Reputation: 51
I'm trying to get frequency from iPhone / iPod music library for a spectrum app on iPod library, helping myself with reading-audio-samples-via-avassetreader to get audio samples and then with using-the-apple-fft-and-accelerate-framework and Apple vDSP Samples, but somehow I'm wrong somewhere and unable to calculate the frequency.
So step by step:
Is this the correct way to get frequencies from an iPod mp3 library?
Here is my code:
static COMPLEX_SPLIT A;
static FFTSetup setupReal;
static uint32_t log2n, n, nOver2;
static int32_t stride;
static float *obtainedReal;
static float scale;
+ (void)initialize
{
log2n = 10;
n = 1 << log2n;
stride = 1;
nOver2 = n / 2;
A.realp = (float *) malloc(nOver2 * sizeof(float));
A.imagp = (float *) malloc(nOver2 * sizeof(float));
obtainedReal = (float *) malloc(n * sizeof(float));
setupReal = vDSP_create_fftsetup(log2n, FFT_RADIX2);
}
- (float) performAcceleratedFastFourierTransForAudioBuffer:(AudioBufferList)ioData
{
NSUInteger * sampleIn = (NSUInteger *)ioData.mBuffers[0].mData;
for (int i = 0; i < nOver2; i++) {
double multiplier = 0.5 * (1 - cos(2*M_PI*i/nOver2-1));
A.realp[i] = multiplier * sampleIn[i];
A.imagp[i] = 0;
}
memset(ioData.mBuffers[0].mData, 0, ioData.mBuffers[0].mDataByteSize);
vDSP_fft_zrip(setupReal, &A, stride, log2n, FFT_FORWARD);
vDSP_zvmags(&A, 1, A.realp, 1, nOver2);
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);
int peakIndex = 0;
for (size_t i=1; i < nOver2-1; ++i) {
if ((obtainedReal[i] > obtainedReal[i-1]) && (obtainedReal[i] > obtainedReal[i+1]))
{
peakIndex = i;
break;
}
}
//here I don't know how to calculate frequency with my data
float frequency = obtainedReal[peakIndex-1] / 44100 / n;
vDSP_destroy_fftsetup(setupReal);
free(obtainedReal);
free(A.realp);
free(A.imagp);
return frequency;
}
I got 1.485757
and 1.332233
as my first frequencies
Upvotes: 2
Views: 2347
Reputation: 12975
It looks to me like there is a problem in the conversion to complex input for the FFT. vDSP_ctoz()
splits a buffer where real and imaginary components are interleaved into two buffers, one real and one imaginary. Your input to that function appears to be just real data that has been casted to COMPLEX
. This means that your input buffer to vDSP_ctoz()
is only half as long as it needs to be and some garbage data beyond the buffer size is getting converted.
You either need to create sampleOut
to be 2*n
in length and set every other value (the real parts) or better yet, you can bypass the vDSP_ctoz()
and directly copy your input data into A.realp
and set A.imagp
to zeros. vDSP_ctoz()
should only be needed when interfacing to a source that produces interleaved complex data.
Edit
Ok, I think I was wrong on my first suggestion since the vDSP documentation says that the real input of the real-to-complex in-place fft should be formatted into the split complex format such that imagp
contains even samples and realp
contains the odd samples. I have not actually used the vDSP library, but I am familiar with a lot of other FFT libraries and I missed that detail.
You should be able to find the peaks using A.realp
after the call to vDSP_zvmags(&A, 1, A.realp, 1, nOver2);
At that point, A.realp
should contain the magnitude squared of the FFT output, which is scalar. If you are going to do the scaling, it should be done before the mag2 operation, but it may not be needed if you are just looking for the peaks.
To get the real frequencies represented by the FFT output, use this formula:
F = (i * Fs) / N, i=0,1,...,N/2
where
i
is the index of the FFT output buffer
Fs
is the audio sampling rate
N
is the FFT length
so your calculation might look like this:
float frequency = (peakIndex * 44100) / n;
Keep in mind that vDSP only returns the first half of the input spectrum for real input since the second half is redundant. So the FFT output represents frequencies from 0
to Fs/2
.
One other note is that I don't know if your peak finding algorithm will work very well since FFT output will not be smooth and there will often be a lot of oscillation. You are simply taking the first sample where the two adjacent samples are lower. If you just want to find a single peak, it would be better just to find the max magnitude across the entire output. If you want to find multiple peaks, you will have to do something more sophisticated.
Upvotes: 3