def __init__(self, lnode, rnode):
from builtins import builtinp
self.lnode = lnode
self.rnode = rnode
#####Make this opaque
if isinstance(lnode, BetaNode):
self.lvars = lnode.pattern
elif isinstance(lnode, AlphaNode):
self.lvars = lnode.vars
self.rvars = rnode.vars
# Detect builtins
if isinstance(rnode, AlphaNode):
if builtinp(self.rnode):
self.svars = lnode.svars
else:
# store svars in lexical order
self.svars = [v for v in self.lvars if v in self.rvars]
else:
self.svars = [v for v in self.lvars if v in self.rvars]
sortVars(self.svars) #destructively sort vars
self.parents = list()
self.children = list()
self.pattern = removedups(self.svars + self.lvars + self.rvars)
# Redundant var, will be refactored out
self.vars = self.pattern
self.builtinInput = None
self.ind = Memory()
self.inferredFacts = Set()
# a pointer to the rule node (which contains the rhs)
self.rule = None
def makeBetaNetwork(self, rule, betaNode, alphaNodeList):
"""I have more than 2 alpha nodes and so I make a network"""
length = len(alphaNodeList)
if length == 0:
betaNode.rule = self.makeRuleNode(rule)
betaNode.rule.betaNode = betaNode
else:
alpha = alphaNodeList[0]
betaChild = self.makeBetaNode(betaNode, alpha)
# connect our newly created BetaNode to its parent BetaNode,
# and connect the parent to its child
betaChild.parents = [betaNode]
betaNode.children = [betaChild]
sharedJoinVars = self.getSharedVars(betaNode, alpha)
sortVars(sharedJoinVars)
if not builtinp(alpha):
# adjust our beta node shared variables
betaNode.svars = sharedJoinVars
# Our betanode has children, and so set up our
# pattern in an order that is conducive to the children JOINs
betaNode.pattern = removedups(sharedJoinVars + betaNode.pattern)
# connect our AlphaNode to its relevant BetaNode
alpha.betaNodes = [betaChild]
self.rete.betaNodeStore.addNode(betaNode)
self.rete.betaNodeStore.addNode(betaChild)
alphaNodeList = alphaNodeList[1:]
return self.makeBetaNetwork(rule, betaChild, alphaNodeList)
def makeBetaNetwork(self, rule, betaNode, alphaNodeList):
"""I have more than 2 alpha nodes and so I make a network"""
length = len(alphaNodeList)
if length == 0:
betaNode.rule = self.makeRuleNode(rule)
betaNode.rule.betaNode = betaNode
else:
alpha = alphaNodeList[0]
betaChild = self.makeBetaNode(betaNode, alpha)
# connect our newly created BetaNode to its parent BetaNode,
# and connect the parent to its child
betaChild.parents = [betaNode]
betaNode.children = [betaChild]
sharedJoinVars = self.getSharedVars(betaNode, alpha)
sortVars(sharedJoinVars)
if not builtinp(alpha):
# adjust our beta node shared variables
betaNode.svars = sharedJoinVars
# Our betanode has children, and so set up our
# pattern in an order that is conducive to the children JOINs
betaNode.pattern = removedups(sharedJoinVars +
betaNode.pattern)
# connect our AlphaNode to its relevant BetaNode
alpha.betaNodes = [betaChild]
self.rete.betaNodeStore.addNode(betaNode)
self.rete.betaNodeStore.addNode(betaChild)
alphaNodeList = alphaNodeList[1:]
return self.makeBetaNetwork(rule, betaChild, alphaNodeList)
def __init__(self, lnode, rnode):
from builtins import builtinp
self.lnode = lnode
self.rnode = rnode
#####Make this opaque
if isinstance(lnode, BetaNode):
self.lvars = lnode.pattern
elif isinstance(lnode, AlphaNode):
self.lvars = lnode.vars
self.rvars = rnode.vars
# Detect builtins
if isinstance(rnode, AlphaNode):
if builtinp(self.rnode):
self.svars = lnode.svars
else:
# store svars in lexical order
self.svars = [v for v in self.lvars if v in self.rvars]
else:
self.svars = [v for v in self.lvars if v in self.rvars]
sortVars(self.svars) #destructively sort vars
self.parents = list()
self.children = list()
self.pattern = removedups(self.svars + self.lvars + self.rvars)
# Redundant var, will be refactored out
self.vars = self.pattern
self.builtinInput = None
self.ind = Memory()
self.inferredFacts = Set()
# a pointer to the rule node (which contains the rhs)
self.rule = None
def __init__(self, pattern):
self.pattern = pattern
#print "pattern", pattern
self.ind = Memory() ###ind=memory, or ind=index
self.betaNodes = list()
self.vars = [v for v in pattern if isinstance(v, Variable)]
sortVars(self.vars)
self.svars = list()
self.dependents = list()
self.dependsOn = list()
def __init__(self, pattern):
self.pattern = pattern
#print "pattern", pattern
self.ind = Memory() ###ind=memory, or ind=index
self.betaNodes = list()
self.vars = [v for v in pattern if isinstance(v, Variable)]
sortVars(self.vars)
self.svars = list()
self.dependents = list()
self.dependsOn = list()
def makeBetaNode(self, node1, node2, futureJoins=True):
sharedVars = self.getSharedVars(node1, node2)
# if our left input is an alpha node, then it has the same shared
# variables as our right input
if isinstance(node1, AlphaNode):
node1.svars = sharedVars
sortVars(node1.svars)
node2.svars = sharedVars
sortVars(node2.svars)
# make new BetaNode
b = BetaNode(node1, node2)
# store the shared variables in our new BetaNode
# the shared vars here will be reset if the beta node has beta children
b.svars = sharedVars
# just add the beta node to the index (which is a flat list), no indexing for now
return b
def makeBetaNode(self, node1, node2, futureJoins=True):
sharedVars = self.getSharedVars(node1, node2)
# if our left input is an alpha node, then it has the same shared
# variables as our right input
if isinstance(node1, AlphaNode):
node1.svars = sharedVars
sortVars(node1.svars)
node2.svars = sharedVars
sortVars(node2.svars)
# make new BetaNode
b = BetaNode(node1, node2)
# store the shared variables in our new BetaNode
# the shared vars here will be reset if the beta node has beta children
b.svars = sharedVars
# just add the beta node to the index (which is a flat list), no indexing for now
return b
