text: // --------------------------------------------------------------------------
  //                   OpenMS -- Open-Source Mass Spectrometry
  // --------------------------------------------------------------------------
  // Copyright The OpenMS Team -- Eberhard Karls University Tuebingen,
  // ETH Zurich, and Freie Universitaet Berlin 2002-2017.
  //
  // This software is released under a three-clause BSD license:
  //  * Redistributions of source code must retain the above copyright
  //    notice, this list of conditions and the following disclaimer.
  //  * Redistributions in binary form must reproduce the above copyright
  //    notice, this list of conditions and the following disclaimer in the
  //    documentation and/or other materials provided with the distribution.
  //  * Neither the name of any author or any participating institution
  //    may be used to endorse or promote products derived from this software
  //    without specific prior written permission.
  // For a full list of authors, refer to the file AUTHORS.
  // --------------------------------------------------------------------------
  // THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS"
  // AND ANY EXPRESS OR IMPLIED WARRANTIES, INCLUDING, BUT NOT LIMITED TO, THE
  // IMPLIED WARRANTIES OF MERCHANTABILITY AND FITNESS FOR A PARTICULAR PURPOSE
  // ARE DISCLAIMED. IN NO EVENT SHALL ANY OF THE AUTHORS OR THE CONTRIBUTING
  // INSTITUTIONS BE LIABLE FOR ANY DIRECT, INDIRECT, INCIDENTAL, SPECIAL,
  // EXEMPLARY, OR CONSEQUENTIAL DAMAGES (INCLUDING, BUT NOT LIMITED TO,
  // PROCUREMENT OF SUBSTITUTE GOODS OR SERVICES; LOSS OF USE, DATA, OR PROFITS;
  // OR BUSINESS INTERRUPTION) HOWEVER CAUSED AND ON ANY THEORY OF LIABILITY,
  // WHETHER IN CONTRACT, STRICT LIABILITY, OR TORT (INCLUDING NEGLIGENCE OR
  // OTHERWISE) ARISING IN ANY WAY OUT OF THE USE OF THIS SOFTWARE, EVEN IF
  // ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
  //
  // --------------------------------------------------------------------------
  // $Maintainer: Oliver Alka $
  // $Authors: Oliver Alka $
  // --------------------------------------------------------------------------
  
  #include <OpenMS/ANALYSIS/MAPMATCHING/FeatureMapping.h>
  #include <OpenMS/MATH/MISC/MathFunctions.h>
  
  using namespace std;
  
  namespace OpenMS
  {
    // return map of ms2 to feature and a vector of unassigned ms2
    FeatureMapping::FeatureToMs2Indices FeatureMapping::assignMS2IndexToFeature(OpenMS::PeakMap& spectra,
                                                                                const OpenMS::KDTreeFeatureMaps& fp_map_kd,
                                                                                const double& precursor_mz_tolerance,
                                                                                const double& precursor_rt_tolerance,
                                                                                bool& ppm)
    {
      map<const BaseFeature*, vector<size_t>> assigned_ms2;
      vector<size_t> unassigned_ms2;
  
      // map precursors to closest feature and retrieve annotated metadata (if possible)
      for (size_t index = 0; index != spectra.size(); ++index)
      {
        if (spectra[index].getMSLevel() != 2) { continue; }
  
        // get precursor meta data (m/z, rt)
        const vector<Precursor> & pcs = spectra[index].getPrecursors();
  
        if (!pcs.empty())
        {
          const double mz = pcs[0].getMZ();
          const double rt = spectra[index].getRT();
  
          // query features in tolerance window
          vector<Size> matches;
  
          // get mz tolerance window
          std::pair<double,double> mz_tolerance_window = Math::getTolWindow(mz, precursor_mz_tolerance, ppm);
          fp_map_kd.queryRegion(rt - precursor_rt_tolerance, rt + precursor_rt_tolerance, mz_tolerance_window.first, mz_tolerance_window.second, matches, true);
  
          // no precursor matches the feature information found
          if (matches.empty())
          {
            unassigned_ms2.push_back(index);
            continue;
          }
  
          // in the case of multiple features in tolerance window, select the one closest in m/z to the precursor
          Size min_distance_feature_index(0);
          double min_distance(1e11);
          for (auto const & k_idx : matches)
          {
            const double f_mz = fp_map_kd.mz(k_idx);
            const double distance = fabs(f_mz - mz);
            if (distance < min_distance)
            {
              min_distance = distance;
              min_distance_feature_index = k_idx;
            }
          }
          const BaseFeature* min_distance_feature = fp_map_kd.feature(min_distance_feature_index);
  
          assigned_ms2[min_distance_feature].push_back(index);
        }
      }
      FeatureMapping::FeatureToMs2Indices feature_mapping;
      feature_mapping.assignedMS2 = assigned_ms2;
      feature_mapping.unassignedMS2 = unassigned_ms2;
      return feature_mapping;
    }
  
  }
  