mathnet-numerics/src/UnitTests/IntegralTransformsTests/HartleyTest.cs

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namespace MathNet.Numerics.UnitTests.IntegralTransformsTests
{
    using System;
    using Distributions;
    using IntegralTransforms;
    using IntegralTransforms.Algorithms;
    using MbUnit.Framework;
    using Sampling;

    [TestFixture]
    public class HartleyTest
    {
        private IContinuousDistribution _uniform = new ContinuousUniform(-1, 1);

        private static void VerifyMatchesDFT(
            double[] samples,
            double maximumError,
            bool inverse,
            Action<Complex[]> dft,
            Func<double[], double[]> hartley)
        {
            var hartleyReal = hartley(samples);

            var fourierComplex = Array.ConvertAll(samples, s => new Complex(s, inverse ? -s : s));
            dft(fourierComplex);
            var fourierReal = Array.ConvertAll(fourierComplex, s => s.Real);

            AssertHelpers.AlmostEqualList(fourierReal, hartleyReal, maximumError);
        }

        [Test]
        [Row(HartleyOptions.Default, FourierOptions.Default)]
        [Row(HartleyOptions.AsymmetricScaling, FourierOptions.AsymmetricScaling)]
        [Row(HartleyOptions.NoScaling, FourierOptions.NoScaling)]
        public void NaiveMatchesDFT(HartleyOptions hartleyOptions, FourierOptions fourierOptions)
        {
            var dht = new DiscreteHartleyTransform();
            var samples = Sample.Random(x => x, _uniform, 0x80);

            VerifyMatchesDFT(
                samples,
                1e-10,
                false,
                s => Transform.FourierForward(s, fourierOptions),
                s => dht.NaiveForward(s, hartleyOptions));

            VerifyMatchesDFT(
                samples,
                1e-10,
                true,
                s => Transform.FourierInverse(s, fourierOptions),
                s => dht.NaiveInverse(s, hartleyOptions));
        }
    }
}