def measureExecutionTime(runsNeeded, threadCount):
startTime = int(round(time.time() * 1000))
runsDone = 0
runsStarted = 0
allResults = []
# Create and reuse threadCount number of workspaces
for i in range(0, threadCount):
workspace = nl4py.newNetLogoHeadlessWorkspace()
workspace.openModel('models/Wolf Sheep Predation.nlogo')
simulate(workspace)
runsStarted = runsStarted + 1
# repeat until runsNeeded is satisfied
while (runsDone < runsNeeded):
# check if workspaces are done. If so, get results and
# start another model run on the workspace, keeping the
# number of workspaces constant
for workspace in nl4py.getAllHeadlessWorkspaces():
newResults = workspace.getScheduledReporterResults()
# getScheduledReporterResults() is non-blocking
# and can return an empty list if the model is
# still running. Check that the model is done by
# checking if the list is not empty.
if len(newResults) > 0:
allResults.extend(newResults)
runsDone = runsDone + 1
if runsStarted < runsNeeded:
# start another simulation if required.
simulate(workspace)
runsStarted = runsStarted + 1
stopTime = int(round(time.time() * 1000))
return (stopTime - startTime)
print('\n2) Starting the model runs... ')
model = "C://Users//Mateen Qureshi//Documents//CSCI378//AFM Initial Migration.nlogo"
n = None
print(
'\n Creating ' + str(n) +
' NetLogo HeadlessWorkspaces with: workspace = nl4py.newNetLogoHeadlessWorkspace()\n and clearing any old workspaces with nl4py.deleteAllHeadlessWorkspaces()'
)
print(
'\n Opening the ' + model +
' model on the NetLogo HeadlessWorkspace with: workspace.openModel("model")'
)
nl4py.deleteAllHeadlessWorkspaces()
workspace = nl4py.newNetLogoHeadlessWorkspace()
workspace.openModel(model)
print(
"\n Setting the parameters to random values with workspace.setParamsRandom()"
)
workspace.setParamsRandom()
# workspace.command('set model-version "sheep-wolves-grass"')
print('\n Send setup command to model using: workspace.command("setup")')
workspace.command("setup")
print(
'\n Schedule reporters to the model to report the ticks passed, the model\'s two stop conditions and number of sheep and wolves for each tick for 100 ticks,\n using: workspace.scheduleReportersAndRun(reporters,0,1,100,"go")'
)