class HistogramSaver:
def __init__(self, settings=None):
print 'Starting Histogram Saver'
self.settings = settings
self.run = array(self.settings.runInfo['run'], 'I')
self.eventNumber = array(int(0), 'I')
self.plotPath = '.'
self.plotRootPath = './root/'
self.plotPdfPath = './pdf/'
self.paveTextOptions = {}
self.dateTime = TDatime()
self.paveText = TPaveText(0.07, 0, 0.22, 0.10, 'NDC')
self.UpdatePaveText()
self.verb = self.settings.runInfo['verbose']
self.optStat1D = 'nemr'
self.optStat2D = 'ne'
self.DefaultPlotStyle()
def DefaultPlotStyle(self):
gStyle.SetPalette(55) # 55 is kRainBow. 53 is kDarkBodyRadiator
gStyle.SetOptStat(self.optStat1D)
gStyle.SetOptFit(11111)
gStyle.SetStatH(0.12)
gStyle.SetStatW(0.15)
gStyle.SetPadBottomMargin(0.15)
gStyle.SetPadTopMargin(0.15)
def SetPath(self, path='.'):
self.plotPath = self.RemoveExtraBackSlashes(path, 2)
self.plotRootPath = self.RemoveExtraBackSlashes(path + '/root/', 3)
self.plotPdfPath = self.RemoveExtraBackSlashes(path + '/pdf/', 3)
self.settings.CheckDirExistence(self.plotPath, True)
self.settings.CheckDirExistence(self.plotRootPath, True)
self.settings.CheckDirExistence(self.plotPdfPath, True)
def RemoveExtraBackSlashes(self, string, times=1):
if times == 0:
return string
string = string.replace('//', '/')
return self.RemoveExtraBackSlashes(string, times - 1)
def UpdatePaveText(self):
self.paveText.Clear()
self.paveText.SetTextSize(0.025)
self.paveTextOptions['svn'] = 'Rev: ' + self.settings.version
self.paveTextOptions['run'] = 'Run ' + str(self.run)
self.paveTextOptions['nEvents'] = 'with ' + str(
self.settings.runInfo['nEvents']) + 'Events'
self.paveTextOptions['DateTime'] = self.dateTime.AsSQLString()
self.paveText.AddText(self.paveTextOptions['svn'])
self.paveText.AddText(self.paveTextOptions['run'])
self.paveText.AddText(self.paveTextOptions['nEvents'])
self.paveText.AddText(self.paveTextOptions['DateTime'])
self.paveText.SetBorderSize(0)
self.paveText.SetFillColor(0)
def MakeOneDHist(pathToDir, distribution):
numFittingSamples = 0
HeaderLabel = TPaveLabel(header_x_left, header_y_bottom, header_x_right,
header_y_top, HeaderText, "NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
LumiLabel = TPaveLabel(topLeft_x_left, topLeft_y_bottom, topLeft_x_right,
topLeft_y_top, LumiText, "NDC")
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
NormLabel = TPaveLabel()
NormLabel.SetDrawOption("NDC")
NormLabel.SetX1NDC(topLeft_x_left)
NormLabel.SetX2NDC(topLeft_x_right)
NormLabel.SetBorderSize(0)
NormLabel.SetFillColor(0)
NormLabel.SetFillStyle(0)
NormText = ""
if arguments.normalizeToUnitArea:
NormText = "Scaled to unit area"
elif arguments.normalizeToData:
NormText = "MC scaled to data"
NormLabel.SetLabel(NormText)
YieldsLabel = TPaveText(0.39, 0.7, 0.59, 0.9, "NDC")
YieldsLabel.SetBorderSize(0)
YieldsLabel.SetFillColor(0)
YieldsLabel.SetFillStyle(0)
YieldsLabel.SetTextAlign(12)
RatiosLabel = TPaveText()
RatiosLabel.SetDrawOption("NDC")
RatiosLabel.SetBorderSize(0)
RatiosLabel.SetFillColor(0)
RatiosLabel.SetFillStyle(0)
RatiosLabel.SetTextAlign(32)
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
fittingIntegral = 0
scaleFactor = 1
HistogramsToFit = []
TargetDataset = distribution['target_dataset']
FittingLegendEntries = []
DataLegendEntries = []
FittingHistogramDatasets = []
Stack_list = []
Stack_list.append(THStack("stack_before", distribution['name']))
Stack_list.append(THStack("stack_after", distribution['name']))
fileName = condor_dir + "/" + distribution['target_dataset'] + ".root"
if not os.path.exists(fileName):
return
inputFile = TFile(fileName)
if inputFile.IsZombie() or not inputFile.GetNkeys():
return
Target = inputFile.Get("OSUAnalysis/" + distribution['channel'] + "/" +
distribution['name']).Clone()
Target.SetDirectory(0)
inputFile.Close()
Target.SetMarkerStyle(20)
Target.SetMarkerSize(0.8)
Target.SetFillStyle(0)
Target.SetLineColor(colors[TargetDataset])
Target.SetLineStyle(1)
Target.SetLineWidth(2)
targetIntegral = Target.Integral()
if (arguments.normalizeToUnitArea and Target.Integral() > 0):
Target.Scale(1. / Target.Integral())
if arguments.rebinFactor:
RebinFactor = int(arguments.rebinFactor)
#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
if Target.GetNbinsX() >= RebinFactor * 5 and Target.GetName().find(
"GenMatch") is -1:
Target.Rebin(RebinFactor)
### formatting target histogram and adding to legend
legendIndex = 0
Legend.AddEntry(Target, labels[TargetDataset], "LEP")
legendIndex = legendIndex + 1
if not outputFile.Get("OSUAnalysis"):
outputFile.mkdir("OSUAnalysis")
if not outputFile.Get("OSUAnalysis/" + distribution['channel']):
outputFile.Get("OSUAnalysis").mkdir(distribution['channel'])
for sample in distribution[
'datasets']: # loop over different samples requested to be fit
dataset_file = "%s/%s.root" % (condor_dir, sample)
inputFile = TFile(dataset_file)
HistogramObj = inputFile.Get(pathToDir + "/" +
distribution['channel'] + "/" +
distribution['name'])
if not HistogramObj:
print "WARNING: Could not find histogram " + pathToDir + "/" + distribution[
'channel'] + "/" + distribution[
'name'] + " in file " + dataset_file + ". Will skip it and continue."
continue
Histogram = HistogramObj.Clone()
Histogram.SetDirectory(0)
inputFile.Close()
if arguments.rebinFactor:
RebinFactor = int(arguments.rebinFactor)
#don't rebin histograms which will have less than 5 bins or any gen-matching histograms
if Histogram.GetNbinsX() >= RebinFactor * 5 and Histogram.GetName(
).find("GenMatch") is -1:
Histogram.Rebin(RebinFactor)
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
if unitBeginIndex is not -1 and unitEndIndex is not -1: #x axis has a unit
yAxisLabel = "Entries / " + str(Histogram.GetXaxis().GetBinWidth(
1)) + " " + xAxisLabel[unitBeginIndex + 1:unitEndIndex]
else:
yAxisLabel = "Entries per bin (" + str(
Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if not arguments.makeFancy:
histoTitle = Histogram.GetTitle()
else:
histoTitle = ""
legLabel = labels[sample]
if (arguments.printYields):
yieldHist = Histogram.Integral()
legLabel = legLabel + " (%.1f)" % yieldHist
FittingLegendEntries.append(legLabel)
if (types[sample] == "bgMC"):
numFittingSamples += 1
fittingIntegral += Histogram.Integral()
Histogram.SetLineStyle(1)
if (arguments.noStack):
Histogram.SetFillStyle(0)
Histogram.SetLineColor(colors[sample])
Histogram.SetLineWidth(2)
else:
Histogram.SetFillStyle(1001)
Histogram.SetFillColor(colors[sample])
Histogram.SetLineColor(1)
Histogram.SetLineWidth(1)
elif (types[sample] == "signalMC"):
numFittingSamples += 1
Histogram.SetFillStyle(0)
Histogram.SetLineColor(colors[sample])
Histogram.SetLineStyle(1)
Histogram.SetLineWidth(2)
if (arguments.normalizeToUnitArea and Histogram.Integral() > 0):
Histogram.Scale(1. / Histogram.Integral())
HistogramsToFit.append(Histogram)
FittingHistogramDatasets.append(sample)
#scaling histograms as per user's specifications
if targetIntegral > 0 and fittingIntegral > 0:
scaleFactor = targetIntegral / fittingIntegral
for fittingHist in HistogramsToFit:
if arguments.normalizeToData:
fittingHist.Scale(scaleFactor)
if arguments.normalizeToUnitArea and not arguments.noStack and fittingIntegral > 0:
fittingHist.Scale(1. / fittingIntegral)
elif arguments.normalizeToUnitArea and arguments.noStack and fittingHist.Integral(
) > 0:
fittingHist.Scale(1. / fittingHist.Integral())
def fitf(x, par):
xBin = HistogramsToFit[0].FindBin(x[0])
value = 0.0
for i in range(0, len(HistogramsToFit)):
value += par[i] * HistogramsToFit[i].GetBinContent(xBin) + par[
i +
len(HistogramsToFit)] * HistogramsToFit[i].GetBinError(xBin)
return value
lowerLimit = Target.GetBinLowEdge(1)
upperLimit = Target.GetBinLowEdge(Target.GetNbinsX()) + Target.GetBinWidth(
Target.GetNbinsX())
if 'lowerLimit' in distribution:
lowerLimit = distribution['lowerLimit']
if 'upperLimit' in distribution:
upperLimit = distribution['upperLimit']
func = TF1("fit", fitf, lowerLimit, upperLimit, 2 * len(HistogramsToFit))
for i in range(0, len(HistogramsToFit)):
if 'fixed_datasets' in distribution and distribution['datasets'][
i] in distribution['fixed_datasets']:
func.FixParameter(i, 1.0)
else:
func.SetParameter(i, 1.0)
# func.SetParLimits (i, 0.0, 1.0e2) # comment this out so we don't have to pre-normalize the QCD input sample
func.SetParName(i, labels[FittingHistogramDatasets[i]])
shiftedScaleFactors = []
if arguments.parametricErrors:
# loop over all input histograms and shift them +- 1 sigma
for i in range(0, len(HistogramsToFit)):
sfs = []
# -1 => -1 sigma, +1 => +1 sigma
for j in [-1, 1]:
# loop over the parameters holding the errors for each dataset, fixing all to 0
for k in range(len(HistogramsToFit), 2 * len(HistogramsToFit)):
func.FixParameter(k, 0)
# fix the error of the dataset of interest to +-1
func.FixParameter(i + len(HistogramsToFit), j)
# perform new fit
for k in range(0, distribution['iterations'] - 1):
if j == -1:
print "Scale down " + labels[FittingHistogramDatasets[
i]] + " iteration " + str(k + 1) + "..."
if j == 1:
print "Scale up " + labels[FittingHistogramDatasets[
i]] + " iteration " + str(k + 1) + "..."
Target.Fit("fit", "QEMR0")
Target.Fit("fit", "VEMR0")
# save the new scale factors for each dataset
for k in range(0, len(HistogramsToFit)):
sfs.append(func.GetParameter(k))
shiftedScaleFactors.append(sfs)
# reset the parameters with the errors of each dataset to 0
for i in range(len(HistogramsToFit), 2 * len(HistogramsToFit)):
func.FixParameter(i, 0)
# do the fit to get the central values
for i in range(0, distribution['iterations'] - 1):
print "Iteration " + str(i + 1) + "..."
Target.Fit("fit", "QEMR0")
Target.Fit("fit", "VEMR0")
if arguments.parametricErrors:
# make a list of the largest errors on each contribution by shifting any other contribution
parErrors = []
# loop over all the datasets
for i in range(0, len(HistogramsToFit)):
centralValue = func.GetParameter(i)
maxError = 0
# find the maximum deviation from the central value and save that
for shiftedScaleFactor in shiftedScaleFactors[i]:
currentError = abs(shiftedScaleFactor - centralValue)
if currentError > maxError:
maxError = currentError
parErrors.append(maxError)
finalMax = 0
if not arguments.noStack:
for fittingHist in HistogramsToFit:
finalMax += fittingHist.GetMaximum()
else:
for fittingHist in HistogramsToFit:
if (fittingHist.GetMaximum() > finalMax):
finalMax = fittingHist.GetMaximum()
if (Target.GetMaximum() > finalMax):
finalMax = Target.GetMaximum()
Target.SetMaximum(1.1 * finalMax)
Target.SetMinimum(0.0001)
Canvas = TCanvas(distribution['name'] + "_FitFunction")
Canvas.cd(1)
Target.Draw()
func.Draw("same")
outputFile.cd("OSUAnalysis/" + distribution['channel'])
Canvas.Write()
if arguments.savePDFs:
if histogram == input_histograms[0]:
Canvas.Print(pdfFileName + "(", "pdf")
else:
Canvas.Print(pdfFileName, "pdf")
Target.SetStats(0)
### formatting bgMC histograms and adding to legend
legendIndex = numFittingSamples - 1
for Histogram in reversed(HistogramsToFit):
if (arguments.noStack):
Legend.AddEntry(Histogram, FittingLegendEntries[legendIndex], "L")
else:
Legend.AddEntry(Histogram, FittingLegendEntries[legendIndex], "F")
legendIndex = legendIndex - 1
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
### Draw everything to the canvases !!!!
for i in range(0, 2): # 0 => before, 1 => after
integrals = []
ratios = []
errors = []
if i == 1:
# loop over each dataset, saving it's yield and the errors on it
for j in range(0, len(HistogramsToFit)):
integrals.append(HistogramsToFit[j].Integral())
HistogramsToFit[j].Scale(func.GetParameter(j))
ratios.append(func.GetParameter(j))
errors.append(func.GetParError(j))
for fittingHist in HistogramsToFit:
if not arguments.noStack:
Stack_list[i].Add(fittingHist)
#creating the histogram to represent the statistical errors on the stack
if not arguments.noStack:
ErrorHisto = HistogramsToFit[0].Clone("errors")
ErrorHisto.SetFillStyle(3001)
ErrorHisto.SetFillColor(13)
ErrorHisto.SetLineWidth(0)
if i == 1:
Legend.AddEntry(ErrorHisto, "Stat. Errors", "F")
for Histogram in HistogramsToFit:
if Histogram is not HistogramsToFit[0]:
ErrorHisto.Add(Histogram)
if i == 0:
Canvas = TCanvas(distribution['name'] + "_Before")
if i == 1:
Canvas = TCanvas(distribution['name'] + "_After")
if makeRatioPlots or makeDiffPlots:
Canvas.SetFillStyle(0)
Canvas.Divide(1, 2)
Canvas.cd(1)
gPad.SetPad(0, 0.25, 1, 1)
gPad.SetMargin(0.15, 0.05, 0.01, 0.07)
gPad.SetFillStyle(0)
gPad.Update()
gPad.Draw()
if arguments.setLogY:
gPad.SetLogy()
Canvas.cd(2)
gPad.SetPad(0, 0, 1, 0.25)
# format: gPad.SetMargin(l,r,b,t)
gPad.SetMargin(0.15, 0.05, 0.4, 0.01)
gPad.SetFillStyle(0)
gPad.SetGridy(1)
gPad.Update()
gPad.Draw()
Canvas.cd(1)
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
if numFittingSamples is not 0 and not arguments.noStack:
finalMax = ErrorHisto.GetMaximum() + ErrorHisto.GetBinError(
ErrorHisto.GetMaximumBin())
else:
for bgMCHist in HistogramsToFit:
if (bgMCHist.GetMaximum() > finalMax):
finalMax = bgMCHist.GetMaximum()
if (Target.GetMaximum() > finalMax):
finalMax = Target.GetMaximum() + Target.GetBinError(
Target.GetMaximumBin())
finalMax = 1.15 * finalMax
if arguments.setYMax:
finalMax = float(arguments.setYMax)
if not arguments.noStack: # draw stacked background samples
Stack_list[i].SetTitle(histoTitle)
Stack_list[i].Draw("HIST")
Stack_list[i].GetXaxis().SetTitle(xAxisLabel)
Stack_list[i].GetYaxis().SetTitle(yAxisLabel)
Stack_list[i].SetMaximum(finalMax)
Stack_list[i].SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
Stack_list[i].GetHistogram().GetXaxis().SetLabelSize(0)
#draw shaded error bands
ErrorHisto.Draw("A E2 SAME")
else: #draw the unstacked backgrounds
HistogramsToFit[0].SetTitle(histoTitle)
HistogramsToFit[0].Draw("HIST")
HistogramsToFit[0].GetXaxis().SetTitle(xAxisLabel)
HistogramsToFit[0].GetYaxis().SetTitle(yAxisLabel)
HistogramsToFit[0].SetMaximum(finalMax)
HistogramsToFit[0].SetMinimum(yAxisMin)
for bgMCHist in HistogramsToFit:
bgMCHist.Draw("A HIST SAME")
Target.Draw("A E X0 SAME")
#legend coordinates, empirically determined :-)
x_left = 0.6761745
x_right = 0.9328859
x_width = x_right - x_left
y_max = 0.9
entry_height = 0.05
if (numFittingSamples is not 0): #then draw the data & bgMC legend
numExtraEntries = 2 # count the target and (lack of) title
Legend.SetX1NDC(x_left)
numExtraEntries = numExtraEntries + 1 # count the stat. errors entry
Legend.SetY1NDC(y_max - entry_height *
(numExtraEntries + numFittingSamples))
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
RatiosLabel.SetX1NDC(x_left - 0.1)
RatiosLabel.SetX2NDC(x_right)
RatiosLabel.SetY2NDC(Legend.GetY1NDC() - 0.1)
RatiosLabel.SetY1NDC(RatiosLabel.GetY2NDC() - entry_height *
(numFittingSamples))
# Deciding which text labels to draw and drawing them
drawLumiLabel = False
drawNormLabel = False
offsetNormLabel = False
drawHeaderLabel = False
if not arguments.normalizeToUnitArea: #don't draw the lumi label if there's no data and it's scaled to unit area
drawLumiLabel = True
# move the normalization label down before drawing if we drew the lumi. label
offsetNormLabel = True
if arguments.normalizeToUnitArea or arguments.normalizeToData:
drawNormLabel = True
if arguments.makeFancy:
drawHeaderLabel = True
drawLumiLabel = False
# now that flags are set, draw the appropriate labels
if drawLumiLabel:
LumiLabel.Draw()
if drawNormLabel:
if offsetNormLabel:
NormLabel.SetY1NDC(topLeft_y_bottom - topLeft_y_offset)
NormLabel.SetY2NDC(topLeft_y_top - topLeft_y_offset)
else:
NormLabel.SetY1NDC(topLeft_y_bottom)
NormLabel.SetY2NDC(topLeft_y_top)
NormLabel.Draw()
if drawHeaderLabel:
HeaderLabel.Draw()
YieldsLabel.Clear()
mcYield = Stack_list[i].GetStack().Last().Integral()
dataYield = Target.Integral()
if i == 0:
YieldsLabel.AddText("Before Fit to Data")
if i == 1:
YieldsLabel.AddText("After Fit to Data")
YieldsLabel.AddText("data yield: " + '%.1f' % dataYield)
YieldsLabel.AddText("bkgd yield: " + '%.1f' % mcYield)
YieldsLabel.AddText("data/bkgd: " + '%.2f' % (dataYield / mcYield))
if i == 1:
for j in range(0, len(FittingLegendEntries)):
if abs(ratios[j] - 1) < 0.001 and abs(
errors[j]
) < 0.001: #then it probably was held fixed
continue
if arguments.showFittedYields:
yield_ = ratios[j] * integrals[j]
yielderror_ = errors[j] * yield_
text = FittingLegendEntries[
j] + " yield: " + '%.0f' % yield_ + ' #pm %.0f' % yielderror_
else:
text = FittingLegendEntries[
j] + " ratio: " + '%.2f' % ratios[
j] + ' #pm %.2f' % errors[j]
text = text + " (fit)"
if arguments.parametricErrors:
yield_ = ratios[j] * integrals[j]
yieldParError_ = parErrors[j] * yield_
if arguments.showFittedYields:
text += ' #pm %.2f' % yieldParError_
else:
text += ' #pm %.2f' % parErrors[j]
text = text + " (sys)"
RatiosLabel.AddText(text)
YieldsLabel.Draw()
RatiosLabel.Draw()
# drawing the ratio or difference plot if requested
if (makeRatioPlots or makeDiffPlots):
Canvas.cd(2)
BgSum = Stack_list[i].GetStack().Last()
if makeRatioPlots:
if arguments.ratioRelErrMax:
Comparison = ratioHistogram(Target, BgSum,
arguments.ratioRelErrMax)
else:
Comparison = ratioHistogram(Target, BgSum)
elif makeDiffPlots:
Comparison = Target.Clone("diff")
Comparison.Add(BgSum, -1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("Data-Bkgd")
Comparison.GetXaxis().SetTitle(xAxisLabel)
Comparison.GetYaxis().CenterTitle()
Comparison.GetYaxis().SetTitleSize(0.1)
Comparison.GetYaxis().SetTitleOffset(0.5)
Comparison.GetXaxis().SetTitleSize(0.15)
Comparison.GetYaxis().SetLabelSize(0.1)
Comparison.GetXaxis().SetLabelSize(0.15)
if makeRatioPlots:
RatioYRange = 1.15
if arguments.ratioYRange:
RatioYRange = float(arguments.ratioYRange)
Comparison.GetYaxis().SetRangeUser(-1 * RatioYRange,
RatioYRange)
elif makeDiffPlots:
YMax = Comparison.GetMaximum()
YMin = Comparison.GetMinimum()
if YMax <= 0 and YMin <= 0:
Comparison.GetYaxis().SetRangeUser(-1.2 * YMin, 0)
elif YMax >= 0 and YMin >= 0:
Comparison.GetYaxis().SetRangeUser(0, 1.2 * YMax)
else: #axis crosses y=0
if abs(YMax) > abs(YMin):
Comparison.GetYaxis().SetRangeUser(
-1.2 * YMax, 1.2 * YMax)
else:
Comparison.GetYaxis().SetRangeUser(
-1.2 * YMin, 1.2 * YMin)
Comparison.GetYaxis().SetNdivisions(205)
Comparison.Draw("E0")
if i == 0:
Canvas.Write(distribution['name'] + "_Before")
if arguments.savePDFs:
pathToDirString = plainTextString(pathToDir)
Canvas.SaveAs(condor_dir + "/fitting_histogram_pdfs/" +
pathToDirString + "/" + distribution['name'] +
"_Before.pdf")
if i == 1:
Canvas.Write(distribution['name'] + "_After")
if arguments.savePDFs:
pathToDirString = plainTextString(pathToDir)
Canvas.SaveAs(condor_dir + "/fitting_histogram_pdfs/" +
pathToDirString + "/" + distribution['name'] +
"_After.pdf")
def main():
cc.cd()
cc.SetBorderMode(0)
cc.SetFixedAspectRatio(1)
cc.FeedbackMode(1)
gStyle.SetOptStat(0)
gStyle.SetGridStyle(1)
gStyle.SetGridColor(11)
hh=TH2D('hh',';X;Y',22,-10.5,11.5,22,-10.5,11.5)
hi=TH2I('hi',';X;Y',22,-10.5,11.5,22,-10.5,11.5)
setupHists([hh,hi])
xax,yax=hh.GetXaxis(),hh.GetYaxis()
hh.Draw('COLZ')
hi.Draw('TEXTSAME')
gPad.SetLogz()
gPad.SetGrid(1,1)
gPad.SetLeftMargin(0.09)
gPad.SetRightMargin(0.11)
#tt2=TPaveText(0.7,0.96,0.9,0.99,'NDC')
ttM=TPaveText(-3+0.05, 7-4.45, 4.0, 8-4.51)
tt2=TPaveText(-3+0.05, 7-5.45, 4.0, 8-5.51)
ttX=TPaveText(-2, 7-8.00, 3, 8-8.00)
ttY=TPaveText(-2, 7-9.00, 3, 8-9.00)
ttZ=TPaveText(-2, 6-8.80, 3, 8-9.30)
ttZ.AddText("positive = beam top/right")
ttime=TPaveText(-10,-12.5,10,-11.8)
tchan=TPaveText(0,0,0.9,1)
setupPaveTexts([tt2,ttM,ttime,tchan,ttX,ttY,ttZ])
ttM.SetTextColor(2)
ttM.SetFillStyle(0)
ttZ.SetFillStyle(0)
tt2.SetFillStyle(0)
tarrow=TText(-0.9,0.7,'Beam Right')
tarrow.SetTextSizePixels(15)
arrow=TArrow(-1.4,0.5,2.4,0.5,0.02,'|>')
arrow.SetAngle(40)
arrow.SetFillColor(1)
arrow.SetLineWidth(2)
tt=TText()
tt.SetTextColor(1)
tt.SetTextAngle(90)
tt.SetTextSize(0.04)
tt.DrawText(12.4,0,'kHz')
tt.SetTextAngle(0)
tt.SetTextColor(1)
tt.DrawTextNDC(0.3,0.92,'FTC FADC SCALERS')
bb=TBox()
bb.SetFillStyle(1001)
bb.SetFillColor(0)
bb.SetLineWidth(1)
bb.SetLineColor(1)
bb.DrawBox(-3.47,-1.47,4.47,2.46)
bb.DrawBox(-1.47,-3.47,2.49,4.47)
bb.DrawBox(-2.47,-2.47,3.49,3.47)
cc.cd()
for xx in [ttM,tt2,ttime,arrow,tarrow,ttX,ttY,ttZ]: xx.Draw()
cc2.cd()
tchan.Draw('NDC')
cc.cd()
gPad.SetEditable(0)
while True:
for ch in ECAL.chans:
loadPV(ch)
ch=ch.vals
xx,yy=ch['X'],ch['Y']
#if (ch['PVVAL']>10):
# print xx,yy,ch['PVVAL']
# swap x to make it downstream view:
xx=-xx
#after, fix the fact x=0 / y=0 don't exists
if xx<0: xx+=1
if yy<0: yy+=1
hh.SetBinContent(xax.FindBin(xx),yax.FindBin(yy),ch['PVVAL'])
hi.SetBinContent(xax.FindBin(xx),yax.FindBin(yy),ch['PVVAL'])
for xx in [ttime,tt2,ttM,ttX,ttY]: xx.Clear()
[total,maximum,top,bottom,left,right]=calcRates(ECAL.chans)
tt2.AddText('Total: %.1f MHz'%(total/1000))
ttM.AddText('Max: %.0f kHz'%(maximum))
if total>1e2:
xasy = (right-left)/total
yasy = (top-bottom)/total
ttX.AddText('X-Asy: %+.1f%%'%(100*xasy))
ttY.AddText('Y-Asy: %+.1f%%'%(100*yasy))
else:
ttX.AddText('X-Asy: N/A')
ttY.AddText('Y-Asy: N/A')
ttime.AddText(makeTime())
if not gPad: sys.exit()
if gPad.GetEvent()==11:
xy=pix2xy(gPad)
ee=ECAL.findChannelXY(xy[0],xy[1])
if ee:
tchan.Clear()
tchan.AddText(printChannel(ee))
cc2.Modified()
cc2.Update()
elif gPad.GetEvent()==12:
tchan.Clear()
cc2.Modified()
cc2.Update()
cc.Modified()
cc.Update()
time.sleep(2)
def main():
if True:
mf=TGMainFrame(gClient.GetRoot(),1500,475)
gvf=TGVerticalFrame(mf,1500,475)
rec=TRootEmbeddedCanvas("ccc",gvf,1500,450)
rec2=TRootEmbeddedCanvas("ccc2",gvf,1500,25)
gvf.AddFrame(rec,TGLayoutHints(ROOT.kLHintsExpandX|ROOT.kLHintsTop))
gvf.AddFrame(rec2,TGLayoutHints(ROOT.kLHintsExpandX|ROOT.kLHintsBottom))
mf.AddFrame(gvf,TGLayoutHints(ROOT.kLHintsExpandX))
cc=rec.GetCanvas()
cc2=rec2.GetCanvas()
mf.SetEditable(0)
mf.SetWindowName('HPS ECAL FADC SCALERS')
mf.MapSubwindows()
mf.Resize(1501,476)# resize to get proper frame placement
mf.MapWindow()
else:
cc=TCanvas('cc','',1500,450)
cc.cd()
cc.SetBorderMode(0)
cc.SetFixedAspectRatio(1)
cc.FeedbackMode(1)
gStyle.SetOptStat(0)
gStyle.SetGridStyle(1)
gStyle.SetGridColor(11)
hh=TH2D('hh',';X;Y',46,-22,24,11,-5,6)
hi=TH2I('hi',';X;Y',46,-22,24,11,-5,6)
setupHists([hh,hi])
xax,yax=hh.GetXaxis(),hh.GetYaxis()
hh.Draw('COLZ')
hi.Draw('TEXTSAME')
gPad.SetLogz()
gPad.SetGrid(1,1)
gPad.SetLeftMargin(0.05)
tt1=TPaveText(0.1,0.9,0.3,1.0,'NDC')
tt2=TPaveText(0.7,0.91,0.9,0.99,'NDC')
ttT=TPaveText(-22+13+0.05,6-5,-22+22,7-5-0.05)
ttB=TPaveText(-22+13+0.05,4-5+0.05,-22+22,5-5)
ttM=TPaveText(-22+0+0.05,5-5+0.05,-22+13,6-5.01)
ttime=TPaveText(-10,-6.5,10,-5.8)
tchan=TPaveText(0,0,0.9,1)
setupPaveTexts([tt1,tt2,ttT,ttB,ttM,ttime,tchan])
ttM.SetTextColor(2)
bb=TBox()
bb.SetFillStyle(1001)
bb.SetFillColor(0)
bb.SetLineWidth(1)
bb.SetLineColor(1)
bb.DrawBox(-9+0.05,-1,0,1.97)
bb.DrawBox(-24,0,24.05,0.97)
tarrow=TText(14.5,0.3,'Beam Left')
arrow=TArrow(19,0.5,23,0.5,0.02,'|>')
arrow.SetAngle(40)
arrow.SetFillColor(1)
arrow.SetLineWidth(2)
tt=TText()
tt.SetTextColor(1)
tt.SetTextAngle(90)
tt.SetTextSize(0.08)
tt.DrawText(25.4,0,'kHz')
tt.SetTextAngle(0)
tt.SetTextColor(2)
tt.DrawTextNDC(0.3,0.92,'ECAL FADC SCALERS')
cc.cd()
for xx in [tt2,ttT,ttB,ttM,arrow,tarrow,ttime]: xx.Draw()
cc2.cd()
tchan.Draw('NDC')
cc.cd()
ll=TLine()
ll.DrawLine(xax.GetXmin(),yax.GetXmin(),xax.GetXmax(),yax.GetXmin())
ll.DrawLine(xax.GetXmin(),yax.GetXmax(),xax.GetXmax(),yax.GetXmax())
ll.DrawLine(xax.GetXmin(),yax.GetXmin(),xax.GetXmin(),0)
ll.DrawLine(xax.GetXmax(),yax.GetXmin(),xax.GetXmax(),0)
ll.DrawLine(xax.GetXmin(),yax.GetXmax(),xax.GetXmin(),1)
ll.DrawLine(xax.GetXmax(),yax.GetXmax(),xax.GetXmax(),1)
ll.DrawLine(xax.GetXmax(),0,0,0)
ll.DrawLine(xax.GetXmax(),1,0,1)
ll.DrawLine(xax.GetXmin(),0,-9,0)
ll.DrawLine(xax.GetXmin(),1,-9,1)
ll.DrawLine(-9,-1,0,-1)
ll.DrawLine(-9,2,0,2)
ll.DrawLine(-9,1,-9,2)
ll.DrawLine(-9,-1,-9,0)
ll.DrawLine(0,-1,0,0)
ll.DrawLine(0,1,0,2)
gPad.SetEditable(0)
while True:
# try:
zvals=getPVS()
for ii in range(len(zvals)):
hh.SetBinContent(xax.FindBin(XVALS[ii]),yax.FindBin(YVALS[ii]),zvals[ii])
hi.SetBinContent(xax.FindBin(XVALS[ii]),yax.FindBin(YVALS[ii]),zvals[ii])
for xx in [ttime,tt2,ttT,ttB,ttM]: xx.Clear()
[top,bottom,maximum]=calcRates(zvals)
tt2.AddText('Total: %.1f MHz'%((top+bottom)/1000))
ttT.AddText('%.1f MHz'%(top/1000))
ttB.AddText('%.1f MHz'%(bottom/1000))
ttM.AddText('MAX SINGLE CRYSTAL = %.0f kHz'%(maximum))
ttime.AddText(makeTime())
if gPad.GetEvent()==11:
xy=pix2xy(gPad)
ee=ECAL.findChannelXY(xy[0],xy[1])
if ee:
tchan.Clear()
tchan.AddText(printChannel(ee))
cc2.Modified()
cc2.Update()
elif gPad.GetEvent()==12:
tchan.Clear()
cc2.Modified()
cc2.Update()
cc.Modified()
cc.Update()
time.sleep(1)
def main():
cc.cd()
cc.SetBorderMode(0)
cc.SetFixedAspectRatio(1)
cc.FeedbackMode(1)
gStyle.SetOptStat(0)
gStyle.SetGridStyle(1)
gStyle.SetGridColor(18)
hh = TH2D('hh', ';X;Y', 8 * 28, 0, 28, 8 * 23, 0, 23)
hi = TH2I('hi', ';X;Y', 8 * 28, 0, 28, 8 * 23, 0, 23)
setupHists([hh, hi])
xax, yax = hh.GetXaxis(), hh.GetYaxis()
hh.Draw('COLZ')
hh.SetMinimum(1)
hh.SetMaximum(1.5e3)
#hi.Draw('TEXTSAME')
gPad.SetLogz()
gPad.SetGrid(1, 1)
gPad.SetLeftMargin(0.09)
gPad.SetRightMargin(0.11)
#tt2=TPaveText(0.7,0.96,0.9,0.99,'NDC')
ttM = TPaveText(-3 + 0.05, 7 - 4.45, 4.0, 8 - 4.51)
tt2 = TPaveText(-3 + 0.05, 7 - 5.45, 4.0, 8 - 5.51)
ttX = TPaveText(-2, 7 - 8.00, 3, 8 - 8.00)
ttY = TPaveText(-2, 7 - 9.00, 3, 8 - 9.00)
ttime = TPaveText(8, -2, 20, -1)
tchan = TPaveText(0, 0, 0.9, 1)
setupPaveTexts([tt2, ttM, ttime, tchan, ttX, ttY])
ttM.SetTextColor(2)
ttM.SetFillStyle(0)
tt2.SetFillStyle(0)
tt = TText()
tt.SetTextColor(1)
tt.SetTextAngle(90)
tt.SetTextSize(0.04)
tt.DrawText(29.5, 10, 'kHz')
tt.SetTextAngle(0)
tt.SetTextColor(1)
tt.DrawTextNDC(0.3, 0.92, 'RICH SSP Scalers')
# bb=TBox()
# bb.SetFillStyle(1001)
# bb.SetFillColor(0)
# bb.SetLineWidth(1)
# bb.SetLineColor(1)
# bb.DrawBox(-3.47,-1.47,4.47,2.46)
# bb.DrawBox(-1.47,-3.47,2.49,4.47)
# bb.DrawBox(-2.47,-2.47,3.49,3.47)
cc.cd()
for xx in [ttime]:
xx.Draw() #ttM,tt2,ttime,ttX,ttY]: xx.Draw()
cc2.cd()
tchan.Draw('NDC')
cc.cd()
gPad.SetEditable(0)
while True:
for ch in ECAL.chans:
loadPV(ch)
ch = ch.vals
xx, yy = ch['X'], ch['Y']
data = ch['PVVAL']
for ix in range(8):
for iy in range(8):
ii = ix * 8 + iy
#print ch['PVNAME'],data[ii]
xoff = float(ix) / 8
yoff = float(iy) / 8
hh.SetBinContent(xax.FindBin(xx + xoff),
yax.FindBin(yy + yoff), data[ii])
# hi.SetBinContent(xax.FindBin(xx+xoff),yax.FindBin(yy+yoff),data[ii])
#
for xx in [ttime]:
ttime.Clear() # xx.,tt2,ttM,ttX,ttY]: xx.Clear()
# [total,maximum,top,bottom,left,right]=calcRates(ECAL.chans)
# tt2.AddText('Total: %.1f MHz'%(total/1000))
# ttM.AddText('Max: %.0f kHz'%(maximum))
# if total>1e2:
# xasy = (right-left)/total
# yasy = (top-bottom)/total
# ttX.AddText('X-Asy: %+.1f%%'%(100*xasy))
# ttY.AddText('Y-Asy: %+.1f%%'%(100*yasy))
# else:
# ttX.AddText('X-Asy: N/A')
# ttY.AddText('Y-Asy: N/A')
ttime.AddText(makeTime())
if not gPad: sys.exit()
# if gPad.GetEvent()==11:
# xy=pix2xy(gPad)
# ee=ECAL.findChannelXY(xy[0],xy[1])
# if ee:
# tchan.Clear()
# tchan.AddText(printChannel(ee))
# cc2.Modified()
# cc2.Update()
# elif gPad.GetEvent()==12:
# tchan.Clear()
# cc2.Modified()
# cc2.Update()
cc.Modified()
cc.Update()
time.sleep(1)
