/* --------------------------------------------------------------------------
CppAD: C++ Algorithmic Differentiation: Copyright (C) 2003-17 Bradley M. Bell

CppAD is distributed under the terms of the
             Eclipse Public License Version 2.0.

This Source Code may also be made available under the following
Secondary License when the conditions for such availability set forth
in the Eclipse Public License, Version 2.0 are satisfied:
      GNU General Public License, Version 2.0 or later.
---------------------------------------------------------------------------- */

/*
$begin lu_invert.cpp$$
$spell
    Geq
    Cpp
    Lu
$$

$section LuInvert: Example and Test$$


$srcfile%example/utility/lu_invert.cpp%0%// BEGIN C++%// END C++%1%$$

$end
*/


// BEGIN C++
# include <cstdlib>               // for rand function
# include <cppad/utility/lu_invert.hpp>      // for CppAD::LuInvert
# include <cppad/utility/near_equal.hpp>     // for CppAD::NearEqual
# include <cppad/utility/vector.hpp>  // for CppAD::vector

bool LuInvert(void)
{   bool  ok = true;

# ifndef _MSC_VER
    using std::rand;
    using std::srand;
# endif
    double eps200 = 200.0 * std::numeric_limits<double>::epsilon();

    size_t  n = 7;                        // number rows in A
    size_t  m = 3;                        // number columns in B
    double  rand_max = double(RAND_MAX);  // maximum rand value
    double  sum;                          // element of L * U
    size_t  i, j, k;                      // temporary indices

    // dimension matrices
    CppAD::vector<double>
        A(n*n), X(n*m), B(n*m), LU(n*n), L(n*n), U(n*n);

    // seed the random number generator
    srand(123);

    // pivot vectors
    CppAD::vector<size_t> ip(n);
    CppAD::vector<size_t> jp(n);

    // set pivot vectors
    for(i = 0; i < n; i++)
    {   ip[i] = (i + 2) % n;      // ip = 2 , 3, ... , n-1, 0, 1
        jp[i] = (n + 2 - i) % n;  // jp = 2 , 1, n-1, n-2, ... , 3
    }

    // chose L, a random lower triangular matrix
    for(i = 0; i < n; i++)
    {   for(j = 0; j <= i; j++)
            L [i * n + j]  = rand() / rand_max;
        for(j = i+1; j < n; j++)
            L [i * n + j]  = 0.;
    }
    // chose U, a random upper triangular matrix with ones on diagonal
    for(i = 0; i < n; i++)
    {   for(j = 0; j < i; j++)
            U [i * n + j]  = 0.;
        U[ i * n + i ] = 1.;
        for(j = i+1; j < n; j++)
            U [i * n + j]  = rand() / rand_max;
    }
    // chose X, a random matrix
    for(i = 0; i < n; i++)
    {   for(k = 0; k < m; k++)
            X[i * m + k] = rand() / rand_max;
    }
    // set LU to a permuted combination of both L and U
    for(i = 0; i < n; i++)
    {   for(j = 0; j <= i; j++)
            LU [ ip[i] * n + jp[j] ]  = L[i * n + j];
        for(j = i+1; j < n; j++)
            LU [ ip[i] * n + jp[j] ]  = U[i * n + j];
    }
    // set A to a permuted version of L * U
    for(i = 0; i < n; i++)
    {   for(j = 0; j < n; j++)
        {   // compute (i,j) entry in permuted matrix
            sum = 0.;
            for(k = 0; k < n; k++)
                sum += L[i * n + k] * U[k * n + j];
            A[ ip[i] * n + jp[j] ] = sum;
        }
    }
    // set B to A * X
    for(i = 0; i < n; i++)
    {   for(k = 0; k < m; k++)
        {   // compute (i,k) entry of B
            sum = 0.;
            for(j = 0; j < n; j++)
                sum += A[i * n + j] * X[j * m + k];
            B[i * m + k] = sum;
        }
    }
    // solve for X
    CppAD::LuInvert(ip, jp, LU, B);

    // check result
    for(i = 0; i < n; i++)
    {   for(k = 0; k < m; k++)
        {   ok &= CppAD::NearEqual(
                X[i * m + k], B[i * m + k], eps200, eps200
            );
        }
    }
    return ok;
}

// END C++
