def test_hillclimb(self):
# arrange
initial_alignment = AlignmentInfo((0, 3, 2), None, None, None)
def neighboring_mock(a, j):
if a.alignment == (0, 3, 2):
return set([
AlignmentInfo((0, 2, 2), None, None, None),
AlignmentInfo((0, 1, 1), None, None, None)
])
elif a.alignment == (0, 2, 2):
return set([
AlignmentInfo((0, 3, 3), None, None, None),
AlignmentInfo((0, 4, 4), None, None, None)
])
return set()
def prob_t_a_given_s_mock(a):
prob_values = {
(0, 3, 2): 0.5,
(0, 2, 2): 0.6,
(0, 1, 1): 0.4,
(0, 3, 3): 0.6,
(0, 4, 4): 0.7
}
return prob_values.get(a.alignment, 0.01)
ibm_model = IBMModel([])
ibm_model.neighboring = neighboring_mock
ibm_model.prob_t_a_given_s = prob_t_a_given_s_mock
# act
best_alignment = ibm_model.hillclimb(initial_alignment)
# assert: hill climbing goes from (0, 3, 2) -> (0, 2, 2) -> (0, 4, 4)
self.assertEqual(best_alignment.alignment, (0, 4, 4))
def test_hillclimb(self):
# arrange
initial_alignment = AlignmentInfo((0, 3, 2), None, None, None)
def neighboring_mock(a, j):
if a.alignment == (0, 3, 2):
return set([
AlignmentInfo((0, 2, 2), None, None, None),
AlignmentInfo((0, 1, 1), None, None, None)
])
elif a.alignment == (0, 2, 2):
return set([
AlignmentInfo((0, 3, 3), None, None, None),
AlignmentInfo((0, 4, 4), None, None, None)
])
return set()
def prob_t_a_given_s_mock(a):
prob_values = {
(0, 3, 2): 0.5,
(0, 2, 2): 0.6,
(0, 1, 1): 0.4,
(0, 3, 3): 0.6,
(0, 4, 4): 0.7
}
return prob_values.get(a.alignment, 0.01)
ibm_model = IBMModel([])
ibm_model.neighboring = neighboring_mock
ibm_model.prob_t_a_given_s = prob_t_a_given_s_mock
# act
best_alignment = ibm_model.hillclimb(initial_alignment)
# assert: hill climbing goes from (0, 3, 2) -> (0, 2, 2) -> (0, 4, 4)
self.assertEqual(best_alignment.alignment, (0, 4, 4))
