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A package for complexity science research

Project description

Complexity Science Package

Download

pip install complexity-science


Cellular Automata

Basic usage:

import complexity_science.ca as cs

1-D CA

ca = cs.wolfram(N, 20) #creates a 1-Dimensional CA of N cells with wolfram rule number 20

ca.initialize([50]) #initializes the 50th cell of the CA

ca.run(100) #returns the resulting state of the CA for 100 iterations following the rule and plots the result with a default colormap

2-D CA

model = cs.brians_brain([128,128], toroidal=False)

Initializes a CA based on brians brain with toroidal boundary conditions

Available models

cs.game([dim], toroidal=True)

cs.applause([dim], alpha=1)

cs.mpa([dim], percent_mpa=0)

The dim parameter is the only required parameter for all models, others are optional. Parameters are set to default value if not specified.

alpha and percent_mpa are examples of model specific parameters.

See model documentation for more information.

Animation

model.animate(iteration=100)

If iteration is not set, animation will continue infinitely.

Modifying Parameters

Models can be initialized randomly, binary, by index, using different functions e.g.

model.initialize_random()

model.initialize_random_bin(0.5)

model.initialize_random_int(0,2)

Models with specific parameters can be modified by this function.

model.modify_rule(parameter = new_value)

See model documentation for more information

Adding rules and models

Please contact the author for more information.


Epidemics

COMING SOON!

Network Fragmentation

COMING SOON!

Contributing:

git clone https://github.com/KristerJazz/complexity-science.git

Project details


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