source: branches/3.2/sources/HeuristicLab.ExtLibs/HeuristicLab.ALGLIB/2.1.2.2591/ALGLIB-2.1.2.2591/spddet.cs @ 4539

/*************************************************************************
Copyright (c) 2005-2007, Sergey Bochkanov (ALGLIB project).

>>> SOURCE LICENSE >>>
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 (www.fsf.org); either version 2 of the 
License, or (at your option) any later version.

This program is distributed in the hope that it will be useful,
but WITHOUT ANY WARRANTY; without even the implied warranty of
MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
GNU General Public License for more details.

A copy of the GNU General Public License is available at
http://www.fsf.org/licensing/licenses

>>> END OF LICENSE >>>
*************************************************************************/

using System;

namespace alglib
{
    public class spddet
    {
        /*************************************************************************
        Determinant calculation of the matrix given by the Cholesky decomposition.

        Input parameters:
            A   -   Cholesky decomposition,
                    output of SMatrixCholesky subroutine.
            N   -   size of matrix A.

        As the determinant is equal to the product of squares of diagonal elements,
        it’s not necessary to specify which triangle - lower or upper - the matrix
        is stored in.

        Result:
            matrix determinant.

          -- ALGLIB --
             Copyright 2005-2008 by Bochkanov Sergey
        *************************************************************************/
        public static double spdmatrixcholeskydet(ref double[,] a,
            int n)
        {
            double result = 0;
            int i = 0;

            result = 1;
            for(i=0; i<=n-1; i++)
            {
                result = result*AP.Math.Sqr(a[i,i]);
            }
            return result;
        }


        /*************************************************************************
        Determinant calculation of the symmetric positive definite matrix.

        Input parameters:
            A       -   matrix. Array with elements [0..N-1, 0..N-1].
            N       -   size of matrix A.
            IsUpper -   if IsUpper = True, then the symmetric matrix A is given by
                        its upper triangle, and the lower triangle isn’t used by
                        subroutine. Similarly, if IsUpper = False, then A is given
                        by its lower triangle.

        Result:
            determinant of matrix A.
            If matrix A is not positive definite, then subroutine returns -1.

          -- ALGLIB --
             Copyright 2005-2008 by Bochkanov Sergey
        *************************************************************************/
        public static double spdmatrixdet(double[,] a,
            int n,
            bool isupper)
        {
            double result = 0;

            a = (double[,])a.Clone();

            if( !cholesky.spdmatrixcholesky(ref a, n, isupper) )
            {
                result = -1;
            }
            else
            {
                result = spdmatrixcholeskydet(ref a, n);
            }
            return result;
        }


        public static double determinantcholesky(ref double[,] a,
            int n)
        {
            double result = 0;
            int i = 0;

            result = 1;
            for(i=1; i<=n; i++)
            {
                result = result*AP.Math.Sqr(a[i,i]);
            }
            return result;
        }


        public static double determinantspd(double[,] a,
            int n,
            bool isupper)
        {
            double result = 0;

            a = (double[,])a.Clone();

            if( !cholesky.choleskydecomposition(ref a, n, isupper) )
            {
                result = -1;
            }
            else
            {
                result = determinantcholesky(ref a, n);
            }
            return result;
        }
    }
}