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/*
* Copyright (C) 2013 Google Inc. All rights reserved.
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*
* THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS
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#include "third_party/blink/renderer/platform/audio/down_sampler.h"
#include <memory>
#include "third_party/blink/renderer/platform/wtf/math_extras.h"
namespace blink {
namespace {
// Computes ideal band-limited half-band filter coefficients.
// In other words, filter out all frequencies higher than 0.25 * Nyquist.
std::unique_ptr<AudioFloatArray> MakeReducedKernel(size_t size) {
auto reduced_kernel = std::make_unique<AudioFloatArray>(size / 2);
// Blackman window parameters.
double alpha = 0.16;
double a0 = 0.5 * (1.0 - alpha);
double a1 = 0.5;
double a2 = 0.5 * alpha;
int n = size;
int half_size = n / 2;
// Half-band filter.
double sinc_scale_factor = 0.5;
// Compute only the odd terms because the even ones are zero, except right in
// the middle at halfSize, which is 0.5 and we'll handle specially during
// processing after doing the main convolution using m_reducedKernel.
for (int i = 1; i < n; i += 2) {
// Compute the sinc() with offset.
double s = sinc_scale_factor * kPiDouble * (i - half_size);
double sinc = !s ? 1.0 : sin(s) / s;
sinc *= sinc_scale_factor;
// Compute Blackman window, matching the offset of the sinc().
double x = static_cast<double>(i) / n;
double window =
a0 - a1 * cos(kTwoPiDouble * x) + a2 * cos(kTwoPiDouble * 2.0 * x);
// Window the sinc() function.
// Then store only the odd terms in the kernel.
// In a sense, this is shifting forward in time by one sample-frame at the
// destination sample-rate.
(*reduced_kernel)[(i - 1) / 2] = sinc * window;
}
return reduced_kernel;
}
} // namespace
DownSampler::DownSampler(size_t input_block_size)
: input_block_size_(input_block_size),
convolver_(input_block_size / 2, // runs at 1/2 source sample-rate
MakeReducedKernel(kDefaultKernelSize)),
temp_buffer_(input_block_size / 2),
input_buffer_(input_block_size * 2) {}
void DownSampler::Process(const float* source_p,
float* dest_p,
size_t source_frames_to_process) {
bool is_input_block_size_good = source_frames_to_process == input_block_size_;
DCHECK(is_input_block_size_good);
if (!is_input_block_size_good)
return;
size_t dest_frames_to_process = source_frames_to_process / 2;
bool is_temp_buffer_good = dest_frames_to_process == temp_buffer_.size();
DCHECK(is_temp_buffer_good);
if (!is_temp_buffer_good)
return;
bool is_reduced_kernel_good =
convolver_.ConvolutionKernelSize() == kDefaultKernelSize / 2;
DCHECK(is_reduced_kernel_good);
if (!is_reduced_kernel_good)
return;
size_t half_size = kDefaultKernelSize / 2;
// Copy source samples to 2nd half of input buffer.
bool is_input_buffer_good =
input_buffer_.size() == source_frames_to_process * 2 &&
half_size <= source_frames_to_process;
DCHECK(is_input_buffer_good);
if (!is_input_buffer_good)
return;
float* input_p = input_buffer_.Data() + source_frames_to_process;
memcpy(input_p, source_p, sizeof(float) * source_frames_to_process);
// Copy the odd sample-frames from sourceP, delayed by one sample-frame
// (destination sample-rate) to match shifting forward in time in
// m_reducedKernel.
float* odd_samples_p = temp_buffer_.Data();
for (unsigned i = 0; i < dest_frames_to_process; ++i)
odd_samples_p[i] = *((input_p - 1) + i * 2);
// Actually process oddSamplesP with m_reducedKernel for efficiency.
// The theoretical kernel is double this size with 0 values for even terms
// (except center).
convolver_.Process(odd_samples_p, dest_p, dest_frames_to_process);
// Now, account for the 0.5 term right in the middle of the kernel.
// This amounts to a delay-line of length halfSize (at the source
// sample-rate), scaled by 0.5.
// Sum into the destination.
for (unsigned i = 0; i < dest_frames_to_process; ++i)
dest_p[i] += 0.5 * *((input_p - half_size) + i * 2);
// Copy 2nd half of input buffer to 1st half.
memcpy(input_buffer_.Data(), input_p,
sizeof(float) * source_frames_to_process);
}
void DownSampler::Reset() {
convolver_.Reset();
input_buffer_.Zero();
}
size_t DownSampler::LatencyFrames() const {
// Divide by two since this is a linear phase kernel and the delay is at the
// center of the kernel.
return convolver_.ConvolutionKernelSize() / 2;
}
} // namespace blink