// Copyright (C) 2009 Davis E. King (davis@dlib.net)
// License: Boost Software License See LICENSE.txt for the full license.
#undef DLIB_SVm_KERNEL_MATRIX_ABSTRACT_
#ifdef DLIB_SVm_KERNEL_MATRIX_ABSTRACT_
#include <vector>
#include "kernel_abstract.h"
#include "../matrix/matrix_abstract.h"
#include "../algs.h"
namespace dlib
{
// ----------------------------------------------------------------------------------------
template <
typename kernel_type,
typename V
>
const matrix_exp kernel_matrix (
const kernel_type& kernel,
const V& v
);
/*!
requires
- kernel == a kernel function object as defined by the file dlib/svm/kernel_abstract.h.
This kernel must also be capable of operating on the contents of v.
- V == dlib::matrix, std::vector, dlib::std_vector_c, dlib::random_subset_selector,
dlib::linearly_independent_subset_finder, or kernel_type::sample_type.
- if (V is a dlib::matrix) then
- is_vector(v) == true
ensures
- if (V is of type kernel_type::sample_type) then
- returns a matrix R such that:
- R::type == kernel_type::scalar_type
- R.size() == 1
- R(0,0) == kernel(v,v)
- else
- returns a matrix R such that:
- R::type == kernel_type::scalar_type
- R is a square matrix of v.size() rows by v.size() columns
- for all valid r and c:
- R(r,c) == kernel(v(r), v(c))
!*/
// ----------------------------------------------------------------------------------------
template <
typename kernel_type,
typename V1,
typename V2
>
const matrix_exp kernel_matrix (
const kernel_type& kernel,
const V1& v1,
const V2& v2
);
/*!
requires
- kernel == a kernel function object as defined by the file dlib/svm/kernel_abstract.h
This kernel must also be capable of operating on the contents of v1 and v2.
- V1 == dlib::matrix, std::vector, dlib::std_vector_c, dlib::random_subset_selector,
dlib::linearly_independent_subset_finder, or kernel_type::sample_type.
- V2 == dlib::matrix, std::vector, dlib::std_vector_c, dlib::random_subset_selector,
dlib::linearly_independent_subset_finder, or kernel_type::sample_type.
- if (V1 is a dlib::matrix) then
- is_vector(v1) == true
- if (V2 is a dlib::matrix) then
- is_vector(v2) == true
ensures
- if (V1 and V2 are of type kernel_type::sample_type) then
- returns a matrix R such that:
- R::type == kernel_type::scalar_type
- R.size() == 1
- R(0,0) == kernel(v1,v2)
- else if (V1 is of type kernel_type::sample_type) then
- returns a matrix R such that:
- R::type == kernel_type::scalar_type
- R.nr() == 1
- R.nc() == v2.size()
- for all valid c:
- R(0,c) == kernel(v1, v2(c))
- else if (V2 is of type kernel_type::sample_type) then
- returns a matrix R such that:
- R::type == kernel_type::scalar_type
- R.nr() == v1.size()
- R.nc() == 1
- for all valid r:
- R(r,0) == kernel(v1(r), v2)
- else
- returns a matrix R such that:
- R::type == kernel_type::scalar_type
- R.nr() == v1.size()
- R.nc() == v2.size()
- for all valid r and c:
- R(r,c) == kernel(v1(r), v2(c))
A note about aliasing (see the examples/matrix_expressions_ex.cpp example program
for a discussion of what aliasing is in the context of the dlib::matrix):
kernel_matrix() expressions can detect aliasing of an argument if that
argument is of type kernel_type::sample_type. However, it can't detect
aliasing though std::vectors or other "list of sample type" container class
arguments. This means that it is safe to assign a kernel_matrix() expression
to a sample_type if V1 or V2 are of sample_type but not safe otherwise. However,
since the latter case results in a general n by m matrix rather than a column
or row vector you shouldn't ever be doing it anyway.
!*/
// ----------------------------------------------------------------------------------------
}
#endif // DLIB_SVm_KERNEL_MATRIX_ABSTRACT_