Elementary cellular automata in Python
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
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