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/*
* Copyright 2023 jacqueline <me@jacqueline.id.au>
*
* SPDX-License-Identifier: GPL-3.0-only
*/
#include "resample.hpp"
/*
* This file contains the implementation for a 32-bit floating point resampler.
* It is largely based on David Bryant's ART resampler, which is BSD-licensed,
* and available at https://github.com/dbry/audio-resampler/.
*
* This resampler uses windowed sinc interpolation filters, with an additional
* lowpass filter to reduce aliasing.
*/
#include <stdint.h>
#include <stdlib.h>
#include <string.h>
#include <algorithm>
#include <cmath>
#include <numeric>
#include "esp_log.h"
#include "sample.hpp"
#include "stream_info.hpp"
namespace audio {
static constexpr double kLowPassRatio = 0.5;
static constexpr size_t kNumFilters = 64;
static constexpr size_t kFilterSize = 16;
typedef std::array<float, kFilterSize> Filter;
static std::array<Filter, kNumFilters + 1> sFilters{};
static bool sFiltersInitialised = false;
auto InitFilter(int index) -> void;
Resampler::Resampler(uint32_t source_sample_rate,
uint32_t target_sample_rate,
uint8_t num_channels)
: source_sample_rate_(source_sample_rate),
target_sample_rate_(target_sample_rate),
factor_(static_cast<double>(target_sample_rate) /
static_cast<double>(source_sample_rate)),
num_channels_(num_channels) {
channel_buffers_.resize(num_channels);
channel_buffer_size_ = kFilterSize * 16;
for (int i = 0; i < num_channels; i++) {
channel_buffers_[i] =
static_cast<float*>(calloc(sizeof(float), channel_buffer_size_));
}
output_offset_ = kFilterSize / 2.0f;
input_index_ = kFilterSize;
if (!sFiltersInitialised) {
sFiltersInitialised = true;
for (int i = 0; i < kNumFilters + 1; i++) {
InitFilter(i);
}
}
}
Resampler::~Resampler() {}
auto Resampler::Process(cpp::span<const sample::Sample> input,
cpp::span<sample::Sample> output,
bool end_of_data) -> std::pair<size_t, size_t> {
size_t samples_used = 0;
size_t samples_produced = 0;
size_t input_frames = input.size() / num_channels_;
size_t output_frames = output.size() / num_channels_;
int half_taps = kFilterSize / 2;
while (output_frames > 0) {
if (output_offset_ >= input_index_ - half_taps) {
if (input_frames > 0) {
// Check whether the channel buffers will overflow with the addition of
// this sample. If so, we need to move the remaining contents back to
// the beginning of the buffer.
if (input_index_ == channel_buffer_size_) {
for (int i = 0; i < num_channels_; ++i) {
memmove(channel_buffers_[i],
channel_buffers_[i] + channel_buffer_size_ - kFilterSize,
kFilterSize * sizeof(float));
}
output_offset_ -= channel_buffer_size_ - kFilterSize;
input_index_ -= channel_buffer_size_ - kFilterSize;
}
for (int i = 0; i < num_channels_; ++i) {
channel_buffers_[i][input_index_] =
sample::ToFloat(input[samples_used++]);
}
input_index_++;
input_frames--;
} else {
break;
}
} else {
for (int i = 0; i < num_channels_; i++) {
output[samples_produced++] = sample::FromFloat(Subsample(i));
}
// NOTE: floating point division here is potentially slow due to FPU
// limitations. Consider explicitly bunding the xtensa libgcc divsion via
// reciprocal implementation if we care about portability between
// compilers.
output_offset_ += 1.0f / factor_;
output_frames--;
}
}
return {samples_used, samples_produced};
}
/*
* Constructs the filter in-place for the given index of sFilters. This only
* needs to be done once, per-filter. 64-bit math is okay here, because filters
* will not be initialised within a performance critical path.
*/
auto InitFilter(int index) -> void {
Filter& filter = sFilters[index];
std::array<double, kFilterSize> working_buffer{};
double fraction = index / static_cast<double>(kNumFilters);
double filter_sum = 0.0;
for (int i = 0; i < kFilterSize; ++i) {
// "dist" is the absolute distance from the sinc maximum to the filter tap
// to be calculated, in radians.
double dist = fabs((kFilterSize / 2.0 - 1.0) + fraction - i) * M_PI;
// "ratio" is that distance divided by half the tap count such that it
// reaches π at the window extremes
double ratio = dist / (kFilterSize / 2.0);
double value;
if (dist != 0.0) {
value = sin(dist * kLowPassRatio) / (dist * kLowPassRatio);
// Hann window. We could alternatively use a Blackman Harris window,
// however our unusually small filter size makes the Hann window's
// steeper cutoff more important.
value *= 0.5 * (1.0 + cos(ratio));
} else {
value = 1.0;
}
working_buffer[i] = value;
filter_sum += value;
}
// Filter should have unity DC gain
double scaler = 1.0 / filter_sum;
double error = 0.0;
for (int i = kFilterSize / 2; i < kFilterSize;
i = kFilterSize - i - (i >= kFilterSize / 2)) {
working_buffer[i] *= scaler;
filter[i] = working_buffer[i] - error;
error += static_cast<double>(filter[i]) - working_buffer[i];
}
}
/*
* Performs sub-sampling with interpolation for the given channel. Assumes that
* the channel buffer has already been filled with samples.
*/
auto Resampler::Subsample(int channel) -> float {
cpp::span<float> source{channel_buffers_[channel], channel_buffer_size_};
int offset_integral = std::floor(output_offset_);
source = source.subspan(offset_integral);
float offset_fractional = output_offset_ - offset_integral;
offset_fractional *= kNumFilters;
int filter_index = std::floor(offset_fractional);
float sum1 = ApplyFilter(sFilters[filter_index],
{source.data() - kFilterSize / 2 + 1, kFilterSize});
offset_fractional -= filter_index;
float sum2 = ApplyFilter(sFilters[filter_index + 1],
{source.data() - kFilterSize / 2 + 1, kFilterSize});
return (sum2 * offset_fractional) + (sum1 * (1.0f - offset_fractional));
}
auto Resampler::ApplyFilter(cpp::span<float> filter, cpp::span<float> input)
-> float {
float sum = 0.0;
for (int i = 0; i < kFilterSize; i++) {
sum += filter[i] * input[i];
}
return sum;
}
} // namespace audio
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