[SpatialPartitioning] Refactor KdTree into KdTreeDense + KdTreeSparse

poncateam · Dec 19, 2023 · 518fed8 · 518fed8
1 parent 8f9df5f
commit 518fed8
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Showing 17 changed files with 316 additions and 192 deletions.
diff --git a/CHANGELOG b/CHANGELOG
@@ -6,7 +6,11 @@ Ponca changelog
 Current head (v.1.3 RC)
 
 - API
-    - [SpatialPartitioning] Change part of the kdtree API (#123)
+    - [spatialPartitioning] Change part of the kdtree API (#123)
+    - [spatialPartitioning] Refactor KdTree into KdTreeDense + KdTreeSparse (#129)
+
+- Docs
+    - [spatialPartitioning] Update KdTree docs to reflect the kdtree API refactor (#129)
 
 --------------------------------------------------------------------------------
 v.1.2

diff --git a/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeKNearestQueries.h b/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeKNearestQueries.h
@@ -25,7 +25,7 @@ class KdTreeKNearestQueryBase : public KdTreeQuery<Traits>, public QueryType
     using QueryAccelType = KdTreeQuery<Traits>;
     using Iterator       = IteratorType<typename Traits::IndexType, typename Traits::DataPoint>;
 
-    inline KdTreeKNearestQueryBase(const KdTreeBase<Traits>* kdtree, IndexType k, typename QueryType::InputType input) :
+    inline KdTreeKNearestQueryBase(const KdTreeImplBase<Traits>* kdtree, IndexType k, typename QueryType::InputType input) :
             KdTreeQuery<Traits>(kdtree), QueryType(k, input) { }
 
 public:

diff --git a/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeNearestQueries.h b/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeNearestQueries.h
@@ -25,7 +25,7 @@ class KdTreeNearestQueryBase : public KdTreeQuery<Traits>, public QueryType
     using QueryAccelType = KdTreeQuery<Traits>;
     using Iterator       = IteratorType<typename Traits::IndexType>;
 
-    KdTreeNearestQueryBase(const KdTreeBase<Traits>* kdtree, typename QueryType::InputType input) :
+    KdTreeNearestQueryBase(const KdTreeImplBase<Traits>* kdtree, typename QueryType::InputType input) :
             KdTreeQuery<Traits>(kdtree), QueryType(input){}
 
 public:

diff --git a/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeQuery.h b/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeQuery.h
@@ -10,7 +10,7 @@
 #include "../../../Common/Containers/stack.h"
 
 namespace Ponca {
-template <typename Traits> class KdTreeBase;
+template <typename Traits> class KdTreeImplBase;
 
 template <typename Traits>
 class KdTreeQuery
@@ -21,7 +21,7 @@ class KdTreeQuery
     using Scalar     = typename DataPoint::Scalar;
     using VectorType = typename DataPoint::VectorType;
 
-    explicit inline KdTreeQuery(const KdTreeBase<Traits>* kdtree) : m_kdtree( kdtree ), m_stack() {}
+    explicit inline KdTreeQuery(const KdTreeImplBase<Traits>* kdtree) : m_kdtree( kdtree ), m_stack() {}
 
 protected:
     /// \brief Init stack for a new search
@@ -30,7 +30,7 @@ class KdTreeQuery
         m_stack.push({0,0});
     }
 
-    const KdTreeBase<Traits>* m_kdtree { nullptr };
+    const KdTreeImplBase<Traits>* m_kdtree { nullptr };
     Stack<IndexSquaredDistance<IndexType, Scalar>, 2 * Traits::MAX_DEPTH> m_stack;
 
     template<typename LeafPreparationFunctor,
@@ -44,11 +44,10 @@ class KdTreeQuery
                          ProcessNeighborFunctor processNeighborFunctor
                          )
     {
-        const auto& nodes   = m_kdtree->nodes();
-        const auto& points  = m_kdtree->points();
-        const auto& indices = m_kdtree->samples();
+        const auto& nodes  = m_kdtree->nodes();
+        const auto& points = m_kdtree->points();
 
-        if (nodes.empty() || points.empty() || indices.empty())
+        if (nodes.empty() || points.empty() || m_kdtree->sample_count() == 0)
             throw std::invalid_argument("Empty KdTree");
 
         while(!m_stack.empty())
@@ -66,7 +65,7 @@ class KdTreeQuery
                     prepareLeafTraversal(start, end);
                     for(IndexType i=start; i<end; ++i)
                     {
-                        IndexType idx = indices[i];
+                        IndexType idx = m_kdtree->pointFromSample(i);
                         if(skipFunctor(idx)) continue;
 
                         Scalar d = (point - points[idx].pos()).squaredNorm();

diff --git a/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeRangeQueries.h b/Ponca/src/SpatialPartitioning/KdTree/Query/kdTreeRangeQueries.h
@@ -30,7 +30,7 @@ class KdTreeRangeQueryBase : public KdTreeQuery<Traits>, public QueryType
     friend Iterator;
 
 public:
-    KdTreeRangeQueryBase(const KdTreeBase<Traits>* kdtree, Scalar radius, typename QueryType::InputType input) :
+    KdTreeRangeQueryBase(const KdTreeImplBase<Traits>* kdtree, Scalar radius, typename QueryType::InputType input) :
             KdTreeQuery<Traits>(kdtree), QueryType(radius, input){}
 
 public: