def plot(year):
base = 'mmttProcessor_DevTools'
hamasses = [(
125,
5,
), (
125,
7,
), (
125,
9,
), (125, 11), (125, 13), (125, 15), (125, 17), (125, 19)]
# define the samples
backgrounds = []
data = 'DATA'
signals = [f'haaH{h}A{a}' for h, a in hamasses]
sampleMap = {
s: get_sample_list(base, year, s)
for s in backgrounds + signals + [data]
}
print(sampleMap)
# load the tfiles
channels = ['mm']
cats = ['dimuon', 'ditau', 'ditauMD']
tfiles = {}
for s in sampleMap:
for sample in sampleMap[s]:
# TODO: we can keep this in the sample map builder
tfiles[sample] = ROOT.TFile.Open(
f'hists/{base}/{year}/{sample}.root')
# styles for plots
styleMap = {
'DATA': {
'label': 'Observed',
}
}
sigcolors = [
ROOT.kRed + 2, ROOT.kRed - 1, ROOT.kRed - 3, ROOT.kGreen + 2,
ROOT.kGreen - 1, ROOT.kGreen - 3, ROOT.kBlue + 2, ROOT.kBlue - 1,
ROOT.kBlue - 3
]
for i, (h, a) in enumerate(hamasses):
styleMap[f'haaH{h}A{a}'] = {
'label':
f'ggH #rightarrow aa (m_{{H}} = {h} GeV, m_{{a}} = {a} GeV',
'linecolor': sigcolors[i],
}
# setup plotter
plotter = Plotter('MMTT', year)
plotter.setStyleMap(styleMap)
for bg in backgrounds:
plotter.addSampleToStack(bg)
for sig in signals:
plotter.addSampleToPlot(sig)
plotter.setDataSample(data)
# plot
plots = {
'mmMass': {
'hPath': '{sample}_{chan}_{cat}_mmMass',
'xlabel': 'm_{#mu#mu} (GeV)',
'binning': [x * 0.1 for x in range(25, 251, 1)],
'ylabel': 'Events / 100 MeV',
'logx': False,
'logy': False,
'plotratio': False,
'blind': blind,
},
'ttMass': {
'hPath': '{sample}_{chan}_{cat}_ttMass',
'xlabel': 'm_{#tau#tau} (GeV)',
'binning': [x * 0.1 for x in range(0, 251, 5)],
'ylabel': 'Events / 0.5 GeV',
'logx': False,
'logy': False,
'plotratio': False,
'blind': blind,
},
'mmttMass': {
'hPath': '{sample}_{chan}_{cat}_mmttMass',
'xlabel': 'm_{#mu#mu#tau#tau} (GeV)',
'binning': range(0, 250, 1),
'ylabel': 'Events / 1 GeV',
'logx': False,
'logy': False,
'plotratio': False,
'blind': blind,
},
'pileup': {
'hPath': '{sample}_{chan}_{cat}_pileup',
'xlabel': 'Number of reconstructed vertices',
'binning': range(0, 120, 1),
'ylabel': 'Events',
'logx': False,
'logy': False,
'plotratio': False,
'blind': blind,
},
}
def sumHists(name, *hists):
hlist = ROOT.TList()
for h in hists:
if h: hlist.Add(h.Clone())
if hlist.IsEmpty():
print('No histograms for', name)
return None
hist = hists[0].Clone(name)
hist.Reset()
hist.Merge(hlist)
return hist
chan = 'mm'
for plot in plots:
for cat in cats:
if plot in ['ttMass', 'mmttMass'] and cat == 'dimuon': continue
# load the histograms
hists = {s: [] for s in sampleMap}
for s in sampleMap:
for sample in sampleMap[s]:
name = f'h_{plot}_{chan}_{cat}_{s}_{sample}'
hist = tfiles[sample].Get(plots[plot]['hPath'].format(
sample=sample, chan=chan, cat=cat))
if hist:
hists[s] += [hist.Clone(name)]
# sum the histograms
for s in hists:
hname = f'{plot}_{chan}_{cat}_{s}'
hist = sumHists(hname, *hists[s])
# bin the histogram
if hist:
binning = array('d', plots[plot]['binning'])
hist = hist.Rebin(
len(binning) - 1, hname + '_rebin', binning)
hists[s] = hist
if s == 'SIG': hists[s].Scale(0.001)
# scale the hists:
for s in hists:
if s == 'DATA': continue
hists[s].Scale(float(plotter.intLumi) / 1000)
# send to plotter
plotter.plot(hists, f'{year}/{chan}/{cat}/{plot}', **plots[plot])
def plot(year):
base = 'mmjProcessor'
# define the samples
backgrounds = ['TT','Z','ZZ']
data = 'DATA'
signals = []
sampleMap = { s: get_sample_list(base,year,s) for s in backgrounds+signals+[data] }
print(sampleMap)
# load the tfiles
channels = ['mmj']
tfiles = {}
for s in sampleMap:
for sample in sampleMap[s]:
# TODO: we can keep this in the sample map builder
tfiles[sample] = ROOT.TFile.Open(f'hists/{base}/{year}/{sample}.root')
# styles for plots
styleMap = {
'TT' : {'label': 't#bar{t}', 'linecolor': ROOT.kGreen+3, 'fillcolor': ROOT.kGreen+3,},
'Z' : {'label': 'Drell-Yan', 'linecolor': ROOT.kOrange-2, 'fillcolor': ROOT.kOrange-2,},
'WZ' : {'label': 'WZ', 'linecolor': ROOT.kViolet, 'fillcolor': ROOT.kViolet,},
'ZZ' : {'label': 'ZZ', 'linecolor': ROOT.kBlue, 'fillcolor': ROOT.kBlue,},
'DATA': {'label': 'Observed',}
}
# setup plotter
plotter = Plotter('MuMuJ',year)
plotter.setStyleMap(styleMap)
for bg in backgrounds: plotter.addSampleToStack(bg)
for sig in signals: plotter.addSampleToPlot(sig)
plotter.setDataSample(data)
# plot
plots = {
'mll' : {'hPath': '{sample}_{chan}_iso_mmMass', 'xlabel': 'm_{#mu#mu} (GeV)', 'binning': [x*0.1 for x in range(25,625,1)], 'ylabel': 'Events / 100 MeV', 'logx': False, 'logy': True, 'plotratio': False,},
'mllj' : {'hPath': '{sample}_{chan}_iso_mmjMass', 'xlabel': 'm_{#mu#mu j} (GeV)', 'binning': [x for x in range(0,300,1)], 'ylabel': 'Events / 1 GeV', 'logx': False, 'logy': False,'plotratio': False,},
'mllj_log' : {'hPath': '{sample}_{chan}_iso_mmjMass', 'xlabel': 'm_{#mu#mu j} (GeV)', 'binning': [x for x in range(0,1200,1)], 'ylabel': 'Events / 1 GeV', 'logx': False, 'logy': True, 'plotratio': False,},
'mllj_jpsi' : {'hPath': '{sample}_{chan}_jpsi_iso_mmjMass', 'xlabel': 'm_{#mu#mu j} (GeV)', 'binning': [x for x in range(0,300,1)], 'ylabel': 'Events / 1 GeV', 'logx': False, 'logy': False,'plotratio': False,},
'mllj_jpsi_log' : {'hPath': '{sample}_{chan}_jpsi_iso_mmjMass', 'xlabel': 'm_{#mu#mu j} (GeV)', 'binning': [x for x in range(0,1200,1)], 'ylabel': 'Events / 1 GeV', 'logx': False, 'logy': True, 'plotratio': False,},
'jpsi' : {'hPath': '{sample}_{chan}_iso_mmMass', 'xlabel': 'm_{#mu#mu} (GeV)', 'binning': [x*0.01 for x in range(250,450,1)], 'ylabel': 'Events / 10 MeV', 'logx': False, 'logy': True, 'plotratio': False,},
'upsilon' : {'hPath': '{sample}_{chan}_iso_mmMass', 'xlabel': 'm_{#mu#mu} (GeV)', 'binning': [x*0.01 for x in range(600,1400,1)], 'ylabel': 'Events / 10 MeV', 'logx': False, 'logy': False, 'plotratio': False,},
'pileup' : {'hPath': '{sample}_{chan}_iso_pileup', 'xlabel': 'Number of reconstructed vertices', 'binning': range(0,120,1), 'ylabel': 'Events', 'logx': False, 'logy': False, 'plotratio': False,},
}
def sumHists(name,*hists):
hlist = ROOT.TList()
for h in hists:
if h: hlist.Add(h.Clone())
if hlist.IsEmpty():
print('No histograms for',name)
return None
hist = hists[0].Clone(name)
hist.Reset()
hist.Merge(hlist)
return hist
for plot in plots:
# individual channels
for chan in channels:
# load the histograms
hists = {s:[] for s in sampleMap}
for s in sampleMap:
for sample in sampleMap[s]:
name = f'h_{plot}_{chan}_{s}_{sample}'
hist = tfiles[sample].Get(plots[plot]['hPath'].format(sample=sample,chan=chan))
if hist:
hists[s] += [hist.Clone(name)]
# sum the histograms
for s in hists:
hname = f'{plot}_{chan}_{s}'
hist = sumHists(hname,*hists[s])
# bin the histogram
if hist:
binning = array('d',plots[plot]['binning'])
hist = hist.Rebin(len(binning)-1,hname+'_rebin',binning)
hists[s] = hist
if s=='SIG': hists[s].Scale(0.001)
# scale the hists:
for s in hists:
if s=='DATA': continue
hists[s].Scale(float(plotter.intLumi)/1000)
# send to plotter
plotter.plot(hists, f'{year}/{chan}/{plot}', **plots[plot])
# combined
hists = {s:[] for s in sampleMap}
for chan in channels:
# load the histograms
for s in sampleMap:
for sample in sampleMap[s]:
name = f'h_{plot}_{chan}_{s}_{sample}'
hist = tfiles[sample].Get(plots[plot]['hPath'].format(sample=sample,chan=chan))
if hist:
hists[s] += [hist.Clone(name)]
# sum the histograms
for s in hists:
hname = f'{plot}_{s}'
hist = sumHists(hname,*hists[s])
# bin the histogram
if hist:
binning = array('d',plots[plot]['binning'])
hist = hist.Rebin(len(binning)-1,hname+'_rebin',binning)
hists[s] = hist
if s=='SIG': hists[s].Scale(0.001)
# scale the hists:
for s in hists:
if s=='DATA': continue
hists[s].Scale(float(plotter.intLumi)/1000)
# send to plotter
plotter.plot(hists, f'{year}/{plot}', **plots[plot])
def plot(year):
base = 'hzzProcessor'
backgrounds = ['ggZZ','qqZZ','HZZ']
data = 'DATA'
signals = []
sampleMap = { s: get_sample_list(base,year,s) for s in backgrounds+signals+[data] }
print(sampleMap)
# load the tfiles
channels = ['2m2e','2e2m','4e','4m']
tfiles = {}
for s in sampleMap:
if None in sampleMap[s]:
sampleMap[s] = [x for x in sampleMap[s] if x is not None]
print(f'Warning: missing samples for {s}')
for sample in sampleMap[s]:
tfiles[sample] = ROOT.TFile.Open(f'hists/hzzProcessor/{year}/{sample}.root')
# styles for plots
styleMap = {
'TT' : {'label': 't#bar{t}', 'linecolor': ROOT.kGreen+3, 'fillcolor': ROOT.kGreen+3,},
'TTV' : {'label': 't#bar{t}V', 'linecolor': ROOT.kGreen+4, 'fillcolor': ROOT.kGreen+4,},
'Z' : {'label': 'Z+X', 'linecolor': ROOT.kGreen+2, 'fillcolor': ROOT.kGreen+2,},
'ggZZ': {'label': 'gg#rightarrowZZ, Z#gamma*', 'linecolor': ROOT.kBlue, 'fillcolor': ROOT.kBlue,},
'qqZZ': {'label': 'q#bar{q}#rightarrowZZ, Z#gamma*', 'linecolor': ROOT.kAzure+6, 'fillcolor': ROOT.kAzure+6,},
'HWW' : {'label': 'H(125)#rightarrowWW#rightarrow2l2#nu', 'linecolor': ROOT.kRed+2, 'fillcolor': ROOT.kRed+2,},
'HZZ' : {'label': 'H(125)#rightarrowZZ#rightarrow4l', 'linecolor': ROOT.kRed+1, 'fillcolor': ROOT.kRed+1,},
'SIG' : {'label': '2HDM+a', 'linecolor': ROOT.kMagenta+1,},
'DATA': {'label': 'Observed',}
}
# setup plotter
plotter = Plotter('MonoHZZ',year)
plotter.setStyleMap(styleMap)
for bg in backgrounds: plotter.addSampleToStack(bg)
for sig in signals: plotter.addSampleToPlot(sig)
plotter.setDataSample(data)
# plot
plots = {
'm4l' : {'hPath': '{sample}_{chan}_hzz_mass', 'xlabel': 'm_{4l} (GeV)', 'binning': range(70,500,4), 'ylabel': 'Events / 4 GeV', 'logx': False, 'logy': False,},
'm4l_zoom' : {'hPath': '{sample}_{chan}_hzz_mass', 'xlabel': 'm_{4l} (GeV)', 'binning': range(70,170,2), 'ylabel': 'Events / 2 GeV', 'logx': False, 'logy': False,},
'm4l_full' : {'hPath': '{sample}_{chan}_massWindow_mass', 'xlabel': 'm_{4l} (GeV)', 'binning': range(113,135,3), 'ylabel': 'Events / 3 GeV', 'logx': False, 'logy': False, 'blind':blind,},
'mz1' : {'hPath': '{sample}_{chan}_hzz_z1mass', 'xlabel': 'm_{ll} (GeV)', 'binning': range(40,120,1), 'ylabel': 'Events / 1 GeV', 'logx': False, 'logy': False,},
'mz2' : {'hPath': '{sample}_{chan}_hzz_z2mass', 'xlabel': 'm_{ll} (GeV)', 'binning': range(12,120,1), 'ylabel': 'Events / 1 GeV', 'logx': False, 'logy': False,},
'met' : {'hPath': '{sample}_{chan}_hzz_met', 'xlabel': 'E_{T}^{miss} (GeV)', 'binning': range(0,420,20), 'ylabel': 'Events / 20 GeV','logx': False, 'logy': True, 'ymin':0.1,},
'met_limit' : {'hPath': '{sample}_{chan}_massWindow_met', 'xlabel': 'E_{T}^{miss} (GeV)', 'binning': [0,25,50,200,500,1000], 'ylabel': 'Events', 'logx': False, 'logy': True, 'ymin':0.1, 'blind':blind,},
'pileup' : {'hPath': '{sample}_{chan}_hzz_pileup', 'xlabel': 'Number of reconstructed vertices', 'binning': range(0,120,1), 'ylabel': 'Events', 'logx': False, 'logy': False,},
}
def sumHists(name,*hists):
hlist = ROOT.TList()
for h in hists:
if h: hlist.Add(h.Clone())
if hlist.IsEmpty():
print('No histograms for',name)
return None
hist = hists[0].Clone(name)
hist.Reset()
hist.Merge(hlist)
return hist
for plot in plots:
# individual channels
for chan in channels:
# load the histograms
hists = {s:[] for s in sampleMap}
for s in sampleMap:
for sample in sampleMap[s]:
name = f'h_{plot}_{chan}_{s}_{sample}'
hist = tfiles[sample].Get(plots[plot]['hPath'].format(sample=sample,chan=chan))
if hist:
hists[s] += [hist.Clone(name)]
# sum the histograms
for s in hists:
hname = f'{plot}_{chan}_{s}'
hist = sumHists(hname,*hists[s])
# bin the histogram
if hist:
binning = array('d',plots[plot]['binning'])
hist = hist.Rebin(len(binning)-1,hname+'_rebin',binning)
hists[s] = hist
if s=='SIG': hists[s].Scale(0.001)
# scale the hists:
for s in hists:
if s=='DATA': continue
hists[s].Scale(float(plotter.intLumi)/1000)
# send to plotter
plotter.plot(hists, f'{year}/{chan}/{plot}', **plots[plot])
# combined
hists = {s:[] for s in sampleMap}
for chan in channels:
# load the histograms
for s in sampleMap:
for sample in sampleMap[s]:
name = f'h_{plot}_{chan}_{s}_{sample}'
hist = tfiles[sample].Get(plots[plot]['hPath'].format(sample=sample,chan=chan))
if hist:
hists[s] += [hist.Clone(name)]
# sum the histograms
for s in hists:
hname = f'{plot}_{s}'
hist = sumHists(hname,*hists[s])
# bin the histogram
if hist:
binning = array('d',plots[plot]['binning'])
hist = hist.Rebin(len(binning)-1,hname+'_rebin',binning)
hists[s] = hist
if s=='SIG': hists[s].Scale(0.001)
# scale the hists:
for s in hists:
if s=='DATA': continue
hists[s].Scale(float(plotter.intLumi)/1000)
# send to plotter
plotter.plot(hists, f'{year}/{plot}', **plots[plot])