Function BoolCases

example/sparse/for_sparse_jac.cpp:27–96

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>) X(n);
   X[0] = 0.;
   X[1] = 1.;

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

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

   // create f: X -> Y and stop tape recording
   CppAD::ADFun<double> f(X, Y);

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

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

   // check that values are stored
   ok &= (f.size_forward_bool() > 0);
   ok &= (f.size_forward_set() == 0);

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