/usr/include/shogun/distance/CustomDistance.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) 1999-2009 Soeren Sonnenburg
* Copyright (C) 1999-2009 Fraunhofer Institute FIRST and Max-Planck-Society
*/
#ifndef _CUSTOMDISTANCE_H___
#define _CUSTOMDISTANCE_H___
#include <shogun/mathematics/Math.h>
#include <shogun/lib/common.h>
#include <shogun/distance/Distance.h>
#include <shogun/features/Features.h>
namespace shogun
{
/** @brief The Custom Distance allows for custom user provided distance matrices.
*
* For squared training matrices it allows to store only the upper triangle of
* the distance to save memory: Full symmetric distance matrices can be stored as
* is or can be internally converted into (or directly given in) upper triangle
* representation. Also note that values are stored as 32bit floats.
*
*/
class CCustomDistance: public CDistance
{
public:
/** default constructor */
CCustomDistance();
/** constructor
*
* compute custom distance from given distance matrix
* @param d distance matrix
*/
CCustomDistance(CDistance* d);
/** constructor
* @param distance_matrix distance matrix
*/
CCustomDistance(const SGMatrix<float64_t> distance_matrix);
/** constructor
*
* sets full distance matrix from full distance matrix
* (from double precision floats)
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
CCustomDistance(
const float64_t* dm, int32_t rows, int32_t cols);
/** constructor
*
* sets full distance matrix from full distance matrix
* (from single precision floats)
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
CCustomDistance(
const float32_t* dm, int32_t rows, int32_t cols);
virtual ~CCustomDistance();
/** initialize distance with dummy features
*
* Distances always need feature objects assigned. As the custom distance
* does not really require this it creates some magic dummy features
* that only know about the number of vectors
*
* @param rows features of left-hand side
* @param cols features of right-hand side
* @return if initializing was successful
*/
virtual bool dummy_init(int32_t rows, int32_t cols);
/** initialize distance
*
* @param l features of left-hand side
* @param r features of right-hand side
* @return if initializing was successful
*/
virtual bool init(CFeatures* l, CFeatures* r);
/** clean up distance */
virtual void cleanup();
/** return what type of distance we are
*
* @return distance type CUSTOM
*/
virtual EDistanceType get_distance_type() { return D_CUSTOM; }
/** return feature type the distance can deal with
*
* @return feature type ANY
*/
virtual EFeatureType get_feature_type() { return F_ANY; }
/** return feature class the distance can deal with
*
* @return feature class ANY
*/
virtual EFeatureClass get_feature_class() { return C_ANY; }
/** return the distance's name
*
* @return name Custom
*/
virtual const char* get_name() const { return "CustomDistance"; }
/** set distance matrix (only elements from upper triangle)
* from elements of upper triangle (concat'd), including the
* main diagonal
*
* small variant for floats64's, triangle needs to have less than 2**32 elements
*
* @param dm distance matrix
* @param len denotes the size of the array and should match len=cols*(cols+1)/2
* @return if setting was successful
*/
bool set_triangle_distance_matrix_from_triangle(
const float64_t* dm, int32_t len)
{
return set_triangle_distance_matrix_from_triangle_generic(dm, len);
}
/** set distance matrix (only elements from upper triangle)
* from elements of upper triangle (concat'd), including the
* main diagonal
*
* small variant for floats32's, triangle needs to have less than 2**32 elements
*
* @param dm distance matrix
* @param len denotes the size of the array and should match len=cols*(cols+1)/2
* @return if setting was successful
*/
bool set_triangle_distance_matrix_from_triangle(
const float32_t* dm, int32_t len)
{
return set_triangle_distance_matrix_from_triangle_generic(dm, len);
}
/** set distance matrix (only elements from upper triangle)
* from elements of upper triangle (concat'd), including the
* main diagonal
*
* big variant, allowing the triangle to have more than 2**31-1 elements
*
* @param dm distance matrix
* @param len denotes the size of the array and should match len=cols*(cols+1)/2
* @return if setting was successful
*/
template <class T>
bool set_triangle_distance_matrix_from_triangle_generic(
const T* dm, int64_t len)
{
ASSERT(dm)
ASSERT(len>0)
int64_t cols = (int64_t) floor(-0.5 + CMath::sqrt(0.25+2*len));
int64_t int32_max=2147483647;
if (cols> int32_max)
SG_ERROR("Matrix larger than %d x %d\n", int32_max)
if (cols*(cols+1)/2 != len)
{
SG_ERROR("dm should be a vector containing a lower triangle matrix, with len=cols*(cols+1)/2 elements\n")
return false;
}
cleanup_custom();
SG_DEBUG("using custom distance of size %dx%d\n", cols,cols)
dmatrix= SG_MALLOC(float32_t, len);
upper_diagonal=true;
num_rows=cols;
num_cols=cols;
for (int64_t i=0; i<len; i++)
dmatrix[i]=dm[i];
dummy_init(num_rows, num_cols);
return true;
}
/** set distance matrix (only elements from upper triangle)
* from squared matrix
*
* for float64's
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
inline bool set_triangle_distance_matrix_from_full(
const float64_t* dm, int32_t rows, int32_t cols)
{
return set_triangle_distance_matrix_from_full_generic(dm, rows, cols);
}
/** set distance matrix (only elements from upper triangle)
* from squared matrix
*
* for float32's
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
inline bool set_triangle_distance_matrix_from_full(
const float32_t* dm, int32_t rows, int32_t cols)
{
return set_triangle_distance_matrix_from_full_generic(dm, rows, cols);
}
/** set distance matrix (only elements from upper triangle)
* from squared matrix
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
template <class T>
bool set_triangle_distance_matrix_from_full_generic(
const T* dm, int32_t rows, int32_t cols)
{
ASSERT(rows==cols)
cleanup_custom();
SG_DEBUG("using custom distance of size %dx%d\n", cols,cols)
dmatrix= SG_MALLOC(float32_t, int64_t(cols)*(cols+1)/2);
upper_diagonal=true;
num_rows=cols;
num_cols=cols;
for (int64_t row=0; row<num_rows; row++)
{
for (int64_t col=row; col<num_cols; col++)
{
int64_t idx=row * num_cols - row*(row+1)/2 + col;
dmatrix[idx]= (float32_t) dm[col*num_rows+row];
}
}
dummy_init(rows, cols);
return true;
}
/** set full distance matrix from full distance matrix
*
* for float64's
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
bool set_full_distance_matrix_from_full(
const float64_t* dm, int32_t rows, int32_t cols)
{
return set_full_distance_matrix_from_full_generic(dm, rows, cols);
}
/** set full distance matrix from full distance matrix
*
* for float32's
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
bool set_full_distance_matrix_from_full(
const float32_t* dm, int32_t rows, int32_t cols)
{
return set_full_distance_matrix_from_full_generic(dm, rows, cols);
}
/** set full distance matrix from full distance matrix
*
* @param dm distance matrix
* @param rows number of rows in matrix
* @param cols number of cols in matrix
* @return if setting was successful
*/
template <class T>
bool set_full_distance_matrix_from_full_generic(const T* dm, int32_t rows, int32_t cols)
{
cleanup_custom();
SG_DEBUG("using custom distance of size %dx%d\n", rows,cols)
dmatrix=SG_MALLOC(float32_t, rows*cols);
upper_diagonal=false;
num_rows=rows;
num_cols=cols;
for (int32_t row=0; row<num_rows; row++)
{
for (int32_t col=0; col<num_cols; col++)
{
dmatrix[row * num_cols + col]=dm[col*num_rows+row];
}
}
dummy_init(rows, cols);
return true;
}
/** get number of vectors of lhs features
*
* @return number of vectors of left-hand side
*/
virtual int32_t get_num_vec_lhs()
{
return num_rows;
}
/** get number of vectors of rhs features
*
* @return number of vectors of right-hand side
*/
virtual int32_t get_num_vec_rhs()
{
return num_cols;
}
/** test whether features have been assigned to lhs and rhs
*
* @return true if features are assigned
*/
virtual bool has_features()
{
return (num_rows>0) && (num_cols>0);
}
protected:
/** compute distance function
*
* @param row row
* @param col col
* @return computed distance function
*/
virtual float64_t compute(int32_t row, int32_t col);
private:
void init();
/** only cleanup stuff specific to Custom distance */
void cleanup_custom();
protected:
/** distance matrix */
float32_t* dmatrix;
/** number of rows */
int32_t num_rows;
/** number of columns */
int32_t num_cols;
/** upper diagonal */
bool upper_diagonal;
};
}
#endif /* _CUSTOMKERNEL_H__ */
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