public void HartleyNaiveIsReversible(HartleyOptions options)
{
var samples = Generate.Random(0x80, GetUniform(1));
var work = new double[samples.Length];
samples.CopyTo(work, 0);
work = Hartley.NaiveForward(work, options);
Assert.IsFalse(work.ListAlmostEqual(samples, 6));
work = Hartley.NaiveInverse(work, options);
AssertHelpers.AlmostEqual(samples, work, 12);
}
public void HartleyDefaultNaiveSatisfiesParsevalsTheorem64(int count)
{
var samples = Generate.Random(count, GetUniform(1));
var timeSpaceEnergy = (from s in samples select s * s).Mean();
var spectrum = new double[samples.Length];
samples.CopyTo(spectrum, 0);
spectrum = Hartley.NaiveForward(spectrum, HartleyOptions.Default);
var frequencySpaceEnergy = (from s in spectrum select s * s).Mean();
Assert.AreEqual(timeSpaceEnergy, frequencySpaceEnergy, 1e-12);
}
public void HartleyDefaultNaiveSatisfiesParsevalsTheorem(int count)
{
var samples = Generate.Random(count, GetUniform(1));
var timeSpaceEnergy = (from s in samples select s * s).Mean();
var work = new double[samples.Length];
samples.CopyTo(work, 0);
// Default -> Symmetric Scaling
work = Hartley.NaiveForward(work, HartleyOptions.Default);
var frequencySpaceEnergy = (from s in work select s * s).Mean();
Assert.AreEqual(timeSpaceEnergy, frequencySpaceEnergy, 1e-12);
}
public void NaiveMatchesDft(HartleyOptions hartleyOptions, FourierOptions fourierOptions)
{
var samples = Generate.Random(0x80, GetUniform(1));
VerifyMatchesDft(
samples,
5,
false,
s => Fourier.Forward(s, fourierOptions),
s => Hartley.NaiveForward(s, hartleyOptions));
VerifyMatchesDft(
samples,
5,
true,
s => Fourier.Inverse(s, fourierOptions),
s => Hartley.NaiveInverse(s, hartleyOptions));
}