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Up-> CppAD speed speed_cppad cppad_det_lu.cpp

CppAD-> Install Introduction AD ADFun preprocessor multi_thread utility ipopt_solve Example speed Appendix

speed-> speed_main speed_utility speed_double speed_adolc speed_cppad speed_fadbad speed_sacado

speed_cppad-> cppad_det_minor.cpp cppad_det_lu.cpp cppad_mat_mul.cpp cppad_ode.cpp cppad_poly.cpp cppad_sparse_hessian.cpp cppad_sparse_jacobian.cpp

cppad_det_lu.cpp

Headings-> Specifications Implementation

# include <cppad/speed/det_by_lu.hpp>
# include <cppad/speed/uniform_01.hpp>
# include <cppad/cppad.hpp>

// Note that CppAD uses global_option["memory"] at the main program level
# include <map>
extern std::map<std::string, bool> global_option;

bool link_det_lu(
     size_t                           size     ,
     size_t                           repeat   ,
     CppAD::vector<double>           &matrix   ,
     CppAD::vector<double>           &gradient )
{
     // --------------------------------------------------------------------
     // check global options
     const char* valid[] = { "memory", "optimize"};
     size_t n_valid = sizeof(valid) / sizeof(valid[0]);
     typedef std::map<std::string, bool>::iterator iterator;
     //
     for(iterator itr=global_option.begin(); itr!=global_option.end(); ++itr)
     {     if( itr->second )
          {     bool ok = false;
               for(size_t i = 0; i < n_valid; i++)
                    ok |= itr->first == valid[i];
               if( ! ok )
                    return false;
          }
     }
     // --------------------------------------------------------------------

     // optimization options: no conditional skips or compare operators
     std::string options="no_compare_op";
     // -----------------------------------------------------
     // setup
     typedef CppAD::AD<double>           ADScalar;
     typedef CppAD::vector<ADScalar>     ADVector;
     CppAD::det_by_lu<ADScalar>          Det(size);

     size_t i;               // temporary index
     size_t m = 1;           // number of dependent variables
     size_t n = size * size; // number of independent variables
     ADVector   A(n);        // AD domain space vector
     ADVector   detA(m);     // AD range space vector
     CppAD::ADFun<double> f; // AD function object

     // vectors of reverse mode weights
     CppAD::vector<double> w(1);
     w[0] = 1.;

     // ------------------------------------------------------
     while(repeat--)
     {     // get the next matrix
          CppAD::uniform_01(n, matrix);
          for( i = 0; i < n; i++)
               A[i] = matrix[i];

          // declare independent variables
          Independent(A);

          // AD computation of the determinant
          detA[0] = Det(A);

          // create function object f : A -> detA
          f.Dependent(A, detA);
          if( global_option["optimize"] )
               f.optimize(options);

          // skip comparison operators
          f.compare_change_count(0);

          // evaluate and return gradient using reverse mode
          f.Forward(0, matrix);
          gradient = f.Reverse(1, w);
     }
     return true;
}