class is Action in action.py, removed alias Action=Actions

axelrod/__init__.py

@@ -7,7 +7,7 @@
 from .version import __version__
 from .load_data_ import load_pso_tables, load_weights
 from . import graph
-from .actions import Actions
+from .action import Action
 from .random_ import random_choice, seed, Pdf
 from .plot import Plot
 from .game import DefaultGame, Game

axelrod/_strategy_utils.py

@@ -3,12 +3,12 @@
 from functools import lru_cache
 
 from axelrod.player import update_history
-from axelrod.actions import Actions
+from axelrod.action import Action
 from axelrod.strategies.cooperator import Cooperator
 from axelrod.strategies.defector import Defector
 
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 def detect_cycle(history, min_size=1, max_size=12, offset=0):

axelrod/actions.py → axelrod/action.py

@@ -3,10 +3,10 @@
 * Cooperate
 * Defect
 
-Use Actions.C and Actions.D instead of 'C' or 'D'. For convenience you can use:
+Uses the enumeration, Action.C and Action.D. For convenience you can use:
 
-from Axelrod import Actions
-C, D = Actions.C, Actions.D
+from axelrod import Action
+C, D = Action.C, Action.D
 """
 
 from enum import Enum
@@ -18,7 +18,7 @@ def __init__(self, *args):
         super(UnknownActionError, self).__init__(*args)
 
 
-class Actions(Enum):
+class Action(Enum):
 
     C = 1
     D = 0
@@ -34,10 +34,10 @@ def __str__(self):
 
     def flip(self):
         """Returns the opposite Action. """
-        if self == Actions.C:
-            return Actions.D
-        if self == Actions.D:
-            return Actions.C
+        if self == Action.C:
+            return Action.D
+        if self == Action.D:
+            return Action.C
 
     @classmethod
     def from_char(cls, character):
@@ -51,14 +51,11 @@ def from_char(cls, character):
         else:
             raise UnknownActionError('Character must be "C" or "D".')
 
-# Type alias for actions.
-Action = Actions
-
 
 def str_to_actions(actions: str) -> tuple:
     """Takes a string like 'CCDD' and returns a tuple of the appropriate
     actions."""
-    return tuple(Actions.from_char(element) for element in actions)
+    return tuple(Action.from_char(element) for element in actions)
 
 
 def actions_to_str(actions: Iterable[Action]) -> str:

axelrod/deterministic_cache.py

@@ -1,7 +1,7 @@
 from collections import UserDict
 import pickle
 
-from .actions import Action
+from .action import Action
 from .player import Player
 
 from typing import List, Tuple

axelrod/game.py

@@ -1,7 +1,7 @@
-from .actions import Action, Actions
+from .action import Action
 from typing import Tuple, Union
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 Score = Union[int, float]
 

axelrod/interaction_utils.py

@@ -11,11 +11,11 @@
 import csv
 import tqdm
 
-from axelrod.actions import Actions, str_to_actions
+from axelrod.action import Action, str_to_actions
 from .game import Game
 
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 def compute_scores(interactions, game=None):
@@ -282,7 +282,7 @@ def string_to_interactions(string):
     interactions = []
     interactions_list = list(string)
     while interactions_list:
-        p1action = Actions.from_char(interactions_list.pop(0))
-        p2action = Actions.from_char(interactions_list.pop(0))
+        p1action = Action.from_char(interactions_list.pop(0))
+        p2action = Action.from_char(interactions_list.pop(0))
         interactions.append((p1action, p2action))
     return interactions

axelrod/match.py

@@ -1,14 +1,14 @@
 from math import ceil, log
 import random
 
-from axelrod.actions import Actions
+from axelrod.action import Action
 from axelrod.game import Game
 from axelrod import DEFAULT_TURNS
 import axelrod.interaction_utils as iu
 from .deterministic_cache import DeterministicCache
 
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 def is_stochastic(players, noise):

axelrod/mock_player.py

@@ -1,11 +1,11 @@
 from itertools import cycle
 
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 
 from typing import List
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class MockPlayer(Player):

axelrod/player.py

@@ -6,13 +6,13 @@
 
 import numpy as np
 
-from axelrod.actions import Actions
+from axelrod.action import Action
 from .game import DefaultGame
 
 import types
 from typing import Dict, Any
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 # Strategy classifiers

axelrod/random_.py

@@ -1,6 +1,6 @@
 import random
 import numpy
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 
 
 def random_choice(p: float = 0.5) -> Action:
@@ -19,15 +19,15 @@ def random_choice(p: float = 0.5) -> Action:
     axelrod.Action
     """
     if p == 0:
-        return Actions.D
+        return Action.D
 
     if p == 1:
-        return Actions.C
+        return Action.C
 
     r = random.random()
     if r < p:
-        return Actions.C
-    return Actions.D
+        return Action.C
+    return Action.D
 
 
 def randrange(a: int, b: int) -> int:

axelrod/result_set.py

@@ -4,13 +4,13 @@
 from numpy import mean, nanmedian, std
 import tqdm
 
-from axelrod.actions import Actions, str_to_actions
+from axelrod.action import Action, str_to_actions
 import axelrod.interaction_utils as iu
 from . import eigen
 from .game import Game
 
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 def update_progress_bar(method):

axelrod/strategies/adaptive.py

@@ -1,9 +1,9 @@
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 
 from typing import List
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Adaptive(Player):

axelrod/strategies/alternator.py

@@ -1,7 +1,7 @@
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Alternator(Player):

axelrod/strategies/ann.py

@@ -1,12 +1,12 @@
 import numpy as np
 
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 from axelrod.load_data_ import load_weights
 
 from typing import List, Tuple
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 nn_weights = load_weights()
 
 

axelrod/strategies/apavlov.py

@@ -1,7 +1,7 @@
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class APavlov2006(Player):

axelrod/strategies/appeaser.py

@@ -1,7 +1,7 @@
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Appeaser(Player):

axelrod/strategies/averagecopier.py

@@ -1,8 +1,8 @@
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 from axelrod.random_ import random_choice
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class AverageCopier(Player):

axelrod/strategies/axelrod_first.py

@@ -4,7 +4,7 @@
 
 import random
 
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 from axelrod.random_ import random_choice
 from axelrod.strategy_transformers import FinalTransformer
@@ -14,7 +14,7 @@
 
 from typing import List, Dict, Tuple
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Davis(Player):

axelrod/strategies/axelrod_second.py

@@ -4,11 +4,11 @@
 
 import random
 
-from axelrod.actions import Actions, Action
+from axelrod.action import Action
 from axelrod.player import Player
 from axelrod.random_ import random_choice
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Champion(Player):

axelrod/strategies/backstabber.py

@@ -1,8 +1,8 @@
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 from axelrod.strategy_transformers import FinalTransformer
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 @FinalTransformer((D, D), name_prefix=None)  # End with two defections

axelrod/strategies/better_and_better.py

@@ -1,8 +1,8 @@
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 from axelrod.random_ import random_choice
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class BetterAndBetter(Player):

axelrod/strategies/calculator.py

@@ -1,9 +1,9 @@
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 from .axelrod_first import Joss
 from axelrod._strategy_utils import detect_cycle
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Calculator(Player):

axelrod/strategies/cooperator.py

@@ -1,7 +1,7 @@
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Cooperator(Player):

axelrod/strategies/cycler.py

@@ -1,10 +1,10 @@
 import copy
 import itertools
 
-from axelrod.actions import Actions, Action, str_to_actions
+from axelrod.action import Action, str_to_actions
 from axelrod.player import Player
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class AntiCycler(Player):

axelrod/strategies/darwin.py

@@ -3,10 +3,10 @@
 indicated by their classifier). We do not recommend putting a lot of time in to
 optimising it.
 """
-from axelrod.actions import Action, Actions
+from axelrod.action import Action
 from axelrod.player import Player
 
-C, D = Actions.C, Actions.D
+C, D = Action.C, Action.D
 
 
 class Darwin(Player):