def is_model(polish_formula, model, generator=None):
if generator is None:
generator = Generator()
formula = generator.to_expression(polish_formula)
solver = aiger_sat.SolverWrapper()
solver.add_expr(~formula)
return not solver.is_sat(assumptions=model)
def generate_model(formula_pre, generator=None):
if generator is None:
generator = Generator()
expr = generator.to_expression(formula_pre)
solver = aiger_sat.SolverWrapper()
try:
solver.add_expr(expr)
except ValueError as e:
print('ValueError', str(e))
return None
model = solver.get_model()
model_str = None
if model:
model_word_pairs = [
'%s %s' % x for x in sorted(model.items(), key=lambda x: x[0])
]
model_str = ' '.join(model_word_pairs)
minimized = minimize_model(expr, model)
minimized_str = None
if minimized:
minimized_word_pairs = [
'%s %s' % x for x in sorted(minimized.items(), key=lambda x: x[0])
]
minimized_str = ' '.join(minimized_word_pairs)
return minimized_str
def minimize_model(formula, model):
if model is None:
return None
solver = aiger_sat.SolverWrapper()
solver.add_expr(~formula)
if solver.is_sat(assumptions=model):
raise ValueError('UNSAT core generation failed.')
minimized = solver.get_unsat_core()
if minimized is None:
minimized = {}
return minimized
def is_model(polish_formula: Text, model: Dict[Text, int]):
formula = generator.to_expression(polish_formula.split())
solver = aiger_sat.SolverWrapper()
solver.add_expr(~formula)
return not solver.is_sat(assumptions=model)
def get_model(formula):
solver = aiger_sat.SolverWrapper()
solver.add_expr(formula)
return solver.get_model()