def DisjunctiveNormalForm(program, safety=DATALOG_SAFETY_NONE, network=None):
for rule in program:
tx_horn_clause = NormalizeClause(rule.formula)
for tx_horn_clause in LloydToporTransformation(tx_horn_clause, True):
if safety in [DATALOG_SAFETY_LOOSE, DATALOG_SAFETY_STRICT]:
rule = Rule(tx_horn_clause,
nsMapping=network and network.nsMap or {})
if not rule.isSafe():
if safety == DATALOG_SAFETY_LOOSE:
warnings.warn("Ignoring unsafe rule (%s)" % rule,
SyntaxWarning, 3)
continue
elif safety == DATALOG_SAFETY_STRICT:
raise SyntaxError("Unsafe RIF Core rule: %s" % rule)
disj = [
i for i in breadth_first(tx_horn_clause.body)
if isinstance(i, Or)
]
if len(disj) > 0:
NormalizeDisjunctions(disj, tx_horn_clause, program, network)
elif isinstance(tx_horn_clause.head, (And, Uniterm)):
# print("No Disjunction in the body")
for hc in ExtendN3Rules(network,
NormalizeClause(tx_horn_clause)):
yield makeRule(hc, network and network.nsMap or {})
def DisjunctiveNormalForm(program, safety=DATALOG_SAFETY_NONE, network=None):
for rule in program:
tx_horn_clause = NormalizeClause(rule.formula)
for tx_horn_clause in LloydToporTransformation(tx_horn_clause, True):
if safety in [DATALOG_SAFETY_LOOSE, DATALOG_SAFETY_STRICT]:
rule = Rule(
tx_horn_clause, nsMapping=network and network.nsMap or {})
if not rule.isSafe():
if safety == DATALOG_SAFETY_LOOSE:
import warnings
warnings.warn("Ignoring unsafe rule (%s)" % rule,
SyntaxWarning,
3)
continue
elif safety == DATALOG_SAFETY_STRICT:
raise SyntaxError("Unsafe RIF Core rule: %s" % rule)
disj = [i for i in breadth_first(
tx_horn_clause.body) if isinstance(i, Or)]
if len(disj) > 0:
NormalizeDisjunctions(disj, tx_horn_clause, program, network)
elif isinstance(tx_horn_clause.head, (And, Uniterm)):
# print("No Disjunction in the body")
for hc in ExtendN3Rules(
network, NormalizeClause(tx_horn_clause)):
yield makeRule(hc, network and network.nsMap or {})
def MapDLPtoNetwork(network,
factGraph,
complementExpansions=[],
constructNetwork=False,
derivedPreds=[],
ignoreNegativeStratus=False,
safety=DATALOG_SAFETY_NONE):
ruleset = set()
negativeStratus = []
for horn_clause in T(factGraph,
complementExpansions=complementExpansions,
derivedPreds=derivedPreds):
# print("## RIF BLD Horn Rules: Before LloydTopor: ##\n", horn_clause)
# print("## RIF BLD Horn Rules: After LloydTopor: ##")
fullReduce = True
for tx_horn_clause in LloydToporTransformation(horn_clause,
fullReduce):
tx_horn_clause = NormalizeClause(tx_horn_clause)
disj = [
i for i in breadth_first(tx_horn_clause.body)
if isinstance(i, Or)
]
if len(disj) > 0:
NormalizeDisjunctions(disj, tx_horn_clause, ruleset, network,
constructNetwork, negativeStratus,
ignoreNegativeStratus)
elif isinstance(tx_horn_clause.head, (And, Uniterm)):
# print("No Disjunction in the body")
for hc in ExtendN3Rules(network,
NormalizeClause(tx_horn_clause),
constructNetwork):
if safety in [DATALOG_SAFETY_LOOSE, DATALOG_SAFETY_STRICT]:
rule = Rule(hc, nsMapping=network.nsMap)
if not rule.isSafe():
if safety == DATALOG_SAFETY_LOOSE:
warnings.warn(
"Ignoring unsafe rule (%s)" % rule,
SyntaxWarning, 3)
continue
elif safety == DATALOG_SAFETY_STRICT:
raise SyntaxError("Unsafe RIF Core rule: %s" %
rule)
_rule = makeRule(hc, network.nsMap)
if _rule.negativeStratus:
negativeStratus.append(_rule)
if _rule is not None and (not _rule.negativeStratus
or not ignoreNegativeStratus):
ruleset.add(_rule)
# Extract free variables anre add rule to ruleset
# print("#######################")
# print("########## Finished Building decision network from DLP ##########")
# renderNetwork(network).write_graphviz('out.dot')
if ignoreNegativeStratus:
return ruleset, negativeStratus
else:
return iter(ruleset)
def MapDLPtoNetwork(network,
factGraph,
complementExpansions=[],
constructNetwork=False,
derivedPreds=[],
ignoreNegativeStratus=False,
safety = DATALOG_SAFETY_NONE):
from FuXi.Rete.SidewaysInformationPassing import GetArgs, iterCondition, GetOp
ruleset=set()
negativeStratus=[]
for horn_clause in T(factGraph,complementExpansions=complementExpansions,derivedPreds=derivedPreds):
# print "## RIF BLD Horn Rules: Before LloydTopor: ##\n",horn_clause
# print "## RIF BLD Horn Rules: After LloydTopor: ##"
fullReduce=True
for tx_horn_clause in LloydToporTransformation(horn_clause,fullReduce):
tx_horn_clause = NormalizeClause(tx_horn_clause)
disj = [i for i in breadth_first(tx_horn_clause.body) if isinstance(i,Or)]
import warnings
if len(disj)>0:
NormalizeDisjunctions(disj,
tx_horn_clause,
ruleset,
network,
constructNetwork,
negativeStratus,
ignoreNegativeStratus)
elif isinstance(tx_horn_clause.head,(And,Uniterm)):
# print "No Disjunction in the body"
for hc in ExtendN3Rules(network,NormalizeClause(tx_horn_clause),constructNetwork):
if safety in [DATALOG_SAFETY_LOOSE, DATALOG_SAFETY_STRICT]:
rule = Rule(hc,nsMapping=network.nsMap)
if not rule.isSafe():
if safety == DATALOG_SAFETY_LOOSE:
import warnings
warnings.warn("Ignoring unsafe rule (%s)"%rule,
SyntaxWarning,
3)
continue
elif safety == DATALOG_SAFETY_STRICT:
raise SyntaxError("Unsafe RIF Core rule: %s"%rule)
_rule=makeRule(hc,network.nsMap)
if _rule.negativeStratus:
negativeStratus.append(_rule)
if _rule is not None and (not _rule.negativeStratus or not ignoreNegativeStratus):
ruleset.add(_rule)
#Extract free variables anre add rule to ruleset
# print "#######################"
# print "########## Finished Building decision network from DLP ##########"
#renderNetwork(network).write_graphviz('out.dot')
if ignoreNegativeStratus:
return ruleset,negativeStratus
else:
return iter(ruleset)
