Math.NET Numerics
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// <copyright file="DiscreteFourierTransform.Naive.cs" company="Math.NET">
// Math.NET Numerics, part of the Math.NET Project
// http://numerics.mathdotnet.com
// http://github.com/mathnet/mathnet-numerics
// http://mathnetnumerics.codeplex.com
//
// Copyright (c) 2009-2010 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,
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// OTHER DEALINGS IN THE SOFTWARE.
// </copyright>
namespace MathNet.Numerics.IntegralTransforms.Algorithms
{
using System;
using System.Numerics;
using Threading;
/// <summary>
/// Complex Fast (FFT) Implementation of the Discrete Fourier Transform (DFT).
/// </summary>
public partial class DiscreteFourierTransform
{
/// <summary>
/// Naive generic DFT, useful e.g. to verify faster algorithms.
/// </summary>
/// <param name="samples">Time-space sample vector.</param>
/// <param name="exponentSign">Fourier series exponent sign.</param>
/// <returns>Corresponding frequency-space vector.</returns>
internal static Complex[] Naive(Complex[] samples, int exponentSign)
{
var w0 = exponentSign * Constants.Pi2 / samples.Length;
var spectrum = new Complex[samples.Length];
CommonParallel.For(
0,
samples.Length,
index =>
{
var wk = w0 * index;
var sum = Complex.Zero;
for (var n = 0; n < samples.Length; n++)
{
var w = n * wk;
sum += samples[n] * new Complex(Math.Cos(w), Math.Sin(w));
}
spectrum[index] = sum;
});
return spectrum;
}
/// <summary>
/// Naive forward DFT, useful e.g. to verify faster algorithms.
/// </summary>
/// <param name="timeSpace">Time-space sample vector.</param>
/// <param name="options">Fourier Transform Convention Options.</param>
/// <returns>Corresponding frequency-space vector.</returns>
public Complex[] NaiveForward(Complex[] timeSpace, FourierOptions options)
{
var frequencySpace = Naive(timeSpace, SignByOptions(options));
ForwardScaleByOptions(options, frequencySpace);
return frequencySpace;
}
/// <summary>
/// Naive inverse DFT, useful e.g. to verify faster algorithms.
/// </summary>
/// <param name="frequencySpace">Frequency-space sample vector.</param>
/// <param name="options">Fourier Transform Convention Options.</param>
/// <returns>Corresponding time-space vector.</returns>
public Complex[] NaiveInverse(Complex[] frequencySpace, FourierOptions options)
{
var timeSpace = Naive(frequencySpace, -SignByOptions(options));
InverseScaleByOptions(options, timeSpace);
return timeSpace;
}
}
}