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add freqAnalyzer strategy (#1444)
* add freqAnalyzer strat * cleanup + wip * remove spurious changes * fixed freq analyzer test * Delete axelrod/tests/strategies/test_freqanalyzer.py * bump num strats * remove unnecessary lines * fix type error * fix test * formatting * python black with correct options * add strat to index * code cleanup
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‎axelrod/strategies/_strategies.py‎

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)
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from .shortmem import ShortMem
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from .stalker import Stalker
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from .frequency_analyzer import FrequencyAnalyzer
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from .titfortat import (
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AdaptiveTitForTat,
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Alexei,
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ForgivingTitForTat,
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Fortress3,
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Fortress4,
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FrequencyAnalyzer,
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GTFT,
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GeneralSoftGrudger,
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GoByMajority,

‎axelrod/strategies/frequency_analyzer.py‎

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from axelrod.action import Action, actions_to_str
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from axelrod.player import Player
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from axelrod.strategy_transformers import (
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FinalTransformer,
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TrackHistoryTransformer,
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)
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C, D = Action.C, Action.D
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class FrequencyAnalyzer(Player):
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"""
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A player starts by playing TitForTat for the first 30 turns (dataset generation phase).
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Take the matrix of last 2 moves by both Player and Opponent.
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While in dataset generation phase, construct a dictionary d, where keys are each 4 move sequence
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and the corresponding value for each key is a list of the subsequent Opponent move. The 4 move sequence
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starts with the Opponent move.
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For example, if a game at turn 5 looks like this:
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Opp: C, C, D, C, D
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Player: C, C, C, D, C
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d should look like this:
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{ [CCCC]: [D],
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[CCDC]: [C],
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[DCCD]: [D] }
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During dataset generation phase, Player will play TitForTat. After end of dataset generation phase,
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Player will switch strategies. Upon encountering a particular 4-move sequence in the game, Player will look up history
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of subsequent Opponent move. If ratio of defections to total moves exceeds p, Player will defect. Otherwise,
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Player will cooperate.
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Could fall under "Hunter" class of strategies.
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More likely falls under LookerUp class of strategies.
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Names:
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- FrequencyAnalyzer (FREQ): Original by Ian Miller
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"""
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# These are various properties for the strategy
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name = "FrequencyAnalyzer"
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classifier = {
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"memory_depth": float("inf"),
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"stochastic": False,
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"long_run_time": False,
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"inspects_source": False,
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"manipulates_source": False,
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"manipulates_state": False,
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}
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def __init__(self) -> None:
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"""
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Parameters
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----------
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p, float
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The probability to cooperate
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"""
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super().__init__()
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self.minimum_cooperation_ratio = 0.25
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self.frequency_table = dict()
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self.last_sequence = ""
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self.current_sequence = ""
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def strategy(self, opponent: Player) -> Action:
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"""This is the actual strategy"""
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if len(self.history) > 5:
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self.last_sequence = (
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str(opponent.history[-3])
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+ str(self.history[-3])
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+ str(opponent.history[-2])
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+ str(self.history[-2])
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)
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self.current_sequence = (
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str(opponent.history[-2])
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+ str(self.history[-2])
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+ str(opponent.history[-1])
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+ str(self.history[-1])
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)
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self.update_table(opponent)
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# dataset generation phase
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if (len(self.history) < 30) or (
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self.current_sequence not in self.frequency_table
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):
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if not self.history:
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return C
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if opponent.history[-1] == D:
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return D
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return C
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# post-dataset generation phase
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results = self.frequency_table[self.current_sequence]
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cooperates = results.count(C)
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if (cooperates / len(self.history)) > self.minimum_cooperation_ratio:
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return C
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return D
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def update_table(self, opponent: Player):
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if self.last_sequence in self.frequency_table.keys():
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results = self.frequency_table[self.last_sequence]
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results.append(opponent.history[-1])
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self.frequency_table[self.last_sequence] = results
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else:
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self.frequency_table[self.last_sequence] = [opponent.history[-1]]

‎axelrod/tests/strategies/test_frequency_analyzer.py‎

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"""Tests for the FrequencyAnalyzer strategy."""
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import axelrod as axl
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from .test_player import TestPlayer
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C, D = axl.Action.C, axl.Action.D
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class Test(TestPlayer):
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name = "FrequencyAnalyzer"
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player = axl.FrequencyAnalyzer
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expected_classifier = {
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"memory_depth": float("inf"),
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"stochastic": False,
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"long_run_time": False,
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"makes_use_of": set(),
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"inspects_source": False,
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"manipulates_source": False,
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"manipulates_state": False,
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}
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def test_strategy_early(self):
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# Test games that end while still in dataset generation phase (<30 turns)
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opponent_actions = [C, C, D, C, D]
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expected = [(C, C), (C, C), (C, D), (D, C), (C, D)]
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self.versus_test(
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axl.MockPlayer(opponent_actions), expected_actions=expected, seed=4
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)
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def test_strategy_defector(self):
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# Test against all defections
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opponent_actions = [D] * 30
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expected = [(C, D)] + [(D, D)] * 29
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self.versus_test(
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axl.MockPlayer(opponent_actions), expected_actions=expected, seed=4
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)
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def test_strategy_cooperator(self):
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# Test games that end while still in dataset generation phase (<30 turns)
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opponent_actions = [C] * 30
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expected = [(C, C)] * 30
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self.versus_test(
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axl.MockPlayer(opponent_actions), expected_actions=expected, seed=4
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)
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def test_strategy_random(self):
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# Test of 50 turns against random strategy
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opponent_actions = [
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C,
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D,
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D,
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D,
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D,
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D,
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D,
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C,
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D,
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C,
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D,
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C,
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D,
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C,
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D,
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D,
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C,
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D,
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C,
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D,
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D,
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C,
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D,
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D,
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D,
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D,
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D,
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C,
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C,
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D,
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D,
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C,
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C,
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C,
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D,
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D,
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C,
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D,
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C,
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C,
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C,
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D,
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D,
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C,
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C,
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C,
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D,
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C,
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D,
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D,
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]
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expected = [
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(C, C),
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(C, D),
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(D, D),
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(D, D),
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(D, D),
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(D, D),
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(D, D),
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(D, C),
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(C, D),
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(D, C),
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(C, D),
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(D, C),
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(C, D),
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(D, C),
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(C, D),
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(D, D),
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(D, C),
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(C, D),
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(D, C),
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(C, D),
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(D, D),
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(D, C),
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(C, D),
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(D, D),
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(D, D),
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(D, D),
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(D, D),
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(D, C),
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(C, C),
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(C, D), # rd 30 (end of dataset generation phase)
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(D, D),
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(D, C),
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(
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D,
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C,
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), # example of non TFT (by this point, FrequencyAnalyzer is generally distrustful of opponent)
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(C, C),
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(D, D),
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(D, D),
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(D, C),
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(D, D),
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(D, C),
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(D, C),
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(D, C),
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(D, D),
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(D, D),
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(D, C),
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(D, C),
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(D, C),
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(D, D),
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(D, C),
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(D, D),
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(D, D),
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]
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self.versus_test(
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axl.MockPlayer(opponent_actions), expected_actions=expected, seed=4
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)

‎docs/index.rst‎

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>>> import axelrod as axl
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>>> len(axl.strategies)
56-
240
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241
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Create matches between two players::
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‎docs/reference/strategy_index.rst‎

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:members:
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.. automodule:: axelrod.strategies.forgiver
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:members:
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.. automodule:: axelrod.strategies.frequency_analyzer
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:members:
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.. automodule:: axelrod.strategies.gambler
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:members:
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.. automodule:: axelrod.strategies.gobymajority

‎run_mypy.py‎

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"axelrod/strategies/darwin.py",
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"axelrod/strategies/defector.py",
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"axelrod/strategies/forgiver.py",
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"axelrod/strategies/frequency_analyzer.py",
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"axelrod/strategies/gradualkiller.py",
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"axelrod/strategies/grudger.py",
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"axelrod/strategies/grumpy.py",

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