/* bitAllocation.cpp - source file for class needed for psychoacoustic bit-allocation
 * written by C. R. Helmrich, last modified in 2021 - see License.htm for legal notices
 *
 * The copyright in this software is being made available under the exhale Copyright License
 * and comes with ABSOLUTELY NO WARRANTY. This software may be subject to other third-
 * party rights, including patent rights. No such rights are granted under this License.
 *
 * Copyright (c) 2018-2021 Christian R. Helmrich, project ecodis. All rights reserved.
 */

#include "exhaleLibPch.h"
#include "bitAllocation.h"

// static helper functions
static inline uint32_t intSqrt (const uint32_t val)
{
  return uint32_t (0.5 + sqrt ((double) val));
}

static inline uint32_t jndModel (const uint32_t val, const uint32_t mean,
                                 const unsigned expTimes512, const unsigned mulTimes512)
{
  const double exp = (double) expTimes512 / 512.0; // exponent
  const double mul = (double) mulTimes512 / 512.0; // a factor
  const double res = pow (mul * (double) val, exp) * pow ((double) mean, 1.0 - exp);

  return uint32_t (__min ((double) UINT_MAX, res + 0.5));
}

static inline uint32_t squareMeanRoot (const uint32_t value1, const uint32_t value2)
{
  const double meanRoot = (sqrt ((double) value1) + sqrt ((double) value2)) * 0.5;

  return uint32_t (meanRoot * meanRoot + 0.5);
}

static void jndPowerLawAndPeakSmoothing (uint32_t* const  stepSizes, const unsigned nStepSizes, const bool lowRateMode,
                                         const uint32_t avgStepSize, const uint8_t sfm, const uint8_t tfm)
{
  const unsigned  expTimes512 = 512u - sfm; // 1.0 - sfm / 2.0
  const unsigned  mulTimes512 = __min (expTimes512, 512u - tfm);
  uint32_t         stepSizeM3 = 0, stepSizeM2 = 0, stepSizeM1 = BA_EPS; // hearing threshold around zero Hz
  unsigned b;

  for (b = 0; b < __min (2, nStepSizes); b++)
  {
    stepSizeM3 = stepSizeM2;
    stepSizeM2 = stepSizeM1;
    stepSizeM1 = stepSizes[b] = jndModel (stepSizes[b], avgStepSize, expTimes512, mulTimes512);
  }
  stepSizes[0] = __min (stepSizeM1, stepSizes[0]); // `- becomes --
  for (/*b*/; b < nStepSizes; b++)
  {
    const uint64_t modifiedB = (lowRateMode ? 16 + b : b);
    const uint64_t oneMinusB = 128 - modifiedB;
    const uint32_t stepSizeB = jndModel (stepSizes[b], avgStepSize, expTimes512, mulTimes512);

    if ((stepSizeM3 <= stepSizeM2) && (stepSizeM3 <= stepSizeM1) && (stepSizeB <= stepSizeM2) && (stepSizeB <= stepSizeM1))
    {
      const uint32_t maxM3M0 = __max (stepSizeM3, stepSizeB); // smoothen local spectral peak of _´`- shape

      stepSizes[b - 2] = uint32_t ((modifiedB * stepSizes[b - 2] + oneMinusB * __min (maxM3M0, stepSizes[b - 2]) + 64) >> 7); // _-`-
      stepSizes[b - 1] = uint32_t ((modifiedB * stepSizes[b - 1] + oneMinusB * __min (maxM3M0, stepSizes[b - 1]) + 64) >> 7); // _---
    }
    stepSizeM3 = stepSizeM2;
    stepSizeM2 = stepSizeM1;
    stepSizeM1 = (stepSizes[b] = stepSizeB); // modified step-size may be smoothened in next loop iteration
  }
}

// constructor
BitAllocator::BitAllocator ()
{
  for (unsigned ch = 0; ch < USAC_MAX_NUM_CHANNELS; ch++)
  {
    m_avgStepSize[ch] = 0;
    m_avgSpecFlat[ch] = 0;
    m_avgTempFlat[ch] = 0;
  }
  m_rateIndex    = 0;
  m_tempSfbValue = nullptr;
  m_tnsPredictor = nullptr;
}

// public functions
void BitAllocator::getChAverageSpecFlat (uint8_t meanSpecFlatInCh[USAC_MAX_NUM_CHANNELS], const unsigned nChannels)
{
  if ((meanSpecFlatInCh == nullptr) || (nChannels > USAC_MAX_NUM_CHANNELS))
  {
    return;
  }
  memcpy (meanSpecFlatInCh, m_avgSpecFlat, nChannels * sizeof (uint8_t));
}

void BitAllocator::getChAverageTempFlat (uint8_t meanTempFlatInCh[USAC_MAX_NUM_CHANNELS], const unsigned nChannels)
{
  if ((meanTempFlatInCh == nullptr) || (nChannels > USAC_MAX_NUM_CHANNELS))
  {
    return;
  }
  memcpy (meanTempFlatInCh, m_avgTempFlat, nChannels * sizeof (uint8_t));
}

uint16_t BitAllocator::getRateCtrlFac (const int32_t rateRatio, const unsigned samplingRate, const uint32_t specFlatness,
                                       const bool prevEightShorts /*= false*/)
{
#if BA_MORE_CBR
  const int32_t ratioFac = rateRatio * (40 - 5 * m_rateIndex);
  const uint32_t brRatio = __max ((prevEightShorts ? (ratioFac * ratioFac + (1 << 16)) >> 17 : 0) - SHRT_MIN, __min (USHRT_MAX, ratioFac)) -
                           (m_rateIndex == 2 ? 1 << 12 : 0);  // rate tuning
  const uint16_t mSfmSqr = (m_rateIndex <= 2 && samplingRate >= 27713 ? (specFlatness * specFlatness) >> m_rateIndex : 0);
#else
  const uint32_t brRatio = __max (1 << 15, __min ((1 << 16) - 1, rateRatio * (36 - 9 * m_rateIndex)));
  const uint16_t mSfmSqr = (m_rateIndex < 2 && samplingRate >= 27713 ? (specFlatness * specFlatness) >> m_rateIndex : 0);
#endif
  const uint16_t mSfmFac = 256 - (((32 + m_rateIndex) * (specFlatness << 4) - mSfmSqr + (1 << 9)) >> 10);

  return uint16_t ((brRatio * mSfmFac + (1 << 7)) >> 8);
}

uint8_t BitAllocator::getScaleFac (const uint32_t sfbStepSize, const int32_t* const sfbSignal, const uint8_t sfbWidth,
                                   const uint32_t sfbRmsValue)
{
  uint8_t sf;
  uint32_t u;
#if !RESTRICT_TO_AAC
  uint64_t meanSpecLoudness = 0;
  double d;
#endif

  if ((sfbSignal == nullptr) || (sfbWidth == 0) || (sfbRmsValue < 46))
  {
    return 0; // use lowest scale factor
  }
#if RESTRICT_TO_AAC
  u = 0;
  for (sf = 0; sf < sfbWidth; sf++)
  {
    u += intSqrt (abs (sfbSignal[sf]));
  }
  u = uint32_t ((u * 16384ui64 + (sfbWidth >> 1)) / sfbWidth);
  u = uint32_t (0.5 + sqrt ((double) u) * 128.0);

  if (u < 42567) return 0;

  u = uint32_t ((sfbStepSize * 42567ui64 + (u >> 1)) / u);
  sf = (u > 1 ? uint8_t (0.5 + 17.7169498394 * log10 ((double) u)) : 4);
#else
  for (sf = 0; sf < sfbWidth; sf++) // simple, low-complexity derivation method for USAC's arithmetic coder
  {
    const int64_t temp = ((int64_t) sfbSignal[sf] + 8) >> 4; // avoid overflow

    meanSpecLoudness += temp * temp;
  }
  meanSpecLoudness = uint64_t (0.5 + pow (256.0 * (double) meanSpecLoudness / sfbWidth, 0.25));

  u = uint32_t (0.5 + pow ((double) sfbRmsValue, 0.75) * 256.0);    // u = 2^8 * (sfbRmsValue^0.75)
  u = uint32_t ((meanSpecLoudness * sfbStepSize * 665 + (u >> 1)) / u); // u = sqrt(6.75) * m*thr/u
  d =  (u > 1 ? log10 ((double) u) : 0.25);

  u = uint32_t (0.5 + pow ((double) sfbRmsValue, 0.25) * 16384.0); // u = 2^14 * (sfbRmsValue^0.25)
  u = uint32_t (((uint64_t) sfbStepSize * 42567 + (u >> 1)) / u);         // u = sqrt(6.75) * thr/u
  d += (u > 1 ? log10 ((double) u) : 0.25);

  sf = uint8_t (0.5 + 8.8584749197 * d);  // sf = (8/3) * log2(u1*u2) = (8/3) * (log2(u1)+log2(u2))
#endif

  return __min (SCHAR_MAX, sf);
}

unsigned BitAllocator::initAllocMemory (LinearPredictor* const linPredictor, const uint8_t numSwb, const uint8_t bitRateMode)
{
  if (linPredictor == nullptr)
  {
    return 1; // invalid arguments error
  }
  m_rateIndex    = bitRateMode;
  m_tnsPredictor = linPredictor;

  if ((m_tempSfbValue = (uint8_t*) malloc (__max (MAX_PREDICTION_ORDER * sizeof (short), numSwb) * sizeof (uint8_t))) == nullptr)
  {
    return 2; // memory allocation error
  }

  return 0; // no error
}

unsigned BitAllocator::initSfbStepSizes (const SfbGroupData* const groupData[USAC_MAX_NUM_CHANNELS], const uint8_t numSwbShort,
                                         const uint32_t specAnaStats[USAC_MAX_NUM_CHANNELS],
                                         const uint32_t tempAnaStats[USAC_MAX_NUM_CHANNELS],
                                         const unsigned nChannels, const unsigned samplingRate, uint32_t* const sfbStepSizes,
                                         const unsigned lfeChannelIndex /*= USAC_MAX_NUM_CHANNELS*/, const bool tnsDisabled /*= false*/)
{
  // equal-loudness weighting based on data from: K. Kurakata, T. Mizunami, and K. Matsushita, "Percentiles
  // of Normal Hearing-Threshold Distribution Under Free-Field Listening Conditions in Numerical Form," Ac.
  // Sci. Tech, vol. 26, no. 5, pp. 447-449, Jan. 2005, https://www.researchgate.net/publication/239433096.
  const unsigned HF/*idx*/= ((123456 - samplingRate) >> 11) + (samplingRate < 37566 ? 2 : 0);  // start SFB
  const unsigned LF/*idx*/= 9;
  const unsigned MF/*idx*/= (samplingRate < 27713 ? HF : __min (HF, 30u));
  const unsigned msShift  = (samplingRate + 36736) >> 15; // TODO: 768 smp
  const unsigned msOffset = 1 << (msShift - 1);
  uint32_t nMeans = 0, sumMeans = 0;

  if ((groupData == nullptr) || (specAnaStats == nullptr) || (tempAnaStats == nullptr) || (sfbStepSizes == nullptr) ||
      (numSwbShort < MIN_NUM_SWB_SHORT) || (numSwbShort > MAX_NUM_SWB_SHORT) || (nChannels > USAC_MAX_NUM_CHANNELS) ||
      (samplingRate < 7350) || (samplingRate > 96000) || (lfeChannelIndex > USAC_MAX_NUM_CHANNELS))
  {
    return 1; // invalid arguments error
  }

  for (unsigned ch = 0; ch < nChannels; ch++)
  {
    const SfbGroupData& grpData = *groupData[ch];
    const uint32_t maxSfbInCh = __min (MAX_NUM_SWB_LONG, grpData.sfbsPerGroup);
    const uint32_t nBandsInCh = grpData.numWindowGroups * maxSfbInCh;
    const uint32_t*   rms = grpData.sfbRmsValues;
    uint32_t*   stepSizes = &sfbStepSizes[ch * numSwbShort * NUM_WINDOW_GROUPS];
// --- apply INTRA-channel simultaneous masking, equal-loudness weighting, and thresholding to SFB RMS data
    uint32_t maskingSlope = 0, gr, b, elw = 58254; // 8/9
    uint32_t rmsEqualLoud = 0;
    uint32_t sumStepSizes = 0;

    m_avgStepSize[ch] = 0;

    b = ((specAnaStats[ch] >> 16) & UCHAR_MAX);
    b = __max (b * b, (tempAnaStats[ch] >> 24) * (tempAnaStats[ch] >> 24));
    m_avgSpecFlat[ch] = uint8_t ((b + (1 << 7)) >> 8); // max. of squared SFM from spec. and temp. analysis

    b = ((tempAnaStats[ch] >> 16) & UCHAR_MAX);
    b = __max (b * b, (specAnaStats[ch] >> 24) * (specAnaStats[ch] >> 24));
    m_avgTempFlat[ch] = uint8_t ((b + (1 << 7)) >> 8); // max. of squared TFM from spec. and temp. analysis

    if ((nBandsInCh == 0) || (grpData.numWindowGroups > NUM_WINDOW_GROUPS))
    {
      continue;
    }
    if ((ch == lfeChannelIndex) || (grpData.numWindowGroups != 1)) // LFE, SHORT windows: no masking or ELW
    {
      for (gr = 0; gr < grpData.numWindowGroups; gr++)
      {
        const uint32_t* gRms = &rms[numSwbShort * gr];
        uint32_t* gStepSizes = &stepSizes[numSwbShort * gr];

        for (b = numSwbShort - 1; b >= maxSfbInCh; b--)
        {
          gStepSizes[b] = 0;
        }
        for (/*b*/; b > 0; b--)
        {
          gStepSizes[b] = __max (gRms[b], BA_EPS);
          sumStepSizes += intSqrt (gStepSizes[b]);
        }
        gStepSizes[0]   = __max (gRms[0], BA_EPS);
        sumStepSizes   += intSqrt (gStepSizes[0]);
      } // for gr

      if (ch != lfeChannelIndex)
      {
// --- SHORT windows: apply perceptual just noticeable difference (JND) model and local band-peak smoothing
        nMeans++;

        for (b = maxSfbInCh - 1; b > 0; b--) // gentle temporal band-peak smoothing; a spectral one follows
        {
          uint32_t maxGrpStep = stepSizes[b], stepSizeM1 = BA_EPS;

          for (gr = 1; gr < grpData.numWindowGroups; gr++)
          {
            const uint32_t curGrpStep = stepSizes[b + numSwbShort * gr];

            if (curGrpStep > maxGrpStep) maxGrpStep = curGrpStep;
          }
          for (gr = 0; gr < grpData.numWindowGroups; gr++)
          {
            const uint32_t newGrpStep = __max (stepSizeM1, (gr + 1 == grpData.numWindowGroups ? BA_EPS : stepSizes[b + numSwbShort * (gr + 1)]));

            stepSizeM1 = stepSizes[b + numSwbShort * gr];

            if ((stepSizeM1 == maxGrpStep) && (maxGrpStep > newGrpStep))
            {
              const uint32_t sqrtOldStep = intSqrt (maxGrpStep);
              const uint32_t sqrtNewStep = intSqrt (newGrpStep);
              uint32_t& gStepSize = stepSizes[b + numSwbShort * gr];

              sumStepSizes += (gStepSize = (sqrtOldStep + sqrtNewStep) >> 1) - sqrtOldStep;
              gStepSize *= gStepSize; // for square-mean-root
            }
          }
        } // for b

        m_avgStepSize[ch] = __min (USHRT_MAX, (sumStepSizes + (nBandsInCh >> 1)) / nBandsInCh);
        sumMeans += m_avgStepSize[ch];
        m_avgStepSize[ch] *= m_avgStepSize[ch];

        for (gr = 0; gr < grpData.numWindowGroups; gr++) // separate spectral peak smoothing for each group
        {
          jndPowerLawAndPeakSmoothing (&stepSizes[numSwbShort * gr], maxSfbInCh, false,
                                       m_avgStepSize[ch], m_avgSpecFlat[ch], 0);
        }
      }
      continue;
    }

    stepSizes[0]   = __max (rms[0], BA_EPS);
    for (b = 1; b < __min (LF, maxSfbInCh); b++) // apply steeper low-frequency simultaneous masking slopes
    {
      maskingSlope = (stepSizes[b - 1] + (msOffset << (9u - b))) >> (msShift + 9u - b);
      stepSizes[b] = __max (rms[b], maskingSlope + BA_EPS);
    }
    for (/*b*/; b < __min (MF, maxSfbInCh); b++) // apply typical mid-frequency simultaneous masking slopes
    {
      maskingSlope = (stepSizes[b - 1] + msOffset) >> msShift;
      stepSizes[b] = __max (rms[b], maskingSlope + BA_EPS);
    }
    if ((samplingRate >= 27713) && (samplingRate < 75132))
    {
      for (/*b*/; b < __min (HF, maxSfbInCh); b++) // compensate high-frequency slopes for linear SFB width
      {
        maskingSlope = ((uint64_t) stepSizes[b - 1] * (9u + b - MF) + (msOffset << 3u)) >> (msShift + 3u);
        stepSizes[b] = __max (rms[b], maskingSlope + BA_EPS);
      }
      for (/*b = HF region*/; b < maxSfbInCh; b++) // apply extra high-frequency equal-loudness attenuation
      {
        for (unsigned d = b - HF; d > 0; d--)
        {
          elw = (elw * 52430 - SHRT_MIN) >> 16; // elw *= 4/5
        }
        rmsEqualLoud = uint32_t (((uint64_t) rms[b] * elw - SHRT_MIN) >> 16);   // equal loudness weighting
        maskingSlope = ((uint64_t) stepSizes[b - 1] * (9u + b - MF) + (msOffset << 3u)) >> (msShift + 3u);
        stepSizes[b] = __max (rmsEqualLoud, maskingSlope + BA_EPS);
      }
    }
    else // no equal-loudness weighting for low or high rates
    {
      for (/*b = MF region*/; b < maxSfbInCh; b++) // compensate high-frequency slopes for linear SFB width
      {
        maskingSlope = ((uint64_t) stepSizes[b - 1] * (9u + b - MF) + (msOffset << 3u)) >> (msShift + 3u);
        stepSizes[b] = __max (rms[b], maskingSlope + BA_EPS);
      }
    }
    stepSizes[b] = 0;
    for (b -= 1; b > __min (MF, maxSfbInCh); b--) // complete simultaneous masking by reversing the pattern
    {
      sumStepSizes += intSqrt (stepSizes[b]);
      maskingSlope     = ((uint64_t) stepSizes[b] * (8u + b - MF) + (msOffset << 3u)) >> (msShift + 3u);
      stepSizes[b - 1] = __max (stepSizes[b - 1], maskingSlope);
    }
    for (/*b*/; b > __min (LF, maxSfbInCh); b--)  // typical reversed mid-freq. simultaneous masking slopes
    {
      sumStepSizes += intSqrt (stepSizes[b]);
      maskingSlope     = (stepSizes[b] + msOffset) >> msShift;
      stepSizes[b - 1] = __max (stepSizes[b - 1], maskingSlope);
    }
    for (/*b = min (9, maxSfbInCh)*/; b > 0; b--) // steeper reversed low-freq. simultaneous masking slopes
    {
      sumStepSizes += intSqrt (stepSizes[b]);
      maskingSlope     = (stepSizes[b] + (msOffset << (10u - b))) >> (msShift + 10u - b);
      stepSizes[b - 1] = __max (stepSizes[b - 1], maskingSlope);
    }
    sumStepSizes   += intSqrt (stepSizes[0]);

// --- LONG window: apply perceptual JND model and local band-peak smoothing, undo equal-loudness weighting
    nMeans++;
    m_avgStepSize[ch] = __min (USHRT_MAX, (sumStepSizes + (nBandsInCh >> 1)) / nBandsInCh);
    sumMeans += m_avgStepSize[ch];
    m_avgStepSize[ch] *= m_avgStepSize[ch];

    jndPowerLawAndPeakSmoothing (stepSizes, maxSfbInCh, (m_rateIndex == 0) && (samplingRate >= 27713),
                                 m_avgStepSize[ch], m_avgSpecFlat[ch], tnsDisabled ? m_avgTempFlat[ch] : 0);

    if ((samplingRate >= 27713) && (samplingRate < 75132))
    {
      elw = 36; // 36/32 = 9/8
      for (b = HF; b < maxSfbInCh; b++)  // undo above additional high-frequency equal-loudness attenuation
      {
        for (unsigned d = b - HF; d > 0; d--)
        {
          elw = (16u + elw * 40) >> 5; // inverse elw *= 5/4. NOTE: this may overflow for 64 kHz, that's OK
        }
        if (elw == 138 || elw >= 1024) elw--;
        rmsEqualLoud = uint32_t (__min (UINT_MAX, (16u + (uint64_t) stepSizes[b] * elw) >> 5));
        stepSizes[b] = rmsEqualLoud;
      }
    }
  } // for ch

  if ((nMeans < 2) || (sumMeans <= nMeans * BA_EPS)) // in case of one channel or low-RMS input, we're done
  {
    return 0; // no error
  }

  sumMeans = (sumMeans + (nMeans >> 1)) / nMeans;
  sumMeans *= sumMeans;  // since we've averaged square-roots

  for (unsigned ch = 0; ch < nChannels; ch++)
  {
    const SfbGroupData& grpData = *groupData[ch];
    const uint32_t maxSfbInCh = __min (MAX_NUM_SWB_LONG, grpData.sfbsPerGroup);
    const uint32_t nBandsInCh = grpData.numWindowGroups * maxSfbInCh;
    const uint32_t chStepSize = m_avgStepSize[ch];
    uint32_t*   stepSizes = &sfbStepSizes[ch * numSwbShort * NUM_WINDOW_GROUPS];
// --- apply INTER-channel simultaneous masking and JND modeling to calculated INTRA-channel step-size data
    uint64_t mAvgStepSize; // modified and averaged step-size

    if ((nBandsInCh == 0) || (grpData.numWindowGroups > NUM_WINDOW_GROUPS) || (ch == lfeChannelIndex))
    {
      continue;
    }
    mAvgStepSize = jndModel (chStepSize, sumMeans, 7 << 6 /*7/8*/, 512);

    for (unsigned gr = 0; gr < grpData.numWindowGroups; gr++)
    {
      uint32_t* gStepSizes = &stepSizes[numSwbShort * gr];

      for (unsigned b = 0; b < maxSfbInCh; b++)
      {
        gStepSizes[b] = uint32_t (__min (UINT_MAX, (mAvgStepSize * gStepSizes[b] + (chStepSize >> 1)) / chStepSize));
      }
    } // for gr

    m_avgStepSize[ch] = (uint32_t) mAvgStepSize;
  } // for ch

  return 0; // no error
}

unsigned BitAllocator::imprSfbStepSizes (const SfbGroupData* const groupData[USAC_MAX_NUM_CHANNELS], const uint8_t numSwbShort,
                                         const int32_t* const mdctSpec[USAC_MAX_NUM_CHANNELS], const unsigned nSamplesInFrame,
                                         const unsigned nChannels, const unsigned samplingRate, uint32_t* const sfbStepSizes,
                                         const unsigned firstChannelIndex, const uint8_t* const sfm, const bool commonWindow,
                                         const uint8_t* const sfbStereoData /*= nullptr*/, const uint8_t stereoConfig /*= 0*/)
{
  const uint8_t maxSfbL16k = 16 + __min (4 + (samplingRate >> 10), (9 << 17) / __max (1, samplingRate)); // SFB index at 15.8 kHz
  const uint32_t redFactor = __max ((samplingRate < 25495 ? 2 : 1), __min (3, m_rateIndex)) - (stereoConfig >> 3);
  const uint32_t redWeight = __min (4, 9 - __min (9, m_rateIndex));
  short* const  tempCoeffs = (short* const) m_tempSfbValue;

  if ((groupData == nullptr) || (mdctSpec == nullptr) || (sfbStepSizes == nullptr) || (sfm == nullptr) || (nSamplesInFrame > 2048) ||
      (numSwbShort < MIN_NUM_SWB_SHORT) || (numSwbShort > MAX_NUM_SWB_SHORT) || (nChannels > USAC_MAX_NUM_CHANNELS) ||
      (samplingRate < 7350) || (samplingRate > 96000) || (firstChannelIndex > USAC_MAX_NUM_CHANNELS))
  {
    return 1; // invalid arguments error
  }

  for (unsigned ch = firstChannelIndex; ch < firstChannelIndex + nChannels; ch++)
  {
    const SfbGroupData& grpData = *groupData[ch];
    const uint32_t maxSfbInCh = __min (MAX_NUM_SWB_LONG, grpData.sfbsPerGroup);
    const bool    eightShorts = (grpData.numWindowGroups != 1);
    const bool  lowRateTuning = (m_rateIndex == 0) && (samplingRate >= 25495 && sfm[ch] <= (SCHAR_MAX >> 1));
    const bool undercodingRed = (m_rateIndex >  0) || (samplingRate >= 25495 && sfm[ch] * 8 > UCHAR_MAX * 7) || lowRateTuning;
    const uint32_t* rms = grpData.sfbRmsValues;
    uint32_t* stepSizes = &sfbStepSizes[ch * numSwbShort * NUM_WINDOW_GROUPS];

    if ((grpData.numWindowGroups * maxSfbInCh == 0) || (grpData.numWindowGroups > NUM_WINDOW_GROUPS))
    {
      continue;
    }
    for (unsigned gr = 0; gr < grpData.numWindowGroups; gr++)
    {
      const uint16_t* grpOff = &grpData.sfbOffsets[numSwbShort * gr];
      const uint8_t*  grpSte = (sfbStereoData == nullptr ? nullptr : &sfbStereoData[numSwbShort * gr]);
      const uint32_t* grpRms = &rms[numSwbShort * gr];
      const uint32_t* refRms = &groupData[firstChannelIndex + nChannels - 1 - ch]->sfbRmsValues[numSwbShort * gr];
      uint32_t* grpStepSizes = &stepSizes[numSwbShort * gr];
      uint32_t  b, grpRmsMin = INT_MAX; // min. RMS value, used for overcoding reduction
      uint64_t  s = (eightShorts ? (nSamplesInFrame * grpData.windowGroupLength[gr]) >> 1 : nSamplesInFrame << 2);

      memset (m_tempSfbValue, UCHAR_MAX, maxSfbInCh * sizeof (uint8_t));
      if (lowRateTuning && (maxSfbInCh > 0) && !eightShorts)
      {
        uint32_t numRedBands = nSamplesInFrame; // final result lies between 1/4 and 1/2

        if ((nChannels == 2) && commonWindow && (grpSte != nullptr))
        {
          for (b = 0; b < maxSfbInCh; b++) if (grpSte[b] == 0) numRedBands += grpOff[b + 1] - grpOff[b];
        }
        b = MAX_NUM_SWB_LONG - ((numRedBands * ((SCHAR_MAX >> 1) + 1 - sfm[ch]) + (1 << 11)) >> 12);

        while ((b < maxSfbInCh) && (grpRms[b] > grpRms[b - 1])) b++; // start after peak

        for (b += ((nChannels == 2) && commonWindow ? b & 1 : 0); b < maxSfbInCh; b++)
        {
          grpStepSizes[b] = __max (grpStepSizes[b], grpRms[b] >= (UINT_MAX >> 1) ? UINT_MAX : (grpRms[b] + 1) << 1);
        }
      }

      // undercoding reduction for case where large number of coefs is quantized to zero
      for (b = 0; b < maxSfbInCh; b++)
      {
        const uint32_t rmsComp = (grpSte != nullptr && grpSte[b] > 0 ? squareMeanRoot (refRms[b], grpRms[b]) : grpRms[b]);
        const uint32_t rmsRef9 = (commonWindow ? refRms[b] >> 9 : rmsComp);
        const uint8_t sfbWidth = grpOff[b + 1] - grpOff[b];

        if (redWeight > 0 && !eightShorts && sfbWidth > (samplingRate >= 18783 ? 8 : 12)) // transient SFBs
        {
          const uint32_t gains = m_tnsPredictor->calcParCorCoeffs (&mdctSpec[ch][grpOff[b]], sfbWidth, MAX_PREDICTION_ORDER, tempCoeffs) >> 24;

          m_tempSfbValue[b] = UCHAR_MAX - uint8_t ((512u + gains * gains * redWeight) >> (10 + (sfbWidth > 16 ? 0 : (20 - sfbWidth) >> 2)));
          if ((b >= 2) && (m_tempSfbValue[b - 1] < m_tempSfbValue[b]) && (m_tempSfbValue[b - 1] < m_tempSfbValue[b - 2]))
          {
            m_tempSfbValue[b - 1] = __min (m_tempSfbValue[b], m_tempSfbValue[b - 2]); // remove local peaks
          }
        }
        if (grpRms[b] < grpRmsMin) grpRmsMin = grpRms[b];

        if (undercodingRed && (rmsComp >= rmsRef9) && (rmsComp < (grpStepSizes[b] >> 1))) // zero-quantized
        {
          s -= (sfbWidth * redFactor * __min (1u << 11, rmsComp) + (1u << 10)) >> 11;
        }
      }

      if ((samplingRate >= 27713) && (b < maxSfbL16k) && !eightShorts) // zeroed HF data
      {
        const uint32_t rmsComp = (grpSte != nullptr && grpSte[b] > 0 ? squareMeanRoot (refRms[b], grpRms[b]) : grpRms[b]);
        const uint32_t rmsRef9 = (commonWindow ? refRms[b] >> 9 : rmsComp);
        const uint8_t sfbWidth = grpOff[maxSfbL16k] - grpOff[b];

        if (undercodingRed && (rmsComp >= rmsRef9)) // check only first SFB above max_sfb as simplification
        {
          s -= (sfbWidth * redFactor * __min (1u << 11, rmsComp) + (1u << 10)) >> 11;
        }
      }
      s = (eightShorts ? s / ((nSamplesInFrame * grpData.windowGroupLength[gr]) >> 8) : s / (nSamplesInFrame >> 5));

      if (redWeight > 0 && !eightShorts) memset (tempCoeffs /*= m_tempSfbValue*/, UCHAR_MAX, MAX_PREDICTION_ORDER * sizeof (short));

      for (b = 0; b < maxSfbInCh; b++) // improve step-sizes by limiting and attenuation
      {
        grpStepSizes[b] = uint32_t ((__max (grpRmsMin, grpStepSizes[b]) * s * (m_tempSfbValue[b] + 1u) + (1u << 14)) >> 15);
        if (grpStepSizes[b] <= (grpRms[b] >> 11)) grpStepSizes[b] = __max (BA_EPS, grpRms[b] >> 11);

        if (lowRateTuning) // clip near-0 SNRs to minimum SNR
        {
          const uint32_t lim = uint32_t ((grpRms[b] * (8192u - (uint64_t) sfm[ch] * sfm[ch]) + (1u << 12)) >> 13);

          if ((grpStepSizes[b] > grpRms[b]) && ((grpStepSizes[b] >> 1) <= lim)) grpStepSizes[b] = grpRms[b];
        }
      }
    }
  } // for ch

  return 0; // no error
}
