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A package for complexity science research

Project description

Complexity Science Package


pip install complexity-science

Cellular Automata

Basic usage:

import 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 #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[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.



If iteration is not set, animation will continue infinitely.

Modifying Parameters

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




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.



Network Fragmentation



git clone

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