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import ROOT
from .fitResidual import fitResidual
from .drawHistoAllChambers import drawHisto
layerCorrectionFactors = {'SL1':(1.17,1.16,1.15,1.14),
'SL2':(1.83,1.20,1.20,1.83),
'SL3':(1.14,1.15,1.16,1.17)}
def plotResLayer(fileName,sl,layer,
dir='DQMData/Run 1/DT/Run summary/DTCalibValidation',
option="HISTOPE1",draw=True):
mean_ymin = -0.02
mean_ymax = 0.02
sig_ymin = 0.
sig_ymax = 0.1
slType = sl
slStr = "SL%d" % slType
layerType = layer
layerStr = "Layer%d" % layerType
verbose = False
nSigmas = 2
ROOT.TH1.AddDirectory(False)
file = ROOT.TFile(fileName,'read')
wheels = (-2,-1,0,1,2)
stations = (1,2,3,4)
# (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 ...) ...
nBins = 250
if slType == 2: nBins = 180
histoMean = ROOT.TH1F("h_ResMeanAll_%s_%s" % (slStr,layerStr),"Mean of residuals",nBins,0,nBins)
histoSigma = ROOT.TH1F("h_ResSigmaAll_%s_%s" % (slStr,layerStr),"Sigma of residuals",nBins,0,nBins)
for st in stations:
nSectors = 12
if st == 4: nSectors = 14
if st == 4 and slType == 2: continue
if verbose: print("Station",st)
for wh in wheels:
if verbose: print("Wheel",wh)
for sec in range(1,nSectors+1):
if verbose: print("Sector",sec)
# Get histogram
histoName = "%s/Wheel%d/Station%d/Sector%d/%s/hResDist_STEP3_W%d_St%d_Sec%d_%s_%s" % (dir,wh,st,sec,slStr,wh,st,sec,slStr,layerStr)
print("Accessing",histoName)
histo = file.Get(histoName)
(histo,fitFunc) = fitResidual(histo,nSigmas,verbose)
fitMean = fitFunc.GetParameter(1)
fitMeanErr = fitFunc.GetParError(1)
fitSigma = fitFunc.GetParameter(2)
fitSigmaErr = fitFunc.GetParError(2)
layerIdx = (layer - 1)
corrFactor = layerCorrectionFactors[slStr][layerIdx]
binHistoNew = (st - 1)*60 + (wh + 2)*nSectors + sec
if verbose: print("Bin in summary histo",binHistoNew)
histoMean.SetBinContent(binHistoNew,fitMean)
histoMean.SetBinError(binHistoNew,fitMeanErr)
histoSigma.SetBinContent(binHistoNew,fitSigma*corrFactor)
histoSigma.SetBinError(binHistoNew,fitSigmaErr*corrFactor)
if sec == 1:
label = "Wheel %d" % wh
if wh == -2: label += " MB%d" % st
histoMean.GetXaxis().SetBinLabel(binHistoNew,label)
histoSigma.GetXaxis().SetBinLabel(binHistoNew,label)
objectsMean = drawHisto(histoMean,title="Mean of residuals (cm)",
ymin=mean_ymin,ymax=mean_ymax,option=option,draw=draw)
objectsSigma = drawHisto(histoSigma,title="Resolution (cm)",
ymin=sig_ymin,ymax=sig_ymax,option=option,draw=draw)
return (objectsMean,objectsSigma)
def plot(fileName,sl,
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 )
def plotMean(fileName,sl,dir='DQMData/Run 1/DT/Run summary/DTCalibValidation',option='HISTOPE1'):
type = 'mean'
objs = plot(fileName,sl,dir,type,option)
return objs
def plotSigma(fileName,sl,dir='DQMData/Run 1/DT/Run summary/DTCalibValidation',option='HISTOPE1'):
type = 'sigma'
objs = plot(fileName,sl,dir,type,option)
return objs
def plotSigmaAll(fileName,dir='DQMData/Run 1/DT/Run summary/DTCalibValidation',option='HISTOPE1',outputFileName=''):
colors = (2,4,12,44,55,38,27,46)
markers = (24,25,26,27,28,30,32,5)
slList = (1,2,3)
labels = ('R-#phi SL1','R-z SL2','R-#phi SL3')
canvas = None
objects = None
histos = []
idx = 0
for sl in slList:
draw = False
if not idx: draw = True
objs = plotSigma(fileName,sl,dir,option)
histos.append(objs[1][1])
histos[-1].SetName( "%s_%d" % (histos[-1].GetName(),idx) )
if not idx:
canvas = objs[0][1]
#objects = objs[2][1]
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")
if not objects: objects = [legend]
else: objects.append(legend)
if outputFileName:
outputFile = ROOT.TFile(outputFileName,'recreate')
outputFile.cd()
for histo in histos: histo.Write()
outputFile.Close()
return 0
else:
return (canvas,histos,objects)
#def plotDataVsMCFromFile(fileNameData,fileNameMC,labels=[]):
def plotFromFile(fileNames,labels=[]):
AddDirectoryStatus_ = ROOT.TH1.AddDirectoryStatus()
ROOT.TH1.AddDirectory(False)
#fileData = ROOT.TFile(fileNameData,'read')
#fileMC = ROOT.TFile(fileNameMC,'read')
rootFiles = []
for file in fileNames: rootFiles.append( ROOT.TFile(file,'read') )
variables = ['h_AverageAll_SL1_0',
'h_AverageAll_SL2_1',
'h_AverageAll_SL3_2']
colors = (1,2,4,12,44,55,38,27,46)
markers = (20,24,25,26,27,28,30,32,5)
objects = None
canvases = []
legends = []
histos = []
idx_var = 0
for var in variables:
print("Accessing",var)
#histoData = fileData.Get(var)
#histoData.SetName(histoData.GetName() + "_data")
#histoMC = fileMC.Get(var)
#histoMC.SetName(histoMC.GetName() + "_mc")
#histoData.SetLineColor(1)
#histoData.SetMarkerStyle(20)
#histoData.SetMarkerSize(1.4)
#histoData.SetMarkerColor(1)
#histoMC.SetLineColor(2)
#histoMC.SetMarkerStyle(24)
#histoMC.SetMarkerSize(1.4)
#histoMC.SetMarkerColor(2)
histos_tmp = []
idx = 0
for file in rootFiles:
histos_tmp.append( file.Get(var) )
histos_tmp[-1].SetName( "%s_%d" % (histos_tmp[-1].GetName(),idx) )
print("Created",histos_tmp[-1].GetName())
histos_tmp[-1].SetLineColor(colors[ idx % len(colors) ])
histos_tmp[-1].SetMarkerColor(colors[ idx % len(colors) ])
histos_tmp[-1].SetMarkerStyle(markers[ idx % len(markers) ])
histos_tmp[-1].SetMarkerSize(1.4)
idx += 1
histos.append( histos_tmp )
canvases.append( ROOT.TCanvas("c_" + var,var) )
canvases[-1].SetGridx()
canvases[-1].SetGridy()
canvases[-1].SetFillColor(0)
canvases[-1].cd()
#histoData.Draw()
#histoMC.Draw("SAME")
#histos.append( (histoData,histoMC) )
histos[-1][0].Draw()
for histo in histos[-1][1:]: histo.Draw("SAME")
if len(labels):
#labelData = labels[0]
#labelMC = labels[1]
legends.append( ROOT.TLegend(0.4,0.7,0.95,0.8) )
idx = 0
for histo in histos[-1]:
legends[-1].AddEntry(histo,labels[idx],"LP")
idx += 1
legends[-1].SetFillColor( canvases[-1].GetFillColor() )
legends[-1].Draw("SAME")
idx_var += 1
if not objects: objects = [legends]
else: objects.append(legends)
ROOT.TH1.AddDirectory(AddDirectoryStatus_)
return (canvases,histos,objects)
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