Accord.Tests.Statistics.GenericHiddenMarkovModelTest.PredictTest C# (CSharp) Method

        public void PredictTest()
        {
            double[][] sequences = new double[][] 
            {
                new double[] { 0, 3, 1, 2 },
            };


            var hmm = HiddenMarkovModel.CreateGeneric(new Forward(4), 4);

            var teacher = new BaumWelchLearning<GeneralDiscreteDistribution>(hmm)
            {
                Tolerance = 1e-10,
                Iterations = 0
            };
            double ll = teacher.Run(sequences);

            double l11, l12, l13, l14;

            double p1 = hmm.Predict(new double[] { 0 }, out l11);
            double p2 = hmm.Predict(new double[] { 0, 3 }, out l12);
            double p3 = hmm.Predict(new double[] { 0, 3, 1 }, out l13);
            double p4 = hmm.Predict(new double[] { 0, 3, 1, 2 }, out l14);

            Assert.AreEqual(3, p1);
            Assert.AreEqual(1, p2);
            Assert.AreEqual(2, p3);
            Assert.AreEqual(2, p4);

            double l21 = hmm.Evaluate(new double[] { 0, 3 });
            double l22 = hmm.Evaluate(new double[] { 0, 3, 1 });
            double l23 = hmm.Evaluate(new double[] { 0, 3, 1, 2 });
            double l24 = hmm.Evaluate(new double[] { 0, 3, 1, 2, 2 });

            Assert.AreEqual(l11, l21, 1e-10);
            Assert.AreEqual(l12, l22, 1e-10);
            Assert.AreEqual(l13, l23, 1e-10);
            Assert.AreEqual(l14, l24, 1e-2);

            Assert.IsFalse(double.IsNaN(l11));
            Assert.IsFalse(double.IsNaN(l12));
            Assert.IsFalse(double.IsNaN(l13));
            Assert.IsFalse(double.IsNaN(l14));

            Assert.IsFalse(double.IsNaN(l21));
            Assert.IsFalse(double.IsNaN(l22));
            Assert.IsFalse(double.IsNaN(l23));
            Assert.IsFalse(double.IsNaN(l24));

            double ln1;
            double[] pn = hmm.Predict(new double[] { 0 }, 4, out ln1);

            Assert.AreEqual(4, pn.Length);
            Assert.AreEqual(3, pn[0]);
            Assert.AreEqual(1, pn[1]);
            Assert.AreEqual(2, pn[2]);
            Assert.AreEqual(2, pn[3]);

            double ln2 = hmm.Evaluate(new double[] { 0, 3, 1, 2, 2 });

            Assert.AreEqual(ln1, ln2, 1e-2);
            Assert.IsFalse(double.IsNaN(ln1));
            Assert.IsFalse(double.IsNaN(ln2));


            // Get the mixture distribution defining next state likelihoods
            Mixture<GeneralDiscreteDistribution> mixture = null;
            double ml11;
            double mp1 = hmm.Predict(new double[] { 0 }, out ml11, out mixture);

            Assert.AreEqual(l11, ml11);
            Assert.AreEqual(p1, mp1);
            Assert.IsNotNull(mixture);

            Assert.AreEqual(4, mixture.Coefficients.Length);
            Assert.AreEqual(4, mixture.Components.Length);
            Assert.AreEqual(0, mixture.Coefficients[0], 1e-10);
            Assert.AreEqual(1, mixture.Coefficients[1], 1e-10);
            Assert.AreEqual(0, mixture.Coefficients[2], 1e-10);
            Assert.AreEqual(0, mixture.Coefficients[3], 1e-10);

            for (int i = 0; i < mixture.Coefficients.Length; i++)
                Assert.IsFalse(double.IsNaN(mixture.Coefficients[i]));

        }