| /* |
| * Copyright (c) 2014 The WebRTC project authors. All Rights Reserved. |
| * |
| * Use of this source code is governed by a BSD-style license |
| * that can be found in the LICENSE file in the root of the source |
| * tree. An additional intellectual property rights grant can be found |
| * in the file PATENTS. All contributing project authors may |
| * be found in the AUTHORS file in the root of the source tree. |
| */ |
| |
| #include "modules/audio_processing/rms_level.h" |
| |
| #include <math.h> |
| #include <algorithm> |
| #include <numeric> |
| |
| #include "rtc_base/checks.h" |
| |
| namespace webrtc { |
| namespace { |
| static constexpr float kMaxSquaredLevel = 32768 * 32768; |
| // kMinLevel is the level corresponding to kMinLevelDb, that is 10^(-127/10). |
| static constexpr float kMinLevel = 1.995262314968883e-13f; |
| |
| // Calculates the normalized RMS value from a mean square value. The input |
| // should be the sum of squared samples divided by the number of samples. The |
| // value will be normalized to full range before computing the RMS, wich is |
| // returned as a negated dBfs. That is, 0 is full amplitude while 127 is very |
| // faint. |
| int ComputeRms(float mean_square) { |
| if (mean_square <= kMinLevel * kMaxSquaredLevel) { |
| // Very faint; simply return the minimum value. |
| return RmsLevel::kMinLevelDb; |
| } |
| // Normalize by the max level. |
| const float mean_square_norm = mean_square / kMaxSquaredLevel; |
| RTC_DCHECK_GT(mean_square_norm, kMinLevel); |
| // 20log_10(x^0.5) = 10log_10(x) |
| const float rms = 10.f * log10(mean_square_norm); |
| RTC_DCHECK_LE(rms, 0.f); |
| RTC_DCHECK_GT(rms, -RmsLevel::kMinLevelDb); |
| // Return the negated value. |
| return static_cast<int>(-rms + 0.5f); |
| } |
| } // namespace |
| |
| RmsLevel::RmsLevel() { |
| Reset(); |
| } |
| |
| RmsLevel::~RmsLevel() = default; |
| |
| void RmsLevel::Reset() { |
| sum_square_ = 0.f; |
| sample_count_ = 0; |
| max_sum_square_ = 0.f; |
| block_size_ = absl::nullopt; |
| } |
| |
| void RmsLevel::Analyze(rtc::ArrayView<const int16_t> data) { |
| if (data.empty()) { |
| return; |
| } |
| |
| CheckBlockSize(data.size()); |
| |
| const float sum_square = |
| std::accumulate(data.begin(), data.end(), 0.f, |
| [](float a, int16_t b) { return a + b * b; }); |
| RTC_DCHECK_GE(sum_square, 0.f); |
| sum_square_ += sum_square; |
| sample_count_ += data.size(); |
| |
| max_sum_square_ = std::max(max_sum_square_, sum_square); |
| } |
| |
| void RmsLevel::AnalyzeMuted(size_t length) { |
| CheckBlockSize(length); |
| sample_count_ += length; |
| } |
| |
| int RmsLevel::Average() { |
| int rms = (sample_count_ == 0) ? RmsLevel::kMinLevelDb |
| : ComputeRms(sum_square_ / sample_count_); |
| Reset(); |
| return rms; |
| } |
| |
| RmsLevel::Levels RmsLevel::AverageAndPeak() { |
| // Note that block_size_ should by design always be non-empty when |
| // sample_count_ != 0. Also, the * operator of absl::optional enforces this |
| // with a DCHECK. |
| Levels levels = (sample_count_ == 0) |
| ? Levels{RmsLevel::kMinLevelDb, RmsLevel::kMinLevelDb} |
| : Levels{ComputeRms(sum_square_ / sample_count_), |
| ComputeRms(max_sum_square_ / *block_size_)}; |
| Reset(); |
| return levels; |
| } |
| |
| void RmsLevel::CheckBlockSize(size_t block_size) { |
| if (block_size_ != block_size) { |
| Reset(); |
| block_size_ = block_size; |
| } |
| } |
| } // namespace webrtc |