## Customize below
struefit.applyDefinitions([DimuonMassMax(80)])
struefits =[]
# models = ('gauss lognormal bifurGauss cbShape gamma'.split() +
# 'cruijff gsh bifurGsh bw sumGaussGauss'.split())
models = 'bifurGauss'.split()
# models += 'sumGaussGauss sumGauss3 sumCruijffGauss sumBwGauss'.split()
for subdet_r9_cat in subdet_r9_categories:
for lo, hi in BinEdges([10, 12, 15, 20, 25, 30, 100]):
## for lo, hi in BinEdges([10, 12, 15]):
for model in models:
fit = struefit.clone().applyDefinitions([subdet_r9_cat,
PhoEtBin(lo, hi),
Model(model)])
if ('EB_lowR9_PhoEt10-12' in fit.name or
'EB_lowR9_PhoEt12-15' in fit.name):
fit.fitRangeFraction -= 0.2
if 'EE' in fit.name:
fit.fitRangeFraction += 0.1
fit.binContentMax = 100
if fit.fitRangeFraction > 1.:
fit.fitRangeFraction = 1.
fit.labels.append('Fit Range Coverage: %.0f%%' %
(100 * fit.fitRangeFraction))
# fit.labels.append('Fit Range: (%.0f, %.0f)%%' % fit.fitRange)
struefits.append(fit)
_fits = struefits
struefit = srecofit.clone(
name = 'strue_mc',
title = 'strue-Fit, Powheg S4',
labels = ['Powheg S4'],
source = _chains['z'],
xName = 's',
xTitle = 's_{true} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1',
xExpression = '100 * (phoE/phoGenE - 1)',
cuts = ['isFSR', 'phoGenE > 0'],
xRange = (-50, 100),
xUnit = '%',
nBins = 150,
pdf = 'bifurGaus',
graphicsExtensions = ['png'],
massWindowScale = 1.5,
massWindow = (87.2, 95.2),
fitScale = 1.2,
fitRange = (-50,100),
doAutoBinning = True,
binContentMax = 200,
binContentMin = 35,
canvasStyle = 'landscape',
doAutoXRange = True,
doAutoXRangeZoom = True,
doAutoFitRange = True,
xRangeSigmaLevel = 5,
xRangeSigmaLevelZoom = 2,
fitRangeMode = 'Fraction',
fitRangeSigmaLevel = 2.0,
fitRangeNumberOfEntries = 3000,
fitRangeFraction = 0.68,
paramLayout = (0.57, 0.92, 0.92),
useCustomChi2Calculator = True,
)
kRatioGen = 'kRatio({mmgMass}, {mmMass})'.format(mmgMass=mmgMassGen,
mmMass=mmMassGen)
## ----------------------------------------------------------------------------
## Customize below
#srecofit.applyDefinitions([Model('cbShape')])
srecofit.applyDefinitions([DimuonMassMax(80)])
_fits = []
for subdet_r9_cat in list(subdet_r9_categories)[:]:
for lo, hi in list(BinEdges([10, 12, 15, 20, 25, 30, 100]))[:]:
for model in 'gauss cbShape bifurGauss cruijff'.split():
print '+++++', model
fit = srecofit.clone()
fit.applyDefinitions([subdet_r9_cat, PhoEtBin(lo, hi),
Model(model)])
_fits.append(fit)
maxIterations = 1
fSigma = 1.5
pullEpsilon = 0.1
mwindows = {}
## Loop over plots
for fitter in _fits[:]:
## Log the current fit configuration
print "++ Processing", fitter.title
print "++ Configuration:"
print fitter.pydump()
xUnit='%',
nBins=120,
fitRange=(-10, 5),
pdf='sech',
# graphicsExtensions = ['png'],
graphicsExtensions=[],
paramLayout=(.25, 0.55, 0.92), # x1, x2, y1
labelsLayout=(.25, 0.6), # x1, y1
)
## ----------------------------------------------------------------------------
## Customize below
_fits = []
for geant in 'g93p01 g94p02 g94cms'.split():
for lo, hi in BinEdges([0.8, 1.2, 1.5, 2, 2.5, 3, 3.5, 4, 5, 10]):
fit = srawfit.clone(source=_chains[geant])
fit.name = '_'.join([fit.name, geant])
fit.title = ', '.join([fit.title, geant])
fit.labels.append(geant)
fit.applyDefinitions([BremBin(lo, hi)])
_fits.append(fit)
maxIterations = 10
fSigma = 2.0
pullEpsilon = 0.01
mwindows = {}
## Loop over plots
for fitter in _fits[:4]:
## Log the current fit configuration
print "++ Processing", fitter.title
# fitRange = (-50, 100),
pdf="gauss",
graphicsExtensions=["png"],
# graphicsExtensions = [],
massWindowScale=1.5,
massWindow=(87.2, 95.2),
fitScale=1.2,
)
## Default fit of strue = Ereco / Egen - 1
struefit = srecofit.clone(
name="strue_mc",
title="strue-Fit, Powheg S4",
xTitle="s_{true} = E^{#gamma}_{reco}/E^{#gamma}_{gen} - 1",
xExpression="100 * (phoE/phoGenE - 1)",
xRange=(-20, 40),
nBins=(120),
fitRange=(-20, 40),
fitScale=1.2,
cuts=["isFSR", "phoGenE > 0"],
)
## Default fit of sgeb = Egen / Ekingen - 1
mu1 = "mu1Pt,mu1Eta,mu1Phi,0.1056"
mu2 = "mu2Pt,mu2Eta,mu2Phi,0.1056"
mu1gen = "mu1GenPt,mu1GenEta,mu1GenPhi,0.1056"
mu2gen = "mu2GenPt,mu2GenEta,mu2GenPhi,0.1056"
phogen = "phoGenEt,phoGenEta,phoGenPhi,0"
mmMassGen = "twoBodyMass({mu1}, {mu2})".format(mu1=mu1gen, mu2=mu2gen)
mmgMassGen = "threeBodyMass({mu1}, {mu2}, {pho})".format(mu1=mu1gen, mu2=mu2gen, pho=phogen)
mmgMassHybrid = "threeBodyMass({mu1}, {mu2}, {pho})".format(mu1=mu1, mu2=mu2, pho=phogen)
struefit = srecofit.clone(
name="strue_mc",
title="strue-Fit, Powheg S4",
labels=[],
source=_chains["z"],
xName="s",
xTitle="E/E_{true} - 1",
xExpression="100 * (phoE/phoGenE - 1)",
cuts=["isFSR", "phoGenE > 0"],
xRange=(-50, 100),
xUnit="%",
nBins=150,
pdf="gauss_an",
graphicsExtensions=["eps"],
massWindowScale=1.5,
massWindow=(70, 110),
fitScale=1.2,
fitRange=(-50, 100),
doAutoBinning=True,
binContentMax=200,
binContentMin=35,
canvasStyle="landscape",
doAutoXRange=True,
doAutoXRangeZoom=True,
doAutoFitRange=True,
xRangeSigmaLevel=5,
xRangeSigmaLevelZoom=2,
fitRangeMode="Fraction",
fitRangeSigmaLevel=2.0,
fitRangeNumberOfEntries=3000,
fitRangeFraction=1.0,
paramLayout=(0.65, 0.92, 0.85),
useCustomChi2Calculator=True,
)
xUnit = '%',
nBins = 120,
fitRange = (-10, 5),
pdf = 'sech',
# graphicsExtensions = ['png'],
graphicsExtensions = [],
paramLayout = (.25, 0.55, 0.92), # x1, x2, y1
labelsLayout = (.25, 0.6), # x1, y1
)
## ----------------------------------------------------------------------------
## Customize below
_fits = []
for geant in 'g93p01 g94p02 g94cms'.split():
for lo, hi in BinEdges([0.8,1.2,1.5,2,2.5,3,3.5,4,5,10]):
fit = srawfit.clone(source = _chains[geant])
fit.name = '_'.join([fit.name, geant])
fit.title = ', '.join([fit.title, geant])
fit.labels.append(geant)
fit.applyDefinitions([BremBin(lo, hi)])
_fits.append(fit)
maxIterations = 10
fSigma = 2.0
pullEpsilon = 0.01
mwindows = {}
## Loop over plots
for fitter in _fits[:4]:
## Log the current fit configuration
print "++ Processing", fitter.title
)
## ----------------------------------------------------------------------------
## Customize below
_fits = []
pdfs = [ROOT.TNamed('bifurGsh', 'Bifur. GSH'),
#ROOT.TNamed('gsh', 'GSH'),
#ROOT.TNamed('sech', 'Hyperbolic Secant'),
#ROOT.TNamed('cruijff', 'Cruijff'),
#ROOT.TNamed('cbShape', 'Crystal Ball'),
ROOT.TNamed('gauss', 'Gaussian'),]
for geant in 'g93p01 g94p02 g94cms'.split():
for pdf in pdfs:
for lo, hi in BinEdges([0.8,1.2,1.5,2,2.5,3,3.5,4,5,10]):
fit = sfit.clone(source = _chains[geant], pdf = pdf.GetName())
fit.name = '_'.join([fit.name, geant, fit.pdf])
fit.title = ', '.join([fit.title, geant, pdf.GetTitle()])
fit.labels.extend([geant, pdf.GetTitle()])
fit.applyDefinitions([BremBin(lo, hi)])
_fits.append(fit)
maxIterations = 1
fSigma = 2.0
pullEpsilon = 0.01
mwindows = {}
## Loop over plots
for fitter in _fits[:9]:
## Log the current fit configuration
print "++ Processing", fitter.title
