0
0
Fork 0
mirror of https://github.com/ryujinx-mirror/ryujinx.git synced 2024-12-27 10:05:48 +00:00
ryujinx-fork/Ryujinx.Audio/Renderer/Dsp/AdpcmHelper.cs
Mary-nyan 1825bd87b4
misc: Reformat Ryujinx.Audio with dotnet-format (#3485)
This is the first commit of a series of reformat around the codebase as
discussed internally some weeks ago.

This project being one that isn't touched that much, it shouldn't cause
conflict with any opened PRs.
2022-07-25 15:46:33 -03:00

202 lines
No EOL
6.9 KiB
C#

using Ryujinx.Audio.Renderer.Dsp.State;
using System;
using System.Diagnostics;
using System.Runtime.CompilerServices;
namespace Ryujinx.Audio.Renderer.Dsp
{
public static class AdpcmHelper
{
private const int FixedPointPrecision = 11;
private const int SamplesPerFrame = 14;
private const int NibblesPerFrame = SamplesPerFrame + 2;
private const int BytesPerFrame = 8;
private const int BitsPerFrame = BytesPerFrame * 8;
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static uint GetAdpcmDataSize(int sampleCount)
{
Debug.Assert(sampleCount >= 0);
int frames = sampleCount / SamplesPerFrame;
int extraSize = 0;
if ((sampleCount % SamplesPerFrame) != 0)
{
extraSize = (sampleCount % SamplesPerFrame) / 2 + 1 + (sampleCount % 2);
}
return (uint)(BytesPerFrame * frames + extraSize);
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static int GetAdpcmOffsetFromSampleOffset(int sampleOffset)
{
Debug.Assert(sampleOffset >= 0);
return GetNibblesFromSampleCount(sampleOffset) / 2;
}
public static int NibbleToSample(int nibble)
{
int frames = nibble / NibblesPerFrame;
int extraNibbles = nibble % NibblesPerFrame;
int samples = SamplesPerFrame * frames;
return samples + extraNibbles - 2;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static int GetNibblesFromSampleCount(int sampleCount)
{
byte headerSize = 0;
if ((sampleCount % SamplesPerFrame) != 0)
{
headerSize = 2;
}
return sampleCount % SamplesPerFrame + NibblesPerFrame * (sampleCount / SamplesPerFrame) + headerSize;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
private static short Saturate(int value)
{
if (value > short.MaxValue)
value = short.MaxValue;
if (value < short.MinValue)
value = short.MinValue;
return (short)value;
}
[MethodImpl(MethodImplOptions.AggressiveInlining)]
public static int Decode(Span<short> output, ReadOnlySpan<byte> input, int startSampleOffset, int endSampleOffset, int offset, int count, ReadOnlySpan<short> coefficients, ref AdpcmLoopContext loopContext)
{
if (input.IsEmpty || endSampleOffset < startSampleOffset)
{
return 0;
}
byte predScale = (byte)loopContext.PredScale;
byte scale = (byte)(predScale & 0xF);
byte coefficientIndex = (byte)((predScale >> 4) & 0xF);
short history0 = loopContext.History0;
short history1 = loopContext.History1;
short coefficient0 = coefficients[coefficientIndex * 2 + 0];
short coefficient1 = coefficients[coefficientIndex * 2 + 1];
int decodedCount = Math.Min(count, endSampleOffset - startSampleOffset - offset);
int nibbles = GetNibblesFromSampleCount(offset + startSampleOffset);
int remaining = decodedCount;
int outputBufferIndex = 0;
int inputIndex = 0;
ReadOnlySpan<byte> targetInput;
targetInput = input.Slice(nibbles / 2);
while (remaining > 0)
{
int samplesCount;
if (((uint)nibbles % NibblesPerFrame) == 0)
{
predScale = targetInput[inputIndex++];
scale = (byte)(predScale & 0xF);
coefficientIndex = (byte)((predScale >> 4) & 0xF);
coefficient0 = coefficients[coefficientIndex * 2 + 0];
coefficient1 = coefficients[coefficientIndex * 2 + 1];
nibbles += 2;
samplesCount = Math.Min(remaining, SamplesPerFrame);
}
else
{
samplesCount = 1;
}
int scaleFixedPoint = FixedPointHelper.ToFixed(1.0f, FixedPointPrecision) << scale;
if (samplesCount < SamplesPerFrame)
{
for (int i = 0; i < samplesCount; i++)
{
int value = targetInput[inputIndex];
int sample;
if ((nibbles & 1) != 0)
{
sample = (value << 28) >> 28;
inputIndex++;
}
else
{
sample = (value << 24) >> 28;
}
nibbles++;
int prediction = coefficient0 * history0 + coefficient1 * history1;
sample = FixedPointHelper.RoundUpAndToInt(sample * scaleFixedPoint + prediction, FixedPointPrecision);
short saturatedSample = Saturate(sample);
history1 = history0;
history0 = saturatedSample;
output[outputBufferIndex++] = saturatedSample;
remaining--;
}
}
else
{
for (int i = 0; i < SamplesPerFrame / 2; i++)
{
int value = targetInput[inputIndex];
int sample0;
int sample1;
sample0 = (value << 24) >> 28;
sample1 = (value << 28) >> 28;
inputIndex++;
int prediction0 = coefficient0 * history0 + coefficient1 * history1;
sample0 = FixedPointHelper.RoundUpAndToInt(sample0 * scaleFixedPoint + prediction0, FixedPointPrecision);
short saturatedSample0 = Saturate(sample0);
int prediction1 = coefficient0 * saturatedSample0 + coefficient1 * history0;
sample1 = FixedPointHelper.RoundUpAndToInt(sample1 * scaleFixedPoint + prediction1, FixedPointPrecision);
short saturatedSample1 = Saturate(sample1);
history1 = saturatedSample0;
history0 = saturatedSample1;
output[outputBufferIndex++] = saturatedSample0;
output[outputBufferIndex++] = saturatedSample1;
}
nibbles += SamplesPerFrame;
remaining -= SamplesPerFrame;
}
}
loopContext.PredScale = predScale;
loopContext.History0 = history0;
loopContext.History1 = history1;
return decodedCount;
}
}
}