def test_equal_atoms(self):
test = parse_next_expression("test")
test = nsnode.find_node(test.type, nsnode.car(test), nsnode.cdr(test))
same = parse_next_expression("test")
same = nsnode.find_node(same.type, nsnode.car(same), nsnode.cdr(same))
other = parse_next_expression("testx")
other = nsnode.find_node(other.type, nsnode.car(other),
nsnode.cdr(other))
self.assertTrue(nsnode.node_equal(test, same) != 0)
self.assertTrue(nsnode.node_equal(test, other) == 0)
def test_equal_atoms(self):
test = parse_next_expression("test")
test = nsnode.find_node(test.type, nsnode.car(test), nsnode.cdr(test))
same = parse_next_expression("test")
same = nsnode.find_node(same.type, nsnode.car(same), nsnode.cdr(same))
other = parse_next_expression("testx")
other = nsnode.find_node(other.type, nsnode.car(other),
nsnode.cdr(other))
self.assertTrue(nsnode.node_equal(test, same) != 0)
self.assertTrue(nsnode.node_equal(test, other) == 0)
def test_trans_in_context(self):
car = nsnode.car
cdr = nsnode.cdr
orig = "(next(c) = c) IN c1"
trans = "next(c) = c"
context = "c1"
origp = parse_next_expression(orig)
transp = parse_next_expression(trans)
contextp = parse_identifier(context)
# contextp is ATOM. We want DOT(None, ATOM)
contextp = nsnode.find_node(nsparser.DOT, None, contextp)
fullp = nsnode.find_node(nsparser.CONTEXT, contextp, transp)
self.checkNodeTypeEqual(origp, fullp)
def test_trans_in_context(self):
car = nsnode.car
cdr = nsnode.cdr
orig = "(next(c) = c) IN c1"
trans = "next(c) = c"
context = "c1"
origp = parse_next_expression(orig)
transp = parse_next_expression(trans)
contextp = parse_identifier(context)
# contextp is ATOM. We want DOT(None, ATOM)
contextp = nsnode.find_node(nsparser.DOT, None, contextp)
fullp = nsnode.find_node(nsparser.CONTEXT, contextp, transp)
self.checkNodeTypeEqual(origp, fullp)
def _compute_epistemic_trans(self, agents):
from .glob import symb_table
trans = None
for agent in agents:
if agent not in self._epistemic:
raise UnknownAgentError(
str(agents) + " are an unknown agents names.")
trans = nsnode.find_node(nsparser.AND, self._epistemic[agent],
trans)
self._epistemic_trans[frozenset(agents)] = BddTrans.from_trans(
symb_table(), trans)
def _compute_epistemic_trans(self, agents):
from .glob import symb_table
trans = None
for agent in agents:
if agent not in self._epistemic:
raise UnknownAgentError(str(agents) +
" are an unknown agents names.")
trans = nsnode.find_node(nsparser.AND,
self._epistemic[agent],
trans)
self._epistemic_trans[agents] = BddTrans.from_trans(symb_table(),
trans)
def mas(agents=None):
"""
Return (and compute if needed) the multi-agent system represented by
the currently read SMV model.
If agents is not None, the set of agents (and groups) of the MAS is
determined by agents.
Otherwise, every top-level module instantiation is considered an agent
where
- her actions are the inputs variables prefixed by her name;
- her observable variables are composed of
* the state variables of the system prefixed by her name;
* the state variables provided as an argument to the module
instantiation.
Note: if the MAS is already computed, agents argument has no effect.
agents -- a set of agents.
"""
global __mas
if __mas is None:
# Check cmps
if not nscompile.cmp_struct_get_read_model(nscompile.cvar.cmps):
raise NuSMVNoReadModelError("Cannot build MAS; no read file.")
if agents is None:
# Get agents names
tree = nsparser.cvar.parsed_tree
main = None
while tree is not None:
module = nsnode.car(tree)
if (nsnode.sprint_node(nsnode.car(nsnode.car(module))) ==
"main"):
main = module
tree = nsnode.cdr(tree)
if main is None:
print("[ERROR] No main module.")
return # TODO Error, cannot find main module
arguments = _get_instances_args_for_module(main)
# arguments is a dict instancename(str)->listofargs(node)
agents = arguments.keys()
# Compute the model
_compute_model()
st = symb_table()
# Flatten arguments and filter on variables
argvars = _flatten_and_filter_variable_args(arguments)
# Get agents observable variables (locals + module parameters)
localvars = _get_variables_by_instances(agents)
#localvars is a dict instancename(str)->listofvars(node)
inputvars = _get_input_vars_by_instances(agents)
# Merge instance variable arguments and local variables
variables = {key: ((key in argvars and argvars[key] or []) +
(key in localvars and localvars[key] or []))
for key in
list(argvars.keys())+list(localvars.keys())}
# Compute epistemic relation
singletrans = {}
for agent in variables:
transexpr = None
for var in variables[agent]:
var = nsnode.sprint_node(var)
transexpr = nsnode.find_node(nsparser.AND,
_get_epistemic_trans(var),
transexpr)
singletrans[agent] = transexpr
# Process variables to get strings instead of nodes
observedvars = {ag: {nsnode.sprint_node(v) for v in variables[ag]}
for ag in variables.keys()}
inputvars = {ag: {nsnode.sprint_node(v)
for v in inputvars[ag]}
for ag in inputvars.keys()}
groups = None
else:
_compute_model()
# observedvars: a dictionary of agent name -> set of observed vars
observedvars = {str(agent.name): {str(var)
for var in agent.observables}
for agent in agents}
# inputsvars: a dictionary of agent name -> set of inputs vars
inputvars = {str(agent.name): {str(ivar)
for ivar in agent.actions}
for agent in agents}
# groups:
# a dictionary of group name -> names of agents of the group
groups = {str(group.name): {str(agent.name)
for agent in group.agents}
for group in agents if isinstance(group, Group)}
# singletrans: a dictionary of agent name -> epistemic transition
singletrans = {}
for agent in agents:
name = str(agent.name)
transexpr = None
for var in observedvars[name]:
transexpr = nsnode.find_node(nsparser.AND,
_get_epistemic_trans(var),
transexpr)
singletrans[name] = transexpr
# Create the MAS
fsm = _prop_database().master.bddFsm
__mas = MAS(fsm._ptr, observedvars, inputvars, singletrans,
groups=groups, freeit=False)
return __mas
def mas(agents=None, initial_ordering=None):
"""
Return (and compute if needed) the multi-agent system represented by
the currently read SMV model.
If agents is not None, the set of agents (and groups) of the MAS is
determined by agents.
Otherwise, every top-level module instantiation is considered an agent
where
- her actions are the inputs variables prefixed by her name;
- her observable variables are composed of
* the state variables of the system prefixed by her name;
* the state variables provided as an argument to the module
instantiation.
If initial_ordering is not None, it must be the path to a variables
ordering file. It is used as the initial ordering for variables of the
model.
Note: if the MAS is already computed, agents and initial_ordering arguments
have no effect.
agents -- a set of agents.
"""
global __mas
if __mas is None:
# Check cmps
if not nscompile.cmp_struct_get_read_model(nscompile.cvar.cmps):
raise NuSMVNoReadModelError("Cannot build MAS; no read file.")
if agents is None:
# Get agents names
tree = nsparser.cvar.parsed_tree
main = None
while tree is not None:
module = nsnode.car(tree)
if (nsnode.sprint_node(nsnode.car(
nsnode.car(module))) == "main"):
main = module
tree = nsnode.cdr(tree)
if main is None:
print("[ERROR] No main module.")
return # TODO Error, cannot find main module
arguments = _get_instances_args_for_module(main)
# arguments is a dict instancename(str)->listofargs(node)
agents = arguments.keys()
# Compute the model
_compute_model(variables_ordering=initial_ordering)
st = symb_table()
# Flatten arguments and filter on variables
argvars = _flatten_and_filter_variable_args(arguments)
# Get agents observable variables (locals + module parameters)
localvars = _get_variables_by_instances(agents)
#localvars is a dict instancename(str)->listofvars(node)
inputvars = _get_input_vars_by_instances(agents)
# Merge instance variable arguments and local variables
variables = {
key: ((key in argvars and argvars[key] or []) +
(key in localvars and localvars[key] or []))
for key in list(argvars.keys()) + list(localvars.keys())
}
# Compute epistemic relation
singletrans = {}
for agent in variables:
transexpr = None
for var in variables[agent]:
var = nsnode.sprint_node(var)
transexpr = nsnode.find_node(nsparser.AND,
_get_epistemic_trans(var),
transexpr)
singletrans[agent] = transexpr
# Process variables to get strings instead of nodes
observedvars = {
ag: {nsnode.sprint_node(v)
for v in variables[ag]}
for ag in variables.keys()
}
inputvars = {
ag: {nsnode.sprint_node(v)
for v in inputvars[ag]}
for ag in inputvars.keys()
}
groups = None
else:
_compute_model(variables_ordering=initial_ordering)
# observedvars: a dictionary of agent name -> set of observed vars
observedvars = {
str(agent.name): [str(var) for var in agent.observables]
for agent in agents
}
# inputsvars: a dictionary of agent name -> set of inputs vars
inputvars = {
str(agent.name): [str(ivar) for ivar in agent.actions]
for agent in agents
}
# groups:
# a dictionary of group name -> names of agents of the group
groups = {
str(group.name): [str(agent.name) for agent in group.agents]
for group in agents if isinstance(group, Group)
}
# singletrans: a dictionary of agent name -> epistemic transition
singletrans = {}
for agent in agents:
name = str(agent.name)
transexpr = None
for var in observedvars[name]:
transexpr = nsnode.find_node(nsparser.AND,
_get_epistemic_trans(var),
transexpr)
singletrans[name] = transexpr
# Create the MAS
fsm = _prop_database().master.bddFsm
__mas = MAS(fsm._ptr,
observedvars,
inputvars,
singletrans,
groups=groups,
freeit=False)
return __mas
def test_trans(self):
# Parse a model
#nsparser.ReadSMVFromFile("tests/pynusmv/models/modules.smv")
#parsed_tree = nsparser.cvar.parsed_tree
nscmd.Cmd_SecureCommandExecute(
"read_model -i tests/pynusmv/models/modules.smv")
nscmd.Cmd_SecureCommandExecute("flatten_hierarchy")
st = nscompile.Compile_get_global_symb_table()
# main = nsnode.find_node(
# nsparser.ATOM,
# nsnode.string2node(nsutils.find_string("main")),
# None)
#
# # Flatten
# nscompile.CompileFlatten_init_flattener()
# st = nscompile.Compile_get_global_symb_table()
# layer = nssymb_table.SymbTable_create_layer(st, "model",
# nssymb_table.SYMB_LAYER_POS_BOTTOM)
# nssymb_table.SymbTable_layer_add_to_class(st, "model", "Model Class")
# nssymb_table.SymbTable_set_default_layers_class_name(st, "Model Class")
#
# #hierarchy = nscompile.Compile_FlattenHierarchy(
# # st, layer, main, None, None, 1, 0, None)
#
# hierarchy = nscompile.FlatHierarchy_create(st)
# instances = nsutils.new_assoc()
#
# nscompile.Compile_ConstructHierarchy(st, layer, main, None, None,
# hierarchy, None, instances)
#
# fhtrans = nscompile.FlatHierarchy_get_trans(hierarchy)
# print("NON FLATTENED")
# print(nsnode.sprint_node(fhtrans))
#
# print(fhtrans.type) #169 = AND
# print(car(fhtrans)) #None
# print(cdr(fhtrans).type) #130 = CONTEXT
# print(car(cdr(fhtrans)).type) #208 = DOT
# print(car(car(cdr(fhtrans)))) #None
# print(cdr(car(cdr(fhtrans))).type) #161 = ATOM
# print(nsnode.sprint_node(cdr(car(cdr(fhtrans))))) #m
#
# print(cdr(cdr(fhtrans)).type) #192 = EQUAL
#
#
#
# trans = nscompile.Compile_FlattenSexp(st, cdr(fhtrans), None)
# print("FLATTENED")
# print(nsnode.sprint_node(trans))
layers = nssymb_table.SymbTable_get_class_layer_names(st, None)
variables = nssymb_table.SymbTable_get_layers_sf_i_vars(st, layers)
ite = nsutils.NodeList_get_first_iter(variables)
while not nsutils.ListIter_is_end(ite):
variable = nsutils.NodeList_get_elem_at(variables, ite)
print(nsnode.sprint_node(variable))
ite = nsutils.ListIter_get_next(ite)
top = nsnode.find_node(nsparser.ATOM,
nsnode.string2node(nsutils.find_string("top")),
None)
trans = nssexp.Expr_equal(nssexp.Expr_next(top, st), top, st)
flattrans = nscompile.Compile_FlattenSexp(st, trans, None)
inmod = nsnode.find_node(
nsparser.ATOM, nsnode.string2node(nsutils.find_string("inmod")),
None)
t = nsnode.find_node(nsparser.ATOM,
nsnode.string2node(nsutils.find_string("t")),
None)
m = nsnode.find_node(nsparser.ATOM,
nsnode.string2node(nsutils.find_string("m")),
None)
my = nsnode.find_node(nsparser.ATOM,
nsnode.string2node(nsutils.find_string("my")),
None)
n = nsnode.find_node(nsparser.ATOM,
nsnode.string2node(nsutils.find_string("n")),
None)
mymod = nsnode.find_node(
nsparser.ATOM, nsnode.string2node(nsutils.find_string("mymod")),
None)
main = nsnode.find_node(
nsparser.ATOM, nsnode.string2node(nsutils.find_string("main")),
None)
minmod = nsnode.find_node(nsparser.DOT,
nsnode.find_node(nsparser.DOT, None, m),
inmod)
ftrans = nssexp.Expr_equal(
nssexp.Expr_next(inmod, st),
nssexp.Expr_or(inmod, nsnode.find_node(nsparser.DOT, my, inmod)),
st)
print(nsnode.sprint_node(ftrans))
res, err = nsparser.ReadNextExprFromString(
"next(inmod) = (inmod | my.inmod) IN n")
self.assertEqual(err, 0)
trans = car(res)
print(nsnode.sprint_node(trans))
conttrans = nsnode.find_node(nsparser.CONTEXT,
nsnode.find_node(nsparser.DOT, None, n),
ftrans)
print(nsnode.sprint_node(conttrans))
fflattrans = nscompile.Compile_FlattenSexp(st, conttrans, None)
flattrans = nscompile.Compile_FlattenSexp(st, trans, None)
print(nsnode.sprint_node(fflattrans))
print(nsnode.sprint_node(flattrans))