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Last active November 1, 2021 20:28
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A very simple Discrete Fourier Transform algorithm (not suitable for real-time processing)
using System;
using System.Collections.Generic;
using System.Linq;
using System.Text;
namespace SimpleDFT
{
class SimpleDFT
{
static void Main(string[] args)
{
var s = new double[1024];
for(int i=0; i<s.Length; i++)
s[i] = Math.Cos(2 * Math.PI * 1 / 1024 * i);
var d = DFT(s);
double normalizer = 1.0 / s.Length * 2;
for (int i = 0; i < d.Item1.Length; i++)
{
d.Item1[i] = d.Item1[i] * normalizer;
d.Item2[i] = d.Item2[i] * normalizer;
}
var output = IDFT(d.Item1, d.Item2);
}
/// <summary>
/// Provides the Discrete Fourier Transform for a real-valued input signal
/// </summary>
/// <param name="input">the signal to transform</param>
/// <param name="partials">the maximum number of partials to calculate. If not value is given it defaults to input/2</param>
/// <returns>The Cos and Sin components of the signal, respectively</returns>
public static Tuple<double[], double[]> DFT(double[] input, int partials = 0)
{
int len = input.Length;
double[] cosDFT = new double[len / 2 + 1];
double[] sinDFT = new double[len / 2 + 1];
if (partials == 0)
partials = len / 2;
for (int n = 0; n <= partials ; n++)
{
double cos = 0.0;
double sin = 0.0;
for (int i = 0; i < len; i++)
{
cos += input[i] * Math.Cos(2 * Math.PI * n / len * i);
sin += input[i] * Math.Sin(2 * Math.PI * n / len * i);
}
cosDFT[n] = cos;
sinDFT[n] = sin;
}
return new Tuple<double[], double[]>(cosDFT, sinDFT);
}
/// <summary>
/// Takes the real-valued Cos and Sin components of Fourier transformed signal and reconstructs the time-domain signal
/// </summary>
/// <param name="cos">Array of cos components, containing frequency components from 0 to pi. sin.Length must match cos.Length</param>
/// <param name="sin">Array of sin components, containing frequency components from 0 to pi. sin.Length must match cos.Length</param>
/// <param name="len">
/// The length of the output signal.
/// If len < (partials-1)*2 then frequency data will be lost in the output signal.
/// if no len parameter is given it defaults to (partials-1)*2
/// </param>
/// <returns>the real-valued time-domain signal</returns>
public static double[] IDFT(double[] cos, double[] sin, int len = 0)
{
if (cos.Length != sin.Length) throw new ArgumentException("cos.Length and sin.Length bust match!");
if (len == 0)
len = (cos.Length - 1) * 2;
double[] output = new double[len];
int partials = sin.Length;
if (partials > len / 2)
partials = len / 2;
for (int n = 0; n <= partials; n++)
{
for (int i = 0; i < len; i++)
{
output[i] += Math.Cos(2 * Math.PI * n / len * i) * cos[n];
output[i] += Math.Sin(2 * Math.PI * n / len * i) * sin[n];
}
}
return output;
}
}
}

Real-Value Discrete Fourier Transformation in C#

This is a very basic version of a Discrete Fourier Transformation.

Not suitable for real-time analysis

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