What is the most efficient way of generating a sine wave for a device running IOS. For the purposes of the exercise assume a frequency of 440Hz and a sampling rate of 44100Hz and 1024 samples.
A vanilla C implementation looks something like.
#define SAMPLES 1024
#define TWO_PI (3.14159 * 2)
#define FREQUENCY 440
#define SAMPLING_RATE 44100
int main(int argc, const char * argv[]) {
float samples[SAMPLES];
float phaseIncrement = TWO_PI * FREQUENCY / SAMPLING_RATE;
float currentPhase = 0.0;
for (int i = 0; i < SAMPLES; i ++){
samples[i] = sin(currentPhase);
currentPhase += phaseIncrement;
}
return 0;
}
To take advantage of the Accelerate Framework and the vecLib vvsinf function the loop can be changed to only do the addition.
#define SAMPLES 1024
#define TWO_PI (3.14159 * 2)
#define FREQUENCY 440
#define SAMPLING_RATE 44100
int main(int argc, const char * argv[]) {
float samples[SAMPLES] __attribute__ ((aligned));
float results[SAMPLES] __attribute__ ((aligned));
float phaseIncrement = TWO_PI * FREQUENCY / SAMPLING_RATE;
float currentPhase = 0.0;
for (int i = 0; i < SAMPLES; i ++){
samples[i] = currentPhase;
currentPhase += phaseIncrement;
}
vvsinf(results, samples, SAMPLES);
return 0;
}
But is just applying the vvsinf function as far as I should go in terms of efficiency?
I don't really understand the Accelerate framework well enough to know if I can also replace the loop. Is there a vecLib or vDSP function I can use?
For that matter is it possible to use an entirely different alogrithm to fill a buffer with a sine wave?
If efficiency is required, you could pre-load a 440hz (44100 / 440) sine waveform look-up table and loop around it without further mapping or pre-load a 1hz (44100 / 44100) sine waveform look-up table and loop around by skipping samples to reach 440hz just as you did by incrementing a phase counter. Using look-up tables should be faster than computing sin().
Method A (using 440hz sine waveform):
#define SAMPLES 1024
#define FREQUENCY 440
#define SAMPLING_RATE 44100
#define WAVEFORM_LENGTH (SAMPLING / FREQUENCY)
int main(int argc, const char * argv[]) {
float waveform[WAVEFORM_LENGTH];
LoadSinWaveForm(waveform);
float samples[SAMPLES] __attribute__ ((aligned));
float results[SAMPLES] __attribute__ ((aligned));
for (int i = 0; i < SAMPLES; i ++){
samples[i] = waveform[i % WAVEFORM_LENGTH];
}
vvsinf(results, samples, SAMPLES);
return 0;
}
Method B (using 1hz sine waveform):
#define SAMPLES 1024
#define FREQUENCY 440
#define TWO_PI (3.14159 * 2)
#define SAMPLING_RATE 44100
#define WAVEFORM_LENGTH SAMPLING_RATE // since it's 1hz
int main(int argc, const char * argv[]) {
float waveform[WAVEFORM_LENGTH];
LoadSinWaveForm(waveform);
float samples[SAMPLES] __attribute__ ((aligned));
float results[SAMPLES] __attribute__ ((aligned));
float phaseIncrement = TWO_PI * FREQUENCY / SAMPLING_RATE;
float currentPhase = 0.0;
for (int i = 0; i < SAMPLES; i ++){
samples[i] = waveform[floor(currentPhase) % WAVEFORM_LENGTH];
currentPhase += phaseIncrement;
}
vvsinf(results, samples, SAMPLES);
return 0;
}
Please note that:
Method A is susceptible to frequency inaccuracy due to assuming that your frequency always divides correctly the sampling rate, which is not true. That means you may get 441hz or 440hz with a glitch.
Method B is susceptible to aliasing as the frequency goes up an gets closer to the Nyquist frequency, but it's a good trade-off between performance, quality and memory consumption if synthesizing reasonable low frequencies such as the one in your example.