def test_read_instance(self):
test_file_path = './sat_test_data/test.cnf'
cnf = SatUtils.read_instance(test_file_path)
self.assertEqual(len(cnf), 2)
self.assertEqual(len(cnf[0]), 6)
self.assertEqual(len(cnf[1]), 4)
def main(self,
max_restarts=10,
max_iterations=1000,
instance_path="./sat_data/test.cnf"):
instance = SatUtils.read_instance(instance_path)
var_count = len(instance[0])
start = time.time()
end = None
for restart in range(max_restarts):
best_solution = SatUtils.initialize_variables(var_count)
for iteration in range(max_iterations):
solution_status, no_of_unsat_clauses = SatUtils.solution_status(
instance, best_solution)
# if solution has been found terminate the search
if solution_status is True:
end = time.time()
print("Iteration,{0},Restart,{1},Duration,{2}".format(
iteration, restart, end - start))
return
best_solution = self.get_best_var_to_flip(
instance, best_solution, no_of_unsat_clauses)
# resetting tabu list in between the restarts
GsatSolver.tabu = []
def main(self, wp, p, max_iterations, instance_path):
cnf_contents = SatUtils.read_instance(instance_path)
# instantiate required search and util objects
novelty_search = NoveltySearch(cnf_contents, p, 1)
variables = cnf_contents[0]
walkSat = WalkSat()
# initialize first solution proposal
proposed_solution = SatUtils.initialize_variables(len(variables))
# start the timer
start = time.time()
end = None
for i in range(max_iterations):
# checking for timeout terminate condition
if time.time() > start + 60:
return
solution_found, unsat_clause, unsat_clause_list = SatUtils.solution_status_with_unsat_clauses(
cnf_contents, proposed_solution)
# if a solution has been identified break out of the search loop and record it
if solution_found is True:
end = time.time()
print("Iteration,{0},Duration,{1}".format(i, end - start))
return
# pick algorithm to run the solution search based on probability
if wp < random.uniform(0, 1):
proposed_solution = walkSat.execute_walk(
cnf_contents, proposed_solution)
else:
random_variable_to_flip = random.choice(variables)
random_unsat_clause = random.choice(unsat_clause_list)
best_flip = novelty_search.execute_search(
proposed_solution, random_variable_to_flip,
random_unsat_clause)
proposed_solution[best_flip] = SatUtils.flip_var(
proposed_solution[best_flip])
flip_scores,
key=flip_scores.get)
best = two_smallest_keys[0]
second_best = two_smallest_keys[1]
# generate noise value
noise_value = random.uniform(0, 1)
# compare noise value generated to the probability of second best variable being selected
if noise_value < self.probability:
return second_best
else:
return best
if __name__ == '__main__':
instance_path = None
# check whether a path to input dataset has been provided or should the default path be used
if len(sys.argv) > 1:
instance_path = sys.argv[1]
else:
instance_path = "./sat_data/uf20-020.cnf"
cnf_contents = SatUtils.read_instance(instance_path)
solver = NoveltySearch(cnf_contents, 0.4, 100000)
for i in range(1):
solver.main()