def toCNF(gndFormulas, formulas, allPositive=False):
'''
convert the given ground formulas to CNF
if allPositive=True, then formulas with negative weights are negated to make all weights positive
@return a new pair (gndFormulas, formulas)
'''
# get list of formula indices where we must negate
newFormulas = []
negate = []
if allPositive:
for idxFormula, formula in enumerate(formulas):
f = formula
if formula.weight < 0:
negate.append(idxFormula)
if isinstance(formula, FOL.Negation):
f = formula.children[0]
else:
f = FOL.Negation([formula])
f.weight = -formula.weight
f.idxFormula = idxFormula
newFormulas.append(f)
# get CNF version of each ground formula
newGndFormulas = []
for gf in gndFormulas:
# non-logical constraint
if not gf.isLogical(
): # don't apply any transformations to non-logical constraints
if gf.idxFormula in negate:
gf.negate()
newGndFormulas.append(gf)
continue
# logical constraint
if gf.idxFormula in negate:
cnf = FOL.Negation([gf]).toCNF()
else:
cnf = gf.toCNF()
if type(
cnf
) == FOL.TrueFalse: # formulas that are always true or false can be ignored
continue
cnf.idxFormula = gf.idxFormula
newGndFormulas.append(cnf)
# return modified formulas
return (newGndFormulas, newFormulas)
def _expandQueries(self, queries):
''' expands the list of queries where necessary, e.g. queries that are just predicate names are expanded to the corresponding list of atoms '''
equeries = []
for query in queries:
#print "got query '%s' of type '%s'" % (str(query), str(type(query)))
if type(query) == str:
prevLen = len(equeries)
if "(" in query: # a fully or partially grounded formula
f = FOL.parseFormula(query)
for gndFormula in f.iterGroundings(self.mln):
equeries.append(gndFormula[0])
else: # just a predicate name
try:
for gndPred in self.mln._getPredGroundings(query):
equeries.append(FOL.parseFormula(gndPred).ground(self.mln, {}))
except:
raise #Exception("Could not expand query '%s'" % query)
if len(equeries) - prevLen == 0:
raise Exception("String query '%s' could not be expanded." % query)
elif isinstance(query, FOL.Formula):
equeries.append(query)
else:
raise Exception("Received query of unsupported type '%s'" % str(type(query)))
return equeries
def _groundAtoms(self, cur, predName, domNames, verbose=False):
# if there are no more parameters to ground, we're done
# and we cann add the ground atom to the MRF
mrf = self.mrf
assert len(mrf.gndFormulas) == 0
if domNames == []:
atom = FOL.GroundAtom(predName, cur)
mrf.addGroundAtom(atom)
return
# create ground atoms for each way of grounding the first of the
# remaining variables whose domains are given in domNames
dom = mrf.domains.get(domNames[0])
if dom is None or len(dom) == 0:
raise Exception("Domain '%s' is empty!" % domNames[0])
for value in dom:
self._groundAtoms(cur + [value], predName, domNames[1:])
def _infer(self, verbose=True, details=False, fittingMethod=InferenceMethods.Exact, fittingThreshold=1e-3, fittingSteps=100, fittingParams=None, maxThreshold=None, greedy=False, **args):
# add formulas to the model whose weights we can then fit
if verbose: print "extending model with %d formulas whose weights will be fit..." % len(self.mrf.softEvidence)
for req in self.mrf.softEvidence:
formula = FOL.parseFormula(req["expr"])
idxFormula = self.mrf._addFormula(formula, 0.0)
gndFormula = formula.ground(self.mrf, {})
self.mrf._addGroundFormula(gndFormula, idxFormula)
req["gndExpr"] = req["expr"]
req["gndFormula"] = gndFormula
req["idxFormula"] = idxFormula
# do fitting
if fittingParams is None: fittingParams = {}
fittingParams.update(args)
results, self.data = self.mrf._fitProbabilityConstraints(self.mrf.softEvidence, fittingMethod=fittingMethod, fittingThreshold=fittingThreshold, fittingSteps=fittingSteps, given=self.given, queries=self.queries, verbose=details, fittingParams=fittingParams, maxThreshold=maxThreshold, greedy=greedy)
return results
def getValidVariableAssignments(self, conjunction, trueOrFalse, gndAtoms):
variableAssignments = []
gndAtomIndices = []
for lit in conjunction.children:
assignments = []
atomIndices = []
for gndAtom in gndAtoms:
try:
if gndAtom.predName != lit.predName:
continue
assignment = []
for (p1, p2) in zip(lit.params, gndAtom.params):
if FOL.isVar(p1):
assignment.append((p1, p2))
elif p1 != p2: raise
assignments.append(tuple(assignment))
atomIndices.append(gndAtom.idx)
except: pass
variableAssignments.append(assignments)
gndAtomIndices.append(atomIndices)
return variableAssignments, gndAtomIndices
def getAdmissibleVarAssignments(self, f, trueGndAtoms):
if not type(f) is Conjunction:
return None
cwPred = False
assignments = []
for child in f.children:
if not isinstance(child, Lit) and not isinstance(child, GroundLit) and not isinstance(child, GroundAtom):
return None
if child.predName in self.mrf.mln.closedWorldPreds and not cwPred:
cwPred = True
for gndAtom in trueGndAtoms:
if gndAtom.predName != child.predName:
continue
assignment = []
try:
for (p1, p2) in zip(child.params, gndAtom.params):
if FOL.isVar(p1):
assignment.append((p1, p2))
elif p1 != p2: raise
assignments.append(tuple(assignment))
except: pass
return assignments
def getValidVariableAssignments(self, conjunction, trueOrFalse, gndAtoms):
variableAssignments = []
gndAtomIndices = []
for lit in conjunction.children:
assignments = []
atomIndices = []
for gndAtom in gndAtoms:
try:
if gndAtom.predName != lit.predName:
continue
assignment = []
for (p1, p2) in zip(lit.params, gndAtom.params):
if FOL.isVar(p1):
assignment.append((p1, p2))
elif p1 != p2:
raise
assignments.append(tuple(assignment))
atomIndices.append(gndAtom.idx)
except:
pass
variableAssignments.append(assignments)
gndAtomIndices.append(atomIndices)
return variableAssignments, gndAtomIndices
