def dofit(self):
mi = ModalInterval(self.data)
mi.setSigmaLevel(1)
self.mode.setVal(mi.halfSampleMode())
self.effsigma.setVal(0.5 * mi.length())
self.bootdata.add(self.bootset)
resampler = Resampler(self.data)
for iboot in range(self.nboot):
mi = ModalInterval(resampler.bootstrap())
mi.setSigmaLevel(1)
self.mode.setVal(mi.halfSampleMode())
self.effsigma.setVal(0.5 * mi.length())
self.bootdata.add(self.bootset)
self.mode.setVal(self.bootdata.mean(self.mode))
self.effsigma.setVal(self.bootdata.mean(self.effsigma))
self.mode.setError(self.bootdata.rmsVar(self.mode).getVal())
self.effsigma.setError(self.bootdata.rmsVar(self.effsigma).getVal())
def dofit(self):
mi = ModalInterval(self.data)
mi.setSigmaLevel(1)
self.mode.setVal(mi.halfSampleMode())
self.effsigma.setVal(0.5 * mi.length())
self.bootdata.add(self.bootset)
resampler = Resampler(self.data)
for iboot in range(self.nboot):
mi = ModalInterval(resampler.bootstrap())
mi.setSigmaLevel(1)
self.mode.setVal(mi.halfSampleMode())
self.effsigma.setVal(0.5 * mi.length())
self.bootdata.add(self.bootset)
self.mode.setVal(self.bootdata.mean(self.mode))
self.effsigma.setVal(self.bootdata.mean(self.effsigma))
self.mode.setError(self.bootdata.rmsVar(self.mode).getVal())
self.effsigma.setError(self.bootdata.rmsVar(self.effsigma).getVal())
def test():
'''
Tests the RooRhoKeysPdf class.
'''
import FWLite.Tools.canvases as canvases
import FWLite.Tools.cmsstyle as cmsstyle
ROOT.RooRandom.randomGenerator().SetSeed(2)
global gnlls, hrhoval, hrhoerr
hrhoval = ROOT.TH1F('hrhoval', 'hrhoval', 100, 0, 5)
hrhoerr = ROOT.TH1F('hrhoerr', 'hrhoerr', 100, 0, 1)
gnlls = []
for itoy in range(1):
global w
w = ROOT.RooWorkspace('w', 'w')
# model = w.factory('Gaussian::model(x[-50, 50], mean[0], sigma[1])')
model = w.factory('BreitWigner::model(x[-5, 5], mean[0], sigma[1])')
x = w.var('x')
oset = ROOT.RooArgSet(x)
data = model.generate(oset, 1000)
w.Import(data)
# rho = w.factory('rho[1, 0, 100]')
# testpdf = RooRhoKeysPdf('testpdf', 'testpdf', x, rho, data)
# w.Import(testpdf)
testpdf = w.factory('RooRhoKeysPdf::testpdf(x, rho[1, 0, 100], modelData)')
rho = w.var('rho')
plot = x.frame()
data.plotOn(plot)
model.plotOn(plot)
testpdf.plotOn(plot, roo.LineColor(ROOT.kRed))
rho.setVal(2)
testpdf.LoadDataSet(data)
testpdf.plotOn(plot, roo.LineColor(ROOT.kGreen))
rho.setVal(3)
testpdf.LoadDataSet(data)
testpdf.plotOn(plot, roo.LineColor(ROOT.kBlack))
canvases.next('RooRhoKeysPdf_Test%d' % itoy)
plot.Draw()
canvases.update()
resampler = Resampler(data)
data0 = resampler.prescale(2, [0], 'data0')
data1 = resampler.prescale(2, [1], 'data1')
w.Import(data0)
w.Import(data1)
testpdf0 = w.factory('RooRhoKeysPdf::testpdf0(x, rho, data0)')
testpdf1 = w.factory('RooRhoKeysPdf::testpdf1(x, rho, data1)')
gnll = ROOT.TGraph()
for rhoval in [0.5 + 0.05 * i for i in range(50)]:
rho.setVal(rhoval)
testpdf0.LoadDataSet(data0)
testpdf1.LoadDataSet(data1)
nll = 0
nll += testpdf0.createNLL(data1).getVal()
nll += testpdf1.createNLL(data0).getVal()
# print rhoval, nll
gnll.SetPoint(gnll.GetN(), rhoval, nll)
locmin = ROOT.TMath.LocMin(gnll.GetN(), gnll.GetY())
xmin = gnll.GetX()[max(locmin-5, 0)]
xmax = gnll.GetX()[min(locmin+5, gnll.GetN()-1)]
fres = gnll.Fit('pol2', 's', '', xmin, xmax)
p1 = fres.Get().GetParams()[1]
p2 = fres.Get().GetParams()[2]
rhoval = - 0.5 * p1 / p2
rhoerr = 1/ROOT.TMath.Sqrt(2 * p2)
hrhoval.Fill(rhoval)
hrhoerr.Fill(rhoerr)
canvases.next('gnll%d' % itoy)
gnll.Draw('ap')
gnll.GetXaxis().SetTitle('#rho')
gnll.GetYaxis().SetTitle('- log L')
gnlls.append(gnll)
canvases.next('rhoerr')
hrhoerr.Draw()
canvases.next('rhoval')
hrhoval.Draw()
canvases.update()
from FWLite.Tools.modalinterval import ModalInterval
global mi
mi = ModalInterval(w.data('data0'))
print mi.halfSampleMode()
