.. image:: images/sm_SimPy_Logo.png :align: left =========================================================== SimPy Cheatsheet =========================================================== :Authors: - Tony Vignaux , - Klaus Muller :Date: 2004-December-1 :SimPy version: 1.5.1 :Web-site: http://simpy.sourceforge.net/ :Python-Version: 2.2, 2.3, 2.4 .. contents:: Contents :depth: 3 This describes version 1.5.1 of *SimPy*. Changes from Versions 1.4.x ----------------------------------- There have been no changes to the SimPy 1.4 API, so existing code under SimPy 1.5 works as before. There are two new synchronization/scheduling facilities (see `Advanced synchronization/scheduling commands`_): - events and signalling, with **yield waitevent** and **yield queueevent** - process waiting for arbitrary conditions, with **yield waituntil** SimPy ------------------- This document briefly outlines the commands available in *SimPy*. It refers to *SimPy* version 1.5 or later. The facilities described require Python 2.2 or later. (When using Python 2.2, the following import statement must be used at the head of SimPy scripts: **from __future__ import generators**) A SimPy model is made up of Processes_, Resources_ and Monitors_ and operations on them. Basic structure of a *SimPy* simulation: - **from SimPy.Simulation import *** which imports all facilities for the simulation program. - **initialize()** which sets up the simulation model - *... the activation of at least one process....* - **simulate(until=endtime)** starts the simulation which will run until one of the following: * there are no more events to execute. *now()==last event time* * the simulation time reaches *endtime*. *now()==endtime* * the *stopSimulation()* command is executed. *now()==stop time* **now()** always returns the current simulation time and **stopSimulation()** will stop all simulation activity. Processes ------------------- Processes inherit from class **Process**, imported from SimPy.Simulation. * **class Pclass(Process):** defines a new Process class (here, *Pclass*). Such a class must have a Process Execution Method (PEM) and may have an *__init__* and other methods: - **__init__(self,..)**, the first line of which must be a call to the Class *__init__* in the form: *Process.__init__(self,name='a_process')*. Other commands can be used to initialize attributes of the object. - **A Process execution method (PEM)**, which may have arguments, describes the actions of a process object and must contain at least one of the *yield* statements to make it a Python generator function. The *yield* statements are: * **yield hold,self,t** to execute a time delay of length *t* (unless the process is interrupted, see below). The process continues at the statement following after a delay in simulated time. * **yield passivate,self** to suspend operations indefinitely. * **yield request,self,r** (see `Resources`_, below) * **yield request,self,rp,priority** (see `Resources`_, below) * **yield release,self,r** (see `Resources`_, below) * **p = Pclass(..)**, constructs a new *Pclass* object, called, *p*, where the arguments are those specified in the Class's *__init__* method. Starting and stopping SimPy Processes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ By the process itself: * **yield passivate,self** suspends the process itself. By other processes: * **activate(p,p.execute(args),at=t,delay=period,prior=boolean)** activates the execution method *p.execute()** of Process *p* with arguments *args*. The default action is to activate at the current time, otherwise one of the optional timing clauses operate. If *prior==True*, the process will be activated before any others in the event list at the specified time. * **reactivate(p,at=t,delay=period,prior=boolean)** will reactivate *p* after it has been passivated. The optional timing clauses work as for *activate*. * **self.cancel(p)** deletes all scheduled future events for process *p*. Note: This new format replaces the *p.cancel()* form of earlier SimPy versions. Asynchronous interruptions ~~~~~~~~~~~~~~~~~~~~~~~~~~ * **self.interrupt(victim)** interrupts another process. The interrupt is just a signal. After this statement, the interrupting process immediately continues its current method. The *victim* must be *active* to be interrupted (that is executing a *yield hold,self,t*) otherwise the interruption has no effect. The introduction of interrupts changes the semantics of *yield hold*. After *before=now(); yield hold,self,T*, we have the post-condition *now()== before+T OR (self.interrupted() AND now()< before+T)*. The program must allow for this, i.e., for interrupted, incomplete activities. When interrupted, the *victim* prematurely and immediately returns from its *yield hold*. It can sense if it has been interrupted by calling: * **self.interrupted()** which returns *True* if it has been interrupted. If so: * *self.interruptCause* gives the *interruptor* instance. * *self.interruptLeft* is the time remaining in the interrupted *yield hold,* The interruption is reset at the *victims* next call to a *yield hold,*. Alternatively it can be reset by calling * **self.interruptReset()** .. --------------------------------------------------------------------- Resources ------------------- The modeller may define Resources. These inherit from class *Resource* which is imported at the start of the program: *from SimPy.Simulation import Resource* A *Resource*, *r*, is established using the command: * **r = Resource(capacity=1, name='a_resource', unitName='units', qType=FIFO, preemptable=0, monitored=False)** - *capacity* is the number of identical units of the resource available. Its default setting is 1 but can be any positive integer. - *name* is the name by which the resource is known (eg *gasStation*) - *unitName* is the name of a unit of the resource (eg *pump*) - *qType* describes the queue discipling of the waiting queue of processes; typically, this is *FIFO* (First-in, First-out). and this is the default. An alternative is *PriorityQ* (see below) - *preemptable* indicates, if it has a non-zero value, that a process being put into the *PriorityQ* may also pre-empt a lower-priority process already using a unit of the resource. This only has an effect when *qType == PriorityQ* (see below) - *monitored* indicates if the number of processes in the resource's queues (see below) are to be monitored (see Monitors_, below) A Resource, *r*, has the following attributes: - *r.n* The number of currently free units - *r.waitQ*, a waiting queue (list) of processes (FIFO by default) The number of Processes waiting is *len(r.waitQ)* - *r.activeQ*, a queue (list) of processes holding units,. The number of Proceeses in the active queue is *len(r.activeQ)* - *r.waitMon* A Monitor recording the number in *r.waitQ* - *r.actMon* A Monitor recording the number in *r.activeQ* A unit of resource, *r*, can be requested and later released by a process using the following yield commands: * **yield request,self,r** to request a unit of resource, **r**. The process may be temporarily queued and suspended until a unit is available. * **yield release,self,r** releases a unit of **r**. This may have the side-effect of allocating the released unit to the next process in the Resource's waiting queue. Requesting resources with priority ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If a *Resource*, *r* is defined with *priority* queueing (that is *qType==PriorityQ*) a request can be made for a unit by: * **yield request,self,r,priority**, where *priority* is real or integer. Larger values of *priority* represent higher priorities and these will go to the head of the *r.waitQ* if there not enough units immediately. Requesting a resource with preemptive priority ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ If a *Resource*, *r*, is defined with *priority* queueing (that is *qType=PriorityQ*) and also *preemption* (that is *preemptable=1*) a request can be made for a unit by: * **yield request,self,r,priority**, where *priority* is real or integer. Larger values of *priority* represent higher priorities and if there are not enough units available immediately, one of the active processes may be preempted. If there are several lower priority processes, that with the lowest priority is suspended, put at the front of the *waitQ* and the higher priority, preempting process gets its resource unit and is put into the *activeQ*. The preempted process is the next one to get a resource unit (unless another preemption occurs). The time for which the preempted process had the resource unit is taken into account when the process gets into the *activeQ* again. Thus, the total hold time is always the same, regardless of whether or not a process gets preempted. Random variates ------------------- *SimPy* uses the standard random variate routines in the Python *random* module. To use them, import the random module: * **from random import Random** * **g = Random([seed])** defines a random variable object *g* using a large integer, *seed* to initialize the sequence. A good range of distributions is available. For example: * **g.random()**, returns the next (uniform) random number between 0 and 1 * **g.expovariate(lambd)**, returns a sample from the exponential distribution with mean *1.0/lambd*. * **g.normalvariate(mu,sigma)**, returns a sample from the normal (Gaussian) distribution. *mu* is the mean, and *sigma* is the standard deviation. Advanced synchronization/scheduling commands -------------------------------------------------------------------- SimPy 1.5 introduces two advanced process scheduling, event signalling and a general "wait until" construct. They complement the existing scheduling facilities, such as *yield hold*, and can make the implementation of many simulation models easier. Because they are higher level constructs,they can lead to much clearer and shorter scripts. Signalling between processes ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ Events in *SimPy* are implemented by class **SimEvent**. This name was chosen because the term 'event' is already being used in Python for e.g. Tkinter events or in Python's standard library module *signal -- Set handlers for asynchronous events*. An instance of a SimEvent is generated by something like **myEvent=SimEvent("MyEvent")**. Associated with a SimEvent are - a boolean **occurred** to show whether an event has happened (has been signalled) - a list **waits**, implementing a set of processes waiting for the event - a list **queues**, implementing a FIFO queue of processes queueing for the event - an attribute **signalparam** to receive an (optional) payload from the **signal** method Processes can *wait* for events by issuing: **yield waitevent,self,** can be: - an event variable, e.g. *myEvent*) - a tuple of events, e.g. *(myEvent,myOtherEvent,TimeOut)*, or - a list of events, e.g. *[myEvent,myOtherEvent,TimeOut]* Processes can *queue* for events by issuing: **yield queueevent,self,** (with as defined above) If one of the events in ** has already happened, the process contines. The *occurred* flag of the event(s) is toggled to False. If none of the events in the ** has happened, the process is passivated after joining the FIFO queue of processes queuing for all the events. The ocurrence of an event is signalled by: **.signal()** The ** is optional. It can be of any Python type. When issued, *signal* causes the *occurred* flag of the event to be toggled to True, if waiting set and and queue are empty. Otherwise, all processes in the event's *waits* list are reactivated at the current time, as well as the first process in its *queues* FIFO queue. "wait until" synchronization -- waiting for any condition ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~ A process can wait for an arbitrary condition by issuing: **yield waituntil,self,** where ** is a reference to a function without parameters which returns the state of the condition to be waited for as a boolean value. The "wait until" construct is the most powerful synchronization construct. It effectively generalizes all other SimPy synchronization constructs, i.e., it could replace all of them (but at a runtime cost). Monitors ---------------------------- Monitors are part of the SimPy package. To define a new Monitor object: * **m=Monitor(name='a_Monitor', ylab='y', tlab='t')**, where *name* is the name of the monitor object, *ylab* and *tlab* are provided as labels for plotting graphs from the data held in the Monitor. Methods: * **m.observe(y [,t])** record the current value of *y* and time *t* (the current time, *now()*, if *t* is missing). * **m.reset([t])** reset the observations. The recorded time series is set to the empty list, *[]* and the starting time to *t* or, if it is missing, to the current simulation time, *now()*. Simple data summaries: * **m.series()**, the recorded time series as a list of data pairs. Each pair, *[t,y]*, records one observation and its time. * **m.yseries()**, a list of the recorded data values. * **m.tseries()**, a list of the recorded times. * **m.count()** the current number of observations. * **m.total()**, the sum of the *y* values * **m.mean()**, the simple average of the observations, unaffected by the time measurements * **m.var()**, the sample variance of the observations. * **m.timeAverage([t])**, the average of the *y* values weighted by the time differences between observations. This is calculated from time 0 (or the last time *m.reset([t])* was called) to time *t* (the current simulation time if *t* is missing). It is assumed that *y* is continuous in time. * **m.histogram(low=0.0,high=100.0,nbins=10)** is a *histogram* object (a derived class of *list*) which contains the number of *y* values in each of its bins. It is calculated from the monitored *y* values. * **m.__str__()**, a string that briefly describes the current state of the monitor. Deprecated methods: The following methods are retained for backwards compatibility but are not recommended. They mey be removed in future releases of SimPy: * **m.tally(y)**, records the current value of *y* and the current time, *now()*. * **m.accum(y [,t])** records the current value of *y* and time *t* (the current time, *now()*, if *t* is missing). .. ------------------------------------------------------------------------- Error Messages ------------------ Advisory messages ~~~~~~~~~~~~~~~~~ These messages are returned by *simulate()*, as in *message=simulate(until=123)*. Upon a normal end of a simulation, *simulate()* returns the message: - **SimPy: Normal exit**. This means that no errors have occurred and the simulation has run to the time specified by the *until* parameter. The following messages, returned by *simulate()*, are produced at a premature termination of the simulation but allow continuation of the program. - **SimPy: No more events at time x**. All processes were completed prior to the endtime given in *simulate(until=endtime)*. - **SimPy: No activities scheduled**. No activities were scheduled when *simulate()* was called. Fatal error messages ~~~~~~~~~~~~~~~~~~~~ These messages are generated when SimPy-related fatal exceptions occur. They end the SimPy program. Fatal SimPy error messages are output to *sysout*. - **Fatal SimPy error: activating function which is not a generator (contains no 'yield')**. A process tried to (re)activate a function which is not a SimPy process (=Python generator). SimPy processes must contain at least one *yield . . .* statement. - **Fatal SimPy error: Simulation not initialized**. The SimPy program called *simulate()* before calling *initialize()*. Monitor error messages ~~~~~~~~~~~~~~~~~~~~~~ - **SimPy: No observations for mean**. No observations were made by the monitor before attempting to calculate the mean. - **SimPy: No observations for sample variance**. No observations were made by the monitor before attempting to calculate the sample variance. - **SimPy: No observations for timeAverage**, No observations were made by the monitor before attempting to calculate the time-average. - **SimPy: No elapsed time for timeAverage**. No simulation time has elapsed before attempting to calculate the time-average. Acknowledgments ------------------- We will be grateful for any corrections or suggestions for improvements to the document. :Version: $Revision: 1.1.1.2.2.1 $ :Python-Version: 2.2, 2.3, 2.5 :Created: 2002-December-10 .. Local Variables: mode: indented-text indent-tabs-mode: nil sentence-end-double-space: t fill-column: 70 End: