def compareTwoHists(file1,histName1,file2,histName2,tag='',fitFunctionName=None,legs=None):
print 'open TFiles'
tFiles = [ TFile(file1), TFile(file2)]
print 'opened ', len(tFiles), ' TFiles'
histos = [tFiles[0].Get(histName1), tFiles[1].Get(histName2)]
print 'compare ', len(histos),' root histos '
compareRootHists.compareHists(histos,legends=legs,normalize=True,fitName=fitFunctionName,t=tag,pad=None,myTextSize=0.05)
for tf in tFiles:
print 'closing ', tf.GetName()
tf.Close()
return
def compareHists(files,histName,tag='',fitFunctionName=None, legends=None):
print 'compareHists for ', len(files), ' for histName ', histName, ' tag ', tag
print 'open TFiles'
tFiles = []
for f in files:
tFiles.append(TFile(f))
print 'opened ', len(tFiles)
histos = []
for tf in tFiles:
print 'tf ', tf.GetName()
h = tf.Get(histName)
histos.append(h)
print 'compare ', len(histos),' root histos'
compareRootHists.compareHists(histos,legends=legends,normalize=True,fitName=fitFunctionName,t=tag,pad=None,myTextSize=0.05)
for tf in tFiles:
print 'closing ', tf.GetName()
tf.Close()
return
def compareSensorHists(files,histName,tag='',half=None,singleCanvas=None,beamspot=False,legends=None):
print 'compareSensorHists for ', len(files), ' for histName ', histName, ' tag ', tag, ' beamspot ', beamspot
sensorHistNames = []
sensors = hps_utils.getSensorNames(beamspot)
for s in sensors:
if hps_utils.getLayer > 3 and hps_utils.getHoleSlot(s) == 'slot':
continue
#if hps_utils.getHalf(s) != 'b' or hps_utils.getLayer(s) !=2 or hps_utils.getAxialStereo(s) != 'axial':
# continue
#if hps_utils.getHalf(s) != 't' or hps_utils.getLayer(s) !=6 or hps_utils.getHoleSlot(s) != 'slot' and hps_utils.getAxialStereo(s) != 'slot':
# continue
#if beamspot and hps_utils.getLayer(s)==0:
# if hps_utils.getHalf(s) != 'b':
# print 'this beamspot sensor is weird! ', s
# sys.exit(1)
if hps_utils.getHalf(s) == 't' and half != 'top':
continue
if hps_utils.getHalf(s) == 'b' and half != 'bottom':
continue
addOn = ''
if hps_utils.getHalf(s) == 't':
addOn = '_top'
else:
addOn = '_bot'
sensorHistNames.append(histName + s + addOn)
print sensorHistNames
print 'open TFiles'
tFiles = []
for f in files:
tFiles.append(TFile(f))
print 'opened ', len(tFiles)
c = None
print 'singleCanvas ', singleCanvas
if singleCanvas != None:
cName = 'c_' + histName + '_' + half + '_' + tag
c = TCanvas(cName, cName, 10, 10, 690*2, 390*2)
c.Divide(2,12)
currentPad = None
graphBinNames = {}
graphMean = []
graphRMS = []
for tf in tFiles:
print 'tf ', tf.GetName()
grM = TGraphErrors()
grM.SetName('grMean_' + tf.GetName())
grR = TGraphErrors()
grR.SetName('grRMS_' + tf.GetName())
graphMean.append( grM )
graphRMS.append( grR )
for hName in sensorHistNames:
histos = []
print 'get ', hName
for tf in tFiles:
print 'tf ', tf.GetName()
h = tf.Get(hName)
histos.append(h)
print 'compare ', len(histos),' root histos'
if c != None:
i = hps_utils.getCanvasIdxTwoCols(hName,beamspot)
currentPad = c.cd(i)
print currentPad
compareRootHists.compareHists(histos,legends=legends,normalize=True,fitName={'name':'gaus','rms':2},t=tag,pad=currentPad,myTextSize=0.1)
print 'make graphs of mean and RMS'
for ih in range(len(histos)):
h = histos[ih]
f = h.GetFunction('fg_' + h.GetName())
if f != None:
mean = f.GetParameter(1)
meanError = f.GetParError(1)
rms = f.GetParameter(2)
rmsError = f.GetParError(2)
ipoint = graphMean[ih].GetN()
graphMean[ih].SetPoint(ipoint, ipoint, mean)
graphRMS[ih].SetPoint(ipoint, ipoint, rms)
graphMean[ih].SetPointError(ipoint, 0., meanError)
graphRMS[ih].SetPointError(ipoint, 0., rmsError)
graphBinNames[ ipoint ] = hps_utils.getshortsensorname( hName )
print 'mean ', mean, ' RMS ', rms, ' fg ', f.GetName()
else:
print 'No fg in histo ', ih, ' name ', h.GetName()
print 'done comparing ', len(histos),' root histos'
if c != None:
c.SaveAs(cName + '.png')
cGrName = 'c_summary' + histName + '_' + half + '_' + tag
cGr = TCanvas(cGrName, cGrName, 10, 10, 690*2, 390*2)
cGr.Divide(1,2)
grMaxValMean = -1000000.
grMaxValRMS = -10000000.
grMinValMean = 1000000.
grMinValRMS = 10000000.
for igr in range(len(graphMean)):
grM = graphMean[ igr ]
grR = graphRMS [ igr ]
limVals = plotutils.getGraphMaxMinVal(grM)
print limVals
if limVals[1] > grMaxValMean:
grMaxValMean = limVals[1]
if limVals[0] < grMinValMean:
grMinValMean = limVals[0]
limVals = plotutils.getGraphMaxMinVal(grR)
if limVals[1] > grMaxValRMS:
grMaxValRMS = limVals[1]
if limVals[0] < grMinValMean:
grMinValRMS = limVals[0]
print grMaxValMean, grMinValMean
for igr in range(len(graphMean)):
grM = graphMean[ igr ]
grR = graphRMS [ igr ]
#print 'igr ', igr, ' name ', grM.GetName()
plotutils.setGraphStyle(grM,igr+1)
plotutils.setGraphStyle(grR,igr+1)
plotutils.setBinLabelsDict(grM,graphBinNames)
plotutils.setBinLabelsDict(grR,graphBinNames)
if igr == 0:
cGr.cd(1)
gPad.SetBottomMargin(0.3)
grM.GetHistogram().SetMaximum(grMaxValMean*1.2)
grM.GetHistogram().SetMinimum(grMinValMean*1.2)
grM.Draw('AXPL')
cGr.cd(2)
gPad.SetBottomMargin(0.3)
grR.SetMaximum(grMaxValRMS)
grR.SetMinimum(grMinValRMS)
grR.Draw('AXPL')
else:
cGr.cd(1)
grM.Draw('PL,same')
cGr.cd(2)
grR.Draw('PL,same')
if legends:
styles = [ 'PL' for x in range( len( graphMean ) ) ]
l = plotutils.getLegendList(0.13,0.75,0.25,0.85,graphMean,legends,styles)
l.Draw()
cGr.SaveAs(cGr.GetName() + '.png')
#ans = raw_input('press anything')
for tf in tFiles:
print 'closing ', tf.GetName()
tf.Close()
return