44 lines
1.5 KiB
Python
44 lines
1.5 KiB
Python
#!/usr/bin/env python3
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import random
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from multiprocessing import freeze_support
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from cellular_automaton import *
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class TestRule(Rule):
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@staticmethod
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def evolve_cell(last_cell_state, neighbours_last_states):
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try:
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return neighbours_last_states[0]
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except IndexError:
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return last_cell_state
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class MyState(SynchronousCellState):
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def __init__(self):
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rand = random.randrange(0, 101, 1)
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init = max(.0, float(rand - 99))
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super().__init__((init,), draw_first_state=init > 0)
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def get_state_draw_color(self, iteration):
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state1 = self.get_state_of_iteration(iteration)[0]
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return [255 if state1 else 0, 0, 0]
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def make_cellular_automaton(dimension, neighborhood, rule, state_class):
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cells = CAFactory.make_cellular_automaton(dimension=dimension, neighborhood=neighborhood, state_class=state_class)
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return CellularAutomaton(cells, dimension, rule)
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if __name__ == "__main__":
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freeze_support()
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random.seed(1000)
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# best single is 400/400 with 0,2 ca speed and 0,09 redraw / multi is 300/300 with 0.083
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neighborhood = MooreNeighborhood(EdgeRule.FIRST_AND_LAST_CELL_OF_DIMENSION_ARE_NEIGHBORS)
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ca = make_cellular_automaton(dimension=[100, 100], neighborhood=neighborhood, rule=TestRule(), state_class=MyState)
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ca_processor = CellularAutomatonMultiProcessor(cellular_automaton=ca, process_count=4)
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ca_window = PyGameFor2D(window_size=[1000, 800], cellular_automaton=ca)
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ca_window.main_loop(cellular_automaton_processor=ca_processor, ca_iterations_per_draw=1)
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