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autocorr.cpp

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#include <math.h>

#include "lregress.h"
#include "autocorr.h"

using namespace std;


void autocorr::acorrSlope( acorrInfo &info )
{

  const size_t len = info.points().size();
  if (len > 0) {
    lregress::lineInfo regressInfo;
    lregress lr;
    vector<lregress::point> regressPoints;
    for (size_t i = 0; i < len; i++) {
      double x = log(i+1);
      double y = log((info.points())[i]);
      regressPoints.push_back( lregress::point(x,y) );
    }
    lr.lr( regressPoints, regressInfo );
    info.slope( regressInfo.slope() );
    info.slopeErr( regressInfo.slopeErr() );
  }
} // acorrSlope


void autocorr::ACF( const double *v, 
                    const size_t N, 
                    acorrInfo &info )
{
  if (! info.points().empty() ) {
    info.points().clear();
  }

  // The devMean array will contain the deviation from the mean.
  // That is, v[i] - mean(v).
  double *devMean = new double[ N ];
  
  double sum;
  size_t i;

  // Calculate the mean and copy the vector v, into devMean
  sum = 0;
  for (i = 0; i < N; i++) {
    sum = sum + v[i];
    devMean[i] = v[i];
  }
  double mean = sum / static_cast<double>(N);

  // Compute the values for the devMean array.  Also calculate the
  // denominator for the autocorrelation function.
  sum = 0;
  for (i = 0; i < N; i++) {
    devMean[i] = devMean[i] - mean;
    sum = sum + (devMean[i]*devMean[i]);
  }
  double denom = sum / static_cast<double>(N);

  // Calculate a std::vector of values which will make up
  // the autocorrelation function.
  double cor = 1.0;
  for (size_t shift = 1; shift <= numPoints_ && cor > limit_; shift++) {
    info.points().push_back( cor );
    size_t n = N - shift;
    sum = 0.0;
    for (i = 0; i < n; i++) {
      sum = sum + (devMean[i] * devMean[i+shift]);
    }
    double numerator = sum / static_cast<double>(n)
    cor = numerator / denom;
  }

  // calculate the log/log slope of the autocorrelation
  acorrSlope( info );

  delete [] m;
} // ACF

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