Merge pull request #410 from Axelrod-Python/284

More refactoring of payoff.py and cooperation.py

Author: marcharper

axelrod/cooperation.py

@@ -1,6 +1,7 @@
 from math import sqrt
 from . import eigen
 from axelrod import Actions
+from axelrod.payoff import player_count
 
 C, D = Actions.C, Actions.D
 
@@ -48,31 +49,7 @@ def cooperation_matrix(interactions):
         and column (j) represents an individual player and the the value Cij
         is the number of times player i cooperated against opponent j.
     """
-
-    # The number of ways (c) to select groups of r members from a set of n
-    # members is given by:
-    #
-    #     c = n! / r!(n - r)!
-    #
-    # In this case, we are selecting pairs of players (p) and thus r = 2,
-    # giving:
-    #
-    #     p = n(n-1) / 2 or p = (n^2 - n) / 2
-    #
-    # However, we also have the case where each player plays itself gving:
-    #
-    #     p = (n^2 + n) / 2
-    #
-    # Using the quadratic equation to rearrange for n gives:
-    #
-    #     n = (-1 +- sqrt(1 + 8p)) / 2
-    #
-    # Taking only the real roots allows us to derive the number of players
-    # given the number of pairs:
-    #
-    #     n = (sqrt(8p + 1) -1) / 2
-
-    nplayers = int((sqrt(len(interactions) * 8 + 1) - 1) / 2)
+    nplayers = player_count(interactions)
     cooperation = [[0 for i in range(nplayers)] for j in range(nplayers)]
     for players, actions in interactions.items():
         p1_actions, p2_actions = zip(*actions)

axelrod/payoff.py

@@ -5,8 +5,63 @@
 C, D = Actions.C, Actions.D
 
 
+def player_count(interactions):
+    """
+    The number of players derived from a dictionary of interactions
+
+    Parameters
+    ----------
+    interactions : dictionary
+        A dictionary of the form:
+
+        e.g. for a round robin between Cooperator, Defector and Alternator
+        with 2 turns per round:
+        {
+            (0, 0): [(C, C), (C, C)].
+            (0, 1): [(C, D), (C, D)],
+            (0, 2): [(C, C), (C, D)],
+            (1, 1): [(D, D), (D, D)],
+            (1, 2): [(D, C), (D, D)],
+            (2, 2): [(C, C), (D, D)]
+        }
+
+        i.e. the key is a pair of player index numbers and the value, a list of
+        plays. The list contains one pair per turn in the round robin.
+        The dictionary contains one entry for each combination of players.
+
+    Returns
+    -------
+    nplayers : integer
+        The number of players in the round robin
+
+        The number of ways (c) to select groups of r members from a set of n
+        members is given by:
+
+            c = n! / r!(n - r)!
+
+        In this case, we are selecting pairs of players (p) and thus r = 2,
+        giving:
+
+            p = n(n-1) / 2 or p = (n^2 - n) / 2
+
+        However, we also have the case where each player plays itself gving:
+
+            p = (n^2 + n) / 2
+
+        Using the quadratic equation to rearrange for n gives:
+
+            n = (-1 +- sqrt(1 + 8p)) / 2
+
+        Taking only the real roots allows us to derive the number of players
+        given the number of pairs:
+
+            n = (sqrt(8p + 1) -1) / 2
+    """
+    return int((math.sqrt(len(interactions) * 8 + 1) - 1) / 2)
+
+
 # As yet unused until RoundRobin returns interactions
-def payoff_matrix(interactions, nplayers, game):
+def payoff_matrix(interactions, game):
     """
     The payoff matrix from a single round robin.
 
@@ -50,6 +105,7 @@ def payoff_matrix(interactions, nplayers, game):
         and column (j) represents an individual player and the the value Pij
         is the payoff value for player (i) versus player (j).
     """
+    nplayers = player_count(interactions)
     payoffs = [[0 for i in range(nplayers)] for j in range(nplayers)]
     for players, actions in interactions.items():
         payoff = interaction_payoff(actions, game)

axelrod/tests/unit/test_payoff.py

@@ -63,9 +63,9 @@ def setUpClass(cls):
         cls.expected_wins = [[2, 0], [0, 0], [0, 2]]
 
         cls.diff_means = [
-            [ 0. ,  0. ,  0.5],
-            [ 0. ,  0. , -0.5],
-            [-0.5,  0.5,  0. ]
+            [0.0,  0.0,  0.5],
+            [0.0,  0.0, -0.5],
+            [-0.5,  0.5,  0.0]
         ]
 
         cls.expected_score_diffs = [
@@ -74,8 +74,14 @@ def setUpClass(cls):
             [-1.0, 0.0, 0.0, 1.0, 0.0, 0.0]
         ]
 
+    def test_player_count(self):
+        nplayers = ap.player_count(self.interactions)
+        self.assertEqual(nplayers, 3)
+        nplayers = ap.player_count({'test': 'test'})
+        self.assertEqual(nplayers, 1)
+
     def test_payoff_matrix(self):
-        payoff_matrix = ap.payoff_matrix(self.interactions, 3, Game())
+        payoff_matrix = ap.payoff_matrix(self.interactions, Game())
         self.assertEqual(payoff_matrix, self.expected_payoff_matrix)
 
     def test_interaction_payoff(self):