using rvalue references to set a given reference tree in FastMKS and DualTreeBoruvka

src/mlpack/methods/emst/dtb.hpp

@@ -160,8 +160,8 @@ class DualTreeBoruvka
    * @param tree Pre-built tree.
    * @param metric An optional instantiated metric to use.
    */
-  DualTreeBoruvka(Tree* tree,
-                  const MetricType metric = MetricType());
+  mlpack_deprecated DualTreeBoruvka(Tree* tree,
+                                    const MetricType metric = MetricType());
 
   /**
    * Create the DualTreeBoruvka object with an already initialized tree.  This
@@ -183,7 +183,7 @@ class DualTreeBoruvka
    * @param tree Pre-built tree.
    * @param dataset Dataset corresponding to the pre-built tree.
    */
-  DualTreeBoruvka(Tree& tree,
+  DualTreeBoruvka(const Tree& tree,
                   const MetricType metric = MetricType());
 
   /**
@@ -249,7 +249,7 @@ class DualTreeBoruvka
    * The CleanupHelper() method taking a reference to the tree is preferred.
    *
    */
-  void CleanupHelper(Tree* tree);
+  mlpack_deprecated void CleanupHelper(Tree* tree);
 
   /**
    * This function resets the values in the nodes of the tree nearest neighbor

src/mlpack/methods/emst/dtb_impl.hpp

@@ -104,7 +104,7 @@ template<
              typename TreeStatType,
              typename TreeMatType> class TreeType>
 DualTreeBoruvka<MetricType, MatType, TreeType>::DualTreeBoruvka(
-    Tree& tree,
+    const Tree& tree,
     const MetricType metric) :
     tree(new Tree(tree)),
     data(&this->tree->Dataset()),

src/mlpack/methods/fastmks/fastmks.hpp

@@ -122,8 +122,8 @@ class FastMKS
    * @param single Whether or not to run single-tree search.
    * @param naive Whether or not to run brute-force (naive) search.
    */
-  FastMKS(Tree* referenceTree,
-          const bool singleMode = false);
+  mlpack_deprecated FastMKS(Tree* referenceTree,
+                            const bool singleMode = false);
 
   /**
    * Create the FastMKS object with an already-initialized tree built on the
@@ -139,7 +139,7 @@ class FastMKS
    * @param single Whether or not to run single-tree search.
    * @param naive Whether or not to run brute-force (naive) search.
    */
-  FastMKS(Tree& referenceTree,
+  FastMKS(const Tree& referenceTree,
           const bool singleMode = false);
 
   /**
@@ -192,19 +192,18 @@ class FastMKS
    *
    * @param tree Tree to use as reference data.
    */
-  void Train(Tree* referenceTree);
+  mlpack_deprecated void Train(Tree* referenceTree);
 
   /**
-   * Train the FastMKS model on the given reference tree.  This takes ownership
-   * of the tree, so you do not need to delete it!  This will throw an exception
-   * if the model is searching in naive mode (i.e. if Naive() == true).
+   * Train the FastMKS model on the given reference tree. This will throw an
+   * exception if the model is searching in naive mode (i.e. if Naive() == true).
    *
    * This method will copy the given tree. You can avoid this copy by using the
    * Train() method that takes a rvalue reference to the tree.
    *
    * @param tree Tree to use as reference data.
    */
-  void Train(Tree& referenceTree);
+  void Train(const Tree& referenceTree);
 
   /**
    * Train the FastMKS model on the given reference tree.  This takes ownership
@@ -267,10 +266,10 @@ class FastMKS
    * @param indices Matrix to store resulting indices of max-kernel search in.
    * @param kernels Matrix to store resulting max-kernel values in.
    */
-  void Search(Tree* querySet,
-              const size_t k,
-              arma::Mat<size_t>& indices,
-              arma::mat& kernels);
+  mlpack_deprecated void Search(Tree* querySet,
+                                const size_t k,
+                                arma::Mat<size_t>& indices,
+                                arma::mat& kernels);
 
   /**
    * Search for the points in the reference set with maximum kernel evaluation
@@ -294,7 +293,7 @@ class FastMKS
    * @param indices Matrix to store resulting indices of max-kernel search in.
    * @param kernels Matrix to store resulting max-kernel values in.
    */
-  void Search(Tree& querySet,
+  void Search(Tree& queryTree,
               const size_t k,
               arma::Mat<size_t>& indices,
               arma::mat& kernels);

src/mlpack/methods/fastmks/fastmks_impl.hpp

@@ -118,7 +118,7 @@ template<typename KernelType,
          template<typename TreeMetricType,
                   typename TreeStatType,
                   typename TreeMatType> class TreeType>
-FastMKS<KernelType, MatType, TreeType>::FastMKS(Tree& referenceTree,
+FastMKS<KernelType, MatType, TreeType>::FastMKS(const Tree& referenceTree,
                                                 const bool singleMode) :
 	referenceTree(new Tree(referenceTree)),
     referenceSet(&this->referenceTree->Dataset()),
@@ -225,7 +225,7 @@ template<typename KernelType,
          template<typename TreeMetricType,
                   typename TreeStatType,
                   typename TreeMatType> class TreeType>
-void FastMKS<KernelType, MatType, TreeType>::Train(Tree& tree)
+void FastMKS<KernelType, MatType, TreeType>::Train(const Tree& tree)
 {
   if (naive)
     throw std::invalid_argument("cannot call FastMKS::Train() with a tree when "
@@ -358,7 +358,7 @@ void FastMKS<KernelType, MatType, TreeType>::Search(
   Tree queryTree(querySet);
   Timer::Stop("tree_building");
 
-  Search(&queryTree, k, indices, kernels);
+  Search(queryTree, k, indices, kernels);
 }
 
 template<typename KernelType,
@@ -372,7 +372,7 @@ void FastMKS<KernelType, MatType, TreeType>::Search(
     arma::Mat<size_t>& indices,
     arma::mat& kernels)
 {
-	Search(*queryTree, k, indices, kernels);
+  Search(*queryTree, k, indices, kernels);
 }
 
 template<typename KernelType,
@@ -505,7 +505,7 @@ void FastMKS<KernelType, MatType, TreeType>::Search(
   // Dual-tree implementation.
   Timer::Stop("computing_products");
 
-  Search(std::move(referenceTree), k, indices, kernels);
+  Search(*referenceTree, k, indices, kernels);
 }
 
 //! Serialize the model.