PyRW

A Python based 2D random walk simulation tool box

Features

Allows any type of 2D domain out of different geometrical features
Allows for any type of random walker, since random walks can be stacked upon each other as superpositions,such as
- Brownian Walker
- Correlated Random Walker
- Composite Random Walker
- Correlated Composite Random Walker
Each random walker can respond to each geometrical feature differently with various implemted boundary conditions
Each random walker can respond to any other random walker differently with various implemted hitting conditions
Live plotting
Final Statistics

Getting Started

Installation

If you have Python2.7 already installed, simply obtain PyRW

git clone https://github.com/alexblaessle/PyRW

and install via:

python setup.py install

Requirements

PyRW only depends on

numpy>=1.8.2
matplotlib>=1.4.3
pickle

and a bunch of standard Python2.7 libraries such as

time
platform
sys

API

The API of pyrw can be found here .

Documentation

The Documentation of pyrw can be found here .

Example

	import pyrw

	#Create RW
	rw=pyrw.RWRW.RW()

	#Grab domain
	d=rw.domain

	#Build circular domain
	vcenter=d.addVertex([0,0])
	c=d.addCircle(vcenter,35)

	##Add run
	r=rw.addNRuns(1)

	#Draw domain
	d.draw(ann=False)

	#Add predator random walker to the middle of the circular domain
	w=rw.addWalker(BCtyp='setBack',typ='pred',HCtyp='stop',RWtyp='CCRW')

	#Add 5 prey random walkers randomly across the domain
	for i in range(5):
		w2=rw.addWalker(BCtyp='setBack',color='m',x0=[-5,1],typ='prey')
		w2.genRandomX0()

	#Define walker of interest
	rw.setVarForAllRuns('walkerOfInterest',w)

	#Run RW
	rw.runs[0].start(plotStep=True)

	#Print Final statistic
	rw.computeStatistics()
	rw.printStatistics()

	raw_input("Done, press [ENTER] to quit")