def main(): dirEmbs = ["."] + [os.path.join("..", d) for d in result.dirEmbs[1:]] tauEmbedding.normalize = True tauEmbedding.era = "Run2011A" table = counter.CounterTable() for i in xrange(len(dirEmbs)): tmp = dirEmbs[:] del tmp[i] row = doCounters(tmp) row.setName("Removed embedding %d" % i) table.appendRow(row) arows = [] arows.append(counter.meanRow(table)) arows.append(counter.maxRow(table)) arows.append(counter.minRow(table)) arows.append(counter.subtractRow("Max-mean", arows[1], arows[0])) arows.append(counter.subtractRow("Mean-min", arows[0], arows[2])) for r in arows: table.appendRow(r) cellFormat = counter.TableFormatText( counter.CellFormatTeX(valueFormat='%.3f')) print "DeltaPhi < 160" print print table.format(cellFormat)
def main(): dirEmbs = ["."] + [os.path.join("..", d) for d in result.dirEmbs[1:]] tauEmbedding.normalize=True tauEmbedding.era = "Run2011A" table = counter.CounterTable() for i in xrange(len(dirEmbs)): tmp = dirEmbs[:] del tmp[i] row = doCounters(tmp) row.setName("Removed embedding %d"%i) table.appendRow(row) arows = [] arows.append(counter.meanRow(table)) arows.append(counter.maxRow(table)) arows.append(counter.minRow(table)) arows.append(counter.subtractRow("Max-mean", arows[1], arows[0])) arows.append(counter.subtractRow("Mean-min", arows[0], arows[2])) for r in arows: table.appendRow(r) cellFormat = counter.TableFormatText(counter.CellFormatTeX(valueFormat='%.3f')) print "DeltaPhi < 160" print print table.format(cellFormat)
def main(): dirEmbs = result.dirEmbs[:] if onlyWjets: dirEmbs.extend(dirEmbsWjets) dirEmbs = ["."] + [os.path.join("..", d) for d in dirEmbs[1:]] # dirEmbs = dirEmbs[0:2] style = tdrstyle.TDRStyle() tauEmbedding.normalize=normalize tauEmbedding.era = "Run2011A" ts = dataset.TreeScan(analysisEmb+"/tree", function=None, selection=And(metCut, bTaggingCut, deltaPhi160Cut)) def printPickEvent(f, tree): f.write("%d:%d:%d\n" % (tree.run, tree.lumi, tree.event)) table = counter.CounterTable() for i, d in enumerate(dirEmbs): datasets = dataset.getDatasetsFromMulticrabCfg(cfgfile=d+"/multicrab.cfg", counters=analysisEmb+"Counters") datasets.updateNAllEventsToPUWeighted() if onlyWjets: datasets.remove(filter(lambda n: n != "WJets_TuneZ2_Summer11", datasets.getAllDatasetNames())) else: if mcEvents: datasets.remove(filter(lambda n: n != "WJets_TuneZ2_Summer11" and n != "TTJets_TuneZ2_Summer11" and not "SingleMu" in n, datasets.getAllDatasetNames())) datasets.loadLuminosities() datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames())) datasets.remove(filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames())) plots.mergeRenameReorderForDataMC(datasets) # for ds in datasets.getAllDatasets(): # f = open("pickEvents_%s_%d.txt" % (ds.getName(), i), "w") # ds.getDatasetRootHisto(ts.clone(function=lambda tree: printPickEvent(f, tree))) # f.close() row = doCounters(datasets) row.setName("Embedding %d" % i) table.appendRow(row) doPlots(table) arows = [] arows.append(counter.meanRow(table)) arows.extend(counter.meanRowFit(table)) arows.append(counter.maxRow(table)) arows.append(counter.minRow(table)) for r in arows: table.appendRow(r) # csvSplitter = counter.TableSplitter([" \pm "]) # cellFormat = counter.TableFormatText(counter.CellFormatTeX(valueFormat='%.3f'), columnSeparator=",") cellFormat = counter.TableFormatText(counter.CellFormatTeX(valueFormat='%.3f')) print "DeltaPhi < 160" print print table.format(cellFormat)
def do(onlyWjets, mcEvents, normalize, formatCounters, formatPlots): dirEmbs = tauEmbedding.dirEmbs[:] if onlyWjets: dirEmbs.extend(dirEmbsWjets) dirEmbs = ["."] + [os.path.join("..", d) for d in dirEmbs[1:]] # dirEmbs = dirEmbs[0:2] # Read luminosity datasets = dataset.getDatasetsFromMulticrabCfg(cfgfile=dirEmbs[0]+"/multicrab.cfg", counters=analysisEmb+"Counters", weightedCounters=False) datasets.loadLuminosities() plots.mergeRenameReorderForDataMC(datasets) lumi = datasets.getDataset("Data").getLuminosity() style = tdrstyle.TDRStyle() histograms.cmsTextMode = histograms.CMSMode.SIMULATION histograms.cmsText[histograms.cmsTextMode] = "Simulation" tauEmbedding.normalize=normalize tauEmbedding.era = "Run2011A" table = counter.CounterTable() for i, d in enumerate(dirEmbs): datasets = dataset.getDatasetsFromMulticrabCfg(cfgfile=d+"/multicrab.cfg", counters=analysisEmb+"Counters", weightedCounters=False) if onlyWjets: datasets.remove(filter(lambda n: n != "WJets_TuneZ2_Summer11", datasets.getAllDatasetNames())) else: if mcEvents: datasets.remove(filter(lambda n: n != "WJets_TuneZ2_Summer11" and n != "TTJets_TuneZ2_Summer11" and not "SingleMu" in n, datasets.getAllDatasetNames())) datasets.loadLuminosities() datasets.remove(filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames())) datasets.remove(filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames())) tauEmbedding.updateAllEventsToWeighted(datasets) plots.mergeRenameReorderForDataMC(datasets) row = doCounters(datasets, onlyWjets, mcEvents, normalize, lumi) row.setName("Embedding %d" % i) table.appendRow(row) if formatPlots: doPlots(table, onlyWjets, mcEvents, normalize, lumi) if not formatCounters: return arows = [] arows.append(counter.meanRow(table)) arows.extend(counter.meanRowFit(table)) arows.append(counter.maxRow(table)) arows.append(counter.minRow(table)) for r in arows: table.appendRow(r) print table.format() ftable = counter.CounterTable() def addRow(name): col = table.getColumn(name=name) minimum = col.getCount(name="Min") maximum = col.getCount(name="Max") mean = col.getCount(name="Mean") ftable.appendRow(counter.CounterRow(name, ["Mean", "Minimum", "Maximum"], [mean, minimum, maximum])) addRow("Data") addRow("EWKMCsum") addRow("TTJets") addRow("WJets") addRow("DYJetsToLL") addRow("SingleTop") addRow("Diboson") cellFormat2 = counter.TableFormatLaTeX(counter.CellFormatTeX(valueFormat="%.4f", withPrecision=2)) print ftable.format(cellFormat2)
def main(): dirEmbs = result.dirEmbs[:] if onlyWjets: dirEmbs.extend(dirEmbsWjets) dirEmbs = ["."] + [os.path.join("..", d) for d in dirEmbs[1:]] # dirEmbs = dirEmbs[0:2] style = tdrstyle.TDRStyle() tauEmbedding.normalize = normalize tauEmbedding.era = "Run2011A" ts = dataset.TreeScan(analysisEmb + "/tree", function=None, selection=And(metCut, bTaggingCut, deltaPhi160Cut)) def printPickEvent(f, tree): f.write("%d:%d:%d\n" % (tree.run, tree.lumi, tree.event)) table = counter.CounterTable() for i, d in enumerate(dirEmbs): datasets = dataset.getDatasetsFromMulticrabCfg( cfgfile=d + "/multicrab.cfg", counters=analysisEmb + "Counters") if onlyWjets: datasets.remove( filter(lambda n: n != "WJets_TuneZ2_Summer11", datasets.getAllDatasetNames())) else: if mcEvents: datasets.remove( filter( lambda n: n != "WJets_TuneZ2_Summer11" and n != "TTJets_TuneZ2_Summer11" and not "SingleMu" in n, datasets.getAllDatasetNames())) datasets.loadLuminosities() datasets.remove( filter(lambda name: "HplusTB" in name, datasets.getAllDatasetNames())) datasets.remove( filter(lambda name: "TTToHplus" in name, datasets.getAllDatasetNames())) tauEmbedding.updateAllEventsToWeighted(datasets) plots.mergeRenameReorderForDataMC(datasets) # for ds in datasets.getAllDatasets(): # f = open("pickEvents_%s_%d.txt" % (ds.getName(), i), "w") # ds.getDatasetRootHisto(ts.clone(function=lambda tree: printPickEvent(f, tree))) # f.close() row = doCounters(datasets) row.setName("Embedding %d" % i) table.appendRow(row) doPlots(table) arows = [] arows.append(counter.meanRow(table)) arows.extend(counter.meanRowFit(table)) arows.append(counter.maxRow(table)) arows.append(counter.minRow(table)) for r in arows: table.appendRow(r) # csvSplitter = counter.TableSplitter([" \pm "]) # cellFormat = counter.TableFormatText(counter.CellFormatTeX(valueFormat='%.3f'), columnSeparator=",") cellFormat = counter.TableFormatText( counter.CellFormatTeX(valueFormat='%.3f')) print "DeltaPhi < 160" print print table.format(cellFormat)
def main(): dirEmbs = ["."] + [os.path.join("..", d) for d in tauEmbedding.dirEmbs[1:]] # dirEmbs = dirEmbs[:2] tauEmbedding.normalize=True tauEmbedding.era = "Run2011A" table = counter.CounterTable() for i in xrange(len(dirEmbs)): tmp = dirEmbs[:] del tmp[i] row = doCounters(tmp) row.setName("Removed embedding %d"%i) table.appendRow(row) arows = [] arows.append(counter.meanRow(table)) arows.append(counter.maxRow(table)) arows.append(counter.minRow(table)) arows.append(counter.subtractRow("Max-mean", arows[1], arows[0])) arows.append(counter.subtractRow("Mean-min", arows[0], arows[2])) for r in arows: table.appendRow(r) cellFormat = counter.TableFormatText(counter.CellFormatTeX(valueFormat='%.3f')) print "DeltaPhi < 160" print print table.format(cellFormat) print print # Format the table as in AN ftable = counter.CounterTable() def addRow(name): col = table.getColumn(name=name) minimum = col.getCount(name="Min") maximum = col.getCount(name="Max") # Maximum deviation from average dev1 = col.getCount(name="Max-mean") dev2 = col.getCount(name="Mean-min") if dev2.value() > dev1.value(): dev1 = dev2 dev1.divide(col.getCount(name="Mean")) dev1.multiply(dataset.Count(100)) ftable.appendRow(counter.CounterRow(name, ["Minimum", "Maximum", "Largest deviation from average (%)"], [minimum, maximum, dev1])) addRow("Data") addRow("EWKMCsum") addRow("TTJets") addRow("WJets") addRow("DYJetsToLL") addRow("SingleTop") addRow("Diboson") cellFormat2 = counter.TableFormatLaTeX(counter.CellFormatTeX(valueFormat="%.4f", withPrecision=2)) cellFormat2.setColumnFormat(counter.CellFormatTeX(valueFormat="%.1f", valueOnly=True), index=2) print ftable.format(cellFormat2)