/// <summary>
/// Initializes a new instance of the Fourier transformer with the given sign and normalization conventions.
/// </summary>
/// <param name="size">The series length of the transformer, which must be positive.</param>
/// <param name="signConvention">The sign convention of the transformer.</param>
/// <param name="normalizationConvention">The normalization convention of the transformer.</param>
public Fourier(int size, FourierSign signConvention, FourierNormalization normalizationConvention)
{
if (size < 1)
throw new YAMPArgumentRangeException("size", 0);
this.size = size;
this.signConvention = signConvention;
this.normalizationConvention = normalizationConvention;
// pre-compute the Nth complex roots of unity
this.roots = Helpers.ComputeRoots(size, +1);
// decompose the size into prime factors
this.factors = Factors(size);
// store a plan for the transform based on the prime factorization
plan = new List<Transformlet>();
foreach (Factor factor in factors)
{
Transformlet t;
switch (factor.Value)
{
// use a radix-specialized transformlet when available
case 2:
t = new RadixTwoTransformlet(size, roots);
break;
case 3:
t = new RadixThreeTransformlet(size, roots);
break;
// eventually, we should make an optimized radix-4 transform
case 5:
t = new RadixFiveTransformlet(size, roots);
break;
case 7:
t = new RadixSevenTransformlet(size, roots);
break;
case 11:
case 13:
// the base transformlet is R^2, but when R is small, this can still be faster than the Bluestein algorithm
// timing measurements appear to indicate that this is the case for radix 11 and 13
// eventually, we should make optimized Winograd transformlets for these factors
t = new Transformlet(factor.Value, size, roots);
break;
default:
// for large factors with no available specialized transformlet, use the Bluestein algorithm
t = new BluesteinTransformlet(factor.Value, size, roots);
break;
}
t.Multiplicity = factor.Multiplicity;
plan.Add(t);
}
}
/// <summary>
/// Initializes a new instance of the Fourier transformer with the given sign and normalization conventions.
/// </summary>
/// <param name="size">The series length of the transformer, which must be positive.</param>
/// <param name="signConvention">The sign convention of the transformer.</param>
/// <param name="normalizationConvention">The normalization convention of the transformer.</param>
/// <remarks>
/// <para>There are multiple conventions for both the sign of the exponent and the overall normalization of
/// Fourier transforms. The default conventions for some widely used software packages are summarized in the following
/// table.</para>
/// <table>
/// <tr><th>Software</th><th>Sign</th><th>Normalization</th></tr>
/// <tr><td>Meta.Numerics</td><td><see cref="FourierSign.Negative"/></td><td><see cref="FourierNormalization.None"/></td></tr>
/// <tr><td>Matlab</td><td><see cref="FourierSign.Negative"/></td><td><see cref="FourierNormalization.None"/></td></tr>
/// <tr><td>Mathmatica</td><td><see cref="FourierSign.Positive"/></td><td><see cref="FourierNormalization.Unitary"/></td></tr>
/// <tr><td>Numerical Recipies</td><td><see cref="FourierSign.Positive"/></td><td><see cref="FourierNormalization.None"/></td></tr>
/// </table>
/// </remarks>
public FourierTransformer(int size, FourierSign signConvention, FourierNormalization normalizationConvention)
{
if (size < 1)
{
throw new ArgumentOutOfRangeException("size");
}
this.size = size;
this.signConvention = signConvention;
this.normalizationConvention = normalizationConvention;
// pre-compute the Nth complex roots of unity
this.roots = FourierAlgorithms.ComputeRoots(size, +1);
// decompose the size into prime factors
this.factors = AdvancedIntegerMath.Factor(size);
// store a plan for the transform based on the prime factorization
plan = new List <Transformlet>();
foreach (Element factor in factors)
{
Transformlet t;
switch (factor.Value)
{
// use a radix-specialized transformlet when available
case 2:
t = new RadixTwoTransformlet(size, roots);
break;
case 3:
t = new RadixThreeTransformlet(size, roots);
break;
// eventually, we should make an optimized radix-4 transform
case 5:
t = new RadixFiveTransformlet(size, roots);
break;
case 7:
t = new RadixSevenTransformlet(size, roots);
break;
case 11:
case 13:
// the base transformlet is R^2, but when R is small, this can still be faster than the Bluestein algorithm
// timing measurements appear to indicate that this is the case for radix 11 and 13
// eventually, we should make optimized Winograd transformlets for these factors
t = new Transformlet(factor.Value, size, roots);
break;
default:
// for large factors with no available specialized transformlet, use the Bluestein algorithm
t = new BluesteinTransformlet(factor.Value, size, roots);
break;
}
t.Multiplicity = factor.Multiplicity;
/*
* if ((factor.Value == 2) && (factor.Multiplicity % 2 == 0)) {
* t = new RadixFourTransformlet(size, roots);
* t.Multiplicity = factor.Multiplicity / 2;
* }
*/
plan.Add(t);
}
}
