def simplify(cnf_file, output_file, num_var_not_fixed, rng):
sol = solve_weighted_max_sat_file(cnf_file, [], 1)
int_sol = []
for i, val in enumerate(sol[0]):
if val:
int_sol.append(i + 1)
else:
int_sol.append(-(i + 1))
sol = rng.choice(int_sol,
size=len(int_sol) - num_var_not_fixed,
replace=False)
output_file += ".wcnf"
fix_var(cnf_file, output_file, sol)
wcnf = WCNF(output_file)
wcnf.to_file(output_file)
return cnf_to_model(output_file, rng)
def generate_wcnfs(path, models_and_contexts):
for i, elem in enumerate(models_and_contexts):
model = elem["model"]
contexts = elem["contexts"]
wcnf = WCNF()
for weight_clause in model:
if weight_clause[0] == None:
wcnf.append(tuple(weight_clause[1]))
else:
wcnf.append(tuple(weight_clause[1]), weight=weight_clause[0])
wcnf.to_file(path + f"_{i}.wcnf")
for j, context in enumerate(contexts):
wcnf_context = wcnf.copy()
# print(context)
for literals in context:
wcnf_context.append((literals,))
wcnf_context.to_file(path + f"_{i}_context_{j}.wcnf")
