Accord.Tests.Statistics.GenericHiddenMarkovModelTest2.DecodeTest C# (CSharp) Method

        public void DecodeTest()
        {

            // Create the transition matrix A
            double[,] transitions = 
            {  
                { 0.7, 0.3 },
                { 0.4, 0.6 }
            };

            // Create the vector of emission densities B
            GeneralDiscreteDistribution[] emissions = 
            {  
                new GeneralDiscreteDistribution(0.1, 0.4, 0.5),
                new GeneralDiscreteDistribution(0.6, 0.3, 0.1)
            };

            // Create the initial probabilities pi
            double[] initial =
            {
                0.6, 0.4
            };

            // Create a new hidden Markov model with discrete probabilities
            var hmm = new HiddenMarkovModel<GeneralDiscreteDistribution, double>(transitions, emissions, initial);

            // After that, one could, for example, query the probability
            // of a sequence occurring. We will consider the sequence
            double[] sequence = new double[] { 0, 1, 2 };

            // And now we will evaluate its likelihood
            double logLikelihood = hmm.Evaluate(sequence);

            // At this point, the log-likelihood of the sequence
            // occurring within the model is -3.3928721329161653.

            // We can also get the Viterbi path of the sequence
            int[] path = hmm.Decode(sequence, out logLikelihood);

            // At this point, the state path will be 1-0-0 and the
            // log-likelihood will be -4.3095199438871337

            Assert.AreEqual(logLikelihood, Math.Log(0.01344), 1e-10);
            Assert.AreEqual(path[0], 1);
            Assert.AreEqual(path[1], 0);
            Assert.AreEqual(path[2], 0);
        }