38 template <
typename MatrixType>
41 MatrixType M = MatrixType::Random(3, 100);
42 MatrixType
q = MatrixType::Random(3, 5);
44 #ifdef NABO_TYPE_CREATE 46 #endif // NABO_TYPE_CREATE 48 #ifdef NABO_TYPE_BRUTE_FORCE 50 #endif // NABO_TYPE_BRUTE_FORCE 52 #ifdef NABO_TYPE_LINEAR_HEAP 54 #endif // NABO_TYPE_TREE_HEAP 56 #ifdef NABO_TYPE_TREE_HEAP 58 #endif // NABO_TYPE_TREE_HEAP 65 #ifdef NABO_EIGEN_DYNAMIC_TYPE 66 int value = testFunction<Eigen::MatrixXf>();
67 #endif // NABO_EIGEN_DYNAMIC_TYPE 69 #ifdef NABO_EIGEN_SEMI_DYNAMIC_TYPE 70 int value = testFunction<Eigen::Matrix<float, 5, Eigen::Dynamic> >();
71 #endif // NABO_EIGEN_SEMI_DYNAMIC_TYPE static NearestNeighbourSearch * create(const CloudType &cloud, const Index dim=std::numeric_limits< Index >::max(), const SearchType preferedType=KDTREE_LINEAR_HEAP, const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Create a nearest-neighbour search.
Nearest neighbour search interface, templatized on scalar type.
static NearestNeighbourSearch * createBruteForce(const CloudType &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0)
Create a nearest-neighbour search, using brute-force search, useful for comparison only...
static NearestNeighbourSearch * createKDTreeLinearHeap(const CloudType &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Create a nearest-neighbour search, using a kd-tree with linear heap, good for small k (~up to 30) ...
static NearestNeighbourSearch * createKDTreeTreeHeap(const CloudType &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Create a nearest-neighbour search, using a kd-tree with tree heap, good for large k (~from 30) ...