def mergeFunc(self,products) :
self.setupDicts()
for eLumis in products["staticEpochLumis"] :
for epoch in eLumis :
for run in eLumis[epoch] :
self.epochLumis[epoch][run] |= eLumis[epoch][run]
if not self.epochLumis : return
lumiDir = self.outputFileName
if not os.path.exists(lumiDir) : utils.mkdir(lumiDir)
lumis = utils.luminosity.recordedInvMicrobarnsShotgun( [utils.jsonFromRunDict(self.epochLumis[epoch]) for epoch in self.epochLumis ] , cores = 4, cacheDir = lumiDir)
probs = [ [1./prescale if prescale else 0 for prescale in epoch] for epoch in self.epochLumis ]
inclu = [ [utils.unionProbability(prob[:i+1]) for i in range(len(prob))] for prob in probs ]
thresholds = sorted(set(self.thresholds))
inclusives = [ [max([0]+[p for p,t in zip(inc,self.thresholds) if t is thresh]) for thresh in thresholds] for inc in inclu ]
weights = np.array(lumis).dot(inclusives) / sum(lumis)
# write total lumi and weight by threshold
lumiHist = r.TH1D('susyTreeLumi','luminosity from susyTree;;1/pb',1,0,1)
lumiHist.SetBinContent(1,sum(lumis))
lumiHist.Write()
weightHist = r.TH1D(self.name,";%s;%s"%(self.var,self.name), len(thresholds), np.array([0.]+thresholds+[max(thresholds)+10]))
for i,w in enumerate(weights) : weightHist.SetBinContent(i+2, w)
weightHist.SetBinContent(len(thresholds)+3, 1)
weightHist.Write()
def mergeFunc(self, products):
self.setup(None, None)
for eLumis in products["staticEpochLumis"]:
for epoch in eLumis:
for run in eLumis[epoch]:
self.epochLumis[epoch][run] |= eLumis[epoch][run]
lumiProbs = []
with open(self.outputFileName, "w") as file:
print >> file, self.triggers
print >> file, ""
for epoch in self.epochLumis:
json = utils.jsonFromRunDict(self.epochLumis[epoch])
lumi = utils.luminosity.recordedInvMicrobarns(json) / 1e6
probs = [
(thresh, 1.0 / prescale)
for thresh, prescale in zip(self.thresh, epoch)[: epoch.index(1.0) + 1]
if prescale
]
inclusive = [
(
probs[i][0],
probs[i + 1][0] if (i < len(probs) - 1) else None,
utils.unionProbability(zip(*probs[: i + 1])[1]),
)
for i in range(len(probs))
]
lumiProbs.append((lumi, inclusive))
print >> file, epoch
print >> file, json
print >> file, lumi, " /pb"
print >> file, [(thresh, "%.4f" % w) for thresh, nextThresh, w in inclusive]
print >> file, ""
print "Wrote prescale jsons by epoch : " + self.outputFileName
lumiVal = sum(lumi for lumi, probs in lumiProbs)
lumiHist = r.TH1D("susyTreeLumi", "luminosity from susyTree;;1/pb", 1, 0, 1)
lumiHist.Fill(0.5, lumiVal)
lumiHist.Write()
ptMax = 10 + max(self.thresh)
weight = r.TH1D("prescaleWeight", "prescaleWeight", ptMax, 0, ptMax)
for lumi, probs in lumiProbs:
epochWeight = lumi / lumiVal
for thresh, nextThresh, prob in probs:
for bin in range(thresh, nextThresh if nextThresh else ptMax):
weight.Fill(bin, epochWeight * prob)
weight.Write()
def mergeFunc(self, products):
self.setup(None, None)
for eLumis in products["staticEpochLumis"]:
for epoch in eLumis:
for run in eLumis[epoch]:
self.epochLumis[epoch][run] |= eLumis[epoch][run]
lumiProbs = []
with open(self.outputFileName, "w") as file:
print >> file, self.triggers
print >> file, ""
for epoch in self.epochLumis:
json = utils.jsonFromRunDict(self.epochLumis[epoch])
lumi = utils.luminosity.recordedInvMicrobarns(json) / 1e6
probs = [(thresh, 1. / prescale) for thresh, prescale in zip(
self.thresh, epoch)[:epoch.index(1.0) + 1] if prescale]
inclusive = [(probs[i][0], probs[i + 1][0] if
(i < len(probs) - 1) else None,
utils.unionProbability(zip(*probs[:i + 1])[1]))
for i in range(len(probs))]
lumiProbs.append((lumi, inclusive))
print >> file, epoch
print >> file, json
print >> file, lumi, " /pb"
print >> file, [(thresh, "%.4f" % w)
for thresh, nextThresh, w in inclusive]
print >> file, ""
print "Wrote prescale jsons by epoch : " + self.outputFileName
lumiVal = sum(lumi for lumi, probs in lumiProbs)
lumiHist = r.TH1D("susyTreeLumi", "luminosity from susyTree;;1/pb", 1,
0, 1)
lumiHist.Fill(0.5, lumiVal)
lumiHist.Write()
ptMax = 10 + max(self.thresh)
weight = r.TH1D("prescaleWeight", "prescaleWeight", ptMax, 0, ptMax)
for lumi, probs in lumiProbs:
epochWeight = lumi / lumiVal
for thresh, nextThresh, prob in probs:
for bin in range(thresh, nextThresh if nextThresh else ptMax):
weight.Fill(bin, epochWeight * prob)
weight.Write()
def mergeFunc(self, products):
self.setupDicts()
for eLumis in products["staticEpochLumis"]:
for epoch in eLumis:
for run in eLumis[epoch]:
self.epochLumis[epoch][run] |= eLumis[epoch][run]
if not self.epochLumis: return
lumiDir = self.outputFileName
if not os.path.exists(lumiDir): utils.mkdir(lumiDir)
lumis = utils.luminosity.recordedInvMicrobarnsShotgun([
utils.jsonFromRunDict(self.epochLumis[epoch])
for epoch in self.epochLumis
],
cores=4,
cacheDir=lumiDir)
probs = [[1. / prescale if prescale else 0 for prescale in epoch]
for epoch in self.epochLumis]
inclu = [[
utils.unionProbability(prob[:i + 1]) for i in range(len(prob))
] for prob in probs]
thresholds = sorted(set(self.thresholds))
inclusives = [[
max([0] + [p for p, t in zip(inc, self.thresholds) if t is thresh])
for thresh in thresholds
] for inc in inclu]
weights = np.array(lumis).dot(inclusives) / sum(lumis)
# write total lumi and weight by threshold
lumiHist = r.TH1D('susyTreeLumi', 'luminosity from susyTree;;1/pb', 1,
0, 1)
lumiHist.SetBinContent(1, sum(lumis))
lumiHist.Write()
weightHist = r.TH1D(
self.name, ";%s;%s" % (self.var, self.name), len(thresholds),
np.array([0.] + thresholds + [max(thresholds) + 10]))
for i, w in enumerate(weights):
weightHist.SetBinContent(i + 2, w)
weightHist.SetBinContent(len(thresholds) + 3, 1)
weightHist.Write()
