Likelihood Weighting

cdef extern from "dbrv.h":
	char dbrv__setup(DBRV *self, char *connectionString);
	char dbrv__logP(DBRV *self, char *nodeName, PyObject *parentValues, double *prob);
	char dbrv__randomSample(DBRV *self, char *nodeName, PyObject *parentValues, unsigned int *sample);
	char dbrv__tearDown(DBRV *self);
 
 
cdef class NodeSample:
	cdef node
	cdef int stateIndex
	cdef list states
	cdef list isSet
	cdef list parents
 
 
cdef class LikelihoodWeighting:
	cdef list __orderedNodes
	cdef size_t __numSample
 
	def __init__(self, orderedNodes, numSamples):
		self.__orderedNodes = orderedNodes
		self.__numSamples = numSamples
 
	cdef __randomSample(self, NodeSample nodeSample):
		print("Call to LikelihoodWeighting.__likelihoodWeighting()")
 
	cdef double __lwSample(self, NodeSample nodeSample, ev, sampleIndex):
		cdef node
		node = nodeSample.node
 
		# Check if already set
		if nodeSample.isSet[sampleIndex]:
			return 0
 
		# Check if evidence
		if node in ev:
			# TODO Working with state indexes here.  Is that right?
			nodeSample.stateIndex = ev[node]
			nodeSample.isSet[sampleIndex] = True
			# Calculate log[P(x|y,z)]
			# Remember that frequencies are listed frequency + 1
			# *****
			return 0.5
 
		# Sample ancestors before sampling present node
		for parent in bnodeSample.parents:
			self.__lwSample(parent, ev, sampleIndex)
		self.__randomSample(nodeSample)
		return 0
 
	cdef __likelihoodWeighting(self, evidence):
		for nodeSample in self.__orderedNodes:
			for i from 0 <= i < self.__numSamples:
				self.__lwSample(nodeSample, evidence, i)