class TransitionTests(Chai):
def setUp(self):
super(TransitionTests, self).setUp()
self.mc = MarkhovChain(random_source=SequentialRandom())
def _make_dice(self):
for i in range(1, 7):
for j in range(1, 7):
self.mc.add_transition(i, j)
self.mc.set_random_state()
def _dice_test(self, trials, expected):
state_counts = Counter()
for _ in range(trials):
state_counts[self.mc.next_state()] += 1
# Test transitions
print()
print("[ State distribution ]\n")
for i in range(1, 7):
print(" {} : {}".format(i, state_counts[i]))
print("\nExpecting {}".format(expected))
for k, c in state_counts.items():
assertEqual(state_counts[k], expected[k])
def test_fair_dice(self):
self._make_dice()
self._dice_test(1200, dict((x, 200) for x in range(1, 7)))
def test_6_weighted_dice(self):
self._make_dice()
for i in range(1, 7):
self.mc.add_transition(i, 6)
expected = dict((x, 200) for x in range(1, 7))
expected[6] = 400
self._dice_test(1400, expected)
def test_6_and_4_weighted_dice(self):
self._make_dice()
for i in range(1, 7):
self.mc.add_transition(i, 6)
self.mc.add_transition(i, 4)
expected = dict((x, 200) for x in range(1, 7))
expected[4] = 400
expected[6] = 400
self._dice_test(1600, expected)
