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 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 calculateStratifiedModel(self,database):
"""
Stratified Negation Semantics for DLP using SPARQL to handle the negation
"""
if not self.negRules:
return
from FuXi.DLP.Negation import StratifiedSPARQL
# from FuXi.Rete.Magic import PrettyPrintRule
import copy
noNegFacts = 0
for i in self.negRules:
#Evaluate the Graph pattern, and instanciate the head of the rule with
#the solutions returned
nsMapping = dict([(v,k) for k,v in self.nsMap.items()])
sel,compiler=StratifiedSPARQL(i,nsMapping)
query=compiler.compile(sel)
i.stratifiedQuery=query
vars = sel.projection
unionClosureG = self.closureGraph(database)
for rt in unionClosureG.query(query):
solutions={}
if isinstance(rt,tuple):
solutions.update(dict([(vars[idx],i) for idx,i in enumerate(rt)]))
else:
solutions[vars[0]]=rt
i.solutions=solutions
head=copy.deepcopy(i.formula.head)
head.ground(solutions)
fact=head.toRDFTuple()
self.inferredFacts.add(fact)
self.feedFactsToAdd(generateTokenSet([fact]))
noNegFacts += 1
#Now we need to clear assertions that cross the individual, concept, relation divide
# toRemove=[]
for s,p,o in self.inferredFacts.triples((None,RDF.type,None)):
if s in unionClosureG.predicates() or\
s in [_s for _s,_p,_o in
unionClosureG.triples_choices(
(None,
RDF.type,
[OWL_NS.Class,
OWL_NS.Restriction]))]:
self.inferredFacts.remove((s,p,o))
return noNegFacts
def calculateStratifiedModel(self,database):
"""
Stratified Negation Semantics for DLP using SPARQL to handle the negation
"""
if not self.negRules:
return
from FuXi.DLP.Negation import StratifiedSPARQL
from FuXi.Rete.Magic import PrettyPrintRule
import copy
noNegFacts = 0
for i in self.negRules:
#Evaluate the Graph pattern, and instanciate the head of the rule with
#the solutions returned
nsMapping = dict([(v,k) for k,v in self.nsMap.items()])
sel,compiler=StratifiedSPARQL(i,nsMapping)
query=compiler.compile(sel)
i.stratifiedQuery=query
vars = sel.projection
unionClosureG = self.closureGraph(database)
for rt in unionClosureG.query(query):
solutions={}
if isinstance(rt,tuple):
solutions.update(dict([(vars[idx],i) for idx,i in enumerate(rt)]))
else:
solutions[vars[0]]=rt
i.solutions=solutions
head=copy.deepcopy(i.formula.head)
head.ground(solutions)
fact=head.toRDFTuple()
self.inferredFacts.add(fact)
self.feedFactsToAdd(generateTokenSet([fact]))
noNegFacts += 1
#Now we need to clear assertions that cross the individual, concept, relation divide
toRemove=[]
for s,p,o in self.inferredFacts.triples((None,RDF.type,None)):
if s in unionClosureG.predicates() or\
s in [_s for _s,_p,_o in
unionClosureG.triples_choices(
(None,
RDF.type,
[OWL_NS.Class,
OWL_NS.Restriction]))]:
self.inferredFacts.remove((s,p,o))
return noNegFacts
