class TestDecisionMaker(unittest.TestCase):
"""Test for decision maker class """
def setUp(self):
"""Set up decision maker object for testing """
self.decision_maker = DecisionMaker(
1,
3,
state='',
alphabet=list(string.ascii_uppercase) + ['<'] + [SPACE_CHAR],
is_txt_stim=True,
stimuli_timing=[1, .2],
seq_constants=None)
self.evidence_fusion = EvidenceFusion(list_name_evidence=['A', 'B'],
len_dist=2)
def tearDown(self):
"""Reset decision maker and evidence fusion at the
end of each test. """
self.decision_maker.reset()
self.evidence_fusion.reset_history()
def test_evidence_fusion_init(self):
self.assertEqual(self.evidence_fusion.evidence_history, {
'A': [],
'B': []
})
self.assertEqual(self.evidence_fusion.likelihood[0], [0.5])
self.assertEqual(self.evidence_fusion.likelihood[1], [0.5])
def test_reset_history(self):
self.evidence_fusion.reset_history()
self.assertEqual(self.evidence_fusion.evidence_history, {
'A': [],
'B': []
})
self.assertEqual(self.evidence_fusion.likelihood[0], [0.5])
self.assertEqual(self.evidence_fusion.likelihood[1], [0.5])
def test_update_and_fuse_with_float_evidence(self):
dict_evidence = {'A': [0.5], 'B': [0.5]}
self.evidence_fusion.update_and_fuse(dict_evidence)
self.assertEqual(self.evidence_fusion.evidence_history['A'][0],
dict_evidence['A'])
self.assertEqual(self.evidence_fusion.evidence_history['B'][0],
dict_evidence['B'])
self.assertEqual(self.evidence_fusion.likelihood[0], [[0.5]])
self.assertEqual(self.evidence_fusion.likelihood[1], [[0.5]])
def test_update_and_fuse_with_inf_evidence(self):
dict_evidence = {'A': [0.5], 'B': [math.inf]}
self.evidence_fusion.update_and_fuse(dict_evidence)
self.assertEqual(self.evidence_fusion.evidence_history['A'][0],
dict_evidence['A'])
self.assertEqual(self.evidence_fusion.evidence_history['B'][0],
dict_evidence['B'])
self.assertEqual(self.evidence_fusion.likelihood[0], [1.0])
self.assertEqual(self.evidence_fusion.likelihood[1], [0.0])
def test_save_history(self):
history = self.evidence_fusion.save_history()
self.assertEqual(0, history)
def test_decision_maker_init(self):
"""Test initialization"""
self.assertEqual(self.decision_maker.min_num_seq, 1)
self.assertEqual(self.decision_maker.max_num_seq, 3)
self.assertEqual(self.decision_maker.state, '')
self.assertEqual(self.decision_maker.displayed_state, '')
def test_decide_without_commit(self):
"""
Test decide method with case of no commit
using a fake probability distribution
"""
probability_distribution = np.ones(len(
self.decision_maker.alphabet)) / 8
decision, chosen_stimuli = self.decision_maker.decide(
probability_distribution)
self.assertTrue(
np.all(self.decision_maker.list_epoch[-1]['list_distribution'][-1]
== probability_distribution))
self.assertFalse(decision)
self.decision_maker.do_epoch()
self.assertEqual(self.decision_maker.sequence_counter, 0)
def test_decide_with_commit(self):
"""Test decide method with case of commit"""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
self.decision_maker.sequence_counter = self.decision_maker.min_num_seq
decision, chosen_stimuli = self.decision_maker.decide(
probability_distribution)
self.assertTrue(decision)
self.assertEqual(chosen_stimuli, None)
def test_update_with_letter(self):
"""Test update method with letter being the new state"""
old_displayed_state = self.decision_maker.displayed_state
old_state = self.decision_maker.state
new_state = 'E'
self.decision_maker.update(state=new_state)
self.assertEqual(self.decision_maker.state, old_state + new_state)
self.assertEqual(self.decision_maker.displayed_state,
old_displayed_state + 'E')
def test_update_with_backspace(self):
"""Test update method with backspace being the new state"""
old_displayed_state = self.decision_maker.displayed_state
old_state = self.decision_maker.state
new_state = '<'
self.decision_maker.update(state=new_state)
self.assertEqual(self.decision_maker.state, old_state + new_state)
self.assertEqual(self.decision_maker.displayed_state,
old_displayed_state[0:-1])
self.assertLess(len(self.decision_maker.displayed_state),
len(self.decision_maker.state))
def test_reset(self):
"""Test reset of decision maker state"""
self.decision_maker.reset()
self.assertEqual(self.decision_maker.state, '')
self.assertEqual(self.decision_maker.displayed_state, '')
self.assertEqual(self.decision_maker.time, 0)
self.assertEqual(self.decision_maker.sequence_counter, 0)
def test_form_display_state(self):
"""Test form display state method with a dummy state"""
self.decision_maker.update(state='ABC<.E')
self.decision_maker.form_display_state(self.decision_maker.state)
self.assertEqual(self.decision_maker.displayed_state, 'ABE')
self.decision_maker.reset()
def test_do_epoch(self):
"""Test do_epoch method"""
probability_distribution = np.ones(len(
self.decision_maker.alphabet)) / 8
decision, chosen_stimuli = self.decision_maker.decide(
probability_distribution)
self.decision_maker.do_epoch()
self.assertEqual(self.decision_maker.sequence_counter, 0)
def test_decide_state_update(self):
"""Tests decide state update method"""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
self.decision_maker.list_epoch[-1]['list_distribution'].append(
probability_distribution)
decision = self.decision_maker.decide_state_update()
expected = 'A' # expect to commit to first letter in sequence, due to uniform probability
self.assertEqual(decision, 'A')
def test_schedule_sequence(self):
"""Test sequence scheduling. Should return new stimuli list, at random."""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
old_counter = self.decision_maker.sequence_counter
self.decision_maker.list_epoch[-1]['list_distribution'].append(
probability_distribution)
stimuli = self.decision_maker.schedule_sequence()
self.assertEqual(self.decision_maker.state, '.')
self.assertEqual(stimuli[0],
self.decision_maker.list_epoch[-1]['list_sti'][-1])
self.assertLess(old_counter, self.decision_maker.sequence_counter)
def test_prepare_stimuli(self):
"""Test that stimuli are prepared as expected"""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
self.decision_maker.list_epoch[-1]['list_distribution'].append(
probability_distribution)
stimuli = self.decision_maker.prepare_stimuli()
self.assertEqual(11, len(stimuli[0][0]))
for i in range(1, len(stimuli[0][0])):
self.assertIn(stimuli[0][0][i], self.decision_maker.alphabet)
self.assertEqual(stimuli[1][0][0:2],
self.decision_maker.stimuli_timing)
class TestDecisionMaker(unittest.TestCase):
"""Test for decision maker class """
def setUp(self):
"""Set up decision maker object for testing """
alphabet = list(string.ascii_uppercase) + ['<'] + [SPACE_CHAR]
stopping_criteria = CriteriaEvaluator(
continue_criteria=[MinIterationsCriteria(min_num_inq=1)],
commit_criteria=[
MaxIterationsCriteria(max_num_inq=10),
ProbThresholdCriteria(threshold=0.8)
])
stimuli_agent = NBestStimuliAgent(alphabet=alphabet, len_query=10)
self.decision_maker = DecisionMaker(
stimuli_agent=stimuli_agent,
stopping_evaluator=stopping_criteria,
state='',
alphabet=alphabet,
is_txt_stim=True,
stimuli_timing=[1, .2],
inq_constants=None)
self.evidence_fusion = EvidenceFusion(list_name_evidence=['A', 'B'],
len_dist=2)
def tearDown(self):
"""Reset decision maker and evidence fusion at the
end of each test. """
self.decision_maker.reset()
self.evidence_fusion.reset_history()
def test_evidence_fusion_init(self):
self.assertEqual(self.evidence_fusion.evidence_history, {
'A': [],
'B': []
})
self.assertEqual(self.evidence_fusion.likelihood[0], [0.5])
self.assertEqual(self.evidence_fusion.likelihood[1], [0.5])
def test_reset_history(self):
self.evidence_fusion.reset_history()
self.assertEqual(self.evidence_fusion.evidence_history, {
'A': [],
'B': []
})
self.assertEqual(self.evidence_fusion.likelihood[0], [0.5])
self.assertEqual(self.evidence_fusion.likelihood[1], [0.5])
def test_update_and_fuse_with_float_evidence(self):
dict_evidence = {'A': [0.5], 'B': [0.5]}
self.evidence_fusion.update_and_fuse(dict_evidence)
self.assertEqual(self.evidence_fusion.evidence_history['A'][0],
dict_evidence['A'])
self.assertEqual(self.evidence_fusion.evidence_history['B'][0],
dict_evidence['B'])
self.assertEqual(self.evidence_fusion.likelihood[0], [[0.5]])
self.assertEqual(self.evidence_fusion.likelihood[1], [[0.5]])
def test_update_and_fuse_with_inf_evidence(self):
dict_evidence = {'A': [0.5], 'B': [math.inf]}
self.evidence_fusion.update_and_fuse(dict_evidence)
self.assertEqual(self.evidence_fusion.evidence_history['A'][0],
dict_evidence['A'])
self.assertEqual(self.evidence_fusion.evidence_history['B'][0],
dict_evidence['B'])
self.assertEqual(self.evidence_fusion.likelihood[0], [1.0])
self.assertEqual(self.evidence_fusion.likelihood[1], [0.0])
def test_save_history(self):
history = self.evidence_fusion.save_history()
self.assertEqual(0, history)
def test_decision_maker_init(self):
"""Test initialization"""
# TODO: Update that test part
# self.assertEqual(self.decision_maker.min_num_inq, 1)
# self.assertEqual(self.decision_maker.max_num_inq, 3)
self.assertEqual(self.decision_maker.state, '')
self.assertEqual(self.decision_maker.displayed_state, '')
def test_update_with_letter(self):
"""Test update method with letter being the new state"""
old_displayed_state = self.decision_maker.displayed_state
old_state = self.decision_maker.state
new_state = 'E'
self.decision_maker.update(state=new_state)
self.assertEqual(self.decision_maker.state, old_state + new_state)
self.assertEqual(self.decision_maker.displayed_state,
old_displayed_state + 'E')
def test_update_with_backspace(self):
"""Test update method with backspace being the new state"""
old_displayed_state = self.decision_maker.displayed_state
old_state = self.decision_maker.state
new_state = '<'
self.decision_maker.update(state=new_state)
self.assertEqual(self.decision_maker.state, old_state + new_state)
self.assertEqual(self.decision_maker.displayed_state,
old_displayed_state[0:-1])
self.assertLess(len(self.decision_maker.displayed_state),
len(self.decision_maker.state))
def test_reset(self):
"""Test reset of decision maker state"""
self.decision_maker.reset()
self.assertEqual(self.decision_maker.state, '')
self.assertEqual(self.decision_maker.displayed_state, '')
self.assertEqual(self.decision_maker.time, 0)
self.assertEqual(self.decision_maker.inquiry_counter, 0)
def test_form_display_state(self):
"""Test form display state method with a dummy state"""
self.decision_maker.update(state='ABC<.E')
self.decision_maker.form_display_state(self.decision_maker.state)
self.assertEqual(self.decision_maker.displayed_state, 'ABE')
self.decision_maker.reset()
def test_do_series(self):
"""Test do_series method"""
probability_distribution = np.ones(len(
self.decision_maker.alphabet)) / 8
decision, chosen_stimuli = self.decision_maker.decide(
probability_distribution)
self.decision_maker.do_series()
self.assertEqual(self.decision_maker.inquiry_counter, 0)
def test_decide_state_update(self):
"""Tests decide state update method"""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
self.decision_maker.list_series[-1]['list_distribution'].append(
probability_distribution)
decision = self.decision_maker.decide_state_update()
expected = 'A' # expect to commit to first letter in inquiry, due to uniform probability
self.assertEqual(decision, 'A')
def test_schedule_inquiry(self):
"""Test inquiry scheduling. Should return new stimuli list, at random."""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
old_counter = self.decision_maker.inquiry_counter
self.decision_maker.list_series[-1]['list_distribution'].append(
probability_distribution)
stimuli = self.decision_maker.schedule_inquiry()
self.assertEqual(self.decision_maker.state, '.')
self.assertEqual(stimuli[0],
self.decision_maker.list_series[-1]['list_sti'][-1])
self.assertLess(old_counter, self.decision_maker.inquiry_counter)
def test_prepare_stimuli(self):
"""Test that stimuli are prepared as expected"""
probability_distribution = np.ones(len(self.decision_maker.alphabet))
self.decision_maker.list_series[-1]['list_distribution'].append(
probability_distribution)
stimuli = self.decision_maker.prepare_stimuli()
self.assertEqual(self.decision_maker.stimuli_agent.len_query + 1,
len(stimuli[0][0]))
for i in range(1, len(stimuli[0][0])):
self.assertIn(stimuli[0][0][i], self.decision_maker.alphabet)
self.assertEqual(stimuli[1][0][0:2],
self.decision_maker.stimuli_timing)