kcat
/
openal-soft
1
0
Fork 0
Code Issues Pull Requests Packages Projects Releases Wiki Activity

Upsample the reverb output as needed

master
Chris Robinson 2022-08-27 21:04:51 -07:00
parent b8d73a226a
commit 0891f1342d
1 changed files with 94 additions and 35 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

129
alc/effects/reverb.cpp
View File

@ -104,21 +104,21 @@ alignas(16) constexpr float B2A[NUM_LINES][NUM_LINES]{
};
/* Converts A-Format to B-Format for early reflections. */
alignas(16) constexpr float EarlyA2B[NUM_LINES][NUM_LINES]{
{ 0.5f, 0.5f, 0.5f, 0.5f },
{ 0.5f, -0.5f, 0.5f, -0.5f },
{ 0.5f, -0.5f, -0.5f, 0.5f },
{ 0.5f, 0.5f, -0.5f, -0.5f }
};
alignas(16) constexpr std::array<std::array<float,NUM_LINES>,NUM_LINES> EarlyA2B{{
{{ 0.5f, 0.5f, 0.5f, 0.5f }},
{{ 0.5f, -0.5f, 0.5f, -0.5f }},
{{ 0.5f, -0.5f, -0.5f, 0.5f }},
{{ 0.5f, 0.5f, -0.5f, -0.5f }}
}};
/* Converts A-Format to B-Format for late reverb. */
constexpr auto InvSqrt2 = static_cast<float>(1.0/al::numbers::sqrt2);
alignas(16) constexpr float LateA2B[NUM_LINES][NUM_LINES]{
{ 0.5f, 0.5f, 0.5f, 0.5f },
{ InvSqrt2, -InvSqrt2, 0.0f, 0.0f },
{ 0.0f, 0.0f, InvSqrt2, -InvSqrt2 },
{ 0.5f, 0.5f, -0.5f, -0.5f }
};
alignas(16) constexpr std::array<std::array<float,NUM_LINES>,NUM_LINES> LateA2B{{
{{ 0.5f, 0.5f, 0.5f, 0.5f }},
{{ InvSqrt2, -InvSqrt2, 0.0f, 0.0f }},
{{ 0.0f, 0.0f, InvSqrt2, -InvSqrt2 }},
{{ 0.5f, 0.5f, -0.5f, -0.5f }}
}};
/* The all-pass and delay lines have a variable length dependent on the
* effect's density parameter, which helps alter the perceived environment
@ -460,7 +460,7 @@ struct ReverbState final : public EffectState {
std::array<std::array<BandSplitter,NUM_LINES>,2> mAmbiSplitter;
static void DoMixRow(const al::span<float> OutBuffer, const al::span<const float> Gains,
static void DoMixRow(const al::span<float> OutBuffer, const al::span<const float,4> Gains,
const float *InSamples, const size_t InStride)
{
std::fill(OutBuffer.begin(), OutBuffer.end(), 0.0f);
@ -486,17 +486,18 @@ struct ReverbState final : public EffectState {
{
ASSUME(todo > 0);
/* Convert back to B-Format, and mix the results to output. */
const al::span<float> tmpspan{al::assume_aligned<16>(mTempLine.data()), todo};
/* When not upsampling, the panning gains convert to B-Format and pan
* at the same time.
*/
for(size_t c{0u};c < NUM_LINES;c++)
{
DoMixRow(tmpspan, EarlyA2B[c], mEarlySamples[0].data(), mEarlySamples[0].size());
const al::span<float> tmpspan{mEarlySamples[c].data(), todo};
MixSamples(tmpspan, samplesOut, mEarly.CurrentGain[c], mEarly.PanGain[c], counter,
offset);
}
for(size_t c{0u};c < NUM_LINES;c++)
{
DoMixRow(tmpspan, LateA2B[c], mLateSamples[0].data(), mLateSamples[0].size());
const al::span<float> tmpspan{mLateSamples[c].data(), todo};
MixSamples(tmpspan, samplesOut, mLate.CurrentGain[c], mLate.PanGain[c], counter,
offset);
}
@ -507,6 +508,10 @@ struct ReverbState final : public EffectState {
{
ASSUME(todo > 0);
/* When upsampling, the B-Format conversion needs to be done separately
* so the proper HF scaling can be applied to each B-Format channel.
* The panning gains then pan and upsample the B-Format channels.
*/
const al::span<float> tmpspan{al::assume_aligned<16>(mTempLine.data()), todo};
for(size_t c{0u};c < NUM_LINES;c++)
{
@ -949,7 +954,7 @@ void ReverbState::updateDelayLine(const float earlyDelay, const float lateDelay,
* focal strength. This function results in a B-Format transformation matrix
* that spatially focuses the signal in the desired direction.
*/
alu::Matrix GetTransformFromVector(const float *vec)
std::array<std::array<float,4>,4> GetTransformFromVector(const float *vec)
{
/* Normalize the panning vector according to the N3D scale, which has an
* extra sqrt(3) term on the directional components. Converting from OpenAL
@ -978,12 +983,12 @@ alu::Matrix GetTransformFromVector(const float *vec)
norm[2] = vec[2] * al::numbers::sqrt3_v<float>;
}
return alu::Matrix{
1.0f, 0.0f, 0.0f, 0.0f,
norm[0], 1.0f-mag, 0.0f, 0.0f,
norm[1], 0.0f, 1.0f-mag, 0.0f,
norm[2], 0.0f, 0.0f, 1.0f-mag
};
return std::array<std::array<float,4>,4>{{
{{1.0f, 0.0f, 0.0f, 0.0f}},
{{norm[0], 1.0f-mag, 0.0f, 0.0f}},
{{norm[1], 0.0f, 1.0f-mag, 0.0f}},
{{norm[2], 0.0f, 0.0f, 1.0f-mag}}
}};
}
/* Update the early and late 3D panning gains. */
@ -993,21 +998,75 @@ void ReverbState::update3DPanning(const float *ReflectionsPan, const float *Late
/* Create matrices that transform a B-Format signal according to the
* panning vectors.
*/
const alu::Matrix earlymat{GetTransformFromVector(ReflectionsPan)};
const alu::Matrix latemat{GetTransformFromVector(LateReverbPan)};
const std::array<std::array<float,4>,4> earlymat{GetTransformFromVector(ReflectionsPan)};
const std::array<std::array<float,4>,4> latemat{GetTransformFromVector(LateReverbPan)};
mOutTarget = target.Main->Buffer;
for(size_t i{0u};i < NUM_LINES;i++)
if(mUpmixOutput)
{
const float coeffs[MaxAmbiChannels]{earlymat[0][i], earlymat[1][i], earlymat[2][i],
earlymat[3][i]};
ComputePanGains(target.Main, coeffs, earlyGain, mEarly.PanGain[i]);
/* When upsampling, combine the early and late transforms with the
* first-order upsample matrix. This results in panning gains that
* apply the panning transform to first-order B-Format, which is then
* upsampled.
*/
auto mult_matrix = [](const al::span<const std::array<float,4>,4> mtx1)
{
auto&& mtx2 = AmbiScale::FirstOrderUp;
std::array<std::array<float,MaxAmbiChannels>,NUM_LINES> res{};
for(size_t i{0};i < mtx1[0].size();++i)
{
for(size_t j{0};j < mtx2[0].size();++j)
{
double sum{0.0};
for(size_t k{0};k < mtx1.size();++k)
sum += double{mtx1[k][i]} * mtx2[k][j];
res[i][j] = static_cast<float>(sum);
}
}
return res;
};
auto earlycoeffs = mult_matrix(earlymat);
auto latecoeffs = mult_matrix(latemat);
mOutTarget = target.Main->Buffer;
for(size_t i{0u};i < NUM_LINES;i++)
ComputePanGains(target.Main, earlycoeffs[i].data(), earlyGain, mEarly.PanGain[i]);
for(size_t i{0u};i < NUM_LINES;i++)
ComputePanGains(target.Main, latecoeffs[i].data(), lateGain, mLate.PanGain[i]);
}
for(size_t i{0u};i < NUM_LINES;i++)
else
{
const float coeffs[MaxAmbiChannels]{latemat[0][i], latemat[1][i], latemat[2][i],
latemat[3][i]};
ComputePanGains(target.Main, coeffs, lateGain, mLate.PanGain[i]);
/* When not upsampling, combine the early and late A-to-B-Format
* conversions with their respective transform. This results panning
* gains that convert A-Format to B-Format, which is then panned.
*/
auto mult_matrix = [](const al::span<const std::array<float,NUM_LINES>,4> mtx1,
const al::span<const std::array<float,4>,4> mtx2)
{
std::array<std::array<float,MaxAmbiChannels>,NUM_LINES> res{};
for(size_t i{0};i < mtx1[0].size();++i)
{
for(size_t j{0};j < mtx2.size();++j)
{
double sum{0.0};
for(size_t k{0};k < mtx1.size();++k)
sum += double{mtx1[k][i]} * mtx2[j][k];
res[i][j] = static_cast<float>(sum);
}
}
return res;
};
auto earlycoeffs = mult_matrix(EarlyA2B, earlymat);
auto latecoeffs = mult_matrix(LateA2B, latemat);
mOutTarget = target.Main->Buffer;
for(size_t i{0u};i < NUM_LINES;i++)
ComputePanGains(target.Main, earlycoeffs[i].data(), earlyGain, mEarly.PanGain[i]);
for(size_t i{0u};i < NUM_LINES;i++)
ComputePanGains(target.Main, latecoeffs[i].data(), lateGain, mLate.PanGain[i]);
}
}