Map dgCmatrix as integer sparse matrix

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難度
5/5
預估耗時
一週以上
新手友好度
25/100
Issue 類型
功能
描述清晰度
需要釐清
活躍度
停滯
技術堆疊
r
領域
data

研究方向

Start with the RcppEigen sparse-matrix mapping entry points used by Eigen::Map and the dgCmatrix/ngCmatrix types described in the issue. Determine whether integer mapping avoids deep copies and define what support for ngCmatrix would require; done should include verified behavior and coverage for the requested mapping.

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描述

Dear developers,

I have a dgCmatrix in R and want to call a function as below in cpp to deal with it.

Eigen::SparseMatrix calc_overlap(Eigen::Map<Eigen::SparseMatrix<int>>& cc_adj,
Eigen::Map<Eigen::SparseMatrix<int>>& cg_adj,
double threshold) {
Eigen::SparseMatrix<int> overlap_mat_all = cc_adj * cg_adj;
return overlap_mat_all;
}

The dgCmatrix 'cc_adj' and 'cg_adj' in R are large sparse matrices with integer values. I want to calculate the product of them by cpp. I used 'Map' to get rid of deep copies of these two large matrices. The scalar <int> is used to save memory. There is no error raised up when mapping to a dgCmatrix with <int>. but I'm not sure how it's working exactly. I guess the function makes deep copies instead, so the mapping doesn't work at all. Is it right?

My concern is that since you only allow mapping to dgCmatrix format sparse matrix for now, is there any possibility that you could wrap up a function to deal with 'ngCmatrix'?

Looking forward to your kind reply.

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C++
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