Merge pull request #817 from Axelrod-Python/init

Refactor Player.__new__ to automatically apply init_args

axelrod/player.py

@@ -77,6 +77,7 @@ def __init__(self, myarg1, ...)
     def wrapper(self, *args, **kwargs):
         r = func(self, *args, **kwargs)
         self.init_args = args
+        self.init_kwargs = kwargs
         return r
     return wrapper
 
@@ -99,6 +100,13 @@ class Player(object):
         'manipulates_state': None
     }
 
+    def __new__(cls, *args, **kwargs):
+        """Caches arguments for Player cloning."""
+        obj = super().__new__(cls)
+        obj.init_args = args
+        obj.init_kwargs = kwargs
+        return obj
+
     def __init__(self):
         """Initiates an empty history and 0 score for a player."""
         self.history = []
@@ -111,7 +119,6 @@ def __init__(self):
         self.cooperations = 0
         self.defections = 0
         self.state_distribution = defaultdict(int)
-        self.init_args = ()
         self.set_match_attributes()
 
     def receive_match_attributes(self):
@@ -162,12 +169,12 @@ def clone(self):
         """Clones the player without history, reapplying configuration
         parameters as necessary."""
 
-        # You may be tempted to reimplement using the `copy` module
+        # You may be tempted to re-implement using the `copy` module
         # Note that this would require a deepcopy in some cases and there may
         # be significant changes required throughout the library.
-        # Consider overriding in special cases only if necessary
+        # Override in special cases only if absolutely necessary
         cls = self.__class__
-        new_player = cls(*self.init_args)
+        new_player = cls(*self.init_args, **self.init_kwargs)
         new_player.match_attributes = copy.copy(self.match_attributes)
         return new_player
 

axelrod/strategies/adaptive.py

@@ -1,4 +1,4 @@
-from axelrod import Actions, Player, init_args
+from axelrod import Actions, Player
 
 C, D = Actions.C, Actions.D
 
@@ -24,7 +24,6 @@ class Adaptive(Player):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self, initial_plays=None):
         super().__init__()
         if not initial_plays:

axelrod/strategies/ann.py

@@ -1,7 +1,7 @@
 # Original Source: https://gist.github.com/mojones/550b32c46a8169bb3cd89d917b73111a#file-ann-strategy-test-L60
 # Original Author: Martin Jones, @mojones
 
-from axelrod import Actions, Player, init_args, load_weights
+from axelrod import Actions, Player, load_weights
 
 C, D = Actions.C, Actions.D
 nn_weights = load_weights()
@@ -62,7 +62,6 @@ class ANN(Player):
         'long_run_time': False
     }
 
-    @init_args
     def __init__(self, weights, num_features, num_hidden):
         super().__init__()
         (i2h, h2o, bias) = split_weights(weights, num_features, num_hidden)
@@ -189,7 +188,6 @@ class EvolvedANN(ANN):
 
     name = "Evolved ANN"
 
-    @init_args
     def __init__(self):
         num_features, num_hidden, weights = nn_weights["Evolved ANN"]
         super().__init__(weights, num_features, num_hidden)
@@ -207,7 +205,6 @@ class EvolvedANN5(ANN):
 
     name = "Evolved ANN 5"
 
-    @init_args
     def __init__(self):
         num_features, num_hidden, weights = nn_weights["Evolved ANN 5"]
         super().__init__(weights, num_features, num_hidden)
@@ -225,7 +222,6 @@ class EvolvedANNNoise05(ANN):
 
     name = "Evolved ANN 5 Noise 05"
 
-    @init_args
     def __init__(self):
         num_features, num_hidden, weights = nn_weights["Evolved ANN 5 Noise 05"]
         super().__init__(weights, num_features, num_hidden)

axelrod/strategies/axelrod_first.py

@@ -4,7 +4,7 @@
 
 import random
 
-from axelrod import Actions, Player, init_args, flip_action, random_choice
+from axelrod import Actions, Player, flip_action, random_choice
 
 from.memoryone import MemoryOnePlayer
 
@@ -34,7 +34,6 @@ class Davis(Player):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self, rounds_to_cooperate=10):
         """
         Parameters
@@ -76,7 +75,6 @@ class RevisedDowning(Player):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self, revised=True):
         super().__init__()
         self.revised = revised
@@ -159,7 +157,6 @@ class Feld(Player):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self, start_coop_prob=1.0, end_coop_prob=0.5,
                  rounds_of_decay=200):
         """
@@ -248,7 +245,6 @@ class Joss(MemoryOnePlayer):
 
     name = "Joss"
 
-    @init_args
     def __init__(self, p=0.9):
         """
         Parameters
@@ -269,7 +265,7 @@ class Nydegger(Player):
     """
     Submitted to Axelrod's first tournament by Rudy Nydegger.
 
-    The program begins with tit for tat for the first three moves, except 
+    The program begins with tit for tat for the first three moves, except
     that if it was the only one to cooperate on the first move and the only one to defect on the second move, it defects on the third move. After the third move, its choice is determined from the 3 preceding outcomes in the following manner.
 
     Let A be the sum formed by counting the other's defection as 2 points and one's own as 1 point, and giving weights of 16, 4, and 1 to the preceding three moves in chronological order. The choice can be described as defecting only when A equals 1, 6, 7, 17, 22, 23, 26, 29, 30, 31, 33, 38, 39, 45, 49, 54, 55, 58, or 61.
@@ -420,7 +416,6 @@ class Tullock(Player):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self, rounds_to_cooperate=11):
         """
         Parameters
@@ -458,7 +453,7 @@ class UnnamedStrategy(Player):
     score than the other player. Unfortunately, the complex process of adjustment
     frequently left the probability of cooperation in the 30% to 70% range, and
     therefore the rule appeared random to many other players.
-    
+
     Names:
 
     - Unnamed Strategy: [Axelrod1980]_

axelrod/strategies/defector.py

@@ -2,6 +2,7 @@
 
 C, D = Actions.C, Actions.D
 
+
 class Defector(Player):
     """A player who only ever defects."""
 

axelrod/strategies/finite_state_machines.py

@@ -1,4 +1,4 @@
-from axelrod import Actions, Player, init_args
+from axelrod import Actions, Player
 
 C, D = Actions.C, Actions.D
 
@@ -47,7 +47,6 @@ class FSMPlayer(Player):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self, transitions=None, initial_state=None,
                  initial_action=None):
         if not transitions:
@@ -91,7 +90,6 @@ class Fortress3(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, D, 2, D),
@@ -121,7 +119,6 @@ class Fortress4(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, C, 1, D),
@@ -151,7 +148,6 @@ class Predator(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (0, C, 0, D),
@@ -195,7 +191,6 @@ class Pun1(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, C, 2, C),
@@ -221,7 +216,6 @@ class Raider(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (0, C, 2, D),
@@ -251,7 +245,6 @@ class Ripoff(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, C, 2, C),
@@ -279,7 +272,6 @@ class SolutionB1(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, C, 2, D),
@@ -307,7 +299,6 @@ class SolutionB5(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, C, 2, C),
@@ -341,7 +332,6 @@ class Thumper(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (1, C, 1, C),
@@ -373,7 +363,6 @@ class EvolvedFSM4(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (0, C, 0, C),
@@ -410,7 +399,6 @@ class EvolvedFSM16(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (0, C, 0, C),
@@ -471,7 +459,6 @@ class EvolvedFSM16Noise05(FSMPlayer):
         'manipulates_state': False
     }
 
-    @init_args
     def __init__(self):
         transitions = (
             (0, C, 8, C),

axelrod/strategies/forgiver.py

@@ -2,6 +2,7 @@
 
 C, D = Actions.C, Actions.D
 
+
 class Forgiver(Player):
     """
     A player starts by cooperating however will defect if at any point

axelrod/strategies/gambler.py

@@ -5,7 +5,7 @@
  https://gist.github.com/GDKO/60c3d0fd423598f3c4e4
 """
 
-from axelrod import Actions, random_choice, load_pso_tables
+from axelrod import Actions, load_pso_tables, random_choice
 from .lookerup import LookerUp, create_lookup_table_from_pattern
 
 

axelrod/strategies/geller.py

@@ -1,11 +1,10 @@
-# -*- coding: utf-8 -*-
-
 import inspect
 
 from axelrod import Actions, Player, random_choice
 
 C, D = Actions.C, Actions.D
 
+
 class Geller(Player):
     """Observes what the player will do in the next round and adjust.