UPDATE 2016-03-15
Please take a look at this project: https://github.com/ooper-shlab/aurioTouch2.0-Swift. It has been ported to Swift and contains every answer you're looking for, if you cam here.
I did a lot of research and learned a lot about FFT and the Accelerate Framework. But after days of experiments I'm kind of frustrated.
I want to display the frequency spectrum of an audio file during playback in a diagram. For every time interval it should show the magnitude in db on the Y-axis (displayed by a red bar) for every frequency (in my case 512 values) calculated by a FFT on the X-Axis.
The output should look like this:
I fill a buffer with 1024 samples extracting only the left channel for the beginning. Then I do all this FFT stuff.
Here is my code so far:
Setting up some variables
- (void)setupVars
{
maxSamples = 1024;
log2n = log2f(maxSamples);
n = 1 << log2n;
stride = 1;
nOver2 = maxSamples/2;
A.realp = (float *) malloc(nOver2 * sizeof(float));
A.imagp = (float *) malloc(nOver2 * sizeof(float));
memset(A.imagp, 0, nOver2 * sizeof(float));
obtainedReal = (float *) malloc(n * sizeof(float));
originalReal = (float *) malloc(n * sizeof(float));
setupReal = vDSP_create_fftsetup(log2n, FFT_RADIX2);
}
Doing the FFT. FrequencyArray is just a data structure that holds 512 float values.
- (FrequencyArry)performFastFourierTransformForSampleData:(SInt16*)sampleData andSampleRate:(UInt16)sampleRate
{
NSLog(@"log2n %i n %i, nOver2 %i", log2n, n, nOver2);
// n = 1024
// log2n 10
// nOver2 = 512
for (int i = 0; i < n; i++) {
originalReal[i] = (float) sampleData[i];
}
vDSP_ctoz((COMPLEX *) originalReal, 2, &A, 1, nOver2);
vDSP_fft_zrip(setupReal, &A, stride, log2n, FFT_FORWARD);
float scale = (float) 1.0 / (2 * n);
vDSP_vsmul(A.realp, 1, &scale, A.realp, 1, nOver2);
vDSP_vsmul(A.imagp, 1, &scale, A.imagp, 1, nOver2);
vDSP_ztoc(&A, 1, (COMPLEX *) obtainedReal, 2, nOver2);
FrequencyArry frequencyArray;
for (int i = 0; i < nOver2; i++) {
frequencyArray.frequency[i] = log10f(obtainedReal[i]); // Magnitude in db???
}
return frequencyArray;
}
The output looks always kind of weird although it some how seems to move according to the music.
I'm happy that I came so far thanks to some very good posts here like this: Using the apple FFT and accelerate Framework
But now I don't know what to do. What am I missing?
Firstly you're not applying a window function prior to the FFT - this will result in smearing of the spectrum due to spectral leakage.
Secondly, you're just using the real component of the FFT output bins to calculate dB magnitude - you need to use the complex magnitude: