def __call__(self, workloadName, arguments):
"""
Create a workload instance for a LHE Step0 request
Just pass it down to MonteCarlo
"""
#Override splitting arguments
# Splitting arguments
timePerEvent = int(arguments.get('TimePerEvent', 60))
filterEfficiency = float(arguments.get('FilterEfficiency', 1.0))
totalTime = int(arguments.get('TotalTime', 9 * 3600))
self.totalEvents = int(int(arguments['RequestNumEvents']) / filterEfficiency)
if arguments.get("LheInputFiles", False) == True \
or arguments.get("LheInputFiles", False) == "True":
self.lheInputFiles = True
# These are mostly place holders because the job splitting algo and
# parameters will be updated after the workflow has been created.
eventsPerJob = int(totalTime/timePerEvent/filterEfficiency)
self.prodJobSplitAlgo = arguments.setdefault("ProdJobSplitAlgo", 'EventBased')
self.prodJobSplitArgs = arguments.setdefault("ProdJobSplitArgs",
{"events_per_job": eventsPerJob,
"events_per_lumi": arguments['EventsPerLumi']})
self.prodJobSplitArgs.setdefault("lheInputFiles", self.lheInputFiles)
mcWorkload = MonteCarloWorkloadFactory.__call__(self, workloadName, arguments)
mcWorkload.setBlockCloseSettings(mcWorkload.getBlockCloseMaxWaitTime(), 5,
250000000, mcWorkload.getBlockCloseMaxSize())
return mcWorkload
def __call__(self, workloadName, arguments):
"""
Create a workload instance for a LHE Step0 request
Just pass it down to MonteCarlo
"""
#Override splitting arguments
# Splitting arguments
timePerEvent = int(arguments.get('TimePerEvent', 60))
filterEfficiency = float(arguments.get('FilterEfficiency', 1.0))
totalTime = int(arguments.get('TotalTime', 9 * 3600))
self.totalEvents = int(int(arguments['RequestNumEvents']) / filterEfficiency)
# These are mostly place holders because the job splitting algo and
# parameters will be updated after the workflow has been created.
eventsPerJob = int(totalTime/timePerEvent/filterEfficiency)
self.prodJobSplitAlgo = arguments.setdefault("ProdJobSplitAlgo", 'EventBased')
self.prodJobSplitArgs = arguments.setdefault("ProdJobSplitArgs",
{"events_per_job": eventsPerJob,
"events_per_lumi": arguments['EventsPerLumi']})
return MonteCarloWorkloadFactory.__call__(self, workloadName, arguments)
def __call__(self, workflowName, args):
workload = MonteCarloWorkloadFactory.__call__(self, workflowName, args)
delattr(workload.taskIterator().next().steps().data.application.configuration,
'configCacheUrl')
return workload
def __call__(self, workflowName, args):
workload = MonteCarloWorkloadFactory.__call__(self, workflowName, args)
#delattr(workload.taskIterator().next().steps().data.application.configuration,
# 'configCacheUrl')
return workload
