def getTreeFromJob(self, job, dilepton, cut="", useNLL=False):
if len(self.runRanges) > 1:
log.logError("Should only have one runRange when calling getTreeFromJob")
runRange = self.runRanges[0]
if useNLL:
path = locations[runRange.era].dataSetPathNLL
else:
path = locations[runRange.era].dataSetPath
tree = ROOT.TChain()
tree.Add(readTrees(path, dilepton)[job])
cut = cut + runRange.runCut
if useNLL:
cut = cut + " && vetoHEM == 1"
if (cut != ""):
log.logDebug("Cutting tree down to: %s" % cut)
if tree.GetEntries() > 0:
tree = tree.CopyTree(cut)
log.logError("Tree size: %d entries" % (tree.GetEntries()))
if (tree != None):
tree.SetDirectory(0)
return tree
def __init__(self, histogram):
if (histogram == None):
log.logWarning("Creating a result from an empty histogram.")
# default configuration
self.dataName = "None"
self.dataVersion = "None"
self.taskName = "None"
self.flagName = "None"
self.dataType = InfoHolder.DataTypes.Unknown
self.is2DHistogram = False
self.scaled = False
self.histogram = histogram
#self.histogram.Sumw2()
self.unscaledIntegral = -1
self.scalingFactor = -1
self.luminosity = -1
self.xSection = -1
self.kFactor = -1
self.nEvents = -1
self.__scaledAndAdded = False
self.currentIntegralError = -1
self.title = None
#log.logDebug("%s" % type(histogram))
self.is2DHistogram = False
if (type(histogram) == ROOT.TH2F):
log.logDebug("2D histogram found: %s" % type(histogram))
self.is2DHistogram = True
def getSignalTreeFromJob(self, job, dilepton, cut="", useNLL=False):
if len(self.runRanges) > 1:
log.logError("Should only have one runRange when calling getTreeFromJob")
runRange = self.runRanges[0]
signalType = job.split("_")[0]
append = {}
append["2016"] = "_Summer16"
append["2017"] = "_Fall17"
append["2018"] = "_Autumn18"
if useNLL:
path = locations[runRange.era]["dataSetPathSignalNLL%s"%signalType]
else:
path = locations[runRange.era]["dataSetPathSignal%s"%signalType]
tree = ROOT.TChain()
tree.Add(readTrees(path, dilepton)[job+append[runRange.era]])
if (cut != ""):
log.logDebug("Cutting tree down to: %s" % cut)
if tree.GetEntries() > 0:
tree = tree.CopyTree(cut)
log.logError("Tree size: %d entries" % (tree.GetEntries()))
if (tree != None):
tree.SetDirectory(0)
return tree
def isHistogramInFile(self, fileName, path):
log.logDebug("Checking path '%s'\n in file %s" % (path, fileName))
file = TFile(fileName, 'READ')
path = file.Get(path)
return (path != None)
def runSoftsusy(parameters): """ parameters: dict holding all information needed to run SOSTUSY for one point result: dict of resulting mass spectrum """ from subprocess import Popen, PIPE #softpoint.x sugra <m0> <m12> <a0> <tanb> <mgut> <sgnMu> template = "%(path)s %(mode)s %(m0)s %(m12)s %(A0)s %(tanb)s %(mgut)s %(sgnMu)s" log.logDebug(template%parameters) proc = Popen(template%parameters, shell=True, stdout=PIPE, stderr=PIPE) slha = proc.communicate()[0] return slha
def getHistogramFromFile(self, fileName, histoPath):
log.logDebug("Getting histogram '%s'\n from file %s" % (histoPath, fileName))
file = TFile(fileName, 'READ')
histogram = file.Get(histoPath)
if (histogram == None):
log.logError("Could not get histogram '%s'\n from file %s" % (histoPath, fileName))
file.Close()
return None
else:
histogram.SetDirectory(0)
histogram.Sumw2()
file.Close()
return histogram
def getTrees(theConfig, datasets, central=True):
import dataInterface
#~ theDataInterface = dataInterface.dataInterface(dataVersion=dataVersion)
theDataInterface = dataInterface.DataInterface(theConfig.dataSetPath,theConfig.dataVersion)
treePathOFOS = "/EMuDileptonTree"
treePathEE = "/EEDileptonTree"
treePathMM = "/MuMuDileptonTree"
treesMCOFOS = ROOT.TList()
treesMCEE = ROOT.TList()
treesMCMM = ROOT.TList()
if central:
cut = theConfig.selection.cut + " && abs(eta1) < 1.4 && abs(eta2) < 1.4"
else:
cut = theConfig.selection.cut + " && 1.6 <= TMath::Max(abs(eta1),abs(eta2)) && !(abs(eta1) > 1.4 && abs(eta1) < 1.6) && !(abs(eta2) > 1.4 && abs(eta2) < 1.6)"
for dataset in datasets:
scale = 0.0
# dynamic scaling
jobs = dataInterface.InfoHolder.theDataSamples[theConfig.dataVersion][dataset]
if (len(jobs) > 1):
log.logDebug("Scaling and adding more than one job: %s" % (jobs))
for job in jobs:
treeMCOFOSraw = theDataInterface.getTreeFromJob(theConfig.flag, theConfig.task, job, treePathOFOS, dataVersion=theConfig.dataVersion, cut=theConfig.selection.cut)
treeMCEEraw = theDataInterface.getTreeFromJob(theConfig.flag, theConfig.task, job, treePathEE, dataVersion=theConfig.dataVersion, cut=theConfig.selection.cut)
treeMCMMraw = theDataInterface.getTreeFromJob(theConfig.flag, theConfig.task, job, treePathMM, dataVersion=theConfig.dataVersion, cut=theConfig.selection.cut)
dynNTotal = theDataInterface.getEventCount(job, theConfig.flag, theConfig.task)
dynXsection = theDataInterface.getCrossSection(job)
dynScale = dynXsection * theConfig.runRange.lumi / dynNTotal
if (dynScale != scale):
log.logInfo("dyn scale for %s (%s): n = %d, x = %f => %f" % (job, dataset, dynNTotal, dynXsection, dynScale))
scale = dynScale
else:
log.logError("No dynamic scale applied. This should never happen!")
# convert trees
treesMCOFOS.Add(dataInterface.DataInterface.convertDileptonTree(treeMCOFOSraw, weight=scale))
treesMCEE.Add(dataInterface.DataInterface.convertDileptonTree(treeMCEEraw, weight=scale))
treesMCMM.Add(dataInterface.DataInterface.convertDileptonTree(treeMCMMraw, weight=scale))
treeMCOFOStotal = ROOT.TTree.MergeTrees(treesMCOFOS)
treeMCEEtotal = ROOT.TTree.MergeTrees(treesMCEE)
treeMCMMtotal = ROOT.TTree.MergeTrees(treesMCMM)
return (treeMCOFOStotal, treeMCEEtotal, treeMCMMtotal)
def convertDileptonTree(tree, nMax= -1, weight=1.0, selection="", weightString=""):
# TODO: make selection more efficient
log.logDebug("Converting DileptonTree")
data = MyDileptonTreeFormat()
newTree = ROOT.TTree("treeInvM", "Dilepton Tree")
newTree.SetDirectory(0)
newTree.Branch("inv", ROOT.AddressOf(data, "inv"), "inv/D")
newTree.Branch("chargeProduct", ROOT.AddressOf(data, "chargeProduct"), "chargeProduct/D")
newTree.Branch("nJets", ROOT.AddressOf(data, "nJets"), "nJets/I")
newTree.Branch("ht", ROOT.AddressOf(data, "ht"), "ht/D")
newTree.Branch("met", ROOT.AddressOf(data, "met"), "met/D")
newTree.Branch("MT2", ROOT.AddressOf(data, "MT2"), "MT2/D")
newTree.Branch("pt1", ROOT.AddressOf(data, "pt1"), "pt1/D")
newTree.Branch("pt2", ROOT.AddressOf(data, "pt2"), "pt2/D")
newTree.Branch("weight", ROOT.AddressOf(data, "weight"), "weight/D")
# only part of tree?
iMax = tree.GetEntries()
if (nMax != -1):
iMax = min(nMax, iMax)
# Fill tree
for i in xrange(iMax):
if (tree.GetEntry(i) > 0):
### depending on the sample we have to switch between p4.M() and mll
#~ data.inv = tree.p4.M()
data.inv = tree.mll
data.chargeProduct = tree.chargeProduct
data.nJets = tree.nJets
data.ht = tree.ht
data.met = tree.met
data.MT2 = tree.MT2
data.pt1 = tree.pt1
data.pt2 = tree.pt2
if (weightString != ""):
eventWeight = eval(weightString)
data.weight = eventWeight
else:
data.weight = weight
newTree.Fill()
#return newTree
return newTree.CopyTree(selection)
def stringJESConversion(string, up=True):
JESUncertainty = 0.075
value = "%s" % string
if (up):
log.logInfo("Scaling up: %s" % JESUncertainty)
value = value.replace("ht", "%f * ht" % (1.0 + JESUncertainty))
value = value.replace("met", "%f * met" % (1.0 + JESUncertainty))
value = value.replace("jet1pt", "%f * jet1pt" % (1.0 + JESUncertainty))
value = value.replace("jet2pt", "%f * jet2pt" % (1.0 + JESUncertainty))
value = value.replace("jet3pt", "%f * jet3pt" % (1.0 + JESUncertainty))
value = value.replace("jet4pt", "%f * jet4pt" % (1.0 + JESUncertainty))
else:
log.logInfo("Scaling down: %s" % JESUncertainty)
value = value.replace("ht", "%f * ht" % (1.0 - JESUncertainty))
value = value.replace("met", "%f * met" % (1.0 - JESUncertainty))
value = value.replace("jet1pt", "%f * jet1pt" % (1.0 - JESUncertainty))
value = value.replace("jet2pt", "%f * jet2pt" % (1.0 - JESUncertainty))
value = value.replace("jet3pt", "%f * jet3pt" % (1.0 - JESUncertainty))
value = value.replace("jet4pt", "%f * jet4pt" % (1.0 - JESUncertainty))
log.logDebug("Converting '%s' into '%s'." % (string, value))
return value
def parseSLHA(slha, pdgIds=[24]):
"""
parse SUSY Les Houches Accord (SLHA) formated strings (e.g. SOFTSUSY output)
"""
from re import match
result = {}
massBlock = ""
block = None
for line in slha.splitlines():
blockRe = match("Block ([a-zA-Z]+).*", line)
if not blockRe == None:
block = blockRe.group(1)
if block == "MASS":
for pdgId in pdgIds:
pdgIdRe = match("\s*%s\s*([0-9.e\+-]+)"%pdgId, line)
if not pdgIdRe == None:
result[pdgId] = float(pdgIdRe.group(1))
for pdgId in pdgIds:
if not pdgId in result:
log.logError("could not find %s"%pdgId)
log.logDebug(slha)
return result
def getTreeFromDataset(self, dataset, dilepton, cut="", useNLL=False):
tree = ROOT.TChain()
baseCut = cut
for runRange in self.runRanges:
if useNLL:
path = locations[runRange.era].dataSetPathNLL
else:
path = locations[runRange.era].dataSetPath
log.logDebug("Adding %s tree from %s"%(dataset, path))
ROOT.TH1.AddDirectory(False)
tmpTree = readTrees(path, dilepton)[dataset]
ROOT.TH1.AddDirectory(True)
tree.Add(tmpTree)
runCuts = []
runCut = ""
for runRange in self.runRanges:
runCuts.append(runRange.runCut[3:])
if useNLL:
runCuts.append("vetoHEM == 1")
runCut = "&& (%s)"%(" || ".join(runCuts))
cut = cut + runCut
print tree.GetEntries()
if (cut != ""):
log.logDebug("Cutting tree down to: %s" % cut)
#tree = tree.CopyTree(cut, "", 1000)
tree = tree.CopyTree(cut)
#log.logError("Tree size: %d entries" % (tree.GetEntries()))
if (tree != None):
tree.SetDirectory(0)
else:
log.logError("Tree invalid")
return tree
def provideNCanvas(n=2, title="Same Sign Dilepton SUSY analysis"):
if (n < 1):
log.logError("'%d' is not a valid number of pads!")
return None
if (n == 1):
[c1, pad1, pad2] = provideDoubleCanvas()
return [c1, [pad1]]
if (n == 2):
[c1, pad1, pad2] = provideDoubleCanvas()
return [c1, [pad1, pad2]]
if (n == 3):
[c1, pad1, pad2, pad3, pad4] = provideQuadCanvas()
return [c1, [pad1, pad2, pad3]]
if (n == 4):
[c1, pad1, pad2, pad3, pad4] = provideQuadCanvas()
return [c1, [pad1, pad2, pad3, pad4]]
# window settings
theCanvasSizeX = 1520
theCanvasSizeY = 920
theScreenSizeX = 1680
theScreenSizeY = 1050
# canvas
posX = int(theScreenSizeX * 0.04)
posY = int(theScreenSizeY * 0.03)
#posX = (theScreenSizeX - theCanvasSizeX) / 2
#posY = (theScreenSizeY - theCanvasSizeY) / 2
c1 = TCanvas('c1', title, posX, posY, theCanvasSizeX, theCanvasSizeY)
i = int(math.ceil(-0.5 + 0.5 * math.sqrt(4.0 * n + 1.0)))
nRows = i
nColumns = i + 1
log.logDebug("no. of columns: %d" % nColumns)
log.logDebug("no. of rows: %d" % nRows)
c1.Divide(nColumns, nRows, 0.0001, 0.0001)
pads = []
iPad = 1
for iRow in range(0, nRows):
for iColumn in range(0, nColumns):
if (iPad <= n):
c1.cd(iPad)
pad = TPad('pad%d' % iPad, 'Pad for %dth histogram' % iPad,
0.03, 0.03, 0.97, 0.97, 0)
pad.Draw()
pads.extend([pad])
iPad += 1
log.logDebug("Pads: %s" % pads)
return [c1, pads]
def getTrees(theConfig, datasets, useNLL=False):
import dataInterface
treesMCEM = ROOT.TList()
treesMCEE = ROOT.TList()
treesMCMM = ROOT.TList()
runRanges = theConfig.runRanges
cut = theConfig.selection.cut
for runRange in runRanges:
theDataInterface = dataInterface.DataInterface([
runRange,
])
for dataset in datasets:
scale = 0.0
# dynamic scaling
eventCounts = totalNumberOfGeneratedEvents(
locations[runRange.era].dataSetPath)
proc = Process(getattr(Backgrounds[runRange.era], dataset),
eventCounts)
if (len(proc.samples) > 1):
log.logDebug("Scaling and adding more than one job: %s" %
(proc.samples))
for job, dynNTotal, dynXsection, dynNegWeightFraction in zip(
proc.samples, proc.nEvents, proc.xsecs,
proc.negWeightFractions):
treeMCEMraw = theDataInterface.getTreeFromJob(job,
"EMu",
cut=cut,
useNLL=useNLL)
treeMCEEraw = theDataInterface.getTreeFromJob(job,
"EE",
cut=cut,
useNLL=useNLL)
treeMCMMraw = theDataInterface.getTreeFromJob(job,
"MuMu",
cut=cut,
useNLL=useNLL)
#~ dynScale = dynXsection * theConfig.runRange.lumi / dynNTotal
print runRange.lumi
dynScale = dynXsection * runRange.lumi / (
dynNTotal * (1 - 2 * dynNegWeightFraction))
if (dynScale != scale):
log.logInfo(
"dyn scale for %s (%s): n = %d, x = %f => %f" %
(job, dataset, dynNTotal, dynXsection, dynScale))
scale = dynScale
else:
log.logError(
"No dynamic scale applied. This should never happen!")
# convert trees
if not treeMCEMraw == None:
treesMCEM.Add(
dataInterface.DataInterface.convertDileptonTree(
treeMCEMraw, weight=scale))
if not treeMCEEraw == None:
treesMCEE.Add(
dataInterface.DataInterface.convertDileptonTree(
treeMCEEraw, weight=scale))
if not treeMCMMraw == None:
treesMCMM.Add(
dataInterface.DataInterface.convertDileptonTree(
treeMCMMraw, weight=scale))
treeMCEMtotal = ROOT.TTree.MergeTrees(treesMCEM)
treeMCEEtotal = ROOT.TTree.MergeTrees(treesMCEE)
treeMCMMtotal = ROOT.TTree.MergeTrees(treesMCMM)
return (treeMCEMtotal, treeMCEEtotal, treeMCMMtotal)
def createLatexTable(fileName, content, format={}):
templateTable = """
\\documentclass[12pt,twoside,a4paper]{article}
\\newcommand{\\MET}{\\ensuremath{\\displaystyle{\\not} E_T~}}
\\newcommand{\\HT}{\\ensuremath{H_T~}}
\\begin{document}
\\begin{table}
%% \\tiny
\\small
\\begin{tabular}{%(cellformat)s}
\\hline
%(header)s
%(content)s
\\end{tabular}
%(caption)s
\\end{table}
\\end{document}
"""
tabMap = {
'cellformat': "c",
'header': "",
'content': "test",
'caption': ""
}
tabContent = None
nColumns = 1
noLineBreak = False
for row in content:
log.logDebug("row: %s" % row)
rowContent = None
hline = False
for column in row:
cellContent = str(column)
if (cellContent == "X-HLINE"):
hline = True
# format floats as specified
if (format.has_key('floatFormat') and isinstance(column, float)):
cellContent = format['floatFormat'] % column
if (rowContent == None):
rowContent = cellContent
else:
rowContent += " & " + cellContent
if (tabContent == None):
tabContent = rowContent
else:
if (not noLineBreak):
tabContent += "\\\\"
if (hline):
tabContent += "\\hline\n "
noLineBreak = True
else:
tabContent += "\n " + rowContent
noLineBreak = False
if (len(row) > nColumns):
nColumns = len(row)
log.logDebug("tabContent: %s" % tabContent)
#tabContent = tabContent.replace("_", "\\_")
tabMap.update({'content': tabContent})
if (format.has_key('cellformat')):
tabMap.update({'cellformat': format['cellformat']})
else:
cellformat = ""
for i in range(0, nColumns):
cellformat += "c"
tabMap.update({'cellformat': cellformat})
if (format.has_key('header')):
header = None
for string in format['header']:
if (header == None):
header = "\\textbf{" + string + "}"
else:
header = header + " & " + "\\textbf{" + string + "}"
tabMap.update({'header': header + "\\\\\\hline"})
if (format.has_key('caption')):
tabMap.update({'caption': "\\caption{" + format['caption'] + "}"})
if (format.has_key("fontsize")):
templateTable = templateTable.replace("\\small",
"\\%s" % format['fontsize'])
file = open(fileName, 'w')
file.write(templateTable % tabMap)
file.close()
def addResult(self, result):
if (self.histogram == None):
log.logWarning("Adding to empty result!")
if (result.histogram == None): log.logWarning("... also adding empty result!")
return result
if (result.histogram == None):
log.logWarning("Adding empty result!")
return self
if (not self.scaled == result.scaled):
log.logError("Cannot add scaled and unscaled results")
return None
if (self.dataType != result.dataType):
log.logError("Cannot add results of different data types (%d, %d)" % (self.dataType, results.dataType))
return None
# lumi info
if (self.luminosity > 0 and result.luminosity > 0):
if (self.dataType == InfoHolder.DataTypes.Data):
self.luminosity += result.luminosity # for data
else:
pass # for MC and Unknown
else:
log.logWarning("Adding results without complete luminosity information (%f, %f)" % (self.luminosity, result.luminosity))
self.luminosity = -1
# xSection info
if (self.xSection > 0 and result.xSection > 0):
self.xSection += result.xSection
else:
if (self.dataType != InfoHolder.DataTypes.Data):
log.logWarning("Adding results without complete xSection information (%f, %f)" % (self.xSection, result.xSection))
self.xSection = -1
# xSection info
if (self.kFactor > 0 and result.kFactor > 0):
if (self.kFactor != result.kFactor):
log.logHighlighted("Adding results with different kFactors (%f, %f). Will not be able to track this any more." % (self.kFactor, result.kFactor))
self.kFactor = -1
else:
log.logInfo("Adding results without complete kFactor information (%f, %f)" % (self.kFactor, result.kFactor))
self.kFactor = -1
if (not self.scaled):
self.histogram.Add(result.histogram)
return self
if (self.scalingFactor == result.scalingFactor):
self.unscaledIntegral += result.unscaledIntegral
self.histogram.Add(result.histogram)
return self
log.logDebug("Combining results: %s, %s" % (str(self), str(result)))
# first calculate new error
self.currentIntegralError = sqrt(self.integralError() * self.integralError() + result.integralError() * result.integralError())
# then change histogram
self.histogram.Add(result.histogram)
self.unscaledIntegral += result.unscaledIntegral
self.scalingFactor = -1
# finally mark result as scaled and added
self.__scaledAndAdded = True
log.logDebug("... to: %s" % (str(self)))
return self
def logMemoryContent(self):
directory = ROOT.gDirectory
list = directory.GetList()
keyNames = [key.GetName() for key in list]
log.logDebug("Memory content:%s" % keyNames)
