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@(@\newcommand{\W}[1]{ \; #1 \; } \newcommand{\R}[1]{ {\rm #1} } \newcommand{\B}[1]{ {\bf #1} } \newcommand{\D}[2]{ \frac{\partial #1}{\partial #2} } \newcommand{\DD}[3]{ \frac{\partial^2 #1}{\partial #2 \partial #3} } \newcommand{\Dpow}[2]{ \frac{\partial^{#1}}{\partial {#2}^{#1}} } \newcommand{\dpow}[2]{ \frac{ {\rm d}^{#1}}{{\rm d}\, {#2}^{#1}} }@)@
Forward Mode Hessian Sparsity: Example and Test
# include <cppad/cppad.hpp>

bool for_hes_sparsity(void)
{     bool ok = true;
     using CppAD::AD;
     typedef CPPAD_TESTVECTOR(size_t)     SizeVector;
     typedef CppAD::sparse_rc<SizeVector> sparsity;
     //
     // domain space vector
     size_t n = 3;
     CPPAD_TESTVECTOR(AD<double>) ax(n);
     ax[0] = 0.;
     ax[1] = 1.;
     ax[2] = 2.;

     // declare independent variables and start recording
     CppAD::Independent(ax);

     // range space vector
     size_t m = 2;
     CPPAD_TESTVECTOR(AD<double>) ay(m);
     ay[0] = sin( ax[2] );
     ay[1] = ax[0] * ax[1];

     // create f: x -> y and stop tape recording
     CppAD::ADFun<double> f(ax, ay);

     // include all x components in sparsity pattern
     CPPAD_TESTVECTOR(bool) select_domain(n);
     for(size_t j = 0; j < n; j++)
          select_domain[j] = true;

     // compute sparsity pattern for H(x) = F_1''(x)
     CPPAD_TESTVECTOR(bool) select_range(m);
     select_range[0]    = false;
     select_range[1]    = true;
     bool internal_bool = true;
     sparsity pattern_out;
     f.for_hes_sparsity(
          select_domain, select_range, internal_bool, pattern_out
     );
     size_t nnz = pattern_out.nnz();
     ok        &= nnz == 2;
     ok        &= pattern_out.nr() == n;
     ok        &= pattern_out.nc() == n;
     {     // check results
          const SizeVector& row( pattern_out.row() );
          const SizeVector& col( pattern_out.col() );
          SizeVector row_major = pattern_out.row_major();
          //
          ok &= row[ row_major[0] ] ==  0  && col[ row_major[0] ] ==  1;
          ok &= row[ row_major[1] ] ==  1  && col[ row_major[1] ] ==  0;
     }
     //
     // compute sparsity pattern for H(x) = F_0''(x)
     select_range[0] = true;
     select_range[1] = false;
     f.for_hes_sparsity(
          select_domain, select_range, internal_bool, pattern_out
     );
     nnz = pattern_out.nnz();
     ok &= nnz == 1;
     ok &= pattern_out.nr() == n;
     ok &= pattern_out.nc() == n;
     {     // check results
          const SizeVector& row( pattern_out.row() );
          const SizeVector& col( pattern_out.col() );
          //
          ok &= row[0] ==  2  && col[0] ==  2;
     }
     return ok;
}

Input File: example/sparse/for_hes_sparsity.cpp