yield hold, self, tib
yield release, self, counter
# print "%8.4f %s: Finished "%(now(),self.name)
## Experiment data -------------------------
maxTime = 400.0 # minutes
counter = Resource(1, name="Clerk", monitored=True)
## Model -----------------------------------
def model(SEED=393939):
seed(SEED)
initialize()
source = Source()
activate(source, source.generate(number=20, rate=0.1), at=0.0)
simulate(until=maxTime)
## Experiment -----------------------------------
model()
plt = SimPlot()
plt.plotStep(counter.waitMon, color="red", width=2)
plt.mainloop()
# Model -----------------------------------
class BankModel(Simulation):
def run(self, aseed):
""" PEM """
seed(aseed)
self.counter = Resource(1, name="Clerk", monitored=True, sim=self)
source = Source(sim=self)
self.activate(source, source.generate(number=20, rate=0.1), at=0.0)
self.simulate(until=maxTime)
# Experiment data -------------------------
maxTime = 400.0 # minutes
seedVal = 393939
# Experiment -----------------------------------
mymodel = BankModel()
mymodel.run(aseed=seedVal)
# Output ---------------------------------------
plt = SimPlot()
plt.plotStep(mymodel.counter.waitMon, color="red", width=2)
plt.mainloop()
tShopOpen = 8
tBeforeOpen = 1
tEndBake = tBeforeOpen + tShopOpen # hours
nrDays = 100
r = random.Random(12371)
PLOTTING = True
# Experiment
waits = {}
waits["retail"] = []
waits["restaurant"] = []
for day in range(nrDays):
bakery = model()
# Analysis/output
print("bakery")
for cType in ["retail", "restaurant"]:
print("Average wait for {0} customers: {1:4.2f} hours".format(
cType, (1.0 * sum(waits[cType])) / len(waits[cType])))
print("Longest wait for {0} customers: {1:4.1f} hours".format(
cType, max(waits[cType])))
nrLong = len([1 for x in waits[cType] if x > 0.25])
nrCust = len(waits[cType])
print("Percentage of {0} customers having to wait for more than"
" 0.25 hours: {1}".format(cType, 100 * nrLong / nrCust))
if PLOTTING:
plt = SimPlot()
plt.plotStep(bakery.stock.bufferMon,
title="Number of baguettes in stock during arbitrary day",
color="blue")
plt.mainloop()
# Prog3.py from SimPy.SimPlot import * plt = SimPlot() plt.plotStep([[0, 0], [1, 1], [2, 4], [3, 9]], color="red", width=2) plt.mainloop()
# Monitorplot.py
from random import uniform
from SimPy.Simulation import *
from SimPy.Recording import *
from SimPy.SimPlot import *
class Source(Process):
def __init__(self, monitor):
Process.__init__(self)
self.moni = monitor
self.arrived = 0
def arrivalGenerator(self):
while True:
yield hold, self, uniform(0, 20)
self.arrived += 1
self.moni.observe(self.arrived)
initialize()
moni = Monitor(name="Arrivals", ylab="nr arrived")
s = Source(moni)
activate(s, s.arrivalGenerator())
simulate(until=100)
plt = SimPlot()
plt.plotStep(moni, color='blue')
plt.mainloop()
tBakeMin = 25/60.; tBakeMax=30/60. #hours
tArrivals = {"retail":1.0/40,"restaurant":1.0/4} #hours
buy = {"retail":[1,2,3],"restaurant":[20,40,60]} #nr baguettes
tShopOpen = 8; tBeforeOpen = 1; tEndBake = tBeforeOpen+tShopOpen #hours
nrDays=100
r=random.Random(12371)
PLOTTING=True
## Experiment ------------------------------
waits={}
waits["retail"]=[]; waits["restaurant"]=[]
bakMod = BakeryModel()
for day in range(nrDays):
bakery = bakMod.run()
## Analysis/output -------------------------
print 'bakery_OO'
for cType in ["retail","restaurant"]:
print "Average wait for %s customers: %4.2f hours"\
%(cType,(1.0*sum(waits[cType]))/len(waits[cType]))
print "Longest wait for %s customers: %4.1f hours"%(cType,max(waits[cType]))
nrLong = len([1 for x in waits[cType] if x>0.25])
nrCust = len(waits[cType])
print "Percentage of %s customers having to wait for more than 0.25 hours: %s"\
%(cType,100*nrLong/nrCust)
if PLOTTING:
plt = SimPlot()
plt.plotStep(bakery.stock.bufferMon,
title="Number of baguettes in stock during arbitrary day",color="blue")
plt.mainloop()
yield hold, self, tib
yield release, self, counter
#print("%8.4f %s: Finished " % (now(), self.name))
## Experiment data -------------------------
maxTime = 400.0 # minutes
counter = Resource(1, name="Clerk", monitored=True)
## Model -----------------------------------
def model(SEED=393939):
seed(SEED)
initialize()
source = Source()
activate(source,
source.generate(number=20, rate=0.1), at=0.0)
simulate(until=maxTime)
## Experiment -----------------------------------
model()
plt = SimPlot()
plt.plotStep(counter.waitMon,
color="red", width=2)
plt.mainloop()
# Experiment data -------------------------
maxTime = 400.0 # minutes
counter = Resource(1, name="Clerk", monitored=True)
# Model -----------------------------------
def model(SEED=393939): # 3
seed(SEED)
initialize()
source = Source()
activate(
source, # 4
source.generate(number=20, rate=0.1),
at=0.0)
simulate(until=maxTime) # 5
# Experiment -----------------------------------
model()
plt = SimPlot() # 6
plt.plotStep(
counter.waitMon, # 7
color="red",
width=2) # 8
plt.mainloop() # 9