import ROOT as r
import json
import numpy as np
import copy
import os
import sys
import Dumbledraw.styles as styles
r.gROOT.SetBatch()
r.gStyle.SetOptStat(0)
styles.ModTDRStyle()
r.gStyle.SetTitleSize(0.045, 'XYZ')
era = sys.argv[1]
outfoldername = sys.argv[2]
f = r.TFile.Open("shapes_mm_recoil_%s.root" % era)
if not os.path.exists(outfoldername):
os.mkdir(outfoldername)
fout = r.TFile.Open("%s/Type1_PFMET_%s.root" % (outfoldername, era),
"recreate")
foutpuppi = r.TFile.Open("%s/Type1_PuppiMET_%s.root" % (outfoldername, era),
"recreate")
r.gROOT.SetBatch()
hist_names = sorted([
k.GetName() for k in f.GetListOfKeys()
if "_ss" not in k.GetName() and "output_tree" not in k.GetName()
def main(args):
styles.ModTDRStyle(l=0.14, b=0.12)
# Read in input root file.
if not os.path.exists(args.input):
print("Input file {} does not exist.".format(args.input))
raise ValueError
infile = ROOT.TFile(args.input, "read")
# Load the fit results
if args.separate_nominal_fit is None:
fit_nominal = infile.Get("fit_nominal")
else:
if not os.path.exists(args.separate_nominal_fit):
print("Input file {} for separate fit does not exist.".format(args.input))
raise ValueError
infile_separate = ROOT.TFile(args.separate_nominal_fit, "read")
fit_nominal = infile_separate.Get("fit_nominal")
fit_alternate = infile.Get("fit_alternate")
# Get POI result RooFit object
res_poi = fit_nominal.floatParsFinal().find(args.poi)
# Get number of channels from fit result
prefix = "_ChannelCompatibilityCheck_{}_".format(args.poi)
parameters = fit_alternate.floatParsFinal()
num_pars = parameters.getSize()
channels = [parameters.at(x).GetName() for x in range(num_pars) if parameters.at(x).GetName().startswith(prefix)]
num_chans = len(channels)
print(channels)
if '_pt_' in channels[1]:
styles.ModTDRStyle(l=0.22, b=0.12)
canv = ROOT.TCanvas("canv")
# Create the plot object.
axis_label = "#sigma#font[42]{{({}#phi)}}#font[52]{{B}}#font[42]{{(#phi#rightarrow#tau#tau)}} (pb)".format("gg" if "gg" in args.poi else "bb")
frame = ROOT.TH2F("frame",
";{};".format(axis_label),
1,
# res_poi.getVal() + 5*res_poi.getAsymErrorLo(),
args.frame_range[0],
args.frame_range[1],
num_chans,
0,
num_chans
)
print("Nominal fit: {} {}/+{}".format(res_poi.getVal(), res_poi.getAsymErrorLo(), res_poi.getAsymErrorHi()))
# Fill TGraphAsymmErrors with fit values.
points = ROOT.TGraphAsymmErrors(num_chans)
if "htt" in channels[0]:
chan_it = sorted(channels)
else:
chan_it = reversed(sorted(channels))
if '_pt_' in channels[1]:
channels_sorted = range(5)
for c in channels:
if 'btag' in c: channels_sorted[4] = c
if '0to50' in c: channels_sorted[3] = c
if '50to100' in c: channels_sorted[2] = c
if '100to200' in c: channels_sorted[1] = c
if 'GT200' in c: channels_sorted[0] = c
chan_it = channels_sorted
for i, ch_ in enumerate(chan_it):
ri = parameters.find(ch_)
points.SetPoint(i, ri.getVal(), i+0.5)
points.SetPointError(i, -ri.getAsymErrorLo(), ri.getAsymErrorHi(), 0, 0)
print("Alternate fit: ", ch_, ri.getVal())
frame.GetYaxis().SetBinLabel(i+1, label_dict[ch_.replace(prefix, "")])
if "htt" not in channels[0] and '_pt_' not in channels[1]:
frame.GetYaxis().SetRangeUser(0, num_chans+0.5)
points.SetLineColor(ROOT.kBlack)
points.SetLineWidth(3)
points.SetMarkerStyle(20)
points.SetMarkerSize(1.3)
# frame.GetXaxis().SetNdivisions(505)
frame.GetXaxis().SetTitleSize(0.05)
frame.GetXaxis().SetLabelSize(0.04)
if '_pt_' in channels[1]:
frame.GetYaxis().SetLabelSize(0.04)
else: frame.GetYaxis().SetLabelSize(0.06)
frame.Draw()
# ROOT.gStyle.SetOptStat(0)
globalFitBand = ROOT.TBox(res_poi.getVal()+res_poi.getAsymErrorLo(), 0, res_poi.getVal()+res_poi.getAsymErrorHi(), num_chans)
globalFitBand.SetFillStyle(1001)
# globalFitBand.SetFillColor(17)
# globalFitBand.SetFillColor(ROOT.TColor.GetColor("#034732"))
globalFitBand.SetFillColor(ROOT.TColor.GetColor("#73a3d4"))
globalFitBand.SetLineStyle(0)
globalFitBand.SetLineColor(ROOT.TColor.GetColor("#73a3d4"))
globalFitBand.Draw("same")
globalFitLine = ROOT.TLine(res_poi.getVal(), 0, res_poi.getVal(), num_chans)
globalFitLine.SetLineWidth(3)
# globalFitLine.SetLineColor(12)
globalFitLine.SetLineColor(ROOT.TColor.GetColor("#1d3d5e"))
globalFitLine.Draw("same")
points.Draw("0PZ SAME")
ROOT.gPad.SetTickx()
ROOT.gPad.SetTicky()
ROOT.gPad.RedrawAxis()
if "htt" not in channels[0] and '_pt_' not in channels[1]:
# l = 0.14, r = 0.04
legend = ROOT.TLegend(0.25, 0.80, 0.85, 0.88)
elif '_pt_' in channels[1]:
legend = ROOT.TLegend(0.24, 0.77, 0.46, 0.92)
legend.SetFillStyle(0)
else:
if args.legend_position == 0:
legend = ROOT.TLegend(0.18, 0.77, 0.48, 0.92)
elif args.legend_position == 1:
legend = ROOT.TLegend(0.65, 0.77, 0.95, 0.92)
elif args.legend_position == 2:
legend = ROOT.TLegend(0.65, 0.13, 0.95, 0.28)
else:
legend = ROOT.TLegend(0.18, 0.13, 0.48, 0.28)
legend.AddEntry(globalFitLine, "Global Best Fit", "l")
legend.AddEntry(globalFitBand, "Global Best Fit #pm 1 #sigma", "f")
legend.SetTextSize(0.032)
if "htt" not in channels[0] and '_pt_' not in channels[1]:
legend.SetNColumns(2)
legend.Draw()
extra_ts = 0.030
limit_tree = infile.Get("limit")
limit_tree.GetEntry(0)
latex2 = ROOT.TLatex()
latex2.SetNDC()
latex2.SetTextAngle(0)
latex2.SetTextColor(ROOT.kBlack)
latex2.SetTextSize(extra_ts)
begin_left = 0.200
begin_right = 0.68
up_pos = 0.690
spacing = 0.04
low_pos = 0.470
# latex2.DrawLatex(begin_left, 0.360, "#chi^{{2}}-like = {:.3f}".format(limit_tree.limit))
# latex2.DrawLatex(begin_left, 0.640, "#chi^{{2}}-like = {:.3f}".format(limit_tree.limit))
# test_stat = "-2 ln #frac{L(n|#hat{#mu})}{L(n|{#hat{#mu}_{k}})}"
# if args.legend_position == 0:
# latex2.DrawLatex(begin_left, up_pos-spacing, "{} = {:.2f}".format(test_stat, limit_tree.limit))
# elif args.legend_position == 1:
# latex2.DrawLatex(begin_right, up_pos-spacing, "{} = {:.2f}".format(test_stat, limit_tree.limit))
# elif args.legend_position == 2:
# latex2.DrawLatex(begin_right, low_pos-spacing, "{} = {:.2f}".format(test_stat, limit_tree.limit))
# else:
# latex2.DrawLatex(begin_left, low_pos-spacing, "{} = {:.2f}".format(test_stat, limit_tree.limit))
# Draw mass of Higgs boson outside of frame
if args.mass is not None:
mass_label = "#font[42]{m_{#phi} = %s GeV}" % args.mass
if '_pt_' in channels[1]:
latex2.DrawLatex(0.26, up_pos, mass_label)
elif args.legend_position == 0:
latex2.DrawLatex(begin_left, up_pos, mass_label)
elif args.legend_position == 1:
latex2.DrawLatex(begin_right, up_pos, mass_label)
elif args.legend_position == 2:
latex2.DrawLatex(begin_right, low_pos, mass_label)
elif args.legend_position == 3:
latex2.DrawLatex(begin_left, low_pos, mass_label)
if args.toy_json is not None:
if args.mass is None:
raise ValueError("Mass needs to be given for readout of json")
with open(args.toy_json, "r") as fi:
res = json.load(fi)["{}.0".format(args.mass)]
label = "#font[42]{{p-value = {:.2f}}}".format(res["p"])
if '_pt_' in channels[1]:
latex2.DrawLatex(0.26, up_pos-1*spacing, label)
elif args.legend_position == 0:
latex2.DrawLatex(begin_left, up_pos-1*spacing, label)
elif args.legend_position == 1:
latex2.DrawLatex(begin_right, up_pos-1*spacing, label)
elif args.legend_position == 2:
latex2.DrawLatex(begin_right, low_pos-1*spacing, label)
elif args.legend_position == 3:
latex2.DrawLatex(begin_left, low_pos-1*spacing, label)
# Draw CMS logo in upper left corner
cms_outside = True
if cms_outside:
styles.DrawCMSLogo(canv, 'CMS', 'Supplementary', 0,
0.095, 0.05, 1.0, '', 0.6)
else:
styles.DrawCMSLogo(canv, 'CMS', 'Supplementary', 11,
0.045, 0.05, 1.0, '', 0.6)
# Draw luminosity label
styles.DrawTitle(canv, "138 fb^{-1} (13 TeV)", 3, 0.6)
canv.Print(args.output + ".png", "png")
canv.Print(args.output + ".pdf", "pdf")
return