cos / mirrors / cros / chromiumos / third_party / webrtc-apm / refs/heads/stabilize-13597.69.B / . / modules / audio_coding / neteq / histogram.cc

/* | |

* Copyright (c) 2019 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 <algorithm> | |

#include <numeric> | |

#include "modules/audio_coding/neteq/histogram.h" | |

#include "rtc_base/checks.h" | |

#include "rtc_base/numerics/safe_conversions.h" | |

namespace webrtc { | |

Histogram::Histogram(size_t num_buckets, int forget_factor) | |

: buckets_(num_buckets, 0), | |

forget_factor_(0), | |

base_forget_factor_(forget_factor) {} | |

Histogram::~Histogram() {} | |

// Each element in the vector is first multiplied by the forgetting factor | |

// |forget_factor_|. Then the vector element indicated by |iat_packets| is then | |

// increased (additive) by 1 - |forget_factor_|. This way, the probability of | |

// |iat_packets| is slightly increased, while the sum of the histogram remains | |

// constant (=1). | |

// Due to inaccuracies in the fixed-point arithmetic, the histogram may no | |

// longer sum up to 1 (in Q30) after the update. To correct this, a correction | |

// term is added or subtracted from the first element (or elements) of the | |

// vector. | |

// The forgetting factor |forget_factor_| is also updated. When the DelayManager | |

// is reset, the factor is set to 0 to facilitate rapid convergence in the | |

// beginning. With each update of the histogram, the factor is increased towards | |

// the steady-state value |kIatFactor_|. | |

void Histogram::Add(int value) { | |

RTC_DCHECK(value >= 0); | |

RTC_DCHECK(value < static_cast<int>(buckets_.size())); | |

int vector_sum = 0; // Sum up the vector elements as they are processed. | |

// Multiply each element in |buckets_| with |forget_factor_|. | |

for (int& bucket : buckets_) { | |

bucket = (static_cast<int64_t>(bucket) * forget_factor_) >> 15; | |

vector_sum += bucket; | |

} | |

// Increase the probability for the currently observed inter-arrival time | |

// by 1 - |forget_factor_|. The factor is in Q15, |buckets_| in Q30. | |

// Thus, left-shift 15 steps to obtain result in Q30. | |

buckets_[value] += (32768 - forget_factor_) << 15; | |

vector_sum += (32768 - forget_factor_) << 15; // Add to vector sum. | |

// |buckets_| should sum up to 1 (in Q30), but it may not due to | |

// fixed-point rounding errors. | |

vector_sum -= 1 << 30; // Should be zero. Compensate if not. | |

if (vector_sum != 0) { | |

// Modify a few values early in |buckets_|. | |

int flip_sign = vector_sum > 0 ? -1 : 1; | |

for (int& bucket : buckets_) { | |

// Add/subtract 1/16 of the element, but not more than |vector_sum|. | |

int correction = flip_sign * std::min(abs(vector_sum), bucket >> 4); | |

bucket += correction; | |

vector_sum += correction; | |

if (abs(vector_sum) == 0) { | |

break; | |

} | |

} | |

} | |

RTC_DCHECK(vector_sum == 0); // Verify that the above is correct. | |

// Update |forget_factor_| (changes only during the first seconds after a | |

// reset). The factor converges to |base_forget_factor_|. | |

forget_factor_ += (base_forget_factor_ - forget_factor_ + 3) >> 2; | |

} | |

int Histogram::Quantile(int probability) { | |

// Find the bucket for which the probability of observing an | |

// inter-arrival time larger than or equal to |index| is larger than or | |

// equal to |probability|. The sought probability is estimated using | |

// the histogram as the reverse cumulant PDF, i.e., the sum of elements from | |

// the end up until |index|. Now, since the sum of all elements is 1 | |

// (in Q30) by definition, and since the solution is often a low value for | |

// |iat_index|, it is more efficient to start with |sum| = 1 and subtract | |

// elements from the start of the histogram. | |

int inverse_probability = (1 << 30) - probability; | |

size_t index = 0; // Start from the beginning of |buckets_|. | |

int sum = 1 << 30; // Assign to 1 in Q30. | |

sum -= buckets_[index]; // Ensure that target level is >= 1. | |

do { | |

// Subtract the probabilities one by one until the sum is no longer greater | |

// than |inverse_probability|. | |

++index; | |

sum -= buckets_[index]; | |

} while ((sum > inverse_probability) && (index < buckets_.size() - 1)); | |

return static_cast<int>(index); | |

} | |

// Set the histogram vector to an exponentially decaying distribution | |

// buckets_[i] = 0.5^(i+1), i = 0, 1, 2, ... | |

// buckets_ is in Q30. | |

void Histogram::Reset() { | |

// Set temp_prob to (slightly more than) 1 in Q14. This ensures that the sum | |

// of buckets_ is 1. | |

uint16_t temp_prob = 0x4002; // 16384 + 2 = 100000000000010 binary. | |

for (int& bucket : buckets_) { | |

temp_prob >>= 1; | |

bucket = temp_prob << 16; | |

} | |

forget_factor_ = 0; // Adapt the histogram faster for the first few packets. | |

} | |

int Histogram::NumBuckets() const { | |

return buckets_.size(); | |

} | |

void Histogram::Scale(int old_bucket_width, int new_bucket_width) { | |

buckets_ = ScaleBuckets(buckets_, old_bucket_width, new_bucket_width); | |

} | |

std::vector<int> Histogram::ScaleBuckets(const std::vector<int>& buckets, | |

int old_bucket_width, | |

int new_bucket_width) { | |

RTC_DCHECK_GT(old_bucket_width, 0); | |

RTC_DCHECK_GT(new_bucket_width, 0); | |

RTC_DCHECK_EQ(old_bucket_width % 10, 0); | |

RTC_DCHECK_EQ(new_bucket_width % 10, 0); | |

std::vector<int> new_histogram(buckets.size(), 0); | |

int64_t acc = 0; | |

int time_counter = 0; | |

size_t new_histogram_idx = 0; | |

for (size_t i = 0; i < buckets.size(); i++) { | |

acc += buckets[i]; | |

time_counter += old_bucket_width; | |

// The bins should be scaled, to ensure the histogram still sums to one. | |

const int64_t scaled_acc = acc * new_bucket_width / time_counter; | |

int64_t actually_used_acc = 0; | |

while (time_counter >= new_bucket_width) { | |

const int64_t old_histogram_val = new_histogram[new_histogram_idx]; | |

new_histogram[new_histogram_idx] = | |

rtc::saturated_cast<int>(old_histogram_val + scaled_acc); | |

actually_used_acc += new_histogram[new_histogram_idx] - old_histogram_val; | |

new_histogram_idx = | |

std::min(new_histogram_idx + 1, new_histogram.size() - 1); | |

time_counter -= new_bucket_width; | |

} | |

// Only subtract the part that was succesfully written to the new histogram. | |

acc -= actually_used_acc; | |

} | |

// If there is anything left in acc (due to rounding errors), add it to the | |

// last bin. If we cannot add everything to the last bin we need to add as | |

// much as possible to the bins after the last bin (this is only possible | |

// when compressing a histogram). | |

while (acc > 0 && new_histogram_idx < new_histogram.size()) { | |

const int64_t old_histogram_val = new_histogram[new_histogram_idx]; | |

new_histogram[new_histogram_idx] = | |

rtc::saturated_cast<int>(old_histogram_val + acc); | |

acc -= new_histogram[new_histogram_idx] - old_histogram_val; | |

new_histogram_idx++; | |

} | |

RTC_DCHECK_EQ(buckets.size(), new_histogram.size()); | |

if (acc == 0) { | |

// If acc is non-zero, we were not able to add everything to the new | |

// histogram, so this check will not hold. | |

RTC_DCHECK_EQ(accumulate(buckets.begin(), buckets.end(), 0ll), | |

accumulate(new_histogram.begin(), new_histogram.end(), 0ll)); | |

} | |

return new_histogram; | |

} | |

} // namespace webrtc |