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makemhr.cpp
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makemhr.cpp
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/*
* HRTF utility for producing and demonstrating the process of creating an
* OpenAL Soft compatible HRIR data set.
*
* Copyright (C) 2011-2019 Christopher Fitzgerald
*
* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 2 of the License, or
* (at your option) any later version.
*
* This program is distributed in the hope that it will be useful,
* but WITHOUT ANY WARRANTY; without even the implied warranty of
* MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the
* GNU General Public License for more details.
*
* You should have received a copy of the GNU General Public License along
* with this program; if not, write to the Free Software Foundation, Inc.,
* 51 Franklin Street, Fifth Floor, Boston, MA 02110-1301 USA.
*
* Or visit: http://www.gnu.org/licenses/old-licenses/gpl-2.0.html
*
* --------------------------------------------------------------------------
*
* A big thanks goes out to all those whose work done in the field of
* binaural sound synthesis using measured HRTFs makes this utility and the
* OpenAL Soft implementation possible.
*
* The algorithm for diffuse-field equalization was adapted from the work
* done by Rio Emmanuel and Larcher Veronique of IRCAM and Bill Gardner of
* MIT Media Laboratory. It operates as follows:
*
* 1. Take the FFT of each HRIR and only keep the magnitude responses.
* 2. Calculate the diffuse-field power-average of all HRIRs weighted by
* their contribution to the total surface area covered by their
* measurement. This has since been modified to use coverage volume for
* multi-field HRIR data sets.
* 3. Take the diffuse-field average and limit its magnitude range.
* 4. Equalize the responses by using the inverse of the diffuse-field
* average.
* 5. Reconstruct the minimum-phase responses.
* 5. Zero the DC component.
* 6. IFFT the result and truncate to the desired-length minimum-phase FIR.
*
* The spherical head algorithm for calculating propagation delay was adapted
* from the paper:
*
* Modeling Interaural Time Difference Assuming a Spherical Head
* Joel David Miller
* Music 150, Musical Acoustics, Stanford University
* December 2, 2001
*
* The formulae for calculating the Kaiser window metrics are from the
* the textbook:
*
* Discrete-Time Signal Processing
* Alan V. Oppenheim and Ronald W. Schafer
* Prentice-Hall Signal Processing Series
* 1999
*/
#define _UNICODE /* NOLINT(bugprone-reserved-identifier) */
#include "config.h"
#include "makemhr.h"
#include <algorithm>
#include <atomic>
#include <chrono>
#include <cmath>
#include <complex>
#include <cstdint>
#include <cstdio>
#include <cstdlib>
#include <cstring>
#include <filesystem>
#include <fstream>
#include <functional>
#include <iostream>
#include <limits>
#include <memory>
#include <numeric>
#include <string_view>
#include <thread>
#include <utility>
#include <vector>
#include "alcomplex.h"
#include "alnumbers.h"
#include "alnumeric.h"
#include "alspan.h"
#include "alstring.h"
#include "loaddef.h"
#include "loadsofa.h"
#include "win_main_utf8.h"
HrirDataT::~HrirDataT() = default;
namespace {
using namespace std::string_view_literals;
struct FileDeleter {
void operator()(gsl::owner<FILE*> f) { fclose(f); }
};
using FilePtr = std::unique_ptr<FILE,FileDeleter>;
// The epsilon used to maintain signal stability.
constexpr double Epsilon{1e-9};
// The limits to the FFT window size override on the command line.
constexpr uint MinFftSize{65536};
constexpr uint MaxFftSize{131072};
// The limits to the equalization range limit on the command line.
constexpr double MinLimit{2.0};
constexpr double MaxLimit{120.0};
// The limits to the truncation window size on the command line.
constexpr uint MinTruncSize{16};
constexpr uint MaxTruncSize{128};
// The limits to the custom head radius on the command line.
constexpr double MinCustomRadius{0.05};
constexpr double MaxCustomRadius{0.15};
// The maximum propagation delay value supported by OpenAL Soft.
constexpr double MaxHrtd{63.0};
// The OpenAL Soft HRTF format marker. It stands for minimum-phase head
// response protocol 03.
constexpr auto GetMHRMarker() noexcept { return "MinPHR03"sv; }
// Head model used for calculating the impulse delays.
enum HeadModelT {
HM_None,
HM_Dataset, // Measure the onset from the dataset.
HM_Sphere, // Calculate the onset using a spherical head model.
HM_Default = HM_Dataset
};
// The defaults for the command line options.
constexpr uint DefaultFftSize{65536};
constexpr bool DefaultEqualize{true};
constexpr bool DefaultSurface{true};
constexpr double DefaultLimit{24.0};
constexpr uint DefaultTruncSize{64};
constexpr double DefaultCustomRadius{0.0};
/* Channel index enums. Mono uses LeftChannel only. */
enum ChannelIndex : uint {
LeftChannel = 0u,
RightChannel = 1u
};
/* Performs a string substitution. Any case-insensitive occurrences of the
* pattern string are replaced with the replacement string. The result is
* truncated if necessary.
*/
auto StrSubst(std::string_view in, const std::string_view pat, const std::string_view rep) -> std::string
{
std::string ret;
ret.reserve(in.size() + pat.size());
while(in.size() >= pat.size())
{
if(al::starts_with(in, pat))
{
in = in.substr(pat.size());
ret += rep;
}
else
{
size_t endpos{1};
while(endpos < in.size() && std::toupper(in[endpos]) != std::toupper(pat.front()))
++endpos;
ret += in.substr(0, endpos);
in = in.substr(endpos);
}
}
ret += in;
return ret;
}
/*********************
*** Math routines ***
*********************/
// Simple clamp routine.
double Clamp(const double val, const double lower, const double upper)
{
return std::min(std::max(val, lower), upper);
}
inline uint dither_rng(uint *seed)
{
*seed = *seed * 96314165 + 907633515;
return *seed;
}
// Performs a triangular probability density function dither. The input samples
// should be normalized (-1 to +1).
void TpdfDither(const al::span<double> out, const al::span<const double> in, const double scale,
const size_t channel, const size_t step, uint *seed)
{
static constexpr double PRNG_SCALE = 1.0 / std::numeric_limits<uint>::max();
assert(channel < step);
for(size_t i{0};i < in.size();++i)
{
uint prn0{dither_rng(seed)};
uint prn1{dither_rng(seed)};
out[i*step + channel] = std::round(in[i]*scale + (prn0*PRNG_SCALE - prn1*PRNG_SCALE));
}
}
/* Apply a range limit (in dB) to the given magnitude response. This is used
* to adjust the effects of the diffuse-field average on the equalization
* process.
*/
void LimitMagnitudeResponse(const uint n, const uint m, const double limit,
const al::span<double> inout)
{
const double halfLim{limit / 2.0};
// Convert the response to dB.
for(uint i{0};i < m;++i)
inout[i] = 20.0 * std::log10(inout[i]);
// Use six octaves to calculate the average magnitude of the signal.
const auto lower = (static_cast<uint>(std::ceil(n / std::pow(2.0, 8.0)))) - 1;
const auto upper = (static_cast<uint>(std::floor(n / std::pow(2.0, 2.0)))) - 1;
double ave{0.0};
for(uint i{lower};i <= upper;++i)
ave += inout[i];
ave /= upper - lower + 1;
// Keep the response within range of the average magnitude.
for(uint i{0};i < m;++i)
inout[i] = Clamp(inout[i], ave - halfLim, ave + halfLim);
// Convert the response back to linear magnitude.
for(uint i{0};i < m;++i)
inout[i] = std::pow(10.0, inout[i] / 20.0);
}
/* Reconstructs the minimum-phase component for the given magnitude response
* of a signal. This is equivalent to phase recomposition, sans the missing
* residuals (which were discarded). The mirrored half of the response is
* reconstructed.
*/
void MinimumPhase(const al::span<double> mags, const al::span<complex_d> out)
{
assert(mags.size() == out.size());
const size_t m{(mags.size()/2) + 1};
size_t i;
for(i = 0;i < m;i++)
out[i] = std::log(mags[i]);
for(;i < mags.size();++i)
{
mags[i] = mags[mags.size() - i];
out[i] = out[mags.size() - i];
}
complex_hilbert(out);
// Remove any DC offset the filter has.
mags[0] = Epsilon;
for(i = 0;i < mags.size();++i)
out[i] = std::polar(mags[i], out[i].imag());
}
/***************************
*** File storage output ***
***************************/
// Write an ASCII string to a file.
auto WriteAscii(const std::string_view out, std::ostream &ostream, const std::string_view filename) -> int
{
if(!ostream.write(out.data(), std::streamsize(out.size())) || ostream.bad())
{
fprintf(stderr, "\nError: Bad write to file '%.*s'.\n", al::sizei(filename),
filename.data());
return 0;
}
return 1;
}
// Write a binary value of the given byte order and byte size to a file,
// loading it from a 32-bit unsigned integer.
auto WriteBin4(const uint bytes, const uint32_t in, std::ostream &ostream,
const std::string_view filename) -> int
{
std::array<char,4> out{};
for(uint i{0};i < bytes;i++)
out[i] = static_cast<char>((in>>(i*8)) & 0x000000FF);
if(!ostream.write(out.data(), std::streamsize(bytes)) || ostream.bad())
{
fprintf(stderr, "\nError: Bad write to file '%.*s'.\n", al::sizei(filename),
filename.data());
return 0;
}
return 1;
}
// Store the OpenAL Soft HRTF data set.
auto StoreMhr(const HrirDataT *hData, const std::string_view filename) -> bool
{
const uint channels{(hData->mChannelType == CT_STEREO) ? 2u : 1u};
const uint n{hData->mIrPoints};
uint dither_seed{22222};
std::ofstream ostream{std::filesystem::u8path(filename)};
if(!ostream.is_open())
{
fprintf(stderr, "\nError: Could not open MHR file '%.*s'.\n", al::sizei(filename),
filename.data());
return false;
}
if(!WriteAscii(GetMHRMarker(), ostream, filename))
return false;
if(!WriteBin4(4, hData->mIrRate, ostream, filename))
return false;
if(!WriteBin4(1, static_cast<uint32_t>(hData->mChannelType), ostream, filename))
return false;
if(!WriteBin4(1, hData->mIrPoints, ostream, filename))
return false;
if(!WriteBin4(1, static_cast<uint>(hData->mFds.size()), ostream, filename))
return false;
for(size_t fi{hData->mFds.size()-1};fi < hData->mFds.size();--fi)
{
auto fdist = static_cast<uint32_t>(std::round(1000.0 * hData->mFds[fi].mDistance));
if(!WriteBin4(2, fdist, ostream, filename))
return false;
if(!WriteBin4(1, static_cast<uint32_t>(hData->mFds[fi].mEvs.size()), ostream, filename))
return false;
for(size_t ei{0};ei < hData->mFds[fi].mEvs.size();++ei)
{
const auto &elev = hData->mFds[fi].mEvs[ei];
if(!WriteBin4(1, static_cast<uint32_t>(elev.mAzs.size()), ostream, filename))
return false;
}
}
for(size_t fi{hData->mFds.size()-1};fi < hData->mFds.size();--fi)
{
static constexpr double scale{8388607.0};
static constexpr uint bps{3u};
for(const auto &evd : hData->mFds[fi].mEvs)
{
for(const auto &azd : evd.mAzs)
{
std::array<double,MaxTruncSize*2_uz> out{};
TpdfDither(out, azd.mIrs[0].first(n), scale, 0, channels, &dither_seed);
if(hData->mChannelType == CT_STEREO)
TpdfDither(out, azd.mIrs[1].first(n), scale, 1, channels, &dither_seed);
const size_t numsamples{size_t{channels} * n};
for(size_t i{0};i < numsamples;i++)
{
const auto v = static_cast<int>(Clamp(out[i], -scale-1.0, scale));
if(!WriteBin4(bps, static_cast<uint32_t>(v), ostream, filename))
return false;
}
}
}
}
for(size_t fi{hData->mFds.size()-1};fi < hData->mFds.size();--fi)
{
/* Delay storage has 2 bits of extra precision. */
static constexpr double DelayPrecScale{4.0};
for(const auto &evd : hData->mFds[fi].mEvs)
{
for(const auto &azd : evd.mAzs)
{
auto v = static_cast<uint>(std::round(azd.mDelays[0]*DelayPrecScale));
if(!WriteBin4(1, v, ostream, filename)) return false;
if(hData->mChannelType == CT_STEREO)
{
v = static_cast<uint>(std::round(azd.mDelays[1]*DelayPrecScale));
if(!WriteBin4(1, v, ostream, filename)) return false;
}
}
}
}
return true;
}
/***********************
*** HRTF processing ***
***********************/
/* Balances the maximum HRIR magnitudes of multi-field data sets by
* independently normalizing each field in relation to the overall maximum.
* This is done to ignore distance attenuation.
*/
void BalanceFieldMagnitudes(const HrirDataT *hData, const uint channels, const uint m)
{
std::array<double,MAX_FD_COUNT> maxMags{};
double maxMag{0.0};
for(size_t fi{0};fi < hData->mFds.size();++fi)
{
for(size_t ei{hData->mFds[fi].mEvStart};ei < hData->mFds[fi].mEvs.size();++ei)
{
for(const auto &azd : hData->mFds[fi].mEvs[ei].mAzs)
{
for(size_t ti{0};ti < channels;++ti)
{
for(size_t i{0};i < m;++i)
maxMags[fi] = std::max(azd.mIrs[ti][i], maxMags[fi]);
}
}
}
maxMag = std::max(maxMags[fi], maxMag);
}
for(size_t fi{0};fi < hData->mFds.size();++fi)
{
const double magFactor{maxMag / maxMags[fi]};
for(size_t ei{hData->mFds[fi].mEvStart};ei < hData->mFds[fi].mEvs.size();++ei)
{
for(const auto &azd : hData->mFds[fi].mEvs[ei].mAzs)
{
for(size_t ti{0};ti < channels;++ti)
{
for(size_t i{0};i < m;++i)
azd.mIrs[ti][i] *= magFactor;
}
}
}
}
}
/* Calculate the contribution of each HRIR to the diffuse-field average based
* on its coverage volume. All volumes are centered at the spherical HRIR
* coordinates and measured by extruded solid angle.
*/
void CalculateDfWeights(const HrirDataT *hData, const al::span<double> weights)
{
double sum, innerRa, outerRa, evs, ev, upperEv, lowerEv;
double solidAngle, solidVolume;
uint fi, ei;
sum = 0.0;
// The head radius acts as the limit for the inner radius.
innerRa = hData->mRadius;
for(fi = 0;fi < hData->mFds.size();fi++)
{
// Each volume ends half way between progressive field measurements.
if((fi + 1) < hData->mFds.size())
outerRa = 0.5f * (hData->mFds[fi].mDistance + hData->mFds[fi + 1].mDistance);
// The final volume has its limit extended to some practical value.
// This is done to emphasize the far-field responses in the average.
else
outerRa = 10.0f;
const double raPowDiff{std::pow(outerRa, 3.0) - std::pow(innerRa, 3.0)};
evs = al::numbers::pi / 2.0 / static_cast<double>(hData->mFds[fi].mEvs.size() - 1);
for(ei = hData->mFds[fi].mEvStart;ei < hData->mFds[fi].mEvs.size();ei++)
{
const auto &elev = hData->mFds[fi].mEvs[ei];
// For each elevation, calculate the upper and lower limits of
// the patch band.
ev = elev.mElevation;
lowerEv = std::max(-al::numbers::pi / 2.0, ev - evs);
upperEv = std::min(al::numbers::pi / 2.0, ev + evs);
// Calculate the surface area of the patch band.
solidAngle = 2.0 * al::numbers::pi * (std::sin(upperEv) - std::sin(lowerEv));
// Then the volume of the extruded patch band.
solidVolume = solidAngle * raPowDiff / 3.0;
// Each weight is the volume of one extruded patch.
weights[(fi*MAX_EV_COUNT) + ei] = solidVolume / static_cast<double>(elev.mAzs.size());
// Sum the total coverage volume of the HRIRs for all fields.
sum += solidAngle;
}
innerRa = outerRa;
}
for(fi = 0;fi < hData->mFds.size();fi++)
{
// Normalize the weights given the total surface coverage for all
// fields.
for(ei = hData->mFds[fi].mEvStart;ei < hData->mFds[fi].mEvs.size();ei++)
weights[(fi * MAX_EV_COUNT) + ei] /= sum;
}
}
/* Calculate the diffuse-field average from the given magnitude responses of
* the HRIR set. Weighting can be applied to compensate for the varying
* coverage of each HRIR. The final average can then be limited by the
* specified magnitude range (in positive dB; 0.0 to skip).
*/
void CalculateDiffuseFieldAverage(const HrirDataT *hData, const uint channels, const uint m,
const bool weighted, const double limit, const al::span<double> dfa)
{
std::vector<double> weights(hData->mFds.size() * MAX_EV_COUNT);
uint count;
if(weighted)
{
// Use coverage weighting to calculate the average.
CalculateDfWeights(hData, weights);
}
else
{
double weight;
// If coverage weighting is not used, the weights still need to be
// averaged by the number of existing HRIRs.
count = hData->mIrCount;
for(size_t fi{0};fi < hData->mFds.size();++fi)
{
for(size_t ei{0};ei < hData->mFds[fi].mEvStart;++ei)
count -= static_cast<uint>(hData->mFds[fi].mEvs[ei].mAzs.size());
}
weight = 1.0 / count;
for(size_t fi{0};fi < hData->mFds.size();++fi)
{
for(size_t ei{hData->mFds[fi].mEvStart};ei < hData->mFds[fi].mEvs.size();++ei)
weights[(fi * MAX_EV_COUNT) + ei] = weight;
}
}
for(size_t ti{0};ti < channels;++ti)
{
for(size_t i{0};i < m;++i)
dfa[(ti * m) + i] = 0.0;
for(size_t fi{0};fi < hData->mFds.size();++fi)
{
for(size_t ei{hData->mFds[fi].mEvStart};ei < hData->mFds[fi].mEvs.size();++ei)
{
for(size_t ai{0};ai < hData->mFds[fi].mEvs[ei].mAzs.size();++ai)
{
HrirAzT *azd = &hData->mFds[fi].mEvs[ei].mAzs[ai];
// Get the weight for this HRIR's contribution.
double weight = weights[(fi * MAX_EV_COUNT) + ei];
// Add this HRIR's weighted power average to the total.
for(size_t i{0};i < m;++i)
dfa[(ti * m) + i] += weight * azd->mIrs[ti][i] * azd->mIrs[ti][i];
}
}
}
// Finish the average calculation and keep it from being too small.
for(size_t i{0};i < m;++i)
dfa[(ti * m) + i] = std::max(sqrt(dfa[(ti * m) + i]), Epsilon);
// Apply a limit to the magnitude range of the diffuse-field average
// if desired.
if(limit > 0.0)
LimitMagnitudeResponse(hData->mFftSize, m, limit, dfa.subspan(ti * m));
}
}
// Perform diffuse-field equalization on the magnitude responses of the HRIR
// set using the given average response.
void DiffuseFieldEqualize(const uint channels, const uint m, const al::span<const double> dfa,
const HrirDataT *hData)
{
for(size_t fi{0};fi < hData->mFds.size();++fi)
{
for(size_t ei{hData->mFds[fi].mEvStart};ei < hData->mFds[fi].mEvs.size();++ei)
{
for(auto &azd : hData->mFds[fi].mEvs[ei].mAzs)
{
for(size_t ti{0};ti < channels;++ti)
{
for(size_t i{0};i < m;++i)
azd.mIrs[ti][i] /= dfa[(ti * m) + i];
}
}
}
}
}
/* Given field and elevation indices and an azimuth, calculate the indices of
* the two HRIRs that bound the coordinate along with a factor for
* calculating the continuous HRIR using interpolation.
*/
void CalcAzIndices(const HrirFdT &field, const uint ei, const double az, uint *a0, uint *a1, double *af)
{
double f{(2.0*al::numbers::pi + az) * static_cast<double>(field.mEvs[ei].mAzs.size()) /
(2.0*al::numbers::pi)};
const uint i{static_cast<uint>(f) % static_cast<uint>(field.mEvs[ei].mAzs.size())};
f -= std::floor(f);
*a0 = i;
*a1 = (i + 1) % static_cast<uint>(field.mEvs[ei].mAzs.size());
*af = f;
}
/* Synthesize any missing onset timings at the bottom elevations of each field.
* This just mirrors some top elevations for the bottom, and blends the
* remaining elevations (not an accurate model).
*/
void SynthesizeOnsets(HrirDataT *hData)
{
const uint channels{(hData->mChannelType == CT_STEREO) ? 2u : 1u};
auto proc_field = [channels](HrirFdT &field) -> void
{
/* Get the starting elevation from the measurements, and use it as the
* upper elevation limit for what needs to be calculated.
*/
const uint upperElevReal{field.mEvStart};
if(upperElevReal <= 0) return;
/* Get the lowest half of the missing elevations' delays by mirroring
* the top elevation delays. The responses are on a spherical grid
* centered between the ears, so these should align.
*/
uint ei{};
if(channels > 1)
{
/* Take the polar opposite position of the desired measurement and
* swap the ears.
*/
field.mEvs[0].mAzs[0].mDelays[0] = field.mEvs[field.mEvs.size()-1].mAzs[0].mDelays[1];
field.mEvs[0].mAzs[0].mDelays[1] = field.mEvs[field.mEvs.size()-1].mAzs[0].mDelays[0];
for(ei = 1u;ei < (upperElevReal+1)/2;++ei)
{
const uint topElev{static_cast<uint>(field.mEvs.size()-ei-1)};
for(uint ai{0u};ai < field.mEvs[ei].mAzs.size();ai++)
{
uint a0, a1;
double af;
/* Rotate this current azimuth by a half-circle, and lookup
* the mirrored elevation to find the indices for the polar
* opposite position (may need blending).
*/
const double az{field.mEvs[ei].mAzs[ai].mAzimuth + al::numbers::pi};
CalcAzIndices(field, topElev, az, &a0, &a1, &af);
/* Blend the delays, and again, swap the ears. */
field.mEvs[ei].mAzs[ai].mDelays[0] = Lerp(
field.mEvs[topElev].mAzs[a0].mDelays[1],
field.mEvs[topElev].mAzs[a1].mDelays[1], af);
field.mEvs[ei].mAzs[ai].mDelays[1] = Lerp(
field.mEvs[topElev].mAzs[a0].mDelays[0],
field.mEvs[topElev].mAzs[a1].mDelays[0], af);
}
}
}
else
{
field.mEvs[0].mAzs[0].mDelays[0] = field.mEvs[field.mEvs.size()-1].mAzs[0].mDelays[0];
for(ei = 1u;ei < (upperElevReal+1)/2;++ei)
{
const uint topElev{static_cast<uint>(field.mEvs.size()-ei-1)};
for(uint ai{0u};ai < field.mEvs[ei].mAzs.size();ai++)
{
uint a0, a1;
double af;
/* For mono data sets, mirror the azimuth front<->back
* since the other ear is a mirror of what we have (e.g.
* the left ear's back-left is simulated with the right
* ear's front-right, which uses the left ear's front-left
* measurement).
*/
double az{field.mEvs[ei].mAzs[ai].mAzimuth};
if(az <= al::numbers::pi) az = al::numbers::pi - az;
else az = (al::numbers::pi*2.0)-az + al::numbers::pi;
CalcAzIndices(field, topElev, az, &a0, &a1, &af);
field.mEvs[ei].mAzs[ai].mDelays[0] = Lerp(
field.mEvs[topElev].mAzs[a0].mDelays[0],
field.mEvs[topElev].mAzs[a1].mDelays[0], af);
}
}
}
/* Record the lowest elevation filled in with the mirrored top. */
const uint lowerElevFake{ei-1u};
/* Fill in the remaining delays using bilinear interpolation. This
* helps smooth the transition back to the real delays.
*/
for(;ei < upperElevReal;++ei)
{
const double ef{(field.mEvs[upperElevReal].mElevation - field.mEvs[ei].mElevation) /
(field.mEvs[upperElevReal].mElevation - field.mEvs[lowerElevFake].mElevation)};
for(uint ai{0u};ai < field.mEvs[ei].mAzs.size();ai++)
{
uint a0, a1, a2, a3;
double af0, af1;
double az{field.mEvs[ei].mAzs[ai].mAzimuth};
CalcAzIndices(field, upperElevReal, az, &a0, &a1, &af0);
CalcAzIndices(field, lowerElevFake, az, &a2, &a3, &af1);
std::array<double,4> blend{{
(1.0-ef) * (1.0-af0),
(1.0-ef) * ( af0),
( ef) * (1.0-af1),
( ef) * ( af1)
}};
for(uint ti{0u};ti < channels;ti++)
{
field.mEvs[ei].mAzs[ai].mDelays[ti] =
field.mEvs[upperElevReal].mAzs[a0].mDelays[ti]*blend[0] +
field.mEvs[upperElevReal].mAzs[a1].mDelays[ti]*blend[1] +
field.mEvs[lowerElevFake].mAzs[a2].mDelays[ti]*blend[2] +
field.mEvs[lowerElevFake].mAzs[a3].mDelays[ti]*blend[3];
}
}
}
};
std::for_each(hData->mFds.begin(), hData->mFds.end(), proc_field);
}
/* Attempt to synthesize any missing HRIRs at the bottom elevations of each
* field. Right now this just blends the lowest elevation HRIRs together and
* applies a low-pass filter to simulate body occlusion. It is a simple, if
* inaccurate model.
*/
void SynthesizeHrirs(HrirDataT *hData)
{
const uint channels{(hData->mChannelType == CT_STEREO) ? 2u : 1u};
auto htemp = std::vector<complex_d>(hData->mFftSize);
const uint m{hData->mFftSize/2u + 1u};
auto filter = std::vector<double>(m);
const double beta{3.5e-6 * hData->mIrRate};
auto proc_field = [channels,m,beta,&htemp,&filter](HrirFdT &field) -> void
{
const uint oi{field.mEvStart};
if(oi <= 0) return;
for(uint ti{0u};ti < channels;ti++)
{
uint a0, a1;
double af;
/* Use the lowest immediate-left response for the left ear and
* lowest immediate-right response for the right ear. Given no comb
* effects as a result of the left response reaching the right ear
* and vice-versa, this produces a decent phantom-center response
* underneath the head.
*/
CalcAzIndices(field, oi, al::numbers::pi / ((ti==0) ? -2.0 : 2.0), &a0, &a1, &af);
for(uint i{0u};i < m;i++)
{
field.mEvs[0].mAzs[0].mIrs[ti][i] = Lerp(field.mEvs[oi].mAzs[a0].mIrs[ti][i],
field.mEvs[oi].mAzs[a1].mIrs[ti][i], af);
}
}
for(uint ei{1u};ei < field.mEvStart;ei++)
{
const double of{static_cast<double>(ei) / field.mEvStart};
const double b{(1.0 - of) * beta};
std::array<double,4> lp{};
/* Calculate a low-pass filter to simulate body occlusion. */
lp[0] = Lerp(1.0, lp[0], b);
lp[1] = Lerp(lp[0], lp[1], b);
lp[2] = Lerp(lp[1], lp[2], b);
lp[3] = Lerp(lp[2], lp[3], b);
htemp[0] = lp[3];
for(size_t i{1u};i < htemp.size();i++)
{
lp[0] = Lerp(0.0, lp[0], b);
lp[1] = Lerp(lp[0], lp[1], b);
lp[2] = Lerp(lp[1], lp[2], b);
lp[3] = Lerp(lp[2], lp[3], b);
htemp[i] = lp[3];
}
/* Get the filter's frequency-domain response and extract the
* frequency magnitudes (phase will be reconstructed later)).
*/
FftForward(static_cast<uint>(htemp.size()), htemp.data());
std::transform(htemp.cbegin(), htemp.cbegin()+m, filter.begin(),
[](const complex_d c) -> double { return std::abs(c); });
for(uint ai{0u};ai < field.mEvs[ei].mAzs.size();ai++)
{
uint a0, a1;
double af;
CalcAzIndices(field, oi, field.mEvs[ei].mAzs[ai].mAzimuth, &a0, &a1, &af);
for(uint ti{0u};ti < channels;ti++)
{
for(uint i{0u};i < m;i++)
{
/* Blend the two defined HRIRs closest to this azimuth,
* then blend that with the synthesized -90 elevation.
*/
const double s1{Lerp(field.mEvs[oi].mAzs[a0].mIrs[ti][i],
field.mEvs[oi].mAzs[a1].mIrs[ti][i], af)};
const double s{Lerp(field.mEvs[0].mAzs[0].mIrs[ti][i], s1, of)};
field.mEvs[ei].mAzs[ai].mIrs[ti][i] = s * filter[i];
}
}
}
}
const double b{beta};
std::array<double,4> lp{};
lp[0] = Lerp(1.0, lp[0], b);
lp[1] = Lerp(lp[0], lp[1], b);
lp[2] = Lerp(lp[1], lp[2], b);
lp[3] = Lerp(lp[2], lp[3], b);
htemp[0] = lp[3];
for(size_t i{1u};i < htemp.size();i++)
{
lp[0] = Lerp(0.0, lp[0], b);
lp[1] = Lerp(lp[0], lp[1], b);
lp[2] = Lerp(lp[1], lp[2], b);
lp[3] = Lerp(lp[2], lp[3], b);
htemp[i] = lp[3];
}
FftForward(static_cast<uint>(htemp.size()), htemp.data());
std::transform(htemp.cbegin(), htemp.cbegin()+m, filter.begin(),
[](const complex_d c) -> double { return std::abs(c); });
for(uint ti{0u};ti < channels;ti++)
{
for(uint i{0u};i < m;i++)
field.mEvs[0].mAzs[0].mIrs[ti][i] *= filter[i];
}
};
std::for_each(hData->mFds.begin(), hData->mFds.end(), proc_field);
}
// The following routines assume a full set of HRIRs for all elevations.
/* Perform minimum-phase reconstruction using the magnitude responses of the
* HRIR set. Work is delegated to this struct, which runs asynchronously on one
* or more threads (sharing the same reconstructor object).
*/
struct HrirReconstructor {
std::vector<al::span<double>> mIrs;
std::atomic<size_t> mCurrent{};
std::atomic<size_t> mDone{};
uint mFftSize{};
uint mIrPoints{};
void Worker()
{
auto h = std::vector<complex_d>(mFftSize);
auto mags = std::vector<double>(mFftSize);
size_t m{(mFftSize/2) + 1};
while(true)
{
/* Load the current index to process. */
size_t idx{mCurrent.load()};
do {
/* If the index is at the end, we're done. */
if(idx >= mIrs.size())
return;
/* Otherwise, increment the current index atomically so other
* threads know to go to the next one. If this call fails, the
* current index was just changed by another thread and the new
* value is loaded into idx, which we'll recheck.
*/
} while(!mCurrent.compare_exchange_weak(idx, idx+1, std::memory_order_relaxed));
/* Now do the reconstruction, and apply the inverse FFT to get the
* time-domain response.
*/
for(size_t i{0};i < m;++i)
mags[i] = std::max(mIrs[idx][i], Epsilon);
MinimumPhase(mags, h);
FftInverse(mFftSize, h.data());
for(uint i{0u};i < mIrPoints;++i)
mIrs[idx][i] = h[i].real();
/* Increment the number of IRs done. */
mDone.fetch_add(1);
}
}
};
void ReconstructHrirs(const HrirDataT *hData, const uint numThreads)
{
const uint channels{(hData->mChannelType == CT_STEREO) ? 2u : 1u};
/* Set up the reconstructor with the needed size info and pointers to the
* IRs to process.
*/
HrirReconstructor reconstructor;
reconstructor.mCurrent.store(0, std::memory_order_relaxed);
reconstructor.mDone.store(0, std::memory_order_relaxed);
reconstructor.mFftSize = hData->mFftSize;
reconstructor.mIrPoints = hData->mIrPoints;
for(const auto &field : hData->mFds)
{
for(auto &elev : field.mEvs)
{
for(const auto &azd : elev.mAzs)
{
for(uint ti{0u};ti < channels;ti++)
reconstructor.mIrs.push_back(azd.mIrs[ti]);
}
}
}
/* Launch threads to work on reconstruction. */
std::vector<std::thread> thrds;
thrds.reserve(numThreads);
for(size_t i{0};i < numThreads;++i)
thrds.emplace_back(std::mem_fn(&HrirReconstructor::Worker), &reconstructor);
/* Keep track of the number of IRs done, periodically reporting it. */
size_t count;
do {
std::this_thread::sleep_for(std::chrono::milliseconds{50});
count = reconstructor.mDone.load();
size_t pcdone{count * 100 / reconstructor.mIrs.size()};
printf("\r%3zu%% done (%zu of %zu)", pcdone, count, reconstructor.mIrs.size());
fflush(stdout);
} while(count < reconstructor.mIrs.size());
fputc('\n', stdout);
for(auto &thrd : thrds)
{
if(thrd.joinable())
thrd.join();
}
}
// Normalize the HRIR set and slightly attenuate the result.
void NormalizeHrirs(HrirDataT *hData)
{
const uint channels{(hData->mChannelType == CT_STEREO) ? 2u : 1u};
const uint irSize{hData->mIrPoints};
/* Find the maximum amplitude and RMS out of all the IRs. */
struct LevelPair { double amp, rms; };
auto mesasure_channel = [irSize](const LevelPair levels, al::span<const double> ir)
{
/* Calculate the peak amplitude and RMS of this IR. */
ir = ir.first(irSize);
auto current = std::accumulate(ir.cbegin(), ir.cend(), LevelPair{0.0, 0.0},
[](const LevelPair cur, const double impulse)
{
return LevelPair{std::max(std::abs(impulse), cur.amp), cur.rms + impulse*impulse};
});
current.rms = std::sqrt(current.rms / irSize);
/* Accumulate levels by taking the maximum amplitude and RMS. */
return LevelPair{std::max(current.amp, levels.amp), std::max(current.rms, levels.rms)};
};
auto measure_azi = [channels,mesasure_channel](const LevelPair levels, const HrirAzT &azi)
{ return std::accumulate(azi.mIrs.begin(), azi.mIrs.begin()+channels, levels, mesasure_channel); };
auto measure_elev = [measure_azi](const LevelPair levels, const HrirEvT &elev)
{ return std::accumulate(elev.mAzs.cbegin(), elev.mAzs.cend(), levels, measure_azi); };
auto measure_field = [measure_elev](const LevelPair levels, const HrirFdT &field)
{ return std::accumulate(field.mEvs.cbegin(), field.mEvs.cend(), levels, measure_elev); };
const auto maxlev = std::accumulate(hData->mFds.begin(), hData->mFds.end(),
LevelPair{0.0, 0.0}, measure_field);
/* Normalize using the maximum RMS of the HRIRs. The RMS measure for the
* non-filtered signal is of an impulse with equal length (to the filter):
*
* rms_impulse = sqrt(sum([ 1^2, 0^2, 0^2, ... ]) / n)
* = sqrt(1 / n)
*
* This helps keep a more consistent volume between the non-filtered signal
* and various data sets.
*/
double factor{std::sqrt(1.0 / irSize) / maxlev.rms};
/* Also ensure the samples themselves won't clip. */
factor = std::min(factor, 0.99/maxlev.amp);
/* Now scale all IRs by the given factor. */
auto proc_channel = [irSize,factor](al::span<double> ir)
{
ir = ir.first(irSize);
std::transform(ir.cbegin(), ir.cend(), ir.begin(),
[factor](double s) { return s * factor; });
};
auto proc_azi = [channels,proc_channel](HrirAzT &azi)
{ std::for_each(azi.mIrs.begin(), azi.mIrs.begin()+channels, proc_channel); };
auto proc_elev = [proc_azi](HrirEvT &elev)
{ std::for_each(elev.mAzs.begin(), elev.mAzs.end(), proc_azi); };
auto proc1_field = [proc_elev](HrirFdT &field)
{ std::for_each(field.mEvs.begin(), field.mEvs.end(), proc_elev); };
std::for_each(hData->mFds.begin(), hData->mFds.end(), proc1_field);
}