def test_viterbi_phrase2(self, part_2_a, multidimensional_viterbi):
"""
Extracted from BOSTON ASL dataset: video 47, frame 12-30
Actual words: BUY CAR
"""
right_y = [42, 40, 41, 43, 52, 55, 59, 60, 55, 47, 39, 32,
34, 36, 42, 42, 42, 34, 25]
left_y = [138, 133, 123, 115, 104, 91, 76, 70, 67, 67, 62,
56, 48, 43, 43, 44, 46, 52, 65]
evidence = list(zip(right_y, left_y))
prob_ans = 8.3138718215932126e-71
states, prior, trans, emiss = self.setup(part_2_a)
seq_ans = ['B1', 'B1', 'B1', 'B1', 'B1', 'B1', 'B2',
'B3','B3', 'B3', 'C1', 'C1', 'C1', 'C1',
'C1', 'C1', 'C1', 'C1', 'C1']
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=71)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_phrase2")
def test_viterbi_phrase1(self, part_2_a, multidimensional_viterbi):
"""
Extracted from BOSTON ASL dataset: video 45, frame 36-56
Actual words: BUY HOUSE
"""
right_y = [48, 53, 54, 53, 48, 48, 48, 53, 48, 48, 46, 46,
53, 58, 66, 72, 71, 76, 76, 76, 76]
left_y = [85, 74, 70, 66, 64, 64, 64, 60, 60, 60, 50, 50,
57, 67, 74, 85, 84, 89, 93, 93, 94]
evidence = list(zip(right_y, left_y))
prob_ans = 3.838599461219723e-75
states, prior, trans, emiss = self.setup(part_2_a)
seq_ans = ['B1', 'B2', 'B3', 'B3', 'B3', 'B3', 'B3',
'B3', 'H1', 'H1','H1', 'H1', 'H2', 'H3',
'H3', 'H3', 'H3', 'H3', 'H3', 'H3', 'H3']
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=77)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_phrase1")
def test_viterbi_case3(self, part_2_a, multidimensional_viterbi):
evidence = [(40, 40)]
prob_ans = 0.000213189518752
seq_ans = ['C1']
states, prior, trans, emiss = self.setup(part_2_a)
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=15)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_case3")
def test_viterbi_case1(self, part_2_a, multidimensional_viterbi):
evidence = []
states, prior, trans, emiss = self.setup(part_2_a)
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
msg = ('when evidence is an empty list, return "None" or [], '
'get {}').format(seq)
self.assertTrue(seq in [None, []], msg)
msg = ('when evidence is an empty list, return prob=0.0, '
'get {}').format(prob)
self.assertTrue(prob == 0., msg)
print_success_message("test_viterbi_case1")
def test_viterbi_case2(self, part_2_a, multidimensional_viterbi):
evidence = [(50, 100)]
prob_ans = 1.18078362571e-05
seq_ans = ['B1']
states, prior, trans, emiss = self.setup(part_2_a)
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=9)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_case2")
def test_viterbi_realsample3(self, part_2_a, multidimensional_viterbi):
"""
Extracted from BOSTON ASL dataset: video 47, frame 21-30
Actual words: CAR
"""
right_y = [47, 39, 32, 34, 36, 42, 42, 42, 34, 25]
left_y = [67, 62, 56, 48, 43, 43, 44, 46, 52, 65]
evidence = list(zip(right_y, left_y))
prob_ans = 1.17739941205e-34
seq_ans = ['C1', 'C1', 'C1', 'C1', 'C1', 'C1', 'C1', 'C1', 'C1', 'C1']
states, prior, trans, emiss = self.setup(part_2_a)
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=38)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_realsample3")
def test_viterbi_realsample2(self, part_2_a, multidimensional_viterbi):
"""
Extracted from BOSTON ASL dataset: video 48, frame 27-35
Actual words: CAR
"""
right_y = [45, 45, 46, 48, 51, 51, 49, 45, 42]
left_y = [47, 45, 43, 45, 48, 48, 54, 61, 67]
evidence = list(zip(right_y, left_y))
prob_ans = 5.80105906918e-28
seq_ans = ['H1', 'H1', 'H1', 'H1', 'H1', 'H1', 'H1', 'H1', 'H1']
states, prior, trans, emiss = self.setup(part_2_a)
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=32)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_realsample2")
def test_viterbi_realsample1(self, part_2_a, multidimensional_viterbi):
"""
Extracted from BOSTON ASL dataset: video 51, frame 17-23
Actual words: BUY
"""
right_y = [44, 51, 57, 63, 61, 60, 59]
left_y = [101, 95, 84, 77, 73, 68, 66]
evidence = list(zip(right_y, left_y))
prob_ans = 4.1704852628957851e-27
seq_ans = ['B1', 'B1', 'B2', 'B2', 'B3', 'B3', 'B3']
states, prior, trans, emiss = self.setup(part_2_a)
seq, prob = multidimensional_viterbi(evidence,
states,
prior,
trans,
emiss)
self.assertAlmostEqual(prob_ans, prob, places=32)
self.assertEqual(seq_ans, seq)
print_success_message("test_viterbi_realsample1")