Comment things a little better, and rename one of the timers.

src/mlpack/methods/emst/dtb.hpp

@@ -23,22 +23,19 @@ namespace mlpack {
 namespace emst {
 
 /**
- * A Stat class for use with fastlib's trees.  This one only stores two values.
- *
- * @param max_neighbor_distance The upper bound on the distance to the nearest
- * neighbor of any point in this node.
- *
- * @param component_membership The index of the component that all points in
- * this node belong to.  This is the same index returned by UnionFind for all
- * points in this node.  If points in this node are in different components,
- * this value will be negative.
+ * A statistic for use with MLPACK trees, which stores the upper bound on
+ * distance to nearest neighbors and the component which this node belongs to.
  */
 class DTBStat
 {
  private:
-  //! Maximum neighbor distance.
+  //! Upper bound on the distance to the nearest neighbor of any point in this
+  //! node.
   double maxNeighborDistance;
-  //! Component membership of this node.
+  //! The index of the component that all points in this node belong to.  This
+  //! is the same index returned by UnionFind for all points in this node.  If
+  //! points in this node are in different components, this value will be
+  //! negative.
   int componentMembership;
 
  public:
@@ -54,7 +51,7 @@ class DTBStat
   DTBStat(const MatType& dataset, const size_t start, const size_t count);
 
   /**
-   * An initializer for non-leaves.  Simply calls the leaf initializer.
+   * An initializer for non-leaves.
    */
   template<typename MatType>
   DTBStat(const MatType& dataset, const size_t start, const size_t count,
@@ -73,7 +70,23 @@ class DTBStat
 }; // class DTBStat
 
 /**
- * Performs the MST calculation using the Dual-Tree Boruvka algorithm.
+ * Performs the MST calculation using the Dual-Tree Boruvka algorithm, using any
+ * type of tree.  At the moment this class does not support arbitrary distance
+ * metrics, and uses the squared Euclidean distance.
+ *
+ * For more information on the algorithm, see the following citation:
+ *
+ * @inproceedings{
+ *   author = {March, W.B., Ram, P., and Gray, A.G.},
+ *   title = {{Fast Euclidean Minimum Spanning Tree: Algorithm, Analysis,
+ *      Applications.}},
+ *   booktitle = {Proceedings of the 16th ACM SIGKDD International Conference
+ *      on Knowledge Discovery and Data Mining}
+ *   series = {KDD '10},
+ *   year = {2010}
+ * }
+ *
+ * @tparam TreeType Type of tree to use.
  */
 template<
   typename TreeType = tree::BinarySpaceTree<bound::HRectBound<2>, DTBStat>
@@ -82,9 +95,9 @@ class DualTreeBoruvka
 {
  private:
   //! Copy of the data (if necessary).
-  arma::mat dataCopy;
+  typename TreeType::Mat dataCopy;
   //! Reference to the data (this is what should be used for accessing data).
-  arma::mat& data;
+  typename TreeType::Mat& data;
 
   //! Pointer to the root of the tree.
   TreeType* tree;
@@ -109,7 +122,7 @@ class DualTreeBoruvka
   //! List of edge distances.
   arma::vec neighborsDistances;
 
-  // output info
+  //! Total distance of the tree.
   double totalDist;
 
   // For sorting the edge list after the computation.
@@ -121,8 +134,6 @@ class DualTreeBoruvka
     }
   } SortFun;
 
-
-////////////////// Constructors ////////////////////////
  public:
   /**
    * Create the tree from the given dataset.  This copies the dataset to an
@@ -161,12 +172,16 @@ class DualTreeBoruvka
   ~DualTreeBoruvka();
 
   /**
-   * Call this function after Init.  It will iteratively find the nearest
-   * neighbor of each component until the MST is complete.
+   * Iteratively find the nearest neighbor of each component until the MST is
+   * complete.  The results will be a 3xN matrix (with N equal to the number of
+   * edges in the minimum spanning tree).  The first row will contain the lesser
+   * index of the edge; the second row will contain the greater index of the
+   * edge; and the third row will contain the distance between the two edges.
+   *
+   * @param results Matrix which results will be stored in.
    */
   void ComputeMST(arma::mat& results);
 
-  ////////////////////////// Private Functions ////////////////////
  private:
   /**
    * Adds a single edge to the edge list

src/mlpack/methods/emst/dtb_impl.hpp

@@ -69,7 +69,7 @@ DualTreeBoruvka<TreeType>::DualTreeBoruvka(
     connections(data.n_cols),
     totalDist(0.0)
 {
-  Timer::Start("emst/treebuilding");
+  Timer::Start("emst/tree_building");
 
   if (!naive)
   {
@@ -83,7 +83,7 @@ DualTreeBoruvka<TreeType>::DualTreeBoruvka(
     tree = new TreeType(data, oldFromNew, data.n_cols);
   }
 
-  Timer::Stop("emst/treebuilding");
+  Timer::Stop("emst/tree_building");
 
   edges.reserve(data.n_cols - 1); // Set size.
 
@@ -120,14 +120,16 @@ DualTreeBoruvka<TreeType>::~DualTreeBoruvka()
 }
 
 /**
- * Call this function after Init.  It will iteratively find the nearest
- * neighbor of each component until the MST is complete.
+ * Iteratively find the nearest neighbor of each component until the MST is
+ * complete.
  */
 template<typename TreeType>
 void DualTreeBoruvka<TreeType>::ComputeMST(arma::mat& results)
 {
   Timer::Start("emst/mst_computation");
 
+  totalDist = 0; // Reset distance.
+
   while (edges.size() < (data.n_cols - 1))
   {
     // Compute neighbors.