def make1dPlot_plot(dataType, pad_plot, hists, title_hist, leg):
#
# producing the plot without ratio plot
#
# this function takes the following parameters:
# dataType....type of the lepton ('mu', 'el')
# pad_plot....pad to be plotted
# hists.......list of histograms to be plotted
# title_hist..histogram where we take the axis labels from
# leg.........legend to be drawn
pad_plot.cd()
# get maximum
max = hists[0][0].GetMaximum()
for i in range(1,len(hists)):
if max < hists[i][0].GetStack().Last().GetMaximum():
max = hists[i][0].GetStack().Last().GetMaximum()
# set standard plot stype
hists[0][0] = helper.set1dPlotStyle(dataType, hists[0][0], helper.getColor(hists[0][1]), '', title_hist)
# draw and set maximum
hists[0][0].Draw("p x0 e")
hists[0][0].SetMinimum(0.001)
hists[0][0].SetMaximum(1.5*max)
for i in range(1,len(hists)):
hists[i][0].Draw("hist same")
hists[i][0].SetMinimum(0.001)
hists[i][0].SetMaximum(1.5*max)
hists[0][0].Draw("p x0 e same")
# draw legend
leg.Draw()
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)
