def processGENFASTSIM():
log.output(" ----> Preparing to produce the GEN-FASTSIM sample <----")
startTime = gmtime()
global workingDir_sim
global doDry
global options
global cmssw_sim
global gt_sim
global publish_sim
global GENFASTSIM_CFFPath
global GENFASTSIM_PublishName
global GENFASTSIM_nEvents
global GENFASTSIM_PNFSLocation
global GENFASTSIM_jobEff
global GENFASTSIM_LHEFiles
sim = GENFASTSIMProducer(timestamp, workingDir_sim, log, setarchitecture)
sim.createConfig(publish_sim, options.configfile, gt_sim, options.lhedir, options.nEvents, options.campaign)
crab = CRABHandler(timestamp, workingDir_sim, log)
if options.nEvents == "-1" or int(options.nEvents) > int(sim.getNLHEevents()):
options.nEvents = sim.getNLHEevents()
crab.nEvents = str(options.nEvents)
if not str(options.nEvents) == "-1" and int(options.nEvents) < 500:
crab.nEventsPerJob = crab.nEvents
else:
crab.nEventsPerJob = "500"
crab.AdditionalCrabInput = sim.getlhefiles()
crab.createCRABcfg(
"crab_genfastsim_" + timestamp + ".cfg",
publish_sim + "_" + options.campaign,
sim.getConfigFileName(),
sim.getOutputFileName(),
"GENFASTSIM",
bool(True),
"",
"",
bool(False),
)
# the 'publish' argument set to bool(False) does not work yet, crabhandler encounters a problem because it wants to split "None" (the dataset when doing GEN-FASTSIM) into several pieces divided by "/" (as in a normal DAS dataset)...
crab.setForceWhiteList(bool(True))
if not doDry:
crab.submitJobs()
nEventsDBS = crab.getnEventsDBS()
##for testing
# crab.idleTime = int(60)
# crab.idleTimeResubmit = int(120)
crab.checkJobs()
time.sleep(60) # to be sure the jobs are in done status
GENFASTSIM_CFFPath = workingDir_sim + "/" + sim.getConfigFileName()
GENFASTSIM_LHEFiles = sim.getlhefiles()
GENFASTSIM_PublishName = crab.publishDataSet()
GENFASTSIM_nEvents = crab.checkFJR()
GENFASTSIM_PNFSLocation = crab.getOutputLocation()
GENFASTSIM_jobEff = crab.getJobEff()
# remove sandbox (lhe files are compressed, but can be sizable when you have a lot of lhe files and tasks: better clean up when a task is done)
log.output("--> Removing task sandbox ")
Popen(
"rm " + workingDir_sim + "/" + crab.UIWorkingDir + "/share/*.tgz",
shell=True,
stdin=PIPE,
stdout=PIPE,
stderr=STDOUT,
close_fds=True,
).stdout.read()
# remove lhe files in crab directory if they were copied when the lhe files in the original lhe directory were gzipped
log.output("--> Removing local copied LHE files in directory for crab")
Popen(
"rm " + workingDir_sim + "/*.lhe", shell=True, stdin=PIPE, stdout=PIPE, stderr=STDOUT, close_fds=True
).stdout.read()
log.output("--> Job Efficiency: " + str(GENFASTSIM_jobEff))
endTime = gmtime()
log.output(
"--> The GEN-FASTSIM production took "
+ str((time.mktime(endTime) - time.mktime(startTime)) / 3600.0)
+ " hours."
)
log.appendToMSG("\n* GEN-FASTSIM production information: ")
if not crab.getOutputLocation() == "":
log.appendToMSG("\n\t-> Data location: " + GENFASTSIM_PNFSLocation + "\n")
log.appendToMSG("\t-> DataSet was published in DBS as: " + GENFASTSIM_PublishName)
log.appendToMSG("\t-> Number of events processed: " + str(GENFASTSIM_nEvents))
def processTOPTREE():
log.output("********** Preparing to produce the TopTree **********")
startTime = gmtime()
global workingDir
global dataType
global doDry
global nEventsDBS
global nEventsTT
global doPBS
global topTreeLocation
global topCffName
global options
global ttreeEventContent
global jobEffTT
global CrabJSON
top = TopTreeProducer(timestamp,workingDir,log)
top.createTopTreeConfig(options.dataset,dataType,options.doGenEvent,options.GlobalTag,options.cmssw_ver,options.cmssw_ver_sample,options.top_config)
topCffName = top.getConfigFileName()
#crab = CRABHandler(timestamp,workingDir,log);
crab = CRABHandler(options.toptree_ver,timestamp,workingDir,log);
useDataSet=""
if doStartFromPAT:
useDataSet=options.dataset
else:
useDataSet=patPublishName
options.RunSelection = ""
crab.setDBSInst("cms_dbs_ph_analysis_02")
type = "TOPTREE"
if not doDry:
crab.scaleJobsSize(useDataSet,options.RunSelection,10) # if to much jobs (>2500) we create new cfg with 2500 jobs
crab.AdditionalCrabInput=getAdditionalInputFiles(crab.AdditionalCrabInput)
crab.createCRABcfg("crab_toptree_"+timestamp+".cfg",
useDataSet,
top.getConfigFileName(),
top.getOutputFileName(),
type,
bool(False),
options.CEBlacklist,
options.RunSelection,
options.forceStandAlone) # empty runselection for top
topTreeLocation = crab.getOutputLocation().split("\n")[0]
if not doDry:
crab.submitJobs()
crab.checkJobs()
#time.sleep(60) # to be shure the jobs are in done status
crab.publishDataSet()
CrabJSON = crab.getCrabJSON()
nEventsTT = crab.checkFJR()
if doStartFromPAT:
nEventsDBS = crab.getnEventsDBS()
ttreeEventContent = top.dumpEventContent(topTreeLocation)
jobEffTT = crab.getJobEff()
log.output("--> Job Efficiency: "+str(crab.getJobEff()))
endTime = gmtime()
log.output("--> The TopTree production took "+ str((time.mktime(endTime)-time.mktime(startTime))/3600.0)+" hours.")
log.appendToMSG("\n* TopTree production information: \n")
if not crab.getOutputLocation() == "":
log.appendToMSG("\t-> Data location: "+topTreeLocation+"\n")
log.appendToMSG("\t-> Number of events processed: "+str(nEventsTT))
def processPATandTOPTREE():
global workingDir
global dbsInst
global dataType
global doDry
global nEventsDBS
global workingDir
global dataType
global nEventsTT
global nEventsDBS
global topTreeLocation
global topCffName
global patCffName
global ttreeEventContent
global options
global jobEffPat
global jobEffTT
global CrabJSON
log.output("********** Preparing to produce the PAT-tuple and TopTree in one go **********")
startTime = gmtime()
# create pat cfg
pat = PatProducer(timestamp,workingDir,log);
pat.createPatConfig(options.dataset,options.GlobalTag,dataType,options.doGenEvent,options.cmssw_ver,options.cmssw_ver_sample,options.flavourHistoryFilterPath,options.runOnMC,options.pat_config)
patCffName = pat.getConfigFileName()
# create toptree cfg
top = TopTreeProducer(timestamp,workingDir,log)
# top.createTopTreeConfig(options.dataset,dataType,options.doGenEvent,options.GlobalTag,options.cmssw_ver,options.cmssw_ver_sample)
top.createTopTreeConfig(options.dataset,dataType,options.doGenEvent,options.GlobalTag,options.cmssw_ver,options.cmssw_ver_sample,options.top_config)
topCffName = top.getConfigFileName()
log.output(" ---> will expand the TopTree config before sending it with crab " )
cmd2 = 'cd '+options.cmssw_ver+'; eval `scramv1 runtime -sh`; cd -; python '+workingDir+'/'+top.getConfigFileName()+'; mv -v expanded.py '+workingDir+'/'
if not workingDir.rfind("CMSSW_5_") == -1:
log.output("Expanding TopTree config:: CMSSW_5_X_Y release detected, setting scram arch to slc5_amd64_gcc462")
cmd2 = "export SCRAM_ARCH=\"slc5_amd64_gcc462\";"+cmd2
pExe = Popen(cmd2, shell=True, stdin=PIPE, stdout=PIPE, stderr=STDOUT, close_fds=True)
log.output(pExe.stdout.read())
# create crab cfg
#crab = CRABHandler(timestamp,workingDir,log);
crab = CRABHandler(options.toptree_ver,timestamp,workingDir,log);
if not dbsInst == "":
crab.setDBSInst(dbsInst)
log.output(" ---> CRAB will use DBS instance "+dbsInst+" to look for your data.")
#crab.nEventsPerJob = "20000"
#crab.nEventsPerJob = "500"
if not doDry:
crab.scaleJobsSize(options.dataset,options.RunSelection,1) # if to much jobs (>2500) we create new cfg with 2500 jobs
crab.runTwoConfigs(patCffName,topCffName)
crab.AdditionalCrabInput=getAdditionalInputFiles(crab.AdditionalCrabInput)
crab.createCRABcfg("crab_"+timestamp+".cfg",
options.dataset,
pat.getConfigFileName(),
top.getOutputFileName(),
"TOPTREE",
bool(False),
options.CEBlacklist,
options.RunSelection,
options.forceStandAlone)
topTreeLocation = crab.getOutputLocation().split("\n")[0]
if not doDry:
crab.submitJobs()
crab.checkJobs()
crab.publishDataSet()
nEventsDBS = crab.getnEventsDBS()
nEventsTT = crab.checkFJR()
CrabJSON = crab.getCrabJSON()
if doStartFromPAT:
nEventsDBS = crab.getnEventsDBS()
ttreeEventContent = top.dumpEventContent(topTreeLocation)
jobEffPat = crab.getJobEff() # same job-eff for pat & TT in case of duo-jobs
jobEffTT = crab.getJobEff()
log.output("--> Job Efficiency: "+str(crab.getJobEff()))
endTime = gmtime()
log.output("--> The TopTree production took "+ str((time.mktime(endTime)-time.mktime(startTime))/3600.0)+" hours.")
log.appendToMSG("\n* TopTree production information: \n")
if not crab.getOutputLocation() == "":
log.appendToMSG("\t-> Data location: "+topTreeLocation+"\n")
log.appendToMSG("\t-> Number of events processed: "+str(nEventsTT))
log.appendToMSG("\n Note: This TopTree was created from PAT inside one single job, the PATtuple was not stored")
def processGENFASTSIM():
log.output(" ----> Preparing to produce the GEN-FASTSIM sample <----")
startTime = gmtime()
global workingDir_sim
global doDry
global options
global cmssw_sim
global gt_sim
global publish_sim
global GENFASTSIM_CFFPath
global GENFASTSIM_PublishName
global GENFASTSIM_nEvents
global GENFASTSIM_PNFSLocation
global GENFASTSIM_jobEff
global GENFASTSIM_LHEFiles
sim = GENFASTSIMProducer(timestamp, workingDir_sim, log, setarchitecture)
sim.createConfig(publish_sim, options.configfile, gt_sim, options.lhedir,
options.nEvents, options.campaign)
crab = CRABHandler(timestamp, workingDir_sim, log)
if options.nEvents == "-1" or int(options.nEvents) > int(
sim.getNLHEevents()):
options.nEvents = sim.getNLHEevents()
crab.nEvents = str(options.nEvents)
if not str(options.nEvents) == "-1" and int(options.nEvents) < 500:
crab.nEventsPerJob = crab.nEvents
else:
crab.nEventsPerJob = "500"
crab.AdditionalCrabInput = sim.getlhefiles()
crab.createCRABcfg("crab_genfastsim_" + timestamp + ".cfg",
publish_sim + "_" + options.campaign,
sim.getConfigFileName(), sim.getOutputFileName(),
"GENFASTSIM", bool(True), "", "", bool(False))
#the 'publish' argument set to bool(False) does not work yet, crabhandler encounters a problem because it wants to split "None" (the dataset when doing GEN-FASTSIM) into several pieces divided by "/" (as in a normal DAS dataset)...
crab.setForceWhiteList(bool(True))
if not doDry:
crab.submitJobs()
nEventsDBS = crab.getnEventsDBS()
##for testing
#crab.idleTime = int(60)
#crab.idleTimeResubmit = int(120)
crab.checkJobs()
time.sleep(60) # to be sure the jobs are in done status
GENFASTSIM_CFFPath = workingDir_sim + "/" + sim.getConfigFileName()
GENFASTSIM_LHEFiles = sim.getlhefiles()
GENFASTSIM_PublishName = crab.publishDataSet()
GENFASTSIM_nEvents = crab.checkFJR()
GENFASTSIM_PNFSLocation = crab.getOutputLocation()
GENFASTSIM_jobEff = crab.getJobEff()
#remove sandbox (lhe files are compressed, but can be sizable when you have a lot of lhe files and tasks: better clean up when a task is done)
log.output("--> Removing task sandbox ")
Popen('rm ' + workingDir_sim + '/' + crab.UIWorkingDir +
'/share/*.tgz',
shell=True,
stdin=PIPE,
stdout=PIPE,
stderr=STDOUT,
close_fds=True).stdout.read()
#remove lhe files in crab directory if they were copied when the lhe files in the original lhe directory were gzipped
log.output("--> Removing local copied LHE files in directory for crab")
Popen('rm ' + workingDir_sim + '/*.lhe',
shell=True,
stdin=PIPE,
stdout=PIPE,
stderr=STDOUT,
close_fds=True).stdout.read()
log.output("--> Job Efficiency: " + str(GENFASTSIM_jobEff))
endTime = gmtime()
log.output("--> The GEN-FASTSIM production took " +
str((time.mktime(endTime) - time.mktime(startTime)) / 3600.0) +
" hours.")
log.appendToMSG("\n* GEN-FASTSIM production information: ")
if not crab.getOutputLocation() == "":
log.appendToMSG("\n\t-> Data location: " + GENFASTSIM_PNFSLocation +
"\n")
log.appendToMSG("\t-> DataSet was published in DBS as: " +
GENFASTSIM_PublishName)
log.appendToMSG("\t-> Number of events processed: " +
str(GENFASTSIM_nEvents))
def processPAT():
global workingDir
global dbsInst
global dataType
global doDry
global patPublishName
global nEventsPAT
global nEventsDBS
global patCffName
global patLocation
global patEventContent
global jobEffPat
global options
global CrabJSON
log.output("********** Preparing to produce the PAT-tuple **********")
startTime = gmtime()
pat = PatProducer(timestamp,workingDir,log);
pat.createPatConfig(options.dataset,options.GlobalTag,dataType,options.doGenEvent,options.cmssw_ver,options.cmssw_ver_sample,options.flavourHistoryFilterPath,options.runOnMC,options.pat_config)
patCffName = pat.getConfigFileName()
#crab = CRABHandler(timestamp,workingDir,log);
crab = CRABHandler(options.toptree_ver,timestamp,workingDir,log);
#print "**"+crab.baseDir
if not dbsInst == "":
crab.setDBSInst(dbsInst)
log.output(" ---> CRAB will use DBS instance "+dbsInst+" to look for your data.")
if not doDry:
crab.scaleJobsSize(options.dataset,options.RunSelection,1) # if to much jobs (>2500) we create new cfg with 2500 jobs
crab.AdditionalCrabInput=getAdditionalInputFiles(crab.AdditionalCrabInput)
crab.createCRABcfg("crab_pat_"+timestamp+".cfg",
options.dataset,
pat.getConfigFileName(),
pat.getOutputFileName(),
"PAT",
bool(True),
options.CEBlacklist,
options.RunSelection,
options.forceStandAlone)
if not doDry:
crab.submitJobs()
nEventsDBS = crab.getnEventsDBS()
crab.checkJobs()
time.sleep(60) # to be shure the jobs are in done status
patPublishName = crab.publishDataSet()
nEventsPAT = crab.checkFJR()
patLocation = crab.getOutputLocation()
patEventContent = pat.dumpEventContent(patLocation)
jobEffPat = crab.getJobEff()
log.output("--> Job Efficiency: "+str(crab.getJobEff()))
endTime = gmtime()
log.output("--> The PAT production took "+ str((time.mktime(endTime)-time.mktime(startTime))/3600.0)+" hours.")
log.appendToMSG("\n* PAT production information: ")
if not crab.getOutputLocation() == "":
log.appendToMSG("\n\t-> Data location: "+patLocation+"\n")
log.appendToMSG("\t-> DataSet was published in DBS as: "+patPublishName)
log.appendToMSG("\t-> Number of events processed: "+str(nEventsPAT))
print "Fatal ERROR, script exiting"
else:
print "Fatal ERROR, script exiting. Please consult " + logFileName + " for more information"
sys.exit(1)
if options.attach == None:
# now prepare our crab cfg
#print crabCfgName
crab.parseCRABcfg(timestamp, options.dir, crabCfgName)
# submit jobs
crab.submitJobs()
# check jobs
else:
crab.doPublish = options.doPublish
if options.doPublish:
log.output("--> Publishing results of crab task to DBS")
crab.baseDir = options.dir
crab.UIWorkingDir = options.attach
crab.checkJobs()
print "Fatal ERROR, script exiting"
else:
print "Fatal ERROR, script exiting. Please consult "+logFileName+" for more information"
sys.exit(1)
if options.attach == None:
# now prepare our crab cfg
#print crabCfgName
crab.parseCRABcfg(timestamp,options.dir,crabCfgName)
# submit jobs
crab.submitJobs()
# check jobs
else:
crab.doPublish = options.doPublish
if options.doPublish:
log.output("--> Publishing results of crab task to DBS")
crab.baseDir = options.dir
crab.UIWorkingDir = options.attach
crab.checkJobs()
def processPATandTOPTREE():
global workingDir
global dbsInst
global dataType
global doDry
global nEventsDBS
global workingDir
global dataType
global nEventsTT
global nEventsDBS
global topTreeLocation
global topCffName
global patCffName
global ttreeEventContent
global options
global jobEffPat
global jobEffTT
global CrabJSON
log.output(
"********** Preparing to produce the PAT-tuple and TopTree in one go **********"
)
startTime = gmtime()
# create pat cfg
pat = PatProducer(timestamp, workingDir, log)
pat.createPatConfig(options.dataset, options.GlobalTag, dataType,
options.doGenEvent, options.cmssw_ver,
options.cmssw_ver_sample,
options.flavourHistoryFilterPath, options.runOnMC,
options.pat_config)
patCffName = pat.getConfigFileName()
# create toptree cfg
top = TopTreeProducer(timestamp, workingDir, log)
# top.createTopTreeConfig(options.dataset,dataType,options.doGenEvent,options.GlobalTag,options.cmssw_ver,options.cmssw_ver_sample)
top.createTopTreeConfig(options.dataset, dataType, options.doGenEvent,
options.GlobalTag, options.cmssw_ver,
options.cmssw_ver_sample, options.top_config)
topCffName = top.getConfigFileName()
log.output(
" ---> will expand the TopTree config before sending it with crab ")
cmd2 = 'cd ' + options.cmssw_ver + '; eval `scramv1 runtime -sh`; cd -; python ' + workingDir + '/' + top.getConfigFileName(
) + '; mv -v expanded.py ' + workingDir + '/'
if not workingDir.rfind("CMSSW_5_") == -1:
log.output(
"Expanding TopTree config:: CMSSW_5_X_Y release detected, setting scram arch to slc5_amd64_gcc462"
)
cmd2 = "export SCRAM_ARCH=\"slc5_amd64_gcc462\";" + cmd2
pExe = Popen(cmd2,
shell=True,
stdin=PIPE,
stdout=PIPE,
stderr=STDOUT,
close_fds=True)
log.output(pExe.stdout.read())
# create crab cfg
#crab = CRABHandler(timestamp,workingDir,log);
crab = CRABHandler(options.toptree_ver, timestamp, workingDir, log)
if not dbsInst == "":
crab.setDBSInst(dbsInst)
log.output(" ---> CRAB will use DBS instance " + dbsInst +
" to look for your data.")
#crab.nEventsPerJob = "20000"
#crab.nEventsPerJob = "500"
if not doDry:
crab.scaleJobsSize(
options.dataset, options.RunSelection,
1) # if to much jobs (>2500) we create new cfg with 2500 jobs
crab.runTwoConfigs(patCffName, topCffName)
crab.AdditionalCrabInput = getAdditionalInputFiles(
crab.AdditionalCrabInput)
crab.createCRABcfg("crab_" + timestamp + ".cfg", options.dataset,
pat.getConfigFileName(), top.getOutputFileName(),
"TOPTREE", bool(False), options.CEBlacklist,
options.RunSelection, options.forceStandAlone)
topTreeLocation = crab.getOutputLocation().split("\n")[0]
if not doDry:
crab.submitJobs()
crab.checkJobs()
crab.publishDataSet()
nEventsDBS = crab.getnEventsDBS()
nEventsTT = crab.checkFJR()
CrabJSON = crab.getCrabJSON()
if doStartFromPAT:
nEventsDBS = crab.getnEventsDBS()
ttreeEventContent = top.dumpEventContent(topTreeLocation)
jobEffPat = crab.getJobEff(
) # same job-eff for pat & TT in case of duo-jobs
jobEffTT = crab.getJobEff()
log.output("--> Job Efficiency: " + str(crab.getJobEff()))
endTime = gmtime()
log.output("--> The TopTree production took " +
str((time.mktime(endTime) - time.mktime(startTime)) / 3600.0) +
" hours.")
log.appendToMSG("\n* TopTree production information: \n")
if not crab.getOutputLocation() == "":
log.appendToMSG("\t-> Data location: " + topTreeLocation + "\n")
log.appendToMSG("\t-> Number of events processed: " + str(nEventsTT))
log.appendToMSG(
"\n Note: This TopTree was created from PAT inside one single job, the PATtuple was not stored"
)
def processTOPTREE():
log.output("********** Preparing to produce the TopTree **********")
startTime = gmtime()
global workingDir
global dataType
global doDry
global nEventsDBS
global nEventsTT
global doPBS
global topTreeLocation
global topCffName
global options
global ttreeEventContent
global jobEffTT
global CrabJSON
top = TopTreeProducer(timestamp, workingDir, log)
top.createTopTreeConfig(options.dataset, dataType, options.doGenEvent,
options.GlobalTag, options.cmssw_ver,
options.cmssw_ver_sample, options.top_config)
topCffName = top.getConfigFileName()
#crab = CRABHandler(timestamp,workingDir,log);
crab = CRABHandler(options.toptree_ver, timestamp, workingDir, log)
useDataSet = ""
if doStartFromPAT:
useDataSet = options.dataset
else:
useDataSet = patPublishName
options.RunSelection = ""
crab.setDBSInst("cms_dbs_ph_analysis_02")
type = "TOPTREE"
if not doDry:
crab.scaleJobsSize(
useDataSet, options.RunSelection,
10) # if to much jobs (>2500) we create new cfg with 2500 jobs
crab.AdditionalCrabInput = getAdditionalInputFiles(
crab.AdditionalCrabInput)
crab.createCRABcfg("crab_toptree_" + timestamp + ".cfg", useDataSet,
top.getConfigFileName(), top.getOutputFileName(), type,
bool(False), options.CEBlacklist, options.RunSelection,
options.forceStandAlone) # empty runselection for top
topTreeLocation = crab.getOutputLocation().split("\n")[0]
if not doDry:
crab.submitJobs()
crab.checkJobs()
#time.sleep(60) # to be shure the jobs are in done status
crab.publishDataSet()
CrabJSON = crab.getCrabJSON()
nEventsTT = crab.checkFJR()
if doStartFromPAT:
nEventsDBS = crab.getnEventsDBS()
ttreeEventContent = top.dumpEventContent(topTreeLocation)
jobEffTT = crab.getJobEff()
log.output("--> Job Efficiency: " + str(crab.getJobEff()))
endTime = gmtime()
log.output("--> The TopTree production took " +
str((time.mktime(endTime) - time.mktime(startTime)) / 3600.0) +
" hours.")
log.appendToMSG("\n* TopTree production information: \n")
if not crab.getOutputLocation() == "":
log.appendToMSG("\t-> Data location: " + topTreeLocation + "\n")
log.appendToMSG("\t-> Number of events processed: " + str(nEventsTT))
def processPAT():
global workingDir
global dbsInst
global dataType
global doDry
global patPublishName
global nEventsPAT
global nEventsDBS
global patCffName
global patLocation
global patEventContent
global jobEffPat
global options
global CrabJSON
log.output("********** Preparing to produce the PAT-tuple **********")
startTime = gmtime()
pat = PatProducer(timestamp, workingDir, log)
pat.createPatConfig(options.dataset, options.GlobalTag, dataType,
options.doGenEvent, options.cmssw_ver,
options.cmssw_ver_sample,
options.flavourHistoryFilterPath, options.runOnMC,
options.pat_config)
patCffName = pat.getConfigFileName()
#crab = CRABHandler(timestamp,workingDir,log);
crab = CRABHandler(options.toptree_ver, timestamp, workingDir, log)
#print "**"+crab.baseDir
if not dbsInst == "":
crab.setDBSInst(dbsInst)
log.output(" ---> CRAB will use DBS instance " + dbsInst +
" to look for your data.")
if not doDry:
crab.scaleJobsSize(
options.dataset, options.RunSelection,
1) # if to much jobs (>2500) we create new cfg with 2500 jobs
crab.AdditionalCrabInput = getAdditionalInputFiles(
crab.AdditionalCrabInput)
crab.createCRABcfg("crab_pat_" + timestamp + ".cfg", options.dataset,
pat.getConfigFileName(), pat.getOutputFileName(), "PAT",
bool(True), options.CEBlacklist, options.RunSelection,
options.forceStandAlone)
if not doDry:
crab.submitJobs()
nEventsDBS = crab.getnEventsDBS()
crab.checkJobs()
time.sleep(60) # to be shure the jobs are in done status
patPublishName = crab.publishDataSet()
nEventsPAT = crab.checkFJR()
patLocation = crab.getOutputLocation()
patEventContent = pat.dumpEventContent(patLocation)
jobEffPat = crab.getJobEff()
log.output("--> Job Efficiency: " + str(crab.getJobEff()))
endTime = gmtime()
log.output("--> The PAT production took " +
str((time.mktime(endTime) - time.mktime(startTime)) / 3600.0) +
" hours.")
log.appendToMSG("\n* PAT production information: ")
if not crab.getOutputLocation() == "":
log.appendToMSG("\n\t-> Data location: " + patLocation + "\n")
log.appendToMSG("\t-> DataSet was published in DBS as: " + patPublishName)
log.appendToMSG("\t-> Number of events processed: " + str(nEventsPAT))