CppAD: A C++ Algorithmic Differentiation Package  20171217
template<class VectorSet >
 void CppAD::local::color_symmetric_cppad ( const VectorSet & pattern, CppAD::vector< size_t > & row, CppAD::vector< size_t > & col, CppAD::vector< size_t > & color )

CppAD algorithm for determining which rows of a symmetric sparse matrix can be computed together.

Template Parameters
 VectorSize is a simple vector class with elements of type size_t. VectorSet is a vector_of_sets class.
Parameters
 pattern [in] Is a representation of the sparsity pattern for the matrix. row [in/out] is a vector specifying which row indices to compute. col [in/out] is a vector, with the same size as row, that specifies which column indices to compute. Input: For each valid index `k`, the index pair `(row[k], col[k])` must be present in the sparsity pattern. It may be that some entries in the sparsity pattern do not need to be computed; i.e, do not appear in the set of `(row[k], col[k])` entries. Output: On output, some of row and column indices may have been swapped std::swap( row[k], col[k] ) So the the the color for row[k] can be used to compute entry (row[k], col[k]). color [out] is a vector with size m. The input value of its elements does not matter. Upon return, it is a coloring for the rows of the sparse matrix. Note that if color[i] == m, then there is no index k for which row[k] == i (for the return value of row). Fix any (i, j) in the sparsity pattern. Suppose that there is a row index i1 with i1 != i, color[i1] == color[i] and (i1, j) is in the sparsity pattern. If follows that for all j1 with j1 != j and color[j1] == color[j], (j1, i ) is not in the sparsity pattern. This routine tries to minimize, with respect to the choice of colors, the maximum, with respect to k, of `color[ row[k] ]`.

Definition at line 81 of file color_symmetric.hpp.