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)
