Using ColPack: Example and Test
Keywords: using colpack: example test colpack jacobian sparse

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Using ColPack: Example and Test
`

    # include <cppad/cppad.hpp>
    bool colpack_jac(void)
    {	bool ok = true;
    	using CppAD::AD;
    	using CppAD::NearEqual;
    	typedef CPPAD_TESTVECTOR(AD<double>) a_vector;
    	typedef CPPAD_TESTVECTOR(double)     d_vector;
    	typedef CppAD::vector<size_t>        i_vector;
    	size_t i, j, k, ell;
    	double eps = 10. * CppAD::numeric_limits<double>::epsilon();

    	// domain space vector
    	size_t n = 4;
    	a_vector  a_x(n);
    	for(j = 0; j < n; j++)
    		a_x[j] = AD<double> (0);

    	// declare independent variables and starting recording
    	CppAD::Independent(a_x);

    	size_t m = 3;
    	a_vector  a_y(m);
    	a_y[0] = a_x[0] + a_x[1];
    	a_y[1] = a_x[2] + a_x[3];
    	a_y[2] = a_x[0] + a_x[1] + a_x[2] + a_x[3] * a_x[3] / 2.;

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

    	// new value for the independent variable vector
    	d_vector x(n);
    	for(j = 0; j < n; j++)
    		x[j] = double(j);

    	/*
    	      [ 1 1 0 0  ]
    	jac = [ 0 0 1 1  ]
    	      [ 1 1 1 x_3]
    	*/
    	d_vector check(m * n);
    	check[0] = 1.; check[1] = 1.; check[2]  = 0.; check[3]  = 0.;
    	check[4] = 0.; check[5] = 0.; check[6]  = 1.; check[7]  = 1.;
    	check[8] = 1.; check[9] = 1.; check[10] = 1.; check[11] = x[3];

    	// Normally one would use f.ForSparseJac or f.RevSparseJac to compute
    	// sparsity pattern, but for this example we extract it from check.
    	std::vector< std::set<size_t> >  p(m);

    	// using row and column indices to compute non-zero in rows 1 and 2
    	i_vector row, col;
    	for(i = 0; i < m; i++)
    	{	for(j = 0; j < n; j++)
    		{	ell = i * n + j;
    			if( check[ell] != 0. )
    			{	row.push_back(i);
    				col.push_back(j);
    				p[i].insert(j);
    			}
    		}
    	}
    	size_t K = row.size();
    	d_vector jac(K);

    	// empty work structure
    	CppAD::sparse_jacobian_work work;
    	ok &= work.color_method == "cppad";

    	// choose to use ColPack
    	work.color_method = "colpack";

    	// forward mode
    	size_t n_sweep = f.SparseJacobianForward(x, p, row, col, jac, work);
    	for(k = 0; k < K; k++)
    	{	ell = row[k] * n + col[k];
    		ok &= NearEqual(check[ell], jac[k], eps, eps);
    	}
    	ok &= n_sweep == 4;

    	// reverse mode
    	work.clear();
    	work.color_method = "colpack";
    	n_sweep = f.SparseJacobianReverse(x, p, row, col, jac, work);
    	for(k = 0; k < K; k++)
    	{	ell = row[k] * n + col[k];
    		ok &= NearEqual(check[ell], jac[k], eps, eps);
    	}
    	ok &= n_sweep == 2;

    	return ok;
    }

`

Input File: example/colpack_jac.cpp