.. image:: images/sm_SimPy_Logo.png
   :align: left

===========================================================
SimPy Cheatsheet
===========================================================

:Authors:  - Tony Vignaux <Vignaux@users.sourceforge.net>,
           - Klaus Muller <Muller@users.sourceforge.net>
:Date: 2003-November-12
:SimPy version: 1.4
:Web-site: http://simpy.sourceforge.net/
:Python-Version: 2.2, 2.3


.. contents:: Contents
   :depth: 2



Changes from Version 1.3
-----------------------------------

There have been changes to Monitor. Old code *should* work but some old
methods, such as *tally* and *accum* are now deprecated and replaced
by *observe(y,t)* 


SimPy
-------------------

This document briefly outlines the commands available in *SimPy*. It
refers to *SimPy* version 1.4 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* 
   
- **stopSimulation()** will stop all simulation activity.

- **now()** always returns the current simulation time.


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 at least these two 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.

    - **An execution method**, 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 Proceeses 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.



Monitors
---------------------------- 

Monitors are part of the SimPy package and can be imported by
*from SimPy.Simulation import Monitor*

To define a new Monitor object:

* **m=Monitor([name])**, where *name* is the name of the monitor
    object, set to *''* if it is missing.

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()** returns the current number of observations.
* **m.total()**, the sum of the *y* values
* **m.mean()**, the simple average of the observations.
* **m.var()**, the sample variance of the observations.
* **m.timeAverage([t])**, the time-average of the *y* values,
  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. See the right hand figure below)
 

.. figure:: images/Mon001.png 
   :scale: 60
   :alt: Different averages

* **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).
 
.. -------------------------------------------------------------------------


SimPlot
---------

This provides an easy way to graph the results of simulation runs. See
the `SimPlot Manual`_.

.. _`SimPlot Manual`: SimPlotManual/ManualPlotting.html


.. -------------------------------------------------------------------------


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: 1.0 $ :Date: $Date: 2004-05-15 11:09:11+02 $ gav
:Python-Version: 2.2, 2.3
:Created: 2002-December-10


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