//
// Math.NET Numerics, part of the Math.NET Project
// https://numerics.mathdotnet.com
//
// Copyright (c) 2009-2018 Math.NET
//
// Permission is hereby granted, free of charge, to any person
// obtaining a copy of this software and associated documentation
// files (the "Software"), to deal in the Software without
// restriction, including without limitation the rights to use,
// copy, modify, merge, publish, distribute, sublicense, and/or sell
// copies of the Software, and to permit persons to whom the
// Software is furnished to do so, subject to the following
// conditions:
//
// The above copyright notice and this permission notice shall be
// included in all copies or substantial portions of the Software.
//
// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
// OTHER DEALINGS IN THE SOFTWARE.
//
using System;
using Complex = System.Numerics.Complex;
namespace IStation.Numerics.Providers.FourierTransform.Managed
{
internal partial class ManagedFourierTransformProvider : IFourierTransformProvider
{
///
/// Try to find out whether the provider is available, at least in principle.
/// Verification may still fail if available, but it will certainly fail if unavailable.
///
public bool IsAvailable()
{
return true;
}
///
/// Initialize and verify that the provided is indeed available. If not, fall back to alternatives like the managed provider
///
public void InitializeVerify()
{
}
///
/// Frees memory buffers, caches and handles allocated in or to the provider.
/// Does not unload the provider itself, it is still usable afterwards.
///
public virtual void FreeResources()
{
}
public override string ToString()
{
return "Managed";
}
public void Forward(Complex32[] samples, FourierTransformScaling scaling)
{
if (samples.Length.IsPowerOfTwo())
{
if (samples.Length >= 1024)
{
Radix2ForwardParallel(samples);
}
else
{
Radix2Forward(samples);
}
}
else
{
BluesteinForward(samples);
}
switch (scaling)
{
case FourierTransformScaling.SymmetricScaling:
{
HalfRescale(samples);
break;
}
case FourierTransformScaling.ForwardScaling:
{
FullRescale(samples);
break;
}
}
}
public void Forward(Complex[] samples, FourierTransformScaling scaling)
{
if (samples.Length.IsPowerOfTwo())
{
if (samples.Length >= 1024)
{
Radix2ForwardParallel(samples);
}
else
{
Radix2Forward(samples);
}
}
else
{
BluesteinForward(samples);
}
switch (scaling)
{
case FourierTransformScaling.SymmetricScaling:
{
HalfRescale(samples);
break;
}
case FourierTransformScaling.ForwardScaling:
{
FullRescale(samples);
break;
}
}
}
public void Backward(Complex32[] spectrum, FourierTransformScaling scaling)
{
if (spectrum.Length.IsPowerOfTwo())
{
if (spectrum.Length >= 1024)
{
Radix2InverseParallel(spectrum);
}
else
{
Radix2Inverse(spectrum);
}
}
else
{
BluesteinInverse(spectrum);
}
switch (scaling)
{
case FourierTransformScaling.SymmetricScaling:
{
HalfRescale(spectrum);
break;
}
case FourierTransformScaling.BackwardScaling:
{
FullRescale(spectrum);
break;
}
}
}
public void Backward(Complex[] spectrum, FourierTransformScaling scaling)
{
if (spectrum.Length.IsPowerOfTwo())
{
if (spectrum.Length >= 1024)
{
Radix2InverseParallel(spectrum);
}
else
{
Radix2Inverse(spectrum);
}
}
else
{
BluesteinInverse(spectrum);
}
switch (scaling)
{
case FourierTransformScaling.SymmetricScaling:
{
HalfRescale(spectrum);
break;
}
case FourierTransformScaling.BackwardScaling:
{
FullRescale(spectrum);
break;
}
}
}
public void ForwardReal(float[] samples, int n, FourierTransformScaling scaling)
{
// TODO: backport proper, optimized implementation from Iridium
Complex32[] data = new Complex32[n];
for (int i = 0; i < data.Length; i++)
{
data[i] = new Complex32(samples[i], 0.0f);
}
Forward(data, scaling);
samples[0] = data[0].Real;
samples[1] = 0f;
for (int i = 1, j = 2; i < data.Length / 2; i++)
{
samples[j++] = data[i].Real;
samples[j++] = data[i].Imaginary;
}
if (n.IsEven())
{
samples[n] = data[data.Length / 2].Real;
samples[n + 1] = 0f;
}
else
{
samples[n - 1] = data[data.Length / 2].Real;
samples[n] = data[data.Length / 2].Imaginary;
}
}
public void ForwardReal(double[] samples, int n, FourierTransformScaling scaling)
{
// TODO: backport proper, optimized implementation from Iridium
Complex[] data = new Complex[n];
for (int i = 0; i < data.Length; i++)
{
data[i] = new Complex(samples[i], 0.0);
}
Forward(data, scaling);
samples[0] = data[0].Real;
samples[1] = 0d;
for (int i = 1, j = 2; i < data.Length/2; i++)
{
samples[j++] = data[i].Real;
samples[j++] = data[i].Imaginary;
}
if (n.IsEven())
{
samples[n] = data[data.Length/2].Real;
samples[n+1] = 0d;
}
else
{
samples[n-1] = data[data.Length / 2].Real;
samples[n] = data[data.Length / 2].Imaginary;
}
}
public void BackwardReal(float[] spectrum, int n, FourierTransformScaling scaling)
{
// TODO: backport proper, optimized implementation from Iridium
Complex32[] data = new Complex32[n];
data[0] = new Complex32(spectrum[0], 0f);
for (int i = 1, j = 2; i < data.Length / 2; i++)
{
data[i] = new Complex32(spectrum[j++], spectrum[j++]);
data[data.Length - i] = data[i].Conjugate();
}
if (n.IsEven())
{
data[data.Length / 2] = new Complex32(spectrum[n], 0f);
}
else
{
data[data.Length / 2] = new Complex32(spectrum[n - 1], spectrum[n]);
data[data.Length / 2 + 1] = data[data.Length / 2].Conjugate();
}
Backward(data, scaling);
for (int i = 0; i < data.Length; i++)
{
spectrum[i] = data[i].Real;
}
spectrum[n] = 0f;
}
public void BackwardReal(double[] spectrum, int n, FourierTransformScaling scaling)
{
// TODO: backport proper, optimized implementation from Iridium
Complex[] data = new Complex[n];
data[0] = new Complex(spectrum[0], 0d);
for (int i = 1, j = 2; i < data.Length/2; i++)
{
data[i] = new Complex(spectrum[j++], spectrum[j++]);
data[data.Length - i] = data[i].Conjugate();
}
if (n.IsEven())
{
data[data.Length/2] = new Complex(spectrum[n], 0d);
}
else
{
data[data.Length/2] = new Complex(spectrum[n-1], spectrum[n]);
data[data.Length/2 + 1] = data[data.Length/2].Conjugate();
}
Backward(data, scaling);
for (int i = 0; i < data.Length; i++)
{
spectrum[i] = data[i].Real;
}
spectrum[n] = 0d;
}
public void ForwardMultidim(Complex32[] samples, int[] dimensions, FourierTransformScaling scaling)
{
throw new NotSupportedException();
}
public void ForwardMultidim(Complex[] samples, int[] dimensions, FourierTransformScaling scaling)
{
throw new NotSupportedException();
}
public void BackwardMultidim(Complex32[] spectrum, int[] dimensions, FourierTransformScaling scaling)
{
throw new NotSupportedException();
}
public void BackwardMultidim(Complex[] spectrum, int[] dimensions, FourierTransformScaling scaling)
{
throw new NotSupportedException();
}
///
/// Fully rescale the FFT result.
///
/// Sample Vector.
private static void FullRescale(Complex32[] samples)
{
var scalingFactor = (float)1.0 / samples.Length;
for (int i = 0; i < samples.Length; i++)
{
samples[i] *= scalingFactor;
}
}
///
/// Fully rescale the FFT result.
///
/// Sample Vector.
private static void FullRescale(Complex[] samples)
{
var scalingFactor = 1.0 / samples.Length;
for (int i = 0; i < samples.Length; i++)
{
samples[i] *= scalingFactor;
}
}
///
/// Half rescale the FFT result (e.g. for symmetric transforms).
///
/// Sample Vector.
private static void HalfRescale(Complex32[] samples)
{
var scalingFactor = (float)Math.Sqrt(1.0 / samples.Length);
for (int i = 0; i < samples.Length; i++)
{
samples[i] *= scalingFactor;
}
}
///
/// Fully rescale the FFT result (e.g. for symmetric transforms).
///
/// Sample Vector.
private static void HalfRescale(Complex[] samples)
{
var scalingFactor = Math.Sqrt(1.0 / samples.Length);
for (int i = 0; i < samples.Length; i++)
{
samples[i] *= scalingFactor;
}
}
}
}