Method cohesion

src/openms/source/COMPARISON/CLUSTERING/ClusterAnalyzer.cpp:646–685

  }

  std::vector<float> ClusterAnalyzer::cohesion(const std::vector<std::vector<Size> > & clusters, const DistanceMatrix<float> & original)
  {
    if (clusters.empty() || clusters.size() > original.dimensionsize())
    {
      throw Exception::InvalidParameter(__FILE__, __LINE__, OPENMS_PRETTY_FUNCTION, "invalid clustering");
    }

    float av_dist(0);     // average of all pairwise distances
    for (Size i = 0; i < original.dimensionsize(); ++i)
    {
      for (Size j = i + 1; j < original.dimensionsize(); ++j)
      {
        av_dist += original.getValue(i, j);
      }
    }
    av_dist /= (((float)original.dimensionsize() * (float)(original.dimensionsize() - 1.0)) / 2.0f);

    std::vector<float> cohesions;
    cohesions.reserve(clusters.size());
    for (Size i = 0; i < clusters.size(); ++i)
    {
      float av_c_dist(0);       // all pairwise distances in cluster i
      for (Size j = 0; j < clusters[i].size(); ++j)
      {
        for (Size k = 0; k < j; ++k)
        {
          av_c_dist += original.getValue(clusters[i][j], clusters[i][k]);
        }
      }

      av_c_dist /= (((float)clusters[i].size() * (float)(clusters[i].size() - 1.0)) / 2.0f); //now av. intra cluster distance
      if (clusters[i].size() == 1)
      {
        av_c_dist = av_dist;
      }
      //~ std::cout << " av clu i " << av_c_dist << std::endl;
      cohesions.push_back(av_c_dist);
    }
    return cohesions;
  }

  String ClusterAnalyzer::newickTree(const std::vector<BinaryTreeNode> & tree, const bool include_distance)
  {