Method next

libpgm/tablecpdfactorization.py:386–425

(current)

                    
        # define function to create the next instantiation
        def next(current): 
            for node in order:
                # multiply all relevant factors together
                relevantfactors = []
                for factor in self.factorlist:
                    if (factor.scope.count(node) > 0):
                        factorcopy = factor.copy()
                        relevantfactors.append(factorcopy)
                for j in range(1, len(relevantfactors)):
                    relevantfactors[0].multiplyfactor(relevantfactors[j])

                # reduce to leave only the one node
                for othernode in order:
                    if (othernode != node and relevantfactors[0].scope.count(othernode) > 0):
                        relevantfactors[0].reducefactor(othernode, current[othernode])
                
                # renormalize
                summ = 0
                for val in relevantfactors[0].vals:
                    summ += val
                for x in range(len(relevantfactors[0].vals)):
                    relevantfactors[0].vals[x] /= summ
                
                # convert random number
                val = random.random()
                lboundary = 0
                uboundary = 0
                for x in range(len(relevantfactors[0].vals)):
                    uboundary += relevantfactors[0].vals[x]
                    if (lboundary <= val and val < uboundary):
                        rindex = x
                        # print s, val
                        break
                    else:
                        lboundary = uboundary 
                
                # modify result
                current[node] = self.bn.Vdata[node]["vals"][rindex]
   
            return current
                        
        # run next() function n times
        for u in range(n-1):