/usr/include/shogun/distance/Distance.h is in libshogun-dev 3.2.0-7.3build4.
This file is owned by root:root, with mode 0o644.
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* This program is free software; you can redistribute it and/or modify
* it under the terms of the GNU General Public License as published by
* the Free Software Foundation; either version 3 of the License, or
* (at your option) any later version.
*
* Written (W) 2006-2009 Christian Gehl
* Written (W) 2006-2009 Soeren Sonnenburg
* Copyright (C) 2006-2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef _DISTANCE_H___
#define _DISTANCE_H___
#include <stdio.h>
#include <shogun/lib/common.h>
#include <shogun/io/File.h>
#include <shogun/mathematics/Math.h>
#include <shogun/base/SGObject.h>
#include <shogun/features/FeatureTypes.h>
#include <shogun/features/Features.h>
namespace shogun
{
class CFile;
class CMath;
class CFeatures;
/** type of distance */
enum EDistanceType
{
D_UNKNOWN = 0,
D_MINKOWSKI = 10,
D_MANHATTAN = 20,
D_CANBERRA = 30,
D_CHEBYSHEW = 40,
D_GEODESIC = 50,
D_JENSEN = 60,
D_MANHATTANWORD = 70,
D_HAMMINGWORD = 80 ,
D_CANBERRAWORD = 90,
D_SPARSEEUCLIDEAN = 100,
D_EUCLIDEAN = 110,
D_CHISQUARE = 120,
D_TANIMOTO = 130,
D_COSINE = 140,
D_BRAYCURTIS = 150,
D_CUSTOM = 160,
D_ATTENUATEDEUCLIDEAN = 170,
D_MAHALANOBIS = 180,
D_DIRECTOR = 190,
D_CUSTOMMAHALANOBIS = 200
};
/** @brief Class Distance, a base class for all the distances used in
* the Shogun toolbox.
*
* The distance (or metric) is a function
* \f$ d: X \times X \to R \f$ satisfying (for all \f$ x,y,z \in X\f$) conditions below:
* - \f$ d(x,y) \geq 0 \f$
*
* - \f$ d(x,y) = 0\f$ if and only if \f$ x=y\f$
*
* - \f$ d(x,y) = d(y,x) \f$
*
* - \f$ d(x,y) \leq d(x,z) + d(z,y) \f$
*
* Currently distance inherited from the CDistance class should be
* symmetric.
*
* The simplest example of a distance function is the Euclidean
* distance: @see CEuclideanDistance
*
* In the means of Shogun toolbox the distance function is defined
* on the 'space' of CFeatures.
*
*/
class CDistance : public CSGObject
{
public:
/** default constructor */
CDistance();
/** init distance
*
* @param lhs features of left-hand side
* @param rhs features of right-hand side
* @return if init was successful
*/
CDistance(CFeatures* lhs, CFeatures* rhs);
virtual ~CDistance();
/** get distance function for lhs feature vector a
* and rhs feature vector b
*
* @param idx_a feature vector a at idx_a
* @param idx_b feature vector b at idx_b
* @return distance value
*/
virtual float64_t distance(int32_t idx_a, int32_t idx_b);
/** get distance function for lhs feature vector a
* and rhs feature vector b. The computation of the
* distance stops if the intermediate result is
* larger than upper_bound. This is useful to use
* with John Langford's Cover Tree and it is ONLY
* implemented for Euclidean distance
*
* @param idx_a feature vector a at idx_a
* @param idx_b feature vector b at idx_b
* @param upper_bound value above which the computation
* halts
* @return distance value or upper_bound
*/
virtual float64_t distance_upper_bounded(int32_t idx_a, int32_t idx_b, float64_t upper_bound)
{
return distance(idx_a, idx_b);
}
/** get distance matrix
*
* @return computed distance matrix (needs to be cleaned up)
*/
SGMatrix<float64_t> get_distance_matrix()
{
return get_distance_matrix<float64_t>();
}
/** get distance matrix (templated)
*
* @return the distance matrix
*/
template <class T> SGMatrix<T> get_distance_matrix();
/** compute row start offset for parallel kernel matrix computation
*
* @param offs offset
* @param n number of columns
* @param symmetric whether matrix is symmetric
*/
int32_t compute_row_start(int64_t offs, int32_t n, bool symmetric)
{
int32_t i_start;
if (symmetric)
i_start=(int32_t) CMath::floor(n-CMath::sqrt(CMath::sq((float64_t) n)-offs));
else
i_start=(int32_t) (offs/int64_t(n));
return i_start;
}
/** helper for computing the kernel matrix in a parallel way
*
* @param p thread parameters
*/
template <class T> static void* get_distance_matrix_helper(void* p);
/** init distance
*
* make sure to check that your distance can deal with the
* supplied features (!)
*
* @param lhs features of left-hand side
* @param rhs features of right-hand side
* @return if init was successful
*/
virtual bool init(CFeatures* lhs, CFeatures* rhs);
/** cleanup distance
*
* abstract base method
*/
virtual void cleanup()=0;
/** load the kernel matrix
*
* @param loader File object via which to load data
*/
void load(CFile* loader);
/** save kernel matrix
*
* @param writer File object via which to save data
*/
void save(CFile* writer);
/** get left-hand side features used in distance matrix
*
* @return left-hand side features
*/
inline CFeatures* get_lhs() { SG_REF(lhs); return lhs; };
/** get right-hand side features used in distance matrix
*
* @return right-hand side features
*/
inline CFeatures* get_rhs() { SG_REF(rhs); return rhs; };
/** replace right-hand side features used in distance matrix
*
* make sure to check that your distance can deal with the
* supplied features (!)
*
* @param rhs features of right-hand side
* @return replaced right-hand side features
*/
CFeatures* replace_rhs(CFeatures* rhs);
/** replace left-hand side features used in distance matrix
*
* make sure to check that your distance can deal with the
* supplied features (!)
*
* @param lhs features of right-hand side
* @return replaced left-hand side features
*/
CFeatures* replace_lhs(CFeatures* lhs);
/** remove lhs and rhs from distance */
virtual void remove_lhs_and_rhs();
/// takes all necessary steps if the lhs is removed from distance matrix
virtual void remove_lhs();
/// takes all necessary steps if the rhs is removed from distance matrix
virtual void remove_rhs();
/** get distance type we are
*
* abstrace base method
*
* @return distance type
*/
virtual EDistanceType get_distance_type()=0 ;
/** get feature type the distance can deal with
*
* abstrace base method
*
* @return feature type
*/
virtual EFeatureType get_feature_type()=0;
/** get feature class the distance can deal with
*
* abstract base method
*
* @return feature class
*/
virtual EFeatureClass get_feature_class()=0;
/** FIXME: precompute matrix should be dropped, handling
* should be via customdistance
*
* @return if precompute_matrix
*/
inline bool get_precompute_matrix() { return precompute_matrix ; }
/** FIXME: precompute matrix should be dropped, handling
* should be via customdistance
*
* @param flag if precompute_matrix
*/
virtual void set_precompute_matrix(bool flag)
{
precompute_matrix=flag;
if (!precompute_matrix)
{
SG_FREE(precomputed_matrix);
precomputed_matrix=NULL;
}
}
/** get number of vectors of lhs features
*
* @return number of vectors of left-hand side
*/
virtual int32_t get_num_vec_lhs()
{
return num_lhs;
}
/** get number of vectors of rhs features
*
* @return number of vectors of right-hand side
*/
virtual int32_t get_num_vec_rhs()
{
return num_rhs;
}
/** test whether features have been assigned to lhs and rhs
*
* @return true if features are assigned
*/
virtual bool has_features()
{
return lhs && rhs;
}
/** test whether features on lhs and rhs are the same
*
* @return true if features are the same
*/
inline bool lhs_equals_rhs()
{
return lhs==rhs;
}
protected:
/// run distance thread
static void* run_distance_thread(void* p);
/// compute distance function for features a and b
/// idx_{a,b} denote the index of the feature vectors
/// in the corresponding feature object
virtual float64_t compute(int32_t idx_a, int32_t idx_b)=0;
/// matrix precomputation
void do_precompute_matrix();
private:
void init();
protected:
/** FIXME: precompute matrix should be dropped, handling
* should be via customdistance
*/
float32_t * precomputed_matrix;
/** FIXME: precompute matrix should be dropped, handling
* should be via customdistance
*/
bool precompute_matrix;
/// feature vectors to occur on the left hand side
CFeatures* lhs;
/// feature vectors to occur on the right hand side
CFeatures* rhs;
/** number of feature vectors on the left hand side */
int32_t num_lhs;
/** number of feature vectors on the right hand side */
int32_t num_rhs;
};
} // namespace shogun
#endif
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