def make2dFRPlot(dataType, canv, outputDir, dataset, hist, title_indeces, name='', exportinroot = False, folder = 'fakerates_2d/', isprompt = False):
#
# produces all 2d fake rate maps
#
# this function takes the following paramters:
# dataType..........type of the lepton ('mu', 'el')
# canv..............canvas to be plotted
# outputDir.........basic output directory
# dataset...........dataset (only to take the title of the X and Y axis from)
# hist..............histogram to be plotted
# title_indeces.....list of two elements which are the indeces of the histograms that carry the X anc Y axis titles in their X axis title
# name..............name of the output file
# exportinroot......True if we want to export the canvas in a root file
# folder............one may change the last outputfolder to something else than fakerates_2d
# isprompt..........temporary solution to plot prompt ratio
# define pad
pad_plot = helper.makePad('tot')
pad_plot.cd()
pad_plot.SetTicks(1,1)
# draw histogram
hist.Draw("text colz e")
# cosmetics
hist.SetMarkerColor(ROOT.kBlack)
hist.SetMarkerSize(1.8)
hist.GetXaxis().SetTitle(helper.getXTitle(dataType, dataset.hists[title_indeces[0]]))
hist.GetYaxis().SetTitle(helper.getXTitle(dataType, dataset.hists[title_indeces[1]]))
hist.GetXaxis().SetTitleSize(0.07)
hist.GetXaxis().SetLabelSize(0.07)
hist.GetYaxis().SetTitleSize(0.07)
hist.GetYaxis().SetLabelSize(0.07)
hist.SetMinimum(0.0)
if dataType == 'el': hist.SetMaximum(0.6)
else : hist.SetMaximum(0.4)
if isprompt == True: prepend = 'PR'
else : prepend = 'FR'
hist.SetTitle(prepend + " 2d Map (" + helper.getLegendName(name) + ")")
# save plot
helper.saveCanvas(canv, pad_plot, outputDir + folder, prepend + "_2dmap_" + name.lower().replace(" ", "_"), False, exportinroot)
pad_plot.Close()
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 make2dPlot(dataType, canv, pad_plot, outputDir, hist, postpend, file_name):
#
# a given canvas, which carries a 2d histogram, is plotted (obviously no ratio plot)
#
# this function takes the following parameters:
# dataType....type of the lepton ('mu', 'el')
# canv........canvas to be plotted
# pad_plot....pad to be plotted
# outputDir...basic output directory
# hist........histogram in the canvas (only important to take the axis labels)
# postpend....postpend to the filename
# file_name...filename of the plot to be created
postpend = "_" + str(postpend.lower())
# draw histogram
hist.Draw('colz')
# ste style thingies
hist.GetXaxis().SetTitle(helper.getXTitle(dataType, hist))
hist.GetYaxis().SetTitle(helper.getYTitle(hist))
hist.GetYaxis().SetTitleSize(0.055)
hist.GetYaxis().SetLabelSize(0.07)
hist.GetYaxis().SetNdivisions(505)
hist.GetXaxis().SetTitleSize(0.07)
hist.GetXaxis().SetLabelSize(0.07)
hist.GetXaxis().SetNdivisions(505)
hist.SetTitle("")
hist.SetMarkerColor(ROOT.kBlack)
hist.SetLineColor(ROOT.kBlack)
# save plot
ROOT.gPad.RedrawAxis()
helper.saveCanvas(canv, pad_plot, outputDir + "plots_2d/", file_name + postpend, False)
# draw histogram
hist.Draw("text colz e")
# cosmetics
hist.SetMarkerColor(ROOT.kBlack)
hist.SetMarkerSize(1.8)
hist.GetXaxis().SetTitle('#mu-pT')
hist.GetYaxis().SetTitle('#mu-|#eta|')
hist.GetXaxis().SetTitleSize(0.07)
hist.GetXaxis().SetLabelSize(0.07)
hist.GetYaxis().SetTitleSize(0.07)
hist.GetYaxis().SetLabelSize(0.07)
hist.SetMinimum(0.0)
hist.SetMaximum(0.4)
hist.SetTitle('')
# save plot
helper.saveCanvas(canv, pad_plot, '', 'UCSx_FR_mu', False, False)
pad_plot.Close()
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 PlotProvenance(dataType, outputDir, mcsets, binstoplot = []):
#
# produce and plot the provenance plot from a list of bins
# 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, ..]
# binstoplot..list of bin numbers (matching origins from Fakerates.cc) we want to plot
# define canvas and pads
canv = helper.makeCanvas(900, 675, 'c1dZ')
pad_plot = helper.makePad('tot')
pad_plot.SetTicks(1,1)
pad_plot.cd()
# define some numbers and lists
nbins = len(binstoplot)
index_loose = 0
index_tight = 0
index_lnt = 0
labels = ['all', 'W', 'B', 'C', 'U/D/S', 'unm.']
hist_plot = []
mcgroups_loose = []
mcgroups_loose_lnt = []
mcgroups_loose_aes = []
mcgroups_tight = []
mcgroups_tight_aes = []
mcnames = []
# 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 the histogram
i = mcsets[0].hists.index(hist)
# only consider plots with 'Provenance' in their names
if not 'Provenance' in hist.GetName(): continue
# h_Loose_Provenance is the denominator after lepton selection only
# h_Loose_ProvenanceLNT is the numerator-subtracted denominator after lepton selection only
# h_Loose_ProvenanceAES is the denominator after event and lepton selection
# h_Tight_Provenance is the numerator after lepton selection only
# h_Tight_ProvenanceAES is the numerator after event and lepton selection
if hist.GetName() == 'h_Loose_Provenance' : index_loose = i
if hist.GetName() == 'h_Loose_ProvenanceLNT': index_loose_lnt = i
if hist.GetName() == 'h_Loose_ProvenanceAES': index_loose_aes = i
if hist.GetName() == 'h_Tight_Provenance' : index_tight = i
if hist.GetName() == 'h_Tight_ProvenanceAES': index_tight_aes = i
# 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 mcset in mcsets:
# strip off the digits from the sample name
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
# we group all provenance plots from samples which have the same label (e.g. dyjets10 and dyjets50)
if foundat == -1:
mcgroups_loose .append(ROOT.THStack())
mcgroups_loose_lnt.append(ROOT.THStack())
mcgroups_loose_aes.append(ROOT.THStack())
mcgroups_tight .append(ROOT.THStack())
mcgroups_tight_aes.append(ROOT.THStack())
mcgroups_loose [len(mcgroups_loose) -1].Add(mcset.hists[index_loose] )
mcgroups_loose_lnt[len(mcgroups_loose_lnt)-1].Add(mcset.hists[index_loose_lnt])
mcgroups_loose_aes[len(mcgroups_loose_aes)-1].Add(mcset.hists[index_loose_aes])
mcgroups_tight [len(mcgroups_tight) -1].Add(mcset.hists[index_tight] )
mcgroups_tight_aes[len(mcgroups_tight_aes)-1].Add(mcset.hists[index_tight_aes])
mcnames.append(label)
else:
mcgroups_loose [foundat].Add(mcset.hists[index_loose] )
mcgroups_loose_lnt[foundat].Add(mcset.hists[index_loose_lnt])
mcgroups_loose_aes[foundat].Add(mcset.hists[index_loose_aes])
mcgroups_tight [foundat].Add(mcset.hists[index_tight] )
mcgroups_tight_aes[foundat].Add(mcset.hists[index_tight_aes])
# fake rate provenance are created with and without event selection
hist_den = [{} for j in range(len(mcnames))]
hist_den_aes = [{} for j in range(len(mcnames))]
hist_num = [{} for j in range(len(mcnames))]
hist_num_aes = [{} for j in range(len(mcnames))]
# create the histograms for each provenance plot (loose, lnt, loose_aes, tight, tight_aes)
for i, plotgroup in enumerate([mcgroups_loose, mcgroups_loose_lnt, mcgroups_loose_aes, mcgroups_tight, mcgroups_tight_aes]):
hist_plot.append([])
for j, group in enumerate(plotgroup):
group.Draw('hist')
histogram = group.GetStack().Last()
if nbins == 0: nbins = histogram.GetNbinsX()
if histogram.GetName() == 'h_Loose_Provenance' : postpend = 'loose'
if histogram.GetName() == 'h_Loose_ProvenanceLNT': postpend = 'loose_lnt'
if histogram.GetName() == 'h_Loose_ProvenanceAES': postpend = 'loose_aes'
if histogram.GetName() == 'h_Tight_Provenance' : postpend = 'tight'
if histogram.GetName() == 'h_Tight_ProvenanceAES': postpend = 'tight_aes'
# we create as many histograms as we want to plot origins and we store them all in hist_plot
hist_plot[i].append(ROOT.TH1F(histogram.GetName() + '_plot' + str(j), histogram.GetName(), nbins, 0, nbins))
# each of these histograms we fill in such a way that only one bin is non-zero
n = 1
for k in range(1, histogram.GetNbinsX()+1):
if binstoplot == [] or k in binstoplot:
hist_plot[i][j].SetBinContent(n, histogram.GetBinContent(k))
n +=1
# copy numerators and denominators for subsequent fake rate production
if hist_plot[i][j].GetName() == 'h_Loose_Provenance_plot' + str(j) : hist_den[j] = copy.deepcopy(hist_plot[i][j])
if hist_plot[i][j].GetName() == 'h_Loose_ProvenanceAES_plot' + str(j): hist_den_aes[j] = copy.deepcopy(hist_plot[i][j])
if hist_plot[i][j].GetName() == 'h_Tight_Provenance_plot' + str(j) : hist_num[j] = copy.deepcopy(hist_plot[i][j])
if hist_plot[i][j].GetName() == 'h_Tight_ProvenanceAES_plot' + str(j): hist_num_aes[j] = copy.deepcopy(hist_plot[i][j])
# produce nice lits of histograms and plot them
hist_plots = makeProvenancePlots(hist_plot[i][j], labels, binstoplot)
hist_plots[0].Draw('hist text')
for k in range(1,len(hist_plots)): hist_plots[k].Draw('hist text same')
helper.saveCanvas(canv, pad_plot, outputDir + "closure/", mcnames[j] + '_' + postpend)
# we create the fake rate provenances with and without event selection
for j in range(len(mcnames)):
hist_num[j].Divide(hist_num[j], hist_den[j], 1, 1, 'B')
hist_nums = makeProvenancePlots(hist_num[j], labels, binstoplot, False)
hist_nums[0].Draw('hist text')
for k in range(1, len(hist_nums)): hist_nums[k].Draw('hist text same')
helper.saveCanvas(canv, pad_plot, outputDir + "closure/", mcnames[j] + '_rate')
hist_num_aes[j].Divide(hist_num_aes[j], hist_den_aes[j], 1, 1, 'B')
hist_nums = makeProvenancePlots(hist_num_aes[j], labels, binstoplot, False)
hist_nums[0].Draw('hist text')
for k in range(1, len(hist_nums)): hist_nums[k].Draw('hist text same')
helper.saveCanvas(canv, pad_plot, outputDir + "closure/", mcnames[j] + '_rate_aes')
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 PlotJPtZooms(dataType, outputDir, dataset, mcsets, leg):
#
# plotting JetPt and JetRawPt distributions 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
#
# this function takes the following parameters:
# 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
# define canvas and pads
canv = helper.makeCanvas(900, 675, 'c1dZ')
pad_plot = helper.makePad('tot')
pad_plot.SetTicks(1,1)
pad_plot.cd()
# 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, 1.0, 2.4]
#bins_pt = [10.0, 20.0, 30.0, 35.0, 37.5, 40.0, 42.5, 45.0, 47.5, 50.0, 55.0, 60.0, 70.0] # old
bins_pt = [10.0, 20.0, 22.5, 25.0, 27.5, 30.0, 32.5, 35.0, 40.0, 50.0, 60.0, 70.0] # new
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 dataset.hists:
# get index of the histogram
i = dataset.hists.index(hist)
# only histograms in the parameter histlist are plotted
if not "JPtZoom" 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_DJPtZoomC_0)
id = hist.GetName().split('_')[-1]
# draw data
hist.Scale(1.0/hist.Integral())
hist.SetFillStyle(0)
hist.SetLineStyle(2)
hist.Draw("HIST")
max = hist.GetMaximum()
# draw mc samples
for mc in mcsets:
mc.hists[i].Scale(1.0/mc.hists[i].Integral())
mc.hists[i].SetFillStyle(0)
mc.hists[i].Draw("HIST SAME")
if mc.hists[i].GetMaximum()>max: max = mc.hists[i].GetMaximum()
# do some cosmetics
hist.SetMaximum(1.5*max)
hist.GetXaxis().SetTitle(helper.getXTitle(dataType, hist))
hist.GetYaxis().SetTitle("1/Integral")
hist.SetTitle("")
hist.GetXaxis().SetTitleSize(0.07)
hist.GetXaxis().SetLabelSize(0.07)
hist.GetYaxis().SetTitleSize(0.07)
hist.GetYaxis().SetLabelSize(0.07)
hist.GetXaxis().SetNdivisions(505)
hist.GetYaxis().SetNdivisions(505)
# draw legend
leg.Draw()
# write bin texts
m = int(id)//(len(bins_pt)-1)
n = int(id)%(len(bins_pt)-1)
if "ZoomC" in hist.GetName(): write = "corr."
else: write = "raw"
text_eta = str(bins_eta[m]) + " #leq jet-|#eta| < " + str(bins_eta[m+1])
text_pt = str(bins_pt[n]) + " #leq jet-p_{T} (" + write + ") < " + str(bins_pt[n+1])
t_eta.DrawLatex(0.22, 0.8, text_eta)
t_pt.DrawLatex(0.22, 0.73, text_pt)
# draw plots
helper.saveCanvas(canv, pad_plot, outputDir + "zoom_jpt/", prepend + helper.getSaveName(hist, '-2:') + postpend, False)
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)
