def calculateCore(self):
# Don't let simultaneous calculations occur if events are triggered too fast
if not self.coreCalculationLock.acquire(False):
print "WARNING: Skipping core calculation because already busy with one."
return
# TODO: actually cache trans CNF
# TODO: support SLURP parser
ltl_current = fsa.stateToLTL(self.env_aut.current_state, swap_io=True).strip()
next_state = copy.deepcopy(self.env_aut.current_state.transitions[0])
next_state.inputs.update(self.actuatorStates)
next_state.inputs.update(self.regionToBitEncoding(self.dest_region))
ltl_next = fsa.stateToLTL(next_state, use_next=True, swap_io=True).strip()
ltl_topo = self.spec['Topo'].replace('\n','').replace('\t','').strip()
ltl_trans = [s.strip() for s in self.spec['SysTrans'].split('\n')]
# note: strip()s make canonical (i.e. terminate in &, no whitespace on either side)
guilty_ltl = self.compiler.unsatCores(self.compiler._getPicosatCommand(), ltl_topo, ltl_current, [ltl_next] + ltl_trans, 1, 1)
print "Guilty LTL: ", guilty_ltl
guilty_spec = []
if self.proj.compile_options["parser"] == "structured":
if guilty_ltl is not None:
for ltl_frag, line_num in self.compiler.LTL2SpecLineNumber.iteritems():
ltl_frags_canonical = [s.strip() for s in ltl_frag.replace("\t","").split('\n')]
if not set(guilty_ltl).isdisjoint(ltl_frags_canonical):
guilty_spec.append(self.compiler.proj.specText.split("\n")[line_num-1])
elif self.proj.compile_options["parser"] == "slurp":
for ltl_frag in guilty_ltl:
canonical_ltl_frag = ltl_frag.lstrip().rstrip("\n\t &")
try:
guilty_clean = self.compiler.reversemapping[canonical_ltl_frag]
except KeyError:
print "WARNING: LTL fragment {!r} not found in canon_ltl->LTL mapping".format(canonical_ltl_frag)
continue
chunks = line_to_chunks(guilty_clean, self.tracebackChunks)
if chunks:
guilty_spec.append('{} (Because you said "{}")'.format(chunks[0].explanation.replace("'",""), chunks[0].input))
else:
print "WARNING: Canonical LTL fragment {!r} not found in spec->LTL mapping".format(guilty_clean)
if self.spec['Topo'].replace('\n','').replace('\t','').strip() in guilty_ltl:
guilty_spec.append("(topological constraints)")
print "Guilty Spec: ", guilty_spec
self.coreCalculationLock.release()
return guilty_spec
def getCurrentStateAsLTL(self, include_env=False):
""" Return a boolean formula (as a string) capturing the current discrete state of the system (and, optionally, the environment as well) """
if self.aut:
# If we have current state in the automaton, use it (since it can capture
# state of internal propositions).
return fsa.stateToLTL(self.aut.current_state, include_env=include_env)
else:
# If we have no automaton yet, determine our state manually
# TODO: support env
# TODO: look at self.hsub.executing_config.initial_truths and pose
return ""
def getCurrentStateAsLTL(self, include_env=False):
""" Return a boolean formula (as a string) capturing the current discrete state of the system (and, optionally, the environment as well) """
if self.aut:
# If we have current state in the automaton, use it (since it can capture
# state of internal propositions).
return fsa.stateToLTL(self.aut.current_state, include_env=include_env)
else:
# If we have no automaton yet, determine our state manually
# TODO: support env
# TODO: look at self.proj.currentConfig.initial_truths and pose
return ""
def calculateCore(self):
# Don't let simultaneous calculations occur if events are triggered too fast
if not self.coreCalculationLock.acquire(False):
print "WARNING: Skipping core calculation because already busy with one."
return
# TODO: actually cache trans CNF
# TODO: support SLURP parser
ltl_current = fsa.stateToLTL(self.env_aut.current_state,
swap_io=True).strip()
next_state = copy.deepcopy(self.env_aut.current_state.transitions[0])
next_state.inputs.update(self.actuatorStates)
next_state.inputs.update(self.regionToBitEncoding(self.dest_region))
ltl_next = fsa.stateToLTL(next_state, use_next=True,
swap_io=True).strip()
ltl_topo = self.spec['Topo'].replace('\n', '').replace('\t',
'').strip()
ltl_trans = [s.strip() for s in self.spec['SysTrans'].split('\n')]
# note: strip()s make canonical (i.e. terminate in &, no whitespace on either side)
guilty_ltl = self.compiler.unsatCores(
self.compiler._getPicosatCommand(), ltl_topo, ltl_current,
[ltl_next] + ltl_trans, 1, 1)
print "Guilty LTL: ", guilty_ltl
guilty_spec = []
if self.proj.compile_options["parser"] == "structured":
if guilty_ltl is not None:
for ltl_frag, line_num in self.compiler.LTL2SpecLineNumber.iteritems(
):
ltl_frags_canonical = [
s.strip()
for s in ltl_frag.replace("\t", "").split('\n')
]
if not set(guilty_ltl).isdisjoint(ltl_frags_canonical):
guilty_spec.append(
self.compiler.proj.specText.split("\n")[line_num -
1])
elif self.proj.compile_options["parser"] == "slurp":
for ltl_frag in guilty_ltl:
canonical_ltl_frag = ltl_frag.lstrip().rstrip("\n\t &")
try:
guilty_clean = self.compiler.reversemapping[
canonical_ltl_frag]
except KeyError:
print "WARNING: LTL fragment {!r} not found in canon_ltl->LTL mapping".format(
canonical_ltl_frag)
continue
chunks = line_to_chunks(guilty_clean, self.tracebackChunks)
if chunks:
guilty_spec.append('{} (Because you said "{}")'.format(
chunks[0].explanation.replace("'", ""),
chunks[0].input))
else:
print "WARNING: Canonical LTL fragment {!r} not found in spec->LTL mapping".format(
guilty_clean)
if self.spec['Topo'].replace('\n',
'').replace('\t',
'').strip() in guilty_ltl:
guilty_spec.append("(topological constraints)")
print "Guilty Spec: ", guilty_spec
self.coreCalculationLock.release()
return guilty_spec