plotResidualsPerLayer Namespace Reference

Functions
def	plot
def	plotFromFile
def	plotMean
def	plotResLayer
def	plotSigma
def	plotSigmaAll

Variables
dictionary	layerCorrectionFactors

Function Documentation

def plotResidualsPerLayer.plot	(		fileName,
			sl,
			dir = 'DQMData/Run 1/DT/Run summary/DTCalibValidation',
			type = 'mean',
			option = 'HISTOPE1'
	)

Definition at line 83 of file plotResidualsPerLayer.py.

References plotResLayer(), print(), and sistrip::SpyUtilities.range().

Referenced by plotMean(), plotResLayer(), and plotSigma().

                  dir='DQMData/Run 1/DT/Run summary/DTCalibValidation',type='mean',option='HISTOPE1'):
    colors = (2,4,12,44,55,38,27,46)
    markers = (24,25,26,27,28,30,32,5)
    labels=['Layer 1','Layer 2','Layer 3','Layer 4']
    idx_type = None
    if type == 'mean': idx_type = 0
    elif type == 'sigma': idx_type = 1
    else: raise RuntimeError("Wrong option: %s" % type)

    idx = 0
    canvas = None
    objects = None
    histos = []
    for layer in range(1,5):
        draw = False
        if not idx: draw = True

        objs = plotResLayer(fileName,sl,layer,dir,option,draw)
        histos.append(objs[idx_type][1])
        histos[-1].SetName( "%s_%d" % (histos[-1].GetName(),idx) )
        if not idx:
            canvas = objs[idx_type][0]
            objects = objs[idx_type][2]

        canvas.cd()
        if idx:
            histos[-1].SetLineColor(colors[ (idx - 1) % len(colors) ])
            histos[-1].SetMarkerColor(colors[ (idx - 1) % len(colors) ])
            histos[-1].SetMarkerStyle(markers[ (idx - 1) % len(markers) ])

            histos[-1].Draw(option + "SAME")

        idx += 1

    legend = ROOT.TLegend(0.4,0.7,0.95,0.8)
    for idx in range( len(histos) ):
        histo = histos[idx]
        label = histo.GetName()
        if len(labels): label = labels[idx]
        legend.AddEntry(histo,label,"LP")

        idx += 1

    canvas.cd()
    legend.SetFillColor( canvas.GetFillColor() )
    legend.Draw("SAME")
    objects.append(legend)

    # Compute averages
    # (Wh-2 MB1 Sec1 ... Wh-2 MB1 Sec12 ... Wh-1 MB1 Sec1 ... Wh-1 MB1 Sec12 ...)
    # (Wh-2 MB2 Sec1 ... Wh-2 MB2 Sec12 ... Wh-1 MB2 Sec1 ... Wh-1 MB1 Sec12 ...) ...  
    import math
    wheels = (-2,-1,0,1,2)
    stations = (1,2,3,4)
    slType = sl
    slStr = "SL%d" % slType

    nBinsAve = len(stations)*len(wheels)
    histoAverage = ROOT.TH1F("h_AverageAll_" + slStr,"",nBinsAve,0,nBinsAve)
    averages = {}
    averagesErr = {}
    averagesSumw = {}
    print("Averages:")
    for st in stations:
        nSectors = 12
        if st == 4: nSectors = 14
        if st == 4 and slType == 2: continue 
        for wh in wheels:
            binHistoAve = (st - 1)*5 + (wh + 2) + 1
            label = "Wheel %d" % wh
            if wh == -2: label += " MB%d" % st  
            histoAverage.GetXaxis().SetBinLabel(binHistoAve,label) 

            averages[(st,wh)] = 0.
            averagesSumw[(st,wh)] = 0.
            for sec in range(1,nSectors+1):
                binHisto = (st - 1)*60 + (wh + 2)*nSectors + sec
                for idx in range( len(histos) ):
                    histo = histos[idx]
                    value = histo.GetBinContent( binHisto ) 
                    error = histo.GetBinError( binHisto ) 
                    averages[(st,wh)]     += value/( error*error ) 
                    averagesSumw[(st,wh)] += 1./( error*error )
            # Average per (st,wh)
            averages[(st,wh)] = averages[(st,wh)]/averagesSumw[(st,wh)]
            averagesErr[(st,wh)] = math.sqrt( 1./averagesSumw[(st,wh)] )
            histoAverage.SetBinContent(binHistoAve,averages[(st,wh)])
            histoAverage.SetBinError(binHistoAve,averagesErr[(st,wh)])
            print("Station %d, Wheel %d: %.4f +/- %.6f" % (st,wh,averages[(st,wh)],averagesErr[(st,wh)]))

    canvasAverage = ROOT.TCanvas("c_" + histoAverage.GetName())
    canvasAverage.SetGridx()
    canvasAverage.SetGridy()
    canvasAverage.SetFillColor( 0 )
    canvasAverage.cd()
    mean_ymin = -0.02
    mean_ymax =  0.02
    sig_ymin = 0.
    sig_ymax = 0.1
    if type == 'mean':
        histoAverage.GetYaxis().SetTitle("Mean of residuals (cm)")
        histoAverage.GetYaxis().SetRangeUser(mean_ymin,mean_ymax)
    elif type == 'sigma':
        histoAverage.GetYaxis().SetTitle("Resolution (cm)")
        histoAverage.GetYaxis().SetRangeUser(sig_ymin,sig_ymax)

    histoAverage.SetStats(0)
    histoAverage.SetLineWidth(2)
    histoAverage.SetMarkerStyle( 27 )
    histoAverage.SetMarkerSize( 1.5 )
    histoAverage.LabelsOption("d","X")
    histoAverage.Draw("E2")           

    return ( (canvas,canvasAverage),(histos,histoAverage),objects )