FeatureExtractionModules/FFTExample/FFTExample.cpp

The FFT class computes the Fourier transform of an N dimensional signal using a Fast Fourier Transform algorithm.GRT MIT License Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>

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. The FFT class computes N independent FFTs, one for each dimension in the input signal. The FFT is computed using the previous M samples input to the FFT instance, where M is equal to the FFT Window Size parameter, which is set by the user when they initialize the FFT. The FFT Window Size parameter must be a power of two (16,32,64,128,256,512,1024,2048,4096,etc.). Note that, because of the symmetries within the FFT computation, the results of an FFT will be half the FFT Window Size. This means that if you create an FFT with a Window Size of 256, the resulting vectors that you will get (such as the magnitude and phase) will each have 128 elements in them.

For each N dimensional input signal, the FFT will output:

• An M dimensional vector containing the magnitude of each frequency component
• An M dimensional vector containing the phase of each frequency component where M is equal to the FFTWindowSize / 2 . These values will be concatenated into one vector, in the order of { [magnitude dimension 1] [phase dimension 1] [magnitude dimension 2] [phase dimension 2] ... [magnitude dimension N] [phase dimension N] }. The size of this concatenated output vector will therefore be equal to N * M * 2 - where N is the number of input dimensions to the FFT, M is the FFTWindowSize/2, and 2 represents the magnitude and phase vectors. If you only really need the magnitude or phase of a signal, as opposed to both, then you can turn off the computation and concatenation of the element you do not need to save unnecessary computations and memory copies, this can either be done in the FFT's constructor or by using the setComputeMagnitude(bool computeMagnitude) and setComputePhase(bool computePhase) functions.

/*
 GRT MIT License
 Copyright (c) <2012> <Nicholas Gillian, Media Lab, MIT>
 
 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.
 */

//You might need to set the specific path of the GRT header relative to your project
#include <GRT/GRT.h>
using namespace GRT;
using namespace std;

int main (int argc, const char * argv[])
{
 //Create a new instance of an FFT with a window size of 256 and a hop size of 1
 FFT fft(256,1);
 
 //Create some varaibles to help generate the signal data
 const UINT numSeconds = 10; //The number of seconds of data we want to generate
 double t = 0; //This keeps track of the time
 double tStep = 1.0/1000.0; //This is how much the time will be updated at each iteration in the for loop
 double freq = 100; //Stores the frequency
 
 //Generate the signal and filter the data
 for(UINT i=0; i<numSeconds*1000; i++){
 
 //Generate the signal
 double signal = sin( t * TWO_PI*freq );
 
 //Compute the FFT of the input signal (and the previous buffer data)
 fft.update( signal );
 
 //Update the t
 t += tStep;
 }
 
 //Take the output of the last FFT and save the values to a file
 Vector<FastFourierTransform> fftResults = fft.getFFTResults();
 
 //The input signal is a 1 dimensional signal, so get the magnitude data for dimension 1 (which is at element 0)
 VectorFloat magnitudeData = fftResults[0].getMagnitudeData();
 
 //Write the magnitude data to a file
 cout << "Magnitude Data:\n";
 for(UINT i=0; i<magnitudeData.getSize(); i++){
 cout << magnitudeData[i] << endl;
 }
 
 return EXIT_SUCCESS;
 
}