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98 lines
3.9 KiB
98 lines
3.9 KiB
// <copyright file="DiscreteFourierTransform.Naive.cs" company="Math.NET">
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// Math.NET Numerics, part of the Math.NET Project
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// http://numerics.mathdotnet.com
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// http://github.com/mathnet/mathnet-numerics
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// http://mathnetnumerics.codeplex.com
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//
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// Copyright (c) 2009-2010 Math.NET
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//
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// Permission is hereby granted, free of charge, to any person
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// obtaining a copy of this software and associated documentation
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// files (the "Software"), to deal in the Software without
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// restriction, including without limitation the rights to use,
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// copy, modify, merge, publish, distribute, sublicense, and/or sell
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// copies of the Software, and to permit persons to whom the
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// Software is furnished to do so, subject to the following
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// conditions:
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//
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// The above copyright notice and this permission notice shall be
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// included in all copies or substantial portions of the Software.
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//
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// THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND,
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// EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES
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// OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND
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// NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR COPYRIGHT
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// HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY,
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// WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING
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// FROM, OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR
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// OTHER DEALINGS IN THE SOFTWARE.
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// </copyright>
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namespace MathNet.Numerics.IntegralTransforms.Algorithms
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{
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using System;
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using System.Numerics;
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using Threading;
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/// <summary>
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/// Complex Fast (FFT) Implementation of the Discrete Fourier Transform (DFT).
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/// </summary>
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public partial class DiscreteFourierTransform
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{
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/// <summary>
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/// Naive generic DFT, useful e.g. to verify faster algorithms.
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/// </summary>
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/// <param name="samples">Time-space sample vector.</param>
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/// <param name="exponentSign">Fourier series exponent sign.</param>
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/// <returns>Corresponding frequency-space vector.</returns>
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internal static Complex[] Naive(Complex[] samples, int exponentSign)
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{
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var w0 = exponentSign * Constants.Pi2 / samples.Length;
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var spectrum = new Complex[samples.Length];
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CommonParallel.For(
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0,
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samples.Length,
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index =>
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{
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var wk = w0 * index;
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var sum = Complex.Zero;
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for (var n = 0; n < samples.Length; n++)
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{
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var w = n * wk;
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sum += samples[n] * new Complex(Math.Cos(w), Math.Sin(w));
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}
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spectrum[index] = sum;
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});
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return spectrum;
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}
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/// <summary>
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/// Naive forward DFT, useful e.g. to verify faster algorithms.
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/// </summary>
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/// <param name="timeSpace">Time-space sample vector.</param>
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/// <param name="options">Fourier Transform Convention Options.</param>
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/// <returns>Corresponding frequency-space vector.</returns>
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public Complex[] NaiveForward(Complex[] timeSpace, FourierOptions options)
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{
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var frequencySpace = Naive(timeSpace, SignByOptions(options));
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ForwardScaleByOptions(options, frequencySpace);
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return frequencySpace;
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}
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/// <summary>
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/// Naive inverse DFT, useful e.g. to verify faster algorithms.
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/// </summary>
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/// <param name="frequencySpace">Frequency-space sample vector.</param>
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/// <param name="options">Fourier Transform Convention Options.</param>
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/// <returns>Corresponding time-space vector.</returns>
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public Complex[] NaiveInverse(Complex[] frequencySpace, FourierOptions options)
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{
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var timeSpace = Naive(frequencySpace, -SignByOptions(options));
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InverseScaleByOptions(options, timeSpace);
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return timeSpace;
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}
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}
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}
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