Revert "Update KDTreeArmadilloAdaptor.hpp"

This reverts commit 33f736c.

inst/include/internal/KDTreeArmadilloAdaptor.hpp

@@ -50,10 +50,6 @@ namespace Rnanoflann {
         {
             return m_data_matrix.get()(dim,idx);
         }
-
-        colvec col(uword idx) const {
-            return m_data_matrix.get().col(idx);
-        }
 
         template <class BBOX>
         bool kdtree_get_bbox(BBOX& bb) const
@@ -64,7 +60,7 @@ namespace Rnanoflann {
 
 
     // Define an Armadillo KDTreeAdaptor class
-    template <class MatrixType, class Distance, bool Square, int DIM = -1>
+    template <class MatrixType, class Distance, bool Square = false, int DIM = -1>
     struct KDTreeArmadilloAdaptor2
     {
         using self_t = KDTreeArmadilloAdaptor2<MatrixType, Distance, Square, DIM>;
@@ -100,10 +96,6 @@ namespace Rnanoflann {
         {
             return m_data_matrix.get().n_cols;
         }
-
-        colvec col(uword idx) const {
-            return m_data_matrix.get().col(idx);
-        }
 
         num_t kdtree_get_pt(uword idx, size_t dim) const
         {
@@ -116,70 +108,4 @@ namespace Rnanoflann {
             return false; // Optional bounding-box computation (not used in this example)
         }
     };
-
-    template <class MatrixType, class Distance, int DIM = -1>
-    struct KDTreeArmadilloAdaptor3
-    {
-        using self_t = KDTreeArmadilloAdaptor3<MatrixType, Distance, DIM>;
-        using num_t = typename MatrixType::elem_type;
-        using IndexType =  uword;
-
-        using metric_t = typename Distance::template traits<num_t, self_t>::distance_t;// You can change the distance metric as needed.
-
-        using index_t = nanoflann::KDTreeSingleIndexAdaptor<metric_t, self_t, DIM, IndexType>;
-
-        index_t* index_;
-
-        const double p;
-        const double p_1;
-
-        const std::reference_wrapper<const MatrixType> m_data_matrix;
-
-        explicit KDTreeArmadilloAdaptor3(const uword dimensionality, const std::reference_wrapper<const MatrixType>& mat, const double p,const uword leafs = 10)
-            : p(p), p_1(1.0/p), m_data_matrix(mat)
-        {
-            const auto dims = mat.get().n_rows; // Assumes column-major Armadillo matrix
-            if (static_cast<uword>(dims) != dimensionality)
-                throw std::runtime_error("Error: 'dimensionality' must match the column count in the data matrix");
-            if (DIM > 0 && static_cast<int>(dims) != DIM)
-                throw std::runtime_error("Data set dimensionality does not match the 'DIM' template argument");
-            index_ = new index_t(dims, *this /* adaptor */, nanoflann::KDTreeSingleIndexAdaptorParams(leafs));
-            index_->buildIndex();
-        }
-
-        ~KDTreeArmadilloAdaptor3() { delete index_; }
-
-        const self_t& derived() const { return *this; }
-        self_t& derived() { return *this; }
-
-        uword kdtree_get_point_count() const
-        {
-            return m_data_matrix.get().n_cols;
-        }
-
-        num_t kdtree_get_pt(uword idx, size_t dim) const
-        {
-            return m_data_matrix.get()(dim,idx);
-        }
-
-        colvec col(uword idx) const {
-            return m_data_matrix.get().col(idx);
-        }
-
-        const double getP() const {
-            return p;
-        }
-
-        const double getP_1() const {
-            return p_1;
-        }
-
-        template <class BBOX>
-        bool kdtree_get_bbox(BBOX& bb) const
-        {
-            return false; // Optional bounding-box computation (not used in this example)
-        }
-    };
-
-
 };