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70 lines
3.0 KiB
C++
70 lines
3.0 KiB
C++
/*This is a C++ Program to perform 2D FFT. A fast Fourier transform (FFT) is an algorithm to compute the discrete Fourier transform (DFT) and its inverse. Fourier analysis converts time (or space) to frequency and vice versa; an FFT rapidly computes such transformations by factorizing the DFT matrix into a product of sparse (mostly zero) factors.*/
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#include <iostream>
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#include <math.h>
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using namespace std;
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#define PI 3.14159265
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int n;
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int main(int argc, char **argv)
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{
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cout << "Enter the size: ";
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cin >> n;
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double inputData[n][n];
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cout << "Enter the 2D elements ";
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for (int i = 0; i < n; i++)
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for (int j = 0; j < n; j++)
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cin >> inputData[i][j];
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double realOut[n][n];
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double imagOut[n][n];
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double amplitudeOut[n][n];
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int height = n;
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int width = n;
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// Two outer loops iterate on output data.
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for (int yWave = 0; yWave < height; yWave++)
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{
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for (int xWave = 0; xWave < width; xWave++)
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{
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// Two inner loops iterate on input data.
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for (int ySpace = 0; ySpace < height; ySpace++)
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{
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for (int xSpace = 0; xSpace < width; xSpace++)
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{
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// Compute real, imag, and ampltude.
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realOut[yWave][xWave] += (inputData[ySpace][xSpace] * cos(
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2 * PI * ((1.0 * xWave * xSpace / width) + (1.0
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* yWave * ySpace / height)))) / sqrt(
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width * height);
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imagOut[yWave][xWave] -= (inputData[ySpace][xSpace] * sin(
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2 * PI * ((1.0 * xWave * xSpace / width) + (1.0
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* yWave * ySpace / height)))) / sqrt(
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width * height);
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amplitudeOut[yWave][xWave] = sqrt(
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realOut[yWave][xWave] * realOut[yWave][xWave]
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+ imagOut[yWave][xWave]
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* imagOut[yWave][xWave]);
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}
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cout << realOut[yWave][xWave] << " + " << imagOut[yWave][xWave]
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<< " i (" << amplitudeOut[yWave][xWave] << ")\n";
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}
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}
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}
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}
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/*
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Enter the size:
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2
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Enter the 2D elements
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2 3
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4 2
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2.5 + 0.0 i
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5.5 + 0.0 i
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-0.5 + -1.8369701987210297E-16 i
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0.5 + -3.0616169978683826E-16 i
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2.5 + 0.0 i
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-0.5 + -3.6739403974420594E-16 i
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-0.5 + -1.8369701987210297E-16 i
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-1.5 + -1.8369701987210297E-16 i
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