public ICategoricalDistribution forward(ICategoricalDistribution f1_t, ICollection <AssignmentProposition> e_tp1) { ICategoricalDistribution s1 = new ProbabilityTable(f1_t.getFor()); // Set up required working variables IProposition[] props = new IProposition[s1.getFor().Size()]; int i = 0; foreach (IRandomVariable rv in s1.getFor()) { props[i] = new RandVar(rv.getName(), rv.getDomain()); ++i; } IProposition Xtp1 = ProbUtil.constructConjunction(props); AssignmentProposition[] xt = new AssignmentProposition[tToTm1StateVarMap.Size()]; IMap <IRandomVariable, AssignmentProposition> xtVarAssignMap = CollectionFactory.CreateInsertionOrderedMap <IRandomVariable, AssignmentProposition>(); i = 0; foreach (IRandomVariable rv in tToTm1StateVarMap.GetKeys()) { xt[i] = new AssignmentProposition(tToTm1StateVarMap.Get(rv), "<Dummy Value>"); xtVarAssignMap.Put(rv, xt[i]); ++i; } // Step 1: Calculate the 1 time step prediction // ∑<sub>x<sub>t</sub></sub> CategoricalDistributionIterator if1_t = new CategoricalDistributionIteratorImpl(transitionModel, xtVarAssignMap, s1, Xtp1, xt); f1_t.iterateOver(if1_t); // Step 2: multiply by the probability of the evidence // and normalize // <b>P</b>(e<sub>t+1</sub> | X<sub>t+1</sub>) ICategoricalDistribution s2 = sensorModel.posteriorDistribution(ProbUtil .constructConjunction(e_tp1.ToArray()), Xtp1); return(s2.multiplyBy(s1).normalize()); }
public ICategoricalDistribution backward(ICategoricalDistribution b_kp2t, ICollection <AssignmentProposition> e_kp1) { ICategoricalDistribution b_kp1t = new ProbabilityTable(b_kp2t.getFor()); // Set up required working variables IProposition[] props = new IProposition[b_kp1t.getFor().Size()]; int i = 0; foreach (IRandomVariable rv in b_kp1t.getFor()) { IRandomVariable prv = tToTm1StateVarMap.Get(rv); props[i] = new RandVar(prv.getName(), prv.getDomain()); ++i; } IProposition Xk = ProbUtil.constructConjunction(props); AssignmentProposition[] ax_kp1 = new AssignmentProposition[tToTm1StateVarMap.Size()]; IMap <IRandomVariable, AssignmentProposition> x_kp1VarAssignMap = CollectionFactory.CreateInsertionOrderedMap <IRandomVariable, AssignmentProposition>(); i = 0; foreach (IRandomVariable rv in b_kp1t.getFor()) { ax_kp1[i] = new AssignmentProposition(rv, "<Dummy Value>"); x_kp1VarAssignMap.Put(rv, ax_kp1[i]); ++i; } IProposition x_kp1 = ProbUtil.constructConjunction(ax_kp1); props = e_kp1.ToArray(); IProposition pe_kp1 = ProbUtil.constructConjunction(props); // ∑<sub>x<sub>k+1</sub></sub> CategoricalDistributionIterator ib_kp2t = new CategoricalDistributionIteratorImpl2(x_kp1VarAssignMap, sensorModel, transitionModel, b_kp1t, pe_kp1, Xk, x_kp1); b_kp2t.iterateOver(ib_kp2t); return(b_kp1t); }