Function BoolCases

example/sparse/rev_sparse_jac.cpp:25–82

vector class, elements of type bool

// define the template function BoolCases<Vector>
template <class Vector>  // vector class, elements of type bool
bool BoolCases(void)
{  bool ok = true;
   using CppAD::AD;

   // domain space vector
   size_t n = 2;
   CPPAD_TESTVECTOR(AD<double>) ax(n);
   ax[0] = 0.;
   ax[1] = 1.;

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

   // range space vector
   size_t m = 3;
   CPPAD_TESTVECTOR(AD<double>) ay(m);
   ay[0] = ax[0];
   ay[1] = ax[0] * ax[1];
   ay[2] = ax[1];

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

   // sparsity pattern for the identity matrix
   Vector r(m * m);
   size_t i, j;
   for(i = 0; i < m; i++)
   {  for(j = 0; j < m; j++)
         r[ i * m + j ] = (i == j);
   }

   // sparsity pattern for F'(x)
   Vector s(m * n);
   s = f.RevSparseJac(m, r);

   // check values
   ok &= (s[ 0 * n + 0 ] == true);  // y[0] does     depend on x[0]
   ok &= (s[ 0 * n + 1 ] == false); // y[0] does not depend on x[1]
   ok &= (s[ 1 * n + 0 ] == true);  // y[1] does     depend on x[0]
   ok &= (s[ 1 * n + 1 ] == true);  // y[1] does     depend on x[1]
   ok &= (s[ 2 * n + 0 ] == false); // y[2] does not depend on x[0]
   ok &= (s[ 2 * n + 1 ] == true);  // y[2] does     depend on x[1]

   // sparsity pattern for F'(x)^T, note R is the identity, so R^T = R
   bool transpose = true;
   Vector st(n * m);
   st = f.RevSparseJac(m, r, transpose);

   // check values
   ok &= (st[ 0 * m + 0 ] == true);  // y[0] does     depend on x[0]
   ok &= (st[ 1 * m + 0 ] == false); // y[0] does not depend on x[1]
   ok &= (st[ 0 * m + 1 ] == true);  // y[1] does     depend on x[0]
   ok &= (st[ 1 * m + 1 ] == true);  // y[1] does     depend on x[1]
   ok &= (st[ 0 * m + 2 ] == false); // y[2] does not depend on x[0]
   ok &= (st[ 1 * m + 2 ] == true);  // y[2] does     depend on x[1]

   return ok;
}