def main():
'''
Main entry point of execution.
'''
make_scale_plots()
make_resolution_plots()
canvases.make_plots("png eps root".split())
def main():
'''
Main entry point of execution
'''
do_barrel_highr9_lownv_fits()
do_barrel_highr9_highnv_fits()
do_barrel_lowr9_lownv_fits()
do_barrel_lowr9_highnv_fits()
do_endcap_highr9_lownv_fits()
do_endcap_highr9_highnv_fits()
do_endcap_lowr9_lownv_fits()
do_endcap_lowr9_highnv_fits()
do_barrel_lowr9_fits()
do_barrel_highr9_fits()
do_endcap_lowr9_fits()
do_endcap_highr9_fits()
do_barrel_lownv_fits()
do_barrel_highnv_fits()
do_endcap_lownv_fits()
do_endcap_highnv_fits()
report_noise_terms()
canvases.make_plots("png eps root".split())
def outro():
'Closing stuff'
canvases.update()
canvases.make_plots(['png', 'eps'])
for c in canvases.canvases:
if c:
w.Import(c, 'c_' + c.GetName())
w.writeToFile(outputfile)
def outro(make_plots=True, save_workspace=True):
'Closing stuff'
canvases.update()
if make_plots:
canvases.make_plots(['png', 'eps'])
if save_workspace:
for c in canvases.canvases:
if c:
w.Import(c, 'c_' + c.GetName())
w.writeToFile(outputfile, False)
check_timer('14. outro')
ct, rt = sw2.CpuTime(), sw2.RealTime()
print '+++ TOTAL CPU time:', ct, 's, real time: %.2f' % rt, 's'
def outro(make_plots=True, save_workspace=True):
"Closing stuff"
canvases.update()
if make_plots:
canvases.make_plots(["png", "eps"])
if save_workspace:
for c in canvases.canvases:
if c:
w.Import(c, "c_" + c.GetName())
w.writeToFile(outputfile, False)
check_timer("14. outro")
ct, rt = sw2.CpuTime(), sw2.RealTime()
print "+++ TOTAL CPU time:", ct, "s, real time: %.2f" % rt, "s"
import JPsi.MuMu.common.cmsstyle as cmsstyle
# target_dir_glob_pattern = '/Users/veverka/Desktop/PHOSPHOR/v2/*/*'
# target_dir_glob_pattern = '/home/veverka/jobs/outputs/htozg_v1/*_yyv5'
target_dir_glob_pattern = '/home/veverka/jobs/outputs/lyon_test/*/*'
for path in glob.glob(target_dir_glob_pattern):
for fname in glob.glob(os.path.join(path, '*_landscape.root')):
print fname
rootfile = ROOT.TFile.Open(fname)
cname = os.path.splitext(os.path.basename(fname))[0]
canvas = rootfile.Get(cname)
canvas.Draw()
canvas.SetWindowSize(1200, 600)
canvases.canvases.append(canvas)
for mask in 'data combo logy fit phor phorhist'.split():
for fname in glob.glob(os.path.join(path, '*_%s.root' % mask)):
print fname
rootfile = ROOT.TFile.Open(fname)
cname = os.path.splitext(os.path.basename(fname))[0]
canvas = rootfile.Get(cname)
canvas.Draw()
canvas.SetWindowSize(600, 400)
canvases.canvases.append(canvas)
canvases.update()
canvases.make_plots('png pdf'.split(), path=path)
del canvases.canvases[:]
## Model for the reconstructed mmg mass of the ISR through transformation
# mmgMassIsrPdf = ROOT.RooFFTConvPdf('mmgMassIsrPdf', 'mmgMassIsrPdf', mmMassFunc,
# mmMass, zmmGenShape, mmMassRes)
mmgMassPdf = w.factory('Voigtian::mmgMassPdf(mmMassFunc, mmMean, GZ, mmRes)')
## Plot the mmg mass data and model overlaid without fitting (!)
mmgPlot = mmgMass.frame(roofit.Range(60, 200))
isrData.plotOn(mmgPlot)
isrData_m1gOplusM2g = isrData.reduce(ROOT.RooArgSet(m1gOplusM2g))
isrData_m1gOplusM2g_binned = isrData_m1gOplusM2g.binnedClone()
isrData_m1gOplusM2g.get().find('m1gOplusM2g').setBins(40)
isrData_m1gOplusM2g_binned2 = isrData_m1gOplusM2g.binnedClone()
# mmgMassPdf.plotOn(mmgPlot, roofit.ProjWData(isrData_m1gOplusM2g),
# roofit.LineColor(ROOT.kRed))
mmgMassPdf.plotOn(mmgPlot, roofit.ProjWData(isrData_m1gOplusM2g_binned),
roofit.LineColor(ROOT.kRed))
mmgMassPdf.plotOn(mmgPlot, roofit.ProjWData(isrData_m1gOplusM2g_binned2),
roofit.LineStyle(ROOT.kDashed))
canvases.next('mmgMass')
mmgPlot.Draw()
for c in canvases.canvases:
c.Update()
canvases.make_plots()
if __name__ == '__main__':
import user
canvases.next(name + '_nll_vs_phor_zoom').SetGrid()
plot = pm.w.var('phoRes').frame(roo.Range(*get_confint(phoRes,1.5)))
nll.plotOn(plot, roo.ShiftToZero())
# plot.GetYaxis().SetRangeUser(0, 10)
plot.Draw()
canvases.next(name + '_nll2d').SetGrid()
h2nll = nll.createHistogram('h2nll', phoScale,
roo.Binning(40, *get_confint(phoScale, 2)),
roo.YVar(phoRes,
roo.Binning(40, *get_confint(phoRes, 2))))
h2nll.Draw('colz')
##------------------------------------------------------------------------------
canvases.update()
canvases.make_plots('png')
canvases.make_plots('eps')
for c in canvases.canvases:
if c:
w.Import(c, 'c_' + c.GetName())
w.writeToFile(outputfile)
if __name__ == '__main__':
# main()
import user
## Model for the reconstructed mmg mass of the ISR through transformation
# mmgMassIsrPdf = ROOT.RooFFTConvPdf('mmgMassIsrPdf', 'mmgMassIsrPdf', mmMassFunc,
# mmMass, zmmGenShape, mmMassRes)
mmgMassPdf = w.factory('Voigtian::mmgMassPdf(mmMassFunc, mmMean, GZ, mmRes)')
## Plot the mmg mass data and model overlaid without fitting (!)
mmgPlot = mmgMass.frame(roofit.Range(60,200))
isrData.plotOn(mmgPlot)
isrData_m1gOplusM2g = isrData.reduce(ROOT.RooArgSet(m1gOplusM2g))
isrData_m1gOplusM2g_binned = isrData_m1gOplusM2g.binnedClone()
isrData_m1gOplusM2g.get().find('m1gOplusM2g').setBins(40)
isrData_m1gOplusM2g_binned2 = isrData_m1gOplusM2g.binnedClone()
# mmgMassPdf.plotOn(mmgPlot, roofit.ProjWData(isrData_m1gOplusM2g),
# roofit.LineColor(ROOT.kRed))
mmgMassPdf.plotOn(mmgPlot, roofit.ProjWData(isrData_m1gOplusM2g_binned),
roofit.LineColor(ROOT.kRed))
mmgMassPdf.plotOn(mmgPlot, roofit.ProjWData(isrData_m1gOplusM2g_binned2),
roofit.LineStyle(ROOT.kDashed))
canvases.next('mmgMass')
mmgPlot.Draw()
for c in canvases.canvases:
c.Update()
canvases.make_plots()
if __name__ == '__main__':
import user
