mlPCLSupportStatistics.h

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// Copyright (c) Fraunhofer MEVIS, Germany. All rights reserved.
// **InsertLicense** code author="Wolf Spindler"
//----------------------------------------------------------------------------------
 
//----------------------------------------------------------------------------------
#pragma once
 
#include "MLPCLSupportSystem.h"
#include <mlTypeDefs.h>
#include <mlPCLTypes.h>
#include <mlPCLSupportTools.h>
 
ML_START_NAMESPACE
 
namespace PCLSupportTools {
 
//----------------------------------------------------------------------------------
//----------------------------------------------------------------------------------
struct PointCloudStatistics {
  PointCloudStatistics():
   minimum( ML_DOUBLE_MAX),
   maximum(-ML_DOUBLE_MAX),
   average(0),
   sum(0),
   sumAbsolute(0),
   median(0){}
  
  double minimum;
  
  double maximum;
  
  double average;
  
  double sum;
  
  double sumAbsolute;
  
  double median;
};
 
//----------------------------------------------------------------------------------
//----------------------------------------------------------------------------------
template <typename POINT_CLOUD_TYPE>
inline PointCloudStatistics getStatistics(const POINT_CLOUD_TYPE &pointCloud,
                                          const std::string &floatPointMemberName="intensityReplacement",
                                          const bool calculateMedian=false)
{
  PointCloudStatistics stats;
  const size_t numPoints = pointCloud.points.size();
  if (numPoints > 0){
    const size_t memberOffset = PCLSupportTools::getByteOffset(pointCloud.points[0], floatPointMemberName);
    if (memberOffset != ML_SIZE_T_MAX){
      
      // Create buffer only for median calculations.
      std::vector<float> vals;
      if (calculateMedian){ vals.resize(numPoints); }
 
      for (size_t c=0; c < numPoints; ++c){
        const unsigned char *pointBase = reinterpret_cast<const unsigned char*>(&(pointCloud.points[c].x));
        const float fltPntVal = *reinterpret_cast<const float *>(pointBase + memberOffset);
        const double pntVal = fltPntVal;
        if (stats.minimum > pntVal){ stats.minimum = pntVal; }
        if (stats.maximum < pntVal){ stats.maximum = pntVal; }
        stats.sum += pntVal;
        stats.sumAbsolute += pntVal < 0. ? -pntVal : pntVal;
        if (calculateMedian){ vals[c] = fltPntVal; }
      }
      if (numPoints > 0){
        stats.average = stats.sum / static_cast<double>(numPoints);
        if (calculateMedian){
          // Sort values and take middle.
          std::sort(vals.begin(), vals.end());
          stats.median = vals[numPoints/2];
        }
      }
    }
  }
  return stats;
}
 
//----------------------------------------------------------------------------------
//----------------------------------------------------------------------------------
template <typename POINT_CLOUD_TYPE>
inline float getMedian(const POINT_CLOUD_TYPE &pointCloud, 
                       const std::string &floatPointMemberName)
{
  float median = 0;
  const size_t numPoints = pointCloud.points.size();
  if (numPoints > 0){
    const size_t memberOffset = PCLSupportTools::getByteOffset(pointCloud.points[0], floatPointMemberName);
    if (memberOffset != ML_SIZE_T_MAX){
      std::vector<float> vals;
      vals.resize(numPoints);
      for (size_t c=0; c < numPoints; ++c){
        const unsigned char *pointBase = reinterpret_cast<const unsigned char*>(&(pointCloud.points[c].x));
        vals[c] = *reinterpret_cast<const float *>(pointBase + memberOffset);
      }
      std::sort(vals.begin(), vals.end());
      median = vals[numPoints/2];
    }
  }
  return median;
}
 
};
 
ML_END_NAMESPACE