Esempio n. 1
0
/** Calculates Sn as estimator of scale for given vector
  *
  * This method implements a naive calculation of Sn, as defined by Rousseeuw
  *and Croux (http://dx.doi.org/10.2307%2F2291267).
  * In contrast to standard deviation, this is more robust towards outliers.
  *
  * @param begin :: Beginning of vector.
  * @param end :: End of vector.
  * @return Sn of supplied data.
  */
double PoldiPeakSearch::getSn(MantidVec::const_iterator begin,
                              MantidVec::const_iterator end) const {
  size_t numberOfPoints = std::distance(begin, end);
  MantidVec absoluteDifferenceMedians(numberOfPoints);

  PARALLEL_FOR_NO_WSP_CHECK()
  for (int i = 0; i < static_cast<int>(numberOfPoints); ++i) {
    double currentValue = *(begin + i);
    MantidVec temp;
    temp.reserve(numberOfPoints - 1);
    for (int j = 0; j < static_cast<int>(numberOfPoints); ++j) {
      if (j != i) {
        temp.push_back(fabs(*(begin + j) - currentValue));
      }
    }
    std::sort(temp.begin(), temp.end());

    absoluteDifferenceMedians[i] =
        getMedianFromSortedVector(temp.begin(), temp.end());
  }

  std::sort(absoluteDifferenceMedians.begin(), absoluteDifferenceMedians.end());

  return 1.1926 * getMedianFromSortedVector(absoluteDifferenceMedians.begin(),
                                            absoluteDifferenceMedians.end());
}
Esempio n. 2
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/** Retrieves a vector with all counts that belong to the background
  *
  * In this method, a vector is assembled which contains all count data that is
  *considered to be background.
  * Whether a point is considered background depends on its distance to the
  *given peak positions.
  *
  * @param peakPositions :: Peak positions.
  * @param correlationCounts :: Vector with the complete correlation spectrum.
  * @return Vector only with counts that belong to the background.
  */
MantidVec PoldiPeakSearch::getBackground(
    std::list<MantidVec::const_iterator> peakPositions,
    const MantidVec &correlationCounts) const {
  size_t backgroundPoints =
      getNumberOfBackgroundPoints(peakPositions, correlationCounts);

  MantidVec background;
  background.reserve(backgroundPoints);

  for (MantidVec::const_iterator point = correlationCounts.begin() + 1;
       point != correlationCounts.end() - 1; ++point) {
    if (distanceToPeaksGreaterThanMinimum(peakPositions, point)) {
      background.push_back(*point);
    }
  }

  return background;
}