dlib C++ Library - matrix_cholesky.h

    // Copyright (C) 2009  Davis E. King (davis@dlib.net)
    // License: Boost Software License   See LICENSE.txt for the full license.
    // This code was adapted from code from the JAMA part of NIST's TNT library.
    //    See: http://math.nist.gov/tnt/
    #ifndef DLIB_MATRIX_CHOLESKY_DECOMPOSITION_H
    #define DLIB_MATRIX_CHOLESKY_DECOMPOSITION_H

    #include "matrix.h"
    #include "matrix_utilities.h"
    #include "matrix_subexp.h"
    #include <cmath>

    #ifdef DLIB_USE_LAPACK
    #include "lapack/potrf.h"
    #endif

    #include "matrix_trsm.h"

    namespace dlib
    {

        template <
            typename matrix_exp_type
            >
        class cholesky_decomposition
        {

        public:

            const static long NR = matrix_exp_type::NR;
            const static long NC = matrix_exp_type::NC;
            typedef typename matrix_exp_type::type type;
            typedef typename matrix_exp_type::mem_manager_type mem_manager_type;
            typedef typename matrix_exp_type::layout_type layout_type;

            typedef matrix<type,0,0,mem_manager_type,layout_type>  matrix_type;
            typedef matrix<type,NR,1,mem_manager_type,layout_type> column_vector_type;

            // You have supplied an invalid type of matrix_exp_type.  You have
            // to use this object with matrices that contain float or double type data.
            COMPILE_TIME_ASSERT((is_same_type<float, type>::value ||
                                 is_same_type<double, type>::value ));

            template <typename EXP>
            cholesky_decomposition(
                const matrix_exp<EXP>& A
            );

            bool is_spd(
            ) const;

            const matrix_type& get_l(
            ) const;

            template <typename EXP>
            const typename EXP::matrix_type solve (
                const matrix_exp<EXP>& B
            ) const;

        private:

            matrix_type L_;     // lower triangular factor
            bool isspd;         // true if matrix to be factored was SPD
        };

    // ----------------------------------------------------------------------------------------
    // ----------------------------------------------------------------------------------------
    //                                      Member functions
    // ----------------------------------------------------------------------------------------
    // ----------------------------------------------------------------------------------------

        template <typename matrix_exp_type>
        bool cholesky_decomposition<matrix_exp_type>::
        is_spd(
        ) const
        {
            return isspd;
        }

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

        template <typename matrix_exp_type>
        const typename cholesky_decomposition<matrix_exp_type>::matrix_type& cholesky_decomposition<matrix_exp_type>::
        get_l(
        ) const
        {
            return L_;
        }

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

        template <typename matrix_exp_type>
        template <typename EXP>
        cholesky_decomposition<matrix_exp_type>::
        cholesky_decomposition(
            const matrix_exp<EXP>& A_
        )
        {
            using std::sqrt;
            COMPILE_TIME_ASSERT((is_same_type<type, typename EXP::type>::value));

            // make sure requires clause is not broken
            DLIB_ASSERT(A_.nr() == A_.nc() && A_.size() > 0,
                "\tcholesky_decomposition::cholesky_decomposition(A_)"
                << "\n\tYou can only use this on square matrices"
                << "\n\tA_.nr():   " << A_.nr()
                << "\n\tA_.nc():   " << A_.nc()
                << "\n\tA_.size(): " << A_.size()
                << "\n\tthis:      " << this
                );

    #ifdef DLIB_USE_LAPACK
            L_ = A_;
            const type eps = max(abs(diag(L_)))*std::sqrt(std::numeric_limits<type>::epsilon())/100;

            // check if the matrix is actually symmetric
            bool is_symmetric = true;
            for (long r = 0; r < L_.nr() && is_symmetric; ++r)
            {
                for (long c = r+1; c < L_.nc() && is_symmetric; ++c)
                {
                    // this is approximately doing: is_symmetric = is_symmetric && ( L_(k,j) == L_(j,k))
                    is_symmetric = is_symmetric && (std::abs(L_(r,c) - L_(c,r)) < eps );
                }
            }

            // now compute the actual cholesky decomposition
            int info = lapack::potrf('L', L_);

            // check if it's really SPD
            if (info == 0 && is_symmetric && min(abs(diag(L_))) > eps*100)
                isspd = true;
            else
                isspd = false;

            L_ = lowerm(L_);
    #else
            const_temp_matrix<EXP> A(A_);

            isspd = true;

            const long n = A.nc();
            L_.set_size(n,n);

            // do nothing if the matrix is empty
            if (A.size() == 0)
                return;

            const type eps = std::numeric_limits<type>::epsilon();

            const type eps2 = max(abs(diag(A)))*std::sqrt(std::numeric_limits<type>::epsilon())/100;

            // compute the upper left corner
            if (A(0,0) > 0)
            {
                L_(0,0) = std::sqrt(A(0,0));
                if (A(0,0) <= eps2)
                    isspd = false;
            }
            else
            {
                isspd = false;
                L_(0,0) = 0;
            }

            // compute the first column
            for (long r = 1; r < A.nr(); ++r)
            {
                // if (L_(0,0) > 0)
                if (L_(0,0) > eps*std::abs(A(r,0)))
                {
                    L_(r,0) = A(r,0)/L_(0,0);
                }
                else
                {
                    isspd = false;
                    L_(r,0) = 0;
                }

                isspd = isspd && (std::abs(A(r,0) - A(0,r)) <= eps*std::abs(A(r,0)) );
            }

            // now compute all the other columns
            for (long c = 1; c < A.nc(); ++c)
            {
                // compute the diagonal element
                type temp = A(c,c);
                for (long i = 0; i < c; ++i)
                    temp -= L_(c,i)*L_(c,i);

                if (temp > 0)
                {
                    L_(c,c) = std::sqrt(temp);
                    if (temp <= eps2)
                        isspd = false;
                }
                else
                {
                    L_(c,c) = 0;
                    isspd = false;
                }

                for (long r = 0; r < c; ++r)
                    L_(r,c) = 0;

                // compute the non diagonal elements
                for (long r = c+1; r < A.nr(); ++r)
                {
                    temp = A(r,c);
                    for (long i = 0; i < c; ++i)
                    {
                        temp -= L_(r,i)*L_(c,i);
                    }

                    // if (L_(c,c) > 0)
                    if (L_(c,c) > eps*std::abs(temp))
                    {
                        L_(r,c) = temp/L_(c,c);
                    }
                    else
                    {
                        isspd = false;
                        L_(r,c) = 0;
                    }

                    isspd = isspd && (std::abs(A(r,c) - A(c,r)) <= eps*std::abs(A(r,c)) );
                }
            }

    #endif
        }

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

        template <typename matrix_exp_type>
        template <typename EXP>
        const typename EXP::matrix_type cholesky_decomposition<matrix_exp_type>::
        solve(
            const matrix_exp<EXP>& B
        ) const
        {
            COMPILE_TIME_ASSERT((is_same_type<type, typename EXP::type>::value));

            // make sure requires clause is not broken
            DLIB_ASSERT(L_.nr() == B.nr(),
                "\tconst matrix cholesky_decomposition::solve(B)"
                << "\n\tInvalid arguments were given to this function."
                << "\n\tL_.nr():  " << L_.nr()
                << "\n\tB.nr():   " << B.nr()
                << "\n\tthis:     " << this
                );

            matrix<type, NR, EXP::NC, mem_manager_type, layout_type>  X(B);

            using namespace blas_bindings;
            // Solve L*y = b;
            triangular_solver(CblasLeft, CblasLower, CblasNoTrans, CblasNonUnit, L_, X);
            // Solve L'*X = Y;
            triangular_solver(CblasLeft, CblasLower, CblasTrans, CblasNonUnit, L_, X);
            return X;
        }

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

    }

    #endif // DLIB_MATRIX_CHOLESKY_DECOMPOSITION_H