def makeRepEffectPlots(hkey):
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'], hkey)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(lumi='MC, {} replacement'.format(
hkey.replace('LxySig-', '').replace('Lxy-', '')),
logy=True)
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
canvas.firstPlot.setTitles(X='', copy=PLOTS[HG.BGORDER[0]])
canvas.firstPlot.setTitles(Y='Normalized Counts')
canvas.makeLegend(lWidth=.27, pos='tr', autoOrder=False, fontscale=0.8)
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
canvas.firstPlot.SetMaximum(10.**7.)
canvas.firstPlot.SetMinimum(10.**0.)
canvas.cleanup('RepEffect_MC_{}.pdf'.format(hkey))
def makeDSAMC2DPlots():
for quantity in ('pT', 'eta', 'trkChi2'):
hkey = 'DSA-12-' + quantity
HISTS, PConfig = HG.getBackgroundHistograms(
FILES['MC'],
hkey,
stack=False,
addFlows=False,
rebin=(10, 10),
rebinVeto=lambda key: 'trkChi2' in key)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
R.gStyle.SetPalette(56)
PConfig['stack'] = ('', '', 'colz')
#PConfig['stack'] = ('', '', 'scat=0.2')
PLOTS = {}
for key in ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(lumi='MC' + lumiExtra.get(CUTSTRING))
canvas.addMainPlot(PLOTS['stack'])
canvas.mainPad.SetLogz()
if quantity == 'trkChi2':
canvas.firstPlot.GetXaxis().SetRangeUser(0., 10.)
canvas.firstPlot.GetYaxis().SetRangeUser(0., 10.)
canvas.scaleMargins(1.75, edges='R')
canvas.scaleMargins(0.8, edges='L')
canvas.cleanup('pdfs/ZEP_2D_{}_{}_MC.pdf'.format(quantity, CUTSTRING))
def makeMC2DPlots(BGList=None, SUFFIX=None):
if BGList is None:
BGORDER = ('WJets', 'WW', 'WZ', 'ZZ', 'tW', 'tbarW', 'ttbar',
'QCD20toInf-ME', 'DY10to50', 'DY50toInf')
SUFFIX = 'Full'
else:
BGORDER = BGList
if SUFFIX is None:
SUFFIX = BGList[0]
for quantity in ('normChi2', 'nTrkLay', 'nPxlHit', 'highPurity',
'isGlobal', 'isMedium', 'hitsBeforeVtx',
'missingHitsAfterVtx'):
if quantity == 'nTrkLay':
R.gStyle.SetPaintTextFormat('.1f')
else:
R.gStyle.SetPaintTextFormat('g')
hkey = 'PAT-12-' + quantity
HG.BGORDER = BGORDER # don't do this, normally
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'],
hkey,
stack=False,
addFlows=False)
HG.BGORDER = BGORDER_REAL
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
if quantity != 'normChi2':
R.gStyle.SetPalette(55)
PConfig['stack'] = ('', '', 'colz text')
else:
R.gStyle.SetPalette(56)
PConfig['stack'] = ('', '', 'colz')
PLOTS = {}
for key in ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(lumi=SUFFIX + lumiExtra.get(CUTSTRING))
canvas.addMainPlot(PLOTS['stack'])
canvas.firstPlot.SetMarkerColor(R.kWhite)
if quantity == 'normChi2':
canvas.firstPlot.GetXaxis().SetRangeUser(0., 10.)
canvas.firstPlot.GetYaxis().SetRangeUser(0., 10.)
canvas.scaleMargins(1.75, edges='R')
canvas.scaleMargins(0.8, edges='L')
canvas.cleanup('pdfs/ZEP_2D_{}_{}_{}_MC.pdf'.format(
quantity, SUFFIX, CUTSTRING))
def makeRepEffectPlots(hkey):
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'], hkey)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
canvas = Plotter.Canvas(
lumi='MC Background, {} PAT association (36.3 fb^{{-1}})'.format(
hkey.replace('LxySig-', '').replace('Lxy-', '')),
logy=True,
cWidth=600 if ARGS.SQUARE else 800)
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
canvas.firstPlot.setTitles(X='', copy=PLOTS[HG.BGORDER[0]])
canvas.firstPlot.setTitles(Y='Event Yield')
canvas.makeLegend(lWidth=.3, pos='tr', autoOrder=False, fontscale=0.8)
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
canvas.firstPlot.SetMaximum(10.**7.)
canvas.firstPlot.SetMinimum(10.**0.)
if ARGS.SQUARE:
canvas.firstPlot.scaleTitleOffsets(1.1, 'X')
z = PLOTS['stack'].plot.GetStack().Last()
print 'MC', hkey, z.Integral(0, z.GetNbinsX() + 1)
canvas.cleanup('pdfs/REPEFF_MC_{}.pdf'.format(hkey), mode='LUMI')
def makeIntegratedSEQMC(hkey='SEQ'):
if DODATA:
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'],
hkey,
extraScale=DATASCALE)
DATAHISTS, DataPConfig = HG.getDataHistograms(FILES['Data'], hkey)
else:
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'], hkey)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
if DODATA:
DATAHISTS = DATAHISTS[hkey]
PConfig['data'] = DataPConfig[hkey]['data']
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
if DODATA:
PLOTS['data'] = Plotter.Plot(DATAHISTS['data'], *PConfig['data'])
canvas = Plotter.Canvas(
lumi='MC' if not DODATA else 'MC + Data',
logy=True,
cWidth=1600,
)
# ratioFactor=0. if not DODATA else 1./3., fontscale=1. if not DODATA else 1.+1./3.)
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
if DODATA:
canvas.addMainPlot(PLOTS['data'])
setBinLabels(canvas)
canvas.makeLegend(lWidth=.27, pos='tr', autoOrder=False,
fontscale=0.8) # if not DODATA else 1.)
if DODATA:
canvas.addLegendEntry(PLOTS['data'])
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
canvas.legend.moveLegend(X=.1)
canvas.firstPlot.setTitles(X='Cut', Y='Normalized Counts')
canvas.firstPlot.SetMaximum(2.e7)
canvas.firstPlot.SetMinimum(1.e4 if 'DSA' not in hkey else 1.e-1)
canvas.scaleMargins(.5, 'L')
canvas.firstPlot.scaleTitleOffsets(.5, 'Y')
R.TGaxis.SetExponentOffset(0., 0.02, "y")
# if DODATA:
# canvas.makeRatioPlot(PLOTS['data'].plot, PLOTS['stack'].plot.GetStack().Last())
# canvas.firstPlot.scaleTitleOffsets(0.8, axes='Y')
# canvas.rat .scaleTitleOffsets(0.8, axes='Y')
# canvas.rat.setTitles(X='', copy=canvas.firstPlot.plot)
# setBinLabels(canvas, '')
#canvas.cleanup('pdfs/NM1_{}_MC.pdf'.format(hkey))
#canvas.finishCanvas(extrascale=1. if not DODATA else 1.+1./3.)
#canvas.save('pdfs/NM1_{}{}_MC.pdf'.format(hkey, BUMPSTRING))
#canvas.deleteCanvas()
canvas.cleanup('pdfs/NM1_{}{}{}_MC.pdf'.format(hkey, BUMPSTRING,
IDPHISTRING))
def makeMCPlots():
quantities = {
'DSA': [],
'PAT': [],
'HYB': [],
'HYB-DSA': [],
'HYB-PAT': []
}
dimQuantities = [
'Lxy', 'LxySig', 'LxyErr', 'vtxChi2', 'mind0Sig', 'mass', 'deltaPhi',
'deltaR', 'cosAlpha', 'cosAlpha-O', 'DCA', 'pTOverM', 'minNHits',
'qsum'
]
for recoType in quantities:
if 'HYB-' in recoType: continue
quantities[recoType].extend(dimQuantities)
quantities['HYB-DSA'].extend(
['pT', 'eta', 'phi', 'd0', 'FPTE', 'd0Sig', 'trkChi2', 'nStations'])
quantities['HYB-PAT'].extend(
['pT', 'eta', 'phi', 'd0', 'relTrkIso', 'd0Sig', 'trkChi2'])
for recoType in ('DSA', 'PAT'):
quantities[recoType].extend(quantities['HYB-' + recoType])
quantities['REF-DSA'] = ['FPTE']
quantities[''] = ['nDimuon', 'nDSA', 'nDSA12', 'nDSA12-pT', 'nDSA-DT']
# consider making deltaPhi not log scale. If so, then uncomment the maximum commands at the bottom
def rebinVeto(key):
if 'Lxy' in key and 'Sig' not in key and 'Err' not in key and 'DSA' not in key:
return True
if 'deltaPhi' in key or 'phi' in key: return True
if 'mass' in key and MASSZOOMED: return True
if 'nStations' in key: return True
if 'cosAlpha' in key: return True
if 'LxySig' in key and 'DSA' in key: return True
if 'mind0Sig' in key and 'DSA' in key: return True
if 'd0' in key and 'Sig' not in key and 'DSA' in key: return True
if 'trkChi2' in key: return True
if 'nDimuon' in key: return True
if 'nDSA' in key: return True
if 'REF-DSA-FPTE' in key: return True
if 'minNHits' in key: return True
if 'qsum' in key: return True
return False
for recoType in quantities:
for quantity in quantities[recoType]:
hkey = recoType + '-' + quantity
if hkey[0] == '-' or recoType == 'DSAPlus':
hkey = quantity
recoType = 'DSAPlus'
DODATA = recoType == 'DSA' or recoType == 'REF-DSA' or (
recoType == 'DSAPlus' and 'nDSA' in quantity)
if DODATA:
HISTS, PConfig = HG.getBackgroundHistograms(
FILES['MC'],
hkey,
addFlows=True,
rebin=10,
rebinVeto=rebinVeto,
extraScale=DATASCALE)
DATAHISTS, DataPConfig = HG.getDataHistograms(
FILES['Data'],
hkey,
addFlows=True,
rebin=10,
rebinVeto=rebinVeto)
else:
HISTS, PConfig = HG.getBackgroundHistograms(
FILES['MC'],
hkey,
addFlows=True,
rebin=10,
rebinVeto=rebinVeto)
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
if DODATA:
DATAHISTS = DATAHISTS[hkey]
PConfig['data'] = DataPConfig[hkey]['data']
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
if DODATA:
PLOTS['data'] = Plotter.Plot(DATAHISTS['data'],
*PConfig['data'])
canvas = Plotter.Canvas(
lumi=('MC' if not DODATA else 'MC + Data') +
lumiExtra.get(CUTSTRING) + ' ({})'.format(recoType),
logy=True,
ratioFactor=0. if not DODATA else 1. / 3.,
fontscale=1. if not DODATA else 1. + 1. / 3.)
if hkey == 'REF-DSA-FPTE':
canvas.mainPad.SetLogx()
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
if DODATA:
canvas.addMainPlot(PLOTS['data'])
# this has to be here because it has to be drawn first
if 'vtxChi2' in hkey:
canvas.firstPlot.GetXaxis().SetRangeUser(0., 50.)
if 'mass' in hkey:
if MASSZOOMED:
canvas.firstPlot.GetXaxis().SetRangeUser(0., 100.)
if 'mind0Sig' in hkey and 'DSA' in hkey:
pass
#canvas.firstPlot.GetXaxis().SetRangeUser(0., 5.)
canvas.firstPlot.setTitles(X='', copy=PLOTS[HG.BGORDER[0]])
canvas.firstPlot.setTitles(Y='Normalized Counts')
canvas.makeLegend(lWidth=.27,
pos='tr' if hkey != 'REF-DSA-FPTE' else 'tl',
autoOrder=False,
fontscale=0.8 if not DODATA else 1.)
if DODATA:
canvas.addLegendEntry(PLOTS['data'])
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
HISTS['sum'] = HISTS['stack'].GetStack().Last()
nBins = HISTS['sum'].GetNbinsX()
val = None
if 'LxySig' in hkey:
val = 100.
if 'vtxChi2' in hkey:
val = 50.
if 'LxyErr' in hkey:
val = 10.
if 'mind0Sig' in hkey:
val = 3.
if 'Lxy' == quantity:
val = 100.
if val is not None:
print '{} Mean : {}'.format(hkey,
HISTS['sum'].GetMean())
print '{} Overflow % : {}'.format(
hkey, HISTS['sum'].GetBinContent(nBins) /
HISTS['sum'].Integral(1, nBins) * 100.)
print '{} > {:<8.0f} % : {}'.format(
hkey, val,
HISTS['sum'].Integral(HISTS['sum'].FindBin(val), nBins) /
HISTS['sum'].Integral(1, nBins) * 100.)
if hkey == 'PAT-LxySig':
h = HG.getHistogram(FILES['MC'], 'DY50toInf', hkey).Clone()
print '{} DY50toInf : {}'.format(
hkey, h.Integral(h.FindBin(100.), h.GetNbinsX()))
if DODATA:
canvas.makeRatioPlot(PLOTS['data'].plot,
PLOTS['stack'].plot.GetStack().Last())
canvas.firstPlot.scaleTitleOffsets(0.8, axes='Y')
canvas.rat.scaleTitleOffsets(0.8, axes='Y')
if 'mass' in hkey:
if MASSZOOMED:
canvas.rat.GetXaxis().SetRangeUser(0., 100.)
if 'REF-DSA-FPTE' in hkey:
canvas.ratPad.SetLogx()
doNotMaximize = True
canvas.firstPlot.SetMaximum({
'DSA': 1000.,
'PAT': 10.**7.,
'HYB': 2. * 10.**5.,
'HYB-DSA': 2. * 10.**5.,
'HYB-PAT': 2. * 10.**5.,
'REF-DSA': 1000.,
'DSAPlus': 1000.
}[recoType])
if recoType == 'DSA' and quantity in [
'pT', 'eta', 'phi', 'FPTE', 'd0Sig', 'trkChi2', 'nStations'
]:
canvas.firstPlot.SetMaximum(10.**5.)
#if recoType == 'PAT' and 'deltaPhi' in quantity:
# canvas.firstPlot.SetMaximum(11.**5.)
if not doNotMaximize:
canvas.firstPlot.SetMaximum(HISTS['sum'].GetMaximum() * 1.05)
canvas.firstPlot.SetMinimum(1.)
#canvas.cleanup('pdfs/ZEP_{}_{}_{}_MC.pdf'.format(quantity, recoType, CUTSTRING))
canvas.finishCanvas(extrascale=1. if not DODATA else 1. + 1. / 3.)
canvas.save('pdfs/ZEP_{}_{}_{}_MC.pdf'.format(
quantity +
('Zoomed' if 'mass' in quantity and MASSZOOMED else ''),
recoType, CUTSTRING))
canvas.deleteCanvas()
import ROOT as R
import DisplacedDimuons.Analysis.HistogramGetter as HG
import DisplacedDimuons.Analysis.Plotter as Plotter
f = R.TFile.Open('roots/HPPlots_Trig_Combined_NS_NH_FPTE_HLT_REP_PT_PC_LXYE_MASS_2Mu2J.root')
h = HG.getAddedSignalHistograms(f, '2Mu2J', ('pT', 'GM-pT', 'pT-HP', 'GM-pT-HP'))
for key in ('', 'GM-'):
h[key+'pT-HP'].Rebin(5)
h[key+'pT' ].Rebin(5)
g = R.TGraphAsymmErrors(h[key+'pT-HP'], h[key+'pT'], 'cp')
p = Plotter.Plot(g, '', '', 'pe')
c = Plotter.Canvas()
c.addMainPlot(p)
p.setTitles(X='pre-refit PAT muon p_{T} [GeV]', Y='High purity fraction')
p.setColor(R.kBlue, which='LM')
c.cleanup('pdfs/HP_2Mu2J_'+key+'HPFrac.pdf')
f = R.TFile.Open('roots/HPPlots_Combined_NS_NH_FPTE_HLT_REP_PT_PC_LXYE_MASS_MC.root')
h, pc = HG.getBackgroundHistograms(f, ('pT', 'pT-HP'), stack=False, rebin=5)
for key in ('stack', 'DY50toInf'):
g = R.TGraphAsymmErrors(h['pT-HP'][key], h['pT'][key], 'cp')
p = Plotter.Plot(g, '', '', 'pe')
c = Plotter.Canvas(lumi=key.title() if key == 'stack' else key)
c.addMainPlot(p)
p.setTitles(X='pre-refit PAT muon p_{T} [GeV]', Y='High purity fraction')
p.setColor(R.kBlue, which='LM')
c.cleanup('pdfs/HP_MC_'+key+'_HPFrac.pdf')
keyList = {
'hLessLxySig': 'LxySig-SplitDPhi',
'hMoreLxySig': 'LxySig-SplitDPhi',
'hLessLxySigBig': 'LxySig-SplitDPhi-Big',
'hMoreLxySigBig': 'LxySig-SplitDPhi-Big',
'hLessLxySigEdges': 'LxySig-SplitDPhi-Edges',
'hMoreLxySigEdges': 'LxySig-SplitDPhi-Edges',
'hLessDeltaPhi': 'deltaPhi-SplitLxySig',
'hMoreDeltaPhi': 'deltaPhi-SplitLxySig',
'hLessDeltaPhiBig': 'deltaPhi-SplitLxySig-Big',
'hMoreDeltaPhiBig': 'deltaPhi-SplitLxySig-Big',
'hDeltaPhi': 'deltaPhi',
'hDeltaPhiBig': 'deltaPhi-Big',
}
HISTS, PConfig = HG.getBackgroundHistograms(f, keyList.keys(), addFlows=False)
DHists = {}
for key in keyList:
DHists[key] = HG.getHistogram(f, 'Data', key).Clone()
def makeSinglePlots(hkey, logy=True):
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[hkey][key], *PConfig[hkey][key])
PLOTS['Data'] = Plotter.Plot(DHists[hkey], 'DoubleMuon2016', 'pe', 'pe')
canvas = Plotter.Canvas(lumi='36.3 fb^{-1} (13 TeV)',
logy=logy,
cWidth=800 if not ARGS.SQUARE else 600)
def makeMCPlot(hkey, DODATA=False, TENP=False):
if DODATA:
if not TENP:
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC_I'], hkey)
DATAHISTS, DataPConfig = HG.getDataHistograms(
FILES['Data_I'], hkey)
lumi = 'MC + Data, |#Delta#Phi| > #pi/2'
else:
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'],
hkey,
extraScale=DATASCALE)
DATAHISTS, DataPConfig = HG.getDataHistograms(FILES['Data'], hkey)
lumi = 'MC + 10% Data'
else:
HISTS, PConfig = HG.getBackgroundHistograms(FILES['MC'], hkey)
lumi = 'MC'
HISTS = HISTS[hkey]
PConfig = PConfig[hkey]
if DODATA:
DATAHISTS = DATAHISTS[hkey]
PConfig['data'] = DataPConfig[hkey]['data']
PLOTS = {}
for key in HG.BGORDER + ('stack', ):
PLOTS[key] = Plotter.Plot(HISTS[key], *PConfig[key])
if DODATA:
PLOTS['data'] = Plotter.Plot(DATAHISTS['data'], *PConfig['data'])
canvas = Plotter.Canvas(
lumi=lumi,
logy=True if hkey != 'nDTHits' else False
#ratioFactor=0. if not DODATA else 1./3., fontscale=1. if not DODATA else 1.+1./3.)
)
for key in HG.BGORDER:
PLOTS[key].setColor(HG.PLOTCONFIG[key]['COLOR'], which='LF')
canvas.addMainPlot(PLOTS['stack'])
if DODATA:
canvas.addMainPlot(PLOTS['data'])
canvas.firstPlot.setTitles(X='', copy=HISTS[HG.BGORDER[0]])
canvas.firstPlot.setTitles(Y='Normalized Counts')
canvas.makeLegend(lWidth=.27, pos='tr', autoOrder=False,
fontscale=0.8) # if not DODATA else 1.)
if DODATA:
canvas.addLegendEntry(PLOTS['data'])
for ref in reversed(HG.BGORDER):
canvas.addLegendEntry(PLOTS[ref])
canvas.legend.resizeHeight()
RT.addBinWidth(canvas.firstPlot)
if canvas.logy:
canvas.firstPlot.SetMinimum(1.)
canvas.firstPlot.SetMaximum(500.)
else:
canvas.firstPlot.SetMinimum(0.)
canvas.firstPlot.SetMaximum(10.)
#if DODATA:
# canvas.makeRatioPlot(PLOTS['data'].plot, PLOTS['stack'].plot.GetStack().Last())
# canvas.firstPlot.scaleTitleOffsets(0.8, axes='Y')
# canvas.rat .scaleTitleOffsets(0.8, axes='Y')
# canvas.rat.setTitles(X='', copy=canvas.firstPlot.plot)
if canvas.logy:
line = R.TLine(CONFIG[hkey]['val'], 0.45, CONFIG[hkey]['val'],
10.**(R.TMath.Log10(500.) * 1.06))
else:
line = R.TLine(CONFIG[hkey]['val'], 0., CONFIG[hkey]['val'],
10. * 1.05)
line.Draw()
line.SetLineStyle(2)
if DODATA:
if not TENP:
DATAHISTS_NO, DataPConfig_NO = HG.getDataHistograms(
FILES['Data_I'], hkey, addFlows=False)
else:
DATAHISTS_NO, DataPConfig_NO = HG.getDataHistograms(FILES['Data'],
hkey,
addFlows=False)
print '\033[32m{:6s} {:8s} {:5.0f} {:5.0f} {:7.2%}\033[m'.format(
'Data' + ('' if not TENP else '10'), hkey,
*fractionCut(hkey, DATAHISTS_NO[hkey]['data']))
canvas.cleanup('pdfs/NM1D_{}_MC{}{}.pdf'.format(
hkey, '' if not DODATA else 'Data', '' if not TENP else '-10'))