def _base_faithfulness_transducer(self):
segments = self.feature_table.get_segments()
transducer = Transducer(segments, name=str(self))
state = State('q0')
transducer.set_as_single_state(state)
return transducer, segments, state
def _base_faithfulness_transducer(self):
segments = self.feature_table.get_segments()
transducer = Transducer(segments, name=str(self))
state = State('q0')
transducer.set_as_single_state(state)
return transducer, segments, state
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))
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
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
