Python RooArgList.remove方法代码示例

# 需要导入模块: from ROOT import RooArgList [as 别名]
# 或者: from ROOT.RooArgList import remove [as 别名]
    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)
#.........这里部分代码省略.........

# 需要导入模块: from ROOT import RooArgList [as 别名]
# 或者: from ROOT.RooArgList import remove [as 别名]
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", "@[email protected]*@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', '@[email protected]', 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)