startTime_processor = time.clock() filename_id = "seed{:0.0f}_noise{:0.0f}_signal{:0.0f}_digitization{:0.0f}".format(args.seedEt_thresh, args.noise_filter, args.tower_thresh, args.digitization) filename = "data/seed{:0.0f}/leading_jets_{}.pkl".format(args.seedEt_thresh, filename_id) data = pickle.load(file(filename)) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ((endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr) tJetEt_correction = np.zeros(data.size) tJetEt_subtracted = np.zeros(data.size) # the new regions aren't working because there are not enough jets in them!!! regions = {1: '', 2: '', 3: '', 4: '', '3a': '', '3b': '', '3c': '', '4a': '', '4b': '', '4c': ''} for region in regions.keys(): region_cut = helpers.region_cut(data['tJet.eta'], region) regions[region] = region_cut if region not in [1, 2, 3, 4]: region_parsed = int(region[0]) else: region_parsed = region
filename_id = "seed{:0.0f}_noise{:0.0f}_signal{:0.0f}_digitization{:0.0f}".format(args.seedEt_thresh, args.noise_filter, args.tower_thresh, args.digitization) filename = "plots/subjets/{}.pkl".format(filename_id) signal = pickle.load(file('../ttbar/{}'.format(filename))) background = pickle.load(file('../dijets/{}'.format(filename))) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ((endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr, labelsize=28) PtCutLabel = "$250\ \mathrm{GeV}\ \leq P_T^\mathrm{oJet} \leq\ 500\ \mathrm{GeV}$" MassCutLabel = "$100\ \mathrm{GeV}\ \leq m^\mathrm{oJet} \leq\ 220\ \mathrm{GeV}$" dataStorage = {} def rescaleY(y, option="fake rate"): validOptions = ["fake rate", "rejection", "purity"] if option == "fake rate": return y elif option == "rejection": return 1./y elif option == "purity": return 1.-y
signal = pickle.load(file('../ttbar/{}'.format(filename))) background = pickle.load(file('../dijets/{}'.format(filename))) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ( (endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr, labelsize=28) PtCutLabel = "$250\ \mathrm{GeV}\ \leq P_T^\mathrm{oJet} \leq\ 500\ \mathrm{GeV}$" MassCutLabel = "$100\ \mathrm{GeV}\ \leq m^\mathrm{oJet} \leq\ 220\ \mathrm{GeV}$" dataStorage = {} def rescaleY(y, option="fake rate"): validOptions = ["fake rate", "rejection", "purity"] if option == "fake rate": return y elif option == "rejection": return 1. / y
args.seedEt_thresh, filename_id) data = pickle.load(file(filename)) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ( (endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr, labelsize=28) tJet_exists = data['tJet.et'] > 0. bins_efficiency = np.arange(0., 2000., 10.) width_efficiency = np.array( [x - bins_efficiency[i - 1] for i, x in enumerate(bins_efficiency)][1:]) bins_multiplicity = np.arange(0.0, 1024.0, 32.0) bins_rho = np.arange(0., 70., 0.5) bins_vertices = np.arange(0., 100., 1.) startTime_wall = time.time() startTime_processor = time.clock()
startTime_processor = time.clock() filename_id = "seed{:0.0f}_noise{:0.0f}_signal{:0.0f}_digitization{:0.0f}".format(args.seedEt_thresh, args.noise_filter, args.tower_thresh, args.digitization) filename = "data/seed{:0.0f}/leading_jets_{}.pkl".format(args.seedEt_thresh, filename_id) data = pickle.load(file(filename)) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ((endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr) startTime_wall = time.time() startTime_processor = time.clock() # buildin plots for pt print "pt combined" fig, ax = pl.subplots(figsize=helpers.figsize) n, bins, weightedPatches = ax.hist(data['oJet.pt'], weights=data['weight'], bins=np.arange(0, 500, 2), stacked=True, fill=False, histtype='step', color='b', label=r'weighted', linewidth=helpers.linewidth, alpha=0.75) axt = ax.twinx() n, bins, unweightedPatches = axt.hist(data['oJet.pt'], bins=np.arange(0, 500, 2), stacked=True, fill=False, histtype='step', color='r', label=r'unweighted', linewidth=helpers.linewidth, alpha=0.75) # http://matplotlib.org/examples/api/two_scales.html for tl in ax.get_yticklabels(): tl.set_color('b')
startTime_processor = time.clock() filename_id = "seed{:0.0f}_noise{:0.0f}_signal{:0.0f}_digitization{:0.0f}".format(args.seedEt_thresh, args.noise_filter, args.tower_thresh, args.digitization) filename = "data/seed{:0.0f}/leading_jets_{}.pkl".format(args.seedEt_thresh, filename_id) data = pickle.load(file(filename)) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ((endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr) startTime_wall = time.time() startTime_processor = time.clock() # standard kinematic plots fig, ax = pl.subplots(figsize=helpers.figsize) n, bins, unweightedPatches = ax.hist(data['oJet.pt'], bins=np.arange(0, 500, 2), label='unweighted', stacked=True, fill=False, histtype='step', alpha=0.75, color='r') axt = ax.twinx() n, bins, weightedPatches = axt.hist(data['oJet.pt'], weights=data['weight'], bins=np.arange(0, 500, 2), label='weighted', stacked=True, fill=False, histtype='step', alpha=0.75, color='b') # http://matplotlib.org/examples/api/two_scales.html for tl in ax.get_yticklabels(): tl.set_color('r') for tl in axt.get_yticklabels(): tl.set_color('b')
filename = "data/seed{:0.0f}/leading_jets_{}.pkl".format( args.seedEt_thresh, filename_id) data = pickle.load(file(filename)) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ( (endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr) startTime_wall = time.time() startTime_processor = time.clock() # buildin plots for pt print "pt combined" fig, ax = pl.subplots(figsize=helpers.figsize) n, bins, weightedPatches = ax.hist(data['oJet.pt'], weights=data['weight'], bins=np.arange(0, 500, 2), stacked=True, fill=False, histtype='step', color='b',
startTime_processor = time.clock() filename_id = "seed{:0.0f}_noise{:0.0f}_signal{:0.0f}_digitization{:0.0f}".format(args.seedEt_thresh, args.noise_filter, args.tower_thresh, args.digitization) filename = "data/seed{:0.0f}/leading_jets_{}.pkl".format(args.seedEt_thresh, filename_id) data = pickle.load(file(filename)) endTime_wall = time.time() endTime_processor = time.clock() print "Finished reading in data:\n\t Wall time: %0.2f s \n\t Clock Time: %0.2f s" % ((endTime_wall - startTime_wall), (endTime_processor - startTime_processor)) dataSetStr = plotConfigs.dataSetStr seedCutStr = '$E_T^\mathrm{seed} >\ %d\ \mathrm{GeV}$' % args.seedEt_thresh noiseCutStr = '$E_T^\mathrm{tower} >\ %d\ \mathrm{GeV}$' % args.noise_filter towerThrStr = '$\\rho\left(E_T^\mathrm{tower} <\ %d\ \mathrm{GeV}\\right)$' % args.tower_thresh helpers = PlotHelpers(dataSetStr=dataSetStr, seedCutStr=seedCutStr, noiseCutStr=noiseCutStr, towerThrStr=towerThrStr, labelsize=28) tJet_exists = data['tJet.et'] > 0. bins_efficiency = np.arange(0., 2000., 10.) width_efficiency = np.array([x - bins_efficiency[i-1] for i, x in enumerate(bins_efficiency)][1:]) bins_multiplicity = np.arange(0.0, 1024.0, 32.0) bins_rho = np.arange(0., 70., 0.5) bins_vertices = np.arange(0., 100., 1.) startTime_wall = time.time() startTime_processor = time.clock() try: print "gTower multiplicity"