Prev Next sacado_det_lu.cpp

Sacado Speed: Gradient of Determinant Using Lu Factorization

Operation Sequence
Note that the Lu factorization operation sequence depends on the matrix being factored.

compute_det_lu
Routine that computes the gradient of determinant using Sacado:
# include <Sacado.hpp>
# include <cppad/speed/det_by_lu.hpp>
# include <cppad/speed/uniform_01.hpp>
# include <cppad/vector.hpp>

void compute_det_lu(
     size_t                     size     , 
     size_t                     repeat   , 
     CppAD::vector<double>     &matrix   ,
     CppAD::vector<double>     &gradient )
{
     // -----------------------------------------------------
     // setup

     // object for computing determinant
     typedef Sacado::Rad::ADvar<double> ADScalar; 
     typedef CppAD::vector<ADScalar>      ADVector; 
     CppAD::det_by_lu<ADScalar>         Det(size);

     size_t i;                // temporary index
     size_t n = size * size;  // number of independent variables
     ADScalar   detA;         // AD value of the determinant
     ADVector   A(n);         // AD version of matrix 
     
     // ------------------------------------------------------
     while(repeat--)
     {    // get the next matrix
          CppAD::uniform_01(n, matrix);

          // set independent variable values
          for(i = 0; i < n; i++)
               A[i] = matrix[i];

          // compute the determinant
          detA = Det(A);

          // compute the gradient of detA
          ADScalar::Gradcomp();

          // evaluate and return gradient using reverse mode
          for(i =0; i < n; i++)
               gradient[i] = A[i].adj(); // partial detA w.r.t A[i]
     }
     // ---------------------------------------------------------
     return;
}

Input File: speed/sacado/det_lu.cpp