From 1e346990048b826451eb6f46134bb09f9b57f3d3 Mon Sep 17 00:00:00 2001
From: Johann Dreo <johann.dreo@thalesgroup.com>
Date: Wed, 24 Dec 2014 15:42:15 +0100
Subject: [PATCH] Add the original Conway rules.

Use it as the demo.
Add the size as an argument option of the script.
Beautify.
---
 life.py | 99 +++++++++++++++++++++++++++++++++++++++++++++------------
 1 file changed, 79 insertions(+), 20 deletions(-)

diff --git a/life.py b/life.py
index a35ae57..7f3b7e7 100644
--- a/life.py
+++ b/life.py
@@ -6,32 +6,76 @@ import random
 def count( node, states, board, graph ):
     """Count the number of neighbours in each given states, in a single pass."""
     nb = {s:0 for s in states}
-
     for neighbor in graph[node]:
         for state in states:
             if board[neighbor] == state:
                 nb[state] += 1
-
-    # This is the max size of the neighborhood on a rhomb Penrose tiling (P2)
-    assert( all(nb[s] <= 11 for s in states) )
-
     return nb
 
 
-class Goucher:
+class Rule:
+    """The template to create a rule for a game of life.
+
+    A rule is just a set of states and a function to compute the state of a given node,
+    given the current board states and a neighborhood represented by an adjacency graph."""
+
+    class State:
+        default = 0
+
+    # Available states, the first one should be the default "empty" (or "dead") one.
+    states = [State.default]
+
+    def __call__(self, node, board, graph ):
+        raise NotImplemented
+
+
+class Conway(Rule):
+    """The original rules for Conway's game of life on square grid."""
+
+    class State:
+        dead = 0
+        live = 1
+
+    states = [State.dead, State.live]
+
+    def __call__(self, node, board, graph ):
+        # "a" is just a shortcut.
+        a = self.State()
+        next = a.dead
+
+        nb = count( node, [a.live], board, graph )
+        if board[node] is a.dead:
+            if nb[a.live] == 3: # reproduction
+                next = a.live
+        else: 
+            assert(board[node] is a.live)
+
+            if nb[a.live] < 2: # under-population
+                next = a.dead
+            elif nb[a.live] > 3: # over-population
+                next = a.dead
+            else: 
+                assert( 2 <= nb[a.live] <= 3 )
+                next = a.live
+
+        return next
+
+
+class Goucher(Rule):
+    """This is the Goucher 4-states rule.
+    It permits gliders on Penrose tiling.
+    From: Adam P. Goucher, "Gliders in cellular automata on Penrose tilings", J. Cellular Automata, 2012"""
+
     class State: # Should be an Enum in py3k
         ground = 0
         head = 1
         tail = 2
         wing = 3
 
-    # Available states, the first one is the default "empty" (or "dead") one.
     states = [ State.ground, State.head, State.tail, State.wing ]
 
     def __call__(self, node, current, graph ):
-        """This is the Goucher 4-states rule.
-        From: Adam P. Goucher, "Gliders in cellular automata on Penrose tilings", J. Cellular Automata, 2012
-        Summarized as:
+        """Summarized as:
         ------------------------------------------------------
         | Current state |  Neighbour condition  | Next state |
         ------------------------------------------------------
@@ -51,7 +95,11 @@ class Goucher:
 
         if current[node] is a.ground:
             # Count the number of neighbors of each state in one pass.
-            nb = count( node, [a.head,a.tail,a.wing], current, graph )
+            stated = [a.head,a.tail,a.wing]
+            nb = count( node, stated, current, graph )
+            # This is the max size of the neighborhood on a rhomb Penrose tiling (P2)
+            assert( all(nb[s] <= 11 for s in stated) )
+
             if nb[a.head] >= 1 and nb[a.tail] >= 1:
                 next = a.wing
             elif nb[a.head] >= 1 and nb[a.wing] >= 3:
@@ -60,6 +108,8 @@ class Goucher:
         elif current[node] is a.head:
             # It is of no use to compute the number of heads and tails if the current state is not ground.
             nb = count( node, [a.wing], current, graph )
+            assert( all(nb[s] <= 11 for s in [a.wing]) )
+
             if nb[a.wing] >= 1:
                 next = a.tail
             else:
@@ -103,29 +153,38 @@ def step( current, graph, rule ):
     return next
 
 
-def play( board, graph, nb_gen, rule ):
+def play( board, graph, rule, nb_gen ):
     for i in range(nb_gen):
         board = step( board, graph, rule )
 
 
 if __name__ == "__main__":
+    import sys
+
     # Simple demo on a square grid torus.
     graph = {}
-    size = 10
+    size = 5
+    if len(sys.argv) >= 2:
+        size = int(sys.argv[1])
+
     for i in range(size):
         for j in range(size):
-            graph[(i,j)] = []
-            # All Moore neighborhood around a coordinate.
-            for di,dj in set(permutations( [0]+[-1,1]*2, 2)):
-                # Use modulo to avoid limits and create a torus.
-                graph[ (i,j) ].append( ( (i+di)%size, (j+dj)%size ) )
 
-    rule = Goucher()
+            # All Moore neighborhood around a coordinate.
+            neighborhood = set(permutations( [0]+[-1,1]*2, 2)) # FIXME ugly
+            assert( len(neighborhood) == 8 )
+
+            graph[(i,j)] = []
+            for di,dj in neighborhood:
+                # Use modulo to avoid limits and create a torus.
+                graph[ (i,j) ].append(( (i+di)%size, (j+dj)%size ))
+
+    rule = Conway()
     # Fill a board with random states.
     board = make_board( graph, lambda x : random.choice(rule.states) )
 
     # Play and print.
-    for i in range(5):
+    for i in range(size):
         print i
         for i in range(size):
             for j in range(size):