def init_first_row(self, positive: bool):
for i in range(len(self.sequence)):
covering = None
was = False
# TODO: dictionary can fasten this search
for rule in self.grammar.get_rules():
if rule.right1 == self.sequence[i]:
was = True
self.__init_cell(i, rule)
rule.tmp_used = True
self.rules_table[0][i].append(sCellRule(rule))
if not was and positive:
if len(self.sequence) > 1:
covering = self.terminal_covering
elif self.__settings.get_value(
'covering', 'is_start_covering_allowed') == "True":
covering = self.start_covering
if covering is not None:
new_rule = covering.add_new_rule(self.grammar,
self.sequence[i])
self.__generated_rules_count += 1
new_rule.tmp_used = True
self.__init_cell(i, new_rule)
self.rules_table[0][i].append(sCellRule(new_rule))
self.cells_parsing_states_table[0][i] = True
def __init_first_row(cyk_values: CykValues, is_sentence_positive: bool, settings: Settings):
for i in range(len(cyk_values.sequence)):
covering = None
was = False
# TODO: dictionary can fasten this search
for rule in cyk_values.grammar.get_rules():
if rule.right1 == cyk_values.sequence[i]:
rule: sRule = rule
was = True
__init_cell(cyk_values, i, rule)
rule.tmp_used = True
cyk_values.rules_table[0][i].append(sCellRule(rule))
if not was and is_sentence_positive:
if len(cyk_values.sequence) > 1:
covering = cyk_values.terminal_covering
elif settings.get_value('covering', 'is_start_covering_allowed') == "True":
covering = cyk_values.start_covering
if covering is not None:
new_rule = covering.add_new_rule(cyk_values.grammar, cyk_values.sequence[i])
new_rule.tmp_used = True
__init_cell(cyk_values, i, new_rule)
cyk_values.rules_table[0][i].append(sCellRule(new_rule))
cyk_values.parallelData.cyk_parsed_cells['{}{}'.format(0, i)] = True
cyk_values.parallelData.cyk_rules_for_cell['{}{}'.format(0, i)] = cyk_values.rules_table[0][i]
cyk_values.parallelData.cyk_probability_array['{}{}'.format(0, i)] = cyk_values.probability_array[0][i]
def __compute_rule(j, pr, rt, rules, sentence, pc):
i = 1
while j + i < len(sentence):
rls = list(rules)
for k in range(i):
for rule in rls:
if rule.right2 is not None:
first_rule_index = rule.right1.index
second_rule_index = rule.right2.index
while not pc['{}{}'.format(k, j)] and not pc['{}{}'.format(i - k - 1, j + k + 1)]:
continue
first_parent_prob = pr['{}{}'.format(k, j)][first_rule_index]
second_parent_prob = pr['{}{}'.format(i - k - 1, j + k + 1)][second_rule_index]
if first_parent_prob is not None and second_parent_prob is not None:
rule.tmp_used = True
rule_left_index = rule.left.index
current_cell_probability = pr['{}{}'.format(i, j)]
current_cell_probability[rule_left_index] = Stochastic.new_calculate_cell('BaumWelch', None,
first_parent_prob,
second_parent_prob,
current_cell_probability[rule_left_index],
rule)
pr['{}{}'.format(i, j)] = current_cell_probability
new_rule = sCellRule(rule, Coordinates(k, j), Coordinates(i - k - 1, j + k + 1))
ru_table = rt['{}{}'.format(i, j)]
ru_table.append(new_rule)
rt['{}{}'.format(i, j)] = ru_table
pc['{}{}'.format(i, j)] = True
i = i + 1
def __handle_rule(i, j, cyk_probability_array, cyk_rules_for_cell, rules_list,
values):
rules = list(rules_list)
for rule in rules:
for k in range(i):
fp = cyk_probability_array['{}{}'.format(k, j)]
sp = cyk_probability_array['{}{}'.format(i - k - 1, j + k + 1)]
cp = cyk_probability_array['{}{}'.format(i, j)]
if rule.right2 is not None:
first_rule_index = rule.right1.index
second_rule_index = rule.right2.index
if fp[first_rule_index] is not None and sp[
second_rule_index] is not None:
rule.tmp_used = True
rule_left_index = rule.left.index
cp[rule_left_index] = __calculate_cell(
fp[first_rule_index], sp[second_rule_index],
cp[rule.left.index], rule)
cyk_probability_array['{}{}'.format(i, j)] = cp
new_rule = sCellRule(rule, Coordinates(k, j),
Coordinates(i - k - 1, j + k + 1))
rt = cyk_rules_for_cell['{}{}'.format(i, j)]
rt.append(new_rule)
cyk_rules_for_cell['{}{}'.format(i, j)] = rt
def __apply_aggressive_and_final_covering(cyk_values: CykValues, i: int,
j: int):
"""
Performs aggressive or final covering on the given cell of the cyk table
:param i:
:param j:
:return:
"""
new_rule = None
valid_combinations_of_indexes = []
for m in range(i):
tmp_symbols_1 = __get_cell_symbols(cyk_values, m, j)
tmp_symbols_2 = __get_cell_symbols(cyk_values, i - m - 1, j + m + 1)
if len(tmp_symbols_1) > 0 and len(tmp_symbols_2) > 0:
valid_combinations_of_indexes.append(m)
if len(valid_combinations_of_indexes) > 0:
random = randint(0, len(valid_combinations_of_indexes) - 1)
symbols_1 = __get_cell_symbols(cyk_values,
valid_combinations_of_indexes[random],
j)
symbols_2 = __get_cell_symbols(
cyk_values, i - valid_combinations_of_indexes[random] - 1,
j + valid_combinations_of_indexes[random] + 1)
index_1 = randint(0, len(symbols_1) - 1)
index_2 = randint(0, len(symbols_2) - 1)
if i is not len(cyk_values.sequence) - 1:
if RandomUtils.make_random_decision_with_probability(
float(
cyk_values.settings.get_value(
'covering', 'aggressive_covering_probability'))):
covering = cyk_values.aggressive_covering
new_rule = covering.add_new_rule(cyk_values.grammar,
symbols_1[index_1],
symbols_2[index_2])
elif cyk_values.settings.get_value(
'covering', 'is_full_covering_allowed') == "True":
covering = cyk_values.final_covering
new_rule = covering.add_new_rule(cyk_values.grammar,
symbols_1[index_1],
symbols_2[index_2])
if new_rule is not None:
new_rule.tmp_used = True
new_cell_rule = sCellRule(
new_rule, Coordinates(valid_combinations_of_indexes[random],
j),
Coordinates(i - valid_combinations_of_indexes[random] - 1,
j + valid_combinations_of_indexes[random] + 1))
cyk_values.rules_table[i][j].append(new_cell_rule)
__calculate_cell(
cyk_values, cyk_values.probability_array[
valid_combinations_of_indexes[random]][j][
new_rule.right1.index], cyk_values.probability_array[
i - valid_combinations_of_indexes[random] -
1][j + valid_combinations_of_indexes[random] +
1][new_rule.right2.index],
cyk_values.probability_array[i][j][new_rule.left.index],
new_rule)
def __apply_aggressive_and_final_covering(self, i: int, j: int):
"""
Performs aggressive or final covering on the given cell of the cyk table
:param i:
:param j:
:return:
"""
new_rule = None
valid_combinations_of_indexes = []
for m in self.iteration_generator(i):
tmp_symbols_1 = self.__get_cell_symbols(m, j)
tmp_symbols_2 = self.__get_cell_symbols(i - m - 1, j + m + 1)
if len(tmp_symbols_1) > 0 and len(tmp_symbols_2) > 0:
valid_combinations_of_indexes.append(m)
if len(valid_combinations_of_indexes) > 0:
random = randint(0, len(valid_combinations_of_indexes) - 1)
symbols_1 = self.__get_cell_symbols(
valid_combinations_of_indexes[random], j)
symbols_2 = self.__get_cell_symbols(
i - valid_combinations_of_indexes[random] - 1,
j + valid_combinations_of_indexes[random] + 1)
index_1 = randint(0, len(symbols_1) - 1)
index_2 = randint(0, len(symbols_2) - 1)
# print("Need rule: {}". format(symbols_1[index_1], symbols_2[index_2]))
if i is not len(self.sequence) - 1:
if RandomUtils.make_random_decision_with_probability(
float(
self.__settings.get_value(
'covering',
'aggressive_covering_probability'))):
covering = self.aggressive_covering
new_rule = covering.add_new_rule(self.grammar,
symbols_1[index_1],
symbols_2[index_2])
elif self.__settings.get_value(
'covering', 'is_full_covering_allowed') == "True":
covering = self.final_covering
new_rule = covering.add_new_rule(self.grammar,
symbols_1[index_1],
symbols_2[index_2])
if new_rule is not None:
self.__generated_rules_count += 1
new_rule.tmp_used = True
new_cell_rule = sCellRule(
new_rule,
Coordinates(valid_combinations_of_indexes[random], j),
Coordinates(i - valid_combinations_of_indexes[random] - 1,
j + valid_combinations_of_indexes[random] + 1))
self.rules_table[i][j].append(new_cell_rule)
self.__Stochastic.calculate_cell(
self.mode, self.default_value, self.probability_array,
Coordinates(valid_combinations_of_indexes[random], j),
Coordinates(i - valid_combinations_of_indexes[random] - 1,
j + valid_combinations_of_indexes[random] + 1),
Coordinates(i, j), new_rule)
def __compute_rule(jobs_queue, pc, pr, rt, rules):
while True:
try:
cell_rule_indexes = jobs_queue.get(block=False)
except:
return None
if cell_rule_indexes is None:
return None
i = cell_rule_indexes.i
j = cell_rule_indexes.j
rls = list(rules)
for k in range(i):
for rule in rls:
if rule.right2 is not None:
first_rule_index = rule.right1.index
second_rule_index = rule.right2.index
while not pc['{}{}'.format(k, j)] and not pc['{}{}'.format(
i - k - 1, j + k + 1)]:
continue
first_parent_prob = pr['{}{}'.format(k,
j)][first_rule_index]
second_parent_prob = pr['{}{}'.format(
i - k - 1, j + k + 1)][second_rule_index]
if first_parent_prob is not None and second_parent_prob is not None:
rule.tmp_used = True
rule_left_index = rule.left.index
current_cell_probability = pr['{}{}'.format(i, j)]
current_cell_probability[
rule_left_index] = Stochastic.new_calculate_cell(
'BaumWelch', None, first_parent_prob,
second_parent_prob,
current_cell_probability[rule_left_index],
rule)
pr['{}{}'.format(i, j)] = current_cell_probability
new_rule = sCellRule(rule, Coordinates(k, j),
Coordinates(i - k - 1, j + k + 1))
ru_table = rt['{}{}'.format(i, j)]
ru_table.append(new_rule)
rt['{}{}'.format(i, j)] = ru_table
pc['{}{}'.format(i, j)] = True
def parse_sentence(self, sequence: str, positive: bool, covering_on,
negative_covering):
self.__logger.info(
'Parsing sentence {0}. Belongs to grammar: {1}'.format(
sequence, positive))
sequence_length = len(sequence)
self._init_probability_array(sequence_length,
len(self.grammar.nonTerminalSymbols))
self._init_rules_table(sequence_length)
self.init_first_row(positive)
s_time = time.time()
# Iterate through upper triangle of the cyk matrix
for i in self.iteration_generator(sequence_length):
for j in self.iteration_generator(sequence_length - i):
for k in self.iteration_generator(i):
for rule in self.grammar.get_rules():
if rule.right2 is not None:
first_rule_index = rule.right1.index
second_rule_index = rule.right2.index
if self.probability_array[k][j][first_rule_index] is not None \
and self.probability_array[i - k - 1][j + k + 1][second_rule_index] is not None:
rule.tmp_used = True
rule_left_index = rule.left.index
parent_cell_probability = self.probability_array[
k][j][first_rule_index]
parent_cell_2_probability = \
self.probability_array[i - k - 1][j + k + 1][second_rule_index]
current_cell_probability = self.probability_array[
i][j][rule_left_index]
self.probability_array[i][j][rule_left_index] = \
self.__Stochastic.new_calculate_cell(self.mode, self.default_value, parent_cell_probability, parent_cell_2_probability,
current_cell_probability, rule)
new_rule = sCellRule(
rule, Coordinates(k, j),
Coordinates(i - k - 1, j + k + 1))
self.rules_table[i][j].append(new_rule)
# Check if probability for cell found
is_rule_occured = self.__find_if_non_terminal_or_start_rule_occured_in_cell(
i, j)
# Aggresive and final covering
if not is_rule_occured and positive and covering_on and \
self.settings.get_value('covering', 'is_full_covering_allowed') == "True":
self.__apply_aggressive_and_final_covering(i, j)
def start_execution(self):
while True:
job: CykIndexes = self.jobs_storage_proxy.get_cell_job().get()
if job is None:
return self.rules_prob_proxy.get_rule_to_add(), self.rules_prob_proxy.get_rules_table(), self.rules_prob_proxy.get_probability_array()
i = job.i
j = job.j
was = False
for k in range(i):
cell_up_state = self.parsing_state_proxy.get_cell_state(k, j).get()
cell_cross_state = self.parsing_state_proxy.get_cell_state(i - k - 1, j + k + 1).get()
while cell_up_state is False and cell_cross_state is False:
cell_up_state = self.parsing_state_proxy.get_cell_state(k, j).get()
cell_cross_state = self.parsing_state_proxy.get_cell_state(i - k - 1, j + k + 1).get()
rules = self.rules_storage_proxy.get_rules().get()
probability_array = self.rules_prob_proxy.get_probability_array().get()
for rule in rules:
if rule.right2 is not None:
first_rule_index = rule.right1.index
second_rule_index = rule.right2.index
if probability_array[k][j][first_rule_index] is not None \
and probability_array[i - k - 1][j + k + 1][second_rule_index] is not None:
rule.tmp_used = True
rule_left_index = rule.left.index
was = True
parent_cell_probability = probability_array[k][j][first_rule_index]
parent_cell_2_probability = \
probability_array[i - k - 1][j + k + 1][second_rule_index]
current_cell_probability = probability_array[i][j][rule_left_index]
current_cell_probability = Stochastic.new_calculate_cell('BaumWelch', None, parent_cell_probability,
parent_cell_2_probability,
current_cell_probability,
rule)
new_rule = sCellRule(rule, Coordinates(k, j), Coordinates(i - k - 1, j + k + 1))
self.rules_prob_proxy.update_rules_table(i, j, new_rule)
self.rules_prob_proxy.update_probability_array(i, j, rule_left_index, current_cell_probability)
if not was:
self.rules_prob_proxy.add_rule_to_add([i, j])
self.parsing_state_proxy.update_cell_state(i, j)
def new_first_row_init(cyk_values: CykValues):
for i in iteration_generator(len(cyk_values.sequence)):
grammar_rules = list(cyk_values.grammar.get_rules())
rules = [
init_cell(cyk_values, i, rule)
for rule in rules_generator(grammar_rules)
if rule.right1 == cyk_values.sequence[i]
]
if len(rules) > 0:
cyk_values.rules_table[0][i].cell_rules.extend(rules)
elif cyk_values.positive:
covering = choose_first_row_covering(cyk_values)
if covering is not None:
new_rule = covering.add_new_rule(cyk_values.grammar,
cyk_values.sequence[i])
init_cell(cyk_values, i, new_rule)
cyk_values.rules_table[0][i].cell_rules.append(
sCellRule(new_rule))
cyk_values.rules_table[0][i].parsed = True
cyk_values.parallelData.cyk_parsed_cells['{}{}'.format(0, i)] = 1
cyk_values.parallelData.cyk_probability_array['{}{}'.format(
0, i)] = cyk_values.probability_array[0][i]
