! Create a two vector sparsity representation from a vector of maps. \param sparse Is a vector of maps representation of sparsity as well as the index in the two vector representation. To be specific; \verbatim for(i = 0; i < sparse.size(); i++) { for(itr = sparse[i].begin(); itr != sparse[i].end(); itr++) { j = itr->first; // (i, j) is a possibly non-zero entry in sparsity pattern
| 48 | k-th possibly non-zero entry. |
| 49 | */ |
| 50 | void sparse_map2vec( |
| 51 | const CppAD::vector< std::map<size_t, size_t> > sparse, |
| 52 | size_t& n_nz , |
| 53 | CppAD::vector<size_t>& i_row , |
| 54 | CppAD::vector<size_t>& j_col ) |
| 55 | { |
| 56 | size_t i, j, k, m; |
| 57 | |
| 58 | // number of rows in sparse |
| 59 | m = sparse.size(); |
| 60 | |
| 61 | // itererator for one row |
| 62 | std::map<size_t, size_t>::const_iterator itr; |
| 63 | |
| 64 | // count the number of possibly non-zeros in sparse |
| 65 | n_nz = 0; |
| 66 | for(i = 0; i < m; i++) |
| 67 | for(itr = sparse[i].begin(); itr != sparse[i].end(); itr++) |
| 68 | ++n_nz; |
| 69 | |
| 70 | // resize the return vectors to accommodate n_nz entries |
| 71 | i_row.resize(n_nz); |
| 72 | j_col.resize(n_nz); |
| 73 | |
| 74 | // set the row and column indices and check assumptions on sparse |
| 75 | k = 0; |
| 76 | for(i = 0; i < m; i++) |
| 77 | { for(itr = sparse[i].begin(); itr != sparse[i].end(); itr++) |
| 78 | { j = itr->first; |
| 79 | CPPAD_ASSERT_UNKNOWN( k == itr->second ); |
| 80 | i_row[k] = i; |
| 81 | j_col[k] = j; |
| 82 | ++k; |
| 83 | } |
| 84 | } |
| 85 | return; |
| 86 | } |
| 87 | |
| 88 | // --------------------------------------------------------------------------- |
| 89 | } // end namespace cppad_ipopt |
no test coverage detected