def showRMSPOH_DAC(sector, poh, gain, wait=True, filename=None):
gStyle.SetOptStat(0)
gStyle.SetCanvasColor(0)
gStyle.SetTitleFillColor(0)
sector.poh[poh].biasGraphs = []
sector.poh[poh].rmsGraphs = []
sector.poh[poh].slopeGraphs = []
sector.ResetAllandInitAll()
data = sector.poh[poh].ScanDACoffset()
if filename is None:
filename = getFilename("poh%s_%d.ps" % (sector.name, poh))
c1 = TCanvas('c1', time.strftime("%Y-%m-%d-%m %H:%M"), 200, 10, 800, 800)
sector.poh[poh].pl = TPaveLabel(0.8, 0.9, 0.95, 0.95,
time.strftime("%Y-%m-%d-%m %H:%M"))
sector.poh[poh].pl.Draw()
c1.Divide(2, 3)
for ch in range(1, 5):
c1.cd(ch)
title = "POHBias_POH" + str(poh) + ":" + str(
ch) + " " + sector.name + " fed channel " + str(
sector.poh[poh].fedchannels[ch]) + "gain =" + str(gain)
f = TH2D('h' + title, title, 2, 0, 255, 2, 0, 1024)
hList.append(f)
f.GetXaxis().SetTitle("DAC")
#f.GetYaxis().SetTitle("FED ADC")
f.Draw()
color = 1
biasGraph = graph([(t[0], t[1]) for t in data[ch]],
color=1,
name="bias_" + str(poh) + ":" + str(ch))
rmsGraph = graph([(t[0], t[2] * 10.) for t in data[ch]],
color=2,
name="rms_" + str(poh) + ":" + str(ch))
slopeGraph = graph([(t[0], t[3] * 10.) for t in data[ch]],
color=3,
name="slope_" + str(poh) + ":" + str(ch))
sector.poh[poh].biasGraphs.append(biasGraph)
sector.poh[poh].rmsGraphs.append(rmsGraph)
sector.poh[poh].slopeGraphs.append(slopeGraph)
biasGraph.Write()
rmsGraph.Write()
slopeGraph.Write()
c1.Update()
c1.Print(filename)
gCanvases.append(c1)
if wait:
raw_input("hit return to continue")
def showRMSAOHTestCCU(sector, aoh, wait=True, filename=None):
gStyle.SetOptStat(0)
gStyle.SetCanvasColor(0)
gStyle.SetTitleFillColor(0)
sector.aoh[aoh].biasGraphs = []
sector.aoh[aoh].rmsGraphs = []
sector.aoh[aoh].slopeGraphs = []
data = sector.aoh[aoh].getBiasRMSCurvesTestCCU()
if filename is None:
filename = getFilename("aoh%s_%d.ps" % (sector.name, aoh))
c1 = TCanvas('c1', time.strftime("%Y-%m-%d-%m %H:%M"), 200, 10, 800, 800)
sector.aoh[aoh].pl = TPaveLabel(0.8, 0.9, 0.95, 0.95,
time.strftime("%Y-%m-%d-%m %H:%M"))
sector.aoh[aoh].pl.Draw()
c1.Divide(2, 3)
for ch in range(1, 7):
c1.cd(ch)
title = "AOHBias_AOH" + str(aoh) + ":" + str(
ch) + " " + sector.name + " fed channel " + str(
sector.aoh[aoh].fedchannels[ch])
f = TH2D('h' + title, title, 2, 10, 40, 2, 0, 1024)
hList.append(f)
f.GetXaxis().SetTitle("aoh bias")
#f.GetYaxis().SetTitle("FED ADC")
f.Draw()
color = 1
biasGraph = graph([(t[0], t[1]) for t in data[ch]],
color=1,
name="bias_" + str(aoh) + ":" + str(ch))
rmsGraph = graph([(t[0], t[2] * 100.) for t in data[ch]],
color=2,
name="rms_" + str(aoh) + ":" + str(ch))
slopeGraph = graph([(t[0], t[3] * 10.) for t in data[ch]],
color=3,
name="slope_" + str(aoh) + ":" + str(ch))
sector.aoh[aoh].biasGraphs.append(biasGraph)
sector.aoh[aoh].rmsGraphs.append(rmsGraph)
sector.aoh[aoh].slopeGraphs.append(slopeGraph)
biasGraph.Write()
rmsGraph.Write()
slopeGraph.Write()
c1.Update()
c1.Print(filename)
gCanvases.append(c1)
if wait:
raw_input("hit return to continue")
def createPaveLabel(x1, y1, x2, y2, text,
fillColor=1, textColor=0,
textSize=None):
label = TPaveLabel(0.80, 0.80, 0.97, 0.88,
'Peak Fit')
label.SetFillColor(fillColor)
label.SetTextColor(textColor)
label.SetTextFont(52)
if (textSize != None):
label.SetTextSize(textSize)
label.Draw()
return label
counter = 0
for Histogram in Histograms:
if Histogram.InheritsFrom("TGraph") and counter == 0:
plotting_options = "AP"
Histogram.Draw(plotting_options)
# Histogram.GetXaxis().SetTitle(xAxisLabel)
Histogram.GetYaxis().SetTitle("cut efficiency")
if counter is 0:
if Histogram.InheritsFrom("TGraph"):
plotting_options = "P"
counter = counter + 1
Legend.Draw()
if arguments.normalizeToUnitArea:
NormLabel = TPaveLabel(0.1, 0.75, 0.35, 0.85, "Scaled to unit area", "NDC")
NormLabel.SetBorderSize(0)
NormLabel.SetFillColor(0)
NormLabel.SetFillStyle(0)
NormLabel.Draw()
outputFile.cd()
Canvas.Write()
if arguments.plot_savePdf:
pdfFileName = outputFileName.replace(".root", ".pdf")
Canvas.SaveAs(pdfFileName)
print "Saved file: " + pdfFileName
outputFile.Close()
print "Saved plot in file: " + outputFileName
# # This macro displays the physical ROOT file structure # from ROOT import TCanvas, TPaveLabel, TPave, TLine, TArrow, TText, TPaveText from ROOT import gROOT gROOT.Reset() c1 = TCanvas( 'c1', 'ROOT File description', 200, 10, 700, 550 ) c1.Range( 0, -0.25, 21, 14 ) title = TPaveLabel( 5, 12, 15, 13.7, c1.GetTitle() ) title.SetFillColor( 16 ) title.Draw() # horizonthal file layout file = TPave( 1, 8.5, 20, 11 ) file.SetFillColor( 11 ) file.Draw() fileh = TPave( 1, 8.5, 2.5, 11 ) fileh.SetFillColor( 44 ) fileh.Draw() lrh = TPave( 2.5, 8.5, 3.3, 11, 1 ) lrh.SetFillColor( 33 ) lrh.Draw() lrh.DrawPave( 6.9, 8.5, 7.7, 11, 1 ) lrh.DrawPave( 10.5, 8.5, 11.3, 11, 1 ) lrh.DrawPave( 14.5, 8.5, 15.3, 11, 1 ) ldot = TLine( 1, 8.5, 0.5, 6.5 )
def plot(MillePedeUser, alignables, config):
logger = logging.getLogger("mpsvalidate")
# more space for labels
gStyle.SetPadBottomMargin(0.25)
gStyle.SetOptStat("emrs")
for mode in ["xyz", "rot"]:
big = PlotData(mode)
# count number of needed bins and max shift
for line in MillePedeUser:
if (line.ObjId != 1):
for i in range(3):
if (abs(line.Par[big.data[i]]) != 999999):
if (mode == "xyz"):
line.Par[big.data[i]] *= 10000
big.numberOfBins[i] += 1
if (abs(line.Par[big.data[i]]) > abs(big.maxShift[i])):
big.maxShift[i] = line.Par[big.data[i]]
# initialize histograms
for i in range(3):
big.histo.append(
TH1F("Big Structure {0} {1}".format(big.xyz[i], mode), "",
big.numberOfBins[i], 0, big.numberOfBins[i]))
if (big.unit != ""):
big.histo[i].SetYTitle("#Delta" + big.xyz[i] + " [" +
big.unit + "]")
else:
big.histo[i].SetYTitle("#Delta" + big.xyz[i])
big.histo[i].SetStats(0)
big.histo[i].SetMarkerStyle(21)
big.histoAxis.append(big.histo[i].GetXaxis())
# bigger labels for the text
big.histoAxis[i].SetLabelSize(0.06)
big.histo[i].GetYaxis().SetTitleOffset(1.6)
# add labels
big.title = TPaveLabel(0.1, 0.8, 0.9, 0.9,
"High Level Structures {0}".format(mode))
big.text = TPaveText(0.05, 0.1, 0.95, 0.75)
big.text.SetTextAlign(12)
# error if shift is bigger than limit
limit = config.limit[mode]
for i in range(3):
if (big.unit != ""):
big.text.AddText("max. shift {0}: {1:.2} {2}".format(
big.xyz[i], float(big.maxShift[i]), big.unit))
if (abs(big.maxShift[i]) > limit):
big.text.AddText("! {0} shift bigger than {1} {2}".format(
big.xyz[i], limit, big.unit))
else:
big.text.AddText("max. shift {0}: {1:.2}".format(
big.xyz[i], float(big.maxShift[i])))
if (abs(big.maxShift[i]) > limit):
big.text.AddText("! {0} shift bigger than {1}".format(
big.xyz[i], limit))
# fill histograms with value and name
for line in MillePedeUser:
if (line.ObjId != 1):
for i in range(3):
if (abs(line.Par[big.data[i]]) != 999999):
# set name of the structure
big.histoAxis[i].SetBinLabel(
big.binPosition[i],
alignables.get_name_by_objid(line.ObjId))
# fill with data, big.data[i] xyz or rot data
# transform xyz data from cm to #mu m
if (mode == "xyz"):
big.histo[i].SetBinContent(
big.binPosition[i],
10000 * line.Par[big.data[i]])
else:
big.histo[i].SetBinContent(big.binPosition[i],
line.Par[big.data[i]])
big.binPosition[i] += 1
# rotate labels
for i in range(3):
big.histoAxis[i].LabelsOption("v")
# reset y range
# two types of ranges
# 1. show all
if (config.rangemodeHL == "all"):
for i in range(3):
big.usedRange[i] = big.maxShift[i]
# 2. use given values
if (config.rangemodeHL == "given"):
# loop over coordinates
for i in range(3):
if (mode == "xyz"):
valuelist = config.rangexyzHL
if (mode == "rot"):
valuelist = config.rangerotHL
# loop over given values
# without last value
for value in valuelist:
# maximum smaller than given value
if (abs(big.maxShift[i]) < value):
big.usedRange[i] = value
break
# if not possible, force highest
if (abs(big.maxShift[i]) > valuelist[-1]):
big.usedRange[i] = valuelist[-1]
# all the same range
if (config.samerangeHL == 1):
# apply new range
for i in range(3):
big.usedRange[i] = max(map(abs, big.usedRange))
# count outlieres
if (config.rangemodeHL == "given"):
for i in range(3):
for binNumber in range(1, big.numberOfBins[i] + 1):
if (abs(big.histo[i].GetBinContent(binNumber)) >
big.usedRange[i]):
big.hiddenEntries[i] += 1
# add number of outlieres to text
for i in range(3):
if (big.hiddenEntries[i] != 0):
big.text.AddText("! {0}: {1} outlier !".format(
big.xyz[i], int(big.hiddenEntries[i])))
# create canvas
cBig = TCanvas("canvasBigStrucutres_{0}".format(mode), "Parameter",
300, 0, 800, 600)
cBig.Divide(2, 2)
# draw histograms
cBig.cd(1)
big.title.Draw()
big.text.Draw()
# draw identification
ident = identification(config)
ident.Draw()
# TGraph copy to hide outlier
copy = 3 * [None]
# loop over coordinates
for i in range(3):
cBig.cd(i + 2)
# option "AXIS" to only draw the axis
big.histo[i].SetLineColor(0)
big.histo[i].Draw("AXIS")
# set new range
big.histo[i].GetYaxis().SetRangeUser(-1.1 * abs(big.usedRange[i]),
1.1 * abs(big.usedRange[i]))
# TGraph object to hide outlier
copy[i] = TGraph(big.histo[i])
# set the new range
copy[i].SetMaximum(1.1 * abs(big.usedRange[i]))
copy[i].SetMinimum(-1.1 * abs(big.usedRange[i]))
# draw the data
copy[i].Draw("PSAME")
cBig.Update()
# save as pdf
cBig.Print("{0}/plots/pdf/structures_{1}.pdf".format(
config.outputPath, mode))
# export as png
image = TImage.Create()
image.FromPad(cBig)
image.WriteImage("{0}/plots/png/structures_{1}.png".format(
config.outputPath, mode))
# add to output list
output = OutputData(plottype="big",
parameter=mode,
filename="structures_{0}".format(mode))
config.outputList.append(output)
# reset BottomMargin
gStyle.SetPadBottomMargin(0.1)
print "Fitted parameters: ctau = -1./[1] = " + str(
ctau) + "; ctau error = + " + str(ctauErrHi) + " - " + str(ctauErrLo)
histName = arguments.histName
histName = histName[histName.rfind('/') +
1:] # strip off anything before the last '/'
outfileRoot = arguments.infile.replace(".root", "_" + histName + "Fit.root")
outputFile = TFile(outfileRoot, "RECREATE")
FitText = "Fitted <c#tau> = " \
+ str.format('{0:.1f}', ctau) + "^{+" \
+ str.format('{0:.1f}', ctauErrHi) + "}_{" \
+ str.format('{0:.1f}', ctauErrLo) + "}"
#, #chi^{2}/NDF = " \
#+ str.format('{0:.1f}', myfunc.GetChisquare()) + "/" + str(myfunc.GetNDF())
FitLabel = TPaveLabel(0.2, 0.8, 0.6, 0.9, FitText, "NDC")
FitLabel.SetBorderSize(0)
FitLabel.SetFillColor(0)
FitLabel.SetFillStyle(0)
FitLabel.Draw()
hist.Write()
can.Write()
outputFile.Close()
outfilePdf = outfileRoot.replace(".root", ".pdf")
can.SaveAs(outfilePdf)
print "Saved plot in " + outfilePdf + " and " + outfileRoot
print "Finished doExpoFit.py"
pad1 = TPad('pad1', 'The pad with the function', 0.03, 0.62, 0.50, 0.92, 21)
pad2 = TPad('pad2', 'The pad with the histogram', 0.51, 0.62, 0.98, 0.92, 21)
pad3 = TPad('pad3', 'The pad with the histogram', 0.03, 0.02, 0.97, 0.57, 21)
pad1.Draw()
pad2.Draw()
pad3.Draw()
#
# We connect the ROOT file generated in a previous tutorial
# see begin_html <a href="hsimple.C.html">An example creating/filling/saving histograms/ntuples on file</a> end_html
#
example = TFile('py-hsimple.root')
example.ls()
# Draw a global picture title
title = TPaveLabel(0.1, 0.94, 0.9, 0.98,
'Drawing options for one dimensional histograms')
title.SetFillColor(16)
title.SetTextFont(52)
title.Draw()
#
# Draw histogram hpx in first pad with the default option.
pad1.cd()
pad1.GetFrame().SetFillColor(18)
hpx = gROOT.FindObject('hpx')
hpx.SetFillColor(45)
hpx.DrawCopy()
label1 = TPaveLabel(-3.5, 700, -1, 800, 'Default option')
label1.SetFillColor(42)
label1.Draw()
#
# Draw hpx as a lego. Clicking on the lego area will show
from ROOT import TCanvas, TF1, TPaveLabel, TPad, TText
from ROOT import gROOT
nut = TCanvas('nut', 'FirstSession', 100, 10, 700, 900)
nut.Range(0, 0, 20, 24)
nut.SetFillColor(10)
nut.SetBorderSize(2)
pl = TPaveLabel(3, 22, 17, 23.7, 'My first PyROOT interactive session', 'br')
pl.SetFillColor(18)
pl.Draw()
t = TText(0, 0, 'a')
t.SetTextFont(62)
t.SetTextSize(0.025)
t.SetTextAlign(12)
t.DrawText(
2, 20.3,
'PyROOT provides ROOT bindings for Python, a powerful interpreter.')
t.DrawText(2, 19.3, 'Blocks of lines can be entered typographically.')
t.DrawText(2, 18.3, 'Previous typed lines can be recalled.')
t.SetTextFont(72)
t.SetTextSize(0.026)
t.DrawText(3, 17, r'>>> x, y = 5, 7')
t.DrawText(3, 16, r'>>> import math; x*math.sqrt(y)')
t.DrawText(
3, 14,
r'>>> for i in range(2,7): print "sqrt(%d) = %f" % (i,math.sqrt(i))')
t.DrawText(3, 10,
r'>>> import ROOT; f1 = ROOT.TF1( "f1", "sin(x)/x", 0, 10 )')
jbessel = TF1("J_0", "ROOT::Math::cyl_bessel_j([0],x)", 0, 10)
jbessel.SetParameters(nu, 0.0)
jbessel.SetTitle("")
jbessel.SetLineStyle(1)
jbessel.SetLineWidth(3)
jbessel.SetLineColor(nu + 1)
JBessel.append(jbessel)
# Setting x axis for JBessel
xaxis = JBessel[0].GetXaxis()
xaxis.SetTitle("x")
xaxis.SetTitleSize(0.06)
xaxis.SetTitleOffset(.7)
# setting the title in a label style
p1 = TPaveLabel(.0, .90, .0 + .50, .90 + .10, "Bessel J functions", "NDC")
p1.SetFillColor(0)
p1.SetTextFont(22)
p1.SetTextColor(kBlack)
# setting the legend
leg.AddEntry(JBessel[0].DrawCopy(), " J_0(x)", "l")
leg.AddEntry(JBessel[1].DrawCopy("same"), " J_1(x)", "l")
leg.AddEntry(JBessel[2].DrawCopy("same"), " J_2(x)", "l")
leg.AddEntry(JBessel[3].DrawCopy("same"), " J_3(x)", "l")
leg.AddEntry(JBessel[4].DrawCopy("same"), " J_4(x)", "l")
leg.Draw()
p1.Draw()
# Set canvas 2
def showRMSPOH(sector, poh, gain, wait=True, filename=None):
gStyle.SetOptStat(0)
gStyle.SetCanvasColor(0)
gStyle.SetTitleFillColor(0)
sector.poh[poh].biasGraphs = []
sector.poh[poh].rmsGraphs = []
sector.poh[poh].slopeGraphs = []
# for poh in range(1,15):
# print sector.poh[poh].group
if sector.poh[poh].group.find('L12') != -1:
sector.ccu.send("channel 0x11").readlines()
elif sector.poh[poh].group.find('L34') != -1:
sector.ccu.send("channel 0x13").readlines()
#cmd=sector.poh[poh].name+" setall %i %i %i %i %i %i %i %i"%(gain,gain,gain,gain,0,0,0,0)
#sector.ccu.send(cmd).readlines()
sector.ResetAllandInitAll()
for ch in range(1, 5):
sector.poh[poh].writegain(ch, gain)
#for ch in range(1,5):
# print ch
# sector.poh[poh].writegain(ch,gain)
data = sector.poh[poh].getBiasRMSCurves()
if filename is None:
filename = getFilename("poh%s_%d.ps" % (sector.name, poh))
c1 = TCanvas('c1', time.strftime("%Y-%m-%d-%m %H:%M"), 200, 10, 800, 800)
sector.poh[poh].pl = TPaveLabel(0.8, 0.9, 0.95, 0.95,
time.strftime("%Y-%m-%d-%m %H:%M"))
sector.poh[poh].pl.Draw()
c1.Divide(2, 3)
for ch in range(1, 5):
c1.cd(ch)
title = "POHBias_POH" + str(poh) + ":" + str(
ch) + " " + sector.name + " fed channel " + str(
sector.poh[poh].fedchannels[ch])
f = TH2D('h' + title, title, 2, 0, 40, 2, 0, 1024)
hList.append(f)
f.GetXaxis().SetTitle("poh bias")
#f.GetYaxis().SetTitle("FED ADC")
f.Draw()
color = 1
biasGraph = graph([(t[0], t[1]) for t in data[ch]],
style=20,
color=1,
name="bias_" + str(poh) + ":" + str(ch))
rmsGraph = graph([(t[0], t[2] * 10.) for t in data[ch]],
style=21,
color=31,
name="rms_" + str(poh) + ":" + str(ch))
slopeGraph = graph([(t[0], t[3] * 10.) for t in data[ch]],
style=24,
color=2,
name="slope_" + str(poh) + ":" + str(ch))
sector.poh[poh].biasGraphs.append(biasGraph)
sector.poh[poh].rmsGraphs.append(rmsGraph)
sector.poh[poh].slopeGraphs.append(slopeGraph)
biasGraph.Write()
print title
biasGraph.Print()
rmsGraph.Write()
slopeGraph.Write()
legend = TLegend(.64, .62, .85, .85)
legend.AddEntry(biasGraph, "Bias", "p")
legend.AddEntry(slopeGraph, "Slope*10,microW/mA", "p")
legend.AddEntry(rmsGraph, "Noise", "p")
legend.Draw()
c1.Update()
#################################################
#################################################
c1.Print(filename)
gCanvases.append(c1)
if wait:
raw_input("hit return to continue")
def MakeOneHist(histogramName):
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"
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas(histogramName)
Histograms = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],
source['dataset'])
inputFile = TFile(dataset_file)
NumHistogramObj = inputFile.Get("OSUAnalysis/" +
source['num_channel'] + "/" +
histogramName)
if 'condor_dir_den' in source: # If specified, take the denominator histogram from a different condor directory.
dataset_fileDen = "condor/%s/%s.root" % (source['condor_dir_den'],
source['dataset'])
inputFileDen = TFile(dataset_fileDen)
DenHistogramObj = inputFileDen.Get("OSUAnalysis/" +
source['den_channel'] + "/" +
histogramName)
else: # Default is to use the same condor directory
DenHistogramObj = inputFile.Get("OSUAnalysis/" +
source['den_channel'] + "/" +
histogramName)
if not NumHistogramObj:
print "WARNING: Could not find histogram " + source[
'num_channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
if not DenHistogramObj:
print "WARNING: Could not find histogram " + source[
'den_channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = NumHistogramObj.Clone()
if Histogram.Class().InheritsFrom("TH2"):
Histogram.SetName(Histogram.GetName() + "__" + source['dataset'])
Histogram.SetDirectory(0)
DenHistogram = DenHistogramObj.Clone()
DenHistogram.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.GetTitle(
).find("GenMatch") is -1 and not Histogram.Class().InheritsFrom(
"TH2"):
Histogram.Rebin(RebinFactor)
DenHistogram.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 = "#epsilon_{ " + cutName + "} (" + str(
Histogram.GetXaxis().GetBinWidth(1)
) + " " + xAxisLabel[unitBeginIndex + 1:unitEndIndex] + " width)"
else:
yAxisLabel = "#epsilon_{ " + cutName + "} (" + str(
Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
#Histogram = ROOT.TGraphAsymmErrors(NumHistogramObj,DenHistogramObj)
if arguments.noTGraph or Histogram.Class().InheritsFrom("TH2"):
Histogram.Divide(DenHistogram)
else:
Histogram = TGraphAsymmErrors(Histogram, DenHistogram)
if not arguments.makeFancy:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = ""
if 'color' in source:
Histogram.SetMarkerColor(colors[source['color']])
Histogram.SetLineColor(colors[source['color']])
else:
Histogram.SetMarkerColor(colors[colorList[colorIndex]])
Histogram.SetLineColor(colors[colorList[colorIndex]])
colorIndex = colorIndex + 1
if colorIndex is len(colorList):
colorIndex = 0
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
### scaling histograms as per user's specifications
for histogram in Histograms:
if arguments.normalizeToUnitArea and histogram.Integral() > 0:
histogram.Scale(1. / histogram.Integral())
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram, LegendEntries[legendIndex], "LEP")
legendIndex = legendIndex + 1
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
if arguments.noTGraph:
for histogram in Histograms:
currentMax = histogram.GetMaximum() + histogram.GetBinError(
histogram.GetMaximumBin())
if (currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5 * finalMax
if finalMax is 0:
finalMax = 1
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
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)
histCounter = 0
plotting_options = ""
if arguments.plot_hist:
plotting_options = "HIST"
for histogram in Histograms:
if histogram.Class().InheritsFrom("TH2"):
histogram.SetTitle(histoTitle)
histogram.Draw("colz")
DatasetName = histogram.GetName()
DatasetName = DatasetName[
DatasetName.rfind('__') +
2:] # substring starting with the last underscore
DatasetLabel = TPaveLabel(topLeft_x_left, topLeft_y_bottom,
topLeft_x_right, topLeft_y_top,
DatasetName, "NDC")
DatasetLabel.SetBorderSize(0)
DatasetLabel.SetFillColor(0)
DatasetLabel.SetFillStyle(0)
DatasetLabel.Draw()
outputFile.cd()
Canvas.SetName(histogram.GetName())
Canvas.Write()
if arguments.makeFancy:
HeaderLabel.Draw()
else:
if histogram.InheritsFrom("TGraph") and histCounter == 0:
plotting_options = "AP"
histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TGraph"):
plotting_options = "P"
histCounter = histCounter + 1
if histogram.Class().InheritsFrom("TH2"):
return
#legend coordinates, empirically determined :-)
x_left = 0.1677852
x_right = 0.9647651
y_min = 0.6765734
y_max = 0.9
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
if arguments.makeFancy:
HeaderLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
Comparison = ratioHistogram(Histograms[0], Histograms[1])
elif makeDiffPlots:
Comparison = Histograms[0].Clone("diff")
Comparison.Add(Histograms[1], -1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("hist1-hist2")
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")
outputFile.cd()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/" + histogramName + ".pdf")
def main():
import argparse
parser = argparse.ArgumentParser(
usage="makePValuePlot.py [options] -o OUTPUTFILE --card CARD1",
description="plots pvalue scans for Z' analysis'",
formatter_class=argparse.ArgumentDefaultsHelpFormatter)
parser.add_argument("--card",
dest="cards",
default=[],
action="append",
help='add datacard to list of curves to plot')
parser.add_argument("--smooth",
dest="smooth",
action="store_true",
default=False,
help="Smooth observed values")
parser.add_argument("-c",
"--config",
dest="config",
default='',
help="config name")
parser.add_argument("-t",
"--tag",
dest="tag",
default='',
help="limit tag")
parser.add_argument("--ratioLabel",
dest="ratioLabel",
default='',
help="label for ratio")
args = parser.parse_args()
canv = ROOT.TCanvas("c1", "c1", 600, 450)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
style = setTDRStyle()
ROOT.gStyle.SetTitleYOffset(1)
ROOT.gStyle.SetPadLeftMargin(0.12)
ROOT.gStyle.SetPadBottomMargin(0.12)
ROOT.gStyle.SetOptStat(0)
ROOT.gStyle.SetTitleXSize(0.055)
ROOT.gStyle.SetLabelSize(0.055, "X")
ROOT.gStyle.SetLabelSize(0.055, "Y")
ROOT.gStyle.SetTitleXOffset(1.05)
#ROOT.gStyle.SetLabelYSize(0.04)
ROOT.gStyle.SetTitleYSize(0.055)
ROOT.gStyle.SetTitleYOffset(1.1)
plotPad.UseCurrentStyle()
plotPad.Draw()
plotPad.cd()
plotPad.DrawFrame(200, 1e-4, 4000, 10, ";M [GeV]; local p-Value")
plotPad.SetLogy()
#ROOT.gStyle.SetLabelXSize(0.04)
leg = ROOT.TLegend(0.32, 0.72, 0.9, 0.875, "", "brNDC")
leg.SetFillColor(10)
leg.SetLineColor(10)
leg.SetShadowColor(0)
leg.SetBorderSize(0)
leg.SetNColumns(2)
leg.SetTextSize(0.06)
graphs = []
name = "pValues_%s_%s" % (args.config, args.tag)
fileForHEPData = TFile("plots/" + name + "_forHEPData.root", "RECREATE")
for index, card in enumerate(args.cards):
if 'width' in card:
width = "signif" + card.split('width')[-1].split('_')[0]
else:
width = 'signif'
masses, pValues = getPValues(card)
minPVal, minPValMass = getMinPValue(card)
print card, minPVal, minPValMass
graphs.append(
ROOT.TGraph(len(masses), numpy.array(masses),
numpy.array(pValues)))
label = card.split("_")[-1].split(".")[0]
if args.smooth:
smoother = ROOT.TGraphSmooth("normal")
graphs[index] = deepcopy(
smoother.SmoothSuper(graphs[index], "linear", 0, 0.005))
graphs[index].SetLineColor(lineColors[width])
graphs[index].SetLineStyle(lineStyles[width])
leg.AddEntry(graphs[index], labels[width], "l")
graphs[index].Draw("Lsame")
graphs[index].SetLineWidth(2)
graphs[index].SetName("graphPVal%s" % width)
graphs[index].Write("graphPVal%s" % width)
leg.Draw()
leg.SetTextSize(0.045)
latex = ROOT.TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.03)
latex.SetNDC(True)
latexCMS = ROOT.TLatex()
latexCMS.SetTextFont(62)
latexCMS.SetTextSize(0.055)
latexCMS.SetNDC(True)
latexCMSExtra = ROOT.TLatex()
latexCMSExtra.SetTextFont(52)
latexCMSExtra.SetTextSize(0.03)
latexCMSExtra.SetNDC(True)
configName = "scanConfiguration_%s" % args.config
config = __import__(configName)
chan = config.leptons
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"139.7 fb^{-1} (13 TeV, #mu^{+}#mu^{-})", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99, "136.8 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"136.8 fb^{-1} (13 TeV, ee) + 139.7 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
cmsExtra = "Preliminary"
latexCMS.DrawLatex(0.14, 0.81, "CMS")
if "Simulation" in cmsExtra:
yLabelPos = 0.78
else:
yLabelPos = 0.78
latexCMSExtra.DrawLatex(0.14, yLabelPos, "%s" % (cmsExtra))
ZeroSigmaLine = ROOT.TLine(200, 0.5, 4000, 0.5)
ZeroSigmaLine.SetLineStyle(ROOT.kDashed)
ZeroSigmaLine.Draw("same")
OneSigmaLine = ROOT.TLine(200, 0.317 / 2, 4000, 0.317 / 2)
OneSigmaLine.SetLineStyle(ROOT.kDashed)
OneSigmaLine.Draw("same")
TwoSigmaLine = ROOT.TLine(200, 0.0455 / 2, 4000, 0.0455 / 2)
TwoSigmaLine.SetLineStyle(ROOT.kDashed)
TwoSigmaLine.Draw("same")
ThreeSigmaLine = ROOT.TLine(200, 0.0027 / 2, 4000, 0.0027 / 2)
ThreeSigmaLine.SetLineStyle(ROOT.kDashed)
ThreeSigmaLine.Draw("same")
FourSigmaLine = ROOT.TLine(200, 0.00006 / 2, 4000, 0.00006 / 2)
FourSigmaLine.SetLineStyle(ROOT.kDashed)
#~ FourSigmaLine.Draw("same")
FiveSigmaLine = ROOT.TLine(200, 3e-07, 4000, 3e-07)
FiveSigmaLine.SetLineStyle(ROOT.kDashed)
#~ FiveSigmaLine.Draw("same")
latex = ROOT.TLatex()
latex.SetTextFont(42)
latex.SetTextAlign(31)
latex.SetTextSize(0.04)
#~ latex.SetNDC(Tru78
latex.DrawLatex(4150, 0.5, "0#sigma")
latex.DrawLatex(4150, 0.317 / 2, "1#sigma")
latex.DrawLatex(4150, 0.0455 / 2, "2#sigma")
latex.DrawLatex(4150, 0.0027 / 2, "3#sigma")
#~ latex.DrawLatex(4200, 0.00006/2, "4#sigma")
#~ latex.DrawLatex(4200, 3e-7, "5#sigma")
#~ ROOT.gPad.WaitPrimitive()
plotPad.SetTicks(1, 1)
plotPad.RedrawAxis()
if args.smooth:
name += "_smoothed"
#name = name+".pdf"
canv.Print("plots/" + name + ".pdf")
canv.Print("plots/" + name + ".root")
plotPad.RedrawAxis()
fileForHEPData.Write()
fileForHEPData.Close()
f1 = TFile(plot["file1"])
f2 = TFile(plot["file2"])
h1 = f1.Get(plot["name"])
h2 = f2.Get(plot["name"])
h1.GetXaxis().SetNdivisions(5)
h1.GetYaxis().SetNdivisions(5)
h1.GetXaxis().SetTitleSize(0.05)
h1.GetYaxis().SetTitleSize(0.05)
h1.GetZaxis().SetTitleSize(0.05)
h1.GetXaxis().SetLabelSize(0.05)
h1.GetYaxis().SetLabelSize(0.05)
h1.GetZaxis().SetLabelSize(0.05)
h1.GetXaxis().SetTitleOffset(1.0)
h1.GetYaxis().SetTitleOffset(1.6)
HeaderLabel = TPaveLabel(0.2, 0.92, 0.8, 0.98,title,"NDC")
# HeaderLabel.SetTextAlign(32)
HeaderLabel.SetTextFont(42)
HeaderLabel.SetTextSize(0.8)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
if h1.Class().InheritsFrom("TH2"):
is2D = True
else:
is2D = False
if is2D:
c.SetRightMargin(0.15)
c.SetLogz(True)
def MakeOneDHist(histogramDirectory, histogramName,integrateDir):
if arguments.verbose:
print "Creating histogram", histogramName, "in directory", histogramDirectory
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetTextFont(42)
HeaderLabel.SetTextSize(0.697674)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
CMSLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
CMSLabel.SetTextAlign(32)
CMSLabel.SetTextFont(42)
CMSLabel.SetTextSize(0.697674)
CMSLabel.SetBorderSize(0)
CMSLabel.SetFillColor(0)
CMSLabel.SetFillStyle(0)
if makeFancy:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,"CMS Preliminary","NDC")
LumiLabel.SetTextFont(62)
LumiLabel.SetTextSize(0.7)
LumiLabel.SetTextAlign(12)
else:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
LumiLabel.SetTextAlign(32)
LumiLabel.SetTextFont(42)
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
canvasName = histogramName
if integrateDir is "left":
canvasName += "_CumulativeLeft"
elif integrateDir is "right":
canvasName += "_CumulativeRight"
Canvas = TCanvas(canvasName)
Histograms = []
RefIndex = -99
LegendEntries = []
colorIndex = 0
markerStyleIndex = 0
fillIndex = 0
for source in input_sources: # loop over different input sources in config file
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],source['dataset'])
inputFile = TFile(dataset_file)
if arguments.generic:
if histogramDirectory == "":
histPath = histogramName
else:
histPath = histogramDirectory + "/" + histogramName
HistogramObj = inputFile.Get(histPath)
else:
HistogramObj = inputFile.Get(source['channel'] + "Plotter/" + histogramDirectory + "/" + histogramName)
if not HistogramObj:
print "WARNING: Could not find histogram " + source['channel'] + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = HistogramObj.Clone()
Histogram.SetDirectory(0)
inputFile.Close()
Histogram.Sumw2()
if arguments.verbose:
print " Got histogram", Histogram.GetName(), "from file", dataset_file
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.GetTitle().find("GenMatch") is -1:
Histogram.Rebin(RebinFactor)
# correct bin contents of object multiplcity plots
if Histogram.GetName().startswith("num") and "PV" not in Histogram.GetName():
# include overflow bin
for bin in range(2,Histogram.GetNbinsX()+2):
content = Histogram.GetBinContent(bin)
Histogram.SetBinContent(bin, content/float(bin-1))
xAxisLabel = Histogram.GetXaxis().GetTitle()
unitBeginIndex = xAxisLabel.find("[")
unitEndIndex = xAxisLabel.find("]")
xAxisLabelVar = xAxisLabel
if "_pfx" in Histogram.GetName() or "_pfy" in Histogram.GetName() or "_sigma" in Histogram.GetName():
yAxisLabel = Histogram.GetYaxis().GetTitle()
else:
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]
xAxisLabelVar = xAxisLabel[0:unitBeginIndex]
else:
yAxisLabel = "Entries per bin (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
if arguments.normalizeToUnitArea and arguments.makeSignificancePlots:
unit = "Efficiency"
else:
unit = "Yield"
if integrateDir is "left":
yAxisLabel = unit + ", " + xAxisLabelVar + "< x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
if integrateDir is "right":
yAxisLabel = unit + ", " + xAxisLabelVar + "> x (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " bin width)"
nbins = Histogram.GetNbinsX()
if not noOverFlow:
Histogram.SetBinContent(nbins, Histogram.GetBinContent(nbins) + Histogram.GetBinContent(nbins+1)) # Add overflow
Histogram.SetBinError(nbins, math.sqrt(math.pow(Histogram.GetBinError(nbins),2) + math.pow(Histogram.GetBinError(nbins+1),2))) # Set the errors to be the sum in quadrature
if not noUnderFlow:
Histogram.SetBinContent(1, Histogram.GetBinContent(1) + Histogram.GetBinContent(0)) # Add underflow
Histogram.SetBinError(1, math.sqrt(math.pow(Histogram.GetBinError(1), 2) + math.pow(Histogram.GetBinError(0), 2))) # Set the errors to be the sum in quadrature
if not arguments.makeFancy and not arguments.generic:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
if len(splitTitle) > 1:
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = splitTitle[0]
else:
histoTitle = ""
if 'color' in source:
Histogram.SetMarkerColor(colors[source['color']])
Histogram.SetLineColor(colors[source['color']])
else:
Histogram.SetMarkerColor(colors[colorList[colorIndex]])
Histogram.SetLineColor(colors[colorList[colorIndex]])
colorIndex = colorIndex + 1
if colorIndex is len(colorList):
colorIndex = 0
markerStyleIndex = markerStyleIndex + 1
if markerStyleIndex is len(markerStyleList):
markerStyleIndex = 0
fillIndex = fillIndex + 1
if 'scale' in source:
Histogram.Scale(source['scale'])
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
else:
markerStyle = markers[markerStyleList[markerStyleIndex]]
fillStyle = 0
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
else:
markerStyle = markerStyle + fills[fillList[fillIndex]]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetMarkerSize(0.5)
Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
if arguments.normalizeToUnitArea and Histogram.Integral() > 0:
Histogram.Scale(1./Histogram.Integral())
Histogram = MakeIntegralHist(Histogram, integrateDir)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
if 'reference' in source:
if source['reference']:
RefIndex = len(Histograms)-1
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
# Legend.AddEntry(histogram,LegendEntries[legendIndex],"P")
legendIndex = legendIndex+1
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
for histogram in Histograms:
currentMax = histogram.GetMaximum() + histogram.GetBinError(histogram.GetMaximumBin())
if(currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5*finalMax
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
addOneToRatio = -1
if arguments.addOneToRatio:
addOneToRatio = arguments.addOneToRatio
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
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)
histCounter = 0
plotting_options = ""
if arguments.generic:
plotting_options = "p,e"
if arguments.plot_hist:
plotting_options = "HIST"
for histogram in Histograms:
histogram.SetTitle(histoTitle)
if arguments.verbose:
print " Drawing hist " + histogram.GetName() + ", with plotting_options = " + plotting_options + ", with mean = " + str(histogram.GetMean()) + ", with color = " + str(histogram.GetLineColor())
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
histogram.SetMaximum(finalMax)
if "_pfx" not in Histogram.GetName() and "_pfy" not in Histogram.GetName() and "_sigma" not in Histogram.GetName():
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
plotting_options = plotting_options + " SAME"
histCounter = histCounter + 1
#legend coordinates, empirically determined :-)
x_left = 0.1677852
x_right = 0.9647651
y_min = 0.6765734
y_max = 0.9
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
# Deciding which text labels to draw and drawing them
if arguments.makeFancy:
HeaderLabel.Draw()
LumiLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Comparisons = []
Canvas.cd(2)
if RefIndex == -99:
Reference = Histograms[0]
else:
Reference = Histograms[RefIndex]
for Histogram in Histograms:
if Histogram is Reference:
continue
if makeRatioPlots:
makeRatio = functools.partial (ratioHistogram,Histogram, Reference)
if arguments.ratioRelErrMax is not -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, relErrMax = float(arguments.ratioRelErrMax))
if addOneToRatio != -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, addOne = bool (addOneToRatio))
Comparison = makeRatio()
elif makeDiffPlots:
Comparison = Reference.Clone("diff")
Comparison.Add(Histograms[1],-1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("X-ref")
Comparison.SetLineColor(Histogram.GetLineColor())
Comparison.SetFillColor(Histogram.GetFillColor())
Comparison.SetFillStyle(Histogram.GetFillStyle())
Comparison.SetMarkerColor(Histogram.GetMarkerColor())
Comparison.SetMarkerStyle(Histogram.GetMarkerStyle())
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)
if addOneToRatio == -1: # it gets initialized to this dummy value of -1
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
else:
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange + 1.0, RatioYRange + 1.0)
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)
Comparisons.append(Comparison)
option = "E0"
for index,Comparison in enumerate(Comparisons):
if index == 0:
option += " SAME"
Comparison.Draw(option)
outputFile.cd(histogramDirectory)
Canvas.Write()
if arguments.verbose:
print " Finished writing canvas: ", Canvas.GetName()
if arguments.savePDFs:
Canvas.SaveAs("comparison_histograms_pdfs/"+histogramName+".pdf")
def MakeOneHist(dirName, histogramName):
HeaderLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetTextFont(42)
HeaderLabel.SetTextSize(0.697674)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
CMSLabel = TPaveLabel(header_x_left,header_y_bottom,header_x_right,header_y_top,HeaderText,"NDC")
CMSLabel.SetTextAlign(32)
CMSLabel.SetTextFont(42)
CMSLabel.SetTextSize(0.697674)
CMSLabel.SetBorderSize(0)
CMSLabel.SetFillColor(0)
CMSLabel.SetFillStyle(0)
if makeFancy:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,"CMS Preliminary","NDC")
LumiLabel.SetTextFont(62)
LumiLabel.SetTextSize(0.7)
LumiLabel.SetTextAlign(12)
else:
LumiLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,LumiText,"NDC")
LumiLabel.SetTextAlign(32)
LumiLabel.SetTextFont(42)
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
#legend coordinates, empirically determined :-)
x_left = 0.4
x_right = 0.7
y_min = 0.15
y_max = 0.3
Legend = TLegend(x_left,y_min,x_right,y_max)
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas(histogramName)
Histograms = []
HistogramClones = []
NBins = []
MaxXValues = []
MinXValues = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],source['dataset'])
inputFile = TFile(dataset_file)
NumHistogramObj = inputFile.Get(source['num_channel'] + "Plotter/" + dirName + "/" + histogramName)
if 'condor_dir_den' in source: # If specified, take the denominator histogram from a different condor directory.
dataset_fileDen = "condor/%s/%s.root" % (source['condor_dir_den'],source['dataset'])
inputFileDen = TFile(dataset_fileDen)
DenHistogramObj = inputFileDen.Get(source['den_channel'] + "Plotter/" + dirName + "/" + histogramName)
else: # Default is to use the same condor directory
DenHistogramObj = inputFile.Get(source['den_channel'] + "Plotter/" + dirName + "/" + histogramName)
if not NumHistogramObj:
print "WARNING: Could not find histogram " + source['num_channel'] + "Plotter/" + dirName + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
if not DenHistogramObj:
print "WARNING: Could not find histogram " + source['den_channel'] + "Plotter/" + dirName + "/" + histogramName + " in file " + dataset_file + ". Will skip it and continue."
return
Histogram = NumHistogramObj.Clone()
if Histogram.Class().InheritsFrom("TH2"):
Histogram.SetName(Histogram.GetName() + "__" + source['dataset'])
Histogram.SetDirectory(0)
DenHistogram = DenHistogramObj.Clone()
DenHistogram.SetDirectory(0)
inputFile.Close()
nbinsN = Histogram.GetNbinsX()
nbinsD = DenHistogram.GetNbinsX()
if not noOverFlow:
# Add overflow
Histogram.SetBinContent( nbinsN, Histogram.GetBinContent(nbinsN) + Histogram.GetBinContent(nbinsN+1))
DenHistogram.SetBinContent(nbinsD, DenHistogram.GetBinContent(nbinsD) + DenHistogram.GetBinContent(nbinsD+1))
# Set the errors to be the sum in quadrature
Histogram.SetBinError( nbinsN, math.sqrt(math.pow(Histogram.GetBinError(nbinsN),2) + math.pow(Histogram.GetBinError(nbinsN+1),2)))
DenHistogram.SetBinError(nbinsD, math.sqrt(math.pow(DenHistogram.GetBinError(nbinsD),2) + math.pow(DenHistogram.GetBinError(nbinsD+1),2)))
if not noUnderFlow:
# Add underflow
Histogram.SetBinContent( 1, Histogram.GetBinContent(1) + Histogram.GetBinContent(0))
DenHistogram.SetBinContent(1, DenHistogram.GetBinContent(1) + DenHistogram.GetBinContent(0))
# Set the errors to be the sum in quadrature
Histogram.SetBinError( 1, math.sqrt(math.pow(Histogram.GetBinError(1), 2) + math.pow(Histogram.GetBinError(0), 2)))
DenHistogram.SetBinError(1, math.sqrt(math.pow(DenHistogram.GetBinError(1), 2) + math.pow(DenHistogram.GetBinError(0), 2)))
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.GetTitle().find("GenMatch") is -1 and not Histogram.Class().InheritsFrom("TH2"):
Histogram.Rebin(RebinFactor)
DenHistogram.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 = "#epsilon_{ " + cutName + "} (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " " + xAxisLabel[unitBeginIndex+1:unitEndIndex] + " width)"
else:
yAxisLabel = "#epsilon_{ " + cutName + "} (" + str(Histogram.GetXaxis().GetBinWidth(1)) + " width)"
if arguments.normalizeToUnitArea:
yAxisLabel = yAxisLabel + " (Unit Area Norm.)"
#check if bin content is consistent
TEfficiency.CheckConsistency(Histogram,DenHistogram)
for i in range(1,Histogram.GetNbinsX()+1):
if Histogram.GetBinContent(i) > DenHistogram.GetBinContent(i):
DenHistogram.SetBinContent(i,Histogram.GetBinContent(i))
#HistogramClone and HistogramClones only used for ratio plot
HistogramClone = Histogram.Clone()
HistogramClone.SetDirectory(0)
HistogramClone.Divide(DenHistogram)
Nbins = HistogramClone.GetNbinsX()
MaxXValue = HistogramClone.GetXaxis().GetBinLowEdge(Nbins+1)
MinXValue = HistogramClone.GetXaxis().GetBinLowEdge(1)
#this Histogram becomes the main TEfficiency
if Histogram.Class().InheritsFrom("TH2"):
Histogram.Divide(DenHistogram)
else:
#using default methods (which give correct uncertainties)
#see https://root.cern.ch/doc/master/classTEfficiency.html (c.f. section IV)
Histogram = TEfficiency(Histogram,DenHistogram)
if not arguments.makeFancy:
fullTitle = Histogram.GetTitle()
splitTitle = fullTitle.split(":")
# print splitTitle
if len(splitTitle) > 1:
histoTitle = splitTitle[1].lstrip(" ")
else:
histoTitle = splitTitle[0]
else:
histoTitle = ""
if 'color' in source:
Histogram.SetMarkerColor(colors[source['color']])
Histogram.SetLineColor(colors[source['color']])
else:
Histogram.SetMarkerColor(colors[colorList[colorIndex]])
Histogram.SetLineColor(colors[colorList[colorIndex]])
colorIndex = colorIndex + 1
if colorIndex is len(colorList):
colorIndex = 0
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
HistogramClones.append(HistogramClone)
NBins.append(Nbins)
MaxXValues.append(MaxXValue)
MinXValues.append(MinXValue)
### scaling histograms as per user's specifications
for histogram in Histograms:
if arguments.normalizeToUnitArea and histogram.Integral() > 0:
histogram.Scale(1./histogram.Integral())
### formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
legendIndex = legendIndex+1
### finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 1.1
if arguments.setYMax:
finalMax = float(arguments.setYMax)
### Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
addOneToRatio = -1
if arguments.addOneToRatio:
addOneToRatio = arguments.addOneToRatio
dontRebinRatio = -1
if arguments.dontRebinRatio:
dontRebinRatio = arguments.dontRebinRatio
ratioRelErrMax = -1
if arguments.ratioRelErrMax:
ratioRelErrMax = arguments.ratioRelErrMax
yAxisMin = 0.0001
if arguments.setYMin:
yAxisMin = float(arguments.setYMin)
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)
histCounter = 0
plotting_options = ""
if arguments.plot_hist:
plotting_options = "HIST"
h = TH2F("h1","",NBins[0],MinXValues[0],MaxXValues[0],110,0.,finalMax)
h.SetTitle(";"+xAxisLabel+";"+yAxisLabel)
h.Draw()
for histogram in Histograms:
if histogram.Class().InheritsFrom("TH2"):
histogram.SetTitle(histoTitle)
histogram.Draw("colz")
DatasetName = histogram.GetName()
DatasetName = DatasetName[DatasetName.rfind('__')+2:] # substring starting with the last underscore
DatasetLabel = TPaveLabel(topLeft_x_left,topLeft_y_bottom,topLeft_x_right,topLeft_y_top,DatasetName,"NDC")
DatasetLabel.SetBorderSize(0)
DatasetLabel.SetFillColor(0)
DatasetLabel.SetFillStyle(0)
DatasetLabel.Draw()
outputFile.cd()
Canvas.SetName(histogram.GetName())
Canvas.Write()
else:
if histogram.InheritsFrom("TEfficiency") and histCounter==0:
plotting_options = "P SAME"
histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TEfficiency"):
plotting_options = "P" + " SAME"
histCounter = histCounter + 1
if histogram.Class().InheritsFrom("TH2"):
return
Legend.Draw()
if arguments.makeFancy:
HeaderLabel.Draw()
LumiLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
makeRatio = functools.partial (ratioHistogram,HistogramClones[0],HistogramClones[1])
if addOneToRatio != -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, addOne = bool (addOneToRatio))
if ratioRelErrMax is not -1: # it gets initialized to this dummy value of -1
makeRatio = functools.partial (makeRatio, relErrMax = float (ratioRelErrMax))
if dontRebinRatio is True:
makeRatio = functools.partial (makeRatio, dontRebinRatio)
Comparison = makeRatio ()
elif makeDiffPlots:
Comparison = Histograms[0].Clone("diff")
Comparison.Add(Histograms[1],-1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("hist1-hist2")
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)
if addOneToRatio == -1: # it gets initialized to this dummy value of -1
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange, RatioYRange)
else:
Comparison.GetYaxis().SetRangeUser(-1*RatioYRange + 1.0, RatioYRange + 1.0)
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")
outputFile.cd(dirName)
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/"+histogramName+".pdf")
def makeLimitPlot(output,obs,exp,chan,printStats=False):
fileForHEPData = TFile("plots/"+output+"_forHEPData.root","RECREATE")
obsLimits = {}
for obsFile in obs:
if 'width' in obsFile:
width = obsFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
obsLimits[width] = createObsGraph(obsFile)
if SMOOTH:
for width,obsGraph in obsLimits.iteritems():
smooth_obs=TGraphSmooth("normal")
GraphObs_nonSmooth=obsGraph
obsLimits[width]=copy.deepcopy(smooth_obs.SmoothSuper(GraphObs_nonSmooth,"linear",0,0.005))
obsLimits[width].SetLineWidth(3)
expLimits = {}
for expFile in exp:
if 'width' in expFile:
width = expFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
expLimits[width] = createExpGraph(expFile)
cCL=TCanvas("cCL", "cCL",0,0,600,450)
gStyle.SetOptStat(0)
gStyle.SetPadRightMargin(0.063)
gStyle.SetPadLeftMargin(0.14)
gStyle.SetPadBottomMargin(0.12)
plotPad = ROOT.TPad("plotPad","plotPad",0,0,1,1)
plotPad.Draw()
plotPad.cd()
smoother=TGraphSmooth("normal")
smoother2=TGraphSmooth("normal")
zprimeX=[]
zprimeY=[]
fileZPrime=open('tools/xsec_ssm.txt','r')
for entries in fileZPrime:
entry=entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1])/1928)
zpX=numpy.array(zprimeX)
zpY=numpy.array(zprimeY)
GraphZPrime=TGraph(len(zprimeX),zpX,zpY)
GraphZPrimeSmooth=smoother2.SmoothSuper(GraphZPrime,"linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen+3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX=[]
zprimePsiY=[]
fileZPrimePsi=open('tools/xsec_psi.txt','r')
for entries in fileZPrimePsi:
entry=entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1])/1928)
zpPsiX=numpy.array(zprimePsiX)
zpPsiY=numpy.array(zprimePsiY)
GraphZPrimePsi=TGraph(len(zprimePsiX),zpPsiX,zpPsiY)
GraphZPrimePsiSmooth=smoother.SmoothSuper(GraphZPrimePsi,"linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
DummyGraph=TH1F("DummyGraph","",100,200,5500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if SPIN2:
DummyGraph.GetYaxis().SetTitle("[#sigma#upoint#font[12]{B}] G_{KK} / #sigma#upoint#font[12]{B}] Z")
else:
DummyGraph.GetYaxis().SetTitle("[#sigma#upoint#font[12]{B}] Z' / [#sigma#upoint#font[12]{B}] Z")
# if SPIN2:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
# else:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(200,5500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(3e-4)
DummyGraph.GetXaxis().SetLabelSize(0.055)
DummyGraph.GetXaxis().SetTitleSize(0.055)
DummyGraph.GetXaxis().SetTitleOffset(1.05)
DummyGraph.GetYaxis().SetLabelSize(0.055)
DummyGraph.GetYaxis().SetTitleSize(0.055)
DummyGraph.GetYaxis().SetTitleOffset(1.3)
DummyGraph.Draw()
plCMS=TPaveLabel(.16,.76,.27,.83,"CMS","NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim=TPaveLabel(.16,.76,.27,.82,"Preliminary","NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
# plPrelim.Draw()
leg=TLegend(0.420517,0.7,0.85,0.878644,"","brNDC")
legWidth=TLegend(0.625,0.5,0.9,0.7,"width","brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.0425)
legWidth.SetTextSize(0.0425)
colors = {'01':ROOT.kBlue,'03':ROOT.kRed,'05':ROOT.kGreen+3,'10':ROOT.kOrange}
# for width in sorted(obsLimits):
# obsGraph = obsLimits[width]
# if colors.has_key(width):
# obsGraph.SetLineColor(colors[width])
# obsGraph.Draw("lsame")
# if width == '0.006':
# leg.AddEntry(obsGraph,"Observed 95% CL limit width 0.6%","l")
# else:
# leg.AddEntry(obsGraph,"Observed 95%% CL limit width %d%%"%int(width),"l")
#
# for width in sorted(expLimits):
# expGraph = expLimits[width]
# if colors.has_key(width):
# expGraph.SetLineColor(colors[width])
# expGraph.Draw("lsame")
# if width == '0.006':
# leg.AddEntry(expGraph,"Expected 95% CL limit width 0.6%, median","l")
# else:
# leg.AddEntry(expGraph,"Expected 95%% CL limit width %d%%, median"%(int(width)),"l")
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
if colors.has_key(width):
obsGraph.SetLineColor(colors[width])
obsGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(obsGraph,"Obs. 95% CL limit","l")
for width in sorted(expLimits):
expGraph = expLimits[width]
if colors.has_key(width):
expGraph.SetLineColor(colors[width])
expGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(expGraph,"Exp. 95% CL limit, median","l")
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
if colors.has_key(width):
obsGraph.SetLineColor(colors[width])
if width == '0.006':
legWidth.AddEntry(obsGraph,"0.6%","l")
else:
legWidth.AddEntry(obsGraph,"%d%%"%int(width),"l")
if not SPIN2:
GraphZPrimeSmooth.Draw("lsame")
GraphZPrimePsiSmooth.Draw("lsame")
leg1=TLegend(0.625,0.35,0.825,0.5,"","brNDC")
leg1.SetTextSize(0.0375)
leg1.AddEntry(GraphZPrimeSmooth,"Z'_{SSM} (width 2.97%)","l")
leg1.AddEntry(GraphZPrimePsiSmooth,"Z'_{#Psi} (width 0.53%)","l")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetLineColor(0)
leg1.SetFillStyle(0)
leg1.SetBorderSize(0)
leg1.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#plCMS.Draw()
plotPad.SetTicks(1,1)
plotPad.RedrawAxis()
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
legWidth.SetLineWidth(0)
legWidth.SetLineStyle(0)
legWidth.SetLineColor(0)
legWidth.SetFillStyle(0)
legWidth.SetNColumns(2)
legWidth.Draw("hist")
if "Moriond" in output:
if (chan=="mumu"):
plLumi=TPaveLabel(.65,.885,.9,.99,"36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})","NBNDC")
elif (chan=="elel"):
plLumi=TPaveLabel(.65,.885,.9,.99,"35.9 fb^{-1} (13 TeV, ee)","NBNDC")
elif (chan=="elmu"):
plLumi=TPaveLabel(.27,.885,.9,.99,"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})","NBNDC")
else:
if (chan=="mumu"):
plLumi=TPaveLabel(.65,.905,.9,.99,"13.0 fb^{-1} (13 TeV, #mu#mu)","NBNDC")
elif (chan=="elel"):
plLumi=TPaveLabel(.65,.905,.9,.99,"2.7 fb^{-1} (13 TeV, ee)","NBNDC")
elif (chan=="elmu"):
plLumi=TPaveLabel(.4,.905,.9,.99,"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)","NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.RedrawAxis()
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
obsGraph.SetName("graphObs%s"%width)
obsGraph.Write("graphObs%s"%width)
for width in sorted(expLimits):
expGraph = expLimits[width]
expGraph.SetName("graphExp%s"%width)
expGraph.Write("graphExp%s"%width)
fileForHEPData.Write()
fileForHEPData.Close()
cCL.Update()
printPlots(cCL,output)
def makeBiasPlot(output,
muFile,
chan,
interference,
printStats=False,
obs2="",
ratioLabel=""):
mu = open(muFile, 'r')
limits = {}
mux = []
muy = []
mu1SigLow = []
mu1SigHigh = []
mu2SigLow = []
mu2SigHigh = []
for entry in mu:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
mux.append(massPoint)
print massPoint, limits[massPoint][medianNr]
muy.append(limits[massPoint][medianNr])
mu1SigLow.append(limits[massPoint][lower1Sig])
mu1SigHigh.append(limits[massPoint][upper1Sig])
mu2SigLow.append(limits[massPoint][lower2Sig])
mu2SigHigh.append(limits[massPoint][upper2Sig])
muX = numpy.array(mux)
muY = numpy.array(muy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of mux: ", len(mux)
if printStats: print "length of mu1SigLow: ", len(mu1SigLow)
if printStats: print "length of mu1SigHigh: ", len(mu1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(mux)):
values2.append(mu2SigLow[x])
xPointsForValues2.append(mux[x])
for x in range(len(mux) - 1, 0 - 1, -1):
values2.append(mu2SigHigh[x])
xPointsForValues2.append(mux[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(mux)):
values.append(mu1SigLow[x])
xPointsForValues.append(mux[x])
for x in range(len(mux) - 1, 0 - 1, -1):
values.append(mu1SigHigh[x])
xPointsForValues.append(mux[x])
if printStats: print "length of values: ", len(values)
mu2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
mu1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "mu2Sig: ", mu2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "mu1Sig: ", mu1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, mu2Sig)
GraphErr2Sig.SetFillColor(ROOT.kYellow + 1)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, mu1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
muX = numpy.array(mux)
muY = numpy.array(muy)
GraphMU = TGraph(len(muX), muX, muY)
GraphMU.SetLineWidth(3)
GraphMU.SetLineStyle(2)
GraphMU.SetLineColor(ROOT.kBlue)
#Draw the graphs:
DummyGraph = TH1F("DummyGraph", "", 100, 10, 40)
DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]")
DummyGraph.GetYaxis().SetTitle("#hat{#mu}")
gStyle.SetOptStat(0)
if "Des" in output:
DummyGraph.GetXaxis().SetRangeUser(10, 28)
else:
DummyGraph.GetXaxis().SetRangeUser(10, 40)
DummyGraph.SetMinimum(-2)
DummyGraph.SetMaximum(10)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
DummyGraph.SetLineColor(ROOT.kWhite)
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphMU.Draw("lpsame")
else:
GraphMU.Draw("lp")
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
leg.AddEntry(GraphMU, "median value", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "1#sigma quantile", "f")
leg.AddEntry(GraphErr2Sig, "2#sigma quantile", "f")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
maxX = 40
if "Des" in output:
maxX = 28
line = ROOT.TLine(10, 0, maxX, 0)
if "mu1" in output:
line = ROOT.TLine(10, 1, maxX, 1)
line.SetLineStyle(ROOT.kDashed)
line.Draw("same")
plotPad.RedrawAxis()
cCL.Update()
printPlots(cCL, output)
#
# This macro displays the ROOT Directory data structure
#
from ROOT import TCanvas, TPaveLabel, TPaveText, TText, TArrow, TLine
from ROOT import gROOT
gROOT.Reset()
c1 = TCanvas('c1', 'ROOT FilDir description', 700, 900)
c1.Range(1, 1, 19, 24.5)
title = TPaveLabel(4, 23, 16, 24.2, 'ROOT File/Directory/Key description')
title.SetFillColor(16)
title.Draw()
keycolor = 42
dircolor = 21
objcolor = 46
file = TPaveText(2, 19, 6, 22)
file.SetFillColor(39)
file.Draw()
file.SetTextSize(0.04)
file.AddText('TFile')
file.AddText('Header')
arrow = TArrow(6, 20.5, 17, 20.5, 0.02, '|>')
arrow.SetFillStyle(1001)
arrow.SetLineWidth(2)
arrow.Draw()
free = TPaveText(8, 20, 11, 21)
free.SetFillColor(18)
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 makeLimitPlot(output,
obs,
exp,
chan,
printStats=False,
obs2="",
ratioLabel=""):
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kYellow + 1)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
smoother = TGraphSmooth("normal")
smoother2 = TGraphSmooth("normal")
zprimeX = []
zprimeY = []
fileZPrime = open('tools/xsec_SSM.txt', 'r')
for entries in fileZPrime:
entry = entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1]) * 1.3 / 1928)
zpX = numpy.array(zprimeX)
zpY = numpy.array(zprimeY)
GraphZPrime = TGraph(481, zpX, zpY)
GraphZPrimeSmooth = smoother2.SmoothSuper(GraphZPrime, "linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen + 3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX = []
zprimePsiY = []
fileZPrimePsi = open('tools/xsec_PSI.txt', 'r')
for entries in fileZPrimePsi:
entry = entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1]) * 1.3 / 1928)
zpPsiX = numpy.array(zprimePsiX)
zpPsiY = numpy.array(zprimePsiY)
GraphZPrimePsi = TGraph(481, zpPsiX, zpPsiY)
GraphZPrimePsiSmooth = smoother.SmoothSuper(GraphZPrimePsi, "linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
if "Moriond" in output:
DummyGraph = TH1F("DummyGraph", "", 100, 120, 4500)
else:
DummyGraph = TH1F("DummyGraph", "", 100, 400, 4500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#mu#mu+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu#mu+X)"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)"
)
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)"
)
gStyle.SetOptStat(0)
if "Moriond" in output:
DummyGraph.GetXaxis().SetRangeUser(120, 4500)
else:
DummyGraph.GetXaxis().SetRangeUser(400, 4500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(4e-4)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
if not SPIN2:
GraphZPrimeSmooth.Draw("lsame")
GraphZPrimePsiSmooth.Draw("lsame")
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.540517, 0.623051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
leg.AddEntry(GraphObs, "% Observed 95% CL limit" % ratioLabel[1], "l")
leg.AddEntry(GraphObs2, "%s Observed 95% CL limit" % ratioLabel[0],
"l")
else:
leg.AddEntry(GraphObs, "Observed 95% CL limit", "l")
leg.AddEntry(GraphExp, "Expected 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Expected 95% CL limit, 1 s.d.", "f")
leg.AddEntry(GraphErr2Sig, "Expected 95% CL limit, 2 s.d.", "f")
leg1 = TLegend(0.665517, 0.483051, 0.834885, 0.623051, "", "brNDC")
leg1.SetTextSize(0.032)
if not SPIN2:
leg1.AddEntry(GraphZPrimePsiSmooth, "Z'_{#Psi} (LOx1.3)", "l")
leg1.AddEntry(GraphZPrimeSmooth, "Z'_{SSM} (LOx1.3)", "l")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetLineColor(0)
leg1.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(400, 1, 4500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(400, 0.9, 4500, 1.1, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
cCL.Update()
printPlots(cCL, output)
def MakeOneHist(varXaxis, varConst, xvalues, constval):
if len(xvalues)<=1:
return # Do not make plot if there is only 1 xvalue
Legend = TLegend()
Legend.SetBorderSize(0)
Legend.SetFillColor(0)
Legend.SetFillStyle(0)
Canvas = TCanvas("sigEff_"+varConst+str(constval)+"_vs_"+varXaxis)
Histograms = []
LegendEntries = []
colorIndex = 0
for source in input_sources: # loop over different input sources in config file
# print "Debug: running over input_source from: ", source['condor_dir'], " for varXaxis=", varXaxis, ", varConst=", varConst
# Create histogram of efficiencies with appropriate binning
xAxisBins = array('d')
xBinWidth = xvalues[1] - xvalues[0]
for xval in xvalues:
xAxisBins.append(xval - xBinWidth/2.0)
xAxisBins.append(xvalues[-1] + xBinWidth/2.0) # add an extra bin boundary for the last bin.
Histogram = TH1F("Histogram", ";x title;signal efficiency", len(xvalues), xAxisBins)
Histogram.SetDirectory(0)
# Now fill the histogram of efficiencies:
for xval in xvalues:
if varXaxis=="mass" and varConst=="lifetime":
mass = xval
lifetime = constval
elif varXaxis=="lifetime" and varConst=="mass":
lifetime = xval
mass = constval
else:
print "Unrecognized value of varXaxis=", varXaxis
return
dataset_file = "condor/%s/%s.root" % (source['condor_dir'],dataset)
dataset_file = dataset_file.replace("MASS", str(mass))
dataset_file = dataset_file.replace("LIFETIME", str(lifetime))
inputFile = TFile(dataset_file)
HistCutflow = inputFile.Get("OSUAnalysis/" + source['channel'] + "CutFlow")
if not HistCutflow:
print "WARNING: Could not find histogram OSUAnalysis/" + source['channel'] + "CutFlow in file " + dataset_file + ". Will skip it and continue."
return
# calculate efficiency
nbinsCutflow = HistCutflow.GetNbinsX()
if arguments.xsecFile:
xsec = float(signal_cross_sections[str(mass)]['value'])
denom = xsec * intLumi
else:
denom = HistCutflow.GetBinContent(1) # denominator is the first entry in the cutflow histogram
eff = HistCutflow.GetBinContent(nbinsCutflow) / denom
effErr = HistCutflow.GetBinError (nbinsCutflow) / denom
ibin = Histogram.FindBin(xval)
Histogram.SetBinContent(ibin, eff)
Histogram.SetBinError (ibin, effErr)
print "Setting bin content for varConst = ", varConst, " = ", constval, " in ibin=", ibin, ", xval=", xval, ", eff=", eff, " +- ", effErr, ", fractional error =", effErr/eff, " numerator = ", HistCutflow.GetBinContent(nbinsCutflow), " denom = ", denom, " from file: ", dataset_file
inputFile.Close()
if varXaxis=="mass":
xAxisLabel = "chargino mass [GeV]"
elif varXaxis=="lifetime":
xAxisLabel = "chargino c#tau [cm]"
else:
print "Unrecognized value of varXaxis=", varXaxis
return
yAxisLabel = "efficiency"
if 'color' in source:
Histogram.SetMarkerColor(colors[source['color']])
Histogram.SetLineColor(colors[source['color']])
else:
Histogram.SetMarkerColor(colors[colorList[colorIndex]])
Histogram.SetLineColor(colors[colorList[colorIndex]])
colorIndex = colorIndex + 1
if colorIndex is len(colorList):
colorIndex = 0
markerStyle = 20
if 'marker' in source:
markerStyle = markers[source['marker']]
if 'fill' in source:
markerStyle = markerStyle + fills[source['fill']]
Histogram.SetMarkerStyle(markerStyle)
Histogram.SetMarkerSize(1)
# Histogram.SetLineWidth(line_width)
Histogram.SetFillStyle(0)
LegendEntries.append(source['legend_entry'])
Histograms.append(Histogram)
# Finish loop over input_sources
# formatting histograms and adding to legend
legendIndex = 0
for histogram in Histograms:
# print "Adding entry to legend: ", LegendEntries[legendIndex]
# Legend.AddEntry(histogram,LegendEntries[legendIndex],"LEP")
Legend.AddEntry(histogram,LegendEntries[legendIndex],"P")
legendIndex = legendIndex+1
# finding the maximum value of anything going on the canvas, so we know how to set the y-axis
finalMax = 0
for histogram in Histograms:
# currentMax = histogram.GetMaximum() + histogram.GetBinError(histogram.GetMaximumBin())
currentMax = histogram.GetMaximum()
if(currentMax > finalMax):
finalMax = currentMax
finalMax = 1.5*finalMax
if finalMax is 0:
finalMax = 1
## if arguments.setYMax:
## finalMax = float(arguments.setYMax)
# Drawing histograms to canvas
makeRatioPlots = arguments.makeRatioPlots
makeDiffPlots = arguments.makeDiffPlots
yAxisMin = 0.0
## if arguments.setYMin:
## yAxisMin = float(arguments.setYMin)
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)
histCounter = 0
plotting_options = "pe, x0" # x0 suppresses the error bar along x
## if arguments.plot_hist:
## plotting_options = "HIST"
for histogram in Histograms:
# histogram.SetTitle(histoTitle)
histogram.Draw(plotting_options)
histogram.GetXaxis().SetTitle(xAxisLabel)
histogram.GetYaxis().SetTitle(yAxisLabel)
if histogram.InheritsFrom("TH1"):
histogram.SetMaximum(finalMax)
histogram.SetMinimum(yAxisMin)
if makeRatioPlots or makeDiffPlots:
histogram.GetXaxis().SetLabelSize(0)
if histCounter is 0:
if histogram.InheritsFrom("TH1"):
plotting_options = plotting_options + " SAME"
elif histogram.InheritsFrom("TGraph"):
plotting_options = "P"
histCounter = histCounter + 1
x_left = 0.15
x_right = 0.55
y_min = 0.6
y_max = 0.8
Legend.SetX1NDC(x_left)
Legend.SetY1NDC(y_min)
Legend.SetX2NDC(x_right)
Legend.SetY2NDC(y_max)
Legend.Draw()
customText = "chargino " + varConst + " " + str(constval)
if varConst == "mass":
customText += " GeV"
elif varConst == "lifetime":
customText += " cm"
customText = customText.replace("lifetime", "c#tau")
CustomLabel = TPaveLabel(x_left, 0.8, x_right, 0.9, customText, "NDC")
CustomLabel.SetBorderSize(0)
CustomLabel.SetFillColor(0)
CustomLabel.SetFillStyle(0)
CustomLabel.Draw()
#drawing the ratio or difference plot if requested
if makeRatioPlots or makeDiffPlots:
Canvas.cd(2)
if makeRatioPlots:
# Comparison = ratioHistogram(Histograms[0],Histograms[1], 1000)
Comparison = Histograms[0].Clone()
Comparison.Divide(Histograms[1])
Comparison.GetYaxis().SetTitle("ratio")
elif makeDiffPlots:
Comparison = Histograms[0].Clone("diff")
Comparison.Add(Histograms[1],-1)
Comparison.SetTitle("")
Comparison.GetYaxis().SetTitle("hist1-hist2")
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(0.7, 1.3)
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")
Comparison.Draw("PE, X0") # X0 suppresses error bar in x direction
outputFile.cd()
Canvas.Write()
if arguments.savePDFs:
Canvas.SaveAs("efficiency_histograms_pdfs/"+histogramName+".pdf")
def plot(MillePedeUser, alignables, mode, struct, parentPlot, config):
logger = logging.getLogger("mpsvalidate")
# skip empty
number = 0
for i in range(3):
if (parentPlot.histo[i].GetEntries() == 0):
number += 1
if (number == 3):
return
# number of bins to start
numberOfBins = 10000
######################################################################
# initialize data hierarchy
# plots[subStrucut]
#
plots = []
# initialize histograms
for subStructNumber, subStruct in enumerate(struct.get_children()):
plots.append(PlotData(mode))
# use a copy for shorter name
plot = plots[subStructNumber]
for i in range(3):
if (mode == "xyz"):
plot.histo.append(
TH1F(
"{0} {1} {2}".format(
struct.get_name() + " " + subStruct.get_name(),
plot.xyz[i], mode),
"Parameter {0}".format(plot.xyz[i]), numberOfBins,
-1000, 1000))
else:
plot.histo.append(
TH1F(
"{0} {1} {2}".format(
struct.get_name() + " " + subStruct.get_name(),
plot.xyz[i], mode),
"Parameter {0}".format(plot.xyz[i]), numberOfBins,
-0.1, 0.1))
plot.histo[i].SetXTitle(plot.unit)
plot.histo[i].SetLineColor(6)
plot.histo[i].SetStats(0)
# add labels
plot.title = TPaveLabel(
0.1, 0.8, 0.9, 0.9,
"Module: {0} {1}".format(struct.get_name(), mode))
plot.text = TPaveText(0.05, 0.1, 0.95, 0.75)
plot.text.SetTextAlign(12)
plot.text.SetTextSizePixels(20)
# save copy
plots[subStructNumber] = plot
######################################################################
# fill histogram
#
for line in MillePedeUser:
# is module ?
if (line.ObjId == 1):
for subStructNumber, subStruct in enumerate(struct.get_children()):
# use a copy for shorter name
plot = plots[subStructNumber]
# module in struct ?
if (subStruct.contains_detid(line.Id)):
for i in range(3):
if (abs(line.Par[plot.data[i]]) != 999999):
# transform xyz data from cm to #mu m
if (mode == "xyz"):
plot.histo[i].Fill(10000 *
line.Par[plot.data[i]])
else:
plot.histo[i].Fill(line.Par[plot.data[i]])
# save copy
plots[subStructNumber] = plot
######################################################################
# find the best range
#
for subStructNumber, subStruct in enumerate(struct.get_children()):
# use a copy for shorter name
plot = plots[subStructNumber]
for i in range(3):
if (plot.histo[i].GetEntries() != 0
and plot.histo[i].GetStdDev() != 0):
# use binShift of the hole structure
binShift = parentPlot.usedRange[i]
# count entries which are not shown anymore
# bin 1 to begin of histogram
for j in range(1, numberOfBins / 2 - binShift):
plot.hiddenEntries[i] += plot.histo[i].GetBinContent(j)
# from the end of shown bins to the end of histogram
for j in range(numberOfBins / 2 + binShift,
plot.histo[i].GetNbinsX()):
plot.hiddenEntries[i] += plot.histo[i].GetBinContent(j)
# merge bins, ca. 100 should be visible in the resulting plot
mergeNumberBins = binShift
# skip empty histogram
if (mergeNumberBins != 0):
# the 2*maxBinShift bins should shrink to 100 bins
mergeNumberBins = int(2. * mergeNumberBins /
config.numberofbins)
# the total number of bins should be dividable by the bins
# shrinked together
if (mergeNumberBins == 0):
mergeNumberBins = 1
while (numberOfBins % mergeNumberBins != 0
and mergeNumberBins != 1):
mergeNumberBins -= 1
# Rebin and save new created histogram and axis
plot.histo[i] = plot.histo[i].Rebin(mergeNumberBins)
# set view range. it is important to note that the number of bins have changed with the rebinning
# the total number and the number of shift must be
# corrected with / mergeNumberBins
plot.histo[i].GetXaxis().SetRange(
int(numberOfBins / (2 * mergeNumberBins) -
binShift / mergeNumberBins),
int(numberOfBins / (2 * mergeNumberBins) +
binShift / mergeNumberBins))
# save copy
plots[subStructNumber] = plot
######################################################################
# make the plots
#
canvas = TCanvas("SubStruct_{0}_{1}".format(struct.get_name(), mode),
"Parameter", 300, 0, 800, 600)
canvas.Divide(2, 2)
canvas.cd(1)
parentPlot.title.Draw()
legend = TLegend(0.05, 0.1, 0.95, 0.75)
for i in range(3):
canvas.cd(i + 2)
# find y maximum
maximum = []
if (parentPlot.histo[i].GetEntries() == 0):
continue
# normalize parent
parentPlot.histo[i].Scale(1. / parentPlot.histo[i].Integral())
maximum.append(parentPlot.histo[i].GetMaximum())
for subStructNumber, subStruct in enumerate(struct.get_children()):
# use a copy for shorter name
plot = plots[subStructNumber]
if (plot.histo[i].GetEntries() > 0):
plot.histo[i].Scale(1. / plot.histo[i].Integral())
maximum.append(plot.histo[i].GetMaximum())
# save copy
plots[subStructNumber] = plot
# set range and plot
parentPlot.histo[i].GetYaxis().SetRangeUser(0., 1.1 * max(maximum))
parentPlot.histo[i].Draw()
for subStructNumber, subStruct in enumerate(struct.get_children()):
# use a copy for shorter name
plot = plots[subStructNumber].histo[i]
plot.SetLineColorAlpha(subStructNumber + 2, 0.5)
plot.Draw("same")
if (i == 0):
legend.AddEntry(plot, subStruct.get_name(), "l")
canvas.cd(1)
legend.Draw()
# draw identification
ident = identification(config)
ident.Draw()
canvas.Update()
# save as pdf
canvas.Print("{0}/plots/pdf/subModules_{1}_{2}.pdf".format(
config.outputPath, mode, struct.get_name()))
# export as png
image = TImage.Create()
image.FromPad(canvas)
image.WriteImage("{0}/plots/png/subModules_{1}_{2}.png".format(
config.outputPath, mode, struct.get_name()))
# add to output list
output = OutputData(plottype="subMod",
name=struct.get_name(),
number=subStructNumber + 1,
parameter=mode,
filename="subModules_{0}_{1}".format(
mode, struct.get_name()))
config.outputList.append(output)
def getAvgHist(infile):
global outRootFile
inputFile = TFile(infile, "READ")
canOrig = inputFile.Get(arguments.canName).Clone()
can = inputFile.Get(arguments.canName).Clone()
if not can:
print "Could not find TCanvas " + can + " in " + inputFile
isFirstHist = True
for obj in can.GetListOfPrimitives():
if arguments.verbose:
print "Reading: ", obj.GetName()
if obj.InheritsFrom("TH1"):
if isFirstHist:
isFirstHist = False
havg = obj.Clone()
hwts = obj.Clone()
havg.SetDirectory(0)
havg.Reset()
hwts.Reset()
# Define average efficiency as weighted arithmetic mean:
# (See http://en.wikipedia.org/wiki/Weighted_arithmetic_mean)
# <eff> = (1/N) * Sum_i (eff_i / sigma_i^2)
# <err> = sqrt(1/N)
# weight_i = 1 / sigma_i^2
# normalization: N = Sum_i (1 / sigma_i^2)
for i in range(1,obj.GetNbinsX()+1):
eff = obj.GetBinContent(i)
err = obj.GetBinError(i)
if arguments.verbose:
print "Debug: bin ", i, ": eff=", eff, ", err=", err
# If error is 0, then reset to be very large value, so that it does not contribute much to the sum
if err == 0:
err = 9.E9
hwts.SetBinContent(i, hwts.GetBinContent(i) + 1.0 / math.pow(err,2))
havg.SetBinContent(i, havg.GetBinContent(i) + eff / math.pow(err,2))
havg.SetBinError (i, havg.GetBinError (i) + err / math.pow(err,2))
if arguments.verbose:
print "Found TH1: ", obj.GetName()
print "yield: ", obj.GetBinContent(2), " +- ", obj.GetBinError(2)
# After looping over all hists, calculate average
for i in range(1,havg.GetNbinsX()+1):
havg.SetBinContent(i, havg.GetBinContent(i) / hwts.GetBinContent(i))
havg.SetBinError (i, math.sqrt( 1.0 / hwts.GetBinContent(i)))
if arguments.verbose:
print "Bin ", i, ": range: (", havg.GetBinLowEdge(i), ", ", havg.GetBinLowEdge(i+1), "): value=", havg.GetBinContent(i), ", error=", havg.GetBinError(i)
outRootFile.cd()
canOrig.SetName(canOrig.GetName() + "_orig")
canOrig.Write()
can.cd()
can.Clear("D")
canNew = TCanvas("canNew", "canNew", can.GetWw(), can.GetWh())
canNew.SetBottomMargin(can.GetBottomMargin())
canNew.SetLeftMargin (can.GetLeftMargin())
havg.SetMaximum(1.1)
if arguments.canName == "totalMcparticleStatus3SusyIdPt":
havg.GetXaxis().SetTitle(havg.GetXaxis().GetTitle().replace("#sum", ""))
if arguments.canName == "stopDecayVxyZoom":
# print "Debug: setting max to 0.8"
havg.SetMaximum(0.8)
havg.GetYaxis().SetTitleOffset(1.4)
havg.GetXaxis().SetTitleOffset(1.4)
havg.GetXaxis().SetNdivisions(509)
havg.Draw("P, E")
#LumiLabel = TPaveLabel(0.7063758,0.8321678,0.9765101,0.9318182,"CMS","NDC")
#LumiLabel = TPaveLabel(0.1641611,0.80,0.4463087,0.90,"CMS","NDC")
LumiLabel = TPaveLabel(0.1858108,0.7904412,0.5084459,0.8897059,"CMS","NDC")
LumiLabel.SetTextFont(62)
LumiLabel.SetTextAlign(12)
LumiLabel.SetBorderSize(0)
LumiLabel.SetFillColor(0)
LumiLabel.SetFillStyle(0)
LumiLabel.Draw()
#HeaderLabel = TPaveLabel(0.03187919, 0.9440559, 0.9110738, 0.9947552,"19.5 fb^{-1} (8 TeV)","NDC") # from makePlots.py
HeaderLabel = TPaveLabel(0.02702703,0.9117647,0.9070946,0.9632353,"19.5 fb^{-1} (8 TeV)","NDC") # from makePlots.py
HeaderLabel.SetTextAlign(32)
HeaderLabel.SetBorderSize(0)
HeaderLabel.SetFillColor(0)
HeaderLabel.SetFillStyle(0)
HeaderLabel.SetTextFont(42);
HeaderLabel.Draw()
outputPdf = arguments.outfile[:arguments.outfile.rfind("/")]
# outputPdf += "/" + canNew.GetName() + ".pdf"
outputPdf += "/" + havg.GetName() + "_avgEff.pdf"
canNew.SaveAs(outputPdf)
canNew.Write()
print "Saving pdf: ", outputPdf
inputFile.Close()
return havg
from ROOT import TArrow, TLine
from ROOT import gROOT, gBenchmark
#gROOT.Reset()
c1 = TCanvas('c1', 'Tree Data Structure', 200, 10, 750, 940)
c1.Range(0, -0.1, 1, 1.15)
gBenchmark.Start('tree')
branchcolor = 26
leafcolor = 30
basketcolor = 42
offsetcolor = 43
#title = TPaveLabel(.3,1.05,.8,1.13,c1.GetTitle())
title = TPaveLabel(.3, 1.05, .8, 1.13, 'Tree Data Structure')
title.SetFillColor(16)
title.Draw()
tree = TPaveText(.01, .75, .15, 1.00)
tree.SetFillColor(18)
tree.SetTextAlign(12)
tnt = tree.AddText('Tree')
tnt.SetTextAlign(22)
tnt.SetTextSize(0.030)
tree.AddText('fScanField')
tree.AddText('fMaxEventLoop')
tree.AddText('fMaxVirtualSize')
tree.AddText('fEntries')
tree.AddText('fDimension')
tree.AddText('fSelectedRows')
tree.Draw()
def showRMSAOH(sector, aoh, gain, wait=True, filename=None):
gStyle.SetOptStat(0)
gStyle.SetCanvasColor(0)
gStyle.SetTitleFillColor(0)
sector.aoh[aoh].biasGraphs = []
sector.aoh[aoh].rmsGraphs = []
sector.aoh[aoh].slopeGraphs = []
if sector.aoh[aoh].group.find('L12') != -1:
sector.ccu.send("channel 0x11").readlines()
elif sector.aoh[aoh].group.find('L3') != -1:
sector.ccu.send("channel 0x13").readlines()
cmd = sector.aoh[aoh].name + " setall %i %i %i %i %i %i %i %i" % (
gain, gain, gain, gain, 0, 0, 0, 0)
sector.ccu.send(cmd).readlines()
#for ch in range(1,5):
# print ch
# sector.aoh[aoh].writegain(ch,gain)
data = sector.aoh[aoh].getBiasRMSCurves()
if filename is None:
filename = getFilename("poh%s_%d.ps" % (sector.name, aoh))
c1 = TCanvas('c1', time.strftime("%Y-%m-%d-%m %H:%M"), 200, 10, 800, 800)
sector.aoh[aoh].pl = TPaveLabel(0.8, 0.9, 0.95, 0.95,
time.strftime("%Y-%m-%d-%m %H:%M"))
sector.aoh[aoh].pl.Draw()
c1.Divide(2, 3)
for ch in range(1, 5):
c1.cd(ch)
title = "POHBias_POH" + str(aoh) + ":" + str(
ch) + " " + sector.name + " fed channel " + str(
sector.aoh[aoh].fedchannels[ch])
f = TH2D('h' + title, title, 2, 0, 80, 2, 0, 1024)
hList.append(f)
f.GetXaxis().SetTitle("poh bias")
#f.GetYaxis().SetTitle("FED ADC")
f.Draw()
color = 1
biasGraph = graph([(t[0], t[1]) for t in data[ch]],
color=1,
name="bias_" + str(aoh) + ":" + str(ch))
rmsGraph = graph([(t[0], t[2] * 10.) for t in data[ch]],
color=2,
name="rms_" + str(aoh) + ":" + str(ch))
slopeGraph = graph([(t[0], t[3] * 10.) for t in data[ch]],
color=3,
name="slope_" + str(aoh) + ":" + str(ch))
sector.aoh[aoh].biasGraphs.append(biasGraph)
sector.aoh[aoh].rmsGraphs.append(rmsGraph)
sector.aoh[aoh].slopeGraphs.append(slopeGraph)
biasGraph.Write()
rmsGraph.Write()
slopeGraph.Write()
c1.Update()
c1.Print(filename)
gCanvases.append(c1)
if wait:
raw_input("hit return to continue")
def makeLimitPlot(output,
obs,
exp,
chan,
printStats=False,
obs2="",
ratioLabel=""):
#fileForHEPData = TFile("plots/"+output+"_forHEPData.root","RECREATE")
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1])
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
print massPoint, limits[massPoint][medianNr]
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
xPointsForErrors = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
xPointsForErrors.append(0)
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
xPointsErrors = numpy.array(xPointsForErrors)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY,
numpy.array(xPointsErrors),
numpy.array(xPointsErrors),
numpy.array(expected2SigLow),
numpy.array(expected2SigHigh))
GraphErr1SigForHEPData = TGraphAsymmErrors(len(expX), expX, expY,
numpy.array(xPointsErrors),
numpy.array(xPointsErrors),
numpy.array(expected1SigLow),
numpy.array(expected1SigHigh))
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kOrange)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen + 1)
#cCL=TCanvas("cCL", "cCL",0,0,567,384)
cCL = TCanvas("cCL", "cCL", 0, 0, 600, 450)
gStyle.SetOptStat(0)
gStyle.SetPadRightMargin(0.063)
gStyle.SetPadLeftMargin(0.14)
gStyle.SetPadBottomMargin(0.12)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
if SPIN2:
signals = ["RS_kMpl01", "RS_kMpl005", "RS_kMpl001"]
elif GUT:
signals = ["ssm", "psi", "kai", "eta", "I", "S", "N"]
else:
signals = ["ssm", "psi"]
xSecCurves = []
for signal in signals:
xSecCurves.append(getXSecCurve(signal, kFacs[signal]))
#xSecCurves.append(getXSecCurve(signal,kFacs[signal],massDependent=True))
#Draw the graphs:
plotPad.SetLogy()
DummyGraph = TH1F("DummyGraph", "", 100, 200, 5500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if SPIN2:
DummyGraph.GetYaxis().SetTitle(
"[#sigma#upoint#font[12]{B}] G_{KK} / [#sigma#upoint#font[12]{B}] Z"
)
else:
DummyGraph.GetYaxis().SetTitle(
"[#sigma#upoint#font[12]{B}] Z' / [#sigma#upoint#font[12]{B}] Z")
# if SPIN2:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowG_{KK}+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
# else:
# if chan=="mumu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#mu^{+}#mu^{-}+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu^{+}#mu^{-}+X)")
# elif chan=="elel":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)")
# elif chan=="elmu":
# DummyGraph.GetYaxis().SetTitle("#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)")
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(200, 5500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(1e-4)
DummyGraph.GetXaxis().SetLabelSize(0.055)
DummyGraph.GetXaxis().SetTitleSize(0.055)
DummyGraph.GetXaxis().SetTitleOffset(1.05)
DummyGraph.GetYaxis().SetLabelSize(0.055)
DummyGraph.GetYaxis().SetTitleSize(0.055)
DummyGraph.GetYaxis().SetTitleOffset(1.3)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
if not EXPONLY:
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
for curve in xSecCurves:
curve.Draw("lsame")
plCMS = TPaveLabel(.16, .81, .27, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.16, .76, .27, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
if "2017" in output or "Combination" in output:
plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
#leg=TLegend(0.540517,0.623051,0.834885,0.878644,"","brNDC") Default
leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC")
if SPIN2:
leg = TLegend(0.5, 0.58, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.0425)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
print ratioLabels
leg.AddEntry(GraphObs, "%s Obs. 95%% CL limit" % ratioLabels[1], "l")
leg.AddEntry(GraphObs2, "%s Obs. 95%% CL limit" % ratioLabels[0], "l")
else:
if not EXPONLY:
leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l")
leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f")
leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f")
leg1 = TLegend(0.7, 0.4, 0.9, 0.55, "", "brNDC")
leg1.SetTextSize(0.05)
if GUT:
leg1 = TLegend(0.6, 0.35, 0.75, 0.623051, "", "brNDC")
if SPIN2:
leg1 = TLegend(0.7, 0.35, 0.9, 0.58, "G_{KK} (LO x 1.6)", "brNDC")
leg1.SetTextSize(0.045)
for index, signal in enumerate(signals):
xSecCurves[index].SetName(labels[signal])
xSecCurves[index].Write(labels[signal])
leg1.AddEntry(xSecCurves[index], labels[signal], "l")
leg1.SetBorderSize(0)
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
leg1.SetLineWidth(0)
leg1.SetLineStyle(0)
leg1.SetFillStyle(0)
leg1.SetLineColor(0)
leg1.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif "2017" in output or "Combination" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"42.4 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .885, .9, .99,
"41.4 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.27, .885, .9, .99,
"77.3 fb^{-1} (13 TeV, ee) + 78.7 fb^{-1} (13 TeV, #mu^{+}#mu^{-})",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.SetTicks(1, 1)
plotPad.RedrawAxis()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(200, 1, 5500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
#GraphErr2SigForHEPData.SetName("graph2Sig")
#GraphErr2SigForHEPData.Write("graph2Sig")
#GraphErr1SigForHEPData.SetName("graph1Sig")
#GraphErr1SigForHEPData.Write("graph1Sig")
#GraphExp.SetName("graphExp")
#GraphExp.Write("graphExp")
#GraphObs.SetName("graphObs")
#GraphObs.Write("graphObs")
#fileForHEPData.Write()
#fileForHEPData.Close()
cCL.Update()
printPlots(cCL, output)
def makeLimitPlot(output, obs, exp, chan, printStats=False):
obsLimits = {}
for obsFile in obs:
if 'width' in obsFile:
width = obsFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
obsLimits[width] = createObsGraph(obsFile)
if SMOOTH:
for width, obsGraph in obsLimits.iteritems():
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = obsGraph
obsLimits[width] = copy.deepcopy(
smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0, 0.005))
obsLimits[width].SetLineWidth(3)
expLimits = {}
for expFile in exp:
if 'width' in expFile:
width = expFile.split('width')[-1].split('_')[0]
else:
width = '0.006'
expLimits[width] = createExpGraph(expFile)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
smoother = TGraphSmooth("normal")
smoother2 = TGraphSmooth("normal")
zprimeX = []
zprimeY = []
fileZPrime = open('tools/xsec_ssm.txt', 'r')
for entries in fileZPrime:
entry = entries.split()
zprimeX.append(float(entry[0]))
zprimeY.append(float(entry[1]) * 1.3 / 1928)
zpX = numpy.array(zprimeX)
zpY = numpy.array(zprimeY)
GraphZPrime = TGraph(481, zpX, zpY)
GraphZPrimeSmooth = smoother2.SmoothSuper(GraphZPrime, "linear")
GraphZPrimeSmooth.SetLineWidth(3)
GraphZPrimeSmooth.SetLineColor(ROOT.kGreen + 3)
GraphZPrimeSmooth.SetLineStyle(2)
zprimePsiX = []
zprimePsiY = []
fileZPrimePsi = open('tools/xsec_psi.txt', 'r')
for entries in fileZPrimePsi:
entry = entries.split()
zprimePsiX.append(float(entry[0]))
zprimePsiY.append(float(entry[1]) * 1.3 / 1928)
zpPsiX = numpy.array(zprimePsiX)
zpPsiY = numpy.array(zprimePsiY)
GraphZPrimePsi = TGraph(481, zpPsiX, zpPsiY)
GraphZPrimePsiSmooth = smoother.SmoothSuper(GraphZPrimePsi, "linear")
GraphZPrimePsiSmooth.SetLineWidth(3)
GraphZPrimePsiSmooth.SetLineColor(ROOT.kBlue)
#Draw the graphs:
plotPad.SetLogy()
if "Moriond" in output:
DummyGraph = TH1F("DummyGraph", "", 100, 200, 5500)
else:
DummyGraph = TH1F("DummyGraph", "", 100, 400, 4500)
DummyGraph.GetXaxis().SetTitle("M [GeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#mu#mu+X) / #sigma(pp#rightarrowZ+X#rightarrow#mu#mu+X)"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrowee+X) / #sigma(pp#rightarrowZ+X#rightarrowee+X)"
)
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"#sigma(pp#rightarrowZ'+X#rightarrow#font[12]{ll}+X) / #sigma(pp#rightarrowZ+X#rightarrow#font[12]{ll}+X)"
)
gStyle.SetOptStat(0)
if "Moriond" in output:
DummyGraph.GetXaxis().SetRangeUser(200, 5500)
else:
DummyGraph.GetXaxis().SetRangeUser(400, 4500)
DummyGraph.SetMinimum(1e-8)
DummyGraph.SetMaximum(4e-4)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
plCMS = TPaveLabel(.12, .81, .22, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.12, .76, .25, .82, "Preliminary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetBorderSize(0)
plPrelim.Draw()
leg = TLegend(0.430517, 0.623051, 0.734885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
colors = {
'01': ROOT.kBlue,
'03': ROOT.kRed,
'05': ROOT.kGreen + 3,
'10': ROOT.kOrange
}
for width in sorted(obsLimits):
obsGraph = obsLimits[width]
if colors.has_key(width):
obsGraph.SetLineColor(colors[width])
obsGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(obsGraph, "Observed 95% CL limit width 0.6%", "l")
else:
leg.AddEntry(obsGraph,
"Observed 95%% CL limit width %d%%" % int(width), "l")
for width in sorted(expLimits):
expGraph = expLimits[width]
if colors.has_key(width):
expGraph.SetLineColor(colors[width])
expGraph.Draw("lsame")
if width == '0.006':
leg.AddEntry(expGraph, "Expected 95% CL limit width 0.6%, median",
"l")
else:
leg.AddEntry(
expGraph,
"Expected 95%% CL limit width %d%%, median" % (int(width)),
"l")
# if not SPIN2:
# GraphZPrimeSmooth.Draw("lsame")
# GraphZPrimePsiSmooth.Draw("lsame")
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
cCL.Update()
printPlots(cCL, output)
# # A function (any dimension) or a formula may reference # an already defined formula # form1 = TFormula( 'form1', 'abs(sin(x)/x)' ) sqroot = TF1( 'sqroot', 'x*gaus(0) + [3]*form1', 0, 10 ) sqroot.SetParameters( 10, 4, 1, 20 ) pad1.SetGridx() pad1.SetGridy() pad1.GetFrame().SetFillColor( 42 ) pad1.GetFrame().SetBorderMode( -1 ) pad1.GetFrame().SetBorderSize( 5 ) sqroot.SetLineColor( 4 ) sqroot.SetLineWidth( 6 ) sqroot.Draw() lfunction = TPaveLabel( 5, 39, 9.8, 46, 'The sqroot function' ) lfunction.SetFillColor( 41 ) lfunction.Draw() c1.Update() # # Create a one dimensional histogram (one float per bin) # and fill it following the distribution in function sqroot. # pad2.cd(); pad2.GetFrame().SetFillColor( 42 ) pad2.GetFrame().SetBorderMode( -1 ) pad2.GetFrame().SetBorderSize( 5 ) h1f = TH1F( 'h1f', 'Test random numbers', 200, 0, 10 ) h1f.SetFillColor( 45 ) h1f.FillRandom( 'sqroot', 10000 )
def makeLimitPlot(output,
obs,
exp,
chan,
interference,
printStats=False,
obs2="",
ratioLabel=""):
fileObs = open(obs, 'r')
fileExp = open(exp, 'r')
observedx = []
observedy = []
obsLimits = {}
xSecs = getFittedXSecCurve("CI_%s" % interference, 1.3)
for entry in fileObs:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in obsLimits: obsLimits[massPoint] = []
obsLimits[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits)
for massPoint in sorted(obsLimits):
observedx.append(massPoint)
observedy.append(numpy.mean(obsLimits[massPoint]))
if (numpy.std(obsLimits[massPoint]) / numpy.mean(obsLimits[massPoint])
> 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits[massPoint]), " std dev: ", numpy.std(
obsLimits[massPoint]), " from: ", obsLimits[massPoint]
if not obs2 == "":
fileObs2 = open(obs2, 'r')
observedx2 = []
observedy2 = []
obsLimits2 = {}
for entry in fileObs2:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in obsLimits2: obsLimits2[massPoint] = []
obsLimits2[massPoint].append(limitEntry)
if printStats: print "len obsLimits:", len(obsLimits2)
for massPoint in sorted(obsLimits2):
observedx2.append(massPoint)
observedy2.append(numpy.mean(obsLimits2[massPoint]))
if (numpy.std(obsLimits2[massPoint]) /
numpy.mean(obsLimits2[massPoint]) > 0.05):
print massPoint, " mean: ", numpy.mean(
obsLimits2[massPoint]), " std dev: ", numpy.std(
obsLimits2[massPoint]
), " from: ", obsLimits2[massPoint]
limits = {}
expectedx = []
expectedy = []
expected1SigLow = []
expected1SigHigh = []
expected2SigLow = []
expected2SigHigh = []
for entry in fileExp:
massPoint = float(entry.split()[0])
limitEntry = float(entry.split()[1]) * xSecs.Eval(
int(float(entry.split()[0])))
if massPoint not in limits: limits[massPoint] = []
limits[massPoint].append(limitEntry)
if printStats: print "len limits:", len(limits)
for massPoint in sorted(limits):
limits[massPoint].sort()
numLimits = len(limits[massPoint])
nrExpts = len(limits[massPoint])
medianNr = int(nrExpts * 0.5)
#get indexes:
upper1Sig = int(nrExpts * (1 - (1 - 0.68) * 0.5))
lower1Sig = int(nrExpts * (1 - 0.68) * 0.5)
upper2Sig = int(nrExpts * (1 - (1 - 0.95) * 0.5))
lower2Sig = int(nrExpts * (1 - 0.95) * 0.5)
if printStats:
print massPoint, ":", limits[massPoint][lower2Sig], limits[
massPoint][lower1Sig], limits[massPoint][medianNr], limits[
massPoint][upper1Sig], limits[massPoint][upper2Sig]
#fill lists:
expectedx.append(massPoint)
print massPoint, limits[massPoint][medianNr]
expectedy.append(limits[massPoint][medianNr])
expected1SigLow.append(limits[massPoint][lower1Sig])
expected1SigHigh.append(limits[massPoint][upper1Sig])
expected2SigLow.append(limits[massPoint][lower2Sig])
expected2SigHigh.append(limits[massPoint][upper2Sig])
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
values2 = []
xPointsForValues2 = []
values = []
xPointsForValues = []
if printStats: print "length of expectedx: ", len(expectedx)
if printStats: print "length of expected1SigLow: ", len(expected1SigLow)
if printStats: print "length of expected1SigHigh: ", len(expected1SigHigh)
#Here is some Voodoo via Sam:
for x in range(0, len(expectedx)):
values2.append(expected2SigLow[x])
xPointsForValues2.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values2.append(expected2SigHigh[x])
xPointsForValues2.append(expectedx[x])
if printStats: print "length of values2: ", len(values2)
for x in range(0, len(expectedx)):
values.append(expected1SigLow[x])
xPointsForValues.append(expectedx[x])
for x in range(len(expectedx) - 1, 0 - 1, -1):
values.append(expected1SigHigh[x])
xPointsForValues.append(expectedx[x])
if printStats: print "length of values: ", len(values)
exp2Sig = numpy.array(values2)
xPoints2 = numpy.array(xPointsForValues2)
exp1Sig = numpy.array(values)
xPoints = numpy.array(xPointsForValues)
if printStats: print "xPoints2: ", xPoints2
if printStats: print "exp2Sig: ", exp2Sig
if printStats: print "xPoints: ", xPoints
if printStats: print "exp1Sig: ", exp1Sig
GraphErr2Sig = TGraphAsymmErrors(len(xPoints), xPoints2, exp2Sig)
GraphErr2Sig.SetFillColor(ROOT.kOrange)
GraphErr1Sig = TGraphAsymmErrors(len(xPoints), xPoints, exp1Sig)
GraphErr1Sig.SetFillColor(ROOT.kGreen + 1)
cCL = TCanvas("cCL", "cCL", 0, 0, 800, 500)
gStyle.SetOptStat(0)
if not obs2 == "":
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0.3, 1, 1)
ratioPad = ROOT.TPad("ratioPad", "ratioPad", 0, 0., 1, 0.3)
plotPad.Draw()
ratioPad.Draw()
plotPad.cd()
else:
plotPad = ROOT.TPad("plotPad", "plotPad", 0, 0, 1, 1)
plotPad.Draw()
plotPad.cd()
expX = numpy.array(expectedx)
expY = numpy.array(expectedy)
GraphExp = TGraph(len(expX), expX, expY)
GraphExp.SetLineWidth(3)
GraphExp.SetLineStyle(2)
GraphExp.SetLineColor(ROOT.kBlue)
obsX = numpy.array(observedx)
obsY = numpy.array(observedy)
if printStats: print "obsX: ", obsX
if printStats: print "obsY: ", obsY
if SMOOTH:
smooth_obs = TGraphSmooth("normal")
GraphObs_nonSmooth = TGraph(len(obsX), obsX, obsY)
GraphObs = smooth_obs.SmoothSuper(GraphObs_nonSmooth, "linear", 0,
0.005)
else:
GraphObs = TGraph(len(obsX), obsX, obsY)
GraphObs.SetLineWidth(3)
if not obs2 == "":
ratio = []
ratiox = []
for index, val in enumerate(observedy):
mass = observedx[index]
foundIndex = -1
for index2, mass2 in enumerate(observedx2):
if mass == mass2:
foundIndex = index2
if foundIndex > 0:
ratio.append(observedy2[foundIndex] / val)
ratiox.append(mass)
ratioA = numpy.array(ratio)
ratioX = numpy.array(ratiox)
obsX2 = numpy.array(observedx2)
obsY2 = numpy.array(observedy2)
ratioGraph = TGraph(len(ratioX), ratioX, ratioA)
if printStats: print "obsX2: ", obsX2
if printStats: print "obsY2: ", obsY2
if SMOOTH:
smooth_obs2 = TGraphSmooth("normal")
GraphObs2_nonSmooth = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2 = smooth_obs2.SmoothSuper(GraphObs2_nonSmooth, "linear",
0, 0.005)
else:
GraphObs2 = TGraph(len(obsX2), obsX2, obsY2)
GraphObs2.SetLineWidth(3)
xSecCurves = []
xSecCurves.append(getFittedXSecCurve("CI_%s" % interference, 1.3))
#Draw the graphs:
plotPad.SetLogy()
DummyGraph = TH1F("DummyGraph", "", 100, 10, 46)
DummyGraph.GetXaxis().SetTitle("#Lambda [TeV]")
if chan == "mumu":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#mu#mu +X) [pb]"
)
elif chan == "elel":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrowee +X) [pb]")
elif chan == "elmu":
DummyGraph.GetYaxis().SetTitle(
"95% CL limit on #sigma(pp#rightarrow CI+X#rightarrow#font[12]{ll}) [pb]"
)
gStyle.SetOptStat(0)
DummyGraph.GetXaxis().SetRangeUser(10, 46)
DummyGraph.SetMinimum(5e-4)
DummyGraph.SetMaximum(1)
DummyGraph.GetXaxis().SetLabelSize(0.04)
DummyGraph.GetXaxis().SetTitleSize(0.045)
DummyGraph.GetXaxis().SetTitleOffset(1.)
DummyGraph.GetYaxis().SetLabelSize(0.04)
DummyGraph.GetYaxis().SetTitleSize(0.045)
DummyGraph.GetYaxis().SetTitleOffset(1.)
DummyGraph.Draw()
if (FULL):
GraphErr2Sig.Draw("F")
GraphErr1Sig.Draw("F")
GraphExp.Draw("lpsame")
else:
if obs2 == "":
GraphExp.Draw("lp")
if not EXPONLY:
GraphObs.Draw("plsame")
if not obs2 == "":
GraphObs2.SetLineColor(ROOT.kRed)
GraphObs2.SetLineStyle(ROOT.kDashed)
GraphObs2.Draw("plsame")
for curve in xSecCurves:
print curve.Eval(28)
#curve.Draw()
curve.Draw("sameR")
plCMS = TPaveLabel(.15, .81, .25, .88, "CMS", "NBNDC")
#plCMS.SetTextSize(0.8)
plCMS.SetTextAlign(12)
plCMS.SetTextFont(62)
plCMS.SetFillColor(0)
plCMS.SetFillStyle(0)
plCMS.SetBorderSize(0)
plCMS.Draw()
plPrelim = TPaveLabel(.15, .76, .275, .82, "Supplementary", "NBNDC")
plPrelim.SetTextSize(0.6)
plPrelim.SetTextAlign(12)
plPrelim.SetTextFont(52)
plPrelim.SetFillColor(0)
plPrelim.SetFillStyle(0)
plPrelim.SetBorderSize(0)
#plPrelim.Draw()
cCL.SetTickx(1)
cCL.SetTicky(1)
cCL.RedrawAxis()
cCL.Update()
#leg=TLegend(0.65,0.65,0.87,0.87,"","brNDC")
leg = TLegend(0.440517, 0.523051, 0.834885, 0.878644, "", "brNDC")
# leg=TLegend(0.55,0.55,0.87,0.87,"","brNDC")
leg.SetTextSize(0.032)
if not obs2 == "":
if ratioLabel == "":
ratioLabel = "Variant/Default"
ratioLabels = ratioLabel.split("/")
print ratioLabels
leg.AddEntry(GraphObs, "%s Observed 95%% CL limit" % ratioLabels[1],
"l")
leg.AddEntry(GraphObs2, "%s Observed 95%% CL limit" % ratioLabels[0],
"l")
else:
if not EXPONLY:
leg.AddEntry(GraphObs, "Obs. 95% CL limit", "l")
leg.AddEntry(GraphExp, "Exp. 95% CL limit, median", "l")
if (FULL):
leg.AddEntry(GraphErr1Sig, "Exp. (68%)", "f")
leg.AddEntry(GraphErr2Sig, "Exp. (95%)", "f")
leg.AddEntry(xSecCurves[0], labels[interference], "l")
leg.SetLineWidth(0)
leg.SetLineStyle(0)
leg.SetFillStyle(0)
leg.SetLineColor(0)
leg.Draw("hist")
if "Moriond" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"36.3 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"35.9 fb^{-1} (13 TeV, ee) + 36.3 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
elif "2017" in output:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"42.1 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"41.5 fb^{-1} (13 TeV, ee)", "NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"41.5 fb^{-1} (13 TeV, ee) + 42.1 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
else:
if (chan == "mumu"):
plLumi = TPaveLabel(.65, .905, .9, .99,
"13.0 fb^{-1} (13 TeV, #mu#mu)", "NBNDC")
elif (chan == "elel"):
plLumi = TPaveLabel(.65, .905, .9, .99, "2.7 fb^{-1} (13 TeV, ee)",
"NBNDC")
elif (chan == "elmu"):
plLumi = TPaveLabel(
.4, .905, .9, .99,
"12.4 fb^{-1} (13 TeV, ee) + 13.0 fb^{-1} (13 TeV, #mu#mu)",
"NBNDC")
plLumi.SetTextSize(0.5)
plLumi.SetTextFont(42)
plLumi.SetFillColor(0)
plLumi.SetBorderSize(0)
plLumi.Draw()
plotPad.RedrawAxis()
if not obs2 == "":
ratioPad.cd()
line = ROOT.TLine(200, 1, 5500, 1)
line.SetLineStyle(ROOT.kDashed)
ROOT.gStyle.SetTitleSize(0.12, "Y")
ROOT.gStyle.SetTitleYOffset(0.35)
ROOT.gStyle.SetNdivisions(000, "Y")
ROOT.gStyle.SetNdivisions(408, "Y")
ratioPad.DrawFrame(200, 0.8, 5500, 1.2, "; ; %s" % ratioLabel)
line.Draw("same")
ratioGraph.Draw("sameP")
cCL.Update()
printPlots(cCL, output)
