def test(self,debug=debug):
print testName, label
query = urlopen(queryFile).read()
factGraph = Graph().parse(urlopen(rdfDoc),format='n3')
factGraph.parse(open('SPARQL/W3C/rdfs-axiomatic-triples.n3'),format='n3')
self.rules.extend(self.network.setupDescriptionLogicProgramming(
factGraph,
addPDSemantics=True,
constructNetwork=False))
if debug:
pprint(list(self.rules))
topDownStore=TopDownSPARQLEntailingStore(
factGraph.store,
factGraph,
idb=self.rules,
DEBUG=debug,
nsBindings=nsMap,
decisionProcedure = BFP_METHOD,
identifyHybridPredicates = True,
templateMap={
STRING.contains : "REGEX(%s,%s)"
})
targetGraph = Graph(topDownStore)
parsedQuery=parse(query)
for pref,nsUri in (setdict(nsMap) | setdict(
parsedQuery.prolog.prefixBindings)).items():
targetGraph.bind(pref,nsUri)
# rt=targetGraph.query('',parsedQuery=parsedQuery)
actualSolns=[ImmutableDict([(k,v)
for k,v in d.items()])
for d in parseResults(
targetGraph.query(query).serialize(
format='xml'))]
expectedSolns=[ImmutableDict([(k,v)
for k,v in d.items()])
for d in parseResults(urlopen(result).read())]
actualSolns.sort(key=lambda d:hash(d))
expectedSolns.sort(key=lambda d:hash(d))
self.failUnless(set(actualSolns) == set(expectedSolns),
"Answers don't match %s v.s. %s"%(actualSolns,
expectedSolns)
)
if debug:
for network,goal in topDownStore.queryNetworks:
pprint(goal)
network.reportConflictSet(True)
def test(self, debug=debug):
if debug:
print testName, label, named_graphs
query = urlopen(queryFile).read()
try:
parsedQuery = parse(query)
except ParseException:
return
assertion = BNode()
result_node = BNode()
test_graph.add((result_node, RDF.type, EARL.TestResult))
test_graph.add(
(result_node, DC['date'], Literal(datetime.date.today())))
test_graph.add((assertion, RDF.type, EARL.Assertion))
test_graph.add((assertion, EARL.assertedBy, MY_FOAF.chime))
test_graph.add((assertion, EARL.subject,
URIRef('http://metacognition.info/software/fuxi')))
test_graph.add((assertion, EARL.test, TEST[testName]))
test_graph.add((assertion, EARL.result, result_node))
if named_graphs:
g = ConjunctiveGraph()
else:
g = Graph()
if debug:
print "Source graph ", rdfDoc
g.parse(urlopen(rdfDoc), publicID=rdfDoc, format='n3')
for sourceUri, graphIri in named_graphs:
g.parse(urlopen(sourceUri), publicID=graphIri, format='n3')
if named_graphs:
factGraph = Graph(g.store, identifier=rdfDoc)
else:
factGraph = g
if ENT.RIF in regime:
rules = []
else:
from FuXi.DLP.CompletionReasoning import GetELHConsequenceProcedureRules
rules = [i for i in self.rdfs_rules] if ENT.RDFS in regime else []
rules.extend(
self.network.setupDescriptionLogicProgramming(
factGraph, addPDSemantics=True, constructNetwork=False))
if query.find('subClassOf') + 1 and (ENT.RDFS not in regime or
testName in COMPLETION_RULES):
if debug:
print "Added completion rules for EL TBox reasoning"
rules.extend(GetELHConsequenceProcedureRules(factGraph))
facts2add = []
for owl_class in factGraph.subjects(RDF.type, OWLNS.Class):
facts2add.append(
(owl_class, RDFS.subClassOf, owl_class, factGraph))
factGraph.addN(facts2add)
if debug:
pprint(list(rules))
if debug:
print query
topDownStore = TopDownSPARQLEntailingStore(
factGraph.store,
factGraph,
idb=rules,
DEBUG=debug,
nsBindings=nsMap,
#hybridPredicates = [RDFS.subClassOf],
identifyHybridPredicates=True,
templateMap={STRING.contains: "REGEX(%s,%s)"})
targetGraph = Graph(topDownStore)
for pref, nsUri in (setdict(nsMap) | setdict(
parsedQuery.prolog.prefixBindings)).items():
targetGraph.bind(pref, nsUri)
rt = targetGraph.query('', parsedQuery=parsedQuery)
if rt.askAnswer:
actualSolns = rt.askAnswer[0]
expectedSolns = parseResults(urlopen(result).read())
else:
actualSolns = [
ImmutableDict([(k, v) for k, v in d.items()])
for d in parseResults(rt.serialize(format='xml'))
]
expectedSolns = [
ImmutableDict([(k, v) for k, v in d.items()])
for d in parseResults(urlopen(result).read())
]
actualSolns.sort(key=lambda d: hash(d))
expectedSolns.sort(key=lambda d: hash(d))
actualSolns = set(actualSolns)
expectedSolns = set(expectedSolns)
if actualSolns == expectedSolns:
test_graph.add((result_node, EARL.outcome, EARL['pass']))
else:
test_graph.add((result_node, EARL.outcome, EARL['fail']))
self.failUnless(
actualSolns == expectedSolns,
"Answers don't match %s v.s. %s" % (actualSolns, expectedSolns))
if debug:
for network, goal in topDownStore.queryNetworks:
pprint(goal)
network.reportConflictSet(True)
def test(self,debug=debug):
if debug:
print testName, label, named_graphs
query = urlopen(queryFile).read()
try:
parsedQuery=parse(query)
except ParseException:
return
assertion = BNode()
result_node = BNode()
test_graph.add((result_node,RDF.type,EARL.TestResult))
test_graph.add((result_node,DC['date'],Literal(datetime.date.today())))
test_graph.add((assertion,RDF.type,EARL.Assertion))
test_graph.add((assertion,EARL.assertedBy,MY_FOAF.chime))
test_graph.add((assertion,
EARL.subject,
URIRef('http://metacognition.info/software/fuxi')))
test_graph.add((assertion,EARL.test,TEST[testName]))
test_graph.add((assertion,EARL.result,result_node))
if named_graphs:
g = ConjunctiveGraph()
else:
g = Graph()
if debug:
print "Source graph ", rdfDoc
g.parse(
urlopen(rdfDoc),
publicID=rdfDoc,
format='n3')
for sourceUri, graphIri in named_graphs:
g.parse(
urlopen(sourceUri),
publicID=graphIri,
format='n3')
if named_graphs:
factGraph = Graph(g.store,identifier=rdfDoc)
else:
factGraph = g
if ENT.RIF in regime:
rules = []
else:
from FuXi.DLP.CompletionReasoning import GetELHConsequenceProcedureRules
rules = [
i for i in self.rdfs_rules
] if ENT.RDFS in regime else []
rules.extend(self.network.setupDescriptionLogicProgramming(
factGraph,
addPDSemantics=True,
constructNetwork=False))
if query.find('subClassOf')+1 and (
ENT.RDFS not in regime or
testName in COMPLETION_RULES
):
if debug:
print "Added completion rules for EL TBox reasoning"
rules.extend(GetELHConsequenceProcedureRules(factGraph))
facts2add = []
for owl_class in factGraph.subjects(RDF.type,OWLNS.Class):
facts2add.append(
(owl_class,RDFS.subClassOf,owl_class,factGraph)
)
factGraph.addN(facts2add)
if debug:
pprint(list(rules))
if debug:
print query
topDownStore=TopDownSPARQLEntailingStore(
factGraph.store,
factGraph,
idb=rules,
DEBUG=debug,
nsBindings=nsMap,
#hybridPredicates = [RDFS.subClassOf],
identifyHybridPredicates = True,
templateMap={
STRING.contains : "REGEX(%s,%s)"
})
targetGraph = Graph(topDownStore)
for pref,nsUri in (setdict(nsMap) | setdict(
parsedQuery.prolog.prefixBindings)).items():
targetGraph.bind(pref,nsUri)
rt=targetGraph.query('',parsedQuery=parsedQuery)
if rt.askAnswer:
actualSolns = rt.askAnswer[0]
expectedSolns = parseResults(urlopen(result).read())
else:
actualSolns=[ImmutableDict([(k,v)
for k,v in d.items()])
for d in parseResults(rt.serialize(format='xml'))]
expectedSolns=[ImmutableDict([(k,v)
for k,v in d.items()])
for d in parseResults(urlopen(result).read())]
actualSolns.sort(key=lambda d:hash(d))
expectedSolns.sort(key=lambda d:hash(d))
actualSolns = set(actualSolns)
expectedSolns = set(expectedSolns)
if actualSolns == expectedSolns:
test_graph.add((result_node,EARL.outcome,EARL['pass']))
else:
test_graph.add((result_node,EARL.outcome,EARL['fail']))
self.failUnless(actualSolns == expectedSolns,
"Answers don't match %s v.s. %s"%(actualSolns,
expectedSolns)
)
if debug:
for network,goal in topDownStore.queryNetworks:
pprint(goal)
network.reportConflictSet(True)
