mirror of
https://git.naxdy.org/Mirror/Ryujinx.git
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220 lines
7.6 KiB
C#
220 lines
7.6 KiB
C#
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//
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// Copyright (c) 2019-2020 Ryujinx
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//
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// This program is free software: you can redistribute it and/or modify
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// it under the terms of the GNU Lesser General Public License as published by
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// the Free Software Foundation, either version 3 of the License, or
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// (at your option) any later version.
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//
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// This program is distributed in the hope that it will be useful,
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// but WITHOUT ANY WARRANTY; without even the implied warranty of
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// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
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// GNU Lesser General Public License for more details.
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//
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// You should have received a copy of the GNU Lesser General Public License
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// along with this program. If not, see <https://www.gnu.org/licenses/>.
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//
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using Ryujinx.Audio.Renderer.Dsp.State;
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using System;
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using System.Diagnostics;
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using System.Runtime.CompilerServices;
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namespace Ryujinx.Audio.Renderer.Dsp
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{
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public static class AdpcmHelper
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{
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private const int FixedPointPrecision = 11;
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private const int SamplesPerFrame = 14;
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private const int NibblesPerFrame = SamplesPerFrame + 2;
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private const int BytesPerFrame = 8;
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private const int BitsPerFrame = BytesPerFrame * 8;
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static uint GetAdpcmDataSize(int sampleCount)
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{
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Debug.Assert(sampleCount >= 0);
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int frames = sampleCount / SamplesPerFrame;
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int extraSize = 0;
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if ((sampleCount % SamplesPerFrame) != 0)
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{
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extraSize = (sampleCount % SamplesPerFrame) / 2 + 1 + (sampleCount % 2);
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}
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return (uint)(BytesPerFrame * frames + extraSize);
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static int GetAdpcmOffsetFromSampleOffset(int sampleOffset)
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{
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Debug.Assert(sampleOffset >= 0);
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return GetNibblesFromSampleCount(sampleOffset) / 2;
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}
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public static int NibbleToSample(int nibble)
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{
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int frames = nibble / NibblesPerFrame;
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int extraNibbles = nibble % NibblesPerFrame;
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int samples = SamplesPerFrame * frames;
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return samples + extraNibbles - 2;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static int GetNibblesFromSampleCount(int sampleCount)
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{
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byte headerSize = 0;
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if ((sampleCount % SamplesPerFrame) != 0)
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{
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headerSize = 2;
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}
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return sampleCount % SamplesPerFrame + NibblesPerFrame * (sampleCount / SamplesPerFrame) + headerSize;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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private static short Saturate(int value)
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{
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if (value > short.MaxValue)
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value = short.MaxValue;
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if (value < short.MinValue)
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value = short.MinValue;
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return (short)value;
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}
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[MethodImpl(MethodImplOptions.AggressiveInlining)]
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public static int Decode(Span<short> output, ReadOnlySpan<byte> input, int startSampleOffset, int endSampleOffset, int offset, int count, ReadOnlySpan<short> coefficients, ref AdpcmLoopContext loopContext)
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{
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if (input.IsEmpty || endSampleOffset < startSampleOffset)
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{
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return 0;
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}
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byte predScale = (byte)loopContext.PredScale;
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byte scale = (byte)(predScale & 0xF);
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byte coefficientIndex = (byte)((predScale >> 4) & 0xF);
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short history0 = loopContext.History0;
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short history1 = loopContext.History1;
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short coefficient0 = coefficients[coefficientIndex * 2 + 0];
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short coefficient1 = coefficients[coefficientIndex * 2 + 1];
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int decodedCount = Math.Min(count, endSampleOffset - startSampleOffset - offset);
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int nibbles = GetNibblesFromSampleCount(offset + startSampleOffset);
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int remaining = decodedCount;
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int outputBufferIndex = 0;
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int inputIndex = 0;
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ReadOnlySpan<byte> targetInput;
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targetInput = input.Slice(nibbles / 2);
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while (remaining > 0)
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{
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int samplesCount;
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if (((uint)nibbles % NibblesPerFrame) == 0)
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{
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predScale = targetInput[inputIndex++];
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scale = (byte)(predScale & 0xF);
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coefficientIndex = (byte)((predScale >> 4) & 0xF);
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coefficient0 = coefficients[coefficientIndex * 2 + 0];
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coefficient1 = coefficients[coefficientIndex * 2 + 1];
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nibbles += 2;
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samplesCount = Math.Min(remaining, SamplesPerFrame);
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}
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else
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{
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samplesCount = 1;
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}
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int scaleFixedPoint = FixedPointHelper.ToFixed(1.0f, FixedPointPrecision) << scale;
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if (samplesCount < SamplesPerFrame)
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{
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for (int i = 0; i < samplesCount; i++)
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{
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int value = targetInput[inputIndex];
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int sample;
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if ((nibbles & 1) != 0)
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{
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sample = (value << 28) >> 28;
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inputIndex++;
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}
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else
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{
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sample = (value << 24) >> 28;
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}
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nibbles++;
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int prediction = coefficient0 * history0 + coefficient1 * history1;
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sample = FixedPointHelper.RoundUpAndToInt(sample * scaleFixedPoint + prediction, FixedPointPrecision);
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short saturatedSample = Saturate(sample);
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history1 = history0;
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history0 = saturatedSample;
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output[outputBufferIndex++] = saturatedSample;
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remaining--;
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}
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}
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else
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{
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for (int i = 0; i < SamplesPerFrame / 2; i++)
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{
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int value = targetInput[inputIndex];
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int sample0;
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int sample1;
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sample0 = (value << 24) >> 28;
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sample1 = (value << 28) >> 28;
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inputIndex++;
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int prediction0 = coefficient0 * history0 + coefficient1 * history1;
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sample0 = FixedPointHelper.RoundUpAndToInt(sample0 * scaleFixedPoint + prediction0, FixedPointPrecision);
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short saturatedSample0 = Saturate(sample0);
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int prediction1 = coefficient0 * saturatedSample0 + coefficient1 * history0;
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sample1 = FixedPointHelper.RoundUpAndToInt(sample1 * scaleFixedPoint + prediction1, FixedPointPrecision);
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short saturatedSample1 = Saturate(sample1);
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history1 = saturatedSample0;
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history0 = saturatedSample1;
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output[outputBufferIndex++] = saturatedSample0;
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output[outputBufferIndex++] = saturatedSample1;
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}
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nibbles += SamplesPerFrame;
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remaining -= SamplesPerFrame;
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}
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}
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loopContext.PredScale = predScale;
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loopContext.History0 = history0;
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loopContext.History1 = history1;
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return decodedCount;
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}
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}
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}
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