dlib C++ Library - kernel_matrix.h

    // Copyright (C) 2009  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    #ifndef DLIB_SVm_KERNEL_MATRIX_
    #define DLIB_SVm_KERNEL_MATRIX_

    #include <vector>
    #include "kernel_matrix_abstract.h"
    #include "../matrix.h"
    #include "../algs.h"

    namespace dlib
    {

    // ----------------------------------------------------------------------------------------
    // ----------------------------------------------------------------------------------------
    // ----------------------------------------------------------------------------------------

        namespace impl
        {
            template <typename kernel_type, typename T>
            inline const typename T::type& access ( const matrix_exp<T>& m, long i)
            {
                return m(i);
            }

            // bind to anything that looks like an array and isn't a matrix
            template <typename kernel_type, typename T>
            inline const typename disable_if<is_matrix<T>,typename T::type>::type& access ( const T& m, long i)
            {
                return m[i];
            }

            // Only use this function if T isn't a std::pair because in that case the entire vector is
            // probably itself a sparse sample.
            template <typename kernel_type, typename T, typename alloc>
            inline typename disable_if<is_pair<T>,const T&>::type access ( const std::vector<T,alloc>& m, long i)
            {
                return m[i];
            }

            // Only use this function if T isn't a std::pair because in that case the entire vector is
            // probably a sparse sample.
            template <typename kernel_type, typename T, typename alloc>
            inline typename disable_if<is_pair<T>,const T&>::type access ( const std_vector_c<T,alloc>& m, long i)
            {
                return m[i];
            }

            template <typename kernel_type>
            inline const typename kernel_type::sample_type& access (
                const typename kernel_type::sample_type& samp,
                long
            )
            {
                return samp;
            }

            // --------------------------------------------

            template <typename kernel_type, typename T>
            inline typename disable_if<is_same_type<T,typename kernel_type::sample_type>,unsigned long>::type
            size ( const T& m)
            {
                return m.size();
            }

            template <typename kernel_type>
            inline size_t size (
                const typename kernel_type::sample_type&
            )
            {
                return 1;
            }

            // --------------------------------------------

            template <typename T>
            typename disable_if<is_matrix<T> >::type assert_is_vector(const T&)
            {}

            template <typename T>
            // This funny #ifdef thing is here because gcc sometimes gives a warning
            // about v being unused otherwise.
    #ifdef ENABLE_ASSERTS
            void assert_is_vector(const matrix_exp<T>& v)
    #else
            void assert_is_vector(const matrix_exp<T>& )
    #endif
            {
                // make sure requires clause is not broken
                DLIB_ASSERT(is_vector(v) == true,
                    "\tconst matrix_exp kernel_matrix()"
                    << "\n\t You have to supply this function with row or column vectors"
                    << "\n\t v.nr(): " << v.nr()
                    << "\n\t v.nc(): " << v.nc()
                    );
            }

        }

        template <typename K, typename vect_type1, typename vect_type2>
        struct op_kern_mat
        {
            op_kern_mat(
                const K& kern_,
                const vect_type1& vect1_,
                const vect_type2& vect2_
            ) :
                kern(kern_),
                vect1(vect1_),
                vect2(vect2_)
            {
                // make sure the requires clauses get checked eventually
                impl::assert_is_vector(vect1);
                impl::assert_is_vector(vect2);
            }

            const K& kern;
            const vect_type1& vect1;
            const vect_type2& vect2;

            typedef typename K::scalar_type type;

            const static long cost = 100;
            const static long NR = (is_same_type<vect_type1,typename K::sample_type>::value) ? 1 : 0;
            const static long NC = (is_same_type<vect_type2,typename K::sample_type>::value) ? 1 : 0;

            typedef const type const_ret_type;
            typedef typename K::mem_manager_type mem_manager_type;
            typedef row_major_layout layout_type;

            const_ret_type apply (long r, long c ) const
            {
                return kern(impl::access<K>(vect1,r), impl::access<K>(vect2,c));
            }

            long nr () const { return impl::size<K>(vect1); }
            long nc () const { return impl::size<K>(vect2); }

            template <typename U> bool aliases               ( const matrix_exp<U>& item ) const { return alias_helper(item.ref()); }
            template <typename U> bool destructively_aliases ( const matrix_exp<U>& item ) const { return alias_helper(item.ref()); }

            template <typename U> bool alias_helper  ( const U& ) const { return false; }

            typedef typename K::sample_type samp_type;

            // Say we destructively alias if one of the vect* objects is actually item.
            bool alias_helper                   (const samp_type& item ) const { return are_same(item, vect1) || are_same(item, vect2); }
            template <typename U> bool are_same (const samp_type& , const U& )         const { return false; }
            bool are_same                       (const samp_type& a, const samp_type& b) const { return (&a == &b); }
        };

    // ----------------------------------------------------------------------------------------

        template <
            typename K,
            typename V1,
            typename V2
            >
        const matrix_op<op_kern_mat<K,V1,V2> > kernel_matrix (
            const K& kern,
            const V1& v1,
            const V2& v2
            )
        {
            typedef op_kern_mat<K,V1,V2> op;
            return matrix_op<op>(op(kern,v1,v2));
        }

    // ----------------------------------------------------------------------------------------

        /*
            It is possible to implement the kernel_matrix() operator with just one operator
            class but treating the version that takes only a single vector separately
            leads to more efficient output by gcc in certain instances.
        */
        template <typename K, typename vect_type1>
        struct op_kern_mat_single
        {
            op_kern_mat_single(
                const K& kern_,
                const vect_type1& vect1_
            ) :
                kern(kern_),
                vect1(vect1_)
            {
                // make sure the requires clauses get checked eventually
                impl::assert_is_vector(vect1);
            }

            const K& kern;
            const vect_type1& vect1;

            typedef typename K::scalar_type type;

            const static long cost = 100;
            const static long NR = (is_same_type<vect_type1,typename K::sample_type>::value) ? 1 : 0;
            const static long NC = (is_same_type<vect_type1,typename K::sample_type>::value) ? 1 : 0;

            typedef const type const_ret_type;
            typedef typename K::mem_manager_type mem_manager_type;
            typedef row_major_layout layout_type;

            const_ret_type apply (long r, long c ) const
            {
                return kern(impl::access<K>(vect1,r), impl::access<K>(vect1,c));
            }

            long nr () const { return impl::size<K>(vect1); }
            long nc () const { return impl::size<K>(vect1); }

            template <typename U> bool aliases               ( const matrix_exp<U>& item ) const { return alias_helper(item.ref()); }
            template <typename U> bool destructively_aliases ( const matrix_exp<U>& item ) const { return alias_helper(item.ref()); }

            template <typename U> bool alias_helper  ( const U& ) const { return false; }

            typedef typename K::sample_type samp_type;

            // Say we destructively alias if vect1 is actually item.
            bool alias_helper                   (const samp_type& item ) const { return are_same(item, vect1); }
            template <typename U> bool are_same (const samp_type& , const U& )         const { return false; }
            bool are_same                       (const samp_type& a, const samp_type& b) const { return (&a == &b); }
        };

        template <
            typename K,
            typename V
            >
        const matrix_op<op_kern_mat_single<K,V> > kernel_matrix (
            const K& kern,
            const V& v
            )
        {
            typedef op_kern_mat_single<K,V> op;
            return matrix_op<op>(op(kern,v));
        }

    // ----------------------------------------------------------------------------------------

        template <
            typename matrix_dest_type,
            typename K,
            typename V
            >
        inline void matrix_assign (
            matrix_dest_type& dest,
            const matrix_exp<matrix_op<op_kern_mat_single<K,V> > >& src
        )
        /*!
            Overload matrix assignment so that when a kernel_matrix expression
            gets assigned it only evaluates half the kernel matrix (since it is symmetric)
        !*/
        {
            for (long r = 0; r < src.nr(); ++r)
            {
                for (long c = r; c < src.nc(); ++c)
                {
                    dest(r,c) = dest(c,r) = src(r,c);
                }
            }
        }

    // ----------------------------------------------------------------------------------------

    }

    #endif // DLIB_SVm_KERNEL_MATRIX_