pypepa 0.4dev

pypepa is a PEPA library and a toolset for PEPA.

pyPEPA
======

pyPEPA is a PEPA library and a toolset for [Performance Evaluation Process Algebra](http://www.dcs.ed.ac.uk/pepa/http://www.dcs.ed.ac.uk/pepa/) (PEPA) by Jane
Hillston. pyPEPA is not a fully PEPA compatible tool, it supports a limited (for now) PEPA syntax (we only allow `<>` operator in system equation), i.e. it does not suport hiding operator (e.g. `P\{a,b,}` ), does not support rates as mathematical expressions (`r= 2*x+y`), does not calculate utilization or passage time. pyPEPA also does not use Kronecker state space representation and Hillston's aggregation algorithms, so it can have worse performance than the PEPA Eclipse Plugin.
All these features, plus more, are planned to be added in next versions. Currently I am working on pyPEPA by myself only but if you are willing to help, just send an email to me or put a pull request.

**Warning: pyPEPA is under development, this is a beta software**


pyPEPA consist of three parts:

1. libpepa - a library written in python (mostly 3.3+ conformant)
2. pyPEPA - a command line tool for solving and graphing
3. distr/ - map reduce tools for solving large PEPA experiments


Installation
============
### Package

1. Clone the project

`git clone [e-mail]:tdi/pyPEPA.git pypepa`

`cd pypepa`

2. Run install

`python setup.py install`


### Virtualenv and pip

For the current version I recommend installing in a virtualenv.

1. Clone the project

`git clone [e-mail]:tdi/pyPEPA.git pypepa`

`cd pypepa`

2. Make a virtualenv

`mkvirtualenv -p /usr/bin/python3 pypepa`

`workon pypepa`

3. Install all requirements

`pip install pyparsing colorama numpy scipy matplotlib`


pypepa
======

### Basic arguments

Show help command:

pypepa -h

Set logging level (the default is NONE):

pypepa --log {DEBUG, INFO, ERROR, NONE}

### Calculations


Calculate steady state for bank scenario. The putput is by default directed to your terminal.

pypepa -st models/bankscenario.pepa

Statespace of models/bankscenario.pepa.1 has 7 states

Steady state vector
Using ; delimiter
1;Idle,WaitingForCustomer,WaitingForEmployee;0.08333333333333337
2;Informed,WaitingForCustomer,WaitingForEmployee;0.25
3;WaitingBankResponse,RequestReceived,WaitingForEmployee;0.16666666666666666
4;WaitingBankResponse,CustomerNotReliable,WaitingForEmployee;0.16666666666666666
5;WaitingBankResponse,CustomerReliable,WaitingForEmployee;0.16666666666666666
6;WaitingBankResponse,WaitingManagerResponse,EvaluatingOffer;0.08333333333333333
7;OfferReceived,WaitingForCustomer,WaitingForEmployee;0.08333333333333333

Calculate actions' throughput:

pypepa -th models/bankscenario.pepa

Statespace of models/bankscenario.pepa.1 has 7 states

Throuhoutput (successful action completion in one time unit)

readInformation 0.08333333333333337
createLoanRequest 0.25
getNotReliableMessage 0.16666666666666666
badOffer 0.08333333333333333
askManager 0.16666666666666666
reset 0.08333333333333333
goodOffer 0.08333333333333333
checkReliability 0.3333333333333333

You can calculate transient time proability for some number of time steps:

pypepa --transient 5 models/bankscenario.pepa

Transient analysis from time 0 to 10

Using ; delimiter
1;Idle,WaitingForCustomer,WaitingForEmployee;0.08351202761947342
2;Informed,WaitingForCustomer,WaitingForEmployee;0.2500169897974121
3;WaitingBankResponse,RequestReceived,WaitingForEmployee;0.16662129023697114
4;WaitingBankResponse,CustomerNotReliable,WaitingForEmployee;0.16657721277634494
5;WaitingBankResponse,CustomerReliable,WaitingForEmployee;0.16657721277634485
6;WaitingBankResponse,WaitingManagerResponse,EvaluatingOffer;0.08328947039778702
7;OfferReceived,WaitingForCustomer,WaitingForEmployee;0.08340579639566591

You can choose a solver by specifying `--solver|-s {direct, sparse}`. By defalt we use sparse solver with LIL matrix becuase it is faster and in overall matrices generated from PEPA models are sparse. There is also an insignificant difference in results.

pypepa allows you to visualize all PEPA components by specifying `-gd` switch. The generated graphiz dot files are by deault saved in `dots` folder in the current directory. You can browse dot files with `xdot`, which you need to install first.

pypepa -gd bankdots models/bankscenario.pepa


Finally pypepa can provide us with a tool for experimentation with rates and actions.
Let's check how throughtput of `askManager` action changes when `rateReset` changes from 1 to 50 with step 1. The default result of this command will be a matplotlib graph.
The format of `-var` is "vartype:varname:value range specifier:value range value". The one valid
vartype for now is `rate`, for value range specifiers you can choose: `range` or `list`. For `range`
you need to provide START, STOP, STEP, whereas for `list` a comma separated list of values.
You can specify other output options with `-f` argument: graph, console, csv.


pypepa.py -var "rate:rateReset:range:1,50,1" -val askManager models/bankscenario.pepa



Instead of `--range` you can specify `--list ` with a custom comma delimited list of values.

### Formatting

You can specify formats of `-st`, `-th` and `--varrate` with a `--format` option.
Currently we support CSV (although `;` not comma delimited), console (the default) and graph (only
for varrate experiments). Additionally you can specify `-o|--output` option with a file argument to
specify where to save the CSV.

pypepa -st models/bankscenario.pepa -f csv -o bank_steady.csv



TODO
====

###Functional

1. Implement rate mathematical expressions with functional rates
2. Implement passage time analysis
3. Implement hiding operator
4. Implement 3d graphs and experiments
5. Implement Kronecker state space and aggregation
6. Implement generalised communication PEPA [genPEPA][genpepa] by Mirco Tribastone
7. Add model manipulation language for reducers
8. Add stochastic probes
9. Add distributed version of BU algorithm

###Non functional

1. Optimize optimize optimize



Licence and credits
===================

Copyright (c) Dariusz Dwornikowski and Poznań University of Technology.
Distributed under the Apache Commons 2.0.



[genpepa]: http://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6354646 "Generalised Communication for Interacting Agents"







.. :changelog:

History
-------

0.4dev (05.06.2013)
+++++++++++++++++++

- Merge with Allan Clark's pull request providing better API
- Changed name from libpepa to pypepa where possible
- First package version, for now only for dev branch
- pypepa cli moved to pypepa.cli for a better packaging