This program is an extensible Conway's game of life. It allows to define different type of grid (for example 2D or 3D) and more complex rules. Each grid inherits an Abstract grid that implement the method (next()) to pass for the next configuration. Furthermore, each element can be whatever type. In this example I designed Grid2DBool that represent the simple Conway's game of life, but could be possible to develop and easily implement more complex grids and rules.
Note: The demo save also the animation in a file .mp4 and plot it through pyplot. The demo could take long time because of storing all the configurations before showing the animation. Therefore, the visualization can be improved using other libraries (as wxpython) that paint the configuration of the grid once it's created. With a more complex view it's convenient to apply MVC pattern declaring the model AbstractGrid as the Observable class.
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 102 103 104 105 106 107 108 109 110 111 112 113 114 115 116 117 118 119 120 121 122 123 124 125 126 127 128 129 130 131 132 133 134 135 136 137 138 139 140 141 142 143 144 145 146 147 148 149 150 151 152 153 154 155 156 157 158 159 160 161 162 163 164 165 166 167 168 169 170 171 172 173 174 175 176 177 178 179 180 181 182 183 184 185 186 187 188 189 190 191 192 193 194 195 196 197 198 | #!/usr/bin/python
# -*- coding: utf-8 -*-
import numpy as np
"""
This program is an extensible Conway's game of life. It allows to define
different type of grid (for example 2D or 3D) and more complex rules.
Each grid inherits an Abstract grid that implement the method (next())
to pass for the next configuration.
Furthermore, each element can be whatever type. In this
example I designed Grid2DBool that represent the simple Conway's game of life,
but could be possible to develop and easily implement more complex grids and
rules.
Note:
The demo save also the animation in a file .mp4 and plot it through pyplot.
The demo could take long time because of storing all the configurations before
showing the animation. Therefore, the visualization can be improved using other
libraries (as wxpython) that paint the configuration of the grid once it's
created.
With a more complex view it's convenient to apply MVC pattern declaring the
model AbstractGrid as the Observable class.
@author Filippo Squillace
@date 02/12/2011
@version 0.0.5
"""
class AbstractGrid():
"""
This class represents the abstract grid that implement
the template method to generate the next configuration. The rules are
definied in the abstract method next_state() and it's not
implemented in this class because depends on the structure of the matrix
and the type of elements in the grid.
"""
def __init__(self):
self.matrix = np.array([], dtype=bool)
def __str__(self):
return self.matrix.__str__()
####### Abstract methods ########
def next_state(self, coords, el):
raise NotImplementedError()
def is_done(self):
raise NotImplementedError()
################################
def add_element(self, coords, el):
self.matrix[coords] = el
def next(self):
# copy the matrix
old_matrix = self.matrix.copy()
itr = self.matrix.flat
coords = itr.coords
for el in itr:
old_matrix[coords] = self.next_state(coords, el)
coords = itr.coords
# copy all the modifications
self.matrix = old_matrix
class Grid2D(AbstractGrid):
def __init__(self, n, m, typ=bool):
AbstractGrid.__init__(self)
self.n = n
self.m = m
self.matrix = np.array([None for x in range(n*m)], dtype=typ).reshape(n,m)
class Grid2DBool(Grid2D):
"""
Represents the classical Conway's game of life with 2D grid
and each element can be either True (alive) or Fase (death)
Params:
n - number of rows
m - number of columns
"""
def __init__(self, n, m):
Grid2D.__init__(self, n, m, bool)
def add_element(self, x, y):
t = (x, y)
Grid2D.add_element(self, t, True)
def next_state(self, coords, el):
# Gets all information from the neighbors
(x, y) = coords
neighbors = 0
if x==0:
x1=0
else:
x1=x-1
if x==self.n-1:
x2=self.n-1
else:
x2=x+1
if y==0:
y1=0
else:
y1=y-1
if y==self.m-1:
y2=self.m-1
else:
y2=y+1
for n in self.matrix[x1:x2+1, y1:y2+1].flat:
if n:
neighbors = neighbors + 1
# Excludes the main element
if el:
neighbors = neighbors - 1
if el: # el alives
if neighbors==2 or neighbors==3:
return True
if neighbors<2 or neighbors>3:
return False
else: # el death
if neighbors==3:
return True
def is_done(self):
return not self.matrix.max() # there is no True
def light_spaceship(g, x, y, invert=False):
"""
Puts the lightweight spaceship right in the grid starting from icoords
"""
if not invert:
g.add_element(x,y)
g.add_element(x+2,y)
g.add_element(x+3,y+1)
g.add_element(x+3,y+2)
g.add_element(x+3,y+3)
g.add_element(x+3,y+4)
g.add_element(x+2,y+4)
g.add_element(x+1,y+4)
g.add_element(x,y+3)
else:
g.add_element(x,y)
g.add_element(x+2,y)
g.add_element(x+3,y-1)
g.add_element(x+3,y-2)
g.add_element(x+3,y-3)
g.add_element(x+3,y-4)
g.add_element(x+2,y-4)
g.add_element(x+1,y-4)
g.add_element(x,y-3)
if __name__ == '__main__':
import matplotlib.pyplot as plt
import matplotlib.animation as animation
n = 50
g = Grid2DBool(n, n)
light_spaceship(g, 5,2)
light_spaceship(g, 25,2)
light_spaceship(g, 45,2)
light_spaceship(g, 5,40, True)
light_spaceship(g, 25,40, True)
light_spaceship(g, 45,40, True)
x = np.arange(0, n+1)
y = np.arange(0, n+1)
X,Y = np.meshgrid(x,y)
ims = []
ims.append((plt.pcolor(X, Y, g.matrix),))
counter = 0
while(not g.is_done() and counter < 100):
g.next()
ims.append((plt.pcolor(X, Y, g.matrix),))
counter = counter + 1
fig = plt.figure(1)
im_ani = animation.ArtistAnimation(fig, ims, interval=2,\
repeat_delay=3000,\
blit=True)
im_ani.save('im.mp4')
plt.axis([0, n, n, 0])
plt.axis('off')
plt.show()
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