def analyse_unsat(Formulas):
conj = conjunctive_partition(Formulas)
ucore = get_unsat_core(conj)
print("Unsat core:")
for f in ucore:
print(f.serialize())
return ucore
def unsat_core(self):
res = self.solver.solve()
if not res:
print('Assertions:', self.fml)
conj = conjunctive_partition(self.fml)
ucore = get_unsat_core(conj)
print("UNSAT-Core size '%d'" % len(ucore))
for f in ucore:
print(f.serialize())
def get_model_or_print_ucore(formula):
m = s.get_model(formula)
if not m:
print('unsat')
from pysmt.rewritings import conjunctive_partition
conj = conjunctive_partition(s.And(formula))
ucore = s.get_unsat_core(conj)
print("UNSAT-Core size '%d'" % len(ucore))
for f in ucore:
print(f.serialize())
return
return m
# We first check whether the constraints on the domain and problem
# are satisfiable in isolation.
assert is_sat(facts)
assert is_sat(domain)
assert is_unsat(problem)
# In isolation they are both fine, rules from both are probably
# interacting.
#
# The problem is given by a nesting of And().
# conjunctive_partition can be used to obtain a "flat"
# structure, i.e., a list of conjuncts.
#
from pysmt.rewritings import conjunctive_partition
conj = conjunctive_partition(problem)
ucore = get_unsat_core(conj)
print("UNSAT-Core size '%d'" % len(ucore))
for f in ucore:
print(f.serialize())
# The exact version of the UNSAT-Core depends on the solver in
# use. Nevertheless, this represents a starting point for your
# debugging. A possible way to approach the result is to look for
# clauses of size 1 (i.e., unit clauses). In the facts list there
# are only 2 facts:
# 2_drink_milk
# 0_nat_norwegian
#
# The clause ("1_color_blue" <-> "0_nat_norwegian")
# Implies that "1_color_blue"
# But (("3_color_blue" | "1_color_blue") <-> "2_nat_norwegian")
# We first check whether the constraints on the domain and problem
# are satisfiable in isolation.
assert is_sat(facts)
assert is_sat(domain)
assert is_unsat(problem)
# In isolation they are both fine, rules from both are probably
# interacting.
#
# The problem is given by a nesting of And().
# conjunctive_partition can be used to obtain a "flat"
# structure, i.e., a list of conjuncts.
#
from pysmt.rewritings import conjunctive_partition
conj = conjunctive_partition(problem)
ucore = get_unsat_core(conj)
print("UNSAT-Core size '%d'" % len(ucore))
for f in ucore:
print(f.serialize())
# The exact version of the UNSAT-Core depends on the solver in
# use. Nevertheless, this represents a starting point for your
# debugging. A possible way to approach the result is to look for
# clauses of size 1 (i.e., unit clauses). In the facts list there
# are only 2 facts:
# 2_drink_milk
# 0_nat_norwegian
#
# The clause ("1_color_blue" <-> "0_nat_norwegian")
# Implies that "1_color_blue"
# But (("3_color_blue" | "1_color_blue") <-> "2_nat_norwegian")
def test_generators_in_shortcuts(self):
flist = [Symbol("x"), Not(Symbol("x"))]
gen_f = (x for x in flist)
ucore = get_unsat_core(gen_f)
self.assertEqual(len(ucore), 2)
def test_shortcut(self):
x = Symbol("x")
core = get_unsat_core([x, Not(x)])
self.assertEqual(len(core), 2)
self.assertIn(x, core)
self.assertIn(Not(x), core)
def test_generators_in_shortcuts(self):
flist = [Symbol("x"), Not(Symbol("x"))]
gen_f = (x for x in flist)
ucore = get_unsat_core(gen_f)
self.assertEqual(len(ucore), 2)
def test_shortcut(self):
x = Symbol("x")
core = get_unsat_core([x, Not(x)])
self.assertEqual(len(core), 2)
self.assertIn(x, core)
self.assertIn(Not(x), core)
