Audio Unit Render Block in Swift? - swift

I have written a sample project in Swift to try out the relatively new Core Audio V3 API stuff. Everything seems to work around creating a custom Audio Unit and loading it in process. But the actual audio rendering isn't going so well. I've often read that the rendering code needs to be in C or C++ but I've also heard Swift is fast and thought I could write some minimal audio rendering code in it.
the rendering code
override var internalRenderBlock: AUInternalRenderBlock {
get {
return {
(_ actionFlags: UnsafeMutablePointer<AudioUnitRenderActionFlags>,
_ timeStamp: UnsafePointer<AudioTimeStamp>,
_ frameCount: AUAudioFrameCount,
_ outputBusNumber: Int,
_ bufferList: UnsafeMutablePointer<AudioBufferList>,
_ renderEvent: UnsafePointer<AURenderEvent>?,
_ pull: AudioToolbox.AURenderPullInputBlock?) -> AUAudioUnitStatus in
let bufferList = bufferList.pointee
let theBuffers = bufferList.mBuffers // only one (AudioBuffer) ??
guard let theBufferData = theBuffers.mData?.assumingMemoryBound(to: Float.self) else {
return 1 // come up with better error?
}
let amountFrames = Int(frameCount)
for frame in 0...amountFrames / 2 {
let frame = theBufferData.advanced(by: frame)
frame.pointee = sin(self.phase)
self.phase += 0.0001
}
return noErr
}
}
}
Sounds Bad
The resulting sound is not what I'd expect. My initial thoughts are that Swift is the wrong choice. Yet Interestingly, AudioToolbox does provide a typealias for this AUAudioUnit's rendering property which looks like:
public typealias AUInternalRenderBlock = (UnsafeMutablePointer<AudioUnitRenderActionFlags>, UnsafePointer<AudioTimeStamp>, AUAudioFrameCount, Int, UnsafeMutablePointer<AudioBufferList>, UnsafePointer<AURenderEvent>?, AudioToolbox.AURenderPullInputBlock?) -> AUAudioUnitStatus
This would lead me to believe that it is perhaps possible to write rendering code in Swift.
observed problems
But still, there are a few things going wrong here. (aside from my obvious lack of competency with Swift memory management stuff).
A) despite theBuffers saying that its mNumberOfBuffers is 2, theBuffers winds up not being an array but rather of type (AudioBuffer). I don't understand the need for parenthesis. I can't find a second AudioBuffer.
B) more importantly, when I write a basic sin wave to the one AudioBuffer I can access, the resulting sound is distorted and inconsistent. Could this be Swift's fault? Is it just impossible to write any audio unit rendering code in Swift? Or have a made some assumptions here that is breaking my rendering somehow?
Finally
If it is simply the case that writing this part in Swift is infeasible, then I would like to have some resources on interoperating Swift and C for Audio Unit rendering blocks. So, could the property returning the closure be written in Swift, but the closure's implementation calls down into C? or does the property have to simply return a C function whose prototype matches the closure's type?
Thanks in advance.
The rest of this project can be seen here for context.

The main reason that you were listening a distorted sound was that the phase increment of 0.0001 is too small, which would take 62832 samples to fill up one period of the sine wave -- merely 0.70 hertz! (Assuming your sample rate is 44100)
In addition to the ultra-low-frequency sine wave, you were listening to a sound of about 44100 / 512 = 86.1 Hz, because you were filling only the half of the audio buffer (amountFrames / 2). So the sound was a near-rectangular wave of the period of your audio rendering period, with slowly varying amplitude in about 0.70 Hz.
I could write a working sine wave generator unit based on your code:
override var internalRenderBlock: AUInternalRenderBlock {
return { ( _, _, frameCount, _, bufferList, _, _) in
let srate = Float(self.bus.format.sampleRate)
var phase = self.phase
for buffer in UnsafeMutableAudioBufferListPointer(bufferList) {
phase = self.phase
assert(buffer.mNumberChannels == 1, "interleaved channel not supported")
let frames = buffer.mData!.assumingMemoryBound(to: Float.self)
for i in 0 ..< Int(frameCount) {
frames[i] = sin(phase)
phase += 2 * .pi * 440 / srate // 440 Hz
if phase > 2 * .pi {
phase -= 2 * .pi // to avoid floating point inaccuracy
}
}
}
self.phase = phase
return noErr
}
}
Regarding the observed problem A, the AudioBufferList is a wrapper for variable length C struct, where the first field mNumberBuffers indicates the number of buffers (i.e. number of non-interleaved channels), and the second field is a variable length array:
typedef struct AudioBufferList {
UInt32 mNumberBuffers;
AudioBuffer mBuffers[1];
} AudioBufferList;
The user of this struct, in Objective-C or C++, is expected to allocate mNumberBuffers * sizeof(AudioBuffer) bytes, which is enough for storing multiple mBuffers. Since C does not perform boundary checks on arrays, the users could just write mBuffers[1] or mBuffers[2] to access the second or third buffer.
Because Swift doesn't have this variable length array feature, Apple provides UnsafeMutableAudioBufferListPointer, which can be used like a Swift collection of AudioBuffers; I used this in the outer for loop above.
Finally, I tried not to access self in the innermost loop in the code, because accessing a Swift or Objective-C object might involve unexpected lags, which was the reason why Apple recommends writing rendering loop in C/C++. But for simple cases like this, I would say writing in Swift is a lot easier and the latency is still manageable.

Related

Accessing Float samples of AVAudioPCMBuffer for processing

I am trying to do some computation on the raw PCM samples of a mp3 files I'm playing with an AVAudioEngine graph. I have a closure every 44100 samples that provides an AVAudioPCMBuffer. It has a property channelData of type UnsafePointer<UnsafeMutablePointer<Float>>?. I have not worked with pointers in Swift 3 and so I'm unclear how to access these Float values.
I have the following code but there are many issues:
audioPlayerNode.installTap(onBus: 0,
bufferSize: 1024,
format: audioPlayerNode.outputFormat(forBus: 0)) { (pcmBuffer, time) in
let numChans = Int(pcmBuffer.format.channelCount)
let frameLength = pcmBuffer.frameLength
if let chans = pcmBuffer.floatChannelData?.pointee {
for a in 0..<numChans {
let samples = chans[a]// samples is type Float. should be pointer to Floats.
for b in 0..<flength {
print("sample: \(b)") // should be samples[b] but that gives error as "samples" is Float
}
}
}
For instance, how do I iterate through the UnsafeMutablePointer<Floats which are N float pointers where N is the number of channels in the buffer. I could not find discussion on accessing buffer samples in the Apple Docs on this Class.
I think the main problem is let samples = chans[a]. Xcode says chans is of type UnsafeMutablePointer<Float>. But that should be NumChannels worth of those pointers. Which is why I use a in 0..<numChans to subscript it. Yet I get just Float when I do.
EDIT:
hm, seems using chans.advanced(by: a) instead of subscripting fixed things
Here is what I've found:
let arraySize = Int(buffer.frameLength)
let samples = Array(UnsafeBufferPointer(start: buffer.floatChannelData![0], count:arraySize))
This is assuming buffer is the name of your AVAudioPCMBuffer.
This way you can avoid pointers, which is likely much simpler. Now you can actually search through the data using a for loop.

Why sometimes Apple Accelerate framework is slow?

I am playing with C and Swift 3.0 code using vecLib and Accelerate framework from Apple as dynamic lib + my code in C lang based project and Swift playground.
And in situation with calling Apple's wrapper from framework of SIMD instruction with 1 or < 4 elements computation function like vvcospif() from framework is slower than simple standart cos(x * PI) when functions calls from loop near 1.000 times as example.
I know about difference between vvcospif() and cos(), I should use exactly vvcospif() for x * PI.
Example in playground, you can just copy code and run it:
import Cocoa
import Accelerate
func cosine_interpolate(alpha: Float, a: Float, b: Float) -> Float {
let ft: Float = alpha * 3.1415927;
let f: Float = (1 - cos(ft)) * 0.5;
return a + f*(b - a);
}
var start: Date = NSDate() as Date
var interp: Float;
for index in 0..<1000 {
interp = cosine_interpolate(alpha: 0.25, a: 1.0, b: 0.75)
}
var end = NSDate();
var timeInterval: Double = end.timeIntervalSince(start);
print("cosine_interpolate in \(timeInterval) seconds")
func fast_cosine_interpolate(alpha: Float, a: Float, b: Float) -> Float {
var x: Float = alpha
var count: Int32 = 1
var result: Float = 0
vvcospif(&result, &x, &count)
let SINSIN_HALF_X: Float = (1 - result) * 0.5;
return a + SINSIN_HALF_X * (b - a);
}
start = NSDate() as Date
for index in 0..<1000 {
interp = fast_cosine_interpolate(alpha: 0.25, a: 1.0, b: 0.75)
}
end = NSDate();
timeInterval = end.timeIntervalSince(start);
print("fast_cosine_interpolate in \(timeInterval) seconds")
My question is:
Why vvcospif() is slow in this example?
May be because vvcospif() it is wrapper under Objective-C runtime and converting data structures / copying of memory from Intel SIMD -> Objective-C -> Swift runtime is slower then tiny cos()?
I also have performance issue with C code +
#include <Accelerate/Accelerate.h>
vvcospif(resultVector, inputVector, &count);
when inputVector and resultVector is small arrays with 1 or 2 elements or just float variable, and calls in loop with ~ 1.000.000 times.
cos(x * PI) computation time near 20 ms.
and
vvcospif(x) with processing one float or float array[2] - computation time near 80 ms! Where is Acceleration? :)
Yes, in Xcode I use compiler -O -whole-module-optimization optimisation with whole module opt. enabled.
For a more detailed discussion with examples, see "Introduction to Fast Bezier (and Trying the Accelerate.framework)".
The first, fundamental problem is that non-inlined function calls are extremely expensive. You don't want function calls if you can possibly help it in performance-critical code. Within a module, the compiler can often inline functions for you, and parts of stdlib can be inlined for you. But when you start crossing module barriers, Swift generally cannot optimize out the call.
The point of SIMD functions is that you set up all your data in the right format, and then call them just one time. That way the cost of the function call is made up by the SIMD optimized code you're calling.
But remember, you don't have to call into Accelerate to get SIMD optimizations. The compiler is perfectly capable of noticing you've written a loop and turning it into an inline SIMD algorithm itself (and it does this all the time). So for many simple problems, the compiler is going to win anyway. Think about it: if calling vvcospif with a count of 1 were faster than calling cos, wouldn't they just implement cos that way?
I haven't played with your code much, but if you want to improve its performance with Accelerate, you want to think about how to arrange all your input data so you can call vvcospif one time with a large N. It's quite possible in that case that it will be much faster that a loop (since cos is not trivial).
If you want an example of Accelerate in practice, and how you need to organize your data, see PinchText. This code is computing offsets for a page full of a few thousand glyphs based on up to 10 touches in real-time, with animations (see PinchText.mov for what the result looks like). In particular look at adjustViewPositions:count:forTouchPoint:. Notice how count is large, and the data is transformed step by step with no loops. Even throwing in a (very expensive) ObjC method call into that method doesn't matter very much because it's only made one time. Getting rid of function calls in loops is a huge part of performance programming.

AVAudioPCMBuffer built programmatically, not playing back in stereo

I'm trying to fill an AVAudioPCMBuffer programmatically in Swift to build a metronome. This is the first real app I'm trying to build, so it's also my first audio app. Right now I'm experimenting with different frameworks and methods of getting the metronome looping accurately.
I'm trying to build an AVAudioPCMBuffer with the length of a measure/bar so that I can use the .Loops option of the AVAudioPlayerNode's scheduleBuffer method. I start by loading my file(2 ch, 44100 Hz, Float32, non-inter, *.wav and *.m4a both have same issue) into a buffer, then copying that buffer frame by frame separated by empty frames into the barBuffer. The loop below is how I'm accomplishing this.
If I schedule the original buffer to play, it will play back in stereo, but when I schedule the barBuffer, I only get the left channel. As I said I'm a beginner at programming, and have no experience with audio programming, so this might be my lack of knowledge on 32 bit float channels, or on this data type UnsafePointer<UnsafeMutablePointer<float>>. When I look at the floatChannelData property in swift, the description makes it sound like this should be copying two channels.
var j = 0
for i in 0..<Int(capacity) {
barBuffer.floatChannelData.memory[j] = buffer.floatChannelData.memory[i]
j += 1
}
j += Int(silenceLengthInSamples)
// loop runs 4 times for 4 beats per bar.
edit: I removed the glaring mistake i += 1, thanks to hotpaw2. The right channel is still missing when barBuffer is played back though.
Unsafe pointers in swift are pretty weird to get used to.
floatChannelData.memory[j] only accesses the first channel of data. To access the other channel(s), you have a couple choices:
Using advancedBy
// Where current channel is at 0
// Get a channel pointer aka UnsafePointer<UnsafeMutablePointer<Float>>
let channelN = floatChannelData.advancedBy( channelNumber )
// Get channel data aka UnsafeMutablePointer<Float>
let channelNData = channelN.memory
// Get first two floats of channel channelNumber
let floatOne = channelNData.memory
let floatTwo = channelNData.advancedBy(1).memory
Using Subscript
// Get channel data aka UnsafeMutablePointer<Float>
let channelNData = floatChannelData[ channelNumber ]
// Get first two floats of channel channelNumber
let floatOne = channelNData[0]
let floatTwo = channelNData[1]
Using subscript is much clearer and the step of advancing and then manually
accessing memory is implicit.
For your loop, try accessing all channels of the buffer by doing something like this:
for i in 0..<Int(capacity) {
for n in 0..<Int(buffer.format.channelCount) {
barBuffer.floatChannelData[n][j] = buffer.floatChannelData[n][i]
}
}
Hope this helps!
This looks like a misunderstanding of Swift "for" loops. The Swift "for" loop automatically increments the "i" array index. But you are incrementing it again in the loop body, which means that you end up skipping every other sample (the Right channel) in your initial buffer.

In swift which loop is faster `for` or `for-in`? Why?

Which loop should I use when have to be extremely aware of the time it takes to iterate over a large array.
Short answer
Don’t micro-optimize like this – any difference there is could be far outweighed by the speed of the operation you are performing inside the loop. If you truly think this loop is a performance bottleneck, perhaps you would be better served by using something like the accelerate framework – but only if profiling shows you that effort is truly worth it.
And don’t fight the language. Use for…in unless what you want to achieve cannot be expressed with for…in. These cases are rare. The benefit of for…in is that it’s incredibly hard to get it wrong. That is much more important. Prioritize correctness over speed. Clarity is important. You might even want to skip a for loop entirely and use map or reduce.
Longer Answer
For arrays, if you try them without the fastest compiler optimization, they perform identically, because they essentially do the same thing.
Presumably your for ;; loop looks something like this:
var sum = 0
for var i = 0; i < a.count; ++i {
sum += a[i]
}
and your for…in loop something like this:
for x in a {
sum += x
}
Let’s rewrite the for…in to show what is really going on under the covers:
var g = a.generate()
while let x = g.next() {
sum += x
}
And then let’s rewrite that for what a.generate() returns, and something like what the let is doing:
var g = IndexingGenerator<[Int]>(a)
var wrapped_x = g.next()
while wrapped_x != nil {
let x = wrapped_x!
sum += x
wrapped_x = g.next()
}
Here is what the implementation for IndexingGenerator<[Int]> might look like:
struct IndexingGeneratorArrayOfInt {
private let _seq: [Int]
var _idx: Int = 0
init(_ seq: [Int]) {
_seq = seq
}
mutating func generate() -> Int? {
if _idx != _seq.endIndex {
return _seq[_idx++]
}
else {
return nil
}
}
}
Wow, that’s a lot of code, surely it performs way slower than the regular for ;; loop!
Nope. Because while that might be what it is logically doing, the compiler has a lot of latitude to optimize. For example, note that IndexingGeneratorArrayOfInt is a struct not a class. This means it has no overhead over declaring the two member variables directly. It also means the compiler might be able to inline the code in generate – there is no indirection going on here, no overloaded methods and vtables or objc_MsgSend. Just some simple pointer arithmetic and deferencing. If you strip away all the syntax for the structs and method calls, you’ll find that what the for…in code ends up being is almost exactly the same as what the for ;; loop is doing.
for…in helps avoid performance errors
If, on the other hand, for the code given at the beginning, you switch compiler optimization to the faster setting, for…in appears to blow for ;; away. In some non-scientific tests I ran using XCTestCase.measureBlock, summing a large array of random numbers, it was an order of magnitude faster.
Why? Because of the use of count:
for var i = 0; i < a.count; ++i {
// ^-- calling a.count every time...
sum += a[i]
}
Maybe the optimizer could have fixed this for you, but in this case it hasn’t. If you pull the invariant out, it goes back to being the same as for…in in terms of speed:
let count = a.count
for var i = 0; i < count; ++i {
sum += a[i]
}
“Oh, I would definitely do that every time, so it doesn’t matter”. To which I say, really? Are you sure? Bet you forget sometimes.
But you want the even better news? Doing the same summation with reduce was (in my, again not very scientific, tests) even faster than the for loops:
let sum = a.reduce(0,+)
But it is also so much more expressive and readable (IMO), and allows you to use let to declare your result. Given that this should be your primary goal anyway, the speed is an added bonus. But hopefully the performance will give you an incentive to do it regardless.
This is just for arrays, but what about other collections? Of course this depends on the implementation but there’s a good reason to believe it would be faster for other collections like dictionaries, custom user-defined collections.
My reason for this would be that the author of the collection can implement an optimized version of generate, because they know exactly how the collection is being used. Suppose subscript lookup involves some calculation (such as pointer arithmetic in the case of an array - you have to add multiple the index by the value size then add that to the base pointer). In the case of generate, you know what is being done is to sequentially walk the collection, and therefore you could optimize for this (for example, in the case of an array, hold a pointer to the next element which you increment each time next is called). Same goes for specialized member versions of reduce or map.
This might even be why reduce is performing so well on arrays – who knows (you could stick a breakpoint on the function passed in if you wanted to try and find out). But it’s just another justification for using the language construct you should probably be using regardless.
Famously stated: "We should forget about small efficiencies, say about 97% of the time: premature optimization is the root of all evil" Donald Knuth. It seems unlikely that you are in the %3.
Focus on the bigger problem at hand. After it is working, if it needs a performance boost, then worry about for loops. But I guarantee you, in the end, bigger structural inefficiencies or poor algorithm choice will be the performance problem, not a for loop.
Worrying about for loops is oh so 1960s.
FWIW, a rudimentary playground test shows map() is about 10 times faster than for enumeration:
class SomeClass1 {
let value: UInt32 = arc4random_uniform(100)
}
class SomeClass2 {
let value: UInt32
init(value: UInt32) {
self.value = value
}
}
var someClass1s = [SomeClass1]()
for _ in 0..<1000 {
someClass1s.append(SomeClass1())
}
var someClass2s = [SomeClass2]()
let startTimeInterval1 = CFAbsoluteTimeGetCurrent()
someClass1s.map { someClass2s.append(SomeClass2(value: $0.value)) }
println("Time1: \(CFAbsoluteTimeGetCurrent() - startTimeInterval1)") // "Time1: 0.489435970783234"
var someMoreClass2s = [SomeClass2]()
let startTimeInterval2 = CFAbsoluteTimeGetCurrent()
for item in someClass1s { someMoreClass2s.append(SomeClass2(value: item.value)) }
println("Time2: \(CFAbsoluteTimeGetCurrent() - startTimeInterval2)") // "Time2 : 4.81457495689392"
The for (with a counter) is just incrementing a counter. Very fast. The for-in uses an iterator (call object to pass the next element). This is much slower. But finally you want to access the element in both cases wich will then make no difference in the end.

Help with live-updating sound on the iPhone

My question is a little tricky, and I'm not exactly experienced (I might get some terms wrong), so here goes.
I'm declaring an instance of an object called "Singer". The instance is called "singer1". "singer1" produces an audio signal. Now, the following is the code where the specifics of the audio signal are determined:
OSStatus playbackCallback(void *inRefCon,
AudioUnitRenderActionFlags *ioActionFlags,
const AudioTimeStamp *inTimeStamp,
UInt32 inBusNumber,
UInt32 inNumberFrames,
AudioBufferList *ioData) {
//Singer *me = (Singer *)inRefCon;
static int phase = 0;
for(UInt32 i = 0; i < ioData->mNumberBuffers; i++) {
int samples = ioData->mBuffers[i].mDataByteSize / sizeof(SInt16);
SInt16 values[samples];
float waves;
float volume=.5;
for(int j = 0; j < samples; j++) {
waves = 0;
waves += sin(kWaveform * 600 * phase)*volume;
waves += sin(kWaveform * 400 * phase)*volume;
waves += sin(kWaveform * 200 * phase)*volume;
waves += sin(kWaveform * 100 * phase)*volume;
waves *= 32500 / 4; // <--------- make sure to divide by how many waves you're stacking
values[j] = (SInt16)waves;
values[j] += values[j]<<16;
phase++;
}
memcpy(ioData->mBuffers[i].mData, values, samples * sizeof(SInt16));
}
return noErr;
}
99% of this is borrowed code, so I only have a basic understanding of how it works (I don't know about the OSStatus class or method or whatever this is. However, you see those 4 lines with 600, 400, 200 and 100 in them? Those determine the frequency. Now, what I want to do (for now) is insert my own variable in there in place of a constant, which I can change on a whim. This variable is called "fr1". "fr1" is declared in the header file, but if I try to compile I get an error about "fr1" being undeclared. Currently, my technique to fix this is the following: right beneath where I #import stuff, I add the line
fr1=0.0;//any number will work properly
This sort of works, as the code will compile and singer1.fr1 will actually change values if I tell it to. The problems are now this:A)even though this compiles and the tone specified will play (0.0 is no tone), I get the warnings "Data definition has no type or storage class" and "Type defaults to 'int' in declaration of 'fr1'". I bet this is because for some reason it's not seeing my previous declaration in the header file (as a float). However, again, if I leave this line out the code won't compile because "fr1 is undeclared". B)Just because I change the value of fr1 doesn't mean that singer1 will update the value stored inside the "playbackcallback" variable or whatever is in charge of updating the output buffers. Perhaps this can be fixed by coding differently? C)even if this did work, there is still a noticeable "gap" when pausing/playing the audio, which I need to eliminate. This might mean a complete overhaul of the code so that I can "dynamically" insert new values without disrupting anything. However, the reason I'm going through all this effort to post is because this method does exactly what I want (I can compute a value mathematically and it goes straight to the DAC, which means I can use it in the future to make triangle, square, etc waves easily). I have uploaded Singer.h and .m to pastebin for your veiwing pleasure, perhaps they will help. Sorry, I can't post 2 HTML tags so here are the full links.
(http://pastebin.com/ewhKW2Tk)
(http://pastebin.com/CNAT4gFv)
So, TL;DR, all I really want to do is be able to define the current equation/value of the 4 waves and re-define them very often without a gap in the sound.
Thanks. (And sorry if the post was confusing or got off track, which I'm pretty sure it did.)
My understanding is that your callback function is called every time the buffer needs to be re-filled. So changing fr1..fr4 will alter the waveform, but only when the buffer updates. You shouldn't need to stop and re-start the sound to get a change, but you will notice an abrupt shift in the timbre if you change your fr values. In order to get a smooth transition in timbre, you'd have to implement something that smoothly changes the fr values over time. Tweaking the buffer size will give you some control over how responsive the sound is to your changing fr values.
Your issue with fr being undefined is due to your callback being a straight c function. Your fr variables are declared as objective-c instance variables as part of your Singer object. They are not accessible by default.
take a look at this project, and see how he implements access to his instance variables from within his callback. Basically he passes a reference to his instance to the callback function, and then accesses instance variables through that.
https://github.com/youpy/dowoscillator
notice:
Sinewave *sineObject = inRefCon;
float freq = sineObject.frequency * 2 * M_PI / samplingRate;
and:
AURenderCallbackStruct input;
input.inputProc = RenderCallback;
input.inputProcRefCon = self;
Also, you'll want to move your callback function outside of your #implementation block, because it's not actually part of your Singer object.
You can see this all in action here: https://github.com/coryalder/SineWaver