nabo.h
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1 /*
2 
3 Copyright (c) 2010--2011, Stephane Magnenat, ASL, ETHZ, Switzerland
4 You can contact the author at <stephane at magnenat dot net>
5 
6 All rights reserved.
7 
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9 modification, are permitted provided that the following conditions are met:
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19 THIS SOFTWARE IS PROVIDED BY THE COPYRIGHT HOLDERS AND CONTRIBUTORS "AS IS" AND
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28 SOFTWARE, EVEN IF ADVISED OF THE POSSIBILITY OF SUCH DAMAGE.
29 
30 */
31 
32 #ifndef __NABO_H
33 #define __NABO_H
34 
35 #include "Eigen/Core"
36 #if EIGEN_VERSION_AT_LEAST(2,92,0)
37  #define EIGEN3_API
38 #endif
39 #ifndef EIGEN3_API
40  #include "Eigen/Array"
41 #endif
42 #include <vector>
43 #include <map>
44 #include "third_party/any.hpp"
45 
204 namespace Nabo
206 {
208 
209 
211  #define NABO_VERSION "1.0.7"
212  #define NABO_VERSION_INT 10007
214 
215  // TODO (c++14) Convert invalidIndex, invalidValue to constexpr templated variables.
216  template <typename IndexType>
217  inline constexpr IndexType invalidIndex() {
218  static_assert(std::is_integral<IndexType>::value, "");
219  return std::is_unsigned<IndexType>::value ? std::numeric_limits<IndexType>::max() : IndexType(-1);
220  }
221 
222  template <typename ValueType>
223  inline constexpr ValueType invalidValue() {
224  static_assert(std::is_floating_point<ValueType>::value, "");
225  return std::numeric_limits<ValueType>::infinity();
226  }
227 
229  //
230  // TODO: replace with C++17 std::any.
231  struct Parameters: public std::map<std::string, linb::any>
232  {
236 
239  Parameters(const std::string& key, const linb::any& value){(*this)[key] = value;}
241 
245  template<typename T>
246  T get(const std::string& key, const T& defaultValue) const
247  {
248  const_iterator it(find(key));
249  if (it != end())
250  return linb::any_cast<T>(it->second);
251  else
252  return defaultValue;
253  }
254  };
255 
257  template<typename T, typename Cloud_T = Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> >
259  {
261  typedef typename Eigen::Matrix<T, Eigen::Dynamic, 1> Vector;
263  typedef typename Eigen::Matrix<T, Eigen::Dynamic, Eigen::Dynamic> Matrix;
265  typedef Cloud_T CloudType;
267  typedef int Index;
269  typedef typename Eigen::Matrix<Index, Eigen::Dynamic, 1> IndexVector;
271  typedef typename Eigen::Matrix<Index, Eigen::Dynamic, Eigen::Dynamic> IndexMatrix;
272 
274  const CloudType& cloud;
276  const Index dim;
278  const unsigned creationOptionFlags;
283 
285  static constexpr Index InvalidIndex = invalidIndex<Index>();
287  static constexpr T InvalidValue = invalidValue<T>();
288 
291  {
299  };
300 
303  {
305  };
306 
309  {
312  };
313 
315 
325  unsigned long knn(const Vector& query, IndexVector& indices, Vector& dists2, const Index k = 1, const T epsilon = 0, const unsigned optionFlags = 0, const T maxRadius = std::numeric_limits<T>::infinity()) const;
326 
328 
338  virtual unsigned long knn(const Matrix& query, IndexMatrix& indices, Matrix& dists2, const Index k = 1, const T epsilon = 0, const unsigned optionFlags = 0, const T maxRadius = std::numeric_limits<T>::infinity()) const = 0;
339 
341 
351  virtual unsigned long knn(const Matrix& query, IndexMatrix& indices, Matrix& dists2, const Vector& maxRadii, const Index k = 1, const T epsilon = 0, const unsigned optionFlags = 0) const = 0;
352 
354 
360  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());
361 
363 
368  static NearestNeighbourSearch* createBruteForce(const CloudType& cloud, const Index dim = std::numeric_limits<Index>::max(), const unsigned creationOptionFlags = 0);
369 
371 
377  static NearestNeighbourSearch* createKDTreeLinearHeap(const CloudType& cloud, const Index dim = std::numeric_limits<Index>::max(), const unsigned creationOptionFlags = 0, const Parameters& additionalParameters = Parameters());
378 
380 
386  static NearestNeighbourSearch* createKDTreeTreeHeap(const CloudType& cloud, const Index dim = std::numeric_limits<Index>::max(), const unsigned creationOptionFlags = 0, const Parameters& additionalParameters = Parameters());
387 
388 
389 
391  template <typename WrongMatrixType>
392  static NearestNeighbourSearch* create(const WrongMatrixType& cloud, const Index dim = std::numeric_limits<Index>::max(), const SearchType preferedType = KDTREE_LINEAR_HEAP, const unsigned creationOptionFlags = 0, const Parameters& additionalParameters = Parameters())
393  {
394  typedef int Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef[sizeof(WrongMatrixType) > 0 ? -1 : 1];
395  Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef dummy;
396  return NULL;
397  }
398 
400  template <typename WrongMatrixType>
401  static NearestNeighbourSearch* createBruteForce(const WrongMatrixType& cloud, const Index dim = std::numeric_limits<Index>::max(), const unsigned creationOptionFlags = 0)
402  {
403  typedef int Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef[sizeof(WrongMatrixType) > 0 ? -1 : 1];
404  Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef dummy;
405  return NULL;
406  }
407 
409  template <typename WrongMatrixType>
410  static NearestNeighbourSearch* createKDTreeLinearHeap(const WrongMatrixType& cloud, const Index dim = std::numeric_limits<Index>::max(), const unsigned creationOptionFlags = 0, const Parameters& additionalParameters = Parameters())
411  {
412  typedef int Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef[sizeof(WrongMatrixType) > 0 ? -1 : 1];
413  Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef dummy;
414  return NULL;
415  }
416 
418  template <typename WrongMatrixType>
419  static NearestNeighbourSearch* createKDTreeTreeHeap(const WrongMatrixType&, const Index dim = std::numeric_limits<Index>::max(), const unsigned creationOptionFlags = 0, const Parameters& additionalParameters = Parameters())
420  {
421  typedef int Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef[sizeof(WrongMatrixType) > 0 ? -1 : 1];
422  Please_make_sure_that_the_decltype_of_the_first_parameter_is_equal_to_the_Matrix_typedef dummy;
423  return NULL;
424  }
425 
428 
429  protected:
431  NearestNeighbourSearch(const CloudType& cloud, const Index dim, const unsigned creationOptionFlags);
432 
434 
440  void checkSizesKnn(const Matrix& query, const IndexMatrix& indices, const Matrix& dists2, const Index k, const unsigned optionFlags, const Vector* maxRadii = 0) const;
441  };
442 
443  // Convenience typedefs
444 
449 
451 }
452 
453 #endif // __NABO_H
Nabo::NearestNeighbourSearch::KDTREE_LINEAR_HEAP
@ KDTREE_LINEAR_HEAP
kd-tree with linear heap, good for small k (~up to 30)
Definition: nabo.h:293
Nabo
Namespace for Nabo.
Definition: experimental/kdtree_cpu.cpp:40
Nabo::NearestNeighbourSearch::KDTREE_CL_PT_IN_NODES
@ KDTREE_CL_PT_IN_NODES
kd-tree using openCL, pt in nodes, only available if OpenCL enabled, UNSTABLE API
Definition: nabo.h:295
Nabo::NearestNeighbourSearch::dim
const Index dim
the dimensionality of the data-point cloud
Definition: nabo.h:276
Nabo::Parameters
Parameter vector.
Definition: nabo.h:231
Nabo::NearestNeighbourSearch::SEARCH_TYPE_COUNT
@ SEARCH_TYPE_COUNT
number of search types
Definition: nabo.h:298
Nabo::NearestNeighbourSearch::checkSizesKnn
void checkSizesKnn(const Matrix &query, const IndexMatrix &indices, const Matrix &dists2, const Index k, const unsigned optionFlags, const Vector *maxRadii=0) const
Make sure that the output matrices have the right sizes. Throw an exception otherwise.
Definition: nabo/nabo.cpp:103
Nabo::NearestNeighbourSearch::NearestNeighbourSearch
NearestNeighbourSearch(const CloudType &cloud, const Index dim, const unsigned creationOptionFlags)
constructor
Definition: nabo/nabo.cpp:69
Nabo::NearestNeighbourSearch::createKDTreeLinearHeap
static NearestNeighbourSearch * createKDTreeLinearHeap(const WrongMatrixType &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Prevent creation of trees with the wrong matrix type. Currently only dynamic size matrices are suppor...
Definition: nabo.h:410
Nabo::NearestNeighbourSearch::TOUCH_STATISTICS
@ TOUCH_STATISTICS
perform statistics on the number of points touched
Definition: nabo.h:304
Nabo::NearestNeighbourSearch::maxBound
const Vector maxBound
the high bound of the search space (axis-aligned bounding box)
Definition: nabo.h:282
Nabo::NearestNeighbourSearch::ALLOW_SELF_MATCH
@ ALLOW_SELF_MATCH
allows the return of the same point as the query, if this point is in the data cloud; forbidden by de...
Definition: nabo.h:310
Nabo::invalidIndex
constexpr IndexType invalidIndex()
Definition: nabo.h:217
Index
NNSNabo::Index Index
Definition: python/nabo.cpp:11
Nabo::NearestNeighbourSearch::createKDTreeTreeHeap
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)
Definition: nabo/nabo.cpp:174
Nabo::NNSearchD
NearestNeighbourSearch< double > NNSearchD
nearest neighbour search with scalars of type double
Definition: nabo.h:448
Nabo::NearestNeighbourSearch::IndexVector
Eigen::Matrix< Index, Eigen::Dynamic, 1 > IndexVector
a vector of indices to data points
Definition: nabo.h:269
Nabo::NearestNeighbourSearch::cloud
const CloudType & cloud
the reference to the data-point cloud, which must remain valid during the lifetime of the NearestNeig...
Definition: nabo.h:274
Nabo::NearestNeighbourSearch< T, CloudType >::SearchType
SearchType
type of search
Definition: nabo.h:290
Nabo::NearestNeighbourSearch::CloudType
Cloud_T CloudType
a column-major Eigen matrix in which each column is a point; this matrix has dim rows
Definition: nabo.h:265
Nabo::NearestNeighbourSearch::creationOptionFlags
const unsigned creationOptionFlags
creation options
Definition: nabo.h:278
Nabo::NearestNeighbourSearch::BRUTE_FORCE_CL
@ BRUTE_FORCE_CL
brute-force using openCL, only available if OpenCL enabled, UNSTABLE API
Definition: nabo.h:297
Nabo::NearestNeighbourSearch::IndexMatrix
Eigen::Matrix< Index, Eigen::Dynamic, Eigen::Dynamic > IndexMatrix
a matrix of indices to data points
Definition: nabo.h:271
Nabo::NearestNeighbourSearch::Matrix
Eigen::Matrix< T, Eigen::Dynamic, Eigen::Dynamic > Matrix
a column-major Eigen matrix in which each column is a point; this matrix has dim rows
Definition: nabo.h:263
Nabo::NNSearchF
NearestNeighbourSearch< float > NNSearchF
nearest neighbour search with scalars of type float
Definition: nabo.h:446
Nabo::NearestNeighbourSearch::createBruteForce
static NearestNeighbourSearch * createBruteForce(const WrongMatrixType &cloud, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0)
Prevent creation of trees with the wrong matrix type. Currently only dynamic size matrices are suppor...
Definition: nabo.h:401
Nabo::NearestNeighbourSearch::createKDTreeLinearHeap
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)
Definition: nabo/nabo.cpp:166
Nabo::NearestNeighbourSearch::KDTREE_TREE_HEAP
@ KDTREE_TREE_HEAP
kd-tree with tree heap, good for large k (~from 30)
Definition: nabo.h:294
Nabo::Parameters::Parameters
Parameters()
Create an empty parameter vector.
Definition: nabo.h:234
Nabo::NearestNeighbourSearch::KDTREE_CL_PT_IN_LEAVES
@ KDTREE_CL_PT_IN_LEAVES
kd-tree using openCL, pt in leaves, only available if OpenCL enabled, UNSTABLE API
Definition: nabo.h:296
Nabo::NearestNeighbourSearch
Nearest neighbour search interface, templatized on scalar type.
Definition: nabo.h:258
Nabo::NearestNeighbourSearch::create
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.
Definition: nabo/nabo.cpp:135
Nabo::NearestNeighbourSearch< T, CloudType >::SearchOptionFlags
SearchOptionFlags
search option
Definition: nabo.h:308
Nabo::NearestNeighbourSearch::InvalidIndex
static constexpr Index InvalidIndex
the invalid index
Definition: nabo.h:285
Nabo::Parameters::get
T get(const std::string &key, const T &defaultValue) const
Get the value of a key, return defaultValue if the key does not exist.
Definition: nabo.h:246
Nabo::NearestNeighbourSearch::Vector
Eigen::Matrix< T, Eigen::Dynamic, 1 > Vector
an Eigen vector of type T, to hold the coordinates of a point
Definition: nabo.h:261
Nabo::Parameters::Parameters
Parameters(const std::string &key, const linb::any &value)
Create a parameter vector with a single entry.
Definition: nabo.h:239
Nabo::NearestNeighbourSearch::~NearestNeighbourSearch
virtual ~NearestNeighbourSearch()
virtual destructor
Definition: nabo.h:427
linb::any
Definition: any.hpp:35
Nabo::NearestNeighbourSearch::minBound
const Vector minBound
the low bound of the search space (axis-aligned bounding box)
Definition: nabo.h:280
Nabo::NearestNeighbourSearch::BRUTE_FORCE
@ BRUTE_FORCE
brute force, check distance to every point in the data
Definition: nabo.h:292
Nabo::NearestNeighbourSearch< T, CloudType >::CreationOptionFlags
CreationOptionFlags
creation option
Definition: nabo.h:302
Nabo::NearestNeighbourSearch::Index
int Index
an index to a Vector or a Matrix, for refering to data points
Definition: nabo.h:267
Nabo::NearestNeighbourSearch::create
static NearestNeighbourSearch * create(const WrongMatrixType &cloud, const Index dim=std::numeric_limits< Index >::max(), const SearchType preferedType=KDTREE_LINEAR_HEAP, const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Prevent creation of trees with the wrong matrix type. Currently only dynamic size matrices are suppor...
Definition: nabo.h:392
Nabo::NearestNeighbourSearch::createBruteForce
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.
Definition: nabo/nabo.cpp:158
Nabo::invalidValue
constexpr ValueType invalidValue()
Definition: nabo.h:223
Nabo::NearestNeighbourSearch::knn
unsigned long knn(const Vector &query, IndexVector &indices, Vector &dists2, const Index k=1, const T epsilon=0, const unsigned optionFlags=0, const T maxRadius=std::numeric_limits< T >::infinity()) const
Find the k nearest neighbours of query.
Definition: nabo/nabo.cpp:83
any.hpp
Nabo::NearestNeighbourSearch::InvalidValue
static constexpr T InvalidValue
the invalid value
Definition: nabo.h:287
Nabo::NearestNeighbourSearch::createKDTreeTreeHeap
static NearestNeighbourSearch * createKDTreeTreeHeap(const WrongMatrixType &, const Index dim=std::numeric_limits< Index >::max(), const unsigned creationOptionFlags=0, const Parameters &additionalParameters=Parameters())
Prevent creation of trees with the wrong matrix type. Currently only dynamic size matrices are suppor...
Definition: nabo.h:419
Nabo::NearestNeighbourSearch::SORT_RESULTS
@ SORT_RESULTS
sort points by distances, when k > 1; do not sort by default
Definition: nabo.h:311


libnabo
Author(s): St├ęphane Magnenat
autogenerated on Sat Mar 23 2024 02:52:25