# include <cppad/cppad.hpp>
# include <limits>

bool fun_assign(void)
{     bool ok = true;
     using CppAD::AD;
     using CppAD::NearEqual;
     size_t i, j;

     // ten times machine percision
     double eps = 10. * CppAD::numeric_limits<double>::epsilon();

     // two ADFun<double> objects
     CppAD::ADFun<double> g;

     // domain space vector
     size_t n  = 3;
     CPPAD_TESTVECTOR(AD<double>) x(n);
     for(j = 0; j < n; j++)
          x[j] = AD<double>(j + 2);

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

     // range space vector
     size_t m = 2;
     CPPAD_TESTVECTOR(AD<double>) y(m);
     y[0] = x[0] + x[0] * x[1];
     y[1] = x[1] * x[2] + x[2];

     // Store operation sequence, and order zero forward results, in f.
     CppAD::ADFun<double> f(x, y);

     // sparsity pattern for the identity matrix
     CPPAD_TESTVECTOR(std::set<size_t>) r(n);
     for(j = 0; j < n; j++)
          r[j].insert(j);

     // Store forward mode sparsity pattern in f
     f.ForSparseJac(n, r);

     // make a copy in g
     g = f;

     // check values that should be equal
     ok &= ( g.size_order() == f.size_order() );
     ok &= ( (g.size_forward_bool() > 0) == (f.size_forward_bool() > 0) );
     ok &= ( (g.size_forward_set() > 0)  == (f.size_forward_set() > 0) );

     // Use zero order Taylor coefficient from f for first order
     // calculation using g.
     CPPAD_TESTVECTOR(double) dx(n), dy(m);
     for(i = 0; i < n; i++)
          dx[i] = 0.;
     dx[1] = 1;
     dy    = g.Forward(1, dx);
     ok &= NearEqual(dy[0], x[0], eps, eps); // partial y[0] w.r.t x[1]
     ok &= NearEqual(dy[1], x[2], eps, eps); // partial y[1] w.r.t x[1]

     // Use forward Jacobian sparsity pattern from f to calculate
     // Hessian sparsity pattern using g.
     CPPAD_TESTVECTOR(std::set<size_t>) s(1), h(n);
     s[0].insert(0); // Compute sparsity pattern for Hessian of y[0]
     h =  f.RevSparseHes(n, s);

     // check sparsity pattern for Hessian of y[0] = x[0] + x[0] * x[1]
     ok  &= ( h[0].find(0) == h[0].end() ); // zero     w.r.t x[0], x[0]
     ok  &= ( h[0].find(1) != h[0].end() ); // non-zero w.r.t x[0], x[1]
     ok  &= ( h[0].find(2) == h[0].end() ); // zero     w.r.t x[0], x[2]

     ok  &= ( h[1].find(0) != h[1].end() ); // non-zero w.r.t x[1], x[0]
     ok  &= ( h[1].find(1) == h[1].end() ); // zero     w.r.t x[1], x[1]
     ok  &= ( h[1].find(2) == h[1].end() ); // zero     w.r.t x[1], x[2]

     ok  &= ( h[2].find(0) == h[2].end() ); // zero     w.r.t x[2], x[0]
     ok  &= ( h[2].find(1) == h[2].end() ); // zero     w.r.t x[2], x[1]
     ok  &= ( h[2].find(2) == h[2].end() ); // zero     w.r.t x[2], x[2]

     return ok;
}