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