Patch submitted by user to fix warnings

[jlblancoc]

TODO: Take a look at the patch:

"there is a couple of warning when compiling in 64 bits" ->

Index: nanoflann.hpp

--- nanoflann.hpp (revision 39165) +++ nanoflann.hpp (working copy) @@ -396,12 +396,12 @@ */ struct KDTreeSingleIndexAdaptorParams {

• KDTreeSingleIndexAdaptorParams(size_t _leaf_maxsize = 10, int dim = -1) :

• KDTreeSingleIndexAdaptorParams(const int _leaf_max_size = 10, size_t dim_ = -1) :
    leaf_max_size(_leaf_max_size), dim(dim_)
  {}

• size_t leaf_max_size;

• int dim;
• const int leaf_max_size;

• size_t dim;

  };

  /* Search options for KDTreeSingleIndexAdaptor::findNeighbors() / @@ -753,7 +753,7 @@ const KDTreeSingleIndexAdaptorParams index_params;

  size_t m_size;

• int dim; //!< Dimensionality of each data point

• size_t dim;  //!< Dimensionality of each data point
  
  /*--------------------- Internal Data Structures --------------------------*/

  @@ -846,7 +846,7 @@ * inputData = dataset with the input features * params = parameters passed to the kdtree algorithm (see http://code.google.com/p/nanoflann/ for help choosing the parameters) */

• KDTreeSingleIndexAdaptor(const int dimensionality, const DatasetAdaptor& inputData, const KDTreeSingleIndexAdaptorParams& params = KDTreeSingleIndexAdaptorParams() ) :

• KDTreeSingleIndexAdaptor(const size_t dimensionality, const DatasetAdaptor& inputData, const KDTreeSingleIndexAdaptorParams& params = KDTreeSingleIndexAdaptorParams() ) :
    dataset(inputData), index_params(params), root_node(NULL), distance(inputData)
  {
    m_size = dataset.kdtree_get_point_count();

  @@ -1371,7 +1371,7 @@ index_t* index; //! The kd-tree index for the user to call its methods as usual with any other FLANN index.

  /// Constructor: takes a const ref to the matrix object with the data points

• KDTreeEigenMatrixAdaptor(const int dimensionality, const MatrixType &mat, const int leaf_max_size = 10) : m_data_matrix(mat)

• KDTreeEigenMatrixAdaptor(const size_t dimensionality, const MatrixType &mat, const int leaf_max_size = 10) : m_data_matrix(mat)
  {
    const size_t dims = mat.cols();
    if (DIM>0 && static_cast<int>(dims)!=DIM)

  @@ -1425,7 +1425,7 @@ }

  // Returns the dim'th component of the idx'th point in the class:

• inline num_t kdtree_get_pt(const size_t idx, int dim) const {
• inline num_t kdtree_get_pt(const size_t idx, size_t dim) const { return m_data_matrix.coeff(idx,dim); }

[jlblancoc]

We'll close this without replacing int -> size_t as proposed. The reason: In C/C++,

The int and unsigned int types are, by definition, the most efficient 
ones available on the platform that can hold at least a 16-bit range.