Skip to content
Permalink
master
Switch branches/tags

Name already in use

A tag already exists with the provided branch name. Many Git commands accept both tag and branch names, so creating this branch may cause unexpected behavior. Are you sure you want to create this branch?
Go to file
 
 
Cannot retrieve contributors at this time
"""
A collection of models derived from Conway's Game Of Life.
Experiment classes included.
"""
import importlib
from xentica import core
from xentica import seeds
from xentica.core import color_effects
from xentica.tools.rules import LifeLike
class GameOfLife(core.CellularAutomaton):
"""
The classic CA built with Xentica framework.
It has only one property called ``state``, which is positive
integer with max value of 1.
"""
state = core.IntegerProperty(max_val=1)
class Topology:
"""
Mandatory class for all ``CellularAutomaton`` instances.
All class variables below are also mandatory.
Here, we declare the topology as a 2-dimensional orthogonal
lattice with Moore neighborhood, wrapped to a 3-torus.
"""
dimensions = 2
lattice = core.OrthogonalLattice()
neighborhood = core.MooreNeighborhood()
border = core.TorusBorder()
def emit(self):
"""
Implement the logic of emit phase.
Statements below will be translated into C code as emit kernel
at the moment of class creation.
Here, we just copy main state to surrounding buffers.
"""
for buf in self.buffers:
buf.state = self.main.state
def absorb(self):
"""
Implement the logic of absorb phase.
Statements below will be translated into C code as well.
Here, we sum all neigbors buffered states and apply Conway
rule to modify cell's own state.
"""
neighbors_alive = core.IntegerVariable()
for i in range(len(self.buffers)):
neighbors_alive += self.neighbors[i].buffer.state
is_born = (8 >> neighbors_alive) & 1
is_sustain = (12 >> neighbors_alive) & 1
self.main.state = is_born | is_sustain & self.main.state
@color_effects.MovingAverage
def color(self):
"""
Implement the logic of cell's color calculation.
Must return a tuple of RGB values computed from ``self.main``
properties.
Also, must be decorated by a class from ``color_effects``
module.
Here, we simply define 0 state as pure black, and 1 state as
pure white.
"""
red = self.main.state * 255
green = self.main.state * 255
blue = self.main.state * 255
return (red, green, blue)
class GameOfLifeStatic(GameOfLife):
"""
Game of Life variant with static border made of live cells.
This is an example of how easy you can inherit other models.
"""
class Topology(GameOfLife.Topology):
"""
You can inherit parent class ``Topology``.
Then, override only necessary variables.
"""
border = core.StaticBorder(1)
class GameOfLifeColor(GameOfLife):
"""
Game Of Life variant with RGB color.
This is an example of how to use multiple properties per cell.
"""
state = core.IntegerProperty(max_val=1)
red = core.IntegerProperty(max_val=255)
green = core.IntegerProperty(max_val=255)
blue = core.IntegerProperty(max_val=255)
def emit(self):
"""Copy all properties to surrounding buffers."""
for buf in self.buffers:
buf.state = self.main.state
buf.red = self.main.red
buf.green = self.main.green
buf.blue = self.main.blue
def absorb(self):
"""
Calculate RGB as neighbors sum for living cell only.
Note, parent ``absorb`` method should be called using direct
class access, not via ``super``.
"""
GameOfLife.absorb(self)
red_sum = core.IntegerVariable()
green_sum = core.IntegerVariable()
blue_sum = core.IntegerVariable()
for i in range(len(self.buffers)):
red_sum += self.neighbors[i].buffer.red + 1
green_sum += self.neighbors[i].buffer.green + 1
blue_sum += self.neighbors[i].buffer.blue + 1
self.main.red = red_sum * self.main.state
self.main.green = green_sum * self.main.state
self.main.blue = blue_sum * self.main.state
@color_effects.MovingAverage
def color(self):
"""Calculate color as usual."""
red = self.main.state * self.main.red
green = self.main.state * self.main.green
blue = self.main.state * self.main.blue
return (red, green, blue)
class GameOfLife6D(GameOfLife):
"""
Game of Life variant in 6D.
Nothing interesting, just to prove you can do it with ease.
"""
class Topology(GameOfLife.Topology):
"""
Hyper-spacewalk, is as easy as increase ``dimensions`` value.
However, we are also changing neighborhood to Von Neumann
here, to prevent neighbors number exponential grow.
"""
dimensions = 6
neighborhood = core.VonNeumannNeighborhood()
class LifelikeCA(GameOfLife):
"""Lifelike CA with a flexible rule that could be changed at runtime."""
rule = core.Parameter(
default=LifeLike.golly2int("B3/S23"),
interactive=True,
)
def absorb(self):
"""Implement parent's clone with a rule as a parameter."""
neighbors_alive = core.IntegerVariable()
for i in range(len(self.buffers)):
neighbors_alive += self.neighbors[i].buffer.state
is_born = (self.rule >> neighbors_alive) & 1
is_sustain = (self.rule >> 9 >> neighbors_alive) & 1
self.main.state = is_born | is_sustain & self.main.state
def step(self):
"""Change the rule interactively after some time passed."""
if self.timestep == 23:
self.rule = LifeLike.golly2int("B3/S23")
super().step()
class GOLExperiment(core.Experiment):
"""
Particular experiment for the vanilla Game of Life.
Here, we define constants and initial conditions from which the
world's seed will be generated.
The ``word`` is an RNG seed string. The ``size``, ``zoom`` and
``pos`` are board contstants. The ``seed`` is a pattern used in
the initial board state generation.
``BigBang`` is a pattern when small area initialized with a
high-density random values.
"""
word = "OBEY XENTICA"
size = (640, 360, )
zoom = 3
pos = [0, 0]
seed = seeds.patterns.BigBang(
pos=(320, 180),
size=(100, 100),
vals={
"state": seeds.random.RandInt(0, 1),
}
)
class GOLExperiment2(GOLExperiment):
"""
Another experiment for the vanilla GoL.
Since it is inherited from ``GOLExperiment``, we can redefine only
values we need.
``PrimordialSoup`` is a pattern when the whole board is
initialized with low-density random values.
"""
word = "XENTICA IS YOUR GODDESS"
seed = seeds.patterns.PrimordialSoup(
vals={
"state": seeds.random.RandInt(0, 1),
}
)
class GOLExperimentColor(GOLExperiment):
"""
The experiment for ``GameOfLifeColor``.
Here, we introduce ``fade_out`` constant, which is used in
rendering and slowly fading out the color of cells.
Note, it is only an aestetic effect, and does not affect the real
cell state.
"""
fade_in = 255
fade_out = 10
smooth_factor = 1
seed = seeds.patterns.PrimordialSoup(
vals={
"state": seeds.random.RandInt(0, 1),
"red": seeds.random.RandInt(0, 255),
"green": seeds.random.RandInt(0, 255),
"blue": seeds.random.RandInt(0, 255),
}
)
class GOLExperiment6D(GOLExperiment2):
"""
Special experiment for 6D Life.
Here, we define the world with 2 spatial and 4 looped
micro-dimensions, 3 cells per micro-dimension.
As a result, we get large quasi-stable oscillators, looping over
micro-dimensions. Strangely formed, but nothing interesting,
really.
"""
size = (640, 360, 3, 3, 3, 3)
class DiamoebaExperiment(GOLExperiment):
"""Experiment with the interactive rule."""
rule = LifeLike.golly2int("B35678/S5678")
def main():
"""Run model/experiment interactively."""
moire = importlib.import_module("moire")
model = GameOfLifeColor(GOLExperimentColor)
gui = moire.GUI(runnable=model)
gui.run()
if __name__ == "__main__":
main()