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This is a Python implementation of elementary cellular automata.

pip install rule_n

Download `rule_n.py` and put it somewhere in your Python path.

import rule_n rule_110 = rule_n.RuleN(110) rule_30 = rule_n.RuleN(30) rule_184 = rule_n.RuleN(184) # Works with anything from 1 to 255 rule_110 = rule_n.RuleN() # Default rule is 110, as that is the most common from rule_n import rule_90 # Shorthand for rule_90 = rule_n.RuleN(90) # Works with 110, 30, 90, 184 # You can also specify a list of rules rule_110 = rule_n.RuleN([False, True, True, False, True, True, True, False]) # Or a string that summarizes the rule rule_110 = rule_n.RuleN("01101110") # See <https://en.wikipedia.org/wiki/Rule_110#Definition> # You can also have a finite canvas rule_110_finite_canvas = rule_n.RuleN(110, canvas_size=5) # A canvas is finite if its size is over 0 data = rule_110.process([True, False, True]) len(data) == 5 # because a False is added to both sides data == [True, True, True, True, False] data_2 = rule_110.process([1, 0, 1]) # You can use any data type, as long data == data_2 # as the boolean values of these are # correct # Return values are always in boolean # With a finite canvas, the output is always as big as the canvas data = rule_110_finite_canvas.process([0, 0, 0, 0, 1]) data == [False, False, False, True, True] data_3 = rule_110([True, False, True]) # Shorthand for # rule_110.process(state) data == data_3 i = 0 for x in rule_110.iterate([1, 0, 1]): # Repeatedly process a state print x i += 1 if i == 10: break # Please do this # Note: Iteration on an infinte canvas seems to have some problems # I recommend using a finite canvas for x in rule_110_finite_canvas.iterate([0, 0, 0, 0, 1]): print x # This breaks automatically if the current state is equal to the # previous, which will probably happen at some point on a finite canvas

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

Donec et mollis dolor. Praesent et diam eget libero egestas mattis sit amet vitae augue. Nam tincidunt congue enim, ut porta lorem lacinia consectetur. Donec ut libero sed arcu vehicula ultricies a non tortor. Lorem ipsum dolor sit amet, consectetur adipiscing elit.

TODO: Figure out how to actually get changelog content.

Changelog content for this version goes here.

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File Name & Checksum SHA256 Checksum Help | Version | File Type | Upload Date |
---|---|---|---|

rule_n-0.2.1-py2.py3-none-any.whl (7.4 kB) Copy SHA256 Checksum SHA256 | 2.7 | Wheel | May 16, 2016 |

rule_n-0.2.1.tar.gz (17.8 kB) Copy SHA256 Checksum SHA256 | – | Source | May 16, 2016 |