Introduction Classes Opeartions and functions Examples References

SimPy: Simulation in Python

Roberto Solar Gallardo

December 6, 2012

Introduction Classes Opeartions and functions Examples References

What is SimPy?

object-oriented process-based discrete-event simulation languagebased on standard Python

Features

use of pythons generators

declare a function that behaves like an iteratora generator is resumable and can branch control elsewheresemi-coroutines

coroutines - functions that alternate execution with each other

the exit/re-entry points are marked by pythons yield keywords

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Simpy programming

The scheduler

a list of future events is maintained automatically

the scheduler is started by the SimPy command simulate

Elements of discrete-event models

Active elements: entities (Process)

Passive elements: resources (Resource, Level and Store)

General Structure of a SimPy program

define one or more SimPy classes and objects

call the function initialize

create and activate at least one of the active entities

start the simulation by calling simulate

report results

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How it works

Simulation. t - Simpys clock

Simulation. timestamps (heap) - event list (t,priority,instance)

1 class Cliente(Process):

2 def visitar(self,tiempoDeServicio):

3 print now(),self.name, ": He llegado"

4 yield hold,self,tiempoDeServicio

5 print now(),self.name, ": Ya me voy"

6

7 initialize()

8 c=Cliente(name="Roberto")

9 activate(c,c.visitar(tiempoDeServicio=1.0),at=1.0)

10 simulate(until=10.0)

Analysis

line 7: t=0 and timestamps=[]

line 9: put c into timestamps (1.0,indefined,c)

line 4: put self into timestamps (now()+timehold,indefined,self)

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Processes

Features

model an entity with activities

i.e. instances of some class that inherits from SimPys Processclass

each entity has a standard method - Process execution method

Process execution method (PEM)

specifies entities actions in detail

each PEM runs in parallel with (and may interact with) thePEMs of other entities

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Resource facilities

simulates something to be queued for

Resources

model a service point with one or more identical service units

Levels

model a container of homogenous material which can be discrete(boxes, bricks, etc) or continuous (fluid)

Stores

model a list of individual objects

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Monitors

collects simulation data for analysis, statistics, etc

Monitors

used to compile summary statistics such as waiting times andqueue lengths

simple averages and variances

time-weighted averages

histograms

Tallys

is an alternative to Monitor that does essentially the same job butuses less storage space at some cost of speed and flexibility

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Operations and functions (1)

Process interaction statements

activate(pi , pi .pem()[, at = t|delay = period ]) - make aprocess instance (pi ) active

reactivate(pi [, at = now()|delay = 0][, prior = false]) - makea process intance (pi ) active (previously-passivated)

cancel(pi ) - cancels all the events associated with a processintance (pi )

interrupt(pi ) - interrupt pi s current activity

Simulation control statements

initialize() - set simulated time to zero

simulate(until=T ) - execute scheduled activities till T

stopSimulation() - force immediate end of simulation

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Operations and functions (2)

Scheduling statements

yield hold,self,T - reactivate self after T

yield passivate,self - make self passive

yield request,self,resource - request use of resource

yield release,self,resource - give up use of resource

yield put,self,level,N - level is increased N units

yield get,self,level,N - level is decreased N units

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Cliente simple

from SimPy.Simulation import *

class Cliente(Process):

def visitar(self,tiempoDeServicio):

print now(),self.name, ": He llegado"

yield hold,self,tiempoDeServicio

print now(),self.name, ": Ya me voy"

initialize()

c=Cliente(name="Roberto")

activate(c,c.visitar(tiempoDeServicio=1.0),at=1.0)

simulate(until=10.0)

Output1.0 Roberto : He llegado

2.0 Roberto : Ya me voy

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Cliente simple, llegada aleatoria

from SimPy.Simulation import *

from random import gammavariate, seed

class Cliente(Process):

def visitar(self,tiempoDeServicio):

print now(),self.name,": He llegado"

yield hold,self,tiempoDeServicio

print now(),self.name,": Ya me voy"

seed()

initialize()

c=Cliente(name="Roberto");

inicio=gammavariate(4,1);

activate(c,c.visitar(tiempoDeServicio=1.0),at=inicio)

simulate(until=10.0);

Output7.92130825474 Roberto : He llegado

8.92130825474 Roberto : Ya me voy

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Varios clientes

from SimPy.Simulation import *

class Cliente(Process):

def visitar(self,tiempoDeServicio):

print now(),self.name, ": He llegado"

yield hold,self,tiempoDeServicio

print now(),self.name, ": Ya me voy"

initialize()

c1=Cliente(name="Roberto")

c2=Cliente(name="Alonso")

c3=Cliente(name="Veronica")

activate(c1,c1.visitar(tiempoDeServicio=3.0),at=1.0)

activate(c2,c2.visitar(tiempoDeServicio=2.4),at=3.0)

activate(c3,c3.visitar(tiempoDeServicio=1.5),at=5.0)

simulate(until=100.0)

Output1.0 Roberto : He llegado

3.0 Alonso : He llegado

4.0 Roberto : Ya me voy

5.0 Veronica : He llegado

5.4 Alonso : Ya me voy

6.5 Veronica : Ya me voy

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Muchos clientes

from SimPy.Simulation import *

class Generador(Process):

def generar(self,totalDeClientes,tasaDeLlegada):

for i in range(totalDeClientes):

c=Cliente(name="Cli-%02d"%(i))

activate(c,c.visitar(tiempoDeServicio=3.5))

yield hold,self,tasaDeLlegada

class Cliente(Process):

def visitar(self,tiempoDeServicio):

print "%2.1f %s: He llegado"%(now(),self.name)

yield hold,self,tiempoDeServicio

print "%2.1f %s: Ya me voy"%(now(),self.name)

initialize()

g=Generador();

activate(g,g.generar(totalDeClientes=5,tasaDeLlegada=2.5))

simulate(until=100.0)

Output0.0 Cli-00: He llegado

2.5 Cli-01: He llegado

3.5 Cli-00: Ya me voy

5.0 Cli-02: He llegado

6.0 Cli-01: Ya me voy

7.5 Cli-03: He llegado

8.5 Cli-02: Ya me voy

10.0 Cli-04: He llegado

11.0 Cli-03: Ya me voy

13.5 Cli-04: Ya me voy

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Muchos clientes, un recurso

from SimPy.Simulation import *

from random import expovariate,seed

class Generador(Process):

def generar(self,totalDeClientes,tasaDeLlegada,recurso):

for i in range(totalDeClientes):

c=Cliente(name="Cli-%02d"%(i))

activate(c,c.visitar(tiempoDeServicio=2.7,recurso=recurso))

t=expovariate(1.0/tasaDeLlegada);

yield hold,self,t

class Cliente(Process):

def visitar(self,tiempoDeServicio=0,recurso=None):

llegada=now()

print "%2.1f %s: He llegado"%(now(),self.name)

yield request,self,recurso

tiempoDeEspera=now()-llegada;

print "%2.1f %s: Tiempo de espera %2.1f"%(now(),self.name,tiempoDeEspera)

yield hold,self,tiempoDeServicio

yield release,self,recurso

print "%2.1f %s: Ya me voy"%(now(),self.name)

recurso=Resource(name="Contador",unitName="Cajero");

seed()

initialize()

g=Generador();

activate(g,g.generar(totalDeClientes=3,tasaDeLlegada=3.0,recurso=recurso),at=0.0)

simulate(until=100.0)

Output0.0 Cli-00: He llegado

0.0 Cli-00: T. Espera 0.0

2.3 Cli-01: He llegado

2.7 Cli-00: Ya me voy

2.7 Cli-01: T. Espera 0.4

3.1 Cli-02: He llegado

5.4 Cli-01: Ya me voy

5.4 Cli-02: T. Espera 2.3

8.1 Cli-02: Ya me voy

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El banco

from SimPy.Simulation import *

from random import expovariate, seed

MEDIA_TIEMPO_DE_SERVICIO=5.0

MEDIA_TIEMPO_DE_LLEGADA=2.5

class Generador(Process):

def generar(self,totalDeClientes,recurso):

for i in range(totalDeClientes):

c=Cliente(name="Cliente-"+str(i));

activate(c,c.visitar(recurso=recurso));

tiempoDeLlegada=expovariate(1.0/MEDIA_TIEMPO_DE_LLEGADA);

yield hold,self,tiempoDeLlegada

class Cliente(Process):

def visitar(self,recurso):

llegada=now()

yield request,self,recurso

tiempoDeEspera=now()-llegada

monitor.observe(tiempoDeEspera);

tiempoDeServicio=expovariate(1.0/MEDIA_TIEMPO_DE_SERVICIO)

yield hold,self,tiempoDeServicio

yield release,self,recurso

seed()

initialize()

monitor=Monitor();

banco=Resource(name="Banco",unitName="Cajero",capacity=2)

generador=Generador(name="Generador")

activate(generador,generador.generar(totalDeClientes=1000,recurso=banco))

simulate(until=2000)

resultado=monitor.count(),monitor.mean()

print "El tiempo promedio de espera de %d atenciones fue %f"%resultado

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SimPlot

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1 http://sourceforge.net/projects/simpy/

2 http://simpy.sourceforge.net/SimPyDocs/_static/

TheBank.pdf

3 http://msor.victoria.ac.nz/twiki/pub/Courses/

OPRE354_2012T2/MoreReferences/LecturesOnSimPy.pdf

4 http://python-ray.googlecode.com/hg-history/

66da0654aaced5c4d2a8d26f2a17707d63c97174/doc/

PyIterGen.pdf

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