def setUp(self):
self.owlGraph = QueryCountingGraph().parse(StringIO(EX_ONT),
format='n3')
rule_store, rule_graph, self.network = SetupRuleStore(makeNetwork=True)
self.program = self.network.setupDescriptionLogicProgramming(
self.owlGraph, addPDSemantics=False, constructNetwork=False)
self.program.update(AdditionalRules(self.owlGraph))
def MagicOWLProof(self, goals, rules, factGraph, conclusionFile):
progLen = len(rules)
magicRuleNo = 0
dPreds = []
for rule in AdditionalRules(factGraph):
rules.append(rule)
if not GROUND_QUERY:
goalDict = dict([((Variable('SUBJECT'), goalP, goalO), goalS)
for goalS, goalP, goalO in goals])
goals = goalDict.keys()
assert goals
topDownStore = TopDownSPARQLEntailingStore(
factGraph.store,
factGraph,
idb=rules,
DEBUG=DEBUG,
identifyHybridPredicates=True,
nsBindings=nsMap)
targetGraph = Graph(topDownStore)
for pref, nsUri in nsMap.items():
targetGraph.bind(pref, nsUri)
start = time.time()
for goal in goals:
queryLiteral = EDBQuery([BuildUnitermFromTuple(goal)], factGraph,
None if GROUND_QUERY else [goal[0]])
query = queryLiteral.asSPARQL()
print "Goal to solve ", query
rt = targetGraph.query(query, initNs=nsMap)
if GROUND_QUERY:
self.failUnless(rt.askAnswer[0], "Failed top-down problem")
else:
if (goalDict[goal]) not in rt or DEBUG:
for network, _goal in topDownStore.queryNetworks:
print network, _goal
network.reportConflictSet(True)
for query in topDownStore.edbQueries:
print query.asSPARQL()
print "Missing", goalDict[goal]
self.failUnless((goalDict[goal]) in rt,
"Failed top-down problem")
sTime = time.time() - start
if sTime > 1:
sTimeStr = "%s seconds" % sTime
else:
sTime = sTime * 1000
sTimeStr = "%s milli seconds" % sTime
return sTimeStr
def setupDescriptionLogicProgramming(self,
owlN3Graph,
expanded=[],
addPDSemantics=True,
classifyTBox=False,
constructNetwork=True,
derivedPreds=[],
ignoreNegativeStratus=False,
safety=DATALOG_SAFETY_NONE):
rt = [
rule for rule in MapDLPtoNetwork(
self,
owlN3Graph,
complementExpansions=expanded,
constructNetwork=constructNetwork,
derivedPreds=derivedPreds,
ignoreNegativeStratus=ignoreNegativeStratus,
safety=safety)
]
if ignoreNegativeStratus:
rules, negRules = rt
rules = set(rules)
self.negRules = set(negRules)
else:
rules = set(rt)
if constructNetwork:
self.rules.update(rules)
additionalRules = set(AdditionalRules(owlN3Graph))
if addPDSemantics:
from FuXi.Horn.HornRules import HornFromN3
additionalRules.update(HornFromN3(StringIO(non_DHL_OWL_Semantics)))
if constructNetwork:
for rule in additionalRules:
self.buildNetwork(iter(rule.formula.body),
iter(rule.formula.head), rule)
self.rules.add(rule)
else:
rules.update(additionalRules)
if constructNetwork:
rules = self.rules
# noRules = len(rules)
if classifyTBox:
self.feedFactsToAdd(generateTokenSet(owlN3Graph))
# print("##### DLP rules fired against OWL/RDF TBOX", self)
return rules
def MagicSetTransformation(factGraph,
rules,
GOALS,
derivedPreds=None,
strictCheck=DDL_STRICTNESS_FALLBACK_DERIVED,
noMagic=None,
defaultPredicates=None):
"""
Takes a goal and a ruleset and returns an iterator
over the rulest that corresponds to the magic set
transformation:
"""
noMagic = noMagic and noMagic or []
magicPredicates = set()
replacement = {}
adornedProgram = SetupDDLAndAdornProgram(
factGraph,
rules,
GOALS,
derivedPreds=derivedPreds,
strictCheck=strictCheck,
defaultPredicates=defaultPredicates)
newRules = []
for rule in adornedProgram:
if rule.isSecondOrder():
import warnings
warnings.warn("Second order rule no supported by GMS: %s" % rule,
RuntimeWarning)
magicPositions = {}
#Generate magic rules
for idx, pred in enumerate(iterCondition(rule.formula.body)):
magicBody = []
if isinstance(pred,
AdornedUniTerm): # and pred not in magicPredicates:
# For each rule r in Pad, and for each occurrence of an adorned
# predicate p a in its body, we generate a magic rule defining magic_p a
prevPreds = [
item for _idx, item in enumerate(rule.formula.body)
if _idx < idx
]
if 'b' not in pred.adornment:
import warnings
warnings.warn(
"adorned predicate w/out any bound arguments(%s in %s) !"
% (pred, rule.formula), RuntimeWarning)
if GetOp(pred) not in noMagic:
magicPred = pred.makeMagicPred()
magicPositions[idx] = (magicPred, pred)
inArcs = [(N, x) for (
N,
x) in IncomingSIPArcs(rule.sip, getOccurrenceId(pred))
if not set(x).difference(GetArgs(pred))]
if len(inArcs) > 1:
# If there are several arcs entering qi, we define the magic rule defining magic_qi
# in two steps. First, for each arc Nj --> qi with label cj , we define a rule with head label_qi_j(cj ). The body
# of the rule is the same as the body of the magic rule in the case where there is a single arc
# entering qi (described above). Then the magic rule is defined as follows. The head is
# magic_q(0). The body contains label_qi_j(cj) for all j (that is, for all arcs entering qi ).
#We combine all incoming arcs into a single list of (body) conditions for the magic set
PrettyPrintRule(rule)
SIPRepresentation(rule.sip)
print pred, magicPred
_body = []
additionalRules = []
for idxSip, (N, x) in enumerate(inArcs):
newPred = pred.clone()
SetOp(newPred,
URIRef('%s_label_%s' % (newPred.op, idxSip)))
ruleBody = And(
buildMagicBody(N, prevPreds, rule.formula.head,
derivedPreds))
additionalRules.append(
Rule(Clause(ruleBody, newPred)))
_body.extend(newPred)
# _body.extend(ruleBody)
additionalRules.append(
Rule(Clause(And(_body), magicPred)))
newRules.extend(additionalRules)
for i in additionalRules:
print i
raise NotImplementedError()
else:
for idxSip, (N, x) in enumerate(inArcs):
ruleBody = And(
buildMagicBody(N, prevPreds, rule.formula.head,
derivedPreds, noMagic))
newRule = Rule(Clause(ruleBody, magicPred))
newRules.append(newRule)
magicPredicates.add(magicPred)
#Modify rules
#we modify the original rule by inserting
#occurrences of the magic predicates corresponding
#to the derived predicates of the body and to the head
#If there are no bound arguments in the head, we don't modify the rule
idxIncrement = 0
newRule = copy.deepcopy(rule)
for idx, (magicPred, origPred) in magicPositions.items():
newRule.formula.body.formulae.insert(idx + idxIncrement, magicPred)
idxIncrement += 1
if 'b' in rule.formula.head.adornment and GetOp(
rule.formula.head) not in noMagic:
headMagicPred = rule.formula.head.makeMagicPred()
if isinstance(newRule.formula.body, Uniterm):
newRule.formula.body = And(
[headMagicPred, newRule.formula.body])
else:
newRule.formula.body.formulae.insert(0, headMagicPred)
newRules.append(newRule)
if not newRules:
newRules.extend(AdditionalRules(factGraph))
for rule in newRules:
if rule.formula.body:
yield rule
def MagicOWLProof(self, goals, rules, factGraph, conclusionFile):
progLen = len(rules)
magicRuleNo = 0
dPreds = []
for rule in AdditionalRules(factGraph):
rules.append(rule)
if not GROUND_QUERY and REASONING_STRATEGY != 'gms':
goalDict = dict([((Variable('SUBJECT'), goalP, goalO), goalS)
for goalS, goalP, goalO in goals])
goals = goalDict.keys()
assert goals
if REASONING_STRATEGY == 'gms':
for rule in MagicSetTransformation(factGraph,
rules,
goals,
dPreds):
magicRuleNo += 1
self.network.buildNetworkFromClause(rule)
self.network.rules.add(rule)
if DEBUG:
log.debug("\t", rule)
log.debug("rate of reduction in the size of the program: ",
(100 - (float(magicRuleNo) / float(progLen)) * 100))
if REASONING_STRATEGY in ['bfp', 'sld']: # and not GROUND_QUERY:
reasoningAlg = TOP_DOWN_METHOD if REASONING_STRATEGY == 'sld' \
else BFP_METHOD
topDownStore = TopDownSPARQLEntailingStore(
factGraph.store,
factGraph,
idb=rules,
DEBUG=DEBUG,
nsBindings=nsMap,
decisionProcedure=reasoningAlg,
identifyHybridPredicates=REASONING_STRATEGY == 'bfp')
targetGraph = Graph(topDownStore)
for pref, nsUri in nsMap.items():
targetGraph.bind(pref, nsUri)
start = time.time()
for goal in goals:
queryLiteral = EDBQuery([BuildUnitermFromTuple(goal)],
factGraph,
None if GROUND_QUERY else [goal[0]])
query = queryLiteral.asSPARQL()
log.debug("Goal to solve ", query)
rt = targetGraph.query(query, initNs=nsMap)
if GROUND_QUERY:
self.failUnless(rt.askAnswer[0], "Failed top-down problem")
else:
if (goalDict[goal]) not in rt or DEBUG:
for network, _goal in topDownStore.queryNetworks:
log.debug(network, _goal)
network.reportConflictSet(True)
for query in topDownStore.edbQueries:
log.debug(query.asSPARQL())
self.failUnless((goalDict[goal]) in rt,
"Failed top-down problem")
sTime = time.time() - start
if sTime > 1:
sTimeStr = "%s seconds" % sTime
else:
sTime = sTime * 1000
sTimeStr = "%s ms" % sTime
return sTimeStr
elif REASONING_STRATEGY == 'gms':
for goal in goals:
adornedGoalSeed = AdornLiteral(goal).makeMagicPred()
goal = adornedGoalSeed.toRDFTuple()
if DEBUG:
log.debug("Magic seed fact ", adornedGoalSeed)
factGraph.add(goal)
timing = self.calculateEntailments(factGraph)
for goal in goals:
# self.failUnless(goal in self.network.inferredFacts or goal in factGraph,
# "Failed GMS query")
if goal not in self.network.inferredFacts and goal not in factGraph:
log.debug("missing triple %s" % (pformat(goal)))
# print(list(factGraph.adornedProgram))
# from FuXi.Rete.Util import renderNetwork
# dot = renderNetwork(
# self.network,self.network.nsMap).write_jpeg('test-fail.jpeg')
self.network.reportConflictSet(True)
log.debug("=== Failed: %s ====" % pformat(goal))
else:
log.debug("=== Passed! ===")
return timing