/*
 *  Copyright (c) 2017 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/aec3/residual_echo_estimator.h"

#include <stddef.h>

#include <algorithm>
#include <vector>

#include "api/array_view.h"
#include "modules/audio_processing/aec3/reverb_model.h"
#include "rtc_base/checks.h"

namespace webrtc {
namespace {

// Computes the indexes that will be used for computing spectral power over
// the blocks surrounding the delay.
void GetRenderIndexesToAnalyze(
    const VectorBuffer& spectrum_buffer,
    const EchoCanceller3Config::EchoModel& echo_model,
    int filter_delay_blocks,
    int* idx_start,
    int* idx_stop) {
  RTC_DCHECK(idx_start);
  RTC_DCHECK(idx_stop);
  size_t window_start;
  size_t window_end;
  window_start =
      std::max(0, filter_delay_blocks -
                      static_cast<int>(echo_model.render_pre_window_size));
  window_end = filter_delay_blocks +
               static_cast<int>(echo_model.render_post_window_size);
  *idx_start = spectrum_buffer.OffsetIndex(spectrum_buffer.read, window_start);
  *idx_stop = spectrum_buffer.OffsetIndex(spectrum_buffer.read, window_end + 1);
}

}  // namespace

ResidualEchoEstimator::ResidualEchoEstimator(const EchoCanceller3Config& config)
    : config_(config) {
  Reset();
}

ResidualEchoEstimator::~ResidualEchoEstimator() = default;

void ResidualEchoEstimator::Estimate(
    const AecState& aec_state,
    const RenderBuffer& render_buffer,
    const std::array<float, kFftLengthBy2Plus1>& S2_linear,
    const std::array<float, kFftLengthBy2Plus1>& Y2,
    std::array<float, kFftLengthBy2Plus1>* R2) {
  RTC_DCHECK(R2);

  // Estimate the power of the stationary noise in the render signal.
  RenderNoisePower(render_buffer, &X2_noise_floor_, &X2_noise_floor_counter_);

  // Estimate the residual echo power.
  if (aec_state.UsableLinearEstimate()) {
    LinearEstimate(S2_linear, aec_state.Erle(), aec_state.ErleUncertainty(),
                   R2);

    // When there is saturated echo, assume the same spectral content as is
    // present in the microphone signal.
    if (aec_state.SaturatedEcho()) {
      std::copy(Y2.begin(), Y2.end(), R2->begin());
    }

    // Adds the estimated unmodelled echo power to the residual echo power
    // estimate.
    echo_reverb_.AddReverb(
        render_buffer.Spectrum(aec_state.FilterLengthBlocks() + 1),
        aec_state.GetReverbFrequencyResponse(), aec_state.ReverbDecay(), *R2);
  } else {
    // Estimate the echo generating signal power.
    std::array<float, kFftLengthBy2Plus1> X2;

    EchoGeneratingPower(render_buffer.GetSpectrumBuffer(), config_.echo_model,
                        aec_state.FilterDelayBlocks(),
                        !aec_state.UseStationaryProperties(), &X2);

    // Subtract the stationary noise power to avoid stationary noise causing
    // excessive echo suppression.
    std::transform(X2.begin(), X2.end(), X2_noise_floor_.begin(), X2.begin(),
                   [&](float a, float b) {
                     return std::max(
                         0.f, a - config_.echo_model.stationary_gate_slope * b);
                   });

    float echo_path_gain;
    echo_path_gain =
        aec_state.TransparentMode() ? 0.01f : config_.ep_strength.default_gain;
    NonLinearEstimate(echo_path_gain, X2, R2);

    // When there is saturated echo, assume the same spectral content as is
    // present in the microphone signal.
    if (aec_state.SaturatedEcho()) {
      std::copy(Y2.begin(), Y2.end(), R2->begin());
    }

    if (!(aec_state.TransparentMode())) {
      echo_reverb_.AddReverbNoFreqShaping(
          render_buffer.Spectrum(aec_state.FilterDelayBlocks() + 1),
          echo_path_gain * echo_path_gain, aec_state.ReverbDecay(), *R2);
    }
  }

  if (aec_state.UseStationaryProperties()) {
    // Scale the echo according to echo audibility.
    std::array<float, kFftLengthBy2Plus1> residual_scaling;
    aec_state.GetResidualEchoScaling(residual_scaling);
    for (size_t k = 0; k < R2->size(); ++k) {
      (*R2)[k] *= residual_scaling[k];
    }
  }
}

void ResidualEchoEstimator::Reset() {
  echo_reverb_.Reset();
  X2_noise_floor_counter_.fill(config_.echo_model.noise_floor_hold);
  X2_noise_floor_.fill(config_.echo_model.min_noise_floor_power);
}

void ResidualEchoEstimator::LinearEstimate(
    const std::array<float, kFftLengthBy2Plus1>& S2_linear,
    const std::array<float, kFftLengthBy2Plus1>& erle,
    absl::optional<float> erle_uncertainty,
    std::array<float, kFftLengthBy2Plus1>* R2) {
  if (erle_uncertainty) {
    for (size_t k = 0; k < R2->size(); ++k) {
      (*R2)[k] = S2_linear[k] * *erle_uncertainty;
    }
  } else {
    std::transform(erle.begin(), erle.end(), S2_linear.begin(), R2->begin(),
                   [](float a, float b) {
                     RTC_DCHECK_LT(0.f, a);
                     return b / a;
                   });
  }
}

void ResidualEchoEstimator::NonLinearEstimate(
    float echo_path_gain,
    const std::array<float, kFftLengthBy2Plus1>& X2,
    std::array<float, kFftLengthBy2Plus1>* R2) {
  // Compute preliminary residual echo.
  std::transform(X2.begin(), X2.end(), R2->begin(), [echo_path_gain](float a) {
    return a * echo_path_gain * echo_path_gain;
  });
}

void ResidualEchoEstimator::EchoGeneratingPower(
    const VectorBuffer& spectrum_buffer,
    const EchoCanceller3Config::EchoModel& echo_model,
    int filter_delay_blocks,
    bool apply_noise_gating,
    std::array<float, kFftLengthBy2Plus1>* X2) const {
  int idx_stop, idx_start;

  RTC_DCHECK(X2);
  GetRenderIndexesToAnalyze(spectrum_buffer, config_.echo_model,
                            filter_delay_blocks, &idx_start, &idx_stop);

  X2->fill(0.f);
  for (int k = idx_start; k != idx_stop; k = spectrum_buffer.IncIndex(k)) {
    std::transform(X2->begin(), X2->end(), spectrum_buffer.buffer[k].begin(),
                   X2->begin(),
                   [](float a, float b) { return std::max(a, b); });
  }

  if (apply_noise_gating) {
    // Apply soft noise gate.
    std::for_each(X2->begin(), X2->end(), [&](float& a) {
      if (config_.echo_model.noise_gate_power > a) {
        a = std::max(0.f, a - config_.echo_model.noise_gate_slope *
                                  (config_.echo_model.noise_gate_power - a));
      }
    });
  }
}

void ResidualEchoEstimator::RenderNoisePower(
    const RenderBuffer& render_buffer,
    std::array<float, kFftLengthBy2Plus1>* X2_noise_floor,
    std::array<int, kFftLengthBy2Plus1>* X2_noise_floor_counter) const {
  RTC_DCHECK(X2_noise_floor);
  RTC_DCHECK(X2_noise_floor_counter);

  const auto render_power = render_buffer.Spectrum(0);
  RTC_DCHECK_EQ(X2_noise_floor->size(), render_power.size());
  RTC_DCHECK_EQ(X2_noise_floor_counter->size(), render_power.size());

  // Estimate the stationary noise power in a minimum statistics manner.
  for (size_t k = 0; k < render_power.size(); ++k) {
    // Decrease rapidly.
    if (render_power[k] < (*X2_noise_floor)[k]) {
      (*X2_noise_floor)[k] = render_power[k];
      (*X2_noise_floor_counter)[k] = 0;
    } else {
      // Increase in a delayed, leaky manner.
      if ((*X2_noise_floor_counter)[k] >=
          static_cast<int>(config_.echo_model.noise_floor_hold)) {
        (*X2_noise_floor)[k] =
            std::max((*X2_noise_floor)[k] * 1.1f,
                     config_.echo_model.min_noise_floor_power);
      } else {
        ++(*X2_noise_floor_counter)[k];
      }
    }
  }
}

}  // namespace webrtc