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#!/usr/bin/env python
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import os
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import re
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import sys
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import math
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import datetime
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import copy
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from optparse import OptionParser
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import OSUT3Analysis.DBTools.osusub_cfg as osusub
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import FWCore.ParameterSet.Config as cms
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def split_composite_datasets(datasets, composite_dataset_definitions):
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for dataset in datasets:
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if dataset in composite_dataset_definitions:
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for component_dataset in composite_dataset_definitions[dataset]:
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datasets.insert(datasets.index(dataset),component_dataset)
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datasets.remove(dataset)
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return datasets
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def get_composite_datasets(datasets, composite_dataset_definitions):
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composite_datasets = []
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for dataset in datasets:
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if dataset in composite_dataset_definitions:
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composite_datasets.append(dataset)
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return composite_datasets
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def set_condor_submit_dir(arguments):
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if arguments.condorDir:
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condor_dir = "condor/%s" % arguments.condorDir
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else:
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now = datetime.datetime.now()
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date_hash = now.strftime("%Y_%m_%d_%H:%M:%S")
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condor_dir = "condor/condor_%s" % date_hash
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#print "Condor submit directory set to ",condor_dir
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return condor_dir
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def set_condor_output_dir(arguments):
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if arguments.condorDir:
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condor_dir = "condor/%s" % arguments.condorDir
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else: #get most recent condor submission directory
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dir_list = []
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for directory in os.listdir("./condor/"):
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if directory.find("condor_") is not -1:
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dir_list.append(directory)
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if len(dir_list) is 0:
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sys.exit("Cannot find last condor working directory")
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dir_list.sort(reverse=True)
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condor_dir = "condor/%s" % dir_list[0]
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#print "Condor output directory set to ",condor_dir
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return condor_dir
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def set_commandline_arguments(parser):
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#### Configuration-related Options
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parser.add_option("-l", "--localConfig", dest="localConfig",
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help="local configuration file")
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parser.add_option("-c", "--condorDir", dest="condorDir",
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help="condor output directory")
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parser.add_option("-o", "--output-file", dest="outputFileName",
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help="specify an output file name for the histogram file, default is 'stacked_histograms.root'")
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parser.add_option("-t", "--no-weights", action="store_true", dest="noWeights", default=False,
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help="do not apply cross section weights")
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parser.add_option("-q", "--quickMerge", action="store_true", dest="quickMerge", default=False,
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help="do merge without making cutflow or plots")
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#### Histogram Formatting Options
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parser.add_option("-n", "--normalize", action="store_true", dest="normalizeToData", default=False,
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help="normalize total background MC yield to the data")
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parser.add_option("-u", "--unit-area", action="store_true", dest="normalizeToUnitArea", default=False,
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help="normalize all samples to unit area (useful to compare shapes)")
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parser.add_option("-e", "--empty", action="store_true", dest="noStack", default=False,
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help="don't stack the background samples, draw them as empty histograms instead")
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parser.add_option("-r", "--ratio", action="store_true", dest="makeRatioPlots", default=False,
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help="draw (data-MC)/MC plots below all 1D histograms")
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parser.add_option("-R", "--ratioYRange", dest="ratioYRange", default=1.15,
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help="maximum of range of vertical scale for ratio plots")
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parser.add_option("-d", "--diff", action="store_true", dest="makeDiffPlots", default=False,
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help="draw data-MC plots below all 1D histograms")
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parser.add_option("-b", "--rebin", dest="rebinFactor",
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help="Rebin all the histograms which will have at least 10 bins after rebinning")
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parser.add_option("--2D", action="store_true", dest="draw2DPlots", default=False,
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help="draw stacked 2D histograms")
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parser.add_option("-y", "--yields", action="store_true", dest="printYields", default=False,
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help="Include the yield of each source in the legend")
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parser.add_option("-p", "--pdfs", action="store_true", dest="savePDFs", default=False,
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help="Save pdfs files for all plots made")
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### Only used by makeBNTreePlot.py (maybe move to another file?)
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parser.add_option("-D", "--dataset", dest="datasetName",
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help="Name of dataset (overrides value from local configuration file)")
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parser.add_option("-C", "--runOnCondor", action="store_true", dest="runOnCondor", default=False,
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help="Run on condor instead of interactively")
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return parser
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def get_short_name(dataset, dataset_names):
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for key in dataset_names:
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if dataset_names[key] == dataset:
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return key
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return "Unknown"
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def stop_ctau (dataset):
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if not re.match (r"stop[^_]*to[^_]*_[^_]*mm.*", dataset):
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return 0.0
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return float (re.sub (r"stop[^_]*to[^_]*_([^_]*)mm.*", r"\1", dataset))
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def source_stop_ctau (ctau):
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return int (math.pow (10.0, math.ceil (math.log10 (ctau))))
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def add_stops (options, masses, ctaus, bottomBranchingRatios = []):
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if not bottomBranchingRatios:
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bottomBranchingRatios.append (50.0)
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for mass in masses:
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for ctau in ctaus:
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for bottomBranchingRatio in bottomBranchingRatios:
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datasetName = 'stop' + str (mass) + "_" + str (ctau) + "mm_br" + str (int (bottomBranchingRatio))
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bottomDatasetName = 'stop' + str (mass) + "toBl_" + str (ctau) + "mm"
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sourceBottomDatasetName = 'stop' + str (mass) + "toBl_" + str (source_stop_ctau (ctau)) + "mm"
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topDatasetName = 'stop' + str (mass) + "toTnu_" + str (ctau) + "mm"
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sourceTopDatasetName = 'stop' + str (mass) + "toTnu_" + str (source_stop_ctau (ctau)) + "mm"
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mixedDatasetName = 'stop' + str (mass) + "toBT_" + str (ctau) + "mm"
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sourceMixedDatasetName = 'stop' + str (mass) + "toBT_" + str (source_stop_ctau (ctau)) + "mm"
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options['datasets'].append (datasetName)
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bottomBranchingRatio /= 100.0
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options['composite_dataset_definitions'][datasetName] = {
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bottomDatasetName : bottomBranchingRatio * bottomBranchingRatio,
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topDatasetName : (1 - bottomBranchingRatio) * (1 - bottomBranchingRatio),
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mixedDatasetName : (1 - bottomBranchingRatio * bottomBranchingRatio - (1 - bottomBranchingRatio) * (1 - bottomBranchingRatio))
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}
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options['dataset_names'][bottomDatasetName] = options['dataset_names'][sourceBottomDatasetName]
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options['dataset_names'][topDatasetName] = options['dataset_names'][sourceTopDatasetName]
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options['dataset_names'][mixedDatasetName] = options['dataset_names'][sourceMixedDatasetName]
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options['nJobs'][bottomDatasetName] = 1
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options['nJobs'][topDatasetName] = 1
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options['nJobs'][mixedDatasetName] = 1
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options['maxEvents'][bottomDatasetName] = -1
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options['maxEvents'][topDatasetName] = -1
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options['maxEvents'][mixedDatasetName] = -1
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options['types'][datasetName] = "signalMC"
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options['types'][bottomDatasetName] = "signalMC"
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options['types'][topDatasetName] = "signalMC"
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options['types'][mixedDatasetName] = "signalMC"
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options['labels'][datasetName] = str (mass) + " GeV stop (#LTc#tau#GT = " + str (ctau) + " mm)"
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options['labels'][bottomDatasetName] = "#tilde{t}#tilde{t}#rightarrowbbll (#LTc#tau#GT = " + str (ctau) + " mm)"
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options['labels'][topDatasetName] = "#tilde{t}#tilde{t}#rightarrowtt#nu#nu (#LTc#tau#GT = " + str (ctau) + " mm)"
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options['labels'][mixedDatasetName] = "#tilde{t}#tilde{t}#rightarrowbtl#nu (#LTc#tau#GT = " + str (ctau) + " mm)"
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def add_channels (process, channels):
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suffix = ""
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if osusub.batchMode:
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suffix = "_" + str (osusub.jobNumber)
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i = 0
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for channel in channels:
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channelName = channel.name.pythonValue ()
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channelName = channelName[1:-1]
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out = cms.OutputModule ("PoolOutputModule",
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fileName = cms.untracked.string ("bean_" + channelName + suffix + ".root"),
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SelectEvents = cms.untracked.PSet (
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SelectEvents = cms.vstring ("myFilterPath" + str (i))
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),
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outputCommands = cms.untracked.vstring (
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"drop *",
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"keep *_BNproducer_*_*",
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"keep double_kt6PFJets*_rho_*",
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),
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dropMetaData = cms.untracked.string ("ALL")
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)
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myFilter = cms.EDFilter ("FilterOnChannelDecision",
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src = cms.InputTag ("OSUAnalysis", "channelDecisions"),
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channelName = cms.string (channelName)
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)
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myFilterPath = cms.Path (myFilter)
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myEndPath = cms.EndPath (out)
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process.__setattr__ ("out" + str (i), out)
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process.OSUAnalysis.channels.append (channel)
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process.OSUAnalysis.useEDMFormat = cms.bool (True)
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process.__setattr__ ("myFilter" + str (i), myFilter)
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process.__setattr__ ("myFilterPath" + str (i), myFilterPath)
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process.__setattr__ ("myEndPath" + str (i), myEndPath)
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i += 1
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