def test_reset_cleans_all(self):
p = axelrod.Gradual()
p.calming = True
p.punishing = True
p.punishment_count = 1
p.punishment_limit = 1
p.reset()
self.assertFalse(p.calming)
self.assertFalse(p.punishing)
self.assertEqual(p.punishment_count, 0)
self.assertEqual(p.punishment_limit, 0)
def test_output_from_literature(self):
"""
This strategy is not fully described in the literature, however the
following two results are reported in:
Bruno Beaufils, Jean-Paul Delahaye, Philippe Mathie
"Our Meeting With Gradual: A Good Strategy For The Iterated Prisoner's
Dilemma" Proc. Artif. Life 1996
This test just ensures that the strategy is as was originally defined.
"""
player = axelrod.Gradual()
opp1 = axelrod.Defector()
match = axelrod.Match((player, opp1), 1000)
match.play()
self.assertEqual(match.final_score(), (915, 1340))
opp2 = axelrod.CyclerCCD()
match = axelrod.Match((player, opp2), 1000)
match.play()
self.assertEqual(match.final_score(), (3472, 767))
