def make1dPlot_ratio(dataType, pad_ratio, hists, title_hist):
#
# producing the ratio plot only
#
# this function takes the following parameters:
# dataType....type of the lepton ('mu', 'el')
# pad_ratio...pad carrying the ratio plot
# hists.......list of histograms to be plotted
# title_hist..histogram where we take the axis labels from
pad_ratio.cd()
# create ratio and draw it
data_bg_ratio = copy.deepcopy(hists[0][0])
data_bg_ratio.Divide(copy.deepcopy(hists[1][0].GetStack().Last()))
data_bg_ratio.Draw("p e")
# set standard ratio plot stype
data_bg_ratio = helper.setRatioStyle(dataType, data_bg_ratio, title_hist)
# draw line at 1.0 ratio
line = helper.makeLine(data_bg_ratio.GetXaxis().GetXmin(), 1.00, data_bg_ratio.GetXaxis().GetXmax(), 1.00)
line.Draw()
def make1dPlot(dataType, canv, pad_plot, pad_ratio, outputDir, hists, title_hist, file_name, leg):
#
# a given canvas, which carries a 1d histogram, is plotted (plot + ratio)
#
# this function takes the following parameters:
# dataType....type of the lepton ('mu', 'el')
# canv........canvas to be plotted
# pad_plot....pad to be plotted
# pad_ratio...pad carrying the ratio plot
# outputDir...basic output directory
# hists.......list of histograms to be plotted
# title_hist..histogram where we take the axis labels from
# file_name...filename of the plot to be created
# leg.........legend to be drawn
# create PLOT
make1dPlot_plot(dataType, pad_plot, hists, title_hist, leg)
# create RATIO
#make1dPlot_ratio(dataType, pad_ratio, hists, title_hist)
# calling the function to produce the ratio plot results in a malfunction i do not understand properly
# so we copy the lines from make1dPlot_ratio() while we still keep that function for other purposes
pad_ratio.cd()
data_bg_ratio = copy.deepcopy(hists[0][0])
data_bg_ratio.Divide(copy.deepcopy(hists[1][0].GetStack().Last()))
data_bg_ratio.Draw("p e")
data_bg_ratio = helper.setRatioStyle(dataType, data_bg_ratio, title_hist)
line = helper.makeLine(data_bg_ratio.GetXaxis().GetXmin(), 1.00, data_bg_ratio.GetXaxis().GetXmax(), 1.00)
line.Draw()
# save plot
ROOT.gPad.RedrawAxis()
helper.saveCanvas(canv, pad_plot, outputDir + "plots_1d/", file_name)
def canvasWithRatio(stack, histo, legend):
c1 = ROOT.TCanvas('canvas', 'canvas', 675, 675)
pad_plot = lib.makePad('plot')
pad_ratio = lib.makePad('ratio')
pad_plot.SetTicks(1,1)
pad_ratio.SetTicks(1,1)
stackcp = copy.deepcopy(stack)
stackhisto = copy.deepcopy(stackcp.GetStack().Last())
hlist = stackcp.GetHists()
newstack = ROOT.THStack('st', 'st')
for i in hlist:
i.Scale(1./stackhisto.Integral())
newstack.Add(copy.deepcopy(i))
pad_plot.cd()
stackcp.Draw('hist')
stackcp.GetYaxis().SetLabelSize(0.05)
histoerr = copy.deepcopy(stackhisto)
histoerr.SetFillColor(ROOT.kGray+3)
histoerr.SetLineColor(ROOT.kGray+3)
histoerr.SetFillStyle(3004)
histoerr.Draw('same e2')
#newstack.Draw('hist')
histo.SetMarkerStyle(20)
histo.SetMarkerSize(0.9)
histo.SetMarkerColor(ROOT.kBlack)
histo.SetLineColor(ROOT.kBlack)
histonorm = copy.deepcopy(histo)
#histonorm.Scale(1./histonorm.Integral())
histonorm.Draw('same pe')
stackmax = stackcp.GetMaximum()
histomax = histo.GetMaximum()
stackcp.SetMaximum(1.15* max(stackmax, histomax) )
legend.Draw('same')
pad_ratio.cd()
#stackhisto.Scale(1./stackhisto.Integral())
histocp = copy.deepcopy(histo)
histocp.SetName('ratio')
histocp.SetStats(0)
#histocp.Scale(1./histocp.Integral())
histocp.Divide(stackhisto)
histocp.GetYaxis().SetRangeUser(0.00, 2.0)
histocp.Draw('pe')
histocp.GetYaxis().SetNdivisions(505)
histocp.GetYaxis().SetLabelSize(0.08)
histocp.GetXaxis().SetLabelSize(0.12)
histocp.GetXaxis().SetTitle(histocp.GetName().split('_')[0])
histocp.GetXaxis().SetTitleOffset(1.15)
histocp.GetXaxis().SetTitleSize(0.15)
histocp.SetTitle('')
fl = ROOT.TF1("fl","[0]*x+[1]",0.,1.)
histocp.Fit(fl)
fl.Draw('same')
line = lib.makeLine(histocp.GetXaxis().GetXmin(), 1., histocp.GetXaxis().GetXmax(), 1.)
line.Draw('same')
pad_ratio.Draw()
pad_ratio.Update()
c1.Update()
return c1, stackhisto, histocp, stackcp, newstack, histonorm, line, histoerr
def make1dFRPlot(dataType, canv, pad_plot, pad_ratio, outputDir, hists, title_hist, file_name, usemarkers = False, ratio_title = '', ratio_max = 1.99, ratio_min = 0.0):
#
# produces all 1d fake rate plots (this function, among others, wants to be improved)
# NOTE: when calling this function make sure that the first histogram in hists is the total data, and the second is the total bg (important for ratio)
#
# this function takes the following paramters:
# dataType..........type of the lepton ('mu', 'el')
# canv..............canvas to be plotted
# pad_plot..........pad of the plot to be plotted
# pad_ratio.........pad of the ratio to be plotted
# outputDir.........basic output directory
# hists.............list of histograms to be plotted to be plotted on top of each other
# title_hist........histogram to get the X axis title from
# file_name.........name of the output file
# usemarkers........True if we want to plot both data and mc with markers (e.g. comparing different ewk subtraction methods), False then mc is plotted as a colored rectangle
# ratio_title.......Y axis title of the ratio plot
# ratio_max.........maximum Y range of the ratio plot
# ratio_min.........minimum Y range of the ratio plot
# define pads, draw options (we use markers for mc if
pad_plot.cd()
if usemarkers:
markersize_mc = 1.4
drawoption_data = "p e1"
drawoption_mc = "p e1 same"
legendoption_mc = "pe"
else:
markersize_mc = 0
drawoption_data = "p e1 x0"
drawoption_mc = "e2 same"
legendoption_mc = "f"
# draw histograms
hists[0][0].Draw(drawoption_data)
hists[0][0].SetMarkerSize(1.4)
for i in range(1,len(hists)):
hists[i][0].SetMarkerSize(markersize_mc)
hists[i][0].Draw(drawoption_mc)
hists[0][0].Draw(drawoption_data + " same")
# set plot style
for i in range(len(hists)):
hists[i][0] = helper.setFRPlotStyle(dataType, hists[i][0], helper.getColor(hists[i][1]))
if i+1 == len(hists):
hists[i][0] = helper.setFRPlotStyle(dataType, hists[i][0], helper.getColor(hists[i][1]), 'FR as function of ' + helper.getXTitle(dataType, title_hist), title_hist)
# define legend, fill and draw it
leg1 = helper.makeLegend(0.22, 0.4, 0.47, 0.65)
#if dataType == 'el': leg1 = helper.makeLegend(0.62, 0.08, 0.87, 0.33)
#else : leg1 = helper.makeLegend(0.22, 0.6, 0.47, 0.85)
leg1.AddEntry(hists[0][0], helper.getLegendName(hists[0][1]), 'pe')
for i in range(1,len(hists)):
leg1.AddEntry(hists[i][0], helper.getLegendName(hists[i][1]), legendoption_mc)
leg1.Draw()
# create RATIO PLOT
pad_ratio.cd()
data_bg_ratio = copy.deepcopy(hists[0][0])
data_bg_ratio.Divide(hists[1][0])
data_bg_ratio.Draw("p e")
data_bg_ratio = helper.setRatioStyle(dataType, data_bg_ratio, title_hist, ratio_title, ratio_max, ratio_min)
line = helper.makeLine(data_bg_ratio.GetXaxis().GetXmin(), 1.00, data_bg_ratio.GetXaxis().GetXmax(), 1.00)
line.Draw()
# produce plot
helper.saveCanvas(canv, pad_plot, outputDir + "fakerates_1d/", file_name)
def PlotCompare(dataType, outputDir, mcsets, histname, leg, cutoff = -1, precise = False):
#
# plot a set of histograms defined by histname and comparing mc samples
# NOTE: ALL SAMPLES MUST CONTAIN THE EXACT SAME LIST OF HISTOGRAMS, OTHERWISE THIS FUNCTION WILL NOT WORK
#
# this function takes the following parameters:
# dataType....type of the lepton ('mu', 'el')
# outputDir...basic output directory
# mcsets......list of mc samples [mcsample1, mcsample2, ..]
# leg.........legend to be plotted
# cutoff......cutoff for the histogram name (see function getSaveName() in lib.py)
# precise.....True if only the histogram with the name matching histname exactly shall be plotted
# define canvas and pads
canv = helper.makeCanvas(900, 675)
pad_plot = helper.makePad('plot')
pad_ratio = helper.makePad('ratio')
pad_ratio.cd()
# iterate over all histograms in root files
# it does not matter which sample we iterate on, as all samples contain the same list of histograms
for hist in mcsets[0].hists:
# get index of histogram
i = mcsets[0].hists.index(hist)
pad_plot.cd()
# if precise is True, we only plot the histogram with the name matching histname exactly
# else, we plot all histograms which have histname in their name (useful for several versions or bins of a histogram)
if precise and not histname == hist.GetName(): continue
if not precise and not histname in hist.GetName(): continue
# pre- and postpends
prepend = ''
postpend = '_compare'
if '_Loose_' in hist.GetName(): prepend = 'Loose_'
if '_Tight_' in hist.GetName(): prepend = 'Tight_'
# draw first histogram
hist.Draw('hist')
hist.SetFillStyle(0)
hist.Scale(1.0/hist.Integral())
max = hist.GetMaximum()
for j in range(1,len(mcsets)):
mcsets[j].hists[i].Draw('hist same')
mcsets[j].hists[i].SetFillStyle(0)
mcsets[j].hists[i].SetLineStyle(2)
mcsets[j].hists[i].Scale(1.0/mcsets[j].hists[i].Integral())
if max < mcsets[j].hists[i].GetMaximum(): max = mcsets[j].hists[i].GetMaximum()
# do some cosmetics
hist.SetMinimum(0.0001)
hist.SetMaximum(1.5 * max)
hist = helper.set1dPlotStyle(dataType, hist, helper.getColor(mcsets[0].GetName()), '', hist, '1/Integral')
# draw legend
leg.Draw()
# draw ratio plot
pad_ratio.cd()
hist_ratio = copy.deepcopy(hist)
hist_ratio.Divide(copy.deepcopy(mcsets[1].hists[i]))
hist_ratio.Draw("p e1")
hist_ratio = helper.setRatioStyle(dataType, hist_ratio, hist)
line = helper.makeLine(hist_ratio.GetXaxis().GetXmin(), 1.00, hist_ratio.GetXaxis().GetXmax(), 1.00)
line.Draw()
# make plot
helper.saveCanvas(canv, pad_plot, outputDir + "compare/", prepend + helper.getSaveName(hist, cutoff) + postpend)
def PlotMETZooms(dataType, outputDir, datasets, mcsets, leg, grouping = False):
#
# plotting MET distribution in bins of lepton eta and lepton pt (binning according to fake rate maps)
# NOTE: ALL SAMPLES MUST CONTAIN THE EXACT SAME LIST OF HISTOGRAMS, OTHERWISE THIS FUNCTION WILL NOT WORK
#
# dataType....type of the lepton ('mu', 'el')
# outputDir...basic output directory
# datasets....list of data samples [datasample1, datasample2, ..]
# mcsets......list of mc samples [mcsample1, mcsample2, ..]
# leg.........legend to be plotted
# grouping....True if mc samples should be grouped before stacking (useful in case of e.g. several QCD files)
# define canvas and pads
canv = helper.makeCanvas(900, 675, 'c1dM')
pad_plot = helper.makePad('plot')
pad_ratio = helper.makePad('ratio')
pad_plot.SetTicks(1,1)
pad_ratio.SetTicks(1,1)
# text for eta binning
t_eta = ROOT.TLatex()
t_eta.SetNDC()
t_eta.SetTextSize(0.05)
t_eta.SetTextAlign(11)
t_eta.SetTextColor(ROOT.kBlack)
# text for pt binning
t_pt = ROOT.TLatex()
t_pt.SetNDC()
t_pt.SetTextSize(0.05)
t_pt.SetTextAlign(11)
t_pt.SetTextColor(ROOT.kBlack)
# bins in eta and pt, with total number of bins
bins_eta = [0.0, 0.5, 1.0, 1.5, 2.0, 2.5]
bins_pt = [20.0, 25.0, 30.0, 35.0, 40.0, 45.0, 50.0]
bins_tot = (len(bins_eta)-1)*(len(bins_pt)-1)
# iterate over all histograms in root files
# it does not matter which sample we iterate on, as all samples contain the same list of histograms
for hist in datasets[0].hists:
# get index of the histogram
i = datasets[0].hists.index(hist)
pad_plot.cd()
# only histograms in the parameter histlist are plotted
if not "METZoom" in hist.GetName(): continue
# pre- and postpends
prepend = ''
postpend = ''
if '_Loose_' in hist.GetName(): prepend = 'Loose_'
if '_Tight_' in hist.GetName(): prepend = 'Tight_'
# get the id of the plot, i.e. the last number in the name (e.g. '0' in h_Loose_FRMETZoom_0)
id = hist.GetName().split('_')[-1]
# we stack both data and mc samples (i.e. one may use several data and several mc samples)
data = ROOT.THStack()
mc = ROOT.THStack()
for dataset in datasets:
data.Add(dataset.hists[i])
# if grouping is enabled, we first sum all 'similar' mc samples before adding them to the stack
# similar means, that we sum all samples which have the same name up to a few digits at the end
# in this way, e.g., the samples dyjets50 and dyjets10 are stacked together
# if grouping is not enabled, we just stack all mc samples in one stack
if grouping:
mcgroups = []
mcnames = []
for mcset in mcsets:
label = ''.join([j for j in mcset.GetName() if not j.isdigit()])
foundat = -1
for j, mcname in enumerate(mcnames):
if label == mcname: foundat = j
if foundat == -1:
mcgroups.append(ROOT.THStack())
mcgroups[len(mcgroups)-1].Add(mcset.hists[i])
mcnames.append(label)
else:
mcgroups[foundat].Add(mcset.hists[i])
for j, group in enumerate(mcgroups):
group.Draw('hist')
histogram = group.GetStack().Last()
mc.Add(histogram)
else:
for mcset in mcsets:
mc.Add(mcset.hists[i])
# draw histogram
mc.Draw('hist')
# define the list of histograms which shall be plotted
# i.e. one has to take the histogram of the stack, not the stack itself
hists = []
hists.append([data.GetStack().Last(), 'data' ])
hists.append([mc , 'totbg'])
# plot pad_plot first, then we add the texts and plot ratio afterwards
make1dPlot_plot(dataType, pad_plot, hists, hists[0][0], leg)
# write bin texts
m = int(id)//(len(bins_pt)-1)
n = int(id)%(len(bins_pt)-1)
if dataType == 'el': lepton = 'e'
else : lepton = '#mu'
text_eta = str(bins_eta[m]) + " #leq " + lepton + "-|#eta| < " + str(bins_eta[m+1])
text_pt = str(bins_pt[n]) + " #leq " + lepton + "-p_{T} < " + str(bins_pt[n+1])
t_eta.DrawLatex(0.22, 0.8, text_eta)
t_pt.DrawLatex(0.22, 0.73, text_pt)
# plot ratio
#make1dPlot_ratio(dataType, pad_ratio, hists, hists[0][0])
# calling the function to produce the ratio plot results in a malfunction i do not understand properly
# so we copy the lines from make1dPlot_ratio() while we still keep that function for other purposes
pad_ratio.cd()
data_bg_ratio = copy.deepcopy(hists[0][0])
data_bg_ratio.Divide(copy.deepcopy(hists[1][0].GetStack().Last()))
data_bg_ratio.Draw("p e")
data_bg_ratio = helper.setRatioStyle(dataType, data_bg_ratio, hists[0][0])
line = helper.makeLine(data_bg_ratio.GetXaxis().GetXmin(), 1.00, data_bg_ratio.GetXaxis().GetXmax(), 1.00)
line.Draw()
# save plot
ROOT.gPad.RedrawAxis()
helper.saveCanvas(canv, pad_plot, outputDir + "zoom_met/", prepend + helper.getSaveName(hist, '-2:') + postpend)
