1 #ifndef STAN_MATH_PRIM_FUN_CSR_EXTRACT_W_HPP
2 #define STAN_MATH_PRIM_FUN_CSR_EXTRACT_W_HPP
3
4 #include <stan/math/prim/fun/Eigen.hpp>
5 #include <stan/math/prim/fun/to_ref.hpp>
6
7 namespace stan {
8 namespace math {
9
10 /** \addtogroup csr_format
11 * @{
12 */
13
14 /* Extract the non-zero values from a sparse matrix.
15 *
16 * @tparam T type of elements in the matrix
17 * @param[in] A sparse matrix.
18 * @return Vector of non-zero entries of A.
19 */
20 template <typename T>
csr_extract_w(const Eigen::SparseMatrix<T,Eigen::RowMajor> & A)21 const Eigen::Matrix<T, Eigen::Dynamic, 1> csr_extract_w(
22 const Eigen::SparseMatrix<T, Eigen::RowMajor>& A) {
23 Eigen::Matrix<T, Eigen::Dynamic, 1> w(A.nonZeros());
24 w.setZero();
25 for (int nze = 0; nze < A.nonZeros(); ++nze) {
26 w[nze] = *(A.valuePtr() + nze);
27 }
28 return w;
29 }
30
31 /* Extract the non-zero values from a dense matrix by converting
32 * to sparse and calling the sparse matrix extractor.
33 *
34 * @tparam T type of elements in the matrix
35 * @tparam R number of rows, can be Eigen::Dynamic
36 * @tparam C number of columns, can be Eigen::Dynamic
37 *
38 * @param[in] A dense matrix.
39 * @return Vector of non-zero entries of A.
40 */
41 template <typename T, require_eigen_dense_base_t<T>* = nullptr>
csr_extract_w(const T & A)42 const Eigen::Matrix<scalar_type_t<T>, Eigen::Dynamic, 1> csr_extract_w(
43 const T& A) {
44 // conversion to sparse seems to touch data twice, so we need to call to_ref
45 Eigen::SparseMatrix<scalar_type_t<T>, Eigen::RowMajor> B
46 = to_ref(A).sparseView();
47 return csr_extract_w(B);
48 }
49
50 /** @} */ // end of csr_format group
51
52 } // namespace math
53 } // namespace stan
54
55 #endif
56