if __name__ == '__main__':
from ROOT import TTree, TRandom3
from array import array
from plotting.Variable import Variable, Binning
from AtlasStyle import redLine, blueLine, greenLine
# create some dummy tree
rndm = TRandom3()
size = array( 'f', [0] )
energy = array( 'f', [0] )
t = TTree( 'tree', 'My Tree' )
t.Branch( 'size', size, 'size/F' )
t.Branch( 'energy', energy, 'energy/F' )
for entry in xrange( 10000 ):
size[0] = rndm.Poisson( 3 )
energy[0] = rndm.Landau( size[0]*2.5, size[0] )
t.Fill()
# define a variable object for each branch
sizeVar = Variable( 'size', title='Cluster Size', binning=Binning(10, 1, 11, range(1,11)) )
energyVar = Variable( 'energy', title='Hit Energy', unit='MeV', binning=Binning(50, 0, 100) )
p = BasicPlot( 'test', sizeVar, Variable( 'RMS(E)', unit = 'MeV' ) )
measure = HalfWidth()
measure.selection = Truncate( 0.68 )
g = p.addGraph( resolutionGraph( t, sizeVar, energyVar, '', measure ) )
p.draw()
g.Draw()
raw_input( 'Continue?' )
# create some dummy tree
rndm = TRandom3()
size = array('f', [0])
energy = array('f', [0])
t = TTree('tree', 'My Tree')
t.Branch('size', size, 'size/F')
t.Branch('energy', energy, 'energy/F')
for entry in xrange(10000):
size[0] = rndm.Poisson(3)
energy[0] = rndm.Landau(size[0] * 2.5, size[0])
t.Fill()
# define a variable object for each branch
sizeVar = Variable('size',
title='Cluster Size',
binning=Binning(10, 1, 11, range(1, 11)))
energyVar = Variable('energy',
title='Hit Energy',
unit='MeV',
binning=Binning(50, 0, 100))
# create a plot using the TreePlot class
treePlotTest = TreePlot('TreePlot Test',
sizeVar,
Variable('Entries'),
tree=t)
treePlotTest.addCut('No Cut')
treePlotTest.addCut('Energy > 15 MeV', 'energy > 15')
treePlotTest.draw()
# create a plot using the BasicPlot class
def testSystematicsCalculator():
from plotting.AtlasStyle import Style
from plotting.Cut import Cut
from plotting.Dataset import Dataset
from plotting.DataMcRatioPlot import DataMcRatioPlot
from plotting.DoublePlot import DoublePlot
from plotting.HistogramStore import HistogramStore
from plotting.Systematics import Systematics
from plotting.Tools import divideGraphs
from plotting.Variable import Binning, Variable
from ROOT import TF1, kViolet, kCyan, kBlack, kDashed
cut = Cut()
luminosity = 36.2
f_zpeak = TF1('z-peak', 'TMath::Voigt((1./[0])*x-91.2, [1], 2.5)')
f_zpeak.SetParNames('TES', 'TER')
f_zpeak.SetParameter('TES', 1.0)
f_zpeak.SetParameter('TER', 10.)
f_cont = TF1('continuum', '[0]*1./x')
f_cont.SetParNames('TES')
f_cont.SetParameter('TES', 1.0)
f_zpeak.SetParameter('TER', 10.)
var = Variable('dimuon_mass',
title='#it{m_{#tau#tau}}',
unit='GeV',
binning=Binning(20, 50., 150.))
store = HistogramStore('testHistogramStore.root')
z_jets = Dataset('z_jets',
'#it{Z}+jets',
style=Style(kCyan),
crossSection=0.0004)
continuum = Dataset('continuum',
'Others',
style=Style(kViolet),
crossSection=0.002)
sysLumi = Systematics.scaleSystematics('sysLumi', 'Lumi', 1.031, 0.968,
1.0)
sysTES = Systematics.treeSystematics('sysTES', 'TES', 'tes_up', 'tes_down')
sysTER = Systematics.treeSystematics('sysTER', 'TER', 'ter_up', 'ter_down')
mcStat = 500000
datasets = [continuum, z_jets]
functions = {z_jets: f_zpeak, continuum: f_cont}
for dataset in datasets:
dataset.addSystematics(sysTES)
dataset.addSystematics(sysLumi)
h = var.createHistogram(dataset.title)
f = functions[dataset]
h.FillRandom(f.GetName(), mcStat)
store.putHistogram(dataset, dataset.nominalSystematics, var, cut, h)
h.Reset()
f.SetParameter('TES', 1.02)
h.FillRandom(f.GetName(), mcStat)
store.putHistogram(dataset, sysTES.up, var, cut, h)
h.Reset()
f.SetParameter('TES', 0.98)
h.FillRandom(f.GetName(), mcStat)
store.putHistogram(dataset, sysTES.down, var, cut, h)
f.SetParameter('TES', 1.0)
z_jets.addSystematics(sysTER)
h.Reset()
f_zpeak.SetParameter('TER', 13)
h.FillRandom(f_zpeak.GetName(), mcStat)
store.putHistogram(z_jets, sysTER.up, var, cut, h)
h.Reset()
f.SetParameter('TER', 7)
h.FillRandom(f_zpeak.GetName(), mcStat)
store.putHistogram(z_jets, sysTER.down, var, cut, h)
p = DataMcRatioPlot('testPlot', var)
for dataset in datasets:
dataset.histogramStore = store
p.addHistogram(
dataset.getHistogram(var, cut=cut, luminosity=luminosity))
systGraph = calculateSystematicsGraph(datasets, var, luminosity=luminosity)
systGraph.SetTitle('Combined Systematics')
p.defaultCombinedErrorStyle.apply(systGraph)
p.setMCSystematicsGraph(systGraph)
p.draw()
p.saveAs('test.pdf')
p1 = DoublePlot('testPlot1',
var,
yVariableDown=Variable('Ratio',
binning=Binning(low=0.8, up=1.2)))
p1.plotDown.yVariable.binning.nDivisions = 205
nominalHist = None
systematicsSet = SystematicsSet()
for dataset in datasets:
systematicsSet |= dataset.combinedSystematicsSet
h = dataset.getHistogram(var, cut=cut, luminosity=luminosity)
if nominalHist:
nominalHist.Add(h)
else:
nominalHist = h
nominalHist.SetLineColor(kBlack)
nominalHist.SetTitle('Nominal')
p1.plotUp.addGraph(systGraph, '2')
p1.plotUp.addHistogram(nominalHist)
rSystGraph = systGraph.Clone()
rSystGraph.SetTitle()
p1.plotDown.addGraph(rSystGraph, '2')
divideGraphs(rSystGraph, nominalHist)
lineColor = 1
for systematics in systematicsSet:
lineColor += 1
upHist = None
downHist = None
# collect all up and down histograms for all datasets
for dataset in datasets:
upH = dataset.getHistogram(var,
cut=cut,
luminosity=luminosity,
systematicVariation=systematics.up)
downH = dataset.getHistogram(var,
cut=cut,
luminosity=luminosity,
systematicVariation=systematics.down)
downH.SetLineColor(lineColor)
downH.SetLineStyle(kDashed)
if upH:
if upHist:
upHist.Add(upH)
else:
upHist = upH
if downH:
if downHist:
downHist.Add(downH)
else:
downHist = downH
upHist.SetLineColor(lineColor)
upHist.SetTitle(systematics.title)
downHist.SetLineColor(lineColor)
downHist.SetLineStyle(kDashed)
downHist.SetTitle('')
rUpHist = upHist.Clone()
rUpHist.Divide(nominalHist)
rUpHist.SetTitle('')
rDownHist = downHist.Clone()
rDownHist.Divide(nominalHist)
rDownHist.SetTitle('')
p1.plotUp.addHistogram(upHist)
p1.plotUp.addHistogram(downHist)
p1.plotDown.addHistogram(rUpHist)
p1.plotDown.addHistogram(rDownHist)
p1.draw()
raw_input()
h2.FillRandom('gaus', 500)
h2.SetLineColor(
kBlue
) # if no fill color is defined, the line color is used to fill stacked histograms
h3 = TH1D('hTest3', 'Data', 20, -4, 4)
h3.FillRandom('gaus', 1500)
h3.SetLineColor(kBlack)
hSum = TH1D('hSum', 'Stat', 20, -4, 4)
mcErrorStyle.apply(hSum)
hRatio = TH1D('hRatio', 'Ratio', 20, -4, 4)
hRatio.Sumw2()
xVar = Variable('Invariant Mass', unit='GeV', binning=Binning(20, -4, 4))
yVarDown = Variable('Ratio', binning=Binning(low=0.5, up=1.5))
# Add the ATLAS label to each plot
BasicPlot.defaultTitleDecorator = AtlasTitleDecorator('work in progress')
# create a double plot with ratios by hand
doubleTest = DoublePlot('testDoublePlot', xVar, yVariableDown=yVarDown)
doubleTest.plotUp.stacked = True
doubleTest.plotUp.addHistogram(hSum, 'E2')
doubleTest.plotUp.addHistogram(h3, 'E0')
hSum.Add(doubleTest.plotUp.addHistogram(h1, stacked=True))
hSum.Add(doubleTest.plotUp.addHistogram(h2, stacked=True, copy=True))
hRatio.Add(h3)
hRatio.Divide(hSum)
doubleTest.plotDown.addHistogram(hRatio, 'E0')
from plotting.Variable import Binning, Variable, VariableBinning
from plotting.Systematics import Systematics, SystematicsSet, SystematicVariation
#===================#
# Weight Expression #
#===================#
weight_total = "weight_total"
# acutally used weight expression:
weight_expression = weight_total
#==========#
# Binnings #
#==========#
bin_pt = VariableBinning([20, 25, 30, 40, 60, 120])
bin_pt_lino = VariableBinning([50, 80, 120])
bin_pt_equal = Binning(10, 20, 120)
bin_pt_fine = Binning(24, 0, 120)
bin_eta = VariableBinning(
[-2.5, -1.52, -1.37, -1.1, -0.05, 0.05, 1.1, 1.37, 1.52, 2.5])
bin_eta_equal = Binning(15, -3, 3)
bin_phi = Binning(11, -3.15, 3.15)
bin_bdt = Binning(20, 0, 1)
#===========#
# Variables #
#===========#
# Variable( name, variable, x-axis title, unit, binning )
var_run_number = Variable('run_number', 'run_number', 'Run Number', '',
Binning(100, 250000, 350000))
var_pull = Variable('pull', 'pull', 'Pull', '', Binning(70, -3.5, 3.5))
from plotting.AtlasStyle import blackLine, redLine, blueLine
from ROOT import TFile, TTree, TRandom3
from array import array
rndm = TRandom3()
pT0 = array('f', [0])
pT1 = array('f', [0])
t = TTree('tree', 'tree')
t.Branch('tau_0_pt', pT0, 'tau_0_pt/F')
t.Branch('tau_1_pt', pT1, 'tau_1_pt/F')
sumOfWeights = 0.
for entry in xrange(10000):
pT0[0] = rndm.Gaus(60, 15)
pT1[0] = rndm.Gaus(50, 10)
t.Fill()
binning = Binning(50, 0, 100)
var_tau_0_pt = Variable('tau_0_pt',
title='p_{T}(#tau_{0})',
unit='GeV',
binning=binning)
var_tau_1_pt = Variable('tau_1_pt',
title='p_{T}(#tau_{1})',
unit='GeV',
binning=binning)
var_tau_pt = CombinedVariable('tau_0_pt',
'p_{T}(#tau)',
'GeV',
binning,
variables=[var_tau_0_pt, var_tau_1_pt])
p = BasicPlot('Test Plot', var_tau_pt)
nBlocks = int(round(barLength * fraction))
t = '\r[{0}] ({1}/{2}) {3:50}'.format(
'#' * nBlocks + '-' * (barLength - nBlocks), current, total, text)
sys.stdout.write(t)
sys.stdout.flush()
if fraction >= 1:
print ''
if __name__ == '__main__':
from plotting.Variable import Variable, Binning
from plotting.BasicPlot import BasicPlot
var = Variable(
'ditau_tau0_decay_mode', 'ditau_tau0_decay_mode',
'Decay Mode (#tau_{0})', '',
Binning(6, 0, 6, ['1p0n', '1p1n', '1pXn', '3p0n', '3pXn', 'Other']))
h = var.createHistogram('h_test')
h.Fill(2)
h.Fill(3)
h.Fill(2)
h.Fill(0)
h.Fill(2)
g = histToGraph(h, 'g_test')
g.SetLineColor(2)
#g = addGraphs( g, g, True )
p = BasicPlot('test', var)
p.addHistogram(h)
from plotting.BasicPlot import BasicPlot, LegendElement
from plotting.DoublePlot import DoublePlot
from plotting.Variable import Binning, Variable, var_Events
from plotting.Tools import histToGraph, combineStatsAndSystematics, addGraphs, divideGraphs, resetGraph,\
divideHistograms, createOutOfRangeArrows
import uuid
from copy import copy
var_dataMc = Variable('Data / Model', binning=Binning(low=0.7, up=1.3))
var_dataMc.binning.nDivisions = 205
class DataMcRatioPlot(DoublePlot):
from AtlasStyle import Style
from ROOT import kRed, kSpring, kGray, TColor
defaultStatErrorTitle = 'Stat. Uncertainty'
defaultSystErrorTitle = 'Syst. Uncertainty'
defaultCombinedErrorTitle = 'Stat #oplus Syst'
defaultStatErrorStyle = Style(TColor.GetColorTransparent(kSpring, 0.3),
lineWidth=0,
fillStyle=1000,
markerStyle=0)
defaultSystErrorStyle = Style(kGray + 3,
lineWidth=0,
fillStyle=3354,
markerStyle=0)
defaultCombinedErrorStyle = Style(kGray + 3,
lineWidth=0,
fillStyle=3354,
markerStyle=0)