refactored src/mlpack/methods/*/ - updated MinDistance(), MaxDistance() and RangeDistance() calls

src/mlpack/methods/emst/dtb_rules_impl.hpp

@@ -115,7 +115,7 @@ double DTBRules<MetricType, TreeType>::Score(TreeType& queryNode,
     return DBL_MAX;
 
   ++scores;
-  const double distance = queryNode.MinDistance(&referenceNode);
+  const double distance = queryNode.MinDistance(referenceNode);
   const double bound = CalculateBound(queryNode);
 
   // If all the points in the reference node are farther than the candidate

src/mlpack/methods/kmeans/dual_tree_kmeans_rules_impl.hpp

@@ -216,7 +216,7 @@ inline double DualTreeKMeansRules<MetricType, TreeType>::Score(
       {
         // If this might affect the lower bound, make it more exact.
         queryNode.Stat().LowerBound() = std::min(queryNode.Stat().LowerBound(),
-            queryNode.MinDistance(&referenceNode));
+            queryNode.MinDistance(referenceNode));
         ++scores;
       }
 
@@ -228,7 +228,7 @@ inline double DualTreeKMeansRules<MetricType, TreeType>::Score(
   if (score != DBL_MAX)
   {
     // Get minimum and maximum distances.
-    const math::Range distances = queryNode.RangeDistance(&referenceNode);
+    const math::Range distances = queryNode.RangeDistance(referenceNode);
 
     score = distances.Lo();
     ++scores;

src/mlpack/methods/neighbor_search/sort_policies/furthest_neighbor_sort_impl.hpp

@@ -18,7 +18,7 @@ inline double FurthestNeighborSort::BestNodeToNodeDistance(
 {
   // This is not implemented yet for the general case because the trees do not
   // accept arbitrary distance metrics.
-  return queryNode->MaxDistance(referenceNode);
+  return queryNode->MaxDistance(*referenceNode);
 }
 
 template<typename TreeType>
@@ -27,7 +27,7 @@ inline double FurthestNeighborSort::BestNodeToNodeDistance(
     const TreeType* referenceNode,
     const double centerToCenterDistance)
 {
-  return queryNode->MaxDistance(referenceNode, centerToCenterDistance);
+  return queryNode->MaxDistance(*referenceNode, centerToCenterDistance);
 }
 
 template<typename TreeType>
@@ -37,7 +37,7 @@ inline double FurthestNeighborSort::BestNodeToNodeDistance(
     const TreeType* referenceChildNode,
     const double centerToCenterDistance)
 {
-  return queryNode->MaxDistance(referenceNode, centerToCenterDistance) +
+  return queryNode->MaxDistance(*referenceNode, centerToCenterDistance) +
       referenceChildNode->ParentDistance();
 }
 

src/mlpack/methods/neighbor_search/sort_policies/nearest_neighbor_sort_impl.hpp

@@ -18,7 +18,7 @@ inline double NearestNeighborSort::BestNodeToNodeDistance(
 {
   // This is not implemented yet for the general case because the trees do not
   // accept arbitrary distance metrics.
-  return queryNode->MinDistance(referenceNode);
+  return queryNode->MinDistance(*referenceNode);
 }
 
 template<typename TreeType>
@@ -27,7 +27,7 @@ inline double NearestNeighborSort::BestNodeToNodeDistance(
     const TreeType* referenceNode,
     const double centerToCenterDistance)
 {
-  return queryNode->MinDistance(referenceNode, centerToCenterDistance);
+  return queryNode->MinDistance(*referenceNode, centerToCenterDistance);
 }
 
 template<typename TreeType>
@@ -37,7 +37,7 @@ inline double NearestNeighborSort::BestNodeToNodeDistance(
     const TreeType* referenceChildNode,
     const double centerToCenterDistance)
 {
-  return queryNode->MinDistance(referenceChildNode, centerToCenterDistance) -
+  return queryNode->MinDistance(*referenceChildNode, centerToCenterDistance) -
       referenceChildNode->ParentDistance();
 }
 

src/mlpack/methods/range_search/range_search_rules_impl.hpp

@@ -179,7 +179,7 @@ double RangeSearchRules<MetricType, TreeType>::Score(TreeType& queryNode,
   else
   {
     // Just perform the calculation.
-    distances = referenceNode.RangeDistance(&queryNode);
+    distances = referenceNode.RangeDistance(queryNode);
     ++scores;
   }