for h in hists:
ratio_hists.append(plot.MakeRatioHist(h, hists[0], False, False))
for tgt in targets:
ratio_hists[tgt[0]].Draw('HISTSAME')
plot.SetupTwoPadSplitAsRatio(
pads, plot.GetAxisHist(
pads[0]), plot.GetAxisHist(pads[1]), 'Ratio to SM', True, 0.0, 5.0)
# Go back and tidy up the axes and frame
pads[0].cd()
pads[0].GetFrame().Draw()
pads[0].RedrawAxis()
# CMS logo
plot.DrawCMSLogo(pads[0], 'Les Houches', '2019', 11, 0.045, 0.05, 1.0, '', 1.0)
plot.DrawTitle(pads[0], 'pp #rightarrow H / Hj', 1)
plot.DrawTitle(pads[0], 'SMEFT', 3)
canv.Print('.png')
canv.Print('.pdf')
for ib in xrange(1, h_nominal.GetNbinsX() + 1):
line = 'xsec / SM for bin %i [%g, %g] = 1.0' % (ib, h_nominal.GetXaxis().GetBinLowEdge(ib), h_nominal.GetXaxis().GetBinUpEdge(ib))
for tgt in targets:
x_tot = hists[tgt[0]].GetBinContent(ib)
x_sm = h_nominal.GetBinContent(ib)
ci = tgt[2]
x_int = (x_tot - x_sm) / ci
x_int = x_int / x_sm
pads[1].SetGrid(0, 1)
h_axes[1].Draw()
r_data = plot.MakeRatioHist(h_data, h_tot, True, False)
r_tot = plot.MakeRatioHist(h_tot, h_tot, True, False)
r_tot.Draw('E2SAME')
r_data.Draw('SAME')
plot.SetupTwoPadSplitAsRatio(pads, plot.GetAxisHist(pads[0]),
plot.GetAxisHist(pads[1]), 'Obs/Exp', True, 0.61,
1.39)
# Go back and tidy up the axes and frame
pads[0].cd()
pads[0].GetFrame().Draw()
pads[0].RedrawAxis()
# CMS logo
plot.DrawCMSLogo(pads[0], 'CMS', 'Preliminary', 11, 0.045, 0.05, 1.0, '', 1.0)
plot.DrawTitle(pads[0], '%.1f pb^{-1} (13 TeV)' % intLumiData, 3)
# latex = ROOT.TLatex()
# plot.Set(latex, NDC=None, TextFont=42, TextSize=0.08)
# latex.DrawLatex(0.67, 0.57, CHANNELS[args.channel])
plot.DrawTitle(pads[0], CHANNELS[args.channel], 1)
# ... and we're done
canv.Print('.png')
canv.Print('.pdf')
canv.Print('.root')
else:
lo = math.sqrt(v_lo[i] * v_lo[i] - v_lo[i + 1] * v_lo[i + 1])
else:
hi = v_hi[i]
lo = v_lo[i]
textfit += '{}^{#plus %.3f}_{#minus %.3f}(%s)' % (hi, abs(lo), br)
pt.AddText(textfit)
pt.SetTextAlign(11)
pt.SetTextFont(42)
pt.Draw()
plot.DrawCMSLogo(pads[0],
args.logo,
args.logo_sub,
11,
0.045,
0.035,
1.2,
cmsTextSize=1.)
legend_l = 0.69
if len(other_scans) > 0:
legend_l = legend_l - len(other_scans) * 0.04
legend = ROOT.TLegend(0.15, legend_l, 0.45, 0.78, '', 'NBNDC')
if len(other_scans) >= 3:
legend = ROOT.TLegend(0.46, 0.83, 0.95, 0.93, '', 'NBNDC')
legend.SetNColumns(2)
legend.AddEntry(main_scan['func'], args.main_label, 'L')
for i, other in enumerate(other_scans):
legend.AddEntry(other['func'], other_scans_opts[i][1], 'L')
ratio_graphs = []
pads[0].cd()
if legend.GetNRows() == 1:
legend.SetY1(legend.GetY2() - 0.5 *
(legend.GetY2() - legend.GetY1()))
legend.Draw()
box = ROOT.TPave(pads[0].GetLeftMargin(), 0.81,
1 - pads[0].GetRightMargin(),
1 - pads[0].GetTopMargin(), 1, 'NDC')
box.Draw()
legend.Draw()
plot.DrawCMSLogo(pads[0], 'CMS', args.cms_sub, 11, 0.045, 0.035, 1.2,
'', 0.8)
plot.DrawTitle(pads[0], args.title_right, 3)
plot.DrawTitle(pads[0], title, 1)
textlabel = ROOT.TPaveText(0.68, 0.88, 0.80, 0.92, "NDC")
textlabel.SetBorderSize(0)
textlabel.SetFillStyle(0)
textlabel.SetTextAlign(32)
textlabel.SetTextSize(0.04)
textlabel.SetTextColor(1)
textlabel.SetTextFont(62)
textlabel.AddText(args.statistic + ", %s Toys" % (toy_graph.GetN()))
textlabel.Draw()
pvalue = ROOT.TPaveText(0.68, 0.83, 0.80, 0.87, "NDC")
pvalue.SetBorderSize(0)
def main():
parser = argparse.ArgumentParser()
parser.add_argument('main', help='Main input file for the scan')
parser.add_argument('--y-cut',
type=float,
default=7.,
help='Remove points with y > y-cut')
parser.add_argument('--y-max',
type=float,
default=8.,
help='y-axis maximum')
parser.add_argument('--output',
'-o',
help='output name without file extension',
default='scan')
parser.add_argument('--POI',
help='use this parameter of interest',
default='r')
parser.add_argument('--translate',
default=None,
help='json file with POI name translation')
parser.add_argument('--main-label',
default='Observed',
type=str,
help='legend label for the main scan')
parser.add_argument('--main-color',
default=1,
type=int,
help='line and marker color for main scan')
parser.add_argument(
'--others',
nargs='*',
help='add secondary scans processed as main: FILE:LABEL:COLOR')
parser.add_argument('--breakdown',
help='do quadratic error subtraction using --others')
parser.add_argument('--logo', default='CMS')
parser.add_argument('--logo-sub', default='Internal')
args = parser.parse_args()
# print '--------------------------------------'
# print args.output
# print '--------------------------------------'
fixed_name = args.POI
xaxis_name = fixed_name
label_name = fixed_name
unit = ""
if args.translate is not None:
with open(args.translate) as jsonfile:
name_translate = json.load(jsonfile)
if args.POI in name_translate:
fixed_name = name_translate[args.POI]
# yvals = [1., 3.84]
yvals = [1., 4.0]
scalePOI = 9.2
xaxis_name = "#sigma [fb]"
label_name = "#sigma"
unit = "fb"
main_scan = BuildScan(args.output, "{0}*{1}".format(scalePOI, args.POI),
[args.main], args.main_color, yvals, args.y_cut)
other_scans = []
other_scans_opts = []
if args.others is not None:
for oargs in args.others:
splitargs = oargs.split(':')
other_scans_opts.append(splitargs)
other_scans.append(
BuildScan(args.output, args.POI, [splitargs[0]],
int(splitargs[2]), yvals, args.y_cut))
canv = ROOT.TCanvas(args.output, args.output)
pads = plot.OnePad()
main_scan['graph'].SetMarkerColor(1)
main_scan['graph'].Draw('AP')
axishist = plot.GetAxisHist(pads[0])
axishist.SetMaximum(args.y_max)
axishist.GetYaxis().SetTitle("- 2 #Delta ln L")
axishist.GetXaxis().SetTitle("%s" % xaxis_name)
new_min = axishist.GetXaxis().GetXmin()
new_max = axishist.GetXaxis().GetXmax()
mins = []
maxs = []
for other in other_scans:
mins.append(other['graph'].GetX()[0])
maxs.append(other['graph'].GetX()[other['graph'].GetN() - 1])
if len(other_scans) > 0:
if min(mins) < main_scan['graph'].GetX()[0]:
new_min = min(mins) - (main_scan['graph'].GetX()[0] - new_min)
if max(maxs) > main_scan['graph'].GetX()[main_scan['graph'].GetN() -
1]:
new_max = max(maxs) + (
new_max -
main_scan['graph'].GetX()[main_scan['graph'].GetN() - 1])
axishist.GetXaxis().SetLimits(new_min, new_max)
for other in other_scans:
if args.breakdown is not None:
other['graph'].SetMarkerSize(0.4)
other['graph'].Draw('PSAME')
line = ROOT.TLine()
line.SetLineColor(16)
# line.SetLineStyle(7)
for yval in yvals:
plot.DrawHorizontalLine(pads[0], line, yval)
if (len(other_scans) == 0):
for cr in main_scan['crossings'][yval]:
if cr['valid_lo']: line.DrawLine(cr['lo'], 0, cr['lo'], yval)
if cr['valid_hi']: line.DrawLine(cr['hi'], 0, cr['hi'], yval)
main_scan['func'].Draw('same')
for other in other_scans:
if args.breakdown is not None:
other['func'].SetLineStyle(2)
other['func'].SetLineWidth(2)
other['func'].Draw('SAME')
box = ROOT.TBox(axishist.GetXaxis().GetXmin(), 0.625 * args.y_max,
axishist.GetXaxis().GetXmax(), args.y_max)
box.Draw()
pads[0].GetFrame().Draw()
pads[0].RedrawAxis()
crossings = main_scan['crossings']
val_nom = main_scan['val']
val_2sig = main_scan['val_2sig']
textfit = '%s = %.1f{}^{#plus %.1f}_{#minus %.1f} %s' % (
label_name, val_nom[0], val_nom[1], abs(val_nom[2]), unit)
pt = ROOT.TPaveText(0.59, 0.82 - len(other_scans) * 0.08, 0.95, 0.91,
'NDCNB')
pt.AddText(textfit)
if args.breakdown is None:
for i, other in enumerate(other_scans):
textfit = '#color[%s]{%s = %.3f{}^{#plus %.3f}_{#minus %.3f}}' % (
other_scans_opts[i][2], fixed_name, other['val'][0],
other['val'][1], abs(other['val'][2]))
pt.AddText(textfit)
if args.breakdown is not None:
pt.SetX1(0.50)
if len(other_scans) >= 3:
pt.SetX1(0.19)
pt.SetX2(0.88)
pt.SetY1(0.66)
pt.SetY2(0.82)
breakdown = args.breakdown.split(',')
v_hi = [val_nom[1]]
v_lo = [val_nom[2]]
for other in other_scans:
v_hi.append(other['val'][1])
v_lo.append(other['val'][2])
assert (len(v_hi) == len(breakdown))
textfit = '%s = %.2f' % (label_name, val_nom[0])
for i, br in enumerate(breakdown):
if i < (len(breakdown) - 1):
if (abs(v_hi[i + 1]) > abs(v_hi[i])):
print 'ERROR SUBTRACTION IS NEGATIVE FOR %s HI' % br
hi = 0.
else:
hi = math.sqrt(v_hi[i] * v_hi[i] -
v_hi[i + 1] * v_hi[i + 1])
if (abs(v_lo[i + 1]) > abs(v_lo[i])):
print 'ERROR SUBTRACTION IS NEGATIVE FOR %s LO' % br
lo = 0.
else:
lo = math.sqrt(v_lo[i] * v_lo[i] -
v_lo[i + 1] * v_lo[i + 1])
else:
hi = v_hi[i]
lo = v_lo[i]
textfit += '{}^{#plus %.2f}_{#minus %.2f}(%s)' % (hi, abs(lo), br)
pt.AddText(textfit)
pt.SetTextAlign(11)
pt.SetTextFont(42)
pt.Draw()
plot.DrawCMSLogo(pads[0],
args.logo,
args.logo_sub,
11,
0.045,
0.035,
1.2,
cmsTextSize=1.)
legend_l = 0.69
if len(other_scans) > 0:
legend_l = legend_l - len(other_scans) * 0.04
legend = ROOT.TLegend(0.15, legend_l, 0.45, 0.78, '', 'NBNDC')
if len(other_scans) >= 3:
legend = ROOT.TLegend(0.46, 0.83, 0.95, 0.93, '', 'NBNDC')
legend.SetNColumns(2)
legend.AddEntry(main_scan['func'], args.main_label, 'L')
for i, other in enumerate(other_scans):
legend.AddEntry(other['func'], other_scans_opts[i][1], 'L')
legend.Draw()
save_graph = main_scan['graph'].Clone()
save_graph.GetXaxis().SetTitle(
'%s = %.2f %+.2f/%+.2f' %
(label_name, val_nom[0], val_nom[2], val_nom[1]))
outfile = ROOT.TFile(args.output + '.root', 'RECREATE')
outfile.WriteTObject(save_graph)
outfile.Close()
canv.Print('.pdf')
canv.Print('.png')
canv.Print('.C')