def _make_transducer(self):
transducer, segments, state = super(
DepConstraint, self)._base_faithfulness_transducer()
for segment in segments:
transducer.add_arc(
Arc(state, segment, segment, CostVector.get_vector(1, 0),
state))
transducer.add_arc(
Arc(state, segment, NULL_SEGMENT, CostVector.get_vector(1, 0),
state))
if segment.has_feature_bundle(self.feature_bundle):
transducer.add_arc(
Arc(state, NULL_SEGMENT, segment,
CostVector.get_vector(1, 1), state))
else:
transducer.add_arc(
Arc(state, NULL_SEGMENT, segment,
CostVector.get_vector(1, 0), state))
if get_configuration("ALLOW_CANDIDATES_WITH_CHANGED_SEGMENTS"):
for first_segment, second_segment in permutations(segments, 2):
transducer.add_arc(
Arc(state, first_segment, second_segment,
CostVector.get_vector(1, 0), state))
return transducer
def _make_transducer(self):
segments = self.feature_table.get_segments()
transducer = Transducer(segments, length_of_cost_vectors=0)
word_segments = self.get_segments()
n = len(self.word_string)
states = [State("q{}".format(i), i) for i in range(n+1)]
for i, state in enumerate(states):
transducer.add_state(state)
transducer.add_arc(Arc(state, NULL_SEGMENT, JOKER_SEGMENT, CostVector.get_empty_vector(), state))
if i != n:
transducer.add_arc(Arc(states[i], word_segments[i], JOKER_SEGMENT, CostVector.get_empty_vector(), states[i+1]))
transducer.initial_state = states[0]
transducer.add_final_state(states[n])
return transducer
def make_optimal_paths(transducer_input):
transducer = pickle.loads(pickle.dumps(transducer_input, -1))
alphabet = transducer.get_alphabet()
new_arcs = list()
for segment in alphabet:
word = Word(segment.get_symbol())
word_transducer = word.get_transducer()
#print(word_transducer.dot_representation())
intersected_machine = Transducer.intersection(word_transducer, transducer)
states = transducer.get_states()
for state1, state2 in itertools.product(states, states):
initial_state = word_transducer.initial_state & state1
final_state = word_transducer.get_a_final_state() & state2
temp_transducer = pickle.loads(pickle.dumps(intersected_machine, -1))
temp_transducer.initial_state = initial_state
temp_transducer.set_final_state(final_state)
temp_transducer.clear_dead_states()
if final_state in temp_transducer.get_final_states(): # otherwise no path.
try:
temp_transducer = remove_suboptimal_paths(temp_transducer)
range = temp_transducer.get_range()
arc = Arc(state1, segment, range, _get_path_cost(temp_transducer), state2)
new_arcs.append(arc)
except KeyError:
pass
#print("****")
#print(temp_transducer.dot_representation())
transducer.set_arcs(new_arcs)
return transducer
def _make_transducer(self):
transducer, segments, state = super(
IdentConstraint, self)._base_faithfulness_transducer()
for segment in segments:
transducer.add_arc(
Arc(state, segment, segment, CostVector.get_vector(1, 0),
state))
transducer.add_arc(
Arc(state, segment, NULL_SEGMENT, CostVector.get_vector(1, 0),
state))
transducer.add_arc(
Arc(state, NULL_SEGMENT, segment, CostVector.get_vector(1, 0),
state))
input_segment = segment
if input_segment.has_feature_bundle(self.feature_bundle):
for output_segment in segments:
if output_segment.has_feature_bundle(self.feature_bundle):
transducer.add_arc(
Arc(state, input_segment, output_segment,
CostVector.get_vector(1, 0), state))
else:
transducer.add_arc(
Arc(state, input_segment, output_segment,
CostVector.get_vector(1, 1), state))
else:
for output_segment in segments:
transducer.add_arc(
Arc(state, input_segment, output_segment,
CostVector.get_vector(1, 0), state))
return transducer
def _make_transducer(self):
def compute_num_of_max_satisfied_bundle(segment):
i = 0
while i < n and symbol_bundle_characteristic_matrix[segment][i]:
i += 1
return i
def compute_highest_num_of_satisfied_bundle(segment, j):
for k in range(j + 1, 0, -1):
if symbol_bundle_characteristic_matrix[segment][k - 1]:
return k
else:
return 0
n = len(self.feature_bundles) - 1
segments = self.feature_table.get_segments()
transducer = Transducer(segments, name=str(self))
symbol_bundle_characteristic_matrix = {
segment: [
segment.has_feature_bundle(self.feature_bundles[i])
for i in range(n + 1)
]
for segment in segments
}
states = {i: {j: 0 for j in range(i)} for i in range(n + 1)}
initial_state = State(
'q0|0'
) # here we use a tuple as label. it will change at the end of this function
states[0][0] = initial_state
transducer.set_as_single_state(initial_state)
if not n:
for segment in segments:
transducer.add_arc(
Arc(
states[0][0], JOKER_SEGMENT, segment,
CostVector([
int(symbol_bundle_characteristic_matrix[segment]
[0])
]), states[0][0]))
transducer.add_arc(
Arc(states[0][0], JOKER_SEGMENT, NULL_SEGMENT, CostVector([0]),
states[0][0]))
else:
for i in range(0, n + 1):
for j in range(i):
state = State('q{0}|{1}'.format(i, j))
states[i][j] = state
transducer.add_state(state)
max_num_of_satisfied_bundle_by_segment = {
segment: compute_num_of_max_satisfied_bundle(segment)
for segment in segments
}
for segment in segments:
transducer.add_arc(
Arc(
states[0][0], JOKER_SEGMENT, segment, CostVector([0]),
states[symbol_bundle_characteristic_matrix[segment]
[0]][0]))
for i in range(n + 1):
for j in range(i):
state = states[i][j]
transducer.add_final_state(state)
if i != n:
for segment in segments:
if symbol_bundle_characteristic_matrix[segment][i]:
new_state_level = i + 1
new_state_mem = min([
j + 1,
max_num_of_satisfied_bundle_by_segment[
segment]
])
else:
new_state_level = compute_highest_num_of_satisfied_bundle(
segment, j)
new_state_mem = min([
max_num_of_satisfied_bundle_by_segment[
segment],
abs(new_state_level - 1)
])
new_terminus = states[new_state_level][
new_state_mem]
transducer.add_arc(
Arc(state, JOKER_SEGMENT, segment,
CostVector([0]), new_terminus))
transducer.add_arc(
Arc(new_terminus, JOKER_SEGMENT, segment,
CostVector([0]), new_terminus))
else: # i = n
for segment in segments:
new_state_level = compute_highest_num_of_satisfied_bundle(
segment, j)
new_state_mem = min([
max_num_of_satisfied_bundle_by_segment[
segment],
abs(new_state_level - 1)
])
new_terminus = states[new_state_level][
new_state_mem]
transducer.add_arc(
Arc(
state, JOKER_SEGMENT, segment,
CostVector([
int(symbol_bundle_characteristic_matrix[
segment][i])
]), new_terminus))
transducer.clear_dead_states()
for state in transducer.states:
transducer.add_arc(
Arc(state, JOKER_SEGMENT, NULL_SEGMENT, CostVector([0]),
state))
return transducer