def plot_projection(t_file, hist_name):
h = t_file.Get(hist_name)
c = TCanvas('c_extrapol','c_extrapol',10,10,1400,900)
c.Divide(1,3)
c.cd(1)
h.Draw('colz')
h.FitSlicesY(0,5,25,10)
hM = gDirectory.Get(h.GetName()+'_1')
if hM == None:
print 'no slice 1 histo found'
else:
c.cd(2)
hM.Draw()
hW = gDirectory.Get(h.GetName()+'_2')
if hW == None:
print 'no slice 2 histo found'
else:
c.cd(3)
hW.Draw()
f = TF1('fpol2','pol2',h.GetXaxis().GetBinCenter(6),h.GetXaxis().GetBinCenter(24))
hW.Fit(f,'R')
min_val = f.GetParameter(1)/(-2.0*f.GetParameter(2))
plotutils.myText(0.5,0.5,'min_val=%.0f mm' % min_val,0.07,2)
ans = raw_input('continue?')
c.Update()
c.SaveAs(hist_name.replace(' ','_') + '.png')
def fitMom(f,name):
c = TCanvas('c','c',10,10,700,500)
h_p = f.Get(name)
setStyle(h_p)
peakbin = findFEEPeakBin(h_p)
l = h_p.GetBinCenter(peakbin)-0.11
h = h_p.GetBinCenter(peakbin)+0.2
f_p = TF1('f'+'_'+name,'gaus',l,h)
h_p.Fit(f_p,'R')
h_p.Draw()
plotutils.myText(0.5,0.85,'<m>=%.2f #sigma=%.2f'%(f_p.GetParameter(1),f_p.GetParameter(2)), 0.05, 2)
c.SaveAs(name + '-' + getFileName(f) + args.tag + '.png')
ans = raw_input('continue?')
def plotResiduals(f,name,half):
f.cd()
c = TCanvas('c','c',10,10,700,500)
c.Print('res-' +name+'-'+half + '-' + getFileName(f) + args.tag + '.ps[')
histos = plotutils.getHistograms(gDirectory)
print 'found ', len(histos), ' histograms'
res_map = {}
for h_p in histos:
if re.match('^' + name + '.*' + half + '$', h_p.GetName() ) and not 'large' in h_p.GetName() and not 'truth' in h_p.GetName() :
print 'found ' , h_p.GetName()
sensorName = utils.getSensor(h_p.GetName())
print 'sensor ', sensorName
setStyle(h_p)
peakbin = findPeakBin(h_p)
l = h_p.GetBinCenter(peakbin) - 5*h_p.GetRMS()
h = h_p.GetBinCenter(peakbin) + 5*h_p.GetRMS()
print 'peakbin ', peakbin, ' c ' , h_p.GetBinCenter(peakbin), ' l ', l, ' h', h
f_p = TF1('f'+'_'+name+'-'+half+'_'+h_p.GetName(),'gaus',l,h)
h_p.Fit(f_p,'R')
c1 = TCanvas('c1-'+h_p.GetName(),'c1-'+h_p.GetName(),10,10,700,500)
h_p.Draw()
plotutils.myText(0.5,0.85,'<m>=%.2f #sigma=%.2f'%(f_p.GetParameter(1),f_p.GetParameter(2)), 0.05, 2)
res_map[sensorName] = f_p
c1.Print('res-' +name+'-'+half + '-' + getFileName(f) + args.tag + '.ps')
#c.SaveAs(name + '-' + getFileName(f) + args.tag + '.png')
#ans = raw_input('continue?')
grMean = TGraph()
grSigma = TGraph()
i=0
binLabels = []
res_map_sort = sorted(res_map.keys())
print res_map
print 'found ', len(res_map), ' res plots'
for sensor in res_map_sort:
fit = res_map[sensor]
grMean.SetPoint(i,i,fit.GetParameter(1))
grSigma.SetPoint(i,i,fit.GetParameter(2))
binLabels.append(sensor)
i=i+1
plotutils.setBinLabels(grMean,binLabels)
plotutils.setBinLabels(grSigma,binLabels)
grMean.SetTitle(name+'-'+half + '-' + getFileName(f) + args.tag + ';;'+name+'-'+half+' mean')
grMean.SetMarkerStyle(20)
c1 = TCanvas('c1-res','c1-res',10,10,700,500)
c1.SetBottomMargin(0.4)
grMean.Draw('ALP')
c1.Print('res-' +name+'-'+half + '-' + getFileName(f) + args.tag + '.ps')
grSigma.SetTitle(name+'-'+half + '-' + getFileName(f) + args.tag + ';;'+name+'-'+half+' #sigma')
grSigma.SetMarkerStyle(20)
c1 = TCanvas('c1-ress','c1-ress',10,10,700,500)
c1.SetBottomMargin(0.4)
grSigma.Draw('ALP')
c1.Print('res-' +name+'-'+half + '-' + getFileName(f) + args.tag + '.ps')
ans = raw_input('continue?')
c.Print('res-' +name+'-'+half + '-' + getFileName(f) + args.tag + '.ps]')
def plotRotations(t_file):
names = hps_utils.getSensorNames()
print ' got ', len(names), ' sensor names'
hname = 'h_res_gbl_vs_u_'
#hname = 'h_res_gbl_vs_vpred_'
c = TCanvas('c','c',10,10,700,500)
grSlopes = TGraphErrors()
grSlopes.SetName('slopes_' + hname)
grSlopesBinLabels = []
for sensorname in names:
name = hname + sensorname
if args.regexp != None:
m = re.match(args.regexp, name)
if m == None:
print 'skip this histogram \"', name, '\"'
continue
h = t_file.Get(name)
if h == None:
print 'no histogram \"', name, '\"'
sys.exit(1)
print 'process \"', name , '\"'
c.Clear()
h.Draw('colz')
c.SaveAs(name + '-' + args.tag + '.png')
#ans = raw_input('continue?')
grMean = TGraphErrors()
grMean.SetName( h.GetName() + '_prjYmean' )
for b in range(1, h.GetNbinsX()+1):
h_p = h.ProjectionY(h.GetName() + '_prjy' + str(b), b, b, 'E')
f = None
if h_p.GetEntries() > 77.:
peakbin = findPeakBin(h_p)
x = h_p.GetBinCenter(peakbin)
minv = x - 1.5*h_p.GetRMS()
maxv = x + 1.5*h_p.GetRMS()
print 'vpred ', h.GetXaxis().GetBinCenter(b) , ' peakbin ', peakbin, ' c ' , h_p.GetBinCenter(peakbin), ' minv ', minv, ' maxv ', maxv
f = TF1('f'+'_'+name,'gaus',minv,maxv)
h_p.Fit(f,'RQ')
ipoint = grMean.GetN()
grMean.SetPoint(ipoint, h.GetXaxis().GetBinCenter(b), f.GetParameter(1))
grMean.SetPointError(ipoint, 0., f.GetParError(1))
c.Clear()
if f != None:
plotutils.myText(0.5,0.85,'<m>=%.2f #sigma=%.2f'%(f.GetParameter(1),f.GetParameter(2)), 0.05, 2)
h_p.Draw()
c.SaveAs(h_p.GetName() + '-' + args.tag + '.png')
#ans = raw_input('continue?')
grMean.SetTitle(name + ';;mean')
grMean.SetMarkerStyle(20)
c.Clear()
fpol1 = TF1('f' + grMean.GetName(),'pol1')
grMean.Fit(fpol1)
grMean.Draw('ALP')
plotutils.myText(0.35,0.8,'slope=%.2e m=%.2e'%(fpol1.GetParameter(1),fpol1.GetParameter(0)), 0.05, 2)
ipoint = grSlopes.GetN()
if args.uflip and hps_utils.getAxialStereo(sensorname) == 'stereo':
print 'flip ', sensorname, ' ', fpol1.GetParameter(1) , ' -> ', -1.*fpol1.GetParameter(1)
grSlopes.SetPoint( ipoint, ipoint, -1.*fpol1.GetParameter(1) )
else:
print 'NO flip ', sensorname, ' ', fpol1.GetParameter(1)
grSlopes.SetPoint( ipoint, ipoint, fpol1.GetParameter(1) )
grSlopes.SetPointError( ipoint, 0., fpol1.GetParError(1) )
grSlopesBinLabels.append( hps_utils.getshortsensorname( sensorname ) )
c.SaveAs(name + '-mean-' + args.tag + '.png')
#ans = raw_input('continue?')
c.Clear()
grSlopes.Draw('ALP')
plotutils.setBinLabels( grSlopes, grSlopesBinLabels )
c.SetBottomMargin(0.2)
if args.uflip:
plotutils.myText(0.35,0.8,'u-flipped', 0.05, 2)
else:
plotutils.myText(0.35,0.8,'NOT u-flipped', 0.05, 2)
if args.uflip:
c.SaveAs(grSlopes.GetName() + '-uflipped-' + args.tag + '.png')
else:
c.SaveAs(grSlopes.GetName() + '-' + args.tag + '.png')
ans = raw_input('continue?')
def noise(files):
if files==None:
print 'No ROOT files'
return
c = TCanvas('cBiasCheck','cBiasCheck',10,10,700,500)
c.Print(c.GetName() + '.ps[')
grOnRMS = TGraph()
grOnMean = TGraph()
grOffRMS = TGraph()
grOffMean = TGraph()
for filename in files:
f = TFile(filename)
if f==None:
print "couldnt open file ", filename
return
m = re.match('hps_00(\d+)\.\S+\.(\d+)\.root',os.path.basename(filename))
if m==None:
print ' this filename is weird' , filename
sys.exit(1)
run = m.group(1)
runName = m.group(1)
if m.group(2)!='':
runName = run + '.' + m.group(2)
#hOffName = 'module_L1t_halfmodule_stereo_slot_sensor0 raw adc - ped maxSample>4 OFF'
#hOnName = 'module_L1t_halfmodule_stereo_slot_sensor0 raw adc - ped maxSample>4 ON'
#hOffName = 'module_L3t_halfmodule_stereo_sensor0 raw adc - ped maxSample>4 OFF'
#hOnName = 'module_L3t_halfmodule_stereo_sensor0 raw adc - ped maxSample>4 ON'
hOffName = 'module_L5t_halfmodule_stereo_slot_sensor0 raw adc - ped maxSample>4 OFF'
hOnName = 'module_L5t_halfmodule_stereo_slot_sensor0 raw adc - ped maxSample>4 ON'
hOff = f.Get(hOffName)
hOn = f.Get(hOnName)
if hOff!=None and hOn!=None:
if hOn.GetEntries()>0:
cOn = TCanvas('cBiasCheckOn %s'%runName,'cBiasCheckOn %s'%runName,10,10,700,500)
hOn.SetFillColor(2)
hOn.SetFillStyle(3003)
hOn.Draw("hist")
myText(0.2,0.7,'HV ON %s'%runName, 0.05,2)
cOn.Print(c.GetName() + '.ps')
grOnRMS.SetPoint(grOnRMS.GetN(),int(run), hOn.GetRMS())
grOnMean.SetPoint(grOnMean.GetN(),int(run), hOn.GetMean())
if hOff.GetEntries()>0:
cOff = TCanvas('cBiasCheckOff %s'%runName,'cBiasCheckOff %s'%runName,10,10,700,500)
hOff.SetFillColor(4)
hOff.SetFillStyle(3003)
hOff.Draw()
myText(0.2,0.7,'HV OFF %s'%runName, 0.05,1)
cOff.Print(c.GetName() + '.ps')
grOffRMS.SetPoint(grOffRMS.GetN(),int(run), hOff.GetRMS())
grOffMean.SetPoint(grOffMean.GetN(),int(run), hOff.GetMean())
if hOn.GetEntries()>0 and hOff.GetEntries()>0:
cOnOff = TCanvas('cBiasCheckOnOff %s'%runName,'cBiasCheckOnOff %s'%runName,10,10,700,500)
hOn.SetLineColor(2)
hOn.SetFillColor(2)
hOn.SetFillStyle(3003)
hOn.DrawNormalized("hist")
hOff.DrawNormalized("same")
myText(0.2,0.7,'HV ON %s'%runName, 0.05,2)
myText(0.2,0.78,'HV OFF %s'%runName, 0.05,1)
cOnOff.Print(c.GetName() + '.ps')
#ans = raw_input('continue?')
else:
print 'couldnt get ', hOnName
setGraphStyle(grOnMean)
setGraphStyle(grOnRMS)
setGraphStyle(grOffMean)
setGraphStyle(grOffRMS)
cGrOnMean = TCanvas('cGrOnMean','cGrOnMean',10,10,700,500)
if grOnMean.GetN()>0:
grOnMean.Draw('ALP')
myText(0.2,0.7,'Mean HV ON', 0.05,1)
cGrOnRMS = TCanvas('cGrOnRMS','cGrOnRMS',10,10,700,500)
if grOnRMS.GetN()>0:
grOnRMS.Draw('ALP')
myText(0.2,0.7,'RMS HV ON', 0.05,1)
cGrOffMean = TCanvas('cGrOffMean','cGrOffMean',10,10,700,500)
if grOffMean.GetN()>0:
grOffMean.Draw('ALP')
myText(0.2,0.7,'Mean HV OFF', 0.05,1)
cGrOffRMS = TCanvas('cGrOffRMS','cGrOffRMS',10,10,700,500)
if grOffRMS.GetN()>0:
grOffRMS.Draw('ALP')
myText(0.2,0.7,'RMS HV OFF', 0.05,1)
#ans = raw_input('continue?')
cGrOnMean.Print(c.GetName() + '.ps')
cGrOffMean.Print(c.GetName() + '.ps')
cGrOnRMS.Print(c.GetName() + '.ps')
cGrOffRMS.Print(c.GetName() + '.ps')
c.Print(c.GetName() + '.ps]')
return
def compareHists(histos,legends=None,normalize=None,fitName=None, t='',pad=None,myTextSize=0.05):
print 'compareHists:'
if fitName != None: print 'fitName: ', fitName
c = None
cName = 'c_'
if pad == None:
for h in histos:
print h.GetName(), ' ', h.GetEntries()
cName += h.GetName()
c = TCanvas(cName, cName ,10 ,10 ,700 ,500)
else:
pad.cd()
fillColors = [33,45,20,4,4,4,4,4,4,4,4]
lineColors = [1,2,3,4,5,6,7,8,9,10]
#lineColors = [1,2,3,4,5,6,7,8,9,10]
lineWidth = 2
n = 0
nm = 0
maxBC = -1.
hFirst = None
for ih in range(len(histos)):
h = histos[ih]
if ih == 0:
hFirst = h
h.SetLineColor(lineColors[ih])
h.SetLineWidth(lineWidth)
h.Sumw2()
if normalize != None:
if h.Integral() == 0:
print 'warning: histogram ', h.GetName(), ' cannot be normalized with no integral!'
else:
h.Scale(1.0/h.Integral())
if h.GetMaximum() > maxBC:
maxBC = h.GetMaximum()
f = None
if fitName != None:
if fitName['name'] == 'gaus':
print 'Fitting ', h.GetName()
fitFuncName = 'fg_' + h.GetName()
fitOpt = '0R'
fg = TF1(fitFuncName,'gaus')
if h.GetRMS() < 1e-10 or h.GetRMS() < h.GetBinWidth(1):
print 'WARNING: histogram ', h.GetName(), ' has small RMS', h.GetRMS(), ' dont fit but use that RMS and mean ', h.GetMean()
fg.SetParameter(0,0)
fg.SetParameter(1, h.GetMean() )
fg.SetParameter(2, h.GetRMS() )
listOfFunctions = h.GetListOfFunctions()
print 'got ', len(listOfFunctions), ' function'
for func in listOfFunctions: print func.GetName()
listOfFunctions.append(fg)
print 'now got ', len(listOfFunctions), ' function'
for func in listOfFunctions: print func.GetName()
else:
if 'xmin' and 'xmax' in fitName:
fg.SetRange(fitName['xmin'],fitName['xmax'])
else:
fg.SetRange(h.GetBinCenter(1),h.GetBinCenter(h.GetNbinsX()+1))
if 'peakbin' in fitName:
bc = getHistMaxBinValue(h)
fg.SetParameter(1,bc)
if 'rms' in fitName:
bc = getHistMaxBinValue(h)
rms = h.GetRMS()
fg.SetParameter(1,bc)
fg.SetParameter(2,rms)
fg.SetRange( bc - rms*fitName['rms'], bc + rms*fitName['rms'] )
h.Fit(fg,fitOpt)
f = fg #h.GetFunction(fitFuncName)
if f != None:
f.SetLineColor(lineColors[ih])
f.SetLineWidth(lineWidth)
if ih != -1:
h.SetFillColor(fillColors[ih])
h.SetFillStyle(3002)
if ih == 0:
h.Draw('hist')
else:
h.Draw('hist,same')
if f != None:
f.Draw('same')
if fitName['name'] == 'gaus':
myText(0.13,0.2+ih*myTextSize,'<m>=%.2e #sigma=%.2e'%(f.GetParameter(1),f.GetParameter(2)),myTextSize,lineColors[ih])
n=n+1
#ans = raw_input('press anywhere to continue')
hFirst.SetMaximum(maxBC)
if legends:
styles = ['FL' for x in range(len(histos))]
l = getLegendList(0.13,0.75,0.25,0.85,histos,legends,styles)
l.Draw()
if c != None:
name = cName
if t != '':
name += '_' + t
c.SaveAs(name + '.png')
