Python Be.false方法代码示例

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def test_bounded_semantics_without_loop(self):
     # parse the ltl property
     spec = Node.from_ptr(parse_ltl_spec("G ( y <= 7 )"))
     
     # it must raise exception when the bound is not feasible
     with self.assertRaises(ValueError):
         ltlspec.bounded_semantics_without_loop(self.fsm, spec, bound=-1)
     
     # verify that the generated expression corresponds to what is announced
     no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
     
     # globally w/o loop is false (this is just a test)
     self.assertEqual(no_loop, Be.false(self.fsm.encoding.manager)) 
     
     # an other more complex generation
     spec = Node.from_ptr(parse_ltl_spec("F (y <= 7)"))
     no_loop = ltlspec.bounded_semantics_without_loop(self.fsm, spec, 10)
     
     #
     # The generated expression is [[f]]^{0}_{k} so (! L_{k}) is not taken 
     # care of. And actually, NuSMV does not generate that part of the 
     # formula: it only enforce the loop condition when the semantics with 
     # loop is used 
     # 
     handcrafted = Be.false(self.fsm.encoding.manager)
     y_le_seven  = Wff(parse_ltl_spec("y <= 7")).to_boolean_wff().to_be(self.fsm.encoding)
     for time_x in reversed(range(11)): # 11 because range 'eats' up the last step
         handcrafted |= self.fsm.encoding.shift_to_time(y_le_seven, time_x)
     
     #### debuging info #####
     #print("noloop  = {}".format(no_loop.to_cnf()))
     #print("hancraft= {}".format(handcrafted.to_cnf()))
     #print(self.fsm.encoding)
     self.assertEqual(no_loop, handcrafted)

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def test_false(self):
     with self.assertRaises(Exception):
         Be.false(None)
     expr = Be.false(self._manager)
     self.assertFalse(expr.is_true())
     self.assertTrue(expr.is_false())
     self.assertTrue(expr.is_constant())

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def test_globally_no_loop(self):
     with Configure(self, __file__, "/models/flipflops.smv"):
         fsm     = self.befsm
         formula = self.nnf("G (a <-> !b)")
         
         #  bound 0
         ref_expr= ltlspec.bounded_semantics_without_loop(fsm, formula, 0)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 0, 0)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))
         
         # bound 1
         ref_expr= ltlspec.bounded_semantics_without_loop(fsm, formula, 1)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 1, 0)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))
         
         # ---- other offset ----
         #  bound 0
         offset  = 1
         ref_expr= Be.false(fsm.encoding.manager)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 0, offset)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))
         
         #  bound 1
         offset  = 1
         ref_expr= Be.false(fsm.encoding.manager)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 1, offset)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def test_next_no_loop(self):
     with Configure(self, __file__, "/models/flipflops.smv"):
         fsm     = self.befsm
         formula = self.nnf("X (a <-> !b)")
         
         #  bound 0
         ref_expr= ltlspec.bounded_semantics_without_loop(fsm, formula, 0)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 0, 0)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))
         
         # bound 1
         ref_expr= ltlspec.bounded_semantics_without_loop(fsm, formula, 1)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 1, 0)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))
         
         # ---- other offset ----
         #  bound 0
         offset  = 1
         ref_expr= Be.false(fsm.encoding.manager)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 0, offset)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))
         
         #  bound 1
         offset  = 1
         ref_expr= Wff.decorate(ltlspec.car(formula)).to_be(fsm.encoding)
         ref_expr= fsm.encoding.shift_to_time(ref_expr, offset+1)
         expr    = ltlspec.bounded_semantics_without_loop_at_offset(fsm, formula, 0, 1, offset)
         self.assertEqual(canonical_cnf(expr), canonical_cnf(ref_expr))

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def test_constant_with_loop(self):
     with tests.Configure(self, __file__, "/example.smv"):
         expr = ast.Constant("TRUE")
         self.assertEqual(Be.true(self.mgr), expr.semantic_with_loop(self.enc, 0, 5, 2))
         
         expr = ast.Constant("FALSE")
         self.assertEqual(Be.false(self.mgr), expr.semantic_with_loop(self.enc, 0, 5, 2))

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def bounded_semantics(self, fsm, k, fairness=True):
        """
        Returns a boolean expression corresponding to the bounded semantics of
        the formula denoted by `self` on a path of length k. This combines both
        the semantics in case of a loopy path and the case of a non-loopy path.

        .. note::
            This function takes the same approach as NuSMV and does not enforce
            the absence of loop when using the more restrictive semantic_no_loop.

        :param fsm: the FSM representing the model. It is used to gain access
            to the encoder (-> shift variables) and to obtain the list of
            fairness constraints.
        :param k: the last time that exists in the universe of this expression
        :param fairness: a flag indicating whether or not the fairness constraints
            should be taken into account while generating the formula.
        :return: a boolean expression translating the bounded semantics of this
            formula.
        """
        enc = fsm.encoding
        noloop = self.semantic_no_loop(enc, 0, k)

        w_loop = Be.false(enc.manager)
        for l in range(k):  # [0; k-1]
            fairness_cond = fairness_constraint(fsm, k, l) if fairness else Be.true(enc.manager)

            w_loop |= loop_condition(enc, k, l) & fairness_cond & self.semantic_with_loop(enc, 0, k, l)

        return noloop | w_loop

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def test_add_(self):
        # using the algebraic notation
        true = Be.true(self._manager)
        false = Be.false(self._manager)

        self.assertTrue((true + false).is_true())
        self.assertFalse((true + false).is_false())
        self.assertTrue((true + false).is_constant())

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def test_sub_(self):
        # and not
        true = Be.true(self._manager)
        false = Be.false(self._manager)

        self.assertTrue((true - false).is_true())
        self.assertFalse((true - false).is_false())
        self.assertTrue((true - false).is_constant())

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def test_and(self):
        # using the function
        true = Be.true(self._manager)
        false = Be.false(self._manager)

        self.assertFalse(true.and_(false).is_true())
        self.assertTrue(true.and_(false).is_false())
        self.assertTrue(true.and_(false).is_constant())

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def test__and_(self):
        # using the keyword
        true = Be.true(self._manager)
        false = Be.false(self._manager)

        self.assertFalse((true and false).is_true())
        self.assertTrue((true and false).is_false())
        self.assertTrue((true and false).is_constant())

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def _semantic(time, cnt):
     """auxiliary function to stop recursing after k steps"""
     # at infinity, it is false: psi MUST happen at some time
     if cnt == k:
         return Be.false(enc.manager)
     psi = self.rhs.semantic_with_loop(enc, time, k, l)
     phi = self.lhs.semantic_with_loop(enc, time, k, l)
     return psi | (phi & _semantic(successor(time, k, l), cnt + 1))

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def semantic_no_loop(self, enc, i, k):
        """The semantics when there is no loop:: [[lhs W rhs]]_{bound}^{time}"""
        # k is not infinity when there is no loop
        if i > k:
            return Be.false(enc.manager)

        psi = self.rhs.semantic_no_loop(enc, i, k)
        phi = self.lhs.semantic_no_loop(enc, i, k)
        return psi | (phi & self.semantic_no_loop(enc, i + 1, k))

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
 def test_globally_no_loop(self):
     with tests.Configure(self, __file__, "/example.smv"):
         i,k     = 0,2
         enc     = self.enc
         mgr     = enc.manager
         a       = ast.Proposition("a")
         formula = ast.Globally(a)
         
         tool = formula.semantic_no_loop(enc, i, k)
         self.assertEqual(Be.false(mgr), tool)

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
    def semantic_with_loop(self, enc, i, k, l):
        # without moving at least one step, it is impossible to go through a loop
        if k == 0:
            return Be.false(enc.manager)

        def _semantic(time, cnt):
            if cnt == k:
                return Be.false(enc.manager)
            now = self.prop.semantic_with_loop(enc, time, k, l)
            return now | _semantic(successor(time, k, l), cnt + 1)

        return _semantic(i, 0)

# 需要导入模块: from pynusmv.be.expression import Be [as 别名]
# 或者: from pynusmv.be.expression.Be import false [as 别名]
def bounded_semantics_at_offset(fsm, formula, bound, offset, fairness=True):
    """
    Generates the Be [[formula]]_{bound} corresponding to the bounded semantic 
    of `formula` but encodes it with an `offset` long shift in the timeline of the encoder.

    .. note:: 

        This function plays the same role as `bounded_semantics_all_loops` but allows to 
        position the time blocks at some place we like in the encoder timeline. This is mostly
        helpful if you want to devise verification methods that need to have multiple parallel
        verifications. (ie. diagnosability).

        Note however, that the two implementations are different.

    .. warning::

        So far, the only supported temporal operators are F, G, U, R, X

    :param fsm: the BeFsm for which the property will be verified. Actually, it is only used to 
        provide the encoder used to assign the variables to some time blocks. The api was kept 
        this ways to keep uniformity with its non-offsetted counterpart.
    :param formula: the property for which to generate a verification problem
        represented in a 'node' format (subclass of :see::class:`pynusmv.node.Node`)
        which corresponds to the format obtained from the ast. (remark: if you
        need to manipulate [ie negate] the formula before passing it, it is
        perfectly valid to pass a node decorated by `Wff.decorate`).
    :param bound: the logical time bound to the problem. (Leave out the offset for this param: if you
        intend to have a problem with at most 10 steps, say bound=10)
    :param offset: the time offset in the encoding block where the sem of this formula will be 
        generated.
    :param fairness: a flag indicating whether or not to take the fairness 
        constraint into account.
    :return: a Be corresponding to the semantics of `formula` for a problem with a maximum of `bound` 
        steps encoded to start at time `offset` in the `fsm` encoding timeline.
    """
    if bound< 0:
        raise ValueError("Bound must be a positive integer")
    if offset<0:
        raise ValueError("The offset must be a positive integer")
    
    enc = fsm.encoding
    straight = bounded_semantics_without_loop_at_offset(fsm, formula, 0, bound, offset)
    k_loop   = Be.false(enc.manager)
    for i in range(bound): 
        fairness_cond = utils.fairness_constraint(fsm, offset+bound, offset+i) \
                                 if fairness \
                                 else Be.true(enc.manager)
        k_loop |= ( utils.loop_condition(enc, offset+bound, offset+i) \
                  & fairness_cond \
                  & bounded_semantics_with_loop_at_offset(fsm, formula, 0, bound, i, offset))
    
    # this is just the sem of the formula
    return straight | k_loop