public void SimpleTransform()
{
Complexd[] r1 = Complexd.ToComplexArray(new double[] { 1, 1, 2, 2, 1, 1, 0, 0 });
Complexd[] r2 = Complexd.ToComplexArray(new double[] { 1, 1, 2, 2, 1, 1, 0, 0 });
r2 = BruteForce(r2);
r1 = DFT.Transform(r1, FurierTransformType.Normal);
for (int i = 0; i < r1.Length; i++)
{
Assert.IsTrue(Complexd.NearEqual(r1[i], r2[i]));
}
}
public void FFTAndInverse()
{
double[] x = new double[] { 0, 0.5, 0.84, 1.0, 0.84, 0.5, 0, -0.5, -0.84, -1.0, -0.84, -0.5, 0, 0.5, 0.84, 1 };
Complexd[] r = DFT.Transform(x, FurierTransformType.Normal);
DFT.TransformInPlace(r, FurierTransformType.Inverse);
for (int i = 0; i < x.Length; i++)
{
Assert.IsTrue(MathHelper.NearEqual(r[i].Re, x[i], 0.01));
Assert.IsTrue(MathHelper.NearEqual(r[i].Im, 0.0, 0.01));
}
}
/// <summary>
/// Performs convolution of two inputs.
/// </summary>
/// <param name="f">The first input.</param>
/// <param name="g">The second input.</param>
/// <returns></returns>
public static Complexf[] Convolution([PowerOfTwoArray] Complexf[] f, [PowerOfTwoArray] Complexf[] g)
{
if (f.Length != g.Length)
{
throw new ArgumentException("The data must be the same length.");
}
Complexf[] t1 = DFT.Transform(f, FurierTransformType.Normal);
Complexf[] t2 = DFT.Transform(g, FurierTransformType.Normal);
// We merge inputs.
for (int i = 0; i < f.Length; i++)
{
t1[i] = t1[i] * t2[i];
}
// Backtransform.
DFT.TransformInPlace(t1, FurierTransformType.Inverse);
return(t1);
}