): if not goingDown: foundMax = True else: goingDown = True maxVal = tmpVal secondMax += 1 elif (tmpVal > maxVal): goingDown = False maxVal = tmpVal secondMax += 1 else: maxVal = tmpVal secondMax += 1 secondMaxx = hist.GetBinCenter(secondMax) print 'found 2nd maximum in bin',secondMax,'value',secondMaxx ## peMean.setVal(secondMaxx) ## bgMean.setVal(secondMaxx*0.6) x.setRange('pedPlus_fit', x.getMin(), ws.var('pedMean').getVal()+pedWidth.getVal()*6.*(Npe+0)) pedPlusOne.fitTo(ws.data('ds'), RooFit.Minos(False), RooFit.Range('pedPlus_fit'), RooFit.PrintLevel(1)) getattr(ws, 'import')(pedPlusOne)
def stackedPlot(self, var, logy = False, pdfName = None, Silent = False): if not pdfName: pdfName = 'total' xvar = self.ws.var(var) nbins = xvar.getBins() if hasattr(self.pars, 'plotRanges'): xvar.setRange('plotRange', self.pars.plotRanges[var][1], self.pars.plotRanges[var][2]) xvar.setBins(self.pars.plotRanges[var][0], 'plotBins') else: xvar.setRange('plotRange', xvar.getMin(), xvar.getMax()) xvar.setBins(nbins, 'plotBins') sframe = xvar.frame() sframe.SetName("%s_stacked" % var) pdf = self.ws.pdf(pdfName) if isinstance(pdf, RooAddPdf): compList = RooArgList(pdf.pdfList()) else: compList = None data = self.ws.data('data_obs') nexp = pdf.expectedEvents(self.ws.set('obsSet')) if not Silent: print pdf.GetName(),'expected: %.0f' % (nexp) print 'data events: %.0f' % (data.sumEntries()) if nexp < 1: nexp = data.sumEntries() theComponents = [] if self.pars.includeSignal: theComponents += self.pars.signals theComponents += self.pars.backgrounds data.plotOn(sframe, RooFit.Invisible(), RooFit.Binning('plotBins')) # dataHist = RooAbsData.createHistogram(data,'dataHist_%s' % var, xvar, # RooFit.Binning('%sBinning' % var)) # #dataHist.Scale(1., 'width') # invData = RooHist(dataHist, 1., 1, RooAbsData.SumW2, 1.0, False) # #invData.Print('v') # sframe.addPlotable(invData, 'pe', True, True) for (idx,component) in enumerate(theComponents): if not Silent: print 'plotting',component,'...', if hasattr(self.pars, '%sPlotting' % (component)): plotCharacteristics = getattr(self.pars, '%sPlotting' % \ (component)) else: plotCharacteristics = {'color' : colorwheel[idx%6], 'title' : component } compCmd = RooCmdArg.none() if compList: compSet = RooArgSet(compList) if compSet.getSize() > 0: compCmd = RooFit.Components(compSet) removals = compList.selectByName('%s*' % component) compList.remove(removals) if not Silent: print 'events', self.ws.function('f_%s_norm' % component).getVal() sys.stdout.flush() if abs(self.ws.function('f_%s_norm' % component).getVal()) >= 1.: pdf.plotOn(sframe, #RooFit.ProjWData(data), RooFit.DrawOption('LF'), RooFit.FillStyle(1001), RooFit.FillColor(plotCharacteristics['color']), RooFit.LineColor(plotCharacteristics['color']), RooFit.VLines(), RooFit.Range('plotRange'), RooFit.NormRange('plotRange'), RooFit.Normalization(nexp, RooAbsReal.NumEvent), compCmd ) tmpCurve = sframe.getCurve() tmpCurve.SetName(component) tmpCurve.SetTitle(plotCharacteristics['title']) if 'visible' in plotCharacteristics: sframe.setInvisible(component, plotCharacteristics['visible']) data.plotOn(sframe, RooFit.Name('theData'), RooFit.Binning('plotBins')) sframe.getHist('theData').SetTitle('data') # theData = RooHist(dataHist, 1., 1, RooAbsData.SumW2, 1.0, True) # theData.SetName('theData') # theData.SetTitle('data') # sframe.addPlotable(theData, 'pe') if (logy): sframe.SetMinimum(0.01) sframe.SetMaximum(1.0e6) else: sframe.SetMaximum(sframe.GetMaximum()*1.35) pass excluded = (var in self.pars.exclude) bname = var if not excluded: for v in self.pars.exclude: if hasattr(self.pars, 'varNames') and \ (self.pars.varNames[v] == var): excluded = True bname = v if excluded: blinder = TBox(self.pars.exclude[bname][0], sframe.GetMinimum(), self.pars.exclude[bname][1], sframe.GetMaximum()) # blinder.SetName('blinder') # blinder.SetTitle('signal region') blinder.SetFillColor(kBlack) if self.pars.blind: blinder.SetFillStyle(1001) else: blinder.SetFillStyle(0) blinder.SetLineStyle(2) sframe.addObject(blinder) elif self.pars.blind: if not Silent: print "blind but can't find exclusion region for", var print 'excluded',excluded,self.pars.exclude print 'hiding data points' sframe.setInvisible('theData', True) #sframe.GetYaxis().SetTitle('Events / GeV') # dataHist.IsA().Destructor(dataHist) if not Silent: print xvar.setBins(nbins) return sframe