kmeans.h

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/*
Copyright (C) 2007-12 Andrea Vedaldi and Brian Fulkerson.
Copyright (C) 2013 Andrea Vedaldi and David Novotny.
All rights reserved.

This file is part of the VLFeat library and is made available under
the terms of the BSD license (see the COPYING file).
*/

#ifndef VL_KMEANS_H
#define VL_KMEANS_H

#include "generic.h"
#include "random.h"
#include "mathop.h"
#include "kdtree.h"

/* ---------------------------------------------------------------- */

typedef enum _VlKMeansAlgorithm {
  VlKMeansLloyd,       
  VlKMeansElkan,       
  VlKMeansANN          
} VlKMeansAlgorithm ;

typedef enum _VlKMeansInitialization {
  VlKMeansRandomSelection,  
  VlKMeansPlusPlus          
} VlKMeansInitialization ;

typedef struct _VlKMeans
{

  vl_type dataType ;                      
  vl_size dimension ;                     
  vl_size numCenters ;                    
  vl_size numTrees ;                      
  vl_size maxNumComparisons ;             
  VlKMeansInitialization initialization ; 
  VlKMeansAlgorithm algorithm ;           
  VlVectorComparisonType distance ;       
  vl_size maxNumIterations ;              
  double minEnergyVariation ;             
  vl_size numRepetitions ;                
  int verbosity ;                         
  void * centers ;                        
  void * centerDistances ;                
  double energy ;                         
  VlFloatVectorComparisonFunction floatVectorComparisonFn ;
  VlDoubleVectorComparisonFunction doubleVectorComparisonFn ;
} VlKMeans ;

VL_EXPORT VlKMeans * vl_kmeans_new (vl_type dataType, VlVectorComparisonType distance) ;
VL_EXPORT VlKMeans * vl_kmeans_new_copy (VlKMeans const * kmeans) ;
VL_EXPORT void vl_kmeans_delete (VlKMeans * self) ;
VL_EXPORT void vl_kmeans_reset (VlKMeans * self) ;

VL_EXPORT double vl_kmeans_cluster (VlKMeans * self,
                                    void const * data,
                                    vl_size dimension,
                                    vl_size numData,
                                    vl_size numCenters) ;

VL_EXPORT void vl_kmeans_quantize (VlKMeans * self,
                                   vl_uint32 * assignments,
                                   void * distances,
                                   void const * data,
                                   vl_size numData) ;

VL_EXPORT void vl_kmeans_quantize_ANN (VlKMeans * self,
                                   vl_uint32 * assignments,
                                   void * distances,
                                   void const * data,
                                   vl_size numData,
                                   vl_size iteration );
VL_EXPORT void vl_kmeans_set_centers (VlKMeans * self,
                                      void const * centers,
                                      vl_size dimension,
                                      vl_size numCenters) ;

VL_EXPORT void vl_kmeans_init_centers_with_rand_data
                  (VlKMeans * self,
                   void const * data,
                   vl_size dimensions,
                   vl_size numData,
                   vl_size numCenters) ;

VL_EXPORT void vl_kmeans_init_centers_plus_plus
                  (VlKMeans * self,
                   void const * data,
                   vl_size dimensions,
                   vl_size numData,
                   vl_size numCenters) ;

VL_EXPORT double vl_kmeans_refine_centers (VlKMeans * self,
                                           void const * data,
                                           vl_size numData) ;

VL_INLINE vl_type vl_kmeans_get_data_type (VlKMeans const * self) ;
VL_INLINE VlVectorComparisonType vl_kmeans_get_distance (VlKMeans const * self) ;

VL_INLINE VlKMeansAlgorithm vl_kmeans_get_algorithm (VlKMeans const * self) ;
VL_INLINE VlKMeansInitialization vl_kmeans_get_initialization (VlKMeans const * self) ;
VL_INLINE vl_size vl_kmeans_get_num_repetitions (VlKMeans const * self) ;

VL_INLINE vl_size vl_kmeans_get_dimension (VlKMeans const * self) ;
VL_INLINE vl_size vl_kmeans_get_num_centers (VlKMeans const * self) ;

VL_INLINE int vl_kmeans_get_verbosity (VlKMeans const * self) ;
VL_INLINE vl_size vl_kmeans_get_max_num_iterations (VlKMeans const * self) ;
VL_INLINE double vl_kmeans_get_min_energy_variation (VlKMeans const * self) ;
VL_INLINE vl_size vl_kmeans_get_max_num_comparisons (VlKMeans const * self) ;
VL_INLINE vl_size vl_kmeans_get_num_trees (VlKMeans const * self) ;
VL_INLINE double vl_kmeans_get_energy (VlKMeans const * self) ;
VL_INLINE void const * vl_kmeans_get_centers (VlKMeans const * self) ;
VL_INLINE void vl_kmeans_set_algorithm (VlKMeans * self, VlKMeansAlgorithm algorithm) ;
VL_INLINE void vl_kmeans_set_initialization (VlKMeans * self, VlKMeansInitialization initialization) ;
VL_INLINE void vl_kmeans_set_num_repetitions (VlKMeans * self, vl_size numRepetitions) ;
VL_INLINE void vl_kmeans_set_max_num_iterations (VlKMeans * self, vl_size maxNumIterations) ;
VL_INLINE void vl_kmeans_set_min_energy_variation (VlKMeans * self, double minEnergyVariation) ;
VL_INLINE void vl_kmeans_set_verbosity (VlKMeans * self, int verbosity) ;
VL_INLINE void vl_kmeans_set_max_num_comparisons (VlKMeans * self, vl_size maxNumComparisons) ;
VL_INLINE void vl_kmeans_set_num_trees (VlKMeans * self, vl_size numTrees) ;
VL_INLINE vl_type
vl_kmeans_get_data_type (VlKMeans const * self)
{
  return self->dataType ;
}

VL_INLINE vl_size
vl_kmeans_get_dimension (VlKMeans const * self)
{
  return self->dimension ;
}

VL_INLINE VlVectorComparisonType
vl_kmeans_get_distance (VlKMeans const * self)
{
  return self->distance ;
}

VL_INLINE vl_size
vl_kmeans_get_num_centers (VlKMeans const * self)
{
  return self->numCenters ;
}

VL_INLINE double
vl_kmeans_get_energy (VlKMeans const * self)
{
  return self->energy ;
}

VL_INLINE int
vl_kmeans_get_verbosity (VlKMeans const * self)
{
  return self->verbosity ;
}

VL_INLINE void
vl_kmeans_set_verbosity (VlKMeans * self, int verbosity)
{
  self->verbosity = verbosity ;
}

VL_INLINE void const *
vl_kmeans_get_centers (VlKMeans const * self)
{
  return self->centers ;
}

VL_INLINE vl_size
vl_kmeans_get_max_num_iterations (VlKMeans const * self)
{
  return self->maxNumIterations ;
}

VL_INLINE void
vl_kmeans_set_max_num_iterations (VlKMeans * self, vl_size maxNumIterations)
{
  self->maxNumIterations = maxNumIterations ;
}

VL_INLINE vl_size
vl_kmeans_get_num_repetitions (VlKMeans const * self)
{
  return self->numRepetitions ;
}

VL_INLINE void
vl_kmeans_set_num_repetitions (VlKMeans * self,
                               vl_size numRepetitions)
{
  assert (numRepetitions >= 1) ;
  self->numRepetitions = numRepetitions ;
}

VL_INLINE double
vl_kmeans_get_min_energy_variation (VlKMeans const * self)
{
  return self->minEnergyVariation ;
}

VL_INLINE void
vl_kmeans_set_min_energy_variation (VlKMeans * self,
                                    double minEnergyVariation)
{
  assert (minEnergyVariation >= 0) ;
  self->minEnergyVariation = minEnergyVariation ;
}

VL_INLINE VlKMeansAlgorithm
vl_kmeans_get_algorithm (VlKMeans const * self)
{
  return self->algorithm ;
}

VL_INLINE void
vl_kmeans_set_algorithm (VlKMeans * self, VlKMeansAlgorithm algorithm)
{
  self->algorithm = algorithm ;
}

VL_INLINE VlKMeansInitialization
vl_kmeans_get_initialization (VlKMeans const * self)
{
  return self->initialization ;
}

VL_INLINE void
vl_kmeans_set_initialization (VlKMeans * self,
                              VlKMeansInitialization initialization)
{
  self->initialization = initialization ;
}

VL_INLINE vl_size
vl_kmeans_get_max_num_comparisons (VlKMeans const * self)
{
  return self->maxNumComparisons ;
}

VL_INLINE void
vl_kmeans_set_max_num_comparisons (VlKMeans * self,
                              vl_size maxNumComparisons)
{
    self->maxNumComparisons = maxNumComparisons;
}

VL_INLINE void
vl_kmeans_set_num_trees (VlKMeans * self, vl_size numTrees)
{
    self->numTrees = numTrees;
}

VL_INLINE vl_size
vl_kmeans_get_num_trees (VlKMeans const * self)
{
    return self->numTrees;
}


/* VL_IKMEANS_H */
#endif