def testQuickFitnessFairGame(self):
"""Fitness should return equal fitnesses a 'totally fair' game"""
G = ArrayWrapper.array(lambda a,b,c,d: 5.0)
for i in range(10):
r = Dynamics.RandomDistribution(7)
f = Dynamics._QuickFitness(r, G, 4)
for k in range(1,7):
self.failIf(f[k] != f[0])
def testFitnessCorrelation(self):
"""Correlation should make a difference"""
G = ArrayWrapper.array(CorelatedGame)
for k in range(20):
p = Dynamics.RandomDistribution(8)
compare = Dynamics._QuickFitness(p, G, 3)
fitness = Dynamics._Fitness(p, G, 0.2, 3)
self.failIf(AlmostEqual(fitness, compare))
def testFitnessZeroCorrelation(self):
"""Fitness should return the same results as QuickFitness if e=0.0."""
for i in range(5):
G = array(GenRandomGame(4, 7))
for k in range(5):
p = Dynamics.RandomDistribution(7)
compare = Dynamics._QuickFitness(p, G, 4)
fitness = Dynamics._Fitness(p, G, 0.0, 4)
self.failUnless(AlmostEqual(fitness, compare))
def testQuickFitness2Players(self):
"""QuickFitness should not make a difference to QF2 in the 2 player case
"""
for i in range(20):
G = array(GenRandomGame(2, 8))
for k in range(5):
p = Dynamics.RandomDistribution(8)
compare = Dynamics._QuickFitness2(p, G)
fitness = Dynamics._QuickFitness(p, G, 2)
self.failUnless(AlmostEqual(fitness, compare))
def testSampledQuickFitness(self):
"""SampledQuickFitness should yield similar results as QuickFitness"""
for i in range(5):
G = array(GenRandomGame(4, 7))
p = Dynamics.RandomDistribution(7)
fitness = Dynamics._QuickFitness(p, G, 4)
failures = 0
for k in range(5):
sampled = Dynamics._SampledQuickFitness(p, G, 4, 5000)
if not AlmostEqual(fitness, sampled, 0.1): failures += 1
self.failIf(failures > 1)
