def __init__(self):
super().__init__()
self.solver = minisolvers.MinisatSolver()
self.nameMap = dict()
self.nVar = 0
self.pushSolver = minisolvers.MinisatSolver()
self.pushNVar = 0
self.pushClauses = list()
def _generate_iclause_pair(self, n_vars):
solver = minisolvers.MinisatSolver()
for i in range(n_vars):
solver.new_var(dvar=True)
iclauses = []
while True:
k_base = 1 if random.random() < self.p_k_2 else 2
k = k_base + np.random.geometric(self.p_geo)
iclause = self._generate_k_iclause(n_vars, k)
solver.add_clause(iclause)
is_sat = solver.solve()
if is_sat:
iclauses.append(iclause)
else:
break
iclause_unsat = iclause
iclause_sat = [-iclause_unsat[0]] + iclause_unsat[1:]
unsat_clauses = iclauses.copy()
unsat_clauses.append(iclause_unsat)
iclauses.append(iclause_sat)
return unsat_clauses, iclauses
def gen_iclause_pair(n, iclauses, p_k_2, p_geo):
# min_n = 10
# max_n = min_n
# n = random.randint(min_n, max_n)
# n = n_vars
solver = minisolvers.MinisatSolver()
for i in range(n):
solver.new_var(dvar=True)
for iclause in iclauses:
solver.add_clause(iclause)
is_sat = solver.solve()
if is_sat:
print("Converting SAT to unSAT")
while True:
k_base = 1 if random.random() < p_k_2 else 2
k = k_base + np.random.geometric(p_geo)
iclause = generate_k_iclause(n, k)
solver.add_clause(iclause)
is_sat = solver.solve()
if is_sat:
iclauses.append(iclause)
else:
print("Conversion Done")
break
iclause_unsat = iclause
iclauses.append(iclause_unsat)
return n, iclauses, p_k_2, p_geo
def push(self):
self.pushSolver = self.solver
self.solver = minisolvers.MinisatSolver()
for i in range(self.nVar):
self.solver.new_var()
for i in self.clauses:
self.solver.add_clause(i)
self.pushNVar = self.nVar
self.pushClauses = self.clauses.copy()
def miniSatUse():
S = minisolvers.MinisatSolver()
for i in range(3):
S.new_var()
for clause in [1], [-1, 2], [-1, 2, 3], [1], [1]:
S.add_clause(clause)
while S.solve():
print(list(S.get_model()))
S.block_model()
def solve_sat(n_vars, iclauses):
solver = minisolvers.MinisatSolver()
for i in range(n_vars):
solver.new_var(dvar=True)
for iclause in iclauses:
solver.add_clause(iclause)
is_sat = solver.solve()
stats = solver.get_stats()
return is_sat, stats
def run_new_sat(self, iclauses):
S = minisolvers.MinisatSolver()
for _ in range(self.sizes[0] + self.sizes[1]):
S.new_var()
for c in iclauses:
S.add_clause(c)
if S.solve():
return True, list(S.get_model())
else:
return False, None
def gen_iclause_pair(args, n):
solver = minisolvers.MinisatSolver()
for i in range(n):
solver.new_var(dvar=True)
iclauses = []
while True:
k_base = 1 if random.random() < args.p_k_2 else 2
k = k_base + np.random.geometric(args.p_geo)
iclause = generate_k_iclause(n, k)
solver.add_clause(iclause)
is_sat = solver.solve()
if is_sat:
iclauses.append(iclause)
else:
break
iclause_unsat = iclause
iclause_sat = [-iclause_unsat[0]] + iclause_unsat[1:]
return n, iclauses, iclause_unsat, iclause_sat
def __init__(self, specs, sizes, filename):
# specs: list of size 2. For example: [2, 3] means each clause has 2 forall vars first, then 3 exists vars.
# sizes: list of size 2. For example: [8, 10] means the problem has 8 forall vars and 10 exists vars.
# filename: the file name of the 2QBF problem
self.specs = specs
self.sizes = sizes
_, self.iclauses = parse_dimacs(filename)
self.temp_filename = self.get_temp_filename(filename)
self.steps = 0
# set up the SAT solver for counter examples
self.omega = minisolvers.MinisatSolver()
# self.omega = SharpSAT()
# add all forall vars
for _ in range(sizes[0]):
self.omega.new_var()
# add all clause vars (Cz) and the clauses to constraint that (Cz == false of clause c)
self.Cz_list = []
for c in self.iclauses:
self.omega.new_var()
Cz = self.omega.nvars()
self.Cz_list.append(Cz)
for Cc in c[:specs[0]]:
self.omega.add_clause([-Cz, -Cc])
