Accord.Tests.Statistics.Models.Fields.IndependentMarkovFunctionTest.ComputeTest3 C# (CSharp) Method

        public void ComputeTest3()
        {
            double[][][] sequences2;
            int[] labels2;
            var model = CreateModel3(out sequences2, out labels2);

            var target = new MarkovMultivariateFunction(model);

            var hcrf = new HiddenConditionalRandomField<double[]>(target);


            double actual;
            double expected;

            for (int k = 0; k < 5; k++)
            {
                foreach (var x in sequences2)
                {
                    for (int c = 0; c < model.Classes; c++)
                    {
                        for (int i = 0; i < model[c].States; i++)
                        {
                            // Check initial state transitions
                            double xa = model.Priors[c];
                            double xb = Math.Exp(model[c].Probabilities[i]);
                            double xc = model[c].Emissions[i].ProbabilityDensityFunction(x[0]);
                            expected = xa * xb * xc;
                            actual = Math.Exp(target.Factors[c].Compute(-1, i, x, 0, c));
                            Assert.AreEqual(expected, actual, 1e-6);
                            Assert.IsFalse(double.IsNaN(actual));
                        }

                        for (int t = 1; t < x.Length; t++)
                        {
                            // Check normal state transitions
                            for (int i = 0; i < model[c].States; i++)
                            {
                                for (int j = 0; j < model[c].States; j++)
                                {
                                    double xb = Math.Exp(model[c].Transitions[i, j]);
                                    double xc = model[c].Emissions[j].ProbabilityDensityFunction(x[t]);
                                    expected = xb * xc;
                                    actual = Math.Exp(target.Factors[c].Compute(i, j, x, t, c));
                                    Assert.AreEqual(expected, actual, 1e-6);
                                    Assert.IsFalse(double.IsNaN(actual));
                                }
                            }
                        }

                        actual = Math.Exp(model.LogLikelihood(x, c));
                        expected = Math.Exp(hcrf.LogLikelihood(x, c));
                        Assert.AreEqual(expected, actual, 1e-10);
                        Assert.IsFalse(double.IsNaN(actual));

                        actual = model.Compute(x);
                        expected = hcrf.Compute(x);
                        Assert.AreEqual(expected, actual);
                        Assert.IsFalse(double.IsNaN(actual));
                    }
                }
            }
        }