/* -*- c++ -*- */
/*
 * Copyright 2012, 2014 Free Software Foundation, Inc.
 *
 * This file is part of GNU Radio
 *
 * GNU Radio is free software; you can redistribute it and/or modify
 * it under the terms of the GNU General Public License as published by
 * the Free Software Foundation; either version 3, or (at your option)
 * any later version.
 *
 * GNU Radio is distributed in the hope that it will be useful,
 * but WITHOUT ANY WARRANTY; without even the implied warranty of
 * MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
 * GNU General Public License for more details.
 *
 * You should have received a copy of the GNU General Public License
 * along with GNU Radio; see the file COPYING.  If not, write to
 * the Free Software Foundation, Inc., 51 Franklin Street,
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/*!
 * \page volk_32f_s32f_calc_spectral_noise_floor_32f
 *
 * \b Overview
 *
 * Computes the spectral noise floor of an input power spectrum.
 *
 * Calculates the spectral noise floor of an input power spectrum by
 * determining the mean of the input power spectrum, then
 * recalculating the mean excluding any power spectrum values that
 * exceed the mean by the spectralExclusionValue (in dB).  Provides a
 * rough estimation of the signal noise floor.
 *
 * <b>Dispatcher Prototype</b>
 * \code
 * void volk_32f_s32f_calc_spectral_noise_floor_32f(float* noiseFloorAmplitude, const float* realDataPoints, const float spectralExclusionValue, const unsigned int num_points)
 * \endcode
 *
 * \b Inputs
 * \li realDataPoints: The input power spectrum.
 * \li spectralExclusionValue: The number of dB above the noise floor that a data point must be to be excluded from the noise floor calculation - default value is 20.
 * \li num_points: The number of data points.
 *
 * \b Outputs
 * \li noiseFloorAmplitude: The noise floor of the input spectrum, in dB.
 *
 * \b Example
 * \code
 * int N = 10000;
 *
 * volk_32f_s32f_calc_spectral_noise_floor_32f
 *
 * volk_free(x);
 * \endcode
 */

#ifndef INCLUDED_volk_32f_s32f_calc_spectral_noise_floor_32f_a_H
#define INCLUDED_volk_32f_s32f_calc_spectral_noise_floor_32f_a_H

#include <volk/volk_common.h>
#include <inttypes.h>
#include <stdio.h>

#ifdef LV_HAVE_AVX
#include <immintrin.h>

static inline void
volk_32f_s32f_calc_spectral_noise_floor_32f_a_avx(float* noiseFloorAmplitude,
                                                  const float* realDataPoints,
                                                  const float spectralExclusionValue,
                                                  const unsigned int num_points)
{
  unsigned int number = 0;
  const unsigned int eighthPoints = num_points / 8;

  const float* dataPointsPtr = realDataPoints;
  __VOLK_ATTR_ALIGNED(32) float avgPointsVector[8];

  __m256 dataPointsVal;
  __m256 avgPointsVal = _mm256_setzero_ps();
  // Calculate the sum (for mean) for all points
  for(; number < eighthPoints; number++){

    dataPointsVal = _mm256_load_ps(dataPointsPtr);

    dataPointsPtr += 8;

    avgPointsVal = _mm256_add_ps(avgPointsVal, dataPointsVal);
  }

  _mm256_store_ps(avgPointsVector, avgPointsVal);

  float sumMean = 0.0;
  sumMean += avgPointsVector[0];
  sumMean += avgPointsVector[1];
  sumMean += avgPointsVector[2];
  sumMean += avgPointsVector[3];
  sumMean += avgPointsVector[4];
  sumMean += avgPointsVector[5];
  sumMean += avgPointsVector[6];
  sumMean += avgPointsVector[7];

  number = eighthPoints * 8;
  for(;number < num_points; number++){
    sumMean += realDataPoints[number];
  }

  // calculate the spectral mean
  // +20 because for the comparison below we only want to throw out bins
  // that are significantly higher (and would, thus, affect the mean more
  const float meanAmplitude = (sumMean / ((float)num_points)) + spectralExclusionValue;

  dataPointsPtr = realDataPoints; // Reset the dataPointsPtr
  __m256 vMeanAmplitudeVector = _mm256_set1_ps(meanAmplitude);
  __m256 vOnesVector = _mm256_set1_ps(1.0);
  __m256 vValidBinCount = _mm256_setzero_ps();
  avgPointsVal = _mm256_setzero_ps();
  __m256 compareMask;
  number = 0;
  // Calculate the sum (for mean) for any points which do NOT exceed the mean amplitude
  for(; number < eighthPoints; number++){

    dataPointsVal = _mm256_load_ps(dataPointsPtr);

    dataPointsPtr += 8;

    // Identify which items do not exceed the mean amplitude
    compareMask = _mm256_cmp_ps(dataPointsVal, vMeanAmplitudeVector, 18);

    // Mask off the items that exceed the mean amplitude and add the avg Points that do not exceed the mean amplitude
    avgPointsVal = _mm256_add_ps(avgPointsVal, _mm256_and_ps(compareMask, dataPointsVal));

    // Count the number of bins which do not exceed the mean amplitude
    vValidBinCount = _mm256_add_ps(vValidBinCount, _mm256_and_ps(compareMask, vOnesVector));
  }

  // Calculate the mean from the remaining data points
  _mm256_store_ps(avgPointsVector, avgPointsVal);

  sumMean = 0.0;
  sumMean += avgPointsVector[0];
  sumMean += avgPointsVector[1];
  sumMean += avgPointsVector[2];
  sumMean += avgPointsVector[3];
  sumMean += avgPointsVector[4];
  sumMean += avgPointsVector[5];
  sumMean += avgPointsVector[6];
  sumMean += avgPointsVector[7];

  // Calculate the number of valid bins from the remaning count
  __VOLK_ATTR_ALIGNED(32) float validBinCountVector[8];
  _mm256_store_ps(validBinCountVector, vValidBinCount);

  float validBinCount = 0;
  validBinCount += validBinCountVector[0];
  validBinCount += validBinCountVector[1];
  validBinCount += validBinCountVector[2];
  validBinCount += validBinCountVector[3];
  validBinCount += validBinCountVector[4];
  validBinCount += validBinCountVector[5];
  validBinCount += validBinCountVector[6];
  validBinCount += validBinCountVector[7];

  number = eighthPoints * 8;
  for(;number < num_points; number++){
    if(realDataPoints[number] <= meanAmplitude){
      sumMean += realDataPoints[number];
      validBinCount += 1.0;
    }
  }

  float localNoiseFloorAmplitude = 0;
  if(validBinCount > 0.0){
    localNoiseFloorAmplitude = sumMean / validBinCount;
  }
  else{
    localNoiseFloorAmplitude = meanAmplitude; // For the odd case that all the amplitudes are equal...
  }

  *noiseFloorAmplitude = localNoiseFloorAmplitude;
}
#endif /* LV_HAVE_AVX */

#ifdef LV_HAVE_SSE
#include <xmmintrin.h>

static inline void
volk_32f_s32f_calc_spectral_noise_floor_32f_a_sse(float* noiseFloorAmplitude,
                                                  const float* realDataPoints,
                                                  const float spectralExclusionValue,
                                                  const unsigned int num_points)
{
  unsigned int number = 0;
  const unsigned int quarterPoints = num_points / 4;

  const float* dataPointsPtr = realDataPoints;
  __VOLK_ATTR_ALIGNED(16) float avgPointsVector[4];

  __m128 dataPointsVal;
  __m128 avgPointsVal = _mm_setzero_ps();
  // Calculate the sum (for mean) for all points
  for(; number < quarterPoints; number++){

    dataPointsVal = _mm_load_ps(dataPointsPtr);

    dataPointsPtr += 4;

    avgPointsVal = _mm_add_ps(avgPointsVal, dataPointsVal);
  }

  _mm_store_ps(avgPointsVector, avgPointsVal);

  float sumMean = 0.0;
  sumMean += avgPointsVector[0];
  sumMean += avgPointsVector[1];
  sumMean += avgPointsVector[2];
  sumMean += avgPointsVector[3];

  number = quarterPoints * 4;
  for(;number < num_points; number++){
    sumMean += realDataPoints[number];
  }

  // calculate the spectral mean
  // +20 because for the comparison below we only want to throw out bins
  // that are significantly higher (and would, thus, affect the mean more
  const float meanAmplitude = (sumMean / ((float)num_points)) + spectralExclusionValue;

  dataPointsPtr = realDataPoints; // Reset the dataPointsPtr
  __m128 vMeanAmplitudeVector = _mm_set_ps1(meanAmplitude);
  __m128 vOnesVector = _mm_set_ps1(1.0);
  __m128 vValidBinCount = _mm_setzero_ps();
  avgPointsVal = _mm_setzero_ps();
  __m128 compareMask;
  number = 0;
  // Calculate the sum (for mean) for any points which do NOT exceed the mean amplitude
  for(; number < quarterPoints; number++){

    dataPointsVal = _mm_load_ps(dataPointsPtr);

    dataPointsPtr += 4;

    // Identify which items do not exceed the mean amplitude
    compareMask = _mm_cmple_ps(dataPointsVal, vMeanAmplitudeVector);

    // Mask off the items that exceed the mean amplitude and add the avg Points that do not exceed the mean amplitude
    avgPointsVal = _mm_add_ps(avgPointsVal, _mm_and_ps(compareMask, dataPointsVal));

    // Count the number of bins which do not exceed the mean amplitude
    vValidBinCount = _mm_add_ps(vValidBinCount, _mm_and_ps(compareMask, vOnesVector));
  }

  // Calculate the mean from the remaining data points
  _mm_store_ps(avgPointsVector, avgPointsVal);

  sumMean = 0.0;
  sumMean += avgPointsVector[0];
  sumMean += avgPointsVector[1];
  sumMean += avgPointsVector[2];
  sumMean += avgPointsVector[3];

  // Calculate the number of valid bins from the remaning count
  __VOLK_ATTR_ALIGNED(16) float validBinCountVector[4];
  _mm_store_ps(validBinCountVector, vValidBinCount);

  float validBinCount = 0;
  validBinCount += validBinCountVector[0];
  validBinCount += validBinCountVector[1];
  validBinCount += validBinCountVector[2];
  validBinCount += validBinCountVector[3];

  number = quarterPoints * 4;
  for(;number < num_points; number++){
    if(realDataPoints[number] <= meanAmplitude){
      sumMean += realDataPoints[number];
      validBinCount += 1.0;
    }
  }

  float localNoiseFloorAmplitude = 0;
  if(validBinCount > 0.0){
    localNoiseFloorAmplitude = sumMean / validBinCount;
  }
  else{
    localNoiseFloorAmplitude = meanAmplitude; // For the odd case that all the amplitudes are equal...
  }

  *noiseFloorAmplitude = localNoiseFloorAmplitude;
}
#endif /* LV_HAVE_SSE */


#ifdef LV_HAVE_GENERIC

static inline void
volk_32f_s32f_calc_spectral_noise_floor_32f_generic(float* noiseFloorAmplitude,
                                                    const float* realDataPoints,
                                                    const float spectralExclusionValue,
                                                    const unsigned int num_points)
{
  float sumMean = 0.0;
  unsigned int number;
  // find the sum (for mean), etc
  for(number = 0; number < num_points; number++){
    // sum (for mean)
    sumMean += realDataPoints[number];
  }

  // calculate the spectral mean
  // +20 because for the comparison below we only want to throw out bins
  // that are significantly higher (and would, thus, affect the mean more)
  const float meanAmplitude = (sumMean / num_points) + spectralExclusionValue;

  // now throw out any bins higher than the mean
  sumMean = 0.0;
  unsigned int newNumDataPoints = num_points;
  for(number = 0; number < num_points; number++){
    if (realDataPoints[number] <= meanAmplitude)
      sumMean += realDataPoints[number];
    else
      newNumDataPoints--;
  }

  float localNoiseFloorAmplitude = 0.0;
  if (newNumDataPoints == 0)             // in the odd case that all
    localNoiseFloorAmplitude = meanAmplitude; // amplitudes are equal!
  else
    localNoiseFloorAmplitude = sumMean / ((float)newNumDataPoints);

  *noiseFloorAmplitude = localNoiseFloorAmplitude;
}
#endif /* LV_HAVE_GENERIC */


#endif /* INCLUDED_volk_32f_s32f_calc_spectral_noise_floor_32f_a_H */

#ifndef INCLUDED_volk_32f_s32f_calc_spectral_noise_floor_32f_u_H
#define INCLUDED_volk_32f_s32f_calc_spectral_noise_floor_32f_u_H

#include <volk/volk_common.h>
#include <inttypes.h>
#include <stdio.h>

#ifdef LV_HAVE_AVX
#include <immintrin.h>

static inline void
volk_32f_s32f_calc_spectral_noise_floor_32f_u_avx(float* noiseFloorAmplitude,
                                                  const float* realDataPoints,
                                                  const float spectralExclusionValue,
                                                  const unsigned int num_points)
{
  unsigned int number = 0;
  const unsigned int eighthPoints = num_points / 8;

  const float* dataPointsPtr = realDataPoints;
  __VOLK_ATTR_ALIGNED(16) float avgPointsVector[8];

  __m256 dataPointsVal;
  __m256 avgPointsVal = _mm256_setzero_ps();
  // Calculate the sum (for mean) for all points
  for(; number < eighthPoints; number++){

    dataPointsVal = _mm256_loadu_ps(dataPointsPtr);

    dataPointsPtr += 8;

    avgPointsVal = _mm256_add_ps(avgPointsVal, dataPointsVal);
  }

  _mm256_storeu_ps(avgPointsVector, avgPointsVal);

  float sumMean = 0.0;
  sumMean += avgPointsVector[0];
  sumMean += avgPointsVector[1];
  sumMean += avgPointsVector[2];
  sumMean += avgPointsVector[3];
  sumMean += avgPointsVector[4];
  sumMean += avgPointsVector[5];
  sumMean += avgPointsVector[6];
  sumMean += avgPointsVector[7];

  number = eighthPoints * 8;
  for(;number < num_points; number++){
    sumMean += realDataPoints[number];
  }

  // calculate the spectral mean
  // +20 because for the comparison below we only want to throw out bins
  // that are significantly higher (and would, thus, affect the mean more
  const float meanAmplitude = (sumMean / ((float)num_points)) + spectralExclusionValue;

  dataPointsPtr = realDataPoints; // Reset the dataPointsPtr
  __m256 vMeanAmplitudeVector = _mm256_set1_ps(meanAmplitude);
  __m256 vOnesVector = _mm256_set1_ps(1.0);
  __m256 vValidBinCount = _mm256_setzero_ps();
  avgPointsVal = _mm256_setzero_ps();
  __m256 compareMask;
  number = 0;
  // Calculate the sum (for mean) for any points which do NOT exceed the mean amplitude
  for(; number < eighthPoints; number++){

    dataPointsVal = _mm256_loadu_ps(dataPointsPtr);

    dataPointsPtr += 8;

    // Identify which items do not exceed the mean amplitude
    compareMask = _mm256_cmp_ps(dataPointsVal, vMeanAmplitudeVector, 18);

    // Mask off the items that exceed the mean amplitude and add the avg Points that do not exceed the mean amplitude
    avgPointsVal = _mm256_add_ps(avgPointsVal, _mm256_and_ps(compareMask, dataPointsVal));

    // Count the number of bins which do not exceed the mean amplitude
    vValidBinCount = _mm256_add_ps(vValidBinCount, _mm256_and_ps(compareMask, vOnesVector));
  }

  // Calculate the mean from the remaining data points
  _mm256_storeu_ps(avgPointsVector, avgPointsVal);

  sumMean = 0.0;
  sumMean += avgPointsVector[0];
  sumMean += avgPointsVector[1];
  sumMean += avgPointsVector[2];
  sumMean += avgPointsVector[3];
  sumMean += avgPointsVector[4];
  sumMean += avgPointsVector[5];
  sumMean += avgPointsVector[6];
  sumMean += avgPointsVector[7];

  // Calculate the number of valid bins from the remaning count
  __VOLK_ATTR_ALIGNED(16) float validBinCountVector[8];
  _mm256_storeu_ps(validBinCountVector, vValidBinCount);

  float validBinCount = 0;
  validBinCount += validBinCountVector[0];
  validBinCount += validBinCountVector[1];
  validBinCount += validBinCountVector[2];
  validBinCount += validBinCountVector[3];
  validBinCount += validBinCountVector[4];
  validBinCount += validBinCountVector[5];
  validBinCount += validBinCountVector[6];
  validBinCount += validBinCountVector[7];

  number = eighthPoints * 8;
  for(;number < num_points; number++){
    if(realDataPoints[number] <= meanAmplitude){
      sumMean += realDataPoints[number];
      validBinCount += 1.0;
    }
  }

  float localNoiseFloorAmplitude = 0;
  if(validBinCount > 0.0){
    localNoiseFloorAmplitude = sumMean / validBinCount;
  }
  else{
    localNoiseFloorAmplitude = meanAmplitude; // For the odd case that all the amplitudes are equal...
  }

  *noiseFloorAmplitude = localNoiseFloorAmplitude;
}
#endif /* LV_HAVE_AVX */
#endif /* INCLUDED_volk_32f_s32f_calc_spectral_noise_floor_32f_u_H */
